diff --git a/doc/paddle/tutorial/cv_case/convnet_image_classification/convnet_image_classification.ipynb b/doc/paddle/tutorial/cv_case/convnet_image_classification/convnet_image_classification.ipynb
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@@ -0,0 +1,364 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 使用卷积神经网络进行图像分类\n",
+    "\n",
+    "本示例教程将会演示如何使用飞桨的卷积神经网络来完成图像分类任务。这是一个较为简单的示例，将会使用一个由三个卷积层组成的网络完成[cifar10](https://www.cs.toronto.edu/~kriz/cifar.html)数据集的图像分类任务。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 设置环境\n",
+    "\n",
+    "我们将使用飞桨2.0beta版本。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.0.0\n",
+      "264e76cae6861ad9b1d4bcd8c3212f7a78c01e4d\n"
+     ]
+    }
+   ],
+   "source": [
+    "import paddle\n",
+    "import paddle.nn.functional as F\n",
+    "from paddle.vision.transforms import Normalize\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "paddle.disable_static()\n",
+    "print(paddle.__version__)\n",
+    "print(paddle.__git_commit__)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 加载并浏览数据集\n",
+    "\n",
+    "我们将会使用飞桨提供的API完成数据集的下载并为后续的训练任务准备好数据迭代器。cifar10数据集由60000张大小为32 * 32的彩色图片组成，其中有50000张图片组成了训练集，另外10000张图片组成了测试集。这些图片分为10个类别，我们的任务是训练一个模型能够把图片进行正确的分类。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cifar10_train = paddle.vision.datasets.cifar.Cifar10(mode='train', transform=None)\n",
+    "\n",
+    "train_images = np.zeros((50000, 32, 32, 3), dtype='float32')\n",
+    "train_labels = np.zeros((50000, 1), dtype='int32')\n",
+    "for i, data in enumerate(cifar10_train):\n",
+    "    train_image, train_label = data\n",
+    "    train_image = train_image.reshape((3, 32, 32 )).astype('float32') / 255.\n",
+    "    train_image = train_image.transpose(1, 2, 0)\n",
+    "    train_images[i, :, :, :] = train_image\n",
+    "    train_labels[i, 0] = train_label"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 浏览数据集\n",
+    "\n",
+    "接下来我们从数据集中随机挑选一些图片并显示，从而对数据集有一个直观的了解。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 25 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "class_names = ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
+    "\n",
+    "plt.figure(figsize=(10,10))\n",
+    "sample_idxs = np.random.choice(50000, size=25, replace=False)\n",
+    "\n",
+    "for i in range(25):\n",
+    "    plt.subplot(5, 5, i+1)\n",
+    "    plt.xticks([])\n",
+    "    plt.yticks([])\n",
+    "    plt.imshow(train_images[sample_idxs[i]], cmap=plt.cm.binary)\n",
+    "    plt.xlabel(class_names[train_labels[sample_idxs[i]][0]])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 组建网络\n",
+    "\n",
+    "接下来我们使用飞桨定义一个使用了三个二维卷积（`Conv2d`)且每次卷积之后使用`relu`激活函数，两个二维池化层（`MaxPool2d`），和两个线性变换层组成的分类网络，来把一个`(32, 32, 3)`形状的图片通过卷积神经网络映射为10个输出，这对应着10个分类的类别。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class MyNet(paddle.nn.Layer):\n",
+    "    def __init__(self, num_classes=1):\n",
+    "        super(MyNet, self).__init__()\n",
+    "\n",
+    "        self.conv1 = paddle.nn.Conv2d(in_channels=3, out_channels=32, kernel_size=(3, 3))\n",
+    "        self.pool1 = paddle.nn.MaxPool2d(kernel_size=2, stride=2)\n",
+    "        \n",
+    "        self.conv2 = paddle.nn.Conv2d(in_channels=32, out_channels=64, kernel_size=(3,3))\n",
+    "        self.pool2 = paddle.nn.MaxPool2d(kernel_size=2, stride=2)    \n",
+    "        \n",
+    "        self.conv3 = paddle.nn.Conv2d(in_channels=64, out_channels=64, kernel_size=(3,3))\n",
+    "\n",
+    "        self.flatten = paddle.nn.Flatten()\n",
+    "        \n",
+    "        self.linear1 = paddle.nn.Linear(in_features=1024, out_features=64)\n",
+    "        self.linear2 = paddle.nn.Linear(in_features=64, out_features=num_classes)\n",
+    "        \n",
+    "    def forward(self, x):\n",
+    "        x = self.conv1(x)\n",
+    "        x = F.relu(x)\n",
+    "        x = self.pool1(x)\n",
+    "        \n",
+    "        x = self.conv2(x)\n",
+    "        x = F.relu(x)\n",
+    "        x = self.pool2(x)\n",
+    "        \n",
+    "        x = self.conv3(x)\n",
+    "        x = F.relu(x)\n",
+    "\n",
+    "        x = self.flatten(x)\n",
+    "        x = self.linear1(x)\n",
+    "        x = F.relu(x)\n",
+    "        x = self.linear2(x)\n",
+    "        return x"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 模型训练\n",
+    "\n",
+    "接下来，我们用一个循环来进行模型的训练，我们将会：\n",
+    "- 使用`paddle.optimizer.Adam`优化器来进行优化。\n",
+    "- 使用`F.softmax_with_cross_entropy`来计算损失值。\n",
+    "- 使用`paddle.io.DataLoader`来加载数据并组建batch。\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "epoch_num = 10\n",
+    "batch_size = 32\n",
+    "learning_rate = 0.001"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "start training ... \n",
+      "epoch: 0, batch_id: 0, loss is: [2.3024805]\n",
+      "epoch: 0, batch_id: 1000, loss is: [1.1422595]\n",
+      "[validation] accuracy/loss: 0.5575079917907715/1.2516425848007202\n",
+      "epoch: 1, batch_id: 0, loss is: [0.9350736]\n",
+      "epoch: 1, batch_id: 1000, loss is: [1.3825703]\n",
+      "[validation] accuracy/loss: 0.5959464907646179/1.1320706605911255\n",
+      "epoch: 2, batch_id: 0, loss is: [0.979844]\n",
+      "epoch: 2, batch_id: 1000, loss is: [0.87730503]\n",
+      "[validation] accuracy/loss: 0.6607428193092346/0.9754576086997986\n",
+      "epoch: 3, batch_id: 0, loss is: [0.7345351]\n",
+      "epoch: 3, batch_id: 1000, loss is: [1.0982555]\n",
+      "[validation] accuracy/loss: 0.6671326160430908/0.9667007327079773\n",
+      "epoch: 4, batch_id: 0, loss is: [0.9291839]\n",
+      "epoch: 4, batch_id: 1000, loss is: [1.1812104]\n",
+      "[validation] accuracy/loss: 0.6895966529846191/0.9075900316238403\n",
+      "epoch: 5, batch_id: 0, loss is: [0.5072213]\n",
+      "epoch: 5, batch_id: 1000, loss is: [0.60360587]\n",
+      "[validation] accuracy/loss: 0.6944888234138489/0.8740479350090027\n",
+      "epoch: 6, batch_id: 0, loss is: [0.5917944]\n",
+      "epoch: 6, batch_id: 1000, loss is: [0.7963876]\n",
+      "[validation] accuracy/loss: 0.7072683572769165/0.8597638607025146\n",
+      "epoch: 7, batch_id: 0, loss is: [0.50116754]\n",
+      "epoch: 7, batch_id: 1000, loss is: [0.95844793]\n",
+      "[validation] accuracy/loss: 0.700579047203064/0.876727819442749\n",
+      "epoch: 8, batch_id: 0, loss is: [0.87496114]\n",
+      "epoch: 8, batch_id: 1000, loss is: [0.68749857]\n",
+      "[validation] accuracy/loss: 0.7198482155799866/0.8403064608573914\n",
+      "epoch: 9, batch_id: 0, loss is: [0.8548105]\n",
+      "epoch: 9, batch_id: 1000, loss is: [0.6488569]\n",
+      "[validation] accuracy/loss: 0.7106629610061646/0.874437153339386\n"
+     ]
+    }
+   ],
+   "source": [
+    "val_acc_history = []\n",
+    "val_loss_history = []\n",
+    "\n",
+    "def train(model):\n",
+    "    print('start training ... ')\n",
+    "    # turn into training mode\n",
+    "    model.train()\n",
+    "\n",
+    "    opt = paddle.optimizer.Adam(learning_rate=learning_rate, \n",
+    "                                parameters=model.parameters())\n",
+    "\n",
+    "    train_loader = paddle.io.DataLoader(cifar10_train,\n",
+    "                                        places=paddle.CPUPlace(), \n",
+    "                                        shuffle=True, \n",
+    "                                        batch_size=batch_size)\n",
+    "    \n",
+    "    cifar10_test = paddle.vision.datasets.cifar.Cifar10(mode='test', transform=None)\n",
+    "    valid_loader = paddle.io.DataLoader(cifar10_test, places=paddle.CPUPlace(), batch_size=batch_size)\n",
+    "\n",
+    "    for epoch in range(epoch_num):\n",
+    "        for batch_id, data in enumerate(train_loader()):\n",
+    "            x_data = paddle.cast(data[0], 'float32')\n",
+    "            x_data = paddle.reshape(x_data, (-1, 3, 32, 32)) / 255.0\n",
+    "            \n",
+    "            y_data = paddle.cast(data[1], 'int64')\n",
+    "            y_data = paddle.reshape(y_data, (-1, 1))\n",
+    "                        \n",
+    "            logits = model(x_data)\n",
+    "            loss = F.softmax_with_cross_entropy(logits, y_data)\n",
+    "            avg_loss = paddle.mean(loss)\n",
+    "            \n",
+    "            if batch_id % 1000 == 0:\n",
+    "                print(\"epoch: {}, batch_id: {}, loss is: {}\".format(epoch, batch_id, avg_loss.numpy()))\n",
+    "            avg_loss.backward()\n",
+    "            opt.minimize(avg_loss)\n",
+    "            model.clear_gradients()\n",
+    "\n",
+    "        # evaluate model after one epoch\n",
+    "        model.eval()\n",
+    "        accuracies = []\n",
+    "        losses = []\n",
+    "        for batch_id, data in enumerate(valid_loader()): \n",
+    "            x_data = paddle.cast(data[0], 'float32')\n",
+    "            x_data = paddle.reshape(x_data, (-1, 3, 32, 32)) / 255.0\n",
+    "            \n",
+    "            y_data = paddle.cast(data[1], 'int64')\n",
+    "            y_data = paddle.reshape(y_data, (-1, 1))           \n",
+    "            \n",
+    "            logits = model(x_data)            \n",
+    "            loss = F.softmax_with_cross_entropy(logits, y_data)\n",
+    "            acc = paddle.metric.accuracy(logits, y_data)\n",
+    "            accuracies.append(np.mean(acc.numpy()))\n",
+    "            losses.append(np.mean(loss.numpy()))\n",
+    "        \n",
+    "        avg_acc, avg_loss = np.mean(accuracies), np.mean(losses)\n",
+    "        print(\"[validation] accuracy/loss: {}/{}\".format(avg_acc, avg_loss))\n",
+    "        val_acc_history.append(avg_acc)\n",
+    "        val_loss_history.append(avg_loss)\n",
+    "        model.train()\n",
+    "\n",
+    "model = MyNet(num_classes=10)\n",
+    "train(model)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x163d6ec50>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "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(val_acc_history, label = 'validation accuracy')\n",
+    "\n",
+    "plt.xlabel('Epoch')\n",
+    "plt.ylabel('Accuracy')\n",
+    "plt.ylim([0.5, 0.8])\n",
+    "plt.legend(loc='lower right')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# The End\n",
+    "\n",
+    "从上面的示例可以看到，在cifar10数据集上，使用简单的卷积神经网络，用飞桨可以达到71%以上的准确率。"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/doc/paddle/tutorial/cv_case/convnet_image_classification/convnet_image_classification.rst b/doc/paddle/tutorial/cv_case/convnet_image_classification/convnet_image_classification.rst
new file mode 100644
index 0000000000000000000000000000000000000000..4f7bc1157aca5325f5bf8e673e59f4ad37654485
--- /dev/null
+++ b/doc/paddle/tutorial/cv_case/convnet_image_classification/convnet_image_classification.rst
@@ -0,0 +1,258 @@
+使用卷积神经网络进行图像分类
+============================
+
+本示例教程将会演示如何使用飞桨的卷积神经网络来完成图像分类任务。这是一个较为简单的示例，将会使用一个由三个卷积层组成的网络完成\ `cifar10 <https://www.cs.toronto.edu/~kriz/cifar.html>`__\ 数据集的图像分类任务。
+
+设置环境
+----------
+
+我们将使用飞桨2.0beta版本。
+
+.. code:: ipython3
+
+    import paddle
+    import paddle.nn.functional as F
+    from paddle.vision.transforms import Normalize
+    import numpy as np
+    import matplotlib.pyplot as plt
+    
+    paddle.disable_static()
+    print(paddle.__version__)
+    print(paddle.__git_commit__)
+
+
+
+.. parsed-literal::
+
+    0.0.0
+    264e76cae6861ad9b1d4bcd8c3212f7a78c01e4d
+
+
+加载并浏览数据集
+-------------------
+
+我们将会使用飞桨提供的API完成数据集的下载并为后续的训练任务准备好数据迭代器。cifar10数据集由60000张大小为32
+\*
+32的彩色图片组成，其中有50000张图片组成了训练集，另外10000张图片组成了测试集。这些图片分为10个类别，我们的任务是训练一个模型能够把图片进行正确的分类。
+
+.. code:: ipython3
+
+    cifar10_train = paddle.vision.datasets.cifar.Cifar10(mode='train', transform=None)
+    
+    train_images = np.zeros((50000, 32, 32, 3), dtype='float32')
+    train_labels = np.zeros((50000, 1), dtype='int32')
+    for i, data in enumerate(cifar10_train):
+        train_image, train_label = data
+        train_image = train_image.reshape((3, 32, 32 )).astype('float32') / 255.
+        train_image = train_image.transpose(1, 2, 0)
+        train_images[i, :, :, :] = train_image
+        train_labels[i, 0] = train_label
+
+浏览数据集
+-------------
+
+接下来我们从数据集中随机挑选一些图片并显示，从而对数据集有一个直观的了解。
+
+.. code:: ipython3
+
+    class_names = ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']
+    
+    plt.figure(figsize=(10,10))
+    sample_idxs = np.random.choice(50000, size=25, replace=False)
+    
+    for i in range(25):
+        plt.subplot(5, 5, i+1)
+        plt.xticks([])
+        plt.yticks([])
+        plt.imshow(train_images[sample_idxs[i]], cmap=plt.cm.binary)
+        plt.xlabel(class_names[train_labels[sample_idxs[i]][0]])
+    plt.show()
+
+
+
+.. image:: convnet_image_classification_files/convnet_image_classification_6_0.png
+
+
+组建网络
+----------
+
+接下来我们使用飞桨定义一个使用了三个二维卷积（\ ``Conv2d``)且每次卷积之后使用\ ``relu``\ 激活函数，两个二维池化层（\ ``MaxPool2d``\ ），和两个线性变换层组成的分类网络，来把一个\ ``(32, 32, 3)``\ 形状的图片通过卷积神经网络映射为10个输出，这对应着10个分类的类别。
+
+.. code:: ipython3
+
+    class MyNet(paddle.nn.Layer):
+        def __init__(self, num_classes=1):
+            super(MyNet, self).__init__()
+    
+            self.conv1 = paddle.nn.Conv2d(in_channels=3, out_channels=32, kernel_size=(3, 3))
+            self.pool1 = paddle.nn.MaxPool2d(kernel_size=2, stride=2)
+            
+            self.conv2 = paddle.nn.Conv2d(in_channels=32, out_channels=64, kernel_size=(3,3))
+            self.pool2 = paddle.nn.MaxPool2d(kernel_size=2, stride=2)    
+            
+            self.conv3 = paddle.nn.Conv2d(in_channels=64, out_channels=64, kernel_size=(3,3))
+    
+            self.flatten = paddle.nn.Flatten()
+            
+            self.linear1 = paddle.nn.Linear(in_features=1024, out_features=64)
+            self.linear2 = paddle.nn.Linear(in_features=64, out_features=num_classes)
+            
+        def forward(self, x):
+            x = self.conv1(x)
+            x = F.relu(x)
+            x = self.pool1(x)
+            
+            x = self.conv2(x)
+            x = F.relu(x)
+            x = self.pool2(x)
+            
+            x = self.conv3(x)
+            x = F.relu(x)
+    
+            x = self.flatten(x)
+            x = self.linear1(x)
+            x = F.relu(x)
+            x = self.linear2(x)
+            return x
+
+模型训练
+--------
+
+接下来，我们用一个循环来进行模型的训练，我们将会： -
+使用\ ``paddle.optimizer.Adam``\ 优化器来进行优化。 -
+使用\ ``F.softmax_with_cross_entropy``\ 来计算损失值。 -
+使用\ ``paddle.io.DataLoader``\ 来加载数据并组建batch。
+
+.. code:: ipython3
+
+    epoch_num = 10
+    batch_size = 32
+    learning_rate = 0.001
+
+.. code:: ipython3
+
+    val_acc_history = []
+    val_loss_history = []
+    
+    def train(model):
+        print('start training ... ')
+        # turn into training mode
+        model.train()
+    
+        opt = paddle.optimizer.Adam(learning_rate=learning_rate, 
+                                    parameters=model.parameters())
+    
+        train_loader = paddle.io.DataLoader(cifar10_train,
+                                            places=paddle.CPUPlace(), 
+                                            shuffle=True, 
+                                            batch_size=batch_size)
+        
+        cifar10_test = paddle.vision.datasets.cifar.Cifar10(mode='test', transform=None)
+        valid_loader = paddle.io.DataLoader(cifar10_test, places=paddle.CPUPlace(), batch_size=batch_size)
+    
+        for epoch in range(epoch_num):
+            for batch_id, data in enumerate(train_loader()):
+                x_data = paddle.cast(data[0], 'float32')
+                x_data = paddle.reshape(x_data, (-1, 3, 32, 32)) / 255.0
+                
+                y_data = paddle.cast(data[1], 'int64')
+                y_data = paddle.reshape(y_data, (-1, 1))
+                            
+                logits = model(x_data)
+                loss = F.softmax_with_cross_entropy(logits, y_data)
+                avg_loss = paddle.mean(loss)
+                
+                if batch_id % 1000 == 0:
+                    print("epoch: {}, batch_id: {}, loss is: {}".format(epoch, batch_id, avg_loss.numpy()))
+                avg_loss.backward()
+                opt.minimize(avg_loss)
+                model.clear_gradients()
+    
+            # evaluate model after one epoch
+            model.eval()
+            accuracies = []
+            losses = []
+            for batch_id, data in enumerate(valid_loader()): 
+                x_data = paddle.cast(data[0], 'float32')
+                x_data = paddle.reshape(x_data, (-1, 3, 32, 32)) / 255.0
+                
+                y_data = paddle.cast(data[1], 'int64')
+                y_data = paddle.reshape(y_data, (-1, 1))           
+                
+                logits = model(x_data)            
+                loss = F.softmax_with_cross_entropy(logits, y_data)
+                acc = paddle.metric.accuracy(logits, y_data)
+                accuracies.append(np.mean(acc.numpy()))
+                losses.append(np.mean(loss.numpy()))
+            
+            avg_acc, avg_loss = np.mean(accuracies), np.mean(losses)
+            print("[validation] accuracy/loss: {}/{}".format(avg_acc, avg_loss))
+            val_acc_history.append(avg_acc)
+            val_loss_history.append(avg_loss)
+            model.train()
+    
+    model = MyNet(num_classes=10)
+    train(model)
+
+
+.. parsed-literal::
+
+    start training ... 
+    epoch: 0, batch_id: 0, loss is: [2.3024805]
+    epoch: 0, batch_id: 1000, loss is: [1.1422595]
+    [validation] accuracy/loss: 0.5575079917907715/1.2516425848007202
+    epoch: 1, batch_id: 0, loss is: [0.9350736]
+    epoch: 1, batch_id: 1000, loss is: [1.3825703]
+    [validation] accuracy/loss: 0.5959464907646179/1.1320706605911255
+    epoch: 2, batch_id: 0, loss is: [0.979844]
+    epoch: 2, batch_id: 1000, loss is: [0.87730503]
+    [validation] accuracy/loss: 0.6607428193092346/0.9754576086997986
+    epoch: 3, batch_id: 0, loss is: [0.7345351]
+    epoch: 3, batch_id: 1000, loss is: [1.0982555]
+    [validation] accuracy/loss: 0.6671326160430908/0.9667007327079773
+    epoch: 4, batch_id: 0, loss is: [0.9291839]
+    epoch: 4, batch_id: 1000, loss is: [1.1812104]
+    [validation] accuracy/loss: 0.6895966529846191/0.9075900316238403
+    epoch: 5, batch_id: 0, loss is: [0.5072213]
+    epoch: 5, batch_id: 1000, loss is: [0.60360587]
+    [validation] accuracy/loss: 0.6944888234138489/0.8740479350090027
+    epoch: 6, batch_id: 0, loss is: [0.5917944]
+    epoch: 6, batch_id: 1000, loss is: [0.7963876]
+    [validation] accuracy/loss: 0.7072683572769165/0.8597638607025146
+    epoch: 7, batch_id: 0, loss is: [0.50116754]
+    epoch: 7, batch_id: 1000, loss is: [0.95844793]
+    [validation] accuracy/loss: 0.700579047203064/0.876727819442749
+    epoch: 8, batch_id: 0, loss is: [0.87496114]
+    epoch: 8, batch_id: 1000, loss is: [0.68749857]
+    [validation] accuracy/loss: 0.7198482155799866/0.8403064608573914
+    epoch: 9, batch_id: 0, loss is: [0.8548105]
+    epoch: 9, batch_id: 1000, loss is: [0.6488569]
+    [validation] accuracy/loss: 0.7106629610061646/0.874437153339386
+
+
+.. code:: ipython3
+
+    plt.plot(val_acc_history, label = 'validation accuracy')
+    
+    plt.xlabel('Epoch')
+    plt.ylabel('Accuracy')
+    plt.ylim([0.5, 0.8])
+    plt.legend(loc='lower right')
+
+
+
+
+.. parsed-literal::
+
+    <matplotlib.legend.Legend at 0x163d6ec50>
+
+
+
+
+.. image:: convnet_image_classification_files/convnet_image_classification_12_1.png
+
+
+The End
+-------
+
+从上面的示例可以看到，在cifar10数据集上，使用简单的卷积神经网络，用飞桨可以达到71%以上的准确率。
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diff --git a/doc/paddle/tutorial/cv_case/image_search/image_search.ipynb b/doc/paddle/tutorial/cv_case/image_search/image_search.ipynb
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@@ -0,0 +1,654 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "jg3_YfhpC1JG"
+   },
+   "source": [
+    "# 基于图片相似度的图片搜索\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 简要介绍\n",
+    "\n",
+    "图片搜索是一种有着广泛的应用场景的深度学习技术的应用，目前，无论是工程图纸的检索，还是互联网上相似图片的搜索，都基于深度学习算法能够实现很好的基于给定图片，检索出跟该图片相似的图片的效果。\n",
+    "\n",
+    "本示例简要介绍如何通过飞桨开源框架，实现图片搜索的功能。其基本思路是，先将图片使用卷积神经网络转换为高维空间的向量表示，然后计算两张图片的高维空间的向量表示之间的相似程度(本示例中，我们使用余弦相似度)。在模型训练阶段，其训练目标是让同一类别的图片的相似程度尽可能的高，不同类别的图片的相似程度尽可能的低。在模型预测阶段，对于用户上传的一张图片，会计算其与图片库中图片的相似程度，返回给用户按照相似程度由高到低的图片的列表作为检索的结果。\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 环境设置\n",
+    "\n",
+    "本示例基于飞桨开源框架2.0版本。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 34
+    },
+    "colab_type": "code",
+    "id": "hhxOPw1SC1JI",
+    "outputId": "6130c395-d0e3-4566-86c6-fd4de9aed371"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.0.0\n",
+      "89af2088b6e74bdfeef2d4d78e08461ed2aafee5\n"
+     ]
+    }
+   ],
+   "source": [
+    "import paddle\n",
+    "import paddle.nn.functional as F\n",
+    "import numpy as np\n",
+    "import random\n",
+    "import matplotlib.pyplot as plt\n",
+    "from PIL import Image\n",
+    "from collections import defaultdict\n",
+    "\n",
+    "paddle.disable_static()\n",
+    "print(paddle.__version__)\n",
+    "print(paddle.__git_commit__)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 数据集\n",
+    "\n",
+    "本示例采用[CIFAR-10](https://www.cs.toronto.edu/~kriz/cifar.html)数据集。这是一个经典的数据集，由50000张图片的训练数据，和10000张图片的测试数据组成，其中每张图片是一个RGB的长和宽都为32的图片。使用`paddle.dataset.cifar`可以方便的完成数据的下载工作，把数据归一化到`(0, 1.0)`区间内，并提供迭代器供按顺序访问数据。我们会把训练数据和测试数据分别存放在两个`numpy`数组中，供后面的训练和评估来使用。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 68
+    },
+    "colab_type": "code",
+    "id": "czLF_NIuC1JW",
+    "outputId": "be9661e0-af81-4137-96fb-1dadb96c0726"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(50000, 3, 32, 32)\n",
+      "(50000,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "cifar10_train = paddle.vision.datasets.cifar.Cifar10(mode='train', transform=None)\n",
+    "x_train = np.zeros((50000, 3, 32, 32))\n",
+    "y_train = np.zeros((50000, 1), dtype='int32')\n",
+    "\n",
+    "for i in range(len(cifar10_train)):\n",
+    "    train_image, train_label = cifar10_train[i]\n",
+    "    train_image = train_image.reshape((3,32,32 ))\n",
+    "    \n",
+    "    # normalize the data\n",
+    "    x_train[i,:, :, :] = train_image / 255.\n",
+    "    y_train[i, 0] = train_label\n",
+    "\n",
+    "y_train = np.squeeze(y_train)\n",
+    "\n",
+    "print(x_train.shape)\n",
+    "print(y_train.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 68
+    },
+    "colab_type": "code",
+    "id": "lJDRE4a9QaJo",
+    "outputId": "ceed15eb-9c2c-4051-8009-0444136b5462"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(10000, 3, 32, 32)\n",
+      "(10000,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "cifar10_test = paddle.vision.datasets.cifar.Cifar10(mode='test', transform=None)\n",
+    "x_test = np.zeros((10000, 3, 32, 32), dtype='float32')\n",
+    "y_test = np.zeros((10000, 1), dtype='int64')\n",
+    "\n",
+    "for i in range(len(cifar10_test)):\n",
+    "    test_image, test_label = cifar10_test[i]\n",
+    "    test_image = test_image.reshape((3,32,32 )) \n",
+    "   \n",
+    "    # normalize the data\n",
+    "    x_test[i,:, :, :] = test_image / 255.\n",
+    "    y_test[i, 0] = test_label\n",
+    "\n",
+    "y_test = np.squeeze(y_test)\n",
+    "\n",
+    "print(x_test.shape)\n",
+    "print(y_test.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 数据探索\n",
+    "\n",
+    "接下来我们随机从训练数据里找一些图片，浏览一下这些图片。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 357
+    },
+    "colab_type": "code",
+    "id": "JhjoI3w7C1JY",
+    "outputId": "4bd42a22-2a48-4296-f0af-5172d8f46793"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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txVo1aVKXskzWCsJWggLHbK6qejp9ni4nVXkNfjByg6ZNymWW9QUJ3YU5G0ZRMleACjpHti52GxDBTDGGGDlgIowUYuzH8XiDWNfz6roGYoRa1mWZF7MNfSQOMcYMEMTBVRG2uYaDObq7uboZMnKkMOxv398+fLvf3eQUm7i5ObwW7VcEEDdo7uuXEwBRCDHE+AXV/Aoh3QolJER3963QoBi+Oj7MbUNpCDj2HQJCqeBCGAA3IMuun9724QKAO6kR0pa3v5wtG0JA7rDBugBbS2+O5u6w4f0ECE4Iooi/IJLnl+f/7//9//x3/+7f8rjrht1uHI83t7cP9zHltSzmwow3N/eUxry/Swj9jd69+4uyXJbT509//N0//Jt/eaLfw/Riy6RllTrPbZFWAgDROi926MaboesB5Fy5aiht4khpZ9KV6XJZViBzc1NiR0IGAEMTBiUXlcdPP82tPp4vHsP55VnMm5qYi6MjGJijfkFjHWA1Vox9isx42vXGGeI+hi4HDhScglB0ikiB0ZjArZVlXVWn+XT+REPmfsCUAkAECyaAROmwY+3MdS3r+XSWab2dptCfo/n08vL06eOnDx+XJsapG4wIzYxUUWsXebfrcr+rzeZlXdZnbjWiDCQdOLgKhMV9UZhKO8/LtKz6isUAQEgxuqoq+WtPDuAGBmaq0lozaYSA7te53YYS+RXgcYcqzdyII1FA90AcORCzqwAAAQBRDAHcVRUcEIEACYiAGdkByQkNEMFsmyyJaZNWpC11nZf5ZK0SuDuIQjTNLataKUut5ZeSbHvmQV3drFhbiAOnLoTEsUeOpoupuDR0gOiIQAhMGBOHGAiDG4soqRoQIbuT2bXvNRUVNXdzcEfcQEwwREACBHRHs+3SwBABkEKfx9vD/TcP73999+Z93w9MpKiOfp17+jWFb+0O/GnwM3OMMcQQQgR8/Wr/0o1vw71f+rctSgkR3LcRHACYeWtGhjEBONQqqho4bFOS6wzD7TrH2cYB2/XAFyB161FeJ4X4OrBA/GXi9wruIcIGEIrIlxTTlunj3/6r3/03/xUO+9TvxnE4HG8O9/exy01riLzb7eXhFJDO5wukGFPqcjKnCrFgWiGt2FFwD6FptD7nftejBYQuYQu0GK/GCBpZD6k5e+MQI1elE+QL+yIq5JRSCCGnjolUG2lxWUSK1HV+fmzI+XDcH276fnyCnwXOZGYCoO3rmyJqp2U9L8Vv+y6F/dgBg4aRMCV0AjLghiSOvDVQCKqt1tmklUJCbkOKYUwxEkWnyAEZVEGBKafE/c4ohcCrwmleosG8rursELStboBgIWToRhSEMgE4x5C67IFZUO3ZWouyZi3RgzhVD6voWmprwhxiTIRf9fwhRHUXd1VzUlBp0gjUZG3rslwmbRXd0bc4MHBD5hgzh0gU1GxZF3MPKZvhrr+paQVgjFy0AVjYJoHMkdHYxMUdGJkgMMZIiSNoZ4nYXJWItDGYMhQ0twLgW5f2Co7BBplt7Sb+twZk7texDhKiEgFTCNzH7sBMulY0hBBCAGaGa4PqkThGRgxNvCzzUrEBpgTY1B2bipoiETObyHWwLc1sIgzoyIREAQzcBMAdEDk4h35/d/v2N9/8+T95/9u/uHv7PqYEbowbcHhFzowc3QmAwOmr8R0RxZhyyikmDuEVIQC3K57/JS1/ufINDEBAdWutqgggNbFSDcDNq5tO09kBxnHIHBHczNVMVRDQ3dUUHX3D/43w9WT5MggEBHTaxoxm2lptIqambuZbRQMq0mpZ1/IF7UetYfqcX37wdYchF+LHGJ665ExKmvp0e7x9urn7w7/767A/Ut93+91hd3SHl9PL6fHz86efZJqiMdGgKXbH/v3bN4fjvkvB61wef3hcTtPsUOZVgCK8P4QciK2pYd0NpxJ/Oq8XQ+12YdiPhxsOsdVSl3OZPtfpRS4TUEiBb2/vv//H/0lz+5u//iv98QerDVeW1hz4y42pIh+fnn76/PgXd/1u1++HLgVYjcyBAcyxOoB5MUVFZlJXkWKyenDmyBSJM9DOaY9pCBTRyefLcnkh8tvjsRt37d17VdXanteGwiJhuPnmHjJ//IO5jV3O4474xspcXn4GRgEXQIyZogAgtRqXcyiZ81312KSU2uoys8PhePdw9ybG+Evw2zbGMdvKRPxqtKuqGy4CZl+C392YGZEckMibaFlXVY1NauykFK2tUQXlpg0QgBkiExA6EkTaKCjKruiKgITuBEROboqGjGwc0U1Da8Tb7AEQr4GP2ygNYJtPfZUtEZE5MSciQ1RG55BSt++G2253g2ilnVyciDgghwBmIQZzVgdCVDX3VqqCADBJhuCr1raupdbm7tdU6HYFuE0cnZC3pAvIiIqESIyxpzyMt988fP+Xb379l8c37/vdzh3UjdAArxClba2+X/G7r05kAAAOzPGVPbGRe15LeXcgwm3kDq84HZg5gKGriLQqooBUm82LiFks6i6lFCYKURAJyd1VxF5Bft/YC47oZrqdB9dBgr8iE45wDX5VLaW01q7PhPt2BEhtta6lFPsS/G7R1tQmB9C6FnUDt4AeEBKmnG06v3z+rPGPnnsc+zQOQ78zw5fzWcoSQdjcWzBDQzum7n445Lt3/TB4KxYHnc9u7nWC7mPQeddhctdFSYyJLMARDJXWECEGZ/YYQ4yUYugo5VRCUjUg5MCHmzuP4fjx41LqcnoWrRgiEH+V+fU0XT69nD6ebnYxdiFmotigmYGBEjIFpGCkxdSrFVmYpc9OCVOXhm7cHW6Od2/68cihQw6OPF16q7Nb61PucwYOa63PZZ2LKHkIw+7ubd/vAnpZ55C6QDHEbICWd4C6NgwK466PiHDZd7oQUKu2FF/Ma2nWGpkE4jHFISb+ClsKpRZXeZ3xuhtc+zfmEEIMAVRBFQxeKSLIIcQQOAZEBoQQ2M1A1GqzJhs5z91NDYkAgkPYcFbX4IbWxI0EAcFAxcTqUttaVKpqVXN3AoiECTAiBaJIpGgC6LQx0ojQAZmICH7BvTl1u9TtSRb0ihBi2I27d/3N+7y/U13qhQCMCJiZmJE5dx2gt7q4aauro6hGBLBC4tZsrmW+XOa6NN9AHzcExyvwT4SMAAhuCu5btQ9EkWOf+rvj7bdvvv3Lu29+m4bRCd0MXQkN0QHIth/5eqoh/mki32p4QBTTK+xmpiJbX46IW8CqKrgTUXDW69xuC/6moo5Uqp7nslRBByYITCnSuoqqU3AEN1NwYAJEYL5yB7Zqajv/zbYGf6t4fOvlEVFUy7KKbjMOMARzE3VptWwc0NeynxBjpJTYAqlxETeCnCj2KXQdEpXVztOlwqyBPUcNZAJrbfM8D5G+f3PoiJ8fy1xUApzXc973HnGst+OwG7/5iz7nLnfW1svTH/X8yerLNJ1Ptqw6a53chPrQCS7zMk/L8+Pn0PW7m9tuGPqb+7QbaRjW6TIvdZ4vl8spH28Odw9rXWtbZAYPATnAK0Lu7mttz9Py+0+nnuJvbo9DDORSRRWREqbd4BjmssxlXep0qZdh8Dh2sR+64bg73N/cvrt/96t+2KuTIzvFaTr3mebLC7jP8wLupZUyn2vTAjrsh8PtXbp/03f96enpcjnLKqgVwUPaOfi0Yuzw212/u+nfcLV1xhhfJE2TVGllvnBrQ8SISG2xOvtX+GV45W9s1wYAQIBERE4QQkwRzAwRFLahmgNsZTwHJgqAEEIwUVR3FWm1leIc4Xrukxs78IYVgEdyNtx4emzqVcXEVNwc3ZEohpgcTKSqOtKMlJAykoE7uG7hQgAbbeBPMj8hxxhSRq9kgTHEuOvGmzweQ+58regADmZuamrGxBxjNNVWmqgUcXIMzOTszZs2raXUWquIoLG/UusIEYEYN7BzI8xsTDJGJEdGZA4597vdzf14vA05IQG4A201AwIQXqeCAGYIaED01Qxmy7dmZiZbe++qTZrrFWZHxI1ss83iArMIA+I1YK+zE19Km0udawP1GKjPHZGta6kVKTiRbxysQEAEG+PSbesoeGsENmaHmqnpdViLgIRmJqqmCvTlLjj8UjDqL6gyEaVAKRhSMzg1bYB9xKzYWdAG5/PaDELXpRS7bmeEU1tUDBwZIKMGE5kvy1xrJI/004+/L7Wk/nC4eXjz7pvjTRwTQxiW/t4gaB2F55Vq6WcpJ/aaA+Xm3ctaT/NymVSnFHMITGmgbpeZNQaQT8t6efzww9gaIHDKTZu6D4fj7njHIb4eyhRTpxg+ntcxTvvU0QAIFhjAnNn7jBW9lnpql8v8XG1NGfqcU5+7sRsP/f4w7Hc5dak2VXcn77p4OB4R/Xy+rMtq2mpZ6jrVZg3RRokp9t1OlIulqZjWF1xXQFMkR0IhEA26DimksVsYT8XWWex8MhFpCxN2XQaweT5P03mrFq/Bv80+HOkKIiESUkD0wGBsKYG5bnNf141URsy0Zc8QHDGEYFEdxd1LWZdlThRiJgyJIICz2ZXed51+85Z+CQCkiaoRc6QOUwjM3Ti62+V8EjXkyWmh0KH59lC7G2wzk1c26peuHxGInYKjAmuI1KU4pG4MKYGJtQrqLthMQQ2x5bTR2wIYS2vNnLJ3A3YdJUJVqM2tXfPg1gehAwKGLf1tkKg2dwUgosCpc2C1jRVTHYUihxSIkcjdwZ3cN1J+CIjs6GaqIO7uGL46zNxd1VpremXigapKa6b6BW/cwmwD9ogohAAAokaAMUVzW9Z1KrWKmhsimAd3E5FWDcCQnch5Yx+gEyGBI4JuTwEFvHYSV86vqRr4leXgBIi0cbrx9UR0d1dWfr2K1xtD6DFrzFXpIvpxKmfxLCEX6KagCk+XKXbddw+3D99//91336fcnc4v0zpJK0nnI57lfN6l1BpCoLrWH37/u5//+Af12O2O77797nj30B8OqR8opD6lY3/X3X7T3eXoJm0GLWSNar29rPHxiX78Y5nPtpYVrKnE3Zh2hxw4zpe2Tj//7m+6x0/h+LBM0+n0Yqr333739rvfpNxtlxJjvLt72O3vTqX+/vGciNbjeDfmLgZwd9dqbQZ/bvNTOU/rGUn2Q59zjDlwQHMp9XK5fArLaS0i6oZBHd2dQlTkoiCrlLWUtagZhAhSpMw19pUHyQLdxde5Ti+itYUuxLzPMVprTz/PCyumi/inuZ2mZZnOoC0FHvsOYwLTl+en4/Njk9fp2EbygY0n/Xq36MruJAghpPQLUXxrPcGIicL2ixkxpLjJR5ygqqhZSmnc7XO345gRIyJ/xSLfEvcVTgAXYsgpEaFrTSkfDrcAGNOAzGaKjK3rl+m0mqg2NwEzgldRzJ+QrzDEmHKHqCSGFh1QVLEsqk2WCZFjGtwjoqpCLY0DaVORLb/SFWLv+pxHVVBMTZmqAywbuRERmZGQwKHJluGquQFQAGJgxOAuSJy6rhvHfjemPm8DdccrUAnu6IK28ZmREBkhuvMrZ24L9Xmaz+czADle6Xcq6qZXUN7MHND9FWZHauoAIoJEHbiZT0tZalN3M98Imo3Qma40TQMi11fqESKgGQAobHwpxVcQ4goBqQG4ARLQdj7YVzQ+2HBQADMXEdFfyn4AVGIhVqcGvhhcxJcGES3WKs1OS+0x3hk1ShA7zl1s60BG0HHjOM8G2OU8QITIFdWt1lqasJmdcmhl8g+Bchf6w253WG7uduOOgjqSgYMhGDBw6Md8hLGUkKJrRXJ0ZAz9sM99p+u0nJ6kLuv6vDuMgSQQQuzG3bHf7YmvI9QU05v7h/uHN0+fPp1r/eF0aSazdIc+RwoROdQygZ1qvYgU04hOFJiCKmq1CrX5ok5MXGtrVZqYUwxpqIqiro7q5MBEgdGIiEzLMivkqeWijiFyDBVUtRggBRw4JJflVGSGFoap4fOlneelzBcCg67LDops4LPqsvGyvwS/X2dX1yMA/cv0ip2NQqRopKa+QewGoMi0dZAQmAhDTgZuAM6s4BTDzd3d27e/2h/vch6AGJA2dAB8A/eg1XI5XZZ5XXJD4t1ux4xlnXPMtzdvOYRhfxj3Qz+E02lc1/X09OmxLa3MbuCm6L6RDv80+DnFceiP3GUta51raQucnmidrBZyTZzi4Q0nMinL5XFdZ7xS0au5xZRi6ogzp2N3/z1yopdHDx9qw7a4WXXfUiVyYFOvramKWnN3ADY0N0dGYIrdcLh7e/fmm+Pt3bjbETDYRgDc2PUCtXprTQ0pUB4wRIbGSAhxm42K6NPj44cPH1PKxBEQ3JG2yce1rFdECBwQwwaAKKCZNVMwtRXUfF6liRuzm7ZSEQytpBg2Isd2IH/RCG7MXFW7kpgQiBmRthLDzfxKREBzcDUA3zh/eAUc3RzMvEhbyrKW+gXwcwcxEwcnpkihMybHFAWp1iZNxL2KPj2fww8/Flm7zG25MNiQu85bW862ttDlcYihYwsYwRkCUo4pjUMSqZ8/f5qWKpy6cbjc3HQ5t2YOyJE4IJH3OR+G2xxyvr9Nx523AqYInodhP+woYhdoPh6X+REJ9weMITzc3kkDZraN3P2a+d++ffPtN+9B2uX09LiWS11+PsFxHO6PtyME5lLcp2piDNxxAMbOJU7VKjShGvN6WCkFMqt1XabLpM6xP2Lo1ICIOGZCTDGYmQET0HyZdLZzIxXPaNhFzdGcCOqAfgiQHadlWZsselrFq4A7pAAxpNylkBLGBBy4H6kb8Kvx8BdWyDXrbP0oEQG6UyAEdndzQAQjMPVXKQ+FQIHBiFMKgIacUre/ubl7+/abb7979/5X4+4mpc6JNkr0pjsDMCJcltnETcEpUkzj4cjsQBA5xtyllIg3CVNJXVK1vuvafGplWUX8lRXnr0PvL6WyiZk6B8YQgURNSpmxLrJOMXB3c9/tj/1+p20xKdYqmCKGECNSSH0MXQSOHPvucB9zzwQgpU5nWUqrorb1wphSULNSAK7o3SZkNNWGgLBlUSQERFO0FskRXKyJNlHRusAyQV3dJISc6JYxm0vWRHDcgl9Vp2m+XC59DyFsdH5AJAB0NzdVFyIyoBiAMAJAbdv7NweApqq+rCrqTm4mrVVCRWgOwTE5BtpmKACA5MQOWs22oSa5gxkBEDv4lyt0ACB3NN/wCBHZ5g6A4OAbYUFVNxnQlxtjAOIgAEaMCWPnXUTM2RG1SkyhpyF1fep6MX8+n8Ns0JbMwN4YzNcCzQzQEdUdAIlC4hxin7s0dGGdm5W1Xi5CDG25WCuB17WoKgbkwByw7/uyn4b+kPIQmDEyGZKbo5tV02CYII7UC5Mie8708OZNWU1dl/UXFikzDkN3c9yv8w1AO5+en9b1sdXnKpZ3vqNd6ok5GCdibSGz93kgolNps1hF4GYALUdAr7WUaVrEiCWGjBQjAW1icSIMfkWT2rpWb7U6AFEOGJhz795Ya8JmzUrzS6lzkaVpU0NA5BBiJuANAjIASqk/3IyHA4cvIQ9hSyhACAaAvjFIiQjIHYFpq08dCUG34FdiDilzjEQM5OzoGDHo4XD7/a///De//Ue/+bO/uL17ixgAedPfIpABuCmgE4KKOKA5EoUQU0gJ0QCxapvX2cADU+5y7scQue/Gwzi2+SyltLWoqzttHf/XwW+q0/nldHrq+8DbUBoITcxUygk9Ad2msT883LtWW0/s6upuYr4SS+wBQyhOTNyn0A8cBaiQzqOVuSxzc1O1CJwSO3BZqgiaoRmAk4OJLOjCIbis8/PT6cOH04cfD2M3HnaJsWlZ12Wdp7accX4hmRNI13W7dAnQubVd3rP1AHE7yERNZCvtQZo2UdkkQYhIBqQMDGrIGEMytWW+lLY6blM3EIHSoImLqoMgtRgc1KCBOrE4sVMgDoEIIRAYCICCB0ZHtI2l6E60IZEoYmDu5gigZqYqIgDAIcD29depBXAgjr9orR1AARqhB3bkNOAOOAw9h4BmgWPuh67bxe5AIYgV84KIRLJJCgxQBdaqk8oJmjP0MXQpp1TG3RjDDjCEkPrcc0ox933skcgiFl/ruhY3CliWZTpdUsq5G3PXh5xTCIk4QVmfizhdzmrmqe9ydJhrZLp//3ZZ2o8/f3g+Pclrn+zupsKB7h9uOJh6XepyKq1huxW/z8Pd+29j1+Wnl/N0Keu5R7kdo6m9rOaGisGNWjPeUpUiUN7g3qbADAhoCujAcB0mOYBoA20sBkhoCRBDNxJibGeS+fl0MtUGKAYuSmaO4KAG0MxaE0Duxjp23d3Dm9v7NzF9NednZgdwZ3cAZA5XJB+YCA0BiJmJLARQATNAI+aYOgoBAMXMQDlyCOnN22++/+2f/+o3v71786Yf9iKm9krH8SvV77USBFUXdcBIdAW/HEBUlzIjehh63tgzIY3jPhJf3n+/Lss8z9qWmEdw7foh5/zlITPTdTnPl2fwLsUQgBDBtalUaQug1HapdRKt6La9M8WAqI6BQg25GaA2J68oZ2ol+DmHte+h7zlGbAGJKAQOkdycCJgwcHADcxIFNQF1ILc6r6fPl09/uPx8V/bO4b7LkUqxZUnLQmWOfom0ZpSOy+AULbnLDoxBvgSMmDd1UTe30qTU1sQdIDBxAAruiK4KIthEm05LXWsBQncQB1GoDZqaSCP2fiCOCGhXfP9K4scYOKaYYjSzGIWYYmBEcrVNIcRExLTpuhyMcdNqo269IWCIDFtOdt8EsDiMQ9fxV+Xlphh3QCIacuwodmMfcw5MueuH3SHFXjE19aWYiCJ4QgxoRIyxQ3X0yOARgpETEjq7gim4B855f/cuDxUQARmQq+hSfVlkXmrTRgQckGnt++6AUTi4W2DuQ2ABP0szktbFNB77XXNdznMKeHsbnf0yr+dplleE3NTmeV6XGdBDDCEG4rAN7WLf7W+Od2/f5X4wSpRyXbvsdchQ1tWhqrkz+uvQVg1UyTaq6SbONgQAMUSnxERkG6rsKiAe3ImYMRAx9jtIMRTQRedyMTVOuc+RN3joqvxgMWgGagpXRnoOMeOfMPxiBCbgLf/HmGNIgWOggMAQEdRMQvMm24dNCMQcUwYiUUMxB4mxu7l5892vf/P9b//izbtvY8xi2jZkycAATBUBNmqhipW1rWurVWPOAKzXttJVpZSZ0HJmM6mluquKptS9ff+9iE7TvEyn3fEGXZqUw/EmvJYxbir10pZToYbWhdAjmcqqrag3lzqdPiCoWWGMy+mCYl0XYooYHBmIVNyCCuqpPv8DzGhy0jIzSc7S9e5OIXCMAQlU1NQIIKWEgE0dm3kzB0MXb1O9+PKI04+8jmfO7/Ju9EW8Gqtz8t0eu5gjxkCIvBAVANvzyK/KSgcQgyq+VkHyUlupTcQdMSIHx3glO7emvlaVppel1Kp25T+xuJXamiqihcD90HUdoQkjppBi4E3U0Pc5xxRiNDMCVLNABA4mCu7EVzsBdw/EaM6vhYC7b+5AzNvccZuDuqm0rrvbHb7cF9yIyIBmFtFvAnHkcUvSXZfHcdztAOmy1EUaoyqiOweHaBA4UT9wF0JLA/AxkCMQKJq5QUqZwi4NY3/7nahezpdpmqd5Pc+Xl9N8maalFFFBhJjC0AfajfHmbejyy3zSUlYVb+38fHFMx5tvjuNI6Si6fn5uaFW9q1Wez+W4yJfReBN5fnr5+PETMdS2qkIIqUvdYbd/9+b+/fu3D28eOHZLEQD0YQxWo69zw2JTU6HogQzN1KEaNQ1qgIRMhJvRhWMzRGBGYjT3ZibaqptHDjFSChhiGGMG623lQtBaRW+H/W4YxtQPyNEMapO1tGUt07KGGDklx7CsbVmr6leAHyJu6QIcrrYOX0ZOSMQISB7c3V036x4KzBwTIBoou6ccd+PNu/e/+uab39w/vB93h9a0qerm/OJg5qINASIFM6+rrEutpWmzEGFj+pirG5haaQuCDUMHpqqmTS/nOYVIoeuGm268NcCYR/SauiF+lfkBnNzQFFRcxFDcXERFK7i62jqfCAFjTHFwtxACx8DBgbfJIbo7uKjM62RaHHxRqSaGUGI06CnnxEybuh0BmDiGgIDmooiEQIiJOSCAljY9nz/88DnbTz5fhn6ZGxHtd8PNzfD22Pdd3vwRTM1BETWx0i+yagDcym+kTYVDROTAGCLHzCkiApmjG5qrgYcYm2JbVdQBzcncPUXschrHdNz3ORNoQ8QUYuQQmEMIOacYAjGbGaTk7owE7kpbVr2iiQ7uwcmvDj90fUJ+4SWhbRWdqTZh7lPm1wwTYri5P9y/vS0Va0VvBgBc1bE1Jwc0FTU/ned1raLuaiZGYByQAhEHpMhmiBE24ZI10yaiPNfZefR46I4eqE2tWCmKq9hcZClaFEVJTaIbRRSIGAdIqU6XZhgxqOrLpSLAeAAHqE201WUR1DZd1tqsVTQL/jqFMfVlKZfLTBHclSjGNORsOfUp5ZzzMPQhDX0/SBMXRQnavEERjIrOV7TEnUiBFVGRAIGANwsIBzJEhG30agiGRhu1jhAYndEyQ8qBkBsL+SBlYNDDzf3hcOz3e+JUmyxr5WkGujQzIFbzUkU3wt/Xwh51c1UXAQcKhKaiAsKbSp08mLmIuqiLIiAzAJCrAZCaI4U+5Zvbh/fffP/27bddt3NgMRFVB/RNJGSmqgCOTtp0mdd5WltpJnYlssjV087MaingXmshQAButXycHwkphDivZpCRe0c2AzX/+koIKYWcYp84BiBrZaMdutsmhddWa1uztpQxDX0mioyIIq0qVCRQQ2mG2taA6o7etNU6VymV0bnjcRfB4TKpmjEzIROxm7sCqAekGOLQ9YGjGJjg8+fF2uPTR2Oky+V8cwj/9B+/ezi+3Y/jbszLIrUq4tZJG/CXZwwQMBDFwCGGEAIxphhMjQJ1XYo5hhgAUDaGACI4qOLl0kqby1LEWmAfRz7u093NsBtT7kII7pY2dzTmwBSupn+Imww5MiM4I6O7XdkI4Srs9U0vQQi4fcvraeRmBubo4OZqKuDQ2i+EWIBuyL/5y++k/tnj5/X0eZmeLpeznM+X1aaK3sgMTUTXubVmX8zi3N0AkQJyYuboyEh2ZVirmzRTynm4vb999+7t6iGn88tzWWdQ2zhYKYVIXROZ13UrhlVNRFDZnJi7fjwKlRAXVyBC0fn0cvG2ohsTSzFtHnjIafxaDOOOZghmiBxzyhbXAkBpWtrGz0vMMUamKK5NXBUXC84ZA5hBE6NIBIwhkZO4OZgABiBG9I3YCRtN/OqPw9LAxTY6plYC7DiFQILIFqx0RDQeH3Y39+NuRITLvDSjUDXEEgM393lZSYCApdavYbJw1WSoAxhsY6QrigUI7OhXdai7+2Y05QCmoJtePKW439/c3b15uH97PNwFjm6wvecGJruDq7vZllxVfVnKPJdWpTWBdRE3roToZlWalFJM9XKZGalVrdXKuqJT7tCUu25PDBSs6dLEmuqfiPoA0RHMfaMNm6tujek2EzcCGGM8dCkgRoQALuKlWjUDMgc3d4SgMIA6NGmrLpe1rNXFQgrMW5gYIBCjOaiaqZkYInYxpphyzEjB1M3CWkie5PnlpLVOl6c3t+Hh6O/fJNNbog7QHK9x86rvfz3ICLucxqEbxz7EqLod0UJMOceQQuCAuGGNDoSivhRDsia+FmlSxp72w/Dmdnd30w9dJH5V/lyNmpgw4KtnBwAwYCBGACJGdwVFRCZGhI3hcE3519x/ZWyZmxo4ONIG+NsG/cMvZzJwoN3dcPPuIJjW4o+fTqelXBrNzaa2rlbFxcxN0LYUYNeDXQEJY4g5bpZ0bk1M1U0NwCwgdV12XJALphDjMp0Q9DAOHAOFwDmGEIMHI0OCfswxB3UBYTNiCiH0lGM/7LVWMG3rpLIG9HHou5hyzGoIcbx/ePhaDLMV52BOeHW7AcTa5Pn58uHD488//TTu5ufH0zQtoGIqotCAMEQOpgLuaBiJI4fozri5I+IXYadvZBjamOsM7ozbQ23eRAKqNgBNgKh1kjabVaRsxIa0ccBc1UyatrWVpaxNPVgIyVJIoPL1YxY2jepVWPoqBYXrVP/L+O9qI7EJQEXNm+DGahvz7e3924e3N4ebPneurtLQtvYezQD1auS7XZC7rkWWpbbaSilrXR3JEThSn9m8lbVUqODMyGVt0gycERk8hIA3Nw+tZdPTur6U2tbavsxg3V1aa3UlDE7oLu6AHgBQRSk4EQ2p++ZwuN3vbF1cGjnNiqeVSgOnhuyUiOKA8Vt3aEXX0/nyUlsrm6+ZFN0meUzA5OpaVlU1V4oxjcOYYnJENTAnogxhp5jmstb50ubLC8Ef/sB3d9133z2kHGtrIgab6A7M1L6cyoFpP/Z3N4fd7hBjuuqsRNx9c0gjwsAUmYnIHM9LO71czudlnpd5WVSX3TDe3e7ePhyGRIGvrGJ8JRHTRi6++v68Fu9bd46b1MjBAV6Z/bD9ljarD9+ElgAbU+tKMd4kAGqmbptx02u0eIVSuUIfWww/T8vHywzdrkVamlY3D8wUBs6uUJZSW90IHIQYA/Yd9ZE7Ihe5TLouomrIHLuehs6YzvNcfvzJ3ct63u/6/X5MuaMlAipnZiLMXUx83O92uw5IW2umSBDMQgh8PBzbOlura1X3lsfx/uHNzeEYOSIH4fDdr37d9VeGnyP4NpdSN1dHbaWWMleHDx+RCNW0H8bL0hB5N3Ypxs3wLDIl5mIOzBw7TikQodPVaupqArPJ54CQeTOzAzS/mmiJoSK4KoF1kRu00+lxml/KuoZuiNPRAZYXYwcFWOr6cj49Pj89f350h90exhGJnFG/FsKGELKBoKmbIPEVDHSkVysqAAjETkAIbi7tmoeQASmAEzpqk8vp5Ju+BXzLviLamrWqIlWhxRjH3b5VKKuU0mpZlumyllJEzSF3+e5un1IgCIAospHhGDfvKiTGEGJkgta8rAsibqySL1WMu6lUaWvgBEzuAgCb+8xWxlLkFHgXeE9YXVUFDUsTEDUxQmOERJw4j2EExZV6iruwR5GqJo6gzZ08EMfgQmpuTUQVGAiJY0ghpCoqhgYBIJoHcKi1SlvRqlb//Pnl55+en57O+32/VUUbg3ZT7X2V+anv82Hoxj7zNfjdRF23gTcww9Z1qGItMl/K5VKWuUgTM1ERUyXEQGF7jLYJ4bUWs+uM9ItLALxaOG4sA3DAa5G3yfcZtooACYHcNrNwAwRVN93U/td6/b89gAUw87nIaakvCz6v61NtZ5MMaojqam7EiWNkDibmBQ3RkJAwJu5T3PdpSDEzaSNxVTdzwBC7oce+a0Si0uZZRNb1TIxAnIdxr7ehzA5iIF2m3MXxMHZ9j0Qmm5QaTR2ZcorQeJ0uCDaM/X5/vLm9uzkeCSikFMbh4e391+MxJEc2dLOtjZxXqTNhULVpWv/4w08hhNqsG4YY3oYYfbO0JGIiIjdiRwZkRAhIMRAaIBihMoKBE1xZ5HAVVF1farQxPUSslWoyn5+fLvNLU4lm8fJiIlEaA1CKi8gyX+Z5mqcZAYe0QAyGanWFr3v+od+r1IZuWilGDmmTnQRm5oDM4M4OgIGBVNSlqsurdR1JkefHZy3++OG574bcDSEmiiRqy7RO0zJfSpPqJON+9+b9tzENtaqKlmU6P39+Pp3mpajjfr/vI+fb49jvQ4zEHQJ59FrrahcEDxxDICMjiNqYiWmben1lZGlWzFY3dw5bYHmrgIARwJkwBjeoqxNZKd6aqWurDiWgJIJE3HMcOdyicKRpzLZ72/VDU3l6fnw+vzxfXrRJlxIGXjcd52YpQARA5iRGTVyMHZJ5aFURKkthlNRxZFum+vQ4PT9d7u/3XZ+YeWNhIMGXCnwL/hxDl0LY6PMIhGDIgOhoxBACKvhc9HSun5+ml9NyWmotgoQhsjSoVc6n9aVfYYzDkFLa/i1TFVVzM6brrG6LWdyMmjbLlG2cj8jEWw9KxEwMiKa+2ZoBOBKCIQARXHl+r2jgK18UAADE/DzBz5/rTz+df/p42tpiR3Ex0MYOMTAHUqmttlJLa+qEMaS+y4chH7vYpxADNW0NAEKIyTCkbj96SiAGjhiCIdrC6oyUhvHQ73fTenl8+rzUOUTinCgPlAemaA7oxcW0qZmCirW6zJeu627v37755v3u5hi77KIceRi6YejoF2sDp9BCbMGtSJ2n0zQt2iQPx8PhMOz2pbRpWmqpZurv3nHKjkhq2+m4bTcQcxLjSEyQIkUDs20WBmouruAEjmYo3kSabLQpYERmDkhb/Jd5nqfLLO7JOOSTlMpSA0HsumaupUCzzSiWtUKZS1vX6WJfC3seHt6rlLr0IgWZKaaQh5RyzolTwK1kVPOmUqRYqd5cXdVAHYxmm7X59DwFiinlvt+l3HEIYjZPZZnLOtUmzVn2d8eU98M+SHMVW5dpnU5tnV0txS7HlDgmSiFkougQwAg2KyIxUCFfAoHILDKLNgBHog1+/JJj3MWs2XZ6GkXgfUyBvEEjDv0wjrt91w39sO+6AdRcldbLy8tqbhlgwHiMu9t+97BLBP6METgcbx+KKKxSpzrhGkK63Y1rqU+PFxEhxM2RT1qb5wm5qZFj3mqoVitBYyuRtCNChFb1fFo/fT7f3O3v7m9S5lJNRAGck3wNYBB+8dO318E8AKMjmdtSZFrb06k8PS9Pz9Oyts2Zk9AZHdxLqZ8/vbD7ekiH/bDbjTHGK93LjIliiDFGInJzUblqFzYvn63J4ZBijDGEEDiEwNEBpEmtdVnXV0+RX4yZEK++YluO+3IhIv7yoj9/WP744/Pnz5ci5ojSiouie2BKIQBRs9KkqokBADJR2NwZEBmAnPjqWpOd0SiE1AUhnJs6cIgxUMRldQzmHGN3uBnHMm40Y4oBY+dhcO6QI7EwFjSlVq1pnaZ1vrRS+nE43Nwcb+84BgVwdwagjSH4y0TJwFpgG3OXGKbzJUbOOe/2u91+6Lq8robGMeWU+5ASEDeta61r22Sq0YGamLsAYArOgZHB0MFtk0YRmJm15qaA1qS2zT15Y8cxR0BrrdT1uniimQKGuq5oBtLQxZeLGbRGaB5DJN9UsrM6rev6J2j/b3775yq1LafWFjXDEFMeUs45p5AChoAIILZO88vjc1ubirWy1f4OUIjmGC6BQtgcvGMiTsTBHVXBFEHRzARbSLkWyZ2boYgt89zq2nfxbtjf3L49HG534y7EUNVLFfFtkQW2WtZlret6sclaWcsZacmDNBEAQuQ/WaqAvi01cFRV3Kfuz/dvRsbH+VES9zdv3rz99vb9rx5uH4aui0yo8uHxx5e/W/TTkhvuKL/pHt4eHx7u9m4rKKrIXjUUDZOFwru4y0P69uH25Xz++9/9uK5lzAMFqkXWUi6XE1BMeZfyMaQdGTQrEUuCkthiYHcSq/NSfvr5qd+PlHa9xXnRUqqICKzfylc9jLmqiRptWw0AiBwAHXlZ7OPT/OHz+YePp/O0mnkMNA5dIKBqrgqm69x+/OnjdH7Z7/PxMNwcD33XIWJgyjnthiH1w24cU07uvizLWtZWq6oR0+a9lGLq+67v+77rUs4hRHeorU7ThM/P0zKLNgdHRiJABkQAcSTgwBT4C5lExB+f159/mj78dL6cFsYIZqWt7kZEIcUUWBEWMzGDzbI9MBKr4Vrd1VaBaOjgTQERckSOENhMrdW5Ue5iyinGtWLKTQ2dbnf7fd89fn5cqyoHpU5wFEyMTAyRgU2CFS/l8vh5mi6GkFIad7vcd62VUiuqOYVmIF+ZK7q51haA7m/v3K0269a6G/ddv0t9ZsKeux3tczeO+0M/7tXtdLk8n07P09wqxByRoKmIiClYDD1hYGayzSPLQBHMzZalXJtBEZcN/WzkyIQIUEuttSEhB66lqlU33UakZVlP04sZDP0Nha7rB3RVrYs0gVCa2Ndo/29/+xtttS3nWpcmQhz7YUw5pxg4BWBqTabzRVfRZnVtrcimwxU333a0kPK2vgMCUmROIWakAJvMxQNRzDnnvCdM7ux2xQ4QaDfuj8eH29s33bBDh1p0WWsVU6dtBlHLepkuUhZ0lzrP03NIche7HNPxcHM8HALH11RJOXfjMObUccjm8a47fnu8PwQeutCGPHzz3f23v7p/+83tzcM4DpERpAi1h8c7bC02PPbHu7u3t7d3wzHXFcCpLu2ip2XROhVs0Kc8pvHY761C4tzF/v54w8Snl+msl9KKqhJHouKwMhpAY2oYhNEReXNLWKv89OmUxuc83u4bLaWV0kproWvyFQFjW1VEvrngb+X15qRBtdnj4/TTzy8/fzwttaUcxiG5GyK46iZ8NJO1GHgTK01qbTL0Q5fSMHY559z1h8PxeHPMXXLzaZ7meV7XxUSZiIkDc4q57/PQD8Mw5JxDjG7QpIbATZu4yiKtNjBghi7wVXmAr6L/XzK/nk7z+WW2IttEZVuchQQxBY6MsM2D3MGv2xoIAVzNS1OpuhbgSoDmraFpRo8pdJkYabRQIMQYBWLI2QBezqfPj59uDylFHlNu+2NLHaQu9hkIWqtWxKV5q2WWOs8vT09N5HBzMw7jZktTS2mtsiNSLKW2rwIGAQkCYQqxizE8vDVHur97IApPp1MtFTnEbtwfH4bdjhhLXddlWpe5VFFlNAD3KupuIujuMaawLWWibWmNM7mhXzcfIAGiu4ErAhAguugGNqiEGFJKc110E7szoIPUdnl5UYMUhj6PMXWmrZwXac0Y5E8dL8Nvf/O9tlqXSy2rNI0h7va7ruuYEQgV8Pn5dHk8n54vT59Pp+dLKVXFHJyAgAgRGZlwW7oRERLz2Pe7EDNsmJxiysPx4e5wdzuMt4yRvKIhQkxxd9y/3e3viLp10XWZ11Lq0tQMCc28lrYuyzRdAFrfB9NS2wwMKR4Ox/7u5vZX33yXU75eSQjH/e3bh2+GbkypI84PabjNh32IHd/gcb/79Tf7N+9u93fjOKYYwJs0DRzf3b7dhZ4sjP3+9s27PI41+mlZn1Z+eixSTrXJUtSQIoTOQxDOmI7DTeDut9+8D8Q/xE8UAq6pihKCytKqM6aUANP2MaCYbehAE//w6YLxKY03twXUvKkW0f36xVTlVSq0TWAAzPx1iQq5cS12fpnOz2ctldwjAsF1J4+0ZqIAHpj6PqdEyFBFztNkbsz7wOOwG29ujw8PD7e3x5SimQ19t4xjWVczu7YbSMycUtxOipwSh4DuQcjdmoq4zaXUttRWY8SUet4cV7Yc5PZFcWkqy+WsdbrbhRrp5SSLqjNRBE5MDK2JbCOhzZ3sy9Fn0sxaFXc33D4JZ/QOIMS0G3Mc+7TPlxZWC9KAAte2/vDhhzI9lsunN/e3w7j77u1D6/eSs2IoyzydL/XlgtOKdZ1dy3R5Op+7lI7H4+3h4Nrm83ldJlMxZKawzvO6rF/uCxLHNBL3l1nHXX5496ub25tvv/l2Wdbpr//65TRRIOoIQoeUtM1SZm8FVDaPt6ZuLtvSlEYMQDEYA1AkZgR0N+LgAJw4ASIxalsWndVsAwJNFnNdtTh6HjpDxctFFMTQgCJSAPfazAEIYo79MNZazi9WWk3MRH8yUQ5v7m6lleXC65qkSE7dw5u7lHKp62Vezi+XDz9+/unHzx8/PL+8rPOiamjOGx60MRECBeZAlIgSYxdiv20jA95sL1M/7I9vHobdnmNyNVcDg8A9BiYaTOOyaG3tcpmWZW5zNVNmcLOytrWUtZSU8LhPEMM8e47h7ubuu2/f7PfjX/7Zn/d9f838xEPub8bDYb8f+13uhj2n5AjEKXXpMO6HfkwcUKRc1ouU9TKfn5fp5K31MUbO/ZByBgxS1aZSXqbl8+nS6mJmTinGlLt+HPZDf6A4/vq7Vk2+f/dAgCHvhsPNeVlKK64iRcriYBAz5Yg5UkB0J3MkJAcqFS5Te35egDISqXlRKVXs63P5Kz9Pv0oYN6INpch9H3djcoCqSgHBpNTrKsrNb+d6YyJtiurNZCxG7vq82w2H4/54czgcDiGwqjJzTqkNg7tdnRcQia6mLSEm5sCBtqSec+6HMS+rO61FpmlOkcYhhhB/cf74qrE0s7LMbV36Pm2EUgcA3HYcbQeJyiZAMn+9Zge4epy7mW0KLHAgSEw5RA59zkPXd4LoRFpoEyuIyHx5sZkHhiHn+9uH8XBTYr8iTrW1eZmensvTc2oVWillKctcWxuHYb8fh6GTWkxFawF3pgCtaWv2lROxu9XW5nWhyKnr7ne7h/v7u9vbJ3hR8WWpnDk0adaqrCCXspxbLWAWOTlwMzOHgJuokpmDAamDupO5I5ptq1ORIwemGMmjs3WtOJoAmlszN2cOedjt0zjuHVOpFrshhNgF8q4bu66ogbuqmKqKlNbWWpGD/onPAoQ+pwpWCFxVWssxD91IITw9n//D7378V//qb/7h9z88Pl/madVmahEgOG4L/7ZnI+aUc+5jN8TQBercuakKAHHoxvHu9n7YHSj1GNgMtam2hg45jcXCNNuyTurYpM3rXJalTcWkEoq5qpiYm3rs++Nxx6G18nw4DL/51a/+8X/0F+/fv/n19+/HYbgGP0Ak6gPf9Onm2O93x4DY5vMqqyn1RfOZAiyaUq36+PTy9Pj5+fGjazmM/TgMu75PuLa4esviVM6fXk6fpvUlRQ4pNkjU98PN7eHh4fjw7iakePNNc9sN0d3G+/ffzMtcSquLt6lOl8vzpZYGhIbu3tRcBJsCmGLgLg8x5NpsmQsxuXvVJuUX9tX2KNPrL9vANEdCSonvbvrf/uZhf8ifn6fn03S+zEtZawMzuHrqbb487gCeIqcU+pz3u2G/H/aH8XDY7ffjMPa5ywiAhNkTM3dXiz7cgp6Irr7lV2TPr80VUwyJMZngOuvpeUkZb276nHlD+bfw/yVgzDZ/p4AOEACBmcxNmi8iZlLbtg3h1dPwyie5rhOhyEibuTEaGsfY73b97hB47wq6rlaNfNtfANJE5qKeCXPMh2647dJOq+hymZ+fLo+fzj/9KPMFA7vI5XyW1mLg3dDvhj4FruuCAAweiBiJ3QPAV7tgobX6+PTh46cfHd8eDmNgY9DlfDo9PV/O8zyX4BzyMq9P7iz13Ja1lgrOKSZk1lUIYOxDShE5IUXHqAjXzTAGZmgWCAHZQoQhh9DlMd7Ukst8aa2KKSJ1w64f+9ubQ5fD+2/qvCzP51lrHckzgbRyWZamPp3PrUmtdV3XWht4KeufWN0HvLLIgQhDIERY1jqX6W///vf/5m/+7l//63//04dPpYIDRU5bEkgpbOVgl7sudjnlFHPImTkSBFFfaxNwjGEYd4fbu9wNzVFVaq3bQg43Y06IPs+i2pp6k1altFJlqSAFsMJGEiSOKYUYVBt4IbShi/e3x2/evf3u22/ePtylX2awDqqgTVt1aQRGHDxTAytlbZdCJOt8wkClystpfn58/vz5Z23lMgy7oR/7/nDYF7nNfW9Ol9NpXS6mJfV96GKgMXQDMTfVyzLH5JEDu2tT0ebmXQxjCgFThCxLfOlwmVdxb2bNuDRfKi7NS6sUQs45xYy4STzMTKVVkfqFsARwFVbj6+/RX9F/tJT47m6XujDs+uEpffgI/qSXea3Nru4sXxT2DogYAsUUYo4xxZzTMPRD33c5b/QhBwwRQnCiq8MHMnMIiGiqV86lGV29/QiApNla2jyXaS7z2gyoNm1im7Ffa/q1URxRGIZD1x/VwYyYIUYCRVEFc9tslF5XPCKSw9VPQMQRna9lQjQgA3WKFDNgWhf3RU7Py2LowyFwyClZN6Sh7vq+7w8hDuqhVbcqPq96uej54svqpYiyqUithLAfh8N+TJHBVFoFcIoBKaAZblDLV4CyikyX5/PpcTcOJi0zs9vp6fPp6TN57SIgNJIV2tKA5ulS16KyCWIgMvcZA8Gu4xQDEClgUXhdAA0bXuKABq5m4BAIMnPyxK5e2BUBADjyMI6Hm93xbuwzuXSXc9WfZ1OTJuaI5AC11lYbLotIq7WKqGlZ1/onaP9mUAkAOYcuRlX8408ffveHn/9f//Vf/Yff/fF8Xkolg0gUgSKFnIe8OxxuHx7ubu9vb27HbgzE6CAmqmIi6taAFFmBiTnFCIju2tp6uZykFL76T5MIzHNdVxE1UVV/1QBvG4LJCWPK3bDbxSAfP/7senZdGQ85cpeYya/7rq7lpbdWp8tkKqXK0mh/2I9DFwHO58tlXZdpCiEYAlMIuUtdzt1wLvLjT88mjzHFm7u7b2veH5NbnV6KiWaCIVE3ZOxuFVNdpw+X04cf/kjIRAkAXGtpdaotJXx/2789pNt9wOC7RlMkaSqOAnFp9FzotKiDO3GMMeWYE4W4Ld4V0SryC1sRXm3P4GoMTsREzABQpZo5B9rvh2Ecd2MXAyPiUlpb2jZ0dwMDdL3u6jbYhrNqbgSQQswpx5CI2R0QnUMgohgihYB4Zf87gDZ1W92Lim0LvwjZpJ3O0+PT8+PLy3mexN2RxLxWFZVaaql1a2u3S0m5//bbv/j2m58+f35alzUGY5aoTURFjcEZzH1boU2ObI7iLmJNFMACEyAYogE6YFBvItOyarG6ls/PTxbS/ruHtE/HdDgMPR2Ou9wdb98Q5fN5XksjclBjwERhzH1R0bZqq5Gw79Kbu+PtcUdgrayiDQk9oDtdLauv2ufXZ8xNy9rmWdYVxPrQk+Hnn384PX++2XkXUlkaY+3Npdp8aUupBJHYGCSleHsYu0gZBFyb1asj40afYoaAaiDiKtaqVgBNbg4bPOkmBJ5j5K7nYRyGfe4PnKKUSR2J0LQ9vZwuz4+np8e5rEqxOtQqZrqVRUXqWuqfoP1rWU2buxFziCyLvpxOP/704R9+/8OPP30MIcc0pLzr8pBz7vq+H/v98Xj38Ob25v54OPa5j7RZ2YqZmJZqsjRcBItQE1AVM1HYjoYmUlWs1roWWVddF1lW0VdfaMSwNauETGwIIeacuuzWzs8vJs9DJiZPDIGAXMH1KwDjyvhD5G2a2sQdNiFzdjNHEgPkbY0mhhSH3V4ElsVqLa0ar3apxJWvXqwUAGnbe9vHoI7LMl3Op7W2EOLxcBsDt3k+XS4fzpc+ww3ujXrFHhxardrUN/EfIAPw695TJGTmwJxS6LoABNy8aflqNL7JJ0xVAfWL3EcAtkYO3Ckwh5BTIITWtFZ5Ps1LkbJtJwRwBzVQ8VdNlonaJsJNMaaYrjt/3V+dvIhDDDEhX/d8mqmCqlgtVZuGjgi8SZum+fHx8fPj58t8adpoIzw6NDVpKpu14VfpJcX49s3b9+++1eJnPYE15hQTg2OprayyrlXNHHnTuhmwAhmAgporuCuwQEInQ/WIxYGqLGZatHiIaczjYby75cyRIItljn03RuZaWykroK7r8vL0Mp3Oda2ttLau6JIjH4bu9jDuhgyu0oq7ArL55lNuYqaq7r9UMTnFb949/Pmvv3n3/uHdw27sibGCz0TL0BmDe1V0YXB1NAUz4hiZIyISQQqUI0d3V9sKH3JADIFo81ZT83WVbQEbOJpaU6vLXNeplgJgMcYYKaXQxRBDIGJ1VmcAdodS67yWaS2lVoiogKLiZshsZrVKrX+a+cuybltLt+1sBi4qqoLoMXLX5d3+cHfz5nC83e92/din3KXcpW7gwOs8a219DLshHw9dl3ugYVrLh8d5eZG6wlLMpAAIBwP3nKKrLPN0uSyn0zxf6lpMN63gtg8wQGAI0XMyIjPdjCI3rsMKWglTIGB0dENtoPLFRRIROYRx3L19+2a3v6HQhxBr0xDo7uFhW7zGjLlLanqeprW0/fGY0tANh3Vt6tIP+93uOPS7xB5dpjyc1vnzaV38/H5cCLgu52U6L+K7Y7p5d7fr+vnpeRU9f/o8r8u8kxPM58e0Kr0s1gxDCEjgoFVhbmERV3NmAHciiInHXc5dqq0BWO7iF26Mm7XaylpCQg5Xviy+ttMIyMpBTVnd8bAb13t5Pi+l6sfnSxOJMTqhmFVBbk7VGVWymQESxRhDYHeXJpsN6UbtSflK0du2DIhIKWVe5ukyuVkOUdCn8/Tx44cff/rh06cPpa4UMKSY+wS4bXu5ikLgq53PMfDtcXz/sPfL7tlqLTZ0+d37NymleVpOp+nx+TyXakgKLEDIOfQDpwSBRNs0z2vVVbkBKTqiFld1R/A4dvuHm93tw/2vfnV8uB93XR9Cb05irYqUUss0zdNpPj0+P338+Hm5XIIqaoO2DpnHob8Zx12Xu0BmYmrI2zIUU1cAEpMmVb6qYg6H3X/6n/53fv3t8ea4H4Y+piJS794ETvnl+TTL2tQwuKADY8ixY+7ynjlufmetFjKGyABh25hO1pgsYcohpi6qGao1R6AYEExlrsvl9FLWC5iEQJgoeUqkiRrB6p4M0SAiJIJIIVBkZAJkIAocY+pMVVtZm6hW1fqnwh7bTGURkYhDCJBTGro4dHE3pN3Y3d7u3r29ub+/PxyP/dBxzOawVitlXtaaU9rdHscuH/c8DhGI+aTPT26lTi82LWbeiLXvIJAxIDto07rWda1lVXVCDMSBmYmJgjNDSJ6zb8HvpgCNGccxo/VdwrCRCsDQv14D/5oz3VSlttXE0Cl4TYnHwxBCVDNABiRznZd1WWug4IAxJ+Rgbil3hA6g2xJuIGrq56kUxW54isTzdG6tQsjdON6+udsPI7mny0xdh1XQrRWZq59reBFS4uRM6KoqYlWl+kbevpLgN1UYE8aIXRe/Dn4z23CaBMS/gGe43blN7wCg7kDEOYXDrn+4OyxLeZmWUtvmp6qOYlAFqBhaq50gUggxhICEIuIqtW0e+25uXe48miKYg4qUpczzPE2XaZrAPVEws6fPnz9++vnl5WldZwCLkVOOKYcvSwc2/v/Xd8RUyvmlnZ+TlgEtEgzMh5Ry10UxyNJyISBBUuDmyKnrD7s8jmnIYvp8ulzmMhUvBu3qL1bdzZFo3B3ePNy+eXfz9tv98Tj2sUPItdlWAomYiNT1fHp5fPz06dOndVoyQkJIKNT1Q5d2Q+67yAFEqzlFTkQMV3Gnm/vm0PzlWjiE3WF/c39zu9u56/Pz0zRPa621AYUxD0MHYJSUowHGmELAvh+Z4+tWw1bcMSQCVLxav7B7oBQ2dTVwYAYGIHet6zKty/l8fql1CeTBgjFg5FS7rmaVxEQx59gbhuwUgbZlFFkVlIhD6PsBwcu6EK+GHFP/p04+vP1TyMwx9Uh2d+Nv7o8PNz20eX/o7+/692+G+/vheNvl3AGGy1yn88v0fFnm5bjf7b89PNymww5zUjWZoaJUmZeXD8tpEs6ce4qIFBS0gQiogYIpmANzYs4hphACBSJ2QKEgwErMzOSmZpJSvrt5xzZquaRIhI7ovxBgr2HvqnK5nNb1QjFS7ANw11qXQnfsIUYR5xjHcWemTy8v67rCtp0oRKLAxIi0Ls+EVftQ2qVIKa3OS53XZv5jDFyXiULaHfd3bx/uHh76rpvnpbs53L3/hst5t5eA0IQLh0ZBOUBgMF0LtNpUrz0AA8lG3KpeFpFWgZQD5i5+CSF3r62VUoBDcN+8Q4gDXkvyX2iNm4A2R364262lfno+LaUauLgjsQK25qCi1Xe9MIWUMgd28NpKUy2liSq4q3ZD7jiwK4lZq3WZ5+l8vpwvy7yoitZW1uXjh58+PT6WuhBTJETmnEMM2w8FzGR2lfx+sSFfp/l3//pf/4e/+pcMjk5s4FRPn5+ZQyllXqs1Q2ekgMjkToyRfehofxydOMQu5SXMda7WnNQ3a1k3hvHmcPur7+/evB2O9zFl1bas8/pykvNlmWapBVGktVaWui6lLKUuigCRc8epj92Quj7FREgutRlipIi0bVB7FbRe9U7XHLOu9Xc/fPjDP/zw/vbeRH74ww9Pz6eq0I/H99/89ubtTWewtraus9Q1cGIOwzAQR2mtlrK0qm4EkTEoKqAAGMKG7JKKqyFAAjKwIq1Mp0/z5XldVnUNgcmtiDQ1J0YiSmFM/bjfY+xeXp51ky0g5dwD0CotMR13Q0yptXEuLU22u3n7ZQEJAIQUooObMxET5cCWk3Qp5kg5Qhc9szDM3p7LtGqNBuF0KU+fn+apMlIXx93Au4FztMBA6IzmtdTpMj2dLrN1+xGRF68VFilzXcu6iDYBB+bIMYXQxRRDiBgI2RwINlMTcERCUncb+vjd+/eJlpdPPw9DF8LXlP7XMLhurfVaq0uDpsFJSpNAYlWZprU58dAPiLSW0loRqe5OHJECUowxT/O024/746B1ra2IqpmL2ul8ISJrtR95H0LKiQMBgZJD5H4YYvKuK8HUAKpRAVLDzWlnNWpKpoboxBRi3B8Ox+PtOOwZYD6fDFsa8rb+6Ovr+WU51i8a7+vmE6DNVNfNDcwZYT90d8fd3c1uqe0816YKSCZg5gLeSNdVRFxE12W9XCZzb6K1NFF1t9ZKikHMKARzr6Wu07RO0zJNy7wsa3lsz8t8Ob18nufJzInI1BgxhZBj4E30SbQ5QNLX++1aO396PH34OA5DSB0BtybnlwsgNZWmoIYbKuJAG+7dVGurtVbguNn1BtLIhM4KwZkgMg1hd3e7u38z3NzF3IO5lAaX1S9LvczrNKm1FNHcVFWbiLSq1RBSiiHnbsjDkLouUAAFbVKNOAM4kjm4O6O7XjP/l/KyVfnw4fn3v//kJZL746fp8el8Ke3mPn/76/3u5j2r+jKVJkQy9Bs3pAMkcG+tOaI7mCEQqBm4AtiWrpFZHdTRIbo3k1bKZbo8LdOLGgLSZsPczGBd6fwCYAKmlB4O33AePA4WsuGGITApo8mWRgg8Ru4pWMjj/oa+du/NKZnDa0kc1VTEW9FWS13nGunCDr68PPG2s8EwrsVfTjXn3a+/+9W7N7e7MYcAZqKKTJGBpJb1cl4vz7VAGqJUPC2fy/JpevoktYW4c++Z+q7vOHTMmUJgYgyEpIaGiA6uqg4K1txr3/fff//tmPWniEPfhRg3w4ivnfsRsevSbr9jDoYohtoMHA0BHK2088t5FQkhpZRzjOAq67yWtVQr4qsih7zbDXd3N9+8u0sEpRR3izEggyNXsbqKcTvUJmWez881hnk+l7qYCSGkyEHMvNXWinIDlsjb3ptNGu/gEbAfxu+///6bb96NQ1qmy6ePL0upxzdZheCVRk5EMafcDzHnEBNuk/urKhfBNwHw1fnCzdAhMR/G/ps391VtWT/NS1EFJA6IjB7Jl6LzXE4vl08fP9dSDEAddNu5pTrP2cx3u9oPAyG2tbR5afNUl3mey+PT6fPj47pMESuhMycgWpYSzO8OoY8RSegq8GMJkTl8KU4IMWKIGBGzQ2gA3nRpiwE6kCMbBaWgQOqoCKLW5nVq+nRekYMaN8WqpkZGCGgOFGIc9zeH43037ImjtuJr9dMJpxmLuICK6uZtjNuWGDRX9QYMEELu8zD2w5BTYkAT1aJijh1QAHIxBANQEam1ibQvG4dF7OXT8unHS8Zp16WcurHPp8tF2hwjpo7WuYILIXQp74YxxqhATVTBbJOiOYILSNNaTCuTYyCOkWMUMTUyDKq1zJf58jSvL03WwEPgGJmY0QDA9XI5Lev8dD5NFdPN95SOyr1z78QG1lyaqyFWtefTKQXmgBSH3O37seevzuXAHNDdHNdVL/PzfFnX5fL8MjcBxLBZrNWytGqtVTEwzFVonj3w0HV93w8AVMXIgJ0Sc20wT/N0eV6Wx9pYW99Al+nny8sfT59/MrFxvE/54f/P3p/0WLJtaWLY6vbeZnYa76K7976X72VTxWJTSIASh4KGEjQRoKF+giDoJwkgp4QE6AdoJnFAUCIpqkQyqyqVzJfv3SbCu9OY2W7WWhrsczzipkRAc5ZFwG9cdz/ux5q192q+RuLAIbEkpNg1orrrW+c2uZtbAwf0iqBDpIeHm7tdAM2RZdpsLorR33QvEJGYQghpGIG4Vq/U1IEQQhrYbDMB1YZEUUIMgcCEXJgRS7OquTZdCX2IUraDJBGAJOIRoHlTr1VLNczlPC8vr4cvv3wJKS7LauYiktBFALS2mvNS10oVqAUhIrduTKwSZJqm9x/e/8Vf/OVvf/tDDPT4+cvPP7/Miy4zLLN9s8cgs3ShPWLpDXi4QmDMDdQvtgVmrkqIzDKO8f2722o+L9XxmKurQVfWRINc9Hicn59epxjymhXcHNS8tVZKkSDH47zfH2/2uxSDNy3rejrNL6/nnz4ffv789NPnz9Dyu9s4DcHActHDaY0xgGNghov1OL4d3yZlBEBdoA5YwbWLzQB20UgHVqAG0AAMyRysOWhd1oYkTsFRDFCRmjswSUyb/e2Hj59uH+6HzY4J61psXvy8wLxSbW6KYEIQhJoQY5+2QCCMgaYhbadpO03TOIQg5lqa1qYg0gUsmpm7NTRS+0c7PwIGjAETYxJJYVRteYgvhFZaXvNc8mqtBKaY4u1+zyEstdmSkcjAqzZrqtrIoWpFsO4wh8yOVMxzs1ZyXU/L/DrPr+s6qyozMHMUFiEgqFpPy1paU3hVmj6ez9uwH+IwTZs6DC1KLcAE3XWeiPFCDDMiF/JvWrEgiARmpvD8fPybv/n7x8dXBDifD01TGm/TkOIYhoGJPbSiTgajVDawOOyIxtr4ODcllRREQmI5zPp8OL4cH5fyVExqHVqrh5c/np7/cD5+dgOw6sD78SGNkTgCijkYdJEINW9uzb1hN5BFI7IQcBzj7e3O7bvA4eb2Ng0jEP1aOeKCLOtsJwYS5OwYgkz7fYpp/77TVVFbW5cFXIchONiyluNpfno95FwIYRdlcBgcQxoCAmBpXtZcay2uWnJ7eTkAsapttzsSCZI2E49YiE9Vz3mdl/O8ZqhOEiJyd3dHRho24/t3737/+9//s3/2z37/+z8Top/2Pz4/navSy3w8HHJr36xlnWDbYa7dW8Ev1Pm+1PWkDnryD2DeQpSHuxsOEYi3m+dfvryclqJOAIDgtbWXl8OXFIYQ1qUUrc1MHXIpp9MJALbb7e3N7v39zW4zRZGmfjiXH78c/9Xf/fjjz58Px9dNopvtnTnOa3k5Lp+fjptxaJ/uCAmYAC5rzcX59StB0d2ta7uhoyE4EjADkCE7Xvb86mB0kSplol5zG5AZdsVoR85OLHGzv334+On3v//9/vam1rouq5fmuVptXpu2CtZEMAiNg6BJYgjoIwJz2A3Tu83N/Xa332yHOArJ0nIt0NSFISJG7GQKMO6Y4p5jXU4mxvDx3bv5+9O7j5+GyG0lgHy73LiE15eX4tRUgXAIcbvZ7G+2JAGX3By4ZDWbl/N6PpE3JuI4hTgiBIVojqa2rHZecs3nen7Kpy/L+bCu1QFTcCIIIkMSCTgXOJyOp/N5LTWMT2U+hpuHu02Smx0fd7RMkFdRc+IQ0jBuhbm1tbm3umg+/8qllwi1Qan6+nr+7/7wy08/PQYJAFpb4LDjmEKSMLAIBmsKYjBRpWpKssmNjuemlE8FOSpiJdWf//TLH3/66cvLL0s5GsaSB4SS58ean92O6KhNwO5iwnEMQMGcmpqbgZt7Q1d3RVfswkDeECuhCuM4DQD3gcMwjSTivVr55jCF1ryUKgYMAt3W07EhReYoF9W64helaQ5DCBySxTSFNJRamWgTw+1mjIw5Y+eeq1qtpbXapXBqqcu8nE9LCsPdOMVxNOLR172upwXQK2pmI3MB67N5DCLTmN4/7P/yzz791Z99+u79zd1+C4D5dv/+3f3r4VgdgnwVjehVj6qiKgB1I6W3ZeGKufWLS04/dzBGH4ZwR+yAQwwp8vG8VENzQGuRwcGO8/z4fDiclzXn5obEpZTXw6G1Ngyvu8309GWz3WxiSs3pOOvPj69/98efX14PBDqlBMTN4LSsr8f59XA28znX0jRQb0LaFTrwqylMXw66zasCGqAhGZAha9/2O5cVAAAJiJy6lL0DWcf8IZsISZxubj589+m7779/9/AwpPD6Unxd6ulcTidYVuw+XKhRUAISKHoV9DHwzTh4jHf73f1+f7OZNkNMoT/8rs0QOJBEokDYAGpXv4cr7PYtWoRvbjb39ze77SYIVVrV1vtWV4V5Pi/VkXAY0+4mjUNMQwSSnmwSM7EAsKrVOhNRlIFQnEen0YBNLde25rWuh7w8r/NrXuZWjYT9ssp3KRYveT2fTsu8ggRiBm+Muk0MYzyHECVGEWVycEYXImFBiNZrmPJrPn8X51qWejiuz4f8+JqZVBgC8ThG5JFClBRiZEdwCIYjZIqtmvPLWRvMw2oSsiHXUubDyy9/+sO//tu//fL0UzOVMOYc0QrYOUqVsVs31BDaMPIwBQNuDQ0agpJ10I4iGXYpMDX0YpqtZbdGRNM0BY5darphl717I12AKpastc7MFCS6w5pboQzk8yJdoLQ1K7WuuTLRUuo4DhICS9zfP4QQN5vNZogTY8vLl8cvdc5LsWUpy7qa2hSGGKIwJ5Exxtvt9P3Dzd1+itFDg3AOvyy4DT4FRE4Fo3MwYFcYx+HDh7u/+t13f/1Pf/ir39xscNHTZyexOu8m/vT+Jk7jhw8fYoxvu2UudV3XCCjiLtwBdg7QT1m7LIdD77HjpZOkoFWY3t1uN1O8v90sea1m3WWglprXpbr+8now82XJBpCGpNqOh3MplfD8WV7/IQaJETkVg/PSTvN6Ph0Dw/v73d3dVmKqqqd5PZzmZc0s/Hpeb5eyZwmEcNFw6z5DX+9LRxyBITiqQ4Me6uhIhtQMFFwB3REdzYDcAMgRgAlJjKUAUQib/f7T9x//6q/+4uOHdylQXZb1eJifn45fHtv5zK0GsMAo3K+J5uWUlxOBboYYbvaB6Ha/udlvpimmgCIOYNqqm0WJQ0iROAA2InPo4iStttaaXZGXRJg2HCdEdkAQiZvNHoO8zvn5XNf5NTARbOlmLwIIpt5aq2aKRCGmabrx5utsBm44GE0ke+IOTShNc2uztrmWeT6fa14JSYipk6NKKVVbLa/Hw5cvj0bx02+/e//+UxwikQWEQObmTQGZkTEvSymlNQhpjCG48prruv6KPCbdfqE1UxcebtMWhTGgCuQ0UEyTxMghkJACqlFpnBuaRzU8La3qEtaKiE19Ph9fvvz05Zc//vL552U9hChO2NZXQR0TUZoYRFtbVgQoZkU1q1lTsFbcFMAIGkBBqAjVoZgVs1n1UHNyrQSAxEzk7mbafr3zE/EwTJvNDUvvnrKZkzQiGqeREPKy5pJzrqW21oyZaEZt7SIOL5ziAESMEIbQ3Jfa5tyWXLsEAjMNSabESXxLusW2Y70f6MOGpqFJMzPTCT/dBLcx40Zl8piQAiJvpvHd+9vf/fb+h4fpJqjNj0s9O0co+XZq8BA2k+xvxsjfzPlr6UwsBMQurHWV4XMHtWbmeOHwUIf0mTl5Zeq6/DEFLC02bdrMGqw5H2c8z/k859O5HI+LOUxTIvSLsx0gFoWlgmSntRqU0lSVyTdTut1vNpvRAHNp81rWXJpqLu35uOwOi8g4AZtZ01Zbu+r8XI6r+xAAgwE0QEXocs6G0EGadtEUu1AYofvFkoCISQSWtNu/++7Tdz98/+7dw3Yc83JaDq/n58eXX376/McfdVk2Ke7GFKZBhIiw1HY4H5bzGdA3Y9oJJeHd1Pt8EpgQoTWrtZhaSCmFyHBBUFwsq820Nm3tTYzY3Zu1ta46HyPHRB5C3EaqgF9eX5e5NOFpTMwcgjhYbTXnuYPzYgzbzY6AiLy01jCosWNwjM2htlLzXNej5bPXDL25ESWFEJjArJRa63qez8+vh5fXw7DZpzhMmw2H4OCqtdVSO2rLQd2bNgASVwBAYmQAQP/VPAkETN0NAYfNzaffDpuHOgbFdlpPP6OXaRpSisSk7rnpvNbX47xmAh8JWbWVUpncTFuu5+PT45c/vr78nPMJ3MiBVD2fw8A3N/tp3AXR8zL//PNz1Xw+vZQ2qLE5ISjQZbVGr+QFvIAupksth7w+LbN4q2DWmgK7ECmgk9k3q7JIvH94/7s/+/PNfhtEmmqudclZmPa7nWl9/PL58HoAXqlUU0NwRivL6bycl5yX0twxxHR3u/+zT++D8NPTy+FwmuelqUuIY+TdJPsIW6w7nDdNNiVNth3BJm8Bzk7ZRvwnn3YfbqDxBoet7HZp2ozDmIYUx7iZhmTL+vx5JeYQQxpI4H5cJqpbtjTUQG+7pddac8kSIpMgqIGqmSOQEAKodplXJAFEt84CAABVQqutIoGBIyi6EgAijjGGuBXh83w4z+X5Ndem01JiRBEQkSBRWC6W3R1x6ZHAA+M0hJvtEIRKqacl59LUjQhU7fH1HGMIgdwCotXa5pzXkr/NyErzpTk1A3JHUuqZ/9UOpEu09qBzBEQjdGKU6Bw9CKQYh83tx49/9hd/+enjpyBxOa/z6+vLly8vn3/55U9/+Lt/9beW8/efPgR+2O4HimJa5lI+v7yWdd0Nw2aagmtiioGZJbAQsjasRUuuqjBMFIOYgzZzN3JwQ1ezWrXUNyZcU309nX55ekI8j2l4N02bKcTEKRB4sbpUi2YQ4hjiYK7rOp9Pr/NSJYQoIeymFFOM6Tgvh/Naa+to7Opcmq/zMZ+eoc6oOg4jjykFCkzsrGYl5+Nyenp5fTme5mXlNJo1BCcidV/m9XCe55Jrq11/RIFCCNNmSuOEzNY8tRijfOtBIOANQJE8DPHm3W7rfLdx1sP52Vo+xzQwCzG0pr7k4yk/Pz2fzxbDTjgAOnoDb9pKW/MyP7+8/LSsr66ZENEc0RhsjOHdw+3t7TAM+Hp4PZ3L4Wgln5q+OAggEXdfDSRQ9+KWwYvrom2u+XWev5yP6Xx8mU8nNwwhXMwMiMza25nEKO/e3dX8abfbIeK8zOd5EWEkmsbJTPM2A9I41VqrVgU3Qaw1k6CDL7nWUpu2FHhZNp6iWgNyCReeehAaE98kfCDYRBMoQ1tSO8fmgavo3NoaoN0PMgmCEI8cb8O0T7vdEFJ0IoDm7VjL0cCJxccUBx4HZ7RVldoOrjByc6iqpWlsxnSR2KuqjtDxHZ0GF0TAsbUusO2X2h8cyYmAGA2slqoNUImYQqIY2MGbWTPI1QGrOY0kKXJKEmMgIQ7MwoTgZuhOCF3MDwDW2pZSqzoRb6cRSXIpz4fzNHApEVxLXc+n4913c23XcwEo5qs6KaBdNnynLi35tqMC9AEmGrjbpUsqjsEoDOP2/uOHT7/94dN3n262u3Kc1+Nhfnk5Pj8fnp9eH59enh+91pvdVPbbLigwr8vL8fj4cjCtm5QkSgIK3RiLiFgApRkUtdrUgESk+4t1D5K+knakL3xDtTT3JdfzkpFMzaO7Y9oggxkjEGEzqEaGwVDU1mWZHz//fDwv0zSlYRPDljmwTECgurqVWmupDRlLaet8LvORrRJYkBgCjQEDIZqvOeeyns7z4TSf5lya1WbLeVnnxUzNYG0tq17s05hCiBLDNG3eP7wfx60R1aabbX64v+338RL8Dg1REZsEGkaSNP7247jhcXlpNZ972ulu61qeX8+n18Pp5ZfHL/OQdkxBrblXt6KtaMmtnks7qmViIBT3ho5BZLcZPrx/9+Hj3TSFp6fHz58POc/mxdqZOCASgoGbVm9WXBfXBT27ZbNc8mGdn46v6fMvf7q72cUwjtNGhIQQ5GKD0M8kBHn/4QbsHITLWvK8eDnqPKvRsSlxSGkchrHLV6xLBodpHIlgLcvhcPj85XGeFyQah3i3GxnBXUUwjek85+NxAddAsBvwfYqTSCWK1risVJywaJ3n87ycV1tNFFlrIA2LpVhSPEcMBmJAzdA6mhZJa7DC0LgVPzxX1s2HqxssuFez0qyoeWlgrk2rNndH7nR7iTFKFCApTVsrram7vYkAMQEHMtd5XVtWVAwhbHaxWjNwEhqmhMSdLtR92ULEccQ4UEohxQgAy1LyWnOpTZ3DAAhrs9oMEMZhuBsnBzwvyzKff360xxfuvffz+bj78JpLe1vIMvjqLt6D3zs5uGO4ALEzD03BQbtNFLg7sAMYkVvYTje//f1f/tnvvn+43Xup8+H58PiYz8fT4Xh8PSzLgoDIrK2VkrW11fXp+enLly/PLwdhqDfdkcbVHQGZ0FmcOLtlheZIzBeM6XXO3IXNsWPk+auqCnSlMWQOgwE+n45LPt2V5OBDCMOAh0yr0dJwqYDo5/Ppj3/4w9Pz43Y37fe3u/174t05D2vWWtVRS57XIIZDWde8zC0vQL2U61q9HBiIrOq61vU8r7loU3CMpcLz8+vz01NdV9+6AbmEOA7TZiIvNA7jdntze/f+4cNm2gChmtXafvtnPwxD+mbn7wZh1DpbUW3VsqOhDcETEjIjMYALeVkpYNN8WE8vUDNTaK2oFbNirWgr7tmwELuwAJi1iszjFG5ut+/e3X/48H6aIhM/PPx0nuG8qtoZKKCjaxezqtpWq7PbSljRK3hr9aR1Xs6Hz59/ur+9vb//MKQE1icCX3GXAMBMu5uh5AGakvkYfKV2rHNea15mlMShL4i9RlJmIQnDEIftNEybmMZcqwSJzJHcakFiCTGUCng6nbNqdTPyLmrOq2FpVnKuqxkWb7mUlouVYmQQQaWtUoQWA1m9sbkYvFW65ohauKzMmXKlfKKY1q9GFw61aa5Ncm3cTRtaVesa2yIcE5GBOrjammsttbYG7khdi9uIgJXU2nlZW2lkGLRhsLVpcyPGNDAitI46sy7aiywUhIKQEHW2n5qXZkieFBCxKBSDqk5IIQQDgLPNtay1qXle67LkNc+/e5prs+vOjxU4AzswAjp2k4BOrgS/qhWatW4AgMxCNAQcRuKBIcn7XXy/jftAsC7r8XR6/HJ8eqzLMp9Oy3muuSAAMbu7qpZSzNrj09Pjl8fj4TCmWEvRNhi7ExmiEzqRIhbVVbUBRmYREWFwAPg6CYNuovlNnmzupWquCmzNrZyPiUBwMwxpHMeKMLs5JScxR9O2LPPr68vjly85T7WU1jwOtfmtWa/tvJRMy1mtleVU1rnVKlEuJA43V1Bws5ZrPi/LvOaq7ihARByZY28DC1OIMQ5pGKImsZUZcTNN2812GIdhSMzUrSj32418I3gtJIANiLTk1y8/vtRmeNzebTj5GgXiOMaYYgjoilbJc8AScGVgMibPbtWtolckRW/EioTC2O2lMIXdfnx4uLm7v729vR2G2Jq+e/f+dNT2mJd1RhA3V8utrbkurczWFvQiAtJtI6wwutb85ZefHm7vb2/uYpTQW3qERF+lIokgRUoJ1DWJ3mxTW+UFc1lezosVBUOB7kSDyCRxGLfb/Xa7mbaTiGxvbm9j2Gy2gajlNZ/PIInCLHnNRQ2ec2nrSueIZ/HmcDRci2+WkhYdpaK15pCdVgUyiAEQAFqzpWSvBUENunkAXTniGlAJ68FXS6i3AfjtKXO3UtqyZsQYgoKZm/efAIaOxIZmXmpz92XJtdTesRNBpEt/0FybtVqaamMU0HaabW3a1IgwRkBERjI1bV4qqJEaa+MCUNZazdeiuVhpJMLNCInUpRmtxdyVwuKAubZ1qWtb19zy2nKp1ex0rt9CY5qF6pFAmMQZgbij0xHQ3Ju7mrlr9/2KTNNA7/b0m3u+2QonTrs6zZ/zn/JZ8XxeTr98Xg6HWks+n9q6WlMEYEQSdvRlXdd1fvzy+PT4tOSZTddlKcMQhwjCQOyIjl5N197KRSRmERImV3foHuadnEgIAiBvPAU1n+f1eDw3dXCbT6eRaTukIU3baUMDH73GYUpxEKI555xXVW3N57k5LM2epo0PowilEKiaN63rcmr5VJaXWlc3RYiEBKZWalGt3prVl9PxcDovpQJ1ERkYp93Hj999+vT9drMZUgRi17EeJDMSmJu3WudlRsKclyEEloBIrf5axguQELvDzXp+/fn15aiH+DTyKDYNMm134zgNw1BbO7y+rsuJoUZRhgyOoKtrvWByOlgTna74LndF8pR4nLoI9JBSHIZpu9mN4zPjyXQBQHdtuta21rZoy2iFyaLEGISJ3WQ7pN1um2JkpmGI0zQMKcTA3W7y7UyIKMU0pJRLA2GeNnWXd9shl0EEcoNidJrXp+enNZfAEoe03Ry2281muxnHUWIcpkmElbiseVnyecnzsq7ruqy5lAKt1Uq50FzUUAsamJ2rnjOcxMQ9qy8Gr9XJIAaK6mLmtcxVa2vL2kxNhBi5F71KwAJDRJfJZMBvfNTcoTXLVSU0R3QzMLhK9Lh3l1dQ1Wpmy5pbrWCGiKbUcbUOjuDNau6OZozmllcotbulA1yfcTOvZrC0GCsgtWYsqgpVrVQtpeXSmKwZM0spdVltKdZqzerdjyiXsmYtRUvW2p309Cvf0tzX5udiWlVYsU/xGEKgMUYObARNW10XNyWSzRTubtLvPm7++e9uPt2NQXCp68/Hv3/8HM8tnLOt81xz1lpdGyNEoRiECVlITU+n0/n4enh5XU5n84YpgirYlT/DDESO0EzXXNZczRFZOhmpuwa+iai6gf+q5AczW9d1mWdmEiYiIg5OATkOw4gg01rDMAwxEnqeT3k+AVBMm3GzCzG0pq2saVM5JsKY+8BWi5Zq5UTQUFAYBR28gdbaamt5Kfn1PK+lqQOyiCQh2uy2N3c3m+0EbmY1xdhSOF6hFto0r6sjtVbzmsZOvQyplGrfnI90ewghZnDLp8PzL+fH8iO2JDYOcbffT9NmGAZ3O8/z8/Org6XEXX1GLTct5gpgSHgRngHs4twXGBoaoBHBxeYRWYSJwXyt9dWLuddmxawCVGELAcaU9pvdOI4hxA5auNnv33/89P33379793Bzs00xigjRxfLsEvzIQ9yOcV9ZiSEE2Rs9vM+b/UNMe8d4rvYPf/rp5TS/Pr54q4HpPD6/DklEJEZJMaY0jqNwdMeS6+l0nJe55Hye59N8GsBVWVVzBSLCyITazM6ZWUkAV/Wj6s9FUTExpEDduvC0ltdjfnw+r1mJIxAboDk08O3Ev3lImx1pOHtd4Iq+cgdT78aJBtDMQR26VZZBa9a0lQLC6u6lVNMCbkSujQE6acTBQb1VrYDuEZCpGdSGpmjaG92tlq7366Vq0zav67CJEtnMTb1WX9d6Pq+mHuMxhEhETXVZdck1v55VDdEQEJ3QSIjIyV1TDG/ZcnM75uVlOY/CQSsQEBGHuN/ttptpf7uTKdSWD4+PWsogYb8dPryb/tnv7/6Dv/7+dx9T8OMf//T09J/+dPgHfdG7BSeKAQmZPApOU7Q2dgU0Fmy1vp5Ox5eXfDx7rUFo4DBICCJ8kZNlYgYE05bXXHLhEBC5D+7NmmpzA+vNyOu1/jq5UCvrUtYFxzSkaTfcDGkYN1tOYwjBQaaRwzjEFNDX+fVpOb6KyO3D+4ePvxHm48vPiWE/8DhJBpmrnfNS1mp6Bl8xErokNkEFq6oltzwvy+G0nJZihiwJOEochiHd3GzTyA75fHph5t3NQ2R2c23aTEvN9YyhaC25xLRKCGlKky+/FokVACaUIGGMcT8NLyksp3WpeYU2L3nOGuMsEgAsl7zOS9NGBM3UoJpX86qmiN5ZyFcf88t6iQTMKBfCficOdnl31Tq3cnJQBAVswi6BUozjkPab7f3N/Xa7S3GchnEzTrvd7vb+/uH9+5v9fhiGnhQgEf965x/iOKZtTbk6MQdw2u1vh9rG6YZlaigG9Ld//4efvzzO8zm3anUpS0AiiSEMKcY4d8My5Npsns/runZdKtUGwo7YHLM6NjWuVuWQW0M6k4u7gx5XOxRjw1WxWUdlWc71eF6/PJ2PcwMKRqLE6tgc7vfxZpso+SnPPM/fgskcCbqKJHK3BWOU7q6lBlq0qQfx7tXr3n0ye6Fk2vVzeyMNEZHUyRqV6q1Bu3iyW6maSyvVVB0BSqtLK6M2jtxtuVr1vNZ57jJeawoxph7/Xpud56zqyBAYE0qf1RKQq0o3l7gsZF7MVlVSdW2uIIGZIA7x5nb/7sN92qWcF265LvMU0+1ueNiND/vx/na73zHkV/HFllebHWQjaSMxAKG5EoaUblIUc815RbeyLvl4zKcDtjIwpZS2QxpCDCwEiA59TmSqtZayrrWZxIE5AAo4diTi2zC8sye+zZMRXFwFmngL6ClKShE5AAmxCMoQnQOba655XRY32+13FHfv3t2r2np6ZG9ToF2SDMLUVBW4Qmhq1ohckbR6q62upZRzzvNa1rWomkgkisZJQkwpiIBpKeuyzOcYx3HcWmvQVRvd0RUte7M815rLwiFNgHH8lXA3gJAHRgzBb/c3v/vhh0Dx5fVwPp/WdW6tleLLqmpFtWor2nJrRV2be/Oml8xI0Z0cybuJK/buArgTYYwhphBDEBEWBkRVbXUt5VzLSQQpYBRKg2w242673e9v7m8f3t1/uNndTMM0DtNm3Gw22+1+O22mOCQiImYmgiu5/brzUwxpM2xgUzIHN2hVQxhqPa/zOSbf3r57f3/33cdPLy+Hn9ZlraWpMVtgYebEnISYEdHcjUEDmYmbgTmpMwsDixJncFXNq6PTTDFUYPLgOmirRUuGib5OisDNzFvztfppbWpNWTQk5VicxeLCE1n85bi2l3O5jseQOtMrkURkRu1qTxGBuhhabV15pi+qEVzAmoMBoKMBaF93kDkIAaE7t+a5aK1N3VrTal7MltpK0W6KmlWLcTVH4Vq1Va1VtWlrBu5EqmYOHoKAIxN1VAZS1ydzBAND6OJg33p0I0JgCEKBKYi7h5im3WZ/t79/d/fw/j5u0jqfyuG1IIzDME4xRVHFp9empZyeDj/+Mc91O+zGePOdDbdOXGtZTIl4t98uy6Jan59US27L0uYT1nUTkDkN283tdjPEJMhoiGbsTq6ttLKuJRcFEpEQIiJ3/jV015ELb/pXqiQAwAzbgW8GTKLkWRvWKiSDGgCgMKUADnaeZ6tzUYvD+HG/DXEaIp7Oq7fsgAF5IHHzYpVbDtjiRB5DXktZvOY5z8uyzHMuc9GmBoAxRgyj8VAxEiG61nU5vbyOcRiGm1bafD7puqJhZAmIzJYGdYCltKUUx+AUb4lCiL+a83fN3ii+225/+O5jisPzy/Hx+eXLl8+Hw2FZ11xyU9VWTYt7RdSLyBlYR15jR3SCwVdwlIGbW0NQEQpBkKg3VpjJvRerhbClOIxTGoa02U93Nze3N7e3dw8Pd+/u797vtzdjHIY0pjiOwzBuBonioBc9+wss5BsrJXfTZqqIJBIReVBIwzTP5+enLyyROaDrZhp22+kpSL64U1zksbvpbehpIQAzoAvihRQHRJEZJFbiFQzN1mZgrXETI2Jnt5gdm7fmIOAKZmCK4AbdWrYXbOOQxg1v7yBuKsp+m+R2U9Hnw+vUxL51hgIyJ3NCJ0AhQpJASEDmCNrn+QIUUIgJ0V3c3NxRDUjB1LQBQh8WqbI3U7XSvHVnbbNmUNWadoNtUHXN2qw4Umum6nYFgF3cQt+SLAQRGYZBtAICdWtXB6A+BxORr/52CMQiEoIEkSAOKCnGYeAQi8O5tEKYcysK1UkMcvNlbs9P69//3esY8Xzyw3kLm/vtZov7+0Ypr9lKBjdh3u93aQhfPo/HVywlt+UMeQlWB6E4xM1m2k5j4kCAZIDm5AbqrZVScm0VOIpIkHAZPDh1DgUCITEQG9G3WyUSxRhiihKYuDMtQRzZANSJLQo2spxX0yZx3N7QuL1BoLycaz6bNQNqpeR1zqWteS3L0rxIdDetra3rupxOy+k8L+tSWzYExMTCLCEmk5ExmKu3c1t9nYe8VDNQtfl0anntTV9yJW+RwMAXI23oaG5OgN/KkAOACBEABJHtNOEH3my2d/fn8ce4zofX15bLOedMiAhdHkavOb0SGpEDgwOgA6HB12fX3U11dR860rY/l8IswogOqESWhrC/2d7e3Oz3u9u724f7h7v7h9vb+/3ubrvZj2mKHJgDo7Bc9SG8S/a4gyN1uPjlV6rp8XQ8Hl9aqUxhs9kAxWk9f/nyy49//GPONa/NJVpbk2AQioFTDDEEZsQL+QSZQ0qRmc29SGHJSAtJk+iM5CEUpBkUTUtVVJDgTIbu6nYogNWjG6Bp8bZCi0ju2FTMouDuZrf58Jv9xx9uP/wubm8NhAkS63w+heWLDO+QLiorZl6r5tIktBAIkYkYerKDyMhJIoBLYBEMTESMEN3BVJsaNtPWrBZA7f4QToKqXUOi1Npaswu3E5FQggCAV1fVpu2roieHPk8hQiEOLKmTlMFJKMVdM6u5NO0UTANEYYwxjNNAfA1+wsAxxa4bGpEopoQU52x/+OX5x9czCZrWep6xtbDa9lyywPpUjj/lcTPROPH2dvrthyGMWev5dG7LuRxf67wIDUwUgrAggmpebJ2DVgEITEOMu2mcUhIkNAcCdEc1c6ullNKamzBI4BAI0eBNM9m9j4OcxeFXYCQA8jB4mDxMFFOQMIa44TACYq2OHpGR1LQA0u7uHZMNwzjP85cvPx8Or2rG4MfjS1nOp7WeSz2rGmgW0JrP59N8OpxfDusyVzV1cGIWwi5ny92iPraW65obVqu36MwUwHE+nco6d2ifWQbN2twwOghzII5BhADgggR52/kJBdAZUxJiHoa42STX/PhlfHqCp3Ja59MF/KQNwJkIQEErWENvhMqdf9XdpaD3/RBREatZLmVdl3Vd17KWGmKttdTVXadp2Ezpw8cPD/fvbm5u7m7v7u4fbm5vd7ubadylNEaJQoLAXQShy6G8ZRUdE/ptSuYO5m4ASMJxCOMGpIY4mOPr4Xg6naftPoxb18735NB9akPvRXQ018VqRkIgZGFhEWIKtVXrgqpQwMEdzaoiucdqLAYd+1WdmwdyQnRkA1IDdCOHFNPt/c42D/vf/Pn+w282d584TrVaa63V2hBD0jTsvxXA6dNvNWcHvphhdKFyhyvtVaR3TzuxB/3yJhGInDpt9jKxIsIQZRhjL2mRUB0ccEhJgzNLf/RrraVUdxORmGIa+jPj1O264SLtS9yteLk1mwFrJbfWWw4iNAwxpa96hAgYWIJ0v9/QX+tmy5rPtUHPuNDZPSAqgiDNxNLEzjRiGIfbQR4w3CCDlyOsz3Z+bKdTWYyI81oUWj9t14pag2skikHGGKcQUwgEgG49icfuE1m0NXUAIupDPrrSC5Cg15Ms4hzM4VsnaCSSkCQMgOzIxCIhhCCE0EoBrxAjCxkGCjHFfRQMgQF92mzP81qaQS7n9bQ4nYsv1RczM11AtazzPK/zsqy5Vr3YHvf7hxeNM0FkISGWFgITdC9cc+0w+7yWsuSSS1VvgI1JIoeRaZAYo4Suy/atJKEwKKARGbEJABGGEMr98OnD5umL/FGPy/EzCRFSF6GiGBHd22paERxAGcDRHMz7ttT772wSmlp+fnn+8uXL7e3DNG7c7Xh8PZ2O7nr/cL/bbr7/4Yd3Dx922/12u99ud9Nmk4YxhBSk7/ncZVh6VvbWfPFLhdEvz7XmZxqmjVsDQ+IUhk2DGYgdsHfocm0QqoMRUY97EibhELqEkLdWcwZmjClxlBAkxhACl9aKYqk6rzm32lcedRf3YgbNFckNmyq5MUOIkYYRBnIqroAk02437H8r978d330H43Zpdnp6Or4eaqmMAR0C85TSV2frq27Hm4KcmcFlgGrggARMxByIGMCaWm25ux64QW12GVkjdbKskA8jx7idNuOyrPNScqm1tnEYVN3NVV1ESmEAR7CU0nY77fabEEWtujk6uXqtVZimzSDCrWnO1WpgIvDgrmbKQiGKyDcJJiIRCQcJQQI7urvVvEKtSgFFSCQGjkFCbw9NQ5hGHkZKGx63stsry/Pzs5VXLj+24yO8HP2oZU1q4eXp4KStanfaQYBAlIRjTJ1/yb0LBU69NwHohq25qgPiRTCFehbkiIbkiICCHAgkuEMQfrsvjLgJcRRpfXyfkgtZogpe6grNEZSFoowhcUohBBQ03m3lz/9is7v7hz/8/fHxSy6zKRSaKmEpJZcGZdVyLnlptRJSGqKwqEEu1Q0dAmAEAAJnUokiwz0jOYRc67KWECsiIljJp3k5nYu7JrNxoF1Mm5g2aUja9PHLl59+/jnn8jX4EezyF7uYgjHaOPDtfry7GaeRo5iBggEiEzgjIYJRV3m9/DFwAwdQxD5GBQATcbN6PL6+vr6WUkoptdWXl5ec1xjDfnf37t3D9999f3f3bhg24zAN4xRj4tCd//giWNdBF9Bx3/6W4XcblG/rMSKZpi25l9xKtdfjaT4fl2WtVZuBOqpdhOuZWYKElNKQ+s6m5mrWWqlaqjYFGGpLMRIiU1cYJKKaa6u1ql5yjOZmpQaHaJHQ0btEn3CafNy1hBlOEEJKYxrf++2ft+F+Ln48fnk8vr4cDsfDqVYNnKKEUfjm/a1eR32IKMISmPnq1IqXhc/MHIAMVKE17eRXVa2tujl1EAEAIDIRshArMQoLIWOUEKyHAYCzkHBQg7yWWpWZGYHAiGGaxt1us9tvQ+CmxdTcUJuVjMK03SZmymsBVxtjaAoIbtq0IkHotpNv9wVhYJqERiER6lRfBAUAgf5E4cAyxjSOKY1xmsZpu4lpwDA2CatqW9bj66vNj7H+hOuxnlsr1CprLvPhhGKuxr35SxiQe1keYriU5WTd/QiJAMhMW3NtTkhCJMR94//a2EdAQiJyRAL/Nr8kwjGF3ThUcA4hpcQszc0MQI0JIrgQxigxBQlsWo/zQc2QhxTCJsWWQjF2QAkTE1gutTbNRUuxUt2N+6IuobudAoQYU4ypZxgikBJvYgKgeQVVXZc1hJjYXbWuSynFMFIMEPeYtpKGkIYYw9zmw+n0ejj8aud37wPlBqquZnrR0pnGdHe7//D+oZY157W1Bg5IGIIhAguZM/TBklsXhHJ3oEsXDhHM0N3O5/N5WYjZwV+eXx6fnpraZrP/4fvvPn368HD/btrshJKEmMIgJFexQkcwRMaL+aMrGCL026Sq5o5MV6l4AABm3kxbNF+Xl5fnl1++PJ5PB9flvCxVzaBTgZjZhUVCSMO42e8R8XQ857Kiu7aazwscIb0ex2HabKaUxhiHEGKQEARFViRYsjU1QkD3c11EahptDLIlDlHCOOC01fF+ieAVbsb44f1vePvxQLefn85/86/+5k8//enL+XUu2RwVGJ0C8SRMG/kfres1YDDGMAzCgnTRMkWiDvHTjvYzhVobEfdmu7kRIXUtZjMgFBFmlohEHRoEZg7gxCiMzIAs0zS5IQA6ZHCnJDFNMfFmO07TOA6BGNWCqaq6KsaQhHEYGNDVPDgCilsABFOrlR2U2Ym/KvcLwpbxNlAS5IBdMBkRmLp8a59dpXFM4zAMY0pDCiEAQFvnczu/tpbXPJ9mW45cTqLKPjQX66K765nZGVyYmciFhTmkKClxDMAA6MTAAsgESF01qDVXMyYMxIGYL61+N8UusA+OFwkNa/6NuSUhjkO4vd2GYUCW7jqVlwLmgTlITCGmOMRhoBjM9Hg8/PiHv1vmc4pbBKCy7IJU2DYPMNzIWs/nI7j6dUZHgEHk4uCDmIYgEsfNZhhGlhCYiH0QHBMDcDN3sGVemBgH0VpbLqAwjrswbNP2JsaBOrFKNbey1lpVfwXyQeyyXg5mYK1rHed1rbUQwXY73dzsTmcqJXcH+N7H7V4j/XqRdclDcrsKHjs4IDOZwbquL68vP//yc6nl+fl5meeUxtub7Xefvvvw/t12u4txcOcunv11OgzerzX2hvtbf/+a/qur/toNFhFZYoxD7Mk6kbBwnHb7m7uH95vNevfwICHk49EBkBCIGpCpz8XyagTWVJe1mjamGuN6XtZx3AzTzTTilMi6XWzztVptxnTxzwnBIaYUGSR4CBnj0UQrFZbb+DBMYx4fFOIfH5//ux9/+cOPf3h6fqzkHCWGhBTM0ZsupZxr1uuN6TLkrbU+bULo2T/aBQmLCOQO/Y70ngVSz5bYHQGtSx+ISHc1a9odYt3QiYEEWLrtpzhgLOzOIgggRBAH2WzGlKIwubs6IGMgDAExgSBIRDMXAXcOQm7kAKrGAqrVvQvhXHdLgBFtAxqgsfdSFomQBYKAsAf2QBZdo1WpCGBamzrkqmup65pzzjkXrzUYRhqiTMZolgGKNwAgAmQSRIKr71CIMQThng0QEjEyA7ECNvN+LQL1po5Qn08aXLBR7o4KpTlh06q1wPUxU7PTMp/m80Q4DByZhZjQ3ICFQhAJEYlaydZqq+X08nx8fj6f5xSrMJNmdA9hZBo0BCp6odhTxx0TOgJ0mcKBODoic4gpxiASYggShIMAk2k3/VDN68pE2NDzqa7Z1TmKxCGkiSWBVoOq2gB9nMZpmvhX2P7ODwUEAFfTWpdlPh5fn56fjucTCg6boVpDcndFBBZEBHXybmZEhoqkCEiGDpdGHAI4ogB4Ke3L58//5X/5n0/T1Frb72///M9//9sfvvvw/v5mt4sxErEpAkCne11RCt0wFgkZ2Z0AgBG8LwUO1sfx3yr59KgRke3+hkO8ub3LZVXNN3d37rQuy/t3D2vOL8tctah7bm19PdRq61JrbehuBk3FzKt6aXnOGuc6rjCNthsboa+55lVz9qp+aZ6qMaFgkDBgjJm4FHtpldfju7v99JtPZbv54+xfvvzD/+tf/esvL8/E8PD9hw8//GZ/extCIBZAPh7Pf/zjj9v7hzdNdVU9Hk8vL6/jZpNi5KtVp7urOhGnGInZvKtgEjGREDEBkqk3MwAXcAXX2prpkouDSRAiRzIKwKFXB4aAEgFJmAUQEIwDD2NkYTevTddcAGBMKUYWQgJzVwcTISYkDObURcGZvVbLJZt/3S0RTLSGtkpBRu9xj8hsRK2QGbu61lKWOlMfCQOyGxb12rS2VlSbNSIJaUdxhBBdq+kM0AiFicgYoT8lRCRBQpQQOBAQdfVgCigBkLRZVivmDSlJCBKZhJCbt4tu7EUpqZCvjlVbK+tXf7u1lL//40//9b/+291+/+7+/rv3393ebFMcHbDU1dwphNrq/HjMNXsp67yIwxAGAClFy7IS4Wa3B0lrrUtZ1RSJOQzurnVVL1A1Rt5v98O0ceyYzsLd53PYbLZbBJuPT8u8lorA0mJd53M7LZbPZVnMobXGpl0t2rssAdYY+dOnj58+fUrxW1YfXEFhrbXWainrsizrPC9zqYWZUkq1VkQ3bwB9QuRuHVACaF/1Wnu+hFe/mwBg6rUaAp6OB1Wdpmm32338+PHDh4+77ZhiZGF08otVaUfFdKdo6snom3cCIXWpWjcDcDdv3to33ulmVpa1laJmIrLdbQdNpeSm+ps/y+t8HoZYvzzOy/n18Hqe5+N5zdVqtVZM1cDdQcHV3MC0M+uCtNy4NSD3GMQUwQW6+ARdColhmLab/WaziSLgXmtzRzFclWcTO5XHX375hz/8/b/823/ZQP/s9392++7+4d273XaPaMwS0ziNU1O/vX+Q8DbqsyXX81ogJEdmNwIEYkA0RyaOFIBJtZlZc2cwIWAEBW9Nq1YApEZdeL5qm0sFgAgWGMmreuujL/XqDuYVCCRCN/BDdgNzA+2SZ7URYAgmjg5uYE1ba9otIoDc1WprrVbzVltbSy7lq924qs7z8Xh8CVYlD92rEKKQMCExcWAhYqeOuu/PEbtjU2jqzVXdHYFDYhwNGhQrbT6dX2Pw/RSIqVRdap5L8dqGoKJuzRq7gDM6KQh7NAO3nOt5Wc55NfRpTIjkDtq94LW5qjVTNUNFRQPSpjWXN+luVTuc1y/Px7WoqqNLU7u9uUPE0+m1uafNDsjX5TUvpzYvrTYHYghIZGZd4LQ5gLZlPteyxiGJJEQqy/nY5qorARBdhi3EwdVKMUSKHY/AQVtdcytNRSZKI0tS1fV8rsvRa0YikEqtRlMxAzDVmsvRwSVMZr9SWBJVbU1rySXn3pbLpdRawZ0QiUREUkwIrs6mtRvqXnJu7YuLd1UZ77MQCjElke58xG4gEsZpvLu7//Tddz9898P3P3x3u9tdC/brWtJBgdandR1/7e4G1vmviELu3mozq0gO7tpqyl8VY1prL68vy/FogN1k3sxqqwpwc3sToyznw8vr888///zTTz8/v55PS87ZajNTNfVrI8o7JaYnHkHM/CDkNgZOgiEGlISZ1UKgwChE++32w/sPm2nUVltrJMbCm3HapHh8fv2H5y9/8zf/9Z9+/ONxOT28f7+/fdjv75bT+fT8us4LM9/e38Vhuttt39/fx7fgByyOq5E4uSI0ZSCJkViACUU0iCGurYPwGpMPjUWoj/p7U6e7XNZWq2k1cCIFqwzkFS6IXvKam1kuCyCiOBM3a2BerXbPj6ZWmhIg5lUViBXf2jxOAISoren5tJRSAbzWMi+n07K8NZZKrX96efx/vxw38xrC6N5BQoSMBBdgFXPgGFECcRCWIAEBWwM1a2YAQCIoVrKpYyllLfO8vuy2aT9tFPl1OT2dXh7Pr7ZmI1yQonlqPo4pAKGXYDZiA7P5lF/n0+H8SkK7TTJvpRZBKFZcK3YCbTMD9KoGvceZ36pLROIwEA2lween18fHl+128+HdByZ8eXkElvuPP+x20wAzlnM9vuTSlCPHTUxJJICOTU1rLXWejy+OdH//Pk27wGF+efzT/HQuZ2Jmiq1azS2lwEhCQkSBA7ifz+dclvNyJpKb29u0uTMa5/l8evY8Z/bKTCYFS0ktB2EBqzU/Pz3O81mV725vc85fg3+z36lqGFKppbU25TzuN9ub/c39/Xme13Vd17WU0lo1b6pvf806cMdN25tQMyKSsMSYRCKz9HYps8SUbm5uPn769O7hYbfbpSCujbBPmFGb9hoVAc2ty+9zb1AjmV263+5WajRrSADurdq42dA3GEwkRgncU2FmBkeRkOJuu8t5Pb5Oc25/+U+Ow+b2vJQrrN0uYrjgva0AnZyEiBcjPdluxvv97ThuAKUarLWoeUfXCPN2nB4e7lMM9WJ/YyKyGcbA6Hkdp+Gc1/Hmxgg+fvz47/3zv364fyjLss7LfJ6J+PbuZtru07h5//G7lC4p2Waz+/f++b9PIY7TJCzWGgNJSCwBiFg4JQGAXGottdVKaEPoDgzgV28/InS3qk3NDKhvKEyA3sjd8QJCbqq1FkSMMTKxWnNwRAbsPrOg5ggggkKO2BDMDftv6J2WVtsyr7U2RGjacl7+nX/nrzebbT+Xcbv9t/76r5em07QXib2t4YzYnZkQe3eGQqQQmAILBw6IYHrJ9BCROCCxITW1NedS19KW7Xb47fc/DONwmE/Pr8+vv/utlbadpjEOHEIMcRhjCAJIIjxEBLNlLud1PeUTCz3c3d7tb242+yjcrLppNwzqbsYO1DFBP/zmtykN1/uy+Xf/3X+XSBBNW8t5CUEe7u8Z8eZuT0Hu3n+/300brtCW+fVQmjpFHqZhs0eSdS2tmQOVmk/nI0rYv/tu3N4EkeXw/PPH7fn1mbrbXooppiENRKhaCSmkAUiKaSnruhxDSHcPn+J00zyc5/nll9s8vwhUZpI4pGm72d6klAQhL8fnp7vT+dSq//Cb7+MQv8bLfDqBg5ldQrnv6KraH5rr4e5Xg8lLgg5deulNg6nXd1eYVOetd3uZy6RX5NKK64NVd0ToTOnriOWb+RB1G76vn+lx2W1FAS4vYuY4XBSvzazVYqrQf2rvDcKFy+BmrdWc8+k8l1y0n5JdZ5XwqwO/ngogIhN1O+QL0sa9i2rg9dkNISDhRU67C1JQb8FrK3VZ59oaAMQYN9ttkHC9xL2BesEvhhjHaz9mXdeffv7xfD53AM9F544uxEmg/suh3zB3v5ZJ1xP4ejeuN+x6Y67AEfj2O+yK4e0+dfCrr3Z2cHep/0fEkIuFgLur2lv65qab7fbTpx+GYQSAZZ7/9A9/OB6P3NtF120C3t7U5T+E10WXsFMjrg/X5e4jYPcFsP6cstAQEzG13h2tBdyZOu2g25tdfhT2Md8FN2VqigghSGBhlj4MudCgrw+jXy9OGsab29sQIwDknD9/fpzn+TKDMkPEIIKIrTVElNjBBQ5u2mtS7MUNA3Qj40sgqTbASzbX06eyzNoa9jtBX9++uwMCIV9O3821IZGESCQOpKqtZtPWM1bEi1I4ESGAmbZauqTqNG3ef3j/tsdcx8f/5vg3x785/gd2/GPe0r85/s3xb47/gRxS1Xqd2JHk1vt3lzQIrnnzJXH8xoTpm5+Bl4ypZ3I9iwOAr3DcX3OJvn3dNXX87/u2r/nrr/99KTwi824IgQkAlnX98acfz+fzpWT4tpL4/0puLpndr8/na57pl9n6Vb/pLXn26xleX/X/T9rk/73/8/bDTW232/3wm9+M4wQApdXn87GapjSEEL6RK+tv0cFNVVutrTXXBn3+8NXVtwtXCAtTH0Uj+jVTtQvb/9LhNIfuSddq7Q413QD0rcjzK5Y6MKcQ5eIiYU31IhWMZICOgEgSZBjSGOJEwojQU+Uvv5yXBYkumpgcICUQgTeMJl5LLbz+8Stn8+0Lb7f/Suf85lP/qB7xb16Fl/LCf3X1/XLlr99+ve0OoAi9kgI10zaJvN9OSQQA1rx+/vzTmucUmYl6yFxk1KnTFNDdm7o5EF2KP3dvrQPTeiear1YLvdt04RQRXz9prtpLhAtjhYhjCET41mq3S62Hwldy6kWb+KKpc72k2Knl3a4mpenh/mOMlxaGHHKpanOuc65zbku1XK2oNXe9vDu4Pgx4DZdrVF9imwDA8HoXO8QXHFonhHZs/tfa/q3Mo+tNh7eq8srPvy4+l+//5rV9vO5qVk2/20//we/f308JAH766cf//X/0H/5X/+JfpBSFBR0uwkJ9ZHh9CsC7va9fnu5LSDg6XKjK3sV1UUR6N6FXaL3LCW79B72tCr/++M0DCRc62FVUu3806J2Dbz7Tal2W9d//9//H/5v/7f/ur/7JPwWA5/Px//xf/WeP+fyb3/7u7v4+pETMfc4PbmpNaz6fjy+PX06Hl/V4xKZJJFDoszOSkMbNdncz7Xeb3S6OAwsbeG11zeu6rLVUVe/WBVn1vM6H4/Hw9Dy/Hupprku2tWitrbXe2hXAUeR+u/vNh/f7zYBe1rK+nI6Lgg1T47QCKTHHcHd/97vf/fYv3334p+PNlgMAfP7yy//h//Qf/9f/+l9inEBGlBFu3uEPv4XbOw3ROxMEAcSJAQiZqIvGChhfJH4JSPpl75xbIejfgwgEBqjwxi672Hz1yx/ACexCQO1f7tqZ5hdrMXcnc24NDBpCRpgR1J2b+7qW19d/63b3v/rrf+c3d3sA+OXzT//x//E//MMf/tvffNoNQzwVO8/tdMqguhloirIZWM2eT6UqxjSlQULw1srr6zyfc87OHLe7XUyJAcxqbdm0KLoIj0MiIi2trHVeSi7a1Kt6KTYO46eP71OU4+l0XpZzybU1dBgC3U5xDEGY0iCbaUgpUIAOwEAiEHI007zM6/PT/Nsf/tn/4n/+v/7u0+8uwX/MpVQ9ruUwl1Nu52xL0dy8uumFQAtN3bpWbO+Lf10yr3o9gI7kbubNtGqtiCgsJIJEAAxfOymX4Md+866QwP4EEP7/CP5vNz3sdUpXttaGiOWqEns6n/+f/+Jf/F/+k//rNI1BQg9+/Db4/Wvw2zX4u3ZLV2u/bogOAMwcQiAi9+7dUFqt2tGRb0IC/Tz6s9SbXteNpS80Pfix97cv6L2eSPVe+SX4a6nnDIR0Oh37y6vrl7b8WM/S5tJGQb1s3araastLXk7Hl5fnzz8dX57K4UBNpxSTDBwSh4QS4zCN58M07zfLzbjdhCECQm55WZb5NNdSzBCIIMpq+no+Pj0/f/nxp9fPT+vLsZ5mXUsrpV7i3wRwI+HT7d06v7672Qq3Jc+/PD8fmtu0yzKcQRoLp/Cuze1u3O6m36ctcACA0/H0n/8X/4//5D/7v+F4Q8MtTnf06bdYJ/sQNTVnuXjzBCdBYhImIQ4IATR0LgkxoHdtQgZkBCEQ9IBACISG2IP6V8GP3ffHGNSwm3sjXryAL/P2i8E5qYXawCwjzIAHxKYemtnxtPz8WD+0/9m/Xft9WZb5X/3r/+a//Zv/9HS4H8f4fK6vh/zyOmvV7YDbMewnMfPnYylKMXbtPK+1vL6cT6d1WZ057fa3wzAIIUFTzWZFUQlJQnDHmmtdaynamqlDVctr3e32y/y7GOXHn39+fH59OZ9zrYg4CN+OcZPiEGW3TXc3m+02xUQduwRMTujoZvn1+fwP//B4Opb/6f/kf3l9SEHmUku1ubTcrKqrY5/ZMyJdXgvKbgbNodcFX3Plr+HMSKTaalnX8+v69IWJxvef0nCDYQAkU3172Vvw09cM2r/G+NcMHHtO8YYZpr4+9H8bEWP4hj1GxEMattNmmqYQOn7tqit2nQ/0f/fVy/AtDe4gJ79OyC4WDt3wo4dbKWuPhL4qIVJ3f+jjSYAuGl2/gRv7W+KKX39tRzFelja8zMq8lCo8b7abN+hlGscf/urPQ1322z1LbE29KmjTvJbznI+H+fC8vL6242tYzikXARjBBrQhMXNwYm2tPD3V03F5eRo2m2k7kVDVVnLO8+pNGYPEyD4IuBlUg9VQDcmwAbvE5twwVKpVjcFHCpEZAZhxmiaJvLTmTdswsSRwKUzAjAy55VzWNwx5a3Z4zo8/Z5qa7IhpQ3oH/mD4TiEBCnUhZgZhFEFjMmag7twDABenjQsvB6ln14xICNyHyeQIbzON/tHIUTr2FDrWhyqhkSOAKXYZta6yxE2Zm3cZSafi3NDBmoHktpQ2dIQpAAjzfre9vblJ05YC0QwIDZENfVGH4iDIyCQs6No8W2sNzYhojEkMDFDMRJWZSEKcppFR1Vup7bS0ZWmlOLkMcdpthYUBNJf19mb/F3/+CQDP8+H1dGC6YJYN6bB6Ud2CBCV1IpJBQorCiYGwmRkAcloYS35ZVv+Vht9pLa1ZKdWaobsQAhOTm7v17dyBzdUA3cno18F/3eiQmbl6y3lZHn9+/Lt/TQjszsTDbWIRvc72epD3WuAfBf91q/+a5F8+e60SeplwqfrI0VC6EMd1TYkhDHEY4hBCuKwf3wR/L+QuGcWbz62ZmZqJ93kycRBJQ+o5vzvUWquUPjliZvcubsHMLMIhBEQ081oL0dq+um5YL8negv/tTVyLprfgByJ2sxgjXiWWiHncbmPF5lbO53ye25K9FpuXej7V07GeDm2eqa6pNQEUokQcWZIEIMqtrXWZczHENA5tM8FpEwKbqbdKazVzoGAxQskNQfMCpxnXzLUFcwJEYhVqyIG4qhF4ImbhfhYhBBIYhpRLoyDG3KBTp60uy9OXz49xqvvvIAJ0046Ga6PoicKOpnvfPPhwa2HvEkDEmYARBUmQBYQxMEWCSB4Ju8gkIXTeXlcSEEJBYIROemT8dkjZS0hjdfEm6qBmhEpcGYn6UJMbIHSLIK4iLaq4WnMQ4+AJAQJXoxpxCpjw2hdnxmlM0zRIEOTLI5Fi7IKiTrhWFwKWFIVMvTWdl2pmiJTSmIZAJAjRAVtnFznGwEGCgOKazbzWRoBDCsiCTEwoIW13w3aTHHC7HW5vthKGtaq5qalWBSaM4syKWNWWrA6YmJGwNjeAbtQbwhDC12cMAOS4ZFfz2tg8IUZhF1KnZloNmkPzy3OKHRdyqZkBumoTQNfqC0Ka23p4efrjH/7wL/4LU+3ryfs0TnFkQTC/3piv1fulUYBvNbNfWetfa+nLZn/tEVyG+O7Q1a3e+PzY1RVEmIX5jSPTH4dvyo5LEKLZdXVAInAXFk4hDkMaxlFE3L21BoBmRsRETAwI0A1zQggxhhhTn/GuK5ZSVRtc+554EdHAazOk/24H6FxNx8vy5Jeh7tu3ApjaeV6ejs9eWjkt58Mhn866rLCumDO3EqxF8IFQUgJCILYQaxooDU3t5Xw6neacMxPuyjbUqmsJgcRUVEW9ORTHlbAwrabHko/n+fz6WuYVWrtkWOSIhMJkhgCCQEIKpqBITo6E0JNKNGUgMi+1Htb5dHi6r56/+0vY3AAAMPmU6HY3PTwMHz7G77/H7z7q3d63g2NH3wsLBqYokMQDeSJPBJFRCAO6gBMCgXXVFSYTQkZgAHIgIHZB4KvwpiE4OUtrvDYuGay5kGIsQKwtEDaOjbgBOKhwC9aSamsu6qwAjs05qrvEaRhuYpA3STKCmCCEvtB1qwgGSGaBxU11XrIZbDcpxhEQ53l5fvyl5jIO4367u799SDHVqqfT/OXxdF4WAxjG9O7+JsYhJhoUam3aWq6lWGveRGAz8NZsXmYJst2m7/mj81Srn5fTspxyPgPaOKSYRMkPa34+nKPI/nYrwrlWR0zRDOD+fvfu4SbGb4g9SzZ0FVUEF+x9AjSA1pwBsl75WX31oy4Ue22/9cttTgRM4NbKfD49P77+9Edrbf/+u5sP32urHe8DiNTpo98ATd5akt/WEN9GKFz6iZedv68C4EgOACjfrmMATCwXaRa2Xzd0e+g5XJr2X4vz3mRFQCARSSnFNKSYOjrYHZjtQpohEUAiDCGGICmlGGOMyd1Lya01IrqC3q4bOxG9oQa/Bv+l8nhr+yHi5RJdj1br8+fHnx9/hKp1Xpfzqc6LrZlKCVoTmDARoxCJsEtwDI2CYjSj3PSw1tOSa14DURJpjEaARmyKamhmzVUtu6+Ei1lutSxrWZZWCtpbeoXY1R6ZEZzRgdHAzBSgO1/0RujaoDVsqtZKzXVdyvwctzXXby8xC7IAYwWdsZ0Hz4QVWVAQGFgosESBxBbRIlkkDH3fQxcARqcOl8FLzn8NficHho7L7lfTOwFDwLlVrMVb1YbgDYUYPQYeWYBQwdCbYA5Qk2sDH5ASkwAUJ1Y2CTnEJN88Ze7uzbyqChEHwWEQEXYzRCvFMwERpTSENKmZU+m2IPc3t/e3t9tpgwgzFOZG1Ezrca1rbSnGzQYAPEYZp1hLn1YpoQtzSlFEaq0GBgxpDDFtCeOD3SzL8eXwZa0LMyJjA29VlzkHUpAYI5faDD0XNXMzY/r6jAGANCUEJ7cL4wodQQmAycWhWk9cL8k2AQB1cO01sswdDQEczLSVsta8YiusDVsGz4AK3Mtd4EsHHuCC1bs25DrAv2cEvXJjBAA09Gvd3p1u7NLAc1dHcLnwkS/rCF+NfBgY6WJfeU0hvMtgXRv8l2kOIrFcIFUs0ikJZo5g/WdeBPSIndmJWGQYhpTSMKQYo4joBatHX7sZSAj2dex2LXbgUgKQk0PXuv1mnPHtkdf889//8Q9/+rvEwt6RrhoIJUoASmCRQLoFEwNyNExNWTOvaqVZbtRAGjAhNnAlgIAUiM2gWsu1tVpyKw4qAoTcJb9MTRs5gVPPwaxHOXydmvXZFrghOJhazrksZ6XsXA1UvZWlnA/l/uB6qYAIPGiVfLbXz2urenhO5XS3j9OGeNqSjBSZREQwEiaEQBj6Ne9eVAAMIP2a4QVSSQCCTj34ARgMwa5GO0oAEYi1EjTX1tRatXPOq5BGZhi3iRISeSMrVBauS6zVnPYybEgC6JkFhVaRwuIkb+0oM1vzsqxLTDIOHKOweC3WqramhDBGkRjHKQHKel5zVjK63W3/7b/4y5v99un56eX4fF4OVct+R4gxl1ry+np4rjqPKYUgN/tJ1dayEvgmxc3Q5esHAFxLOZe1FkuNb7YP33/4Tu3dH/6Ej69fSiuq2no8AjWAtTS9Dg2XpdRc52V+eTm29o2YhzoReAM2MAJExz6zvwxFrm0VB3DsjvDf1OSXSWSnYzkxxBQ203C725C2m9202wzjIDGgm6MBwzfB/02T75L2w9cd8rLb06W6f1sO7DKHN3NHN8Zv9vVrUYCAfe79tci+Cgxe5wdvuIJORuiiQdxlZ6/OAted5OvR0f4sIjHErq/CTACNkK5DqIuezKXbh9d5wFuEowPY5Wr2AfWvzuByaK2Hz59ffvxxN22HmC5+cb3dQmAOzZzckMAJyFCBasXqbrXV1gU1sTUgtz5zBmJg8S5Zb9DU1RwAAwcWZoSmFogrgKuBeefVXt78tW5xAO0mM93AEgm7GeBaz8WqggLmms+n1+X1aG8PmRm06nk2RKuLHp5EGn7ayajh5kbsJuA+8CZhiigBXRCkqykTITG9BT9cEsVr8FsvQukq4GV8MSEScHFjuuiXQ1NttVitgYU3A9AWYfRG9cz1xPUsdU21OXJhjQAIMqA1QMa20mX8flnIEFPkIckQQwziAKrOiEpQUBhdCCXGGNiRooT9uBnffbjfb97d7kPiz09lrXNpi4HGIU0m04apAIsBNgciRBFhomZM7oFZqLtlEhGholZdl1xmJ8ObaZNivJluXf319Fragm6IHgIjkrlVdQBXs9p0XsvL63w8Lq299aRBkNGci6eLEhdgN9vp7WpFJIGgzmB6GVr1Zxb7QMU7oAbRCeIYH97d02++Gx5/w2Yff/ubh48fbvebGEVrM1S6tuvgsof7t4HxlvdfLvM1mMl7qxcd/Koa7opu6PCPtkwH6D086kJ7F6WxK2apLzHYceVvAGq6qN93C6aeVCJ0UqF5a1artqZNlYns+g7gutBcIO8OVxHw/mrunfx/HPxvJ+j4di0ui8DbygRg2urxVQ8vJCIsqOjmVbW5KkB1LdASwRRDVCe2Bq1Uag4OoNawOTbXtVbyFlNraC6GqZE0gNWsOCCFFELcbiFKtuaOczwplqrZFIgDkF85tpcUqpt2lgbuQkyBh4Bnz7U8vxyO56U2J8naTvPpW6FIM2+11jwLqugizuHJ/R9Sgye+v6P7d+nh47R/2MA+hsTgzMI0EKIzd1UnAr9YECLgpc8HF9KYQZ8zAyFJT02RzYJeQCnm6qaqVWsmilMI+xi26FEXmx+5vCRfRquDAwJnr2IVoCUdF2W0mrkNIm/RH4K8f7g5He6HcQNI87q4GwcCpsSsLZTWXAKzE2Hab+P+bhfjEMmtPr0+H/Mxe3EGJnJ0SXRzP+wA0iBC7A1AteXVDNHJFI7nuuY65uwOu+2OhFi5LnWdT4fnl5fHx4e7999/+GG635DyYX4GWAGVIgGiuXXyOyJwFF/lvLZTF7V6C36zZu5q13C4TKQ76eaKGsNrq+9rn58A7FqNgyMaAQ0xPdxs14/74+/A7Pb773Z3d5th4MDNm9rbFgIA4IQX4sxlPwT3Tpu5DPT7h7f9lAgdEN1R0TqmiP4xOrkH5hWr04PfL+ik6zbcney68ICQEF+gcL1ReHUBuayXpZQ151xyaa1fS1DlWlmq1IDE7FRrK7X1Z/3StXubWV5O+B9v75d64w1MeGG0fHsmBiX7+VxCwqJuoOamSgCBkMHIaiSoKcZgxODUFEL/fWaqpWqpVqqit9JqbuvSyAjctNjaQJ2AmCWyJBRxD0PS7bjTrOfm1eplDUW3i7FoH4xbaVaaN6PAgTkJRwHA1mxZtBQMSQjHEMf4jRgp9La6ulXQxg3ojP4YLZxq3nF5UH32+oHKHcnoZs6JNzdxumG6IZmu6WcnWXtX52AAQmfoeDbEXuhf1B6REAUAHJoZmII3hEagDDYiTgCpFWlHXR+lPo1SJ2/RHJzMU4Jh5ye0KdSIBiZ5FwJfgYhEGJPEJMzUFPp4GBGQkZ0cDBRVdclzCrQfxvtp/+nmTq3+4csfPr88H87rsl6Gygjq5kgemYckgdjRFbS1BgYE0gxKUa3O7j61SEBEmyBZGALUlpf5Oac08J9N49TKTZS2Fm+eiai5X1zAHQzQEUu31mv6bQ9M6npWwOYILInipeoHv2DbLj1+AEB24muj3y+aup1vZF3UQ5KMvHV4f/Q/r83o4X3c7JIEZqBwSVo7lJKg+zQTX3uG5mDOzbyrBBg44BUeA9ZFKa9Bgpf8D9Gvq0ffO9W9uUlXu/SrrKhDbxz0yPRrWBKiEF+E7oKEEEgEANy8ai21dj5zXtdSq14QT9bAW4aGaITNlYhrrXNec6vWW3dXrqKDXxsYfQJgcFmsrnFO2OEAl7bCW3sAgAAiAJZy/PzlgFTVu7QnM08pCgFoZfSjSAhRwiRpE4cNSyBAba3mpa6LtUoImut6Wl4M5yDdnKCDGVhYkV2VKiJzCOP25taB1ElPcym1aW0Gbsidswiu7kUtqxWHiIgsQeIQ05jiGAQRwjiFcQrD+JvvfnhTjEHC3s3jQIQAWl0XnF/8pebyueXPlp/t9DPu7hOnmmuI0+7ufbz/YfMeUxCjoEjuBmD0VYjcEVCQhISB0UDdm6upAgE6sKErWFMzJdTAngCIIYGGlrkVKq+wPkZ/HqMlaNBKzV4qV01s40gbpo24hAAPMQpd7cbd1lKO80JoZthU1e0C1QWrVs+5rFWbw3aq+ziNkXab4bT403H+6cvxvNZcrFUzVwBwNzeNgQNyShyDOOOyltLFUg1ADYEC8sA4UIuBHjYy0Kba0LTVZtuRA5VB0nfvtvutPr3W06LVIJe6riVnVQV1dGzLkh2MGL7dYySfnwylceQ4QNcIvLTgzQHUUPsNvCJtvvao8DrFRiAARghoCQqJw82mGNZpRBFABHe6NsARoDcRkHsP+LI7qoMaNHM1rH7RPLG3BACvwzNAIHRDQjf61W7pAM2s2YVc6uB+mTFgn1y9Nd8QAAiFKEjowd+3fiBUtWatlLLkdVmXNedai5p2dUJ3cFVH8IxI2LQxcWcK115LfV2MvllgEf7Rzg9fd/6uin+Z9H39ogOZeS5Fc1NrBuYASBICuzZG14ZgK2IINSVPQMAcXMGhlpqXuayrloKEtZSViBxq1zWUEIbEQ5I0UAgUehMjRIBhezPt79Lu9nA4nE6n83w+r4tqBa3dIaU5V+JiVkwbOHTlhmHYbjatqhPfvnu/u7vf7m//2V/91WYc306nV22dnqqurRXLqy3QEJWqY9P1qK+PAUNbq0han+7b4YVbk/ctbm5jHAyBwBmMABD0cqEdsBuPqoNW1QwMw2YIHMmosbSO8cFuHu3sjeqZsAQqsc3oa4Q1eQMrJc/rbHnl1iLCGCRTKISB1Dca2S8lTFM7nZfX4zmIAVBtXda4F7BmTau21rSoZ8rLstRW+5xjzXo4ldOca6n9tncZOtfmallaBI6DMEkUI1BnDISClERuN2k3xg58mAZBjM1NPVjzMQ1RiBmQMQGllUpDrY7uaIDq3sDUqjZrbYqynQJ/k5HJ+vKzh+TDDQojmrCMiAymbs08I2lvBFy0o+2qzYiX/RocyAlB0LzOy/NPfnqqea6UmjWyRqrcCMz7EkCIQhiEOos9MPYhjYGro6qbQTFfu86eE3jf4DuKC66ZHTqhGXwb/m7etFVVdWPwS0nPfJmf+6WH16sNRgoShnEIEvqy4ACqWmpZ8zqvS17zWnJrzXqX4Fq39zF907pkqK0ykqmWWtTUrX9nL+H7gvPWJLngFg38Wip9XYPxbWG6fsa9exc3dBfAbkzoiMiOqIAE3Jnt6t4E3Vyt1aLaSi2llHVtpVpTY1wzd7kxEhlS2u520+1N3G5lHFGCIwBykCAsJNzclnV5PR6eHh8/f/75pz/96fj60rVbicklBOHmmrVVMxSWFOM47G72w7jZ72///C//ycfvvt/f3n94+LC7inkAdN9IQ2MzKM28aVUUF+TgyMs8r2s9woENsBg6EMv+/g/n18N3f376+Gf/ZHP7HiUIYjTvceiA7tJay3NruWIrtaznPKcp3g/f7aYJA+aWLEVbg5qaVVB1r21uYJySbzmngcnY25Lz+XQ6L2drObkBCRMEwsVtbctC24B2mVy0pq+vp+fXw36LSDIvZS1amhtAQA+MSXiIgStAw6eX4xQP3380x4CUmsLhcCq1jeOQRJjReg+l+mkpAIwUhygiKQUnAnR0pSGE+33ab8YkbABArES5VHAY4zCN25BGJTrl+ZyPFSsyYPOAOImIoLotrdWi4r7fD+9vpyDfBP/88hOkDTlwDASbSB7J2b0ZOCJfM/uLrGY35rtuZHq5twBg6K5lyadXPb64NYtk3sBVTd0YrzZ0hABIfi3W4Doc60kBI5oBKDTDi6Cx9+ZAX3eQur4xXNp3/4iQjN+ohvS4J2ZE6EolZt1PijqvKsY4TVOIERHM/Apkb6XWUkq56h/A9e31rp6DazcrdFciRuqI+z5TxN74e9vwL2/Qv1Wz/cdvGZAuNkffSBIhEnLogrpdV4yuuiKdGkcX4AlLYBF3y+tq6hcvjlJ6l9+YmSsCAxQgCWFQIIpj3O7jfk8hqnqr2qq2hkyRB9nt7uLdu3RzF7YbQAosx+fHvC5atTm0IF0MwxHCEAebxnWVEFIYPn749E/+6b/18dP3w7jdjlMMXxVj3NRaU6CuCAoNa9VQHKs7aUUzL9AQq3lWL6VpPb2+EooEHqcUBTe7u4FFygptbVa77WE+ty9/elyOJ7HK5BSFfeeHkyqAop0z5BW1eTNUD+4B24bKlmAnvqOS2K3SWsEa1Aq5WFsrOAUQpswAoh7yHMqC/rV5uax1Weo4GIs3tVLbsqo5NAKPkiQEFnI0pVzyaT4fzyciGWPaj9Mzv+SSmza6eKO6uTugKlblYsxKgs4CKUpgBsdBJCWRIEzJ0YFy72QFCtOw3Yx7DqmBLa2utaoZIBKgMA2BA6BHj5EokANPI+ym+K2xtZxef6ZhK8hhHBluAkZyRXMwJMBAJNhlYdEczfEidQng4GxgvXVnZi1rXpZ11SWjNYIo1uhClumb9gVuD869HU8M1ZzBGQ17b+Hq+ol9kkDmPWv7WtpDd+5CRzdg/Hb/xMAyxDSN42ba9HweANQ056yufZYXY+wD5BjjtN3EGAGwttotaNXULoKRl24ngb3x9cy7ft2V+0uCXfD2MlQ0B6BrZtT38qtn1YUJeIUyfJ1r4BUMgN9o8SDRMI6b3ZYITLW2amYk0sWdiSmkGGIKKRGyVqhrO83nulbtzgvalZfQzYnMrLaGtWGt2CjCtuANSpgoDbbqvJ6ffnk6LxmEN7f7jz98mvZ3d+Nu2Ow2cXM37H7C8PTll8N8cqsWQl9WSHiaRguxlEKO7969//7T999998Nut69qrTWPBnBxdmhNSy2gDgCqjZRqrmVeHSsMBIGBmBQtWzmtZcm1Lar+vP3DuE3jFBP7PtKQJjs/5dPrPB8BZNrez4/nv/2//zdPv3zeRPjw7v53f/VXe8Pznx6P+hlq8aZq0AysAaMPQpuE7zbtfip3qQ5QPbeixJgIjBERctGq1jy2aIWzi/lgLaG/hctlmzO6GNuzBfaKrmoIhMbgQiQk5ASm0HR5fPxpTNP9dvztx/c5zz896VLyeV5DDIxgCiEwx1HCCJiK2lLPKWBKgUXAzdDm0kh82o5EYHB2dCEa43Czu5+mO6XQWlZHM1JlN+1wLBkIBmJmJ7wDbK1pWeOvsn6Q1+efZLwdw3ZTMoIToVnfZ7FbFV9YVX2e53QRsXqjx4A7gquDowpBDAvROhfXediuw7ZGAYkE2ik6vT+A3mnC4ArO4ARK6EwASGaol54USKfP++W6IxjRtdPrDuTyjTcoEQ1D2kzTNE7jMPbxrKqqX+Z7whxiTMPQPWTjEKdpijGqG6zQSe/XMCQikt4pvWqUIoAI+mWofAEKwJUXf93i3Pp4j+jXc8i3Qcc3A71fHb/e+QkpShiiELo2Ku5mcgl+5BDGaYrjNEyTKZ6Pa251OS7LedHu/nBpkyChrmuji6dcHtJyWP0I4QHCu7AdtwIVDsf200/Hl5djI9i/a7S5vY9TDJFkO423t9tz3Rz8mDXX3FYvreZcS1FVJKIgJMwk0243brcotNZyPJ2TpH2awlWJ/MKh6CMaIgSoawFEb8hFwmYgQa/WllZOtaxV1VRam0/ry5eXH/9+K+kubuK4scOXfHxezwdCGVrLXw5P/93ffvnlM9xMmkRKK6/LH356PB6OZOsQeXd3K8OkHjjIGMLN4HdDvgl5xLNYbcDo7iquqUNWqtVmStbEWJAjIghvmPltUUYUiUEiU0BgcCKgKOSEzBJDQOIujwEORGheDudn8zrG4dP9XvXjMMjnl5d5XRHJ1LSrATgCEjg11fNcFjYmbs2YPQojiaE4BWBA4hjSJkybYb+dbkmGOec5n2utrVmpZtVc3RFQCAlJLm5NrcLi5L/Gxcjj55+HXaPtB1MD4P8PW//1Y1mWrHliJpbY4ghXITIiM0ve6tu370yTMxwQJAECJP9nvhF8JAmQ6CGn1RVdVZmVkRnCxRFbLWFmfNjHI6L6tiMRicwIePg5+6y1bJl93/dT8rImCKxKGViX6iWgmxkIGc2eu1Pr0kAQYo+G22q3T2X+4dPDNKRtfwxXt7uO202UBCJVBJ+tuqt3VsW0goIpXW7j6+WWlACN3OVIXeV2F0kfg/FaC6MG/ILpZeZN32+327ZtnXNrdO+lFSfCjn0ITRNjjM47RIpNbLvWeZ9zLlwvOj5m55wXBQMmUVURUlVUZaIQo/d+lf2nlNaLguqqWcbPH3QDIP1cwcDXN/y/evMvG+FFR/j1pd9gNaEjMDJxRIeq3jlmRuYQYrfZhq4LsU1J07lokmVYzqdp1Ro65xBp5XmVUsxwDfZg58KnU/t0vnma3i54c/e6d+30ON2/Hx4ejgn0tIDbXU+CwRnnGQ6TTLblHtorK/k8w5xTGqd5mJbNlNrGVOaSmWWq6TiN+vBJBA6H467fvdxdt7GB57vYGq1HiM4REqY5pVxghrBpPHvylOeax5LHqoUcNy20HXqX6/Tp/kFjJ23e9C4fLJ9KnpyLlVmGoU4HlrTrrzZdU3K9P9z/u3/3nz58+Ni6/OLF9jd/+M3+7kXFpg19DLEP3PLiTXUZsySzRoRroVpYaqhSq1JVKSLgtfO8IU+q+yZ8Pi6RqG3bvuuDCwpWi6hIjM55DiEwslTIRXIuhNjGoCBjHUkgRrreNvvN929e3L37+OnheBzn6ThMKZdcJJdSa8EQRGSYSy5pHEvfuL7j633X97vQRmMEUOd88O6qv+7jztNmzPl0ejzNxwpzLmmak5QCuFqgCA1zBasCILWUJZfla9s5gDsdB+DeEXehiSE472tdG4WXWn29lV7GvWiEsGpZCABALzM3ZBARRIWVH5amXN35tJ1PwZae2+pUQAugKqxR3wr2nBukuiLnPgviCGAF834+PAlWOYcDdWBEtpoNHemXkmy1FhKBmtT1q0gVAnA+hBCa2MQYYwjsHQCuy5iIVkETfmXlXbNZzFhV5bIFaNvE6+ub/X6/2+0A7OlwOB6Ph8NhmmdTMTNC0ktUhBmsseOrtODzyf+lRPgXJ/9/9QdAAVaboSdijwzgiEIIbbdpuk1sd+iiGKVlysnmqYxDnsakYkjsHCBSFS2lppTUwJFDZkSiUXjRc3EFN+ej7ZpNPqWHj+fDYUoICUb/02FcLHiNNcVp8NMSKkQO29iqpDItlkue5zQvUlaUi6qi1Jpzmomk6DSeIzvVLzLSSz1F5Jg5oKrmlGtSyACAEgt6KFOWpKzeo/PEEVsuToYyjkeaXFO6utt0fnQ4myaKjeXO6oSWnYO+b0MbU9WH0/DTx6f3H+43sVKwl3nqIYMLyKaqtZgUFEHJCiKAWgqljKVwrabmDT0QErng46brrlx0oNuudfz59oYXMjIBGDlmAB+CC9HFZl38tuRqK4kwIHormOeKbkEN0jbtvm/s7mbbNfOcHs9D8E9LrjGG6MihVhBRXXKppaq6EFoCF0PjXailggkDO2amoEBzyeM8jNNxnE9GknIe12kCIRHCcyVrYqo55ZxSOo6lylcin3my3ZXfbfa3N9e7tmuCzyQiz7hrs+dx2SqOVzHTSzovgBZGdM4baC15HMbjp4f7+8d5TlUkD8dyerDxkVsigwoGQPLZDQSoYAQmpvXSDaBn6aCtvvfPhfCq6/JgHo1BDcTIEM27i8VnXXIllzTPVgWJqggCOOdiCE3T+BiY2HkXQyAigRVTbaJS6irOx1Xm55xTtZULrKorGMPUrvdXv/nVr371q++/++57RHz37t0Pf/nxj3/848ePH5e0qBozEpGqrLXAxfkAYKtmAvArC/PzxPHLf+LX/8MM1moQEbx3fWw8EZr2/e7Fq7f97hZdPyW7fxqGKR9O9emUzlOalwpGRFarGmjVNYF57VcgKgGwJqhnGXj8wJ/Gp9r5VpKeH09zFmWvJ/nw0+F8XJoALZS2jL3MbV1YS/Cua8JSGMxkWeqSSNWxC+wQkVRIJSKCY4m8DfTZa/0cCrfaKNh5llpNTIqAQOWSTkv1NaeK5ruwDdwycASnE6daqhQ9ckjv9XpTrmrbVsc1eEKszpmPHCE2256aZlQ5iZQQrd9AVOt6DQ4ixtYT2XkeMUtUAxe4NqhgRDljSpALiDrAQNwwadu0fbfd766um8ahxd12RZg/P5mqVkQrU9i07Wp59c41HGL0LnDReh64SHXMawDvXNN5mEgxxtjFbtduvt2+CBynZXl3f38cxlLXTpMWkRCgKKKp87Tr+qt+v2k2DG4eJjAJwVmlh6eT2BlQU1nmfC41ZbFlKeOQlpzLmrmBiEjeOVXNOc0pjWP+5ps5l68Wf/BdjP2m3Wzarg0uMBFwXTF8dtHcIgIoXMJuzAzREGutdR4IoN/sTHQYhtPpeDodh3GclyVVpfMwPj4Mv/wUy0whYmgpbtD59bzHtew1Q8ULf5doFQ99XgmXC72t/oLVGqCr8gi+msBdHotqzaXkwherDjJz166EspacExEmWht+WcQASimKUEXsObqnOLe27p+R7SrCa9RH17b73e7Vi5e/+81vmqa5vbnZbrcIwET3Dw/jOIpdvLqXhW+2HuCrI+Wrr38Zmkr/8uQHNQQIzrcxNMGvXcq+27XNjrmdEx5O+eP99OHT+dPD+XgalyXXKu7Z9naRwjhaKyoyMkWtVouIptkG0/vpafEcTDAvRYAhdGw522k8zTFAz3WDs2BSKi1nz9ZHNmkMrWUKaAExEPXemRrVgiUF65hJGBqCz5JYW/OHavXkVXVFyiMSAYOZFVuGhdipQfAxuKb1PSl7IMxmYqwAosvTOIK6gMjWeFETRCWHPjpB9E3k6BcDccCbGOqmiRi3G980zrNzgKCllrnKFDBaaOiKOa0tJyMFVg7gAYMqIjShbWLPvgHnqlb31wYMIiMyYvMOaAVXGjrHTQxN40LDYsROUy5rPQsIRWUuU0niMlep267d9M3t7oUZbDeb8zikkpdlmZf5PPkmwpxbBOtCuN3sW99KtgLKGJzHEMNS8qenpznP7MGsLHmZlzwtOs15HFMquT6rzxGYqCqo1Dwt6XRczucsX5/8d3cv9vvrGCIjOjS/jpOZ1FDV1tIcVsCjipiaghGiUUrz4dMHQkN2ZvbwdD883dcyVy1TytNS1IXw4f59yenqY9jtuxevN2+3HLtSiur6XZAMQc1ZvYjlL83y50C2i8YHcb0GmIis1wZa+wDVvvTVzGx1tXgf2rYBwBB813Vt28YmgsE4jgAQQmDvLeckZU6LmiEiMQWKYJCdr1XAgakS4pp8KCJahRC1VlP13t/e3Oyvrq6urmIIbdP+4z//04f3H6ZlLlaIHZGuOYvP0UHrNvzlnP8SSQKf/T9fJgPri0FVj9g3XRcjgzH6rum974ahTA/37x+GD4/Dh8fh8eHp+PBxGU6SMyF6xzGEEKPz7AjQ6WpHqLmmuS5jqaVaqaWaFlj8jMhqWASAI7XiivqiKfroVXyFUNkn74vHEqhuPG6vtuzIxbBt4saRZ5IYaimYZpi92/aeXLTiTZ5DykDVUkppWcjQzKEgATn2HIOCiMoyzkjOx4Y8IzGhY3QOmAQjcQzeu8BCkqUUVyp6BFVAQnbsgncGznlm75mbzvfXUbi/in6/322aTaSIqmaF2AiwCoq1oem906VkxuyxgBdXDVNWIwRoQ+eoWcR0WkqeNq7tRPxl5aNzGCM1DQZnCEZAiM571zTOewKsDLbtQvQ8TbmKoDMACJEMxFSK5aVOYuLbtmv6rmulJkTIeTmdTufpNMznqsWzM8WaMCV7eDy3PXz39u1m14vW6eHTp+PpcHrqu8AMVfI0pcMxD1NZcl35LGtsP4DNORuI8wqmtZT6vDNcFv+rV3f72+tN33nnCA1BGQEQeGXCwrNRcj1piXA1+JrVNB0f3oFK23WEPD89zIdHXEatdcUlEjktdfn08TSc+GqsFNq7174zRiM0RLko2cB07f0DwAUjDc8O3MtI/+LZlgp1BhNyaOSUW/vr2Tgzxxg3fdd2nZl659u2iTF676XKygMkphV2XUSWnERtbaTRs0bAe+8QTY3QTM1YRagiItg8jafj4Xg4XO33V9fXTYyI4GMkdjHEDx8+nIezqKrWdQZi8vmN/lzV22Xo8XmZ/7ea/0TYRuoaF70PLjKwJwcap0GH6fHxNP5yf7w/DsdhXlJyLDdXmz7cdLHt2r6NbQjBeWQS4GpQSs3LnKchDad0OtXzIFOudRoVC5IHYkGHnq0KFIHVH1SVa4lWi+UC2bA6rNvGX1/tfHBZanDUmDjgbXAJJC/LMujYuCYEK+nzYPzzvqzPucGkgExN04BxLosm1aJAwrxaFo3JHCIjr+drpOgQa86SqtYewXvnggtrKi0hOiZP3EXfbXpsmwV0GOae3E3f7Ltt7xvy7Bwxcku497Rt/HYTPUOoOZfc1bRG66alTH1a5qXm5eHh+CSp5mmaT6++Lbe//199liuuMJA13OX5sdpqghUzqUXUELAUKaWKqmfHxN47M6giRrrIMpRpqbnFvmvbQF0MzqSMfT+Om3E6ipbgfBE8nMu4aBLa7K7evvmOHL/7+P7xND+extN5qlKdI5U6LzWlWopIVTAjQ2aMjtVsUVET7zEwddG10X1t6XffvHmxubrZ73dN2xhBhYtrZlWmIyqC2Fo7OkdGDkhVTbMtw/nhRynp6mobqdXjIxwPks9USt/1TR+63W5L1Q+fZJhmNWg31+dD28ZIgLBqr82MQU01m1bT1b0iqw/k8jMYgK0WCrWaMQ8E6kLUuLf21bM4CACAmDd9d3O1v76+ik18ZpLh+j2rioACYDVFrUvJc8pLziv02rEjQjBlphg8OgeqJnWdTwkBo4HUw9PDu598v+mR0AV/dXX9u9//fnt1td3u9ldX//E//Puff343T1POikrVTGidUqA9g9A/7wRrTaCravD5n8+vxXm62jdX++gJGV0f9yA0nNLT0/HD/f3j8Tgs81SSatnG+PL29pu7F29fvr69vt32uyY0zABQxeZSxyWPS5rnOY1DPp3Sx0/jT+8OH+7n47mqQIiO2aGPECIEj57XERGioanVopgBMkENJHvf/OrFXdP4h6fHakJ5dmSb4NjqfJ6P07mkqWvatm273V9FNjrvXPDsmR37gDGEPvamJOeKkJkYkNY3nK04qg6IkQFYDVVVrNZ8Ju9Imsb1+77Zth0pai5QlY084VXfXL158X2Ib755MU7JUmXRSNjF0O+6ro9dE/roNt51nhvHhKhm1cQ0iYqq1aJlrr/8/Mt/+l/+/bsf/3g8PJzPj+fx9Lf/3fiv/6f/083LdRcDqSCFRJxQuKjza3YVxQQJc5ZcSs211FoF2LmePDE7Z0DOqSHiKOlxOnSHjya2DQ01TeNddL7Zhh03R6WaF+d98eQIXr7e3r36Zre/bmPz84cPP79/+OOffzkNKVWgRQhXrhb6GDaO05JNlABjdG3vqlmRUoo6Zudd5/zL2433XyX5bPrYd7FtgmOoZZK6zgUZjfBZDAurv70Wy6WmVOYlLeP544/L4yfEStOnwLEdP9r0UGtWoT42wsETUM2URtRsRMvp08O7Py3T0TEyKkNFNbC1zqiOxLE5AmcKIAAVwcgIzcCqqqz5c1hGBnA1ir0U37Nefx71OebdZnu1v9puNuRYRFTl4tJDQMIVqqVmVmspueRcc1UzUgNSIkQwlTWpYu3OERuu7Oda17WwHI+PP//0Y/AuBC9St9vtbrv99ttv07KM56PU8vDp42B1HY+kWr8yUD4XMp9XBVxsi//y6GfCrnF941EIDdFYKpakJSkqtj6EwLeudwH3V/vv3rz97pu3377+9vb6pmt6T2xQpc6pDtNyPA9Pwzicp/ncZh9TUT6NOiROtVDl0PQuthQihsZCCz6C844hoES0oNXX7CFHktZw69x11zZNzPOYSgn47PgXnad5mqZlXlKXxWBf5TPW2nt/e3f38tUrrIigyDXG2G97FViWKRGKgKmCClttuEbOKlKkSHWFGIUiV7QxYr9r+GbT3+23TRNzMSvCBsjomdro73Zdu9u/vL2elzIPc56TphqDv7ra7nZt1/ouusaRX/2hwHiJ8y5qYmoqIMXGcc6lfPj08O6nHx8eP56mob15veR8KWEUStFlqYC1eF6FHSIFwcY5A4AI1FpzLlJVDYk1Z3TeEV+GwaI6LWmZtc507IZd29/ur9++fHXTb5oQvGLy81ysFkgKSdAbGtFS8uPp+M8//Pmf/vTDDz+/TyUBqoqhWalCjE10zjs01LpKvFDWV2VmhlIhRNps3X4X+Gt5r0oGLQ4VZUnLAQCo3ZNrAf06MgBiJNa8pOm0PHycPvxyvr8/HE6n8VDTuL8K+3rYqXJ+N5RTFu+xQRcmW9JpwOW8WR69A0K/TB9+/M+Hims8gwYSRiN1zBgibHq+2Ydd4yMTkxpUImVgBAORi0jElDQjAKkrWEq89nKHz8vLMe93u6v9volRVFcrAjE5x+wco5G/gIFrqVoqlIq50IolIFUEMyklqwiRMbP3n7M9LEjVKlar1fR0/wG0LtP48Zdf7l6+7DZbRLq7vfn1r34lpdRlKTkxOaIsCsUubdOLCNAM4SIZurQGPx/7X/X7ycAhhjVFWW0ZRykEKle7zYu7a+/ZRe42Ybtrr2/2L1+8vLm63W32MbRkaCJS5pxhToXA50QTaC15ycuSazXk2HW7WB3k6p1vyEcKHn1EH4w9EjrUaNIqbqRuaukh9R42rm1dIDE0aHzDLvq2M+eWnMcpn47TOM99R0jCoSypfk6Jbdv2t7/73YdP98PDMA3nXM8++LbvVCGeT/OIc61rwpRH2XptXTqlMs4yzMYAqcGrFq87vOmbb26aty+u7q53SPR4mEjBMQE7DuwCR6Z9CNfe587O0c1zLKlG72+vd5suRIeO7ZIZZWCgZIiABo6ADA0ZEIFDJMdVbRjnp/M4pjxn+fxaVDUt5Xxe5gWJ8zNQ0mqVtGQw894RkSqoYBUrNZU6Ok/bbRuiR7BSZJkXqecPdAwcmhi+f/Mth9i2PRMpcWUeBB5P83HJ5yKVHv/x53dTmt9/+vTz+48/vPt4HifvnPcuM4FZrYUZDZomeBdbYUnzMqd6LiIqOZsqlKSEsN9haPGvFH7jeAZ0j5/eNePTshyd83gLbU/OMZIzA6tV8phPj+PHv0y//GX6+cfDh4+fPh1nVXe16a/bnac9F6ARbZi1XarMUzpWWLI0dW51QkAsIZ/L/amep1JTJpPglBBNiZh8g/utf3Xbvty3d5uwacgHIzZVIDCPq6NmlfoKAoJAAVb9QfzG7t4AdHBR+DVd03jnUapzjsya5kK8EZO6SndBpAoDBCREMlyDIhAJZZUim0gVAHUekZg9IQIKXHKkTMo8nB5Nax3P56fHh93+ut9ualVH1LVt0zRNaAoVM0Ms9nzmX/omF5HTxSzwL1r8X75QIZBvmt5ha9WhMYILPvZ93zTBB970zfXN9up6v7u67rqNcwEUa66Sk1w0kC4l74jMYFnqMJVhkqWg+c5tfBO9g8AuEnt0hLzyc5DAvOVOcUtwhXiFuGe88bRv2+DCkuqi83FMqQqkuogcz8PHh8effv5lXlLX9m17DjFW6//wry8oaHZus72+uv4G5QzYwRKaLly/fIOmZZmXZRzmUWo15cB6taE2YpqXYx7Pp5kBNtS0++7lzebty/bVdX+zbfsmpiwllbxkUOPgfIyhadoY2hgc+0Bm1jp2NUr0fts1XXQOFVHXQHF7NqXipfZaN2QzM+fc7urq7uXL4+mUwOB0DrFH/FIqX1gfqsi2JrpWkZx1mCqabXrn/aoKRVNRsZqrAenlINaaa1pqyWW0xbPrSjMvs4ESMzqHFin24sopzx+O08fT6ZymrGmYzp8eHw+n8zBlVYgaqujFcWLqA3sRVjbRqppES5EVSWrrcA4sFV1KzVW+DrV0nz7dHw6nw+NTDJFItlc3xJF8w74hAimaz8fx48/jL38efvqH5cNPcryf7g/Dh0F828fv9y7udnc7n0rrs6ulpnkYf3x//piBN/02ImHNAn6cFinzEwyHeTgdas7OsxHNCtUQ2brG3V613921f3jTvX3RXt007GyaMwPsutgENlwxGySKBrYMx/HDf7RE8t3fAlzDqgUgWkO5HLoYGyTc9L3zvkqd5joOY86ZnXPEjQux4QxoapeIfseiZWJcFkhFVKsI6UXFfXEWAgEDMCFryeP5IS2PD598aGLbkXMiOo0DEYUYDQBLWc8KXIlNl0f1PAsEwK/q/b/y9AGYghbwGF7e3O6218whuNg2fXABDcFMpQYfrrrdptkEF8wwl1qLlHmRnFCrqqzOxjWmcZzleC6nAYbkMnXW9tx15FrvA7G7jDVETQuW4sFakCu2t9HfcdyTbTah3+04NA/jPKT08elwGqe5lMMwfHx4fHw6Ph1PuUjwAQ1LqY9P5X/3v/8/v369npYwLbjkiD6Evs9u01/3b37ze4dV6jIvw9P5mHM1YO/h5rrdxDCNp8eHMZ8fvKPt61dvX3T/6ncvv/3u1e5q0xBLKdO4nI6n82nMWbrOxdi1/abpNy7GnGqqosgukPMWmR1dUEdweQhEtErVVm8FgoEAiEjJxTn+5u13qnB99/L1zz//8S8/3b18vSJ6AYAQvHddG7u+a7s2higih9NUinjvmWiz7byjVVbqnDURbcMhuK5riKiUAoIlErFn57ZNd7e9/v7Vqxe73aaNnqO40Am1M4Gbz/P9D+8/fDw8FElqxVBd4M58qWZqS05VlImaxiGTEeRaxjnXKrVWUcPP8nswJMtFnw7l8Wmp9avFP04zY5rHuQm+aSK60J1Prt0CBbRpfHxY7n9JH39Yfvnz9PMf89NHzGMdpnqeIaovyZsRR2waf/0yprqchIYhLXkYiwFW8T6gEXbVJIsthlOBYYacIXglqqpLhWq2OCpDxjn1kiHlZa4ccFhSCMzsyTswfDYXoJjllJfDk2teWM1fduVngBmxa2Ikx03TEGKVWktZYzkaXMUmbIha2VSdI+eYgzNDIggOl0RiwkwOkU1ZAU3JjBAYgFdTUUk5p1ykGgA5dM75UEUAwIdQ1szvZ4rzXwkS/hun/H/9uwjo0LW+vdptb272zvkYYtt0BJRT1qKgPvrYN03jg0MGADEVKSnNyzTXPJeyiKZxHoapzNmyuKohKxQLyluKuxB2EFofPCCoZM0Jl0QiwepG6zXqLcGdpyukqKopn4ZpmtL9PD2ch09Ph1XOcRzGx8PxPM5LKqLGyFJkmubX3/x6WS7PpRqcC5zVcdNhuHJy1d7tdm9+08Dy9PDL9v5j0z/UWr33IfqujZvG95G3nb+76vu++fX3r3/zq9dvv7ndbzvJ5XQ4CsBxWJ6ezuO01GqIxO6SqeiZkoGqIRAxMIDnNc/hEu+AyGssFAB8nbCEAKBaS0Wk/dUNcbh99eblt9/vX/748uVd03aXxU/Uxrjfdrv9putbdrykPC3oPcbIiGxrQj0C0Rp2g6uf2qoW01K1VlNDIteG5ma3/82rb377+s2L3a5vGgWnYOBMOCS1MeXzOA3DqJCdx76PzrMIpEXGKc1zNlVDYCLP5BjBrErORVR1vVc+m3OQEFVlnOo4FZGvFr8BGxKyQ9dQ7A3DOI74eF8qpOH8/h/+Y37/Yz8/8Pmxnh5tyUiMvuWAyIE0S5qGOdHm2l7/wce7+PFTl++vb/Sgw1PSY62hd8zRQXQEEdOOrWkdRIutU8S54pRtFlCDIEXO+uFnSaf88ZeZIi9su+smbHtoEc0hAgOrYTXLtvY56+cY7lVMsmZdETOGSI48cxXJKaV5kVoBwLFjvwYmaiZTMEU1VDB1TH3ot327QjBrzVqrVkVTMiWDNdSSVmMzAQEYQi1lWM65qhGz8+yjdw5gtSQ/i9ueu3rP/ND1F7pUn/bXvkUAJu5iV7tu08Y2OiJDSDnnUmQeFjTqu60LLTu6RACBMaEgiNbzPDzcfzoPp5znVHJWGWcx6nwTOStBJNj6sMP+mpoGHYvmOteaq8kcy7yp+QbqK28vmHYIVMpxPJ/Kcvj46WPKPz8d74+n8zhMS66qWTQXqWpr4mMBq9lygSzw7OGGanBUfSTaND3Hnh35F3t389rXc7u77nbXm/0NoGuJmrYn9kiuaZpXL1+8ePXdyxfXf/+H7759semDpiT39+/PGYralO04y5RQ9WI4ZwOP6BAcIws+uxoNL2yUtedL8MWkAxeXpRmYrlkjqmIGLjRXt92brvuulre//Zu2idvd9vJcmDddd3u1vb7dh8almrOqC+YDGFApOk4zrvr3C8HSSjUTqTUJmAIWs6wWHXv1t3H3+1dvf/fm7e1+H0NcBGspk+q55vMypboEx7u+9c43jdvuWh+CGo1j+nR/RLNVztUwt0ydIwUrGYTEzC46OibvPRPjyrYUK8X067LfMREyIBkhEInW6XzIOR+Ow/T48Okf/oN9/OnO5rYukpOBYiBmdiEoUl3S6fHppx9/2ubShEBhT33Z3ug3b2jm43J/mEtZKhds/HbfGVB68olSZVONgQAhMnpEyDiLFZMhVau2TLpthVufI0nwQ8UeXMDgiNSeJQeOXZNdbD9nqptarVVKtcaYyLFDJjPLOc/TvMyLihIxIwFiESmr+5FIVu2yVED2zkUfHDGaai1aq9Zqa3Dm6kKyNUD4YkPwTBlBS8kpFUMfm94HYsbVMvAc+vtfH/VfHL3P+5bZX8vIqGtaLa1nRhCTKqaqkkudl+Q5Em9cQHIApKBl7RZqXpZlfDo+/uWXd/ePD8syqynHxiBU9UgOWYkDKQMAStGkNUuuU5pPsIwhzW0t1yYvCV4RXqNEKXOaPx0Ov5wPP6fyfpo/nIbTOKeciwhcbNgE5JgIiFbLxjr1/vJaEZRQHUP03DUUAjV9UXLGIe72Vy9evqqb/twS3Vx3TXcVI++uobvCfnfz8sXtm29f7FqW5TTP47TkOakiG/jYdi3BmBMCgAiIMCIDBMcK5tZy18AzrCpbEMs5z8c8p5RyKlJ07YxXIQDvnHPe+UjkQsPOx91uZwTU9o7R+/jluXS+awIjliynaTqcp2Gal1RqxVJ0yRUBgl8LjjVLx6RYLlpMq4ISEGFw8bbrv9nvX19f3+72fdMaU1nm4+n00/v7H9798vHh0zRPkdn1bdNY27lu0zjvxdATpDk4EOtbZozeRU8+kJiKeXYoFS4q1UBNG71zppBLnqbq/V99GF3j2YAUQVSqLjnXkiw92mnR+f5R3/3YnJ+WNTnGlJ0xmGNwgVKBcVjmH375ZZy7l3d3r99cbTc7oqvrm9+GHW+eZrNPTydApBhuXr/eeTxqPuZhmaksgGLE63ZsCWgwS6hcbSlqpm0gVhKjapSNBRsX9oGdajJTDw6wU2z6qzty4fMKKjmXnFWEEEMIirCkNI7T+XSe5xnAyBEgiEoqVUzRudWeKKK1FKkVVNGa0IauaRvnHBGaaa05LTkvOaVS0uquNyQC9J6Cagy+iJhceESriYW+aPnXU+jZ9f885Lu4gREvFnzVz80YZu7aRkoEk7xMIhdG6IpnphhcJBcZnKkVrcXMRHQZxuH4+OnTxz//9MMvHz8uy0LMu91ViDvgXiSaIYCSZKnHMp2Wms75vJRR69ia9I72zK+c+8bRS6IWainTMJ7ePT786eH+p3F6XOqiUBSAnGcPiBcE65p3TIRABjWXDPylg8GIXeBtpM6bw6IGtgyHeyhWPLd3t2+d29acG8abzu+v+jYSty/I+c3+ervdQIyjlJRyquqaeNWH0G8odBWb+9M055/R1MoCJa1/YevJO7/Gv6xxL2uzTqUej6c//umHn979/Onx/jwO1aTWUlN2RLvN9ts3b//13/2b67uX6AmYq0rKMi05ePryXAjahoj06TAeh/TpeDqO0zKnWlUNzUBUCFiqMZCqkKJbs28JpcK4JATbRX8b3G/urr9/cbvpWnZMzFnrMDy9e/fD/+8//MMf//L+6TTXIo2jpu26DYaOXWRDy6V4J/sWr2LX95vgnYKI1FxqVXXRVUMtCKYIGlpqt8FFZ0DzvBweZbtbeYvPiz/NowFUA3ZsGoojEBnn8v5xTo+n7vERl3lGZoc+gHNrFBUAgqjOY9ZSNU9pGV2pdH3FjXfk2TggrnNgkyolS85AHL21DS6RpJIYVkE1WxRnsVFsBnCATqF6XPvsjjk2+/7q293Lb3bNdSBfZTYTACdqXanN/o2LF9i4qtZSa86qioDMrFLnaRqG8zzPtRTnL1EGl/BQZCQ2s1KKlqIrZ0+VkIL3TYjOx7ZponcEUHKe52kczuM41HkyK6vsmImCtyaEKqqlrKc9IJIjdvzfUPE/b1QX0xSsi//y9fn3105UqfV0PhNBrVlELuNBAwTKJeWyELHVUmq1WnIuh9Pw9HD/9Hj/9PT49Pg4LYtjD0ptz+ypKEjGukCex2XJS5rGZTgth1wnhEKetGu5bULTNRw8eLRaZJnyfFzGp3E4DPO5qJIHdkxuDeUDW/P0CQCBiZEZANbC5/NrUaE043hCRUwLEtfZHcaYEGIdrZjn6IIPjMi0FDJipQ5cKBjGAvmUNC/Lea5pQYDQOt568g1iNEy1Fp3rcD6dj8fz6QQAYqKiiPS5ACEEFa3z8tO7d//u//s//9N/+ePj4bjkBRxLrfM4omobm9/+6jc+dN8rhrYPbYuEVbVUIfocKg9qlkoZxvk46OGcj0OaUl1LwyoXQT0SWDWB1RGC6JAI2RGbEUJAumnj6/3227vbV7c3TdMCe0OqmlOe52kYzofhfJwmIeAYw3Ubr7bBN1RAFilZKgH0jXdEmz6GwAI1VYBJoQIge2D05BnbCO2G212gwMVwGAlh3PTur5J87j++MwBVc45yF0JgJBgmOT2k8jS7seRsAwhFuopEjKI1FSjVckVR8cA98KZO7uGndPp4D1zBT+A/TjodJ1kKYpkO8ss/1dz5DeTOmXRExmOGpcAicC46ZV1EF9CIROQ8uxBcEyO3zfXNt9/9/n/69e/+pgkbRhZJZmpIalCrsWt93Hw5+Uspta63bFMtuZxOp/PxVHJehb1MdInKjY0a1CoppXkYa8lo4JlRgZAvhzYTxrAO73rAZp6NfVbDVNUUbHXMkHeuadpqUMHEcG3DrFXkyhpYO01q9lUpbJ//pWArK9SeMcGwSkHm+fHpaKZqIlpghVUgGsDS1+AjKtZWPJEuS1nmaZoeT8Onx8P5+FhzRlWoomJ5WshGdpit5oWWoZwO5+F4GIaHeT4lHdWqc5BjWJZ+3mwm2420aVzrUSbLM5QKCg5dCB6tABuuyExat7/PLOIVVoDKxO5r8KDkMn/6NP/0F9cdzEVDVKbi4xmBLZlIqWYGDuEYaOh8Gzw4j96xPzITr7eqYZC8EGi76W+yhT5VxYen88PjJ8f86ePu5+tdv9tur/ZLLloFgdYjDRCY2UTLPP3TP/7D/+P/9f/8L3/+gVwIXbvZbdXsPKfpfE7j9Ph4AvL3T6eXb9+8/Ob1y5cvmdfi/ctXqfXjw/ndx8OSqFT0zm2ZTTQXHceqYm51JjAAgBhcjoGVCsMIFrfBf/fi+levX768u9vtr13TK/psUNUMsGmaV7cvphmqDZKl4bD33Ztu7wM9TlNNo6Vi1QWPRJrKUg24IXMKHlRBRcGQCNvGv7iJu6vQ9E4cDFkBSplD1/m/Ovm7brN2o4PjJroYnQsOafn4KddUS9JcbAFovCmBApSCKZsIiNgiKoxNFlgyWTbAucBSeVB/zrTMJiLBqy1p+vjQRI4dBbI+kogbsoxVT0VnQ4yhR3II0SCKEUARyVKromKD/gr8VTJvgiJopuDW8Yx6YP/VJUbMxAyQDCDlPI7DcDqNw7lKdc55pug5OCZCAdAqNeU0LvMw1VockzlPgIiLiBSRoqIILgZqmr5pI/s2yZwrTxmKmNXV7uyYm+jVVExSVTAFohh9G2P0PhGZGTyb25+jVC7tKABAA9FLPf/5hdRaD8fTz+8/5pRKLbVmXDGrITRtw+DykmrO4hIg1HlYxuF0Pp+O5/PxPA9nSUlL1VwQSH0WWNRRqnkebTzNp8fDcHwch4eczwIZUMFTymGoy0NJUYqWPNU+MKayPJY6I4uLFByjVoHPeOHnX/G5g0HEjo3Ye2b/uRcjtY6Hp8PHn7XpPDGYILOLXYixbZmQUjYRQ4RlsvFYGUGIlRHwoozQWmXOJpXA+u3mbs6b/bXzcZyWeRkJ8MPH+9C2yr7b7ZZcpAoIGJgCIlEIzkTyNPzxj3989/6X8zTcvfpme3XVbbZqoEaIDErjkv/zP/7zeZx/dTpWleurq263W6fAXzYysXHM45DQgicXvQPEWo1RoLKIMSGzERmgKTMgEqNj8s6hQRf4tuu+e3335sXd1e6qaTryUZFTkVyNOWw3+7ffvCnih/T+fBxUQao55QZcZ34WT8VprkIGpIZlpfoYoa6wOjMCcw5DoBh4nQPJOrauSgb81/0n93d//z8wcfA+sPOefHBNF3/58Hg4/i/5IdeacrEYUAkqGRnMC6XFVETREsIiJkMFgO06LJOKKVtaJFFJZMQh+IbAL9VSnReFhrrWN42rJxmqPFWxEG9vr7quA2JKCR5PWpfjOAwmChyO53e/fBDyJUlOteQMaD4yYpU67/d3v/ndf+82AS4aGgJy5LyaTeN4OBzG4TxPg4pQ1wSGTXQhuKo6TvM8LeOcpmmZpklVgncAwIQGsqQ0LfN5GKZlzrVmVbh10cem3/VZxnFOueRcQQQYiCkGNvBigXItZkbmYjTpNm2T5yWlRVRgja6GZ6MfAJgJACJWsAr2tfwi5/z+46c//fDjPM7LsuRlAdQmhOur/du3b25210wuOOcdoUq1LDJLmWuea5pLWuoyy7LokpAIa0EuWpc82/lxPh7H0+k8T0Ot2QAQGRBVbNH6WOe8yDDlj918temb4A1sLnLENkcAy4wFczVRXQ99vDTSL7oFIGYPBCEL+/BlwaicpvP94dPE7Ey1LN777f7m5vZue3PnQzyNeUlVDZZlejzcz+MwlVKkIpmqSq0migoERMjddnt7OL94/fLVq9drVkXJ5cP94yTwaUih77KYVNEiYEDE3nPbeNMynw+PDx9dDN/96vvf/+3f7W/uimEtUlOSlOuSH+8ffvjjnz9+eng6Hdnx73/3u5vbu7YJbp3KXDZvAAEPtAneOa9MRW2qxRP5DRug6gqdUcTVQoYIyETR+8jkHL7c7b775uXLu5umaZEdsKsIKVWp5sP25to3cYvU3J/mZV7O88ym131Ei960A3LFlZlONQnl2KkDg8mYiJmcR2J1hOzJeUgl2SkDQBI9Fx3nJY8lL1/UigDg/u2//d8Sk2e/xiw5T7ENvvnxP/6nnz7yL1UhCwhQBcoCZpAL1gqKVFAHg6XoWaCCbjyJh5x0XmROtmRMmYv3hsExR0WuZR6SFvBMaigE5ok9uM5vr0PfRQSSUZeBatF5qQAGPjw9ffrzn/7h6fhxnlKac0kZAEITmKvq+O3b33zz9vf95hoAAIm9R+cMMeVyOp2Px+MyzzVnUwHxHiE6jp5SVikpzeMy5yWlWrOZVgQirARmDGa1QE6LWWUi50PfbZ2PcbPZImUp6GgZnNRlJYU+I8DMUVmqKHHwHlu42u1qkYNUSdVM9cJAew73upz8lzv/193+Uuvj4fDTz++H07BMS80lRnd9dXW1v9lurm5u7vbbfdd2wVFZlpSGaTgMp+OwzuCmQXKyWqEKEFguCqmq5lHSMKRhLMsstZgBEdsqbjOrZrNoKXnOdki1X0oTPTEbaK6UIAgB8NrRl9Xbxuwuk20FNWN27MKaawpfwZPNrEpOeQIzp2KaCbvg9GrXvHl917Tdw2GclmJApyNPp/thGp7Ox1zyCpF4XnKIwOQiCwgy+RibzjEubTPZkkWP05IejzRlRQIDEGVA73wonGuteT4+3M/T1G/31zc3L16+3l3fVIVaVHLSqmDoYvf+48N4Ph5P5+PhUNJikqEkIPo8TkbE6F0XfRe9Zy+IaeXfGrrgAamUkktNxQzNB/KemYiJPFHjXN+GFzf7l3e311fXsWmACNBUpdSyRjB5H5wvzASmRcqQci118zQsuQaCOde0lLTUcamVakV1CgASvOs75z35C3IaFWTJNietVXOVWSznIlm0/pWJ1P2P/9P/AczqJe/ViIEZhqm2bYMI1awaiLmqtCwiZCawjpWT2eNip6xMOKoSyM6DCtSKSeGsMKoK6AKqLjRtG+Z8eFjmORtQ9WSM/d63veMudL0gTjlbllJQAMGqci64jMPDT//4n47ccE4lzSVPGYxCbJ0D4llL+rf/4/9lfSWE5GNkH0qtSy2H0+k8DKVWvBSlsOZfMyKh1pJzTqVm1QoEqKZatZowIJlbq1mRuizT+Tw03XA1tP2m2W/jpgt92F1vh+PjMh7rPNcySykE6BqKzoecxZCQOZDd3iHSktKSq2i1C90FLl1Bu0SXXCJ/nvM/AKCKHM/nj/cPTw+HtCTP4e72Zr+/++673/6rP/zdb3/z3c3VLgQqeZrLPBwfH+4/PD0+PBzGp3Mah1JLQQBGRAXNtdRUrdZFrGTU6hCFnQIokIl8oZ+aFcBabbJyrIObVognM6GqFTFRQKYVZErMIQRiv86zpAoxsfdaZYXjfT5gEME5cowsyo6C726ur9+8efPbX//6b//wh67vPz0ep1SIw8PDvdZlWaYxDQC82W42m82m2yDyPGVVpNDd3r363d/87u2bb26u9zUvmjO5EUILTY9NZ6ElF4P3rePoOHjvCBFkOD7Vh0/A4fb6Zn91VSvmufabDtiGkgsAxmb/4uUf/s3fj+cjYmXvSlnm82F+egje6+0WIACAY9xt4+6qcewQiQxJCQMAUYgtAM1L0nEeclLVhrmJ2EXHjEXUMbZt3G36/e5qu71C9IZoWs0ErIKpKk7z+OHTp5/ef/j0+HQ4D3MqE7A8DO/PqWFQkzEvY8o15YJiqJyN3MopboL30SOALllL0YwgVZZUShUFAxVY8SJfl/05LbXKPC8ilS7+vfrw6dMwDqnmdZNPgHNFXcCTObMKMCoNhiPgCESGVsFN2jPQmkNhNiosZqo6V5lFloiV6CSoyWAs1DB433Te7Ty2RFxUqhGAM/VgTCToACIpy3g+netQS5Ey1zxlEHa+IweE0zfffFvLhQO/pnE753IpyzwN47gsC5gR88odNgV9TvC/yCBMzIRQAQ1BzMC0ghI5JkQEYkRUBa2gggyxjU3TdH3cbttx206nbjod5+Gcp6mWIqqOBA2rmq29xU3IYo/H85TyvMwqujr71rWGF0j4Kky0r59LrfV4OJ8O55qla/oXdy+///bbf/X73/3+t797+82bm6vrJpBoTvM8T8OyzDkttWRQCY53vWuavuwgLUWzkkItMCdhKSzFgTg0YVRkU7T14L4kjpgCKJqY5Sok6kgcsWeGdT2LfeGmISE5IveseFjhKGRW1xbG59dCCJ7JM2I1Jmrbtu06zwxmK/+UEB0zEq7OU/ZuVWk3Md7d3H3/3a9DbB4fj8OwTEX77fb27u725q5t3FBSzrnU0vZbDCEBiiihucCxbbvGB2YGU83MqCII2Lf9pt84coHdzaZzRBF1mPMoQN7fvLhrWz8OB6n5dHhoSMfHg202+hk3ThiDC8FVAwNjJCIM6w/sHVGIvmOM8yxJFkJwDmN03nmvGDj0Tdc1Xd/2TWxEoZhpzYprXJzmUp+OTz/98stP798fTucll6pSAZ6mZUglECCoWCpr/ABoXpTBWkfMl56iIahYzqVUYSJRzetDA3OMvvGxC/R1w+///n/7v+ZcxvNZal4fSa3l3fuPP/z5z4dp8qjItBhYURb1pIGhIBwNDgLqnCNkIAH4pPokdin4FDJAUoBq45wfwTyYq3oCI0DKEggxoHdMjAZaSgGgECJ1WGaSwibsHF/1jd/y2C6ZLAhVR5XBKhF7Bc0FvuYOEqH3npnTkqZpSilV0eCZgJUQiapqLpWISzVEZkeU7ZIssIqCwcCUTBw57xwzxRA2fbvp266LbRNi49ouEgbrml3fztv+1HXDsR0Ox3kc05JNcnBGagqEyMih63W7v55yyVWKiAGuKSUIRpdBtBEY4+qefl78RU6Pp2XIt9e3v/n1r//tf/f3v//tb7959eLu9mq/7aXk85LmNAyn4zScRDSEuNnsfOivzKNrfOgBfC4yDfP56XR8OB+eznVcIkgATSSyytzRwUos0YsVBQiUyXDlG62bZS1S1+1SLkoEXO3PtaqZIBIyOXZIaGpaxaqYfKliLlA9IFMl5ugjGD0+PonYOE1dvxGFaiBip+F8OBxzKfac87XfXf/d3/39fn/97uf3P/707k8//rwsk9ZSSzrn8f7jx3c//bSU8rbrQ9vnZV40KS5Sy751YCglm1bUanmCkkiVTSJT38a7Xf/mZtdEP2zix6fTH395mMcRpCKI1DwOp/fvfrTpmJfsCEw+Z5MgGqrAlEUBonfOITlCJBH1FK53L7cupaGeZ3UIhmQYnNt03DY+9t5F13nnHZOCktRaVU0NsZRyOo8fP338048//eXdx2leCCH4FU1dq6oIXninctmtRdQBNV3sNg0FFrOSasllnJKqheDIEUfHaKAYIm63tL3p3Nd+/n//P/+/c87DMGgp0TtQK6V8OgyfHh6nnCMCETJoFlBRQg0OKsLZYAZERw0iAqjqUk3VWAwBGC4VNgDWrIMVMGOzuUhQ82JbMB8IAwpiVdWq7LBpWBzlWVMWywSOfPSxcdogs4igspkTNGbfGkIqzWZ39VW4IjCRmc3zPE1Tznl1VDtm9M55LwZLLqKwJvuu8WQrRNBg5bwCqIIqgnnGEELfdVf73c3Vfr/Z9DEEMFJxhMDEsSERyUVFtZoaKkyyVk6lllqy1oJaa3XON00bmySqpVZRQYWLjwcBPpOIvzr5TTSNxSm/ffn67/7mD//rf/N3v/r+u74NziPUtJRaNeW81FoQuW23DC6ErlY1cCG0m37vQyOAwzA/fLi/508hVTvPI+kCdQbJCKs+ZxXnXFY+IhAQo9FqXVuDVLSqgupzGikCoCle/GoMSETKyGCKZlJT0Srw15oFJmbiaisQrYzjNJzG02k8nYem65zzVWFJaZzn8/k0DGMpAqAp5ZIrs2uatus671yahmUePr7/WfNS8vxw/+n9L+84BARrAi8iVVWskhYyKWk+HR7LMqLUZTzl6dT44Mn66G92m+ttG8kiKvfNnDOB5mVapmE6PR0eP+kYP163nEZU6Lvu6yTiFTRrBoYEhMTEzsCgVkGEtul6v6kpnadGYHGOO961bhtDE53zKIy0XhhIBLRALbVKEnkaxncf7v/0l1/effj4dDpVQSa6ICwNxMCMLvRZVQAgAnIUvAveEeEqbFddNQ7AdJnGPpPugR25SC7+lc3E/fKXH0XqvCRVC45BoeZynNK85KwGCLQCJc3SmrynYAgJjTw0HtiZioiYIRawIgaGjsk5CoxoZBUW0ZSzmpSl9mi9x95T7Igamsy0Ahl55q4LppwXk1TKZIW0IAQO3jfkSIXBIbcUXGg2vQssUN9+/+vYNF8ejFnJeRzHcRylrq10ct6H4L1jA1xSnpdcax7nueR8Of9wzZkyVFMBYzZVBAjebfvu7u725d3d3X7fhUApSy5y0eJazQWMmEPoNhGgECKAaF3ycl6mYc5z1rlIKeqd3242iHgcTlorApCBAa4o0eec8r/K82WlfbP5/fe/+tvf/vrN3c02UllOyzmJrfMOx85tNhvoe6halrzMU05JS/Hs9l3T9B21bcpl37itYXNe8DDMDDOUM1RQUHBqtGJMjZ/lKQiGF0uCrR53Xn9SNVG84BpWNbRVqUorsoyUVyW7lSVblUsLY30lROwcO1eAllTK04GQQSAEP0xjiAHJlVpP53FJSS6oy4IAUk8///zLP/3jPx4Ox2maj4fHp4eP0zShlk3flrRM43g6HV+8etl43vcdeWkLVMXY+ECwnI5/+qf//PTxPUpmEEfU3b1oHO765tXtvothOj4taM1u7wij55qXX/7yw8f3P50ePr642nxz1XRQHXC6vtbnk98ABcjI+YBI2AT2DolU1QSLYVLK2/76b7d/U+bp6elTqRLihn00Z0TVREwKmrAJSgHJUEuZ58P5/OOHT//xv/z4w/v7x9OSxdgFNJCia6ovrdY8AFureDB2FPsQOyaDkkpeDAm8I+9ot2kQTQ3qyqlTBQWpUjLU1d//efEP56OILLmaQnEOFUouy1JKvQyeV6iYoanjDFZXvBhzF9x+F0LAWmpVU3SlYkoiVVGBHTWBtdo8liXXKgqA5DygJa3FKDZdf7XbxK4SSc2x4f3NFshtNuXYn47ugzPd3F7vX1yF/Q5jrBXQyLMLIcQuusCG+ur1d+EZBa1qpZQ1KzLnvHqz2XkfYmwiEdRSlqWsJL6UU6nV4DlkE9BM1UwAilRXaxW50KzXZPpSdF6eC2QwRCAuUlMuS6lTzmPOQ0pDXsa0THke87yUnJKYYuND1+5e3N6cxtF+soOo1vp1fg/9i/heQgzBbbbd3e3V9dXGO8vL+XR6yHkhhz567ztCx44AWMHEE4qBoBZVfQ5YJ/WeNl2sm7a0cWn82fPAcBSZTKuoACO5r7Ydfc7ZtmfqD8FqiSMi0IsNBmCdTpiJKRoDf40iVDVZieJfWxXcin1TA60CJlYt55xyZkcGVGqd5nntRH9OOkiaHx/u//mf/uHx8R6Bnh4f83yeh/MvP5UQHBqoSi0lL8s0HOfzpgiqoBlUcYOmp/uPf/njP3/85R1Kjp6v9/td36upcy42MQSfJ8ul2pKWXMWwSj0dD/cf3h8//UxpOzy9mTdt5FDT8nnBGKyh8ewc0sW7Ywi0uvzBKlhuG/dy+4Ir7EI/jFNRmjWP8wkxkUcEAdB1MI1mZGo1L+N5Oh+m8Sy1NME7h2YoVRQU9FJGIShcgmAAEciBD+Q9MV7oMMwUo28Ce0YzSVVEyRGaGZkiyDKmaVj06/RevOBvLqnTa2K8qqEiKwWwBqAHYMeh8TPgeSkCEELY7bpXr/Zd4+alAGDTtga05LLMaR5mNOv7mHL9IE9ZxIOLzvdtCLXK+SlnjOH65evfXn//vWu7ZToTaL9rnQtV+fjp4S/b/yRpfvXmxYtv3tx886vQbpaUAdQ7h8RAYKBmebd/6Z+BkKoyz/M8T6UUVSMmH1yMMcTI3qtornle0jROS1qKZFUlRGRyfKGWq2muYpCJ2HFml9x5YGapIkva9X1k55gRGNiB96nWYZyfTseHw+Phklk+pjTVWkyFGfrWMfkYu83u6ubly8MwllxKztNamPDFbvnMKvkqj9BRtw/dlefWis1P508m+fB0j6DX11dtG9ZuidSci6WlLkmWnNOS8rQ4gyTW5ELTiAA0FSi5Y7yO/mXjx8gHwbHIIiJKxArIz83GNWzAAFcD1MXwTkQEhsCmlxhOeE4mgEvzD5l5dTSIyNod/KxawFVSybyqIX3rAaDMpZQ6L/O64cKzCJ+JwOw5zhWG8/G//NM/vH/XNU2rKh6ldZCGozje7nbBu6xS5umXH/88nE4VneJFgOgQnh7u3/3lh6f7j6bincupbHbXY8qLaFKLHNrt1bIsx6ncn+cpS1EUBal5mYYlaJkHybP6LwKt9Q2qhmIrjc1KBSF0zpuCCoIoafGofdu2vmtj83Q8vr9/PD89vDv9xXGOd3dI1+tcZ03YZVIyRJWW6du7622/ycLDkh8P52EoZXV7rWm2CGAXmAYSIZuCrPV8jOyiC9F1beMItdRUTECBsPWBmRgtL9Ph6Xx6XGr98nLcm2+/r1WWVEwxumBq0zS7p/OxHCTPDOAQAmDbNnevbieid58Oc6l929zd3v7mt99fbftxyoDYt52CDuNwPBwePz3WnLu+oSUhAzLEEHZ9d7vf4pwezqeUQcD7ptvf3ra7zXjyVosL7Ng16Oyqv36xrYU3N227i20fXGQgUxNmNYMiUmsuMvsU1erz4td5nqZpqlKZ2Xtu26Zt2xAiIKjp2sQe52WaJ5FiYCvGAyIxERKDoYqKQq7COQOxAVbRWqrmkrabbdM2ITB7Y6/sxpwfT6f7p6dPjw+n8ynlJJrB1DGHGDyxA2Ry3jdXt/vvvn97mpb7j5+mcXif0lTyf8PH//mpeNrf9NPStxsHXOc8lDyPy9kTqW0BVhyHzDmnVFO2VCyrFpGiRmqWy2IKeWGzJiulFEy2jHfRjU14rPlcYLC66Dpy4IvsAJ7NBuv9HxkUaL3YrmFKq+Tm61jCv17/vAamIeJXvlEzW82RYMoEwXsEsFy1AhKtb1Ab427TNU3jmVcjZq11rbyYsGnCdrt1jmvezdN0Gobgwzdv34YQhvOgBpHR8uJ8KGLznJacpeTj8TidjlLKymU1wKq6lDou+TjO5GKDvqKcpvHxNByHaV6SaW28u91v7676TROio+jZuS9SZUbqXdiHgGQGWkUNCI0BKKJ2HDc+bmPTNm0MbVWBecxQhjwdxiNTvtl049qqkbW2YkNCYu/8frtpu+1cbUzy6em4jON4UX5dUNgXG/gKdXbrw6kKwMwh+Nj6GF0MTICiKsrRoxE2sXHMBIoiDA70r0pM9z/8b/6PopJLIcQmNFLleDz88c9/eZj/wzzOBggEBrjdbX/zh79JzBn++HQ6b/v29Tev/vXf//2bVy/GMata8CGl+f7h/XtPZT5PYyInClJUlKDbx5vb3eu723qan375tJQ6LvMwH8/LJ2nGuZzyMusoUFXFSlqMBtfWDOfDJMPPT4ZW8iSSzKqIlFpTzlMa3r79+2+/+e83mxcAoKLzNC3zbABrr67r27brCHFJi4iscvRcypyS1GKIzBoAgF1cGUyIxAamVWxKpYqVUlPKpWQppaSlbjdd17KPRi4JnObl/vHp4XB4Oh6WtDBj9L5r+r71XYyRmU1NTRR2Xbjbb7abzW9//d0wng+Hx2k8E6w3/Qvw0C5m4XXxu9sXe9Hr7XUbWgKpQOIDO3bIWLWOy5xLPQ9jymLgFZ05ViLwHsyEWUzrUqiIZInz4nLpze6CT018rOlQylMqo6jJMzFlbT4AwYUWbJcwKmB2SEhMuCrX1vDqdVX/V7vAJdOamfiLkNRUU5rTPGrJjtChrRtJYGrbdrvfvbi9ffny7vWrl1f7bfDeRKd5yimrChGs8IX9fk8E5+PpdDodz8Nms/n93/whNu2nj58Ox9O0JFHzIZ6G8c8//jQdHqZxnOfZI97s95t+03Vt23Z9vymih/PgH5+KwL5tcq7HKR1O4+Pj0/l0MC03+831N1ffvrj69s03N1c7x03bNvTsU4rMb/pWNlsRKaKZLZsVM0MLjm+a3evd3e3mpgldEn2cjh+H+0M5TbZUsFzs43Hcb4bvprTphInVsBgAu6bfxLZv+z5V+/R0rFJ/dgirGVjVEI1ojQA1ISQgT8SmJmq4Eum990RYc0UzBmx9aCKBI3IODa2aet3t99v91/QhcC9efSNSU8mE2MYotfro7g8H552ZVsBsWB1RG3c328KubeIwTt6hC+gjugZcVSkVSA0nxNmF1G5ETBRLtVy1ooN+529fb968fTk/zX/507vxdHwczt3De76nroY0DjnNUouWalXB1KE4D1OeZ2E1EKtaF9UsUkVqFU05jcvQtte1ps8n/4rObJqm7brNdtu2jfNORMxARGutua5Qn1JrNQRepybIjBxC9N6vH1YtxcyqGFVhkiWVcU7r7WCqldwigHOq52k5nM7jPJla17TbTbNpm74NbeDI6E1Jq9aaau2dNiRNbH/7/TfD+fjTTz8OpwM9B3uuHdyvl1Lw7sXdNdqp7yKR1VzMJDQxhuhjVKIl5XFaDodzqepD60PjgvOOmMLarFPV+twgJjNv4AHZudJ1J09TiGdyeVzGVFXq5a69yvIQgND0c74dmNqFnP789fWCX/8uVSWiNbxg5R1+yVkwlZJMSnDUxrDt2xDidbeJ3l9d7+/ubr959eqb1y9fv3qx322Dd6a6LHMt1UCZMQTfNM1m24PZ+TgMY/hFNwABAABJREFUwzDMS9f3v/71b33TPD48Hg7H02nMpSDx4+FAJl3gYZxLzmrQtu3t9c1ms3EhNJttf71D0NPpVKvkrpcq5/MwDOfxdJBl3DW839396s2LN3dXt/tNG4IKf53D5Ilu27b0m1JkynVMZZbqQAipC+G63e67fRM6UTsv08fT/fvjh4/nh+N0TCWr1MMwPZ7H85SWLE1gABRDI9e0Gybqu27K5XAaEJ6zR1YmICIQEhGsgaMEKzFA1HKWZamEpRQlBCmVwYL33jF5pjWpBwgNCLHrY9839LWrL6WhlDpOs5nmJqjWcTouaag1FVFTBM/e0exs1EmMpSSrueZ6Or7/0w///vHYzsNQcwKAWktKcymza6eG6jDVInO1ws5tr/DFm+7b374eHtP2n344pvHD06H8OC/xqbviUkaVjKCkhmtwrXNcEBMpgSle2k54wYWZgYKg/fV4DEAUkF3bbXa73W67dd7lXEQUAMV0XpZ1BLiqJBRUUNXMFJhc17sQW2IC0crZVBDAe9c0TRNb4pCVDnOGpahZrnWal7TSwZy7udrdXO1fvrjZ9q0D1ZryeLZlZMlmxaGGOsnw2Fzd/vrt3ZK++y///A/Hp/t5TlLruoeron1FHwrev7q9dTq03pvUnBYw7bq+6zfNZidq83Q+Tvlpyiq6RRdiaAL74EVEqtYiJoYYHGtD0ETz5Aidp2C91/YWaln6g9w//nz/VOb5gvR+vqSbqVU0oovyoaqiKuA611kfwdfpA4goIvhcEXgfQvii7Tcw0OoZdl2/22z3N/ur66urze7u+vrFy7u72+ub66ur7XazaZsQmJAQ1AQRmJEZ2SERMbMZlhe3tWoVJRe6zYZcuN7vRFQvNVp6OhzfvnxxOJ2yWC0ipbRN8/LudrPbsvfZ4LSU45SO4/gwjFMIpnae5mU85/EYIL+83b292/3mV99e77eoRVJZlrws+XOTjIk2TXPdbXJVtiWPpcyVyWIMu9Du200MXSWe5+n+/Pj+8Mu7x3cfPt2fh6GWRACj2HkYpznlIsEZrkgM5Bg7M52XfDgND4/H43mqiuSjB4eqegG9ACDYKncmE7WqUERqHpjmNVnOVNlh2wTviR2QW8Hh3ETXNOgbaFrir7JI3cf3P5RSh2kG0K7xADJO4/n8UHNWtaogBNwzNrrUUxWQMpNkBiz59Pj0l7nwMo1SMjyfOETmohFYGWqWjGSxoc3OX912ty+vYixX32w/PvlhOOvj0j5VIRZbECuBOQDGlTDrxVCLKYIB0tp1Qlg/cvhM1KGvHJdIGGPs+s3V1dV+v2vbxsxyLlVEVUut0zRN01RqfW7Zm5nWUkzMuyCqgOR8BF6xZGCqZojESM6IK1CtICpVLgRgJNps+75tr6/2t9f72+t9G72VvEySRaQkKAtZZUSsaTkfXIy7l6/evLz97a++PZ1PP717P5xHM9OVyfvVgeqdu9ntLe0jOxPVqszUNF3bb11s85LHVA9TOswJzFzwjQmSOY/sWJjADNARuGjQO2oXYH8C55ULeEe315Xx2PST90POi2QpX3sK174yGioCwyXp2vS5zl9XNa1EhUs+yeX4r7WI6Ep2+ny1DM7d3V396vs3d5v99f7q+vbq9vbm7ubu7vr6+ma32276tm1CCJ4cE68M2NUJFxzzWkCsny0Cu6CbDMmQkZ+x6uhEZFmW66v97dV+yVmMVFRKjsFf73dt16HjMZePT6f3D0fC4zRnR6pgfUDrPOxbD/z9VfvN3f7Fy7vgwzKeFkkpp5zz5zeHiGKIfddFRQSX5kICyBibZru9bvqdsZ9yfhyHT4cPh/PjMB7neShpYTJGWichK4a2iojU43BelsR0oZhXVWa3hpGsmOY1hs9gBdWt/RioIlkkqahqwoqGIBeHBRH5UJxDYnMOY/BN9H0fqrgeoNa/qtvcP/3n/08VWXImsq4NhJBSfnoYS0rrgRs87q/DZmelPC2TWJkclNZxdEn0VCoJVltFdAYqgAzAKCBzKrmI89z1od/Gzabt+54s333TfPjkx5FyArQm+oAuEFdUcwYOjQx1DcBTtTUDEdBstaibrarYC6rpCxDSOb/fX7148eLF3V3fdQaW0rLawkotOeVxnKZ5XlMxGNckPlO1XNOy+CWltq2xaYGwmuVSTSqgxVJjVEFcB9qAhkaxCbud67v2ar/bdE3wHBwhyDInKXkez8N4LtPoJDs07x3UejqfzDfNdr/tun/9t/+qCIzDPI/zxd2BKF+l+TLxputy0yFSFVsxYqFpfWiAfJZ8WtJhnE5LQrSmuLaGojmAc+wIQasSErPrkLfq24W0O0ucc87O++1m+6Jvvus3Z+8exnHMy3CeRCoiGKKZABggGiiiXib7F3YLIDIzfa7/v/AIDUREpMqKNvxSFkDXtX/7r/6mZXu5v7nZX13f7He73bbfNCEQAxMymtZcDI1I10WgDGBQSBXpQo9Y7yBuNeoD0BdNAmiFambOu/1uu91szEAMDQxFGcEzEqESNjF47/uuvd7285LNTERyzmnZLC93kfTVrmmDE6J5SeO4jMM8z0sp+cuLQSQfQtsFYvYBTOelVWBq+vbqhvrtYngezu8ffv50+JCmM2ttiSh49kjIYK6JsYmNc67UehpOP73/+el4rFX6tn/z+k3X9t+89ln0z7/8knOas6iZ9wymuWQz884pwFLrnOuURAFax57XzxBUhZqljhnA2EEI3DXSNVoy5cWWwU7flFq+cvUt+SAipRYkoBIIrBRRSQjKhAgQGt7sXbtFwFw1A2YiIUJCASiGBKhGdpGo0SXcwQBqMTBoW+43LjbkGNDMe7y69lc34ePPKGpS0Sp575gQLgPJZ7+rmSoYfu5ArUAnM7OVKQgmX3eVnXO77fb66mqz3Xh2S1pqraoqKimlZZ5TWkouttppkAzWlomJSMppGAbngwsrGDKYWUpWVKacOSduGjKjS3yFIJJzPsbYdU3TBAJVlVSy1FxTGsfhNI5pHEkLgQXvcREY0jmDcNNu969evv7tmP/8578cj0PKuZZ64QTBl89Y8D76sEZjOvaOA4KrYinPx2E4nofjeD4vMxE0mVxinpwSdE0fyMcYGSi6pke3reRby12rbYN54eB9DPvt5s3VfvB8fz6OaSo5lZwuANGLQXc16tNz/ig8h4/Zczm/7gUrG2UVSV1GgVXqV3UExBjevn3tIb/Y3Fxtd9vdpu2a6DytdmTTzwInfHYNAJIZq61YcbT1+LtMAy9pnAAEikgICgqrGo3ZOWaHSGLrnzA0BRVb9WlExByd671bSln56yWXkruaN2y6CWwqpyWVIqVYqVZXS8MX9BiwYx/9mr1tqj7VJCw+amhHsWl6fDw/fXj46Tg8lDqjWfTOEZNHAywFL0b8qqWkx8Ppp48fPzzc51Lvrm9vXrzexYhE3jsRSTnnssqpDU2l1jUWRg1KlVIvDGAVq6a8FkiAplaKiipVW6mBAAwgUm2Z6umYa/1qzv/y7Y2IXnzojtG0prwkjHEJDog5ttxsuNk455gzUYNWrBhUIyLvmKtW0HpxrayfG0VQQiFPHHvabsij1DxP4wBmm5av977b4DTXZcnTAA6VvdZqKpdih9fndhn3ulVSaqKqYmaEBCYiRUp9HgkDE202/XbTM3ORMk7DPM+riWde5mkaSy5gqzSSaL2LghEYIpSSD8eDmBG76+urzX6nIsfjU1rmc5oFjWNk78IqB9Ba1BYQtAqaB+8YgQgcmamUvIzDeBzHaZxKTiKKAAYE6LqH6f5cXn3z7dvvf/XqxTffvvnueBzef/w4TtOqT9EvZ7+BAa4dHyMRQKJaJJXhaRw/HZ4eDw+n8TQsMzniaNVpMpmq3O1534Vt0/ah3bi2U4qLWCyla6BroDToiAjb4F9d73MbnqbzsIzHw8M4yqXAJjRQuADKwVDWYf8luuci8nn+IT+3LL8wbURqFfnquTBvt32+2nax9d6pak6pLokIiJGZnfPeOc/s2DEzEsOqTcVVCYm2IiMvIOPnwdsajPqsk1ivxVVBtK78DQDF9Z6w5vICqJlHpMAemqIOzMREipTc5GUuaakpp1zKOsGjNZLk67RfQERH5BiREdDFzbYGS8myYk75lMYPD788Hj6ehodSk/MekUKMYEiMRTSlkkoZUj6OS17mT4/nd58efn64r2YYu0Ik5MZlOI7TMC8pVTFSQCtyCYIwrMXErKoy0bbzABdYn6gQoneOiYGgihrqqqqqalXUVIe6HE+LfL34mz6IKFVSNSAEVUJo2tw1NLdMTE3HPiIFRALyGHoulcWgFgBdQ1tJgVbY+arPslWOrOYImhbbaCZ5HobHh0dGkJK806bDolaKLFPpojFqrSqi6xHAl4+UIhEQEIJVNV2FzbZ+yrRWrfIleh0xeOeYaynzMg/DkFJCxlLLetuvNYMqrQgyuHxcVnWdqKR5BiQXggu+225i03Ym5F1OiyCmWnhZKgsCSC0AWjPmTMs8OEYCY6bGO0SrNY/D+HQ+n87DtKRcV9AxAlBzSk9jrRC/+fY319e3v/rVrw/n4el0rE9SQRW+np+balWp7PyqPq7rYK/Uh+H0eDwMwzjP85wWQAPUWmueswl0cbPtyMem6zYb37WCBKnGQDFgE3gJagaluFw2RHeb9tsXNw8PN79s29P5WGRV9JMBGyiYgOJqQIJV/A/wdfCzrSwY+4wcB0RUxRWs+FcrBsHMpNaCxcBqRQZgJh8cIupFVLhGHaxDB7JVyAXPy/5ZCgUr3cS+bJGgdvkRAWElul6yERQvcakEpqJrzYgrA4p49aRwBWMjrKyVkllVBTBmDj5qI1JzCOGrMC80csYBXVj1dlXKUKbDksaaHsfD+4efT+eHJQ2q6lzDHDyTZ0fAZpCrjEs5DnPrxrwsT+f58Tw/jQkQxlSXLMOUPjwcPz0dcxViJmU1KLUimCMCgFxUDZC4a/x+2wPg4TzNc1apgOAQHBMQOtUqsjZfFCBJNZE0z8O0fG24dLkkUStVRW3tLQAAedr2rmYBxrZFZFATUCW27S6gwnKuOalmhcLOABGVaHWrwaomLhVUCCV4dFzLMh8fj5rfE9g4PaW8hAabyrVKWqBWcN5Eq66wBcCiYmK6IokUCMFEDPSSML4KTFeu71cNDFMpaVlKHsfxdD6VWnzwS1qmaZznqdYKtlroEFYxv+l6uzEFUUvL8vj4iET9dnMdb/bX19vddl6mmnMxPY8D6qX0RFwX9OoLUtPqiNsmOCYwnebp6XB+Op9P85KqPse6sZ/0OEjTX89Lefnq5re/+5thnv/4wx/VVFae0+cPtWopS65zQKiiS17mlIvZnOt5ns/jklItWZe5qlZNVcakcWnByXVBRAqBm4ZDQ4IoBtFjcM47dK6mXMbJHGPftIFfNvHt1fbHq83TMT6NU6kK6OFZ8WOi61YMAIJqAM87FALY5w4/Ea8KP0Qyy2Amop858CIyjOPT07G6mkIObYjBN8EhelUQsQxiapXEiQT1zIbESIwIhorPMshVQ7DSjy4/IYKqIMElU5YuxgNCQAI0AlA0ANMVsHWJP5bLzAIBRLXWkktJOeVabQ3DAg4ePTrHSGRd3zNdWuQKVDAU6p2PYjjn+bhMH54ePhwfD8v5vJyHNCxpLlVy1lwmhNTG0IXYt6GKTnMNlJ6Oo8eQczouaamo6plIC51PU130Tz/+8vOHR0DXb7ZLtjlLrrYGRprZUgoAdm283mzevL5Zo8pqtbmqijlDRxQ9ihlmM0DvHSAuOee85HmeU/qrxb9GR67C7YvbDMl77hpfOjGyGIBQTcUACaFtnSark4KAJNFEa2hlziqiYBe7/DTWnOuq7EoJHReTaZmfACyXcVoKMziHJcs02TSTAhQRQCAmRBABKVCyEYJFiB4dITJdQqLB1BTJ+4s0fT2ItJayzPPwbOYXraIyL/M8zzmnC88DiJ5LVoUvt831YzqP48G5zcMDEm22G+9dCJGQSkqixUTJwIjWk8xUwGS9OTLinJ0jQoR5np/O42GYT0suCs5zYPRMVSDXdBzn87zsq7gQYtOscQP/VXovgIFV06LmRLVKnnOacx7mfJ7n05SGcZ7mlOYCqkGA2GLkzoXWxybGEKNrAnkPAlAcBkfBYXDkGBaTeRE06Dz0cYN21zWvrnYPh81UUpKqIAbM6zuknzO6VlbJamu4nOQX9w/CmhuyhnYiIvz1azGzWiWVEjSTsREgone0fm81EBEwW8mqCKS2xp8LgK37yvqdV9XC8wQRCREUANTkOQuBLu8cABBdmgS2fiD1YnEREVunlaoIoKJSq9QqompgiETEZit+GFR98PyVYEkNpmrHRaDkKjYu6bSkpLnKsqRzThOhRu8Y0VRSqgboOUQfPXsEDS4weTNMWc5TOs85KwLH6L3zvtRayvnD09Pj+WwIXdu0jYtJ1LCUjASqIobMFGPs2rZvGjFxbt0onaJWAUOjZ5U2IzKRIa7ua7AvH/XL4idZicVgBOs4zci8kyaEHERQPAOpQqmAxIqNQ42UPRGCLJIcmLNc5TyUlPVi61BNs0yjVpFiuihU9alU50Y1KyXnpKaGZstcaiIfYkwgqojmPBERKOaE41kJgfYYN9T2Pnq8rFwwIGfA29Dys/rK1HLK0zgOwzClZbU45jpN05RLWjXn69m0XvjxMyDX7FJZGojqNI7v/vLufBqur692u23Xd56ZfDRyoIoGhGCqIhWI0ByoGJCaLEUBqpnNczrPeUolVzP05KKLbfCRkbRqAXyaJv/4eDg8fnp8zKUiEKiYyFdxUcC8MkeqmCmYgqRSpmU+n4fjOB/P45RyKtI417Thutu9ffHi7cvXr25u99td03UcAhAaGAXC6CB6804ZBa3klMYkn2pdWu6aradvbq6ehtNhGuaUk4hZBSAEvpwHprCm8iMirpp/VH0u2C8X7Mt2IJdX8Xw7uzTJvPOB0SHxc6I+roW6AVxExqC68gINANd5gRJRjNG5z6K0lXEEa62x7tcAlx3IVkmBKiAyE6+FAtizNGHtSF5Cky6x/gbrZYOImEiJzBGDga11pdQqX/sUqspxTu8eTuNSSq2GClj6bQC3VUrRI5GpqRQbUzlQZnYvb2/6pkGzlCuT38T9vt96F1I6jnOpxi7Gftttdh0HSzlNMk2yEGIX211/laoB4HkcDapWIMfOu6aLPriUS8qlJDEFdsFEchFNRVUIzTuMAcgACdU5tMYAu6Yh+srPf5HGX5gvALS+uUhEjghIEFRLKYuiERqtE+Su8Y5c37SeYclznmU+lvMsuegKEpRiJZkYLgVSFi3SNtn7Uc2WJalIYAAlqKBIeUIGYo6IKoJF0QRKprJgdMwWW+evWuobtsvkuYJWcGXfdO558atqXtI8TeM4pprJkYhMyziOQ85ZtZIBMD8vsHW4/uXkJwQzUICay7keS84155oyqPVtx0xEbECmkqvUywYmvJ52hkgOERDXaFOn6AwdoCE5RIfk0HtiT8EywS8P96dpfHz49Jd3P0/zAgDrLgRff6lplZyXOddhmsclLaVkqVWlSl2Nr2jARNH5JoQmxOgDI11oYqoKq8u7VpDqUVqvmwZAMBmhWWDn2Tfxhunb16/GWk7zogKHcUnZwBRsXVeml7s1X2DGdOnzI5LZejGDi9vHrNYK9nUJA3hRoAaP0XNwjpkZEBVMRGxVdhAQsRnol0Na12vFusLXpb62FZmJna4CwufO4mXxm5mKGoAyCRLzarK+bCoX5IQBrk8aTNSq1FpLqaXI2qowR0SMleUiqvtKSlZVTtP4NJznTAbgPQRPwTuEmDZ98MwEqpazOM6mmZ3b95s2BikVkcWob9vYe0RSVnDYbVpy3Yub7dX1xjU0lpotZ6uRQt+23796oUaqiqDnZbIqMbjgnWOsUk/DlHNVMUb6/7P3J82SbFuaILSa3WhjzWnc/d7XRbwX2UgiDCgB/gQiDGGKCPWDmCBM+QX8AOYMQASKIqWAqkwyIzJecxtvTmNm2uxmrcVgq5kfvxGZWWMIfVf8HTe3o6Zmpmvv1XxNARW1dluUWqLnXd/vx9h1nSHAmhkodv6wG91bhF9T+GpIbrjSBszqZu8LoqLrorUSSlsWkMCNfb8b9999eASoH3/+Qc5zPtf5VE6rpGytu43ozCgL8AXqXMZh2Q1sZqfzYlD2IzO5jo2AfOVO3GEcDOE053mpOQkIdc4fhni36x8P8f3RH3pP4MCsSjYpUNNdv/O3lcy0pHVdlnWZs0nAUKRcpsvlcs4liwgSg9k12d8McxFbBgmbpyKSqmnVNK8nBRRjIDhq3/fsWM1yLtM0zdM0zbOZhOBjDH2Mfd+N48DMUouR74oVJcOi2gQCRdScp9CHgvB3f/lzzenLx4/Pnz+dzmc080j+DTLG1CTpMqXLml+X9fkyrSLgPDD5PkaVWLKCmUH0jgMp6JyW18spvgzeB88hKBE7qbVOc05LZpV9QHfk+76XEgktBuw67PtYBYYBfKgKgcIff/j4LFMqVU2UHACJQVP+YETmplrT/CjwmpBb2x4bhhpaYXRdyhDJ+RBijNxFjj4454gIVDVJJiLPDj0xo2FTvwWRWkq5uqhoCCHGiIiiigiAjApm7lbvXR14cdNBVGuOqdyM2NTaGqgNKwpgqq09JaJVayplWteqQoTecwjRExKQVA3es/c3DxKRer68LmUexu+6bvDOwGZZn0Vt1w8xdoZQqgCuRbgfPAIZYKlNPQ6QGSPpaMxKexwsRu27Pr5/t9uN3qHJVAWbjJHbjbu/+e2vHLssOdd8/nkRtSHE6NmkXKYsqqZI5IL3l3VKKUlVlSoivvcP98fH+33XxTWXXJ4Y7eFuuL/fOf8G2+9ai5U2dgkieEIhcoioYKYCtRBDBVJkRucoeBdjuNuN98c7NC3TLKtodlZXtJq20S+oYSlQimkxQUNn/WjMqOzVMBo5omFgZuo87gf//tgbIOkCJVnKyLgf492u28XQue2/QB7MSkUBNLNAb+ox1ZxzTqmWIiaFMOU0X+ZlXmoupnpNMhtMqgGi7M3m30RqoEF/quqiykR914UQnPMGlkqZ5vnl5eVyuTT/r77vBukNEL2PhszeOd8BDRUUmGgptSIyGNRa0VUGn0qenqbpfH769HF6fZW0tsSL36AVVSHnOl/Wl8v8+Xz69PKyqoR+QB8MiR11vUcCE2OEWtN5AtNipsw+uND7LhoRexAp65prKYwyOAgdYSTG6IPvevYR2YVcIYQqsC5JV5WlYJWXy7xoragKdPO1RgBHDXChtunJbMB3ay1+uTF0f3FcYVoAVdWqqlgLS2bGiETMZACi1jrGAgA3Oo1dzY7byc2wQbcArJRqopsRi3MNiKCmIu2X2q+rSK21qjTxWVNtOz+YmphIFSlVtAITMHlmR4wmhSvSNzQ4Uy01AcjhMB4PD97Bujx9unye5rW2nMQ5T6BCor5aFjGpCgqE6NgNjvsuAKt5DSMdsHPcD8Pw+Dh4j2ldyLnDbo/q9nF8//h43O8JYDfEcQi7viPDMXpHUCGLATOTc44DU53WVGsFZgSHBA/H3XfvHh7udsQ8reuyrIb1/n48HIZvHHtGDkhADg3N1IggRvaZXt06g+VVKmk0h0qOqfd+13VdjI79rucxuhhC5F/fH3bvnk/nyzzNJRfTCstans/z+ZJZAYAGzw9D+M3jMHR+OQxrSrmsSDAMXYwc2A57/927EZCD89Etz24mtMeD3/XsyCxLWSVjJU8A2uC1WkqpX+sxMys115JBzVTTkpZlXqYlrUlFyFoiawRm+FUuV9vE6jqxVrENnWZQTHPJqeRSs5hokdP59Pr6+vT0PC+zqbJrLrkMREoIxIPZbjfGcbcDQnZELqesZkW1lFRVDJQdm2lKa85JpAAoogKqoV39L0DN1lXOl/T8cv709PSXTx+nnFzfdeM47nc+xKHzwXNNuaR8ulzOJ3t2PM8TI3cu7kPfKaEPBCClGJp4LuiKF3TcD0MYd8PuPrigVWlai8LDPv/m4UOZcl1WkKI1F0nFrCIaOkIEVEK9UhB1S5quS69tKMBGwmidAHjzvdQ1FcK1YG3ze2rwHYQYomPPpElLc7UhQkfkvXdXduC1kYibD5DZDUuYc0Yz73zngwuBmIikIoDVZrhum2P3VlOpSgN3q7UWECCxY4jOUQE0c0Cd9+ydSUVKUrW5at8Chhn6zj3ej4+Pd8Hx58/lPyz5p88nMXVd3O33McYuerRa67TUtaxFmbqu67su+KHrvUkV1L7nzrvA49APu6EDsLzWPuz+6le/0fd2N+zuhp0inOclSQ6evrs/1qESmmhdBZFpP+4c+yJ6mVNW6aJ3SMG7fuzuD7vv39/10adSDPXdhyOR7Peh67/16nsc90CGvPlGMWEM7Iuf9qXOFUzEZHBxCD52PHZxHLsYPCL1ntjEo+3HvnPYB1oPXckiVWuFy7R+/EIv/TrvxQy7QPd3/YeH7jBEPeK6ptcLi9VhCDFycLgb/aH3YjAGXCLVys7Z48ENgWo1UtEqpSAhEFgVqSIiIvbVbdzUai1tQzDVXMo6LyXlzQ4KsLFTBNTaCPma+l8R6k3FUjcBBQM1KzWnkpe8hnVR09P5dDq9TtN5TYkIA5pq2E6utqQETM43A5TQdaZizK6KQsk1qUotKdWCKjXNc8lJpRDoNth+I32jqktOl3WdU15TKanklIsYGETnI/suBPQoTCvaVNYiVVXKsqRlStMlzVPxwUtFYpRKqgimBMUMmWLX0W4f7u47DnXNUiF4P3T+/jCmd3c1LWZFrCgbpGRViqmCoImBqFY0RFDALbe3DXlhAIZbJ0Xelv2qmlKal8VAPXL7RSZwzN659jmLqhmQmSF4ZCRkZuf9282/LdbY1ka1KiJVck7UQJdEohWQTQVU0bbPs5UkIqImalv53+zRGtrLbesLEYKISq21ZkNQaPQOlTehT0yxD0OJ/ej6gYPz3RD8EP3QsamPXd8Pfd8Rcewregqd01KIqeu7vhsGP4ToKJg5id4TcODe+xi8U5Pg434PQ9cR8i52DlmqJhQ/+LvH/f2BoJpozVIWycR0GHfO+VRlWtN46Gup0bm+C+N+2I/DYeyJcF5TrunBdsgaAx4OI79h9rjfPLxT0AJVTNWEkAJRZ0U/kCcfn2OpZde73Rh3+9D3wXtHhCrGBGU5Q12dJybbj3HXOdqC0Oal24/uspRmE0AIXcfHfdj1oXOhlu50ppSTojnHXQgxsqiuuaQ0m6TIOkQ+9Dx4ylkBFU1EIFdBBFURMAGVDWHWNh+rUqsWQzSzlNK6rLW0GQ4Ymhi2xv7X32h1/zUBuN5hrfNnCiYqqaZpWRRMVU7n07LOIgVBrUGakbz3Q9+7EER1mVdTDCF45wApdj2zK6UikZkVqaRaS13XZZkvNa0mFRmQgN5s+wAgppe6XmoSgtB1h8O9XxdR8+B8gVBtjC5GjyGWEBf2pWQ0GIYxMoJlqUsp0ciIHSuQSK2VayURREfqCCJzhxwQzZqfLErf4eP9QPSOO6CIrg/85eXzaZqy1CqAxQC0FaRoLVwMVFR0k4dulKAKWsy+IvxEdV7Wy/kiVAI5ZnSOo/fkXIjBh4CIV704A0IkbErUrUkP19SioYcRgZhga9RVUTVAUSm1wGJIZNsvNfEREJFSUq51gx+bVakpZVVoyoItlTBUNc0lV8mG6kJA9FW1tnvs+tWwc+PdTmkyV7PNBoF6fP/bd+EuIBCT60LHzIBWpQ6pq7U2dwby7Mh7CMF5F5kcNlAMkTMAUQXDYRf7MXJrpxpIkZQqGt25477seotsKFaLSVKx1pgkMqQillJGtD74rg99H733iNRyLtViKACCZu8e7717U/NHQrG2lJs25LGIN9t3To8dgtZa+8jj4Idd8MG11bT1dmterCYTdlcrQtcoSE6ZHEG333kjMgTTTWnCe4sBgifEmDIWqYgYg2OHalW1Mmp04JmGjnqP0SMDKQCjgVURa3mlNFtr+zpSEpFpms7nsxHnXC/nyzRNa0qlZIBthFEJHW8DzWv8tyoB6laKmiqIbaMqYsq1pJwMVGqZpssyTzk1z1w0M8/OBR9icGalVDOb58V73xRUwEyl5pTbSpRLVpWS87rOOS0lr6CVPIEWrcWk3pYlUbks01xWF8Ld3f047Gut0rh9MY5jfzzsui4QQq15nea8JimVHHeeQWvOc0o+mSIxVislL+u6SslQnREqOvbMkXxAJ+iYHLLHGHG3C+z2RiagRlgNVcB0WRr0Wi1DQaAW+Y3AX6uI1usCqjUXgLnkdFuU1TSVPJcVyMwFhw0/7IAQHBmDoJgBEyqSISEigyhYG/t9RdeZmSkSOnKIUFEFTRjUDKGKSFtCQOEqK9aqfS011+aI1KiHUtaS1MxjcKiKYmbZcra06gpqJanXyi4uWlesGb/u/MjoO8+ZhWu2VVUg6PFxH/ehodoR0MwEKhlx34GBa11HNARiZU/h5hZtqGpWpK61mEHwzjvnHatpyqUiIFIMgXdMhj0GBwRgilZBxdSkGjbDNTIDx9wFF6NzjgGp2SdIcwRpxgBFduPwzc5/Or20T2Tr7puhVVUzsc7p48EDOM/oPDKZ1VxrUQNC95XUUaxcSW+NBGaoquackaNGu9PWUTDJqVotiAiIIXgSBjBiQNAm3jAOMXhnJp7RERJBCG3iAtjidANsVdOs+jVgSi3Pzy8/f/xI7HOV8zTNy5pyrlLNtA3zmLC1mq+KeVvwi0IVq5tZbtPXQgBQgKFxLyvllJdpni6XlAuIAMDiXEppTuuyrKHrmnpVk7WIPjQzZJWa1jWnvKwp51RLqbXUmkErmjIZZAAtsqrmr+wxETlfLuu6fHh/d9jfR9859m1HDN73Xdzveh8caK0lLdO8Xi7TNKWcBQ1NclpmIso5Gdpa0rKcpymrQOdGYjR17NkH9kFDcTGELoTO1cwqiBgedKj6qAo5mxXTApDnVDSVXGsFbfj6rd5XkU2KZMu0KwAs6yQ3b1KAYpJAHCs7QQ/q1DyKg4xiWCoIA7cEyCGLaVUFwyrNuhbbPo6GRMhAgZCJlUjYVMFUihXTWmu9AjHIsUMEEZHNJQ2MsEVAlZI0gUEwZaskpKar5GIpU0GACMZmILKoXDCPXN9yLhRFsBbIyZKoAGjfBe+xqJQqpZQqpWo2MyTv2DnHzK3MRDJAVEM1BAIywSp1zXkuKwI4H1t/UUGzZWENwXcYBQ2hcZgb6xka4rZK2cR8yAWO3nnmtvmqqrm2PyqZUaMwCSEHfmOkBm734W8MWqNW0dDATMuWqSOZ0TbfQwPCqlJLUQVmfw1+RZO2rgFdHQ3RsKGsaBOquy66spHqiBw7QNwabmQIZiCqWiuoaDNnC44cIyEB4tamweY9ZGqiNR2/+5cuDO2d9MPwz//lv0g5ITtRXdaUSqlSG6p744WQMbXzfaNZawqiUNuIeUu70ABj3x3v7oa+Z+aS0/n1tMxzaecEICLn2MfYdb0PkbndM4IAnh0zEYCqlpxqLqnUUorUoiJmgmBM6AiYALRqyf+j/+J/vN9tduMh9L/+zR+899+9//Xd3X0fh+Bjw7o5ohB83wVmNJVacl7XNM/TPK9pzbUiYdfFzseOHSvoWjAlHeYOjLow3N/vju/jcGTXIXsK5sc61ILeh+FQ8ipih1yPc7r/9eXx10+///z085fT62VZizShJNUm7Xvt81+FPVrVVEqRtPwX/9P/yWG/b+8lxu63v/09MnUudM55psAu+C4E74Jrdt7UZvK0KYcyExiIityCH6BJ0TNzs2axht2zDeYtUmqtJrJJ4DC1IFAzYARCQzQ1qUVKLaWCgW87MKGY9qVWKVWEALz3RN6QR5FuXR8ev/NXhWjn4v3dr10IQ78PvuPGuzJT02K11JpLrTWLFgNk8o68900BrYFKaNuDjBhI1XIpfcldSYgwdjH60Jx2urIaWHDRsWvMBTVgBEfsmtzkVcdRDQg5+M6TQ+KWFKs2rK1sREtTEdVa97sPzoVb8OPp4x9hQ0c1IucVO40AzZsJvs5sr8rOm6SDtc2zLYtv1Sjx9sDtwRsKrHFBN5enbd/+OrG9bn4N6nklk18n81eL6wbmMuUw9Lt37CIArOv6808/T9OlVTt6uyWvL34jn7y5xuvJWuV/+8v1n4nIOd+m2W353Agit/eMgERM1HrSb17r2gi3N9GhZrbJgW+oqu2jNVPb73e/+vVvu74HgJzTy/PnUtbgY7sAau01RESgbcDeJtxXQEyz+bZt2aXNVgc26LBoQ7+T9z5EFyI718piFdFatBle6Nb1rLJhcnOuuTb4K7TccPvGrl/u22nL7e3u9/vf/e63wzAAQCn5+fSS00obSAg2qNAGB95Odft2bvfb7cy3u2qbL+D2sV2/OLveOVsDF6/3bLuibfvZsB1b8wBuaEGA1uxtv48Am5cBQKvGnQv7ce+cBwCRsqSzSCHmbWfbxhtXiNH1j+t7efMiX2Nje69tF2u0A0DgLXFGABNTsNt445uP4Pr7b+7tDXpFXz+3241ot8ZWUwz2Me6YtrIf/8FH/E/HPx3/dPz/xUH/+af80/FPxz8d/794uJ/+9G8AvmbDrRpvoylrOjpEzjluLfI2klW1K1JKtwbclTolzbrkK+vrmllsqR5cPeqQgInanKC1yq7qkPIVdnfTd7nl7G0Ot72UdN34+Ph9iD0ALPPy57/8eD5PhLQhdvEqIWu3/wFcT4w3EigCIm46as2ftyV/1ESoXbNAbfISWzr53ytb+pqySc3rOpW0SE1gyo7YeXIdoKsVSpGUct/13//q+77vAEDMlipVb8P/b5O///ixpZ9NllRVpUjNUquoEnHoeud885cqJatKU/ty3jcBnFuVoCqIyK4hW78idv7jr3v9YAEMwBFGbpT5rSnwn/mA/sEjv6gm/pFX/Pbx280mb8B9dmUBvn2hW0XWmla11lLKuq6llPZbG32YiJlDCF3X9X1/a5Jfb+k3p7S3H9A37+nrXffmct/e0N+y7LYTwFblgrVOKiJe58AG8Pal4FaZfy2020W+QbCYbXXUtZK9vZT7P/4f/jc3EBUYhq47HO+9D7W1AAG6rru/O/ZdR0y11mmZcymGKFXWtZSUSy4555JTWta0LCVn2wgltdElDQDRsXMhhHaPEYMP1PV+3I9D3zkXqtj5Mk3rkspSUMkDcGPfOjQicAxMRqDUoB3ruszL9Fd/+B/+z/7n/+Wvfv0HAPjzn3/83/1v//f/9//qvwmx8943JLJziIgbUaR5c7ZliIAJOGwx7x33neuHuN/1IfrmuBy6MAzDYb8fhj50nfeByTdBqWt5+80tuN1SW7mJcCWWAurp+eOf/+7/9enHf39++gvAejj2491jf/grpePrCT99uvz5zz/983/2z/7X/+X/6m/+5g8AsBT5d6+Xl1QQmoPm9Wv+5nv/xf22WT1LrZKLlFXTmi7P56efp/PzMs9h2H3/u3+2f3jnQpfS+vT555SW6MM4Hu4ePoz7owtRAfK6pnVd14WdOxwffIw37t71bvqHRSzcqlxAUIBj8L/bdYPb/imlVGttUff25rtdPl2LW/x2vdCrGOA/DPW3JOjWkWlmbeu65pxzziLy9uQ3xvEmP8BMRDnn8/n88ePHP/7xj09PT+u6AoD33nsfYzwejx8+fPjd7373L/7Fv9jtdrApyFTbdMWQCG99x9uVvF2/rA2SWwNKTc0QgQmZwXG7lTbgs117bkTYrBtVJadkqo6ZkBRRDTZgMrbGIQASGl41kTZ4WnNiuCIbtp5pO1q79PYVuL/7N/9Vm3ghIiIPu/37D993XV9qNRU0izGW0yGEoKa55mmeswg5rqVezmua15yLSDWVmnOa15qSlFKbJ14uKWVRBWDnfYyRAyEpO3ABh97vDsMw9l0cDGhN+bIu5+W8aDanRoTsAZwJoRIKQQUTK6Wu67qu87pOqroul/ZOLpf5X//r//b/9H/+v3jsQ3DOYdN+big0s8bgvn3EwGQckIkIyXnqoxuGuN8P/RBiZN95F0LX9btxN+6G3W4cxqGPQ4ydD47Jsdsie2sTXkOUrnIB7a6QmnNZPv/8x//w3/3fPv75vz0//cURPH7A8f5XYffzXO5+/Ch/+cvLH//+h9Pr9L/4X07tvVTVlzX/PK3U5iZXDdM3AXMNIdwihhDNtJa8Lst0OpV14rour59ff/7716ef5+nS7fazynE6u9iv6/rl8485rX3oD4f7WeBQJPaDIaZ1bSHkQ6ddCej06xjv227w9Rb/RfALACHWN1u3iNRabyygX6xa7cG3P996pP9o8N+e8GbKYKWUpbm1berstdEBWpDfor393OYFiLgsy8vLy+fPn3/88ccvX76klIhoGAZmFpHdbpdzHobh97///ZtXV9VNVre1zFS2iPw2kTFrXOwrFUKuq1Xr3uMmVMbwJv4BwIDMBFTSup5PJxPtu96HSN4ZkLbE2gzg+okZMl+7i6wAptCWkq0TbNeW5/X//e0SXQijmlSphsDOc+zjsB/GsVaBWlEEzKZpfXk5X5ZLzqmqIXOMoVY5v0zrmtTUOzfuduHON7tMSbnknNY0L+s0LzlXAyNiF5g9IRmSERswpJTbG+iH3eO7h4Pq02k4rdOqWQCYIxjXZKVITrWspeZccsklq1XHHMJXxpVz7ng4HsfH2HhjjSEqqmZIjgmdD4BYq6jqNupvSgZKteBULaUyXaZhl/ZHH1ZXFaSiCMbO390Pjw+Hx4e7u7vm+Dg634Xom+6QKt7wrNfgt1xzXpfz6eX56fOXj388n19Ma9/5vtO7453rdkuCp6fpL3+af/rpvC7lbQaICG2GxNCUi75OK65PuG7BCG0s4hDb1z6vy+nzz2k6j950Oes6UVm9Ji6UX3++aDHnRRXWJRh4rVjWcnlZ0Uj27BzWGhD80IVuGKJznq+B93XntzdCw5uU0jVhNoNq5gh+kZpsA4s3Kfftz1uswHWrfxvb8A+Ob8tJaAq8y7KcTqdlWZpHK169Q9pG135odMLGL27Jgpl1XXc4HH7zm988Pj4SUd/3x+Mx5/zDDz+UUuDKVn771eD2+euVItx8jL7mL7drQwAHaExGyIq1moE1xmPLFhC0iZVvjXpERFSpeZ3Pry8ff/qoonf3j7vDoaeRPDf5ObVNPg1NDVDbrPxaZDSs6DXNwa2IBgSDb5cncOO4F5NSKxD4EMfdPsbec7CaRUrNpZScal1znte5igAxMeestZTLZVrXVU1CiC56Di5Ez9Fj3zW2ZM5lXlIpRbTZE4CBiRbRDVCXc5HmGWMc+jHG/v6OQx5O67yWKmJSzIpoFisCIk1lxVMg9oHtbhxu/GQiil03jmMMxIzWkNogqAqAzBxCR8zadFsafGz7ktpUWUWs5CqmyBpqVYM16fmUAWz8HD4dx3ePp4eH093d8Xg8HI7jbjf0fed9YA6tNQDQFLjyuq7ny+X55fnp6cvTp4/nlx/z6RVy8cTB++ADEkuylMo0reuaABpb9ut3w4iesOWGV2fs2+ATrgUcbBPwFvzVkNGZWc0lzUlU0lTKalaDJ4+aLy+gQrH3Ph66EELs4hBi7xigrPmirdeDzvt+1wg3nvHNnbxdhW4jpRb8CtCAHdt0jc3ct8k9fnv8IuDf/nwL7P8+wX97Ziva53lelqWR/2OMXdfF2ICu+Ivgbw+27GC/3yNi3/ctN2lrwbIsqjpNU9/3zrlf9iaaUu4NXrZt+4BNf3DbwAEMqGXoWzQSAJnqtURvI/PbR9SYDQgAqjWv8/T68vL5k4gSOed97HtHVx2Uay/oumBiM32CRlTewqFdBm0KPgBg9ouSyx3v7gxMVIkphtB1Q2RvqabzNF9Oy3JJec1iiog+kPeGTlUvl1LSmuY1rXMqKzAtZe7HcRj6oYuDj30f+xAcO1NQ0aKlSq1S15TmaZqXOSUrVVTAtFwueV5KFrx7eDg+3O8O92E6vZzOz8+v82Wqa7GqDBg9xa4P3oXgnAeH8v3DPrgrXLERwhyG4IixZEMwJkBAUWvifYTeBcdS5nmtRcw2kjLRFfVvJgLrWoEg9iEAIeZpKudT+vTz/Jfhshs/jvvucBgfHsaHh8O7x+P9/fHu/m437pzrAGDN68vzy88fP378+Pmnn56evrxOp7OW1x4vHWd0UivkXBwXRHHOxYhdz8QuRnfzICEkz9wEof4Twd80LwGRCB0CADrzQxd24yD5kvN5zfNSsiGO48iMOS0GeOj6u93u7u5+tzuMww7JrVWXlObpVEoBRBcHQA6xQ1O+3TrXmxTwRq+5Lp3X27Dd+c4sML4RvfxPhfp/Irb/E7/7i4qgleLtAABmHoZht9sNw+C9F5GtaX0tAW5LU3vC4XCoteacU0pmFmMEgO+++25ZFiIax/H2/Fbnvcl7AACQWqRf1Q23BkzbgDdfGTMAAgQyghaN15b0tZd8bRcggNZa5nk5n+bTS6kau6Efx70KITa1aYTmzwOAoNoa8aoKBkpbcxCRgBDt6vfVPij6Zu0F13edmpZSENGRYyBUkCJ5zeualjVnqWII7BhYgU2xFkupllRKqQ2taoqQV3BErWe88b2tC+bIs2cE9OZEzfsQ2MUQ15TWlEpJa04ppyULXSYKsd/vu9Dv+9HEyrxaSqUqEHlynl1sm6xn58whdc7Rm3fTmFuGbIBietV+QGtkBARi8G6Td9zaI3arQhGvdnU5KzntB4qBx8FKhqfzJafl9XUOgWPvxrG7Ow739/t3j8fHx+Pju/u7u8NuNwDA+Tx9+vT0ww8//vzzl8+fL+fTWlMONMOYfRQhVUOpwipEGAJ3nY+dA6jM9M0XQxSadyj853Z+BEIgAGBgczH6rgtL9KUAELmux8AxeiZ0Vfth/+Hx3bvH7+8eHoZh70Ooojqva0paS82JEIwYpKAJgf6iO7c1HhEBvhEbbte2JaUAv9gr2zb+duf/zwb/W4gW/IPgf9vtgw2L1Xgum84fXQ+4RlWrAm6lh5m1VSCEzd2w1f+tcSAiTT5MRP6Rnb8hwuwW6dDetzYNmzfv+/pPABt8qAmjwZvH/7FDTWuu65znKRdtTfTrJOL6gRPom9zDmsFNIzZsgP83T0bcXu7b9+EIUKqs01xrDT7WruLemUISLcDYjQGG1kksTSy7aUmpbBHFxOjJc+z70MXmZv86nU6iBODYBR+9d875EGMXY/BxuB8fALTKWtJlXc7zfJ7Pa82rytN0hi90rPv9bve4H4PJFEOak4oxMQBKFil5mma0GhnWJd0Il6Zaa005sTdmyLWoGiGbYVXzTtFXDoAMaAJkSMZEYNA8JoiQGZgJUEVUiqpg38f3j6Pneb6s67poNQEo6nOp61Ken9effjiP4+f9sT8c++NhAIDX1+nl+fzl8/P5ktYMIuAAfWRERG65Ylul0QeOMXSdxFhryd+W9OCI3HVToJY7fv0ir89qhcJViRAIzJH3zjv2zgUfaNiPoTctUEtwtBt27x7e//Z3f31//87HwZByTiWtOdcqxo6jeQT1DA6VQRmguXLdblQCAN2C/yqW+/UepAbWbmLYb+K2hevbUuBtbP+iz/+PBv/bo6XrbTVpEd51naq2XL25a7UuwK3LeMv/6Y2/8NvFqNF+p2l6eXlJKQHAMAxE9ItVpn017fq2ovsKSLTW2le6XbG1ZFLtuvU3vvimiqatTX8dx22reAMyN68Cq5LX2qJum1NdYX3tuVucXx9VA9C29dMms7xtcFdIoP4i+t10mUrJ0+WiahbR+x6JkB2FSKKo1UyhNSFyySmXnEWqqYqUolUQMHiOnmNAzxU0pbqeprIkq8rIXR9jjCHEEEOMsUkyedcYCBBDIMfdvs9SUk3EGEJ0zJEdA0LsvdBKMaWyrHme0zwtjeDOaEPk75Zys4tARGLcJJ42WLNtHyOoAQEZoIiBmAAYtkmigVQDNduatwBbwYZM3MWuiyOC+/TpaVqmUotUMwMRzasy5xeaY3Dd4Poh7MYIYNMlzVOapjUXU/DMRB4QgciIoL1ICxqiNo8g+gcoTgBokpK8dfLJ/rHgp8ZurtlMCBEbM0OrqQAYAXmOzvcERqpjFx8fH94/fnh8/L4fdgacSslV11xTkaqGxM4rKXpGR8BghEbf7lDUukbX7vF1eLI9wA0JAvDGDBLsOku/9fxuj8O3T/tPBP8vVH3a0R5spw0hhBBuE75aaxvdt/beLR2A//ghIq1rOE0TAKSUvPeqOo7jN/G/5bUt+OmtYJl9i2ho4yW8QpFvWPY3R9Mubc24rw+IlJLWtCzLdMkVSi5aGyukbF8C4OZcRA2HcZ04maG2suAa79A4VwgApkaEb78b9+NPP5loleJD7AcOXd8NI/lQEJVduZzTuorkJo+Xcyolb4r5DYHsyAUPndPImUFyScs6X6Z8SZjFk6tFSxT22Qhqs8UkI6YY/H4YHg+H+7u7D+8++L4TUEB0xKSGuZQ1YSFS79ldyuWHH59//vjl9eVcSg3eD3133MXzbFW/3h/9EIexQwIVQeRm4dBWgJbni6KqlOZ8sKXRRmwAQGRmUKsSATE5771vo77RFPb7flrivEBp8shqAlVEiKlqzZXnKT0/T2CgYiag5ogQlBiMqTpXHSuzERuhEVsTsDR96wf1ttvfSv0NKEBvEv7mVNgCXVVKWpfLSaQ455jJENZ1TmkpOUNVFACgGOJx3D3e3717927c7YDCtEipJeW05HVOOVdVQES3KRIhMsLtPzPctn68cm9aOSvaMpnGzCEAZjMEUeU3Cao1bYV1bVX3tQv9tfNv3+YItyj6hz0CeLNGfP2g3qT6baTXJou3xL4N7VvO/49mE+3BZvW5ubmWcjqdWjXRdV1r+18vzBoHAgCAbiUjYGvDfR35t9YcIOoWi43NB231N9ziXq/vZxOQMpSSpulyfn15fX5+VaPHdZWSa5pr8eQcodsc55ABkFyjptWrFIURqJjeABO36zFrInp6U/JyayoIAMToAocOnS9qUOo2Kr0mSM1fxayogRU12/w+m7gSO2LH7YvPpeYsKQsWMzZXFKiSqUBd05okKyp77vqOHRwlItbgIAauxmqAzX1RGc0RBseMTLHTrtuFsBgujaNrbL5glq9ka2s+96ao7RO9ybhvVt4ilrOU0vRam8+Dbm6zoFZbHxV9U1pv7eLgvaMQeBzCOHSiACZNUsbUzERNpcn2X6OTyTE2/akmESOO1bN4VkfaNn8kM1KzKlJLrbXWfwQCt7F4Nj4iXrdXbd0iQhPJJS2X0+vnjzmvPgTnHTKltJSSwBQJGX30cT/u3z08Ptzf7/YH58Jaaioll9oED3Nts2BCIjCHjScCYFJrXgmQuEGbCABVQUzM2j8uooLIIcShH5xjtjbKQsdfceMtIZ/n+VZyM29M15sk/j/M//FbRMDbJ8CbM9tX7VC5zfBvGUEL+77vY4w3iN4vTnJ7obbzn8/ny+WyrmuttTUOWzXx9UrUTDelkq2JjooEhnQVHNnszK5MLMDWlWnVvhGgYlMb17YQ6KYkbipStC6X88vldFqW1CTIVSSvy3w5+0jdOJJveUIzjrxtCSDXm93at3BdrKyx1Dc63jf3met3B0Qiphj70O8E8Pn1lEs+XS65FEIInr0PRAOoprxcLudlmcqaSilSBQCdgVeIjXgL6IAdOmVDRHJswasnIEPAEF0gpuBj9P3Q7/oYIhVZnl8+2elpzVIqoHHn++N48NxRYOfEIT7GuDvcff/rX//5Lz9++vz8crqAGjpv5G4bpohMl+l8PnsXmJ1py5atycurak7FDMsGSTKAJguBgKBiVSootBsoxn4cd8MwBM8iSTXFyOMQawU0laYGi9W0XudRurFRcSOmtr4wICFpYAusnoWppWSopIpSreZaU8qpFLGbE87XuxIQ1JTAgLDhElv1hojsuGot63J5+fL5pz/N8yXE4ELwPhiCSmFHhD6wux8OD4e7x/uHoR9ELa1prTVXEZHS5OkaERARocm7ISCDmeQ0nV5KTF23C7EjxwYobeGseZnOp5cvJRcfusPxLvpf9TGQVkNkQOe+pvciMs9z20hbWLZRXEvU227cYrUtCredHK+An7fx/xYIAAClFLtO+wCgNedaO8B73xr+wzA05f+3bYLbqW4JSK11mqbX19eXl5d1XVW15QvfRP7G3dOtZX/DPRqgakPYtNSgdfev5MotrZcmMtxkx9UI7IoWb/mp1rKcnz8/f/54Op1U4f7hHZJnomWaX56fgMw5HygAbKOEDavCqm2mZ7iZn1yvFwE2JY3W8f4263H7471Bk7R3ArzmNvNYl3UBhNB3MTjnHDGggfPMzH3X5TXlNeWUASz0IXahC50aeGfeg+8wowASOQrReY+eldAIBBnZex98iLGPrg9EBGldUtUmSFMrRN+nY+ljb2jsOATf7bqHON7d33V9PBz3X55fSy4h8P6wu63otx0mBvPeEG54MjUwBDEBVahSRbQhHkCp9U6azZAj7rpwOIyPj3f39+PQByIrOdWyegd95MVxITMFaX2W2wjFzLa9HzeT2VaSoTmyzknnqidlNCRs7oMK2sZLa8opV9Nb7+Ia+wAAKlKaiwUzAwICX5s9YFrTcrm8fnn5/OMynbpx9LFDdkBshOQ4hrjrx8P+OO73rovKmGvNRbJI2TjAdfPTJSBoYpfbi6tqzWtdl9olRy74QAC55vPL0zydap7n88vT54+1lG7Yaf7VcRzG6GFranyzubaav4Hn2iPMfBvj35pqLSxvXH24zgh+keG3KN0EHK+4QLvK+zZkbnvce3/b829LzC3Ubz+3m6Rdxrqup9Pp6ekppfTGFOTtYc3tq5Vp2twWcEsEWm3Z4t+sjZnau2h13SZaAKiGcHM2vRUxTCa1zpfzdD6XUpn9bheBHCAty1KfVA2879DYh449mZU33BW9oTC/JgCgm0zVplZMv5gwuLv7D1V1zaXUOq1FtTanNXYcgtvvBvYkVUSqViPk/Xik3b2I5DVP0wXV9mPogw8ORWSqPGmYSYuYEpHD4DF6jA6iI7c5s4Aiwoao90SWSkk1aZF1WaZpVXl+/vIUYx+6bjyM93dHP4TYu773jj883O2WtZRSVMtvfvM+xnAL/nUtJa1gpLrNUW37RBAQCG5qny0RsoLS8ncm8p73u/7x4fj+w/133z+MO2+SUlrSOue0EppjRKyqbddUuxpMtvuo9WAQtsg3JUBgUs+586n32aHcqOyEBNpwyramvOaCoPWbG31LR1NKqGLegfcuEJKRQbOgqyUt0+t0+jy9/JzTJQZVrGvRYqDoxt3huHs4HB53+72LYdZqKauYijXqfzWVpsKDtl3+1sojQzOVXFNaJinD0I82jAiWlstPf/r/PH/8i6Rpvby+Pn9R02F/x3V5f9zvovf94Jy3tzrEAHDtyd3WyRbAt7WgRXLbw982Bd9W/m1W1zKFFvytqr89vxURraX/dpLXkgIzu80CGyignRCvyOJ2MaWUaZqen59zzvv9/nblb5uUtZSSM7QuLBESGthmCQqI7b03FXjCJhhaSs4pEeM4jDGEBuczgwptzTdQY0ImBrV1yTkXZt91zozEIIumJcuaUqqIXgTuHh46JkBQ3fJBbTLWtOlQ3/oYKtsrGFxdDt98MQ7JmdZSJZUKAM65rh+cY0R1jrrOG2paklRZlsVEg/chRBc8B4JUQITQB/QjEZp4r8Fc77ACKhISeLLAED0FR0xQRJZU1mYvrtgFIM+eLDotXmpQq1qKIIhZQYzYqBGiUgsxd5557PdDb2oK9fHu4P2VbgUgIqpSa0W8Au+vjSprEWUb+GR7nJSZPLsuhv2uu7/bvX9/fHjYH46eSOY0zfM0XZaUCiCwA0IFaNLBepNOgOZq2RQQbTP/ADJm7Vze9+thSGNXojPHCFvog4qkJS0zp7WWIozwi7Kf6IohNW1ytG1AgNbw5GWdT0+ffvz88c/T689a1xSp5HXKUo0pjF2/Q/LE0YgFsGrTMkMiaPV4U3upqqpCW3rYFp52l6uUlKYXkGLyAayKpPXy/OWHv/34p38n65SXyzJfELHMrx3Bl7t779x49y4OO3bO/4O+eouxVpw3HH57sEV+Sw2aRc8t8jc7zWuDMITQdvJbaXDL9lvKEMLVD6T1vYjWdW2pRKv8zWxd12mapmkiosPh0OqCVhQgYkMKp5TeMvy+TWO01lpLYSJjUzVUkCvcHjdFja16UrCS8zxN83xZ5otjhPs7HMcm7qOwicRuc5xqqebLaTq/nqfLQsqgWKsUtSSaa11SSqn0/TgM4/5QAdRUDAHAmUELfrwhiloKIqZSVVsJ0nBB39b8p8s55XQ6nw1xfzzc3T98ePxuHEYwafDclBcCl5cyn6fT62up1cfu+HBP7M7TYlJzWqSLYRx6pkCEwYfAgtySGxJhAc+EgkVgyvJ0TtOyZql9dGZ63McQXRhcH+LdTsVapQfE3oWe2COxpnqRM5rVnEyN2Xnv+y4MIdKV4oIN1tTet4kC3eYsequoDU3ZAMCUGb3Drg/jbrg/7t+9Oz7c7fb7zgererlMp9fn1/NpWS5qhnHwxEYMQKpaRZSvwC5TUzBD0lYuEzCa99LHfOzn+zE9HNIYxREBNjEmQzWpdT6t89nlBFoRuTGh4fZe6NrwNEJH7Ih5U80kUUkpnV++/Onv/92P/+HfyvSJUU9k4PokiHHcdXtyPoldUkbCLnoXyDnnAR0yItUqltaitTZhX2rzB2l4vlakmpSynNkEtaDWstbp9fPp4x+ffvhbWScpCUCYeanrM/MPw64qPJR6fPiwG3fGXyVi327gbded3xifNMJf8+dpwd/KhFYTAUDb0lvXve/7w+Hw7t27/X4fQiilPD8/t7F8497e0HttrWlz5b7vx3Hc7/fruv75z3/+4YcfPn786L3/3e9+99d//dd/+MMfjscjbBTMbWSgqjeD0F8sYVqL1sret+mZmNW6aQ0SNjNZaFgxM1iX5dPHn1+fvyzn1+DJ5ge7P+x2hxCCICoRekfsiKikMr2+fv754+fPT/P5HLkzgXlNWQGcz7VO0ySiORUTRWvmuNI4v6YmVc2Mm1juFTmwGUVt2upopizOvk4jwF3OZ5FqWn30saPYsQ/oAznyat4Xcuw8+NqXGDqm81KLoZbSMXjRorWuFRKAdR07DsSM4NhVo1pVVK05VhGp4Sr6cik/fb6cpklMdkMMjoLnEHyM3gdEYHQBgQwVgJCCKqQiWiWVtZmqIgCoODQypm84Jm0afLVYecOx3mAR2O4kx46dwxh4GOJuPxzvdvd3h/v7w24IzlmRpeZ5WS7zMs1zWmYjdC7yNtO6asM182jTbU5LaMFrH2SI1gftQh27dBzWw5B3Q42+Gc5gVXPNlVe05FoLEhCTMVXE+jYnIwRHoI5NySE5IiZkQmKyUqQsy/R6ev54evnk9eII5IwYKoahc64b+24Y0LuWTTrnuiYHh01xjEutSSsWqFJLrUZkgKRNGHvb/U1KWU4kqa7nvPRrKufnj9PLp/n0pa6LqXiP5pyqzZeXpy8/o++VnRqwac9k3sObxL6U0or5W0S1bbbl5HAt6Vu7ri0TpZRSStv/AaC17u/v79s5d7tdayWez+e3BN6G4W+JQIv8/X7fAP+n0+lPf/rT3/7t3/7www/OuTZ9/O677w6HQ1tlQgjDMOz3+5xz13WtffC24afNG6IkQgP0zEytkb8hdg3QELWhnxAQTSSv63S+vHxxKL2uoZxpvZQQshmGGI9H1/WmvC7Ll89Pn37+/PL8mpdVI4rAy+mcRNHHIrJMFwRo62PbBkSb/JiYGOpVQgO+/tmUN26lZNuovtn559M5BL7f9/2+i6NXmD59mU6vcTfsuzjG2IchFAykaGLjEM+XZ7HcDWigWLEauSKs5pAcOUQjA0I21ZTyuuaaK5KL7ETwnOqnl+WPPzy9XiYfOB10jL7vYj/0HpicYw7sIqEDVFMzwFrFoVVT1QJqjgnREFQ0pyQpT7dMpiHcARwRA3Cb220saQOkBtrxfd+NYzfuuv1+OBz6/aE/HMZ+iMF7k7qul2Wdcl6lKhiBUZWKJjWLGhCxY4fN6NEQgNuLM1oMcL+X407vhrrvSxdSF2oXJAb1DogBUdUAtXnnqpkhgXMYI1QVpNn7ha6TGISm1ojGbKgeyREyIhMwo1TVskqeTBJCRTRRS2n1HO+G4Xj/sH+4H+8O3a4fdv1xvzt2sXPkERE2Z2LI4AojkrZiG1ERnRkyNg0ORDMpeT7rOi2vnwD0NC2vX35K66Raa/u4tx4HFpFlXV5fn5SdiniTwZF1PVx77C2XvsWk977ruvv7+3VdzawN51oDr+XzjZl/Pp9fX18/f/58Op3a7A0AWrQPw9D3PSLGGC+Xy+Vy+fLly9PTU611HMfj8Xh/f7/f74dhaNV+CKFhDV5eXp6enk6nEyL++OOPDw8Pl8ulNSCY+XA4PD4+mlnOua0d7WLeThxqLTmtqhJU/dCzc0xmzdTsOgK4GkBj53k/xDXwolnzlJ7TubzC5QsRTTm73eEB/7qDBzF+fT1/+vjl8+eny2nSKg5DKfZ6XqaclJ2oyDp3wSGAZ++cZ3aiAlfUMDDaJtMpm3pFG9NvzH9thMFfIKuc5BV9N8a4GwfqXLF8mU+TWk373XDE8d67iKYx+Lu7u67j47GrdUaoOVdfSYCc82OM3ntiZ2oGoEjQ6BYiRSsCoIiApVxTrqVqrYaEJcO86LJqETIMyIFcx64DYNWiVkWrqhEi8wYoxzYYNlUrueRc1l9gvAE22jYYEiM7YiZHyITM1Hd+t+8P+2F/6He7ru9D33PfmeeKZrXmdZ1TWlUUgR13jgFBVa0WBSLvvQ9C7AC1ZRPOoXc2BDvu9N1R7/Z66MsYS/TZO3EOyd0GvoCArIQATMAMIcAw2D4DOQO0vjf6ig0FNEUTRCO8cfsAwUDrMp1/+svf//Dn/3B6+ZzSAqwhhKE77O7ePX74/vDwPow77xmhal21sJBWIaIWraRIIlWkqopWNRG9wkQRQUQrEDGUktNyXkv+8tMfw/l1Wsv59YuB+tgZBzP13Hy72UClprxe5jN7hKDSIz4eHmLsrhtmM/bb6nbn3K34b8EJ16HdpnR97b19+vQJEVsJYGZ93zdRnbYhxxjv7u7MbFmWL1++TNPUYPlt097v9/f39+35t1qgbe8tquHaa2wYgRDCw8PDr3/963Ec13VtyUKrJt5CA9t1qyoBQtcxITPfmj4NwHsd7xtaRclYEuRZ53OSacmO5gBglzX5/TGOXRHJ4l5f57bGEbLzzrlQakm5nKe5AooUWac+umWaUlpqzlr91V5CG/REZZtEbL7DpRqg857IEVJrSxC5t5u/86QBIZCP3JF3IKKayzpDPpfpuZ6fQtyx79HFrgt9/+Bgr3XJy2m+TOeyKlkfujGELkZEAkNDk9aPps3lu1k2iRFa7Tw/HA8xdAbUBdZKKWMVr9gh9eg6oyhiKUkpqlIQzXty5JFRRdqslAjMrEipNb+tYRAbZpacIzAIwe12sR9CF51jNJEY3G7f73ah79G5XNJUkk5nbtyD1l1XFSIOjjXG3LF3NWupVchhCKHvwfmEyQyMWcee7wZ7t5fHfbk/6NCpI/FkzMDM4BEYrfmDIhARoycgNAmAu70VtIIQVwQIuzF8tU82MykmtY2Um94YIYBpSeXTzz/+6//6//pv/9//j+ePf5S8jGPfHw+/+et//v673x7uv3NxzAq1rGmd9PwMr3EKIXoXg3cxsg9ILldb5iWnZCKggNyYHyJiqYIygMec13W9rK/PRcR1O6VQavGhG+8fQ1VT9SygUnJlAobKmrjM+VV/enlxVX772z+Mu/1tUW4Z9W63G8exNe0AoKlu5JzXdW2MOufcMAwt3kopXde1wfvr62uM8Ve/+tXDw0PXdV3XtZL+w4cPDw8PbTVJKV0ul3Ec371791d/9Ve///3vf/vb3zrnnp6eGs637/sPHz7UWkMIqvr4+Hh/f99yewDouu7Dhw/e+wbyu1wubbl5//699zcBjKtnTKmFiqiCARHZhrIxMzVDQGrT4zJP8/PT9PylTGddpyyQKnFxZFZTUSkvP/Z8mVcLl1nSujh24929dy74Tl/PgFBySVpTWtL5FNg+f/r5w/v7u+PoHW5YLFWtUktj/qCI5JRSSsu6AlDXD8EHYqeqeU1mtpfHr8G/60PfNd9kZmI1H10ATlBLlcsqYpJ9d/Bozg3B+85Fqz6pcUHo0Lz1sffOGUBWE4SKWEwr2BUpaqaqkkyRVDu2u10XfaiCiKZqKcuaZckiWD1ZDCygc5a0JKkzsY3YBcfNXAnawtIS8VpEv6YxRBACdh31PTvHYBACDT2Pox/H6BikFCaMwRxV0FqztmQSAZ3zXd8zc63VAIycCNSiUqUBOUQVVMmz89T3bIaE0gU97vVxJ4+7cjfUcZDgFZrCPBEyQFv6mswaWGsnNRkwhzQiGpGiWzIqhHE30I2eDKZStfmjGG19/iuxI6/L0+dPH3/+6fz8jKAUOkFPYTCO52nNr8s0Tes6p3Um086HcRwPx0M/DhxCiH0/7JB8KSJV8EZEM20OSAyABo6odUlLSa9ffiZ/Crs79NF1ffQeU1HJbFmrgolJNkkmqxUqJZVVp8NRarlFftd1tdb9fj+O4zAMTUvjNqXPV7cSuipttOxAVS+Xy22l8N7f3d09Pj7iZsiDRNTO1taUYRhqrW8HeBuRxPvWwOu67t27dy0NqbU+Pj4ej8cGB1bVxu1tvYBpmhpZaLfb3d/fuzcWV02USwxEtJTKLMTXuYyKlmoGbeCDanVd5tPr5eVpennRdLGI0DnsI6kt02rzkgVxd9EwFgts5rswdj0xi2AuMs3zdDlVEDPxnqP3oLWs0/T6FAl8HJBImmZWWk3V+aBq67IdiEQGECqRq7XMl1lNH2v9GvyPj3vnYgzEYGQQONyNj9X1miaQ4sAQMlkiYSwIqlUY1Qij99b3oCLMLG38rRukpoBVUAE1bJ56FQBAjQ0i2bFzncdcsdTmm5ZOy0VPQH7pd/XhLhriXNK0THk9OQYD2Q19y+UcI25OGGstcoW9AwAw4zDi3ZH7zjnnwIAIPQtDdeSZ0URFZJ1yWYHZELXpnBGRBnWOERyAmWrKaV3L6VznqeTcIMNkKlgBQfaj7jsdXN339e6gu04C1eDEFGoFdgQEyIzU3NkBkdtmDrYhuQGQmAZ2zAF4mKuvBsP+8FYlUqrUKk3MFBtCXAkJmH2I3TDufeiWJCp52OOc7OPT6dNrfn4+n17P0+WUpnOdLwgau/7hw/vf/rO/2d8fRa0fdh/ef7/f3QUXAJCJjBrPUKQWBEXHDaFIznXDPnWvyzQZoGN0sStGUjOUi1bVsmpayrqY8zV14r2wAXkwAyi35qVzbrfbOef2+33XdW3XbVt9KaVt+41RftPbUNXbCPA2BXDOxRgb2f42zG/dgXa0X0kpPT8//93f/V3rJh4Oh8Ypar97f3+vqm3E8PDwsN/vW4XfPvlbOXAbT7Rx4FdakYKKiiiQE4M1iWhurT6P1sxXVEUNCck5rimtl8v5+eXp4+eaLrsx1ENP5Mjs9DrVInRaw+ES79753d2uG13sgvOp6nmaPz+/fPz86enpU4i03+/ef/j+t99//+Hx2JGtr19OJfW7e3Q+55zyOs8TAozjDgDXeV6XJS2JCD2AJQ+IOafz61lBq7wJ/t1uRGLn0ayUXJGx9x7dzmKwWkwFwQjAahYzwCzkEJkMkRyzF7E111prrqJmiKRoolZKKSWVkjQnkwKbmwGgkUcHjomQEDKAmazrjB5c3zmN4AAMqpW1LPN8IRRsK0i7m8wRkQEDBnYdc7yp2RFBH2kcqIvNSQXVDFSl1FoEsUkbSLOmkNoWcYM2HUWstTbBP1UpeV2XNE91WVSEARDV2ISsOi79kALl0ZWxK7tRotfmTmsG2rRSGsJ3s34ABLpSN5qZ15Wx5widU9876ZNQ149EX9GKOS3rMis4T1YdM5AhIQPwpsMbugEpaBERnOf0w8fPS5Gff/70+vSyTpdyOdfLhQmHw2Eqxd8dJq3LmodhRPKA7rA7OnYtiLRu9rSMBp5xu0RHLhA5qaWFm/MewCuRlmxlXlMq81TWVb0v3VBy9B6Naq1SdL2hBYmoFd4xxpbMNyBdy/NvWL2b5BZseI1Nn6cxc1vt3ZaGtlK0lOH19fVyuXz69Kkhc1ovYFmWn3/+uXX47u/vQwiHwyGEMI7jOI6NtJNzbleVc57nuSH5G6bwtuLc8ou3UOXzZXp5OTsffYi1kHMFEJggEqAWKatKFQXHvu+j1s0zp5aacvGeUtEsAGLTUtO84Jy7LIDO+9ANA4BeLqfXy/r5ef705ct5mqrU0XUPd4e/+f1f//ZX3z8ee++gLNOlFhEDDmvKa1rneWo2R85xrcmsMhkBgGxeYyqZUPkrBREAwPnYASISVFmXdWWH+6Ef+j76ewTOxUrKeZlqTgIJwQCJOIYwqGGpti71Ml9KLsANWYPN/KvklNZUctKSVSpuBDA0ICMH5BjZMzAROpO8SsJ+7LrgYseqRqyiec2T1QyaS04p5a7rvQ/Be8fREfowxDhs+yoAIkbHnSNHzZqpqX2aVEGssacYzfttB0Zrfk+iZipSN7t3JUYzLVJyrVW0CqhtAmvOaoTUuzS4OfDqqDoWVJAKRPDGUIcRCKx9zg1R1YYwW2JNyM4jEhIAO46hQx2xsHfDbSFTqcvlNF3OwJ24joOaCJaKDtFL1YohhGE/jHcJHChczpf5Mp/y+vJ6Wi6TpiRpKcsaXejIAfuqsKRynuei8DrNu9263x2JyFo+VKvUolqptRYdt4mJGlYxKQWAwJDQeXZI6HSANF3WPJ8vUrJ0MaQUulyFRcualyVf1OrbtL9t1A1/3dr4InKD5bRsv+Hz2tCuZQfn8/l8PpdS+r5vO3Aj6gNAS8svl8vnz5///b//958+fWrTxHaS0+l0Pp+/fPmy2+12u91vfvObFvmtpmiAn5YCNA4fXY9a6/l8br3DVkEMw3BrKudcfv7p88effu77se+HfihNJ5oJAgNqkbxoLaLgQ0TYm1nXD7v9/jTuAMVFh+wFWAVShaUoSrZ5DtMljiPtD3POf/+nH3/8/Hqa6ut5FpFhHB8f73/3u9/+q3/1L75/92h1rmkuUiSVoqrqllRTrmldnGcm6vqIZLFzXXCIxE0gFKF3cei6/cOd929cel0IYAAEUlRVoZrq5q/cNN1VmLhVFheRYgDO9YaOqacwOgveGHy59uFNtdScmdU5BbMKgEhtACEbEbsoSmO3IYBlyyWRaj+MUCtoIULvIUYeuqAVYvDONdPVbXQJbEjsHDsfbnJRCOCYvGNmNsOGuGwgiJLFe+AenWcwNVGVmy23ihhWLaUykUOydqFVVRQMCcUTRJaOc0dLj2uPyUFpxZ9UNEPn8Apox2vableVty3wt1pRwMi4cToBkMj7gNAruuC6W/DntP7857//8fPP1O98HDofPQVEB4zo5fPnn15fn0tObXKbllVKfjU7lTStU64JQRQ0VUU0ZEfOiVkqeZrmkuV0Pt3tjyKCYQO3AwJRUzAgIGpSB2aW13WdLmmanK9pmtFNSlyllnWZXqfz83m9zEzqnDNV02o1Cci6XlKevuXDbAK+bc9v0dVGgP56tH211eqtDm9Pbttyw/a1BG1ZltuMoK0FLYAbmGe326nqly9fGkWvsXSHYWiQobfEnpzzDQh8k/oSkcvl0uQA24Udj8fbe6lVnl/Onz697HZ1P6pUjDESAxNkUtSiZTURBVS1FIOqxtj14y4MQ6kJGKrCkmpey3kpKVXv0FU1Ecs5Xc6XXJ+ens7nWbALsdsfjn0f3n94/O6777/78OH+OJ5f0rrUaZmkCLsEFlKFWqxUISYAcI5CdM4RNuVXAUQCBGZyzP3uW5dexw4AjcjQBQXQIhXmaZ0vK1NgNyA49oEkrLOs6wwGISBSHcYw3t/tXDxKFROVKpJrTiWveVkkryoiJZeSa26A6LysSdJaaq5aNiC0kFatUmSWEC7DMK53l9CFGOj+OO47IrAudo6bNatz3KxIiRkJFb+W/ICI23DPeTOAUgGNtnREqf2yIxWrWlWbsXyRhhsyyVQZkR0DCCqAAoo5EMfW+TqG1HFykMhKTVpga+u4iM4DoHm86epoaxCiEfI2nfvqctdi7eYk1/ivGAIH78It+JfL+d/9P//rf/u3/8bd39EwNmc4MgYDIDmfTz/98Jenn3+eT895WdKC4l3pIqAZGXpix1bNeFEicp69A9Oa83K5ZE7n19f5+FBLsR6IkB0jeFP0aEho2FjSKKXMr19On39eXr6w67n7PC9llZJSXuZ1eT2dvjyhLPt99EiByIFCXUVSXs91ne3q0tvy8PP53IJ/mqYWdQDQ+lIt6m6EPLgyf0opr6+vbeq2AVgA2qIAALXWhhfY7XaHw4GZ7+/vHx4eHh4eROSnn35q5LxGAbiJ/7RuQusU3EBErZRor9umBjcOcoyxMfzevJd8vqwAjtF7DmQADIRWoJBVqBnRmEPrHJGqjzEOI8XOnFfQlCWtl2VOT+dZSz6Mkdl1PqDK8+dPr6mq1t3xcLj7ztC/nM/e03ff3d09PITgzKRImZfp6fm55DL0O+cGwEjEIfiu78bdeDiO/RAck1Q1AQIi3GTmzZRjuOlEAoBrPysgKKqgVAC1BFlKAZgdrzF0fd+z8y5Ebl08DkDO2GPo/bDrnQMGUCklzdN5uZyroRF7uu7WVXPKy5J4mi6XS51Psiy1ViuKBSRLLrlWHe5zc1Inhr4LkXY4DswUfCRka8MyZNh0+MWkqn4FYGy7f2PWXJ0MyBHRZnlAiIwEZERmULURcrVBJDXnzGzsXVPF9o7G3lSqoxI4dbR6yGQFTFVMAa1J1l01mt5cRDO7xE3afaMXbdovAARoAGLgwKzNKICaUq67VWQprX/549/92//uv+HHOxz6Rs7mJgyDmtc0vZzmp/Pl5VxSAWaNQQELo1QRNWIG5zDE0A27w2G/3w99bwRDFwm56YQ2ygAROsdKjWcOrfXX1BCsjRtr0lKk4OvTs53XJa/LmtYp52kp8xRYJThJpcxzgipequayLFLSjatg1wOuM78bOa8F9q2d1iLTrhT9FpAt279N+G9nuPUOQwh3d3fjOLbu/X6/b7GNiC0jAIBxHNv2XkpppcTlcmnjAADw3t/6CHQVBWgNiLfY5PbVplJTLn2VWqXkTAhAQGweKlm1mgkRAqtILZURkNnF6PvezR1qlVLWOV3O82VOaDL0wQxNraZ8npapKpLvh2Hc7RT9kqtzGLrBuSBVlqVcLpfX0/n59VRyqcV2OxrGvusGdm7Y9Yfjftz3feeZoBQBAQRiZHKEBrUW4m/Qyg61mKKapDXP56nU6r0HUMlZSjZ56fv+/Yf3/dDd3T3u5a6KAXrnBnQu1aKlcPAxRuddLimp6LImBTHsfOy62HeRkEsu65Lm8yU8v+gXl8pzni9lzpxESllrNk9VrTF4Q9ezAfhAgEzMHBCaXiGAmUitNUstNc95md9wFQxQACuAIRE5YCAgRgAiAasmAZSZgpEhLtv8TlDVEKVUxSzEgZmQsB/cbgRUglS0JM2lmDYxCkAlNCRgh75h7llvWlaqDeNBRoamNxXbFvxEhpulAqt5BkQMjFHfON4DQKn18+vzn37+kZcTdN5YAY0NCYGJLGuZ0vq6np8vJSn3AwgrlEyWSlUwcETout14PN69+/D+w4cPD+/uiTE6j8APD+/34+gQTaUR4pQIQAFNRLWR1Q2YuOu6YRhkWedFn1/Oq85rXvKay1whFwcKHuoiC86ayxzJeUU2Q8BavvIUEGOMrZK3NyJcrbWmV0GOBky5BVub/7cm/+2Hxs9tkbnf71X19fXVzO7v75l5v99779v4oAW2mbVC4P37933fl1Jaj+DLly/n89l730AHjT7Q2gFt7F9KmedZVRtfAL7eYdZcmtswp5aCoMgN64VgYCICgIiVKdSgTIYAzod+iOPeck51SnlZ1pJyZjRVq1XWJWGp87xW4njYYfC5lCWll9eT93Q8DMu8Xi4TWfny5fnzl5fX10lEUKgLw/i+f3j30A9jP7SemHPOwMw7NDJqgFJoX2wBrd+w+kxFFGrBtKzn87kUDbEnAsm55kXyarWkwxii9z46x6wgAkVUyqRzcstc8q4fhq6PRWpel5RTyklqZe88IIUueM9ByAVmJ4ZLLilJWgWyRtRKVjUhtLFCKzfZlG2zOKnZBIAa4bGWnFNe06KSuMmCvdn5EcExxACEkItl0zYnY4etcXvF/wltrL+tIa9mVhXJigPmOPR9F30XzOq0vKT5PK+qKoruKp9CwA6cJ+eIHBIZkRETsuGNcI9bIwCJrhJ8ttm0IBkyoAP0RAEokNlbGJmYTaqnkmlCLGhYAYRaFQNIArCCZGEgF/vx+I7HXe1CJks1G0GMITjfGX94uP/DH/76V99/ONztfHDfPX5A5NiNfdd7ZlDdpnoEAGSgTWsGVDexAqQm4YSiYF7EcpJ1SvmSqQp6EsA8V5Ba0uI8uKAuEHsnpcBX2HUzTQj4Rqjn5qjXkoIW+TeTjBZ+rYw/Ho+t925XAm+bC7SE/HQ6NVhujLGBeVuDUFVvVL9xHL33zcarYYGbyOdtqgdXH6vbKFFE3mp+v/1qGn62zXOacyUjonHThAbEzaZbVESuQG5E58gHMETOaqhiYI0QTKo2TQsS5qrWMTNXsOfX19MlPb2cY3DH/fDSx8ERWv7y5fX59Xy+rGDqwdVanaNh6PZ3u6Hv2RExmLWGFgDapuooUrVKLVzzbQoDAK4oiGiuui7L6XROuQ47c85JzlYripZS53km52Mc0bEqplRO0zmtqxZD4hBD7Ptu6IEoreu6rGm6mOgs1cy8dyqxiR4yU9d3+8NRq4GC9d3BoayXj58qBIxoToSy2izpXPIy57yUnNacEKnvBjObpmme53mdvcf3d3v9JvKRmbrgjkNgtGlesYoBAzjP3rtA7IE8ACJ5cp5U0AQUgLZWIlUxteC69/d3h/1dF926nD6mPE+LWhYxvvbCiIwdk0dywAxMwI6cI+TW4W8UrwZGRkRWFSIyUyRC9IDRqDfugXtyEdkpKvEb9igzDHsYD8TYrAYBBLGNmQ0rOHEhxN3D3X7//rvf/r67f8yOM0KSAozDEHd9vOuHx8Ph3eP9fj/Gjvuh3w97IrfmWnPRKlcNvkaCsk0MyhQB0MRU1lwX0eqc34X7/kOXQQXLpUJdJYuYVcNVRQv4YBoAxEyoqZTcFuXbm7Irgefb9RoBoNX8Xdfd/qlu6mbaGgG3yX+DA7STNGTOTRV2HMemwNtyiltBkVJq9f+NzN9KhvaKN7rRjbrffmh9h9ZZfPsW1ERMcMunlTfO5abZw86ZWnOnERExFdOqWtQEkNmR80zMTMG7wBi8B4PLZTIkih2yB6JlXX/46eX5ZU5Z+74bOu/BsKwO9fn5dD7P05wYcQwiIqoVQJjAOWLPAKaKZhU3+R7VjUtZcl68696yep2hM1TDCs3PgNWuXEBC8iH6EACg5CKyqtVcdV3W8/RSSw7oAHB6VXIc+t7HwM6rNH9YyetqamQagm88GARSleDduBtBlWS478jy4AOq2RhjFLVpqQqWMtRKqqBiNSugeG9qjSKScgJ0hojE30hfGRJyCCE6YNLA+bKIqHluTQ8lUiIEUHbgFEANmxCDmpFET33HuyEcdrv9bu8dWc3U0E+bcN81afpmd7eWCyAjsUO4zvwasxsRgQEJtYIhkgPygB4oIHXkOuc6chFImf3tvRC7sDt2hweSDHUVK9aEwpyLoRvCcAyHQ3d3jPf399+9+/Xv/O4wqy6qSSo67Hu/68Nd1+/7buj7EJgd9OPweHxA5NP5Ms9zXjNUEdxYyXYDIZkgAFlFEyBQQiFRECIxhbLWslStCqq1ABqaGkob4UJFMJWaNS3pF93+W9n/9q9vCbNvqx64EmwbMm+bl1zZ+y34G7Z/GAa4FuotXNt5Wmvgtmk3yvBtHWlPgyvdsOUIb8P+djFtHnnb+RHRexei98E5z4SATEzEhE20iymgmUGzoCYxy6UuKS1LWlOKRIjgHfXBcQ2BsQ8+OEpakLkbeui61Wya1y/PL0+vs5mrVb8wYcn58hocpLLmUgHQkXPsEaiktFzOzhFYGYaBnTMFNTEpakJoalq1Fim5ZqhF3+784Htkc1iGHT6apZwEoFYBI4fdYejGLnZdUMPpPF+mfL5c1rRIXbsuHB/eE/CX55d0KTTP/W539/AYYq9G2VJJa1lTupxaLcyEzIGdIwoxOn9/9GiHjjzU9w8PUktVJTM9vZS6OMexZ3Y7sX5Ngxk6H6uo967vuzWPzuEwjs6HN6sySLVSrZobo9/vguT19PI6L0mskhkDMyoREiRPGTkzizeraGhGKMMQ7u+Gu7td13UIltOclrPkBFr5ZrRspoqkqIJaQZsnChkAmSECMXu8ae4yIqIBg1YUMRUkh+igFe8cHfch9OR6rOL4ayeW2e8OD8e7d7Kc6mJZk5oR+cP+7tff//p3v/7rP/z6D79+/M3j/nHYHV3fZ7CXebmkvNZiCN5jYIwAAdE7R46RAY1zrmY1r1mKELFzpKYgm5y8AYACNhdKLUzW9TH0bl7WeT7LXE4v+vTD0/I6ewZCKFVMkYzEyAiMUAuq1GJ5mdebAFaL29tf9Y15Nr3R0nu7WLSdv8F74Dqfa62BFpAtUwgh7Pd7ImrPbLg9VW0EgRb/LfLbLzYRkZRSe8WbTEA7oV6NPW9Hu842Yrx+LzyO43G/7/rBhdiKI2RukC5H6Dgyo5oRc+i7teR1Kqfz9Hp6XecJgvcqMZDro5B5wl3nfHAhEvf97uEhcThP6/kyX9Y8pUqIppn1NZ9Pn532ndvth6HzQ9fvum4/7j37NE9fPurp5fPheHj/3Xe73Q6QzGqtq5oyNy0gyVJzLSj1bX/cUeihqiq6YPvdPtaYpZSSK6FDijEwc8l1zfn0Op/P6zxPCjr0ftfv9rujVXjFy1LXLAWdF0UmZyQCJRdJ6yI1mxUAdY6cC13s+n4fQhe7EBmjh4guhKgpT/Mll5pOZ5HUH3bc+dhFIHQhqBggYZEGwGQGgMZnKG+JPapWq63ZBuHDLg6dD6TTdJmWtdqFrJB6JgQohgtjcSwKpggIxmxDR0OHwaHWnERV1pyWmsUqmH2j6tAQBA10oIp6NasBQCQmdo2I03Z+habUWAARKRB72nQFvHOhsZgNhZ2/Kg6DY77f7b+7v7eO6xikjkVqUTwcH37169//4W/+5f/gb/7Vbz/8Zt/vnfPFZM6JA/XJZalqhmRkSjWzCpmiEhJalbwUq1KmyUph59CsimAVKGqqgAZarCwVtahDTcfDqB/ed1Ffn0/Pr4KWgjMew9BHM50vi9YqAkKgSmqosmEG6FtfKL0qZ92WgxtL/7bnv00E7Krn0ap3u6oAtU1er4J/rQvYGBktz2/N/Ka321BDDUHQQAFmlnOepunWFLjNC/CNsedNXLi96FtPa2baDcNhPw59DCEAAgN4Qk/gCTyz944dAgA7Dn1nCfnsWpcieB+iD0JUvBRXhDxhF13sozqMu93h3d1s/CWXllaaYRVhBSVZqryk2Xk6rrv74+5+P+w6JHKmsF7mskyq5fI6SkrH+7vY986hSDZUJFKkrFCqbFKtbw7nfC9Wi1UACj56xx0GqaH4ZLWC1mVKy7rO83I+TzlXRDjsD7/61fd39++67piWPA5zKTLXRcWyGAhkgbXCnHVJtaRklpGMGT2VUhWRGSkQo1FdCzalsVLKWorkZOpUuR9YCQ3R2BAERIqUVLQWlIq1lJLSKe2OT/WmqQ4AYLXqNGXv/ND3cd/fv+/H/cuXT3+ZlleoAgrNpwe1KoixCpghIAI5Cg7BUlrndQFEdgglVckohVVI9dq3w2bOpCqotHEYFDYFEgUjxCa7AdwU90wNDRiQiINznoi9857ZN2MOYgJi/lpbBqbvxu4PD0enkfm978Jc688vFxeHh3ffHe4e94c9e5rWi9Sy5jXXVGoxUTZDM9EqUlWygXhmcAwKWqEk05zlcgGp7D0BuJKlKFVVNUSoWmuZqxmQCwgfHu+/ux9q/d2Xz1/+/d/+OeDLXexQeezGZU4//Omn82lSsGpWARmQAIJ3caRxP97E4d+W6+2RNqtv8P4Gobu1A2/Lwa0hd0P4t423VeDtbDfBn2bOy8zTNP3000+n06mUMgzD999/f3d311aB206+LEvr+bVtvK0OrYJoDb9WLLTgb3nE251/13frMAwx+hCIiBA8WiAMnp3bUNvs2Hn2IaDnYy65FpVapkvvwNZlqnlZ5iqVgH3ww26gzveH/fHdoVN8Senpsu6G4TLrMiV0tutHAjrP9rLML9Pyer6UDw+M3IfBE0OuoDmn+fXpy+np+e7+7vHD+91uZFYgUzAhNo6GhEzOf2M95pyPoNBI8pv9n4qVWnOuKWupNde1pLTmXJIB+NANu8PDu18fjw8inNdTq2sdMSLWKlhq88RAZvbeQAH91gtTabMH1Aol1WJ1WddasIqWsq5r0ZpBvVTseyXHpQAzNsidVKnVpBBIYAABswoNbnPbkMGq6LqWOdQ1g5gPnXdunWdQKyYZwBxvcvpKamCOwAyIAJkcZ7RZCpeaAXxkV0tumiLfYglgE1HYpJevLYCbbC8hkiPyQI00UwEI0RMBsyf2TNSU/QntKgNJN2A/AARH7/bx9+/3nds5x+rj07ycUsmq87Kez6/n82enS02pprXkRWtu1g2IgGoNWyUlO7KxiyF68GhsFURz1nUhETJnAJQSlUpZzbZsn9IqKsXYhT7uDz70ImHta4yfdvt4GAc0x+CRoRt8SqwqilbQUEELUIS+4zC4t2CStzv/bZB2uVymaWox3LL02wZ7o9//IlO4deZvSIE22GvB3wh55/P56elpmqa2prTN/wYiarTf19fXUkoL+67rbnCANh24CXi1WuNmLgAAjukwDrLfd0PnvW/pB5l4Rh+8c0QI5MhxWwJcJNzv94YQfSjLxJqX1+c8nWfCaubQXAz9OPghxt3gg5vXkvOS0qpVtULNVQGJjBAFaSkm8yoiuy6OoetdRyLmlKDkNBcpp+fn1y9f5vPl7u4wjJ49FlVznuLIsQvuGzJ/S4i8SWW2AqXUNad1XdIyLfNlSmsyESLwnedAkXsk7/2uO7zr9h+4262n87Iu83IpefXRs3daS0UixM4z7/p+CEjo2XXOo2iaL6jSe+8BZJ3ymvLrJEuWZgSecwWFwKEUdX5Zk7EBN+Q8OSYmZETHyN53AWu0/di/GcNubaFaJKe6rmVdOUdi0tCBAaP1TctL1bJlk7oN47YgVOaCdjYQ08G0q+ZFK7CwM+aNqN1GYIRG1C6sKWUhM5JXckZsREjUhgEkaqaKQN4FonbjtqEjGAhAQSiAshnzXQPGOXx3jPTduO+9KHw6p5Lm8/nL82U5vZ7m10+8/Pzd3cAgrIVqRqmoyqBMoCI55WlN07J4x3x/9LueAqNDRRBVK8XAoBKAQs1QMpaCIgCFJIe8ai0mqG5c5MPFutezPL28ns8rEI53gwmdnqY5zz5iv3O5iKgW1FoRRdXBSEReb64db2v+G6K+qWiez+cWY22DvXXa3nJpbop6t5r/Fo2tzm/BX0oZx/H2+Ol0WpZlHMdGCmgLUIv80+l0Op3MbBiGNghoqIEm/tGS/NtU8kYWuF3McT9yLV0X2Xm86vETogvO8TbJBYCm60NMu93Q9d3jw0NNa5lOXwifP/5cESqBOeYuxmGIQ2QfUspPTy9//MsPf/rz89MzzJOktTigtSTnGDmw01pqqbas5XyaqJrNg7vrhkgBqVY5nU4vT0+n55fj3f7d4yEOvpqAi268i7vdMIzdLn/T7c85pbRO02W9nCWvJeeaaklZijSBa3a+63vXBUNG7tjv+sMD+CErTss8rxezHALGMfq+w+BccM55BjDoAICIGdkZ1iWd5rXkXHIplmte87Kk17UsqZZaRdQUHUcKUEXntYIIqZIiA3vuYiDvyTvvXAiOkU1gHOMtvUQE58h5QiBTLWldl7pGDf6CpM4HsADgGJ2oVJtA2jLlEAjBTLOZmFWwBQzApIoTrYYrcmGniMAMxEbUtmsgbiBCJAfkwDl0jrB1fzkQBWQyVOaGBtw03qCJPQAqqEIFUiIA/LrvAQCgISfi1bFWlXk5nc6fzpcv59Oc5rWH/DqUofSe1KN6MAfm1BCVSMHE1+JrdnmmCrhOQMESKVMlFAOpYmCZwcxyyrmUmqtIBSumGUrWWrVCwX5ayly6pxeblqLqQnQu9lJEEdBBv48csUgQMTWWYnXJ5rJQUchvQY9vW/23vb117G77/O2ZcG0Hvl04WvLfOnNtJ7erM3e5HrfGYcsIWnHRuoDtDDciQAMIt1ygwYRfXl4eHx8bFvg2khSRJg00jmPrGjDR2EeqfUsQzMDAxBAAuQ0WNgSXoRkqIaL37IJHoOzdIoW8VyJh5Bji2Pe7sRt7ZpIq05K+fH7+84+ffvh4uqQhZSpiqdbTvATvwDB65zR0DKxS12UqpddSeqTQee+1uuapknlZHc6sZeWqAqHzFUUN1MbjN8pX7vn5eZkuz58+rpdXMmXEwH7o+y5EMEWGEEK/G33syUd0HdBAbsiil+ny5fXjuj6HHneu73ZDHHa+2/nQh+A9Ezdcu0BdS5rm83Ipry/n15eUl1KTSKmllFylSq1KTDF249Dtxn7XhwHNqVS2iiamZEAmjOwJgqc+OucQDYc+8BWxSERdH4YxgnrHWPOc5rK62WJSrap9rTuigaNnLgxMltl1YEHES1UpK+JKlIiUcFVMoiRazRJScaGaGVPr+ymiASM6okgckVmdQ+ed4wC49fCYAyACaQBWafdlFU0K0CCBZtWhAjYvh2+0YqWWl+nLjy9/Pk28rPlPn15/+vJ0mT5LNe9iBzVKChnQBBggeGLnGDypY0HCiG6X+RDFdO3oGXNVMzWoRtWsyTyXpvyXJVUtxaoomphWUAExM0yynsp0Wv15IuLd/f1j7GItpeTV+TDsB40MOLBjJFKltJbzy0nstcKylkWv2P4N6sAM1yF/29u7rjscDq2j1uLw9vbxipVssd3A9g3/13Xd7QnwZmpoV12wtw2CW3XQFH4bw/+G829t/5RSCKGlA/M8NyBwS0MaNbgBjRr4hwhjcND59q7tqpCppiomImJipojARI4ZiERFFarYuizLNE/LmkSQXb8fD8fD3f3dOAzLNE3L+jqvnz+9/Pjz6ePTBD4oBmNKWr68TF3AyHHvXAxd53Dw4LVYzdWD1cFhN3TRMazrWk2Pd/d959iyrYuIQFVwPZIDs3le5G3wa60l5ctpvrycGTU4txv7GDw5aJx7dgxAzKEfjr7bIcWqnEpJeTGoPlDvxi64OIwhDhw6dt4zMaEDtCoppTLNy+vzfHrO6bXkyzxPS0q5Wd6KqpkaRtd1XefH0Q+RPZuqZiVE55EYmckhMhiCESihNgKac9942jf0Pzl2CGapyiJyUhE1n7M/Xxyg2+/7rgsuVqJKFEvx68rrVMsKjoH2GDghFQJRBGIhl9krkYFuWvpmgLht+OiMGIibRJdjDkiBOSBzExsDdD70Bs4MRYqWi0kWNVAlcwZE5Nl5g29gZKL1srw8nz6tjEvKL6fzZXpN+SJCYAl0sXyqs9NamAmHMXSBvTKI1oKg4ByBdd7QLLhsuuS0plWWhKVac4oG0FJtzZqqVTHVDZEEQEgeXajoKqASo2vTiajCp9M5pcm0qpk0j53gnfMIxN4B1iwZwwL4jej12+H52xnb2232bcP/NtgHgLewv9sCcXsCXsW22xrRyAKI2Kr9W+S3Hl7OuQmHtV+/9fxbgtDKhyb13878/Pz8t3/7t+M4/v73v28KvwiAbMSGbAhqaICKm7SXNjZog9YYkjlCIjGsomuql/P5+dOnL8/PaynoXB9c13ewUSen6Tydz/Pp+Tyd15RqH9V7C45MsdaigOPg73s6DiESWE1Qq6o4cdv+aAJg7Mi7cHd37ALn6SmvFVKuRQr6IlZU9t/6DrrDMMqapMB8qaDZBwST0jtuHuuKAA5p3h3su3jX95E4IMq6zITl7rhn6wKaY3I+AHqpmHJeRUArmeVlPr08T6fXdXkteTUQ7ASNFHgpNVfDRpt1Hn3nxwMPowZeoaaUCDUge/adj847JCQzk/8ve3/WJEtypQeCZ9HFFnePiLtmJpAooMjq4rCaLcIXjsjwZf7x/I5mj8gMW7qazUIVASSQeddYfLFNVc8586DmHn4vUEuz2fPQUgZIZFwPX8zN9OjZvvN9RTIUh2RsaFqeye5VbZ7TknLTxKrBR06dN3KYUziN9O79LAIvX4cXL93Ni21s1ITn2R4fZP8gadGuw9BEHxFQ0YlHI4LKbqnZTCqYp9KzA7AhWa3wITlCjxAIouMG2RugahFV4taFG+e2wE0pRefHND+m9MA5N64jbJk75miA1yTxqpqmYTztwVNKRcpsmkRzUSw6p3wcpjkWK9PiycHuLm499QviMk1zyiDYGnrH3Ebz0YHwPJVxmO4fbZlXkVY1S1lOkyxZ1YzIxdA4H40b125jc+vbzSvnb5WWWZbZ0qyPj8fP9+/nNHp2YJZyATDvXQguhOAc+i4E2gJLbLeX+uXFPq99+zVn0R8D/i4PXjT2LlCci0lX732B5dYeXoX3VUgvnud/LwLB1fIvQKAL4uCSa9QQozYa62jgX//1X9/c3Py7f/fvzmerxXLShVURyWyFfdVgnwEQSSopkpkUNEIDWrKMU3p4ePjdDz88ff6kaYrETfQE8Hj/cDTN03QapuNpmY8jFegcbxtrOiNAyZxO1DO+bfnbnX9523qw0yHNk4hqx+bRRNNpWJac5mVqfd/2bd/4MR9tgSylpDRlhaW0pss0q1wZf9OEGEPwnohKUcmWS3Ji7IgcM3oAL+qhqpGAgRUri+YByswEjqtSAIpA0TQvJRUBKWBKYHkaD6f9OO5zPplmDsjMjYsWnDm3jNlyAUP2sd1sY79xbWeMWbKykhVTQuVQVa3XAWVAVcmSREDzPH0xbplTSXPyrihxIRB1xh05YPPOgWMxTaAzmGc0BstFNBcrBSyzy+y1VhSZGkJnlhGz9wJFxaqoMhABEyKCAmJt7a3EPJ7QE3kijxQE2Cq0mjvydy7ckd9SSXMGsXFJ2ZG1XXDcOdcwBzXBq5TfzLSYFjVaFb0Z8CwJZWolJZlEyrxk8wSeDdkGxvk05NOIx3lKGpDcbuO/exPbEOfcTMX2YxlGc74WFyEXGFRn0SICRkE8Ti6rNRt81W3b9vXuZmcGh8NhmR8/f364v/98mu7VShNbEzqeUs6CCE3jdjftpg9Ny8ROrVFtzJ6/D14dF+O/Tq3/AeOvQ0E1/q87SDXgWgikMyPwPM+1gYfnWb3Lm1dLrjvINb7ggjKks0ZgDR9qCDZN08PDw6dPn+pesK4x05TTvEwsmZBr45yMq4xSJUanOipSGSYRDSnnsizL4XD48PHz08NDF4ijN4NlXub9E+VMpkuSZUg65wbsReu+edlsbjsCnIbloaTW9GVDr1t+2ToEpcReSZja6IJzqjBO4zCP4zSgd+Rd7FqZ2jSeSi7jOB90tqkI4fyV52dHIbrtrpuGdj5lsMKEjlzTdH3f9/3O+aYoMTcucCkzZklplvmQ05ysEKJ3jICisORyHKaKw6tsbEDmutjyxglKWdQyIrWuvQHO2dJUlnGRAsjRx67rexcaQ1QX1TVmZQEBVZoNrDQI7Dk6YmYTXeY8zwfeHi43BsxKlrykhWconhiCb4pu0Vnjp5eUA2NJ4v0pesBK/TsVSHrTW9+C8+gC+CjkYtPdMGFOJ7WBuJAzMzBamRnZGSCCACiBABkTBqaA7JEdkAPyBMEwsHPkd8gvyL8I8cZgUHlMky3TAh6Zmhi2zjXMzkSv8xdEYoyeN02IhUrjMFBy6ATRcSCOYpqVFViF9idNeZnTgWgZJ3448E+f54f9Mozldtv81V++/vZNF32zYB4wHciQg/M+eEZ0pJ6yLuOS5qQpL6fh9LTfbqHZfvPydbPdvBHVh4fT54f9r//Lb/ZPD/1O+847bpaip1M+HJaSl7ZzhOqcGDpEKxnHE4s8f59rMO/FzV673K/M/vqvlXUXACrV34XSr6JuKztY13WVk9/MLsN/Nb/gs0pnjRSuo4z6e40dKkOkqtaWoapWxpH6QVclBk3TNA0nrJKbYITsKRCsc2PIlRwDSK0UEVAkFCk5z+M8Px2Hx+Nkm+gQo+mS52X/SCX3TWPAmsWb7Rzc9eEvv7978fZGDO/vD3YaaEq3kXaevKmhxegQGxNo2jbEVhSOx/lxvx/GAzpfwLiJvuvxeBwXfdqPT4tCm9G5ZZouPAv12nLbxhcvblDT2HopyXtu2th2bdf1se3ZBRQzhSWN06RakkoByQyaJQsagkPCIpBLKbKIgadKa1JABRhc4x1ui4ScZgCrLZEQKQYKHkpBoEAcXHDkvSITEhGCFUhL0XnKs6GwJ6crr70ZXsD210dlytWiBRQFp4kPg+dAm971O2las2QiClqoiBawBRziZgMUODaBnFMDdjE2GwCVkhEXImLHiGaCdUKBGADqNVwx/USeXCAXkRujaNCYtQYNUETcGnaiPmdN8zKPpzQNWjL6hlzLvmPniYj0K3E7Ju69vwmhISrBY6DF21FUUUgzLrM6FEmqWUxlmJZxWQDycbKHAT8e+X5vT4/p8x6Ip3GOP/umB2bxyQyxabhp2rZpms7H7SJ4fzjtHw+Hh8dh//7z46clwfdDEgEkL5KPw3T/uP98v5/GYXvbtp1vIolYyTaNsiwZQVULmIigGSwzLzN/JT14SdEvhn0xxWvjh6t8/pLkX6B4l1nA63jhwq5fh3Yv3QE7E3JfeP4vD14bP13p/F0C/qoasCxLnRd6TlJUc05pnpAJgBSUgYsrjI6QK3EEoJqWIpJLEShEUN+yFMkre5c5zD6pz2MaRm8a2CORmjnGm9b1u/b7V9sXr3dLMUv5fWRN6JnQcJ5F0YoBet80vm065piWNI5pmhYzYGZyRCG4boOxLxjmBMOwQNambdMwfuH5AzO1Hb95s+va8XQsKa2kGZ4AcZpn0SmLqICIlVTSskTnXtzetG3rCqgWJAQi9kSeOZAB+hhNZBiOOS+o4phi7KN1C01Lnpc0i2ZCMwPziMRqoqyKRoTOeXLReQcmmcay2JRnycIFIKthCR6c8y7Ejb/ZbLd0loUjxBBcCN4xA5AWm8by8ZMWaVx81WyaZgskJc9JxqWcEqQS0FwwaAtHF5veuRaxBSS1OaeDKJkikmOnzAaiJlJDO1FbpVKIkRmdRxfZd8CdQqvSirWAHWGD0qnQItNQ9uPp/fHxt2n66JyF2HLo0DdIjHhWd7oM9iBz2LnmpYsROLuAnpdgTznNNkqWZViWAjktqRRDcI6gGTEX/nyyUVFiwzfsC82L/O3vHqdFm76/uetCEzati3237Te3u93d7cuXr74tyD89PL179+H3v/lhPJyy2DAt07KM83QchnGZPj3cPx6ORSDG7mZ7c3sTQ2CT4hwRknc+Bm4iN4GBKRdUAZXngas/duaXnty18cO5F/CVl8bzCMA19uZ6Q6kevkoA1Ryhxvb1r7W4aFdMoV8d9QkX8U87TxCN4ygiu93u9vb2Qt1tZnVMBo3MoEjJRsSFyBM5pkooqQAqUnIuCkKkUkRVmMnH3oVlkULTQpY6SYE5kGfnDAhIvafbbbvbdTebtgtRNTMSESlTVjolSKVkEOPStn7Xt03bIVLOsswJDF+8ePHy9cvYRggO2576G2x34IdSZi1p3h+X02DlyvOnaVYVQgwhSNMCUU6lqGi2omlapiJSXRwa5izLMqm4JXdGWnKyyvrITC44T+QCIPsQUkowqEgGFQRnwMTkPApgkaJaiiYwQ3KAhAZIIKYmher0vSMwLSJLKTmlwjkKOjEsqiDOiAldZZvD51ZfCK6JgdkBsKgB2pJtmHFcml5vuiZGxtiW5Oa5zAgZPFNj3Ak37H3H3CB2InlePqud6hZJTAQMZkBYWa5t5fBaiYOAHLlI3BhGUZ8LFFUzRVJWZU2iViRN4+N0ej+N70EOMUYfOuc7cqvxExJeJ/3IxBt2t+g82eJ4aV1zG2LI2UPxpYAtYslyQgUiT8CaaZrh/qksDNtt3PSND93pYXp890CfTr84JL9RcNR4blvftuydMYl34hi6prSxNEEdm4EWhSQllTSncRrH43Ech0UFnffORe8DcxUXUoCqbu6bpgmhyQoI6D370Hzxda7meeCPYv4//tNXIfoFbAdfDv9dRvQAwHu/2Wy89xec/8Xa8TzM99WHXt7/Otaoz5SzBHhV+7sGkqkW0YTAalaKmCEaICqRICGWSl6/srVWvvrK8L8seZ5yyrppvXfoRD1Z410gAGYVUzR2vOnb3XbTNq1jJ2XOqSCgIU9CNutxzALFt+baELuuiXEc8zRPoqVp4zffvX377RsXOWspiOoj9zvXnVwYcp41FU1fgnwePn9S1ZRLSinlNM7zcBpESvRsIPM8IlrbdG3btW2jjRFCKeXpdISTaBkR1DvnYwyNOR+ImfgsLQWVeEdMAZfknEdk71tgpOTGWUpJDpTQ2LEhFRGZZ4PENMXgwGSexpSGnIcmQhZfDEGsqFgSBGWSZpou4R8iBu/bNjAHJFarMTog+9OQm0Y3m43vN653ocmGA82ZPPtIoUPnARjNSJUkj7bgulIQmAmQTcuq9Wl1ZAdErJLyIzG5BrjN4lO2cZ6KVrzAxNwwOyBMaTgeP6b5s5X74BRDT6FzvnPcnsW4EJ8dPwAyU0u0qWQDDNx5+nYXF7+YFCelseSgkDMm9M6IDYikUMmWFEJ0ty938e3mYXM8POxP8/RwPLWD50ANRWYuJT88PhyO7x6efjCA03zcP53S8QTlgKTonBGKaSlLyUteRBKYgDGkrPNiXnRZSs7JNCOAd76NNzE2eZgJcbfrbm427ooA52KilzsF55rfV8e1leJZ0vs6KPiqcHAJ5mtqgIgXgsDL+/yxnV/e6lIRrBCAGjJcsoNrxPH6RcAKSLaVqkRBAclMEUSkboaqIPX8UI0JiVlVpzE9Ph7fv/+wzMs3d9+9uW06GaMkLwVyyXlZkVVMwbVtt/GhU6XjaTodR1FQ4GOG4yz74wKUd0R3SG3bBMefP9+fxkfgcvPi5ud//vPX370RtmEacsYFwG823d1tN435RIGBvkyT3eGwN1tlv5Scsc9AqWgqRSXlZXRM0TdMGKNHRAOdpmVclrRMZRkYrWvbOsyqCkDknAVkQHQuuFCqgKGYgUqlS3AcASxLRmA0Y3TsgqhbSlmWlHLxRNQ3TIC6EGZmI0YDVTPRirCpTdV5Oy/yXLyFUrQUIwYiZCLAKqGK05SOh3mzSSHAZtP4tmtugmsFiZ2jEJFYBUqRLLaUPOZ0kjyaKRBSZQWsbHx0nuxFcCIKgAxEjOQN3FJsSXlOWQwcG5OYFREChCUNKZ1EF+9caGLsXsb2ZQhbx+us+LVDq8uubfpNt2sDClFpTtY2bvGLoORMkIMVDxIQgoPohRgKwMGZiSmAd67vmk2zKZOw5/E0ffj05ALcvWxDQBOfNY2nUy6pFlcAyzTm6bgs06CiSjrPyziOyzSmecmzlGQidTyJzFgEDX0IIYSSl1xrcCIkgsRuu91stxv3rD70tbu+uOVawLtW6a6V/Lo1rDItrpKn4cVvX97nTyYIF6zUxYdXz3+B/X1V9ru0EirEuFb7KqV3pQO7HuyBOkyqpU572LqfZFA1KFWXqbLnmK2KLWaUsw7DfDicjvujqQRH265pFbx4WFK2qeRFCZquAQ7EwTeNAmrRlAUAu66bQSahtMgxW2x8u91sdjvnnZQ8zaciy2bXvnh79+LNXX/TPRwPw1SWwlMx9SFsNpu728TEeUb4Yi9zwzSycxzb0DShbdui3Hanw3E47NOSpCATOWLP7JnYM3KLDIvMMuVpGgkphMYrpKUsi6RSfIg3QN772PbEPuUkUgjBVLImVPDOe4679ra4XHIyQ+bWlEqep3EaTqfG4zbetV1sHCkEMWM2JlArjEzOsfO5LMNxGFOW86xCET3u09Pjst1SaIg8ICMDKmiS6QhAZKUksDebTd/2zhovgrVsWIpl05SnND+k6eM8vCvLwcCIHJgBGSMAyrmnawbAQREAHSIDIBbROS1LMgMjrNrhApArEQgBNL41x8Hfdv12u/t2s/0uNDuuKKUz39fF9Xvmm12f5psuOEnRw0x5n57YioEpk3qyhqAha5w1Xol10RIZ2JSMPDgHaJJVExGkpfz+9/c5ZaY3XWyKL2Y6jdM4DiknJtpsm7zo8TgfD8sySym2fzg83Tzd9P08S1pKTjWEZmbvXANoMfi7F04yf3z/aTgO+6cTMWRNfRM22367fS6SVZusNlxt/kKPOwzD6XQ6Ho9VHq/C+CoDT9d1L168ePny5atXr6og7x8nC5efdob3XbaVy0SwnBlBqz1X+7czaZqeyXxrdWCz2bRtW7mGP336NAzD3d3dF0KdZrYiamA1dQUxVV1Hu5iZkYzAxExMDaXosuTDcTgeTyUnR4Ba2NQ5JpCMmM0WUxfCzd2dC82cFT3NaREwIu43G3Kb4yHf3w9DkcL+7mb3/a9+/rPXLZZpGE7zMjlPr759/fZnb2PfFNM5LadxmTLPGYsZNs3u5YvF8/z4pEjwHF6CY+fIMXnywbd92wITe1M87I9zUhQIuqr/5jQbOKisxY5jcNq0jrhte++DiKVcxnn2Rdq2JSYiYh88IgmpZLMaL2OtobGP4iTRXMQAHYAhYOX/wWJ5jhbBR3aOkRskIwTiSsBLREzsiT3S866sosMpHZ4WMB8SkwdyVY4ezWwayjikcVzSIiuzlY8MZGpqpciSZU75uCyPeX7SPIIWYl/DTTCj2uJfm7hqiJVRD10k16gFMVekqAEzI6wNC8JK0I+OPbdbIozRt/3NZvum7V56315P8l0fhNh46iJHR8Vc28SjC0uCYTJCNFxLBMzgGeuAIdQsXE0BtFhJxWRIeaqCiIfD3LeNFEcQQbxoTrMNx3Qah+Bd120QqJQpJctZl0U+fXgK3jl2ojgcp7TklLLzmhfJSZEJ2W+3Li8wDqOr6l7su2334uXd27dv7+7u/LlIVhHydZCujvSczkdl0a3jfdXTVgwvEbVte3d39+2334rIq1evatH+2tvDVdhfDbgeK9fTmZm7hvc1vqgP1tdeCocXIEDdVlJK9/f37969e/fuXVUK/SpSAFNYPT/Wzaeq8gAgkSP0gA6h8iOpIZqhqORSDKBrGwbRPOdl0MYRggAks0XEteHFm1ebzfY0LVmFHKnpZrPxcSPiYpyOg+hYBIxCuH3xYncb0ucp54wETQw3d7fdbpO0lCkP8zwtaUychE0JPIdNh2giSm2PV0vO3d7dKVgBJRaH6pyn7WYeUyk4TSUSmkLOZZrGkkd2xM4DUutdc3MDu1vPLsZWAcZhSqmoSCmWy8IFLzkaIokaGAUfmBARCcmzdx6I/ZJkSUVNvePgPANLzuNpCg52rvVtCDE6R4CVSwsNwEwd43az3W62l9xSxeapHPdJSvGBzSmSEVOdLSUCotOnT6ePHw5v3778xS++ffXipg2eCFVTkSmnY0n7ko6qmTicK3BiZmBAwIhqKAYKKsTEpRr1ltyNaF8sIGbnjKl2gM+yXbXq4Jk5+BBj07XttuvvQtw45+rsF6gC2BdCSqCoydK4ZCh5EdUk8HjUx4PF4D0SF/Gkm4CbiBkpOJfBz2KpLMlgmfI4jIAyjicDYefQgF3btrdN+9IxlzKVfJpnPh207ZjpxkfnXSYcRHCYs/z0ME3zaZi9909PY7UcANo/ndhDjN670LTti5ceAZjg5u725asXb797/ebtm9ev3rx5/cafkTallE+fPv3www+Pj4+Pj48VRV+FMS6Kfddeet3+iH766afPnz/XQP3t27d9339VF6i/XPD/F4hu/b0OEddagJ3ZQeq74RWVaN0+aoX/dDoty/LrX//6d7/73Y8//lgHEI7H43NdCYxNSQUQdGXGFClFTBHQHDM2ah4NDWohkBEJGchzv+m+eftKlzEvp8N+iXiD7AWgmE0pddS9fPvyzZs3w7yM0zTOY1Hd3kQDr8IhHh+elsMpDdOccwZCZFZUJOi61ndt07UK8HA4LCUPU1qS5GKligYiUWDCLpILdy/wWrGHfTAVyYsuydEYG/C+b5omxjoqNKecp3kxzQDZeWrbxvsAa37lnOPgnSFJUTFVBGR0jgGslGQKRIgGFQBV5eYQkZmdD0TkXGRf0CWgDODabP0mlzSnIqdx4WDEghjBHNA6KF+9MRJF76P3F3A/EoZAIRIRqpnkM/R6PQxRlyXPy6yam4YdCe42MTrVbLqYLqAZAYg8ug5MEBS0qAEAIxqhGaqBqCbQAsCGkXkLuMkaijkAQ7I6p1+LgXU2gshX7dkY+9BsmqaPsfc+EPF1Mnl9IIAD82gGBkxNbGK74Xajfpi0jDmVEUmg9bbr+BV1220f2i13BcODLrCkPM8zkYhU+SOPSMQ+JRxOsrBO8/L0NO+fluMxq/rhlL0jAAoxbLa9ERFoznI6TU1jTYgvX/qmaULku7ubm13fb5q27ZqwNXPLtDDBbte9ennz9rs3L17ebfrtZrO5hP3TNP3mN7/567/+64eHhyqtd3Hylwwfzny+cC7mXTp2Nzc3fd/vdrs60lNxOJcIv/6zevvLL5d9pKKAQgillAtHwKXUd0klqnrfhw8fagzym9/8pmp+OOc+ffr08PBQrpRtGcAjIJMBiEAxQ4O8hg+YpQh7AkJgAgJ2UoxQ+6559fK2ZZ+OTzJ9BilNCG3bkitLTsUsq3Lw7bblNvjW0YCiGnyH6FU4Fbi53Xx+OOBe0zKP42kYNaVUVKFy8ztXAI7jNOVciuUCpZQiqEjEjOjAO23YmsbwyvPPS8oi45JUZDpOXb/c3Pno3ctXt1qmp0/DOE0ImmZQTU1c8S6iuRTJWWNsX9y9arpN17VN3+5EjMA7yiXN0yh5YWJEZAMzlJRAXAjBea6sXhS4MWtVpjkf9gticL6fxmE8PR7nKT8ehgn7NobgkNn72HWtj00lm7bKpHX+JsHTq2/ab3/eAXpVl4SK6LVQjmNGBkCZ59P9/QfHyeFrg45QASpJcwTYKAbTDJrAMlCqkUaV1gMCsyS4lrAUOqONWiNCYtXeQc0IrPL3IjI77ziG0ITQxtC60DgXKuXjGeyOBvBlFRYIsXG+jw0QAZpYn0v55hc/W0Af7h8PxzTuIU/GWm52sYRbunm7e/XNzi/ht3+L+0MWySk3ER2xdz42yBQA8OOnx3mag+dpmT59/HQ8HUvJReDHnz40sUk595v4s5+/zrkYKDtsou/aru9vYmyZXdOG7a7Z3bSbm77r+jZ0wTXM7B2HwG3jY9dWKTgivLRgT6fTf/yP//E//If/cLH2i/lVlN7FLK+huLVKl1L6/Plzjf+reoeqViqe6tvrcfndzmpfF04O733V6qrjPXW3XWnGzmc4TdO7d+8eHh6qNOjpdLrIBH38+PHjx49V6uu8KWNk9jEgOZPKjemmeTrmeUk5zzOhY/bMjskhO9SM4F7ebTdtn26m4dE/vh+6SK9fvdrudsO0KOr7zx+WXE7DOM4TOxfbiA7VDMGpYcnYtHxz0263jfto8zx8/PDBlc4tY1nSaVqic6koiM1Fl6KgpGolSyqmhGTOiMxwFJ3E9GqtudpzXxZJy0KSc9YQenZ+t20l7TQdxqMUkZyKlLlkFwIbesAiIillAEtpdMERR3LsPSMxOwbA4LyYOEZCNEciULKYSGV1ATULEEN0zjExIBdhwwBOBGCYx5KymBS1lIuBIpEoIJEqijdCM1nSvFz6ls7T3Yvm7Xe9WVDlpYAUEdWLzDUzIZlB9g7M5mU5DVNDTqs0CyIyewQ0DCoFNAEsZl4tVN4eMjOoNLfJCAyDQSfWirqipqC46nZgNXxm5zg4F4NvQ2hiaL1vnY/ee+fYMRNdyB/sK+s3g6wwFzOUqgo9Fi1MmeiYy8OYTidZBtGsh6zYgbSgrR4GHZLMOQ8DMOe80DJJBQJxsFzKfn/Iy9J1UVQMOMau67DtYoxt2zXb7Y7YIzACGlqtrLRNu9ve9v0mxiZG7yM3Xeg2TdM0wcUYYgjBMVdpOCBUlXwmVqtHSun9+/e///3vL2Dby8wsnAf+LvX86rQv4lkVZvv09HQ6nW5vb6vAZtXVvQz5XnrycOb5ugj+4pmQE89U36sNf9lbqZ6/tglrhF+RC1+9qm7Knl0bYogtEUuRouwN0DQnb0VyVtVsYkBK3gDUTIhhE5tNYI3uhIseW0fqHYXgjKjb9LFtDOFwGp6ejv22c8EjE5qqlKKWFYC038Sbm3bbB8nL4XHf2NI7kyTHcV6ITuPSNH4WywqoUMRSKkuWbEBOghEiZwH5cqE5IjbQkm2ZC6SkAk3cN33XNPzy1U3jytNDvP/8cJrnkoqohInRS9u6xjvCao15mk6qg1VkWuy6bhtc3G12YK1DBQRVy0mWOaVU8jIv0yxqIcTtbhvbhhwTcdM1YmWYh2yIIUZnm77vonkWqpxuauM4z1NidmimOm9eneSMWGJH25vu9Zstu4joipiIXhJEACUCICBSBGB03sGSBjxJU6kZHCN5Bw5QkQ2sGC5qWawACIKAFCuzSO0feqPerCvqioJaBgRCJqSa6TvnnIvBd963wbchtMFH5yL7SiwVmB07BmKDyjgOXyxHtfsp/WE/FEmpLNM8fX74/MO7Dz9+vn//8PR0GJap5EVKsfEw558eP53K3/3h05zTH97fl7Iw+TQxkS1LeXpIkrE0RbWgCRO0bei7brfb+sAh+H7T3tz0m03Xdk0Tm7odk2PHznEMPsTQrFPahJWSmFzlHlkbazVUL6pWagWumH3RWpezCHeFyl27+mpdFZBf08hqySJSd4c6rle98UVRoyb5lYejkvZXe77sL5divpnVOv84jnWA/6uu4SXLCCFsNptrDs/611evXtVRQgAgpCY22HQ+toa46GKmSAGigd54CtO4pCRSzEzBKSmYCSE49cyeI1LrTm2UNA+nPRD4tott2Oy2OafD/vQxPNyJNl0DpGKSUi4iWXApFlu+u+1evdyOB0vjfEClbSzZnk4ji/SH06bxiUGRQGDJuqQyznnKQsydoPcRwTm4VrcER4gIZpK1ZDIBLSUtGpznEJ2T2HR9n3JBonlksJLFUtImEjvXRM8cQnBImFVEBUDTMqsiEZkkIo0OnSPHTJGJiF1Jc8lZqos4nU5zmtk7jo2Pu9gGH+aqKGaIQFXq3mhtyZkUERMlM5VSpmsRxVpL77oYYiTytSK0VoXqxBUonAfyTdAURfKSEMjMvNMqrAmkBqYACoS20mwbogAkk6XuMwBkEBWiGCvU9h4SIREjEDnnXfChmn3nfet99C46F9h557xjx1VdheismwHXkLg5599+vP9Pv/9RyjKncRyGp/3jpw8fHx72T8M8llJAlUAYM8JxzsVOxwkMjAA3bbdpYt86YmwjNN4IXb/p+67t23a37W9vdpu+a7oqXeGbJvabtm1j04YYfAzBecfsmJ3nyOwIuRbIwExroQvU4KJkYKZQpY3N4CzF/EUkU7vlfd/Xov3F1V+KbdVQq/XieW7vkpBXpd15nmvk772voz6qegECXH/WpYF3KQSM4/j09FQRu/DlUZt8iFgxglUOuEL96zZxDe9dmVeIRaGozlmkKDEguBgaU9QMoKmAIiKhGYjImdrHBSJmJ23ni7PK39z2rTLd3t0ej8dpTofDqela8gSoYnnJKWcpirkgogWnbQDx1VUQh2gIiqxFh3HGcbaGDMGKLbnMKc9LWlIh50MQRiNS/DLCdARGJqiLw9REaCJFQjKQpGnJx+Ooqt98+1bevNzvH4fhVNKSC6TFeYxN49u2abuWHKdcskgWnOf8+fOHaVpKSsy47dvttt9u+6Zp+9h2hjlJyZKLjuO4PzwteSFH/e7mzduubWLfhsHjQdKynNhUE/QNB0eAXMtnAODISbEsoOW6DVNL51hh9wRgxDUHpJXe26rIJwIoGjLWpn1OKlJoESIkMLSiOgEIE6GrGxY5doiVjw8MnIFTCwYODQgR1pZiJfDywcXgGx8aH1rvo3Oeq7KXc2fOXlezfkCq29Jl7LV+k9M8/8+/+e3/+L/8NUDOeZ6GYT4N8+GU56UUQOdcoxCAAT351vvGu+A5hBB9s910r1/0u10b2+hCRHRt2253292m7zdd33ZdG2MMzFSpbojYOYeEdUJ5paADREBVNS2I+TxODFZPGEwBEBQA0BQUVhVixZXR/Groqlp+bd3V6l2M8VoSb7/f1ykaRKy7Q53JvWQBFRdQyfkr/0+Mse4O15vIhainvm3lCDydTvW11y2AP/b8tTRwc3Oz2Wzi+ajbUJUAXp8MIKpjyklLyjKlZKLBkWN05JiVnfcGPhiAKVg2WSSXnC1lImocg2TfuW7T3Ny83N3e9Tc3zTTvD0dVSPOSUjLQOrUtWupyVjMtpUwpz4eyDAS573c3d7vbF7u8LIf9kErRLMs4mTkj0gJzztOypJRNawmOmBBUTL8YbXKMyGiMxWF2RIwFZMFSVb+wCBQFQ4zR393tmsCHx31Z0jwWK2hA7KypjGwMgIQIhYpqyXmpQEs0qJzApVjTNFXrxPvYIfvgU16K5lzyskxpGV0AR9oEagJLhmVZtCiAl+CZgGnVvztjt0S+nB1DpPP/AYAQoIr1XfOVVz06OgMdEVDV1LQubARFW0o5mmUCRHbO+RACxoBoCqBIBt4sKHhVWml8K6qBHHPwPgbfBN/40FbWO8fRucpt6J3zzq1unwhXz79GLtfoqxW05pxjjKjWoIPQoxkjE4KJMoBnDuwbF6P30bu2afpmu930d7t2s2lj14Smcd63bdNv+q5r27aJPjjHXHV64TyGbmigKkW0mIpWezZTE6yISrC1FYlka4Xy8l8DBTWtDwF86fQBnHN3d3fffffdz372sxcvXlRS3WpOpZTT6dS27cPDw9PTUyXbgDPDn3PuAr+rnBwXEp76BDyL6pRSanRQjfwCH6rV+0t7/+uO/dVMUd1xqqpnCOGSSpRSaj5SnyYix2l6OBzmAlksKxBAIxSYAsPafqg0qma5lCmXcclLUTUggtZzIPTRt03X73bddhvbdhZFZjVLKXtPAEoMJlXQVSs4htDQMmNpG2pC9+rNi9vbm75vJqLYNLYsBGRiUkRAc5ZpSXOqOx05gui9dzSPc0nLtc6Fq5VnR1awmJpkTWaOsG07a1qO3emYTu8+dpG+fXXT7zY4zft5Oe6PTwBxCLt5K4B916IpEjqitgkv77Z928xLzilLkmmY52lx/tC2bdd1281ms9n2226zbfs+7g+Hx6eHJHI67olnE24DvbzdeC6Pj/OQRQFTgeDVO2KuyRxIObN+Xo9/sHMXxpi6VhVXG1/jakNgALiSKyQEXgUVrZgJ6FzKkMtYckYj72LT9mgb58nAjJwZG3gtThXrpURiZsfsvYsxtDE03jXONeyq2UfnonfBrQczMzHDudtsAIBAV56/j81//8vvG5hi4xhBRUCUxSrXHyKCASMGR8H5JoQYQvAuhOA5Ru9jcM4TO2a3soSvH1p3RatJqek5M7eVkEbtItyldkm81it5aameffr5tatPNABABdIael1Sy6Zpvv/+e0T8xS9+sdvt8AzOr034ZVmqrjYzPz4+Vud8KQ1cBDkqz38t7O/3+zp1T2cpvsPhcDweD4dDBQvVneLC23MN/r30GuDL+aKacdSA/8LYf7071COX8vn+/qcPH7I5Jed8450DM8l5AZGScp7FxDMU1XEup0WGWeciasaMS6BNE3Zt45rOty06N4scx3F/PO6PpzzNITIi1HBTc6n3xTFD8Opp04XXb+6cb7757ruu60pO8zwhEbMLIbILZrJImeZlmlJKyYp5D8Fx30ZCOqV5nga9SnwcIiCaqWjJGdRK0VwIycVWXdu0/SLyNI5pyVbUkQUET8hMIppyGaflNM5g5Jkcs/PASE30jilGv8xpGpalKvemDCvZCZqamsYmxBhvb26IcJwXUSuSJSdE6Pto0J+G03QqyzHxlJvATXTeO0cEalZEspYr5TFEqjEFMRNd1CCfF+iZMLuuymq09c9YawJ10dY5BURSNVAhFFnXUBXeQACn4LSuYAAkduy9j56D900TOh9qht+QC7waf1h9/mqQVBsMz8ZvduHtBoAm+l9987ajFGOdUAYyc1Dzigp2AAZkh545eOe882tZm2t35SwliOf3r//TqsT4PPNy1VonXA39eeu8GjWC1eD1vJnaGjRcPP+6IdQd5Nm9eO/fvn2LiG/evGma5mKW1zV/M6tRfU3U8eoAgFJKzQ4eHx+Z+cOHD+M4Vs9fcfgVNTQMQ90jLkR9eMUgdh3qn7/LF8F/TU9qxnG9O1y/pIg8nU73+z1w4NA0xESQDdQEJEtJuSyqJZEW1TnBvNiUYClQZ/UJIDBq48RoLkXnuQAchmGclmlZ8rw0yxkOz4BIYEjEMfbKYlPOnWzJudCErgFHec6pZEMg55wPzvlihlK57Sw4R47aJtxsuk3bmFlw5L6gVgSnYCKacp7nRCaM4GkpIpNIs3m5uXvb9BsHINNhGqZUUklLDO5V2xWAJWdkSqmMkKIP3pGoIqlCIdPokdExgnM4jQCAMUYAPBwOj0+PSNb3/atXrzfb7etXb4rZOIyH4+lhfCyqm67vse+2N4e53H+8X3Lqu9i1sWsxuFq2QxTKhS53B5G8jyF0Fb9YS30rhO6ZLqKaHELdh2q5zRAA1cCMTdHIkMhRy7SYKpPz0bPzhKjg1VS1riQBQCJm9tF3PjRxjfaDc8G7yC4SV+P3q8N3TMzIXIWx15gEsUKAr29LcP6bu9sIs2NGQiIkA4dV2wOR8OxYjVYLXw3ctNjZROn8ARfzRgADqq3FirOu16FmRYRUFzwBGX6x6M/vYKqGdX+8TMutn3c2ftUiRa5yS+fczc1NFcmdpunx8fF4PFbBnO122zSNc26z2bx8+bJKaC/LcpnGgTMV1zAMnz59AgBV/emnn47HY7XMS8xf237XYfyliUhncV77U0d9/qWCcOEavNyOa/tXkcp0EBpw5hALAoqIqoAWkbTkJeda7gfFUGWakAy1EhywmsuCw5yTPJFjRToeh6JmhsuSxmEcTkO/bWLjARiBnYvb7Z2J5bn4AoVzMXgcT1YkjcdxOBVT8o5qLUkKI3nyFNg11ISw3dZSb1OK3N1sb7bb5+IlgKujr4gMyCJipsSmyzwmKeba29dt293c3E2o0+FTGY55GZlds22j9yG4WhovRYgAENQUUQiFSKlWExywJxcIkUN0iCya07IM43A6nVRBDF6+eNnECBU9VxYR6do2KLwUm0WfDtOwlNNY5gTjDMExEZIJ6XKc5trGhzrP75oYe2KDVbJKa2yrKwDHAKowBhqs4+iX/Z0BDdkQzQIzKwekaFoQlRBEUuVnVgNRUqv0EhXf2MTQhdCG0AQfnXdn4w+Enl1g59mxc46dAyKsqo4Xa8dKEPSFsTHRpm009bRy+hsBrKO/hHgWrtPV9yqYidaq8tVs/HlTBFgJe5kIwGBtK9gX3cV1l/gTiEO7ig7gHEo9G88Kcq8Flq+NCs4Fv5rAj+P4+fPnx8dHEblU/isD52azuYhnXUJuO/fhTqcTANTo4P7+vhJ1Xg45i3lcoonLz1oRrNihL0/cvsoIrscrLznC15eiqpCbmglYRpkNiqqoiEoRKXUquIiaobECIBE4AGPiOvUDWIpM0zxMqgACMM9pydnWsVQZhul0GtVaIM7ZEMn71ggM/aI4ZJlLtmliVWcZCdEzsqtiEozs0UcmIIved128udk0MSKCKXRN07UNX5WWHJgSUdN2kvM8Gogwsyks02j41B2fNoR934HMh8/vD/vTMp8cu1v2my1v2wYQp0UU0ICyUc6FQYJTNM2iRSWLiikwMCMHCt43XfCDm9MyTFP66afTOEnRm9sb9ry92exut6paSp5zCV3ruqBg/l14uN8fT8tpyEhAaAgFy/Dt41N+hl6S920T+woCKKViLouSruGB1Sr2c3NtLVcpnFfrmSUGEZWMUAuCTCLzPC5oAkS1zg/UMHnnq8F33nUhVLSxZ65VvehcIPbsPLtq+oxMsBYjn7HllcQHzuykXxjjmeLn3FhTPlcubTWPdT2frfv5pfSFIeMlc4dziHtVkF//c53l2nmg3f7okcs7wBdecX0rvSLYvuwdVS3De388Hj9+/Pj4+Hjpol9M7hqZY2fc/gXqV4v2j4+Pdm4BXM7nMjK4VlOuoESXniIApJQuBl/f83KSFf9f952KL0C8vkHPXxOJXPAueCIDTZZEiABRiiwpqRiRI+cD+wp6EM3sjIyRgyMICEwiUnLRRTQXWXJJKZclA6D3AYnHcd4/HUWM2M1JTZuSQRSHRR+G6cPjw5yW4GnXxLc3GwzNXDArFAQyYHSNw7raneMYQwyeGdOcpIhjDP4LRLkz01reqcwkUIoSapF5OOVi7dN9CGF3e1earhgepvm0PxCCIBYptulc8CZ1MF8kyzyPVhbG7MjIIRBUn8sEzEpQCZgDWNhtW0LNWXKa53nwIxOjC77t2uDZ1d978sGhWRODZ3p8PCxLLlIMRDSb5HwVXiKSc8H7lh2ZKWJGylDxB7Wcp1prWrAinezaUdXof338slEA1DK4ygwmyIwEBoGQmYJ3TfBt8K13Ta3nk/PEnlyl9Au1yVd9PjGv4Tqeq2NfUPd8weRjZiXntKSq9l2F9AiNLmBAPVff170EL1742WivQvfz5rb26+BSoavbAX5dHzlHEM94+PVj4Xkj+DIfPsdQUIkXrqWT11n6CxtP9fYX3fvak79M46WUrkd36qdXgO1XtYCLi750B65BPtd5+yVAuOwa11tD0zQ1DLke76WzKPj1uFFFHC/zbJ5RCIsRESCUYvOSVcH54NgRopoVyWbiUJlDiKHSXOdcjofTaZr3UxrmPC8LqrXs+hBu726dw+O4TCVvp4zM01z6Pof2FoDvn07vPj789qcfi+a3r+52TeNjqyjD/Hmcs5JvGmE0E81ZAUw8IYonY8ZlzqUUU5unk+rznIJDFcl5Gofj6TQPJxRxJWjJ83GP83Ls+7br7l68DDEauznL49O+5GWcp/1+07XNZrvZ3dy2bWeCaVn2Tw+n4ZjS4hg3fdt3TRO8Dy4wMZhlFUjOYnT8zetdvu3nRYg5Blym4/F0FNOma7fb7d3ti67tFCAy9SG8vOnvtvHzp/v9/nSappRTyk4zdH1Dz3JdiOSJAhIhGAE5ZENGKiDZihQwFTMtCquywjOsduVfqIF0TWVVrYAUMzBANTarylqMHJijc43jyBSZKpDbP6t5EQM7YIc+kAvsHHtXC3VnMhCF59KjgRmg4ZXQhanM43g6HIgYCRArdtjqGNq6N60EgmuD47q1XvuZdnnzen0A6jj32XQr1wnVeQSAGhM9Wyycm/5fGLnA14/U55+vm4qIZLsyGDO7sOW3bfvmzZvdblcpN0MItTs2juPDw8P9/f3T09N+v/96zwKAL5U/Lnf8YsB4Bdq/2PzF7OvmUveg+tcLaW+VD6lD+xVQVOOIavy1Bnk5jVLK/uHx4fPnrutzdMkZIRhYUUhZVYHm5IgcIwCICaMFj53jTSDyLhWYhvThw8efPjz8+Dg8neZ5XjrH373c/ovvv/vZv/wXQPjXf/Ofn94ft7sRDA7HYbu9UYqOw4/vPvz2h5/+09/+nQv0crdtYsu+PZ2Ov//p4/4wvH2TttstM0qReVzMrIkUGz5Edo4MoJQ8j2O72eW0PBv/65//5TzPfvvN7nBI00imvfdayt3pCOw2L17dvfn29Xd/VorMhZv+5atvf5mXuWmbJjYh+H7T393ddV2LxMuybPZPp+E0L8kxbfqub5s2+hgrkn2FwwQfnPfOBTNckpiBcz7lHPb7LCXEuN1uX7x83bZdFcE1oLfz9Pq7h6fH/eF4GsapzmpLSb/6l/9932/rNwkhvv32O6IKBDJVMZWixVREikkpoirFLKvJavxfhNkGUAeFrNa2wASsPj9rSQZVoiYQd+w677sK2nPsa4RPjtFxLQE6rj7fs/PVHyERPhveJWiH1WcC7La7SzGG2HWb21zyavxVHhQNAS5Cq0hIldvEXarZZzvBZ8s5p7WX0B+f3wGxNg5WR311MepzcH2fryz9Txj/JZJSVZWy2b1i58/3Jbx588Y513Wdmb1+/bqG1vXLVlsdx7Hrujq9dzqdvkoc4Cot/wrMd4n5LwH/9WuvHf6FLAgAalW/gvnq77XJV/95PWugqt98802FFQNAiM033/1SpHRtH6PzbBV6KgZFwBSxdmEYa7zGhI3DNjZ9vyUXZ4H+6URh57aP8WncD0vOuffuu5ebX/3iu7/4139liCPG+6d917VmtjuNXde9ePMz70LGYL6jZhsa96//6i9/+f3PbrY3m9vjn5/0dDy9evmy73siUtF5Xsw0BgoOvUN2VOnD53F49c3PfYjPF/Dp0x9qjl2KVD5qRgSzIgKI7Cp4ujGzaZrSMue0mOoaWT0PaRAgmmq+msqqcVVl9LvarmEtWOPFja24nSLFzJDIcU3/+LIi6+ZdipRS5KpT1bb93ctvQmwAoJQynI4p5XXJVm9+ju1Xi75496/n6K4XMcCVWQKsIIBzhQxhZd175t5bv85zOPrF418lkH/SeOBMXLWC0qXM01BKvn7VuSd4vip/hAv801/K4HIZ//iRNez/4oV49aR/8vF8atWv+tj0lVi5Inmq5A4AXHMuXl5d72/1z3+MwL08/6sd4frB63Tgi/M6b4p/ssJHZzrg65/X52ZmMcbtdlsrAiktTw+f0jKdX2t42bzhDIS6pmJEoOd2I6lBLrLMS8o5lVoXNEKMntsm9n0PAKdhzOcB5LpLNrFBxJTzvCzzvBDhZtO1MTK7UsppGKWI9+6L+aWqOo91Va5ANxWJTXv78s3F/vFPLsR/Pv75+Ofj//IH/eNP+efjn49/Pv6veLjj/g/wZV6Hlz4wXCKHZ/rEL2PmC3h2jawvz6jHl/86v31tqVWkGpz7VOeCMiERk6ty52fe1XLmZMy5qBoiEzIzt223vbmrIVnO+XA8prSsp0241sDNrKo+NY33q6x6ykXPCAGimrCsDaQKDACoEJEaUq4Js5lVYE+9RHUwUUVrwHdpwq+piplq5fc+j/gjETEYqIhVeAWs0aaBBe/7rruQ3l51Mf6PR2fPecHl9j2nYc835o/Ke//Vn3cVfksp4/GQK6P2M8Lqy9NDOPuhqxQGL38+x9X1H9eVSfvyNVWJvGhKImpI5By3cVUnxPUJ5x92ftfnisW5d3qVKcQYb25uVoFQkdM4ppzPucblBP+xC/KnrtE/+Irnr1jzM7t6tJZuqjrw9cW6TuHsq081MDPvfd+2F+Y79+v/5f9lBiJ6xsBWOey1NrzKY7NT1ZRTyUWf6Q2wMtdWkIeIFiklVyQsnPcCLaJ2HiU0q/Rf7H1o284Hp6aiknKSLGqCgN77tu92211sGkQ3L+np8HQ4HI7H/dPT/vFhP0+FsG1Cv9nsfvUv/tX//d//P1+8fAMAx+Pxf/yf/qeffvoRCJzjED0ilqwiYqA3u5tf/eqXb16/7btdLvb54ek0TCJCBCH6lOaHh/vT6Vgkp5SXuTCH7XYbowdQQqw9BZFC5Ju4YQ6GME/T4/39NA4mggghulrKRCa1CpqcShGq0H/nQ2jbuEGD6XRMeTFUYtfElphVy+vXL/6Hf/2vbm92cJWg1jz2v94gES+9ubrLApiBIhiuZKr19l3yZRPRy8r742rFP/ljnzPw8Xj4m//P//vhwwdmh+zOQIuKu1qBRkgM5BHYgAHQQA0UyAgArRotKICYKQE4qqAoM8DaJzEgMwQoanPSx8Py7uPxNBXn2xd3/Z//7Ob1XddERoQiJeec81JKPk+GmBqomahIeaYSqkWolNJ333337/8f//7Vq1cAcBqH/+/f/M3Hhwe+6iY+V2Bg3aXWEYq/7xr+vVf18j4GIGtLdsVYkwIpgBAgGKMSGJsi6OVjwKj2eOoNFgTDuinUK64i8vr2xV/9y3+5227q57mHT//ZauFNa5uYiV2dnUMCInDOeefM7EzDVGfg6qlz9dfrxVppGFfQTN0mKk2b2YqoWY0/xL7rnWfRXKQsaan4eSQK3nf9Jk27tumQ/JLy036/PzztD/tPHz/94cf3h6fZLHru+n4nqv/m3/67Fy8BAMZx/PWvf/2f/rf/ZKjkKUZP7ExQTVXLq5cvFIqBfftNUOOn4/DwdMg5I0LbhnE8/f4Pv79/+DRNp2VJkrFp+levX8fol3lUE2YCg1yS93G7eelDq2bjMH7++Gk4HjUXJIsN+cgxOmQGxGlO+6d9SiX4WLvQXbd5cfOGEA8Pn8fxVLQwc9v0SJjS+Mtffv8Xv/pFNX44+5//CsP74jBTNVUrpZhVSEwdI750/ut9MRFRUYMKSsPrntn/wXMoOT9+/PDx979lF+hs/HX9KNpaj2KHFBGdVXXj1fgVAdjqBCIqQDExIgiETEBkBpoVxFaddMJU7Djmd5+GX//288N+Yd9+83Zny6v0zbZvHRHkklNOOS8lZ1FRMwVUAxHJdTCnZBGptV0xSSm1TXPh8EulfHx4+OH9e7eOST2b8dn4Af4x4//7ttQrUv1q6RfjJwBWIANTAgQhK2RCUshktW9iAOYVu40CkAEEcdUTAjTVkgWArkBx4JCQgKt4plnFadaWKa/2KghETMTBQwAzMwTCqnwKRYqomhoRqWndHWpgJ2qiKqvxX1rOCIDsXPAeyTQVhORJnAdAJiLniDGn5QSSiIIZdoF5t+2id4jTtGh5HCdZ8rDsl8fD51JWfrWc8/39/e//8PusyUDJsfMxho4I1dK0nJo2NE189eptbLaAJiopFwMzxMMw3T8+vXv/Yf/0KZcSw+b2Fm9KFisfP34Yx4GYTKXIEmP78sXYNH0uOk/LaX+ah6XkDFh4Eg7mPTjn2TXjmD+8/7wk2fRb772Z7LYpxj44N8yn4/FpHicwjLERyYfhs+e8zP/+sj5qn/nSc/qvtDwzNc0pjeMMAM15kp8QV6tGBgVRLamchkFNm+a541U3oC9njf9Jx1dr3fsQ4srXBACEVVIFBEwNDRnIIQZEZ3XVgwGooSIYA1XdFAXwoEBI3rngfQhmNk+LJCFDQiLnfNYkC3MR4yWbluU0jMM8DgsaOmY4zx0IOGMkBgQjVSjCmMsaAnlwzscmMrOafPP27bPmNyCvBH3P2MFr43+ejPoHL8iffM6ZY8cM2OoQGgJAhX6u3UPigqpQxGSBnEAE1QiJXWA2T46YkFAQF7VsKIgKZMiKxkB4niWth6vhGTMhco3F7Gz8BKaiZIhGjLWJSgbPsaiqFqFcSkVNAIB4D7bOfqhZUZNyRaUDqApqhkiO2awwGZixRwA8T8UToVlZsghRInSEGBkphtvN5vXLF2i0P06ncZ7GrPo8n2xmaVnGYZjyVFSQKfimbcV7B1iOjj5+/Hh3++Kbbz81zfz+4/tPnx+WlBGpbdthOB0Pw+k4HvaDqMDGZ8lZMikuKU3zQoSVMKJkRbh37pizpCRpSpLVTIGUQFBlWeq4LI1Dfrzf5wJS1HtvKlKkbWP07njcD6fDdBy1CDtfynKaHk7fvREp16vhT7YJ/3cdZiYq4zh++PBJRG7vbm5udtvthphrPaIyHaeU9vvjx48f1Oz16xfMrvJi/fHC/a85EOtMsQve8arlxgBishQ1AyBGRGLE1U3B+hMBERiYgHDVBlQDQCRn6AENoBhg5WW/tLXOdQBDUgMxELNilkUUoHK61pMiRqhIcQQ2FLTKJMTETdNsNn0MERnvbu+uh2HoyzYh/Lc0/vNdA6ge2xBxNX4kANNiy1TSUOaxzKMsi+WMagTsfHTOB+9DDKGJHGJ0wRNnhQwkVT/UEL9g8QKHYGAKKoYr4pNopbBBMzWs2RTWyKqKFcAKhj2fG1aA1+UWIiAAKoIzyySqWAMKJFKFUgoYECkYeEdMDs8ffC4vgpmhFZMilk1riGGO8e2rV323OQzD4/749LjvN4GfEX4UvW9CLCKIwt55HxyyQ+e8ZwzDaX737uPf/PpvgfjXf/ubz48PYBZCs9veSLFlnLCQg5ZJ2HlEKyV5F/pu4zisYbhIKWU4TDkfShGVGvKwD8EF79gbSEnTOJyeHp6mcRFDIjcPJt4T4qj5D3lyjtG0pGWZ57wkNQMoSOr5GXd9XXO6eP7r8tJ1LHBdqPsqVq+Q7f3+6e/+7u+mafrm27c/+9nP2rZ1ztV0gAlEyuFw+undh//yd3+LiMzYdm3bPotkXNcd/vizro8/Pqv6sJoiYvS+icE7QjDJaZ6XskyLAAWoiFjAyiKwlgURkaiOM9WxRlA1MZWcUkp5nqwC0k0NUZAs45x0WUqRRGQ+sMMQmoZ9i9wAotWI2NRAzFYqhloVVkWr+gmV2ciHENqmbUJwbddfYp8zmOP5uDbwf8Cw/2Gzv9zU56S/5mbnbQXBUKQs43T4PB7uh8PjfDqVadSUTQyhRtLBR99v+tu7u92Lu93dawphLoYG2aqyC35VeTyTqJ6Lnoi4TkUgYR1Urgjv67NUsPNIXE0rqJ4wwBnPg1BJrcwATARMEdZJKTNDUyMCNKQqkXk2foCVKuIMydE1GS0mBRjdzXbbb7abpe82TYx0e/tcHkcEImIkAiIATy6yi955z+wI1IZh+vjxE1Eoqj/8/vdPhwMgBN/0/ZaB05RKSo6dGpWcp3EYTjGGpqSsWapP9uy06OFpX6fKwIAYnPMxR5e9r1SoaRlP03F/XJbkvQd2qSyFEJFmwgOR876JAc3StJSURJQd1Am3f4qP/d+dASCknCtVjoh471+/fhVjMEMzzVlOx+HD+08//vj+48fPTRNTypeP+G9T+QdgxhDctu/6vo2eTWWZBpUFtEhW40CsWCNKODtwAkAgqpYPVSkJzUxF1sGeSqWsSOaYgFANi5qBeA/bXWuhQ9e+eLHpNjfOBwMVE0ADMjyv3vX8QAELYI1WTRWXJKdhLqIh+G6T/ni87/8/RzV7MNGS8zhMx8f953enx8+r8S+zpGJiqmhASMyeNpv+1evXr8ZBirXbWyGn5IAcGK3aMFeHi5WZ1FAVBFY9+so4AWb1GsMF7WgC9RcpBivTEJiugdqlI7FmrYCADggRtF5qNDRDVEAjZGJiiATPO2gFiMI6W75mFbmO0qohQxMjBd9Z2/ZN0/Dr1zchPPfGRKSIaDEEYIXA1LXOeVeKlJKXeUlLmoZFTJ72T+M0FzEwIProkD2x8zG0bVE8HZ7m6YBaYmjSnJYxzfOETDc3u5yWp/uPp9NQc2FiJARCYiTHrir05JJqcgimkiaVoiXnLIbkXAhNU7qWifKcKuMAg0N2tRj2DywF1cu2COce5NfB5Fe/I1H0wTmvqsMwfPr0sevan//8Z33fETEATdP06dPDb37zw7t375dUtrttiNH7lSTnmsvj7/ssvQIC/8nNqyLYtn3z8sVut92G4LTk4cQi+Wl/AJO6KImIHQHyWt4GrYX+ShtmoKYmUkRyybmUUn03knGVUcfKuobOW78J37juJbQu7rZ9e3sbfbCSZlVZU/WKaTYFNAZTLaYLGbFRKWVO+TQeP5U9oYXgRPTP//yX5/VZK1df99HOf/yqZf6PR0ZfPHL1X7N69RFBQFIejk+f3u8/fXz69GE8PKZpLGmxIiqqokuSackpF7HStM3n+88vP39+uN/fvnrd39yFfotNa+zBAOwL9KTjmg+AIdYko2LGiZEUDNdpkrX5VE/azGSVoF8JBq8uQM3ZYO3mrH2kWoVEMFg17wCrkK7HSl+PdZRGTc8cewSgUPkBkMykFCWouNEWHfhIhGm3u26Ma845LSkti5kxWvEsJRNXaGNZljTP8zzNBpaWpaS8ZClJRMUz923bgABDEpmGI6AxQPBRlrJMy+l0QsayTCLluH8ah9GAmMn5yod35hlGrrT3AMCIKqKSJSUw9c4BMQKCaF6SIEqp6vFQCpUs5Qsy0j9x/Ffk3gjAzG3Tbrfbx8fHnPPj0+O7d++cc7d3dyb2+fPDTz++/+nH94fj6eZ28+LuRd/3F/7Mf9JH/GMnxUR9G6O0N7t+07eIkFFdZWSreV4ViEbgdeqxcq9V9QA4Y7RBtUo+lFxSLkXUDIzYyLGLIQQPxJQtWenR+c0W/I2PNzGE6AA0FSk1RavFOiRY5zu0mC1Fc1FCjqBUtAxTHoaxlEQI/WaTcvlHvuT/CQcCIKjlJY2H4fHz/tO7w6eP0+NTmgZJyUTQKvkUAkAuZVqWJc3zMptpSnk4Tjf3j7uXr7rdret7bjuKzbLdqF7ReMGFgllXbitQRMbacalDsKvVVhAOMZypMM6TpPXmACIAW03ZcYWymKjYCoxBBUAwh2Qr5zsTOqIKFjAxKwKqK6ijSguqGSCqYUqCaqbE7JnBom9b3zRXQp1a58bHcRxEteSmFCkqTdd479W0lKxqAEpETOAYczIwwzpU56BoGp6mlHLOCyLs5dGzA4WU0vF4EpFpOKnZPM05J1NVdgQNh+C8Q0IzKZrqxKQjB4Cl1HEi6Nv+9ds3McZ5nJdlSSmrFKoCJFJUF7UyjZPJPxRenjPG+i87zyt8tSk8w0DWdJ1xu938/GffiZaH+4dxGP/2b/92nue//O/+Eox++N0ffvPbHz59fvDev33zzffff397c+O9r29+YRb7quH3vC/g159uX1OEADu63XbCuW8jMyzzMo7DNE0lZ0JkprqMal3J6r2v1f5KwrIuL6h0GVnyUnIuRaB2vDFy7Da7zaZn54Y5L+WoxF275bhD1yM6yDmVnAoisAVPHIiZHSGCSC5pSpKGRaRoDBEdKWYBTgXGMac0v9mfylkboma655noL0E0F7jNn7prX1+3P/UyuzQI18qCmkqahuPnD/tP70/3H9Lp4FSQvXo0lrV/j8RFzUeaZpo9mgHSMI7H/fDhw8dms4ubjd9sutvbm1ev73YbuW711eFr0UpyDwRgaiKVcbzOMypeU1BcIHnrSKyd83Oo5r2O49QHtTarzwuykn7QKmWHUOuFxEhiBlJqWxqgUkOraFFVQzYCQyH0zjXeNezUJHnH7o/S5IosqqM4IjJNs5i1rQFAqe6CgJVATbJIypqKoSlaTqkw5Yo1YkCwnGcrzjmHZEgguZyOeZ00V1ETADBRQooxkqc6lp7HRcWAAQwueCdmv+m3u5ud3cowjJ8/f56msWZGlRSs5HKRnfn7jgskDc6Vp3/gyddH0zTffPuNmBLR4+NjVb/s2g6Mf/ub37179yGltN1uX7168erVy65rmVn170EZ2BcGb2bXQ0FmfyIQYKK+DWrBE6qUeR7H8TSM47QsorpGitX5WPUpcEnIcRVmhfq7oYnpUvK0LFkKIsQYo3XsGx97ZvLC3i3eOMSGYwMcVCnnooaAbAACJFarCshEUsowp8NhPBwGM91tPTEZeXTRNcJillWB7Y9j/P8Gx/VGj5fvXC8gmUJJZR6X/cP4cD89Pco0oSgRsyNFqs4WiZBdMAydtkua5lFSRjCVIpZUi5pUOoVV4+VL/mJXkab1cTAAVhFVyyJStKSSKu7nQm9wadzBuiOff1aKfCNSZq5z44IVE2AVtoFajR/ZcBW+MjBkY8eoWlYMl1T4l5lmLWBA7Ch4H533XdNsYuiBFlGHUMvD5+uHGEJomlgZ1Lq2JeYsaRlnVACmnFXJpAhAgUXzvMzDXETZoQmfpPgY277nQFLdzJKZqO0iAnLg4Tie9qPkAohoiMD1qznitmtj60XzOIzLOJdlURRCQgRGqt+zlBJDePPm1TzNpaQiSQVULQRvpqICf+w11lUBiFjV10RMVYkwBMfuKga4ugj1IVhvjJkBO371+jU7F4J3jn/zm9++f/dBFbTYDz+8m8Zls929eHF7e7Orln92Ql/k/PaMsL2qKQDmXLSWcxkQKiD6i3iECIMnZTTJKZdxOB2Pp9MwnMZxyUUqR/U6eC+GlWVsdQ5VY6miWA2MjQxgKfk4DMfxBEQ3u9um36aCKSNkTYsBOkeejFEq/tUAFBld8GZaVCyrU2J1wbtpnj8/PN7ffz4cD44ZyLdtq+hDu3Wxb/vdqTlsd3eOL62+WjDHFVtoz1fpfKWuAFTXt/HL+KhWtgHWIll9N8W140WmXLKMp+Xh8/T4eX581Cl58hxJxVQVKt0eAbHzIZILN+xEIadlmabhdBQpzvt+u7159TruduYDN63vtn3/LKAKAA6BKq+raT1pzUUBtJRSrGTJhuDY2MwxG4CIqMkFDn1eD6ujQEFmdeYIsfZPCM3AUBGBdNWutVoqUFQwQQMGUqhK56Xi8BBQTYspADkk8j420bnWwKkgIREwY8XYXxYZVdUnEQGwEAMSQqlbm2jRJGIMFeNNtXpZikhBIFWVlFUhNtFhFbRwjOCIQ3Sg5gMzU12itbaE56wHVr5aqzBRqIkkKBDUyIQJVPV0PA27AfF127W7m92Slmmci4hjNrMi5UJE/9VhZiI2T/nwNM1zVlUiiC01rW/b4CtH0IUF6Hwznk3XjJn6vlMt4zj0Xe+dH0/jh3fvcyrH/dE5v9u0L253m03XNGHl9P/C4p8b2WuQh2v+vcx5GhdVdd6F6JvY+MBIRF8sdQNVLVnF5jlN4zhP0zwvKdVIbK3vrZy/lwATYJU5rmxCAGiKiHUFjvN0//hoAAi86bbzlIJLpZSUBYwqnwIAVdrvlCa14r0DoCJiaoJW18RpGJ4Oh6f9cRzHEGMq2gD54Cs9QF4SIjfdhq4M5v+Mw9af9far5ZzH47J/GD5/HJ8eZBxYlX3EAEXXEN1M0YwqSVBsYtMBYk55Hsdj8EC4u7vZ3d1t7l5y1yVyQmzkw3lmvB7OsVc0UwGTIhWvVwxMVPSZkKWoWWWOMtDKFamXXjSuwXaN+pidqhESViUMq4gud2kV1w6mqgICkxiQWlHRJS+lxvlgiHTO+UAAiF3TRcQwL9nA2g4BmCk6F58luiv1cgyiqipA4JjaZqNq47QsOS+lmGBl4fGeSGB2s0kWVVBVo7Isw+lUJIaGvfexaRwTmeWc8zznZZZSagXycvkqhn84DfM8SSllySjg2FVaLiYGNAIqpXz+/Fm0xOh3u91ut0XET58+LfPsvEeAIv5aHKIuBkRAMFVbpnz/6fTDbx6enkZVZVd8W3a78ObN3c3tzW6z9SGuoG6z2lcHQEI78wysJCUiBRF3m01Z0jBOaU7R0Wbbvbzdvbjddn0TfCWYXs1+5eQ1MgCskQyCiKY0T+N4PA6H/bh/Gkyx2/Y3N9uXL5GoIY/XuBdVzXOah0HBTUuaxzkv2Yqe092qVloBbUpA504/VkhKrafKineAyp2ZUnp8fJIiHt227cbbWzaYl1yMOHQuxhCiAs3jPI3DOB7JYXN3631ICVWNCIuUaZr2h8MwTEvKaoTkiLz3TdNG7wMxL37OKXsfru6LrRAMg+c4Da9+Xrn8P5XErZvyucdodi4fwJmZlUTyPIz3n06fPwz3n9I4AJj3vm0b9k5qZwShqngCgHOuacJ22yLQNE4N4aaNzWbzzc9/3t/eqvcZeTRYFLIgh/AVwo8QFRENTdREdE3rzRTX7lIdqDDDs+rDOi2nurbwrv+lYmDA6wWziiM9+3IAqGAtBAAkFKnAc1DVXGTl210vzApbrt6BHAFgKRlAiJnYEANRvJ5KVjURE1GRYgUgVJ4mzCLJxKQK+DCT90wogkh2HmpCAIGyjJOWotlbVOoIHahomlOas2RBBGbilXt3JY1S0XmaEUGy1GYFI62Ga0qAxGxgpZRlXp4en5zzt7e7EPw0jXULrQUU+3qxrAMUqjrPaf80vPvx4dOnI4AhL+COuxu/LKeUZivS9Rsi5oruRKyVGTU1VZEimkuW/dPT4+PjcDyqao3OGdE3rm9D2zhmW+bxdPLee+drNHFGfdXNXSyVklJalnmex/E07Pen42EaTgXAZQEibtvgAkWOTHx1U3Sel+E0FqNpSdM4LfOSSzExXEcnHdWW6VflGzU9DyCdzelsXWollWmaHh8eOh9uuj7Pac5i5JueggWx07zop/vHcRwBdbPdOELPrko3i8C8TA/7x8NhX0oJITRN27WremGMjWNvAFD7jP8NsA5/4tA1fQAAsNotArCS0ziMj/dPn94dP31c9k9QUoiRHDNqYKLgmMk5NtWckooQQnTQkDrC2AXYdC42/e3di2++5a47pTIUdQalqKDilzgfd55hknUsT+RCDWlnvKSKoSqaEDskZKS6Q8Aa7Np5t1jrgIQEXOPOC9RMTU1FzaquDxMzmpmYSqlDJfUNdC0dVoJ5AiAzVcmGRKYAXJTHqTABuUjUXCJeVV2WNAzTcBpySUhYmuh9aNrQbgJEyEcpgp49k3eEggyAKqCmCMCEYCpp0ZzzyItPqSvOO0aQImkWFXIciJTOdPdE6JwDxJLq/K4iKK8ISquPGLsQXAjBOR+bkFJJS2qapuuaw2G/pOVwHOZlUZHpSnQUnj2LqUpa8uk0PT4dHx8PzCg2zPn90xOIDClNy7zc3Ny2bde2fdd1zhMpq1Xl9el0Oo7jaZrm+/uHP/zhD48PT8uyaNa2CRC8qXrPZmU47d//ZMNx3+92fb/ZbFYW7dr4VbG0pOPxeP9wfzwd8zIv8zKNS8lI2LEPprAseRgnF8lHh8iXJaZq4zQfjkMWm1Iex3nJqe63RFXF1TM7PA/d1ubwuQKgutImrXUiA2Bizz6GZjyNj/f3mEtkHm5fFCTybZuNh1nh6eHp9Nvf/SCi3377tu+a2r0uWeZxzirH0+HDxw/LMjWx2dxu+n7TNU1smhCCI2dmy7yMQ9X2bb4A+VTxuYpFrFTPZz8O8OX29Uc9/HXEEmHdVi5VAyREJdM0j6fP758+vr9/9+P4+KjT6AmYwDyWGRxZGzdNjCF4MEueJCVTIcs6HSjG23673d3tXr0J21sNzSA4lzwmWZCKgMhZpOVi/KpFREsdZ9QiNRyvtx2BzoALoMuCJFxrMmepBq1X5PIEO8dGALYK4Rjq5VFbu4f1D2pma7CPoKv+6yXsc1VVR0EQMgIgmZqWRRHRRxZZ+y71U0tVtF5yluyck1r3RyBGZxgCUQFaq/CVo5IQmQyRgJkBQaUYCAAqmGYzRGMkpOiRaeUPIyIzrQAoRGcKIqWKsQKBXY3z1z0NEZm5aVomXpY0DOM8z00Tuq5v2/nh8TiMk0qZvzD+s3uoOqCEhKCa52Uoeck6FDuo4dOTdw6XeX58fGiafrfbvXjxYrPZxhjUdBxPx+P+6elxv9+P4/jw8Pj588fj4VREPLtNt/HOmZQQWC2Pw3FJ8+FwaPf7+j5VUYOIpnEcxul4ODw9PT0+Ps7zhGB133TceB+JvZnWYdjqDL74DqrDNB9Op6KwZKnJvpkhuapueoHKWnUSomLreGH1IJUXEYick+Bj27Z9v9l0m9PhdNw/fFwSEz3sD8CefRvaPXJIGZ4Op3fvP8Smf/v2pXNcVW/naR6GYVzmp/3jw8O9qgTvY4w3213bNgDrxJqILPO8zPN5RP2Lb4TrrfnK2P8pHYH6Kj4/fyVYRwDNZVlOp4eP9+/+sP/0YXh6LNNEImqQ5gmtqGQCi94JkYAhokN0jqtqYyDpne4aut3Guxdb6jb7AlJKFksFlM/B/JdfxFW9y1RncS/seAhgNf06jyoAUWWtW2uvNewlU1NYKSsq8r+qvzJW81YRFaz5AgJQlbKueOpLubDOsNXg2+r8LyMCMTtAVLHKtw2ERFTn/9WsqFtSOgtFwfPuU0m864SDd4CWcy6Sg6/N+CXlJIplETB0LuJZXdtMSlkQIfjYNG3btSFE5gowhVriMgPnuAKKci45Wc4FQBFs5eRHNNTV85tpyVU9lghFGjNFxHfv3t/c7Jqm3Wx3Yu/GaTIpS1rsa+M3AGPHm217c9ttd44/zJ8fPuQy7m4pxGhmx+Ph8eHeAIn8zc3Nd99+980337x+/QoJP3/+9PBwv98/Hg7HYRhPp+MwDEuaU0oWI/OmaT0oE7FqGaehDGvNbdNvXr958+0333z77beA+P79u/fv33/88KHq5PjgNv2m7/u22ThuAULONs2TSvGOQ/CIoKB0dhxFZBjHwzAosCgsteOqhqzeAcKVp1AtRVMu68BV13ofKxNqqNADYmTHwWfRx6fD4XjY7x+fjqcpZec/EEdkTxwEKCURRSPut5vNZtM0XVpyLsvpdNrv9/vjfn98PJ0OxLgsXSmlChoWqfuXlVLmZSklE6Hj50IsAtQxeQKrTul8mwCQnnf+50evfb5d+mKwlveqAieQ6jIN+48/3r/7/ecff78cn8ggOA7Bm5RxOE2jtX2rUsB0mSY09MFv+jY6JoLW8U3n+yY2wVrKAVLRpWRIWYuC1fEbtDqbc71FuVKq5y8iq9Ot9AZoK6CvEtR8xZ16LnrU1X4u8CBWx0hIeG5iqMLKS01MF0ocqDCB+joiqrheW6Wf62VBquMIlzwPQAyLmYouRcSMc56fjf/8SiQkcM6H4KNzkZnAkBy3vubnOc+iYqboXUBaJwqJULWoFkQIMcamibFx7IoImlbRjerZ4Ly9mLGUhIhUe39Xu39dF4jIrkq1+EpAWpMB/+C8D69evfFN8+nh3lBB5Asd+Cv7J+KmCTe33Ztvdh8+hd/9/uk07Jtuq8pmuizz09PTsixm9PS0WeZpHE+n4UBEDw/3+/3TOAzDOE7TXDWttA60ojqP3vMKVpBiZqlozmXJZRqnUla+2yLyh9//8PHTx8N+X6Q0TcPcE0IIfrPZEMZhSKUURAuB2zY2MXxZtgRVnZY8zAuQN8CsWjkhEBVFQY0AagKlZrLkZVnmJbEPPXNomxiD956Zc84yz6oWY9t1mxhb54ICTSkP82IAiA6RAUkNcxEf2t3diyb6vutibA0g55JSWtKSlqWUwoy8UvWe79lZLKCyiYoIEbHja69OX1DffbVZ/ynnf+3srzaF+mzGmuefhseP+w8/7T++Gx7vyzxFH0KIzFxUlpRMi/O8OAdwdNNMyE1sGIDb0Drogr/btNsmMEPg7GwWCZJJpLbCV3gOfTmkAwBORFciB61S06gil66uqgESUwUUrAh/M9Oanp/He+vsdy1crKOOiGimQGdUiENiRIAKE14hXXAJ+MyArA4GVltERLgUFNdEw1QkiQpgAhBRE7ka6a0XlNayNHNw3HrqG/bAxXlseicqx/1phGU2QRPvg5hW3VJEEoEihFj5S7xzTkWOh32VhTezaZmlFETyPsTY4XlQDMmwDiUYXHwZgDG7tu3ubl+YwcPD52kaAEBVQmj0Nd7dvWg3DQXcP30HAn/5F/9d13Vf2L2tA+bk8OZ288tffffw+PF//l/m/fFT05WmpZtdj0gll2VeAPF4UtWy3z/84ccfiGiVqZWqmVEqOTIzI/oYqjoOlCJr3wjJIZpzoqBF9o+Pw+n0+9/9bp6nz/efS8l93/Wbru+7Td/FGIL3TYwpwdP+kFPe3W63N/121zdNY2hrnlgXv0FRSVmQSRFFrOgZ9VEKOvFg3rm2bUV1GKYsRUwdU2iafrfdbjZV6uvx8elxf1hS3t3eOXZmoGqAaMSqJqJaFgCs5QM08B76Lmz62DRNjAGAc6mDp9y0DTqLxbGjbtN7H2q3VSrtFGIpRVXMDKkGss9WXVsTSCs8od6nq53hChxxHWOvQg3nQhlo9cYeYVmmpw9/ePrw4/H+fTruSTIBlFIWQCYnYkUUENCxgg2ngcg1XU9UjscTSGx3beP9rmtvOkeWiBPJtGQPGkAd2pkbwfT8/yuQT/X8Iiq6xu1qVY/RrGb6X2o2nvEY1fh1hV6ft7IrbqPL7kYrUstwhf6C1SIBrU8AqCTIpghUc411gkDEqsIccY2BK2MQQIaqkabLZfcNIbx+8+bPfvHLaZkBsGn7rtl03aYJgZ15j76BcRrKbMtJGEHwjG0wRUTvmdjNC1plDSxFRaAKJJtRbTqsXQ0hVsRKXF4huobnWefamFcVJtd2/atXb/7sF78yA2Z3f/9pnuec5XQa53Fxzr24vQWG5c03BPz9z34eY/PlpTtv24hNF958c/f9L95+8+2L/fHTNJ0eHrF25i+KtAAGoCkveZ9EdFmSiBKuNBCAAEhMRsjO8RlvXdV1iOqjQI5DpUg/7ven4TjPUymlaWMTw6br2iY0TWiayMwp5WHMw3Akos2mvbvbtu1KgPFVhVwM5EzQU9QqnwYDeSR2volt13Vd183LkiUXKaGJ/Xaz2W3bvifv6qvmlPb747Qs5MM4TtM4LXMSUbvUpdcBM0QwJCAQAKkVKUQgYu9dCKFr2xBcsVYss8MYuja2AFCVRWrFuZQq6wJfKQVc3xX88qF/IgbwMliHCKAlL2nY3z++/8PThx/LcNBlYjAByEuuxDtVmI1g1RrNS2FWF5rExVSCQ9VICA4hMHgE9GaY2BIb03O8oWud8stQxdUUrFasxMwMi66tL8J1vG6tXp/Nfq3rqIqtBZ5Lzaa+6bmyVw2b1ECzkqL3DonWhMDWYtjzVN85v6jdL1XJRQCAfEUs2/oFLCMUwixawNJlf+37/l//67/abHYiCkbEkTkwBx9cEx2gpDS8f//Thx8fclIAUJNpmlJOZhJCaNtA5AAgpVzySXJBgL7r37x4RUSSc5LctjFJKaJErokNAiEqQEl5Uau3CgzETErJvg23ty9+8Ys//6t/8z8457bb3Q8//O79h3eH/f50GJ4e99M4IL65272k2+Bd8+b1q/AsqIDXy8zMmGmz7f7slz//t//235jl/+0//6/v378Lwd/sdibqfWDHm23/+tWrGJuU8ul0HIZpHGYEYvZN07BzK4oMoUqYr8W52vxk73xk9ohOVJd5NpWnx4QGb1+/urnZbTZ9jIEYveO2jYj0+f7heJzmeby5vXn16vbly1vvXfVveO0BEAEJ0CExKIhIZUJAAh9j129ub2/77da3bSplXpKovri9e/Xmze2LO2Z3PB2XaRGRp8NhfzyexlEATqfp4f7hdDzmlMEEARwhMGMdCUMoaKJ5nk7jeFzSWEqOIQQfNpveB69oQDVkQyYHAFJW2YiLyEftRtAqMHGd8+MFhrB+yXUMn+AC2FuP5y1w9Xhr6m+E6BAk59PDp4d3f3j46Yfh8ZNHIzAkziDzPItYKeJc1fmFtNQMHglJRIsoIolVyoayzHPxvu2QAwNbQvVsjtahPDSobv+qWQqwYvvNqlcDNVG4qNoSn1N9XBvOUBF+Z4yRmpwxOasywbrPrJKPdSITRCwtBRGbpmHH5+qdcNXxI0Dg2kaoQ5wrLl+1iCCArmoEgKBgdTsvAAU0g5bLl4kxfPfdtzHGOnCIwGqghuxd37cpLZ8+vStZx2EehtHAck7zPBUpzARgaydpdYSV104RzIfgmDMCCLH3wSpbL9VdseGIpLkkUysXbQ8ARGra7ttvv/mzP/v+599/F2Jkhn7T7G42H96/+/jhnhlVBcya2IbY+dC0XXeRHruy/6qWp4jkHL94efOv/m9/MY7Hn9794f37Dw8PT1K077rWRe998DU9doiiChUOHJwLoW3bnohSnlSViOo3hLqUgL330UUfW++bOv87Epe89F1vpne3t7vdNjY+VOW1GJlpnpeHh4d5zk3Tvnhxs7vZNm1TQ4+vfB0iVvFSZFdn5tdCJvsYmr7fbG9u2q4TxKI6L3NWiU3c7Lb9bptzPg6np4d9Tvnp6ek4DOM0icHpOOz3h2EYc0qg6hgrCVT9cAEVEy1pnSMYjvM8Mnki37ZNiBFdLUdKBauVkhdNRUs16DWuNVtzAfm62k/Pmf8VmOlc37OvjH997TMdCCEQKJaSx8Ph/sPT5/fD4SmNozlyzIBsYpVKtDhicM5hcOgQHJFzgV0ARDWrzDlFZFmWcYTZx75pPRAgECqTEAmdvYgBGKp95fkBCMGIVzwXnpv2qysnqnrydtYwv5IurNx8VvV5AIFsVWJcYwRDRCXglOV4OplCKRCCUytISmzeIwAyAml1DrjusrqGziqCgKpC9bQIEIzWllAxK2ZyudbM1G+anNsiKqJgWlRyzi642MWlLJ/vP/747sdP9x8fnx4QUVRTSswUYxNClKI5ZxFzjvu2b9smBK+mwzwSsakCIpELzIhe1eZpMrQq9qaiCOM0zaUUMCJE7/3t7Ytf/erPfvnn321vfYwuxG9fvdn82S+//ekPP/36b/7GeRc8q2TVJEKQtZTW7PrePNdQa9OECELkX/75n03j+Jvf/m6e0niaSzbHvmkaQidij48HRCqljMNUsnkXb29fbrc3bduXkh8eK8vNmlUBoHPekQ+haULXxD6Ehp0XqRMgO+dYtcToiQARYgx3L2/ZuWFYjofD0+ODc823v/zV999/39dqRc0E0a6LYogYfWhCA+xy0eIAjISs8U3bdH3XbzYb58NpGud5nuZZwBSUHcemKSL74+nd+/frMMA4p1xKOe33x2EY52nOSwKU4H1g9sAmmktZikJlX1nmYTgdDk/H457Jx6b33gdy7B0gFCsiOecCIIRUq/pVL6jaf63RLvNy3YJFRVREQj7PPeEqdmYKF4huNf0LhAfOLrhqahNIKdNpfvq4//Tj8fGTqhjynAqCMlspSgie0RMEskAYvWujj00TYm/IUyqI6L1j50op46QnLp23Tdtwg+jBWJAKIiG6iilQVEFT0uss3lnt2+F5EL+21azWJ2vlnoAIrmL+87W4oIHqgN5Vk+M8/7POKZjmInkR1ZEdAYjz2LSOyDEZmoIi8Hl3xNV9XIYdTWtp2BCA6LKb2qXEfvlQAymaqliyY1CVlOeizN7vD/sPHz98/Pj+cNxP01BZg0SEOTA7IqodOUR0LrRt28RoFdirWkudTMyAxM45VyqIEI25cc7VYeGVYMKU2TVt9/LFqzdv397d3dVmRtu13rkmNI5YJItoE7uSVWzJRV0oS978UZ//+pJK3U1vd7c///7nf/EXfzEcx//yX367zMs8p7YtbYsqNk1zlYpPSzbDEGLTdE3TORdqemyV84WYiZkdkwsuhNg1oY2hDSESswiVEhGtaaJaMRN21LZNv930fZ9LOR4O+/3eQPtN9/rN65evXvjoz27/a0AcAjKyI1ZgJvTsCR0Q9m2/6TabbtN1PTFPaamedinlNJwe94/m6HQ8ffr8+cOnT0+Ph3maRGvVxw6H4zRNOWUTcWyRsP3/sfcfvbYlWZogtpTZFkdd9ZQ/VxGRmVWVVaxukgDRIzbIGcEBhxxwQoC/hP+BE84IAgTIX8AZRwQIotkgqrtUVoaHcvH0FUftvc1srcWB7XPefR4RWRGRkYUikObPrz+/99xztjKzJT4RpKFgaoO7loJWJX/KMA27/Xa3v49NSyJNFBEJIdZA2Mzci88EOSKic8H/hEk540g+uSs0Sw19TM9q68s+eSDPc38O+AGBCQJBSWl4+LD98Hp3937YbWttS62uD05EMUYCa2O1gsRGOApHZmGq4Yqqq5aSYXKfCMdoKYUp5ZgKNeazzLfCrPyLBmj446hMTkYFM3D6jDJF/Jju1D3ITsO9LmEMs4A61/5a1f+FuZPp7gruyMKCQWQadbvdqxqS932UsGrbGtPORBjAOv/nfgJUVEANpOeI+gwlrgsTY5XHAAAAVd3tHt6/f7c/HMBguVwA4G4/FoOHh/z+/fsfXr368OH9NB3NCznjx5wGSynjOKqZMLdNG5tIxOM0qimeLJ+ZiTSbKxGraiojILgvq91r01gpBcBTSiHEq8urJzfPlstLwu64L+aFCV1LmrKE5osvfuIGUbpphEkH4rHtu/UqnS00P3nU5s4JqBoSMeHFxcVf//Vf56Tb7eHNmzfDMDZN7Ps+BDGznEtKWdWYJYQIiDnnlHJKk2ohJGGOQZoQ26YRqiSGPoY2SOA5yqMQw+xLAuauTdNcXG66viX0u/vtq1dvdofx6urpy89fXl1fdosGZ8f784r1ySQwNctmbAAgLDFwiM1ytVqvVovFoms7ZGqmqZp2T9P06u2b3TjG7747Hscfvvvh3fsP93f34zBB1Zk0OB6HcZpUC7gJYCO0CKGVxtSheMk6QKnpay7lcNzv9g9dtwihZYrMsdYIXVEVSjFTO/eq4VyxAhBmCfIjzsWpdu2nhtVJeQgREOzRK+1kRAm1EFIhZYhSK/zv3r5/88P+4T6NQ0XJVgBMtQ6PUYRACAMBkTORA+RSkh7UIRUDhKNlTMItLSSasammaUxTCF10jrW8V4+zCvj7DCj+eGvkJA4FflriqnwQflrR/NEgqqGC1pIgnct2Do8a77XL6EQoIQDk3X43DCMRltIvV70asgHYfOnPMuU2T30gJnKnU84CFXYAzMiOM//n0TGBBA+Nh+TuKBGJuPdQ1JDUYZzGwzAcqgE7nj0rTpHe7N/aNLXhnCvD3owNnN2oNgS9lFxZaimNiJRzJpIQgnlbylQb5stl//Ll8y++eHZ9tewX4TjkoiZETuAAEpr1RY+OJfuUik+KBE3kED7tk3x6vau7UX3Muq7/8ssv9rvjt7/5dhyO4zQeDofVahmjEDEhgxcEYgnMXLQM06C5FM3oJsJNkCbELjZt0wqFEJu2bWNoRQKROAAZADZiUs0egbxt2/XF2tzubj+8fffh7mFLHJ48ffLi5YvlesFMVbjgdz4z7qBFS1EAQpYYuGnbxXK13mwuLi5Wq0XTNgpeteMkiKrefvjw/vY2FR2Gab/d77b77XaXpjTPMIc05ZxTNWJGJ3GMxF0IRp44VadZc0cDV01pHMfjNA65mzTqXOhEcHNTP6mwnp6IU/e5przwyMLgfEIn2oXjef9/HAN8nCP0+HfmjrubpTzud9u7D9vb2+lw0JyFhZiswuAqfx6ZERCqn0jtjxhAlYYBRWDibJxRCgdVBgAHL5pLSXwuWVg91FPf1elHhyh1fbJq/jOfM81YGURzJ3PHR7HPvDZU4goAzrUWR6yxKbjPBCXw2uVB5hgj0bQ/jtv7bUX4XY2bvhgR8Cwf5IDmSEh80v5GFmH3sydRjb0JuGKAy9kLCwAAYuAnT5ehvR6GtRZkicJIbIhqbkj3/+a/RwQzdVU4ebFi7evUd6ie7YBwPB4r3JhmNr6Dea0gIMI0JXCYppE5DMcjInVdCwjTKCEIIl1eXfz0Lz7/i7968eyztl94N6Ibi5ABp+Rmc18AwItKTh0hta1cXXQSfoTC8FPxBQBEpAZKzsyXl5eff/7Zz3729eGw/9WvfnU47A+HVYzNctkEadxJVQkFAKdpch9UM4JHwbYJbRP7puvbrmu6Kj3ctiHGGEKDyNW7hpQBnJkkSIwhxCghfLi7/cWvvn316vWUy9PLm88+f/nis2cxBj+1S097JzyeCu6WS0m5CLIEarpmtV5d3Ty5uLhYrdbdog8xaEruhgBt0xLRw8P2bre9vbs/DiMYlqzTOJX5fiNhlUjKVl120KEYGUQkI2cCBFMtBhDcyQHUrWhJWXPy2tw1dUA3BTVQA4eq/T2vslRnHplqMVMtH2t4PnMnwbw6pj8uVQF8QgM66yCeDSuIoEx53G/397f77cN4OJZpQoBGmEmqrPhcfnbIqloKeiGCs+JB0QIAFKSJseWWkMEV3IgZmAxMTc3MFdTAdO7R1fY+em2oP5r8/giFOK92dQH/uN45uCFWvwWq50+PT7LyEuohVyA00gx5rAwAJ3B085LKNGYHi40cDkPbB3cOTkw8t8kIaMYFARIJIc3Xeu5FVzkwqm0CcH5EIGHCrgvZIoCXghKkaajtiMmK6vpNDKFeQzhlDXU7BVU9dyuQ2QFSzmYegsw23ISEqFY1ueomBubq7sfjUUJcr1exCdPYlKJEvlwunz2/fvbicr3m0CpLLW6DAaTEajhrorG5ccmRQdqGl8vA/KPJ/3EgIiLXyY9IIdD19dVXX311d3f/9t2bu9thv9+HIE1THTcCs9TOpc0NDEOCEKSJoYmxibEJTRMiEMVqwt7EECISV55WVWolqllBo277/eHN23fffv9qt91eXz95/uLF9fV113X1qTw9Q/TbOf+JN+nE3Lbtcr2+uLq8vL5arVcxNoA4TdOUkrs1TXN5efmw299tt7uH7ft37w6HI5O4oRZVM7c6ORnAzUptfRcgcyfEyGJoBGBuakUNRM3VwczUqtdjyUlDJmJHNM0VMMuIgQMgFCsfG9qmRfOUSko/4lyc91KfE+LTicLHOiee/z73A7DmwarjsL/7sL39kI4HSwlUa1FOmJh4ZmSr5VJMi6kCWJ38UNmqqkgQZ7nD2p2qWwQ7CzC7BKBoIEWplErlPrX3DT6pSQAInHRgq1Aqn/qXiFA1uRGqHZJThb+bO1qFAVVOzClxN5/L/5Xz4nQK0ixrGjSPiRwZKWuZxrTd7kNAs7bz2EYiIIOTnF6F9iMyzSovNa46VarIK2qWPEjAR4hjVZuG8f72Qc03F+u2aQB49jxxnlkDH4s7jB/r3jB71JwxhYTMXL85NzsRUsqqmnMBdCJX82HYt11lgsZxOJZipVjbdotl3y8aDkZYgmQHJ1J0DFyRVATkzuZms1JoSyHKpyIYv2MFgFM9BRG7vvv8iy/uHx5+/Ztf73a73W5rpiJxvUbmSswNRFiffLNM6E3gEEMIQYTrH0ASDkFCCCFEIQn12p9lWqqG/XH78Jvf/OabX/7y9es3Xdd+9dVXP/vZz1bLJZwK47MW5+O58OiwK5Ygts1yvby6ub68vl5fbkKMOec8HsdxUjVkXq9WLz97mXJ59+ED1XWrlGxq6pVx5g51PULEWoxIWhjZaiE2RletXkxqquqlFCvF1epRlpyncRAORAhEJY9WMoEzSQzRwcqYq+VcSlMxndJ4HMbDcf2JmYo7+oztR3gkVw0A/jF1PS0HfuazmGpO07B7uH/3dvfhvU8pIDg4mVtRFG9CdMRccsllmiZVZUaqevYEiMxuFEyY2q6JQZDAXItBcVckl0htQ90S4kKxSxOmgtU6r6qhIcC8+Z8nfw1O/DTf4QS5qSFChYYxshAGYq8mPGbF1NyBK07XHXHen93B0MAQnHh2DrRkecyaNCC3IRIBz6DUFBsJIbgwMqNrTRSQZj5xFXf1Obeq+ApARGF2QgcNNRSeLz8Sncjh4DFQCDwrawMBhFOCVl87b2tIePZmNatBAJ6znnlZrBERzuhmVQOs0H0rqimNlRMuIiEEs4xYFw7mysesyihm5mgFzWv27sgAAG7FEQEY8cd75t81HEII19fXn3322cuXL+/v79+8frvdbrt2wSyLxUpEfO6xMwsjBUYXxhjOKxoTCTFXgECMUWJkCVQFDE9VXwfIOd/d3f/q17/+/vvvwf3i4vKzz14+e/Ysxuin8XcfLBM3TbNery+vri6vLtebddt1gJBKrg0SOK3HqppSOh6Pw3HQ2ZzZNZupmpuZV488otnfWU2L4azjT+xuWXUqpZgVcyolp5xz0pIrljFNI7OICBClNGouiIwMhKgGJee616sqoM/1YP5Rzm8zYA7gtLv7Kc6dX3cS9prT/NoayDltb2/fv/7h7Q/f379/59MEWnhWLvVZyxGgYozKDCYJLDxjR+t8JGchloCIuSRGQm5C18XFqlluwqqV5Qq6tWmTXZNp8Vlbihxofmw/DsHHoWZtSeLHk3Q3BIoUGpFWArhNarUnA65Vu81nji8gAFUBEK9ZFFFtqIxqY8ZijQTveoPIDYUggGiGbgwoiEIGAAZq6FARvZWE5DSLsSG4mREiCQNydH7scoNIIbTLxQY9ovtiGUPD4BW2xOgBMdRnrP4GEZ28azSlNI5DzhbC3Pmr5eu6GNQL8xH7AeZu5HUhgJTG3W5rM7CBSikpp5KTqTHFGuloKuauBrmAOgIwMYqTmaVxYiyRvcT8aZ//4zhXoethVwoKOvZ99/TJk5/99Ke77e7u9u7hYXt/f09EwoGJtWhhEgmxCU0bRYjBhSoGjp0ImUIIMcbYNrFpOERmrtGkqgKiME8539/fv/rhh1/+8pfb3e6rL774i5/97NmzZ13X1ye1LqPnw/vtomVdZJeL5c2TJzdPni4367brKsSQRZqOuq6veiOHu7tf/fpXf/M3f/Pdd9/d3t6O46hqdtrHz9d/piXUqQJQ3MZcxpyLq7oNOQ85FTcFTDlP0zQMQ0oTAhB6zhOMLDEi4jQeVS1IU8uipZRxnMZxzLkAYNM2Tde13WKz3vBHDb+qi3jip8+IuRmoPpf9Ac/THh71y8bD8dV3v/nul9+8/f67Yb9rmSIiugsTA3ixyadiNuVctBAhc4xty0SmVburul2AIRaDoiWPI/ZN7Pr15c3Fk+ebp5d9H0K3gHhhk2RM2cfi0ynnPzkafzL5ce6undeuU6OuLhSOiCFwwxKZQQGIaoe9zM0OcK0CDFR7lTOCy9xUVV2LTUMpYwY1QWxj4BClpaaPbRNjCEJCyLXQ6pXYR4DyMfeAM5TA57JCXQhorrmcHjJEEem6TkgQPEZCAtMC7l6zhU/LtogYRGKM5jXBK2lKpVgIM3YdT36E7l47wB8fbgM7rfM55+12VwsBqgrujFg1yQMHYVdWJyjmjk5cj5mYORA7GUiq1E74PTP/9w6EEMJms66Z/69//Zvdbn84HERksVjFEJHoJLwIc2UUAZk4iIRQ/SZFAodqPCl11XtMX58bb69effvtt3d3dyLy4sWLL7/8crVeMXN9Jk9p4u8dzLxarVrwy8vr9eai6SrQGAxAAklARjwch/uH7bffffcf/vZvf/7NL968ebvb7XP1YCnnye9mio8QePUiFPchpe3xeL/fq5bdNIylKIAjqnvWPE1TyZkImbkY1PAfAKY0aqnac0gsWlRLcbeKf2iblkTMoe/7x6KX4AZW/5wb/X7K/ec0fy7tOwBgldzKuRx22w9v3nx48+awfbCUoIkUODAxMzpoztM0JdWsxQGYGE7+QWV2hnMkJEEubpYJjZi7fnn95Nn1sxfLi6tmtQl9xKYruMoFJ/ek2SpdDgwM0H4cXArMJcyPZlszQgcM3Y0RhSSEwALqYHNlBaUK8te0Zr6A6lC86lZjKWVM4zTlaSpp8pKrIasHwbZvumVsl03bxRCbGKMw4qnxUnn+BHSCWFS4IuJJPxzcVQuYWSmuH+WuESEIAKAQg81XHcgFnNhjBGbH2RwezoomVTqcmFR1mqZxzE2jIhxCqATb2gistMWZ5lHmzmhVmDSz3W43TalWB0So75pF13ZtG0MQRuoohEZN1bzUPgYQEUcOCK5ddlMgD4x/d8r/cY5hPTsAgLbrXn7++Xa7++YXv7i/v7+7e4CH7cXFddf1IQQiJCY3H8chM0Zh5ibG2HZtqEG+CDI7kDkyoHvtJmlNexxgv99/8803v/rNr8386ur6iy+/fP7iRQgBwAkRT7PicZ/8RyOEcH1zY323Xm/apkWuCh1IQoEZDVR1t9//7d/+/F/9q//u3/ybf/frb789DGMq2Q2KmqqefeHNZuz9PA3BAcncjtN0u92aFnO7P+wnLVYJBQ5mriWrFmaKjZAhIte1fprGUuG7qrOCHlVD4UhCEiMymWN8rOE37/jm9Xhq9eZjX6OuAlZvpCsgGjKWkve73cPt3e7+Pg9DQyxt2wZuhUUEAXKxlPJ+nFIpCk4sTYyAmFXVLOVccW5UHYIJEXTRhpuL9YuXL7/6yU9fvPys7TqXDtoeYp9KN5oO2UetazOdApRzy/HR5K8X8jzH6k/NDGmG25tDVoUxo7oQNqEJHGaHhdm3wysjKNdiAMJoMCZLx2kcq99JAEcAY5a+j8tl1y6a2AqxEAOignvFJMzAqMr5LJUjDMhMs4exg4MVBdO5lvPJ9HAidbRqJIZe/U2RiUTmDO784irIUcuyORcAkBCYAouklAEgxqZmoZWKWKfsx+fAABgR0QymaSylMEvft5vV6uJiuVy2TcP1YSFCEQKtWVddpirYAxnJ2cy8qH7ShPlDBkI95ouLixefvfj6669vP9xut7vD8bjdbtu2Xa3WlSWVVevW51FCEK1kbJ9P4oRVmVmTlSMoIZj74Xj88OHDq1evttvtxcXFF1988fTZs/V6fttzr/TvPkwWWa/XEGLbdswyxyBESIzMRctut3/95s03v/zlN7/85as3b+7vtyc55FmU8XFhoT5qc3/arPaIJ827wbQkcz/mKVfZD6RqIllKUS0AzszI4o41NaupRM6JkYpm4RBjtVxD5CochmCfYkmg4p7mgve82FXhtlnNCwHwJEJcf27jcf/+3et3b17tt1vNOTI3jA0jE4J7MZtyGXJOOWc1IAT0Yqa5FLeiWmrIOatHg7qRK1FzeXFxc329WK4kNkaiHKHdmLRDhkPOUymqClyzkMq//W1sv5/9Ek61LaSqplXLymYwTFMqpocxIm+Wy6ZpZ4mKyvCHWX6zVEq0goGL0wEPs/62VhdmcHAi6LpmuWhjJyRoqADmTnNqP4sH1RzbwRTZABjJZz2dKhU8E7h17i/UyQyurjnnPKkbEImcNEiw6vZxoNPmiohmfjweR8TipqbMstksNptNKfr2zdvdbt/3fYxVxptO8IdHogbgZpVIVp/GYq7E7fWTzbPnl6t1I+KpjGBG4O6WcylupzSFDBkwKAKguqkaMNvvRPj9vql/yjpBAl9dXv3VX/3l9mH7/fc/vH799u7uQwhhuVyKSKkUKctEiOBBxsORRbgJUUQciUQbgBnB6TW0phDCMA5v37794Ycf7u7vRcLPfvrTv/qrv7y8vBBheMz++DtjfgAgorbtwGe+JpwaLgAECofD8bsffvjmF7/85W9+8+bt+5wyEZup66z7OAekVuElZz6iz5mAgztkd7CipQBaBre5+c5VVKY2aMwMAIMENRjHIedSraJszimUYuxC5wBFa7UNzNzUZh+J+oy5u6urOpFjNdImr819dCef++SOAISIbuY5P9x9+O7Xv3z13beHw94NWFgImdDMqujcUEo2d2GRQEgAUKqkprsB1JWIJeCsKWTk1jXt1dXlarUYhuPd/UO/2TAIxI1RPKTtfhhzmcAyUmXK1K7gWSXvNPlPclowr1Uwy/agcwUcFbXDOMCY9TB0Evum6xqKsQkhSpAq2KVmORetGgjq1cXhMAwpl6zkqcx8YXBiaprQNEFC1eZUc1Cbt55PniOf/zlFKj5T5iqMwWZy4Se/USEYtTiCNf8AIiKulXgRqbpxQIQOlrOZ6ZRzjOHi8uLF86c/+clXOZd/92//5t27D+4AYFrlPuY2AFVek5kBAcMMA5irgY4i/OTp1fMX14tFQww5FSsqMzFC4YSEcTBDVCiOgHSCjPyxO/+jGlu/7L/44ou727u//fnP9/vjMAzbh4f07FkpJZuqarZCiAgujFFC16ZcVFWpsrgrg6N2Vk6o55TSmzdv3r9/j4hXV1dfffXl51983vf9H7LbPx6IFDi4KFZo09wOJ3coJW93u+9fvfr1d9+9efNmu92pWa0mAPhMPz/XfAhOm/+pE2+zfooBqLubArpyjRVrgixRYgxNCMEdzUCQ3L1KdYQYQCCn5AhmaqYhCNZMe9apP/318TU3Mytuc+WrbpB18p+P1HDGhpjqOBwfHu7ev3t9e/teU2YEQypVzrmUKU2TlgSgVbsKZvG7Ur3uEJE5xEBBJERERndBbygs+0Xftkw0TpNMacGBmwVwlxUPQz4Mo1pGNHQyx5r+2MkO6zxmbD/WxXiuXKAQGyIQEHFJedof9TDYkCzqsp3apm8aJBGODYsgkZhxqAglV/NSihNdgVOIHPb3u+PDfkglGwIJcRAODFCq6ZWaOcy974oLqEpAc7gyM44qdbg+EOoOFdjk4I/mTDVrDiLmZkRAVBGDJEIxcoghxnAq5s9rRa3zdX37+ctn/+X/8J//V//V/4gQP//86X/4m29evXp3d3t/HIaU8mwa6OjuNQwTAZbaNiOzXE8jxvDixZMXL550fUNoM0waoUZtWOFMwJVGX9vCNZ5ABPrDLLrPDyGciA6mECQ8efLk65/85J/+0382DtMvf/Gr7W633++bpnGqx1wQAKwIYWnb2Z0N5vIBMVXnD0TCMJcfh2F48+bNw8PD1eXli5cvX37++fX1dQjBZ+EQ+gOPtrZWTpUxOsFD0cyOw3h7d//dDz98/+rVw26XcnJAYsaiJ+0bOD+TH8/8lHafswGqtUwiQKgzv4p6NBIXXX+xuVwtN5X1WIqrVugLNbElRgQyN9WSc2Im5BkdC7XBDlQ7YOep71Zc1Ukd0AndfO6d19WbEIiqTgUTF0+H/W77cHfc76ZpBCcnnhCyqU5jySlrVkIMwYHMHLRwcXdX8OqTFZrY9q3EyCJ1p2iZVl28WC1BbTyOsUVAWa6ulstLBzqO0+FwHIcB3ZmwCuhW/zqzWX3r4+Q/X9RzZlOvNRNXjWFVH8dUhgmTTpCP49QMk4TIMWKLxIwitX5dZf7R1BNEaNcAgJyNhuJ+nBxRYoxtKzEQ8ywdArOxHlgFTtQw8uTcUCHJ4LM4jPo5zkc3gB/nMDW+YZqdFB3nRwQRRbhtY9NGEal/F+GSZ8HGtmm++PKzv/5nP/vrv/5JE4MI3Nysv/3N67dv3t8/bPeH4zRNqk6AZpDVxnE8HA7n0NdPMKHFonvy5PLm5qIJ8rHCfmIlMCJTAGCYb0J9rmZgOTPDHzH5T7fKoVYiF4v+2bNn/+Sf/OV+t7v9cLvbHYbhuN0FZEIk4LoRORON7VSXM5hpJIGZAUhVc87TOAJC08Tj8bjf7x3g+fPnX3315fX1dd8t7GTN8kcOfASymCeVlnI4HD7c3v7w+vXrt+92+0MtDtFpmM0F7x+91znh//RHeMapVIFpJu6abrVYX11crdeXMbTgZAZuSBSFMcYWqeqyZji1deD0b12zTpHdx/Fo56/a+zOWDSsAc549VJsKw+Fw9+HDw91dyQlr+bwHeQwAALcDSURBVAxhKsWtWKk2FTM+BU5lOXcD81puY6EgHJiZyN0IMBJ2wosYWgnoSMhtt+yXF12/ZmmGKR8Ox2E45jwBGCHMkDWYpfV/1FGaHVpq9QJP5B5HYCSrWtrqWkzVBckMjsPEsjcAJVw1EWKUOgGEailEwQu5MzZ93xt2QwlxAGIMoV8t+vVKYoPE4Axoc09E1REqe7/m9+6OZERAWHOsk3qIGTgwIKIj6Ce3380sm9UYqsb/pZoGhdAIcde2XdvVBGC9XoYQxnF0gHFKy+Xi66+/+Oqrz5YL6fvwz//FV59/cbN9mB7u9h/u7u+3u/1+X3IJLKXYbj989/3rf/tv/+bu9n4OQdWQueu6zWZ9eblerxZM7qrVpOyUrtSKKgEgWK0akCOQOwCxsEj8w3f+edGplmcAAA6I6/XqL//yL4ZheP3q1bfffjel8e5eEVBC6Ba9iBQwBAh76po2XxqcRI5FAoAP07jdbu8+3LrbxWZzPA6IuNlsvv7qqy+//Gq5WCLSLFD4x4QoACds1ok2U5PLkstuu3///v2bt2/ff/iwPwylaMVcV663MwEUVz/vV/74w+vfa/sVPoJraokaASOHVb+8XF9eXT25uLjuuiVzcEME6tqemUOI7sqUnCtaoSr3EM3YdaRZDfYR0N3dTV2L0xwROJDPUBc0cHQkEBZW1cPxePv+/ZtXr+5vPwjSouumbCmXlBJqFkIOgdxrgEp1c6hrR02bmYSJ0SsMuZQciNsmMqPn7KpM0i/Wz56/vHr2WWgXKdvDYXi4307jYFrqEo1zieWUoJwL6nXynxAaAI8VGOpkq3+3qstUvVWCI05FYRxhCDj2HmMkYqY5GJszTHV0Ya5bfdP13XIis9Xlpl/2yKLuFXkOVe3R0c0qvPcUkBvC7M5eEbePJj86IoEj/CiHQZyB3+QA7miVaARcK1jL5WKx6CuGf7FYNE2oaV7XtReX688+e/rk6ZUwEPnFxWK1WtgLHo5pu99vd/v9fq+5xBBy1vuHQ7+I33373d3tvapW9GQMcbVabjbLxaKNkV2rHTjNHQqoj0fd0KpiYdUvAQdXRTUnsKb5owv+p8I7AEDbNs+ePf3JT77+y7/6CwN7uH84HvduHmIEhBAjgHtWdOvbrpghi0hk5qI6TcO79+/u7u622y0TAUDKuesXbds8f/Hi5uZJ0zRwwq79WUYpZbvdvv9w++7Dh7uHh2mazGYi4Uyhhkors6oScL40803/eKkQzpMfAGpogRRDXK5WFxeX683FcrFumo4lmiGg0Cn1M9OTK9oM+qyT304U8t+uaLqpaTEmR8AqOlln2emrQVG14zB+uP3w5tWrd2/eHHYPjCiABVCQJASJoYnMCDXFmK1pyWcirFnFZgaZBXXNzLWgeKDYCDVBurZbrTeby5vN5c1yfUEch6KHw+Fw2Fdn7XnteoQ9+DGnD6C60c0BR62Fnw5I3efKGCOjhIZjG2NsG2KZTH0c8Xg04RZMRGbgq6pp1lJmAJYbB+lXqysKBbFfLUXYLRUrkSMSmaKjAhOAOrmbK5LXtcrnYi7OluhYARY1tnN3AC2u55ofIom0lRMFiJUMqWjCSCRNEzeb9Wq9rCimruuaJj5st4i4Xi9vbq5unlwsV52aHg+DOSASU2gauArdcsnj1IJ5EyRnfdget9v71bInpJQSETax6btuc7FerxcS0Kxo0aq9hafuIvLHZwkJGQiZazcrpTKOY2pD29nvEO/+/eP8XNbUAwm7rnv+4tm/+Jf/goT+zb/+14fjPpeStZhZDFFCUJGcp75fmANLEAnucDgebz/cfvOLb7bbrYTQd93ueBTm6+vr9cXm4uq673s6ESHr/vpHHCXAqaNkdR8CJwDLJT1sH25vb+/v7veHA5jPRm6IyMjOrkBe0dn+yFv63PSr7ekzgg5m5UCvhX5qmna13qwvr/rFKratNJE5VqK4cDD3lKqDQ5XScDEnJCIuYHOFrO4zn56Ia/GSvdpgYC3xo3tdx4mYS87HYXz7/sOvf/Wrd2/fDoetlUkQCQgNF6FZLbq+a9rAWN0fUp5SFQ3KpSobc138OERxhJwzuItwH0PXhL7rVpv19ZObZy9e3jx73i5XyGIAuZRhGKZxcNN6lX2eOBWF5HO55dH5SN06VH+cPFtRd6yEG2GBgIEjh0AihjClPJllgGOa2q5rmijETCiEblpScjPwnItlVWRuF71JaLoeCfME5mhzNc+h9s5R1dxA6xV+FKXMJLhapLPTWZnPVdtHx01MwXEWYKXqBoTmWAVc647C867CAkg5KSLd3Fx99tmz66uLrmunYVdKRiJEVzZGIMK2QWYhgCBclByb5aqNUQCqkj+zSN/3l5frzeWyaaoIAbgTEeNMcJyTyPrkzqDKE0bMDFIqRPmPqqLPAz/ZjYlps9n89KdfT9P45vXr7fZhfxiqVEmaUqUqtW2jqiJRJORShnF82D28f//u3bt3OefNxYUDHIdh0XVX1zc3T26Wq9VjiNuftPn7iVtWJ6oBWCnpcNhtd9v94TBOU+AgPBcHq8/D+St5RX6fbKR/+xJ81IByB2CiGJp+sVhfXq4vLrvFKjadiBAzACERM3rx6hXnc5N7Pi//WEE+g3cf3xS3UqwkYzKpoBia91cEQAbEktL24eHDu3dvXr2+v7sVhkAohNVibNEvN+tl10ZytZJTGhNTg5SQxuwZoXDtiBMTCaM7AIIzxRj6pm3btl8uLq9vrp483VzfLNab0HYoAoRqmvOU8+Rmv32HfvfOT0hVwRp8dqBFwGrcYebghEAxREAjpNpTKWZDylM++m4vQdqm6dp20XfLvlstewIoKaeUSi6p2DHB6KwSnbjUPmJo0KozLzgFYmAmpZJNPde6tJPXpkclUfhshUO1J+bgUOGAxT6m/YgAyOZYTcQdUK0kHQsgGQxp2u2H45CYQwhaipeSjocUQnjx4sXXX31xfbVpQhgPoGpBxBGGNLllAqvSEISeiIr5lIpqNncArNhGkdAvuqur5dXVouskCDHS+aHymfF46lhANZz1nLIDhhBFXAT+dBvouqzYHKaGEJ48ebrfHz7/4vP9fofvPux2+5zKmEtKKTbNzfVVCGGxWMQYdvv9hw8fvvvuN7v9DpH6vq/ogGEcmxivb66fPn3aNg08aiv+8cfnDrVSaycXFgM3K3kcjsPxkHJWsyhQpXJP0RGcwOg1m6MKmasR+elIqpIbIqDjbPrg7kTS9f1qs9lcXq0uLvt+FZuOiGsMgVAtWxTBaBaPJmZiErOafxrUYr9BmdvJp/XAanibTdkqBA7IkeoSUEs7aRq3Dw8P9/fD8Wimbdf2TWiElt3i8vJ6uVy1TXArw2E75QxeBI0jMzpgYQVFtjP/tE4/YWJp26bvum6xWGwurp8/v3r2vF2uKDQcAgUBAkCbl7PqH1W3BT+l/fBbyH4AOeXq9ZLO1ZRTRx0AHA0YucY56o5qxbVYdXdJCDiGMHVNmRKoRmZmmqY0DsfjME5Zk3HhaA6OZAAszODV6b7iCIgIWQiYOLudtEQrPQAVAGfywDm6A4eKV6jL06Nhbuo566ilAKKqZh0IMCmPKY3TZObL5SIEQYSUiqqvVt3nn7/44ovni75BsFkvjGZIkpk55NljuH6AWeWIAwIzN00TQhCJTdOs14v1qm8Cc5WS+XhQFQjk1WgQyZGIrJb6gNkxQtNh+MhO/hPHuR7W9/3Nzc0XX3yx3W6Px/F4HAoUVZ3GqdJsqk6+SMg57w/77Xab8nRz82S1WlVSQ9M0y+Vys9ksl8s/acJ/emDnxuQsZmf1Xp2NceDE6zsLLH2ySZ2AWfAJOPXTTwAABGKOISyWm+vrm6vrm+V6E7uOeCZ0zWoUABVJxkwAUoOwGhKWoogGAExoiOA6E9U/DjMrVopxMUStiBGk2rB1cgTQUkqaNCciaGNcLRbrRdc3YblcXlxctV3HBDlNuYiaOBoQoWIQYaHsquDFVIvWzyVEJgwhtl3bLxbL1WZ1ebm+uunWG2MZVT2lSqobxyHnbFag2lw/QkR+TLt+hPDLudjc9Z3Zs3WnqgnNrPbrc5kTTmDAKnpTSqmzUFOecDgyNkGEZRqn42G83z6MuThHD63nAmlCFhYJwkyAoEgEIggCTggi3DKFat/jVtzVPYEpYLXjrNguPJ+PG9ojwUh3yzamcpimo2muEuBqyYFyGlOaipYY5cmTqymNRJCmEoQ36+UXX7z47MWNMJQyVUUaBECitmlM2KwyqWbpD1Sd8lS3qBgrOT6yRCLp2r5rW2FCNKSPdiazhdAsyWCIwOIALFHgZGOCzMJM/KdPs8rJOQuTLBaLL7/8crfbvXr15sOHWxYRLhKka9vNZrNer9u2DUGYOYawXC6JVy9fvpQQPny4Zebnz59/9tlndebXNYX+1JXJAc5S/oiABmSnn7ifNKTmelvlLJ42fwSsWzp81JY85R0z4NNPnwDg7iE0F5dX1zfPnj97+eTpZ12/RKCimrMyByGZIxgEImcWN9OgrlZzgJISEIUmEnNtHZ0hBadnzE1VS1YWAgQkJ3e0ihtHtgpOCUJ9G9fLHtwuN+uLzfpitei6jiQ4QTJVcuk7DCLT5KlAMVDooC9u2UoqeZpSqSQxohikaWLbdsvVanV1vbq6bldrD80h573uZUqV43gcx2kYrMxo3dlF4jwqUvoRIhYAJKUy7xizZfu55XkqA84h6ylq1VrGIhGJQdxchIkw53w8HqtqNZiloimXlAsBI2VHAFAr6EUoiHPtbAsqObhWqX2b+zyIFVhX3AmgICgiEBK4KdocDQKaK8JHHzUDy2VM6ZjSwU2FAiBC9XnWwgyrZX99fREDDOOxlMQMOduzF09evnxydb0G0JxKFU4BL26zCJMj1hSsCis4Ql29av9juViIxJwNkZvYtm0XQhXkqT2KU8ukPsvoBJVqYUTEzuhoricjX6a/9x4Lp/0/xvjkyZOXL18+ffqr+7v7+7uHKqSzWC7X63XfL+ophBBWqxWAE9FqtaoAu7btnjx5cn19XSv8f/9hiI5MyIDsJyg8EVVqIVd96FOsD48m23n/Pz2OAKfUY44GToKv9f9Ewmq1ubq8ubq6Wa8uQmjMYZqyw1iLLyyMM6gKncDdmEhRq7VZShNJaLo2BFE1tWrm/MluqZVpxKUaXDmZn0Df6K7u0zRqTgy27GJgvtisLzab9XIZmqhu2RUMkSnEJqhayJaSpwzFCF3diulUisiU1NyNEKNw18TFYrlar9ebTb9aQQij2XFMRY2QqzFmLiWN2WbDTQDw2T7bZtzr/OfRqCQWd4darwM8EderWTeSVxKju7oBzhAtqioZ0AJCCOLm4zgdh3FKU9M0fd8js1QRXAko7OQ2WwEVA0KnGt5TQiOrWyS6EwM509wLY3ACVBJHPAEzoTgaoJuLoxPGc4DoZjlP03QsaSQEZkac6awEvuybL754gYCvX8PuQOA+TevNxdUXX7x89vx6sYyqY84FARjdcnFwqAp/mgEInUgqfoxjkCACDkTYdq1wzHmsaIK26UPsWKI7uioizLJqtc0/l8krqMkYAYAAag2c4dFC9qeNujlXcSsAWK1WT589++qrr3bb/WF/RBiWi+XFZrNarZqmUbVSrOvaGJ88ffo057TdbdM0rVbLi4vL6+u5wv/3SPXn4QCG7ChGgVAArfoPBpaubbuuE5ZZvcV9hnTMCtFVPtNmUop7PcdPD8nPOz8giYS+Wy76VYw9c0TgUizlIadcUild1/ddiPGs2OcASF68TGkcxzFraQCYMARhrntSBZh93Pm1aMmqYkwK4K5gAMjELK6Wh2G/2+639zodu4CLRXu5WS1XS5YGiMBRkKWS1JzA3EPxPNk4+JRAi7sqeAgmbZt0JvKTawjNsl+sV6vlahWbJqmm47A7TikXsIqZIaxN8RoxnRojJ4kdA9OTz8YnO3+aL6VXZ+2PfOlzk9Mr4hhPlNjqT4kggYmp+ihCgpSKpZxNJUYiRmbGSqVCh1p0N6tMfCUA8wJmCMjz7ABgQhQHPrEkzRAQhImRgAHcgcwVK/uITDCe0QlV5ay6jGIt5AASkBu4lSh4c7XWosTTYWiF2Z3TGJ49u768XDL7NOVSElUcC5wZOLNeW106qzJZpQo0Tey6drVeIMhuP5oZMdb+MQCaeSn1fM/2x/WWnxIsRBSvpcTqWP0f0/D6gwYRumPdrGKMlYr3cL998+bdOE6xiU3bLhaLrmvrjhlCqKJ/x+Ph/uHe3TebzfX11WKxqBX+Px7R8+Oh5vthysepBQpGJABCATmEZr1eb1brNkZGQnfXCkjzE2y/LoZUwfJ4YsnVqXhaAgCg0gAqhSPG0AZpiASxqhWRK5jqOI41lG3VYowsjEju1cV0GsdxmqYK8i+liGq1NWDhs/oLALhDKVpyKaEQEoHNnUYlY1cth+PhuN+VaWC0vu9Wy8Vi0TVNdGSfIUMIJPPGRgAgQFWYgmwa0bFlMaKInqs+lxabRmFhFAYJyGgwHsdB/TjllA2cGEGAGAArKg5PK+IpYj+Ren5r5y8lA0Clu5EqERYt4LNcZpWvZSQHn1E31fLLZlb6/GE4kzWKGVqZSg7iVQgJZ7+pGYpLFXuJgG6gZRYX1zmrUERlnplz4G5GzDFGCAEZ0MEKuhMBAaKgC8aP6Mv5iAILMkLVrgUgAFWdALDrwvX1JrRFLbdNG6UnWC/6ZtFxSaPmrLkkMySQwFXjBBBZBHE2LCpWz8WDyGrVX12tr642Ofvb93dqGSg5JvVcCk5TyjmZq8/7BhLxSQXG3J0EEAuRV7q6miO6uf/JJf/zeIxL6dru5cuXu93+u2+/H4exlGqa1nVdR0SIzsxmejwcDseDqsamvbq83GwuHmOH/p6TP+Xy9vbhsD2u1ut+2XddIAkBuGm7q6ub6+vrvu2EEOp6WRtNlb6P86cTErMQzV2SujScg/+6l9VCZpCIyO5YLXaZOMaIKFo8pTQOx5JTaseu7du2qSJOx8PxMByGcVCzGKMDHI8Hc+2XSxZqm6apsjAAMO/8JeccUqHqZQlV4lkhpWkadg8PaTqSW9s2F6vVYrWMURDB0PxUrKjF9QpVQndCwhgBzEoKjsuupxAmxwwIRCnnEQ9QSh50kkn7jD4ORQeDAhWCQzM8CKBGkTZX+s6FPpv1hk/OmudbI1Wc0IjAgI0A2GpLhgGpUheqjXhVRzCDEwIZUABnRi8YMGIgBHZCdUXHEzv/hD+Fk8arnwAI9a0MvJxFmsCqxzZVXSAjFgRCR2dDR6usHqyRzCfFX0RkCsINElMN9gGIxBxqGa9pIlLslkysbds2YSF4yQQId1rSqdPhNXo8SfcgSUCEojpbQgMicgjNZrOaJn369HIcy6vX71mYqje816xQqwEqzmpIDFAxE1WLzdHrvnoK0D51U/h7j3ptq87f1Wefffb5558Pw3h/fy+ncdY1UrNxHHPOMcauX6xW6+oUfp5gf8+Rcvn+3d2Hd/fri2m1Xq6X3eU635ii4npz+ezJsyfXN2/fvhunSU1hLuM9gu99KhN2/pE9imBr8XW92lxcXK1Wm8Vi2XV927axjW0TiUIphmilKICZFtVcCgBoLvl43A/jaFaIJMbAIqplSpOkgEy1GnK+M5X/P01TtffE2VABVbWkNI7H6bgH07YNi7br266JERHUVcGqNl2tnJmbVpBn1aQicCYlYjdgFgnIQZAdiChjoZKSaUmTTftRi6uBIxGLc+UlgaPrx0y/xke1Le4zUXueYJ/u/AbzCqQGxZhrt3K2I/Iqa24I1eFmzv5nd1cAUHNnR0MAQcaqQIsuoGB68vuujZwTOdfdwbXuToZVWnpm98yHZ0jCZIClGKpWe1kqMwwTwNUBXCuF++MGRRRCA9i5JnczdQAkDgTBnNAJYhcCY2glmARkalDFVDUrgIfIEpiVmblujFrU3JHF3NT0hMlhptC2/cXFBkBefn5zOKbvvnvfRAkcuBIT63NRy/yz3RnXFLSy+wEAmWgWzAMAAwKuiKC/3/CZaQ91hyGmvu+fPHnys5/9VFV//etfV91rVashsZnmnFPJiLjZbJarddf3VcLonPf9PdP+MeXfvHn/q1+9Xq0f1uvlxap/crHaP9lcLNuuXz5//tnXX355d3v3/avXh+HIzIBAYFrbTbVKipUq53BqofrZYQa8ouD7fvn82WcvPvvy2dOXF5c3i9W66xdt20kQdI6Bm4brTKgtBfOSchmn8TjuUy4SQtPGvu+IecpJTY/DwQFVrZRyRrq7+zSlYRgIyd2FiYDMLU/TYbfVNAWCronLftH3vbC4QynFyI3QkdC5ItfMZ/maUz8IwLWSXY6azSS0HVGYkhpI6JYcsk5TAdtvD82YuO2a2BBgccgl2xyB1NCC/DT5K6PvFParVTjs45wfuR5ClSZTBJ9BwQSG55e701xFNDBTgxMhAM0UEBCcq1cvI4KRn8qkJ6UDgFpinfsHcJLfOxUUHWyG5EN172AHBDIgdMhqVrSeIwHWUEPBStF0JiqlKb969eHh4a2WbHNLA4kY3EqZQmjXK2m7nh3MdEpFGLqwAPCcVbWwMACYg2Y1G2vTefazIxQnc60J6QxDQAgBl6tIgl0XudZAHV3BDQiZyAAQsJKLq4pQTXoAiWZmgpVaXjGgP0PE/+mo4BgmWq9XX375Ra5qluNgZsMwTNMkQrnknDMAxKZZrzfL1aq6U/0pWMPfM7Lq++3x+w8Py+SrsWwP4/E4TtPw2c3FiydXl5fXf/HTv9jtDuOU9F0xRAOfUac+d+/h0YJ6bp5UaL45MHEI7Xp18eTJ86dPn19eXq/W67brQxu50vOt0joRkWxGbJU6q8dxymVyQBFumiBBiDBr1f9I5m6Oano+FzOrl1FEANGYwSHnnMZxGgdy62ITYwwSCNkMLKubGZsTARK6g6JXWR2cZYAdwAnQlAgzwLHkghQkAmMxc0ASri4BVlJK2YqGqpTZIAVkcgOooAB/NPnhtBOYqZubqmmxR+cCAMLCtZ0HCAaVR0xAbugOoGBnVZ9alDFzq4wmmNn0VINlIJ91s9DQEcHZHwmHOFTdWMCiszaKA7irARgoMDBx1a9GmDcacUICEnUoxbKbVdGvqrECWoqOZ2z/9mH///5//auf//w/lKLuKMJzYSFrTtP1zc0//+f/xc3TK8dBbUx5XCxWL1/0McjhqGnKyArk7p6mNB6OhLRerZbr1YJiaDg0wcy1JFUz0zTtHx7ujseh2M1JhgxAwQpY8UoaDUJq2T2fYVQ471iIyO4+pamUMutGYGAqbg5/7yWAHmuNIgJA08TnL56plePx8P7DB7XysL3vFm1KQ1Fl5q7vlsvlcrU6i1XOGfWjr3/yMMehwCEDZPBJi415SuNhr1Pq267vlv/sn/41uG932ymN28NBc0YiQphV+ypCyGZ7CjtpeBGiE6G6SFyuNleXT65vnl5e3vSLpYSICGYlF4WqjQ6Vl8aIYO5aNJecppRyBvcg0sQgIu6mlZ5PNWyuefMjtSj3UkpKqdLZLBctejweTTUwtW3TLbsYojpMU8nqIAyRgKuREKFVUft5P5whDFX2FlyIsnsq+VCyT5mlbZqeWEANKhQW2VxTyYdtonHqNhfCfWA28nKuSAGfiwt18ruquZsWy8WLPtYmEYrkdS0C9Aq+IwACI3PAomYVhzED8d3ITtI/bm4ArtUSAKkmxEgzvXkWNHaAWuQjQEafqXYVTgiKYO6FlBAx1FY3grvOsEREdKfsqtlGMEcOWCVGvZilYqOdQEsp5bevb7/5+ff7w5iSzuVhRy2axunl54ebmy9JZH+8325v7+5uLy8vA6/Xq8Wb1w93d+/3x6FoJsI0TfuHHRNdX19fXG7Wl6uuD6FxEScyBDTF7W5/PI4pZyQQmbV3zc3USlE1qwJCgOTOdf2zuYFQO4hoZlpyZZJX73FT/b0Atj9y/AiQw8zL1fLmyc3zz55nLe/evdsf9sN4XHRdaOJms1muV4vFouu6EEL9lT9Ltl+HAyhwchIjymCaPTskWzZyOAzr/vLzly/Nyuu3b8Y0fff99/e7nYK5Kf62qNkj5OTMvDUQiX27XC7Wq8V62S+bpo1NDJFJEE5+fPPmWHLdAqs1R0pJ1ZHk5I0BWrKhVwnTGdbrCJ8GQaqz9w9iArWSyzSORNS1XWhbECmIXgygsDqqgxEIgiAioQk4VaxXnRiGoFWGDCEQMjhUk+VSiDMAsUguxUwRXMwbcFAdp2RTOpbSTsvlxTq0Ad2rHp6DzS7c86rp4I5mqApFQT/d+bGR+mPwWpM6uXqQu9epfoKruDs4EjidUXXgNvvzgdvJtYUYEbFqmzpV6UtE4FoCNEOrOsROaAjFPVdTe0EMXEuIlRfI6Fzx1Jazj4jABEzkruq5+Jh9OgeozNz1fRO7Dx8Od3e7YZjcoY0R3Mbx2C3643jYbtvvf3j1q1/96ptvvnny9Obq4tmTpzc///n333zzy2+++c1ut4uNgFsaJxG5vLxYb1bLdb9cd6tVt7nor65WXRsR8f2Hw5ScJcTYmDoTqrm5FtdsRUuqiBVmrFaoc6cQvErimlZVL69EOa9Lh35Sif3Txm9P2nPq3vf9zc313f3dr371i1evXquWxWLx/Pnzr7/++uXLl9XC4Fxa+zNOfkRCCSBRgYoBmxfQQl5ynqbBfX1xcYH4xb/8l/8DQzfT4uVwHIoWqADT6hR5Zp6fjouZwdGcAsc2NG1smhCbIE3krpVu0YXI7qpWylQr9JqmNE5jSqlkVVMtBVGk4dpr0JzqSlH0TPchZHkMvph7Daqq5p7KlFQVHSRI03fUhEELZEVDRBFFVAQ1kOqMxYyOzuiGpuBVmgaz+VjMwQNhI9yFgE7DOCloplCIDuNhTGPOKTJvVqtAktyGYdi/e7PoF1//9CeX4UKYDKGoqaMCqHnVn4OZdVQ5bucgfh4CgeYSYZ38Ff6P8JgT6LUoULuw50pLBRGcFbaqU/esfoQIaFTjNCBEpAoTMAM3cquVBQJn9NpHIHRBZ0ImMC/qcCpbmheFrFAQ0EiR3EiNSoGs8HG3bNrm8y+eb3dfd4v29ev3797e51y6thEmte7m6UXTCoDlrOOYDodjt9vtdrvFcqGGqrjfjx9ut8xopmmYzP3V67u+79ab5XLdL1fd5cXy+snmYrPsF93dwzBOpaVQA2uDGoeUrMVdZxzL3HRjmAnajj5rB5acS31oSGZKo6PQHyXj9UePEMJ6vV6vViIyjsP79+8Wi+XFxcXcJHtkEvxnP4yTlZfXYiTW2pEXKxNYaSJfXm1++tOvpzJN0yhR3r5/f7/dHsdhSrnScGr6AfDRZR5rkEkgxIG4CWHRxNWiXSwXy1W/3CyaKICmWtJUpnEchvF4NAJix4JoTh4DUQhNwyESkwMUNTtZXNQJoJ8WleHk3VJKIaKUMwK0TRtnpW0bUjZVdiFyIWAyKA4MwE7ETFbtd8ms8goBEQygmLsbncJrNUjFvBQ+AmEeDykNU54yMzIGDlr8MA53d3fjcdhsVoIWGiFmBXBkJyaYBV7tbExaFFTxR31+EIK5/1TF2wDgRPx1QANUBwC3Snk49Vq8BkQVrT5vWVaFf+ms/z+XGyscl3xm4gK686lPUj06eRY9qxiACiUwM6zIIqg3BBCqoZc7uqEbzeaj9UyWy+6//C//6uUX6/cfbn/4/s0vfv7d9uFQGRGLZXd9ffni+RUgP316qfp5bG2xaEMDEvCrr75YrRaLZfPmzevjMB4Px91u//Cwv7/bDeNIhG5+2O/vbu9ev313fXPx8vMX45iHIRF5ygUcctGcdRpTTokIJJCdeFkVqFbjSiJg8VymaRpKsSY2IcYYAyEXB+GW/t7V/t85zs9u27abzebm5ubt27fv3r1z8IuLi+vr67Ztzy30xzCBP9fnIxiBkhcBDAyRMTAIG6OCp6KjhPjs6ZXDX8Qo10+vf/mLX377w/dv3r97eNgdxwxe5h5rBYiQQ0WmONgJGtkIrhbx5nJ5dX25uVitN4u2bZBh9v86HPe7/WEfD8cmjamoVm0BREGODkGds1rOkNWyVok4zEWncZzG4SPC193d1ayUUqWrKz9SRMaUk+apZHMQN2ETshkgRAZUIeJaPVICAVd7aybyijZyRmBwS9lyIVUwKNMREElzg8jC2W233zkgOaUpm5VpGt68fjUcd13bxCZyjCHG0HShQhQJilrNcHIuaEaftsfFGABctV7emSgx603AySPvVHc991bd4AQdtLrDA4DNFuNwuknwkYBb/UG9mimc8BkEJ1B07dIjITJRXRZ8ztnrO7MR18QGAADQAI3YHyW3Mcqz55ebS372fP3s6frmarl9OCJz0zTLVd91XQydKrYxrNf9k+edMGwu235Bi/7i8rLte7u93ewPx/3+sN0ePry/f/XDu1Ls6vKi61qk+jxUqrMiQHXCBCdmvtgsS/Gu70XiLAhdVYzBfAZyomqN7HPRNA5TKX48ZObQNE2MkUPA9s9YYv8dozbDN5vNy5cvD4fD4XDouu7p06eXl5dt29YC+5834P84zGq2R+BCGASCgJATVA5blhgWfffs6RMJslgulot+fbG+eH35/v3tw+5wHMfqrWFWrWsLIAoLEbHTql8+f/rkxfMnz59ePXt6cXV1sd6sFsu2iQIEpeiUqBFoAyw7maY+53KKiAGAAKU4FYVULKU85jKMecplynmahuGwHY69WTlfw8p6LKVUa9cYo4QAACmlIU2pItjdmVSo0EzbMkBHohC0hKIihVHQiVBYkJmJiVEACQzVkT2GMBNeABuRiFycxqJDKupGhEGo71tBIoSS8wheSsZxaGLslsreSdMQYVU2VldAx4C1E3++LWJkZq6gZ7dfcABEqbL3SE5o6mclpRmyg34SA573XqyZwgxVN0S0EzHTHcANwGcxxBpTzYp2CEhWmzeAjNWoGCOLfiRuGcCMjyhe+fXsGADNMfhH9BW4K5J1DT1/srla91mrWPH8DgRC1PKLPue03V+qDjE2bRO6BhHb9epFShfqJeV8OKSHh/27N3dpyl0FeUUqpRwOR3Vou3Z/yDfXm65pIndd1/zFz74gos9fPt9sLphiyZiylawnIiSWUsYhHYZhvz8A4nKxKOof3j+MY46hXS4Xl9ebm5smtvpHKfn8IQNPtLy6TV1cXPz0pz9tmqbrOmb+8ssvLy8vY4zwKTTwzzi8luhndJkzUWAUAWY/gbXmP00TntxcNV272mw+e/ny1du37959eH97d7/dHg+HYRjGcSy5mBsRxRib2HSxu9psnj97/uWXn//kp18+e/F0tVy2XZTAiF5K0ZKsJCZbLtrlonUHV9CToTTgzDQv5qV4Kro/jrd327uHbUrDON7tdh8Oh0Y113OpnxtEiqoZxa6rdJ2imnMuWeuUUJ/VKPGEsQFAZopNCTEmYSJwU0KMQZqmbbsuxChEQqE2JEopKeecEyK2bYNERbOkLJLNXFgQCdYeJS6XC2E+gZSPJQ2IxqBCFkIgdBYUFHdn5mUXhR5PfnQDV69OsvVOzRh+YakUc53rUQ4zqH+eTwZoFRKAM1EbZkQ9wImBf8Jjz33I8zzHk8P4CatVlQucwc9Stjg7NBiQA0kV+NdaUEA2ZP8kTq6nUBC8bcJmtQCiXEoqKeWqvcvCsW2XAL6+sJwP7kZAwk6IXdcihiqgnLMfj9Nnz2+mcUIAEWqbUFR3u8PhOI1TVoUnNxd92y/79XLZydcSAl9fXy/6FsFznkOtUlLOpWRLKU9jvt/uX7+5ReRnz58S8f32cDxO6OPt3eHd7cPhiKv1538mHt3vGHXXqnQdEakeu0+fPl0sFtX68h+u4mA2+7DBTGtwRHPXnMdpGlJKEqIjCnMIITRN2/cXFxfXT57e39/f3t3db7eH/f5wOAzDUHJx8Moob9t20S0uN5ub6+unT2+ePn26vlg3MTJXNe5cclbLACZCIQjXCkutbleBOHBAULesmnIeRitFCUfTfUoPw+HD9uHtfr+oRKk6ZkFfJCKSEIg4a86pqBoCCrOjzzEfeN3wEIWZiLlCmMzd1FQLIxJRA9DE0LYRveYCyEgNtq3qNE3z5EfMJYtkGkczkxAQQdWEJYTQNJGJU5oY3V2jsDAyVooMIjNEAQBECPLJXRYHqu2BolCtUB2MsYKqEITAvRKZan0CK5TFYXYqQ5oBvKdKbC3ozL/uVJePGg7AGXVcu/gAqmZeKgKWBBmlCqkBM1EV8DRzciJgPkUWiIQ1kTgn/FABGFqmlDQlBkRgRE06ZZ3MEgISI1NxH5GwiRSlqQzGUrKquau5Aua6vndN5AuYppDSBAAhUnARYQlDencvQs+eXq+Xm6vL6/Wqu75cskDb9sKgNppNqkl1GsbxeBz3u2PKikD3D/tvv39bFKfim82KA3WLdjjq+9v79//h7v378euv/3qzufqzz726+Z839rZt627v7l3XVXPxs0Tfn30JqByOs+vWibRjpaTDfrfr4nKxDBI4xtq9I+Ku7YLE5XL17OnTYRiGcZjGYZqmlHI16kNCFm5ibJp20XfL5aLvurbrZutn1ZxTyTmXjGAsKMIhhprJItQ2SxXtBAdTVfc85sPxsN0+3G8fPuy2d4fdw373/uH+zX67Pu/8ldXnDjGGGFthdrM0pVIKEjYSQwgApFqsuv4gBZYYYmxCVQdUN1N3K0VJELu2XS4Xm826CWEcRyvF1CVKrSNU6zRmNvOcM/NoZkU1xFhK2R8P7q6qV1eXN89vYgjbh2XJU4wxhGq7ijXUkhjcPU3jWcq7DlHNqp6z5lxKKfPknwWKrCrfV//Qk5kLk1c73VMK4KfJDw5uhAjOzFC1t04ynFUUzGoHkomqbnfRXLQouCOgMRlnV2amma9VUdAVa1CZvLW64KYlay72uBKLAIQgFSjkEMDdvaAzY0BC4cDIOGv7M1AEUCgKoOeG6CzmgSEIcRdYArOYm4gQcotI3EzJQ1OitKvFar1eLRaNhI4JkNiseM4ARChMJmJEBpSQKUjsl7S5SDlbbPu26/q+QeDhWBDkw4fdp0Xlf6hRd/i+75umqSvCjD78B9v23T1nS0lD0MT5CCpeGiiTyDTyOHTj8RAlSikcIoigMJE0MTZNs3TX9UpLKZpVSwVcwwxeRBEWCSFyCHVLh+qeokVzKVYU3IhBhILUCvgsFY8nhlUpJadpGA774/7h4eHD/f3t3fbufrt92O0ettv7D/e3b3cPN3ra+c0sTVMax6ZtjTWn5A45Te4QYgwh1qaJFnQHJhSWNjRN07RtA0RJSyql5FLBdoGpbdtF3/VtI8w5TXVuU1XpRxRhnz2kS8mzLu5pfXYtZUpTzokQNpt14FXXttDGIDXlqVQJIiYRdrc8wY8wC5Kmo6qnyVJS1XnyCyOZopIiFrV9mooZihCLkFCdhQZWkbruUBuCpq6FEEq9DCIIs+7w3HY4wZmZ2V0BfMpT1pyr5qAQEXNgoRC4VsgRZpa3uutMS1BVLZpzTlPOH/v8iBS4wwguDoBC4uACQthUqz9ERhCEau0eHKDUciUGYgRhcjWbHBwpAhCgMcaGuhqpMLEQh7gMcZGSOkAIsV1EaYLITAVGZAIgiuAqYiF6bFLTj2YeQ3wO9PkXWooRQYzcd41IcKf7u+Pl5ZPFYtN13T/QDHw8t/EkPnH+/p8Fyff7hrtPqRzHRESoKR2G0mRZWk9tWTZayngcqm0xxRjbTpqGJRIzEAEBgVOgECJC+Fh7nqvSgASOriVVVzItmrOazeooIiKBhGE2IgSY9ewALduU0vGwv7+7u7+7vb27vX94eNjtD8dxyGV/GO93u/vb29t373YvHj5OftXhsD9st3U2plFq/UxiaGOIMcx7FiET913bxiaGEGOMMSJSNkslp5TMjRGDcBND20RhBNNqVF1SslLQbYoRoKpUVFz2qGpAyCxW0FWJQHPebx+O+13O08311eVms+g7IVS18XhQ865rhXB2/bNKtft4a+Tz5/9CDUqqnre17GfMGJmlqiaqDSWrO4kgsVCFzToYGvxo8ptrQQQRCVInP6q56QzMPIF6kYhCYABPJRfLxd1wxgMgE9NJ4GVuGfpJTggAwE2tlFKylvz82V/GME8YQhLqacaoIQK5G0IE11ONAWcijbujuhdHI3Tm2l4QcDdPDkYoAGdU6QxHZKpmW973WtSq/XEMgUWYBQHNzV3F+tqarDlJa9YvsgNIfRJRzCzlhOBNE0SESS42qesumZvHk/8ftOf/I0mMf9CQo+uav/rpZ4jYtTGykY1dyJe936zbJ1cXm/W67dcS44y/jy2FiBKwho6V/05V1QPg8TWZtVBrIF1AC4CCF3AmB2au7owcagt/DhlneDXA3ICSjNJS7EOXOyOQrl+pOk0p74fh8vrZ1dWTn/7sLyvNEQC6fvHTf/LXbt60LQchYiZk4tDEru9DCPXhMlVh6bsu1udDREQAaC4NlmxuQiTMIhyYWMRVx3FK01TFdUKIUhUHzHLOKaVpmhxAQhAJzKym4zAeDof9fo8I6/X64vLi5upqtVwEYVXt9rs6+WOILAJgecrrm+cSP1aV8O37b2ox/nR15sDonPz5LEAx91krrKV2BB9/mZmYPndkq905zIGGw8cVZ671zx4BH8XZTi5Q54959Pyf32T+v9NoYr9aPQnSnL7/ESR3Osgf2UvhKeeZF4H5iGqvAmY090d1oI8PGpzT4cdNkRm+8uhAfS5E1F/F05J3SqdrlukzOr2Snap0PwDWltvHd/oHXgL+04wp5XcftsOQZqUuNyITgiDUVO80YjxXHCrnbr7/cL4AZ/zRb729n4Xq4PQF4IwBqtfcH7+6vluNQ+2E1S3VPGvWsUUzV9NcSppS1/XPXzxv2w4ApnF8//b1eDjgSWu0/lNL1OebVfMprooY853HWl48g+XwVF+Z/3vitJ5VmPH0TJ4KJQ5QrX1wBtpXqKEqAFRtzCrKSIinYBlOKd2MluMQ2+WK5QTi/k+RaP7j+Mfxj+M/v/EPAin7x/GP4x/Hf/5Dfvm3/xpOQP1aRuGPQqoANQX4JNk6Rc4IBLMu9azqSXM09DFqf8SJOKWXYGYIQEIswhKqv/05fPskR6hCSTPy1Ks8Ts6Wik3ZplS6bvHs6Yu2bQFgGMfvX785HI7Es3jYo1yjxlGMJ+7RKTUrtSB5iuqrK+PMHD9zOU/FAp8ZHycHe5jzmo9mUlVHjpiRCdy19rjUYIbZAEv1w56vWxX7AAczb5vu+uI6hjhfr0+ysP//CP4fFV8/tgzHpG/ux+NYmKDqE886bgAfmacfMWJ+xpoDnO7gqWRUpeDU0eodefzR839/nB6cPmUWA/BHrz3zBT59B/ATALUyU5YtvbhoukAAkMr4Yfd2SEc8OeGd5sj5oYdT6uGnzAXg5INb6xYfU5NPr975rT55cAHwxy+cL/XsmFwruFXfYE5GoRY5HosduYO7tbG/WN/EOU0G+T/9H/73Bl5sVk9khq7hGJDJGYAAGYERCWtX9NwTMkYIjDFwGzkGDkxN5LYJMYoIsxDWGjgAosOsy82mOh5GJFxs+sVmvdw8kSa6psqIq/7pc56MCCEAB+BQ1IYhbbfHu7v9+9vhzV16/f74/bvdVz/96//N//p/+9WXPwGA71+//T/+n/+v/92/+/eLvosi6GgOqgaADsQSYtNJaEKIzEhccj7ud9vj8ZCGycyFJIQYmkjCyOauWkY3JQcCJpSsuhv3RZU5SGzbrmcJ7lS0pHGsFsOxaZcXm265CIvGTI/bh7Q/+LG2UhILdqvQLUOz5NhybDhIaKRxw3RMX3/+s//Ff/2/fPHkRb21NQX95OH4tGL/2w/E4yfjR6/5Y5O73y4E/r53+J2vJCJmrvWLN/fj/+X/8cu/+fZh1WIfKRIFgUAgVdAUqDi7IbsTGKEBQka2Cog30NmgNZeiUy5Hw53K5GIkPjduwA0dKnik1guA0E/WgoD4SIJvBpvONZfTOoSnTjU6oCEBAJObWS72X3y++N/9T1/85GkHAB+27/7v/9//2y9e/41IFGL2Ki+BTBRCmPVv1XLJDlWaCapwOSOKhCZ2SFxUrZJU6gE6wKyAWUHuROhmWrk2lWZ7qqQhITq4mpdSppzMlJECSRMjIeaiZuZMxX3SXNuebo6O5p5K/vL5X/3P/8f/q6dXL+v1kP/+v/1/qns2VzdECIKLjmNAIRMHQgyIgZHnWisRMQJUV+LA0Ai3jTSBA2Pb8KKNXRfaJoRIxLN1OaAjGhGyiBY97AYiTFcLvbrw4WnTdQDqWjwnK8XL3LVRB2X20HDTAXFRT7vheHu3fbe/eze8eb3/9of7tpE0HeuZHMfx3//6N//Nv/33m+WyEbFiWiznMmMrQ2y6RdP2TdN0rSxWqDo83H14eLjb3e+mIbuDSGz7XoIgu1oah53mTAZELBzU/VimYobIEpquW0hsEFlVp2HUksGx6/uLm5vl5abbLIlgOuynh914+3Dcbofj3qG0K+5W0m+kW4a2i23TtKG1gsPuOE35v/6f/M8eTyE7BRS/3Yr7z3Pyn79WaEp9wWEs/+7b7f/nP3y46mnZUCMUBRpC4SpmTdkYDNgLgzKaIyUIBUQB1cC0oClDUS2HSR8yvkvx4MEoKDDWdpORzjv23Ndhmid/deyljzu5/2jy44lCcpr89HHyq41JEXA/zZySMR1++eZv/vWv/5sQ2kAhIAkwO4pwExtiQkc1Uy0OKCIIAFD14DFI7OICiVIqVR2o4l4QUUSEUOAkAuemVsydiQgItHqezJK6dVdPOR3GoZRCiJFD37YIWI3PgLmAD2WaStGc3Z2d1WzIkwOMeTjfO4mxVQc0A4QQKARsAgghubE7I0aiGJEJ/KRaTTP7xt0NEI1iBiwlq8/uaky1QeMOptVhowopC5hRKZHQx70RDJrfx74PMSKQZbWinmsPP485D8kthm6z7ter5WZ9dd0zcBvadT9cr7tn1/3zr24W3RwnN23z4ssvfrI/bLpeHKdhGscpjcm0TtcY2rZpm66NV1eLl1+sm2gPDx9u3394++rd3e3ucBjAqV/0oYmEOE3DvabRABmISBrum3jV3yBRyRkcWThIjLFBxJKKqlqxtm0vrjbry4vFxaZf9G0T0mF4/+0Pb1+9ef/mzeG4M0950nREIY6A6pQLaCnjmFJ1N/3Dxh8ymR8HDn9s4vCHTPvf+UqfE5yPH8eEXRuXfdP33IXK6oOAwIyMCIgMCFbYM7sKuoMwYnJKAOgKUKKUVXR02k0oI00koKIUrMK/AdxRgbyG4YhM884/dwqAqE712QF7Rhoj1clPADM4vVKHq/QrE6g6kzZBzqEDIjXctdIHbqLEyBKQA1BgDiESnjSUqt2vVJEXRUcGYpJAEQxFs6oCkpolzSS8aJdNIw0BuJZScsnZs4ELMzp5UTRkqb1mwipjzGkyUEjgbiQFBQEyqAEwCYATKWNVjHChQGYFgSU8vjVSnCpsl5hCoBiQ2QmBjQQhMDVCsSHhE6CZGJER0RyqHcVkkg3ANBM4OpHPy8dJem22DEGvUDp0Bvc8+tGnkjQOuekXzNGymhZPuUxpGKfDMD0cskpYHuFCpevXXd9eXF42sV10+2Unq443T7o2zjcmNM3N589fDIdo6FMhHohDkATmxGEGjXex7+PNzeLF881qJdPY31+vll3ztv9we7vNybq+CyEg4CBYpokqQkBIutC0TdOvmEVLAlN3IKRQhb0l1IesaeJq0fUxtESdhPViWWJbhkkdQtseh33SAUhjg00jbRtDDEJSqMTGQ2z//gKe/xkORIyBmigxcAgo7Fxj7bmg4wROZAJZPIu7uppXlXtUz46HnsplE5iEmSaQWIJAQOKT1xm4Iz+a/PT7J389Ip1VGBERvJr+zG3tWtypIe7ssiCPjJQQMVBoa7ArjQhH5IgcmKUKBpoToYhUO2g012KoyCBo6MnLpHpwV+QQAB0zAJMDk4XQMrGBTwagCIjOLOQIwnXyYw2lCZGQIUhoDNBMHamCkIxolsQFR0Ch2TKDiRzMoRrYPoL37oeMiMQYERzIHVSd0BBJGGOkJkrTcBQWIQSqLgBqVYWQs3rKVtnIDbtDEcK+kbbhEIQZi3pST1ndDNCJoGE28MrNLGMpk3khCVViVHVKaRgPh/HhkG73OWM6TKguy34RQmhX69AthAXdcBoW0eVU95EmXH12c7G/H94/jMcxazb3Sr0IIiE2bRu7RVz0cbkMLNZEulheLZvOMqAJYzwOSZiJqQqe5OVSYqNMHCQuAjJbITWMoUVwK1pUj0OCStaMTdu20jTqfDzmMT0c9tNhNzjzQSFeXX/52efMWMpkntwygFbHA0JUzd3qYnP1VE7VPvg0dP9D9u3Hr/mo4ffpT3/f+/z23v74O7/9W39HLPC7MxSc2TDV+3yWr5utUcyhCGamLDBhKaDkYMRNF9ltynrfuC5pSdJOFkXYUQqIz2xz+9HnncEpH2tqlYkCeFoOkGaS7RmuMuN+5xqgz4mMf3QSnAcBBqSWpQttkAgEghQ4CM1Vcg6zkx1XLJzWSUfsopMeHw7Ddpq2EzovVkLCULi4HR5GW6jcdKEjUwJnJEB2JGIkJmBEYlbwXEoFMBp6iAwctJCaZSuIQJHcfJwmVxNmYWakCsRVTylvc94/1vCUw6gs2BLP9jGGRM5UsbyETI6YDUBBAau3wlxJdAIkdR9zKUUFTMUBsA2WiqnCXBV3YzOcMyonQGIohkW9qCmYGzBN3gA6mVmeyjTpOOpx0MOgiiCNl+yaDQxC08YWsagOw4geTfH0IDJj28d2EaZ7cNCKlmCWMOMrQ4zVXVFTmh62GXzyxTInAxAJbduvnDISArhVmZ3YCjISYmAgdsBSjN2RYyAEYfQ8lbEUY0amKByCRCbSovv9wf2w2x24aYx5sV5fPvtssehKntJ0GA77NB21TOBKjCQBJLTdgv5Im+55Xv3OCVrnwH8eII6TBWPtj8yHVAUSwMHBhDQKNu6uGYsVM4LcuCBMBfY9+YIjiFBmAFPAcjLM+BPHzDudO0t+hmT91utOf+bBzMu2v+zXXdMTcrICUO3l0OHsZEdcbaoMAYicwDl4LFokuxQyY3SiHAOEQD0AuHkoCGNQADUyJopIXEU7gQ0J3NHVNFnKWioBhRmROCOAWs5Vy79qkCq6M4ogGbo5qDuTM9fI4NHOPyaLQE1LQOhmSBiI2sAxMhGqwyGZDmZQCJmJhCAQREImr8a52TxlTVa0YCDOBUqGUlwVCMGqlLXXwgtWVUs8cX3UIScrUyZAQq7cTzVUI3V2MArNYrlYLhZNCIJMQMTUtG2QoKnkY/qoRuoGecQyBtTAPlUpYZ4dRTmQe5mmKSc7HvXDfWkjrdrelLbbcZhKxkBdRGZ1y2lKxRJxhjJbgE0OjqDQMDsCxxhCEMcJJzUznZxFzFsmacIw2mF/GIYUgsSuD8t1012w9LFZElAax+GYDtv9NB0QtO1iiIT0CQ7xD32Ea3BJH0tupy5VNWX9xGTuj3zzP3Gc0/5PDnTu/JFXaFpFvDmUKnjmhoKLJvak6uOoWbW4jp0KYwGeukB9KInUSkqZs7k50KkzDeeu8inKr59ZLwc9WhjtI2Dw1AJEOKG3T0f6SGsGEeYF65SOBQlPNpfT9DRwo0W3wzFrcgc7S4sBzDLWCKiEFgVbpigagTH2q5UUW1v1dQkhrlbLGBoAL5CzT9MwFEsaUVrmgByc0UnVVFPRMadjnrIWRAzMbWwECQTBsZCqWVE3NYIqXMEMVLQoIBNjDO5937X8SP9G1OfYxAwUvDgU9Ak8u6nDlH3KnnNVpSAhjExNwEWkNopESgZTtlSczBlBDc1RHdUgKTi4FjO1M3jXHWrqUfm4VlV+VC1nr9K+xcygZk4YkGIjsSGSkmw8TsB7aYTdJErTxtgEPIkTCNHFonlxtZqId7G5a/bHQ9aaDHkxNffkllWzWlacGKHliCilsJNQiBQjBAYzU1Pi6g0OM/TSGTEEiYSYJwLrhYARo4zmKZdgWfJEWSQyuqaUjsejMKmCc28ZAARQHKgUn8ZpfzgOhz1ASakJDTH5OAz2qbjq7xu1feXuWtKY8zRVtmtWNUSsRPe2bWJsiPg0FX9ch/tPOc59fYDZ+QQBDLDU/zVQdVATsMjOQas/PSUgUPJRXExHNdQSTJG8IxD8dE/+Oz9+hgw8GlQjED8lDo9R4VB7BoCnm/FxthBiF5tl2wk3JZeUi7tXB8x6OISzZAE4owWxRmARqGUPFLhbOgKgwDiND3f3iNR2fZQ4HIc06ZBzcjVhEgooguCQ3YsDGJhBUcjZcraCgAAejJAY3BAVZhMARARhFqhoEqoVBScAt6htkOZxXUkoADCoWcmVqg+5mLkmgzH7fvIpe2VSoiMjCmETadXJahE2KyCiw+Su2DAjISADMjIZYipeiudUECwwCsDJ7VvNnRwDYXGgmbdnAFr3KwDjKMEluKNEB0qTbh+OKeXwsOsWcbVqQ8Crp5dhdXVWm+5i/OlnzxY9l2Pa3h/fvr1/9+7+9v3DdrtL0y5ZIlaAknPJJWfLbs6GzIGlk6aPxOLGKBWoBAiOimTMVXMRGwl903HJ6e49lmMn1sf2ahFTlP0wJFOadkZqjJ7VwZxmYwZQt+ylWE5auRtTStM0DeNkOo3TSGTgendz91g04rfHuQpAiMKkOR/3u/cf3n/73fdvP9xu9/spZUJaLlfPnz9/+dnnX3z5+WIR1VzLyRrEDH5fhvCHjb+7C/A744tTalLbQ9VNrjo+YgFUBzScku53xyYc16HE6GBlmNI0pKxF2NCZBTIlLZ0AdtgMiArBnM9Am3NJDmbw2emz4dztB4CTVcyjKOvUBagVBDzJVyIi0AzAP79dpSdrVhUGEgmhKe6m2UCR/JTeMFpAi1wasa7BPlCDLoElSpDI3ND2uHs47FJKk+Xjfvzhh1f73d6Jmi4uL/oWmxYDuo7jvkBhckBAAQISIwM2RwNIJVU1UzUDV0ZkRnA28CqaDYgSIiAoghYHjO6fiBFX/Vh0R1UAg+xuZmOxY/Yh+1jQZgtw0GJYqYjZhoJHwwQsjMOo5G4NNELV6Mscsrq7oZtlrV69ANUs2KpEAdUSbMXgmNnMpqjrKCATCQJDdtoPlnW83w4IbqBNF65vFsuOW4Tm0c5PhH0MyzZMxUobVstuHKbhcDweYThMOR+ZDdBK0VRKSsnUCCgIRIgopqpUjIIDAAEIYxAiktjE2IQYmq5p+qa3w+F+eyvj2OXxInDfttrIHZaHsRzylAGhbdSRBEMrQhKaEGMlOAfhKkx+UrTQqqFQhV3S4TDoH7Dzu3mxomM57h7evX31m9/85t/9h59/++rt/f4wpUyIq9X65cvPH362JeYXL55JmGmnj4LfHyfLZ7rLnzz+o2lF3WbVDBGq3bOBZwc1IMdU7JiGXo7LhUbKbCN5ompf7J6L7w/7jNlU2aiBtoE4Atuf6nByPn88ZQ5wIqc9+slc8X/8bTMbSzqmEUmo+nKHqAToRKF6QxMqWxEv0UuDHoEZiAnqawMHdqqC5KBu45TGYbrf7R7uH8yg73sJsesWODVgpWRWIuqEAhAas4UQzCkXN7diNWSfGx6zRy2IzWeFgMTMDlCsivn/2Aa+cgoREc3R1Iv5mPSYbJ+sOIUYmy70fSCHcUxacr1wk4ENXrAwQJqKkGelwHQBCAjZKjrCyZ3BkN2dDKqoi05jcbcgjESujsYuZA4pu3pVu6xmllDU9invJ1eFnKbhmB52RyK4uuw+e9r99PPu62W6NK9gRS1lu92+fv36/t12v5+mDMcxGSCymGMpXtQADZHdrRQD9ybKrGOD6FWxPSsSMkIjDF0DGNq+WS4Xm9VF13aB43B7m9+9xXFqSl6VdB06YInWgMHxkKacShpzkNDJoiEhaZp2uVysNov1atH1relhiCJCQiiMpgiO6qbFtfjZge53Zs4OFbRpaTgebj+8ffXtr3/587/95uf/5m+++e7th0MqWY0Aurb/9a++ffvmXSk6/NO/evbs6Wq1rKZjs5Dz7929/+Oz//f97m+DfD6WG+a6uhcDhJN0N6ICJHA1EMBsMIzTEY8TFKdpTKM5tE3vSApaSpoOx+SjsrOHCDliSXPKeNqq5/b8J4n/vJzNIRNVNDqeUv7Hpz0XAfyU7ZPPOnMI+NGnE9T9kIeHcZ/NorRCMYSIwk7K0d1AE/gU9BgwBdJQkIAKCFJsZtXfcdqNh91hp8XA8HAYxikBsRE+PGyPwxRDG7kVjBhpSgiNNE3DVBycyZvAjlosa8laack+S9wIcuSGSUq10KtwJ2ZTzaXkXCqw6fGpS8Va1FCXGMGInVDBwKvkv3AV/YRitVTvQWLsVm3bdS3naTyOt9OQEKRvfCgwFOfJVJ2QAnojta/jZuBqOemUqpgjErmrmztlQqJSfNbnIzar1vY2ZU/qw6SHw7DfTw+7SUv57u3h3W1Tyqq9OnyW592ylHJ/9+GH775/+/37wz45t2Y8JTcj5ChxQYwA7qaqg+nRSlEKSgpeVBOScdagToIICqrkBqBohcG6yIsuMgm2zXqxYLPLPt5sVs+f3nCI/X6Uh32621LRHMUIQyBxbIL0fbO66DfrftE1IcrAxAQEhqAExhUaCuRCFTj1O2eaz/DOmUowjcOH929/+PbXv/rFz3/9i2++//67t3fbobg6MOJe9tvtDhGf3DxZrZer1XK5XJzeEdxh1mB/tP//sTu/PeYdfDr56/iRZZA6FIdsJ/I0ICKqw+QVmUvBKmykjMNgNGZVJ5LggKAG2SznVAxMAuKCwZjmHt8nM3gOL+icCHxsLfyd43Hj4NHrT7BbePwtT5ZHnUgJCKHK5GBVDoGSbRhyegDfh6hAQYIENTea0XEsPB6G9+/e3d7f55QRqev6GJubJ09YwnBMmjUnGw8lhAzi+zFTp7GLROAoSMYEgSlwLZsa+mwGi4SRY+SKq3VFM5id4fDEQpnh1I+GMAGjC0EUbCMjY1buBsVtOY5Grp5TGQ0JS1EHZ7TNavH5T//i6ZObdS+379/9t/vh/f6YWI6jPwzKQtltEaAVxEgtUpWOKMUtlzTplLTG1sTgaqTunpnJkJzQnW3W7phpzEUhFZ2KOVG/Xg5Dvn3YD2kPnpc39/9sKhcAAJBT+vDmzfe/+uX3v3572GcOCwoLlA5QpFm1i8uu7cBt2O80v7dyl8bkxUYuzAUpADIHiV2SwMzuNubx4JaGA2iaGmayEiWyp8vNYnGxevnk6WdPn7149jTEcLndLj/chjdvX+/3dwYP05RLcrOeYdOGq83icrNoI0PVnijJdXJNYJnJYhAMEkLoOnk8/c/Y3sdPXlW/LDnd3314+/bN+/fvHnY7BZcQAroABmYiVC2H4+H97bu7+9ui5aPJotWyX52BHyfw/P5/wET50Q7/29//7ZjF3Yt5Ukd09frZBIjFIRtWK60GKMTAylMai48aGgDOaVKHQc0sIxojaslOxYUcxZzca3PN4SM2Bxxttp0CqASgmZh1IsN/ckUBKrLncdSDWDH+p50f7RGHqParzdkVNekkUEL1V3Yuo96/3e/fAwy2kNBdrzFGRCOOTdN1XRsCbXe7N2/efv/qh5zzcrn+6suvn9zcrNebh+3OFR7utyE2RW13GArk3bCTwUMQK4SRvGGPRoRNIyJgGdEhSGRkQhJkRgZAZlDUai6MDkLUxUigPiT2T5ZMoZnd4EweAsRACoSEY4ZZUyjZ5IqMZl6pPU3TPnv29OWLZz0lO24JIRdNxcZk26NWYRwCjDLb91Qmn7trsaKuCg6oMw4D3X3KSmZVKWh+/s3QXdACQSYnRgoiJA0HIL7fDmPK99u03U2lzCBWLXrc7h7e396//7A/ZIkldhAXIbRtbPu265fLFVgB4JyOXdtBmUxdrYgXERJGQY9gAoDmRUuVjnMFLyUKLHpZdS13MpWpw7C+ul7dPFs9/6xrYrt+oLbJ5HgfOBU4kOkE7lcX64vLi9VmseybGERNEYzQY+BFFwJ37h5FHGxK0LThR3v/450fZx0Qdy05jfvdw253fxwOqWRHJBYGB8AojAQlu7vmPJWSEYGZZ3ALzUoS7n42OIVTDfAPh/TO64R/7JFVWNHvnvwAxSApYLWMqK316lFngOYIBgwxhqiik5oXih1LEEKAGRjSCbnTMUkCiSLizNXSZc7bP57Kx17f33UCPx6nutHc4fP5wH8HlMDRauAN7mBpFp3DgMA++rjV3Z3ZMVmbrpbeRkCwGCHEJsTGrQzD8Pbt29evX1N1C2qa1Wq1WCxK1r7v01SargOk/fGYNRUzM797uz8eqF17s6Emhhg9hqJqxoqGQSKjEFZ+goE7zpWK2VIXoSriirE0JI/PSGDuwJ3U1Q2YKTJ1gSbBYbCctRRmcvr/0fafy5EtW3oguIS7bxECItVRVxerORwbs+mxef9XGLLHmm3FJqtuXXFUZkJFbOHuS8wP3wEgz73FZo9Zh8FOInGQQETsvdyXf+sTaESsnADjMIx9oHp/P3/+WNdFVKtKrnyeMZBHCmMXQwwpcnPIbepC0TYLJOStYQFENy9i6B7ZAjAQEqKrBfB9cAeiQM5kIVWFSBDQ61XnArveQ/jCPsWKalYTM3EPDkBMKcZdNxz73b7f7cGKyGK6R7ieIpxPCxoc+7jvu7Hv+q6LXQSCqnUpfJaQyTDw9WH31YfbX//qq7c3Vz6tP0u2c0VVq+LmxNR13W4/XO2H1YtXwYSRPKT41TcfdodbwF2KIQYGdUQPgY9Xu6FzcG1ORrnkaca+S69tfL4oIb9Um6nUnPO8rOdSVkcg5oseDBCQCZkpMI5DGoY28IsxBry4929Io/rfsgC/uMX/B/j8/9aZ//n5Xz6Hy84PSuBNv+2gBmpAoBErsXZdSBIqASiEwP0w9n1niJwLoV+PAYAeZ/O6my1OArNoy/EBJ0cwR4RmJ43e2t1Xrw5fPV4V/N8j9Wy7fRumYrOmf/UN7uji1QuQowkkjqEbgqKHBJk9B1l1PRtKPc85BEbXFAKHwEzneXl4ePj06dPj48PxeN133fF4TKl7eLj/9PEulxxCGIZR1KbH+6r1eL0305//+glYbj6Mb+hwdbsfxiCQTc2joxNjAMcW/GemDtY2GCCzJpc2J/MIxKnbxZ5fj/q42Rw5qJoIMGJETIT7RNpzLbpsFxYalO8IeS0Pd3csS/30/f3nOzTtI8eWTrI59gEhBWZmcrEqJs0hS10BgAiYMDJHJkBVLVrcHA0aP4GIwDw5jImM0ASrYzEEAHJLia9ujqqFaDV8zgwFQupSd7U/yDu7OhqnA3fH0O9DP8Rh6Pth6HtEYhjHeHyzl3mkz3QHRd7tutt9fzX0QxdjIEfPhqvS+dBlMGW6/XDzu2/ffvf17fVhvyDcuZ6neYKHcxqXN7cxMqghYkrhuB9T5IMeTrf72HUfvvnAcffwBAYYCIl4P/aghzFVyclUTERUc4ldwsN+ZP7iHG7PRsvujc9tZrWUdZ3m+WlezqUWMdVtE2/0WQhMQARo03z++ecf/+Vf/nld177vU0pd14UQ2295juj5u6X+f4je/6LgN3dMf9n/X76t7fwGaMBtjQa/5HR4Ig3R+0S7Ie6tL3UEpbQb+91u2O2dEJYVwYaBEdDIpQ6LxDnTqeJqmwj3cmwneJny/Z8jNf1bogr8O5u/u7upuJEpAKbIQ8+HhIOhjcF7zgWgFHk8ndxrZByHBAjutizzMk+1FiI6Ho/H4xER52W+v7s/n54iMyZc8nKels/398T45u2NKU/ndcmzmFIK17eHcQwpAgVvxF8CNgWtYmqGjbUjABQpXtZ6cxGngCGMqX8NxwSmzXdXFEoxcmSkSHDsMCF3nM6rLsWrtDUCHeD0cP+//X//lyEFKouU3Mfw7moE98g4Jhg7GhJ3kRjZHcxQ1aUauDEBkXtATiF0XepCYKpV1mJatZk0EIUQiAGRDJmsYFaPpqFIyVoULXX9u7fqlp8+zh7sgpDHGG5vr3/3u+9+86vvzEgxVYtrDdWDIscEQ4QUA6QxXl33GNd7+tEXnPI3V8P7/XAzdruIAQwIPfQa+9qPJYQJvb/ZffubD1fHPZmvy3L+fP/px7tznK3C7ngAMEDPpSj4sOvfvb+lMYkUjuFwdZxXlDzN2QktpfD+3e31gddzmE+P8/mc12zB+siHXXx7c4iv8nouJeS/uO9E8rJM5/Pj0+l+ms7LuhYRNXffBKpEgIzruvzpX//l6enhz3/+8/v379+8effu3fsPHz68ub29ur4ahuECxMgvXAP+RxaC18eE1+Df83P+BZRQt50fuRE7oSH17qod+a4LVyMednhNB49v0Qp1Yxx2/XhQQOeuCSIQYeg7S0PRuHC4K3RWVGADugQ2bvSMxuF/nu0/b/x/91X8nd4HL+p5eNYjXL6nLTYtr4I4Iu+6w+3+62N3HTTFXKerXuezlmVZ6+f7z8sarvbj1XEQKcq2LpNIHochdOk3v/n1mzdvTufzw+PTfD6b2vVxf5qWf/nTX376+Pl0Pl/fXDFhCgmJl7XmHx/EdbfvmWh/xWkMMaRAAZFdoIIYtmgEVa9EzhyIyM1VpZRsWhF16IYthu9S/GAKYC4tLtcxsVHiMWEfQ594P/g5W6lghqZtZlgfP/98AkwEXaD9kIiimQaEoQ/7kfc99QHRXRVUXQSKOLrHAExAjBiII3MXYwzADKGYuuMl4hMRiAIixeCM1a2KLiQruDkaEqcEKkU8l83IHQC6Ln37zdfDQJEjAlentcI821K9KmOIXTfEYOwUlJPypJMPbMWvSQ5exiqDeUKPMXQd80B06GvXzei46w6ueDqdn+a7P/9w9+PHu0+P+9F2x6u85lIFAyoSxNQN4er2anc9Ehozha67eyiJ5wUMwWLgXT9qpzMsVFdZJm17cEoxdVeHMbw6kV3CLb7gnbo3vngLMoOqtdQqImrQ4oDB3U0dYVnn03T+fHf3w/c/XF1d3d6+e//+w9fffP3Vh6+++uqrt2/fHI/HYRjau/0aXPz/s/gvO38r/tcLigGIQTVg2wyjWvG3YOjAuB/i1d4POzpEC8MbBMHQYUgQOlCI0QCc3ANTSrvkO6nhyamNis1YL6D+xVrHNxen/3On/v/Rh6ujYaAQMTHGiJ2s4TxZnU7Lqcoi6OZecplPeaky3F7v+zEh2bycf/75h4eHu/1+TMP44cOHcdyfTlPOGdxTCn2fns5PP3/88a8//GQOXR9zXruuCzGEmFRVM+nCvjAOgRK3QmFEZOSYgA0czbQqI2GXOg4MAFplxUUkI9QYutdhsGETMjeOnQEDiJI7xUCRadfTleGqXpXUsCqUbLnoWqqbJfKxp6td6FIAdGZMCcdEh446cpVaFLQR+gAdSVtmIUPL5cPA3CVBhBTADENAZgVsgkti6lPinjy4oE6KC2gRMKA6z3ld89NJluVZAz/0/T/8/nelvgtE6KQOVaBWK2oi7e5gMPG61BNPn1YT76su6zpr1Ue4M+nJ9yke9+PNUUexINb3iWPQHMr0dFryX3+4++Mff/zhTz+s2YbhSDFwirHrILJ7IHQeuPGRu4RM6OCI7qgA5OCIEAhp03xUlwJaiDiFuBvjOPzizG9mulHUW+CyOjh0XXfYHW6ub4/Hq4+fH1StShXBEAnA1cyrm4qq5Sqm9vDw8NPHj1368zjujofj27fvvv32m9/97nf/+I//+O23315dXaWUGiL7t7DfVr2beuLl63TBidofX/y3pbOEL8/8DtUgbBBvyzx1BGCiFPm4664PeNjTPmF0DmjEqRqcVym16JZpNwxdOuyPBfoy8a5ADATE6iyGiH7p+I1t0/l5O6P+vdN+e/w9vMMBNmv/C8/vCws7d3c1VEgx9WFgjL7Sjx/vTx9//Pz9p7rKOB6qwel0Ok3zOq/98P7Nu5sPX72LKXy6++m//td/+vz587tvvn7/4eur4xGATY2Irq4OkanWdZpPn+4/3j1+Hsddqfn+/m7cj7EPN29uwPjm+ng9vhvDLpp6kSJZA6SUIqc+JaYOHEWUMgFiCn2MkQgrCRhWQGsAwWs9/7OWEQHcXNVETNXAORCGQIA0GBiwAqlhKZ6LzgupSEDtEx0G7jpGAmaMEYeAXQBCM2npbOCwmYwRAQUMATgER3JAJ0Tm0EVzIGZgttZmBeJIsY8BGQgMtQBh0phtrW6agy1IdWTjy2sJIdxcXQEMoU1+AMzBFNSbT5+pu9aqC9/nx7un8/3Pd0/3p+n+9AQezCLYGOhm15sBA5lKWmYKQZgLwOz26TT/8fv7v/x4f/fpgVLvzNx3se/iMFIXmVy7LnTUDYeUui4SoYsJQXk2e2PCFJkowth7HmQZIyMAcuKU+LVufCs60w2C2npYQ3dm7rp+tzvudoe+G2I4M1VEb0WqpuauCKJ+MaRWs9ndmULq0g8//fjjjz98+vTx6enp4eHht7/9zZs3b7suEdGWrfJvFv9LecCrVeLS8Nul9ttM8YujhPn2sU1yAAyobdGEGBm7SF0X+x57TpGROeai1Wdxb4T5se92Q7/b7bPSWHJHJYKxB/KATs+VjWAXrj79X7HzIyBBCJgipcRdpH6p/umH+x/+5e6HP//gau8/vKcQHh8e55wJeEh8fdwdd517nefzw+PDtMzfprTbjcxk6i2gO3XJVe6fHn/+9Onh6WGaz8Q8zdPHz59u7DoNw25/CJBurq5vr97uuw5s8rpiUgATkdZDQQCmSMTMEWDz/yKngBw5OtdSyy+ubXB3dGhpR25qBs0eM1ULTEQeyBNSc/NDYhhJ1PMapIprYYI+AbIbAhMmwkCA4GbmulU9NUs3xhQgBubIHMiMqnpUR8Su6wj5YsLCHikE4hQoBkQaGThy6uPVrA/nuixZi1aSjPzVVUzhGe1vt6AZNUk2IlCzIAlk5uZgglIE1mX54x///F/+6V8+f/9xOk0utWe62vVv9n00TKK4TEtZCNzMcpGlyKT6ea5/eVw/ncp5Xsc0YJ/ibkzjrt/v0zhaoCSVI+7HcQzM4GgCXoOXgMwEjBSaXLKHXdRDF/Zdd56mNZeq1UGad+Fzjbmbuz6TVwAAFVqKGlCMcej7w253POzmc3Hxou5iAu4IboDmwCESh+YFqNJEBno+n/KyPDzc//Wvf/3Xf/3j//w//7/+/b//97/+9Xf7/aGU4q6bm42/3u62Py9fsBck8hfFb+4ObvCSxnD5p76loW3rsm9iXjR1lWJKhBS7ruu4Cxw4xKrOIaWuSGXmw37Xd10I7HOJeI6ypupdDeIdQjQPcJntw8W61c02hgu8oha96m78lWPC/+CDkLo4dGkM2AVPCfu5LncfH3764ee7z/eI2O8GIrz//BEAv3r31fvr3aFj9prXteQ1pq4fFIBrlWVZiDBFAkDV+vj09N/+9S///KfvT+elVJnn5ZEfIxMS/frq+ubmJnJ3c33z5vZdP/I8q5l1XcJQc1lzWSZbYkhjvwucgBAMqlQVCcQAzuCEIFJLLa/X5fBsesAIhoQAql6q5awBkQEoeEC4OAoQsbthjywRpBqABwbfQHdzcxV03ESNTMibq0AIgWKEGDmmiESG7o5SG+mQAnOb/TiYE3IkaKsiYSQITClBH7Ejy4GsQIk4cziOzK9n406wuS88Bz8Qtmx0cAd1EnTMa/388f6nn+4eH+d5XlXqLoU09Bk4A06iNssChqa11HUuSy6L6H3Wu8keV8uqUSyLrVWXUnOVAMix61MfEvepi0QICqABauSaQh+DBeZAIcU4diH2bEN/HMZlWZZclrzkOu/HPb/S878a9l2O/QANgWKOw7jf7Q99N6TY/FKrintbyBFbJMRz72rU1B/m7rWWvCzzPD08PMzzjIjuGiN/8w1s/pPbxP6LXvfV/e8Ahv7fK34z+MXO/3cfvsEBVovUimrJoW1UgTgkjHukrutUjZmHcSQOqmK+Wp25nvaq184Rdxn6DJ1AMAiwjaT+r3oQUR/7Me07Son6iAk117Vs0A/SshREWOe8G8Z3N9fvb69TgJqX6Xxac+76wZAQMecMAIhYSgZAUb1/fPzp093H+4c1VxFd15WJUoqH5UpVqaUZRe77PgbK2aV4t+/U8f7hdDqdas593314i4c9Bw5I4LZtJpcLia8+tkdwx7YOIwJtsdkg1VaoZBYsUMcUPRihOYo1O0E2AAdHNNwMi9uJMwu0l8XIKVDPzDHEFJgjB+YAnDj1CZnU3U0bkUHVTE0vFLQgjM/WLwiMCAxEgB2QgjKhxmVOny2nV70yAiIwQHwOe2kLexuDA7g7u6pUrhnyKiWLNO9jIowhdB130RCzqJTKbuSgYkvVqq7u4lAcs4GY51IfH+aff364fvORu+EWcSSK/RCoZ0pEhN5cF7uYrO+nXmsMMYQQQuoTD2GIePDDrZuqeS7rtDylMHbxJUrJDFsZvpQZACA4Y4jxeHU8Ho8xhs2NYhO2XzycgczBTH3bZDfTxQbOhRDAodb68ePH//Sf/tO6LsxsZl999WEYxob/I36xDMHLErA9i18U/2XU5946/Jd+4fmnPPN7/Hk+ZwYitq7rusBabK3ejGLNKTKPw4BMDADITlxFl1LWvObpCZeHayvOcaZ6gt2T6ex9BlQkR0IksJbd1JZPfOYvt2L4t3f7/4MxISH3sd93u4569ohK5NSlbuiHfsgqJtXdgbE/7q+/+fqb9+/egdvT+fT48LTkPIw7jp0DLEtuubjn6eQOw7h7eDyfpzkXUXMzyzkzs5iL6HSen9JTSmnoenVBocenqdgahz4b/umPy88/383z6eo4BNzFOO6H2Oy/CIAJwUzUwTHyEMPwBeD38sIusof2+k1BqlbGgMAIBk7gTugvxb6xJKwl3wGoNh0WAWEMxDE4RwqRE4dL8VNoniDoZuYgxUylKX1buyhmbkZIYAaqkBi3ODxmwuBkRFbJCsBz6PfLpWP/Aub1y6S2IVTgHsDYjVq+dxuONeMmBajui6ihoQi5I4CJZQFVAMdimMWymJjhWh4fHj/99NNxP6aAHJBjjKlnCoSBgAAIyR2AuQ+cAgMREwWiyBxTpJ6dt0pH1dyfO4AQeLscqjrPS85LG8tf3CWgOVoCQAuAa0nvW0FuD78IWC9mVBvc0NLR9DmKrI2df/jheyI8HA6IyEzv33+FSAAvFAD4+8Vvz5+3L78qfv/bnd9fr2Fffl3M12JztrXQWpAQyR3NMMUYuhQ4MDlQVi9Sl2VZ5qms56DnN0kHlgX50TCJP6o/GaxAFaIDET5b1mwqRtvukF+Sef/u49/63wTUcTfwMISBgK16n9LhMOyPw2k6T1NelsUMqqiq1VpO5/NaJtV6Ps3naV5LqVVzrQBITCIyzxMAjrv16bSczlPOeSPEmalqKXWapru7O1Xpu67r0rIsKcV5Wad1UsQsfvfZHx/DdHJQPZ9ryYYjxRDNENp+KlKlqnrgLoYv5/xtGd8sSBoc3bJPEQBQ1KogI5C5u3JoyblkDtaMWbYoP1MDURAjRyRmDozc7DESBqZIgYmZGEDFFQxMTatVMzUFcbCNluUuojYtklk61i7CGGlIsQ+MIaAXl6W0lluGYvoCRyHARla+3JkvO+J28RAb/hBDiiFGzoJoAKI6rTkwaqKOgKzZHzQ/HDRjMJyrLVnXKu5m6/p49ymSj1Q7zENPu7E/HK8CEQPhduhosDG5oVmDoAghIARwbqWy1aEKeHott6xV7u4+L8tydXXs+4GoRXuAGYBKznld87quJecq1c3aNBpguxiN7LaR6N0doMWpuJs1yRcCEQOgiHz69Ok//sf/uK5r33chpNvbNzHGUuqzvvhv2v7nN/flTNJq/nlKcZn5bd/VKD2XDb/1aOaA4KCGSw1TkaVIzhZMWStqAE9MCtApszmsVafz/PR4P50etMwd192OFWEBPcjaZ0tFsZgZVkgCgdG5nXWbf62jIxoAgRsAubdr9FzpdrmDtqvmL0yBLxl+GCH0FIfQMUVnLwe5fbt/eHj8fO+Pp2VZJ6lmCp/v4b/8t//97uFj6hgBRbTkuq51LaXUam4cGAFMjTmcl3WalvPpVNbFTAkJAyPSsix39/emejo9DcMQYvz10+Nut6tSHx/P3//0WSCGeL0betCUotWCtQhTSDGJoJiWkmvJtSpg6NLwSzOPlzX8kl/ABG3gzo2ZD65u2ogN4O7gYGpgDupk6rZh6ahO1qjEjWIa2JkVWIDIkR25kTHUATcr0W2HuZifuYO5mYCpVjUwRTUCZ8KYAkcORMrULqThL5ZoBxCA+uVXcVuy25hG1pynkhdVQYDAFJiqQhWb14IIVbhjYgDeVhB0I1VQ0al6VtPtyWtepvmJps88XfX54VamN5DfoxaIryXT7mCiVbUE12fkrjWifimF5jf2ip0GIvL09DRNU0ophBhCaE0NuotZswma5zmXLCLbtQOwjfDkl+u5/eWZ7vKKCf3S+S7L8v3334cQ3r59G0I085ubW7/EXz4X/7ZUXX7Cy9e3n/gsF3bdGApfXBh7oeJtb0EzzxGnWcK5wFJqrQqIyG3ZhVrR3AhZxOZczudpPj/WPDFaN8TD0FOI2cKhYD8XnsGci6TVtYAZAjejqC+fhm8m3f89XGBj9f09qyACjBw7TpFj4Ajs+33/7sNhWa/WchM6zKvmrLUYuf/08ce7h48hhMCMwKpWq+Ra25icAjcvbmYmpmXJ52mqtYL7lgcFUGs5n01qOU/d2A8hpXd/+tPhsP/48dPPnz5/unsUj4crIwrT+STFHh94edOjY+RoKu5epRapas7cTLe/cEAITebvuM0L2vGRiAJjZIwMTADszn5JodqYp+Im6qIu1cwBEJ0ZiEIKXRdTHyiSORRVz24CHgiYIGBzAXakjUJNyBSAoIl6iEzRVDdJQClC6ASOiN5H5uDILUaj70LfvRbCKuAMsHgz4tkOpu2IR2ZuKmt+fHz46f7hx3l5VMvMyIE9Q606rUXM18KJKRIG5sCBkNCwqi+rnrKKb/QxREA3tIqyYplgebT5wZZ7K6MmJO4vB0wTK0WmUnO0AX1AFwSGTZDq20R624Fe7jQzm6bpdDofj1fDMCIyb/ILc9u6wWmacl7VtDX9KmpuzS/yeez+vBC0skTYmmF3V1UiYg6IUKtczv9ZRH/7299fX1+n1MnFAui51J/rA1+K/+W030B+NVN9dWqADYjdPrYNBcjdEdVpkTRVXEVFLRB2GxEeREuVqoalyLwsy3wuywm17oZuTLub60NKXVU/LqV7mBFr9bLmcqpldYYm9b+8A9u8+RV0+gyDOeALlerVjB+brSJennQrfsQUYoqJiYiAkHeH7gMeYm/Hm/R0WlVomerT4/Txp89//dNff/p4cidEChQBsM1dFRwcHCkwxxDcoXn156rujkQEToTupuqrSc7rPIep6w0AiXa7YZrOp/P08HTKFen7O1VblvvbmzR0v/rwtgOzQLya1yqiarAtNID2nEC3FX+pSoBEDm3DB7Dn94CgpSfj1gJs+5UZqEHz5JZG0nZ0IgAKHCgQMQKCqAK4mwIzBWSn6OTEsPkqbFIzV/Ttd7UIdiUwRBCBxkouoASViMA9JXR3ZOYGctMrlAJMdHI7AW2d/8V9kQnYzKWWZXq4+/zj/eefl3kS0XY9gcAdxRzEHFANhCk5GAADgHkWnaotao4bXoGEBOCqUnKZz/l0n58+refbYRmxYycDwEZHrLZgkJCUqYAvKlhKZSBjbAUBiLXWIjNRelbaubuIlFJKqbUKUVPmgJupyLIsDw8Pj4+PpZTnGmsBz839cNui/2bbazc90QYl4maq622t+dOf/qRqIYSc6+9+97ubm9vnyK2Xn/KMoPlzR7BN+AGgEQVUTP4O2v/3ztGIBpjNZ8Gp+FrBvM2FAxGqqajW6jmXWlaTgqApYBe6w9gfj4eu680tdYtpraaLwwz6aKUICzD4psrxC0K5Ffa/9WRenhQQbUtFO0a+fjQEmhi5lQbznjpOV/urQSoApLzq0/35X//4/bJMT6fp8eFcigRKm5kKADRXb8A2A3P3WoqatZxyfzVouWAopmZi5p+hqPRdUtVa6ryupbjYfa1S5Rz5yvXryCFQCMTcxuuBbfPrcAAF+MIqKsyrEEEi9EDNKnxjL5ur4waKEbTzvxkhoDmIelUo2iQt5ETViZwiMxCpWc4qFQJjzxRiAGCkgL41DogcYgAMIkFFrFk6MF3g2G3a1MiBVQGr4lqbvQ8zceSQohPrK1t1N835JHrfOMLQzG05MCXiZOqlrtP59Omnnz/9/Gmd82XEoMjMRG0q3kZpCOjObqhuIrJWyWriQERxi05wcFL1eVlPT6fHu8+Hu+PuzXU6jjaEStWsge2adRn3TCmGqOinvM6oJIljaMM4MzOtpeS1j0fbvXm5A5EBUKqUUkKIROQOplpLOZ+nT58+3d1/FhEkInRw2OR6DgQUIjKiuMIFlfXt7r/kg279CyEBAobAZnY6nf70p39d1vXz5/t1zX/4wx/evn07juPzbLwF2rcMebMt+qpx9Rqu2DZ/1S92/gtDHp5hGNgI/oiI4C5ma9Xz6ucCq7JACNw809vhXAktBMQuROrIQyLs+64ZsgORAR3WskhdPCzuJ8mi+Gh9gWBbd+noSgaEyC91je0p+qX/gg00au/LBh2FS5zfczWqirkyA0dEdDdDhn5M+8M+hC7yAM4l69t3b83AnKf/9b89nQpCJiQHw5a4QwwIbC4NKG0GoG0xVfO2824BORjCppeYlnleF25Lo2+2d2KmroR1P6av3r378Ob9kAbG0KXOQJyFBM0EzQCqQ3V4WZdDEWNCZGhxgm213ObUbYe/hH4KWuuh1b0IFIGsoM2XidwRIhmiceulthcEhEzu5I6GFz0XAvC2hwIaAIpCmyeAXTLUmAmN8HLLQa1OpAQlpkCJYwpDF7suPG/9Dq6mohW2tp/InQEBFEjNXU1VRaSaiJu2ZxMCH/vOmdwJAMm2eFJEMFVTzaWstRZRM0NGJoyMROhGhFhVl1KnXNZSqouBuBf3oJuO2Zj0eIw7ITdAL+RmFQxZHZ+dhcyKWXZP8OrCEAUAyqWua06pI2Z3MDU1a23/+TznWttvATdoZh2N50JEhNQYOxdszmEzrd0Owhu6uqHg7l5rfXyq65pVpOu6UvK33357c3PT9X2IibnNXi/36DZMAGgWzM+Tfvs7Z354OWT/EvVvo/5V7Gn1pxVnoWIYfMuydXcAY4IUyDE4GRgyOF2WEmwc8Rh2SW86m0p9iLAWyBbE2JgcAMEaoZyM6XmxfEEuL28HAMGWM8eEzOgO6vBaAe9g1aRoJiUjJQJ3A4TAYeyHlAbmxBTAgxk83v9+Xeuy5NT9LG12VrOIql1aAANteFdbEcEIKQQGwMbURLMt5mRb3E1EADBSYAqESEwpYey6rhs+vL99++b2eDgQs7kBOTFy4ABszZzbmuDv1c6/dfIOqi7Q3DpAybXJsAVU24kNEAlAHUHU1mJFUYyrgqgyw9jHyBHVmTkEiIQBIQXqoyd2RkMwAzQ3c25DWLuEJl6wYQcHa7sCEBNhICMzFUQARxXPLu7eM/aBbq/6q6s+xOcuCZEiUAfI265C7BgMAgIbKBDFLh6Ph6vjrk/MYEgQd93VmzeUujmXmovmAqLBWx54zaWuuWYxUWsm023RaqcbZjSkgrGGQftD2B273djFwAEYWxxN6CKNPYGKiZq4VgX3gMZEgZt5IgvH4BIDP+8wiBhCAMC8rnOMwzByiOoObq0ETb1UXXNZSzZzcAVXuOD6xA3cJ7dt8Glm4MitYFXNHNCeW3dEAnBmcgep5dPHn//T//L/+emn77/+5tsPHz7cvnl7PF71u7EfxqHvu5Aic0Oq2sm9jaZbK/Bc/K8wgucT/0XKv3UJ0FCC6r4qnDKeVporrAJc1Jpw3gwRQsDEwdUNTUWt1lo95wiAGIKKoGtHuie9CfQu1iXAk6TVQ3UyJGx2aeDsTg1iuZz+ES5RqNBM74yQImFkDKHBzxrR8eLk4+5F65SnVXOMoUuRKZAxQVDBbFW1IFLgFAP85tdfBabdvv/+h4+n0/L0cHq4f3x8OJ3Oa871+Ya/vB3mphxp3A0OOJ3nIlUYUNtCu2kLmbg5Y4ogIowpvHlzvH2zv7ra/fY339zeXoXE6jWrFc2iRU0AgDkCmdXiX7gSQWgDJMFtXNPyibwdydERzVo+NzRI18WtiOVi0nKRHdWNAFsoodRaQMGII2MgRoyBUuRtYsst4xfUvFRFQBVRactcI39ezqVbbj0aNfN8R0Q3r6rgzswUvA/YR3quGATiMEZQbJBDg23oYlBI6gGGYX/z5s3Nm9th7Ls+Uoj72+uvf/Nd6IaHp2k6n/M0eykBDaqUkmFal1rN1P3i7E5IFNpLSSn1h/H45t31h2+u3n99uHk77q9S7JhYwRwQmwECMVizGKkSgl8gIN4SN1BIXIEpPY9hWuQTEeVSwrpWkdBGom6MwDH2434Yd3R6AGwJSxADsgFzO6dv9IVnySNsMhVwd7WGxTxvzngBXhssassy/fBDOZ8f7x7uf/rph9u3747Hq2Ech91uv9uP/TCkbnMHiCm0aKfWTQO6mai8zoR62TV/ufNjm10aQDY4F3xaYS6+iiVxIgczBGdAImIwd6zgqlJL1oqBAwDxNmM0BumwHgjeBJ4i3dV+sahAcunZaaOmwKsxyMtfoFkGIQSCyNgFioHcDcxTmxZe/o26VRMVc1AkT0yBElMkYFeopYCDBWXgm5tdjB/SwF//6t35vD7cP3368f77v/z8L3/8693do4jC5rGLAM6MMaX9fnzz5lbVRCtkG/ZdIJYqWlWkqjW2TSNKg7sh4X4/fvXV2+++e/er7z5c3+xDQHHRWqssosXdEDFQcDfH8ou2KzSJZbPZKG6s2BmJbUw5IiAmJwRANa/ia9VcrSo4QCBLkfcxpsSJmRDmRdZMXaShA+8xBAQKsU/jmGIMgGgG7ihiRWpD4N0MoWVQOKHHQIEpMYKjgZkTM17uFL2k1ucQHLC6vITSIIUUjoE6pmbvc1ncEREcSENKcAT74A8fH8bjcbw6jYfD26+/+vU//CH246eP9w8PD/Pjk0nuIyFYzeXh7jGLlCJ0OeACIBMEBkIYd8NX337zqz/8/h/+w//tV7//zbsPXx/2B0Ryanop3EaMWIEMInoA7xsLqTnCb7AzQq0cEV+COhExhsBEa15zzlUkqVZVBEOE1A9vv/r6NJ9Oy7RIxVocgdDdAKk5gWIL7NFG8ttiYwmRGE0b78A3wI+YaENJwMyVwMxV5XQ6lVofHu76v/4lpYREKaXdOI7DbmjrwG5/OB6vr24Ox6v9Yd/1PYcI5k1P9OrMDxvQ38ikl7EygLmTAzh6cZwynFeYiuWqauwGrkDQyImOBq5qUmpe12lCpMCRMPgzSOYaoPTo1zFMXfgsZYaYlaVpTi5qX4BGN9gI0M8tSLtUWywFUx+oi+RmoBbxVcRV20m2xqepCTCFlEIfOJiqIJqra3HkwOFwTL/u33713a05LVO9/zj903/+52laT0+TqVjT1CAiWDfEmzf79+9uv/7m/bLkeTmVwt9+99XY98uUn55Onz59Pp/nhqYwNkNuMbDUhdvbwx9+/+13373f7QcKrlZVZS2zW+UQQ4hMwU0VEL+ofQgi7a1oK5uzbaG6uBkkgDkEJyAw8+bKoAaAGIj6RH3iLnJTsqh6ru6uRaCqanOZihY77xvxGoEJ1dDNazUxVVUwvxS/BWonLjCn1leAOzW3LwdAB+BmEwBmAKJVnme5CMjYEbebH1/Ozw4ACgjInlI37sZxv+t2/Xjcv/3w7sM3X799/w5Dt2atVdCdYTwehxRZRYbdp9PTeZ0zobSdN7SUZAZCTH26vr15/9WH919/ffvuw25/FUIHG4EVXoofAMg3Dk8LA7ww5BAcAc0CkQKk1yg0MyNiw/xFNoUegiERx3Tz7t20Tvenh0Xy6enRVCmyOyCiYZsJGjaliz93QUCIjsREzu3UuVkD4ouj1TaMNzOrpiLrPLc7HQGIKAYOqUtd1w/jOO4Oh+P1ze319c317c3hcBzHXdf1gcNu7L8ICL+8F/jLCftGYBaHpdKUfV7rml0HgMDohM2UyM1VtYqUWte8zgsR9V2fUkeaADfLIwJNqDu26xTeWZ1JzqsWZfzCfP/L2/95pI9AhIEwMaaAfcA+ABiAQsdfAP5EFBo4TByQIzUTv8jEjuSuqhXAGdqkHGPfO3EI/TxVFB53AzMTYddFUzADZhqG8c2742/+8PW337579+5mnld0U9Xf/vbbw7hbl/rp090f//XPP/z48f7+tCwqVh0QQIc+vH979e0377/79v379zd+8XpEd2rWOG2MBsEJI8dA4bV5WchZAIEuJhoG7gIADoZmruopeAy++e25I3GKwEx95LEPgcndzbyKV3FxVIWstgos4qtAUa9qVfQ4xqGLMURCIkTw2mBhVXOxhiAZIzK2KTRCS3JseeOgjogUU2IEInfNdVVZ5bXgFLdTZPv8hb60YZcbQ1+QNSbaH8e3H97dvn+b+j5XF1FT5xD24/j+67eHw0iA47D79OOn6WkqXFRV0DlseYPIGFLohq4fhzT0ISUghhf2jj+Pk9uJ2l6my8+D822WcplCv+LAXORotQog1VJFams+Wmr01Zs31eTx/LTmvC7LuiytP2qSOjEAg0DIGC4bMMPlsofAgJvOudHxGuralPiNlo9EzfuRESNhDBg5AFjJ63me1Nu3hJBiSv24219dX9/e3r55++7du/fv3364Phzs2SC0Hb+IkGxLs7qMBmlrBMwcq/FadFrKsooKghNtiRIKKlqr5Cy51lzKuhKRSW2iECBsVvAAyOgd1UMoH/a6BrtTXczUm8OPOxlgg9EuZI122EdEgsAUmVLAnrFnGNiBgByHgC9HS8SAmIhTSG2olkJq20HggAwhkJmYKTowkbqWWhTElU6P5z/96c9/+tOfnx6f3Hy/H93gfFpTih++fvvv/v2v/5//73/89rt3feS81F99/RUBfnh3sx9Hd/r0+f6f/suH//xP//V//c//9fvvP+VFAGDo4pub/T/8/rt//IdfvX97vRu6kqu5M22DK9VqbtSIMUQh9l380syjViMECC0hthnEuioU2Jh8RTwGo8uG6o6B2kBskwKIWqlexdXANxVNu8dBzYvYsgqBu5qK9QkCu7iXXKpYmxqWXFXNwQNRLBQZmaGt2IzI6ohkQEgQESMDA6ChGOovQWUDeCbSPRf/M9ljA8YRgJm6rjteHfthWJZ8Oi/TaZJau5QOx+Obt2+PV3swX87LbjfsdsPYdxQ4jj0y1lzBPTDtDvvdYT/shtQlCry9eS+qFsNXv/oyb8ZNiPPF6feX29Hz47LnVZHa/pmCI0FM/f54/e7D1/M0n56epFat2Uy2NcW3QR5Ao0eBv5DWyImYsFEGLvSdbchk4PaMujRGGCIjdindHA4xBhHJRZZ1rVW311BrPp8eatF1lZxBNCC/f/fudfoQbQ+gS6Zy0/i0X60ticm5iC25LiuUQtozX1zo3UCq1FKkVK1qaghgKqaiqqaYq6ooqLobg45B3kQ5o+5Xe6yQHcGoRe/Z5irwcrxqxOjmh59C+4AuQB+AgCLxmF6yLRvJp4tdxLDFxnobjbeDQ4vO3YJ/n9suF8s13326/+d//uO//uuf53kehu7rr96pWl6/J/LjcffNNx/+3T/+7rtfvXMpkvXb998EpMMu9SkSh3fvjl1PoQNx4cQ//fQI5u+uj7/5zfvf/e7rb799t993IaALGlCMEYnAY5WSy2qmJoJMkVP6hZOPm7e8MkbkRgGnFsUNxUFUmSBUItogR2KMhG4G1gL2YFUXbdx8YOYQOIXQdzwm7hPHSAiwrmJiJevQaRfZHea1iAFzqAbzKkuuRdQcmDEECgEjY2pyABYkQuQ2fY2MfeKOnThAiF9yrxvr19G3M/+LOB0v7a1TMzgl5Bg7U/vx5493d0/nx3PkcHW4ub66urq+GnfDOq8NbBrHfhyG45ub99997UQff/y0ThMi3Ly5bd8ZIhEZgJiDN9kjIAA2xyqAesmnvOyFF/IhbhZU9lp7eVk6NyDezWutpVQiagg5qJsSYry9fV/XOp3PbvZw93NeastpId4GYQDN1WG7dLTFzrkoIUAl0tZ9tV+IDtq2f0RzIw4BGng4dMNXX3317u3b/W4PDtM01VIByNyraC5lXhZTD+rr6fzw6fPjw71ecgcRgbfrCM/OK+5gZgSXaQShGatrLrauNa9Ye46hRyZEMofW86sUV2usWDeTKlClOixrrmtmEVRBt8R6TPXa5RC9D1gLqFOrSENzJETf8ElEAgjNoKMVP1Ni6Bj7gJHAgPZ95FdA7JD6MfVgCOamJibcpEykYGCwjZPB3QMjYeRgIsu0fPzp0//+T//8xz/+Saq/fXv77/7db0spP//4sZQaA43DcH11dXtzU9fFew+Hjh3AM4IS63Eff/vbd7HH8TC+++rtP/1v/1Jz+fU3H/7Df/jdr3/z/uZ6RFL3ygEicUyROSJClQjgy7KseQ1McbcPoXutaAytbSZtRLttG7rcqk7ogiAbzwkJkRhyk6cEjUwIIA7uEBBjwEjUMex62g9h14fE5AhmXqqVaqX6WqyLbObzWtWBWavBeS3LKmsRNUcEYmKGGLkLHFp3xczBm74tMvYGfYCO+QqCwS+KXy+ny9egbmNJqIjkZc1LdnNXzzkX9Y8/fXy8P4HBeH08Xh1u394eb25SCrUoIsbIu/3w9t3bD7/67lf/7vcGGGL3eHePblc3V4erw7gfU4rMiGAA0lqP7aANBGAOAl/my7x6Zu3pNUkC/20L0GC4UkspJYQARGYK7kYEjsNwuH3z/ttv57b5POLnWrOrElwETY1i04YnjdED6IDB3QODG4Kru4EhYgwRiQMnBxRR1YYegCEwh/3x+v1X375/9y6FOJ/PtVYCcgBRndf8+Pi4LFndOUYiaoeJrWAAIkEXMDJuM3Nrsl9UJ/LGEUEHqo6L+LTKNE2HDrtu79HVrWpd12WZTnmZa8lqFdFrraEUjEXN87rUvAaXAMBMMRIHO5jcxPI5dHPx6mCICG5gANpQgOb8FRAiQSTsGDvGjjwRJMYUoGN0oC6+WEbgpYvxbV5oAA0y3WLSoRloi4ADEQUKKUTNmJfp4e7ph+8/Pj2cv/rw4de//uYPf/jV6TSNY1dLcTUwD0iRyACAaIgdOdRSzaqaEet+3334cOMEsQ99FyTXr79685tff9gdokKWvJqqOzIldYixCxzNWvhEqTUDdhxSjB2+VvWJORqoK5uFsIHCiMiAhN6idwFcUcHb5NPN3dWIIAaObejFRAGROaD3gY4DH3dx3zMjZrE1uwhU8yI2VyA0MVuyirp7rWpz1VJNNjObJjpxDpRijF3ou9B1FHsMgYiQHYJ6YugT74XlhQ1p4AoubTx0sXRpWK6pi2jN6/xwf3d6fHCRWuXjx89i+Pmnz7Xq1fFwfX149+HN2w/vrm5uAHx6OjNRl8LhuHv39buvf/PdN7/9dVV/fDobOGjdH/e742HYjV3fBWYkB1Bs5442HkIFsPYVfFX2l4Hm5ZRu4r7Ahdq4bfvm4E6I5lZLXdfc9UDMquruBEpAiLQbr3796z8M/RhCjDF9vvtZ5olAoUU1NOgDm6UJPEvczQ0BAhEwI4CqN6v8w+Fwc/0GgB6fzk9PT6fzKZeiRmIE3MfhMBxvdv3QDztVIWJkIiIRneZ1zUXalM9xvz88G5MgQcc+skdu2DwagqsJggOxU2gnAILqvlQ4LXY6LYfkw+46pqBQlzo/TU/Tw916OqkWTpT6LuTAMXFK4KZ5lrw4AYYYYgopOeGO69s43zPdUTdb1G2lVQRHCAiIDuwe0CNAT57IOoSOoGdIDB1xJHDwgI4vDYtXkarKEJCYMUROfdd3MSJCGw2SysZ7dGQMXewrYVlsOuXpvDKF3/7mu//7f/iH3//uu59+/ng4DKenKS9lejovp/N63q3LhIYYiQBVqllRFwURMwDZjfHX3717e3vl5n0f+oEXOdW7k0oxVTdASjEOXRpSN7jrvJxKKeDe8ZDSkNLwRfE3mre6i6EaEkHrsJ2IedP6WDvMOppvyakqBghBIAXoIjK40mWA1ER4TCkQApaiIrZWW9WRwMHFrIjlbFXNzMUsi9fN6NMv+nAjohAhJet673tMgil6yxRmsMDYCb7JIF8c+1/PkJ8Xha33N9O85vPj03w6t3PufJ5ztXVemXg39tfXx+s318ebY78btVYOHAJ3KRKOx5vrm7c3V7c3ucg4jvPQk8f9bjfuxm4YYkrE4XKM/7J9f1Xyf7OxP3cAClAB6utv2FSwBKBQa+HSpO1+KX4gICJCDrv9lbmVmhEBmR/u70qeq0hDwdqLx/am+mbXim7NN5itKTYQgRhp7Ie3b98Nw3g7r49PT58+f346nUupHFNRX6tWBSOm1IHHNj/kENgBU59UtFqpNReJKb7IqAESQc8QQotjBwNoeU3aBCEXBEQBitEqvq45ryylSJfMa5Zaaykll3UVWVFQXYkSx5S6zsBcC7gQRWR2YgdElw7gNvqbLv51lUkUYZM2be8uQGMfBfTIlBh6ho69Z0hMiSAQMIJ/aQxkZktel3VNoU8cQkgp9jFFZm48JxUxVXgmmVBIsQ+sWqGu5k77/f73v//1//Q//e7b796J5qurw8PdxEiuBlK9ZpdsCsUZkUxLG69pi7BF6xPF0N9e791BvKqVtU4mxURUVM0RYkxr35VBBQnWuppr4ICBgMhexY3Dc9vv4GBgCkRKiDEQJeIGRDs0CileJrRMQJG3E+lmhoHqWNXXal3RtXgRr4oIkIvNWZ5WX9Qporotq6xZcrGNNedexEUNoYHI2LiqiMYioVrMnlbtVtkcq5iZgANxxa8Xldd6/k3EvTF027OFzc1KXUGyzOd5nTMChxBRHcUiYtelq6vj1e31/urQjUOIZIrMFCN3XcdM/Th0fRcCS1FyCwh96sZx6Mch9R2HzZgM3OmVWwRum7ldAL8NiNgOBRup3BAMURGfoUpoaT6tGweEWiuFHCQEcFVxdds46+1oQZzSuw9f96kbh/2n3U+fP/58enrMdVWrsE3Y3a3BUkAXbR06OpK5gaOKrUupVVJKb9+9/27YlVo/ff788fPnT58/u8O0LB8/fR7HvbgTetswYJtlNJDTzfz5Tn3NogkIiSEwEoI7CTg46jO0uAF/jdvJ7qTuUquUWnI1EBEnCjF0EmIteZ3XLArYhdh1fW7M9BA4pS6GaO4ila1GjzcJ3/Z6M5e5shoqITbJFRqgIxoSUMAYLAXqIvYRu0CJMTBurqAbOLM91HRapqfzaeyBhtSHmLpGfAZzq7Wu6yIqiBA2ImhMMUWupgQexmE37vvf/8Nv/vAPv766To+P97e3V08Py+Fw2A1dFyGxKpu4ic5m4FDdbVMogBNhZEM3My0iq2SxAlhdRUW0aq0GUJL7ZSrLjkYBOQYMlE1yLa+nY5cgp8b1bNIxREJQNUTaBv4ObtCUhkRASLbhVI32QMQEiOZQ1dZqS9Ylaxcb+92L+JzlJO7VxHxdJRcpsnX45iDias1bB8kRHMwRHQzdxB3azFrFgNmZjZiQDSuclvrKzANejZN/8UVwA62al3x+fJrPZ3cPMcQUEWiNYejibt/vjsOw62MXKWBjN4UQUkpEGGMKIQQmZowBh8T73XA87sZdn7rUXv6r3/i3MD7+TVfyi+/3X/QFYiaq6q4N0WaKXQcArfix2RM3XIEIEbphh0iAHEMfQt8Pn6f5VMqsVsWqiBi42TPu35ZZDMyRu5Ha6V1UYVmLmO0Ox+sUh/1+d7zaHY7LPANSFTlPEwaKXUTa3P63wSpuXIztnNmExpdXy7gdrQmhsUhUX94C2rRmW5KoXfx/W/0rqilSe6YUwCGvFcRiV/sqRSQiM3OIoet7QsrFTCqSEsiO6Trm65CfmCdjb7sCwAXUMiIIRCFgDJACNrQ/cNsmoUUBv76w3qQYKo1oX6XkCuCFAE2t1LqWbGYhBm5sC1cHrSrzkg3w7fvbt++uvv327e2bfUg1Jdgfdoerfb9LqaMYgMncVbWoVnNwbJG27AZmAirkyuiIEBkUCI3Vzd2QIzqZK0ArRjC3jaqDYGhZ8t35HuPx5qY+e8UFpjYwuyi+AZFADUoR1cY02eahzaRiY4/aSzx6CBgicfNnMS9V57V0ARN7Cqzu4r5WOS+a1auBGuhm9dIGX6jmZttGGQCRkBr/jJFDCIFjDMxMSObo6ujuYprrMq/6mkyyXai2HhgAIFzokGpS6jJPD/f3T0+P5pC6bn/ciWjJc9dT11PXc0wUIhA5kjNBCE2SCC3BnIhixL4n23c31/vrm+N+33ddQHIAa3RkfKnk53q+DNQutL/nqfEzqQb9i+XA3UW1iIrUWqu7GWDsOwcwEXOnVvwbSQi2ORPxeLjhNPTH69vTw/n0eTo9rMtpns/zNJdctVk3oDm4iCFyl7px3F/f3Djg3cO9mP748ZOH2O0Ot7dvxv0hdv3xeJzneVlXd6ha53nqYAjM24zgWYGDLQtY25590Q+1F+yE3iSTiqgXz59XUMgW6GGmZgbu4K4iKmIM4I0dFggJHGtVU6+iVV3UQ6TU9YGp6zo3yDmrVdCCyDHSjtJtWJ8Cq3TqqBAcCF2bopAQmfxC5m9jJmoNP9Ml+QdfLg0h9TH1qUtMpuV8zssMMVDggBhMoUhxB2dEqyRQCiwRTsvT3eOjuP32d199893b25uBqZZ8Ep37Po37MfZASSiYg5dalnVVw808hxBcG9sKzYYupRATha4POw5VZV0nlUKIDY9wJ+ZAnDbMBclMcymTrmv9VIy//fD/uAS2Q0DEV6w/vyj2za3p9lucJjBB2/QvHWs7BLSAhMvm5bCNPLcbokFwUNXnpT6eylxMADkEYHwZRm0+YNA4qgbODITITJF5W/CpAf7NYKD9FnPVV5oLuKzoeqm31p3w1lq6eVP11eKmXd/v9uPhOIrIeu5CH4dd7AaOCTdKkVczMROzNihVVQXwmGi/7xPK1fV4OHRdx4GdUC97e2vdW14ivIIA8PL581/psjro5eNlFWsGD40mq2qqClRLEQdyFb8MBp3aq23OU8gt6yyMuy7GXdfv0m7s58duit0QxlKqGpk7gFap65oReNwdrq5v373/Con6/eE8TwZugKVKFYkppa5jDjGlOM9Vqjuoaq3Vnj3ILo/2uZrW2hqNVwrFy86PCA3IbH9c3ggEgKZbE5GLD7GKZCnRY5Cqay7LuizrvOQ5l0KpQwoUIlBo+0Ng4hBNrRHITLWh+qxhxH5P4YRh8bA5ILqxe0AIQAExtOkVYWhH/ZfbfPt49UKoC92Yhi517pDzLFY1UAghhgGRialJpJkI3FRyzn6eTvePD1XKuw/X3377ZhwjgphmAB2Gfhz7EIHYiQHIza1oo/EDNY9JZ7FarbgqKSAjUAiBKfYu4jmrN6zOmbg5UwJC0eoOBqomVetS1tM8hXQlWp9fTmhsBCTEiw2TOXjLVHVrkkhEcKbYgSNWRzIAQ4fmmoGikNHJPRD2TJF56OM4xL4LiGhua9HzlB8el6moEQ/jECIDGLY51KVOvUGkroBEgSNRH0MgJnRGiIwpxdh1zU3I3Ezirh+av2u7D83VvbZFHeBCVIQm0bcWYtl3cb8f94f9eDgMh6Hkshz60Mdx1/VjDAmJ1E215lrWdVmWeamlrvNSSzbTlPjm5qgDDUPf9xTYCAWhwhZQIuYCoO6KcHmDgGCjgbS5sl8q/3m1EoeCkF7O/O5StdmNIJCZiGgtFRDdXswzfAu93vw1Nv4AOqJjxzs8dIy9wy4MuncBMgoGZlaWZXp8fHSn482bm9u3N2/epZSOb9/lkkVrCCHEuJZSRTbmn1mMkQM/x3FJfbmHtk2jFb+q1HZeuez86AE9kkciaFwIk2bh1ibICNA4/82kqIQiqqouda2BAbo1L/dPD6e7n5eHn5fpnMXGvu+GcRj3setDDIGBuBm3AIdgGqqSSjWda8WoXQ8p0EBA4EjmESSBJ8TknhwDeASIDsGhnQ0QN9ex1ws2ACBSCv2Yxn4Y3M1VRIwA2DEQxZAgEROnmAjBanHVvOb5dH56fMx52e2OV8eBGd2VEGII49Dv+sEpA3hbI1vYt1h2MyYmCOgGZJxIxBYrtVrHGJ1IQi5yWkvJmdq2yE2a2Mh1ag4USF3XPM95OS/n67x84du/vapG1tsaLnDwjRHpBghE2NTuQOSATTXejgBM6A6q5oABgblp+DhF5kBVbc56muvTVKa5ZjUIGGoLomnk1g2yQtimDK3Ix6HfDcNu6LsYmTCkELsYu8gxOpKpqoqLHL70um+FdCktvSBtDOBASsFSx7vd6CLXt1fDfuQuLLMPu5670PUhBECopquJ5vW8LudlmqbTqVZd1qmUxSy7s9W1LjNZJTRKgQIxtdm5OYh7BVBARSCCeJnev97w8W+KvwAUAHk16rO28zdznBa0Wmr1i0WRN6KaoeG2aG6gGTiiERqruggbdKGPY0ROHpLFqG5a5m7qGtHt6vbN4fqm2+1ijKHvpbmqemPu1QrtSAKALTmdmgZW9eVI/3eKX2RzSbq85kCQCBK1i/Es33QEv2z7F1SZgJn7PsXopjkXBPciVVyryVrXVVY1AqLUD92w45gwEDI0ii46hBC0BgMq1mIqFpSZdWDfE2gEYvARa48WARNwZ54MI1AADACb8v8LSObltRJQCqmPQxc7d60pMTqCB+ZIHImZG82NEdCD1VpLlnXJJa8Astt3+31PBO4eQuj7fjf2fZ/WnGuVIiVLKVYqVIGirigAytgYrQ4VbK3ZKybTUCtTLUXP61xydlBm6roYiNDA1Iu4IwRicV2lrJKLVdmw2EvxO1yEhW0W/GK5fgGmt6hSQgqvIj6dEGNoi8aG0nOjRidKkZjJAJZid+fy6Sk/TnUtxjEwk5tKNW8GIoxEiORMFBhT4BTDbj/e3lxfX1/dHI+7/W7outglDsEJVbVUyTlLrSpyOFwzh5eLhAKgF+xJL2cRBWCgSsH6IVzdHPsu3r67TkMsWtVqGJsulcBF6lTWKqUu03k+PU5Pj6fHRxFb1nPRyWwpi/38/V9PP3/qu3B1c3WrFdC6oERJTA0UUAGUoEn7YuvBnqmsX95PDTM189W9XgT5Wy2J1lorA7bjiruFWqCx7bfp/WY7A+aOm5qIEVAVapZ1mU8TlhowhJTCbgddLyGgCU6apN+NO2AeDnvuUpFaVLcud6P+/kKTD9tBo40PL6X+5QoAZtYEOJsIuv0zxIiQGBuDpVALa0Zqbg7YKD5mKoDQpXTY481NfxjKOq9lnVzRzPvdTq8OeUm5olYE4pD60A3UUERyJOTm985eOQhwUSriRUTrAjKj5QApgHXkV1QHVEIIQMljb5YMontwY2BG5taR+iVN+HlyQZRCl2LHGBywT71RoNbaITeXWjJw1ybKBsN5XmoxAE+J9vs07BKQOXjXD7v9frcbuhTmWZclP03nfqLTcl5kMRSxmnMRcWg/rOvE7GmZswjSmTgy9uBQay211ppDoAMMKUZQQGfgiERCIObS/EwSU/xCpbSh/dsg/6IThpdZVTPDwTaTU3PaqGPtzXCAZ1ldGxYDM/B2ugNVr2JFTBqBFREBVFXVHcipxUkzwUaubof8QBw4xBhTl/phGIcxpAiIVbUWFVEVq1VLLqW8jh8ygAKwOjA42MtGigjsIECVk/e7LgbcX42xI1idF+LISOSoalmEkbLUWsq5lHOts+oKiKHz0DlyrTmfHu/vP30auoBo4+2xr/toHTo6ml/aDQdzoO1zt8ab9WfriAvXBxoZyCuYAr30Y9bc1qUgcTsIO4FIQAJ0QkBXA7/4i6s1OwRs1tS16PSk62q5MhH1oyFWN9UqoCrV8iKlIAAxI4KaVSsNbmucKGh6ukvFb8x/a8/4pez/reK/9Cwva0YgSISRQAFCq1IC0oZ5tOmOmQoEizEMY7i6on1aSi5lqWtZkWiXht3xep2vzHTNmPpdSD1y3BwgyBuF0X07aZmhmquBqaJm1jn6OlDXRd9HuA6lR3U3ImLWgJpMWQpAdIiOyfFiwezwGotBgEAciBnI0SNH31aKLS4FL+JoIkwxqtS8aM4SI3cpHo5DP0bxugqQJgPniMReaj1P093TI+/8cTpVKchublmqVEdlZIysxWyqZa0VkJAqegYDFS+15DyHQE4y+hgpEbCqgioYqtfqtqFKCK+vWWhLsLu0xdpsC2BAbKA3NRjPDGoVV2NmJkRGQy/qBAiNFNRcQNqoZqMHOAF0kYae+p5WRaJ2lXWDrEKMzHjJ7G0sSlVb1/L4eDJzrbosZRhHIq5VcsnLurS8sZLzdD7vxmPO5fnec1/cz27sAO7isHmMIbK5GizAJSRFB46ODBdzUjcQ0VxkEUN0UhfDBTBjrHGA0MWbd+Pxdgidy5pFcpUcglWr6i1xwJCBHem5gtvRuB0BNkFhfZb6okPr/xuSjJfU9+eHu1epVTLHZC6ixdSDBGRAJzTXKi7iolZFSlG1DegwlWWa7j6R2f54GA8HZyxel9O6uimA1eLnE5QKhGy2zFNwxxDMva455zXnTEy73f5CW6QGv9vrgvfn1/jFQtCGFLVU1ZfodETgixk0OnArfsQt7WkjjaqqGjsH7vq433f7FM7nWc/ycF6I4/hmNxzeXMuUYj/P3o/XHHoHMt/GzUibXd+Fb6BuRggMwF6irx0szN3NADcDHkPtvNbGwwvqUF1ntyASQXuAPUIiZkB0R/NXnAUEAmNwRnBgA24S6UAhdQEaC8MdCWOMqeuX1c7TOi+lG7vdVXe4HuPI67yu07xKepzmYkW8zHnxU/n5/k67Oq+LmlJkZgJnDC14k6tjNisKChRSREDJKlnKKmtZc5k5NEYpXh/2CHE+zUXqxQjRqnkWK6+wmFb82HRgF9z2ciGhQXKACGqNoe9GROQxEAC3dO+mhQxExISXsFhVq6JuYGox4K4Px10Ug1yhNqznOU9G3c0b+UPFxNXM56XMSz5Py9PTNI5DPwxMJKIiJZcsKgiYSz4/PX377X19QZ7MrLqvgNy2qjZKQkBENhOzal4dFciAHJiAGYg3BMukWW2xk7VVkix2tLsaut1w/fZ4uBo5goEiATX9ZyBncDIDdWjTo2YY49s8z9VAcdv5xTeEnJ6zKzaC+Wu279YSuGpVKcZoJiJZzLgwgBETmEsulouWKksu67qxJszArK7TfH8XmJDJY1gBlGHd7OPESvF5QjVKMYgWQq6FQhDVdZrXZVnyyhxKrcM4xhCauemzP/r/SPFLM4z+wo+wgXF+GQM9TwEb0uu22f45IUYOKaYQHTgV46dJiPXmSLFLMY5dr2IQ0ugYDAgvRztzVAA3F1UVMd3Q8kAeUDqse87UlXdjuO1hxJWtVDMxdJaqkEsVA8NocVQVlwFTRyEavkRaXTYYAReCgMjA0R3w4r3vLlrV3BjYwA2giNw/TqdpCV3odtFI5nI+LZObD9rPa1EQRS0iUGzKuc9pWnMVAWwckz4GNsCm5c6iVUEMvLqrlrnkuS5TXfJaypx66kInvauhqD+dlnmZAYECho4MNatWfZ7AtuIH9xZl0/p/uPidt4SzpvJyNTREEDRC1cgA0ByWU+Q+cmQmhMDbSlGrrgQIKuaR8TjGd9cjYv70mKs4EjISE23m5KLOaAJVcy51LSLqgSmEEGLoUuz71MUQQ/v+7QBWap3O52Ven9v+Boyp6hZZ1bQbG9dsE39W0SLq6opEHJAdOKjjZasAA3QPAAAYOMRhHK/e3ozH/dXb2/Gwa/16N/TjYTeMsdsPIbGTG6ibABBiIAzo1AhKBhU3Rg6688UBvlX7BetEdmAHhldqaHBHE7dqQlprrbmq4IKqEgO7Qs1ry7iRaVmmuSxrqdVUwN20Sl5jDDadT65KjIzM7Kqas+VsJZs7hkC5BhFIk4GXUpdpKqWYOseYS+36joj7rtvtD6lLTdHdwH56tRC0/9rlVNCwWP1yh2nLhaiJeaOhmjlsITqN2LPxTLEFDBuYYrW4aDzniuCnSUiLLc3Mis2pxcYwEACImrsZglZdcs1ZTB2ciJDZEskuikeJg7wf6iEZ18k9IwADqRVTlWUuRR1DCQMuiwwH2O1TP2Ic8QusxlSz2YrQ4h26NmMFdDWptc7rbGYxJEMwwqdp+vnu4f50jgMB2+enT6eK61qI4hVAMTcyCGgIjkQhALMYzquuOROHwyF2kdEFAYCpqrqCVFumua5aZ1knPZ/zsmapeXfs3hw6tL5mX9f14e70dHpSV07U7zru2NjqC4kUACCk0EgXlwva9h1/Qf3cTLf2FJ0ICM1c1EmMAIhQmQjdEQShiK8VQhYx26i1QEPiN4fOHdesVUzUY4rH/a7vEl80laqyrlrcVbSKmVMVtXkhwhhDn8I4dF0KYWMvQZWqVV4Z0W1bv5lsVgPbyXrbccxAxUW8FHXBqkBO6myOLUzKDM3YLJpHVXALABxjtz9e7a6Pw+EQ+wEJEDl1XT8Ow67rhp4iO5parYKE3Mw5YHPoAjd111eD4mfM//UmD80q/W9MbsylVrNSyrJMudRcSggxhoiOWqsUkTXLupaL14+attAsiFECL2Z5zdWMGYfUBQQXBTN1aHxOkFrmyZalqtRaS87uzhzBWEptNCwtShzBMTZkxO2/V/wAqs22/wuXWHNXMweo6qKNO3Gh8rluJ00DMCczEK25ripPiz2ucCqBEZbsPSjkWqsUAVetZmKQtkQDUTUDq0XXLGtVMXAgAmeCFBEBUpLU5WOgBFLLWcoiBgYMFF3U1pOuWR3Fo9Dj2h31+mbY38Qdqu785ZpYreuaF8CUIjEnBFQTsSq25rJM88nMY0xBMuf1p7v77z9+vns8vR2PinZ/euDsANx3KA0l50AcHKiqr8WmpT6d8uPTdD5lQJ4nSBxNCrgikyM6Qakyn5flXOrs62zzVNdSVNe8+HFYAy4qLKK11m2RJZdqRigqtb4cxwAg7Iag6sxGVUEABC5mrJeueVsIyJvmJwZiUoecVYrmIjlqCpsLikQXo2reBYrEkSlGjMRXO3aAZa1ifl5t3O1+86tv3t1cdYFcyjydp2k6nSkSEXM1CDGa+7pmERH1qm5OsM0GXNUQMEXu4i86Un3OtAdj2GindNn9ay1UMph6KYABRFy1YWfoRm7BrTMNUqEWViHA1A/HYXek0DsmJCTuQkyp61Lfxy5hIHcTKeaGSIQSOBFFxtC8Tt03ASm8IGjtGW5h2tR6YaJmBLR9kzuZQSlFbV6X89PjvGZwJuQQYuDQmNdaq6l7CMSx22auAq6Am7lCc9hvlDkKMY3JfcCSxQ0QDaBULbKWWs2MEGPqhnEXU48YDEDFXKFmCVgRkIK76zPCeyl+gxfQ11VVteortN/cxSxXJYKqXszVfHNwMlExUVJvzY6hilVYZ69YfnqYf3qqTxL60Ob2BlJrKUtVkbKK7ByQE0dyIbcq1XLxtVgWr7aRdIiwS9gxQ9SQ1uSmucznp2VeiipgTP2g5l5my0vNZSk+V8C4W+f3+zfrHrjWw3OYirkvdT3N01qh63Tsd8iUy7KUZalTzsuyrgbGISGSOf/lh7u//PjztOT9h6F3ytM5Ch6GqxT6yAkjxdgH6sBDXuvd3bJI/fT58eH+dHpaTXE3LuiQl1lrAfDYpf1x7woPD6fpqZQJavYiVkXU5fxUTXA65/df3wxjl7pwHY8OgIwQoILUUnPJXxT/vg9qEIPFQKFSqVRFq6LIJQPTAQCw+Ra2ACt3E3MzAifGXDRFSoETYw6QI+VqQwpDgiEiMUSCLvJxjG+uOgcgktiFGEM/dLf7ITHUfDhP5/v7093jmc/zKkYcWi+HAOre7lQ1IHPArUXfTFi+ePh2hty0atZINe6o6rVYzVIWMUPVVvDgYlqlWeOCEWJECGDqRm7EGPqeh2GMsWMKBBCIU4rap37ou74PMRLza8cef/m4IEWXRuDV45nqb/7i+fFFn9x6IpFa1nVdl2VeTRG8TVQDxwhItnXXTkSMEREUG9mvsTbMVaVIkxC5exejIxQAcUBAM8tVSqlVCjiEGBrho41vsY2AvYU1CzExkrsCqF3Ifc/F/zyj1C1d5gv3XjVX8zb52I7oZiamZtK+14ysBtCACCbLUkTz56f5bpJZBg5s2AgmLmpZUaouRXJVc0SKFEkriNY113nJ65rNjbdUNw4pErGhgM11XdZczueneV6rKIWERO6uddU8y7LWtayrGJ/M1Ygw7fJ68/xyzD3XOpeVFcUJmElhyed5PU/rtOQ11+oIIQoASaXH03Sel6JKTBR4FTD3jmFZFHWuqz89LtOU81oXWX/4y33o8f7+6fQ4T+di4jHMbl7WRaQC6Lgb3r4FRH64m+fTKhlVXM0NAQO6Qa1WqtRaB4j9kIgYEA1MXFTkohR9VfyHIZlBSdaL5mprsVxkKbp4vZzFEAmZOfaRGE1VRaWaq7e2nyOJUmENTIzQBRo6txE5cCLYjL0duhDeXw9d5BDyXO3T589m1of3x3e3X3/9lUj9+cePw8+f+OPd07wqQK6iMVCLvSIEsJbcBgBm4GZs1nCdl5JqVejkBma2uZQ7umMptaw5TzlPM0AAQOZmwKFlWRqDl8AjUwxsLZbHgZFC5KHrupQCM6sGgC4y9GkY+n4YujSk2FPkxjBDZKSI0BzRLkZYFDY1/ZYS2d7/52fu4AJewV9IPkQUYowhSimwYeFqiqZgUsABQ9g8sdxV1AE40CZDc3cwRAgcwK3WAm7rsqYYupQcYS1V3TlEBKi1ql7kEQpQxGEJRZiYOVJIyGSmVWpQBmqkicvA6G8APwCwTZr9BUegfYpbHIshWMMGqrgouDpZJc8dSseEAHO2OS+Pp2maoXi0PjbmrRFXpKKEBadVdqsc1R05xYgAYqd1zefztOQFCboUmt627yIAzjmv65JLXZY8nae8FjGPyXsTAG/HHpGskkHVzdbzA8aOu8M83ZrK5YV4Nc+iDAKSsTCSreW05GnO85pLUQFiTJFwK44QmCKPu34cRltqFZlPtjyepN4t5/L0ef35x8eHh/O8rmvJQDad17JUqa7VzSZ3cHIAQ1KXuB8gMEoGUIjBAruCUQjdvj/c7N99uL19dzheDeMucQxAaO5i7tWDWwoQA77eLkOf2B2SU69UxJboc0AEbB7ZauqIxIRhSw5tXGGp5uaERE17tMk5nZAMHNipGGcFRI3cOTpCCjR0EREd8GHR85rP58ePnwIRcUiByZFpywB3U3czImRmJ3MHEVXQZ99FRmhKjNfU6/Y/3dzUVVqMOIGiI0mtWmvDgTlACjGlaKUwISNiS03kEJgZwaTWvJZ11Sq7fRr7lEJgIlQjwBQCdDGlEC9oOCITNm4Yt8iQi5kHE0Ir/kuF+aU9uYzOYUtT+UWOWstaa4FN0EjXgO4uDcpWbYimu9Yi7tayOrbVz40QYwgAXmpxFUIqkauII6xF1CFEQ0Qz3ZQVgOqmLuYeVEMIMTgDOSCaAUJMAZn9YpT2bxb/5QFfPBoAu6n3CYDByBXcCIzQmUoI+RBkjIFB52V9OM2PT9P5jMoonYvGyrlIXautFcF1Wuq8lrXIYJ6QxeA8LXcP958+fZqXmQKOQ+92JOKYkqo+nafTeVrWsix5nZYqCki9e1dHAMh5LWVVrYQW2RDEZK7L03K6W+enZwjD3HPVuZSgKO6GTuQiWVrUvG+cuHaeU0HysB8HBQOzZc5P9+t5Wq16LVryuk7r+TE/PSyn85xzWZZFVMsqWg0MTUBEHZH6ECKGLhJH5pS6dDio77qYDMnVlWMYjuPh5nD75upwNfZdjB1RIG/ZB6rkRmab3+CrR2BGREiI7iRqKRqTgVlVMrNs6IgUAjKru6tJ3aKEALceEQA2yiYQBvLEQrSoy6nMq+y6uBuwyUUiQeTw9oqHUR/O9TSvf/zXP//l+49v3vw8DL2LLMt8f5qnea1qcmkUzWDLoWumE4QpYOx4N4Rxl5hfmzEiIrqpiWqpaobcsgeCiZo5InKMXdeN47AbepC173kce3cch33XDYkDaC3TND88nB7uyPn6aj90XeRAwN723BAhlHDx7TJndHIjaFxJd0RsWTxkG+3DnbAVy0aitqauR3Qi344L+Jp52ViTGEIIIbb7qfl+b16EGwO7gTNqZujW0kA2fJOgVnf3WkuLfNfNmxObW5qYbwF6bmaKgMQegNtpBREBqqgjVY4M4NYHU3C0jQT+ZfE/P2fVLVvh1TwPCZkoIKGpkyu7BbBIAmSOyqydr0PMbwa9Sh69TufT3cPp8WGazoCplriuc1pkXZbpPC/z2mGo05zPS5lzHYoGtnktnz7f/fX7H3764fvzdCbm/W63LqVUU2Cp9fsfPz8+PjZ66DIvZh5TvwdIw4gI0zLVkgNjjCEEEsdi6rrU5bEsJ7+YkarZspbTtIYgqRbR2jirhIEppcjoLXMyurKuTh7eXl2tsi6n893n/Nfv7+4+n9cliyiS11Kn01KyopEbWDYRk2Ja26kR3QgDE4U4xP2hO97u9zf7/X54S8eu8350DipqGDCOadiNu90uptSijRrLSb06CgZDcwc1ky+y+hCdEAMTIVhAJgR3Uy9iqm7mCkSMuGUGN0VGE2Q8m00TI/WBxyHt9n03psBsanlac1FwN1AgqQqBPDKkjlKk/cBV9OFhPc9rUem7PjCpylqr+CZlt40sBYGJEzFjZI6J+453Qzzs0pu3xxifGcdIFIlSC2RyE1Pf3ClJpRqYxci7Q/OWRwKLkcahOx6P7jQMY4o9I5uJ65ZBRSH0u37YDaFFHCMB0eZou0XX0RZDiQTQtn3GS7irv3D4AV7zKp+/2ObetqEUX+6WTQyLF0nplvNxIWNsP2Sbkbu19NAXDZpvWJ+ampkTuAMqIjaja0JVaOJMdzNDpMbk8csTahRdJHMMIbCokCGgPZf93y3+JkX8m53/2VXN0JW8sufoK2JFkIR18HXwqTfRCc9rWZfT/eO0TkUzRgBby/SIGJbl6W6edBGjlJY1n+fl8TwTc6l1enj8dPfw8fP9p7vHaT4j8rIqYFLsjPpa608fnx4eHqtIqXmZZ3dP/ZDVDAMhPD48as1DiiltgKqDiWXNp5qnV+NkELPSaAzonl09dDEgcgjJqZFXoVS1DLUwWuhSVzQ/3D9+vj/95a8P95+nvGZEGHadg+eqDt51gYhNnNWiNBMAwGYCGAkH7g/x6mq4vt1dvRmOV+M4duNI3WDEKqqORpEoBm62DG2QCmCgBtVADUHJKqrgF9clmCoyEVJz4AcAdzZ10ZbECtUcGRy9eTfAFgcHjhvGi4CJ+aZL76/233x9e7zecUrTWr7//tPjaRKFJZtCDmuBpvzrKXWcYjjue3VesiCY+bIKqLszcGJjcFFTJ4AUaDfE60M6jP1+6Idd6seuG7quT9/9+quu27wJEBGxQ9pxAFNBZte1llW1mlc3B6O+72/fxUCkkvNigWC/371962Y4DjvmgB4ILIVhGPb7Q04pHW6uxsMYAxE2a2EyNAVzJOCI3CH3xBHoxWoct2ACRKzPpKnLjt1q4WKf5BvFRdU2EsNL5eOLPYGZmXGbWrSyhE0f2FjDbWmg9osR3S7rS6MREgEjIKjZBQK//OTLcyN6+cBtIXFsckRrvF3RppkCv6S3/R2Sz7bz68vO31Y1cydrdkJCnlmnoGfyHDz3pL2vqU6yLh8fVrAiIqesVjBh6CBjWR8/zbOdl/NjrWTkcdflnKd5/njH67r2KcxPD5/unp6mvFTLgqagoBSL4lJ9qrV+ul8fH7PUkuu6rJOacsxPS5lWRfTp6cGt7rq0H7vDfkgxMbKDaJ29LO6XExkRhAAhGKECFjNQQ7bIgVNSVdV1KWXNi5cY5KAeqsJ5zh8fHj5+fvj8aZmniuD92O8PVzGFcsgGGpuLQDsvtGg49YCcup4jGUkc6HjVHY79YZ/2x3Q8jP0QgcRd1ERNDUW0zsusBoSBQojMjs0f0gS8uGay+gt679YrwyZgjkSQ0AyKeq66FtWmGdsEDlvr2txj9HKBGXEM/Lbvf391eP/uujvsT7nukX/69PBwWooIAbiCaKOgOyPFREMfBoptHiktQNSRkdBRzKpoKYLgXeDDLt28GY/Hcbffdfs+jD2niEyHmyt+tfMDBKKEkQHMgRFbCvhqqmAOTClSSps5gq8lxeQAIYVabVkWRSslE3hejbjfX930Q0q7ESNbsyZAhkDURcaehoG7HcWRQtcs6fGi2HvuiFqBtYyI548tpGNTMjf41RyfU5Mu/8y99c9mdjkPtAWkXa3LGQIAL/5q8Kw/v0TpAkAz/G7ZpW3Z52c+gbu5wWbrDRvlnmCLwAK7UA9bhJ+qwTa2eMXz+0XxN/PaX+z86qDbWEPQC9lKcmZ5ZJsD5EgarGCdJS/LupiKARXgGCIT98Gilzyd5/y4LmfzFHtl01LLNM+qOp9DZMzLdJpzNUTuOBEqY+iNhqzhadZSdS64CotQEaoeDFCdsTpOK7itS3EtNVeRQuQ4eIiJAE1mKzO8fjlEEAiRndAQqzmIqgNxyKpTKdOac64oPoBb88ANkbqYxn5/E7qdJ8Ldfnz77rYbOlVRqAYK7MBIvDnmShEmHvqBAxZdKdo4hmEXhx67HYQRILqaqZpezHGq1qUsIsYcAiQIHRIZgAGKWVUrquUywduKP4bmtegtEZUQ+8gAsFZLoYVIO7mjY3ONt0tm6OaaYGDq5s6Oe6APyL/rhqvbm0L8fhj/enX3l7/++HieHEnMioqaA3hn1HvYUxgGjDumFJEZiALRiCEAGVFVy7moWkBLQxpud/E44nHvY2cpKYDU4jH6SwhBgyGIOHHAkDobxp1W1epSG2Bei6xZStaSc1mtFKnFp3me5pxFHDyGkGIcUj8M3f763XBIEEOWYtUZDDlCoO56l6Tv+qvQHSgOuPn22utq2FZv37C0zSYNmjjSsdm+u4GrgzsBPsdrblXZuP1VVGzTRBESogOHAC2X57JcEFG7O82NNuei7WyAAMz8TCA2s22BuECOG82QkOgSlEJ4cfp196379C0nETZ7d3+eWTwnfr/a+a2ZvL4wL9vNB+jkil7ZFpIT10e3M3oBMjWxmq1WVTcPFGIKKaYOmII7VqnVa8VVEBFTYGQSkWmalnlmQkYwlWrA3ThASOqAMaV+3B9j6sShumPaxcGBA8TIPgIChdBWRpMKoVe187KqSGRigBEAyL2o5sWfJ5ebjogoJCJGcDEtRcArMq1SH0/npVQHDBgDqkfisdvHq/QuvZGSFzCB6Dj0w9X1VTf0jl41z+spW3Y0jmHoewBY5xndh34A8jWTegnBQzLqTblM1V1AamN2CaLHwJvK3aRaZRAPHkJqw3FVrxXyKjXLS5ISQNgWabO2w7eLXatJrbWWXMqatQnW1ZqQxADQjRg3T34wr2AlBcmVRXuHa2aP0cdex27pAq5UDQo6gwuYqXVKe8c3Mb4dul1K/7/2rlxJjuOIZmZV9TGzu1juggCCoEIRCpKGDDky9f9fIEuGLMkQGUFyj+npOjLz0ajuWQAy5Iub3kx3TB9T58v3XkpKcRjCmKY0HsOQIFCvTXPX7WlDEhpmH+d6POg8thg3Mgl9FrvGBkIhBEES8uieYM1VVVtITBEUg0toDeZeSSvVpS0Pz6eSK4Hm6XB/d3c/pqvDHI+jBnNvtXqEx17WdEw8RE+DxtCtNtiVyKWXU/bufACGARVQ932GFtnXBWCYQwkOBkg3L67LtO9eS1nXszWttTY1NQcMDuscGYdvEhZs8tttUQHGRoTo9p5dW+gE9KMsjG7VsGv4thJWfRchW6qAN2CeBUTElWpgIHSlO+Db2uXLPT+paqmltfYpyaeorVVNPHrhtnpdqD2JPgu1wCZwuJvDwMYRxEyBqJfWQDcddiTlUVlJUiNhs5YzlQKgl2DiDj1zoiEEMEg4jYhJWZp5cWosHoKH2IERDiEOIzO7qnt2MUUtxVutKUDcyExCWjPV8+kF8DM7raen5fkwI6UxsJh5rqVpc0Ku9fl8buZxGMdoTYoMMVKYeZ5TcDFTYufBwxCn+XBMQ6LIVVM869qgriGFwxwJJCnCbEggAaVgLo7mokVrQ2COAGpTNYWbBBpiIoZDDapujOaMmEzCYIZcaj7nsuSWX+zViCiueWWi0F0jDAZ3UK72sLRfn8rjk5UvcSgiolI+63dLaw/svxynn5f18bRePS0xBX14wPOTlMK1upq7wozd2WkUvIG/H4Zvvrq5ngY0hGEc31xNx5vjcJQK/+WptvNZ5Ey0lpZzW3HOxHkcKrMHbaY151brywxDDihQBUxsvfV0f1piEHsQHwI4SZyGdLypteWqJRgK2qInW07lbOqTF7mKI+braCmC2N2cXIPpPECElODsQpWd3DIBBBXyIJdiQRRADCc0uJork8SYJHRvj46tuLsSjHvbpyqkFyDQzdb1dDo9WvPTsq5rW7OKONy1VjfdLC69DwLUQX8WDiESyJvCTXhT1IDQHBDuBSatg7dQQl879KJNktLYbZGEWaTnQINIULXuYhYHYdlGji87/0b7IVVd++p9XyqbYyn6tNZJNNk51mfKj5Yfg+dpHmIYARhr09CLMJi7mmsp3lZhmVgimGmmKBiigc6GnDNT2WufEaFT43tlYyGHWctqKyBxIA5qulotWk2buTuJkMzSZYtGzl5bs5AVRaugWl2tZpG4rLY8Ptie56+t/vTzf/79479ub+6vDm+mcYb7kvM5L6XWXGtuSiFMQUJqTc4xpDSEIKzsxI1gATJiiFwtkkPY0NAgZ8iqVrURcWFQrRVmrbJEkhQoqLXSStHWmGQYZmKqrRqMiURItSvrCGxmzVstRWOqw3Q0p+fn0/PpOT+fdM34pMRd/Mtf/8Z7yUQ3dI5GbbZke1718VzW6u4XkHd/233jzxyEotAhxttp/MPdm48f392+uzvc3aTAfnui+1N6f3q7lNINzbHlgK6G4cPt9bvb63f3bw5D8mIS03BzHA9X43DgCvvlSZdzVs2lns9LdlsHWa/HcnethwHC6qq1vnv7MaWLGWlgviIi5rQT5LpljhFZYENQgQVHgienpppqC0MOcQnDKc53y5JVbRjGu7u7N/d3h+u30zyC1eG+ab/HIMR8cAbLQCzcYU/0ypK+sXa7RgdEMLASK7N0GkEXEfdXyNxJhSDCOKrIV90/kIiGcfzm47etVjNfc/twWnNVEe6mtr4ZbewybNpTAL28J8h1K+i1dX5A3SESYhKJvAl0jIB+FA4iiSkFDgQQcxDZOz9zR51TL0j5X53/8ySFqZVWv/vTd/M892/mMfzw8crNRrFoc2iJ24hyjNTmeQ4xOUjVaqtq1mfXpqauTsZEY88zEzt8tarum3rCsau2CCAWSanbQQiBzBpAkrq/TjLTsi6tZlc1EMASh3k+hBAJprXW9ZSXUz4/oeUp6HGQ62lkCbnad99/Px+2ZxnT9OHtH5vqzdVXx/lmGicQreWcy5pLqarqkBimw2Hs5ocxRUkkaMhOFexCMiIJBafQV10Gq1aq1lobyGOMDLK2WRmHwHFMxN5aaa3UUhk8DBMLN2sO73guM0uQEASOWpu5u4mENEwHBy3LeT2f83r+4ds/H6aLfyfxP//x933Rto3j2F2U1ftYcDn4ct4LC523YSCJjDEexzQNKcXITGbW+h9p3ZL9BRkKLN20Z0ixm54Ts8Qu9gvsBFVY12rBzJxgzB7FY0DgfhNwH4bx+ngbY+rzJZBBtuHk4P1eL+3UL3MVNnQKtnlNW2vaTTGEJaaYUkophSD7ucSbldVGaO3A2iXj1svPXi55SbjtV6PN5qFv01/e5OYU5w7mFMKBORBRq/Xh4decV8I2E75QsndJLHYR1ic/uKf6AGyz+gvxmHalw6f3dsHvmIh3f3ja4JOdlcwXDgW9/OJLfP4B5PB5nr++/7onYnLznx7yuagQMYxhhEauTOh2l0SdC+37E32GWVwgTiIyOIAvuNL78/OWFu2LmU8yLB3CeOEdgjqG0kXo/WJu1v1dCd7lQEGEiR2YD8d379+P00REtZWfH38sdY0hiYReFLFX63DfEqXMLGEr4CW7t4fTi8ZZXtDfSxPpg7l3ktD+D9KW3+0cke7mhq5YCvspe6vbeS6XF4n+6iQQ0YYcm83T8d3th3GYtsby6Z7tNV7jNX4/If/7lNd4jdf4f4zXzv8ar/E7jd8AVpkBRR7vhwoAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<PIL.Image.Image image mode=RGB size=340x340 at 0x16A8FDFD0>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "height_width = 32\n",
+    "\n",
+    "def show_collage(examples):\n",
+    "    box_size = height_width + 2\n",
+    "    num_rows, num_cols = examples.shape[:2]\n",
+    "\n",
+    "    collage = Image.new(\n",
+    "        mode=\"RGB\",\n",
+    "        size=(num_cols * box_size, num_rows * box_size),\n",
+    "        color=(255, 255, 255),\n",
+    "    )\n",
+    "    for row_idx in range(num_rows):\n",
+    "        for col_idx in range(num_cols):\n",
+    "            array = (np.array(examples[row_idx, col_idx]) * 255).astype(np.uint8)\n",
+    "            array = array.transpose(1,2,0)\n",
+    "            collage.paste(\n",
+    "                Image.fromarray(array), (col_idx * box_size, row_idx * box_size)\n",
+    "            )\n",
+    "\n",
+    "    collage = collage.resize((2 * num_cols * box_size, 2 * num_rows * box_size))\n",
+    "    return collage\n",
+    "\n",
+    "sample_idxs = np.random.randint(0, 50000, size=(5, 5))\n",
+    "examples = x_train[sample_idxs]\n",
+    "show_collage(examples)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 构建训练数据\n",
+    "\n",
+    "图片检索的模型的训练样本跟我们常见的分类任务的训练样本不太一样的地方在于，每个训练样本并不是一个`(image, class)`这样的形式。而是（image0, image1, similary_or_not)的形式，即，每一个训练样本由两张图片组成，而其`label`是这两张图片是否相似的标志位（0或者1）。\n",
+    "\n",
+    "很自然的我们能够想到，来自同一个类别的两张图片，是相似的图片，而来自不同类别的两张图片，应该是不相似的图片。\n",
+    "\n",
+    "为了能够方便的抽样出相似图片（以及不相似图片）的样本，我们先建立能够根据类别找到该类别下所有图片的索引。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "-L3amT6BC1Jm"
+   },
+   "outputs": [],
+   "source": [
+    "class_idx_to_train_idxs = defaultdict(list)\n",
+    "for y_train_idx, y in enumerate(y_train):\n",
+    "    class_idx_to_train_idxs[y].append(y_train_idx)\n",
+    "\n",
+    "class_idx_to_test_idxs = defaultdict(list)\n",
+    "for y_test_idx, y in enumerate(y_test):\n",
+    "    class_idx_to_test_idxs[y].append(y_test_idx)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "有了上面的索引，我们就可以为飞桨准备一个读取数据的迭代器。该迭代器每次生成`2 * number of classes`张图片，在CIFAR10数据集中，这会是20张图片。前10张图片，和后10张图片，分别是10个类别中每个类别随机抽出的一张图片。这样，在实际的训练过程中，我们就会有10张相似的图片和90张不相似的图片（前10张图片中的任意一张图片，都与后10张的对应位置的1张图片相似，而与其他9张图片不相似）。\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "Bj3vLn2rC1Jq"
+   },
+   "outputs": [],
+   "source": [
+    "num_classes = 10\n",
+    "\n",
+    "def reader_creator(num_batchs):\n",
+    "    def reader():\n",
+    "        iter_step = 0\n",
+    "        while True:\n",
+    "            if iter_step >= num_batchs:\n",
+    "                break\n",
+    "            iter_step += 1\n",
+    "            x = np.empty((2, num_classes, 3, height_width, height_width), dtype=np.float32)\n",
+    "            for class_idx in range(num_classes):\n",
+    "                examples_for_class = class_idx_to_train_idxs[class_idx]\n",
+    "                anchor_idx = random.choice(examples_for_class)\n",
+    "                positive_idx = random.choice(examples_for_class)\n",
+    "                while positive_idx == anchor_idx:\n",
+    "                    positive_idx = random.choice(examples_for_class)\n",
+    "                x[0, class_idx] = x_train[anchor_idx]\n",
+    "                x[1, class_idx] = x_train[positive_idx]\n",
+    "            yield x\n",
+    "\n",
+    "    return reader\n",
+    "\n",
+    "\n",
+    "# num_batchs: how many batchs to generate\n",
+    "def anchor_positive_pairs(num_batchs=100):\n",
+    "    return reader_creator(num_batchs)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "zIxWRe9GC1Jt"
+   },
+   "outputs": [],
+   "source": [
+    "pairs_train_reader = anchor_positive_pairs(num_batchs=1000)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "拿出第一批次的图片，并可视化的展示出来，如下所示。（这样更容易理解训练样本的构成）"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 153
+    },
+    "colab_type": "code",
+    "id": "XeAYtBaSC1J1",
+    "outputId": "f8e3ed0e-3f91-4e07-d83a-9c398d59ba59",
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(2, 10, 3, 32, 32)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<PIL.Image.Image image mode=RGB size=680x136 at 0x16AFE2C90>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\n",
+    "examples = next(pairs_train_reader())\n",
+    "print(examples.shape)\n",
+    "show_collage(examples)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 把图片转换为高维的向量表示的网络\n",
+    "\n",
+    "我们的目标是首先把图片转换为高维空间的表示，然后计算图片在高维空间表示时的相似度。\n",
+    "下面的网络结构用来把一个形状为`(3, 32, 32)`的图片转换成形状为`(8,)`的向量。在有些资料中也会把这个转换成的向量称为`Embedding`，请注意，这与自然语言处理领域的词向量的区别。\n",
+    "下面的模型由三个连续的卷积加一个全局均值池化，然后用一个线性全链接层映射到维数为8的向量空间。为了后续计算余弦相似度时的便利，我们还在最后用[l2_normalize](https://www.paddlepaddle.org.cn/documentation/docs/zh/api_cn/layers_cn/l2_normalize_cn.html)做了归一化。（即，余弦相似度的分母部分）\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "QKurk9QAC1J8"
+   },
+   "outputs": [],
+   "source": [
+    "class MyNet(paddle.nn.Layer):\n",
+    "    def __init__(self):\n",
+    "        super(MyNet, self).__init__()\n",
+    "\n",
+    "        self.conv1 = paddle.nn.Conv2d(in_channels=3, \n",
+    "                                      out_channels=32, \n",
+    "                                      kernel_size=(3, 3),\n",
+    "                                      stride=2)\n",
+    "         \n",
+    "        self.conv2 = paddle.nn.Conv2d(in_channels=32, \n",
+    "                                      out_channels=64, \n",
+    "                                      kernel_size=(3,3), \n",
+    "                                      stride=2)       \n",
+    "        \n",
+    "        self.conv3 = paddle.nn.Conv2d(in_channels=64, \n",
+    "                                      out_channels=128, \n",
+    "                                      kernel_size=(3,3),\n",
+    "                                      stride=2)\n",
+    "       \n",
+    "        self.gloabl_pool = paddle.nn.AdaptiveAvgPool2d((1,1))\n",
+    "\n",
+    "        self.fc1 = paddle.nn.Linear(in_features=128, out_features=8)\n",
+    "    def forward(self, x):\n",
+    "        x = self.conv1(x)\n",
+    "        x = F.relu(x)\n",
+    "        x = self.conv2(x)\n",
+    "        x = F.relu(x)\n",
+    "        x = self.conv3(x)\n",
+    "        x = F.relu(x)\n",
+    "        x = self.gloabl_pool(x)\n",
+    "        x = paddle.squeeze(x, axis=[2, 3])\n",
+    "        x = self.fc1(x)\n",
+    "        x = F.l2_normalize(x, axis=1)\n",
+    "\n",
+    "        return x\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "在模型的训练过程中如下面的代码所示：\n",
+    "\n",
+    "- `inverse_temperature`参数起到的作用是让softmax在计算梯度时，能够处于梯度更显著的区域。（可以参考[attention is all you need](https://arxiv.org/abs/1706.03762)中，在点积之后的`scale`操作）。\n",
+    "- 整个计算过程，会先用上面的网络分别计算前10张图片（anchors)的高维表示，和后10张图片的高维表示。然后再用[matmul](https://www.paddlepaddle.org.cn/documentation/docs/zh/api_cn/layers_cn/matmul_cn.html)计算前10张图片分别与后10张图片的相似度。（所以`similarities`会是一个`(10, 10)`的Tensor）。\n",
+    "- 为[softmax_with_cross_entropy](https://www.paddlepaddle.org.cn/documentation/docs/zh/api_cn/layers_cn/softmax_with_cross_entropy_cn.html)构造类别标签时，则相应的，可以构造出来0 ~ num_classes的标签值，用来让学习的目标成为相似的图片的相似度尽可能的趋向于1.0，而不相似的图片的相似度尽可能的趋向于-1.0。\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "colab_type": "code",
+    "id": "v0qA9wX1C1KD",
+    "outputId": "e8d1b3bd-5412-4081-f30a-d2303b041578"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "start training ... \n",
+      "epoch: 0, batch_id: 0, loss is: [2.3080945]\n",
+      "epoch: 0, batch_id: 500, loss is: [2.326215]\n",
+      "epoch: 1, batch_id: 0, loss is: [2.0898924]\n",
+      "epoch: 1, batch_id: 500, loss is: [1.8754089]\n",
+      "epoch: 2, batch_id: 0, loss is: [2.2416227]\n",
+      "epoch: 2, batch_id: 500, loss is: [1.9024051]\n",
+      "epoch: 3, batch_id: 0, loss is: [1.841417]\n",
+      "epoch: 3, batch_id: 500, loss is: [2.1239076]\n",
+      "epoch: 4, batch_id: 0, loss is: [1.9291763]\n",
+      "epoch: 4, batch_id: 500, loss is: [2.2363486]\n",
+      "epoch: 5, batch_id: 0, loss is: [2.0078473]\n",
+      "epoch: 5, batch_id: 500, loss is: [2.0765374]\n",
+      "epoch: 6, batch_id: 0, loss is: [2.080376]\n",
+      "epoch: 6, batch_id: 500, loss is: [2.1759136]\n",
+      "epoch: 7, batch_id: 0, loss is: [1.908263]\n",
+      "epoch: 7, batch_id: 500, loss is: [1.7774136]\n",
+      "epoch: 8, batch_id: 0, loss is: [1.6335764]\n",
+      "epoch: 8, batch_id: 500, loss is: [1.5713912]\n",
+      "epoch: 9, batch_id: 0, loss is: [2.287479]\n",
+      "epoch: 9, batch_id: 500, loss is: [1.7719988]\n",
+      "epoch: 10, batch_id: 0, loss is: [1.2894523]\n",
+      "epoch: 10, batch_id: 500, loss is: [1.599735]\n",
+      "epoch: 11, batch_id: 0, loss is: [1.78816]\n",
+      "epoch: 11, batch_id: 500, loss is: [1.4773489]\n",
+      "epoch: 12, batch_id: 0, loss is: [1.6737808]\n",
+      "epoch: 12, batch_id: 500, loss is: [1.8889393]\n",
+      "epoch: 13, batch_id: 0, loss is: [1.6156021]\n",
+      "epoch: 13, batch_id: 500, loss is: [1.3851049]\n",
+      "epoch: 14, batch_id: 0, loss is: [1.3854092]\n",
+      "epoch: 14, batch_id: 500, loss is: [2.0325592]\n",
+      "epoch: 15, batch_id: 0, loss is: [1.9734558]\n",
+      "epoch: 15, batch_id: 500, loss is: [1.8050598]\n",
+      "epoch: 16, batch_id: 0, loss is: [1.7084911]\n",
+      "epoch: 16, batch_id: 500, loss is: [1.8919995]\n",
+      "epoch: 17, batch_id: 0, loss is: [1.3137552]\n",
+      "epoch: 17, batch_id: 500, loss is: [1.8817297]\n",
+      "epoch: 18, batch_id: 0, loss is: [1.9453808]\n",
+      "epoch: 18, batch_id: 500, loss is: [2.1317677]\n",
+      "epoch: 19, batch_id: 0, loss is: [1.6051079]\n",
+      "epoch: 19, batch_id: 500, loss is: [1.779858]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 定义训练过程\n",
+    "\n",
+    "def train(model):\n",
+    "    print('start training ... ')\n",
+    "    model.train()\n",
+    "\n",
+    "    inverse_temperature = paddle.to_tensor(np.array([1.0/0.2], dtype='float32'))\n",
+    "\n",
+    "    epoch_num = 20\n",
+    "    \n",
+    "    opt = paddle.optimizer.Adam(learning_rate=0.0001,\n",
+    "                                parameters=model.parameters())\n",
+    "    \n",
+    "    for epoch in range(epoch_num):\n",
+    "        for batch_id, data in enumerate(pairs_train_reader()):\n",
+    "            anchors_data, positives_data = data[0], data[1]\n",
+    "\n",
+    "            anchors = paddle.to_tensor(anchors_data)\n",
+    "            positives = paddle.to_tensor(positives_data)\n",
+    "            \n",
+    "            anchor_embeddings = model(anchors)\n",
+    "            positive_embeddings = model(positives)\n",
+    "      \n",
+    "            similarities = paddle.matmul(anchor_embeddings, positive_embeddings, transpose_y=True) \n",
+    "            similarities = paddle.multiply(similarities, inverse_temperature)\n",
+    "            \n",
+    "            sparse_labels = paddle.arange(0, num_classes, dtype='int64')\n",
+    "            sparse_labels = paddle.reshape(sparse_labels, (num_classes, 1))\n",
+    "\n",
+    "            loss = F.softmax_with_cross_entropy(similarities, sparse_labels)\n",
+    "            \n",
+    "            avg_loss = paddle.mean(loss)\n",
+    "            if batch_id % 500 == 0:\n",
+    "                print(\"epoch: {}, batch_id: {}, loss is: {}\".format(epoch, batch_id, avg_loss.numpy()))\n",
+    "            avg_loss.backward()\n",
+    "            opt.minimize(avg_loss)\n",
+    "            model.clear_gradients()\n",
+    "\n",
+    "model = MyNet()\n",
+    "train(model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "v2izWWI9PutF"
+   },
+   "source": [
+    "# 模型预测 \n",
+    "\n",
+    "前述的模型训练训练结束之后，我们就可以用该网络结构来计算出任意一张图片的高维向量表示（embedding)，通过计算该图片与图片库中其他图片的高维向量表示之间的相似度，就可以按照相似程度进行排序，排序越靠前，则相似程度越高。\n",
+    "\n",
+    "下面我们对测试集中所有的图片都两两计算相似度，然后选一部分相似的图片展示出来。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "IDE4kmUkPr_T"
+   },
+   "outputs": [],
+   "source": [
+    "near_neighbours_per_example = 10\n",
+    "\n",
+    "x_test_t = paddle.to_tensor(x_test)\n",
+    "test_images_embeddings = model(x_test_t)\n",
+    "similarities_matrix = paddle.matmul(test_images_embeddings, test_images_embeddings, transpose_y=True) \n",
+    "\n",
+    "indicies = paddle.argsort(similarities_matrix, descending=True)\n",
+    "indicies = indicies.numpy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "kgBsMRarC1KF"
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<PIL.Image.Image image mode=RGB size=748x680 at 0x16A29DE90>"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num_collage_examples = 10\n",
+    "\n",
+    "examples = np.empty(\n",
+    "    (\n",
+    "        num_collage_examples,\n",
+    "        near_neighbours_per_example + 1,\n",
+    "        3,\n",
+    "        height_width,\n",
+    "        height_width,\n",
+    "    ),\n",
+    "    dtype=np.float32,\n",
+    ")\n",
+    "for row_idx in range(num_collage_examples):\n",
+    "    examples[row_idx, 0] = x_test[row_idx]\n",
+    "    anchor_near_neighbours = indicies[row_idx][1:near_neighbours_per_example+1]\n",
+    "    for col_idx, nn_idx in enumerate(anchor_near_neighbours):\n",
+    "        examples[row_idx, col_idx + 1] = x_test[nn_idx]\n",
+    "\n",
+    "show_collage(examples)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 328
+    },
+    "colab_type": "code",
+    "id": "wrbuQDPHUBEi",
+    "outputId": "3f46eb46-fa8e-4b9c-e11f-f9bbb1abf2d5"
+   },
+   "source": [
+    "# The end\n",
+    "\n",
+    "上面展示的结果当中，每一行里其余的图片都是跟第一张图片按照相似度进行排序相似的图片。你也可以调整网络结构和超参数，以获得更好的结果。"
+   ]
+  }
+ ],
+ "metadata": {
+  "accelerator": "GPU",
+  "colab": {
+   "collapsed_sections": [],
+   "name": "metric_learning.ipynb",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/doc/paddle/tutorial/cv_case/image_search/image_search.rst b/doc/paddle/tutorial/cv_case/image_search/image_search.rst
new file mode 100644
index 0000000000000000000000000000000000000000..a4449ec99115f1b0a7542d1902548ffbeed4fdc7
--- /dev/null
+++ b/doc/paddle/tutorial/cv_case/image_search/image_search.rst
@@ -0,0 +1,407 @@
+基于图片相似度的图片搜索
+========================
+
+简要介绍
+--------
+
+图片搜索是一种有着广泛的应用场景的深度学习技术的应用，目前，无论是工程图纸的检索，还是互联网上相似图片的搜索，都基于深度学习算法能够实现很好的基于给定图片，检索出跟该图片相似的图片的效果。
+
+本示例简要介绍如何通过飞桨开源框架，实现图片搜索的功能。其基本思路是，先将图片使用卷积神经网络转换为高维空间的向量表示，然后计算两张图片的高维空间的向量表示之间的相似程度(本示例中，我们使用余弦相似度)。在模型训练阶段，其训练目标是让同一类别的图片的相似程度尽可能的高，不同类别的图片的相似程度尽可能的低。在模型预测阶段，对于用户上传的一张图片，会计算其与图片库中图片的相似程度，返回给用户按照相似程度由高到低的图片的列表作为检索的结果。
+
+环境设置
+--------
+
+本示例基于飞桨开源框架2.0版本。
+
+.. code:: ipython3
+
+    import paddle
+    import paddle.nn.functional as F
+    import numpy as np
+    import random
+    import matplotlib.pyplot as plt
+    from PIL import Image
+    from collections import defaultdict
+    
+    paddle.disable_static()
+    print(paddle.__version__)
+    print(paddle.__git_commit__)
+
+
+.. parsed-literal::
+
+    0.0.0
+    89af2088b6e74bdfeef2d4d78e08461ed2aafee5
+
+
+数据集
+------
+
+本示例采用\ `CIFAR-10 <https://www.cs.toronto.edu/~kriz/cifar.html>`__\ 数据集。这是一个经典的数据集，由50000张图片的训练数据，和10000张图片的测试数据组成，其中每张图片是一个RGB的长和宽都为32的图片。使用\ ``paddle.dataset.cifar``\ 可以方便的完成数据的下载工作，把数据归一化到\ ``(0, 1.0)``\ 区间内，并提供迭代器供按顺序访问数据。我们会把训练数据和测试数据分别存放在两个\ ``numpy``\ 数组中，供后面的训练和评估来使用。
+
+.. code:: ipython3
+
+    cifar10_train = paddle.vision.datasets.cifar.Cifar10(mode='train', transform=None)
+    x_train = np.zeros((50000, 3, 32, 32))
+    y_train = np.zeros((50000, 1), dtype='int32')
+    
+    for i in range(len(cifar10_train)):
+        train_image, train_label = cifar10_train[i]
+        train_image = train_image.reshape((3,32,32 ))
+        
+        # normalize the data
+        x_train[i,:, :, :] = train_image / 255.
+        y_train[i, 0] = train_label
+    
+    y_train = np.squeeze(y_train)
+    
+    print(x_train.shape)
+    print(y_train.shape)
+
+
+.. parsed-literal::
+
+    (50000, 3, 32, 32)
+    (50000,)
+
+
+.. code:: ipython3
+
+    cifar10_test = paddle.vision.datasets.cifar.Cifar10(mode='test', transform=None)
+    x_test = np.zeros((10000, 3, 32, 32), dtype='float32')
+    y_test = np.zeros((10000, 1), dtype='int64')
+    
+    for i in range(len(cifar10_test)):
+        test_image, test_label = cifar10_test[i]
+        test_image = test_image.reshape((3,32,32 )) 
+       
+        # normalize the data
+        x_test[i,:, :, :] = test_image / 255.
+        y_test[i, 0] = test_label
+    
+    y_test = np.squeeze(y_test)
+    
+    print(x_test.shape)
+    print(y_test.shape)
+
+
+.. parsed-literal::
+
+    (10000, 3, 32, 32)
+    (10000,)
+
+
+数据探索
+--------
+
+接下来我们随机从训练数据里找一些图片，浏览一下这些图片。
+
+.. code:: ipython3
+
+    height_width = 32
+    
+    def show_collage(examples):
+        box_size = height_width + 2
+        num_rows, num_cols = examples.shape[:2]
+    
+        collage = Image.new(
+            mode="RGB",
+            size=(num_cols * box_size, num_rows * box_size),
+            color=(255, 255, 255),
+        )
+        for row_idx in range(num_rows):
+            for col_idx in range(num_cols):
+                array = (np.array(examples[row_idx, col_idx]) * 255).astype(np.uint8)
+                array = array.transpose(1,2,0)
+                collage.paste(
+                    Image.fromarray(array), (col_idx * box_size, row_idx * box_size)
+                )
+    
+        collage = collage.resize((2 * num_cols * box_size, 2 * num_rows * box_size))
+        return collage
+    
+    sample_idxs = np.random.randint(0, 50000, size=(5, 5))
+    examples = x_train[sample_idxs]
+    show_collage(examples)
+
+
+
+
+.. image:: image_search_files/image_search_8_0.png
+
+
+
+构建训练数据
+--------------
+
+图片检索的模型的训练样本跟我们常见的分类任务的训练样本不太一样的地方在于，每个训练样本并不是一个\ ``(image, class)``\ 这样的形式。而是（image0,
+image1,
+similary_or_not)的形式，即，每一个训练样本由两张图片组成，而其\ ``label``\ 是这两张图片是否相似的标志位（0或者1）。
+
+很自然的我们能够想到，来自同一个类别的两张图片，是相似的图片，而来自不同类别的两张图片，应该是不相似的图片。
+
+为了能够方便的抽样出相似图片（以及不相似图片）的样本，我们先建立能够根据类别找到该类别下所有图片的索引。
+
+.. code:: ipython3
+
+    class_idx_to_train_idxs = defaultdict(list)
+    for y_train_idx, y in enumerate(y_train):
+        class_idx_to_train_idxs[y].append(y_train_idx)
+    
+    class_idx_to_test_idxs = defaultdict(list)
+    for y_test_idx, y in enumerate(y_test):
+        class_idx_to_test_idxs[y].append(y_test_idx)
+
+有了上面的索引，我们就可以为飞桨准备一个读取数据的迭代器。该迭代器每次生成\ ``2 * number of classes``\ 张图片，在CIFAR10数据集中，这会是20张图片。前10张图片，和后10张图片，分别是10个类别中每个类别随机抽出的一张图片。这样，在实际的训练过程中，我们就会有10张相似的图片和90张不相似的图片（前10张图片中的任意一张图片，都与后10张的对应位置的1张图片相似，而与其他9张图片不相似）。
+
+.. code:: ipython3
+
+    num_classes = 10
+    
+    def reader_creator(num_batchs):
+        def reader():
+            iter_step = 0
+            while True:
+                if iter_step >= num_batchs:
+                    break
+                iter_step += 1
+                x = np.empty((2, num_classes, 3, height_width, height_width), dtype=np.float32)
+                for class_idx in range(num_classes):
+                    examples_for_class = class_idx_to_train_idxs[class_idx]
+                    anchor_idx = random.choice(examples_for_class)
+                    positive_idx = random.choice(examples_for_class)
+                    while positive_idx == anchor_idx:
+                        positive_idx = random.choice(examples_for_class)
+                    x[0, class_idx] = x_train[anchor_idx]
+                    x[1, class_idx] = x_train[positive_idx]
+                yield x
+    
+        return reader
+    
+    
+    # num_batchs: how many batchs to generate
+    def anchor_positive_pairs(num_batchs=100):
+        return reader_creator(num_batchs)
+
+
+.. code:: ipython3
+
+    pairs_train_reader = anchor_positive_pairs(num_batchs=1000)
+
+拿出第一批次的图片，并可视化的展示出来，如下所示。（这样更容易理解训练样本的构成）
+
+.. code:: ipython3
+
+    
+    examples = next(pairs_train_reader())
+    print(examples.shape)
+    show_collage(examples)
+
+
+.. parsed-literal::
+
+    (2, 10, 3, 32, 32)
+
+
+
+
+.. image:: image_search_files/image_search_15_1.png
+
+
+
+把图片转换为高维的向量表示的网络
+-----------------------------------
+
+我们的目标是首先把图片转换为高维空间的表示，然后计算图片在高维空间表示时的相似度。
+下面的网络结构用来把一个形状为\ ``(3, 32, 32)``\ 的图片转换成形状为\ ``(8,)``\ 的向量。在有些资料中也会把这个转换成的向量称为\ ``Embedding``\ ，请注意，这与自然语言处理领域的词向量的区别。
+下面的模型由三个连续的卷积加一个全局均值池化，然后用一个线性全链接层映射到维数为8的向量空间。为了后续计算余弦相似度时的便利，我们还在最后用\ `l2_normalize <https://www.paddlepaddle.org.cn/documentation/docs/zh/api_cn/layers_cn/l2_normalize_cn.html>`__\ 做了归一化。（即，余弦相似度的分母部分）
+
+.. code:: ipython3
+
+    class MyNet(paddle.nn.Layer):
+        def __init__(self):
+            super(MyNet, self).__init__()
+    
+            self.conv1 = paddle.nn.Conv2d(in_channels=3, 
+                                          out_channels=32, 
+                                          kernel_size=(3, 3),
+                                          stride=2)
+             
+            self.conv2 = paddle.nn.Conv2d(in_channels=32, 
+                                          out_channels=64, 
+                                          kernel_size=(3,3), 
+                                          stride=2)       
+            
+            self.conv3 = paddle.nn.Conv2d(in_channels=64, 
+                                          out_channels=128, 
+                                          kernel_size=(3,3),
+                                          stride=2)
+           
+            self.gloabl_pool = paddle.nn.AdaptiveAvgPool2d((1,1))
+    
+            self.fc1 = paddle.nn.Linear(in_features=128, out_features=8)
+        def forward(self, x):
+            x = self.conv1(x)
+            x = F.relu(x)
+            x = self.conv2(x)
+            x = F.relu(x)
+            x = self.conv3(x)
+            x = F.relu(x)
+            x = self.gloabl_pool(x)
+            x = paddle.squeeze(x, axis=[2, 3])
+            x = self.fc1(x)
+            x = F.l2_normalize(x, axis=1)
+    
+            return x
+
+
+在模型的训练过程中如下面的代码所示：
+
+-  ``inverse_temperature``\ 参数起到的作用是让softmax在计算梯度时，能够处于梯度更显著的区域。（可以参考\ `attention
+   is all you
+   need <https://arxiv.org/abs/1706.03762>`__\ 中，在点积之后的\ ``scale``\ 操作）。
+-  整个计算过程，会先用上面的网络分别计算前10张图片（anchors)的高维表示，和后10张图片的高维表示。然后再用\ `matmul <https://www.paddlepaddle.org.cn/documentation/docs/zh/api_cn/layers_cn/matmul_cn.html>`__\ 计算前10张图片分别与后10张图片的相似度。（所以\ ``similarities``\ 会是一个\ ``(10, 10)``\ 的Tensor）。
+-  为\ `softmax_with_cross_entropy <https://www.paddlepaddle.org.cn/documentation/docs/zh/api_cn/layers_cn/softmax_with_cross_entropy_cn.html>`__\ 构造类别标签时，则相应的，可以构造出来0
+   ~
+   num_classes的标签值，用来让学习的目标成为相似的图片的相似度尽可能的趋向于1.0，而不相似的图片的相似度尽可能的趋向于-1.0。
+
+.. code:: ipython3
+
+    # 定义训练过程
+    
+    def train(model):
+        print('start training ... ')
+        model.train()
+    
+        inverse_temperature = paddle.to_tensor(np.array([1.0/0.2], dtype='float32'))
+    
+        epoch_num = 20
+        
+        opt = paddle.optimizer.Adam(learning_rate=0.0001,
+                                    parameters=model.parameters())
+        
+        for epoch in range(epoch_num):
+            for batch_id, data in enumerate(pairs_train_reader()):
+                anchors_data, positives_data = data[0], data[1]
+    
+                anchors = paddle.to_tensor(anchors_data)
+                positives = paddle.to_tensor(positives_data)
+                
+                anchor_embeddings = model(anchors)
+                positive_embeddings = model(positives)
+          
+                similarities = paddle.matmul(anchor_embeddings, positive_embeddings, transpose_y=True) 
+                similarities = paddle.multiply(similarities, inverse_temperature)
+                
+                sparse_labels = paddle.arange(0, num_classes, dtype='int64')
+                sparse_labels = paddle.reshape(sparse_labels, (num_classes, 1))
+    
+                loss = F.softmax_with_cross_entropy(similarities, sparse_labels)
+                
+                avg_loss = paddle.mean(loss)
+                if batch_id % 500 == 0:
+                    print("epoch: {}, batch_id: {}, loss is: {}".format(epoch, batch_id, avg_loss.numpy()))
+                avg_loss.backward()
+                opt.minimize(avg_loss)
+                model.clear_gradients()
+    
+    model = MyNet()
+    train(model)
+
+
+.. parsed-literal::
+
+    start training ... 
+    epoch: 0, batch_id: 0, loss is: [2.3080945]
+    epoch: 0, batch_id: 500, loss is: [2.326215]
+    epoch: 1, batch_id: 0, loss is: [2.0898924]
+    epoch: 1, batch_id: 500, loss is: [1.8754089]
+    epoch: 2, batch_id: 0, loss is: [2.2416227]
+    epoch: 2, batch_id: 500, loss is: [1.9024051]
+    epoch: 3, batch_id: 0, loss is: [1.841417]
+    epoch: 3, batch_id: 500, loss is: [2.1239076]
+    epoch: 4, batch_id: 0, loss is: [1.9291763]
+    epoch: 4, batch_id: 500, loss is: [2.2363486]
+    epoch: 5, batch_id: 0, loss is: [2.0078473]
+    epoch: 5, batch_id: 500, loss is: [2.0765374]
+    epoch: 6, batch_id: 0, loss is: [2.080376]
+    epoch: 6, batch_id: 500, loss is: [2.1759136]
+    epoch: 7, batch_id: 0, loss is: [1.908263]
+    epoch: 7, batch_id: 500, loss is: [1.7774136]
+    epoch: 8, batch_id: 0, loss is: [1.6335764]
+    epoch: 8, batch_id: 500, loss is: [1.5713912]
+    epoch: 9, batch_id: 0, loss is: [2.287479]
+    epoch: 9, batch_id: 500, loss is: [1.7719988]
+    epoch: 10, batch_id: 0, loss is: [1.2894523]
+    epoch: 10, batch_id: 500, loss is: [1.599735]
+    epoch: 11, batch_id: 0, loss is: [1.78816]
+    epoch: 11, batch_id: 500, loss is: [1.4773489]
+    epoch: 12, batch_id: 0, loss is: [1.6737808]
+    epoch: 12, batch_id: 500, loss is: [1.8889393]
+    epoch: 13, batch_id: 0, loss is: [1.6156021]
+    epoch: 13, batch_id: 500, loss is: [1.3851049]
+    epoch: 14, batch_id: 0, loss is: [1.3854092]
+    epoch: 14, batch_id: 500, loss is: [2.0325592]
+    epoch: 15, batch_id: 0, loss is: [1.9734558]
+    epoch: 15, batch_id: 500, loss is: [1.8050598]
+    epoch: 16, batch_id: 0, loss is: [1.7084911]
+    epoch: 16, batch_id: 500, loss is: [1.8919995]
+    epoch: 17, batch_id: 0, loss is: [1.3137552]
+    epoch: 17, batch_id: 500, loss is: [1.8817297]
+    epoch: 18, batch_id: 0, loss is: [1.9453808]
+    epoch: 18, batch_id: 500, loss is: [2.1317677]
+    epoch: 19, batch_id: 0, loss is: [1.6051079]
+    epoch: 19, batch_id: 500, loss is: [1.779858]
+
+
+模型预测
+--------
+
+前述的模型训练训练结束之后，我们就可以用该网络结构来计算出任意一张图片的高维向量表示（embedding)，通过计算该图片与图片库中其他图片的高维向量表示之间的相似度，就可以按照相似程度进行排序，排序越靠前，则相似程度越高。
+
+下面我们对测试集中所有的图片都两两计算相似度，然后选一部分相似的图片展示出来。
+
+.. code:: ipython3
+
+    near_neighbours_per_example = 10
+    
+    x_test_t = paddle.to_tensor(x_test)
+    test_images_embeddings = model(x_test_t)
+    similarities_matrix = paddle.matmul(test_images_embeddings, test_images_embeddings, transpose_y=True) 
+    
+    indicies = paddle.argsort(similarities_matrix, descending=True)
+    indicies = indicies.numpy()
+
+.. code:: ipython3
+
+    num_collage_examples = 10
+    
+    examples = np.empty(
+        (
+            num_collage_examples,
+            near_neighbours_per_example + 1,
+            3,
+            height_width,
+            height_width,
+        ),
+        dtype=np.float32,
+    )
+    for row_idx in range(num_collage_examples):
+        examples[row_idx, 0] = x_test[row_idx]
+        anchor_near_neighbours = indicies[row_idx][1:near_neighbours_per_example+1]
+        for col_idx, nn_idx in enumerate(anchor_near_neighbours):
+            examples[row_idx, col_idx + 1] = x_test[nn_idx]
+    
+    show_collage(examples)
+
+
+
+
+.. image:: image_search_files/image_search_22_0.png
+
+
+
+The end
+-------
+
+上面展示的结果当中，每一行里其余的图片都是跟第一张图片按照相似度进行排序相似的图片。你也可以调整网络结构和超参数，以获得更好的结果。
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diff --git a/doc/paddle/tutorial/cv_case/image_segmentation/pets_image_segmentation_U_Net_like.ipynb b/doc/paddle/tutorial/cv_case/image_segmentation/pets_image_segmentation_U_Net_like.ipynb
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+++ b/doc/paddle/tutorial/cv_case/image_segmentation/pets_image_segmentation_U_Net_like.ipynb
@@ -0,0 +1,981 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "ueGUN2EQeScw"
+   },
+   "source": [
+    "# 基于U型语义分割模型实现的宠物图像分割\n",
+    "\n",
+    "本示例教程当前是基于2.0-beta版本Paddle做的案例实现，未来会随着2.0的系列版本发布进行升级。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 1.简要介绍\n",
+    "\n",
+    "在计算机视觉领域，图像分割指的是将数字图像细分为多个图像子区域的过程。图像分割的目的是简化或改变图像的表示形式，使得图像更容易理解和分析。图像分割通常用于定位图像中的物体和边界（线，曲线等）。更精确的，图像分割是对图像中的每个像素加标签的一个过程，这一过程使得具有相同标签的像素具有某种共同视觉特性。图像分割的领域非常多，无人车、地块检测、表计识别等等。\n",
+    "\n",
+    "本示例简要介绍如何通过飞桨开源框架，实现图像分割。这里我们是采用了一个在图像分割领域比较熟知的U-Net网络结构，是一个基于FCN做改进后的一个深度学习网络，包含下采样（编码器，特征提取）和上采样（解码器，分辨率还原）两个阶段，因模型结构比较像U型而命名为U-Net。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2.环境设置\n",
+    "\n",
+    "导入一些比较基础常用的模块，确认自己的飞桨版本。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": "'0.0.0'"
+     },
+     "metadata": {},
+     "execution_count": 1
+    }
+   ],
+   "source": [
+    "import os\n",
+    "import io\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "from PIL import Image as PilImage\n",
+    "\n",
+    "import paddle\n",
+    "from paddle.nn import functional as F\n",
+    "\n",
+    "paddle.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "VMC2xLAxeScx"
+   },
+   "source": [
+    "## 3.数据集"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "H0KiJ_5N936Y"
+   },
+   "source": [
+    "### 3.1 数据集下载\n",
+    "\n",
+    "本案例使用Oxford-IIIT Pet数据集，官网：https://www.robots.ox.ac.uk/~vgg/data/pets 。\n",
+    "\n",
+    "数据集统计如下：\n",
+    "\n",
+    "![alt 数据集统计信息](https://www.robots.ox.ac.uk/~vgg/data/pets/breed_count.jpg)\n",
+    "\n",
+    "数据集包含两个压缩文件：\n",
+    "\n",
+    "1. 原图：https://www.robots.ox.ac.uk/~vgg/data/pets/data/images.tar.gz\n",
+    "2. 分割图像：https://www.robots.ox.ac.uk/~vgg/data/pets/data/annotations.tar.gz"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 119
+    },
+    "colab_type": "code",
+    "id": "xJd9y-u9eScy",
+    "outputId": "3985783f-7166-4afa-f511-16427b3e2a71",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "!curl -O http://www.robots.ox.ac.uk/~vgg/data/pets/data/images.tar.gz\n",
+    "!curl -O http://www.robots.ox.ac.uk/~vgg/data/pets/data/annotations.tar.gz\n",
+    "!tar -xf images.tar.gz\n",
+    "!tar -xf annotations.tar.gz"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "L5cP2CBz-Mra"
+   },
+   "source": [
+    "### 3.2 数据集概览\n",
+    "\n",
+    "首先我们先看看下载到磁盘上的文件结构是什么样，来了解一下我们的数据集。\n",
+    "\n",
+    "1. 首先看一下images.tar.gz这个压缩包，该文件解压后得到一个images目录，这个目录比较简单，里面直接放的是用类名和序号命名好的图片文件，每个图片是对应的宠物照片。\n",
+    "\n",
+    "```bash\n",
+    ".\n",
+    "├── samoyed_7.jpg\n",
+    "├── ......\n",
+    "└── samoyed_81.jpg\n",
+    "```\n",
+    "\n",
+    "2. 然后我们在看下annotations.tar.gz，文件解压后的目录里面包含以下内容，目录中的README文件将每个目录和文件做了比较详细的介绍，我们可以通过README来查看每个目录文件的说明。\n",
+    "\n",
+    "```bash\n",
+    ".\n",
+    "├── README\n",
+    "├── list.txt\n",
+    "├── test.txt\n",
+    "├── trainval.txt\n",
+    "├── trimaps\n",
+    "│    ├── Abyssinian_1.png\n",
+    "│    ├── Abyssinian_10.png\n",
+    "│    ├── ......\n",
+    "│    └── yorkshire_terrier_99.png\n",
+    "└── xmls\n",
+    "      ├── Abyssinian_1.xml\n",
+    "      ├── Abyssinian_10.xml\n",
+    "      ├── ......\n",
+    "      └── yorkshire_terrier_190.xml\n",
+    "```\n",
+    "\n",
+    "本次我们主要使用到images和annotations/trimaps两个目录，即原图和三元图像文件，前者作为训练的输入数据，后者是对应的标签数据。\n",
+    "\n",
+    "我们来看看这个数据集给我们提供了多少个训练样本。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 204
+    },
+    "colab_type": "code",
+    "id": "tqB7YQ4leSc4",
+    "outputId": "8872356c-ef32-4c94-defb-66250a00890a",
+    "tags": []
+   },
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": "用于训练的图片样本数量: 7390\n"
+    }
+   ],
+   "source": [
+    "train_images_path = \"images/\"\n",
+    "label_images_path = \"annotations/trimaps/\"\n",
+    "\n",
+    "print(\"用于训练的图片样本数量:\", len([os.path.join(train_images_path, image_name) \n",
+    "          for image_name in os.listdir(train_images_path) \n",
+    "          if image_name.endswith('.jpg')]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 3.3 数据集类定义\n",
+    "\n",
+    "飞桨（PaddlePaddle）数据集加载方案是统一使用Dataset（数据集定义） + DataLoader（多进程数据集加载）。\n",
+    "\n",
+    "首先我们先进行数据集的定义，数据集定义主要是实现一个新的Dataset类，继承父类paddle.io.Dataset，并实现父类中以下两个抽象方法，`__getitem__`和`__len__`：\n",
+    "\n",
+    "```python\n",
+    "class MyDataset(Dataset):\n",
+    "    def __init__(self):\n",
+    "        ...\n",
+    "        \n",
+    "    # 每次迭代时返回数据和对应的标签\n",
+    "    def __getitem__(self, idx):\n",
+    "        return x, y\n",
+    "\n",
+    "    # 返回整个数据集的总数\n",
+    "    def __len__(self):\n",
+    "        return count(samples)\n",
+    "```\n",
+    "\n",
+    "在数据集内部可以结合图像数据预处理相关API进行图像的预处理（改变大小、反转、调整格式等）。\n",
+    "\n",
+    "由于加载进来的图像不一定都符合自己的需求，举个例子，已下载的这些图片里面就会有RGBA格式的图片，这个时候图片就不符合我们所需3通道的需求，我们需要进行图片的格式转换，那么这里我们直接实现了一个通用的图片读取接口，确保读取出来的图片都是满足我们的需求。\n",
+    "\n",
+    "另外图片加载出来的默认shape是HWC，这个时候要看看是否满足后面训练的需要，如果Layer的默认格式和这个不是符合的情况下，需要看下Layer有没有参数可以进行格式调整。不过如果layer较多的话，还是直接调整原数据Shape比较好，否则每个layer都要做参数设置，如果有遗漏就会导致训练出错，那么在本案例中是直接对数据源的shape做了统一调整，从HWC转换成了CHW，因为飞桨的卷积等API的默认输入格式为CHW，这样处理方便后续模型训练。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import random\n",
+    "\n",
+    "from paddle.io import Dataset\n",
+    "from paddle.vision.transforms import transforms\n",
+    "\n",
+    "\n",
+    "class ImgTranspose(object):\n",
+    "    \"\"\"\n",
+    "    图像预处理工具，用于将Mask图像进行升维(160, 160) => (160, 160, 1)，\n",
+    "    并对图像的维度进行转换从HWC变为CHW\n",
+    "    \"\"\"\n",
+    "    def __init__(self, fmt):\n",
+    "        self.format = fmt\n",
+    "        \n",
+    "    def __call__(self, img):\n",
+    "        if len(img.shape) == 2:\n",
+    "            img = np.expand_dims(img, axis=2)\n",
+    "            \n",
+    "        return img.transpose(self.format)\n",
+    "\n",
+    "class PetDataset(Dataset):\n",
+    "    \"\"\"\n",
+    "    数据集定义\n",
+    "    \"\"\"\n",
+    "    def __init__(self, image_path, label_path, mode='train'):\n",
+    "        \"\"\"\n",
+    "        构造函数\n",
+    "        \"\"\"\n",
+    "        self.image_size = (160, 160)\n",
+    "        self.image_path = image_path\n",
+    "        self.label_path = label_path\n",
+    "        self.mode = mode.lower()\n",
+    "        self.eval_image_num = 1000\n",
+    "        \n",
+    "        assert self.mode in ['train', 'test'], \\\n",
+    "            \"mode should be 'train' or 'test', but got {}\".format(self.mode)\n",
+    "        \n",
+    "        self._parse_dataset()\n",
+    "        \n",
+    "        self.transforms = transforms.Compose([\n",
+    "            ImgTranspose((2, 0, 1))\n",
+    "        ])\n",
+    "        \n",
+    "    def _sort_images(self, image_dir, image_type):\n",
+    "        \"\"\"\n",
+    "        对文件夹内的图像进行按照文件名排序\n",
+    "        \"\"\"\n",
+    "        files = []\n",
+    "\n",
+    "        for image_name in os.listdir(image_dir):\n",
+    "            if image_name.endswith('.{}'.format(image_type)) \\\n",
+    "                    and not image_name.startswith('.'):\n",
+    "                files.append(os.path.join(image_dir, image_name))\n",
+    "\n",
+    "        return sorted(files)\n",
+    "        \n",
+    "    def _parse_dataset(self):\n",
+    "        \"\"\"\n",
+    "        由于所有文件都是散落在文件夹中，在训练时我们需要使用的是数据集和标签对应的数据关系，\n",
+    "        所以我们第一步是对原始的数据集进行整理，得到数据集和标签两个数组，分别一一对应。\n",
+    "        这样可以在使用的时候能够很方便的找到原始数据和标签的对应关系，否则对于原有的文件夹图片数据无法直接应用。\n",
+    "        在这里是用了一个非常简单的方法，按照文件名称进行排序。\n",
+    "        因为刚好数据和标签的文件名是按照这个逻辑制作的，名字都一样，只有扩展名不一样。\n",
+    "        \"\"\"\n",
+    "        temp_train_images = self._sort_images(self.image_path, 'jpg')\n",
+    "        temp_label_images = self._sort_images(self.label_path, 'png')\n",
+    "\n",
+    "        random.Random(1337).shuffle(temp_train_images)\n",
+    "        random.Random(1337).shuffle(temp_label_images)\n",
+    "        \n",
+    "        if self.mode == 'train':\n",
+    "            self.train_images = temp_train_images[:-self.eval_image_num]\n",
+    "            self.label_images = temp_label_images[:-self.eval_image_num]\n",
+    "        else:\n",
+    "            self.train_images = temp_train_images[-self.eval_image_num:]\n",
+    "            self.label_images = temp_label_images[-self.eval_image_num:]\n",
+    "    \n",
+    "    def _load_img(self, path, color_mode='rgb'):\n",
+    "        \"\"\"\n",
+    "        统一的图像处理接口封装，用于规整图像大小和通道\n",
+    "        \"\"\"\n",
+    "        with open(path, 'rb') as f:\n",
+    "            img = PilImage.open(io.BytesIO(f.read()))\n",
+    "            if color_mode == 'grayscale':\n",
+    "                # if image is not already an 8-bit, 16-bit or 32-bit grayscale image\n",
+    "                # convert it to an 8-bit grayscale image.\n",
+    "                if img.mode not in ('L', 'I;16', 'I'):\n",
+    "                    img = img.convert('L')\n",
+    "            elif color_mode == 'rgba':\n",
+    "                if img.mode != 'RGBA':\n",
+    "                    img = img.convert('RGBA')\n",
+    "            elif color_mode == 'rgb':\n",
+    "                if img.mode != 'RGB':\n",
+    "                    img = img.convert('RGB')\n",
+    "            else:\n",
+    "                raise ValueError('color_mode must be \"grayscale\", \"rgb\", or \"rgba\"')\n",
+    "\n",
+    "            if self.image_size is not None:\n",
+    "                if img.size != self.image_size:\n",
+    "                    img = img.resize(self.image_size, PilImage.NEAREST)\n",
+    "\n",
+    "            return img\n",
+    "\n",
+    "    def __getitem__(self, idx):\n",
+    "        \"\"\"\n",
+    "        返回 image, label\n",
+    "        \"\"\"\n",
+    "        # 花了比较多的时间在数据处理这里，需要处理成模型能适配的格式，踩了一些坑（比如有不是RGB格式的）\n",
+    "        # 有图片会出现通道数和期望不符的情况，需要进行相关考虑\n",
+    "\n",
+    "        # 加载原始图像\n",
+    "        train_image = self._load_img(self.train_images[idx])\n",
+    "        x = np.array(train_image, dtype='float32')\n",
+    "\n",
+    "        # 对图像进行预处理，统一大小，转换维度格式（HWC => CHW）\n",
+    "        x = self.transforms(x)\n",
+    "        \n",
+    "        # 加载Label图像\n",
+    "        label_image = self._load_img(self.label_images[idx], color_mode=\"grayscale\")  \n",
+    "        y = np.array(label_image, dtype='uint8')  \n",
+    "\n",
+    "        # 图像预处理\n",
+    "        # Label图像是二维的数组(size, size)，升维到(size, size, 1)后才能用于最后loss计算\n",
+    "        y = self.transforms(y)\n",
+    "        \n",
+    "        # 返回img, label，转换为需要的格式\n",
+    "        return x, y.astype('int64')\n",
+    "        \n",
+    "    def __len__(self):\n",
+    "        \"\"\"\n",
+    "        返回数据集总数\n",
+    "        \"\"\"\n",
+    "        return len(self.train_images)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "GYxTHfbBESSG"
+   },
+   "source": [
+    "### 3.4 PetDataSet数据集抽样展示\n",
+    "\n",
+    "实现好Dataset数据集后，我们来测试一下数据集是否符合预期，因为Dataset是一个可以被迭代的Class，我们通过for循环从里面读取数据来用matplotlib进行展示，这里要注意的是对于分割的标签文件因为是1通道的灰度图片，需要在使用imshow接口时注意下传参cmap='gray'。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 479
+    },
+    "colab_type": "code",
+    "id": "MTO-C5qFDnPn",
+    "outputId": "0937ed5e-1216-4773-9b54-16db8fe7b457"
+   },
+   "outputs": [
+    {
+     "output_type": "display_data",
+     "data": {
+      "text/plain": "<Figure size 432x288 with 2 Axes>",
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\n"
+     },
+     "metadata": {
+      "needs_background": "light"
+     }
+    }
+   ],
+   "source": [
+    "# 训练数据集\n",
+    "train_dataset = PetDataset(train_images_path, label_images_path, mode='train')\n",
+    "\n",
+    "# 验证数据集\n",
+    "val_dataset = PetDataset(train_images_path, label_images_path, mode='test')\n",
+    "\n",
+    "# 抽样一个数据\n",
+    "image, label = train_dataset[0]\n",
+    "\n",
+    "# 进行图片的展示\n",
+    "plt.figure()\n",
+    "\n",
+    "plt.subplot(1,2,1), \n",
+    "plt.title('Train Image')\n",
+    "plt.imshow(image.transpose((1, 2, 0)).astype('uint8'))\n",
+    "plt.axis('off')\n",
+    "\n",
+    "plt.subplot(1,2,2), \n",
+    "plt.title('Label')\n",
+    "plt.imshow(np.squeeze(label, axis=0).astype('uint8'), cmap='gray')\n",
+    "plt.axis('off')\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "d9JyZz3ZEnQ1"
+   },
+   "source": [
+    "## 4.模型组网\n",
+    "\n",
+    "U-Net是一个U型网络结构，可以看做两个大的阶段，图像先经过Encoder编码器进行下采样得到高级语义特征图，再经过Decoder解码器上采样将特征图恢复到原图片的分辨率。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "wi-ouGZL--BN"
+   },
+   "source": [
+    "### 4.1 定义SeparableConv2d接口\n",
+    "\n",
+    "我们为了减少卷积操作中的训练参数来提升性能，是继承paddle.nn.Layer自定义了一个SeparableConv2d Layer类，整个过程是把`filter_size * filter_size * num_filters`的Conv2d操作拆解为两个子Conv2d，先对输入数据的每个通道使用`filter_size * filter_size * 1`的卷积核进行计算，输入输出通道数目相同，之后在使用`1 * 1 * num_filters`的卷积核计算。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "0c-FikH-A4qP"
+   },
+   "outputs": [],
+   "source": [
+    "class SeparableConv2d(paddle.nn.Layer):\n",
+    "    def __init__(self, \n",
+    "                 in_channels, \n",
+    "                 out_channels, \n",
+    "                 kernel_size, \n",
+    "                 stride=1, \n",
+    "                 padding=0, \n",
+    "                 dilation=1, \n",
+    "                 groups=None, \n",
+    "                 weight_attr=None, \n",
+    "                 bias_attr=None, \n",
+    "                 data_format=\"NCHW\"):\n",
+    "        super(SeparableConv2d, self).__init__()\n",
+    "        # 第一次卷积操作没有偏置参数\n",
+    "        self.conv_1 = paddle.nn.Conv2d(in_channels, \n",
+    "                                       in_channels, \n",
+    "                                       kernel_size, \n",
+    "                                       stride=stride,\n",
+    "                                       padding=padding,\n",
+    "                                       dilation=dilation,\n",
+    "                                       groups=in_channels, \n",
+    "                                       weight_attr=weight_attr, \n",
+    "                                       bias_attr=False,  \n",
+    "                                       data_format=data_format)\n",
+    "        self.pointwise = paddle.nn.Conv2d(in_channels, \n",
+    "                                          out_channels, \n",
+    "                                          1, \n",
+    "                                          stride=1, \n",
+    "                                          padding=0, \n",
+    "                                          dilation=1, \n",
+    "                                          groups=1, \n",
+    "                                          weight_attr=weight_attr, \n",
+    "                                          data_format=data_format)\n",
+    "        \n",
+    "    def forward(self, inputs):\n",
+    "        y = self.conv_1(inputs)\n",
+    "        y = self.pointwise(y)\n",
+    "\n",
+    "        return y"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "zNyzlqQmBEEi"
+   },
+   "source": [
+    "### 4.2 定义Encoder编码器\n",
+    "\n",
+    "我们将网络结构中的Encoder下采样过程进行了一个Layer封装，方便后续调用，减少代码编写，下采样是有一个模型逐渐向下画曲线的一个过程，这个过程中是不断的重复一个单元结构将通道数不断增加，形状不断缩小，并且引入残差网络结构，我们将这些都抽象出来进行统一封装。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "OpUi9VUeGmXp"
+   },
+   "outputs": [],
+   "source": [
+    "class Encoder(paddle.nn.Layer):\n",
+    "    def __init__(self, in_channels, out_channels):\n",
+    "        super(Encoder, self).__init__()\n",
+    "        \n",
+    "        self.relu = paddle.nn.ReLU()\n",
+    "        self.separable_conv_01 = SeparableConv2d(in_channels, \n",
+    "                                                 out_channels, \n",
+    "                                                 kernel_size=3, \n",
+    "                                                 padding='same')\n",
+    "        self.bn = paddle.nn.BatchNorm2d(out_channels)\n",
+    "        self.separable_conv_02 = SeparableConv2d(out_channels, \n",
+    "                                                 out_channels, \n",
+    "                                                 kernel_size=3, \n",
+    "                                                 padding='same')\n",
+    "        self.pool = paddle.nn.MaxPool2d(kernel_size=3, stride=2, padding=1)\n",
+    "        self.residual_conv = paddle.nn.Conv2d(in_channels, \n",
+    "                                              out_channels, \n",
+    "                                              kernel_size=1, \n",
+    "                                              stride=2, \n",
+    "                                              padding='same')\n",
+    "\n",
+    "    def forward(self, inputs):\n",
+    "        previous_block_activation = inputs\n",
+    "        \n",
+    "        y = self.relu(inputs)\n",
+    "        y = self.separable_conv_01(y)\n",
+    "        y = self.bn(y)\n",
+    "        y = self.relu(y)\n",
+    "        y = self.separable_conv_02(y)\n",
+    "        y = self.bn(y)\n",
+    "        y = self.pool(y)\n",
+    "        \n",
+    "        residual = self.residual_conv(previous_block_activation)\n",
+    "        y = paddle.add(y, residual)\n",
+    "\n",
+    "        return y"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "nPBRD42WGmuH"
+   },
+   "source": [
+    "### 4.3 定义Decoder解码器\n",
+    "\n",
+    "在通道数达到最大得到高级语义特征图后，网络结构会开始进行decode操作，进行上采样，通道数逐渐减小，对应图片尺寸逐步增加，直至恢复到原图像大小，那么这个过程里面也是通过不断的重复相同结构的残差网络完成，我们也是为了减少代码编写，将这个过程定义一个Layer来放到模型组网中使用。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "ltVurq8OGvK7"
+   },
+   "outputs": [],
+   "source": [
+    "class Decoder(paddle.nn.Layer):\n",
+    "    def __init__(self, in_channels, out_channels):\n",
+    "        super(Decoder, self).__init__()\n",
+    "\n",
+    "        self.relu = paddle.nn.ReLU()\n",
+    "        self.conv_transpose_01 = paddle.nn.ConvTranspose2d(in_channels, \n",
+    "                                                           out_channels, \n",
+    "                                                           kernel_size=3, \n",
+    "                                                           padding='same')\n",
+    "        self.conv_transpose_02 = paddle.nn.ConvTranspose2d(out_channels, \n",
+    "                                                           out_channels, \n",
+    "                                                           kernel_size=3, \n",
+    "                                                           padding='same')\n",
+    "        self.bn = paddle.nn.BatchNorm2d(out_channels)\n",
+    "        self.upsample = paddle.nn.UpSample(scale_factor=2.0)\n",
+    "        self.residual_conv = paddle.nn.Conv2d(in_channels, \n",
+    "                                              out_channels, \n",
+    "                                              kernel_size=1, \n",
+    "                                              padding='same')\n",
+    "\n",
+    "    def forward(self, inputs):\n",
+    "        previous_block_activation = inputs\n",
+    "\n",
+    "        y = self.relu(inputs)\n",
+    "        y = self.conv_transpose_01(y)\n",
+    "        y = self.bn(y)\n",
+    "        y = self.relu(y)\n",
+    "        y = self.conv_transpose_02(y)\n",
+    "        y = self.bn(y)\n",
+    "        y = self.upsample(y)\n",
+    "        \n",
+    "        residual = self.upsample(previous_block_activation)\n",
+    "        residual = self.residual_conv(residual)\n",
+    "        \n",
+    "        y = paddle.add(y, residual)\n",
+    "        \n",
+    "        return y"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "vLKLj2FMGvdc"
+   },
+   "source": [
+    "### 4.4 训练模型组网\n",
+    "\n",
+    "按照U型网络结构格式进行整体的网络结构搭建，三次下采样，四次上采样。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "an1YFILpG4Xy"
+   },
+   "outputs": [],
+   "source": [
+    "class PetModel(paddle.nn.Layer):\n",
+    "    def __init__(self, num_classes):\n",
+    "        super(PetModel, self).__init__()\n",
+    "\n",
+    "        self.conv_1 = paddle.nn.Conv2d(3, 32, \n",
+    "                                       kernel_size=3,\n",
+    "                                       stride=2,\n",
+    "                                       padding='same')\n",
+    "        self.bn = paddle.nn.BatchNorm2d(32)\n",
+    "        self.relu = paddle.nn.ReLU()\n",
+    "\n",
+    "        in_channels = 32\n",
+    "        self.encoders = []\n",
+    "        self.encoder_list = [64, 128, 256]\n",
+    "        self.decoder_list = [256, 128, 64, 32]\n",
+    "\n",
+    "        # 根据下采样个数和配置循环定义子Layer，避免重复写一样的程序\n",
+    "        for out_channels in self.encoder_list:\n",
+    "            block = self.add_sublayer('encoder_%s'.format(out_channels),\n",
+    "                                      Encoder(in_channels, out_channels))\n",
+    "            self.encoders.append(block)\n",
+    "            in_channels = out_channels\n",
+    "\n",
+    "        self.decoders = []\n",
+    "\n",
+    "        # 根据上采样个数和配置循环定义子Layer，避免重复写一样的程序\n",
+    "        for out_channels in self.decoder_list:\n",
+    "            block = self.add_sublayer('decoder_%s'.format(out_channels), \n",
+    "                                      Decoder(in_channels, out_channels))\n",
+    "            self.decoders.append(block)\n",
+    "            in_channels = out_channels\n",
+    "\n",
+    "        self.output_conv = paddle.nn.Conv2d(in_channels, \n",
+    "                                            num_classes, \n",
+    "                                            kernel_size=3, \n",
+    "                                            padding='same')\n",
+    "    \n",
+    "    def forward(self, inputs):\n",
+    "        y = self.conv_1(inputs)\n",
+    "        y = self.bn(y)\n",
+    "        y = self.relu(y)\n",
+    "        \n",
+    "        for encoder in self.encoders:\n",
+    "            y = encoder(y)\n",
+    "\n",
+    "        for decoder in self.decoders:\n",
+    "            y = decoder(y)\n",
+    "        \n",
+    "        y = self.output_conv(y)\n",
+    "        \n",
+    "        return y"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "6Nf7hQ60G4sj"
+   },
+   "source": [
+    "### 4.5 模型可视化\n",
+    "\n",
+    "调用飞桨提供的summary接口对组建好的模型进行可视化，方便进行模型结构和参数信息的查看和确认。\n",
+    "@TODO，需要替换"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "colab_type": "code",
+    "id": "1_MXfWkZeSdE",
+    "outputId": "4c9870de-9eb6-47e8-e88c-79509ef78cf5",
+    "tags": []
+   },
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": "--------------------------------------------------------------------------------\n   Layer (type)          Input Shape         Output Shape         Param #\n================================================================================\n      Conv2d-22    [-1, 3, 160, 160]     [-1, 32, 80, 80]             896\n  BatchNorm2d-9     [-1, 32, 80, 80]     [-1, 32, 80, 80]              64\n         ReLU-9     [-1, 32, 80, 80]     [-1, 32, 80, 80]               0\n        ReLU-12    [-1, 256, 20, 20]    [-1, 256, 20, 20]               0\n      Conv2d-33    [-1, 128, 20, 20]    [-1, 128, 20, 20]           1,152\n      Conv2d-34    [-1, 128, 20, 20]    [-1, 256, 20, 20]          33,024\nSeparableConv2d-11    [-1, 128, 20, 20]    [-1, 256, 20, 20]               0\n BatchNorm2d-12    [-1, 256, 20, 20]    [-1, 256, 20, 20]             512\n      Conv2d-35    [-1, 256, 20, 20]    [-1, 256, 20, 20]           2,304\n      Conv2d-36    [-1, 256, 20, 20]    [-1, 256, 20, 20]          65,792\nSeparableConv2d-12    [-1, 256, 20, 20]    [-1, 256, 20, 20]               0\n    MaxPool2d-6    [-1, 256, 20, 20]    [-1, 256, 10, 10]               0\n      Conv2d-37    [-1, 128, 20, 20]    [-1, 256, 10, 10]          33,024\n      Encoder-6    [-1, 128, 20, 20]    [-1, 256, 10, 10]               0\n        ReLU-16     [-1, 32, 80, 80]     [-1, 32, 80, 80]               0\nConvTranspose2d-15     [-1, 64, 80, 80]     [-1, 32, 80, 80]          18,464\n BatchNorm2d-16     [-1, 32, 80, 80]     [-1, 32, 80, 80]              64\nConvTranspose2d-16     [-1, 32, 80, 80]     [-1, 32, 80, 80]           9,248\n     UpSample-8     [-1, 64, 80, 80]   [-1, 64, 160, 160]               0\n      Conv2d-41   [-1, 64, 160, 160]   [-1, 32, 160, 160]           2,080\n      Decoder-8     [-1, 64, 80, 80]   [-1, 32, 160, 160]               0\n      Conv2d-42   [-1, 32, 160, 160]    [-1, 4, 160, 160]           1,156\n================================================================================\nTotal params: 167,780\nTrainable params: 167,780\nNon-trainable params: 0\n--------------------------------------------------------------------------------\nInput size (MB): 0.29\nForward/backward pass size (MB): 43.16\nParams size (MB): 0.64\nEstimated Total Size (MB): 44.10\n--------------------------------------------------------------------------------\n\n"
+    },
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": "{'total_params': 167780, 'trainable_params': 167780}"
+     },
+     "metadata": {},
+     "execution_count": 11
+    }
+   ],
+   "source": [
+    "from paddle.static import InputSpec\n",
+    "\n",
+    "paddle.disable_static()\n",
+    "num_classes = 4\n",
+    "model = paddle.Model(PetModel(num_classes))\n",
+    "model.summary((3, 160, 160))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "j9Trlcvj8R7L"
+   },
+   "source": [
+    "## 5.模型训练"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "8Sskbyz58X4J"
+   },
+   "source": [
+    "### 5.1 配置信息\n",
+    "\n",
+    "定义训练BATCH_SIZE、训练轮次和计算设备等信息。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "4fSkTiRB8OpP"
+   },
+   "outputs": [],
+   "source": [
+    "BATCH_SIZE = 32\n",
+    "EPOCHS = 15\n",
+    "device = paddle.set_device('gpu')\n",
+    "paddle.disable_static(device)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "x_vaedRa8eoy"
+   },
+   "source": [
+    "### 5.3 自定义Loss\n",
+    "\n",
+    "在这个任务中我们使用SoftmaxWithCrossEntropy损失函数来做计算，飞桨中有functional形式的API，这里我们做一个自定义操作，实现一个Class形式API放到模型训练中使用。没有直接使用CrossEntropyLoss的原因主要是对计算维度的自定义需求，本次需要进行softmax计算的维度是1，不是默认的最后一维，所以我们采用上面提到的损失函数，通过axis参数来指定softmax计算维度。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "AEZq_jT78jNe"
+   },
+   "outputs": [],
+   "source": [
+    "class SoftmaxWithCrossEntropy(paddle.nn.Layer):\n",
+    "    def __init__(self):\n",
+    "        super(SoftmaxWithCrossEntropy, self).__init__()\n",
+    "\n",
+    "    def forward(self, input, label):\n",
+    "        loss = F.softmax_with_cross_entropy(input, \n",
+    "                                            label, \n",
+    "                                            return_softmax=False,\n",
+    "                                            axis=1)\n",
+    "        return paddle.mean(loss)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "rj6MPPMkJIdZ"
+   },
+   "source": [
+    "### 5.4 启动模型训练\n",
+    "\n",
+    "使用模型代码进行Model实例生成，使用prepare接口定义优化器、损失函数和评价指标等信息，用于后续训练使用。在所有初步配置完成后，调用fit接口开启训练执行过程，调用fit时只需要将前面定义好的训练数据集、测试数据集、训练轮次（Epoch）和批次大小（batch_size）配置好即可。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 51
+    },
+    "colab_type": "code",
+    "id": "m-cVyjNreSdO",
+    "outputId": "9b37dd07-746b-41cc-c8e2-687a83b1ad75",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "optim = paddle.optimizer.RMSProp(learning_rate=0.001, \n",
+    "                                 rho=0.9, \n",
+    "                                 momentum=0.0, \n",
+    "                                 epsilon=1e-07, \n",
+    "                                 centered=False,\n",
+    "                                 parameters=model.parameters())\n",
+    "model = paddle.Model(PetModel(num_classes, model_tools))\n",
+    "model.prepare(optim, \n",
+    "              SoftmaxWithCrossEntropy())\n",
+    "\n",
+    "model.fit(train_dataset, \n",
+    "    val_dataset, \n",
+    "    epochs=EPOCHS, \n",
+    "    batch_size=BATCH_SIZE\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "-mouwS1kJRqJ"
+   },
+   "source": [
+    "## 6.模型预测"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "Dvjxu91DJd1G"
+   },
+   "source": [
+    "### 6.1 预测数据集准备和预测\n",
+    "\n",
+    "继续使用PetDataset来实例化待预测使用的数据集。这里我们为了方便没有在另外准备预测数据，复用了评估数据。\n",
+    "\n",
+    "我们可以直接使用model.predict接口来对数据集进行预测操作，只需要将预测数据集传递到接口内即可。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "Ur088_vjeSdR"
+   },
+   "outputs": [],
+   "source": [
+    "predict_results = model.predict(val_dataset)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "-DpAEFBSJioy"
+   },
+   "source": [
+    "### 6.2 预测结果可视化\n",
+    "\n",
+    "从我们的预测数据集中抽3个动物来看看预测的效果，展示一下原图、标签图和预测结果。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "1mfaFkO5S1PU"
+   },
+   "outputs": [],
+   "source": [
+    "plt.figure(figsize=(10, 10))\n",
+    "\n",
+    "i = 0\n",
+    "mask_idx = 0\n",
+    "\n",
+    "for data in val_dataset:\n",
+    "    if i > 8: \n",
+    "        break\n",
+    "    plt.subplot(3, 3, i + 1)\n",
+    "    plt.imshow(data[0].transpose((1, 2, 0)).astype('uint8'))\n",
+    "    plt.title('Input Image')\n",
+    "    plt.axis(\"off\")\n",
+    "\n",
+    "    plt.subplot(3, 3, i + 2)\n",
+    "    plt.imshow(np.squeeze(data[1], axis=0).astype('uint8'), cmap='gray')\n",
+    "    plt.title('Label')\n",
+    "    plt.axis(\"off\")\n",
+    "    \n",
+    "    \n",
+    "    data = val_preds[0][mask_idx][0].transpose((1, 2, 0))\n",
+    "    mask = np.argmax(data, axis=-1)\n",
+    "    mask = np.expand_dims(mask, axis=-1)\n",
+    "\n",
+    "    plt.subplot(3, 3, i + 3)\n",
+    "    plt.imshow(np.squeeze(mask, axis=2).astype('uint8'), cmap='gray')\n",
+    "    plt.title('Predict')\n",
+    "    plt.axis(\"off\")\n",
+    "    i += 3\n",
+    "    mask_idx += 1\n",
+    "\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "accelerator": "GPU",
+  "colab": {
+   "collapsed_sections": [],
+   "name": "pets_image_segmentation_U_Net_like.ipynb",
+   "provenance": [],
+   "toc_visible": true
+  },
+  "kernelspec": {
+   "display_name": "Python 3.7.4 64-bit",
+   "language": "python",
+   "name": "python_defaultSpec_1599452401282"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4-final"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
\ No newline at end of file
diff --git a/doc/paddle/tutorial/cv_case/image_segmentation/pets_image_segmentation_U_Net_like.rst b/doc/paddle/tutorial/cv_case/image_segmentation/pets_image_segmentation_U_Net_like.rst
new file mode 100644
index 0000000000000000000000000000000000000000..09d13b579b307e285cbb872b530030f3a267316b
--- /dev/null
+++ b/doc/paddle/tutorial/cv_case/image_segmentation/pets_image_segmentation_U_Net_like.rst
@@ -0,0 +1,693 @@
+基于U型语义分割模型实现的宠物图像分割
+=====================================
+
+本示例教程当前是基于2.0-beta版本Paddle做的案例实现，未来会随着2.0的系列版本发布进行升级。
+
+1.简要介绍
+----------
+
+在计算机视觉领域，图像分割指的是将数字图像细分为多个图像子区域的过程。图像分割的目的是简化或改变图像的表示形式，使得图像更容易理解和分析。图像分割通常用于定位图像中的物体和边界（线，曲线等）。更精确的，图像分割是对图像中的每个像素加标签的一个过程，这一过程使得具有相同标签的像素具有某种共同视觉特性。图像分割的领域非常多，无人车、地块检测、表计识别等等。
+
+本示例简要介绍如何通过飞桨开源框架，实现图像分割。这里我们是采用了一个在图像分割领域比较熟知的U-Net网络结构，是一个基于FCN做改进后的一个深度学习网络，包含下采样（编码器，特征提取）和上采样（解码器，分辨率还原）两个阶段，因模型结构比较像U型而命名为U-Net。
+
+2.环境设置
+----------
+
+导入一些比较基础常用的模块，确认自己的飞桨版本。
+
+.. code:: ipython3
+
+    import os
+    import io
+    import numpy as np
+    import matplotlib.pyplot as plt
+    from PIL import Image as PilImage
+    
+    import paddle
+    from paddle.nn import functional as F
+    
+    paddle.__version__
+
+
+
+
+.. parsed-literal::
+
+    '0.0.0'
+
+
+
+3.数据集
+--------
+
+3.1 数据集下载
+~~~~~~~~~~~~~~
+
+本案例使用Oxford-IIIT
+Pet数据集，官网：https://www.robots.ox.ac.uk/~vgg/data/pets 。
+
+数据集统计如下：
+
+.. figure:: https://www.robots.ox.ac.uk/~vgg/data/pets/breed_count.jpg
+   :alt: alt 数据集统计信息
+
+   alt 数据集统计信息
+
+数据集包含两个压缩文件：
+
+1. 原图：https://www.robots.ox.ac.uk/~vgg/data/pets/data/images.tar.gz
+2. 分割图像：https://www.robots.ox.ac.uk/~vgg/data/pets/data/annotations.tar.gz
+
+.. code:: ipython3
+
+    !curl -O http://www.robots.ox.ac.uk/~vgg/data/pets/data/images.tar.gz
+    !curl -O http://www.robots.ox.ac.uk/~vgg/data/pets/data/annotations.tar.gz
+    !tar -xf images.tar.gz
+    !tar -xf annotations.tar.gz
+
+3.2 数据集概览
+~~~~~~~~~~~~~~
+
+首先我们先看看下载到磁盘上的文件结构是什么样，来了解一下我们的数据集。
+
+1. 首先看一下images.tar.gz这个压缩包，该文件解压后得到一个images目录，这个目录比较简单，里面直接放的是用类名和序号命名好的图片文件，每个图片是对应的宠物照片。
+
+.. code:: bash
+
+   .
+   ├── samoyed_7.jpg
+   ├── ......
+   └── samoyed_81.jpg
+
+2. 然后我们在看下annotations.tar.gz，文件解压后的目录里面包含以下内容，目录中的README文件将每个目录和文件做了比较详细的介绍，我们可以通过README来查看每个目录文件的说明。
+
+.. code:: bash
+
+   .
+   ├── README
+   ├── list.txt
+   ├── test.txt
+   ├── trainval.txt
+   ├── trimaps
+   │    ├── Abyssinian_1.png
+   │    ├── Abyssinian_10.png
+   │    ├── ......
+   │    └── yorkshire_terrier_99.png
+   └── xmls
+         ├── Abyssinian_1.xml
+         ├── Abyssinian_10.xml
+         ├── ......
+         └── yorkshire_terrier_190.xml
+
+本次我们主要使用到images和annotations/trimaps两个目录，即原图和三元图像文件，前者作为训练的输入数据，后者是对应的标签数据。
+
+我们来看看这个数据集给我们提供了多少个训练样本。
+
+.. code:: ipython3
+
+    train_images_path = "images/"
+    label_images_path = "annotations/trimaps/"
+    
+    print("用于训练的图片样本数量:", len([os.path.join(train_images_path, image_name) 
+              for image_name in os.listdir(train_images_path) 
+              if image_name.endswith('.jpg')]))
+
+
+.. parsed-literal::
+
+    用于训练的图片样本数量: 7390
+
+
+3.3 数据集类定义
+~~~~~~~~~~~~~~~~
+
+飞桨（PaddlePaddle）数据集加载方案是统一使用Dataset（数据集定义） +
+DataLoader（多进程数据集加载）。
+
+首先我们先进行数据集的定义，数据集定义主要是实现一个新的Dataset类，继承父类paddle.io.Dataset，并实现父类中以下两个抽象方法，\ ``__getitem__``\ 和\ ``__len__``\ ：
+
+.. code:: python
+
+   class MyDataset(Dataset):
+       def __init__(self):
+           ...
+           
+       # 每次迭代时返回数据和对应的标签
+       def __getitem__(self, idx):
+           return x, y
+
+       # 返回整个数据集的总数
+       def __len__(self):
+           return count(samples)
+
+在数据集内部可以结合图像数据预处理相关API进行图像的预处理（改变大小、反转、调整格式等）。
+
+由于加载进来的图像不一定都符合自己的需求，举个例子，已下载的这些图片里面就会有RGBA格式的图片，这个时候图片就不符合我们所需3通道的需求，我们需要进行图片的格式转换，那么这里我们直接实现了一个通用的图片读取接口，确保读取出来的图片都是满足我们的需求。
+
+另外图片加载出来的默认shape是HWC，这个时候要看看是否满足后面训练的需要，如果Layer的默认格式和这个不是符合的情况下，需要看下Layer有没有参数可以进行格式调整。不过如果layer较多的话，还是直接调整原数据Shape比较好，否则每个layer都要做参数设置，如果有遗漏就会导致训练出错，那么在本案例中是直接对数据源的shape做了统一调整，从HWC转换成了CHW，因为飞桨的卷积等API的默认输入格式为CHW，这样处理方便后续模型训练。
+
+.. code:: ipython3
+
+    import random
+    
+    from paddle.io import Dataset
+    from paddle.vision.transforms import transforms
+    
+    
+    class ImgTranspose(object):
+        """
+        图像预处理工具，用于将Mask图像进行升维(160, 160) => (160, 160, 1)，
+        并对图像的维度进行转换从HWC变为CHW
+        """
+        def __init__(self, fmt):
+            self.format = fmt
+            
+        def __call__(self, img):
+            if len(img.shape) == 2:
+                img = np.expand_dims(img, axis=2)
+                
+            return img.transpose(self.format)
+    
+    class PetDataset(Dataset):
+        """
+        数据集定义
+        """
+        def __init__(self, image_path, label_path, mode='train'):
+            """
+            构造函数
+            """
+            self.image_size = (160, 160)
+            self.image_path = image_path
+            self.label_path = label_path
+            self.mode = mode.lower()
+            self.eval_image_num = 1000
+            
+            assert self.mode in ['train', 'test'], \
+                "mode should be 'train' or 'test', but got {}".format(self.mode)
+            
+            self._parse_dataset()
+            
+            self.transforms = transforms.Compose([
+                ImgTranspose((2, 0, 1))
+            ])
+            
+        def _sort_images(self, image_dir, image_type):
+            """
+            对文件夹内的图像进行按照文件名排序
+            """
+            files = []
+    
+            for image_name in os.listdir(image_dir):
+                if image_name.endswith('.{}'.format(image_type)) \
+                        and not image_name.startswith('.'):
+                    files.append(os.path.join(image_dir, image_name))
+    
+            return sorted(files)
+            
+        def _parse_dataset(self):
+            """
+            由于所有文件都是散落在文件夹中，在训练时我们需要使用的是数据集和标签对应的数据关系，
+            所以我们第一步是对原始的数据集进行整理，得到数据集和标签两个数组，分别一一对应。
+            这样可以在使用的时候能够很方便的找到原始数据和标签的对应关系，否则对于原有的文件夹图片数据无法直接应用。
+            在这里是用了一个非常简单的方法，按照文件名称进行排序。
+            因为刚好数据和标签的文件名是按照这个逻辑制作的，名字都一样，只有扩展名不一样。
+            """
+            temp_train_images = self._sort_images(self.image_path, 'jpg')
+            temp_label_images = self._sort_images(self.label_path, 'png')
+    
+            random.Random(1337).shuffle(temp_train_images)
+            random.Random(1337).shuffle(temp_label_images)
+            
+            if self.mode == 'train':
+                self.train_images = temp_train_images[:-self.eval_image_num]
+                self.label_images = temp_label_images[:-self.eval_image_num]
+            else:
+                self.train_images = temp_train_images[-self.eval_image_num:]
+                self.label_images = temp_label_images[-self.eval_image_num:]
+        
+        def _load_img(self, path, color_mode='rgb'):
+            """
+            统一的图像处理接口封装，用于规整图像大小和通道
+            """
+            with open(path, 'rb') as f:
+                img = PilImage.open(io.BytesIO(f.read()))
+                if color_mode == 'grayscale':
+                    # if image is not already an 8-bit, 16-bit or 32-bit grayscale image
+                    # convert it to an 8-bit grayscale image.
+                    if img.mode not in ('L', 'I;16', 'I'):
+                        img = img.convert('L')
+                elif color_mode == 'rgba':
+                    if img.mode != 'RGBA':
+                        img = img.convert('RGBA')
+                elif color_mode == 'rgb':
+                    if img.mode != 'RGB':
+                        img = img.convert('RGB')
+                else:
+                    raise ValueError('color_mode must be "grayscale", "rgb", or "rgba"')
+    
+                if self.image_size is not None:
+                    if img.size != self.image_size:
+                        img = img.resize(self.image_size, PilImage.NEAREST)
+    
+                return img
+    
+        def __getitem__(self, idx):
+            """
+            返回 image, label
+            """
+            # 花了比较多的时间在数据处理这里，需要处理成模型能适配的格式，踩了一些坑（比如有不是RGB格式的）
+            # 有图片会出现通道数和期望不符的情况，需要进行相关考虑
+    
+            # 加载原始图像
+            train_image = self._load_img(self.train_images[idx])
+            x = np.array(train_image, dtype='float32')
+    
+            # 对图像进行预处理，统一大小，转换维度格式（HWC => CHW）
+            x = self.transforms(x)
+            
+            # 加载Label图像
+            label_image = self._load_img(self.label_images[idx], color_mode="grayscale")  
+            y = np.array(label_image, dtype='uint8')  
+    
+            # 图像预处理
+            # Label图像是二维的数组(size, size)，升维到(size, size, 1)后才能用于最后loss计算
+            y = self.transforms(y)
+            
+            # 返回img, label，转换为需要的格式
+            return x, y.astype('int64')
+            
+        def __len__(self):
+            """
+            返回数据集总数
+            """
+            return len(self.train_images)
+
+3.4 PetDataSet数据集抽样展示
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+实现好Dataset数据集后，我们来测试一下数据集是否符合预期，因为Dataset是一个可以被迭代的Class，我们通过for循环从里面读取数据来用matplotlib进行展示，这里要注意的是对于分割的标签文件因为是1通道的灰度图片，需要在使用imshow接口时注意下传参cmap=‘gray’。
+
+.. code:: ipython3
+
+    # 训练数据集
+    train_dataset = PetDataset(train_images_path, label_images_path, mode='train')
+    
+    # 验证数据集
+    val_dataset = PetDataset(train_images_path, label_images_path, mode='test')
+    
+    # 抽样一个数据
+    image, label = train_dataset[0]
+    
+    # 进行图片的展示
+    plt.figure()
+    
+    plt.subplot(1,2,1), 
+    plt.title('Train Image')
+    plt.imshow(image.transpose((1, 2, 0)).astype('uint8'))
+    plt.axis('off')
+    
+    plt.subplot(1,2,2), 
+    plt.title('Label')
+    plt.imshow(np.squeeze(label, axis=0).astype('uint8'), cmap='gray')
+    plt.axis('off')
+    
+    plt.show()
+
+
+
+.. image:: pets_image_segmentation_U_Net_like_files/pets_image_segmentation_U_Net_like_12_0.svg
+
+
+4.模型组网
+----------
+
+U-Net是一个U型网络结构，可以看做两个大的阶段，图像先经过Encoder编码器进行下采样得到高级语义特征图，再经过Decoder解码器上采样将特征图恢复到原图片的分辨率。
+
+4.1 定义SeparableConv2d接口
+~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+我们为了减少卷积操作中的训练参数来提升性能，是继承paddle.nn.Layer自定义了一个SeparableConv2d
+Layer类，整个过程是把\ ``filter_size * filter_size * num_filters``\ 的Conv2d操作拆解为两个子Conv2d，先对输入数据的每个通道使用\ ``filter_size * filter_size * 1``\ 的卷积核进行计算，输入输出通道数目相同，之后在使用\ ``1 * 1 * num_filters``\ 的卷积核计算。
+
+.. code:: ipython3
+
+    class SeparableConv2d(paddle.nn.Layer):
+        def __init__(self, 
+                     in_channels, 
+                     out_channels, 
+                     kernel_size, 
+                     stride=1, 
+                     padding=0, 
+                     dilation=1, 
+                     groups=None, 
+                     weight_attr=None, 
+                     bias_attr=None, 
+                     data_format="NCHW"):
+            super(SeparableConv2d, self).__init__()
+            # 第一次卷积操作没有偏置参数
+            self.conv_1 = paddle.nn.Conv2d(in_channels, 
+                                           in_channels, 
+                                           kernel_size, 
+                                           stride=stride,
+                                           padding=padding,
+                                           dilation=dilation,
+                                           groups=in_channels, 
+                                           weight_attr=weight_attr, 
+                                           bias_attr=False,  
+                                           data_format=data_format)
+            self.pointwise = paddle.nn.Conv2d(in_channels, 
+                                              out_channels, 
+                                              1, 
+                                              stride=1, 
+                                              padding=0, 
+                                              dilation=1, 
+                                              groups=1, 
+                                              weight_attr=weight_attr, 
+                                              data_format=data_format)
+            
+        def forward(self, inputs):
+            y = self.conv_1(inputs)
+            y = self.pointwise(y)
+    
+            return y
+
+4.2 定义Encoder编码器
+~~~~~~~~~~~~~~~~~~~~~
+
+我们将网络结构中的Encoder下采样过程进行了一个Layer封装，方便后续调用，减少代码编写，下采样是有一个模型逐渐向下画曲线的一个过程，这个过程中是不断的重复一个单元结构将通道数不断增加，形状不断缩小，并且引入残差网络结构，我们将这些都抽象出来进行统一封装。
+
+.. code:: ipython3
+
+    class Encoder(paddle.nn.Layer):
+        def __init__(self, in_channels, out_channels):
+            super(Encoder, self).__init__()
+            
+            self.relu = paddle.nn.ReLU()
+            self.separable_conv_01 = SeparableConv2d(in_channels, 
+                                                     out_channels, 
+                                                     kernel_size=3, 
+                                                     padding='same')
+            self.bn = paddle.nn.BatchNorm2d(out_channels)
+            self.separable_conv_02 = SeparableConv2d(out_channels, 
+                                                     out_channels, 
+                                                     kernel_size=3, 
+                                                     padding='same')
+            self.pool = paddle.nn.MaxPool2d(kernel_size=3, stride=2, padding=1)
+            self.residual_conv = paddle.nn.Conv2d(in_channels, 
+                                                  out_channels, 
+                                                  kernel_size=1, 
+                                                  stride=2, 
+                                                  padding='same')
+    
+        def forward(self, inputs):
+            previous_block_activation = inputs
+            
+            y = self.relu(inputs)
+            y = self.separable_conv_01(y)
+            y = self.bn(y)
+            y = self.relu(y)
+            y = self.separable_conv_02(y)
+            y = self.bn(y)
+            y = self.pool(y)
+            
+            residual = self.residual_conv(previous_block_activation)
+            y = paddle.add(y, residual)
+    
+            return y
+
+4.3 定义Decoder解码器
+~~~~~~~~~~~~~~~~~~~~~
+
+在通道数达到最大得到高级语义特征图后，网络结构会开始进行decode操作，进行上采样，通道数逐渐减小，对应图片尺寸逐步增加，直至恢复到原图像大小，那么这个过程里面也是通过不断的重复相同结构的残差网络完成，我们也是为了减少代码编写，将这个过程定义一个Layer来放到模型组网中使用。
+
+.. code:: ipython3
+
+    class Decoder(paddle.nn.Layer):
+        def __init__(self, in_channels, out_channels):
+            super(Decoder, self).__init__()
+    
+            self.relu = paddle.nn.ReLU()
+            self.conv_transpose_01 = paddle.nn.ConvTranspose2d(in_channels, 
+                                                               out_channels, 
+                                                               kernel_size=3, 
+                                                               padding='same')
+            self.conv_transpose_02 = paddle.nn.ConvTranspose2d(out_channels, 
+                                                               out_channels, 
+                                                               kernel_size=3, 
+                                                               padding='same')
+            self.bn = paddle.nn.BatchNorm2d(out_channels)
+            self.upsample = paddle.nn.UpSample(scale_factor=2.0)
+            self.residual_conv = paddle.nn.Conv2d(in_channels, 
+                                                  out_channels, 
+                                                  kernel_size=1, 
+                                                  padding='same')
+    
+        def forward(self, inputs):
+            previous_block_activation = inputs
+    
+            y = self.relu(inputs)
+            y = self.conv_transpose_01(y)
+            y = self.bn(y)
+            y = self.relu(y)
+            y = self.conv_transpose_02(y)
+            y = self.bn(y)
+            y = self.upsample(y)
+            
+            residual = self.upsample(previous_block_activation)
+            residual = self.residual_conv(residual)
+            
+            y = paddle.add(y, residual)
+            
+            return y
+
+4.4 训练模型组网
+~~~~~~~~~~~~~~~~
+
+按照U型网络结构格式进行整体的网络结构搭建，三次下采样，四次上采样。
+
+.. code:: ipython3
+
+    class PetModel(paddle.nn.Layer):
+        def __init__(self, num_classes):
+            super(PetModel, self).__init__()
+    
+            self.conv_1 = paddle.nn.Conv2d(3, 32, 
+                                           kernel_size=3,
+                                           stride=2,
+                                           padding='same')
+            self.bn = paddle.nn.BatchNorm2d(32)
+            self.relu = paddle.nn.ReLU()
+    
+            in_channels = 32
+            self.encoders = []
+            self.encoder_list = [64, 128, 256]
+            self.decoder_list = [256, 128, 64, 32]
+    
+            # 根据下采样个数和配置循环定义子Layer，避免重复写一样的程序
+            for out_channels in self.encoder_list:
+                block = self.add_sublayer('encoder_%s'.format(out_channels),
+                                          Encoder(in_channels, out_channels))
+                self.encoders.append(block)
+                in_channels = out_channels
+    
+            self.decoders = []
+    
+            # 根据上采样个数和配置循环定义子Layer，避免重复写一样的程序
+            for out_channels in self.decoder_list:
+                block = self.add_sublayer('decoder_%s'.format(out_channels), 
+                                          Decoder(in_channels, out_channels))
+                self.decoders.append(block)
+                in_channels = out_channels
+    
+            self.output_conv = paddle.nn.Conv2d(in_channels, 
+                                                num_classes, 
+                                                kernel_size=3, 
+                                                padding='same')
+        
+        def forward(self, inputs):
+            y = self.conv_1(inputs)
+            y = self.bn(y)
+            y = self.relu(y)
+            
+            for encoder in self.encoders:
+                y = encoder(y)
+    
+            for decoder in self.decoders:
+                y = decoder(y)
+            
+            y = self.output_conv(y)
+            
+            return y
+
+4.5 模型可视化
+~~~~~~~~~~~~~~
+
+调用飞桨提供的summary接口对组建好的模型进行可视化，方便进行模型结构和参数信息的查看和确认。
+@TODO，需要替换
+
+.. code:: ipython3
+
+    from paddle.static import InputSpec
+    
+    paddle.disable_static()
+    num_classes = 4
+    model = paddle.Model(PetModel(num_classes))
+    model.summary((3, 160, 160))
+
+
+.. parsed-literal::
+
+    --------------------------------------------------------------------------------
+       Layer (type)          Input Shape         Output Shape         Param #
+    ================================================================================
+          Conv2d-22    [-1, 3, 160, 160]     [-1, 32, 80, 80]             896
+      BatchNorm2d-9     [-1, 32, 80, 80]     [-1, 32, 80, 80]              64
+             ReLU-9     [-1, 32, 80, 80]     [-1, 32, 80, 80]               0
+            ReLU-12    [-1, 256, 20, 20]    [-1, 256, 20, 20]               0
+          Conv2d-33    [-1, 128, 20, 20]    [-1, 128, 20, 20]           1,152
+          Conv2d-34    [-1, 128, 20, 20]    [-1, 256, 20, 20]          33,024
+    SeparableConv2d-11    [-1, 128, 20, 20]    [-1, 256, 20, 20]               0
+     BatchNorm2d-12    [-1, 256, 20, 20]    [-1, 256, 20, 20]             512
+          Conv2d-35    [-1, 256, 20, 20]    [-1, 256, 20, 20]           2,304
+          Conv2d-36    [-1, 256, 20, 20]    [-1, 256, 20, 20]          65,792
+    SeparableConv2d-12    [-1, 256, 20, 20]    [-1, 256, 20, 20]               0
+        MaxPool2d-6    [-1, 256, 20, 20]    [-1, 256, 10, 10]               0
+          Conv2d-37    [-1, 128, 20, 20]    [-1, 256, 10, 10]          33,024
+          Encoder-6    [-1, 128, 20, 20]    [-1, 256, 10, 10]               0
+            ReLU-16     [-1, 32, 80, 80]     [-1, 32, 80, 80]               0
+    ConvTranspose2d-15     [-1, 64, 80, 80]     [-1, 32, 80, 80]          18,464
+     BatchNorm2d-16     [-1, 32, 80, 80]     [-1, 32, 80, 80]              64
+    ConvTranspose2d-16     [-1, 32, 80, 80]     [-1, 32, 80, 80]           9,248
+         UpSample-8     [-1, 64, 80, 80]   [-1, 64, 160, 160]               0
+          Conv2d-41   [-1, 64, 160, 160]   [-1, 32, 160, 160]           2,080
+          Decoder-8     [-1, 64, 80, 80]   [-1, 32, 160, 160]               0
+          Conv2d-42   [-1, 32, 160, 160]    [-1, 4, 160, 160]           1,156
+    ================================================================================
+    Total params: 167,780
+    Trainable params: 167,780
+    Non-trainable params: 0
+    --------------------------------------------------------------------------------
+    Input size (MB): 0.29
+    Forward/backward pass size (MB): 43.16
+    Params size (MB): 0.64
+    Estimated Total Size (MB): 44.10
+    --------------------------------------------------------------------------------
+    
+
+
+
+
+.. parsed-literal::
+
+    {'total_params': 167780, 'trainable_params': 167780}
+
+
+
+5.模型训练
+----------
+
+5.1 配置信息
+~~~~~~~~~~~~
+
+定义训练BATCH_SIZE、训练轮次和计算设备等信息。
+
+.. code:: ipython3
+
+    BATCH_SIZE = 32
+    EPOCHS = 15
+    device = paddle.set_device('gpu')
+    paddle.disable_static(device)
+
+5.3 自定义Loss
+~~~~~~~~~~~~~~
+
+在这个任务中我们使用SoftmaxWithCrossEntropy损失函数来做计算，飞桨中有functional形式的API，这里我们做一个自定义操作，实现一个Class形式API放到模型训练中使用。没有直接使用CrossEntropyLoss的原因主要是对计算维度的自定义需求，本次需要进行softmax计算的维度是1，不是默认的最后一维，所以我们采用上面提到的损失函数，通过axis参数来指定softmax计算维度。
+
+.. code:: ipython3
+
+    class SoftmaxWithCrossEntropy(paddle.nn.Layer):
+        def __init__(self):
+            super(SoftmaxWithCrossEntropy, self).__init__()
+    
+        def forward(self, input, label):
+            loss = F.softmax_with_cross_entropy(input, 
+                                                label, 
+                                                return_softmax=False,
+                                                axis=1)
+            return paddle.mean(loss)
+
+5.4 启动模型训练
+~~~~~~~~~~~~~~~~
+
+使用模型代码进行Model实例生成，使用prepare接口定义优化器、损失函数和评价指标等信息，用于后续训练使用。在所有初步配置完成后，调用fit接口开启训练执行过程，调用fit时只需要将前面定义好的训练数据集、测试数据集、训练轮次（Epoch）和批次大小（batch_size）配置好即可。
+
+.. code:: ipython3
+
+    optim = paddle.optimizer.RMSProp(learning_rate=0.001, 
+                                     rho=0.9, 
+                                     momentum=0.0, 
+                                     epsilon=1e-07, 
+                                     centered=False,
+                                     parameters=model.parameters())
+    model = paddle.Model(PetModel(num_classes, model_tools))
+    model.prepare(optim, 
+                  SoftmaxWithCrossEntropy())
+    
+    model.fit(train_dataset, 
+        val_dataset, 
+        epochs=EPOCHS, 
+        batch_size=BATCH_SIZE
+    )
+
+6.模型预测
+----------
+
+6.1 预测数据集准备和预测
+~~~~~~~~~~~~~~~~~~~~~~~~
+
+继续使用PetDataset来实例化待预测使用的数据集。这里我们为了方便没有在另外准备预测数据，复用了评估数据。
+
+我们可以直接使用model.predict接口来对数据集进行预测操作，只需要将预测数据集传递到接口内即可。
+
+.. code:: ipython3
+
+    predict_results = model.predict(val_dataset)
+
+6.2 预测结果可视化
+~~~~~~~~~~~~~~~~~~
+
+从我们的预测数据集中抽3个动物来看看预测的效果，展示一下原图、标签图和预测结果。
+
+.. code:: ipython3
+
+    plt.figure(figsize=(10, 10))
+    
+    i = 0
+    mask_idx = 0
+    
+    for data in val_dataset:
+        if i > 8: 
+            break
+        plt.subplot(3, 3, i + 1)
+        plt.imshow(data[0].transpose((1, 2, 0)).astype('uint8'))
+        plt.title('Input Image')
+        plt.axis("off")
+    
+        plt.subplot(3, 3, i + 2)
+        plt.imshow(np.squeeze(data[1], axis=0).astype('uint8'), cmap='gray')
+        plt.title('Label')
+        plt.axis("off")
+        
+        
+        data = val_preds[0][mask_idx][0].transpose((1, 2, 0))
+        mask = np.argmax(data, axis=-1)
+        mask = np.expand_dims(mask, axis=-1)
+    
+        plt.subplot(3, 3, i + 3)
+        plt.imshow(np.squeeze(mask, axis=2).astype('uint8'), cmap='gray')
+        plt.title('Predict')
+        plt.axis("off")
+        i += 3
+        mask_idx += 1
+    
+    plt.show()
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diff --git a/doc/paddle/tutorial/cv_case/index_cn.rst b/doc/paddle/tutorial/cv_case/index_cn.rst
index 2bf44a2bde89c7f01bc25b9df76e6cf6ff4b545e..7b141b6acfff67f020cc5846fccba98afbaeed59 100644
--- a/doc/paddle/tutorial/cv_case/index_cn.rst
+++ b/doc/paddle/tutorial/cv_case/index_cn.rst
@@ -6,10 +6,16 @@
 在这里PaddlePaddle为大家提供了一篇cv的教程供大家学习：
     
      - `图像分类 <./mnist_lenet_classification/mnist_lenet_classification.html>`_ ：介绍使用 Paddle 在MNIST数据集上完成图像分类。
-    
+     - `图像分类 <./convnet_image_classification/convnet_image_classification.html>`_ ：介绍使用 Paddle 在CIFA10数据集上完成图像分类。    
+     - `图像搜索 <./image_search/image_search.html>`_ ：介绍使用 Paddle 实现图像搜索。
+     - `图像分割 <./image_segmentation/pets_image_segmentation_U_Net_like.html>`_ ：介绍使用 Paddle 实现U-Net模型完成图像分割。
+
+
 ..  toctree::
     :hidden:
     :titlesonly:
 
     mnist_lenet_classification/mnist_lenet_classification.rst
-
+    convnet_image_classification/convnet_image_classification.rst
+    image_search/image_search.rst
+    image_segmentation/pets_image_segmentation_U_Net_like.rst
diff --git a/doc/paddle/tutorial/index_cn.rst b/doc/paddle/tutorial/index_cn.rst
index 8bff97402ebb3864fd804d6c1858ae367469e927..2daf66c34ae9ad0edb60ad5eef6c5516d69dc72b 100644
--- a/doc/paddle/tutorial/index_cn.rst
+++ b/doc/paddle/tutorial/index_cn.rst
@@ -11,9 +11,13 @@
 
 **内容简介**
 
+    - `快速上手 <./simple_case/index_cn.html>`_ ：快速了解Paddle 2的特性与功能。
     - `计算机视觉 <./cv_case/index_cn.html>`_ ：介绍使用 Paddle 解决计算机视觉领域的案例
+    - `自然语言处理 <./nlp_case/index_cn.html>`_ ：介绍使用 Paddle 解决自然语言处理领域的案例
 
 ..  toctree::
     :hidden:
 
+    quick_start/index_cn.rst
     cv_case/index_cn.rst
+    nlp_case/index_cn.rst
diff --git a/doc/paddle/tutorial/nlp_case/imdb_bow_classification/imdb_bow_classification.ipynb b/doc/paddle/tutorial/nlp_case/imdb_bow_classification/imdb_bow_classification.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..aa3874ebf923b0d2c8401ccdae1f382045bed065
--- /dev/null
+++ b/doc/paddle/tutorial/nlp_case/imdb_bow_classification/imdb_bow_classification.ipynb
@@ -0,0 +1,376 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# IMDB 数据集使用BOW网络的文本分类\n",
+    "\n",
+    "本示例教程演示如何在IMDB数据集上用简单的BOW网络完成文本分类的任务。\n",
+    "\n",
+    "IMDB数据集是一个对电影评论标注为正向评论与负向评论的数据集，共有25000条文本数据作为训练集，25000条文本数据作为测试集。\n",
+    "该数据集的官方地址为： http://ai.stanford.edu/~amaas/data/sentiment/\n",
+    "\n",
+    "- Warning: `paddle.dataset.imdb`先在是一个非常粗野的实现，后续需要有替代的方案。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 环境设置\n",
+    "\n",
+    "本示例基于飞桨开源框架2.0版本。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.0.0\n",
+      "264e76cae6861ad9b1d4bcd8c3212f7a78c01e4d\n"
+     ]
+    }
+   ],
+   "source": [
+    "import paddle\n",
+    "import numpy as np\n",
+    "\n",
+    "paddle.disable_static()\n",
+    "print(paddle.__version__)\n",
+    "print(paddle.__git_commit__)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 加载数据\n",
+    "\n",
+    "我们会使用`paddle.dataset`完成数据下载，构建字典和准备数据读取器。在飞桨2.0版本中，推荐使用padding的方式来对同一个batch中长度不一的数据进行补齐，所以在字典中，我们还会添加一个特殊的`<pad>`词，用来在后续对batch中较短的句子进行填充。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Loading IMDB word dict....\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Loading IMDB word dict....\")\n",
+    "word_dict = paddle.dataset.imdb.word_dict()\n",
+    "\n",
+    "train_reader = paddle.dataset.imdb.train(word_dict)\n",
+    "test_reader = paddle.dataset.imdb.test(word_dict)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "the:0\n",
+      "and:1\n",
+      "a:2\n",
+      "of:3\n",
+      "to:4\n",
+      "...\n",
+      "virtual:5143\n",
+      "warriors:5144\n",
+      "widely:5145\n",
+      "<unk>:5146\n",
+      "<pad>:5147\n",
+      "totally 5148 words\n"
+     ]
+    }
+   ],
+   "source": [
+    "# add a pad token to the dict for later padding the sequence\n",
+    "word_dict['<pad>'] = len(word_dict)\n",
+    "\n",
+    "for k in list(word_dict)[:5]:\n",
+    "    print(\"{}:{}\".format(k.decode('ASCII'), word_dict[k]))\n",
+    "\n",
+    "print(\"...\")\n",
+    "\n",
+    "for k in list(word_dict)[-5:]:\n",
+    "    print(\"{}:{}\".format(k if isinstance(k, str) else k.decode('ASCII'), word_dict[k]))\n",
+    "\n",
+    "print(\"totally {} words\".format(len(word_dict)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 参数设置\n",
+    "\n",
+    "在这里我们设置一下词表大小，`embedding`的大小，batch_size，等等"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "vocab_size = len(word_dict)\n",
+    "emb_size = 256\n",
+    "seq_len = 200\n",
+    "batch_size = 32\n",
+    "epoch_num = 2\n",
+    "pad_id = word_dict['<pad>']\n",
+    "\n",
+    "classes = ['negative', 'positive']\n",
+    "\n",
+    "def ids_to_str(ids):\n",
+    "    #print(ids)\n",
+    "    words = []\n",
+    "    for k in ids:\n",
+    "        w = list(word_dict)[k]\n",
+    "        words.append(w if isinstance(w, str) else w.decode('ASCII'))\n",
+    "    return \" \".join(words)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "在这里，取出一条数据打印出来看看，可以对数据有一个初步直观的印象。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[5146, 43, 71, 6, 1092, 14, 0, 878, 130, 151, 5146, 18, 281, 747, 0, 5146, 3, 5146, 2165, 37, 5146, 46, 5, 71, 4089, 377, 162, 46, 5, 32, 1287, 300, 35, 203, 2136, 565, 14, 2, 253, 26, 146, 61, 372, 1, 615, 5146, 5, 30, 0, 50, 3290, 6, 2148, 14, 0, 5146, 11, 17, 451, 24, 4, 127, 10, 0, 878, 130, 43, 2, 50, 5146, 751, 5146, 5, 2, 221, 3727, 6, 9, 1167, 373, 9, 5, 5146, 7, 5, 1343, 13, 2, 5146, 1, 250, 7, 98, 4270, 56, 2316, 0, 928, 11, 11, 9, 16, 5, 5146, 5146, 6, 50, 69, 27, 280, 27, 108, 1045, 0, 2633, 4177, 3180, 17, 1675, 1, 2571] 0\n",
+      "<unk> has much in common with the third man another <unk> film set among the <unk> of <unk> europe like <unk> there is much inventive camera work there is an innocent american who gets emotionally involved with a woman he doesnt really understand and whose <unk> is all the more striking in contrast with the <unk> br but id have to say that the third man has a more <unk> storyline <unk> is a bit disjointed in this respect perhaps this is <unk> it is presented as a <unk> and making it too coherent would spoil the effect br br this movie is <unk> <unk> in more than one sense one never sees the sun shine grim but intriguing and frightening\n",
+      "negative\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 取出来第一条数据看看样子。\n",
+    "sent, label = next(train_reader())\n",
+    "print(sent, label)\n",
+    "\n",
+    "print(ids_to_str(sent))\n",
+    "print(classes[label])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 用padding的方式对齐数据\n",
+    "\n",
+    "文本数据中，每一句话的长度都是不一样的，为了方便后续的神经网络的计算，常见的处理方式是把数据集中的数据都统一成同样长度的数据。这包括：对于较长的数据进行截断处理，对于较短的数据用特殊的词`<pad>`进行填充。接下来的代码会对数据集中的数据进行这样的处理。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(25000, 200)\n",
+      "(25000, 1)\n",
+      "(25000, 200)\n",
+      "(25000, 1)\n",
+      "<unk> has much in common with the third man another <unk> film set among the <unk> of <unk> europe like <unk> there is much inventive camera work there is an innocent american who gets emotionally involved with a woman he doesnt really understand and whose <unk> is all the more striking in contrast with the <unk> br but id have to say that the third man has a more <unk> storyline <unk> is a bit disjointed in this respect perhaps this is <unk> it is presented as a <unk> and making it too coherent would spoil the effect br br this movie is <unk> <unk> in more than one sense one never sees the sun shine grim but intriguing and frightening <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad>\n",
+      "<unk> is the most original movie ive seen in years if you like unique thrillers that are influenced by film noir then this is just the right cure for all of those hollywood summer <unk> <unk> the theaters these days von <unk> <unk> like breaking the waves have gotten more <unk> but this is really his best work it is <unk> without being distracting and offers the perfect combination of suspense and dark humor its too bad he decided <unk> cameras were the wave of the future its hard to say who talked him away from the style he <unk> here but its everyones loss that he went into his heavily <unk> <unk> direction instead <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad>\n",
+      "<unk> von <unk> is never <unk> in trying out new techniques some of them are very original while others are best <unk> br he depicts <unk> germany as a <unk> train journey with so many cities lying in ruins <unk> <unk> a young american of german descent feels <unk> to help in their <unk> it is not a simple task as he quickly finds outbr br his uncle finds him a job as a night <unk> on the <unk> <unk> line his job is to <unk> to the needs of the passengers when the shoes are <unk> a <unk> mark is made on the <unk> a terrible argument <unk> when a passengers shoes are not <unk> despite the fact they have been <unk> there are many <unk> to the german <unk> of <unk> to such stupid <unk> br the <unk> journey is like an <unk> <unk> mans <unk> through life with all its <unk> and <unk> in one sequence <unk> <unk> through the back <unk> to discover them filled with <unk> bodies appearing to have just escaped from <unk> these images horrible as they are are <unk> as in a dream each with its own terrible impact yet <unk> br\n"
+     ]
+    }
+   ],
+   "source": [
+    "def create_padded_dataset(reader):\n",
+    "    padded_sents = []\n",
+    "    labels = []\n",
+    "    for batch_id, data in enumerate(reader):\n",
+    "        sent, label = data\n",
+    "        padded_sent = sent[:seq_len] + [pad_id] * (seq_len - len(sent))\n",
+    "        padded_sents.append(padded_sent)\n",
+    "        labels.append(label)\n",
+    "    return np.array(padded_sents), np.expand_dims(np.array(labels), axis=1)\n",
+    "\n",
+    "train_sents, train_labels = create_padded_dataset(train_reader())\n",
+    "test_sents, test_labels = create_padded_dataset(test_reader())\n",
+    "\n",
+    "print(train_sents.shape)\n",
+    "print(train_labels.shape)\n",
+    "print(test_sents.shape)\n",
+    "print(test_labels.shape)\n",
+    "\n",
+    "for sent in train_sents[:3]:\n",
+    "    print(ids_to_str(sent))\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 组建网络\n",
+    "\n",
+    "本示例中，我们将会使用一个不考虑词的顺序的BOW的网络，在查找到每个词对应的embedding后，简单的取平均，作为一个句子的表示。然后用`Linear`进行线性变换。为了防止过拟合，我们还使用了`Dropout`。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class MyNet(paddle.nn.Layer):\n",
+    "    def __init__(self):\n",
+    "        super(MyNet, self).__init__()\n",
+    "        self.emb = paddle.nn.Embedding(vocab_size, emb_size)\n",
+    "        self.fc = paddle.nn.Linear(in_features=emb_size, out_features=2)\n",
+    "        self.dropout = paddle.nn.Dropout(0.5)\n",
+    "\n",
+    "    def forward(self, x):\n",
+    "        x = self.emb(x)\n",
+    "        x = paddle.reduce_mean(x, dim=1)\n",
+    "        x = self.dropout(x)\n",
+    "        x = self.fc(x)\n",
+    "        return x"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 开始模型的训练\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "epoch: 0, batch_id: 0, loss is: [0.6926701]\n",
+      "epoch: 0, batch_id: 500, loss is: [0.41248566]\n",
+      "[validation] accuracy/loss: 0.8505121469497681/0.3615057170391083\n",
+      "epoch: 1, batch_id: 0, loss is: [0.29521096]\n",
+      "epoch: 1, batch_id: 500, loss is: [0.2916747]\n",
+      "[validation] accuracy/loss: 0.86475670337677/0.3259459137916565\n"
+     ]
+    }
+   ],
+   "source": [
+    "def train(model):\n",
+    "    model.train()\n",
+    "\n",
+    "    opt = paddle.optimizer.Adam(learning_rate=0.001, parameters=model.parameters())\n",
+    "\n",
+    "    for epoch in range(epoch_num):\n",
+    "        # shuffle data\n",
+    "        perm = np.random.permutation(len(train_sents))\n",
+    "        train_sents_shuffled = train_sents[perm]\n",
+    "        train_labels_shuffled = train_labels[perm]\n",
+    "        \n",
+    "        for batch_id in range(len(train_sents_shuffled) // batch_size):\n",
+    "            x_data = train_sents_shuffled[(batch_id * batch_size):((batch_id+1)*batch_size)]\n",
+    "            y_data = train_labels_shuffled[(batch_id * batch_size):((batch_id+1)*batch_size)]\n",
+    "            \n",
+    "            sent = paddle.to_tensor(x_data)\n",
+    "            label = paddle.to_tensor(y_data)\n",
+    "            \n",
+    "            logits = model(sent)\n",
+    "            loss = paddle.nn.functional.softmax_with_cross_entropy(logits, label)\n",
+    "            \n",
+    "            avg_loss = paddle.mean(loss)\n",
+    "            if batch_id % 500 == 0:\n",
+    "                print(\"epoch: {}, batch_id: {}, loss is: {}\".format(epoch, batch_id, avg_loss.numpy()))\n",
+    "            avg_loss.backward()\n",
+    "            opt.minimize(avg_loss)\n",
+    "            model.clear_gradients()\n",
+    "\n",
+    "        # evaluate model after one epoch\n",
+    "        model.eval()\n",
+    "        accuracies = []\n",
+    "        losses = []\n",
+    "        for batch_id in range(len(test_sents) // batch_size):\n",
+    "            x_data = test_sents[(batch_id * batch_size):((batch_id+1)*batch_size)]\n",
+    "            y_data = test_labels[(batch_id * batch_size):((batch_id+1)*batch_size)]\n",
+    "        \n",
+    "            sent = paddle.to_tensor(x_data)\n",
+    "            label = paddle.to_tensor(y_data)\n",
+    "\n",
+    "            logits = model(sent)\n",
+    "            loss = paddle.nn.functional.softmax_with_cross_entropy(logits, label)\n",
+    "            acc = paddle.metric.accuracy(logits, label)\n",
+    "            \n",
+    "            accuracies.append(acc.numpy())\n",
+    "            losses.append(loss.numpy())\n",
+    "        \n",
+    "        avg_acc, avg_loss = np.mean(accuracies), np.mean(losses)\n",
+    "        print(\"[validation] accuracy/loss: {}/{}\".format(avg_acc, avg_loss))\n",
+    "        \n",
+    "        model.train()\n",
+    "        \n",
+    "model = MyNet()\n",
+    "train(model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# The End\n",
+    "\n",
+    "可以看到，在这个数据集上，经过两轮的迭代可以得到86%左右的准确率。你也可以通过调整网络结构和超参数，来获得更好的效果。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "name": "cifar-10-cnn.ipynb",
+   "private_outputs": true,
+   "provenance": [],
+   "toc_visible": true
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/doc/paddle/tutorial/nlp_case/imdb_bow_classification/imdb_bow_classification.rst b/doc/paddle/tutorial/nlp_case/imdb_bow_classification/imdb_bow_classification.rst
new file mode 100644
index 0000000000000000000000000000000000000000..8e1f245a779b5722a47df65768d99887691001c7
--- /dev/null
+++ b/doc/paddle/tutorial/nlp_case/imdb_bow_classification/imdb_bow_classification.rst
@@ -0,0 +1,265 @@
+IMDB 数据集使用BOW网络的文本分类
+================================
+
+本示例教程演示如何在IMDB数据集上用简单的BOW网络完成文本分类的任务。
+
+IMDB数据集是一个对电影评论标注为正向评论与负向评论的数据集，共有25000条文本数据作为训练集，25000条文本数据作为测试集。
+该数据集的官方地址为： http://ai.stanford.edu/~amaas/data/sentiment/
+
+-  Warning:
+   ``paddle.dataset.imdb``\ 先在是一个非常粗野的实现，后续需要有替代的方案。
+
+环境设置
+--------
+
+本示例基于飞桨开源框架2.0版本。
+
+.. code:: 
+
+    import paddle
+    import numpy as np
+    
+    paddle.disable_static()
+    print(paddle.__version__)
+    print(paddle.__git_commit__)
+
+
+
+.. parsed-literal::
+
+    0.0.0
+    264e76cae6861ad9b1d4bcd8c3212f7a78c01e4d
+
+
+加载数据
+--------
+
+我们会使用\ ``paddle.dataset``\ 完成数据下载，构建字典和准备数据读取器。在飞桨2.0版本中，推荐使用padding的方式来对同一个batch中长度不一的数据进行补齐，所以在字典中，我们还会添加一个特殊的\ ``<pad>``\ 词，用来在后续对batch中较短的句子进行填充。
+
+.. code:: 
+
+    print("Loading IMDB word dict....")
+    word_dict = paddle.dataset.imdb.word_dict()
+    
+    train_reader = paddle.dataset.imdb.train(word_dict)
+    test_reader = paddle.dataset.imdb.test(word_dict)
+
+
+
+.. parsed-literal::
+
+    Loading IMDB word dict....
+
+
+.. code:: 
+
+    # add a pad token to the dict for later padding the sequence
+    word_dict['<pad>'] = len(word_dict)
+    
+    for k in list(word_dict)[:5]:
+        print("{}:{}".format(k.decode('ASCII'), word_dict[k]))
+    
+    print("...")
+    
+    for k in list(word_dict)[-5:]:
+        print("{}:{}".format(k if isinstance(k, str) else k.decode('ASCII'), word_dict[k]))
+    
+    print("totally {} words".format(len(word_dict)))
+
+
+.. parsed-literal::
+
+    the:0
+    and:1
+    a:2
+    of:3
+    to:4
+    ...
+    virtual:5143
+    warriors:5144
+    widely:5145
+    <unk>:5146
+    <pad>:5147
+    totally 5148 words
+
+
+参数设置
+--------
+
+在这里我们设置一下词表大小，\ ``embedding``\ 的大小，batch_size，等等
+
+.. code:: 
+
+    vocab_size = len(word_dict)
+    emb_size = 256
+    seq_len = 200
+    batch_size = 32
+    epoch_num = 2
+    pad_id = word_dict['<pad>']
+    
+    classes = ['negative', 'positive']
+    
+    def ids_to_str(ids):
+        #print(ids)
+        words = []
+        for k in ids:
+            w = list(word_dict)[k]
+            words.append(w if isinstance(w, str) else w.decode('ASCII'))
+        return " ".join(words)
+
+在这里，取出一条数据打印出来看看，可以对数据有一个初步直观的印象。
+
+.. code:: 
+
+    # 取出来第一条数据看看样子。
+    sent, label = next(train_reader())
+    print(sent, label)
+    
+    print(ids_to_str(sent))
+    print(classes[label])
+
+
+.. parsed-literal::
+
+    [5146, 43, 71, 6, 1092, 14, 0, 878, 130, 151, 5146, 18, 281, 747, 0, 5146, 3, 5146, 2165, 37, 5146, 46, 5, 71, 4089, 377, 162, 46, 5, 32, 1287, 300, 35, 203, 2136, 565, 14, 2, 253, 26, 146, 61, 372, 1, 615, 5146, 5, 30, 0, 50, 3290, 6, 2148, 14, 0, 5146, 11, 17, 451, 24, 4, 127, 10, 0, 878, 130, 43, 2, 50, 5146, 751, 5146, 5, 2, 221, 3727, 6, 9, 1167, 373, 9, 5, 5146, 7, 5, 1343, 13, 2, 5146, 1, 250, 7, 98, 4270, 56, 2316, 0, 928, 11, 11, 9, 16, 5, 5146, 5146, 6, 50, 69, 27, 280, 27, 108, 1045, 0, 2633, 4177, 3180, 17, 1675, 1, 2571] 0
+    <unk> has much in common with the third man another <unk> film set among the <unk> of <unk> europe like <unk> there is much inventive camera work there is an innocent american who gets emotionally involved with a woman he doesnt really understand and whose <unk> is all the more striking in contrast with the <unk> br but id have to say that the third man has a more <unk> storyline <unk> is a bit disjointed in this respect perhaps this is <unk> it is presented as a <unk> and making it too coherent would spoil the effect br br this movie is <unk> <unk> in more than one sense one never sees the sun shine grim but intriguing and frightening
+    negative
+
+
+用padding的方式对齐数据
+----------------------------
+
+文本数据中，每一句话的长度都是不一样的，为了方便后续的神经网络的计算，常见的处理方式是把数据集中的数据都统一成同样长度的数据。这包括：对于较长的数据进行截断处理，对于较短的数据用特殊的词\ ``<pad>``\ 进行填充。接下来的代码会对数据集中的数据进行这样的处理。
+
+.. code:: 
+
+    def create_padded_dataset(reader):
+        padded_sents = []
+        labels = []
+        for batch_id, data in enumerate(reader):
+            sent, label = data
+            padded_sent = sent[:seq_len] + [pad_id] * (seq_len - len(sent))
+            padded_sents.append(padded_sent)
+            labels.append(label)
+        return np.array(padded_sents), np.expand_dims(np.array(labels), axis=1)
+    
+    train_sents, train_labels = create_padded_dataset(train_reader())
+    test_sents, test_labels = create_padded_dataset(test_reader())
+    
+    print(train_sents.shape)
+    print(train_labels.shape)
+    print(test_sents.shape)
+    print(test_labels.shape)
+    
+    for sent in train_sents[:3]:
+        print(ids_to_str(sent))
+
+
+
+.. parsed-literal::
+
+    (25000, 200)
+    (25000, 1)
+    (25000, 200)
+    (25000, 1)
+    <unk> has much in common with the third man another <unk> film set among the <unk> of <unk> europe like <unk> there is much inventive camera work there is an innocent american who gets emotionally involved with a woman he doesnt really understand and whose <unk> is all the more striking in contrast with the <unk> br but id have to say that the third man has a more <unk> storyline <unk> is a bit disjointed in this respect perhaps this is <unk> it is presented as a <unk> and making it too coherent would spoil the effect br br this movie is <unk> <unk> in more than one sense one never sees the sun shine grim but intriguing and frightening <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad>
+    <unk> is the most original movie ive seen in years if you like unique thrillers that are influenced by film noir then this is just the right cure for all of those hollywood summer <unk> <unk> the theaters these days von <unk> <unk> like breaking the waves have gotten more <unk> but this is really his best work it is <unk> without being distracting and offers the perfect combination of suspense and dark humor its too bad he decided <unk> cameras were the wave of the future its hard to say who talked him away from the style he <unk> here but its everyones loss that he went into his heavily <unk> <unk> direction instead <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad> <pad>
+    <unk> von <unk> is never <unk> in trying out new techniques some of them are very original while others are best <unk> br he depicts <unk> germany as a <unk> train journey with so many cities lying in ruins <unk> <unk> a young american of german descent feels <unk> to help in their <unk> it is not a simple task as he quickly finds outbr br his uncle finds him a job as a night <unk> on the <unk> <unk> line his job is to <unk> to the needs of the passengers when the shoes are <unk> a <unk> mark is made on the <unk> a terrible argument <unk> when a passengers shoes are not <unk> despite the fact they have been <unk> there are many <unk> to the german <unk> of <unk> to such stupid <unk> br the <unk> journey is like an <unk> <unk> mans <unk> through life with all its <unk> and <unk> in one sequence <unk> <unk> through the back <unk> to discover them filled with <unk> bodies appearing to have just escaped from <unk> these images horrible as they are are <unk> as in a dream each with its own terrible impact yet <unk> br
+
+
+组建网络
+--------
+
+本示例中，我们将会使用一个不考虑词的顺序的BOW的网络，在查找到每个词对应的embedding后，简单的取平均，作为一个句子的表示。然后用\ ``Linear``\ 进行线性变换。为了防止过拟合，我们还使用了\ ``Dropout``\ 。
+
+.. code:: 
+
+    class MyNet(paddle.nn.Layer):
+        def __init__(self):
+            super(MyNet, self).__init__()
+            self.emb = paddle.nn.Embedding(vocab_size, emb_size)
+            self.fc = paddle.nn.Linear(in_features=emb_size, out_features=2)
+            self.dropout = paddle.nn.Dropout(0.5)
+    
+        def forward(self, x):
+            x = self.emb(x)
+            x = paddle.reduce_mean(x, dim=1)
+            x = self.dropout(x)
+            x = self.fc(x)
+            return x
+
+开始模型的训练
+--------------
+
+.. code:: 
+
+    def train(model):
+        model.train()
+    
+        opt = paddle.optimizer.Adam(learning_rate=0.001, parameters=model.parameters())
+    
+        for epoch in range(epoch_num):
+            # shuffle data
+            perm = np.random.permutation(len(train_sents))
+            train_sents_shuffled = train_sents[perm]
+            train_labels_shuffled = train_labels[perm]
+            
+            for batch_id in range(len(train_sents_shuffled) // batch_size):
+                x_data = train_sents_shuffled[(batch_id * batch_size):((batch_id+1)*batch_size)]
+                y_data = train_labels_shuffled[(batch_id * batch_size):((batch_id+1)*batch_size)]
+                
+                sent = paddle.to_tensor(x_data)
+                label = paddle.to_tensor(y_data)
+                
+                logits = model(sent)
+                loss = paddle.nn.functional.softmax_with_cross_entropy(logits, label)
+                
+                avg_loss = paddle.mean(loss)
+                if batch_id % 500 == 0:
+                    print("epoch: {}, batch_id: {}, loss is: {}".format(epoch, batch_id, avg_loss.numpy()))
+                avg_loss.backward()
+                opt.minimize(avg_loss)
+                model.clear_gradients()
+    
+            # evaluate model after one epoch
+            model.eval()
+            accuracies = []
+            losses = []
+            for batch_id in range(len(test_sents) // batch_size):
+                x_data = test_sents[(batch_id * batch_size):((batch_id+1)*batch_size)]
+                y_data = test_labels[(batch_id * batch_size):((batch_id+1)*batch_size)]
+            
+                sent = paddle.to_tensor(x_data)
+                label = paddle.to_tensor(y_data)
+    
+                logits = model(sent)
+                loss = paddle.nn.functional.softmax_with_cross_entropy(logits, label)
+                acc = paddle.metric.accuracy(logits, label)
+                
+                accuracies.append(acc.numpy())
+                losses.append(loss.numpy())
+            
+            avg_acc, avg_loss = np.mean(accuracies), np.mean(losses)
+            print("[validation] accuracy/loss: {}/{}".format(avg_acc, avg_loss))
+            
+            model.train()
+            
+    model = MyNet()
+    train(model)
+
+
+.. parsed-literal::
+
+    epoch: 0, batch_id: 0, loss is: [0.6926701]
+    epoch: 0, batch_id: 500, loss is: [0.41248566]
+    [validation] accuracy/loss: 0.8505121469497681/0.3615057170391083
+    epoch: 1, batch_id: 0, loss is: [0.29521096]
+    epoch: 1, batch_id: 500, loss is: [0.2916747]
+    [validation] accuracy/loss: 0.86475670337677/0.3259459137916565
+
+
+The End
+--------
+
+可以看到，在这个数据集上，经过两轮的迭代可以得到86%左右的准确率。你也可以通过调整网络结构和超参数，来获得更好的效果。
+
diff --git a/doc/paddle/tutorial/nlp_case/index_cn.rst b/doc/paddle/tutorial/nlp_case/index_cn.rst
new file mode 100644
index 0000000000000000000000000000000000000000..e93096215a1e3791a141be2392028f313087a219
--- /dev/null
+++ b/doc/paddle/tutorial/nlp_case/index_cn.rst
@@ -0,0 +1,19 @@
+################
+自然语言处理
+################
+
+
+在这里PaddlePaddle为大家提供了一篇nlp的教程供大家学习：
+    
+     - `N-Gram <./n_gram_model/n_gram_model.html>`_ ：介绍使用 Paddle 实现N-Gram 模型。
+     - `文本分类 <./imdb_bow_classification/imdb_bow_classification.html>`_ ：介绍使用 Paddle 在IMDB数据集上完成文本分类。    
+     - `文本翻译 <./seq2seq_with_attention/seq2seq_with_attention.html>`_ ：介绍使用 Paddle 实现文本翻译。
+
+
+..  toctree::
+    :hidden:
+    :titlesonly:
+
+    n_gram_model/n_gram_model.rst
+    imdb_bow_classification/imdb_bow_classification.rst
+    seq2seq_with_attention/seq2seq_with_attention.rst
diff --git a/doc/paddle/tutorial/nlp_case/n_gram_model/n_gram_model.ipynb b/doc/paddle/tutorial/nlp_case/n_gram_model/n_gram_model.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..e26c272cd42ae6c278e3844f272dbd4f02723d1f
--- /dev/null
+++ b/doc/paddle/tutorial/nlp_case/n_gram_model/n_gram_model.ipynb
@@ -0,0 +1,427 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "# 用N-Gram模型在莎士比亚文集中训练word embedding\n",
+    "N-gram 是计算机语言学和概率论范畴内的概念，是指给定的一段文本中N个项目的序列。\n",
+    "N=1 时 N-gram 又称为 unigram，N=2 称为 bigram，N=3 称为 trigram，以此类推。实际应用通常采用 bigram 和 trigram 进行计算。\n",
+    "本示例在莎士比亚文集上实现了trigram。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 环境\n",
+    "本教程基于paddle-develop编写，如果您的环境不是本版本，请先安装paddle-develop。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.0.0'"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import paddle\n",
+    "paddle.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 数据集&&相关参数\n",
+    "训练数据集采用了莎士比亚文集，[下载](https://ocw.mit.edu/ans7870/6/6.006/s08/lecturenotes/files/t8.shakespeare.txt)，保存为txt格式即可。<br>\n",
+    "context_size设为2，意味着是trigram。embedding_dim设为256。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "--2020-09-09 14:58:26--  https://ocw.mit.edu/ans7870/6/6.006/s08/lecturenotes/files/t8.shakespeare.txt\n",
+      "正在解析主机 ocw.mit.edu (ocw.mit.edu)... 151.101.110.133\n",
+      "正在连接 ocw.mit.edu (ocw.mit.edu)|151.101.110.133|:443... 已连接。\n",
+      "已发出 HTTP 请求，正在等待回应... 200 OK\n",
+      "长度：5458199 (5.2M) [text/plain]\n",
+      "正在保存至: “t8.shakespeare.txt”\n",
+      "\n",
+      "t8.shakespeare.txt  100%[===================>]   5.21M  94.1KB/s  用时 70s       \n",
+      "\n",
+      "2020-09-09 14:59:38 (75.7 KB/s) - 已保存 “t8.shakespeare.txt” [5458199/5458199])\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "!wget https://ocw.mit.edu/ans7870/6/6.006/s08/lecturenotes/files/t8.shakespeare.txt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "embedding_dim = 256\n",
+    "context_size = 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Length of text: 5458199 characters\n"
+     ]
+    }
+   ],
+   "source": [
+    "# 文件路径\n",
+    "path_to_file = './t8.shakespeare.txt'\n",
+    "test_sentence = open(path_to_file, 'rb').read().decode(encoding='utf-8')\n",
+    "\n",
+    "# 文本长度是指文本中的字符个数\n",
+    "print ('Length of text: {} characters'.format(len(test_sentence)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 去除标点符号\n",
+    "因为标点符号本身无实际意义，用`string`库中的punctuation，完成英文符号的替换。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'!': '', '\"': '', '#': '', '$': '', '%': '', '&': '', \"'\": '', '(': '', ')': '', '*': '', '+': '', ',': '', '-': '', '.': '', '/': '', ':': '', ';': '', '<': '', '=': '', '>': '', '?': '', '@': '', '[': '', '\\\\': '', ']': '', '^': '', '_': '', '`': '', '{': '', '|': '', '}': '', '~': ''}\n"
+     ]
+    }
+   ],
+   "source": [
+    "from string import punctuation\n",
+    "process_dicts={i:'' for i in punctuation}\n",
+    "print(process_dicts)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "28343\n"
+     ]
+    }
+   ],
+   "source": [
+    "punc_table = str.maketrans(process_dicts)\n",
+    "test_sentence = test_sentence.translate(punc_table)\n",
+    "test_sentence = test_sentence.lower().split()\n",
+    "vocab = set(test_sentence)\n",
+    "print(len(vocab))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 数据预处理\n",
+    "将文本被拆成了元组的形式，格式为(('第一个词', '第二个词'), '第三个词');其中，第三个词就是我们的目标。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[['this', 'is'], 'the'], [['is', 'the'], '100th'], [['the', '100th'], 'etext']]\n"
+     ]
+    }
+   ],
+   "source": [
+    "trigram = [[[test_sentence[i], test_sentence[i + 1]], test_sentence[i + 2]]\n",
+    "           for i in range(len(test_sentence) - 2)]\n",
+    "\n",
+    "word_to_idx = {word: i for i, word in enumerate(vocab)}\n",
+    "idx_to_word = {word_to_idx[word]: word for word in word_to_idx}\n",
+    "# 看一下数据集\n",
+    "print(trigram[:3])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 构建`Dataset`类 加载数据\n",
+    "用`paddle.io.Dataset`构建数据集，然后作为参数传入到`paddle.io.DataLoader`，完成数据集的加载。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import paddle\n",
+    "import numpy as np\n",
+    "batch_size = 256\n",
+    "paddle.disable_static()\n",
+    "class TrainDataset(paddle.io.Dataset):\n",
+    "    def __init__(self, tuple_data):\n",
+    "        self.tuple_data = tuple_data\n",
+    "\n",
+    "    def __getitem__(self, idx):\n",
+    "        data = self.tuple_data[idx][0]\n",
+    "        label = self.tuple_data[idx][1]\n",
+    "        data = np.array(list(map(lambda w: word_to_idx[w], data)))\n",
+    "        label = np.array(word_to_idx[label])\n",
+    "        return data, label\n",
+    "    \n",
+    "    def __len__(self):\n",
+    "        return len(self.tuple_data)\n",
+    "train_dataset = TrainDataset(trigram)\n",
+    "train_loader = paddle.io.DataLoader(train_dataset,places=paddle.CPUPlace(), return_list=True,\n",
+    "                                    shuffle=True, batch_size=batch_size, drop_last=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 组网&训练\n",
+    "这里用paddle动态图的方式组网。为了构建Trigram模型，用一层 `Embedding` 与两层 `Linear` 完成构建。`Embedding` 层对输入的前两个单词embedding，然后输入到后面的两个`Linear`层中，完成特征提取。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import paddle\n",
+    "import numpy as np\n",
+    "hidden_size = 1024\n",
+    "class NGramModel(paddle.nn.Layer):\n",
+    "    def __init__(self, vocab_size, embedding_dim, context_size):\n",
+    "        super(NGramModel, self).__init__()\n",
+    "        self.embedding = paddle.nn.Embedding(num_embeddings=vocab_size, embedding_dim=embedding_dim)\n",
+    "        self.linear1 = paddle.nn.Linear(context_size * embedding_dim, hidden_size)\n",
+    "        self.linear2 = paddle.nn.Linear(hidden_size, len(vocab))\n",
+    "\n",
+    "    def forward(self, x):\n",
+    "        x = self.embedding(x)\n",
+    "        x = paddle.reshape(x, [-1, context_size * embedding_dim])\n",
+    "        x = self.linear1(x)\n",
+    "        x = paddle.nn.functional.relu(x)\n",
+    "        x = self.linear2(x)\n",
+    "        return x"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 定义`train()`函数，对模型进行训练。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "epoch: 0, batch_id: 0, loss is: [10.252193]\n",
+      "epoch: 0, batch_id: 500, loss is: [6.894636]\n",
+      "epoch: 0, batch_id: 1000, loss is: [6.849346]\n",
+      "epoch: 0, batch_id: 1500, loss is: [6.931605]\n",
+      "epoch: 0, batch_id: 2000, loss is: [6.6860313]\n",
+      "epoch: 0, batch_id: 2500, loss is: [6.2472367]\n",
+      "epoch: 0, batch_id: 3000, loss is: [6.8818874]\n",
+      "epoch: 0, batch_id: 3500, loss is: [6.941615]\n",
+      "epoch: 1, batch_id: 0, loss is: [6.3628616]\n",
+      "epoch: 1, batch_id: 500, loss is: [6.2065206]\n",
+      "epoch: 1, batch_id: 1000, loss is: [6.5334334]\n",
+      "epoch: 1, batch_id: 1500, loss is: [6.5788]\n",
+      "epoch: 1, batch_id: 2000, loss is: [6.352103]\n",
+      "epoch: 1, batch_id: 2500, loss is: [6.6272373]\n",
+      "epoch: 1, batch_id: 3000, loss is: [6.801074]\n",
+      "epoch: 1, batch_id: 3500, loss is: [6.2274427]\n"
+     ]
+    }
+   ],
+   "source": [
+    "vocab_size = len(vocab)\n",
+    "epochs = 2\n",
+    "losses = []\n",
+    "def train(model):\n",
+    "    model.train()\n",
+    "    optim = paddle.optimizer.Adam(learning_rate=0.01, parameters=model.parameters())\n",
+    "    for epoch in range(epochs):\n",
+    "        for batch_id, data in enumerate(train_loader()):\n",
+    "            x_data = data[0]\n",
+    "            y_data = data[1]\n",
+    "            predicts = model(x_data)\n",
+    "            y_data = paddle.reshape(y_data, ([-1, 1]))\n",
+    "            loss = paddle.nn.functional.softmax_with_cross_entropy(predicts, y_data)\n",
+    "            avg_loss = paddle.mean(loss)\n",
+    "            avg_loss.backward()\n",
+    "            if batch_id % 500 == 0:\n",
+    "                losses.append(avg_loss.numpy())\n",
+    "                print(\"epoch: {}, batch_id: {}, loss is: {}\".format(epoch, batch_id, avg_loss.numpy())) \n",
+    "            optim.minimize(avg_loss)\n",
+    "            model.clear_gradients()\n",
+    "model = NGramModel(vocab_size, embedding_dim, context_size)\n",
+    "train(model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 打印loss下降曲线\n",
+    "通过可视化loss的曲线，可以看到模型训练的效果。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x14e27b3c8>]"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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vjBTaJWleehEJDgV9E8ntksjpkqLOGxEJDAV9M3KzUnVGLyKBoaBvRp4WIBGRAFHQNyMvM5V1JRXU1NXHuhQRkYgp6JuRl5VGvcP6EvXSi8i+T0HfDE1XLCJBoqBvRq566UUkQBT0zeiVkYqZzuhFJBhaHPRmNsjM5jb6KDWzG5rsY2Z2l5mtNLP5ZjYi8pKjr0NyuJdenTciEgAtXnjE3ZcBwwHMrB1QBDzXZLexwMDwx+HAfeHPcS83M1VDNyISCK01dHMC8LG7r2qyfRzwiIe8D2SaWa9WOmZU5emmKREJiNYK+gtpfoHwXGBNo+eF4W07MbOrzKzAzAqKi4tbqaTI5GWlsb6kklr10ovIPi7ioDezDsBZwNMtfQ93n+zu+e6en52dHWlJrSI3K5XaemfD9qpYlyIiEpGIFgcPGwvMdvcNzbxWBPRp9DwvvC3ufd5Lv6X88znq483G0kqKd1RxcK8umFmsy9knVNbU8dnmMj7bVMZnm8v5bFMZG0orueW0wRzYs3OsyxOJitYI+otoftgGYBowwcymELoIW+Lu61rhmFGXl5UGxMcCJO7OhtIqFhSVsKCohIXhj43h3zZG79+N/xt3iIIqrLKmjtVbyvl0U0Ogl/HZpnI+21zGuiZ3O3fv1IHKmnomPD6baROOJqV9uxhVLRI9EQW9maUDJwFXN9p2DYC73w+8DJwGrATKgcsjOV5b6pWRAsAbSzfSNb0DvTJSyclIoUtKclTPnt2dtSWVLCgsYdHaL4J9045qAJIMDsjuxNEDujMkN4N6d+5+cyVjJ83g0tH9uOGkgXRJaR+1+uJFVW0da7aU8+mm0Fn5p+Gz9FWby1lbUoH7F/t2Te9Av25pjD6gG/27pdO3ezr9u6XTr3sanVPa8/byYi598EN+/fISbh83JHZ/KJEoMW/8HREH8vPzvaCgINZlAHD6XTNYtLZ0p21pHdqRk5FCr4wUcrqkhj43PM9IoVdGKllp7ffoh4G7U7i1goXhM/UFRSUsWlvKlrJQqLdLMgb26MSQ3AyG9O7CoXkZDO7VhbQOO/983lJWzR+mL+OJD1fTLb0DPzz1IMaPyCMpKXjDOf9ZtpHbXljEmq3lO4V5Zlp7+nVLp3/3dPqFQzz0OZ2M1N3/4PvlvxbzwLuf8vdL8zlhcM8o/glEosPMZrl7frOvKeh3rbaung3bq1hfUsG6kkrWl1Q2+lzB+pJKNmyvoq5+57/DhhuudvoB0CWFnIxU6ur9i+GXtSVsK68BIDnJOLBnZ4bkduHQ3AyG5IZCfW+GEhYWlXDrCwuZvXobw/tkcvu4Qxial9mqfyextKWsmpP+9DYZae05Y2hv+ofDvH/3dDLTOkT03lW1dZxz739ZX1rJqxPH0KNLSitVLdI2FPRRVFfvbNpRFf4B0MwPhNIKNpRUUd2oTbN9O2NQTufPA31I7wwG5XRulfHh+nrnuTlF/OaVpWwuq+KC/D7cdMogunXqGPF7x9rEKXN4ecE6Xvzu0RyU06XV33/lxu2ccfe7fK1fVx6+fFQgfyOS4PqqoG+Ni7EJrV2S0bNLCj27pECf5s+e3Z0tZdWfXwg8sGdnOiRHZ5qhpCTjvJF5nHxITya9voKH/vsZLy9Yx40nD+Jbh+9Hcrt9c3qj1xdv4IW5a7nhxIFRCXmAAT06c+sZh/Dj5xbw4HufcsWY/aNyHJG2tm9+1+9jzIxunTqGzt5zM6IW8o11TmnPT884mFdvGMPQvExum7aIM+5+lw8+2Rz1Y7e2kooafvL8Ag7K6cz/Hjcgqse6aFQfTjmkJ799dSkLi0qieizZNxVvr+KeN1dw+l0zeHfFpliXs0c0dJMA3J1XF67nly8toWhbBWcN682PTxtMTsa+MQ79o6nzeXrWGp6/7qg2ueawtayasZNmkNaxHf/67tFfuvgticfdmb16K4/MXMXLC9ZRU+d0TkmmY3ISr0w8huzOsR8a/aqhG53RJwAzY+yhvXj9+8dy/QkDeXXRer7+x7f4y1srqaqti3V5X2nGimKeLFjDVccc0GYXlrPSO/Cnbwzj001l/OJfi9vkmBKfKqrrmPLhak6/613Ou28mby7ZyMVH9OWNG4/lmWuPZHtlLTc+PY/6+vg6YW5KZ/QJaPXmcn7x0mJeW7yB/t3TufXMgzl+UI9Yl/UlZVW1nHznO3RMTuLliWPa/Gam3766lPve+pj7Lx7BqUP2ibn4pJV8tqmMR99fxdMFayitrOWgnM5cMrovZw/PJb3jF7/hPfr+Kn72/EJ+ctpgrjwmttd0dDFWdrJftzT+9u183lq2kdtfXMzl//iIEwf34GdnHEzfbumxLu9zv//3MtaWVPD01aNjcsfq9048kPdWbuJHzyxgWJ9MemXE51QY0jrq6p23lm3kkZmreHt5MclJxqlDcvj26H58rV9Ws/fGXHz4fsxYXszv/r2UI/bvxqF5GTGofPd0Rp/gqmvrefC9T7nrjRXU1jtXH7M/1x0/IOZTAXz02RbOv38mlx3Zj5+fdUjM6vh0Uxmn3zWDoXkZ/POKI2inlsvA2VpWzZMFa3js/VUUbq2gR+eOfOvwvlw0qs8e3U/RcE0ntUPomk7jM/62pD562a31JZX85pUlvDB3LWMGdueBS/PpmBybsK+sqeO0STOorqvn3zccE7NvnAZPF6zhpqnz+eGpg6Le9SNtZ37hNh6ZuYpp89ZSXVvP4f278u3R/Tj5kJ6038s25Jkfb+abD7zPeSPy+MP5w6JU8VfT0I3sVk5GCpMuPIyjB3Tnpqnzuf6JOdz7zREx6bu/8/XlfLKpjH9ecXjMQx5g/Mg83lpezJ+mL+fIA7ozfBf3S0j8q6yp46X563jk/VXMW7ONtA7t+EZ+Hpcc0Y9BOS2fFHD0Ad2YcPwA7n5zJcccmM1Zw3q3YtWRi/13kcSV8/P7UFZVy89fXMxNU+fzx/OHtekdovPWbONv73zChV/rw1EDurfZcb+KmfHrsw9l7uptTJwyh5euH0OnOPgBJHtu844q/jbjU54qWMOWsmoOyE7n/846hHNH5NK5lSYBnHjCQN5buYmfPLuAw/pk0qdrWqu8b2tQe6V8yWVH9eemUwbx3Jwibp22kLYa3quuredHz8ynR+cUfnz64DY55p7KSGvPnRcMZ82Wcn4+bVGsy5G98NL8dZx05ztMfudjvtYvi39ecTivf/9YLj2yX6uFPEByuyQmXXgYANdPmUNNHK1Op6CXZv3vcQdwzbEH8Nj7q7nj1aVtEvZ/eWslS9dv51fnDInLqZZH9e/KhK8PZOqsQqbNWxvrcuJKvF3rg9AdrNc+NovrHp9NXlYqr0w8hr9eks9RA7pHbarxPl3T+PW5hzJn9TYmvb4iKsdoCf3+Kc0yM3506iDKqmr569uf0LljMhO+PjBqx1u6vpR73lzJ2cN7x/U0wdd/fQDvrijmJ8/F36/n0VJVW8fG0tDEfQ2ztn4xaV9oMr9NO6o5ekB3bh57EIN7RWcuoj3l7kybt5afT1tEWVUdPzr1IK4c07/NrjedOaw37ywv5t63VnLUgO6MPqBbmxz3q0TUdWNmmcADwBDAgf9x95mNXj8OeAH4NLzpWXe//aveU1038aW+3vnB0/N4dk4Rt515MJcf1b/Vj1FbV8+59/2Xoq0VvPb9Y+maHtmUw9G2Zks5YyfN4KCczky56oh9dqI4CN35ub60mQAvqWR9aWhbw6I3jXXumExOo7UY0jsm8+zsIkorazhvRB7fP+lAesdgCc6N2yv56XMLmb54A8P7ZPL78UMZGIOV18qqajnz7ncpr67jlYljyGqD/9PR7LqZBLzq7uPDi4Q3d3ozw93PiPA4EiNJScbvxg+lvLqO/3txMekdkvnG1/rs/gv3wgPvfsr8whLu/eaIuA95CP16/qtzhjBxylzu/c/HTDwxer/pRMM7y4v5/b+XsWZr+efrITSWmdaenC6hAD80N3OnxXV6ZYRmam1ubPuGEw7kL2+t5B///YwX563l8qP6c+1xB+zRwi+Rcneen1vEz6ctpqKmjh+fdhDfOXr/mN33kN4xmbsuOoxz/vIeP3xmPpMvGRnTdZ1bfEZvZhnAXGB/38WbhM/of7A3Qa8z+vhUVVvHlY/M4t0Vxdx10WGcMbR12sc+Lt7B2EkzOH5QNvdfHNtvhr31vSfn8sLcIp66ejT5/brGupzdqq937nv7Y/4wfRn7d0/nqAHdPw/wnl1Cq6PldEkhtUNk908Ubavgj9OX8dycIjJS2zPh+AFcMrpv1O7L2FBayU+eW8DrSzYysm8Wvxs/lAOyO0XlWHvrgRmf8MuXlvCLs4dwyRF9o3qsqNwwZWbDgcnAYmAYMAuY6O5ljfY5DngGKATWEgr9r2xZUNDHr4rqOi598ENmr97K376dz/EHRTY/Tn29c8HkmSzfsIPXvnfMPreq0/bKGk67awb19fDKDWPi8gJyg+2VNdz41DymL97AuOG9uePcoREH+u4sWlvCHa8sZcaKTeRlpXLTKYM4c2jvVmvXdXeemV3E7S8uoqq2nptOGcTlR/WPq7uX6+udyx76iA8+2cy0CUdH1Ku/O9GavTIZGAHc5+6HAWXAzU32mQ30dfdhwN3A87so8CozKzCzguLi4ghKkmhK7dCOBy7LZ3CvLlzz2CxmfhzZ3PaPvr+Kjz7bys/OOHifC3kIzfk/6cLDWF8aGheOx84TgBUbtjPunvd4c+lGbjvzYP58wfCohzzAIb0zePQ7h/Pod0bRJaU9E6fMZdy97/HfjyOfw31dSQWXP/QRP3h6HoNyOvPqDcdwxZjYDdXsSlKS8cfzh9E5JZnvPjGbyprYzBYbSdAXAoXu/kH4+VRCwf85dy919x3hxy8D7c3sS3fBuPtkd8939/zs7OwISpJo65LSnof/ZxT7dU3jioc/Ys7qrS16nzVbyvntq0s59sBszhuR28pVtp0R+2VxwwkDmTZvLc/NKYp1OV/y0vx1jLv3PUora3n8yiO4/Kj+bT48NmZgNv/67tHcecEwtpRV882/fcDl//iQpetL9/q93J2nPlrDyX96hw8+2cJtZx7Mk1eNpn/3+JmMr6nszh354zeGs3zDDn710pKY1NDioHf39cAaMxsU3nQCoWGcz5lZjoX/V5nZqPDx9r0ljmQnXdM78M8rDqd7545c9o+PWLJu775h3Z1bnl2AAb8+99B9aly+Of97/ABG9evKz55fyKrNZbv/gjZQW1fPr19ewnWPz+agnM68dP3RjOofu+sISUnGOYfl8caNx/KT0wYza9VWxk6awU1Pz2NdScUevUfRtgou/cdH/PCZ+Rzcuwuv3jCGy4/qv0+s7XvsgdlcOaY/j76/iumL1rf58SNtrxxOqL2yA/AJcDlwAYC7329mE4BrgVqgAvi+u//3q95TY/T7jjVbyjn//pnU1tfz1NWj2X8PL4A9+dFqfvTMAn559hAujvIFqrZStK2CsX9+h/7ZnZh6zei9nhSrNW3eUcWEx+cw85PNfHt0X356+sFtsnzl3thWXs1f3vqYh977DDP4ztH9uea4A5q9zuHuTPloDb96aQn17tw89iAuPrzvPhHwjVXX1nPufe9RuLWCVyaOafVprzV7pUTNyo07uOCvM+mYnMRT14wmL+urbyBaX1LJSXe+zSG9u/D4FUfsc9+sX+Wl+eu47vHZTDh+AD84ZdDuvyAK5q3ZxrWPzWJzWTW/PudQzhuZF5M69tSaLeX86bXlPDeniKy09nz36wO5+Ii+n/9gKtxazs3PLODdlZsYvX83fjd+6D59k9onxTs44+53ozLttYJeomrx2lIunDyTrukdeOqa0fTo3PyFVXfnykcKeHflJv59wzFxtchJa/nh1Hk8PauQP18wnNMP7dWmN1M98eFqbnthET26dOT+i0cyJDc+F8FozsKiUIfOuys3sV/XNH5wyiBKK2r4zcuhMe1bThvMN0ftF4gTg4Zpr286ZRDXHd96014r6CXqZq3ayiV//4A+WWk8efURZKZ9+canF+YWMXHKXH56+mCuGBPbZdeipayqlnP+8h7LN+ygR+eOnDMil/NH5jGgR/Ta6ipr6vj5tEVM+WgNxxyYzaQLhrfJnZjR8M7yYjJIGyYAAAdTSURBVH7zytLPr/scPaA7d5x36G5/U9yXuDvXT5nLywvW8dTVoxnZN6tV3ldBL23ivZWbuPyhjxic05nHrjh8p7snN+2o4qQ/vU2/7ulMvebIuGuDa03VtfW8uXQjU2cV8p9lG6mrd4b3yWT8yDzOHNa7Ve8UXbutgmsfm8W8whImHD+A75104D7/d1tf77w4fy317pw9PHefv1jfnNLKGk6bNAOAlye2zj0YCnppM68v3sA1j81iRN8sHr581Of92hMen830RRt46fqjYzL3SKwUb6/ihblFPF1QyLIN2+mQnMQph+QwfmQeRw/oHlEo/3flJiY8MYea2nr++I1hnHxITitWLtE2a9VWvvHXmZx2aC/uunB4xD/QFPTSpqbNW8vEKXM49sBsJl+Sz3+WbeTqR2fxg5MPjOoMmPHM3VlYVMrUWWt4Yd5atpXXkNMlhXNH5DJ+ZN4edyw1vNffZnzCHa8s5YDsTvz1kpF79fUSP+55cwV/mL6c348fyvn5kc0hpaCXNjflw9Xc/OwCTj64J3PWbCO7U0demHBUTNsO40VVbR1vLAkN7by1bCP1DiP7ZjF+ZB6nD+31lb/G76iq5UdT5/PSgnWcfmgvfjd+aFwstygtU1fvfOuB95lfWMK/vnt0RD+wFfQSEw0TOrVLMl647qh9qgukrWwsreS5OUU8PauQlRt3kNI+iVMPyWH8yD4ceUC3nbpMPi7ewdWPzuKT4h3cMnYwV4xp+7tcpfWtK6lg7KQZ5GWl8uy1R7X4ngcFvcTMlA9X0yE5iXNHxHc/d6y5O/MKS5g6aw3T5q6ltLKW3hkpnDcyj/NG5LFsw3ZufGoeHZKTuOeiwzgyTtbTldYxfdF6rnp0FleO6c9PTj+4Re+hoBfZh1TW1PH6kg08XVDIjBXF1Ie/RYf1yeS+b42IyYIeEn2/emkxA3p04oKv7deir1fQi+yj1peEhnbq6uu58pj9ozanu+z7ornClIhEUU5GCtced0Csy5B9nFogREQCTkEvIhJwCnoRkYBT0IuIBJyCXkQk4BT0IiIBp6AXEQk4Bb2ISMDF3Z2xZlYMrIrgLboDm1qpnGiI9/og/muM9/og/muM9/pANe6tvu6e3dwLcRf0kTKzgl3dBhwP4r0+iP8a470+iP8a470+UI2tSUM3IiIBp6AXEQm4IAb95FgXsBvxXh/Ef43xXh/Ef43xXh+oxlYTuDF6ERHZWRDP6EVEpBEFvYhIwAUm6M3sVDNbZmYrzezmWNfTlJn1MbP/mNliM1tkZhNjXVNzzKydmc0xs3/FupbmmFmmmU01s6VmtsTMRse6psbM7Hvhf9+FZvaEmaXEQU0PmtlGM1vYaFtXM3vNzFaEP2fFYY2/D/87zzez58wsM57qa/TajWbmZha3C/kGIujNrB1wLzAWOBi4yMxatsJu9NQCN7r7wcARwHVxWCPARGBJrIv4CpOAV939IGAYcVSrmeUC1wP57j4EaAdcGNuqAHgIOLXJtpuBN9x9IPBG+HksPcSXa3wNGOLuQ4HlwC1tXVQjD/Hl+jCzPsDJwOq2LmhvBCLogVHASnf/xN2rgSnAuBjXtBN3X+fus8OPtxMKqNzYVrUzM8sDTgceiHUtzTGzDOAY4O8A7l7t7ttiW9WXJAOpZpYMpAFrY1wP7v4OsKXJ5nHAw+HHDwNnt2lRTTRXo7tPd/fa8NP3gbw2L+yLWpr7OwS4E/ghENddLUEJ+lxgTaPnhcRZiDZmZv2Aw4APYlvJl/yZ0H/a+lgXsgv9gWLgH+HhpQfMLD3WRTVw9yLgD4TO7tYBJe4+PbZV7VJPd18Xfrwe6BnLYvbA/wCvxLqIxsxsHFDk7vNiXcvuBCXo9xlm1gl4BrjB3UtjXU8DMzsD2Ojus2Jdy1dIBkYA97n7YUAZsR9y+Fx4nHscoR9IvYF0M7s4tlXtnod6rOP2jNTMfkJo6POfsa6lgZmlAT8Gbo11LXsiKEFfBPRp9DwvvC2umFl7QiH/T3d/Ntb1NHEUcJaZfUZo6OvrZvZYbEv6kkKg0N0bfhOaSij448WJwKfuXuzuNcCzwJExrmlXNphZL4Dw540xrqdZZnYZcAbwLY+vm34OIPQDfV74eyYPmG1mOTGtaheCEvQfAQPNrL+ZdSB0AWxajGvaiZkZobHlJe7+p1jX05S73+Luee7ej9Df35vuHldno+6+HlhjZoPCm04AFsewpKZWA0eYWVr43/sE4uhicRPTgEvDjy8FXohhLc0ys1MJDSWe5e7lsa6nMXdf4O493L1f+HumEBgR/j8adwIR9OELNhOAfxP6xnrK3RfFtqovOQq4hNCZ8tzwx2mxLmof9F3gn2Y2HxgO/DrG9Xwu/JvGVGA2sIDQ91fMb5E3syeAmcAgMys0s+8AdwAnmdkKQr+J3BGHNd4DdAZeC3+/3B9n9e0zNAWCiEjABeKMXkREdk1BLyIScAp6EZGAU9CLiAScgl5EJOAU9CIiAaegFxEJuP8HvHiKw1jJ554AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib.ticker as ticker\n",
+    "%matplotlib inline\n",
+    "\n",
+    "plt.figure()\n",
+    "plt.plot(losses)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 预测\n",
+    "用训练好的模型进行预测。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "the input words is: of, william\n",
+      "the predict words is: shakespeare\n",
+      "the true words is: shakespeare\n"
+     ]
+    }
+   ],
+   "source": [
+    "import random\n",
+    "def test(model):\n",
+    "    model.eval()\n",
+    "    # 从最后10组数据中随机选取1个\n",
+    "    idx = random.randint(len(trigram)-10, len(trigram)-1)\n",
+    "    print('the input words is: ' + trigram[idx][0][0] + ', ' + trigram[idx][0][1])\n",
+    "    x_data = list(map(lambda w: word_to_idx[w], trigram[idx][0]))\n",
+    "    x_data = paddle.to_tensor(np.array(x_data))\n",
+    "    predicts = model(x_data)\n",
+    "    predicts = predicts.numpy().tolist()[0]\n",
+    "    predicts = predicts.index(max(predicts))\n",
+    "    print('the predict words is: ' + idx_to_word[predicts])\n",
+    "    y_data = trigram[idx][1]\n",
+    "    print('the true words is: ' + y_data)\n",
+    "test(model)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/doc/paddle/tutorial/nlp_case/n_gram_model/n_gram_model.rst b/doc/paddle/tutorial/nlp_case/n_gram_model/n_gram_model.rst
new file mode 100644
index 0000000000000000000000000000000000000000..78c224ff003ce1ba08d4f335234705992b3d9369
--- /dev/null
+++ b/doc/paddle/tutorial/nlp_case/n_gram_model/n_gram_model.rst
@@ -0,0 +1,288 @@
+用N-Gram模型在莎士比亚文集中训练word embedding
+==============================================
+
+N-gram
+是计算机语言学和概率论范畴内的概念，是指给定的一段文本中N个项目的序列。
+N=1 时 N-gram 又称为 unigram，N=2 称为 bigram，N=3 称为
+trigram，以此类推。实际应用通常采用 bigram 和 trigram 进行计算。
+本示例在莎士比亚文集上实现了trigram。
+
+环境
+----
+
+本教程基于paddle-develop编写，如果您的环境不是本版本，请先安装paddle-develop。
+
+.. code:: ipython3
+
+    import paddle
+    paddle.__version__
+
+
+
+
+.. parsed-literal::
+
+    '0.0.0'
+
+
+
+数据集&&相关参数
+----------------
+
+训练数据集采用了莎士比亚文集，\ `下载 <https://ocw.mit.edu/ans7870/6/6.006/s08/lecturenotes/files/t8.shakespeare.txt>`__\ ，保存为txt格式即可。
+context_size设为2，意味着是trigram。embedding_dim设为256。
+
+.. code:: ipython3
+
+    !wget https://ocw.mit.edu/ans7870/6/6.006/s08/lecturenotes/files/t8.shakespeare.txt
+
+
+.. parsed-literal::
+
+    --2020-09-09 14:58:26--  https://ocw.mit.edu/ans7870/6/6.006/s08/lecturenotes/files/t8.shakespeare.txt
+    正在解析主机 ocw.mit.edu (ocw.mit.edu)... 151.101.110.133
+    正在连接 ocw.mit.edu (ocw.mit.edu)|151.101.110.133|:443... 已连接。
+    已发出 HTTP 请求，正在等待回应... 200 OK
+    长度：5458199 (5.2M) [text/plain]
+    正在保存至: “t8.shakespeare.txt”
+    
+    t8.shakespeare.txt  100%[===================>]   5.21M  94.1KB/s  用时 70s       
+    
+    2020-09-09 14:59:38 (75.7 KB/s) - 已保存 “t8.shakespeare.txt” [5458199/5458199])
+    
+
+
+.. code:: ipython3
+
+    embedding_dim = 256
+    context_size = 2
+
+.. code:: ipython3
+
+    # 文件路径
+    path_to_file = './t8.shakespeare.txt'
+    test_sentence = open(path_to_file, 'rb').read().decode(encoding='utf-8')
+    
+    # 文本长度是指文本中的字符个数
+    print ('Length of text: {} characters'.format(len(test_sentence)))
+
+
+.. parsed-literal::
+
+    Length of text: 5458199 characters
+
+
+去除标点符号
+------------
+
+因为标点符号本身无实际意义，用\ ``string``\ 库中的punctuation，完成英文符号的替换。
+
+.. code:: ipython3
+
+    from string import punctuation
+    process_dicts={i:'' for i in punctuation}
+    print(process_dicts)
+
+
+.. parsed-literal::
+
+    {'!': '', '"': '', '#': '', '$': '', '%': '', '&': '', "'": '', '(': '', ')': '', '*': '', '+': '', ',': '', '-': '', '.': '', '/': '', ':': '', ';': '', '<': '', '=': '', '>': '', '?': '', '@': '', '[': '', '\\': '', ']': '', '^': '', '_': '', '`': '', '{': '', '|': '', '}': '', '~': ''}
+
+
+.. code:: ipython3
+
+    punc_table = str.maketrans(process_dicts)
+    test_sentence = test_sentence.translate(punc_table)
+    test_sentence = test_sentence.lower().split()
+    vocab = set(test_sentence)
+    print(len(vocab))
+
+
+.. parsed-literal::
+
+    28343
+
+
+数据预处理
+----------
+
+将文本被拆成了元组的形式，格式为((‘第一个词’, ‘第二个词’),
+‘第三个词’);其中，第三个词就是我们的目标。
+
+.. code:: ipython3
+
+    trigram = [[[test_sentence[i], test_sentence[i + 1]], test_sentence[i + 2]]
+               for i in range(len(test_sentence) - 2)]
+    
+    word_to_idx = {word: i for i, word in enumerate(vocab)}
+    idx_to_word = {word_to_idx[word]: word for word in word_to_idx}
+    # 看一下数据集
+    print(trigram[:3])
+
+
+.. parsed-literal::
+
+    [[['this', 'is'], 'the'], [['is', 'the'], '100th'], [['the', '100th'], 'etext']]
+
+
+构建\ ``Dataset``\ 类 加载数据
+------------------------------
+
+用\ ``paddle.io.Dataset``\ 构建数据集，然后作为参数传入到\ ``paddle.io.DataLoader``\ ，完成数据集的加载。
+
+.. code:: ipython3
+
+    import paddle
+    import numpy as np
+    batch_size = 256
+    paddle.disable_static()
+    class TrainDataset(paddle.io.Dataset):
+        def __init__(self, tuple_data):
+            self.tuple_data = tuple_data
+    
+        def __getitem__(self, idx):
+            data = self.tuple_data[idx][0]
+            label = self.tuple_data[idx][1]
+            data = np.array(list(map(lambda w: word_to_idx[w], data)))
+            label = np.array(word_to_idx[label])
+            return data, label
+        
+        def __len__(self):
+            return len(self.tuple_data)
+    train_dataset = TrainDataset(trigram)
+    train_loader = paddle.io.DataLoader(train_dataset,places=paddle.CPUPlace(), return_list=True,
+                                        shuffle=True, batch_size=batch_size, drop_last=True)
+
+组网&训练
+---------
+
+这里用paddle动态图的方式组网。为了构建Trigram模型，用一层 ``Embedding``
+与两层 ``Linear`` 完成构建。\ ``Embedding``
+层对输入的前两个单词embedding，然后输入到后面的两个\ ``Linear``\ 层中，完成特征提取。
+
+.. code:: ipython3
+
+    import paddle
+    import numpy as np
+    hidden_size = 1024
+    class NGramModel(paddle.nn.Layer):
+        def __init__(self, vocab_size, embedding_dim, context_size):
+            super(NGramModel, self).__init__()
+            self.embedding = paddle.nn.Embedding(num_embeddings=vocab_size, embedding_dim=embedding_dim)
+            self.linear1 = paddle.nn.Linear(context_size * embedding_dim, hidden_size)
+            self.linear2 = paddle.nn.Linear(hidden_size, len(vocab))
+    
+        def forward(self, x):
+            x = self.embedding(x)
+            x = paddle.reshape(x, [-1, context_size * embedding_dim])
+            x = self.linear1(x)
+            x = paddle.nn.functional.relu(x)
+            x = self.linear2(x)
+            return x
+
+定义\ ``train()``\ 函数，对模型进行训练。
+-----------------------------------------
+
+.. code:: ipython3
+
+    vocab_size = len(vocab)
+    epochs = 2
+    losses = []
+    def train(model):
+        model.train()
+        optim = paddle.optimizer.Adam(learning_rate=0.01, parameters=model.parameters())
+        for epoch in range(epochs):
+            for batch_id, data in enumerate(train_loader()):
+                x_data = data[0]
+                y_data = data[1]
+                predicts = model(x_data)
+                y_data = paddle.reshape(y_data, ([-1, 1]))
+                loss = paddle.nn.functional.softmax_with_cross_entropy(predicts, y_data)
+                avg_loss = paddle.mean(loss)
+                avg_loss.backward()
+                if batch_id % 500 == 0:
+                    losses.append(avg_loss.numpy())
+                    print("epoch: {}, batch_id: {}, loss is: {}".format(epoch, batch_id, avg_loss.numpy())) 
+                optim.minimize(avg_loss)
+                model.clear_gradients()
+    model = NGramModel(vocab_size, embedding_dim, context_size)
+    train(model)
+
+
+.. parsed-literal::
+
+    epoch: 0, batch_id: 0, loss is: [10.252193]
+    epoch: 0, batch_id: 500, loss is: [6.894636]
+    epoch: 0, batch_id: 1000, loss is: [6.849346]
+    epoch: 0, batch_id: 1500, loss is: [6.931605]
+    epoch: 0, batch_id: 2000, loss is: [6.6860313]
+    epoch: 0, batch_id: 2500, loss is: [6.2472367]
+    epoch: 0, batch_id: 3000, loss is: [6.8818874]
+    epoch: 0, batch_id: 3500, loss is: [6.941615]
+    epoch: 1, batch_id: 0, loss is: [6.3628616]
+    epoch: 1, batch_id: 500, loss is: [6.2065206]
+    epoch: 1, batch_id: 1000, loss is: [6.5334334]
+    epoch: 1, batch_id: 1500, loss is: [6.5788]
+    epoch: 1, batch_id: 2000, loss is: [6.352103]
+    epoch: 1, batch_id: 2500, loss is: [6.6272373]
+    epoch: 1, batch_id: 3000, loss is: [6.801074]
+    epoch: 1, batch_id: 3500, loss is: [6.2274427]
+
+
+打印loss下降曲线
+----------------
+
+通过可视化loss的曲线，可以看到模型训练的效果。
+
+.. code:: ipython3
+
+    import matplotlib.pyplot as plt
+    import matplotlib.ticker as ticker
+    %matplotlib inline
+    
+    plt.figure()
+    plt.plot(losses)
+
+
+
+
+.. parsed-literal::
+
+    [<matplotlib.lines.Line2D at 0x14e27b3c8>]
+
+
+
+
+.. image:: n_gram_model_files/n_gram_model_19_1.png
+
+
+预测
+----
+
+用训练好的模型进行预测。
+
+.. code:: ipython3
+
+    import random
+    def test(model):
+        model.eval()
+        # 从最后10组数据中随机选取1个
+        idx = random.randint(len(trigram)-10, len(trigram)-1)
+        print('the input words is: ' + trigram[idx][0][0] + ', ' + trigram[idx][0][1])
+        x_data = list(map(lambda w: word_to_idx[w], trigram[idx][0]))
+        x_data = paddle.to_tensor(np.array(x_data))
+        predicts = model(x_data)
+        predicts = predicts.numpy().tolist()[0]
+        predicts = predicts.index(max(predicts))
+        print('the predict words is: ' + idx_to_word[predicts])
+        y_data = trigram[idx][1]
+        print('the true words is: ' + y_data)
+    test(model)
+
+
+.. parsed-literal::
+
+    the input words is: of, william
+    the predict words is: shakespeare
+    the true words is: shakespeare
+
diff --git a/doc/paddle/tutorial/nlp_case/n_gram_model/n_gram_model_files/n_gram_model_19_1.png b/doc/paddle/tutorial/nlp_case/n_gram_model/n_gram_model_files/n_gram_model_19_1.png
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diff --git a/doc/paddle/tutorial/nlp_case/seq2seq_with_attention/seq2seq_with_attention.ipynb b/doc/paddle/tutorial/nlp_case/seq2seq_with_attention/seq2seq_with_attention.ipynb
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+++ b/doc/paddle/tutorial/nlp_case/seq2seq_with_attention/seq2seq_with_attention.ipynb
@@ -0,0 +1,665 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 使用注意力机制的LSTM的机器翻译\n",
+    "\n",
+    "本示例教程介绍如何使用飞桨完成一个机器翻译任务。我们将会使用飞桨提供的LSTM的API，组建一个`sequence to sequence with attention`的机器翻译的模型，并在示例的数据集上完成从英文翻译成中文的机器翻译。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 环境设置\n",
+    "\n",
+    "本示例教程基于飞桨2.0-beta版本。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.0.0\n",
+      "89af2088b6e74bdfeef2d4d78e08461ed2aafee5\n"
+     ]
+    }
+   ],
+   "source": [
+    "import paddle\n",
+    "import paddle.nn.functional as F\n",
+    "import re\n",
+    "import numpy as np\n",
+    "\n",
+    "paddle.disable_static()\n",
+    "print(paddle.__version__)\n",
+    "print(paddle.__git_commit__)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 下载数据集\n",
+    "\n",
+    "我们将使用 [http://www.manythings.org/anki/](http://www.manythings.org/anki/) 提供的中英文的英汉句对作为数据集，来完成本任务。该数据集含有23610个中英文双语的句对。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "--2020-09-04 16:13:35--  https://www.manythings.org/anki/cmn-eng.zip\n",
+      "Resolving www.manythings.org (www.manythings.org)... 104.24.109.196, 172.67.173.198, 2606:4700:3037::6818:6cc4, ...\n",
+      "Connecting to www.manythings.org (www.manythings.org)|104.24.109.196|:443... connected.\n",
+      "HTTP request sent, awaiting response... 200 OK\n",
+      "Length: 1030722 (1007K) [application/zip]\n",
+      "Saving to: ‘cmn-eng.zip’\n",
+      "\n",
+      "cmn-eng.zip         100%[===================>]   1007K   520KB/s    in 1.9s    \n",
+      "\n",
+      "2020-09-04 16:13:38 (520 KB/s) - ‘cmn-eng.zip’ saved [1030722/1030722]\n",
+      "\n",
+      "Archive:  cmn-eng.zip\n",
+      "  inflating: cmn.txt                 \n",
+      "  inflating: _about.txt              \n"
+     ]
+    }
+   ],
+   "source": [
+    "!wget -c https://www.manythings.org/anki/cmn-eng.zip && unzip cmn-eng.zip"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "   23610 cmn.txt\r\n"
+     ]
+    }
+   ],
+   "source": [
+    "!wc -l cmn.txt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 构建双语句对的数据结构\n",
+    "\n",
+    "接下来我们通过处理下载下来的双语句对的文本文件，将双语句对读入到python的数据结构中。这里做了如下的处理。\n",
+    "\n",
+    "- 对于英文，会把全部英文都变成小写，并只保留英文的单词。\n",
+    "- 对于中文，为了简便起见，未做分词，按照字做了切分。\n",
+    "- 为了后续的程序运行的更快，我们通过限制句子长度，和只保留部分英文单词开头的句子的方式，得到了一个较小的数据集。这样得到了一个有5508个句对的数据集。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "MAX_LEN = 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "5508\n",
+      "(['i', 'won'], ['我', '赢', '了', '。'])\n",
+      "(['he', 'ran'], ['他', '跑', '了', '。'])\n",
+      "(['i', 'quit'], ['我', '退', '出', '。'])\n",
+      "(['i', 'm', 'ok'], ['我', '沒', '事', '。'])\n",
+      "(['i', 'm', 'up'], ['我', '已', '经', '起', '来', '了', '。'])\n",
+      "(['we', 'try'], ['我', '们', '来', '试', '试', '。'])\n",
+      "(['he', 'came'], ['他', '来', '了', '。'])\n",
+      "(['he', 'runs'], ['他', '跑', '。'])\n",
+      "(['i', 'agree'], ['我', '同', '意', '。'])\n",
+      "(['i', 'm', 'ill'], ['我', '生', '病', '了', '。'])\n"
+     ]
+    }
+   ],
+   "source": [
+    "lines = open('cmn.txt', encoding='utf-8').read().strip().split('\\n')\n",
+    "words_re = re.compile(r'\\w+')\n",
+    "\n",
+    "pairs = []\n",
+    "for l in lines:\n",
+    "    en_sent, cn_sent, _ = l.split('\\t')\n",
+    "    pairs.append((words_re.findall(en_sent.lower()), list(cn_sent)))\n",
+    "\n",
+    "# create a smaller dataset to make the demo process faster\n",
+    "filtered_pairs = []\n",
+    "\n",
+    "for x in pairs:\n",
+    "    if len(x[0]) < MAX_LEN and len(x[1]) < MAX_LEN and \\\n",
+    "    x[0][0] in ('i', 'you', 'he', 'she', 'we', 'they'):\n",
+    "        filtered_pairs.append(x)\n",
+    "           \n",
+    "print(len(filtered_pairs))\n",
+    "for x in filtered_pairs[:10]: print(x) "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#  创建词表\n",
+    "\n",
+    "接下来我们分别创建中英文的词表，这两份词表会用来将英文和中文的句子转换为词的ID构成的序列。词表中还加入了如下三个特殊的词：\n",
+    "- `<pad>`: 用来对较短的句子进行填充。\n",
+    "- `<bos>`: \"begin of sentence\"， 表示句子的开始的特殊词。\n",
+    "- `<eos>`: \"end of sentence\"， 表示句子的结束的特殊词。\n",
+    "\n",
+    "Note: 在实际的任务中，可能还需要通过`<unk>`（或者`<oov>`）特殊词来表示未在词表中出现的词。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2539\n",
+      "2039\n"
+     ]
+    }
+   ],
+   "source": [
+    "en_vocab = {}\n",
+    "cn_vocab = {}\n",
+    "\n",
+    "# create special token for pad, begin of sentence, end of sentence\n",
+    "en_vocab['<pad>'], en_vocab['<bos>'], en_vocab['<eos>'] = 0, 1, 2\n",
+    "cn_vocab['<pad>'], cn_vocab['<bos>'], cn_vocab['<eos>'] = 0, 1, 2\n",
+    "\n",
+    "en_idx, cn_idx = 3, 3\n",
+    "for en, cn in filtered_pairs:\n",
+    "    for w in en: \n",
+    "        if w not in en_vocab: \n",
+    "            en_vocab[w] = en_idx\n",
+    "            en_idx += 1\n",
+    "    for w in cn:  \n",
+    "        if w not in cn_vocab: \n",
+    "            cn_vocab[w] = cn_idx\n",
+    "            cn_idx += 1\n",
+    "\n",
+    "print(len(list(en_vocab)))\n",
+    "print(len(list(cn_vocab)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 创建padding过的数据集\n",
+    "\n",
+    "接下来根据词表，我们将会创建一份实际的用于训练的用numpy array组织起来的数据集。\n",
+    "- 所有的句子都通过`<pad>`补充成为了长度相同的句子。\n",
+    "- 对于英文句子（源语言），我们将其反转了过来，这会带来更好的翻译的效果。\n",
+    "- 所创建的`padded_cn_label_sents`是训练过程中的预测的目标，即，每个中文的当前词去预测下一个词是什么词。\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(5508, 11)\n",
+      "(5508, 12)\n",
+      "(5508, 12)\n"
+     ]
+    }
+   ],
+   "source": [
+    "padded_en_sents = []\n",
+    "padded_cn_sents = []\n",
+    "padded_cn_label_sents = []\n",
+    "for en, cn in filtered_pairs:\n",
+    "    # reverse source sentence\n",
+    "    padded_en_sent = en + ['<eos>'] + ['<pad>'] * (MAX_LEN - len(en))\n",
+    "    padded_en_sent.reverse()\n",
+    "    padded_cn_sent = ['<bos>'] + cn + ['<eos>'] + ['<pad>'] * (MAX_LEN - len(cn))\n",
+    "    padded_cn_label_sent = cn + ['<eos>'] + ['<pad>'] * (MAX_LEN - len(cn) + 1) \n",
+    "\n",
+    "    padded_en_sents.append([en_vocab[w] for w in padded_en_sent])\n",
+    "    padded_cn_sents.append([cn_vocab[w] for w in padded_cn_sent])\n",
+    "    padded_cn_label_sents.append([cn_vocab[w] for w in padded_cn_label_sent])\n",
+    "\n",
+    "train_en_sents = np.array(padded_en_sents)\n",
+    "train_cn_sents = np.array(padded_cn_sents)\n",
+    "train_cn_label_sents = np.array(padded_cn_label_sents)\n",
+    "\n",
+    "print(train_en_sents.shape)\n",
+    "print(train_cn_sents.shape)\n",
+    "print(train_cn_label_sents.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 创建网络\n",
+    "\n",
+    "我们将会创建一个Encoder-AttentionDecoder架构的模型结构用来完成机器翻译任务。\n",
+    "首先我们将设置一些必要的网络结构中用到的参数。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "embedding_size = 128\n",
+    "hidden_size = 256\n",
+    "num_encoder_lstm_layers = 1\n",
+    "en_vocab_size = len(list(en_vocab))\n",
+    "cn_vocab_size = len(list(cn_vocab))\n",
+    "epochs = 20\n",
+    "batch_size = 16"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Encoder部分\n",
+    "\n",
+    "在编码器的部分，我们通过查找完Embedding之后接一个LSTM的方式构建一个对源语言编码的网络。飞桨的RNN系列的API，除了LSTM之外，还提供了SimleRNN, GRU供使用，同时，还可以使用反向RNN，双向RNN，多层RNN等形式。也可以通过`dropout`参数设置是否对多层RNN的中间层进行`dropout`处理，来防止过拟合。\n",
+    "\n",
+    "除了使用序列到序列的RNN操作之外，也可以通过SimpleRNN, GRUCell, LSTMCell等API更灵活的创建单步的RNN计算，甚至通过继承RNNCellBase来实现自己的RNN计算单元。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# encoder: simply learn representation of source sentence\n",
+    "class Encoder(paddle.nn.Layer):\n",
+    "    def __init__(self):\n",
+    "        super(Encoder, self).__init__()\n",
+    "        self.emb = paddle.nn.Embedding(en_vocab_size, embedding_size,)\n",
+    "        self.lstm = paddle.nn.LSTM(input_size=embedding_size, \n",
+    "                                   hidden_size=hidden_size, \n",
+    "                                   num_layers=num_encoder_lstm_layers)\n",
+    "\n",
+    "    def forward(self, x):\n",
+    "        x = self.emb(x)\n",
+    "        x, (_, _) = self.lstm(x)\n",
+    "        return x"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# AttentionDecoder部分\n",
+    "\n",
+    "在解码器部分，我们通过一个带有注意力机制的LSTM来完成解码。\n",
+    "\n",
+    "- 单步的LSTM：在解码器的实现的部分，我们同样使用LSTM，与Encoder部分不同的是，下面的代码，每次只让LSTM往前计算一次。整体的recurrent部分，是在训练循环内完成的。\n",
+    "- 注意力机制：这里使用了一个由两个Linear组成的网络来完成注意力机制的计算，它用来计算出目标语言在每次翻译一个词的时候，需要对源语言当中的每个词需要赋予多少的权重。\n",
+    "- 对于第一次接触这样的网络结构来说，下面的代码在理解起来可能稍微有些复杂，你可以通过插入打印每个tensor在不同步骤时的形状的方式来更好的理解。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# only move one step of LSTM, \n",
+    "# the recurrent loop is implemented inside training loop\n",
+    "class AttentionDecoder(paddle.nn.Layer):\n",
+    "    def __init__(self):\n",
+    "        super(AttentionDecoder, self).__init__()\n",
+    "        self.emb = paddle.nn.Embedding(cn_vocab_size, embedding_size)\n",
+    "        self.lstm = paddle.nn.LSTM(input_size=embedding_size + hidden_size, \n",
+    "                                   hidden_size=hidden_size)\n",
+    "\n",
+    "        # for computing attention weights\n",
+    "        self.attention_linear1 = paddle.nn.Linear(hidden_size * 2, hidden_size)\n",
+    "        self.attention_linear2 = paddle.nn.Linear(hidden_size, 1)\n",
+    "        \n",
+    "        # for computing output logits\n",
+    "        self.outlinear =paddle.nn.Linear(hidden_size, cn_vocab_size)\n",
+    "\n",
+    "    def forward(self, x, previous_hidden, previous_cell, encoder_outputs):\n",
+    "        x = self.emb(x)\n",
+    "        \n",
+    "        attention_inputs = paddle.concat((encoder_outputs, \n",
+    "                                      paddle.tile(previous_hidden, repeat_times=[1, MAX_LEN+1, 1])),\n",
+    "                                      axis=-1\n",
+    "                                     )\n",
+    "\n",
+    "        attention_hidden = self.attention_linear1(attention_inputs)\n",
+    "        attention_hidden = F.tanh(attention_hidden)\n",
+    "        attention_logits = self.attention_linear2(attention_hidden)\n",
+    "        attention_logits = paddle.squeeze(attention_logits)\n",
+    "\n",
+    "        attention_weights = F.softmax(attention_logits)        \n",
+    "        attention_weights = paddle.expand_as(paddle.unsqueeze(attention_weights, -1), \n",
+    "                                             encoder_outputs)\n",
+    "\n",
+    "        context_vector = paddle.multiply(encoder_outputs, attention_weights)               \n",
+    "        context_vector = paddle.reduce_sum(context_vector, 1)\n",
+    "        context_vector = paddle.unsqueeze(context_vector, 1)\n",
+    "        \n",
+    "        lstm_input = paddle.concat((x, context_vector), axis=-1)\n",
+    "\n",
+    "        # LSTM requirement to previous hidden/state: \n",
+    "        # (number_of_layers * direction, batch, hidden)\n",
+    "        previous_hidden = paddle.transpose(previous_hidden, [1, 0, 2])\n",
+    "        previous_cell = paddle.transpose(previous_cell, [1, 0, 2])\n",
+    "        \n",
+    "        x, (hidden, cell) = self.lstm(lstm_input, (previous_hidden, previous_cell))\n",
+    "        \n",
+    "        # change the return to (batch, number_of_layers * direction, hidden)\n",
+    "        hidden = paddle.transpose(hidden, [1, 0, 2])\n",
+    "        cell = paddle.transpose(cell, [1, 0, 2])\n",
+    "\n",
+    "        output = self.outlinear(hidden)\n",
+    "        output = paddle.squeeze(output)\n",
+    "        return output, (hidden, cell)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 训练模型\n",
+    "\n",
+    "接下来我们开始训练模型。\n",
+    "\n",
+    "- 在每个epoch开始之前，我们对训练数据进行了随机打乱。\n",
+    "- 我们通过多次调用`atten_decoder`，在这里实现了解码时的recurrent循环。\n",
+    "- `teacher forcing`策略: 在每次解码下一个词时，我们给定了训练数据当中的真实词作为了预测下一个词时的输入。相应的，你也可以尝试用模型预测的结果作为下一个词的输入。（或者混合使用）"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "epoch:0\n",
+      "iter 0, loss:[7.6194725]\n",
+      "iter 200, loss:[3.4147663]\n",
+      "epoch:1\n",
+      "iter 0, loss:[3.0931656]\n",
+      "iter 200, loss:[2.7543137]\n",
+      "epoch:2\n",
+      "iter 0, loss:[2.8413522]\n",
+      "iter 200, loss:[2.340513]\n",
+      "epoch:3\n",
+      "iter 0, loss:[2.597812]\n",
+      "iter 200, loss:[2.5552855]\n",
+      "epoch:4\n",
+      "iter 0, loss:[2.0783448]\n",
+      "iter 200, loss:[2.4544785]\n",
+      "epoch:5\n",
+      "iter 0, loss:[1.8709135]\n",
+      "iter 200, loss:[1.8736631]\n",
+      "epoch:6\n",
+      "iter 0, loss:[1.9589291]\n",
+      "iter 200, loss:[2.119414]\n",
+      "epoch:7\n",
+      "iter 0, loss:[1.5829577]\n",
+      "iter 200, loss:[1.6002902]\n",
+      "epoch:8\n",
+      "iter 0, loss:[1.6022769]\n",
+      "iter 200, loss:[1.52694]\n",
+      "epoch:9\n",
+      "iter 0, loss:[1.3616685]\n",
+      "iter 200, loss:[1.5420443]\n",
+      "epoch:10\n",
+      "iter 0, loss:[1.0397792]\n",
+      "iter 200, loss:[1.2458231]\n",
+      "epoch:11\n",
+      "iter 0, loss:[1.2107158]\n",
+      "iter 200, loss:[1.426417]\n",
+      "epoch:12\n",
+      "iter 0, loss:[1.1840894]\n",
+      "iter 200, loss:[1.0999664]\n",
+      "epoch:13\n",
+      "iter 0, loss:[1.0968472]\n",
+      "iter 200, loss:[0.8149167]\n",
+      "epoch:14\n",
+      "iter 0, loss:[0.95585203]\n",
+      "iter 200, loss:[1.0070628]\n",
+      "epoch:15\n",
+      "iter 0, loss:[0.89463925]\n",
+      "iter 200, loss:[0.8288595]\n",
+      "epoch:16\n",
+      "iter 0, loss:[0.5672495]\n",
+      "iter 200, loss:[0.7317069]\n",
+      "epoch:17\n",
+      "iter 0, loss:[0.76785177]\n",
+      "iter 200, loss:[0.5319323]\n",
+      "epoch:18\n",
+      "iter 0, loss:[0.5250005]\n",
+      "iter 200, loss:[0.4182841]\n",
+      "epoch:19\n",
+      "iter 0, loss:[0.52320284]\n",
+      "iter 200, loss:[0.47618982]\n"
+     ]
+    }
+   ],
+   "source": [
+    "encoder = Encoder()\n",
+    "atten_decoder = AttentionDecoder()\n",
+    "\n",
+    "opt = paddle.optimizer.Adam(learning_rate=0.001, \n",
+    "                            parameters=encoder.parameters()+atten_decoder.parameters())\n",
+    "\n",
+    "for epoch in range(epochs):\n",
+    "    print(\"epoch:{}\".format(epoch))\n",
+    "\n",
+    "    # shuffle training data\n",
+    "    perm = np.random.permutation(len(train_en_sents))\n",
+    "    train_en_sents_shuffled = train_en_sents[perm]\n",
+    "    train_cn_sents_shuffled = train_cn_sents[perm]\n",
+    "    train_cn_label_sents_shuffled = train_cn_label_sents[perm]\n",
+    "\n",
+    "    for iteration in range(train_en_sents_shuffled.shape[0] // batch_size):\n",
+    "        x_data = train_en_sents_shuffled[(batch_size*iteration):(batch_size*(iteration+1))]\n",
+    "        sent = paddle.to_tensor(x_data)\n",
+    "        en_repr = encoder(sent)\n",
+    "\n",
+    "        x_cn_data = train_cn_sents_shuffled[(batch_size*iteration):(batch_size*(iteration+1))]\n",
+    "        x_cn_label_data = train_cn_label_sents_shuffled[(batch_size*iteration):(batch_size*(iteration+1))]\n",
+    "\n",
+    "        # shape: (batch,  num_layer(=1 here) * num_of_direction(=1 here), hidden_size)\n",
+    "        hidden = paddle.zeros([batch_size, 1, hidden_size])\n",
+    "        cell = paddle.zeros([batch_size, 1, hidden_size])\n",
+    "\n",
+    "        loss = paddle.zeros([1])\n",
+    "        # the decoder recurrent loop mentioned above\n",
+    "        for i in range(MAX_LEN + 2):\n",
+    "            cn_word = paddle.to_tensor(x_cn_data[:,i:i+1])\n",
+    "            cn_word_label = paddle.to_tensor(x_cn_label_data[:,i:i+1])\n",
+    "\n",
+    "            logits, (hidden, cell) = atten_decoder(cn_word, hidden, cell, en_repr)\n",
+    "            step_loss = F.softmax_with_cross_entropy(logits, cn_word_label)\n",
+    "            avg_step_loss = paddle.mean(step_loss)\n",
+    "            loss += avg_step_loss\n",
+    "\n",
+    "        loss = loss / (MAX_LEN + 2)\n",
+    "        if(iteration % 200 == 0):\n",
+    "            print(\"iter {}, loss:{}\".format(iteration, loss.numpy()))\n",
+    "\n",
+    "        loss.backward()\n",
+    "        opt.minimize(loss)\n",
+    "        encoder.clear_gradients()\n",
+    "        atten_decoder.clear_gradients()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 使用模型进行机器翻译\n",
+    "\n",
+    "根据你所使用的计算设备的不同，上面的训练过程可能需要不等的时间。（在一台Mac笔记本上，大约耗时15~20分钟）\n",
+    "完成上面的模型训练之后，我们可以得到一个能够从英文翻译成中文的机器翻译模型。接下来我们通过一个greedy search来实现使用该模型完成实际的机器翻译。（实际的任务中，你可能需要用beam search算法来提升效果）"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "i agree with him\n",
+      "true: 我同意他。\n",
+      "pred: 我同意他。\n",
+      "i think i ll take a bath tonight\n",
+      "true: 我想我今晚會洗澡。\n",
+      "pred: 我想我今晚會洗澡。\n",
+      "he asked for a drink of water\n",
+      "true: 他要了水喝。\n",
+      "pred: 他喝了一杯水。\n",
+      "i began running\n",
+      "true: 我開始跑。\n",
+      "pred: 我開始跑。\n",
+      "i m sick\n",
+      "true: 我生病了。\n",
+      "pred: 我生病了。\n",
+      "you had better go to the dentist s\n",
+      "true: 你最好去看牙醫。\n",
+      "pred: 你最好去看牙醫。\n",
+      "we went for a walk in the forest\n",
+      "true: 我们去了林中散步。\n",
+      "pred: 我們去公园散步。\n",
+      "you ve arrived very early\n",
+      "true: 你來得很早。\n",
+      "pred: 你去早个。\n",
+      "he pretended not to be listening\n",
+      "true: 他裝作沒在聽。\n",
+      "pred: 他假装聽到它。\n",
+      "he always wanted to study japanese\n",
+      "true: 他一直想學日語。\n",
+      "pred: 他一直想學日語。\n"
+     ]
+    }
+   ],
+   "source": [
+    "encoder.eval()\n",
+    "atten_decoder.eval()\n",
+    "\n",
+    "num_of_exampels_to_evaluate = 10\n",
+    "\n",
+    "indices = np.random.choice(len(train_en_sents),  num_of_exampels_to_evaluate, replace=False)\n",
+    "x_data = train_en_sents[indices]\n",
+    "sent = paddle.to_tensor(x_data)\n",
+    "en_repr = encoder(sent)\n",
+    "\n",
+    "word = np.array(\n",
+    "    [[cn_vocab['<bos>']]] * num_of_exampels_to_evaluate\n",
+    ")\n",
+    "word = paddle.to_tensor(word)\n",
+    "\n",
+    "hidden = paddle.zeros([num_of_exampels_to_evaluate, 1, hidden_size])\n",
+    "cell = paddle.zeros([num_of_exampels_to_evaluate, 1, hidden_size])\n",
+    "\n",
+    "decoded_sent = []\n",
+    "for i in range(MAX_LEN + 2):\n",
+    "    logits, (hidden, cell) = atten_decoder(word, hidden, cell, en_repr)\n",
+    "    word = paddle.argmax(logits, axis=1)\n",
+    "    decoded_sent.append(word.numpy())\n",
+    "    word = paddle.unsqueeze(word, axis=-1)\n",
+    "    \n",
+    "results = np.stack(decoded_sent, axis=1)\n",
+    "for i in range(num_of_exampels_to_evaluate):\n",
+    "    en_input = \" \".join(filtered_pairs[indices[i]][0])\n",
+    "    ground_truth_translate = \"\".join(filtered_pairs[indices[i]][1])\n",
+    "    model_translate = \"\"\n",
+    "    for k in results[i]:\n",
+    "        w = list(cn_vocab)[k]\n",
+    "        if w != '<pad>' and w != '<eos>':\n",
+    "            model_translate += w\n",
+    "    print(en_input)\n",
+    "    print(\"true: {}\".format(ground_truth_translate))\n",
+    "    print(\"pred: {}\".format(model_translate))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# The End\n",
+    "\n",
+    "你还可以通过变换网络结构，调整数据集，尝试不同的参数的方式来进一步提升本示例当中的机器翻译的效果。同时，也可以尝试在其他的类似的任务中用飞桨来完成实际的实践。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/doc/paddle/tutorial/nlp_case/seq2seq_with_attention/seq2seq_with_attention.rst b/doc/paddle/tutorial/nlp_case/seq2seq_with_attention/seq2seq_with_attention.rst
new file mode 100644
index 0000000000000000000000000000000000000000..8002c68adaefba71c5c0179b75e9c9ff84ac6296
--- /dev/null
+++ b/doc/paddle/tutorial/nlp_case/seq2seq_with_attention/seq2seq_with_attention.rst
@@ -0,0 +1,517 @@
+使用注意力机制的LSTM的机器翻译
+==============================
+
+本示例教程介绍如何使用飞桨完成一个机器翻译任务。我们将会使用飞桨提供的LSTM的API，组建一个\ ``sequence to sequence with attention``\ 的机器翻译的模型，并在示例的数据集上完成从英文翻译成中文的机器翻译。
+
+环境设置
+---------
+
+本示例教程基于飞桨2.0-beta版本。
+
+.. code:: ipython3
+
+    import paddle
+    import paddle.nn.functional as F
+    import re
+    import numpy as np
+    
+    paddle.disable_static()
+    print(paddle.__version__)
+    print(paddle.__git_commit__)
+
+
+.. parsed-literal::
+
+    0.0.0
+    89af2088b6e74bdfeef2d4d78e08461ed2aafee5
+
+
+下载数据集
+------------
+
+我们将使用 http://www.manythings.org/anki/
+提供的中英文的英汉句对作为数据集，来完成本任务。该数据集含有23610个中英文双语的句对。
+
+.. code:: ipython3
+
+    !wget -c https://www.manythings.org/anki/cmn-eng.zip && unzip cmn-eng.zip
+
+
+.. parsed-literal::
+
+    --2020-09-04 16:13:35--  https://www.manythings.org/anki/cmn-eng.zip
+    Resolving www.manythings.org (www.manythings.org)... 104.24.109.196, 172.67.173.198, 2606:4700:3037::6818:6cc4, ...
+    Connecting to www.manythings.org (www.manythings.org)|104.24.109.196|:443... connected.
+    HTTP request sent, awaiting response... 200 OK
+    Length: 1030722 (1007K) [application/zip]
+    Saving to: ‘cmn-eng.zip’
+    
+    cmn-eng.zip         100%[===================>]   1007K   520KB/s    in 1.9s    
+    
+    2020-09-04 16:13:38 (520 KB/s) - ‘cmn-eng.zip’ saved [1030722/1030722]
+    
+    Archive:  cmn-eng.zip
+      inflating: cmn.txt                 
+      inflating: _about.txt              
+
+
+.. code:: ipython3
+
+    !wc -l cmn.txt
+
+
+.. parsed-literal::
+
+       23610 cmn.txt
+
+
+构建双语句对的数据结构
+-------------------------
+
+接下来我们通过处理下载下来的双语句对的文本文件，将双语句对读入到python的数据结构中。这里做了如下的处理。
+
+-  对于英文，会把全部英文都变成小写，并只保留英文的单词。
+-  对于中文，为了简便起见，未做分词，按照字做了切分。
+-  为了后续的程序运行的更快，我们通过限制句子长度，和只保留部分英文单词开头的句子的方式，得到了一个较小的数据集。这样得到了一个有5508个句对的数据集。
+
+.. code:: ipython3
+
+    MAX_LEN = 10
+
+.. code:: ipython3
+
+    lines = open('cmn.txt', encoding='utf-8').read().strip().split('\n')
+    words_re = re.compile(r'\w+')
+    
+    pairs = []
+    for l in lines:
+        en_sent, cn_sent, _ = l.split('\t')
+        pairs.append((words_re.findall(en_sent.lower()), list(cn_sent)))
+    
+    # create a smaller dataset to make the demo process faster
+    filtered_pairs = []
+    
+    for x in pairs:
+        if len(x[0]) < MAX_LEN and len(x[1]) < MAX_LEN and \
+        x[0][0] in ('i', 'you', 'he', 'she', 'we', 'they'):
+            filtered_pairs.append(x)
+               
+    print(len(filtered_pairs))
+    for x in filtered_pairs[:10]: print(x) 
+
+
+.. parsed-literal::
+
+    5508
+    (['i', 'won'], ['我', '赢', '了', '。'])
+    (['he', 'ran'], ['他', '跑', '了', '。'])
+    (['i', 'quit'], ['我', '退', '出', '。'])
+    (['i', 'm', 'ok'], ['我', '沒', '事', '。'])
+    (['i', 'm', 'up'], ['我', '已', '经', '起', '来', '了', '。'])
+    (['we', 'try'], ['我', '们', '来', '试', '试', '。'])
+    (['he', 'came'], ['他', '来', '了', '。'])
+    (['he', 'runs'], ['他', '跑', '。'])
+    (['i', 'agree'], ['我', '同', '意', '。'])
+    (['i', 'm', 'ill'], ['我', '生', '病', '了', '。'])
+
+
+创建词表
+----------
+
+接下来我们分别创建中英文的词表，这两份词表会用来将英文和中文的句子转换为词的ID构成的序列。词表中还加入了如下三个特殊的词：
+- ``<pad>``: 用来对较短的句子进行填充。 - ``<bos>``: “begin of
+sentence”， 表示句子的开始的特殊词。 - ``<eos>``: “end of sentence”，
+表示句子的结束的特殊词。
+
+Note:
+在实际的任务中，可能还需要通过\ ``<unk>``\ （或者\ ``<oov>``\ ）特殊词来表示未在词表中出现的词。
+
+.. code:: ipython3
+
+    en_vocab = {}
+    cn_vocab = {}
+    
+    # create special token for pad, begin of sentence, end of sentence
+    en_vocab['<pad>'], en_vocab['<bos>'], en_vocab['<eos>'] = 0, 1, 2
+    cn_vocab['<pad>'], cn_vocab['<bos>'], cn_vocab['<eos>'] = 0, 1, 2
+    
+    en_idx, cn_idx = 3, 3
+    for en, cn in filtered_pairs:
+        for w in en: 
+            if w not in en_vocab: 
+                en_vocab[w] = en_idx
+                en_idx += 1
+        for w in cn:  
+            if w not in cn_vocab: 
+                cn_vocab[w] = cn_idx
+                cn_idx += 1
+    
+    print(len(list(en_vocab)))
+    print(len(list(cn_vocab)))
+
+
+.. parsed-literal::
+
+    2539
+    2039
+
+
+创建padding过的数据集
+-----------------------------
+
+接下来根据词表，我们将会创建一份实际的用于训练的用numpy
+array组织起来的数据集。 -
+所有的句子都通过\ ``<pad>``\ 补充成为了长度相同的句子。 -
+对于英文句子（源语言），我们将其反转了过来，这会带来更好的翻译的效果。 -
+所创建的\ ``padded_cn_label_sents``\ 是训练过程中的预测的目标，即，每个中文的当前词去预测下一个词是什么词。
+
+.. code:: ipython3
+
+    padded_en_sents = []
+    padded_cn_sents = []
+    padded_cn_label_sents = []
+    for en, cn in filtered_pairs:
+        # reverse source sentence
+        padded_en_sent = en + ['<eos>'] + ['<pad>'] * (MAX_LEN - len(en))
+        padded_en_sent.reverse()
+        padded_cn_sent = ['<bos>'] + cn + ['<eos>'] + ['<pad>'] * (MAX_LEN - len(cn))
+        padded_cn_label_sent = cn + ['<eos>'] + ['<pad>'] * (MAX_LEN - len(cn) + 1) 
+    
+        padded_en_sents.append([en_vocab[w] for w in padded_en_sent])
+        padded_cn_sents.append([cn_vocab[w] for w in padded_cn_sent])
+        padded_cn_label_sents.append([cn_vocab[w] for w in padded_cn_label_sent])
+    
+    train_en_sents = np.array(padded_en_sents)
+    train_cn_sents = np.array(padded_cn_sents)
+    train_cn_label_sents = np.array(padded_cn_label_sents)
+    
+    print(train_en_sents.shape)
+    print(train_cn_sents.shape)
+    print(train_cn_label_sents.shape)
+
+
+.. parsed-literal::
+
+    (5508, 11)
+    (5508, 12)
+    (5508, 12)
+
+
+创建网络
+---------
+
+我们将会创建一个Encoder-AttentionDecoder架构的模型结构用来完成机器翻译任务。
+首先我们将设置一些必要的网络结构中用到的参数。
+
+.. code:: ipython3
+
+    embedding_size = 128
+    hidden_size = 256
+    num_encoder_lstm_layers = 1
+    en_vocab_size = len(list(en_vocab))
+    cn_vocab_size = len(list(cn_vocab))
+    epochs = 20
+    batch_size = 16
+
+Encoder部分
+----------------
+
+在编码器的部分，我们通过查找完Embedding之后接一个LSTM的方式构建一个对源语言编码的网络。飞桨的RNN系列的API，除了LSTM之外，还提供了SimleRNN,
+GRU供使用，同时，还可以使用反向RNN，双向RNN，多层RNN等形式。也可以通过\ ``dropout``\ 参数设置是否对多层RNN的中间层进行\ ``dropout``\ 处理，来防止过拟合。
+
+除了使用序列到序列的RNN操作之外，也可以通过SimpleRNN, GRUCell,
+LSTMCell等API更灵活的创建单步的RNN计算，甚至通过继承RNNCellBase来实现自己的RNN计算单元。
+
+.. code:: ipython3
+
+    # encoder: simply learn representation of source sentence
+    class Encoder(paddle.nn.Layer):
+        def __init__(self):
+            super(Encoder, self).__init__()
+            self.emb = paddle.nn.Embedding(en_vocab_size, embedding_size,)
+            self.lstm = paddle.nn.LSTM(input_size=embedding_size, 
+                                       hidden_size=hidden_size, 
+                                       num_layers=num_encoder_lstm_layers)
+    
+        def forward(self, x):
+            x = self.emb(x)
+            x, (_, _) = self.lstm(x)
+            return x
+
+AttentionDecoder部分
+------------------------
+
+在解码器部分，我们通过一个带有注意力机制的LSTM来完成解码。
+
+-  单步的LSTM：在解码器的实现的部分，我们同样使用LSTM，与Encoder部分不同的是，下面的代码，每次只让LSTM往前计算一次。整体的recurrent部分，是在训练循环内完成的。
+-  注意力机制：这里使用了一个由两个Linear组成的网络来完成注意力机制的计算，它用来计算出目标语言在每次翻译一个词的时候，需要对源语言当中的每个词需要赋予多少的权重。
+-  对于第一次接触这样的网络结构来说，下面的代码在理解起来可能稍微有些复杂，你可以通过插入打印每个tensor在不同步骤时的形状的方式来更好的理解。
+
+.. code:: ipython3
+
+    # only move one step of LSTM, 
+    # the recurrent loop is implemented inside training loop
+    class AttentionDecoder(paddle.nn.Layer):
+        def __init__(self):
+            super(AttentionDecoder, self).__init__()
+            self.emb = paddle.nn.Embedding(cn_vocab_size, embedding_size)
+            self.lstm = paddle.nn.LSTM(input_size=embedding_size + hidden_size, 
+                                       hidden_size=hidden_size)
+    
+            # for computing attention weights
+            self.attention_linear1 = paddle.nn.Linear(hidden_size * 2, hidden_size)
+            self.attention_linear2 = paddle.nn.Linear(hidden_size, 1)
+            
+            # for computing output logits
+            self.outlinear =paddle.nn.Linear(hidden_size, cn_vocab_size)
+    
+        def forward(self, x, previous_hidden, previous_cell, encoder_outputs):
+            x = self.emb(x)
+            
+            attention_inputs = paddle.concat((encoder_outputs, 
+                                          paddle.tile(previous_hidden, repeat_times=[1, MAX_LEN+1, 1])),
+                                          axis=-1
+                                         )
+    
+            attention_hidden = self.attention_linear1(attention_inputs)
+            attention_hidden = F.tanh(attention_hidden)
+            attention_logits = self.attention_linear2(attention_hidden)
+            attention_logits = paddle.squeeze(attention_logits)
+    
+            attention_weights = F.softmax(attention_logits)        
+            attention_weights = paddle.expand_as(paddle.unsqueeze(attention_weights, -1), 
+                                                 encoder_outputs)
+    
+            context_vector = paddle.multiply(encoder_outputs, attention_weights)               
+            context_vector = paddle.reduce_sum(context_vector, 1)
+            context_vector = paddle.unsqueeze(context_vector, 1)
+            
+            lstm_input = paddle.concat((x, context_vector), axis=-1)
+    
+            # LSTM requirement to previous hidden/state: 
+            # (number_of_layers * direction, batch, hidden)
+            previous_hidden = paddle.transpose(previous_hidden, [1, 0, 2])
+            previous_cell = paddle.transpose(previous_cell, [1, 0, 2])
+            
+            x, (hidden, cell) = self.lstm(lstm_input, (previous_hidden, previous_cell))
+            
+            # change the return to (batch, number_of_layers * direction, hidden)
+            hidden = paddle.transpose(hidden, [1, 0, 2])
+            cell = paddle.transpose(cell, [1, 0, 2])
+    
+            output = self.outlinear(hidden)
+            output = paddle.squeeze(output)
+            return output, (hidden, cell)
+
+训练模型
+--------
+
+接下来我们开始训练模型。
+
+-  在每个epoch开始之前，我们对训练数据进行了随机打乱。
+-  我们通过多次调用\ ``atten_decoder``\ ，在这里实现了解码时的recurrent循环。
+-  ``teacher forcing``\ 策略:
+   在每次解码下一个词时，我们给定了训练数据当中的真实词作为了预测下一个词时的输入。相应的，你也可以尝试用模型预测的结果作为下一个词的输入。（或者混合使用）
+
+.. code:: ipython3
+
+    encoder = Encoder()
+    atten_decoder = AttentionDecoder()
+    
+    opt = paddle.optimizer.Adam(learning_rate=0.001, 
+                                parameters=encoder.parameters()+atten_decoder.parameters())
+    
+    for epoch in range(epochs):
+        print("epoch:{}".format(epoch))
+    
+        # shuffle training data
+        perm = np.random.permutation(len(train_en_sents))
+        train_en_sents_shuffled = train_en_sents[perm]
+        train_cn_sents_shuffled = train_cn_sents[perm]
+        train_cn_label_sents_shuffled = train_cn_label_sents[perm]
+    
+        for iteration in range(train_en_sents_shuffled.shape[0] // batch_size):
+            x_data = train_en_sents_shuffled[(batch_size*iteration):(batch_size*(iteration+1))]
+            sent = paddle.to_tensor(x_data)
+            en_repr = encoder(sent)
+    
+            x_cn_data = train_cn_sents_shuffled[(batch_size*iteration):(batch_size*(iteration+1))]
+            x_cn_label_data = train_cn_label_sents_shuffled[(batch_size*iteration):(batch_size*(iteration+1))]
+    
+            # shape: (batch,  num_layer(=1 here) * num_of_direction(=1 here), hidden_size)
+            hidden = paddle.zeros([batch_size, 1, hidden_size])
+            cell = paddle.zeros([batch_size, 1, hidden_size])
+    
+            loss = paddle.zeros([1])
+            # the decoder recurrent loop mentioned above
+            for i in range(MAX_LEN + 2):
+                cn_word = paddle.to_tensor(x_cn_data[:,i:i+1])
+                cn_word_label = paddle.to_tensor(x_cn_label_data[:,i:i+1])
+    
+                logits, (hidden, cell) = atten_decoder(cn_word, hidden, cell, en_repr)
+                step_loss = F.softmax_with_cross_entropy(logits, cn_word_label)
+                avg_step_loss = paddle.mean(step_loss)
+                loss += avg_step_loss
+    
+            loss = loss / (MAX_LEN + 2)
+            if(iteration % 200 == 0):
+                print("iter {}, loss:{}".format(iteration, loss.numpy()))
+    
+            loss.backward()
+            opt.minimize(loss)
+            encoder.clear_gradients()
+            atten_decoder.clear_gradients()
+
+
+.. parsed-literal::
+
+    epoch:0
+    iter 0, loss:[7.6194725]
+    iter 200, loss:[3.4147663]
+    epoch:1
+    iter 0, loss:[3.0931656]
+    iter 200, loss:[2.7543137]
+    epoch:2
+    iter 0, loss:[2.8413522]
+    iter 200, loss:[2.340513]
+    epoch:3
+    iter 0, loss:[2.597812]
+    iter 200, loss:[2.5552855]
+    epoch:4
+    iter 0, loss:[2.0783448]
+    iter 200, loss:[2.4544785]
+    epoch:5
+    iter 0, loss:[1.8709135]
+    iter 200, loss:[1.8736631]
+    epoch:6
+    iter 0, loss:[1.9589291]
+    iter 200, loss:[2.119414]
+    epoch:7
+    iter 0, loss:[1.5829577]
+    iter 200, loss:[1.6002902]
+    epoch:8
+    iter 0, loss:[1.6022769]
+    iter 200, loss:[1.52694]
+    epoch:9
+    iter 0, loss:[1.3616685]
+    iter 200, loss:[1.5420443]
+    epoch:10
+    iter 0, loss:[1.0397792]
+    iter 200, loss:[1.2458231]
+    epoch:11
+    iter 0, loss:[1.2107158]
+    iter 200, loss:[1.426417]
+    epoch:12
+    iter 0, loss:[1.1840894]
+    iter 200, loss:[1.0999664]
+    epoch:13
+    iter 0, loss:[1.0968472]
+    iter 200, loss:[0.8149167]
+    epoch:14
+    iter 0, loss:[0.95585203]
+    iter 200, loss:[1.0070628]
+    epoch:15
+    iter 0, loss:[0.89463925]
+    iter 200, loss:[0.8288595]
+    epoch:16
+    iter 0, loss:[0.5672495]
+    iter 200, loss:[0.7317069]
+    epoch:17
+    iter 0, loss:[0.76785177]
+    iter 200, loss:[0.5319323]
+    epoch:18
+    iter 0, loss:[0.5250005]
+    iter 200, loss:[0.4182841]
+    epoch:19
+    iter 0, loss:[0.52320284]
+    iter 200, loss:[0.47618982]
+
+
+使用模型进行机器翻译
+-----------------------
+
+根据你所使用的计算设备的不同，上面的训练过程可能需要不等的时间。（在一台Mac笔记本上，大约耗时15~20分钟）
+完成上面的模型训练之后，我们可以得到一个能够从英文翻译成中文的机器翻译模型。接下来我们通过一个greedy
+search来实现使用该模型完成实际的机器翻译。（实际的任务中，你可能需要用beam
+search算法来提升效果）
+
+.. code:: ipython3
+
+    encoder.eval()
+    atten_decoder.eval()
+    
+    num_of_exampels_to_evaluate = 10
+    
+    indices = np.random.choice(len(train_en_sents),  num_of_exampels_to_evaluate, replace=False)
+    x_data = train_en_sents[indices]
+    sent = paddle.to_tensor(x_data)
+    en_repr = encoder(sent)
+    
+    word = np.array(
+        [[cn_vocab['<bos>']]] * num_of_exampels_to_evaluate
+    )
+    word = paddle.to_tensor(word)
+    
+    hidden = paddle.zeros([num_of_exampels_to_evaluate, 1, hidden_size])
+    cell = paddle.zeros([num_of_exampels_to_evaluate, 1, hidden_size])
+    
+    decoded_sent = []
+    for i in range(MAX_LEN + 2):
+        logits, (hidden, cell) = atten_decoder(word, hidden, cell, en_repr)
+        word = paddle.argmax(logits, axis=1)
+        decoded_sent.append(word.numpy())
+        word = paddle.unsqueeze(word, axis=-1)
+        
+    results = np.stack(decoded_sent, axis=1)
+    for i in range(num_of_exampels_to_evaluate):
+        en_input = " ".join(filtered_pairs[indices[i]][0])
+        ground_truth_translate = "".join(filtered_pairs[indices[i]][1])
+        model_translate = ""
+        for k in results[i]:
+            w = list(cn_vocab)[k]
+            if w != '<pad>' and w != '<eos>':
+                model_translate += w
+        print(en_input)
+        print("true: {}".format(ground_truth_translate))
+        print("pred: {}".format(model_translate))
+
+
+.. parsed-literal::
+
+    i agree with him
+    true: 我同意他。
+    pred: 我同意他。
+    i think i ll take a bath tonight
+    true: 我想我今晚會洗澡。
+    pred: 我想我今晚會洗澡。
+    he asked for a drink of water
+    true: 他要了水喝。
+    pred: 他喝了一杯水。
+    i began running
+    true: 我開始跑。
+    pred: 我開始跑。
+    i m sick
+    true: 我生病了。
+    pred: 我生病了。
+    you had better go to the dentist s
+    true: 你最好去看牙醫。
+    pred: 你最好去看牙醫。
+    we went for a walk in the forest
+    true: 我们去了林中散步。
+    pred: 我們去公园散步。
+    you ve arrived very early
+    true: 你來得很早。
+    pred: 你去早个。
+    he pretended not to be listening
+    true: 他裝作沒在聽。
+    pred: 他假装聽到它。
+    he always wanted to study japanese
+    true: 他一直想學日語。
+    pred: 他一直想學日語。
+
+
+The End
+-------
+
+你还可以通过变换网络结构，调整数据集，尝试不同的参数的方式来进一步提升本示例当中的机器翻译的效果。同时，也可以尝试在其他的类似的任务中用飞桨来完成实际的实践。
+
diff --git a/doc/paddle/tutorial/quick_start/dynamic_graph/dynamic_graph.ipynb b/doc/paddle/tutorial/quick_start/dynamic_graph/dynamic_graph.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..ff48fae8a18c7f20331365a139508c6ef60b1c45
--- /dev/null
+++ b/doc/paddle/tutorial/quick_start/dynamic_graph/dynamic_graph.ipynb
@@ -0,0 +1,308 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 动态图\n",
+    "\n",
+    "从飞桨开源框架2.0beta版本开始，飞桨默认为用户开启了动态图模式。在这种模式下，每次执行一个运算，可以立即得到结果（而不是事先定义好网络结构，然后再执行）。\n",
+    "\n",
+    "在动态图模式下，您可以更加方便的组织代码，更容易的调试程序，本示例教程将向你介绍飞桨的动态图的使用。\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 设置环境\n",
+    "\n",
+    "我们将使用飞桨2.0beta版本，并确认已经开启了动态图模式。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.0.0\n",
+      "89af2088b6e74bdfeef2d4d78e08461ed2aafee5\n"
+     ]
+    }
+   ],
+   "source": [
+    "import paddle\n",
+    "import paddle.nn.functional as F\n",
+    "import numpy as np\n",
+    "\n",
+    "paddle.disable_static()\n",
+    "print(paddle.__version__)\n",
+    "print(paddle.__git_commit__)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 基本用法\n",
+    "\n",
+    "在动态图模式下，您可以直接运行一个飞桨提供的API，它会立刻返回结果到python。不再需要首先创建一个计算图，然后再给定数据去运行。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[-0.49341336 -0.8112665 ]\n",
+      " [ 0.8929015   0.24661176]\n",
+      " [-0.64440054 -0.7945008 ]\n",
+      " [-0.07345356  1.3641853 ]]\n",
+      "[1. 2.]\n",
+      "[[0.5065867  1.1887336 ]\n",
+      " [1.8929014  2.2466118 ]\n",
+      " [0.35559946 1.2054992 ]\n",
+      " [0.92654645 3.3641853 ]]\n",
+      "[-2.1159463  1.386125  -2.2334023  2.654917 ]\n"
+     ]
+    }
+   ],
+   "source": [
+    "a = paddle.randn([4, 2])\n",
+    "b = paddle.arange(1, 3, dtype='float32')\n",
+    "\n",
+    "print(a.numpy())\n",
+    "print(b.numpy())\n",
+    "\n",
+    "c = a + b\n",
+    "print(c.numpy())\n",
+    "\n",
+    "d = paddle.matmul(a, b)\n",
+    "print(d.numpy())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 使用python的控制流\n",
+    "\n",
+    "动态图模式下，您可以使用python的条件判断和循环，这类控制语句来执行神经网络的计算。（不再需要`cond`, `loop`这类OP)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0 +> [5 6 7]\n",
+      "1 +> [5 7 9]\n",
+      "2 +> [ 5  9 15]\n",
+      "3 -> [-3  3 21]\n",
+      "4 -> [-3 11 75]\n",
+      "5 +> [  5  37 249]\n",
+      "6 +> [  5  69 735]\n",
+      "7 -> [  -3  123 2181]\n",
+      "8 +> [   5  261 6567]\n",
+      "9 +> [    5   517 19689]\n"
+     ]
+    }
+   ],
+   "source": [
+    "a = paddle.to_tensor(np.array([1, 2, 3]))\n",
+    "b = paddle.to_tensor(np.array([4, 5, 6]))\n",
+    "\n",
+    "for i in range(10):\n",
+    "    r = paddle.rand([1,])\n",
+    "    if r > 0.5:\n",
+    "        c = paddle.pow(a, i) + b\n",
+    "        print(\"{} +> {}\".format(i, c.numpy()))\n",
+    "    else:\n",
+    "        c = paddle.pow(a, i) - b\n",
+    "        print(\"{} -> {}\".format(i, c.numpy()))\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 构建更加灵活的网络：控制流\n",
+    "\n",
+    "- 使用动态图可以用来创建更加灵活的网络，比如根据控制流选择不同的分支网络，和方便的构建权重共享的网络。接下来我们来看一个具体的例子，在这个例子中，第二个线性变换只有0.5的可能性会运行。\n",
+    "- 在sequence to sequence with attention的机器翻译的示例中，你会看到更实际的使用动态图构建RNN类的网络带来的灵活性。\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class MyModel(paddle.nn.Layer):\n",
+    "    def __init__(self, input_size, hidden_size):\n",
+    "        super(MyModel, self).__init__()\n",
+    "        self.linear1 = paddle.nn.Linear(input_size, hidden_size)\n",
+    "        self.linear2 = paddle.nn.Linear(hidden_size, hidden_size)\n",
+    "        self.linear3 = paddle.nn.Linear(hidden_size, 1)\n",
+    "\n",
+    "    def forward(self, inputs):\n",
+    "        x = self.linear1(inputs)\n",
+    "        x = F.relu(x)\n",
+    "\n",
+    "        if paddle.rand([1,]) > 0.5: \n",
+    "            x = self.linear2(x)\n",
+    "            x = F.relu(x)\n",
+    "\n",
+    "        x = self.linear3(x)\n",
+    "        \n",
+    "        return x     "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0 [2.0915627]\n",
+      "200 [0.67530334]\n",
+      "400 [0.52042854]\n",
+      "600 [0.28010666]\n",
+      "800 [0.09739777]\n",
+      "1000 [0.09307177]\n",
+      "1200 [0.04252927]\n",
+      "1400 [0.03095707]\n",
+      "1600 [0.03022156]\n",
+      "1800 [0.01616007]\n",
+      "2000 [0.01069116]\n",
+      "2200 [0.0055158]\n",
+      "2400 [0.00195092]\n",
+      "2600 [0.00101116]\n",
+      "2800 [0.00192219]\n"
+     ]
+    }
+   ],
+   "source": [
+    "total_data, batch_size, input_size, hidden_size = 1000, 64, 128, 256\n",
+    "\n",
+    "x_data = np.random.randn(total_data, input_size).astype(np.float32)\n",
+    "y_data = np.random.randn(total_data, 1).astype(np.float32)\n",
+    "\n",
+    "model = MyModel(input_size, hidden_size)\n",
+    "\n",
+    "loss_fn = paddle.nn.MSELoss(reduction='mean')\n",
+    "optimizer = paddle.optimizer.SGD(learning_rate=0.01, \n",
+    "                                 parameters=model.parameters())\n",
+    "\n",
+    "for t in range(200 * (total_data // batch_size)):\n",
+    "    idx = np.random.choice(total_data, batch_size, replace=False)\n",
+    "    x = paddle.to_tensor(x_data[idx,:])\n",
+    "    y = paddle.to_tensor(y_data[idx,:])\n",
+    "    y_pred = model(x)\n",
+    "\n",
+    "    loss = loss_fn(y_pred, y)\n",
+    "    if t % 200 == 0:\n",
+    "        print(t, loss.numpy())\n",
+    "\n",
+    "    loss.backward()\n",
+    "    optimizer.minimize(loss)\n",
+    "    model.clear_gradients()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 构建更加灵活的网络：共享权重\n",
+    "\n",
+    "- 使用动态图还可以更加方便的创建共享权重的网络，下面的示例展示了一个共享了权重的简单的AutoEncoder的示例。\n",
+    "- 你也可以参考图像搜索的示例看到共享参数权重的更实际的使用。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "step: 0, loss: [0.37666085]\n",
+      "step: 1, loss: [0.3063845]\n",
+      "step: 2, loss: [0.2647248]\n",
+      "step: 3, loss: [0.23831272]\n",
+      "step: 4, loss: [0.21714918]\n",
+      "step: 5, loss: [0.1955545]\n",
+      "step: 6, loss: [0.17261818]\n",
+      "step: 7, loss: [0.15009595]\n",
+      "step: 8, loss: [0.13051331]\n",
+      "step: 9, loss: [0.11537809]\n"
+     ]
+    }
+   ],
+   "source": [
+    "inputs = paddle.rand((256, 64))\n",
+    "\n",
+    "linear = paddle.nn.Linear(64, 8, bias_attr=False)\n",
+    "loss_fn = paddle.nn.MSELoss()\n",
+    "optimizer = paddle.optimizer.Adam(0.01, parameters=linear.parameters())\n",
+    "\n",
+    "for i in range(10):\n",
+    "    hidden = linear(inputs)\n",
+    "    # weight from input to hidden is shared with the linear mapping from hidden to output\n",
+    "    outputs = paddle.matmul(hidden, linear.weight, transpose_y=True) \n",
+    "    loss = loss_fn(outputs, inputs)\n",
+    "    loss.backward()\n",
+    "    print(\"step: {}, loss: {}\".format(i, loss.numpy()))\n",
+    "    optimizer.minimize(loss)\n",
+    "    linear.clear_gradients()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# The end\n",
+    "\n",
+    "可以看到使用动态图带来了更灵活易用的方式来组网和训练。"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/doc/paddle/tutorial/quick_start/dynamic_graph/dynamic_graph.rst b/doc/paddle/tutorial/quick_start/dynamic_graph/dynamic_graph.rst
new file mode 100644
index 0000000000000000000000000000000000000000..4a3315cab2d7ac298eb3dbb7f68b696b77d49323
--- /dev/null
+++ b/doc/paddle/tutorial/quick_start/dynamic_graph/dynamic_graph.rst
@@ -0,0 +1,218 @@
+动态图
+======
+
+从飞桨开源框架2.0beta版本开始，飞桨默认为用户开启了动态图模式。在这种模式下，每次执行一个运算，可以立即得到结果（而不是事先定义好网络结构，然后再执行）。
+
+在动态图模式下，您可以更加方便的组织代码，更容易的调试程序，本示例教程将向你介绍飞桨的动态图的使用。
+
+设置环境
+--------
+
+我们将使用飞桨2.0beta版本，并确认已经开启了动态图模式。
+
+.. code:: ipython3
+
+    import paddle
+    import paddle.nn.functional as F
+    import numpy as np
+    
+    paddle.disable_static()
+    print(paddle.__version__)
+    print(paddle.__git_commit__)
+
+
+
+.. parsed-literal::
+
+    0.0.0
+    89af2088b6e74bdfeef2d4d78e08461ed2aafee5
+
+
+基本用法
+--------
+
+在动态图模式下，您可以直接运行一个飞桨提供的API，它会立刻返回结果到python。不再需要首先创建一个计算图，然后再给定数据去运行。
+
+.. code:: ipython3
+
+    a = paddle.randn([4, 2])
+    b = paddle.arange(1, 3, dtype='float32')
+    
+    print(a.numpy())
+    print(b.numpy())
+    
+    c = a + b
+    print(c.numpy())
+    
+    d = paddle.matmul(a, b)
+    print(d.numpy())
+
+
+.. parsed-literal::
+
+    [[-0.49341336 -0.8112665 ]
+     [ 0.8929015   0.24661176]
+     [-0.64440054 -0.7945008 ]
+     [-0.07345356  1.3641853 ]]
+    [1. 2.]
+    [[0.5065867  1.1887336 ]
+     [1.8929014  2.2466118 ]
+     [0.35559946 1.2054992 ]
+     [0.92654645 3.3641853 ]]
+    [-2.1159463  1.386125  -2.2334023  2.654917 ]
+
+
+使用python的控制流
+------------------
+
+动态图模式下，您可以使用python的条件判断和循环，这类控制语句来执行神经网络的计算。（不再需要\ ``cond``,
+``loop``\ 这类OP)
+
+.. code:: ipython3
+
+    a = paddle.to_tensor(np.array([1, 2, 3]))
+    b = paddle.to_tensor(np.array([4, 5, 6]))
+    
+    for i in range(10):
+        r = paddle.rand([1,])
+        if r > 0.5:
+            c = paddle.pow(a, i) + b
+            print("{} +> {}".format(i, c.numpy()))
+        else:
+            c = paddle.pow(a, i) - b
+            print("{} -> {}".format(i, c.numpy()))
+
+
+
+.. parsed-literal::
+
+    0 +> [5 6 7]
+    1 +> [5 7 9]
+    2 +> [ 5  9 15]
+    3 -> [-3  3 21]
+    4 -> [-3 11 75]
+    5 +> [  5  37 249]
+    6 +> [  5  69 735]
+    7 -> [  -3  123 2181]
+    8 +> [   5  261 6567]
+    9 +> [    5   517 19689]
+
+
+构建更加灵活的网络：控制流
+-------------------------------
+
+-  使用动态图可以用来创建更加灵活的网络，比如根据控制流选择不同的分支网络，和方便的构建权重共享的网络。接下来我们来看一个具体的例子，在这个例子中，第二个线性变换只有0.5的可能性会运行。
+-  在sequence to sequence with
+   attention的机器翻译的示例中，你会看到更实际的使用动态图构建RNN类的网络带来的灵活性。
+
+.. code:: ipython3
+
+    class MyModel(paddle.nn.Layer):
+        def __init__(self, input_size, hidden_size):
+            super(MyModel, self).__init__()
+            self.linear1 = paddle.nn.Linear(input_size, hidden_size)
+            self.linear2 = paddle.nn.Linear(hidden_size, hidden_size)
+            self.linear3 = paddle.nn.Linear(hidden_size, 1)
+    
+        def forward(self, inputs):
+            x = self.linear1(inputs)
+            x = F.relu(x)
+    
+            if paddle.rand([1,]) > 0.5: 
+                x = self.linear2(x)
+                x = F.relu(x)
+    
+            x = self.linear3(x)
+            
+            return x     
+
+.. code:: ipython3
+
+    total_data, batch_size, input_size, hidden_size = 1000, 64, 128, 256
+    
+    x_data = np.random.randn(total_data, input_size).astype(np.float32)
+    y_data = np.random.randn(total_data, 1).astype(np.float32)
+    
+    model = MyModel(input_size, hidden_size)
+    
+    loss_fn = paddle.nn.MSELoss(reduction='mean')
+    optimizer = paddle.optimizer.SGD(learning_rate=0.01, 
+                                     parameters=model.parameters())
+    
+    for t in range(200 * (total_data // batch_size)):
+        idx = np.random.choice(total_data, batch_size, replace=False)
+        x = paddle.to_tensor(x_data[idx,:])
+        y = paddle.to_tensor(y_data[idx,:])
+        y_pred = model(x)
+    
+        loss = loss_fn(y_pred, y)
+        if t % 200 == 0:
+            print(t, loss.numpy())
+    
+        loss.backward()
+        optimizer.minimize(loss)
+        model.clear_gradients()
+
+
+.. parsed-literal::
+
+    0 [2.0915627]
+    200 [0.67530334]
+    400 [0.52042854]
+    600 [0.28010666]
+    800 [0.09739777]
+    1000 [0.09307177]
+    1200 [0.04252927]
+    1400 [0.03095707]
+    1600 [0.03022156]
+    1800 [0.01616007]
+    2000 [0.01069116]
+    2200 [0.0055158]
+    2400 [0.00195092]
+    2600 [0.00101116]
+    2800 [0.00192219]
+
+
+构建更加灵活的网络：共享权重
+---------------------------------
+
+-  使用动态图还可以更加方便的创建共享权重的网络，下面的示例展示了一个共享了权重的简单的AutoEncoder的示例。
+-  你也可以参考图像搜索的示例看到共享参数权重的更实际的使用。
+
+.. code:: ipython3
+
+    inputs = paddle.rand((256, 64))
+    
+    linear = paddle.nn.Linear(64, 8, bias_attr=False)
+    loss_fn = paddle.nn.MSELoss()
+    optimizer = paddle.optimizer.Adam(0.01, parameters=linear.parameters())
+    
+    for i in range(10):
+        hidden = linear(inputs)
+        # weight from input to hidden is shared with the linear mapping from hidden to output
+        outputs = paddle.matmul(hidden, linear.weight, transpose_y=True) 
+        loss = loss_fn(outputs, inputs)
+        loss.backward()
+        print("step: {}, loss: {}".format(i, loss.numpy()))
+        optimizer.minimize(loss)
+        linear.clear_gradients()
+
+
+.. parsed-literal::
+
+    step: 0, loss: [0.37666085]
+    step: 1, loss: [0.3063845]
+    step: 2, loss: [0.2647248]
+    step: 3, loss: [0.23831272]
+    step: 4, loss: [0.21714918]
+    step: 5, loss: [0.1955545]
+    step: 6, loss: [0.17261818]
+    step: 7, loss: [0.15009595]
+    step: 8, loss: [0.13051331]
+    step: 9, loss: [0.11537809]
+
+
+The end
+--------
+
+可以看到使用动态图带来了更灵活易用的方式来组网和训练。
diff --git a/doc/paddle/tutorial/quick_start/getting_started/getting_started.ipynb b/doc/paddle/tutorial/quick_start/getting_started/getting_started.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..f2a27f4d2d297a037ab338093856eec453590370
--- /dev/null
+++ b/doc/paddle/tutorial/quick_start/getting_started/getting_started.ipynb
@@ -0,0 +1,219 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 快速上手飞桨（PaddlePaddle）\n",
+    "\n",
+    "本示例通过一个基础案例带您从一个飞桨新手快速掌握如何使用。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 1. 安装飞桨\n",
+    "\n",
+    "如果您已经安装好飞桨那么可以跳过此步骤。我们针对用户提供了一个方便易用的安装引导页面，您可以通过选择自己的系统和软件版本来获取对应的安装命令，具体可以点击[快速安装](https://www.paddlepaddle.org.cn/install/quick)查看。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. 导入飞桨\n",
+    "\n",
+    "这个示例我们采用了Notebook的形式来进行编写，您可以直接通过AIStudio或Jupyter等平台工具来运行这个案例，Notebook的好处是可以通过浏览器来运行Python程序，边看教程边运行结果，可以对比学习，并且可以做到单步运行调试。\n",
+    "\n",
+    "安装好飞桨后我们就可以在Python程序中进行飞桨的导入。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.0.0'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import paddle\n",
+    "\n",
+    "paddle.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 3. 实践一个手写数字识别任务\n",
+    "\n",
+    "对于深度学习任务如果简单来看，其实分为几个核心步骤：1. 数据集的准备和加载；2. 模型的构建；3.模型训练；4.模型评估。那么接下来我们就一步一步带您通过飞桨的少量API快速实现。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 3.1 数据加载\n",
+    "\n",
+    "加载我们框架为您准备好的一个手写数字识别数据集。这里我们使用两个数据集，一个用来做模型的训练，一个用来做模型的评估。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_dataset = paddle.vision.datasets.MNIST(mode='train', chw_format=False)\n",
+    "val_dataset =  paddle.vision.datasets.MNIST(mode='test', chw_format=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 3.2 模型搭建\n",
+    "\n",
+    "通过Sequential将一层一层的网络结构组建起来。通过数据集加载接口的chw_format参数我们已经将[1, 28, 28]形状的图片数据改变形状为[1, 784]，那么在组网过程中不在需要先进行Flatten操作。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mnist = paddle.nn.Sequential(\n",
+    "    paddle.nn.Linear(784, 512),\n",
+    "    paddle.nn.ReLU(),\n",
+    "    paddle.nn.Dropout(0.2),\n",
+    "    paddle.nn.Linear(512, 10)\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 3.3 模型训练\n",
+    "\n",
+    "配置好我们模型训练需要的损失计算方法和优化方法后就可以使用fit接口来开启我们的模型训练过程。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/5\n",
+      "step 1875/1875 [==============================] - loss: 0.2571 - acc: 0.9037 - 10ms/step          \n",
+      "Epoch 2/5\n",
+      "step 1875/1875 [==============================] - loss: 0.1880 - acc: 0.9458 - 14ms/step          \n",
+      "Epoch 3/5\n",
+      "step 1875/1875 [==============================] - loss: 0.0279 - acc: 0.9549 - 11ms/step          \n",
+      "Epoch 4/5\n",
+      "step 1875/1875 [==============================] - loss: 0.0505 - acc: 0.9608 - 13ms/step          \n",
+      "Epoch 5/5\n",
+      "step 1875/1875 [==============================] - loss: 0.2253 - acc: 0.9646 - 12ms/step          \n"
+     ]
+    }
+   ],
+   "source": [
+    "# 开启动态图模式\n",
+    "paddle.disable_static()  \n",
+    "\n",
+    "# 预计模型结构生成模型实例，便于进行后续的配置、训练和验证\n",
+    "model = paddle.Model(mnist)  \n",
+    "\n",
+    "# 模型训练相关配置，准备损失计算方法，优化器和精度计算方法\n",
+    "model.prepare(paddle.optimizer.Adam(parameters=mnist.parameters()),\n",
+    "              paddle.nn.CrossEntropyLoss(),\n",
+    "              paddle.metric.Accuracy())\n",
+    "\n",
+    "# 开始模型训练\n",
+    "model.fit(train_dataset,\n",
+    "          epochs=5, \n",
+    "          batch_size=32,\n",
+    "          verbose=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 3.4 模型评估\n",
+    "\n",
+    "使用我们刚才训练得到的模型参数进行模型的评估操作，看看我们的模型精度如何。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'loss': [3.576278e-07], 'acc': 0.9666}"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.evaluate(val_dataset, verbose=0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "那么初步训练得到的模型效果在97%附近，我们可以进一步通过调整其中的训练参数来提升我们的模型精度。\n",
+    "\n",
+    "至此我们可以知道如何通过飞桨的几个简单API来快速完成一个深度学习任务，大家可以针对自己的需求来更换其中的代码，如果需要使用自己的数据集，那么可以更换数据集加载部分程序，如果需要替换模型，那么可以更改模型代码实现等等。我们也为大家提供了很多其他场景的示例代码来教大家如何使用我们的飞桨API，大家可以查看下面的链接或通过页面导航来查看自己感兴趣的部分。\n",
+    "\n",
+    "TODO：补充其他示例教程的快速链接。"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.7.4 64-bit",
+   "language": "python",
+   "name": "python37464bitc4da1ac836094043840bff631bedbf7f"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/doc/paddle/tutorial/quick_start/getting_started/getting_started.rst b/doc/paddle/tutorial/quick_start/getting_started/getting_started.rst
new file mode 100644
index 0000000000000000000000000000000000000000..5263af9f3998396492576b051f3536cccd67f94c
--- /dev/null
+++ b/doc/paddle/tutorial/quick_start/getting_started/getting_started.rst
@@ -0,0 +1,127 @@
+快速上手飞桨（PaddlePaddle）
+============================
+
+本示例通过一个基础案例带您从一个飞桨新手快速掌握如何使用。
+
+1. 安装飞桨
+-----------
+
+如果您已经安装好飞桨那么可以跳过此步骤。我们针对用户提供了一个方便易用的安装引导页面，您可以通过选择自己的系统和软件版本来获取对应的安装命令，具体可以点击\ `快速安装 <https://www.paddlepaddle.org.cn/install/quick>`__\ 查看。
+
+2. 导入飞桨
+-----------
+
+这个示例我们采用了Notebook的形式来进行编写，您可以直接通过AIStudio或Jupyter等平台工具来运行这个案例，Notebook的好处是可以通过浏览器来运行Python程序，边看教程边运行结果，可以对比学习，并且可以做到单步运行调试。
+
+安装好飞桨后我们就可以在Python程序中进行飞桨的导入。
+
+.. code:: ipython3
+
+    import paddle
+    
+    paddle.__version__
+
+
+
+
+.. parsed-literal::
+
+    '0.0.0'
+
+
+
+3. 实践一个手写数字识别任务
+---------------------------
+
+对于深度学习任务如果简单来看，其实分为几个核心步骤：1.
+数据集的准备和加载；2.
+模型的构建；3.模型训练；4.模型评估。那么接下来我们就一步一步带您通过飞桨的少量API快速实现。
+
+3.1 数据加载
+~~~~~~~~~~~~
+
+加载我们框架为您准备好的一个手写数字识别数据集。这里我们使用两个数据集，一个用来做模型的训练，一个用来做模型的评估。
+
+.. code:: ipython3
+
+    train_dataset = paddle.vision.datasets.MNIST(mode='train', chw_format=False)
+    val_dataset =  paddle.vision.datasets.MNIST(mode='test', chw_format=False)
+
+3.2 模型搭建
+~~~~~~~~~~~~
+
+通过Sequential将一层一层的网络结构组建起来。通过数据集加载接口的chw_format参数我们已经将[1,
+28, 28]形状的图片数据改变形状为[1,
+784]，那么在组网过程中不在需要先进行Flatten操作。
+
+.. code:: ipython3
+
+    mnist = paddle.nn.Sequential(
+        paddle.nn.Linear(784, 512),
+        paddle.nn.ReLU(),
+        paddle.nn.Dropout(0.2),
+        paddle.nn.Linear(512, 10)
+    )
+
+3.3 模型训练
+~~~~~~~~~~~~
+
+配置好我们模型训练需要的损失计算方法和优化方法后就可以使用fit接口来开启我们的模型训练过程。
+
+.. code:: ipython3
+
+    # 开启动态图模式
+    paddle.disable_static()  
+    
+    # 预计模型结构生成模型实例，便于进行后续的配置、训练和验证
+    model = paddle.Model(mnist)  
+    
+    # 模型训练相关配置，准备损失计算方法，优化器和精度计算方法
+    model.prepare(paddle.optimizer.Adam(parameters=mnist.parameters()),
+                  paddle.nn.CrossEntropyLoss(),
+                  paddle.metric.Accuracy())
+    
+    # 开始模型训练
+    model.fit(train_dataset,
+              epochs=5, 
+              batch_size=32,
+              verbose=1)
+
+
+.. parsed-literal::
+
+    Epoch 1/5
+    step 1875/1875 [==============================] - loss: 0.2571 - acc: 0.9037 - 10ms/step          
+    Epoch 2/5
+    step 1875/1875 [==============================] - loss: 0.1880 - acc: 0.9458 - 14ms/step          
+    Epoch 3/5
+    step 1875/1875 [==============================] - loss: 0.0279 - acc: 0.9549 - 11ms/step          
+    Epoch 4/5
+    step 1875/1875 [==============================] - loss: 0.0505 - acc: 0.9608 - 13ms/step          
+    Epoch 5/5
+    step 1875/1875 [==============================] - loss: 0.2253 - acc: 0.9646 - 12ms/step          
+
+
+3.4 模型评估
+~~~~~~~~~~~~
+
+使用我们刚才训练得到的模型参数进行模型的评估操作，看看我们的模型精度如何。
+
+.. code:: ipython3
+
+    model.evaluate(val_dataset, verbose=0)
+
+
+
+
+.. parsed-literal::
+
+    {'loss': [3.576278e-07], 'acc': 0.9666}
+
+
+
+那么初步训练得到的模型效果在97%附近，我们可以进一步通过调整其中的训练参数来提升我们的模型精度。
+
+至此我们可以知道如何通过飞桨的几个简单API来快速完成一个深度学习任务，大家可以针对自己的需求来更换其中的代码，如果需要使用自己的数据集，那么可以更换数据集加载部分程序，如果需要替换模型，那么可以更改模型代码实现等等。我们也为大家提供了很多其他场景的示例代码来教大家如何使用我们的飞桨API，大家可以查看下面的链接或通过页面导航来查看自己感兴趣的部分。
+
+TODO：补充其他示例教程的快速链接。
diff --git a/doc/paddle/tutorial/quick_start/hello_paddle/hello_paddle.ipynb b/doc/paddle/tutorial/quick_start/hello_paddle/hello_paddle.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..e947d5c235dd6706d92dd1e59609970e06cea6e8
--- /dev/null
+++ b/doc/paddle/tutorial/quick_start/hello_paddle/hello_paddle.ipynb
@@ -0,0 +1,343 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Hello Paddle: 从普通程序走向机器学习程序"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "这篇示例向你介绍普通的程序跟机器学习程序的区别，并带着你用飞桨框架，实现你的第一个机器学习程序。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 普通程序跟机器学习程序的逻辑区别\n",
+    "\n",
+    "作为一名开发者，你最熟悉的开始学习一门编程语言，或者一个深度学习框架的方式，可能是通过一个hello, world程序。\n",
+    "\n",
+    "学习飞桨也可以这样，这篇小示例教程将会通过一个非常简单的示例来向你展示如何开始使用飞桨。\n",
+    "\n",
+    "机器学习程序跟通常的程序最大的不同是，通常的程序是在给定输入的情况下，通过告诉计算机处理数据的规则，然后得到处理后的结果。而机器学习程序则是在并不知道这些规则的情况下，让机器来从数据当中**学习**出来规则。\n",
+    "\n",
+    "作为热身，我们先来看看通常的程序所做的事情。\n",
+    "\n",
+    "我们现在面临这样一个任务：\n",
+    "\n",
+    "我们乘坐出租车的时候，会有一个10元的起步价，只要上车就需要收取。出租车每行驶1公里，需要再支付每公里2元的行驶费用。当一个乘客坐完出租车之后，车上的计价器需要算出来该乘客需要支付的乘车费用。\n",
+    "\n",
+    "如果用python来实现该功能，会如下所示："
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "12.0\n",
+      "16.0\n",
+      "20.0\n",
+      "28.0\n",
+      "30.0\n",
+      "50.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "def calculate_fee(distance_travelled):\n",
+    "    return 10 + 2 * distance_travelled\n",
+    "\n",
+    "for x in [1.0, 3.0, 5.0, 9.0, 10.0, 20.0]:\n",
+    "    print(calculate_fee(x))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "接下来，我们把问题稍微变换一下，现在我们知道乘客每次乘坐出租车的公里数，也知道乘客每次下车的时候支付给出租车司机的总费用。但是并不知道乘车的起步价，以及每公里行驶费用是多少。我们希望让机器从这些数据当中学习出来计算总费用的规则。\n",
+    "\n",
+    "更具体的，我们想要让机器学习程序通过数据学习出来下面的公式当中的参数w和参数b（这是一个非常简单的示例，所以`w`和`b`都是浮点数，随着对深度学习了解的深入，你将会知道`w`和`b`通常情况下会是矩阵和向量）。这样，当下次乘车的时候，我们知道了行驶里程`distance_travelled`的时候，我们就可以估算出来用户的总费用`total_fee`了。\n",
+    "\n",
+    "```\n",
+    "total_fee = w * distance_travelled + b\n",
+    "```\n",
+    "\n",
+    "接下来，我们看看用飞桨如何实现这个hello, world级别的机器学习程序。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 导入飞桨\n",
+    "\n",
+    "为了能够使用飞桨，我们需要先用python的`import`语句导入飞桨`paddle`。\n",
+    "同时，为了能够更好的对数组进行计算和处理，我们也还需要导入`numpy`。\n",
+    "\n",
+    "如果你是在本机运行这个notebook，而且还没有安装飞桨，可以去飞桨的官网查看如何安装：[飞桨官网](https://www.paddlepaddle.org.cn/)。并且请使用2.0beta或以上版本的飞桨。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "paddle version 0.0.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "import paddle\n",
+    "paddle.disable_static()\n",
+    "print(\"paddle version \" + paddle.__version__)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 准备数据\n",
+    "\n",
+    "在这个机器学习任务中，我们已经知道了乘客的行驶里程`distance_travelled`，和对应的，这些乘客的总费用`total_fee`。\n",
+    "通常情况下，在机器学习任务中，像`distance_travelled`这样的输入值，一般被称为`x`（或者特征`feature`），像`total_fee`这样的输出值，一般被称为`y`（或者标签`label`)。\n",
+    "\n",
+    "我们用`paddle.to_tensor`把示例数据转换为paddle的Tensor数据。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_data = paddle.to_tensor([[1.], [3.0], [5.0], [9.0], [10.0], [20.0]])\n",
+    "y_data = paddle.to_tensor([[12.], [16.0], [20.0], [28.0], [30.0], [50.0]])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 用飞桨定义模型的计算\n",
+    "\n",
+    "使用飞桨定义模型的计算的过程，本质上，是我们用python，通过飞桨提供的API，来告诉飞桨我们的计算规则的过程。回顾一下，我们想要通过飞桨用机器学习方法，从数据当中学习出来如下公式当中的`w`和`b`。这样在未来，给定`x`时就可以估算出来`y`值（估算出来的`y`记为`y_predict`）\n",
+    "\n",
+    "```\n",
+    "y_predict = w * x + b\n",
+    "```\n",
+    "\n",
+    "我们将会用飞桨的线性变换层：`paddle.nn.Linear`来实现这个计算过程，这个公式里的变量`x, y, w, b, y_predict`，对应着飞桨里面的[Tensor概念](https://www.paddlepaddle.org.cn/documentation/docs/zh/beginners_guide/basic_concept/tensor.html)。\n",
+    "\n",
+    "### 稍微补充一下\n",
+    "\n",
+    "在这里的示例中，我们根据经验，已经事先知道了`distance_travelled`和`total_fee`之间是线性的关系，而在更实际的问题当中，`x`和`y`的关系通常是非线性的，因此也就需要使用更多类型，也更复杂的神经网络。(比如，BMI指数跟你的身高就不是线性关系，一张图片里的某个像素值跟这个图片是猫还是狗也不是线性关系。）\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "linear = paddle.nn.Linear(in_features=1, out_features=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 准备好运行飞桨\n",
+    "\n",
+    "机器（计算机）在一开始的时候会随便猜`w`和`b`，我们先看看机器猜的怎么样。你应该可以看到，这时候的`w`是一个随机值，`b`是0.0，这是飞桨的初始化策略，也是这个领域常用的初始化策略。（如果你愿意，也可以采用其他的初始化的方式，今后你也会看到，选择不同的初始化策略也是对于做好深度学习任务来说很重要的一点）。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "w before optimize: -1.7107375860214233\n",
+      "b before optimize: 0.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "w_before_opt = linear.weight.numpy().item()\n",
+    "b_before_opt = linear.bias.numpy().item()\n",
+    "\n",
+    "print(\"w before optimize: {}\".format(w_before_opt))\n",
+    "print(\"b before optimize: {}\".format(b_before_opt))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 告诉飞桨怎么样学习\n",
+    "\n",
+    "前面我们定义好了神经网络（尽管是一个最简单的神经网络），我们还需要告诉飞桨，怎么样去**学习**，从而能得到参数`w`和`b`。\n",
+    "\n",
+    "这个过程简单的来陈述一下，你应该就会大致明白了（尽管背后的理论和知识还需要逐步的去学习）。在机器学习/深度学习当中，机器（计算机）在最开始的时候，得到参数`w`和`b`的方式是随便猜一下，用这种随便猜测得到的参数值，去进行计算（预测）的时候，得到的`y_predict`，跟实际的`y`值一定是有**差距**的。接下来，机器会根据这个差距来**调整`w`和`b`**，随着这样的逐步的调整，`w`和`b`会越来越正确，`y_predict`跟`y`之间的差距也会越来越小，从而最终能得到好用的`w`和`b`。这个过程就是机器**学习**的过程。\n",
+    "\n",
+    "用更加技术的语言来说，衡量**差距**的函数（一个公式）就是损失函数，用来**调整**参数的方法就是优化算法。\n",
+    "\n",
+    "在本示例当中，我们用最简单的均方误差(mean square error)作为损失函数(`paddle.nn.MSELoss`)；和最常见的优化算法SGD（stocastic gradient descent)作为优化算法（传给`paddle.optimizer.SGD`的参数`learning_rate`，你可以理解为控制每次调整的步子大小的参数）。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mse_loss = paddle.nn.MSELoss()\n",
+    "sgd_optimizer = paddle.optimizer.SGD(learning_rate=0.001, parameters = linear.parameters())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 运行优化算法\n",
+    "\n",
+    "接下来，我们让飞桨运行一下这个优化算法，这会是一个前面介绍过的逐步调整参数的过程，你应该可以看到loss值（衡量`y`和`y_predict`的差距的`loss`)在不断的降低。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "epoch 0 loss [2107.3943]\n",
+      "epoch 1000 loss [7.8432994]\n",
+      "epoch 2000 loss [1.7537074]\n",
+      "epoch 3000 loss [0.39211753]\n",
+      "epoch 4000 loss [0.08767726]\n",
+      "finished training， loss [0.01963376]\n"
+     ]
+    }
+   ],
+   "source": [
+    "total_epoch = 5000\n",
+    "for i in range(total_epoch):\n",
+    "    y_predict = linear(x_data)\n",
+    "    loss = mse_loss(y_predict, y_data)\n",
+    "    loss.backward()\n",
+    "    sgd_optimizer.minimize(loss)\n",
+    "    linear.clear_gradients()\n",
+    "    \n",
+    "    if i%1000 == 0:\n",
+    "        print(\"epoch {} loss {}\".format(i, loss.numpy()))\n",
+    "        \n",
+    "print(\"finished training， loss {}\".format(loss.numpy()))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 机器学习出来的参数\n",
+    "\n",
+    "经过了这样的对参数`w`和`b`的调整（**学习**)，我们再通过下面的程序，来看看现在的参数变成了多少。你应该会发现`w`变成了很接近2.0的一个值，`b`变成了接近10.0的一个值。虽然并不是正好的2和10，但却是从数据当中学习出来的还不错的模型的参数，可以在未来的时候，用从这批数据当中学习到的参数来预估了。（如果你愿意，也可以通过让机器多学习一段时间，从而得到更加接近2.0和10.0的参数值。)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "w after optimize: 2.017843246459961\n",
+      "b after optimize: 9.771851539611816\n"
+     ]
+    }
+   ],
+   "source": [
+    "w_after_opt = linear.weight.numpy().item()\n",
+    "b_after_opt = linear.bias.numpy().item()\n",
+    "\n",
+    "print(\"w after optimize: {}\".format(w_after_opt))\n",
+    "print(\"b after optimize: {}\".format(b_after_opt))\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# hello paddle\n",
+    "\n",
+    "通过这个小示例，希望你已经初步了解了飞桨，能在接下来随着对飞桨的更多学习，来解决实际遇到的问题。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "hello paddle\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"hello paddle\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "name": "hello-paddle.ipynb",
+   "private_outputs": true,
+   "provenance": [],
+   "toc_visible": true
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/doc/paddle/tutorial/quick_start/hello_paddle/hello_paddle.rst b/doc/paddle/tutorial/quick_start/hello_paddle/hello_paddle.rst
new file mode 100644
index 0000000000000000000000000000000000000000..f7e94e9ae0f52bdf7df01671f448414dccabfe3f
--- /dev/null
+++ b/doc/paddle/tutorial/quick_start/hello_paddle/hello_paddle.rst
@@ -0,0 +1,210 @@
+Hello Paddle: 从普通程序走向机器学习程序
+========================================
+
+这篇示例向你介绍普通的程序跟机器学习程序的区别，并带着你用飞桨框架，实现你的第一个机器学习程序。
+
+普通程序跟机器学习程序的逻辑区别
+--------------------------------
+
+作为一名开发者，你最熟悉的开始学习一门编程语言，或者一个深度学习框架的方式，可能是通过一个hello,
+world程序。
+
+学习飞桨也可以这样，这篇小示例教程将会通过一个非常简单的示例来向你展示如何开始使用飞桨。
+
+机器学习程序跟通常的程序最大的不同是，通常的程序是在给定输入的情况下，通过告诉计算机处理数据的规则，然后得到处理后的结果。而机器学习程序则是在并不知道这些规则的情况下，让机器来从数据当中\ **学习**\ 出来规则。
+
+作为热身，我们先来看看通常的程序所做的事情。
+
+我们现在面临这样一个任务：
+
+我们乘坐出租车的时候，会有一个10元的起步价，只要上车就需要收取。出租车每行驶1公里，需要再支付每公里2元的行驶费用。当一个乘客坐完出租车之后，车上的计价器需要算出来该乘客需要支付的乘车费用。
+
+如果用python来实现该功能，会如下所示：
+
+.. code:: ipython3
+
+    def calculate_fee(distance_travelled):
+        return 10 + 2 * distance_travelled
+    
+    for x in [1.0, 3.0, 5.0, 9.0, 10.0, 20.0]:
+        print(calculate_fee(x))
+
+
+.. parsed-literal::
+
+    12.0
+    16.0
+    20.0
+    28.0
+    30.0
+    50.0
+
+
+接下来，我们把问题稍微变换一下，现在我们知道乘客每次乘坐出租车的公里数，也知道乘客每次下车的时候支付给出租车司机的总费用。但是并不知道乘车的起步价，以及每公里行驶费用是多少。我们希望让机器从这些数据当中学习出来计算总费用的规则。
+
+更具体的，我们想要让机器学习程序通过数据学习出来下面的公式当中的参数w和参数b（这是一个非常简单的示例，所以\ ``w``\ 和\ ``b``\ 都是浮点数，随着对深度学习了解的深入，你将会知道\ ``w``\ 和\ ``b``\ 通常情况下会是矩阵和向量）。这样，当下次乘车的时候，我们知道了行驶里程\ ``distance_travelled``\ 的时候，我们就可以估算出来用户的总费用\ ``total_fee``\ 了。
+
+::
+
+   total_fee = w * distance_travelled + b
+
+接下来，我们看看用飞桨如何实现这个hello, world级别的机器学习程序。
+
+导入飞桨
+---------
+
+为了能够使用飞桨，我们需要先用python的\ ``import``\ 语句导入飞桨\ ``paddle``\ 。
+同时，为了能够更好的对数组进行计算和处理，我们也还需要导入\ ``numpy``\ 。
+
+如果你是在本机运行这个notebook，而且还没有安装飞桨，可以去飞桨的官网查看如何安装：\ `飞桨官网 <https://www.paddlepaddle.org.cn/>`__\ 。并且请使用2.0beta或以上版本的飞桨。
+
+.. code:: ipython3
+
+    import paddle
+    paddle.disable_static()
+    print("paddle version " + paddle.__version__)
+
+
+.. parsed-literal::
+
+    paddle version 0.0.0
+
+
+准备数据
+---------
+
+在这个机器学习任务中，我们已经知道了乘客的行驶里程\ ``distance_travelled``\ ，和对应的，这些乘客的总费用\ ``total_fee``\ 。
+通常情况下，在机器学习任务中，像\ ``distance_travelled``\ 这样的输入值，一般被称为\ ``x``\ （或者特征\ ``feature``\ ），像\ ``total_fee``\ 这样的输出值，一般被称为\ ``y``\ （或者标签\ ``label``)。
+
+我们用\ ``paddle.to_tensor``\ 把示例数据转换为paddle的Tensor数据。
+
+.. code:: ipython3
+
+    x_data = paddle.to_tensor([[1.], [3.0], [5.0], [9.0], [10.0], [20.0]])
+    y_data = paddle.to_tensor([[12.], [16.0], [20.0], [28.0], [30.0], [50.0]])
+
+用飞桨定义模型的计算
+--------------------
+
+使用飞桨定义模型的计算的过程，本质上，是我们用python，通过飞桨提供的API，来告诉飞桨我们的计算规则的过程。回顾一下，我们想要通过飞桨用机器学习方法，从数据当中学习出来如下公式当中的\ ``w``\ 和\ ``b``\ 。这样在未来，给定\ ``x``\ 时就可以估算出来\ ``y``\ 值（估算出来的\ ``y``\ 记为\ ``y_predict``\ ）
+
+::
+
+   y_predict = w * x + b
+
+我们将会用飞桨的线性变换层：\ ``paddle.nn.Linear``\ 来实现这个计算过程，这个公式里的变量\ ``x, y, w, b, y_predict``\ ，对应着飞桨里面的\ `Tensor概念 <https://www.paddlepaddle.org.cn/documentation/docs/zh/beginners_guide/basic_concept/tensor.html>`__\ 。
+
+稍微补充一下
+~~~~~~~~~~~~
+
+在这里的示例中，我们根据经验，已经事先知道了\ ``distance_travelled``\ 和\ ``total_fee``\ 之间是线性的关系，而在更实际的问题当中，\ ``x``\ 和\ ``y``\ 的关系通常是非线性的，因此也就需要使用更多类型，也更复杂的神经网络。(比如，BMI指数跟你的身高就不是线性关系，一张图片里的某个像素值跟这个图片是猫还是狗也不是线性关系。）
+
+.. code:: ipython3
+
+    linear = paddle.nn.Linear(in_features=1, out_features=1)
+
+准备好运行飞桨
+----------------
+
+机器（计算机）在一开始的时候会随便猜\ ``w``\ 和\ ``b``\ ，我们先看看机器猜的怎么样。你应该可以看到，这时候的\ ``w``\ 是一个随机值，\ ``b``\ 是0.0，这是飞桨的初始化策略，也是这个领域常用的初始化策略。（如果你愿意，也可以采用其他的初始化的方式，今后你也会看到，选择不同的初始化策略也是对于做好深度学习任务来说很重要的一点）。
+
+.. code:: ipython3
+
+    w_before_opt = linear.weight.numpy().item()
+    b_before_opt = linear.bias.numpy().item()
+    
+    print("w before optimize: {}".format(w_before_opt))
+    print("b before optimize: {}".format(b_before_opt))
+
+
+.. parsed-literal::
+
+    w before optimize: -1.7107375860214233
+    b before optimize: 0.0
+
+
+告诉飞桨怎么样学习
+--------------------
+
+前面我们定义好了神经网络（尽管是一个最简单的神经网络），我们还需要告诉飞桨，怎么样去\ **学习**\ ，从而能得到参数\ ``w``\ 和\ ``b``\ 。
+
+这个过程简单的来陈述一下，你应该就会大致明白了（尽管背后的理论和知识还需要逐步的去学习）。在机器学习/深度学习当中，机器（计算机）在最开始的时候，得到参数\ ``w``\ 和\ ``b``\ 的方式是随便猜一下，用这种随便猜测得到的参数值，去进行计算（预测）的时候，得到的\ ``y_predict``\ ，跟实际的\ ``y``\ 值一定是有\ **差距**\ 的。接下来，机器会根据这个差距来\ **调整\ ``w``\ 和\ ``b``**\ ，随着这样的逐步的调整，\ ``w``\ 和\ ``b``\ 会越来越正确，\ ``y_predict``\ 跟\ ``y``\ 之间的差距也会越来越小，从而最终能得到好用的\ ``w``\ 和\ ``b``\ 。这个过程就是机器\ **学习**\ 的过程。
+
+用更加技术的语言来说，衡量\ **差距**\ 的函数（一个公式）就是损失函数，用来\ **调整**\ 参数的方法就是优化算法。
+
+在本示例当中，我们用最简单的均方误差(mean square
+error)作为损失函数(``paddle.nn.MSELoss``)；和最常见的优化算法SGD（stocastic
+gradient
+descent)作为优化算法（传给\ ``paddle.optimizer.SGD``\ 的参数\ ``learning_rate``\ ，你可以理解为控制每次调整的步子大小的参数）。
+
+.. code:: ipython3
+
+    mse_loss = paddle.nn.MSELoss()
+    sgd_optimizer = paddle.optimizer.SGD(learning_rate=0.001, parameters = linear.parameters())
+
+运行优化算法
+---------------
+
+接下来，我们让飞桨运行一下这个优化算法，这会是一个前面介绍过的逐步调整参数的过程，你应该可以看到loss值（衡量\ ``y``\ 和\ ``y_predict``\ 的差距的\ ``loss``)在不断的降低。
+
+.. code:: ipython3
+
+    total_epoch = 5000
+    for i in range(total_epoch):
+        y_predict = linear(x_data)
+        loss = mse_loss(y_predict, y_data)
+        loss.backward()
+        sgd_optimizer.minimize(loss)
+        linear.clear_gradients()
+        
+        if i%1000 == 0:
+            print("epoch {} loss {}".format(i, loss.numpy()))
+            
+    print("finished training， loss {}".format(loss.numpy()))
+
+
+.. parsed-literal::
+
+    epoch 0 loss [2107.3943]
+    epoch 1000 loss [7.8432994]
+    epoch 2000 loss [1.7537074]
+    epoch 3000 loss [0.39211753]
+    epoch 4000 loss [0.08767726]
+    finished training， loss [0.01963376]
+
+
+机器学习出来的参数
+-------------------
+
+经过了这样的对参数\ ``w``\ 和\ ``b``\ 的调整（\ **学习**)，我们再通过下面的程序，来看看现在的参数变成了多少。你应该会发现\ ``w``\ 变成了很接近2.0的一个值，\ ``b``\ 变成了接近10.0的一个值。虽然并不是正好的2和10，但却是从数据当中学习出来的还不错的模型的参数，可以在未来的时候，用从这批数据当中学习到的参数来预估了。（如果你愿意，也可以通过让机器多学习一段时间，从而得到更加接近2.0和10.0的参数值。)
+
+.. code:: ipython3
+
+    w_after_opt = linear.weight.numpy().item()
+    b_after_opt = linear.bias.numpy().item()
+    
+    print("w after optimize: {}".format(w_after_opt))
+    print("b after optimize: {}".format(b_after_opt))
+
+
+
+.. parsed-literal::
+
+    w after optimize: 2.017843246459961
+    b after optimize: 9.771851539611816
+
+
+hello paddle
+---------------
+
+通过这个小示例，希望你已经初步了解了飞桨，能在接下来随着对飞桨的更多学习，来解决实际遇到的问题。
+
+.. code:: ipython3
+
+    print("hello paddle")
+
+
+.. parsed-literal::
+
+    hello paddle
+
diff --git a/doc/paddle/tutorial/quick_start/high_level_api/high_level_api.ipynb b/doc/paddle/tutorial/quick_start/high_level_api/high_level_api.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..6474cbc09909a7a2571704ee4e19a679a049f797
--- /dev/null
+++ b/doc/paddle/tutorial/quick_start/high_level_api/high_level_api.ipynb
@@ -0,0 +1,623 @@
+{
+ "metadata": {
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4-final"
+  },
+  "orig_nbformat": 2,
+  "kernelspec": {
+   "name": "python37464bitc4da1ac836094043840bff631bedbf7f",
+   "display_name": "Python 3.7.4 64-bit"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2,
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 飞桨高层API使用指南\n",
+    "\n",
+    "## 1. 简介\n",
+    "\n",
+    "飞桨2.0全新推出高层API，是对飞桨API的进一步封装与升级，提供了更加简洁易用的API，进一步提升了飞桨的易学易用性，并增强飞桨的功能。\n",
+    "\n",
+    "飞桨高层API面向从深度学习小白到资深开发者的所有人群，对于AI初学者来说，使用高层API可以简单快速的构建深度学习项目，对于资深开发者来说，可以快速完成算法迭代。\n",
+    "\n",
+    "飞桨高层API具有以下特点：\n",
+    "\n",
+    "* 易学易用: 高层API是对普通动态图API的进一步封装和优化，同时保持与普通API的兼容性，高层API使用更加易学易用，同样的实现使用高层API可以节省大量的代码。\n",
+    "* 低代码开发: 使用飞桨高层API的一个明显特点是，用户可编程代码量大大缩减。\n",
+    "* 动静转换: 高层API支持动静转换，用户只需要改一行代码即可实现将动态图代码在静态图模式下训练，既方便用户使用动态图调试模型，又提升了模型训练效率。\n",
+    "\n",
+    "在功能增强与使用方式上，高层API有以下升级：\n",
+    "\n",
+    "* 模型训练方式升级: 高层API中封装了Model类，继承了Model类的神经网络可以仅用几行代码完成模型的训练。\n",
+    "* 新增图像处理模块transform: 飞桨新增了图像预处理模块，其中包含数十种数据处理函数，基本涵盖了常用的数据处理、数据增强方法。\n",
+    "* 提供常用的神经网络模型可供调用: 高层API中集成了计算机视觉领域和自然语言处理领域常用模型，包括但不限于mobilenet、resnet、yolov3、cyclegan、bert、transformer、seq2seq等等。同时发布了对应模型的预训练模型，用户可以直接使用这些模型或者在此基础上完成二次开发。\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. 安装并使用飞桨高层API\n",
+    "\n",
+    "飞桨高层API无需独立安装，只需要安装好paddlepaddle即可，安装完成后import paddle即可使用相关高层API，如：paddle.Model、视觉领域paddle.vision、NLP领域paddle.text。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": "'0.0.0'"
+     },
+     "metadata": {},
+     "execution_count": 4
+    }
+   ],
+   "source": [
+    "import paddle\n",
+    "import paddle.vision as vision\n",
+    "import paddle.text as text\n",
+    "\n",
+    "paddle.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. 目录\n",
+    "\n",
+    "本指南教学内容覆盖\n",
+    "\n",
+    "* 使用高层API提供的自带数据集进行相关深度学习任务训练。\n",
+    "* 使用自定义数据进行数据集的定义、数据预处理和训练。\n",
+    "* 如何在数据集定义和加载中应用数据增强相关接口。\n",
+    "* 如何进行模型的组网。\n",
+    "* 高层API进行模型训练的相关API使用。\n",
+    "* 如何在fit接口满足需求的时候进行自定义，使用基础API来完成训练。\n",
+    "* 如何使用多卡来加速训练。\n",
+    "\n",
+    "其他端到端的示例教程：\n",
+    "* TBD"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 3. 数据集定义、加载和数据预处理\n",
+    "\n",
+    "对于深度学习任务，均是框架针对各种类型数字的计算，是无法直接使用原始图片和文本等文件来完成。那么就是涉及到了一项动作，就是将原始的各种数据文件进行处理加工，转换成深度学习任务可以使用的数据。\n",
+    "\n",
+    "### 3.1 框架自带数据集使用\n",
+    "\n",
+    "高层API将一些我们常用到的数据集作为领域API对用户进行开放，对应API所在目录为`paddle.vision.datasets`，那么我们先看下提供了哪些数据集。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": "['DatasetFolder',\n 'ImageFolder',\n 'MNIST',\n 'Flowers',\n 'Cifar10',\n 'Cifar100',\n 'VOC2012']"
+     },
+     "metadata": {},
+     "execution_count": 17
+    }
+   ],
+   "source": [
+    "paddle.vision.datasets.__all__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "这里我们是加载一个手写数字识别的数据集，用`mode`来标识是训练数据还是测试数据集。数据集接口会自动从远端下载数据集到本机缓存目录`~/.cache/paddle/dataset`。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 测试数据集\n",
+    "train_dataset = vision.datasets.MNIST(mode='train')\n",
+    "\n",
+    "# 验证数据集\n",
+    "val_dataset = vision.datasets.MNIST(mode='test')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 3.2 自定义数据集\n",
+    "\n",
+    "更多的时候我们是需要自己使用已有的相关数据来定义数据集，那么这里我们通过一个案例来了解如何进行数据集的定义，飞桨为用户提供了`paddle.io.Dataset`基类，让用户通过类的集成来快速实现数据集定义。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": "=============train dataset=============\ntraindata1 label1\ntraindata2 label2\ntraindata3 label3\ntraindata4 label4\n=============evaluation dataset=============\ntestdata1 label1\ntestdata2 label2\ntestdata3 label3\ntestdata4 label4\n"
+    }
+   ],
+   "source": [
+    "from paddle.io import Dataset\n",
+    "\n",
+    "\n",
+    "class MyDataset(Dataset):\n",
+    "    \"\"\"\n",
+    "    步骤一：继承paddle.io.Dataset类\n",
+    "    \"\"\"\n",
+    "    def __init__(self, mode='train'):\n",
+    "        \"\"\"\n",
+    "        步骤二：实现构造函数，定义数据读取方式，划分训练和测试数据集\n",
+    "        \"\"\"\n",
+    "        super(MyDataset, self).__init__()\n",
+    "\n",
+    "        if mode == 'train':\n",
+    "            self.data = [\n",
+    "                ['traindata1', 'label1'],\n",
+    "                ['traindata2', 'label2'],\n",
+    "                ['traindata3', 'label3'],\n",
+    "                ['traindata4', 'label4'],\n",
+    "            ]\n",
+    "        else:\n",
+    "            self.data = [\n",
+    "                ['testdata1', 'label1'],\n",
+    "                ['testdata2', 'label2'],\n",
+    "                ['testdata3', 'label3'],\n",
+    "                ['testdata4', 'label4'],\n",
+    "            ]\n",
+    "    \n",
+    "    def __getitem__(self, index):\n",
+    "        \"\"\"\n",
+    "        步骤三：实现__getitem__方法，定义指定index时如何获取数据，并返回单条数据（训练数据，对应的标签）\n",
+    "        \"\"\"\n",
+    "        data = self.data[index][0]\n",
+    "        label = self.data[index][1]\n",
+    "\n",
+    "        return data, label\n",
+    "\n",
+    "    def __len__(self):\n",
+    "        \"\"\"\n",
+    "        步骤四：实现__len__方法，返回数据集总数目\n",
+    "        \"\"\"\n",
+    "        return len(self.data)\n",
+    "\n",
+    "# 测试定义的数据集\n",
+    "train_dataset = MyDataset(mode='train')\n",
+    "val_dataset = MyDataset(mode='test')\n",
+    "\n",
+    "print('=============train dataset=============')\n",
+    "for data, label in train_dataset:\n",
+    "    print(data, label)\n",
+    "\n",
+    "print('=============evaluation dataset=============')\n",
+    "for data, label in val_dataset:\n",
+    "    print(data, label)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 3.3 数据增强\n",
+    "\n",
+    "训练过程中有时会遇到过拟合的问题，其中一个解决方法就是对训练数据做增强，对数据进行处理得到不同的图像，从而泛化数据集。数据增强API是定义在领域目录的transofrms下，这里我们介绍两种使用方式，一种是基于框架自带数据集，一种是基于自己定义的数据集。\n",
+    "\n",
+    "#### 3.3.1 框架自带数据集"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from paddle.vision.transforms import Compose, Resize, ColorJitter\n",
+    "\n",
+    "\n",
+    "# 定义想要使用那些数据增强方式，这里用到了随机调整亮度、对比度和饱和度，改变图片大小\n",
+    "transform = Compose([ColorJitter(), Resize(size=100)])\n",
+    "\n",
+    "# 通过transform参数传递定义好的数据增项方法即可完成对自带数据集的应用\n",
+    "train_dataset = vision.datasets.MNIST(mode='train', transform=transform)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### 3.3.2 自定义数据集\n",
+    "\n",
+    "针对自定义数据集使用数据增强有两种方式，一种是在数据集的构造函数中进行数据增强方法的定义，之后对__getitem__中返回的数据进行应用。另外一种方式也可以给自定义的数据集类暴漏一个构造参数，在实例化类的时候将数据增强方法传递进去。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from paddle.io import Dataset\n",
+    "\n",
+    "\n",
+    "class MyDataset(Dataset):\n",
+    "    def __init__(self, mode='train'):\n",
+    "        super(MyDataset, self).__init__()\n",
+    "\n",
+    "        if mode == 'train':\n",
+    "            self.data = [\n",
+    "                ['traindata1', 'label1'],\n",
+    "                ['traindata2', 'label2'],\n",
+    "                ['traindata3', 'label3'],\n",
+    "                ['traindata4', 'label4'],\n",
+    "            ]\n",
+    "        else:\n",
+    "            self.data = [\n",
+    "                ['testdata1', 'label1'],\n",
+    "                ['testdata2', 'label2'],\n",
+    "                ['testdata3', 'label3'],\n",
+    "                ['testdata4', 'label4'],\n",
+    "            ]\n",
+    "\n",
+    "        # 定义要使用的数据预处理方法，针对图片的操作\n",
+    "        self.transform = Compose([ColorJitter(), Resize(size=100)])\n",
+    "    \n",
+    "    def __getitem__(self, index):\n",
+    "        data = self.data[index][0]\n",
+    "\n",
+    "        # 在这里对训练数据进行应用\n",
+    "        # 这里只是一个示例，测试时需要将数据集更换为图片数据进行测试\n",
+    "        data = self.transform(data)\n",
+    "\n",
+    "        label = self.data[index][1]\n",
+    "\n",
+    "        return data, label\n",
+    "\n",
+    "    def __len__(self):\n",
+    "        return len(self.data)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 4. 模型组网\n",
+    "\n",
+    "针对高层API在模型组网上和基础API是统一的一套，无需投入额外的学习使用成本。那么这里我举几个简单的例子来做示例。\n",
+    "\n",
+    "### 4.1 Sequential组网\n",
+    "\n",
+    "针对顺序的线性网络结构我们可以直接使用Sequential来快速完成组网，可以减少类的定义等代码编写。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Sequential形式组网\n",
+    "mnist = paddle.nn.Sequential(\n",
+    "    paddle.nn.Flatten(),\n",
+    "    paddle.nn.Linear(784, 512),\n",
+    "    paddle.nn.ReLU(),\n",
+    "    paddle.nn.Dropout(0.2),\n",
+    "    paddle.nn.Linear(512, 10)\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 4.2 SubClass组网\n",
+    "针对一些比较复杂的网络结构，就可以使用Layer子类定义的方式来进行模型代码编写，在`__init__`构造函数中进行组网Layer的声明，在`forward`中使用声明的Layer变量进行前向计算。子类组网方式也可以实现sublayer的复用，针对相同的layer可以在构造函数中一次性定义，在forward中多次调用。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Layer类继承方式组网\n",
+    "class Mnist(paddle.nn.Layer):\n",
+    "    def __init__(self):\n",
+    "        super(Mnist, self).__init__()\n",
+    "\n",
+    "        self.flatten = paddle.nn.Flatten()\n",
+    "        self.linear_1 = paddle.nn.Linear(784, 512)\n",
+    "        self.linear_2 = paddle.nn.Linear(512, 10)\n",
+    "        self.relu = paddle.nn.ReLU()\n",
+    "        self.dropout = paddle.nn.Dropout(0.2)\n",
+    "\n",
+    "    def forward(self, inputs):\n",
+    "        y = self.flatten(inputs)\n",
+    "        y = self.linear_1(y)\n",
+    "        y = self.relu(y)\n",
+    "        y = self.dropout(y)\n",
+    "        y = self.linear_2(y)\n",
+    "\n",
+    "        return y\n",
+    "\n",
+    "mnist = Mnist()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 4.3 模型封装\n",
+    "\n",
+    "定义好网络结构之后我们来使用`paddle.Model`完成模型的封装，将网络结构组合成一个可快速使用高层API进行训练、评估和预测的类。\n",
+    "\n",
+    "在封装的时候我们有两种场景，动态图训练模式和静态图训练模式。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 场景1：动态图模式\n",
+    "\n",
+    "# 启动动态图训练模式\n",
+    "paddle.disable_static()\n",
+    "# 使用GPU训练\n",
+    "paddle.set_device('gpu')\n",
+    "# 模型封装\n",
+    "model = paddle.Model(mnist)\n",
+    "\n",
+    "\n",
+    "# 场景2：静态图模式\n",
+    "\n",
+    "# input = paddle.static.InputSpec([None, 1, 28, 28], dtype='float32')\n",
+    "# label = paddle.static.InputSpec([None, 1], dtype='int8')\n",
+    "# model = paddle.Model(mnist, input, label)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 4.4 模型可视化\n",
+    "\n",
+    "在组建好我们的网络结构后，一般我们会想去对我们的网络结构进行一下可视化，逐层的去对齐一下我们的网络结构参数，看看是否符合我们的预期。这里可以通过`Model.summary`接口进行可视化展示。\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.summary((1, 28, 28))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "另外，summary接口有两种使用方式，下面我们通过两个示例来做展示，除了`Model.summary`这种配套`paddle.Model`封装使用的接口外，还有一套配合没有经过`paddle.Model`封装的方式来使用。可以直接将实例化好的Layer子类放到`paddle.summary`接口中进行可视化呈现。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "paddle.summary(mnist, (1, 28, 28))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "这里面有一个注意的点，有的用户可能会疑惑为什么要传递`(1, 28, 28)`这个input_size参数，因为在动态图中，网络定义阶段是还没有得到输入数据的形状信息，我们想要做网络结构的呈现就无从下手，那么我们通过告知接口网络结构的输入数据形状，这样网络可以通过逐层的计算推导得到完整的网络结构信息进行呈现。如果是动态图运行模式，那么就不需要给summary接口传递输入数据形状这个值了，因为在Model封装的时候我们已经定义好了InputSpec，其中包含了输入数据的形状格式。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 5. 模型训练\n",
+    "\n",
+    "使用`paddle.Model`封装成模型类后进行训练非常的简洁方便，我们可以直接通过调用`Model.fit`就可以完成训练过程。\n",
+    "\n",
+    "在使用`Model.fit`接口启动训练前，我们先通过`Model.prepare`接口来对训练进行提前的配置准备工作，包括设置模型优化器，Loss计算方法，精度计算方法等。\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 为模型训练做准备，设置优化器，损失函数和精度计算方式\n",
+    "model.prepare(paddle.optimizer.Adam(parameters=model.parameters()), \n",
+    "              paddle.nn.CrossEntropyLoss(),\n",
+    "              paddle.metric.Accuracy())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "做好模型训练的前期准备工作后，我们正式调用`fit()`接口来启动训练过程，需要指定一下至少3个关键参数：训练数据集，训练轮次和单次训练数据批次大小。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 启动模型训练，指定训练数据集，设置训练轮次，设置每次数据集计算的批次大小，设置日志格式\n",
+    "model.fit(train_dataset, \n",
+    "          epochs=10, \n",
+    "          batch_size=32,\n",
+    "          verbose=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 5.1 单机单卡\n",
+    "\n",
+    "我们把刚才单步教学的训练代码做一个整合，这个完整的代码示例就是我们的单机单卡训练程序。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# 启动动态图训练模式\n",
+    "paddle.disable_static()\n",
+    "\n",
+    "# 使用GPU训练\n",
+    "paddle.set_device('gpu')\n",
+    "\n",
+    "# 构建模型训练用的Model，告知需要训练哪个模型\n",
+    "model = paddle.Model(mnist)\n",
+    "\n",
+    "# 为模型训练做准备，设置优化器，损失函数和精度计算方式\n",
+    "model.prepare(paddle.optimizer.Adam(parameters=model.parameters()), \n",
+    "              paddle.nn.CrossEntropyLoss(),\n",
+    "              paddle.metric.Accuracy())\n",
+    "\n",
+    "# 启动模型训练，指定训练数据集，设置训练轮次，设置每次数据集计算的批次大小，设置日志格式\n",
+    "model.fit(train_dataset, \n",
+    "          epochs=10, \n",
+    "          batch_size=32,\n",
+    "          verbose=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 5.2 单机多卡\n",
+    "\n",
+    "对于高层API来实现单机多卡非常简单，整个训练代码和单机单卡没有差异。直接使用`paddle.distributed.launch`启动单机单卡的程序即可。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# train.py里面包含的就是单机单卡代码\n",
+    "python -m paddle.distributed.launch train.py"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 6. 模型评估\n",
+    "\n",
+    "对于训练好的模型进行评估操作可以使用`evaluate`接口来实现。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result = model.evaluate(val_dataset, verbose=1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 7. 模型预测\n",
+    "\n",
+    "高层API中提供`predict`接口，支持用户使用测试数据来完成模型的预测。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pred_result = model.predict(val_dataset)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 8. 模型部署\n",
+    "\n",
+    "### 8.1 模型存储\n",
+    "\n",
+    "模型训练和验证达到我们的预期后，可以使用`save`接口来将我们的模型保存下来，用于后续模型的Fine-tuning或推理部署。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 保存用于推理部署的模型（training=False）\n",
+    "model.save('~/model/mnist', training=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 8.2 预测部署\n",
+    "\n",
+    "有了用于推理部署的模型，就可以使用推理部署框架来完成预测服务部署，具体可以参见：[预测部署](https://www.paddlepaddle.org.cn/documentation/docs/zh/advanced_guide/inference_deployment/index_cn.html)， 包括服务端部署、移动端部署和模型压缩。"
+   ]
+  }
+ ]
+}
\ No newline at end of file
diff --git a/doc/paddle/tutorial/quick_start/high_level_api/high_level_api.rst b/doc/paddle/tutorial/quick_start/high_level_api/high_level_api.rst
new file mode 100644
index 0000000000000000000000000000000000000000..e783ccc5b0607d88499c69f24c5d3fdc485e1aa5
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@@ -0,0 +1,436 @@
+飞桨高层API使用指南
+===================
+
+1. 简介
+-------
+
+飞桨2.0全新推出高层API，是对飞桨API的进一步封装与升级，提供了更加简洁易用的API，进一步提升了飞桨的易学易用性，并增强飞桨的功能。
+
+飞桨高层API面向从深度学习小白到资深开发者的所有人群，对于AI初学者来说，使用高层API可以简单快速的构建深度学习项目，对于资深开发者来说，可以快速完成算法迭代。
+
+飞桨高层API具有以下特点：
+
+-  易学易用:
+   高层API是对普通动态图API的进一步封装和优化，同时保持与普通API的兼容性，高层API使用更加易学易用，同样的实现使用高层API可以节省大量的代码。
+-  低代码开发:
+   使用飞桨高层API的一个明显特点是，用户可编程代码量大大缩减。
+-  动静转换:
+   高层API支持动静转换，用户只需要改一行代码即可实现将动态图代码在静态图模式下训练，既方便用户使用动态图调试模型，又提升了模型训练效率。
+
+在功能增强与使用方式上，高层API有以下升级：
+
+-  模型训练方式升级:
+   高层API中封装了Model类，继承了Model类的神经网络可以仅用几行代码完成模型的训练。
+-  新增图像处理模块transform:
+   飞桨新增了图像预处理模块，其中包含数十种数据处理函数，基本涵盖了常用的数据处理、数据增强方法。
+-  提供常用的神经网络模型可供调用:
+   高层API中集成了计算机视觉领域和自然语言处理领域常用模型，包括但不限于mobilenet、resnet、yolov3、cyclegan、bert、transformer、seq2seq等等。同时发布了对应模型的预训练模型，用户可以直接使用这些模型或者在此基础上完成二次开发。
+
+2. 安装并使用飞桨高层API
+------------------------
+
+飞桨高层API无需独立安装，只需要安装好paddlepaddle即可，安装完成后import
+paddle即可使用相关高层API，如：paddle.Model、视觉领域paddle.vision、NLP领域paddle.text。
+
+.. code:: ipython3
+
+    import paddle
+    import paddle.vision as vision
+    import paddle.text as text
+    
+    paddle.__version__
+
+
+
+
+.. parsed-literal::
+
+    '0.0.0'
+
+
+
+2. 目录
+-------
+
+本指南教学内容覆盖
+
+-  使用高层API提供的自带数据集进行相关深度学习任务训练。
+-  使用自定义数据进行数据集的定义、数据预处理和训练。
+-  如何在数据集定义和加载中应用数据增强相关接口。
+-  如何进行模型的组网。
+-  高层API进行模型训练的相关API使用。
+-  如何在fit接口满足需求的时候进行自定义，使用基础API来完成训练。
+-  如何使用多卡来加速训练。
+
+其他端到端的示例教程： \* TBD
+
+3. 数据集定义、加载和数据预处理
+-------------------------------
+
+对于深度学习任务，均是框架针对各种类型数字的计算，是无法直接使用原始图片和文本等文件来完成。那么就是涉及到了一项动作，就是将原始的各种数据文件进行处理加工，转换成深度学习任务可以使用的数据。
+
+3.1 框架自带数据集使用
+~~~~~~~~~~~~~~~~~~~~~~
+
+高层API将一些我们常用到的数据集作为领域API对用户进行开放，对应API所在目录为\ ``paddle.vision.datasets``\ ，那么我们先看下提供了哪些数据集。
+
+.. code:: ipython3
+
+    paddle.vision.datasets.__all__
+
+
+
+
+.. parsed-literal::
+
+    ['DatasetFolder',
+     'ImageFolder',
+     'MNIST',
+     'Flowers',
+     'Cifar10',
+     'Cifar100',
+     'VOC2012']
+
+
+
+这里我们是加载一个手写数字识别的数据集，用\ ``mode``\ 来标识是训练数据还是测试数据集。数据集接口会自动从远端下载数据集到本机缓存目录\ ``~/.cache/paddle/dataset``\ 。
+
+.. code:: ipython3
+
+    # 测试数据集
+    train_dataset = vision.datasets.MNIST(mode='train')
+    
+    # 验证数据集
+    val_dataset = vision.datasets.MNIST(mode='test')
+
+3.2 自定义数据集
+~~~~~~~~~~~~~~~~
+
+更多的时候我们是需要自己使用已有的相关数据来定义数据集，那么这里我们通过一个案例来了解如何进行数据集的定义，飞桨为用户提供了\ ``paddle.io.Dataset``\ 基类，让用户通过类的集成来快速实现数据集定义。
+
+.. code:: ipython3
+
+    from paddle.io import Dataset
+    
+    
+    class MyDataset(Dataset):
+        """
+        步骤一：继承paddle.io.Dataset类
+        """
+        def __init__(self, mode='train'):
+            """
+            步骤二：实现构造函数，定义数据读取方式，划分训练和测试数据集
+            """
+            super(MyDataset, self).__init__()
+    
+            if mode == 'train':
+                self.data = [
+                    ['traindata1', 'label1'],
+                    ['traindata2', 'label2'],
+                    ['traindata3', 'label3'],
+                    ['traindata4', 'label4'],
+                ]
+            else:
+                self.data = [
+                    ['testdata1', 'label1'],
+                    ['testdata2', 'label2'],
+                    ['testdata3', 'label3'],
+                    ['testdata4', 'label4'],
+                ]
+        
+        def __getitem__(self, index):
+            """
+            步骤三：实现__getitem__方法，定义指定index时如何获取数据，并返回单条数据（训练数据，对应的标签）
+            """
+            data = self.data[index][0]
+            label = self.data[index][1]
+    
+            return data, label
+    
+        def __len__(self):
+            """
+            步骤四：实现__len__方法，返回数据集总数目
+            """
+            return len(self.data)
+    
+    # 测试定义的数据集
+    train_dataset = MyDataset(mode='train')
+    val_dataset = MyDataset(mode='test')
+    
+    print('=============train dataset=============')
+    for data, label in train_dataset:
+        print(data, label)
+    
+    print('=============evaluation dataset=============')
+    for data, label in val_dataset:
+        print(data, label)
+
+
+.. parsed-literal::
+
+    =============train dataset=============
+    traindata1 label1
+    traindata2 label2
+    traindata3 label3
+    traindata4 label4
+    =============evaluation dataset=============
+    testdata1 label1
+    testdata2 label2
+    testdata3 label3
+    testdata4 label4
+
+
+3.3 数据增强
+~~~~~~~~~~~~
+
+训练过程中有时会遇到过拟合的问题，其中一个解决方法就是对训练数据做增强，对数据进行处理得到不同的图像，从而泛化数据集。数据增强API是定义在领域目录的transofrms下，这里我们介绍两种使用方式，一种是基于框架自带数据集，一种是基于自己定义的数据集。
+
+3.3.1 框架自带数据集
+^^^^^^^^^^^^^^^^^^^^
+
+.. code:: ipython3
+
+    from paddle.vision.transforms import Compose, Resize, ColorJitter
+    
+    
+    # 定义想要使用那些数据增强方式，这里用到了随机调整亮度、对比度和饱和度，改变图片大小
+    transform = Compose([ColorJitter(), Resize(size=100)])
+    
+    # 通过transform参数传递定义好的数据增项方法即可完成对自带数据集的应用
+    train_dataset = vision.datasets.MNIST(mode='train', transform=transform)
+
+3.3.2 自定义数据集
+^^^^^^^^^^^^^^^^^^
+
+针对自定义数据集使用数据增强有两种方式，一种是在数据集的构造函数中进行数据增强方法的定义，之后对__getitem__中返回的数据进行应用。另外一种方式也可以给自定义的数据集类暴漏一个构造参数，在实例化类的时候将数据增强方法传递进去。
+
+.. code:: ipython3
+
+    from paddle.io import Dataset
+    
+    
+    class MyDataset(Dataset):
+        def __init__(self, mode='train'):
+            super(MyDataset, self).__init__()
+    
+            if mode == 'train':
+                self.data = [
+                    ['traindata1', 'label1'],
+                    ['traindata2', 'label2'],
+                    ['traindata3', 'label3'],
+                    ['traindata4', 'label4'],
+                ]
+            else:
+                self.data = [
+                    ['testdata1', 'label1'],
+                    ['testdata2', 'label2'],
+                    ['testdata3', 'label3'],
+                    ['testdata4', 'label4'],
+                ]
+    
+            # 定义要使用的数据预处理方法，针对图片的操作
+            self.transform = Compose([ColorJitter(), Resize(size=100)])
+        
+        def __getitem__(self, index):
+            data = self.data[index][0]
+    
+            # 在这里对训练数据进行应用
+            # 这里只是一个示例，测试时需要将数据集更换为图片数据进行测试
+            data = self.transform(data)
+    
+            label = self.data[index][1]
+    
+            return data, label
+    
+        def __len__(self):
+            return len(self.data)
+
+4. 模型组网
+-----------
+
+针对高层API在模型组网上和基础API是统一的一套，无需投入额外的学习使用成本。那么这里我举几个简单的例子来做示例。
+
+4.1 Sequential组网
+~~~~~~~~~~~~~~~~~~
+
+针对顺序的线性网络结构我们可以直接使用Sequential来快速完成组网，可以减少类的定义等代码编写。
+
+.. code:: ipython3
+
+    # Sequential形式组网
+    mnist = paddle.nn.Sequential(
+        paddle.nn.Flatten(),
+        paddle.nn.Linear(784, 512),
+        paddle.nn.ReLU(),
+        paddle.nn.Dropout(0.2),
+        paddle.nn.Linear(512, 10)
+    )
+
+4.2 SubClass组网
+~~~~~~~~~~~~~~~~
+
+针对一些比较复杂的网络结构，就可以使用Layer子类定义的方式来进行模型代码编写，在\ ``__init__``\ 构造函数中进行组网Layer的声明，在\ ``forward``\ 中使用声明的Layer变量进行前向计算。子类组网方式也可以实现sublayer的复用，针对相同的layer可以在构造函数中一次性定义，在forward中多次调用。
+
+.. code:: ipython3
+
+    # Layer类继承方式组网
+    class Mnist(paddle.nn.Layer):
+        def __init__(self):
+            super(Mnist, self).__init__()
+    
+            self.flatten = paddle.nn.Flatten()
+            self.linear_1 = paddle.nn.Linear(784, 512)
+            self.linear_2 = paddle.nn.Linear(512, 10)
+            self.relu = paddle.nn.ReLU()
+            self.dropout = paddle.nn.Dropout(0.2)
+    
+        def forward(self, inputs):
+            y = self.flatten(inputs)
+            y = self.linear_1(y)
+            y = self.relu(y)
+            y = self.dropout(y)
+            y = self.linear_2(y)
+    
+            return y
+    
+    mnist = Mnist()
+
+4.3 模型封装
+~~~~~~~~~~~~
+
+定义好网络结构之后我们来使用\ ``paddle.Model``\ 完成模型的封装，将网络结构组合成一个可快速使用高层API进行训练、评估和预测的类。
+
+在封装的时候我们有两种场景，动态图训练模式和静态图训练模式。
+
+.. code:: ipython3
+
+    # 场景1：动态图模式
+    
+    # 启动动态图训练模式
+    paddle.disable_static()
+    # 使用GPU训练
+    paddle.set_device('gpu')
+    # 模型封装
+    model = paddle.Model(mnist)
+    
+    
+    # 场景2：静态图模式
+    
+    # input = paddle.static.InputSpec([None, 1, 28, 28], dtype='float32')
+    # label = paddle.static.InputSpec([None, 1], dtype='int8')
+    # model = paddle.Model(mnist, input, label)
+
+4.4 模型可视化
+~~~~~~~~~~~~~~
+
+在组建好我们的网络结构后，一般我们会想去对我们的网络结构进行一下可视化，逐层的去对齐一下我们的网络结构参数，看看是否符合我们的预期。这里可以通过\ ``Model.summary``\ 接口进行可视化展示。
+
+.. code:: ipython3
+
+    model.summary((1, 28, 28))
+
+另外，summary接口有两种使用方式，下面我们通过两个示例来做展示，除了\ ``Model.summary``\ 这种配套\ ``paddle.Model``\ 封装使用的接口外，还有一套配合没有经过\ ``paddle.Model``\ 封装的方式来使用。可以直接将实例化好的Layer子类放到\ ``paddle.summary``\ 接口中进行可视化呈现。
+
+.. code:: ipython3
+
+    paddle.summary(mnist, (1, 28, 28))
+
+这里面有一个注意的点，有的用户可能会疑惑为什么要传递\ ``(1, 28, 28)``\ 这个input_size参数，因为在动态图中，网络定义阶段是还没有得到输入数据的形状信息，我们想要做网络结构的呈现就无从下手，那么我们通过告知接口网络结构的输入数据形状，这样网络可以通过逐层的计算推导得到完整的网络结构信息进行呈现。如果是动态图运行模式，那么就不需要给summary接口传递输入数据形状这个值了，因为在Model封装的时候我们已经定义好了InputSpec，其中包含了输入数据的形状格式。
+
+5. 模型训练
+-----------
+
+使用\ ``paddle.Model``\ 封装成模型类后进行训练非常的简洁方便，我们可以直接通过调用\ ``Model.fit``\ 就可以完成训练过程。
+
+在使用\ ``Model.fit``\ 接口启动训练前，我们先通过\ ``Model.prepare``\ 接口来对训练进行提前的配置准备工作，包括设置模型优化器，Loss计算方法，精度计算方法等。
+
+.. code:: ipython3
+
+    # 为模型训练做准备，设置优化器，损失函数和精度计算方式
+    model.prepare(paddle.optimizer.Adam(parameters=model.parameters()), 
+                  paddle.nn.CrossEntropyLoss(),
+                  paddle.metric.Accuracy())
+
+做好模型训练的前期准备工作后，我们正式调用\ ``fit()``\ 接口来启动训练过程，需要指定一下至少3个关键参数：训练数据集，训练轮次和单次训练数据批次大小。
+
+.. code:: ipython3
+
+    # 启动模型训练，指定训练数据集，设置训练轮次，设置每次数据集计算的批次大小，设置日志格式
+    model.fit(train_dataset, 
+              epochs=10, 
+              batch_size=32,
+              verbose=1)
+
+5.1 单机单卡
+~~~~~~~~~~~~
+
+我们把刚才单步教学的训练代码做一个整合，这个完整的代码示例就是我们的单机单卡训练程序。
+
+.. code:: ipython3
+
+    # 启动动态图训练模式
+    paddle.disable_static()
+    
+    # 使用GPU训练
+    paddle.set_device('gpu')
+    
+    # 构建模型训练用的Model，告知需要训练哪个模型
+    model = paddle.Model(mnist)
+    
+    # 为模型训练做准备，设置优化器，损失函数和精度计算方式
+    model.prepare(paddle.optimizer.Adam(parameters=model.parameters()), 
+                  paddle.nn.CrossEntropyLoss(),
+                  paddle.metric.Accuracy())
+    
+    # 启动模型训练，指定训练数据集，设置训练轮次，设置每次数据集计算的批次大小，设置日志格式
+    model.fit(train_dataset, 
+              epochs=10, 
+              batch_size=32,
+              verbose=1)
+
+5.2 单机多卡
+~~~~~~~~~~~~
+
+对于高层API来实现单机多卡非常简单，整个训练代码和单机单卡没有差异。直接使用\ ``paddle.distributed.launch``\ 启动单机单卡的程序即可。
+
+.. code:: ipython3
+
+    # train.py里面包含的就是单机单卡代码
+    python -m paddle.distributed.launch train.py
+
+6. 模型评估
+-----------
+
+对于训练好的模型进行评估操作可以使用\ ``evaluate``\ 接口来实现。
+
+.. code:: ipython3
+
+    result = model.evaluate(val_dataset, verbose=1)
+
+7. 模型预测
+-----------
+
+高层API中提供\ ``predict``\ 接口，支持用户使用测试数据来完成模型的预测。
+
+.. code:: ipython3
+
+    pred_result = model.predict(val_dataset)
+
+8. 模型部署
+-----------
+
+8.1 模型存储
+~~~~~~~~~~~~
+
+模型训练和验证达到我们的预期后，可以使用\ ``save``\ 接口来将我们的模型保存下来，用于后续模型的Fine-tuning或推理部署。
+
+.. code:: ipython3
+
+    # 保存用于推理部署的模型（training=False）
+    model.save('~/model/mnist', training=False)
+
+8.2 预测部署
+~~~~~~~~~~~~
+
+有了用于推理部署的模型，就可以使用推理部署框架来完成预测服务部署，具体可以参见：\ `预测部署 <https://www.paddlepaddle.org.cn/documentation/docs/zh/advanced_guide/inference_deployment/index_cn.html>`__\ ，
+包括服务端部署、移动端部署和模型压缩。
diff --git a/doc/paddle/tutorial/quick_start/index_cn.rst b/doc/paddle/tutorial/quick_start/index_cn.rst
new file mode 100644
index 0000000000000000000000000000000000000000..8c90bc463cba92f965a5b3c160ebb5bb78da84aa
--- /dev/null
+++ b/doc/paddle/tutorial/quick_start/index_cn.rst
@@ -0,0 +1,25 @@
+################
+快速上手
+################
+
+
+在这里PaddlePaddle为大家提供了一些简单的案例，快速上手paddle 2.0:
+    
+     - `hello paddle <./hello_paddle/hello_paddle.html>`_ ：简单介绍 Paddle，完成您的第一个Paddle项目。
+     - `Paddle 动态图 <./dynamic_graph/dynamic_graph.html>`_ ：介绍使用 Paddle 动态图。    
+     - `高层API快速上手 <./getting_started/getting_started.html>`_ ：介绍Paddle高层API，快速完成模型搭建。
+     - `高层API详细介绍 <./high_level_api/high_level_api.html>`_ ：详细介绍Paddle高层API。
+     - `模型加载与保存 <./save_model/save_model.html>`_ ：介绍Paddle 模型的加载与保存。
+     - `线性回归 <./linear_regression/linear_regression.html>`_ ：介绍使用 Paddle 实现线性回归任务。
+
+
+..  toctree::
+    :hidden:
+    :titlesonly:
+
+    hello_paddle/hello_paddle.rst
+    dynamic_graph/dynamic_graph.rst
+    getting_started/getting_started.rst
+    high_level_api/high_level_api.rst
+    save_model/save_model.rst
+    linear_regression/linear_regression.rst
diff --git a/doc/paddle/tutorial/quick_start/linear_regression/linear_regression.ipynb b/doc/paddle/tutorial/quick_start/linear_regression/linear_regression.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..e2215946e2bc0b0043ce925de43f1ff9d3cb02e5
--- /dev/null
+++ b/doc/paddle/tutorial/quick_start/linear_regression/linear_regression.ipynb
@@ -0,0 +1,649 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "V0CqD2QfXd9R"
+   },
+   "source": [
+    "# 线性回归\n",
+    "NOTE: 本示例教程依然在开发中，目前是基于2.0beta版本（由于2.0beta没有正式发版，在用最新develop版whl包下载的paddle）。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "6lPmRFntXYIp"
+   },
+   "source": [
+    "# 简要介绍\n",
+    "经典的线性回归模型主要用来预测一些存在着线性关系的数据集。回归模型可以理解为：存在一个点集，用一条曲线去拟合它分布的过程。如果拟合曲线是一条直线，则称为线性回归。如果是一条二次曲线，则被称为二次回归。线性回归是回归模型中最简单的一种。 \n",
+    "本示例简要介绍如何用飞桨开源框架，实现波士顿房价预测。其思路是，假设uci-housing数据集中的房子属性和房价之间的关系可以被属性间的线性组合描述。在模型训练阶段，让假设的预测结果和真实值之间的误差越来越小。在模型预测阶段，预测器会读取训练好的模型，对从未遇见过的房子属性进行房价预测。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "ndB_NJGPXbIt"
+   },
+   "source": [
+    "# 环境设置\n",
+    "本示例基于飞桨开源框架2.0版本。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 35
+    },
+    "colab_type": "code",
+    "id": "ujM1I5GaZLXH",
+    "outputId": "1b138a90-2e29-4cac-89a9-2ab21f4d6974"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.0.0'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import paddle\n",
+    "import numpy as np\n",
+    "import os\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "\n",
+    "paddle.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "OEOMtGXCZaRR"
+   },
+   "source": [
+    "# 数据集\n",
+    "本示例采用uci-housing数据集，这是经典线性回归的数据集。数据集共506行,每行14列。前13列用来描述房屋的各种信息，最后一列为该类房屋价格中位数。飞桨提供了读取uci_housing训练集和测试集的接口，分别为paddle.dataset.uci_housing.train()和paddle.dataset.uci_housing.test()。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "前13列用来描述房屋的各种信息\n",
+    "\n",
+    "![avatar](https://ai-studio-static-online.cdn.bcebos.com/c19602ce74284e3b9a50422f8dc37c0c1c79cf5cd8424994b6a6b073dcb7c057)\n",
+    "\n",
+    "下面我们来浏览一下数据是什么样子的："
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[-0.0405441   0.06636364 -0.32356227 -0.06916996 -0.03435197  0.05563625\n",
+      " -0.03475696  0.02682186 -0.37171335 -0.21419304 -0.33569506  0.10143217\n",
+      " -0.21172912]\n"
+     ]
+    },
+    {
+     "data": {
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k3tPQQEZHsoXQthMsT7hO1X6C5TO970i2ULc8OGZtWZrtJ5VwQ88hWNfoHIP2P9O+Z6qrsO0Wu0b1kHSdlutnPuuy0b4m817dsvncfyrhNjznybzXsA14vm36nspllT83aguN9he8txtjtFW1fUBQl5V16pjGnx9Cl7sLk/Zs1Hc3KlNtH127DTECIEqajd0Y0wHzo9PtqdPHB6Kg2VjWrWkjjXImtWO/OLWhmcY0s80rhY2NG9VZWL6gsh5r1zfaz3yOo8g5oRVzzYFWxnezXFZlDqRZG6xd12zbZnmw2eRQZttGWtm+1Rxno/Obr9yj1GWT6Fb1p7Us4+i2rcPlih0ayOi2rcMazKQ6XDpgZoOZVMfjNwplAJoJi1H6fswn+kEEVvSGx8KK3u6Ihbm2hcFMSr1p+mUgzGBfSjuvHqlqG2uWZ7RqSUrbt2zU3Xv26ebNG6vW37y5tHzH1mGt6k9X7SfYvtn7br1yk+7es69u+SmDvXVlCVsWbL/z6hEN9qVCzyFY1+gcd149olX9ae2o6Rdq9z1TXYVtt9g1q89W62c+67LRvk4Z7G3r/gf7UqEx9PFLz9byvmTDNrBr99N179m+ZaNOHuipahe17SSsLWzfslE7v/e4tm/ZWLd8x3d/3rUx2qpV/emqzwa7dj+t27YOa9fup3XrlZs0NJDR39y/P/TzwyPPPl/eJlhe2Se2W1hcrlqSqoutoEy1fXS392MAoq3ZuI8xHTA/Ot2eOn18IAqajWUfeGqs6rP93Xv26eSBnrqx3ycuP6c89lvI8ch8CB3TLD02xt7x3Z/XnW9lPqp2/Lxr99N1Y501yzMNx+zNxtC1+YSw8fh8j6PIOaEVc8mB1sZ3WP5u+5aNWrM8o3985BflXEdYGwzaXu26oF2GHbdRHmzN8sys+qzZtpFWtm81xxl2fvOZe5QkY218biXaipGREbt79+6G66emihrL5lX0rRKO0QkZRwkl1NPTVU+2xdws2FcGmsVxbQwPZlJtj9+wY7Zahny+qNGJY9v2pR31JZNKJpmt3wGRiOFW1cbOyr6UUqnWYj0sZie9orJ5f0HbDuZdZGK4E30xoimXK+rg5LFYWNGbUjrdMBYiE8OzNTVVrOtHV/Wn5Xm2ri04jmbsv6emisqrqKNZ+uUYWpA4nu8YjrJi0deB8ZwKnq+k62hlX0pHporKFz2lEq4GMkm9kCuoUPRV8K1cR3LN/2PvbaPjuM4zwefe+uhudIME0AQYmSApUaYoa2dBGYCdsZLoKFKieGInzhxCdI5Jy5YzTCj6I6Pj0PbJmR/+sZu1wmgZOw5Fm5PYkklPIpNJnFgZxxkrGidRMhuANnl2Fck0JZEErRAgAJJAo7vr4979UX0L9XGrurrRABpAPefwEF11634+73vf96nqLgrTduwnq1LY3HnNYUZVUMzrYIxjcq4KDg7OAZtzZBQKi3FYjEOjBIQAjAOdOQVzFQbLZlApAaUEVYshpyno6dAxUzbBGIPNAc45NJVCpQSm5bRvMw5VoegrZKCqzvf0GOOYKhnuGIp5HdTzDeyo86ZpY2Ku6vqFjErBQULX16unDtqWw97xZHUKw+QwarwQ8ysbMwDcqhiYr9o1jhDkdIqNGWf9ksxP3FwmWc8bZQNlw4bNObKqAlUhKBv+Pk6VDB+Xkq5ZsP3unBY5LmFPFmNQCAElQFajmDcY7Nrc0Br3Bb+6siomSwbMmg3kdIqKyWHaDAol0ChBRqMwbA7TYqExGZbt2kXZsJHTFVjMKes93gBH62HVxhP14PUBWZWCUALDYmA1nwACEDhrWLEW1su0OBgAw3LWTFcoejp01yc12raIcxrRLRjjuF6qomIyKATI6Qo6dYdbKgVMu+Z/a/bMOQ/5u5Jh++w9iOB+EVVuFaDtOHz7Z55fht4Ab3zuPcvSToolR9txOA6L0dcEojSQOG0k1U3aGquKw+2OxcYQAs3aTBIbT1L3KrTZts3rUqxeyHJfxjim5w1wzmHWNJCcSsHg5LWUkFqcT9yYP6ENtR2HveMnhKBDJyhVF7TbQpY6+lHts8idKXF+SdzmHAoh7lyIzxmVgnHAtJ28XOR2vJaXz5s2VEqhEIDU3mASzK0JIVAIQCkN5eON5tpJtaQmNaf1hLbj8EogSqeL0vc6dIqq6dfGunMablYNlGvala5QbKrpwwrlYMyxMeGDNIUipxMwBpTN2jUqha4ScAZUrbCd2oyBEuJqFddLBgx7QUPpzmmYNawFbU9TsCmfidVz4/S5enPltW/vtVF2l6Rt77wntNnIk20dAbUalYqFC1MlPH5yDOMzZffbFNt6AFTQ7gFhihQAHJ5uWUauRtnNzmK+rs0YhoVXJ8PXbt7A0Q09fZAuRSSiuLOrN59I6PPaSaViYbpqYGrODNV3d18h5WGKhrEYv5hi7SGTUbEl+qG5NYF6fnRLd4dbNqn/zmZVZKFiQ3YlRpQiRfvAshheuTaLgx6bOb5/CHdv7oSqLnz7r8fzN2Mcr16bxYFnR9FbyOBT796Fw6fPu9f/twM/iZtlC1/47g/xofvuwKfPnJeWe+qR3XjhX/8Nv3Rvv6/9IyMD+N1vv4rJuSpOPDqMnb0FXJicw4FnR90yz37knahazHfsxKPD2LW5E7T2IF5vZ/S3F2XnGeP40fVSZJ1J61mtqLeux/cPYVdfQTpHb92Ux/hMJbSOmzdkcXsxn0jkjZpLb79k68IYxxtTJVy7VfH1V7Z2xbweW1e9eUlyjapSvKVr4ZUOMht7cs8AnnnpdTzx87tC/H74nj584qG7fOXj2gvNWT5igqOOp/BB0xRs6e6I5NVTj+zGH/3Da3ji53f5OCjjyKYGvkFtmjZemZhbVL5IKUFfZziw6StkpH5+Q07FB078L/fYsX2DOPlPl/DSa1OefWDhAbn4/WJVPkiXIkWKZcBi9TWBKD066niqm6RYL2hFDCHQzH2fJDae1B6X+75TihTtiGBezBjH5Zl5lA0LtyoWDp929JXf/sW7ceLvX8Ohn30rTIvhf7z8b3jP7i04dOrsovbblYZ3/EH/9vA9ffj4Q3f5fMnx/UP4qx+M4/5dm/HpM+fdch97cKdvLo7vH4LNGD769e+HcruPPbjTzYN8WkOuvhbQjB7UiMawljSnFEsHmd+I0/dkmmqUzrqzt4A3b5VRNm1MzRm+er762DswUzLwxHPnQprwwcCe/60fjONLf/+GW2/XZh23ebSzJNpeo/pc3FzVq0tmd7LjsnKtstl1pbJMlQ3XuQPA+EwZj58cw1yFYapsrHDvUqRoT0TZTRKbmSzJrzUs5xvXKVJEIYo7k6XGffVU2YBtQ1pfysMUzWAxfjFFitWIRvxoK/13ihTrARNzVVfYABybOVgnRpkqGa7IcPCBO11xQ1xftTgOnhzDnqGtrogpK/fJb5zDyPC2UPuHT5/HwQfuxPhMGQeeHcXEXNVtT5S5NDUfOnbg2VFMLcLWveNqVZ2rCfXWVfBCNkcyHh0+fR6XpuYXPX/11mWqZODS1Hyov7K1a2aNF8sL2dx8+sx57BnaKuX3nqGtofLriYftgiheffIb59y183Jwsb5jYq66ZPlilJ83LO47dujUWRy4f0fkPtDMfpEiRYoUK5WfpbpJivWCpYwhkiCJjaf2mCJF8xB5ycTswsMrBx+4E0885+QlMyUTTzznaCvioTFgbeihQf+2Z2hryJccPDmGkeFtrvYkygXn4uDJMUyXTGlu582DWp3nybDetacUS496+p5MU43SWSfmqqhaHFdnKqF6rkyX3QfoxDGhCQd90cjwNl+9Mr2unrbXSttZDXa4eh5/bgEstiBQCYzPlGGxtfVK2xQpWonF2E3UtXZqcynqoJX+2mIcvHZ9K+pLkSKNJ1KsNzTiR1P7SJGiMZg2k9uMzSKvMSzbvaYrp4Wup8Spw3tOVm58pgyFEunxrpzm/i3rY4euSK8zLLvekBONq1V1ribUW1fhSxs53qEri56/eutiWHZie9FVIQAAIABJREFUPjSzxovlRZSNiTm2Auej5n698LBdEMcrsUZeDi52zZYyfoniYPCL2sInu20H9oFm9osUKVKkWKn8LM0LU6wXrDTXk7S/0n1MkWI1Q+QlwIIuKvIRr24Spa2sZjsL+o6kulJUOTGP3mOirDcPamWeJ8N6155SLD3q6XsyrSNK/7BsBkqSXyM04WA9ikeAiNLr6ml7rbSd1WCH6+qX6FRK0N+d8x3r785Brb1fO0WKFGHE2U2z1yqpzaWog8XwTlaXQlpXX4oUreRnihSrAY340dQ+UqRoDJpC5TajRKfquqq419wom6HrGXfq8J6TlevvzsFmXHr8Rtl0/5b1cd6wpdfpamOvLIoaV6vqXE2ot67ClzZyfN6wFz1/9dZFV5XEfGhmjRfLiygbE3OsBs5Hzf164WG7II5XYo28HFzsmi1l/BLFweD9NOGT3bYD+0Az+0WKFClSrFR+luaFKdYLVprrSdpf6T6mSLGaIfISb24i8pEbZdM9HqWtrGY7C/qOpLpSVLl5ww4dE2W9eVAr8zwZ1rv2lGLpUU/fk2kdUfqHqlAwnvwaoQkH6/H+uFGUXldP22ul7awGO1xXSksxp+Pp/UPuooj3ABeyFMWcvsK9S5GiPRFlN0lspjcvv1ZXCfoK6XvkU0Qjiju9+cZ9dTGnQ1EgrS/lYYpmsBi/mCLFakQjfrSV/jtFivWAvkIGxwM2c7xOjFLM6zjx6LBT9sWLODIy4Ls+oxIc3z+EM2NX8OSegchyTz2yG6dHL4faPzIygOMvXkR/dw4nHh1GXyHjtifKbC92hI6deHQYxUXYundcrapzNaHeugpeyOZIxqMjIwPYXuxY9PzVW5diXsf2Ykeov7K1a2aNF8sL2dw8uWcAZ8auSPl9ZuxKqPx64mG7IIpXTz2y2107LwcX6zv6Cpklyxej/LyuEt+xY/sGceJ7r0XuA83sFylSpEixUvlZqpukWC9YyhgiCZLYeGqPKVI0D5GX9HXqbm5y/MWLOLrXyUu68xqO7nW0lWP7BteUHhr0b2fGroR8yfH9Qzg9etnVnkS54Fwc3z+Enrwmze28eVCr8zwZ1rv2lGLpUU/fk2mqUTprXyGDjEqwpTsbqmdrTw5H9+6WasJBX3R69LKvXpleV0/ba6XtrAY7JJyv3p8SlWF4eJiPjo5Gnq9ULEyVDViMQ6UEXTkKBSqy2XX1ZtsUzWHZvjIQx+Mgh4s5fcn520ibsrLez/kMRV7ToGmte5rYNG1MzFXdNvoKmZbWv4bQFhxOCsOwMFla4E5vXoeu1+e64GBWo6iYzL2+M0cxW2Yt48lK2GKK9uFwuv4pmkTbcFiGqP20UrFgw0LVBspGfT/arP+OQ2pzbYVl4XErYonVAstiju3ZDKpC0aFTlKrOL4h15zRMzxsomzYUSpDTKGzm/Dx/1WIgBAAHTMaRUZ1vJ1qMQaUUKgEszgHu/J9RKCzGYTMOVaEg4OBwbHSmYqJqMigEoJTAsBmymoJN+QwoJWCMY6pkwLCcfglRI3iMLvJb1rJ2FlunBG3LYe/4NYXCshlMxqEpFH2FDFSVRs6RZTFMzlVh2AwKJdAVip4OPfaaJP0QPJwpm5HXM8Zxo2ygbNgOvyhBVlfQlQvzJKoub5uEkBoXaWKuCTsybeabL+85qzY3oj1KAYVS9OR0X5+8fdRUCpUSmBaDzQHGOWgD/fOOK6crsBiHabHF8rut44l6YIzjeqkKgMO0OCzGoVGCnE4xX4szNIWiN69j1rAcXnEOjVJQz7wHObhY35FEV7AshpsVw80zg1zzlhN83JBV3HGplKBDp+jMOLzx8jKjUpQMO7JOb71iv4gqtwrQdhy+/TPPL0NvgDc+955laSfFkqPtOByHVudnQX8p9LdgjrbcOVyaMzaEVcXhdkdcDLFYXia5PomNr1H7aNu8LkV7wpdv1/K8slE/fzBN27GxWtxOCKBSWvtlJyc/dHIDAtPmjdhZ23M46N968zpuVm03b9cVAsPmUIjz+lebcyiEQFMJTMvRn5TadXOm7dMMQADOgZxOMVuxoVECVaWomLZTh0KhKo4WLXSs3ryOGxWrrp5ACAdjQE5XsCET1iCA1utZ6xRtz+GVQlDfM222YB8KAa9puazGbV1x7KZUZTBrvkajBIxzcA5kdQrGHC1YrpkAWY1iUz4DxrhPN4iyG1mfXW3PU1+rtZelqGsRiGxw1UdJjaBSsXBhqoTHT45hfKbsPn25owiYJkkfuknR9oji8M5ifkmTnmxWxZYE9a9E/0zTxisTc6E27+4rpDa9yqHrKrY0KOoJDo69fh1Dd2xaMl6slC2maA+k659iLSJqP91ZzEfyPcqfNuO/45DaXIq1DlWleEtXDoxxvHptFnu/NOpy/fj+IXzhuz/Ed16ecH+p6PlzV3H/rs145qXX8aH77sCnz5xHbyGDT717Fw6fPu9e++SeAXzv1Wt47+4tePzUWff4kZEBdOgKPvuXL2NyropnP/JOVC2GA88utHvi0WH0d3W44gWlBL2d4V9TkB1bDKLaWS+glKCY1/HqtdnQevzEhqxbRjZHlBLcKJuh63b2FnBhci50fNfmzkjRTNZ+VHnRdldOx7Vb/uuiuBWsS9bmk3sG8MxLr+OJn9+FXZs7Y3lhWQyvXJvFQc8+cXz/EO7e3AlVpT4be2OqhGu3Kj5bkfWptzPj9uvo377q2lqwf5/5D2+LHCMAd1wyG603r2sRYk7/4uwVvGf3Fhyq+aaH7+nDxx+6y7fXizXsydf3Ca3wHZqmYEt3R+R5y2L48a0ybsybbr+DXBPlBB/fP9SPB962WZKXOl8sfEuX//Ulm+r0UXA5RYoUKRpBK/OzqLxR6HDeHC2pntwKpDljipVEVAyxWF4mvT6JjS+nPaZI0Y6Q5ZxHRgbwu99+FZNz1cjczLIYXp2Y8+WaR0YGsKmg48jfvIrJWQOf/eV7kNUoqhb35Qlr4T6lzL8VVSU0l0K7mpw18H/8yv+GWxXLl/uKnKkrF9Y7jowM4M/PXsUjw/144rlz7vGje3djY4eGj3w1WiOL0jxEvn7gZ3agO6/jw1/5l1Aevp61pxRLD1ff+7dZHPjaKO7bUcT+d23HF1+4ENKXjowM4Cc2ZmDNc1yfM0La7jMvvY5DP/tWmBbz2Yjgck+ehNoO6ga9CfwQpcTRX/LxZVplO+2uAa/Krys2i6my4QacADA+U8bjJ8dwo+x8kzNFinZHFIenysYK98zBSvRvYq4qbTO16fUJwcEH77ltSXnR7raYYmmRrn+KtYio/bQd+N4OfUiRYjkwVTJc0Q9wuH7w5Bj2DG11Px86dRYjw9vw6TPnsWdoqyu6HHzgTldkEWU/feY8Roa3uQ/QieOHT5/HdMnEwQfuxPhMGZem5kPtHnh2FFOl1MZWAjIeJFmPqOsm5qoN1dfK9pNyS3at4HiStifmqu5NDXH9QUnsP1UycGlqPmQrUW2IfnltLdi/uDF6xyWz0fVoZ2JORoa3uTeYAGDP0NbQXi9bw5XExFwVhufGGCDvp5eP7xvsT/WKFClSrClE5Y1Ch1upHC3NGVO0IxbLy5TXKVK0DrKc8/Dp864uEpWbyXJNJ6+rYM/QVhx84E5Ml0woVAnlCWs17o/Trg4+cCcmZo1Q7itypqh1OHD/DvfhIHH8iefO4epMJVYji9I8RL7+xHPncGW6vO7z8BQrg6mSgQNfc7h54P4dOHTqrFRfOnz6PFSqYHymItV29wxtxUzJDNlIyuWlxbr66oHFuEsugfGZMiy2tl5pm2Ltot05vBL9a/c5SbG8EHxgfGl5kfJufSNd/xRrEXG8Xmm+t0MfUqRYDhiWLeV6V07zfVYocY+L8t6/ZWWDxzt0BR1wvoXYoSvSMoZlt2xsKZIjigf11iPqOtNmDdXXyvaTciuO+0najhqjZbNQO43wXfQryr6EbcbVV89G15udiTkN+qao+Qmu4UrCtBkoka+3t59ePi51XpoiRYoUy42o3IzX/N1K+bc0Z0zRjlgsL1Nep0jROtTTW6Jys6hc06upAIjOE9agvSbVroLnLZu58ULwXJx2Va8dK2KNRI4pq2O95eEpVgZeW5FpuQLjM2XYnEfqVUm0pxStx7r6JTqVEvR3+3++sL87B5US5/3bKVK0OeI43A5Yif61+5ykWF4IPlCytLxIebe+ka5/irWIOF6vNN/boQ8pUiwHdFWRcv1G2fR9thl3j4vy3r9lZYPH5w3brXfesKVldHX1vnJkNSOKB/XWI+o6TaEN1dfK9pNyK477SdqOGqOq+CUvXVUa4rvoV5R93SibsfV5xxVVx3qzMzEnQd8UNT/BNVxJaAoF46jbTy8flzovTZEiRYrlRlRuRmr+bqX8W5ozpmhHLJaXKa9TpGgd6uktUblZVK4pNBWRE0bmCWvQXuPmMi5HVhUaeW2cdiVrJ1hvnJ4gq2O95eEpVgZevsu0XIH+7hwUQiJtp572lGJp0D5q1DKgmNPx9P4hl2TineRdOYq+Qvu+czdFCoEoDhdz+gr3zMFK9K+vkJG2mdr0+oTg4Asvv7mkvGh3W0yxtEjXP8VaRNR+2g58b4c+pEixHCjmdZx4dNjH9eP7h3Bm7Ir7+di+QZwevYwn9wzgzNgVPLlnwCn34kUcGRnwXfvkngGcHr2Mp/cN+o4fGRlAT17D8Rcvor87h+3FjlC7Jx4dRjGf2thKQMaDJOsRdV1fIdNQfa1sPym3ZNcKjidpu6+QwfHAPnFcEvsX8zq2FztCthLVhuiX19aC/Ysbo3dcMhtdj3Ym5uT06GUc8/imM2NXQnu9bA1XEn2FDHSV+Pot66eXj988O57qFSlSpFhTiMobhQ63UjlamjOmaEcslpcpr1OkaB1kOeeRkQFXF4nKzWS5ppPXZXFm7AqOv3gRPXkNNrNDecJajfvjtKvjL15EX6ceyn1FzhS1Die+9xqO7t3tO350725s6c7GamRRmofI14/u3Y2tPbl1n4enWBkU8zpOfNDh5onvvYZj+wal+tKRkQFYzEZ/d1aq7Z4Zu4LuvBaykZTLSwvC+fL/lCghpAfAnwK4HcAbAPZyzmcCZe4F8DSADQBsAP8n5/xP69U9PDzMR0dHI89XKhamygYsxqFSgq6c8xzh9ZINlRJ06BQgwMZsBnQNPiGeYlFYNkLE8TjI4WJORzbb2JuZk9bRTFut6F+jdZmmjYm5KizGkdcVGDaHaTNoivOArKo2/7ywt26VEvQVMtC01j/ZbVkME3PVhvrNGMdUyYBh2dBVBcW8Xs9vtQWHZQiOvzevY6ZsomzaUCiBRgl6OnRomuLyQlMITJu7a5NRKQqaww8LFm6WmXtuY47CsIHZiuPre/M6dH2BS0GubcxR3CwzFHN6JAcXw3XZtZQCk6WFY8E+LhVaabPLgLbh8CqbtxRLiAa50DYcDsK732VV55dWLMagUIqerOYbY2eOwraBeYMl8lleH69S4vrvjTkKDmdSgj6bAFCgJvK59fbQRtZoPdp2E2NeFh43yuGVguAfwME5wAFkanEZAEyVDDDGYHOAcw6t9mtFlVqMk1EpTMZhWAwKJcipFFWLwfTkq3NVDg7nW4sW425sZNdyeV2hKJs2NmQVzFUXbCmnUzf26aj9TWt/lz32m89QlDzXdegUJYPBZhy6QtEt8QGzNZvNaQq4Zzw5jcJmzitPdFVBd07DraqJsmHD5hxZVYGqEJSN6PhVxLhVywYBQAgAkJBtNxELC7Qlh73jyekKLMZhWsz3t3ecsvEDfs4xzkEJgaoApsXBOJDRKDblM76yjNdeVVnjlkIJqpbDAUoJsiqFaXNQAthifyAEhACMAxp1/raY8xobzjk4CBjn0FUKq5afKbW3AFBCoKnAfJW5vACAsmkjq1LYHCBw+mtzDo1S6BpBxWAghECp9UNXCAybu5+t2hhEf0WblAIKoVAVAtNiUBUCq5ZHCJvSFYqeDh2qSsEYx/VSFRXThkoIMhpF1XLqE/0Te5pKCQzbmQ+tZr+MceQzCiqm3x6F3WkKhUqAisWgKhSZ2tjazQ8DyXlsWQw3KwbAAUUBSlWGDTmK+Zr/InD8o8U4bMahUYKMTlExGBjnUAgBpQSUIJTjzZs2MgqFzTlMe8EHZjQKw+KoWDYU4p9jcW1WI7hZtpHVKAiB73whq8BmHGXD4aHgtPO/s64swE+9tl5lgyGrUd8ab8wp6NAd+xR7g2UzdGYVX8wkNIUorSFo2905DTNlsxlft2xYC9rE7Z95fhl6A7zxufcsSzsplhxtw+F69mcYFiZLhqtzxe01oq4OjeOGp2xXjuJ6yUYxr4TytpvlBX/YmaOYqd1jqbeXBX3gpg4dU2XTzem8OWh3XnFjT5USdGYpZiss1MZ6zOUWgbbhsAxLvZaVioV52/LFBYLHXTnq438zbQu7sxjHprwSqk/XlVi79WkclEJXCUqG7drjvEli99q4+fP2TWg5jKHufCdZkxWwwbbI6+L8cDP3fFoNb27jxMwKunKtiSfjctK4uLDR2NFbXuSDlNJEdXtjaU2l0BWCeYPBtBkytdzP5hwqpaC1HE1TKDLqQs5IKcCYo8koNV0TILAZ9+XROZ1gttJ+eV0SDt8oG65uk88ooMTJ161a7qZQJ78HavlvbcwAYNjMyfFreq87X5xDreV5jDuamTgntAqh96gUKJvMzZ3nPZqUphBUanm2qjjrVK2tU7aWm4k511VHU65aC30ntTYpARTq2J9p+7UFL6cASLWZxeRiMg5rKoXFODjjrmYY1NHEGLIttNsWoy043GrI/Mh02UDVtGt6FoFlA4RwKITCsJmrc3TmFMxXHV2X1fQfwVPToz/ZNV3NqulLQiNmjDtaUe2zYTPwmjYW1OG6sho0TVmw35odEArotb2mUrOlrKbAshf0ZmGv3msU6tcLvX6zajrX2oxDUwgU4uiGCiXIZxRsyNbnZ9Se4fU/WU3BpnzGp3t6dXWZHXrrzagUhkdXX4wfXqks4jMAvss5/xwh5DO1z58OlJkH8Cjn/AIh5C0Axgghf8M5v9Fso5WKhQtTJTx+cgzjM2X3SfAdxQw25RX8wudfwtP7h7CpoGGuMo8tXR3t6JBSrGNEcXhnMd/QwztJ6mi2rWxWxZYWJEeNtK9pCrZ0d8CyGF65NouDnmuO7x/C3Zs7m0pOTNPGKxNzoT7c3Vdo6YN0zfSbMY5Xr83iwLOj7jUnHh3Grs2dq85vBcf/8D19+M2fuwu/8bWF+TgyMoBbnRa2bsjhwlQJ3/rBON6zewsOnTrrljm2bxAbOzRs7sjg9alqaN3yGvDg//0P7uddvXnouhq7N8RxsFmuy9r7s0PvwrVbRqgt0celQit8ynpEOm8pBNYKF7z7XW8hg0+9excOnz4f2pMsi+HCVAlnL93C7b0bEvks2R53bN8gnj93Fe+9tx87ihm8JvHZ24sZABYqFUdgkc3zrt48KKWxe2gja7RW1rMRrMcxtxKC31/47g/xofvuwKfPnPfFZRmV4nP//V9D546MDOB3v/0qejt1fPyhu9z5f/iePnzswZ1ufPPwPX04/O67MV+1YFgMTzx3zldHTldw7O9+hE88dBe2dmdweSZsSy/+6zX86ZjzS0iFDMWply6HYqin9w/hD777Q3zn5Qn387d+MI4v/f0brk39leezKD85a/j8RbD/4lqbMXz0698PjX9yrhqKX2Ux7pN7BvDMS6/jEw/d5dr2WoqFgejYfmdvARcm5xIf37W5E8W8HjmHj/3UHdi8IYuenI4Lk3M4+rev4td+egc++Q0/tzZkVZiM42Nf/767L3zlH18Pcdlbb7Gg48zoFbx39xZUTBtPPHcOvYUMfvsX7w5xd0NWhaZSfOSro77jf372Kv7j4BZpW17eiHY/9uBOPH/uKu7ftdlX9ul9g/iDFy64nPb288/PXsW+f79NalO3OjPY3t2BH10vufP38D19+PiDO/H4qbPSPdJrz4L/9+0oYv+7tsfa2dG9u/E7f/0K3nl7F957b/+q9sOWxfDjW2VwzpHVKH48Y0IlDPOmivmqBZUSWIxj3rB9/sLr//q7c/jS/kEwEN+xY/sG8T9fmcC/v7MYWq9iQcfv/c2r+M7LE9L6vn7gJ/HmLQtjr1/Hw//7bZiaM0PzXCxoeP+X/9k99sUPvB0aJbhVsXzrLNZrcq6KIyMDyOsUhCqh+vq7OTZmnZujb+laeNVKd94/Z1Faw67ePC5Ozfvs9/j+IXzBw51283VrzR+nSLGaUM/+DMPCq5Ml5DXg9XnE7jWirr4NGl6bCutTUXlbXgOm54FtPRn84udfSrSXBX3gb/zM7dK98Fs/GMfP3t2HWxU9dM40TUzPm742WqVJp1hZLHWOWqlYmK4a0rhg7PXrGLpjE96YvIWP/8n5ptoWdhes+1+v3sAX/u4ivvLYO2BaDL/u0b29dht1n2BjTvXFLFF7bdz8UYpQ3/76N+/DJYlte8ecZE3Wq7YQ54cZ4y29V9Wq/h0ZGcDmDVncXswvKlaLGntGpXj0j/+fSK42GjvGaQRP/Pyu2LofvqcPn3jortAafEGiZwRzu9/6hV24OW/ixN+/FspNv/iBt8NmHL/5Jz/wXbupM4Mj337Fp620uw0wxvHGVAnXblVw+PR59BYy+Nyef4eqxX357B9+4O3gAD4W0HY6dAWf/cuX3Xz4iy9cCM3X0b27oakUx/7uR7Gagsj3vbmzNx+vp6kJLaAzp2L/f13g4FOP7MYf/cNr+PiDO12tItj+h+67A8+89Do+8x/ehqrFcODZUWn+30yeI+PwFz/wdpgWk/JLpqMd3bsbxUJm0Xaboj6S+BH33sbuLZir+rWDrzz2DtwoGS7PPvveuzF8xybf9UdGBrAhp8Gyw3rphqyK//IX/x8m56r44w8P41bZwn/+0x9IbWZTZwYbcyouTpR8fXh63yAogatryLh8bN8gvujRzYSdeG1AjP+3fmEXpuaMSI3k2L5BdHdYsc9Vyezg2Y+8EwBc/yPTPY/+7atSzV3Yobde2TgX44dX6nWu7wPwTO3vZwD8SrAA5/yHnPMLtb9/DGACQO9iGp0qLySAADA+U8bjJ8dwo8xwo8zcz5YNVC3nqcUUKdoJURyeKifnatI6WtHWYtBM+xNzVXcjEtccPDlW+3WQxjExV5X2odn64tpptN9TJcPdbMQ1B54dXZV+Kzj+PUNb3QfoAGdsh0+fx/h02eXFyPA2N4gXZQ6dOgvT4pHcyWia7/Nkba7i9oalsAFZe4bFpW1NLvF6rrSdr1ak85ZCYK1wwbvfHXzgTjfRAPx7khjv27cXE/ss2R536NRZjAxvi/W1s7X4fKpsYLIkn+fJklF3D21kjdbKejaC9TjmVkLwb8/QVjeZBxbisktT89Jzh0+fx8EH7sSeoa2++d8ztNUX3+wZ2orx6TKmS6YrvnjrmCmZ2DO0FQdPjmGuKrel9w32u3+rVJHGUI/XxuD9PDK8zf18MPBZlA/6i2D/xbXTJVM6fln8KotxP33mvDtO17bXUCwMRI9nYq7a0PGpkhE7h4dPn8elqXn3+j1DW90H6ETZw6fPY2LWwExt3cQ6y7jsrffqTAUjw9twfW5BLDz4wJ1S7k7MGrg6UwkdP3D/jsi2vLwR7Yr9JFj28VNnfZz29vPA/TsiberKdDk0t3uGtrqCvWyP9Nqz4P+B+3fUtbMnnjuHgw/c6e6Hq9kPT8xVYVgcpg2YtvOQxoZcxvVfE7MGpktmyF8Exz0xG96TDp06i/cN9kvX6+pMxZ1TWX0ix3rwnttg25DOs23Dd2ym1t/gOov1Em0XC1lpffNVlsgPRWkNkxL7PRjgTrv5urXmj1OkWE2oZ38ij8poWt29RtRVMeT6VFTeJuqeq7DEe1nQB0bthSPD27C1Jy89t3ljx6rbL1Mkw1LnqFNlIzIuePCe21zNo9m2o/SL+3b2YnymjPHpsvsAnTjvtdsojaNq8UR7bdz8yfo2m0D/TrIm61VbiPPDrb5X1ar+iZxwsbFa1NgvTc3HcrXR2DEuv61Xt9ARZLF1vdzu6kwFTzx3TpqbzpRM9wE677Xj0+WQttLuNjBVMnBpat6di4MP3AmFKqF8drpkug/QiWOHT5/HdMn05cOy+XriuXOufhWnKYh8y5s7e/Nxb7syTU1oAVYgx/vkN5x19GoVwfbF/5c8X2iScaSZPEfG4ZmaJiGbE5mO9sRz51pitynqI4kfEVrU9bmwdjA+Xfbx7MF7bgtdf/j0eUzcqkr10olZw7WFqzMV9wE6UcZrM+PTju4R7MP1OcOna8i4fCigmwk78dqAGP/VmUqsRnLo1Nm6z1XJ7ODS1LzP/4jjXt0zSnMXbXnrlY1zMX54pR5/3sw5fxMAOOdvEkL64goTQt4JQAdwMeL8rwP4dQDYtm1bZD0WWwg0BcZnyrAY9312fkYUMCw72WhSpGgBkvA4CYfrIWkdrWhrMWimfdNm8mtstmx9aAbN9NuwbOk1K+m3kvriIILj78pp0rF11H46eXymDIUSaRlKkvt68Tmu/FKsv6xee4XsbaXtvN3QyngixfpAu3GhWT/sHUeUD7ZsBl77uxGfFbXHCT+edA6jy0RcX9tDG1mjdlvP5UC7jblZDq8UBL/jYpcOKNJzXbmFh/sFgvWIMsFysvqj1pLXXvkq8tyoGCrYluL55qDsc5L+e/sZN35v/BoV44q6hW23YywMNM/hqPFE+dCo42L8cXPYoSuJuCsgykSV9darUIIOfYHzSTkhjgt+xrUVbDcpp73lvX0M9itoS96+JOkXgIb6FFV2JfeeRnls2gzCRYgYwWJcavsCsrmMWhfO5f5N+MCo+ihZ8H3B9sVncc7bh6iy3nWO3T8T+KFGc9Agd1ba13nRjv54tcUTKVIEkZTD9ezP8vjkenuNqKsZjSwqf4s7BREhAAAgAElEQVTay4J1Re2FSu2XTBtpN0V7YDF+eKlzVItxV9sItiFiDjtCQ05av6xuUWdUvCPsNirOD/6wS9ReW2/+gueSzHeryqwmtMIPR85Jk/eqmkFU/zp0ZdGxWlzdwWNJcv6o/tTTCOLqTpq/yc4F2/EiLp8U+Yk41u76mmHZoRxe5FFeJBlzPY0hTh+T5fuiP42uocxf1ltzWZmothu1HRmHxXw2oqO1wm5XE1Yqp0vqR6K0peAxFqNnBBG0qSi78+pwsvs0QV2jnh0FPwfHHzwmK1/vuaooO4iqu55uKdry1ht5X6tJP7xkv0RHCPkfhJD/V/LvfQ3WcxuArwF4jHMujS4451/mnA9zzod7e6N/rE6lBP3dOd+x/u4cVEqg1rxqf3cOlBAwDuhq617XmCJFPSThcRyHkyJpHa1oazFopn1NofJrlOZc3XLNQTP91lVFes1K+q2kvjiI4PhvlE3p2OYN210Tm3FpGcaTrZv3c1z5pVh/Wb3KCtnbStt5u6EV8USK9YV240Kzftg7jigfrCrULdeIz4ra44Qfrxefi39RZertoY2sUbut53Kg3cbcLIdXCoJ/cbFL1LkbZTN0TvZ53rAxb9h1649aS0L8eW5UDHWjbPo+e28cyT4n6b+3n1HtBePXqBjXHWfNttsxFgaa53DUeKJ8XNRxXVXqzuG8YSfirlg3USaOy+Iau/bKznp7ird+73HBz7i2gu0m5bS3fJxNBW3J25ek9txIn6LKruTe0yiPNYWCcYDxhbxGpcRdZ5kfk81l1LoQIvdvwgdG1cf4gu9TIuqgxD/PcT7Xy7+4/TOJH2o0Bw1yZ6V9nRft6I9XWzyRYmlw+2eeb/hfuyAph+vZn+rxyfX2GlFXMxqZbN+K28uCdUXthTbjDbeboj2wGD+81DmqSqPjAhFzeL9A1GjbUf0XdUbFGcJuo+L84P3fqL22nsYSPJdkvltVZjWhFX641feqmkFU/+YNe9GxWlzdwWNJcv6o/tTLb+PqbkSPCZ4TttpI3uLNT8SxdtfXdFUJ5fAij/Ki3pjr6Qb19DFZvi/60+gayvyld03j2k+iZzRqOzIOx/Eryo5aYberCSuV0yX1I1HaUvAYjdEzotZZ8L8eZ+cNW3qfJqhr1NPYvJ9l2k0SjaTec1VRdhBVdz3dUrTlrTfyvlaTfnjJdmvO+c9xzv+d5N83AVyrPRwnHpKbkNVBCNkA4HkA/4Vz/s+L7VMxp+Pp/UPuBPZ3O+/C7cpRdOWo+1lVgIxKUMzri20yRYqWIorDxVxyriatoxVtLQbNtN9XyOB44Jrj+4fQV8g01Ye+Qkbah2bri2un0X4X8zpOPDrsu+bEo8Or0m8Fx39m7Aq+9EH/fBwZGUB/T87lxenRyzi2b9BX5ti+QWgqieRO1TR9n3trcxW3NyyFDcja01Uibat3iddzpe18tSKdtxQCa4UL3v3u+IsXHZ8r2ZPEeL9/aSqxz5Ltccf2DeL06OVYX9tZi8+LOR29efk89+b1untoI2u0VtazEazHMbcSgn9nxq7gyT1+uznx6DC2Fzuk546MDOD4ixdxZuyKb/7PjF3xxTdnxq6gvyeHnryGo3t3h+rozms4M3YFx/cPoZCR29I3z467f1vMlsZQT9fG4P18evSy+/l44LMoH/QXwf6La3vymnT8svhVFuM+uWfAHadr22soFgaix9NXyDR0vJjXY+fwyMgAthc73OvPjF3BU4+EudXXqaO7tm5inWVc9ta7pTuL06OXsamgu3w9/uJFKXf7OnVs6c6Gjp/43muRbXl5I9oV+0mw7NP7Bn2c9vbzxPdei7SprT250NyeGbuCp2u8lu2RXnsW/D/xvdfq2tnRvbtx/MWL7n64mv1wXyEDXSXQFEBTgKf3D+FWuer6r75OHT15LeQvguPu6wzvScf2DeKbZ8el67WlO+vOqaw+kWO98PKbUGr9Cs6zosB3rLvW3+A6i/USbU/NVaT1dWRoIj8UpTX0Suz3eIA77ebr1po/TpFiNaGe/Yk8qmqadfcaUVdWl+tTUXmbqLuQpbH1exH0gVF74enRy7gyXZKeu3ZzftXtlymSYalz1GJOj4wLXnj5TVfzaLbtKP3ipQuT6O/Oob8nhy8HdG+v3UZpHBmVJNpr4+ZP1rfOBPp3kjVZr9pCnB9u9b2qVvVP5ISLjdWixr692BHL1UZjx7j8tl7dQkeQxdb1crst3Vkc3btbmpt25zV8/lfvDV3b35MLaSvtbgPFvI7txQ53Lo6/eBE2s0P5bE9ewxc/8PbQmHvymi8fls3X0b27Xf0qTlMQ+ZY3d/bm4952ZZqa0ALUQI731CPOOnq1imD74v/txQ6XQzKONJPnyDjcXdMkZHMi09GO7t3dErtNUR9J/IjQojYVwtpBf0/Ox7MXXn4zdP2RkQH0bchI9dK+Tt21hS3dWfz++++NtJn+Hkf3CPZhU0H36RoyLh8L6GbCTrw2IMa/pTsbq5Ec2zdY97kqmR1sL3b4/I847tU9ozR30Za3Xtk4F+OHCefL/1OihJAjAKY4558jhHwGQA/n/FOBMjqA/w7grzjnv5+07uHhYT46Ohp5vlKxMFU2YNW+ydSVc54jvF5yvnFcyFAwABuzGdBV+i2JFEuGZSNEHI+DHC7mdGSzjb2ZOWkdMnvRqFNusuS/3luur5CBpiV/Ir5atXB9fuH6TR06Mhm1qbFaFsPEXBWWzaAqFH2FDFSV+s6ZNoMWOBcF07Sd+hoYW1y/GXPeC25YzrcGinkdlJKm+h1VVwzagsNAeB66siomSwZU6jyZX7WYO3+Z2jwQ4rySZ95wzuV1BVWLgRCAc8DmHBlFQUYDVArcLC/UsTFHUbWAislQyFDMVZmPb5wjxPUbZeb+L1tLmX2IvUTYiq7L+SrjCKVA2bYwV/H3jVLSMAcbQaN21goftAi0DYdXeB5StBEa5ELbcNgLy2KYrRquf+3qUHy+SPhQy+YwGXd/EUClBFmNYK7KsCFHccvjL3M6RaeuQdMUZx+brcJkrPbrcQSmzbExR8HhTErQZxMAClRMlY2QLw762Lg9FJCvEQDpuq1H225izMvC40Y4vJKwLIbpeQOm7XBUoQQaJdBUig0ZDTNlE4wx2BxQCKAqBBVzgc8dGYqKwWHaDLpKwTlg2MytR1cJyoYT7zDu/FKHUouPTJuBcydGAiHIaQQlT4yTVSlszmHaHJQCnAEm48jU4kjR30KW+my+kKGYrTIwxqGpFBolKNV+oUulBIbNQAkBJYBCHTuumjYoJchpFDZDbTwKunMablVNZ8w2A3Xnh6BicnDOQ3GsN04EnPiPg4Rsu4lYWKAtOcwYx/W5Kiq1udRqY8lo1PHPAR8XHP/GjIIbFau2PrX42OOvy5bjgxVKoKsUls1RsWzkdQUVcyGmdl77S6EqgGk5PMmqzi+NqQqB4YnTNYXAsDk0SkAIYDOH5xbnbl0ZTYFtOxyntb4I/lQt5vRRoVAIULGY2xbAHc5zDpU411UsxzZojfO6SlAxFvoOAJpKkVEJ5ir2Qj9VAsty+GzU2tQ9diC4CwBl0zmvKRSEcDAGZDXqy0Oc/Y+iYjJkVIqKtXCNpji5DOMcCiFu33I6Rbl2vaZQqLXxqgpFTieYr8pzjgi0XTxhWQw3KwbAAUUBSrXYYL7K3b2ew3nVFxN5nk5hWdw9bjOOnKbAshlM5vBKVShsxsA4fFz0+slchsC2/euT0x2Oi9wyq1EQAncNVEqwIUdh2v5jWc25jhDH1zGXCw5fNUqQr/nInE5RMfzxyY0yc+Oc3rwemQ8C0VqDN//XFQpddXywQghyuoKuXGJfl2jdRFti/Buzel2dJIjVrE0ILNevkL3xufcsSzspmlvTBtanbThcz/4Mw8JkycDGHPXlXEKHmjOtkB+smAyFLMWN+QWNa6bMwLnjV8XeJvK2YK52o8zcvSzoZzIqhWEzEBCfL+/Kapgqm26805PV3BylO69gNpAvirEInZRz7vOpYhzrIZ9rEm3DYRlanZcH7aRTUzBvy7kfpwUHEbynUchQlAzu469aix1ulhfsqWzC1b5l9yhk41dV6rs/UMxpmDUsn4YuYpCgru0dU2dW8Y07Th9pdE2i7r0mnc8m7t20RV4X54fr6VXLAcY4rpeqqJgMCkFL40nv2AkhUIiTj1mMw7QYNNV5q0XZSH4vTNbGjbKBsmG7v3ytEMDmgF7LR726AgDfenTnHF3G+3l63kDFtKGrTv7m1Wg0xXmVuK5Q95iwM6GxWLajpQidRqcEDAv5glqzxXbJ65JwWMyxzYHOLAU4YARytbyuwLC5q+10eHLcoD4AOHoAJcTVkjVKoKoEpsXdc6SWKIp8X6vlP25eTgnyAc0qp1PMVWyoCkWH7tfBgvpWRnVyuUqtvmztvpphixyeQCXE0SoUAptzN8fTFIqcRtw8U/glSolnvpw6u7MaJktGpP+S2YqqEhgmh9A+ALgcnTNMlKq2Zx9RsCHbmN0uQjNrBG3B4VbDO3ea6vBgtmwv6L41Gxe6qGEz6LVjYs0c3Y25b7/0xr0qJajaDBnF0ZOCekTVcrQmYXsZj74r6lAoQUFToesKbpQNmJajozDRR5W4OjCrcd9ijv16x+C1RU2hPs0vozrPTOkKQdVcqF9oeIzz2lsJHO1vUz7+2SoZJwH4/E9Wo249orzQ1aM0ZO/1HZozBrMF+tpKZRCfA/AcIeTXAFwG8AgAEEKGARzknP8nAHsB3A+gSAj5cO26D3POf9Bso5WKhQtTJTx+cgzjM2X3CcTbixlwzvD+L/8LTnxwGLt+ojN9gC5FWyKKwzuL+cSJpGna0jru7iuEHsyhFJieN31l/+zQu3DtluEe++x778bQHZsS1SdDtWrhh9fD/blrkzOmLQ0myKpK8ZauXOi4ZTG8cm0WBz3tHN8/hLs3d8YmLpqmYEt3R+L249ZI1xW8em0WB54ddc+deHQYu2p9aKbfvZ3L982lVoExLp2Ht27K483ZCm7Mmzh06uzC/O0bhK4SnLt8A2/b0uWb26889g4YFsNvfM0/33/w3R/iOy9PeL6hakLTNMzMldFdyEn5JtY5iZ1Flbltg45fOfZPeHr/EHYUARiQ3jiRcbtatXB5uhqq8y1dGbz/y//clH0lQSN21goftBaQzkMKgbXABe8+8/6hfnzkp7fhtSm5L3rtegmHT593jx/duxtdeR2cMUzPI3RNscDQ25GBbXNMzRvh87mFeSpk/f0Sc/uWLl3an53FhfmN2kMFgn6u3ro1GnusdqzHMbcSlBJMlQxfXPPkngE889LreOLnd2HX5k438b96Yx7XZgNxzv4h9ORVzMwbMCyGJ5475577/K/ei86sit/7m1fxofvuwKfPnPddxxjDR7/+fV95XaF4vFb/w/f04WMP7sQXX7iAX/vpHfjkNxbqPjIygGJBR1ZT8Mb1sq8eEWtSSkIx25GRAfzut1/F5FzVjWPr5c4boOHHNxbi2Yfv6cPHH7rLZ4PeuigliWLcpOVWCxjjmJit+uL+L37g7TADvPDOlRi/adq4NDOPydkqvvKPr4f44l23px7ZjaxG8dGvfx+9hQw+9e5d0muO7RvEF1+44MbUf/zhYRgW9/XP5frP7cJbe/N4dWLOd/7IyAB6OzMoVS1fe4dPn49tW9T7W7+wC7fKFr78vYtSG9AV4Nee8fNoZ28BFybnfLw9tm8Qz5+7igff9hMhO9i8IYttG3O4PDOPa7cqvn3u+P4hFAsablVMzFVZaN+YmSujK5/12XRw3sRYPnTfHXjmpdfxsQd34n++MoH7d/Xho18/i/t2FLH/XdtDfmFXbz72Aax2A6UEE7NyX/jYT92BYkHHmdEreODuzcjpCo793Y/w0Z99KyghmKtaPk541+APP/B2VEyGT37jHHoLGfz2L97ts4eje3dj+6YOn0Yh5rCQofi//voVHPiZHejdkIFlc0zOVnH49Hm8f6gfvzy4BTcDueexfYM4+U+X8NJrU/jjDw+jbDB89Otnfe115XU89pV/CY3z4w/dhbHXr2Pw9iKeP3cV7723P3YdZVoDYzzE36Df7WrRr1nItIZj+wZR6rDxlg25hm7wrjV/nCLFakI9+9N1FZsplWqLt3Vl8OMb4Vxr7PXrGLpjE+4oZvDmLROXp+d9vln4pf/64UH8+EbY/4q8SuZnnq69ReI/Bfbv3s4s3pLx+0tvjrKhli9G6aSdORX7Tvwv6ThWU36ewkErc9SgDv0bP3M73ntvv4+3Iv8pFpy9L5+tUymi72nMzJXRU8j57jkYhoUrlSrGXr+On7qrD9dr8YhrA557ktVqWK/4ymPvgGkx/LpH/z514Cdxa950cz9vzPvee/tdLWVHMeNqKu8f6scDb9sstdl69z+SrEk2q6IIuP1//hP3SbVumU02e++mHRDnh+vpVcsBSgn6OhOQusm6i3ldeq9HlpfFHZdpC7L7SM9+5J2oWgxH/zask4h6gusR/NxX21Sk+9T+IXzrB+P40t+/4fMXslxF5AFCd3HvR+0bxLfOXcUv3duPt66CPYhSgp58Bsg7c/7GVAmzlYXXSYpczZuLyXyp8EEP3L0ZPXkNhsXdXM9r11/w3Lvz5jpHRgawqTODI3/5inv+Dz/wdkzP01AsoasEOaLiyozl9iGqTxtyKn7n+X/Fd16ecHUybw54dO9udGZVdGRUXJ0pu/19+J4+fPzBnT4/e+KDwyhkFYwHywU0rqD/CvqJqHukuzY7/uLNm9XQuQ3Z5HlgdP3p8y9JINaLMY5rs2VcmjJxsOYHPvvL97h2Ieb2q48NY6bEfFz5yoeHQQjBTMnwaRhHRgbQoSs49c+X8R8Ht4Ri7O68BsaBqzdMqe1568hnVGzryqErF/bDQW3q2L5BdHdo6O/u8D2AJq6TaVNx+3AzHIvaL4X/SVo+qg9JbLERrEj0wTmf4pw/xDnfWft/unZ8tPYAHTjnJznnGuf8Xs+/ph+gA5xvU4iJA4DxmTIePzmGW2UGTXGc3oGvjWKqZCx6jClSLAWiODxVTs7ZibmqtI6JuWqo7GQp3J5hcd+xB++5LXF9Mlyfl4/p+nxr7XBibuGGlGjnYAP9TIq4NfLeYBXnDjwb73OWq9/Liah5mJirwrC4u0mLc4+fOguFKrhvZ29obseny+4DdG75k2PYM7TV93nzxg48fnIMd/ZtqMu3JHYWVaZqcffvG2WGyQb2kyhbqBisaftqNVrhg9YC0nlIIbAWuODdZ9432I8bZRbpi0RSJ44/8dw5jE+Xkc9o0mts26m/mXkS11QM3vI5XgvrlqJ9IItrPn3mPPYMbfXFeVMlA1VZnHNyDIwRTJdMVxAR537zT36AqzMV7Bna6grD3uumS2ao/PU5wz22Z2grDp06iz1DW90Hh0TZw6fP4+pMBYbFQ/WIWFM2tsOnz+PgA3cmimMFgvHsnqGtIRtMWtdahizun5HwQjZXE3NVXJl21kfGF++6ffIb59w1P/jAnZHXCO6Iz1dnKqH+uVz/2qi0/4dPn8eV6XKovXpti3qvzlTwn//0B5E2oFBFmlMEeXvo1FmMDG+T2sGlqXlMzFVxaWo+tM8dPDkGywZUqkj3jTv7NoRsOjhvYizi/0OnzuJ9g/3ug1kH7t8h9QuN5BHtgDhfKPzNyPA2HD59HjMlE3uGtmK6ZOL6nBHihLeO6ZLprtvBB+4M2cMTz50LaRRiDlWqYM/QVjzx3DlYNlwbETGPKfHJh06dxYH7d7icF+vkbW98uiwd5+Mnx/DgPbe5fGtmHVvld5NAZrOHTp2FYfFVrTekSJEijChtsWLIcz+h9d4sM4x7fKcoI/xSvVxN1u7jp85ClezfSX1b1FjMmh4nG0ea561vBPdWsUfL8p9GEKXj3tm3IVSfuMfy4D23SW3Ke09SVu/4dNl9gE4cMy3u3qwXx7wxiLBPr8bzvsH+JddCvHrLXEXuY2TtrcV7IOsFcfd6Gjku2wdkdV+amseBZ0elOWKjsbJ0nzo5hpHhbQD8/kKWq3hzPN/9qJotHlyFe9BUycClqXlMl0xMl0xfrubNxWS+VPigw6fPQ6GKL9cTZQ4G7t15c53Dp89jfLrsOz9dMqWxhEIVEBBfH6L6ZNlw6xTrFczx3rzp3Jv09nfP0NaQnz3wtVFUZeUa9F9x94qbuY/cSP0pkmOqZMCy4XLw4AN3+uwCQO1/GuLK+EwFV6bLIQ3j8OnzmC6ZOHD/DmmMrVIF125WI23PW8eV6TImIzgT9EuHTp1F1eI+Dnivk2lTcTxuB44F+9CMLcahvR9/bjEstpBMCYzPlGGJ38mEeEjIXu6upUiRCEk43Mo6ZGXtwDHGF9enVowpCUybyduxWUvbiR2PZUvPxfmc5er3csKImAeLOT9/KztHSZh7ANChK9LyXTktVLf3f1nbAq0o0wyHk9rCUthHUiyXvbY70nlIIbAWuODdZ1jt9XtRY5Id79CVyHPiJ73FZ1mdUWjEbzeKtbBuKdoHUXFNV07zxXmGZUfGOYzzyJimQ1fQgehzccdEH8T/srKUQFqPZTuv7IqLs5LmzsF4Nqo/6z0Pl8X9UbwIzpXFFjgUNb/edRNrXo8j3pg6Lu6ut08IeNtJ2nZcmeCXW8dnypH5k0JJZP9Mm0WOj3HnFTaN7I3BXCQ4Vq9tRfVrte1J9Xxhh664YxV+zVsOkPsG77pE8UCWJ4q1E9cIX+eNeaJ8slIjVpxfjhqnWFsx1kbXMW4exd+t8pVRtkIJVrXekCJFijAitcUI/yl8mTe+CJbpyml186o4PxM8ltS3NVKndxwp1i+Ce2tk7NXg3hfH/2B94lhc3idsQFav7Jq4OMbXD099i72PkwTe9hrRXtbiPZD1gqj4NWpNo47L9gFZ3fXy3kZi5bjcEfD7i7i8VZYDNpsPrDQMy/blO1Hjj/Kl4ngw//KWkeXL4u9grhhVByWAHfBpUX2iBG4b9fQx77k4HSJJuTj/FWU3gr+L5Xa9+lMkg2HZPp55ueqFbE8WdhTFtzi+JtFBRP1xzx4EbY0S+Djg5Umj8VE7cCzYh2ZsMQ7t/Tu4LYZKCfq7/T+d29+dg1p7/7D4rKuteUVeihStRhyHl6IOWVklcIySxfWpFWNKAk2h8naU1rrBuPHoqiI9F+dzlqvfy4moeVCp82542TnGw9wDnJ+TlpW/UTZDdXv/l7Ut0Ioywb0lCZLawlLYR1Isl722O9J5SCGwFrjg3WcoIbFjkh2fN+zIc6K+ZuapEb/dKNbCuqVoH0TFNTfKpi/O01UlMs6hhETGNPOG7dYlOxd3TFwXdz3jkNajKjR2bOLvJLlzMJ6N6s96z8NlcX8UL4JzpdIFDkXNr3fdxJrX44g3po6Lu+vtE8H2krZdb0zB+xH93bnI/MlmPLJ/mkIjx0cJgRKT8ybJRYJjJZ76ovq12vaker5w3rDdsQq/JrgR5IQX9c73d+ekeaJYO3GN8HXemCfKJ9s1YsX55ahxirUVY210HVvld5MgylYYx6rWG1KkSBFGpLYY4T+FL/PGF8EyN8pm3bwqzs8EjyX1bY3U6R1HivWL4N4aGXs1uPfV00689YljcXmfsAFZvbJr4uIYXz889S32Pk4SeNtrRHtZi/dA1gui4teoNY06LtsHZHXXyxEbiZXjckfA7y/i8lZZDthsPrDS0FXFzdPicrEoXyqOB/MvbxlZviz+FrmiQFQdjCOUp0f1iXG4ddbTx7zn4nSIJOXi/FfcveJm7iM3Un+K5NBVxcczr07lhWxPDtqQQFAfCZ4L2k4cZ8V9mXo6grduLwe81zUaH7UDx4J9aMYW47CuIpBiTsfT+4fcCezvdt5vviFHYdoOIU98cBjFfPL3SqdIsZyI4nAxl5yzfYWMtI6+Qvi90r35cHu6SnzHXnj5zcT1ybCpQz6mTR2ttcO+QgbHA+0cb6CfSRG3RsW8jhOPDvvOnXg03ucsV7+XE1Hz0FfIQFcJju0b9M/fvkHYzMZLFyZDc9vfk8OXPhie7zNjV3yfr92cx9P7h3Bx4lZdviWxs6gyGZW4f3flKHob2E+ibCGr06btq9VohQ9aC0jnIYXAWuCCd5/55tlxdOVopC86MjLgO35072709+RQqprSaxTFqb+ZeRLXZHXS8jleC+uWon0gi2ue3DOAM2NXfHFeMa8jI4tz9g+BUo6evObYlOfc53/1XmzpzuLM2BU8uWcgdF1PXguV31TQ3WNnxq7g2L5BnBm7gqce8dd9ZGQAW7qz0FUSqkfEmrKxHRkZwPEXLyaKYwWC8eyZsSshG0xa11qGLO7vlvBCNld9hQy29jjrI+OLd92eemS3u+bHX7wYeY3gjvi8pTsb6p/L9Q8OS/t/ZGQAW3tyofbqtS3q3dKdxe+//95IG7CZHZqbvkImxNtj+wZxevSy1A62FzvQV8hge7EjtM8d3z8EVQEsZkv3jYsTt0I2HZw3MRbx/7F9g/jm2XH84Qec60587zWpX2gkj2gHxPlC4W9Oj17GkZEBdOc1nBm7gp68hk0FPcQJbx09ec1dt+MvXgzZw9G9u0MahZhDi9k4M3YFR/fuhqrAtRER82gSn3xs3yBOfO81l/Ninbzt9ffkpON8ev8QXnj5TZdvzaxjq/xuEshs9ti+QegqWdV6Q4oUKcKI0hazujz3E1rvxhxFv8d3ijLCL9XL1WTtPr1vEJZk/07q26LGoqkkchxpnre+EdxbxR4ty38aQZSOe3HiVqg+cY/lhZfflNqU956krN7+nhy+HNC/NZXgaUkcI8Yn7NOr8Xzz7PiSayFevaWQlfsYWXtr8R7IekHcvZ5Gjsv2AVnd24sdOPHosDRHbDRWlu5T+4dwevQyAL+/kOUq3hzPdz+qZovHV+EeVMzr2F7sQE9eQ09e8+Vq3lxM5kuFDzoyMgCb2b5cT5Q5Hrh355tpkOIAACAASURBVM11jowMoL8n5zvfk9eksYTNbHBwXx+i+qQqcOsU6xXM8W7b6Nyb9Pb3zNiVkJ898cFhZGTlGvRfcfeKm7mP3Ej9KZKjmNehKnA5ePzFiz67AMTDcyzElf7uLLb25EIaxpGRAfTkNZz43mvSGNtiNjZvzETanreOrT059EZwJuiXju0bREYlPg54r5NpU3E8bgeOBfvQjC3GgXC+un5KtB6Gh4f56Oho5PlKxcJU2YDFOFRK0JVzniOcKtnIago2FTKgq+zJ8BTLhmUjRhyPgxwu5nRks429mdk0bUzMVd06+goZaJoCxpz3YRuWDV1V0KkpvrYKWYqc4rQ1WfL3wVtO1JcU1aqF6/ML12/q0JHJtP5t05bFnHHbDKpC0VfIQFWbf5Y4ah7j1ig4x8W8DkpJ5HEAMAzLN9+9eR263tT8tAWHgfA8dOc0zBkmLNvZk6oWc8eb1Sgsm6NiMWzIKpg3Fs7ldIqqxcA5gWUzUEqgUQKFEpRqT+ELfmY1iorJUMhQzFUX6hCfveuUxM5k+8n1ku3+rVG14XWS2QKlRMqzlUIrfNAi0DYcXuF5SNFGaJALbcNhAcY4rs9VUTZtaIrzazsdGYJb5QU/uSFHYViAZXOYjIPVjoMA4ICqEKgKQTngnzsUtSG/GoS4pitHccPTn1bYW2rDi8Ky8Dgph9sB3riGEAKFAJRSXzwnyt2sVDHviUPyGQoCoFRlrk1ZjEOp/YojIY7tgQCcO6+rUIlznHOAUgLDYtBUpx5ee/WkZXNQSpBVKUybA3Be12wx7sZLqkKcb1hzwKjZtqZQaMpCHNWZpZitOP3VKEGmFk+JeBVAZGx7vVRFxbShEscniBhOU5wvGtyoWNLYdxnQFhyWxf+WZWOyZMCucUChBLpKYTEO05LPu6ZQmDYDIYBKCAzmvKaS8wWOKMSJrwWvNE+dWY2iajKXY85rLgk0lcC0uNsXXaVQKGDaQNWyoRACSgCF0toeYKOQVVCqMpi201ZOc3KtUtWGQgk0hYAS4sb6ukKhqwQ25zAt7tqFphCYNkchQ1E2ORjnIHC+3WvXOKRQgoppg4oxKQTdHZlQbkUIASEcjAGaSmHbHCZjUAhBTlfQlVvg7Ey5irLBXFvorelDN8oGAO7b5zp0CsPi7qvLbc6hkIW+i8+UADaH+8ushs1h2sy1tbJhI6crMDz5T4J8r+3iCSDsCwk4bA5oNV9m2I4fYZwDcHhp1Xya8EEi9xNzoVICG8762Ywjo1IABFXLdn1ZPkNg2gjniSZz554AKGQI5qoLscyGnALLXsg9tRrPhf/TFFKzCedVT6K9jEYwbzjr6OWryDfFZ7GOQVvvyqqYLBkuDzZ1aLg+b7qfvf5RUylU6vBE5ivjdIQkEBqJGEtWo9iY1RelkyRE23H49s88vwy9Ad743HuWpZ0Uza1pA+vTVhyup0Nen6sipyOU47Gaj/PGpsKXCS2tK0d9vlOvxZwVi0k14WBeFfQzGZWCEKBisoZ0Lm89hYyCqsV9+i7n3KedeccRzPMW6zvXCNqKw0uNqL14MfcIGOMoGQZulW2fxlwyuLQ+oe+LWEfYlKZQbMrrPhsI6sOFLEWpynyxejGnY860fBq6iEG6chRlEzAsBrN2LlOLcTqzii+mXQotpFKxcLNqwmQc3Q3oOU3cu2mLvC5F4/e8GvHDsrKAkw8z5sT7nPOm/XmQdyI2J+Du25Fsxt1cxOZOrqJ4dJmsRlE2mZOr1rQWy+boqW9fbcNh7zzndAUEHIZV05dErqZSWJy7elM+Q30xhKY4+a5e+9UnmzFQQnz+TleJGwM4c0VhMce/iVyf1vQLkX/pKonM9XI1PcP0+OG5QFzDuRO3iD44+ZzzeUF7I+jOaZg1LJQNGzYHsqrT31K19lmj2JR3Hsa5UTYWymkU3Vmt4X0lzg5k909nymZDscsyxTttw+GlAmMcs1UDpYoNs2YHhBAY9gKnFEoAsqBrZVUnzjZshkztb3H/WqcEDA7HcyqFHdAb7No+T2tt2IxLyxHixPHdWQ3X5w3XH3EOEIIFbarGcxF/kBrnhcbQndMwPW+gYoa1qUJWQYeqOtyr9SWrKSAAyqaNnKbAZtzVAFVKfHp4oxxshrPBazZmFN/zFAnyjMgG1tWdokrFwoWpEh4/OYbxmbL75GVXh4a+fCa9cZai7SHj8NP7h7CzmG+Iv5qmYEt3h+8YYxyvXpvFgWdHMT5TxrOPDaG7kAu1ddcmFZmMii0BUX/LIuwnk1GxZQkemgtCVSne0pWrXzABTNPGKxNzofm5u6+AbFaNnA9KCXo7/U89B+dePLG9a3MnGOP44WQJBz3tHN8/hLs3dy6HsL1k8M4DYxxXb8xjZt7EoVNnfePszKl43x++5JvjjAL83nd+iE88dBfe/+Ux3LejiP3v2u679ti+QWzs0NwbF8H1yNB4W4pbQwFZmXx2cfMSZQtBe11JJJmbtY5W+eIUqx+WxfCjqdXro2X7z5GRAfzut1/F5FwVx/YN4uQ/XcJLr03h6N7d+J2/fgXvvL0L7723PxRPa5TD4lQSN+TBOZqyGa+/Wax/jas7RYrFQhbfReHfbho+m/tvB34SN8uWz488XfsloD8bG8fI8FZcnzNw+PR5qZ0e3bsbmkrxsa9/32dff/DdH+I7L0/gN37mdqnNPn/uKn7p3n58oVZO9OV6yXDLPnxPHz7+0F3SeFd8AUcWw+7sLeDC5Fykbznx6DB+YkM28ZytRcjmTsYF2Z7ivba3kMGn3r3Lxw/vNXF5RhIh6o2pEq7dqiSqP6ovXo798YeHcXPexBPPnXPLfPWxd2CmZPiOPfXIbvzRP7yGjz24E2ffmMLg7UVfrO/luOBXb2cGG7OOwEap8+3aRsbuXJMF8uG56MlnwBjHtVvRe+azH3knSpbtO+8dv8yeVlPMkASN+EIBL8++8o+v40P33YFnXlr4/9d+egc++Y1zvjnfvCGLbd0duDA5h784ewXv2b3Fx4+vPvYO3Cyb+PWvjfmu29SZ+f/Zu/MoOY77TvDfyKuuBtCNBhoi2eBpHsJ6AQvd1jnW0ORIK4+0Y2sBUmsBoEV5IYIcSW85erT4dtdr7fofURw+zrMtAiTGpkyCskUB9lpD+pIla+mxLEsAJXLHFCGKBwiQFNFoNAh0dR15xP5RldlZWZlZR9eR2fX9vNcP6KqszMjIX0RG/Cq6Cs+/fg6f+dNnQ+PIHfd8ZOsmTIzl8Pvf+klDeT5/5NnQOI+Lq2AbDPbJYX30clz46jIkLlfSvl29zJFQe/q8sItGUFx+wjBUHP/ZBcxdWArN8b5trYGPPvBPTX3lupwGTVO8XFSruVjcvCrYz1iWg+ffvNDRHLrd17STO+tF30npEzZGWcn9LyqOLlq3Buvy4XFkGLX3U9qJZzc/7Lbvjz3U2HYLOvDCkonLJzP4tQe+h8/+8lW48b/bhNfPVXD7ofBcecMxQsYVvWQYKs4uLHXczjguSa+oeUCnj3ey717lE8Li7m2aGtrGp+v3mdfOLeHsktlwX71nx9aGecyt77sCxTU2NiOX+PcLgn1a2Nz1wT0zqNgKbn34Bw390bGXz+ALTzwfOq8Jzrfuu2kbvv3jnzVs98EtU/j0DVc39Ff+/sKyHBx/8wJuO9Q4t8sZKh74+5/i1vddgbyh4gvfeM7LN2U0Bbf80fdj+5/xXPR4YH2hsZ8aDxlerC9kmvrSTvuvuHYQfP+0m7FLN/NzaqYoAutyGayrX95WudD7v3k8NI+xcU0GX3ryea89fPnj70DVUJtyvu57MHOLFe91X/3eK3j/tZvw+SPPNvU5n7nxmoZ2tn/3DK7dWMCL80uRubpgLgtAU+7v/pu3YaKgA6hi7kIlsoxf/vg7UDadhvONyg13kjvpJs57Pc5fHZm6Ns2Xlt8QAIBTCyXc8djTqFoS86XqkEtH1FpYDN9+6FhP4ne+uPyGHgBcNbU29FhnlthWAOD0YiW0fk4vVjreV7DuTy2UsPeRo5gvVnF6seJNqt3n9nV5nKSaL1ZRsaQ3UAaWz9O0ZFMdFzI6dsxs9upl7/uvbHrtHY89DdOSmCuGx2s/2xKtfowfcqW9jw67/9x1+Fnsu/4qry/d+/4rcWqhhDsffwb7rr8KO2cvDR1Pr81lIscNbDNENWFtrmLJpn7k9seehqqo2Dl7KU4tLCcx3Of97fTOx5/BQtFsal87ZjYDQGSb3Tl7Kfb5tnPL4t92x8zm2PFu1Bj29GIltm9xx7mjrN1YCLun+F+77/qrmuJjXxvXqJ36ny9WcWJ+qe39R5XFH2OvLZS9xXLuYyfPlpoe+9zXn8GOmc2447GnccOWi5rG+rcH9nvX4Wdx8mypoa5Wcu5R9REX1yfml5qe959/WHtK05ihX/xxtmNmMz5/pPFfNxELLNf5ifklr5/ZOXtpU3ycPFvyFtD5X3fqbAnvuGzSeywYR+64x82FBMsTFedxcRWMm2CfHNZHtxsXvY5xIkqnuLnWfLGKvY8ejczxVgM5N7evrFqyb/enbubQvZx3s++kXlhJHHUSz1HtO6PruP3QMZwvOTi1UMJ7r96IctXxtg3LlQ9y3Ml2RmkXF8Pue1nBthmcx7j31DTkPoPnGzZ3ve3RYzh1ttTUH92w5SIA4fOa4Hzrc19/pmk7d94f1V+cXqx4C+jc5+86/CwWiqZXz2eLZkO+6cT8Usv+J039VJrKOgpa5UKj8hgnz5Ya2sPZohma83Xfg/G/bufspV5Owt3O7WuC7ez2Q8cw1yJXF8xlheX+7nz8GQAKTp4txZbxbNFsOt+o3HAnuZNu4rzXbSXZy597zHKWJ4auUwslKKL2HFHSRcVwL+K3atkN++7nsVaDXtZPsO7dfVUtO/o4ttN5oROqatlQBCL75+BjliMxntO97VVFdNy3M75pJRg/5DJtJ9V9dNT9Zzyne/9X6x2x+3hUn9uqXbDNEIW3udgxkBDIG2rLdpo31Mjno9qs+7i7XVhZ/OMt/2vdthvVh0T1jf4yVy0bo6yTWAjeU/yvjbxG9dfEzTPaKWNU/IXtP6os/hgL219cjJ9aKMGR4fcX/37dduCvq5Wce5hW98xWbbXVtRpV/jhz6yj4r5//Wvv7Mr+oa5E3al814n8sGEeqIrwxTVg5osoUFVfBuAmWN3Jc1UZc9DrGiSidYudh9X6i3RyGv6900J+5Wjdz6F7Ou9l3Ui+sJI46iee4tutvw3Yg77KS8UUvsJ1R2rWK4ai5e3D+kDfUVOQ+g+cbNw8LPiZl7fyi+p2w+VY7x3LrOqrPzBsq8lAb/h9XzmD/k6Z+Kk1lHQVR18PNUcS1HzdOAXhx2k7ON659hbUz//ihVa4urhyKaJ3rissbriR30mr7fu3Db6Q+iU5TBKYnGj9Oc3oiB0fWniNKuqgY7kX8GprasO9+Hms16GX9BOve3ZehqdBVJfw46urpvg1NhSMR2T8HH9MUgXMl09vedmTHfTvjm1aC8UOutPfRUfefcyXT+7+bjHUfj+pz49oF2wxRTVibixsD2Y7EUtVu2U6Xqnbk81Ft1n3c3S6sLP7xlv+1btuN6kOi+kZ/mQ2tMak5ajqJheA9xf/ayGtUf03cPKOdMkbFX9j+o8rij7Gw/cXF+PREDooIv4f49+u2A39dreTcw7S6Z7Zqq62u1ajyx5lbR8F//fzX2t+X+UVdi6Wq7f1xgPtYMI5sR3rjlrByRJUpKq6CcRMsb+S4qo246HWME1E6xc213H6i3fmYv6/s1/2pmzl0L+fd7DupF1YSR53Ec1zb9bdhNZB3Wcn4ohfYzijt4mI47r2s4PxhqWqnIvcZPN+4eVjwMSFq5xfV74TNt9o5lttfRPWZS1W7oZ5b5ciC/U+a+qk0lXUURF0PN0cR136C+bF2c75x7SusnfnHBK1ydXHlcGTrXFdc3nAluZNW2/drH34jla2bzBnYv3vGq8DpiRwe2LUdhiYwmTOGXDqi1sJieP/umZ7E72TBwMFbZr19v3j6fOixNuTZVgBgaiwTWj9TY51/x3yw7qcnat/TPVkwMDWWwYHAcQ50eZykmiwYyGgCD+za3nSeuiaa6rhYMXHk2EmvXg4+9VLTax/YtR26JrCxEB6v/WxLtPoxfsiV9j467P5z786tOPCdF72+9OBTL2F6Iof7b96GA995EYePvho6nj5fqkSOG9hmiGrC2lxGE039yP5d22E7Ng4ffRXTE1ncu3NrZDu9/+ZtmCjoTe3ryLGTABDZZg8ffRUHfNu5ZfFve+TYydjxbtQYdmosE9u3uOPcUdZuLITdU/yvPfCdF5vi40Ab16id+p8sGLhsMt/2/qPK4o+xSyayuP/mbQ3bbF6fa3rsvpu24cixk3hg13Z8+7k3msb6+wP7vXfnVmxen2uoq5Wce1R9xMX1ZZP5puf95x/WntI0ZugXf5wdOXYS9+xo/Pe+m7Y11fllk3mvnzl89NWm+Ni8PoeH9sw0vW56fQ4/PDHvPRaMI3fc4+ZCguWJivO4uArGTbBPDuuj242LXsc4EaVT3FxrsmDg4J7ZyByvEci5uX2loYm+3Z+6mUP3ct7NvpN6YSVx1Ek8R7Xvimli/+4ZrM3V3qD+7gtzyBqKt21YrnyQ4062M0q7uBh238sKts3gPMa9p6Yh9xk837C564N7ZjC9PtfUH337uTcAhM9rgvOt+27a1rSdO++P6i+mxjJ4cHfz3G6ioHv1vL6gN+SbLpvMt+x/0tRPpamso6BVLjQqj7F5fa6hPawv6KE5X/c9GP/rDh991ctJuNu5fU2wne3fPYONLXJ1wVxWWO7v/pu3AXCweX0utozrC3rT+UblhjvJnXQT571uK8L9qM3VYnZ2Vh49ejTy+XLZwnypCqv+16VZTUFB15DNjtQ321J3BvYnA3FxHIzhyZzRs/h1HIn5YhVVy4ahqVijqw3H2pA3kMmwrbhM08bpxYpXP1NjGei62vB4wVBRtSVM24GuKthYMHCubHl1PFkwoCiiqe7dxwHAspza/mwHmqpgaiwDTetqDXQiYtjlP+ecoUJXJc6XnOV6syRMx4GmCOiqgGlLrMspeKvkYCyroFhxIGXtUztyuoKq5cCsX4uMpmBtRoNhRMdrsC2N5xRkNKPbuqUudNGfJSaG+9kXU7p02EcnJoZd/r5YUxQAEmXLqffDy/1q3lBwoVz75JcNeR1niqbXR2c0BboGaAI4V+/HNUVgLKOgWJWYGsvAspy+txm2y4EZSBy3G8NpEzbmcxyJucUKTNuBoggYioChK6jaEhkNqFQlqo6E7UjoqgJVABXLgaEpEABsKetjIglVUTCZ0zFfMmHaDlRFoGAoKJm18ag7rrIchI5LLcvGXLHWjnRFIKMrKJkObEfCUBVoqkDJtKEKgayhQBUCxYoNWwJZXcH6nIGFkgnHcWDXP01PFbVPR6hYjf1k3Pi3zxIRw1Gx0M49xX2t49S+ksl0JBxHQtcUbCw0vmYl9ew4Em+VK1iqLPfthUxtHO6Ozy3f+FupfxWmaTkwNBUTOR1nS1WUTQeaADK6AsuWtfJKiayuYn3OwPmKiVLVhi0lNEWBgAQgkDUEqqaEoghUreUy5AwFZVPCqrcZTRFQhMBETm+I6YmcjrNLVZRNu9a2VAXr80ZT/OXqX7PjL/dCyQyds50pVlA2Haii9lfxUta+8k5KAVUAtgSklE3nrwpgTU7BhVLjediO6Cb2EzeeCOOvY0URUACULaf+6UiKF7NrM7oXA4qoze+8fxVAOrWvM1N9r3P3szanomJKVKxaP+W2G0URmFusoFK/9roiMJ7Vcb5qe1/lkdUVlM3l12W0Wn+mqQrWZ3XMl6oQApCy1ofZ9X54LKuiVHWa8gBRqlXL61fd8cnZsum18w15HWeWzI7n+44jca5Urbed2vlsKGQG1Y+uVOJi+PK7nxxAabrzyhc/POwipFI317SDuk5MDJfLFixYeMt3f/HPgxxH4sxiBRkNWKw0ztXKpoQEULUcr6/M6gIFw4DjOJgrVjGWURpeF5UbDhtv2LbTlDcVQuCtcu3eaNXHtu30ez3MjQ5zDJokiYnhqPx6P7nx5Obru4mnlcRRMJ6j3i8AmvMc63IK5ot205hiXU4FBLBY9ufWazkd3Te2GVS+ZEDtLBHzOlod3LlexbShCAFdE7Ds2txOiNpcTwgBVQFKpoOcrqBiOrCkhCpEwzzGloChKlhrtFx7kJgYDrbZdRm1YQ6TNRTAqc3n/LmBpaqE5ThQRS13vOSbJ+UNBcWqU5v3qQpEPZelqwKqqOWIFEX46hLIavW8UzWQMytWYPrGKw4kbAfQ6/1Kbb8KNtbngsH+B4D3mHc967kE/7F62U9F9YPd9I8JHrskJoYHKSqfpGsKtPo1rtrLOaucrgACKJZtL4dlaAKmVRuLW/WcnvvJso6UcCS8fkhTa3kRN5fm9jkQAuuzOs4sVRvGUaqq4MxipZa/rR/fdmr9WS1X60ARAjlDxXh9oa+XW6iXQwhAUxUoArDquT/HkchoKoQAyqYNXVVg6AKWJb1cmNu+FEWJzK0F69DNny3nBrvPb3TRViKfHKl3lcplCy/MF3H7oWM4tVDyVmRePA6opuj74JxopaJi+OrJQk8mPYoisHFN418kXcI3nyPpuopLJvINj5mmjedPL+L2Q8fw3isnsfs9l+GOx55uuF5P/OgUHvyHV7xV0NduWhNa9y5NU3DxeC70ubRyHInjb17A3keO4tRCCV/4yHWYuWJD2/W2f/cMfnZuCf/XEz/G/t0z2DRWgLGms1jVNAULSyb2+drTgd0zuG7TGi6kG4B+92f9lOayU++lvY927z+t7l/+/rFSsTC/VG1qA9dsKGDTGgXPv3mhoW/9szvegzfPN29/7cZC7GLnTrBdUlpEjfnOlUxvXOSOEa+azOP4XC2uN45l8FsfuhZ3HX4WpxZK+OCWKXzmxmsaYv7A7hlcs7GAn8wVG9rgvTu34pKJHJYqNvY+2ngMdxwK1MZnL84v4f5vHscdv/xzKFXtxuPdcDVu9/UL9+7ciryh4gvfeA5zixU88sl3Yn6x2nQeGU3BLX/0/YbHrt44hhfmFpu29ZdntQuLBUURbd1TFKW28Mo/nnbrcNOabMvjdOJnby1fUzfunvjRKXx42yWR9wm/qUB5wqzXMkCh+XHHkTj+VvM5ViwFX/v+iaYy7N89g9//1k/wt8+dxvREDn+y9114q2Q1jfevnRrDT88UsfeRo01ty93m93z7cWMTQFOMf/nj70DZdPC5rz8TiOVcw/Zh99YHdm3Hk8+8hl/bvnnVxX5wvuf2GV/66+OYW6xgf/1bIcqmgzVZHZdPFrC+sHz+luU0jSf+4tPvxevnKqHjjw0hc8FNa5tjb0JV8Pyb5cg54OTY8rZhuZCwcsXNIU3T9vpxf5mvmxpryEFe3OF4KKx+D94yiw2F0f5kQ6JREzUH8n/qjaIITNX7w3W+FKZlOTi5EN6fOY6D43NFLCyWMDGWC+13/Qvpwvqkr+97N84smg2vfWzvu3Ah5L7czqdj9XLevdKxEfWOPw8Rd5/spU7v5VFWEkf+eI66p1+7aQ2qVdtr47/zkbfjbeN5fOyh+Pa4LqSZDCNfwnZGaRLWDu/ZsRV//N2X8dkbr/Hmhh/cMoVP33A1/uDbL+A33nsFPn/kWWwcy+CLO34eFUs2zk13bUcpr2MTkIq8pL/NhtXHA7u24w++/YI3Rz6wewaKomPuQgVLVRsP/+PLDXUSnGMHX3//zdtgaArWZHVcvC7nLS6L6g8v8nVu7nb3f/O4d8zg9v7+J+763vmBa/syF486l25zYexTk8W9HlHX2Z8H/eCWKXz2xmsaxh0H98xC1wQ+8fAPQtuLG5+fvuFqPP3KPLZfPtnQv/jjd9OabMM6hahczPREDosVu6ms47naIrPxnIFzS0W8eb6Muw6Ht+N7d27FprVZXD5ZaIrXuPbbzrZhebhu8hu9bCsjtUpgvrT85h0AnFoo4fZDx1Cu1v7ygyjpomJ4vlQdcsnIdXpxOam/9/1Xejc2YPl67Zy91Pt97yNHMV8cves3X1x+8wkAbthyUUf1dvuhY9hy8Trv/3Nd1OHpxYo3cHH3u+/QMd4PBiTN/Vmay04UpdX9y98/nlkKbwNnlqqhfWvVkqHbd9N3R2G7pDQLjovcMeJccTmu911/lZe4AIAdM5ubYn5fvV0F2+Bdh59F1ZLeAjr/MfzjULccO2Y2Y6FoNh8v0C/cdfhZnC2a2Hf9VTi1UMKJ+aXQ8zgxv9T02OnFSui2ozgu7lZU3PSyDoPHcONu5+ylsfeJfh3fH1NhZbj90DHsmNns/V6xZOR4391vsG252/j349ZrWHnOFk1vAV3c9mH31jseexo7Zy9dlbEfVld3HX7W6y9uf+xpqIqKs0UTJ+aXms4/bDxRrjqR4492rXQO2Onr/eMrf5lX2lYG0f4pOS6/+8mOf2g0rGQOFNefuWPQq6bWttXvhvVJlo2m15ox92UaTf26T7Y6ZpLiMO6e7m/jWy5e1/U4iPkSonhh7fDzR57FjpnNDXPDHTObccdjT2PHzGZv4da+66+CqqjNc9PHnoZpyVS2s7D6cM/b/X3foWOwbOBsPXcUrJPgHDv4+jsff6ZpLtjuHMefu3KP2c72Yde3X3OoqHNhLmx1ictZ+fNowXHH3keP4uTZUmR7cePzjseexg1bLmrqX+LiNyoXU7FkbOzNF6s4Mb/klSWsXHcdfjY0fxNXF+1uG5WHG6bkL3/uIcuR3gVxnVoowXJW11fa0urFGE4+/zVSFRF6vVTfqutTCyXv62RGSdWyG+rGkZ3Xmxv33bYB03bC25PtdLwv6lya+7M0l50oSjv3L7d/jG8Dzc/ZA2gzbJeUZsFxEbAcv+7j4zm9YZvg72Gv8T+uCIQ+7h+Hlm5gFQAAIABJREFUuuUYz+ne862OlzdU5FH7lIi8oUZu01TOiHHYKI6LuxUVN72sw+Ax3DhodZ/o1/Hd4+QNNbIMbvwCiIz7uLYVth9/vQa3jYr74PZxc5zVGPtR187fvygCXv8QPP+wuVov7vUrnQN2+vp+jU8G0f6JKPlW0sfE9WcS8ePK4P7D+iRbNr828r7MPNzIGsY8Pmn54Lh7ur9+VlJXzJcQxYubu/jnMP7f/fPJqPubIpDKdtZqLuf+7kjpzYeDddLO64NzwXbnOP7cVSfbh5WnX3OoqGNG3YM4j0unuJyVKy6fGve8+7gTMqaOi9+oMrXKC1ctuyG/FVfusHjtJEfRbh8z7HYxUp9EpykC0xONn2c8PZGDVv+OYaKki4thSgb/NbIdGXq9bN/AeXoiB0Mbva+SNjS1oW4U0Xm9uXHfbRvQVSW8PakjdWscmjT3Z2kuO1GUdu5fbv8Y1wbC+lZ1AG2G7ZLSLDguApbj1338XMls2Cb4e9hr/I87EqGP+8ehbjnOlUwsVe22jrdUtXGuZAJA02v82zSVM2IcNorj4m5FxU0v6zB4DDcOWt0n+nV89zhLVTuyDG48AoiM+7i2FbYft17DyhMV98Ht4+Y4qzH2o66dW69uv7RUtbFUtZvOP2w80Yt7/UrngJ2+vl/jk0G0fyJKvpX0MXH9mbvfdvcf1iepovm1kfdl5uFG1jDm8UnLB8fd0/31s5K6Yr6EKF7c3MU/h/H/7p9PRt3fHIlUtrNWczn3d0UIbz4crJN2Xh+cC7Y7x/HnrjrZPqw8/ZpDRR0z6h7EeVw6xeWsXHH51Ljn3ceVkDF1XPxGlalVXtjQ1Ib8Vly5w+K1kxxFu33MsNuFkDJ9q6DjzM7OyqNHj4Y+Vy5bsGHhXMmB5UhoisB4TkHZBtYaOnSdnRTFGthoJyqOy2ULJ8+XcOpsbbXvUtXG9PocNq/NIZvtzQdLOo7EfLGKqlXrCCcLRk++D940bZxerHhtb2os47U5y6p9pbJpO9BVBVNjGWhadxPXuPL38jhRTNPG3FIFtl37dDVNEfjmv7yBLzzxPKYncti/ewZP/OgUHvyHVzA9sfyd4I4j+142JCCGXcHvPP+zfe/CpnV5Lz4ymoILFQtSAiXTxlhGw1hWxVLFge1IGJqAEAKlqg1DU7AhZ7RsA8HrvyGv4ydzxYbvoj+wewbXbVrTj7qngHLZwgvzRe/rBNz2cfVkIe5aJiKGo8YTKrSe9cWUHh3eNxMRw0Ct3GeKFZSrNhRFwFAFpASWzNoETghg93/+vtc+v7r3XdAUBabtQFMEDE1BsWLjzGIFDz31Ij5z4zW4ZkMBqqrg+TcvNPStf3bHe/Dm+WpTe792YwGGoXnlCdYjgLbrtss+hbozkDhuFcOriX9ctHEsg8/eeDWu2FBAzlBRtmy8dLqI8byOdTkdX/v+CWy/fBKbJ3JYm9PxVsnE+ZIJIQQ2rc0gb2i4UDbxiYd/gI1jGfxv//btuGg8C9uR9U/1lTh5toSH//Fl3P0rb8dYVoNpOTA0FeNZDW+cL2NhycS6nI6KZeH1cxXkDRU5Q8V4Xsfp8xXMF6s4cuwkbn3fFcgbKr7wjecwt1jBI598JyqW443v3LFuRlNwyx99v+Hc8oaKxYqFW/7o+w3bXrtpTU/mHi2kKoaj7jPB8bRbhz+3oVD/umwJKQEJIKOpmMjpWCiZqFo2hBBQBaAoSmh/uy6jYq5Y9cY5T5+Yh6HreNvaLMbzOv7+xz/D9ssnva+UCBtHx90f2713Bs/xg1um8H98eAscAOeKVeQzKj75laMN/f7vf+sn+NvnTmN6Ioc/2fsuvFWymsb7106N4adnil6b+60PXet9TYW7ze/59uPGJoCmOv/yx9+Bsul4X+katf17r5zE7vdc1lBnD+zajiefeQ2/tn1zp7GfmPFElLD4vHfnVnzpr49jbrGC/bu2w9AEyqaDNVkdl08WGs7fspym8cRffPq9eP1cpelef82GAjIZra24Cttv3BwwuM+1hopX32rMyVx30RikFA1zeUURmC9WUan/5bQjJSxbwpGArglcvCbbcQ4yOJ/VFODMYhVjWR0CsnYf8OVZEi5xMbzavgL1lS9+eNhFGLpurmkH9ZaIGA7OgT64ZQr/+4e3QBUCGT1+/mSaNl4/X8bcheWx3WdvvAbXbVoDy3JwplSFZUtoqsCj330ZC0sWPvWvr4KuCuiKgnxGQcV0oKm1vtz9pB29/ntGU2BJia/+0yvYOXsp1Hquz5YSHz/4zz3Lw/Urjz0CEhHDpmnj+dOLTff266bGWt7Pur327YwF/O9jZDUFQghUbQcCtVwJILCxYOBc2er4PYjgcxsLhjcuDY4lq1Xba+O/85G3423j+a7ae7v5kkG8d9JjqZrXUXIE+4+JnI4X5hYb5p13/8rbcaFsYTyv46vfewUP/sMruO2XLsfH3305zi2ZWJPV8MW/+jH++4vX4X+amfb6C1tKmLaEoSqQQmJ9JvZ9q0TGsONIvDJfxIn5JW/Oc8lEFv/xb457c+QHd8/gbesyMG0JCdTnOrWfilmr16eOv4n3XT0FTRXI6yqqtkTVcqAotcWFtgOoCnDJeD4yx/HIJ9/p5a3cPIZQBBbLFr74Vz/Gb7z3Cu8rXaPySmH7vWfHVvzxd1/GnR+4ti95qKh8zdUbxxpibcC5sH5IZAwPSlTOSgIwbYlS1UKxamPDmOHlad28qKYKvFUyUara2LQ2g7NFE+P52iexaaqAadXG1sWKBV0TDbkvf/xevXHMy/UF+zP3eJdO5pE3VJwrmtj76PJ+Htw9g0smsqjaEtKRMB0J03bwypkl/NX/9wY+uv2ShlzZvTu3YtPabFP+Jqwu4mI7bNuoPFyn7aKL8WH0G3mjtoiOb67RCgx9cuk4Es//7Dw+9ehyDD+0ZwbXvW1tT26wnXRynYibEAshOkpid1t+x5E9O04353rxugwqlgydYA+qbEhADPu5NzNVkXgt8GbIA7u249A/ncB3X5rHfTdtwx/+15fw6Ruuxh98+wXvJup/E6ZVfUUlSK7ZWMCZJROW7UBLR3JgVSmXLcyXlt+gnWy9GDIRMczxBLm6uG8mIoaj3tj2L4bZv3sGF6/NYLFqYyyj4o23Kg19qL+ffnDPDK5avxz/buLV37c6jtOwIGNjwWhYQBdWj+7Cm3bHJF30KdSdkU6Q9IvjSJwrVfHGuTJuC4xX3CTCB7dM4TM3XtNw/7nvpm3I6gr+/Vd/uNxW9sxiaq2BhSUTC8Uq7nz8maa2XshoUCBwy8Pf9xI9n73xmoZ27i5ImrtQbVpk9ODuGVw8kYGU7h81RC9+BRB6bgdvmcWmtZmG1w8oaZiaGG51nwkmh8azGo6fXsTvfesnDcnksOvrJt3u/pW3Ny1+9C9GC4s7N2FeNmt/4BIcR8eVG2heiBbXv7vn6DgOzhSruM03F35wzww2FAxULAeKIvB3//IGLpooYLJgYGpNBhevq/1la/CepGlKQ93lDBWWI70Fpf4Fh3ELAHWt9mk9puXAloCUMnb7QkbFUtWBZTveYgIJ0U3sJ2I80Yr/3BVFQAFQtpYX4zuOhK4pGM+Fn39wPLEhr6NsW7hQXv5Dlg15w1tA125chY1TohbQBff58K2/iMWyhc/8yQ9D28v0RA5fufUXYVqyITndydw1TNh81j8Wc9uzuwAmBXPaxMUwF9GtPqOwiA5YngMJASwUzaaxVrtvXD24ewbXRORpH9v7LpwvWY05kF3bsTan4a2S1bBAfP+u7Xi03jd9tb6Y/fbA2PaidRkUK/aK83D9ymOPiMTEcNwf3kdZ6bWPGwv4c/thf2xxz46teOr4m/jIL0w3xHY770EACH3u2qmxyAV5/jzHeF7FYtnpqL27WuVLOv1Dg4RIzbyOkiNucdPZUhW2I3F2sdrQvh7cM4NNazJ480KlYT7qv8+F9RcP7ZnBNVOxbSiRMRw6Ttgzg4m8jtfPlTFfrOLpV+axY3YzSvVPk/Of9303bcOPXz+HmSs2RNaN+55fcBFbcJ7+5vlK5OK3qbUGqpaE49T+WCmjK9hQyMTmFcL+qLBfY4a4P4hcRX8AkMgYHqS4nJUXr//mWlw0nsFrC415Uff5W993Bf786dfw0e2X4OF/fLlpceiDe2awJlsbd+d0FTldga4pWJ8zQhdlXr1xDG9VqnjjXOP7OY988p0Yy2hYqtp4+UzRWygXdswDu2dwyUQGplXL46gCtT+wjsjf+OuindgOW8wclYfr5Fp0MT7kIjoAeG1hCR976HsN37M7PZHD1z71blwykR9UESm9hj65nLtQwUcf+MemGP7zO96HjWsyKz5uv/Yf1/aEELj5wX9qeu7x296Di8dzYbvrqvym7fTsOHG66WdeP1caSNmQgBgOE1VnD3/iF/GB+5/C9EQOv/2RLfjdJ57Db39kC2579Ji3jft7q/oaYB1TfyUihjmeIFcX981ExHBUuX/3V38eVdvx+lU3pqP6UH8/vZKxQlx5bv3KDxoe69WYh1Zk5BMk/RLVFtzxzoN7ZvC7TzzXVlt5/Lb34PjPLuC3/+K/hW7vcl8Xte/f/sgWAAh9rpP22O95TIdSE8Od1pvbX7tjZ/d1cdfXUJXQOGkVd3HXLq7cALqKhX7sM8USMZ5Ikn70MWH7fPgTvxjbXtrZppt5aDtjMbfdp2SOm7gY5iK61WdUFtG5OukHO82f/t1/+Nf4RP0PL/zb/8ned+PXD0bn86Je16t+KmHjy7RJXAx3op/X3p/zixoHP/yJX8StX/lBx+9BAOhJfrof55/S3Hlq5nWUHK3aT9Tzj9/2ntj7Y1R/0aINJTKG28nTPrhnBkb9a7DD5j5f3ftufPxgfF/qzl+i+q64HFnc62igEhnDw9AqXsP6EP/z7tgimM/zb+d/b7xVLizqOX853LYZdcy0tbEux0eRMTxSH81gObKh4gDg1ELJ+7hxoqSrWnZoDFctO+IVydh/fNuLeM52Oj5OXPkjy9DFceJ008+YtjOQsiVVVJ2p9ZXhpxZKGM/p3r/+bdzfW9XXqNcx9RbHE+Tq9325X6LKnTdU5KF6v7sxHdWH+vvplZxzXHmCjyW9bolWIqotuOMddzwUfD6srVi2g7yhtrV93L79Y63gc520x7T2l8PWab25/XXwenZzfVvFXdy1a1XubmKhH/uk1aMffUzYPqP6Vf88tdU23cxD2xmLuW2Vc1yi0dRJP9hp/lQR4fdZR8bn86Je16t+iuPL0dXPa+9vA1HjYFURXb0HIdGbNtGP82funEZFq/YT9bwV0kb897mo/iKNbaidPG3wfbrgtlK27kvdx6P6rrgcGe/3lDSt4jXqPus+744tWuXv3N/byYW16sv877uvhjF1r8dHQ/kcXiHEeiHEN4UQL9T/nYjZdq0Q4jUhxB+s9LiaIjA90bjie3oiBy29H5NJI8bQ1NAYNrT4jzgf9v7j2p6uKuHPqZ13T3Hl7+Vx4nTTzwyqbEkVVWd2ffHG9EQO50qm969/G/f3VvU16nVMvcXxBLn6fV/ul6hyL1Xtxn61HtNRfai/n17JOceVJ/hY0uuWaCWi2oLbLt3xUPD5sLaiqQqWqnbk9u6PK2rf50pm5HOdtMe09pfD1mm9uf118JrFXd+oOGkVd3HXLq7c3cZCP/ZJq0c/YiBsn63aSzvbdDMPbWcs5rZVznGJRlMn/WCn+VNHInR7RcTn86Je16t+ivf/0dXPa+/P+UWNg21HdvUeRK/y0/04f+bOaVS0aj9Rz2st7o9R/UUa21A7eVo3lxA19xGidV/qPh7Vd8XlyHi/p6RpFa9R91n3eXdsEdde/L+3yoW105f533dfDWPqXo+PhtV73w3gW1LKqwF8q/57lN8F8P/24qCTOQP7d894FTg9kcP+3TOYzBm92D1R300WDBy8ZbYhhg/eMovJQm9iuF/7nxrLhLa9qbEMpsYyOBB47kD9uV6Wv5fHiRN3rnGvGUTZkiqszh7YtR0Hn3oJ0xM53HfTNhw5dhIP7NqOI8dOetvcu3MrDnznxbbqa9TrmHqL4wly9fu+3C9h5b5351asL+hev7p/9ww21s8jrA/199MH96zsnKPq8bLJfOrqlmglwtrCgd0z3vjnyLGTTW3xvpu2YX1Bb2orU2MZXDaZx/03bwtt65vX5xraWNi+3WMf+M6LuHfn1hW1x7T2l8PWab25/fWRYydxz46tsdf3nh1bceTYSVw2mW86xv5A3AXHPa2uXVy5u42FfuyTVo9+xEDYPqfX55r6VX97mZ7IYfP62tgo2Pe2O3cN02os5rZnznGJRlcn/WCn+VNDE02P7d+1HY508MCu7U2Pu31T2Ot62U/x/j+6+nnt/XnqsHnQPTu24vDRVyPHx3E56F7lp/tx/syd06ho1X6inp8ayzQ9nvHd58L6iwf3pLMNtZOnPXLsJC6ZyGJ9QW867/tu2oZvP/dGbF/qvucX13eFlcOd9/B+T0nTKl7D+hD3+Xt3bsXBp17CvTu3NuXzgrnhdnNh7fRlbtsMO2Ya21ivx0dCysF/9ZgQ4jiA66WUbwghLgLwHSnltSHbzQC4C8BfA5iVUn661b5bfS9yuWxhvlSF5UhoisBkzkA2O1LfakvdG9hHDMXFseNIzBerqFo2DE3FZMGA0sNPP+rX/k3TxunFitf2psYy0PXa6l/LcmrP2Q40VcHUWAaa1t0a37jy9/I4ceLONcqAypaIGA4TrLOMpqBk2lAVBQISEAKGKlAyHTiOREZXIQCUTbvt+hrU9ae+SkwMczxBrg7vm4mJYceROFOsoGzaUOp9rJRA2XKgKQIbCwYMYzmm/X2oqggYmoJS1UZWV7FhLLPisUJYPQLo65iHujaQi9DpWGK1CLaFiZyOhZIZ+rsQAqoAdE2B5UiYltPQVhxH4lypinK19rVCiiKgKQKKEFifr23T7rFyhhp6jJWc2xDbdKpiuNN6c/trAQn3m+ajYkdRlND+dl1GxVxxeZyzsWDgrYrd0bWLK3e3sdCPfaZUYsYTSdKPGAjuczyr1dqRXZuXZvVa25orVhvmmf7+Va9/+kQnc9cwwfls3lBQrNQ+DUIRgIRI0xw3cTF8+d1PDqA0g/PKFz887CIMXTfXtIN6S1wMA531g53mTwE09UEV04GmCpRNB5YjoasKMppAsWJHvq7X/dSI3f97KZEx3Il+Xnt/njqrKRBCwKx/JaN7z91YMHCubHX8HkSv8tP9OP8U5s5TNa+j5GjVfqKeD3vccSROL1Zg2g6ymgJbSli2hKEp2FBo2YYSG8Ot8rQAoNdzyQBgOhKOlNAVBUo91zCe1bx5UkZTYDsSVmCbVn2XvxzBPAbv94mQ2BgehlbxGva8qOdqS9Va7sCyHQil1raklKH52nZzYe30ZW6+VzoStu+YaW1jXYyPot/IG9IiunNSynHf7wtSyonANgqAbwPYA+BGxCyiE0J8CsCnAODSSy+dOXHiRN/KTiOtr70F45gGgDFMaccYprRjDNNq0Lc4ZgzTgDCGKe04nqC0S1wMcxHd6pPmRXTsh2kAGMO0GnBeR2nHGKa0YwxT2kXGcN/+jEAI8XdCiP8W8vOrbe7iDgB/KaU82WpDKeVDUspZKeXsxo0bV1ZwoiFhHFPaMYYp7RjDlHaMYUo7xjClHWOYVgPGMaUdY5jSjjFMaccYprRjDFPaMYYp7RjDNGx9+94xKeW/iXpOCPGmEOIi39e5ng7Z7D0AfkkIcQeAMQCGEGJRSnl3n4pMREREREREREREREREREREREREI6Zvi+ha+AaA3wDwxfq/fxHcQEq5y/2/EOITqH2dKxfQERERERERERERERERERERERERUc/07etcW/gigA8IIV4A8IH67xBCzAoh/vOQykREREREREREREREREREREREREQjZiifRCelnAdwY8jjRwH8LyGPfwXAV/peMCIiIiIiIiIiIiIiIiIiIiIiIhopw/okOiIiIiIiIiIiIiIiIiIiIiIiIqKhE1LKYZehp4QQcwBOrGAXGwCc6VFx0nh8liH6+GeklB8axMF7EMetDLt+WYbhHH81xXCUYV9TvySVBUhWebotS1pjOAl1P+wyDPv4SSlDVkr584M4UJ/74STU5bDLMOzjD7MMA+mLu4zhUb4uSTl+GsowyBguxpRjEJJ+LUalDL0+fpLGxMOuW5YhOWXo5PhJiuFeGHbdswyDL8Nqi+F2JOH6+rE88VqVZzXGcBKuwbDLMOzjD7oMSc5NrNSwryWPv4rGEz2K4WFfkySUYdjHT2IZ0hTDSZSE6zkIST7PyBhedYvoVkoIcVRKOTuqx2cZknH8fkvC+bEMwz/+apSkOk1SWYBklSdJZRmEJJzvsMsw7OOzDL2VhPMYdhmGffyklCFpklAnwy7DsI/PMiSrHMM+PsuQjOP3UxLOjWVIRhmGffxhSsK5swzJKcNqlbS6ZXniJa08g5CEcx52GYZ9/KSUYTUYdj3y+IzjoCTUybDLMOzjswyrz6jUZVrPk1/nSkRERERERERERERERERERERERCOLi+iIiIiIiIiIiIiIiIiIiIiIiIhoZHERXbOHRvz4AMuQhOP3WxLOj2UY/vFXoyTVaZLKAiSrPEkqyyAk4XyHXYZhHx9gGXopCecx7DIM+/hAMsqQNEmok2GXYdjHB1gGv2GXY9jHB1iGJBy/n5JwbixDzbDLMOzjD1MSzp1lqElCGVarpNUtyxMvaeUZhCSc87DLMOzjA8kow2ow7Hrk8SkoCXUy7DIM+/gAy7DajEpdpvI8hZRy2GUgIiIiIiIiIiIiIiIiIiIiIiIiGgp+Eh0RERERERERERERERERERERERGNLC6iIyIiIiIiIiIiIiIiIiIiIiIiopHFRXREREREREREREREREREREREREQ0sriIjoiIiIiIiIiIiIiIiIiIiIiIiEYWF9ERERERERERERERERERERERERHRyOIiOiIiIiIiIiIiIiIiIiIiIiIiIhpZXERHREREREREREREREREREREREREI4uL6IiIiIiIiIiIiIiIiIiIiIiIiGhkcREdERERERERERERERERERERERERjSwuoiMiIiIiIiIiIiIiIiIiIiIiIqKRxUV0RERERERERERERERERERERERENLK4iI6IiIiIiIiIiIiIiIiIiIiIiIhGFhfRERERERERERERERERERERERER0cjiIjoiIiIiIiIiIiIiIiIiIiIiIiIaWatuEd2HPvQhCYA//OnHz8AwjvnTp5+BYQzzp08/A8MY5k+ffgaGMcyfPv4MBGOYP338GQjGMH/6+DMwjGP+9OlnYBjD/OnTz8AwhvnTp5+BYQzzp48/A8EY5k8ffwaCMcyfPv4MBGOYP338ibTqFtGdOXNm2EUgWjHGMaUdY5jSjjFMaccYprRjDFPaMYZpNWAcU9oxhintGMOUdoxhSjvGMKUdY5jSjjFMw7DqFtERERERERERERERERERERERERERtYuL6IiIiIiIiIiIiIiIiIiIiIiIiGhkcREdERERERERERERERERERERERERjSwuoiMiIiIiIiIiIiIiIiIiIiIiIqKRxUV0RERERERERERERERERERERERENLK4iI6IiIiIiIiIiIiIiIiIiIiIiIhGljbsAiSB40icXarAtiUkAAHAdCRsRyKnq7AdCQkJyNrjqiKgKwKOlFAVBUIAFcuB7UjoqoKsLrBUdeA4EpqqQEBCEQK2I2FJiayuYn3OwNlSFRXTRk5XUbEcWPXXT41loGndr290HIn5YhVVy4ahqZgsGFAU0bP6Wi3SWk/lsoX5UhWWI6EpApM5A9ksmzIRhWOf0R+sV3IxFtKtUrFwZmn5+m3IG8hkmq+fadoo2ybOl5ymax2MgfGcgnMlB5M5A6oqcHqx4j03NZaBrqsty8W4aq3VWD7u+bDnAHS0vaIIOI7EmWIF5aoNVRHIaArKVm0emDVUbChkvO3mi1U4jgNbAqbtQFMEdFVB2bKhiNr8UtcUrM3oOF8xUarasOrzUct2YDoSWU2BEAKm7UAIAdTnmVICVduBqghkNQUSvvlpfb+mLaEK1F8HlOrzUKBWHn89nClWUDZtqEIgZ6gYz7Wui2FKYpkoneL6BgHp5W00RaCQUbE2W4s1y3Iwt1iBqgCmXcslqYqArgrv96ymwJaApgpUffvJGQoUARQrzfeXpHPPu2o7GM+rkBJwZO0505JeXs3QFGS0Wl9l2RJOvc/SFYGMrsCyJcpWrV/MaAokBNsxEQ0Ux97tu/zuJzt+zStf/HAfSkJEg8R+cnhGdb7b6Xm3s31wm4mc7r1PryoKVAGULachVyKEgKEKVG0JrT7fc9tBPqNgjWGgaFaxWHaQNxQsVdM3rwvj5rsqZi1npSiAqihNea5WOTQhBFQBKIqCiZyOhZLZ8LhQBDRFoFRdvibuNq3m5LomYFm1dRhSStgSkFI27SerK6hY0svFjWVVrMks79dxatfZsh1YUkIVAkIAUgK6JlC1JAxFAPV8nL9c58tVFCu2t75jY8HAubLVEGP+84k7v7Cc43yxioplQwBembJ6LXfoP05U++hHO0qiYN7VkbV8qSpqORj3+mc1BYBA2arlcQ1VgaoAxYoNpR6LmlJr76ivGLJsB0p9XZAta2uFhKjlPsYyChYrDuz62p8NhQyA5eupa0pDfAevrVteKSXyGQVLvryQu2//2iFFEV3nwkdFu+/1tCOdvXcPOY7EK2cWUTJtr0LPly3cdfhZbBzL4Lc+dC0e/seX8Zv/6kp87uvP4NRCCdMTOdy7cyvGMhoMTeBs0cRdh5/1njuwewb/5Uen8OA/vILpiRz+08d+Aboq8O+/+kOcWijhg1um8Nkbr8G+Q8fw3isnsfs9l+GOx55ueP11m9Z0tZDOcSSOv3mi8IZ9AAAgAElEQVQBex856u3v4C2zuHbTmpFrKHHSWk/lsoUX5ou4/dAxr9z7d8/g6slCagdjRNQ/7DP6g/VKLsZCulUqFn5ypvn6XbOh0DC5Mk0bS5aJV89WQq91WAxsWqvjhfkirpzM4GMPfa/hueumxmIX0jGuWms1lo97HkDTc4988p2oWE7b2x+8ZRZXbxzDC3OL3uMf3DKFT99wdcO8zr/d/d88Hjqn/NJfH8fcYgX37tyK9QUdZ4tVzF2oNMxHg/93X3/fTduQ1ZWGeeZd/8O1OLNYbdhu/67teOKZ1/D+azfhj7/7Mm593xX486dfw0e3X9Kw3SOffCcqpoO9jx5tKOOmtVlcPlmIrIthzqHSOq+j5ImKpYym4GvfP4EPb7ukoX0/sGs7JvIW3rYmi+OnF/FffnSqYRt/n+C23+88/2bTfh7cMwNDU3Drwz9IVZ9vWQ6ef/MC9h06ht/5yNux7dJxWPUVdMWKjTP1fsx/nhMFHRXTxp4/XD7X+2/eBkNT8IVvPIe5xQoe2LUdTz7zGn5t+2a2YyIaCI69iYjisZ8cnlGd73Z63u1sH7bNgd0z+L1v/QR/+9xpL/8RzJW487onn3mtaS63f9d2XDwBvH6uglfmzuPyjWtXRTsJq6t7dmzFH3/3Zdz5gWub8mGtcmj37NiKp46/if/xF6axz1c/7j5vfd8VXm4seE3cfN3/8/TJ0Dn5k8+8hn+79WKUTcfLt/nXYITl0mp5Wwfziybu/+Zx3PHLPwfTcnDn4880le0zN1yNJ555Dddftwl5Q/XmrQdvmcV4XsPchWpDDuAzN17jxYC/HGG/+3MOt/zR92NzjsEyLeZt7Dr4z7Htox/tKIncct//zeP4jfdegc8fWb7Wf/Dxd3jXNiwW7t25teG63n/zNqzL6/iPfxOew80ZKh74+5/iN//VlfjD//oSPnPjNfh9X7we3DOLjN54Pf2532Ce2C1vcK3Qbb90OT7yC9MN/cmB3TNYl9Pw6xHXPa3Xr5fafa+nXSP/da7zxSpOnC3h9IUqzhZNnL6w/IbDvuuvwl2Hn8WOmc1eQwGAUwsl3HX4WZxZrEJVVG9797l9h45h5+yl3u//69d+hLNF09tmx8xmr5Pc+/4rvUbhf/3pxUrX5+M2EHd/ex85ivlidUX1tNqktZ7mS1Wv8QO1ct9+6BjmS8kuNxENB/uM/mC9kouxkG5nlsKv35mlxut3erGCxbITea3DHjct4PZDx3Cu5DQ912qcz7hqrdVYPu75sOdOzC91tP3eR47i9GKl4fEdM5ub5nX+7aLmlPuuv8r7v6qoOHm21DQfDf7fff3nvv5M0zzz1EK5abvbH3saO2cvxeeP1Oa2dx1+Fnvff2XTdifml7wFdP4ynphfiq2LYc6hklgmSqeoWDoxv4Sds5c2te87HnsaFUvi9GLFywH5t/H3CW77DdvPbY8ew6mzpdT1+e55n1ooYcvF61C1JGwbsG3glK8fA5bP07YBTVEbHr/z8Vo/5vaFd9T7K7ZjIhoUjr2JiOKxnxyeUZ3vdnre7Wwfts2+Q8ewY2az93tYrsSd14XN5W5/7GmUq7V84Tsum1w17SSsrtx8Ulg+rFUO7fNHanPhfYH68eeo3Plg8Jq4+bqoOfnO2Utxtmg25Nv8azDCcmm3HzqGqiW9XN1C0fQW0AXL5ubT7jr8bMO8de8jR2HZaMoB+GPAX46w3/05h1Y5x2CZTEu2bB/9aEdJ5JZ7x8xmbwEdUCu//9qGxULwut75+DN4baEcmcNdKJrec+719sfr3kebr6c/voN5Yre8wbVCO2cvbepP9h06hkrMdU/r9euldt/raVe6lj/3QdWykTcaPwnCrdzxnI5TCyXv3+A2eUOFIhD6nOpb1elu6/LvT1VE6Ost2+n6fML2V7Xsrva3WqW1nixHhseL+50pREQ+7DP6g/VKLsZCurV7/dzfo7aNezy4r3big3HVWquxfKvng8/lDbWj7U8tlGDaTsPjUXNGq75d1PPjOd37vyIay+J/Tdyc1F+GqPK68053P2Hz0Kh6yBtqbF0Mcw6V1nkdJU9ULOUNNTJvo4jlPju4TVj7jdpPWE4q6X2+vw90y+qWOKovcWTzObnnn4fq/e7WE9sxEQ0Cx95ERPHYTw7PqM53Oz3vdraP2sbNo7i/R83rIt/Lr7cPexW1k7i68ue5gs/H5Y2i6s+/DsP/mMudW0a9XlVE0/yznVyae73i8mjBax+ct9pSRh63nd/d/YTlA4I5x2CZgh8sFtY++tGOksgtd1j9RuVYXWHX1f09btuw2PVvE3ydP87MkDxxML7jclDBx9rNhY+CXo9XRv6T6AxNxVLVbviZnsgBAM6VTExP5Lx//aYncliq2nAkQp+zfRfE3dbl35/tyNDXa2p3l8bQ1ND9GVr0V0aNorTWk6aI8HgZkY/iJKLOsM/oD9YruRgL6dbu9dMUEbtt3OPBfbUTH4yr1lqN5eOeD3vOPwdsZ/vpiRx0VWl4PGrOqNW3i3r+XMn0/u9IhM5H4/YfnGdGnYs773T3EzYPjXrtUtWOrYthzqGSWCZKp6hYWqrakXkbRy732cFtwtpv1H787dh9LOl9vr8P1BQBVRFQRe0nqi9RhIAimu+LS1W7oS9064ntmIgGgWNvIqJ47CeHZ1Tnu52edzvbR23jzkPc36PmdZHv5dfbh7qK2klcXfnzXMHn4/JGUfXnX4fhf8zlzi2jXm87smn+2U4uzb1ecXm04LUPzltVISKP287v7n7C8gHBnGOwTME1QWHtox/tKInccofVb1SO1RV2Xd3f47YNi13/NsHX+fevh+SJg/Edl4MKPtZOLnxU9Hq8MvKL6CYLBi5bn8PUGgPrCzqm1hi4d+dWTE/kcOA7L+LenVtx5NhJ3HfTNq/ipydq32G8YcyA7dje9u5zB3bP4PDRV73f/9PHfgHrC7q3zZFjJ3Fg9wymJ3I4+NRLeGDX9qbXT41luj6fg7fMNuzv4C2zmCwYK6qn1Sat9TSZM7C/HjtArdz7d89gMpfschPRcLDP6A/WK7kYC+m2IR9+/TbkG6/f1FgGY1kl8lqHPa5rwP7dMxjPKU3PtRrnM65aazWWj3s+7LnLJvMdbX/wlllMjWUaHj9y7GTTvM6/XdSc8sB3XvT+bzs2Nq/PNc1Hg/93X3/fTdua5pnTE9mm7fbv2o7DR1/FPTtqc9t7d27Fwadeatrussk8Du6ZbSrjZZP52LoY5hwqiWWidIqKpcsm8zh89NWm9v3Aru3IaAJTYxkvB+Tfxt8nuO03bD8P7pnB9Ppc6vp897ynJ3J47vW3YGgCqgqoKjDt68eA5fNUVcBy7IbH77+51o+5feED9f6K7ZiIBoVjbyKieOwnh2dU57udnnc724dtc2D3DI4cO+n9HpYrced1YXO5/bu2I2vU8oU/PDG/atpJWF25+aSwfFirHNo9O2pz4QOB+vHnqNz5YPCauPm6qDn54aOvYn1Bb8i3+ddghOXS9u+egaEJL1c3UdBx/83bQsvm5tPu3bm1Yd568JZZaCqacgD+GPCXI+x3f86hVc4xWCZdE6H13+o6rrQdJZFb7iPHTuKeHY3X2n9tw2IheF3vv3kbLpnIRuZwJwq695x7vf3xenBP8/X0x3cwT+yWN7hW6PDRV5v6kwO7Z5CJue5pvX691O57Pe0SMuTrFNJsdnZWHj16tKPXOI7E2aUKbFtCAhAATEfCcSSyulr/VDkJKWsfBagoAroi4EgJVVEgBFCxHNiOhK4qyOoCS1UHjpTQFAUCEooQsB0JSwJZXcH6nIGzpSoqpoOcrqBiObDqr58ay0DTul/f6DgS88UqqlbtEwMmCwaUFK5277cu6mlglRgXx+WyhflSFZYjoSkCkzkD2ezIfzMztScRMUyDtcr6jMTE8CqrV1qBDmMhMTFMNZWKhTNLy9dvQ95AJtN8/UzTRtk2cb7kNF3rYAyM5xScKzmYzBlQVYHTixXvuamxDHS99V+AJbyPGUgct4rhVmP5uOfDngPQ0faKIuA4EmeKFZRNG6oQyGgKylZtHpjVVWwoZLzt5otVOI4DWwKW7UBVBHRVQcWyIURtfqlrCtZmdJyvmCjVP/0qq6uwbAemI5HVFAghYNoOhBAQkBBCQMraVysqikBWUyDhm5/W92vaEqoARP1ToMqmjWw9Fk3baaiH2jk5UAWQM1SM51rXxTAldV7Hfjh94voGAenlbTRFoJBRsTZbizXLcjC3WIGqAKYtYTuy3saF93tWU2BLQFMFqr795AwFigCKleb7S4xEjCfc867aDsbzKqSE95fRpiW9vJquKchoAhKAZUk49T5LUwQyugLLlihb9d81BRIiEX0L9VUiYpjI1cXYe2Rj+PK7n+z4Na988cN9KAmt0MjGMHUnoTmKkZjXJXEOPgidnnc72we3mcjp3vv0tU/WBsqWg5wvVyKEgKEKVG0JrT7fc9tBPqNgjWGgaFaxWHaQNxQsVZM3r+t23cSZYgUV04EiAKX+6ePBPFerHJoQtXpVFAUTOR0LJbPhcVH/9o9SdfmauNu0mpPrmoBlSWiqAiklbAlIKZv2k9UVVCzpzUHHsirWZJb36zi162zZDmxZW88hBCAloGsCVUvCUARQz8f5y3W+XEWxYnvrOzYWDJwrWw0x5j+fuPMLyzm6jwPwypTVa7lD/3Gi2kc/2lFAImI4mHeVUnoxpqnCu/5ZTQEgULFsKIqAoSpQFaBYqf3ufhtN1ZYQkJCoxYV/XZCUgFAAxwHGMgoWK7VjZnUFGwq1P5x361DXlIb4Dl5bf3nzGQVLvryQu2//2iFFEV3nwkdFu+/1+ERW0NBHOUmgKAIbxrI93ef6Quttptb09pguRRHYuKa7T7IbJWmtp2xWwyXDn6AQUUqwz+gP1iu5GAvplslouCR+IgUA0HUVuq4ibPgeFgMF33aXTOQ7LhfjqrVWY/m456Oe63R7RRFtzek6nXes1zJAG/PJfok7pyTOoZJYJkqnTvsGl6YpuGg8F7tNK+Od3yqGrhfnTUSUBBx7ExHFYz85PKM63+30vNvZPmybXrxPv07LYl19WjQxxFxOL7XKd3WTcwNi5taF+G26aQPtvGalbWs8n2may28M/PF08Bjtnl+rmA4eJ0w/2lESrbTck2PdH3tdSC6nqSyBfiGqvMG3ENradxv7HSXtvtfTjpH/OlciIiIiIiIiIiIiIiIiIiIiIiIaXVxER0RERERERERERERERERERERERCOLi+iIiIiIiIiIiIiIiIiIiIiIiIhoZHERHREREREREREREREREREREREREY0sLqIjIiIiIiIiIiIiIiIiIiIiIiKikTXURXRCiA8JIY4LIX4qhLg7ZrudQggphJgdZPmIiIiIiIiIiIiIiIiIiIiIiIhodRvaIjohhArgywB+BcAWAL8uhNgSst0aAJ8F8M+DLSERERERERERERERERERERERERGtdsP8JLp3AviplPIlKWUVwJ8C+NWQ7X4XwJcAlAdZOCIiIiIiIiIiIiIiIiIiIiIiIlr9hrmI7hIAJ32/n6o/5hFCvAPAZinlE3E7EkJ8SghxVAhxdG5urvclJRoAxjGlHWOY0o4xTGnHGKa0YwxT2jGGaTVgHFPaMYYp7RjDlHaMYUo7xjClHWOY0o4xTMM2zEV0IuQx6T0phALgfgCfa7UjKeVDUspZKeXsxo0be1hEosFhHFPaMYYp7RjDlHaMYUo7xjClHWOYVgPGMaUdY5jSjjFMaccYprRjDFPaMYYp7RjDNGzDXER3CsBm3+/TAF73/b4GwM8D+I4Q4hUA7wbwDSHE7MBKSERERERERERERERERERERERERKvaMBfR/QDA1UKIK4QQBoD/GcA33CellG9JKTdIKS+XUl4O4HsA/p2U8uhwiktERERERERERERERERERERERESrzdAW0UkpLQCfBvA3AH4M4HEp5b8IIf5vIcS/G1a5iIiIiIiIiIiIiIiIiIiIiIiIaHRowzy4lPIvAfxl4LH/M2Lb6wdRJiIiIiIiIiIiIiIiIiIiIiIiIhodw/w6VyIiIiIiIiIiIiIiIiIiIiIiIqKh4iI6IiIiIiIiIiIiIiIiIiIiIiIiGllcREdEREREREREREREREREREREREQji4voiIiIiIiIiIiIiIiIiIiIiIiIaGRxER0RERERERERERERERERERERERGNLC6iIyIiIiIiIiIiIiIiIiIiIiIiopHFRXREREREREREREREREREREREREQ0sriIjoiIiIiIiIiIiIiIiIiIiIiIiEYWF9ERERERERERERERERERERERERHRyOIiOiIiIiIiIiIiIiIiIiIiIiIiIhpZXERHREREREREREREREREREREREREI4uL6IiIiIiIiIiIiIiIiIiIiIiIiGhkcREdERERERERERERERERERERERERjSwuoiMiIiIiIiIiIiIiIiIiIiIiIqKRxUV0RERERERERERERERERERERERENLK4iI6IiIiIiIiIiIiIiIiIiIiIiIhGFhfRERERERERERERERERERERERER0cjiIjoiIiIiIiIiIiIiIiIiIiIiIiIaWVxER0RERERERERERERERERERERERCOLi+iIiIiIiIiIiIiIiIiIiIiIiIhoZHERHREREREREREREREREREREREREY2soS6iE0J8SAhxXAjxUyHE3SHP/wchxHNCiGeFEN8SQlw2jHISERERERERERERERERERERERHR6jS0RXRCCBXAlwH8CoAtAH5dCLElsNkPAcxKKbcCOAzgS4MtJREREREREREREREREREREREREa1mw/wkuncC+KmU8iUpZRXAnwL4Vf8GUsq/l1Iu1X/9HoDpAZeRiIiIiIiIiIiIiIiIiIiIiIiIVrFhLqK7BMBJ3++n6o9F+U0AfxX2hBDiU0KIo0KIo3Nzcz0sItHgMI4p7RjDlHaMYUo7xjClHWOY0o4xTKsB45jSjjFMaccYprRjDFPaMYYp7RjDlHaMYRq2YS6iEyGPydANhdgNYBbAvWHPSykfkv8/e28fJ0V15/t/TlVXdfd0D8wwzEwiQxQNQibeURhUwF2DmqhZSVwDghseFBMYJIn7cxXj/SXsNUtyb5S4bh4uDpAbFNENCHF1dWNMjGiuQAIjC6sIKioOD84MzQzM9FN1VZ37R08V/VDVDzM9/fh9v16+HLqez/l+T53vp875Hs6ncc6n1dfX5/AWCSJ/kB0TpQ7ZMFHqkA0TpQ7ZMFHqkA0TpQ7ZMFEOkB0TpQ7ZMFHqkA0TpQ7ZMFHqkA0TpQ7ZMFHqkA0ThcZRwGsfAzA+5t9NAE4k7sQY+yKA7wH4Auc8nKd7IwiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCICqAQmai2wNgImNsAmNMBnAbgOdjd2CMTQGwDsBXOefdBbhHgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIoowp2CA6zrkK4NsAfgfgHQBbOedvM8b+iTH21cHd1gDwAniGMfafjLHnbU5HEARBEARBEARBEARBEARBEARBEARBEARBEARBEFlTyOVcwTn/DwD/kfDbP8b8/cW83xRBEARBEARBEARBEARBEARBEARBEARBEARBEARRMRRyOVeCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCIAiCKCg0iI4gCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIKoWGgQHUEQBEEQBEEQBEEQBEEQBEEQBEEQBEEQBEEQBFGx0CA6giAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIomJxFPoG8o2uc/j8ChRVg+wQUeeRIQis0LdFEEQJQu1J4aE6IAoF2R5RzpB9E0TxQP5IlAtky0SlQrZfPlBdEgRBEERm0DuTqETI7vMPlTlRKpCtlh4VNYhO1zkOd/Vj6aa9ONYbRFOtGxsWT8OkxmoyVIIgsoLak8JDdUAUCrI9opwh+yaI4oH8kSgXyJaJSoVsv3yguiQIgiCIzKB3JlGJkN3nHypzolQgWy1NKmo5V59fMQ0UAI71BrF00174/EqB74wgiFKD2pPCQ3VAFAqyPaKcIfsmiOKB/JEoF8iWiUqFbL98oLokCIIgiMygdyZRiZDd5x8qc6JUIFstTSoqE52iaqaBGhzrDUJRtQLdEUEQpQq1J4WH6oAoFGR7RDlD9k0QxQP5I1EukC0TlQrZfvlAdUmUIxc88GKhb4EgiDKE3plEJUJ2n3+ozIlSgWy1NKmoTHSyQ0RTrTvut6ZaN2SHWKA7IgiiVKH2pPBQHRCFgmyPKGfIvgmieCB/JMoFsmWiUiHbLx+oLgmCIAgiM+idSVQiZPf5h8qcKBXIVkuTihpEV+eRsWHxNNNQjTWH6zxyge+MIIhSg9qTwkN1QBQKsj2inCH7JojigfyRKBfIlolKhWy/fKC6JAiCIIjMoHcmUYmQ3ecfKnOiVCBbLU1sl3NljHk55wM22y7inB8ZudsaGQSBYVJjNZ5dcRUUVYPsEFHnkSEIrNC3RhBEiUHtSeGhOiAKBdkeUc6QfRNE8UD+SJQLZMtEpUK2Xz5QXRIEQRBEZtA7k6hEyO7zD5U5USqQrZYmtoPoAOxnjP13zvlW4wfGmAvA9wHMBzBxpG9uJBAEhvpqZ6FvgyCIMoDak8JDdUAUCrI9opwh+yaI4oH8kSgXyJaJSoVsv3yguiQIgiCIzKB3JlGJkN3nHypzolQgWy09Ui3nej2AJYyx3zPGPssYuxnAfwFwApiSl7sjCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgiBHENhPd4HKtX2aMrQRwCMAnAG7gnL+dr5sbKUIhFb6gAsYAzgGdczgdIsZ6nZQ6kSh6DPtVdQ6HwFDnluFypUoqSRAEkTuoDYpC5UAQpQ35MDES6DqHz68MKTV/7LGSKEDVdGiDcarxtygIEBkgCALqPDIAoC+oIKho0DiHyyFCdjAEwhoiOofTIUDXedTORQENXiccjlTz6AiCyDWqqqN7IIyIpsMhMDgdAvyKBrckQuccYVU3fVXjHE5JxFhPaWpTse0YYwwAh84BSWBgDFA0Dklg0DkHwCAyIKjqEAUGtyyg1l2az00Q1K8kCIIgCGvoHUlYMRztpJDE6TYOAbIY1V9UnUMUGFySgFBEN+19bJUMp5PsPVMS7aLWLeF0UEEookFkDG5ZRI073lZ0neOUP2zuI4kCOOembqbrPC4ed0kCRjkl9CvqOS0tRQyeqa0Wo00X4z2VKrFl6ZIFaBqgaDo0ncMtiXCIDEElqoOIDHBKAgKKDoCDc0AbbCOqZAGMMfjDubM9YuSwbb0ZYw4AKwF8A8AKAH8D4GeMsRWc88N5ur+cEwqpeM/nx89feRe3z5yA724/gGO9QTTVurFh0TRM+lQ1GSFRtBj2e9fmDtNuH1vYiol1Hgo+CCLPVKIIQG1QFCoHgsg/uWxzyYeJkUDXOQ539WPppr3n4svF0zCpMX18GXtsvdeJ+2+chJXbDsT9bZzzoTkteGLnh7j/xskAgJ7+cNz2xxa24uevvIuefiXp2PaFrZg8eD8kxBDlRjbidtzg0zSD1ozz6roObXASpjAojMYOaLW6tqrqONTVj+Ux75u1C6bitUPduHpSA7719JuWfp5p21FMWLWBRnu15KoJqPPK2L63E7MmN8Iti1j76vtYctUEPPzSYfQMhLFmbgsaqiPwOh0IqTokGvhLlAjZ9isrUUcgCIIghk4pvzdIeyGsGI52kotrxw6CcwjRgS+Z6CKJ9319cwO+c+1E3PXUm+f+fd3FSfZ+8VgPDaRLgarq6BkIg4Oj1x9BW0L5/fyVd/HywW401bqxZm4LGke5UFMlIahocMsius6EsfTJc7a0Zm6LGW9+f3YzzgbVpHg8XK3j+Okg7tm6P6UNZmqrhbRpO4rxnkqVRM32wa82I6BocRrOo/Muxf/8j0PoGQjjl7e3ItLP8fM/vpc0DmntgqkY5Xbgf774jmnX6xa1ot7rTBr8ebi7H21PdlD9FZBUatQ+AOMAtHLO13PO/xbAowCeY4z9r7zcXY4JhVQENBU1bgnfu6kZnxlThfmtTQCAY71BLH1yL3x+pcB3SRD2+IIKOj48haeXTseOlbPw9NLp6PjwFHxBsluiMohENBzvDeCoz4/jvQFEIlpB7sMQAeav340vrNmB+et34z2fH6GQWpD7yRe+oGIGgkD03XnX5o6Ka4OoLSaIZEayfc51m0ttGTES+PyKKU4Bg/Hlpsziy9hjl8+6yBRils+6CBvf+BCrZjdjy7LpWDW7GU/s/BBzWsej83QQvf4IQhEdj9x6qSm6/PyVd7HyhslYc2sLQhEd9V6neT/LN3egeyCMw139uGXtG7jqoVdxy9o3cLirH7rOR7R8iJFH1zl6+sM43htAT384ZZ1msm825ys0hqiZzq51neMjnx+HP+nH/PW7cfXDO/C1tTttfcA47/eePYD3e/yYt24X/uqhVzFv3S683+PH9549ED2fzbW7B8KmYA9E/XDFU2/i5qlN+NbTbyb5vLFPpm1HMWHVBn53+wHMaR2PldsO4HhvCHOnfQYrtx1Arz9i/r581kU41hvEym0H8PHpIA6e7McX1uzAvHW7cKirH6qqj+h9q6qOE31BHPX5caIvmHS9UvIDojBkExtWqo5AEARBnCMb7aTU3xukvRBWDEc7GQ6JMePX1u7E4U/68e2n96XURcx4oC8ASRTw2IKp2PyNK/C9m5oRVnWsmt2MKeNrMKd1vKW9nwpUnr2niqFit3WfDaF7IITjfUH4wxp++sq7SeU3p3W8+e+V2w7gqC+A/Z1ncNVDr2J/5xlzAF3sPka8qajcMh7XNJgD6IzfrWwwU1stlE2nohjvqVRJ1GxP+xOqMbEAACAASURBVCNJGs49W/eb2oZDEHHXU29iTut4cwCdsd8v/vgenA4Rq2Z/Hn/4h6vx46/9N/z0D+/i7RNnTY3pcFc/evxhdJ8Nx+m9VH/5J9Xw5zs45x2xP3DOX2CM/QHA90f2tkaGgKbieF84aSQ4ADzyh/dwrDcIRS3MgAyCyASXJKB1wlh8fcPuOBt2STQ7myh/IhENh7oHktrwyQ1eSJKY13uxEwG2LJuOcWU8k07VufnMBsd6g1Ar7GMStcUEEc9It8+5bnOpLSNGAkXVLO0qk/gy9tgat2T+fd5oV9KsxYfmtGBUjN3fs/Utc9sjt14KpyRgyeN74vb/ye8OY19nH471BhHRdEsh7dkVV6G+2pmr4iDyTDazjDPZt9RmLdsJxIl27fMrOOoLYNVzb2XkA8Z5V81uThI/v7v9AFbNbk55voimW7YLnHNLn4/dp9S0Kbs20Hi+KlmEKDDz7yqI5nZj3ypZjDt2+eYObG2bgfNq3CNyz1aZAo2MnY7BJXZLyQ+IwpBNbFipOgJBEAQRJVvtpNTfG6S9EFYMRzsZDlYx48pt0Ziu7ckOy5jQLtv2pl0fxWXVNnQasvfUWgKApG1r5rbElWNPv4J9nX0AEBcvGv+OjRmrZNGyzI14U2Cw3K5x67Yp0QYztdVC2XQqivGeSpVEzRawtitjm2F3iVrPlPE1WHHNZ/HRKX9cFrtHbr0UVXJ04N2q2c149PeHcfd1F5s6U6y2S/WXX2y/9iYOoIuhFUDtyNzOyBJUdPz8lXfjZvL//JV3cfPUaDa6plo3ZEd+B2IQRDaEItY2HIqM7OxsgsgndjNVugfClsJB90A47/dYqSKAQ2Boqo3/iNVU64ajwj4iUVtMEPHkon1ONUsx120utWXESCA7REu7yiS+jD22Lxgx/3ZJouXAHZckwi07zGVDjG33PrMfvf5I0v733zgJ6xa1YtvyGXAIzMxOZ0BCWumTzSzjTPYt1lnLdu+KbMRtO6HdygeM89oNdKtxSynPZ/e+YYxZ+nzsPqWmTdm1gcbzBRQNms7Nv43f+4IRc1/jd4NjvUGo2sj1r60yBS6P6b/Y+UFfUKHsdGXEcLMNhiK6ZT/YKjasVB2BIAiiHBnK+yNb7aTU3xukvRBWDEc7GQ6pJv0YfyfGhOmybS+fdRHqvU4oqo5ql4SNd1yOKeNr4p6r0uw9VQz1ydkQ/GHVzN5nDGQ0Mnh9d3v0b4PYeNH4d2zMaBdLG/voHJbbRWbdNiXaYKa2WiibTkUx3lOpkqjZBhTNVvuYMr4Gkihg2/IZGOORcX1zg7nP8lkXodcii929z+yHSzo3yXBO6/gkneK72w/g7usmUv3lmYxSpjDGLmOMPcwY+wjADwG8M6J3NUIwBtw+cwJWv3AQ89fvxuoXDuL2mRPgEKIGvmHRNNR55ELfJkHYYmfDrLL6YUQZk2oppmISDipVBKhzy3hsYav57MaMyTp3Zb07qS0miHiG2z6nW4Yv120utWXESFDnkbFh8bQ4u9qwOLP4MvbY9h1HsGZuC5pq3RgIq5a+FVA0iIL1zMfYWbkAUO91wut0YPULBzG3fRfmr9+N+2+clCTskhBT2mQzyziTfYtx1nKqd0U24rad4GnlA8Z57cT5VAKq7BDhcYpYu2BqXLuwdsFUPPfmMfzvr09N8nljn0zbjmLCqg18aE4Ltnd0Ys3cFoyrdWHb3o+xZm4Laj2S+Xv7jiNmBoKGahntO46Y52yqdcMhjlymZ7tMgcbAPSs/qPc6cbIvREtilwmZLgWdimz6wZWqIxAEQZQbQ31/ZKudlPp7g7QXworhaCfDIdWkH+PvxJgwXbbt80a7cN8Nk7Dqubcw6yc7sOq5t0y9xbD3Ue7K0lpSxVDz1u3C3PZdWP3CQdx3wyRzIF3sQEbDDppq3XhswVRs7+g0/71mbgvGeCQzZmzfcQSPzrs0zpZi401RAB6ziMdFEUnHWdlgprZaKJtORTHeU6mSqNmO8UhJGs6j8y7FKwe7cP+Nk/B3G3ZjbvsuLHl8D7597URzIF2dR7adhDkQVs32qM4jW+5zwVgP1V+esc35yxi7GMBtAP4OgA/AFgCMc35Nnu4t53AOy5n8W5ZNx/blM1Ff7aQlGYiiJpUNE0Q5kGopJkM4iO1AFEo4MESAxPT75S4CuFwOTKzzYMuy6VB1DofAUOeW4SqBJQRyCbXFBBHPcNvndMvw5brNpbaMGAkEgWFSYzWeXXEVFFWD7BBR55Ezii+NY3+zYiaCigbGgKe+eSUEZu1b1S4Hjg/6QuK2gBI/yOnu6yYmZaxbue0AVt98CZY8voeEtDLB+CCQaA+pBoal2jeb8+WLVO8KQ9RMXDLGStw+v64Ka+a2xC2fYecDxnkf/f1hPDSnJWlp5Sd2fogHvvy5lNeurVLx+JIrIAoMssjgEBi+ctk4uKTo7GRF1SE7BGxdNh0a53BKIsZ6Sk+bSmwDGWNg4PjHr3weksDAGLBo5gRIAoPOOR786ufhYAz/cttlEBiDPxyBKAroGczE0lQbXVq1wTtyy0xLomDdfxkcuGflB3dfNxFtCbPCaUns0iXTpaBTkU0/uFJ1BIIgiHJjqO+PbLWTUn9vkPZCWDEc7WQ4WMWMxlKidjGhXVxsTLJySaKl3vLrZdPBAFQ5BXjk0vDXXJFpDPXd7dGldFe/cDBuIGPjKBdeWzkLDMBTuz/C4hkX4Ls3fg5OhwC3LOBMUDVjxp6BMOq8TvzmrpkIRjRwHk1+MBBW8cCXP4df//kobr18vNkGiQKDMUfrwoZo26RxwCUJljF4prZaKJtORTHeU6mSWJYuWYCmAb9eNh26zuGSRDhEhr//4kTMX787zs5XPPUmtiybju/PbobIGN7tGrBuUwIRU2P6/k3Nlvt4ZJHqL8+k6q0cAvAnAF/hnL8PAIyxe/JyVyMEBzDzwjosvfpCiAKDpnNseP0DcA40jnYV+vYIIi0c1hknaM5zZqiqju6BMCKaDkkU0OB1wuEYuZntRPYwcGy84/K4NnprxzEoqoYGr9NSOBjJDyt2VLII4HI5MK4CnjMVtv2JQt8YQeSIbN+Xw22f02U8Gok2l9oyYiQQBDbkQRSCwNBQ7YKuc/j8ChRVg1sWsWnJFTh6OoAqOZpBa/wYN0a7HfDIXqxb2GoKkU21bqxb1Aqn49ygkKZaNyaM9eBYbxBTxtdg+ayLUOOW0BeMYPKnq/HGd68hIa1MiB3sNad1POo8MhqqnagdnNFttW+qAWd2+9S6JfT0hwsiwqZ6V2Qjbl9Q50FNlZRWMDf2n9RYjR/d0gJd17G1bQY452CMQWTAj25pMcvN7trjaqrifFrVOSSRQRSEsvO9TNtAXec45Y9++HAIDKrOMcolwS0L5rs+H/F6g9eJ9oWt5lIpiQP3rPzAaFNjKXSWxuFSyTpJLrJuNnideGrplYioHAIDdA5IDmbZD65kHYEgCKKcGOr7I1vtJN17oxTe4aS9EFYMRzsZzjVjY0bJIcAhMPzi61Ns48c6j4xNd16Bo75zmkytR8LaV9/Hmrkt5uoBiXqLyADZIWC0q/QmR2VDrH5llGFsDFXvdeLu6ybiwnoPVs1uRvuOI9jX2QfgXNa52IGM6xa2wuuKlhsAfPPqzybF2LVV3DL2jr2X2ioZjAGLZ06AWxYxyimhNxiBompwCDF17Un/jJnaaiFsOh3FeE+lSiZleVwJWPYNAMAjiwhFdEwY68GmO6/Aj3/7Dl4+2G1qufVeJzjn+NEtLah1S0k6xKY7rwAYcLw3QDpuHknVe5mDaCa6VxljLwH4NYCc1ghj7EYAPwUgAvgl5/zHCdudADYBaEU0G958zvlHQ72e1yli4YzzseTxPabhrV0wFV5XZaVTJUoXp83MByctv5QWVdVxqKs/SSCf3FhddMFlpaKqOk6eDccJCWsXTEVtlQOyQ4QkiZjc4I0TDhq8TkhSYeyfRIDKxbY/4aS2mCh9hvK+HG77nEnGI2pziUohVpjRdY6us2Gseu6t+IFMVc7B/VxJ4iEQP5iHg+P65gbcPnNCXBatdYta8blPjSLRpUwQBIaJ9V78/RcvRtuTHXH2MqmxOq6eMxlwZrVPrVvCez0DSQPrEs8/UqR7V2Qjbo/xODMSzLM5r90+JFwnYwwatqI2w3rJBQ6HgMmN1djaNgOqpsOR8PHZyg84eNFlaRwOla6T5CLrJmMM/UE1qQzZKOt2kfq0BEEQpc9Q3x9D0U7s3huV/g4niKFgGZuliT/Cqh6nyaxb1Ir/Nee/gYEhqGgVq7cYy1pb6QOTGqvx/Levwsm+UNzEz4fmtOAnvzuMfZ19aKp147waN1ySYDuQ0SqOtouv08XdFJMTI41d38Ati+g6G47zlXULW/GDmy+BKDDLSZ2xOoRx/OK1OwuixVUyjHPrvCmMMQfnXGWMeQD8LaLLul4L4AkAz3LOXx7WhRkTAbwL4EsAjgHYA+DvOOcHY/ZZAaCFc76cMXYbgFs45/NTnXfatGl87969lttO9AUxb92uJAOO7bRWyQLAUPYjxIkhkTeDsLNjXec49MlZLIv5MLJ+USsml3mHLBfY+f/Wthk4r8ZdwDvLKwW34VTY1dGvl03HeaPdZOMjRCikwhdUSmUmfFHYMLUnRCxZ+lBR2HAqCmHfqYSXXLT9JdbO5Z0hlE9e7HioNpxvjNn/AAfn0WylzpgBbT6/Al3XoXGA82h2JQAIRTSIQnRpR8khQNU4QqoGpyhA54A+mO3Kyh9/s2ImRAYEIzq0mDhWBxBSdAgCwDkD5xwuWcBASMOCX/456TyJyw1ZzSLOxAdTHZe4rdZ9bgZwumsM9X4yoCxtuKc/jFvWvpG2nov1/OkY6XdF4rUSbQ9AVnZ+Nhwxl2fmHBAG/6/qHLJDgK7zaLsrCmCMQ9dh7lss7TCQuR2rqo4zIQXggCgC/rCOapeA/pAOxgBZFKDpHBE9mq1LZNEMdMayOpLAMKZKLtgEqUzJpx3mgwLGNUVhw7moT9syXDYDHJz6n+VLUdjwcLnggRdH5LyJfPTjm/JyHSIrysKGh8pwNYJi6A+QNgmgBOK6YsgWaGSBDkU0iIzBLYuocecmts42bkp1XKr7id3fyAou2GT2TqdB1LolnA4oCEY0OB3n9BeRMQgMCKnRunI6GEIRPW55RuCcn31qVHQlgeNngpZ6y9Zl01GffoJxUdiwrnP0BRUEFQ0ajy5POdYTjfETfx/jls3ytCqbLcumRycfcY6vPbYzabuxhOuGxdPQOMqJoBJvO8b1jNhY0zkEgUEWBdS6JfSFVDOToCwy+MNatP6Ec3G1SxIQjuhQOYckCBBS2Es6cqVLWdmw5BCg6hxc56ZmmKgnxNZHkcabRWHDucaqHTkdVBCOaBAYg+RgUDVAZNFJVYqmQ2BArz8SN3C0fWErxnhkm3hxOlyD7TGA+BUMBjXiaLvEcKvN+/5To1xJmRiLOVNdPu5TUVT0+M/18eo9MmR5aPpaqqP+AmAq59wP4CkATzHGxgC4FcADAIY1iA7AFQDe55x/AACMsV8DuBnAwZh9bgbw4ODf2wD8gjHGuN3IvzRENN0ylWJY1XHtI6+Z6ZPHeiUMhAIYV1NVlEZGVC6KEu0crL75EjN9sOQQoCgaiXFpsPN/VdMLdEeZUwzBVj6wqyN9sKNM5J5QSMV7Pn/SMgIT6zzUpqTAzlYjJdCeELml3HxIVfWCvC8zXYZvKJRbHeUaKp/hYcz+/9kr7ybNPN6weBqcDgE//u07SduM5Sp6BsJ45NZL4XWKaNv8Juq9Ttx/4ySs3Bbd9/f3XG0dv0aiywcZ+zXVurHxjmnoC0Sw4U8fJF3vyW9ckXa5IeNDUOxyoEFFxadHuUyR0so3U31AAhC37frmBtx93cVx2RLsPjYVw4epYsZKgA3btN+5WmYyF8seDoeRfFfEYmd7ToeAxb/6S0Z2fv+Nk9HTH8bGNz7E7TMn4ImdH+Ibf3Uh7n1mf5KfN9W68S/zL8P614+Y+37nuotLqh1WVR0nzgajA3clASd6I4hEIjgdkPDzV97FP1x/MQTG4BtQsPGND7Hims8iouq4Z+v+uHbxbLWKC2qrinogXS7ssJji+1LWSXJBtvVpVXe2saGumx9UqX9FEARRPOQiBh5ufyAXfYFKf4eXAsWQLdAqtlkztwWNo1y4oM4zrFgq27gpdgJSNrG+1f4PzWnBEzs/xD1fmpTy3FYaRPvCVvzslXfR068kxWWGVlNfLePb104E57D0s57+MDRdBx8cgGfdF+Q40R/CedWuoo5vdJ3jI58fXWdDcWWx6c4rACDu97a/vgCLZk5ARNPBGLN87u7+MB7b8T7++998znL75z5Vjd+smImBkIqv/uINy+sZcXSijja22oltez7Guj99hOubG/DtaydixVNvxtnF64e7cNOl4+J+f+TWS/F//u8HSfaSSdnkQpeyOs8vvj4FEVW31PDaF7ZC03V86+l9pIcVgEzakbULpuLF/ccx+9JxGAirpo9c39yAp5dOh6rpOOoLYNW/vYXv3WTtCyFVR89AGH2uCABg8a/+gnqvE///30yO00rsNN0TfUGcCUYwsd6bk1Uj7Aa45XIg6UjrvIqi4nBPch9vUr0n3UA6S1K9qZPumHN+mnO+jnN+bdZXSmYcgM6Yfx8b/M1yH865CuAMgLqkG2VsGWNsL2Nsb09Pj+0FJVFAU238LIymWjfY4JMe6w3irs0dUDUgrEaNgiDyRSZ27AsqWLJxD5Y8vgfz1+/Gksf3YMnGPfAFy9NWQyEVx3sDOOrz43hvAKGQOuRz2fm/QyzuwWhGsDVv3S58Yc0OzFu3C4e6+qGqxRcQZ9oWW6GqOkSBZVRHubSLQlEsz+ALKmaHAjj3HizXNiUdmdqww85WKYipOIrNh4bbDh/q6kdE4ynb4pFqv4y0++Nqq1BfnbvZdcVWR8VGsZXPcGy4EHQPhLF8cwfmtI43BS8gWo5LN+3FUV/ActvKbQewfNZFONYbxL3P7Ed3v4JjvUEsn3WRKbwAQJUsWvqjwFjcfsd6gzjWG8I9W/dbXq/rbNgmDmb4+HTUl08NhPHnIz341jUTsfqFg5jbvgs/fPEgDnUP4Ja1b+Cqh17FLWvfwDsnzyISOTdoyudXTAEk9tl9fiVp25zW8abolLhvIqnOW8wMx4Z1naOnP4zjvQH09Ieh69ZzBw3hyaiXeet24f0eP070hWzr2eqciddTVR09/WF0nYmKcYnHGEtT2J2/uz+E0/74+9d1bv728Wk/uvtDts+VSRnk+l1hdT072zvqC2Rs552no35u+OOc1vG495n9ln5+rDeI/2/Lf8btW+j3VLZ23D0QhqJyRDQgogF3be5A4+gq3DXYPjoEEcd7Q2aZ9PojpigMnGsXj50ODmb2zIzY+uvuD6EvcM7WTvYF0XUmiLOhcFy/RVHUpGNT+ZsVhh02eJ1QVA2dvQEc7w3EtY12FFt8X6o6STqyseFM2xW7urMrQ5ExbFk2Ha+tnIUty6YjEolQ/5PImFLrExNEIsVsw+li4Ew1j6H2S3PVF0j1Di8W3bmUyYUNG3pBrK0t39yRVX93uFjFNiu3HcBRX2DYsXW2cVO64+zux2p/I25Kd24rDcLQcKziMkOrmdM6HiueetNWk6nzyjgbVPH1X/4Z73YNWO7zQY8fZwMRnA4Ut77m8ys46gvElUW91zmYoQ8IRXTUe52Y19qE2ZeOw23rd+Oan7yGD3v8NmXjxP03Toamw3K7JAqIqLo50BKIlv1RX8C8Dzsd7djpIOZO+wwAmHWUaBdzp30m6fd7n9lvaS/pyJUuZXUeIya2etblmztw2h8pOT0s1xSqL5FJO7LiqTcxd9pncGpAifOdlw9240j3ABb/6i9Y8vge7Ovsg8+vWPrCUV8Ap/0R0/YNvShRK/noVMDyeOM+uwfCae3U0D+s9D5Dt3vn5Nk4/ffwYN8kVn+M/b27P2Rqyqf96TWVfOi8PX7rPl7PEK+RShWpZ4z9g91/Q7paPFa9ysQSzmQfcM7Xc86ncc6n1dfX217QKTKsXTDVNDZjtKjHeW704bHeIHQeXV4iXzOqCQLIzI5V3XpWg5qF4FsqGLPC5q/fjS+s2YH563fjPZ9/yEFfg9eJ9oWtcf7fvrAVDd6RX3poOBRDsJUpmbbFVnQPhPHkzg+T2ujHEuoo13ZRCIrpGSqpTcmETG3Y5RAs+xOuMswQSaSm2HxouO3w8s0dWP/akST7Nt6XxdR+ZUqx1VGxUWzlMxwbLgTG7P8at2RZjlWyaLutxi3F7QcgaV/GgIfmtMT540NzWsBY8mzoKlm0vJcp42vgkgSsmduS5NcPPv8Wrn446stHfX5c2/wpfOvpc2KjMZgnth/atrkDJ86GzI88qbKTJW6zKwuruLvQWc+GylBtOHFgnCFMWYlQdh8ROOe29Zx4TqvrHerqxy9ffx/v9/gxb92upGPqPDI2LJ6W1P8xzv+1tTtx+JN+fPvpfeZxx/sCOPxJP+av342rH94R3cfmubIpg1xgdz072zP8NPY3OztP9MdY20/VJsT+v5DvqWztODK4dInAosvtGPdvPI/A4tso4+9YjDLO9LkT6+9ra3fi49NB/ODf38bVD+/Aret2IazpOOoLxfVbDvf4EQ6rw7a1SETDoe6BuHMf6h5IO5Cu2OL7UtVJ0jES/Qm7unM6mGUZauBx9iFJEqpdFC8SmVFqfWKCSKSYbThVDJwPzSNXfQG7d/gYl1Ryuk0xkgsbLoZsgalim+HG1tnGTemOs7sfu/2NuCnVuVPFXplsC0W0JE1mzdwWdJ4OmEs2tu84Yqnb/OyV93DXU28Wvb6mqFpcfDZlfA3uu2ES7tj4F3zxn1/Dqufewn03TMJd11yEu2IGp/3slfeS9IfHFkzFD194G1/859fx8EvvWOrL3f0hnDwTstS07HQt4JxtiYMDlu32EQXrDHlW9pKOXOlSVufJ5FmHe91Sp1B9iUzbEVFgltpG4m/tO47gsQRfMNoIw+7tdGEg6muJx7cvbEX7jiPmOyWVnRrayfeePWCp933k82N/5xmzTTOOTzVA78SZIL62dqepKR/+JHqeVJpKPnTeXH/nSJW7TgTgxcitZ3wMwPiYfzcBOGGzzzHGmAPAaACnh3rBAUXD5l1HsfGOyyEKDJrOseH1D/Ctaz977iYGZ/ZHBteeJohiwsh+FNsIlGv2I7tZYVuWTce4ISx/4XAImNxYja1tM6BqOhwlsixqMQRb+SCi6Vj3p4/QG1Dj2ujRbkdcHeXaLgpBMT1DJbUpuSRVfyIpXS5R1pSTDxnvm60dxwDAtG+nQ0BjtQsOh4Cu/lDRtF+ZUk51NBJQ+QwPY/Z/XzBiWY4BRYOi6Zbb+oKRuP0AJJ1H58ATOz/EqtnNqHFL6AtG8MTOD/E/vvL5pHMGFM3yXpbPugjffnof6r1O8zx1XicefukdvHywG0DUl+/Zuh+PL4lfIsBOKOrpD0MSBZxX4zazkyU+nxFLx26zKyeruDvdecsNuxmZz664CvXV8YNZ7IQngTH8+LeHsGXZdAAAYwwPPv9WXD0b5wSQdL3lmzuw8Y7LseTxPbb30TjKidU3X4IqWcQYj4w1vzsUd/6V2w5g1exmtD3ZgaWb9uLxJVckze63e65syiAX2F1va9sMW3+OJZWdywltQ6zt2/lB4r6l1A5LooCIFi0fefC9Yrxf+oIR1HmdcW2UUT5WZZzpc1vV34qn3sSq2c14+WA3jvUGwcBs+y3DtbXugbB9n6i2yva4YovvS1UnKQR2decPa0llKIsMf7t2p6V9jHJbnZ0gCILIF6li4HxotrnqC9i9w0tRtylXJJs+bz4z/trF1QFFG3ZsnercsSTG8dnG+nb7G3FTqnOnir2Mv1NtO3EmhO0dnVg1uxkX1XvQeTqIh186jAe+PNk8bl9nH37yu8NYNbsZExu8eK97AD/53WHs6+wDEJ1kVMzIDtGM1Y71RjNhJWZG++72A3jqm1fGldW+zj48/NJh/OvS6VBUHRxAr18x9QHj/xvvuByn/QoCioZRbge+vuHPWDW72VLTAuLr1sq2jPK020fTecb2kknZ5EKXsjqPnYYX+6yxlLMeVmxk2o5oOo/zHYPE3/Z19iEU0U0trS8YwU9+dxg9A+Gkera6Vs9AGANh1dR0A4qGapcD+zr7zHdKKjs1tJNVs5stV1Ex7suqb2LXZ+nuD8edZ+W2A1h98yWodkm2mko+dN5cf+dI9bY+yTn/J875D6z+G9LV4tkDYCJjbAJjTAZwG4DnE/Z5HsDtg3/PBfBHzvmQ3zgOgWHnBz586dHXce0jr+FLj76OnR/4zMIzsh45RMDpYKjzyEO9FEGMCDVuAY8lzDB6bGEratzlJ3CORGYUhyP6se8zdR6cV+MuCWG4XJdXScR4zq0dx8w2esnje5CYyb7YMuYMhWJ6hjq3bNmm1Lnp/ZeKdP0JonIoJx+Kfd8YbfHiX/0FjDHzfVlM7VemlFMdjQRUPsPDmP2/vaMzaebxhsXTcH5dleW2NXNb0L7jCJpq3Xjk1kvRUC1HZxLuOBI3k3ffUR++c93FWP3CQcxfvxurXziI71x3MVxycma5ploXHp13adL16jwyjvUGsa+zD21PdmD++t3wDYRNQdPgWG8QIotfbsMQb2Jpqo0uGWB85LHKTrZh8TTUeeSkbds7OpOyJRj7JpLqvOVINjMy7ZZV7QtG0DMQhuwQMa62Cpxzy3q2yp5mbLObtW3cR1DRsOTxPZi/fjdOxwjksfvGZlkULLIm2j1XvrMP2pYBg6XtnV9XlbGdjx8T9XPDH7d3dOKRWy+19POmWjf+Zf5lcfuWWjvc4HVCdjBIIiCJwGMLW9F1JoDHBttHVdcwrtZllkmtR8Kj8y5NahebxrgzzoCWKiOFgcbt+y3DtbWhijWGYwAAIABJREFU9omKMb4vRZ2kEKSqu8Qy9CvW9lnMfWaCKDYueODFrP8jiExIFQPnQ/PIZV/A6h1eirpNuVIMGX+t4uo1c1twfl3VsGNru5jdLm5Kd5zd/Vjtb8RN6c5tpUEYGo5VXGZoNds7OrF2wVRs7+jE7TMnYPULB+EbUMzlGRO1kn2dfVj9wkEc9QXQ9mSHOYCuqdad8VLPhaLOI+P8uiqzLFJl3Upsu3oGwghFNJwaCMM3EIaeMHzj5YPdOO1XcO8z+9FQ7cSZQHSJUqvsfbUeCWO9clwcbRUvbtv7MQCYdZRoF9v2fpz0+yO3XmppL5mUTS50KavzGDGx1bO2L2zFGI9UMXpYsZFJO7J2wVRs2/uxabNx+uwYd5Le4ZIEjHI7cO8z+9H2ZAd6BsJYM7cFYwbtvnawvtt3HEk69rGFrdj4xodoe7ID9z6zH3VeGf/7j++bdtHgdaa0U0M7SZX10E7/dVj4vaELW50nlaaSD5233mPdx6sf4jWY3Zg0xtg+zvmUId9pJhdn7G8A/AuiWe9+xTn/EWPsnwDs5Zw/zxhzAXgSwBREM9Ddxjn/INU5p02bxvfu3Wu57VR/CCfOhMz1sA1DP2+0CwFFG0y9KAAMGO1yFv3Ljcg7eTMIOzs+3htAjVtAX1CHqnM4BGb+O9Vs51LkeG8A89fvThoxnG5md7mhqjoOdfWbad6NTtTkxuqhiNsFt2E7Mn3OfNtFKKTCF1RMf6tzy3ANc9Zesdn2SDzjCFIUNpyqPzG22pWvWySKhCx9qChs2IpM2uGRbL9Gsi0qsXYu7wyhfPJix9nacKFQVR3dA2EwcBjfJWSHaIoAPr8CXdehcYBzDmnw40goEo0/HQKD5BCgahwhVYdTZNA5oHMOQWBwSQyBcLTvLwoM+476cNXEBmg6R1jVoQ/+7pKi51A0DgYOxhg0ziEyluS3G++4HKueeyvJlx+ddxkUTTdnJl7f3IDvXHexmcnAECWf2PkhHvzqJTivJipK6DqHz69AUTXz2Y1YOnFbrVtCbzBiuW8iqc47TIrOhnv6w7hl7RtJdWKVGctYisHIpBVbL/d8aRImNVZDEFjKcwKw3JaYiS7xPmLPuW5RK1a/cDBpXyMTXVOtG48vuQJ3bPxLRs9lnLve68TyWReZM2wvHT8aYzzD/9CUaE+iAHz1F9blU+eRccofRiiiQ2SAWxYxynnOdg0/DkY0yKIAlxz1U40DLocAp8QQUnREdA6RRbNKCgzgPDr4SnYI0HUebXdFAYxx6Hp0CWfOUTTtMJC5HauqjjMhBeCAKAL+sI5ql4D+kA7GAFkUoOncLBOBMag6h6ZH2zppsL0bGGzvJJHBKQmodVtrc3b2bdgfAPzp/mvwdxus+y1W/ZlsMtENtU+U4/i+lCk6G05HNnVXbDE/MSKUnA1bka+BZx/9+KasjxnKvQ3lOhVMWdjwULGLgfPRfo90X6CQ76ACaC9FEdelilsNvaCQGX91nSfFNjXu3MTWVs8OIG0cn22sH7s/YywaTwhCRudO1CBq3RJOBxSEIlo0LhvUX0TGIDAgrEbryulgCEV0CAKDrkf1HiO2MJY8NbQTY6CWUxLw7af3mb+tmduCi+q9aBhl+72gaGy4L6ggqGjgAG6zaEP+bcVMnDwbjtOH1i6Yihf3H8f0i84ttbnk8T1xx/162XQwRAcQH/UFcM/W/0S914n7b5yET41yQeeAKDCcPBOE1+nA6CoJwmBdcI64eFEHh6ZH71d2CJBEhmBEh845HEI0rtb0aEweVnVog20RExhEgWGsx2mrVdnZYK50KSsblgYHPnOdm5qhYaNnwxEEFS2qMUhC3L0XGUVhw7nGqh05HVQQjugQjLrTotoGYwyKFrU3SWCoq5LhV7XB+uOQBAHC4H4a54io0XbFITAIAHRwnDwTAgNDTZUMhwgwRFe/EgUGtywgoOjmvwUG9PQrqK924lODbYvhv7HXM9pIn1/BLWvfwKrZzZYa3uqbL8HPXnkvqU3bsHgaPj3aiXdO9psrTBh+/4s/vhc3qdY4zyXjRqfUVEZQ5zVRFBU9/nN9kXqPDFkemr6WahDdGM75kJdOLRSpHCkUUtEVCCOicgiDQqbkYKhxi3AJDjid9DGNSEnBg8tQSMV7Pn9cR+Wxha2YWOcpu4/BlfSs6chhsFVwG05FJs+ZT7sYqWuRbQ+LorBhu/5EY5WT6pBIR1HYsB3p2mFqF4lBylIgKTasPq6sXTAVtVUSPj3Kjfe6B/DoHw7jG391Ie59Zn+cSDu22oltez7G1ZMa8cTOD3H7zAlxQsjjSy5Hf0jFd/71nLj76LxLUeORsealQ5jTOh51HhkN1U40ep34ZCCMnv4wfH4F2zs6cfd1F5f6gI+is2GrgXEbFk8zB8RZ7Z/uI0KqcwJI2ta+sBX//p/HcPWkxiThzLiP2HMawnesmLZmbgsefim6LMWGxdPgdYrm0g7pnkvXOT7y+dF1NpTR/tlgVxZOh4DFv/pLRuVjbNN1nuSbxnPXV8u4/8bJ6PUruGdrvF82jnLhgjqP5fFD+HBa1P0JKxLbtOubG3DfDZPgG1CwctsBS3v66W2XobZKxgV1Hkt7SayjWDG3qdaNp5deiTNBNal/cfFYDz44HcjY36yIRDQc6h5IOvfkBi8kKfVyJMXwMbUIKDkbBjKvO+rbVgQlacOJ0CC6iqYsbDjX5Kv9Hsm+QKHeQQW6bsHjumzjOKI0sYpVr29uwPdnN0PTOT46FcDPXnkP9dUyvndTM86GVJzqD+MzY9w4f4wnlX8X3IYTsbPpifVe9PhDULXostSazrFt78eYNbkRVbKIaqcEHRx3bNwT1wb8/JV3zfisfWErJBE47Y/EleN3rp2Iu2KSFWxYNA111RK6zkaX2LaKFRNjv013XoGwqsfdd6I+YaVrkN8Om6Kz4WLDsLd/e7MTX7msKUlLcssifnvgBGZf1hT3Ds1En7Lalmj3E+u9eK9nAI/+/nCSPhyri9V7nbj7uomYMNaDKqeIsYOTWT/y+XHUF0CVHF36+bMNHgyENCx9cq+l5lWCPpT9ILpSJZUjHe8NoOtMAI2jq8wRiF1nAjgT0nFxo5dmAxLpKHhwWWmzWSlzTM4puA3ngnzZRalmXCpzisKG7foTjaOryrItJnJKUdjwcKiEDJ1EWkggyQMn+oKYt25Xkl9sbZsBSRTSziJsqnWbGcWmjK/B8lkXoc4j49OjXfjBv7+NJVdNAGMMY70yRMbwydkQdhzqwu1XXWjOfjUGZJXhgI+itOGRmJE5lCyBsZkTre4j9ji3LELVozNpJYcAh8AQVOKzEJybEZt+BnV3fwhfW7tzWBnCrLDLWvabFTPBwJLKJ1UWv4imW/rmqtnNAKIZ16wyPRqzcu2O39o2w8zumAEl159IbNPWLWqNKyu7zIapZjPH2qLkECCLDP5w/Oxrt1NAf1BLmoWcC3+LRLRo2zh47gavM+0AOsKk5Gw4GyherAjKwoZpEF1FUxY2PBKUg2ZbiGcokK5T8Lgum4ziRGkTm61N5xwCY+gLRlBbJUHTAVXX4RAESCIwENZwakDBhLoqNI5OGeMV3IatsIuVjDIIKdH4ysgQJzkE1Lhl6Do3tSNRYPjBv7+dlK0qMSu4XRwYu1+6LPiA/YoLsZnyrTLsx+5LfjskitKGiwnD3uxWfkjUcGO3GTZp55PpMvTHrraQuFJKptlD7TKOjlSG0wJge9Ol1fsbJqrO8bX2Pyf9vmXZdKh6eQ0mJMoTVeeWa1aXq/26XA6MK7EglRh58mUXI+lvZNuljV1/4rWVs/J/MwSRZ0ai/aq0/g1BZEJE0639QtPBedRnatyS5T5VsghRYOa2fZ19prD4+spZePlgN77xVxdi/vrdSdddPHNC0kcOh0PIZnAPMUQEgeVcsE11TqttmVw/7X164v85xuNM+s2OiGpt94qqZXYCGxRVszxvRNUtP+rZ7a+omu07q8Ytxf07cXuVLKY8XtX0IT1bqZDYphnlZfyWqj2zq38rW6yx+EZrtXpSLvxNkkQaEEVYQvEiQRBE6VIOmm0hnqFSdZ1UcQNRXggCi4ttj/cGcNPP/i+2LJsOAJb6Sqn2/exipcQysNpuaEfHewNxA+iAqG9oCW2FXRwY26bY7RMbg1fJYsp9Yv2S/JbIJ4a9xeq0BlYabuw2wybtfNLOlhPtPp3+kWqb3bEN1bbLVJcNpd0bzBKHwND21xdg7rTPQBSYmW40oGhwlOboSKLCcAgMTbXupFHFZL/nMDJlRDQdUnlkyiBsGOm6Jn8j7LDrT5BtEIQ16dpram8JIhlJFKz9QhTMbX3BiOU+AUWDpnPb469vbsAYj4xty2fA51fwysEuXNfciDqPDMais4tLdPYgMQRGIgPeUJEdomm3sRkUh2uXsec1aKp1Q3ZYZw1LtT/TdMttfcFI9Fgb3w0MZuizO94hlnfMmtim9QUjcWWVqj2zq6eRJBO/KCbfIYoLiheJQpCvrHIEQYw8pfh9o1J1nWzjDKJ8kB2iqa0wxrDxjsvx2/86ieuaG1HjlhBQNLiK3G+HQqZxEmPM1JzadxzBvs4+M+5NjAvt2o50saIRgwNAQNFS7hPrl+S3RD4x7M1Op02l4coOMaXP2dmyld0nQnpGesqvBU9BnVvG7MuasOTxPbj2kdew5PE9mH1ZEyZ/2ouxVXKhb48g0lLnlvHYwlY01UZH8xvryte5yX6BaIB5qKsf89btwhfW7MC8dbtwqKsfqlres/orkXzUNfkbYYddf4JsgyCSyaS9pvaWIJJp8DrRnuAX7Qtb0eB1os4jY8Oiadje0YlHbr00bp81c1swfowb2/Z+jIfmtMRt27B4Guo9Mu6+7mIseXwP5rbvwvaOTiyccT5Wv3AQc9t3Yd66XTjc1Q+9zDMGEFF0neNwVz9uWfsGrnroVdyy9o2C1n+dR8aGxdNwfXMD7rthUs7s0jhvoj8Yy1Bks7+Vb66Z24L2HUewvaMT48e48ei8ZL88v67K9njDt8uZxOfe3tGJcbUurJkbbafadxwx/wai5fLT2y4zyy2fZOIXxeY7RHFB8SJBEAQxVEr1+0al6jrZxhlE+VDrlkxt5Yv//BpWPfcWFs44H9s7OjF//W6seu6tweUTyyc+yCZOmrduF+a278LqFw7ivhsm4frmBmxYPA0NXmecz2zv6EyKj439jN+tYsW1C6Zie0en+e/z66qSfNGI0xP9kvyWyCeGvW3b+7GlllTrkSy3bVg8DbVuKaXPWdmynd3HQnpGZjDOy6tAUq2LfKIviHnrdiWNyNy6bAbOq6XlaYi05G0Ibio7DoVU+IIKVJ3DITDUuWW4SjzFeK6w9fG2GbQEVZSisOFckK+6Jn8rOorChqmtIYZBUdhwPsnUX6i9LSnyYsfFYsOFxMhAoGo6HAkZCHSd49RAGJqug/Po8jmiwOCWRYxySugNRqDrOjQOcM7NWYU+v4Jb1r5h+uS6Ra1Y/cLBJB99dsVVOV9atIggGx6kpz8cZw9A4etf1zk+ORuyfHcM576ynWWbav9Y35REAbLEEFJ0yA4RtW4JZ8MRhBQtzi9r3NbHJ/p2hpRkf0JVdfQMZlURBAaPLCCiAYqmQ9c5XJKIiKZD0zkcogCnxFDrduZ9NnQmflGMvlNilKQNZwrFixVB0dlwMWei++jHN2V9zFCeZyjXqWCKzoaJKKX8DimArlMUcR1l86lM7OKBVbOb0fZkh/nvNPFBUdhwpgwnTtraNgOfGuWCILAkn6l1RzWsRB+KjZtdUjSbVkjVITLA4xShaBwRVTePAWCeV3IIcAgMQcXaL8lvc0ZJ2XChMOyNgSOicVMTkQQGHYAoMIxxy0l+kKjhAsk+F2vL6ezegPSMOGxtuKK+TEU03WZt7eKexUEQsbhcDoyjj8qW2Pq4NnQfj0S0aEdtMPhr8DohSZTWNx+kKvuRqGsryN8IK/JlfwSRT0bqfZepv1B7SxDJOByC7YcSQWBoGOVK+j1RCKxPEEwUVYvzyRq3ZOmjwYiG470BEhOLgKGIu5kek2gPQLT+FVXL6TNkc0+CwMA5z/l9CQLLSgxMtb+lb3rO/TnG4Yz7d0bHVwAOh4BPl8BzZ+IXufAd0hrKF4oXCYIgip9ifQ+X8jukUnWdbOMMonQwYlirCYp28UCNW4r790jE1oUiVQzU0x+GomrQbGJ5zrkZ/1v5jJUPDSVuTjqPTVxOfkvkk0ztrb7aabY7J88Ebf0pqKjo6Yepq9nZva5z0zdjdbh8aoGlTEX1aKSEtbYBmGtwEwRR+uTaxyMRDYe6B3DX5g4c6w2aacgnN3iLIqguZ9KVPbXnRCEh+yPKjZF835G/EET+MNLxL9201/TlDYunYVJjtSlWyg4xzif7ghFLHz3RF8Rt63dbnoPIH5nU6XCOSbQHIFr/siO3sU62z5Gv+yIIKzKxv+HaKGkN5Q31fwmCIIqbYn4P0zuEIIoDI4Z99PeHcfvMCfju9gNxsWydV7b01b5gJO7f5RTDSg7r9knVOeYPZrXaeMflFMsTxBBJ1M7s/OmdT/qx+oWDKXW1VDocaW6ZUVE9L1lk2NJ2Jf50/zXYsXIW/nT/NdjSdiVkkT4GEKWDquo40RfEUZ8fJ/qCUNXin4WULxq8zqR1w9sXtqLBO7QZBd0DYTOYBqIjse/a3IHugfCQ79EY+X28N4Ce/jCtMW5DurKPresp42vwbytm4qlvXgmdc3SfDZFfECMK9SeIciOT913s+6v7bAjdZ0MZ9UVy/W4miEokzv/6Qzjtt+5L+vyKKY4AUV9+9PeH8cnZkLl/rVvChsXTTJ/c3tGJtQumxvnomrkt4Jyb51i6aS98fiXPT00A1nWarj6yOabOI2PTnVdg4x2XY8uy6dh4x+XYdOcV5lIoI/EcU8bXYNXsZvjDKj45G4Ku86QYKdFOzQ8VOb4vgrCiziOntb9M9klFbN9rXmsTNt5xOTyyGM2IE9OvIv2guLDT4xLrySWxpHfr2gVTKV4kCIIoEkZC888VdhpKvUfOqk9A35AIYnj0BRV8ciaE+2+cDEXVUT+oYxrxtSwyPPXNK7Ft+Qz869Ir8etl0/HkN67AaLeEKeNryjKGdQgMa+a2JPVxf/TiQdR7nVi3qBU1VRI23XkFrm9uMPdJVw7pYh6KiYhSQ9c5uvtD+Pi0H8d7Azjtz8xuE7UzSWR4YlCzM9qVh+a0oH3HkbT6YCptcLh6RqVQUZnoGANO+9WkGSbnjaaRlURpoKo6DnX1Y3mMDbcvbMXkxmo4HBU1JtYSh0PA5MZqbG2bAVXT4RAFNHidQy4bVbdOlapm0UlTVR3dA2FENB1uSYRvQMHSJzPPJFGppCt7o65/c9dM9AyE0fbkOZ9YM7cFZ6uduGCMh/yCGBGoP0GUG6na3KM+v+X7a83cFjz80mH0DIRT9kVy/W4miErDauZgrP+tW9SKsR4ZgiAkpeOfMr4Gt8+cgHnrdsX1PSfWe/HsiqvMNP0//cN7WDW7GTVuCX3BCB5+6TAe+PJk8zzZpPQfytKjhD3plliwKu9sl2UIqzpWPfdWnI1kQjZ1bdzTlPE1uO+GSXGz+DfdeQXCqp40OzbWTsmWiHwiCAyTGqtt7c+I8Ue7HdiybDoAZG2jRt9rXmsTFs44H0se35Ok8QgCyzoTJZEbYnUcabDvCsBSj5vU4MX7p/xx9dS+sBWvHerGxjsuhygwaDrHhtc/wLeu/SzGFvjZCIIgiNxo/iOFlYZS75GT3jWp+gT0DYkghoeuc5zsC8XFyQ/NacFPfncY+zr7UO914nhvCG2bO1DvdeL+Gyfhvmf2x/nbp0c7UVvlLNl+u1W8H1Q0PPzS4Tj9iAHo6VeS4vx1C1vxg5svga5zuGX7bybpstYPJTs/QRQSOx23cZQLF9R5UtptKu2sfWEr+kNRzXZfZx+A1FpfKm0wneaRD0pBP66oHlMoolvOMAlFaBYGURp0D4TN4AeI2vDyIcySikQ0HO8N4KgvOgo6Eimfda4dDgHn1bjxmToPzqtxDyswdAjMHIlt0FTrhiNTYXwwYJ23bhe+sGYH3j5x1hyAAFBmDztUVc+o7B0OAYwxcwAdEC3TldsOoPN0MMkvytnuifxC/Qmi3LBrcwXGbN9fK7cdwPJZF2XUF8nlu5kgypFUs2pPDYSTZg7G+l/bkx34z2NncMvaN6DpPM6Xl8+6yBRcjGOXbtqL3mAE9dVOjKutguwQsfMDH9qe7MD89bvR9mQHegbCQ1qCxBCKbln7Bq566FXcsvYNHO7qp1nCw8BYYiEWoz7syttYYiXxGMZYUl2ky1pnZZu6znHaH8Y7J89mXNfGc1jZ5FFfwPIeYu20vrp0Pz4QpYkgMEv7i43xZ/74VcxfvxunAxEwcGha5rGA0fdaevWFWPHUm5Yaz1AyURLDJ1HHmbduFw519afU4xLrafnmDlzSVIMvPfo6rn3kNXzp0dex8wNfxloSQRAEAFzwwItD+o9ITaa6cyFJ1FD6QmpWfQK7d1ZXf4j0cILIAJ9fQVuCD313e1SHAYC7r5tobl8+6yKs3HYgyd8GwlrJ+lsqrcFIaGHoR6cGFNx93cSkOL9tcwcOnezHVQ+9iq/+4g28c/Is+gJhdPeH4vSFdDGP3fZT/sJnDiUIK6xsduW2AzjqC1i+t2N1N8aYrXa2fPD7ozGADkit16bSEwF7zSMflIp+XFFfsIp5hglBZEJE061tOAuxNhLRcKh7APPX78YX1uzA/PW7cah7oGQ7dCNJg9eJxxLSpz+WxRJ0iQFrlSxmlRWiUukeCOP3b5/MqOztRtNXyWKcX5DdE7mE+hNEuWH3vvu3N48BsH9/1bgl8+9s+iIEQZwjlXCgqjr8iprW/2rcEo71BvHDFw9i3aJzvlznkdP2Pa1S+LcvbMX2jk7z35mm9KcBH7kn1RILduXtEFjSMQ/NacGDz7+VJEqlmplqZ5sf+fzY33km6aNCqro2nsPKJilGIkoJq4/Sd23uQF9QzSq+NPpeosBsNZ5ss0oSucFu4IGtHmcTG14w1jNkLYkgCIIYObLRnYuFbPsEdu+ssKqTHk4QGWDnczVuCU21bkwY6zG3G3pM4r49/WH0BJSS9LdstIYxHgkXjK2y/UZn/N22uQOn/RF8be3OOH0hXftmtz0Q1opuwA1BAKm/WSe+txN1tweffwtrF0y11XM/U1eV8RKsxbxka6noxxW1nKsxwyTW8IpphglBpEMSBWsbFjMfD9s9ELbMoLRl2XSMq63K+T2XMpIkYnKDF1uWTYeqczgEhgavE5KUOhNH7NIfsXXVF4xY1l8mmT0qiYim48EXDuHeL07E00ung3MOxhg8sgBJEuPK165dDyhanF+Q3RO5hPoTRLnBGENTjTPuffebjmN45A/vAbB/fxmZqrLtixAEcQ474eA3K2Yiour46FQgrf8Zf798sBs/uPkSbFk2HRq3f1/F9j2tUvjXuiX86JYW/I+vZJdSnwZ85J5USyzYlfdASEXjKCe2ts3Aib4gfH7FXHbm4Ml+PLviKtRXRz8QGjNTE22EMYaTZ4KWtrn65kuyHvhmPMcnZ0NJ1wsoGsVIRMlg91FaYDDjy8ZqV9qsu4bW0D0QttV47PQf8o2Rxa6OU8WAVr+7HELWWhJBEAQx8qTTnYeC1TLguczAb9dnt+sT2PUhNJ2THk4QGWDnc021bjy74ipwcHO7nWbq8ysY45HRPRAuOX+z0xqCioaJ9V480zYDEU2HIDC4ZQGahpS6lXH8ab+SpC9sbZuRsn2zq4sPT/nhcTpMbYMgigUjm5zVN2vJIaCnP2zqexw8Tnd7+WA3AOD7sz9veY6TfUFzOeWmWjc+Pdptq9cWw5KtdpSKflxRg+jcsoDfrJgBReXQdA5RYJAdjD56EyVDg9eJ9oWt5qxYI1NENrOkijGD0kgHmsNBksSsOrmqquPE2SAUlUMSGf7wD1/A+teOYGvHMbTvOII1c1vM9M7FNPK70MTagEcWseO+WdA5RziiYcPrH2DnBz5sbZthLq1i+MD1zQ1JPrFmbgvqq51xflGMdk+ULtSfIMqJ2HZ18zevxKw1O7DzgWvw5ZbzcNOl50HTOV76r5P4P7e3QhRECAzQOaDpGh7Y/taQ+iIEQZwjVjiYMr4Gy2ddhBq3BCWig4PjZ6+8h4fmtOCJnR9iTut41HlkjPHIaN9xxMww9pPfHQYQFVQOnezHksf3oKnWjU13XoFNd16Bo74AqmQRAUXD+XVVSX1PI4W/sZRGV38IskNMKcZYke3HHSIzjPpJxK683/mkH9s7OvGPsz8PTefwyCLuv3ESBMbQF4xA189lDjVmphqindGmP/j8W/jGX11oaZsN1U7LwXCJdW3YU6xY96lRrqTrnV9XlfQbxUhEsZLqo7QRXx7q6sfkxuqMBtI1VrtsNR5hMNOD4Rttf30BFs2cgICi4kSfnhPdpJi1mHyRWAZep3Xb6pIEy7pySQJ+eXsrHDH9ZFXXwMFL7oMpQRBEJWC8yx/5w3vmxMGmWje2ts0Y0vkStWrj/ZBJXyBTrPrsqfrLVt+Q1i6Yig2vf5BSDy90v6DQ1ycIAzufa6x2oTcYgaLq+PWy6TgTjCCoaPjXpVei62zUdhmLxu89/WGIAivJ7092WoPkEPBez4BZLtc3N2DV7M+Dgw9O5uT42BfApl0fYclVE/DwS4dNLaHOI2O0W8KU8TXmcpTHeoPgnKf8ZlrnkbFuYauZCT9WB/vF16cUongIIiUiAx659VLc+8x+008e+PLnIDCGcETH6hfexssHu9FU68aWZdPNQXF9wQjadxzBywe7sfKGSdh05xU47Vfg8yvY3tGJ22dOMCfIGgN6BYFZam+GlmunJxaaUtGPK2oQnUMEjvcpZjYiI03zhXXFZ0AEYYXDIWByY3V0MJGmwzF+Xo77AAAgAElEQVSEYGIoGZRCIRW+oGLOoK1zy3C5Mm8+IhEN3QNhyxm4+Qg088mZkIIzgQjueurNuCAVAHZ+4EN9tRO/uWsmIppeVCO/C0msDcy8sA4LZ5yPFQnl9+3rPosGrzNpaRVjZH7s7BdZFDCmSo6zn7EeEW+uug5BRTft8Pdvn6RBT8SQsOtPnE/9CaIEiW1Xq10i/vK969B1Nhxv3wumwi078PUNf46z+XWLpkLVQcImQQwD2SGi7a8vwNenX4D+kJrUJ66vlvHcvuP41jUT8a2nz/WP1i1sxT9cfzF8fgX33zjJFGpP9gUxZXwNJjZ4ITsYzgRVrHrurXPHLWpFbzAMBoagck5gAYDDXf1xIvG6Ra0YV+OCP3wuQ93poIJQRIPIGNyyiBr3ub5sth93rEgl/lQCsc/vkgUoEQ4l4SNS7D5Pf/NK/PDFg3j5YLc5wEZgQFPNxbhtw+64SSY//u0h9AyEsW5RK+qrXRAEljQzlTGGB59/Cy8f7Mac1vFoqnVb9s8fWzAVG5dcjiUb95ii4PdvaoaiaujpD6PWLcWJ64YtTGqsxsR6b1I8KwhsRGfHprOrxO21bmnw40hl2mGlkkq3MEj1UdrI4rh8cwe2ts3AeTVu87xnQhGE1WgsavgzEO2HNVTLcRnLXFK0TxXrnwwcJ8+Gcdv63XF9sUn1Hsjy0KTdctNihoJdGTy99Mq4fm/7wlaMdskY7ZKT2q++oIKIyvHNp/4S10bKWWZpHq7uRhAEUapk8v7NJblIUhBL90AYez88haeXTofOOQTG8MeDJzHGI5t9geGSbTYZ4xvSlmXTEVZ1aDpHbZUDf//FifjWtZ+FQ2AIhdS490yh+wWFvj5BJMaEE+u9ps9JDgFOB8Ph7n60PRk/mOuJnR9iyVUT8Oybx3HL1HG4b3DgjBEnNBbhAJZ0xGo781ub8LdTm6Bzjoiqo6bKgY13XA5N16FoHH8Xozs8NKcFm3Z9hL//4sWo9/4/9r48zorySvup9a69bwjdssli64fQF7GBREEMSSYYx4BgoCGisohbEgdxJsMk8zHOFyTEaCJrokYWhYBLRhM3FEwERBqUUQQJAjZrd99e71rr90fdqq66t+r27YXu2931/H7+pGt5q+q95z3vOc973nNYjBuUjRtHFGHZziNGnsvLQgYQ4SXIAHI9DDbdPQ6iLKM2wKEo02HQbwUZDmy6ZxxEScbFxgh+9dZx1ASiHQq46evck43LB5Ik8Ye/f4XfzBqNK7KcaAjxmPdsi6/4zOwyZLsUnrQ+xGPF60e1c6vvuA5eB42oIGPx5gOGcZPporGmogyiKEOUZciyDJ4X8WVNwKCXVO7NivMiCAIUobynGTdWG4xqvK/HQYETlbHfmeNE1TFPvnNc2zBemOFAjovpcNudCUKWe14UdDKMHTtWPnjwoOm5c/UhzIoRTirUSE+bnLCRArpsBk0mxx0Fz4s4Vh1ICP4YWeg1dVAjEQEn/MGE64fleVIaM60973xDGDPX70sYl3rSuSchmZ4hCKK7Aw3SUob1MvDOT27E/Oc/tpSHM/4gblq1O6GND5ZOwpV5HtP2IxEBdVEO/gDfbjm2kTZICxlONs7tbAM2WkFayLAeql595JZhmHR1EVwMhbueO5Ag38/PH4dbfr3HcOylheUosktT9UV0iRxfTns4naDayrXNUS3YTUVxjgtb7r0BX9UETc+tuO1aPL3rBB79zgjDrt3f/8gHXgSCUUEjcPX3/eqO6yDLMp54UyEe1UC3H6zdm3DtpnvG4afbPkVBBouHpgxPyP5blOnEoDyPRqJ0hIiUJDkhkM+M/OkEpKUM67+/wOtI+F3XVfgwotCLf9QGE4Id+2U6cKFRCYpePq1UI+FUFOe4sHxaKRZtqtR2rJrtRj1XH8LEle8DULLP/fz7pch2saj4w0cJ7W1dcANOVgeRHyPA9UF2W++9AbN/n3jPy0smwB/guuI3Nu1Xs2fGn59aWpgg65f7HduBtLMnejrawpPos6TwoowNe05i71d+rK3wYfcXl7D63ROaf8rzIs43R9AY4g1jRCXB9YFaa+aUYfO+M9j7lT9h0diKN3lpYTn6pVA+1gzdzMWkhQxb9cG2heUI85KWWY6hCfTPcJravJ3hG3aUd7PRLUgLGdZj0GNvdMHbtA+nf/m9Nt/Tnu9pz3PSGe39TVPsh7SQ4bauU3QW1Lm8vUkK9PAHIjjfGE34hv5ZDuR5nZ385m2D2r/5Xhq1ASHpPNPdazTtfH5a+nU2eh6S+YwAcNofBEUSmGPi46r+93N3XW+6rrVj8Xj0y+p5MixJMpqjHL6ui2i6Y2ppIR6cMhz3tcI7rHj9KFbcdi2GFHhM+2zFbdfCyZAaJ6X3g1ZOH4WrCjwoynKZ/i5q4OJPvjWi3T56F3JPfQFpK8PdBUmScdofxKWmCCK8ZMrnbr7nBsiyjLnPmq/BmK3NbF1wA87Vhw084YsLyrVAVv21Ly+ZgMIMp/Y+qYwjs+vWzCnD7947oWXO68xxIghSQmByN41Dy4f1qRD+ZOX8/GGum97Kho2uBcNQGFnoxbaF5dizdBK2LSxP6pj6wy3ZlgBlzNy3uTLlMVMdiJreXx2IAgB4UTIfl6KU0FZPQDI90z/bZe+cMoFeBiiSSCoPasp9PYpzXKCT7PL2hzmIIjokxzZs6GGXB7bRm6Dq1dvKinHf5kqQBEzlO953OVsfBhcjnm3YsNF+1AQVW9vNUqZjrykiYHC+x/Scm6WweNJQjUBRj9Mkhfs2VyLfy5rel+9lsXTHESyeNBRn68NY8MJBhHnR9Fp/gMPiSUMx3VdiyAZ8NkbcnPGH4A+22FNqqYABOW4UZDjaRHz4gy3BVeozFrxw0NB+b4b++81+18UxHyq+jxZtqkSEl7TfJ9vFmP6W2bEdnYr+Fk3fQS2pAACHqxoQiAiWdg8vyJj//Mc43xjRgoPUc9XNUdN7IrzU5b9xa3IVf95M1vuSHPZVtMZb6EHTJPpnu9A/0wkXQ+L+m6/C1gXlWgCd3j+tDkTBC3LCGFm8uRKcIBuOLdlyCAtuHGIY7yqseJOO2GK9jYtpD6z6ICpIuOXXe3Dz6j245dd7MGfjR5b93Bm+YUd5Nxs2bNjoqWjL/NuZUOfyK/M8HebrI7xk+g0RvvvnU3UdSJKIVueZ7rYLuvv5Nvo2kvmM/iCHM/4QeNHc5lP9b6t1LU7omTJMkgQCEdGgO6b7SrS/k/EOKl9VY8ELuFnKwEnp/aBlO49AjJnRZr/Lsp1H8IvvX9uhQJu+zj3ZuLwgSQJeJ42lO45Ycr1ibAOy1RqMFQcXzxNGBfO5U2+DWI2j6b6SpNyYOjan+0q0vztznNSHeS2A7nK03xnoU9EcahlLPdQylvbCt42+BIahMCDHjYF5HgzIcSfd2dVRQrC1+9sTFJXOSKZnbJhDLwOiJCeVBzXlvnpNKin3BUlJb2sHPdnoLNjj3EZvgqpXpZietNLD8eqyOMcFUZJtPWrDRgehLhY0hHnTsXe+IYxTtUHTcw1h3pS4VAkXijCfryiCSAiqoizmNn+QQ7aLsSRI3SxlGZDVVnCCeSBfZ7Wf7tB/v1V/J/Ot1ONWstQQ5rV/W5U9UUsqqPc7GQoUAdP2VLPH7F39Qc5C9szJwMv5G7cmV/Hnrfq+r8hhX0V7eA+GoVCU4URzRMDsjfu1ADq9fypIcps2KFCxg/GLxla8iSjJ7V5c7m1cTHuQrF/1SCYLVm0wbehHe5OWDRs2+ip6g/5L929gGCqld+xuu6C7n2+jbyOZz8gJItystV+s+t9WfGpPzmwWrzv0vnIy3kH9vxUv0BDmTTkp9d9qBUWr30WW5Q71a1/nnmxcfvBCcq6XJKx5M0tdYsIrWOklSjc8rORdHc9W3Jj+Ov3ffYkD7lMWiMdBYm1c8MXaCh/cDtJe+LZhwwIdDRZp7f72BEWlMxw0ibVzyox6Zk4ZHHYGOksUeh2abt74wVdYE9d/enmgaRIjizLw2v0T8OGyydhy7w3I9bBJ26dJwnIR2db9NtoDK3vC47DHuY2eiVwPCwLAuz+9CYfP1CXo4bUVPjA0YTi2Zk4Zdhz82tajNmx0EOpiwbrdJ7Fy+ijDOFs/1wffldm4pn8m1sfNO0/OvA6ZThp5XhbP3XU9xpRka21KsnLNxaYIVs0wtrlqxihcbIokBlVRZMLYXzl9FHZWVqEhzFsSPyFOtAzIaiv0WdD0z+is9tMd+u+36u9kvpV63EyWVs0YhXW7T2rlEfIs7GeSJDCiKAN/fmAiPlw2GQUZDlAUgSdnXpfQXm2As3zXnZVVWD/XKLMb542Fi+3637g1uYo/b9X3fUUO+yray3uo/un2RePxwdJJ2L5ovKEMK00Smk6Ob9tqg4L2bN2isd5nVs+vmVOGYxcaQJEEzviDON8QhtCGTBe9jYtpD8z6YG2FDzsOfm24LpksdEY/2pu0bNiw0VfRG/Rfsm9oz/x8OZBKP3e3XdDdz7fRt5HMZ2RpCiFORG2AS+BXVM5k1YxR2PjBVwnn18wpA9OD9Fk84nWH3ldet/skVt9xnWl/rKvwIdNJ49BpfwKXtXJ6Czeh56T0fpCVrx5/vr3o69yTjcsPVcbW7T6JZ2Yncq21AQ47K6tMubuNH3yVcHxdhQ+1gcSgOzO9tGrGKLhYKuFd9NAHvLY23tRxqv7dlzhgQo3o7S1IVhc5EhHQxPPgBBmiJIMiCbA0AYok4KFoOJ10F7+tjR6GLrN20qm+dyQi4IQ/qKXpVUnFYXmelMYMz4s4Vh1IuF9fQlaIlSARRAk0RaLQ6+ixZU+jUQEXg0rJFpJQFjEZmkA/jwMOBw0plqaVE5QFxzwP25W7UdJKhvV9kemi0BgWwQkSnAwJTpBBEMrCcrw8CIKEY5eatTJLqhGhX6zQIxIRUBfl4A/wSeXQRo9AWsiwlT2RyTC2LWGjNaSFDKsw06dr5pTh2PlGlA3KA0MRYEgCuS4WQVFAmJPACRJEScaOg19j2uhiW4/2TXSJHKeTPXw5oR+HBV4HHpoyDIPyPfCwFHLdLE7UBLDghYPaucH5HrhZCk0RHnc997E2dlfNGIUn3jyOmkAULy64AY1hAU/v+hJLJl+F+iAPN6sQvzkeBmve/wfmTxysXb9x3lgMK/DiQlMYvCijLlayZGdlFRZ8cwj++y/HUJDB4qEpww36YtWMUSjKdGJQnqdT7FlJknH8UrNWPkANvOpImQ4LpKUM67+/wOvAo98ZoZVqUO3dEYVe/KM2mNBHV+V7cLw6oP0+U0sL8dh3r9bsaRdLIsJJKfkfZr/Ds3eNRV2QBwEgxIkozGDBSzIe2HrY9F1VmaoP8wa/B0BX/cZJv0f/zPjzU0sLE2T9cr9jO5BW9kRvQCq8RXvbPd8cQWOI10q6quM500Vj9saPDDbY5n1nsPcrv6l/y3ECqoOcZosdu9CAQQWZhndO5heboRu5mLSQYUGQcL4pDE7H37A0ARnAHN1v05osdLQfO8q72egWpIUM6zHosTe64G3ah9O//F6b72nP97TnOemM9v6mKfZDWsjw5Zp/uxJW31B5qha/eP1YSvPz5V4vSHWe6e41mnY8Py39Ohs9D8l8RgA47Q8izAkQJBl1QR75GQ5kuxiEOAEOWilbKskySIJAQYYDjWEe2W4GDE2gwO1Ips/SWobj9dvU0kI8OGW44e/l066BIElgSBIkCXxdF8bKvx5DTSCKtRU+jCjwoCEiIMiJOF0bxNO7TqAmEDVwWGvnlGFTzA9K5qt3lm/ehdxTX0Bay3B3QS9jE4bkYfGkoQau9bHvXo2oIOHVQ1WYNW4g6oIcIryIDCeN+2M8m54DFmUJzREB/gBn4N6en389oryI6mZO430H5rkNPK2ZvK+cPgp/3HsKP/nWiKTjbc2cMvzuvRN4+2h1p4+TNBqHlg/rU0F05xvCePuz87i59ArIsgyCIPDe0QuYek1/9I+LdrRhwwRp4Vx2BiIRAf4wB0GSQZME8lxsUmKurdfHg+dFxQGK3V/oTWo49micbwhj5vp9hjSkxTkubF80Hv0ynd09KaSNDJtNkH9aXA5JQqtykqyP+2eb6/JIREAoFgCSrP2OyrqNy460kGFLe+La/pYyaMNGDGkhwyqs9Om2heWQZODVQ2exrfIsNs4bi8E57pT0aEdg6+AeA5sg6WSoiwW8KIEmCXgcFDKdLPxBDrev+dB0jM7asD/h+EsLy8FSJAJRAdsOnMGscQPhZEjIMiDJMiiSBEUABEmAJgmEOeMijSTJaAhzCHMiRBlw0iRoquW6HBeDujCHCC+BIgAXSyHb1bkLPF204SRtZVj//U6WBMfLilzoFpGs+kiVozAngiSAi00RjZR+ZclEFGSklsWhpjlqKXcRXkJ9iIMsA/2znSAIAqIkg6WUbFuSLLf6u13u39isfQBJnxl/T46LMQ0AbO2aVL6ZocmE8dfa+5kgreyJ3gKOE1ATbLFDMlwUvKzy+6i6kSQByAR4SQJFEHCyJAgk6lM9eF5EY4RHVFBsKHWjGABtoZgiCThoEkFONN1IpkK/uEyRhOlckMwvTiOkhQy3Zguri6E0BRRltK0cV1fzbja6HGkhw3rYQXR2EJ2KnhREB6TfukF79HH8N7zz+QX84vVj2vlk83NXLSL30nkmbf06Gz0PyfxUlSsRBAmcJEOSZDgZKsa1SBAkoDnCg6FIRHgR5xsj2FlZhZ/feg2uyEpqQ6a9DMfrN4+DRIiTIcsyGJpElBfxj+ogBuW5MffZAwl2tcpFCIKES80RXGiMIMKLoEgCJEEgxIm4pn8meNF805/e/2EoEixDJN0gmCofoD9GEAQoAiBJsr3++WVBNydkSRVpL8OXC63JmotVyqnzgqT8W5QR4UWQJAGWIpHjYlAT5Az+6JiSbDw0ZRhKcl2oqguj9IoMkKRybTPHKRyhpCT2qA9yyPOycDsoRDgJoiwrwaw6WdbrMCt5j+fGaoNRjff1OChwovINXcXfdYOMWz6wW6wkgiByAWwDMAjAaQAzZVmuj7tmNIC1ADIBiAAel2V5W0eey4sSfvH6MYMBCwCTr+6HS40RFGQ40lEB2bBhQEcdnvbscHU6aQzogFPFMBQG5LjbfX9PAi9KpnW8BVGCP8hpDrF6fMELB9u0qNVbYNYXd6zbj1eWTMSAVvoiWR9bwemkgQgQBqcdE0UZTEs5d8PYeOvhCWgIS7gUjIIOcymNs/hFlwIPC5bt8WSEDRMksyds9D1EowJqQy1jP9/NwuHoGWPfSp/yogyaIvD9MQNwu68Yh8/4ke91oCDDCXg659mRiAAOAprDLUF5WS5SWwwuznHhrYcn4Fx9ryN5bdgA0EIUSJIEgiAgyTJ4UQmYkmSgMRwCAHObR5ItbCEZgIRf/vUL1DRzKBuUh2wXA5IgMCDbCYKQIUiAKCrBHyQJyJATyBSaJMDqyENRUs7Vh4F8j2Kn+YNKQEmEj5iSL60RIVbnJUnpA1GSwQkiapojpsROa+30VOi/P8IpQZUuljZ8F0kSCb6DJMmoC3PgRQlTfr0nod0wJ6CmGSkFeoU4wVS+LjRGMGPdPu2YGri54vXP43alJg80MXv/ZO9jtYihEHsiKILQAjoBJUvAGX8I2W4GGU4GnCiCIUkIogSSVOa+841hkDriMMfFQIYMUZYRFUT4gxIIEiAIAmFewPlGEU6aRFRQMrJyogRREsGLMmQZCEYFcIIImiQQFSQ4aBJibEwzJAEHQ4IXJcgAwpzSlj+oBCNGBeXvCC9BECWEeQkRXsCAbHePluX2wmyRJhiVwFAEeFGGIMnIdFII6YL6XSyJQFSEh6WUfowdd9BKNoTmiKhd1xxJDFLT+3EUSeCjk7V4+v2TWlkUXpRxqSmC5z48hXu+MQSP/OlTQ0ZON0vhF38+qmX2jF/0ZhgK+RbBAPGL6fmt9A9Nk+if7UJNcxTNEb7NfrENI6xs4agg4ebVLbpUvwBoBjOerjN4t14a8GDDhg0bBqTTukF7M4Pqv+GMP5jAFyabn/Uc+We/mILGGEdyoTHcqXpfnWdUu0flvC8Hf23PX30Pyfz7jvrryQJVJEmCKANyCpu5WoPqp6r+SFV9SAvspSgSogSwDAEhKkMEwImS4iNyMi40RjBrw/6ENu+fPEzxPTKd7Xqn7oBZsI3XSSEQESFIMqK8DAJKIgzESlUPynMDhDl/FeYEnKsXIckyJBkGTkHFB0snwUmTECTFV6cIAiQBRARl41AgopST9DgYBIMiGmIb+4JRARlOCpwgg4sF2YmShB9u/AgFXgf+7Z+uRpRXNkJFeAmNYR4NIR5XFXrgYChwsfdvCHE4Wx/GodN+3PWNIRBFGRFBQkOIg4uhEOVFSFACJ/WcWEd5qNY4jzTJ0tXnIUkymiIcorykBbCxlLJJORyTUVGScLFJ4ZlO+0MgAMgABua6wNIkwpwyfkiCwN4TNbgy34v+WU7IMI6bw1UNmP/8x9i2sBzzn/8Ye5ZOAknIqJMljQ9haRJ1QQ5RQcI/qoMYc2UWGJoEHxVxtjGscEwMhTAn4IpMJxoigrah08VSyuZAikK2k8alpgi42AY9liKR62ZRmNE2fdVWPZ/K9anOKalsgO3IvNBdlstjAHbJsvxLgiAei/29LO6aEIB5siyfIAiiP4BKgiDekmW5ob0PpUkCi745CPMmDDaQai4GqAuJOFsfQv8sV48tI2mj9yMSESBCMBwTISASQcqOiD/MaY4goCjo+zZXYtvC8g4FyrUGfYaNZDurezoYikRxjithxwVNkeAE0dSQ5ASxq1+z29GRvkjWx1aIRARcCrWU2eVFGZfkKIrQMnbUsfHWwxPwlT/aKmESTwhkxwV/qOmq7UC63geGJPDpz6cgEGlZpPM6SQQj9oJVX0M0KuDL2kSCdXi+p0cE0lnrUwJ3xukzhlKyV3fGfB6JCAhLAs7WJ+rabQtvwMSVuw26+NUl4xEV5DYFNtuw0ZVoD2Fw/FIznnznOJZMvgphTsTSHUcwYUgeltw8FFFBAkUqY/StH38TNc1RUCQBJ0OhIIMFCQJ7lk4CRSq0TJiT8OGJalAkAX+Aw39MK4UEoLpJCTIqyGDxdX0YRZkOiJISUFUb4LTSrg9NGY6nd32pBUKpaf3V8gJ60u6Fu8clHIsvAwAkL9lpRQbGlyS1KjEQ34+9hVQ0K7Gd7PtV6Pth+bRSU73+xcVm7Kyswr9/rzRWht4op4KgkNXVzVFkuRhMLS3E20erDW34gy2bUcaUZGPxpKHgBAmPffdqZLtYbK882+4NQmZEmFrKWC97XicNPlbK8r/eOKrJrFpaONfD4FJTBC8eOIPpvhKIkgyKYBEQeax+27y88V+PnMeto4vx9K4vMX/iYPTLckKQlGDSTXtPYf3fTiuZqRbdAFkmQJKERupXN0exfs9JTPeVIM/DItfD4uApP8YOzjOU6nhoynCIkqSV5Ygvf7u2woff6sbgmjllyHByyHb3/o1WhgyYkpLNoKo+DAKA10GDIBhwogSABCcqAYohTgk2pAjgfFMUhVkOuNRAxBgx/c7nF1A2KA9ZbgZ/PnwO2yrPmpZLlSQJx2sSbbmHJg/F0h1H8Pz8caiqC2H5a59h+bRSLYAOUPzXpTuOYH2FD0/9cAyEWBB0U+Ty/3acoPRXW/1iG0YwFIlF3xyEGWOvjC1+yNhx8GuIkrFqSzKuwoqnG5Ln6BDvZpd4tWHDho2uR2esm7TGW8dzKixFaAF0p1Lgo82QatAaxwmmdk9n8tf2/NX3YOWXDyvwJvh0bfXXzdpWOYkn3zmOH00YjGU7j3SIDzBkDadINEZ4rHrzmObjKf4F8MnXdRhckKn561NLC/Ev3x4BF0OhMNOBff86GbIE8LGNOSxJwOkgEIz2nPUCs/5eP9cHOQAs3lxpWpbyRxMG44PjlzB3wmDsWDwe/iCHdbtP4nBVAxZ9cxDI2EYzZaOkhKmlhZjuK0G2iwEvSshxK7xEWJBwoTGClyvP4ge+YvTLcgIy0BjikeVmNPucoRRf75bSfljz/j9we9kAg2/97F1jY/40DVkGNu07hRtHFGlyov5u/6gOGniBQ6f9mD62BKdrg1p7U0sL8eDNw3DnxhaOfOPcsXAwJObFsu51RO6S8Vl2Qpb0gCTJONcQQpgXE0qpPnXnaPzX619o5Yn7ZztBESQKMxygSAL1QQ5RQYYoKwGcZ+vDuFAfxLeuuQKCpFS3YikC7/70RsiyEjTqZikwFAECBPb962RIkrLxixNJNIZ51Ac5reRrPJ9U08zh0e+MwGMv/69p+WWVO3vizeMYNygbt44uNvCPq2aMQlOGA4NyPSmv9bSVl03l+lTnlKmlhXhoynDDN2ycNxYOuuPjU0V3WS23AZgU+/cfAexGXBCdLMtf6v59niCIagAFANodROdxkLh1dLEhyGHNnDJkuRnIkoSKP3yM9XN9uLpfZo8k3W30fogQTIN7huQBqQ5ny8wVUueUdjZz2miaTFgQUknrzg6k6+5sFIVeB9ZV+BK+tdDrQH2YN3WiWbp3lrZNBpamWu0Lq98yWR8D5jIY4AU0hngs2XLIoP89DKU58OrYaAhLrRImVoTAq0vGY+zj7xnvsYPoeh2yXKSFLrYdmL6G2lASgrUHBNEVeFhsufcG1DRHNfLjwSnDsWnvKcM38TyPYJQBJ4RxqZkzyH575nN/WAnEsOo7AJoufnXJeFxo4mwC1kbaoj2BXCoZtnxaKeqDPJa/9hnO1ofx428NQ22AM9grK6ePwgv7TmP+xMF48aOvEwhCNcjqwSnDseL1zzXSJD5A59m/f2UIknvxwBnMnzgY8ycOxuLNlVg1Y5RGZIY4EfMnDsYZf0h7N0AZp2bHlu08guXTSjVCD0BSss+KDNy2sFyz76za1pOFvY1UrA5Ete9Xg9QcNIml3939f90AACAASURBVB6JVW8dw+O3jzL9Ln0/7Dp6Cc/MLsP9W40y9Nrhc/jRhMGY/fuPEuQUAI5XN2PRJp2enVOGBd8cCkmWEeJElOS68MSbSkaNMSXZ+JdvjzAsVjwzuwwnqgMAlOCec/WhlH0xU6K+wgcHQ2L5tFKs230SAHCpKYJ5zxplv6aZw+GqBizdcQRPzhwNB00i08Xg/snDDH2wZk4Z7p98FUKcqMmvShLOLh+Ex984qgW0zv3DAcN9B0434OYRBagLCglz0fn6YMLCzdoKH3751y8M4+3pXV/ih+MG4mx9GMunlWrjE2iZ/5ZPK8XbR6txtj6MJVsOYdvCcmSnR1KWywZJknHaH8SlpgiW7jhiGmD4zOwxiPASHvnTp7FsAiPxk+0tmeCenHkdnDSRYJ+srfCh8lQtvjG8CLeVFWP1uyewZMshPHfX9dheeRaLN1di+6LxkGXZ1B55aWE5Hn35M5AE4GYpnK0PI9vFYMKQPPz4W8MgyYAoyXDQBGoCPGZvNG4+cNMUakM8eFGCK5aFzqpEUXvA0hRe2HsKa+aUGeaMtTq/2EbryHczmDa6GPOf/9jQh8cuGKnnZLyNNU9n/B1U3i3VQIfu2gBrw4YNG30ZKjes2uLZLgYNYR5EG6ZtM956bYUPNAnUNkdwsSmacG7RNwehMQU+2gxtCVqrCSaZWzqJv7bnr74HK798+6LxHfbXzdpWOYnl00o1P6y97Zv5os/MHpOQfXrtnDKMH1qA5qiAP84fB4IAXCwJQNnI+D+fnMW00cUJwSoFGQ4UZTKtvke6wKy/q5uiWP7aZyjwOjCnfKAhOOWZ2WXwOCjcOrrYsBl75fRROHGxEb7B+Ybj6yp8ePQ7I3HXcx9rQTAP3DwsYSO3usFMC2LTnV81YxSmjy3BzoNVWHDjEM2OB4ACryMh0OmZ2WV45v0T2jXzJw6GP8CZ8gJf1QQNfNd0Xwnui/laan8s2HQQK267tsM8VGt8lp2QJT3gjwXCnauPJHChD7/0CZZPK8WiTZXYfexSTAccMOU1Vk4fhUOn/QkxSk/OvA7ZbgbznzduVP7g+CV877oBpvzwopuGosCrbNjS80kADFzTdF9Jwny8dIfCsQ7J9xjGjnpuxW3Xws3SpuXnrfqnLXo+letTnVOm+0oSOOQFL3TO+FTRXdsTi2RZvgAAsf8XJruYIIhxAFgAJzvy0FBUSujQJVsOgRdkMJRCii3aVGnYYW3DRjrBKrinIZz6bgaaJFCcY1SAxTku0Loo35rmKM7Vh1DTHIXUhuA61WmbtWE/blq1G7M27McJfxDVzdGEsbd4cyWqA9GU204FqtF7+5oPMXHl+7h9zYc4fqm5Td/QUdA0iZFFGdi+aDw+WDoJ2xeN14IL8jwsNs4bq/W/unilphjtS2itL5L9lvo+3rN0ErYtLEdhBotLzRFLGeQESTM4gBb9HxVaxo46NlIJNLUiBKKCbHmPjd6DztDFNnoHLndg+uWEJMn4R20Qc37/EWas24cVrx/Fw1OGo3+WA+v/dlq77qUF48AwDGZt2I/GsJAg++2ZzwVJbrXv1PNRwXxxWw3Es2Gju2Hl3CfzKVUyLNvFwM1SKPA6lN29MhLslWU7j2C6rwRLdxzBghuHJATfqOfv21ypEAiThpoG6Ez3lZi22S/TiQKvA14HjRWvH8WsDfux/LXP4HXQyPeyCeNUDSbRQ/0WldBrjeyzOm+lF/Rtm/Wj1XN6GtSygmqQ2orXj2LGun2Y//zH+NGEwZAkcztD7YcxJdm4bcwAPPP+CSyfVoodi8fjhbvH4bXD5zCltMh0gcEf20GuBtCp5+7bcgiBqKDJQ1SQ8J/fvwZTSwuxeNLQhLbu33oIj0wdjke/MwKzNuw39cWs/EyzMbRocyVIgsDOyir8y7dH4JGpw01lf/GkoQAUstzJtGSFVgPo1GuXbDmEXI8joY2lO46AJAhM95WgPsgnnF+y5RAWTxqK28qKTeeiMQPzEvrCary5WSUAR5VnPVQ51//dE2yJjsIf5HDGH9L63Ux/1QV5bQFr8aShWgCdev4n2z8FL5oH5t9cegVIQinvpB6nYrzH2XqlrJqV3lGzvEkyEOJEFOe44GRILLl5KGoDHO6M+ZuBqLlfUB3kMHP9Pvz4pU9wsiaAH6zd26kcRZ6HxT+XleCNT8/hubuux3uP3ISXFpZjZKG3V2b8v1yoDfGWYztV3iaZb/jhssnYs3QSPlw2GX99aAJyPJQpXxGJCAnt9mQ/w4YNGzZ6KmiS0LIUqb7RitePoj7Ipzx3x/PWLy0sx+ufnMW4/34PDWEhYY3kvs2VmBurnNUevW/FUZtxJl0xt9jzV9+DlV+u+rfxx9vir5u1rd/g0tH2zXxRvf+hHrtvyyE0RQTM/cMBTPn1Hsx79gBqmxVfZvHmSswYe6VpsEpVXRhNPWi9IFl/L540NMHPvn/rIcgyTDdDfuuaK0w55Kq6sHZsuq8kgQPT+9NmQWxLdxzBufqIlkla5dO2LSzHEzNGJfiT9289pLUHAP0ynZa8QDzfZSVjqm+vP9ZWHqo1PktNQqJHX03I0p3gBNGwsU4PPY+j1wFmvMaynUcwY+yVCWNF4Tciptda8cMPv/QJfva9qxPeI15ek3FPFElYyrZV+Xmr/mmLHk7l+lTnlMs5PlVcNmaFIIh3CYL4zOS/29rYzhUANgGYL8uy6S9HEMRCgiAOEgRxsKamxrIt3sKAIwloRlxPJt1t9GykIsed4YTkuVisrfAZCMG1FT7kudgOB6FZOW28ZG4wt0UZJwPPK9kOqupD8DpozPIVa89obRHzcoCmSfTPduHKPA/6Z7eUiCZJAiOKMvDKkon4cNlkvLJkYo8tN2WGVHUx0Hpf1AajpgvStUElUIOmSeQ6GTRFlMW9cf/9HmZt2G+QwUduGYatC8qR4aQt9b9+7Khjo7VAUyC1sRh/j430R6oybBNCNlSkoi+6Em3Rw2ZE0cenahHhJexeOgkfPDoZj9wyDCW5Hk2vWjlYbZ3PaZJI2nd/vn98mwKbbfQetEWG0wXtCeRSybCGMA+SIPDod5RFmqhgbjOrxIDVGFTPm5Em+mvM7hFlGQ9NGZZATN635RBcLJ0wTtVgEj3Ub1EJvdbIPqvzVnpB37ZZP1o9pzvQERlWSz+ZBakt23kEooXaU/tBve/to9VYtKkSM9btw7xnD2BKaREKMxyWcmolwyW5LmxbWI7l00rx1Ltf4tjFAB6eMhzDi7ym11+R5UogChe8cBANYQ7VzRF8XRfCZ+ca8cDWwwY/0+r5dUEO030lWLbzCPplOZPKtV6GrcaAKFsHS+V52KSkqJTk3lTGW56HRYhTdIIqz3qocq7/m+nGkpxdpYs5QTT0u9lv19r5ZL+DLMuQZICIpY8pznFpZYDUsmpWeociCayaMQoOmsDAPDdWzRiFDCcDQTQGO5MELMaWpBHoxy80YuuCcuxeOglbF5Tjo5M1HeYoVH/63huvgpulkOFk0D/LBYaxF1WANvDEFou7oiSnzNsks1X1wXKCTKI5LKHyVK1BHipP1ZoGOqSbn2Gja9ETbWIbNvToqTKc52Lxs+8lZrdatLlS46RTgbo2QJME3v38AuaMH4zdSyeBocz9OSmWnbQ9er8tnElXzC29Zf7qqTLcHbDyy1X/Nv54W/x1s7ZVTsLKr2pL+8mCxvRQfAtg9R3XYf1cHwq8Dty35ZC28TBpQEo38ZftkeFk/W3li1lyxRa6SR/g0hp/lSxIhiIJUGQLn6Zs/uZNr9dvhknGC8TzXVYypvr2+mNt5aFa47PshCzpoYdZmjJsrNNDz+Pox0Fbx4pZ0Fdr/G9BhhI8OqYkW3uPeHlNxj2pmwbjz4U4USs/nwraysumcn2qc8rlHJ8qLlv+XFmWb7E6RxDEJYIgrpBl+UIsSK7a4rpMAG8A+HdZlvcnedYGABsAYOzYsZYzkmrA6QVP6TwShOFvm3Sy0fVIRY5pksB7P/0GHAyjlX6I8nybnBCnk8awPA+2LSxPKB9R02weuJRqqksrw8hq7LVFGVuB50Ucqw4kpCwHgNXvnki7wFiSJHpkealUkKouVpGsLyK8+WJahG8J1DAL2lRl8JFbhmHS1UVaWZ13f3qTqQwypCKDakmVzFha+b88PAH/9NReg0zluVoMVEuZJlsWaNZW+FDQRqM2GhVQG2op7ZLvZuHoASUhews6ak/0NELIRseR71aCb+PnoHx39zi0bdHD8UTRI7cMg29wviGl+NoKH5wMqV2nOljtnc/jy1eZ6VqSlJHndSLbRRoCm+3x1jfQVlsiHZBKifp4qGTYk+8cx7/9Uykq/vCRRtqZtaUSA1bneVGKZUySke914LX7JyLHzYClSUQFCSRBIMTxpm0GIgIG5btN7S6GIrBx3lhDaZOBee6EY2pJWT2hF3+N/pz6/fHnzUofmbUd349Wz+kOdESG1e+3soPVbFoqJEmGP8iBE0RsvfcGNEcFFHgdWD6tVCs9tW73SRTnuOBiksup2TmKJNAQ5rGzsgo/mjAYmU4ai2JlLvXXjynJxkNThoGmCPzyB/8HFEnA66DhZChEBAnNEQGPv3HUUN70V28dx5PvHMd/fv9aCJKMlxaWQ5ZlkAQBSZZBEASy3QzyPCwmDMmDw2KcqXJ8ZV6LDKvH4q+V4saP+t6yLKNflhMXGiKWz+if7bKci6zu0f9dkOEAQynXrtt9Eqt0O+TV+e+3u77Url/XzSU5u0oXszSlkdFn68Omv11r51VZtfp9XCyJMCfhwM9uBi8omXD/9uhk0BRQ4HFAkiSt9OuU0isgybJ2X2n/DGQ4WIiiBAdNQpBksCSBWb5iDL8iE9kuBnSMyI1/thqsN7KfF/2zXQnlXimy493am7mFjqIz/LpU+9aqjTwPZeDdojwPJ0PCNzg/QR6cTKItrW7yi/cz9LyEjd6LnmgT27ChR0+VYaeTBhmKtspJq2iNx43X+1b8NE0pm8Xbo/fbwpkUeKznlnP1oVZLjaeC3jJ/9VQZ7g4k8+876q+bta1yEk++cxwrp4/Sgl7b074Zn6P3P1QU57jwdV0I85//2ODTUkRL0KjZPUWZjm7jL9sjw2b9XZip8BQ1zVHtG9WS13keFjRF4hfTRmLisEJQJAEZgChJlj6aPsDF0neXZayf60NhhsP0vAxlE+KlpohhI58/yJlen+thteO1AfNrGkIcinNdBl99Z2UV1s4p0zbsFee4sHHuWDiYFh+wvTxUa3yWPgkJJ4hgaQp5HrbXJGRJBemgh/M8LCK8gAE5zgQe56k7R+O/Xv/CEOCVjLew4g4KM5WAuHW7lWKcD00ZBpIg8OqSCcjxKMmPKIoEoHBm7z1yE0iCQK6bxS++XwqPg8YTbx5DtovFC3ePQ12s4sSF+iC23HsDapqj8Ac57KyswvyJg/HEm8cxblB2Av+qlqBuCxfVVl42letTnVN2VlYlfMPGeWPhoDs+PlUQ8URsV4AgiFUA/LIs/5IgiMcA5Mqy/GjcNSyAvwL4H1mWf5Nq22PHjpUPHjxoeq45EsGlJh5VdUpkZ4gTMSDHCQdDIddN4btP7cXGeWN7VWYoG52KLhMKKzkORiL4yh9NcEKG5DngcTo7/Nxz9SFMXPl+wvEPl03GgBy39nf8IrjqWJ2rD2mL7yqKc1x4dckENISNY68k14VBuZ4OlxqxeubWBeW48Yn3UZzjane9666EfhHsMhpE3S7DyaDvAwD4z//5HG8fbYmxLs5RsmEAioPDiyIm/NIorx8um4xZG/Zj64JyjaAAgJm+YlSMH2ioIb+uwoeRRRkQBAkn/MGEcTU4zwF/UDQlD9SysWZjsTZ2T4GHBcumTjhEowK+rE1sc3i+xw6ka0FayHAwEsH5Jh5ndTqtONeF/plMp+hiGz0LbQx+TQsZBoCa5ihuX/Ohpic/eHSyQW8CLXpXnWf/fP94ECSF3+76EtN9JcjzsCjIcCDPQ1nqSxVWelOvawEZE1fuxp6lk0CTBLJdio1gZvsMy/O0m9S10WF0iRy3x5boDqiZnOOd+9Z8StXuCXMCbly1GwC0TQB6eV8zpwxvfHoOk0YW4eCpOkwaWWgg8FbNGIVMJw2vi0F1Y0Qrdaiee+LN46gJRLG2wofdX1zCtsqzWmDa/ImDUZDhQFSQDOU8AWX8v/bABIiSsrnBQZGQZECSZTC0kr0pzIkgCAIUAZAkabBfW7Ntrc4LgoTqQBSCqJCuNEkktG3Wj220odNWhgVBwqXmiKl/o/dpzORu/VwfBFHC/VsPG+SnMMOB/3jtM/xowmDDAsP6uT5c3S8TkiTj2KVmA/G0Zk4ZNu87g71f+TV5WfrtkfjWkx/go3+9GbWxErAFXgce/c4IA5H4zOwxiPCSVgJHv8hwuKpBuybTyWjlZFUy75VD53B72QBDe+oYuHFEUcL758YIRQLAzFifqeVw9deumVMGliLAS0rZT7P3XlfhgygZ+095BgMHTeJcQ+JcdLEhhMJMl1bWRh8QpwYNrq/woV+2A8GICIokQBAAHdvIw4sSCIKAkyEQ5iSIkgyaIlHodbTmJ6eNPdERSJKMr2oDqGmOYumOI63KU4HXgX/7p5EGPffkzOswMN+NS01cwu8zKM+B0/4oKk/Vwjc4P+H8yEIvGIaytFHyvQzyXCy+rAlq42NqaSEenDJcu3bRNwdh2ujihHsrT9XiihwPRvbLwFc1QTy96wQOVzUAaLGvrshywR/kIEkSRFkpO9uHFkfSQoZrmyOoC3E4Vx8x8MS5bhb5Gan5dWby85eHJ+CMif06OM+B78Q2kKhQ5UHPuenbNuPebKQF0kKG9Rj02Btd8Dbtw+lffq/N97Tne9rznHRGe3/TFPsh7WQ4XRC/1qBuvBhS4IGbpbV5OhUeN76tZPw0TZPt0vtWdowVZ8JxAmqCxmdYcTU06HbNO104f6WtX9fXYOWXd8aal1kbADrFjjbzq1+YPw5hQdQ4Ej23orfnV9x2LZwMiXwvCyXxNWFY/8z1MHA76NbWC9JOhvX9rfI9TpZEhJNQE+Dw9K4vNW6hwOvAsu+ORFGmA6drQ3h61wnUBKJYM6cMx843YmT/LIO+W1vhg5MmMP/5g5pv9cDNwwzXPDf/ejQEOfxku7n/t2rGKORnONAvk0V9sIVPA8x17NoKH/pnOxDlZciyDBdL4VJjFAs2GbmUK7KcyHQwaIryCHMiRBlw0iRYmkAwGvubIZHvUTiZzljL7aI14cuNtJPhzoYkyWiKcIjyEnhJhiTJYCgSFEkgwosgSQJeB4mq+qgl32TFa+l529/NHgNekJLyunquadWMUXCzSiAwQRC40BDBori5XH/9mjllkGUZEV5CQ5jHlxeaMN1XDBCALCtZ9mUQbdanbZXjVK5PdU7JcTGoD/Om80MbxpXlye4KossDsB3AlQC+BnCHLMt1BEGMBbBYluV7CYKoAPAcgM91t94ly/InydpONpAuNYbRHBUME1lhpgNPvfslfn7rNT1ZSdnoGnS7c2kVMGZFuLUV8Qvqavv6BZtIREATz4MTZIiSDIokwNIEMhklxa6V03aqLmQwTDbOHYsR/ToesHrGH8RNOkNJxZ6lkzDn9x91S2BseyaN9iy+tgPdLsNWiO+DqaWF+Nn3StEQ4nGxKYKdlVV44OZh+N17JwwLUk/FjAAVLy++AQzDIMNJY1KcXMz0FePhW4YlLE61d1x1NiFwucd3L0FayPClxjD8IQ6XGqOaPVGU5UCem0VRlsv0Hhs2YkgLGQYS9e7upZMS9CagzKdNEQH3ba7EzsXjURvg4HZQBnJkfYUP//7qZ5pDZ0bWJtNx+gB+9RhLU5pNcvBnNyMayx5jLyCmBXo9QdJWdIT40tvf6+f6sLOyCtN9JVomsZ2VVVj23atRF+DQL8uJi40RBKIC3CylZRqrCUSx5d4bMOf3HyWMseXTSrFoUyWKc1zYuXg8oqIc2xVM4ne7TmDvV3786o7rIEqygch5fv714EUZC144aEoA9fDNZ2ktw6n4BlZ+24rbrsX85z82HNt09zhMXr1H2y2uytbo4iwUZblQ0xzFz145gvkTB6NfphOiLKM2wEGWZfxw40eaHBVmOPDgi4fxypKJyPOwmszH6/bn7roey1/7zFIWx5RkY8U/X2uacXDpt0di/vMfm967bvdJbbd7/2wX+mU6tf6oC0Zx/GKzJqPxvsS63SdxuKoBU0sL8fNbrwEnSpj7hwMJz9l0zzgwsYBRlSBXn8HzohLgKSmZ8l47dBar3z2htXmhMQJ/kMOuo5cwpbRIe88IL2Leswc6e+ykjT3RUVQ3RRARRIiSwi8oAYsREFCCDCmSQK6HhcdBgxeVzJqBiACPg4Yck9VhRR7IsoxgLBCRJAi8eugsvjuqP+567kDCBivA6GdZ2SgvLigHScBwbv1cH1a8ftRw7aJvDsK8CYMhSDJ4Ucapmmb0y3YbeBF9ICmg2FchTsST7xxPCHB94e5x8Dpp8ILUm3nKtJDhxnAUVXURgz5aV+FDSa4TWa7UNmKeqw/B7SARikqarUqTBKav29eq3atiz9JJGJjnMRxra1CEjS5HWsiwHnYQnR1Ep8IOousYGkJRfF0XxpIth5L6QRcaw63yuGbrFjN9xXhk6nDwMdvHxVDI9zo6NNe3xlHHB87pN34n42rqQny6zztp7dfZ6BlIFqSnJnt4YOthzY5X8f6/3IT/95cv8PNbS8GJSpyFnitdfcd1+MPfv8LPb70m2dpOj5JhSZI13VfgdWib1wq8Djw0ZRiuzHPjQkMYL+w7jX+fdg3+6/XPE/iteeMHIciJyPOw6JflRGOIh5ulIMoyLjZG4HXQeODFw5pOenHBDYjwUgIH9uICJZv9bB0PZsWpPX77KEOSlV4SvJYu6FEyfDmgcnivHqrCjLFXgiIJuFkKJEGAF5UstmrCGH0Wx2w3i6V/+lTTLa1xaVNLC7H02yNRF+Q02f7huIEYXuQ1rKOY3Wv1958fmIhLTVFTXqKH875tgeUHdov1I8uyH8AUk+MHAdwb+/dmAJs79blQyGZVCNVIzfkTFbJrQJpnqrJhw6pcqiB1TjBsKqk0I5JgusubzSGQ7Xaalopt5kUtgE595wWbUi8TmwzJUparCzxdHUDX1oA4f5DrUBnd3gB9H4wpycaPJgzWFoLVgLk/f3JWC5g7Wx/Gos2V2HLvDTh6oVm7jmEYFOc4EIpKCXKx9ys/HsYwUCSBfDejZXdo77hyOmkMiJEIGlkRjLY7wONyj28bnQcZQGOIT7AncruphKeN7kVPzRChTwsf5kWQhHnpAWWedWDn4vGoCXAJQQ+/eus4Fm2uxPN3XY9bnvwA922uVEjjuD5IpuP0KbbVMh8sS2k2ydjH38Nv7xyFsoF5ECQZ/jCHAhJtyvZpw8blRKol9dTdi8GoCCG2c7FAZ39nuxi8fbTasEEAAO75xhDM2rAf7z1yEyRZNgRJqRAtxli2S9noUuB1mI7hE9UBFGU68P/+8gWWTytFnodFYYYDTobCD9Yq2XKWTys1lMhQbdWXl0wAAaJV4vFy7krvjYgv26Fm/rvQGNb6Kb4kN6D8Lm6WSjgmyoqePVzVYCDLXlkyEYBS3rummYMkA3N1wV5r55RhTEk2Dlc1IM/DIipIWFfhQ7aT1n43UU6UOzdLJZXFh6YM0+RQPbds5xEsn1YKiiQs79W//wePTkJDmAMvKJkHJFnGoDw3Nt0zDv4AhywXg637T+PGEUVawFNxjgv3Tx6GQ2f8GFWSa/ocQCE7s12JssgwFK7IcuH4pWY8+c5xTPeVYMfi8SiMlbuIxkrXTvcVKxssYqV7CAL4493jAAChqICLjREUZTqQ67FJfADIdbM4XRfUstFNGJKHxZOGoi7IgReVrH0sTaIuyIETJGS7WWS5GFCUokP6ZzsByAipmfxIAmFexJTSIjCUIk+SiZzq/SwrG0WSZUgyDOeyXUzCtev/dhpzxrf4r+vntpQwU9tSZVwNaqZJAgteOIjl00o1ohpQdPWlpgjmPdsnyesuRzAqJeijxZsrsX3heAQioZQyTRMEcPR8wLDgsK7ChwKvwyAr8XavClUe4uEPcwlyZGVn27Bhw4aNzgMnyvjdeyewfFophhd6NfsYMHL2yTgONWjNbN2iIcyhNsAZssWkOtdbVUJQOWqVn7oUjIIOc8hzsSBJ4HhNYlB2cbYDIU5K+h32vGOjr0GGjIYwhzCn+GVq5uiaQNRwXXGOCyxFYsVt11pypY/86VMsn1ba49d24jPTqdyT6sfog+n0fUCTsOS3Fm06AAB475Gb8L3f/t1wftvCcoNOIgnCnAOLBd39/kc+XGhQEh3keR2mz/z5rSJqmqPgBBFOlgTHy+BECQxFIsfFdEoWObOMWB3x3/oyR9DToF/bXv+30wBaOLcBOW58XRfUZFLPa21bWG4Izk3Gpalr5uqmU3WcZTppiJJsyRGqPJz6txrrodoegiSb8hJ63rcwxQztQMfkNh1lvmN1FHsYBElOIP+X7jiCflnObqtLbsNGW6A6XnpYEW7tgX7B5sNlk/HKkokJDlwwKpkSecGoElHtdNIYkOPGwDwPBuS44XTSlgpc3cnRERR6HYrjF+sX1REs9DpQkNGxXVztgVVAnD/IWd5zOfunp0DfB4snDU2YsBdtrkTZoDzDPWfrw6AIAtsWlmPP0knYtrAcNCFhzP/dhZcrz5rKxcuVZzFrw34crwmC4wQAHR9X6g7xWRv246ZVuzFrw36c8AcRiQipfz8nXPbxbaPzYGVP9HSn2Ebb0RnjvzuhBv5QBPCKhd50sSRu/e1efHK20TToYfGkoYo+pkhsnFtmGvwbiSTXcXo9ru5y1tskn/zHFAwqyDT0s16P27DREyBJMs41hPB1XViT5Znr9+F4dQBX5XvwypKJKM5xmY6TDRsa9wAAIABJREFUhjCP4hwXJBlKCXGTayQZlvcC1oFLD00ZhktNUSz99khc3S8DA/M8KM5xgxcl7VqzoJGz9WGEoiJuX/MhJq58H7ev+RDHLzVDihv/6gaT+OsEQTI9Hn9/X4Wqn6/IcsEf4PD93xn7iaFJ0987xIkJxy42RrBy+iiDftdvlGJpCg9NGZZgf9+35RAWTxqK4hwXcj0scj0MnAyJL2sC2u92sjqY8B5WMqrK8aB8t6k85XlYiLEAE7N79X+frA7iZHUAF5oimLl+H76x8n3csX4/glERj7/xBeqCHNb/7TReO3wOm++5ATsWj8fyaaX4y5FzGJivlNc0e865+hC+/ztrWSRJAsMKvHj4luFY8fpRzFi3D7N//xH+URsEACx/7TPM2rAfy1/7DFFBwhl/EHP/cABTVu/Bj549gKaIgBcPnMGFhojWvtUY6StjgaZJDMr1YGiBFzsWj8e8CYMw79kDmLFuHx57+X8hSBLWvn8SUV7Ej7d9glt+vQd3btyP07VB1ASieGHvKVTVRw02QpgT8fyHp8GLijyRRHI/y8pGIQki4Zwqx/HXUgRa1ZnZLkazr5wMqR3TX7t40lDToOVkfIKN9kM/16k4Wx8GL0kGmfqyNoho1NzulGUk6M/Fmyvx0JRhhutUmbPir+Jhb7KzYcOGje4BL0h4+2g1Fm2qRHVz1JKzT8ZxHK9ReCIzfvpn3yvVAujU9lKZ69XysVbzkxU/xUuC+VoOp8x1yb7Dnnds9HbE+2I/WLMXxy8244GthzW/LMfFYOO8sUb7bU4ZagNRHL3QnJQrzfOwPXptJ75/Zq7fp20KUf0Ys7W8ZTuPtMpRFee4TP3/eD7Byv86frEZ//KnT8ELMl48cAazNuxHVV3I9FpBkvGzV47gga2H8eXFAO5Yv0/j5I7F+KmO9MvPXjmCY53o0/d1jqCnobX1fcqCj4jn75JxaVbjzMXSoCkSLE2lxKX1z3YZYj94QTLlJdRnhKJiynLXEblNV5nvU0F0kgUBQRIEslx9qits9FBku0hTwi27E+VXXbAZkOM2DUIzI/Jm+YoBKCnKz9WHwPNG5W+lwFnamCmhPWAYCiMLvYYF+JGFXjBMx9tuD9oTEHc5+6enQN8HVhO2PiMioPQRQQAFHhYD8zwQJBnffXovAGD1uyew+4tL2LpAkYsXF5RjQLYDq989oZEFNTFyIs/Fmo6rPFdqWcWsdoj7w6kvdNQEOZysbrJ8j3P1IcvxZaPrYWVPdLdRZ6Pr0RnjPx3A0hS2VZ5N0JtX5jrRHBGTOlPqgvDp2iBK+2fhb49OBgCDvvKHOUR53lTHBaO8RtyqwfcqVJvEKoC/xl5QttGD4A9yiAoylmw5lLDQXhPktICp9XON42Tl9FHYWVmFJ2deB0ESkethsGqGMSDqyZnXgaGAtXPKDMdXzRiFdbtPJg1cGpTvwcq/HkNjmIeLpbUynQRaCE8r0vJUbbDVxR+rDSbVgWibN570RVj1H00SCUT+xnljMTDPnSA/q9/+Er966zhW3HYt3v3pjVhx27Uoymzx8/I8bNLAtmdml2Hd7pO4+/mDcNAUFm1q0cdP7zqRII+5Hgar77jOcOyZ2WXon+XE8mmlOBfbNauHGqi38YOvEtpbM6cMOyurDN/09K4T+Mn2T1Ef5BPG06o7rkOel8Vzd12P74/uj4o/fIQZ6/Zh0SZlU86SLYfw9K4TCYGFal+pfXyxKWJq29WHeUMfqNef8YcMx6rqwvjJ9k8TSM7pvhIs2lypyXp7NmH1NtA0icJMJyiSTFiEWrrjCBbcOCShL5fuOIL6II8ZY69MtBG2HMKCG4dgw56TWDOnDO8dvZA0cMnJmPMsFKX4mut053ZWViVcu3HeWLhYqlWdOSDHha0LylF5qhZRQTYEl6qwsrf60ga7rgRDmQck86JslKnNlagNmY9Jq0yHg/I9CTKV5SJT5q/sTXY2bNiw0T3Qc9RWczpLU8h3m/PJXiep2SYqP/3igha9b5V52Wqu5zgB5+pDqA2Z80+1IQ7n6kOW/FRD2DxgXM0mlYyrsecdG70dZr7Y0h0tQXALXjiI+jCPEUUZ2LawHDsWj8dzd12PCC/h/q2Hk2aOKs5xoSDD0alrt10Ns/755V+/wDOzy7SAHyv/pTkimHJXKke1Zk4ZANngaxXnuJDjYfDkzOuS+l8rpytcl+r7TfeVAFD4iTVxvNjK6aPw+BtHMd1XYrphafHmSlTHZRpsa79M95Uk+LEd8eltjqBnobX1fRdLJYyF38wajQE5TsOx4lwXnrpztCmvm+dhTccZRQIk0VJlMBmXtmrGKDgZ0hD7ob57Mt43VbnriNymq8z3qTy8NGVe9tFBk/AHRXhTz0how0a3oDYoYkC2w1Au1cWSqA2K8HSR/ManIX/klmGYdHURZm3Yj7P1LSnB9URgKmViOwKGoTAgx90pbXUU6qQTr2eSBcRd7v7pCdD3gTphx/dhrofVjhfnKCVS/vN/PseDU4ZjRIEnQTZXv3sC2yrP4qWF5agP8ThX3zLh6nfSOZ20aRniVMsxdsYOcUGSMe+5SmycW2Z4D6+DxAl/Ysr97gwUtWFtT9CUTSz1NfSWDBF6Hbz63RPaPDQg24VARDQ4U/FyH+JErVTBb+4cbSjFreorQZJx86//jrd//A2Djstykbj2F7sAIGmf9ZZ+ttG3wQlK2WRTWRaVXa8kSWBEYQZeWliOmuYo8r0ONIQ4/Ot3r8ZPt38KAHj0OyNQkuPCiwvKIcsyZADnG8L48UvK+U13j0NDmEeehwVLk/jNnaNBEQQok1JCxTkusBSBmkAUhRkO5LgYrVTlkslXYdWMUVi64wjW7T6p/Vsd3+srfPj3Vz9L+Jb4xR+rDSaCRfYfO1DECKv+C3OioeSrWuoAgHZMlGT81xtHcbiqIeaPkFj6pyM4XNWAD5dNBjwtbdIkaSofWS4Gj+44opWYiC/feriqAU+8eRwvLSwHJ0g43xBGiBPhddB47q7rEYgKyPc6sOL1z7XyFWNKshPkaV2FD14njR/ecCUivIgt996Ai40RNIR5bN53BtN9JbjnG0NQmOHAT7d/qr2PWfnahhCHGev2oTjHhT/ePc7wvirBf7Y+jF+9dRzLp5Ui28UktHu2PozzDWE0xhZM9BvLUi2lm2xBRS/rdlbyFlj1hdVis5ulLM9RJIHtlWcBAA9OGQYHQxhskEKvQ/OnIryEylO1eHFBOSRZOc/QBEgQYFkaI4sysH3ReAiiBDpWhtts7Km2lJnOXDVjFB7cehg1gSg2zh2LQq8DG+eNxZPvHMfK6aO0XeXqYlRb+AQb7Ueh14F1FT5DCa61FT5s2HPScF0yu5MgzOdXioRB5oJRHv6giIF5zpT4K3WzXzwXkOpmPxs2bNiw0T7o+RGzOV3l7EmSwPB8I5+c72ZxMWDMXrf63RNY/e4J7Fk6CQNy3KhpjqY813OcoJVi3XLvDZa8yJzff5T0vPk8pdi3N//67/jsF1MS5qy7/1hpzzs2ej1aK4Go+mUkqWSojgoSGsO8tokiGVe6vsKHfA/VpWu3nQ2z/nn7aDUevHkYnAyJdRU+S52W4aSR42awbWE5ooKEpjCPPC+Lp+4cDVGSNf/7fx6YqPnlDWEe//nnowAUbqu6WeGqPA4KW++9AYIk40R1AL9667jBd1d/r8NVDSAAQ3vqtfd8Y4h2vR56Tq69/dLZG6FsjqBnobX1/WwXi4IMBzbdMw7VTVE0hHk8/sYXGFboxXN3XQ+WJsEJEt48cgFjB+di093jQJIEGsM8slwMfj1rNFiL9chz9WFcmevWKvpsXzQevChBkmSs3X1S49IawjyeePM4fjd7jIELVN89npdQA1B/9VbsnhTQEblNV5nvU0F0FEHgqTtH4+GXPmkh/+f6kOEgIEr2wreN9AdNEvj+7/YmKMptC8svy/MiEQH+MGcILCrwGIm8fy4rxg837k/Y5bRtYblGDOpLsnVnPWtBkFAdiIKP1bsv9DpA0527E6Q9AXHp0j/dCX0fSJKE9XN9WoaH4hwlAt/JkHhxQTlESUZDiEOBl8V/334tooKMC81R0CSBtx6egG8/tddAMnsdJKobedy58YD2vPiddE4njQEpBs3FIz54z6z9VNtYsOmQoY1tC8tNdxHqx5eNrgdFENgw14eFOhndMNcHiug7Y9aGgs4Y/+kAkiRwVRz5W+hVdiSp8/5vd32Z4EytnVOGQFTAE28eR00gqpX7AIz6Su2nqb/5u/ZMvf3SWp+11s+dOb+b2T6pBlXbsJEMLE0hzEsJsjy1tBAUSeBcfajFBiQIPPjiYSyfVooVrx/F8mmlqIktxvxw40cAlDGwdUE55ujscAA47Q9h+WufJYyXHYvHmwZ1MDSpBeTVBKJ48p3jmD9xMOqDPPJj2bwESUZ2jPwUJRkOhgJkGatnXgcqRuyowSwMRUKSZM2OtdpgQlPmQVssTUGSZPiDHDhBBEEQoAiAJMkE+1h/XW+1n5Nt0FGzdcZDzSYoSRJ+fus1WHjjUPiDnEYexy/S+YMcVrz+eYKOXzVjlCGATtW78e9TE4iCJAicsZC9Py0aj598awSOXmjG2fowagJRFGQ48PJ9E8CLEgiCwB8//Aozxl4JUZLRFBGAhrBhh/j2yrMoznFh+bRSw/uQBIH1c30aQb6zsgr+IIcxJdlYPGkoZBl47q7r8fSuEzhc1WBY5Dhc1YBFmypRnOPCituu1dpV2/YHOfx42yd4ZclErU85QQRDkXhpYTkIKKUgVbnPdrOY6SvGlNIiZLsYXJnnwnuP3AQAECUZb/7vBVxbnK1lyXPFgu5YmsKibw7CjLFXgiIJiJKMHQe/7hVBU5IkoyHMgY+Vx5GhBMaLkgyGJOBkSUR4GbIsg6UpuFgKU0sLMd1XYvhNRYvF3xAnWp4TYwFPe7/yY0ppEVa8fhTbF43HwLxEH6rAw8I3OF/jNVQ/ckSBwi7TNIn+2cqu7HibI8fFaHpnRFEGXl4yARFegoMi8KdF4yHKMkiCAEkg5tNSyI/ZWCOKMvD47aMgSRK2LxoPWZbhYqk+v8GuK0HTJIYXGG1gj4PE3q/8huuS2aoMSZgGmmc4KYSiLQtyeRksIlzqG0A6utnPhg0bNnoyutMvj+fpXSyFl5dM0OwZggAuNkVQ6HXA4aAxwGF8LzrEJeUv2rJ2UBNsyS6XjBdp7bxZUPbeEzXaNY1hCQNy3Fq/Oxga2xaW2/OOjV4PK39bX3JU9ctIksQHxy9hzvjBuNQYwRsPfgP5XhbrK/4/e+8eH0V97/+/ZmZndmd3k2yyJOGSCIhcTD2xJKhcehSlVfsV61EQrFwUKxep0p6vop6vcloP7e8UKcdHbQsEbFFAKgpSWz2ntUXRcwRUApWjqYDcTEDIZnPb++xcfn9sZrKzM7PZ3WzCbjLPx8MHZnZ2duYz78/7836/P5/P+12rlGiWN4i5HTRe/OA0Jo8pxbhy5yV5tt4iihIIgsCuZVPgDXDYuC+2yWTFjLFw2Wm47AwoEihzMtpNKfNqwFhICGJs4ydFEhhSYIXHF4bbacUZbxClBQzqFtSCZSiU2BlEeAEulsajN4+D1UJBkCQEOQEtfg5WmkVFsR0XOsNY/WaDJqZW4mCwc8lktIeiCEdFzTmJ71QvPpUOiXJjtJgyU58+k0QtJpeOnub3SZJAiYNBayCKR1/rzrB/pLEd+095seX+a7DoxY9V7/u1pVPgj/AIcQLaQ1Hsbbio8TnXzKrGS/tP40e3f035naGFNpzvCOGUJ4D9p7zKxkIg1lcA4GJHCKIUi2eRJIGyAgY/+ad/gCBJeHHRtfCFowhEeJAE8NRtV4IgCCXOK8dhRVGEIEGJ5cQ2cmcmt6IogaZIvPvYDRBECRc6wlj39nF4/JGUZT4+PmxjSHBRCVwW5okISRpYGRwmTZokHTp0SPezQDgMIJbNy+OLwBvgsLu+EY/MGIexbodpEJr0RL/NyBjJcSAcxilvROP0XO62wmHL7naGcJjXzYA11u0AScacOHkn7g1r92m+/97K6RjpdmiOXyp4XsTnF30qY27j/FpMKC/I+kK6HJ7Qu+QynCrxbWghSXRGoli05WON3Bv1h5aAAEvX4g8Ayq69xEkRhum93k/WV1IdV+J3FsZfo8JlxcTVezXn51r/6kdyQoYD4TDOd0bR1BrLgBHkBFSUsBheSGddF5vkNhn0/5yQ4UR6GiM5jocnwIEgAEmK/SdIEn76VgPebmhWnvtCe1C1GBiI6ashDspQX9/yi/096mQjHTm+1AGSJLM2vmdDnw8S+kWOe2tL5BqiKOFcexBtwahS0vXmqjI8MmOcSuY2L5yEK4Y4cKzZj+f3Hsd9U0fjpf2ncd/U0aoFTuvn1eC9z5sxaXRJwsR9DUQJeKjrN+QAZiFrQXswitZAVBm7xpQ5cLEjrJRJlM8FQWj6wS/3Hlf191/uPQ6Pj8Pjt47XLMwrL7RhlNuhBFiOXfRpJonGljpxwuNP6bgcGPrnb41XsoIZXTcxa5gBeSPD6fowie1yc1UZVswYp/p+Yjudawti2pp3lYVnLpZGVBBRXmhTAnnyBsRxpU580RLQfW9ftgVxsTOsydQxvrwAAAz9I71nXHf31bDRJL6/44hK5n/1zglFDrcsugZhTlDJutwvakaVaBYEPvunYygtYDR9bt3dV8NKk3g47rfkHbdHGtvx4b/chNZgFIu3HkKp06or8/K1H75pLJa/fBhTL3dj/pSRSl/X60dy2wiCiM+b/elmns5JeyIeUZRwxhuALxyFhSTAi7FJELnt9PTf1geuRZATVLIgv9PJY9wqXbV2djVYhsJ/HT2PmV+vULffvBpsO3AW+095Ff2xYsa4pLaBbOvIk/WlDkZjl/RXTCGH4wnZJCdk2OidFrAWzNuszq58WbEVRXatr6fnG147qlDX9jVtygFFTshwPKOefKsf7iYzzvzstrS/01/Pk8m99ReZtkGKz5RzMiyTi355OjZAsviFbFukOtaf9QaUeZfNC2ow1GXXXFeOw3z4Lzei2R/tcS7HQhI4fNaLR145mvUY+SUgb/w6k9xEL64g+3cef0TlO8t64I9/a8K9k0eiM8Tjl++cwPIbr0BbXJylxEHDbrWApUmEoyJKnbSuDdlFTsqwXrvIPvqv3/1CiU/J/vGWD05jVm0l3I5Yxi1REnGhI6K74GfZDVdgqMuKFh+H5S8fTupje/wRbJxfi/FdvrFevCPRp9w4vxZ2hsLC336kOva8QQwrE38uk7hLOvQy3tXf5KQM5xpyfCQxZrZmVjXeP3YRt3+9QpGfm6vK8MhNY1WxrrWzq1HioMEyFrQForjQGcbu+kYsuX4MKotZlBd1l2KNRgWcaQuixRdRx19uGotfvnMC3/vG5cpiPvnapQVWjCy244uWAJ77yzFNDDo+XtvT5+nIrVG7PDfnaridViW23FPbyv1FT5+k0McNf2BQLaI71xYEAKXspExFMWtm9TFJhUvuXJ5rC8LFkmgPiYrTI/+dbfk91xZMqa+ket6l5nx7CHPqDmju89WlU5Rd5dmiv4LeGfzOJZdhmcR7L2ZptIWius9i9O52LpmcsuylMinSG7KxQ1LvHj0BLi/6Vz+SEzKcL3rPpH9Is//nhAwnkkzPsgwFXpQQ5UWVfo5EeLQEu5/baSNx2/PG2XJpCxDloZwv/w0gJZ1spMezOb6bfTtlzABJhoiihM4wh0BEUGRZT+b2LJ+GYpZGsz8CQIIkASQJiGIsoxVFErAzJIKcCAtJIMyLiAoi2oNRRAURpQVWsDQFjhe7Fq7w+P6OIyh1WpVFUkFOwKghdiz4zUeq399y/zW62cRWzazC0m31qr8B6O7wXX3HVbhqRJGSJU3ORhXiBAiSFMvE5Ih9lmjLegMc7lz/ge7vr36zAXuWT0NpgRUeX0T3PPnzHsgbGfb4Inhqz1FNZq6f3lmt+5x67XJzVRl+/J2rVDtE430Go++svuOqWNYwCbDRJIY4rKqdp4mlLFsCEQiiCFEERAmwxn2np2fUe5dbu8q3jHDFyk0xFAFOiGUtoy0keEHS1f96u3hlXS77Hc3+CM63h1Q76tfefTXag5xyTM7a9+rSKcrv1C2o1ZX5xP7wl3++XvceEvvRnuXTEBXETMaxnLQn4vH4Ivj0XIfqWLxu0WtLI/2z7YFrcaEzDJamUNIlvzRJQJAkiBLgsJIIRrpjJLJ+BACSACQQae0+NvKz+yumYC6iyy7JZNjonf5u8WSQRLfderK5E2PKCnXtwXNtQdgYAmFOUs4HzNjzICAnZDgecxFdZpiL6PqedG2JvvDLUx1bs2UDZCsOndgWmxfUoGp4kXLdhvMdykbGimIWf/7BVNW8kV58qq9j5P1M3vh1JrlLfL+nLSQsJIEQp9UVst+6amYVxpQ6cf+Wj5Q4hV5MZFy5M6kN2UVOyrCRj776jqvACd2Z3oz84xcXXYv7t3xkGNd5Zclk3NOl25L52HLm+Pg4T2LlAj3d/PryqSBA6M49ylmqooIISy+yVKUzv5kJeeQT5qQM5yLxsVFRisUq2kNRNLWFcPyrTtx29XBQXaWj9eygV5dMjiU74EXwgoQWfwSb3j+pGx9sD0YQiooIR2PZ+wmCwH2/7VlnlRfY0OyPGNo8c+oOGF4jsYpDKnIrx4304kCvL5+KsoKeE5bE6ysjfZJpfC1vraNMIAjAwZCqVPiyoSln1DIxyWVKHYzhTqZsw4uSStEAXfXhE/pKmdOqmxK8zNnj5JVC4kT8EDsDqzW76ikqiPrPk2a9+3j0yseRJNEvuwTybDeCCr17l3eDJGZmIEnC+N2lKKMAwDAWjOgKCEQiXcGCrhKw2ZC33pSD1btHmTJCP+V+Ov3LJPvwooSpl7ux+PrLlbJbm98/ZdoSgxSKIpL+nQ8Y6VlRknDsgk9TnmpcmRNWqwVDAGX89odFvPHwVNzxq/0afSVJUq8zgurpyGT3nsn4ns64YmKSCSRJwGW3wtUVPz3XFtSVOY4XYLFYe1yUUezQz4qwYX4tBFHEurePY1ZtJcaWObFqZhU27jupLOCZWOnC89+diA3zauCwWmIL9QiApgiUOq2q+2pqC8HF0qpMZWUFVvgjvO792xkKHC+ojl/sjOjarYmBHo4XdK/pYmmlbZKdl/i7+Q7HC3i7oRlvNzSrjv/o9u7njA+uCpJWj73d0IynZ0owGp6KWRo7HrwOzV3Z+g+f8eL2r1dg1RufYuGUURhaxIIE0BaKoJi1asrI6u3Cfvq2KkR5Ed4A12MZXlHU1+OtAQ5FLI0RLlbXvzHqP1RcafH44wCU+x5aaENHKIof7vybIpMkATisFtWxzQsnQYprU1kOE6/tYmnV7xjdg3ye/DfHC8ZjTy/81FyA4wXYGXUmvfjn1GtLO0PptkVz1w7qDfNr8c7fL+CqimLVe1o7uxojilk4rRTCURH+iACKJDWloI0W9MqZJeSFy22BqKokk6yv+iKmkEg++/n5SDIb+LsJmehKHYxuDKjUwcAX5RErWBzDaSVNm9LExMQkQ7Ltl6c6tiY7L10bwCh+kSrxcyU7l0zGyeZOLNxSj2fe/LuSXe6EN4Bn3vw7AChjlYWwYERx8t/t7b2ZmAw0Ev1bAIDOdKscg3CxNEii278rdVqxdnY1hhbaYKEIkASh6KsJw4vgstLai+Ug8X66KEkodVqxamYVygqscFotACSwtAVRUVTiS7JPFx8rag9F4bCSWDWzSvlb3qQmny+I6fnY8XGe+PdlFBOI8tqkMylstkwLPbnJ5m/oyqVJXhMr62pV9EtsozWvLPraWd+EjfNrFf0ST1NbCL4Ij2hQ0mQ81CsHX2hj0B4M4v/u/ATLpo9R4sLDi2yaa5c6rbi81AFelNAW4iBJErY9cC34rjnPV+ubYv2qyxYy6rMcL6Qtt3LcyKgfp3qNnvRJpjGbQWUtOawkvmzVptPfuqhW2SloYpLLMIwF40sdqoWgfbVbyEISqCjWqQ+f0FdomsKEMqfqnsqc1mSlZ1REIjyOt2gn1scNcWR1IR1NkfrPk2a9exmjNO5lBVbF2QZiCnrx1kOpZsVIGW+A65ff6Qv07n3Z9nqsmlmFtxuaNc9i+O5SlNF4+kveskVv+5dJ3+BgKMyfMlJV4mz9vBo4GPO9DDaiUSGTEmw5h5GelUAoC+iAmL5eur0eLz94HcodVt0SK2+tmIr2oKDRV31lv2RzfM9kXDEx6Q2MhdKVOcaSuv6wWEhMKC/Aq0ungO/aSVvqYOCPRvGDGeNUC0HkEpUA8Pit47H6zc/wvW9crikR8OPvVOHHf2jAkcZ25Z5EScJjt4xXpev/9b01uLmqTLXAq6KYRbBr17ZMOnarUZu0h6KqtslG2+UDPT1n4mTflvuv0T3/ZLMfi178WDNpKIqSptxC3fxa/OFvTbolHsoLeU05hfj3O7HShfumjsa9L3QvPkn8vcTJyboFtbpyNNzFYmihzXDhkFHbWC3640K8bJAkgfHlBdizfJomo17iMW+AU64ny6GefMr/L08KJDsv/p4IQcyqn5orMJZYOaN44p9Try2DnKDbFiO6dg4PsdNwOxgQkPDa0imICiJIkgBLk+gI8jje5tctGfTP3xqftOSwXEJb9knjdy7H66tsxxT0yGc/Px8xeqc0RWrsVpIkdWNAI91WnG/XjzUv3FKvuq5pU5qYmJj0TLb98lTH1mTn9YcNIGMUu/7kX2fAHxGVWMq4Id0xFoIg8E7DVyCArJeZNzExiSH7n+2hKNxOqxIn+fF3qhDkBPz7f/1dU+Jww/xaFJdpF7jkGol++vuPT1eVRLy5qgwP3zQWi148qPK1REnCzVVlque+uaoMw13jFJ8q3i+TfcB4PZ+Kj20U5xkscSGTgYleXEqunKAn1wU2GmVOqyZmpRczI0mi+cVwAAAgAElEQVQCBSylKW2aGMedWOnC//s/EzDvhQ8x9XI35k8ZieVxMeL182oAAPtPecHxoio+m41+J8eNenO9eD1gdG9UhjbkoLKm/GER9adbsGPxZOxbOR07Fk9G/ekWjCkrhJvN/YHMxKQ/cbMMNsyvRUVxLAOGbPTp9RWapjCi2I6RbgdGFNvTWjjQEuQUpxCIOagPba9HS5DLzoN0Uea0YmPC82zsRUavZn9ECZ4C3QvBQlEBc2sr8P7jN2Lfyul4//EbMbe2IutZMfI5+0ayDCPxf8vPImc7jH936+fVwGkjdWXUxZI41xbEWW8A59qCiEa726S/5C2b9KZ/mfQNHC/i8Bmvyp44fCZmSJoMLpr9EV2dEstkkj8kjpE/njkBO5dMhiRJ2LF4Mh795ljl3Ka2EDy+CLwhfX3qD4u6+ophLCpdlq0NANkc39OxfUxMsoHbwWDzwkkqmTPaRSgjihI8vggudoRwvj2Ec21BtIWiGFpow2VuB4a7WFAUiRAnKQvogFgffWn/aTw7uxpr774a4aiIRdNG49HXPkGp04q6BbVY13Wc4yWsmBHr9zdXlcUWzhbawPEiSrv6VlNbCN/fcRhPfvtK1f2vnV2NkW676hnSsVv12mTNrGrsrm9UtU0mbZeP9PSciZN9z+89gbWzqzXv5Pm9JzCx0oVVM6sQiPC40BlWdpr//nAjttx/Dd559AZsuf8a/OFvTZg96TJlAR0Qe18rdx3FWW8Q3oDabo5/v8umj1GC5/L3Fm89hK86YmNHiz+imZxcuq0eT99WpXnGMqcV7SEO59qC+LI1gGZf7J57apvyAltKsiHvkB1RbEdpQSwbmd6x+N/ZuO+kbvtu3HcSu+sblfFo8/unsH5ejWY82V3fqLmnbPupuYLbwWCk244SB42yAgYlDlrVdrvrGzVj7ki3XffdDS+KLapkGAuGu1gMc9kxzMWiotgOqyWWfe5sa1Cz8P+J3bFSyIu3HsJFXxhnvepz5tZWwGm14HxnGEUsjbm1FUl3VffHu8pnPz8fSfZOE+3WZn8Epz2deGXJZLy3cjpeWTIZpz2d6AwZx5r1YhUmJiYmJsnJtl+e6tia7Lz+tNeMYtf+iKiKpXhDUczddBA3rN2H6599F3bGApedxrmOmI/Icbzu9aNRwTBubmJiYozsF+6ubwQvCtgwrwYEQaA1EMXKXTG/48SFDo1NmA8x4sS4giQBK3cdRanTit8tvg6rZn4NdsaCn931D5hTW4FVM6tgtZAoK7Rh1cwqVQxgVm2lRoc9sfsonvz2ldhd34i6BTHdmYqPLfuDxSwNjy+Cc21BeHwRJS4wWOJCJgMXvRiUlSY0NkfdglpQBNAWisLtYFTny3FiuX/wvAiPL4JAREBpgQ0b5tWgbkEtSp1WfH/HYfxLXBx3xYyx+OdXY7G/xddfriygA2J9d/nLh7HkhjFYM6sam98/pcRn18yK9dmJlS5suf8abP/edZAgqWJ2qSDHjRJ1QDr9uKeY3fp5NbBmuLkg99Lu9CE2mkTt6CG4d3P3aukN82tho0nYelmGz8SkP+A4vtfl0FLFZrNgrFudNcbFkiCzHPPrr9Jpelk6Mq13DxiX/SiwUZh+ZblGzzhtyRc+pVvjPp93WSTLMCKnfnY7GBBEzACwWEiUFzDYcv81qtKZJ5r92P69WpWMFrAkTnm1u8BHuKzwhWNBASN5O98e6pVMmAwerAb2hJU2ZWewkc/lP+PHHYIgMMTJYOeSybAzJJraI5i7SS3fALDurydQUcxiWJEt6bPrlbrqK92azfFdz/Zxs4zpJ5j0GUbZsPRswFiafw7n2sL4xd7jmp2+T99WBYokQFtI+MM8WgOcqo/KGcLis6humFeDqZe7ccfEEerd0vNqUF7kwB8fngZRAubFZRWTs9kdaWxHU1sIForArmVTwPFdGaEYUin5KZOO3ZrYJgRBgCKAn95ZrWqbdNoun+npORMn+440tuPZPx3DziWTAQAEQSAqiHj+u19HR4jXlH0oL2Rw29UjNNl1i+wW3fIreqV649+v0QKkprYQHn3tE2z73rW6n1Mkodl9a5Q1bHx5AYBYoL+0a+wSREml/3srG4m+2dhSp3I9lqHw+vKpiPIiaAsJC0ngV/dOVO5bPs9hpTQZIn96ZzV+dLv6nkiSyKqfmiuQJIFRbgfaQ5xShkMC8MqSyTEfjyRgY0i8unQKJElKmg3QSCfK2RLW3X21YQkQWSYjvKg659FvjsX0K8vx3QR7nqFgqK9km+P1h6aCE0QIogSWprr7I8fDE+B6lXU3VX2ZbvzARB+LhcR4nczvAHC+PaSyZVmawIThLpy46Iedie2YnzDclTTWHH9dG0MgGCXgsF3ihzYxMTHJcbLtl6c6tiY7zyj7d1somvJYnKqdkCzWoo5dS4q9XsjSsFAE7kmI4yTOGQ2UagomJr0lE1ta9s1/emc1RFGEhSLgjwi40BFGU1sIE4Y6MdzF6tqEuU5iXCEqxDZQ/ug7VQhxguIz3VxVhkduGquqZrBxfmxxjvx9o5gARRJYOGUUfvHX4/jhN8fBabNg9R1Xwc5QIAkCv1s8GSQBXR/7hMeP5/5yDLNqK+F2MAhyPIpYCwptzKCIC5kMLERRQnuIQ5gTEO2yCViGQgFjwXGPH0u31aPUacXqO67CSLcdForEywdOo+6/zygL6oZ0ZUqX+4e8CPbmqjKsmDFOFfuTF749dsv4WHUSAtj+vWtBELF+IvdXiiR0+66FIpQ48IlmP5ZNH4PLh9jx+kNT4fFFVBVQ4itRpIIcN3LZ6VhsT5JAkyRIIhbzS0c371k+DaGogPYgh60PXAsAEEQJuw59iQevvyLd1xS7dkbfylPCUVF3F0c4amaOMckPPAH9nUieQN9k0SJJoDUYxbwXPsS0Ne/ill/sxzFPwHAnUybIqXvjkVP6ZhuLhcRwF6tk6ejNxIScxj2eimIWIU5fz/jDxru65AmAO9d/gGlr3sWd6z/AsYu+pKu283mXhd69b5xfi8NnvHjslvFY/WYDZm88gDl1B5R24EVg0Ysf46Z17+Fbz72PE81+PH7reNzyi/2YtuZdzHvhQ3zZGkRHUL/9AxERN6zdl1Te5tQdwOcXfeDNbGImPWDaEyYy/TmGZZPEcWdO3QGc9ATwzB8/Q9BgHLujpkIJAD3zx8+SPvvnF32YU3cAN6zd1y+6NZvju82mzphnLqAz6Wv0dh0mIooSzngDaA1EsXR7PWbVViqL3uLLZ05b8y7uWr8fFzvDiHaViJTRyxD2UNeOQr3jkaiI8x1hfH+HehfiE7uPYtn0MQBifR4SMHvjAVy/dh/u2XQQzZ1avyRduzW+TYa7WJQXsbptk0rbDQSSPac82RePxx8BY6FQXmCDN8Bh3gsfouErnyaL9uKthxDiRN2dphwvYfWbDZi76SBWv9mAx24Zj5uryhDkBAiiZJgRTi6dEI98vKkthDMtQd3PGQulesa2UFSTNUy+55ZABMcu+vDUnqM4dtGPuZsO4vqu8eaExw9RlHolG3q+2QmPX9ntW+KwoqzAhhHFdpQV2FDi6P4di4VUftdlt6rGJpqmDO8pm+NYLkGSBEocVpQXxfrx0KJY9rjL3A4ML7ajxGHDcBfbYzZAPeKzJbSHokoJkHjiZVIQJdU5d9RU6No7doZWdlXL14jXVyRJwBvgcE9X5pe7NuzHsYs+RCKxDY9yRpi5mw5mFDtJRV9mEj8w0UcUJXzRon5vX3gCONMa0NiyHC+hxRfBqjc+xdxNB7HqjU/R4osk9Q3jr9vcGc2LeI2JiYlJLpBNvzxVX6Sn8+LttaGFNnzREkh5LJYTI6RiJ6QSu45GBbQFooq9vnjrIbT4Iqqs4XpzRgOlmoKJSW/ojS0t+yrlRSyK7VYQgOJjUCSZt/MFiXGF9mAUK2aMRVtXlj1VlrmE+MGy7fVKJQMAhjGBzy/4MP83H+HthmYs2VaPk80BLHrxY8zddBB31x3AdzcfBGOhND52WyiK5/5yDPdNHa3MG8bmAkM44w0AwKCIC5kMDOT47slmP+bE2wQXfPAEIli6LaZDjjS2Y9GLH2Phbz/CyWY/aka5AXRXc/hbUwfuXP8BzneEVFkkZ9VWamJ/cob+J3YfxYoZY3GmJYjpP38PP3zlbxBESemv8f8vU1HMghckHGlsBxDbuLv6zQZQFAmCIDQVUBZvPaSpXtETctxoWBGLQETA3XUHcN2/v5ORbq5wsaApEgt/+xFuWvceFr34Mf6ppjJjP3xgROZSJJ+zhZiYAP0vw/2xaG+IXT9F+xB7bgcXjdK4Z/KOEtMlpzLYxK+u/uCJG7Fn+bS0VnhfSvTufUJ5Ae6bdrlu+SdvgNO094oZYzWTait3HYUo6be/KMXav+F8h668NZzvUIx+M3Bg0hOmPWEio1duekMelGDTG3dkhypqIN+SJGHnksn45d7jeLuhGU6rfkltp5XULXdu6lYTk8zxBjic9QaV7HLxO3v1Fset3HUUgiipFoK4HYxu36Yp/Z2GQU4w3EHsYmll9+NP3mro0YbNZ7s110k22Rc/SWb0Lo1sGo4XNWPEk9++EsUOGj95q0H1juPf79crilC3QD02rJkVK8UCxMrNbkgoc1o3v1YT0OJ4wTCzWDgqYvHWQ6rFpPJnmQTsEsnENzPpf+KzJWzcdxLFCeVi43dcy6VH4s9J5je+tP80Xn7wOl19ZSQfRqXX0o2dpKIvTRnNHrptue0QGltDGls2Kkq6MYhkvqE57pmYmJhcelL1RdLxWdIdi9OZYzGaK0mMXSdOXK/c1b3ZST6WGKc045kmJtmzpb0BDj95q0HxMYQ87l+JcQVJAi5z2zU+uVFc4TK3Xfnu7vpGrE/w+eNjAvJ37AyluU5i1nsg5vfp+f7LXz6Ms96g6QOZ5BVyfFcuoQp0j+ERXr/6nZ2h4GJp1TG5Lzb7Iin1Ufn46CEOjOzqr0ca27Hzo7Oo67I5Nr9/StN3N8yvhSAKqmNrZ1fDQhKaDJbyb+n141Tbpre6Odvx50GVWkHexRH/UvMhW4iJiUx/y3B/OFZWqwXjhqhTtA+xM7Bac1s9GZWPu+gLp/2OMh1s5NXV+YjevUsGExkcL8BisaraW4J+WVbKoI/IqWkXbzuMzQtqVPLmtJIosdPY99j1mP7z98ELub87yOTSYtoTJjI0TWGCTgmoXC+DYTTuuFgaJGEs37wo4e2GZgCALyKizR9SPfvJ5k6U2A0Wapi61cQEgH7ZEACq8spUVwkLXpQQ5UUIkgQ7Q8Eb4FSZlZItjqIpEj/7r8+xamYV3A4GQ4tshn1b73hpgRWSJOl+VlZgxc4lk2EhCUUnxP+2ng2bz3ZrX6EnC6IopVUOO1m516jQHYCLlxmZZO9fSPD35M+f+UMDjjS240e3d7/jxOcYX9ZdRuFks18p+wDEsuT5I7xSeirICRjmsmkCWoyFUnb0J94bRcTup6zAmpEP1ROp+maZlAAyS3Bmj/iSa0ca2/HMHxrw//7PlXhlyWRIEkASMbmfVVupyGB7iMMzd1yFbQ9cCzqJPf/j71yFEhsNb4hDVBDwVUfMzxQlqPqVTLIFqZnETnrSl9kOVg9mjNpSb1LPaGI0mW9ojnsmJiYmuUGqvkiq56U7FqdjJ+jNlTSc78DYcic+eOJG8KJkeL34SXa9OKUZzzQxyY4tLYoSQlEebzc0w+Pj8Pit4/O6fyXGFQRJwpfeIKKCOiZkFFf4qj2ELfdfg45QFN4Ah+0HziqxqGFFNjzzx8+UmID8nSCnbm95Dk/OLC8j+81GNnuI4+HxQeVbp+p355N/nk/3Ohgweh89vadIkg2jcia4xP4V5ARwcfMqclwYgBIn7qmPysftVgpDHFZVDLGYpfH68qkIR0XYaTJWVlWUYKFIMBSBxVvrlRheeyiKZ/90TCm3rPdbjCWzebFsxTmyGX8eVJnoWEY/YwbLkAiHs1ee0sSkr3Cx+jLsYvumK/dXmTqrVZ2iPdcX0Mnold1x2ij9zDw244FDrwxTbwabfKWndohvbztj0T03HBV02/+Nw03Kec+8+XcAQGeYx9xNB3H1v+3F3E0H4YuI+O/Hr4eFGlRDo0kGJLMnTAYfNE2pxrBcX0AHGOvb9lAU7zR8ZZhdL94u2H/Cg2InqypHUuxk4WL1y52butXERL9syBlvQFNe+Yw3iMbWIO5aHytbf7I5gCAnKBmV5H/jAyHxyEEWOc1+hBexp75Jd0fhXz77Srd04dBCG4YVsbpZxf79v/4OxkKBJPX7+2CzYTNBTxbOtQczKodtVP6Sprrfz8Z9J3Xfs1527Q3za7Hr0Jeq36goZnGi2Y8jje2oKGZBdy3sS1b6tMLFoqzQCk9XJtKKYhbr59VgywensXRbPR597RMMLbLBxWozkLsdDEa67ZrMYpsXTgLLULi5qgxFXRkRE++zt/KXim+WSQkgswRndknMluDxR+C0WTC8iEVliR3lBTZIErD6zQZFbh+ZMQ4v/s8p3LjuPfzlM317Z4idgZulccIbK3N/uiWIZ/74GU56YuU9P7/gM4yR9EfsBDDjB9nEqC31JvWsFv0xz26Qndn0DU1MTEwGLumOxenaCfJcCU2RmLvpIMaWO+GLdJcJP+UJJB2/5LGoNCHbc75WUzAxySa9taVlv+5kc6wfHmlsx3c3f4jX65t0+1eBLT9swvi4AktbsPXAGU227931jZpnXDOrGuvePo61f/4cjIXE6jcb8Gp9E1a/2YCoIKLFH8GiaaNV33luztUY7rKpjv363hr8+A+fanxkt4NBWYHVUOf9/YJP5Vun6nfnk3+eT/c6GDB6HzwvJn1PPC9CECVlw2g8FcUsWvycpnLD2tnVGFFsw+76RuXYr++tUTI77q5vVDLJyX/r9dHd9Y3YvHAShjismhiixUKirMCGy0rsGFJgw4hiu7LmQQIBjz9WZnbupoNYuq0eHn9EWSBoVBkjE3IxzkFI0sDqZJMmTZIOHTqk+1lnOAwKQHtIVHZxuFgSxy74UV5kx4hie//erEm+0W/Luo3k+FxbEDaGQJiTFBmW/+4L+eU4Hsc8ASXduGz4jS91gGHyY6FbfyOKEi76QuAFQJQkkAQBCwWUF7CGOwPkQVdOVSoPNnKaUZ4X08pIkYRLLsNGiKKE9hCHr9rDSjp6uR2uGOKAJ8Cpnp8kCW2bLahFiYOBhSJgtQAdcbo+Eo3ipv/4H0WGK4utmPnL/ZpV8juXTEZ5gS3T9jXpe3JCho3sCQFAoc3WX7dokp/khAzrjTtrZlXjpf2n8YNvjsMIlxWBSLd82xkSBVYGoiiq7IJf3lONmpFu8KIEiiRw5KwXNSPdaAtGlZKuFcWxcucTygsMdWs4zMMb4pTfc7MMbDbTzshh+kWO07Ul8gGPL4I713+gsj+23H8NVr3xqcYmWX3HVVj04seYWOnCv95+JYYWsRC7sg5QJAELSUCUJIgSEOR4PPDiIUy93I0lN4yBhSJAkwQ4QYQkAT/7r7/j7YZmLP3HUVgwdTTErmts3X8adf99BhMrXVg2fQzcDgbDXSyGFnZnBuN5Eec7YiUCwlEBVguF0gIr7FYKJSyDEx6/oQ0bT+JuzGKWRlsoeql20V5yGdaThb/+3xtw/5aPNLLw6tIpGO5i9S6TFJ4X8flFH57fexyzaitRUcyiqCs7hTWuzWVfQ86uXepg8EVLQPVef33vRPjCPGx07P277BZEohJCUQEkEZPFX7/zBV6tb0JFMYs9y6ehtMAKnhfh8YfBCZKSHYyxkCAAkCSZ9L3L/kGIE0CSBCSp278CJHzZGoKNJvHwjiPKfdYtqMWVQwt7JUs9+WaA/vuLf249MvlOEnLCnrjU9LTLO1G25exysr0hSgIYyoKoKEEQJfCCiAIbDUmS0PCVD5UlLBpbQyhx0GgNRGFnKEQFEU6bBQ/vOKLoXJoiQJMkopKIeZs/zHrsRE9/pqp7c5ickGHd/r5gEmgLgfu3fKyyZUudDC50RvD9HYfjdGMNRg2xgReBMCfGxelIOCiLad8ObHJChuMZ9eRb/XA3mXHmZ7el/Z3+ep5M7q2/yLQNUnymnJPh/qS3sfZU7MV4Mp1jke35YjuNZ/74GWbVVsLF0hCl2Ngil4OLj4uHeTGWDdXB6F47GhVi9lGa1RRyNG5zyf06k/wj3f6biOzXlTqt+PF3vob/PHoOsyddBhtNwmmlEIyzCYtYEuEoMKTAcL4gJ2WY50Uca/bhF389jkXTRmNokS02z0kSCHA8GIoEQRAgCKC5M7ZprsTB4NBpL2pGuUFTBKKChE3vxRb6LL/xCpAkQCDmyxMEgUhUgJWm0OXeI8DxaAtEEeQEXF1ZhBKHVXM/S7d169C1s6vBMpSSLV/2rQGk5Hdn2T/vU3L8XnNShvsSo/fx6tIpmFN3QPc9FbM0mn1hRLvisTRJoKXLx5dlnSIJcLwImoplwbeQBGiKwG/++xRqRrnhdjAoLbBix8EzqPvvM0o/KLTRYCwkWgMc2kNRHD7jxX3TLockSUq1k57ib0bE68tSpxUrZozF6CEOJaMdgKxlSMxUN2ch3mz44SW3cvoTCsApb0RjrF5e5kRHyCx7YJL7FLEkTuvI8Gh33wyUkgSU2Gm8/OB1sbKXNhIsZUkrCMxxPDyBbgfLyIEbKJAkgfICNu2Bw2ohsfqOq2BnYqWLrF2Ou+wsp7MYId9IHIhX33EVRg9xoNhBwR8Wcb4zDIok8OHJFjz/7knl+Y1KV4XDPE54tYGJT388Ax0hEaUOBl/5IvjRzCtRNbxIlRqfF6UB064mfYehPdFHutgkt8niQud+IzFNv+xQPX1bFX7yVgNcLIP5U0Zi+cuHNWPP+NLusiIUSeCDEx48/vqnAIDNC2oAACNcVlXpETfLJF1Ap6ezx7oduRCQNTHJKnqp6Y3S+NsZChMrXfi3O74GUZLQ1BpUTZLIAcP1736BH3xzHP7w8FSca48oi7DkvjS8KGZb/eh2CSQJSBIBoqs7fnSmXfW7gihBkroXLsnBBxtD4TI3ixAnwuOL4NhFH3bXN+LJb18Jt4PBjsXXgSIIsAwFF6stYUBbSPjDPBb+NnZvN1eVYcWMcSr7Ng8XgPQKPVkgCejKQk/lsI0WElksJMaXOfGDGeM0m1SGl3dv8JGzPcdfL943YRkKFEHgydf/V3l/j8wYp9Lba2dXY/H1o/HAN0bBQpGI8AJaAxEUWmm0B3ks3nZIdW55oQ2j3DZdWbGQhCJ/bgcDFwscu+BTXUNe+P3ITWPx8oPXoTMUxfmOMIakUKalpyBishK5yd5fT2UmzBKc6RO/kFKQJNAkCTLh3cmLNVuDHM53xEqgsDSFEjuD1mBsIxZFEnAwhK694bTyWPCb7sVSLy66BpGoqCxuls/73Udn8XZDMyqKWay7+2r85r5acAJUOnfj/Fr8fvlUBDgha7EPo0Dy2FJnUhk1SQ2j/i6KEl5dOkVZgFnmtOJcRwghLqqycRtbA4hErWj2caox7T9/MDVt+3awxc5MBhe5vMDPZPCRjVh7KvZiPAxjUcVSUtXzFguJCeUFaPaHcd/U0Xhi91Hlnn9170TsXDIZAFDAUvCFBGUBnZ0h4QlwcPI8/BFRtVBOrqaQDmbcxmQgkW7/TUT265raQigtoDHz6xVY++fP8fTMKjS1a+cLLivOr/kCUZRwwuPHL/4a24xHUyRIgtAs3Nlz+BzurBmBlbuOquIE8f6R7Fv9f//ZgPumjsZL+09rdJns2y+aNhrP/ukYPP4I6ubXKrElAF2xjQK8unQKokJMz5EkcLI5oNx3vG+dit+dT/55Pt3rYMDoffCCqHucgKSxO9bOrkYhS4MkCMx74UP1cZsFT//+M3j8EWxeOAlLp1+BUFeMobEthDnXjsT8KaMhIVZ2WZQktAY4zN10UPndxdePAScAUUGERBJw0EiZxLmuK4Y48OYj09AR4uHxRfBVRwgEQSAQ4WGzUCh1WmGx9F7PZaKbE+Ml2Y435/YMX5ZpD4nKAAbEhPeh7fUIREQUJCm1aGKSK3QYyHBHKPnESiZEIjyOtwRUZdq+bI0gneSV8i6r+Gsc8wTAcQO7fLJRSSUjvAEOC3/7ERa9+DHmbjqIRS9+jIW//QjeAIdmf0RR+EDsnS/bXo/mrrJIAwFvgFMGuSON7Vj04sf436ZWfNkaUWTnnk0HceUIF1bcOEZ5fqN29oY4w34yotgOhrHAZacw1GVXyeZQlx0uuzkWmPSMkT3R3ge62CS3kYOv6ZbeywXidehwFwuSJHHvCx/i7YZmLL7+cmUBHaAeexgmVlbEQhK4Z9NB1QK6oS47Dp/1oqk9otKvJ7zGY7+RzvaGuP5pCBOTfkQvNb1RGv8gJ+DRm8ehxc+hNRBVFtABsX6yctdRtAWimFVbiaXbYj6t/tjE41RLrCzhKU8Qc+oOYNqadzF300E8fut4zKmtwGO3jMfqNxswd9PBmL1+wYeHdxzBU3uO4vOLPjy953/xVXsE8174ELM3HsDqNxuw/MYr4PVHcNeG/bj+2Vhfv9i1AzmxtMFd6/fjYmcYpV1lgmbVVmrs28VbD8EbGDz9Xk8WRAn6ZZ6SlMPuqaxHe5hXFtABqbV1om/yVUdYdY1ZtZUaWYsFzsOwUBS++R/v454uOfqqM6wsfos/96w3CG+A05UVWf7kZ/H4I5prPLH7aOw+Xj6MU54AOsM8dtc3giS1bZX4G3PqDuALTwBP7TlqWAKlJ38ukzITuViaIpcRRSlW7vqCD3M3HcT1z+7D3V3lruPfHc+LONMawEmPH/d02R53bdgf012//1/Fl/QZ6EgLSamONbaGNH3moe31mFVbqfz96GufwM7Qmust214PTpAw0u1Q/M7eEu8ry7+zeOshtIWiacUcTIzR6+/y4mK5jI3FQsJlp+CwMSob12FjYLzT19cAACAASURBVKUJzZjmM/AXjezbwRo7MzExMbkUZCvWnm78X46lpGsnWCwkJAnKohP5nh/ecQQAUOpgcNYbVo0hTe0RHD7rxZdtEZxs7sTnzX5Eo5kvtjDjNiYDjXT7bzzxfp0kEYqvQIDQ7Sf+SO7HiOOR/Y+3G5qxdFs9Zm88gHkvfIiaUW4A3T794usvVxbQAfpxAtm3mlVbqfjwibpMPr5y11Esmz4GTW2x78THLOSFfXL8fe6mgzjlCWLrgTN47JbxmFjpUnzrVP3ufPLP8+leBwNG78NCkbrHI7yosTtW7jqK5s4IWgNR7XEfp/SFxVsPQRCBYUUsWgIcfrjzb5ix7j18d/NBNLaGsPXAGUiIVW2QWfqPo/BVZ0TVX75sDeFce7DHEsB6c13Hmv1o8XOY98KH+OlbfwcAPPbaJ7jx5+/h7izPhWWytiI+XpLtePOgWkTHi5L+6lBRQojLr4HMZHCSTIazgShK8PgiONcWREuQwxlPJ15ZMhnvrZyOV5ZMxhlPJ1qCqSsbT0DfwfIMogmyVEi2kyBqsHq9p4wU+QTHCyh1WlG3oBY7l0xG3YJaTBzp1pWdqWNLseLGMZAkCWe9AZxrC2oCy6n0E39YP6jtDw+cdjXpO/paF5vkD83+CJ7fexyrZlZh55LJWDWzCs/vPZ6XC53jxyKKJHoce9wsg51dNsL/PHEjrhldjIe21xvqb6Ox3+xPJoMJt4PB5oWTlKBKRTGLkW675ti6u69GiYPG0CIWdoZKmq3OxdJoagvFstXpnEORBFbu0g9WykFKveP/MedqPPntKxHiBPzLt69UytfJ57TpLOxbvPUQWgIRXOgMIxDhsWpmFSZWulDqtCIcFbH27mrULajF8CLboN9FqycLVguBjfNrVcc2zq9FmdN4R6fRAhs5QNSbjGkTK12oW1CLsWVO1TVkmUu8pp2hIMe3ZDmK8Pq+jJ2hEIoKaGoP4kJH9wLLeLmUnyUc1X8G+T7sDIWX9p/Gv97+NXC8AI8vogoM6rWRHKjPNJim9/42L5wEt4PJ6ncGM94Ah7PeoGpiRl7AFv/umv0RNLaGNOct216PhVNGKX8LBvaGmLBL0Ejfulha873+8NN76sPxMZxE2TfJLsliCInvKF371oydmZiYmPQfibH2Z++6Cq8smYyoIOrGmXMBSdLPrCRJxmOIHJsZU1aIh3q5Id+M25iYxBBFCRIkbP/eddhy/zVK33CxNAQj/yDP+kliPGDnksn42V3/gK8NK8DOJZOxZ/kUbH3gWjAWssc4gexbyZ8ZxRLiP5ePxccskvn0T+w+ihUzxiq+dap+dz755/l0r4MBo/dR5rTqHjcaQ+V4r97xxL7gDXBKOWP5uNwHlr98GARBKL+5YOpojV2w/OXDiPBSj/Evj8FGgxY/h7Wzq/H8dyfqxl76ai5Mjndc7AjhfHtIE/dIjJcY6ZhM482DKteuhSRQUcyqGrCimIWFjNXuNjHJdZLJcG9JTHt5ZNUMjCotxD2bDqKprTv9sJ1Jfe2t6WClhrxyPfG9MhYKhCDqv/MkGSnyDZah8Pit45XBt6KYxcsPXqcrO4Io4coRrtiuuji5HF/qUHbwpdJPTNk06Q19qYtN8g1JNw09gfzTJfFjkQQkHXs4Tr+Ux4obxxhOUhvpV7M/mQwmjFLTA9CUV6YtJIKcgCAXc/T1+kmQE8B12YoEod+XKIJIGqw0WjTb7Ivg0dc+wdrZ1WgPRTXnGC00CUYEzP9NdymCdXdfDStN4uEdR5Rjv763BjdXleHthmbVvQ6mXbRGsjCsUFtCMFlZqZ4W2CTzM4xgLBRuripTxrdVM6tU12gPRQ3lUYjT9U1tIVCEseyebPZj0YsfK2Pnz/98DEca2zXBc8pgnJDvIyqIuG/qaJXfGl+uwaiN5D6RSTAtkzITvS0bNNjgeCHpgjb53fGiZHjeMBeLiZUuADCUIzIhGChnB9WTt8Tv9YefnqwPG5V6HUylsfuTZDGExHeUrn1rxidMTExM+g+6K1NMU1sIz951Fa4c4dLMf8THmXMBK61vD1hpCkGON4yhy2NJb8cUM25jYqKdP60oZvHKksmKrzDcxQ6IfpIYD5CfNb6E6yO/+yilOIHsW8mfGcUS4j+Xj8XHLHry6ceUOVHhYhUfKBW/O5/883y618FAsvehd/xCZ9gwLpZIfKxX/puxUD32geEuFh88cSMYi7FdQBJIGv8SRQlhg98pL7TiQkcYFzvD+n5rHyT9kXXuc385ptFHctwjMV5ipGMyjTcPnFUYKVDEktiQsLN7w/xaFLFkWiUqTUwuFclkuLckruYPcvq7bINpZG2UHax48tFw7GuS7SQoc1rTzkiRb/CipFm9TiWRnZ52aLtZRrefuNnunRmmbJr0hr7UxSb5hV5JjSd2H0U+znfFj0X+cBTr59WoZHz9vBplIb3RTuepY0uT6m/d301BZ5uYDCT0UtMnllcuL2JR4rDCzlAocdAocdB4bs7Vqn6ydnY1ih00dtc34rk5V+ONw026/bY1EFEFJeOJLUCSdI/LC+dW7joKp9WiOceoDO3ploBKNzz62idoSyhP8P0dh/HUbVWDfhdtqiUEk9FTWY9MM6Y9fVuVMr5t3HcSa2ZVK9fYXd+IDQmytnZ2NUYU27D5/VOq+2jxc7rnljhoPL/3BIDusXPZ9DHKOfHBc5oksHZ2teoaa2ZVY3d9I9bMqgZFEpqxOD7DnFEbyX0i42BaBiWAelM2aLARC/7q65n4d0dTpOF5X3qDWDZ9DJZNH4O/fvaVrr3Bi4LqWImDRt0C7Xm76xuVv9fMqsbeBu31+sJPT9aHe8pEaZJdksUQEmM26fqLZnzCxMTEpP+Ij7VPHVuaF5lAk9kDRmOIHJuxxP2b8e+bcRsTE13be9v+04qvIEHS7SdOW37NF7gdDJ6KiwcA+iVc9eIEiTGpYgeNdXdfrfju8r96vv3a2dXYuO+kbsyiJ5+epSmVb52q351P/nk+3etgwOh96B3Xm+NfO7saZYVWlDho7fECRtMXUukD8m/SBmVlRQlJ41/eAIczLUHd7woisHLXUXgDnL7f2gdJf2Sdq1dZRY57JNpHu+sbNW3dm3gzIQ2w1WOTJk2SDh06pPtZWyAMigJ8IRG8KMFCEihgSQgCEOBEVBTb+/luTfKMfhuVjOQ4GhUQEqIaGWYpGjTdu8wN59qCmLbmXeXv91ZOxw1r92nOe2/ldIx0O1K6JsfxOObRZqrJtd1cuYAoxlKp6u0k4HkRzf5IyhkpknDJZViPRNkDoOwETJSdCpcVE1fv1VwjUS7DYR7eEKf0EzfLwGbrlrlIhMfxFq1sjhvigNVqymYOkxMynMyeKHbY+usWTXKAprYgvpGgvwDggyduxAh9uzInZNgIeSwKcjx+/c4XWHz95aBIAoIoYfP7p/CDb47FiGI7znoDhjbC0cZWjCotTGvs70lnm+Qc/SLHmcjwQEMUJZzxBuD1cxhWZAWIWH+kSAI0SUAEQBEE/BEeC3/7EaZe7saSG8aApghQJIFt+0/jozPtePzW8djywWnNzr26+bV4af8Z3DFxhCajppwVDAD++PA0dIZ51TkvLroGUV7C4m2HVNd7+vefKt+T2blkMuZuOqg6Ju+QvES7aAeMDKeSiSqZn2FEon0+sdKFZdPHYMLQAnx+wYe9DRcx55pKDHFaQZEEGIoAJ4j47ubuLIRrZ1ejvNAGmiJwrj2MIU4GFEmApSk8tP2wrpzI2Q+f/dMxePwRbF44CWPcdpxtD6GpNQSXnUaBjYaNJtHii+CZPzbgqduuxOyNBzTPII/Fem20ZlY1Xtp/Gv/8rfH5mrUrp+2JbCDrv4udYVXG8nV3X43f/M8p5d2JooQzrQGEOAEPvXxYo8ee/PYEUCSB2RsP4NFvjsUdNRWQJAkEQcDBkHjwpXosmz4GLpZGeyiKjftOYv28ibBQ3fqpkKFwwR+BxxeBN8Bhd30jHpkxDuOGOOANRbPhp/fYFnp9WM+PBpLaoblE3slwRyiML1sjGhv3shIrHDSjitlEBRGRKA+HlVbs20AkCitt0Y2nmbGzvCTnZHjUk2/1w90MPM787LZLfQuGZPpOU3ymnJPh/kSOtUcFsdfzH/2FkT1gNIac8XRiVGkhygsZXOzkMKHM2av5oxyN2wwYv84k9zGyvT966iZEohJIArAzJIJc93yBjSYgSQSGFBjOF+SkDBvFu9959AbctO495e/4OAEA7Dh4BjWj3BhaaIPLTuOnbzXA4+OwYsZYXFHmAEEQCER4kAQBUZLgtFoQc8UJMDSBMCfqxiwGqE8/UMhJGc41eF6Ep8vuIEkCDEVCkiRIAARRAi9KIImYz1jE0sqCN7kvpNMHeF7E5xd9SllWeZN1sZ3GCJfdsK+cawvi4R1H8Ngt41Xx343zayFJEm7/1QeYWOnS/XxCeUHWYyGyztWLKQPqmF+8fVTM0mgLRdOJgRp+eEmsHIIgSgDsBDAKwBkAcyRJajM4txDA3wHskSTp4d78bpATcfisFxNHugEAEoD3Pvfg65e5YevlAiQTk/5AdnR86K4vnY0FdIC2TIhRuZN0di0xjAXjSx3YuWSyYjiWOhgzCKiDvEJdDzkjxUBFr0TN8++exH+umKqSHTfLwBviUpJLm82CEUkceavVgnFD1LI5xM6YC+hMUsLInqgZ6UZxbsXYTPoYawZl8nIZeSzy+ID9p7x4tb5J+ayimMVKywQAyUt51Ix0w86QaY39PelsE5PBCkkSGOV2wGmzIBwVQQEosFngYtUBgCGipFsi9sHrr8DCqQJYhsJP7vwHSGKsVKgkSWAsFCgy1tdPNPuxamYVxpQ60NgaUi2gqyhmcb4jjI37TmL1HVdhTJkDLG3RlKGVr+fxR1TPUFGsLVEg60kj29ckdVIp65HMzzAi0T4/0tiO1W824NWlU7D6zQY0tYWUMaKimMWe5dMwosCG15dPjckqAbAMBVdXdgobbVHuT4KkKycVxSxeXz4VFpLAr+6dqHqWUcV22GkKEV6EIErYU9+EccMK8dRtV2JYkS3pWJzYRnLJ5J/eWW2WQMlhZP3nstPYuWQyBEkCTZIgE94dSRIYVeKANxDB6juugp2h0B6K4ud/ji3EHFHMgkBMJtb99QTW/TWWAbGimMXOJZPh8UewdFu98rsVxSwkaPvMcJKI2TQFVvzo9q+hzGkFTVMY3g/+o1EfzqRcs0nmcDyBNn9IZeOebO7E0EIbilh1zOZcWxDzXqrXvJudSybrXtuMnZmYmJj0L3Ks/VxbsNfzH/2FoT2gM4bYGRIldjdONneixE73egEdYMZtTEyMbO+OII+1f/4cC6eMwpgyB+S0RaIEbHrvFB68/opLc8O9wCjeLYiSbpxg55LJKHNa8b1/HIMwL4AiCNAUgR/f/jWEeREEYtmj9hw+h2//wzCMKXOCpXUWtxjMq5g+vUm+Y7GQGKYzxy+KEtpDHEKcAEECSpxWDHFoMw2m0wcsFhITygvw6tIpiAoiLCQBh5VCoS15X2EsFDz+CH7+52NYNbMKLpZGkBNQVmDFZ+c7UVHM4khju/K528FgWJEN5QW2PtlMKOvcnkq06tlH2Yo3Xyqr50kAeyVJ+hlBEE92/f2EwbmrAbxn8FlalDoYTBjuwomLftiZWGmICcNdsFAYdKVjTPIXuistZ7aR017KK5mPnPViw/xazS6m0jT7CsNYMMIM/PVIJhkiBgpuB4OtD1yLs96goptHuu1wWq0oZNVtUEoiK3IJxBbSjTAXzZlkQKmDwajSQtyz6WCv5dAkvzHSX/loV8aPQ7SFxNYHrsXC336kymwkP1epgzHUxfJkn7mg1MQkO5AkgTLjXcvKOXoBgp6CBqIoKfb/0m31uLmqDCtmjFMWOMnZxOSsYEOLbKhI2LUY/xvx14vXHVZLrJRAqdOKFTPGYvQQByRIEEVp0Ni7fUm6i+RS8TsSfUP5XZY5rbrH5WsYyWoqcjKsiO2+j4QxhKYpDCtidbPulRfYDO8p0zYyyQ1IkkCJw2o4mSJjsZAoLbBhaDCqkYPhRbFAtZE8b5xfq9qhnViSNbG/DMshP92on+ajHXopSTUW43YwKC20Y26cD2jU3slsZSPM2JmJiYlJemQjlp6Jvs5FGMaCYRZK11ZW2dgmJiYZo2d7b5xfi12HvsR9U0fjpf2nMau2Em4HgxIHgx0fncE/1VTmpW2uF+8ucdDY/P4prJ1drcoUvnF+rbKIpixhsa5e9qxF3xiNClf6esn06U0GIqnGPORzU+0DmSTmiddxS7fVK3ZEiZ3BSLdd6fvy4tm+tjHk+3nuL8ewZla1KvtdsrhHNtdaXJJyrgRBHAMwXZKkrwiCGAZgnyRJ43XOqwWwEsCfAExKJRNdspSOoijh8wudWLKt2yjetKAW48qyn2bQZECSE2nO+zJ1dqJyKWQotAQ5cydsH5NKGaYskRMynEiy5+c4QSPvJAl4AqZcDlJyRoZztIyBST+Tgf7OGRmOx+g5ygutCHH6DgfH8WnpYrPPDCjMVP1ZJlMHP74MEZ2klGCy6yd+5rJZYn27qySdw0rCHxYgSBJsNKW7I9Lot2gLCUtX2QFBlODxc6rFKn1k76bCoJXhdMYtI7nJRkAq3WvHH5d33NIWErwoIcqLYBlK+f9s32sq9230eWIZiQzKShiRk/ZEpsTvviYIQJIAkohlb6BIApIEREURFEEoGQ712i0dXSd/JutRvZKs/einZ0web8bLCRlO9x2nY8+mayub5B05IcPxmOVcM8Ms59r39IUtkc0xOtf1dTpjTx7bBZkyaP06k0uDUfzEQgIeH4elcfGOuvm1uGKIo6fKRzkpw3o6tm5BLYY4GBAEAV4QEVVK1pIIR7VlWPV8eJIklYUv6eoqvViTUczapF/JSRkeTKQy9qcTy0rsr3JsrTtjXneVAKIrY3+UFyFIUCqfZCsmJ39fFPWvr3d+Bvah8QeXaBFduyRJrri/2yRJKk44hwTwDoAFAGYgySI6giCWAFgCAJdddlnt2bNndX/3YkcYszbu16T8271sKsqLku/uNzFBHw8GqchxOMzjhDeg2R011u0wJ6LzGI8vgjvXf6DRTXuWT8v27opLLsN6GD3/7mVT0eyPmPI+gMlgUU1OyLCpi01kMtDfOSHDifT1ONRffcZcqNdv9JkcZyrD+YxRcHJ810avaFSILfAQJdgsJARJQlSQ4LRS+KojosmgNKFcvUEs3UVT8efKmekyWfgmX+u5vxzDfVNHg+NFrHrj0/6wd1Nh0MpwP/odaWMkq2NLnTjh8auOb33gWkR4Malc99S3snF/8vVIkkB7iMNX7WHVxMnG+bV4fu9xvN3QrNuf6hbUYliRzXBRWBJy0p5IJD5gSpIESABhPlZOhLGQEEUJVppEayCKi51hbPngtJLFQf73e9+4HI++9onSZmtnV6O80IZRbkefT5Tkcn8ZAOSEDCeLRfCiqLIpAZg+oEk8OSHD8ZiL6DLDXETXN/S1TTxYxuhsxlIGaLxk0Pp1Jn1Hso1RNEWCIoFQVARDEfD4OPxi73E8+e0rlWoeMhXFLF5+8DoML7QlK6eckzJspGN3PHgd7n3hQ0UfrZ9Xg1+9cwJvNzSrfHIAhnGoZJ8Z+Xd6vnh81YS6+bUocdKgSNJw42dPi4T6gr7cmJhD5KQM9yd67xNA0g2WbgcDUZSUjdFsl46ICmJa8plKzLenc3oTN64oZvHreyciHBVVcRujWF5fb0ps9oVx13rtOrDXl09NVuXF8Gb6LP0aQRB/JQjiU53/7kjxEssB/KckSY09nShJ0iZJkiZJkjSptLTU8LwwL6DUaUXdglrsXDIZdQtqUeq0IsILiEaFFG/LxKRvSEWOvSFOcZqAWB35h7bXwxvi+vNWTbIMZ6CbOD6/9FKqujgRjhdUgxoAlDqtiIoiIlEBq2ZWYWKly5T3AYYcCJq76SBuWLsPczcdxAlvAOEwf8nuKVUZ9oY4/HLvcayaWYWdSyZj1cwq/HLvcVM2ByF6+qupLXTJ9He29PDEShdWzaxCkOPh8UUgir3bdNMf9ksu6hST9MlUhvMZb4BTAgpArH8s3VaP8x0hcByPz5v9mLvpIH74yt9wqiWAOXUxGW8L8spiHPl7y7bXo7mrFGuy6z/3l2O40BnGubagqo8nnjurtlLzG4u3HoI30HPfla81q7YST+w+CjtD5ZS+7CtyXYZ7O26JogSPL6KRnWygJ6uLtx5Csz+iOX7WG9Q9N142k/WtTO7b6HpfdYZx7KIPnzR2KAvo5M+Xba/HrNpKAPr9aem2enzpDeLYRV9W27K3ZEOO5eDqnes/wLQ17+LujQdwqiWAH77yN8zddBAXOsJoD3FoD/I46w1i5a6jir6I/1cOxAKxNlu56yjOeoMp6aHekmt2Xi7Tl7ohE1KVYaN3HIwKGpsyXXs219rEJL/IdXvCxKQn+lqG832MTnWMyFYsxYyXpI+phwcniT7Mnes/wOcXfXhqz1FMW/Munv79/+Jcexj/9sfPEOFFNPsiePzWCSCI2HxWPE1tIXh8EU2Mpr/ojQwb6VhfhFfNh/zqnROKvxvvkxv59j19ZoTed1buOopl08fE/Ort9Tja1Im71u/X9a0T3+ucugP4whPAU3uO9pkvridLxy76wPOi7nHTV9CSD3rY6D2f8QaUY0/tOYrPE8+54MOZ1gDm1B3AD1/5G056/Lhrw/605TOV/iSfI69BWHf31Uo8JtVrJPu91kBUE7cxiuWlGlPOlHBUX3eFo2JG1+uzRXSSJH1TkqSrdP57A8DFrjKu6Pq3WecSUwA8TBDEGQA/B7CQIIif9eaerBYSj986HqvfbMDcTQex+s0GPH7reDAW8pINZCYm6cCLkq4C4M0BNq9hGUpXN7GM4Q6VAQVjoVBR3F2ffWKlC4/fOh73bDqI2RsPYPWbDXjslvHKQjpT3gcG+bwomCCA+6aOVvXZ+6aOBpG3G4ZMMiVRfwGx3S2MJb/0d/xzTKx04bFbYmPSDWv3ZcWZ7w/7JZ91isngxig42eyLwBPolutl08dg5a6jyrkkAf1+JagDA3qLZO+bOhpz6g5oAnaJ57pYOuPJKfla8jXaQ9EBoS/znd6MW0bBwWwFe436Ai+ImuOpLMpM1rcyCdoZT9bGMuIZ3ZOLpQEY9yeXnenzQOKloKeJjodePgyKjJXhldtObqPEf+NpagvBzlD9Mkk+UOy8vqavdUNfYvSOz7QENDZlOvZsPreJiYmJST6Qz2N0OmNEtmIpZrzExCQ19HyYxI1Ry18+jEXTRqM9GMWqNz7FN//jfSz4zUd4/NbY/JVMRTELb1ep6HxDT8feXFUGXpA08yHD46r8yT55soXOmSyCNvqO7GvH+456vrXee5U3bfWVL57OJsGBGA8YLBi957PeYPINytsOobE1pBvvTUc+U+lPchIfeb5n7qaDWPXGp/iqPawbC9a7RrLfM4qF6cXy+nrDA0UQuvYhleG8bZ8touuBPwC4r+v/7wPwRuIJkiTNkyTpMkmSRgF4DMBWSZKe7M2PiqKkEcSVu45CFKW8HMhMBh8WUl8BWPI31asJYg6xnm4aLHrJ7WCweeEkRbZXzBirazQsmz7GlPcBRD4vCpYk4IndWhmVcv/WTbJMov6S01LLabvzhfjnWDZ9jEa+e+vM94f9ks86xWRwYzQBJAdbZblOXEwiiJJ+v6LULn7i9ZP18cRze7PwTb6WfI2N+05izazqvNeX+U5vxq1Mdoyng1FfsFCk5niQE3qUzWR9K5OgndH15AWtRv2lPRQFYNyfKJLo80DipSCViQ6SACii+33KbZT4bzwVxSyCnNAvk+QDxc7ra/paN/Qleu84Vob5hOq8prZQWvZsPreJiYmJST6Qz2N0OmNEtmIpZrzExCQ1evJh5LjM0EIbHnr5sGY+b8WMsQC6bcrd9Y15OZelp2Ofuq0K399xWDMfYosrVSv75MkWOmeyCNroO7KvHf//er51svfaV7640W9GL8HCIpO+w+g92+MS5CTbHJjs81TkM5X+xFgorJgxVhMLXrq9XjcWrHeNZL9nFJ/Ti+X19YYHlqGwdrY69rx2dnXGCYsu1SK6nwH4FkEQJwB8q+tvEAQxiSCIF/rqRwVJ31iMilJeDmQmg48ilsSG+bUqBbBhfi2K2EvVlU2yQZTXN5yifGYpRvMNkiQwvrwAe5ZPwwdP3IgxZQ7d9nA7GGyYXws3m/sBEZOeyedFwaKBPSGaq+gGHYn6a8/yaRhfXgAyD+Q4nvjnmDC0IOvOvJtldO2XbOrzfNYpJoMbt4NB3QJ1/1gzq1oJtsrHExeTbH7/FNbPq9FM/JcllBBJDH66HYxhH088d3d9IzYm9N1UJ6fka+2ub8SaWdXw+CP4+Z+PYfUdV2HfY9Px+vKpeakv853ejFt9XTbLaDK0zGnVHB/ptvc4cZqsb2UStDO6XoufM1wouqFr4gSI9afEPrt2djVEScqbzCnpkMpEhygBLX4OI4ptWDu7WtEX8f+uu/tqTZuNdNv7ZZJ8oNh5fU0+l9TTe8elTgaehGolFcWsYTxOz57N5zYxMTExyQfyeYxOZ4zIVizFjJeYmKRGTz6MHJcxWmtQWcJi17IpePnB6/D/s3fv8XGU9734P88zszetZEuWLYMtc40xcXJksBRioE1IaBPSkORQG0hr44SkNoYmOc0vIdD2R5MefmkDDoeWtr7gJiRg0kLs5iSFNpdD4tAGCLGg9kkcjMPV4mLZsmRb0t5m5vn9sZrRXmb2Iu1ldvfzfr30sndndubZme/z7Hy/OzO796Vj+Mzl5+XVaBqB2xhrX/yVaWg0hslkeuzKzMkLneg8k5Og3V6zeU0ftu15wcnLt+15wZmWm1sX2q/VysW91hmow4lFVD1e+9nuF4D3BZX2ZXLqtwAAIABJREFUPIUuyCwWG6X0p+5oEGfPd//O3a0WXKhPus07LxrIq9t41fKqfcFDZySIhXPCuP0jb8dDG1fh9o+8HQvnhNE5w++ghGqyL3wHBgbU3r17XacdORnH6q1PZAVKb1cED/7RO7FoThiBAAcpKqhmWYVXHMfjBpIwcCpmwZg6+bMjIhGEjnBYr1XzqMKOnkrgqi0/yxubvnPTpVjQUdGD7LrHcCm8tsdDG1ehOxJkrDeJeNzAoZEJ5+cE7ELQ0u5ooX3sixg+ciKO1dvyjyd2b7oECzNuYU7kwhcxXEi1PpPicQMjsaRz/FLp8XyGYwrNTE3ieDbHEo3GMCy8fmL6ZyZ3Dx7GZ393Gc7tbsPBo+m4XtAewheuWObcrbe3K4JvbXgndClhmBZ0TaKnPQRdz7+4xrKUc/ctIQSu2f6kZx/PnDeoa+iKBDAaSzmPu6PBkr+cspdlWRZMBSilyl5GlTCGZ6AWOUtu/Nmx4vY8ANd5M3n1rZl+yeq2vFs/8FYkpn7SdUF7CJ+5fCnOnh9FW0hDVziAN07GMXwqfULO/I4gXjo6ibaghsmkicVdYezeexj/feWSctvk++MJ+6fK7Dut2F903Pn9gzg6nsDWtSsR1AXiKQvzokG0hTTEkxakACwF519dClgKSFkWNCEQCWrojNR9DKEMMxwbfBvDhY4pAZR0PFvDGg/Vj+9i+KxbH61Ba5rPy1/5YL2b4Gmm+7TE9+S7GG4V5X5GVKKW0sT1EuZ1VFFuOUz6LsXP44cHhvG+5T341HuXYjJp4vPf3pfXj/954yoIAAFNwLCABdFgsfMOGiaGC31nByAvJ/fK7YtN85L5moAmYVoWhk8l0RHW8ZV//zV+eGDYOUknN7d22693rO7DN594aVb1gWLtzV3njvUDWLqgHYeOjuc93ygngrtomBiuBq/9HNIl1n/9aQyNxvC+5T34zOXnOT/p2tsVwY7rBhDQBT5+3y9c673lxGcp/Wn4VBy/vyX/+0yvWnChPpnVF3UJXQqkDPe670z6+mzNYJ2eE1vqJDrLUjj45klseGA6ULev68fSBVEEgw19sEi14YvkstpfQlPteX3QVuHAyRcxXEwNtwfV2QzGM1/EsGUpPPfmSWzMOJ6497p+nH/aHMYoFeOLGC6kkcdgHiPVTEsXSKrFK8lPpUwMjydgWAphXcJUCoapENAkFnicNFdsPY3axyuIMTwDjRo7lS7alXtCX+b80ZCGyaQFw7SgSYGQLqEgZtIm3x9PANnvXUoBCSBuWNClQFCXsCyFgC55UlyDm+HY4OsYnu0xZaOOl1QW38UwT6KbGZ5EV33Ndkw8W/X6jGjSegnzOqq4QhcWBjQJTQIpU2FkPIkbMk6K2X5dP06fGy43t2mYGPbb8a1lKRybSMC0FCxLwVJAKCAxPxpybU/uxaWaAKSUVT2pp5yLBBs4R2iYGK6WUmpEbhcoW5ZK13tNy/lZ5JRpVSU+/dZ/fcZzAzT8UVI5pBRYdtocfOemS5tlcKIWFA7rWNz4CQ5lyLw9Mscmbo9W0qjjmZQC5/N4gppUI4/BjTqmEAHpvud254FAQMPirraKrqdR+zjVV6PGjlffqvTyvNaRO39n5bqz71V625M/NerYUMhsjymbcZsQEVFl1OszgvUSotK45TBuOU1PR7iljvX8dnwrpUBPR+m/CFSP3NRrncyTm0upNaLcx1IKLOrM/hnXavFb/20ULXfUxMGJiPyIY1M2bg/yO8YoNTPGN1FzYx+nmWLsEJEbjg35uE2IiMgLPyOIGl8r9uNWfM9EzYL9t3zl/fYLERERERERERERERERERERERERURPhSXRERERERERERERERERERERERETUsngSHREREREREREREREREREREREREbUsnkRHRERERERERERERERERERERERELYsn0REREREREREREREREREREREREVHLEkqperehooQQRwG8MotFzAdwrELNacT1sw3e6z+mlLqiFiuvQBwXU+/tyzbUZ/3NFMNe6r1PM/mpLYC/2jPTtjRqDPth29e7DfVev1/aEFZKvb0WK6ryOOyHbVnvNtR7/fVsQ03G4hnGcCvvF7+svxHaUMsYnijQjlrw+75olTZUev1+Oiau97ZlG/zThnLW76cYroR6b3u2ofZtaLYYLoUf9m8mtqewYu1pxhj2wz6odxvqvf5at8HPtYnZqve+5Pqb6HiiQjFc733ihzbUe/1+bEMjxbAf+WF/1oKf36dnDDfdSXSzJYTYq5QaaNX1sw3+WH+1+eH9sQ31X38z8tM29VNbAH+1x09tqQU/vN96t6He62cbKssP76Pebaj3+v3SBr/xwzapdxvqvX62wV/tqPf62QZ/rL+a/PDe2AZ/tKHe668nP7x3tsE/bWhWftu2bE9hfmtPLfjhPde7DfVev1/a0AzqvR25fsZxLj9sk3q3od7rZxuaT6tsy0Z9n/w5VyIiIiIiIiIiIiIiIiIiIiIiImpZPImOiIiIiIiIiIiIiIiIiIiIiIiIWhZPost3b4uvH2Ab/LD+avPD+2Mb6r/+ZuSnbeqntgD+ao+f2lILfni/9W5DvdcPsA2V5If3Ue821Hv9gD/a4Dd+2Cb1bkO91w+wDZnq3Y56rx9gG/yw/mryw3tjG9Lq3YZ6r7+e/PDe2YY0P7ShWflt27I9hfmtPbXgh/dc7zbUe/2AP9rQDOq9Hbl+yuWHbVLvNtR7/QDb0GxaZVs25PsUSql6t4GIiIiIiIiIiIiIiIiIiIiIiIioLngnOiIiIiIiIiIiIiIiIiIiIiIiImpZPImOiIiIiIiIiIiIiIiIiIiIiIiIWhZPoiMiIiIiIiIiIiIiIiIiIiIiIqKWxZPoiIiIiIiIiIiIiIiIiIiIiIiIqGXxJDoiIiIiIiIiIiIiIiIiIiIiIiJqWTyJjoiIiIiIiIiIiIiIiIiIiIiIiFoWT6IjIiIiIiIiIiIiIiIiIiIiIiKilsWT6IiIiIiIiIiIiIiIiIiIiIiIiKhl8SQ6IiIiIiIiIiIiIiIiIiIiIiIialk8iY6IiIiIiIiIiIiIiIiIiIiIiIhaFk+iIyIiIiIiIiIiIiIiIiIiIiIiopbFk+iIiIiIiIiIiIiIiIiIiIiIiIioZfEkOiIiIiIiIiIiIiIiIiIiIiIiImpZPImOiIiIiIiIiIiIiIiIiIiIiIiIWhZPoiMiIiIiIiIiIiIiIiIiIiIiIqKW1XQn0V1xxRUKAP/4V42/mmEc869KfzXDGOZflf5qhjHMvyr91QxjmH9V/KsJxjD/qvhXE4xh/lXxr2YYx/yr0l/NMIb5V6W/mmEM869KfzXDGOZfFf9qgjHMvyr+1QRjmH9V/KsJxjD/qvjnqelOojt27Fi9m0A0a4xjanSMYWp0jGFqdIxhanSMYWp0jGFqBoxjanSMYWp0jGFqdIxhanSMYWp0jGFqdIxhqoemO4mOiIiIiIiIiIiIiIiIiIiIiIiIqFQ8iY6IiIiIiIiIiIiIiIiIiIiIiIhaVl1PohNCXCGEOCiE+I0Q4tYC860RQighxEAt20dERERERERERERERERERERERETNrW4n0QkhNAD/AOADAJYD+AMhxHKX+ToAfAbAz2vbQiIiIiIiIiIiIiIiIiIiIiIiImp29bwT3UUAfqOUelEplQTwzwA+4jLf7QDuBBCvZeOIiIiIiIiIiIiIiIiIiIiIiIio+el1XPdiAIczHg8BeGfmDEKICwEsUUo9IoT4vNeChBAbAWwEgDPOOKPgSg3DwvB4AinTQkCT6GkPQdfr+qu2RADKi2Pyt1YdZyoVw626/aj+eDxBjY7jMDW6Vj8etiyFkYkkkoaJoK6hOxqElKLoNPIPv8RwZrwEdAldCsSSjB0qjV/imKqvWY/5ah3DzbodqX6aaRxm/2hNzRTDNO2sWx8t+zUvf+WDVWhJ9TGGyU1mni2EgCYAKaUvc+xaxHApdSrWsmimmmUcZq23cdXzJDq3KFDORCEkgLsBfLzYgpRS9wK4FwAGBgaU13yGYeG5I6ewaecghkZj6O2KYNu6fpy/sIPJG9VdqXFM/tbK40wlYriVtx/VH48nqNFxHKZG18rHw5alcPDIKWy4f6/T93asH8CyhR0A4DmNxRV/8UMMu8XS5jV9uPP7B3F0PMHYoaL8EMdUfc18zFfLGG7m7Uj10yzjMPtH62qWGKbWxRimXG559h2r+/DNJ17CZ393me9y7GrHcKEaVuYJQqxl0Uw1wzjMWm9jq2e2MgRgScbjXgCvZzzuAPB2AHuEEC8DWAXge0KIgZmucHg84SRtADA0GsOmnYMYHk/MdJFERFk4zswOtx81AsYpNTPGN1F9jEwkncIJkO57G+7fi5GJZMFpRLnc4uXmXfux6bJzGTtE5OAxX2VwOxJ5Y/8gIqJm4ZZn37J7P1b3L2nJHLuUOhVrWdTqWOttbPW8E90vACwVQpwN4DUAHwXwh/ZEpdQJAPPtx0KIPQA+r5TaO9MVpkzLCUbb0GgMhmnNdJFERFk4zswOtx81AsYpNTPGN1F9JA3Tte8lDdP5v9c0okxesdQZCTj/Z+wQEY/5KoPbkcgb+wcRETWLQnl2K+bYxWpYpc5D1MxY621sdbsTnVLKAPApAD8A8GsADyulfiWE+J9CiA9XY50BTaK3K5L1XG9XBLrG24cTUWVwnJkdbj9qBIxTamaMb6L6COqaa98L6lrBaUS5vOJlLJZy/s/YISIe81UGtyORN/YPIiJqFoXy7FbMsUupU7GWRa2Otd7GVteMRSn1b0qp85RS5yqlvjz13F8opb7nMu9ls7kLHQD0tIewbV2/E5S9XRFsW9ePnvbQbBZLROTgODM73H7UCBin1MwY30T10R0NYsf6gay+t2P9ALqjwYLTiHK5xcvmNX3YtucFxg4ROXjMVxncjkTe2D+IiKhZuOXZd6zuw+7Bwy2ZY5dSp2Iti1oda72NTSil6t2GihoYGFB793qfa2cYFobHEzBMC7om0dMegq7z6icqiajViorFMfmbj8eZhohhH28/qj/fxDDjlGbINzFcCOObiqhJHLfi8bBlKYxMJJE0TAR1Dd3RIKQURadR2Zo+hjPjJaBL6FIglmTsNJGGOJ4g/6vjMV9TxTCPnVtSU8VwNbF/+BZjmMp21q2Plv2al7/ywSq0xNH0eR35S2aeLYSAJgAp5Wxy7IaO4VLqVKxlNb2GjuFaYK3X9zw3uF7LVviBrkss6owUn5GIaIY4zswOtx81AsYpNTPGN1F9SCmwoMP9zhyFphHlco2XaH3aQkT+xWO+yuB2JPLG/kFERM2CdZlspWwPbjNqdaz1Ni5e9kNEREREREREREREREREREREREQtiyfRERERERERERERERERERERERERUcviSXRERERERERERERERERERERERETUsngSHREREREREREREREREREREREREbUsvd4NqId43MBILAkhAKUASymEdA3z20OQUtS7eUQF2fFrWAq6FOiOBBEOt2RXJqI64BiUxu1A1NjYh6kaLEthZCKJpGEiqGvojgZLzi8zXxvQJAzTgjmVp9r/16SEJgApJbqjQQDAWCyJWNKEqRTCuoagLjCZMJGyFEK6hGWpdJxrEj3tIeg6r6MjqiXDsDA8nkDKtKBLgZAuMZE0EQlosJRCwrCcvmoqhVBAw/xoY9amMscxIQQABUsBASkgBJA0FQJSwFIKgIAmgJhhQZMCkaBEV6Qx3zcRjyuJ/IP9kYjI/2ZTO6mnrLqNLhHU0vUXw1LQpEA4IBFPWc5n0Py2IEIhfgaVKjcuuiIBHI8lEU+Z0IRAJKihM5IdK5alcGwi4cwT0CSUUk7dzLJUVj4eDkjMCQVwKmlM19IK5OClxqofY9qPbWpUmdsyHJQwTSBpWjAthUhAg64JxJLpOogmgFBAYjJpAVBQCjCnxoi2oIQQAhOJysUeVU/Ljd7xuIFDIxP4u8eex8cuORu37N6PodEYersi2HHdAJad1sEgJN+y4/fGnYNO3G5d14+l3VEWBOqAH2L1x31QWxyD0rgdqNk1+9jKPkzVYFkKB4+cwob7907nl+sHsGxh8fwy87UL2kP4whXLcPOu/Vn/t5d5x+o+fPOJl3DrB94KADhyMp41feu6fvzdY8/j6Klk3mu3revH+Qs7eCId1UWzf7a4MQwLzx05hU0Znzdb1q7ET58bxruW9eCPv/WMaz8vdezwE7cx0B6vrr/0bHS3B7F772Fcdv5CRIIatvzkN7j+0rNx5/cP4uh4ApvX9GHhHANndUcb6n2XohVjv1m57ctk0uRxJZFPlJrncVwmIqqf2dRO6im33e9b3oNPv3cpbnzwmenHl5+X9xl03vwoT6QrgVtcbFvXj3seex4/PDCM3q7IVM4YdnJGy1I4+OYpbHhg+jWb1/Q5+eZtVy7HiZiRl48nOiy8djyGzz68r2AMlhqrfoxpP7apUeXWbL/04eWYTJpZNZy7r1mBv/q353B0PIF//Fg/UqcU/u7Hh/LOQ9qydiXmRHT81aO/duK6UWKqFbVU9dyyFEZiSdy4cxCr+5c4gQsAQ6MxbHhgL0YmknVuJZE3O34z4/bGnYMYiTFua83+ELtqy89w6R0/wVVbfoaDR07BslS9m9YyqrkP4nEDr41O4pWRCbw2Ool43KhAixsfx6A0bgdqZn76fKvWWMw+TNUwMpF0ihvAVH55v3d+aVkKR08lcOREDG+ejDuv3XTZuU4hJvP/9jJv2b0fq/uX4JWRSbwyMpk33c513V67aecghscTOHoqgddGJ3H0VILHruSwY7JYbJQ6X+5ryv1sKbaearY39/XHJ9Kvf/X4BIZPxnF8It13Xx+LOf8OjU7i9bEY3jgxiddGJ/HGiUkcORV3CvZAuh/e9OAz+MjKXvzxt57x7OeFxg6/chsD7fHq5l378dpoHGsGzsDNu/ZjdCLlPL/psnMxNBrDzbv245WRybLedyKRfZwwfDKGN6b2if3c8Yl43v9fH4vBMKxqbYosfjquotnx2pc8rqRW56f6WSn9keMyEVHleeVcbs/PtHaSuYzMesrrY7GK1jcMw8LrY7G8vCG33av7lzgn0DmPXT6Djk22zjFhoTjIyqlPxfNi5I0Tsby42DRV37If2znjm1M5+ZsnYs4JdJnz2PlmwlCu+bhpwjmBzn5+w/17cWw8kdXOzFpd1nwT2XW1YxOJsmK62PaqhHL7GXnL3L+bLjsXxydSeTWczz68z6lt6FLDjQ8+43oe0k0PPgPDRFZcb7h/L944ka4pzXScpOpoqdOfRybSt/IeGo2hMxJwgs82NBpD0jDr1Dqi4uz4zTQ0GoPBRL/mvD7EvnPTpVjQEapz61pDtfYB71DkjWNQGrcDNTO/fL5VcyxmH6ZqSBpmyfml/eXd3T86iJve8xZ0hKdz08w81Stn7YwEsh57TXebljItXLP9SV7JSFmqfYV1uZ8txdZTqyvCLUvh5ZGJvDs+/u1HL4AmBbb85Dd5Vxbbd1/72CVnY1Fn2LUfKqWK9vNGq015jYH2+2sLatCkcP7fBi1vvGoLaiW/70TCwPPHso8TtqxdiUf3vYbLzl/o3OFu67p+7Pn1ETw0OIQta1di55Ov4IkXR2p2Z06/HFfR7Hntywf/6J08rqSW5bf6WSl5HsdlIqLK8sq5li5ox6Gj43nPzwnrZddOMpdx/ycuQsKwcPePDub/2tws6xtudxK384ZETr6Tm8d55XWtckxYKA5eHZ3My6lzY+Suq1eUVP9qC2p4fSydU3e3h1xfY+ebUrjXxUzlfrwwmTLxxtGY085dmy52ny9hYt3Xfu68l52fdM8HCuW21b7TWDk1SvJmWQqx5PS2LFRvtafZcec1JkiBvLh+40Qca7Y96cRBRxnjJFVPS92JLmmY0KVAb1cEY7EUersiWdN7uyIQgl8ekH/Z8ZuptysCnV961RwPQuqvWvsg88rVn//pe/DQxlWYE9YxEku2/B3pOAalcTtQM6vX51vuHQxMGFW7qwf7MFVDUNdc4yqoa3nz2l/ere5fgtGJFF4dmXRem5mneuWsY7EUJpMmJpOm53Sv16ZMhQXtIWy/rh9b165EQJN4bYx3pWt1pV7lOtOrYcs9yfTNk3FMJAzcduVyXLikM289M2nvhUs6cduVyzGRMPDmyXjReLfbYSkgnrKwoD3krOuHv3wD3dEQ/uz3lmNRZxh/9wcX4KGNq3Dblcvx+MEj+PMPLk/3f0161p2K9fNG4zUG2u9vMmnCtJTzf/v5sVjKmXcymY6H9F0fJjEy4b2fjk3m323opgefce52Z18FfuPOQXxkZa8zfcO7zsHQ6PSdOauNdYPm4bUvCx1X+uXuXETVUs07Mc7kDnel5Hkcl4mo0qp5N6lG4JWbDY+7350rMxeyFaudZC7jlZFJp56S92tzs7xT0/B4Iu/OZXbeIJCdp+XmcV55XavUGt321d0/Oogjp/Jz6gXtIbx5Io7XTsTw5ok4LjmnG/OiQc98MvPxZNLEwjlhtAV1hHT3fNvONy2Vn1v3dkWgecSgYaqsO4yNTCRd53vp2ETW+3zp2ETJMV1oe1XyTmPl1CjJ28hEEjKnflOoFgvAiTuvMcFSyIvrrmgQ1/T3OjWr3PHGns/tHKbMz6DhU3Hnboqt+HlUaS11Et3ciIbOiMTWdf3YPXgYd6zuc4KwtyuCez56IbTW+DyjBmXHb2bcbl3Xj85IS3VlX+BBSP1Vax/YV67+/E/fg+HxFK699ym8e/MeXHvvUzg0MtHSxe/uSNB1DOqOBOvcstriWEzNrB6fb/YdDDLH2xdHEti9aVXWfJW6gpNjGVVDdzSIHesHsuJqx/oBdEfz48r+8q4zEkBbUMM9jx1yctNte17A5jX5/7eXecfqPuwePIzerjAWzg3lTbdzXbfXbl3Xj2deHsHn378MuwcP42TcwMfvexq/fece/pRViyv1C+WZfvFc6meLfTX2NdufxJptT+L2Rw7g8+9f5pxIZ6+n3PZeuKQTn3//Mtz+yAGs2fYkrtn+ZMF4z2zH7/yvn+K27/7Sacc1/b344IrF+IMdT+Gyr+7BdV97GvGUha/8+3PYPXgYqweWYPhkHGv/8ef42/9zCFvWrszqh1vWrsR3nxnCP/zhSs9+ftfVK9Bo37W4jYH2eLV5TR8Wd4Wxa++r2LymD13RgPP8tj0voLcrMrUNwvjLf/0V3r15D67Z/hRePjaJl0cmXPeT192G7LvdZV4hrpTKmm7/3zCr/5OurBs0D699WSg3ZC2Bml217vDtlh+W0odKyfM4LhNRJfEnor1zs5RpuR+vC5RdO8nUFpy+o3WlT4r2arNhWhACWecU7B48jK0Zud7uwcOun0Ht4db4viB3X124pBMfu+RsXHvvU1k59TX9vfj8+5fhtu/+Eu/evAf/9PQrWHfxmdj8g+fyztmw61v2YzuXvP2RX8FUCvc/8RLuunpF1msy801dQ9Y+svNxTQPuvib7ddvW9UOp7P2/bc8LeW3atq4f9zx2KOu93/PYIWzP2fdeMe21vYDKntRfTo2SvKX3h3LiaNueFzAvGsir4dx9zQqntmFYJrauXel6HtKWtSuha8iK623r+vEfB4/guovPdGpWf/mvv8qrJd2xui/vHKbcz6Df3/IEDr55Cp/61rMt+XlUaS31u3QnYiauvfcp7N60Cl/80NsgBPDQxlWwlIIuJb74vV/iy1f11buZRJ7GYhbO7A7hoY2rYFgKuhToiEiMxSxEw/VuXWuxD0Jyb7fLg5DaqdY+sK9cNSy4XlH70MZVWNyiP+saDutY2h3NGoO6I8GW+5lbjsXUzOrx+eZ1B4OHNmafRFepKzg5llE1SCmwbGEHvnPTpUgaJoK6hu5o0PVnGOwv78ZiKQQ1iaPjCXz1BwfxrQ2rMDqRRGdbAA9tXIWEYSGgCTz4R++EOVX0CAckbrvybbj9kV/h+kvPhi4lHvjERTCVwthkChLAX3zobbAshYAunTg3LIWHn34FV7/jTHz8vqdx25XLXa/a5k9ZtSY7JjOLuG5fKJc6X65SP1vcrsa+Zfd+3Hblctz+yAFnPeW2d9Nl55YV74Xacc78KK7/xi+ypt28Kz0NAF4bjeO27/4SQ6MxPDw4BAD4xvUXIaAJ6FIgqEt86MLFCOsSuzZdjKRhIahLPLxxFVKWwuHjk/jaf76IL3347QW3qd/kjoFCCAgo/MWH3oaAFBACuO6SsxGQAqZS+NKH3w5NAH/z0QsghQCgcPsjB/DDA8MA0tv1f/zzf+H2j7wdHeFA3n6yc7bcGLDvdpd5hzv7am17uv1/Xav+F1qsGzQPr305nlB5uWFnROL9f/sEawnU9LzG4tnmbIXyw0J9qJQ8j+MyEVUSfyLaOzcLTN2VO/d5KWXZtZPMZdh3gbLv8lRublqIV5t1TUIphW8+8RJuu3I5OiPp/CSWNPHPG1fBshQ0KRAOyKzPoPawRCIFoPFuNF623H3lloPfsns/7vv4O7Ly6dX9S3DTg89gaDSGo6eSuO3K5eiOBnHa3DAeeOIlrL/4LPzZ7y2HgsKbJ+L4y+8dwLOHx3DgjVO47crl+Mq/P4ev/P5/Q++8NkABQgAnYyms7l+Cv3r01/jj97wFD3zyIkiRzscDusTJWAqAcGppb56I457HnscXrnhr1nt49vAYvvnES7jv4+/A8YkkJpMmejpCOJpzR/Oj4wmc3hkuKaa9thdQ2ZP6y6lRkregruFELIV4ysLtH3k72oIaLJWuOfzThvT5RSdiKSRSFu66ZgUCmsTYZBKWUrjlA29FZGpMMJWCJgSShokTkyn86Qfeii9ccT6OjScRS5q4dGlPVr+w6yJ27I3FUvjmEy/lncPk9hlk16dueGCw5T6PKq2lMnf76qh3/vVPsp5/aOMqnDYVpc7DAAAgAElEQVQ3jD/5nfOYMJGvGZZC35cey3v+pzdfVvvGtDgehNRftfaBfeVqta6obXThsN7yhX+OxdTM6vH5Vmi8tQsKlb5bHMcyqgYpRUmFCfvLu7t/dBA3vect2LymDzfv2o+/f+wQ1l18Jtb+489x/ycuwnvv+mnea3/yuXfjZNzADw8M45O/dQ6u3v5k3jwPbVyFBR0hvOuvf5w37Q9XnVW1q7apcZX6hfJMv3gu9bPF62pse732espt70TCKCvevdrRGQk4dzpzm5b52Pbw4BAeHhzCQxtXQZMC3dEg3uPWtz//brznqz91rkTuaW+8ImehMfCVkQm8e/Me57F9ovy19z7lPLYLxbah0Rjagprrfprfls7Z7JMs7Ku67bvd3fn9g86xw3efGXKm73j8xZpuY9YNmofXvkwmTRwamciKxQf/6J2sJVBLsOtnmfFfiZxtNvW4Ynkex2UiqiT+RLR3btbTHvLM2cqtnWQu48zuNqeecsfqPudErUqcFN3THsK2df3OT7pm5g1KKXzm8vOcabs2XYw1257My2sy/fTmy7B4bgucQYf8fdUdDRa8c7gtszb17OEx3PDAIID0ttv+Hy9j+3+8jIc2rsrbvnYO/uzhMaz72tOu8wDAJ3/rHHzkH9L590MbV+Fr//ki/vT33upaS/uzDy536nP2/t/w2+fgC7v24+h4AjvWD2Bem3u8d0bKO5aoxUn9pfYz8tYdDSKeMjC3TYdhWfjct/c5++tvP3oB/r9Hfo2j4wlsXtOHiYQBSyn88beedebZvm4l2kI63vPVn+LHn3s33nvX43nrsGtFuf3lhweGsfFd5+Lae5/yjI9CtSv7/630eVRpLfXNkdfVUZNJE7oUOP+0OUyYyNeqdYUfzQwPQuqvGvvAvnJ1JJZkfyNXHIup2dX6861Qn+Ld4qgZ2V/effmqPliWBSHE1JWJQEdIOkVY96tSJea3BwteeT2ZNJ27MXldDV6Nq7apcZX6hfJsvngu5bPF62rsRZ0RnDYn7Kyn3Pa+eTJeVrx7tWNxVwQC7n3TvvNZ0OPuBZNJE+ctbHce57VFk3j85sugaxI97SHoenP97E/uXR3sO3HazxUaz9z2Uyik47z52XcbCmgCH7/0HMipO9zpUiASlPjwhYvx+/29iAQlPvXet+BPfve8mm5j1g2ah9u+dLvzFeDez5kvUrOp1h2+q11z4bhMRJVS7btJNYJCudlsT1r2WgYAp57y8A0XQylVkZOidV3i/IUdePiGi2GYVl5utqynHQ/fcDFSpuV8VuXmNTb7c6vZ8jovbncmd9smIT0/L/TadsVyRTsHB6bvUOg1T29XBL1dEXz5qj4o5V4vawtoWHZah1OfC+sSuibw9394YUXj2m178aR+f5JSYHFnG07Gk5gbDjh3ngxoEpoU+NuPXgApBQJSwAIQ1AX+5aZLkDIsBHQJXQrEU1bWXfPLqeEu6ozgZ7e8xzM+vD6DMuO+lT6PKq01Ru8p3ZEgtuX8LvXmNX1YMi+C+W0cnMj/7Cv8MmO4kndlIaK0cFhnfyNPjA2iyirUpxZ3teHM7igWd7XxBDpqKvaXdwvnRtAzJ4zFXW04Y14buqLp/y/sCOflrtvW9WNhRxinz41gx3UD2D14GHddvcI1v92191Xcsbova1rm1eC7Bw+7Tued2VuXHZOLu9qwoCPkWR8pdb6ZsK/Gzo3LzBPoZtLe0+aEXZfrFe9e7Vg0N+LaNzev6cO2PS9g9+BhLJkXwd3X5PfLM7vbcLrH6+2+fUZ3FIs6I035RYt9Vwf7fe8ePIzFXWFsXpMeh7btecH5PwDnyu4zu9s891MopGcdJ/TMieD0zggWzo04z82LhrP+38zbmOonHM6OReaL1Epy478SORv7EBE1Cq+8odXyaq/crBK5o9syMuspizojFc1NdV1iUWfENW8IBDQs6kznGqfPjTi1lfntwbxcZlsLfm5l7iuvHHxhR/bzuwcP5+XHdu3Kft4tV9yydiV2Dx52Htt3KHTL0+1lnj43ggUdIcyfqovlrnN+ewjzoiGnPtczJ+w8rnRcV3I5VF1SCnS2pceb3q42nNEdxemd6VruGd1R9Ha1YeHcCE6fG0F3NIyejnRdt6cjHT92X9i191XXWlJXNOA6za6FFYoPt8+g3Lhvtc+jShJKNdet5AcGBtTevXs9p8fjBo7HkkhN/UZ5UJOYG9IRCvFLOSqqZp9gheI4HjcwEkvyriw0E76I4UbC/uY7volhxgbNkG9i2G/YpxpKTeK40WK4GgzDwvB4wvUKaMtSODaegGlZUCr9s1eaFIgENcwJBTAaS8GyLJgKeVdlW5bCyETSc3oLYAz7mB2flb4au9zlFpo/s28GNIlgQCCetBDUNXRFAjiZSCGeNLP6ZebPuxTq2yVqyOMJw7BwdDyBlGlBSoFoUCJlAknTgmUphAMaUqYF01LQNYlQQKArwi8TmlRDxnA5eGzb9Jo+huuNfajqGMNN4qxbHy37NS9/5YO+X1eJfJHXVSt/If/LrK0IIZCcymUCUmBeaZ9bvojhavHqG7nPd0XSNazc+TLz5nAgfTetuGFBE0A0pCFpKqQMK+sOhfZy7buAxZLu/ZL9tmKaOoYrxY43AYWUqZyaiH0HO21qzHDrB6Uuu5S4J1eeG6jlMo9wWMciJlzUwMJhHYsZw0Q1wf5GXhgbRJXFPkWUz74C2o2UAj1zwp6vLfQTVfwJK/KzasVnucstNL9r34xO/3eeHsp6XNLrW4CuS5zegu+bWhOPbYlmh32IiBoF8+vWxX1fmNf2cXvebb6Z5M15y/HIy7nvqJZKjbeZxKTrsgvUo6h0df39AiHEFUKIg0KI3wghbnWZ/v8IIQ4IIfYLIR4TQpxZj3YSERERERERERERERERERERERFRc6rbSXRCCA3APwD4AIDlAP5ACLE8Z7ZnAQwopfoA7AJwZ21bSURERERERERERERERERERERERM2snvfEvgjAb5RSLwKAEOKfAXwEwAF7BqXUTzLmfwrAutmuNB43MBJLwrAUdCnQHQkiGNRwfDIB01RQSP/4bcpSMC2FSECDaSkoKECln9fs3ylWCpqUEAJIGFO/da5JhAMCk0kLlqWgaxICClIImJaCoRTCAQ3zIkEcjyWRSJmIBDQkDAvG1Ot72kPQ9Zmf38jf8i5No24ntxgO8/b2RFnYT6ZxW1QHtyvZGAuzV89tmEgYODY5ve75bUGEQvnrTqVMxM0UTsasvHbmtr8zIjEWs9AdCULTBIbHE860nvYQAgGtaLsYV8UVO5YvNN1tGoCy5pdSwLIUjk0kEE+a0KRASJeIG+k8MBzUMD8acuYbmUjCsiyYCkiZFnQpENAk4oYJKdL5ZUCXmBMK4GQihVjShDGVjxqmhZSlENYlrKnXa1JACEAKAaWA5NRzYV1CISM/nVpuylTQBCBE+j3FpvJQIL28zO1wbCKBeMqEJgQiQQ2dkeLbop782KZmk7uNuyIBHJ9MIpZKx35Qk5jXFnStYzj9xCOmyl2/EAKaAKSUFd/XhcYGAeXUbXQpEA1pmBNOr98wLBwdT0CTQMpM15I0KRDQhPM4rEuYCtA1gWTGciJBCSmAiUT+54vf2e87aVrobNOgFGCp9LSUoZy6WlCXCOnpscowFaypMSsgBUIBCcNUiBvpcTGkSyiIqvTjVMrM+0zWNFn086ArEsBoLJU3xhiGheHxBFKmVZFaHjUXHss1llbYX63wHlsd9zFRc2rVfLfc913K/K557dT39JqU0AQQN6ysWokQAkFNIGkq6FP5nj3OtoUkorqOiZSByaSFtqDEZLLx8jo3dh6fSKVrVlICmpRZda7cPH9OKJ032bUvS6XPjRBCQVlAKCCRSKW3j13TAgBNCCRMC5pI59lJUyFlWEVz8oAuYBjp8zCUUjAVoJTKy+HCAYmEoZxaXHtYQ0doermWld7PhmnBUAqaSLdNKSCgCyQNhaAUgBB59bOT8SQmEqZzfseCaBBjccMzl3TLLe12uNUcRyaSSBgmBOC0KRxI1w4z1+PVP6rRj/wot+5qx54m0jUYe/+HdQlAIG5M17I0CUwkTEgpoE/9JU0FTJ0xZJgW5NR5QaZKnyskRLr20R6SGE9YMKfO/ZkfTf+sqr0NA7qELgUmk9P70FJAZKovCAlYFmBYCu1BDfGsmpN06kR2vUFKMeNaeKso9bueUtRz9F4M4HDG4yEA7yww/ycB/LvbBCHERgAbAeCMM87wXEA8buDQyARu3DmIodEYersiuO/6d0ACiKdMZ4OejBu4edd+LGgP4QtXLMN9P3sJn/ytc/C5b+9zXrd5TR/aQzqCusDxiRRu3rXfmbZtXT/+9b+GsP0/XkZvVwR/c+0FCGgCf/ytZzE0GsP7lvfgM5efh007B3HJOd1Yd/GZuOnBZ7Jef/7CjhkV3yxL4eCRU9hw/15neTvWD2DZwo6W6yiF+HE7lRLHbjG8dV0/lnZHG/ZgjJpHqWNxtbGfTOO2KM9sjie4XVuT32LBL+NwOeq5DRMJA88fy1/3efOjWclVKmVi0kjh1eMJ13a6tX/hnAAOjUzgnO4Qrr33qaxp5/e0FzyRzm9xVUulxnCxY/lC0wHkTbv/ExchYVglz79j/QCWLmjHoaPjzvPvW96DT713aVZelznf3T866JpT3vn9gzg6nsDmNX2YFw3g+EQSR08lsvLR3P/br7/r6hUIB2RWnnnz+5fh2Hgya76ta1fikX2v4V3LFuKbT7yE6y89G9955jVctXJx1nz3f+IiJFIWNjywN6uNC+eEcVZ31HNb1DOH8lte14jjcDG52ziznpEZJyc7QjhrXjSrjuG2fzJjqpR95LaMO1b34ZtPvITP/u6yiu1rr1gK6RIPPf0KPrhicVb/3rJ2JbraDJzWEcbB4XH8638NZc2TOSbY/XfPc0fylrP9un4EdYnr7/uFb8b8UuLYMCw8d+QUNu0cxBevfCtWnNEJY+oMuomEiWNT41jm++yKBpBImbjua9Pv9e5rViCoS3zpewdwdDyBLWtX4tF9r+G/r1xS0X6cSpl4bng877N1fnsAV297quDnwbZ1/bjnsefxwwPDTly8ZX4UB4fHs/rBbGp5VFn1Hotb+ViuEflxf1U6hv34Hqmy/LaP6z0OE82WX2LYb/lurZT7vkuZ322e3OP8zWv68moldl736L7X8nK5rWtXYlFXGK+PJfDy0ZM4a8GcphiHi+XgufUwO6/rigZx5/efw8cuORu37N6f9drHDx7BlSsW48aM7Wcv8/pLz3ZqY1vWrsTf//iQs0/s/Ox/P3PYNSd/dN9r+L2+RYinLKfellmzcKulpeu2FkbGU7j7Rwdx03vegpRh4bMP78tr26ffuxSP7HsNl52/EG1Bzclbd6wfQGebjqOnklk1gE9ffp4TA7m1E7dail1zWP/1pwvWHHPbNN5mYu2OnxfsH9XoR7VUbo347h8dzIu9v//DC5196xYLm9f0Ze3Xu69ZgbltAXz1B+413EhQw5af/Aaf/K1z8LX/fBGfvvw8/F1mreC6AYQC2fszs/Zr94UPrliMv//xIae9uecK3fDbZ+HKC3qzxpNt6/oxN6LjDzz2u9/2Xz2U+l1PqepZ2XHbY8p1RiHWARgAsNltulLqXqXUgFJqYMGCBZ4rHIklnQ0HAEOjMQwdj+HV4zEMn0ri+EQKw6emv3DYdNm5uHnXfqzuX+J0FPt1N+/aj2PjSWhSc+a3p23aOYg1A2c4j//kof/C8YmUM8/q/iXOILnhXec4nSLz9cPjieJb0O09TiSdDmIvb8P9ezEykZzR8pqVH7dTKXHsFsM37hzESIz7l+qv1LG42thPpnFblGc2xxPcrq3Jb7Hgl3G4HPXchscm3dd9bDJ73cPjCYzHLc92uj2fMoAbdw5iLGblTSt2nO+3uKqlksfhIsfyhaa7TXtlZLKs+TfcvxfD44ms51f3L8nL6zLn88opN112rvN/TWo4fDyWl4/m/t9+/ee+vS8vzxwajefNd+ODz2DNwBm4ZXc6t715135seNc5efO9MjLpnECX2cZXRiYLbot65lB+a1MjjsPF5G7jzHoGMB0nh4/H8sY3t/2TGVMzWf/QaMyJ5Urua69YemVkEmsGzsjr3zc9+AwShsLweMKpAWXOkzkm2P3XbTk3PDCIoeMxX435pcSx/b6HRmNYvmgukoaCaQKmCQxljGPA9Ps0TUCXWtbzn304PY7ZY+FNU+NVpfvx8HjC9bPVMFH082DTzkGs7l/iPLbH9tx+MJtaHlVWvcfiVj6Wa0R+3F+VjmE/vkeqLL/t43qPw0Sz5ZcY9lu+Wyvlvu9S5nebJ/c4361WYud1brncjQ8+g3gyXS+88MzuphmHi+XgufUwO687fDyG1f1LnJOYMl+7ZuAM5wS63GVm1sZuevCZrH1i52deOfmagTNwfCKVVW/LrFm41dJu3DmIpKGcWt3oRMo5gS63bXY97eZd+7Py1g3374VhIq8GkBkDubUTt1qKXXMoVnPMbVPKUEX7RzX6US2VWyN2i73MfesWC7n79bMP78Nro3HPGu7oRMqZZu/vrFrBA/n7MzO+7b5gx7nd3txzhdYMnJE3nmzaOYhEgf3ut/1XD6V+11Oqel5qNARgScbjXgCv584khPgdAH8O4N1KqVlVowxrOrhsbcH8u0DY83RGAhgajTn/5s7TFtQgBVynaRlnddrz2jKXp0nh+nrDtGbwDoGkYbouL2mYM1pes2rU7eQWw0OjMeeKbyJiP8nEbVEd3K5kYyzMXj23Yanrth97zVvo+dxllfLeGFfFFTuWLzbdLScsZ/6h0RhSppX1vFfOaEzN5zW9MxJw/i9FdlsyX1MoJ81sg1d77bzTXo5bHuq1HdqCWsFtUc8cqlHzukaSu40LxWJuHcNr/2TGVLnrt5dht6NS+7pQW73qNlJMj9m587j1X6/l5NalGmHMzxwD7bbaLfYaSyyV/57s998GzXlsb6dK9mOvz9bcNnm13R5f7ceen9UzrOVRc+GxXGNphf3VCu+x1XEfEzWnVs13y33fpcxfKK/MfOyV13l+lz81/ppNNA4Xy8GNnHqYPd3O6wrVpLyWmVnPytwndn7m9XpNirwcrpRamr2/CtXRcvd9bt5qKuW53lIeZ2633Odya465bcq9sZhb/6hGP/Iju91u29erxmpz26+F4jhzWm7sZs6T+7rMOMutzwL55woVqkHlPldqLbwVVPp4uJ53ovsFgKVCiLOFEEEAHwXwvcwZhBAXAtgO4MNKqeHZrlCXAr1dkaznJpNm3p89z1gshd6uiPNvpt6uCCaTJiwF12lmxg6x57VlLs+0lOvrdW1muyaoa67LC+rePxnVihp1O7nFcG9XBHqL3IqTqBTsJ9O4LaqD25VsjIXZq+c2LHXduhQF5y30fO6ySnlvjKviih3LF5ruNi0zByxl/t6uCAKazHreK2fUp+bzmj4WSzn/txRc89FCy8/NM73ei5132stxy0O9XjuZNAtui3rmUH5sU7PJ3caFYjG3juG1f+yYmsn67WXY7ajUvi7UVq+6jaWmx+zcedz6r9dyMvux/Zzfx/zMMVCXApoU0ET6z2sskUJAivzPxcmkmTUW2tupkv3Y67M1tz1ebbfbZz/2/KyeYS2PmguP5RpLK+yvVniPrY77mKg5tWq+W+77LmX+Qnll5mOvvM7zu/yp8VdronG4WA6u59TD7Ol2XleoJuW1zMx8MHOf2PmZ1+tNS+XlcKXU0uz9VaiOlrvvc/NWTQjP9ZbyOHO75T6XW3PMbVPuOUFu/aMa/ciP7Ha7bV+vGqvNbb8WiuPMabmxmzlP7uvc6h2FzhUqVIPKfa6UWnirqPTxcN2qO0opA8CnAPwAwK8BPKyU+pUQ4n8KIT48NdtmAO0Avi2E+C8hxPc8FleS7kgQW9f1OxuwtyuC3nkRnDEvgp6OIOZFA+jpCGLzmj70dkWwbc8L2LymD7sHD+Ouq1dkvW7zmj7Mbw/CtExnfnvatnX92LX3Vefx31x7AeZFA848uwcPY9tUO3Y8/iK2rF2Z9/qe9tDM3mM0iB3rB7KWt2P9ALqjwZlvuCbUqNvJLYa3rutHd8Tf7SaqJfaTadwW1cHtSjbGwuzVcxvOb3Nf9/y27HX3tIfQHpae7XR7PqADW9f1ozMi86YVO85nXBVX7Fi+0HS3aWd2t5U1/471A+hpD2U9v3vwcF5elzmfV065bc8Lzv9Ny8SSeZG8fDT3//br77p6RV6e2dsVzptv69qV2LX3VdyxOp3bbl7Thx2Pv5g335ndbdhx3UBeG8/sbiu4LeqZQ/mxTc0mdxtn1jOA6ThZMi+SN7657Z/MmJrJ+nu7Ik4sV3Jfe8XSmd1t2LX31bz+vWXtSoR0gZ72kFMDypwnc0yw+6/bcrZf14/eeZGGG/Pt993bFcGB108gqAtoGqBpQG/GOAZMv09NAwzLzHr+7mvS45g9Fm6ZGq8q3Y972kOun626hqzn3D4Ptq3rx+7Bw85je2zP7QezqeVRc+GxXGNphf3VCu+x1XEfEzWnVs13y33fpczvNk/ucb5brcTO69xyua1rVyIcTNcLn31lpGnG4WI5eG49zM7rlsyLYPfgYdyxui/vtbv2voqtOdsvs0aVmQ9m7hM7P/PKyXftfRXzooGseltmzcKtlrZ1XT+CunBqdV3RAO6+ZoVr2+x62uY1fVl56471A9A15NUAMmMgt3biVkuxaw7Fao65bQroIu81uf2jGv3Ij+x2u8Ve5r51i4Xc/Xr3NSuwuCvsWcPtigacafb+zqoVXJe/PzPj2+4Ldpzb7c09V2jX3lfzxpNt6/oRKrDfG3X/VVKp3/WUSiiXn1NoZAMDA2rv3r2e0+NxAyOxJAxLQZcC3ZEggkENxycTME0FBUAASFkKlqUQDmhTd5VTUCp9K0ApBQJSwFIKmpQQAkgYFkxLIaBJhAMCk0kLllLQpYSAghQCpqVgKCAckJgXCeJ4LIlEykIkIJEwLBhTr+9pD0HXZ35+o2UpjEwkkTTSV3d3R4OQDXi2e7XNYDvVbCMWimO3GA6H6/nLzNRAfBHDtcB+Mq3JtoVvYrjJtivNQpmx4JsY9pN69qdEwsCxyel1z28LIhTKX3cqZSJupnAyZuW1M7f9nRGJsZiF7kgQmiYwPJ5wpvW0hxAIFL8CzOdjTE3iuFgMFzuWLzTdbRqAsuaXUsCyFI5NJBBPmdCEQEiXiBvpPDAc0DA/GnLmG5lIwrIsmAowTAuaFAhoEgnDhBDp/DKgS8wJBXAykUJs6u5X4UD6JzJTlkJYl7BU+mcUNSkgBSCEgJp6TkqBsC6hkJGfTi03ZSpoU/MDQDxlIjwViynTytoO6fdkQRNAJKihM1J8W9STX/O6RhqHi8ndxl2RAI5PJhFPmZBSIKhJzGsLutYxpvuJe0yVu34hBDQBSCkrHn+FxgYB5dRtdCkQDWmYE06v3zAsHB1PQJNAylQwLTXVx4XzOKxLmArQNYFkxnIiQQkpgIlE/udLAb44nrDfd9K00NmmQSk4V0anDOXU1QK6REgXUAAMQznjmC4FQgEJw1SIG1OPdQkFUZWxJZUy8z6TNU0W/TzoigQwGkvljTGGYaWXZ1rQK1DLazG+iOFq8vmxHOWYwf5quBhmTDY/1iZa01m3Plr2a17+ygd9v64StURe58ccvBbKfd+lzO+a1059T5++szYQNyxEMmolQggENYGkqaBP5Xv2ONsWkojqOiZSBiaTFtqCEpNJ/+V1M4lhO49PpCxIAcipu49n1rly8/w5oXTeZNe+lFIQQkAIQFkKoYBEImXBUAqaSNe0FABNCCRNC1Kk8+ykqZAyrKI5eUAXMAwFXZNQSjnrzM3hwgGJhKGcHLQ9rKEjNL1cy0rvZ8O0YKr0+RxCAEoBAV0gaSgE0wW4vPrZyXgSEwnTOb9jQTSIsbjhmUu65ZZ2O9xqjvbzAJw2hQPp2mHmerz6RzX6UQ5fxHBu3dWOPU2kazD2/g/rEoBAwpiuZWkSmEikH9u/RpM0FQQUFNJxkXlekFKAkIBlAe0hifFEep3hgMT8aPqiOnsbBnQJXQrEpu5OJwVgKqTPC0pZznJMSyEa1BDPqjlJp05knzskpZhxLbxVlPpdTwbPDdRymVLOLzUgbhnQTIH57eGKrmdetPg8PR2VXadNSoEFHbz6tZhG3U7hsI7FdS5yVLrwYhefU6ZVkRNJqfEwBqrHD2MGUTNrlT7mNU5X4pigntswFNKxuHAiBQAIBDQEAhrcDt/d2h/NmG9xV1vZ7WqVuJqNYsfyhaZ7TSt3filFSTlduXlHpwzCtKZPGOrpCE+fWKcUwkEtrzATCequxZOxWNJ5ne5yYp9b4S41VTR2K7b4MYfyY5saUTnFNikFeuZ4x35u7IUDGhbNCWM0Zp8gmiyrmFfOPnYrnpZaPCx3bLDpusTpnRHXaaVu187yPyrqrtD79qNAQHP9TC5ln7vNo+sSizLev2UpDJ+KOydWR4IaOoI6jk4kXfPccmOVOXN1VGu7VuJYjic91U4rHHvP9j3ONB45dtVOK8QxUStq1Xy33Pddyvxu85TzPb19/I6p3G5uOAjLUoilFEylkDSmb1okhICmNe7JK8XqXfb0zNx/PGEgICUg0icauV1Alzl/ysq+ALWQ7mgwve0BtE3Vv4Dsk88W5ORRpcTPbPtWZ1soL5dfkHPxdCm5pVfNsVD7ctfjphr9yI9m2+7u9pmve27b9NjwxomY+8ltkcy6kExfEA0gIDV0d+RfuGxZFiaT6Rt/BTQJTQCjsRS6IoG89fPEuWylftdTipY6qk4kDDx/bAI37hzE0GjMuY3fwjkKXQiWdFcIolYXjxs4NJLfj5Z2R2dUzDMMC88dOYVNGcvbtq4f5y/sYFGlRVQ6Biodozh802YAACAASURBVES5GGPUarzG6bd0R9kXiCrMshQOHjmFDffvdfrVN65/B0Ynkvjsw/uc53ZcN4BQQGL915+efm79AJYt7HBOknt5ZAJHTsZx8679WfMsXdCOQ0fHs9Zx/ycuQsKwsp7LXB41N7e4s/c/AM9pXlc6u8XetnX9uOex5/HDA8NViy/7fdz9o4P42CVn45bd++saz4W2K/tVc3Hb19vXrcTrEK55rpSirFhl3aQ6/LxdmXOSn8w0Hv3cx4iIiMrhdrx//ycuwmTSxKadg1jQHsIXrliWlwMv62lv2nMPvHL/u65ega/954u4/tKzsXBOGGd1R4vWqQrlyF7bnjUs8oNidR+36ZvX9OHO7x/E0fFEXu3NrUZwx+o+PH7wCD50QW/WcTX7QXW11M+5vjY6iWvvfQpDozHnud6uCB7euAoKM7tLBLUUX9zmvN5Xonr1o4c2rppRH3p9LIZrtj+Z3y9vuDjrqm6qCF/EcK5Kx8BMYrTe/YpK5osYrvQ4SC3FFzFcLq9x+qGNq8rqCxxrm4YvbtXfrI5PJLDv8Am0BTWMxVLYtucFfObypbjtu7/E0GgMFy7pxBeuWIbT5oYhIDA0Oom7fvg8nj08hvct78GXPvx2qKmfn1BK4Rq3/PeGi/P69H0ff4ezjsx5v3PTpQ15FWoRTRHDlbza1C3ujo4n8J2bLgUAXLXlZ56xkdsOTQLPHxnH57+9L+81t125HDc8MAgAWfGa+RMXkaAGw8r++ZZS39fRUwlcteVnuO3K5bj9kQMF47kWV+va7alCv2rI44l6sO+AFNIF4inL8+fV3X7qtZwvu9z2tde4+vANFyOgyZJjFWjKuokvYria23W2x73MOX3PFzFcK3Y8fv1j/YiGAk5cz41ItIe971LThGNXM2mpGG4UM/m51Jngz7mWhzFMQPHj/e3X9bse1xc5dmvIGM7MpZ8/Mu6a8/zThlUQQgFI16bCAR2aBPYdPlG09pSbqwc04NlXvetkXsuhmmjIGK6kYnWfo6cS+PPv7Mfq/iXojAQwFkth9+BhXH/p2TgZN9AdDWJRZwThgMStu/fj5vefj+u/8QuX4+dVSBgWLCv9s7BvnoxDCOFae2M/KAt/zhUADEtlBRIADI3GkLIUuqPNeSY4NRc/XInq1Y8Ma2Yn5KZMy315pjXjNlJjqXQMlBujfuhX1FgqPQ4S+Z3nOF1GX+BYS1ScZSm8MRZ3CoH21YZzwrpzAt0XP7wcsaSJ6742fQe6u65egd2DQ/jIhYudLyp7uyL45icu8jzGyn2+Lai5zps0zKq/bypfJe9w5hV3X/3BQWf/e8WG150TezpCrq/pnPrpiQuXdOJjl5ydFa+b1/ThO8+8hqtWLi7rqvRMScN01lMonmt1hzi7PV7toOqy74C096Vj6D97ft4xyPlTd4VIpUw8NzzuOb0Ubvvaa1w1TAtKqZJi1ca6SXVUa7tW4riXOSf5iWEpfP1j/UiYwCemTu6cjmvdM645dhERUbModrzvdVxvNdmNjDJz6buuXuGZ84wnDIxNJrNy++3r+jG/PVhWrv6+5T349OXnedbJvJZDVCvF6j6WZeXdWe6uq1dgXjSQ1T++cf078MnfOgcnYinX5SUMhb/+t187v+6weU0fFs5xr72xH1RGS903W5cCvV3ZVzn1dkWQMhVOxJi8kf+NxJJOEQ5ID4Y37hzESCxZszZ49SN9hl82BDTpvjytpYanllbpGCg3Rv3Qr6ixVHocJPI7z3G6jL7AsZaouJGJJG7I6Se37N6PSFBHb1cEmy47F6MTKafIYs/zuW/vw4Z3neMUZOznXx2Z9DzGyn1+Mmm6zhvUebGZH41MJJ2iMpDe3xvu34uRifLHVK+4+8zlSxHUNQR1zTM23Npx+HgMr3jE3lgsBQDYdNm5efF686792PCuc/Liu5z3Zbd1LJYqGM+V3H6ltMerHVRdw+MJbNo5iPcuP931GGR4POHMV2h6Kdz2tde4qmuy5Fi1sW5SHdXarpU47mXOSX6iS4FoKFB2XHPsIiKiZlHseN/ruF6K5jp2y8ylx2Ipz5ynI6zn5fY37Bx06lu583vl6qv7l+Qdf2TWybyWQ1Qrxeo+pkJe/etz396HodF4Xi3tc9/eh5GJpOvyXj42gdX9S5z5b961H6YF9oMqaqmMZX5bEFvX9TsB1dsVwZa1K3HvT1/glXzUEPxwJWp3JL8fbV3Xj+5IcEbL62kPYVvO8rat60dPO2812ioqHQPlxqgf+hU1loAmsGXtyrzjiYDWXEkxkc1rnC5nvOVYS1Sc19WLuiZw9zUr0B0Nel7lq0mR9/w9jx3C1pzPqx3rB9DTHsKO9QNZz5/Z3Zb33I71A+iOzuwYn6qrknc481rW2fOj6I4G0R0NesaG19X49zx2CHes7sv73Ng9eBgA0B11v/rcLY7LeV92W3cPHs5bf2Y81+oOcYW2HVWffQckSxU+BqnEMYrbvu7pCHrmuaXGqo11k+qo1natSExVuPZGNBvdkeCM4ppjFxERNQu34/0zu9ucz7lte17A5jXZx/V3rO5Dk51Dl5VLb9vzAnq7wnnv+66rV0AK9zvaBzSRN3+hXN3rDn8BTTDXJl8oVvdRHvWItmD2iW52vXfbnhfyagR3rO7DPY8dcn7dwV5GLGlge86xNvtB5bTUbyeFQjpOnxPCN66/CFIApqWw4/EX8cSLI/gfv7O03s0jKsq+EjVzwK31lajhsI6l3VE8tHEVDEtBlwLdkeCMf4pN1yXOX9iBh2+4GIZpQdcketpD0PWWOse3pVU6BsqNUT/0K2osKVPh0X2v4b6PvwOaFDAthV17X8X6S86ud9OIqqLQOF3qeMuxlqg4++rF3H7SFtBwbk87YkkTzx8Zd50npMu854+OJzCeMHDblcvRHQ3i9LlhnD43AikFli3swHduuhRJw0RQ15wCS+5zlfxpS6ocr1iZydWmnnEX0pz97xYvUgrX104mTRwdT+CrPziI265cjs5IAJNJE6d3hvDlq/rwxQ+ZEML9M8G01Kzelx3bX76qD5Zl4eEbLoZSKi+eK7n9SmkP+1V92HdAkh7xZh+DVOIYxd7X/3LTJYinLGgCiAQ1dAR1zzy3lFi1sW5SHdXarpWIqUrX3ohmIxzWoceSZcc1xy4iImoWXrndaCyBb1x/EXRN4OjJBL7y+/8NAU1iLJbCN594CV/80Nvq3fSKysylnz08hmPjSehS4oFPXARTKbx5Io6v/eeL+H+vfJvrcUMkqGHZaR14aOMqmAoIByTmR0Oeubp9hz+35SzpamOuTXVXrO7jVX+aTGZfxGnf1fHZw2NOPa07GsTcSABf2LUfR8cTzq872Ms4Np7EiiVz2Q+qpOUylvaAjljKxPqvP43fvftxPPHiCK/ko4bhlytRw2Edi7vacGZ3FIu72mZdxNN1iUWdEZzRHcWizgiLKS2o0jFQToz6pV9R4+iOBHHlBb24/hu/wHvv+imu/8YvcOUFvYwZampe43Sp4y3HWqLivK5enN8ewrxoCKfPTV/p7HbV7sKOcN5rN6/pw53fP4jbHzmAUEBDT/t0YVJKgQUdISzuasOCjvTzbs+RP1XyDmeecRedvkuMV2x4XY2/Y/0Ajo4ncMMDg/jct/fhtLlhdEVCzjJOm+Merzsef7HgVemlsNu6cG4EizojrvFcyzvEsV/Vj30HpB8feMP1GMS+E1JPe6jg9FJJKdDTEcYZ89qwuKsN86IhBAKaZ55bSqxmYt2kOqqxXSt13Fvp2hvRbMw0rjl2ERFRs3DL7boiIUgBGKaJUEDi1n/5v7j23qdw+yMH8OnLz2u6umduLn3fz15COKjhuq8/jd/5X4/j1n/5v/jUe5fiu88Mueb286Pp+tbirjacMa8NPR3hgrn67sHDeXe1tZfDXJv8olAsetWfzuxu8/yFkGcPj+H2Rw4gZVrOCXRbM37dwa6hndndhs5IkP2gSoRSzfUTSgMDA2rv3r2e0+NxAwYMnIhZvJKPylWzkadQHMfjBkZiScavj6VSJobHE84+6mlPF899wBcxXG1u218phaMT0/1mQTSIYHC631SiXyWTRsF1UEX4JoY5FtMM+SaGC6lWfOcud25E4kTM4njZeGoSx/U8lqgny1IYmUgiaZgIaOkvGWMpE+0hDfGUBSEAXQgkLQXLUghoEvOjQYzFDViWBVOlfypACgEpgLhhOccluv7/s/fu4VWU59r4/c5pHRNWWCSgJHJqBFN3kCyQk1WUXapbW7eFihsCghpAquzPWtRv7+1Pu213pbQ/d9Vy7CeWgwcErW7twRZL/baolUBl2wgiIiaAJIQkJCtrrTl+f6zMMLNmZh2SlWStZO7r8pLMmnln5p37fed57nne56G1tvWrE/XnTFy1mOy3PEbOclgU5bgdK8mgKQKGIqAoyrLfE59NkYdFS0SwfVZ2z1IUZZzr5MFLcpxTDAUKsD1vIvTtEkJAE4BlKIiyAkGUbXlj4DpDgaEIIrwED0dndGx398lzbueFPZFNqGNDkGSwukxGsqzgbDiGqCCBJgQejkbAc+FZqse5GIKoIBt8RACa31jgphHh5Vz04QcqBhSHrWxnAI6/OLAxYDicjoap6l2q/6bnNUXB0cLyEwOGwwMJox96o0/O8/njN3bruO5cX3fPlSZy1q9zMDCR+M70uijwggJCCGQlvi0mZhR7kNMclmUFrREeEV6CpChwszSGejicjwnaNpai4GIJIrwMSVZAUwRuhkKYl8B1+WuSArhYCkM9nKZZsAwFjibojEkQuvrLw9EodLG69uOZ6vTH5aHvPtCR0xzOFVzQLeJZ630uGpKiIMrLkBWApgg4mkBWAEGKb2NoAgoXdF03SyHWpWlQFAFHUxjq5UwLVKw0unT1ve7cVx7raipsL3hQeTTRqIijzWHcvb0WDS0RbcVUwENBEIgjkDnIeUSjImKKaNgWU0Qgil4V45xgkfQhCBION3aY5pkJJX5njukD2PX/2KAxiwAviwAPTdhzuxmM7AGneV7EkSbz+2V8sc8RD5MgX+cWO3uiPOjLi+t34CAZkvG7p+PV7WZQTKHX5st8nVMcONAHhzAUgc9FI+B24UhjB/YfP4vZFRehIybBxVCQZAURSQZNAY3tMbA0BQUKvjgXAUE8/f+ooBcejkKnIIMicRGmNSai+Wwnarbt18bexuoQRha5cbothpqtxu0XBdwodLE42tRh+G3z4skYP7yg10SRASLAdAuiKOPzc2HUn4vAy9HwcDSG+jgIgoCYKGF410ftxD66aEh85ernzWGcaO6El6M1HowO+rRAySNn2k3P8ivDfDjS2IEVujl53cIqbH/3BPZ91qw9bwC2z4WiCII+zrJ9K65YXb+2jy91P9ndi/5c+n2K/S78yz9chpggQUZc+NevWre6pmQBiVYcTdY/+v19LhqdvKyNdRdDQQEZsDzX3ztFGQVg9YMKy1CGoDcriKKMw2faDTzdUB3C+BI/Pj0bNnBh7bxKDC90a9xXMyAlws5vrD1+FqExw1Cc5ayEVkGAAAxzv6vrYxObpNyhXTChg+wiE5vSzna+ZKgL8ze9l7a969ixDrqLnnAnHQ0zmd4FJPftHF47cODAgYN8g5VveD4mQBBlAICalogAUBRAUuILwArcNE62xkzvxEuH+eBy5d+7T5YVfN4cxpnzUazedQgNLRHMqSjBqtmXGvyyJ26dCLFrgefwQjeawzwkWcEQD4sfvvoR3qxr1Hz2jqiIx3/7MZbOHIOLhngQIUBLmEdEiPtAQ30cOmIifvh6nXbc1juuBADTIjs1KEmSZcgyICsKXDpf3+p+9IFFHE3ASwoURek17clO3xrMutdAhJ1GpA9A9XE0BFGGKMkQAHTEBLz7aVzvlRUFRAEEWUHjeR5+NwOOJjjRHIGbpXDPcwdR7Hfhh/94OYJ+DhQASVbQ1BlDTJTgYmltfBR5zDrumrmV+NW+4/jnv78Uw3xc1gLq0tHmutN3uTQWBlUmupMtnZqAoaK0yIMXl01DwEPB53b31WU6yE/0+wqt9mgUnzebDbHRQRcKeom/doLg2KALZ8OSs8owAcnmmZFF3n68MgA5wOHeRrL+TxSwxwZdWZv3c/y55yS6GYiWExx2nreDHiAnOJwMmcyj3Qkc7a3x4wS39imcVYZZhFVwyLqFVQh4WXz4xTmMLi7E3dtrUex34YHrx2P1rkO2/1aP33HXlWiPSoY2t95xJRY/8xfT2Ht26ZVYssW8/bGbL8e4Yh8W/PJ902+vrJypBR9lE9kQYNJETnK48XwUx5o6bJ+r+lE7MWho8+LJuGiICx+fbjfsv3ZeJcaPKMBQnwtN7THcsu6dpHO7fvuWJVPwwK5DePCGCbhkqActYQHLdXxKfC527atcUYUxWZZxNsxj+Tb7tlIh1bn0+xT7XXjkWxWI8JKhbzYvmozxIwosAwytPgzogwkTObr1jisRE2VL3ur3nzE2iOrpo7ByxwHDWH/jw5P4x6qyTHme8/aE1XhWS0w3dcSwfmEVuK7scAVuVgt6s8Kp1ghu3fhu2vx97ObLcfnIIUnnqWT2iALA76IQ8GbHV7QLAiz0MFiw+X3LANYN1SFMGF5gCJCzaydxvzxBznI4U5syGZdmrvmTaZuVvevYsXmJnOBwT7mTjm92sqUTB040Y9KooJZh5uCJZlSNCgKA7fFBD+fwOreRExx2YISTiS5j5KRf5yB/YeXDPLt0CmKCBAA4HxUNAWX3zr5Ue8/93weuxT9tzljvzFkON7XH8NHJNjz86kfaPW1cFMJjr9dZ+l9Ln/3A5POpPs8XzZ3Y+u7nqPnaOLAMMfnn+mPWLaxCOCbinza/j0llAZMusnnxZJQX+3G0qQNP/OEIbp8xBg/uPpRUX7Dy+e+5rtzgm2dbe7LTt9Rr78vFqr2MnOVwX8DuOftdNBpaIrb63pYlkxETFYNvrx8HauDbvdeVg6UJ3BwNXpTR3MEb2tlQHcKTez7Rgk6fu2uqpY778E0VeOz1Ou3/2eBcOtpcd/quH8aC7cnyTmXpCURZMTxMAGhoiUCUFbRG5H66KgcO0sf5iKwZZUCcv3dvr8X5XuRvc4S3PGdrRMY1a/di/qb3cKQpDJ4XU7Q0OJBsnnHQu+B5MWn/W3E4W3Cee+awm1uaI3w/X1lqOM/bwUBGJvNod8Zrb42ffJ5THAxuNHbENNEEiHN35Y4D4EUFk0YFNV6vmDVOE0rs/q0eL0gwtXkuzFuOPYrAcruXo9HYHrP8jRelXumL5jCviSfquWq27kdzeHCMY16Skz7Xu7fXorEjZtlH4Zhk2n/1rkOI8PFnxYtSyrldv52hCB66YQK+/9KH+J+T57UAOv059c/Frn1elDRh7JZ17+CvDW1aAJ1dWyn7Kcm5EvdZMWscWsKCqW9qtu3H2XAMgJl3c0NlpvGjXqMVR080d9ryVr9/zdVjNZFe3W/ljgOYN/mSAclzq75avesQVswaF+fzjgOgKRrnwgJONHcmvX9BkjPir5ejU85TyeyR2za9h/qWWNY0Dqt5fsX2WvCiYuJDzdVjtd8bO2JptZO4n4OeIVObMl3bNpm969ixDrqLnnInHf56OQqjiwtx26b3cM3avbht03sYXVwIL0clPd7htQMHDhw4yDdY+TD15yJobOfR2M4b/Mq5oTLDe05WBtb3Al6U4OVowz0FPKyt/6X+W+/zrdhei49Pt+Ohl/8Hd141FiWFLkv/XH/Myh0HMKIwvpjJShep2bpf00Xmhsq0ADr974m+pZXPn+ibZ9snt9O37DSdgaYHDBbYPeeYqCTV9xpaoibfXj8OHtx9KD7H7DgAhqYhSsDJlqipnRXbazE3VKb9bafjqmNX/X82OJeONpcM+aABD6ogOoYiKC0ylnEoLfKAEJK3LzIHgwvZ+vAsCBJOtnTiRHMYJ1s6IQj2k1qqc6oiSFMOTWz9Cbt5hsnPVQR5haYwD4rYz/N6ZNuBcZ575sjnQDTneTsYyEhmL+vR3fHaW+Mnn+cUB4MbdsEhFImn51d/04uVdv9WYRUY1xzmLceeJCuW21sjgu0xHEN3826To6cCTL7D7nmrSBY0ZLddUhQ0tccDbOzmXqvtNE3h/pc+NIhsiW1HeBFN7THIcrz8iR1X9MKYXVuZPONk50rcJ+BhTcK/es6oEF9Qk8i7ZNdoxVG79hP3pyliuZ+6faDx3G48Bzys9m+KxPsvVdAbS1MZ8beTl1LOU8nsnXQ1jnR1lWTzfOI2umtjQ0sEomRc9GUbTCg5i4KziUxtynRt22T2rmPHOuguesqddPjbyVsv6O7k5aTHJ7u2dPRoBw4cOHDgoK9h5++p/yXzG+kB9r2AY2h08pLhnlojgq1+pCLR51P76f6XPgRg7z/rj5G6Kija+eaqX5SuvpCJz58t2PnDdj7dQNMDBgvsnrNel7XiWzrjQD2OItC0k2THAPbarzp21bGaDc6lo80lQz5owIMqiM7DUdhRMxV//N41eOv+a/DH712DHTVT8Vbd6bx9kTkYXGAoguVfG40/3Hc13rr/Gvzhvqux/GujM+KvIEg43NiB+V0rCOdveg+HGztshYt0BBVH3LuAEr8L66tDWp+p5QpK/NkveeXgAkQx/uFAkhW8sGwaln9tNIAL/f9W3WnD/iqHsyXYFfs4y+de7OOy0v5ARD4HotnZEx5uUJlVDgYgBEGC301Zzmf6efTWUCn++L1rAMRLrKlzcDrorfkyn+cUB4MbdsEhsnKB15PKAhjq47BrxXRsv/NKjBjixq4V07FxUQiyYg6CkxVzwNTu2nqsW1hlGHtr5lZi89ufYe28StP2DXuPYXdtPTYuMo7XzYsnI9hL9k1PBZh8h4e9cP924rTdXGfHIwKCW9a9g3ueO2h6zpsXT0aJ34UNCXPyuoVViAmiJmbZXcvHX8azyx05044iD4vNiydbckUvjLVGBMypKMHGRSG8uGwaNi4KYU5FCTwcjab2GE62dGqBeXYI+jjbcyXu08lLJuFfPYbuej0k8s7ufjmGtuSoXfuJ+9sFrKrbBxrP7cazKtqq85z6jJLdvxVPN3T52IlcWDuvEqOC3pTzlJ3f/uqBBgCpNY5MdJVk8zwQt6tUjYdjKNwaKo2Pd5pKq53E/Rz0DEmDgkQZp1ojONEc1mxgN2ttO7tZyrTNzt517FgH3UVPuZOOhpksGC6Zb5fs2n7x1qeICDJOnY9m7E86cODAgQMHvQW9DzOpLICNi0II+l0I+l2m5A2yomDLkimaXytIkuU7MV+/FwR9HMqGegw6wu7aeqxP0JXWzovrRyoSfT590A5FiKX/PKeiBEN9HF5cNg1blkxBZ1dGfXVf9VmovxNiDAzSw8q3zsTnzxbs/GE7n26g6QGDBXbPmaEJXlg2DX/83tW4OODBS8unY1JZQNvHTkdKHDuqZqRqJ6mCWHfX1uMXC8za7+7aek3rVbf3lHPpaHPJkA8aMFGUgRX4kqwuckc0iuPNMW31VGmRB+sXVmGIl0WJ1wW3m+njq3WQZ+gz9cqOx9GoiKPNYSOHq0MoD/rS5u/Jlk7M3/SeQQApLfLgxWXTMLLIm/Y5h3oZzFyzN+XxgxGCIKGxIwZRVsBQBCV+F1g2Jyb+fudwb0AUZRw+026oH7++OoThBRxiooKhXgqfJc791SEM8zOQZZI13vK8iKYwrz33Yh8HjnPeK3bo5nyWExwOR6OWnBobdMHndvfVJTrIT+QEh+2g2gjrFlyBoN+tzWdeF4WGljjnZ4wNonr6KC3tvfohe8LwAjBMesJQb8yX2bCRHKSNPuFxX9oS/YnWzhjqz8VLG6rcXbewCgEviyFuGo0dAs62x7SU/apI+ZPfHUFTRww/+85EuFkK333uoPb7L28PQZBgGA9r51WiuIBDa6eIIh+HL5o78eSeo2jqiOEXCyahpNCNmCDj+Nmwtn3z4skoL/ajJSKAF+NBLkEfB6qXPuqrZT/VrGWqADN+eEG2z5mTHJZlBUe+bEfNtv0o9rvwwPXjDc99Q3UI40v8+PRs2NRH5cV+HG3qMGzfuCiEn//xE7xZ1wgg/hFg1exyjCvxw8NeeJaiKMd9F0kGQ1PwchTCMUnzGSeVBfD9b4zXyqSoItxPf38EB+tbUVrkwSsrZyLo49Ac5k1caWqP4ZZ176ChJYJbQ6Wmd8izS6dAEBXUbEv/ucuyYnmuxH1aIzzOhXk0JYyhJ26diHElfgz1uUy8m1NRglWzLzX4Fur1ADBxdOsdVyImypa81e9v9f5ct7AKb3x4Ev9YVZYpz3PangCsx7N+7lq/sAocQxAVZBS4WYwO+pLefyJPS/wuMAwFWVZwNhxDVJBBE8DD0Qh40pun9H47RQh+faABP/vjUQCpNY5MdBUrf3VDdQiFHgY73v0cN04caeJFwMvi4kKPwbayaycTGyyHkLMcTmZTftocNvX/iEIXXv/wJK6ruAiKooAQgrfqTuPrX70IANKydx07Ni+RExzOBndSaZip5js7387u2i4q5HCqLdYjf9JBVpATHHZgxOiH3uiT83z++I3dOq4719fdc6WJnPTrHOQvVB/miT8cwe0zxhh84PXVIciyjO8+dxDFfhf+5R8m4L6dHxp8zFHDvIgJCmQl7l/QlAKOpjGswPZ7QU5zmOdFnO3kERNlSLKCsx08Lgq44aKpruzuEvxuBvfo9Ci9z5eoGzxx6xVgGYIIL2n++ZyKEtxzXbnBLti4KIRhPg4sQ6G1U8CZ81GDP/+f86+Ah6Xw8z1HTc/JSkuw8vkTz5lt7clO37LSbnpJ9+or5DSHextWz/nZpVMQFWSD37h2XiW8HI1HX6tDU0fMdh/92PnVvuO4fcYYvHrwJO782mgQQtDcwRvGwvrqEJ7aE9f91LHz2sEGVI0OoqTABb+LgawocLM0fvRGnbZfxNKbiwAAIABJREFUtjiXjjaXSd/101iwPdmgCqKzc/p2LpuGi53gHwep0e/O5anWCG7d+K6Zw8un4+KAx7S/FU40h3HN2r2m7X9ePQujgj7LY6JREc2RC4LIEA+F63++zzBRjy/2OQFDuY9+53AmSDcY0W5cPLv0SkQECeOLfRBkEa0RWWsLUDBzzd6kvO9NJI6poIcblOJ4N/ohJzicaTCyAwc65ASH7WBlI/zk25fjspEBLfAYgLU9vXw6FEXp1wByZ27tMwxqgSTbONnSiZ//8SiWzxoHmiKgCcG5cAwjCt2IijI6eUkTFFSUFnnw8E0VWL6tVgviaWyPYXihG2fOR7Hmt4dx5egAFs8YA1FWQFMEHpZCW0TE4mf+gmK/C6tml+OSoBdN7TGUFLgwusseSgxGKXSxfRZEB/RMgMkAOclhNegrwkuQFMDHUeBFBYJF0JBVHyVul2UZU3/8luk87zx4bUp7RZYVfPzleSzfVquJzA/dcBkIiZepOdm1irw1ImDD3mN4esEkyzZlWUFbNIZTLTEs316Lh2+qwGOv1xn4vGXJFDz86keWdtXwAnfSe04HoiijqSOKqE7413O+OcxDlmVICqAo8dK0RR573ltdi9pOqv19LhqdvAxRkkFTBC6GggLSHZ7ntD2hQn/vFEVAAYiK8fJ/XNdzZRkq7aC3VOe6MH4UsBQFigAulkInL0OQZLA246jAQ+NEc9QU6KHXOBJ9U1FWMtJVrIIAAeBMe9TWrrLSeOyCCfMQOc1hK5vyXFSw1B1eXDYN5zoFywVWeg0ilV3q2LF5h5zhcDrc6cliX54XcaTJHAyXjg6ceG2Agk5extJnP8hI23bGR68gZzjs4AKcILqMkZN+nYP8hiwr+PJ81Po77LJpUHOn3mZhw7+0fDrkLm1UkhXQNIGHoVBSaPvtNmc5rPpLNKUgwssGG4KmKcMCwFWzyzG22AeKEHzZFgVDEwzxsHj8tx9rQTvrq0PYtu9zLJx2CUoK3ZC6+oihiKU/9PLKGWAogigv4VaL3x//9t9h7DAfSJcWIitx32+Yz2XpW+r9P0IIOJqAlxRNA+gN7Sld7aa3dbZeRs5yuK+Q+DwF0Zqzj918OcqH+0GR+KKTiCSiPSJBlBWwFAFDU4gKEihCAAIcPdNhWPzsczHwuxhtfmkJ8wj6ObhYGoIoa1qWaYFtdQgji9zgJUXbLxnnUvEzm/zNkbFge8JB5W3YpR8XnDKUDvIEdvXSBSn9tPdqOv3ECZyxeHkXsLRBpBjhd8HlYsDzIl5cNs3JuOUga0jk3hAXbSnSTSjxm4Q+u3HB0gSXBOKiXlMLbzLGty4NgaEITjSHwVAEw7wcXK7u8TgTQc9ZZX4BbjeDkXl4z8nKmTgYfBhIgr6VjfDkn47h9XtnIByTNY7b2SInzrZjXEkhRFlBY0fM0Bd90U/5Oqc4GDyQZQXnozzCsS6RhKbgc9HY91kzdtY2aPuVFnnw+r0zIcoKvBxtOeYCHlb7N0MRjAx4IMpyPJvHoiqIkoKoIOHTpjAOfN6MhdNGg2Mo7Fw+HTQBJAWgCVBY7DcKeR28JrYs/9poLJg2Gk3tMTSHeeyurcd9Xx+f1qrA7gohFEVQXOBKud9AQ7IVmEA8QOtMe1TrS30fybKCpvaY1tcXDfFoGeBKizwo9ruwYtY4BDwsOnkJHi71R3OKIhgZcGPrHVd2raCPB3f+5tAp3DhxpCkzotqmGuCjBiwRouDzs53Y8s5xPHxTBcpL/CY+23E8Ksj4/FwYo4q8qG+NoLE9hmK/C7ICNIdjEKX4Cv9U/GIYCsMLPRofLx3uhygrON0WgSQr+KFpNa4nKQ/tftNn4msO86ZAPPW5BCziFxOfYZ6L6Bp6azzrecZQBAUeCu26YCUKQCcvwsMxaIuI8QBlCvjVO5/hm1eUWmZ0fHnldFuNQy3dqvffXlw2zVZXsQLDUNZBcXZ+hY3Gk9jOQOVOf8PKphTCMVsfcFTQZeBPwGOdDT+Zz+/YsQ66i1Tc4XkRp9tj8XJyIix9tWSQZWCol8WOu6Zq/GYpJi0dWH9t8cWI72PrHVdmNO85GpoDBw4cOOhNWGkXimJto59qi2Lehnfx6ndn2mqjDE26FjLSAJGh5GHF8lQZokRRBssQPHbz5fByNDp5CYQADA2MGOKGrMRt4sfn/h0evkkGL8YXkd35tdE4Fxbw7H9/hnmTLwHd5bdY9WWEl9DayUOQrJ/FyCIvQAiKfS7N7yawXvim981ZhgJDxbPh9cR/SnYOfbtW/nA6fnKOBBc5SAOJz/OLc2FLzno5GgQAQxOcOh8FRQhiogSWpuIBbnK8jDFDA5IMjC324akFk+DlKEQFGYoS54Xc5XMOL3SBpsyBo+OHF+DVe2YgEpMRFWV82RbBz/d8kpaeK4oyTrXF9Te9DqyvUmKto3Uve1yua8CDytNgbYKHaIogGhUdx8tBzsOOw2wGk1OJ34X11SGT+FDs4wyG0dalIRT5Pab9Lh3mg8vFYKQTNOcgS7Ayyjd2paFVud7QEsHd22stM32xNGU9LmhKE/USea/yWw2sS+R3JshU0GuO8Nq+pntz3kN5gWzMxQ4GBgaaoG9nI/z6wElMHVeMQjeDiCBb8p8ixHZeVRQMqH5y4KA7kGUFJ1s70dIpmMpXPV8zFf+0+X1t2/M1U9HQEsWTez7B/77hMssx1xoRtH+LsoLFz1w4fv3CKjz11lG8WdeolalY8Mv3LcVPPZrDFwLoJpUF8A+VI7FQd9yauZV44g9H8KNbKpOKHDmUkj9voO97IG4f1mzdj9fumYkz52O2fZmsr4M+DlvvuNJU+mTz4skpM3/JsoLTbTFTKc4lM8fgOxvfM1zn6l2H8PLKGZalJtdXh7D38Bm8WdeIN+sasXFRyMTnTl6y5PgX5zrhZikEPCyaO2L4/ksXSuWsW1iFp7s4ng6/VGHOqr/WzK1EUzuPg/WtqNm6H6+snJmxiGfV7obqEJ7UldWwu0ZnvGSGRJ49etMEhMYMM9gYW5ZOQYSXcPuWDwz8nTe5DLv216NoxhjTePv2unfxysqZGGnx7Bs7Yib/7Q9/O21pM6kZ5tKFnS/L0Kmzyznc6Vsk8wFPWATMDS9kHZ/fQb9DlhUcbQqjuSOSVOO1g72/mzmPVV9TVpDRvOdoaA4cOHDgoLdgZ08H/Zzlu6o5zGNSWQBDPKzl78eawuAYCr/adxxLZ45BcYELw/xsf9xaj2CnT6i+cmNHDEu2GLPKvnHvVZAUxaB3JZaaXLewCkdOt+HGiSO1rLRblkyx7MvPmsLwu2jERGsdWlEUPPraR1g1+1KD3731jisRE+Wkvrm+bGZ3/Cer8rCrZl9q0EJ64pc5fl5+w83Slpzt5OMBaPPX7dN48/1vjMep1oixRGuCpnvv7Evx1J5PcOdVY3G/ThdTS75aBcd92RbTKkukq+fKsoIjje2m4359oB7fmlRq2t5THS0f0K85/wkh1xNCjhBCPiWEPGTxu4sQ8mLX7+8TQkb35HwcQ2F9dVy0BaBN2tv2HUdzhO9J0w4c9Ak4hsK6hVUmDnMZlO9gWRoTSvx4cdk0/Hn1LLy4bBomlPjRFjOWihpXUmgpUpztdMaKg+zCyihfvr0Wc0Nlhv3sMn2V+F3YkDC3r68OYaj7goOSyPts8ttO0LN7rzhZzPIf2ZiLHQwMZDr+cx2Jc+VzNdOw9+MzePT1w6jZuh+irGDTn4+Z+L++OgQPS9nOqwOtnxw46A6awzxi4gVBEYiPhRXba0FTFF5ZORPvPHgtXlk5EzRFYUWXLfTj336MNXMrDWNu7bxKbNh7THv/PP7bj43ja8cBzY6aGyoznbNm6358eT4KOcH24EVJ22/FrHH47nPG4x7cfQhzQ2XgRSnlvVoJrs1hZ8zbQd/3KtTV18n6MllfUxSB381oYpzV8Xawanf1rkOQFZtspF2ZwVZYzPULp4/Bi8umYeOiED45fR6/WGB8hwz1sfjZdyYatv1iQRWe3HMUq3cdQkyUcd/ODw3trtRxPBN+Wd3Xg7sPYcWscdrfqfidbrsrdP5Msmt0xktmSOTZdRUXmWyMhnMR07wXHwdRLJweL3P98E0VmFQW0NpN9uyt/LdHXz+Mi4e4TLpKpqXsrXzZDWkG4znc6Vsk8wGt7FxBNB7v+PwO+gPNYR7Lt9cm1cB4XsTJlk6caA7jZEsneP4CebPpx6m+ZsDDmL7PJJv3HA3NgQMHDhz0FuzsaYYi2Lx4suFdtWZuXIdZMWscmtpjWDuv0vT7k3uOarrJ6l2HUH8ugnAs/1LR2ekTqr9kVRmq0MOafLC7E3zilTsO4O+/epFhvyf3HLXty/t2fgiaIiYbfM3cSjz+248xN1Rm8rtPNHem9M1X74prAN31nxJ5o15Htvwyx8/LbwzzubB50WSTjls21IMfvlFn4M3JlqhJs0vUdNVxpAbQqfupc42q8Z5s6URTewxnwxcC6BL3TaZ3NYd5y+PmTb7EcntPdbR8QL8t1yGE0AB+AeDrABoAfEAIeU1RlDrdbncCaFEU5SuEkNsArAEwv7vnDPMSLh7CYeeyaRC60h26GArfnT0OLWEJTe0xJyWmg5xGmJdwyVC3oUyEz0WhLSJhWAbtsCxtyubFdxhLU2RLpOB5EU1h3in96sAWdkZ5ZWkh/vvBayHJCmiK4OCJZsvyOAxD4StBH15YNg28KEOSFeza/wVuuqIU44t9Gt/0vD/RbJ1SNxN+60sTvrhsGlwMweQfvZWyrWQllR3kB8K8hLHDjHPxEA+F5nBmc7GD/MdAFPTVj7/XrN1r2N7QEi8Zue+zZgDAc3dNhQJAkOKBdd+97itaX/zk25djRnkxpK5+8HJUj/ppIJXMdTAwkU6ZBV6UQBHrACRRkrXyfLKs4FRbBOsXViHg5VAy6ysAFGy940oQACxDgaUIfn7bFaApAkKA1d+YgL+7eAguvagQAQ8LWVFwcSBebrCkwIUZY4OYXTEcFwc8GOJhQaBA6sqMN7KrtmRzmIekKNiyZAqe3HMUAQ9ruNZJZQGsmDUO5SV+EEK0ADyr+04luDowg2OsV6pKNmVk1L5MKW6LZnE7nWdh167UlT3GqkRsVJDw8E0VCHhYtEYEbNh7DAfrWyFKMuZvek8LOHnjw5N4+KYKBH0cRhS6ce/zB1Fe4seWJVNAU6Tr3aHgYH0rACAmyij2u7B2XiVGFLohKQq+bItiiIc1XJv+nuxKq4iShOdqpkGSZYiSgs1vf4adtQ0IeFhMKgvgX/7hMiiIl99ws7ShLIYgSGjsiGnvohK/CyxLQ5YV8KKEn31nIlojAvbUncHsiuEIeFiUFLgwqSyAg/Wttv0+2MeLLCtojfCI8BIkRYHPRUOS49xlu7ISSbIMWQEkWYGLofBczVQIogKKABxNMGNsEHfPGguOobXns+racXjg5Y+08zS0xMunyLKCWT/dq318+envj+BgfStKizzgGOsAODv/LSrIJl0lUzAMhQnDC7Bz+XSIkgyGplDid4FJY3HOYOdOXyPMS9j+7gnDXLX57c/w3eu+gl+vnI6YqGj8czEEYd74wTSVz+9oZw56A+o84eUovLBsmqav7TvahAde/giirOBIkznTnKqlpePvZuKrsSyNYSyNgIdLe95zNDQH2cboh97I+JjPH7+xF67EgQMH/Q1elFDsd5n82AgvYfzwAryycma8TCghePS1j3CwvlXTXH7yuyN4vmYaznbEEPCy8HE0NlZXgZfjesvOZdPgd1No6cw/29xOn/BwNJraYwCgaUcH61sxqSwAigDPLp0ChqJACDRfnCIEf/ze1fiyLYrX/noKDEWw7Y4rISkKWjsFsDRB0MfhhWXTEBNltIR50BSw9juVoAkBx1BwcxSeq5kGRVFACMGrBxrwZl0j7rxqLBpaIgjotIFhfs5Sl9DvU+x34dKuReStEQGynFmgY6IflqifAT3zyxw/Lz8hdi0uFSQZQT+Hl++egagogSJEq2AV8HB4vmYqRhS6QVEEDEWwZclkAARRUYaXo8HSBAQE+x66FrIC/OqOK+FiKKxfWIVTbVGN0yr3G1oiONUawbwN76K0yIPtd07FjLFB1Fw91uC3Bn2creYBXOCdqv+qY8jNGr/r6PXhjYtC2F1bn7TdfEZKb5wQcjmABwBUAFAA1AH4maIoh3p47isBfKooymdd53kBwM1d7au4GcCjXf/eBeBpQghRFKVbXyaHeGiwFHCqjTc5hwUuCrese8dJiekgpzHMR+MzizIRY4M9T5OZaBhlQ6TgeTGpGOPAAWBtlD91WyXOdggm7gQ9nGUbzREet216z9DGGx+diZd3sOBaT/ltV9Ji/79eh8k/eitpW0EPZ1n6x+7eHOQeenMudpBfGKiCvp1YMsRDa/PXqr8vN8y7//z35Sgt8mDVteNw2ciA9puWvv+2Stz7wiFDe+n000Armetg4CHdMgscQ9uWQ1bLV6ltPfGHI7h9xhjcrSuDoS838YsFkxAVZEMaf7VMRlM7jweuH28ow5pY+lJN+X/PdeUo9PA41Wou2ykrinatk8oC+P43xuPB3RfKC1iVyFDv224OGaiiSjYQ9HHYvHiyqT/tykCofZmqr7v7LOyOc7OUdYnYRZPBMgSPvV6nbVN5pgZUqyvPH76pAsu31QKIC+/FBRxunnShnIuaiW5SWQBNHTHQFMGj36pAJy9h0TN/MfBaDVDT35NdadX/+msDrh4/3MDjdQurUORlICuKdg79+0vltCTJONzYYenXHtOtdLcbbz/9fXzsWvX7YB4vsqzg8+awxqdivwsPXD/ewC39fFfsd+Ff/mGClpmwtMiDJ26diO9/oxxn2gXc/cwHhufzk29frgXSqeVTGDo+L6urpx++qQKPvV4XL9vks/bH7MrdZ1q61Q4MQ2mB1JlgMHOnP6AuJtlZ26BtKy3y4JFvjrf1DdXnk8rnd7QzB70FjqHx1G2VaGg1c/Sp2yrBUMS+VCrHpPR3u+urZTLvORqaAwcOHDjoLXg42uR/rJ1XCQ9Hg6KIVp5QlhXc9/XxqDvdjtaIAI6m0NQRg6wokBUFP/7Nx7j3unJ0xERDWxuqQxiTh98LrPSJuA5g1o5eOXAS35lcivk6P/qJWyeiuNBlKlO5Zclk1J/r1Py5ORUluOe6cty2+YJ+pS9lqfqDarUGvc/dERPQGhFQWuRBa0QAEA/uUQBLXUK/zwPXjzdoCxsXhVBc4E47LiTRD1OvI1t+mePn5R9EUcbhM+0Gnj67dAoEUUHNtgtj5pklk9HWKWj8m1NRgnuvKzfov2vmVuLtI2dw48SRhvLIa+ZWYndtPb7/jfGaxqRyT81S2NASQTgmonr6KIPGtm5hFUYUumw1DyDOuzkVJbh9xhiDbraxOoQ5FSV4s67RUh/eUB1CkSf/ylanA5IsHo0QcjOAnwL4MYD9AAiAEID/DeD7iqK82u0TEzIPwPWKotzV9fciAFMVRblHt89HXfs0dP19rGufswltLQOwDAAuueSS0IkTJyzPebKlEy6GQmtEBEWgRV/u+6wZLy6bhplr/oTSIs+Ard3roMfo1S/i6fD4ZEunZoyoKC2KZ5no6QroxI8NW5eGUOT3mESKS4f54HKlJ+L15vV2B/pIcDaDFd591V4foN85bAU992aMDWLZNePA0kTLbqSK1Cp3RFkx9feJ5rApaxIA/Hn1LIwK+kzbYzERn5w1C33p8jsZt+dvei+laOhkVeo2coLDJ1s6sXXfccybfIm2mmPX/i+weMaYfpnbHPQfuvHRICc4nAqCIOFMR8yQ3fNbV5SiyMeiwE3hfESGKCuGeXfzoiqMCHhR5GVNQc36+THTQLhcsyUcAOhFHmeLw32JpvYYbln3jomjiT6l3JX5raVTMIggG6pDmDC8AAxDaW2pQR36FYBBH4chHhYP7DqEVbPL8fCrH5nO+fBNFQAuCIb639bOq8T5qKhlDnOzFFbvOmQYm/r9dy6bhnOdAlZsrzVcj4otS6ZYXsMrK2ci6OPSCizsR+Qkh60yGgJI2peJPtycihL8240VoCmiZWA72tSR8bOwCw4tL/ajsSOGU60RNId5bQVsaZEHj918OZY++4HWRmmRBzvumopfvPWpIehE5RwQF7D/87YrtKBP/bGP3Xw5OIaCi6HQHhVtOa8GQKn3ZDcmtyyZoomI+u0vLJsGCsCRMx22nOZFKantb3VdaqCgei8jhrgt+z3dQNwE5IU9kQpN7TF8dLJN6/eNi0JJ5xqr39VnaGV7vLBsGq7q0vnWzqvEMD8Hv5vB9B//Sdvv7dWz4OEYBNwMmsK8rW9vl4mwP9FN7pjQT7pG3nG4rTOKL1rMgUhDvaytbwggLZ/fsXfzEnnBYVlWcLotYssvv4vCxH/fYzpO1dJS+bt9xV0rDe1cVMgnPTYXkRcc7g3kcia67lxbd9Dd+8nBvstJv85B/qCxPYpvr9tneo+9vHIGSgrcAIx+OiEEHE3QGhHQ1B6Dh6Vxz/MHsXZeJYoL3Gjt5E1+cop3Ys5w2C6bu/q3AsXUV3MqSvDIN7+K021R030/u/RK/OR38ZKrakaroV4O9+38q9aGnX+XuPDOyk9/vmYaHnv9b1g1+1I8uecTvFnXaLvvjrum4kdv1CXdJ5O4ECsdZtXsSw0BVD3RwLLl5/URcobD/YlTrRHcuvFdWy1D1XbHFftRf65Ty+JoNwYS9atJZQGsml2OsqEe1J+LwO9iwEsyfrXvOO68aiwe/+1hrZrDnvuvwe1dQXr6Nncun46LAx7baiqyrKChpRMLLPS5HXdNxcJfvm+pDw+AuCpbDqf6Yv/vAL6uKMrnum0fEkLeAvBq13/ZvKjEiL509oGiKJsAbAKAyZMn20YFsjTB6fNGwWPdwioA0NKQN7Q4KTEd9A/S4XFvlo2jKGJIUcwxNApY2lCucJiXswwwshOUc6nMnVUkuP6jZTbboyiSsqTXQES6c3EiVO69fu9M1LdEsWTLX0xz9M7aBo0716zda3p+mWaDcrkYXDrMlxa/rZCM2y8um5YyKM7tZjAyzaC5XPxgM1CRiT1x48SRptUcLD3wx7kDI9xuBuVB41zSn0GxmczDdg6TKMo40thheL+trw7hg+Nn8ejrhy+sMPKyhnm3ZtsBvPW9qyClmB8z7adcsiUc9D66a0v0J9Its0BRBCMDXhS4edtFAWpbajp+qxV+a+ZWotDNWJ5TLU+R+Fux3wW/izGsAF6/sArFfpftGDvVFsWP3vgYj918OcYW+0z7eDna9r6t/ArHHk4N/Up3PVL1pYuh8NjNl2OYn4MCaIKXKrT6XTQeu/lyeDkanbwEl4XvYyWYB/0cnquZCpoQeDgahS5zQJ6+HKaXM9qn6grYxKxN6gpwAGjqiNmWOR5b7MNz732O6y4bYcu3y0YUaIGbap/YjUmaIpbbZVkBoUhSTid7FyUbi+rf40r8KA14LMdALo6XvpqLeVEy9LtVGZxUvze0RGxtD0lW8PbqWV19qWDbvs8xb/Il2j6lRR54OAZFHjalVsCydE4FM6ljttDNYOfy6aAJQFFUxtzJtk6SK8iGTZyIjpiMlo6IwZ491ngewws4W9+wpDC9TFuOvesgEdmahymKJOVXR0zGrhXTTR++GYogFosHro0Numz9uL7irl5DG6jz1kBDPvp1Dhzo4XB4YEO1/yK8te8oiLK2n93isqE+Du1RUdNb9N+09H5yf9lzmdrDqYK2TrZ0GvpqUlkAt88YY1gwrb9vF0NMGa1UHSqVf6f3p+38dFlR8KNbKlHkYfGjWyrxyDclSIq1XcJQJOU+mcSFWPnwRR42az59LmoE/YF8mocFSbbVMuy03Z/+/ojtGNDrV3bZ30YVePCDmy/HI69+pAXQAfHAKkv7XJJTjnU73ay1U8DDN1WgvMTf4/GTT0jlWbAJAXQAgK5tPc3N1wCgTPd3KYBTdvsQQhgAQwCc6+4JBUkxpShfueMAll0zTgu0cFJiOshlqIFCeiQLFMoU6oebkUVeFBe44iJFkRejgj6MLPLaBtAdbuzA/E3v4Zq1ezF/03s43NgBQZB6/XozQWNHTBNYgPj4X7G9Fo0dsay2d66Tx5Ez7bhl3TuYueZPuGXdOzhyph2yI34mBUURdPKy5Rxdc/VYAHHu0NSF8jv651fsi5d3UPmmBn0UJ0lP63Kl5rcdknF7ZJE3awE0ycaXg/6DIClaFiHgAlcFyRnngxGJ78p8yCqpOkxW7yqr99vd22sxs7xE+3vF9lr4XZRh3n30pgkICwCdYn7MtJ9yyZZw4MAKapkFPex8SooiCHhd2li4OOAxfOxT21LT8a+YNU4TSYAL5Qc9HGN5ztbIhXIWeqyafaE0gNrO3TsOYNXsctsx1hzmcbC+FUuf/QCfNYVN+3TyUtL7TvQrBpvYl00k68vmMI/Fz/wFS5/9AKfaoib7pGbrfnzaGMbSZz/A/E3vYemzH2DxM3/RSj0A5nfCv75yCIfPtOPb6/bh6p/E7c8z52M4F+E1oU1t/8Hdh7Bi1jiUFsVLZepRWuSB38UY7PMN1SHsrq3X/t68eDJcrPUY+qwpjBsnjoQCe755OMbUJ3ZjUpIV6/cJTYFjaNtzsLoFO6ZjbbbrAwVLizzwsHTSMTBYx0tiv1vNX6l+V31Eu+ez4Jfv46o1f8Jtm97HTVeUYtf+L7Tf1RKu2dYKehuJY/bWje/iXKfQrQ8r+Xbv2UYymzgRfheFIr/H4JsX+T1Z8Q0de9dBbyIZv+Zveg/zNryLx16vw/e/MR5zKkqwvjqE85EYPjkbxvxN7+Grj+7B/E3v4XxURInfZfDj+oO7g33ecuDAgQMHPYPe/jv8ZXtSXaM5bPaBa7buR0tEwFCfC16OsdRb9H5yPthzdvep1w0IMb7z7fQq9b4BYvpd1aFU2Pl3en/azk+nKYKgjwOMZcTiAAAgAElEQVTDUJov7WGttTKOodPaJxMk+vD668iGTz9YNYJ8BUtTtlpGsrFiNwb0+pXV8Su21+Jvp9rR2ingoRsuM+huHGO+FlX7SjXW7fS0L89HsXxbLY42dmRl/OQLUgXRCYSQSxI3EkJGARB7eO4PAJQTQsYQQjgAtwF4LWGf1wDc3vXveQDeUpLVn00Bu9VR8bKBkkFEc+AgFxH0WAcKBT39x9nGjpgp8OnuLvGiO4FNvQWrSHA1+jqb7fGSnNLgdGANuz5VP4qsrw5h39Emw2/q8+M4BuOL49mg/rx6Fl5cNg3ji33guN4JZumrsZhsfDnoPziZAhzkO5I5TMnmYv3fbRHJMO9+/asX4e7ttdh3tCmr7/5ctH0cONAj6OOwefFkA0e761Oqbe2urceauZUI+jib8Qj87DsTTeNid209Nuw9hrXzKg2/jR7mtWxn9DAfSvwu0/WvmVuJDXuPafs+uecoNiaMw1FBb9bu20H3oc+6ZreC1SpDnH6VaOI7YW6ozPRxumbrfkQF61X6Km9HBb0mPlw8JF7W4Z0Hr8UrK2diwvAC/OiWSu3v8cMLMMxnzcEn9xzFyh0HMCboRdlQj4nXdnyzGpMbqkPYtf8LrJlbadpe4nch6OMsz/HErRO1TNB27zarcyUGCjrjwhpBH4dRQa/W71bz11Afq813G/YewxO3TjQ9I46Gra2wc/l0vL16FnYun44JJX7cdfVXDPyjKJJ1raC3kc5HrnSRb/eebWTSl60RCR+fbMULXbbvC8um4eOTrVnxDXNJO3Mw8GDHrwMnmk0f8x755lfx8clW+NyutLSo/vDVBvu85cCBAwcOega9/bdh7zGTj6j331JVHgj6OIwZZs7cr/rJG6pDCHhyP0tqOhUWaAJDX9npVUEfhydunQjZJuObXjfYXVuPdQurjHbEwiqDPz3Ux2JDgq2xbmEVtu07brLZ09HnsqnhOXCgosTvMvG0bKgHmxdNth0rAQ+L3bX1WJ8wBtbMrcSu/V9oYyOZ1lezdT/8bsaguw23uBZV+0pnTkumEaeaMwcaUkUXPALgj4SQ/wBQi3gp1SkAHgLwYE9OrCiKSAi5B8DvAdAAnlEU5W+EkH8HsF9RlNcA/B8A2wghnyKege62npzTrtwfSxEooE1lQBw4yDXkWtk4IHkwiT6wSb3eYh/Xa4FNyaBGgieOf4bunhFr155dKZmBms40m7Cbo10MhReXTYPPRaHQPQzvPHgt6k614Qevf2x4fhzHYGQfcauvxqITrJWbyLR8sAMHuYZkDlOy95v+74CXRlOY1+ZAv4tCQ0sED7z8EX7y7cvxwrJpkLLw7s9F28eBAz2yWWZBbetHt1RClmWIXSsPTbYRTeGSoBcvdo2zmCjjd/9zGnNDZQh4WMhKvHxyQ0sErREBzR28ZTselgLL0obrJ4Tg0deMpQCaOmK4KOA23aMsK9i5fDpESQbTVZrW6r7tSuWlW0LPgT3UVaLqs7Z6zlYZ4vSrRBPfCbblJIi1/XNxwIMRhW4AsBwHiSVq7UrW6jmrloBRMdTHocDF4IVl0yArCtwsjWG+eDtN7THTOfWcZhkKHE2weMYYUBTRxg2jK6csywoKXAzcDIXna6aBl2Scbo3gP35zGE8vmIShPhcmlPgN76ISv8s0ftQyLmqpGIfXyUFRBKODPgS8bPy5KIDPReHllTMgiDLYLl9PkmXtubkYCi8tnw5BkrV55Ke/P4oHbxhvqTtcnGAvFLPmFdLZ1gp6G+mWEU8H+Xbv2YZdX8YECSdbOjU+DfNyYGkKT/7pGB54+SNt39IiD14sL+6xb5hL2pmDgQcrfvlcFL751CHDfg0tEc2f27t6lsbpzYuqUHHxEE2HisVErZJDf/hqg33ecuDAgQMHPYPe/jtY34qf/v4IHr6pApeNKICbo8FQBKfbIuAYGixj/c7RZ+D3umjLfS4a4gZDAc1hCT53395jptDrCirU+9R0G0lG2VAPdtw1FYIka5nprO6bpghkxVrPAtDl1wNuhgJFgG13XAlJUfBlWxR7DzfioRsuw7/eWAGaIvBwFAiALUumgKYIJFnB5rc/w87aBiyeMcZwH+noc06pVAe9AYahMGF4gaVG+uX5qK2W9tANl0GSZWxZMgUuhoqXVCVAadFosDTBjrumgrIZa60RAQ0t8fLTI4u8husZb6FfMQyVdKyrGF7o0vQZliJ4RKcRH6xvxa/2HcfO5dOhKIpp/PRE581FjTipR6Moyq8JIccB3A/gXsRL6f4NwK2KonzY05MrivIbAL9J2Pb/6f4dBfCdnp5HhYejsH5hlZZaVY1qdnMUhub6W8yBA8SFiqPNYW01oLrC79JhvoxKUWYTqYJJ+jKwKRnUSPAVur5To6+z2Z6HTf4Scj4iWkOWFbhZCusWVmmlUNRVJR6OwsnWGOZvMvL+1XtmYIiL63bfRaMimiN8t4U+t5vByF4O4nCCtXITdvaEh3NEWwf5ATuHSQ00WF8dMtka7xxtxMZFIQR9HEYGPDjTLmDplg8M+2xdGsLiLbXax8XSIg9eXDatxx8A+2K+deCgJ7AKFLKDld0CQNtGSFwwYRkKDBRsrA5huW48bl48GS6OAi/KaO0U0Ngew8OvfmQaz8/XTMP8Te9hUlkAD1w/HusXhnD3jgvtrJ1Xic6YhHPhGCJ8/FouGhIXNO/7+njUnW43nDPgMV5na4THmfMxbQW3up+a2Ul/v0fOtJv2Ky/242hTR8rjBzKsuKCW1RakeACRKnTZQV0lWrN1v5bFa/WuQ4Y+9btobFkyBV4uXjpzVNBrWCXq4S783hoRbMVuhiLYtCiEZduMPIoKcT7oeZTpM6QoAo6hcf9LHxrOO6eiBGfDPJZvM46B0oA3zq3GdtNvKoeKC1y2/NPzzGqfNXMr8bM3P0FTR0zz41iWNgiTsqwYAvj09203Hwx2n88KFEUw1OcCfKn3jcVEfHLWrIfcVDkchxrOY/yIAowKelM31AVRlLXx9sKyadi27zg2/t/PUVrkwav3zECUl3GqtROKgq4PQbAUinsTsqzgbDiGqCCBJgQeLvXHvEyQbZ0k32BnE0uKgoWb3zfwrDzow2//eQbOR2RNQyj0UIgJsPQNXQxlGeRrey05op05GJjgOAYXMTSawzxigoRwTLb9GKcmHCgt8uCRmy7DiIAX8ze9Z6tDd8dX68n7cLDPWw4cOHDgoGdItP8O1rfisdfr8PLKGWju4A1+4dY7rtT8bb0/WeRh0dgeRVSQ4HfRpvfSz74zET/4r7/h3uvKcXEg92MP9LpC4n1a+cq/2nccD1w/ARsXhQz++C8WVKE1IsDD0nj7yBmTvrxmbiUe/+3H+OEtfwcCAl6UQBGCRc/8BQ0tEUwqC+D73xiPxV1/a1mu/ByWPvuByW4hhOBkS6fBlqC6yryqdkZzmLcMpFP1guYwrwVN5rJ/7mgJuQWr58EwFEYUurXtLREBQR+HEYVu0/haO68Sq54/qAWnlRZ58NjNl2Ppsx9ov79y4CRmVwzHxUPcpu/ma+ZW4qe/PxK322mj31nkYfHp2bClDmY31lU90ko/e+iGy1B3uh3FfhdWzS7HmGE+MDTBMJ87Lf03HZ23J8f2JkgPqqPmJCZPnqzs37/f8rez7VF08CJECaAIICsAQwN+joGfZZyMFg5Soc9Gqh2PT7Z0asKFCvUDdWKkcV9BECQcbuwwCdkTSvxgLVZ59ydUkVwfCZ7so1R32qMoYjvZA+jvj4j9zmErqC/IJ/5wBN+bcykYitbmaBdDwNEU5m5415L3Fw3xdOvlGo1aB6SWB3059S7Ip/HVR8gJDiezJ4YV5L5j7KBfkRMctnNMXAyFxc/8BTPGBrHsmnFgaQKWphDscr70gTxr51XiJ787YnD2Xlw2zfSBZRDPVwMZfcLjTGyJfIHV2Nt6x5WIibJh28++MxFulsJ3nztoECm8HI2OmIjFz/wFD99Ugcder0Ox34Xvf2M8Htx9yDD2hvlZPPLq33D7jDF4cPchrZ1Lgl6cbo1oAUJ6kUZvs1oF+umvfcuSKZbBe6+snGkIIGpqj+GWde+Y9tu5fDpu3Wi27xKP7yX0O4etuPB8zVS0RUTTR+EJwwuS+ix68c7D0RBlBYIoa+JZMj/D6jqeuHUiinwclugCpVWh/OGbKvBpY1gLuNuw95gtjzL1Y6yu5bm7pmLBL9838eTllTMQ5SXL3/QcsuNfOvs8dvPlGDHEbXkv3RH4siwK5oQ90ddIpodEBAmjh/rS9u9FUcbhM+2G8ba+OoThBRzcLMGJczE8tecT3D5jDH6177g2l/aloGvFGbXcbUdMypp+kG2dJE3kBIet+nhjdQg/3/MJ3qxr1PZTeXauU7DUEM50xiCIiuYbsgyBh6Xw7XXv5tRHAAdZRU5wOF0kcn1ORQnuua7c8DFuY3UIQ30sFBAEPSw+ORvGUC+bdR06G+/Dfpq3BhryisPZxOiH3sj4mM8fv7EXrsSM7lxbd9Dd+8nBvut3v85B/sHuPTS80IVvPW32C1+7ZyYkGYYAFdXHLva78PSCSQjzIk62RLWFa0U+Fj94rQ5NHTHsXDYdF3dlYLNAznDYKiioOcxb+sqqHvXErVfgooAbzR08CtwMHv/tx3izrlELqPvNoZOonj4GZ85H0Rzmsbu2Hvd9fbymPxf7XXj0WxXo5CWs3nVIa9fqGSQu4txQHcKTXTZ7Ot9g013wmYv2eo5fa85wuK/QncXCAHC2I4YwL+HM+SjcLIV7njto+50l0VafU1GCf7uxAjKA401hPLnnKJo6Yli3sAoBL4sfvl6njQU7HU3VwewCMu20sZdXzohn6GyNmhZ56zmYjv5mh54cmwXYcjhpEB0h5L8QL+FqCUVRvtWz68o+kg2khpZO3Gbh+L20fDpkRem3ICQHeYN+dy5PNIcx1EebVr6eC0sYFUxj6XYvQRCkuHiRUNpmsCLTl1AffkTsdw5bQd8vk8oCWDFrHII+DhcHPBjqZg3Z4sIxAXP+878BAH9ePQsMRSwFvVR9l42A1J5msksXzvgyICc4bGdPvLBsGkodW8JBcuQEhwHzu4qmYCkWvbJyJgDYiibLt9Vq29R5WZ2v3CyFmKigxO+CKMo9mjP7as51kBYGnUCSLVjZgluWTMHzfzmhlWIVJBkuhkaRj8Oxpg7sqTuDW6eUYZjfBYYmoCngZEsUQT8HF0NBVuIB3YoCSLICmiKICBKKvCyigmxp7/zn/CvQHOYR8LAoKXDhezs/xMH6VpQWefD6vTPRycsQJRk0ReBiKPCSAlGScaxLqDlY36oFzSbinQev1WwpWVZwui2Cc2EebjYeANjYHsOGvcfw89uuwNVr9yY9vhfR7xy24sIfv3cNlmz5i6WvcHHAVnRPilRClK1IdvcMiLKCU60RNId5bNh7DAfrW7FrxXTM2/Cu6Tx6PvTEj9FnBmNpCjQBpv74Lc1HCHhYtEYEVJYW4lw4XrpC3ban7gxmVwzHhBEFYKh4xi5BlPHXhjZtnw17jwEANlRXQZQV7Z1yz3MHDeVjAeDt1bPgYiiwDAVRVqDICgghECRZK2l3LhxDVJDhdzHwcAx8LgqKQrRsZUUeFuciPKJCfIV9VIhnmySIj9dd+7/AXVd/pTt9lTP2RHegZlcDFAiiAkIAmhAIsqLNZ2owEkUBigwIXfNb/blOg7gMxO2PkUM8GQXQnWmPWs6PalmS+Zve0z7i2H3M6W1BN1mA58SyIYaPeXmYiSBnOJxoEwuShBmP/8m0359Xz4IkiXCxrDZ3xAQBLtY6yEgNLtZve2XlTBSwtGPTDgzkDIeB1L6S1Xwyp6IEq78xAW0RARcNcYOlKQz1ctpcGo2KOBOO4RoLe+3Pq2d1W4fuzY9kjs+YEXKKw32JHAwE0+AE0WWMfvfrHOQXVLtPlmVIXRoKRaD5jlN//JbpmESNQv8ee75mKi4Z6rX9zvTO0SZMHTcs2Tszpzl8sqUTM9dcsIsnlQVw/5xLUTbUC4oQuFgKgihDkBRU/x9z0M6WJVPAUAQyAI4mIISApQjaY2Lc56MI2iMCigs4iHI8+3dTexT//l8fA4CmAZQWeVDid6EpzGtaFU0BHTEJX7ZF8bM3P0FxAYdHv3U5JDl+PQxNIEkKvjwfxd7DZ3D7zLGGrOJ2AYJ9FLSTEfo5wCgVcprDvYFMv/O/ds9MiJKCiCDBy9HgRRlAXO+Q5C6uygrORwScaotiw95juH/OpXjo5f8xtfX0P03CmfaYpnHtrq1HzdfGIeBlcS7Ma1mlb3zyvw3XPKksgKcXTAIAS/1A1W8bWiKadqZqLu88eC0IIdq96b/hjwx4tHlAlBU0tsc03fdgfWvK86pInGtUdEcj7kbWRtsfU3kRP83oynIciqIYCAcADS0RiLIMLzdoAxIc5BGG+Wh81hwzrXwdG+zfF2ViaZvBDruSXrwoWc9Bkmy5nRelXr3OXIG+Xw7Wt2oBGR89OtsyW9yb/+sq3PGr2nj0e1u0W30nynbvAwWiKKf8ANOXmeyc8ZV7sLMnMMCy+zoY2Eh8V51s6Uw6n1r9FvCw2t+lRR4tgK49asyk9Pt/nmFpv6Q7Z+ZL9lAHDlLByhYc5udMGY7WzqvE6pc+RFNHDOsXVuGpt45qKwrXLazCprePIeDhUD19lCGDyLqFVeAYgv//zU+wdOYYuFnacuwG/Rw2vX1Ma1MtA1Be4kd9S1Qba1ZZStR9VWEmUdBRywnqMw3fPmOMoczd2nmVcLPWJfS6U44wH2HFBYpYz7WiJGf1PPq53e53oeuciQFzzWHe8rm1RgTL9jOBLCumVbsbF4Ww/GujcfX44YYx8uzSKZBlRQtsUvn/tG6s/GLBJDAUZdjnZ9+ZiICXwWdnw4ayt0/cOhH/8ZvDhuyqatDoA9ePx5Z3jmPltV9BpGuFvP64oT4WrZ0innrrqGks61fHz6kowb2zLzW8y9YtrAKxX7c6IKHODb8+UI8bJ47E028d1fp2yzvHDZnffrXvOO68aqxW5ledPx75VgV+8FqdFvzLUCTjDHReznp+FCUZCi7YOfr/J+7b2/663fj0cjQivOT4iFmClU1sNc8FfTSON4tYvMWYdZllrH3DRJ25oSUCL6s4Nq2DrCMdX8lqPnmzrhF3XjUW8ze9hz+vnoX5m/ZpGXBlWcbR5ngmOqvxwPQgaDeVbdJdOD6jAwcOHDhIBrsszz/53RE0dcSwcVEIcypKTNmIEzUK9T02qSwAv5vF2Q7e8r3WFhFQMTKAIZ781Tj0pW8nlQXw0A0TDL6Z6oPfedVY2z6Yt+FdQ18XF3AmnUn/HNbOq8RP5v0dzoUF7VxzKkqwavalBq1Zf8x/zr8CDH0hyEefTb/ma2Mxd3KZ4bfNiydjqLd/fLzuoLdsJwfdQybf+Yv9Lpxui2L5tlrMGBs06bh6Hq+ZW4ndtfV46IYJKCl0WZ6jwMPiB/9Vp2lXk8oCcLOUVu5YzQKpn8smlQXwwPXjDdWDUlWoULXfpo4YJFlBY3tUmwcSq6H8YsEkRAXZMDesmVuJVw+exC1VI23Pq0dimW2gexpxtrM2plKZliqK8me7/zI+Wz+DIgSlCWlTS4s8XSuCuy9MO3DQV2iNyJoYAMQnzbu316I14vA3H6C+CPQoLfKAoSnL7YPlI6Jdv7TZ8N3nYrG+OoS6U23ah7zEY1P1HUNZvw8YiqCxI5bympsjvOW1NUf4lMc6yH/Y2ROE5FX2BwcODLCbizmGtv2tk5e0f6+vDuFY43kwFNFEDQBdK5is5/N050xnznUwUGA1ljwco4kPQJzfq3cdwopZ4+Jc33EAc0Nl2m8ru/6uuXqsJrzof2MoGnNDZVi96xD8LsZy7H5+ttPQ5oO74+dbds04w1ibGyoznUPdd8PeY1pZQbXdzYsna6Vfm8M8arbux9xQmeX9AcDmxZNtjx/osOKCrMDWV8jmefS2cqZz/+7aeqxbWGV4bmvnVWoZ3hLbzwQqZ/RcWb6tFot0gWnq9vpzES0wU922MmGsnAsLWqkJddv9L30ImqK1QDh1+307P8Sq2eWGe3pyz1GsmDUOq3cdwtxQGVrCguVxNEXj/pc+tOT6iu212jXNDZWZ3mUrdxxATBxcvrz6nOdNvkR7Zmrfqn2o/78qxAIX5o+WsIAVs8Zp9scwb/rzRmNHDCu210KSFdvxpvqKarCw+v/EfXvbX09mfw0WraA/4HdTWF8dMsxz66tDtvqEnW+o2sn6bT21iR04sEI6vpLdfKLObwxFtPdWY0cMTeF4m3Wn2izHQybzbiJS2SbdheMzOnDgwIGDZLDyN/Xay/Jttfi3GytSahTqe2zFrLh+4uWs32t+N4sV22sRjuWvvxf0cdi4KKTdb6Jvpvpzdv5Sc5jX9lX72kpn0j+H1bsOgRDKcK65oTKT1qw/5n+9+Fe0dGWqV39X/cn7dn6Iky1Rw281W/dDstFfctHP6i3byUH3kMl3/lWzy7F8W5y7Vjqunsd6DUSSrfn5RXMnVswaZ2g/URv77nMH8K+6uWzV7HKTllWzdb82Pq3mxgd3H8Kq2eXYuCiEH75Rp32HXzFrnEn30ge86o9fds24pOfVI+jjsqIRW92L3TnTQaplOJXdajVHQQiwfmGVYRX8+oVVIAQQpMG1+tdBfiJZ9qx8Riwm4mznhXT7w7wcXK7urRJMLAFU4nelvSq9t6G+CBKjoEv8Lsvtg+Ujol2/JOP7l62d+ENdI7573VewoTpkWIWSqu9iMREAsOOuqWAogrpTbfjB6x9jfXUIgiSBIqn5MlDHooP0QAjw9IJJuOe5gxrvnl4wCU4M3eDEQCm5bDcXq/Np4m+bFoVQOtSFdx68Vrv3iwMuuGlzJiWWJtiyZApoKp6efPPbn2FnbUPac6Yz5zoYKLAaZwxNLPmtZnrU/1v/N01ZH0cR6LImKSY7SV0N+N3rvoI/fu9qsDQFjiGQ5HgZga13XIkNe49hZ22DKfuSmrK/vMSPVbPLUVrkwcsrZ0AQZVOKfHVlpl0GJ0GSMX54AV5ZOTOfyxF2G1ZccDHE9Lw2VIdQ4u9+1vFUc3vQx2Hzosmo2ab7/f+x9+5hUlTn/u93VVVXX2eYYS4oDIISwIxmFGbUQU+ibrLdyU+M24CYLQOKEQbNjvll7xDzO5GdZJucRyUef3EnCJIEI0g2BOLPRE+8xMSYxzsDCTHIiHibAZ0bMzB9ra6qdf7oqaKqu6pv091T3bM+z+Mj03Xp6lXvetf7fmvVelcmtqsqxS/XtCMmq+AJMBiUIAoEtT6Xft9dAodgVMbA2EsoTbVePHrLxaCgODYcti0TYVVaIfltXs3eFJViw5JmUzkJu1XEjH3Fbh+7Ff9mTvXixfVXgDeUdzWuRKbtZ3c+O1vXjrXbrkyysUy7z5oPS/Z1Vv830jucWOHrnCl+7FrbjoCbg9stQFUpRiISIpIClVLwXKIcMMdxuo2pY+Watt9yMSiAnWsuwfefPKSvXqj1N0VRsW31RRgKSvjFLRdjYDSWEvtvXdWGWq8LA6Oxovkwq/67cVkLplV7Jo1WMBGMhBV8PBLGrrXteox76PhJVHuqLe2REODhla1Yu/207354ZStq/S78/t8u10sTuwXCYlpGUcjGrqz8ibZCi6aFbV25EM3TpyCuqBA4gu8s+STWbN+PrSsXmvrDeDRbu2vZuqoNNR4Bx0cieeu5rH8xGAwGIx12q0cZ8xGeIxk1Cm0cC8VkNATc8Lt5yzzezRPcceWcsh2HtLy9yiNg55p2eISEtquoKniOQzAmo380hulTPNj+ygf4yY0L8ZWd+01tMMUr4Lmvf0bXgdPl1cZtyTl7plxbyxGttttto5SWzTPZTLoOo7Tk8pz/7Hq/brt2Oq6VJhKRZNy7tCWl0sFoNI7G6oRG2FTrxVl1PuscFcCGJc2YPsWDGp+I+6+/wFSmtXc4AlVVMTAaQ0SS8YtbLoaLJxB5grgCyIoKUeDgFTk8e6gfA6MS7l3aArfApXyfnfbmstG7rVZQ5DhSEI240Ks2Zsp4fISQBbCpB0sp3Z/Xt04QVR4OIYnH3deeD5/IIywp8Ig8qjwcTrGVvBhlgPZGtNEJaG8MliuxmIy3B1OX259X789ZlNFKsyQHrOdOq3LERLp0A8Fkfoho9/s/OhmxtffnDvWjY9EsrPjpa2gIuHH3tedjdr0ffpFHfcBt23Z29vbUHZdiOBRHx8/ewO7ORRmvuRL7IiN7fCIHv1swxRN+twCfOPF+hlFa4nEFh/uDKT7l3MZA2U2kyzQWJW+rcvGW5XJmTXWb/OPy1ib0jUop5etqfULWPpP5XEalYNXPKKilfWvlMY3/Nv491S9aHqdSYCQSx1XNjQhLKn7yxyPYsKQZdX4RU/0invrrcVzf1oQVP30NvcPWJVsfWrEQAEwlW62W7N+6qg0zanyWcZf2Zma6sq/JJfQmE3Y+98xqit2diyArKoQCvBCUyberKoVLIKaYxiUQKIqKdwZDKZN3at1unFntNV1TvZ/q5/eKPPpOxbBq08smO0lXJkLbnlwqJtnetHISB3pGEJaUtP0GgO0+2op/yZ/3nIjg/BlTAECfFGhciUwce6vY7nx2tq5dk9328aw0WI5o91lbCc7Ytskrv9m1WVhScPjjUdz95CHs7lyEKg/F+0Mh9J2KmsrtahNEvv6P8zG3IYAPh8Mp+2zuaMWGJc3gCMG0Kg8EgQPHEcRlFd8wlCPZsrIVv77tUsSVxKThWq8rpfzweMqEWKH131/ffimi8cRkVq/Io8Y7ebSCiUDgCL735FspdrdrbbulPfrdHEISZ/KjNX4XhoLxFG3qjGq3tR9g95MxDrLJlYzxQCyugJDEy4HfueY8xBUFR/qCOKPGZyq39FBHK7auXIg12/fr59y1tn1cE+iSr0WLTWo8Arr7g+PScywtkk8AACAASURBVFnOyGAwGIx02JULNGovosBn1Ci0cWwwGMP//T/OxfItr5qeT/WdimLD/3kTA8EYHupoLctyrsl5u6Yb/fgPR3CTYaV4TeO9sf0sXXuaWeuF3y3gB0+dfllJ04GNbZ3uPiTn7JlybS1HNGLMJ622iQKP+dO8ZfFMdrI/P3YauTznN2q+mgaSSf9tqvViMCjhweeP4J4vfgpn1iRWoNP8ypaOVrzyv/5h7CVBm/iX57C3qwc3XXq2aWExTVdrqBIxGJL0VfKaar343zdciGqvgFse2WfKBzo/PRtb/vw+fvhMN+4bq0hi/D477c1lo6HZraBYCI24UGVh9WvKsH0GgPtt/vthXt84gZyKqFi97Q2sfuQN3PDwq1j9yBtYve0NnIqo43q7m8EoFXVe0XIZ/Tpv+c44HwxbL7c/GM59eU2tNIvxXFopAqegDQQzan1oqDo92cvu88mC1e+3s/cqL4e1l8/RH/Ye6BnB6kfewMqfvQZZpWnbzs7eglEVHT97I+vVPiqxLzKyJxSzjifKeXl2Rn70B2OWPsVJ404upBuLkrfZlcsZjarYbPCPyeUhe4cTy/2vvPTsrH0m87mMSiK5L9X73SlL1mvlMbUHiHu7evRtm1YsxN6uHmx98d2UspqbViyErCrY29WDb33+k/jKzv149lA/Ord3YdnmV7Dq56/j8y3T8fXd5rIYyeUEbntsP9Z85hxT6U6rJfvTLYmvvZm5t6sH9y61L/s6mbHyuYLAYXqNF2fV+TG9xluQF4HS+fb+YAw3J8U0N297A/3BmGWpm54TEQwbJqoln19RkbZ0QrrSCsbyDVb2ppUSbqr1YuZUL370pQvN48JY39D+nup3mcYjzfbcAkkpRfzA8gswq86HOr9oug6tbPHerh7U+l2Wxymqgvuvv8DS1o39d29XT8pYNt6VBssRrX337PtQ92da22ptaPz//ddfkOIfa/0u7O3q0dtvKCThg6FwSqkQrRzKmkf3oT8Ys9xn3Y4uqBT6BDogYafaqmLafp3bu0AI0fvRcCRe0DIhdnAcQWOVB2dN9WFGrQ9T/ZNPKyg16eJOq8+D0dTcMBxTLbUpSaYspmUUnGxzJW28bhrzJ40BD4bDiZdJm6dPscztmqdPMZ2zoUDxW3JsMhCSxq3nspyRwWAwGOmwKhdo1F5y0Sk4jgAEurZifD51MhLXV3q6rUzLuSbn7ZputLR1Zkqefvtj+zEciuvak4vnsOKnr+HZQ/2mfToWnY3NLxw16UxA6n3YuKwFboGY7pWW+9neu5VtmFXnM23X8skHll+AmVO9lppUOT2TLadrnQxk+5y/3u/G1pUJW7bScY12bLTZWr8LA8EYQpKCm37+OlY/8obuVzp3dEHgOMyo9WFatceyDGpjwI27rm621NXuWDwXd13drE+g07b9z11/SSl9fNuOLqy89Gw01XpxoGcEG585nNIXp/pdKbqNcWW+UurBhSoLq5Hp1aF3KKX/kNeZHUi6Zb3LbbUQxuTE4xEwt85vWka/zivC4xnfW4ATSSGX248rqvW5lPILVBn29s5xgIu3XpY13b2ORuW09ra7c1HWq31UYl9kZA8rE8LQmMy2kO63nzutSl9JicJ6mX5FpZAgY2hYyuhHmc9lVDLJbyq6BA4CR/DjGxfoqx19/58/hbuuViAKHCgFvveF86BSQKUUu9a2gxCA0sRKqZJM8f3rPoVo3DpWSl5O364shigkVtVxCUTve1b7RSQZfSdVU8lEjbqAiLuWNEMgxLSCkyZeWJVBlGU1USJbUcFzBAJHLM+tYVcadLJh1w6Z2sc2f7K53z6RT1sGIVPphHTbjX0hLMmW+33yjMT2Go+AQVHCY7deAp4jcHEEbheH7//zp/C9aylUleolPX+1rh0cCFQKcARQ6OnVdLS+E/DwiMUpekfC4AjBVJ8Lv75tEeIKhaJS/Mc158ErcJAUqn+nyBG4XARRicLrEvDdL5wPgQCP3XoJPAIHlQIKpfjuF87H965N3KOAhy/oSoPliHafv/yZOQASqyARAvCE4D+uOQ9+kcN3rjkPskrxnWvOg8/NYdfadrh4grhCIasUVR5e36dvNAqV0rQlfnuHE+UB7fYRxiawamRTAqTQZUIYziFd3Gn1eV8olmILdmWjZVXNKaaNRmUMRTLHyozJTb65kiBwet6WLh740/orIHAEDX4Roph6zkLYaSH0XJYzMhgMBiMdmbSXdDk0kJhY5uIpwjEV8THd1y7/MP5dbhqxqlJE4uZ8XMup7PQjY7lUu5KVKqX48Y0L4OI58Dywe2y85jkCQoDNHQuhqBQypXALPHxuHjvXXAKeEHhFHtVul37vOELAEeBH/7IAHheHen/ixTRtOyFEX3E3+dhcdSOmOTHGA8cRzD+jCr++7VJE44nqDVqsKvIcRFfCBxGSKKX6nWvOgzLWL/auW4SobB0jR+Iyjg0nbPIT9X49nveOzXXqG40CNjnpOQ1+221WpY9VlZr6T63XZfKjIk8Qjil47NZLIHDEtHq+1Yp9gLUebCRbjbPW68JwJG7ab25DQG8P15julm+fnVRZRLplvaNRmSVVDMcTjcqWpdPm1vnL1n4Ludy+3fKgTiqRw4Ku02TTFh6PgBkWtu3icyuHpPWdqT6Xrb1Nr/HmdP1218aofFiZEIZGpdpCNv453W/XVlICgOMj9qW5PxiKZR3TMJ/LqGQsl6z3n/5nY7VHL6fxwHPdKeUzjCUL50+rAgB8fCpq2ffiirl8gF1ZDEWlCEkKYmEVax7dhw1Lmi33OzoQgihwKd9vV7IzXUnPT9T7U0p5Jf82oy9KVxp0MsXXdu0wtyGQsdykbf5k4+O1MigDozHLsSFT6YRM27W+MDBqXeLFKwqo84u29x1Itb37r78AHheHn/zxHcu+82J3H665sMlkdxuXtaAuIOKHz3SbStD8+A9H9L8fveVivX8Yj3t8/zFct3CGqWSosd2n5JZyVCTa6mrJxOMKDvcH9dig89OzseTCJjz5l15cfcEM3P7YftzQ2oQrPjnNFD88duslaUv8NtUmSonY7ZNc2iObEiCFLhOSD0xbKB6iyEOM88BY24pjDxOs4lEhIqXYgl3ZaIHnso5pK1H/YxSPfHMlLW87Nhy2jQdm1Ppsj7ez03PqPPCK2fukQum5LGdkMBgMRjoyaS92ubVb4PD3Y8M4u6Fazxv/e227bf5h/LucNGLt93980qwnaTmVnX5kLJdqV7JSklWseOSNRB4dV7Fme2rO/pWdB0y59X1Pd2MgGMPWVW2omSZmLPWYbns+ZSKZ5sQoBBxH0Fidqn/o+O1trS4gWmux/SGsfuQNNNUmKhw8+PzbGBiV8M3Pzde1KDsf1XMijIBbyNiXtc8EnkvpP9rfdtddM7YSdLLPzaZPZatxXtXciDsWzzNpeZq/XvXz1wvSZzNlIndafUgImUkIWZ/zt00wdst6n4rEMBQpbMkFBqMY2JVOK2f7rfdZ98t6X+7LazYG3ClLiTqpRI7m/K/b9BIuu/ePuG7TS+juG4VaZm+jFILxtkWu91rrO4eOnyyYvTEmL343Z2lHfrdzJuwySoNXtLYFr1i+tpCtf852/Lby1w91tMItcBUX0zAYxUQrp2FVPsNYsnAwFEN33yi++5s3U0pLblzWgof/dNS0zL5VKY2HVizEaDSOD4bCujix+YWjKee7d2kLHnz+iOn7h0JS2pKdxt+SvL0/GEsp5ZV8bqs2sfueyUK69szUPuliaqtSN1P9LvzrzgO2Y0Om0gnZllZIt1+6+2617d9/9VecCMVt+86ytrNS7G79noM4NhzF0taZ+mda+Rrtb2P/MB635jPnpJQMnYx2mQ/9wZgpNljWdhZu29GFZW1n6WWnr13YlBI//OCpQ5g51ZtSblcrh6KVEplV50vZJ1f7y2WfYsK0heKRa9taxcQugYxbm6pE/Y/hXPLVZu3sdCSiFFXjYzAYDAajGNjlmh8MhbFgVp0pb6SU4qFkLaWjFXu7ekx/V3nLRyPWfv+Dzx8x6T+abrS3qydFF3pg+QWYXuPRP9uz78OUmGLTioXY+uK7p/Po7dY5e3Juve6KOROaTzPNiVEq7GxN4Ai2WJQyfvD5I/p+63Z0YWnrTKy7Yo5Ji6KUpugfG5e1gOcIav1iyrb/fcOFmFHrySkez7WPZLN/thrn0taZKVqe5q8L1WfTvppDKX1W+zchpB7A9QD+BcAMAI/n9Y0TyGhcwew6t2lZ76FgFJ//ySv40/orJvryGIyMVGLZOLdbwLx683L79T4Rbnd+b1AaS8g5rUSOnfN//PbL8noTopwZb1vkeq+1vrNm+35sXbmwIPbGmLycjCh469gI/nttu7688stHBlDtqUeN/UvajApkNKrghbf6sHNNOyilIITgif29+MKCGZjqz3y8E8nWP2c7flv5a4EDQpJNWe4yjmkYjGKilQ60K5+hfR6Nn14Za2BUwvZbLkb/aAyNVW782+6/4kDPCI70B3HPFz+FM6Z44HHx4DnoY5qiUmx+4SiWtjaZSh8e6BnBD5/p1s83Eonjh89040DPCIDT5T20UoZW15ippKddrpN87uQ2sfueyYJdO9iVRjO2T7qYev60Kvz69ksRjavgCPDRSBTf/c0h/Z5bjQ125Rq0Nz4zbc/mPJnuu9U2n8jDB+tSnnblZrRjjJ8ZS/PYlQa1O99ks8t8SPYBWlsa21SlqX7i2UP9+O4XzgMAbL/lYlAAFEA4JuM/rjkP06d4wXEEs+v8qPG5sGttOxQKvfRPLvaXyz7FhGkLxSPXtrWLiWdUe8elTVWi/sdwLvlqs+nstJgaH4PBYDAYxcAu1/SJPJSkMY8jibj/ni9+CtNrEitfu12JcozfvrpZf14wxduAdItQOQnt9/cOR/DDZ7qxYUkz5k0LQFYSGdaGJechFItj280XIRiT0T8aw//z/x3Gf157HjYsacbcxgCO9Afxwlt92HbzRRAFDpKsYuuL72J3Vy8A+zzaqoykln9PVD7NNCdGqbCztYikoNbvwoYlzajxukzarnE/Y1/R4AjBPb87rB87Eonjvqe78a3PnwtFpbjv6UQfb6xyo9rrgosn8LgS5WYVlWYVj+faR7LZP1uNM5vy0pmuJxNpMyFCSBWA6wDcCGAeEhPnzqGUNuX1bROMJCuQZOCGh181NWy5LanKmLxUatk4t1vAjAJNYjKWkHMaLOg6TSHaIpd7bew7a7bvB5DoO7vWtrMJdIycETiCB/94FN/89Zv6Z021Xuya2zCBV8WYCASOYFdXL+7//RH9s6ZaL77YWpahMoDc/HO243eyvz42HK7YmIbBKBZa6UC78hna5zw5LZoc6BnB2/1B3P3kIWxY0oyBYEz/vONnr6Op1osNS5r17Z3bu/TzLW6eBjGptNaBnhG8PxTGhifetP1+rZRhujKHdmUQ7fxC8rmT28TueyYLdu1gVxotuX3sYmpjyc1jw2Fcv+UV03a7scGyRE4O2zPtl+m+25WkkBTVcptduRntGONnxtI8dqVB7c432ewyH5J9gNaWxjbliLWfoBSmt661z3d3LjJN4pzqd5tKNtmRjZ1ma8vFgGkLxSOftrWLicejTbFYmVFq8tFm09lpMTU+BoPBYDCKgV2uGZYU8Elj3kgkjrCkWOojmr7SVOvFZWX0vMD4+w/0jKBzexe23XyR/hu3rGzF3U8eSvm9x09GU3SlXV292HbzRVj9yBum/e3yaKsyklr+PVH5NNOcGKUina3FFVXvd1tWturarnE/Y18x+qiBYEzvk8Z9p/pFy213X3s+5p9RhbPqslspJNc+ks3+2Wqc2ZSXznQ9mcj0Ok8/gC8D+AGAOZTSfwdQtutUigKPGq912a06Lyvlx3A+diWJmf2WB5rzNzJZg65StwXrO4xCUuPlLe2pxjv5+vJkp5AlyZ1CKfxznVeEz6YsMvPLDIY1WulAq/IZxpKFXtHchze/cBQbl7WkPW5zUskR7fNZdb6UcoVWnxm/v84v5l3S06qUV/K5rdrE7nsmC+nas1Dt46Q8Jt19t9p2//UXYKrfZdsH9uz7MMXuNi5rwYxaj6lfaOVrtL+t+sLGZS3Y+uK7WZUMZaTSGHCbYgOtFNCefR/qZaef2N9rGT8cOn4ypTR1JZcCdFKfrDSc0rZMw2CUA3Z2OsXLMZ/EYDAYjLLDLtecVefDgQ+GTHnj3q4ezKj1pOR+P/rShdj8wlE01SZKnXrF8hkLrX5/Y/VpnUbTl6w0m+R8efNYHpecg8+q82HrSuucPTm31tpxovJppjkxSkU6WzNqpVZ9UCsjnbxN03ut+pWdDjZzqjcnDSXXPpLN/tlqnFa/T/PXheqzhFL7ZeAJIV8H8CUk3tPcCWAXgOcopefk9W0loK2tje7bt89ym6pSDIaikGWK+NjS5G6BQ8AlwONhKxExMlKy1z3T2XE0KmMoIunL69d5RWa/DkNVKYZCUkpZF1Wl6O4b1UuDaA58/rQqALA8BgBkWUV/MIa4osI1vpIGjrBhAJZt8cs1l4DnOMQVFQE3j5hMC/GbdVjfqQgcYcOqShGRYhiJqLo91Xg5eMXUclCMyicWkzEYlrIte+MIG7ZDG28ACkVNvNEzOBrDrDofZtcllm2xG6tyJRqVIUHGqKEfMb9cNpTEjvOx4UpHizFVVYVCoZeR5gnAcZwuCiTHWI/ecjECHgEcgJisghCAUkChFALHocEvYiQqQ5IVEEJASOK7vCKPKlHAQEgyldbiOKL7guTv13yCXTyc/FuSt2t+SFZU8ByBwJGUc1u1SY5+qext2Pi7CSEQeQJJoaCUpuQf2bZPun212P2B57qxtHVmQsircmP6FO+ElFrLdK3J9ukSOMgqBVWpZd+p9bpwIiIhGlfAEQIXR0A4AllJlDjmCOB385AUiris6t8JnB4XXQIHgSOISAq8Ig9ZNe9b4BjR0fHEeIjHlYQPGIsN/G4OoZgKF08QVyhklaLawyMsnY4fvCKHiKTC7x773OGlADPl99n023TawkTkI3n4YsfacLq2VVVqee+sfj8w/riZaRiOxjE2nGcslBPpviPZTqd4OXzuRy8X3CcVUBtlJHCMDZea2d96Kudj3r/n6iJcSSr5XFs+5Pt7HNh2ZZ/XMZxHurjOxVOEYyriKoVb4KBSQFZV8GM6CqWAW+AQkhSoNDEuzqjxpRsLHWfDVvm0R+QQjCogBABNlHPnuETerFCKY8NREALU+ER4BA5eN4cpbhHDkbhJvzK252AohlhcBUcSK3yLAoGiAnFZNeXWxYptsqUUcVaZ4zgbLlfS2ZosqzgRliApKhSVQqUUYUlBlVvAmdUeXdNN1qJqvS4MR+KQZAUekYMUp5DGYul6nwtD4TikMf1V5DmIAkEoljqvIR99N5/fmWmf5M+Nv28cebjtxrSZN6X0AQAPEELOAfAvAP4PgOmEkDsBPE4pfTvd8U5DlhX0nZJw244uXQh5qKMV8xuYAMEoH3iepP3bqUwWsSOTmD1/WhUev/2yFKeeTqQ93DeKdQa/tbmjFedOqyrr9ktuC7+bR+9wFOt2dOHSc+rQsWgWbn9sf8pvppSaHqo0BtxwubJ7m0cQOJCxSJ8QUtbtx5hYZFnBu0Mxy3hCFFlMMdkoZEnyiUSWVRzuG8WDz7+Nmy49G3fuPWgak1SV4shA0DRWbeloxbzGAFwuPuWhdyb/7PEI8EBAtaeEP5LBKAMyCQLa33LSpB3RENbUBUTsXHMJeELgFXnUeE/Hmw88123Zx7WXOowx6VXNjbhj8TxTHKrtO94yh3bbcy3lNZHlFCcKq3zj3qUteLG7DyvaZ0OSFQyFJF0o0trHaFvJonSNR8DbA0F0bjff62nVbn2fT9T78bXPzkvZZyIm7aS77/nahFa6NldSviuLUqEMe1wuHjNqzaVDaiwqidQmt7Pfft90FGJCWy5ahxZv2eX32U6Os9MWJmoCnZMm9OWK1f2zals7bWZ+YwDvDISwZrth8vrqixFT1HG3iccjYAabNMdIQyn6X6bvMGptABCNA4/ffllBfVIm3wmkTsLORS9kMBgMBkOD4wjq/KKeAwyGYhA4AklWEFcIeI7A7eLw8ckYOg3j0r1LW/CLl9/DV/9hLoIxGdteeg9f/8f5E/1zcsYun/YJCg73B1Oeh8yr92M4HE/RCUg1sZ1ANxSSEJdVuF2ndQlV5VCfHDv4J34S22TUnBjjJ92LwwPBmD5xzStyqPUmXla20+80LXgoJJmfy6xs1V9sbUgT8zZUuTPG83bb5zYEUp4HJecaufaRbPa328fqc6v9CtVns5pBQCl9l1L6A0rppwBcBKAGwO8KcgUlZDB0egIdAPQOR3Dbji4Mhsq2Qi1jkhGPJwKVGx5+FZdvfAE3PPwqDvcHEY8rmQ/OE0mScWw4jA+GQjg2HIYkyTmfQxM7lm95BZdvfAHLt7yCw32jkGW1CFc8sRgHMiDhZ9Y8ug9DY35Gc/Izan1oqDq9kofdMf3BmC4SadvW7egaWymovDG2RVhS9d+55jPn6BPoAPNvzsf+JUnG4GgUb00SG2QUHxZPMCoRbbxZ2jpTn1wDnB6T+oOxlLGqc0cXjp+KIhaTSx6fMBiViCZaXLfpJVx27x9x3aaXcLhvFN9+/CAuu/eP+PbjB/GWYfsXN72M7o9H8a87D+C6TS+hu28U7w+F8MVNL+Mz9yX6Yt+pGEYiEj46mejLdn18KCSlxKRLW2emxKHGuJYxMVjlDr94+T38j5YZuPGnr+m20903inhcwfGRCI6PhPHWR6csbefbjx/E8VNRXfTWzrnm0X34a89J/Xwf2eyTyR5UlWJgNIZjw2EMjMagqvbVEHKlmOdmVD6ZdAorn9zdN2qyM6tzvNU3isHRqKV2kim/z6QnGLHSFiaCXK7ZadjZgKrSlLa1u3eDIUmfQKd9/sGJcNm2CaO8GG//y0bzTfcdyX3ohodfxcenYqj1ugrqkzL5zonQyxkMBoNRmSTnAMbcefmWV/DOQAhH+kP6BDogMS7dufcglrbOxG2P7Uc0ruKmS8/GA891V0z81x+MWT8PCUuWOsHbfUG8MxDC8i2v6LnUWx+fwruDwbSaljHXssrH3vr4FPpORlj+z3AsdjpCPK7gcN8orh+Lm7/08Kt4++Mg3h0M4kTotD1bHX9sTNM1PZfZ3oUTkez8S6acwW671fOgyZTX5rwMD6X0bwA2APhO4S+nuMRVqt9ojd7hCOLM0TLKBLtApVgTqiRJRvdAyCRCdA+Ecp5IV8kTwZKRZMXSz0iyvXCT7pi4olpuk5XKmvxl/J08R6x9taLmbP+aDY9E5JRjK9UGGcWHxROMSkTzwzVel+24Y/X5wGgMg2HriaXMxzIYuWElWmiTW4HEpLbkvrZ+z0Gsu2KOLmR8MBS2nAjVOxxJ28clWUmJSdPty5g4rHKHpa0z8ZWd+1Pu/fFTUSzf8gr+duxUisiv2c7S1pkYGI1Z3mufyOv/7rfZJ509ZDMJKV+KeW7G5KAQE9qsznHbji6MRGRL7SRTfp+PnjDRlOM1a+SiVdndO8nic5/Il22bMMqL8fS/bDXfdN9RKr03k+8stV7OYDAYjMrFKgcw6i537j2I+oBoOS5pGopP5PVJdZUS/8k2z0PsPq8PiCkvcHZu70LPiUhaTcuYa1ndi87tXfhL70mW/zMcS7oJaclx8/o9B9FzIoK/9pzU7dnqeDvNLhxTsuoDmXIGu+12z4Mqxa9lIu0kOkJINSHkfxFCfkwIuYok+CqAdwBcX5pLLBwCR9BUay4N01TrhVAG5QUYDCB9oFIMBmxWWxrIcZbxZJkIBgCiwFv6GVGwX0413TEunrP2W3xllSI1/k5Fpba+Olf712yYI5g0NsgoPiyeYFQimh8eicRtxx2rz4dCUsnjEwajUrETLWq8LgD2k9q07cZJT8btPpHX+7ZdHxcFPiUmTbcvY+Kwyh3q/NYivia0pbOdmrGyEFb3eiQS1/+22yedPRRzhapyXv2K4QwKMaHN7hwcgaV2kim/z0dPmGjK8Zo1ctGq7O4db5EbhiWlbNuEUV6Mp/9lq/mm+45S6b2ZfCfLRxkMBoNRKDLpMr3DEfDE+tmAUXfpHY7o5UsrAbvnIVaxcFOtFzyxfpZnpVkZ29aYa6W7Fyz/ZzgV2wlpNvGqT+ThE3ndnq2Ot9Pj3hsMZdUHMuUMdtvtngdNlrw20yyM7QDmA/gbgFsBPAtgGYB/ppRem++XEkKmEkKeI4QcGft/rcU+FxJCXiGE/J0QcpAQckO+36fhFjhsWrFQv+FNtV5sWrEQbqGyJqMwKpdST9zIR4SIRs2lAKJRuegTweJxxfSdE7lcf51fxNZVbSY/s3VVW9qAOd0xjQE3Nne0mrZt7mhFY6AwNb2dgvF3bn3x3RRfvbmjFW7Bxo44YrI3zQaHglEAwGO3XmJ/bIVNRmSUBhZPMCqRxoAbv1rXjpamKSnjzsMrWyHyBFuSPr93aQv2dvWMKz6xihsYjMmGVpISQNqJTHaT2rTtTbVehCUlZXtTrRcXjPXtvV09uHdpS0rc6eKBuKxg+5cvxrabL8KCmTXY29WT4g8yxbWMwpCuTKlV7jDVL1raRnQsL4orqq3tjETilnaxacVCbH7hqL7/3q4ebFmZ3h5Sr1tFQ8CNLStb8fjtl+K5r38GD61YCElOfVvWeOzxkUjGEi3JwuKCmTXYsKQZYUnWj7NrR+3zvpMRHB+J5FQONtM5WWnZ3JFlFf2nougdiweGglH0j0Z1Wxgcjer3qX80ihOhwrRzvhPaOEL02MUuBiIE2HbzRZBViuFQVN+fUopfrWu3ze/z0RMmmnK8Zo1ctCo7bcbFEWxc1pLkk10p/vLhla2o84ss9mUUlPH0v2w1X6vveHhlK1RVtc8DC6y1ZdJG2YuObxtf2AAAIABJREFUDAaDwSgUdjmAUXf5+FQ0Jf7TNNJ7l7Zg8wtH0VTrRWO1G5UyFDUG3HjIJhZOHqM3LmvBx6eilu1opVkZ25YQgg9PJOJkLs1kRSARt6iqyvJwhqOwnZBmE6+GpdMV6QgoiIXd7+3qSXkus2nFQvzubx9lXBVOVSl4Dmn1PLucojHgLttcvxAQSu0dCiHkb5TST439mwcwCOAsSunouL6UkPsAnKCU3kMI+RaAWkrpnUn7zANAKaVHCCHTAXQB+CSldCTdudva2ui+ffsst4WiUQyGFcRlCo4AKgVcAkG9j4ff4xnPT2JMDkoW7tjZcTQq48hQSH9TsKnWi4c6WjG3zg+PRyj4dRwbDuOGh181iSpNtV7sWtuOGbW+nK7vnaGQvlSpFmCdO60KwjgnncTjCg73B1O+89zGAFyuiZkNrS25KskKRIFHnV8ElyFaTneMLKvoD8YgKyoEnkNjwJ1vu024DafD+Dv9bh4xmZp+M6XU8l53vTeI7z55GE21Xvz2q5eidziGrvcG0Xp2vb5v56dnY8mFTaZjC2WDjJLiCBtm8QRjHDjChq0wjqcNATfuWDwXs+v98Ll4nIrFsXrbG7ihtQlfWDADA6MxDIUk7O3qwb/+w1zMqvPgwxOxnMfiUsc1jIJREjvOJ5YoR7SSlGse3YeGgBvf/Nx8rN9z0NQn/uv5t/HsoX5c1dyIry6eZ+ozG5e14L6nuzEQjOGhFQuhUoqv7Dygb//Rly5EtUfA6kf26X37E41+EEJAALgEDrG4opcR0I7b0tGKM2s8qHa7MByJ5xTXlgGOtmGjTWj3Y+uqNsyfVqW3vTF3IIRA5An6RmPo3G62DZ/I47FXP8SN7WchIimme6zZTkOViDsWz8ODz7+Npa0zUecX0VDlRjQu48u/OH2+B5ZfgDOmeOB28YjLaoo9WF33I6svwnBIwtd3/1X/7N6lLfjFy+/h6/84X/9NVsda7WdkYDSG6za9hN7hCBbMrME3/mm+Xi5GazO3wGHVz183fTa3IYAjA0E88Fw3brr07JRjrL4r073RzpnunhUYx8YTuSLLKt4/EcLAaAzr9xy09IObVizEj/9wBM8e6k/xe+NpZ1lWcbhv1FansLrfmztaIQoEtzyyzzbPfGjFQlR5BXT89HXc0NqEKz45LSXWaapxYzSqWOb3+egJE00e1+wIG85kA1b7J2szp2IShkJx9J5IrCIQlhQ0TfViilfA34+Nmj6bWe1lsW/l4AgbBvL3GblovsbvEDhOzw8vPacOHYtm4fbH9hdda0unjTpRGy4DHGPDpWb2t57K+Zj377m6CFeSSj7Xlg/5/h4Htp2j8zpGeWKVAxjzDy1P/cqVn8BoVEaVx4W6QGJCyZG+IB58/ggGgjFsXNaC+io36v0u1PptnxeUlQ3H44lS7opKQQH84KlDulb17aubMRKOI66omOJzYePTh1Py7R/fuAB+kcfqR6zb1qh/JXSphaAgplh904qF2PHKB9jd1Yurmhvxtc/OM+kgRc7DGamUlQ2XAjvd6BP1fnT3B032vHFZC6o9AuIqxV8+OIHL5jUiHJMRTtLvHlh+AeqrRAAEQ0FJfy6z5tPnYE5jAFP91ovuaNfywHPduP3KT2A4FNfz01l1Psyu81vqjMacohz1iRyx/TGZJtHtp5QutPs776shpBvAFZTSjwghZwJ4gVI6P8MxfwWwjFJ6JN1+6TrSseEwjvafwpzGasgqhcAR/W+rCUEMRhITnlweGw7jub9/hH9oPhOUJmYk/+HQR/jH884sig1LkozugVSBb36DH6KYKvClE2CmVXkKNREs6+9k/TqFCbfh8aIF6poPf+7vH+G7Tx7Wt79055W44eFXsXNNO27caraLzk/PxqpLz4asUrgKaIOMkuIIG2bxBGMcOMKGrUg3nho/X97ahLWXz4GLJ4grFC6B4MyAG4QQk39uDLgzPrBgY3jZwgSSAmKcCAQkVtO6Y/FczGkMQOAIfvHSu1g4uw41Xhem+kXs2fchlrWdhZOROKb6RQwFJaiUYqpfxMZnDmNgVMK6K+agxutCWFJwToMfK376Wko/u/va83H+jCkAgDePncSGJ95M2efx2y9DQ1VlrX48hqNtONkmgOzux4lQDH/tOamX7938wlEMBGN4ZPXFuHnb62gIuHXboADOqfcjriQmw9V6T0+WJITgu795M8WWPC4O6/cctL0Oq+vedvNFlra1YUkz7n7ykH4uu9+cvJ8RozCp7Wdl56sfecP02e7ORVi+5RXbY9K1s911aucsYR9ybDyRK8dHIuj+eFS3ky0rWy3vy4Ylzejc3pXy93jbOdMLa0bBGAAUSnHj1tds88y4QuETOSzfkohvXvzmlSl5KYt1ADjIhsf70qIkyRiMSFAUQKUUHCHwuzl84ccvZ4yrjZ9PcnsoRxxjw/mSq+arkZzDJeeHNV4B9VWlf7kwWS/MJh+d5JS9DeeLAyeC6bBJdDnj6LyOUb4kv7R2bDgCgScIuAVE4wpCkoLpNR5IsgpKgZFwHNOmuHG0P5SSj2eI88rSho+PRCzz3w1LmgEAU30igjEZ9QERHhePYEzGSDiOc8+sQu+JCIIxGT4xURae50jiWV21B99/8u949lC/6ZwPLL8QJ8ISarwufRX9pa0zcfeTh7Dz1ktwo4XeVcFalhMpSxsuNnYTz+JxBQPBGOJqIm8cDEbxn799S/cVb/cFseGJN036nabHReOqpb7269svRaNN7K1pWPnoX5MIWxvO9JrbBYSQU4aTeMf+JkisEled5wVNo5R+hMRJPiKENKbbmRByMQARwNF0+2VCVilWbetK+fxP668Yz2kZjJIhqxQ+UQBHAIUCHAF8opC2vOp4EEUB8xv82LW2XRchGvyirZiSrhSAIHCYXuO1PG485FNytthoImxcUdlkrQLjcvGYUeuDLKvoG43iM/On4bm5jdj64rvY3dWr24NKU+1iy5/fx43ts3FmlTutIDhRSJKMgZCUVV9jTCwsnmAYKXexXn9wmGY8NX6+u6sXu7t68af1V8Dr4ky+KteHf7mM4cxHMiqV5JKUB3pGsPqRN/DSnVeCUorhsIxz6v0Q+ISweN3CJhAC/OCpt7Dx+hZcv+UVAMCute262KhNNAGAP/z75Zb9zCfy+qQQn8hb7pOpJACjOCTbBJDd/YhIClY/8gYWzKzBuivm4FufPxcjkThEnqB3OJJYNctgGy/deaXJb2vC2bHhsKUt7VrbnvY6rK7bzrZqvC7Tuex+s7ZfJJ4o/2p825XjCOZPq8Ljt1+GsCTb2nnyZ1qZDO3cydvTtbN2nVoba0I+gfV4ppWW0R6+8ATgOK4S39zNm7iimuxk+hQPNixpRo3XpT9U4QjBjBoP9qxbhBqfCzwhcPEEC2bW4EDPyLh8VSadguOI3jc+GApBsYhdtvz5fawYyzMHQhLiyul9rPLSQuoVTHsoHPneEVEUUA9gICRBHdPpRqMK7rhyDi6d2wBFpeA5gpePDDhSv2JMXrLVfJPzsHT54cN/OoqvfXYuPhgKldwnaXohg8FgMBjjJTkH0HQXI7vWtuv/9ok8VArTC1walRjnaTm1kd7hCKZP8cAr8hgKSpZt8af1V0Dgie024wQ67ZwqpSZdAgDuuroZO9dcAp4QNATcpmvJlNNPglW1GA7A6EOMuFw8KIDLN76gf7ZgZg02LGmGrFKcXe+31O92rW231dfismp5DapKIckK7r/+AjRWuXPuK4zMk+g8lNJ4PicmhPwewBkWm76d43nOBLAdwE2UUktLIISsBbAWAM466yzbc2n1hpNnWgrMQTIcQDZ2PMXL45MzavClsTf+tLcEp3iL97BeFAXMyPIh9UT0Maf161zLgVQS2fri8WLVxptWJBZJ1eyBI/Z24cRJF/m+AcwoLCyeYOSK08rG5OqHjf5055p2W7u2+3y8Dymy7UvMR04eShVLOAlR4C37gSjwcPFAx6JZWP3IG6YSlzVeF775ufnoORHRjx2JxC3Po6jU8vOwpEBRKQIeIVFmzuYaGLlRCBtOZxOZjruquTGlZMpjt16S0/lcAme5f1xR0x5ndd12tqXZq3Yuu9+s7Xe0P4hQTE4py6IJkwOjsLVzI021Xrh4znTuXNrZro23dLTiquZGk+h/VXMjBkOSqbRMphK1TqGUvtjFc7qdNATcUCn0N6S18iZ7u3pxfVuTqSzwxmUt+M4XmrHpj++UzFe5eA5xxdqmBZ7TtZPjI6d9c7q8dLxMZu0hE9nacKHaMFk3GwlHLbU7lkcysqVUfjiT5muVh+1aa503coSgY9EsfZU65pMmN5Mxr2NUFsyGGRpa/miVa0qKimqPALeLA1/EuD8fimnDVm1yVXMjVAr0nEh8ZtUWLp7DFK/LRm+w166MNNV6cXQghNWPvGEqB3ugZ0Tfbpcf2pXZdHJuPpmpVD9s1L8WzKzBN/5pvq4vbbv5IlttTLTxRVb2nq4sdTZ9hZEgUwbzWr4nppR+llJ6vsV/TwDoG5scp02S67c6ByGkGsBTAO6ilL6a5rseppS2UUrbGhoabK/JJ3J4qKMVTbWJt0w1EcMnskSOMfFkY8ehmKoLF0BipvBtO7oQilnPNC41dV7Rso/VecWifWdjwG35nY2BiVmCtD8Y0wVYIHGP1u3oQn8wNiHXU0qy9cXjxaqNb39sP9ZePgc+d8LP/+HQR46yi0wMhCTLvj0Qkib4yiYXLJ5g5Ep/MGbZdyfK5+fqh43+9In9vbZjeLHG9mzPzXzk5KFUsYSTqPOL2LqqzdQPtq5qQ51fRFhScftj+022f+feg/CIPNbvOYgHnz+Ce5e2JB5SvnAUG5e1mM5z79IW7Nn3IR5asdD0+cZlLaj1u/D9pw5BVilm1flSjtWugZEbhbDhdDaR6bi7rm7WxTcgYTM/eOoQtqxszfp8AkdS7GHjsha4BT7tcVbXPavOl/LZvUtbsLerx3Quq2O1/e5d2oIHnz+CNY/uw5CN37drs1l1vpTPGgNubF3Vpp87l3a2a+POHV246+pm07nuurpZn0Cn7Xfn3oNY2joz7W9xAqX0xY0BN2ZOTdjYHYvn4is7zT5v/Z6DWPOZc/QJdMbPh0Nx3HV1c8l8VWPADVEg2JTkUzcn5ZmNATc2j8U3dvFVIfLSyaw9ZCJbGy5WG9ppdzVe6zyymJoZozxxSkxslYc993drvc3tIilxK/NJkxen2DCDkS/MhhkaxtgeOJ0fN9V6sLerB4pKcWw4ih2vvJeSJzzU0Qqfe2KeFxTThq3a5NtXN+MrO/fjweePoNbvStEUNne0wi0Q3PO7t1Ly8E0rFuLhPx3F/ddfYPr8geUXYOZUb0rbP/j8EQCn88I7Fs/Vt6fL6YdCkj6pSDve6bn5ZKZS/bBRv1p3xRyTvvTg80cstd29XT2o9bvwwPILstKwrGw9l77CSJBp6YZiTb39DYCbANwz9v8nUr6YEBHA4wAepZT+qhBfeiqq4IW3+rBzTTsopSCE4In9vfjCghmo9RfiGxiM4uL00g8ej4C5deZSAHVeER5P8VaJcbl4nNsYMH3nRJbSs1vKWFacMdGxErBrYxdP4OUEzK0TMNXngsfFOcYuMuH0vs0ww+IJhka5912jP73/9wkBQrNro98s1tiebdxQ7u3MYKTDWJIyuZyEXcxDxv7fOxzBD5/p1ksfzq7zYXdnO6LxRFk/gOKGi2dBUVXsXtuOiKyCA/DxqSi+95tDONAzgu9co2J2nR81Phd2rW2HQgGPi0O9383exJ0g0tlEpuN4jqTYzLOH+nH3tednfb6IpOC+p0/b1Ugkjvue7saP/mUBmmq8tsfZXTcA/TOtpOkPrmsxXUPysQBwIiRhaetM/PCZ02/K2pWayOa7jb97/rQq/OC6Fqiqit2di0Apzaqd7dq4dzgCniOm78pUopaVzUggCBxmT/Wj2uNCJG7dZnZt7hP5RLnXEvkqQeAwvdoLv8jrsYtVuUJB4HDutCrs7lwEWVFR5eGLkpcy7WH8FKsN7WLXwZBScs2MwRgPVrb83ScPo+uuxSY79rg4BGPWPpz5JAaDwWCUM1ps/6vORYgrKjiOQOQ5cAT47hfOR1xR8fHJKLb8+X0Mh2Vsu/ki8BwZW/mfRzimotKqjSfnOwLPQR2LGXqHI/jebw7hm5+bj+23XKy3V0PAjb7RKJ491I+BUcmkNxAkysMf6Q/ini9+CmdM8cDj4uETeVS7XSad4F93HtD1ASARa8xpDOClO6/MmNPb5egsN2eUEqN+FZZkk00e6BnBfU93Y/stF2MkEk+UhKUU/3HNeeAIwBOC3Z3tkNX02q2drc9p8GfVVxgJMmXpDYSQf7PbSCn9f/P83nsA7CaEfBnAhwCuBwBCSBuAdZTSWwEsB/AZAHWEkJvHjruZUvqXPL8TAkewq6tXf0gIJGZbfrG1Kd9TMhglpRxKP3g8AmaUWAB0ufhxl5QrFHbLOws8W6GqUNi1sYvndPG51DY4XsqhbzNOw+IJhka5991kf3r/749gV1cvdncuwvQar75fMcf2bM5d7u3MYGRCK0mZjF3MYyzReqBnBJ3bu9BU68Xjt18GDsDyLa+mHLO7cxFu+vnrlsv+cxzBVL8bYBPBHYOdTWTCriwqx3FZn08UeAwEY+jc3mU6h9fFZzWRz+p7svlu47EDozHcZljNRruGdKUmcvnufNsXSF9u13jOgdGYbRkOVjbDjCBwaKz22LZZurLUpW5HQeBQF/BktZ8xlirGizZMexg/xWrDdLHrRGhmDEa+2NlyNK6m6LAxOcJ8EoPBYDAqEkHgcKYhtjdybDiMsKQkdJeuXuzu6gWQGAMfWX0xpnhdpbzUkpGc7xhzuQM9I/iXra/pOpWWJ2u5tKZjAYl2uvva8wEkJhB1/Ox1/bip/sRxRp1gIGmFW02ryCa/T5fLMxilRNOkBkZTSx8PBGN4uz+Iu588hA1LmlP6yvkzpmB6TXp7t7N1ryjkrYVNRjJlMTyAAIAqm//yglI6RCldTCmdO/b/E2Of7xubQAdK6Q5KqYtSeqHhv7wn0AGJklG717Xjz9+8Ei+svwJ//uaV2L2unS2bzygbGvzWZc8aHL7kZjyu4NhwGB8MhXBsOIx4vHJn9lstZZxc3oUxPup9rpR+kE0bO9kOy7VvT1YaA27LeIL188mH00qK54rVmPVQRyvqfdYCz0T5UeYjGZMRVaWW5cO1Eq3JfXfrqjbUel3gOWCLYdtVzY3YeeslUCnFf69tx1N3/F/YsrIVVzU3Wi7dr6oUA6MxHBsOY2A0BpWt+Fg2yLIKWVXx2K2X4I/fuBy/XHOJ7X1OR63XlVP5V6DwdpNvSdtSkO21pStR65Tf4jSs2mzjshZsffHdlLIlG5e1YFadr6DtmG+cI8sqjo9E8MFQCMdHIpDl0qy6xLSH8VOoNky2gTpv7rGrk/UKxuQllzzMqj/9al1ilXPNroeC0ZL6SQaDwWAwioWWA/McwdxpAez48sX4/b9djt/+62XYdvNF2HZzG9wCqbi8zy73yZQnqyoFBcWOL1+C/17bjl+uuQR71i3C9lsuxvQad1a5/3h1AifrDIzJQbJ2Vut1mWzyquZGPHrLxTij2oPHbr0E+98fApBeA7HS4/K1daYJmyGU2jcAIWQ/pXRhCa9n3LS1tdF9+/ZZbovFZLw9GMJtO7rQOxzRE7959X643ewtQEZGSrbcSTo7jkZlDEWksin9EI8rONwfTOl35zYGHFtaczzIsorjpyKQZAqOACoFRIFgerXXVOJlgnCEDY8HWVZxuG8Uv/1LL5a1nQWeIxAFDo1+EaJo3w/KwQ4lSUZEkRGMqnr/rveJbHwy4wgbZvEEw0g8rqA/GMu2RJcjbNiIJMnoD0mQZBWKSrFn34e45sImnDutyjRu2fnRuXX+ksQhkiRjIHQ6/mnI4PcZRaUkdlysWKIcUFWK94dC+GAojPoqN2q8LggcwJFESRCZUnjG3pSNxBW4eA4NfhHvDIaw5tF9aAi4ccfiuZg3LYCRSByd20/323uXtuAXL7+HOxbPw5k1btR6Ty/9r6oU3X2jWPPoPn3/ravaMH9aVaUt8V9xNqzFyOsMPnrjshY0VLkxe6o/6zxEs73+0RjqAyJ4jsAjcGgIeGzPYWU3WzpacWaNBzXe9OUhVJViKCRZlpnVtqmqCoUi65KrpSDdddvtp5Wy5TiuEL/BcfFEoTC2mUvgIHAEEUmBV+QhKxRRWQVPAK/IZ7SvXEiXLxJC0B+MIa6our8dicqJa+Q5nIrGcfO2N/TjNne0psRRxUKW1UQcOlZGKbm0rINxjA2Ptw1lWcXJmISodDqP94gc/Lxg0u7Sxa7loFcwUnCMDReb5DysziuabNuoWxn7U5WHR+9ILMWuu94bRNvZ9SXzkwxbJo0NJzP7W0/lfMz791xdhCtJJZ9ry4d8f48D267i8jpGeaDlwA88142bLj0bd+49mKK5fG3xPEyvdaNKFNONd2Vlw1a6g5b7cBzBYCiGaFwBTwj8bh6SQhGXVXhFHn0nY1izfZ9Jr7jv6W4MBGPY3NGKKV4Bskqz0h/S5eLj3c7ImbKy4YkkWTu7qrkRd13dDI4j4AiB20Xw8UgMnYb+taWjFVMDLsgKdD3izOrT/SOdHlclChgISfpxmfLcSaQJJ2P74zI9eaqoVhkMS/iv59821dr+r+ffxneuOQ8z2ENvRhkQi8noORVB74kIfCKfWCZ4qhdnEa9jJ270B08LJkCi7vZtO7qwa227Y0qwFpL+YAw3bn3NsoTWdJslnwEWvBlJ1xb9wZgepL/+/gjWXTEHdX4RBMCZgn2JqXKwQ0qBD0+kCoxsYpbzYPEEw4iTSornw0hUxpG+IHwij5FIHK+/P4Kn3uxLGbfS+dF6gnH7qUzjoCgKmMEmzTEmCSMRCX2notjwxJt6TPDA8gtQ6xdNEzWMouOWla340e/fRu9wBL3DEax+5A1su/kibHjiTTQE3PqYFZYUrL7sbKzb0YW7rz0fZ0zx6ILIUEjSxRIg0c/XPLrPVH4jGRbDOgNjjAwk7t36PQdx97Xno9rrQmNV5vKTwGnbW7/noMn2eI5DXFEt77GV3XRa2FcymQQ6jku8tW8lMiZepJk4e8u2HOx4ysZOVizbrASlptPFOcPhuN6/rmpuxPrPnWvSZBqrRDQE3Lr/XbejK2P+XyiSyygxcofjCFw8B0opXDyX88TfcFzCcYuJQrOmIuscoRz0CkZlkk0cZ8zDMr1QaPRJx4bDlna9c007btz6asH8JItFGQwGg1FqtBx4w5Jm/OLl90zPCH7x8ntY2joTnTu68Nitl4CDhClCdvm4k7AaX610h3U7uvCrzkUYicRNefsdi+fp+267+SL88vUPTO207aX3sO6KOejc3oV1O7qwYUkz7n7yEDYua4HbxWOqYJ1Hp8uxs5kExHJ0RjFJF5catbMFM2tw06Vn48afvqbb6mO3XqJPoANOa2uP3nIxVv389dOT5Fa24pNnVNvquJoe11DlxoPPv41nD/VnNSEuH0240Dgtrs/0JOpqQsj/BPAJAH8D8DNKqVz8yyoOhMByVjhheRWjTBiJxjE4GjM9UNu4rAXVbgHTHDpxQ1apaUIZkHC+coUuAxpXVOvfq9iXKpjEM7xTyNQWWvsumFmDb/zTfJM/T9dm5WCHg2HJXjh3aP+erLB4glEpqCpFf1Jcce/SFvzwme6UcSudHx0MS+PyU2wcZDDMRCRFn8QEJPra13f/FXdfe37KJKkNS5rRub0LndsTouOzh/r18/hEHg0Bd0rM9NCKhWgIuOETeZMgIsmKZT+XZOuScqzvOge7HMQn8ojGsy+Zls72Vj/yhuU9trObZPtKJhuBLpPIyOyNUSjSxTnGB0WrLzvbUpP5j2s+ies2vXL6uDT5P8M55DKO2e1b7RFs8/jqLOcHlYNewag88onjctGt7OyaUlowP8liUYaTKdWqcgwGo/RoOfD0KR7LZwTVHgG9wxEMjMYgcB5MKbN3IuzGV7/IW47tcUU15fZLW2eacqj6gGjbTto5arwuXefatbY9rxepnDAJiDF5yRSXGrWzdVfM0fsDAN1fWPWvEyHJPElue1dGHdcn8vrk1GcP9WfVF3LVhAuNE+P6TGtmPwCgDYkJdJ8HcH/Rr6iIUIoUo7xz70GkqWjLYDiKuEpTHmqs33MQcQcLawJH9LrbGk21XggVKma4eM769/L27tYuuBsKSUW9VieSqS209rUKMtK1WTnYIRPOywcWTzAqhaGQlPIG4Z17D+KOxXNTxi07P0oIGbefYuMgg2FGodYxgU/kUz6r8br0f9f5RdP2sKTgjsVzU8as2x7bjzsWz8VIJG4SRESBt+znomBdSo71Xedgl4OEJQV8DuFuJtuzusd2dpNsX8lkI9BlEhmZvTEKRbp80WinZ1R7LDWZ+oDHfFya/J/hHHIZx+z2LUQeXw56BaPyyCeOy8Xe0+WPhfKTLBZlMBgMxkSg5cAeF2/5jMDjSmwfGiuHXm7Yja+8zdjOJeVM2oQ4jXTtpJ1jJBLXtyl5NtlETwJiTG4yxaVG7Sy5j2jHW/Wv5Lg2Gx1X0+M0zTj5OCty1YQLjRPj+kzZSjOltINSugXAMgCfLsE1FQ3VRhBW2VNvRpmg2IgVqoMDscaAGw91tOrOV1vqvzFQmTP/GwNubE76vZsz/F4W3J0mU1to7VvnF3Nqs3KwQyaclw8snmBUCnY+d3a9P8U/2vnRPxz6aNx+io2DDIYZTXA1ok2ISv5MExqbar1orHKb+uisOh9m1/ts+rkPm184ahJE6vwitq5qM51j66q2lMl5GqzvOofGgBtbknz0xmUtmOp3wStmL3jZ2Z5mZ0DqPbaym3uXtqTYVzLZCHSZREZmb4xC4RM5yzjHK5onqNpNNNXygGwbao4sAAAgAElEQVTyf4ZzyGUcs9u3EHl8OegVjMojnzguF3tPlz8Wyk+yWJTBYDAYE0GdX8SWjlaEJetxKCwpuHdpC/Z29ZTls510ca/Vs8/knGkkEjf9HYzJlucLxmSTfqCd0+PKb6L9RE8CYkxuMsWlRu0suY8AwN6uHvzkxoWm/rWloxV7u3pM+2XScY16nFHLy9QXctWEC40T4/pMdZf01qWUyqTM65Rpb2cbb0JTrRcu9oYoo0zwjAUByTbsdnAQ4HLxOLcxgF1r2yGrFAJH0Bhww+Vy7jWPB0HgcO60KuzuXARZUSHwHBoDbgiCvZ8Rbe7rZAzuMrWF1r59o9Gc2qwc7LDeJ+Khjla9NIYmMNb7ShOkMLKHxROMSsHO5/pFPmXccrl4zK3z636UEII/HPoIrWfXj9tPsXGQwTBT73dj66o28xL2K9vgdp0ef7RJUvc93a0LG9OnePH47ZdBkhWIAo86v4jBYMyyfw0FJQwEYyZBhOMI5k+rSjmH3bL5rO86B0HgMK8xgF+uaYckq+AIMBiUUOVxocabvY+2sj3NzjSS77FmN7++/VKEYwreGwzhh890p9hXMppAl1yqwbi/cR9NZGT2xigGVW4R9QEVv1zTDpVScIRA4IGAS8DmjlZ95d7BoGSdB3AEL66/Iqv8n+EcchnH7Pat9vLjzuPLQa9gVB75xHG56FZWdu1xcag7f3rB/CSLRRkMBoMxEXAcwZk1HpwIWeeoPpHHT/54BF9dPA8NJZqAUkjsxleOs372yXHElNvv7eox5VAjYet2aqxyY+etl+D7Tx3CgZ4RXROo9+c30T4bjYHBKBaZ4lKj5qqqKrasbEXn9tMx9R2L5+G3f+nFhiXNqPOLaKxy44wqN7722Xk49NGopU2n0+M2d7Tiweff1q8jU1/IVRMuNE6M6wlNs2oKIUQBENL+BOAFEB77N6WUVhf9CnOkra2N7tu3z3KbLKvo7h81GeWWla2Y31jFBC5GNpRsFqmdHasqxeGPT2GtwYYfXtmKc8+onrCa0OWELKvoD8YQV1S4HCRul7DW94TbcCbs2uIT9X4MhCT93jX4RbwzGHJUffRCEIvJGAxLusBY7xPhdmea7z6pcIQNs3iCMQ4cYcMaVj53c0crGqvcmOoTLe25GH6qhOMgozCU5KbkG0tUCqpKMRSSTMIFAP0zl8BB4AgiUnphw6p/bVnZinq/CMKRrM6R7hrLtO+WlQ1b2YJd+6oqxWAohmhcBU8Ar8ijxpv7fTXaWTAqY9XPX8/qHudyrdnur+2jqioGQ5Ip/ioTeysGjoonKgVNL0h+Gc74ucfFYyAYM9nh5o5WnDuN5QE54ggbVlWK7o9HsWa7edL6/DNS/Uq6MS8eV1geP/lwhA2Ph3Q2rarUVj91km5VxrGoEyh7G86X2d96Kudj3r/n6pJ8T6nI5/cApWu7HCirvI5R/hjzV6/IYyQcR9+pKNbvOXhab+loxVS/CyoFGvwiRDHtGOlIG7YbX+c2BDAciUOSFRBCwBOA47gUvUoUeNR6Xfq+XpFH38mYOeYeG6+TjxvvpJ1cNQnGuHGkDU8EucalybZq7DNG283Wpq3OdyIiWeqDTuwnExjX25487SS6ciTTQ++BUBSyAtObpQ1+DxO7GNngiOTSic4tGyb6umVZxeG+Uf3tB6eJ3SVqH0fYsB3GB2QKBSilEAUeNR4B3f3BlHs3vzGAkahcdn2BMS4cYcMsnmCMA0fYsBFVpRgMxhCSFLw/GMKDzx/R31ayGyOLMWZNdJzAyAkmkJQZsqzi+MkI+kdjGApJ2NvVg6//43y4BW7ck6PKtO+WjQ3nI8IVWnRyks8vU3srBo6LJyYDmqbw27/0YlnbWeA5AlHg0GjxcIzZakYcYcOyrOL4qQgkmYIjgEoBUSCYXu0tWQzMKFscYcPjxcqmVZVa6qdO1eBYv8ybirDhfGCT6Ngkulxxmg0zJgarXPvRWy7GFK+AiKRCUlRQANG4giq3gOlTrOPJJBxrw1YTco4MBE2//8c3LkA0ruKMag98bh71fnfaF/7YeF2RONaGJwIn2Xm6ybDJfTl5kuxEXfsEtZ/tF0yq1+JOhCW8Pxg2zQrfuKwFPOHQWO2Z6MtjMLKC4wgaqvJbznaicMKbgf3BmC4AAYla2ut2dGF35yJMr/FmOLr4lON9LST2NuLFx6eijr53jMkHiycYlQTHEcgqxcqfvWZaLtvOzxZrTJ/s4yCDUUyGI3Hc+FNzHz/00SjuvvZ8U3y15tF9ePz2y1L6YqZ+z/pu8RgKSXq7A+nvUz77Z0Oh7/F4xhFmb4yJxKgpbPnz+wAS5UV2dy7CdMMkOifoH4zsOBGWcGw4kpLXeQTeMq9jPohRaVjZtJUG9+Dzb+Nri+ehc4fzVoNl/ZLBYDAYpcAq117189exu3MR/vPJv+OmS8/GnXsNK9KtbMUny7iCWPL4OjAaM/3+hoAbEUkxxdHpYgM2XjMmA06yczt9cHfnopTPH3iuG1/77LwJr/zgpPYDgEm1XIqkqLpDBxKGsX7PQUiKOsFXxmBUNnbOeigklewa4opqenCoXYfM+r8jSGcj7N4xnAaLJxiVRi5+1gljOoPByA1JViz7uE/kUz6TZCXleNbvJw67e2d1n/LZfyJg9sQoV7KNl5iNlw8sr2MwUrHydUtbZ+oT6ADm1xgMBoMx+bDLtWVFxdLWmfoEOu3zzu1dFTVOJv/+dVfMSYmjWWzAYDiHdD7LMtbfzmL9ZCbVSnSKSi0NRlUrq6QtgzEeirFcZikf5thdv4vn0FTrNV1HU60XAu+MucROWuZ1IrCzkYgkAwC23XwRfve3j7C4eRpqvC6EJQUeF291Kgaj6LB4glEpaGMPAPz32nbQsfLEI5E49nb1WI6RThjTGQxGdmh9SKEU226+CA8+fwQHekYAJOLgsGTut021XogCn3J8WJIdPzGrUhEF3jKHMd4nu/0XzKzBuivmoM4vgpBE6d1sfWgx/W+xxhE2ZjCKbQPZagp2Nh6WZBwfUdEYcGdT2olRAlhex2CkYuXr6vyirWZ3fEQFpZSNvQwGg8GoaOxyc4HnbMfJStJMkn9/jdeV8Tdr+ZmqqlAoWLzAYGTATtPIR+tI57OMny+YWYM5DYGK92H5MKlUG8+YwRhpqvXCbSNAMxiTDa3syHWbXsJl9/4R1216Cd19o+MWEEWbvmf38Cdf0l1/Y8CNzR2t+nU01XqxuaMVjYGJXxq0WO1eTtjZyNGBEC7f+AI2PPEmOhbNwt6uHtzw8KvY8MSbGApKk6qNGM6BxROMSsA49ly+8QV841d/BQDc87vDuPvJQ/jq4nlo8IspxzlhTGcwGJkx9qHP3JeIpb75uflYMLNGj4Nn1flMsfHWVW2oG+v3xuMPfzxakn7PSKXOL2Lrqjbb+2S3/1XNjfjGP83H3U8ewrLNr2D5lley9qHF9r/FGEfYmMEohQ1kqynY2fjhj0exfMsrONw3CllmK505AZbXMRipWPm6adUey76iqBTLt7zCxl4Gg8FgVDx2uXljwI0zpliPkxSomHEx+feHJSVtXq/lZ99+/CDeGQixeIHByICdpiHLal5aRzqfpX2+YGYNvvm5+eg5EWa6rwWE0spyVG1tbXTfvn2W2/pORvDuYMhUo3vjshbMqfejcYrX8hgGw0DJpsans+NCEI3KGIpIkFUKgSOo84rweAQMjMZw3aaXUmYmP377ZeOqQ605f62kSbb1tO2u045M1y/LKvqDMciKCoHnHPMGeLHa3QLH2rCVjWxc1oL7nu42rZiyYUkzOrd36X/vWtue0S5yIVebY5QcR9iwXTxxTr0f01g8wUiPI2wYsB97ND9rNw5FozKODoX0cj7ZjunZkOyDT0Vi+PyDL5uurwhjIyN3SmLHxY6HnUY2bxu6xlY7isQVCByB380jILowHImbjgOAj09F8f+zd/dhblR3nui/51SpJLW6Tbfb3Q7QxhDCy3gyJrgdwkt2Q4ZNNrswySZ2SAYMeRvAMMnczbIE9s7lbu5lMxficJmBDDaQCcNbJrx42GQgLyTkMsmFIYkbBm7GwXgINjYh7na72+4XSfV27h9SlfVSpZbUaqkkfT/PowesLlWdOvU7p875qVR18V3/VNbG/+6Ks7F3cg4/e3Ucn/s3J8N0XLiuQkyTWJEyMJ2xYdoOhBD+589c1Y//+u9P8x9P0sh23yJtFcO1/uLUdVXo8f/7a87FcF8icL0DyVwsWbaDi+9+vqq5iTe/shwXhiZhxAQypluxnPXODSspPKcV3oHvuP4k3rYs0ZA4Dauvao5LUTvWJXQpkDaL22yNvyqOzHiilQrrVQiBL3/3V3hq57j/95GBJJ74wnmYN11YjovYAjkA11U4OJdFxnKgCYGkoaE/mTs+02kTadNBwpDImK4/VonrEnNmrk/uTWjoi+eWL43xWzasxdd+mJvbjgwk8chV5+C4/q6eN0QihpdyXsfcQseLRAwvldL8aVwXePXAbFFbufPSdfj6T3aX9bvfvvJsCIC5uujr6Biu5MQbnqz5M3tuvrAp22mWevYHaF7d1aCt5nXU/grPj5oUMHQJKQDbUYFjytWDPYhpWqU8ZiRjOCwHUbj/cV3i4KxZlh9euSyOtHk0p3TjRWtw0xM76/7us7AsSUOD7SpYdnjOIajsQPh8u9blm6lN7rYfyRhuhlpjpzB/FpSbGJ/J4GN3PlfWVh6+8mz8H//wL2Vj7tI2tFB5hBAwNAHTUdAE/LtDfuLu5zHUGw/N+wbtE4DA3EkE47MaoYXuqtlGxnbx1R/swo0XrUF/MobptIWv/mAX/vKT74JlOYjx0YDUBTIZG7sn53B1weBm66ZRnDKYWrJH60gpcNrKPjx+zXlVn/ArlTMsUbJQ+XVdRjJRXW+9t8kgqmorl8Xx8JVnw1GAFMAXvvWifwEdkKuT/mSs6N9vHc7g0LxVMS6qVU/MUXeqNJ4gahdh5x6vn/UezzMxA//84vWTdzz9Km68aA0GUwaG+uJYmYo35AK6oD74u396Dj781//kl6nbbyNOnSnsoqJThnqxe2I28EcGE7NZbL10HY7psXHJPT/3/37/Z89C1nYxlw1+BOuBIxn0JnR84PePxce2Pud/7raLz8CsaeMz9/4S+6fSeGzzOf7nX9w3ja/9MHfeO2W4F5oUOK5BFybRwqQUNV08LKWAUsGPKJzPOnBTuR9Slsbctk2j+Id/3o+Lz1pd1dzEtl28cmAGmwv67cL4DLswrp654UK8c9pSXfAZ1Ea3bRrF7U+/iqd2jlfcTqUfC03MZv0228iLCrtBUL3esmEtJmZMfw557tsHsW8qUzS22LZpFKev7Cu7kC7sOI0MJGE5CgeOZHDvs6/jc+99O6599CV8YnQE5//eyrJxy4peByv7kn6Mz5s2XvndjH8BHZBrT7YTfie6TpvnR9lSzeuYW6B2Vdr/eBeivzk1X9ZWBFD0ZR6Q69/enErj2kdfaljMsz0REVEUuK4qy89841OjsGyFVFwPHVMmYu11I6Ow/NSxx8RxcNbE1JyJLz7yEvZPpfHBNcO4/7NnQQhAlxKAwoe//mxRTqmax75WU5ah3ji+9KHTii5ULJ03h5U9rktc/s1fBF4cVLp8VObnS/HjQ2qcWmPNdVVZ/qwwN+G6CvPZ4O9q3jqcwafOPako1xH06OSweBlMGdh1YAa3/WgXPnXuSUX5sgc/9x7sn0pj/1Taz/v2J2MYGUji2PyPygLbiOXiigeKcycrlyVw4mCqo+Kz9bdgaiJdCkzMZnHVA2P4xN3P46oHxjAxm4UuBcZns60uHlFTTKZNP/EA5Drbqx8cw2TaXNJHtHlf/hw/0IOhvoW/bK9UzjDNesRco9VT7k56ZJG3Lx/+em5fLrnneTiuwkRJvzwykMR02ir69+ScuWBcVKuemKPuVGk8QdQuws49Xj87MpDEr383U3R+8frJp3aO46oHxrBx2z/h0m/8fEn74MHeRFH5on5OJ6rH5JzpJySAXPxfcf8OjM9my96/7rGXsfn8k3Nt5KEXYNqq6O97J+dxxf07MDlnBrbxyTkTU3MW/vPD/1z0uS8+8hL2H0r775V+/sV907jpiZ3YPT6LS7/xc0zMcXwUZWF9/OsH5zA5ZwbG3OYHx7Bx/Ql4Y7K6xziMz2b9BKC3jsL49OIwSK1zw2r3d/P5J/sJQa9MlcpRrbD62jC6asHtBH22sJ68NtvoMne6oHq9fnuuXj1Xvu/ksrHF5gfHAvN/YccpayvsnZzHdY+9jA2jq3Dto7kvjD6ybiRw3GI7uXV5MR7TJG56YmfRj8NGBpLQtfC74XXKPL8dLNW8jrkFakeV+h9D18raysHZ4LHmdNpqaMyzPRERURQEzRd0qeHqh17wv8sqHVNajkLaDP/xTBSF5acOzlrYdyjtX0AH5C6mv/ybv8Ceg/P41/FZ/Ov4XFlOaTpt1f2dbWFZNp9/sn8BXWG5CufNYWXfOzkf+Lmg5aMyPw/bF+YJoqHWWAvKnxXmJibnTLx+cC40j1ua6yhtQ5XixfvbhtFVZfmywm2+uG8aVz0whmsffQlCCEgpwtvIA+W5k72T8x0Xn111EV1ME7jz0nVFz/+989J1iGkCNhNS1CVsN/iuBLarQp+R7d2eMyrlDBOl8teinnJ30iAqaF++8uRObNs0WlQnWzeNYvvYPv/ft2xYi23PvLZgXFSrnpij7lRpPEHULoLOPVs25vrV0j7WO78sZT+50Lrb5ZxOVI+wO0Najhv4fuEdI0u/5+8xNOyfSmPbM6/hlg1ri9q41669ZUrX22McTcBU+vz+qcp3UaLWG0wZuKtkLH3LhrW4/endMG0nNOY0KXD707vLjv1dm0bL+t9q4rNZdw/1zmmDKSOwTIstx0J3b620nYU+G9YeeefVysLq1YvTkYEkYpoIHlsE9F9h65Pi6DEqvIuCG3K3R1epomM33Bsvm9du2zSK4d7gu0t20jy/HQz3xrE1IO8QdnyqxdwCtaNK/U/Q3HF5KoZbP35G4FjR+zxzdURE1CmC5gtS5M5J9/z0N4HfFdz9j6+13fmqmnlR6d96DM1/ebyc0vaxfWX5hWrzu4VlqeaOdmFlLyxX4eeClo/K/HypnhpHjVFrrIXlz7zchGk7gbm4rZeu8/OwhbmO0jZUKV68vwW1oduf3o2tJX3XLRvWwvuas5Y20mNoHRefXXXPa8tRmJ7L4OErz4btKuhSQEpAKfDuMdQ1dCkwMpAs6uRGBpL59lD8aJ2+pIaZtIN9U/PQpcBQyoBhNKfbqFTOMEvxaKBmqKfcnTSICtqXp3aO46aPvBOPXHUObMeFrkkMpQz89z/6fVz3709Hj6FBCOCOS87Ei3snG9KH1xNz1J2CxhOvjR/hxT1dql0fuVV67onpEroU+KtPvgu/DnjsmGk7Rf3kVz/2Tpx7yhCcfBswTXtRY4RKffCz17+/reqWqFbeXbRK4z+mycD3C+8YWZqPnTcdjAwk/Uew3vvpd+Nw2sLknOm3a2+Z/VO5x19uPv9kDKYM9PcYuHh0BBesWYn+ZAxSCDxy5dn47eFM0ecXuotSaZ8IoC37yXYmpcCx/Qnc9JF3osfQMJ228LUf5h4f6v1aNSi2vF/Qf+2Hu3Dzx/4AbzsmAU0KpAr6d+8YA8C9n343bn96t3++KI3PsF+XL8W5c7DXQI+hBZZpsXcxDWujpXfJDtrOQp8tbI8LrYuOCqrXD64ZxrHHJPCP152PmCaLxhaFfZ0mBVxXQUoB23YxPpuF7Sr8+L+8D3f/42t4ZGw/gKN9rHeMvLso5L5ECh63SCGKjp2uS5y+sq9oXjvcGy97nKynk+b57SAW03D6cG/RvG64N45YbHHtT5cCd3xyLc5cPQjHVdCkaFjegqhWpmljIv+DqEq53Ur9T9jc0bJdv397bWKuaA7ZqHwac3VERBQFhq7hg2uGsWF0lf/I1qQhce+n340VvQYGew18+8qz/TzpwdksptNm252vvHnWUG8cm88/Gf3JGBSApKFhsDeO737+PPTGc+MIx1V4bMcbmDfL5yov7pvGfc+9ji9/+J3QBPDIVedAKVXT/L9wzlc4F/OUzpvD5t6l5Sv8XOnyUZmfh+0L8wTRUGusCccNHs/mc6veXZ8LH6k6bzqYzdp+Hva4/mTodyQLxUtpPsMzMZtFxnKLHkV933Ov4ysfXVu0Xu9xym9bloAQAt++8mzc8v1Xisb986bT8Pj0coeu68JRqLkPWayuuoiuPynxjrctg+MACoCrAAHAhcIQv/imLjGYNLB106h/K3zvl7aDyVwb8B47Ypo2dk3MlS132lCqKRfSLVTOMF75G8WyHD+p3qiEapBay91Jg6iwfUkYErMZBwq5kyOQi4tD83P4zN/+sqa4qEa9MUfdJ2g88Y63LcMx8a66wS/h6CNvvF/se78EOm1lX1tcIFJ47vHOdwrAmmOX4Q9PGyq7AKEvpmHrplHsmTiCE4eW4ZN3P9+wMUKlPjiR6KopC3Uh7+4epX3JcG+87P0tG9fiqz/Y5f8i0dCPfrE4MpDEO4ZT+NafvAfjM1lMzpl4bMcb+KN3jeCmJ3b6y6we7ME9l63HbT/ehU+dexLue+51bBhdhZgm8ad/+A586/k9WHfiIAZTBmxXYXhZ3H/8a6W7KIX1iXFd4vJv/qIt+8koqOeCM9dVsF2Fk1ak8PrBOWx75jVMzGaLfq1aGlvbNo3isR1v4JYNa3Hfc69DCIFP3/vLouN2ylAvdk/MBsbkxGy2KD7vuqz47nWF++G4Cv/jyZ14auf4omMiKO4Ky9SIu5gGtdFtm0Zx+9OvAqj8a/qgzxbW0+rBnsD2zx9nVFZarx9cM4w/u+BUfKJgbHLPZevxt595N776g1fwqXNP8h9d4tXxO1aksGt81n+sinfHCAB47jeT2LJxLeK6wOrBHmzZuBb3Pvs6bv34Gbj20ZfwnRf2B45bdA1lx07XJY7rT5btQ1CuoZPm+e0iFtNw/EBPQ9fZn5QYPWnQny8qBYyeNMj5IjVdLbndhfqfSnnLTMbG4YyNifwjqarJp1Wbb2WujqjxTrzhyVYXgagtlF7A8b/+xzV4/eAcbv7+K5iYzWLrplHsPTiD1YMr8dvp3I8Pt4/t8/MsX7jg1La79mAwZeD+z56FA0cy/uNTvTns4y+8iUvPPgHjM1ms6DWgawKfOu8kSAFYDuAo5f+obWI2iy9+IHfRTb25n8I537ZnXsOWjWuLylQ6bw7LrcV1WZQ3q5QXicr8PGxfmCeIhlpjzXUVtm0aLco9FOZWS2P9zy44BScM9uCt6Vyuw2tLQO5Hym8dThflB8PKM5CM4VDaxIOfew9+dySDr19yJj7/rRf9ZW67+AzEdFGUMy7M5Xn9wUzGwrzp4LKC3O5tF5+Bv/jeK34ucOWyREPj08v13fajXYH5nGbklYV3YUKnWL9+vdqxY0fg3w7NZfDmdLZs0nVcfxyu29gLb6gjNe1bnkpx3AiZjI3J9NFfIQZ9Qf3m1LyfgPaMDCTx8JVnNzzBuJhyLiXLcvDK+GxZn3H6cO+SXEhXizov3IhkDAfty6Obz8bBWaus7o/vj+PDX39uyeKy1TFHC4pEDIeNJ47vj2N5KtGsIlIETMxk8dE7ny3rkx6/5rywcWUkYrhU2PnumV8fwMNj+4vOL14/uRRjBPbBbaMpcbzU4+GoCbtQqvD9WP4Ximkrd2fIVFxDrxHDVNqCaTtIGhoOHMkWjanuumwUpw71Yjpjl90d7ndHMvjyd39Vloy489J1+PpPdvsXON112SiGeuPIWE7FuyiF9Yk3feSd+Mzf/rLovQr9ZDO0TQzXM+YP+sxdm0ZxbH8C/cmjF+CVxtxAMhdLruvCdlVgP//IVefg4rv+qez9v7vibLw5nYZSCjFNYrgvjuOOSfpxElSmWzasLbq7Yb0xERZ3D195dkN/oRpWX9Vc3FjUjvN370mbi7pbYyTHE81WWK9CiMDY/Purz4XluKHjlrD3gdzdFvrzF2lMp02kzdzdmKAAy3XRG9eQNl1/3NKb0NAXry7ewsZepw2l8NrkfNv+QKMGHR3DnC92hbaI4Vpyu4v9gVgtc7la862cJy6JtojhpVDPBWR7br6wKdvpRPXUXQ3aZl5H7afSBRzeXHaoz8CfXXBq0YUx3o/SNoyuwk1P7FxonhvJGB6fyeBjd5Z/B/fQn7wH40cy+OIjL/n7+9eXnAlNyqI6CMo/1Ktwzpc0NNiugmW7ofPmWp+OEOWnKbTJ028iGcPNUGvs+HfBD7lDvesqTKdNvDWdwVWF7emyUZw2nBuPVxqrB+WsSn8E6+V3LcdFTJeYzdi4+fu/xobRVRhMGWW5PCDXH/zLm0dw43d+VdYnfPvKsyFwNHfSyPj0cn03XrTGv8ivcNsNzCuHFrolsw0hxHIADwM4EcAeABcrpaZCll0G4NcAHldKfX4x202brj85A3K3JL/6wTH/tv1vTjnoMSQggGMS8Sh2RkQNSRwkEjqOX+AztqsCb+Nvlz4zaglVU86lND6bDe0zqr1IwDsxWo6b+0KpwqNbal1HOz66NkjQ42xN2wmt+6WMy1bHXCswGVm7SuMJpFpcOGqqTnnkVqXz3YfPPB66FLBtB4ahI5HQYc9ll6QvXqo+mP1cZayfxfHGaYCCUrk7zsRLkieFt533LoTLWA40KaBLgZguYTsKGdtBXJOwHdf/VeEyIzcuyrUvF0MpAyt645iaz91yfzabgeMqGJpE1nb95AiQa5dXPTCGR686B27ALe+VUtgwuspPBnufueahF3DjRWvw1M5xfx2PX3MeThgMPsl5iZp50w7sG3oMrey9tGXjt9NuxVvxt0nCcElNzpllx/SK+3f4yaKgOgr6zFUP5o5hYf0F3VHG+/ebU/OBx9Jy3MD3FRROXdlbdI/uwdgAACAASURBVGFY4baCynT99pdx40VrcNUDY4s6d4adiwv3p1ZhydBChfUXlKw8krWQNh0IkbsLlRS5zFzGdGDoEgJA2rTxO8eFEAquCwiR2x/TdNquH7ZtF4czJqAATQPmsi76EhIzGRdCAIYm4bgKlqsgBaAJATt/x0RNCsSkwPIeo6YfqxUeg0ox6/1/6d/Cch6Oq8r6u+WpuD/O9/r9mUzu4ubjj0nUPMevNPbqlHl+O6s1j1O6vFKK80WKhEq5Xdt2i+I6KDdXS/9T7VzOay+15Fu9dXvzlgNzWehpk/MWIoq8Rnw3tFiuq3BwLpvLQQjR0Isd6r0Aqda5fumPZzQBSCmrWnfpj58GkjEcmjeRthzEdQlXAa5S0ISAFEDGzh0rAeCK+3fgxovWlOVMvLksAP/isdK/9SdjbZMj9i7eSZsOnPyNl4LGD1II/wI6771Dc1bRxTVe/uHvrz4XvzuSCY39sNjxyuHNox1XQUoBQ5PoM3RMZ2wAgILCkYyJuayTO35S+vPqRCw/37ZsHDjiQubj5dhjkmXxEnan3bC5fr1zs6AYjukStqugXFX0qMrCfIKjFBIxzgmbLagfOZQ2kbUcSCEQ0wVsB7njqElkbQf7puYRkwKDPQbmJJA2HeyfnkdMSsj88dalgO3m+pzJuSxiuvR/uOdt76qSPuWqB8bwyJVnQwGh+UEvF7hgbjCf3/XG2ytSCl/56NqK8W3ZLnoMLbBPEEBNN1So5aJYL9fn9aWl2/b61tJj1RfTir7nWNFjIB6vb77QqlnGDQCeVkrdLIS4If/v60OWvQnAPzZio5Umjq/8bgY3PbETWzeNYkVvDLOZeRzf38NOiSIlk7Gxe7L8NvynDKYanjTQ5dFHQ3lGBpLQu6hNLPZCQtt28cqBmbJbtJ6+sq/qydJC6+iUO2gWDlZt28Wbh4O/hLVd1fVx2UjN7FM6SRQuMqZo0KUM6ZPa61FNlWL6fVueKXvsTzuNEdjPVcb6WRxvnHb7068G3lo+rkvc/P1fl/2t8FGTt378DPTGNVz14AsY6o3jSx86zX88xR2fXIsTh5YF3kl9/1Qa86ZT9CiLBz53VmBbTlsOrn3kJf/Rlt6vFL0kRdBn+pOxon+HJX4L71py88f+ILBvmDeLPzsykIRS8O8aFXSnk3Z/XHajVLpYO6yOliX0RV3g7boKTsiYWwvp/18bn8PbjkmEHp+w/fDibDGPq2z04y9rfSwxgKLlP7hmGF/60OmYmMni3mdf9x/l87n3vh3XPvpSWTsfGUjiLz/xLtz909eKHvvTTv2wbbv47ZHcnQgTMYnfTlmwLAuH5mO44+lX8V8+eCqkEJicNXHvs6/jmve/A5btFt3BYMvGtTjSZ+PEgZ667vq+UByEjVsC39cqXyy12Dk+UHnsVemRibT0aj3GQcs/9Cfv4XyRIiGsn9OkwCsHZsrieqn7H6+99IaMVSq1Ec5biKjdNGrcuBhBcxvvsXsnDqYWNbeudd5U71w/7K7m9z33Or74gdMqrvuDa4bL7hS3bdMobn/6VUzMmGXzMi9XM9Rn4L/9x9+reAFHfzIGTYrAv3kXsIwMJP0fUkaV6yrsmZzzH9861BvH//2JMwLHD07AHCbs4po508Flf/PzwNgPOqb3f/YsAMCBIxl/Hl2aR1vRF8djv3wDd/1sDz64Zhif/8NTcM1DLxTFxU93HcCFZxxf9P6tHz8Df/P//qYsXqqpm0bkpYLW8/VLzoRlu7jnZ78p29dtm0bhuC7+tOCxm92YD2uVavqROy9dhydfehMXnXE8ZrN2UT9y72fejek5syjfsfXSdTAdF//Lt/+5KKZ7DA3TCQsAcPk3f4E7/vjMwPaUsV0cmjNDc3315garGfsbuoZ501l03q2wXoPyYqUx7uV4ptNW6LaDjtUXLji1bL5w6opUXRfStar3/giA+/L/fx+A/xS0kBBiFMBKAE81YqPexLGQlzjb9sxr2D+V+9WT7QBZO3flIlGUTKbNwF/qTaYbH6tDKQNbN436bcbrbIa66JnrlfqMaozPZst+ibL5wbH83Uqq04h1tJvx2SykCK57TYquj8tGamaf0kkW2zdQJ1HYsnFtUZ+0ZeNa5O5F1T7CYlqIXEx7fcNEfmzcTmME9nOVsX4WxxunBd3N7Yr7d2Dv5Hzg36577GVsPv9k7J9K49pHX8L4TC4Rsvn8k/0EAgCcuXow8PhkTBeH5qyiZfdPpbHn4HxgW947Oe9v74r7d/jzXO9W/UGfmU5bRf8OS4wU/rJRk6KsT7zt4jOwanmy6L2/vmQdvvLkzrL6Kpx/h92Brdvm6F7SqJB3PMLqSISMo6tNbk3OmfgfT+7ELRvWlh23B557HXddVtz/37JhLW5/enfF4xO2H14y7J7L1wfe7a0agykD91y+vqhMi1lfWL3unZwPjMfS5TeMrsK+Q7l27rX/DaOrcO2jLwW28/1Tafznh/+5aNl264fHZ7MwbQXLASwHuPrBMaw8pgdX5/tHXWp4cyrj18nUnFV2B4PrHnsZ+w+l657nVoqDoL/dtWkUP/qXt3DnpevKxjPDveFJ5EbNzzmfiK5aj3HQ8hqPL0VE2Lztud0TLckteu0lLOdXqY1w3kJE7SYK3+sEzW2ue+xl7J2cX/TcutZ500KfCytP2F3NN4yuWnDdG0ZXBR6DDaOrAudlXq5mw+gqP7/izVkLeT8WHArJpyxPGdg+tg93bRqFUtHOEU/Omdg7Oe/XxebzT8b/9b1fl+UDtmxci4Oz2bL99S6uKTQykMSeg3OhsR90TPdOzvvlCMuj7T+Uxsb1JwDIHVvvQjlvmeu3v4yN608oe//aR18KjJdq6qYReamg9Xhz4qB93fzgGA7NWV2fD2uVavqRax56ARvXn4CDs2ZZP7L/ULos33Fw1vQvoPPeu+6xl3FozvJjf/9UGr1xPTSv612YW/o3IPgOdYvNDXoGUwZWD/aU5XtrzbsV1mtQ/1sa414eZ/vYvrL+yNt20LEKmi8cnK+v7bTqZzorlVJvAYBS6i0hxHDpAkIICeBWAJcBuKDSyoQQVwK4EgBOOOGE0OUSMYmtm0bLrkDsMSRe3DcNIFehrso9XqIdbrNKnaOaOG7m3Y8MQ8dpQyn/cce6FBhKGTCM7vl133BvPLDPqJRULxT2uCM7/0iZZq2jWartixdiOS6+++KbgXX/+Nh+rFwW7+q4bCTeUa3YYscTiVi0f1lGjZexXXz1B7v82/RPpy189Qe78JeffFdLylNvPxx2vvvOC/v9ZQr7hnYaI7Cfqyxq9dOosUSzeOO0sF8m9xgaehD8q1zvDlzecgDK1hP0K1/v+AT92vf2p3dj26bRol9H3rJhLb72w1244T+c7n/em+dKKXDcMUncddmo/0jN3C8kR3HHT14FsHBipPAOY1II3Pz9V4r6xL/43iu4/Y/fVfSeFMBTO8fL9qtw/t2uj8tudAx7SaPSX5QOpgy8dTgdWEeaQOhnqmHaDp7aOY6JGbPsuN31sz347HvfjoevPBv7p9KYTlv42g93+fmUsOMTtB93XTaKFSnDf/REvb+oXuzj54L2P6w9l77n7W/h8oVt22vThW270p0MCv/byvNUrXFsOblH5ABH+y3v/NKfjEGKo3coKKyfQl4d17vfC8VB6d8sx8GXn3gFF4+O4N5PvxuaFHBchWOSesU7gzRqfr7YXANVtpi+uNZjHLT842P7OV+kRWnUeKJ03qZJged2T+BLf/8rAGh6btFrL995IbiNVOoDozZvocrabV5HVKoRMRyF73UqzW0WO7euZ95U6XNh5al0V/OF1l1p7uX9f9jfbv7+K9h66Trc8ZPduGXD2rI7hfUndThK4a8vWYc//dYLRX9LGhL/7T/8HuIxiYzdmu/xqo1h03aK8kv9yVhZPsByXKwaSGJq3irLOS1PxbD10nW4+qHiOrjxf/6qaDuFsR90TL24WSjHpuXnd2HLhN0dsJ7H6zYqLxW2vwvt62K32+5aNZaoth/RpAjMzVb7XtBxzlhOWX+z9dJ1+N+/8y8AUPa3WzashRTBfdlic4MeKQVOHEyhvyeGh688G47KfT+6IhWvKe9WWK8LPaLV2+5pK/vwlY+uheu6eOSqc/xHHnu5nmqPVb3zhSX7pksI8WMAbwv4059XuYprAHxPKbXPuwtGGKXU3QDuBoD169eH1kTGcjH2+kF864qzoZSCEAI/2fkWBn7/WH+ZkYEkpBCw8geCqFmqieNmPz7NMHQcH8EvxJslFtNw+nBv0UUCw73xBR8v4z2Du57Hw5SVQQt5VGAEbwNdbV8MlD+nvPALjpgm8fBY7sINr+6FEPjOC/tx6493Y2QgifeeOozVg9U/a52CtdMjGZthseOJ5QXjCeoOuhSYmM3iqgfG/Pda2YZq6YcLBZ3vfvQvb+HWH+/2l/H2y80/Zqxdxgjs5yqLWv3UG8Ot4o3Twm4tP286MB038G/end685QCUrSfs0Zm6FIG30p+YzaIvoeOmj7wz90iA/AVOE7PZou0VznN1XeL33rYMj1x1Dn47ncbknIkH/mkPNoyuwpX/9mQc15/E25YlQhMjhY9QnE5bgX1ixnJx0xNH7zzn3cmsdL8Ky9XoR3Q2S6NjuNKFQWF1JKVc1EVl3npf3DftH8uRgSRuvGiNv35Dwr+zWuG2w45Poy90C1p/ox4/F1avQY8lDnpU6HTaglHSNxS27bD+onTZVp6nao3jmCZhObn6MfL9lnd+mU5bGOyN+31WYf0E1fFi9rtSHJT+7bfTuSTyI2P78Uh+7jkykMQjV52z4Fy1EfPzenMNVJ3F9MW1HuOg5R8e249PvGcV54tUt0aOJwxDh5i3cOk3nq8Y15X6vkbx2os3z/TaSDV9YNTmLVRZu83riEo1Ioaj8L1OpbnNYufW9cybKn0urDxhy3vzpkrrrjT38v4/7G8Ts1nMZm388VmrsSyh495PvxuzWRvT8xZmMhYmZnJ3Vfu7X+wt+vHZ7U+/ij8+azUA4B3DvZHPr5U+qtGrs6B8wFUPjOHMVf342sfPwLHHJOAqhd8dzuDxF97EjRetwWDKwDHJGAxdYqLkjouFsR90TL24WSjH5uQvhglbxnFV1fGykEblpcL2d6F9LdQO+bBGa9VYotp+xHFVYG622veCjvNvD2ewfWxfUZ+SsVxMzGaxfyqNr/1wV1Fb2/LDV/DlD79zSXKDhaQUWJ6KA6maP+orzR9X07YWyvVVe6zq7YeX7GytlPp3Sql3Bry+A+CAEOJYAMj/dzxgFecA+LwQYg+ArwG4XAhx82LKtKLHwOhJK3DJPc/jfVuewSX3PI/Rk1bgN+NHABy9pbmuAXFd1P34D6KlMpgMvg3/YJKxulRiMQ3HD/Rg9WAKxw/0VHUB3a4DM/jonc/ir368u+zxMNtq/HX5cG8c20qOea3riJrCOjrvlv8HH73zWew6MAM3PwD29vnhsf34qx/vxuG0hUvued6/gK7d9z9K2KfUZzAZPJ5gvXWfTmpDhee7oVQuxkv364W9k0X9dTvopGO0FFg/i+ONWcJuLb96sCfwb1s2rsW2Z17LfYn48TMw3GfkxjjPvFZ0e/wX904GHp+EIbE8FSu7lf7WS9fhW8/vgaFLXPvoS7jqgTFMzGaLthf0q0MpBd62LIFUXMdNT+zEI2P7cdMTO5GK6xUvoAOKH6FYWn5v3Pbs7vGiMfH2sX1l+1VarkY/orOdeUmj4wd6MNR39Jeeleoo7DPVGEjGyuYft2xYi+1j+yo+HnOh47OYMjVT2L6tHuwJ3N/S5beP7cOq5bl27rX/7WP7cOvHzwhtJ3/5iXcVLdtu/fBwbxyGLhDTgJgGbN00igOH57E13z/aroPjBxJ+nQykYrjt4jPK+sWR5cmmzfPC5tlDKaOquWoj5ue15hqoOWo9xmGPy7RdxfkiRcZCcb1Qnm4pynHrj3fjknuex0zGxsq+xIJ9IOctRNRuovC9TtDcZsvGtVg92LPouXWt86aFPhdWnqDlS+enYctuH9sXeAy2j+0LnJd5uZPtY/tw56XrcO+zr8PQJa5+6AV84Laf4gt/9yIMXeLeZ1/H6sEerF7egyv+zdtx0xM78Ym7n8dNT+zEZ847CctTMYwsTyIeE5H/Hqv0UY3bnnkNf/XJdxXVy52XrsP2sX0AchcXagL465/8K353OIPrHnvZzyFZjosvPfYyvvX8nrJzdmHsBx3T1YM9fjnC8mgjy5N4bMcbAOAfo9K4eGzHG2Xv3/rxMwLjpZq6aUReKmg93pw4aF+3bRrNxRDzYS1RTT9y56Xr8NiON7Ci1yjrR0aWJ8vyHSt6jbJ2tWXjWixPxfzY99pfaZ/SX5A/eXHfNG56YicAYMsPX8EXP3AahnvjS5IbbLSF8seNaFtB+ebFzBdEK57HLYTYAmBSKXWzEOIGAMuVUl+qsPynAaxXSn1+oXWvX79e7dixI/BvEzNZPP/aOM5cPQgnfwvzF/dOYl3Bv3sMCQjgmER0k7rUMk0LiEpxnMnYmEyb/q+VB5MGEono3wmmW0zMZPHRO5/1r3S+eHQEV77vZMQ0gZgmMdwbr/h4mCC27WJ8NgvbcaHXuY68SMRwaR0BuZPZ49ec519VXrjPqbiGrK0asf8UoM36lMjEcNB44uyThxt2FxRqHzW2oUjEcDVM08bEnFn22J/S/rodtFk/13R11E9T4nixMdws3phFQMH7ntH7dR8ATM6ZcF0XjgKUUojlf3mbsRxoUkCXAjFdwnYUMraLuCbgKsDN3xl9maHh4LxZ9OhkXdcwNZ+F5SjYroLr5tabMATmsy6kFFDe9nQJXQqkzYV/dVjvHUgKP5fMP47Rsl0YuoaBZAzjs1l8+bu/wobRVf4vKV/YM4nLzz2pqL5Kt7WEd0TpmBheijqamMnizx9/GRtGV2G4L47euA7TcTHQYxRdVNmMO9a0StC+AQjd39LlB5IxHMlaSJsOpABcBUgBKJV7HJ2hS7hurv3qmoQQCq4LiPwyUemHgerj2LZdHM6YgAI0DZjLuuhLSMxkXAgBGJqE4ypYroImco9/tl0FJ3+H25gUWN5jNPVCsqB59lTaqmmuyvlp3SIXw4VqOcYTM1l846f/io3rT/AfC/zYjjfw2feeDNt1Of7sXJGO4SCV4rqaPF2jLKYP5byuodouhhvlxBuerPkze26+sCnb6UT11F0NIj+vi8K40XUVDs5lkbFcaAJIGhr6k42Zu9U6b6r0uUrlKVxeCJGbT0hZ1boHkjFMpa2ifx+aN5GxnNy8LJ9/0YSAFEDWzh2ruC6QsY7mVxxXQYrcj8M0KbAilTs/TqWzyJousraLmCahaQKm7eJbz+/B5/7NyRhelqhUhZGIYddVmE6bSJtO7lGNusRvDs5hRa8BTQgcyVhIWy6OOyaBREyDruVyTIX5n9LcU39Cz+WVQ2I/LHa8cnjzaG++aGgSA8kYpjM2TNtBTJcwNIG5rANX5Z7kIERuvYmYRNZyYSuFmJT54xYcLwtpVN4jKIZjuoTtKihX+TnD0nxCvY/ObKJIxHCjBfUjh9ImspYL6R07J5fbEELAdFw4rkJMCgz2GJiznfzxOxqDR3O/DqTI5UBiukR/srjfTBqanyPWBNBjSJh2Lpfi5X9LY7pd8nOV8seNalv3PfsbrDtx0M8/bx/bh698dG2lOU3oRls1y7gZwCNCiM8BeAPAxwFACLEewGal1J8sxUZN28EXvv1y2fvPXv9+nDC4iHsQEjVRIqHjeCYIIqv0Gdze42Gevf79OK4/Wdc6dV3W/dkoKq0joPx55522z1HGPqV2lcYT1H06tQ0Zhg7MmXjflmeK3i/tr9tBpx6jRmH9LM5CY5ZGfPF4fLz8+Az2BidiB8Kedl/FdLfeR2Iu9DmlFJ7aOY6ndhbfgP7yc0/C8aEFbuwjOjvVUtSRaTuBx+vZ699flNDq5OMTtm/VPioUAJbri3vURbvRdVnUL/Xnm/ayCE/pgvpvzlUJqO0Ym7aDu362B3f9bE/R+wud44iarVJcV9P3NaMcC+G8hYjaTRTGjVIKDPdVvJBrUeuuZd600OcasXzQsqX/XuDCtpoMphJ405zH+2/9x7K/eT8cjLrSRzW+OTWPT979fNlyz17//qN1FzbXLXi/UuyHHdOFHhk5VPKjq/4lHm43Ku9R63q6LZ8QNUHHq5Z+NB7Xaz5+i4mzdsnPLUU5C9f55tR8bl5eMjf/739U35ymJT+VVEpNKqUuUEqdkv/vofz7O4IuoFNK/W01d6FbiPds3EIjA933HGkiWjrsZxbGOqJ2xximbsFYJ6JGYF/SXni8qJsx/qlWjBnqBIxjIiKi+nXaebTT9oeIukOj+66uet5Ao55fTUQUhv3MwlhH1O4Yw9QtGOtE1AjsS9oLjxd1M8Y/1YoxQ52AcUxERFS/TjuPdtr+EFF3aHTf1VX3v5ZS4LSVfXj8mvMi/1xgImpP7GcWxjqidscYpm7BWCeiRmBf0l54vKibMf6pVowZ6gSMYyIiovp12nm00/aHiLpDo/uurrqIDmif5wITUftiP7Mw1hG1O8YwdQvGOhE1AvuS9sLjRd2M8U+1YsxQJ2AcExER1a/TzqOdtj9E1B0a2Xd11eNciYiIiIiIiIiIiIiIiIiIiIiIiAp13Z3oiIiIiIiIiIiIiIiIiIhoaZx4w5M1f2bPzRcuQUmIiIiIqsc70REREREREREREREREREREREREVHX4kV0RERERERERERERERERERERERE1LW67nGurqswOWfCtB0YuobBlAEpRauLRURdrtv7pm7ffyJqX53Sf3XKfhBRdLGfiQYeB6Lqsb10Ph5j6iSMZyIiotbotHNwp+0PEXWHRvZdXXURnesq7Dowgyvu34H9U2mMDCRxz+XrcdrKPnb+RNQy3d43dfv+E1H76pT+q1P2g4iii/1MNPA4EFWP7aXz8RhTJ2E8ExERtUannYM7bX+IqDs0uu/qqovoJudMv+IAYP9UGlfcvwOPX3MehvriLS4dEXWrbu+bun3/iah9dUr/1Sn7QUTRxX4mGngciKrH9tL5eIypkzCeqd2deMOTNX9mz80XLkFJytVTNiLqHp12Du60/SGi7tDovks2uoBRZtqOX3Ge/VNpmLbTohIREbFv6vb9J6L21Sn9V6fsBxFFF/uZaOBxIKoe20vn4zGmTsJ4JiIiao1OOwd32v4QUXdodN/VVRfRGbqGkYFk0XsjA0kYutaiEhERsW/q9v0novbVKf1Xp+wHEUUX+5lo4HEgqh7bS+fjMaZOwngmIiJqjU47B3fa/hBRd2h039VVF9ENpgzcc/l6vwK9Z+EOpowWl4yIulm3903dvv9E1L46pf/qlP0gouhiPxMNPA5E1WN76Xw8xtRJGM9ERESt0Wnn4E7bHyLqDo3uu/RGFi7qpBQ4bWUfHr/mPJi2A0PXMJgyIKVoddGIqIt1e9/U7ftPRO2rU/qvTtkPIoou9jPRwONAVD22l87HY0ydhPFMRETUGp12Du60/SGi7tDovqurLqIDchU41BdvdTGIiIp0e9/U7ftPRO2rU/qvTtkPIoou9jPRwONAVD22l87HY0ydhPFMRETUGp12Du60/SGi7tDIvqurHudKREREREREREREREREREREREREVKjr7kQHAJmMjcm0CdtV0KXAYNJAItGVVUFUEdsKRR1jlFqFsUcUHbbtYnw2C8txEdMkhnvj0PX6fivEtk3N5roKk3Nmyx6REbR9AEXv9Sd0TMyZfhtb0RPDwXkLluMiGdMAABnbgSYEkoaG/uTi9qGwTEIIaAKQUpbVTavrjhqn3mMZ9rlGx0bh+pKGBttVsGwXMV1ClwJpM7edgWQMU2kLpu0gFdcwb7p+uxlKGZjO2IFlauR5LEpcV2E6bcKyXQCAAmC7Co6rEJMCCUMiYykopUL7H7ZralccU1I7Y/wSERGFc12FIxkTc1kHQgBKAY5SkEIgJgUGkjEYRnufNyvNqcPmx96c+EjWgmW7sFwF11XQpICUgCYlVqTiZXP2SnPsheaDzAtRJ1qKuPbW6bouXAVYrhuax10o1+a6LhyFolxOveXz8kZp04GjFBIxze8nat0303aQMCRMS8FsQH6tvXvxOmQyNnZPzuHqB8ewfyqNkYEktm4axSmDKU4GiQqwrVDUMUapVRh7RNFh2y5eOTCDzQXtcdumUZy+sq/mCRLbNjWb6yrsOjCDK+7f4cfcPZevx2kr+5qS9Ava/v2fPQtZ2y16b+umUdzx9Kt4aud40b8nZkx86UOn4brHXvaX3bJxLVYuS+DEwVRd+xBUpls2rMV9z72OL37gNL9uWl131Dj1Hsuwz50y1IvdE7MNi43C7Qz1xgNj/qs/2IWhPgN/dsGp2PzgGM59+yA2nbMa1zz0Qmg78srkuqph57EocV2FPZNzmMlY0KWA7SrMm45fdx9cM4wvXHBq0Tk3qP9hu6Z2xDEltTPGLxERUTjXVXhzeh7T8xbu+MlufOrck3D99uL54Yq+OFb3J9v2QrpKc3QAFefH2zaNIqYBh+asovcL8zqFc/ZKc+yJ2WzF+SDzQtSJliKuvXXe9qNd+Nx7345rH30pNI+7UK7tth/tKuv36i2flzc6cCRT1AfUsr6FcnaLya+1JCMnhFguhPiREGJ3/r8DIcudIIR4SgjxayHETiHEiYvd9mTa9CeBALB/Ko2rHxzDZNpc7KqJOgrbCkUdY5RahbFHFB3js1n/wgMg1x43PziG8dlszeti26Zmm5wz/aQEkIu5K+7fgcm55sRc0Pb3Ts6XvXf1g2PYMLqq7N+bzz/ZT0x4f7vusZexd3K+7n0IKtP121/GhtFVRXXT6rqjxqn3WIZ9bnw229DYKNxOWMxvPv/kXJvIn0Ou+Ldv9y+g85YrbUdemRp5HouSyTkTmzW1tgAAIABJREFUeyfncWjOwviMWfQlCgBsGF1Vds4N6n/YrqkdcUxJ7YzxS0REFG5yzkTWVrj6oRewYXSVfyEJcHR+uP9QGhNtPIepNEdfaH68+cExaFIre78wr1M4Z680x15oPsi8EHWipYhrb50bRlf5F9B56y7N4y6Uawvq9+otn5c3Ku0DallfNX1Svfm1Vv2s9QYATyulTgHwdP7fQe4HsEUp9XsAzgIwvtgN267yK8+zfyoN21WLXTVRR2FboahjjFKrMPaIosNy3OD26Lg1r4ttm5rNtJ3AmDNtp2Xb7zG0wDL1J2Nl/+5PxgKX7TG0uvchrE68bXnrbXXdUePUeyzDPhd2XmhETIbFfGl70KSoqh2ZttPQ81iUmLaDHkMrehXuZ1BdhvU/bNfUbjimpHbG+CUiIgpn2g6kKM5TFPJyIu183qw0R69mfuzVT+n73vJ2wRy40hy7cLu1lpOoXS1FXHvrrCaPG7Z9r92GraOe8nl5o8Wsr5o+qd78WqsuovsIgPvy/38fgP9UuoAQYg0AXSn1IwBQSs0qpeYXu2FdCowMJIveGxlIQuetPYmKsK1Q1DFGqVUYe0TREdNkcHvUap/msG1Tsxm6Fhhzhq61bPvzphNYpum0Vfbv6bQVuOy86dS9D2F14m3LW2+r644ap95jGfa5sPNCI2IyLOZL24PjqqrakaFrDT2PRYmha5g3naJX4X4G1WVY/8N2Te2GY0pqZ4xfIiKicIauwVXFeYpCXk6knc+blebo1cyPvfopfd9bXi+YA1eaYxdut9ZyErWrpYhrb53V5HHDtu+127B11FM+L2+0mPVV0yfVm19rVVZupVLqLQDI/3c4YJlTAUwLIf5eCPGiEGKLECKwxoQQVwohdgghdkxMTFTc8GDSwNZNo34ljgwksXXTKAaTxqJ2iGixaonjZmBbqZ9lOXhzah57J+fw5tQ8LKs7fvmw2Biutd4Yo9Ro1cYwY4+iqtn9cBQM98axraQ9bts0iuHeeM3rYttuvaiNh5faYMrAPZevL4q5ey5fj8FUc2IuaPurB3vK3tu6aRTbx/aV/XvbM69hy8a1Rctu2bgWqwd76t6HoDLdsmEtto/tK6qbVtddmE6MYddVmJjJ4s2peUzMZGHbLiZmsjhwOI3fTqf99906f2lf77EM+9xwb7yhsVG4nbCY3/bMa7k2kT+H3PPT3+DOS9dVbEdemRp5HmuURsTxYMrA6sEeLE/FMNxnYHkqVlR328f2lZ1zg/qfKLTrxWrH8VW7a/WYmGNKWqxWjicaGb/s/7pXJ46JqbswhrtP6bw3bH47mDIQ1wW2XroO28f24ZYN5fPDkeVJ9CW1uufIjbCYGA6ba2sScF0Xd102Gjo/3rZpFI7rlL3v5XXuumwUPYasao690Hwwqnkhaoxu7YeXIq69dW4f24dbP35GxTzuQDLmt3Fvmbs2HW23Qf1eveXz8kalfUAt61soZ7eY/JpQamk6cSHEjwG8LeBPfw7gPqVUf8GyU0qpgZLPbwTwNwDOBPAGgIcBfE8p9TeVtrt+/Xq1Y8eOwL9ZloNXxmdxXL+BjKlguwq6FBhMGkgk9Jr2j7pS0346UCmOmymTsTGZNtlWauD1M1c/OIb9U2k/2XT6cC9isZb/AiKyMVxvvTFGu04kYtiyHJiOhem068def1LC0GJRaOcUbZGI4SARP39VZNsuxmezsB0XuiYx3BuHrtf3WyGeV6rSlDiOynh4qbmuwuScCdPO/epvMGVANvEXy0HbB4CDc1nMZx28fnAOv9o/jQvPOA6aFLAchRf2TGLdiYOIaQJxXUIIgaztQhNA0tDQn1zcPhSWSQgBTQBSyrK6WUTdMYar5LoKuw7M4Ir7d2D/VBofXDOMP7vgVNz+9Kv41Lkn4frtL/vnjHsuX4/TVvbVdezrPZZhn2t0uypcXzL/aB7LdhHTJXQpkM7/ancgGcNU2oJpO0jFNcybrn9uGkoZmM7YgWWq4zwW2fFEIddVmE6bsOzcozMUco8JdPPn2IQhkbEUlFJF/U8r+8RGa+fx1RKLbAw36phxTNnxIhvDjdCI+GX/F3mRi+ETb3iy5nXvufnCmj9Tz3aouWo4rpzXUUOUznsXmt+6rsKRjIm5rAMhAKUARylIIaBLAdt18X/+w0588QOnLTRHjmwMF86BY7rEbMbG5d/8hZ8X+N8uXANNiqL5seMqPPT8Hpx/+kqsWp4EIOAqBU0ICAG8cSiNW77/CiZms7j/s2ehN6HDst2Kc+yF5oOtzqlRdGO4nS1FXNu2i98eTmMmayOZH4sbmkQyLjGQjPu5tF0HZnDbj3bh8nNOxHH9SeydnMftT+8uarfKVXAUinI59ZbPyxulTQeOAhIxiRWpeE3rK6yvhCFhWgpWA/JrSzZ7V0r9u7C/CSEOCCGOVUq9JYQ4FsB4wGL7AbyolPpN/jP/E8DZyF1YV5fx2aw/cfOMDCTx8JVn43gmMojKJBI620aNSvuZ/VNpXP3gWK6fGehpcemiq956Y4xSK4zPZvGJu58PHk+wnVObaufzl65LHNefXHjBKvC8Qs0mpcBQX+vuOBW2fQGBTX/zc79POPXYZbjpiZ1l576bPvJOvPP4Y3DC8sb1E9XWSavrrhtMzpn+FwkAsGF0FTY/OIYbL1rjX0AH5M4ZV9y/A49fc15dx6TeYxn2uUbHxoLrSx3938Ll+kuaxVDIRQONPI9FiZQCy1O1H4dOatftPL7qVo06ZhxTUjtrRPyy/yMionZROu9daH4rpUB/Txz9PcDETBYfvfPZslzJjRetWdQcudUK58ATM1n/AjoAeGrnOHa+NYPHrznPn+8V1sNdP9sDIFcPj19zHgCU1dHl3/wFHr/mvPAxQSr47UrlJOoUSxHXU2kLl3zj52V91ePXnOdfsFbYF24YXVXU7oGj7Xb4mETDyuXnjaps82HrWIp+oFWPc/0ugE/l//9TAL4TsMwvAQwIIYby//5DADsXs1HbVUUHG8idDO0W3lKViDoL+5n6sN6onTBeqRMxromokGk7RX1CfzIW2Ef0GBpMm4/m6lRhcRAWD4wFomIcX7UfHjOixmBbIiKidlE67wWqn9+GfdabM3fCHLma+qm0zGLql4gao9Z2zLxf6y6iuxnAB4QQuwF8IP9vCCHWCyG+AQBKKQfAfwXwtBDi/0Pudnr3LGajuhT+c3A9IwNJ6Ly1JxE1CPuZ+rDeqJ0wXqkTMa6JqJCha0V9wnTaCuwj5vOP2KDOFBYHYfHAWCAqxvFV++ExI2oMtiUiImoXpfNeoPr5bdhnvTlzJ8yRq6mfSssspn6JqDFqbcfM+7XoIjql1KRS6gKl1Cn5/x7Kv79DKfUnBcv9SCm1Vin1B0qpTyulzMVsd7g3jq2bRv2DPjKQxNZNoxju5a0+iagx2M/Uh/VG7YTxSp2IcU1EhQZTBu65fL3fJ2wf24dtJX3Elo1rsXqwB4Mpo5VFpSUUFgfbx/bhlg1ri+LhnsvXMxaISnB81X54zIgag22JiIjaRem8t5b5bdBnb9mwFtvH9nXMHLma+qm0zGLql4gao9Z2vO2Z17BlY3fn/YRSnXUL7fXr16sdO3aE/t2yHIzPZmG7CroUGO6NIxbrnqsmaVGa9lO5heKYoi3C/UykYzjC9UbREZkYZrxSnSITw0EY11SlpsQxx8Ot57oKk3MmTDt3t7mBZAyH0iYylgtNAElDQ3/SgGy/O4owhmsQFAdTaQuu68JRgFIKhq5hMNWWsdCuIj2eoGIcXwWKdAzzmFEVIh3DUcG2FGmRi+ETb3iy5nXvufnCmj9Tz3aouWo4rpzXUcOUzntrmd8WflYIAU0AUspq1tE2MVxN/VRaZjH1S5HWNjFMtbfjpKHBdhUs2+3kdhu6Q3ozSxEFsZiG4wd6Wl0MIupg7Gfqw3qjdsJ4pU7EuCaiQlIKDPUV3y1kuC/RotJQqwTFQem/iSgcx1fth8eMqDHYloiIqF0EzXub8dl2Uc0+VlqmG+qIKOoW2467TUse50pEREREREREREREREREREREREQUBbyIjoiIiIiIiIiIiIiIiIiIiIiIiLpW1z3OlYiIiIiIiIiIiIiIiIja04k3PNnqIhARERFRB+Kd6IiIiIiIiIiIiIiIiIiIiIiIiKhr8SI6IiIiIiIiIiIiIiIiIiIiIiIi6lpCKdXqMjSUEGICwN5FrGIFgIMNKk47bp9lCN/+QaXUh5qx8QbE8UJaXb8sQ2u230kxHKbVx7RQlMoCRKs89ZalXWM4CnXf6jK0evtRKUNCKfXOZmxoifvhKNRlq8vQ6u23sgxN6YvrjOFuPi5R2X47lKGZMTxXoRzNEPVj0S1laPT2ozQmbnXdsgzRKUMt249SDDdCq+ueZWh+GTothqsRheNbiOWpbKHydGIMR+EYtLoMrd5+s8sQ5dzEYrX6WHL7HTSeaFAMt/qYRKEMrd5+FMvQTjEcRVE4ns0Q5f0MjeGOu4husYQQO5RS67t1+yxDNLa/1KKwfyxD67ffiaJUp1EqCxCt8kSpLM0Qhf1tdRlavX2WobGisB+tLkOrtx+VMkRNFOqk1WVo9fZZhmiVo9XbZxmisf2lFIV9YxmiUYZWb7+VorDvLEN0ytCpola3LE9lUStPM0Rhn1tdhlZvPypl6AStrkdun3FcKgp10uoytHr7LEPn6Za6bNf95ONciYiIiIiIiIiIiIiIiIiIiIiIqGvxIjoiIiIiIiIiIiIiIiIiIiIiIiLqWryIrtzdXb59gGWIwvaXWhT2j2Vo/fY7UZTqNEplAaJVniiVpRmisL+tLkOrtw+wDI0Uhf1odRlavX0gGmWImijUSavL0OrtAyxDoVaXo9XbB1iGKGx/KUVh31iGnFaXodXbb6Uo7DvLkBOFMnSqqNUty1NZ1MrTDFHY51aXodXbB6JRhk7Q6nrk9qlUFOqk1WVo9fYBlqHTdEtdtuV+CqVUq8tARERERERERERERERERERERERE1BK8Ex0RERERERERERERERERERERERF1LV5ER0RERERERERERERERERERERERF2LF9ERERERERERERERERERERERERFR1+JFdERERERERERERERERERERERERNS1eBEdERERERERERERERERERERERERdS1eREdERERERERERERERERERERERERdixfRERERERERERERERERERERERERUdfiRXRERERERERERERERERERERERETUtXgRHREREREREREREREREREREREREXUtXkRHREREREREREREREREREREREREXYsX0REREREREREREREREREREREREVHX4kV0RERERERERERERERERERERERE1LV4ER0RERERERERERERERERERERERF1LV5ER0RERERERERERERERERERERERF2LF9ERERERERERERERERERERERERFR1+q4i+g+9KEPKQB88bUUr6ZhHPO1RK+mYQzztUSvpmEM87VEr6ZhDPO1hK+mYAzztYSvpmAM87WEr6ZhHPO1RK+mYQzztUSvpmEM87VEr6ZhDPO1hK+mYAzztYSvpmAM87WEr6ZgDPO1hK9QHXcR3cGDB1tdBKJFYxxTu2MMU7tjDFO7YwxTu2MMU7tjDFMnYBxTu2MMU7tjDFO7YwxTu2MMU7tjDFO7YwxTK3TcRXRERERERERERERERERERERERERE1eJFdERERERERERERERERERERERERNS1eBEdERERERERERERERERERERERERdS1eREdERERERERERERERERERERERERdixfRERERERERERERERERERERERERUdfiRXRERERERERERERERERERERERETUtfRWF6DZMhkbk2kTtqugS4FlSQkJYHLOgSYFYroAlIDluHCUQkLXoEkgbblwXIWYJmBoEqajYDsuErHc3zPW0eUNXWAu68BRCjEpEdMETEdBKQVD1zCYMgAAB+eyyFoOkjENWduF7SrENInh3jh0vf7rG11XYXLOhGk7/vakFA2qwc7RrvVUGsODSQOJRG1NudI6CuslFdcwb7qwHBe6FIhpArYLLE/Eyj5/KGPBctyyGLZtF+OzWX8dqbiGZYniujZNGxNzR9c3lDJgGHrVx6hwG8mYBgCwHHfJj6tlORifzfrlHu6NIxbTyuq3Ny4xm82VZyAZw1TaKtunwn0orcN2jdWFFO5XT1winXVh5eusx5BQANKm69djXJfQJOC4QNZ2IQSgFOAoBSkEYlLA0AVcBegaMJs5+tm+hITtAvOmC5Vf3vt8IiYR04GZ9NHl+5MS02kXMU3AclRg/1x6nPuTEgfnnKr68aBjCgCzpomZtFPUFqSUobFRjYX6jLA4DpPN2jg4f3R9K3oMxONdN5xoSF9MnaETYsG2XRyaN/0xbSImkbGO9ompeK7Pmc/m3pNSQJcCAsiNe00XMSmQigscLuk7vb5sKm3DdJyi/ndZUmI2o9BjCMxmj26vNyFh2UBvTMdk2sQxSYnDBX30MUmJuBar2FctpNa+zLZdzFsmZgrOLd5nguYXR9LuomKhmef+Ws8DnaDW+q20vDeGAxQ0IWC5Co6rYGgSQ/lztvd513XhKPjjYl0KZG3Xb1MAoMlc+xFCwXXhtyfHVYjrErZ7dFyiidw4SCnAVQqalDA0AdNxYTkqN7/Nz3Hnzfx8VgrE821cCsDNf9Zrm5rIjaXMfBl74hJpU8FyXGhSIGVIzOfHZ4YmoUmBtHV0/COl8OsqpkvoUiBtOoHj4KBxMYCOHPfWIyzuCt+PabIoX5GMabAdF7ZSSMQ09Md1TGdsmE7ueCuVe0kpoAlASon+hJ47Do7rx5mUAhnT8WNTl8LPgcS0XI4jY7twC2Ixbbt+zHn9vOUquG4uFkU+3gwpYKvcdhwFWHZunQCQthwk8u97bcBRCrrMbSOT30bSkOiL6Zicz5Vbk7k8jaELZK1cOzM04edZeuMaTFsBUHAV4OTLFNclFAQGkjEcyVqwbNdvwzFNIhETyFoKlusirkkIIfx6ikmBZFxCIJf/cZVCXNdgu7n2kpubSGTso8cmN54vPkcmYrljOFdwHmyXsYTrKhycyyJjOeiNa/n3cn9zXFVUl4YmENOAmawLQ5NH41TXkDQE5vNzwcJ4AXKxl7Gco+8poCc/v/b6WkMXUAr+8db9YwsI5N6PaQK6Jorml/1JidlsrpyuyvXhXuwmDQnTzh0nTQjIfPx546LC4+UdU2/8ZOgS82Yu17e8x8CcZRbNTXNz3fC+sbTfKzyHuAqwXBeaEEgYufjz1tPN/eViBI2DHEcFju/Dxv1B7wMIXDYs/xU0NhUCgctS47X7nM6LK1Fwro/Hjo6tDmeykKI4T7YsKWE5gCaL3/f6ssGkgcm06ec0bVdhIKUV5c76khIagOmAfNpQfttTacs/H8TzY8PCc+OK/PixdNzTn9AxMWcezfUKwMx/zhubLO8xiuYtleZshTo1z9qucVzv8VjMcSzsixO6BISAnf8uYZmhFfXHfUkNvUbwukvbnjevGkoZOJx1cjnvgvmT9z1BxlIQQvjfX3hjAW++2GOIorFGKi5xOO347W5qzkFMSsRjArNZBytSWmA7TMRkfowiYDu5MVFpvmdFjwGlcuesoP3wzjvVxFfp90CGLmFoKMr3dGsemdrXiTc8WfNn9tx84RKUZGmV9qnHxDVMpS0oAHb+PJ7UJVzk+hJv7q9romw+2xuXmMnm8gW6FJBSQKncXFxK+PP8wvmXkc+d6bpAxiwel0AAGdMt6qM0KZE0BByn+LtCr//y5mjePB3I5Ru8+eOc6fjb14UA8nN9tyD/4OUlHBf53JpEf7I4LyOgiq7vGEoZuRxMQN5LCOHnKRxXQQ/Io4Xlzg7Nm0jn58WGJjGQjBVtJ+gc6LoK02kTaTN3vUoipmFFKl53/jPKSvOuhdfjOI7rz/cSugw8/2ZtBwLw86Je7jaZz08dzTsdzT3o+fjPWK5/fZHt5Lbt5UNdV/nxCQX/e5WYFH4bcJTyc7iGJnOBLFCUN4rncwy5bUo/FhL5mCyMsURMwMrnMmz3aG7Y0IWfhxDiaE6wNL6SMYmslcvPxDSJwWQM0xmrKN8thTem0OC4CmY+V1gp/kvjqZ74rCUWGhHDXTVayWRs7J6cw9UPjmH/VBojA0ls3TSKE5bHMZjSsPOtefT36Dg4a+K6x17G/qk0PrhmGH9+4RpMz1v43ZEMto/twxf+8BTc8ZPdmJgx8eUPr8G86fjLjwwksfXSdbjjJ7vx1M5xjAwkcdemUcybDv7ie7/GxGwW93/2LGQtF1c8sAPnvn0Qm85ZjWseesH//LZNozh9ZV9dF9K5rsKuAzO44v4d/vruuXw9TlvZ1xYdXbO0az2FxfApg6mqJ8WV1qHrEr89nMb4TBYxTWBqXmJzyXJP/PP/z96XB0ZRZXv/au01SXc2tkQ22QImkoYYYEZR3kMZUZ4GcCSJAkpAHZnnU9AZh1GH8T0Q+ZxxFJJhHJRNQdCn4qDOIKhPXAOCGjZZNGHJvvVeXVXfH9W30tVVFUhETTTnH0h1LbdunXvuOb+zVWHqpRnY/lkVyt47ifk/H4Cpl2ao9yNrhqEpOC0MqhqDWLChHOMHpaDkisGISDJ8IVF10IbDERyu1Y9naKoDxxv85/xGkYiEQ9WtWLChHGlOCxZfM0yzHmOvuZDCUxBEHKrxGs6j0fzuPliNzeVVKC3y4MmdR1T5sOaWMbg41YGvG/2obAjAzjPwh0X4kyMYkOwATVPdklfPRZGIpOE12kfjjo1tc1ZW5IHTyqLwbx9p5rFPogWtoQjqWsOQZBn3vrhf/X1VYS76ua0ABXzTENJ9gwy3BUerveocux0cVu36CsunX4Kv6/XnD0ixoNEvIhyRQVOAIIo43RJA30QbIhEJX9X7NOujtMiD/ikWNPkl1PqCSHNYDeW4kfxZNzcPSXYWp5v04+iVyGNm2Qed2iPOJTMEQcTJRj+qYnlPEDHAbTcMoAiFIjhSZ7xef0oAyIWQxT3046DuzguSJKPOG0JAEGHjGZxuDqH8RB08A1M177R2zliEIxLmr9fKPLeDgxCWcbymBRzLIi3BAoeFQXVrWKMX3D1pqOZ+ywuy8dyeE7h70lD0SuTwTWPYUD9vEQQk2micrA8ZyFvlHc4n2Ct+/0/gGMPvNjTVAY5jdLqCJMloDoUNZbTZvs9SEhr9Ai7uBC98n3qqmT4zPN35ow2k6+j8tne+JMk4VN2KJ3cewZ1XXoxAnF1YWuTBsHQnvqrz4Yl/HsZtPxuk0V1WTM/GY28cRq03hBXTs2HnGbjsHDiGhigpQSgRScajr1egtjWs03OfmJkDjqXxq0371PW2cNJQzXpZMT0bqQkWrHjjkKp/lhZ58NpnVbh8WC/cv63tfk/NGg0hIuGeLfs1/PCXnUfgsvH41aSLcaoppLs/eYfSIg/sPINb/v6x7ve8AS5cd2mGbi3H6sXr5uYhFJF+dHrv+VJsQJKFoVHnC2vkblmRB/3cVpxpDmHeuk+R5rTg/inD0SvRgpN1fuz4/AxuyO2n4ZGyIg+S7CzONIV0uvPygmwcPduMCUPT4Q9F0OATVH0w2cHh4VcrUOsN4elZo0HTdLtyPZYP1s4eA4qiUNsa0oyFyP45Ewair8sKQZRR2xpCvS+MbeWVmDNhIF7eewo35PbD2vdP4NbxAzX8GfuM1YW5SHHyeO79Eyh77yQy3DY8PWs03A6LAlgyFAKCjAZfGEk2Fo1+AY+9cUh3z1WFuXh9/ylMH3sRwoKIlmBEt4af3HkEta1hLCsYhVBE1mE3Fo7GnLWf6GzRyVnp+NVVQ3Dnxr3qb7sPVePanH6ae5QVecBH79GddIlY2XiTJwM3XZaJgKAkLIUjEupjcDUyVwk2FokWBgFBgl+QsOPAaUzL7YfmoIS6dvjl5b2nMOWSPrgoxQ5RkiBIjMo7e0/WY9a4AWj2C5p5XV2Yi/REHjUtYWzffwq3TBiA6taIbr9zWmgUP/OJbl2MGZhqKuuIXCSya+2csfAFI0iyc/CHRHAshTc/P4uxg1IQTBIhA3j09Qr1/NWFueBZCs+8dxJTLumDAal2VLeEsHzHIdR6QzoM43B1q+kekpbAg6ZohCISQhERvX4CgfAXkgRBxJFar1bWFnuQYGUxa81HGv69OMWBypaAxnbOSLYhEzYdNvDmr8fjuAHGYKY3mh3v67Lgpr9+qBnH0DRHTyDdBabubtOFwxEcqfXhyZ1HdPvcmlvGwGVnwTMUqpr1NtegFIshr5afqMOYganok2RBS1DC2eYghvayo9EnavbuuycNxUXJFhyJwdoyk21IS1AcZq2hiE4fKCvy4M+xuGixB0PSE3C01qvRAUuLPEi0saApoCUo6O6zujAXQVFC3wQrOI5BJCLBJ4QN8cBYzKq7+gTORd2Vj82+x5A05zkDzDtq0xE738rRONsSwvz1xr4EsgYmDEmHSFNgQhR8oSBESQnMIE7nRJ7BkTof/mKw9gj/cgyFqjgcYe2csbCyDKpbAupaWjhpKF77rApXjeiNmhY/BqQl6r7lwVNNeHLXMZQWeeANhnHf1s+xujAXfZIsOGGAmVyUYkFNi4AWfwgpiTa0+AWUn6zX4T2v3T0eVY0hw/dYXeTBsDQHJAnn5K9IRMLplkAMji7DaaXPuSZ7qId66IeneJn68NThKk5A4h/SnBb89hfDcc+W/UhzWrBw0hBcnO4ABRpnmsM6P3KsvUSwq1W7vtLJGWL3LZw0FOkJPM42hTA/Tp4lOzg0BQRERBl3bdLb0ivibP1YWzzW9qcA1HnDGrzjqVmjwdGUDgsg47p1/EDVLk1x8giElWRGbyiCzR9/rbHv47GSeIzOaFxGOFosVmaE8z0xMwfNDl6DIcTvgZIk42S9D9UtQVNNzSGuAAAgAElEQVR/+bn4oLvoSLE2czx/rZuTB78gmsYPEHyU4EorZ+TAytG4a9M+Dc/H2uB2nlH554mZOW0BlAkWbPrwJMreO6nGScgyUNsaAkNTWPjCPs19nBYWkizjrk3a472TLPAGRdwRx78bPvgae47XY3VhLryhCNa+r/BlWoIFoYiEqsYA9p6sx/SxF6ElIODXL3ym4ZkkOwdZlvHAti+QlsDjt7/IAstIONkQRmVDAKlOHok2Di3BCE7W+fHkzqMq1itKkjrOyVnp+M0vRsAbUorBLNtxUIM3S7KMh175EmkJvI53CT8BMOTPsmIPUqOFZToTv3GheZiSZbnDF3VlGjNmjPzpp58a/naq0Y9HXvsSBZ5MuGyK0N1WXomHrhupVAEQJYQjMmavVYTV6EwX7rt6mGbBPT0rF/84cAq5AxTPHc/QWPLKF6hqDKjPyXDbsGRqFuavL1f/XjptFHiWxuNvHsbCSUPUa/55z+WY8+wnuuu3zB+Hvi5bh9+/tjWEG1a9r7vfy3dOQFqCpcP3+7FSJ+fpe9slzPj4VKNfBdAIZbht2FySj35u+3ndu717NAUEFTx8Z9FEPPp6hW69/PYXI1D0zMd4fl4+TjcF0Ndlw81rPlTXzANThqvA7u77JqLomY8Mg0VXF3kwolcCqluDpuMxOv7SneORnmBVj51uCqgBRmXFHizdXmF4TarDgpP1Pnxd71eBnf4pdgxIcXQq8r69eTSSM0umjsTPH9uFyVnpuH/KCNS1htTflk4bheN1Ps1msWJ6NganOUFRFP727leYPuYiMDQFUZKx9dNvcPvlFyPFwXc0KPAH52FAmdODZ1tUXvvXf12hkbsLJg5GioNH7yQrvEEBXzcEULr7GGq9IWy8/TJcsWI31s4eq8rR2Gv6JFnB0hQKSj9ol6fIHAPARcl202/Z4AtrlJXVhbno67YiFJYw0+CaLSX5mPnXD1Fa5EE/lwVuRxuvEqppDeLGVXs01744fxz6uqyG43ihJB8/W75L+5zz3CPOJTOqmwP4psGvUQSfmJmDi5Lt6JWkv/+FkEHfkroED3eBeeihLkLt6ZYmvNAleBjQGxXvLp6IYzU+DEpzoKYlhFC0wlFTQECyncc9Wz7T8fyyGy/BAy99jrJiD17dV4X8wWkY2supWR9me/OSqVlYur3CdL/fXJIPazTzyUzesgyN9ES9nG3vPeMdN7F7SN8kK0RZxlc1vjZdIdkOK89AluUO6Svk+JaSfPTtoFyobQ3hwZcP6Pjq0RuyL7g+3wkeBr4nPj4XD3eWOmoHtHe+IEqYWfYBlkzNMrULCS8QnjezGzPcNjw+IwfJDk4XfLK8IFsBOl76XHf90mmjMOfZTwCYr7el00Yhw23D4q0HsK+yCRluGzbNy8esNVrejdWvYq9fVZgLAKj3htu1fWPHE7u2Upw8WJpWbYbYa9fPzcORGi9Kdx/T2Mnn822+BXU5Ho6XVWbf4tk5eZi99mOkOS3tYhWx67nAk2nKn5vm5aM1IMDGM2pWtj8sIsHKojUoYNrTe3RjaU+uz19fjrWzxwKAKa9sK6/UAccEoF509XDMefaT81ovS6eNQlqCBQlWFoFwBDzLYNmOg4YBp0TvJ8cAYHSmCwsnDcGgNAdoisLZ5qDhXrdiejb6JFlBURSO1/rw5M6j2FfZpP5OeD5+XmL/Jv9fO3usIf4Tu47JsXPolT+4PhErGz/4zVUQJRlBQSlDV9ngN+VfC0ujwRfGPw6cwnWXZqB3ogUBQUJ1SxD1vjBKdx9T5RThl7uuHIK7NinBiI9MG6nhnadn5SLRxqL4mY8N7ahf/vVDrJ09FlaOMZRBz8/Lx88fa7O1Jmel47e/yELRMx+1y3/k/6MzXTp+e3rWaDC0NiFxeUE2Hn/zsPpuG267DAwNjc7hdnB45NUKpCXweOi6kSoYX+cNIcHCovjv+ndcf1ue+u4EtO5oUu4PVG3gB+dhADjbHMB0E+xgQpwNvm3BOJxtCeoCjtOcFrz15RlcldVHrXzhtNC4/qk9hvftqD4ZP47O6JY91D510r7vEjwMAKcb/XhuzwkUjhuo0+2ILKSADvEe0RM3l+TjSLUXw/s4EY5og99vHT8Q7x6uxvWXZmic3SumZ2NwqgNfnmkFYKwPLLvxEgBA7yQrGJqCnWMMcbyl00aplWRi7xO7h3M0hd5JNjT6QwgK0jm/5Y/Vd9IJPu4SPGxk++49WY+ZYy/CNzFBy/2T7RiQ2obhd+Q7xuvZL5TkY9fBs5iVPwAMTaHeG4adZxAURJxuDuJMow+eAam4Y6Oxw53orQ9dN7JdO4/YYLG6H9Eb1r5/AgWeTKQ4eCQ7eGz++GvclNcft/z9Y9N1uW3BOIREGd6ggCQbh19t2qfqDGea9XrUlpJ81HpD6JNkgz8souiZjwxtwPfvv7Ld99hckg/AXIYQ/qr3BXG6MajB0dvb3y4Qftrl7Loe+vHRd1yJrkvwcLxM/b/FV+JMcxBuB48mfxj1vjASrawaTHff1cPUALNwRDLd61e+dUTFhVx2HrWtQY1NTs4l8sfMXn5i5qVw2TnD3zbefhkqG/wavCzeNid6Q2ayDZUNASQ7OLjsPM42B5HitJjar2Rc5N+l00YhLEpYur0CK6Zno1eiVQ1+M3ruuf4mzzHCA5bdeAl8YRFD052GdqDRNbF7YG1rCF+cau4QxtaV4ybOpUvcsOp9w30sFs8ym/91c/Nw75b96v5phvGQ85+dk4fa1iBuXvOR5nyCT2z88GtMG91PxeteKMnH3//vuA57vzmvPwCo35Hw6ZB0J/6wXY/V/+YXI3Ck2quuJ29IwKpdX+HmvP4IixK2lVfi99eNhCjJanGa2HE/PiMHqU4LOIZCk1/AXZv2qliZUSIrwTBqvSEsnTYKT+48isXXDIPTwmr2+nisg8RD0RQM1/vLd04AAFP+JN/xfIPfYvEMiqLw8Ktf6ObujzdcookriSPTB/ykwv1pCoZMwLEUWgIRBMKiGq0JAAsmDlbPBYCqxgDu2rQX6+bmwReNwCbHY6mqMQCXjdP8becZ3PvifiyZmgU7z6jXMDRleH1ElDr1juGIaHi/cETs1P1+rNRd5ykiycb8Ip1/MGx79yBBTYDS/sZovVhYGlWNAUhRZ/Lu+yaq19w7eagaQAcopU+rGgOYd/kgjYJT1RjAHRvKsWX+uHbHM35QCuZdPkgNHlvz7nEVmCckiG1r1mXjDO8VFCQ0BcKobgmqQpkAOy47h2SHsQLQXtSy2bgpEznD0MomeOv4gbg1JqtgeUE2ZGg3k6rGABZtPYAXSvJhZWlcm9NPnT/iyKTQPbMCAKVFVyyv0VE+MQpcXl6QjW3llbjv6mF4/M3D6j2IHDW6prTIgzSnRfN9CE/Fz/H6uXnt8iBRBsixOzbuxZaSfAgm15DjCzaUY0tJPpJssu57BAW9/ElPtJiOQ4pb31WNAQjnuUecS2ZEJFkNoCO/3bNlvwqQdPR+HaXuWh76Qs9DD3VfMpP53YCNUe8Lq3vI6EwXWgIRLHnlCxUkJuADCSA2kqt9XTakOS2Yv75c1Y/j14fZ3kyOk/NJwA0xcCgKaulwM3krQZGF8cYSyQwnwebkPcm18zeUY8nULNS2hnV7yKrCXDz/8ddqBtWK6dlq0LLZum/vuNAJuSBJkiFfSVLn7IP2yIyHqW7Aw52ljtoB7Z0vRr8zsf3a44X21gL5f6qTR2VDQAMiVDUGcP+2A3h2zljD6+18W8Uhs2fYeQbNAUHVp/ZVNiESo0MTirVTY69PsHL4n39U4LafDTrnO/RPsWOmJ0MDGJFAD6Nra1pDWLq9AssLsk2fHwhHUNsK0xaH3U2PMKJ4WWU2F0RvXjI1S4dVPL3rqC7Lc3lBNhKtLPxhYz5maUAGsGzHQcMKGqMzXbDzDNKcFiyZmgWXjUN6gsV0TyBjJ8fin+eycSjwZKpBUOT4/dsOYMnULBUfMePl9AQLyoo96jj+Z8dB3JzXHzxL47k9SvUMWZYNbav1c9t40MiGMNrr0pwWOC0sip7R2m9kHcWuwfgxx/5N/m+G/8SuY3Ksq+uVsbKRVM0ky8+MfxkK0UxrBVd793C1rhpK7PwSfiHVBpZMzdLxzl2b9mLj7ZcZPo/IaJZRWqQY2lpxicUFnkzUeUPtyro0pwVD05147e6fwR3N5l47eyzWvHscW8qr0OATDOU4CbyragyAZylNYDLROcpu8eBsc1CX/CWa6Bv13rDmOQs2lOPF+ePQ5zyTcrtrtYELRbEYMCHCO/HHZAD+sKj7ZhaOhmdgqhqUkOFWkkZv8mRg5b+Oau5xLr3R6Pg/77lcg4l1ddnQHam72/csQ+HanH6oaQm2y88d4T05KjOVlugsGryCJlAuPvg9fs99oSQfdp4BH8WQ4+/f12XTVFwxszftPKNUfRHa1qrRHl5W7EGynYMMmOKBhLqrT+Bc1F352Mj2fXFBPmpaQprzWkMCGv0hpDgVB2hHvmO8nt0/xYaCMZk43RTQBceRRHgSeL9kapZOryR7OkUBS6ZmYUi6E8tuvAQMTYGmKDQFBJTuPgY7z+h0vwUTBxs6qp+elQsrR2P8oBTDb5nmtKDWq6309NSs0QjFBI7G61GCJMMfFiHJsuqjkQz0oXPZq5FzyBBCobCkw9G7K1/2UA/91CgcEVWbv2+SFTQNWDlaLXwRu1eTuAmCSawu8hiu8wGpdk3BFYIxrC7MxenmoBr0Gyt/jOzlNKcFVo5Gc0Aw0VmUwBszW9xIb1gxPRspTiU4eOuCcab2K7kP+dfOM7CDUfWdeDu0PUzA6G/yHCM8oI/Lhlv//jFWzsg572ti90Clnbjxe3UG/+zKRMZtNL+xc2A2/w2+MBZMHKza6mYYDzm/yR+G08JidKYL+yqbNBjYXZv2YtO8fNS0BLFkahZKdx9DX5fVEHsnWB2g5dPVhbmmsRkkqI/w8ZwJA+G2c7DxLO6fMgJHq70YnO4wHHeqk49WipVUjKV3ohXFf//YEGOMxTBcdg73XT0MQUHCoq3GeF7s/N374n4NBhc7DsJPsT7+xdcMQ+9EpbgBx9BIc1owb92n50xyiccz3vzPnxvOndhJn0rH+4V2Y5JkGDKBEJFR2aAER9T7wshwK2BTewvKyjFoCghK+X63FpzKcNvQFBB0f5NFHHuNKMmG17NM5z4NzzKG9+PZnnYOsdRd54mlKWN+6QC42d49YvndbL1IUaWEiT6Tiblf7ySr5h7kt/aCRTmT8XA0haJx/THn2U9w1cp3MOfZT1A0rj/snHZtcAytXt8UEDA5Kx1lxR5sLslHWbEHk7PSwVDQtNciz1+09QACYXMFwMjxPm/dp6j3hU3nUTaZN1k2Dsy9f9uBdoOnQhFJ5yi4c+NeTaur+LF1dTJSxjLcNtP5KfBk4v5tB7Bw0hCV18m3fmx6tu6aBRvKsXDSEN3949dJVaMChJ/vmiDXCNE+8kbXkHVBzjP6HgylvxbtjIOJG3dH1vy5ZIaZM0k0qVJ7IWQQIaLg3LDqfUxYvgs3rHofh6tbdUGDXZEu5Dz0UPcmM5nfDdhYI4sXTBysgrELJg7W7Zd3bNxrKFdrWkNYMHGwqh/beFa3Psz25qaAoK6byVnpuO/qYVi6vQI3/fVDLN1egUafAFBoV95KkqyTJTPLPsBXtT48+PIBHK5uRcgEAMg02Xfu3LgXBZ5M9e9FWw+Apal21317x+Nl+PlQRJJN9YULTe3pLT9W6qgd0N75hD/bswvZmHPasxsJv5gHnxjzmj9GlzV7hj8sot4Xxv3bDmDBxMHIcNsM7VCzdzhZ50OBJ/O83gEA7rzyYg1fpTktECUYXpueoAC1z+05gQQrpzlndKYLa2ePhSQDx2q9OFnvU/WE7qxHGBGRyaMzXSgr9iA9wWI4X+S7GWEVBZ5MVZYDbeuZYBdG95NkYMGGclXfjtepF0wcDJqisPiaNhld/PePsfiaYRid6dLcK9HKYqYnA/6w2C5OkuLgDXk8xcGr72c23iQbpxnHreMHItXJq458C0sjw2031W/JPY3kv9Fet3DSEJ0zkKwjMiayBuPHHPs3+b8Z/uOPs0m7g14ZKxtJezNJVnAEU3nI0KAoStUbrsrqowbQAdr5NeIXM4zOTFdo24tpUxlKx0WNkwB8M/4lAG/x3z/G7//3Cxyt9iIsKnbf7ZcPxExPRrtOGHIvWYaOtxZtPYCQoLf/F209gCQbZzimoCDqnnO+CVdA+5jHT4E4xoR3GL0NHpGMA3SDgqTj4zs2lOM/cjN0+m9n9MlYTKx4XH+dw6yHvj11Z/tekmQIotJq3Ex2dcaWoag2W8YbiqgBdIAWqzPDe0VJhiTLcNt5w/vXtIZ0e/D9U4Yb2oxOC4NEK9vuHj5/fTkOnGrBL//6oaGOEvstu6tP4FzUXflYNLBHKVBq0PJNf/0QS175Av6wCEFs0/M78h3jcWhRAk41Bg2D4wo8meeVsN83yYpGn4Cl2ytw1cp38MBLnwMAlu04hKXbK7D4mmGQZFmn+5EEAaPCHQCF4nH9VYwkdj3cP2W4Ts9v9AmaYgbxehRDU1i0VcERiK5EG+hDhHcEUTL10ZwPfxklQHZXvuyhHvqpkY1nVJs/IkmQDGwVYi/3TbJiydQsDE13YsX0bM0eTUixdyidjFqwoRynm4NYur0C912t7Nex9r+RvUxscjM9R5FxtOa3WFvcSG9YtPUAZFmRQ/W+cLv4Rey//rCo4l9VjQGdTG0PEzD6mzzHCA/4pt6PqsZAh66J3QN5ljF9r87gn12ZyLiN5ip2Dszmst4X1tjqZhhP7Pl3bNyrwS0IVTUGUNMSxPTSD1Q+ZyjKEHu38W1BdLF8auUYw/NFCTo+zky2ISIBhX/7CJNWvoMlr3yBlkAEk7PSdeNmaAWzYaKYzOhMF1iGxsoZORia7kSaUxusRjCMDLcNCVYO9287cF5YB9GjYjG42HHYeAYURSE90YLJWel46PosAEDx3z/Gv/2/d1H4t4/wh/8YhRXTs0FBqYR9qtGP2taQDvMleEaaU0m4dVhYY19dJ+sS/KSC6ERJVieSKKBpTqX6D/nwpbuPYXVhbrvALRGqpbuPIdnBYcX0bPW8DLcSkb2tvFL9e+WMHJTuPqYuvv4pdqwpHoMMtw1r3j2OVdHnkfNLizxId3aufHiKg8eaW8Zo7rfmljFIcfCdnbYfJXXXeXJYaKwu8mj5rcgDh+X8l7KdN76HjdcqGmaZzqIsq+cDQIMvpPJwPDBNU8Cqwlw18C6WCIjOMrRuDa2Yng2WpkyDx2Ip3WlBafR9dlZU41dXDdE44X911RA4LEw7wULmc9Ve5H2602I4j0YZXWTezBxGkiwbBhhYOabDmcpdPSsA0CtjzYGwkv0RMz/EgRi7gQ9ItYOPtqUh39osA2VgmsOQx2OJ/G5haZ0cXlWYG3XCGQducDRlyLdcFAQggIDR93BaGR3vsDSFsChheYH2nqSiVfzYHJbzU1zPJTPMnEmMSQkiK2d8PyvXcXWi3hfGE/88jCVTs7C5JB9LpmbhiX8e7hYOmwshi3vox0Gme2U3COKIlcXx1XKM9OX+KXadzJNlGYPTHJicla4GmMfL1L0n63H3pKG6vXnvyXqsKsyFnafx4LX6bKf5G8ohy2hX3jI0Zej8vX/bASy6ejie+OdhUDDWQZJsnOm+PDjNoXl3jtG/V5s8NpYHdoui31g70E6N0PfJVzKMM8q7Pgd3njpqB7R3PktTasUCt4FdSOy6NbeMwbbySqyckaPjZWInEv3XDOQ62xLU3X/ljBz0dVnVY9vKK1VbNvYZbgeH0t3H1EClP910KfzhiO7cZAen4+flBdl4cudRpDh4lO4+ptNVYt9heUE2lu04qNFTSTblY28cNLz2v7bsx9LtFbh1/EAkWBisKR6DyVnp2HBbHh6fmQMAuGfzZ7jvxf2o94bQFFD0hB9D4IcktYFBFKUNKP6vLft133t5QTbWvHscK6ZnG/KJmUzzhiIo3X3M8H6BsHnGLuGXtASL6mQcnenCkqlZ4BgaK2bkqKD38oJsPPp6BUquGAy3g0Oqkzd83rbySvRKtGDt7LGqnCX3SHbw6vttK6/U8cuqwlws23FQJ+/tFha3jh+IOc9+gumlH+BEnc9wDdV5w+o9zd43fq8bkGockEeAxNIiD1KdSoBA/BxvK69U9w3y29ZPv9HtJX+5eTQykm26fSTR1rX1yhQHj7JiRV40BwS8XXEGHEuBZyn0c1t137+s2AOOofDK3ip1H5ZNbOcUB6/yS7KjLQDDDKPjaMpwj7bzNFYX5iIQjiAiiYb7dUQSNceSHbwp/5G207FtjJa88gUmrXwnKqPCuOuqi8/phFlVmKvBJ2JtXzM8gWeM9SFLnEMjw23rUAW5C1VtIFaeGYHbXZUYynheY+1kcqw9TNk4uBPgownSPENj0TXDkWA1xx7Mjsc7L+MxsR769tSd7ft6X1ithpWeYMG6uXmq0yzDbUNZkQc0bY4Fmx1/u+JMtL2TbOosS3Hw4E1wMy5aPbG2NWS4xuS4jJ2qxgB6JVp0NuPOimoIIvDo6xV4atZorJ09FkPSnaZ7M3EokqB4I8yqu/oEzkXdlY+NdAGzoOXYpLKOfMd4HDrWFxhLhI9igzjMdA+7hdUFly7aekBNMly09YBaQTRWvvvDoqJfG+0nolLJjWcpHYbSK9GiG297a5NgEUumZkGUZDAUhbVzxuLtijM6PiF7kIVljH00DH1e/GWU1HAhceQe6qEe+u6IyF0FA2UQEY3120FpDiRG8dQjNV6wNI1HX6/Q2U5Pz8pFRDKu+Ez2a1I0Y3lBNvaerMe6uXkQJQlPz9LqxBel2NXYDSPfWSAcAUND9REDWlvczPYPRxOPSncfg9vB6XRxYo8+PUuJ94jF1sg5jf6w5rpt5ZUambetvNJ0XOQepUUeHQ5RWuTBkzuPquOLxxKfmJmjwxDi98AUB4/+KXadXO8s/tmViYzbyI7vn2xXv4EZLratvFLd71fOyEGyg1PPf2Jmju78WHyVYKKEMtw2FZdMc1oQjkim9iJLU+qzYvnUG4oYnh8brEeOAZQuyH7BhnI8MGWEbj938Ax4lgIoYNd9V+Cx6Zfg5jUftpss6w+LKCvywMJS7QZ1kuMrpmfDaWUxOSsddd6whv8z3Err3OqWEGaWfYD/2rwfD0wZgUafoC/osKEcLE3jTEuo3eRpUkWTYKm1rcZdBTrrU/lJtXPlWRoPX5+FBp/CaDyj/M3FOCv2VTbBG4rg8Rk56OeyorTIo2uH8tyeE3joupH48y8vhZVjwNDA5pJ8iDJgZWnwLIWHrhuJB6/NwpnmIJbtOIRabwhlRR70cVnhsikC56U7xyMkSLBxNDaX5CMiKWUK050WsJ1wuAEATVMY1isBL9854UfR1ua7ou46T+EIkOpk8UJJvmIA0RQYWkY4cv73aAmK2H2wGpvm5UOWZVCUAmRPH5OBNbeMUZ1RxPCJFTgZbiW45i87j+D3140EADz8agWWFYzCs3PyYOMVY4sIvOfeP4FZ4waAZyisLvJo2rSsjjoVTzcH8Ngbh9X2QE0BAY+9cRh//uWl5yXsWJbG8F4J2DJ/HCRZxi+jJczJ+Xdu3IuX7hwPK8cYvk97RhsxsuOv4VkGHMdgeLpTXbssTSHdaUGtL4zJWem6ntsMRcEVzcDUjYFlcPdVQzR9xFcX5oJnKUQk2vAa1uT7dPWsAKBNqSG8JkrAY28cxmNRBWb8oBQsmDgYDb4w6n1hPPN/x7H4mmGwcQx84QjKij0Y2suJ4meUMrNG80ABeHHBOIQjEmiKggwZQUFSzyXynGMohCIS7DyNZ+fkgaYQrSAlQZJkDT8TJYAA4YlWFkunjYKdV7I6Eq0sTje3ncfQlKFM8YUk/GXnEQ3PkzZCz+05oTn+3J4T+P11IzVjs7AUEq3np7ieS2ZQFLC8oK2aH5kXszZ+QUE/9r/sPIKHovKgI/R9tiu80HQhZHEP/TjIdK/s4voEEHV+F3kwf0O5auiQwG4jfbk5ENbt1Q9eOwKVDQHcPWkoyk/UYVTfRPjCIpIdPDbNuwwRUdFtSSsUoG1vfn5ePkKRCPzRNu1me35Na9BQ3oqyrAYrG13rD4u4dfxAUzknQ1arusR/v8qGAOY8+0mMkwdIsnHwC6JOHouysTxoDYpIT7CYtoxvj1jGZO/vZKXq9shiouvEO+V/TNRRO6C982maxnN7TiiVOCgKfV02bLjtMtAU1PLzLEtjWK8EPHqDssdtLslHKCKBoSnwLI3/d1MOWJoGBWW9ZCbbdPrHqsJcUIBqp/ZOsuJErQ/LdhzCkHQn1s3NU/Wm7ftPYePtlwFQ2iaebQ7ikVcrsK+yCRluG1KcPJoDAu7atA9pTguWThuF/il2MDSF/3zhMyX7OLremgICHn/zMGq9IaQlWFDrDeHxNw9j6bRRGJBqR2swgmQ7hwemDFfP3VfZhN9EwZqqxoAmm7K2VZEjKQ4eLjuPRS/ux77KJgBKBYoX54+D08oYtiR9/M3DbS3nHd23zQSh+JYDk7PS8eC1WSj820eoagygqlGxkZZOG4VBaQ4cr/Wp3+LuSReDpSmsLszV2A8k2Ch+PQMyFk4agj5JNmwuyQdDU6AABKN8GAt4xV/bK9GqZpGatUD1hiJ47A3l2z94bRYeebUCaQk8Hr5+JJ6flw8ZiuNOkmX8fmoWGv2Crh1iqpOHlaOxYOJg2HgGv/1FFhgaWDt7LADAyjGgIOOtihrNPFY1BkBBW8HkyZ1HdWtodaEC4ts4Fpvm5asB1vq5AtbPzVNbSJxpDhqel56grB1JVirtLLvxEvR12VDdEsT62/JQ7w0jKIiQZRnr5+YpewZH4ZeX9QdNU6oNKckyvMEI3j9So9rnLE3BbqERCAMJ1gvLdxeSaJpCn/1z2nsAACAASURBVCQrHp+RA5edw9hBqdhVcRbXj+4HK0sjwcqpeyNNUdhZcQa5A1KwubwKywuUgMLi8QMN57d3khWNvjBKLh8MG0+ruBwBvWO/bWmRBxKA1/efwtrZY9W2l+T+kizDYWHxh9e+xL2Th2rG5LTQECSo30ORyxQWThqKJ6M2T4qDR4qTR0tAwANThiPFqQSrGrU7WbT1AJ6fl4/MZJuqY8WOM8nG4tk5eeBYCsEoBkkAX3KvtbPHGs5JMCIZ4iYro6B+7HqKTx5rj2w8g7Wzx6oyv3T3MdR6Qx3CFbpzS1izef3TLy/V6J52noGVpbH4mmE6fIBUDIrFgPaerEejTy/rEi0sLCyl0SdFSWm1lxjlD3KcZaBrN1zV2NMC77ug7mzfU5DValiE156elYtf/9tQuGwcOIbGM+8dw60TBiLJxuL5efmQZFnFyQKChN0HqzVyUJQk9E9NgI1n0OgTTHWEtAQLGFrWybvVRR60BAUkWDkEBREv79XK5zXvHsfMsZma98hw21Ddoq1Od+fGvVg6bRQiooTa1jBCgoQlr3xhigPGVoYZmOrAa7+agNPNQR1m1V19Auei7srHRti7WUB5rEzsyHeMx6GlaJtTMz56++BZ1Y9hpHssL8gGBWMMg1RiqWoMIMHKYUt5Fdz2trVHUUp1NqP9hLQ/9of1FU5P1vl14zV7B5edByDhbEtIIxuemJmDYX2SkGhlVD5haaX9rJ2nkWjlcM/mz3R74pM3jwZAn5O/+GihhNj36iiOLEW7uvyY1mYP9VB3ICEiqTbOgg3leH5evqm9TDALYmfXtobx+JtafZplKLUbAWkBS7r0EVle1agkMVs5Gkm2DLXN++SsdGy8/TK0BCNo9ofV5JZ9lU3qc1IcPJJsHFa8eQg35/VHnTeMJ3ceVfETmqLAMsCmeflAtBpW/LucaVL+3lfZhFW7vsLD14/ExtsvQ5NfgJ1nEBYlPHhtFmwcjSVTR4KhgYdf/VLF1tbcMga9Ei2QJFnVowRRxo4Dp1WczcYxSHNa1L2KoijwjIIHiJIMNhoPQtOUZj+jaRm13pA6vmU7DuHxGTnok2RVbFaGhtvGtbsH0jSFASkOuOxcW/wKRyPVYekU/tmViYyb4K5b5o+DLMvq+EVRUr+RjWPw/Lx8VLcEUe8L47k9J7Bw0lDYOBrPz8sHQyuJVlvmj4MgSrCxSvzOmWblfIJ7Zrht6JNkhT8cUb9VLH4Zi5+tmJ5tYnMrsUl/uulS9Eq0qnxa0xoy5Nm6Vm2r+wy3TVM9l1BVYwAUBY09289tQ02rti38iunZSHNaVAxy0dYDWDptlOoTIXif28Hhm4aAGlgY72d5elYuWIbC2tljsXjrAdR6Q9h4+2VIsLJItGj5VIaMW1btUZ/ZHBBMkwJSnTyKo3KBHItv8cqzDBZOGqKOxxeKXFBf3U8qiI6m2kpBxzKJhaMxON2hOh8EUQJDAUu3V+CuKy/GxtsvQ21rSF1Q9/z7MPRJaj+702VXlD47z+KpWaMNhU36d4SI0jTVbo/gHlKoO84TzwJ1XgmVDQFV+GUm25DqPH+Ak6UpbC6vwsp/HVWPZbhtuNGTodkgaROnM00Bb1XU4LfXKiU2a70hMDSNRCsLWVYyuTRgI8egORBBqlMB0QVRKWXutrNgWaUSXa03hPnryzXjMQtMMHIgsyyNvi4bTjX6DYWtEJHQJ8mmMZiJopPajnM73sgm15DIe45j0M9t11yTaudw96ShuoBBG0/DxjOG9yOZZppI6417sbkkHw4Lg1WFuWpVPuJItVvodsfWlSleGaMoCrXeEBZvPYCnZo0GTVGq0kz4bu37SvCyLyhi6fYKrJyRg6pGJQPl6Vm5ag93cv6jr1dg0dXD0eALq4GMD0wZoQtQ+93UkVi35wQKxmTiVKNf5dtUJw+HRYbTog3ccFoUPrdwNCycdt1xLA1JVjKASSCo06rfZgVRwlsVNRon4ExPBu6adDF+ddUQzbdeUzwGvROsaAwInVJcXVYW3zQJOplxkYvwPWUYuPfw9aMM7ydKsm7sAPC7qDzoCBm1bLh/2wFsmT+uw/f6voljgBafXhanOH68QSc9ZExWjtYFMawuzO0WWbU0TSHVyWPJ1Cz0TbKqe42Vow31ZYeF1e3VKQ4ej75+UDWObooGshNncbKDg2CSvRiOSPCFRFAUjVoT4xAUhaAgIcHKaa7nWRqCJMNhY+ALSYbX2nkGd21S9lIjObfo6uFYvPWATtdZMT0bj71xWB3noq0HsLkkHxzHIMNl1wG6AHCy3oev630aeZDs4OFydQ5oSHda8OycsToZ09lK1e3RuXSdHyt11A4wOz/FweOefx92zsABcr0kyajzhSDKSlCRjaPR4Atj/vqPkea04Le/GI417x3HnAkDsf62PNCUUnHxD699ibcqalQeXfX2V5g2uh9qvSHsq2xCUyCMB69VqoP9fGi6kg276ytdsPqqwlzUtYZxz5bPVMCCgCNrZ49FrTeEx944jPuuHqa23SDr2WllsG5uHgBFH1i96xj2HK9XARZCGW6l4ldZsQfz15drsin3VTapcmRzSb4aQAdEdXZJwummIO4zaEu0ZGoW5q8vV6tImyW7iNE2z10d5IuvpPdWRQ0evDZL8z77Kpsw59lP8MpdEzA4zaHiCjJk3LhqD9KcFlW2pTgt2Pzx1zqZ9vfZYyCIMpa88pmGRzmGwuy1n2B1Ya6aKBh/7arCXABtbajMWqAumZqlgog0RalBlXdt3IdabwjPzc1DQzAMISLBG2rbX8g9Fm09gGU3XoIHXvo0GgDEYNWur1DgycTS7UpW+9Gzzfj3kX2Mk2co6ObtsTcOY/3cPNS0hhRn3dtHUeDJVPlvcla6oQ1x75b96rssmZqlZh7fs2W/5rz/2XEQt/1sEB565UvUekNYMjULR2u8WLq9QglO/Y9R+M/Nn2muefxNJTCnxS8gNYEHR1Go97aNraYliLQEC5r8AvxhCm5715fDLpvivJi15iOkOS1YOGkImvwRhCMibDyr4mjbyivx60lDVWA1KIiYPuYi/OvLM4a27pP/Ooot5VUA2rKm/3TTpUh1WmDhaGyJAuA0TaHeG4I3KGBqTj/MefYTjdwisvP1hT/DreMH4rbntMG5Q3o5UN0S1truhbmQZBm3jBsAK8egd5IVzf4w7tq0TxPkZlbRQJZlOHgGyQ4eL905HkJEggwlIEAQZVhYGhs+OIGPTzZh5Ywc+MPiOYNAV0zPxtnmoCFuQlOUxl7tlWiF23Z++5skyahuCel0vl6J1g7pAWaVQWPB7a5KXDt4VDyJJpWRXr97vA4DKi3y4M87j+jOfaEkH0FBQoMvpH4zoi8//+HXmD7mIoCiIMsynv/wG9wyfqBmDBnunhZ43wWdGzfpuhSKSLpqWHdt2ot1c/PA0govXT6sF8IRGf/9jwpdwu/vp47Eyn8dxdA+idhWXqn+HhYldS82C2D2BiMAZCQ7eU0AKMcALYEIkh08zjYHcUOuVj4rcsaiCwA2qk53UbIdHEtj4aQhqm5q5Lwj+yygrJMTdT7wLI3S3cewr7JJh1l1R5/Auai78rGRPUoCJnQO0LiM3/P9jvE4tNJ5xGoYHPfcnhO4dfxAJFoZNfiTZSjVIU9RFBhKaV3aXjBnhlvBBDaX5MMfFhEQIggJEoKChD4uq+F+sqUk39Qh/uTOo7piH/3c+gIgqwtz0egLo1eiBbPXfqR5xj1b9mPJ1CzcvOId9b7vLJoIXygCh4VFRJIN90QLR8PCALUGPqm0GJ+ULOtx9I7gyN05KL+Heqi7E8FXiI1DQV9c4ulZuXj09QodHkAwISI7MtxKtamwKKKsKBctwYjmPiujFe1rvSHIAL6uV6rnr5yRowYYFf7to7b7/nyAKuv2VTapGMGKNw/hV1cNgSzLeDiaOErwrfW35eHmNW1BefGyUqn0dkQd763jB+LhV7/EI9ePRHqCBWFRAkVReHXfKVw+LA0NPgGpTh6LrxmhBNbxjCYY7VSjH//5wmdYMHEw8galoCkg4N4t+/HUrNFgWfq89qrYcyRJm6RQ6w1BlGT85wuf4alZo5GeqMSWpHHt+6JomlKSux3nzwvdVUdqb9w0rfXjS5IMK8egT5IVuRdlw23jVP8rx+j9r5GIhEa/NmllVWEuHnntS9S2hqOJxg5wjILf7qtsUlqxb1OqO9IUpbO5nRYWpxqDWPt+NDGbprBubh6W7ThoqHs/MTNHU6SHHONNEvEBoH+KkvxMEj4JRgW06R4EayXHLkq2Y3NJPpoCAn4fxbvWzc1Tu3Iu2npATa7un2LH6aaAGlwai/OyhPeg5e34GI6a1pDpO5h1F4xNnnbbOAxKc6jnMdGORkaJb52hn1QQXViUDBXUrQvGoTUYwfz15SrwNzDVgYevHwWGAliWgo2zo3eSFcN7Z8F2DsFEqLsKmx7quhQQJDgsDIb0csZk/SjHXee+HIACEsY7Ap6YmQOOoTU8e7rJj3cPV+uyuQemKtniPEPjnUUT1QpsHMfgVKMfD79agQUTB8MOJVq/3htCvU/QgRsJFmXnJu1Y45WYBBtjGJhgbyerur3KcTRNYUiaE1vmj0NElDRR/mbUmcj75pCoyxa7Y0O5CiC7bLzuflVNxsF/ogz4QiI2fPC1Lmvz1/82pFtmBRCK5bVYpdAbjOCBlz43dJyKkqwqjiQTdl9lE+ho6woCBJJsgJLLB+Omv36oBjKGRVGj6CwvyEZr1OEiRGRcnO5UK2V4Q4JSMS7q1CL8/Je3j+LRG7KRaOXRGowgM9kOjqFwvNaH+7d+rioJRFEJhEWdkmpURXDP8Xql2l6ikg1IFLnUKI92di9hWQaJNlYjM3iWAhutLJDutOiqvbTXUpwzUWi4TlRHMsssjQdOuyKFIjJ4lsLF6U41EEKGhFCk64+9hy4ssTTQK8miycblWQqdLCj8vRNN06pcJC36Up1WXeU4Ulkl1lBbVZiL1VGnBABNueyqxoCauWhmCFk5GhJYbPn4axSMydQZOH+5eTQYSqmAKcsyhvZyqtURFMemjAQLj2A4aOhECQpKlSoLS+vk3OoiD7Z++o0ui7F3khV3b9qnC+whVXDN5PFFbjusHANBlNSWtuK3KKpJ0xSEiKwxsNcUj/lO9vjummXYVagj82fmFBiS6sDG2y+DJMsofkYB+YiTIcNtw+MzclDgycRtPxuE9AQL/mvLfgCKk+LZOWOVYDyeAU1RkGwyGnxhvHe4FouvGQGOofBCST5oSnGytgQEtYpSLFU1KqAlWUuxgAhDU3j67a9QPK4/WoIRzVpbOSMHdp7RyIanZ41GssMCioJa9cxIBvjD2opxGW4bLIwCLhqNj7TPJEHKpJXk/PXaoJg/vl6BR2/I7vJ2uFElPdrEYZjiVNqlEZCWgE5VjQEV7JrpycAt4wdoqmclO3g0+MI6oGzeuk+xdNooVDUGcLo5qDrNE60s1s4eq7SZcvI40xRERJSx4s1DWF6QrWkrSCj226wu8sAXFjQBmEQeP/JqBRZfM0wDbsXeIzPZjvW35eFscxCrdn2FX08aCreDU/l3QIod6wwC/UqLPLAbVByv9YZwpMarcQKWXD5YndNbxw/EPw6cwrq5efCFRTh4Bst2HFQD6J65dQxagxE8MGU4IpKMLSX5EKOVe8KihEVXD8ead4+r+4XLxuGZ/zuuBoQlxFRQja3oCCgVJe/YuDcaODtCzWqXJECQJPAsja2ffoNbJwz6Vjz2fVC8DORYGpCBWkGELCtgaa9EK5J/Phh2nkZNq1JlvMCTiRQHjyuG9cInJ+pVW1eGolvtOV4PoC2A7uW9p1DgyUDRM0qwHqmYSxy0SoKTkjkejkg40xzApyfq8OC1WSi5fDB4hjYMqF8ydaTedo8GhhLnjCzL8IclbLjtMrVa9xMzc+ANGVd/oWkKgiSDlaCuWUmS0RQIIxAWEZFk5A5Iwccn2yoKGAWBEpuQY2jwHIVIRF/taXlBNp7/6CRunTBIk2l/vnu4UfDboq0H8NKd43+QlrA/BBnhUauLPHi5vApD+ySqOMDDr1aYdktoDekrBi3YUI4lU7M0QQNVjUr1o3jM7OFXK/B04WhcPqyXJtCIVIiP3WNJ+80eurB0LtykK5NZe6jWYERNRHr3cDVunTDQMOH3XxVnACitwuKrzZLkolpvCDaeUSt4AADPKBW5a1uDqGkJIdHKQZRlNPkVrM5lV/DqtAQLip75SCdn/nTTpYZVzmMpw22DJMtgaWjaq8facMN7J4AC8MfX26ouk4A6EuS+dHtFpzCr7kbdlY+N7ClBFDvUNeN8n0Psg0hEgl9QqrK8UJKPloAAp5UDBRmLrh6OrZ9+g/zBaZpKLH1dVrjt1rakOoOqa2TNkPGyNNA7yYrKBj/qvWHQFKUGlxr7AWSsLvKgzhs21G2THZyqq6c6lWD3FAetzh2AaCcW2dTxTCrlAQTPpfDu4VrMHJsJjqV1usaaYqUAgShKSLTJOv6yc233o2lah6PLMK7+bLQmu3NQfg/1UHcnEtB8NlqJvbIxgGQHh2fn5IFlKEREGRFRNKwMT1qRxtrorUEBT+/6Cr+bmoX5G7TFQ+59cT+WThuldDH58CSm5vTDPVu+0Mj7x988jEFpDtX/bONprJubh9ZgRFMlzs4zKFlXrsNxGYpSz0928JAhq9XfKIqCLyRgydQs/PrfhoJnlGTyB6/NQqrDAoahUecLgRJEFHgyYOFopDot7VZy41nGMAi5s13DaJpCH5fVEFPoDp3IujoZ4ftG+0xsddT0BAteumM8AoKI47U+bPjgazX5xB8W4bAwYChg4aShqDjTqgakrpieDX9Y1ASJkkTSVz87rSuqUlrkAcdQaPCF8bdbPHBaObVy7D+/PKMkFyZY1GSZoGCsMzE0hT9ur8BdVw7RVH+MJSO9gGUoDaa3OlpRX5SBJCuH9bflgQKFsy1BNQmVXBubSGDGp/ExHKW7j+Hh67N0OtXKGTmqPCJ+qwUTB6vJftXNAXAsjeqWkOY8mqKwbMchg6q6l3aGVX5aQXSiJGuytQnDRiQZ89eXY/ygFBTm99dkI5cVK1U0Ttb5NR+wJwuih34I4mkap5uDusCyvknnX9Uw2c6jJShosoLcDh7JcZnuPEPrsrlXF+aCY2isLvLgrS9O4+HthzTrgaIopCVo79MUiBgC1o/ekA1A2441Nrit3hcCF9fmIiKJCAnmXun2qqlIkoyjtd4OZzN1NICJ9OCOlzPEmDW6X3utZilQ2HO8Xs3EJ78tYof/aAJ1Y5XCvi6b4fylOHiIcpsM75tkVatHnG4OqkEghDLcShug3YsmgqaUVtu/+98vdHz40HUjIclKq9cNH5xA8fiB4FgaDQ0C1r5/RFfBhfATTVPoF61IJIgieJbWle2lacBh0SsLFpY2rLgAQM0iuVDUHAyhujmkkxkcQ8Fttyot5gzaEpu1FE918IatmVM7UbHIzFFMfRtU7HsihqbQ3BrRzWvvpJ+UWtVDAAQRaPYLqGoMqntqhtvaLarHANp9k2Tzbbj9MkM5LMuy0kYy0YoTdT489MqXGkMpKIgoK/ZorqEpoFeiVRfoUlbsAcdSkEISZoztD4dFaR1CghEbfWE4rSzqvG3VUSZnpeOBKSNAUYCF1rfTjJfvBZ5MZLhtCIuyTs6l2HhMvTQDr39RjSHpTgxOc4JjlPaGeQNcGvBFMSDNnS5G+gXJYL/n34d1yl6o84Uwb30ceLz+U7x05/jvpJL1j0Wf+KGIpimkOHgVWKn3hQ2DGMycAptuvwyPvl6BxdcMNwQ0KADz15djdKYLj03Pxh9vGIWIKGts1tVFHvxl5xG8VVGDyVnpWDhpKGavbavq+6ebLoUgKi3u3Q7KsI1Ak19Q218MSLWDpiicbgqoztMpl/RRf78oxY4zTQEs23EIALDsxkuQmWwHQwPN/ogaiEuAj6dnjVarOBF9SqkAYdMck2Tgm3p9qyISdEecOGTeUx28YSLFQ9d1/cANo+QfloFOR1wxPRt3b1IquhHbJf7a0Zku3JDbDylODouvGQGaUnSV2tYQkqNzVBoT9FzVqFSQAIyd5itn5KDeG4KVo/E/Ow7i1vED1QqeRt+mn1tpE8uzNB58+XOdPH5gygjUekO4ec1Hpq0qKQCJNhYUbLg5rz9+979faN75THMAZe+dVAKPbrwEfVw2fFPvx5L//QJpCXr9NLaqKHlGko3Dy3eOh9PCIiwq+8+9W/armbVLpo5EyeWDIYhKwGls0tmzc8ai3hvWBQgerfGi1htCP5cVi68ZAZYGnpubB4YGUhMscRXOPKApCou2HlBb2pCWy1ae0Zy7ckYOmK6vEgNo20MiEQk13hAAGZChBk0QW4djaTzzf8d19tXqwlzUeUNq54hkB6fykCBKsPEMbvRkqHNPQOj4TG4A2H2oEkXjBiIz2Y4+Lhte3XcKQ/skoo/LaghO+8IRQ51nSLoTS6Zm4bk9J/CbKSPQ4A9jzXvH8NB1I/HIa1/izisvhhOUju/Kij1Yv+cEyt47iclZ6fjdtVlgaCXQubolpNMVXtl3CpJBe6FabwiSJCPDbdfsJSkOCzbdfhlq4jpl9E60dgqbNMMuhEjHMgHaS2bs6kTTlNpml+BOPEvh89PNuu4NRslwGW6bKdYcX82PBA3EY2ZpCTwoswrx143UtX4Vuv4W1+3oXLhJVyYzvnTZORULve7SDMws+xDjB6UoLaUZCixNgaJkjO6fggy3kqD63J4T2HT7ZQCA081ByLKsVpddtesr/P66kSj820dYXpANl51Dko3D6t3HUODJRFCQ2qrbXTcSFpZBRJLQHBAM1wcAnaM5PUFbna60yIMVbx7C3VcNQZKd07wnsV1fumM8Up0WPHTdSNwx8WI4LSyCgogFEwer67CzmFV3o+7Mx/H26KlGv6FMNGsB2lFiWRp9Eqyo8YbARQNCZ8XYL6uLPEh1cnj73itUf4QsQ5MQNTkrHYuvGY6l00YhM1mpxB27ZojvQ4aEdR+cVB3tFAUEBeNAfIamwTNAksuqC2Z7YmaOWuV5dZEH3zT4sfZ9pZNIX5fyfaubAzjTEkKjT8CAmKCW2GeQRCbynjxD44rh6eA5CklWHk1+rc/IEk1g8gqCOX9FC44YVWlff9vY88aRz+VT6aEe6qHvlnolWpBs51Ba5MFrn1Vhak4//OXtg5gzYSB6J1nBMUpL5+U7DqnYwuSsdPAsjY23XwaGosBEjVghIqnYRPya3lfZhMxkG0IRCbkDUnQduu7fprSUFCVZtddXzsiBy86iwRdGUFDkE59MgxYo1SdHiCQ2WWgKrmQbqptDeOJfh3V26No5YwFA4/9eNzcPoYikkWOxSQVmnc2+iy4fLpuS7P1T6xzSVcgoEZqsjatG9FZ99mSPbgkImL32E6Q5LXh8Rg76umyYnJUOp4XFoq3aDgiPv3kYHENjUlYvFaMA2pKx1t+Wh8xkG5r9EfwyputPWbEHCVYWx2rauuEM6+00TRi8Oa8/Hn71S6Ql8Hjw2qxz6gVPzMwBE8W0KCj2Z6qTg8uu8PypRj+ufPwdtVVtrD88NpGgPT6NXyu13hASrBwykm2q7+ZMcxDLdhxCWgKPVYW5eOrto7r1u7wgGzxD454tnyHNaVEDCZsCAvIGuDAo1QGGVpIX8ga4QHfS50x1h4ovHaExY8bIn376qeFvNS1BHKv16jJE+rls+PULn2HlzBy1hSChDLcNz8/L11TkIMdJFkRsNGpP9YYfNX1vH9WMj081+tVWaYQyok6L+Lai7REBuGOD1uKDZs40BzCj9APDZz3y2pd4YMoIXLXyHfX4y3dOAAVFwMUaVGtnj0FYlDXO8/MJXjvdFMDMMv3zt8wfh74um+bc2DVo4xml/3xE0qzH2tYQblj1vuk6NqOOru8GXwiHz7bq5Myw3glq+VKjZ5iVKwdwIUuZ/+A8bEZkDrzBCCKSpJu//il2tAQENPoF9TcSUMExFJoDEV0/95f3nsKUS/pgUJoDzdEo+HjHSaqTR/7/vK3+PTTNgRpfWFVOYiPc+yRZDVt517aG8ODLB3RtMW7O649hvRN0/FrbGsLr+6twVVYftRXA2xVncG1OxgUPYjiXzOhoqXyzd+1MxZfTTX6cqPPrlJ9BqXb0cZnKsy7BwxdKFvdQ96fq5gCO1/l0MmtQqgO9kmxGl3QJHo4lSZJxtiWI1qAAh4UFS1M4YfBOaQkW+EIint6lN1xWFeZClmVNkEzs3tfgC+FItRepTh4MRSmGniCqVbcIZbiVTHBAcQhNN9BDXijJR0ZcCfZ4ORbbhmVIugP1PkHze1mxB6/uq8IvsvuCpmkdoLv9syqUvXcSGW4b/vzLSzEw1WG6h5vpF6TqQWeypisbfPj5Y7t1x99bfCUyky+8jOmELfO98HFHdYkfgkh7Vn9IxIk6H57ceVQT+BM7j6ca/ZiwfJfuHlsXjMOjrx/EY9OzVfCOUIbbhqXTRuHJnUfVQCfCW0Y8N399OTbclqep6kt+X3bjJVj3wUldZUbSRiDJzqHRJyDByoKhgeO1fk1wsI1jEIooLe1Ji8TY+6+fmwdRhhq8F/9sQZQxON0JG9fWCjme7840B/CrTft0QV2lRR70cVngtmkzfjur36ML8LCR7HqhJB9/eO1L3DJuADKT7Theq/AUAFUf7etSWjvHBu+unT0Wz3/8tVphJs1pweJrhunaU5EgQ8JXpA3v6EwXFk4agouS7fiq1qsC25Oz0tXq/KIMMBRQ5wub2nVG70R08klZveCycXBaWMiAhgeJzP7jDZcAUByLpMKiy6a35cqKPbo1MDkrXXWsciytAphG70/o3cVXgqEAiqLAMxQ+P9UCe7QNZ/xaXDt7rKYNLdC2Pvu5rRAissbRubrIg/ITdZgwJF2p1MHQEGUJxUKTfwAAIABJREFUgihj0YsHNDxudm8juzeGupQ+EYlIOFTdqlbfMpJRL5Tk48vTLYa/EX4kwO1//6PNMTP/5wMwK38ArlixGwCw694rUGyC29EUcLopiP/+x0FNoD8JJCXrKD3Rio0fnMDcnw0y1OMAYNHWAxqHSWmRBykODsfr/Jpg/UQrB1mWcfBsq1rVsXT3MTwwZbga+Pfi/HHwhiK64OXn512Gs81KwGoshkLWhJGNdSHxx85gF0bUyfZrXYKHzfaRdXPzVHyYfJPhvZ040xzSV3FPsBhizf1T7JhZ1ub0+PMvL0Wm247mQBjxCThJNh5f1/t0HSP6uKz42fLdmrHF68I99O2pk/Z9l+DhmpYAzraEdFhXnyQLUpxWUx4ncndyVjoevDYLLE2pMqXRH8LpJn0Cd1oCj/1VLdhWXok5EwYiw21HRJJwss6v6sCrC3Nh4xlYOQY8QyMsiqhsCOjWx4AUO2aUaZ2CQ9OcaApGVPkW21rrkde+1NmgpUUe2HkGA1IcaAqEDeVZX5cNj3aTKsXfljrBx12Ch42oyR9CZUNAx4OZyTbVkfttiOxbT/zzMBZdPRzNAQH1vrCqA8faVkDbPMbPb6yubKYjN/hCaPS3yf0+LisafWH4w6KGX8uKPEhx8ioGEo9HWzkaLUERJ2NsztIiD4b3SlB9OrGYbd8kKyQZmsSrJ2bmICIplZUJnvvwdSMx868fRhNiGFPbKhwRz4u/JEnGmeYAzjQHUe8Lw8EzmiDC9nDkTuolP7hd10M/fhrwwOsdvubksmvP99QfnIfjdfnJWen4/XUj8Ydo8lAgTl4Rey0tgddVuV1VmIt3DtVg3MWp+Ou7x3DXlUM0cojYOTfn9cegNAdqW0OYXvqBbky77puIutYQIpKEx944jIWThmBQmgMRSYY/FIGVY7D1029QNG4Aqhr1esbgNCfSE9v0ICMb1cgON7PNyZ7QHt70XcSJkHtKkgRRRqeqj38P9IPz8Lclo29X7wub4v2JVhZBQVLt+0Qrq+mCWVbswbbySvxmyghD7GLptFEIixLSEyy4YdUe3XjeXTQRMoDCv32ku3b9bXmqP4XYmEk2ToN/lRZ5MCzdiVpfGI3+MHiGBiggJEgaW3bljBylSq6Tx5mmAFa+dURTyTnepo+1K2L1FLeDR01LEBxDo6/Lds4kv/bWSjzOvuPzMyi5YrAh1rx+bh6ujMaokPEM7+1ES1DU+XouSrYgyWaaVGI62J9UyZSIJBu2c91cko+Fk4agwRfWfARyjiBKhsfDEbGzYFEP9VCnyKxMPymnf77EsnR7gDwARVgZPaumNYS3Kmrw4LVZmuPhiAiaonSZA3Oe/RQv3TG+w23C5PNs9Xi+a7Az2UydWd9mcualO8ebPudcrcB+Cm3WyBxUtwY1wZtk/p66eTRcdh6Ltra1SXmrogYVZ1qx7MZLMCjNgefn5UOSlUDOl8qrMG10Pw3A9tT/Z+/d46sor/3/z8y+ZychISThElSkGI0YhCA3e1qoleoRyxe5aIGgeCGA1v48reI5lWoP2p+Ilq8eRSLnVOXWgqJfrfZUrZbj+aK2EqkcTYuUgg2KJIQkJDs7+zbz/WNnhpk9z+z7ZWbv9X69fL0k2dl79sznWc961rOetRZPxMPXXQKbhUe3N4Chbht8QQHv3j1TlUwaUrQkPNDWLQdN/uvumcz7XuG2azakpY26x2/Qloktd9kwecww1SnHzUsbUK4onZsuYtmMUx4fNr51SDUuNr51CA/Ou4RZ7cgfDJftjizdnUzFF0EE85TET9J0sjSTpMsWE+YnoGPzpUQwM8DzHCwc0N0fwC3P78fD112iaastlRl/7M3PsHLmWJwz1IVnb7oMfb4g2nt9CAkCvv/LP+nOfWUuu2pB9193z0RIZxwJInDO0CJ83ulh/j4UMc6k+WPXimk41edHkd2CgUAI8xtGy6fVI+3c47/7LNxixG5VJUoc7wq3YP/lbdPwrYuGh6v1FtlR5tI/5afXwkwq257MqWm9Sp2ZmPppLZM8egmcj75xiNl2Rq9Sz0AghB99p1ZumclKUL3zinHyzyVtKZF+DoRbBrF+P3poEe6bc7Hsf0g/l9bDIVHE3Kf2YeLoMtx79YWqKk8bF03APb/5H7li111X1qL1RK/qe//T7o9x79Xsano2C4+l//EB9q2ZparaZ7daVAcUpBYYUosuqS3CyDInc+MkE6d9swXL/5f8rPkNo9HR68Py5z6UT3hGVkYeV1ks/21IFDG/YbQcJFo7p04zNykTMDcumoByt13WY0efD8OHOMFxkAPLNeUuZoWrCrdDU0Fc+j2rtWffQFB1QnfnrVPR6wsyKwj+yz+GVNXLtiybLNtf5bNmjYE3W9tx3zV1OKfCDQAQBVH+jKFuOza88RdNlVGnjUdnnx8b3zqE739rnKz5F1dO17x/kd3C1LZUlTFy3lw1mEx25cZ35c9bOye8flaOZwAoK2KP6WAqfcGzTHvf2cSiKp2WzCFBRIWb3U5aqox4vMuLu3Z/rEruuPbSGlW1Nr32ZL5gCBY+3G5XeSJaqtQpVS3atGQSnnz7MHa3HMeyGWN0/bhfrQi3pH/8hktlrZ/sHZAT6CQd7mn5DP989UXymvGWr5+PH86+QE6gmzi6DE4br2lR9MqBL9DdH5BPTksttAHIbVFYa6x0Vo/VjV2s0o9dsDBza3g9P653IMhcp15Q6VZVN65023Gq38+8j7tXTFNV87HwHAARp/r8mkqKbocVP/uNuu3Mz37zF/zviHgCyxcmUsfM63t/SMTrH38ht8UOCSJe3P93NM4YE/69jsbHVro1sTCJYEjUdAYJCSGs2h6ugvXk4onwBQRV5WHJB1614yNsvXkKQoIIrxBCR69P184oK2s+/rvPmFW8K0scON7Vjzdb29HR65fHiCCKKCuyobPPj6/ODMBh45if8/B1l+DN1nZTVClOFTPrOJJSpx1lRUGVBh1WDqXO9Pj4pzw+/J+P2nD7rHGaNtqSX6psbybdR5b/ef+1IqrLilBZ4mTOg4IIld3/1Ypp+NELH6v2KPr9IQwf4kCf7+x4jYxHVxQ7McQpwGFV+ybSYRPJ97736ovkJPDZdVVyO8OKYju+v/OAyh8GgB9fU3dWJ1Has8erL57nEBREOSlm14ppcceRk9lTIQgidSK7JrzZ2o4V3xiL+Q2j0eUJqJLKpPXatlumIBgSNTHV1Ts+wrM3XYblz32ItXPq5AQ66fdr9hzEjlungueA7e8fw/VTztWNf961+0949qbJqsNJkq122nh8o7Ya615rxepZX1P53MNKHPIesuQHsWIIrDW+3rpfmhOixXlZ67RUE+ukzhcUt80cenHxUqc1qhakQ6lAeK5TvrbMZUNHrx/g2C1Uz60owg93f4wNCycw9c9xHNrPsFu/d/b5VWPqB7/6E3Y3TdfE6axWXt7vkeJPkl/A8xxsPAdBFNF6old1CBEALhoeXttH6pXV0Wj9/Hr8SNHWdd+aWTF1GS2mwfMcqkqcENwi3A4rLqgu1o0BhRRxIslv+t0/fVOOjUqvW7W9BbtWTAO73kV0CiqJTi8ZjueA84YV4bOTfUzBhgRte4Wa8nBrAr22PMlUnSCIWOiV6bdmYLLU2+hr7/WhptwFi6L8pTQevIEgc4wNBEM4Z6g7LZ8f2RIk3jHosls0FRk2LKiHy67fYiSZ8R0Isu1MrJYosSaOQrEnvgD7/vmCAk71+ZiJkE6bBYIYbosbFEK44ZkP0NzYoNqcOt4VrmwSPjXyR/kEt43nMDLiRKbNwjO1Z9Np5xee2B2ysy5tBnb0+ZgtALu8AXmTSbq2ldtbMjJvxLIZIUFglsLVC8yns1WPy8Zr2iptWjIJLpt+20SjkE1bTBgb3UQwkwWqQyLkgITbwV4kljht8oIksgrQrhXTorYDU26uegMhWDjgRI+fOY6cgzYgEVvM81y4BTqnLsO/ackk8DyYdq6syAYLz7Gf3+AiLJ4Ah55d7PYG5IVvovA8NMlU4Tbh6bcxtJZJHta9kxKVmra1aAJrrISv5sYG9PtCuGt3OAlV2hyUKg689ekJzBhXiTGus4knkrZYmgMAi24SJoeTOkEYAHDZrKgpd2HlzLGyPZB+f9fuj+XvtewXf8Srd1yO3U3T8WW3F50ev7zZFK6ooz8ebFY+avBPeY+kU77KRKpIzJy4AWh9/I7BdVaZy4ZOj19+HpE+beQY7ej1qZKT9BItpRaV0qnx3U3TVSeZAajuZfngdSj/Hdm+OjJ4G/mdhrlFTaLg8S4vsxrZ0VMe3e+pfNa+IFtnSr+b53n5M6RERGXi55Zlk2HlOdy2dT/WzqlTHQST7r3y/fW0/df2Pt3EsMjN1zKXDXtajmPVrLGq1xc7rMz3tphEx4A61qb3fayDrTSi2S9gMLmjqhj71swCx3FY1Pw+Niyox4YF9bj7xYP4qmeA+R6n+sKttKUk3Ap3OIF/3+F2/OTai3Hv1RchJIjY8u7f5KROvQ1hXyDcRraq1ClvfJzsHQDPcbh91tc0lXe/OjOg+i5jK93y+66cOZbZoui55VPk09THu7xyJb5tN0+Rq+Bkuh2qXuyi3x8+MJzoBo8Z/QY9P66syKaqmiGtU+12K0bZ1aH0gOIQnsTxLi98gxuLyvfdtWKa7uHujj6fpr1lpB2oKXfBZiLbYBbMvL532XhcM2GUZg0kxVX0NO6yW6PEIHn8/M3P5IThQEiAw2rBowsn4K8dfegbCGqSx5U+MIDwxtzg+7HjxAIWR1TXaD3Ry1yDSAeMpLXoxNFluOeqWnV7q6UNmHF+hVz5VlqPSmtKM7SXThUz6zgSnucwqqwoY52fQoKA66ecq+pIpdTxutdaVb6JFIeIFg/Vmwf9IUFl9zkAlcUOrJw5VqXVJxdPhE3nGUp2P7Iogt7G/0urZuDvp/vR6fHLifn/d80sZstDy+BnStUodb+jnv/NeCbKe6W3dmWNyWT3VAiCSA1Wwn2nJ7y20ot7t5/xwW7lmb+zWjh5/cv6PccBf2334FsXDUeP149NSyap9oc2LKjHl93ewXXSgCaJb82eg9h52zSs2bNfjqOtnDkWJbwVX6sqxlc9A3IMSbJrLFvEWuNHi2lJ/x+vT5GuQ8sUt80sevd3d9P0mFrQi9MGQgLuvGIcjp3q1431/NviieDAjv9zEJlxqZpyFzo9ftX1H+8KH8CUDpQqCYlQxROlojS7VkxDdYkTX/SwY3NWC8/UVuT+zpH2PlXHh3T63Eq/SoqVRl7nVz0DcpxIun82C3uvJ9lDJcbfqU4j0mJCSU25K3yaxcJjT0sbnlo8SX6NJNgX9/8dTy9R/3xLY/iEu96JrmSqThBELGwWDpsitLhpySTYLOlfEEubWJHjYU9LGzYsqAc/aD2kyb/CbZc37ZREJtyl8vmsyhLxjkG900zRjGcy41tyzJQUSsAmVTo9fhw95WHev25vAIGQgHuuqsW611px/TMfYN1rrbjnqlqMLHOiujg8ofqDIp696TKM1KnCUuayyc64jedQ5NBOg5VuOzYvbVBpb/PSBlRGqWoytMiOyhIHfvjCx2ja1iKX1a8qZgRQsjhvxLIZggDNxuyaPQd1E4DiHZfxEBKAJ985jLVz6rBrxTSsnVOHJ985DDMU3cimLSaMjcvGtvlOm7lsvqA40SNtfiupKXfJG98A8NGxTuy4dSpeXDkdzY0NKHZYmfZZmaguLX5qylxwWHlUFNuxcdEE1Th6prEBwwarTSVqi/Vsip6dG+KyQRDDLViaGxuwa8U0NDc2YHZdFWwWHqPKi+TEjWhE85fWz69HMmbBwvNypU7puzz/3tGMJFRIlXqV96Cy2EFrmTiIVoWQ5fspgw371szCy6svR21VyWCFDXXFAenk/qyLhuPRNw4BgKyxzXuPYP38epXmnl4yCUOL7Ni1YhosFk4ztjYsqMdXgy119PxUScuxEoKOd3nh9YcwvNQJt8OKda+1ygkf5W4bHls4gTkelElLkcEpKQjEvEcxAoySbYl3zBoZ6Rn0+0OyDdF7HsoxWuG2o6rEId93KYCnpKbchS+7vWja1oIDbd14s7Udoiiq7pvyXla47Tjc0Yd5m/bh8vW/x7xN+/Bljzfq82MR+XzsVov83ZQ6eW75ZbBZONkOTRxdpvme0nsNL3Ey5wel3620zQfauvH8e0ex89apKl15/exT6awxFk3bynuvvN+Rm6/d3gCuvmQETp7xqV4/EAhpPi+cOK17Ww2FMFiRS/IJQoLA/D59viD8oZDGh96woB6b9x6R36+m3AWXzYJR5UVydfpHfnsILrsF6+aOxxCXTfP8Ny6agKFuG7a8+zeVHe3xBnDZ+cPgtPLwBkJY/tyHcgLdlmWTdf04uzV8elva+JDGwcLm92HheWxcdCl2KaqMPfLbQ7IO97S0qeIieptHyuDuxNFlaG5swGMLJ8Bq4cO+ydKGjFfV1ItdHD3liTqu8wmWH9fc2ICdHxxjrlMFQURHrw9fdPWjo9cn6591HyMTC453eXU3IkOCiA0L6jVjw6Z4b0ljrBgGkRpmXt/HiqskE8OpcNtx15Vn13b3vvQ/cNkt6PMFsO61Vtgs7E1zyQe2WXgUOXjYFcnTSmrKXbBykK9Zb96XsHBQzSt3XjFOE99t2t6ClTPHatajPMeZpkpxqphZxywy6eMLAtA7wC4EMLzUKc/nwNkxU1XsSCoeGmn3BVHUjZ0UOXimj6tn9/U2/gMhAQs2vy+3st+1Yhp4AE8tnsicZ54e9KOj2YtE9KWM5Wzee0Qzv+ndN9pTIYjcwBp7e1raUFnikJPKlEhrW734sZRIqxeXEEXgl3/8HN3eAEICUOq04d++dyn23j0T6+aOh2twfQWcrQwnrZckX4fnRGYcLSgIqCi2yzZGsmusGMQwRlz63IoijR2U1quJ7oPp2ehE11mUg5JZ9O6vhYNGC5J/EDm37WlpU83fDqsFX6tyw2njNblFzUsbEAgJuOGZD/DJl2eY8X8RHFOzTy2eJPsnEjXl+gcw9br9AeHEfLfdwsyJiuY6Kvd3hg9xqroAZMrn1tt72fr+MVSXOvHS6hlyrM/Kc8y9nmQPlRRUJTqe06nqwAEWnsMd3xqH1z/+AltvnoLTHj86PX48/95R3Hv1RRBEUVUS1BHjRBfHcQmf3CSIWAgimGX6l3/9/LR/lrSJ9ULTdAwEQwgJgNcfxPemnItSpxVWnse+NbNUp8Fcdosm81eq9pZo6dp4K0vEWxkrmdNMnE4lj2hVZczcVirX+IMhPPH2YY2dfnrJJPzklU+x5uoL8aOIyih3v3gQr9w+A3895VHd801LJmF2XZWqXPzsuiqMLHPhueVTYLNwCAoC+JB2GrTZLKitKla1aakqdsAWJSnGauVxYXUJs2xuJOms5hYLERzTZtz8D2MBqBNnJI53hdspskhnxZdASNAp6W/8LLqQwLbFN12efltMGJthxQ5saZyM27YpbH7jZAxjJNAaGWX7UGkzX3MKigv7wjXlTviCIpb8+9mWe81LG/DsvqMa+8xqu8EPViXY91k7vnPJSPxqxTSEBBF9A0EMH3K2bWCitljPptw32J5EyfEub/gEeIkN37/iArnMd015uO2bXqKeni9TO2j/O3p9mnayD82rT/BpAMPcDtx1Za3GlxjGaGeZKslU6iXC6M3n/f6Qru/HqlBQ5ND3C8RgCB29fnR7/bKPLSUE7bh1KkKCiNODATipml1NuQvP3jQZjy6cAA7hk7SVJQ7c/cJBAMCTiyeiyxOQ17XnVhTJWh5XWYyTvewqT5EnbyXtv7R6Bvp9IRw95cFPX21FZYkdO2+dCgvPgePC7aIfmhdOBjvR440Z/DNrNaN0IN3T6lIHqkouwONvf4a7v3NhTL+R5zmMHBJO/Gja1iIH9CLHdZHdgubGBrltVKIVudt1qi0lEryVNualNtsVbjtGlTnR1R+Qq9pI887z7x1l+sfx+N3x+Kx6p9KlMbb15ino6PWh2xuQtS1V71Nqu9xl06z/pBaiQHgN8uNrwq1cLTyHJ36nXu94/CE5cKpsHfng/7ok7vuaK5Sn6yuLHbjzinFwO2z4+Vufab7P/IbR2Lz3CO65qhbbbp6CkCiiyG7FQCCkG3iVntGBtm789NVWrJw5Fr6ggNHlLuxZNQO+QEhuRfKL/xuuMCdRU+7CyDKX3JJ4qNuh0QMAZoXQ4SVhPXX0+jTjYOX2FlkHNisPK89h89JJCInhtdUD3x0Pu4WTx6BeBRYp8aqy2KFp2bxpySSMKndmPJ5Y4bajeWkDmhR+kNTK7snFEzP62UZBmvt2N01HICTAZuFht3Bo/u9jwH8fU7123Vx2NYmyIivTdwbUi2ppg4OpBwuPUqdVFXcudVrhDYRkX9nCczjweSeqS6syf2MKjFhxEyMTK66STAyH9TflLhvO+ALYtWIaRKirb0wcXYY7rxiHimJHuEUUJyIQ4mC1chB8AU2FmWcaG9AfCKlayEvzPiveyg8eMPrlbdPwZbcXFcXsAwanPer2Vne/eBAvNE1HdWnm7akRMLOOs40giiiys9dgw4rtqC5x4qF59bj/Wu26P9F4qD2igl1IELH1/WMqP+nZfUfx4LxLwIHD0Y4zcdt9vY3/0OBhwciK/E8vbcDGRZdCEEV5nhEBXFhVLMdZ9L5jIvqKjOU4rTxeWjUDgZAQ9b7RngpB5AbW2LvrylqMLHUiEBI0sYWNiybgZ7/5C/517sVMH7hvICDP648tnKBqxSodVom0T5uWTIJrcD3/01db5cpW/f4Q0541L23Q7P3VlLvgtFpU875kux+aVw9BEDTreZuVx0urZyAQFFRrRMkOSuu9JxdPZNqvaHve6Up+y+ZeYiGid395nmf6ww/Pr4fXH4IgitjdNB0WLuyrlrts8ms5LtzK/e4XD6KyONzB7JyKInT0+jB8iAMHj5/BYwsnQBBF3PL181VjZNOSSdj+/lHcOGOMHCcaV1WMw+192PHB57hxxhhVl4VoMfxY2hHB4anfH9bEbuLZy0jWL0qmxXHkZ0XGmpV/f9ozwNzrcdmTO4hWUEl0gghmcPL+ay/Gxjc+Q3mRFctmjAHPASOGODFiiBOTzqmHCBHXbXpPIzSpJ3DkBLN+fj0eePUT3HVlLfWlJtKKleeYZfozVZqd5zlUlzpxrNODttP9KBo0xi67FcOKtafAylx2VJc6VYG/6lInSh22pErXxrOJFu8CKxlnQzrtGOkIxsrENnNbqVxit1rQ0eeTW/BIG3x9viA6+nyqSi0S4YQPQbO5sXrHR9hx61TZoZhdV4XvX3EBvrdF3e6htprdCN1i4eVy9XarBRadVq5KIsvq65HNoIDDyrYZDmtYjxae3Y4gWrWjdG1u260WzK6rkluEdHsD2NPSZooFgM3Cvq9mPeFLJA/PcxhXVazZyDebzVfOd1/2DGBPS5vGX75vTh2KHVbYrRYsf+4PKpvbtL0Fa+fUqYIX0RLVh7kdmDq2Eve/8gnmN4yWqyiVOmyq1yVii/Vsim5bWCsPfxDyokq65lVSe+2IZL1YZfiHlzrR4w2o7EKytj2bvoRepV5WAiShhtmedWkDRpQ5UeaK/3kNczuY78NBBM9xuPOKcbhj5wFVy+R+fwhfdoef1dabp2haES1/bj9+eds0+IIhBHoG4HZYw75UsQO+gCC3w5CCmFIF2sMdfdj41iGN/7thQb1caUmp63BLeycEtwi3w6obWJSg4F9spGSfMpddDvRKyXHRbIvVyuOi4aXhtgr+IL7o9uLh6y6BzcKj2xvAyx99gcbp56o2rKVWuaxnpdfSJdXnpwxiS/ZNhIgV29S2eM2eg9h561RdGxrN744Myo0Y4oq6UcfS/F1X1gKAKpj5s+sukROyImEFVx+aV491cwWc8vhViecbFtTj5Y++kMfziDInll8+RpP0aAakZEtlIlhlsUOTnL1pySQ8+c5hHGjrxve2/AHA2Zja8FKn7nyntLMH2rqx7rXWQf070OUNwDLYeqzcZcP/mjQar39yUmVHpRbxgP4aJtp8q7fxIVVxBPT9g5pyF9bNHY9hxXZNAolUmXP9/Hr4g4KmYu7qHR9lZR7meQ4jys7Gb7q9ATz6xiF09PkKxi4LgqhpU93c2ICmfzgPk86rUPmUIRHMahK7VkxjxprXzrlYtpnyIW4e2Ly0ASsVQX2p0vJAIATgbGUKl90KC8/h8Mk+Ob528ahySibIALHiJkYmnrhKMjEc1t8MtToAd3jcSLaZZfOlWBvPc+juD8AXCGLbzVMgiIDdGq5SN/fJ9zTz/tabpzDjrVICfkgQ8cMXPsbaOXVMf4TV3koQC6fAgZl1nG0sPA9/KMiM+Vt5DlarfhuzRMdSZbFDZffL3XZNMsj6+fUQBRHDShy4eFR53HZfb23ltPG475o6VctkKdbx3PIp6FS0dbVbedVBRb3vmKi+lLEcnueT2iSnPRWCyA7Rxt5Qtx1dnoB8CKq7P4AhrnB8SS9+PL9htPzzgUBIXZzIyuMfLqhir39WzdBUthrqtuGfr74IjRExr6btLdip2PuT1lisxPmkbHfk6yM6ZQqCiG6vHye6B1QHkpRx4mjxr0QSiSjBOLNEu7+SdqTn1enx4ZTHr4nPjassRpc3ID/PYEiQ1//hGO2HqCl34Ze3TcNXPT5VTPbJxRPx8HWXYPTQIpzoGUB5kQ3N/30MfzzWLbd+DwmiHMs73N4nH0gtK7KD5yC3L07ku0m/Zx3ij1dbiY6tVFocx/tZAwGRudezu2l63NephBPF5PrApgOO464C8DgAC4B/F0Xx4YjfOwBsBdAAoBPA9aIoHov2npMnTxb379/P/N2X3f04eqpf46SeP6wI97/6Ke684gJcWF2iqRz0RVc/Ll//e8377VszC6PKiyAIIr46M4Avu73janEwAAAgAElEQVTo9Pixee8RuaUN9aXOK7Lmsevp+HhXP/71159qgiM/ufZi1AwGcTNBIpM667WdHj/mbdrHTERNx/iI5/qSMdAdvT78+OWDmvv90Lx6s47rnGs4Gqxn9NTiSeA54MueAQxx2VSV6ICwjnbeNhXfeGSv5v3evXsmrBZePl2yqPl9zd++tHoGqkqcmus41unB5539qiot51W407ZwTybjPhm+6OrHTxk24/5rL8ao8iKc6OnH3zoY82KlGyOGxE4ITIVgUMBfTvZqNhBY87ACQ2g4V7aYMB5JzC2G0HAkyvlu5BAnBBG4fad6s3fEEAc8vhBO9AzIrSaVvLhyuurnseb5YFDAofZezcJTuneJ2mI9mzJiiAOfnezTJCfUDg+38ovm40feo1i+TLZsezqJtc7RIStfKhlfItvEeubxaiIYFPBlT7jSV6fHjz0tbfj+t8aB5zgUOSyY9eh/af5m14ppuP6ZDzRjL/L3NeUu/Nv3LgXP8Tjt8cvBGomachd23joVxU4rvvtkWOMTR5dh5cyxg1XCXHDYeHj9qes6lYBJmjGVhhO1LSx79exNlzGfvZ6dZr3H7Loq/ODbF+ja7WSJJ96SyFo0EY1J7y0IAkJiuN2F8gR6qjZdb+5YN3e8HEjddssU/NOuj+UAabc3gM17j+DxGy7FORVuvbc2hD8hPbvmxgY5qAucrUo0eqgLRzo8eLv1JOZOHKVac8SrncjnX+a04rOOPpUOm5c2YFS5E/5guLLK0VMePPH2YXT0+VLSaDxzv95rXlo9Axw4+IPhqo9BQVRVOOj0+PHjlw/inqsuxLd//q7ms2PMw2kjh3bZEBrWe347bp2qSn7dvLQBZUU2fJ1hq97/51k4dqpf42u6HVac6BnQrMOrS5xo7/NpKmlGar3cZdMk+OVozsx7YsVNdDCEhpOMqyQEax4Gzs6R1z/zgdYGrpqBqlIn829P9HiZ8/4rt1+OkWUupl8S3nvx4uipfjz/3lFtRZrGBjz+u880FWkKaV8mCR0bQsO54ERPP7x+AQ//55+zEvMPBgXZ7lt4jjlmdjdNx/BSZ8w5WTmmXHYLTp7xMV+vN87e/qdv4lSfD/3+EEYPdeG8oe64bEUi+spGXF2BqdZ1hDk5797XE/6bYw9fE+9LDa1h1lrhl7dNxV/bPRhWbNfEj5sbGzDUbUdIEHHslEeuNi9RUx7uEvXtn2tjXPvWzMKIIS7ZxklV4PoGgvjGhr3M19utlqTW66nEb6V78lXPQNQYi946a1xlscbH33rzFBQ7rar1YjKxxRxhaA3HQ7T7Kz3HjW8dwt3fuVBOJpeQYqqLFWvH7bdMxcxH92o+5927Z6oS3KW/Xzd3PC4eWQqO4xAIhrAowk+YXVeF22eNU4+1GIe4pUTP0x4/2k57defjbGornvhKqqR7nyNnleg4jrMAeArAlQCOA/iQ47hXRVFsVbzsFgBdoih+jeO4GwCsB3B9sp8p6lSi++l3L8baORfDwgNf9Q4ACPcslsQS68Q8z3MQRVGzeXG8i/pSE+klJIi6rcoySSIZxazXZrpvezzXl8xpplQzsYnEiHxGIUHEg6+34s3W9sGEuomaEtBblk2G08a20S67VdbF3097mBocCGirJHV7/Th5ZkB1ImDDgnqUFdkwNE2t9LLVqiwk6tiMORcDAARBv0JrpunyBuRAL3C2PZIZgpy5ssWE8ej0+OWWdNIY2vjWIdMlW0fOd7PrquR2jMr50uPr161EVFniUFXbiDVfdnkD8gY4cLaah2QDErXFejZl521T8chv1c/okd8ekitmxVtVKR5fhmXbpYC51CJMr9V3rrBZ9Sv1GR0jBJGizeeJJCZ0eQOaQErriV6smzseYxxu5jOS2qvqjUmpheCGBfX411//GQCwYWE9U8ftvT5YeE7+3YG2bjRtawEQDjQMdTs0J2+TIVPVBYyghUySqN/IOm06Zpg7ofWYXkuXcZXFaX9+sU5oJ5Lgw2pDq5xbIol1b5W/EwQRHb0+3cAqS4N6c8f5lW7sWjEN3d4ARBHo6PPJY076/tY4KmHnGunZlblsqu95oK0by5/7EO/88Jvyz0RRxHPLp8BhDbfLrCyJr72e8hkJgojjXf0a/6FpewvWzR2PqlKHJoki2vOPRTyn/vWecSAoRE2Ck3yvttPenFboLPSqL3rPr0PRvlryKXc3TWc+K4BDRbFdVWWjssQBX0S7yo2LJsgVjliVNCPtEaudcCp6JvSJFTcxMpmOq0SbhytLHPh7p16sLexfsOZZvXm/vMimu34M771ArnBT6rTi2ZsuQ78/JLffvOvKWk1FmkKK35pZx9lGEIBdf/ycuSGdCc0o7f4XXf3MMSOKYkw/ljUet948RdOKMNp+5l8HDyJI/47XViSir2zE1QmCyA6RawUAePx3hzF34ij82zuHsWz6efIar8jOo8cbxMLN72PDgnqMKnfhsYUT5ENiB9q6cbzLC4dOHNJutTD9hpAA3dcn4+ukeohIstWPLZwQNcait86KtPWVxQ6cPDOAZb/QP3CWrb3EQiXa/ZX2fm6cMQY93oBuTFU5dx895WFqNiSKzL8fM8yNYcXhzz/l8WH7LVNVBwNvnDEGOz74XK5AN7LMpdslQRBEnPL40O8LISiIeOS3f4l6yCSb2sp0ngiQ/g4ouWznOgXAX0VR/BsAcBz3KwBzASiT6OYCeGDw/18E8CTHcZyYZPk8m4XXtMl4avFEdPT58eQ7hzWnmCRDFU/gjFrTENnArteSzOABdqOMj0QnhGz29Sa0901qg3TfnBCOtPfhgVfD00OkswAgpo22cBxTg6xWEV5/iNnabteKaWnZQM4mTr3S/oPJETYLj9v+4XzctftsYuLGRROyYlOy4TRlCrPaYiL9CIKAW75+viq597GFEyAI7DamRkWa715aPQMDAQEWDnDZLZrTTHarBXta2jRtT55aPAk7PziG3U3TVVV8os19sWxAorZY7/0sHIfKEnUgvLLELl9jvCXxk/FlUqkMkS1fwspz2LCgXlM9xWpwv8VAFc10SSSZh6XfymIHzqsoQo83gB23TsVDioMF6+fX49E3DgEA9rS0oXlpg6qFRHNjA4a57Xhp9Qz0DQTR0RcO6Ogla3R6/KgqdWp+N7uuChzH4Yuu/rTpMN0BGjNoIduw1jAixIRsWLR1kBT49QdD6PT4U9ZFNFucaFJcpvzLaDoDoPldc2MDaqtKdOeOQEiUfYdFDTV4eskkrFK0+9y8tAFVxcYPkkvP7queAeb3PNzeh3WvteLpJZPwb+8clm1Yc2MDKiOqgcdDp8evClBLHO8Kn6xu2sZuL5/s848nHhCPf6A3p9dWl6C61KGx4dlO/CjkTRm95zcQCKG5sUFVHZLj2HEHHsCjbxzC/IbRKIIF/pAAt8MSTqJTJNYV2S3guPhtpZnXy2YjVtzEyGRaJ7HmYZ5nx9qiJZmz5v3mxgaM1Gm/LhEtfmW18gWdEAyYW8fZjqPbLDy+XTccT/3+sBxjrii2o9RpzbhmovkNscYzazwu+8Uf8fLqyzWJ+6xxplxDRr53LBLRVz7F1QmCUK8VOnp9eO9vnQCgTURubEC/L4Snl0yCCKDxP/6osT8dfT6c6htIaP0TK3ab6BySaIwhEslWSwdXo60D4yk4s3LmWI3NpIMzxsEfDGF+w2is2XMQa+fU6cZUlfzn/5zAjlunokPRbeTGGWN04yZFjrBmNHGlpQ0Y6rbh/lc/xZut7Xjvb51oXtoAp43t27HiVuvn16Oj148Dbd0AwvryBkJpjfPGSzbyRNLd/jiXSXSjALQp/n0cwFS914iiGOQ4rgdABYBTyXwgz4VPEiuDGGVFdiz59z9g7Zw6TR9upaGKtRCjvtRENuA5YOOiCZqAgdFjAmYeH9ns613IRLtvJ3rCfeMllJVRpHsay0a77BZmkoDLrp2g9U4EhCLSt82SLMmyGRI8B5QV2SLmRVtWbIpRkmuTwcJzzPtqMeDzJzKLIELeBAfCtuKHL3yMF5qm5/jKkqOzzx91/pKqpkjV9yrcdgx127F57xHsbjmOZTPGxN16LJYNUNpiqbVkmcsGEWH7G2lv9d7P7bDgzisu0CSylbtsCSXLJ+PLtPf5mJUhdjdNZ1YgkcimL+H1h/DyR1/g2Zsug4XnEBJEbHn3b/jBt8cZOsCdatAr3bB8gkQ2NV12C5696TIU2S3o9gbwdutJzJs0Co2/OBt0bG5swLq54+ELCnjw9VYcaOtGTbkLyy8fg1KXFS+tmoGBoDYJdphbxMurL4fXH8QX3V5sWjIJqxXJOuvn1+P5947iwXmXqDQ+u64Kd15xARY1v29on9ZoWjAKkWsYQRATtmGsdZCylcX8htGocNvh9Qcxcogr6Sqb0WxxoskBmfIvo+kMgOZ3TdtasOPWqXDbLZoNgqeXTILHF8DTSxuwansLDrf3wW7l8NzyKeC5sG/hsHKGGmd6REsEkzZKjnd5sWrHR3Jym3R/XmiaDkEU5TY98bSMlhI3Wc+4e/BUeKSmU33+seIB8WzqRJvTh7odKHPZCzrxI5foJfMEQ4LcfkqKHfBgxx2Od/ejo1e9ceIPCrBH2ES7lU9onW3m9bIZiRY3MTKZ1kmsediqExux8lxU+5dMwlus+FUhJwRLmFHHuYijS1r63pRzUWS3oHcgiCEuK5Ir25EYsQ6PRBvP0cYjaz2qHGccx+GBVz+RN9Ej3zse4tVXvHF1giDMh/IQlZRAB5xdA6+bOx6n+wW5GrP0uzV7DmLd3PGwW3k8vfcIbvuHscwOKCx4nsO4ymLsbpqOYEiAdbDLBwCc9vhwontAk5AXbQ5JNMYQaV9d9rDvtXnvEc0h83j2vCN9t8iq7rGuh8gu8pqvy8t85s2NDXj1wPHBAyFOlLpsOOMNYomivetTiydhxwef43B7n/z3lcUO3HnFOIwZFg6+n/Joq5A3bW/BS6tn4MF5l+Bf/jGEo6c8uO//fIKOPh9T56y4lZT8p6xCe6S9D8uf+zDrcd5s5Imku9J+LpPoWFcc6UrF8xpwHLcCwAoAOOecc3Q/0B8S8cKHf8cNU85Fp8cPm4WDMOjU6RkqQRBULTtG6JyKKvQWCETqxKPjgaCAF/Yf12x03v6tr2XzUhOmkMZHIW/kxWuLWUS7b/EEBWMFy8pcdlSXOlXBturScM/4SPTawyoz/FlBHqnqC8/zhtG3NxCKajMCIREbIk7Nb3jjEH763fEZvzYjJtfGq+GBYAg/+81fVO0hf/abv+Dx712arUslDEJAEFBZ7FBpYfPeIwjkqBJdpuywssR3bXUJHvjueHzZ7UWnx4+HXv+znMwTLQDLqjYazQZItriy2IEffaeWWS06ngMt/pCIJ97+TPWMnnj7M7nlbiKbLdWlDuxaMQ0hEXDaeAxzO6La+kBIYK4vgqHo+mAtnG/buh8vrZ6BqiQq90TDZbdg3qRRWP7chzGTzLNB3Os6A1Vn0dv4qS51MP0Jl92iWl+Wu2w4ecananez9eYpWDaYQCclkXr9IQRdIoYUWfG9Kefilq+fL7cnriyx4wffvkBucRg5TipLHOjoBe5+8SBmnF+BrTdPwWmPH50eP55/7yjuurIWw9wODHM7VBstUgKddH+N6NMaSQtAanZYj3Qc3EjXekzZyiIycHjR8NKk/V89W5xockCm/MtYOmMlfQuiiMPtfXh231Fsu2UKAODYqX785JVPUVlix31z6rDj1qmw8hx++utPo7bYyDbx6lipzRFlTrywcjr8QQF/+aoXj75xSHXaucxlk//ueJcX/f4Qrvj5f8nzziO/PaQbDJaQKuI+tnCCqgrwpiWTcP8rn6Km3IWqBNvLp0qssRWvf2Uku5oPxKthZuVOUcR1T7+nemZ3v3gQLzRNZz4rt8OCf/nHC1WJBc1LG/Dqn45j0nkVSa+zjbhezldixU1yQbwazrRO7FYLZtdVYX7DaHkttaelTZ6HHTYOQyIS24YU2eCwcTHtX6J2L5fxKzNgNB3Hq+FcxNFzqaVY1Z6jjWc9v9hltzCr14woc8rvLQhiSi2PE9FXPHF1M5CJdR1BZJNMaFiyYW6Hhbk+LrJbUAT270YPdeGFD/+Oe6++CD3eAI50eDBh9BDdNs/SWlMQBJzy+FXxrq03T4EvKOCrnrOto6XPiTWHJBJj0Iv3STG7R984hHVzx2PMMDeKHJaYcWJA67v1+0NxxQ6Nst+YTYxgh6WDozXlLhxo68ajbxxSdUqrdNtx7aU1eOLtz3DjjDE41efXaPL2neFDhYfb+2C38Hhx5XSc6vOrDvxvv2Uqc9wEggJcdguOnvKgyG7BypljsXnvEabO9eJW0lyvjL1Iv8tmnNeMeSK5TKI7DmC04t81AL7Uec1xjuOsAIYAOB35RqIoPgPgGQCYPHmy7pkGURTxx2PduLp+JHoHgjivogjHTvXLp1YjDdXsuiqNcY4W0KPAF5EK8ejYaeWZG51mKM1eKOPDaBt52SReW8wi2n0bMcSVclCQ5zmcV+FGidMWc4Ie5nYwP2+YwqFnBXmk9kHrXms1TKWWmDaDEzWboOvn1wNc5o8HGtFpilfDFo5DR59PPsEBSO2BjevwEZnBYeFxz1W1miqXjhy19s2UHVbC8xyGlzrR4w3g/9v1p7jssl7QYVxlsa4NkGzxVz0DzGrRkQllejalo3eAaecSabmrd/3DdAI9Ejad1s/WGPoYCLCfxUAg/cmZQUFktlp5afWMtH9WPMSrYSNVZ9Hb+Hlp9QyNP7H15ik4ecan3uBobMDjv/tM9fenPX45gS4yifTppQ34z/85gd0tx+VraG5skNesymtQBkKUgbrD7X2484pxqK0uwYPzLlEF+qTXf9HVbwqf1khaAFKzwyzSWZ0jHesxZSuLSD84E4G3RJMDMuVfxtKZXtL300smoaPXj8b/+CPWzR2P5c99iImjy3DjjDFYvOUPqnkpssVGLsdaPDrWO1TU7wupKg8AZyvFKf8tPRJp3pFOR0cL4la47bj36ovQOxBQJWxwCLdq/9l1l2DkEFfW1xfRxlYhxwdySSK2OPL56c1/gk6JolAIcgKd9Nqm7S3YfstULP0P9TgHJ8adGG3E9XK+YsRYa7wazrROyl023areABAIATc/t19j819aPQOBdNu/OOJXZukYkQmMpuN4NZyTeTKHsVBA32/QG88A5ESKnbdOxYOvt+LN1nbZLw4KIrN6zbq54zF8iFNeN6RiKxLRVzxxdTOQ7nUdQWSbTGmY5zm4bFbd6uDS/2sSaa08/rF+lHxgVEr4lbooKFGuNaX9NqWN+7yzH2tf+QSPLZzAnEOitatMJMYQLd6XrD2NtMcuuyWu2KFR9huziRHsMM9zGDnEJcddD7R1y/u/w0ud6PSEk+Gkbpd6mqwqceCeq2px1+4/MTV99JSHOW5sVh4nugdUB6+lqv+RvpJe3KqsyI69P5oJm4XDHTsPqKrSZjs2kek8kXRXOM5l5s2HAMZxHDeG4zg7gBsAvBrxmlcB3Dj4/wsAvCOKyRdWtlstuPOKcbhj5wEsf+5DtPf68MTbh7F5aQP2tLRh/fx61JSHWyvVlLvw42vqmJsRkf2NCSJbhEQwNzqpHLZxkCYqJdRyIzbR7pvSsdy3ZhZeXn15ShuHo8qL5OpDeq+L9Xl6QR6pqqlR5opYNkMQoNkEXbPnILJVRCveZ2I0OA4an2H9/HpQDl3hIeiMMcGE83Ii81eidlkv6NDlDejaAOkzxla5mfa23xduWRJ5XZHvFxLZdi4R30nv+mPZ+apiBzYvbVDZis1LG+S2A3pYOI75LCwZsDGBYLiaYnNjA3atmIbmxgZUFjsQCOammmK8SEEv5b3NVXUWPZ8gEBQ046TYaWUm4c9vGK36e6mVz8qZYzX6XbW9BSu+OVb1eqm1QOQ1KAMhynH75OKJGD9qCM4ZWoSqEqduxScz+LRG0kImSNb+ZAplKwslmQq8JbMOyIR/GU1n5S4bmpc24M4rxmnH646PsHLmWBzvCp/KB8Ac12v2HMTKmWfHtRHHWiR6h4p8wRAeWzhBda82LZmEPS1t8r83LKjHV2cG5PeS1lHS/+tpiec5FDutuH0wpnf9Mx9g+XMfYtWOj/DAd8ejtroEVitvqPWFWWwpcZZEn9mAjh8QEkTNOBcE4NDJXszbtA+Xr/895m3ah0MnezU+rYRZ18tmw+yx1kzqpMsbkBPogPC9Wbm9BV2Dm+SBILvydiAopN3+xYpfSZtm8Y6vfMOsOs7FPJnrWGg0IsczoJ43Fv/7H/CDb1+AP/zzt2S/WG8cFtktqnVDKrYiEX2lK45PEIRxYa2PNyyox+a9R+SWl8rfNTc24Hg3owXs9hZmbEO51mR1ESyyh6vdScWRlNSUh9tV6vkCidioaPG+VHwvpT0e6nbEFTs0yn5jIWK18rhoeClTM4IgYO2cOoyrKo6qyWHFDnkeZWn6ibcPozliD2HLssmw8pzcrhg467PcecU4ja/EGpfNSxsw1G3DOUOLYLda0NHn01xbPsUm0h1DzVklOlEUgxzH3QHgDQAWAL8QRfFTjuP+FcB+URRfBfAfALZxHPdXhCvQ3ZDKZ1a47RhX7ZbbOQ1129HR50NIEHDv1RfBGwjh2ZsuQ78/hBKnFTwHpoGkE6NErggm2RaMyB4Vbju23jwFn3f2yyfjz60oypuNvEwhTfAb3wqX069w21FV4pBPt2a7kmGsz+MGExz0TtsYZa4ICWybERpcOEgtzSN/XyAxxqQRReD5946q2kM+/95R3H/txbm+NCLLhHTHkPEHUaLtVSNJxC4ne7o82unGo6c8cDusMa9B1HlGiZzLSfb6rVYeF1aXYHfTdARDAqwWHlXFDlhjVANw2S3YsKBeU+EwEy1WXXZtC7KNiybkrJ1rvBipOoveST9pro2nuk3kONvT0obmxgZ4/Wzt2Sxn/ZCacheqS51xVWNLZNyapY2ckbSQCXJVxUqvkouylUUsvaULI1Q0j6azbq8fVgswppKd9F3msqGm3IV+f/iZsQKmSjtg1LEWiZ42S5w28Bzw6MIJg62kfbBbObkNdb8/hCK7BQ+82ir/XWTVgmha0tsoFkXRkOM+U7a0kKstpZtUfWKLTmwg8nFIa4Rsty0kYhMrbpKvxGNHYvkh0Sq1ptv+xYpf5aItqJEwq45zseYwUyxU79DCy6svR4XbLm8K68Wo07VuSFRfRvDfCYLIHJHrY5uVR99AEB19Phzv8uL5945i561TYeE52b8+3u2NO7ah9D9YXQSlFqhSwp6ysmg87SrjtVHZ6nwQb2VsI+w3FioszQiCiFMeP9a91oq1c+qiarK73x9V0x19Powoc2piTid62ONmzDC3xleKFR81S5w3FdIdQ81lO1eIovgbAL+J+NlPFP8/AGBhOj+zpz8ol0mcXVeFTUsm4cl3DmP1rK+hyxOQk15KnFY4bGoDOXF0Ge68YhxCooiOXh8FqYisY7XwmF1XhfkNo+XEjT0tbTHbghHZxRcUVOVVtyybnOtLMjw8z2FcZTF+8O0L4m6hnUssHPDYwgn44Qtnkw6kMrqAcTL4HTYL02Y4bGGbYeHZrQYtBrvfRsNl53H3VRfi+OnwfbNbwv922ckWFxq8zqYZZ/CyhMm0V02FVIIOFW47mpc2yKeuaspdeGrxJOz44HNcUF2c0c+O9z2ibUBZrTxGlrmY76tHmcuO6lKnqlVddakTZa70L2qDIVHTguyu3R/jpVW5aeeaCEYJzFe47ap2qpJP8ODrrXhoXr3qGm1W9ryrTIKrKXfhritrMa6yGCd7B5jzeFAQsWvFNADhRMju/oAm8XJLY2qBEDMlpxlFC5kgF+1qY7U/ULayMGvgTc9uR7Pnejrz+kO45fkWPHzdJcxn1e8Pyad/Z9dVMQOmUouNXSumod8fgiOHLQTjRU+b1aUO/PlEL4rsFnR5/BgxxAmeAy6oDh+Osll5nPEG5BPQyo0O6aR0NC0ZrYVzLDJhS9PdoqSQSYdPrHf44VSf+rR7OLGOQ2WxQ3UYa/PeI7QhlmNixU3ykXjtSCybG20zLt32L1b8yh8MFfT4MquOc7HmMFMsVE/XgiDIY7iy2KGZh6QYdbp8JLPqiyCIzCEdspPWz8VOK16943J4/WxbXuSIfx2n9D827z2i2Ycb6rbh6SWTsGrHR3j0jUNYN3c8xgxzw27hwu01Z47F5r1HcKCtO6UEmlwlHUnfv7LYgZUzx6LMZUO/P2T4A89GIhuHzjo9fjkupkyei9Tk7TsPYOXMsbKm3249iU1LJmH1jo9kXT29tAElditsNvUz1vPFixwW1feJ/L4jhrg039dMcd5kSXe8iEuhO6ohmTx5srh//37m79p7B3DdpvdUN292XRXWzrkYHl8AVosFNgsHl92CYe6z5ZIlZ/Seq2rVGxMUpCo0svag9XTc0z+Av3f5sEqxkfz00gacU+7AkCJnti6PiEJHrw/zNu3TGGmDnHzMuYajYfB7p+K0x4e20/047QmgrMiGIS4bHv7PP+PN1nZDzQ/BoIC/nOyV22/UlIdbCV442OqovdeLr3p8Kodt05JJGD7EiaoSQ9oUQ2i4/cwA2rr68YNf/Um+b4/fcClGlxehqtSQ943IEKd6B/Blz4BmDI0c4sQw9hgyhIazbW9T3ezt7vfhtCeA0x4/Oj1+7Glpw/LLx6B2eAmGuqNfbyw7mOr1A8jIRna2Ksz8/bQH33hkr+bn794zC+cMLdL7s6zoOBlfIlec7PHiT8d7VBsbB9q6sW/NLIwqP3sfT3t8OPRVr2aj/YLhxRAETvO8/f4gDnV4NL7/sY4zmDa2Sq7yNG/TPk1w7cLhxagu1QZNCAAm0nAukmXimSPMXAUrWtLM4Y6+hO+1ZEcnji7Dj75TqzpxvHlpuKLkz37zZ3T0+cDlCDoAACAASURBVNDc2IDqEgdO9vpUSYhSEtmBtm4Acc3JOfcnWPdx681T4A2EmN+to88n309BEPFFjxcdvT4MBEJwWC2oKLaD5ziUFVlRVqQ/t1MCmbnWzVHIuYaB9NxLQRBxrNOj6kYweqgLgiji5uf2q9fZpQ4c6fBo/IB4fFoicyS5XjCEhpMlXu3HY3Oz5RPEil/p+dmFMr6S0LGpNZwKZoqF6un6vAo3Fja/ryn+cX6lG3/r8OCJtw+rfK9Ux2Q64ioZwjTrOsK8nHfv6wn/zbGHr4n3pabVcKLrskReLwgi/nzijHyg+oWm6ejzBVFkt8gxt8oSO+656iLYrTyctnAlvGW/+KMmmbijz5fSOikXsQ9pfXHyzIAZclIMp+FsxQy+6OrH5et/L/974ugyrJw5FhcNL4HLbpWTTKWYrRQvWjunDnta2jSJ6fddU4ea8iJNclw8vnihx0gkkrwX+r8opCQ6vU2id374TZwePCEbmZ2pNJDXP/OB2YNURGrkfHH5RVc/U4e7VkxTbdARuSNy4pSI3ETNETnXcDQMfu9URCZlS8GKsVVuuGxWw2wkxgqMftHVj5/++lONw3b/tRcb7p4PYggNH+/qxw0MW/yrFdNQY8z7RmSIL7u9eODVTzRj6IHvjterPmYIDefC3qYSdGAdhKkpd+Gl1TNiBrk7en348csHNc8oskJYstdv9o3sJH1LwwVIck28Oviiqx93DJ5AVCbcPbl4IvN+f9ntxSLF5oj0vr9aMQ0jB9eteuP5xZXTcW6F2xQ6zAGm0nC2g7Zm8smTQW+87m6azhxvsey5co6SgqYVbjtGDHHip7/+FG+2tmveT3liHwDu2HlATqCTiHG/DeFPRGpThMicr9fOqUPTthbV/ez0DOBg2xnVRkhHny+uud3MSZzpIE/GqCE0nK57GalJQQh3J2Cts1l+Vzy6JzJHkv68ITScLIlo3yg2N1b8KpU1Yz6QhI5NreFUMFMsVE/XO2+bytzn3LdmFuxWS9rHq4HjHqZa1xHmhJLo2CRjFxLxKU57fPi4rQdF9vCBq2///F3Na3atmCZXmWJdy7q54zF8iNOUyUR69t8AdjcSw2k4W3NWvAdQlcW6fn79BIgi8K3H/kvzfnpx3FjjxsBzdE5IYu2i+8uctnPNNhadlluH2/vQtK0F/33PLGZ5QynRIJ19dAkiGYKCyNRhUMivZFgzY7b2MkbCTPcuEBRU13mgrRvLn/sQ+9bMMpRjEqsHvCCKeLO1XbW5BwBr51yctWs0IyEdWyyQLS44RJ0xdP+1xtZCLuxtKu0WI20uEB5zgaAQ82/9wZDOM0rMh9e7/lh21ujotSCjFgGJEW+LB7vVgo6+cAUqiWhjLxBia18QRHndqjeeOwcPiRHmJ9vtas3kkyeDnt3WG2+x7Pkwt0Me/wfaurHutVZsWTYZADRzj/R+ymfa0euTW5tKmOV+R2pTL25W5rLJ/y/dzwG/gOXPfah5z3jm9nxu4RwP+T5Gs0m67mWkJttOe5j+533X1CXt0xKZw+z+fDIkon2j2NxY8atU1oz5QCHqOFnMFAvV07XePqfdasnIeCV9EQQRSTJ2IRGfosxlx/AhTty2dT/Wzqlj2rz+wdaxetcytqoYNWXm7NCgZ//J7sYmW3NWPLHgyBaqHMfh0Fe9CcVxY40bmqPVpHPtUlBN66VNoprycGWQmnIXHls4AaVOK15cOR0WntPdAJcWl0ooSEVkGyvPMXVoNaETkK9IE6fSzrA2UQktZrp3ZpkTYl2nw2bB7LoqNDc2YNeKaWhubMDsuio4bAXlHiSM3coz76stty0MiBxgFlsQiZnsLZDafbZb2XYuXc/IrBqQKHPZUV3qxLq547FrxTSsmzse1aVOlLmMqQWjogyK7FszCy+vvpx50jXRsWezsOcbq+XsfFPhtqO5sUGzxh1aZEdIFNHR66MkbyIhzDZHJIqe3dYbb7Hsud74Z33O7LoqcFy4gqQ0NvPpfuvd225vQP7/cJUuERzH4cWV09Hc2ICJo8tUvyeik0+ayTWZupd66+xk7QyRWczuzyeDGe1IrPhVIT5HJYX+/RPBTLFQvefqsluyOoZJXwRBRJIpuyAI4TjWiR4vKortePWOy3FpzRBN3GvDgnqcW1GECrdd31baLKZMoAPI7qZCtu5dvLFgKalrVHkRhpc6cW5FETNXaU9Lmxwv6ej1qeJGRvi+hUhBtXOV+ki39/pQVeJAe68PThuPO3YeiKsHN/UULnhyXubc7w/iUIcHqwZ7wdeUu/D00gbUVrphtxdUYUlDY5RWBwxyruFYGPjeqTDLnBDrOoNBAX852YuVCpuyeWkDLqwugdWYCWGG0HAgEMKh9j7NfautKobNRs5pIZGELTCEhgHz2FsgNZubaTtnlvkgGuksc55O8rVlSiL3O179BoMCvuzxor3Xh4FACCVOK26PY41bwJCGY2CmOSJR9Oz2uMpiHO7oS5s9j/yc2XVVuPOKC1TjWXp/AIa0w0BiOmbd2w0L6vHIbw+ho8+ne5/Xz6/H8+8dxV1X1pKtipM8GKOG0XAm7qXe/F1bVYy/nvKY2m/MR5L05w2j4WQxmx2J5Rfnw7osFcwcm8g2ZoqFRnuuQML+Y0auI8fji9Z1RMahdq5sMmEXYtm8Ux4fBgICLFy4aFKZK2z3DGyjksZE38lwGjb6vRMEEV1eH7w+Ab6ggBM9Xmx9/xjuurI2qbiU0b+vCdBf8BVSEh1wdoEoCAKCgojrn/kg7j7BZltcEmkn54vLjl4ffvzyQcxvGI0ylw3d3gD2tLThoXn1hiitTxienGs4nzDLnBDtOjt6fZi3aV/c86ABMISGyRYTShK0BYbQsBlJ1uZmw86ZZT5II4YLkOQzwaCA9j4fgiEBVguPqmIHc3NHqcNE1rgFCmm4wNGz2+m258r34zgOi5rfT9fYNKw/ofzONisPK8/B6z97Pzs9fua8vLtpOoaXOvN9/iTOYlgNp4No/qc0DgrIbzQFRj1UApA/IRHPuq4A12UqKDYRH2aLhRpF10a5jghoXUdkHEqi0yfddiEV+2xQG5USJvlOhtSwGe4d6xr14iWxxoAZvq+B0b1RBVe6SiqbKAgijnf3J9QnOJ19dAkiGfzBEN5sbcebre2qn99/bWH2tiaIXGKWOSHadfqDoYTmQSIM2WKCyD7J2txs2DmzzAd60ELb2FitPEaWuTQ/Zz23yhIHvuhKbI1LEIWInt1Otz1Xvl+hjE3ld5bslBK9eVkURZp7iLwhmv9pdr8xX6HnYnziWdcV+nMs9O8fL2aLhRrluRrlOgiCMA7ptgtms8+Zhuxu8uTy3sUbZ2ddY7JjgLSSGQouiQ44W9rwq54B1JS7NBmd1CeYMCo2K8/UrM1gpcYJgjAHZFOSw261kP9AAKBy2WaAxmt0SMPmJNpzI80ThDHRG5shQYQg5F8CmZ6dqii2k40i8h5aZxNE+qFxRaQL0hJBEIQxSTaeRbFNwiikqkWK6RqLgvQMOz1+3LZ1P554+zDWz69HTbkLE0eX4dmbLsP2W6ZCRDiISRBGw8pzeGrxRDx702XYtWIanr3pMjy1eCKs5AgQBKGDIIjo6PXhi65+dPT6VPObleewYUF4HgTCDtmGBfVkU2JQ4bZj681TVLZ4681TUOG25/rSiCwj+ZTSwuZ4lxe3bd2vqbpC5I4Ktx1blk1W2bktyyZnbbxGs8FGgDScHrL9nKM9t1xrniCIMJF2odxlQ3Njg2psrp9fjwdfb81Lm9vp8WPjW4ewdk4ddq2YhrVz6rDxrUOw8hzZKCLvoXW2+TC6z07QuIoH0nF8kJaSg/RFEESmiTeeFWmPur0U2ySMQSpxdkEQIULE9lum4tmbLsPE0WUUL8kxBVmJTiqHeLzLi0ffOIQNC+pR7LBi1Y6PKEuZMDSBoICBgIC1r3wia/WxhRMQCAq5vjSCIAxIrJMPXn8Ij/w2vLlV5rKh2xvAI789hCcXTwTcub56Y+MLqm3xlmWTc31JRA6gMvPGh+c51FaX4OXVl2e9XakZTkKShlMnF885Vpu4XGmeIIgwenahusSh8rsffeMQDrR14/5r88/mCoKAG2eMwZo9B+V7sH5+PQJBgWwUkffQOttcmMFnJ2hcxYJ0HD+kpcQhfREEkQ3iiWex7FHz0gZUFjtUcTKKbRK5INk4u56uR5Q5UeaieEmuKMhKdFI5RAA40NaNMwNBOYEOoCxlwriEROCHL3ys0uoPX/gYITr4QxAEg1gnH+xWCzr6fGja1oLrn/kATdta0NHno/LAMaDKTYSE0qeUoBLbxoPnOVSWODCqvAiVJY6sLTzNYCtIw6mTi+cc67nlSvMEQYTRswv+kIh1r7XKfveBtu68tbkhEXICHRC+B2v2HERIJBtF5D+0zjYXZvDZCRpXsSAdxw9pKXFIXwRBZItYa0WWPWra3oI7rxinel2+rrMJY5NsnF1P1yEBFC/JIQWZRBdZErTCbacKDIQpEEWRqVVRpCw6giC0xDr5QC3fkoMqNxESNIaIaJjBVpCGUycXz5meG0EYGz27IIpiwYxdil0QhQzN0+bCDD47QeMqFqTj+CEtJQ7piyAIo6Bnj8YMc5NdJ3JOsj4GzbPGpCDbufI8h3GVxdjdNB3BkAALz6Gm3KUSKGUpE0ZEymImrRJEZhEEEZ0ev+lbDMWyGdTyLTnIFhMSNIYyi9ltsRlsBWk4dbL9nKVxMbTIht1N0yGKIj03gjAAyjmL4/RjTLXVroKwuUaYA83uRxDmgaU18q/MgxHslZnJlq2ldUt0SMfxQ1pKnET1RT4YQRCZQs8eFTksunadbBKRCfR0lYyPQX6cMSnISnSCIOJwRx8WNb+Pb2zYi5/++lNsXtpAWcqE4Sl32TRa3by0AeUuW46vjCDyB6n//LxN+3D5+t9j3qZ9OHSyF4JgvqoJ8Zx8oHZKiUO2mFBCYygz5IMtNssJd9JwamTzOSvHxdT//x0san4fZwaCFAAkiBwTOWc98OonujGmQrG5uZ4D88GPIMyBntYAFMRYzwdyba/MTLZtbaHMoclAOk4M0lJiJKIv8sEIgsgkevZomNvBtOtkk4hMEE1XyfgY5McZEy7fWilMnjxZ3L9/f9TXdPT6MG/TPlVG5+y6Kjzw3fF0kp+IRtYEoafjjl4ffvzyQcxvGI0ylw3d3gD2tLThoXn1qCxxZOvyCPOScw2bAdYcUVMerhhhxnGWZydtDKFhssVEChhCw2YgX2xxntlgiax8ATNpONXnHO/f58u4MACkYSJlIivPLWp+P5sxJlP4E7mcA8leGh5TaDgeSGv5QRL2Km80nAqkf2ORoI5Jw0RCGHTNSus6IuOcd+/rCf/NsYevifelpOEkiNceCYKIr84MaNbq5KuklYLSsFJ71z/zQVp1lad7CGZA9yYXZDtXVm/hN1vbcf+1IkaVF+XoqggiNv5gCG+2tuPN1nbVz++/lvpiE0S6yLf+89LJByJ9kC0miMyTL7aYbHBhkMpzlk4v3rZ1P453eeXThrXVJZpgSb6MC4IwO5Hj9sWV0ynGxCCXcyDZSyJbkNbyA/LZk4P0byxIx0QmiVdfZBcIgsg08dgjac3u8QXJJhFpQRkHemzhhLTrivw441GQSXQcx8m9hSeOLsPKmWPlkohSqUWCMCIcx2F2XZWm+hHHkWYJIl0o5wiJmnJX3o4zOuGQOGSLCSLzpNMWk50jjEynxy8n4gDhoMttW/czTy/arRbmuLBbLQBI6wSRLSLHbafHH3VsKinkcZrN715oazoid+hpzWbh0dHrK8ixThQO2ba1hTyHEumFtJQ5yAcjCCJZ0mmbpTX72jl1ca/VCSIayjhQtzeQNV2Rz5I7+FxfQC6wcMD6+fWYXVeFH32nFutea8WCze/j+mc+oF7YhKGxWzjc8a1xWPdaK65/5gOse60Vd3xrHOwWMpgEkS6kOULZf379/Hrk4zCTTk/M27QPl6//PeZt2kfzYByQLSaIzJMuW0x2jjA6iZzUr3DbsWXZZNW42LJsMircdtI6QWSRyHG7ee8RzZwljU0lhTxOs/3dC2lNR+QWltaeXDwRHX2+ghzrRGGRTVtbyHMokV5IS5mFfDCCIJIh3bZZWrPHu1YniFgo40DZ0hX5LLmlICvR8TyPdw+dxH1zLkb7mQGsnVOHzXuP4EBbt+6pf4IwAv6QiCffOYy1c+rk6kdPvnMYD3x3fK4vjSDyBp7n8fx7R1Xj7Pn3juKhefW5vrS00+nxY+Nbh1TfdeNbh/DQvHqaB6NAtpggMk+6bDHZOcLoJFpdblxlMV5efbnmBGJHry/uinYEQaRG5Lg90NaN5987it1N0yGKIvN0sCCI+OrMADy+YEHGoFhVNze+dQgPfHe87j1LhUJa0xG5haW1gYCATb//K/mfRN6TTVtL6zoiXZCWMgv5YARBJEMiXRokolXoktbsB9q68egbYZtf4bZjZJkLw0udVMmLSBhlHEjS1bq54zG2qhgum1p/6aoel8y4INJHQSbRlbtsuPbSGize8gGOd3nl0xCPvnEIB9q6qRc2YVgsHHDjjDFYs+egSrt0kocg0keF2467rqyVnZN8Pp0iCALTpgiCkOtLMzRkiwki86TLFpOdI4yOVF2OpXXpxGHk72qrSzTBl0Qq2hEEkRqscXvXlbW6wXjWWC60GFSkjZo4ugw3zhiDRc3vx7RvyVBIazoit7C0tmvFNPI/iYIgm7aW1nVEuiAtZRbywQiCSIZEY1qx4mXKNfuBtm6se60VW5ZNpgQ6Imki40AdfT4MH+JETZlLc4Ay3lhuLCjWm1sKMonutNePldtbVJmba/YcxNo5dVj3Wiv1wiYMS0iEvMADzmp3d9P0HF8ZQeQPPM9hXGUxdjdNRzAkwGrhUVXsyEvnmmxKctB9I4jMky5bTOOVMCrKU4nVpQ68tHoGAkEh6epysSraEUS6SNeJWjPD8xxqq0uYVSFZsE4PF1oMKtJGrZw5VjM/J3qiOpoWE31GBJEsLJ8VIP+TKAyyGT+jdR2RLkhLmaWQ4uoEQaQPvZgWx3EQBFFjQ2JV6KL1IJFu4tVUvNXj4omtUaw3txRcEp0giOj3sTM3pSzSzJyWokAzkTqCKKKy2KEqh7157xGIIvW/Joh0IQgiDnf0peWkgBGINv+IosicD8mmRIdsMUFknnTZ4mzaOfL3zU02n1+8pxITOXEYraIdQaSLdJ6oNTs8z8XdVkYQhKzHoHJBNDsaaaMq3PaUTlTHo8Voz4gg0gXLZ91+61RaZ5sM8uOTI5vxM4pfxYZ0HB+kpeSIV1/5FlcnCCI7sGJa6+fX44FXP8FdV9YmFS/Lp/UgzfHpI5V7GY+m4tFmvLE1ivXmloJLouv0+HH0lIeZuZmpXtgUaCbShd3C456ranH3i2fLjW9YUA/b4ElXgiBSJ5/6zMeaf+gkQ3KQLSaIzJMuW5wtO0f+vrnJ9vOLV9+J6JdO2RLZIJ/85EzBsifNjQ2YXVeFN1vb5ddlMgaVC2LZ0UgbxXFcSvMzaZEwCiwtHu1gx51pnW1MyI9PnmzaYopfRYd0HD+kpcRJRF/koxEEkQzSenF303R82e1Fp8ePR984hANt3Wg90ZtSvMzs0ByfPrJxL+PRZrxzJcV6c0vB7fb6gyE88fZhrJ9fj5pyF4CweJuXNmQseKk3GDo9/rR/FpHfBEOCnLQBhLV094sHEQwJOb4ygsgf8qnPfKz5RzrJoJwP6SRDbMgWE0TmSZctzpadI3/f3GT7+cWr70T1K52IHFVeJLevIIh0kk9+cqZg2ZOmbS2475o6zVjOlwQ6ID47qrRRw0udKc3PpEXCKLC0+MTbh9G8tIHW2SaB/PjkyaYtpvhVdEjH8UNaSpxE9EU+GkEQycLzHERRxILN76NpWwsOtHUDSE+8zMzQHJ8+snEv49FmInMlxXpzR04q0XEcNxTALgDnATgGYJEoil0Rr7kUwNMASgGEADwkiuKuVD/bbrWgo8+HR984JLdh6/eHMKIsc8FLchyJdBHUKTcepGrjBJE28ukUS6z5h04yJAfZYoLIPOmyxdmyc+Tvm5tsP7949U3zNGE08slPzhR69sTCc3k9lhO1o6naN9IiYRRYWuzo82FEmTOvx3w+QX588mTTFpNfHB3ScfyQlhInEX2Rj0YQRCpQvEwLzfHpIxv3Mh5t0lxpDnJVie5eAG+LojgOwNuD/46kH8AyURQvBnAVgP/NcVxZqh8sZYB29PnQtK0FP3zhYwwf4kSZK3PZydJgUEKDgUgGp42tJaet4IpKEkTGyKdTLPHMP3SSIXHIFhNE5kmnLc6GnSN/39xk+/klom+apwkjkU9+cqaIZk/yeSwnY0dTsW+kRcIo6GmxzGXP6zGfT5AfnzzZtsXkF+tDOk4M0lJiJKIv8tEIgkgFipdpoTk+fWTrXsbSJs2V5oATxeyXTeE47hCAmaIonuA4bgSAvaIo1sb4m48BLBBF8XC0102ePFncv39/1M8XBBGdHn/WspOpX3XekLWHpadj0hKRIjnXsFnI9jyRKfLQZhhCw3l4X4nsYQgNmwUz2eICswtZ+ULZ1HAunp+Z9J2H5J2GswlpNzpZsieG8yfIjhIJYjgNpwJp0dwkab/ySsOpQPo3BknomDRMxE2i+sqiXaB1HZFxzrv39YT/5tjD18T7UtIwA/It1Bg85mwqDRvpXpLODYPuTc9JO1cA1aIongCAwUS6qmgv5jhuCgA7gCPp+HApAzRbFFJZUSKzkJYIIjtke57IFGQzMgPdV4LIDmayxWQXzE0unp+Z9E0QSki70SnU+YDsKFHIkBbNTaHa7XRB+jcGpGMikySqL7ILBEGkAtkQNTTHpw8j3UvSufHJWBIdx3G/AzCc8asfJ/g+IwBsA3CjKIqCzmtWAFgBAOecc06CV5odaDAQsYhXx6QlwqiYwRYXImQz4icRDdN9JYwI2eHcQnYhdXKpYXp+RDogO0wA5rcnyerY7N+byB/IFhOJYjT7RRomksFIOiYN5x9G0lc2IA0TZoc0nF8Umg0GMqfhQryXRHLwmXpjURS/LYrieMZ/rwA4OZgcJyXJtbPeg+O4UgCvA7hPFMUPonzWM6IoThZFcXJlZWUmvg5BZBzSMWF2SMOE2SENE2aHNEyYHdIwYXZIw0Q+QDomzA5pmDA7pGHC7JCGCbNDGibMDmmYMDukYSLXZCyJLgavArhx8P9vBPBK5As4jrMDeBnAVlEUX8jitREEQRAEQRAEQRAEQRAEQRAEQRAEQRAEQRAEQRAFQsbaucbgYQC7OY67BcDfASwEAI7jJgNYKYrirQAWAfgGgAqO424a/LubRFH8UzouQBBEdHv98PpDCIkinDYLhrkd1EOaMDzBoID2Ph8CIQE2C4+qYges1lzlwxIEYXYE4f+xd/9RcpT3ne8/T3VPj1qjwRoPI2EzCrAOVqIQee0ZY0An9+AQ/8g1CZdIzm5sIYOPhYjW63uzhoV7T8hmg70Xgn18womJZNkGC+LEGExwQhJDWJPsyj9gZNa6WIlMMBAGO/oxjIxmNJqe7qr7x6hb86N6pn9UddXz1Pt1Th+YUc/001Wf5/s8VfN0VaCxyZJK5YoK+Zz6ewpLjoXNPt9V1GLAbtSyM9gW6eL7gY5NTuvUTEU5Y1Qs5LS6yD4BXOTqfLKRcYWxBy4Jy7MkMg5EjPEFUSEnncO2BtBJzMvRac2Mc4yJdklkEV0QBGOSrgj5/oikj5z+//sl3R/H6/t+oBfHJnX4tVO66cEDGh2f0mBfUXu2DWv92l4Ci9Qql3390+ETuuH+/bXc7to6pJ9b2+vEyXYAneX7gQ4dPqHte0caGgubfb6rqMWA3ahlZ7At0iVsf9y5ZaPWnrVC5/f3sE8Ah7g6n2xkXGHsgUvC8rz3wxdruuyTcSBCjC+ICjnpHLY1gE6qV3O68562ffEp6hAi18w4x5hoH3vPzLVhbLKkl8ZO1hbQSdLo+JS27x3R2GQp4dYB9R2ZmK6dZJdmc3vD/ft1ZGI64ZYBsNHYZKk2aZOWHwubfb6rqMWA3ahlZ7At0iVsf9z04AG9NHaSfQI4xtX5ZCPjCmMPXBKW55fGTpJxIGKML4gKOekctjWATqpXc14aO0kdQiyaGecYE+2TyUV0pXJFKwu5WlCrRsenVCpXEmoVsLyZih+a23LFT6hFAGxWKleaGgubfb6rqMWA3ahlZ7At0qXe/lhZyLFPAMe4Op9sZFxh7IFLwvLMOWcgeowviAo56Ry2NYBOWuqc2sLvUYcQhWbGOcZE+2RyEV0hn9PJUkWDfcV53x/sK6qQz9X5KSB5XTkvNLf5XCa7MoA2FfK5psbCZp/vKmoxYDdq2Rlsi3Sptz9OlirsE8Axrs4nGxlXGHvgkrA8c84ZiB7jC6JCTjqHbQ2gk5Y6p7bwe9QhRKGZcY4x0T52n51rUX9PQef1r9SdWzbWAlu993B/TyHh1gH1rVnVrV1bh+bldtfWIa1Z1Z1wywDYqL+noD3bhhseC5t9vquoxYDdqGVnsC3SJWx/3Lllo87rX8k+ARzj6nyykXGFsQcuCcvzef0ryTgQMcYXRIWcdA7bGkAn1as55/WvpA4hFs2Mc4yJ9jFBECTdhkgNDw8HIyMjyz7P9wONT01rquTL9wN15TwNrOpWPp/JdYVojOnUCy2V45mZio5MTKvsB8p7RmtWdauri5XKaEgqMmwD3w80NllSqTx75Zf+noI8r2Obr6Oafa8Jb5vUZJhajBalJsM2iLPeZKnOL6eFbdGRDeVChlvh+4GOTU7r1IyvnJGKhZxWFxfvEzLcFjKMRFX7r1Gg6bKvih8on/O0pvFzUqmeTzRSn6KoYdRBq6U6w80ql/3ZY8OKX+vLnmfIp9ucynA7OlmLOzW+ZESmM0xO4jV3+xYLOZX9M0hkRAAAIABJREFUQDNlP45tzXEdYnf+LY82/TMv3v6+Rp9KhiMWVt8lNVzzGR+alpkM18tGM5khX6lUdwfkO9mKtDnyWknb945odHyqtuJz/dpeAovU8v1A/3xsktwCMfL9QIcOn8hMP/M8o4Hexq940ezzXUQtBuIXdy2mlp3BtkgXzzNa07tiyedkba4CuKR+/13pTP9tZFxpd+yhDiItfD/Qc0cnQrPI/Aqu63Qt7sT4gmwgJ/FhjgYgSfXqeyM1n/qFepbLRqNzCuYfdsnsZdfGJs8soJOk0fEpbd87orHJUsItA+ojt0D86GdYDhkB4kc/A+qjfwD2ov9Gg+2ItCCLyDLyD2Ah6gIAW1G/UA/ZyKbMXomuVK7Uwv7Wdat1w+Vv0upil0rlinw/YFUxUqlUrmhgVbduvXKDVhe7dHxqRruefF6lciXppgHOmDs+VI2OTznbz7iEcPOoxUD8oqzF1Dm4hnEIsMfCMcj3/Uwda4SJYlzO2jEb0qteFn3f19ET08w/4bRO12KO6xAVshQf5mgAGpHGOkz9Qj1pyUYa+43LMruIrpDPabCvqIFV3brxPet180MHuDwnUq9YyOk/v3e9bnrwTF7v3LJRxUIu6aYBzqiOD3MnRYN9RRXy7vU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\n",
+      "text/plain": [
+       "<Figure size 2520x2520 with 210 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib\n",
+    "\n",
+    "train_data=paddle.dataset.uci_housing.train()\n",
+    "sample_data=next(train_data())\n",
+    "print(sample_data[0])\n",
+    "\n",
+    "# 画图看特征间的关系,主要是变量两两之间的关系（线性或非线性，有无明显较为相关关系）\n",
+    "feature_names = ['CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', 'RM', 'AGE','DIS', 'RAD', 'TAX', 'PTRATIO', 'B', 'LSTAT', 'MEDV']\n",
+    "feature_num = len(feature_names)\n",
+    "features_np=np.array([x[0] for x in train_data()],np.float32)\n",
+    "labels_np=np.array([x[1] for x in train_data()],np.float32)\n",
+    "data_np=np.c_[features_np,labels_np]\n",
+    "df=pd.DataFrame(data_np,columns=feature_names)\n",
+    "\n",
+    "matplotlib.use('TkAgg')\n",
+    "%matplotlib inline\n",
+    "sns.pairplot(df.dropna())\n",
+    "\n",
+    "plt.show()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "上图中，对角线上是各属性的直方图，非对角线上的是两个不同属性之间的相关图。\n",
+    "从图中我们可以看出，RM（每栋房平均客房数）、LSTAT（低收入人群占比）、与房价成明显的相关关系、NOX（一氧化碳浓度）和DIS（与波士顿就业中心距离）成明显相关关系等。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x1080 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# 相关性分析\n",
+    "fig, ax = plt.subplots(figsize=(15,15)) \n",
+    "ax=sns.heatmap(df.corr(), cbar=True, annot=True)\n",
+    "ax.set_ylim([14, 0])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "IUhqen8LWAYM"
+   },
+   "source": [
+    "***数据归一化处理***\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "下图为大家展示各属性的取值范围分布："
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x1a3adcb410>"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "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": [
+    "sns.boxplot(data=df.iloc[:,0:13])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "做归一化（或 Feature scaling）至少有以下3个理由：\n",
+    "\n",
+    "*   过大或过小的数值范围会导致计算时的浮点上溢或下溢。\n",
+    "*   不同的数值范围会导致不同属性对模型的重要性不同（至少在训练的初始阶段如此），而这个隐含的假设常常是不合理的。这会对优化的过程造成困难，使训练时间大大的加长.\n",
+    "\n",
+    "*   很多的机器学习技巧/模型（例如L1，L2正则项，向量空间模型-Vector Space Model）都基于这样的假设：所有的属性取值都差不多是以0为均值且取值范围相近的。\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 90
+    },
+    "colab_type": "code",
+    "id": "lIZU50uyVxWm",
+    "outputId": "d4b8b9e3-09ab-4049-d014-8b545de6d1e8"
+   },
+   "outputs": [],
+   "source": [
+    "features_max=[]\n",
+    "features_min=[]\n",
+    "features_avg=[]\n",
+    "for i in range(13):\n",
+    "  i_feature_max=max([data[1][0][i] for data in enumerate(train_data())])\n",
+    "  features_max.append(i_feature_max)\n",
+    "  i_feature_min=min([data[1][0][i] for data in enumerate(train_data())])\n",
+    "  features_min.append(i_feature_min)\n",
+    "  i_feature_avg=sum([data[1][0][i] for data in enumerate(train_data())])/506\n",
+    "  features_avg.append(i_feature_avg)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "B58sJYihZtz1"
+   },
+   "outputs": [],
+   "source": [
+    "BATCH_SIZE=20\n",
+    "def feature_norm(input):\n",
+    "  f_size=input.shape[0]\n",
+    "  output_features=np.zeros((f_size,13),np.float32)\n",
+    "  for batch_id in range(f_size):\n",
+    "    for index in range(13):\n",
+    "      output_features[batch_id][index]=(input[batch_id][index]-features_avg[index])/(features_max[index]-features_min[index])\n",
+    "  return output_features \n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "Q8cLSjzGvFCS"
+   },
+   "source": [
+    "定义绘制训练过程的损失值变化趋势的方法draw_train_process"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "3Ht5-iErvCXI"
+   },
+   "outputs": [],
+   "source": [
+    "global iter\n",
+    "iter=0\n",
+    "iters=[]\n",
+    "train_costs=[]\n",
+    "\n",
+    "def draw_train_process(iters,train_costs):\n",
+    "    plt.title(\"training cost\" ,fontsize=24)\n",
+    "    plt.xlabel(\"iter\", fontsize=14)\n",
+    "    plt.ylabel(\"cost\", fontsize=14)\n",
+    "    plt.plot(iters, train_costs,color='red',label='training cost')\n",
+    "    plt.show()\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "qdvxla-waYoZ"
+   },
+   "source": [
+    "***数据提供器***\n",
+    "\n",
+    "下面我们分别定义了用于训练和测试的数据提供器。提供器每次读入一个大小为BATCH_SIZE的数据批次。如果您希望加一些随机性，它可以同时定义一个批次大小和一个缓存大小。这样的话，每次数据提供器会从缓存中随机读取批次大小那么多的数据。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "ej2xXIgwZSlg"
+   },
+   "outputs": [],
+   "source": [
+    "BATCH_SIZE=20\n",
+    "BUF_SIZE=500\n",
+    "\n",
+    "train_reader=paddle.batch(paddle.reader.shuffle(paddle.dataset.uci_housing.train(),buf_size=BUF_SIZE),batch_size=BATCH_SIZE)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "JkEt541Cl0s8"
+   },
+   "source": [
+    "# 模型配置\n",
+    "线性回归就是一个从输入到输出的简单的全连接层。\n",
+    "\n",
+    "对于波士顿房价数据集，假设属性和房价之间的关系可以被属性间的线性组合描述。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "colab": {},
+    "colab_type": "code",
+    "id": "JW2IHEVbbCI3"
+   },
+   "outputs": [],
+   "source": [
+    "class Regressor(paddle.nn.Layer):\n",
+    "  def __init__(self):\n",
+    "    super(Regressor,self).__init__()\n",
+    "    self.fc=paddle.nn.Linear(13,1,None)\n",
+    "\n",
+    "  def forward(self,inputs):\n",
+    "    pred=self.fc(inputs)\n",
+    "    return pred"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "oxD989B_cBjF"
+   },
+   "source": [
+    "# 模型训练\n",
+    "下面为大家展示模型训练的代码。\n",
+    "这里用到的是线性回归模型最常用的损失函数--均方误差（MSE），用来衡量模型预测的房价和真实房价的差异。\n",
+    "对损失函数进行优化所采用的方法是梯度下降法"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 562
+    },
+    "colab_type": "code",
+    "id": "m2as0xbvc6Ec",
+    "outputId": "18c62056-d21b-4b7b-b622-4b4b28f4ff93"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "start training ... \n",
+      "Pass:0,Cost:531.75244\n",
+      "Pass:30,Cost:61.10927\n",
+      "Pass:60,Cost:22.68571\n",
+      "Pass:90,Cost:34.80560\n",
+      "Pass:120,Cost:78.28358\n",
+      "Pass:150,Cost:124.95644\n",
+      "Pass:180,Cost:91.88014\n",
+      "Pass:210,Cost:15.23689\n",
+      "Pass:240,Cost:34.86035\n",
+      "Pass:270,Cost:54.76824\n",
+      "Pass:300,Cost:65.88247\n",
+      "Pass:330,Cost:41.25426\n",
+      "Pass:360,Cost:64.10200\n",
+      "Pass:390,Cost:77.11707\n",
+      "Pass:420,Cost:20.80456\n",
+      "Pass:450,Cost:29.80167\n",
+      "Pass:480,Cost:41.59278\n"
+     ]
+    }
+   ],
+   "source": [
+    "y_preds=[]\n",
+    "labels_list=[]\n",
+    "def train(model):\n",
+    "  print('start training ... ')\n",
+    "  model.train()\n",
+    "  EPOCH_NUM=500\n",
+    "  optimizer=paddle.optimizer.SGD(learning_rate=0.001, parameters = model.parameters())\n",
+    "  iter=0\n",
+    "\n",
+    "  for epoch_id in range(EPOCH_NUM):\n",
+    "    train_cost=0\n",
+    "    for batch_id,data in enumerate(train_reader()):\n",
+    "        features_np=np.array([x[0] for x in data],np.float32)\n",
+    "        labels_np=np.array([x[1] for x in data],np.float32)\n",
+    "        features=paddle.to_variable(feature_norm(features_np))\n",
+    "        labels=paddle.to_variable(labels_np)\n",
+    "        #前向计算\n",
+    "        y_pred=model(features)\n",
+    "        \n",
+    "        cost=paddle.nn.functional.square_error_cost(y_pred,label=labels)\n",
+    "        avg_cost=paddle.mean(cost)\n",
+    "        train_cost = [avg_cost.numpy()]\n",
+    "        #反向传播\n",
+    "        avg_cost.backward()\n",
+    "        #最小化loss，更新参数\n",
+    "        opts=optimizer.minimize(avg_cost)\n",
+    "        # 清除梯度\n",
+    "        model.clear_gradients()\n",
+    "        if batch_id%30==0 and epoch_id%30==0:\n",
+    "            print(\"Pass:%d,Cost:%0.5f\"%(epoch_id,train_cost[0][0]))\n",
+    "\n",
+    "        iter=iter+BATCH_SIZE\n",
+    "        iters.append(iter)\n",
+    "        train_costs.append(train_cost[0][0])\n",
+    "        \n",
+    "            \n",
+    "          \n",
+    "paddle.disable_static()\n",
+    "model = Regressor()\n",
+    "train(model)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "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": [
+    "matplotlib.use('TkAgg')\n",
+    "%matplotlib inline\n",
+    "draw_train_process(iters,train_costs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "可以从上图看出，随着训练轮次的增加，损失在呈降低趋势。但由于每次仅基于少量样本更新参数和计算损失，所以损失下降曲线会出现震荡。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "YC73FnkakWbY"
+   },
+   "source": [
+    "# 模型预测\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 386
+    },
+    "colab_type": "code",
+    "id": "71AiNeZccwxq",
+    "outputId": "9518e34b-cb5b-49fc-8bfd-7d3c40f3eb32"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "No.0: infer result is 12.20,ground truth is 8.50\n",
+      "No.10: infer result is 5.65,ground truth is 7.00\n",
+      "No.20: infer result is 14.87,ground truth is 11.70\n",
+      "No.30: infer result is 16.60,ground truth is 11.70\n",
+      "No.40: infer result is 13.71,ground truth is 10.80\n",
+      "No.50: infer result is 16.11,ground truth is 14.90\n",
+      "No.60: infer result is 18.78,ground truth is 21.40\n",
+      "No.70: infer result is 15.53,ground truth is 13.80\n",
+      "No.80: infer result is 18.10,ground truth is 20.60\n",
+      "No.90: infer result is 21.39,ground truth is 24.50\n",
+      "平均误差为: [12.917107]\n"
+     ]
+    }
+   ],
+   "source": [
+    "#获取预测数据\n",
+    "INFER_BATCH_SIZE=100\n",
+    "infer_reader=paddle.batch(paddle.dataset.uci_housing.test(),batch_size=INFER_BATCH_SIZE)\n",
+    "infer_data = next(infer_reader())\n",
+    "infer_features_np = np.array([data[0] for data in infer_data]).astype(\"float32\")\n",
+    "infer_labels_np= np.array([data[1] for data in infer_data]).astype(\"float32\")\n",
+    "\n",
+    "infer_features=paddle.to_variable(feature_norm(infer_features_np))\n",
+    "infer_labels=paddle.to_variable(infer_labels_np)\n",
+    "fetch_list=model(infer_features).numpy()\n",
+    "\n",
+    "sum_cost=0\n",
+    "for i in range(INFER_BATCH_SIZE):\n",
+    "    infer_result=fetch_list[i][0]\n",
+    "    ground_truth=infer_labels.numpy()[i]\n",
+    "    if i%10==0:\n",
+    "        print(\"No.%d: infer result is %.2f,ground truth is %.2f\" % (i, infer_result,ground_truth))\n",
+    "    cost=np.power(infer_result-ground_truth,2)\n",
+    "    sum_cost+=cost\n",
+    "print(\"平均误差为:\",sum_cost/INFER_BATCH_SIZE)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_pred_ground(pred, groud):\n",
+    "    plt.figure()   \n",
+    "    plt.title(\"Predication v.s. Ground\", fontsize=24)\n",
+    "    plt.xlabel(\"groud price(unit:$1000)\", fontsize=14)\n",
+    "    plt.ylabel(\"predict price\", fontsize=14)\n",
+    "    plt.scatter(pred, groud, alpha=0.5)  #  scatter:散点图,alpha:\"透明度\"\n",
+    "    plt.plot(groud, groud, c='red')\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "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": [
+    "plot_pred_ground(fetch_list, infer_labels_np)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "上图可以看出，我们训练出来的模型的预测结果与真实结果是较为接近的。"
+   ]
+  }
+ ],
+ "metadata": {
+  "accelerator": "GPU",
+  "colab": {
+   "collapsed_sections": [],
+   "name": "线性回归（基于paddle2.0-alpha）",
+   "provenance": [],
+   "toc_visible": true
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/doc/paddle/tutorial/quick_start/linear_regression/linear_regression.rst b/doc/paddle/tutorial/quick_start/linear_regression/linear_regression.rst
new file mode 100644
index 0000000000000000000000000000000000000000..73d32122d83b01831db24847a57172bec88dbfbe
--- /dev/null
+++ b/doc/paddle/tutorial/quick_start/linear_regression/linear_regression.rst
@@ -0,0 +1,358 @@
+线性回归
+========
+
+NOTE:
+本示例教程依然在开发中，目前是基于2.0beta版本（由于2.0beta没有正式发版，在用最新develop版whl包下载的paddle）。
+
+简要介绍
+--------
+
+经典的线性回归模型主要用来预测一些存在着线性关系的数据集。回归模型可以理解为：存在一个点集，用一条曲线去拟合它分布的过程。如果拟合曲线是一条直线，则称为线性回归。如果是一条二次曲线，则被称为二次回归。线性回归是回归模型中最简单的一种。
+本示例简要介绍如何用飞桨开源框架，实现波士顿房价预测。其思路是，假设uci-housing数据集中的房子属性和房价之间的关系可以被属性间的线性组合描述。在模型训练阶段，让假设的预测结果和真实值之间的误差越来越小。在模型预测阶段，预测器会读取训练好的模型，对从未遇见过的房子属性进行房价预测。
+
+环境设置
+--------
+
+本示例基于飞桨开源框架2.0版本。
+
+.. code:: ipython3
+
+    import paddle
+    import numpy as np
+    import os
+    import matplotlib.pyplot as plt
+    import pandas as pd
+    import seaborn as sns
+    
+    paddle.__version__
+
+
+
+
+.. parsed-literal::
+
+    '0.0.0'
+
+
+
+数据集
+------
+
+本示例采用uci-housing数据集，这是经典线性回归的数据集。数据集共506行,每行14列。前13列用来描述房屋的各种信息，最后一列为该类房屋价格中位数。飞桨提供了读取uci_housing训练集和测试集的接口，分别为paddle.dataset.uci_housing.train()和paddle.dataset.uci_housing.test()。
+
+前13列用来描述房屋的各种信息
+
+.. figure:: https://ai-studio-static-online.cdn.bcebos.com/c19602ce74284e3b9a50422f8dc37c0c1c79cf5cd8424994b6a6b073dcb7c057
+   :alt: avatar
+
+   avatar
+
+下面我们来浏览一下数据是什么样子的：
+
+.. code:: ipython3
+
+    import matplotlib.pyplot as plt
+    import matplotlib
+    
+    train_data=paddle.dataset.uci_housing.train()
+    sample_data=next(train_data())
+    print(sample_data[0])
+    
+    # 画图看特征间的关系,主要是变量两两之间的关系（线性或非线性，有无明显较为相关关系）
+    feature_names = ['CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', 'RM', 'AGE','DIS', 'RAD', 'TAX', 'PTRATIO', 'B', 'LSTAT', 'MEDV']
+    feature_num = len(feature_names)
+    features_np=np.array([x[0] for x in train_data()],np.float32)
+    labels_np=np.array([x[1] for x in train_data()],np.float32)
+    data_np=np.c_[features_np,labels_np]
+    df=pd.DataFrame(data_np,columns=feature_names)
+    
+    matplotlib.use('TkAgg')
+    %matplotlib inline
+    sns.pairplot(df.dropna())
+    
+    plt.show()
+    
+
+
+
+.. parsed-literal::
+
+    [-0.0405441   0.06636364 -0.32356227 -0.06916996 -0.03435197  0.05563625
+     -0.03475696  0.02682186 -0.37171335 -0.21419304 -0.33569506  0.10143217
+     -0.21172912]
+
+
+
+.. image:: linear_regression_files/linear_regression_6_1.png
+
+
+上图中，对角线上是各属性的直方图，非对角线上的是两个不同属性之间的相关图。
+从图中我们可以看出，RM（每栋房平均客房数）、LSTAT（低收入人群占比）、与房价成明显的相关关系、NOX（一氧化碳浓度）和DIS（与波士顿就业中心距离）成明显相关关系等。
+
+.. code:: ipython3
+
+    # 相关性分析
+    fig, ax = plt.subplots(figsize=(15,15)) 
+    ax=sns.heatmap(df.corr(), cbar=True, annot=True)
+    ax.set_ylim([14, 0])
+    plt.show()
+
+
+
+.. image:: linear_regression_files/linear_regression_8_0.png
+
+
+**数据归一化处理**
+
+下图为大家展示各属性的取值范围分布：
+
+.. code:: ipython3
+
+    sns.boxplot(data=df.iloc[:,0:13])
+
+
+
+
+.. parsed-literal::
+
+    <matplotlib.axes._subplots.AxesSubplot at 0x1a3adcb410>
+
+
+
+
+.. image:: linear_regression_files/linear_regression_11_1.png
+
+
+做归一化（或 Feature scaling）至少有以下3个理由：
+
+-  过大或过小的数值范围会导致计算时的浮点上溢或下溢。
+
+-  不同的数值范围会导致不同属性对模型的重要性不同（至少在训练的初始阶段如此），而这个隐含的假设常常是不合理的。这会对优化的过程造成困难，使训练时间大大的加长.
+
+-  很多的机器学习技巧/模型（例如L1，L2正则项，向量空间模型-Vector Space
+   Model）都基于这样的假设：所有的属性取值都差不多是以0为均值且取值范围相近的。
+
+.. code:: ipython3
+
+    features_max=[]
+    features_min=[]
+    features_avg=[]
+    for i in range(13):
+      i_feature_max=max([data[1][0][i] for data in enumerate(train_data())])
+      features_max.append(i_feature_max)
+      i_feature_min=min([data[1][0][i] for data in enumerate(train_data())])
+      features_min.append(i_feature_min)
+      i_feature_avg=sum([data[1][0][i] for data in enumerate(train_data())])/506
+      features_avg.append(i_feature_avg)
+
+
+.. code:: ipython3
+
+    BATCH_SIZE=20
+    def feature_norm(input):
+      f_size=input.shape[0]
+      output_features=np.zeros((f_size,13),np.float32)
+      for batch_id in range(f_size):
+        for index in range(13):
+          output_features[batch_id][index]=(input[batch_id][index]-features_avg[index])/(features_max[index]-features_min[index])
+      return output_features 
+    
+
+
+定义绘制训练过程的损失值变化趋势的方法draw_train_process
+
+.. code:: ipython3
+
+    global iter
+    iter=0
+    iters=[]
+    train_costs=[]
+    
+    def draw_train_process(iters,train_costs):
+        plt.title("training cost" ,fontsize=24)
+        plt.xlabel("iter", fontsize=14)
+        plt.ylabel("cost", fontsize=14)
+        plt.plot(iters, train_costs,color='red',label='training cost')
+        plt.show()
+        
+
+**数据提供器**
+
+下面我们分别定义了用于训练和测试的数据提供器。提供器每次读入一个大小为BATCH_SIZE的数据批次。如果您希望加一些随机性，它可以同时定义一个批次大小和一个缓存大小。这样的话，每次数据提供器会从缓存中随机读取批次大小那么多的数据。
+
+.. code:: ipython3
+
+    BATCH_SIZE=20
+    BUF_SIZE=500
+    
+    train_reader=paddle.batch(paddle.reader.shuffle(paddle.dataset.uci_housing.train(),buf_size=BUF_SIZE),batch_size=BATCH_SIZE)
+
+模型配置
+--------
+
+线性回归就是一个从输入到输出的简单的全连接层。
+
+对于波士顿房价数据集，假设属性和房价之间的关系可以被属性间的线性组合描述。
+
+.. code:: ipython3
+
+    class Regressor(paddle.nn.Layer):
+      def __init__(self):
+        super(Regressor,self).__init__()
+        self.fc=paddle.nn.Linear(13,1,None)
+    
+      def forward(self,inputs):
+        pred=self.fc(inputs)
+        return pred
+
+模型训练
+---------
+
+下面为大家展示模型训练的代码。
+这里用到的是线性回归模型最常用的损失函数–均方误差（MSE），用来衡量模型预测的房价和真实房价的差异。
+对损失函数进行优化所采用的方法是梯度下降法
+
+.. code:: ipython3
+
+    y_preds=[]
+    labels_list=[]
+    def train(model):
+      print('start training ... ')
+      model.train()
+      EPOCH_NUM=500
+      optimizer=paddle.optimizer.SGD(learning_rate=0.001, parameters = model.parameters())
+      iter=0
+    
+      for epoch_id in range(EPOCH_NUM):
+        train_cost=0
+        for batch_id,data in enumerate(train_reader()):
+            features_np=np.array([x[0] for x in data],np.float32)
+            labels_np=np.array([x[1] for x in data],np.float32)
+            features=paddle.to_variable(feature_norm(features_np))
+            labels=paddle.to_variable(labels_np)
+            #前向计算
+            y_pred=model(features)
+            
+            cost=paddle.nn.functional.square_error_cost(y_pred,label=labels)
+            avg_cost=paddle.mean(cost)
+            train_cost = [avg_cost.numpy()]
+            #反向传播
+            avg_cost.backward()
+            #最小化loss，更新参数
+            opts=optimizer.minimize(avg_cost)
+            # 清除梯度
+            model.clear_gradients()
+            if batch_id%30==0 and epoch_id%30==0:
+                print("Pass:%d,Cost:%0.5f"%(epoch_id,train_cost[0][0]))
+    
+            iter=iter+BATCH_SIZE
+            iters.append(iter)
+            train_costs.append(train_cost[0][0])
+            
+                
+              
+    paddle.disable_static()
+    model = Regressor()
+    train(model)
+    
+
+
+
+.. parsed-literal::
+
+    start training ... 
+    Pass:0,Cost:531.75244
+    Pass:30,Cost:61.10927
+    Pass:60,Cost:22.68571
+    Pass:90,Cost:34.80560
+    Pass:120,Cost:78.28358
+    Pass:150,Cost:124.95644
+    Pass:180,Cost:91.88014
+    Pass:210,Cost:15.23689
+    Pass:240,Cost:34.86035
+    Pass:270,Cost:54.76824
+    Pass:300,Cost:65.88247
+    Pass:330,Cost:41.25426
+    Pass:360,Cost:64.10200
+    Pass:390,Cost:77.11707
+    Pass:420,Cost:20.80456
+    Pass:450,Cost:29.80167
+    Pass:480,Cost:41.59278
+
+
+.. code:: ipython3
+
+    matplotlib.use('TkAgg')
+    %matplotlib inline
+    draw_train_process(iters,train_costs)
+
+
+
+.. image:: linear_regression_files/linear_regression_23_0.png
+
+
+可以从上图看出，随着训练轮次的增加，损失在呈降低趋势。但由于每次仅基于少量样本更新参数和计算损失，所以损失下降曲线会出现震荡。
+
+模型预测
+----------
+
+.. code:: ipython3
+
+    #获取预测数据
+    INFER_BATCH_SIZE=100
+    infer_reader=paddle.batch(paddle.dataset.uci_housing.test(),batch_size=INFER_BATCH_SIZE)
+    infer_data = next(infer_reader())
+    infer_features_np = np.array([data[0] for data in infer_data]).astype("float32")
+    infer_labels_np= np.array([data[1] for data in infer_data]).astype("float32")
+    
+    infer_features=paddle.to_variable(feature_norm(infer_features_np))
+    infer_labels=paddle.to_variable(infer_labels_np)
+    fetch_list=model(infer_features).numpy()
+    
+    sum_cost=0
+    for i in range(INFER_BATCH_SIZE):
+        infer_result=fetch_list[i][0]
+        ground_truth=infer_labels.numpy()[i]
+        if i%10==0:
+            print("No.%d: infer result is %.2f,ground truth is %.2f" % (i, infer_result,ground_truth))
+        cost=np.power(infer_result-ground_truth,2)
+        sum_cost+=cost
+    print("平均误差为:",sum_cost/INFER_BATCH_SIZE)
+
+
+.. parsed-literal::
+
+    No.0: infer result is 12.20,ground truth is 8.50
+    No.10: infer result is 5.65,ground truth is 7.00
+    No.20: infer result is 14.87,ground truth is 11.70
+    No.30: infer result is 16.60,ground truth is 11.70
+    No.40: infer result is 13.71,ground truth is 10.80
+    No.50: infer result is 16.11,ground truth is 14.90
+    No.60: infer result is 18.78,ground truth is 21.40
+    No.70: infer result is 15.53,ground truth is 13.80
+    No.80: infer result is 18.10,ground truth is 20.60
+    No.90: infer result is 21.39,ground truth is 24.50
+    平均误差为: [12.917107]
+
+
+.. code:: ipython3
+
+    def plot_pred_ground(pred, groud):
+        plt.figure()   
+        plt.title("Predication v.s. Ground", fontsize=24)
+        plt.xlabel("groud price(unit:$1000)", fontsize=14)
+        plt.ylabel("predict price", fontsize=14)
+        plt.scatter(pred, groud, alpha=0.5)  #  scatter:散点图,alpha:"透明度"
+        plt.plot(groud, groud, c='red')
+        plt.show()
+
+.. code:: ipython3
+
+    plot_pred_ground(fetch_list, infer_labels_np)
+
+
+
+.. image:: linear_regression_files/linear_regression_28_0.png
+
+
+上图可以看出，我们训练出来的模型的预测结果与真实结果是较为接近的。
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@@ -0,0 +1,388 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 模型保存及加载\n",
+    "本教程将基于Paddle高阶API对模型参数的保存和加载进行讲解。在日常训练模型过程中我们会遇到一些突发情况，导致训练过程主动或被动的中断，因此在模型没有完全训练好的情况下，我们需要高频的保存下模型参数，在发生意外时可以快速载入保存的参数继续训练。抑或是模型已经训练好了，我们需要使用训练好的参数进行预测或部署模型上线。面对上述情况，Paddle中提供了保存模型和提取模型的方法，支持从上一次保存状态开始训练，只要我们随时保存训练过程中的模型状态，就不用从初始状态重新训练。\n",
+    "下面将基于手写数字识别的模型讲解paddle如何保存及加载模型，并恢复训练，网络结构部分的讲解省略。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 环境\n",
+    "本教程基于paddle-develop编写，如果您的环境不是本版本，请先安装paddle-develop版本。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.0.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "import paddle\n",
+    "import paddle.nn.functional as F\n",
+    "from paddle.nn import Layer\n",
+    "from paddle.vision.datasets import MNIST\n",
+    "from paddle.metric import Accuracy\n",
+    "from paddle.nn import Conv2d,MaxPool2d,Linear\n",
+    "from paddle.static import InputSpec\n",
+    "\n",
+    "print(paddle.__version__)\n",
+    "paddle.disable_static()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 数据集\n",
+    "手写数字的MNIST数据集，包含60,000个用于训练的示例和10,000个用于测试的示例。这些数字已经过尺寸标准化并位于图像中心，图像是固定大小(28x28像素)，其值为0到1。该数据集的官方地址为：http://yann.lecun.com/exdb/mnist/\n",
+    "本例中我们使用飞桨自带的mnist数据集。使用from paddle.vision.datasets import MNIST 引入即可。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_dataset = MNIST(mode='train')\n",
+    "test_dataset = MNIST(mode='test')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 模型搭建"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class MyModel(Layer):\n",
+    "    def __init__(self):\n",
+    "        super(MyModel, self).__init__()\n",
+    "        self.conv1 = paddle.nn.Conv2d(in_channels=1, out_channels=6, kernel_size=5, stride=1, padding=2)\n",
+    "        self.max_pool1 = MaxPool2d(kernel_size=2, stride=2)\n",
+    "        self.conv2 = Conv2d(in_channels=6, out_channels=16, kernel_size=5, stride=1)\n",
+    "        self.max_pool2 = MaxPool2d(kernel_size=2, stride=2)\n",
+    "        self.linear1 = Linear(in_features=16*5*5, out_features=120)\n",
+    "        self.linear2 = Linear(in_features=120, out_features=84)\n",
+    "        self.linear3 = Linear(in_features=84, out_features=10)\n",
+    "\n",
+    "    def forward(self, x):\n",
+    "        x = self.conv1(x)\n",
+    "        x = F.relu(x)\n",
+    "        x = self.max_pool1(x)\n",
+    "        x = F.relu(x)\n",
+    "        x = self.conv2(x)\n",
+    "        x = self.max_pool2(x)\n",
+    "        x = paddle.flatten(x, start_axis=1, stop_axis=-1)\n",
+    "        x = self.linear1(x)\n",
+    "        x = F.relu(x)\n",
+    "        x = self.linear2(x)\n",
+    "        x = F.relu(x)\n",
+    "        x = self.linear3(x)\n",
+    "        x = F.softmax(x)\n",
+    "        return x"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 模型训练\n",
+    "通过`Model` 构建实例，快速完成模型训练"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/1\n",
+      "step 100/938 - loss: 1.6177 - acc_top1: 0.6119 - acc_top2: 0.6813 - 15ms/step\n",
+      "step 200/938 - loss: 1.7720 - acc_top1: 0.7230 - acc_top2: 0.7788 - 15ms/step\n",
+      "step 300/938 - loss: 1.6114 - acc_top1: 0.7666 - acc_top2: 0.8164 - 15ms/step\n",
+      "step 400/938 - loss: 1.6537 - acc_top1: 0.7890 - acc_top2: 0.8350 - 15ms/step\n",
+      "step 500/938 - loss: 1.5229 - acc_top1: 0.8170 - acc_top2: 0.8619 - 15ms/step\n",
+      "step 600/938 - loss: 1.5269 - acc_top1: 0.8391 - acc_top2: 0.8821 - 15ms/step\n",
+      "step 700/938 - loss: 1.4821 - acc_top1: 0.8561 - acc_top2: 0.8970 - 15ms/step\n",
+      "step 800/938 - loss: 1.4860 - acc_top1: 0.8689 - acc_top2: 0.9081 - 15ms/step\n",
+      "step 900/938 - loss: 1.5032 - acc_top1: 0.8799 - acc_top2: 0.9174 - 15ms/step\n",
+      "step 938/938 - loss: 1.4617 - acc_top1: 0.8835 - acc_top2: 0.9203 - 15ms/step\n",
+      "save checkpoint at /Users/dingjiawei/online_repo/book/paddle2.0_docs/save_model/mnist_checkpoint/0\n",
+      "Eval begin...\n",
+      "step 100/157 - loss: 1.4765 - acc_top1: 0.9636 - acc_top2: 0.9891 - 6ms/step\n",
+      "step 157/157 - loss: 1.4612 - acc_top1: 0.9705 - acc_top2: 0.9910 - 6ms/step\n",
+      "Eval samples: 10000\n",
+      "save checkpoint at /Users/dingjiawei/online_repo/book/paddle2.0_docs/save_model/mnist_checkpoint/final\n"
+     ]
+    }
+   ],
+   "source": [
+    "inputs = InputSpec([None, 784], 'float32', 'x')\n",
+    "labels = InputSpec([None, 10], 'float32', 'x')\n",
+    "model = paddle.Model(MyModel(), inputs, labels)\n",
+    "\n",
+    "optim = paddle.optimizer.Adam(learning_rate=0.001, parameters=model.parameters())\n",
+    "\n",
+    "model.prepare(\n",
+    "    optim,\n",
+    "    paddle.nn.loss.CrossEntropyLoss(),\n",
+    "    Accuracy(topk=(1, 2))\n",
+    "    )\n",
+    "model.fit(train_dataset,\n",
+    "        test_dataset,\n",
+    "        epochs=1,\n",
+    "        log_freq=100,\n",
+    "        batch_size=64,\n",
+    "        save_dir='mnist_checkpoint')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 保存模型参数\n",
+    "\n",
+    "目前Paddle框架有三种保存模型参数的体系，分别是：\n",
+    "#### paddle 高阶API-模型参数保存\n",
+    "    * paddle.Model.fit\n",
+    "    * paddle.Model.save\n",
+    "#### paddle 基础框架-动态图-模型参数保存 \n",
+    "    * paddle.save\n",
+    "#### paddle 基础框架-静态图-模型参数保存 \n",
+    "    * paddle.io.save\n",
+    "    * paddle.io.save_inference_model\n",
+    "\n",
+    "下面将基于高阶API对模型保存与加载的方法进行讲解。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "#### 方法一：\n",
+    "* paddle.Model.fit(train_data, epochs, batch_size, save_dir, log_freq) <br><br>\n",
+    "在使用model.fit函数进行网络循环训练时，在save_dir参数中指定保存模型的路径，save_freq指定写入频率，即可同时实现模型的训练和保存。mode.fit()只能保存模型参数，不能保存优化器参数，每个epoch结束只会生成一个.pdparams文件。可以边训练边保存，每次epoch结束会实时生成一个.pdparams文件。 \n",
+    "\n",
+    "#### 方法二：\n",
+    "* paddle.Model.save(self, path, training=True) <br><br>\n",
+    "model.save(path)方法可以保存模型结构、网络参数和优化器参数，参数training=true的使用场景是在训练过程中，此时会保存网络参数和优化器参数。每个epoch生成两种文件 0.pdparams,0.pdopt，分别存储了模型参数和优化器参数，但是只会在整个模型训练完成后才会生成包含所有epoch参数的文件，path的格式为'dirname/file_prefix' 或 'file_prefix'，其中dirname指定路径名称，file_prefix 指定参数文件的名称。当training=false的时候，代表已经训练结束，此时存储的是预测模型结构和网络参数。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 方法一：训练过程中实时保存每个epoch的模型参数\n",
+    "model.fit(train_dataset,\n",
+    "        test_dataset,\n",
+    "        epochs=2,\n",
+    "        batch_size=64,\n",
+    "        save_dir='mnist_checkpoint'\n",
+    "        )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 方法二：model.save()保存模型和优化器参数信息\n",
+    "model.save('mnist_checkpoint/test')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 加载模型参数\n",
+    "\n",
+    "当恢复训练状态时，需要加载模型数据，此时我们可以使用加载函数从存储模型状态和优化器状态的文件中载入模型参数和优化器参数，如果不需要恢复优化器，则不必使用优化器状态文件。\n",
+    "#### 高阶API-模型参数加载\n",
+    "    * paddle.Model.load\n",
+    "#### paddle 基础框架-动态图-模型参数加载\n",
+    "    * paddle.load\n",
+    "#### paddle 基础框架-静态图-模型参数加载\n",
+    "    * paddle.io.load \n",
+    "    * paddle.io.load_inference_model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "下面将对高阶API的模型参数加载方法进行讲解\n",
+    "* model.load(self, path, skip_mismatch=False, reset_optimizer=False)<br><br>\n",
+    "model.load能够同时加载模型和优化器参数。通过reset_optimizer参数来指定是否需要恢复优化器参数，若reset_optimizer参数为True，则重新初始化优化器参数，若reset_optimizer参数为False，则从路径中恢复优化器参数。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# 高阶API加载模型\n",
+    "model.load('mnist_checkpoint/test')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 恢复训练\n",
+    "\n",
+    "理想的恢复训练是模型状态回到训练中断的时刻，恢复训练之后的梯度更新走向是和恢复训练前的梯度走向完全相同的。基于此，我们可以通过恢复训练后的损失变化，判断上述方法是否能准确的恢复训练。即从epoch 0结束时保存的模型参数和优化器状态恢复训练，校验其后训练的损失变化（epoch 1）是否和不中断时的训练完全一致。\n",
+    "\n",
+    "说明：\n",
+    "\n",
+    "恢复训练有如下两个要点：\n",
+    "\n",
+    "* 保存模型时同时保存模型参数和优化器参数\n",
+    "\n",
+    "* 恢复参数时同时恢复模型参数和优化器参数。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/2\n",
+      "step 100/938 - loss: 1.4635 - acc_top1: 0.9650 - acc_top2: 0.9898 - 15ms/step\n",
+      "step 200/938 - loss: 1.5459 - acc_top1: 0.9659 - acc_top2: 0.9897 - 15ms/step\n",
+      "step 300/938 - loss: 1.5109 - acc_top1: 0.9658 - acc_top2: 0.9893 - 15ms/step\n",
+      "step 400/938 - loss: 1.4797 - acc_top1: 0.9664 - acc_top2: 0.9899 - 15ms/step\n",
+      "step 500/938 - loss: 1.4786 - acc_top1: 0.9673 - acc_top2: 0.9902 - 15ms/step\n",
+      "step 600/938 - loss: 1.5082 - acc_top1: 0.9679 - acc_top2: 0.9906 - 15ms/step\n",
+      "step 700/938 - loss: 1.4768 - acc_top1: 0.9687 - acc_top2: 0.9909 - 15ms/step\n",
+      "step 800/938 - loss: 1.4638 - acc_top1: 0.9696 - acc_top2: 0.9913 - 15ms/step\n",
+      "step 900/938 - loss: 1.5058 - acc_top1: 0.9704 - acc_top2: 0.9916 - 15ms/step\n",
+      "step 938/938 - loss: 1.4702 - acc_top1: 0.9708 - acc_top2: 0.9917 - 15ms/step\n",
+      "Eval begin...\n",
+      "step 100/157 - loss: 1.4613 - acc_top1: 0.9755 - acc_top2: 0.9944 - 5ms/step\n",
+      "step 157/157 - loss: 1.4612 - acc_top1: 0.9805 - acc_top2: 0.9956 - 5ms/step\n",
+      "Eval samples: 10000\n",
+      "Epoch 2/2\n",
+      "step 100/938 - loss: 1.4832 - acc_top1: 0.9789 - acc_top2: 0.9927 - 15ms/step\n",
+      "step 200/938 - loss: 1.4618 - acc_top1: 0.9779 - acc_top2: 0.9932 - 14ms/step\n",
+      "step 300/938 - loss: 1.4613 - acc_top1: 0.9779 - acc_top2: 0.9929 - 15ms/step\n",
+      "step 400/938 - loss: 1.4765 - acc_top1: 0.9772 - acc_top2: 0.9932 - 15ms/step\n",
+      "step 500/938 - loss: 1.4932 - acc_top1: 0.9775 - acc_top2: 0.9934 - 15ms/step\n",
+      "step 600/938 - loss: 1.4773 - acc_top1: 0.9773 - acc_top2: 0.9936 - 15ms/step\n",
+      "step 700/938 - loss: 1.4612 - acc_top1: 0.9783 - acc_top2: 0.9939 - 15ms/step\n",
+      "step 800/938 - loss: 1.4653 - acc_top1: 0.9779 - acc_top2: 0.9939 - 15ms/step\n",
+      "step 900/938 - loss: 1.4639 - acc_top1: 0.9780 - acc_top2: 0.9939 - 15ms/step\n",
+      "step 938/938 - loss: 1.4678 - acc_top1: 0.9779 - acc_top2: 0.9937 - 15ms/step\n",
+      "Eval begin...\n",
+      "step 100/157 - loss: 1.4612 - acc_top1: 0.9733 - acc_top2: 0.9945 - 6ms/step\n",
+      "step 157/157 - loss: 1.4612 - acc_top1: 0.9778 - acc_top2: 0.9952 - 6ms/step\n",
+      "Eval samples: 10000\n"
+     ]
+    }
+   ],
+   "source": [
+    "import paddle\n",
+    "from paddle.vision.datasets import MNIST\n",
+    "from paddle.metric import Accuracy\n",
+    "from paddle.static import InputSpec\n",
+    "#\n",
+    "#\n",
+    "train_dataset = MNIST(mode='train')\n",
+    "test_dataset = MNIST(mode='test')\n",
+    "\n",
+    "paddle.disable_static()\n",
+    "\n",
+    "inputs = InputSpec([None, 784], 'float32', 'x')\n",
+    "labels = InputSpec([None, 10], 'float32', 'x')\n",
+    "model = paddle.Model(MyModel(), inputs, labels)\n",
+    "optim = paddle.optimizer.Adam(learning_rate=0.001, parameters=model.parameters())\n",
+    "model.load(\"./mnist_checkpoint/final\")\n",
+    "model.prepare( \n",
+    "      optim,\n",
+    "      paddle.nn.loss.CrossEntropyLoss(),\n",
+    "      Accuracy(topk=(1, 2))\n",
+    "      )\n",
+    "model.fit(train_data=train_dataset,\n",
+    "        eval_data=test_dataset,\n",
+    "        batch_size=64,\n",
+    "        log_freq=100,\n",
+    "        epochs=2\n",
+    "        )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 总结\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "以上就是用Mnist手写数字识别的例子对保存模型、加载模型、恢复训练进行讲解，Paddle提供了很多保存和加载的API方法，您可以根据自己的需求进行选择。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/doc/paddle/tutorial/quick_start/save_model/save_model.rst b/doc/paddle/tutorial/quick_start/save_model/save_model.rst
new file mode 100644
index 0000000000000000000000000000000000000000..4c51ae1b173a8b882a498c917ca4471b453cc612
--- /dev/null
+++ b/doc/paddle/tutorial/quick_start/save_model/save_model.rst
@@ -0,0 +1,266 @@
+模型保存及加载
+==============
+
+本教程将基于Paddle高阶API对模型参数的保存和加载进行讲解。在日常训练模型过程中我们会遇到一些突发情况，导致训练过程主动或被动的中断，因此在模型没有完全训练好的情况下，我们需要高频的保存下模型参数，在发生意外时可以快速载入保存的参数继续训练。抑或是模型已经训练好了，我们需要使用训练好的参数进行预测或部署模型上线。面对上述情况，Paddle中提供了保存模型和提取模型的方法，支持从上一次保存状态开始训练，只要我们随时保存训练过程中的模型状态，就不用从初始状态重新训练。
+下面将基于手写数字识别的模型讲解paddle如何保存及加载模型，并恢复训练，网络结构部分的讲解省略。
+
+环境
+----
+
+本教程基于paddle-develop编写，如果您的环境不是本版本，请先安装paddle-develop版本。
+
+.. code:: ipython3
+
+    import paddle
+    import paddle.nn.functional as F
+    from paddle.nn import Layer
+    from paddle.vision.datasets import MNIST
+    from paddle.metric import Accuracy
+    from paddle.nn import Conv2d,MaxPool2d,Linear
+    from paddle.static import InputSpec
+    
+    print(paddle.__version__)
+    paddle.disable_static()
+
+
+.. parsed-literal::
+
+    0.0.0
+
+
+数据集
+------
+
+手写数字的MNIST数据集，包含60,000个用于训练的示例和10,000个用于测试的示例。这些数字已经过尺寸标准化并位于图像中心，图像是固定大小(28x28像素)，其值为0到1。该数据集的官方地址为：http://yann.lecun.com/exdb/mnist/
+本例中我们使用飞桨自带的mnist数据集。使用from paddle.vision.datasets
+import MNIST 引入即可。
+
+.. code:: ipython3
+
+    train_dataset = MNIST(mode='train')
+    test_dataset = MNIST(mode='test')
+
+模型搭建
+--------
+
+.. code:: ipython3
+
+    class MyModel(Layer):
+        def __init__(self):
+            super(MyModel, self).__init__()
+            self.conv1 = paddle.nn.Conv2d(in_channels=1, out_channels=6, kernel_size=5, stride=1, padding=2)
+            self.max_pool1 = MaxPool2d(kernel_size=2, stride=2)
+            self.conv2 = Conv2d(in_channels=6, out_channels=16, kernel_size=5, stride=1)
+            self.max_pool2 = MaxPool2d(kernel_size=2, stride=2)
+            self.linear1 = Linear(in_features=16*5*5, out_features=120)
+            self.linear2 = Linear(in_features=120, out_features=84)
+            self.linear3 = Linear(in_features=84, out_features=10)
+    
+        def forward(self, x):
+            x = self.conv1(x)
+            x = F.relu(x)
+            x = self.max_pool1(x)
+            x = F.relu(x)
+            x = self.conv2(x)
+            x = self.max_pool2(x)
+            x = paddle.flatten(x, start_axis=1, stop_axis=-1)
+            x = self.linear1(x)
+            x = F.relu(x)
+            x = self.linear2(x)
+            x = F.relu(x)
+            x = self.linear3(x)
+            x = F.softmax(x)
+            return x
+
+模型训练
+--------
+
+通过\ ``Model`` 构建实例，快速完成模型训练
+
+.. code:: ipython3
+
+    inputs = InputSpec([None, 784], 'float32', 'x')
+    labels = InputSpec([None, 10], 'float32', 'x')
+    model = paddle.Model(MyModel(), inputs, labels)
+    
+    optim = paddle.optimizer.Adam(learning_rate=0.001, parameters=model.parameters())
+    
+    model.prepare(
+        optim,
+        paddle.nn.loss.CrossEntropyLoss(),
+        Accuracy(topk=(1, 2))
+        )
+    model.fit(train_dataset,
+            test_dataset,
+            epochs=1,
+            log_freq=100,
+            batch_size=64,
+            save_dir='mnist_checkpoint')
+
+
+
+.. parsed-literal::
+
+    Epoch 1/1
+    step 100/938 - loss: 1.6177 - acc_top1: 0.6119 - acc_top2: 0.6813 - 15ms/step
+    step 200/938 - loss: 1.7720 - acc_top1: 0.7230 - acc_top2: 0.7788 - 15ms/step
+    step 300/938 - loss: 1.6114 - acc_top1: 0.7666 - acc_top2: 0.8164 - 15ms/step
+    step 400/938 - loss: 1.6537 - acc_top1: 0.7890 - acc_top2: 0.8350 - 15ms/step
+    step 500/938 - loss: 1.5229 - acc_top1: 0.8170 - acc_top2: 0.8619 - 15ms/step
+    step 600/938 - loss: 1.5269 - acc_top1: 0.8391 - acc_top2: 0.8821 - 15ms/step
+    step 700/938 - loss: 1.4821 - acc_top1: 0.8561 - acc_top2: 0.8970 - 15ms/step
+    step 800/938 - loss: 1.4860 - acc_top1: 0.8689 - acc_top2: 0.9081 - 15ms/step
+    step 900/938 - loss: 1.5032 - acc_top1: 0.8799 - acc_top2: 0.9174 - 15ms/step
+    step 938/938 - loss: 1.4617 - acc_top1: 0.8835 - acc_top2: 0.9203 - 15ms/step
+    save checkpoint at /Users/dingjiawei/online_repo/book/paddle2.0_docs/save_model/mnist_checkpoint/0
+    Eval begin...
+    step 100/157 - loss: 1.4765 - acc_top1: 0.9636 - acc_top2: 0.9891 - 6ms/step
+    step 157/157 - loss: 1.4612 - acc_top1: 0.9705 - acc_top2: 0.9910 - 6ms/step
+    Eval samples: 10000
+    save checkpoint at /Users/dingjiawei/online_repo/book/paddle2.0_docs/save_model/mnist_checkpoint/final
+
+
+保存模型参数
+------------
+
+目前Paddle框架有三种保存模型参数的体系，分别是： #### paddle
+高阶API-模型参数保存 \* paddle.Model.fit \* paddle.Model.save ####
+paddle 基础框架-动态图-模型参数保存 \* paddle.save #### paddle
+基础框架-静态图-模型参数保存 \* paddle.io.save \*
+paddle.io.save_inference_model
+
+下面将基于高阶API对模型保存与加载的方法进行讲解。
+
+方法一：
+^^^^^^^^
+
+-  paddle.Model.fit(train_data, epochs, batch_size, save_dir, log_freq)
+   在使用model.fit函数进行网络循环训练时，在save_dir参数中指定保存模型的路径，save_freq指定写入频率，即可同时实现模型的训练和保存。mode.fit()只能保存模型参数，不能保存优化器参数，每个epoch结束只会生成一个.pdparams文件。可以边训练边保存，每次epoch结束会实时生成一个.pdparams文件。
+
+方法二：
+^^^^^^^^
+
+-  paddle.Model.save(self, path, training=True)
+   model.save(path)方法可以保存模型结构、网络参数和优化器参数，参数training=true的使用场景是在训练过程中，此时会保存网络参数和优化器参数。每个epoch生成两种文件
+   0.pdparams,0.pdopt，分别存储了模型参数和优化器参数，但是只会在整个模型训练完成后才会生成包含所有epoch参数的文件，path的格式为’dirname/file_prefix’
+   或 ‘file_prefix’，其中dirname指定路径名称，file_prefix
+   指定参数文件的名称。当training=false的时候，代表已经训练结束，此时存储的是预测模型结构和网络参数。
+
+.. code:: ipython3
+
+    # 方法一：训练过程中实时保存每个epoch的模型参数
+    model.fit(train_dataset,
+            test_dataset,
+            epochs=2,
+            batch_size=64,
+            save_dir='mnist_checkpoint'
+            )
+
+.. code:: ipython3
+
+    # 方法二：model.save()保存模型和优化器参数信息
+    model.save('mnist_checkpoint/test')
+
+加载模型参数
+------------
+
+当恢复训练状态时，需要加载模型数据，此时我们可以使用加载函数从存储模型状态和优化器状态的文件中载入模型参数和优化器参数，如果不需要恢复优化器，则不必使用优化器状态文件。
+#### 高阶API-模型参数加载 \* paddle.Model.load #### paddle
+基础框架-动态图-模型参数加载 \* paddle.load #### paddle
+基础框架-静态图-模型参数加载 \* paddle.io.load \*
+paddle.io.load_inference_model
+
+下面将对高阶API的模型参数加载方法进行讲解 \* model.load(self, path,
+skip_mismatch=False, reset_optimizer=False)
+model.load能够同时加载模型和优化器参数。通过reset_optimizer参数来指定是否需要恢复优化器参数，若reset_optimizer参数为True，则重新初始化优化器参数，若reset_optimizer参数为False，则从路径中恢复优化器参数。
+
+.. code:: ipython3
+
+    # 高阶API加载模型
+    model.load('mnist_checkpoint/test')
+
+恢复训练
+--------
+
+理想的恢复训练是模型状态回到训练中断的时刻，恢复训练之后的梯度更新走向是和恢复训练前的梯度走向完全相同的。基于此，我们可以通过恢复训练后的损失变化，判断上述方法是否能准确的恢复训练。即从epoch
+0结束时保存的模型参数和优化器状态恢复训练，校验其后训练的损失变化（epoch
+1）是否和不中断时的训练完全一致。
+
+说明：
+
+恢复训练有如下两个要点：
+
+-  保存模型时同时保存模型参数和优化器参数
+
+-  恢复参数时同时恢复模型参数和优化器参数。
+
+.. code:: ipython3
+
+    import paddle
+    from paddle.vision.datasets import MNIST
+    from paddle.metric import Accuracy
+    from paddle.static import InputSpec
+    #
+    #
+    train_dataset = MNIST(mode='train')
+    test_dataset = MNIST(mode='test')
+    
+    paddle.disable_static()
+    
+    inputs = InputSpec([None, 784], 'float32', 'x')
+    labels = InputSpec([None, 10], 'float32', 'x')
+    model = paddle.Model(MyModel(), inputs, labels)
+    optim = paddle.optimizer.Adam(learning_rate=0.001, parameters=model.parameters())
+    model.load("./mnist_checkpoint/final")
+    model.prepare( 
+          optim,
+          paddle.nn.loss.CrossEntropyLoss(),
+          Accuracy(topk=(1, 2))
+          )
+    model.fit(train_data=train_dataset,
+            eval_data=test_dataset,
+            batch_size=64,
+            log_freq=100,
+            epochs=2
+            )
+
+
+.. parsed-literal::
+
+    Epoch 1/2
+    step 100/938 - loss: 1.4635 - acc_top1: 0.9650 - acc_top2: 0.9898 - 15ms/step
+    step 200/938 - loss: 1.5459 - acc_top1: 0.9659 - acc_top2: 0.9897 - 15ms/step
+    step 300/938 - loss: 1.5109 - acc_top1: 0.9658 - acc_top2: 0.9893 - 15ms/step
+    step 400/938 - loss: 1.4797 - acc_top1: 0.9664 - acc_top2: 0.9899 - 15ms/step
+    step 500/938 - loss: 1.4786 - acc_top1: 0.9673 - acc_top2: 0.9902 - 15ms/step
+    step 600/938 - loss: 1.5082 - acc_top1: 0.9679 - acc_top2: 0.9906 - 15ms/step
+    step 700/938 - loss: 1.4768 - acc_top1: 0.9687 - acc_top2: 0.9909 - 15ms/step
+    step 800/938 - loss: 1.4638 - acc_top1: 0.9696 - acc_top2: 0.9913 - 15ms/step
+    step 900/938 - loss: 1.5058 - acc_top1: 0.9704 - acc_top2: 0.9916 - 15ms/step
+    step 938/938 - loss: 1.4702 - acc_top1: 0.9708 - acc_top2: 0.9917 - 15ms/step
+    Eval begin...
+    step 100/157 - loss: 1.4613 - acc_top1: 0.9755 - acc_top2: 0.9944 - 5ms/step
+    step 157/157 - loss: 1.4612 - acc_top1: 0.9805 - acc_top2: 0.9956 - 5ms/step
+    Eval samples: 10000
+    Epoch 2/2
+    step 100/938 - loss: 1.4832 - acc_top1: 0.9789 - acc_top2: 0.9927 - 15ms/step
+    step 200/938 - loss: 1.4618 - acc_top1: 0.9779 - acc_top2: 0.9932 - 14ms/step
+    step 300/938 - loss: 1.4613 - acc_top1: 0.9779 - acc_top2: 0.9929 - 15ms/step
+    step 400/938 - loss: 1.4765 - acc_top1: 0.9772 - acc_top2: 0.9932 - 15ms/step
+    step 500/938 - loss: 1.4932 - acc_top1: 0.9775 - acc_top2: 0.9934 - 15ms/step
+    step 600/938 - loss: 1.4773 - acc_top1: 0.9773 - acc_top2: 0.9936 - 15ms/step
+    step 700/938 - loss: 1.4612 - acc_top1: 0.9783 - acc_top2: 0.9939 - 15ms/step
+    step 800/938 - loss: 1.4653 - acc_top1: 0.9779 - acc_top2: 0.9939 - 15ms/step
+    step 900/938 - loss: 1.4639 - acc_top1: 0.9780 - acc_top2: 0.9939 - 15ms/step
+    step 938/938 - loss: 1.4678 - acc_top1: 0.9779 - acc_top2: 0.9937 - 15ms/step
+    Eval begin...
+    step 100/157 - loss: 1.4612 - acc_top1: 0.9733 - acc_top2: 0.9945 - 6ms/step
+    step 157/157 - loss: 1.4612 - acc_top1: 0.9778 - acc_top2: 0.9952 - 6ms/step
+    Eval samples: 10000
+
+
+总结
+----
+
+以上就是用Mnist手写数字识别的例子对保存模型、加载模型、恢复训练进行讲解，Paddle提供了很多保存和加载的API方法，您可以根据自己的需求进行选择。
+