natanielruiz
2017-08-08 18a21d4b07c581a8954b08518115fb035c712b28
Added new correct cropping for training and smoothing for video.
2个文件已添加
6个文件已修改
620 ■■■■■ 已修改文件
code/datasets.py 34 ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史
code/test_on_video.py 15 ●●●● 补丁 | 查看 | 原始文档 | blame | 历史
code/test_resnet_bins.py 5 ●●●● 补丁 | 查看 | 原始文档 | blame | 历史
code/train_resnet_bins.py 26 ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史
code/utils.py 6 ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史
practice/.ipynb_checkpoints/smoothing_ypr-checkpoint.ipynb 248 ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史
practice/load_300W-LP.ipynb 38 ●●●● 补丁 | 查看 | 原始文档 | blame | 历史
practice/smoothing_ypr.ipynb 248 ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史
code/datasets.py
@@ -81,9 +81,24 @@
    def __getitem__(self, index):
        img = Image.open(os.path.join(self.data_dir, self.X_train[index] + self.img_ext))
        img = img.convert('RGB')
        mat_path = os.path.join(self.data_dir, self.y_train[index] + self.annot_ext)
        # Crop the face
        pt2d = utils.get_pt2d_from_mat(mat_path)
        x_min = min(pt2d[0,:])
        y_min = min(pt2d[1,:])
        x_max = max(pt2d[0,:])
        y_max = max(pt2d[1,:])
        k = 0.15
        x_min -= k * abs(x_max - x_min)
        y_min -= 4 * k * abs(y_max - y_min)
        x_max += k * abs(x_max - x_min)
        y_max += 0.4 * k * abs(y_max - y_min)
        img = img.crop((int(x_min), int(y_min), int(x_max), int(y_max)))
        # We get the pose in radians
        pose = utils.get_ypr_from_mat(os.path.join(self.data_dir, self.y_train[index] + self.annot_ext))
        pose = utils.get_ypr_from_mat(mat_path)
        # And convert to degrees.
        pitch = pose[0] * 180 / np.pi
        yaw = pose[1] * 180 / np.pi
@@ -117,9 +132,24 @@
    def __getitem__(self, index):
        img = Image.open(os.path.join(self.data_dir, self.X_train[index] + self.img_ext))
        img = img.convert('RGB')
        mat_path = os.path.join(self.data_dir, self.y_train[index] + self.annot_ext)
        # Crop the face
        pt2d = utils.get_pt2d_from_mat(mat_path)
        x_min = min(pt2d[0,:])
        y_min = min(pt2d[1,:])
        x_max = max(pt2d[0,:])
        y_max = max(pt2d[1,:])
        k = 0.15
        x_min -= k * abs(x_max - x_min)
        y_min -= 4 * k * abs(y_max - y_min)
        x_max += k * abs(x_max - x_min)
        y_max += 0.4 * k * abs(y_max - y_min)
        img = img.crop((int(x_min), int(y_min), int(x_max), int(y_max)))
        # We get the pose in radians
        pose = utils.get_ypr_from_mat(os.path.join(self.data_dir, self.y_train[index] + self.annot_ext))
        pose = utils.get_ypr_from_mat(mat_path)
        # And convert to degrees.
        pitch = pose[0] * 180 / np.pi
        yaw = pose[1] * 180 / np.pi
code/test_on_video.py
@@ -45,10 +45,12 @@
    if not os.path.exists(args.video_path):
        sys.exit('Video does not exist')
    # ResNet50 with 3 outputs.
    model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 6, 3], 66)
    # ResNet101 with 3 outputs.
    # model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 23, 3], 66)
    # ResNet50
    # model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 6, 3], 66)
    # ResNet18
    # model = hopenet.Hopenet(torchvision.models.resnet.BasicBlock, [2, 2, 2, 2], 66)
    model = hopenet.Hopenet(torchvision.models.resnet.BasicBlock, [2, 2, 2, 2], 66)
    print 'Loading snapshot.'
    # Load snapshot
@@ -79,6 +81,8 @@
    fourcc = cv2.VideoWriter_fourcc(*'MJPG')
    out = cv2.VideoWriter('output/video/output-%s.avi' % args.output_string, fourcc, 30.0, (width, height))
    txt_out = open('output/video/output-%s.txt' % args.output_string, 'w')
    bbox_file = open(args.bboxes, 'r')
    frame_num = 1
@@ -95,6 +99,7 @@
            out.release()
            video.release()
            bbox_file.close()
            txt_out.close()
            sys.exit(0)
        # Save all frames as they are if they don't have bbox annotation.
@@ -104,6 +109,7 @@
                out.release()
                video.release()
                bbox_file.close()
                txt_out.close()
                sys.exit(0)
            out.write(frame)
            frame_num += 1
@@ -113,6 +119,7 @@
            out.release()
            video.release()
            bbox_file.close()
            txt_out.close()
            sys.exit(0)
        x_min, y_min, x_max, y_max = int(line[1]), int(line[2]), int(line[3]), int(line[4])
@@ -136,6 +143,7 @@
        roll_predicted = torch.sum(roll_predicted.data[0] * idx_tensor) * 3 - 99
        # Print new frame with cube and TODO: axis
        txt_out.write(str(frame_num) + ' %f %f %f\n' % (yaw_predicted, pitch_predicted, roll_predicted))
        utils.plot_pose_cube(frame, yaw_predicted, pitch_predicted, roll_predicted, (x_min + x_max) / 2, (y_min + y_max) / 2, size = 200)
        out.write(frame)
@@ -147,6 +155,7 @@
            out.release()
            video.release()
            bbox_file.close()
            txt_out.close()
            sys.exit(0)
        out.write(frame)
        frame_num += 1
code/test_resnet_bins.py
@@ -46,8 +46,11 @@
    gpu = args.gpu_id
    snapshot_path = os.path.join('output/snapshots', args.snapshot + '.pkl')
    # ResNet50 with 3 outputs.
    # ResNet101 with 3 outputs.
    # model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 23, 3], 66)
    # ResNet50
    # model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 6, 3], 66)
    # ResNet18
    model = hopenet.Hopenet(torchvision.models.resnet.BasicBlock, [2, 2, 2, 2], 66)
    print 'Loading snapshot.'
code/train_resnet_bins.py
@@ -91,9 +91,13 @@
    if not os.path.exists('output/snapshots'):
        os.makedirs('output/snapshots')
    # ResNet50 with 3 outputs.
    model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 6, 3], 66)
    load_filtered_state_dict(model, model_zoo.load_url(model_urls['resnet50']))
    # ResNet101 with 3 outputs
    # model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 23, 3], 66)
    # ResNet50
    # model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 6, 3], 66)
    # ResNet18
    model = hopenet.Hopenet(torchvision.models.resnet.BasicBlock, [2, 2, 2, 2], 66)
    load_filtered_state_dict(model, model_zoo.load_url(model_urls['resnet18']))
    print 'Loading data.'
@@ -109,15 +113,15 @@
    model.cuda(gpu)
    criterion = nn.CrossEntropyLoss()
    # optimizer = torch.optim.Adam([{'params': get_ignored_params(model), 'lr': args.lr},
    #                               {'params': get_non_ignored_params(model), 'lr': args.lr * 10}],
    #                               lr = args.lr)
    optimizer = torch.optim.Adam([{'params': get_ignored_params(model), 'lr': args.lr},
                                  {'params': get_non_ignored_params(model), 'lr': args.lr * 10}],
                                  lr = args.lr)
    # optimizer = torch.optim.SGD([{'params': get_ignored_params(model), 'lr': args.lr},
    #                               {'params': get_non_ignored_params(model), 'lr': args.lr}],
    #                               lr = args.lr, momentum=0.9)
    optimizer = torch.optim.RMSprop([{'params': get_ignored_params(model), 'lr': args.lr},
                                  {'params': get_non_ignored_params(model), 'lr': args.lr * 10}],
                                  lr = args.lr)
    # optimizer = torch.optim.RMSprop([{'params': get_ignored_params(model), 'lr': args.lr},
    #                               {'params': get_non_ignored_params(model), 'lr': args.lr * 10}],
    #                               lr = args.lr)
    print 'Ready to train network.'
@@ -147,7 +151,7 @@
        if epoch % 1 == 0 and epoch < num_epochs - 1:
            print 'Taking snapshot...'
            torch.save(model.state_dict(),
            'output/snapshots/resnet50_binned_RMSprop_epoch_' + str(epoch+1) + '.pkl')
            'output/snapshots/resnet18_cr_epoch_'+ str(epoch+1) + '.pkl')
    # Save the final Trained Model
    torch.save(model.state_dict(), 'output/snapshots/resnet50_binned_RMSprop_epoch_' + str(epoch+1) + '.pkl')
    torch.save(model.state_dict(), 'output/snapshots/resnet18_cr_epoch_' + str(epoch+1) + '.pkl')
code/utils.py
@@ -70,5 +70,11 @@
    pose_params = pre_pose_params[:3]
    return pose_params
def get_pt2d_from_mat(mat_path):
    # Get 2D landmarks
    mat = sio.loadmat(mat_path)
    pt2d = mat['pt2d']
    return pt2d
def mse_loss(input, target):
    return torch.sum(torch.abs(input.data - target.data) ** 2)
practice/.ipynb_checkpoints/smoothing_ypr-checkpoint.ipynb
New file
@@ -0,0 +1,248 @@
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import imp\n",
    "import cv2\n",
    "\n",
    "utils = imp.load_source('utils', '../code/utils.py')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "video_path = '../data/video/SGT036_2016_07_25_pivothead_AVI.avi'\n",
    "bbox_path = '../data/video/annotations/SGT036_childface.txt'\n",
    "\n",
    "annot_path = '../output/video/output-SGT036_resnet18_cr_epoch_1.txt'\n",
    "output_string = 'SGT036_resnet18_cr_epoch_1_flat_smoothed'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-6.069214 -0.831665  0.53318  ..., -3.836042 -3.868275 -2.377155]\n",
      "(8508,)\n",
      "(53464,)\n"
     ]
    }
   ],
   "source": [
    "fid = open(annot_path)\n",
    "bbox = open(bbox_path)\n",
    "list_frames = []\n",
    "list_y = []\n",
    "list_p = []\n",
    "list_r = []\n",
    "list_x_min = []\n",
    "list_x_max = []\n",
    "list_y_min = []\n",
    "list_y_max = []\n",
    "\n",
    "for line in fid:\n",
    "    line = line.strip('\\n')\n",
    "    line = line.split(' ')\n",
    "    list_frames.append(int(line[0]))\n",
    "    list_y.append(float(line[1]))\n",
    "    list_p.append(float(line[2]))\n",
    "    list_r.append(float(line[3]))\n",
    "    \n",
    "for line in bbox:\n",
    "    line = line.strip('\\n')\n",
    "    line = line.split(' ')\n",
    "    frame = int(line[0])\n",
    "    x_min, y_min, x_max, y_max = int(line[1]), int(line[2]), int(line[3]), int(line[4])\n",
    "    list_x_min.append(x_min)\n",
    "    list_x_max.append(x_max)\n",
    "    list_y_min.append(y_min)\n",
    "    list_y_max.append(y_max)\n",
    "    \n",
    "frames = np.array(list_frames)\n",
    "y = np.array(list_y)\n",
    "p = np.array(list_p)\n",
    "r = np.array(list_r)\n",
    "x_min_arr = np.array(list_x_min)\n",
    "x_max_arr = np.array(list_x_max)\n",
    "y_min_arr = np.array(list_y_min)\n",
    "y_max_arr = np.array(list_y_max)\n",
    "\n",
    "print y\n",
    "print y.shape\n",
    "print x_min_arr.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done\n"
     ]
    }
   ],
   "source": [
    "window_len = 6\n",
    "pad = window_len / 2\n",
    "window = 'flat'\n",
    "\n",
    "s = np.r_[y[window_len-1:0:-1],y,y[-2:-window_len-1:-1]]\n",
    "t = np.r_[p[window_len-1:0:-1],p,p[-2:-window_len-1:-1]]\n",
    "u = np.r_[r[window_len-1:0:-1],r,r[-2:-window_len-1:-1]]\n",
    "\n",
    "xa = np.r_[x_min_arr[window_len-1:0:-1],x_min_arr,x_min_arr[-2:-window_len-1:-1]]\n",
    "xb = np.r_[x_max_arr[window_len-1:0:-1],x_max_arr,x_max_arr[-2:-window_len-1:-1]]\n",
    "ya = np.r_[y_min_arr[window_len-1:0:-1],y_min_arr,y_min_arr[-2:-window_len-1:-1]]\n",
    "yb = np.r_[y_max_arr[window_len-1:0:-1],y_max_arr,y_max_arr[-2:-window_len-1:-1]]\n",
    "\n",
    "if window == 'flat':\n",
    "    w=np.ones(window_len, 'd')\n",
    "else:\n",
    "    w=eval('np.' + window + '(window_len)')\n",
    "\n",
    "y = np.convolve(w / w.sum(), s, mode='valid')[pad:-pad]\n",
    "p = np.convolve(w / w.sum(), t, mode='valid')[pad:-pad]\n",
    "r = np.convolve(w / w.sum(), u, mode='valid')[pad:-pad]\n",
    "x_min_arr = np.convolve(w / w.sum(), xa, mode='valid')[pad:-pad]\n",
    "x_max_arr = np.convolve(w / w.sum(), xb, mode='valid')[pad:-pad]\n",
    "y_min_arr = np.convolve(w / w.sum(), ya, mode='valid')[pad:-pad]\n",
    "y_max_arr = np.convolve(w / w.sum(), yb, mode='valid')[pad:-pad]\n",
    "\n",
    "pose_dict = {}\n",
    "bbox_dict = {}\n",
    "for idx in xrange(len(frames)-1):\n",
    "    pose_dict[frames[idx], 'yaw'] = y[idx]\n",
    "    pose_dict[frames[idx], 'pitch'] = p[idx]\n",
    "    pose_dict[frames[idx], 'roll'] = r[idx]\n",
    "\n",
    "for idx in xrange(len(frames)-1):\n",
    "    bbox_dict[frames[idx], 'x_min'] = x_min_arr[idx]\n",
    "    bbox_dict[frames[idx], 'x_max'] = x_max_arr[idx]\n",
    "    bbox_dict[frames[idx], 'y_min'] = y_min_arr[idx]\n",
    "    bbox_dict[frames[idx], 'y_max'] = y_max_arr[idx]\n",
    "    \n",
    "print 'Done'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done\n"
     ]
    }
   ],
   "source": [
    "video = cv2.VideoCapture(video_path)\n",
    "width = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))   # float\n",
    "height = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT)) # float\n",
    "\n",
    "# Define the codec and create VideoWriter object\n",
    "fourcc = cv2.VideoWriter_fourcc(*'MJPG')\n",
    "out = cv2.VideoWriter('../output/video/output-%s.avi' % output_string, fourcc, 30.0, (width, height))\n",
    "\n",
    "txt_out = open('../output/video/output-%s.txt' % output_string, 'w')\n",
    "\n",
    "for frame_num in xrange(10000):\n",
    "    ret,frame = video.read()\n",
    "    if ret == False:\n",
    "        out.release()\n",
    "        video.release()\n",
    "        bbox_file.close()\n",
    "        txt_out.close()\n",
    "        sys.exit(0)\n",
    "        \n",
    "    if (frame_num, 'x_min') in bbox_dict.keys():\n",
    "        x_min = bbox_dict[frame_num, 'x_min']\n",
    "        x_max = bbox_dict[frame_num, 'x_max']\n",
    "        y_min = bbox_dict[frame_num, 'y_min']\n",
    "        y_max = bbox_dict[frame_num, 'y_max']\n",
    "\n",
    "        yaw_predicted = pose_dict[frame_num, 'yaw']\n",
    "        pitch_predicted = pose_dict[frame_num, 'pitch']\n",
    "        roll_predicted = pose_dict[frame_num, 'roll']\n",
    "\n",
    "        # Print new frame with cube and TODO: axis\n",
    "        txt_out.write(str(frame_num) + ' %f %f %f\\n' % (yaw_predicted, pitch_predicted, roll_predicted))\n",
    "        utils.plot_pose_cube(frame, yaw_predicted, pitch_predicted, roll_predicted, (x_min + x_max) / 2, (y_min + y_max) / 2, size = 200)\n",
    "        out.write(frame)\n",
    "    else:\n",
    "        out.write(frame)\n",
    "        \n",
    "print 'Done'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda root]",
   "language": "python",
   "name": "conda-root-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
practice/load_300W-LP.ipynb
@@ -2,7 +2,7 @@
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
@@ -21,7 +21,7 @@
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
@@ -33,16 +33,16 @@
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "execution_count": 128,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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YJzeEIf58pqsjmg8XYAiCcYajC1Z9J7DpefycaLsM7qh7/DJszVSOJP7aSRT0HuF7jvqrSm9\nBR89CZ+lwCFhQ8IPTWm7rsE5heCH+g+NwnHiHNsmh4ESwZCdIERQHh3rT7k719PaSLzp1Qz5I2se\nQeJpC7Z1JepNphJxAws+taliuqnx62lvSAB7g1ArH5AaigTz2OpP97iAz2DP1ikI8JtKqQj8r0OH\n5nMi8tTw/mXg1lu+/BmYiFBah9cl9915N1//hjfylrf8EtEbCq2GuFeRJGwmxA3fHnL5cUOe6aEA\nZz6f0zcritJSFQXL+QKnUtYsBI/V4Iay5Fw+C1VRIDFtjksrfROKSCkNhT7CbDbLNRTek/qExEQR\nE/vTXJB15eplXB9wkym7sxnl2T2WBcwfeSyn61Q8JeIQtM2S6SgJdIbeWLt5vsN4PCb47hkVh2zQ\niXNu6AeRVZ0pJcK6pXsS3CCZds5hC7NBQuuVet2oBdi0YRPjAUNKgRB6Tq5fw5qCkU3sbE2zjsHq\n03DOKUh6o2Rcy7RziJFQ9rRP4mkWR5OSB8OmGcva1DMgeX6xfxZ3240T+dMQDaL5N8GerVN4vYg8\nqZQ6C/yGUupPbnxTROQztW9/ts99eK5MScpxeRTOzHb469/xPawOOn79N36XkTU4Z9A6Y+RNKksN\nkZ5KmeEa2OW6dKy6jq5dEfoVs/Euu7s7dKOKo6ODXDNgc4sy4wwCQ3GL2fAJCjYqQj+oG9eS4q7L\naT0Rtala1ErRdz0pRPohexBjzJLdvmN/9y6293ZYOtjamqC00PuOaoDn64KldSp08xAXtW60qjGu\nQGJAuGEC2qFSj9OiJ6PNJnMCbHou2kxe3FR+XRTFxhGsYX7f53oFpxU+BBCFLizT2QR99YDm+ISq\nGtMFxWrZs1WPkRRzezK6XFEwELYxRpRZt54HhjBQpVP59brtex53i3MRJYKWXI+Sw4TTxj5DC5nP\nfDOJ+8zvwc2NguTTsY9fAE5BRJ4cfl9RSv0i+XFxTyulLojIU0qpC8CVz/DdZ/Xch+fKYoxoA6XK\nBNsdsz3+0x/4AfYmMz754KNAzjQIgZjWrbcZHEMm35QSSILSgtHCbGtEXVZsbW3lCkk3RpMbsWQ2\n3GXikkH6rAf9AdwgrFGU64q/th/IMDfUHhQDekj4QYzTti2zotys3JbIbHsLZxW+bZivWrSRwcEl\n9CAOAvADlE+QSamhmq/telKyFFbT9R6NgDIbmXJVVkMdRJYzR/ED+hhqMVAblOOHFmxd14HOTgFO\n27CvP6eUylJvt1Z6CsZqZtMRi/mK5WqOULMoG7pJiR1lJ6jItSNanXZI9kMa1Ayy6/Xra/J47ZDW\nRO4pMZkLpDKqWNfVrImDT4MeBlPPnOPPMPlsSOFT/n+m3TpZ+Gzsc3YKSqkxoEVkPvz99cDfB/4f\n4D8A/uHw+63PxYF+rnYj1L2pffY6q2A1CsEx6AEclFsF3/e938NTl69QmofouoZ20w1Jnd5oJhOG\nxhi0DAy+NZzZmREiWO0IoSclRV0WlEVead3QwKSTuCnUCSHkRq5DF2MR2cD4pmnx3lMU1Wb/VVVR\nFBCGB7Ts7OxQDJWLXmsKY7n34p0cPv00GHiyOebEGebzOUq5mwQ7wCbFCvm5Gk2/yuKfsmTVdhRD\neLFsWkZVuenVuIb/Wmt8OwiWhmxKOVRuamFTgm2tJcppJ+l1j8J1XcVoNKJZnWBswaprsS6z8tNx\nxZmdGb69Qtd0xFDgvRA8aBUZ1xU+eUIbMvFoLQnZFG8pGSa9Wes+1k1TT2slci+JHt+3OFMAgRQF\nNTyJLUlAwugmxLO+v/I43pCZ4FM5g0zgyjDuNz/iMNtnQQo3PEHqmdtWfGZn9f/Xng1SOAf84jDR\nLPAzIvJ2pdR7gJ9TSv0N4FHgrz77w3z+LOpcmINoTIqUyuAKxfn9Hca1o1kd8ehjD5+2PJfcPVnr\nhNIRbQ3GCD4pVJS8ChOxaCwRrRVJa8QZWh83TH3newJ5VV/DbK0yc76eoG3bEkIgDs1V1r0LtLYb\ndr7rOooyr/rWnBKqezt7RB+5duU6ujQkB08fXGG5bJhMq1zkRV6xjcl9ItAKSbmsO6KI5KrL7ACE\n1XyeHwPXe+qqxnDap2A9PsBNq773OUOyLhsOIVAOhOsaLaz7NEDOWoyqmpQiTil0Sjht2aor1Ewg\neJ6+0tC2Lc2qYzraQiQRQ0IbS1EoQkobDiOEQGEsbgjD0sARrdu85fbpNzg23+AKMqmoXa68lUiS\njASty86x7/sh/DnlgJQ+zWqsHd6NZmx2BkN0NjR5ucH+zPDyzfY5OwUReQj4kk/z+nXgjc/moP51\nWhycc368lyCxRwxoI4xGJX2f+yca4zby4+wcIimFTZOQ6Lv8MNKYn92AaIxeP5xVYY1G9xlZ9H4I\nO4rcKEQzsPrq9KGvuRJxYMqlH0jOLBmWIcUmIrlM2BZ0Tcu4NqekZBCuXr7Ocr5ky26ze26PfmvK\nYZto246qqjb7WasO1/AZ2OglVp1s4H1ZjxGlqKsiOwvrbpIMr3UEcXhilHZDWi3EDTCOMebuTEP4\nsj7ftZNbLBZsVyVRwCmQEEgKbIqMC4Pd2eHo2NO3C0KIGfUgxJhXeqMVyYfNODjnkJgIMZd0fyZb\nT+CiSHTtHF0LzWp4jN2AEoxRSBxS1Faj6LPAiUEJOjwiYP2jPmV/QhpI6U9/ELf+GKdP2cRz6FA+\n7xSNz7Wl025oaIaHcugIw2Ph0gB1byxQWq8EIXpsKggxOwut1ulQ0EahJKIkEmPaFOJ0bUvX59h7\nXE3zxJBTMU03VEeuMwFrmJpXvUyirbXyMQrKZZXgZDIhdD2HqyU7d9zB4mhFd3LC3uwMu2f2qM6f\nxUjgyqLlySeeJidmhVXbnLZEN6ct0Y0tsCmLvPq+ZzQaEXw+vz4kaptRgNaaqiw3xx9jRAbhEGno\nnITKD0AZzsU4PciXc32Fc45y2Ebf9yRrKAtH5ewm29LFFiuKalwxGhcct8MzKUTjXA1EfB/xqUOG\nsGtdh5En4c26hI2QS05VoyEEhMB8ccilS5dyIZW2TCYjvO/RBpTknpLrhrbrkMhaizZnMvrQuR4l\nDYKvtSn92SD+ZwkfbuAznulYnpndfDb2eeIUckOMbMPvjRisQOtTrfxnM3XDaiwiFGn9tyIqi8rl\ndDgJxBDRvspP7Yk9Skdk6KRjdJUbo7QRp0uS0kjMIYGyWUY97yt637JatSyXc5L0VFXBbHuCtRrp\nI6vl8KSk0dAEQ2lckbX5EmKuXlQa5yzGaMQmRLIwJlpFDD3R/3/svUeM7Ft+3/c56Z8qdbzppQlv\nhmFMakwStAgGWYYWBixAXBky7J3llQDBW6+8kleGV1oatqCFbQje2IAt2ARhk7SHMkmRMsUZa94M\nX3439O1UXfVPJ3px/lXd9848vjuBYJoDXHTfqu6uqn/4nV/4hp7tYBEu0aiKslxxc/0ORVnx1k9+\nGVMpLtrnaA1lcFxftRkqrPzUqXfTe1AobVAolOwozATCEYKu3QJQmTLL0sUdIi/Rj32mU5caqXKQ\nC8FN2VRuYAqtciNQGmLw2NFTFvW+xBj63ExdX294fnHNarXicLmkqpZEb5GFp/cbTKk5PT2mXQ/Y\npLHCItSUiQTF2iX80HH/pKTUCmkdUmoCgqRMNpQVGdvgYwYCaa3obU9jBGfhMf/0f/p1/vE/+Wf4\nVHF8ekRVlYz9iBYFDx+uWJQly7JgMSuZ1QX37x/z4OE9qiIrbdWl5vhoSVVqjMr6CUoLyvgge3p6\nS0px8r0opx6DJsoNUheQDDGI7AGBQpL5MnaHdwDGicMRUpyatbcZSJqmKoW67dv4P2svyb9Ma7er\nwO1sey+5HjyRRIiebbcBJdHGYEdLmjAO2+2W8/PnaC05PllxcnJEiJ5h6Egp7Jt5d3fqvUiIVhDz\njTVGT4oCZXSWhJtGhHESFinLkrPnT3nw+bd5cvYE4x2PHn2OIOD66oIbe0OvE5u2I0S4uriZNA8E\nIplsxJIM3iZstJkenHa0ZonUMqfyMeRuiYvsDGOMqUheMowBJUugQ0tNVVQvUKfdMKKUJwS/RyvO\nZrO97iOQRWK6jouzMw4PDzk+OuDw8JCyMviQm5XzRc1ytZgmLYGiyIIpfvLJGMcxy+AXeoKPA5O5\n6w41KqXEh8x03bFQpZR0vmKMDS41FPUBzy46EBuqokETWH/4nALQJOzYs1jMp/GxpTbFXhDm8HDF\nYjmn0IqyMhwcLHnzOG9exhjm8zmz2YzFYsHOFq6koGkajCnzKDREJGo/1hU7mbsp6xoH9mSsSjC5\niIW9zd9o9F7kRg8vZi1/0vpRUPiMdbfuvls/72v35HDe040DpijyjigF1jm87Tk7e8ZiMeP45BBr\ns0X7MPZTXar38/qdotEOK+Ccy2lwDAiZyVSdn3oLQqGNpkjQVA3eRW6ub1gu5ywWC1SC5eoUXZec\nXV0RcWyHgZswcrVeA6CpKWQ9ya2NeB/YXl9lEFJV0cwUVZl5ByIGfLAM1jFbNbmkcC6n6zYzQLUu\nqaoa5wQ+dBhTYEyBmOrkzP23OJcZnndVqXaalFVVcXR0NP18IIY8lRj6NqfnKULwGSIislmOUgY1\n3dDGKCojaNc3xMmsdV/uEYgB5PS6u9ffAdL2EwVX8jN/7a/TNF/m+eUGUymapuLyfM3H73/CJ1eP\nESGyWd/gpOHD846kPM1sRtj0KOVRyhE/uZls9ASRLIB72lyx2eTPsloevnActNY8mDcsFzPqwiBi\nQJL1KQ4ODqZRrWCxWFBOEPLRTxtJYZglhXXZw9KnSIgRnyL9OGD9i1ORz1o/Cgqfse6OnXY7eMYM\n5AvJh0x5DTHzCKyPKF3hBs/N+oqqKjg9PcUUCmsH+n7cS5vdPz4G2I81d9/v6lSbAs18hvWBru+z\nsarWiEnBd1y3UFd0XcflxTlvPXoD6wYWVUPRFPTOc321pm7yjV42Sw7Xnnc/eh/RB67ON9iJ07Bt\nbxAi0TQNTdMwayTHx4fMZjWkSKELioUijANRiFzvd46PP3qCHSNPHj/n4OCAt956i9lyJPpIoUvC\n5N2gpKauKpTKGhDGmEz/nm7aYRho25amaTJU2mRFpBgypVymiBW5bNJaUFUF3dYiRbaLyzh/RfCJ\ncXDEqZ+RJpXtRL5RhE97sVngjnxbPr+VFXzxc2/z8z/9GtYn0Nmd248gouLKblBScnF+yZOn5zw5\nz1oeT5+fcXX2mO12y3rTMljHps/6EKMLdKOjXS+R4oSUBBc3U3aimMqJnpl5TFMbZPSESf6/aRqq\n2Zx+GAhScniUdR4u19cZDFdmsd5VytdBOw6owuCJuBRz4NAaP/8MYNWd9ZciKNy9ab8DT/49/O7d\nr3ur84mQ46aJwc4HITemAoP1jNZzdb2lnsPByYJusLSdo+u3U2TPaD2lFOM40rY9JycnAHuG5E4u\nvaqylt52uyWJLO3Ozgwm5QxEThz+1WKG1Jqh6zk6OuD4+IgwOkxZ4GPi+vkZfojMZjUnJwcUhwtu\nbMHv/Itv88E7n0xTAEnXdcznDV/60peo6uwAZfvAh+894eR4RTMraCpFiBZSrmWbxYLgJTFe8O1v\nvc842gzWmtCYQijW1y2Hh8cIDFpPTB/hc+NwHF+AcGd685Qek5WWxUS80gKMLtiSGO3ANvZYm/sS\n4xhQCqRJhJibsEVRTWNSnUeGIk0061vwzzAM2aVquld2186hkhwZyWFjMg9BZwcnvCJFzX2hEFHg\nDucMb72GR2CBKBVajLTbnk3b4SPEJDh7fsl7H37E5eUl6AOePjnn2dNzNpsNVV3ifMvF5VMuLy8Z\ndcfgFJqE8HksfNlZxMaR0Axa8sFmQ9nUWAtJlIRNQBlL2Y4TYVCTJHTWYuqKJE1m965fvanwlyIo\n/GmunXJQSh4fxn2XHfJXH6DtHNvOIQ2Mo2AY4OKiRYQRKRd03XbCFDg2my3GFFRVg3PDZCUn9n2L\nXYd+Z66iEKAVQkpubra4GKgrTaENlRSs25axb3lw/xExeZyz2SDWSdZXN5wenHL/9JTj40Oeb9cU\n0tBeb+m2PU0zoywNddnw1ltvsFjMePLkSU7FlUIqGFpLXRqIIjP4hMQoQd9tKMyMB/fuc3PVYkzJ\n8UlWqZo3C/p+pB9GhtZSTjWyUgptJG1/O9vfgZh2kwuAymhCzGUZwaNTImiHG0aGocPKahJeCazX\na0ARCpXFZswCKTPNOUOZJ3i6EOys+e5yWO4C0rz3GBRFgoJIlDDabS4tKEAIKjNBn7UgVJqkFFGq\nKVsE5hUxrnAhs1p58yHx3/xJrLXcpBGjK4IXWDcQ4kCIW548e59vffvrvP/ON9EIZBBsbgZGXyLq\nE6rVQ6Rp6Cf+zfLggPl8jpt6M1VT88bBfa6vrxmd5fDwkOXhAaYoiCJnQ68HxX/07/+7r3TN/ygo\nfMZ6QQZt0iTYBYUQAjebnqt1iw+S9Wbgpn3KaB3b3vPmg4N93SiE4OLiiqIo9s7LYez3iks7pSVg\nn6GoSbPBWU/ftdRlRRkjRpvsceED3mZrc+dHhr5Hp6y34DpLXVa89vARMgjWF5c8v3jOs7Mb4mB5\ncC8LsJSl4fDwEKlgvb5CCUm7bYkucnxywGa9wbue6vUTFssGJX2GARPphw2rgyU/87M/zdX1ZVZY\nFi0hVEBujA2DZRHy+DTlpBYhbsePOyzBrozI+osRkQRaZBFX5y0pZL5FVVV0sUAKh9EFUmjqusKY\nzPcgyf2NH2PMo2GRsuVfFOycqXeBWE7Mw12ZOHqJDRqXJCFGVFkDk3NUlIgApJjH1yll3MIEYB4n\nHIIC6oncJoSg0BqtZ4xkN6yUBEJUjG5NxPJgvuInXv8prr9wTbvpMKkG5pjZ68yOf4zy8HME2TCb\nDHyklOjCTKpZmYxm/O11eleLY/e55t8D4PFHQeEV1i4Q3OXg79yM27Yn+MRyccCmt6yvrrE+azse\nHDQoJfE+7LUAFovFdKOHfYNxPp/vRUV26L4sDCLw1pFiwkzjpdIY1JRFhBBIE6nJGINIgVrf1sqH\n8wPKsuT8/AxPTyoUtrfMmoaRkrbd0DSnWDdQiOIOHsJTmpqqrAFLXWTORZExx7le10DSBBdoZnM+\n+vgGIS0n92rqoiTYgWADPnqMNCg8KUaCHUmy2Os1VlXFYrEAuAM2Gifwk0EkMIUm2IysLIqCpxdZ\noNdbOD9vWa6O8shWS6JQCG7xCS/8k4no097U5mXGpxACJwxeGrwwRBmxwU+TCYWgABFIkzmvmkhV\nISa0FlgyTwQgOQsxUpgiD9StRThDLWZTiRqQYaC3CdF5nrz3IWL9u8zNjOPVIw6PjvFKIeuAWUBS\nimMhf9IAACAASURBVEUIaJ1FeXo7IgpJqnSGzZOvm+B8Hg0T0FLtsRTXxV8x1+m7a7fbvnzCP30p\nECOQpvmwIsWClHoQQ655J3hTIJGUxBMZvcU6l01VtGV1dIBuZ6yvLJURVGWWXZNCE5Kj3QwsFjOq\nwmBdj9IeiaSsSmIYkSI7WFtrGbr8urHMtbUXMat/CklSmn7SQVAYJDWFbPCDYdNu2YqO1UpxXBxR\nzY64Wl/n2tuD3ThUSCh6dCgQqUSOCeduSIWjjIlx8LirgGPLqpphCnAmN0JD8qTkUEpSqRrEQIgd\nbui5d1xRlocczA5xQtAHR9CeauZpwzWzukaphhgM1gWaZkZV1QTv6NqWpiopCoOKgVFrkvOEmKh1\nQRgDKIMqDdvtlr53IFt0PTlojZb5qiJKT4qX6DoQMIRUg+pRhGzME+bocoDgKYsCkJPhjqXQKovB\n6pHgblDxBAOTDFski17sxnqCICCkNCnMQHRgpL7lLMkKZKbMZYyAIqkaxwatPW7sGMMFrX2Xi/Xv\ncdX9S8q0xLv7NPwEsj9ldfgai9lrEOYU+hBbeoKMhOBRxZTBiMy4SG4FRETpCSIQ8IwykOexkYrF\nK99Df+mCwg9zvbyb7JqQbdtOJ1qgVEFdzyZtg8hsXjK6Aa2z/LqSkiAklSlYzRekFKhMgQ+RusqC\nHRlSnDAmz7jHwU6gnoHM6d/RjQ3WumxRpzXW5+ARUmJzdUVIkfm8QRUGXSvGOHB9fcO8KmkqzaKs\neP0Ln+Nifc03/vAMKcop88gNvKurNVcXI9fXWyKB0bWUjeDzX3y0f58JB2iGZFGFAee4Wq9ZrVYs\nlwfEGOm6jmHIxi3L5XLSpMiwcGstUhe3CEZydlKWWWhVCkEIjuizIO7u+CtpCCniYqDddggUTdNQ\nV2bKxnL2FgGSJPhJas0GTMlEQZ9o2pMupve3akw/nPUnN/OUGQhuSwg91m9Zbx7z9OxdPnj8DsYk\n2kEQdabjJ2UJssOnDhFHxrFHzWQmVEGWgrtjRR/0ZnqVNMGl4wum1N9L//1HQeGl9TKT8oVxJLe0\nZiZ9QO8iSLLpasz6C4OzKFNN0Gh5xwHZ4HzcM/J2Tk9iIkLt0vfZbJYFSFyGWCM1KUGIcH11gy6r\n3EyTkt6OpMGz7TpOT08pmzw9EAVs7RYfet44OuLe8Qmrw2Ou2p5Hp8d8UJ0TAxiVCD6w3XZsty1Q\n5FLIXTOEnsPlCSf3T+iGAR9bDg7muHhrDVcUBbPZjK7LhiYpJaLIMObZLNu3JcLEFp2g0MnhnNqX\nYpnxWexVr1P0SLKZaqa2S5KAfhxZ32wnnoOmLEuOjg5yoEoZ6RdiRqc6FyasQpqoCJMsPvJ7yCJ/\nuCuEHkGH9dds2gseP32PkAYe3H+NJ2ffYrSBGLdcdY+RdY8YOgbfU5YOox2r5him4wsS7mg5Or2d\nXkVMmg23z8GtW92rrB8FhZfWXUz5d6s5U0ocHh6yaXsuLi5JyaB3FnEios0k3GrEXqcvTfToGAJK\nSMJ00Yv8Ihl8IzSQa9TCGOyYG4hSaNwUfPpxAKZxqY9IMWUZEyqvahpG2yMUeALj2FEXgqOTI6qy\nJETH5uYSJQIxWNp2pK4k275lGEaE1MSUuNm2bFPH66/f58HrDxEKRmeZz+spgBmkUtkk1xjKWqAL\nw2bTUhQFTZMzoBgn7Qaxa576aQJh9sd1pyi1awxG7xEiZPqzkrgxp+zBwbbtuVrfUFcnpOAoKzM1\n1rJ4qdEl/bbH2YSPDuc8ZamIMQPClJQoofb9oU8lJn3f608ONMkHQhrZtlecnX9EXZeMtiHJE+zw\nmI17TBAD3/7wA55eShaLFSeHP8npkcXrLcs4Q8giMzZ3fZOUhYKyGV4OBiLl7HL/dqbr8lXXj4LC\np6x92jpdtLvpw+5iUkqxWCyw40jTVOhCoazAObtXItplBDsIc276pEkbIcNY62KnSwApClyIDH0P\nISImbHywWQbNjjnzUFJnd+mbK6qmzg2/lNGPPgRmdY2YnI2XszkXFxecjQPKlAw+cn5+zvV6w/p6\nRBsLEmxI9Daw7RxeJl578xFvf/HznJ6skMpTVlBWBqVSpmozjU8jaF3scQFaa4Rir2yktbz1yhQC\nU6g77k7szWCzLNpOmk1n5qj1E9koq2IPo6OoGvoB7t07YTYvcj9G58wN8nsZhhtkTPTdSFneErFi\n9EhzK75iJhfvqqomBGV+T7f8mO+BMPBd1l1fy0yUU3TthudnHzP0N8zmB5TVEh8KyuIBi9Uao1oW\nM09h1hh1hY+CoZ9TLsD1n0fVc6IoEWTNTBkiCg+pQEpF9ALQKASCQAw9KTmifPXM6EdB4TPWLjCo\nmNFxcMuUBCjKLIPuYpjEQAuSiHv4rbcup8Ja5xGVzCQjdachmsee2Tpkp5EwDAOakpTAusx/yBd2\nmqYTAqV1BgXJAiP1XslZSInvHct6xmK25Ob6mn7b4oGoC7713vt8/PQcbwuOjk6AyNZGzq8u0XpG\ntVxw77X7zA4aks6MT2P0/jMPvUUkT13XlGW2nZNa5UwjxqwOTSZFOQfOZVBW3eTpgXWCFP0LEva7\nTAEghlwOKKUx2uBCQCiFLkvoOrSBuikwhSBFQUpyYqaCVhVSFDiXQVI7MZXdtGjHcbjrxFWW9f5c\n/EDrJeqzkGmiOGdPzeBbrq4+5uLqA6pGYb2grJc8//gKoSoO5/fotn9MWVkODz2KkTick/wzhDvO\nATDUCJPwyUEIeNej44iLB5RFlclqKUK0BL9B0BFCS4jlK3+MHwWFV1x7rsMUEHYiKLN5jSkk/TbD\ndFMyWOvZbgYOD+d7P4eUbm3mgUki3kwagRaYSoiYSCFOYq53remL3LV2eRy3m0Un4XMzM0aqpuby\n8pyUAkfygPlywdhb2nWHS55mucLMl9x/4w22v/UJiJpn5xscliBayvmC49OHPHjwGgcnCmkURWXQ\nSk8GrQmhJIUGkfKNtdls6LrcVJzPlsQYGcZM9soZUp6fF6WeeigjIRiUuHWjEkKg5W0qP7Rb3Jhv\namcjEcHi4JgUxdSQVRQlaJMIPnfjU2QqIwqUMoxTUzOEOzJsURDvFNe7ssXa3O/4YaoX7a4ZuFuG\nXtGNj3HxMTqVkAY2l1fYYDk8XjErCm7UFpkuqcwEm08DaRwJasSNA7rJ4j5KQPIWb6/xfsBqiVEB\npQpEdMTUkuIlm+3HjOMVdfHFV37fnxkUhBD/DfC3gbOU0r8xPfaphi9CiP8M+I/Jw5l/kFL63179\nMP75W7tdbJ8xqJ1vV9YhmC/nQNwHCSU0XdujdOC0kFl9eL7g/PwyO0SLbBZyV7Vod+PHOwpAO3ah\n93GaNmSx1hAifpJ4RxeowWWSj7jFU2y3W6yusMPI5uoS1285uX+Ph6+/CVXDF95u0cX/C6khojk4\nXDA7vMfqeI5UhoOjQ6TeZhu6pmbs1jRlCXj6vmdWVyBFJub4gNRZdOWm3ebdPto9sWo2a6bjmOi6\njhg9esJVFEWBs+MLXITgHJWoSGHAjwObzZbBOmwAXdWUTY0Uhhg94+iQ0hNTyBYSMWLt7rjl8xGC\nIUaRlZwlJCknxW3YNYHtpB9p9J9eUMgv1+HcOYO9ZNP3eF8Swpw33vwSR4fHzHXJsuk4e/4tgksY\nBYUw6KSQQU54FIVLCesswW7pN5cwbmFRUpWSQkVSGnH2ir77hE8e/xGzeWJWfu6V3/erZAr/GPhH\nwD+589h3NXwRQvwk8HeBrwCPyPLvX04pfQ+9z++2XqR9rlYr1uv1NGaSIL+7dt1340J8+vNToyZJ\nhAwIZUEOubZPZFUm53NjUCgIkeVyiVAKFwVeGmwKjNtzXnvwCDc4vvnBc1YHCw6WAq81192We6fH\nFKrEek8SCaVLUgiM1mKMBKOQE/hk6BNVLVjOawY7UpUayZyz83Pam5bToxmuUAgZQUkijpOTDH91\noeSDj5/z7OMP+Kmf/BJvPHqDdui4fH7Goi756V/4EjYIosoaCqYqmVUV2W7CUohAVQaU37JsDEom\nRIQoBKPzJC/puw6toW17yrKmMDXSaAItkH92243UZYlMilLnCUM26hG0bVZ7ms/nuCgnyLdkCBWx\nKFBmxfHqQQY3JZnPuXM0skL6LISaKBFJoEyJtYHrraR3I6vTFUNwbLagdElAUpcSOb32DjUqRYF3\nEa0NQkhClLgwElOPViUpmil/iCBG/J3m5Gc1KncZwi4jGlrYDM/o/Dew8ZrkH3LU/AoL9fOclD+F\nMRvq8oTBBhDX1M0SlwTdxmPMFY0P+G3CsSFwTtc/oRu2lCyp7Rq/Hdj0nm78iIubr2P7a2p5ylz8\nOCq+/cp322cGhZTSbwohPvfSw59m+PJ3gP8hpTQC7wkhvk1WeP7tV35Hr7DW63W+kJzL47t+/cP8\n8y+sSHoh4scYsS6by85mc5yHmLJ0eHSOg8M59x8cIROcnQm6fkvf95RlQT+4vehr3tVvy4O7jckd\ntFrK28ZmSgEpchqeVX8cpqwpRpenABOhatNmd2yVOlazGaf3Tzg9PeXq6oIhOFwI9NFz73TJGCIX\n6y31rEKbRFkGpAhEbymrOutLxgygctaRvEPpXKNXZU2IWaClbgxKCkIc6AePl11WZDJFDhZ1QYpi\nsjLT4ASJLH+nRIRY4q3ADmLKkub4NJUVpqDSy3xMVjXOBfSYLdqFzH6a42Tpvn5+wXqdiUYyCQSS\nGCRuSDTGoESFn4xkpYgkEUBGEgkXPUYWWaNyyt6yzduLN/7dft3LISF+xjAjVc9oxzPGcUTrBeNQ\nMT88ZlWtqFFIdY/kBw6Xv8zQnlOIJfUMkjubGq9P6cQzxmjxMWDHLVq2mOoGp/8Vg4XNMLDdXuPC\nlkrOEbImRI0dL1/5mv9+ewqfZvjyGvDP7/zcx9Nj37HED+j7oJRiu93Sti3ln6JcfgYHRULKhiki\nZvepuqqyKSsGZ8fsrBwdhwcLCp0I3nN0dMTwpOP6+prj46M8MWhbpJxRVRXOjvuS5C4pCiaykJET\n4GfImP8hp7llWbK5aRmdJc/7IEwSb4UxBCnBJQKBR48e0TQVz58+IaqELAqETxRFNmk5OiyJMlDV\nmqaSiBTwjqlkykxFkGiVTW60ueUWFGUBQmLtiJDZj1HrgqQNkC3tazMjRkVwCRGzGEpKUJT1HrBU\nluV+SmOMyQ7aWlMU1SRoO8mdyawBuSgOQKZMUktxv8OPg8NPRrV9u6Hvt2idJWi1zOAmrUQmjEUP\nQqJ0QqlJUXpvfxdeOBevvL6bmUvK7lMkiQ09ZbFEiZPMXtUnqAjRPsM5iTT3CVFSmtehPEGbhlIN\nDNah9cDV+jcZuSapBiUeosSKsnKM7jFPzn6HrncZNq0q6uoAI2a4NDKEK9Lw0St/jB+40ZjSpxu+\nfMbv/UC+D+v1er+z/iBLSklCfEdZMb3HDIiZsoUY4gQmgrpM9P3Aen0DRjH2A/dPTzhYLki4jD3X\nda6bx6yEY1QihuyatGNB7jKEnVrzLjMwxkw+E4KYAkXR4GLAu5TlwcaR9z74kIcPH9K2G8qyxCA4\nPjjKhjFek6Knaip8DCAiAkFRaOarJYvzpySlKa1HSI2LDoGlKATRWaSqKUtDilmwVAooywKp8nFx\nQ2QYLGWlqOusgeBswFqP9A0pCcaQCCZnV4t6wWy25HB1xKxRex7DTtxkdxxCCJRG5emNUnu2o5Rq\nf07wASkziCeknd+zZj4rCVECEXFymBHIYSRGj5DZsaqPjpuba4ahI0RHSp4QIkqViOl22DEmm1pN\nE4zb9cKV+rLOxks4hd31uWtOK/GQN1/7BYZOo2eC1eyE6AbG9C1Eec3gnmd5NaGxKeKSxNkL0M8Z\nwhnn619HzwRN+Raz+hiVStquZdtvuLrssgeIqajKmnlzCrFGaoFN5y9X4H/i+n6DwqcZvnwCvHHn\n516fHvsLu3yaTvXk6+ico6oagg1sRosdOvyQMEpSNXW2dXchY+XJHgpuUlci2r2VGeRsZ9f53jEF\ndwSWnWBpUej9rqW1IniP1orFYs633vuAspx0DjcdSimqMo/ZfBizOInM7McQPMvlAUf37qHLipOj\nQy5vNhQqu3MbXSJlQqVs+hqZsBnTccjOTxZt5F4pKSZLCI7RO7Su0KpCFAkZZiyXmd5bFQ2z2SLr\nFxYVs2ZB3fh9hrSrt3fBMGdMGY+Rg7MgTP0XmAK1b5EKIp6dshEIEhqZbi/pjNUQCClzkCkVpayZ\nl/Vk4mtpuw3b7RbvLFLeSs7fZm7fC8DpO8VUc2BQGFNQxs+xqkq+9NYJQjgQPTfbD3j3yde49pqD\n6nOgakKaU5bH3AzPCPYJhD/m+fk3OVheYpqjrJodHX2/IXiNUQ95ePRLGfauBfPVPcryGJEqZLLc\n3Dwl+f6VP8X3GxQ+zfDlfwb+OyHEf0VuNH4J+J3v8zX+XKzdTrRrSqrJsMUozWI2p3WOdbulbioW\nixnBOm6u1+AD1dzs9QKy2YtAyVt4797ibWpG7Xj+ux0mJZ8Vg7ynHzLfwrlAIiGlyorIQ89iNkea\nDBEehoFSG+rZnPlyhk+RzdUVRiTefO11MIp2HFGoTOLRBm1KRu/w4wAKFrMlSeSpyjg4jKmoq5ro\nLKPt801UBJqmoq5neAdKFcSgOFwd8ZW3v8JyudwDs0QSqCkbkkKT4pZc8wQIUCq1931QSmX9yZQI\nMTcFQZKkvEOLziPIJMKkHi0zVCsFiPni39HbU0r4SSRVSomY1LkLqdCqolpULMpV/kzeU1UVVVXd\nAa19p8X7y0t8yuPAC2C3Qh0xSlgtDhnGDbrcMsoNZx8+ZXvdEvWGenmMKI54+tF7XDy/JIxPWTSX\nPHpokOkI7OfQxdvo4gTrMgV7bu6zKGb0dsN23FCqQwp1D6NnSLklxIJ4853GuJ+2XmUk+d+Tm4on\nQoiPgf+cHAy+w/AlpfR1IcQ/Bb5BTlj+/g8+efizXVn5V2TvAO8zbDndkngOD1dEETFTCt22Pd2m\nQwmNKt1+JxzHkXJeAXEvrLmzZ9+NxXYCruM4Zq1FPeBDRkP2fY8pa5qmYbQRaz3L1Yqry0uM0pwe\nZVy8HyeTEpVl4tp2IEbPvYcPETJxdX1NO44MnUMiiVFRFA0p9UidsmWbVNx0Hev1FUPf8vDhfbyz\nFCqn+WVZkkL+HFJqVqtjutbx5MkF90+/wKP7hzkFH9dondGX0XuUyCpTyr9o/95PupQwQbj1DoGY\nnw+T14IgB1SCJKjcIAyTj2dCk/ko3T7oxjviLdLkUqWUkeQyBVkrg0BRVA2FbDIGopQsFouc2X3P\nRe2LpexuI9l9Dgk09QohT2iiZ4xn1PIpxeyA6/Y5D4oNttD4IfD8+Q2Xz68xYsOssChRovg8BV8F\n9xpeSnTpaTdg1AGlOqWYOUzRUTT3mNVvErwmxHNiLYj8EMFLKaX/4FOe+q6GLymlfwj8w1d+B3/K\n67uNjXYXZH4uQrpzAcielFpSdMQgEGlEy0Q3OECCVCQR8ckRRaBMgoXRSCJKabYxMF8eIVXWDGhm\nOzHSHQxXT2SdSE2BJRKQbLYtZTXLNnCUmFRQlAHsZK3Wdfg0oitBqUAoi6wNYtlg7YiNI6YoGV0g\nEKgtbIcN80WDOTymvn+P98+fM/YtSgm2bNCNBp/AdZQSdGEYvSdq2J5d8PjjM7ScczgvMcsGqR0p\ndQgZqKoFIZ4g1SOePZf877/2v6Jly1d/7udob9oJIxCo6xIlND5YiDljQt4RVH2ZgxAjg32RkPYy\nS1UHgQgvn9d8TDuzvUWehkSyES01xnn86GmlQUuL0SOFFHs1aqGzErOpDCF5un5NVc1QwoBUhMnj\nxdxpJu7f987/hSOiaknqmqR6SBoRNIVQmekojtBFFqkxIhGjYWFe5+HiZ/ndb52z/fy7BPcaQzwl\nmgKzPCSOFe2Y2HT3mN/7JbQ5QYg5gpLkWuZNS1F9zHV8Ak5QyAVzc0wpAlQzbsYF5eJLCPPq4q0/\nQjSKmE02kpxgqjL/X6h8Uu+Al3agoh1FNsZIUWoKrxFa0XbtC3h3IQTb7ZZysmjPRqhxDzLyMRBS\nIkmBUJK273DOIlKuacMdQ9FdebHLMoqigKCZz+dstx2bzYbjo3JCDXp6lzUTvfccHR4xjiPn5+fU\npaEqa0SC0Y40RW541rMZyY34wSOCI0Q4OFiRomb0PU1UoAq6AZSS1IcHPLj3BX791/8FX/vt32e5\naPgP/+7f4fT0Ie9/+CHee1aLBUWh6Yae4HJJ4IOdyoJbY5aXl73TP7j7dXdMi2T23+8e352PkMKU\n0UlCSAQbUEQG4fJjwqOlx2uBVwJpRwoTkNKhVUWKluQsoXCkkKiqBj15XYTPSB2E6JG4yYS8oDCz\nTNf2Pd63IPIokaSJSaJNYj22nNw/4P5rJ1xefUztI0klQtKc3n/I/YMjNhfPubi4Zjm/ZLaQGGOR\nUnF18TGb9ozlqqTWj7LXqClou2u8WVLNCqpCELVC6x/BnL+/lSQkPf3LphwvX7wZtixvLc9C/n8g\new5KmY1EpYL5fE4/tCipGIaezfqCk+NDlst57uCHgBc5KKAkm76DmNBCk7wl4ffNuJ0j0U4CvigK\nnBszBFkkukk6vCwqrB1wLrGYfAurqmJ9fU2cDFbnZc2Xv/AFvv2t9zIVN2b7eKkEVVFiSk1KM87F\nWQ4Yc4EwYH3i8OgtUhR0tuK/+C//EUIa3v7xz/Orf/vf4/UH9/jw3XehO2e1WlFUFS4kbDfsm4k+\nWJx/Ucnq5QmSi7cqQbv+yt2vMYU9nmP3MzAhOhEEl5mpeYoQiSnuyxORQEnQRmBkHptan9DaU5mI\nioLkNL4fccNImC+pq4ayrNEiZ4n7y+Wly0fKLeDzE7HMo11vEazx7hlD/JiYDKQFQi5xRAZ/STI9\nora4myOunlmivmF5sMBHQWslQ5yTTIlNa3x7SaRn214xji3WDVy3CRW+wHI25/DgHqwEsTDookSU\nBkQA+VdMzfmHtyTsLMJ39NOYUEJOrkcBSXaQCpO9mylAaQg+0bYtWldIDG3b4mxgNq+JIU8XNutb\nezYhBMR8wfqU5bhRWQlokuUlTXqCuwxlZzi7v0GiJySH0Zrlck632VKdVszqhiEObNuW+8dHdF1H\nv9kSRkc9m1Mqzf35nIvFcza9xXuPFGCkQmtJbTT6YIExgq7foEtNU1dIFih1SO8i//V/+z/y+S+9\nzdtffoNf/Ld+jkoZ/vW//gaXZxd8+c0Fy4NFFkUZ+mmUGvcYABteDAovZwtC2OnrbcZ1VytTp9vJ\nxd2MIVOvwbn8vQsBFwPOZ3GWSKIKmcOh3eQArnbaDYbSjEQlaJoZUd1uCG60rOZZ9yHp21vm5fct\nUyAJUFETyZRtwSVd/3WeXfwuvX8f0hKl76P0I1w0jOmCJ9ffwImWaBq6viWELbVuSdWKZzfPePzB\nGd22p+0szXzEmDWmsKAiEoELkhAHrnuNDQcI0bJsAsKUlBxjZPU9kb3+QgYFPZ2Y3bwfZ1/5d1+u\nT1/8/128wkTjVZoUApJ809iYcNYigGKyo9+VDHsATtFws75CKcFpc8zQ9RiTU/3dWHNn4qGjYJyw\n+jGCKEsKaTK92LIXIbm+vn7hfXvvJyqzmjrlk8ahVEijudm2CO+QRrPZbFhfXPDayTGvP3hItCOp\n66m0YRMGlMqMy1JrnB+xw0izPMG5gqJaZrn5pDi9/xq//7vv8Hu/+0f8wi/+23zpx97grc+f4H3P\nN//4m3TXLa/de53Z0oCStEOfvRaUxofsQRBCZPC3Wpc7uPFuSSlRU1DY3fi3308OSyK8EBR2gSXG\nSAzTBCNG+tHuPTny/B9ECEQPyUukDBQ6UghF8iPzOrKaz1CFxtQVUhnG0RO6dn/e6lV5J1i9eG1J\n6qyVobJmRoxXdPbbPLv+Dc6ufwNItL2krF7n+vqb2Nhg6dD1FiETvWhpwxUhCdK15d2Pvkm0BXWx\ngkbTu45lEWjqHikHXASV9yjUrEMkwRgabjqNliuq6iHSHKDLiqRevd//FzIo7Dr6SimOjo64fNZ+\n/3/sLgpNeKRIhGARckRpv9/d8oV7K02+82jo+56UBNY6xjFQ1ysGG4hBkCZNv3zxsldb2hmSGpmF\nSrKwliCGgJGKSudOuRN+T+xpmuaFLGOnZUACowRBZpRl37ekLo/zuqHHx8DY9xilmdcNV2fnHC0X\nyOSRPuMphJAoJSbruIhMCd9vqZTBJ8XBvGG+OOEPfu8P+a3f/B1+8Rf/HX75b/4KUfZstpd88vF7\nJOtZrZYcHS1RytKPA1JorA+45DKpyWabvcHxwnHdjW1h6thPvRQp71Kdb52kNekFFOjd3kIKd/52\n8jnFF5E0KWd5H7FIUhAkCaOL6ORZlHm8OlutGEk8fn7GaLOr+LJc0I+Wk8MT5CQ2u9PHuLtCNIQE\nyEjAYmPL4M95cv4OY3iGVitULenGj+l9hXULymaORLI+H7C+I2kQKDbbjhgVUVjGeENVVfg0YgdL\nbTzGTNgpIdB1QwjtBMTz+LjB+g3O91QhoimI/OnjFP5Ml7WWuq736fQPtjLwJTcZE0kMCGmRakTq\nHlJCS0VSOneNlUZJcNYSQ0YYKqkJ3hM8lMWczbZFqwbrr9hsNpkKHXcXutzvaoUpJq+BDCMOLk7z\n82woKopir61Q1/X+ptjtVGpywx7agaHPmol2tNlFqtCM224C6XhODw85WK54/tFHSOc4624yj0Aq\nXIr7HVekicnpHTHAweKE2fyYr/0//5IPP/iY//Qf/H1ee+MNlPR89MklF08eM24HVss5h0cL0IFx\noncjBb2N+ATWRYbJjMVR7JmMIQTUnR5DBiOFF3ggO5zH7vOrF4BO8cXjEgUxZcdrrbMallJi8m4I\nhCTxUeAiBCFQMTErDM1syXx5yGW/5fHzc7zRmKpGe8/V5oyDeklQBlPWaD2hJl9KFVzK5aBI0jzE\nlQAAIABJREFUniydqhhtwWrxNmO0XFydo0pPH64RumZeZkzEfHGPxiz45OpDgu/xrkSLAi8gmkA/\nrBn8yEHjsIOiDRJRTwjQZNDVnEq8TVMWyAIkB4hYknzAhxEfus80tL67/kIGBciaiIvFggcPHvDO\n1//gB/hLd06s8IAnpI62veDs/GPGcdzr5zt3S6HWWrPdbnEpkoSk6waWywOkLNhuLuh7h48jjx8/\n5nB1gDF6XxfvphmiyIIrWikaU6KizAHIegbvidpPbkuCYRheuFEAiCPOe1KYZODIdmpFUaGUwdts\nLto0DY8ePSI5x9D13FiHLCVEjxIJKWR2no4JgkcYjRGRWXNAUx3yx+88QceK/+Tv/T0Wqxn9cMPX\nv/7PubjuGUeV+xRFBsds2ytMGEEKBuvxYYI7C4kPKfcTuIUS57Ip7o8JQH8ngO7s9O42GlW6BXnt\nnt8/h0AKgVICQ0JPSFSZAj5GCBIbI2OSBBExSrMyDSkqLs7XrLfPuOhaZkdHXD59zG/9xv9Fd9ny\n1R//Cn/zl/4Gtcyen9kz46WOvorEFBAqkpJCiBl1/XmOhMP7U7bD19h0H5CkR5eeUkOpFaVsmB8d\nYWVNraDfljTVCfcfPgA18snZt3n/o3cY+j9mnaDzFjszNPMGYUqSnjOvfomjeUVdkZW4/AGz2QIt\nEyl1kH6I4KU/z2uz2Xz2D03ru87Eyai4DJQNCCzdcMPVzTW/+dtfo+23/PjbDyi0REVPxEMKGN0Q\nGNn0kc6NWDsgteFoOWewFuc7ilJzvMo8BFNIjBEokeHOMWaJdofFp5EkImVjqGc1th8QUiJFIMSc\nVkuhqMpqT9RxdhecMtqvKNQLny0lT2UnEdN+ZH5yhE/w9PyKrVJUR8e8/fk3+eb773L5/GmuoIJE\npgJcQUHJg4dfZXV8wB984w9RB5EvfuEt3r3+kI+/ec6HH33M1/7PP+KN1+7xs1/9CSqj8NFx0wEh\nEqLFT+zKSMKFRBKSYRzxKeLHhCk115uWTdeia5Pl86fzZITeG8Vkd65JdDVkyzoR7G0W4fx+xCul\nRAr2I1ujJEoLTFSoKY7WPus3EDuMzrTxbQw8ffo4s1ljQTmb8fzJDT4kHrzxFf7o6l/xz/7v32cb\nK371b/0t3oiaWhYUPmDqki55YlFQpg1aAF5DmlExx5uCmfY8v97QKMdoj6jlI6SRbNsN6CcU0mBj\nw4E6YDFz1Mv7zIu30fo+ZhEppWfsPmK4aUjSoUqJp8KYL3N08hWWqy9i1Feo65pmtpiUviNSKmRh\nwBQo8SONxu9rJZENYj969pT/5dd+jR/7iS/zxbfuYZRCiF1jKyFVnjgoDUZIrEvUdYFUER8s80VF\nM1uRyOi6siwxRiFSuINyi/udMpB3a1NM0mRTmv2ypdnOVnw3xiuK23l9CLn82TfvYoZo76jfz549\n4/L5OafHh7z55pugJc1iRnyeWXXOBZRU2GHkjde/wL2H93j89DHeW1bHx0SpuFl3vP/uh7z73gck\nLzhcnWDKhoSmHR3bLtvqWV3iJzctJfVUJkT6MWQDWLlhWPcUWpJSYNxYVAQpBDJBnyaeSRhpw4a6\nrvcZU0qaoCQiCfzo9qVF1oiUqARaS4xxaCUolEYpSTHZzQsJutCIoiABgw1shpanT58ileJ0uULE\nyKa3bAbLVddjlsfcPFvz/z1+zq9cralIzJSkvH9CpRSlUiRtSEPM4z8RAUdiEsOxFcHWBPsQIyVV\nNaOoJNpc8M63vsGH8ZLV6jjb01clphZIWTObz0DOKcMj/trbv8onn/wfbG9+n6PVSG1GVvPIcn5A\nXTyiaQ6o65qqqRFCUaSsYi2UREmz5+K8yvorHxTENIGcQLaMKfHBk2d868MPeOPHvkTwItuFpWnX\nnmzIylKxXDVUMUzCpgYfRrpuQ1Eoqkpj3W0zzPuElrcSYLvgYIyBiZq9V2LygUIbosg2ZCF4QvAI\nkciE0sTOyxJu7dzh1lo9il3Jk5Fs1zc3CCV5/fXXSSmxdVuG4EhC4YMgYeiHyOn91zg4fsDZ2ROe\nPX/MbDajLEtUM+Mb73zEJx885ZMPn3HYvMnB6hhSgQuREMH63L+42jUFRdZMCCHiR4t3mcdxlW7o\nbjY0umCmCmamZDWbU0hN9J7owiRtl0eySmR9TB88RLDiRU/IfCwzf0KnODlNkfkWJlBqQ6gkRgtS\nISiTwohcBnSjY72+4fl1y2q1QhUVY4IxRT55fsHFTQe6xC+PeOf5msfnlxQCZkpTFXlKJOuSJCMi\nlUAmOiHspIglSbFAcczh/K/z8OiIhKYfz6hmF8zm57z/0TtIE1nNFTGuud48ozkds3jP8IhV8RCl\nZpz8uOK9Dzd029+jqhWmLCirA8riAU3TTMzTPH5MYQcQE4QU9pqgr7L+ygeFnT5+FJGEpCgrBpdw\nSfL0/OqWkJMSwacJQGRBJKraEG2kaWqUUXiXs4iiKDGFQqoqTwxkbkztdvwstJIDRlkUELLHw94K\nLt42/naeEbvyoCiKfddeyN0Nwf57IRVCAtEQUsJ6RyDvpo/u30eXBVfra/qiZ725QcgCP2Z9Ay8T\n9x++xba3PHv6IbqqUWXJ8fExTy+3fPMb3+LZ0ytwmtN7jzDFjHXbo3QkEnBuZLCOGzc5OmtN8oEU\nwHV2j/XAt/zyz/w83ns2mxY9+RgMIRCURNcFhweH+4wKspR913UIH+h6u+8/ZLfuMWMtpMQkUEpQ\nuAwgEz0URcR6QVEkhPdUMVEUGR26Xq+5uroixoQ0FR4BAqqmxkfH1eaGcn5CfXSfm2fPeXa15qiZ\ncW021EajCkUjFkhRUKRFzhQARD4/KQmCl2g1Q/o3aZrXMGXuGfTpPY6OXufp2Sc8fXpGd9FxcBiZ\nLRLeX1Opp8zKr3KyXLAo76MXX4TX/gbPzhpiGLDjQzqpqAvYmQblsez/z96b/FqS5fd9n9+ZIuKO\nb8qphu7qiT2JbJqUSNqGbRr6AwgvTHgj25BhGDZggAANS6a5MMQNF/IEAbZMwYAF0AtPAkQQ3pii\nRMILE5I4NbvZA7u7uobMqsx8450i4kxenIh7X1ZVt6qKPbCLPEDivXz53s377o3zi9/5/r5DHqCy\ncep1YOG+m/UXRWG/CnFpt/X82I/+ZV548BLbzSHAJIVQsgj3bX8kxoPSEVVMRUPwzGcVYUgEHs/D\nKZW0kvHny2Yu+og+RdIth+cQAtFEUGBtCZgB9scHKNbpB1emvC8449Eiq8MItOt7lsdHHJ+e8PjJ\nE66vrpjenbPddHS7iO8EneDB/eeZTCY8fPiQybxGW8fipEh1X335FS6e3LBd9SgafM5Egb73WCDk\nwM3Nihgjs1o4f/MVTo7PePG551jMlsTe4zvPGw8f8cPP/ziLyRFdzmQs56sVj6+uuNmWVO1+3R+O\nVkOIzu2pTSXVHlOo6zgIwBRJhD4kJCT6FNCpAI9REn3qML1HN5kohk1XHn/deto+cXR0xGSyIMeS\nIJVS4MHdUy5uNlzvViSZwHTCl77+MveWR8yNotIKV1kwmqnViD7gIuTRJLYckVKKNHWNsxqtE0ll\npPNMmwk3VxtCyKw3kbpxNPNMG1Zs268yqc9o6k+i1QVOLTib/wQ2vcR2u6apl6XYmHjAk9JI+lII\n6pAS9U4GMN9i/UVRANLYLZA4XpQ71H/+c/8Zv/Gb/4iUekRMCTVRiuAjKQOiUMoR/aZQn61DpOjv\nvY+ECNvtGu891WCV5oYMhLEoeO8JKRZSjTbPbGqlFG3oD3TqnKlqh9Ky7x7KXfRQHArwKMPPpuIB\noTWbzYaTxRyU4unTp+jhXPvgbsPm5nVCyJzeOeUvffLTPL54g5R6zETRTCqWxwuurnr+8A++yOXF\niryN1PMpi3unrPuWZmJ4cvWEHMtG/sQnPsGHz+aEEHjllVcwKfHay9/gwx/+ME/efEyWjA+Z3/+j\nL3K+WnG167hqd3Q5F/9DAdUPycrGYmxdNtrwmhilcOlguNL7SEz9/u9aD6PVlDC5YBS9JEzSWAym\nK8epwmmIxZF7OuX4+Jg7J6ccV2kQvEVmjSP0HX/45W/SZ5jXlm8+fINvnL3KWfMxdp3n/OkFrqpw\ndYOb7CAXR6fiDu2IqUN0j61bnL0kylMg4/NTQnqd9eobEDwqgWtKd3lxuWa13XBytGFiXuFk8jL1\noqYyD5hWd9HpRRrTYa1gXKSaaKx2KBnTrwT2x4X3bkL0574oZDm46eiksEm4szxFoXn+3/5rvPrN\nf0yIHdYoUhhShnuFDHfvFIGsyVnISZMirFdbuj7S+w1HR0cHuqyP5MFPYdzsk8lkCCsFsqJLmV3n\nadsWO6vLc7xFBR6TmQu46Pfn6nE0NwJvWY2xdQVw7GPg5uaG3W7HcrnEUPPc3VPWl3Bjdnzmhz7D\npGno2y3TxlFPFfPlHGsNX/nKH/Hyy6+wudlCqplOF7jZBJ+2PHn0Kj/1Uz/GV77wBV760Av07ZYv\nf+kpKSVO7pyhjcOzJugKOz9i5RN/8PqrvPzqa7RdTxYNYoky2Ni7ismUPd4yYiW3fSnSoD8Yb4I+\nFZAxpkib4n5UmUWTciLmkrqYsqBSog9+j3c0VU3sPauray6NQ2xkNq1pGsViVmM/+gKNcXzzzSuu\nVi1XXc/Dx+f0H3mpvP+DbqTabrFWo42gs0WyI0VFooQJZ3/Jzeo3afsOVwm7cMH1zWMurx7z4L4h\n9BWTpaGZLTi/SFzfrPEBanXN2eyC5XRNu4vMZ5rZ0jJZToHBM1Ju60fKkeEg1n7v6899UUjwjNu/\nMxVtv+P+2R1ef+MRs3nD9cU5zaQhpBJk6kOPzrpo+WV06WHACTTeB7ouMJmWgNXzp0+ZTqesri8R\nU+5SZSJR+PXaGCpXEUNGUib5Ei/X35o0jLTekeQznrXHGPqxOIydiFKKfjArsbbQoa+vr7GV47nn\nngNxWO04PT5jORNeeuHDXK7PC6NRw2Rao3SZWvzWb/0WNzc34ME0E46XJzy+fMJnPvlRLi4f8Xu/\n93tsri948uYjrDYs6gXaGK5WryHWcXb3Do8v11STOeunF/zR69+EEEAE+gha4ewElyyyg+lRyacc\ngdKUEt16ux874swz5KWUi3Y5poRXCTKIj/QJrBJEOxIl87NKoRRyVbrDfrvj5ZdfxmhN/7GPsZbA\n8w/OkDTBqMzxbMLHP/wcJ2f3+PLXXmH1aMXl5SVX1yt+6PkHzGYF2OvbDj/ViKrQyhaX6OQHtX0k\nxA1d/BOubs5RNrDptgDMFpCDxreWehGwJhNRdD00DSyP7jCdzhE0RhoyHrGlEyJbtJ6jkoXcknMx\nx1XKlETs97neb+7DfwX8h8CT4dt+Ief8fw//9j3PfZhMZjx+/JiTk5O9h/9h/QuSgAsPtqjXpEwB\n0IoUPbPacqUqSGWz55yZTGpan1jtNqy2W5rZHMGhxaCkzNXPby5w1YT5YkrKRT+/Xq/JqeQwFpXj\nhDaUbMhFMyX6iNUaN5tgTCk0XZ+H1CmL0oXA5H23H3GGWIDI0uqUtzJnQ0qK0G4geFIf0LWjkoae\nyNHJMceLipubTLu5ZrYQ7ty9j5l2+IsrdAqcHp0wmxp2G8Xv/Mbv8/AbLdunGR484OilFwinU9bn\nT/nNf/zb+/N+Sm5fwG6uPJGRZ5D54698kV3f0XVF/aisRWQIyMkJAoTQYaea+WJKXWvq2kHKVK4U\nwllj9v/X+ea6OEX5hE+ZEBLKmnIMS7Y4HRPKaE5p6GCuNZNeoZyDqiIZy6rtOD+/4ukmcXo05+H5\nCnPaIFWDMRVhs4Nty9zVTBYN0489oHvjCZuLFa+dP+Wju49gpxPqXUvjFLFrse4ONhlSjlhzTae+\nxrr9pzxe/Q7r9Arm6ITQOwi7MpESMAIpCcYbVqtLHj9+StvBdmMhHSNhgqYqav5c4ZgSpbBwM4mo\nOyQNKkiRW1d84r27n77/3AeA/zbn/Ldvf0G+a7kP335dXV0xn8/ZbDbvP1p8L4m9XUTSPtrsNvpv\nKsO2Lw5JKQtN7XCiab1nWjli13N67wFajwElB2xgbPNjjLi3AIgjU3IEjcqYaXyz83DsKO5HRYY8\nyrnj8DEQ/EGcpZQahJ7l6GBV5ujoDsY4Lq4viCHwkQ9/lBdOTolZUVWW+mhOnla0qeLzX/s6v/X5\nL/Dw5ooP/eRfIRlX6LqP3iSGQOgjJNmDpzkEUIrVtlieyQAOitEoo3F1Rd+2BZOJ5WgjSmFN5uho\nxtHREYvFYkjC8nsbtZwFpYvewHuPcjXJbwgZWh/K43U9EaEyVSFC5aIlyUqTVMGNktKk1KEphKhu\n13J1eYnOCkmZxjruHJ9wvFxSGeg3LSFGdrsWOy1S+E/90Mf4yhe/zOrmgu3uClKNGOhCx3Y9RZOY\nTROI4EMiqoZufUKjPoOzL+IqoXePucpfZLV9A59hu+voW0hXNVcbj3iLVZ7YC77VNJMzRMpo+P3f\n/9/9er+5D99qfU9yH95pVVW1byff2xqMVd7u4g8c5LsjCFi4CorJZMJyuWRzvUE7h87gMmRtubNc\nsqhrdqG0vE3TDFOMvD8XhxCYz0q46tXVFW7QOex2JSCl73uaybJ0BKF4NRZzVxlEWJmUS5Gqa003\nAmgMfo9SIu0nkwkhRaxR1E2D0TUXVyvE1swrxZ3ZkimGXc6IsbjlEaE2fP4PXuPXf+uf0i1OeeFf\n/jhPLtaI76HzZO/ZDQ7Vwfs9cYisyX2kmk73vyOAFUvXe8gZVdekAQRtmpqmcpwdLZlOCle/u3lM\nqjXL4yNCgq5PJKXwQ0bFzc0NV9ttOS5Jma6IKccwxfBaiaCNJas8YD1FCZ+0oI1CKaH1nsvzC9qr\nNcYpUheZ2IaTxRHz6YxKJVTqWa/XaK3Zbrew63nxhQeE3Qbalu3ukrabokRjg6XdTdCqxbkdohMp\ne3xvsHyIk+k9cljieQ1lvoiSN1BcEmPHag1925ECaKmYVDWrlSflyOXlNV0LUteDYeuo5P1OJ2Yf\n1p8GU/hPReTfBf4Z8PO5xMZ9z3Ifbq/FYsHFxcVeNPT+1lCDB2FU+fzg/BNjgn3MW5mTO+dYpRVG\nSi4kKRKj58GdE+IAfq1Wq2LsMciab3P1x81U4uDifuw2ftxsNjRNtS8KhZ9wYDVud4Wyu1gssYMH\nYR4SSXQ1oW37skGGDqWqGtbbHdeXV1Af8+DeA46my2KX1rd0SfHFVx7xhW9+nZe/tOJJZ3jcdeS8\nLcrFtsd0AZOKGSup5E3YqtoXTWMc3W4HRiPWkJXgux1UDm0dMSV0UzOb1Nw/O+H05AinIPuWvtsh\n2RF04vLyAp8S2ja88fSCy+tN6YyUkJUGbcvdOCasHmA1DUYseRBVxZDQdogB0AqMBg0hebpty9XF\nBfQepWvoI1NVcTSbUxuLkqLCFaORmIm9L+Y5E88Pf+bjSPTMnaGZKLSMZLKAD5sBNO6Juafttjg7\nx7p70J9AlVn1T3jzfEpOpwS/Zddf0fdwuohkSVgHmy3UldB3N6zWl5wtP7TvAFNKt6YL3/n1fovC\n/wj8EmX3/BLwXwN//b08QP5T5j7cXrvdjul0Oj7ue/thSUMNKAQjAFHlTR4Bur7vURJRHBR5ejBA\nMVVNJBOjJ8WIMxolsPMBH4rduhlBQh/YDAlO5Y/QdR2TSclbHPEQkeJ8nLLeF58Q/f4oMoKHSnmc\nK1yHGLfUdY2zRSOx221ZbTdEH7h/9wwfPVkJ1zcbrq63TPKUF154kaQUuIrXXn+TV1cbvvHGDd94\ntObhtWeVhKQdDMYyiCKKoHJGVPFIQNuyWUUjQgFfB6FQHv0OGg1GEwFTOWaThg+98DyTpiLHntW2\nRWJPbQ11XZM0XK1WrM6vWW8uudm2hAzKuMEEVcMoH88ZYkINbnpjqrfTJSBXRHAKIBFTR5JI3TQ8\nurkhxwQxkduISEL6RK3MUOATMhx5YutpmuLQRAxMminH8yOm1hBTh9alkyEX1uj1+grtPCn3KGPJ\nkmi7gModqb+g6zzT5iUmzQOunn6Vm5srlssp09kGW3mSFH5BTpnFRBNSjx9l5taSs3obUnb7Zvie\n98Bb1vsqCjnnN289mb8H/Prw1x/M3Id9YYA9pjBU/5EjsGt3NFUBCUUNBSEWp51y0ywinxBKMYgp\n7HECrYobsxG1j7obH3df+Xm71mFMQR7vEOP3wGE0WYxgD0rDNrbsdju2SdhsNvRqy/FyzqyZ4AfM\nIUXFxz/0EqDQ8xl/8vQJN8ryK7/6D7iIil1WBFeTuhb6DroO+gBJkZUtep8YEa2eef77pSmTBVXm\n5WORY3CDnk4bfPKsN4EYCn9j2/ac32xALulaz816Tdu2JdNBNKI0yYdSdSYGSWpIfhKUyjit0FpR\nOYuW4mCltcaZ4po16oHGveMqS2Usuwyp90RR0Cd0KPyGOBwbXVXhk5CDQigFKAePM0LtFISyWTWa\nJIHeZ2QXULEF8XShI0WFNhVGJ1A72k4zc59BacfxvMa4lzm7v+T4eIOrIIvGWkOORxzNHzCbLlG6\nvnW9CN9NcOF9FQUZgmCGv/5bwB8Nn/8A5j6MmALvCDb64cx8c3NDnjalNU09mDIG1JUjKRBn6Lfb\nA5HICMoPYF8qo7WqmRSg0hi22y2TZvYMDjLKqkWKy3DvD1qJTMEj6rreezXeTlcyw6gzDq5GWjvq\nqqHbrWl9S44JiYp2E3HVhGUzZTKd0irhSe/5W3/nf+DKN+xCxfXak+c7UoioBBKElBVZFGghaZCB\nKJNEyG873w5nXinpW8oY0Lq0/qLwvuPp0xY3hORcb7b7CMAYApIHbwTVIMPvrcuWRDtHT0aIkAWN\nwqpM7RSVMVTWoAYhlNGjQ9JgEa9BZYetSzHt+h1EKcG5RPy2Z7Nak+8uMZXBVo7QtgNpSiMGGlPh\nTEUKsRi/poSRIc8iOiIRr0BjqRrFbnfF1dU5MQeczrjqiEnzHE3zEpIspyeeT3zyj6nnFywmBWiO\nWTAyI+UjTo8e0Kg7WHv31ij6u5iTyPvPffhpEflRyrv/MvAfwQ947oO8tSEry1pL0zRc3bJBC7mM\nerquw9UV3XaF68DYghP4vufi6oagxyxE2SdAVVW1R9H3ASXDY2utD2M7pUg57mXWmQMHYfzeMX5e\nBsCt4B1xz2uoJw05FkDQ990eND07u8tyOkMpxVdf+QY/94t/C718QD29T7+1TGpFX9+gQkJ1PUIk\na0sJloOEUOlbHgj62cCUoA4TkKwGGnZOUBLjsaFHW0sIijRMCpStcA34GFFBDUckXUJqa4vvevq+\no3YOWZTiWhmNklzgAhG0Kg5WIoUyrqWQe9KQSp4loyTvXbuapmFz1QKanBJ92xX8RxRKCyqq/XFR\niS3uVIOCs0y58mDeUpyjldjB9FcjCOTAyfEZi2XFrl8RdoGcF0zr51HxHrZumE4e8dnPfoab8PtU\nuwqlLCqA2AqRBZP6mFodMW1Ogbh/7t9XoDG/c+7D//xtvv97n/sgiiQdRlmiN6isQHWIbPB5MnwP\nIPK2rkvGqptvdwsKBkuwNnr6FBGj2Yai4w8U/kBWgmGD0pnaWbyP9F3kerUjpMzieMbVzZrr6w3z\nxZJtF5jbitiXc2zXdSU1e5g2jGPEsUhUtQLcvoPY7YrmYjx6aFUCZVMq7kLkjHOglFBZqLVB9TW1\nnjCZT4l9xmTNcn5EOznjl3757/LGdsdHP/fTtBFAcXYG0QfO1YzgI30/gohCjUapgvCnbemgIodN\nn3MmAfWuQ0yxRE9aBvf84ipV6ULwGRmK0feFzGXA6RLbpnUpnLV1ZbqQyzlZhunPNgRy26GMpqkt\nFdAYjbPm8Brq0jmFnIg5FO5JSnQ5Y8WBzWSVQAdi39F1icuLN3j9lTnTheP0wRJJgcZZdAwEXwrM\n0URYNo5KNDlFgghRJZQJ5NhilcZZR1XPsHbAVBRUJJJx9H2gqedMZ4qb7UNOTo9I/FVO+p/E61/n\nZvcVbNMys5+g0f8aTf0TTCYvQJ1Qri6dJekWFm6Gxuw7d574YDAaxYN0g8eiATFIDsML9e1brX0j\ns/cIfKfvGViFZrxrGHzbkVMusy5d/h/vW9pBsaeNRaREj9lB2TgyDa8uzzmaTQfDlYOUeowqG1mL\nIRV9w0hrbpqGvi+O0PtzOs9yIay1OOdoQygqQcl439NLxayZEVSimUz4+7/6K0xmkR/9+EfoRGGG\n/yP1HSkGVjIZitXo41DadSjd0tV6hw+JnMHH4krlY8FBsi0Cr6SkOC6ljKBwqnD0U+4KC7G84qj9\ngX94vaHgHzGi+w6N7DEUZy0zp3F2QqUVlRYqp5hWFc5qRsw6C6Sc6WOgD0IfA13fE/pI11/TqIa5\nm9GrDdCSY6bdtnzp619Hpgo1+wiTuUMIRQZtBIPB2npv0Fts2W5dhiohShAVgYgoAXIZieaIqMBs\n1lA3NX0Xqd2SanJElrZYtvefYL0ulm51/RmMehFnltRNRVRhf7MYlbHfrfWBKAqSFWRQZKJEJBlA\nIcmWNu7brP3FORaFtz72sFnruqaqLW3b7lvP1XpDTJEUMp3v6VpP23bUzYQssNpsCCljjOVmtWE+\nm3GzXg05DnZP4RUR6rrev+kjmSnG0k2MLeOIKo85ECGkvQwbiox47DqyQNuWc/uolmw7z3S6pJpM\n+eznPotPwvG9e/Qp03UdihIE46xmneqBlHSQfJdU6Z62bXlzs2PX9XSdpw8FXe/7cuH2QeiCJ6Po\nA4SYEOUGea8Qo9mPVUVkiH47cEL6UI5QWinykMoFUGuHcRqD2k8YK6eY1Y55U+TqRg9FJUVCTKgE\n9JHUK1QoxeJ6s6VvI81yjj6/GjgUHVebLf0jj5q8AXXFSx95QN1oBIO1CiPldS/dyNuvJaXLjSil\n8jvTl2NFSqDE4mpDM6mKTFsZZvMFWRKZSGMnmMlfIqe7hC5QyYvMJ59isrgPtoQOpf5VGUm5AAAg\nAElEQVTwGn03SUwfiKLQd5mjowmb7RXJGxR2H/clHBKbbguL9l8bPgoF3Aqx3Z/Vgf1mbJoGpDxW\nGs1RAGMKxz2G0jora6gmU9q+J/cZozNPLy4QdDGabbecHc0JBNo27U1MxmJzWwSUKJt17AzGTmL0\nFjDG7acSo8y4rouISmI5w7dtj7M9Wjxkx4OjUx49vmRzk3n19dc5//++QOd7YuixGioNVismR2cc\nHx8zn8+xxnC2nKMmB0v1F0Sz2exYrTe0bc/55TUpQdt1XG57klg26x3OgtcK6xyt9/iQCLHFVXZP\nHScrus7v8ZKqsoW9N3RMCmFaFw5KydzUOKVonGYxqZk4i7PCtHZoE0tSktZ0MeFzZNP1rLc79Eax\nyRtaldnEnlkzwxzP6bodZMtaAruVJrx6wTpkbnaJl168y3JSkbWmag4gr1Lleeach5OpDF1KUdHG\nmEipuEfnpJnNmjI2zwwx98uCH+iCBdWuxvAJJD9Hdgqd5zT1Xaqqocubt014bgug4FbH+x1YH4ii\nMJtU+HCJUj1dbNFJgQYnhqTTcCQojkVKjYywvK+2BdUdzTHe/vhlmmCKN/9uV+7ow1095vLGo1Sh\n5dpyJ0mDhLkPO0SXArLd7VjMJhir6PsO5yZ7CfVsNtsfU0Yz09u06NvR7ePRIecyuei6bk+GGjsL\nHzI5Fdeo3TYybSyrVcdkdsp/+V/8Ig8fXrFrewoPuuAQQkCrhFKFFNQ0lslkgnWao6Mjjo4W3L17\nl8Viwb2PfoJq0nBvukAtNR+6e4++79ntdqzlATfXK1arUjDWbUcbIprMjohSpc1PMZApiU+TyrDb\nDYatORH7Yu1mlKKpG6w5GLMaSTirmThT8iBVwgioXDAAZTKZhCLQ96Wo7gVRjaNZNtiqZnW14eje\nCUYlrp+cw9UVURquNwHOV1SvnVPbGnPvhMnRFGsmWDtyRA58gLHZHKPrUxJSUsQYKNGDmhTL+6BV\nRBtXfBiGa69Y/YGr76EkkYOg0JjKkYiQFYL7nlCc4QNSFF5/40ugniKqRdOg5ZgJx2QzK2lLcvBF\nfCvjUQ86gjwAZu/0wu+1BIOWQfShKHRdR7vbURkHWVHVVQmM8Z6IIcWiWss5szyqaZzBpxanS7s/\nYgUjSemZpQ7pR8aYZ4xUxq+Nz280Whl/T6MbgtKI9DT1gt02ELzw7/zsX8fWDr8NCAati0OTRCEy\n2rkltKrYrjPtbocxhjcfvUJKAWNLWlUzO2I6n/Hcc/e5+9xd7t69w8nZMcvlnMrUHNmGfAqbzYY2\neK53O9Z9y/Vuw81mS98F+hxIUXB1XdD7ymBttf8dEkJlLDpD9gFBUNYWxyOA4AkS8JTgHPEdvg9o\nbcBYglKEEOn60incrFZ0XcDFjBHF8d07qKxo7pwRdzvW1zdc7hLz+ZST4wX37yy5c7xguZzSNBUi\neY//KMVeuAbsaeeQSZHhyOBgKAi+B60NtnYlgs6YMpGRgKDQOpPVDCsZFQWhx1SJmHuyKHJ0jOD3\n+P8Nn73vffOt1geiKBi7wudLfLii3WUcZ4R6A5yg3DHA/kID9gj1CBiJSKnG34YiXX4+P9MuQmnx\nQ4gYlXC2whjHzc11SV2WGjGa3PXFmYnMeruhUpHF0WIvgBo3+263e2b6MJao2xfeKMoSEbrBuHQ8\nVozyaaUUVtckp9msA32XOLt7hnNCPZnSbjrKcHCQEaMRUai9U49GZEZKnhBKHiMYEIX3QgjQbldc\nPr7mjVcekvBUE8fJ6YK7d8+499Ef4mi55OzsjKOjJW3fsVhO2cSe63aLD5nr6xWb9Q7vM74PhACm\nmZaux1jUUKStLoQulUcsxWFNGUNqI1TWYFRG5UTOCSnvSLl7Z1M2c+WYLOYcn5wQV1turjcEr7C6\nolKOiXHMnEPnzM1Uo0goydRGmM8qtAr7G4HW1TBKHt79XAxSy3VhKE2kQjAFME6lY9O1ZdIsmU4b\nTGWKpf6Af4joworMGrRCVEITSGzJaJSaEoNB629dFN43u/8d1geiKDy6+G28+g10qtD9D6NsT286\n2pCZKzucARU5D2o+YMxnNEGTRINryNqCsaSk0boqctYY0CmCaHyIhOywYghtxGpH9hlUIGpDbmqu\ndi2bPoKe0O92hWcQepQW2CmcMyzmx4gpWvgYhfVmg9UKyQkxeQBHE9u2e8a9eVyjOYvVZvBwUHRt\n0SCkBIHAtDbUzqGSIUbHvJ7z87/wi5At6BpRg1sRALFo/3NmuKoJ3Lzj1ZGHUqWG2X+I5aJu15GH\n60sefvOS2T//E5Q1TI8WHN0944WPvkQzn7E4O+F4Maeqal68e8p2UcRfl0MRbbuOPidaV37nqqqK\n8jIX8pC1BmMEpbZYY8skIyVCVCAWsiLZmhwzmcLxaBpNo1QJBa4bKmvJR/NSaCjHMKdLYpfRml30\nnJ+f473HYXAxUk3m6FpIImzwOCkvjVWCShliRgl4bbCiITtyZ3DKoJRBVY5pvaCpHdaYkiqOLV6K\nQzeYI5g9mxYSNeQBH8qgdYdgGWPvD0XgLzqFd1wpO3pvkaCZZItSQxz7riN1b5BSAJOJsaP3LdoY\njHHl+1NNnxWS55hqikh5I5QoBH8g4dwCG0oga6E0d11LzhFjSoTc+fklomyJNc+HAJm+C7hJw2y2\nQETY7TpULFMHYwzOlotFGxlGzolGSuF6K+jZtm1Jnsoy3LWKaedY6Ky1VK4i7Dy73Y4UKUDpsCaT\nCd3uWd+JNF5svHdazFu59lsfiH3P5WbDa2+8yR996cuI0UyPFpzdvcu9O3f45Kc/zXw+x7iKDz14\nnj6U59p1HdcUbCSlRFbpIBTLEVLGVhZrLCJDnie6UJmBdrcr9GZnqOuKFIu9fIqBvusQVbQoxph9\nFzLmRJQov5rlfFGKVLstWopUBFFaa2QAmEfuRB5fNJ7tQBVqeB4Vrp6UIj6Mff+srw9EUXD6FJ/v\nDGYnS5TUxCy0vSeblkxPt7lg152jjMfhcNJANiQ/IasGJaeo6g5EX9pXMWTZ3ppcHCYSfd9jTZFT\nl1SpBCQ2mw1d55nPF/T9IWnZGIdziqYpBWezLseERTOoJge9gxnBqwx5iE8fAcZSSHZ7NaW1lq4b\nCEQx0e76IaOy4BL9rse4hqae0baG/+Q//nmqalI6Cqtpt9+5O8xbi4LPCkQQM1jEhWI5vn7zivXT\nG17Of8znf/f3efDgAfeee8DJ2SnHx8dMZjOOTu/QDJhM17WloMsYwBsGqveQHJUzPniMilhj0ErT\nyFj80sALGTbvcPSLWZNSJEUIOqGVKqE1CYxJVJXFOsf8+AStT7m5vCxHzJhQOaFcATuhuGSNOFTK\nuQjwZWRUlvdtMpnQTOe4qkENhK0/rWDpfa1vwdh9p/WBKApGTjDyAiIOZ+8Tk6NqalKq2HUXKNOx\n6c5Zb17Fp0u0BmtrnKqZ5DvUs/voaDH9Atc0mGEuLkOgyYgnHFyY8x7xt05QsTguT6dTUtQYU7FZ\nbxDR1FVF1xYFoxLDarUm+kBVVdzc3BTqc23JMWAqc+sCTnsm48hZGC+4cWKxp+AqjTWDMjGXf+t9\nz2YbmE3uEXyADF3bY6zj+uIpY4LzuOTWx3dzL7v902+9+2Xrhucyth8KkaIByT6Cht31hq9dfZWv\nf/XrWOc4Pj7m+PSkTDee+xDHx0umVY0xmph7Uu5hCLbpcwe52NiJjiVERoQsuWSxyOBmLELwA1NU\nC0oXtypFHoouYBXiEzkFVEik6HHWYkRhEE6PjosTdehKJiiDwOrWrzxu9PFaGb826lKqqoJB45JS\n2is8/6yuD0RRyMzR+QFaGghHeDrEZhSG3lfoLFT2hDzb4EPg+uoh1ng220tEGRbHD+h9hlyhUkOO\nFgiQD9OA28Ej3nvIY/Cp39uEFYEP9D5Q4tyq8nNZEXzicn1drMWmDTnfDjSxwzhxyCrIZe7cj3ei\nAWC8PT0pAOOB0WhNNVyU5UiSVHFGXq93/L1f+dUyARlMSG77RIxFZmzR38td7PZzu822e4ZFKkDO\nSBjqQ1aoLORQ0rZTCsSYeXP7kCeP3uCr5stMju6zWMy4d/+UFz78Imd3j1kcTxGBGD3ih9TpnBDj\nIAWgvJa1rYfNdwgevv377cfJqnQzIQSyPrweQWC9XpM6z+nJEbWrMM2E0LXEENhEj+SioNWq/Hwg\noVIih4AzY2jQwVfz9hp1LDnnwni89dp9dzuIP2edQkqWGBaErsG6Ba5qaWqD5AXWzIipJUTHzBgu\nrwN9+yaPt29gTM90eo8cYnHgTRYlDVoGWDix5wyMG3h0FNJq8Fq0DSmHQvMNaRAwWZxTiFTE0FLX\n06KVyIK1FWTFdtNixe6tzJxzBUXX457VWG32ncJbWY3l9x7faGG73Q4XoRkKiGY2nRNsQ99lBAco\nEE8WhaSEEvVMpHtOt4k4z979R4n0vnMae4V8yDrY/8xb3JZlzxYt52+5lUGgKK07eaDu5szq4eus\n3tQ8euUb/MmXvoitLSdnxzz34nPcu3ePO3fvUxlbuojkidGTc0TXCvEa0QYomE9l9VC8CocAHVFa\nl2BdNQbSZlDF4CREIbUtsS+PuZhMmDcTjFa4pqFdlYmMtfqZwpNV6VbeCTP4bjMQv9PrA1EUnKtQ\nckrMUyp3hJtuMTYRvcNYDb0pF27SnC4zvr3k69/8CtV0A7OOmFqUHlKYcipyqNQR0mp/rk/50LqP\nJieJjN/1qMG2ve97et+Tsqf3EbKlridsVmu6zhdSTkhEH/ZFxntfmJKVwyePqDyM4yIY+8xmHLUT\nhzuQ7FvlMUgmpaH7SMJms+Pv/Hd/F+fm9J0fxl+lMIyg5EiOGuPlxsd/p6IwciRKCzz8wztsAp3f\nclcaNWf5cAa/vfLQUuecyTFiBnZg8oHV1TWiFFfnV7z2yutMZlNefO4lTk6PePHFByyWMyaTBlMN\nnYrRA028HPWsPWRZwqDgHoqvkkFkBQfymnZYJcUUJidW2w05JSqjcdYyqWqyy+VGkA4j46KJUc9c\nI7ePe0NJ/D6ud/+/fyCKglJC1SwQdYRhijUZ6LGmRulCUU5hSrvR9HHDbLokS4/INc4FRPcoHSHv\niliHTMw3eH+1xxHGN3rkA4x8gpvrNfPFlOxLsEjXdYiypBwhFTCwbdsCXCaPtYaRhTBu9GZS8ABj\nzK3jg5CHzX+bmn27mBjjnmnbRzVjkWlbjk/uFpPWiw1GzUpRUJB1pkI/I6iySqMye+7EW1vZGCOS\nCrimkWeIVW87QgybZf8IA0cDGdh/g2Xc4OgGGWTMrUgJSX0B/0SR+1QErNqy6zy7Tc/1oxXVxPGl\n5Yw7d485vXPC6ekJd++dsTw+prKOph7j9TzaOvIwxQl6S86REOPeJk9zaON9TkhOWIE+BpQx9N6X\naL+UqKuqdBrKYnKx0U9DdubeLPfWevZY9YOxPhBF4cHdT+3PyiWE9RStBzCnmxAlQtWDFXLbMpUf\n4tMf+xlIl1RWkNiBuiFzRYgWY2YFj+iEeJWZ2QVP108gRZxV9KHH50gUsM0UnzTXT66H0WJxVbI6\n0/WB1WpFPa3JMdH3DJz/jBZFXRWtg1YWrSGnMNzlS9filIKY0JKLGKtLhBRR1qCtBa/KcYWEKIXR\niiyGEHqm+SP8T3/7f8FfB2ai0WpE4kvYqKuKMVJIsUTgqTJr11aAiGYwfxnOzT4HQi5RdlprGuxe\nhTlOCMZzqw5mH0YScsInKJSgcjyJg51a0ZwkJJdiU/6uCHK4LAsRSCBCDgn6jphht4u0Fy2PXz4H\nSkGtqop6Jty5c8qLH3qe+8/d5fjOksmkopkVQxen79L1O7zvCKF0dUjAOYNSAskOGFHZxDvv2XQd\nlbG4BDOdMBhMGop1AqUcTlu0GCQKooSmrmmaKbZqiKJK2Gx6y7GKW1URiN9V7PHdF6V3Y7LyIsXe\n/R7l2f9Kzvm/F5ET4H8DXqIYrfxsLuatyPc4+2Ec0cktltmYyqxVROcSzWZ0jdUzcnWXB/ch+ivE\nnwMLcm7wQaAPGNOjiPS74hpsXQltjTEiRqEGSXTfB6y13NzcPEM/nk4LM69tS64DqVCYc/R43zGb\nTGkmFZvrS9o2k/HUzjKpLdqUuTvcQrVzIgl7bEFGoxVVoQedQvaBrvVU1QSja66vnuL7luV8Rtd5\ntB6t6iPGKOpKiFnwvpiKQBnRiRT3JshYpfcp2MX81RS7dqUwuTxWzmC0Hi6N/cAeJUISUFljciZR\n+BcRgZgL1jci9UPcXvn8ne+qz4jZCIxzkvHoVrCfnvVW8/Txhq98+VXmyxnNrOHs7JSjkyUPHjzg\n/v0Fd+6e0tQLjNEgJZfDh36YGBTqmFOlYBOLLF0rKQrMPThcNrgzpYhYY4rlvTroU8aPI+byg7Le\nTacQKG7Nvysic+Cfi8j/A/z7wD/KOf+yiPxN4G8Cf0O+D9kPY8tWdIqHVh9KOs+YLGRtTcqnCOB3\nhsqcImpGSDO0PiXlCYJFZYihZb26GkxcD4KkrAr7jazwvpBs+r5/5hzZdR3b7RbvI/PprNyhjGJS\nG4Lviht0UBwdLXCVwTkD+TByVLfa8izsi4S3dk9nS6lEwWmkoOARmumMdhNwjeLX/o//k0Vtya5m\nu+n2516kOBohQ3jrCHbGTKQcG3z2WHEkgT4mGusGtPxwZlYqk7M6AHhyyNpKtrwfUoiZBcjMUoxY\nEuiUyTJyI+Vtx91v1Wof3te4Z172fbfvOmKCnCaIMuQkXJ63nD/d8sbDFdo4muZl5suej3zkw9y9\nd8bp6QlnZyecnh1Tu0IusqnIwzMRfCymu7Z0d4YDmJpS2hPLvPekENBy4CGMY+TSbeVSJN/2i77f\nK/67u96N89Ij4NHw+UpE/phi2/4zFJs2gL8P/BPgb/B9yH4Y34iYwl7nLsMdp5itgIhBxEGumM+e\np2NKTj3kCSo4tFuScjVYqXt8t2NzfYE1Cj+YcwL7sV+MhaUIak8YGkG6kuQUsbo4AeXoMXVD8Blr\nDd1ug7EVzaRQsHe7jhQjdhBd7U101CFsVimFRvZuRAArX87MAaFqGmpdo2Nkd7Pj+bvHPHlyTvBw\nNJ2QswwA4lgUTOlmfCAmsEYojsyCV6Aw5aiiKI7EOSP6dn875mKYwYX68G9eEkJxtUZltAg+FxC0\nZOCOE4wRXbnNknj7uo2rlM6p3xcF48afGQHQjDHj9VCeewyF9rxarbm6vuDRw6cYozk9O2a5XHLn\nzilnZ2fcu3eHO8spzz24x3QyJydPxmOVQ1QBoQ9GCkOGx4AvmUFYB6Wj9PhbU6MfrFP6e3q2IvIS\n8C8BvwPcywfz1jcoxwt4l9kP8h3MfRir99gew21CSbnUYgpkUVg3IaaIccdITGQ0ojWRMuISAk2V\nubl4yPXVBffv36UNXZG2Ose2L3eAShV6cTHXKZs2+FDyINHU1QSjFJKLA0/f7WiamsoKee7IMbDd\nrgmxkJCaqmY+nZXOZCBNheT3HYoenKBjjITeIykXqu8gqIp9pA0d0gtf+Gd/iEnw4Qf36btISord\ntkVpKRoAo1Da4I1hs9uSLISUUMqQyLjZhNCXI0pfGyJDPJ26DXaO4CJYZ98myBIpsnJNMWDOudAG\nkwASC6CBEMrggZQhpOKCosaCfqtjeAawy4dY+rdqQrLsCAlAkaWE/oIhhnFcaghdInh49PoFj15/\nylf1y7iBQHVnOeVTn/44P/5jn+PDLz1Pu1uTUoeicBtGjwdJeX88GEe6Vh9Uq+P4OKWEGRirST9b\n9L6X2ON7Ob6866IgIjPg/wJ+Lud8c/sNyzlneY/ZDfk7mPvw7Zbkck7dz86NIGkYuelM5hgTpaQQ\nq1Tc3uOOFDykEsIy3tnKSFCj9WiEooYZeSHTjHyD0YC12+3IOVI5Q1M3ODOYuwZPn3qs01SqQSlF\n7apyNxIh32pTb+MKjasGSbaQJNH7vnD5lcKaithFrp9cczo5JoauqPMypCioWg8cf4N1hhQi2Wac\nhj5EjClBLSVnRCHOEGKExrLrWpKtBhV6mTyULqlgZ3mQlIcwqAbNYDIbM2hN1gVwDLHIhZMWchL8\nWCRyAd1SUuQYgQOR6vZR8LDUaLn5dmctKaPVYgyphuZjHKFqlLjCfBxeXyWWnGC78fTdBVdPrvnG\nNx/y5S99gx/53Kf4K3/5c9y5e0QMLdoIvd8w6iUOlPRnSVzvxPMARje7W8/17dfqn4X1roqCiFhK\nQfhfc87/YPjymzJYvYvIA+Dx8PU/Y9kP451k0K6LGnCCMqkgFwoqOSOUItD3PSkEFGVePo62oMTT\npQgxpAFPiEAh3pSUpvGcGUgDyaWYjw6bO/aIZGbTht57QvD0fQHz3ODurHI5mwcSOg6dg0jJHEgJ\nRQH9GhS7UFKgsg/kkNie39CIZX5nxmq1RuceskHnVLCNqhh62Lqm8z2SI7Ub05vV3rxF8CTGMJpy\n4fsB4EQJHYfvLf4BeQTXSRILLTzG0mWESNZmD7h1qSWExM4HJGSiKPwQQo0xjP5stzfb7TVSmMvn\nb9lZt3deln3uhOgB9AvsgeJSbD1DC4T3kRg0Ogpf/pNXef2NR3zla1/hX/mpH+cjH/0Qd++eYemf\n4YzcLgpFwHX4/Ad1vZvpg1Dcm/845/zf3PqnXwP+PeCXh4//8NbX/wxlPxySn5KUjZ/IQ4uaEdUU\n9D1FyEUi3e+Kz6Fvu7Kh+22hMQ8pR3t/QTQiaU9zHtObxoui/CmFpaos2pSiQvZ03Y6U2HssNk2D\nHWf1YaQu28K4YxDh5DyoGTMqg1Ga2lWs2x3RB+4s79EuN8TrjhR7Kmtxy4q+S5DLBMTacsSyWpGz\nxkxnJd/AJ0IuITchBJT2e8KSMpq27+m6rhwRlGANaG2Lh2MongIwxKCHjgEOpPce5yijzViMVEUq\nelXMXUdwuOs9DFLmGA+v4zstkQNx620rPxswrFVRJhaQNIPR+6IQh67k4HOpiP0IGMPV9Zrf/b3P\n8+prL/MjP/IZfuRzP8xnP/lCiSc0+W0J5/v3fJh8/aCud9Mp/KvAXwM+LyK/P3ztFyjF4H8Xkf8A\n+CbwswD5+5T9oAda8ngZxVLE8Xp8cxQqDaj48JUkoFSHZEVSudQEhKwtbz5d4aVB5xqrIxfrp+RK\n6FNgtpiScsRILBmFUuK/xWjSgNJHMp2yaKNR2uKsplZgRUAc9aSii4FcH4hJMjAJAwGjLQmFQ6Fz\nYQlKzvQqs+22bIJHoqPXoFyxev/al7+Eu8nEyx3uaE6UHmsUMXRM64wWT2UVRXItVM7iU0QbiA58\nSoh4XKNQvpz5Y9b4kHBZU9cLwnDhT1VHEkXvM9EpYs74kOj7LVKX30UBOjpEK0IsiHydK/pe6CWi\nokD0+CxkV75HUChdEXMipETM8UB+GqYOiTycxw9FY2zZtUr7gqJQGAryr1AoUaQh6bsky0BMCeX0\n0KZkrFmXTi8IOQt4xaOQefz4K3z5Sx3+Zyo+9dnnmC0zojp0NJjocKEhVYmsDJmaJA0xuRIIqwKo\nhOSDfP32dbhf+V+wHdVIq1bsIwlud8LfofVupg//L996ePJXv8XPfO+zH74TS1JxwOl6Hj9+oxBq\njMYmi2g1nLnLHcZaVyLF+k3RDIiw3W1L2IvS+EEPkWwZUXatYjqvScPIK8bSUo9ailFV1zTNoI4M\nhNiSRGOQof0vHYkdRmGbFEhdojI13WpNlQ2CxzYNfhiHxQEEK11CiVTr+x7jBiBsUAb6vsdaS06J\n4PtCnCKSU0SlhNUC2SOqqBGDFGt240qo7a735JyoZg1YfSjODF1PFpwtKsVJU7HddeXoIaATKCP4\nOATDaIg5oXMkpjRY3Udy1oyy8n05uHV+fysGcZuFKnLoPEaKuFJFA7LHSgCd1PCcY6lBunRrvu14\n+Nor/MNfu+ZrL3+Mf+Pf/Anunc2pnIYugvQoPbxmeMBRYgeheCyq7zPN+d0zo36wZiXfjZUHC7Jc\nGHnWKHLsuT6/4P69M6y17OKYrgQ+HgRSY7t4O+exqqq9NsJriCETdebJkydYjmiaep8OHXJpha11\nt1D9kqUQQsCoVNpdVVh9610RPaGgco5We1zSNMFweX5DuukRnxEtxExhKsZEu+sIJtKkYeMAW9/h\nu35P83Wiyb7oDqxoTI4UnVIkE3CmJuQ0ora0uhjUxiFW3lhFVQ1BMSOQNzga9b5wMPoYi/EtisV8\nWl43JfikkF0/jPwE0QWQlKTQOUPwxf+gjDHYdwi3xpSjK3eKowFvGVlq/Sz4V3QOaZ+pIerZzVrI\nUEUjEYdjhA9dmcykwKM3n/Lkty959OYVP/2v/ySf/sQLHE01rlaEyABKBzK+ANciyBC++32tCvkv\nisJ7WBqGibkQkZwIvmOzuqF6cJ80EFF8CCQ3iJOkjPBa32OG8JUY4/7oELxHlOLo6ITtzeVwpi0G\nKN77AmSmRBjAutH1B9gHywoZN4SN+BDIKez9FVQuBWg6bVBRkS8T6ydb2tWWyWSCqi035xf7vMmu\n71hWVQH9xmxEa8nCkDzVUrsKK4oUI9EH7KyicQ41HVSUA5Mvj/ZhQ6htVVWDerRgINZO8HkwLyWj\ntWXWKHa9R3uY1UtSAh9KQvd8Puf8ekUMYd+p9aHUaIWCnKmqGrxHVCiaiAFzAPaFAYY9N04VVDku\njNqV/5+8N4uRLb/v+z7/9SxV1ftd5s4MhzPiTpGhqSgiJSaRZS2GbUGW4iQQICSBESSBA0PJY54S\nwE8BEjhvCeAnB0iAwEAMB45gC3EcC4wgKZRAcQuHHJKzz916qe0s/zUP/1PVPRQlXmoY0Rwd4OJ2\n3e6uW119zu/8fr/vtkNVssrXMK9SZXyQN/cTGrJAqIwUiegCQhmEFgyuL/wLB1/68qtsNoHws5/m\nIx+4izqrMbLaw6U7453yksR0Uf5LAi98l+NdURT2S6mcv2eWWMqCnBNKZrIIbIeL0WsAACAASURB\nVDdrtpsrXNchKKNCnAxPxujLDG40XVdcjrVQOBcmi3Xoezd1EQIfI7PZAiUCksJhMFYxm80BCBQ3\npfV6vadq77ImtdbI2IOSZJELfXbS6MfgGLseRMOsPuIPv/EVHr55hUaiK8V2vcbHzOgjYgyMo6Ou\nA9JHun5ACIHJ08hSpnicT2BKgpOtWoSSuIlQtTu9ix07pFggzN3Yo4WkaUvn4PyASJIkJrbipI8w\nbUUICsTOMSkxuMhmGDk5KKzPbnAMgys/b5ws6pEFQVAG4V1JzRZp36Xlmwu9XYG4MU6oG9yB3b/F\nGMkT0zKmEhO4I4hlpYoZi3MIaSarOwg5IqwCo4he0jvBN795n9/4J5+lW3+cn/ixj/L0nZZcXjFS\nFqdsIURpQqV4x5jjTdjze2VNS/Xka713RVF4R0dWQCRnBykSwsD5w4d02zU6C7qh34fKDuNATGn/\nC0lkkJYEbLc9w+Bu3PEjtYokJIujBSLofdKU91OIrIKmrWhn9d6TsOs35K7czRqRsFVFlqIQe4TC\nCoVVmlxJhj7wL373t3nw+sDyUU8tNJ0PaJ0w04XjvUdmSgcTQmEpInCba2drJSSDiNRZImVGxbJ0\nDSliTJgUkZlIYe/5GGgagdUGpSXJBwRFA9HYBdLu/CtHBjcZr2qB0YX1pxD0FNGXj5NuorZl6k6B\nMSXCRGAQ0xiQcyInQfq2fZr4NlXit0OY18Y0ec+i3HEt9juI6ftSSmDNRD7Sk8eiZRfLF2IpSuhE\njI4hG771rQfE4Q8R8ZCf/slDTk9PIDlyUnsVa5Hflx3DD+qIefPEX/vnvijkXMhCpeUL5Oi5ujxH\npEycaKrrbluSmkIApfAxTJLZxHLZFRWhD3hftudKKbwLeL/BHi0w2qJUQk4XarH0Vgyxm15FQQOM\nqa9hP4AEfd+XO/jOLGRyGBIxcXdxmy998TcI6ZirdaTVkc3Yc9QIal0Ss90UYtt1A0PX723ktGn2\nbW6WBcffuA1+gueMaOnGbpr7i/8AEsaxx1rLYeOZtS2zuqKpLUoKjFKYiacdc0JLwdFB6YqyUHhf\nJMtqoi2bqqWuW1xKXG1K8ZUUr4IQXEEjpC3ogSy26loXktP17+/tt8y3Mx//KLFoT5eelsPGFATm\nWtAWaA4OuH12xsnJCTlHttstFxcXrFYR4kSo0MXvYYwV998c+Rf/54tIN/AzP/PTHB82xd8iF8HW\nLvfjB6l1SGyf+Gv/3BeFJCgc26m1G8eBR/cfoCTUdU0Guq5jjI7Mjrk47K3iN+tuv1hUEi7Or3j4\n8CHL5ZLWKt73/HtoDMwqOD49wfny9c45bKunvIeu8ANiRmmxD3u1PtONA/0wsO48B/MZUhoqWfwG\n/8k/+t8Zh8DFsMHHuizVBk+NZExbZrMZbhyp61JsuonPYIwhBl9k0ymRBWQpcN6TyJi6olsti825\n1UijyCKhtKBpKrp+II8ePwbyYkaKkdoarNIIJTBGoZUkxELyQapyp88RrUTRQChFZSuS0FxtOozS\ntFM03MVwcX0xA24MhcWZ8rQEVPuLfF9A/5jjumjktz3eoyMx7hmkQgjkYsHJ7dssDg9QlaWqDPV8\nRrOYczJsee3r38QFjxICU7W4JQyj4vXXV/zW//W71NWcn/zUX8DcmhcS2ER5DukHWxSc6777F03H\nu6Mo+C3buEaaQKbkIsqUwUdiGohTJ5AFZV7M5UJQSmEwKCFIQeD6gfvnj9lWDenp53hZaLjyXHUd\n3fCIen7I+hIeLyVXfeZLL/6/nJ68n6995UVESFRWc3r7kPd/+IM0cwtDx9XVFV/46leIfuBHnnuG\n9z5zj6N5Q4oelRTRJ1pdpNRFbl3uzlVdkyuo7QzjyzLPdQOdyvgJ5Xhjk5HyhFmAYehww5IoJaOv\nEFlxiKKRDcMAIw6fBH0WjC5QmYyPkcEFht6DVIQoCD6S0haMKs1u8MTgaGzFzBqCU2ipuGBk5SIP\nuw2N0ZwczrnlF5weHqKKZwyVFrSmKjyFlDAN+DJgF6drAjEG6kagbIupBVw6ThYaPzq8z3TOF5q2\n1MUEJmVGU5UirhJSxj0NPeeE3IeIl4tQqR1lenLWmhaOOxuD4MuOSE0oT4NmOL9Ceoe5dUYfBpra\ncvtoweoqcd/KQtaKgWFcouoKRGQdLvnqm4c8/oe/zTdeueIv//xn+JBoidozMw502b287fh2mjM3\neAgwLSdvdEVJ7VGV62Nif2Ioyeu+LM3jzpZvQ0hXpPjkesR3RVG4v34d3UjOHz5mtb6gW2/oNj3j\nZmA5vDHNkpNybvrbViXpR8Q7kCOLxYyUEm+8dZ8uKq6y4euf+wLPnx0g5IpqJnEJLlcdnVNsh5G6\nbXGbK1549hYffv/7ODlaUNUQxch2WGIPjnjq7AApnmV1dcHD+/d59fXXEM++p7g1BccuA9JNPIGU\n7J5GG/OUJzmpLyttyp136jSMFFilGGXcL59CjKTsqW2DD2WD3o8RER1RQkwFGhQ5E7MAJKay+3yK\nTCrv0c6XMsR9250poiwXR44OmxK7nq+ZjZttT20bIoLKKGzdUGuLkJBsppYNPidc8HTJEZNATj4F\nUgpiZQmLGbO+x2iFFGEynCkak+KiLEjBT3f2XIxjkkAwcRzkjRHhBl9hd2R2RKfyea016QZ7siwh\nI6srT8iJ4+NDNJlx0/HgwQP86DCmQqLo/EAKAU9hlybVc9Un/uCLLzKfHXNycIdZrZk1MKsl4/+f\nFL6sKVT+WLQkokTbxRRwvuPR+dee+KneFUXh//79z/HqW6/xha98mfPz8ykEJpBCJslZ+SJ57Voc\ncqEm933Pg9ffREtomoqqtkQhkLZiPXgi8Is/8VGaReB4PiNF2PqAVA3WJG6f3ubqlft87GMf5dmn\njhHCoU1kDFswDhMFkTKjHz17j8VsxnK5ZLntEMYyV9cc/52FuzFm2lF4siikI7WbhacWPscSCFPV\nhrpRbDuPigpSkTvHDC4KUgygwOlEpQwpRlwMhBABhZQFTdDaknIkiYL3EyOBgnqIlLHWFOCeYpEm\np7tvcAmrJSlm3Ji4cj0hXXF21JCqGi0SehKiKTslaouEUJqh94WxGBNC6GLDJou02hpFW1fEpIgi\ngDBlwTdduGEXiCvkjS6hXOgiX7+nwD7J+jqO7+2aCSFKOMw+XyNl0JLROfJqjVKCfisY+wE3jAhR\n0qq8y6UQJEGOsRjdSIeSks0YefFrD3jpA5ecHp9QmQ2N1QjzXRiN7+iYlj7T4hzY2wCMrmPs/5wt\nGv/rv/v38Bm2gwOlGfqAnKBin3ab5WuL9vJ4JIVAkzVDDCwfL4k5YOuqaP+V5c69ezjvmZuGLA2d\nz8QpgUoIz+X5FZ/+sX+FZ546hTgS/AalM5UMSJvJLlIbg60rchYsZhXaHPPg/iMuri75yHP3GIae\nxWLB6ErQi9Zyz5r0sZi3+GkpVk0+CsYWvsPt26dslxv6vsz8Xe/LzC0NWRvGYUCLzOHpGRcP35oE\nPBIpNaNzCKH25KKQUykMlDErTqQspW3pWGJkzAKppgwFrcnek7Og2/Skui5mplkgYmBoIm6MhFlL\nVWs0GSsFymrkDRVoZSwJgVIlZCe4jkoJGqPphEMLcCngQxGk5ZgQukZQUrwK5sl+WZxvcANudgo7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001niUcoVHIK5t8cq6OLFjH77T8SGJwvuYHiG1Z9O9SeQ1zi9+j9fv/+YTP9c7yX3474G/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\nzzpkRzKrruX61aucOXmGcd2Qh5FyF3v6/q3tFP5/sIakXdE0ocVhi6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WvUeLMyQQdg/mG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\n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8/B3mlKUGdZ2mDSh6WqU8qlFIbfx7OwM1Y/56OjoRsmhrwfzRJHzeFFvnTJC0y4hazsc9VB3\nHwJuYdu90LLIOb9BUp7nHM5Lbh3MOZyWzCcZuVEk0nnzSGsSozBKoyRDCXWs0eJOLjF4EBbH2JYP\nY42d8vAcVgqs9LslaK0xiabIU4os5c/85m8wLVJk1zIxmnySY+lwxrCsaz789DHf/eMf8/vf/yGP\nnp2SljPSrGCz9s1NvvXNX+Pt+w+wTeubIPZl2cNOcj1YEW9zEjIAQmAzQM+hxscY42FyKVluKhDe\nSX/8yaccP37C7b09jqZT6vMl2lk++sEPePToEZPJhM1mg1KKk5OTocNOMMdCt52QwBnGaIxhMpsN\n+XVGaaZZwSTJ+PK9Bzy4f5e6Oufrv/yLvP32fcpZwelywXRvTmu7IaiKFdSbhk1dsdls+OSTT5iU\n5bWX7evBPK+Qtp36C0c3xCmCvxMHCo0xlFk69FzLjMEoTWoStFRoKQdfJ5hvAuVTc0Y/AnXpJ9xn\nTLG2GWslES3m8HdiFAcHBxRphgk94eh8TZD0jUGWmw1n5yvOq4qz1Rqd5ZTzPWrreHa2IMsy9mdz\n8jTDdXbIZH7RT/wMQ6zLbW+rkpaFBwMaX1y4Xq/ZK6dMspxJXrA+WyC6lvPTk2E/nRDfCYwZ3tcl\nNLKXO9Za6rbB9tkbIaVG4DMcuralrTcoQCnBnTu3UUZvCYOgtbq2oVqtOTtfstr4oO1NMN6fC+YZ\nw5uxJgiSc+yIxpBrmqaUmWFe5uxNCvLEkGrIU0NiFFoKpHAo4QYG2hWTirVQ/LMrdhVrzNi+BxBK\ng9SIyFTSUkDXcrS/z1e//A6TPCNRDmsbLC3SSESiWdY1T5ZLfvTJQ77/4U85bx2HDx4wObiFzEpE\na3nr7j3e/dKXPJCSZj6dKNx7NNZYg4bPAjIWGgb6Ks49WilZWcunj5/w7NkxrrN8/f1/g9KkUDVM\nTUrmJKzroQLUOcfe3h5CCObzuS8Z4CJ2F+YwWA0BsAhMs16vvfnW79Oa64Tl2Smr9ZLT02OSzFBM\nS7IyYXG+wAlf2iFRZIl/9h9+/CGnqyVWwGa9vva6+7lgnpjixTkOno7t6XDMGEOqvbYxSpH01ZAC\ni5bbi31ro1y49PfYh4k1yXic8Vi2SF2GxoUQg/ny3nvvMd+becRMgZC+U05nfRP4xXpNbR0niyXH\niyVZOSefzhDGm0JlWTKb+e/Hkn78M04cDYw+jm8Fc0smKVmRI7Tqc8/2OF8ufGwKye3DA6ZlibC+\nZODp06dbmc7GGGaz2aWs95CFHQtGYDAf6cEIJXwr48PDQ4osHUobjDGs1zWts1s+jaTvW5EmfZbG\n4v9/6Tlj02Is2ePPgsYJ/w4pMEWRkaaGRHvfJjBfnOEbO9DjY7sW+zgNJtAYLNi1YEM2QvwsQdK/\n/7Vf4Gj/AGEdoT2skA6U8A0OPa7Ls7MFT0/PmM73yCZTWgTOWrIkYW9vz9+rs89lnsA0YS7D3I2r\nca21nJydslyds1iuOD47HdL959MZ8/mcaVEyK0qS3oeKc+UWi4XfRrEst2JKY8AinodQOg8+2Cml\n5GC+x7tffsdfx/j5vX37NkWRbgV3wzMAKGOo26Zn1OsHSV+PxFCxvchjE2v8AndRWIQxY1hruX37\nNtoYTk7OaLqOpmmp6xYlJMZZJlqQ0XJ/b8KdsmSv3CPTBqME0vTbs2uHSPrtAoUGJRFSkos+EwBA\n+Lw3tMIpiVM+PmNDwmJ7kTnsfADet8IVwmcKCEAKlPI+Tqos0km0U/QfYjtFagps5/gzv/WnabqW\nP/rgvyXb+PoXpRPaDsq92ywXp5w1jh99/AkHBz/gt37jm5SJQLdrTtdLZntz9tspd+/s8+OPf4rJ\nCoyABkHdSITWtJ2iMBKhXN9xxj93yFcLgEztOprVkvnRAYfzWzx79JA8Edy6vcdbt4/45Cc/5PBg\nhnhcc7pcoCwkbctUOg4STWc7mvNzrIWnz878ok8KZN0ipCPJFbapsSS41uE2LViL1YLZ7dscnzym\nSFMen57xzv23efrwmH/rK7/AbGX48eoxFQ179zOOHs85e7JhXuzRNR2zyYR1tYS1pV0u6YSgPDhi\n80WtJH0ZOBq4UsJnWTb4NKFz/1hDxUmIvhXU7hjO2HGNrxGYKJbQ8d8vosv362MdyN6Blb5GSF3A\nufv7+4M0jqP8xqhBGp+fn/P42VOstUwmEw4ODthsfH8z07drMsYgxbYWHAuseGzhsyD9Dw4OKIpi\nyBdzAtrG0nT+c9xFM/XZbMasnPjUoairZ6jqjUGEsTnsx7Ld/D105gmtvFarFU8eP2M+n3N4eIhw\nvicF1m990nb18G42m82wt49zbhDY13lfgV4PzcN2TOYquurBxt8Jk/D48WParsOYdIClLxb8RVfQ\nNE2ZT2c+c1lpdA8KgPWZ1H0emJQC1cd4RK+BnMDnyeA1Ddb6+IlgyKCW9H/3dTxORru1KR9vEUL6\nugQhgA4hFIILxgzPaYyhspZf+qVf4q07d1l9+oS67lAIKttgO5+CQtdxulzwwx/8iKfPnnEwm3Lr\n7l3++e//AcenZ0zmM6bTEuVrI0BIOixKXWj7rrtIewmOeuiRppTi/Px8yOA4Ozvj7S99maTIWZ+d\n8NNPH3F2csy7d+/QOWiqmv2jQ6qm5cHdO3z7ox/w9OlTkJosL9jf30dIvxzTNKWufDvcJElQiWG5\n6frNjS3CSZTWqNynUinhG1QeHx/z7tEd/s9/+n9QHkxo64rZwZSDwzmJzNBWkzaaRkrOV16INJ3v\ntz3NUtA+w/269HOheYK5NvZvYhs3SJmxHxEkbSgfDo6nFn1QFOHTWNzFGJX0TQSdFN6cEWJoIbWL\nvS/279ydPS6lHBjQH/Sl2o4QcxG0XYcTgqaP2GdJyoMHD4ZcMolAWLe1o4NzjrPlgocPH1K1HZPp\nlP35HIlPs5lPZ5RRXEOOBr8LJQT6bTzWVFU1+H/L5ZJOOFRisE6wrisePn6CSfvyAKVp65q29l1X\nQxuq4N+EwGvIWYvz6jyA0O/OIL0w6XDDcwb/6fR04cvFV2sMiiwxYFu0sGgDR0cHfVP3i1KLrutA\n+mTTum3gBkvwhcwjhPjbQohHQojvRMcOhBD/WAjx/f73fvTZfy2E+EAI8UdCiP/o+kMZvn/lZ9eJ\nRYwd+lCfEyLh8YIILyfEF7RUw9yFzOPYhIijNwjPOK7fysP16R9C+AXPFkrniNkqZCe4vuUtfY+D\ni6wFSXg1Dt/7IPhPXlD4uMj7X/sqkzJHSnBue/t6YwwWb8r8+MOPWCyXFL3jboyhqiqfvDmZROPy\nY1TCDRH9MO/x323bsl6vMcYM7W6FEKw2G0ySgVEIbaiajvP1Gidk333VQ8q5SQaEbTKZDLlxk8kE\nIcRQ8xMjY9ZarOvLqm1D29V0zvbdXP17rOuaxWKJlpJEG4osx3YN+3sz9uYT8iJhtV72HXwsJsl6\nBvTzutpsbgQYXEfz/A/AXxwdC/uOfg34nf7fCCF+CfgrwNf77/x34kVpxQDcvOHc1rcj3yUUWgV/\nJ0iyGN4Mx9I0ZTKZDP5DMB1Vr32k9PvrSCF60+oChbJKYAO61e9EgJJbpQTDuRFIEM4VAfWRCt/n\nQOOEwuI7kDoUVio6IbFSIZOUfDrF9f7J+WLJn/+zf44//ae+xYO797B1Q2aM33pxsWS1WrE3P2B2\ncMi3/+AP+X9+/zt8+NNPODzcZ29/hm1q3v3yl/jS2/dJtMT0nXIS3WdoGLmFpo276EynUwC++93v\nsl6vuXPnDqtNxfzwiGwywRQTZoe3+N3/65/z8U8/RWiDEL7HHc4XoLVtu/Wepn0X1sBQWmuqqmK9\nXqMThU41xlzEvkKTj+V6hVAGZVKKcsrHH/yExx9/wt3DAzIJ9+/uU5aK2UQjZI3SDmv9LufKpCjt\ne4h3fVbHdemFzOOc+13g2ejwX8LvN0r/+z+Ojv8d51zlnPsh8AF+w6sXDyRKU9nlMO6ChsNPkKSh\nfVCIWgdbPTiswNa+mOGckGM1NMOzF40KrYDO2q2KUC8FHU3bYp3zCFxo06Rkj5z1DeO5XBrRzyvI\nfp/OzpcWBDnjQmWqVEhlUL0ZE/oya62ZTQoODw89bH24j+p3y3bODelH67qiaRqOz0559OQxy9WK\nIssx0oMMqu/sOfQw6zVM0zRgL2I6oc9AKJcOCzf4O6F9VKjk1Cphcb7yXVEt/Pjjn/L02bPeMYe2\n9Vt/lH3JdkgoDQ0S8zxnNptRFAVN07BerykK3/VoOp/gpKDq9wUKGtnvFeTfc7Ve01U1Rgpmk5Ll\n4oQi0zT1muVyQZom7B/uIbQizTPapgHpWFerP5Hctqv2Hb0PfBid91F/7BIJIf6aEOJfCiH+ZZyZ\n+zIUat2TJBnScOJ8stA2KQTiQlujPM+ZTqc+jypLEYmGHtUK1ZOt7bxvoxXC+M+tFGDU8CO1/wmm\nWkff1dPZvrTXx2NcMO+Er70RQiCUAaVxVuHQIAy2kyATTJqj0wyhDS3QCUfnrG8QUtU06xV//s/+\nO/y53/otpLNM84y6Lyxbrzfed1Kapycn/PDDj/juBx+gtODWrVsDs33pnbfRUmCUQGufXS6c7wM3\nDoaGuc7znCRJmM/nrFYrHj9+zNOnT5EIUp1SllM6J2mc5PDeWzxbLPjeD37g50456rYactdCL7fg\n98StrIChbmhdb2i6+qKzkRBMZzOfEiU1xWSCA9Z1w535EdQtt+Zz9oqMe3f3ULLhl7/+ZZpmydni\nCZ1tkFoxncxJtCZPfRl5e4NK0s+Mtjl39b6jL/jexZ6kyruqL8s8AWoMCYxxC6m266iqZivbABg0\nTTAbQnDR9fGZpmt9zNH5z4TyCBv9QhriNBeJ1YOZo0bjGky0iIQQCBSm15QOH7C01qJ0v1+mdTjX\nBwQjcyJOmzfK8JX33iPptyxp25auT7OHULdSc3p6xqPHT9g8uIdWgv39fZzwUDP0+xWxOyNiHCQN\nFkLYoiM8T7PxJQp5nrNQiq51pCYlyTOqVcfx6TOKPMfpC7/m/PycLC8Gv3Uc4Xd9mnrbdignQOGb\nRa43Q9KoB3EMrmtR0lCk0Fa1b32sJft7E54+eYbRE6yFuqkoesGmjMZ13dCI5SZr8GU1z0Ph9xtF\nbO87+jHwdnTeg/7YC+l5PQpeRLHzHwrggKG4ahfFfg/gnX8AKT3SJTzDxD5KQNgC4mOd24ICrkLS\nLplr/bR3fdZ0YjKkvKg1Qio61/eSs9YDCwGIUKNsByn58jvvMC0nNJtqEAaN7ejCLnFI1tWG49OT\nIeWlLEvfTNBebO3eNM1QrxSgk3HeXQAMwrGg8bMsQzjo2hb63hGttVgcs7195nsH/PTxQ07Oz5Ba\nDPMfYjWhYDEUFMZ7i4b7GKOHOe26xlsT1jftCPGitm0pstzH49qO1GgO9/e4c/sQQYeIzNuwboQP\n0kXv53r0sswT9h2F7X1Hfxv4K0KIVAjxZeBrwL944dXcFTle16QYXQvJg0qpodtkyIEa57aFxntS\nSirbsm5rr320xCmBTAw6T8EoOtmnzCjp9waNtFGAmtuu8z/RDsvx2AKjiZ45jfGwbtU0VJsGZwVa\nJTgLzuLjPkohjfaMA+D6TIq2pWsasB2z6ZR/+1u/wWRS9CYQgy/StQ6hJMvVhk8fPUL2WyUmSvKT\nn/yEJ0+ecPvWIVliaLuarEfCQtAVLrR0WNTgGfv4+Nj7XzPfM0AjOD9Z0mwqhFBoldBaSLKcfDZh\nsV7x+PgZlW2HbUFC8meopxn2Pup/AgPdvXebtx7cH3Lz0jRFGj8mIT2impdTFoslqdIk0vCDDz7g\nfHGGUfCld+9z794t7t8/ZLVa8PT4CUhNmmdMi3KorH2lzCOE+J+Bfw68L4T4SPi9Rv8m8BeEEN8H\n/oP+3zjn/gD4u8AfAv8Q+C+ccy80IkN0/mWZJ5b2cdJnXdf9bmHbkekYNQsgQZBcTdcOpl9sonjT\nyUcbwneH++5A2AJkHudpbZMcsh7GUjyOcwSEK0791/24wznWWt5//33eedsr/ZBIGWsN3xGzHVJr\ngtmktaYoisHvCMw+TqiNc8zCzgOhKjOMI2QZpGk+oGVCSVabDZu+bsqbln4f07BlSdB8Y60WZ5wH\noRjuAWzteJBlmW9BlZhBE4Ye2kL4hii+bHyGtb4cvGkrL1j7jYtvuv5e6PM45/7qFR/t3HfUOfc3\ngL9xk0H4ILfaWmQBNo4zeeNWr7CNyoX+xMAQIKw2DUYlOOsQypEmmiI1tOuKMimYJlOq84bvf+cD\nmtwjVG/bu0zynIO8oGgFy1XNPMtIlSbroWvhLKLtIXAhPEqF10oBgXNS0TQtyjo6rZFKI7Tf3Q2V\noKRk03Z0XYuSGictlW1pO4cguWDQfmtD4S76x8WLuVquSEzGt/7N3+CDf/1jfvTRYxJjEShaOpxW\npMnEV3EqyR/98Xf5xjd+naO7d5h974/56U8ecrj/gKdPKs4X1m8Glea49YpWdAgjkA042yJwKCnR\nOBrXkSaa5XoJRoAR1E2LXW64c2eG7Cq0wM89krqDqvMMv1h3WOHjbucnZyzKY043KzbVkqIomEwM\nVeVjMSErpHu8prw3x8qW6f6MW7Re8wjFSlienhxTbTZM3v9F7qbfZHKQsjn4Y541P2GSb3h09phO\nl0zvz6j/ELQWHBRz2vOaTkm6dY2WkuYGUPVrk55zXQpMFVOQLnEiKfSYvRQ469P1A2sqFUy8tW9E\ncXxKk9dkSco0z3zZ8npNahL2pxOkcLSdX9CJUb69rvMdO0NQTUrQzm9tAcJvZWAdot9RQfT/uVHt\nTMg6iJshBoChiySwikCC4Rl7TeGkYz6f85WvfIX6n/0OZVGwqiuQPiWpzKdgHVXVsFics1idc3jn\nnm81e/YxXeP30wkgQ9AsBNhWOrq+iDBoo2BubaqL3tFtY4dMaq01WkBdV1sM759F4dxFX+nBQoDB\nhMszn8kw9JJufRlDa7thl+snn3zK4f7BcN2u6zg+PmaxWJBMfE+Ftd6wPDvn+PiYci/l6OiQfqdI\nlBKE9ixd1/Vtp67vyXyhmOcqxhmjaOHv8MK8D9JBD1uXiW9KfnZ2RnW+wijJZlPjOjg7W9JULRuj\nyLRHsGyXsza+R3QoO56nfpNc27aAREpQ+mIMgZTwWcqCYBrgs4K50JBSSo/q0ftPOtTO9KasAG0u\ndjoL/OkkJHnGpq5IEs27774zJMJuqsrHovoaoLBIT5cLHj9+zJ279zk6OuLpszNOP30EeJQv+Ida\na7+HqXM9WCKxfa5b7M8FkxJ84HS5OGW9XpMIgZTenGqjTkX+nQjoLkCbeBv44C9qfRF783PqC986\n4eNq8tAAACAASURBVBNeN5sNy+WS/fkeuUlYOy8g1+s1p6cnFHuKx8sntNMNxiRMiymttdy9c4ui\nMLjat72y7cWztNayO8FqN33hmAe2oVNgkHxBGgZ7f914pnECBD7juEhTJI7caO4dHbE3Kdms1jxr\nzmmahh/88U+QwlGWOUWW8+j0hNuHh2R5wmwy7VNJEixTssxrIYVAS0Xrm6f5NBsLogWdaESvVhz4\n4KPwTTd8PU5fkCfNkGbSyX63tEjzBC0EDEmlDqibNV1nKeZTvvXr3+T9r3yF737/+2R5wbpaQWep\nNo3vwJkYHj56ik5/xPzgDl/72tewFo5PF0zLnKpas2laEqU5ODhgUa2p6xqlJVIInPB+irUWreQQ\nX3POsVgs+NZv/Caf/PQjXNt55lWSu0eHLM7OqGu/fYe11qNxfWmDlH6fnaTMkf2WIufn5xwe3Bpi\ncsvlkvl0j8XSV3tOD/bYm83BOuazGdLBcZ+KtCrWPHn6KbfuTymLGWavpDQzint7fPt7HzCbZNy5\nvceP//gJeZaghGazKZlrxWp1TnW2uvZ6fK0SQ29KYyaKndwLupCUUvoOomVZ8s6Dt/naV9/jq+99\nhbfv3ePenXscHRz2+39aNpuadbWhbjrWTcNyXfPo5ISfPnnCx4+f8ujZMceLJVXdsWlbamupu47O\nOmzncK0dTIFhr5jOM03YpToGAgIFSFpoj7IJrUDtSPHpsxqklOR5Okj2d9991zvhgsGMDY79ZDLB\n4hdr2NmtLEsmReGbnGiNVgKEJc/KnVD/YHqp7d2uQ5JnnudDb7VgXoX7BGDGObfVMBEYEjxDvtvt\n27c5ODgYQgm6F46h10FZljx6+JDHjx+zXq89amo0y/WKRa/9bCewLZw8PWVzXjMpS8oi5fatfeBC\n42RZNvjcN0kTez00j7i8FwwwvLjgzwSpF15AjG6FrOkYkg4qv6orkizB/n/kvUmMZVma5/U7w53f\nbIMP4R5DRs6Z1UOVKFCD6JZowaZRC7FnAaJZwYYVbEDqLTRCQkICFZOA3jUSAlqFqoTUSFBAC3Wq\nKquqKyNjcvdwcxvfdN+dzsDi3HvtuWdEpWdVqxVZXMnczJ+ZPXvDPfd83//7D13Lsij47jc/5C//\nk7/ONM3BdPzg/Xep+6veZ59/zmaz4eX1Ja1tsZ3jJx99inVd0L/3bp5//r0PePz4MWfLBdNiwnw6\nZZGHiBF6+orwnrpqSCYZpu2omwYpNZNpjFKa8lAjdFAxxnEctDDOglIopRHiXgvTdc2IdA3zrDhO\nSKKCsjqQxoq77Ya//M/809zc3PCHf/QTUh3jbO8FoGPKQ81ESWSU8urymvpQ8f67T/nRj37EyXIe\n6DF34YR3fWJaFEV0bUAs4ygadTA6ue+PVBQWy263I0kSbi+v0DC64pysVsSx5vb2ZnTEOVkGXU+8\n3ZEVOfbovfzRj37E+m7LkydPxt2ptYaT87PgweY83jnefedJsL9SDdu7O4SHVkjiRLHZ3vHnfu37\nrO0rzL7lwTvLsHMmktt/6i/ykz/4lFevXvLwwbscenlCnufcbcq3Pm2/HouHtxuSvom2HR/HvLjx\nPruwoOTAhhaS1XLJ6XLFJMmYpAnCaSY9ObCIErJvfJPdoWQ6KzjUNReXr8A6utbQeTMu2C9eXtC0\nHeVuz+lqhbXBJD7WgdEbKxmsjYxFVDWBAhfYBs45XNehlcL3twkl+wUjcL3AbYBtx77ojWGrMQZF\niBOUQBRrVvMFjx8+4qcffRyEczrEtQ+Ja8Z59ocKKTfsdsFNRwmJFEE4dtw7jry/2NH0FlHDBWmw\nyW2dxfTmHLe3t0RaBj7aoaJRkvz05DUYeGjsnXOj26e1FhEFyH0+n48Q/rBjDbva8XkSqyAKjPrP\ngyWWxXNzc0Uy0aTRrzCNF9yWz9lcrzm4A2en7/LgfEWexdS7dhxSt+199MrbHl+LxeP96w44X3UM\ni+fLFtqXcbC8F+DdmAbtrePR2SnvPDhnkiYUUUSiMrRzuP7Nmud5iGOPFFXTsJzOuLi+4m6z5uLq\nEmsdQsC2PGCt57CvKMsDprMUSUwrFWlsEHGKFB6Ph7pGCkWcJkF0ZgzeQJzl2F4AdzxHsaJnF/QW\nTkIItGR08BE4hLfBYkkPxogdSsBiNuXdp++QpQmHriGJE/b1YZz9WO9omo5SlNze3jKbzdD6nkE+\nxMerSI+Rh4fOUh8RTkU/4AWwbYM1ARDYbDZMJ3kI2r29w/aD3WMQYmCAGGNemxdp7udTwBhNMpvN\nQo6PsxgXvPcGjiKu1265QMUa5kG73Yb9pqDIJ2RZwvXdM3abPaJQzCYpZ6cnnJws+Xxt6EzTl2yK\ntq1+Ccs2GGv2P+7BD6jMMVw63D6+mX0f0bYtwgm0EEihEJ0lFpLvf/BNPnz8hEJIMg8TrbFVQ5YE\n/Ytpw3zi/dNzPHA4PcN8+9vsDwd+8tOPWO+2IcO0dbRVxd3djt2u5Pr6lupwYDWfc3qypM5blBDM\n51O0Ccodbx14S+dDsx+lHucdQh6hdFLijQHnRyMS7z1V02IBb0MPYTuD8R6vA9halR0WQRrH/PA7\n3+PzX33O3/3t3xr7EtnHPdoOWueJrOezzz4jTxPOTlY0TUMSB3P0KE05efCQ7uUzqqoaTQK1kONO\nMbA4ptNp4PxBcN+UsJhMuXaOQ92w2WzwzvHOO48oiiLAzT074fT0lNlsxu36brwgXl5e4r3n5vpu\nJO1aa3HKjazuEJqcoIUMsS/A2dkZ6/Wa6+trdCRp2pq6tEyKHO1TukOH1o5XFy/A1Tx8sOLH/+Aj\nvvjii9E8RPK6JvHnHV8bwOBNGcJXHV9GWhzKgoG3NcgQTNeCC0hYJBWzyYT5dEYWxSgEkQhDyEgA\nxqCsI5OKBIU0BroW0bZkSrHIJzw5f8jT84e8c3pOGqXEcdI3up7dtuTjjz/m02fPuHh1RVnVHOqa\nsrqPVx/KFeHvnXyOxXzD48c56JkESoigxe/7kKDGbLFdhzOGstyF6XvX4k1gcC8WC771rW+RZVm4\nL+jRrQYvwsWm6Vq22y1lWbKYzcnTpM8LDWVQURScnJwE2k0vNxhKxSzLgHtrqOOdaGC0D8HJXdex\n3+9fU50OCdTW2lHSPYAax6/Tcbln/L0HH4SSfDCxbJsGHUUhwtJ7oj5EOFxsZUDdooSmqoiVZDYv\nWCxnI59uGMIHEOPtz9mvxc4jekbyV5Vkw/FmaXbMxD0+AcfZD31tTAjDneUTFpMCb10wvdCarjpQ\n6IT6ECTAAztAxRFCCoo4pmstiRR88M47WPsQYxwnT0IS28UXL7i5vabc7Wk7y+fPnvH555/x9J1H\nnJ+f8uTJE+I4ReuIYjJBqt4sxDlcZ/CxHKFn6z3CWpTnPjyKvpyRitZYuq6lrZvRp3l3uCEtcpzV\nSBVzaBxpXvD08Ts8On/Aq9tramdQcgiylegoocgLXl1eIPH883/1n+Pm7pY0ThB18JU+FhYmSYLp\nHXTGKJD+NW5Nh/VBR+W9D5w1HQWzkTLmdLXk+uqKu7s78jzn9PSUQ11ys96wWq2YzWbcbdZs6gNx\nmnI4HJBS9kyDCVIITk5OOBwOQTNFQOxcZwKTXIWebrFYYK1lv99zc3PFbDFFC0Ua5UzzKZeHO8pm\nT3vxgunsId/97rf5n9Xv8fLlSyKlyfIoCPxeXr31efu1WDzAa1eZN3egN28/Bg1eG0i+4STjZUdt\n9qTWMtMx3zg9ZWUVeePIpUC2NZEUGFfi1CHIsDsLXpL6HKTGeoilRihNYwXOSpR3rPKCRZoRI4l1\nwkt/QWs6jIlQWrGuIg5fHIgKT5dvybKMB1lC1BqKPLjWOFshnMPjcVGGjCRSKagEQnq6ao8xLZ1p\nESIQPJ2HsmkQUlM2NUZAXTWkqUKKjsYZtnclZbMnn2WovaYta1wXkLoojWmdZW8NVkaYsuJFY7Dz\nJWK5Yn99QxR5rGl6WF1Sd02fZ1PhsVgTdpuiKCg3G7RW4aoep6zXa4Tc8cMffI//5//6HYrVFJFH\n3O03LCY5RIqljtnpDTc3L/jW935AeqmojEYiiHQg6wbJBsxmE9brBN+aUTJxcnIScnWUDNGSUVCC\nxlkID/5C1jycRFxcXTNbTZksCq7qiD0GlVj27S3JTHOeBfb6legQKkKrJMji3/L42iyeP83xJgI3\n7E5aaxSSXEfMJ1Pm83nY6gGrJPjQ0LvO4FJL4yy6r327pkUoF6TRSuBbH1Kte1l2osPcYTmfoZQi\nz3OevXhOJYL966EsaZQKuZkD6XE6RQl1RNi8vxhYa3F9KSfbEMXRmlCaOeeo6wNREiNVRNt1dK5l\nt98jEgtIjHE467m+3VI1LSqKQ7hTj5gNvs7LxXQUBw5kzouLi5FEOTTdQ39R9fazx4TRQcczNP8D\nxIwQIwNjUKAOIwR8YAj4vgdLkmRkFIRmvwTn6Hqvifv5lBqZCMPjOCaJDiBDXdfBa7p/Dtvtltvb\nW9brJeksKGbNzlCkKZHM2ceB7iO7CB+rMQLllxIw+NMcx/Sc4WutNW3X4bynahrarMD5AB1HIpAy\npQsoj2k7Yq2pDgfSOENLONQ1cRxqYJWkGAQyilFK4oBJHgUDijRjoiNWkwnnqyW7cs92u+WLy1e0\nbcvV1Uuqu4bVYsn5YkGssxH5cz68AUP/ExYzxCICFayvLDb86x2b62uub+54eXWF8WCsZ2tCDHqi\nE5zz7MoGYxyb7Y66c8RJQi4FKo7wXjBdLmC3Y7fbofAcdgc+/vwzkiQJKB+esiypupbJZEpdN8Rx\nQhwn0KdDBKdPQRwnrFYnaK0pyxJEGGBWVcVut+P999/n5tUXzIqAwN3c3JBFgcWdVSn7ssK2HbPJ\nlJ9+9pwkzUZ5NwS91OBp8MXdFyFHJ825Xd+F0g1PnCbkeU7Ttay3G+I0oT0cuN2sWS1P0SpmkimS\nB0+p4gNNJtAyoygcQgsmWcGuNT2lKPr/3+I5lhkcswyiKCISEtt2Y2/Umo4YOFiDsAEsEN7T1Zam\nMzjXBAay8UBH2xhSNJ2zKBvuw3pQsUJ5TywkSmqEApnlIVZeK+quoawOWGdoqpo6rfsGNxqv1h7x\nWt9Gr/kxrcE5Q2ta2qah6xpubm64urnmxctXbMoShKLpDAdKZK9ddc7jrAzWT01D6yVpFnO1WSNa\nNTrWDLvCAAcP6OTgG30sDxikA8OVf3DBGXakwZj9cDhgnet3lICmzSYBXcuTGJWm2H7YLfrnrZUa\n0UNjDPoouWI4BsnDsFtNJpPXNFvH/MVh97Q2wNpJkmDaFulzirTgZLnkC3dHmiXMF5KT0xW2EqRS\nU9sQa/+LxCT8mVg8x4zdY2a1w2PxwYctitBJjBcyvIl9QEfnwy5wd7sOJ5UK30micCWXkQr+BR1I\nJFpHSOeo9/tg9BFHwV1HiFB3K0kRx8wmOUJ4NrvtWKZ1XYdpO0w8sCF0gK+dD9a+DPScoIZTSoEM\nJ/Grqwvu7jbU9SHAtw7a8oBIAsJUHWpM12FskHd7EXbKLMvQkQLZl1HOkmQpSZZye3uL1IqqqRFt\ncAHNJ8Uo+ntz8Qzl02QyGUu2AVnL85zy0PZKUB3YBpEO0/s8w/cCNtc2iH646eOQ6KbjQME5Rk3f\nHBIfL5Tg0RCMQoYLz0Alcs6RZOnIwtjtdjzRc7I0ITrEiDaUnX6asljNefnJJWm+wHVu5CC+7fFn\nYvGMw8U3TNyl1LRNzWo6YXF2SpzlXO/3TJOEiVSYpsU0DevbW140tzx+/JjTZYESmnS5ou4ssdKU\nSLZVySSSTJOgbkxNFTT0hxBU6wWkiSRRMVmksbRkqcb5lkIkLGYz4n7AGKuQ2oxS2J5t0NV1cA9V\nEtf0Ii0t0FLQdU0w8osiTk5OaKxnXwY+V6vCCV6k017TH9xGozhhulzx6uqSuj3DdI6yDhKM5XLJ\n48ePx4Hj1dXVKCCbTqcjBJ2nE9rWkCQZWZZxc3NDWVaUZcnp6XmYP1UVSZKRJBmduaKua+bzKYdy\nh1KK/X5PohXzomAxX3CwhiIvOJWe/e7A5cUF5w8fU6QZddehpX4NsrY+WPg2pqMxHSqOOHv4gChN\nuLm5oalrXFOTTydEaRJMRJSh6lr2+wN5IohFQr0uyWRMe6hoDiXrdc3qdM6nP/2ctmdfYAXe/5Km\nYb85/PwyWBp+dqfxvdRg2LaHw1qL84IoSUnSFBnHWCGpOsNNucdFEXdNxW19QEwLXu427IWgzWI+\nX99wXZfcdjWlsKjphJv6wG1TsjE1dWfwUo3+ZcYYhHE9mKAokow8SVlMJswmk3tCZV9idF1HW9Uh\nCrCfowwcviB+s+B6OpIPnyU+ABoeIq2ZTxekSdJHqGvyNGU5mbGYzjhbrBDW8fDkjCLJqMs99X7H\nYrFAKcXt7e24oxwOh1G2PpAu1+s13vvRU8AYM7qLDqValmU8fPiQtm1fYwu0bcujR4/C4LWn2rRt\nO6o967omiWIWszm2C+rWtm5GDwNrLZPJZCTUDsnZA7Rd9QYnu92O/X5PHMc8f/6cJEnYbDajT3bX\ndWgZcfPqMsD+1hEpHZyHupYkT5gtZszny1A29rvr2x6/VDvPsJCOU92OyaPwegyGkL2wKs9pheDm\nUIYyBsHnn3wS7tSGgep63bDZ7/g//vAPXysHEh1seBWCb773Ae8n75NLR+5hEgdOnJoU+KalbSqk\nMUityFWESgu0EHRNGZjUop9HOYd3Dh2F/BgpBLYnOzo8ifQY4zFtTVftsU2N71qcA6FgNVvihULp\nmEPXO366ALJKoe95aVlG3TYo65lIxYsXL9AIpllo4JumIS4UfmVQUnFydk4SJ5zMF/zu7/4ur+QV\ni8WCLC3CCRtp8ixcxLI02HY1TTN6LwxD1ShS1FVJ0zScnp5imno0cRc9X81Yi84DBH17eUUcRYF/\nGEWj7e5yGQwa27alaVvWmw1SqbD7Ng2dMVR1TWcMddMEL7ckYbvZkSVBWl5uS2LOaXcNXdTwzvkj\ntnULwrErN2wOa4r5GVmcMM2KrzSM+bLjl27xvLkDDSfKABQcyw9cDxrEWR4shoB93aC04K6pAnTq\nQy9S07E7lCFyvC9hoigijg10FmctaEVpg/7+m4+esnAOk6REAYnFGo+TPsi0Y0kkFamKkVH3M4v7\nTc286MVjHo8yDust3hmUD0rUWV7QGoeQmmkxQUiNl4rU9/ElPtgBS+6p9TpNqXSEevwE33Qc7ja0\nUUyRBXtbZyxCC06WK9q25fz0jLIsmRYTiizn9vaWoihYrVbs9/vXzFQGycEANAwGiN57kiTCdA2H\n/jbT1ONQVylFB2ilyNPgY73vdygvJcaE1zpw1HajtVXwawu91bADDtZVx2kHWmvm83m/A3YkPpj1\n6zTlatsgz5PxOeTTnDiNXvM6+DOLtr15sr1Z5g23D8dQDmmtQShq23G5vg3UDQV709D10RZKBwm1\n6RxNe6A2Aa3JPLRlhRSCV7fXNF3bI0aK07rGLldMk4RUBW6csARqjQiDTo3A9UiV9370Zgu0f9uD\nBWGBBCKlxzeBA6e9wEpFGiesFks6E2TCSV4AEotAyiQsnF6NOkYkSoFDIKOQANHu99xevuKVFKRR\nzCTLMU2QdmRxQiUrJllOXR7QQnK2OmH/4hXe+7FMG/yph1nQMbvD9DvuIJtwNqfcbena8N4MqF4c\n6RFtVEKSZxll3aAjjfEeY8KMp+u6sHjaFtnf53Q6Hb22j51Mx8DfflFP5zP2N9vAPCgK9tuSPFNU\n5QF5cD1zw3H64ITprODiVYVwfcy8+DO68xwP5I6v5MPAD+4Jps45hA3aH+tDs7yvDqMmKJmk3Fw1\nrLcbnHOci5TJbMoPf/Dnmc4nzE9X4SrZdfzWb/4mTd3w4+cvyJKUIsv4+PqGeVbwnYfvsComPD09\nC2RS04KzIWUhksQiwspQbztjMVJgdeDaieh16bgQIlBzmjoMR61BA3kc8/j8AcYBQmHQtJ1FqJi4\nfy2iviQU5ojnh6cVILzk8fKU6Ds/4H/77CNipZnmBa4zbLeB6Lq9W/Nx9xF5nnN7dc00D1ZQu92u\nL8XuLY2Lohh1Ve+9915ISOib+wHtHGQC1S74UQtrWa/XTB4Gc1npA7yd5zlysyVPApTdmj0OgWmD\nGHFA/ObzOYvFgtlsNr7vwFghbDabEezY7vfMF3MuLy95+t0f8Or5F8jSkD5MiYqC4uSEn3z8knfe\neUw+LTDPSook71njb2+3+0u1eN4EEr5sxznmvw3zgel0GnabpuWzZ5/Tti0P3nnMrtxzaGpm8zmP\nZg+Yzmd8/zvf5fzRQ+bnS5xzfPrppwEmTRJOT085Oznl4fk5//uPf5dytyc1jnWcYsua987Ox4we\nAIUKjGl///i992OUx3CSHX9v4Ix556AXsg17qe79ELASKzyRjsYhqxQhQ8iJsJM554m0wgpHXdVI\nIZj1LOVB/uB6zf9QIh0OB54+fTrOUNI0DfB1XyoNF6VBG3QcERIg52hs1Ifpv5Rh7uX8fT6SUmr0\ny46Vvt9FtKbse0e4ZzUM8oVj+99hx4vj133m4jim2WwpTh9yd3dH0zSs5inEhqJIKBZL5KTg02fX\nr9ltxXGMrVvEL/vOc1x/Htvk6r5kGPzWBmZtJEMAlemvfEIGJ83aR+QqZZZNg8kHoBNBKzwfP/sp\nwnlyHfMwnXJ6+pDvfOc7/Nqv/ipRoqltzWa35eLygtIZHIr3vvfn+I3/8r/mvXcf8q1Hj4I7y/kj\njIDd+pLZ7StW0xmr1YymrRHtjkRJYhPqdtlpZByRFAVax+g066NNRAAFTIgM9AeD6Fpcd+htrSyx\nD2Wasy1KZuQ95cYoGVja1iOcxVYNru1o6yAlcN6E+ZF3pM7xOFmy31a0uuLxo6cgI/amgTzn6uIV\nUicoKZnkBfNE8MlhgxIW4TvOTxe8vOwoihzrgu2tjiM+/NY3ubm5Gecqbdsym5/gnSLTCdvNLU1r\nWe/WXN3mnCxnuPIWFSekuWNSKCpjSLMC66FpDVorkljT1CXOudGccjKZUFUVt7e3Yy8W9xmrI2L4\n4BE//vwF/8STHyKsZzWZ8PLwKfvrFnW1IeeEZKr40T/4v3nx2Ue0ds6utWgdYX6+zeB4fC0Xz5cd\nQgjiXucO3PuZDYsstAvIo2EaBLViGidY0/balhQLbA8HhIUsijk7f8jD0yWrWUYiCLQd50iEIHaW\nk3zCZr/nkz/8A/6z//hvcXJyRr3fhfxSGUom5SSm6uh0g8wLpsWUpizBdW80oRLZzzKC71u/8ziD\n8wbrLDiD7VFAvMU5C1JivcJ5ByoOz1OBqAPbWTowTUdX1ThjaaugJ4pUgtcQ9X1WNiko24B+FSLA\nzsIHVeh+s2W73bJaLsNrpQOUvdlsxob92J6qLMtRpTqbzUaDSecceZ6TRDE//aPfH2Xzdd1SVgce\nPTinre5T5pIkoTw4nLX9rukQQo1Ri0mSMJ/PKcty5N0NO9tQYQx918COECIYx5+dndF1myApX0Xj\nAhsea9PY4A3hHJ3twmv9lsfXcvEcox6vAQBCIsQwPLuXZAutQpkzlC995GEcabIkQUnouhZnuvCm\n5hlWSLrGsJjM+eBb3+ZUQqol5rBDJ5pECTo8mYBVkeHrmpsvXvA//Hf/LSBRHk4Xc4QNcfOLyZR5\nPiGWMcIrTmYrKqEDE8HV/XMZRFe9BVPPgcA5rO3w1oYPZ0OQU/9met+TV73AoVFRiieUdar1SOmx\nXUtX1ZiqAeeJddTHzAejkDA8d0yN53a7oW7DIDZKE9brcix79vs908kkNNVJeO232y3T6XSkyFgb\nohv3+/0YC3J6ejqSPCHMgCZ5wU9cMFJ01mKko+vunViVUhTZhDTdYrZbui7QbiKlx/mOtUHBOuSe\ndl039lzH7IJjfdQg8S7LclS4trZlmk5xQF21489IBZh+bmjB/dKlYb9xHDfQx7f5pkP4YMk0prHJ\nUM7VbfApU0c9xNl8yvksJ1eCtMjJE8158ZB0PuVqu+f6ao0UgiiZMJ+AV5ZtuWEiJqRpTCwE7z95\nyu/+vz9C1A0fnJ1xu96iteZ8teLdJ0+oy5ZHDx7yve98l7/0F3+dcrMOjqT5giKe8tPrf0jUmyzq\nOO9N3SXCB0axcEFq3fTWr845bHMIM562QrgQxIRTCKkCd65nKcvWEpk+1Wxf0vWOqVIqmq4NftdS\nkMQRaR5O/O88fkIyLXj+6iWm70meP38eTrTO0JYVL1++RHsBieDhw4c8e/6CzWbDYrFguVxSliWz\n2WzM5RnQruOI98PhwCQvWMxXdHVNWR+IpaTpLLfbLas0RiCZzyecVg2fvbil3GxIlCRbznl1fRV4\nhXnGdrsdofDhnBgW8fB1lmX3uamRZHa6wjnH8+fPOTmzvPve+3Rxx66zND4oj/MiZTJJ2DY9/acf\nebzt8XMXjxDivwD+GnDpvf9hf9u/D/zrwKAc+ne99/9L/71/B/jXAAv8W97733zrR/NzDmfs6AuN\nAKfCYHCY8xzPgJxzJBryJGaa52RxQmsNJQYdxaFPAGxr+PTTT8ke5SGZbDYJ/YZWOCHJplPmp6dY\noWmaDhGFGZCVDi8Es8Wcx0/eYXV6AjokuLm6o267cAXlfgYz0IjGeRTDzMdgmp6k6QxdU2G7LgjQ\nXM+2dh6lQuQhPoASnQt0HGMMjbE4BNZ7nLN97S5x3mO9wfnAAneEXiWO4/57geu13++RUSgnd7sd\nJ7MFdV1zdnaG98GXbTB0b9t2VGEO0HVVVRgTFu8Yb6IVremo64ZD1UDrKLK8184w8u3yPPAAjTHE\nSUrdz4SEELRNh3eM/c6wSIZSbVAOwz1YZK3B9P4Gu92O+TLG2hiQFEWKVpKmDufNZDKBG+icJaKv\n/d/yeJud578C/hPgv3nj9v/Ie/8fHN8gXo9VfAz8lhDi2/7nmr3/LC3n+ApwP/XtLWy1RAj6NeYN\ntgAAIABJREFUkFuobeA8ic6EBQbMZzPOJxPmseK9kxXSWg5NzTLJqbyjilOi+YyyrNhevuK3L7fE\nccwHV1csFkuePH6H2WwBIuabv/brXL265urqih8+esR8Pme/uaBpOp4+eZ/lfEWUFzy7uqCrG0xd\noWNBnmY0CqSx44AvTZNg82psr2dpQulmDN4YnG1p6wBV47rxxEijGOcEXWfxwmCdZ71dI+IwMNy1\nNa3pEHFw9yxNw3a3QyhJ1MW4W8d6u2H5+AO25Z5ddaBI5+hYs1guubq+xhjDZBKiSooiTNvX6/Uo\nabbWkvYzlkGKnef5aEdluo6mt87d7/fk+YRHj96hPgRz9ma/5tC2bHcVuRcs5quel5chnMW1Hfum\nwcgQTpylKbtdSefsSNsZLj6DdHrQ8Tx+/Jjr62tWqxX2sKXdhFLSOUdZVuhSUN1UROWUZDlDa0GS\nxCglwsWmaanb8h/tkNR7//eEEO+/5f2NsYrAJ0KIIVbx//w5f+UrB53HvY/3vh/+9bk4ImTcCGPG\neAgBRFIRK02uNdM4JhMCKRVCaWSaEnvDoY4RpiMyFp12lD6iWMy52W355NkLXlxc8+jBAxbzFZGO\nmJ6coPOc89MT8jwnjjqaJqSLlXVF3TZMohwtJVGWBuNz3yFihUb2WZpH/ZsUSO9QiMEEJuxCNph8\nBE7b/UWk6TqkiBEyxAYiUqazBZUKWpoaRzzN2TUVm92Gstrz/PICFKxOT+i6juvra7ZOk6QpKtI4\nPK73nw4uOd0IRTsXDE6O52p1XZPkBYvFYnxfBs+zIbVh8DjY7w9UVUWa5yRZmMWUDoxx1G2Ld2He\npnwwgUx0RC27YPF9BOF3zuIsrwUyDz4LQ8+VpulwrrJeryk0PR8vsEHyLKM6VFRRRcR0FCIWRUaW\nJ3i7x/F6DtHbHH+anuffFEL8K8DfB/5t7/0dIULxd45+5itjFf+448vk2N6HWEK8H8sP2wfSmV73\n760j8oJYKVIVUSQx8yxnojXSetLYEec5pQuJCilQSclUKJLlnNOTc25ubtlvy0DvQfLRRx+xWq1I\nkwQd/J+w3vT5MZI8m/Qp54GjVmQZ0zwjQWDbhigWxGjSNCaKA0KmBGFe08eji/6xO2OxXU/DNy4A\nB3Z47j54WDuoOkcUe85OH7DfboiKCcJ1XO+3fHb5BU3bQqT45OIFCEEtBdZ2XN3dUHeS5dkpcZog\n0xjDvW6n6zqyWIe0ib4kGhw8Q1lmxpN3+HqYk+R5jsD1JFHJfn/ovaRnxHGK1DHOQdtZmi6wDTrn\n0d4TJzpYZTV1sOLt7YsBuvY+vGpA2o5VrcMcb5hf7fd7kklMqoPuSKuYyWTGtdlRlgfSxmCqCnzU\n+8b15GLZz9Z+geNPunj+U+BvEgrEvwn8h8C/+ovcgRDibwB/I3z9+veOiZ/HnxH3u40VYPubIymR\nNvQF2gsyqZklGeeTGQ+mMxZak8YSJTKINS2SXM6oiw5jppjGcDcPphO3At6fFMRRTl03PHznYa8n\n8ejIM/EV1BXCQJrmZCiQkEQxTx6EyMJIQLPfcuhKUmWZrwomk4wk1T2q5YMi1QBO4C3Yzo8fwoCz\n4LwgvBQCmSS0QuLQJPMFaTbHpTmzOOL29pqr/Y5NuefZ5SvKtuZ2vSZOY1Skef7iJW1Xc3d3x49v\nPgq9SNfxL/z1v0ZeFOzK/f1MrUexbm5uiBZBGLc6GcqfksPhwMnJCXXTjZLozSbY237jg6fUdc3l\n5SXOOXa7XQjltaEf64yl7gxNa6jajqxzyFxRxAmrRSCArvcHlNJkSdTTbRzFNLiLDty1gZVureX8\n/JzHjx/zySefsN/vexuyDIwbF5pSijTKkHLHy5cvUWXOcnFKFCuapiZWMVrKMTHhbY8/0eLx3r8a\nvhZC/OfA/9T/961jFf1rmaTKv9nnvPGzYQENuaHcC8egn9R7j+/tpBIdkUcJi6JgmqXkWpMphZYC\nJ0FJwVLEtL1U2yiFUB3zNOL0wSm7fQVewzQIxCy9oTkdsin72I5zIguq6y2RFAjT0dUdxhracoOt\nDmRKECeqTzmwDB7Jw3P1zmGtRziB9BKFwqP6FDmPEBZPMP5wCLyU5NMFcVpQG0vTNQH+tYHjlaY5\n6bQgTlO++e1vMZtNub295eb6mhcvXnBz+eORrrRcrUiyNPD1TLCB6urAGliv10yS+7iROI45HA4j\nS2BwDO3fv5FVMOxGQ+k36Kq0DmVi23Ucmhpnk3HXGnwWQj8T4GelNUIpjPPj9weofJjxHAcAHw6H\nUZiXpim68WNmqZQKKUKg167bIZzr82jj3mykDI+DfwzEUCHEI3+fhv0vAb/Xf/0/Av+9EOJvEQCD\nt4pVFOJ1ScHAU/vZnUf0iks3qh2FCAhTLCUISR6nzPIJq9mc9588ZZnnzLymiBUCh040nfJUIoT2\nNk3DYV+xmEq6ukSIiJMiBRERRQleSPaHPUoJdJSCgsNBYQnak8lkiurVjZQVCovE0R4O0FQ8eHgK\nqkYIi3UNSkaAw5igcA2NtgtyAxH6Iq96tMl5vI/wQuKVJolzosmc5dk5Mk6pO8H159c0h4rlYsHJ\n2Snf/uH3yWaTEC/iOk5XK6ZFweeff87v//7v8/Liis4Yrj65oyxL7jZrHj9+jDOW6nDg6vYFJ8sV\nz9cbPv30U05OTvi292PW6c3NDbPZjCgOyWuLxYI8z9nv93zx7DnTRRDaffrZi+Cj5u791rQaiJwB\nLBn6JCFCmRYrTZ6kKBVDHNEJTdfV4OWo6Rmg8WFAOrAahiyfQCatiWXG8+fP+e6Dp3z44Yf8w1cV\nO3ahRDWGzWbDeh3UwziPfIMz+TbH20DVfxv4K8CpEOI58O8Bf0UI8RcIZdunwL/Rn/g/FkIMsYqG\nt4xVPM4k/bJ+ZxiIRabfmZRCCnCuT2WOE0R9QHlH7A3n84wnJzMycyB2CpPAQXmSSKMTTYRDCk8r\nLZHQKBljGsdEBS5XV1co1RL37IBMBotP0QnoYKEyat8hvSfzGUrEeNOSTzK6tqYuKzpTkaQipM2L\nAt95RCQQKrjxCCXorMXQYnyHdx3SW6T31FGHEwbftWjt8EgaXyGSlHgaYRYRLoq43DWo77zP4cUL\nvvjsc/JYsJRpCPZNIk6LGYn1JFXNtGt5lMS8N5lycXXJk0nB7/yvv8mjp++iTMeTd55g6oqPDltk\nHDE9XXHxbMuhNdxtdzx58oT24hVxktCYjmI25VCXVKbGCItMFKYOu0FeFESJxFrDZnfLbFGw3d1i\n8ZjW0hkfxgF1RaIEh7pBKodUjjiSWOeRvT4p6xRTp8cZluk6Ll+9om0appMJ1hjqqgp0rKoiTRKk\nS6mtp44Ud6rlld/STAPHL1Ie6TqUd+z3B+peyCdETJIn2Nu3jxj5k8Yq/sYf8/O/cKzicQnGG18f\n///45uMhqvMGbFBeZknEbDJlsZiNuZtxHKPl6+nYjlATeyDGI3tHymF2APcM7eE4Jp0mIkIojVIC\nqeiteruRIqKERxIYEW8qYPvX6bWLxdHrN5qBOBH8CIQQSEfI9ukMzhhkLCjShNtDCXicgLptuKwO\nCBx5EmNPTlhOJ8wXU9LJlGw6I5sUTJopjbeUTcvN3S0yTUizPMyLeieZ5Ww+XtkHCk5RFMHG+Ihz\n2HXdmKlTRMmo85nNZqNza6TuE7O7uhn9HAboeWj6q7qls2u6LtgOh9fvHpQYHEIHX4UhRnP43DT3\naeCRVKRxcCMty5JDVdN2gWM4PMZB9RpFGXk2wdpfwP2Drw3D4P7kgp/N2bk/+YLbpuh3Hnr+mreO\nJFJEVvDNb3zAD7//XT587z0mhCtwIF/2huk98xdvEF6hI0ciM6QPL8VQJw+M4Nc9Ee5PfqGzIOuM\nJA6H9Y7tXfBctqYlUpIsidFS4W14bkkUGnjjDa5H1waUDR+Gnw4/xtgrpcLtBNk1xlBvtzQvXqCK\nGUYlGOmYFAnnD1Yh/Xt9h7WWm+sNF5tbsiTlafk0cL9mM+RkQrO+Q2Q5tC2dFzgZURtPMV8hdcrt\ntiSK85Guc3FxQVVVvPPkCc+ePcNfXjGfz5lMJiO3rG1biigZxWtJkoyllmnD65nnOQcbPNUOU0nV\ndDgCCDCbTGkbQ2c97WaPlxJvQ+cXRfreQKUvuQDm8zmPHj0ak+Latu2RwQNRGtK0m67l4uKCg9hi\nYxtkFqbDC4nSMdYLsjTGE3zc+Iq++8uOr8niuT/+WOBAuJAlKAJxEEJYlLUdqr/arJZLZtNJT2PR\nPe0iJMMheyUqhBNUCpAq8OF6+yYt+tLqSBd0jP8Pu6RSAu9tUB84AqzcNnhvkd6SpBGxViEpQarX\n6unRk9oeKUqHj694LaQn7DzGYqsKgcbIFpdKlPDEGpwKiKFzjiTP2Gw2XG02NAJmsxlpb+DutAYh\neHV7y6GuaVrDxaurUTSoFHTOo3qLqLquQyPe02AuLi548OjhmMDXVjXldkcq7yXgg3fbgwcPMG03\nShxs29G1wdCxNR3WBm6eUoFWkyUJwu/DhcT5ICjse6PBCPF4x1osFkgpefnyJXEcBx5clhLpAa0L\nHDmyoPSNogTlQ89ZNx2dHXbQZrxgvu3xNVk8r5t8DB8/M+fxHi8d3kvAht/yIKwBJ0gizQePH3E2\nnyJtSzEJrOCknwFIKcYo+EhHDEvCejPaDg3oz7EN0pdZAUtpwgzGtDhrsV2Hcr30QEqKNCFJQjMc\npcn4HJyx2Db8jve+t546+hvOoSKNdL0m1HsISnDwDkyL6lrSpGWSRONiT/OMLk5opxNaY2i6DiEC\nx61qOl7dBEOP+YNzPvjed5nMZtzcrdlsNmx3JS9evAgGh2mK7Qz78jDqaLZ3a2bFhO12y3KxoNzv\nubsJEu3Fakkcx2y3W4o0OIm+ePFinLu8ePGCSV4wmUwo18FY3nQdd7uWSTmnNYY8TZlPpzjnwUue\nv7zE+BBoHMcRs3neS+bvPe6UUmy3W/7oj/5oNO6QUnJ6ekqcCBKryHXRS1cceqpJo4SimCLyjLtt\nw7Ys8UiiSBBFCVEUc3Nz99Zn7ddk8bx+fNXCcf2QFNGXckKAcOhIoYxFSUGRp0zSkDsaTj6H94GH\n5gfCqZQIpQh7lwcjxzfgeNe7h1rvg7OGctK6Jqx5b8cP2Q9tpfCEtuX+98J9DwukXzQEw8URtu53\nRaXCMFZ6wDiQDi1kQN2sx3cN0qZEziCbHnZ1nlhApBTSONI0RwsNOmLTxyhuN3tawtR9u91SVk0g\nSGZJMHq0LhBv++fsjMVFYb5TVRWXl5fMZjOKohgTr/M0G83fB7fQ9XrNbBHk0jc3N+RpxmQy4a6n\n2ABY70blqekvHsJ54ihCyKA/Ej6EJEdR6PsGG948zxmSHHa73Qhlr9frsBPpMPdD379nWkQ4GwbC\nXoDpHIeqoeksUayxBmzvuvO2x9fEeuro5Dm6wo/N/dGV3xOuSENvYTvTG4RL3n/3CUUS47uOWEm8\n7yXBfXanUgrZzw98P3AFgvmggBCdED6kVug4Gj8PX4v+xIa+XMSjBSg83nR4E24b3uwkScbYjfCY\nAwwdKx1OFh0RKT2WhrIX8mnRh11FGhVHRCooRcHjbODPxRJSZ0mdJQcS64lNR46nEIKHyyUnWc5p\nVvD09AHfePyYIo5p9ntMVdFVB7a3N6wvL5F92RlHEaZr2e8DrDv0Zfv9nixOuL29DR55PUR8cXFB\nfajIknSEsbfbLVEU8fLlS6QMEZP7/Z7VakUUhR60855DU2OcHYm9xnbU9YHlfIHWwe20Mw2dC7D0\nbDYbh6+bzYYkSV6TKmRZxnw+ZzYLYJEl7O5DvL33wRxSx0kwrIwSjHOs5gtmswl1VY6s/Lc5vjY7\nz2tX32GneaNcsv2LqKJgS2sNwdvMWs7Pznj/8WNO5wV5BDGOLIrRkeodM0PEYEjGft0DwXuBFO5n\nHsfwd998PN6HxIJYRXRtE1xuNCRxWJxZllEU09A/6JRY9c/DBjtX68MMR9igyRlSsZH3Ugwpg0FG\nWDACK01wLPWulypv6WrNROYoZ1HG0BlLjAhqzLoKPnLOcyIVqzShjRSryZMxZfri4pKyLImznLvN\nhhcvv2B7c0EkW8puN8aGKKVwxvLq1auAyB0qZBQQtNvb2zFQ95OPP8b74HX9/PnzkVZzeXnJbrvl\nG0/fC+aJ19fUCRzalkNdhaCq3ugkEiXCB00TwiGVRyo/CuFubm5Gu91nz54BAUVdLpdst1u89+yb\nA5lKeHVxia4bfuX7D5FZw765Y7criaSibgw6TZFRRpxInr7/IU+evMvf+Tt/963P2a/N4vmy482d\nKPQ8IsQkhp8goG2QxgmTIgv+aP2MXoiQRxpOzPB/K0I5F+4iJCL43pVyuMfXPg8WBKKPiO/Jp85Z\nlFTU1oaYxP4ki3poXOlQ83vUCFePwIB1gRF+JLwSQjAEG0t/70swPMqhTJVeIbsWR4exNYlM+9sd\nUji01EEr1AaSJS7Ii6XU6J5Tp5VCCcFJljKPI0QUU0QKbMOPlUB5S6IFphU468YKoKlqrL8PVvbe\nY42hOhxeSz0YskYH88Su66CHtSGc7EiD8562V8xKQmkqpUBrSaw0nQghVtZ2I1Cw3W5D9HzPcBjQ\nvsHrYL/fY6KW6Tz0WUOJdygrjDDEMAr4vBO9449gMskp8n/EQ9J/XMebO89Qxry284jX60wlJFIJ\nlPcUqWaaZWAanFNEWiF8D4XByMLuL+TQX9Utvs9k+XJS4ND3DCjS8PWhc4Gh0HZY06EIJ0uaZsRp\nDkLipKbpHJEMmhPXtSgEtu2wnTkCQPpkb9Vnkw4mFFKNZiEi6u2r8CSTsCNYGkpfEREhEoXwgkgK\npIUkybHWU9eGptljepJnGumRcpMkitaAkZbZNGOePeGnT88wP10jnGTvQzmZxQmL6Yw4u1ePeu/x\nvawiBErd0HVd8HrriaSDYjTLMpy1XF1djbIH42/HjNE6aYidwztDnqQUWU5jHY33iKbGY7m5uWG5\nXJJlGWVZ3sdFShkYDz1cvlwuuWluSNKU1oby7urqhr27ZPpeRpYVHPA0TRdiKqXi8vIVi8WKf/Gv\n/8v8xm/87bc+Z78ePc+Ru8xrN39VDzSgLup+8Bi4T1Fv/NfDyeK+DAofHikVXoqxTJJCj/dxTL8/\n/nwMFAyPy3qPGcrIvmEdPpRSWAQeifX3xiQDWPDac3PDTvjmYxUjSOJ6+lIQbQf5cJLHeCGonaHF\n4aIQwitUGD954YhiQZIq8jwhy2KyNMJWJc1uQ71dI40hwhF5EK4jlvDg7IQ8TTBdcLAZ4OHhNe66\njvoQ7G4H55whB2go09q2HSkzgwXV8D3V5wTVjaFqm3GmNrJIoiAfH97zNI3HvmaYGw07x3CM8oV+\nYLs6ORkDsgZpdpIkKKFp+uRu40JES3Wox3lWiE55++Nrs/O8zSFETwwdFtlY5vje3TMejT+GBTSW\nbULgZUDcpBB9wQZ48drJO5QCx4jfm33Q8LXrZc5aalRvrii1RqkoeKx9ye8Icb8Qw672+vN7s2wY\nf18KvAsBwFHWlyneYEwwK4mECCMwLxHO0bT1aDmbxrIfMsYhSa6uaZvgky2kRCcxbdshtGA+m5Kl\nCW3bYFw2TvaHSqCu6wB5LxfjyTnsAINXtXOOpmvHi8+xp57Wmk1dhwCxrsP05Rg9IhlpHdBIZ/BC\njdZS13eHMcd00PUMOqKhZB4Z1L2Xm40ipA2l4oB4lmVJ3ZuLGGMoqwNn2YL9fs8f/MEfBLj8LY+v\nxeLxRx9AONH7z8PJ1BmDdqHicip8L2h5PUoIimzCopijrWeeT9DWY+hh6c7gOomyECkAgRO2P1kV\nKInx9447zjlkXxIKHygx3tsA5/YlZWo1h7qBTjNdzsiyrJeHh8cea4HxLUpauroP9bWW2gU9iTPh\nam5NeHN1pFFeoJCYnu0gffBsQIRZUKwUUiVYIwHBTE9J4qDoVEaHKBSh8FFGpAu8AyckFkBJdAR5\nlDE1Fmc7TF310m8XqDAy5pvnT9B/QfDx73+MFU2I3lCK9eUX/PDDvwT7PV9cXFBeBQW+TmIaIYic\nQ7aWWGts05FKRaQjyurA/hB2oE4LDq6jkZ65ha702NqCg8Z2gSMnJU5LZJrSVg1JseDl5S01Lfvb\nV33l4EnyhCiOKfKccl8Rq5gszpBWkMiUw75iu78DpVivb3n4eI7Z1KA8na+IvOBXPvyQl598TtpN\nubxe89u/9feQw7b3FsfXYvH8aY+BbXtcXskjlMwfzYbE0e+Mu80b9yWECIyE/niznBxKhwEejXSI\nEhw5elJhCfqiNwe/3h3Z7TqH63mzYUcNO4QTofT0g18BfgQ4gJH7JnVMpIKHgOg9EuTwf9c/BjxK\n6vFCFMkYETuEj2mVwHUtrfPhtihmpRYY71jOZ1T7ZmRCNIdQJi1PTnj24sWYnWOGHKH+9W6apl/E\nYqQ6DTuQdffp2Z2FyJgwu5MC4QR4Of78ayWydXRN23sX3JsUDlD1wNZ2LhjlD4niu91urEa896HX\n0iWJCp531kRI5VlNV+x2FU39pk3YH398LRfPVz+BL99SoygaXUFHBxo80dFW7kVwRxFShtKpf4OD\n57N/jRmjVDBR9NzPXiCoPYf7L8sQbjVfLoBAZxkj1gX4sY53o0mG80H+63safNME/4IBxhZ9b6MT\niZagtETIo2UsRCCjxjFIjY4SoiQ/KmV8sKzyDh1phAv2vV4EXmB4Mh7vQODJowwlghNoZyyt9yiT\nsVos+Wd//df5rb//I25vb0myhKbuuLi4IC3ysb+ROuLQAwMQjFK32y1Ch+iVtm2ZzKZUVTDVl1Gg\nS2mtUU5hveNuvWWaZyyKUCLe3a5xvW+0MQbaEMVyc3sT+qy+5AqhWTVFnqOkx7jwOud5zqtXlyyz\nychNDGoVS9t1zOYZzvb5pSIhLyRnp2dsNiUXF7dY82fAt+3Lj6+uR4fmdZjie/zP7C73vcyXM7eP\nwYm+Exrrae/B9otnMOWIogilg08ZKjAAwh0QtNVDb9MvJOdc79F2H8I1PrMjSpJzgRHxxgNkMEtE\namSf0C3e4Mw5H+LipZQEZH14XuGCIrUKMlUvUCrwAQcwQlpLrCQozTc/+IDf++QLyu0OiUDJYPSu\nkxikoOnMPbetbfFeBClCFIWEvDgen+MgXNP9ruC9J0rioCGqKsqyIpES50zPQBA4C9be8+ts1+H7\nYaq1NqTgGROiSlT/94qCrCigUCQ+AB2dtbRdjfcps9mULnaI2iGkZT4rODtfYVrDoRfy9YO1tzq+\nlovnFz2GUmA4AtzLl5ZtzntAwCg3CE24UPJnFo8f5i39VXtgB3ddR5rf01JQOkSYiB6QAIRwY/lo\n/etznmMofvh7/phlYS1OSAKHj3CiR7pnN4S+ZlyY/eIWKpQ8uKMmvf+ZocSSzuEloZ8TEobYSQ/O\nGaQQ/eKRfPD0CR9+8B43V6/YlIexJEt7ikzVNIHaFFKBgHsCZ9eERn4gZg5QvDsq28Ze1lnMURqb\n9/eoKq6H8MU91xAYAZ7gRpSidTSqXb33LFdLms2+R2RVv/PFTEzE9fWajaswQmCakru7G5w7622v\nfrFwq68HVM2XT/Tf/ABG6HOAP4+v2INB+RAv7vvB3LEN6/HPj3BwP9x7k1M39FDDrOfYwWW1WlFM\nJ1gpsULy/3H3JrG2ZumZ1rOav9nd6W4fNyIzI9OZTttlOw1UCbBKBQKJIWKCxIBGlBAjmlk1I6Sa\n1IBGjJBgBBITJJBACAmVEAyYlDGutFzOsNN2ZkZmRNz2tLv5m9Ux+Nb69z7nRoRvpNMiotbV0Tl3\nn7Obv1lrfd/7vd/7BixBVyRdkYwk74K+7WHvsmsdQrN3308+936nKnG8fClQoicXtUVVjUzcuqFt\n51RVQ7mZlVKyOjsnznFVRV18O1XCh8AYRnx0uOjQlc3yvwoTEl9/8pR/5td/g1//zi/TXV+jY+CT\nTz7hJx9+iItBHAxCwlYNWlmCT1xcXIhLdT62pmlu+feUx9u2pXOeIXi6fmQYvaBtytDMZsQAdd1M\nrnJt20qnqa3o8w5RGNXeey4uLlhvN2hr2PUd3W5gs9lN0Hff9xOlByLzecvXvv4uv/zLv8zx8YpP\nnn/MOI5861vfEh+mtxxfqZ2n3ISHq8PhzXcX6j2s15SE9hY2fPD8fctAYVKnaQvXeQI556YwDqQt\nQluL0jXaGkKSWpLKYoORdOtzlc9xOHGL4EbMeVeMEW30wecv1IdCxBP37WQsSeVdCI02FVXN1Dw3\njHstZ5vhX8EfEjoJu5wsHq9z31Dp+U1J/vbByZnYM4J4+WhN3CqUrUQjrus4OZlh60oKsuNWJksM\nUyH1kNJUdl1hGojmhAuewTvCVA5gel6M4HYjndkJSdUHUpKmt1IonYy1mhpbV2x2W169fsFwvSHk\nRr7SbCcu3iO6bklRcX5+zmp1zGoVqaoZp6enfOVdEj5rHMb2CWHcKt6U5i1/W8IXY4ys2tyeYCmH\ncKXQKY9lveMQSLnbVCmNc9J9WHaH6Tm2JmnhzuVXJbJnR6j02ZNHa00sTOuDMBMl5lZKlVYK4Yir\nkuvYDHxoi7J15uoZqkoTI0TvJl0Eo6UNYsr3ouSFuqCM040toZciw+0Jnj56yDe+/h6zumbT99BE\nMR6uIqOPuLDj3r1HNI1myGo6hzWsQ5PlGCM66WnyWDSJwOD8JORhlL4VzsYY6V0v55dyfpA6UEpT\nQTaV3SlHG8MwSEE103XERmXObGFxzqMGz27X8cOPfkoIuTCr6xyGv/39+CUJ295sR/60UWLhwnMq\nj31WmFduvMMO0E/bvQovqoR2cHvyhRCEM5V5W4ucGFsreUhSBg+0yxX1fI5p2pybKJThVgHv7tdh\nOApF+NDlwuS+sj9fHdE0M5S2+KBIqqKdL7BmTsTSDwnnNd4lhj4ymy2ZtwsqOyN5RfJJoaJ/AAAg\nAElEQVRJBJA96GjRyWJUhVKW3kVGn4hoTDXD1i11u+BkPuev/sb3+I1f/TXmM8nvShgkCCJ5J6wI\nPk0yuKUVoew+h4tHKaQKe13jgme76+mHgZAiPgZSUhhTUdkmU4xEQbXbbtnerAHhMl5dXTG4UXTb\n2pbRe45OTjg7O8V7N0n5nhyfoZXl6mqNVjXrm55+l7i82GG1dJu+ev2a588/mRbRtxlfksnzduOz\n6DuHDWuHj92dTLd2gINxmDuV/x9Ouq7r2O12064zPUcLBQetUcbSzhaSe9j9jmGUfmMST7tJus0c\nPzyuskCUfMsYM8HrUe0pSjFBTGIJCZq6bpnNFlhTU1U11hZxdNmd5J/IXClKh6uRWosR5rnJFKNx\nGJi3DV979ylnxyf7Bj4lVCBTWdy47+w81NsrNh53d/pbWt1KfvYxMI6ys8dwpwUln6Ny3suiWJC+\n8polrC4aBrvdbmJGaC064ymq3LcDoIlBc3FxMxFOz8/PPwfpfXN8pSZPmSTl5j6cOAXJObzpChBw\nuEsdnpzDyVLQobs8Nq216J6dn0+F2AJVp5QywbJhuVyyOFoxXy5o57NpVyqv+WlfRaCkaZqsQLpg\nPp+TkqziwzBM0O2Uv9RF6dKw7XqMqTCmIngYhpHgE0pbig+QMRVGW6ypqKuGWlWopCEKu8LoiqaZ\n0bRzqrrFGAtJ40NiUbecnZ7yW9/7Hr/yK79CjCLofthpW0x+j46Op3NTrs1ms3njOpTdvM92l0nL\nsd1sN6xvthP0PXT9pEO92ezYbbaTD2rbtpOvT9GLK6+vjGbXbSZXuKLn5r3n3r0H7HY9J8f3efjg\nHaqqZbMWTevZTAQe1Vevn+dNXhnsc5w9rJlXc2tzYu6xMaHxbLdbobdrSzCJPnrqOJDQ+OSweGw1\nLx3fhFgoQB6lxClbay2CHSmRdEInjetGtustbT3HuUjfO5bLBpcMOipSHMA5lB7pr4Ve74YR1w0Q\nQdGC2QERn7w4FlQabTVGKVot/DurtZgrZVLcMI4kYzEedFKiammsOMpZqaX42DO6da6bGKwyEDwp\nm+IGRJ00WSGnjjFQWYXWFVrZaTV3ZcdAhEdQIqoSF4rL7TlP3nvI03cfsNCaZCqiMmz7AZ0iKXR0\nLqC8IholTOUUqZr6jcVKRWFiV9qgzJIUIq5LxFp28DEFdEyMKYhGNQmfyGpBDTY7IxwdnTCfL9lk\n54ax2zGzBiqL8Z6wcyxsje0cZ0cLLq4+5t3vPGSY9zitGWaJ6mRF7BXfePg+ia/x+Inh8vwlIXPh\n3mZ8SSbPp5Mvv8g4zFdSRqa896gDUqJA2ZktABPyJkXVT6fhlF0OyFKu1bTLJQUqSPIdfZjcAFLe\nJRLSjzKGcWp401pLuTKVyg5T/F+q78qpCdouu+hhnqSthRRRQU0Jtooy4cnHIIVW+dkY4ZpLDclD\nyswFlVV67hx72RVDEE7a2ekp7zx5wnK55GqzwYc41cDKVwnHDl+jXIPDYyh/60Z/K8T23gtKGeN0\nXaYoQ6mpgFoeK88ruWff95Niadmxyw5+GOqptG/Q2+129LuRo+N392E9bx+2fakmT7mAn5W07U+a\niIwbrYkqkIJit9uJFlec4WPAB5P9SvVUoHPO7ftisnu01jojTuK9ELPCTpUVb/rBkVLE+8Bus8EN\nA0YpVlqTvBbqBxXeO7rc7KUA5aVLNIZA9E6g4gwX18aCyZtgZlnrrO5jjabyPc45dn2PNluqtmF5\nwPZVSmHRYGSHAjBJwi1JgmJe9fPKr0VMRIqGcvwxJSl0HtzUh6BK01jRV3Ae21b8yje/za9859v8\nwQ8+YDeOuKRJSrHebTFuoGqbSUe6GFGVuhvsF6/SEkCSepaL0I2O3TBS++zs3c6JvbQsxOjRprpV\nZD06Opr6esZx3GsXaM0HH3zAZncjrnJRsdncACe0bcvZ2RnPb7YkpXj16iXf/e53ef7JS9aXI34Y\n0fGLLd5fmskDTLP/s0eBgEtcmlcoJSawPssIpShNblrvtQsKRDydHHUnLDzoKTo8gVbvHZmLJllV\nVSyXS7RWxOCpoogn6gJSxEhwXspEWXw+xEgY3VS4MwX1s/JeIYTJya3kXyH0U5E3pX0v0PS5Edb3\nrc+dv6balkLY1ZQdaQ+gTORO7/fSt0AMAZcSjU6YCBjFydGKx/fv8aN5i0+J7TACmtGL8EkaFdUB\npHwIWd9N/mOMGC2Md/K5cd6jVCUSVDqfL1/Isx5Z49LUAlFQv5IjHpYRCmdQqWpaHKqq4vHjx/xw\n9wyfC96L3MZyfn7O+avXxDB+ofv1SzN5Dk/4Z43S7zlt3Xl1TUngzsF5XNKMMWHjm69z6/XzzaW1\nFk3lMplChJSIStRb2ralqWoqY6eaTYyRsd+xMAv8zmFCENJpyOKFUbxtwihWJjrfsCEjQ03VYrRM\nkElLbhxBGVRKtN6RQuT6ZiMqpIOoW6ogvTslNBO3OY1KCa2QnSLsgROMRhlN1IZEQRSRHUkraiO8\nPO9HmbDW4jNCZa1l3O3QMWK14eHxMf/s936TodvyBz/8IZcfP0MZMYcKSWhPpXO0KIUCE0p5iH4K\nUibSYT6Kc8KmH6mjcNSSS9npTs6XjwEx9nKTP+mEZub+HeHIbTk+PubV+TMBY6KlUjBftCwWM0Jw\nxOQxpmE2a7h3csq33v8W69d/wM8+/DP0ITXoLcaXZPK82YD2WUMU2+4+W0iA+wY0RUh7wcI9irJX\n/yyTp7yfIVfAS2dRDCSdY2ZEnujEikKm5ANOCqreE7XCUIH3k9aaioEQHF23RQWmGok2+9U5kvYt\n12bPoD4MocoNF7yXmor3qLDPmazOfKyycxKnFRplhMNW7gejqfTe17Mwuuu6xZjbO7Mx8tyUIv1u\nhzKGB6cnvPPoET/9+CMqa3BCtyVNu1e1vyZpn+Md1ufKTifKDEpqOyHgQ0JH+XJReozQsjhE0j5H\ny+dRKcXx8fEEM5+enk5ablNxXItpckE8i/YbSdjnJQR0zrFbi5j/F5k8f+5fKqXeU0r9n0qpHyil\n/lAp9R/lx8+UUv9AKfUn+fvpwXP+jlLqT5VSf6yU+lf+vPdImZZyeNLLz4c1miL0UHSPlVL4jBTN\nVytZ9SJoIzrSeyrNPtTp+/5Wz8jdOpExhio/13vP0PciK5sT/mJzkWKk2+2orDALvHNTyBNDYOh7\nri7FieD6+prr62uGYZhWyLI7lJ6X0nfinJtc7oLzjFlG1hhDpQ1Wm4n4q5TCavmqrL6lxa21ZtYu\nMllSKDV13WLrBm0rTFVTVy111eY8Zb8ryOcYid5jlCIFEehYLmb86ne+za9997sisJLCVPsp7SAF\nUi8/l4lcdqUSNcjvXX4s0buRiFy/YfT0fW6X9uMEf5fW7/Pzc37wgx/cupalFndzc4NS0r5d+n6q\nqhIF080Nx8crvv719/K9sKN4DC1WxzTNrGzqbzXeZufxiPPb7ymlVsD/q5T6B8C/A/wfKaW/r5T6\n28DfBv6W+rl9Sf/84YZeelPyiqa0hmhwYcCHxBAiytZ0LhDjyHG1Zy/HJEKEqL357zRSQkC4RAyS\nlwiPKtF1HYu2wZC4ub5GEcUBzQX6wdF3I3VuwW7rhtFL3eHZixdcr0XR0o9hupAliZ7P57z//vt8\n/etfp5m1cpoTWCXsbBXlvZdHx8yaduKllUYvINOAcs+RsiTlbu0cUlAVYAFlpKBrrexiMVFbWZ3n\nVgQWY/S4cSQEydfk3EXiODAGx6qpeOfBCX/tN3+d73/wA/7kp5+w6z1Wa0I3TJYvh3WgzxqzWUNw\nXiIEnbjuenonetbHZy1URnQG/Jj7kWbTZLy+vubi4oLZbDbJUJVaT1VVXF++ovKJwUNo6gz4yHVZ\nPl7y/vvvs+ki/+h3fsi/+Df+ZVbHR9Rtw9XV9g3u4+eNt3FJeAY8yz+vlVIfIFaJ/ypiPQLw3wL/\nF/C3+Ll9Sf/8IeHWYe+LJoQRm6nvu103VawrLIXkCRO0gGZPiZkubpKw4FbRtYRGPhDNPpQqyXvS\nteQXbiSaSF0l2npGt+3ph5HXF5f88Ic/5MGjR5ydCNpzfHzMOI58/PHHDF3Ps2fPODo64jiKaHry\nAT+OWLV3JyiTTkCNnFcUODrFPaKGyBCXm1drLVC6Umhyr5OSEFdlNzu0GCOTDCkVKDgIMKEkl1FZ\n+VRCTJjVNfPa8PDsHi9eX3Iz7HAx4Z1Dt7drO581eaZzqQTI0GiCTwwpcDpbSNqJnnqPFEzgxuGu\nVhRztBZhxZJnhRCwKR0AS/LY2HW4XeTq6oqul4Ls0dGR7Lh1JaDKL3Ly3DnobwC/BfxD4FHaG1w9\nBx7ln38hvqSfNgoKNWSBdK01g3ccH51ys93x7PlL/C99BxVB24oQdtPkKejWYfjAlGftE1o/uilP\nKrJP3W6HUtI/UsiI9WJO1Jo0ZKv0XcfF+aW4rm23bHYd3/nVX+X9b35zuvmbzLX6zd/4nvhras31\nxSVD1zNEeY/gPV13w/X1NavFkpOjYxaz2R4xzJB3ypNdK9FbUEqQN20sVLI/ptz3Y2wGDGLCkbCm\nsCkiIWtn+zCKVkMspFHhn8UUsU2FSoHdsMPGyLuPH/Nbv/arxACvf+8HmBhp6pZtCm9MmE+rnYHs\nKPsO1IitW0zTUM8XvH79mrHfTeG69yO7XbxFy1FKyhPr9XqylT/MR5WuJpStaRqUTiJq4hXPX3zC\nzc0Ny+WcDz74Q/7wj/+IbhjYje4vZ/IopZbA/wj8xymlmzs0l6TUF2jBk9ebPEnfdkz5UHZJKCss\n5gBK1kaE8ri9u0yr3UEedfi6d6k+BZk6zJuAKe72ymCNJRgxnR0Hx9D1KKMZXGC1Oubevft4H2nm\nhkU7Y7FYYI3kLDYEMWfqRTJ4t9tJfpHDkn7XcXp6xmq1mvKQ0pVQAA91kCtqlabQVAqL4u+TtMmI\nZNb6jopgEipG9EFBcCp4ap1fV7pOnfNSNzI5HJNqGO88eszlN3b8Pz/4U252/SSOcnheb5UG3rz+\nwn7I0lyVEoi+cNLK9SMn/D5xMJn2nkFFgqpc36lNwYrgpOzcWdlI70sFbdvy5InkyaN31K30Dn0R\nU9+3mjxKqQqZOP99Sul/yg+/UNleUSn1BHiZH38rX9J04En6thPv7oURREUQnpj2TWsh3iaKlr/X\nWksL8p3XLAXEwy+d9r8vq12BcCttGLRIxAZjc/gmmmEhRWxd8/DePbQxrE6OiVGQsnEcGWJkMZvT\nNI0QEZMgbtu+nz5zKf6tVitmedcpodPh8cMBbJ9DVDUpot6ZGHIwefcNUgfL00cZjUoFzZJCa4wR\nVRjrucfIKmnR7ncdjx4+pAtwenxCP54Ts6LkGyHxZ4z9zZ5KVzjKaLbdLhfAK1JyE1oX3N59u0DW\nE9MjpUkEfhhEC85jILeOlIjl9PSU13aYgJVldtFu21ZUXkvo9pbjbWwVFeIE90FK6T8/+NX/Avzb\nwN/P3//ng8e/kC+pnJSyuiuEXnMIXcvvOzuSbIQA87qi63bE5OnDwE5prnNl3kawLuKtJvUBO2tI\nTrSum7bOTOSEsVJn6b2j6qRAppOwAApgYFGYVAQMEzogNiCNJyZPs6xZ3X8HnyIPx/dICWkrVkKr\nr1uxoE+5BkOIrHdioqRSwo3DZPBU3vPek6c0TSMeOHWdV/t88xhIqYMoJsIpWmKAXrnc65MdIGxN\nSlI3IimUsjQKkZyKOTdAxOqJDq0SVa1wu52I5wfPoOck1YCKuNGR4khICWsSdhx598ER//xvfoff\n+b3f5/nLl8x1jQ+RoBLB1pK7FBZ6TCg/iHtBCviqmnb2yijwjt3N9QQzl10rZGeDkNszrLW4fuD0\n6JjdekOjLbUyPHzwcJL4OhoNp1kSONSKGz1iqwbSyGq1IPrA6ekpf/zBz/jxT1/w+Nvf5qMPf0of\nmKxm3ma8zc7z28C/CfyBUur7+bG/i0ya/0Ep9TeBD4F/HSD9vL6kebyBhN35XcxFwvJz+b7b7dg1\nArtqJTpvn/e60/OznsHhdl1CnASyCiup/xQbe62l+1JrKUKCoFuz2QyfEjZGQpTQ8lZ4C1MSD6Ar\nC6PcEIvVSuxBtMYrnx0ZPp2mVOo6E9xOofEHTIxAoKo14+iIEZQWwypjDCmKTHEkEL0sAFZrFJEU\n/L5xDUSEHnndUl8zOVxsrFiBPH74iIf373F5foFWGmukeOtCFNxBG9TnCAneZR8UBsEhA6LkqiV8\nLjaKwNTysVgsGLU5YL9bkt8b/yqlcN7R2Jp+cAxOdr3KGow2mGz9+ItG2/5v4LNe8V/6jOd8IV/S\nu+HVYdvBYXgCckJt6dHPFiJJwbbbcWMr+myt550jIlyxSBKOSlJyc2U+mx/F1s+lQCq8tIP3S4iP\nTAnhYinmKnGQK56mY/BYJUo2ujAXKrmAwvcSWk/W3CBZlW9+Tbuco1LCaoPNif9u2E3vR6btCw+O\nKcQsIZIigUrEEKd8QOtIt9uQkD4f7z2FKzxrKpSOZO1HasQlPDrh/kUf8s2exDIlBVQMpOjke0rU\nSTFEuRbf+cb7JOeJ/cjlj38qtJuqZowZlSwTJxUGSTmQ21oV3vvp3LdtO4VmhfndGM1yuWS1WrG5\nvtlrXo9SJ9tsNiQfuLi4YKUrrK1pjKWqGvpuZLPruHfvjKg01zcbLq4GLq8Hjo8WXF5eM/SOtl3s\nP+9bjC8Jw2A/Pm/XUVpNxcppRS+ruNZEJTe7+Me4g7Dv9gpnYKKThGx+dbhCldW8gAXKmnyj6n1S\nffC+Pr+2tEsDKe2Nm+7sgMXbByS8M/lmKmZPwFQvSVqB0VO+o8g7n8wggOk5UhxNTFaPeOnNUSK/\nW3aUMSulRhWFIqMUKTjpXh1GkveoKEKHNsPj5MJvzOZPSluSc6gYaa3h0dl93nvymN//6Ue4BEYb\naiNiV+7W9cyOfuq20GTZdQ5DtgkIyXnXXav3AhClEKfHE9lTVpvJfVxn5Z1SaPUR2maGczvOL24Y\nBkPXJzCW+Wz5OXfmm+NLM3kOb/TP/X3ai7vDnvpOPoE+himUigfPPfwOoBO4GAm5b4SD3e7Wc3S2\n+tBK8qH8NxMjQVmISKiVdyJyfhNV0We+fVzlQiuY2gZ8zrUAjN2He6GEUFo6SMvOc8iOADCmOpj4\nxbNVULiEsMZVilkDWhFTYPQepTOVyIuVh4lCXwkhYLVw9VKU/p40ZsUfK7UgozSVSpysVjx58IBZ\nW6MGh9GK0WqRlZINfxIgkWu4r78c7j4FkLnbihFCQGdT30MVHu+lmFtcrVU8RE0TOnvS2lpaw30M\nbLYddnmMj1pEI+sWZRyz+ZJ5M//Lq/P8/zWm/CSKrGzywmeCXDwjsGwqxhjo3YhLkcE7kqpESVKx\nV6TJJzvE3I+ThFBZquIlnrYZkUkh4g/yK62leNeahhQTY9eT0BhvSFUlstJJVnWSFN1ium1Jb6yA\nIIJo7QmbZWrLBIlTiKjVHhFUKFQo4eM+FxCD4YRSskobHaecQcI8QdaskeMnRQwhM20DRoE1lhRH\nUhCo2+XwscoTOwW5BjFETBSPIr/rSEPHN955zNlswcvda1pjCEqja4XrevYrheych/1DKUkrucmo\nWLGIL122hTndjcMkMg/7fK86EHov4i1KmQlZtZVhtVpgG8X51TnuZMFm3TP4wOm9xywXp2z/9Gcc\nr5bUWVX2bceXfvLcOlnlIhwOrSZbD2MMMa/KthYI+xA8uQXf5kmTUpwq97coJWnPqdPkJqlcP9FJ\nHtOTMk8OJ5xIIxFlld9XrPcAqIRjev8evAlmRH2HuKr3iqfTaxz+fPBZpXYiiwrZY1QrhdI58fYj\nYTrOMgkza0HlHCWUcLOI29/eIYKLoqEA1JUhJeGRHS/mXF9XmBSZVQ1JOZl0t66ZJvHZtZRyHHf5\ncId9QeFAB86nfVtF8ll2OIsfimN2lReryGKx4IKArhpScrSzGShD1c7wUeSND8mtf974Uk6euzWM\nw8fL/yT21mgl/Tw+idnUy8tzHp2esqgrogpZSDyHeVpN+YN3Luc7SXIPiqBGXuW92PrFIJT8ooup\ntVifp+Cyy5rONzaokPLNpjCFSwZYJZPTBS8ghDqQnioHdEDRTabI9u4n0fR/mIyJQRC70gIwCUEG\nKSIWexWlpZVbKcUQxv2EzZNSUDUtLQ7a4FVu5NORFEVoXYVI8DIxtdak0RFSQKWI0VBZ+LVf+ib9\ndsPltuPk5Azd95xf3xA46N7NB1tkkWWH2F/nctMX/YPFYkHf9/h0sLCFOCnjFMCg73uSF6RuNqtR\nyK5zdDxnuZwRZ45YJ7RRHC+P+PjVlvfee4/Liw2z0zPmtbDiv0il/0s5ecq4WxQ9fHxfEc+tBwV1\n227php55XU270Bt8q4MwMJQdQpNzg5yIhzCFKrbKO00Ck9K0SkfnJcTRVhQ3lfQXRalSAvJzZTIt\nKIm8bFG+4YD+fnh8BdVTep8bHR734W5cRkjSNKaQlmWVHRaSzNYJ1Mg+kvJ6ua6Uz4yotmkRhbfa\nMKQ+5yuRFMMk0GjMXrg+RqnBpBg5PTpmNV9wvdlitZpyOJ3gbnvV3fDrEAS6K+giVKqDHTrneYe1\nsWEYIERxrcgtC1pDVRnqRpNaw9rvmC1X6NpOWgW73Y5kNbpuZFH66vXzfPq4e5PsK+XsH1eKqNJe\nlSVXmPWdGzMi8PKUZJcwjXTrwpQ6UvTZylypKYbWKEyUcC9mLeoUyU5zGqzcsLq4aidBB40GjSJm\niHwoluUmF2SFcbT3Rb0DnkzKo5+yLBY2QYwe7xHL+ZSE3Knlxg2Z7JlSQluVTY2Rfh4SKe6F7VUQ\ndoXWWjpbYyIiLOyUe56KpFNiv4hprTlaLTk5XvHq8gqrteRqb4Rtt4/x7sQBbiGU5b1MXU33Q8xg\nwTiOE8NgHEfCmFs7jJw1aw1Vnd3yrEZHaNuaXZRJOTrHxeUlpnkHlxDN6+qfgLDtbh5QoNjDobUW\nxRbvUG2NskZEHfo+24bknEOriTw5WZCEvAMoubF7n+VhByew7OBQQVQsqVus0lQqy9NqjcvaztIJ\n6hhUTz02kNu2xXlbbuQ+dtNjJSSMMQqMW0KnIkyiIFUqbw75hjqoPeh054Yrk7jcQPnzxeCxUfht\nKhV7E3DOT3zAIroYk7SA+xBwg5u0F5KOE+0nRuHDiRC7GOFaND6OKERh9ezklHefvMP59Q2xbqhr\nAV9UerOJ8XBhvNuANgzDBFFvt1sxAD5A36pcRL26uqKpsoGyMfROjIWHQdwcVkcLFosZMQZS8JhK\nsR52vLi8BANVbdhut9z/xiOsUXTrmwm9fJvxpZk8dwulcFsIRKr+Hp3Ijs8K5R0EWDQNNRabDLtd\nJ3JFEbRa4HoINZhKE1JEaWEMhCRmS0mJNcgSachaD1023/WY3Kq8G9fUxkoOk2/kSs8IUURIiLJu\nG+2xdUOMifV2oGoabFtjg8X1DtuIllsdDaZq6NxIrBLJaGLFFNc3qHwzFz9UI1prQER8VFECWFSU\nYqQkziFGAhLSuLi3FNQ214tGCbOUkvg/kQg65txRQtlkIson6qDxwYtEbRTWhUpFlyBPimCxAVRQ\n+HjDcml5eO+I5+stcwMzk8T1LSVUJvBGJS7bhzp4pdmteJYWPl9RIPWkCejwmSxaVxaMeBHF5LCt\nwjPQJI/rHKqq6ROMxmBsZH48p9eKDz/+mNE+on366zxLH3KyPMP6ET2v+AI10i/P5Pm8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WZTunyzLpp5VwJGgyZMiMnQtqTYzbtKnSaQ3BFZUKsyhML9mZaKYohsgtB1FijxkdpNNsO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\nl85zaZf2Ke3/BzEvuGvrMr5NAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4ba809e050>"
       "<matplotlib.figure.Figure at 0x7fac60267550>"
      ]
     },
     "metadata": {},
@@ -52,13 +52,14 @@
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " ['roi', 'Shape_Para', 'Pose_Para', 'Exp_Para', '__header__', '__globals__', 'Color_Para', 'Illum_Para', 'pt2d', '__version__', 'Tex_Para']\n",
      "pitch, yaw, roll:  16.8574 45.7653 17.3256\n"
      "[ 56 -85 619 478]\n",
      "['roi', 'Shape_Para', 'Pose_Para', 'Exp_Para', '__header__', '__globals__', 'Color_Para', 'Illum_Para', 'pt2d', '__version__', 'Tex_Para']\n",
      "pitch, yaw, roll:  -0.978765 18.7533 9.07337\n"
     ]
    }
   ],
   "source": [
    "img_name = 'AFW_4584451140_2_'\n",
    "img_name = 'AFW_5144909700_3_0'\n",
    "img_path = os.path.join(AFW, img_name + '.jpg')\n",
    "mat_path = os.path.join(AFW, img_name + '.mat')\n",
    "\n",
@@ -66,8 +67,25 @@
    "img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)\n",
    "mat = sio.loadmat(mat_path)\n",
    "\n",
    "h, w, depth = img.shape\n",
    "bbox = mat['roi'][0] - w/2\n",
    "x_min = min(mat['pt2d'][0,:])\n",
    "y_min = min(mat['pt2d'][1,:])\n",
    "x_max = max(mat['pt2d'][0,:])\n",
    "y_max = max(mat['pt2d'][1,:])\n",
    "\n",
    "k = 0.15\n",
    "x_min -= k * abs(x_max - x_min)\n",
    "y_min -= 4 * k * abs(y_max - y_min)\n",
    "x_max += k * abs(x_max - x_min)\n",
    "y_max += 0.4 * k * abs(y_max - y_min)\n",
    "\n",
    "cropped_img = img[int(y_min):int(y_max), int(x_min):int(x_max), :]\n",
    "\n",
    "plt.imshow(img)\n",
    "plt.imshow(cropped_img)\n",
    "plt.show()\n",
    "print bbox\n",
    "print mat.keys()\n",
    "pitch, yaw, roll = mat['Pose_Para'][0][0:3] * 180 / np.pi\n",
    "print 'pitch, yaw, roll: ', pitch, yaw, roll"
@@ -75,7 +93,7 @@
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
@@ -93,7 +111,7 @@
     "data": {
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UMpSGxWv+bCPZSCSq9YWnSr0sP7FCWTa4l9iFtCYFEZQMQPNiCftFvilVVZXNhhcvMqVL2hO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o2Y2NjnZe8/GVMJo7KZfpul/0zp9ExYEKido69C7v0bUfwQs4BVcaKiqi1wGKNJUUI3jOZ\nTolxAKvpfWBuaikfvF/N22OCZSt2ZjFBHga0Ey2GzgdSEH+FqSuNhbLtbc5m5JWmoGFs44xCKs5Z\nrJHxIIAyitT3oll4pNk2ovxGzcdcRnKj/kQIgaFrmVaOYeiYWIvTClfAX6loB+QQUSQUiegHohfT\nltgHkXsrqfJoJTdOg0AeVmV08WvoaduWaVOL/mERXx0nDGNpMf70fSAZ8VPIWUGC6aTm/OOPre4B\naSYmrFKyM2stitJK0+cByKsUfcX50MJHsU4k81ThtmgrAjZ5CCxSW8qMKOpUCIgtKWnApphQ1gKR\nbDQ+Cc6hqiz1dEJbOBGLxQLjtLA5tehE6IKdEAyMIlEEXwrJ63Ln7c/6DPyFnpwv4BVCWJmg3HPP\nPTzrK76Om1/8Ys7sHXDXRz/KfGuTZz3ri5jOKprGkZL4BFgF77vzveQhcPXWcXYeP0u/bEUvIEk0\nN9aUxDmTkyIauXirnSRJ2tfGiJ01MBTknFbkMjPXaKnxg6euazQanxPKB4xW2GRYti315QeW8kr8\nxGgJUCDjLIDKOSpjSUYyiUV3aG0fSxpstLAGY4awkoZb9WVXXhkrToWVLn0MgameSqpdpgYqRZRK\npOALxLkoUKmMJ5JVIS/pTJIEGcnapfues8DFz5w/Jw9UwU2kcS5f0JUceXBzzlCJfFvWhiEmhm5g\nY+sqHjx7bhVAR2JUNhofIqEoYWUfyAgqNQHZKkLOpJjIBW6sySs158sJVRSA0ggtT0UuLeUkx58o\njlRBAq0WhaaUM7pyQhbTgs4sQ5RVZpA5ZIxmyqi1GBkrpWjPHga9J1ufoyL8F/4ad5aUE895znO4\n595P8qaf/j/443e9my9+3nN4xZe9hI2NCevzisoGjIOYBrSBO97zp5w4vkXoWkLb48OhOrO4D427\na/FY0IaAKlmEpl101PUEYxwpQszjKM+iMNLR1oacFMMQ6HPGkxhSxmeZ0kcNPiYW3YJ//KpbV8f1\nr3/3d+TBRiztdc5YVXZBYyigv9WPUK6NAI8KvFdrfUntfDmSL4QgOIduSd8uGQZBKHovFGBVvCpS\nEBxC9IEwDOLj0C7xfU8cPD6EQiVGEJQxrhCTuvQJlJFR3rlz56CAw+JqdJhW4LPV2LUgN1siXmeC\nUfRBuCcuROLuLv/b8WuAI56dZZRsraWyjtpV8lOJL+c4WsQIniDmVH7yJe8zNk3HbCJlmYjk8b4o\nWARlZLcPRYk5piTHlhNrG+sMwctxFl6IfEixGByvQwlGR/UjlVIcr68cwvRUpnDZGo1f6qrmrW99\nK2tui1u//Cv4tu/4Dp5x09X0MeNsZhj2mVQVWTm6YSAnDymy3D9g7/RZhv2lzI6ViI7kLPJnWWkR\nMdGKLGiVVQo/eE8OAVc54QeMY6YsUV9lASnhIz5GlkPPxFUok8r7lBTRWfqxq35kjXLwQsVNqxtJ\nF5DMWAKkIr8GhwK2KyNcykNX3iON+oWFE3HorBXIZWY/QsW991SmLspTQdB7q8DQEbNkTkVwGaus\njNOU7KZW2ZW9nrWWtm1XmVaK5Tsw2v0JDXlUoBaoc0nsUyb6wO7OAc++7lk8cO+nSG1PVZqUrz/7\nMP/nxlWMCMacRahWzsVAnyPJGLK1K9j5QKJGY/MhfXrEY0DhUejCixh7EUnEZSJH+gqImKs1bgVW\nUjmzvb19CYNXKckCUgmeklQdTh+gBJ+cUGhuOHHsip+BpzKFfOSnrFgAQwddy8Qdx9jMjTceY7m4\niA4BPWgmegNChcKyphzLBx7lI3/0bnYfeIihW9Brz6DAWzF9iUqT0IV1pzFJr1R8exK9SmhjiG3P\nNCo2osHmBMHjFOTgMZoVL8DkRHewwJea1CPQ26HryUOEXBHiqAU/koEyOXeQOhQJrTKKRE4BkxNa\nmhso7wnDktAtBH2YE5U2IrsWAS+BYgheJMqKWUpUmT4GhtiTVEA7RVUbmsoI2Sd5Yt9iQyIPEHxm\nSIqsK0I2hJBYHrSkfY/uIfcZoiZGRVQWrwwDmi4aeh/Y3b2I0YnMQDIZryO98XgGYuoFRr1sUX3A\nxIxOmqejaQfPnqs5t1xw7fY6O/d9AhcTtnhNAlA1KOswyuKUZpI0k5ipq4ZJ1VBpJ07kGPEC1YZo\njGh6orBZkKumaDkkk2gC1MYSFXij8EaRreAKamWw2dAHR9IzlKlYayxGJ3pd001PEnJaXe8xPOQo\nMGwVZeowSv2N0wvpWyR2Dq7cdfqpoPAZ1rhr7hxc5J57P8H9Dz7OdL6BrUYzWNEBiO0eD33yXv7e\n93wPZ8+eZzkE+qBQdvKkn/GEmXjZVfu2I/SDPHA5rWzLskImFyUIdENg1i18HwAAIABJREFUZ2eH\nvcWypM8KT+Kga1n0PYu+47te+OLV+x8sF/SdZ/DxCTN80U/0qwziqK/k0d1+/H2UrRffxUM/Su89\nfd/T9z1d163eMx7JGkKM2MphbEXKMgWYTufM19bY2t4m5sTuwT67e3siiVeQjGPTcTKp2djY4LHH\nHiufUZiUyq5ctnMSHISrG+GOGIe2hn3AJ3jwU/fxFS97GbuPPcq5Rx5iUls6v+TN24K7G8uNo6zI\nsWY3qkjGZynFRIPTSq+h7OYKVnTpsdwJpYE9TmnG8mN87yFHYXwqRSqZXgiBajbBzSarEm08z0d/\nxj7OeE2ONlfHEuJK11NB4TOsMSj0qeOgGzh/8YCQJc2W7VKaTt2Fs7zxn/wTfNvT9h5taoYEQ3rS\nj8CkywCVhQQVB78C7axuzDKeiirTp0BbHIWNrVi2LfttRxc9EcFB9DHQx8gQDyEib3rnu+Q9Sop/\n9GecJqxcqspaoeTG+pmiHDV42ZXKw5PKXH98/6M3Z7ysjAg54WMiJgXKoa3DVjW2bpjMZxw7cVwm\nMTmx6NrVzT5OIKra8vDDD60APTHGMjUdz+YYzEr5kwoIKybOLlpCEmGTZ159Lffd/efkbkmOPc4d\nAoTecOHh1bEeBVkpEEXowlBdBcnghWRVrpfwOgqZqlDLXRF7tWWcOgbWMfCMXpYpCEPWKuknZGdY\nBBkxj99vDNaXP/xwSOs+umK8cqjQUz2FT7PGk5pSItvIsu3Z3QukiAy6lUfphM6af/bf/tfsnX6c\nRx9+mNo1OFuBcmAt+M/uzKNYZfYkJSIoOkstaPKhW9X4nYayK6cUiTFgdIX3IgA67O2h19ahEXRi\nilHsyy6bUIcE1ppLO/II23F14x+5qcZMIhbR1rGZGGMAa1YIH6MEm49ST9i5VniDEvSMs/ihgKFc\nI+Al25GTyLNn55iszwtJa5/YtiStRGZdK0IY+NjH72F7e4Ou98JqVGJrL+xTqaNFBEX0KMYmrJuv\ns3j8UW555rP5xO3v5bE//3OuXV+Hdo8+DaSkLznnY1BUpZdhTMkYshyzp/RWyphS2I6sqNZHG4Ap\nloBZ9BSAVcC1VtysY0GKuiLdpqzBzCekiYPuMIOJhUGq9IhezKv3Ohowxs9w+gp2qbKeyhQ+y+r7\nnsEvyFHz0Q/fBwH6folKPejMO972O3zsQ3ex2N1jPl1DK0cIaQUK+nTraLfeHHnJKLySUkLHjF92\nOKVZa6bEwYsOgGx9K0hvzjKjzlqTjeXA9+wvW/qURI0HRZ8z33jzC1bRp+07ll232nmPduvH3cZ7\nf0lwGP/f0dLAKqEDA2VGXm7OIv82ZiNt2x7u5uPnKKH6dj5jbINxE2w1RRVrN9vUKGfZOnmCrePb\n2MrRDT3dUGjPIayyhNVDqxQKQw6ZHMeuuxEhFaXpUyAkqa/3zl3gWcdP8MgH7mYratRykLmMrQsU\nuZyrtl0FwrHhSqnhCUlQimUyE8gFkVgyoqKlQMort+qxQTpK4q1Gt2NztoCWVIbkA2HwMm50hkd2\nzjEMssmMMPkxyxvP75idrUx6jlzTo9nfk62nMoUnWUoNLPc7PvmxR0RBp2rwi0dZ7vS8+d++iaHt\nWCx6KtOUeb2CHNH5qHfTp1967Iirw9FReQfJGLqBje0tAA6GDquFWTfWtQMCgYhErJW5u/dLkXzT\na9LcTBEVDr9H7yNap9UDNX6utfayuvOIZZqGHA9vvBgjTV3JQ8xheaAMl+xUl+MWbKFSK60wusI6\nTRgi00ld1KOMWOEZGdM2zQRtDbZynDlzZhWYLj72KClJxmKtPaRsX8Krk/0uxkTSSVySrCbst1y7\nscHH/+wODj55P9uDmLR0SjOQ+MGDM6vr5pxb9ShGxWqjtLAWyxTDaoNB/BwMgiMxo6msUqPt50oe\nPqRD2vd0OpXXCOoIn5OMobOUJsZYglFQWfrCjh3JXqKQnWXUq5QY0KhDkZcxcGotPhMhX7n00lNB\n4UmWip5M5txjF+Rk5YyKnre8+ae4ePosbdtjTUVIhZmXEyoHFIGsqs/63jYrfMG5J/KqfBjTT79o\n2eUC861NhuBxQnmTMVdMoCSdzikSUxbfhmTpQmR3ecC0bojWFYckWf/v+97H33/pS4llt1qhBPMh\nwQkgFWSgpKQKU2jDzjmaphGjGa3FUKYcw0ieGvEYY2Douk6EX60RCbksnAdrK3IWGriPeZVmm7oS\nDUttUMZQT0StacwKzpx9/JAKnWV0FEMmqYAxo9cDgJjZ5JCwTpHQ7Jw/zc3XPYM7f+NtbPSBN+w8\n9Gmvzc8cP0VWeSXConKhYSsrNvQlQ1BOSZNXF+ARmQCgNNoURhtj6WHIMazO9UhwE0ppJjopg6xS\nWC2w5aAVzfqc3W5xJLPLrCzqMgJ9ryarcw6XQtHFT+TKgc5PBYUnWc4ockycPX2B049C3Zzm4x99\nL7/8i79Et684uXGMBx94hBPHr6GPQktWJFSOT9AA/FzWKBiaes/B3n6BzoIrxivBe7StyTqRMeSx\nf5BlF1u27apbHp3l1c9+Du8o7933PfWRAHA0Qxj/zugjGIaUVl6NTVMoWimSS9ngbPFFLKlqLACb\nsdt+tHyAonrkPZWrcdaOj1EZASrhfhwBKBljVsCk9fV1Lly4wNbW+soBq1BJyTkVVaLDVVUVPksM\n7foW37Z845veBG+69Hz/u2OnuJgD22acGJQduOywY6bgnJPfE6SUSU6j4wAkMewpWfrRhxKkPDw6\nadBaF0KVAR9X0PoQDCSIMeB9JgSDrSse39nBTnV5v8TOzgVmsxl1I4pXpoisjJ/nnFsFx5TSEyZd\nn209FRQuW6P4xbhCNPTdOR49ezcXdj/FF586yS/8979AEx1Oac5fWDJbO0bbtjili5RXRabCctjs\nSTmImxKsegkhC93VqsKczOBVptWZZEcM/oBdyEhuWtf0KTCQSJVBZ6lxXQiSnk4aYRAq4TL0wyA7\nip5gySsY75AiiyHh8diYqRvRK9QaVIolJU9i40yhCkePI6JMxlSatlXkKN/d6ApnI0OKhJjYVR6V\nA00ULcg0mcmIta7p/MA0zKRM6PZRJiHtuQFQ+KjJ9QSlMkMIRGNFcr2qmG9u4nPCaEcMhiGDq8Sq\nTdobkehKYIrSWFTa8o9/6i1PuM4/ftUp1jxUZTrhVWSmFUutqDKYmNAh4IzI0AUEB0EIkEMxzo14\nL5JpKiSqQsAaakWXofERaysSmqFSDD7SpURUSjgQ/UDWlloZ5m6K7z1dPdDazHywNGYNq+fMNrdZ\n9udYC4VWbRTTzS2MltFrZTQxH2YJpriWj0srxeCf6in8la3FwQV817Iwjv/8a7/MZv21vOudf4Lu\nLco7yQaS7FSBQvnNh5JfR3eGy6lqh5z3MXUXqrRBFIB9ifA5Cfrf5Ixzjna5EDVooy65EQxqBWpR\nSrD1InveY6pD52EfA0YFiGV44NWqsz5y8q07zCLGFPToRMJaJeKjCLBKGYU1SsRQxsaZE+3Bow01\nEyLBBjIZ50TAJUa/wulrYwhR+hMxBPpWSo/JRHw377777lWTFYTASUExgoIelNL8wFt+4QnX8l/8\nra/H3v8wiwcfZVJZTAwQspQyRhqndlCiAYkiaS3BQGUGA14pJkoVTEJA54zLMpDSSPmWUhIGaraX\n9InG35VSWGOpiqmv05bYexaxI2XpYJgs57jzA8Zq5utr5DNni2O2TILGZi5ZoY24ix3lWlyOZv1c\neJJPBYUnWVZF5hsVQ3+Oe+/5ID/8Q3/E5uwYB0PL4AeyQ4IAR+s5Vrz7zw4aERnywwuWV+lwFi6Q\nUG+RURUxYZ0YpPRBzFrHh8OWskKljLLCURhGliCHHpMAv/GRj/LNX/IC8UlMCp3Ec0ApXUZ6eWWT\nvupqR0EtjmNHpS6bOmRp7TmlhY2ZDzEPIUbarsN1NdPKEXNEW42yCj8MohlRvCBM7TBJCUTaB+Lg\nJRsqhigXLlw4FHAdHwwMP/R//+KnPcM/9b3/JU1d03Ud9+3fx/TsDut2zjAkTNKlKWvIRaHJ+VRG\nmaJ54VXE6wIMy4mJEsBSYVFLpocSM5jBEylTGmDNSE8pZ5lS9EGmOkR5jUacqTEKg8Z3obBHBXMR\nrSYauLC3i0Hh/YBKmmQoTubi+TmOOUXeXpqjOR6Ol1OS83vF9/yTvUB9Zt+H/wn4r4Cz5aX/Q875\nbeXffN77PozLacN8prjpec/mi264hre8+TdwSpOGxHQ6ZRw4jHoHhd5eOtUFD1C68VpdxkUo04fR\nlUDHlT0pAKns/lIzQ992WAVVU5UbIQjffhzLjRyZfAgiElai3JAvv/66laJuFz0p5oK7L9Ro9Kpn\nMWafMQroJ6KIRbgjawOquDYpEToVgZQkhqhKxm4xF0l6MkOQKcQMiHgqO0GZ4qpcO/lMlJQGXc/F\nnfMCqqoMdVVxsNxfKTutzebEGPnnv/TrT7heP/UPXi/nYEUnjuSk6Bc9y70lU+W44FtsFjOd9fmM\nyipSCoQ4ECZWeB5KYYycB4PBZlUUm8XIlpBQSpNQ+GToQsaqjC6UZY0RtWU9Xr9cPC3KuLYfqOta\nYMulZ5OdwarE6H1pJg0HKXDfA/eznBsmQaGyRpUplK0KnT5EtJFMcMzIZrPZIZBKa7z/q50+jL4P\nB0opB7xbKfX28v/+Tc75Xx99sbrU9+FpwO8rpZ6VP0/Uly5HftlqQtcveOiRT9C3B0ybGcFnmpmM\nApW4EgiNdeyec2hKCkcyhssyOHkk8wr8IvLfJUjkXMQ4i34BCpQm9gNZwaRp8D4S+gBZpgUxilq0\nLoFkhMlmpclebsKxr9BnqR2SAh3L6DHmlVFrLuYi4002IulkCX15vHmCD1hnMa4q9bynriqappGu\nfD60Ve8WSyZrjhR6DhYdCiRbyJF60tAtl3zojg+Qdeb666/HKcNysWRtPufbf/QnnnC9fuy7vk3G\nqRgxai2KUFkLmGm57DA64H0iRnis76nW11nf2Gb92Cbzpib2LXpYMOzvc7EfCP3A4uJFNvSEKinm\nymFCwMaKQRcMh6i7ynUMEZsV0Q+YytF7T6MVfUxMa2n4mdI4TSVDcE7k2EII6Mpy0HUMSaOtIvuA\nrh37oafa3GKJfPcYxYU6FOi4VxmUNLUtZkWEMloTB39Y+sVEjn+FQSHLnf3pfB8+0/qC8H0Y4blt\nl1GpZXtzwgMP3MfgE1pVtKkn0tGoiYwQkfpc54JOvILP0SMCrmR2hTS5CiYRtYLMyo3ISrcw+cDm\n+gbnz58XnT/vZSZdFJVSDkWwNMkbF5j0uIYURQ0tS/9CZ1DFhMQqsXrr+34VDOJl0vGVPtLp1gZr\nD3H8OdtijFrgu0imolEsDxb0fc/m5iaUXVUpzeAjF/bP8f73v5/FhT1u/YpbmVQ1r/vxH3vCefuR\nb/9GtLLkDMoW0FJWgrrUAxZDTJrsFfV0zrkz59m5uIfSU55+y80887kv4MTTn0FAsbW+xsxkTHeA\nCgNtN7C7c4GPfuhuHvjYx8lDIrQ9VTZCNU+d4CwQYZQKRW1giKDrmqgAMtpZciknR9fxo9MoXUoP\ntJQlXfSgayqtMVl6RHpaMz+xReusSNOlDDGKSKySPkLMispqyIejzqNIxvEaNZdNZT7b+sv4Pnwd\n8N8opf4ucCfwT7PYxn3e+z4cDQrdYJk0liEEdvf3IM4w1tDjUVYMO5JSfA5j4EuWQQhOBskkLOoS\nbUBVmphk8STUSH8g54ytGra3t7m4uyOBQB0ColbjRDVqG4qz00tvOsUdQOcHxPdSlKFVAKsVdVVh\njWXh/WhAVdB8lwYFZw7f22lTsBDiZ9DUNfP5XKTemoa6rlfNNaM1k8rRLxfYynHx/EVCipw7d46P\nf+JTvOXu9wPwM7z/ks/70W/5JvYWB1RNhZmYQkcHrWTOn5KMbLOJMqHpI4u9nvNndlFYrrvmBp7/\nJTczmygePL/H6d7TJ/jw/R/m7tveTd0vyN2CGDO33HILX/War+W1r/tWPvjeO3jfn9zG+TPnaIzj\n6n4JCO09RVGYTiO1XIt9fRoBXUqtds+juKpxPJizSL0FBN+RU6TCHAKmnMVOGxbtHoPOUjpETVCj\nmG3EZEWyGqsPfSyMEZj7+LtSapWtXcn6y/g+/O/AjyBZw48A/yvwvVf6weqvue8DyMPQ9Ym1eSUq\nxcYQo1nh3J3TpFB2co6o51K6+lcYKMyRQJBLXwLK7vJp3kalTMyR/d1d1jY22D62xdnz58harcg2\n42hVlcbgiIAbV+8HtBaPw3EHizEKr0F5VCHvHCUyHV2xNBjFLSmv0H5V+Xc5Z44dO8akrqmsEwMc\nI+rT+zu7AOwtDmjbnjf+1n96wjn59X/6RvGpVJFzFy9wtj/LfD6XBqUSHU1QjHrGZC36hqkjhsz+\nXsv5c/vkpPnKV30N115zins+8nHu+LN38rxX3MqznnETL3reC6iAJmbe/u9/nu3ZDBUzd9x+J7fd\nfgc3v/AFfOmLXszf+b5/wJ++80+458/vRp/bxxgBbWkjbkwViiprUh7EtUqXxt5lBfPlj2UqWZxS\nqkxhYjH8KWNVBOW4d3DAUBmRvE9KlKlyxmpE5ylBLqnpiFIdAwKUTe5zcG78C/s+HO0lKKXeAvxW\n+ePnl+/Dp1lHewFu3jGkir39ihQUGg85UKuK3FYEzaqGF800UEpCRCi2YsXBS9Jd5KU6QzLjQPLw\ncxNZHH+UwhEFVYfIoos5jMJG2dV7ndnf3UUZw+bmJsu+o+06tLPoIeKO5KtZi4DJ2Da/KytefN1V\ntFEw+I2r6KuaWmuMgXmxvlPFoamxluwjFslezu/toJylamrREcwKlzM6RoJvUcuB3eVAaCaQMn3X\n4bThX/3x719yrv/F138j3/VFz6G/uMezr7uBq45ts3b9KfwG5Kam7RbstAuqtZmgORUoGuF8xARE\nqsayHHrhWpxL3Hvfpzh2/AS3fuVreMbTn8Yj93yEd/z7X+fs/Z+k39ec2ZxiJpEL+w+Tu4673vsO\ntnSHu7hLO2vYrR3V+iYffP9dPPTHH8CmjpPPP8Urv+GVnH7PvZx/8CHmQ6bOmXZxESqFNQPERmDn\nKeNzRruKoIpdTQjy3ZUGU/gqyuBzYjEEcnZ0U83xrJkWrcbJqas5PSxRQWGWntNmD50yNkJlHKqq\niEYzGE2lx8xAEY3BGNkgohGdyzZc+aP+F/Z9UMUIprzsvwA+XH7/gvF9GFeMkezTFfUJPtsacQnj\nz9Gls2wso/Ye4++r0RfkMvpDyQ7pygtjzBzs7OLqWpSYQkKZS7UJlSq0W+t45bOfwW0cFV/NK8LP\nCi9fVegskmC54CWaqmJiRPlZtQPLriMOLcpZUSGy0BExvQB0hmXLT9z1R084D//qNX+b1g9c3Nvl\nQ4/cRYXmmuPXcHL7KhrjqKe1+DIazdkLZ0kKZk2DDwPOWNrRnyFppqai3+3RbaS9sMPt+49x4003\n8PVf8TfYxLBz98e45x1/wFrf4qLhoLJcvPsuzn3qftRsznJ5QNzfY8MKR+CZz3sxL3jNVzE9foJP\n3nE3H3v7H6L3Mhfue4wP7P0hX/+d38PZ+x/gg3/8bpqQsfMN1HKBbTN6FolakYnSFFYF46AzLYA/\n6ulxRDmp8F/qpIrvpkLVDXtD4L4L59g56DAYkhrEqFYbsinkOWfFUpDD0sGYiHMOCOikgVAyqytb\nfxnfh7cqpW6R25b7ge8rN9gXjO8DUIxNi2S2uvJmzadblweFlc5eGUwcDQyCJSztBJDgUHoPCsHI\nm5iKZLgWE1UfmU0aqWmJqxtvHIv6EMh1syoFtBb58aOCKt6LpJuztmQ1ubABKaQmmM0brpkeY2Fa\nDrqWmMBmi8bwsx++tBcwrn/0ilfS9z05Z+7Pp6W3UDdsHzuO8ZGrTlxNU02oXIWtDNppdpb77Ozt\n0swa+l4IVTkj9OkIWWV2+5522bG4uMdy94CX3/pl3HzTc5gnzf133MknbvtT1lPCDC211jQTyzwb\nDrqW5WJJHDz1vKHrD6ByrF//DIbpOidP3cBrn3szdUzc/fa3UcUef2aHd/3pn/FlL30JL/m6v8ld\n77mdMw89QmMc0/Xj5OECWskY1OaEUeJsm0s/RxWH8NGLYdSfGKcGDoGoR2VR9YTT+wc8vr/HZG1T\nPCEXwpJMKROTENoiwjnJxkr2CSQMkQGHQ6mAzRbn/v/xffiez/JvPq99H45qDFhXka2MlEYdwNGa\nXjZ1tXrYcyFFrdAG4xP9JCCmMTvIHDYcU+HlJ3XYc8hRypI01iKlHEhB1I5ziCz2D2SXqA+JTilJ\nE0vngguYzQAJeJOmWeHwx2MT8JKgCsf3z1mRg0xKLvhdnjHbYtbMmE97fuz9f/yEY3rDq14lgiJV\nRdu27Az7nDt/jmPbWzx962oaV3HukccwPnLt8atYm87oY2Dj2CbZKHCaMw+epaoqUglIyliZ0AwB\nXTl2uwX9kDi/d5G2a/mb3/Aabjx5ksWZc9zxznexfPBBNnJG+46EJxlFxJPDgB4yJmZmlaMPHUFn\nlv2S3RRYDz0XuwVVZfmSr/oy3vGf/wNPdwbtE+c+9kn+8Ox5XnLrl/Hqb/4m3nf7HXzwtvcyc4aN\n/YBTNSkpGm2pfKbSUv65DBgjyFRr5WEugLCkEEh219FsbND1kdn6Bh+59y4+tneB9fWLXH3sJBvG\nEYMXHowzAoBSMISBVNWiTKUdikyKSI/DGBKe/Dl0Cp5CND7JGpWAnbaSxpfxoNZ6FeEF+PPpLb8/\nE0YBDrvQSR1mB/no/0uS9meKvHkWqKQu8aDYHQrQJqtLGlkjNHlckrYeirMC3PnQ49z6zOvlO5RM\naGwSeu/RUa9QcskH6ZGkQEiRf377711yLG984atoh57JbApXrzO7dkbbtkwmEzY3M1elxI033EjO\nmYOHL7C3exrrE087fpJpM6HzA7P5nGZrA1/DwXKf3YNdcAanTPnuihShsTUX9/fpw8Bj586w7Ae+\n5XXfzNpkyu7td3Hnbbeh2yUbzuCXexijyMbQpiBYBhOJNhB1IuqBrDU6Cffj9KP3sXFyg0lT0Zzs\nOfvQJznIPUtVoRlY39nj/N4O90wa1AtfyDVPP0W41fChD3yQa088jbZfkr3HGotNiiqLJqMFwqi/\nEJMEdkZlKJGNnzlL0uBmM1Iz4WLfM1nfRFcVu/sHmPmUrfk6w3IpOqLdgCv3hi8gLXKZxIyI05SI\nURNDf8X3/FNB4UmW95FgAqpyKwQiHJYCOY+w2Cf+W6XG7jifNjCM2YPhEOMwvo+UDGXerKQ/aArq\nb/WaAoXMyGhr/H4JkW8HVpqLKUr9OYqGjGukT8cYMVYf9hSyxscoPQUNv3nXh55wfN95/XM5dfIa\nrt4+wfD/sfemsbZk133fb+2hqs650xv69UCyOUgiaYoSTVm26ES2bNlS5MiGx8AIkiBC4hj+lNhw\ngkCKgSCBYSAxMn1KgMQJIMBJnMROIkOWYmuybFkyRcoUZY5ikz3369dvvPeeqar23isf1q5zz33q\n4bVEud+T7gIOznzOrnOqdq291n+41HO6WJDGxPLWPcrxkuVySV8dpdM42lk/ZWKfOWxaXIQ2J2Ts\nWaYNs8cPSHOhUHjhpRehSqxPZRbNmIr1asFiveKF6y8yb1v+wp/512hz4TM/89P0P/cFDqKgkhjW\nS3ww1yVN0LmGPgUyMLpC0YSK0GBwXUW49YXP8vzpCeWVV3nZeT7/zz9DFxz9uGE/OjrvkLFw57nn\n+bmXX+XpD36Yb/vE7+Ebv/GD/JP/90dZ5kQIEZeVRgqxghQEkHSWMW7bkVoMVYoVg/tcODja57WT\nU0Y8vu3MFLAUXrl3l8Wm5/HDA8Zc8M6hORlfRDHmaq70e+dwvuDN6G/rNvYgcTEpPECklKCpB5ie\npeTGBVBbNrwOtnyaCLaTg56fFbYio9Y1rG/auXLT8yYLn6YW3HbiONMgoC41DC1wBmKZXjMd/CVb\nQfE7v+l9/JNnnj8zUamtxymz+dF//iuv+1v8qY/+TrTKig0eXrxxnfViyVNXr3Ht8hVWqxUNI6t7\nC662cxgUyYEyKH6ErpkxvzojrzaV0xBY9Bu6g479K0esJHHzlZe5eecm6gOdWPVc8WgxbsD1u/c4\nPr7LN3/DN/J7v/Vb6L/2PL/yC5/k5OXrPH3wGCcnd/CdI2EalSEHYjG15A1CdmbikrTQuMBMHG3B\nfDPzyPDM1/jVX32etcLolYPWUfrBQFgzs6+T1YaiA7e+8jV+/NkX+Nh3fAd/9i/9RT79qU/ymU/+\nAunesTFIRRExte7oTdtCnDOQ2i6ZzTtURooTZpcu8ezXniGLZ0gJzRCKsCKj6yWUxH4MPHbpiGGz\nBApJPaX4bSHTe8FlRwmFUjxyf3/0TeJiUnirCJ5VzswD5jys4JKiY0+sduQZJWGYf0Rx0w6miegD\nLmdCgSYEUqlUYbEes6rVCTzVTHZ30tlONDYZBT2T1bIzeiChOArJQRLIThnLSKbBdS1lGPEi7HV7\npPVAaCNa2E5iKQguCGTlp7/w5V+z+X/8499Cqbj54D1ZBoorZBfJXlm5kdVwj+NbK546vMITV65w\nWQ9I7aEVaSsZ6ZRTRIR2PiclgThDJXN3WJIDXLt8yKWjA24d3+aLN54jeEcLuDygJdOjSIjcXR1z\n97WbfOLDH+F3PvU0X/x7P8Xdl19ANBFkw2m/hOgNTlyEIJG+JOgaVlpYUVj2PamMBDxt8fic6ZoO\nxsyljccFz6iJeU6Ao2yERCTEyKJcZlPucXDgmEdhefwy89xw62d/jr/3hV/mO7/3X+Fb/vy/xz/4\nxz/PKy9d57WTFU+MwtGYWc9uEEXRcYNIYfTmJyrZsR/ndOku88dm3IuJZ1a3GfZaShBGGTgZRvr2\ngN7DCZk4bBjTnKvtAWWxop1nhs0aiQ0xNmg2f8k+C67hbQkvXkws5IeTAAAgAElEQVQKbxEiYoWh\nnAn1vniHD+agNGY1E46axk/vmQ7uKapt4bnPFZWzzkK9pl475NeAXXbpsLKzXEBsQjmTJTM5Ll97\n+Vlhq46UM4iSeqtkf/qZl859x5/6+MeQVEiNVIt7NeJO7UpM4KjNWDshTcD1pi798q1XuX3nFpfb\nQ5566ilGEjG00DjiXmuw8dwTJZDyQNFET+a97/8Al959jS9+9cs89/KLxC7iqzPSUgfW/Yb9gyNe\nfukFUkp83yf+Jcqdu/yjv/djxPUa6QdCFBrfbd2rDQRklvGhibZuL+bhOQHEJsu8XdSnilHLU82s\nRi22Vsc6BcthTS+QirBKwt58n6Mw42S5YbjZ85N/++/w/o99jE985Ju5+l3fTczKz//Yj3Pr2efR\nPrOnHsQo8IwbvJjNvY4DTdtwdPkSX757mxCN4GSKVsZ7Kak6ZWkml8zzr7wElx7jUtMyrDe2r+ZC\nSmuadkY2axxwjlVaPfA+fzEpvEXM53P61ZrNZsO1w0sM63XtPpgBqMdv6cZTsa6ICYSqFrxaejFx\nAbQimM5qElPf+vz3TjvpbjhX25EVd2DUazVSTBVT1gpumBiX3lWRFDG/SKm3u7blX/7G9/LzX32B\nT3zwvezP92icZ6AQ2wCaaZoqJ1d0a7w76QTO230U65U3TcSlgqRMwbHQDS/cecV+v7zk4OCAOJvR\n1dbnYTPjq1/9Klcef4wPvf89nIwrvvLKc7x89wa5cxyMJnm2zIkkIy54vvSVZ3j88lV+/3f/YV7+\nqX/I8UuvspeUNhe6YK5TGaUPIGJmtqIBqNZrYyGVslVwEqnemLCVdhNntO+Uk3UDvKMk+70mB63m\n2iGf+AN/gA9/2+8ELXztlz7Nl372H3PtoOHScsl6MXDzs7/CjV/9KrOrVzm6dpXv/tPfzyc/+U95\n9md/llxsydSPgy0LxFyqO4T5wR5Hjz9GWm8o3pO1MA7V5alA1kwikfNIKjZxPX/zButLV3j3pUPI\nhTHnLakta0FTrV/4yIPGxaTwFrE/mxNxrJanRl7y3nT7nDCmZF0JhFGrt4GX7QSQKw9SZNJhub+m\ncHbGN7qybrEFu0XKbdTqNXVSEO+2PAepqcaWoZns4PWxqXbsiouRPBpAKQ8jly9d4t/4Q7+fV5sb\naMokD23bkoBQrOIvIobYzZkYmjOV4JLMuCQI45jw3sRLCWZUK84xm81sYmkdEk1SrUhhVdb8jm//\nKEXg+vIWGzIv3L5ODg7fdaxvJVZDYpF61EEnnk/8jm/lw+96H5/6+/+Q5pXnuexbXMk4VUqagDuO\nTVaUYnZxAM4z9AmJ1eW5aiQ6mTw1DeeRUyEEs4cV8XipdPhKJJqyxXhlH3n8Cndnc977nvfxvd/8\nUU7v3OGFX/x5PtS0zLLic8+4KIz9hut3b/FzvvCRb/8415Ljsz/7j2jEm8hrEoIaOvGwnXP58csc\n55HrixN6wEkDjGQ1v8igioqD6l+ZS2ZZCq8sTwjAwf4+nW+hKClVJ3BVnGbS25B4v5gU3iI2mw1d\n25LGnuPjY65dusw6ZyQGhn7DHg3qZCuiOQmYBlfdmbXgsKWD1gNdJoOVvLNu0AqTnoBLAknOm3xY\n/YHtBGBgCJOEdyKQE2N1GXLG47OaghfGoaeLDUkNz9CvNxzrPaIPfMuHfgcni1Oef+lFmhjJpTDv\n9nHYMsQETTKaC76qBw/DhugbvI+IQBOcmduIw3eNFTWDkIJSdLCCX116pFK4tzlFo+fW4phbJ/fQ\nJjAMPeRkbtCpx3vPR973DXzo2pO88tkv8Suf/DGuEOidgGQ0CEVN0WpQo48jgTKMuGiTrGpGmsB6\nM1KcwYpLzrSzFq9CGwNaki0lnEOz2nIjJco4blWuS1HSMNKvTrh3fExcLDlYLpm3gY9867fw+Z/9\nSW64xDw0xFQ46iI4ZdX3PPMLv8jNF17kj37X9/H58PN0MTAsB0QhBk/nItcuXyI3c56/d5dXhzWl\njWifacWjQRkk4bItKr3ztSVldOke4bXFgtMx8e5rT+DLaC3W2uQuKZMuagpfvxiGwZRs6hkZZzWG\n48Up8/nc5L+wduK401YsWHaQRInicOK37s2TTFq8PxO4j8nWuGmisftyH6IyJ1Nm6imUbAYyEbOt\n3116uKK0IZKHkej8dnIpw8jLzz7P9edf5EMf+hDf8a0f59bdO9y+c6eiFz1d1zH2/dbyfGpZlpLM\n+qwuYVRscohVAGTCQsQYz9qi9XqjUPo1N2/cYTEMLNdrQmjIQ+bVV1/lyuNP8j1/4LtpUuHlz3+J\nz37q83TLnsMEPg8MM8+YCs75CtxymGuiw2eTQytqB3pRRy5WCM6w1a2QetAEcQzJlkr9OKBSsymg\njc2WfWmFYMft6zd47rP/jOA9/u4djt71FL/wUz+NS3CvmM7mgXf0aUMojnnT8GSInLxwnR/5f/4P\nvu0jH+LLv/zP8EEITgghcjg/YD7fZ3lwhWef/RL3UNZ4cwMnGejKGe9FVAzyXF3Gp5PN0gcW6zXp\n5i3e/+SThJzYLJdG20bh64lo/O0eYz9Y2l7T0VW/Yda2FJmxWq/ZZ/66ZEilrkkrOrEISPBIKmcF\nyfveeH8NIU+GMjVbcP78H9vVQpiIs3adE1N7EjFhlWn9TBWkrfqBpRQ2mw34SMAIVs9+/ku8/Myz\nvOcD7+MT3/pxbpwuuHH9VRaLFQfzvS0d1xCP0HYNrbQUTYz9QCm9pbmNkLJNHl6UPJqqkJeAqPk8\nZE3cOTllselZ9xvyWHj15g2uXb7Cn/6eP8581vDFT/4SJ8+9xFXfsLfpceOIRk+vCZ/NF7KUsgV2\nbHkgaqpFZTTz21ILh0XMYStJofO+qjPLVsoeJ4xDqjoNeuaXUBI6sUBd4KAfOP7C5/nKnVvcu3aN\nTz73EnGx4V3zq6w14zXgomdMic16wZ47IPUDl2dzbg+nvPLiVznYb7l3ekLXNcwPj5g3B4gLtI89\nyY0vfY5119FvMg2FUArBDQiZUuSsjVml8KbuVR8dMQRur5eML77Ie65c5urREcN6zbBZ4fXrrKfw\n2z1SSgRvuPsxJxoa2tbchGRTOQs7x3OpUALnrWI8JtPTC87j9ayWcD+a6X4otHPn7dvuj4CzIlhd\nRQfnyMFqEoO6ejZhu/N4OfNE8CFQstm7R7WmaFDhxnMv8uyXv8J7P/atfPSjH2W1WvHic8+bMChT\nT/2Mbi2qxLbDpWQ2ecOAuhYfAi4LeZOQAOrKVkT23rBgUyXELh1e4fHL13j6O9/N4vY9Pv0z/5Sw\nvEfTjxxsEgczIQ0bUoRjGdE9Yf+0gWwIT8ngROtiCYo4y+7kDGmaxoI6x1iNYXzToCnjEdbrNYeH\n+6z7DS4EpMgWLEUyVmhRJahQxPNEt8fIQFjcIy+PuTIUojaU057HLj9GSQNBIDGQo2MjA37esBl7\nYihoWrM6vcf+wR73hpFUCsM4sv/kIXvf9BHSJ3+OXjdIcISUaEkkByFkShAk+zPRHa0TvxPWaszL\npm3ZjInrt2+Thg1XDw5p5zNztXrAuJgU3iKkmsomBdVMdI7las3BbMaVo6ssNq9xFOekxSmzGClk\nskAOnsvLhtPguNsp9yg8kYWr2dHgGYOgukaIaKkCqA6KJJARJNGWGcULqVgr0Ytg5udWzFyG0boJ\nWvBlpE2eUBxehWMxWHJGSE6YoFKSTOzTjaMJvGgyPn4V+nTB07rA7c99iV/82vNcunaVx556giee\nfjfrceClG9dZrdcc94VQ4FK7T0RonOA0Ma42PP9Y3PojNiHgFTaLEyQnjvYOePLKk1zZPySMhTvX\nb7D64q/y2X/yKVwq7A8jh2LLj3avZVkGpDVpuJA9QQJDWdPGttYGGpbLJV3XkXJmOW6Yz+cslkvi\nrDWjXacMFNTDTCMxQ+MapBQu7R2xOl0QQ6BrG5br0TQmVClV7h41JyYfPGVccdi05FVm7Hva2Yys\nK9rDBjim8Z6h72mbhr39IxbHJ8z3AiWPHF0+wN+FPneMQ+Zp33BFO5bvfR/Lj32E5fs/wnj4FM2d\nGyzTMcv9hnVy+NxxOAprWVDcmdWfMsHrhSvFo1oYnNI3sHbCyXrFK8sN3/CupzkI49vY5/X1kt9/\nsfGw6SnsRhsbq0A7AQrzWUvEEbADae4C42bNnm8MhwuomH38/tDSR2EZFCVzOQlHg9CKoNET0xon\njZGNCoZ3lgE7DRZCaRhLtu92BnUNKtuq+TpY79yWEEa79WJyXmNx5tiEkpy1SRGHl2CGKy4jueCS\nFSpDbbnhHC54mqQmQ163fSiZVb/h6Mplnn76aY6+6f0cHB0h3nwa+2Fg1Zsc+6WTQtME5t2MWQwc\n7h+wPD7mtVeuc/vWayxfvU7JmXloCElhSFZQGw3spZgL9uSGPeEIpi5N5+PW7zLnTNd1bDbWp2+a\njs3QI96z7NcMoqyzIQULytyZX8fMOROdrcK3SmbMmRC6rSnu9H0Ti9TGc1b0nXcdm9Watm0ppVjl\nHzt5eOdIfc9sNkMoNE3D2vccnAaWJRH3A1fwPDa/xvChj5A/9mHKt38P/9+P/x1+4h/8bbomUdLa\nfDGLQ4tHGbeEtV1vzmk84h05OMNajCNzMV2NtghH84ZPv/baL6nq736rff4iU3iLSCnhJVCT06qW\n47YtxLg/xznHerOmw+NEETzkxIbMWIVRNGd6FVbOUZzDi9LImTKO4eOnxNWS4W1xU8SANcjWOQrF\nSFBqPgHOu63cOKrMFLLCRsFrMYi0KF6qHVy07KF+E42rKktF0TET1dMvVlsp9VkMHM4OKcuRlz73\nZW5+4SvEeQezhg2ZsDejPdiD4DlaGN7hdL3h9O4dFveOOeg62qah36zphp7GB2IwNeiURqIzEk/Q\nTAp+y8+YJoetiazIloI9sTsnT8lJz5KiJLU+fhITxVVjCBGdx5diwjDeMfSjeVqWM2+Laam21T3Y\nwTY4Z34e0fstfsOpKUFNQrnenRVVJ2Ud+23X5BRN5NYLjW+ZHRzhD69wEvY5TsLR1SfYn8+Q/ial\n9CTxJInkoPg8FXmtTnPOtKg6dJFte6MPxqr1DgmeO5sLQtTXLYoWyBmpjUVzTbain4uRxXLFpaND\nMzwRaErFIhZhDEboaTDewqiFjbcJoHWA+ApGKiDVpXjbpTTTjxCscJhrFXw3XJ0QMPwSrtKtNdvE\nBXbWKnpGoioTWSYXvNoOEJxNDlR14SElxgjFmy7DMA7E7CnjYHToUriyGEgna7KDg/mM8bVTkig4\n4bVgMukuZaI49saRvdjQloxoMbJWyZQhk71HPIzZ2n/rPMDotmfoxWJB2xoachgGOyPHpkrIW6HR\nBWvNKVop1o51v0aDicSY7YFlUZEq/y4G7DrzeTOvhy0tvqboImemPibdbvSl6AN93zNvuy2c26kB\nUsQ7yMWWNCnRBm+dnzkEDyGYO3fwnma+xzjbZy2Bm4uBV++egouUUglwWqonRcFvzQDYTlCqsjWg\nmTg0mjOpH3DOgwtsxpG+3L/3vHE8cElSRLyIfEZEfrTevyIiPyEiX6nXl3de+0Mi8oyIfFlEvu+B\nR/MQhjCZrJ7pHk7S3FLhxOtNz97REbGbscEKaCKese5kISttrf4ODlaaTL0XqyUgBY/Bcj3WdnK5\ndiNqG9PVOsIk4e7F2mm+2E4exW2XFq0P5ncQILYNrvVIqIYnVSpHctm25XzVV3Rq/IZ509I7pQRH\nL8arGD30UuhLYhTlpFXWLaQAQx7RYSBsRto+05celWzGtK7QRVsSLPtTkvYkMuphINHrSK8jQ1TW\nLtGH83Tv2Wx2LktommbL6jS8hMG1pzbooJlRCwTPOo9skmUZXqHBkdOAUKwVOWyqIa1N9rN5e651\nOrVfJ3h535vkWxOsxtFVSfvgPHlMVmOItfXrw1bmbpJ4d1lonGcWI02A+f6M0DZI17Fxjv3LV9m/\n+gRrnaHza6RwyFgibTuj8WE7jt3ryeNz2j+jM5+MrhryppIheGL75mbHu/F2pIT+IvDFnfs/CPyU\nqn4Q+Kl6Hznv+/BHgP9e5G2oRj6EsS3s6JnF+vS4w7PZDBA8h9euos4z1MJWqqCkmKGpp+qxPldU\na/ZRz+hGisYjBDXw0ZTGOq3oO87Qjw4x2TWg80bVDWLpsSt2u1FHQE00Vcy9qVGttmRTXyJDyYha\nF1/EHI1DLWN4B85bncQcohNJE6+0mddmcLODV/3IrVi418BJK2zSyJATpTLzQnRbN6mEUrxnUCM4\nuaZFYmPZDIaInGLa1rGCiHI2mbGxZNQZ7Xi2v8d66Ildy5CtUt9rZl2SAZUwN+9WPHMJBKwmIdik\n6MWWVc5ZCj5lCn3f03UdwLam0FYR2pTS9iCdWLNarG4wDANttOuJSDYOJnZC9sxCS/SB4IVu1hDn\nHRsp5MazWi/4xo9+jKOnv5mhezd9eJLZ0dOMy0xTjHAXfPO6F+89wdmlEW/Ls1hbt29TMOyBXi4i\n7wH+KPA3dh7+E8AP19s/DPzJncf/lqr2qvosMPk+PJIxnTmmgs5kjDKtNbtgNl0nJycsV2ueev97\nGYsi9QzhFJp8pr83qtmolVJIW1BSFSQV3U4MxoPfASDVs6WvWYKI2ZVHzCIuTG5S9ew/zzArMM+O\neYF99ewVmGVhls/WzVCnht2CsxP21DMvjk4dMzydOstGMDn7ZgA/KDLaxFicZwCWKZmISCmUpEgq\nBPW1FuJqIdTj1RMl4rPgsxDV2+3hjPY9uVZPdYSmaTg9PT33nwzDsC0ChhBYk1nlkU1JaHC4GOxA\nUUdThDY2BG/isz64s6zDm4zalA1OxcupljC5O8UYTU07523HZpcSv1Xixhyv82iyaRTFacQREVWa\nEAmNRxpYlzXX777G7Tuvcm/Z831/5gf40//Of8S3fdefYD22XLn0OH7M2/3xfp/I6fHdi0MIrtrI\nxWCuVg8YD1pT+O+A/xg42HnsiR3h1leBJ+rtR9734f6Y/nhVYGIaVhZbGQtxFlEnnCxOAeXKY49x\n9+Yte3NRE9vc+byk1k4qWnDO1Ju985bS14nAWqECpRgNuzIhdyM4qzeUXEzoNGUoBmZqMoC5QrsK\nvVJ1lGI77rqxItgkIYdMug421rYYLqOIVe0nG7ipNnE1+aoHqPR9MrVp7wxXKA5XxNqlxSHRINxe\nwcWIz7Y9QQLDpq/AIL/VadBYn68QY1UzqfXe2/LBGzjIe8/pYsHBwQHL5ZL5fM4wbhhKYsSIR5Mf\np9c6mUW/PZgbX1vIQ8bHqqAd47b7sFtfSMkO7uVmzeHevhU7a+Y2aS7mMRngKdl117WsFktmc6uJ\nxLY1307naNpI05joaka5dfc2Ly++QHfpCX7Pd/5hKMI3vf8DHPnCZ37i/+LK3iHX18Z03J0YpiJo\nyucnpm33JHhcEWby9VVz/mPAa6r6SyLyB1/vNaqqb7etKI+A7wMYKtFztlQoKvQZXLHCUzdTnEvV\n8QdOT09xh4dcfc9TnFy/xbjZcBw3RBFaKbikZOlYusAthT0nHCC0GYJWEpT3ZC/MpMWRjK+QgWLP\n+1o7WKXEfjeDMeOTI2dh0GxqRS6Z6IpYipw0QzCwU0aZpWKWbl6rFH2pywtXacVGtppAQWixNmz9\nXU7bcobINMUQe40zCLECozgISvHWSg3i8IZKppRMzmpdF2/LJ4JhAVBMwKZmAyLGFxlqi7IMmVYi\nkpR2dsBqM5CbyO1hw7KAFs/MR2KCqIn9xqM6ELuGYbCOgQRPX5eB8zinjJbRbNKa/f19lsslbYw4\ncdv6QRoTM2/SdEGM8LVarXA1uxhcIgaDSTvxrJanzJuWqAaoavZnSO8RiTiZ4d0eXj1uTISSkPEu\nl1yi3PynpHCVfOkb+H3f/2/ywnPPcP0rnyJ0xcQcS/WUVKtKIYVNM6cka4VKMZPaUhI61gndPfjh\n+SDTx3cCf1xEvh/ogEMR+ZvADaky7yLyFPBaff0j7/uwG7tkpOmya8s+UYlBiN7aeqenp3jveeyJ\nx7l75zbD4qRSeXfqAQprTcRiuPYsdaKpbSxRQ+E5Z3UBw7jXs7A4BKEtGa8ZI/IVxKmZ2Lp6UE8p\nowNf7Kw/8TRwvp5SytYFqmiuNnZC9sbFdrXyIXr+L5Ki2+VNqOxJLZbp9GVEqsS5U2rnRCYo57lW\n7JQJnPvsmpEJVZ1oB6dgsGSTaCsOhpLoNbMZMwMFh8dHj8e8MWahI40D+21n3RPfWJen/jYhBMZx\nZNa0nJ6esndwiZOTk22BcxiGbfawt7dHqJyPGCOr9ZpYW6IxWqsxj4kmBDOQ9WG7nYZlSIQwx7ct\n7WxmdZKq+dC2HboR9ucHqCqrxZJSbvHk0Zx3PfUYd19wpBJR56DY4pKilJKgJKL3ppshJmdXdFID\nE7JUTYYHjLesKajqD6nqe1T1/VgB8adV9d/C/B1+oL7sB4Afqbf/LvCvi0grIh/gEfd92J0MpssE\nHNntX08FsVgdko6Pj7m3WXB07Squ69iMRmBxEmql3wqOGymsUXpVUv0+ypl/ZJDaGcBaVKrm5DyW\nzLyJeLXOhS8ZjxIFAmaA6mvR0KM40VpstItXCAV8UnwqNCqmwVBrJ0OxCaLstsBqlhKL0BYhqtCq\ns+titzt12wIXdemRinUEiurWVzJpsZ3Wuy3FfLoA2wMyhLCtso9V5xFn5jijKMsy0lNY55Ekii/F\nqvtOiNjkNaXTwPbzpv9s+i/7NIJ39cC1VmVKg5G9NOMc5Dxu8RETZFtVt3oMuRYWVc1Kb3++V5cV\no4HgHDRtoO0iMUZi24J4QtOwt3/IrDnAu4bgrBA5rE658fILrBd3kLLeFhK32+CrLVzwtXhs2auP\nweoIXUOctYS2oZl1D7zP/0ZwCv8F8H+KyJ8Dngf+bP1Bfkv5Ptwfu9kCnJ3tnDiaxtaOgu18m7rT\nfOBD38Td125x9+YtmnrudZrJQRlxbNCaXtsZzlMqCcvW1F6Z1AHIFBPPUOVynFnRU402bGtbVzvv\ntXNBTfkrT4DqnSB1Rx6F7YGfOZOGG7SgWVFXW53itmrWAriCeVCKoLUIZsaojqYJtm4vxXQa6ucn\ncQSBprZ0UxVtmUxpppgm3KmaH6sD9mxm2zsUo6dP7cdcaeYxeHwaacWWLwHFqdLEBgfEZsakaK2Y\n8e0E7R5zYrY3Z7lYc3BwwGq12hYcp8lotVpBE7cTVGwbVpv1th242Ww42NsjDSN7nWUaYzIVqPl8\nTs4n1h3yvqJkTagnIUiI7B8c0rZ7xNiSF4m7x3f46j//FM9//lc48EpRZ2S3Yn6iBmwD5wzzIGkk\nYScNvEOseo1UN/EHjbfVrFDVf6iqf6zevq2qf1hVP6iq36Oqd3Ze99dU9RtV9cOq+uNv/IkPf+ya\ntE6Fpwm5NsVUCZ9651MRyAfLHl6+8RrNfJ/DK4+RsTNoCDbT9zkxZFt/Jx8YxZYSEv0WEScYJXnq\nehSA4BlrkW7CUUyGLqUUnOjZBaUMPV4LM+8pQ08s5n/YZOjwNDi6ELeFtd3PArYT0W6qP92feA4h\n1HNMLsbnVyuGhjqhmAktFVBkB2bTttv702NFAG/O1+rEPBVr5rIZB3rOWo6bNNqEERpaPHsx0qgS\nycwagzR30abi6C293/W3CI2xRmPbshkGYuMZxg3ilG7WoGRCdIhTmtbaomO1gp9+qwl12TWNcTSq\nkU7qB5p6Vl8tljgPMXpElL29ORlFcaSs9DmTacBFfDtHvefpp9/HrZt3bcmj7pynZ9d1iPfbbKuN\ncZulSvCkYgAmGTLSJ2b5DP/xlvv8r+tI+W0UUxuqaZot5BcmJ+Z0DoO++6d572HMdDGwWffcOTnl\n2pPv4an3vY/ihb6kLe4gIfRFGEQYnGMUZV3GswpzLltWH0CiQPSoeCbjLlWTfy84EGPSTRev0IVI\n4zykzMxHpCIaOxeY1UkhUJcqrgKZsNbdlmeghSS27MkOBgpDyYzTxSxXaIoRt1rxNM565sF7pOi2\ndz+BjaZW3/Sb5myZRUItA6jXWTD8Q8kMJZtTM3ZARu8Nh4Bnv43kccNe2yI50zVmoNKESB7Stk6h\n2aDCy+WS2Lb048CQRkLwjONAjIGURkAJwTMMPTHWAmVd/izWK1wMrIee0DbMZjN8nYTSMG6RhsF5\nmhDougYfDIDlG8t+1Af6kjheLJG2pT28RGjn+GYfF+d8+3d8J8MIhfYcmG3aN8UZN2XCWExLra5p\nq1K1Z99F3jWbP/g+/3U4bn5LxxtNChNe4fViwgAczjrSpjdRjAJf+NWvMDs64omn322ybVoQ8aSi\nbFJiU4p5D3q2aMipvjB9bqG2NL2jqCPhGDIkHLW6AFK1Ces0IRSa6AleII3MYtgiGFtvLMZG7Iwe\nJvRmwTAFdZJIxQ7CcUuywsZQUY+Ds8eyF3xWq1cUm1iCiqkyAaid9V0M5nNQD7BcNSdKXQpMl+yg\nL8b43NS6wbRkmNbUUTwzPHP1tN6ZTFvJW2Pf6APkqpEgluU1TVOhwG47ubvgGYZh24Kc/sepA7JL\nlJoyqem+94ZqnJY6zjnSMG6XDlIRqDEGI5rVrEhEGFJhsdqwyol2vsf84BKPPfkuCDMef+JpZrPL\nrIfavZms5eu+F0IgxIiryMYYI23b0oXIzAUOfcuT8yM+eO0JHjQuJoW3iNcrKsIZyvF+0MjuUmPs\nDd0WYwTxHF2+xOe++AV8iLz3A+8H2L4+a2EsuuUPaHDnCDpBzPdxuzxwjoyQk1IKmBW7iauU+rfu\n1ptjTeM1F9N1cG6LkqTotte+BUmpcSKaKqGmakXH6TLkxKDZyEbO1q6lprJaOxGoCchuPRQrMrOp\nabaqbkVfdg+2KTOYMoY+p+394kwQBW9wy+AMVBXF0eJYHJ9w5egSwzAw70zQta0oxOiD+VLUWoX3\npiy12qyNRFQPaLOqK7StsR4nYNRms9kWF1V1i7KcDvLNZqJ6+XYAABZiSURBVGP1hloHaZpmC4Ca\nmJi+OkJPE4fK2fLz5u1bPP/yS4S2o2lnzPf2me8d0nT7HOxf3i4RvThcCKaRucPNmEKKFauj81w+\nOOTpJ57i0qx94H3+ghD1FrG7bpx2hgkFZ/qNkdY522FTsg6B90QnpDD9ERlPYtws2J97Xnj1OZqm\n4b3f8CFu3LzBYr1gs9mYqOgYaEJLzLAJiXmxs9tQlNEbDmE/dui9NetGzHcRU5GOYil7KIr4maWv\nzjOmniFVWG8MpJLp1OCvSUdcBNVEVAg1Kxld5U8Wq2nMum5rk1cwvUKyYQx2J8ICOF9LnWqXUFuo\nqh7JyjhszLtSxPABYgdVybXW4CvVm+lMrSCOop7gAzPnzIGp8jw8ig4m5nK0d0TaJObN3EhFMXDS\nr/CN5yRvKHstizJSpBjhaDAna4Dcj9uJQZ2w6jcgwlASi81AO2tZjwb3CMWUr1oXjPhVBG1nxuj0\nnmHY0OKYzxqcjsxipBsP6Ls92r19OjU36lsH8FpaMm/mPOUK1597hhsf/ibEz2l0w7Urwqin9AzM\nqkhwlgmebrkgeFY+4VBmObOflce7jqO9lqMYmGmP6IWa829aTEi7qTU51jQziKXi22xhx1PALlSM\nvTMugSq3bt3k2rVrxNPInZu3SJo4SdX1uQiHzm0P1Mn1KYqnCw3juCZmQzMWlFxGxBl1G3GgJt2V\np7pERSxONF4Rj5YzDMZ2++rNaVuU6Uxmh6iBuMB7+w2kThy2refRdtNnGUux6swK1k5Uwy5IVZcq\nWowRqEq6vyYmlhlILUB6nCFBBcaxJzQtOCV2LWm1ZO9gn8ViQRNMrl3FpNhijJRUSCnXtiLkrMRo\nZ/Su63Bq/ynRM4yjZWwOigqLzRo0Mpt1pLFnSIluFlHAxVDxFDtmPXXpNWUcwDaD8GLFYFWhH0bG\naG3k4BzRe44XCwh7aN9XD4u89Z84S/DtNxGsrhSk0DphhgnghDyCZrQkfHMxKfymxW7FfUrnpsdz\nbRwWPcMZwHkptcmMRdUKeNevX+exJ59gPp9z89UbrI8XQGHetXRFGcQ0EsYCaVICKmqFJK1rfDGM\ng4hV6rWYI1XFKZu6NCbVLpV/4cUgy1rOrOWmXa2Apf1ybsMRPXPTDt4bVLsUSpmWVfU99YOmqUao\nAqPUiSl4RlW0Tgy2vq6QUISyI0c+YQx8JS1FL4RsEu1CoY0NOY+0jV37EOmHkRAbxlxsgqzbPZTC\nkIxLgROGZJlBKnmbQeXaauzHkXY2YzX0jCiuOkXPNGzbqPOmIadM05gCNkDJoy31vKeJzbbe4Jyj\n6ew+uaCu4EKkKGxSZlAHQ2KgZ9613L6zAikM/cbwJj7QeDUUKEouEyR94sQEGgczCgcOYhqJJMQZ\nr6VsHnz5cFFTeIs4b9PmtsCVCSfvoxV61J2dVXPO1hKqFeHpsvsZriochabh3r17nJwuufL4EzSH\nB/Q+cG9MbJxjLcKqFiD76jehqrTBagTembhKjLGCekCDQyvAJ5dCaOK2Lz+19lLJjCYHfU6sQ1Vp\nqpakcTFM9dlXzsRUHygpI3pWjAzOm3BJOHM2mpB8xokwPABOrDevhaQGGsro9r4BmHYYm05tInDg\nSqaksW63LUv29m2Z1HbRyFFty3oYKWKtvhBbNkNiVFhteryLtM2MNBbms31KhjQWgm8Y+oQPDUMq\n4APHp0v6lBEfWfcDMbY0MZJqrQhnWg55Gnutk0z7yO5Sc9K1dHW5JaXa/mVFY8PpMFLSUNGQa1zJ\n5KHn7mu32J/vVcNg6yw4sWJl03Q0TYv3gQZHW4lrPisxZ8owksaecRzesCj+enGRKfw6Y9oBfHRk\nV7aptWULNVPgfF9/y26rZ2Cp7L6xL3XHCTz+5FPcunWH1emCW+MAviWGYLN3GVkNPUexYblZM/eR\nkUI2aWIjX2frOtSTrgnKloLfzd9FQM9Qfd57vEwUbkNR5pr7u0pCUgzqXFzNlpLZs00ZhlPLOoyO\n7MiUcxNkLlW7smRSVUemDidX16ot5mLKUGrG5cVES0Jl/rmSKzYDTo9PmM8702mcdxyfnHB0dMTJ\nyQnd3pyT9ZIQA2NKhBjtN88J8Y7N0JNLxnlHPw40XcsqW/dBywSIskmgidHajAhdlV9LavR3J4a9\naF2wAq6zmtJu6zCEgPPGnAzOo2Ounp4eiQ51ER0zs3aGjpk0bIh7B+SxZxw2Js2fE84FghjRvuQq\nvuI9rWaanPE5E2rLNZMRVyje04QLNefftLgfHjtUOXMndrbzaq05h9t2CXa7FhO5B+wMJc7RxgBR\nWNw9ZnW85OrVa3SxYz0sOD5dk8eRmffE6MhjIhHJ44B4t+3jOwxqKE4Y01nv36u1MCW4emDbdqRi\nSk9jqQW3Uqz1qebiVIptTyzurK5QlxsFNeJSjVILDhnjbATvyKNNBOLtdzBvRlvKaDauiMjkxr0D\noxZH0WE7FlEzmqF2TaY2o4GyHKGd0I6GPOz29tmM1trb9AP9kHA+khQzBM4w1tbh1IFwzgRRmibQ\na+VtZBPLAUdJShO8ndUpxK6zTEnEZN4ERG2f8NX3Iroz3sME7prahsF5hrp/KA4fZ2RV1qsVl971\nmP2GztM2gX6zwil0TWAYDFshaozUcUgMKVMKNCSCZlzOtfuQGKWQcEQfzybaB4iL5cOvI3YRhBMA\nZwt/5jxpalp+wFnraTqD+CZuU808jMzaOV4Cr75y3eS724h2LaM4NiWxGnukrn3jvKVXAwwlLeZt\nsFPD2K5xa2Ex1XFOabptiGzrI9P73NSmrHZppWY/6mRbrJzW5DpBpHeeK5wJ0Wxt7qnP1UvjQxVN\nteVIdH4rRksuUJctwXm6EAkqtC6YdkUqeDfVGmpbL0/LNKMsrzcbxpRQMRu8zTggIvTDwGK1MsxF\nKYj3uOoE7mNktdmYOI4We78Txn6g8QEdk31/xR9M/IMJ4Ti1Fqf/eZuB1f1kWm7uLiVLMR3NjDKM\nmTKadNtE0845c3x8THAT8cyWDkYMs/+tbVtbxjJC6knDmlzrJkWE7D3aNLjm60id/u0eu+vCSQps\nOsOUUhjHQuMFLYJ4j9QzsBYhO0vHpRS8c7T14NOcTONRvOHTyWgwzHomEfY899a3Cdmz1sTSZWIe\nuayRvSw0xS4i3nANpZgeoQgpOCQIeZ1N3KS2AkOxNb/TqYW4oSTFqaP02bgX3htqbiiUxmjMi+Up\nsW1putaAPbX70quBdHc1HhIZRDhKDTIoTWjRldIW8L5BspCzEL1UYZQe7wVJCeRMlfh0Hrcgo27W\n0g8DosqGhOs8M6qPZ4jcWy04PDzk3mJBjJE7wwlxP7LsN4iTihXIiBQKhXDYUrzjznLJlatXOV2t\nTDEbTI8yOkpONHuR1aYnREfjjZ150AUurxs7U28UL1Y/Sf1A13WsDwrr0VrGLnlCbIGW0c/o944I\nl2YsXSKnkXZ+xHGcc9ocok7RfsGyJA6vvptxnBFdZL/13H31OXxJuDGjbQtigr1SEv1gStIigivC\nmpHRJZSR0Tlm3jFzyr43V7MHjYtJ4W3GtBTYLgm2XYbXz892QU3TcmL7XOUDTEpFUN0ZRFDnSYqp\nMwVBxbNySlOstdlKQVywBoOvSxTOKM5j0K0cGt5AQE7NYEZEOOnsvlQYdHCmME1djz6utmsUJ2jl\naIylKhPJjtHtzrZO4nLPHSmbVoixYgwwyTOjcgitn3D8EGMt3Lrpt3I8taoaBi6QT9fshWo9hyJS\naBRmPsCo7LV7rO6ecnVvj5OTE/YP9uiXPXshkFNmWC2YTZiIAm5U0mbgapyzvnUP54S9YCKsbRPx\ng7VfYyrkJLTem6djiJTFhn5+1mdNKdHGiLrCKIm9tXWKZg7mXmg1ESUQJCHjhpRneAkUzWz6jG8i\nB01HO440SVlr4vLRIcvTu7TtjNPTY1YrU9T2Esmw5VZYkdKfcTiSElPBpYQXR4MQndBgGhnNhev0\nb15MB/ZEiKHkc8XE++Mc5XoHAamq296933lsO4l4z8YpWZ1RjnOx9bxk1ioEKcz9pOko265AqMSX\n5DPJBrBtg02oRYDLK7edFJxCNP/yrbRYmlX9AmcAqQIVsSg479DNcK5OAsacdAXedayMo2EJVHdb\nsvbZ0SvjmHFO8NV5yzm/rcyTILqIDpm9zsRDLAmpqMuSzzwrh5HONaTVwDx05ORIm0LbOVIq+BLw\no633u6ZhtTRx1ZIzjTrIhrIsSQhYKu8woZhWIqE4SoZZbEh5IMlgNRgKsfOMuceMoD3NcmTetDQK\nTfDmECaDmd8WuLOYsyeeeTejaWeshkzaZN51dJmX753wmqyZNcJrt24xe/xxblx/ldPTezSpx48j\nvumsZjFaZuWrLgcITTEnLBkL0ZlPZYMB2hoXabnwkvxNi63YRylbVuD97MEpti0qq0ShWip2vb6g\nVuqdF1NaLmdtLYrinTK5WKp3jJpYABvNVljMxUxoMZCTHZSKL0B7Bs12VUWJSo2eag6ZSoMGcjEc\nwhbXX3EKuZg/46RhWKbsRtl6X7qpcyEOFcepU7Qa2cKZVwFYPUZLgcZX6bKBpm23ywdqNV0UinMM\nHpKe6Sl673E5cFoKEj0p6VYEpZRCn3tkFlmRkcYRY8tyGNDgbZKat/SY/V83m5GzmdzEmYmlaDQI\nuKZsjEaF2LRkB818n9AvKn25SssnrdwKWAVwbcdGlb4JNHsdvVNGEtErg0BZL3ni4JDHj45QaRlU\nCNHx/nc9xXw9Q8cVeXPCsJ7x6stfQxlNNDdUkh2TOxTnVK2zwIiJ6zbiGINnCAHftAxtJHQPruZ8\nMSm8RUyFoV0TjgkLv0sxnjoSaNlCdL3sYNMdCAZYCr7KlYczHsXu9fQ9M1UyhVFBMTNZEPuj+7Ut\nCTARlaBAAUkKCnvqzzAWxQg0zntDQJbMcdeeiYxu57NJIVI5SLUg1r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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4ce01dc610>"
       "<matplotlib.figure.Figure at 0x7facea084ad0>"
      ]
     },
     "metadata": {},
practice/smoothing_ypr.ipynb
New file
@@ -0,0 +1,248 @@
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import imp\n",
    "import cv2\n",
    "\n",
    "utils = imp.load_source('utils', '../code/utils.py')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "video_path = '../data/video/SGT036_2016_07_25_pivothead_AVI.avi'\n",
    "bbox_path = '../data/video/annotations/SGT036_childface.txt'\n",
    "\n",
    "annot_path = '../output/video/output-SGT036_resnet18_cr_epoch_1.txt'\n",
    "output_string = 'SGT036_resnet18_cr_epoch_1_flat_smoothed'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-6.069214 -0.831665  0.53318  ..., -3.836042 -3.868275 -2.377155]\n",
      "(8508,)\n",
      "(53464,)\n"
     ]
    }
   ],
   "source": [
    "fid = open(annot_path)\n",
    "bbox = open(bbox_path)\n",
    "list_frames = []\n",
    "list_y = []\n",
    "list_p = []\n",
    "list_r = []\n",
    "list_x_min = []\n",
    "list_x_max = []\n",
    "list_y_min = []\n",
    "list_y_max = []\n",
    "\n",
    "for line in fid:\n",
    "    line = line.strip('\\n')\n",
    "    line = line.split(' ')\n",
    "    list_frames.append(int(line[0]))\n",
    "    list_y.append(float(line[1]))\n",
    "    list_p.append(float(line[2]))\n",
    "    list_r.append(float(line[3]))\n",
    "    \n",
    "for line in bbox:\n",
    "    line = line.strip('\\n')\n",
    "    line = line.split(' ')\n",
    "    frame = int(line[0])\n",
    "    x_min, y_min, x_max, y_max = int(line[1]), int(line[2]), int(line[3]), int(line[4])\n",
    "    list_x_min.append(x_min)\n",
    "    list_x_max.append(x_max)\n",
    "    list_y_min.append(y_min)\n",
    "    list_y_max.append(y_max)\n",
    "    \n",
    "frames = np.array(list_frames)\n",
    "y = np.array(list_y)\n",
    "p = np.array(list_p)\n",
    "r = np.array(list_r)\n",
    "x_min_arr = np.array(list_x_min)\n",
    "x_max_arr = np.array(list_x_max)\n",
    "y_min_arr = np.array(list_y_min)\n",
    "y_max_arr = np.array(list_y_max)\n",
    "\n",
    "print y\n",
    "print y.shape\n",
    "print x_min_arr.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done\n"
     ]
    }
   ],
   "source": [
    "window_len = 6\n",
    "pad = window_len / 2\n",
    "window = 'flat'\n",
    "\n",
    "s = np.r_[y[window_len-1:0:-1],y,y[-2:-window_len-1:-1]]\n",
    "t = np.r_[p[window_len-1:0:-1],p,p[-2:-window_len-1:-1]]\n",
    "u = np.r_[r[window_len-1:0:-1],r,r[-2:-window_len-1:-1]]\n",
    "\n",
    "xa = np.r_[x_min_arr[window_len-1:0:-1],x_min_arr,x_min_arr[-2:-window_len-1:-1]]\n",
    "xb = np.r_[x_max_arr[window_len-1:0:-1],x_max_arr,x_max_arr[-2:-window_len-1:-1]]\n",
    "ya = np.r_[y_min_arr[window_len-1:0:-1],y_min_arr,y_min_arr[-2:-window_len-1:-1]]\n",
    "yb = np.r_[y_max_arr[window_len-1:0:-1],y_max_arr,y_max_arr[-2:-window_len-1:-1]]\n",
    "\n",
    "if window == 'flat':\n",
    "    w=np.ones(window_len, 'd')\n",
    "else:\n",
    "    w=eval('np.' + window + '(window_len)')\n",
    "\n",
    "y = np.convolve(w / w.sum(), s, mode='valid')[pad:-pad]\n",
    "p = np.convolve(w / w.sum(), t, mode='valid')[pad:-pad]\n",
    "r = np.convolve(w / w.sum(), u, mode='valid')[pad:-pad]\n",
    "x_min_arr = np.convolve(w / w.sum(), xa, mode='valid')[pad:-pad]\n",
    "x_max_arr = np.convolve(w / w.sum(), xb, mode='valid')[pad:-pad]\n",
    "y_min_arr = np.convolve(w / w.sum(), ya, mode='valid')[pad:-pad]\n",
    "y_max_arr = np.convolve(w / w.sum(), yb, mode='valid')[pad:-pad]\n",
    "\n",
    "pose_dict = {}\n",
    "bbox_dict = {}\n",
    "for idx in xrange(len(frames)-1):\n",
    "    pose_dict[frames[idx], 'yaw'] = y[idx]\n",
    "    pose_dict[frames[idx], 'pitch'] = p[idx]\n",
    "    pose_dict[frames[idx], 'roll'] = r[idx]\n",
    "\n",
    "for idx in xrange(len(frames)-1):\n",
    "    bbox_dict[frames[idx], 'x_min'] = x_min_arr[idx]\n",
    "    bbox_dict[frames[idx], 'x_max'] = x_max_arr[idx]\n",
    "    bbox_dict[frames[idx], 'y_min'] = y_min_arr[idx]\n",
    "    bbox_dict[frames[idx], 'y_max'] = y_max_arr[idx]\n",
    "    \n",
    "print 'Done'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done\n"
     ]
    }
   ],
   "source": [
    "video = cv2.VideoCapture(video_path)\n",
    "width = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))   # float\n",
    "height = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT)) # float\n",
    "\n",
    "# Define the codec and create VideoWriter object\n",
    "fourcc = cv2.VideoWriter_fourcc(*'MJPG')\n",
    "out = cv2.VideoWriter('../output/video/output-%s.avi' % output_string, fourcc, 30.0, (width, height))\n",
    "\n",
    "txt_out = open('../output/video/output-%s.txt' % output_string, 'w')\n",
    "\n",
    "for frame_num in xrange(10000):\n",
    "    ret,frame = video.read()\n",
    "    if ret == False:\n",
    "        out.release()\n",
    "        video.release()\n",
    "        bbox_file.close()\n",
    "        txt_out.close()\n",
    "        sys.exit(0)\n",
    "        \n",
    "    if (frame_num, 'x_min') in bbox_dict.keys():\n",
    "        x_min = bbox_dict[frame_num, 'x_min']\n",
    "        x_max = bbox_dict[frame_num, 'x_max']\n",
    "        y_min = bbox_dict[frame_num, 'y_min']\n",
    "        y_max = bbox_dict[frame_num, 'y_max']\n",
    "\n",
    "        yaw_predicted = pose_dict[frame_num, 'yaw']\n",
    "        pitch_predicted = pose_dict[frame_num, 'pitch']\n",
    "        roll_predicted = pose_dict[frame_num, 'roll']\n",
    "\n",
    "        # Print new frame with cube and TODO: axis\n",
    "        txt_out.write(str(frame_num) + ' %f %f %f\\n' % (yaw_predicted, pitch_predicted, roll_predicted))\n",
    "        utils.plot_pose_cube(frame, yaw_predicted, pitch_predicted, roll_predicted, (x_min + x_max) / 2, (y_min + y_max) / 2, size = 200)\n",
    "        out.write(frame)\n",
    "    else:\n",
    "        out.write(frame)\n",
    "        \n",
    "print 'Done'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda root]",
   "language": "python",
   "name": "conda-root-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
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}