clean up 3d face plot

author: adamhrv <adam@ahprojects.com> 2019-01-06 14:29:35 +0100
committer: adamhrv <adam@ahprojects.com> 2019-01-06 14:29:35 +0100
commit: 2efde746810a0264ad2cf09dc9b003bfcd17a4d5 (patch)
tree: 54efdf68339210d931ce130ab07e0369208e392a /megapixels
parent: 374dc54d049766fce225ca84d31fdf51f40f292c (diff)
3 files changed, 232 insertions, 2574 deletions
diff --git a/megapixels/notebooks/face_analysis/3d_face_plot.ipynb b/megapixels/notebooks/face_analysis/3d_face_plot.ipynb
index 537e471b..f136015f 100755..100644
--- a/megapixels/notebooks/face_analysis/3d_face_plot.ipynb
+++ b/megapixels/notebooks/face_analysis/3d_face_plot.ipynb
@@ -11,18 +11,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 88,
    "metadata": {},
    "outputs": [
     {
-     "ename": "ModuleNotFoundError",
-     "evalue": "No module named 'face_alignment'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m-------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mModuleNotFoundError\u001b[0m               Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-1-c83e215f6ccb>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     16\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mrandom\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mrandint\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'/work/megapixels_dev/3rdparty/face-alignment'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 18\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mface_alignment\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     19\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     20\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mmpl_toolkits\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmplot3d\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mAxes3D\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'face_alignment'"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The autoreload extension is already loaded. To reload it, use:\n",
+      "  %reload_ext autoreload\n"
      ]
     }
    ],
@@ -33,6 +30,9 @@
     "from os.path import join\n",
     "import sys\n",
     "import time\n",
+    "from random import randint\n",
+    "import random\n",
+    "\n",
     "import cv2 as cv\n",
     "import numpy as np\n",
     "import imutils\n",
@@ -41,22 +41,24 @@
     "from glob import glob\n",
     "from matplotlib import cbook\n",
     "from matplotlib import cm\n",
-    "from matplotlib.colors import LightSource\n",
-    "from random import randint\n",
-    "sys.path.append('/work/megapixels_dev/3rdparty/face-alignment')\n",
+    "#from matplotlib.colors import LightSource\n",
     "import face_alignment\n",
     "import numpy as np\n",
+    "\n",
     "from mpl_toolkits.mplot3d import Axes3D\n",
     "import matplotlib.pyplot as plt\n",
     "import mpl_toolkits.mplot3d.axes3d as p3\n",
     "from matplotlib import animation\n",
-    "import random\n",
-    "from skimage import io"
+    "\n",
+    "from skimage import io\n",
+    "from tqdm import tqdm_notebook as tqdm\n",
+    "from IPython.display import clear_output\n",
+    "from pathlib import Path"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 89,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -68,151 +70,102 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 90,
    "metadata": {},
    "outputs": [],
    "source": [
     "# init 3d face\n",
     "# Run the 3D face alignment on a test image, without CUDA.\n",
-    "fa = face_alignment.FaceAlignment(face_alignment.LandmarksType._3D, \n",
-    "                                  enable_cuda=True, flip_input=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 54,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "80\n"
-     ]
-    }
-   ],
-   "source": [
-    "data_bodega = '../data_bodega/'\n",
-    "fp = join(data_bodega,'images/msceleb/**/*.jpg')\n",
-    "face_files = glob(fp,recursive=True)\n",
-    "face_files = [f for f in face_files if os.path.basename(f) == '0-FaceId-0.jpg']\n",
-    "print(len(face_files))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 39,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "../data_bodega/images/msceleb/m.0k014/0-FaceId-0.jpg\n"
-     ]
-    }
-   ],
-   "source": [
-    "fp_face = face_files[randint(0,len(face_files)-1)]\n",
-    "im = io.imread(fp_face)"
+    "fa = face_alignment.FaceAlignment(face_alignment.LandmarksType._3D, device='cuda:0', flip_input=True)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "preds = fa.get_landmarks(im)[-1]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 276,
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(31.0, 256.0) (97.0, 293.0) (-101.42858, 71.526764)\n"
-     ]
+     "data": {
+      "text/plain": [
+       "<matplotlib.image.AxesImage at 0x7fa3cc186c50>"
+      ]
+     },
+     "execution_count": 276,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
-    "xmm = (np.min(preds[:,0]),np.max(preds[:,0]))\n",
-    "ymm = (np.min(preds[:,1]),np.max(preds[:,1]))\n",
-    "zmm = (np.min(preds[:,2]),np.max(preds[:,2]))\n",
-    "print(xmm,ymm,zmm)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 44,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# # draw person\n",
-    "# fig = plt.figure(figsize=plt.figaspect(.5))\n",
-    "# ax = fig.add_subplot(1, 2, 1)\n",
-    "# ax.imshow(im)\n",
-    "# ax.plot(preds[0:17,0],preds[0:17,1],marker='o',markersize=6,linestyle='-',color='w',lw=2)\n",
-    "# ax.plot(preds[17:22,0],preds[17:22,1],marker='o',markersize=6,linestyle='-',color='w',lw=2)\n",
-    "# ax.plot(preds[22:27,0],preds[22:27,1],marker='o',markersize=6,linestyle='-',color='w',lw=2)\n",
-    "# ax.plot(preds[27:31,0],preds[27:31,1],marker='o',markersize=6,linestyle='-',color='w',lw=2)\n",
-    "# ax.plot(preds[31:36,0],preds[31:36,1],marker='o',markersize=6,linestyle='-',color='w',lw=2)\n",
-    "# ax.plot(preds[36:42,0],preds[36:42,1],marker='o',markersize=6,linestyle='-',color='w',lw=2)\n",
-    "# ax.plot(preds[42:48,0],preds[42:48,1],marker='o',markersize=6,linestyle='-',color='w',lw=2)\n",
-    "# ax.plot(preds[48:60,0],preds[48:60,1],marker='o',markersize=6,linestyle='-',color='w',lw=2)\n",
-    "# ax.plot(preds[60:68,0],preds[60:68,1],marker='o',markersize=6,linestyle='-',color='w',lw=2) \n",
-    "# ax.axis('off')\n",
-    "# plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "preds_orig = preds.copy()"
+    "fp_im = '/data_store_hdd/datasets/people/vgg_face2/media/original/test/n000009/0012_01.jpg'\n",
+    "im = cv.imread(fp_im)\n",
+    "plt.imshow(im)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 287,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "xmm_sc = (1.2*np.min(preds[:,0]),1.2*np.max(preds_orig[:,0]))\n",
-    "xmm = (np.min(preds_orig[:,0]),np.max(preds_orig[:,0]))\n",
-    "ymm = (np.min(preds_orig[:,1]),np.max(preds_orig[:,1]))\n",
-    "zmm = (np.min(preds_orig[:,2]),np.max(preds_orig[:,2]))\n"
-   ]
+   "source": []
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 288,
    "metadata": {},
    "outputs": [],
    "source": [
-    "#$preds = np.array( [p[0]-xmm[0], p[1]-ymm[1], p[2]-zmm[0]] for p in preds_orig)\n",
-    "preds = np.zeros_like(preds_orig).astype(np.uint8)\n",
-    "for i,p in enumerate(preds_orig):\n",
-    "  x,y,z = p\n",
-    "  preds[i] = np.array([x - xmm[0], y - ymm[0], z - zmm[0]])\n",
-    "  preds[i] = np.array([x - xmm[0], z - zmm[0], y - ymm[0]])\n",
-    "  #preds[i] = np.array([x - xmm[0], abs((z - zmm[0])+zmm[0]), y - ymm[0]])\n",
+    "def generate_3d_face_plain(im, lm):\n",
+    "  preds = lm\n",
+    "  fig = plt.figure(figsize=plt.figaspect(.5))\n",
+    "  ax = fig.add_subplot(1, 2, 1)\n",
+    "  ax.imshow(im)\n",
+    "  ax.plot(preds[0:17,0],preds[0:17,1],marker='o',markersize=6,linestyle='-',color='w',lw=2)\n",
+    "  ax.plot(preds[17:22,0],preds[17:22,1],marker='o',markersize=6,linestyle='-',color='w',lw=2)\n",
+    "  ax.plot(preds[22:27,0],preds[22:27,1],marker='o',markersize=6,linestyle='-',color='w',lw=2)\n",
+    "  ax.plot(preds[27:31,0],preds[27:31,1],marker='o',markersize=6,linestyle='-',color='w',lw=2)\n",
+    "  ax.plot(preds[31:36,0],preds[31:36,1],marker='o',markersize=6,linestyle='-',color='w',lw=2)\n",
+    "  ax.plot(preds[36:42,0],preds[36:42,1],marker='o',markersize=6,linestyle='-',color='w',lw=2)\n",
+    "  ax.plot(preds[42:48,0],preds[42:48,1],marker='o',markersize=6,linestyle='-',color='w',lw=2)\n",
+    "  ax.plot(preds[48:60,0],preds[48:60,1],marker='o',markersize=6,linestyle='-',color='w',lw=2)\n",
+    "  ax.plot(preds[60:68,0],preds[60:68,1],marker='o',markersize=6,linestyle='-',color='w',lw=2) \n",
+    "  ax.axis('off')\n",
+    "\n",
+    "  ax = fig.add_subplot(1, 2, 2, projection='3d')\n",
+    "  surf = ax.scatter(preds[:,0]*1.2,preds[:,1],preds[:,2],c=\"cyan\", alpha=1.0, edgecolor='b')\n",
+    "  ax.plot3D(preds[:17,0]*1.2,preds[:17,1], preds[:17,2], color='blue' )\n",
+    "  ax.plot3D(preds[17:22,0]*1.2,preds[17:22,1],preds[17:22,2], color='blue')\n",
+    "  ax.plot3D(preds[22:27,0]*1.2,preds[22:27,1],preds[22:27,2], color='blue')\n",
+    "  ax.plot3D(preds[27:31,0]*1.2,preds[27:31,1],preds[27:31,2], color='blue')\n",
+    "  ax.plot3D(preds[31:36,0]*1.2,preds[31:36,1],preds[31:36,2], color='blue')\n",
+    "  ax.plot3D(preds[36:42,0]*1.2,preds[36:42,1],preds[36:42,2], color='blue')\n",
+    "  ax.plot3D(preds[42:48,0]*1.2,preds[42:48,1],preds[42:48,2], color='blue')\n",
+    "  ax.plot3D(preds[48:,0]*1.2,preds[48:,1],preds[48:,2], color='blue' )\n",
+    "  \n",
+    "  # pad\n",
+    "  xmm = (np.min(lm[:,0]),np.max(lm[:,0]))\n",
+    "  ymm = (np.min(lm[:,1]),np.max(lm[:,1]))\n",
+    "  zmm = (np.min(lm[:,2]),np.max(lm[:,2]))\n",
     "  \n",
-    "#preds = np.rot90(preds,2,axes=(0,1))"
+    "  print(xmm, ymm, zmm)\n",
+    "#   ax.set_xticks([])\n",
+    "#   ax.set_yticks([])\n",
+    "#   ax.set_zticks([])\n",
+    "  plt.setp( ax.get_xticklabels(), visible=False)\n",
+    "  plt.setp( ax.get_yticklabels(), visible=False)\n",
+    "  #ax.set_xlim(xmm[0]-50, xmm[1]+50)\n",
+    "  #ax.set_ylim(ymm[0]-50, ymm[1]+50)\n",
+    "  #ax.set_ylim(zmm[0]- .1*zmm[0],zmm[1] + .1*zmm[1])\n",
+    "  #ax.set_ylim(103, 275)\n",
+    "  #ax.set_zlim((-100,100))\n",
+    "  ax.view_init(elev=15., azim=135.)\n",
+    "\n",
+    "  plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
-   "metadata": {
-    "scrolled": false
-   },
+   "execution_count": 367,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -997,7 +950,7 @@
     {
      "data": {
       "text/html": [
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\" 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\" width=\"960\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -1010,123 +963,167 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "(31.0, 256.0) (97.0, 293.0) (-101.42858, 71.526764)\n",
-      "143.0 195.0 -15.428581237792969\n"
+      "(68.0, 201.0) (110.0, 225.0) (-61.021374, 41.419292)\n"
      ]
     }
    ],
    "source": [
-    "#TODO: Make this nice\n",
-    "fig = plt.figure(figsize=(16,16),dpi=72)\n",
-    "ax = fig.add_subplot(111, projection='3d')\n",
-    "\n",
-    "preds_scaled = np.array([1.2*x,y,z] for x,y,z in preds)\n",
-    "\n",
-    "preds_plot = np.zeros_like(preds)\n",
-    "for i,p in enumerate(preds):\n",
-    "  x,y,z = p\n",
-    "  preds_plot[i] = np.array([x,y,z])\n",
-    "\n",
-    "clr1 = '#00ff00'\n",
-    "clr2 = '#00ff00'\n",
-    "\n",
-    "clr1 = '#ff0000'\n",
-    "clr2 = '#ff0000'\n",
-    "\n",
-    "ax.set_facecolor('black')\n",
-    "#ax.set_facecolor((1, 0, 0))\n",
-    "\n",
-    "ls = LightSource(270, 45)\n",
-    "# To use a custom hillshading mode, override the built-in shading and pass\n",
-    "# in the rgb colors of the shaded surface calculated from \"shade\".\n",
-    "#rgb = ls.shade(preds[:,1], cmap=cm.gist_earth, vert_exag=0.1, blend_mode='soft')\n",
-    "rh = rhex()\n",
-    "surf = ax.scatter(preds_plot[:,0]*1.2,preds_plot[:,1],preds_plot[:,2],c=rh, \n",
-    "                  alpha=1.0, s=65, edgecolor=rh)\n",
-    "#facecolors=rgb,linewidth=0, antialiased=False, shade=Fals\n",
-    "\n",
-    "\n",
-    "#surf = ax.plot_surface(x, y, z, rstride=1, cstride=1, facecolors=rgb,\n",
-    "#                       linewidth=0, antialiased=False, shade=False)\n",
-    "\n",
-    "\n",
-    "#surf.actor.property.specular = 0.1\n",
-    "#surf.actor.property.specular_power = 5\n",
-    "\n",
-    "lw = 3\n",
-    "ax.plot3D(preds_plot[:17,0]*1.2,preds_plot[:17,1], preds_plot[:17,2], color=rhex(),linewidth=lw)\n",
-    "ax.plot3D(preds_plot[17:22,0]*1.2,preds_plot[17:22,1],preds_plot[17:22,2], color=rhex(),linewidth=lw)\n",
-    "ax.plot3D(preds_plot[22:27,0]*1.2,preds_plot[22:27,1],preds_plot[22:27,2], color=rhex(),linewidth=lw)\n",
-    "ax.plot3D(preds_plot[27:31,0]*1.2,preds_plot[27:31,1],preds_plot[27:31,2], color=rhex(),linewidth=lw)\n",
-    "ax.plot3D(preds_plot[31:36,0]*1.2,preds_plot[31:36,1],preds_plot[31:36,2], color=rhex(),linewidth=lw)\n",
-    "ax.plot3D(preds_plot[36:42,0]*1.2,preds_plot[36:42,1],preds_plot[36:42,2], color=rhex(),linewidth=lw)\n",
-    "ax.plot3D(preds_plot[42:48,0]*1.2,preds_plot[42:48,1],preds_plot[42:48,2], color=rhex(),linewidth=lw)\n",
-    "ax.plot3D(preds_plot[48:,0]*1.2,preds_plot[48:,1],preds_plot[48:,2], color=rhex(), linewidth=lw)\n",
-    "\n",
-    "\n",
-    "print(xmm,ymm,zmm)\n",
-    "# ax.set_xlim3d(left=xmm[0],right=xmm[1])\n",
-    "# ax.set_ylim3d(bottom=ymm[0],top=ymm[1])\n",
-    "# ax.set_zlim3d(bottom=zmm[0],top=zmm[1])\n",
-    "\n",
-    "cx = ((xmm[0] - xmm[1]) // 2) + xmm[1]\n",
-    "cy = ((ymm[1] - ymm[0]) // 2) + ymm[0]\n",
-    "cz = ((zmm[1] - zmm[0]) // 2) + zmm[0]\n",
-    "print(cx,cy,cz)\n",
-    "\n",
-    "xpts = [cx,cx]\n",
-    "ypts = [cy,cy]\n",
-    "zpts = [zmm[0],zmm[1]]\n",
-    "\n",
-    "#ax.plot3D(xpts,ypts,zpts,color='red')\n",
-    "\n",
-    "# need to make this dynamic, sigh\n",
-    "ax.view_init(elev=120., azim=70.)\n",
-    "#ax.view_init(elev=90., azim=40.)\n",
-    "\n",
-    "margin = 20\n",
+    "im = cv.imread(fp_im)\n",
+    "im_rgb = cv.cvtColor(im, cv.COLOR_BGR2RGB)\n",
+    "lm = fa.get_landmarks(im_rgb)[-1]\n",
+    "generate_3d_face_plain(im_rgb, lm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 393,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    " # line weight\n",
+    "def generate_3d_face(lm, fp_out, num_frames=30, dpi=72, stroke_weight=2, size=(480,480),\n",
+    "  mark_size=10, mark_type='.', mark_clr=(0,255,0), fps=10, transparent=False):\n",
+    "  '''Generates 3D plot of face landmarks\n",
+    "  '''\n",
+    "  # convert opencv BGR numpy image to RGB\n",
+    "  bg_color = '#%02x%02x%02x' % (0,0,0)\n",
+    "  mark_clr = '#%02x%02x%02x' % (0,255,255)\n",
+    "  \n",
+    "  # scale to make larger\n",
+    "  #lm = np.array([1.2*x,y,z] for x,y,z in list(lm))\n",
+    "  \n",
+    "  # center x,y,z\n",
+    "  xmm = (np.min(lm[:,0]),np.max(lm[:,0]))\n",
+    "  ymm = (np.min(lm[:,1]),np.max(lm[:,1]))\n",
+    "  zmm = (np.min(lm[:,2]),np.max(lm[:,2]))\n",
+    "  \n",
+    "  # make copy of landmarks\n",
+    "  lm_orig = lm.copy()\n",
+    "  xmm = (np.min(lm_orig[:,0]),np.max(lm_orig[:,0]))\n",
+    "  ymm = (np.min(lm_orig[:,1]),np.max(lm_orig[:,1]))\n",
+    "  zmm = (np.min(lm_orig[:,2]),np.max(lm_orig[:,2]))\n",
+    "  \n",
+    "  # swap the y and z components to improve 3d rotation angles for matplotlib\n",
+    "  lm = np.zeros_like(lm_orig).astype(np.uint8)\n",
+    "  for i,p in enumerate(lm_orig):\n",
+    "    x,y,z = p\n",
+    "    lm[i] = np.array([x - xmm[0], z - zmm[0], y - ymm[0]])\n",
+    "  \n",
+    "  # Create plot\n",
+    "  figsize = (size[0]/dpi, size[1]/dpi )\n",
+    "  fig = plt.figure(figsize=figsize, dpi=dpi)  # frameon=False\n",
+    "  #fig.set_size_inches(100/100, 1, forward=False)\n",
+    "  fig.tight_layout()\n",
+    "  fig.subplots_adjust(left=0, bottom=0, right=1, top=1, wspace=None, hspace=None)\n",
+    "  ax = fig.add_subplot(111, projection='3d')\n",
+    "  ax.set_facecolor(bg_color) # background color\n",
+    "  \n",
+    "  xscale, yscale, zscale = (1.2, 1.0, 1.0)\n",
+    "  \n",
+    "  # scatter plot the dots\n",
+    "  # jaw line\n",
+    "  mark_clr = '#%02x%02x%02x' % (0,255,0)  # green\n",
+    "  ax.plot3D(lm[:17,0]*1.2,lm[:17,1], lm[:17,2],\n",
+    "            marker=mark_type, markersize=mark_size, color=mark_clr,linewidth=stroke_weight)\n",
+    "  # stage-right eyebrow\n",
+    "  mark_clr = '#%02x%02x%02x' % (255,0,0)  # green\n",
+    "  ax.plot3D(lm[17:22,0]*1.2,lm[17:22,1],lm[17:22,2],\n",
+    "            marker=mark_type, markersize=mark_size, color=mark_clr,linewidth=stroke_weight)\n",
+    "  # stage-left eyebrow\n",
+    "  mark_clr = '#%02x%02x%02x' % (255,255,0)  # yellow\n",
+    "  ax.plot3D(lm[22:27,0]*1.2,lm[22:27,1],lm[22:27,2], \n",
+    "            marker=mark_type, markersize=mark_size, color=mark_clr,linewidth=stroke_weight)\n",
+    "  # nose ridge\n",
+    "  mark_clr = '#%02x%02x%02x' % (0,0,255)  # blue\n",
+    "  ax.plot3D(lm[27:31,0]*1.2,lm[27:31,1],lm[27:31,2],\n",
+    "            marker=mark_type, markersize=mark_size, color=mark_clr,linewidth=stroke_weight)\n",
+    "  # nose-bottom\n",
+    "  mark_clr = '#%02x%02x%02x' % (255,0,255)  # magenta\n",
+    "  ax.plot3D(lm[31:36,0]*1.2,lm[31:36,1],lm[31:36,2],\n",
+    "            marker=mark_type, markersize=mark_size, color=mark_clr,linewidth=stroke_weight)\n",
+    "  # stage-left eye\n",
+    "  mark_clr = '#%02x%02x%02x' % (0,255,255)  # cyan\n",
+    "  px, py, pz = lm[36:42,0]*1.2,lm[36:42,1],lm[36:42,2]\n",
+    "  px = np.append(px, lm[36,0]*1.2)\n",
+    "  py = np.append(py, lm[36,1])\n",
+    "  pz = np.append(pz, lm[36,2])\n",
+    "  ax.plot3D(px, py, pz, marker=mark_type, markersize=mark_size, color=mark_clr,linewidth=stroke_weight)\n",
+    "  \n",
+    "  # stage-right eye\n",
+    "  mark_clr = '#%02x%02x%02x' % (255,255,255)  # white\n",
+    "  px, py, pz = lm[42:48,0]*1.2,lm[42:48,1],lm[42:48,2]\n",
+    "  px = np.append(px, lm[42,0]*1.2)\n",
+    "  py = np.append(py, lm[42,1])\n",
+    "  pz = np.append(pz, lm[42,2])\n",
+    "  ax.plot3D(px, py, pz, marker=mark_type, markersize=mark_size, color=mark_clr,linewidth=stroke_weight)\n",
+    "  \n",
+    "  # mouth\n",
+    "  mark_clr = '#%02x%02x%02x' % (255,125,0)  # orange?\n",
+    "  px, py, pz = lm[48:,0]*1.2,lm[48:,1],lm[48:,2]\n",
+    "  px = np.append(px, lm[48,0]*1.2)\n",
+    "  py = np.append(py, lm[48,1])\n",
+    "  pz = np.append(pz, lm[48,2])\n",
+    "  ax.plot3D(px, py, pz, marker=mark_type, markersize=mark_size, color=mark_clr, linewidth=stroke_weight)\n",
+    "  \n",
+    "  rh = '#00ff00'  # edge color\n",
+    "  #ax.scatter(lm[:,0]*xscale,lm[:,1]*yscale,lm[:,2]*zscale, c=rh, alpha=1.0, s=35, edgecolor=rh)\n",
+    "  #ax.scatter(lm[:,0]*xscale,lm[:,1]*yscale,lm[:,2]*zscale, c=rh, alpha=1.0, s=1)\n",
+    "  \n",
+    "  # center center x,y,z points\n",
+    "  cx = ((xmm[0] - xmm[1]) // 2) + xmm[1]\n",
+    "  cy = ((ymm[1] - ymm[0]) // 2) + ymm[0]\n",
+    "  cz = ((zmm[1] - zmm[0]) // 2) + zmm[0]\n",
+    "  \n",
+    "  # set initial plot view\n",
+    "  ax.view_init(elev=120., azim=70.)\n",
+    "  \n",
+    "  # remove ticks\n",
+    "  ax.set_xticks([])\n",
+    "  ax.set_yticks([])\n",
+    "  ax.set_zticks([])\n",
+    "    \n",
+    "  # remove axis\n",
+    "  ax.set_frame_on(False)\n",
+    "  ax.set_axis_off()\n",
     "\n",
-    "#ax.set_xlim(xmm[0] - margin,xmm[1] + margin)\n",
-    "#ax.set_ylim(ymm[0] - margin,ymm[1] + margin)\n",
-    "#ax.set_zlim(zmm[0] - margin,zmm[1] + margin)\n",
+    "  # rotation increments: from 0 to 360 in num_frames\n",
+    "  phi = np.linspace(0, 2*np.pi, num_frames)\n",
     "\n",
-    "ax.set_xticks([])\n",
-    "ax.set_yticks([])\n",
-    "ax.set_zticks([])\n",
-    "ax.set_axis_off()\n",
-    "ax.set_xlabel('x')\n",
-    "ax.set_ylabel('y')\n",
-    "ax.set_zlabel('z')\n",
-    "plt.savefig('test.png', dpi=80)\n",
-    "plt.show()\n"
+    "  def update(phi):\n",
+    "    ax.view_init(180,phi*180./np.pi)\n",
+    "  \n",
+    "  ani = matplotlib.animation.FuncAnimation(fig, update, frames=phi)\n",
+    "  savefig_kwargs = {'pad_inches': 0, 'transparent': transparent}\n",
+    "  ani.save(fp_out, writer='imagemagick', fps=fps, savefig_kwargs=savefig_kwargs)\n",
+    "  clear_output()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
-   "metadata": {},
+   "execution_count": 394,
+   "metadata": {
+    "scrolled": false
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "../data_bodega/output/m.0k014.gif\n"
+      "time: 0.0017\n",
+      "Saved file to /home/adam/Downloads/0012_01.gif\n"
      ]
     }
    ],
    "source": [
-    "fname_out = join(data_bodega,'output', '{}.gif'.format(os.path.basename(os.path.dirname(fp_face))))\n",
-    "\n",
-    "phi = np.linspace(0, 2*np.pi,60)\n",
-    "\n",
-    "def update(phi):\n",
-    "    ax.view_init(180,phi*180./np.pi)\n",
-    "    #ax.view_init(90,phi*90./np.pi)\n",
-    "    #ax.view_init(elev=90., azim=90.)\n",
+    "# filepaths\n",
+    "dir_out = '/home/adam/Downloads/'\n",
+    "fp_out = join(dir_out, '{}.gif'.format(Path(fp_im).stem))\n",
     "\n",
-    "ani = matplotlib.animation.FuncAnimation(fig, update, frames=phi)\n",
-    "ani.save(fname_out, writer='imagemagick', fps=10)\n",
-    "#plt.show()"
+    "# generate 3D face\n",
+    "st = time.time()\n",
+    "generate_3d_face(lm,fp_out, num_frames=20, fps=10)\n",
+    "print('time: {:.4f}'.format((time.time()-st)/1000))\n",
+    "print(f'Saved file to {fp_out}')"
    ]
   },
   {
@@ -1142,13 +1139,20 @@
    "metadata": {},
    "outputs": [],
    "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python [conda env:megapixels]",
    "language": "python",
-   "name": "python3"
+   "name": "conda-env-megapixels-py"
   },
   "language_info": {
    "codemirror_mode": {
diff --git a/megapixels/notebooks/face_analysis/3d_face_plot_batch.ipynb b/megapixels/notebooks/face_analysis/3d_face_plot_batch.ipynb
deleted file mode 100644
index 45e309d3..00000000
--- a/megapixels/notebooks/face_analysis/3d_face_plot_batch.ipynb
+++ /dev/null
@@ -1,291 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# 3D Face Plot\n",
-    "\n",
-    "Attenzione visualization"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 43,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The autoreload extension is already loaded. To reload it, use:\n",
-      "  %reload_ext autoreload\n"
-     ]
-    }
-   ],
-   "source": [
-    "%load_ext autoreload\n",
-    "%autoreload 2\n",
-    "import os\n",
-    "from os.path import join\n",
-    "import sys\n",
-    "import time\n",
-    "import cv2 as cv\n",
-    "import numpy as np\n",
-    "import imutils\n",
-    "import matplotlib.animation\n",
-    "%matplotlib notebook\n",
-    "from glob import glob\n",
-    "from matplotlib import cbook\n",
-    "from matplotlib import cm\n",
-    "from matplotlib.colors import LightSource\n",
-    "from random import randint\n",
-    "sys.path.append('/megapixels/3rdparty/face-alignment')\n",
-    "import face_alignment\n",
-    "import numpy as np\n",
-    "from mpl_toolkits.mplot3d import Axes3D\n",
-    "import matplotlib.pyplot as plt\n",
-    "import mpl_toolkits.mplot3d.axes3d as p3\n",
-    "from matplotlib import animation\n",
-    "import random\n",
-    "from skimage import io\n",
-    "from tqdm import tqdm_notebook as tqdm\n",
-    "from IPython.display import clear_output\n",
-    "from pathlib import Path\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Generate random hex colors\n",
-    "def rhex():\n",
-    "  r = lambda: random.randint(0,255)\n",
-    "  return '#%02X%02X%02X' % (r(), r(), r())"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Downloading the Face Alignment Network(FAN). Please wait...\n",
-      "Downloading the Face Alignment depth Network (FAN-D). Please wait...\n"
-     ]
-    }
-   ],
-   "source": [
-    "# init 3d face\n",
-    "# Run the 3D face alignment on a test image, without CUDA.\n",
-    "fa = face_alignment.FaceAlignment(face_alignment.LandmarksType._3D, \n",
-    "                                  enable_cuda=True, flip_input=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "100\n"
-     ]
-    }
-   ],
-   "source": [
-    "data_bodega = '/megapixels/data_bodega/'\n",
-    "fp = join(data_bodega,'images/senators/*.jpg')\n",
-    "face_files = glob(fp,recursive=True)\n",
-    "print(len(face_files))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 44,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def generate_3d_face(fpath,output_dir):\n",
-    "  # load image\n",
-    "  im = io.imread(fpath)\n",
-    "  \n",
-    "  # generate 3d predictions\n",
-    "  preds = fa.get_landmarks(im)\n",
-    "  if preds is None:\n",
-    "    return\n",
-    "  preds = preds[-1]\n",
-    "  \n",
-    "  # plot style\n",
-    "  num_frames = 60\n",
-    "  lw = 2 # line weight\n",
-    "  bg_color = '#%02x%02x%02x' % (60,59,110)\n",
-    "  mark_clr = '#%02x%02x%02x' % (255,255,255) \n",
-    "  mark_type='$\\star$'\n",
-    "  mark_size = 20\n",
-    "  print(bg_color)\n",
-    "  \n",
-    "  dpi = 72\n",
-    "  figsize = (16,16)\n",
-    "  \n",
-    "  # center x,y,z\n",
-    "  xmm = (np.min(preds[:,0]),np.max(preds[:,0]))\n",
-    "  ymm = (np.min(preds[:,1]),np.max(preds[:,1]))\n",
-    "  zmm = (np.min(preds[:,2]),np.max(preds[:,2]))\n",
-    "  \n",
-    "  preds_orig = preds.copy()\n",
-    "  xmm_sc = (1.2*np.min(preds[:,0]),1.2*np.max(preds_orig[:,0]))\n",
-    "  xmm = (np.min(preds_orig[:,0]),np.max(preds_orig[:,0]))\n",
-    "  ymm = (np.min(preds_orig[:,1]),np.max(preds_orig[:,1]))\n",
-    "  zmm = (np.min(preds_orig[:,2]),np.max(preds_orig[:,2]))\n",
-    "  \n",
-    "  # swap the y and z components to improve 3d rotation angles\n",
-    "  preds = np.zeros_like(preds_orig).astype(np.uint8)\n",
-    "  for i,p in enumerate(preds_orig):\n",
-    "    x,y,z = p\n",
-    "    #preds[i] = np.array([x - xmm[0], y - ymm[0], z - zmm[0]]) # ?\n",
-    "    preds[i] = np.array([x - xmm[0], z - zmm[0], y - ymm[0]])\n",
-    "  \n",
-    "  # Create plot\n",
-    "  fig = plt.figure(figsize=figsize,dpi=dpi)\n",
-    "  fig.tight_layout()\n",
-    "  ax = fig.add_subplot(111, projection='3d')\n",
-    "  ax.set_facecolor(bg_color) # background color\n",
-    "  \n",
-    "  preds_plot = np.zeros_like(preds)\n",
-    "  for i,p in enumerate(preds):\n",
-    "    x,y,z = p\n",
-    "    preds_plot[i] = np.array([x,y,z])\n",
-    "\n",
-    "  \n",
-    "  # scatter plot the dots\n",
-    "  ax.plot3D(preds_plot[:17,0]*1.2,preds_plot[:17,1], preds_plot[:17,2],\n",
-    "            marker=mark_type,markersize=mark_size,color=mark_clr,linewidth=lw)\n",
-    "  ax.plot3D(preds_plot[17:22,0]*1.2,preds_plot[17:22,1],preds_plot[17:22,2],\n",
-    "            marker=mark_type,markersize=mark_size,color=mark_clr,linewidth=lw)\n",
-    "  ax.plot3D(preds_plot[22:27,0]*1.2,preds_plot[22:27,1],preds_plot[22:27,2], \n",
-    "            marker=mark_type,markersize=mark_size,color=mark_clr,linewidth=lw)\n",
-    "  ax.plot3D(preds_plot[27:31,0]*1.2,preds_plot[27:31,1],preds_plot[27:31,2],\n",
-    "            marker=mark_type,markersize=mark_size,color=mark_clr,linewidth=lw)\n",
-    "  ax.plot3D(preds_plot[31:36,0]*1.2,preds_plot[31:36,1],preds_plot[31:36,2],\n",
-    "            marker=mark_type,markersize=mark_size,color=mark_clr,linewidth=lw)\n",
-    "  ax.plot3D(preds_plot[36:42,0]*1.2,preds_plot[36:42,1],preds_plot[36:42,2],\n",
-    "            marker=mark_type,markersize=mark_size,color=mark_clr,linewidth=lw)\n",
-    "  ax.plot3D(preds_plot[42:48,0]*1.2,preds_plot[42:48,1],preds_plot[42:48,2],\n",
-    "            marker=mark_type,markersize=mark_size,color=mark_clr,linewidth=lw)\n",
-    "  ax.plot3D(preds_plot[48:,0]*1.2,preds_plot[48:,1],preds_plot[48:,2],\n",
-    "            marker=mark_type,markersize=mark_size,color=mark_clr, linewidth=lw)\n",
-    "\n",
-    "  \n",
-    "  rh = '#ffffff'\n",
-    "  ax.scatter(preds_plot[:,0]*1.2,preds_plot[:,1],preds_plot[:,2],c=rh, alpha=1.0, s=35, edgecolor=rh)\n",
-    "  \n",
-    "  # center points\n",
-    "  cx = ((xmm[0] - xmm[1]) // 2) + xmm[1]\n",
-    "  cy = ((ymm[1] - ymm[0]) // 2) + ymm[0]\n",
-    "  cz = ((zmm[1] - zmm[0]) // 2) + zmm[0]\n",
-    "\n",
-    "  #xpts = [cx,cx]\n",
-    "  #ypts = [cy,cy]\n",
-    "  #zpts = [zmm[0],zmm[1]]\n",
-    "\n",
-    "  ax.view_init(elev=120., azim=70.)\n",
-    "  \n",
-    "  ax.set_xticks([])\n",
-    "  ax.set_yticks([])\n",
-    "  ax.set_zticks([])\n",
-    "  ax.set_axis_off()\n",
-    "  ax.set_xlabel('x')\n",
-    "  ax.set_ylabel('y')\n",
-    "  ax.set_zlabel('z')\n",
-    "\n",
-    "  # write animation to disk\n",
-    "  fname_out = join(output_dir, '{}.gif'.format(Path(fpath).stem))\n",
-    "  print(fname_out)\n",
-    "  # rotation increments\n",
-    "  phi = np.linspace(0, 2*np.pi, num_frames)\n",
-    "\n",
-    "  def update(phi):\n",
-    "      ax.view_init(180,phi*180./np.pi)\n",
-    "  \n",
-    "  ani = matplotlib.animation.FuncAnimation(fig, update, frames=phi)\n",
-    "  ani.save(fname_out, writer='imagemagick', fps=10)\n",
-    "  #del ani"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 47,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "output_dir = join(data_bodega,'output','senators_3d_points')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 49,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n"
-     ]
-    }
-   ],
-   "source": [
-    "for f in tqdm(face_files):\n",
-    "  generate_3d_face(f,output_dir)\n",
-    "  clear_output()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "cv.L"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python [conda env:megapixels]",
-   "language": "python",
-   "name": "conda-env-megapixels-py"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.6"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/megapixels/notebooks/face_analysis/3d_face_plot_batch_frames.ipynb b/megapixels/notebooks/face_analysis/3d_face_plot_batch_frames.ipynb
deleted file mode 100644
index 6ade79dc..00000000
--- a/megapixels/notebooks/face_analysis/3d_face_plot_batch_frames.ipynb
+++ /dev/null
@@ -1,2055 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# 3D Face Plot\n",
-    "\n",
-    "Process faces for Georgetown Color of Surveillance"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 128,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The autoreload extension is already loaded. To reload it, use:\n",
-      "  %reload_ext autoreload\n"
-     ]
-    }
-   ],
-   "source": [
-    "%load_ext autoreload\n",
-    "%autoreload 2\n",
-    "import os\n",
-    "from os.path import join\n",
-    "import sys\n",
-    "import time\n",
-    "import cv2 as cv\n",
-    "import numpy as np\n",
-    "import imutils\n",
-    "import matplotlib.animation\n",
-    "%matplotlib notebook\n",
-    "from glob import glob\n",
-    "from matplotlib import cbook\n",
-    "from matplotlib import cm\n",
-    "from matplotlib.colors import LightSource\n",
-    "from random import randint\n",
-    "sys.path.append('/megapixels/3rdparty/face-alignment')\n",
-    "import face_alignment\n",
-    "import numpy as np\n",
-    "from mpl_toolkits.mplot3d import Axes3D\n",
-    "import matplotlib.pyplot as plt\n",
-    "import mpl_toolkits.mplot3d.axes3d as p3\n",
-    "from matplotlib import animation\n",
-    "import random\n",
-    "from skimage import io\n",
-    "from tqdm import tqdm_notebook as tqdm\n",
-    "from IPython.display import clear_output\n",
-    "from pathlib import Path\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 129,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# init 3d face\n",
-    "# Run the 3D face alignment on a test image, without CUDA.\n",
-    "fa = face_alignment.FaceAlignment(face_alignment.LandmarksType._3D, \n",
-    "                                  enable_cuda=True, flip_input=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "100\n"
-     ]
-    }
-   ],
-   "source": [
-    "data_bodega = '/megapixels/data_bodega/'\n",
-    "fp = join(data_bodega,'images/senators/*.jpg')\n",
-    "face_files = glob(fp,recursive=True)\n",
-    "print(len(face_files))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 97,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "\n",
-    "def ensure_dir(d):\n",
-    "  \"\"\"Create directory if not exist\n",
-    "    :param d: path to directory\n",
-    "  \"\"\"\n",
-    "  if not os.path.exists(d):\n",
-    "      os.makedirs(d, exist_ok=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 109,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def generate_3d_face(fpath,output_dir,anim=False,ext='png'):\n",
-    "  # load image\n",
-    "  im = io.imread(fpath)\n",
-    "  \n",
-    "  # generate 3d predictions\n",
-    "  preds = fa.get_landmarks(im)\n",
-    "  if preds is None:\n",
-    "    return\n",
-    "  preds = preds[-1]\n",
-    "  \n",
-    "  # plot style\n",
-    "  num_frames = 60\n",
-    "  lw = 2 # line weight\n",
-    "  bg_color = '#%02x%02x%02x' % (60,59,110)\n",
-    "  mark_clr = '#%02x%02x%02x' % (255,255,255)\n",
-    "  mark_clr = '#%02x%02x%02x' % (0,255,0)\n",
-    "  #mark_type='$\\star$'\n",
-    "  #mark_size = 20\n",
-    "  mark_type='o'\n",
-    "  mark_size = 10\n",
-    "  rh = '#ffffff'\n",
-    "  dpi = 72\n",
-    "  figsize = (16,16)\n",
-    "  \n",
-    "  # center x,y,z\n",
-    "  xmm = (np.min(preds[:,0]),np.max(preds[:,0]))\n",
-    "  ymm = (np.min(preds[:,1]),np.max(preds[:,1]))\n",
-    "  zmm = (np.min(preds[:,2]),np.max(preds[:,2]))\n",
-    "  \n",
-    "  preds_orig = preds.copy()\n",
-    "  xmm_sc = (1.2*np.min(preds[:,0]),1.2*np.max(preds_orig[:,0]))\n",
-    "  xmm = (np.min(preds_orig[:,0]),np.max(preds_orig[:,0]))\n",
-    "  ymm = (np.min(preds_orig[:,1]),np.max(preds_orig[:,1]))\n",
-    "  zmm = (np.min(preds_orig[:,2]),np.max(preds_orig[:,2]))\n",
-    "  \n",
-    "  # swap the y and z components to improve 3d rotation angles\n",
-    "  preds = np.zeros_like(preds_orig).astype(np.uint8)\n",
-    "  for i,p in enumerate(preds_orig):\n",
-    "    x,y,z = p\n",
-    "    #preds[i] = np.array([x - xmm[0], y - ymm[0], z - zmm[0]]) # ?\n",
-    "    preds[i] = np.array([x - xmm[0], z - zmm[0], y - ymm[0]])\n",
-    "  \n",
-    "  # Create plot\n",
-    "  fig = plt.figure(figsize=figsize,dpi=dpi)\n",
-    "  fig.tight_layout()\n",
-    "  ax = fig.add_subplot(111, projection='3d')\n",
-    "  ax.set_facecolor(bg_color) # background color\n",
-    "  \n",
-    "  preds_plot = np.zeros_like(preds)\n",
-    "  for i,p in enumerate(preds):\n",
-    "    x,y,z = p\n",
-    "    preds_plot[i] = np.array([x,y,z])\n",
-    "\n",
-    "  \n",
-    "  # scatter plot the dots\n",
-    "  ax.plot3D(preds_plot[:17,0]*1.2,preds_plot[:17,1], preds_plot[:17,2],\n",
-    "            marker=mark_type,markersize=mark_size,color=mark_clr,linewidth=lw)\n",
-    "  ax.plot3D(preds_plot[17:22,0]*1.2,preds_plot[17:22,1],preds_plot[17:22,2],\n",
-    "            marker=mark_type,markersize=mark_size,color=mark_clr,linewidth=lw)\n",
-    "  ax.plot3D(preds_plot[22:27,0]*1.2,preds_plot[22:27,1],preds_plot[22:27,2], \n",
-    "            marker=mark_type,markersize=mark_size,color=mark_clr,linewidth=lw)\n",
-    "  ax.plot3D(preds_plot[27:31,0]*1.2,preds_plot[27:31,1],preds_plot[27:31,2],\n",
-    "            marker=mark_type,markersize=mark_size,color=mark_clr,linewidth=lw)\n",
-    "  ax.plot3D(preds_plot[31:36,0]*1.2,preds_plot[31:36,1],preds_plot[31:36,2],\n",
-    "            marker=mark_type,markersize=mark_size,color=mark_clr,linewidth=lw)\n",
-    "  ax.plot3D(preds_plot[36:42,0]*1.2,preds_plot[36:42,1],preds_plot[36:42,2],\n",
-    "            marker=mark_type,markersize=mark_size,color=mark_clr,linewidth=lw)\n",
-    "  ax.plot3D(preds_plot[42:48,0]*1.2,preds_plot[42:48,1],preds_plot[42:48,2],\n",
-    "            marker=mark_type,markersize=mark_size,color=mark_clr,linewidth=lw)\n",
-    "  ax.plot3D(preds_plot[48:,0]*1.2,preds_plot[48:,1],preds_plot[48:,2],\n",
-    "            marker=mark_type,markersize=mark_size,color=mark_clr, linewidth=lw)\n",
-    "\n",
-    "  \n",
-    "  ax.scatter(preds_plot[:,0]*1.2,preds_plot[:,1],preds_plot[:,2],c=rh, alpha=1.0, s=35, edgecolor=rh)\n",
-    "  \n",
-    "  # center points\n",
-    "  cx = ((xmm[0] - xmm[1]) // 2) + xmm[1]\n",
-    "  cy = ((ymm[1] - ymm[0]) // 2) + ymm[0]\n",
-    "  cz = ((zmm[1] - zmm[0]) // 2) + zmm[0]\n",
-    "  \n",
-    "  # ?\n",
-    "  ax.view_init(elev=120., azim=70.)\n",
-    "  \n",
-    "  ax.set_xticks([])\n",
-    "  ax.set_yticks([])\n",
-    "  ax.set_zticks([])\n",
-    "  ax.set_axis_off()\n",
-    "  ax.set_xlabel('x')\n",
-    "  ax.set_ylabel('y')\n",
-    "  ax.set_zlabel('z')\n",
-    "\n",
-    "  \n",
-    "  phis = np.linspace(0, 2*np.pi, num_frames)\n",
-    "  \n",
-    "  if anim:\n",
-    "    def update(phi):\n",
-    "       ax.view_init(180,phi*180./np.pi)\n",
-    "    fname_out = join(output_dir,'{}.gif'.format(Path(fpath).stem))\n",
-    "    ani = matplotlib.animation.FuncAnimation(fig, update, frames=phis)\n",
-    "    ani.save(fname_out, writer='imagemagick', fps=10)\n",
-    "    del ani\n",
-    "  else:\n",
-    "    for i,phi in enumerate(phis):\n",
-    "      # ext (jpg,png,pdf)\n",
-    "      person_name = Path(fpath).stem\n",
-    "      fname_out = join(output_dir,person_name,'{}.{}'.format(str(i).zfill(4), ext))\n",
-    "      ensure_dir(Path(fname_out).parent)\n",
-    "      ax.view_init(180,phi*180./np.pi)\n",
-    "      fig.savefig(fname_out, transparent=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 110,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "output_dir = join(data_bodega,'output','senators_3d_points_frames')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 123,
-   "metadata": {
-    "scrolled": false
-   },
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support.' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option)\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "<div id='7198d195-0982-48dc-b3f1-788db85c55f0'></div>"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "ename": "KeyboardInterrupt",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-123-8c302f1f5d5d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtqdm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mface_files\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m   \u001b[0mgenerate_3d_face\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0moutput_dir\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m   \u001b[0mclear_output\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m<ipython-input-109-6767cbc7c4df>\u001b[0m in \u001b[0;36mgenerate_3d_face\u001b[0;34m(fpath, output_dir, anim, ext)\u001b[0m\n\u001b[1;32m    107\u001b[0m       \u001b[0mensure_dir\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mPath\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname_out\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparent\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    108\u001b[0m       \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mview_init\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m180\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mphi\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0;36m180.\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 109\u001b[0;31m       \u001b[0mfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msavefig\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname_out\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtransparent\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;32m~/anaconda3/envs/megapixels/lib/python3.6/site-packages/matplotlib/figure.py\u001b[0m in \u001b[0;36msavefig\u001b[0;34m(self, fname, **kwargs)\u001b[0m\n\u001b[1;32m   2033\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_frameon\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mframeon\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2034\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2035\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprint_figure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2036\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2037\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mframeon\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/anaconda3/envs/megapixels/lib/python3.6/site-packages/matplotlib/backend_bases.py\u001b[0m in \u001b[0;36mprint_figure\u001b[0;34m(self, filename, dpi, facecolor, edgecolor, orientation, format, **kwargs)\u001b[0m\n\u001b[1;32m   2261\u001b[0m                 \u001b[0morientation\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morientation\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2262\u001b[0m                 \u001b[0mbbox_inches_restore\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0m_bbox_inches_restore\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2263\u001b[0;31m                 **kwargs)\n\u001b[0m\u001b[1;32m   2264\u001b[0m         \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2265\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mbbox_inches\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mrestore_bbox\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/anaconda3/envs/megapixels/lib/python3.6/site-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36mprint_png\u001b[0;34m(self, filename_or_obj, *args, **kwargs)\u001b[0m\n\u001b[1;32m    526\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mcbook\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen_file_cm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename_or_obj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"wb\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mfh\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    527\u001b[0m                 _png.write_png(renderer._renderer, fh,\n\u001b[0;32m--> 528\u001b[0;31m                                self.figure.dpi, metadata=metadata)\n\u001b[0m\u001b[1;32m    529\u001b[0m         \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    530\u001b[0m             \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdpi\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0moriginal_dpi\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
-     ]
-    }
-   ],
-   "source": [
-    "for f in tqdm(face_files):\n",
-    "  generate_3d_face(f,output_dir)\n",
-    "  clear_output()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 130,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(550, 450, 3)"
-      ]
-     },
-     "execution_count": 130,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "im = cv.imread('/data_store/datasets/gov/images/senators/wyden_ron.jpg')\n",
-    "im.shape"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 132,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "\n",
-       "mpl.get_websocket_type = function() {\n",
-       "    if (typeof(WebSocket) !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert('Your browser does not have WebSocket support.' +\n",
-       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "              'Firefox 4 and 5 are also supported but you ' +\n",
-       "              'have to enable WebSockets in about:config.');\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent = (\n",
-       "                \"This browser does not support binary websocket messages. \" +\n",
-       "                    \"Performance may be slow.\");\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = $('<div/>');\n",
-       "    this._root_extra_style(this.root)\n",
-       "    this.root.attr('style', 'display: inline-block');\n",
-       "\n",
-       "    $(parent_element).append(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen =  function () {\n",
-       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
-       "            fig.send_message(\"send_image_mode\", {});\n",
-       "            if (mpl.ratio != 1) {\n",
-       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
-       "            }\n",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var backingStore = this.context.backingStorePixelRatio ||\n",
-       "\tthis.context.webkitBackingStorePixelRatio ||\n",
-       "\tthis.context.mozBackingStorePixelRatio ||\n",
-       "\tthis.context.msBackingStorePixelRatio ||\n",
-       "\tthis.context.oBackingStorePixelRatio ||\n",
-       "\tthis.context.backingStorePixelRatio || 1;\n",
-       "\n",
-       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband = $('<canvas/>');\n",
-       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
-       "\n",
-       "    var pass_mouse_events = true;\n",
-       "\n",
-       "    canvas_div.resizable({\n",
-       "        start: function(event, ui) {\n",
-       "            pass_mouse_events = false;\n",
-       "        },\n",
-       "        resize: function(event, ui) {\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "        stop: function(event, ui) {\n",
-       "            pass_mouse_events = true;\n",
-       "            fig.request_resize(ui.size.width, ui.size.height);\n",
-       "        },\n",
-       "    });\n",
-       "\n",
-       "    function mouse_event_fn(event) {\n",
-       "        if (pass_mouse_events)\n",
-       "            return fig.mouse_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
-       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
-       "\n",
-       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
-       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
-       "\n",
-       "    canvas_div.on(\"wheel\", function (event) {\n",
-       "        event = event.originalEvent;\n",
-       "        event['data'] = 'scroll'\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        mouse_event_fn(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.append(canvas);\n",
-       "    canvas_div.append(rubberband);\n",
-       "\n",
-       "    this.rubberband = rubberband;\n",
-       "    this.rubberband_canvas = rubberband[0];\n",
-       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
-       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
-       "\n",
-       "    this._resize_canvas = function(width, height) {\n",
-       "        // Keep the size of the canvas, canvas container, and rubber band\n",
-       "        // canvas in synch.\n",
-       "        canvas_div.css('width', width)\n",
-       "        canvas_div.css('height', height)\n",
-       "\n",
-       "        canvas.attr('width', width * mpl.ratio);\n",
-       "        canvas.attr('height', height * mpl.ratio);\n",
-       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
-       "\n",
-       "        rubberband.attr('width', width);\n",
-       "        rubberband.attr('height', height);\n",
-       "    }\n",
-       "\n",
-       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
-       "    // upon first draw.\n",
-       "    this._resize_canvas(600, 600);\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus () {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            // put a spacer in here.\n",
-       "            continue;\n",
-       "        }\n",
-       "        var button = $('<button/>');\n",
-       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
-       "                        'ui-button-icon-only');\n",
-       "        button.attr('role', 'button');\n",
-       "        button.attr('aria-disabled', 'false');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "\n",
-       "        var icon_img = $('<span/>');\n",
-       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
-       "        icon_img.addClass(image);\n",
-       "        icon_img.addClass('ui-corner-all');\n",
-       "\n",
-       "        var tooltip_span = $('<span/>');\n",
-       "        tooltip_span.addClass('ui-button-text');\n",
-       "        tooltip_span.html(tooltip);\n",
-       "\n",
-       "        button.append(icon_img);\n",
-       "        button.append(tooltip_span);\n",
-       "\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker_span = $('<span/>');\n",
-       "\n",
-       "    var fmt_picker = $('<select/>');\n",
-       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
-       "    fmt_picker_span.append(fmt_picker);\n",
-       "    nav_element.append(fmt_picker_span);\n",
-       "    this.format_dropdown = fmt_picker[0];\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = $(\n",
-       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
-       "        fmt_picker.append(option)\n",
-       "    }\n",
-       "\n",
-       "    // Add hover states to the ui-buttons\n",
-       "    $( \".ui-button\" ).hover(\n",
-       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
-       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
-       "    );\n",
-       "\n",
-       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function(type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function() {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1]);\n",
-       "        fig.send_message(\"refresh\", {});\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
-       "    var x0 = msg['x0'] / mpl.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
-       "    var x1 = msg['x1'] / mpl.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    var width = fig.canvas.width/mpl.ratio\n",
-       "    fig.root.unbind('remove')\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable()\n",
-       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
-       "    fig.close_ws(fig, msg);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width/mpl.ratio\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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-       "<img 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Bnq7TjAy2MbYcDtXp3uYvdbL4vVuNmYG2bw3yM78cLxddbO72MOT+308m+9hb0Gufdq7P/ChSDxBIpOFR3kvPrwvI/EYOvBeHfb+Z5LcVOdKdc5k8fqUNp9Ofg4TrlR1QUJ6BL8UQnoEX4RU0qPU8ezbcfmQ9VJSSY/ypXnYTJhMkpNKejLJRKqO5WNFJfE8qaTnUzqfFyvDvFwdSfsaE3/Ps5X4a74/EM/yjPB8aZTd5Ql2FsdYnx1m/mYPty+f5/sL7YwMnKLnfCOdbfWcPVNDW0s1Z05W09RQSl1lEdWVESrLohSXllBSWkp5ZSWxygpilRWUlFcQLS0jWlZJsKQMb7gEZyiKKxTDGYoeCFe4GHcwisdfjCcUwxsuxR8uwROM4A6EcQfCeENhnIEwBlcIjc2HxupBIznQWp3o7W5MLh9Wjx+HN4AvHCIcjRAuDlFcEqU4FqY4Fqaiopi6+jLqG8ppPVnLSE8zkwMnuD7Rytx1OZu1PT/Aw3i268FCL7sLfTxb7Ofp0gDPFpOF52DbSi2jHy89HyO8h8lJ4v1U0pOuvaf7DGQzBJZOfDINNT9d6BPSI/gshPQIvghHjxzZl91Jlp7ERcoSpwqnWuk1m6xOOsn5mAxMNp1IpivpTMJ0WHyK8GTqlFLF7tIwTxf62Fvq59WafOyDxSHWZ4eZ+X6Qaxe6Ge0/y7kzjZxqrqe8Ki4wFeVEy0oJl8QIl8QIRovVDIwvHFXFxOYPY/WFsHojWL0RTO4QRqccVm8Em68IqzuA1R1CcgUxO/yYHX4szgBmZwizM4TB5sdgDWC0BZE8YSzuEJInjDMUxREuxhosRuuIUGgNo5FC5Jp95Jjc5JjcFEo+dPYgenuQQslHvtUrh8VNvtlJvtlJgcWFzuZCb3cjOT3YnU7cLhvFRW6a6qOcPV3Jd9NnWbzbz/LcEFsLsiQ+j8vOq+WD0pCqPWV6j1MJRKphq0zyociuEpna1WGSla3kZ5udymaoLpP8COkRfA5CegRfhGTpeTTbnVJ6fradqbOQnsOEJZur5s+VnsSOKrHD+rmlJ9Xf8mJlkL2lPl6sDPBsdYCthW6W7/Rw82I7o32n6T5/gpNNtcTKyikqKZczL0Ux3JESXKEYVl8xVl8xNn8JNn8JkjeKMxDDHS7FHYxidgUxOOQwucIYnWF0jgBGZwiHrwiHrwirI7BPdiRXEJsnjMMbxe4rxugMobX60dkC6O0BDM4ARlcQizeCzR/C6gticfqwOANYHQEsTh9GmxuT1YXJ6sLicGN1+jA6/OgdfnR2H1rJjVZyo7O55GPtHkx2DzqrB43ZjdbiwSBZsdtNOF0mysrcdJ2rYXLsDPN3B9hbHuPl8ih7y3Km50AbWD6YLZT//0fTvi9KpJKDbMU5G+nJJlPzKRmljxnWTZf9EdIj+CUQ0iP4IijSo2R5Eoe0EqUn1QJnmZbS/9ipvOlqJH4O6clWRA4Tn4/N9iRewac7R6q/79n9IZ4uDbC7PMjmQj/3bnVy80o7U8OnOd9+nJaTjVRVVRGJyTU2rlAMT6QMT6gYVyimyo7VV4zkjWJ2R3D4S+LHxLB6I0ieMJI7guSNInmjWDxFWL0RnP4obl8UpyeCzRNWwx5/zheM4Q6WYHAE0Vp9aK0+dHYfeocfgzOAyR1C8gaxeGTRsbsDakgOLxaHG8kuh83pxej0ysJj82KwujDYfRjsvrgwyWF2eDHZQ5jsIYw2NxqTEa3JgN1loqoqzOnTNYyPt7N0a4CNuwM8WBzi8eLowf/jjNIzmlF60mV6fgnp+VSxTpXp+VzpEcNbgl8KIT2CL8LRI0d4Mt+bUnTS7Y+VabHAdENbiV+kT+7L8XRpQI3d5UF2lwd5tnL40FQ2nUO6zia5o1Kef7U2uu9Y5bHX6xPysctDvFoe5M3aEG/Whni1NsSL1XgoneLKKM9Xx3gZ/5ndlVF2V0Z5tjrG8/UJnq9PsLcyKv+Na8M8Xx/i0XIvD+/3srPYx8OVER4uj/JweZKNhTGW7o1wYbyD7s4znDt7nLYzTdQ21FFaVUm4JEaopIJgcTm+cBSXP4TbF8IdCOMLR/GGirB7/JisNsx2B3aPH6c/iitQjDtYooZSl+MJyTLjDZfii5QRiFYQiFbgLyrHGy5VIxCtwBsuRXIFsTgDGG1ejDavnNFxh7C6Q1icAUx2HwarR80SKY+Z7D7MDr/6vNHmxmh3YbS7MFjlDI/R5sbs8KrSY3XLAmWwutBZHBhtbgxWF1qzHY3Jhs7iwOrxE62soO5EE5MTXSzOjLN9b4zd+yO8WBnk9eoge0tygfPe0jC7yxM8WZ7g0fIkT5fGebI0wt7SIC9Xh3i9MsTL1YT2tHawDe0tDWadtclGetJJcfIxz9fk2FuVa7+erQyl/ewkfn5SzVZL/NnEz6Ly+VQ+z+kuWoT0CD4HIT2CL8LnSE8q8TlMep7dH0gpPMoX+MdITzrx+ZTOJp30vFwdS3h8kJdLA7xYGeDFyiDPVwbVzuPFyjDPlkfYXZL/TTdk92JlWJWll+tDPN8a4fnmKM82JthaHGFlpp/rl9qZHDzOUHcDZ8/UcOpELSeba2hqqqGqtprSqkoisXI8oWKc/gg2lx+nL4jLHyJQVEKgqARvqAib24fN7cPu8ePyyRkbpU5HERFlCEsWEK96X5ESveRWpcbpj+KLlBEqqSJUUoUnFMMVKMbujajnTvxZg9Wz7/yFRjsFBhsakwOt2YnG5EBjslFokuQwWik0WlWR0UtO9JITs8OL5PJjdngxO7zxeqMARpubAoNEvt5CoUkiz2BAJ5kIR1y0nKxgtK+Zxdt97K1N8HJ9gperYzxfGuR5wnvybHmE3fsjPL0/xNOFPl6uDPNmYzRlG0ke4vwlpSft8+ujqvQkik+qz06mbKnSbpPFad/nMkNhs5AewecipEfwRUiWnn07LGexE3qy+GQjPcnZnUTp2VvNXMj5sUMKyTJz2BDWQelJfGxIjUThebY8wrPlEZ4sDfMkLj0vVoblY5LiZVx4nq8MsrfSz7P1YZ6tjfBoZYz7d/q5fbWTqeHT9Jyrob2liqaGUpoaKmhoqKKmtpKy6ipiFZWES8pwBYqweeTaGYc/hDtUhK+oBHeoCIc/hNXjx+YNYPcFcfjCahZGERFFUIw2LzqLC73k3veccqySoVGyOlZ3CF+kDH9ROYFoBb5ImVwH5A6pxynCpJzLaPOiMTkoMNgoNNrjwuMgX28hV2ckV2ckT2cmT2cmX2+hwCChMdnQmGzoJScGqwu95MRocyO5/EguPya7B63ZjtZsx2BzkmcwoDEZsdhNxEp8NDQUMTXawsbcCI/uj7G3PBFvP4M8X5bF9eXasJx9Wx5hN14H9GotvfQktqNUbeew+FQx+jmkJ/nCIPkcyeJzWF2PkB7B5yCkR/BFOHrkiLryb7ptJBLX60i1AGG6bE/a5fuTREeVnXjqPlVNwqfU4rxaG1UjWWiSI/GYxJ99vT627+febIzzal1+/vnqWHwIa0yNp8ujPI2vB5NqqO31+giv1uXzPVsZ4tHyMNvzA9y71s3o4Gm6zjfS1FhOdU0JFVUxYmVFVFaXUlIZIxIrjs/MKsMXKsbmCccLjIN4QsV4wyXYvSEsTh+Sy48rUKSKkZKJUYaklGEnJeOTavgpVSgCY7R5cfiKcAdLVPlRhr10FpeayTHavPvESmt2qpFOehTxUeSnwCCRpzOTqzWRr7egNdvRWRzoLHKmSGu2Y7S50VsdGOx2Ckwm8o1G9JKFcHGQvt7TXLvQzcbcNE9XJnmxNs7L1UFerQ3xcm1YfU/2VofZXRrm8f2D2cJUbSnbyOZnUz2f6ve/3BhLKz57q6kzoKkuGpKHypIFand5f41Pqq0shPQIPgchPYIvQrL0pBu+ykZ40q33kVywnJzZSRSeZOlRvrQT/z1sOCC5o0nX2WQ6Jvk5+er/Q8Hr3uowz1bH4jHO3toEu6tTPFsd5+n9IXYX+9lbkotkX69P8HZzirebU7xeH2NvZZTdpWEeLgxw/1YXs9fOMzF4klMnqqiuKSESK8YV8OOJRIiUxgiXRAkUR3AF/HhDRXhDRTg8QbWOxumPYA9EsPpCGB1+jA4/kieMJ1KGO1wqTyl3BrB5wpgdfvSSG5Pdp8pOYmZHua+X3GokDn0pw2PKsJeSzVEKnZVaIYevCIPVo4qOkuHRmp3oLK648MSHsiQ7WotNHdpKDmXYK19vIVdrIldrUiVIuV1otKIxW8k3SeSZbRwz2NFYXOitDvxhL9VVRQz3neb+7UF2Fsd4tTbKm82xuCgM8Hy5nxfrozxbHefJivz4PlFN0R4+NT5FjFJJT6KwKPEp0pNOfBLrgXYX+w/sWyakR/A5COkRfBGOHjkib2uQYvuIVJmexMdT7XOUSXrUOook4dmX5VkfPVA7ka6o87ChgMM6n9dro7xZH1Pj1eoIrxKusF+sj/J2Y5w362O8Xh3nRVxWdpcHeXx/iCdLwzxdHuHp8giPlid5sjzB7soYj+8P8XhhgN37I+wtj/FqfYo3mxd4vTHNs9Ux+fiFEdbuDnD7uy4uT5ylu+M4VTVllJTFcAUj2Pxh7P4o3kgx/kgIZzCINV6b4/KFsToCGB1+dX0csyuI0RXE5AzIs7CC8mwtR6AYizskP+4OIdn9qqgk1vUoEpQ47KW3edFZPftCb/OqoTymldzobV6MDj+OQLFaAK3Ik9bsJE8nkaeTKDTa0VlcFBhs6hBWctYmWXYKDBK5WhM5GiM5GqMqO8rtPJ2ZPKOFXIOZHL2Zb7VW8kxuCq1eCiQHesmCy+vmeEM1Vye7mb85zMPlSZ5vXOTF5iAvV3t4s9rL6/URdleneLI6zd7KKHtxwX25OqK2A1WA1+Us4OuEx34u6Uk8bl97XR9TpSeT+KSTn+R6t1TSs7s6zNME8Ukc5hI1PYKfEyE9gi9CKulJNfU8eU+eTPtlJWd8kusKUmV5lH8TpSf5S/tjiz4TO4t0nZPyXOLziT//Yn0kHqM8XR5hZ2mIB0tjbC0MszE3zPrsEKt3B1i9O8jynX5WZgZYmxth5d4QK/eGWJsb4cHKNLtb3/Fs+yqPNy6ysTDGwq0Rrl3qZ7jvNJ1t9dRWlxAIB/GGgji8AblGxlOEyRmIT9n27RuSkux+jFYfJpsfk82P3upDJ3mx+YoIxqoJxqpxBOT1dMxOWYwS620SZ1UlhiI9kiu4b3FCJaujDE3pLC41A6SX3HGJsWGwenD4inAFinH4ipBcQQxWD/l6K7laC/l6q5pBKjRa92VsEiNHY+RYoYFjhQa+ydfxbYGeY4UGcjRGdegrMTNUaLGTb7STq7fyq0IT3+ok8gw2cg0WjumM5BvMGK02YjXFnDhTzXcXu1maGWdv/QIvNiY/ZBhXx3i+OsazlaEPUrKWOJvv40UnsY19TDtMfPzNxjhvNsZ5uTF2YIgrUV4Ss6WfKj3Jw1zpMrhCegSfg5AewRdBkZ5Uw1mZpqNnWmww8fjk558vD6Ws51GvUD9Seg6bsp6uQ0nuiJTanUTheR3PAMnDG3KB8qP7YzxYGGF7boi1e/2s3u1j6VYP9693sHiji9nrXczf6OP6pXauTrdy7UIb9270sjo/zvriJPO3+7h1tZvvLvQy2H+epsZaKspLcHndmG12LA4nFpssBTrJi84WQGcLxNeoCaKTZGmRXEFZdiweDJIXyR3B5o3ijVQQLKnBV1SJzRtVFyG0eorUmh6LM4DdG8HhK8LiDGCwejDZfaroKLKjzMJSipwTa3p0Fpf6eOIwmHK88hqV4mat2Um+3hof0nLEf95Brta0T2pSSc+xQoP6fKp6n3y9hRydRJ7RSZ7RyTGdiW8KtHybryFHYyTP5CBfcnHM5ORbk5dCp4fqpmp6ek6xsjDEm40R3m+O8mp5kL2VUZ4ujx4YTn29PsHr9YmMMvMxka30HBD3zXFebY4fGObKRnqSLwzSDW8lTn9P/lwn3hfSI/gchPQIvgjJ0okOsIcAACAASURBVJNJbg7L7qTL9CQPb6WaiZVOehK/uLOVnuTankwdzZuN8Q/Pp8oQrX4Y1niyNML23DCb80NszA6xfm+QtbsDLN/pY/l2L0u3e5m92cfd6z1cmWpjcvgEE0PNXJ5s5fa1Hmau9/HdxXbGhk4z2NfC2bOnKCmL4Q8FMNms6C0SRqsDk1UWCq3kRm+PC48zjNEeQGOWZcjiDmGy+eVVim1+nIEYnnA53mgVnqJKnKEyJG80vuJySJaehKnlyjRzZVaVkr1RRMYYH64yOvwY4kNdepsXkzOAySkPrSlDWxqLC0389RoTZn8pBc+KJBUYbOTrrQmzt2yq3ORojPuEJl9vUYuac7UmVX4S63gSxSdXbyVHbydHL2d78nV68rQGCvQm8gw2cvR2/rvGwn8rsPMrnZVALMrxUzXcut6pDl+9XBmW11jamFTb1osVeXaXLDzjH9rP+sgBkUlsSx8rPUom57BMz772Gj8mk/Sk+vxkmpGWSnrSbVMhpEfwOQjpEXwREqUnleQo0pJpCnqm/bMSZzGlmnmlfOkmDnUldjipQhmCOmzacKLYpLp6fr8xpsa79VHeb4zzPmEYYW99lCcrY2zN97Fyt4uF293M3R7i3o0h7lzr58aVXr6/1M2VqfNcGGtjbOg0QwOn6OuTo7//DAMDrQwOttHe3kBLSzVNJ8poOllNTUM1oVg5Nq8LvWRBazKjtzrkbRcs8srEytYMBpu8TYPG6kFr8aC3+jA7Q6rQ2AMxfLEaAmV1qvA4gqXx1ZaLsXiKsHiK5BWY3fJqzCZnQP4dVg8Guw9TPBtk9xWrYfEUYXZH1EhcvdnkCmN2R7B4itDZ/OSbXOQZneQaHBSanRSanehtXlWYlIUFdRaHOs1ca7arxcnJs7YSI3G2ljIkllzInGuwkGtwkGuSf7fOKFFoNlNokI/N0Ukc09n4Rm/k1wY9ersbq8tNY30509P9LNyb5tnKJO82Rni3OcTL1TFZdNan2Fse4+minOl7szHJ280J3mxkHsJKliFFVpLFJdUxmWp6UrXjVNKTbgg43efmwMWHcj/Nas17S4NCegSfhZAewRchWXrSpbOfLvaye79PjWdL8saOe8sD8l5H8R2tU80UyVSQfNhVZ6pi58QVclNJTuJsG7X4c21cXi15VZ6e/HpjlLebY7zdHOPNxiiv41fubzbGebE2zuOlcXbuj7I2O8DstfPcuHCW6ZEWhvtPMtjbTH93Ez3nG+lob6C9tZYzLdWcOlXJyZNVcpyo5uSpWk631HPyVB3VteVUVMUorYhQVhUjUlqE5HKisVjIN8pTtjWSA43FRaHJJdfo2ORsisbiQmvxyFs+2PzobH6MzjAWbzFWfwxHqBxPUSWeokps/hiOYBmOYBmStxizuwiLJ4rBEcLkimB2F2FyRTA4QujtQYzOMJK3GHugFMlbjN4eRGv1o5F86s/YA6U4gmU4Q+XYA6XY/CXYAzEcwVIcwVJVfDSSl3yTi2M6ObOis8mF1hZ3SF1XRy850RqtaIwWCoxypqbQaFdndn1YtPBD9il56EwJrdmpLnioDJspP6/8q5xbPb/JTKHRQIFBL09rd3kor6mi/dxJ5q/383J5lHcrI3K7Xh3mxeoEz9cn2V2RZ+q9XJ/g7cY4bzczD5UmZmbebk7ERWn8QGSSnk8tjFYKrVPJkPJZShSqw5aASF7ZWUiP4OdASI/gi3D0yJF9mZxfQnoy1RakEp/kq85spGdfB5TiKvzF2jgv1j8MTbxaH+HNxqgqPK/Whnm5McqrzXGerY6xvTjCxuwQ8zd7uHHhLJfHWxjqaeJ8ew0dZ6tpa6nizKkKWk5WcKq5jObjpTQ3ldPUWE5DfSnVlVHKysNyVBQTLQ4TjgQIRHz4iwK4Az70Ulx49HpytAbyTVbyjXbyDQ4K45KjtXkpNDspMMeHuuLCYnCGsfrKsAfLsMWlxBEsw+KJqpIieYvlYTFnGIMjtE94jM4wJlcEyVuMzR/D5o8heYtVGdLZ5N9l9ZXgKarCU1SFO1IZl54PwuMIlmL1FatZJ63Vp2Z9Ci0ezC55F3a7N6JuOqox2SjUW8g3mOMFyXZVVBKlJ3G4TZGe5NvJYpPuXFqzU649sjrQWmzkGszkGszkWew4/B7KKor5bryd3ftjvFwZlxcvXB2KD2mNyys6r09kPXyVSnpSic/HSk+65z9VejJNCEglPYlbWgjpEXwOQnoEX4RU0pO4NocqQEmyk0p6UtXvpPsSzSQ/ydKTKX2fapZWqtlY+zsJOeujdDYvN0bZWx3i8eogj1eG2JgfYvHWADPXergy2cFYfwvD3afoONvEmTM1tJyu4uSJco4fl6OxoYzGhjLqa0upqCimrDRK0O/DZrdikcyYJQmzJGE0W9CZTejN8nBWgd5AvtFInsFAXrz2JM9gI09vp8DsRmv1obcH0Ft9FFq8WH0l2INlWDwxjM4ojkg1jkg1ZncJkrcUqz8mi1CgApu/HJOrGIOjCIOjCLO7BLO7BIOjCJ0tjNEZxeKRjze7S1QBkofDolg8UTVrlCg9rnCFGo5gKfbAh13dlQ1OTZ4IemeQArNblTeTMyALkCuIweqSh6n0yrCWpBY5K1kb5bYyxV2pDUrM9iQWUessLvXnEuuTDoiTM4De4SdfclFgdZNrdpCrM6K3mGluqmDu+ggP7n8XF+Qh3qwO83Z9WB0GVYY+X6ylr99JFptE6cmU9ckkPdnWBqnZm/XRA1PbE8Un+SIj3YSAdCs8P18eEtIj+CyE9Ai+CJmkZ9+CgknCo8iOsr3C3vIHSUq1iGC2xcfpZpco09mVSJaZxA7n1WZy3cTIPuF5sTqhDls835xmb3OSB8vDbC4OsLHQz70b3Vyd7uDC6Dn6u87Q2XKC8y0nOdlUS31jKU2N5dTXllJdXUpVVYzysmKiJSHCkQD+UIBgOIzb68MsWTGYzOiMElqDhEZvQaO3UKA3xcMgZzsMZnmYx+yUi5etPgyOIHpnEL09iMUpZ2fsgQocwUokbykWTwxXUR2OcA0WT6ksPb4yHOEa7KFqJH8FRncMk6cUs7cMe6gai69cfSzxOb3zgxzp7RH09ghGZ1R9zOQqxuKJYfOX4wxV4QxX4AiVYw9+yDRZ/TE1bIFSbIFSjO4wWquPArObPIMNjcWFTp3m7kRjtsZnX1nVAud8vVVd0ydxbZ/ElZyTpSZxmKvAYPuQ1YnL0L6wyhKmcQTksHspsLjQmGx4Az66O89w5dIIj1emeLs1rmYC36wP8HZjUN6Xa238gPSkk5hPkZ5Ms7vSFUsfyGxmkJ7kmp9shSc5hPQIPgchPYIvQqL0JEpLJulRhCdZehKHt9IVGf8c0vNyI/1MrDcb47zamPzQiajDV/Giz9WxD9KzNs3zzWl2N6bYWR5mea6H+3e7uXH5HFPDrYz0nKajtZnW5kbamptpqqukuqaYqupiOaNTVkRprIhIUZBAxIc36MHpdsvCY3ViNFnRGixoDXHp0VnJ11jI18rSU2iQ148pMMprzmglNwa7T15bxx3B4AqhswUwu4swOoqwByqwByqweGJI3jJVeszeMqy+MlV6bMEqJH8FZm8ZZm8ZFl85zkgt1kClel8RnkTpMbmKMbmKVeHR2cJorSEKLQE0UhC9PYLJVYzZE0XylaiCkyg89mAZznAFznAFkq9ELXI+prWQb5RXSZZXf/Zhdnriu6U7963UnCgwibeVzUoTZSf5eOUYRXiSZanA5CDf5KLA5kNj81Fo88SzUU6cPi/NzXX09Zxl5d4QLzfGeLsxzvvtCd6sD/BmfSDelmRx/iWkJ122J9UwmJAewX9lhPQIvgjJ0pOqYHFvafBAlkeRnReJG2hmsSlotsKjrIicKZLT/vuKRuMFym83x+Q1WFTxGZcLU9cmeLI6zaPlSR4sTTB3Z5DrV87z3fRZBnubaTtTz8nmKmqryigvjRErLZHlJuDC63PhdNmQ7FYkuxWLTcJkkzBIFnQmM1qDhQKtkQKtkXydkXytidxCA8fydRwrNJGnMZKnkZ+TC3mt8ro28anl7mA5rnAFNl8ZRkcRjkAFZncMm78Cq7cSi7scyVeFK9KAPVKPq7gJs78Ko7cCa7AOe6QeW7gOW1i+rYTBU47BU44UrMHsr8Lkq8QSqEbvLkPvLsPsr8IaqJSFyR3D5CpB7yxWo9Aui5DeHpGHxuKS44pUYg+WIflKMLoi6JxhjJ4ojlA5Vn8MsyeKRvJSYHZTYHbvW91Zm7DGj7L4YXKdToHBRo7GrC5uqAx9KaFkhxIfTyVDeQYb+QaHPMvL4CTHKK/fY3B4MLnkHekDkSIiJTH6uk8ye6Of7YVJ3m5f4PX6CC9XB3m12oe86aw8xPVyY0xua5tKG5xMKzqZxCfxsWyHzTIdm+rzspckQOnEJzFTm+lzKqRH8DkI6RF8ERTpSV49+cA09KTsjiI7iZFOYLKZwZVqOm3yl7ayGu3LjdSdgdJxvN6cit8f4+3mKO8347Oz1uT1Vp6tT/JsfZKHy1Osz4+yPDvKje96mBpuZaz/FO2ttTQ2lFFZFaWkOEwoHCQYCeEP+HC5ndicdsxWC3qLCb3FLIdkwSBZ0ZktaIwm8nX6eDbHTKHeoi6w9+tCvbydgtZAvs6oDsVYHEEkVxF2bwnecDX+olrcgSosrhjuUA02XxU2XxV2Xw02bzW2QC3OaCPukuP4y09hCdVi9FVjDzXiKmqWI3ocRzykUD1aVzk6dwVSqB6TvwaTvwZruAGDtwq9pwpzoBZrSM4ImTylGD0l6D0lGLwx9J4SNM4iCm0htI4IBncxJm8xUqAUa7ACKVCO2VeKwV2MzlmEwV2sDoFJfnllaJ3NjzYuOoXxvztxqMpgTp/pUYa6crWWfZFYB5QoPoocJf5Mjk4i3+Ag3+AgR2slRydRaJE3K7U4fdg8QezuADaXn4bGCqbHzjN7Y5QXG1fkWp7VEV6sDPBqbTgu3HFxiUvP2zTZnXdbk7zbmswoP4dJj3JMKulJJUCJn5V0WZ/EQuZ0FyOZPq9CegSfg5AewRfh6JEj8vDVR0pPcqbnxerBGh51mCqpADLdVPXkOp1k0ckkPMnSI9+Wp6S/2xiR99eKz87a25hid+MC24sjLN7sYea7ToZ7mmk/Uc3ppnJqysNEi72EIy7sbhuSy4rNY0dyOrDaHZjtNoySvJigQbJistkx2JwYbE70Nhs6qxWdVUJn/jA1W1ls75jRzDGdLD06kw3J7cMZCMs7pPuKcQVLCRbX4i+qxltUizdaT7D0OP6SRlxFdfhKmvEWH8cRqsNTeopQ9Vmi9R04i09gizThKT2Fr7wFX3kL/ooz+EpP4S87jbu4GSlQiy1Uj7/8FJ5YM97SE0Tr2vGXn8JZ1IQzXC/X7MTrduyBSqy+ciRvGRZPKWZ3DEM8+6Oxh8mXAhRYgxjcxVj8ZUiBcvlff4Uc3lK5gNoTxeAKyUXZ9oA8w0vdZd36oaZHd7CQOVF8lK0slEiUnEKjnRyNmRyNXBidozFzrNCkhvJ4gcFGgd5OboGcfdOZzOjMVnRm64dVsCUvha4AVU3V9Pe3sTU/wu8ejPKnOyP8uDHA2/Vhue1tHsy+vNuc4F2S1CjSk0l8spGeVBmkdENkqYQnUXxSTVlPFJ1Ukw6SZ1cK6RF8DkJ6BF+ETMNbqRYbTLVbc6pNExOlJ90VY7qan4OzrUZTpvffpviyf7s5wdut/VfOSg3Qm80x3m1N8nxtmqcrUyzNDHBpvI2h3lMcP15LaXmUaEkIl8+J3W3D4rBhtEsYbBZ0dhMaswGNwYjGYIx3lhZ0Zgt6iw29xYbGaFFFSG+R5Blayno0xg9TtHUmG0aLG6e7CG+oDH+kgmBxLeFYI6HiRvzRBgIlzXLETlNUfY5geSuByjaK63soqu3CW9pKtLaHsuMDlDb34a9qxV/VSlF9J8WN3UQbugjXdOKv6iBU202wpgt/VQfBmi6iTX1EGnqINPQQOzFIpKEHf3U77vIzuEpP4oydwB07ibPkOI6iBqRgDZZANSafXBNkdMfQu6LkSwHyLH4KJR8WbzG2QCn2YBlGTwkmbywuPTGMzuL4DDG5dkhr9ZNrcHJMZ+NbrZUcrZVcnY1cnY0crZVjGkmNHK1VlZgPomNRFydUFjTM1Vv5ptDErwuMfFNo4ptCE99q929Qmqs1cUwjb2dxLF/HsXwdeVqDunrzsUKDnB0y2Mi32LF4vYRjJfT3t7EyM86D+9O83Znip+1hfrs9LLet9Qlerk3yan2Kl5tTqnC/2xrnh81xftwe3yc92WR9MmV6DssSZRr2UpdsSLq4SBSZ5NvpPutCegSfi5AewRchW+nJtIdPqmm1yWuHpKvxSZadz5WeNxvjvNsaV8Xn1cYkL+N7Jr3ZHOPd9gR7q1PsLk0yd3OAkf4W2tsaqaypIlxajD8axup2YbLZ5YyNxUyhxUihpKfAqKNAp6dAr0NnMqNXpUdSpccg2eXMj2SVC5WNRlV48vQmNAYJk+TB5gwSCJXjCVXhCVURLmmivPospZVtBKLNFJW3Eio7Q6D0LCV1A4QqO4jW9lB5cpyy4yOEq3sobxqh8sQIseO9ROrPU9zURfHxfspOjhBrHiJS34u3uhd/bT+BugEiTSMUnxgnemKUcNMQocZBoidGCTYM4G/sw13XiavqHO7KdtyV7XirWnGVn8ZefBxrUSOWYB3GeLbH4Cqh0BYiXwqgtQXUhRIt3mLyLF7yJR96ewSzqwzJU4EzVIXNX47kLUVvC5NrkFdvThSfHK2VXxWY+VWBmf8l36TeztGY+bbAKNdD6T5Ij7ItRb7eQp7Bxrca8wfh0cg7rucaPmTZ8rUmcjV6cgp1H/b70ujJ1WjJ0+rI0X7Y20tvtpBvktBZPVTU1TI5NcjN61Psrl/kx60hfrfdL2dT4tLzYiMuPRvTvN2ckqVna4zf7IymlJ50EpRq7Z7kLE86aTpsRlii9GRa3FBIj+A/AiE9gi9CJulJnoKeSnr2fXkeUkOQzUJomUQq8cs/0wyZ13HhebcxxbutSd5sT6grML/fnuLBwigrt/uZGjrDyeYayqvLCMSiuMMhHAE/JqcDvc2qhs4qoZUsaM0mtPF1dvRmCwazDYPZhtFix2C2ozfJ4pNvMJMbH8LKjRcrK0MwSv2O019KKHqcSNkpispPU1bbTsOpQRpODVLT1EN1Uy+Vjf2UNQ5T1jRKtK6f8uZRalovUHl6kmjDIFWnp6k7e4nq1kkqWkapPDNGZeskdeeuUNt+hfKWixSfvEDJqYuUt35HXdcNGnpvU33+GkUnJig5PUVl+xUq269Q0X6J0tZpSluniZ4aJ9A4SKC2G2/1efyVbfirWvGVt2ANN2DyVWJwln4QoH1T2+X9vuTVn2PxguiEWWHOsBoWn7whqkbyopG8FFo85Boc5OjtfKu1qis758T/7zQmecVqg9Ulr+xstsu7rJutFFrs8swso51jWgu/LtTzqwKd+h7kaXXkFGr2SY8S3xbo9+3inqMxUmgwUqA3kKvRopEcRMtinDzdxI3L3TxfHuHdxghvN6fkHdrXJ3i+Oc2rrQu83LnA250p3m9P8H57gndbYx8tPdnM/sokO+myPofJTrpIXi5CCSE9gs9BSI/gi3D06BF1Y8F9s7WSFidMzPokr4ScWDyZroYgeUHBTJFpqm6qdP6BjiAuPe+3Jnm/NckPO5Moqy8/X5/k3pUuLo+00NRQSjgawRMMYfV6MLucmJyOD5ITD51VQm+zYoyH3iKhM1vQmiQ1NHoLuYUG8uNDLjkaI8d0Jo7pTBSYHBhsfsyOsLrYn6+4nqLyM1Q19lDb3E9Tywgn2y/Q0nGZ053f0dg6Rf2ZCzSevUJ1y0XKTk5Rf+4ajR3XqT93jYozl2jovEFj102q269QefYiVe2XqOu8SkPPTRp7b9PUe5fj/XMc75/jxOA8bdPrnLu0xcmhBarOX6Ou+yanRxc4OTxHY/9tarq+p7b7OtWd14i1XqC4ZYzoyWGizQOUNPdR1NSFu/wMzpKTeEpOqHVB9kg9Zm+Zuv6PxRPF7InKQ1ruIoyuCHpHCK3dj8bmw+AKYfYWYfJFsfii6qKGZk8UozOEwRFEa/VRaPGoCxzqrT55V/l4IbTG4iLfZJV3VNcY+FZrVBd3/KbQxK8LPxSN5+rkmXJ5Wl1K6UklQDkFhRToDRToDfy6UE+hScLqdtFQX8q1Cx2szY7xZmuaV5vySt+vN6d4v32Btw8u8WbnIq+3L/Bqa5pXW9MfJT3pZnVlMyyW7vPxudKTrrZOSI/gcxDSI/giHD16hBcrw/9lpSdVB/Bu+0MnIV9xy0NebzbGebw0wZWxswx0NFBeEcEdCGL1+DE5nWpWp9BsosBkpMBkRGMxq9JjdtgxO+xx6bGqwqMzW9EaJHkaul5ecyffZCXPKO/+nWd0YnJFsPnKCMQaCZafIFzRQkl1J/WnRjneOsmp9ku0dF2lrfc67QMzHD93lcazVzjecZ369uvUtl3jeM8Mx3tmaOq+Q33HTZr7ZzneP0Nl+3dUnL1M1bnvaOi5RfOALDkto8ucGd/g9Ogap0aXOXdxm84rDzk9tkJd7wxNg3O0Tq1xenyZ40Oz1PXeprrrBtVdN6jqvE7F+cuUtV2g5PQoxaeGCTd1462Ua39C1e0Eq9oIVrXhKzuJPVKPFKzB6K3AmLDYockth8EVQucIoHMEMLhCGNxBtM6gfN8h7wFmcIZV6VH28pLFx0OhyfUh4uvt5BlsHNPJtTu/KtBxTGvhW42ZX+UbPoiQLr74o16eUZet9BzLL6BAp6fQYIxvZmpBY7bi9rvo6TjJ9SuDvNq6IMvNZlyyty/wbucibx9c4sXWBV5sXuLl1uWspCdVxiddMXQq+UmXGcokPtl+DoX0CH4JhPQIvghHjx7h5epISulJHNpKnn2VqtYm3Xo6ibOuMu0rlG6V5UyzVw4Iz9Yk77flYS1Zfsb5aXuEH3ameb4+yc1LXbSdrqWhLoY3FERrkzfJ1El2tJKEVpJ35843GikwmdBYLOhtNgx2uVbHaLWhtchDKlqLDb3kxGT3IDm8mG1udbsEvc1LoSSvS6ORglgDlbij9ZTUd1B5apCaljHqz1yktXeGc4NzdI4scn5kia7xVfovbNE2tMjJnrsc777L6f77nBxYoHV0hdbRFc5OrtM2scbZyXXOjK1Q3z1DffcdGnvvcmp0mbbJLVqndui4vEvX9y/ouLpH28XHdFzepfvaHq0XHtI8us6piS1aprdpHlujYXiRxpH71A7MUTc4T/3QAvV9d6npvknZ2UvEWqYJNg3hqenEV91JtL5HHvaqbMNbfgZfeQue0lPyFHh3BVpHKfm2EDpnETpnEQWOILlWH7lWH4WuIIUuWXoKJA95Rhd5Jjf5Jh/5Zg/5Zo98X7ltdJGrtZOjsfGNRuJYfPp5rt5Krt5Kjt7MMa1FzvDkyzU9OTpJXgXaZKPQJFFoMJNTKGd6cpVi5vgyAomhPJ6v1ZGv1ZGr0coF0Xoz32qNfFuowxsK0nyikZXbw7zavsKbnYuqiLzfktf12du6xLOtS7zYufpR0pNKaD4I/FTGjM9hs7uSxSfdGj/JxyV/jsXwluDnQEiP4Itw9OgRXq2O8HxpUI0Xy0P7bifHq9X4FPB1eW2StxvjvEmxIFqqq8NMxZSZvozTZnUS4v3WJD9sT/HDtlxU+m5rknebE7zZGeflxkW2Fsbo7jhOSawIfzCIzRtAY3aTb3CgkRzorXIo088NNic6ya6GxmylwGxVZ2FpTDZ0FgcGq1xnYnb4MUheNGY3BVY3esmPyR5B8lTgKmrGW3KKksZ+6s9eobHjOqd6Zzk3tkH39AOGrj6j5/JDeq88YuDac3ouP+Xc5A4tQ6t0Tj+kY/Ih56ce0nHxCd3f7dJ//QW937+k4+oeZy895sz0A9ovP6Hj6h6d117R8d0rOq++pfv793R//57Oq2/pvfGe7pvvOX/lOS2Tjzg1/oATo9s0Dq3SMLTK8YlNzlx+TOuVJ5wYX6d+8D41/bPU9tyhqvMm4eZx7NU9OGu68db04C7vwFXRhbu8LR5ncJeexh5txhppotBVht5bgc5bSp49wjEpyDEpSK4tRI4jQI49hD4+rGVwFKGRQuRZ/OSafeSYvGrkmz1oJB8FZg/HdDa1+FkNncSvNAa+0Uh8o5H4ttDCMY0sRQVmG4VGK4Xx4cc8rTwEmas1yUOQhSa1jicx8jXx4wpM/PdjGlmmCuRC6UKjFcnto7ejia3lCzxZm+L9wwvy6t8bo7zdGuf15pRc5/PgWlai8357ap/UKGKTfEy2kpQp23NYJItSqvo8IT2Cz0VIj+CLoGR6EmdsJWZ20q3XkUpOPkd6Mm2u+DFZnndx8ZGlZ5p3mxO82p7k6fI0y7eGaDtdSygcxO31YvX41Z26dZYPwmO0u9RQduXWmK2q9BSaJHUlZUV8lE0ttSYXBUYn+WYnelsYk6sEa7AOd+wMvvJ2Sk8M09j5PSe6ZzgzuEzn5DZ9lx4zdP05/Vd36b+6y+D3Lxm49oLuS085O75N76Vdui89peviE3q+26P/+5cM3nrL0N0fGLjzjt6br+i4+ozO68/pvfmOnuvv6Lz6mvNX39Jz4zd0X/+J3hs/MjTzWwZu/0TntVe0XdzlzPQTTk8+4uT4A05N7nDm0hParj2j/dozWi48oGl0laaRFZqGFmnov0e05QLO2j5cNb0E6vtxVXbiquzEXdmOp+Is7vI2XGUt+Cpa8ZS1YArWYg7WYA7WoHWXUeAoIc8eIc8eIdcRJt8ZxeCNYfLKhc46R5RCW0idFZZn8atT4rVWP4UWL7kGhyo732gkvtFa+EZr4dcaM99oJH5daNknPflGudhZa7RSoDNnlJ7Eqe15WoO8ZYjGwje5moS1fuThOppwWgAAIABJREFUMp1k50RzGXO3RthemOTdzsX4WlAjvN+e4PXWRLywObtMT7L0HJbp+RTp+RjxSV7oUEiP4OdGSI/gi5CqpieV4KSaWZUsKOmE59XmuBrJiwtme+WZqhNITuu/35ZXYn6/NcnbnUneb07zfusiz9Yvc/dKHxP9Z4jFwtg9bqxOF2a7C7PVKYf9w6wgWWLk0EoSGrO8I7jWYkNrlbNChRa7OmOowOSg0OimQG+nQG9HY3SiMbsxeYuxR2oJVJ0lUtdPpGGImvarnBtfo2N6h+6Lj+m9ssvAtReM3/6Rkevv6b3yit4rrxi99ROjt36i98or+r97yfCtt0ze+1PG4zGx8GdML/8508t/zoXV/5WRud8wMvcbRhf+nIF7f0bXzd/QeeMn+u7+BQOz/xvDc3/JyNz/YPjun9J/50/pvf0jPbd+oG/mR4bnf8fw/O/ou/cbOu/8wPlb7zh9ZY/jE5s0T25xenqbE5NrVHTfJtJyidCJCcLNI/gbBuSo68Nb1YG74hzuinNE6jqI1HXgq2jFXdKCJyYXP9uKjmMO1qNxl6NxlZLviJFvVRY59KOxB9E5i9C7ouhdUVV+lGGvXKOLHL08u0uZ1XVMb/0QOhvfam0cK5TX+lE2K9UZHWgNdgr1lpRZnUThydfLU9yVhQ4LdGYKdSY0Oh2FBr08o0uvJ0enw+mz0t11gltX+3mxeYl3W+P8dnuY3+2M8dOOnHl8vX3xs4a2UonPYfKT/Fg66TlsirtyjPK5Tf58C+kRfA5CegRfBEV6Mi0+mFz0mEp6MmVsDvtiTXdsuizP/vT/NO+2lLVR5NvvtyZ5/yA+ZXj7Eivzkwz2nOTE8Up8gQBWlxeL3YPR6kByOrC5XZic8V2/jRZ5irPeJIfBIEf8/jGdiRy9vAZMjk4iRyfXmHyjkRfYKzC70Vj9GJyluKP1hKtbKT8xRFXrRWrOXub08Aqjt94wefdHRm//yND194ze+onJuT9j9M7vGLj+Iz3XfmD0zu+YuPfnjNz5Df3X3zF297dcXfuffLf+11xa/isurvwVV9b/mstrf8W1nf+LyaX/nbGFv2Bq9f9gYumvGZ77Swbn/pILm/833+38v1zZ+X+4tPG3XFz/GyZX/09Gl/4nw/f/ktHlv2Ry/a8YWv4Leu7+lp47P9F157e0XHlF48QWTWObNI1v0DSxTt3QAlW9dyk99z2h42P46ofkqBvAX9uPr6YPV2UnnopOvJVdBGu68FWex1txDk95uzwEFjuDNdKEJViPFG6U9wzzlKBzF6N1RdE4i+TtLhwR8qxBciV5s9NCS4ACs58Ci5cCs1zcnG9yk29ykWd0kmd0xu+7ydM51H228g0O8vR2cnQSvy4w7qvbOVZoIDdhmnqi9BSYHPLWFQXywoUao4FCg55f5+ZxrKCQYxo932oLKK8pYWjoHE+3LvPmwSg/PRzlTx+O8dtHE/y0PRlvl5+e6Ul1TLbSc1imJ530pCuITv5ZIT2Cz0FIj+CLoAxvJRcrp1qQLJP0pJOfdF+w6Yoqs/0S/vAFPy3PmomLzw87F/lxZ5ofHozJq+HuXGT2zhAtLZWUlYdw+fxILj8muweLw43N7cLqcqC32cg3GlXJyTcaydXrOabVckyrJU9vUqeh5xrkFYBV4SmUF9LLNdrRO4MYPSVYww2Eas5R0jxAdfsVGntmON4/y/mLj5i49xNTs79j/M5vGbr5G0bv/I7J2f/B6N0/Y/jO7xiZ+TPG7v05E3P/H3vvFRxVgq3pdsecOHG7MHLpnTJTSnkLEt57772R9wYhBMh7pZUF5L3HFeULqoDCu8J7qK7uM2cizus8nImY7piYmPnuw1YmQoWrru7LuXHyj1ihVObOFA/snd9e619rDZFQMEhsbi/x+f0klRwjveoLMoxfkmn8mkzTV2RUfUV29ffEF58kOv8YcSWniC/9jJjCU8QWfUaK6YwAPMbTpJjOkGI6Q1LV18SVf0Zs2Sliyz8lpuw4O0qG2ZY3wOZ93WzK7mJVRguL46wsiK5i7u4y5u4uY8b2AqZt3k/k+izClycSvCCWwHnRBM7bRcjCKEIWRhE4ZzuGaRsxTNuI3/SNgu9n6hp8pqx+5f2JXIY+bCGa4HmoA2Yg94lAZpiMh1cYYr0QHtoQ3DRBuGmC8PAMfA16JJpAR4jHQJC70oC7TJjXY4ciV7meCRJP/uChYOII+LiOLH11lwo+HzeJADciuQqRXIVEpXNMgvYYaXkXyVVM9JA4DNHjxTJ8gwJZtmwBlUXxtFTH02aNorM6hm5rPB2WeJorX4eVD4l3QdGbjrM//pB29r8ls2r/jLHntRN6nPotckKPUx9Fv//97zhcEUV96c7XoqFsl6N+P/rx27qy3tWZ9S7oeZeJcizwNFbGjdqrJVyI203xgp+iKpGmqnjazQl0WBJpN8fSaY2iyRJHcsompk4NxN/fC4NfMN4+YXh6Bwvw46VFrhXa090VQunC3rnloVSOQI8EF4UMkVqLVOuNXO+DVOuNu8oLN6VQZpko80TuFYA+bBZ+05YTMnc701cnMXtDJou257EippLV8SY2Zh5m+752duZ0EZPTS1ROL9H7+4g9OOAAnaTiE8TmDRGXP0xy6XESi4+SVHyCpNKTZFm+YZ/tO7KtZ0gu/5ykss9ILP2MmPyTROUeJ67wFIllXxFf8gUxJZ+TYjpDQsXXJFSeJsV8nlTLDyRUfUtsxRfEVX5JfNWXxFScYnfpCXYXHWfXwUF27O9n695OVqU2sCyxhoUxRhbEVDIvuozZ2wuZvukgU1ZlEbYklaAFiQQvjmfa6gxmrN3D1FXpTFqaRNiSOPznbMd31la8p2/CK3IVXhHLMUxZSeCM1QROX4nv1GXowuYh95uG1GcKHvpJuOvChfAMdkCPuzbI4fGxA5B4BHpEKn/cFb64ygyvGZw9VELnnIfKwESplvFiDZ94CJOaXaQaAV5HfD126HEVCx1bIpncMW/Jvu7iTaWw8SIlco0n/sF+pCSu44gthfa6BFqs0XTY4mkz/3rgGQs1fwskvQt63ncOvinD44Qep/4RckKPUx9Fb4KehrJdDtAZ/XiskdEe9ovgh0LP2+5A3zRN9vX3xI/Eq2NajYKJtGUk29Nutkcc7eZY6sui2bJ1KUHBXmh1arx8g/DyC0drCEHu6Y1EpUSklOEmlztAxw4/7goFIpUKsVottLGrPJFqvZHpDIg1etxVXnioDIi1fkj1AXiHTiVkzkqmLhGyOwu35bA8qoB1iUY2p9exNfMQu3LaiM7rJS6vn5TCY6QUnyCl+ARJhceILzhKYtFxUko/JTZviKgD/ew+0EPUwV5icgeJLzpGStlnpJZ/Tmr558QVCdmd6LwTJJd9RVrlt6RXnSbNeIbkim+IL/+KrNoL7Kn5gfTq8+ytv0JW3WXSbOdINJ4m0fQNKdYzJJq+Jqr0U7bnDrNt/wDbDwyyOauL1emNLE9uYEliDYsSLMyPNQpZn53FzNleyOwteUzdsJ/Jq/Ywdc0epqzOJHxZCpOWJhG+JJHgRVEEzN2Bz8wteE5ehSZsKZ7hy/Cdslxoc5+2Eu+IxaiCZqHwn47EWzA7e+gn4aEVsj0iXSgifQgibRCiEfiRaoORaoMRawLxUPrhJvdhgljPOJGGcSI1LjKdA3rcFF6vurpGNquPLku6SpS4jACPq1iGi0jKRA8RLm+Y1Dza6GyHHg+ZHJWnmiWLJlFeGEVTTTLN1nhajDG0mmI/GHDs/29/7Wu/BXo+NKNqPz+d0OPU31NO6HHqo8gOPQ1lu34T9HxIR9ZoUHk33Lx7zURLVazDGG03MI/+Umgf9UVhLopi+cq5+PhrUetU6PwC0fqFovQKQKrWI1Yq8JDLHNkdkUqFq0wmlLQUCsQqT2RaLVJPT0RKoU1dqtYLgwcVXnhofJB7BaP2DccvYg6TF25k+opoZq7LYPGOg6yMKWJjioVtew6zM7uJ6IOdggm5YJC04hNklH9GetkpUktOklL6KWnln5FR+QVJxSeIyx9mV06vI2Lyh4jNP0pcwTESi08SV3SSmILjxBZ8SqbpO7Jt58mynCXTcpbUqtMkVHzNvobL5By6wp66i+ytv8Le+itk1PxAsvk7Uizfk1b9PUnmb4kp/4ztucNszO5ny74+NmV3szajlVWpTSxNrGNxfA3zY8zM3FnK3F3lLIqpZP7OUmZuLSBybQ6TV2YRvjyTgIWJBC6II2hhPEELogictxO/2dvwjFiLOnwFmrCljoyPz9RVeEcuQxe+AHXwHOS+M5B4T0HsHYG7LhyxfhJi/SQkXuGIdKGItSGIdcHI9aHI9aFItcGOTM9EiRfjRBrGizW4yvW4Kw14qHxwkekZL/ZkgkSLi0yPy6iypH1Xl30H1yvokTDRXcp4dykTPGSOHV9jY6JUiZtEjlgmYdIkPQf2bqW2UlhFcaQy+oMzNaPB5k1w8zGgZ6wR2gk9Tv295YQepz6K3gY9owHn7wk9o1tq33axfetroy7kTcZYmqriaTYmjHwxxDmipSqWNlsaR4wp5GZtY9KUMDTenqi8tKh9/JF7++Gh9hYARqV2bEO3LwV1lQrGZZFSg1StF9rXvbyEtnWF0K7uKvPETeWNRBuAJmAK+tDZhMxZyYyVUcxal8rcTftZtruI1XEVrE20sDG1ls1pDezIaiL6QDcxB3tJyB0kpfgEqSUnyaz4nL3mb9hnPc3+6u/IsZ0h2/ItaeWfk1R8UoiST4nNP0pM3jDxBSeILfiUmPyTROedIK3yW/aYvyfDeIYM8/ekGc8QV/YlKaYzZNjOsbfhMnsbLpN96ArZh644fk+znSOu4muiyz5jV9EpNu4bYsO+ATYfHGRddg+r93SyPK2VpSlNLEw4xOxoGzN2GJm+tYw5OyqZub2CyPUFhK/MIXR5NoFL0glbkUX4yizCV6QRtiyJkCUJBMzbhdf0zWgj16GZtBLtpOXoJq/AMG21sN09Yim6kEVoQ+bhGTwXpf9M5L7TkftNQ+k3DYXvVOQ+EcKGd+9JKL0nIdeHIdYE4aEKwE0hdHfZw1XhjYvciwlSHeMlWkc4Wt1HNrKP81C8yuaMKnONhh5XidJR6rKXu9ykKtxkAvS4isSoNWLWrppNVsom6qtSR7q2hJEJHwI9Qkn2l3AzGobeBj5/K/S8r1NsLPSMbTpwQo9Tv0VO6HHqo+h9mZ63wc6vmbvTWB71GtS8zXj5tjbb0dBjB59mY4IQ5iTaRkpZnWZh5USzKY5GUyqVBdEkxaxGF+CLSq9Dodch0euR6Ax4qIV5PBovH1Q6b0RKjaNDy0OhRqrRCUMJNcKcHqlGh1wjzHsRK0fKJApvPDwDkftEoAmeTeDMVcxcE8/CbTmsjjexNaOGnVlChmdXdgtROW0k5PeQVnac1NLjpBQeI2mkxLXX+BX7rKfZZz1Nlulrsi3fkmM7Q27deQ7UnCW37jz5hy6SW/8DB2rOs7/6HFmWs6RXnSYq9zjReSeIKzxFctlXZFrOkmU7T7LxNMnG06SavyOv9UeKOu+R1/ojB5tvsv/IDbLqLhNT+hXb806yq+gU0SVfElP+NTHlX7O18CQb9w+xJquXJcmtLExoYk50A7N21zF7dx0LYxtYkniYRfENzN5hImJtIaEr9+O7KB3fhRkELMkifPVeJq3OYtLKTIIXx+M3Zwde0zejnrQadfgK1OEr8Jy0FM+wxWhDFqELFdradWEL8QyeiypgFkr/mSj8ZiD3mYLMEIlYH4ZkJOsj8QzGQxWAu9IfN4Wfw+jsqvDGRWZgglTHRJneAUIu8ldb3ceLNQ7wGd3N5SKSCtked6kDhtxG/D32zi6Hx0eqwEUix0UkRSL1ICTYixWLp1CeH0ebNYMWUyIdlg/L9HRYEh3g8x8BesZ2kr3JA+SEHqd+i5zQ49RH0YdCz/tWTLzN0DzWJPmuLpN3dZ6Mfb6pKp5GYyKtpmTaTLG0m3bTaY6l3RRPmyWZBmMq+zI2s3XTYnR+gSj1BiSeejy0ejx0WiR6PWqfADx1/qg0PkiVI5OWFWokaq1jIrNkZBihfSChh1yDWKHGTarBTeGLhyYIpd80NCFz8Zu+iikrk5i37SDLE6xsyTrEzv3NRB9oI+ZgO3G5XaSXDXPA+hUHqr/hQPW35Fi+5YDtDIUNP1B4+CJ59efZV/0t+2u/J6/+PAWHLlJ86BIljdcoa7lJWctNSptvUdx4g4P1l8mpuUB80WfEFZ4ituBTEku+IMt2nn21FwU/j/Uc2fWXKGr/kby2mxxouc7BxuvsO3yVjOoLRJd8zc7CL4gt+ZIU6znizOeItZwn2nSW7SVfsSn/FGtyjrIqe4gl6V0sSG5jfkIzC+IbWZbYytKEFmZF1RC5pYrJG0oJXHYA78X78FuWQ9iabEJXZhK8PIPgJSkEzI/FZ/ZutJHrUYSuRBW6AkXgYlQB81H6z0UZMBtt8EJ0IYtQB8xDYZiJwjATuWEqYrvPRx2CuyoEd1Uwbsog3NWBjvDwDMTD0x8XpYEJcgPjZd64KH1xU/vjpvZnosLH0d5u3+RuL3HZ29nHu0sZ5yZxlLXsWR478Nihx02qEtrdxTLcpTJEchkKlYopk4LZnxlFi2UPrdbUEZCJc5iaW8zxtJjeDjd/i+dnLPh8SBfXu865sS30zpZ1p/4RckKPUx9Fb4Ke0aDztgzP2MGDRypfeXY+pAX2XVDzrrtS+4V9LPR0GHfRZd4ttKlbEqguS2Tr+jnMmRWO2icAqZcBsc4Lkc4LiZcBqcEbjW8gaq0fCpU3UqX21T4trZewi0sjrDDwkGscQ+qkCg0ihQ53uR6xNgS5zxS8Jy3Gf8Zqpq2MYcmuPFYnVLEpq5H4wh5Sy4fIrDrBPvMpciyfUVj3DZVNF6hsvkx542WKD1+k6NAFSo5corT5KsWNlzlYf468+vMUHr5IafM1KtpuUtn2I5XttzF338fU9YDy1tsUHLlO/uFrZNvOk151msSSL0go/pwM8/fsrf6BfQ2XOdh4nbzmm+S33GDfkctkH75ETsNVsuouk2o5R0zpN8SVf0ey8Txp1kukN1wj/fANMo7cJLX+OonVl4kxnSe68nu2FX3FxoOfsTbnOKv39rMue4A1ewZYntbBgrgjzN5dx+T1ZQStLiR0TSHha3IIX51F+OosItZmM3lVBpOWpxIwbxf6aZtQT1mHLGQpYt85SH3nIPWbjTxgLvKAuch8ZiE1zERqmInIO5KJnkFM0AQyQRWEiyoAd3UgYs8wJNpwZNpwIfujC0asC0SsC8RN7e+Y6CzAUCCuKj/cRrw+o8FnglglLCn1kDF+VFlrbKZndCeXi1jBRLGMP7iLGSeSCgDkIUOvUbN1/RJsJXE0m5PorPkwX8/YbM6vgaIPHXD4If650eeYE3qc+kfKCT1OfRSNhp7RGZ5fbEh/w0qJsdOWP9QY+SFm5Te9NvqYpqp4jlQl0GpKptUYTYdxJ12WnXRao2i3JVGeH8ecGaH4+OmRGwKRe/shN/gj9fFDZvBFZvBFrvdBpjEgVXuj0BrQePuj0vsK5auR9mSRQodYqRegSK5BIlcLwKMyoPQORx0wg4BpawhfuIP5W7JZm2RiU0YD23M6SCo9yp6qU+y3fU1+/XcUHjpLeeNZqpovUtV0CWPrdcqbr1LaeNkBPSVNVyg4dIG8+h8oOHSRwsOXKG2+RlnzDcpbb2HpeYC19zHGzvuUNN2kqOkmxc23yG+8wb7ai6RWnSbLdp69dRfZ13CZ3KYb7D98lbRqwbScUXuOnIar7Km9RJr1PEnGs6SYL5BmvkRc1VliTOeJtZwn3naBWNMFoqvOE2f8gXjjJeKNl4itvMju0rPsKPmG7cVfs6XgC9bnHGNt9jBr9gywIL6JmTsbmLG9himbigldlU3Q8j0EL88gZEUGoSsyCF6SRODCWAIXRuM/Zwf+UzfiE7EOffhKvMKXoQ9bijZkMdrghWiDF+IZPE8ocflNQ+EzDZnvVGS+U4WSlz4CqW4yHtow3D2DEelDUPhFIPeJQOIV/lq7u4vSgIvMgKvcBzeFN65yL1xkeiZK1IwXKYUQyx0Zn9HwM7Zd3VWiZKJEzDixmPFiGePclbiJtYikSqZGBJG3ZwsNlfG0mmM+2Mz8t8bfAj3vOwffNtXZCT1O/b3khJ7/xDpy5AiTJ0/mn//5n9m4ceNrr/37v/87W7duZfz48chkMmpqal57/d/+7d9YunQpn3zyCZ6engwODv6qvz0Wet5Wyvq1c3U+JJU++kL6rnbZsdBjz/SMhp420046LDtpt0TTYkkmd+9uIiMC8PLWIjcEovQJQOkbiMLXH4WPH/IR6JF7+qDQ+qLx9ndAj4dc4yhtiBSeSFTCtm4PuQaxXIOHwguppw+evhF4Bc8hZNYGIhZHs2hbLutTa9myt4ldB3pIKjlGWuVJcqxfOaCnoukcVc0XqWi6hKntBhXN1ylvukZZ41XKWq5T1nKd4sYrFBy66IjCI5cpbbpOWctNTF33sPQ8wtT1gIq2O5S33qa09TbFrbfJPXztNeDJPnSFg43XyT50xQE8WQ0X2H9YyPTsqb1EZs1l0mwXSTadI7r8DLsrvyfGdJ4E2yXiLBeIM/5AnPEHEo2XSDZfIa7qEtHl59lR8g1bCr5gw8FPWbfvGGuzj7I6a5AlKV0sSGhnQVwLs3ZamLQun6AVOQQszSBoaQZBy9IJWppK0OJEQpckEb44gbAFsQTN2Y1h6iYMU9ZjmLIer4g16MKXoR0BIFXgHJQBs1H6zUHqNxOZ7wykvtNQ+k5H5TcDmc80JIZIJD6TkflFCo+9woVZPyMLTMfL9EyUCn4fF7kXrnIvJkp1wv4user18JC9Fm9sW5eImSiRME4k5Q+uclwlOlylCgIDDaTFrcRUEEWrJeGXcGKKpcMimO/bTLEjP3879Lyv1PW2c/FDy15O6HHq7ykn9Pwn1qlTp/j8889JT0//BfRERUWxZs0a/v3f/53Hjx8jFov56quvHK/PmTOH1NRU/vKXv3Dx4kXGjx/PgwcPPvhv//73v+NIZRSHyndxqHwXhyt2c6QyisMVu1/7/V3bz99X1npXNmfs57zJT/Amv0GzMYEmUxJtlmTaTDG0mHbSaomi2RpPgzGZpNgNhIb6ozd44RkQgmdACGq/IKR6H1QGP1QGP9Q+ASi9AtD4BKP3Cx6Z26PDTapywI5YJSwWdVMISy1dZDpEKi/UXn74hkwlYPJ8Ji/YTOTSBBZuLWBTRjO7DvSRUCzM20mvPMU+yyvoKW+6QFXLFSpar1DefJXypmuOKGu5TkXbTUztP1LeeoPy1hsUN12lpPkapU3XKW+9RWX7bYyd9zF3P3T8LG+/S2n7XYpafiTvyHVyDl0R4sg19o/4d7IPX2LfkcvkHLrE3rofyKw7z96Gy+w7dI1U23lhdo/lLLurviPOdpHk+mtkNNwgre4aadVXSbdeIdV8haSqH4itOEtU2Wm25H/JhgOnWJE5xOKUXhan9LIso5+lGYMszxxgVWY3ixKPMDuqhsiNRUxel0vY6v2ErsgibMUeApanEboyk9CVmQQtS8NrQTyGhTEYFsbgNW8nimnrkUauQRa+ElnYMmRhyxAHLUHkNx83wxxEhhloQxfgNXkRukmL0YTNRxk8B4nfdMS+0xB5h+OiCmCC0hcXpYFPJFrGi/VMkHgxUeothMSL8WKh1X20v8dFrHDM6Zkokr+W8bGXupRyGe4SKS4SOZ+IlPxBpOIPEhlKvZJViyNIj1lBkynDAT4CiMTQahQmNneaY2k3Cnu67OWr0V1cv6bl3X7s6BLYm8DnfRmhd4HS2PPcCT1O/RY5occpSktLX4Oe//k//yf//M//zKNHjxzPFRQUsG7dOgD+9Kc/8U//9E/89//+3x2v79ixg717937w3xQyPbsd0HOkMsoBPaPjfdDzoVmg0RfcNx37IRdlYQ5PEq2mZDqtKY7py23WaJrM8VRXJrJ723ICQvzQ+nrj6RuCxjcQT78gdAEhAux4+yHX+6DwepXlUWgNQreWWu9YPipSeDo6ez5xlzNRKux0UnkF4Rs6i6Apy5i6NIpZ6zNZEWdiS3YXO0agJ73yFHstX5Fb/z0ljT9Q2nSBypZLGFuvUtUiQE9l21UqW69T2XodY9stTO0/Yum8i7HtRyrbfsTcfRdT912qOu5g7LzryPRYex9j63uCtfcxVV0PKOu4R3nnfYpafiS36QYHG6+zv/E62Q1X2Vt/hVTrWVIt35Jm/oaEii9JqvqaFNO3ZNZeIKvhMlkNl9lTf5kU20WSrRdItl4ktfoyaTVXSKu+SqrtCimWq6Rar5FqvUay5RLxVedJrDxPTPn37Cj8mm35X7LpwCnWZR9n/b4TbNw/zLrsflbv6WVpYiNzdgvt7lM3lxCxPo/wNTmErsombFUWISsyCFyWjN+ieHwWxGKYH433/F0Y5u3EMHs7uqkb0U3bgDZyHaqw5ciDlyALmI8yaD6a4HlowxehDV+COmwx2nChC0wbMk/Y7j4y4dlF4cdEuS8uMh8h2yMzjACQ0MY+UaJmgkQhxEiGZ+yurtEgJJFI8JAKRuYJMhWfSFR8IpYjkkuZPsWPretmU1OeRIs5nmZT3Miwwhg6LHF0WOKEsqwphi5L3Ds7tN63juJdIPRrmgbelt1xQo9T/wg5ocepX0DP/fv3+S//5b/wf/7P/3E8d+LECby9vQH47LPP0Gq1r32GzWZj0aJFH/w3R2d67FmdN4HP+8pb79vl8yboGZvp+ZA70ZYqYXt1m0kwMXdYhPJWq2k3bdZojpjjMZXFs2XjYvyD/dD5+qD1C3UAjz4wFJXBH4WXr2O6skrvi0rv69iwLlXrHY/dpCrHF944DwWuci88VD6ofcIImDyf0BlrmLM6mUXb89iU0cDug/1GXFyTAAAgAElEQVRE5Q6QUHycPaYvyKn+loLD5ylrvkhF62WqWi87oKei5RrGjuuYOm9g6riFueM2ls472LrvY+64g6nrDtX9D7H03h8xMN/D3H0fS88jbH1PHGGHntL2u0KZq+mGAD7NNznQeJP9jdfJqj1PmvU0qaavSa78ivjyL0is/EqY1DySFdpbf4XM2itk1Fwm1XKRZOtFkiwXSDBfJM58kVjTJRLNV0g0XyHJfJFE0wUSTReIrTjLzqJv2Jb/JRtyTrIq4ygrModYnTXEqj0DrMjoE8zO8YeYE13DzJ0mpm8tY8rmIqZsLGDy+v2Er93HpDV7CV2VTvCKVIKWJRG4NFGIhdEELIgicP5ufGZuRTdlPZ6TV6EOXYImdBGeYYvxiliOJmwpmrCl+ExZjW/kSnwil6EOnIPcMBWpdwQiTSguCj9c5b4O6BEyPtpXnVwj0DPOTcI4NwnjR7Wujw2RRIK7RIqbRI7LKOhxlYgJCfZk1eIIjIVCt1aLOX5ktELcSGkr1gE93da3G5U/ZAeXE3qc+v+jnNDj1C+g58qVK7i4uLx2zNmzZ5FKpQD09/cTGhr62uvt7e1MnTr1rX+jrKyM3//+94743e9+x+9+xy+CtzzvDGc4wxm/+x1O6HHqN+l3H/sf4NTH19syPf/3//5fx3MnT558LdOj0+le+4zq6upfnelprIr+hafHnuk5UhlFY9WHmZff9tpYE/K77kB/bXmrzZRIm0m4a24xx1NdFkdG8gYmR4ShMvihCQjCEBaBd3A4Gt9APFRaxBo9Mp0Bmc6A0tsPtZefw6wsUemQabwcrer2koarRImrzBOZLhC59yS8whcyZWks87fsY0f2IaLyu4krGiSl7ARpFZ+yx/w1B2rPkH/oHEWNFyhtukBZ80VM7Vexdd/E0nkdU+d1agfuUTtwj7rB+9QNPKR+8BENQ4+pH3xEzcAjqvsfYu17MNK19ZDq/sdU9z91hFDieiiUwDpvU9l+m4rOO1R23aW86y5l3fco7bpLZc99qrrvUtl1h9KO2xS13iSvWWhnL+q8R0HHXfKablHaco/Cpjvkt9ynoPUBeS33Sa+7QaLtCgm2a6Q03Ca94TYZtqtkVl8jwyb4fVJMF0k2XiCx8jyJFeeIK/ue7cXfs6XwDFsKTrOl4Au25n/GlrxTbNw/xLp9vaza08n8uHqmbatk6uYSItcXELH+IJPW7mfKplymbcpl6sYDTFqdRfjqDCJWZxK2PJXQpYmELEkgcN5OdJFr8Jy8Cu/ItfjO2Ixh6ib0kevwm7oevymr8Z603DH3R6KLxF0VPDLM0BdXuQ8TZXpHectFqmGiVMlEqfK18tboTI/dzOwuUyNSeDoygROlSlxkKsQaHTKNGqWnHP8gL6KjN9JoTqajJoNWY4Iwp8eaSNtIxqfTat8T9x+/vDU24+OEHqd+i5zQ49RbPT2PHz92PFdYWPhOT8/OnTt/tafn7wU9H9K99a6L8YcAz1joaTcnjXS/xNBsScBaGktS/BrCwoNR+vqjCQzGO3QyuoAQlN5+uCk0iDV6oXNL74PaJwCtTyAyjZdjr5bd0OwhFxZS2qHHTa5Frg9C6ROBb+QyZq5JZdmuQqIPtBJbOEBs4QCp5SfJqPqMbNtpcuu/p+DweQqP/PAa9FT33MLadQNL903qBgXgqR964AAee9QMPMTW9wBb/0MsPQ+o7n9M7eBTagefUzv4nJqBZyPw8xhL731M3YLnx9hzH2PPfcq77lLadZeyzjtU9t5zQE/5yHNF7T9S2Hab4q77FHbeo7D1DuVtDyhuuUdB6wOKOx5T3PmEnMa7ZDbcIrXuFhmN99nb9IDsupvsrbvJnprrpJovkVh5noQR2Eks+46YEgF2NuZ9w8bcr9mU9xnbCj5nW8HnbM07zqaDg6zb18vipEZm7TIzY2vlKLPzPiat3U/k+v1ErMshbNUegpelEbw8haDFiQQsiBFi3i50U9ajn7IWnxkb8Z2xGf3Ujegi1uIVsQafiJVC+3vwQlT+cxFrI3BXBeOhDMJd6eeY0vwm6Hmbj2f0Hi47GNvf4ypXIfHUo9B6otDI8fbVsHnLKo6YkhzQ02iKo9mSIJS6LPF02QRof9saijd1Z30M6Bn9WU7ocervISf0/CfW//7f/5u//vWvFBYWsn79ev7617/yv/7X/wJg9+7drF27lv/xP/4HT548QSqVvta9NXv2bNLS0vjLX/7C5cuX/6burSZjzBu7t+zA01j1S9D50LvC0bDyJo/C++JNn2GfbttqTEDYuh5NqzGGJmsyJXk72bl9KcGTwlD5TUITOBmNbwASnQF3tQ4PlRaZzoDCyxeFly+efkFo/YNR6nwcfh47/IiVWtykGke3jkjpjcYQgTZ0LpMW7WRpVAkbMhqILztKUuUJkiuFDE+O7YwwZ2cEeIqbLlLecomK1suYO65R3XOL6p5b1Pbdpn7oviMahh9y6OgjDh99SsPQY2oHhagZeELNwCNqBp5QN/SM+uHn1A8/p27oBbWDzx3QY+65h6X/EdaBx1gHHmPpf0RFz10qe++9Bj2VXXep6r4nwE/HPYo77lLccZfC9nsUtD+goP0BhW0PyWsXIrf9MQfbHpHd/JCMuh/JPnyborbHHDxylwOH75BVe4NU8yWSjRdIqDhHbMkZYkrOsLP4Ozblf8mGvM/YsP8EWw6eZFv+SXYWfsqOwuPsKjzGuuweVmS0syK9lcXJh5k34vmJ3FjkMDoHLd9DyAphsnPA4mQC5scSMD+WwHnR+M7Zhu+srRhmbMEwTQAeRchS5MFLUAQvQBW8AM9gYZ+X3Hc6Is9g3FQBuCt8he3sUp1gYhbb4UXBRKkAO/Zsz9h5PR5yDSKFJ2K1Nx4qLe5KT1zlwt42sUaH3FODm1KJWK1m9tzpWAqiaDUn0WpOoqkygS5LiqNTq8OSONK2nvCLeBPIvOm4d71v7Ln0a8+/sbA12o/nhB6nfouc0POfWKWlpQjemlcxd+5cQJjTs2XLFsaPH49UKn3jnJ4lS5bwhz/8AY1G8zfN6RkLPfY4UhlFkzGGJuOHzd75kItmmyn+vce/CZJea8u1xDugp8OUNPKlEUuTNZkDezaycvUMdP7+iPVhyLzDkOn1iNQ6pFpv1D4ByPU+jsdKbz+kWm/cFTrhi2ukbGHftyVWahHJheWSYpUBr6AZ+E9bydwNmWzMPMSu/G7iKz8lxfQ5e6zfkttwntwGYU9WUeMFSpovUdl2BWPHNUyd16nuuoGt+ya1/beoG77NoaH7HBq6T93gPRqGH3L42GOOHH9C/dADagcf0XD0GTUDT0bBzxNqB58K4DP4gvrBFzQMP6dm4BG2vgeYeu9j7nuApf+hEEOPsQ4/oXroCea+Bxh77lHZdRdT7wNM/Y+o7H5IUfsdijtuU9b3mNzOh+R3PSG/6wm5HY840PqQgo4nFHY+JbflMfsa7rC35hbZNdfJrrvJvoYfya67SVbNdfZUXyPdcpl0y2VSTReJKTvHrtIzRJefIb7iDLFlXxNT9iW7i46zK3+IXflDbNk/wKYDw2zcP8TqPZ2syWxnTWY7y5MOM3tXJTO2lzF9SyFTNuYRuX4/4av3ErE6i4iV6UxemUrkymTCl8bjP387hpmb0E9fi2bychShi1CEzEPiNx2F/3SUgdOQ+UUi1obgrg4UFpQqvEe2sGsYJxLa1V3Ewj4te5v62CnNoyc0u0g8cVfoEKl1iJQa3ORyXOUqxEoFLko1Lko1PsF+HExdTkPZLlqtKcIUcYuwM+7VstxXADR6B9eHxrve865M0YcCz9jPsp+/Tuhx6rfICT1OfRT9o6HnbSn3X3uHORp6Oqz2i3AiXZYU2kwxtFliOWRKIj1xDYsWTUHl5YOrJgAPT3/Enp5Itd6oDP54+gUh0xmQeHqh8Q1EpjPgJtcyzkPBJx5SxovliBSeyLVeKHTeQrZHJpQ73JXeeIXMImDmOhZuy2HbvmaiiwZIqjpFhuVL9lafIf/wBfIOCXu0SpovUdYqAI+l+ybWnlvYum8KWZ7+W9QP3+XQ4AMODT6gYeA+DcMPOHzsEUeOP6Zh+CF1ww8F6Bl8POLveQU+dUPPqBt6Qf3wSw4de0nt0BOqBx5h7LmHqfe+A35qhp86wjrwCGvfA6q672Hue/ga9JR03qFi4Bl5nY/J7XpCbtcT8jufktfxhPz2x+S3P6ag9Qm5Rx6QXfsjGeZLpJkvkW69QsZIpFsuk2w8T0L5WeJKv2Nn0TdEl31HXNVZUsxnSTZ/R7LxNNElJ9mRO8D2/b2syWxnZXony9PbWJhwmOUpTaxMa2FZyhHmR1uYs7uKaVtLmLR2P2Gr9xGyIpPQZWmELE0lbHkqU9dmMnV1KiFLovCfvx2fWZvxnLLKAT0in6lIDJFIfSMQG8IRa0NwG9nK7ir3GYEez9egZ7SHZ/R05rHrKcaLBJ+Xu9ITkUqFq0zGRKkCD7kMF4WGCXI1ah8v0mMWYSncSbM1lSaTAD1tlmSaquJHlpIm0mlNotOa9E74Gfva2+IfCT2j3+eEHqd+i5zQ49RH0djhhGP9PHbo+TU+gNEX2DddgJtNQrSY4x3xpiFrbw2L/fUkumzJtFhiaa5OxFSaxMbVC4gIDUOi0eCi0eKq9kSm1uAdGIIhKBSZzhup1gulty+6gBBken/clHrGidSINXrEGj0StZDdcZfKmChR4yrzxE2pR2oIx3fKckIXbWdtUhkxBd0klQ+z1/YV+2vPkHfoHPmHzlHYeJ7SpgtUjACPtecWdf13qB+4S03/Her67lLff4/D/Q85MviAI3bwGRbi0DEBgOqGH1I7+IjqgUcjpa6nr5W3aoZeUDP0gvrjL6keeoKl/6GQwel9gLnvIbZBIcNTPfQE2+BjqgeEz7L0P8Lc95Cq3gdUdD2grPsB5T33Ke97TnHXSwo6X1LU+YKC9mevR8cTCtqfUdj2lJz6OyRX/UBC+VmSKs+TXPUDiZVnia84Q7LxPElV5wSPT/l3xJadIb7yO5JN35Ns/o64ss/ZWXCUrft7WZnWwqLEwyxIqGdOlJmpWyuYurWC6dsrmLK1hMgtxYSuOYD/siwCl2XiszAF3dw4dPNi0c+NQjtrB9pZOzDM3Y3PnB34z92J3+xt6CLWog5dgtRvNmKvKXjoJiMxRCLSR+DmGY6LJgRXdSCucl8myvRMkHgKayhG4GYs+Ixzk/CJq5j/Z6IHn7iKhePEwjGuUgXuchXuchVuCjVSlRo3lRYXuRaVTsvqFTPZn7mdBmMa7bYkumwJ9FYLi0hbjXG0WZId0DM27BAzGozeBEe/NjvUZop/7fwbfR6OvjF5l2fICT1O/RY5ocepj6KxRubRc3p+K/S8LdU+FnpaLQmOaDG/Od0vxEiWxyZMYm43JwmfZY2n0RpPTvomZkQE46X3xl2mZrxMhodGhbdvIL5BoXgFBAslq1HdW+5KT1zkWibKdbirhVKFRCkAj7tUxkSpEpHKC4nOH03wbMIWbWHW+mS27bGRUnGUPZYvOFj/PfmHL1DU9AMlTecoafyBkpaLVLVfFUpafbepHbhL7cBd6ofuc2jwAYcH7nO4/yGHB+7TMHB/BHoe0jD8kNqjd6k/9pDaoQdY+u5h6b2Ptfchtr5HVA8KsFM9/JLq4ZfUDr+k9uhzbINPsA48dgCPpf8R1UNPqTv2gtqjz1+Dn5rBx6+Djz36nlLR+xPlPX+kuOslhR3PKWh/Rn7bU/LbnlLY8dwRxR3Pya79kUzrdVJNF0msPEtCxffEl39HbOlp4srOEF91nrjKc8SWnSG65FviKr8lrvJLoopPsLPgKJsP9LIqo4VFSYdYkFDP7Ggb07cLwDNjRyXTtpcxdVspkzcVErG5iKlbipm2uYApm3KZujmPKZsPMmVTNpEb9zJt0z4i12YSuTpdKHfN2Y5h+gY0YUtRBM5DGTAbmc80lP6zUAXMFnZ4GSLxUIfgItMzTqRhnLuSiSJ7vDItu0qUjjLXJ67iV/N7xDJcJHJcJPLXwUemdDz2UKiZNSuMXbtWUWNMo8UkwEuPLYEuczztpvi3Qs/Y//8fCj3vygDZP6fdnPDW889+fjqhx6l/pJzQ49RH0WjoGW1e/o8IPZ3WBDqsCbRZE+kYgZ4WczwttgQOWeJJiVtJqL83nhotblIVExUKJDpP/AJD8fYPQmPwQ6TUONrWxRo9Hko9rgodrkovRCNGZ5FcgYdMjodMaEMWaQzIvYPQh88nYuku5mzKZNveOlIrj5Fl/ZLchrPkHz7vgJ7SpguUtl6iqv0q5q4bDuipG7zngJ6GEehpGAU99UNC1A7fp274ITWD9zH33hUMyiMt67aBZ1gHn2MbeuGImuFnDuixA4914DE1w8+oPfqcmuFnVA89dYBP9dBTh9HZ2PeQyr7HVPY9pLL/GZV9f6Si9ydKun96I/QUdb6gpPMFxR3PyT3ygJz6O46ylj3DE1d2htjS0+wq/pbtBV+x9eApNuWcYGveCbblHWd73hA78o6y9eAAWw70s3ZvFyvSW5kXW8fsaBuzos1M31VFxNZSJm0uJnJLMdN3lDNrZwUzd5Yyc3sRs3YUM3NHIdO3HGDalhxmbNnPtPXZTFubReTKZMKWxhI0bztekavwDFuMNnQBqoBZqIPm4hk8D03ALJR+0xDpwnGRGYQSl7sSF7EKl5HdW46uPanK0b31WplrDPS4yZS/CHe5iogIP9avn4+lPOWjQs/YY53Q49THlBN6nPooskOPY93ESLeWPZqMMTSbPsyD84suq7f4AUZDz+gLrv2ia7/Aj71Qd4264HdaUxxdMC3VyVRXxLBu1XQ0SilSmXB3rjB4oQ/0wxAQjFLrhYdCzXgPCS4yFe5KT6F1XeeHTO+PVOeHxNNLyPxI5EJ5S65igsQTkcYPmXcYXpFLmLI6nkU7D7DzwBFSq447oCe34SyFh85S0nSOspYfqOgQsjyW7ptCSWvwngN6GgbvOWCnvv8e9f0jc3oG71MzErWDj7ANPMDSex9LjzCnx9z7GGv/U8z9T7EMPMPU9xRT3xMh43P0OdVDT7ENPhkpaz2lZvjZKOB5/XfL4BPM/U8xDghROfCUqoGXVPX/7ACf0q7nlHQ+o7jjqSPszxW0PKSo7TF5TffZW3edDNtl9tRcJavuKum2iyQbz7Oz+Gu2FXzBlgOfsmHfUTYdOMqWg0fZkXeU6OJP2Zl/jC25Q6zJ6mJ5WiuLkxpZEN/A/Pg65sbWMHO3hRm7zMzYbWR+rI0FcdUsirexJN4iRIKZ+THlzNtdxPzdRczckseMjQeYvj6L6WvTiVyRSODcbRimrsErYrljaakqcA7qwNko/Wci9Y7AXekneHs8VEwUCeAz1rhsz/i81souljFBJGWCSOqAn7HhKlWgN6iYOTuc0vw4Wq2ptFtT6LIlCBBvTvgF9LwLZn4L9Iz+G2+DntHg44Qep/6RckKPUx9FdiPzazN5jDGvWtVNsR8MPe8yIY+FnrEX2zZrouPx2Av0m6LLmkSPNYmemmSOmOMpztvOjBkBSKRiXNyleMi1+IQG4RMahFTliYtIyjh3MePcxbgpNIjUOuReASgNQSgNQUh1fog1etyVGlwkcjwUatwUGsZJdbhrg5D5ReI7Yy2zN+1hZXwpUQVtpBlPsKf6K/IOn6XgyDmKG89S1XYRY+cVLN23BONy74/U9N9xlLdqR3w9NSMeHzv01A7co7r/AdX9wlweu/+mZkAAGNvAM2wDz7AMPMMy8Bxj/zOq+p5i7H+G7dhP1B5/SfXR59iGn/0irENPXwvLwLNXsNP/bFS8oKr/J6r6f6Ky/ycqel9Q0fuC8p7nlPc8p6z7GaVdTynueExe8z0K2x5S0PqAA0dus+/QDXIO3yTn8E32HbpGVt3VkTUWP5BoPEt81WniRjq4oopOEVV0kl1Fp1izp4fFic0siG9kbswhFic1sjSlmeVpLSxLbWZZajNLkhtZEFfLwvg6liY0sCSxhiWJNSxNsLIwtor5MeXM3VnMtA0HmbbhIHO25jN9fZZgcF4Ug8+MjXhPWY1u0lKUQfNRBM5B4T8Lmd90RPoIxJpA3JV+TJBoGeeuZLy7/Bem5dHhKlEK85vEMsf/KTv82LM/rlKFIyRKOYEhBvbt2UmLNZOO6j10VSfRZUuk05JIm/X9WZyx4PI+6Hnf+dNhSXwj8Dihx6n/r+SEHqc+isZCj72cNTrL82uh530D094GPXbwedtF+7XnLYl0WxLpqUmmriqOvJxNTJrkjau7Oy7uCmQaAz6hQeiDfPCQKRnvJuIPrh7Cl5CnF1KtN3KvAOReAcj0/og0BjxUWlzlKgF65BrclZ5MVPgg1oehCpxJ0PwtLNqdy8Z0KwmlfaRbTrG39hsKGs9T1HyOkqZzGNsvYem6irXnR2y9P1Ldd9sBOfawP1c7Aj32qcwC9AjeHUcMvoKe6sHnWAdfYB18gWngOab+l5gGnmM9+hLr0edUvyFeg5/B51gGngkZnv5nGMcAT2XfSyr7XgrgM/DyFQD1vXTAjx167BObC9sektd8j4NNtznQ+CP7j9wi5/B19h26Rmb9NdJqLpNqO0+i6TsSqr4XWtdLviSu7HN2FZ1iY84gKzO6WJ7WwbLUdlZldrAmq4vVezpZkd7KivRWliQ3Mj+unoXxdSyKrWVhrI0FMVbmRlcyZ1cps3YUM2NLPpHr9zN1/QFmbjrI1DV7mLxSgB7fmZvwnrYew9Q1eIYtRhW8AIX/LCQ+UwWDs2cQInWAI9sjgI/0tYnMo4cTOkpeY6BnvIfkjdAjViow+HuRnryZI+b090LP36O89b7z533Q02KOd0KPU/9QOaHHqY+i3//+dzSbYl/L8thBp8kYQ4s5jhbz3yfDY399dFrdDjujoedtafrRF+xuSyK9lgS6q5OwlUWRnbkO30AtE92luEn1eAeEo/f3RqlXM97NnU9c3JngLkah80bjG4jaJwCF1oBY7Y1IY3CsEXBMYJarcVPqcdcGoQ6ZiWHaUqavT2VtqpntB5tIMR0nq+Zr9tWfpqhZMDFXtJ7H1HYBW891zL23qe77Zdh6X8GQPetTO3DXkeGx9j7E1vOY6l5hmai597GjnGUefIFp6CWmoZdUDb3AdvSPWId/omrwGVWDzzAOPccy/ALbMSFqTvxE9fGXVB9/ifXoS0yDzwRYGjm+auA5VQPPqRx4KWR5Bl46wMc0+DPm4Z8xDf7sAJ/ynueUdTyhpO0R+S33yWu+58j4FLY/IL/1DrkttyhouU1+6x1yWm+T03KT7MNXSa/5gYzai2RUXyDT9gPZdZfJrr1KkvEsUaVfsrPoM7bln2RT3jE25h5lQ84ga/Z2s2pPJ6v2dLJ6TwerMttZmtLE8uQGliTUsjDOyryYKuZEVTBlSwFTN+UzfXMeUzfsJ3xFBsFLEwmaH4P39M14T92A94yN+M1Yj8/UVaiD5iLznYHEewoiz+CRbI+BCRKhfX30nJ4Jotfn9LjL1MKKEomc8R4SxntI3pnpcZHLUeg0bFi/EEtJEk3WTHqqU+ixJtJdLZRo3wc97wOiv6W1fewNh/38G93N1Wp585BEJ/Q49VvlhB6nPoo+FHredcf3IWH3/LSZ4l/L9Pwa6Bn9fI81if6R9l9z8U7Skpbj5aPGTapB7hmA3i8UkVKCi9SViR4iXMUyPBRqFDpvxwoKud4HsacP7iovPvGQvvqSGtma7abUIzFEYpi6jIB5G5i+IYNlCZVs2NNAUtVRMmu+Jqf+O8rar2Dpv0n90I/U9F6luu86xu4bWHtelbjGht3nI5S8hCyPPbtj6X6Mpfsxpu7HmHoeYep7gmXgOZaB55gGnmPse0FF33MhGzPwHOPAU8xDT4VsztHnDtCpOfETNSdfOuDHPPQc89AI9IwAj3HwJ4xDf6Rq8CeMgz9hHfoZ69DPVA/+Cevgn7AM/Iyx9yWV3c8p63xMSdsjiloekN9y3xHFnY8o6XpMcecDCtvvUdx+j6KO++R23CG34w4HW26R03iDnMYbZDdcZY/tEntsl0g1niOh6nsSzedJsp4j2XKWGNNpYo3fElP1FVEVX7C7/HN2FJ1g/b7ekQxQB2uz2lmd2cqajCbW7mliTWYjS5OrWRRrYn5UJbO2FTJlfY7QzbUildBFMfjP2Y52ylrB3xO5Cn34IjTB8xB7RSLSheKhCcJd4etYSeEqUb9xFYWbVOWYyOwmUwqDDMUyh79nrLnZVapggkKFu1rJtGkBFO/byuEqwcPTbY2npyZVKNfakn8R7ytPvatd/V2ZIHt8CPSMHifhhB6n/p5yQo9TH0V26BlrXH4f9LxtTP77oGdseWss9Lxr6uyboKfNFEv5wS0kxCzC00uNSKFDrvVHpfdngsiFT9zHMdFDhJtMiUipEfYlqbSI1DpUBn+UhiBken/GiaSOFmM3mZLxEjUuCj0i70h8ZqwkZOE2Zm/bx5o0K1v2NZJmOcne2m/IaThDadtlzH03qBu8RXX3Vaw9QteWrfsmNvtQwlEZHkfJa+iew7j8CnqeYO55hrnniQN6jL2PMfc/w9z/jKre51T2PKOi+ynlvc8o733mgB7r8BOsx545oKf6+Etqjj+n5vhzR7bHMiyUxoyDLzAOvsA09EfMw3/GOPRHTEN/pPron4UY+tkBPVU9L6jofkppxyOKWu9T0CZEYfsDCtsfOKCnpOshxZ0PKOq8R1HnPXI77pDfPgp6Dl8nu+E66baLpJt/ELq8yk8TbzxLgukc8cazRFV9w+7Kr4mp+oroyi+JrvySncUn2XxgmA05fazd282GfV2sz+5k3d4ONuxtY/3eFlakNrA4zsz8qErm7Chm9vYi5m7LY/bmHKavTWfyigT85m5HP2Ut2knL0YQK0CP3nY5YPwkPTRCuMgMuMh0TpcL6kbHGZXuWRxrkW6AAACAASURBVKTwRKTwxF2ueg2U7fAzOlwkcsbJFEyQywkJ8yYvaxP1VUl0WlME6KlNoaM6me7qFEd8KAC9D2reF28qLf+a89oJPU79Fjmhx6mPIgF64misiqGxKoYmY6yju6rJGOu423tTm/m77ghHd22NvpC+7W5UaEN/N/S8Nm/ELLT8dliSKcnZyu5tC1FpFYiVQju6i0TOBJELE8WuuNkHyI2UJRRaA2ovP1QGf6SePog1elzFMtwkQpu6m1QlzO3RBKDwn0Xg3PVMXrabxVF5bNt/hNjiTvbWfM6Bhm/JO/Id5R0XMXdfw9ZzXfDzdF6huusG1s6b2Lpujfh7br8Wlt7b2PrvYht44OjSMnc/xNLzCEvXU0zdTzH2PMPY92IkoyOUoEabi0u7n1Ha/YyK/hdUDj6ncvA5lmM/UX3yT9Se/BM1J37i0MmfOPzpHzl06k/UnPgZ27GfsAy9HIGdn7EM/xnr0X/Fduy/CT+P/yu2Y/8V69F/wTz0J0yDP1PZ/4Ly3meU9Tx1REXfc8r7nlPR/4LirscUdT6iuPshJT3Cz6KuB+S23ia/9R65zXdGvD43yW64zp6aq2TYLpNmuUiS5QKJ1osk2S6RbL1AvOUsCZbviDV+ze6Kz9hZ9ik7ik6w5cAxNuUMs/nAMNsODrH14ACb9/exKbuLjXs7WZ/VytKkWuZFm5ixtYiZ24qZv7uMRdHlLI4qYe72XMJWpREwbxc+M7fgOXkVqpDFeHhPx0M3GQ9tGB5KP8aJ1PzBXVgu6yrzZKJEzQSJAjeJHDeJHHepAg+ZEg+Z0rGTzR52g/PYjeyfSGR8IpGg9dERvXM5edm7abem0G2LpbsmmbbqZHpqUumpSX0r9LwJgD60jPU+KBo9BHHsOfqmc9oeTuhx6rfICT1OfRT9/ve/o8Uc/6ug503mx7G1/zdlaTosie+9aNuBpuMNwGN/jx2QOq0JtNsyKdq3g11bFqLVq5Cp1LgoZLhIpbjJPHCTiXF1Vzm+gOSe3uj9QvEOCEehNQjbsuUa3EViXEVy3MQKPORaJJ5ByAyReE1exKQl25i2Oo6lUXls29dAQlE7e8xHyW34isLG0xg7LmDsvCIMIuz+kZquW1R3XKem6xa13T9S3f0Kemr67mPru4+19x7W/vvUDj+mZugR1t6HWHsfY+t9Sk2fkOkx9jyjovcFJT0vKO17Tnnvi9eiou8lZf0vKRv4mZKBnynu/yOmoT9RfeK/Un3iz1Qff+mAnsOf/Zm6T3+m9uSfsA4Jfh3z0J+wHv0XbMf+G9XH/43q4/+GcehfqRj6M5XD/4Jp8M8YB38WPD8DL6kcHCmHDf5E5cBLyvueU9b7jKKuB+S336Wg/QFFnY8o6nxEYcdDcpvuvvL+tNzlwJHb7D/8IzmHbrH/8I/sP3yH9JprJFdfJrn6Mkm2S0KZy3aeFNt3JJi/Js74JVFln7E97xRbDpxgY87g/8veeXU3dWhr++yLfXYAW724Y9NbCKQRWgghISEBQjcdUwymd9x7kazi3rst906HkN7oYIx7B5Lsn/F8F0ta2I4hJOyz+S40x5hjSVoy5sJaetY73zkn605b2HBKgJ61JwpZe7KA9ScF8Fl+MIXFO2NZtCOa+ZsjmbshmDlrz/DumlO8vfYEs5btZ+bSPUxe4M2E91bjNvNjNBPeRek5C5nTRBzUHjiq3JE7e6Jw8ULu7IncxWMo7GhdUGif7uCylbts4DMcemQaNTKtC06enny67AP27PImK96PQuMu8k2+ZJkOjAg9zyp72c4N+cz8BaPz8M/ms6Dnz1rh7dBjj5cJO/TY45XEYOgZDDwjQc+zhpk9T+kZ6aL5d2aN2NrUbT+Xb3tuOEjgkY1sWr8Edy9XtO5uyJzdcFSrkKpVyNQaJCpnsSzh6jWJ8VNnMn7qTJzHThDnr0iUGvHLTO02Eafxs3GbOpeJ7yzlraVbeG/FbpZuD2LdsUR2BGRxKLaC0wmNBKVcIjr3W+Lyf0RX8BPx+b9gKriOyVraMhbewFB0C2PxbQwldzAW2fw79zCWNpFQ3kJCeQsmi2BcNllaMZW0YShpQ1fSalVYnqoqtoy2CGpNXHk3sWVdRJd1EVPejb6iB2NVF8aqLszV7STUdJBY20lynaD+GKu6MFR2El/eib6iR1B1yvuJrxggvmKAWEsPMWW9xJT1ElfWQ2xpN7GlQjdXbGmn8DvLuogu6SSyuI3wwhYRcmyKz5n0O5xJv0NQ+l0RevzT73Am7bYIPqdSbnI69RYHzD+zJ/57fPXf4af7hr36b9ir/5q98dfYo7/CrrhL7Iy6wJbgRjYF1LHuZDlrT5YK8HOimPWni/D2L2GTfxFrjmWz8lA6n+9LYomPjkVbI3l3nT/vrD7Ju2tO8c6a48xatp/XP/Fl5kc+zPhwC+Pf/RznKfNReL6JzHkSDuqxOGo8kao9kTt5oXQZj9J1HCqXsUJH36Cpy7a/HbnW7el5p7GiGV6isnp71BoULi4o3TxZ9MG7+GxfTkb8fgoNe8gz+JJtPvgH6Pkz4PmrRufneX+eBz3DP8N2pcce/6mwQ489XknYoCc9ducfoGf4fqzBwDPYB2DLFzFT/tWpskNm84xwB5wdf4gTB9ay7osPcPN0Re4sLH20QY9UpcZR6SQaULXu43DxnIjz2AlD78rVTqhdBDByHjcdj6lzGPfGIqbOX86cz3Ywf9VePtsVxuYzaewKzuWIrgr/pHOEpl8lruAH9IU/oy/8GWPhDWGhqPVogx69NY1FdzFY1R5T2QOSKttIrGgloazVulurnQRLmzB5uViYxRNj6UBX3om+ogtdeaf42FQzgLn2EfqKLvQVXcRXdmOsFEpYhsqnwJNY20lSbTeJNV0kVHVjqhbeJ7zXVsoSMtbSQ1zpIOixQo6tHGYo70Ff3ouutFcofRV3EFEgKFLRxR2E57eIkBOUfncI8Pin3xHzTNptTqXc5EjidfwMP7Mv/if84r7FN+4bfOO+YU/cV+yKucrO6CvsjL7CjvALbAs9x6aAGjacEYYcep8uxfuMhY0BFjadKcH7VBFrj+WJ4LN0t4FFWyNZsDmUBRuDeHvVCWavOMSsZft557P9vPXpbmYs9hbm90ydj9JjBkq3SSjdJgng4+SFynUC2rGT0HpOQDN2PBo3YaO60sV9CPQIwOMueoHENne1E3KNFpWzC6NUTsycPYWVKxaRECWY8HPj95BnPvTC0POsz9SLmqD/7AZjJKXHDj32+L8IO/TY45XEX4GeZ3V7DIee4Rfkke5E/8qskeEX9ALbhd3kR1r8Qfb5LGfZ0jk4uzsh0QjtwxKlColKKRwVWqGM5eqJi+dEnDzGo3b1RKp2YYxcg6PSCaXV6Kxy98J5wgw8ps9l3OzFTJu/kvdW7Gb+6gN8siOY9UfNbDmVhl+khVPmBkLSrhBX8APGkhsYS6zDCK1pFlvVb6MrvImu8CaxeTeJyb9JbP5tDCVNJFW2DQGfhLJWEstaMVkeoi+xdm6VdWAs78RU0YWxvFN8nFDTR1J9P4k1XSTVdpPa2EtyXQ8J1Z0kVHeSVNdFamMvKQ09JNUJ70mylrhMVdas7BMgxurf0ZX3oq/oQ1feK8KOADydGCoGGZ3L+0koH8BU1ove0oOupBtdSTdxxV1E5bcSmddCSI7Q2u6ffoeTKdc5lXqD02k3xXk+p1JvcDL5FofNNzho/IUD+h/ZG/c9vrHf4RNxjc2hF9kcepGt4ZfZEXmZ7REX2R52nh1hZ9kWWs+moEq8z1hYd7KI1cfy2XC6hPWnillzNJfP/dL4dG8iH++KF7q6dkQxZ30As1ccZeayg8z6ZB+zlu5ixodbmDp/DZPe+RT3Ke+KM3sctV5ItF7InMeh8piIk+dknDwnCyMOrKqODXhs8CNAtNvQ2T5qJ5ROWtQurvxL7oTHeC/mL3iTuJA9FJr9yDP4km/e/5ehZ6SbgWcZoZ/12Xtes8BIKpAdeuzxnww79NjjlcRI0DOSh+dloedFJfjhF9whF3zjU+gpMPqRY/IjOc4Pn00f8+GiWahdNTiqhQ3YjgolUqUKiVKDRO6MymUsTh7j8ZgwFVevSWjdxyFVu4gbs5VOroJ3w3UsWq/puE97j3GzFzN1wWrmrtzDwrWH+NQnhHVHTCL0nE5oFJUeQ/F1IQe1pZutXVrG4tvoi26hK7xJdN4NonKvE517k/ji+yRWtIrgY8vkSmGLurm0hfjSNkwVnSRUdZNY3UNCVbf4OLm2j9T6AVLqe8lo7CPrfD8ZjX2k1nWTXN9NSn2vCD3J9d2k1feQWtdNUk0v5poezNW9mKv6MZY/BZ/4yn7iK/ut4NMtAk98eSfGym7Mld2YynswlfWSWDlAQkW/AD7FneiLO4kv6UJX3E5cURvhBQ8JzrlPQOYdEXJE2Em5zum0m5xMuclR8w0OG3/hgP579ul+YG/c92yPuMam4EtsDBLAZ3vEJbZHXGRH+AV2RpxnR3gjW0Kq2eBfyrqTRXxxrADv06VstD5ffjCLZfuS+GiXkY926vlwRwzzN4Xw5qqTzPzsMK8v3cuMj3Yx/cOtzHh/PdPnrWDsjAWoPWcid5smbF7XeiF18kLuMl5Qe8ZOQuMxEZWLFwqnsSLwyLVug9raXf8APSqNRoAehQvOYz14850ZhJ3ZQZH5gPA3/hLQM+Rm4AWhx/bvDG82eJaKZIcee/xfhB167PFK4h//+B+y9HtE6HmWcflVlLeGX9gHQ0+uUeh6MUTsYu3Kubz99gSkahmj5HJGy9Q4KpRIFEokcjWOMieUzh44j53A2InTcB47AbWrJxKVs7g1W65xRqJ1xdHJDeXYqbhOm8e4N5cw/YP1zFu9jw82HGXl3ii2+aezOySPo/pqglIvEp55jZi874jJ/Z64/B+HrJ6wDR40lNwhvvg2uqJbROfdIDJbgB5D8QPMZQ9JrGgltaaT9LpuMht6yWroIaO+h7TaLlJqBXjJbHxM1tknYmaf+5WCK/+m4Mq/yb/8G4VXHlN09QkFl5+QdW6AzLP9pDX2k1wvAFB6Q6/4ekp9Lyl1/STVDZBU+xhzpdCxpS/vxVzzGGP1Iyv89Aq+n4oujJXdmKp6SKzpwlzZRVJlH+l1T0ive0JyVT8J5T2Yy7pJKO8hsaIXc4WgFEUVC/ATkHlnyNTm02k3OZX2M6dSb3DE+BMH439gv+479ht+YJ/uB7ZHXGNj6GU2hl5mc8hltoRfZFv4BQF8Is6xPVxQezYHV+EdUMaak8WsO21h/ZlSNvmXs/pYPisPZgqDDHcb+Ginno936Zi7IZjZK08y45P9TFuymxkf+fDG4o28/v5axr2xCO24WUL7uvMkJE7jBPhxEkpdSpfxqN0mil1dNiOzXOsmbmF3UDgPmeQs1Tij1KhQO7swSumOwsWFKTMmc9RvnQgkReY/Gpn/bHbPSOdGgp6RVJ7B0DPYgzf8JsUOPfb4vww79NjjlcRg6Blczhpe3nqWkfnPurf+jpF5JEjKN+yj0HpBLzD6Cf4D835iwnaybOlspk1zQ6ZW8ppcxWsyLY4yNY4SBQ5SJXLr0kiVy1hR4Rkj1zBapkWisKbKGZnGHbmTF5qxMxg7830mvrOUmUs2Mm/1PhZ5H2XZzlC8jyfiE5jNsfgaQtIvE555jejcb4my7twyFF9/um6i9I6QlrsC+JTcQV98W9ycbixpFpSdqnbSarvIaOgms7GHrLPdZDYKz9Nqu0it6yG9warmnBsg69wA2ecfkXvxVwou/UrJtSeUXfuVsmu/Yrn2G0VXn1B45Veyzg2Q2tAnKEHnB8i58Jjs84/IaOwno+ERaQ2PSGt4THLdExKqB0SPkKlmAFNln+j7SazuJamml+TaPtLrB0hv6COrsY+8S7+Rc+k3ss8/Jr2hj9S6HlJqu0mt7iKpWiiHxZa2E21pISy/iaDsOwRk3sI/4yan065zKv06Z9J+5njidxw2fct+43ccSPyR/eYf8Yn9ms0RXwoZeYWtEZfYHnGJbeEX2RJ6ji1hjWwLa2B7eB3bwmrYFFTJmhMW1pywsPZUCWtOFrHuZBHrTxex4mAay/YlCROct0Uxf2Mos1ccY+ayg8xcuodZH23j9UUbGPfmEpwmvIvW602krpOROo9H5jweR60Xjk6eSLTWVHsg0bgP6dZyUGgZI9f8YX2Fo9IJtZOgQI5xGY+jkxvOXl5sXPch2fp9wlRmw9CW9eeBzUjlrMGg9Gf+HttnygY8gyel29rXn1cCs0OPPf5TYYcee7ySeBGl58+g53ndW8/qFnmRttrh0FMw7EKebd5PdNgOlnz4OhOnOCPTqhgtVwl32zI1o8dIGe0oR+kkfDEpnYXhhI5KJ0ZJVYySCn4fqdIJidYVmdYTlesEnCbMYtzsxUye8ymzPt7CvFX7WbD2MB9vC2btIRPb/TM5Fl9FSPplwjK+JCrnGyKzviEu/0dR3RkMPabSexgsdzFY7mIsFQzMptJmEsraSanqJLW6i7TaLtLqOkmv7yKzsYP0unbS6gQYSqvpJqNeUH8yG3rJauwj+2w/2Y0D5Jzvp+jqI0qvCVl27VdKv/qd4i9/J/v8I9LO9pF2to+ci4/IvfiE7POPyDonZGbjY9Ibn5Da8BuJNY8w1z4aAj02hSeppk8spWWeHSDn7CNyzz8i//Jv5F/+nfyLT8g+209mQy+pNZ0kVrRirmhFXy4MQIwuaSWisJngnLsEZt3mTPoNTqX+wqnUX/BP/4VTSd9yLOFbDid8y+GkHziQ+CM7dV+zNfpLNkd/ydboL9keeZWd0VfZHnFJhJ7t4Y3siBTAZ0twLetOlbH2RBlrT5ay+kQR608Vs9G/lBUHMvjEN4HFPjo+3qXjwx0xvPXFCWZ9fphZn+7lrU98eOOjzUx8+xOcJ85BM+5tpK6TkblMQOE6EakVfBw0noxRueOocsdRPbSsNRL02NZYqLRqHFQqJC6TcFB7oHD1YNXnC8iMFfZv5Rt8/1L31nDgGQ49w03/zzIxD18f8yLQM/jn7dBjj5cJO/TY45WEDXqeBTmin2fQXq3BF8HBE5dHmtr6IiWvkWT1kcphBfH7hQu5wdcKPQcJOrOJuQtm4DbBBQeV0K0lVWiQSJW8ZoUeuUYrdtjYylpj5BpGywXocbRCj9TJC5X7JNymvM2Et5Yw5b1lTFu0jjnLdzFv1X4+2RHMppPJ7A3L43RCPWGZV4nI+oqInG+JzPmB2IJfMFhuY7TcxVx2H0OpoO7El9zDWN6MqeIhCZVtGMseYihtxlTeSlJ1J0nVnaRUd5Bc3UZydRupNa2kVLeQXN1GWl2nCDuZDb1DHqc39JHZ0EvepT4Kr/ZRcKWX4i8fU/zl7+Rf+ZXMC4/IOD9AxvkBCq7+RvGXv1N45VfyLz22qj6PyTj7KxmNv5Pe8BuJ9U9IrH9CQt1jjNX9mKt7BbN03QDJDQOkNQgqUfbZfvIvPCL/0mMKLj+h4OJjci8MkHW2l6SaduJLm4gvbbKuuxCGKkYUtoj+HluZ60zKDQIzb3Aq5XuOJX/L0aRvOJr0PYeSvsPX8BXb475kW+xVtsd8ya6YL9kd+yU+UZfZFnGOHRFnhYxsYHtEPVtCa9gSXMumwGo2nKlg3YliNpyy4H2yhJUHs/hsXxofbIvn4z1GPt5j5N11/rz9xXFmLTvI28t8eesTHybP+wLXaQvRTHwPmetU5K4TUXtMRuk2CYnWizEqD/4lc2aM0gWp2k1UeWyA42BVDaVKJwGkrc9lag0SjQaZ8zgc1W44apxZOH82cUG7yNT7UWj684nMz4Kd4XN9npfDP08jeXqGt8Q/b3aPHXrs8TJhhx57vJL4xz/+h+x43z+oOH/w8DyjbPUi6s7zoGckv8Gz5pHk660XeONe8g37yTIe5IDvKibPGI/c2YlRCjVSlQKJdAyvjR7NGIkCiUIrDpZTaIXW9DEyJaMkckZLFTjIVcKWbI0Ljs7uyN3Ho530Bh4z5+M1ezGT5n3O28u2M2/1Plb6hrM7OJPDsRZCUs8TkfUVYVlfEZn7HVF5PxFbcANd0S30xbcxljYJk5aL7xJbeA+DpRVTWTuGsg6iC+8RWXCbuNK7mKpaMVW1kmAzMVe1k1bTbS0VdZFc20F6Yw8Z5wdIP9dPaqNgTk4720dawyNS64XXcy48IefCEzIvPCL9rFDWSqrtJqWun9SGPvKvPqb0m98p/fo3ir/8laKrv5F/+Teyzv9G5rnfyGj8XVB8Gn4lof6JVfXpJ6FugJSGx6Q0PiKl8ZGg+NT1kHW2l+xzfeReGKDw8m/kXhS8REl1XSRUtmOqbEdf1kFUsbA2I7KolZDcJoKy7xGYdZfALNtm9uucSP2JY8k/cDjhOw4nfMsh87fsN3zFXt1V9uqusiv2MntiL7M76iI7o86zK+YcO2Ma2RnTiE90A9sj69gaXs3m0Co2Blaw8UwZG/1L2XjKwqbTwtH7eBHLdqfwoU88S3bFs2RnDB9sDefdlSd469N9zPrYh6nvr8Pt9Q9RT5qP1G0aMpcJKN0monSbiFQzVgAWpRMytZM4wdv2WKLUIFFqcFSoh6REqWG0QtjDpVA7I1OrkKikeE2ayCHfDRjD92Ex7x8RZl40nwdJzzIyDz43+HNoK6/9WWnLDj32eNmwQ489Xkn8Feh51lyP/wb05Oj2kKfbNwR6Mg0H2LdzJeMne+Go1TJGpUWmViKVj+Ffo0Yx2lEutKurrRN0rV9Sjgo1Y2RKRktlOCrUOCg1SJ3ckLqORTl2PE5T3sDjjQV4zV7M5PnLeXf5dhas82OVXwS+YVki9IRnXiMs6yui8r4nOu8XEXjiS+5gLG0ivuQecUX3iC28R3xJC0ZLO7ridqIL7xFVeIf4yvsk1LQLaW1bTyxvI7m6h7S6flLrekis7STjfD9ZFx+L4JN2ts96/JXUs49Ja3hEeuNjMs4+IfPi72SceySYmOt6SKkTjMu5lwco+eoRJV89wvLV75Rc+zeFV/9N3sV/k3nuN9IbfiO57gnmuseY6x4LJa6aPsy1/STXPyK5YYCUxkck1gkwlV7XTXp9F+kNveScfUTm2QGS63owVggzhvQWYYVGeH4LkfkPhyg9/hm3xTyZ9gvH0n7iaMpPHE74jkPmbzlo+oaDhq/x033Jvrir7NVdwTf2ErujL7Ar+oIIPDtjGtkRVcf2yFo2h1ayNbyGzcFVbPIvZ8PpEjadKmfT6VI2nSzB+3gRK/0yWbLTwGIfHR/timXJjigWrg9kzvKDvPnJbqYtWo/L6x+imjgPqds0pM7jkbuMR+E6AbnWA6naDalSmLsjV2tE4JGqtCLwOMhVOMhVQ6FHbh16qdIgV8uQqsbgPm48e33WogvZS4npPwc9z+vgepGZPnboscd/K+zQY49XEsOhZ/im5eGLQP9q6ervwM6zLsi2icwFpn3kG/aTbTiAz5aleIx3wUGjQeLihkKrRipz4F+jRjFGpkSi1CBVaYd8QTnIVYyRKXGQq8TzEo07EhdPFO4TcZnyNuPfWsLkecuY+fF6Plh/gKXbTrLpmIH9kYUc05cTkn6R8Oyvicj5lpj8n4krvC5MXC5twlzebDUtC6smDKUPiS1qJrqgici8+8QWNRNf1kJibYcIPYlV7aLSk1rTKZSyGvtIP9dH1sVHZF96Cj3p5/qFstU5QdVJqe8lrbGfjHOPyLrwhMzzj8XXE2p7SaoV2tVzL/SRd6mPvMtPyL/8GwVXfifn4r/JPPcrmY2PSax5RHxVn5DVwjoLU00fCXUDJNX3k9wwQGr9gKBCVXeQUdctdpyl1HZjruogvrQNQ+lDdCUtQst6dhPB2U2E5j0gOOf+EJXnRPIvnEq9wYnUnzmW/COHE74TgMf0DfsNX+EXfw2/+Gvs1V3FN+4Ke2IvC9ATfRafqEZ2RNWzI6peUHrCatkWXsfW0Bq2BFayyb+cTf7lbDxlYfOZMjadLmXdkXw+25fK0j1mlu428MkuHUu2RTJvzTHmrNjPzCXbGfv2Z2infoDEdbqwfNRpHDKXCThqxuKochc2rVvhWarSijmSymODnjFKQWFUqFTI1CqkShVObu6sX/spwcd3iF6eP8vBvp8XVXz+7HP2rHMjNRUMTzv02ONlwg499ngl8aLQM7icNdz8+LwL45/Bzp9Bz5CulWHQkxW/n83rP8BlrAYHjQaZmwdyjQqZ3JExjo5/KDnY7sIFlUcobYnlCY07crcJqD2n4DHjPSbP+YTpC1cy+5NNvL/Wj8Ubj7B8dygbjyXgE5DB4bhyTiWcIyDlMhHZ3wt+HhF6mjCW2YzLTRjLHhJb3ERUwV0i8+6hK2kRZu/UdGCsbMVc3S7syKruEKCntoPsc31kXxgg88IAWRcfkXlhgLSzT0tb6ef6h5SxUhv6SD87MAL0CAMJU2q7SG/sEUpljX1kNPaR1thv7eASymQJdQPEV/Whr+y1Kj0DYonLBj1pDY9Ib+gTus2s5uq0+h6SqjuFklZ5O8byDnRlbYTlNxOYdZeg7HuE5DYRktskbmb3z7jNyZTrnEj+hWNJP3M08ScOm3/gkOl7Dhq/44DhW/bHf4Of/mv26b8UwWd3zCV2Rp3HJ6qR7RH1f8htYbVsDa1ha2gN24KrBfCxQs+aI/msOpbLisNZLNoeywfboli0KYwFa08yd/VR5q48wLT3vfF483MUY99AovVkjHqs0L2lGYtE7YFULSiGUpV2RMgZCXqkaqG0pVSrUbs4o3Z2QeXswqefLOSYnzeF5iN/CXr+DH6e17Y+WA0a7vUZ/jN26LHH/2XYocceryT+m9DzosDzLJOmrXtrMPRsWrdIhB6JixtSlQK5QoKjVCregY+RKcUcLVWI6SBXIVVphTt3p7EoPSbhNH46Xm/MZ+rcZUxfuJJZSzcyf9VeFq47wDKfILyPGtnhn86hi4aB+QAAIABJREFU2DJOJ54nKO2qaGKOL76NwXIXU9l9jGW2Tq37GMubiS25T3ThPaILmtBbWjGWC8BjKG/FWNlKck0nqbUdpNS0k17fQc75XrIv9pFxoZfMCwNknO+3Qk8PqY29YpkrpaGH5LoeUenJPP94iAKUWGc9Xy+0vadZISWlvlec15NaLxiVE+sfYajux1DdL3ZyJdQNjAg9qTWdpNZ1C3OEarswVbZjKBOgJ75CgJ7QvAcEZN4hMOvuEOgJyW0SBxYetwKPDXoGg48IPbqv/gg9kefYHv4UfHZENrAjsoFt4XVsC6sV4WeTfznep0vZcMrCqiP5wvTm43ks2hbHoq3RLPAOYe6aU8xbfZyFa44wc/FWxr2zCpXXbCRaT0arPHDQeI4IPTaIHl7SGg49Co0rCo0WpUaFxtUFjasbMq0LixfNYf+u1RSYDv8t6HlR5Wck4Hlex9dg6HlWg4EdeuzxsmGHHnu8kvi70DN8qNnfBZ8XbccdPKen0OxHgfEAmXo/Nq59X4SefynVjJY6IpU54CCRiOrOaKmCURI5rznKxBwlkYvlL5naCYWLF2rPKTiPfx3PmfNEpef1D72Zu3IPC9Yc5PNdIWw5mciuoCyOxVcRnH6V8OxvxPKWvugW8SV3MJTewVx5F3PFfczlTRjKHqArtaalGb2lFV1JC3ElD4greYC+9CGJVoUnra6djMYOci/2knOpn8yLfWRd6ifrUr8IPmlne0k/1ycqPzaVJ+PsExF40s8OkNYomJhTG/rIaOwXX7MdbQpPcsMAyQ19JNY/IrHhVxLrfyOh7rG1m+sRiVZPj1jequ0jsaqdxKoOTJXtGMta0Fma0ZW0EFvSSqylhciihwRZFZ2AzDuiwhOUfU8sc51Jv/UUehJ+5ohZOB5N+JlDxh/Yr/9WWEIad01I3VXB0BxziV3RF/GJPPc0o4T29a1htWwJrRGOIdV4B5Szwb+MjWfK2HBKmOHzxbF8PtpjZslOAx9sjmL+Wn/mrz7F/FVHefOjnUxbsAm3qXNRuk3EUevFGPVYJFpPpBphCrNC64JUpR0C088CH9vfl1ytQaVWCkqPiysSrQuzZ0/He80SMuMOvjD0FJkPDBlm+GfwM3y+z4ucs0OPPf4bYYcee7ySsEHP4Bb14UbmZ3l6bPlnkDPS8xcBnuEX8lzDfuuF348c40Ey9AfZvP4D3Ma7IXFy4n8VKv53zCgcJK8x2sGB0RIlY6QC9IyWKHnNQS4Cz2ipAqlCg0ylRq5xxmnsFJzHzcBt0iw8X5/PxHeWMm3ucmZ+uIUFq/azYPUhlu8KY9NxM7uCsjhlrCE88xqRud8RV/Qz+qJbwgBCy20BeqrukFDZREKl0L6tL2smvvwh+ooW9FaPT0xhM3HFLehKWjFXtJFa20Z6fQfZ59vJudBJ9oVOsi72kH15gNyrj8m+PCCqPra0lbkyzj4hvfGxCDwi+Fjn9KRbZ/JknP1VMC6f/5X087+Sev5XEs/2k3S2D3N9/9PurbrHmGv7SaztF4HHZmJOqO7EXNUhmJYrWoi1tBBT8pCY4hYii1qJLHpIWH4TgZn3OJ12E/+Mm6LKY4Me//Q7nEq9xdGkGxxJvM6xxF84lvgTxxJ/EQHoQPx37Nd/y97Yr/CN/RLf2C/ZG3dN9PfsjrnIrugLwjFGAJ9t4XVsDKpkc2gVm0Oq2RhUyaagSrYGVbElsJL1ZyysPlHIZ4cy+fxgGp/tMbFkcwQL1wcyd+UR3vlkD7OX+DDprcU4eQkdXGNUHgL0OHsKi0W1LsjUmiFdgM8DH0eFGplCiUqtRKERlMUxajfGTRzPB++/hSncV/zbf55yU2jaT3HCQRF8ngVALwo9w99j+x3Djc926LHH/0XYoccerySe1b01eN9WdrzvH4zLI83j+bM5IS/i4XmeaXMo9BwgM/4QWzYsxmviWGQuLvyvQsVrjmNwkLwmdG9JlDjKNWJZy6b22L6khLtwDQqtC86eU3GfNIuxU9/Ca+YCJr6zlOnzVvD6hxuZ/4UfC9YcZOWeCLafSWFPSA7+CfVEZn9NVJ4APbrCmxisKo+x7K4IPeaK+0OgJ778oQg9sUUP0Vva0FvaMJW3iqWt7PPtZJ3vIOt8B5kXusm61E/OlUeC2nOhdxDw9D2FmmGwMxh6Uht7h0BP1vnfRehJOfeExMY+Eht7MdX1kVD/BFPtI4xWT49tqWlSfT+JdX3C/i/rQlNDeSvxZU+BJ7qk1TqTp5mw/CYCMgQ1JyDzDqF590Uzc0iucO50+i2OpdzgaNINjidd53jSz3+AHj/dN+yN/Yo9MVdF6Hla6noKPbtjLrIz+izbI+rZFFzF1rBatobVsjmkms3BVYOgp5Q1J4tZcUTw9qzYl8hH26P5YGMI81cd4+1lvsxeuoup7y7Fedx05K4TxY3rChcvVC5jrUqPmtFSxRDVcCTgsZnl5UoVarVahJ5RShfcPT2Y995MdEE+fwl6RgKf4fDzvM6uvwo9z0o79NjjZcIOPfZ4JfE86BmSI3h4Bk91zY7b/VLA82ceBtvFucDoR5H5APmmg+SaDrFr68dMmT4OjYc7Y7TOOMilSOVj+OdooXtLqtIiUShxkMkZIx36BSVTOyHVOCPXuqH1mIzbxDcYO/ltxs96n+nzlzP7g7W8+/lOFm84xGLvY3zmE8Lagzq2nkzlaFw5wWmXCM28RlSeYGTWF93CaLmLqewu5oo7mMutnp7Se+LAvniLUOKylbmMFW0YK9owlbeQVNNOWl0nmefayTjbRtrZDlLOdpBuBZ+MC72knHuayWd7SGroIblR6N6ylbPSzz7t7EptHOzdEdZOpDY+EefuJNT3Y6rrFrK2VwSe+Ko+9BU9xFcKAwoTaoUlpYbKTgyVnRirutCVtRBraSa8sInIoodEFbcQUfyQsIKHBOc2EZx5l5Cse4Tn3SemuEVQggoeEJ77gJCse1Zfzy2Op97kRPINjif/Ipa3jph/4qDhew7Ef8e+uK9FpWef7qshxuY9sZfZE3sJ37jL7Iw6z/bwRraG1bIjskEwO4fXscUKPhvPlLH+TCnrTpWx5lgha47m8YVfCsv3GvlkZyyL1gcwd+Vh5iw/yMwFK3GbNAuVxxQcNZ7InT1F6JFpXHFUOjFaquBfDtIhIG0raQ020cuUWpRqDWqtFoXWCYXWBYnWFRd3V2bPmkTEyW3PhJ7Bf/9F5gMi9DwLfGzw86LQM9LncKSuLzv02OM/HXbosccriT+DnpFWTAxXfZ5nVH6hVvQXAJ/BF2gb9BQmHOaQ73KmTvNE7eqC1MmVURIHZNIxOMhlvCZVMEoixVEq5TVHB15zdGCURPrUvKx1wVHjgkTjjtZjMi7jZ+E6+S3rfJ4VzPhgDW98tJm5K/ayYPUhvtgTjY9/JvvCCghIqici+yoRuV8TnS8YmeMKbojTmJPK75NYdp+E8ibrGor7GCz3haGFZQ8wljdjqGjBXClkYnWb0MFV20VaQzdpDd2k1neRXN9FamOPADmNvSQ29pLQ0ENCQy/m+h7M9T0k1feS0thPSqOgxiTV95PS+IjUs49JbugjoVZYFppQ00diXd+QYYOJdX0k1vWQdLaf5MYnmGqE5aOxZV3ElXWhr+jBWN2LsboXU3U3hoou4ss7RbNyXGkrUZZWIoofElH8kNCCJgJy7hOYc4fg7FuE5dwkIvcuUUUPiCxsIjT3DgHpNzid8rNwtG5aP5lyk+NJ1zli/onDph/FPGT8gYOG7/HTf42f/muhvGUFIN/YL/GNuyLAT/Qldkacxyf8HDvCG9kZeY5d0WfxiWxga6gwv2f9mVI2+Jexwb8M7zMWNp4uZv3xHFbuT2CZr573NwUzZ9Ux3ll5hNmL1jP+jfm4THoTqdpTMDBr3dA4CxvWJRp3HGUqRjnIGO0oZ5SDjFEOMnEK+Bjr3jcHqRKpXIFMoUSu1qB0ckXl7IZM7YSzmwtTp47nmJ83ucZ95Jn8yDfvJ8/kJz4enAUJByhMPEhBwoEhOfx9eaa/Pt/nRVvZB6cdeuzxMmGHHnu8khgOPUNKWtbXM+L+uGJipPk7Lwo9f6XU9UzoMe+nMOEwJ/evZsbr49G4CebQURIH5DIHHBVyXpPJBMiRShntIEDP6EHQI3dyxVHthlTrgYvXNFwnzMZ18lu4zlyI57ufMn7+F8z4YBNzPvNl4ZojrNmnY09QPoeiygjLuEBs4ddEF35DdP4PROf9REzeL+gL72C23CWx7B5J5U0kVzwQVlKI0COoP6bKByRUPySxuo3E6jaSatpF6Emp7SK1rpvUum6S6rpIru8mqUGAm4QGIc0NvRhrezHV9mKu6xviu0m0PrdBj7lGABVzda8IPalnBfARSle9JDf0kdz4BGOVFXpKO4kdBj3xld3oyjvRlXeir+gitqyNaEsLkSUthBc1E17UTHBBE2dy7xKQd4fw3FtE5t4kIu82Ufn3icy7R2jWLQJSf+FM8k8EZFznVOoNEXpOJN8QVR4b8Nigx9bJtTfuGr4xQ8FnT8xVYVpzxHkxd0WdF6Fnm9XUvMG/DO+AcrwDytnsX8qmMyV4n8pl1cEklvnqWbQ5hHdWH+Ot5YeYtXgDk958H7cpbyPTeAnzedQuaJy9xC3rjjIVox3lf4CeUQ4yxkgUYkpkcqRyBVKlatB0cA3Obi5MnjSO/bs3PBd0Bj9+EeB5Geh50RESduixx8uGHXrs8UrCBj2DPTyDoed5G9T/bJ/Wn3kChl9sXxR6bK8VmQ8QeNSbd9+dhqunBxKtCw5yGTK5FIlM+DIaLZEiV8iQSCQ4SKSMkcrEjhqp1gOl6zhUrhNQuU9GO24W2glv4vr6+3i8+xnj5n/BlEWbmLNiPx+sP8VK31i2ns7EN6yIkPSL6Cw/oLf8TEzBD0Rn/0BE1g9E51wnLvcGiSV3Sa56SEp1CwnlTeKyUWNpkzjAMKm2VYSexOo2kqo7SKruILW6i+QaIRNqOjBWt2Oq7sRY2yWmobobfZWQxpoezHV9mOv6MNX2klDfT2LDAEnW8pWhupv4qi7MNT0k1vWRdu4JaeeeWKFogIRaYZ5PYm0/hkoh4yv60Jf3El/Zi6GqD0NVD/qKLuLKOoiv6MBY1SUYmItbiC5oIqLgPuH59wgruE940QPCi+4JLfqF94govEN4/j1Cc+8QlHkL/7TrBKTfIChD2MN1ygo8J5Jt3h5B8bEBz4H474ZCz3Dgib7CrqjL7I4SVlXsjrqIb9RFdkWdZ2fkObaHNbA1pI6NgRVs8C8VVJ4AC97+Jaw7lc+qw2l87mdm8bZw3ll1gtnLj/DG4o1Mfesj3Ce/h9xlAhKVK1K1Gwond6RaDyRqD2Gyt0TBaEf5EIVncI52lKNQCEqPg0z+tFtQo8XJWctYTw92bllJdrwvhYkHnyo1IwDNSOAz0nteVul50flZduixx8uEHXrs8UriH//4H3IMe4eUtGzAMxx6/uqKib+qAg2/ID8Pemz+htjAnSxe/A7jJk9E4eyGVKVEIXfEUWptTXeUIJEIc3skMjkOMrng81E7CbN5ROiZhsvkObjPWMCUBSt545NtvLliF++tOsTH24JZuTuKDYcS8T6aynb/bI4aaonM+wZdyU/EFf1EdN5PhGd+T0TmT0Rl/4Kp5A7Jla0kV7ZiKnsglrbMZQ+Jt5a4zJUtmCoeYq5sEdZQVLVbwaeT5JouEq1pqu7EUNNJfFUX+spOdBUdxJa3E1PWTmx5B3EVncRVdKCr7ERX2Ul8dTeGmh6Mtb3oq7rQVXair+wUVJ7GR6KJOe3cE1HtMdd0kVAjgI6+vBddWY9wLO+2pqDwxJV1oC9vx1Tegr6kCV1xEzEFd0XAiS5uIqasmejSZmItzcSUPCSq6AER+U2EZAvQE5B2i6CMOwRl38M/4zanUm8NUXuOJ13naMLPYonrQPx3Ynlrn+4rsYV9T8xVdkVdZmfkJXaEX2B31GX2RF8RoWe3FXx2hDeyNaSOTYG2FvZSNvqX4u1fwtqTBaw5msGKA4l85BPFe2tP8/YXx3ljyVamvPspY6cvROk+WYQeidZVmN6t9hBmQFnhxlbmGg49YyQK5EoVCpUaB6nQTThGrkGpFbavu7i7snnD50OgJ9e4b0SY+U9Dz/MA6EXUHjv02ONlwg499ngl8aLQ83f2av2V+TzP61gZCXpsZk59yB4+XvIeE6dMQqZ1EaHHQSIRTKYOwnRmR6kUB5lc6LBROiFROSPVegxRebxmvs/Etz5mxofreHPFLuas3s9C79Os8I1m/SETO/1z2BmYz87gQo4aaonK/xa95Wd0JdeJzb9OeNZPhGf+LEBP8T2SKlpIqmgR1R1T2QNM5S0i9BgrWzBWtopTmRNrO0ms7SSlppdk61DBRGuaansx1vQIJabKLuIqhPJTbFkXseUdxJQNhSBdZRf6qm7hfeUd6Co6SKjtFctetvJWcoMweDChtvsP0KMr6yGurIvYUgF2xNJWeTvmsocYSpqIL75PbOFdYorvEVtyn9jSB8SUNYvgE1XcInZzBWXfE3dvBWbdJSjrPgEZdzmVekvMvwo9OyMv4RNxke1h561Kz2V2RV54Cj2RF9gR3si20Ho2B9WwMbAC74ByNgUIS0nXnixg7bFMvjiUzCe745i3IYA5q0/zxsfbmfre53jMXITaY7qwbFTtJnrAJBp3YSqzTIWDVCmWtwaDj83TI1eqUGiEYYavSZSMlqmfCz3/LaXHDj32eJVhhx57vJJ4Ueh51k6tvwM9L9K99aJKjzncj8+WzmfylEmCOVmhQCV3ZLSDA/8c7cj/jnJk1JgxjJZKBOhRanBQO+OgcsVRMxaF6wSU7pNxmvgOXrOWMO6tpUxYsIYpS7YxY9ke5qw7ybI9caw/ksT+yDIOxdVwMLYK/5QLxBb/iLHiFsby2+iKbhGRc4PI3JvE5t/GWHIfQ0mTCAbGsockVLZhrGxFV/oAfVkz5uo2zNXtIvAkWVdGJNc+bRNPqBfWQCTWC9ORjTVPM77mEfE1A+ir+4mr7CW2ogdddQ/xtX1i6qv7hWNVt9h5JZSzekX/j83MnFDT9xR2SruJtXQRY+mwZhtxZR0YKrowVXRiLHuIqbQZY0kz8ZZm9KXWVnxLM9HFTUQXNxFZ8pDw4jbCiloJzXtIUHYTgVn3Cci8R0DGfTH9M+5yxjq350TyDY4l/jLE0DzYyPxM6Am9gE/4BXZGXGRnxEV2hwsenx1hZ9kaXM+W4FoBegKq8PavFOFn/ali1hzPYvWRdD7zM/LB1nAWbAxm1rLdTFm4Bs+3PkU9bhYSrafg49G4IHN2R+bsjtLJFZlSi1ShGeLnGWxkdpSphO4tjQsSlTOj5E6MVjhbvT1anD3c2bxxBTmGvRQlHRJBZiTD8ot4ev4u9PyZsdkOPfb4T4cdeuzxSuLvQs9I8POfKGuNNDfkWdBTZD6AOdyPZR/PY9Lkicg1zigUClRyBxF6/jnakddGW6FHrsBRpRXv2qVOXijdJqF0m4rTxHfwnL2U8e9+zpQPNjL9093MWrmfeZuC+GK/mY0nMjgQU8VhXS1H9LUEZ1whruQnDOU3iS+9ia7oDpG5N4kpuIuu8C5GK+zoi+6hL7qHqbzlD9BjqG7FUNWGoapN9O2YqjtJqOrGXNODueapidhoXQ8hZpUNeh5hqH1EXE2/NXvR1fahr+tHX9ePrnYAY91jjLV94r85FHaETKjtxlzdS1xp91PgKekkuqR9CPQYK7sxV3ZhKm/FWGrdqF76kDgr8EQUC4bliIL7hBU+IKyolbCiVoLzHxKY+4CAnCb8s5o4nXGPM2l3BfDJvIe/VfGxKT1HzD+Jecj4w9CVFCOVt8Iusj3kPDvCzrMz4iK7wi7gE36O7aGNbAmqY3NgLZsCq9ngX4m3vzCwcGNgBWtPFbPmWDarjmaw/ICZD7dH8v7mUN78bC9TPliH5zufoZ74JlInLxy1HiL0yF08UDq5Ilc5IVVoREPzcPBxlKmQKjTI1S5I1S6MUQopGwQ9m7yX/38BPX8VfOzQY4+XCTv02OOVxD/+8T/kGvcNgRxxs7phr/ja4OWELwI9LzWbx+gn7tmyQU+ucZ/Q1hu/d8j8HmPoXj5eMpdxE8cLSx3lclQyKQ6Oo/jXaAn/O0rCKEeJuGvLUemETO2B1KryaMZOQev5OtqJ7+H11mdMWbiWmZ/68O664yzcHMinfka2BOSzO6KMI7oGTidcIjD1MtGF36Av/QVd2Q3iSm4TU3STqLzbxOY/IL6oGUNJkwA8hfeJK7ovzOUpFYYT6kofEFfWTGz5Q3TW1Je3ii3geksrcaWtxFnaiCvpILqknejiDmt2EWvpIba8j5iKfiEr+4gs7yKyvIuIsk7xGFHWSURFN9GVPZjrB8SSlq2sZTMxm6q7Bfiq7BR/V1SR9XeWtBNjaSPG0oauQlB6jJVC67rO0mn9/wlTmMOLmgnJv8/pnHuczrnHmdz7+Bc0E1D4kID8B8Lz3Af45zRzMuMeJ1Pv4Z9+T4Se02m3RV/PYLXnkPEH9sV/w954K+xEf8me6KFGZp+oK2wLPse24HP4hF1kR9hFdoSdZ2twI5sC6tjoX81G/2q8A6rxDqgS5vYEVrDutEWEnhUHElm8I4oFm0OZtfwgUz/cyvh5q3CeOhep2wQcnccidXJD4ToWzdjxaJzdkcjVSBUapAoNjlbj8vAyl6NCjUzljEzjzhiVO2NUwg4vlZMzWjdXVq1cQp7Bl5Kkp6DzLOgZXuJ6me6tZ62vsEOPPf4bYYcee7ySGA49z8qRoOdZ5a2/On25wPj0Qj1Y1Sk0+lFk2k+R9bVc417yDL4UmIT9W4VmPwwhvixZ/C6e472Qa7QolUoUEmH/lg16HBXyp9NylU7CDiUnL9Qek9F6TsN53Bu4TX+fqQs3MPsTHxZuPMEyPx2rjiSzNaQI39gqjhgbCUr7irDMb4nM/Y6Yoh+ILf2ZOMsNdJY7AvgU3CG2oAl9oaDwxBffx1D8AF1xE7HFTeKeLZsyoitrEaCnrAV9eatYfoqvEDqkdOWCbyfG0kVMaSfRlg4iSjqItHQSbukkzNJLeGkPYaVdBBW1EVDQQkBBC/75DzmT18yZvGYCC1sJKmojtqxLHCpotHZymWt6BOCp7ERX1kKcpY2IglYiClqJLGwjuriD2NJO0cisr+gSfT268m6iS9qJLGolJLeZ4JwHBOY+ENWcgJwmzuQ0EZDXTEBeM/7ZLZzJesiZrIf4Z7dyKqOZk6mC2hOYdZeAzDucSb8jgs/gmT0HDd+zV/81vrqvhJUUMULbuq2Ta0/MVXyirrAj9IKg9oReYHvoBbaHnmNLUAObAmrYFFDD5sBa1p+pZN3pcraEVLM1tIYN/mWsOpbNykPpfLLXzPtbIpi3MZjZKw8zfckOxs9fi/OM+cjdJyN1GYfE2R2VuxfO4yahdHIVhxHaFJ/h/h5bictRocZBoUWicUem9UTu5IrSyRmVswsfLZlLpn4fhUlHRwSbZwHPyyo9duixx6sMO/TY45XEX4WeweAzHHj+ynDCkaAnzzQUegoM+0ToKTT6CV0thqEt64bQ3Sxa+CYe49xROjmjVCpRSiVIpI6McpDz2hgZEqUCR4USiVKFo0pr/dIRoMdp3AxcJr3J2Fkf8/qSrcxZ6cdHPmGsOprEulNZbA0txU9Xz/GEiwSnf01Y1ndE5n1PTNGPxJT8TGzJdXSWO+gsd4gpuCOUtwqEkpahpAljSTP6kgfEWsHHBj36UkHdia9oI76iDUNlO8aqLkzV3RirOjBVdxNf2U1cWQ8x5T3EWnqILu0hwtJNhKWb8OIeK/T0EV7aQ3BxO4GFrUPAxz//IYFF7QQXtxNV0k5UsbAnK668HX2l0A0WX9WFrqIDXZmwRmIw9MRauoQurooedOXdgqm5rIu48m5iy7qIKGolLL+F4BwBdAJzHxCU1zwUfqzQE5jTTED2AwJzmgnMbsE/s5nTGYLCY4Me/4y7nEm7LbSwJ13nqPknjojQ8w2+uq/ZG/sVu2OvDcov2RVzlR2Rl0Xo+aPSU8NG/2o2BdSwwb+KDWcq2BJSLc7uWX08jxWHM/h0XwILN4czd0Mws5YfYdrHPkxe5I3bzEUox05F6jweqbMnKncvNF4TUWrdkCg1wtwnlRMypRaJXD3E3+NgBZ8xMmElikTlikzjjsrZDYXWCaWTMwsWvk1KrC+5CUfIMx8Sy1tFCfspTHyq+uSb9/+lvVt/B3rs5S17/LfCDj32eCVh8/SI29SN+4Y8zzHsJcewV+zoGKnEZXvd9l5bKerP0gY6gzPfPMi/E7+XAsM+Cg0HyDfsJ994hIL4wxQaD1FkOkyR+RD64J3MmTMVjZsWuasrEqUClUKOo6Mjox1UjHFUI5FLkSpVSFVqYe2Ekxcy53EoPSbhPPENPKbPZdycFbz12R4Wrj/OMr94vjiWyRcncvAOKsFPf5ZjCZc5nXKVkIxvCM35nsiCn4kpvkFsyU30pXfRWe4QlX+TyLwbxBXcwVDShKm0GZPlIXrrNvW4kgfoSlrQlbQQX9omGILLO/6QJisA6SsElSfK0k1s8SOiSx4Rac3wwgGCC7sJKRLgJ6S4k6DCdgLyW/HPayEgv1V4nN9OQH47oYVCCSqq5KEwa6eye8jQwbhywbsTa+kiuqSTGEsX8ZX9GKsfEV/Zj66ihxjrwMLY0m6iijsIy28hJLeZkNxmQvMeElrYSmjhU+XHP/u+CECBuU1DMiDnvgBBmfc4k35LnMx8yponk29wPPEXjlrXUfjGfcPO6G/YFX0NX93X+Oq+Zmf0VbaFX2Rr2Hm2hJ5juzV9wi/gEyEYmbeFNOB9pooNpyvZcKaCzYG1YheXuHn9ZAFrTuSz/EAqC7dGM887jGnLDjBt6R5eX+rD+DnL0Hi9gdR1MjLncUicxiKzrqTtNATbAAAgAElEQVSQqgWDsg1+pCq1sO7EUcIYW0plYuegLRVaJ2Hvm7MbM998nbjgHaQbjpCbcISChANYkg9RnLSfkqSDlCQdFDu7XhZ0/qqX53k3L3boscfLhB167PFKYrCReTj0ZOn3iBAz+AL4LDXnWWDzt6HHsI8C4wEKjAfIMxwUzxWY9lFg3kuBeS9xwTuYO3c6ancNDhoNEqUCpVwmrJ4YrWDUa3IBelRK5Bo1cidXZM7jkLtMQDV2Ms4T38D99XlMmL+aOasOsHhLIKuPp7Mx2MKm4HK2R9Tgpz/PYfMlTqd+RWDG1wRlfEt47k9EF94Qsug6UQVCRhfcIq7wtgg9NqXH5unRlbQQW9RMfGkbSVXdmCo6xTRXdpFQ1U1SdSdJNb2Yq3vRl/WhL3+EvrwffXm/4OUp7SeipJfwon5CC3oJL+4lrKibkIJOQgo6CcprJyivneD8DgLyO/G3Qk+MpY3Y0nZiS9tF6DFU9QhltNJ2okvaiSvrIba0mxhLF7ryXvQVfYLaZOkisqid6JJOooo7iCxqJ6KgnfD8NsLzW4gsbCOyqJ3wglZCch4SlPUA//R7nEq/y8m0OxxPtmbKLY4l3+R4yi1rKes6x80/cjThR46YfuSw8QcOG38QHx+yDifcFfU12yOusS38S7ZFXGFr+GW2hF9kS/hFNoddYGvYeQF2rLkjXDAybw2uZ1NgNZsCqwXY8a/G27+SzQEVbA6oYP3JEtadLmHdqUJWHkpnsY+OhVujmbn8KNM/8eX1pT5MmrcczfjZyN2moXSbiNTZE5mLF0rXccg0rkjVLoyWq3BQapAoVTjIFcIgQmuOkQnjEhzlCiQKJRKFErWLMzInJ1TunkyfNZMw/+0k6w+Tm3SCwsSDAvQk+FGctJ/iRKGUlWfy+wP0DN+19bLgM9LQ0JHWxdihxx4vG3bosccrieHQY1NrRlJ6RroQ/hn0/B2lJ990kDzjASFNgpcn1ygoP8WmvRQad5Fv9iPfuJfowC3MfW8aLh7OSDQapEoJcoUERwcJ/xwj458Owu4tqUqJVKVGonVB5uKFwm08Kq+paCcJ0DN50VrmrT3Mxz7BeJ/OYmt4BdsiKvGJqsNPf55Dpov4p31HYNp3BKV/T0jmj0Tl3ySm8DZR+TcF6Mm/SWzRHaF7y/IAo+UBJstDsaU7vqwFvaWV2KJmdCUtf1R4rPCTXN1DQlU3CdZ9WSbrxnNDZb/YTh5j6SK6uIeoom4iijsJL+kivKSLsOJOQos6CClsJ7igjaD8VoLyWwkvbhOhR1feSXylUD6z+XRiS9uJKm4TgSe6pJPY0m4ReGygE1nUTkRhGxFWyIkq7hhyzqb+BGU94GR6E0fT7nEk9S5Hkm9yOOkGh5NucCT5JkeSb3Iw6RbHU+9xIuUuRxNvccj8MwcMQvrpf2Rv3Pfsjfue3VHfsiv6Gj6RV9kWdoktIRfYEnKBrWEX2BYu5GDo2Wmd2yN2bgXViOntLyg+3v6VeJ8WpjN7n7Gw4Uwxq49m8eFOPe9vi+HNVSeZ+vFuZny8g8nzV+A0YRYKj2mo3Cchdx2HzEVYRyHXuglqj1IjqDhSYfKyo0KORKFEoVKLQzFt6ShXCEqPkxMyZzcmvz6FoJObSYw7KEJPacphisyCd60g4emMnmeVtV5W+Xme0jNSSdoOPfZ42bBDjz1eSbwo9Az39Pynocfm68k37yfXdJAc4wGyjAfJMe8jJ2EvuebdFBh9KTbvocDoQ6FJ+H+EntjK/Lmzcfcah9LZA4VKhVwhTGH+l1TKP6VSpHI5Elt5y8lNAB7PSai9puMy5W28Zr/P9A838v6GEyzbHcnmgFx2RFWzM7qevboLHDZf4WjiFfzTvsM/+VtOJnyJf8o3RObdIKbwtphR+TeJLbyLvuieADzW8pbBCjyGcqEzK6bwAXpLq9D6PUjpEUCnm8TqHpJqevl/7L1XVFwHlrbdvWa+6bYVQEQByjkjlMHKCZRAIJGRyFBUkaHIOVRRmZxzFsrZylaWlTNKlt295lv/fzEza3rWTM/ctJ//4lAlwEi2292/L6b2WntxqHOKutE5eurd79677NB7qo6+p/LIN5QefI/6wDsU3a8p6XwzJIs731LQ9Q2F3e8p7n5PYec7CjoEGMprF8zPhQNt5/os7uxH1vUKWdcrijuFDq2CtpcG4NHDjEHVGQCdvJaX5Da/ILf5hQF6BkNRbrMwkyer/hlJNc9IqH5OfNUzYiseEV32wJCS0vuIdfeIK3tAnPYesZq7iNW3ESlvIVLeIlJxk4iSG4TLrxNW+BXBBecJyj9HQPZpfNKP45NxDL+sEwbo8c8+QeAA+OihZ1/WUfzSD+GfKaT3QLu6Pn1ShAGFhunMCfVsDVezIUjOSs805juHs2BLILOcdmI7awnmk+cboMfEZsoPoGeUqfmI0GM6oO6MGWfGmAEVaJyVNaMtLBhlYc2kGZNJit6DMj9iiNLToo6gRSMSAH8Y9HwKfP6WZa6PLQQ2Qo8xfmkYoccYv0r8VOj5Kd1avxR6mlUfoKdWPQA92gjqtWE06kJp0YbSrA2jSRVCkzKKclksGWmxbHTezuzFjthOnYf5eGvGWZgxxnQsvzMz4f+YCyrPGEtLxlqOZ7TVRMwmzsRs8mwsp9szacEqpi3ZyLz1vqz1SmR7WAF+qY0E5h8iuPAIUcqzxJdeILH8EqmVX5FW/hVS3SVSy66QW3eboub7lLQ/pqTjEXn1d8ituy0MJxwEPaqu56h6XqLu7UfR+ZLi1qeUdLwwQM5w2Ck//C3lh7+l+ti31B3/ltqj76g4/I7yQ0Ov1V+v6vvWMKxQ2Sf4b2Tdb4WOrwHzcVHnawrbXxgmJOe3PqOgTTAv60GosP2DcjMYbvSqjv61nKbn5Da/oKDtFYXtrylsfz3kfF7LS3KbXpJS/5Kkmn6SavpJrHlBQvVzEqqfE1vxBEnpQ8Sa+0jU94hRf41YfYco1QfoMQCP7BphRVcILhDa1IPzzuKfcRz/jOPsyz5BYO4pAvNO4Jt5DP+Mo+zLOi4YmLOEoYS+aQcN0LM3uUuY0aMvd6X1CMCTMrCHK7GBbSIdW8JUrPHPYeG2SBZsCWTGqu2Mn7EY0wlzMLObgamtMLNnrNVETK3sMLWyM0DP52PGCR6ecaaMGdiubm5phamFJWZW1oa0sLHFxNqaMVY22E6xIzp8J8VZwdTrEoZAj1DaEozNLTrJD4zMv8TjM9J7hqs5nxoxYYQeY/ySMEKPMX6V+KnQ86nVE/pvg39rpafeoPQI0NOsDaVeK3xWvSIWrSyd1IwcXNz3s3i1KxNnLcPC2o5xllaYmJnyTxamAvSYWzDWcjxjrGwYYz0J04kzMZ88F+uZDkxc6MT0pZuYu86HtV7JbA8txD+ticD8Q4QUHvsB9KRXXCW17MoQ6FF0PEHW+pDsmptkVd+gqPHukPLWYOhRdvUja3uGovPlJ5WeskOCwlN3XACfyiPfUHH4gwJUfvhbKo58R9nApGb1oT+gOfxHAX4OvKek9xtk3W8NWdTV/2GeTvMT8lqektfy1AA+Avx8KFPpgWewojP8dT30DFeD9H6f9IZ+kmteklzzkpS6V0hr+5HW9pNY9ZyY0kdEa+8So/7akGL1bQP4RCpuCsAju0Zo4WVCC84Jmf/lQDu6YFYOyj9pgB6/9CP4Zxxlf/YJ/DKO4p9xWGhVzziIb3ofe5I6BT/PwO+DoccrpY29iQ3sEJfhHKFh/f587HdEsXBrEDNWbcd6+lAj82iriYyxnGCAHhML6yHQo/fxjDUdJ6g9FgOrJ8bbYG49HktbO8bZ2GAy3g67qROICtlGYUYgddp4g5G5VRM5MLsnitbS6L8r9HzsfSNBj/5aI/QY45eEEXqM8avEXws9g1Ue/QNxJI/OSPlTPT3NSgmN6kgaNR/Unlq1iDpVHJXyVGRyFZmFbQRE6djulcOiFXuZNGkxluMnYmppwe+tzPidhZmwI8nKhjFWtoyxmYzFlHlYT1+I9eylTFm8hlkrnJm33pcNvqnsipARlN1JaNFxwmUniVJ+SbzuIvGlF5CWXyG94hqZVdfJrLpObt1t8urvkFN7i+yam6RXXCWz6jpFjXeFdvURoEfV/QpF50sUnS8/6ukZDD+Vh7+l6uh7Ko6+NyhAlUf/IGxJP/H/UHny/6X06B8Nqyo0h741GJRLeoT9W3rfjlDCek5O02Nym5+Q2/yEgrbng0per4dAT07Tc3KanhsMzIXtr4coQIOVHv2x3gBd1PUN+W3vyG56RV7z6yGZVf+ClMpHJFU8JLn8AdKKh0grHgom59J7gr9HfZsoxY0P3h79fJ6BwYRhhcJ8npBCAXwCck7im3YY37TDQpt6+hH8Mw7jn3EYnzShTX1PUic+aQcMKyn803vxTesyKD2eSY3siq5ge1Qpm0OKWeoWg71LiAF6TCfMwWT8VEZZTuBzCztGmQtTlvXQM3qchTCQcAB6RpmYMsbE1ODpMR2AHxNziyGeHrupExAFu1CQvp86bTxNGqFrq0UdQXuphCaNyAA9bdofgs/fCno+NbNn+PuM0GOMXxpG6DHGrxKf6t4aPJV5eJv6p2btfBRmNFEfVXoa1SLq1SIa1BLaFBLaS8S0KcW06sJo0YXRoIukWiOhXBVPpTwVlayYrKIGJPmnCU47RmDiQdx981m82IWp0xZgaT2eUdbj+MzaXOiqsbYT1gdMmMH4GYuwm+2A3ZwVTHFYy7RlW1i8NZBtwbl4xmoJye0mvOg4YcUnEJecFaBHd5HksstIdZdJLbtCRuU1MqtukF5xjUT1BRJU50mvuEZx0z1kzfeFfVvtHzw9yu4XqHoEdWd4Du7e0vS+oXRY2Us/v0dz8B3qg+/RHPoW7eE/ojv6z5Qe+7+UH/9nw+JQfQu6fmqyfthhSY/QAi/remVQewZDT3GXAD1F7a8pHvDo6JUbPcwUtr82gJAedvRmZ3n3N8i7v0HR+y2Kg39A1fcHZJ1vKWx7RV7zC3Ian5HT+IzcpufkND4js+4x6TUPyap/YjhOqbxHUtkdEktvE6+9aejeEskuEVF4cQB4vkQkP49Ifp5I2TnDUtGQ/DMEDJS4fNMOD6g+Q6HHK6UHT2k3ntJufNP78E/vxS+9W8iMLrylzbjFVrErugLnCDmr9iaybFek4OmZuRTzyfMxtZnG781s+Mzcls/NbAzQY2o5ntHjLPhs7LgfdGqNNhXUH72f5/OxggqkN9bbTrFDHLwVWWYQTbpEmjQDHVuaCNrLxDRpRMKcngHoGQl8BgPQz/Hw/BToGek9Rugxxi8NI/QY41eJ4cMJhys9g4cTDld39A9E/QPzr4Ue/RTZerWIJrWEFqUAPB1KEa3acJp04dTpIikri6FUk0ClLAN5kQZpQTsh2ZcIzbxERMYF9kdU4eTkw+zZyzG3GM9n1uP43MaSz82thP+YbCZiMWUWtrPtmThvCRPnr2SKw1qmL9/K0u1hbA8txDO+nKDcbkILjhJSeAyx4gyJuosklV5EqrtEkuYCUt0lMquuk15xFanuMjHyM8TJzpBVcR1l2xNkzfcFM3O70LKu7HyGuvsF6t5+Sg+8Rdf7xpCa7leG1Pa8HpLqHgFYZN39KLpfo+x5g6L3G5QH3qM68B3qg39Ec/iPlB37v+iO/IHSw999UHh63qDseUNJ72vkPa9QHHiDsu8t8p5XFLQ/I7flMfktjylqf4asU1iBoeh6K0BPu/CzoLWfgtZ+ijveGHZx5TY/I6f52YAx+o0BeBS93xrm+qgP/hH1wT8i63xLQWs/uU3Pyap5ZMjs2sdk1z4mo/YR6TUPSa26j7TiLomlt0nQ3SJee5N47U3DcEJxyRUiBlSe8KJzRJVcIqrkEiL5RcIKvyS04CxhhV+yL+u4Ye2Eb9phw86twR1bntJu9iZ1C96eVAF4/DN68M/owSelhd1x1bjGVOIcXoKTVzLLXUXM/mIXtrOWYDFlAaY20/jduPH83syGURbjfwA9+nUnY83MMTG3wNTC0mBiHmtm/mGGj4kpJhbCCIWJUycQG+qMPCuI5rIEoTVdG0WLVihvtQxAT6NW/JOg529Z4jJCjzH+XmGEHmP8KvEx6BkOPsO7tUZ6aI40El8PNIOh52NyuWEVhUpEywD0NKsjadJGUl8qolsrpkmdQIEsj6jcWoKyDxCSfYb96ecIzDhPaNpRdu4rYfmmQEzGz+Jzq/GYjJ+ApcWkgUm4dtjNmsekBUuwneeA3YLlzFyxidmrdrBqdyyuUSp8pbWE5vcRKT+BSH6KaMVp4tWnSdacJVF7lkTdBVIrLpJde4OsymuklV4mRXOJTN0ViurvImu8T3HjQxStT1G0P0fR/hxN9ytKD7ylrO/dD4BH1fkSdVf/kCzrfYO6q1/o9DIYj19Q0NpPUftrZB3vkHe9p7jjPYVt7yhqf4us51vkvd8h632PvOcd8t43KPreUtL3CuWhN2iOvEPR94qSA/3CyomBNRjq3n5UPS9RdvWjO/At8va3yNvfImt7g7xdyMGdYoru10IH2cCU5pKedyh6hQWoygPC5+sBSK/05Le8JKfuCZnVD8msfkh27WNy65+S1/yCjNpHpFU/IK36AcnlX5OgvU2c+ibRimtEya4gKr5MlPwyItklwovOEVb4JRLlFaJVXyFWXCa04KzQrZV9goDMY+zLOs6+rOP4pQ+YmAda1vXb1T2Te/BM7sFL2ou3tBvvlI4P0CNtY3dsDa7RVbhEKHDykrLcVcQsp53YzV6K+cTZmFhP4nMzGz43s2GshY0w7NLKBlPL8Yw1txJWnZhZChPAB9LE3MIAQIPBSO/tmT1nMpnxu9EUhNBUFkdrabSwfHRg3UqzSmTYxzUS9IwELT+nq+vnlsb0968ReozxS8IIPcb4VeK3v/2NoLIMK2npQWi410d/briC87Ecvh+oQfVD4BnysB20c6tt4HPq1SKatJF0asNoVonIK8rBJ6UCl6ganEWteKecJjj7EtHFl/CJa2K9pxSTifb8HzOhJdjKcjJWNlOxmTyD6fYOTF7kgO28xUy0X8GcVS7MX+2Oo2cyrtE6fFMaCNZDT8lJopUniVeeIElzgkT1KZLKzpNaeYH0qstkVV0lq/IaedW3KK69R3H9Awrq7pFff5+S1ucou/oNwKNXeFTdrwxlLL2PRz+UUP96Wd871D2vUXa9QtHZj7zj9aClo28oan+LvOs9RW3vyWl6Q0rtczIaX5HZ8pbsljfktgr7uYq631J84DWKvrcoDwrQo+4T9m/pF5vqwUvV+ZLyvu9QtL1F2f5eyI63KNrfoOx8g7r7Hbo+wURddug9ql5hLYWs6w0lA0MM5d3fUND5hryOt+S3vyG36SXZDc/Jqn9GSuUDksruklj6Ncnl90ipfEBG7RNhy/pAplQ+ILn8Hgm6O0QrryOSXSGy+DKRxReJKD4vZNEFxIrLSJRXECsuE1b4JcF5pw2lrX1ZxwUjc/oRfFL7PkxgHoAe75QDeKccEBaQpvTgLe3EL02AHq8kYUDhLkkl2yKVOHoms2R7BNOWD3h6bGcwxnICY8zHDyyuHZomFtaMsbA2wI8wfdmMseZmmFiYY2ppxWhzKz4fZ4GJhTUWVtZY2dniYD+TorS9VMhDaSmLoW0gBwNNq0ZQefRdXCPt3xqsrP610DOi2jPo7w9WaY3QY4xfEkboMcavEoOhRw8+vwb0GHZuDayeaFVH0ar54PVp0YioKwuhRh1BcUE2fomlrA/WstS7hl1xx9mXeZFk9TUi0jtxC8rHdvZKfmdpwe8sLRhrYYPthFlMmjGXmQ4OTLFfgt18ByYuXslcx23MXe2Ok2cq7rEV+Kc1EVJw8AP0qE6QoD5OsvYkiZoTJJSeJaXiPOlVl8muvkZu9Q3yawXoKay9R3HjQ/Jq7yNre26AmrK+d2h7XguAMQA92kHTmPWmZf3r+mN1zxtUXW9Rd78T9l51CGspivVKT9sfyGt5j7T6BSl1r0hvfEtG4yuyGvvJaemnoPM1xb1vKB5QfZR9bw3eoOKO58janqHseIGy4wWK9ueU932Hqu0tqo5vUXV8OxR6et5QevC9AXqUPW8ED9DA6gr9JOe89lfktArwlVX/gozaZ6TWPCW5/AEJursk6O6SVHZfMC9XPSa58hHSqseGTKy4R1zpHSTqG0QpryFSXCWy+CLhReeIKD5PZPFFokouIVZcNkBPSP4Zw3JRPfToN6v7pgnAo8/h0OOb2o1/eu8noWfqsm1YTl2Iic10xlhOwMR8PCYjQI+ppQBDQ6HHYkToMbUcj4WVNTZ2dqxwmIM8Yy9VJSG0lsfSWhotgI9W8pOgR3+PDb4nf84Mnx+9ZtjfN0KPMf4WYYSe/8XxP//zP4SFhTFlyhRGjx7NnDlzaGlpMZz/05/+hLe3N6NHj2b8+PGo1eoh7//nf/5nnJ2d+fzzz5k8eTKdnZ0/+bOHQ8/w3VmDQWjwuZ8KPYPhp0Ud9dHSmL681aASlJ4WlYg2VSTN6kjqVWIatCJaNSIalFEoZKkESrWsDdIyY4cOx8AWnCUHiSz8igTFWSIzm1m6zh0TOzs+s7TGavw07KbPY+q8RcxYvIyp9suZsmgZM5dvYNGaXSxa7846nzQ8EyoJSG8mrEiYwhylOEWM4gTxyhMC8KiPk6A9TUrpl2RVXSG39gZ5tbfIqbpJTtVtCuruUdj4kMLmxxR3vfxBl5ayS2hZ1x54S+nBbwxwoxuYwKy/Tg8+6gPvUB54h2Kg/VyYwixkQfs35De/JbvxNWk1L0mve0NG/TvSal+TUfeKrIZX5LW+/aAM9byj5MBb5L1vKO7sJ6fpMTlNj5F1vKS4/QXy9ucou98ha3uDrP09JV3vkbe/obj1FfL2Nyi7vqH00B/RHfoW9cHvKO58bejiyml9SX7Ha/LaXpPR9ILUhiek1D0hufa5MKCw6gmx5Q+R6O4h1t5FortHbPlD4ioekVguqDvJ5feQVjw0qEGx6puIS64iLtF3bp0jUnYOseLyEE9PRLFgbg7KPWUAHj306AFHP5fHoPSk9uKbIXh6fFK6DGZmz8Rmdkkq2SmuYLtIhaNnMg7bwpnisBnzyfMZay0oPSaWQteWyYCqY2JhbVB6TH6g9FgwZpyZUN6ytGKshQ1jzMcLJTELSyzG27Bh3XLUeQHUqSJpKYsZAj36bFFHCWWtgS6uj6k9f82k5o9dN/j+HsmnZ4QeY/ySMELP/+L4z//8T7Kzs3n37h3ff/89t2/fxtTUlEuXLgGwf/9+XF1d+dOf/sTTp0+xtLTkxIkThvevXbuWqKgo/vznP3PlyhVGjx7No0ePftJnfwx6BkvZI8HQp8zKfy306P0CjQqRkCXhNCrDqVNF0qAV0aUTJtTqSpIRZ6hwFlUx070Wh4AW1oT14pNyFknRGWLyutnkLmLCgiWYT52N5YSZ2M1YyJR5DkxbtIxp9iuZvngVC51ccFi/m8Ub97DeNx3vpGr2Z7YSITtKlOIUYuVpYgfKWwmqY8QpjhCvPIFUd5aMiktk1Vwnq/oGUt1lkjQXSdJ+RVb9PXIbH5HX8pTcxkfkNDwkv/kJso6XyDv7kXW8RNnzBk3fNwMb1YXOLHXfW0q6+5F3vUTZ+xrNwXco+96iPPBOmJo8MGAwr/0VuW395La+IqfpDVkNr0ivf01mwzsy6t+SWttPWs1LA/jkDGRB2yvyO1+S2/6czIbHSKvuklb7gKKOVxS295Pf+kw4bnuFrOMdso535DW9JLv+GXlNLylqf42i5z1yvaLT8lLYol7/mNT6p2Q0vSC94SXJdc+Iq3xMXOVj4queEVf5lJjyx4i1DxGp7xOpukeU5gES3SPiyp+QWP6ApPKvDZmgu0O89jYxqhtIFNcQl1xFJL+MSH4RseIi0aqvEMkvDslI2QXCCr8kMOfkR6FHX+LSd3HpF456p3Tgm9aFb3onnkmNuMVW4RojKD0r9ySy2CVsCPToBxKaWNoO8u9YDgGgwdAjbFcXTMx66BlrIfiATMwtsLabwM7t6ykrDqZRKx4Retp10QalR+/30YPPcPj5e0HPSGmEHmP8kjBCjzGGhLu7O/n5+fzXf/0X//RP/8STJ08M5zIyMti9ezcA79694x//8R/513/9V8N5Pz8/4uPjf9LnfAp6/pploX8z6CmJokkRYYCeOq2ILl04LRoRFYoE4rNk7IyuYr5PIyuCO1kvPoyn9CxhOaeIyOpm0944pixZg+XsRVhMnI3NjAVMnu/AtMUrmL54FTOXOAnQs86dxRv2ss4nzQA9kfJjiJWnkajOEKs8SZzi+FDo0Z4hrewCGVVXyai8Rrz6ArHKc0gU50muuEVazV0y6x+RWv010srbpNXcNQwELGh7bpibU9jxnMKO5xR3vUTW3U9hx3MK2p9R1PkCec8rIbtfU9DxQsj2fnLb+slpfTmwzfwVmfX9AujUvSK1th9p9QtSq18MgM9LMmv6yax9QVbzc3LanpHV8oSU2gcklt8mpfoeBe395Le9JK/1hWGycnHHGwpbXxsWh2Y3PCevuZ+i9rfkt7wiv+UV2c0vkdY+Rlr7mJS6J6Q0vCCl4QWJ1U+JrXhCbMUj4iqfGqYvi9T3iVDeJUJ5l0jVPcTah8SVPyG58hEpVfeRVt4jseyOAXpi1TeJVl5HorhGVIng34lWXSZGfdWg8kTKLhjAJ7zoHEG5pwzQo/f0eEl7h0CPvmXdO01Qebyk7fimdw6BHre4ClwiFAbombpkC5ZTF2JqM4uxVhMNSs9g47IedvQ5XOkZazaw+20Q9IyztMJu8hQ8dm+lsiSM5tJomgegpq0shnZdtCH10NM2AEXD4UcPPX/Negoj9Bjj1wgj9BjDEP/93/+NnZ0dhw4d4uHDh/zDP/wDf/nLXwzn+/r6mDFjBgBHjhxhypQpQ96vVL0uqIYAACAASURBVCrZvHnzT/qs4d1b+lk9f81k5V8KPS3qSJpVETQqJTQqYwZei6BeLaJOE0W7LowmjYgquZjMvFz8U2pZGdrBqrBONsUcY6/0PMHZ5wjJO45zYCFTHXdhNd8Ji4nzsZ6+kEnzlzJr6RfMdPiCGYudmL1sMw5r3Fi2yWuI0qOHHrHyNNElx4mRHyVOcYQ4xRGS1KdI1pwmXnGSWNVZErQXkCi+JKLoJP5ZhwkpPE2k/CIJpTeJL71JnO4GsdrrxGiuEa2+Sqz2OokVN0msuEms7iviSq+SWHGDtLq7pNTcIbnqFslVt0ipuUNKzR2k1bdJrLghvKfqNklVdwfyHolVD0iqfkhC5X2kNU9JrXtOcvUTUqqfkFb7TICe2hdk1r4gre4JSTUPSK59SGL1fWJLbxFffoeMxqdkt7wgt+klsq535La9JLdNWFaaWvuYlJpHpNc9J6uxn6zGflKrnwlZ91xYJFrxgPiqRyRUPyW+6gnRZY+I0t4nSnsfceldokvvI9HdI1J9hwjVbSJUtxFpvkZSep+4CsHPozcxJ5XdJ7H06yHgE6u+SYz6OjHqq8RprxKruWYocUUUnx+i9gTlniIw5ySBOScHOrgO4Z1yQBhEmHnoA/SkdOKVKqg8XtJ2vFPb8U5tZW9SPbvjK4dAz5LtEcxY7oL1dHvG2c4eYmTWg40efAYfD059F9dYc4sh0GMzcRJzFiwkJMiLmoHSVqNWLABPeaxB5ekojTEcG0zOHwGfvzf0DC6nGaHHGL8kjNBjDAC+//57/P39Wb9+PX/5y1+4du0aJiYmQ645f/481tbWALS3t2Nvbz/kfH19PStXrhzx7+fl5fHb3/7WkL/5zW8Mvp3akjBqS8I+Ws76MfD5MV+PAY6Gzff58KAWoKdBHU2dKo5WzQevQoMmiiZdOK2aEBoUYoqLMhDl1bJB3Mvq4BY2RfbgnnaJkILrRJRcxj+pjVWuCcxZ44PN3MVYzliIzdzFTF/qxNTFjkxd7Mj0xetZ8oUbqzYHsNE/Ey9pNfuzWhAVH0ckP4Wo5CSRxUcQFx0iWnaQhJIjpOjOkqI+TUzxUSKLjiGSnyJcdor9ucdwT+7GI/kAPhlHCZdfQqK5TozuJtHaGwQVfIlf1gl2xXWyM7aD3dIePNJ62ZPSi1f6QYKKThGQdwz/3KP4ZR8lIO8Y+3KO4pXai2dqF3tSetmbegCvjGN4pR/HN+cM+/PPEVx0kUjVVRIq7pBcfY+k2vuk1j0io/EpmY3Pyax7SmbdU6TVD0msekB81QMSqx4g0d4ivuxr0uufktPST37LG8GX0/WarLYXSBuekFzziOSaR6TVvyC9oZ/UuhckVT4jseo5CdWPkZTeH8iHRJc9QqR9SJjyLqFKAXAk2lvE6G4So7uJWHcbse42ktI7hkysuEdy1QOkFfeFrq3yuyTo7pBY+jVxZbeJK7tNbOktEtQ3SNAK0BOt+oooxWVEJZcILz5PWPFZwmVfElF8nuC804alo4LqcwzftIMEZB5hX9ZRAXpSOtmb0olnWideqZ14J7fim9KOb2orexLrcI0txzW2jK1hctZ4pbBip4g5jjsZP2MxY8dPY5S5LWMtbBhtNrJ/Z5SpuVDSMrM0lLvGmZsLC0jNLTAxH89YM2vMrScwbdZsVjo6khAXToNOQt3Av3M92OjLWx2lH1SftkHdXXr4GVzq0rez/xTo+THVdXj3lqGEppMYoccYvziM0GMMvv/+eyIjI1m2bBn//u//DmBQer7//nvDdQcPHhyi9EydOnXI31GpVD9L6RkMPSOZln9quevnQs8Pv2UOhp5YWtQfZvw0asU060S0acJoVEpQyNKIzq9mY2wnX4Q2sy6yF4+UiwTmXiVUdpng3CO4hJaw0k3CFPtVWM1cxPg59kxbIgDPFPtVTLNfw+LVrqzcEsCmgCy8pNUEZrcSWXSMCNlxImTHiZIdJqrwIJLiPmLkhwxKT4zsmAF6wooFlcc1sR23xE72pPTil3Wc4MIvCSk6R2jxefbnncY/8xiu8V1si25me0wLLtGNbBbVslVcz874VrbFNOES3ciOuBZ2xreyI64FZ0kdWyKr2BxezebIOlxi2tgW04FrYi97047gk3WC4OILRJfdJL7qaxKq75Jc+1Dw29Q9IbXqISk1j4ZAT0LlfcSamySU3yWr6QW5ra8oaH1rgJ6c9ldIG54IpavaZ2Q09pPZ9NoAPQlVT4iveoREdw+J7p5B2YlU3yVIdotA2Q0CZTcIU1xFpL6GSH2NuNI7H7LsNvHld4grv0tixb0PPh7tLRK0t0nQ3h6i9MRpbhCvu0Gs5itD19bwwYQRxecJyT9jAB7B2HzUAD0BmUcM0CMoPR+gx0fahk9KCx4JteyOKcctphTn8BLWeKWwclcUcxx3Yj3dnjHWUw2rJ8aYjx/Rv/O5idkQ6BHA5wP0mFrYYGphg/l4G2YtmM/a9etJT4qmXis2QI9BxRkoaemhp6NUUIDay2M/Cj6DO75+kJqRlZ4f7eAaBDuDVSUj9Bjjl4QRev6Xx/fff09UVBQODg7827/9m+F1vafn6dOnhtcyMzM/6enx9/f/WZ6e4YMIR4Ia/TfDT+VPGWo20vJCQ3lrIBtVYhqVkiE7vZq1YppKxbRqImnVRFNRkkhmsY5d0j6cIvtYLT6OR8oZgnLOsr/oPMGai3hkd7IhNJ9Z9quxnmWP9Sx7ZiwWlJ5JC1YxeYET9mvccHTex9bAfALSGgjL60AsO4pEfgyJ/BjiokNEFfYiLjpArPwoSeozSLVfEqM4QXjBEUILjrIv5yC+Wb24JrbiltTGzqRWtse34jwAMTvjW9md0M6u2BZ2xbayO74N17gmNodX8EWAklW+cpZ5FrDEPYfFblks2pXBol0Z2Ltmssgti8XuOazwLmK5TxFLvYtZ6i1nmU8Ja0Kq2SRuZnfqQfbLLhCmvoqk/BZxFV8LWX6XxMq7JFffJ77yLonV90msvk906S1E6mskVHwtmKLb+slpfEFecz95ba/JbX1FSs0jwW9T/YT0hn4yGl+RVv9SgJ6KRyRWPiK29B4xOqEbS6T5mkj1HcIUtwlVfE1wyS0Ciy4TVHyJYNllIpRfIVJfI0orpEhzhVDVRaJUXyFRXhW8O8prRCuvCybmwS3rqqtINNeQqL5CXHIFiewy4uJLROSfIyL/HJEFwgyf0IKzBvAJzDnO/uxj+KUfMmxZ907txSelC5/UTmHRaGo73smteCY14pnUiEdcNa6SUnaJdWyPULDeNx2n3dHM+8IVq2mLGG01hc/NbAQj80B5ayTgEdrUrT50dllYYmopdG+ZWE5grOUkRltNxH75MlzddiHPS6C5NJomfYlKX7Ya6NjSA09HacwPyluDQeQnQY/64/fpTxlQOPgaI/QY45eEEXr+l4dYLGbRokX8y7/8yw/O7du3Dzc3N/7jP/6DZ8+eYW1tPaR7a82aNYjFYv785z9z9erVn929NXwwoV7RGaz2CAbjiB/kTwGg4e/9GCD92CyRBo2gBrWoJdSr45ErlHilnWJJ+GkcIs6wO+UQYfKjhKnOElZ2ke3pLaz0T8d25kKsZizGbvZSFqxYz8yl65hsv5qpDmtZumkPX+wMZkdwEUEZLUTmdxMjP0RsyWFiSw4jKe4zQI+k+DDRJceJLjlOROFRgvIOsj/voAF6PFI7cE/rxD2tE7f0TrYnNLFJXM26sFK2RlXhElXN1rAKNoeX4xJVzTZJNRuC1awOkLPMI5MF25NY4JLAApcE7Hcks2h7EvYuiaxyz2SVTyGO/jKWexWyxDOfRe7ZLPEqwjFQJ4BP2mE8c04TWHyBINlFguWXEGlvkFh9n6SaB8SW3xkCPTFlt0mrf0xh11uyW4Tlovktr8hrekN+81sya1+QVP5IyKonSGuekd7QT0LFI+LK7pNc9YDEinskVtxDormDSHObKO0dIlW3CS25RWDRNXyzTuGbfRK/nFN4557Et+AkfoWn8C08gXf+EbzzDhOYf5SgnKMEZh0lIPso/jnHCMg9TkD+SQLyTwuZe5yg/BOEFJ4mQnbhg5G5UIAeUf45wgrOGcpbemUnMOc4+7KPGBaM+qQdENZOpHXhl9qBb0o7XslNeCU2sDehFo/oStyiynCN0rIjUsmW/Tls8Epk8ToPrCYvYJTlZMZa2GFmZcdYM2tGmY4z5OhxZoweZyZMYja3wMTCElNLK6Fjy3K8sGDU0orRZhMZbTGV31vMYtnq1fjv86ZS/UG9GQ4zbYO6uQafG96qrldi2nXRAvhoRCNmszrSAD6fKnv9lDRCjzF+SRih539xfPfdd/zmN7/hd7/7HaNGjTJkZGQkIMzp8fLyYvTo0VhbW484p2fr1q189tlnTJo06WfP6RkMPYP9O78G9LRqxB+V3ZsGoKdJLaFBk4BarcYv6wQLw04zP/Q0u6VHiSo5TZTmApGll9iW1Mxyr1Rspi/EYqo9trOWMH/ZBmYuWc+UxWuYvXIzjtt8Wb07hF2hcoIzWxEV9BAjP0ScTEhx0QGiCnuRFPchKT5MVNExIgqPEpJ7kICsHvyze/HL6sEns4e96V3syehmd0YXHlk9eKR3sSu5FefoWnbFNrArtoFtoirWB2tZH6JhbbCa5QGFLPHNY5FHBvNck5m7K4l5rsk4eKTj4JHOMo9MvvDOw8mvmPVBKtYEKlmzX8VKPxkrfeU47VezPrKBnckH2J16BK+ck/jnn2Vf4TnCVVeJLr9D/IDSk1TzgISqe0h0N4mvvEtW83OKut8JRuaW5xS2vSG38TV5TW/Iru8ntfIJyRWPSSp/RGLlY6Q1gsoTXzrgvxlIifYWkWohQ0uuEVhwFb+c8+yVHsY9pQ+P1IPsTT+MR+oB3FN7cEvpwC2lnV2p7eyVduCZ0MqeuGZc45pwi29md0ILHkmdeKb04JnSi1dqL36ZhwjIPkJQ/klCi84QVniGsMIvCc8TMjT/S4JyThsMzP4Zh9mXfWQI9PhlHhBWTqR14Z/Sjp+0TVB5Euvwih8EPaJSdkQq2RaUxyafZOzXumM5aT6jLCZhYjkBi/ETMTEf/6PQowcfEyuhnGViYc3n5hMZbTmdUbbzWL15MyGhftSo44eUrYYoNwOwM7ikNRx8BpefDJ6enwE9H/ui8WPqrRF6jPFLwgg9xvhV4lPQM8SvoxwKPsMXj44EO4Ypyz+hDDaSp2D4a02qaFo1Ilo1Yho0CSi0GvYXnmax6DRzw06xK/kE8arLSCtuEK29gXtcM6u9Mpi4cA02s5cyad4KlnyxhZn2jsxZtpbF63exauc+Vu+JYke4gpCsNqIKe4ktOUyMXDAvi/IPICroEYzMylPEKc8QU3KKsPzDBOYcJCC7D5/MHnwyetmT2sWejB5cpe24SttxS+lgd2onbgktuETVsDm8gs0hZWwOL2dtsIYl3oXYexWwcG8es10zmLk9hRnbk5m9I4EFu5Kx353Kqr3ZrPHKY5VnPmv8ZKzep2R9sJaN4WWsDynFcZ+KNSGVbIxqYnN0K3vSDrG/8CyBsvOEKq4g0d1ErL1BUs0DkmoeEF16iyjVVVJqH5Ld8oK89ldkNz4TNqe3vSGnsZ/cxtcC9FQ/I6XqKfG6+0Rr7xJf/tCg9Ei0t5BobyFSXSdMfoWgwguEFF5gf+5ZPFNPsDvpIC6SJrZE1LAhpIIv9qlwDChhpU8xSz3zWOGVi6O/jHUB+az3yWKNZzor3FJZ4Z6C49501vjlszm4BOcwFdsjK9gR08Cu2BbcE9rZI+3AM6UHn/Q+/LMOsz/3mKGc5Z9xGO/UXvwyha4tA+xk9bEv5xD+GT34ZXThm9KOt7QZ7wHo2RNfg0dMOa5RWnaJNOwUqXAJK2SjXwrzvnDF3G4Ooy2mMs56Ela2kzG3nsAo03F8bmLKKNNxfDbWxHCshyA9AJnbTsTKbhKmVhMxtZmNid1CpixYi5u3NwmJIuq1iXRUxNE+MI15MPQY2tcHoGiwIjTSnB7DTi5tlLC09CPw83O6u4zQY4y/Rxihxxi/Svy9oeenPEw/NVBtyENZHUPrwAO7SROPWqMgVHkWp6TLLJVcZHfKWRLV10gp+5ok3T2Cs47gLtJiv263oOwsXceKdS7MtHdk1mInFq7ZzvId+1jjGYOrSE1odheigj6iZUeQFB9GUnyYyPwDiAsPEq84TrLmLDHKM0QrThMpO0m47CRhxScIKjyKX84hvHMO4pXdh2fWAVwTW1kbXo7TfjWLPfJYsCuTRW7ZLHXPY/meIlbulbPWr5SN/hrW+6r4wqOIFbtyWbYjG4ftWczeEM+01RKmOkUwcUUQditCsF4WhJ1TJFM2xLLcq5Ctomo2hVewJriMdWHVbI5qwC25l4D80wQVnyNYfolI5TVEquvElN5BrLmJSHWdWN1tMhqekdPST1bTC7Lqn5HT+IL8lldk1Q+0uFc9FRSesofEqL9GrL5DtPYusaX3iS29h0R7i/CSrwgpvoRv1im80o7glXYEz9TDgsKTdICtompWeBexyC2LuduSmeOSwFzneGZvljBzYyQzN0Yxa10wMxx9mLbSi0nLPZm00pcpjv7MXh+C/bYYluyMZ8WeNJZ7F7DST8a6IA3O4mp2xNazO7EV96Q24Wei4JXaHd/GrphmdsY04BrXZFCP3BNb8EzpwCdtIFNa8Epuwjt5oLQVV417dJkBelzFGraFF7HBV8q8L1yxmDiPsVbTGWc9CQvbyZjbTGKsuYUBbvRKz2DFx5AW1oy1sGGUmR1jbRdgNmUpC5x2ERgWSWZGPPXqODoqhBxextKrO/rzw8FnuOozHHo+Cj4/o639Y9caoccYvySM0GOMXyX+1tAzvB39584I+ST0aKJp00bRpJbQoolFpykmUnma9alfsSL2igA9quska++SXPoASdEZ/BNrcdjoyVSHtcxZsZGV67cxc9FKpi9awVwnZ5buCGS1Zxy7xTrCcrqJKjw4BHpEBUJZK0F1kiTdl0QrThOtODPQqn6SMPlJQopOEFh4HN+8w3jlHsIn9xDbYhpY6l3MfLdsFrhmsdyriLUBKrYEl7I5sBzn4Br2ijsJiOvFL6abPREteIQ2sDu4Dhf/ShxdC1jqksnCzQnMXi9mslME1kv2Y7kkEOsVodjvzsZZVM12SR3rg8tZE1zGpsgadid1sa/gDCHyC4SUXCZMcVXoohpQZMJLvhrStZXd/JKcxhcG6MluEGb7pFQ8JqH0AXHae0Sr7hCluk2U6jYSzddINHeQaG8ZFB7fzOPskR5kj7QPT2kf7gnduMW3syWynKV7spi7LZHpG8TM2iRm1iYR09eFMNlxH5NW+DFtpTdTlrszaakbdot3MsHBnQlL9zDjC38WbQnHwVnMEtcEluxOx8E9i5W+RawLVrMpvJRt0bXsiK1ne0wdO2Ma2BZVj4uobmARbRXbJXXsiK5jZ0w9rnGN7EluG5jJI6g8XslNeCXVsye+BvfYCnZLSg3Q4ybR4hJWyDrvJOY67cJq8gJMxs/EZAB6LGwnC34dcwvGmlsYVB196stbJhaWjDazZoz5eD4zm8AYu0WYT12FwzpPwsUx5GYn0aCOHhF6Bqs8I0HPSIqPYQyENurT4GOEHmP8ymGEHmP8KvH/F/SM9EAd6ZqPzRhp1Yhp0cbQphXgp1UTjU6ZSYziIM5pF3GKvYCH9CwJymvEq+8g1d0jVfsVopweljjvY7L9Ouat2syydZuYsWg50+YvY8ayzThsC2atTwp7Y6sJz+8jqvjIkIwoOEhsyTGkurOkVl0mXncRifIs4TIBdkKLTxIqP02Q7Az+hSfZk3mQHQltrPRXsWBXDovc8tgaUYNXche+qb3sS+8lLPso4oIzSJVXSSj5itjiS4hzziLJO0t0/pfE5J0kKLkTn+hGXPYpWe2RxdLtqczZEMOkVRHYrAhlnnMyO8V1+KZ245HUJhijxTW4JrYTkHtcKHEVXWRf4SUCiy4TIr9KlOoWMbq7ZDa8JKf5NTnNr8lseElu0yvyW95Q1P4NBS3vyG18TVrVU2I1d5EobxNVchOR8hahxVcJLLxCUPEVwhRXCSy6SED+OXwyjrEnqRePpC7c4lrZLm5gu6iGzWElrPRMw2FXPPO2RDJ3Yxhz1gUyaakHlvO2Yjl7M+bT12M6ZQ0mk1czbupaTKZswGTaJsxnOWOzYBd2i9yZtsqfBVslLNwai8OOJJbvzcTJN48NwUo2harZFKoWPFKBatbsV7MhRIezqIodMbXsjK1jZ2wdu+LqcUusZ09SI3uSGvGSNuKZ3IBXUi0ecZVCq7pYh6tYUHl2ijVsCc7DyTOeWU5Cy7qZ3RxMbKYwznYS5hOmYGY9foiiMxx+9NAzxnICYywm8pnFNEZNWIHZjA2scA4mITkNRVHmR+fvfKy09bFZPR9TekYEn4F76lMzfQbfeyOlEXqM8UvCCD3G+FXibwk9g03KgwHmUw/X4WAz0nWG1wegp0kbS6tGRJlcSqKig52pZ1gbcxbPtC9J0FwnWnWNOPVNMstvkFhynNV7o5nksJ7ZKzcxb7kj0xcsZto8B2atcGbZrkg2BeYQkNJMZOEhxLKjPwCfGMUJkkvPIS2/TKzmPHHaC0RrziPRXCBKcwGR7iKhqgt45RzBMbiMuW65LPdVsE3cgEdSJxFFp4mWn0NcfJaQzMOE5RwmNPsQXvEt7AjT4hykZJ13Put88tjgV8C2ECVu4VrcI0txDdOyLUDOlgAF672LcNiWyuwNcczYEIuTVzHbI6oIyj3EvuxefNM7cU9qwz25mz1ph/DNOUOI/Doh8uvElj8krf4lafXCeoq0muekVj8jreY52fX9FLS+RdbxHfLOP1DY+g1ZdS9JKH0gqDwlN4koucG+3At4ZZzBK/M0/nlf4pN9Gq/Mk+yR9uEW386umGa2hJaz2r+EVT6FLPOQ4rBLwnzncGauDmCCw26s5jszerITv7dZxmfWS/nMZgWj7VYzduJaTCdtxHTKZsZN3YLJ1K2Mm+7CuOkuWM7ZxcTFXkxe4sOCjRGscE9htXcWGwNlfOGXz0qvbBa4peKwJ4dlngV8EaBgc0QZ2yTV7IitZlt0JS6SCpzF5eyMrsItvkYAnpR6fKT1H6BHojXkdpGKDfuzWbUnlllOwnBCs0nzGGc3zQA9Y80t+P2Ysfx+zFg+G2syxNczuMw12nwCoywmMsp6LiZT12I1fwer3cRI07LQlmTTWTZU2flYfuz8cOhp00po030afIYDzPAvHYPvYSP0GOPvEUboMcavEr/97W+GDCb8VPfW4BwOPYOPhz8whz88PwU8w68b8rtKRKs6io5SCY3qOMrkUqTKFnZmnGdd4gX8c08Tp75ClOoqkaoLpFRdI0l7kvX+8Uxf5sy8VZuZu8iByXPmM3WhPfOctrN6bzwu4UX4Z7QhLj6ORHaCyIIjRBUdQyw7iqjoMLHy40i150ktF5SeOM1F4kovE6O9QrTmMiL1RYIV53FN6WHRnmKmO6eyKbSS/TlHCSs6TZT8S8TFZwnOOsLe2E52ierZEaZmrVciDtsimb8pmFlf+DHDyYuZTl4s2hjMih0RrPVIYKNnHuu889ngLWeDr5yVbtk4bEtl5hoJ851TcNwrY192N8H5fezL7mWPtAPXhA52JXbjmXGCANlVwjV3SKp9TlbzGzKbXpNS89Kwoyu1+gUZ1YLaI+v4DlnHdxS2fkNe82uSyh8ZoCdScRP/7HN4pZ1iT+pJ9qSfxCv9OJ5px/BI6mKbuAFnUTVfBChY5pGPg2smczZHMmdzKDPWBzJp2W7MZq5n7GRHRtksZrTVIsZYLsF80lrMJm/Bcuo2Js52Y8J8DyYt3MuEeXsZP8cDm7l7sZvjyoR5rkxe6M4sp30s3xHLag8p63yzWeGZxWL3NBZsS8F+dzZLPPNx9JOzOUyDs7gcZ0kZm0RaNkZq2CTSsiO6Ate4avYm1eMjbcQ3pYE9CZW4xZTiKtbgJtHgHq3FJULBpqBcnDzjmb5y2wD0zGGc3TRB5bGbzGhzKwF2TMYKOc7UAD4C8FgydpwlY8zsGG1pwxjbOVjO3MikJe6s8UgkOb0AlSybNm3UR43Lw6FmOPAM7vgabGhu04kN4GMAnWFqz4/dk0boMcbfM4zQY4xfJfRKz+BpzIO3qw+eojxS2/qPlbcGPyQ/NSL/pzx0OwwLGMXUqySUyxMoUFcQWvglnjmX2F94CbHiFmFFVwiXX0RadYuUskvsjCxgjuNO5q/cxOQZs5kwez7T7ZfjsMWbnWEFeCeVE5l/gFj5ceJKTgiwU3yIKNlhIouPEK08SaLuAum1N0mvv4205iYxukuEyk8TWHgcn9xD7MnowSmknGUBataL6gjIP0mY/BxBhafxSTvAltBKHL1LmLQyChsHfyznbGOU7UJG2S1g3NQlTFywGqvpDoy1m8s/jJvI6AlzGDvJnlF267BZ4MFsp30sd4lhpVs6K3dnYb8znXkuqSx2zWVLuBbPpEZ8pG34ZvTin3UYr/SDeKYfZV/BRcIU14mteEBS1WOSqh6TWPmI5OonSGueDipvvaKo/RuK2t5T2Cr8zKh5TqLuPmLlTcTKmwTnX8Q7/RTuKUfYltSLS3wnLvFtbBHVsy5Iy2r/Epa6pTF3q4S5W0TMXLePqU57mbBsN2azNzF60heMnuCIyURH7GZvYsqizcx02MN8x1AWrxezwjmWVduScdwuZdWONJa7SFm2VcrSTbHM+SKAaSs8sV3gju1CDybY72X2mmCWbovGaXcSa3yzWBNQiGNAEU77ZWwIV7E5XM3WCB2bQtVsCFOzKUKLs0jHdnEFnkmN+Ka14JvSwN7EKnbHluEq1rBbrGW3RMOWUBnr/LNx3BvHLKedWExbhNmkeVhMmomZ3WTM7CZjam1r6NYaY2bJGPPxjDa3YoyFAjr1bQAAIABJREFUNeOsrIU5PVaWmFhPYozNTMymbmTq0gDmr4/APSSL3LwcypXpdI3QrfWx/Vojlb2Gqz566PmB0jPs3vspCuynFCEj9Bjjl4QReozxq4R+4ejwvVv61EPP8MFlDSXhhhxp/s7wh6Z+j9DPAZ7B+36atcJD3PBNViuhUZuASpFLhvogccqLhBTfJDDnOkE5VwgtvEyc5hYxyku4hMmYs9qVhY5bmGO/hGmLVjFtyTqW7wjDXVTC/uQaxHl9xMhOECM7RrT8EJFFBxAV9yFRnSKp4jIpVddIqLhKpOYS0aWXiau4SkzlVUS6i/jlH8EzvQev7D78ik4SrL6Cd+E5diYfYF1EPXO252KxNALzxaFMdhSxfEcyDuuDsJ66FNvpDkydt5KZi1ZiM3UOFrZTGTvWFjMrO2ynzGbynBWYTJyL6eQlTF++kwVbwrHfEYu9qxQHjzxWeclZHSBnc7AG57Ay3OKb8cs8hH/OMfyyjuOXc4rAwnNEaa4TU3ab2Mq7xFXeJ6HyPknVD8lufklx93tKet6j6Pkjso7vKGp7T37zW7IbXpJW/YRY7ddI1DcILbqIX84pvHJO4J51mK3xTWyQ1LI2TMtK32xWeqWyzDWalW4xLNspYtHmfUxb4Ybdom1YzHDBYsY2LGZsw3b2LuatCmDRuiA2e2ThEVSKd3gV/tE17ItuYn9MM6HJPYQm9xCc2MUecQ3r9ufi6JOKvUs8s1aGMGmxL9Zz3JgwfyfT7d1ZsjmUrQG57AiV4xKsYMt+GZuC5DiHqnGJ0OEiKmO7uIqd0VXsjK5hb0ITvqmt+Ka14JVUi2d8FbujdewWa3GL0rAxpJg1vpk47klgppMbVtMdsJiyAMspcxhtNZEx4ydgZjPBsIbC1MKGMea2fG5mI3h4rCcxysqW0dZ22M5ezvRlbsx0TGTxliy+8ChAJC1GI5NSr0yiRyehqzyOrvI4OstiDdOXB29ZH2n31vCSmN7o3KKT/OC++2u+cHxKoTVCjzF+aRihxxi/SgyGnsF7t0aCnuH+neHQo7928B6u4Xt7fmw/14jb2fWD2nQDyw71x9oYdMpMCrWdpGovEKH4mqCcm4TkXiOk6CskqluI5BfZHCxjpuMO5i7fwFwHB2Yv38Bcx22s2xuHb6yW0PRG4gqOEic7RZzsJDElhxEX9yGWHyJWe5a02utk1t8mufoGUborRGkuEam6QKTqAmGqLwkuOU1w8WkitRcQlV4lsuwWPoUX2Z7Qy7rwBha4FjJjQzLT1yexyCWVdXvzWekswWbmGiynLMN21iomzl2OxcTZmFjPYMzYaVjZzmTi9EVMmbsS61n22M1bw/x1PizcGsGCrWJmbopmsWsuqzxL2BisZYe4hp3iBlzEtbjGteEh7cE76xgBeWcILDyHSH0NSdltYiq+Jr76PglV90isvm8YUCjrekdJ97eG8lZuo2ByTq15SqzuNlHqG4TILrIv/yxeOSdwy+zDOb6JjdE1fBEkY4VXOo5eUlZ6xLBip4glLmEsWO/LlKWu2C3cidWsHYyftRvb2XuYtTQQJ5dENnpksT+6GklKOyJpG5HSFoLiGwiKbyBC2kF01kFisg8RmNrG9kg1m4KKcXLPYemmRBasFjNtSQC289ywnbOT6Uv2sNotmS1+eewKVeMa+v+x917Pbd1puu70zdm7pns6ud0tZzm05STbypKVA0Ul5pwzcgYBEokEIwAigzlnUjlLVJZIimKSqJxt98yp83885wISm6IpuWfcvbUv+FZ9BXABvFAV19Lze7/kYGumjZCsKrbnugnJ8xGS52OntI4IZRMx2jYS9e0k6FtJfAY90TIfEWI34SIXmzLL+S7JyOpYDZ9viOHPHy/hDx98yZsLP+M//vI+v3trIX96+wP+8Oe3+P2bC3hjwTv8xxsL+N+//wv//sa7/PbtT/jdO4v448Kv+OvKnXy5MZu/bjCzbE85W5IcqI02/A4NbU4VvV7ZC9AzF+xMxxzt6jNTXc9n/czelfU8/fU/uf9mT39+HvPQM69fonnomddr0XPomVnIPBN6ppeNviSl9UJdzyzgmfnQfP6A/iXQ0+EJLh5t8Ujo9ARrFALuQsqdTZjcx5F6biCunCSraJAM62XybEPklZ8nRODms7WRLF6zlaXffcd3uxLYHJ1HnLASsbkdVXk/WvspNJWnUVaeRG47iKhsL+LKQ8hcp8ivuYyuZhBd3Sjahgm0tRPk14+ja5igoHkSU/tNjC23KWi6jsw/QpbjElGm0+xWHyBU1kO4vIcoeTdRsnbChY2E5daxM9XB0i1CPl6WwMKlUXzw9Q7+9NEa/rRwNX9Y+B1vfbGR977azjtf7GbhkmgWr81gY2QBG6KKWLbTwGcb1SzaVsDincWsTXGxW9pCmKyTHdJWtuY1ESJpI6bgEEklp0kpO0OuaxBl7SSahil0TXfQNd2hsPkuprYHFHc8orzvKWU932Nt/x5Ly2MMDffR1t5C4Zsk23aZzMoLpJWdJc50jCjDIcIL+9mlbGaHtJ4N6Q7WJhazIamI9TF6lmzP46tNGXyyMoZPlsXy4ZJ4Fi1NZ/EaMcs2aFiz3ciW6BK2RFvZmWhgc4SAtTuyWbo+hW83JrFkUzKrQrLYsEfMhnApITEFbI0vIyTJQVSGj10pHrYn2PkuzMhn6/J4f1kSv1u0mwXLEvloo4CQbAeRYj8RsmrCxAHCn3Vv7RDXEa5qJkbXQZS6hWhlM7GaZuLVdc+gx0+E0ElYnoP1aSV8l2RkbYKOr7cm8vaiFfzpo6/584ef89sFH/D7tz/kL+99xJtvv8cbC97izbff4ddvvMH/+v1b/O6dRXzw9WY+Xr6Tb7aksTkun7UJVr6N8LApyU9Ybg2FJVXUOZV0uhX0+lT0+BUvuDzdPvkLLs1sp2dm6mu24zPXTq5fcuh42fLgeeiZ1y/RPPTM67VoZvfWTGdnNvzM7Nh6WS3Pq6Dnv/PQnT1a/+/1DM/ee+R0+sT0+4W0edTYXLUUuQ+h90+QUz5ORvEgGcVXSC8bJLXkPLtEfhZvSeTzldtYtm4T3+1MYkuMiMi8crJ0bQgtfWgcA6jtp5FXHkdccRhh5SFElUcQOU4jrhpA5BxA5r6MpmYCTc04BY1TFDROoau/jiowisw1SHb5WVKLB0gqOkOS+TzJ5gFSLGfILT2PqOw8wtJziEsGkFhPIrGeJE3TS4ygmui8ALsz7GyJL2ZjjJn1EYWsj7SwMbqYDZHFbE2oJDTFSWReA2HZdexIq2FznIf1sS5WRzlYElHJ2rRqtglaiNDuY496XxC4lPuIMpwgvugMYu846rop8htvY2x/SFHnYywdjyhqDy4ZLe9+QkXfj5jbnlDQ/BBNwx2UNVNIfRNk2S+TUXmRlLIzxFmOE204RJSul92KJnZI69maVcXaeBOrIrR8vSWPz9el8fm6NL7clMniTXl8s0XEii0KVm1TsWqbipWb5SxalsJ7n4WzcHEonyzZyAeL1/DrBZ/xh7e+YMHCJbz1yVJ+/87n/Padz/njBytY8FkYn3ybyJrtGjZHFbMtvoLtaU7WxpWxLNzIR5tF/PHLGP7yTRJLwvRES2pIyO8gIb+DCGUT4YpGdkkbpmf2RGtan0Uz8dom4jT1RCv8hIld7BG62JZrZ12KmbUJOhZvSeD9L9ew4NOl007Pb/78Hn9+90P+9NbbvLHgL/zprQX89o0/8+s/vsNfPl3JZ5tS+Wa3nA0ZlewQ1rA1u56lMQ3szqknRVVHcXkFzZ4g6Oz3yV5Iac0FO6+Cntn1Pi/7ea6dXf/dmHmPz0PPvH6J5qFnXq9FPwc90w7QrBqeuaYw/yuhp8Mno+35Q9wjp9svYn8gl26vCruzmmL3fvT+cbLLxkixXCa96DKp1iukWM+xR1zLt9vSWLRyO0vWbGJVaCIbogTsySkjQ9tCnqkHjWMAReVJZBXHgtvVHUeROo4jcQ0gcZ5BVHUGkeM8UvcwMs8w6uox1NVjyL1XybNdIKfsDOnWU6SVDJBadJa0kotkll4kt/wyosq/bwZXVFxE4xhE7x5BXXkRgekwAtNhsgz9JKnbiZM3Ey1qIErURLSohYi8RuJkbcRLu0iQdRMj7CBa0EF4dgs70+rZkhhgRbSTdWm1bM1tISr/IDGFx4kqOEaIvJ9d+UeILTqL0DuOsmYKbcMtjO0PsXQ8CsYzp6e05wkVvf+Jpf0phS2PyG+8i6r2JvLAdXKqBsmyXyat4hzx1lPEmY8Sq+tjt6yRUFEtWzPsrI4ysHSnkq825fDNxhy+2Srg651Svt4hY2monG+3SPl2k4Qlm4R8/V067y4K5T/eWsGCT1by1yVr+XDxKv73nxby72+8x5/eW8TbHy/mt299yG/+8gG/fnMRv16wmjc/2sJnq9NYslXG6t16tqe72JLhYl2Kna/DC3hnWRpvLUlh0VYZkcIakgu6STX0EqVqJVzZQpSmnQhNcDpzrP75oMIOEvStxGsbiFIGCJe4CRO5CRU6WZ9qYU2cli83xfH+l2t4a9Ey3lz4Gb9+811+8+f3ePP9j3jzvfd4460FvLHgL/z+zQX85s0PePfLDXwVKmZ5tIktghp2SdrZlNPMkphGwoR1ZGjrKLOV0uyV0letYO8z6JkGmxnQMxt8XrVl/VXXXrao9H8CPPPQM69/huahZ16vRa+CnufA0+jIo8mWS5Mtdxp65prc+q+GnvYZ1n13QMiBmly6PQrsTh9Wz34KAhNklY6SYLxEovECMYZzxBnPEKFoZsn2bP66PJRv1mxlfXgWIUkaoqVu8ky9iEsOoKw4FYSe8uPI7MdQeQbQBM6jqx+ioOkaBY2jaKpHkLuHUHgHUfqGUPmHUXgHkTgvIrJfRB24Sn7dJEr/KHm2IcRVQ0icw8idQyirhlA4Bsl3j1DgHcdUfROD/waFvgkK/eNovSPI7JcQV5wnu/gMGaYBMkwDZJrPkFU0QIbhFCm6Y2QUnCBdd4Ik1WGixf1EifqIUR4kWnmQCMUBYvXHSLQE3aY9uoPs0h0m2nKatIrLiNyjyAPXyW+8i6H5QTAa7wU7uDoeYe36geLOHzC3PaGw6T75dbdRBW4gcA4HhxFWnCep5BTxpkNEazvZJa4jJNfPuoQylu3Rs3S3lu8idIQmlLAtqZjFYSo+2pTDh2szeH9FHB8sj+Gvq2P4dmM0nyzZyJsff8OCT5ey8KuVvPf5Mv79T+/z//xuAb95833e/3Qx7y/6knc++Yzfvf0+v1+4mPe+WsfCZTt4b2kUC1clsCRcy/osBxuyXKxOqWR5mIGvQzR8uknBttQqIuVNZFgOkllyhAzrYbLLjpFuPUxq8QFSzPuCy2KNvSTq24nLbyZSHmCP0MWuvCq2C6pYm2xiRZSSz9ZH88FX3/HWomX84d1P+M2f3+P3b3/Iu58u5q2P/sof33mf3/7lHf741kf8/v1v+XBlNF+HGVmR4GKzsJPtkj425XSxMr6BRHk1UlMAl8tIV0BIb7WEHo/kRbB5CfR0+35axPzCNObn98kcwDP7u/PQM6/XrXnomddr0Vw1PTNTW9NDCl/i9PwroeenJ9Znr14FXX4JfT4BTQ4Fla56in3H0HonSTYPEVN4gWjdWXaqThKmPUGEsoMVu8R8tiacNSFRhGcWEC+tJMfShcYxgLZqAEXFKaSlx5GUHkVceRy5+zRq/zn0jSOYWiextN3E0nYLY/N1DI0TmJqvU9R2E0vrFLraa2iqr6KuHkRbM4I6MIzCM4zYdQm55wq6mlEMdeMU1o6h8Q6hcQ2hcw9jcF9D7xlC5x5E47yIzHYOceVZBGUXyC05h6jsAgrHIDLHBWT2S0gczzrSnNfIK7tEinGAZMNp0k1nyC6+QF7pZfLKLpBbcZFc+yWSS04RbzlGvOUYKSUD5FVdReqdRFt/d3pQoanpIcVtT7F2PKWi62/Ye/9fKrr+RknrY4wNd9FVTyGuGkJgu0y69TRxxsNE5vewU1LPtrwA69OdLI0wszzCxIaEErZn2NiSWMLaKCOLNgt4e3kSC76JY8HX0SxcnsBna1P5breAZdtTWLRqB58s3817X+/gva+2s+DTdfxx4TL+8MES3v9sDZ8sXsvCz1fxh/e/4sOlIawMSWT1jjzeX57IW9/G886abL6NtrA6xca6HC87c/xsT3PyXWwZ6+Ir2JjmIlrVSXrRETKtx0i1HCbJtI9E417i9N3E6rqI03VMFzTHqusIk3gJE7nZmmNjTaKB5ZEKFq2LmnZ6/vDuJ7zx3ics+OhzPvhyCW9+uIj/eOsDfv/el7z35QYWLgtnxW4FG5IdbMmqY7e0j3BZP7tE3YRkNiLQutEV2aj16+irzWVvrYiuOdJYM+N56qvH/9Oloy9LZ81V8/M/TXG97Lvz0DOvX6J56JnXa9Fs6JndvTU9rPD/Iuhp9ynp8Enp8wmotamocDdR5D+J2jtBguEy0QXnCdcOsE1+nJ2aY4QrO1i1R8oXayNZvzOOWIGFVLWbvOJgWkvjGEBaehxR8REE1sOIK48jc51C5TuPpnYQQ9Mk5tYpDE2TqKsHya8dRld3FUPTGIamMfJrh1H6LyP3XkRTMxQEoMBVZO7LyD1X0NeOYayfoLB2jPzAMBr3FXTuQYy+qxj9wxj9w+h9l9F6rqDzDaH1XEPtuorWcw1jzQQ63xAqz2UU7ito/GMovKMIbUNklFwk3XqBDPNZcq0XEZUPIrEPIqq6gsxzlazKcyRbj5JoOUJq6ZkXoKeg8T4FjfcxNT3E2v495V0/YOv5L5z9/x/2nv+irP0p5qb76GtuIqsaRlQZhJ4Ew2GiNN3skNSyNdfPugwn30aYWRZpZl1iCZuSylgepuPb7Uo+W5/Dx6vT+WBFOotW5/D52ly+3ihgQ4SKtWESloYk88X6RN77Jpx3v9rJu19t5S+LNvDnT75jwadrePfT1fzlw2X84YOlfLE2jk0RYrZG6Vj0XR4frszh/dVCvgozsSqxkg15fqKkjUQKawnJ8LAh0caGVDe7RI1EqbuIUnexU9JChLr92YLS9mCaK7+dRH07iQVtJOQ3EikPECkJsDXHxndJRlZEKfl0beQ09Lzx/qe8+cGnvPXxF7z72de88cFf+fWChbz5yXI+XRnG4i3pbEwwEZLlY0deA2HSHiJkvYRJugnPa0Va6MFQWklDdT59tdnsrRP+Q9AzXej8rC39VdDzsvgl0DPfvTWvf7bmoWder0Wz5/TMBp/nYPOPDCX8uXb12VNjX/YwfTn0/D26vDK6fFKqHQWUudsw+84iqhgjXHeOCPUAe1RHCVUcZ6fyCDH5XWxNNrJ6VxbhSULSlJXkFFYjKO5HXn4SeflpBJbgaojs4oOIKo6h8JxF5TuP0neR/JoRDA2TmFtuUNR+naL26xR3BN9b2iYxNo9R2HiN/NohNNVX0FRfQVV9GaXvIir/ZTTVg+iqr6KvGcHYME5R4yRF9eOU1I5Q0nCNkoZrFDdcxVI/QlHDKPrqa8gdl1E4LqD1n0MXuEx+YBC1bxhVYAy5b4y8qqtkVgyTWTZETskFBCXnEJaeR1R5EZlrEIlrkOyKAdLLT5JlGyC78gK5lYNI3eNoa2+jrb1Nft0djI0PsLZ/T3HnD5S0PaWi7XvKmx9T2vgQc90dCgNTKKuGkdiukGUdIMV4jDj9XnYrmtiU42VNqp1VSeWsTalkfZqd7xJL+GqXlsXbVSwPkbF8o5SlG+Us36xj9XYj68Ks7Mr0ESVqIFJYy+4sJyEpxayPKWBZqIRl28WsDBWx+LtkPl8RxVerY1kXImFPfAURyS5CYuysD69kc3QVW5I9bMuuZltuLduFtcRrOknK7yO1sJ8EXQ9JBXtJMuwn0bCfhML9xBXuJ76wj0TjXtKKD5FVeoSc8mNkFO8nxdRDjKaRXUIXobkOtuXaWZ9qYdWzOT3vfr6Ktz9bzruLvuGtj79gwUef8+ePPuM3737Mr9/9KwuXb2djrJJtGSVEiALsFjSwS9DCLlE7MbIeEhR9JMlb0JgqKC0rprlawd76XPbWSugNqH8WeJ63tM9cPDpXF9fLOrtmp77+Ueh5GSS1eebn9Mzrl2keeub1WjRzIvPz4YQz01uz3ZzZ83pmOz2vqs2ZC3jmOn3OdX3277R6pTT7JPid+VR4OyjynSXTOkSo9gQhqhNsyO1lq6iHSM1exNZDJKqr2ZVhZGeKjGihhWS1E2lRD0rrCRQlJ5FXHkdiO4zEdhil8ySFtYOYG0ewdkxibb9OcccUxR03KO64QWn3LaydUxiaRiloGKGgYQR94wjG5jGMjdcorL+KoW4Yff0I+voRtNVXkbsvIa+6iModdH4K6sYx1o5SWH2NwuoRCgJXyfcHQ+O/isY9gto9jMZ/Ca1/CLVvGLX/GnLvCFLXVYSOq2RVDJJVPkxW6SDpxZdINV8kxXI2WEhtPUNq6RnSK86Sbb9Env0KAvswEtcocu8EKt8kmsANChvuYml9hKX1Eeam+5jq72Kuu4Oh+iZ633V03klUVdeQOYbILDkbXDuRv48waROb0t2sS7SxMr6YDRmVbMupYmu2g/VpdtYnV7IhoYRV4WaW7zaxfLeFtdHlbIivYlduE4mavaQW7CfLeJAs034y9HtJVHaSoOggUdlJtLiZnZkBQtN97MyoJiK3mYicFiJym4kUtRAr6yBe3UOUrI0wURPbsqvZI24hStVLhvU4WRWnyCk/hdQVnKmUaz+DsOoCItc58hwD5NpPk115klTr4el0V7S6gTCxi90CO6EiBxvSilgdq2XR2lg+WLyRhYvXs/CL5bzz1694+5Mv+eTzL/jTB4v4j/e+4O2lkSyLKGRTWjm7RbXsFjWzU9hGqLCLcOle4tX7ERS0UVFpwefU0BWQ0x6Q0eyV0+2fu3trJvT0Vavoq1bNuW199lTmmTU+sw8Oc0HMyw4gLS7RSw8o89Azr1+qeeiZ12tREHryaLDn0OjIpakqj2angKaqPJqq8mh1CmhzCV/Ykj4XCLW7xHO6PK+Kl7XS/hz0tHkktHqlNPokeJ1aKnxtFHvPkmm5Qoj2BJsVx/guo5sQSRdxhfvJd54hx9JJtKSS7ekaooRWUrVupJY+lMUnUZacRuU4hcJ5FIXzKCrXKUx1Q1ibRylun8Dafp3SzimsnVPPXJ4pzK2T6OtHplNdumeAY2ocw9Q4hqVxDHPrJObWSQyNE6h9wyjcV1B7BsmvHSW/dhSVdwiV+woq1xAK9xBKz3DwmncIrX8MbWAUje8yas8gSs8gSu9VJM7hYI2NfZjsyiEyy6+QXnKFlKJLJFsukmg6R4L5NImWAdJKz5FZeYGsyktk2y4jdFxF4hpF4Rmfhh5jw12KWh4GgafxHsa6Oxhqb6Pz36DQd50C7yRa9zhK5yg5ZZeIMx4nRneAPZJmtjyDnhVxRWzMKGNrji0IPpkutmQ42ZhqZ1VsCSuirKyJKWF9kp3NaS7CRE0k6feRaT6OoOQk4pJTCItPkGM6RobhCJnGo6QbjxKn2ku0vJdoeQfRsi6ipJ1EydqJVnYRq+4hXt1DjKKTCEkLIdm1bM9rIkzWSbLxCEnmw2RYjyNynCOvcoDM8pPk2AbIqjhBeunRIOwUHyTa0Ee4potwdSvh8hr2iKrYlWcjVORgY5qVNbF6Pl+XwAeLN/Hh4o189OVq3v10MW9/+hWff/klf1n4Ob97/2veXhbH4j0G1sSXEprrJ1TQTKigla15neyS7SVWvR+xqYMqh4l6t5KegJwWr5JGj4ouvyQIPv6ge/l8b1aXT0q3X0ZPQE5fjZK+GuVPoGeuVRQz75u5ZvXMvtdmHkp+Dnpmxjz0zOuXaB565vVaFExvCWh05NLoyKXZKaDFJZwGnzaXMBhzOD0/cYBe4vL8I9Az+4E850P6+WRmz7NTa0BGtVeL3dtGiesMaforrBMdYa3oIGvT9xJrOIbQdQlb+13yPafJKe4iKd9Lan6AnMJ6REV7EZtPIbacRmY7gcx5HKnjOArnAPrqyxjqhjA3jmBqGqW4bRJrZ7Bw2dA0RmHjKMbmcUwtExQ2jqKvH0FTPUhh3QjmpnFK225gbbtBacdNSjrvYGm5ianpBoX1E+jrJtFWjyFzXkFSdRmJ4woS+2Vkziso3FdQ+YdRe0ZReUZQeC6jdF8NpqwcVxA5BhHZhxHahhDYr5JnGyajdJA062XSS4IAlFl+hazKK2TbLpPtuEKuY5Bs2yBCxwgSxzWU3gm0/uvoa25iaX6AteUR1pag06Ovu01hXRB6DM/AJ98zgdI9Rm75ZVKs50gxHCda1sXWdB/rk4KuzuasCrZkV7I+pZx1yWVsSLGxMd3JhrQqNqVVsTXTzc68GiKkTSTl9yEsPYncfh69dxCN6zxKxxnEpSeRVp5BZjtLjvUEqYaDwTAeILlgP4m6vcRpeolRdROj6iZa2UWkvIMwSSu7Rc2EyTqJUPYQpe4jVttHfME+Ui1HiNf3E6nqJELZQaS6nQh1O7uV7YTKW9kmaSJE2swOWRNh8jr2SNzsEVWxVWBnS2YZ65NMfLkplY++CeGjb7fy6dINLPxyGe8sWswnn3/GWx8v5o2Pl/PuymQ+Dc3n6zAj65Iq2ZpZTUhuMyHiXnZK+4mS70NoaJuGnk6/nHaPllavhp7qnwLPbOjprVbQW634CezMBp6fg57Zrs3s78wFPS+r85mHnnn9Es1Dz7xei14GPS0u4bTr0+r+aVrrZXN6/lHoeZXt/vxB+5MR+jOgp9MT/A+iwafB5m7CZDtGovI8q9IOsDxlP2tS+0gvO4+qdhRr1yPMTeMU1F5C5z+JuKyf7KJOMgv7yCw8TrrhOBLbCeSO4yieLRc11g9jar6GuSUIPCUdN6jsuUt5121Ku+5S3nOfqv1Pcex7Qln3PcwtNzA0TpBfM4ImMIzaP4RQYCipAAAgAElEQVTWP4QmMIyuZnQ6paWrnSC/Zhx93ST62utoq8dQ+6+h9F5F5RtB5RtB6RlG6b2K3DWMtGoQuWsYmXMIhfsqUlfQ7ZFUjSB0BNNcORWDZFdcJadyhDzHCELXNQTOEQTOYYSOqwjsw8EWensQelTuCbS+G+irb1HU9BBry2OsLY8x1t0l33sTrWcKnWcKvesGetcN1FUTyGyjZBZfIsl4liT9CaJkPWzJ9LM+xcWGdAebs6rYlOlkTWIFqxPKWZNYwcaMIOyEZPnYJaglUtZMtLydpPw+si1HkFaeReU6j8Z1DrXrDDrvRfTVV9AHBpE6zpBTcpRs6xGyig+TZjxEuvEoqaajpBT+HYJi1T1EyjuIkLWToN1HUv5BkvIPkmE6Rl7pKaT282QVHyXFsJ9EfT+JhftIMh4g2XKEpKKjJBQfJbnoMInm/cQVdjxbPOpia56DrXkONqQWs2R7Nl+uieDzVbv467cb+OSbVfz1m5V8tOgz3v90GQs+XccH63L4epeBZRFFrI0rZ2Oym43JAbZktbFT3EO4rBdhQTPuKjONXvUzqNHS7c+nu1o8J/TMBp+egPyV0DN74/qr5vfMvE9n1v7MhJy5GhPmC5nn9c/SPPTM67VoJvQ8h5zXBT2vcnue1/FM/447+J9CnUeFraoBc+VhEpXnWJGyjyWJ/axK7iG97DzKmjFMrXcpapmkqHmUosZLyO2HyLP2kqrvIcN4ggzjiWnoUTpPovVdwNg0gqV1jKKOSYo7bmDtnKK89y5lPXco77lPRe8DbP2PqOh9QFHbTYxNk+hqr6Gtvoq2+iqawHCwUyswHKzReR6BUTSBUfJrxtHVTKLxj6H2jaL0jEyHwjOMwn0VmXMIieMKMucQcu8ISl+wc0vuuYbMNYroGfjk2YbJs48icIwhdo4icY0idl6b/nwm9MirRlG6xtF4r6OvvoWl8QHFzY8oanpIYc1ttJ4ptJ4p9N6bFLinfgI9yYYzJOQfI1LazdbMajameaahZ3OWi7XJtp9Az7ZML7sEtYRLGomUthKn6iKtcD/ZlqNIKk+hrDqNsuo0Ws85CmuHKKwdQuW5iNh2GrHtNHllJ0k3HSbdeJQ08xHSTYdJNRychp4oRSd7xC3EqftJ0OwnWXeI7KKTCMsHkFddRFg+QFbxUdLNh8i0HiOr9ARZ5afJrBggvXKAjLITpFoPk2DsIkoZIELqZpugim2CKjamWVm+M49v1sfyxaowPvlmPZ8uWcOiZWv4+MsveX/RCt75fBMfbsjjm11mlkaWBFvmE6pYl+BlQ1oTocIu9ki6ydM14rGbfgI9XQERXT7pPxV6fm5o4cz7dPZ35qFnXv8nNA8983otehn0NDsFLwDQTOh51UTm/25662UdJq86qbZ5JHS4xHR6xDR6VNicPkyVfaRqzrIiqZ+v47pZEtNOkuUsEs9V8mtvUNAwgallAmvrOFLbUTJMPcRpu8gsPk1OyRlkjtNI7SeRV51GX3056O503aSs5zal3bco7b5NZd9DHPueYOt/RHnPfSytU5iarwe7up7N7LF2BJ2gsu57WNvvUNR6C0PDJNqaa0HgqRlHUzOOunocVWAMlffadDwHoOcQJHEOI7IPI3ZeQ+YZR+m/jso3idI7gdxzLej4OIeRecaReyemQ+oeQzINRSMI7FcR2a4ic1z7O/R4JtH5pzDV38PS+ABz7X30/tvTLo/Be3s69K4p1I5JcoqvkFQ4QJzmCOHiLrbn1LEtq4ZNGS42Z7nYmuNhc6abdckO1ibZWZ/qYHO6k22ZXnbm1bBbWMduQQN7hI1Ey9tJ0PSQYz2EwnEq6PT4LqB0nUXhPIPMeQaJfQCx7TTCitOIKs6QV36WNPMRYrV9xGh6iVB0EqnsIlrdE6wRMp0gp+g0wtJzSCovIHdcDtZLOS8hqjhDuukwyYaDJBkPkmg6RLzpEDHGw8Qb9xNn6Cda10qY1MMekZMQoZMdEg8hOZWsj1KxZHMiX6wOZ+Hi9Xy1chNL14ew6JuVLPxiHR8vj2BRiIJvw6wsiypleUQJK6PKWRFpZ1Wsny3ZreyWdCLUNeJ1mGn2a+n2Senxaun1a+jyCV8JPc/Bp9sve2Vaa2Z662Wdj7O7t+a6D59/9irgmYeeef1SzUPPvF6LfvWrf5t2dZqq8qYhZzb0zF4yOrt1/Z8BPbPH5c/8vNMf7GyZ3iztDk6ybfMqsDkrMdubEFhPsylvH8vT+vgqopEw9SGyKs6jq7+Boek6xqZJTPXXkNtPklO0n3hdF1klx8kpO4nUfhJx5XEkVafQ1QxiaZvE2jlFafdtSrpuUdweDGt7sD7H2Hgdfe0YhoZJrO13KO28R3n3A6ztdyhuu01Jx13Kuu5T2nkPS+sdjE03MTROYWy5jbHlDqbWu5ha72Jovk1h0y30DVPo6m+QX3cddfU4St8YUvcYgqpriNyTSNzXkXonkXsnkHnGUXhHUXvH0PjG0dVNkV97A031JErfGHL3GDLnGBLHNYT2UUS2a4jto8gd48gd4ygc46ick2g9U5hq7mGpe4AhcAetZwqlYxK1Y5L8qusYXDcxum9R4L6Jpuo6ecWDJBWcIU59jHBxF9tyGtiSVcOmLC9bcnxsywuwXVhLSE4NWzK9bM50E5LtJTQnwG5hHXtE9ewWNLBb0EC0vJ14dTcpBX3kFh1EVHoUhX0AccVJBKXHEJSfIrf0BNnWY2RYDpNRdIx0y1GSDQdJKNxPouEAqZYj5FYMIK66gMIzjNwVdMjkrmHE9suI7ZeRuQaRuQYR2S+SXnSCJGMQepJMR0m0HCPedIR4wwHiDPuC0CPxskfkZKvQSZiilt1SL1sTC1iyKZnPVkfw16Vb+HbdDlZtDePzFRv5ak0Ey3cIWRJdzJLICr4JL2HxDiPf7i5iaVgFK2N8bM1pI1rVj9zcGoQen4pun4Qen/on0POqmAk9s0FnZrv6q0Y9zFVHN1fdzz/Szj4PPfP6JZqHnnm9Fr0Kep6/nwk9L5vX88+Cntk1CTO3R8+Gnn6vlE6/HLurBIujFrntFDtVh/ku9wBfRzWxS7mP9LIBChqnMDZex9J8HUv9NZSOAfKsB0nSd5NefIjMkiOIK48jqDyG2HESbc0g5tYJLB3XsXYGC5GtHbcpbrs97d6Ym6cwN09R1HqL0s57VPQ8nIYea/sdyrruU979gNLu+xS336Oo7S6W1jtY2u9jab9PUUdw9YO57R6m1rsvgI+mZgJV9SQK3yRi1yQSzxRiz3WknhvIPOPIPOOo/OPoa69TWD+Fqek2+oYp8uuuT0OP3DWOzDmBxD6O2DaGxDGG0jmJomoChWMcZdUEGvcNjNV3sdQ9wFh9F51nCpV9AqVtHLVtHL3jBsaqmxRUTaG1Xye3aJBk/QCxqqPsEfWwLaeBzZm1bM4KPAOeGnZKGtglaiQ0L7iiYkdegF2CWvaI6gkTB12ePcJGYhQdJGp7SdL1kGXah8B6BIV9AEnFAOLy0wjLBxCUnSa35CTplmdpLctR0ouPkmE9TmbJCXIrBhDazyGuuoDYeYU820VyKy6SV3mJnIrzZJWdJafiPLmV58kuP0u69RSpliOkWo6QVnySdOspkotPkFJ0lCTLIWL1nYRLfYSJXWwTeditrCVcESA01cTSrWl8uTaaRStCWbphF2tCIli6YRff7chgS7yOtalVLI+pYmlUJYt3mPhml4WlYRWsivUTmtdBfP4B1NZOfE4zTV7lC9DTHRC+0L31grMzB/TM5e68DGz+u9AzV4v6fPfWvP4Vmoeeeb0WzYaeVreIVrfoBfBpdYteCj3PwafFIXjlnJ7Zp8fnBZQzaxFmF2LOBp/n0NPmkdDtlrDPI6PXr6C8woS5yoeu9gxRlnPsVJ3km4R2tkn3kVIygLHxOtbWW5S33qS0cRSt8ywC62GS9e1kWPrIKt5LjvUguWVHkThOU1h/FWPzOMbmcaydNynruU9l/yNKu+9T3nmPsq77VPY+wt7/BFvfY8q7H1DW84CSrnvY+h7j2PsUe/+T6WuW1jsUddynuPMB1p4nFHc/prj7MSVdT7C0PcDUco+ChlsU1N+hsOEuuvrr6Bpuoam5icR7A1ngLrLAHVS1d1FX30RdPYW+/ibFbfcp7XxEScdDCptuBje++4Pt6GrfDVTeKWTOCaRVQYdH6ZxEWTWBzHENRdUoGvcNTDX3sNY9xFr3EIP/LoXeuxQ476Atv0FBxQ0KKqfQ2aZQV1wnzzREguYUsapjhEv62JLRwOb0ekLy6ggV1bFDXM8eeTORsi4iZO2ESxsIF9URLqojTNzAbmEduwS1hIkbiFG2kajtJTV/L2m6fWQZDqGsOIvUdhFJ5QUkFReR2weR2a4gqDhHTuUZsisGyC47RW7FADnlp8kuO0VmyQkyrMdJKTpKouUU0caThOkPEWs8Sqz5GAnFJ4k1HyXWfJRo42HijIdJNB4l2XyctOLgmo5EyxGSLIdIMvQQp6olWh4gVOpll8xHhMzPznQL63flsmJrMovX7eGb9TtZERLF1j1xRGWYSFVVs1vWyPrMBtal+FgeUcqKsDKW7SlnVYyXMEk3WZazmByHqHYaafMq6K+W0O1R0udX0xvIm4acmfU7M69NFzq/Ip3131k4OtsZ+rlRErM/n4eeef1SzUPPvF6LZkPPbIfnVemtuSYy/6PDCX9adyCl0y+jKyCn0//3lRMzizS7fcGHdKtPQqdPTLdPQqdfgNuto9JThqWmB5k3OJ9ml+QAMeqDZJWcxth8I9h11X6d4oaraJwD5BYfIFnbTqZxL7lFB8mxHiKv/Bhi+6lg63njKKaWCYrab1He+4DyvY+wdt6lpOMulf2Pcez/nsr+x5T3PqSs5wHlvQ+x73uK68CPVO37HlvfY8q6H1HS+YDi9nuUdD+irPcJJb1PKep6hLX7KcVdTzC03KOg6Q66hltoa4Ohqb2BpuYmqtqbqKrvoKm9N70vy9T8AHPrfUraH1HW9ZiyziA4FTbcRVd7C5X3Ogr3dZSeG2g8U6hc11E9gx2NcxKNcxKVYxy1YxKd8wYm/12s1Q8oqXmIOXAPnesWha67FFTdRee4hb7qdhCCHLcQmIdJzh8gQXmMCHEv2zIa2Jpez/bsBkIFjYQKGtklbiFC3kOEopsoZRuRilYi5G2ES9sIk7SyR9zCLmFTsMVc0kqUopM4TS/J+fvJsZwgr/QUgrLTiMrPIS6/gLD0HKLyc+SVnw1CTvHxabcmw3qc7LJT5JSfRmAL1m8JXEMkWE6QYD5McvEJsirPkOs4T2bFANEF+4gt2BdMZxUcJLZgH1H6vcTk9xGt7SFG0060splIeSMRilp2igPsEdeyM8fOumgFS0Oz+XpDBF+uCWFNSBSR6flkqmoRGHrIMO0nUtHLLnEbaxPcrIiysSzKzvJ4P3sU+xEUD1Dq6KHabqTZrQ4WJfukwSnLM5yduUBnZsy8J2YeFGZenw08czlCM3+eC25+zgGah555/VLNQ8+8Xot+9at/o80lpKUqbzqeDyRscwlpdQqCMQt6/pHdWy+bBTLXw3Q29ATjxW6V4JbpIPS0+sV0BqR0V4up9evwei2UeOoorD6FyHWBZP0JknTHyC45TWHjJBXddyhtv05R/SBK50lyrftIUreTWdBPbtEhcooPIyg/gdh2GpX/8jT0WDvvUNx9l6LOu1jablHe/QD7vqc49n//AvDY9j7BdehvOPf/gL3/STDd1fOY8p7HVPQ+oaz3KWW9T7F2PcLU9gBLR/BV33gbXcMt8utuo6kJujjywHUUgSmU1TfR1d9F33CPgsb7GFseUtzxiNKOx1T0PKWs8wmlHY8xNT0kv/Ye6sBtlO6gu6N0TqJyXUftuo7GOYm6agKt43kEa3YKqm5g8tyhyH8fa/UDzP77aOw30TnvUOi6i855B53zDgXue+icdxCYh0nRnCZBeYxIUQ8hafVsS61jW0Y9oTmNhOY0skPYwh5pF2HyLqJU3cRoeonR9BKp7CJS2UWEopNd4hZ2CJvYIWxij7SNSGUPsdq9pBmOkFl8nOySk+SWnSGndIAs6ymyi06SXXKaLOspcqwnyC4dIKfsDELbBWSuQeTuIZS+IdTVYyiqRxE4L5NVfpq00pPkOs4j9Q8i8lwipeQYKcVHSCk6SrLlSLBt3XKI2PxeojVBSAuXNRMmayRKUctuUQ1hknp25nlYHavh2505fLM5mq9WhbAuJIb4vAqytW3kFPSRW3SIFN0B9kg7WJ/kZUWsk+Vxblam1LJTvo+comOUVjThqyigzq6mKyCnwy+hu1pBt1f1DwHPc+iZfRiY6ZR2BRQvNAXMvofmSou9ytGZh555/as0Dz3zei361a/+jVangGZH7nTMBJ9Wp2D657lienih6++7t+ZyfF6EHclPIujsSGcAj2wagp7H82ttfintARmdNcEljO1+Hc2eQhz2KspqT6LxnSWv7BLJ5jNklpylsH6Csp47lHTcwNgwA3pUHWTq9pFrPExu8THyKk8icgyg8g2iqxvF0DRJUfttLB13MLffxtp5l8reR9j2PqGy/zFlPcG0lm3vE2x7n2Df93Q65WXvf0Jl39Ng9H5PeV8wSrufYu18TFHnYywdjyhsuk9h030MzQ8wND+goPH+NOQUNj3A0Pxw+rWo7TElnd9T2vUDFd3fU9b5hJL2JxTW30MTuIvcdwu58zoSxxgy+1iwYPlZqG1jqCuuoakcJd82QUHVDQyum5i9dykOPMBa/RBL4AFaxy20jlvoHLfQOG+T776L3nUXjf0m2YWXSVWfIlFxlAhhN6EZjYSm1bMjs4mduS3syGkmNDfYqbRH1km0pp943X7idfuJ1e4lQX+AeN1+IpU97Ja0B4cJKrqJVvUTl3+AVNNx8irOIXZcQvpscKPIfhGJ/TJyRzBk9ktIq4KDHOXuIRS+EZT+YGecqOoyMs8w+oYbyH1DiFwXyKo4RZ7jLELneUSuc2SUnZgGnrSio6SaD5FqPkSSYT/R2k72SBrZJapnj9hHmKiGSEkDO3N9fJegYUlYHit3xrNiUzghe9KIETjJzO8hU7eXHMtBkjV97BK3sDrBw/I4N8sTvKxJr2OXYj955oNUlNdQXamnqUpLV0BBi08U/Bv3KKfXUMyM2Xu4ng/l/Mlh4NmE5uevs2vkXtXm/iromXnfzkPPvP7Zmoeeeb0WPYeeJnsOTfacn4DPz8XPQc/cD08xbR7xC6Dz/H2HT/oCCM2En86AlM5A8DtdfhU91Rr21qnpDajp8GlxOisorjmCqf4K2bZhIoxnibOcQR8YC0JP100KG4aR2U6QbQk6PRn5e8kpPEheyVHyKk4jsp9F5QuuitDXj1PYfANj601Mbbco7X1IZe+j6cJlx96nVO37Hsfep9Pg49j7dDps/d9j3/sDtr4fKO15QsmzOh5r52PM7Q8xtj9+IQytjylseYSx8QGWlseYWh9janmKoeUpxpZHWNqfYu36EWvXj5R2/khJ+xOKWx+RX3cHhf8WMu8USs8kCucY8mewo7SP/QR69FWTmLy3MHvvYPbewei7g9X7EMMzR0djv4my4jr59pvTqS152QRp+gskKk8QKztMuKCLHZlNbE9vYEdmE7tzW9iZ20Jobis7hC3sEgcdnHjdfhL0B0jQHyDFeIRU01ESCw4Sq91LnLqfKGUfMeq9xOsOkm45ibDyItKqQVTea6h9o9Pt/PneUfJ911D7RlB5noX3Gkr/KEr/KHL/KOrqcbS1E+gbbqCpGUfqGyKt9CRJxUdIKj5CZuVpcirPkFk6QIrlOMnGI6QZD5Fo2E+iIbikNErVSri8iUh5gChpNbHSBiIFXtYlyFgWls7KHTGsC41jV1Qu8WIXGdou0rTBLrRYZRchufWsiHWyMt7PysRq1mc2EK7YR67pAKWlAWoq82muCsJJq1s8vTz3+Rb1Hr/ipdDT5Z0beGbGTOiZ7erM5fa8DHrmOqzMQ8+8/pmah555vRb96lf/RktV3jT0PAefmdDzMgCaCTwzoefnXJ7n0DMTbGYCz0wAmgk+7f7gksbOgDT4APep6Qso2Vetos+vps5dhqN+H5aGi+TYhtmZP0BYwXE01SNYO25T1nkLY/0wUttRcor3kqjpID2/h2zDPoSlJ38CPbq6MfR1kxiab2Fpv0d59yNs3Y8p63pIefcj7P3fU7XvRxx7f8De//10OPb+QNX+v2Hf+wP2/h+p6P5+GnaK259gaX+Cue3xC2FpD4KNoekxhY3PXpufYGh5SkHLE0wtT7G0/UBJ139R0vVflHb+iLX1CebmIPSoq2+iCkyh8E4Fa3qe1fGoq8aCYb+G1jZGvn2cQtcNTJ7bmL13sPjuYfLcweS5g8FzB33VbdS2KeRlEygrrqO2TaGqvIG0ZIz0/PPEyY4SJT5AuKAr6PRkNLIjs4nQ7L/HDkErO4VthMk6iVb1E6vZR4LuIGmm46SbT5BiOEqC7iDx+QeIVPYRrdpHfP4h0k0nEVVcQuYYQuMdI98/MR1a3zga7xga7xgqzyhK9zUUrpHgoEb3CGL3MNpnLf/a2glU1SPIvMFN88/TWUmWQ+RUniHXdpb04mOkWg4Tq+sjTt9PnL6fWF03sZpOYtQdxCnriZVUkyitI1rkYmO8jG9Ck1gaEsa6nUmERgtIkgXIKOglvWAf6fr97Ja2sCWrjhWxTlbEe1iVEGB9RjNRyr3kmvsoLXdR79DS5lLS+cLfuWx6i/pM6JnT9ZkFO7PB5zn0vGyGz1z1PS9rU593eub1r9Q89MzrtWgm9DTasmm0Zb/g9sys8/lnQ89M+JkLgGaDT7s/mOLqDgS7WNp9Svp8cvYHFOwNKGn0FuGs76ak6Rw5VYNs1Z5gR/4xtJ5rWFpuUtI+haFuCHHFYbIsfSTld5Ch7yHHuB9R2SkElQOI7GdRegbRVI+grblGfs14sOW95TZlXQ+p7HpERc9jKnuf4Nj7wzTwOPufgU/fD9Nh6/uByt5gGqqo7TGW1kcUtQaBx9T66BnsPIegJ9PAU1D/CEPjEwqbn1LY/JSCZ6+m5u8pav+R4o6/YWn7AXPzk2A9T8M9tLW30dbeQhWYQuW9jtozido9gcY5jsY5jrZqDJ1jAn3VJAb3FCbP7WdxB4PrFoXOm+iqptDaplBWXEdeNoG0ZAxpyRji4msILVdJ054jVnqECOE+wvI6Cc1oJCStnu3pDYRkBmN7ViPb85rYntvMDkEr4dIeohT9xGn3k2Y6TmbRKdLNJ0guPEJywVHi8w8Rpz9McuEJsixnEVUOIqsaQe2dID9wg/zADbQzoEf9LFSeUaSuq4irhhA5BhE4BhE6B5G6h5F5giF1DyGwXwzW91iPE63rJ6XoKBmlJ0krOkqy6SAJhfueAU8fMfldxGo6g6GoI0roI1YYIFrgYG2MkK+2xPLVpt1sDMsgPFlDuqaZDPM+0g0HSMrvZ7ugno1pNSyLdrAsxsPKeD+bMlqIVvWTZ+iitMxGk1NNp1tB98y/a6/kBadntuMzG3pmuzs9NS9uX/85yHnZXKx56JnX/0nNQ8+8XoteJ/Q8b49vdYumoWdm99Zs1+e54/N8HH+7X06PX8qBGgUHa5U0+8w4As2UN51GGrhGWNEFIs1nUdlGKKgbx9J8nYKaK4jKD5Fp7iUxv5V0fQc55r2Iyk4hsp1D4riA0jOIyjeC+lmtiL7hBobmW1T0PMbR+xR791MqOh5R2fkYe/dTXP1/w7X3R2xdTyjteEh55xMqup4XGj+luPUR5uZHmJoeYml5GkxbtT7G3PaEoo7vsbQ/xdz6PeaWHzC3/ICl9UcsrT9iavsRQ/MP6BufUtD4lIKmJ5iag98zNX+P6Rkkaevvoqm5Gez4CgRTXCr3BErn2LTTo3GMkm8fR+eYoMD598GDRvdtjO4g/OidN1FXXEdRPomsdByh5Sp5piFyDFfIMVwhTXuOKNFB9uT2sTunne3pDWxLrWNrSi1b0oKxLaN+GnpCc9rZI+ohQtpPjGofKYXHyDCfIsN8ijTjCVILT5JqPEWKcYB0yzmE5YOI7SNIq0ZRuCdQ+26g8U+hC9xE/yx0gZtoAzfR+IP/TrFzFKFjhDzbEOklZ8mtuIjENYTQcRmB/SJCxyXErkvk2c+RaDpEXOF+4gr3k2I+TFrRkRfAJ0IVLGQOlzUTJa8jXOAjIs9LZI6d9dFCvtwcw+cbwtgcpyAqp5SMwh7Si4M1QTGqbjZn17A22c+yqCpWxfn4LrGa7TkdJKl7ERhaKC8rpsOjpMcvo8cf7Njq9Mto94np9slfCT3T8DMH9MzevP6q+T3/KPDMtYF9Hnrm9c/UPPTM67Xo/3bomRlzQk9AzL5aGQfr5DR6jFR46impP4G2bozkymGSSy4jLR9CGxjBUD+GLnAJYfkBMi09xGuaSdO3kWPuezn0+MfQN0xR2HSLiu4nOHq+x9b1hLK2B5S3P8TW9QRX/99w9v9ARccjSlruU9bxmPKO7ylpf4K17TFFzY8wNT3G3PwES8szwGl7gqX96QvQY2n9kaK2v1Hc/p8Ut/8n5rb/xNjyIwVNP1LQ+BR9w5Npx8fU/D3GpqdzQo/CPYHSNY6iahSVIxgz01v6qkkKnVMYXDenU1tm710KXLfQVN6YdnkE5mFyDFfI1F8kQ3eBFPUZIgT72Z3Ty67stqDDk1b/AvSEZDYQKmgmNK+FHbkdhIn7gtCjPECy/jjpxtOkG0+TZjhFmuE06aYzZBZfIKf0MtKqcRTuv7fcq3030fhvoQvcpKD6VjBqbpNffQtt4CYK33UkrjFEVdcQOq6SXX4Zge0yQsdlcirOk1NxDoH9IqKqy+TZz5FmPU684QCxBf8/e+8VHPed5feOylt+cI3LL3bZZd+7YXZtX2/Zd313Z2c0kkaBCTmQyKFzzt1odEBGA0HEzf4AACAASURBVA10jsi5EZkpBjGBBBGJQCRGiRIlSprZ9X1w7a1aV9kPrrI/96EBCIRAilp5LFcZ36pTRPe/m3j6/fH5n/M955ymtOY85XUXdqAn3zZBjnmQLF0vWbpecg09ZKrayFLGyVH4eCdPw789Usy/O5LPkVI7uUo/QucE5fXnKK05x3HjMO8K23izKMxfHPfzVnEb75Z1k64ao9w6jsrZQ0tzDcNREyfjeiZiOsZiSUgZimq+M9PzXdDzqqGF37WW4gB6DvRj6AB6DvSj6Mf09OwHPfsZmnciqmEkqmMsbiDRtuXvaVdzslPH6Q49nX4n9Z4YNW0f4uxYRhu4l1zG6ZpC55/GEpnBFLyB3HUKQfUw+ZZuym0DSGvGUTdfRdV6E433FobgLMatTefW+Ar27g3s3Ru4hpKgU9/zgPqeBzQNPKEl8RTv6DNaR57iHvqEpoGPaU18jmvgMxr6k8BT1/MN8DQMPKd+KBkNw1/QkPiS+qHn1PZ/sQU8X9OY+JrGxG+oT/yGmv6vqer7+hvo6f2cqr4vdrJCzr5n2HueYu9+hL07CT/m6Cqm0DJG/+IO9FT4lrB6lrF6lveFnurQA+yBzR3o0TQsoqydR+K4Q6n5OiWma+RpLpIlP0W6dIw0yQDHhN07Ja7Dwk4OCztJkfZyTNFNiqKfNMXIFvScIld/mgLLBYqsFymuvERx5SVK7VcQ1dxC0jSL0rOIJbqJOXYfU3QTQ3gdY2QDU3QTS3QTW+wB9vhD7B2PsbY/oqLtIcbIBir/CnLPIrKWGfThFbT+u0iaJpE039yayDyJpPnGTpTVX6S45jzFVWf3lLbGOV6R2JktlGXsJ12THKaYowjzXpGJv8iQ8HahjlxdiAJjN2VVZyipO09h9Zlk11ZxKGlizg9xSNxHqnyYAvNFRLZx1M4OWt1VjMb0nG7T7EDPWMxIIq7eF3r2A5/9PD27Z/XsHfj5OhOaX7V24gB6DvS70gH0HOhH0e6W9d3Asw06L8v07AWel0HP3htn8r0k6Oz29Oz29uyO/Xw/I/Ek8PTHdCTaFIx2ajnZZaDdZ8Xl9tEQnKCmfQaVbwF56xyKxhvIG66jbrmBznsVWd04AscQ+aZ2Sip7EFePoGj+CK1nEo33FvrADMbQHObwXSrjq1R2rmHruEd19yZ1HZvUtK9R17mBe+AJLYMf0zL4Me7Bx3gTH+NNfEbL0DMa+z+nofcz6ns+pb73M+r7v6Bh4DmNA1/hGvqKpuGvkp1Yw18loWcr01M7+BV1Q19TM/AlNQNfUjf0NdX9z3H2fo6jJ+ntqer/nNqhL6kf/JLaoedUD36Gs/cJ9q0BhZXxdSrC97AElrAHlrEHlrH5k1meSu/KVnnr/k44A5tU+deTmZ6tzq1t6JFVzVBsvEqe5iI5yjNkycZJFw+TKu4nXdxLuqSHFHE3RyXJIYXbXp5U5QCp8gQZqjEy1eNkqEbJ1Z/mhPEsJ4xnyTefp9ByibLqm0iaZlF5lzBHH1DR9nAHaHTBVfQ7gxY3sUbuUxHbwBp/gCW6iTa4jKL1LtKmeQT1U0jdMyhaZpC3JNdRSN2TiJtuIGy8irDxKuLGqwjqL1JSe4HCqrMUOc9QUHmS/Mpx8vdAT7quhxR1JxnqDjLkQQ6V2Xi3xEq60k2po5/yqnEENWcorTlNof0kxxTd/LIoyM+P+3m7JE6qcpgc3UlKKy8isY6gtcfxttgZa9Nzpl3Lyfiuzemx/T09+3p7XtJ+vt86l73dWbvhZ/dKl+8CngPoOdDvQgfQc6AfRbuHE26Xtb5Pm/qL0KP6Zm3Fd8ReM/N+7+01O79gao4n5/Uk2hSMdGiY6NTREzDhb3XRGujFEbtGWes0guYpFI1XENQmF1bKXBcRV41TZh2g2NRBsb2HspohFM2XUbfcQNlyA63vDqbwPJbtzedtK8m26dg9nNE1qmKr1HVs0tT3KAk+Q09oSTyidfAx7v6PaR74lMa+ZzT0fkZD3xYADX5B4+CXSeBJfE3TcBJ8XIkvcSWSJa3GxG9oGPqa6oGvqer7gur+58n3h55T1/c5tb3PqN7q6Kodek7DyNc0jHxNTeJzbD1PsHU9orLtPrbYOrbIKvbgIk7/XaoCizh8i1hbFrF5lnF4V6nybeDw3cfuTe7WqvKv4ww9oCLwAKNnHVXjIrLaOaTO6WSbuvYcWbIxsmXDZEoGk7N5pMk4KunisLSLI7JuUlWDpKkSyVCOkq6cSIZqjFz9OU4YL5Bn+pACyyWKKz9CUHsLecsCGv8K5ugDbJ1PsHd9jLX9UbITLbKBObyJNXSfyvB97PENKmMbVERX0QUWUbjnkTbOUl47hahxGlnTNIqWGWTNdxA13kBUn4QdsevKVsdWckbPdranoPJkcjChZYTjpkFOmIc4YR4iS99DpqaTLHU7qVIPH5RWc7i8luOGCEW2QYodY0jqz1LuPEmBdYyj8h7eLo3xVlGUD0Td5BjGyDedpMh8CqGxH609TMBvZ6xdy+l2FePx7TLt1rqJfUpZ+5e3vh17PXDbZeDt9/ZrGhh+Scb1ZU0Gez93sHD0QD9UB9BzoB9F+0HP9/HxDAZVDIXUDIXU33o9FFKTCGteeu1VkXgJ9GzfsBNRXXJIYZuG4TYNY21qRiIauv1WYt4WbP4zFLvnKWqaRVr/EcXVH1JQfQFhwyXEjnGElkHKLB0UOHsprB5E5rqIyn0dhfv6DvRsz4IxRO6iDy9gDq9gC29gj6xT2/kQV+9Dmvsf4xn+hNbhx7j77ydBqP8pTQNf0DT4DHfiC1pGvqR5KzxjXydj9Ld4hn9LS+IrWkd+g2/8P9A6+h9wDf+W2qHfUjv4FfWDX9Kc+CLpDxp8lpzd0/+M6oHPqR3+kprEcxyDn2PtfYql/TGm+MOtrMgqttAKVcG71PjnqAsuUOVbwNp8F1vLMvaWdRytmzhaN7G1buL0P6AmuElV+CHW4EOM3g0UDXcR2u9QZrlBkfY8eapT5MgGyJH1ky3tI12anMuTpujjqLyLQ7IOjii6SNEMkq4dJ00zRqpqglTVBMcUY6Qox8nWn+e46SJ5lsvkWz6i2HENYfUkCvc8Wt8yFbH72Dse4+h8gq39EZat0pY99hh76AH20AOc8Q1s8VUqY/cwhRbRtNxF2TSPsH4GYf0M0sZZ5M1ziOpvIay9TlnVZcQNHyFpvEJ57XlKa85TVnuBstoLlFSfo6jyJNnGIbL1A2Rouskx9JNrHOCEoYfj2nay1VGOCJs4VNZMisRHvrmHgsphCh3jKOvPIXBMUGgZJUOTIF09TIZmhGzDGAUV4xRYEpzQdiMxRDA7WomHKxhr13CyXcVYmz45jbnNxFhs/4nM++3jeulOrq1zMRzRbk1u1r0APXuB5lXnbu/rvWd4+xwfQM+BfogOoOdAP4r2lrf2Dij8PuWtV4HNqz7/Uoh6SdZneDf4RPX0R/UkYlrG4hr6wkZ8vips7i4UnimkLQtIXLcpapikoPEm5e4biKtGEVh6KTK1Uerso6x6GFHthyibr6FqvZn09ITmMIUWMIXvYowmh+BVRFewRtawxdZxtt+nvuchTX2PdkpcrVslLk/iKZ7hL/CPPMc3+iWBiS/xbcfJr/BP/CYZo18TGPsNgbHf4B//a3zjf03L6F/hGv4NruHf0Jj4moahr7bKWF9SNfAF1p7PsHQ9xdj5Cdq2h6iimygjG6iDa6gDq6h8d9F6FtB7F6jwL+AM3qU6uERVYBmHZwWn9x7O1g3szevY3OvU+JN+ntrQfZyhB9iDj7D67qNzLSO13aHcdINi3YcUas+SpxwlVz5IpmSQDPEgGfJ+MhUDpMi7OCrvIkXZR7omQYZuIgk+6nHSNROkaybI0J4m13SBE+ZLnDBfIr/iCiWOG4hrb6NtXcQcXMPe8Zjqzo+p7vwYZ/tjHG2PcLY/prr9Yxzhh9iC96kIrSczWbF1bG3J3WI6zzKihllEDbMvQI+g5hplVZcR1F5BUHeZ8poLFDvOUOg4nQzbKQoqxjluSpBjGCRT20Ouvo/jhn5y9D3kqONkKkIcETZxVOQmXZ6EnkLbCCXVp1A2fkixdZwc/RAZ2iEKKs9SZD9Pof0sBeYR8o0DFGi7UFuCOGtddIbNjHfoONmhZ7TdsBNj0W+DzOvE7vUUwxEtiV1nY78MzV7oednZe53zORhUHUDPgX6QDqDnQD+KXgd6XlXy+r7Q832g6bugJ3lj19EXSWZ9xtq1dIf1ePyVVDRF0LTeROWZQ9w0RbFrmqLmOwi8txDVjFFu7SHf2Ea5ox9B9TDCmgsompJmZmNo7gXoMcWWMMeXqYiuUBG+hy22jqNtMwk9vY93vD2tg4/xDX9CYOQzPCPPCIx+kYyJL/Gf2o6v8Z/8iuDJrwiOfUVw4jcEJ36Df+K3SegZ+y3NI9tm5q+pHfyKmsHf4Bx8jq3vc4ydn6CLf4w68ghFaANZYA1ZcBWl/x5y3xIyzzzK1lk0njlMvrvYg4vYg4s4/EtJ4PHeo7p1A1vTGvbmdWoDj7a6t5LDCZ3hJziDjzC7V1E4ZxFbb1NuukKp4SKF6pNkyxJkiAdJFw2QJRsgS95PiqwnaV5W9pGhGSFTfzIJPpoJMnWnyDKcIlN3hlzTBY6bP9yBnmL7dcS1Uxi8y1hC69g7HlLd+TE1XZ+8AD21nU9xRh5hDz3AElrHGl2nMraBve0+ltA6Wu8K4sY5xI1zyFxzSF0zCOsmKau5Rkn1ZcprLlNee4mymosU2U9TYD9Fvu0k+dYJCirGOWEeJtc4tNWq3p+EHmMf2aoY6bIAh8pdHBO7yVIFKKzoo8g+SlntGeQNlyioGE8uUdUMUmg/S1n1JUqrLlBgHuGEvo98TSdaix9nrYuuiIWJDiOnOkw/GHr27uTahp5t8Pm7QM9AQPmd0LP7PB9Az4F+iA6g50A/irbLW7t3b+3N8uyX7fldZXp2f+dlPp++cPL9xNYqi96Qgf6wlrE2NYNtKjoieuqam6hoHsPgvoy8dQ6hbxlR4B7S8AKChjMUOfooMrZTVjGEoHKM8poLSJs/Qt5yHV3wDsbwPIbIAsboIobYEsbYylamZ5XK6Br2tjWqOjep6X6Aq/8xTQNPaB18im/oU/yJzwiPPCM09jnh8S8In/xyJ4Ink5kf//hzQuNfE9gK79jXtAwnvT4Nw19QO/ScmqEvMXV+hqHzGcaOz9BEnyDyriNoXaW85R4i3xpi/zoizzJS7zJy7zLylgWkrjsomqbReeap9C9g9c1j881THVylJrBOlXedyuZVKpvXqA5u7d6KPaY6dJ+q8ENqwg+oDmxgbFhGXTWH3D6F1HaTEsOFJPQI+8gQ9ZAu6SFD2kuqrJNjsk6OKbpJ1yTI1k6QpRknU3+SLMMpso2nOWG5QL71MvnWy+RVXKKg8gpFtmtI6+9g8t+jMrKJo+0RVR1PqOn6hOrOj6nqeJKEoI5PsEcfURl+gNm/jsm/jiW4iSm0gSGwhs67ity9iLhxDmnDHJKGGQS1tyitukaJ4zLFjguUOC4k119UniavcmJnEepx8ygnzMMcNyVNzPnmoWRZytRPhipKisTHB2UNpEhayVIFKbD0UuIcp7zuDOL6D8nU9POBuIP3RZ3kVZymqOpDyh1nyDMOU2gYQmjqxOp00dzkZCBq5mS7iZPtRsbaTQy1GxltM35v6NkNOjtZz+3zsA00e/xy32oeeI0zubd7c+95PoCeA/0QHUDPgX4Uva6R+fuUub4Levb77n4+gv2AZ+fmHVSRCKkZDuvoDZroCelIRBWMdqoZ7dAR8dmpcQWxNfWj999CE1lBHV9HFV9F6DpHUdUABaYk9JRbRymvuYDYdRlp81U0/tvow/MYo3cxxpcxxJbQRxcxRpaSqxCiK1TGV3G0r1PV8YDa7se4ep/S3P8ZnqFneBOfERh/RmDsc4LjXySHF26Fd+ILvOPP8Y4/JzD+Nb4t4HEPP6dxq4urqv8Z1q5PMHU8Qexfp6R5maLGu+TXzZFXO0tB/TwlTUuIPatIfetI3ItImu8iab6LvHkOWeMUctcdtK1zGL0LmL1zVPoWqQmuUrcHeqoCD2mIf0x97AnVofvURO7TEHtIfeQhFa4V9DXzyO1TSCpvUGq4SK5ilEzJEFmSPjJlfWTKezkmaeewuI0jknaOyno5Jh0kRTZEqnqUNM0YGbqJLei5uBWXKbJfpdhxDYVrFktwjcrIZhJ84g+p7nhCXfdTajo/prrjCVVtT7DHHlMZeYjJt4m2dR1N6yoq9woq9xLK1mWUrcvImu8idy0gqrtDec3kDvQUVp6nsDK57LTAdoZ820lOWMbINY2QpR8i17gdA+SZBskzDXLc2EeGKspRkYd3i2t3oCfP1L0DPcWOMxyRdfNOaYz3BEnoKXReoNxxmmLLKKUVCRS2HlxNVYR8FobjOsbjesbjBobbTAx1GBhp0zMa2X+j+qtiN/DsBz3f1Riw17uzH/Bs3xMOoOdAvwsdQM+BfhTthp69YLP3ae91zc0/BHp237xfCT0hJYmQipGwjr6Qma6gnkRUwXinmrFOPe2hSlzNzTibYxj81zBEFtDH19DG1xC6zlPkHNqCnsQO9IgaL+0LPfroIrpIcs+TZTf0tG3ibL9PTdcj6rqf0tT3jJbBz2lNfI539Bn+8S8ITDzfVdr6Es/EF3jGn+MZ/wrP2Ne0jHyJe/g59QPJYYP2nk+p6PwYTWQTRWiDItcC2c4pMm2TZNlvkVc9TVH9PAL3CjLvGjLvGuKmBaRNC8hdCyhcs8gaplG47qBvmcfoXcDiu4vNv/QC9Njca9jc61QFHlIfe0Jd9DH10Qc0xh/gantMQ+whNvcaxrq7KBx3kNknKTddJk89QbZsmBzZALnyAbIUfaRJOjgsjHFIFOeQuItDwl4OCXs5Ih/iqCJBimqEHONZTlgukFfxIfnWyxQ7rlHivI7CNUtlaB17ZBNb9D7OtkfUdH5MY98z6rqfUtv1Cc74Y+yxx9iijzB576NqWkPpWkXWsIisaQlFyxIqzwqKliUUTXd3oKes+joljssUWM9RYD3zAvQcN4+SYxwmS580MecYBpMmZn0fObpecvQ9ZKiiHBG28uuimh3oOWHsotgxRmnNKfIrT3NI0s07pW0clvRSaDtHifNDBM4zlFaOIqgcRu3oxuO2EQsaGG3TcDJmYDxuIBE3MtiuZ6RNz/jvCHq2wWe/ERDfygwdQM+B/ifrAHoO9KPouzI931Xm+rtCz8syPLtv5C+b2TMQUjMcVjMaUTIaVtMTNtIdMW4NL1QxsTXivyNoweOtp8I/iCl4A1NkAXVoBUHdBYoqExSaOyizDlNWOUFJ9TnErsvI3NdQB6a+2d8UuYs6vIA6vIAhchfTVkeXNba1Gyq2gSP+kKq2J9R1JVvVXf2f4058TtPIFzSPPsc99iVNW+EaTQ4lrB96TvXAF1QPfIGj5xmW9o/Rx56gjjxC5F2nsHGe3OopDhsucMhwjkP682RWXqW4fpryhlmEjXOIXPNImxZQNM6jaVxA3TCPunEOTcMM6vppdI13MLlnMbfMYfct4vSvUuVbw9G6ir1lHXtLsm19eyJzY/wRrR3JaG57QpV3nQrXChrnDDL7JALzFQp05zihGue4YojjikFy5H2kits5JIjyviDKe4J23i1r573yDn4t7OTt8nbeEXRwVJEgTT1OhvYkOcazFFQmS1ySuinMvhWswTUckQdUxR9S2/EEV+9nNHQ/pa7zY5xtj6iMPsAafoCu9T6KhlWktcuIapcQ199F1rSE2nsPlWcFZfMiwtopymsmk9kex0fkWc6QZzlFQeXpnfLWNvBk6YfIMQySaxwix9BPjq6XbG0PGeoO0hThF6AnWx3iuKGTgsph8m0jZBhGOSTr4wNpL+m6UUqqL1NWfQmR8wwC2yhiewKts4O430BPRMXJuILxiJ7xkInBiJGBNh3DbZrvBT2vW97aCz17B37uWxI7KG8d6H+iDqDnQD+KXtayvht49vP4vAp8Xhd69itpbbfcjuwzkXkn4xNJQs9YVMV4RElP2EhP1MRQVEMirOBkTM2puJq+iI6w34HN24HZfxlDcBqVf4Wy6vMUVAxRaO6gvHKEcttJip3nETZdRuK+hiZ4B11oDn14Hk1ofgd69OGFHeipiK5gja0lDbWxBzhij6jp+ISGnmc09D2jaehzXIkvaBx5jmv0S1yjX9I48pyG4c+pGdyCnd7PsXY+xdL+MZrwQ+SB+4i86xS5lsm03+KY+Qq/ko/yjnqcY6YL5DivU944g9A1i7B+GkHdNOK6GZSN8+gbl9DW30XbOIeuYQZt/TSa+tsYmqYxNs9g897F4buHw7v6LejZ3r1VH32Au+0BLe0PaW57Qo1/E1vzKtqqWeSOWwgtH1GgO0ee6hS58kGOKwbJlvWSImrjg/LIDvS8V97Be+UdvCPo4M2SGL8qjfO+uI8jsgTHFCNkaE9ywnKBE5YLCKpuom+5i9l7D1toE3tkk6r4wx3gqWl/jLPtEdbIfcyh+2hbNpHXryKtXUFUs/wC9Ki9914NPdYz5FlPccI6TrYhQaZucKe8te3p2c70pKvaXwo9+dYEJ6wJMgyjHFEMcEQ+RJZxgtKaK3ugZwits52OgIH+qJKTcQUnw0bGgkYGwgYG2jU/CHp2g8/LoGfvpPPd0LP7e9tndO9ZPoCeA/2udAA9B/pR9LLurd0Q9Dp7uF4FPq9T2toGnt3gs3ctxV5PwvD2zTqqZyBmSE6PDaoYCSsYjekZ6lDSFdPj9nmo9g5h9VxE652ltOYcuZYhcg3tCG2jCCrHyLdOIGq8jLTlOqrgHVThOZShWdTBORSB2ST4BOcwhrYyPtFlLJF7mEP3qIzexxZ7QFXHxzg7P6Gq6ynO7k+p7t3akzX4nOqtcPR/RmV3EnS0sY9RBx+i8G0icK9QUD/P8eppjpgu8yvFOL+QJHhLPkR6xTkKqq8happF4ppD1DBDedVtiu3XKXPcQNe0iMW9jMW1iK5+Fl3dHbS1U6irb2Kon8LSPIPNs4DTt0yVbxWnZ42q1vs4Wh5Q6b6PzbOB1feA2ugDXNENmmL3aQo/ptZ7H0fzKrqqWeTWWxRqL5EtHydLMkKudIhcWT/ZkiT0HBJEk9keYQcflHXxfnmy7POLgiC/KAjy67JO3hf28J6gmw/EA6QoR8nUTHDccAaR8wbKhmmMrcuYfKuYg+tUhO7vRGXkIdbwAyyBB2iaN5HVriGtWUVcu4Ks8R7y5mXk7kVUravImpYQ1tyhvPrWDvTkV5znhPk0+dYznKg4yXHLBLnmYXJMCbINCY5bRsizjlFgTQ4ozDH0k6aMc0zs5bCgifdKa8mQechSBcnVd5Bt6CXT0Ee6fpgMXbJDLd96kULnBQqs5yi2jSCoGEdWOYS5LkBXWJMsvcZVjEf0jIUMDER09Me1DLXpXtvTs99cnpd1cO3O8mwPK9w9sHD3Wdvt7/nWWfV/+yFl+/oB9Bzoh+gAeg70o2h799Y23PwQ6NkPZvYDnpdBz95sz3BM/+LU2X28PomwhoGoloHo1pqKsIb+iIbBiCm5ybpNQ1/cjK+1iTpXG5WhqwibzpBjHyBb34GkchhxxTB51jEEjZcRua8h9k0iC0yjCM2iCMwi802j9M+g9s+gCcyiC81jCC+iCyyi8d7FGFqjInYfZ9fH2NoeY+/8BFvHJzi6PsXZ/RmOnmfYuj/D1v0Zlo4n6KKPUQceI/I8pLx1nVL3Knl1MxzRn+cdxRh/KerlV5I+3lMPUVR3BUVwBm1kCV1oGZV3CaX7LuVVtyl1TCJw3kLXfJdK7wpWzzKmxnl0NVNoq2+jq5nC0jCL3b1IlXeJat8ytYF7OD33cbY8wtH6BHvLYwyNqxiaV3GGkn6epvgT6oIPqPOsU9OyiqVuHo1zCpHpI3KVJ8mRjZErHSJL3EOmqJtjwjgflEeS2Z6yNo6Ud3OkvJtfF0f5ZZ6PX+b5eL+snQ/KO3i7OMYv8yL8qiDGO6UdHBEPkKM9Q57pQ8qqJpG6FlG4V1C2bqJqeYi69RG6wGPMoYeYAg/RNG8irV1BUrOMpGYZeeMSiqYlpK5FlO5VZK5lBLWzCKqnKK++RYnzOgXWC+RZznHCfDoJPRVjO1OYs41DZJsHya1IkFuRIMvYT6ahlwxVlMOCJg6V1nNEUEe6vIlMtYdMTZQURTupql4yzCPkVVyiqOIqZZWXKbCOkW0ep9AwjtgyhtreS7W7nv6QnuFwcnjmcNjAcDgJKYmYluH46/t4RveAy35ZnL0TzhN7ztHO5OZ9fD37jZYY8KsY8KsYDKgZCmp2YjBwMJzwQD9MB9BzoB9Fu6FnO9OzG3Bep339daDnuz73d4WenZt89Jsy2EhURSKqZzSqYzSuo7/NgM9XQ0NLEGfoPDLXGQrtw2TruhBVDiOyjlBYOb4DPSLvTcSBO0iC08h800i9d5B776AJzO6ELriA1n8XjfducgryC9DzFHvnU5zdn+Hs/gxb16dYO59S0fEJpvhjdJEnqAOPEbTcp6Bhkby6OTJsN3hXPsYvBQP8ZXkvqYbT5NovInLfxhBbwtq5QUX7JsbQPTTeJYTVtxBVTyGtm0HvXqTSu4LNdw9L8wLG+hkMddPoa+9gqZ/D1nx3B3pq/Cs4Pfepan1MlfcTqryfYHStoW+6h82/QXXoPnXhB1T7NqhvXaOuZZWK2jl0jinE5qvka89yQnnyBehJFcY5XPYN9BwV9CShpyjEm3mt/CrPx7slMd4rjfN2YZhfHPfzF7k+/jzHy1uFcY5KBkmVj3HcdJFix20EtbNIm1aRNW8ia95E2foAQ+AhRv8D1E0bu6BnCWXDEipXEny2oae8ZoaSqluUVU1S7Li2Az3HTac4bpnYF3pyLEPkViTINPWRYewlUxnmqMDFobI6lQUi2wAAIABJREFUDgtqXoCeY/IOUlX9ZJnGyDdfpNDyESXWD8mzJMg0jpKvmUBqHkbvaKOh1cFQ2JAEnq25UjvQsyv+R0PP7knmrws9+55Vv4p+n/Jb4HMAPQf6oTqAngP9KHrjjZ/Q65XR45HS45HuQM9eE+PfNdvzfaFnKKR+YeLy7t1C/ZFkFudbKyqi30R/JFn26oslN7KPR3SMx9S0Ba34fTU0hjrQu4YR2YY4rumipDJBuWOUEsdEckVF81XE3psIWycRtk4i8txG7r2DwjOFLjSP0j+DwjOFovVOEnoCSxgjG1jaNrF1PqEi/oiK+GNs7VtZnq5Pqdzy7ZjbnqCPPEDlX0PWeo/Cujly7JOkmq7wlniYnxd385ZggDTLOUTuGRT+BXTh5Jwgc3ydyrb7GIKrqN0LlNqvI6y+hbw+CT0VW9BT0bqEpXkBS/MChoYZjPUzWJpmsXsWcXhWcHjuYW+5R63vEQ2hT2mIPKM6+IiqwEOcoQdUBTepDd2nxrtGvW+dOu8aFXWzqG03KTdcpEB3jnz1aY7LEjvQkyKIcaQ8ymFhjMPCTo4K+zkq6uNIeZS381t5M6+VN/Na+GW+h1/me/hFXiv/d0Y9//pYDX96tI6f53j5y+MhPhD2kak+zQnzJYR1c8ia7yF3r6JuXUfv20Dv20DdtIGodglR7RKSmqWdTI+yeRHNVnmrrGaKIseNZJan8hInKs6TazlNrmmCXMsouZZRjlckyLUMkWUYJMc8SK5liOMVQ2QYe0k39JCmCHOo/BvoSZM2ka7wkK1tI1XRTapygFz9aY4bTpNjmCDbPE6GaYg07Qj58gnUpk6sVW7CARPDES2j0V1rVKKab3Vf/V2hZ69Jed/29Oi393F9H+jZBp69cQA9B/ohOoCeA/0oeuONn9DjkdLdKtkBn5eZmV9mdP4uY/PrZIT23oQT+9ys9z7B7l2KuPNHIKJOLiON6hiNajkdlTMUVtER1OIP1WN3daFz9JCv6aTAlqC0epTy6tOU111A2HQZsfcmgpZrlDV/hKD1OnLfFArPbTSBWaTeO4jdk0hbptAEFtEGlzFEVjHHN7C2P6Ii/ghL7CG2+BMcXU+xd35CRccTTG2PMMQeoA1vIGyao6DmFunmi7yvGOUt0QA/L+nimHaCgqqraCMr6KL3MEZXsXZuYIguYwqvJiOwis6zhKRuCkndFPKGabTN85haFrF4ljG672JsmsfYNI++cRaTaw5L88IO8NhalrE3L1Hj36Qh/Iim+Cc0Rp9QH3lIQ/gRjcGH1Ac2qfWv4Y7epyX2AHvTHFrnJEXa8+QqTpMrHydfOUqWqJcMQTLTc0wY56i4jTRpL+myUdLlCTJkXbxf6uOdwpZkFHv4dYmXX5f5+fkJF/8uu5afvVfBn7zn4P86XMPPT/j4QNRLhnqcIts1ZI3zqNxLaHyraP1raP1rqNwbiOuWtyJZ1pI130XqXkTqWkTcsEBpddLvVGS/Sr71IsdNp8g1TXDcfJJcyyg55mGOVyTIMQ+SZewn29RPjnmAbFM/abpOjqnbSFUEOVTeyOHyeo4Ia0mVuMhSesnVdZGpHiRTM0K+4TwF+jPkmsY4ZukmVT9ChmqUEtkQFmsLDY12uvbx3ew1Eb8u9GxnP/dCz7eM/vtke3bvrnvV7q2XQc9e8BnwH3h6DvTDdAA9B/pR9Cro2Q94Xrfc9b8S9JyNyklEpXSGlQTDTqqaohirOijUtHOicojS6lEENWcQ1H+IqPkKMu8kgpZrlLuvIvLcQOG/g9I7hdo/g8Qzhdg9iaz1zg706MP3MMXWqWh7+AL0VLY/wdr2GGPsAfrofXSRTRS+FUrr75DnuM4H6gl+JeznTUEf78sTFFRdReyewRhdxRRbw9K2gaPnMZa2DSzRdSoia5iCK+g8S8gbZ5DUTSGrv4OmaQ5D6yLm1iUMzQvoXHMYXHMvQo/vHk7vKvbWFRzuZWoCGzREHtIYe0xdOLl7qz70MBlb0NMaf4iv8zG13mXM9TOUGS9xXHmG44oJ8pWjZIv7yBT27EDPMUk76bI+spRjZCpHyFL08EGZn3eLPbxf6uMDQZBDwhDvCQP8srCZf3+8nj/+oIKfvW3lj96p5E9TG3irMM4hUT+5+nMIam4jbZhD7b23Az3q1nUk9SsvQI+0aQFx0wKi+nkEtbMvQE+e9QK5pglyjOM70JNtSmZ5tqEny9hHtin5b4qmnaOqOCnywA70HBXVJaFH4eO4vptszTDZ2gny9Rco0J8hxzj6AvQIFYNU2l00N1t3Mo7f1Wb+utCztwvr+0LPzvuv0WywF3p2w88B9Bzoh+oAeg70o2g39GzH7v1be/dxvQx8fhfQs32jHo7pv3VTfxX0DEU1Oz6J8aiWMzEF43ERg1ERXVENLc3NVNf4KNFHOF4xRHHVBMK6M4gbLyFzX0Xun0TkuYGw9ToS3ySa4B20/mkUnimE7kmE7klk3hnUoSXUwWXUwWW0oTWMsftYYg+3SlyPMEcfYIrcRxfeQBVYRe5dprB6kjTjOd5XDPPz4nbeFvdyRDmMyHX7G9iJrVHZvom94yGOzkdY2x9RGdvAGFhG2TyD3HUHecM0ktrbiKonkTdMo3EvoHEvoHbNomyYRtMwg841h6l5gYrWJZy+Nap8a9QENqgJrNPc9gRP9ye4Ox5TF9rc8vtsUh98TF3wAfWhNYK9T4gnnuHvfkRtYAW58yaFug8pUJ+lUD1OjrSPLHEPaaI20iQdpMo6yVIOkq0eI1c9Qq66nxRhlKPlYVIkUbJUnaSr2jkqjfBrgZc3i9z8+8wa/tW7FfzBWwb+jzeN/Oujtfz7rFbeF/aQZ/qQEud1pE3zKL33UPmSpS5p0yrixhWE9UsIGxYQNs4haJilyHGTAtt1ip2TlDhuUGj7iFzzWTJ1I2TpRzluPkmOeZhsU2Ins5Np6CPT0EumoZd0fReHFVHel4Y4ImnlsLCRo8J6jokaSJU0k6XwUWAaIN90ijzTOYr1V8jTnyHbMMYRYx9ZxgQF2mG0pijuBjsRn57RNsULmZz/UdCzG3z2g5z9dm69sHF9nxL0viXpfaBnOw6g50A/RAfQc6AfRW+88RO6WyV0tYjpahG/NvS87n6ul010fhX07F44+jK/wqugZzj6DTCNxnWMtSsZjSpIhBUkQlpCLU5c9dWILW5yLUPk204iqDmDovkjlK3XUQZvI/HdROKbROG/jWYrFJ7bCFq+gR5l4C5K/yKa0Aq68DqG6Ca68AbG8CaG0AaG8DqG8Dq68DqCphkKqm9wWHWSX5R28v8URnlP0oWg4SoKzxSWtuRur4roCpWxezg7NrC1baAP3MMc2cAa2UTvXUZSN4mo5gbS+ltI628hqUtCj8I1m5zGXH8HWX0SitSuWTRNMxjddzE3L1Hl26A+nOzQCie+oPPUb+k7+x8I9T7F2/aAlvjHNMU+pSn2MU2xTcIDT2gf+5Rg3yMaIvdQ105RrL9CoeYcBaoxsiW9ZIq6d6AnTd5FlnKQHNUoOaph8lQJMsRdpAk7SBXFOCaKcUQY4gNhgPfFAY5Iwhwq9/PWiUb+LM3JH7yl5/ffNvLH79n481wPx+RD5BhOUVp1DVHzPBL3IvKWe0ibVpG47iGsX0JQP095/Qxl9XcosF0nz3qV/MqrFFReId96mRzTGTK0w2Tqh8kxjZFlHCLD0EeWMRk70GPsIV3fxQeyMO+KAxwWt3BE3ECKpIEUcSMpomYyZT4KzUMUms5TYLpEvv4jjptOkWEa55hulALDKEJTL9V1LtoCBnojGsaiqm8N3fyu16+KvaWqoYj2lXDTH1S9sHtr+73XgZ7B4IuQ0+9T7sQB9Bzoh+oAev43Vm1tLb//+7/PP/yH/5B//s//ORaLhf/6X//rzvW//du/paioiJ/+9Kf8s3/2zwgGgy98/6/+6q9ISUnhH/yDf8Af/MEfMDY29tq/+403frIDPNuxX9v664LP/0rQMxjTMdSmY7hdSSKqZDisYSRkINRaQZPLiqzSRY55kOPWU5RXn0XpvoLKew118DZS/yRS/yRK/yRKz01U3kkUnttJg7N7EknrHeS+eeTeBTShFfSRTfSRTdSBe2hDa2gD99AFV9EG7qHyr1BYc5Osiov8SjzIX5Z08KuyTnIsJ9H6pzFH72JrX6Uitow1toyzbRV72xqV0TWMgWXMkQ0qwhsYfCtI628hrr2JvHEKZeNtpPW3ENXcQlI3hbjhDpK6KaRbZS9Z/R3kdbdQNc6gb1yi2r+ZLGnFHxBOPKPvwv/L+JW/IZ54RqjrEZ72pzTFPsW1BT3BvkfEhj/G271ObWgRZfUtivVXKFCfTXp6xD1kiDpfyPRkKgbIUY2SpRgmRzpEhqiHNEEnKYIYh0rDvFfs5/3yAEelEdLlcdKkYQ6VeXg7z8WfHrbx+28b+f23jfxpagPvCzpJVQ6Rb71IWcM0Qtc80uZlJK57iBtXENQtJqGnYZrSuimKHDfJr7zGiYornLBc5Lj5PNnG02Roh8nQJcgyjJChHyBN15NsS9f3kKHvIdPY8w30yIO8K/FxWNzCUUnjDvQcEzaRKfORbxiiwHiOfONF8gxXyLGcJM00TpruJMX6UaQVXbjcNfRsjVEYDe1Ttv0ekLM3dk9Yfp2MTn9QtRO7X79O88GroKffpzyAngP9IB1Az//G+vTTT/lP/+k/AfAf/+N/5P3338fj8excFwqFZGdn87d/+7c8fPiQf/JP/gmXL1/euf7uu++i0Wj4L//lvzA9Pc1Pf/pTNjc3X+t3v/HGT+h0i3aiu1WyL9C8Tplr9+uXQc9+4PMq6HmVZ2Fo1x+B3Z/ZbgtOxJLD3/raNQyGtSQCJsZCBmI+Pa3NRmT2+uQ0XvNJyqtPo/RcReO/gTp4G1VoKpnxab2BvOU6itYbKDy3kfjuIHHfRuK+jbhlGplnHm34Hsb4BrrIKkrfMprgKkrfCtLmOaTNc5TWTJKqneAD2RC/Evbygbyf7IpT6EPTWNsXsXUuU9O7SXX3JtUdG1S3reKIrGCLrGKLbWAJrmEOrmD0L6FqnkHeeDsZ9ZOIq69RWnmRcudVhNXXKa+6hrDmBqLamwiqryNyXkPouI6qdga7dzPZqRVeJTj0lN6zv+X0tf+PruEvCHQ+xht/SmPoE+pCD6mLruPp3MDTfZ/a0CIV7mmUjmsUGi5RqDlHnnKULGkP6aJOjgnbSZN0kSrtJk3eT6pymDTZEMdKOkkXdpMp7iVV1MX7RRF+XRDgcHmYDEU7acr4Fvy0kSaL83aeiz9+18y/+IWGn71TwS9yPLxfEiNLN0Fh9SQltbcRuxYRNm5F/V3K62cQ1N2hvHaKkqpJihw3yLVcJNN4hlzjabL142ToEmToB8nQ9ZOm7SZV00WqppM0bRfp+i4yDN1kGLqT5S1lmPekfg6LWzgmdZEubyJV1MCR8kZSJT7y9QlOGM5zXP8hWYYLpBvOkWY4T5r2NAL9GCZ7DJ/PQW+7gr64kkG/7ltTx3d3KO6MZ3iJwflV0LMNPruhZvt7u706r+Pd2W8a8+4SV79PSZ9XQZ9XQa9HfgA9B/rBOoCeAwFJ6Dl06BBSqRSA//yf/zN//+//fR48eLDzmerqanJzcwH4/PPP+b3f+z3+5m/+Zud6aWkpZrP5tX7fNvR0NAt3oOdlmZ7vCz37Ac93LS19oXV21xPsy7ZG733C3c7w7DZBD8X1DIUNJEJ6xqIq4j4jniYrMqubvIohCmwTlNeeR95yBZXvOtrwHdThO6hCU8gCt1H6bqH23ULtn0YRmEXumUbaMpWEHu8cusgqhvgG2sgqUs9dRK0LlDRMI3DNUlY/RYbhNIfl/RxRDJBvO4/aO4UhPIO1/S72rhXsXSs4Oldxtq1S1b5GdXyNqtgqtugKluBd9L45zIEFKiPLmAML6D0zKF2TCKsuIbBfQFh5gfKKc5RZziKsOIfIeh5x5QUktg8RVyZ/VlTfwNB8F4t3jYb2p3j7nuMf+IpA75c0RT6lLvCIKu86Ds8aNu8q1tYVLJ4NDJ57yOtnEVdPUVY5San5MkW6JPRkSHtJEyeHE6aI46RI2zkq6eKIqItDgg4OFYVJEcTIkHSQJesiVRQjRRglTRwnU9ZGhixGqqSNVEkbKeI47xZ7+IvsRv5tShX/55tafvZrE3961MF7wjayLRcpdFxDVD+PqPEu4sYlRA2LCOqmKa2+RXHVDQps1yiyXSPfepnsbeDRDpOmGSRDO0Cappc0VSdpqk4ytF1k6pORqu0gRdNOmr6dI6oIH8iDHBW3kCZtIlPWTJqoiWPlDaRLW8kzDZJrOU2m+RyH9Nc5pvuQdO1ZynQ92O1eXE1VdIY1DMflSQDxmL6znPWyqcr7dlftk9ncne151eb0vaDzsrP4sgaGvfeBA+g50A/RAfT8b67Ozk5++tOf8pOf/IR//I//Mevr6wBsbGzw9/7e3+O//bf/tvPZM2fO8Cd/8icAXLhwgT/8wz984f/y+/0cOXLktX7vG2/8hA63gA63gM4WId0eMb0+Kb0+KX1+GX1+WfL1/0To2Y69XoT9tq3vCz3xbwzQozE9o1EDibCJ4bCO0aiMuNeMx1WJ1NxKQcUgRc4JBHUXkO2CHk1kGlVoCqn/FgrvZDL8d5D7Z1D6ZveFHk34HqLWBQTuOQob7lBUc4v8quukasdJUw+RpR9FXH8Vc2QOc3QWS9ssju4VnN0r2NqXsEWXscdWcEbvURVLZnv0nmnUzbfQuW9j8c9h8c9h9Eyjdt1EXH2Rcvs5xM4LSO3nEVvPIbaeQ1RxFlHF2eTPlacQWc8gsV9B2TCNvnWZuvanNPc+x93zBQ3xZ9QGP8XpfYK1ZQ2LewmLewmzexWdewNV4zKiqmkEjikEjklKzZco1J0mVz5IirCTI+VxjpaHOSaOkCJLdnAdKo9zSJA0MKeJImRI42TJ20kVRUgRhkkVRUiXxEgXJwEoVdxOiqiN98tCvFPg4Re5DfzJuwb++Nc6/s1hC78s9JGuP8WJyouU1Uwhqp9H3LCApPHuDvSUViWNy9tt6lmGU2TpxkjXJEhT95Gu6SdV3UOqsoM0dQeZum6yDMlI13aQpmknQ9dOiirKEXmIo+IW0mXNZMndpImaSBG4yJB6yTcNk2M5R6blPO/pr5GivUCW5jQSYzu11Y34Wqz0RjQMx5QkQlqGvcaXdlnt9ufs16W4nx9nv66s3aWs7zQmfwf07D7Lr/LzHUDPgX6oDqDnQAA8ffqUuro6/vqv/xqAubk5/tE/+kcvfGZycpJ/+k//KQAjIyP82Z/92QvXe3t7+eUvf7nv/9/Y2Mgbb7yxEz/5yTfQ0+EWfAt6tn9+3S6uveWtVw0m3PsU+7KliS/L8uxX7tpO+yf/iBgYjRoYjehJRIwMh3WMxb+BHomphQJrP6VVEwgbzr8APdrwHdTB20h8k0g9N5FtQY/SP4PSP4PcM42k9Q4y7xya8DK6yCqa8D2kviVE3kUErXc54bhKiv4MxzTDFNnPI6y/gt53m4r4PKbIDMbIFNb2OaxtC1ij81QE56gIzmEP3aU6vow9uoiu9SZK10eomq6ibbmBwTOFwTOFvvU2srorCKvOoaq7hK7xIzT1l5HXXkTkOIvAdpoSyzhl5lFKTaOUmE5TXnkRSfUNjP4lqjsfUdv1CZXRBxh9a6hbNtE2ryS3tDcuYGhdQ+1aQVa7gMB5C6FzEon9I0pMp8lTJcgUtnGsJMjhIg8fFDbz63wX7xS4eDO3np9n1PBmTgPHBCHSJREypFEyZTGOlQc5UurnWHmQdHGUVGGYY4IIKaI2UkRtHJO0cUwQ4v0iD3+e7uRfvqvlj95S8q+O2HizJMZheX9y7YPtGiX2mwhr7lBWc5uSqkmKHR9RaLtMif0KBdYLZOtHydSNkKYeIFXdQ7q2jxR1JynKNlJV7WToOskydJNt7CJd20aqOkaaJs4xZYQjiiApshZSpY2kyVwcEzZxtNxHujRKgfkUxysukWW+SIr6PMe1IxQZ+9E7ArS6a+nwOUiETQxFdPSHtfSHlN8ClP28aHt3zL0Mdl72ALBd4vq7AM6rsjzb536/OICeA/0QHUDPgXZ05swZUlJSgG8yPf/9v//3netnz559IdPzR3/0Ry98PxAIfO9MT3tzOR1uAV2tom9leXq8ku/duv6y/Vt7DcwvA57XgZ69XSzbr0fCOkYiSehJgo+ORFTPSETPeDxZ3mptMiOuaKaoYpBS50lEjeeRtn6EwncdTWgKTWgKdfA2Yu9NRJ4biL03UQamUQVmUWzt4pL7ZlH4F1AFF9EEltBH19CE15D5lylvWSDDfI5j2gmOV55D1nILTWAWfeAO+uAU+uAUxuCtnbAE72ANz+KMLuKMLuCMLmAPz1Hhv4M1MI01PIslOI3ReweDZwpdyy2UjddQ1F1B47qKofk6uqaP0DZcQVnzIfKq84gqT1FiGae04hTlFecoNSVLYCLnDfSeJSyhDUyhDWTNC5Q1zSBtmEPTtIzOfQ9NyyKShkWEtfOUOKcos9+kxHyBDGkvR0uivJfdwK/SKvnFMQv/7n0d//ptOX/8Kxn/5l0df57m4M3selKEYVLKI6SUR0gXRDlWEuRYqZ80QYgMUYR0aZSj5UFSRTFSRTHSJTFSxWGOCgJJY/MhM3/8lpZ/8Qs1/zKljr844SNFMcgJ44fkmy9RVHmdYvt1CuxXya/8kALbRYrtl8gznyZLN0K6eoij8h6OKjpJUXdyVB7jmCLOMUV8K7PTSbaxizRNnBRVlFR1jFRNlGOqMMeUzRyV1nFUWschYSOHRK2kKMIUWMfIrzjLCfNZctSnEJg7UdtDuFw19AdNDEaMnIrqGQvrGA5pGYlIX+pL+9Z8qdeAnu3sz34Zz759Mqh7Qea7Oi5fltU5gJ4D/Y/WAfQcaEcTExP87Gc/A77x9Dx8+HDnek1NzSs9PWVlZd/L07MNPNvQ0+OVfJPh+Z6Znt3Qs5+R8mUQtJ9/Ye9Nf+/N/lVPyzsRS3ZzJaLJ7dTjcUUSelwViCxNFFqTc3pEjReQt36E0nsNbfh20szsTxqZxS3XkbTeQBmYRh2YRxWYRR2YRxmYRxVcRBlcRBNeRhtZ3YGe/OpJUvSnSDGcpKT2I7TBOfTBLejxJ0HHFJjE4LuB3nsdU2ASe2ye6ra7OGPz2COzOKJzWAPTOCLzVMXuYg/PYfbextg6iaHlJhrXVVQNV9A1X8ewFbqmj1DVX0RRewFp1VnEjtOIbKf5/9l7z++o0vReu/sEnzPjsX18xnaPJ/T0dM90z3TOdAAEyjlnqXLOSTmVcuVcpSwhECCSAIEEElmJ2GGiffw/+Iu9lv3R1/lQSC2EBHTwy7vWqd9a91LtqkLow7P3vvbvDo+s6QyCulNUmqapspxE1XMdoydedF3TfYNy+zWqWy6j7llB3b2KonMFUcdKfMfypgWqG85TqD5EamWA3XmdvL1Px5t75Lz+qZRffVzLC+9V8sJ7lbyepGV/kZ20in4yBD7Sa71kCOORUu0ktcZFlthPrixEvjQOOtmSCNmSULzGR+wnXehlf5WDd7IbeDXFxAsfKXlxn4nXsttJEQ5QoDtGsfE0Fbbz8XRWwzlK6s9S1nCaivrTlJjjHVuZqhHS5TEyFFEylBEyVGEy5EFS5QEyVGGytRHyDANkaUOkq/xkqANkav1kaHxkKnpJl3WQKm0nWdTBfrGDTGWAUtsk5ZYpSk2HqNEfQFsfor6tD5/LwlhQz9GQjmm/kSNePZM+FSNB8ba1Nzs5lDsNGVxvTd+pBX3Mq3oAenZyYB/n0O7Usbl5q5r17WoS0JPQt1ECev4fVjQa5Z//+Z/5j//4D/74xz/y2muvoVarNz4XCAQUFBTwr//6r/zhD3/gueeee6B7a8+ePWi1Wv793/+dpaWlr929Fe2pfcDp+TbQszm19URj7ndoYX/S9NaOsLN+EwlqmAyoORDQPQQ9YmvPA9Aj6zuPwjGP2nsJlSdey7MVejTeVVSeJTTeVdS+NdS+W6h8tzagR+27g8x9m0zTDFnGE5S1zqPxrqLx3EDluILGdQmd6xIm3xUaI8tYfFcweS5hdC/SGLpBU3iJxvA1GkPXaQxdx+q9/BUAea9hcV/B7LqM2XUZfd9FNN1zmB2LGPsuou+ZR9d9Dm3XLNquWTSdZ1F1nEXZfgaN/Tyy1llqbScp0R+mpuEM4rYFFL1L1HZcoqTxIvmGU5SYTlFuPUNt40VqmxaobVqg1HiCHPkYH+V385s9el76UMZL71bxqw+q+fVHAt7YJ+GDTB0f5ZhJq+ikWBqiWB4hVxwktcZFRo2bLIGX9GoXaVVOsoU+8qUhCuURCpUDFKoGKVAOkK+IkC0Nki0NkiMLkVzjYHdZF6+lmvnpx0p+sUfPBwV9ZMgOkKs+QonpDCXWWUrqZylvOk953cx9F2aaLM0EGfJBUiRh0uQhMuQh0mUB0mUBUuUB0hR+sjRhcvWxr9wdVRx40tVeMpQOUiWd7Jd0sF/QSo7YTpGqB1l9GE19CHVdEFu9j86OXly9rYz49RyJyDkcVHHEp+GQNz71eDgo3xZ6tqtFe9Rk5W8DPZvP1SdJTW/n7mwdYDrUL0lAT0LfSgno+X9YWVlZ/PCHP+T73/8+L7zwAjabjX/7t3/b+Pxf/uVfKC8v5wc/+AHPPffctnN60tPT+d73vsfzzz//tef0bIaegT7hN4aezcePcniepKB5YsvF/RsBT0C7AT0T9ztmjkYVRDxGHD0WpHV9cehpOYLQfuoB6FG6L21Aj6R/AaljcQN6NL6V+E//TbSBO2iDd9EF7qEN3EPpuYXEtUqa4RhlrfNIncsYQrdQOq+iclxB676M2X+d+sgqHSN3aIquUBe8jtm9gMWzeD/O0xS6TGv0Go2BqzQGrlLnuYzNfYlG/zWZHy5jAAAgAElEQVSaAtdp9F/D2DePvuc8FucCpv4LG8e67nMb8KPpPIum82wciHououmaR9R8hgrLNBXmY9Q0nKHEdJIc9RGSagZJromQKRmmWHuYYt0Ueapx9pY5eC+jgV/tEvPC22W89F4l7yYr+TTHxP6iejJr2sgRdpEj7KFA7KFEGqFIGqFAFiZb6CNb6CNP5Cerxk1GlZPsWg8FkiAFsjB5sgh58ih58ij5igh58jA50iB58hDZEj/pAje7Cpp5OUnFS7uVvJbawO6KIKnCEfK00xSZZyipn6WyeZaK+tOU2U5QbDlKlnqUNFmUZHFgA3bSZN77To+PVLmPDFWQXH2MbF2YTE0w7vCsOz1KFymibvYL20kVNFIgaaJK3Yq1uRt7exvdHc14u5uI9Dcw4LIx4ddyKKziUEjJpD++/se8Kob9jy/A36nmZ7vxDJvb07fO4Xmc07NT6mq7720HPJtneSWgJ6FvqwT0JPRU9F1Cz+ZW953SVt+l07O562W98+VR0DMZUHMkIifqNeHqsyGt76W8bpyK5sMIOk4i7T2HwjGPyrO4AT3ivosbhczr0KP1r25Ajy54F334M4z3W9Yl/cvU9Fwj3Xicmq7LqHy3MEXuoHZfR+uJ1/LUR1ZpHrxNx/A9mmOr1IduxKHHu4DJfQGT+wyNoUXaYtdpDl+jKXgNm2cRm2eRlvANWiNLNAWvYeyfQ997DrPzAibHPCbHPIa+82i7z6LpOoO68zS6nln0vecw9V/A7LqMyXEZZcc5Kq3HKDMdodRwhFz5BCnVQ3xU6GZvuZc0QYRc+QgZogj7q728n9XAa3s1vPhuBa+8V8brn9byca6JlPJmMms6yBS0kyXoJFvQQ77ES4l8kBJ5jCJFlFyJn3xxgAJpgGyBm8waJ1m1LgqkAQpkYXJlIXKk8Z/5igjZkgAZQg/ZEj/ZEj+ZIi+7y9p5O8PAr/dr+M0+M7sKneypDJGtnKLQdIoi25mN1FZ53UmKLYfJVA+TKo2wX+SPQ4/cR5rcQ4bCT5rC/xX0GKLk6CNk6eKprSxdIP5a4SZF2MN+gZ0MQQOl0jqE2gba2pvx9VgI9RoZcOoZcZkYdZsY98ZdxYNhOQcCcsZ8yjiIeHVPBD2PAp2t0LPV6VmHnyeBnu3g50ldngT0JPRdKgE9CT0VPfvsM0S6a75z6HlUl9Y3rel5HPRsBZ8DAS0TATUH/KoN6DkclhHzmXH31yGt76XMNrYBPZKeWWR951G6F1C4FpE7Fh+CHq1vDV1gbSO9pQvexTzwWyyx36Hx36W2+wrlHQsUNp1DG7yLefALjOHb6ANLWMKr6LyXaIzdpHnwNg2hFZrCS9T5r2LxLFIfvEK9fwGj6zQWz3kaAos0Ba/R4LtKg/8KDf4rtMdWaI+t0OC/gsV5AbNjHmP/HCbHPBbXRYz9c6g7T6PsOIWy4xTanjMYHXE3yNC/sJESEzacoMpyhCLFBPvL/Owt9PFBZhefFvayv9xFUqmDtzPqeXmPjl9+KOLljwS8myQiOVtNepGFzGo7udJ+cqX95Eh6yRb3kidxU6oepFIzRrlqhGJVlAJpgEJZkGJFmFyRl6xaF5k1TvIlfooVYfLkcbcnXxGhSBkhRxogXeAmXeAmW+olS+IhW+IgpaqdD3PNvLxHx2upbbyb08N+wTA52mlyDMfIN01T0TBDRcNJSsxTZKiGSJMESRH7NqAnQ+4hSxXcaEvPUAfIM8bIN0fJNYbJ1gfJMd4PhY9UQR+ptZ3kCeoQqnRojHp8PToO+cQcDwo5HhRy1C/nsFfNpEfHQb+B8Yic8YicsaAyDiNuw47Q8zjw2Tp883HQsz5peafure3cnG8KPYN94gT0JPStlICehJ6Knn32GaLdAmI9wgcGFG7edX29cHFzPMn+WxPe+I7MB7yaB2MbwNmuk2u7i/uD800ehp0H6yN0TPq0HPBqGPXFf9/hkJJhr55gvxFjYyel1lHKGuPpLWnfLArnHGr3Amr3AnLnBWT9cQDS+K6i8S+j8t6M1/F477s8oXuYY19ijv4Wjf8uVV1XKGyZR+hcwTL0JXUjv8USvUlddC3enh68QlP0Ko3ha1j8l7EFr8Tfi1ynJXKdptBVrN456nwXqfMtYvNdod5/g/rANer8V7F6L2PxXMLsXqTRf4OW0BJm5wVs7ovYPPNY3HNoe2ZQ2o+j6DiGtucMhv5zmJxzaLrOoGg7Ra1tijL9GKXaEfLlUdJqPCSVOkgq6Sat2kFatYNPi+28lW7j9WQ976QZ+SjHQkp5K7mibgpk/RSqfOSrAhSoQhQqgxSropSqBynTDFOoGCJfNkC+NEyBLB55kiBZAi9ZQg+FsiAlyhDFiiD5cj8FigCFyiAFqhD5cj85Eg9ZIhdZIhc5Eg+FKh8FChcZwl7ez2nipU9NvJJcz6flfnI0hygwHqHQfITyxuOUWI9QbD5IrnaUDGWE/RIvyWIXScI+kqX9pCq8pCl9pCsD8ZoeQ5R80wD5pgFyjWFyDCFyDCGylS7SRA5Sap3k1DYiNeiwNmiJuRQcCsiZDso4HJBy0KvkgFfFAa+Oca+O0YCK0YAiHn41o179tut4p1b0xwHRuO/heACUtjxUPKo1fbuHl+06tTZDz/rk9gT0JPRtlYCehJ6KtoOedft6M/TsBD6bL6brGxGOu+Owsx7fFHp2ejJ+EHoMTAb1TAb1HAjomPBvrovQbkDPhD8+mv9IQMGIR0e434ilsY2KulHKG4/EC5l7Z1E65tC4F1C5LqJwzCPpm0dxf3aPLrCGyhMHns3QY4p+Ed+GIvgZFfZLFDXPIfffwTz8W6wjX2IduEldbBlr6BoNkUs0RC5RF1zE5F3AFrxCQ+Q6bYMrtEZv0BS6Sr1/gXr/Jep9lzegp853HZv3GkbHIkbHImbXZRqDy7RE1rC6FqnzxGMr9Ci7ZlD3nEHXfw51zxkkbceoNB2gSD1EgXKAXHmYLLGflGo3qTUussVuMsVukiq6+LiolU8KW9hXbietppcCuZtchY8CVYgCXZQCdZR8VYQCZZRC5QBFymEKFcPkSQfIlUTJFoUpkEUokEXIEfnJEnjJEfsoVYUpVYUpVgbIl/soUPgpVAbIU/opUPjJl/vIFrvIFDrIkbgpUHopVHvJV3j4uMjOCx/reHmvlY9K3WSrD1BgOkyx7QhlDccoshyi0DhOnm6EbM0AyVIfScI+dtd2sk/cQ7LMHZ/DowqSrY2QbxqgwDy4AT3Z+mA8vaVykipxsr/WSVZNEwqThoZmDcM+BZM+FZNeDZO+zfVn6xCiZjygiIdPzbhXt239zXadiU8SY171NtCj3YiN9f6Y7SYeNXl5u/b0YYc0kd5K6DtVAnoSeip6UujZaUDZZugZccdj1KNizKveiIefTh9/cd9uGNvDbeq6DdhZB571J9/199ZvApM+PQe8Gg77FYy7NUT7tTQ2N1NdN0Rl42FE9rMoemdRr0OP8wLyvvMIu88i7Z9D6V6I1/L47qD0rKFwr6IN3EEXvIsx8jnGyOfoQ/eo6bpMWftFVOF7WEZ+h234S+piN6mP3aAufJn6wEXqg/PYfPMYvfOYfYtY/JdoDF/bcHrqfZdp9MfTWhb3lXibuusKJvdVbP4l6gLL8fBdp95/A5vrKjbHNcy9lzF0L6Kyz6NoP4+87RyytjkU9nkU9nnEraepaThOqeEAucpYfP8rWZgMeYgMWZgceZBCdZgSfZRy4xBVllFqbOOIGqYQNR1G0HCIKvM4ZcYRSg3DlOqGKNEOUqCKkSMN36/NiZEvHyJPNkiuJEauJEqOJBRvU5fEI0/mo1AZoFQTiAONykeB0kuWzEmm0EG22EWOxE2WyEmWyEm2xEGO1EmOJL4j+yv7rLye2sQHRQ72iaJkakYpqTtCSd0RCi0H4tCjHyZLEyVF5mWfuJfdtZ0kS/tIkXtIVXjJ0oTJ0X3l8uQZY2Trg6SrvaSrvaTJe0gR97GvxkFmdSNKrY7Gei2DXjGjPhnDbg0jHi0j3vtr1q+Kx/r63jh+OAW1FXy+DvRs7/RsDz2PqqHbqcNrpw2Gt7asDzukCehJ6FspAT0JPRV9E+gZdki3r+lxPx584seqx8Z27s7DXS7abWMdhiaDeg76DRzw6pjw6Znw6TnkVzDhUTPk0tDU2kxV3QCV9QcRtZ96wOlROOaR9p6jpuMskr555M4FdME46Kh9ayjcy2gDt9CH7mCKfoYl+hm64G2EfVeo6b2MPvYZtuEvsQ1+Tl3sJnXhJayhazSGr2ELxIuWtY45tI45dM55LJ7FjU6tBv8VGnxXqfdeweS8hKF/AaNjEZv3Gk2hFZpCK9T7b9AUWKIluIrVtYSpdwld5zXU7ZdQti4gb4uHrH0xvjFp6xwV1pMUG46SIx8juSbCvtowyaIwWcph8rTjlBrHqbUdRFg/hbz1OPqes5gdc9jcC1hdF9H3zCJvmkZQd4gq8yQ11kPUWg9tOEeFqmHyFYPkyofi4CMf2ICh+GTmANkSP7lSDwVKL8XKAAUKP8XqEMXqEDlyLxmCfjIE/eRI3BuRJXWTLXGQJXWzv8rBm1ltvJ3bzfslTj6uCZKiHKLYFoeeYusURaYJ8nQj5OgGSFeG2C92sEfQRZrCSYrcQ4rcQ4Yq+FB6ax16UpVu0mXdpAh72FfVQ2ZVHQq9isZGFcMuEeNueXyQn+f+evUpNwqXnyRGPcoda3OeFHp2XPteTdxhfcR05ifZY2trm3tiOGFC37US0JPQU9HXgZ7Nx4+CnlGP6pHQM+pRPhTrN4P111ufhLefZbI98GxAT8D4FfR4DYz59PF2Yo+aAZeGhvvQU95wEFHHSaQ9Zx+Cnur2M/dTXIvoQ2toA7fQBNZQeJbQBm+iD9/GFLv3APTU9l3BNPQllsHPMUfvYo2sYQnHt52wBi5j9S1i9lxE3z+PqncWTf95zO4F6ryXqPPG01p13kvY3JcwOC6g77uIqX/hfg3PCs3BZZqDy7SEVmiP3KLOvYrZsYaxbwVDz1V0XZfRdF1G1f1VyO0LCJpmqbCepEgzRYowvinofnGMbM0EReYjlFumENimEDceQdU+g6H3HBbnBWzuBepdCxi7Z1G0nkTcOE1N3VEE9cfj212YD1GqnaBYPUahYox85Qj5qmEKlEPxjUXvQ896R1au1EOO1Emh3Ee+3EeJJkypNkKe0k+OyEmOyEmexE2exE2+1EOO3EuO1EmuwkdqrZt383v5oMjBh6UePq4Jsl85QkndUYptRyiyHKLINBmHHu3gA9CTroyntlLkno1tJ/KMsY301jr0pKk8ZMh7SBH2kFTZTWZVHUqzjIZmGcNOCQdcCibcqgehx6vaAvQPw/3W9f5NoWendf8k0PMk6a0E9CT0/4US0JPQU9HXqenZzvl5lNOzFXzWYzvo2XpD2Dxuf30ez8OFndsDz3hAt7EFxWRQz5gvHuM+DYcCUiY8CobcSjo6mhDUR6hunEDYfgJJ9xlkvbNo3AsonReQ9Z1H3HUOaf8FVJ7LaIKr6MO30QZvovKtfAU8g59jGfwcTWANufsGav8q9aO/wzb4OYbwzfgGpu4FlI55lP2zaPrPoXfNY/QsoO47h7rvHPr+OSyui1+FcwGzYxFD94V49FzE6rwST2XdjybfEq3BVdpCa7SHb9IRuUV77A4t4Zs0h9ZoDKxgCy1TF1ql3ncLiysORuKWC1RaT1NinKZIf5gy8zGq62eQtM6i7ZxD3zWHuXcOU+9FzH0L1Luv0uC5Rr37Kpb+RfTd8e0vhA2nqLUco1g7Qb5yhALVKMXaCUp0BynSjJOrGKRAOUS+YpBMsf/+ZGYP2VIv2TIPWVI3eXI3xVo/JboAJWo/BUoveXI3OVInefJ4PU+xJkCu0k++KkSqOMAHRQ4+qvCypzbCPvkIGfpJ8uqOUWSeosRyiDzjGHnaQbK1MdIUfvbU9rC7tpN0pSs+dVkTr+fJ0UXJNUTJM8bINUTJ0gU2oGez05NVXYfOpKW1WcWoR8y4V8KE58mdne2gZzu4f7KU7/YOz5PW9DxJmutR83oSE5kT+q6UgJ6Enoq+KfSsX/g2PxUOux52e7YDn68DPY9u693+iXf8vtOzDj0jfj3jfgNjfi0H/RImvDJGPUq67I1IGkLUNI5Q23oMUecMku4zqJwXUDovIO+fQ9YbT22pvVdQB1YwRu9ijN5FG7yJKXYP69AX2Ia/xDzwGWr/Kmr/KqaBu3RM/SN1w59jCK+i8V3dKIxW9J9H2XcOrWMOde955J1nkNlPo+6exdA7h6F3bmO4oK4zvo+WsvEMyqYZlE0zaFrPom2bRd9xHlPnAubuizS4rtAeWqIjvIQ9toY9tkZHdJW28DKtkSXaIis0B2/T4LlNo/cuda6bmPuW0XdfQd2xgLJ9HrX9ItquRfSdixi6FtB3XtwIa/9V6l03aHAvYeu/jrH7Cqq2RSQN56m1nKZYe5gi7SFKDUeosp6gxnqCCtMR8lXDFGnHKNaMxvfZEnhIE7rJkfnIlnnIEMfBJl/pJk/hIl/mokDloUjjI18Zf79Q7aVEGyRXEyRHHSVVGmFXuYc9NWHSlBNkGabIsUxT1HSK8vpjVDZMU2CeoNg0Rr5xmDSFn32ifpKl/eTo/BuQU2AaosA0RJ4xFp/Tow2RqnSTLHeSLHeSLu8iVdzD/upu8gWNmK16Otq0jHkl96FH8f8b6Nmc8pr0aZ84vfWolvZHOTwJpyeh70IJ6Enoqeg/C3oeBT5PCj3b1fZ8XeiZCOoZDRiYCBgfgp7urkZkjUFqG0aoaZlG0HESUedM3JFxXkDhmEfedwG5cwGV5/JD0GOM3sUy+DnWoS82oEcTXMU29BkdU/9I/chnmCNrGEJLGAJX0XovoXJeQOOcR+2YQ9k9uwE9Cvtp1PYzKNtnkLeeRNp8ElnTSYTmIwiMRxGbphEZjyKznkBRdwpN01nUzbOom2cx2eeo779Io3ORNt8NWv1LtPqXaPZep9F3lUbvdRrcK9Q712h036LJc5sG9yr1rhWs/dcx917F0ncNS981TD1XMHVfxtx9FWPXJcw9V6h3LtHoXqHBtYy19zp6+xWkzRcRN84jrD9PhekkFabjVFlOUls/Q03dKSrMxyhUj1GsG6dIO0auPEy60Eu6yEOu3P8Q9OTKneSI+8lXuinS+CjS+ChUe+MukCFMvi5MtjZGujzGntoQKdJhcvSHybUeo7DhFGVtZ6lpmaG25SQldYcosx6gyDJGujJAitRFhspDgSmezsozxig0D1NoHibfFN97K0MdIFnuZJ+0n33SftKlnfGJzNXdFAibsNYZ6WrXMeYTMeYRfy3oeVK4/ybQs7Wo+evU9CSgJ6GnqQT0JPRU9F1Az/pFctileMjt2a6o+UkLmR/12eYOrR1reoL6DegZCxoZD+iYCoiZ9EmZ8Cnp7alH0eRD0DBAdfNRatqOI+g4iez+ZOZ1p0fmuIjCtYjCe2MDejSBNfTh2xvHulC81kd3H3rsh/5I48hnWGJrWGJrmCJLGIPX0HkvoXZdRNE/h6TtNMKW4wiajyFsmqbGeohywzg50jAp1V5SKr2klvnIF8QoFA1SJB6iRDpCmXyMWt0UAt0RBLojiHXTyA2nUBhn0Fhn0TfOY2i6gKHpAtqm82gaz6FpuoCu4yJ6+wK23qvU9V2jvv8aDY7rNDiv0uC5ToN7iQbXMg3OFZrct2h0rdLoWqXJvUajaxVb3w30HZeRN8xTaz2PuHkRScslJM3ziBpnkTSfR9JyDkH9GWrqTlFqOkSZcZIS/QQFqhi58niHWI7cT47cS7bcRZ7CRYHaTYHKQ77cGT9WeSjRBagwRaiyxKi0DpJnGCBbP0iWepRM1QSFpqOUNZ2luPEMFfY5pK6rCNvPUttyktL6KSrqDlJimyBV7iNF6iJb66fIEiVbFyZLGyLPMECBaYh80wCZmiBpSt8G8OyT9pMmsZMi6CKpspN8QSO2ehPdHXrGvELG3QImXLLHwvvXdTS/DvRshZ31c+ubQs9OAwx3GkY66pInoCehb6UE9CT0VPTss88Q6xES7RYQ7RY8AD3bDSl8HPRsdnpG3Mr7zo5q29jazv6VE7R9IfTWNNmTdG9NBvUcCuiZCMUHFx52K5j0SRn3i+nt1aNucqJoGqa6cQpRx0mE9lNIus8i7ZlD2jOHqOc8cmd8/y2N/waG8Cqm6G20gZV4jU/kFqaBuxgH7qEJrWEIr1I3fI/2yd9TN3wPY+wO5tgdzJE19IElFI55xF2nkfScRt5zFkV33OmpsB4mvcbJnoIm3tyr5lfvVvLim4W8/EE57ydZ+DSzgfQSD6llUdIrBsgVD1MgH6VYNUqJ8BBVkmmqpUeolk0j0ZxCojmFXDuDTn8WheYESn0ciJSWGVSWWVTWs6hts2jqzqKsO42m8Rzm1ouY2hew2C9hsl/C0L6ArvUCutYLaJrnkFpnqNEeo0p9lBrDCUTWM4jrTiOwzVBzP61VXXeCKvMxqk1HqTJPUK4bokIzRJk6Rpk6RpEyQrbMR44qvslnjsJFodJFkcpNvtpHviLe2VWk9lNpiiGwjSFunqK4fpJi2yS5hgMUWU9Q0zaHtPsqgs4FRH2X0fiXqe04T1XzaYptBym2jlNiGiJF7CBV4iRD4SdbP0iaOkiqMkS6OkK2NkaOboBsTZBMtZd0uYM0qYN0ST9pkk6SKjtJquymVGSjrUFDwGFm0Clh0CVi1CPZcV1vXb9P5mhuP3hwp/b0dbjfDP1fNQp8NSdr3K1izKXcNjZ/Zz3WPxt1Khh1Kh76N+szuEY9qgT0JPStlICehJ6KtoOerbspbwad9fe2DijcWsi8NTa7QN8V9Dyqk2Uz9Bz06zY6vg665RzwShj3Se9DTx/ypkFqG6cQ20/dr+s5i6T7PJLu84h751A4LyFzXkIbWMIYWUMfWkPjX0YbWsMQvY1l6DMsw1+gi9zCHLtFw+jndBz8A7aRLzAN3MUUu4cpehtDcBl5/xxC+ynE3TMo+2cxuC+i7Z+nWDfOO6kWXnq/hh+9sp+/+MmbfP+5V/jBT17juV8l89ouCUk5XewvDrG/JExqdZTk2jDpwjDZ1WMUCg5SJBinTDJFrXyaWvk0Ytk0as0MCuUJFJoTqIwzKI0nkGiPIzWcRGo4iUR/DIH6MALdURTmU2jqzqKtn0XTeA6F7TRS80mk5pNITCeo1R6hUjFFuewgleopqvXTVOmOUqE5TKn6IKWayXhoJyjVjFGmHaRIHqBIHqBYEaRIHqBA6iNL4iFL6SNN4SdH5aZA4SRf7iBLFk935cpcZEsclOmi1FpHkbdPU9l6lPLGw+SbDlLZPIuk+xIqxzLSvqtInddQeW8gsM9R2TRDkXWSQvMoBbooyaJ+0mVuMpUBsvWDZGiipKnCZGiiZGtj8dAEydL4yFA4SZP1ky7pJ1XUxd4KO3sruigRWehs0hF2WBhySRl2yxj1Kh4AnEcV8X/X0LMZeLZCz/p5sg40myFmO4DZCjtPCj1jXnUCehL6VkpAT0JPRTtBz2bA2e54u+0ovi70bL6QP9jS/mjo2QpN26W31uOgX8dBn5aJ+7UVE0454x4pIz4Jzl4dxqZutM0RBM2HkHbPIO2eQdx1GnH3WcTdZ5H0XkDtuYrCfQW1bwlD+CaG8M14+3poDV34JobobQyxO2hCa5iiN7EN3aVl4gvqx3+PdeRLzINfYIrdQxe+idKxsAE9Os8cTbFlGsJLlOnH+PlbVfzgR7v5s++/yP/8wfN8/y//nj/7qx/yl3/3Cs+9uI/duY3kSUbIFI/wUWmQVwu6eKe0n0+qguyuCvNxeYCPi3zsKQ6yrzhESmmErIphsiqGya8apLh2iDLxCOXSMcol41RIJygWjJJdPkBW5SAFtSMUVg9QXD1AYWWEgorwA5Fd7COvLEheWZCc8gD5VWFyK+KvM8rcpJc6ySx3k1nlJaPSRXpVPyklHewvaiOlsIPUIjspxZ0kV3aTJoxPPE6X9JMu6iJd1EWu3EmR0kuxykeu1EOpNkKNZQRx6zQC+wxVLScpthxDaL+Iov8aeu8tlK4lpM5riPsWkfQsUNk0Q6HlALn6QbKVAZJF/WSr/ORowuQYhsgxDJGlGyBTGyNbG4m3rqsDZKq9ZCicpIp7SBF1kyboYk9ZHHrKJSZ6WzQMOK2MOGUMuuUMex90MdfX+GaHc319fpfQs91635ru2nyebD73doqt6eit5+tO87cS0JPQt1ECehJ6KtoMPbEe4UP1POuvN7esbv78gZbWHS6U211kt3N6tkLP1u/sBD1bbwibO1kOeDUc9KgZcSsY8igYc8njRah+OX6njrrWDozNPsStk4jsxxDZTyCwn0DUOYO45wzi3nPx7ivfVRTua2j8yxjCNzHH7qAL30QTXEUbWkMTWkMXjUOPeeAmLRNf0HjgD9SP/x7L8BcYorfRBFdROOaR9Z1F7jiD3jtPY3SJloE1VF1n+TS3kRffreDP/+5d/sdfvcyf/dXP+K9/+b/5m+d/zcvvp5NW3YCw9RDi7hmq2k+S23CQ/MbD5DZMkqSJsksU4D2Bm12iILtEQd6rCvBKoYPXi1x8WOxkd0kfu0t6+Di/i/ez2vkgu4P3szr5MLuHD3J7+Si3h08y7Hya1cHuzA725naRlNfNnpxO9uR0siuthY8z2vgovYUPUxo34t19Ft7ea+TtvUbeSjLwxqcm3tht4I29Jt7ea+SdvXo+2KPnk30Gdieb+CTdzCdZZj7JM5Nc2UqKsJNUUReZkh6yJH1kintJE/VQoPFTZo5R2zJFjX0GQccZKptmkPVeQetZwRy8h8a7itx9A1HvApKeBaqaT1NknSRHN0CuOkSqxEmuJkiuNkKBZYx88yh5phFyjAPk6KJkacJkaXxkKT2kyftIFnaxX9BJWk0Hu8tb2VvZTrzvWEMAACAASURBVKVUT1+7kkGPiRGnjJhLweA2Ls92TuZ37fQ86rzZeS6W6pEPJNs5VgnoSeg/WwnoSeip6HHQs91wwp2mNQ855dteLB8FPY+Cms1u0OPSX1t/z7hPw6RPG98jya1iyPMV9BzwKjngVxFy6WlsbcPc4kHccgBhxzSC9qMI2o9tdHKJes+i9l5C5buK1LGIynsDXXAVc+wO+sitDbdHE1rDMHALU2wNY3SVlokvaDn4JxoP/AHL8Bfx796v6VE4zqFyn8PgW6Ahtkzr8G0s3mvky4Lsyjbz41cy+PO/eYs/+1+/4L//r7/hh8+/zC8/SCZb0oii9wjawCzqwDzV3acQ9J6lqu8EuU3jpBiGSDEMkmmbIMs2yT7tMK9V+3hXFCZFFiVbGiRD7GVPRT/v57fzfn47b2e18nZOO+/m2fkwz84Hma18mNHCB+nNfJjdwvuZTbyx38KbyVZe32fm9SQrb+yz8foeI7/5SMNrn+h47VMtr+/W8dqnGn65S8qL74r5xTsifvG+hJc/lPDrDyS8tUvE27uEvPOxkPd2C3lvr5D3k0V8WmAkqaaFZIGdDHE3qaIukgV29gs6yVV7KDSGqG6epLrjFDVtM1S3nEHlvIExcAtr+HO0vvhsJKnjMpKeBapbzlBoOUCOboAcVZBUiZN8XZg8XZRC6zgF5nHyzaNfQY82RLbKS6bCTZqkh/2CTvbV2smobWN3eQt7K9uokuvp61Aw6DUy4pISdcoZ9CofAoWvl97afobV42K78+ZJoOdR4JOAnoSehhLQk9BT0Xr31nrEeoRPBD3bwdGQU/5Y8HncAMMnKXTeevF/VEx41Ey4NPGUhFvGmEvJQY+aKa+SiFtDe5uVuqZ2xG2jSDqmELQfpKZtitqO4xuOj9I1j8q7gMRxEZn7GrrgMubYLQyxm+ija+giqxgHb2MeuYN16DbmgZu0HviS1sN/ouXQP2AZ/hxNaBm17zoK9wW03osY/YsYA1ewha/TMnSLzrF7NPguo2iZJq2shRd/U8pPfpHOX//41/z537zI37+xl1SRDZnjAMaBM1hGF1AG51EEL9I2cQVD+DQS90lk7hPooxcxRC+h8M9T0HKEsq4TaEMXaYosYAucQ9F3nMqmMQosMfYI+9grcZEi95CmDrJX4uVToYsPq7p4r6SN13Pr+dFHEn6epObVbBuvZNXxSlYdL+7T8KMPRTy/W8Er+zW8lmni12l6/v7DGn74VjF/82YxP36rgJ+8ms1zL6fz3M9389zzH/Pjn3/ET1/axQuvfMJLr3/CS+8W80a6mg+KzGSIO0kX95Ii6iZJ0Emmwk2OLkBl8ySiztPUtJ1G3L2ANXKPxsHf0zD0B/SBW2i8qyjdN5D0XqC2/TRF5nGy1SGyFW6y5C7ydWHy9THyTCMUW8cpsoyRZxgiXx+L1/LIXWTI+kkRdrKvpp2k6jYyaltJqmwiqaYFgUaHp0vGgFvNqEfCoFPFoHNn2HnSeNzafdS6387Z3C79td15tVMN0pPCUQJ6EvoulICehJ6K1qEn0lX7gNuzNbYWMm9b5HwfetbB50mh58Gn4u8OekY993d8d2kZ8MoZ8EnjnS1uFZNuJYNOFX0dJpoam5G1DiO1H0bSMYXYfhRh13GEnfFuLqVrHo13Abn7EmrfErrgMqboTQyxeJgGb2Majodl8BaWwVu0H/yS5kN/oHHyd5gG76EJLaPyXUXlvoDaPY/GcwGddxFz6Bp1sRWaBtZoH7xJU/Aaivopskp62JNi5oVXM/nJy6n89J1c3svXUN4UQ+s/hXVoAbX/LKbYAv1Ty3SMXqIuMocleAb75BI9UzfpnFrDHL5A08g13KfuEj51l/Dpz4ie+xLPsVv0HryBovcIst4jWIKz1A0uovCdReQ6RUXXYbLqR/hI7uLnOWbeqOogzTJAiiHIXqWLV4vr+U2BhfeqWtkj7WWPuJsPK5r4ZYqcnyUJeHGfgF/uLuVvX/6UH/z4bf77X/yS//K9n/Ffvvcz/sdf/oL/+b9f4vvP/Yrv/egjfvR2Ka+lqMiTeSnWhyi+P5en0DRAiXWYmo6jiLvPIrTPonZfp2X0D7SP/x+aRv60AT0a/zLCrvNUtZyk0DxKhsJPpsxJtsJNoSFMgTFGjmGIfOMgeYYhcjRhsjVB0pVu0qV9pEl6SRbYSapuY391ywb07K9pRqTT4e2R3k9pSRhyqRl2qLetifkuoedRTs9ORfyb398uXbwd3Gz+ex4FPgnoSei7VAJ6EnoqevbZZ4h01W7E5rb1rdCzFXi2Qs+gQ/YQ9Gz++Sjo2emm8E2hZyM95tYw4dIy6FMw4JMy7FEx7ooXNA+7FLjsBtqa65E3DyHtnEJqP4y06xjS7pOIuk8g7DyJwnketeciau8VtIEl9OFljNFV9NFVDLE1TIO3MA3fxjh0C/PATSxDa7Qf/JKmg7+n4cBvMQ3diTs9/mtovAsPQk/4BpbIEpbwDZpjqzRHljF0zVImHSCruJdXP5Dw0rtV/PITIa+na8nVBxD3HEbjnUHpOkld9CKuwzfpnbxOS+wi9eFZ+qeW8Ry7he/EHbrHr+M8skrs3OcMnr5N9MwdRi/8lsFznxM9c5em6DmaBs7Te/AKfdNr1I1cwTi4gDI8S1XvEbLqYrxT206S1kNZ50EKW8fIrIvwnqiDXeJOUg0+cutCZBk8JEnsvJaj5vU8FW/mKXktpYK//dWH/MXfv8Z/+4tf8F+//zz/7c9/zvd/+Arf/9vf8L2/f5U//+kenn+vijfTdOTLglRaR6i0jlBsHqasfoKq5kNIek4j64t30xmDa7RP/AMdE/9E4/Af0flvovasoPEvU9NxlvLGY/FJzDIvGVIHOSo3xaYoBcYY2YYYufpYPK2lCpKh9JEu+6p4OVlgZ391y1fQU9VIsqAJqUGHr1fKsFcZL4J/Quh53Dr/JsDzqAL+7YqbHwc9Oz10JKAnof9sJaAnoaeidegJd9Y8Enq2xnbQM9D/Ffhs1x2yXY3Ao24MTwI9O3026lEx4lIz5lIz1h93eiJeCYMeFWMOFWP9UsbdCsJ9OnrarciaIog7DiKxH0LeewxpzwkEXdNUtR1G0nsKWf8sKs8i2sAShsgKxugq2vAy2vAyhtgahsGbGAZvYhpYwTK0RuuBz6k/8AW2sc8xDd3BEFtDH15G7Yk7PTrfAtboMnUDq9hiK5hC16mPrNIYXsPaex2x8RjlknGSsv28vreV1/a28npKK/tqPWTJg3xU1kaKoAtN5yRdY0t0TazQEJ5D238M++girqklBs/exX/4KtFTqxy69AXTC/c4svA5R698wdHLv+Xo5d8SnL5KbGaNAxc+Y3juCxxHluk7skzXwWvYRxepC55G2jGGyXOc5th5dJ5jSHsPkm8LUNkaQ+M+jNo1haA1SonRSUptA1mSZjKFjbyXWsXf/WIXf/vTD/jJL/by/EvJvPCrVF55u5hfv1/Jq58IeX+/geSSDnKELkS2KSTN04iap6luPIyocwZF/xw6/yW03kto/ddoHv0t9sn/Q9vYP2KL/Ratby3eweW4TGnTMYpsB8nSREmWOEmT9JKn8VJqjVFojpKpD5OhDpCu8pMqc5Mq6SdV3EOysIsUYWe8oFrQTkptG1mCNpKrG0gRNqGw6Ag6JAz7ZEz4pIw4NQz1ax5K5e6YPnJrto0xj3Yjdlr/O4HK5hTYdttR7NQY8DgAe1SaKwE9CX2XSkBPQk9Fzz77DOHOmo2IdNUy0Ct6KB4FPeuFzOvQM+j4qpNryCl/ZOfIdwU9mz/f+H1uDWNODSM9GgY9EqIeMYMeFeP9SsZ7pYy75Qw61TjsRkT1foQtYwjaxpF2H0HcdYyatinKGw5Qa59G0HUcuWsele8q2uANDJEVtOFlNKEl9NFV9ANrGIfWsAytYRu5RdPYXaxj9zCP3ME0dCfuBsXW0PsXUbnm0PkWsESWqIutYIksofVewuS9jtW7jLV3CVXTLBLDGQqrjvNpboy9+SN8UhAhpTZKSq2f19MsvJumJUdo5+Oqbt4sa+NX2Xp+tkdMqqSTqoYQbUNn8RxeIHTqBlOX7nLiwm1OLt7j7I3fceLyF5y88iXDp5aYunCPmRt/4sji74keX2Pw+E1CkzfwTF6hf/QibaEZ+kcv0jdygfbAaWzOw0hbBrA4pugaOEezdxpVSwyhyU2JtI0KeQcV0nb2ZSp46Te5vPx6ER9+JGHXJ0re+0jBJ/tt7M2xk17WT4VsGJl1Enn9JOq2U6jtZ1B1nUViP42i/yI671XM4RsYwzeoG7pN9+F/ovPgP9Ey8ifM4c/ReFeR9l2l2j5LgW2KfPMEaYog+8UO0iS95Gt9lNqiFJojZOqDpCq8JMvcpIgdJNV2sV9gJ/l+pAk7SBN2kCpoJ1vUSkpNIymiRpQ2HSGXhGG/lAm/OA49fdongp5hl+IbQ8928ahZVzsVOG/n7DwJ9DwEbwnoSeg7VAJ6EnoqevaZZwh2VBHsqCJkrybSVfvAlhTrEesWMdAjZqBHzGCvhKE+6UOxDjxb01xb3Z51GNop5fWoWoaNY7eGEY+WEY+WUa+OUa+OEY+WYbeGYbcmXnfhVD3wf239m8ZcaoYcSoI9GkyNHSjawkjbRqhqm6bGfoSq9oOI2kaRtB1DZj+NpG8eqfcCisAldLFVtJFV1MFVtOEVTNGbWAduYhu8Rf3wHeqG71E/eg/b8B3Mg6uYB1cwD66gC15B7ppH47uMbeA21ugdLJHbWIJrceBx38DacxlN2zyy+nOUyo6RWXaQjPIDZJROklt1hKyKKXbnDfBetp/dZTFeTmrkuTeF/O0bNfz1b0r4MNdMRrWdWtswuu5jtIUv4J9aIXDwGsGpa3gPLBM4tIZn4jr26FmiJ1Y4vPgF09f/RPD4CpFTNwkeW8U5dZWe0YvYB+dxjl/FPbFES+AMmq5xBK1+6sJHsE+cpy18ElFdgCJlF3tLTKTV1JFe3czHKTbe2qXn7U+0vL+ngbd3W3lnj429uV3k1QQplQ8jqjuGvHUGVcdZNB2zyOynkXbMIOk4iab/PCbvAvXRJWzRNZpGP6fr8D/QNvEHGoe/xBi+jcK9jKjvOuVt5yisG6HAGiVF5WNfjYN9Qge52gillgGKzRGy1R6y1C6yFA721drZW91OUk0HyQI7KcLOeHqrNn68t6aT9Np6iqQ6WlqkxCcwS+LzqFxqRpyax86/2S799aiU1U7gsRlAhlzq+Nq+v86HN50H67H5s/VzYfO/2/ieR8WwR8WQW7kRgy4Fgy7FA+9tF8OexETmhL6dEtCT0FPRs888g7+tgkB75QPgs3k/rliPkGiXkFj3V/Az2Ct5KAb6pRuxE/xsLnbeHDvdGHZ86t0GejaDz9B9oNlcU/QQ9LgVDDslxBwyWttsmDp9qOwxStoPUdF5kJqug0jaDyBoPoSwdRphzxlErvMb0KMJr6AKLqEOLmEKr1IXu4klsoQ1soo1dou6odvUDd3GNriGZWAZy8Ay+tBVlO4FNL6rWKN3sEVuYw3fwupfxeZZwuq4hqFrAZ39Apq2eQSGM5TJj1Nce4KiqlOU1pyjpPY8BbXnSK88SUrFEd5K7udHryr4qxeq+MHPCnn+jRp+87Gc9zPq2JXVwf4SJ/nSYUpUExTIRkir9pNU6mR3US+78tvIUwQQtgyjd06j6ZlG1XUUUcMYRbogWTIn+QoPVaYItdYB8iS97Mo38m62mkpLCFXnIXR9x8lVethbYeedLBsfFbTzSV4nn2T0sT/fy75CD3vyHXya72BvsYs86TDV1mNImmeQdcwi7ZpD3juPsnce2X2XR9RxEmXfOXSeC9iiSzQN36XtwO+wH/ojDaNfYhm4i8q3gtR5jdreRQoaTlBgiZFrCpIkc5EidJMsdlFgGIjX9BiC5Ol95Gk8ZMr7SappZ09FK0lV7RuprX017eyraWd/bQd7BF1kCW1UKXT0tksZcYsZcYsZcsriML2ppufrwM9OrspOMLTVcdkKPVtBf8ilZtCpegB01t/bCkmboWcddrbGo8AnAT0JfRsloCehp6Jnn3kGb0vZQ+CznuraKHC+Dz07Ac+3hZ7H1UU8FFueWrfGZuhZTwts/VuGnSoGHTJGHHLcHXpaO/ox2wNUtB2ion2a6vYjCFoOUN4wQnnDCLVd04gcs0hd8ygDV5B6riB2XULiuoTaewXL/U1FTaHrmCIr912fWzSMxMHHOrCKPngtXhDtv4YpdAtzcA1TYBWLbwWr+waW/quYei9j6F5E33kRed0ZRLqTiBSnEEhnqBGdpUJ0jjLReXJqZ8iuOUFO9RTvJXfx4lsG/vrnpfz4lTJe/UhKSlkH+yrbSKrqYFdpJx+W9vFBcR+vp/Xw0u4WXvi4kR+/b+aFT228kGTl1dQW3svu5p20Dt5IauGXnxh54QM1P3pLwM/eEfPKHhW/+kjGj9+o5i9/Xsxb+xvYV+ygTD5GbnWU9NIAyQU+UgoCJOf7ScnzkVUaJrsiRm7tIIWSEYrk41TopxDYppE0nUBQfxxR6yxS+zlU3XMoe8+j7D2PoncWVf95dJ4LWCM3aJv8LZ2H/0jHofieZobwKjLnJWq7zlPZfoYc0wGytT4y1C52C3pJk7jJUYYpsw5TYAiSq/NSbPKTo7q/r1Z1G0nVbaSLusiQ9pIm7t4AnmSBnaSadgolRmQaNZ7OuNMz7JYx4JQz7FQxet9FfJLYbo1v7WzctiZtm3W/k7uzncPzSJfHrXki6HkU+CSgJ6FvowT0JPRUtBl61sEnZK9+CHz+M6DnUWmwxxU+7wQ926W3dnJ6hh1qBvsVjDiUBDs12O12GuwuBC0HqGydpqplmqqWg5TVD1FcP0CNfQqx4zRSx3lk3kVEzkUE/RcRORZQui/FYed+GMPLWGIr1A3dpGHkNtaBVSyxFXTh62iDN9CHVjBF7sTBJ3ATo3cFk/MGpv5rGPouo+9aQN95EXXzOWTm00i1M4iVM4hkswhl56iWnSe/5jg5NcfIrTnMp5le3vykjZ+8IuHnb9by9j4teVInRWo/Beog6bIgqeIB9tdG2V0R5O3sft7M7OXXKW28vL+ZF/c18nJSI28mt/F6Uhtv7mvntaQGXvnUys/elvHTt6S8tEvFrz/W84t3lPzdSxLe+LiZPdlOCqtHyCoeIL0gQkZBjIyCGOkFEdLyfWSW+smuDJNfO0iRdJRSxTgV+kmqzYeptU1RY5tG0jqLvGMOVfccip5zcfDpO4faMXff6Vmm49Dv6TryJ+yTv8M2eAtDaAlJ3zzVHacpbzlBpn6EdKWLVFkvn9b2kKnwUqAdoMw6TJ7OT67aTZHRR5ail2RhO/uqmtlX1UyGuJtsWQ8Z4k72V7eQXNNKqqCd5JpWyuQGVAY13i7ZA9Az5IjvTbUTwD8O7Lcb5bBTOmvrefB1oWdrbAc93wR4EtCT0LdVAnoSeip69pln8LWWb0CPv63iAbdnPaJdwseCT6zvq9gJftZfDzpkD3znISDZoS5iM/RsBzqbY8SlfuDG8fD/ISfmlDLkkhLrkePoMdPR2YKsPkxV4yTlzYepbDtMWesoJU1RqtsnkPbNIHHMovAuInYu3Ieeiyg8lzGErmOK3sAcXUYfXsY8uIp1+CZ1o7exDK1hHlzFFFvDNnyH+pHPqB/+EuvAZ5ijdzH+X/buIzbufDv0fF/gbWy8txjYi5nNPAN+A3sxgOe5g9QSRUmkJOZYOeecc7GKFchizmQVo6icJYqUREpUzjm0+tr3zmy8NGDAgJc2DMPAdxYlVpfYJMVuXVuLVwc4EFn1q7Aoih+ec36///BTXH0Pcfc+wNNzH0cqjx5PYhVH+Bp23w2MlqvojdfQG5bRGpcRai7QorpEk3yBevFpDjbNs7Oyl/+nzM+OgyGqVD1IPIOoIpP4syskjz0nOvUAc2YJgecoLc6jNFgPU2Ocpso0RavjCELbEWo1WfYIetkvGqJSOMTu+m52HEzx9f44f703wbf7M+yvzVFRN0l1yxxVrfNUNsxR2TDHgcZ5qltOcLBpnoMt41RJJqiS5ajTzNBomKPBdJgW+zwCz1EEnqNIAhfQJFbQpa9j/NDeMnRcwdC5hK3vOu6RW4RnnpM69bd0nPk98SNvcI8+xNJ3C2XiEuLIGQTBkxyyTbJf00m5KkmZqotGxwStrlmEvhnqrYPUmHppdPZTqUlQLg1TLomwXx6j1pChWtfBQXWSckkkfzaPPEaNMoLa6sHjtzHaZSZ/Po+eyR4T0z0mDvf+MvBshp71Q8KboaiA93XgKW7rbgc/xWvWz/FsFzsl9JTiDxEl9JTii0TxTM/69tb6Ss9W6JnKaMl1aX8Gn+Lh5vW5vjK0nV8aa1gp/qt3PXZmBswfzTXM9v8ErvWvM91rYKZHx3yvjrGMjcEOL75YF+rILMroCaTtp5G2zSEKTaBsn0XbdR5DzyK20VsYh2+jHVjFOHwby/hdHNl7uCfz/9qy9/FOPyEw95zwkdeE598SnHudH3Ce/5HQ4d/in/2RwPQ7vLnXOIaf4Oh/mM+e+1g6VrGmb+BMr2KPr2APrmByXsVouYbOfBWVbgmx5gKt6rM0Ky7TIDpPrfAk1Y2z7K3uo7wmQ3lTmgOqburNgwSGFuk9do+eo3fJLbwmd+kNkwtvmTj/hu7DD+icvEPX/EOiuRu4+i+hDM/RbJmkQT9JpWCE8tohdh0YYG/1OAcaczRJD9MomaNeNEN1yyS1gmnqhDPUtE5R2zpDvWiWKuEEdbIsDeppmgxztJjnaDbP0WiZpdlxhFb3EaSh82iT1zF23sKYuYEmeRV1cglNehFL33VcI3eIzr0kceK3JE78luDUU2wDq+gzV5BFz9Dim6fZNUu1aYDdihRlyhSHjL0I3FmEvhla3Nk8eszdVJnS7JNHKRMHqZBHOaiKU61PU61NckAZY48owF5JiAp5lEaVF6fLQTxqJ9tjZvZDpSfba2Kq28hsj6GQW33Gi3cybrZ7ajMIbQT/9XgpBs96EK3/+VgPoF+LnRJ6SvGHiBJ6SvFF4jdfffUReMaSsp9tYd8IPcU7uda+znX9lJtVfLZCz0a5FXqKhzSLcyP0rH/OtcrPVGHrvZrJLgNjGRvxRBJzWw5dbB5J7AySyBwi/zjyyBTa9Cm0XRexDOexoxtYxTB0C/PYbWzjd3BM3MI2fgd77j6+2SeE5l8SOfqGyJF3hObeEpx9g3/2Hf6ZHwpXX3dPvMQ+9LiAHmfvA6ydN7F1rOJI3cTStoI1eAOzewWjbQWdaRmFbrGAnlbVZRol5z6g5zAHasc5UD/Knrpuylo7qZT34UidJz15na6ZVUbPPmR26Q1zV94ydek13XO36J5apWv+NvHZGwTGljCmT6IMnEDsOMohUZb99WPsrZ6gpnWeetFRmmXzNEpnqBVlOdQ0Qa1g6gOActS0TlIrzFElGqNGnkdPq/kIrZbDNJvnaDDPFNAjCZ5DnVjBUIQeVfvP0RM/9o7Y0bd4sw8w9SyjTi0gCh2n2T1NgyPHQX0vu+QJ9qjS1FgGEHknEXgnaXGOU2cZoNrURaWuPV/lEQc5oIxRpUlQpUtxSN1OhTxKmdBPuTjIPmmYZo2HgNdBZ9zJVK+Z2QEDs/3G/zT0bFbt3E57a7Ph5p/dtgV6ind1bdb6KqGnFJ8TJfSU4otE8Zb14q3rP6v2pFUbomctJzs1vwo9G7XENpsNKkbPbL+pgJypXvPH2Wdkqtf8E4L6Nq4qTfcamOzW5rNXxWS3lly3kd6MD3e8H0Mshzx2BkXoCFLPJGLPOPLwDJLoMTSZS2h7l1H1XkPTv4J+6AaGoWX0Q1cxDC1jnbiLZ/YJ/vkXBI+8Jjj/Dv/cG1y5l1hHnmIZfYoj+xL7xAtso88wDzzEMfAI5+BjPANPsGbuYO64hbH9BprIMjrfCibfLczOW+gtN5BqFhFrFxHplpCaF2lVnaNBcpomwWkamk/Q2HKSAw3T7Dg0yM7qQeqkU4gM08itMzjbzxEfvE770A3a+pdxJc7jjF/AFr+IKX4JbeQcQsdhGvWzNGhnqZPO0yQ9Qav8HHLtZeS6i4g0x2iST1EtGKWiYZBqwSh14gmqBaPUiEapFY99VOUR2Y8icZ1A4j5Os+MILa55hN5jSMKXULdfR5deRZe+jqp9CVX7ErqOa9gHb+EZu09o+hmh2RcEZ55jHVxFkzqPNHqCZs8UDdZh6iwDVKg7KFO0U65J0+AYQeybQuybotE2Qo2plypDJ3vkIfZKAlTIw9TpEjQYUlRp4hyQh9kvCbBX5GOf2M8+sR+J1kYybGMgZWOmz8B0n46Zvo8rPWtHNWz0uS3OTVu0G83srBuALm7LrkF/I/hs1s7a6I+CtT8INkPPdgecS+gpxedECT2l+CKxvr1V3OL6aKC5CD2bwSeb+Tl8tvplUAye9fDZCE0/VXzyvwymes1M9piY7DGR6zYWcrLX8BF6pns/fs2155vq0Rfe61iXlokeNVO9Wka7jITa27C19aONH8cUPYUhcAKZawpJYBJJ5DCq9Hk0vVfR9F5FO7CCbmgZ7dBVVL0LKHoX0A0tY/lQ8XFNPcE/l6/weCbfYBt/ns/sSxwTr7CNvcA8+ATn8DM8w8/xjbzA1nsfU+Y26tgNpMGrqH3XMfnvYvbex+i4g9ywjNRwHYX5BirXFbTOa2jtq2iMy0hlS0ikV2gSXqCy9hgH6o6zr/Yo5XVz7KqdprJ1joOSGQ5Jp6lRzNGgOU6d+gQ10uP5M4EEJzjYepRDgiPUSk4gMVxCY72K2rqI0ngRpekCCtMZGiXTVLeMU1E3SHXLGPWiHE2ySRpkWRrlOVo0c9RrZqjTTtNiOYzYeRyR+zhC7zGE/hOIg6dQxJbQJG6gSdxAFl1CEllAHr+MsfsGrtH8wYSBySd4so9wTdzH0HMVWewEmaXT1AAAIABJREFUwsAcdbah/M4rXZpyWZy9yjj7NEnqHUMIP6Cn4cOaSk2C3TI/FfIwNZo4LeZOWsydVKtjPwPPXpEPldFCps3CcIftw+dHx3SvnlyfmameD5dk2SZ6Nob7z3Gz0Y6v9ZXOzVpV69tY66ugxX8UFH4uthhe3s6Qcwk9pficKKGnFF8k1tCzfq5nPXyyaVUBPFuhZy3XV3zWw2aj2ze6bzvoKQbPGnome0w//Wffo9sQUpPdOnIZPbmMnrEuPbkeJdO9Sia6NUTjfpzRTvRtx7C2ncYSPo3CPYsoOIksfBhVxznUPVfQ9F5FN3gd3cgKuuFrqHoXkPdcQjVwBePoDcxjt3HkHhXQ45t+hzP3Ctfka+y5Vzizr7GPv8Qy9BTXyHM8Yy/xj77E3vcAc+Yu6tgNJGvoCd7D6nuE0XUPpek6CvNNVLY7aL3XsARvYg89wBN8gt5wC7VmFYFkiarGM9Q0n+NAwzn2Npzl+9oT7G6YY2d9lu+bxilrzVEhPsIB6TH2txylouEYlQ0nqG4+RbXgFHWSM8hNS+id19DYF9HaLqO1XUZjuUiDaIaqpgkq64eoaR2nQTxJq3KGVtU0LappRIaj+UqRdppm8xxCxxGErmMIvccQB08hCZ1GGb+CJnEDdft1JOHLiMOXkMUWMPWs4h67jy/7iMDkE9wTD3GM3UXXtYQseoxW/xQ1lgEO6tIcVCcpk0YK6KmzDyLyTxfQc0iXoULdzi6pj0pFhFptewE9Vao29ov97BV62S/2F77Wmqx0xayMZKxF6DH8KvRsNLO2FXo22t241ib7Q6CnAJ8SekrxBaOEnlJ8kfjNV18x1C4t5HBCxkhSzmhKwUhSXsjxtIbxtIaJDi0THVqynTqynbqPv87oC5ntMhRyIqNnvFP3syxev9ljs12GnzCzAXB+aRY/b/H7yHUbmenVMtOtYapbTl/GSCrlwdfehT56GGXkFALfHILANK2BOYSheeTtx1GmT6PJnEPTfR5t3zX0Q6uo+pbRDi9jGLmFaewO9twTPDOv8M6+xj/3A8HD7/HPvsM7+Sp/tfaJp7jHnhGYfE0w+xrX0BMcA4+w9t5Hm7iBOr6CJn4TTfQm6sAq2uAdjKH76H23MXjvYvHdxx17TCD1jM6RH0n0PcXXfhOl8SIC2VlaxedoFp6hWXyCFslJGsTHC1krOEKD+Dgt0hO0iM8gkFxEILmIUHaeVukZWiQnUejOo7UsYPYs4Q2vEmy7j917i3rhHIeaslTUjVAjnKBBmkOkn0PhOI7CeQyhdRqhYwaRew6haxqBc4YWxyyt7iOIAqeRhy4jj15FFruGtO0qkvBlBKFLiCILaDuWcQ3fxzv2CNfYYwx9d9H13ESZvIA4OE2re4xD+jR75CG+F/v4XuyjUpek2tJDo3ucRm+OBtc4NZYB9ira2CP2sk/koFwRZp82QZUhTo0uQqU0yD5xG7uEUXYLg+xvtXBQYCIZ0DCc1jLaZWZ+4Cdgr30eJ3tMPwP6+h2JhTbu+vbrBrlRC2qrdT8b3t/gMMKNKjxr90/2W7aVUwNWpgby63N95kJO9pdOZC7F50UJPaX4IvEp9Kx9P5ZSF+BTjJ/irzdDzHinjrEObSG3Qk8xlIq/Xw+W9SD6JeApfl9rme0yMtmtzV92o1vOcJeank4zbe0xbG0DGCMTqMJTCAJTtPhyNHpzyOLH0HWcwdx1Dn3XebS9i2gHb6AZuI5m4Cq6oVUMI7cwj93DMfkU19QL/IffEjryA/65N7inXuCafI47+wzf1Guic++JzL7HO/ESz8gzPCPPsPY8yFdCYjdQRFZQB2+gDd3CGL6HKXgPS+gR7thLgsk3RDrfkpn4ke7sOxKDz7GHbqGzrKDSXUOmWkShW0ChW0CsvIBQfg6h/BwtktOIFOeRqC4i115GY7iGWn8FreEyKt15lLqzGGwXsfuuEIhepy15h3D7PfTWqzQI5qlunKZRMker5ghC/RFEhiNILccQWeZpNU/SaptC4JxB7JlF6DmM0D1Pq/cY4uAZpOHLSEKLCEOXEYYu0xq8SGvwIuLoIqaem3jHHuGfeIJj5CHqzHWU6SuIw8dosA19OFW5jTJZkN2yIHuVEWqt3dQ7Bqj3jFPrnqDeOUaFrpPdYh9lAhcVwjx69qpi7JX52Cdx5as7khh7xFHKWt3UiI0IlCZ627WMdxsY7zFzuN9YgEPx52iz1uyvQc92cyMcrUfQZnAqXrcGmRJ6SvGlooSeUnyR2Ag9oynFzyo9Yyn1R1kMoDX4bIaZ7aJnI9R8Cj3bhdD6ytNERs94RvPhvegZyxiY6NKSzaiZ7JIx1qVkqNNIKhHC25bBGRnEEM0hCkzR7BmjwTWGODqPJnUSU9cZdF1nUXcvoO5fyWffNbRD19ENrWIavYs99wTn1DN8s68JHH6Lb/Y17qkXOHPPcOae4Z9+Q9vhH4nO/Ygv+wr32HN8Yy+w9z1Ck7iBKn4DVdsNNNGbGNruYIreRR+8gyl4D2fbC7yJV/hTb0gM/EDn+I8kh37AF3uCxXEXg+U2Ss0KSt0VFNolRPILCGXnEUjP0SI+g0h+AZlmAZn6MirdElrDInrTEkbbIkbbIp7ACqHYLSLtt4il7hKM3UFruYJAfooWyXFEulPIzKeRWU4iMh9DaDpCq3GWJnOOFuskrY5JhK5pRN55hL6jCP0nkITOIgktFNAjCC7QErhAs/88osgCpp6buEce4PlwJk/+EMLzNPtmqDb2UqnpoEwapkwWZI8izH5NO3XWXurs/dQ7R6l1jlFjG6ZclWS32MceoZtDUg/lijB7FFHKxG7KRQ72i/1USOPsFUUpb3XQIjegNJgZTOvJ9pqY6LVsiZ7tDO7/Z6CnMJz8iSrRL0HPGng2W1tCTyk+J0roKcUXic3QM5ZWFvAzmlIwmlR9lBsiaJP21a9Bz1YI2g6SPvXYYvSMduoZ7jQy/mEeaSqjYrJLRS6jp7/DTjoZJN4ewx/vRh0cRuQZpsk9SmtoGlnbPPqO4+g7TiLvOIe4YwFpZhFF9xLqD+0uy9g9HNknuCaf4Zp8jjP3DPfUCzzTL3Fkn+LMPSMw85bo3HvCMz8U0OMee4697xH69C306VsYUncwp+5hTz/C3H4PXegGuuBNrOHH2MKPsUeeEOh4RXzgPfH+3xJO/4Aj9ASz+xFq022U5hWU5hXE2sVCtiovItJcRqq/gli1gEyzgEJzGYP5Kk7PLXzB+7Qln5DseEYoeheH+xomxzW0jusojJdRmS6hdSyhcV9G7bqE1HYyv+tLP0WjKUuTZZwm6wRNjhxCz2FE/vw8jzh8Dkn4EpK2JUTRKwgil2n2n6MleBZx7CLGnhWs/Tcw964gjZ+lzj9LvW+aOtsQFdoEexVt7JL4KZNH2Kdq54Cph1rHELW2AaotfVSZ8zu2vhcF2C3wsFfko0YZYZ8izC5piF1CJ2UCGxWSAJWSMHuFXg4KTOhNBrw+K5M95g/VDSdzvT+hZ63Fmu0yfDS0v35w/z8KPdsB0Fbri9tbxZWbjXINPtODto8AtJYl9JTic6KEnlJ8kfjNV18xGJcwGJf8DD1r8BlJyhlJKBlJKH+Gn48AVASatRzr0DKa1hRy7EMbbKuq0EagWbttq8f+0hzv1DGa0TCa0THcaWQ0k3/e6YyWuS4tM91asl1Ghros9GXsxOJ+LMEutL4eWlyjNHkmEPjH0SZn0aaPoEyfpyV5mpbkKUQdZ1F9GHK2TtzDkXuEczJ/UrNl9AHO3FO8s69xTT7HM/0S38xbAjNv8U+9xT3xMo+e0Rc4h59h7L6HKXMfdfsqmvgqxsQdrKl7GNtuoIvcxBh5iDHyGH3oIbboQzypp3hTL3DFnmPw3kfvuYfStorasYrKfgOZaRm5eQWF5ToSw1WkxmvIrFeR6a+h0a+i1a2iNV7HbLuNzXkPf+AJPv9j7M7baHRLqHRLqC1XkBnPo7RcQmo7j9x5AZnjLK2WozSYZmm2zCKwz9Biz9Fsy1Jvz9LimaHVfwRR4CTCwHlafeeRxa8iS15BElugKXCKpsAJRJEzaDoXUSYuIo2doc49xX5zHxWmXip1SfbIQ/mURajUpjhozFBvG6HRPUGNc4SDxgxV+gT7lDF2NjvZ3eygQuSlWh5hj8jHbqGbcrGb/RIvB8U+9jQ72NNopVlmIOIz0p0wM9ldVDXp+2mm7KPdghsc0bBRq2s7rdftQmft9T+FoOK1xY8pXvMp9KzBp7jqUwygEnpK8TlRQk8pvkhshp7ias8vQU8xfNa+X4+erQaa/7PRk4ePjuFO/UfomenOZy6jZ6TLTH+nhfZ2L/ZAGp2/mxbXKA2uMVq8oyhj02iTh1GkztGSPE1r6jSi9DlkXZdQ9V7FOHIL28QDHLlHOMYfYR17iGvyGf7Db/HOvMI3+zp/YOH0G3yTb/BkX+GdeIl3/BXu0RdY+x9h6X6Iun0VZXQFXXwVc/I2hvgq+rZVDJH76EP3UQfvYgjdxRp7hCP2GGv4MTr3XXTuuyjtN1A58vCRW5aRW5ZRWFeQmq4itywjs15FYVxBY7yF1nQbrWUVvfkWBstNrM47WJ13MNtvoTFcRWW4gtK6iNR0Aan5PELTaUSWk4htJ2m1ztNknaPFOofAPkOzLUuzLUuDI0erdxZB4Gi+0hM6jzBwEXn7tQJ6moOnafQfRxA6hTxxAUnbaYThExyyj7HHkKFc10m5so3dMj9l8gDl8igH9R3UWPtpcI1T756g2jHMIUMnleo29spD7GpxUNbqYJ/Iy0F5mN0CD7sELvZJvVRIfRwQedndaKOswYJIaSIZMTOUzld6CtDoNXyEngJWviB6PgWfT6FnqvfT4NkIPaVKTyn+UFFCTym+SPzmq68YiIkZiIkL8FkbZP5otmcT8BSjZw01xbmGnZEP92+0Zj2UNkPPRgPIvxQ4m+VIp7aAnqlOA1MZfT67NIx1aRnu0tCdtOMPRDD6UrS4Bql3jtLsGkLsH0PRlkMaP0Vr4jSC1Gkk6XPIMxdRdi2i61vBOnoX+/h9HOOPsE88xpl7hnf2NYH5d4SO5Hd0uSdf4cq+wj/1Ft/kG7zZN3jHX+EaeZ6v+HTeQd2+jK59BWNqFUP7Csb2G2jbVlGHb6IO30TuXUXhu4kmcBu17zYqzw3U3tX8v+5lVK5ryCxLyK1XUNiuorBdReVYRuNZQeVYRWa+jtJ2E4n5OjLjCjLTMlLjNZTmFQyu2xhct/OtLcdlFK6LSO1nEFiP0WI5TLNllmbrFM32GZps0zSac9SZJ6i3jtPomM6DJ3wCWew8yvgi8rYryNuvImy7RGv4LPXeozT4j9ISPI4wcpJG72HqXDNUmvso07RRpoqwU+LmO5Gd3RIPFZoYNdZ+6p1jNHpzVNmHqDT3sU8dp0zkYbfARpnAxn6pmwq5n32yADuaHOxssrFP7KFS4qW8yc6uOhP7mw2YrVZG0vnLkkz1fDxEv9F8WK5L+9ERDZsNNG8HPeuB8mtyKyD9WvSsb3UVz/iU0FOKz4kSekrxReI3X31Ff5uI/jZRAT4bbVvfDDzr0VOMmuIKz0hK/VEW37ceQhtVezaaD/oUZH5JjnWq89mhZSxtYCJtINuRn/sZ7VIz0qVkJGOhLehD5wjR7Oih2TOGwDOMNDCMLDKWPzQvcRpR6jSS5BnEqbNIO/KHGFpH7+CYeIAr9whH9gmW0YdYRp/gP/yWwPw7fLPvcGZf4M69Jjz3I8GZH/BPvsMz8Rrv+CuCk+9wjT7DlLmNLn0ddewKqugVtPFlNO3X81va4zeR+leQ+66jCt5EFVpFHlhGFVhB7r2K0r2E0n0ZufMyKs8VNL5raHzX0PqX0QVWkLuXEDsXkXmuInYuIrQvIHUsInddQe66gtq3gsK5hNR6EYntNArPWaTukwjs83no2Keot41RYx2l1jZGgzVHo22SBvsUrZ7DSCInUcTPokouoE5dQZ1cRp5YoiVyjkb/cWrd89T7jtASPEaT/wg1zhyHbOPsN3azR+1nt9zDDqGNXRIne2Q+DhmS1NoGqHOMcsg+wl5jD3v1GfbIQ+xstrKjyUCFxMlBpZ9KRYBysZ/v6q18V2dmT6OV8iYbu6qN7K7XUS0yEQrYmO7WMt8rZ7JLlT/WoMtY2Kq+vtK41blUv7TSs13YbPWYX4Ke7ba3sr0msr2mj6o+pUHmUvwhooSeUnyRKEZPf5voPwQ968GzFXpGPwxEb3XWz0YVos/N0Q5VPtMaRpMGxlJGxtIGhjs0DGVUDGYUjHZZaQv6MDjDtNi6aXKPIvAMIw8OIQmNIIke+xl6ZJ0X0PRexTJyG/v4PZzZh9gnHmMeeYBp+BG+uTcf2lxvcUw8x5V9RbAIPd7sGzwTrwlOvsMz9hJLzz30HTcK6NHErqFNXkcTX0UTv4nEfw2p9xpy/wrywDIS7yIS7yIi50XEjgtIHecROy4g91xG5b+CwruIwruI2ruE1HURqXcBqXcBifMCQud5JJ5LKH2LhRRZz9BsPIrAchSZ+yRSzwlanYcL6Kmzj3PINkitfYRmxzQt7jlaPYcRBI4ij51BlTiPKrmAMrGIMrGENH6ZptCZPHo8h6n3z9PkP0KdZ5pDtnEOWEeoMHRRpvCyW+pip8hOmdTLXkWAamMntbYBamxDHLAOsc/Uy35jN2WyIDsazHzXqKdS6qJK6adS5qes1c03tWa+qTGyu97MnnozOw/p2ddopEluJRp2MN2jYa5HwmSXKv+Z6zIyuQm6i9GzFXx+7Y7DX4KlT7XC1sNnO5WeNfCsR8/a/SX0lOJzooSeUnyR+M1XX9EdbaU7IqAnKqQvJmawXcFQQvkhVQy2KxlOqj7KjSCz3Rzu0PwsRzq1jHRqGe7IDxaPdekZ7zYw1qUv5GhGV1gzlFYXHlOcxc83mtEVHvOpXI+w9W25sbSSwbSRSNyLNRBH7B6gxtRLva0LcaQXWWgYqW8cTfsJ1MmTKDtPo0ifRJE+ibrrHMrMRRRdl7CO3Mc5/qSQ/uk3+KZe54eXx1/hzb7Bn/sRz/hb3GN58Phyb/Hn3uMafY257wmG7odoOu4ii99AGl1GHrmCNnoNffQamshVtOEr+QwuovVdRO27iNR9HqHjAmLXpZ9g47mExHMBqfciIu8FhM6ziGwnEVpPILGfQuo4jcx5BrH9BELrMQTWeQTWeUT2I0g9R5C7j6DyHUceOIbAPUeTfYpa6zgNtgka7VlaPEcRh88hCp1FHD6HIr6Qv4J66gry2CVUsTx4DrqOcMg1R4PnCDXOaQ5ax9hn6OaAoZMKXZpyZYTdYgc7Wi18J3SxXxOlUhunytRJtb2POucwjd4RGp291FjSfNdq56/qDHzXYKFCFqBS5Ke82cWeBju7a435rLewq9bCXx8yIVDasTtsDCX1DHdoGEznPxPjnfkTu7eD5i0P2uzWfTLXn0m1UTVnM+R8ahfXZpWizSpG261EldBTis+JEnpK8UViM/SswWewPZ9rCNoKPtsF0UboWQ+gNfisB08xeoqx9Lm5GXrWcrxDxVCnkVjCjTuaQhfJUm8fptbaTZOnE4GvC6F7CHloDml0HkX6JMrUCeSpE0iTJ5Clz6LquoR19C6Oscc4xh7jyT3P79iazg8vuydefkDPe7wT7/CMv8WX/YHQzI8Ep36LZ/wt9qEX2AafY+57gjp9B2X7Koq2FVTRqygjV1BGrqAKLeUzcBmV7xJK70XE7otI3AvIPZcRuy8idJ5H4DhHq/0srfbTNFlO0GQ6hsh2CqH1JELLcYTWEwitJxBYjyGwHkPkOIbMcwqZ9yQC2ywix2HEznlErsM0mLJU6UapNY3T7JykxT2HIHiyAB5Z20X0ncuYum+gSV1BGr2AJHyBBt8JKhwzHHDM0OA+TI0zl6/u6Lup0KXZp03kz+KReCiTONmnCFFtSVNt7uCgOU2lKcMBcxdVli4qdTH2yoN822Thu2Yr5SIPFRI/+wVe9jQ52VVrYUe1nu+qdHxfa2JHjZnvauzIDT68Pg8jaSPDHRoGUvnP4diH08Y3mkFbX2Xc8mTxbaBnsxPIf8kcz3bAs53X2ehsq40gVEJPKT4nSugpxReJX4qezeDzSypB20FPcaVmfcXmPxM9a2278Q4Vw51G4u1OvNEU5vgcza4J6m19NLkzNLs7aHUOIPJOIg7MIE8cQ5HMp7j9KNLUGZSZizjG7mIbfbAlenzZH/CMv8Uznq/wRGZ/R3jmb/FOvMM58grH8Etsg8/Rdz1Ak7qNMnYdRWQZefga8sgV5B/wowwuIvcvIPVe/NCmWkLpW0LuuYzUdRGJ8wIi+zmEtrM0m07SaDyKxHEGieMMQutJRLYPaT+B2HESqfskqsA5lP6ztNpmEToOI3IeReg4TI1hnEPaEWrM2Xw7y38MUegsguBZROHzyOMLGLtvYO69iTKxiCh8DlHwHLXuo1TYpjhon6LeNVdAT6Wxmwp9iv2adr4X+9gj8VAu9XJA00atrZMaax49FcYOKowdHDSk2SX1sUPg4JtGM7uETvZL/ewX+9jb4qas0cGuWgvfVOn59pCOb6uMfFNtYUe9E4U5iD/gY7TDVKj0rKFnYhPwfAo9v+YMqV+Dns1aW78EPRtux/+wdrMKVAk9pfjcKKGnFF8kNkLPQFxegM9gu5KBuGJdy+vn7a7hpOqjNVvh51Po2QxB61tYn0LPdtYUo2fD2aOUIv+eUwqG01qScTOhtiSO9DEk4SO0eMdpdHcj9HQhcPTT6hxD6M0iCk8jbZtDGp9H3D6PNHkCRfosttFbWIduYx25jzv3FN/US7yTL3COP8Mx+gzn2HM8E68L6AlO/Zbo3O+Jzf9/hGf+Fn/ufQFF1oFnGHseoe28hyp1G2Uyn+rEh4zfRN52A0X0OprwCobITQyhG2h8V1C4FpA7L6FwX0LmvIDEfg6B+RQyzwWk7vNI3eeRey8i855H6jmHxHMGqfcscv955P6z+aulO4/T6jpOq+MIdZYpqs2TNDoPIw6dRBI9iyy2gDhyAWnbJbQdy1j772Dpu42ifRFB8CzNvpNUO+c4YJvkkC1HjTNHlXWUCmMflfpM/hBCZYTvBG72iL1UyoNUGxLUWjuosaSpMiU5aEhyQJ9f902jmb+u1fNdo5lysZt9Ii+7mx3sbrCzq97G93VWvq428j8P6fm62si3tTb2CMJo7XFCoRCjHUbGOn9qm/5nomc7A87bHX7ezqVYtnr9jXZMbvSYEnpK8TlRQk8pvkhshp41+AzEFQX0rIdPMW6GEsqPsLR230aQGEpvnIMp1c++/hz4FN//SVhtUpUaSysL6BlKq0nFDQTCMRzpY6gSZ5G1zSMODyMLDCJyDSJyjSPyTtDiG0EQyiKOTiFrP4Ikfgxp8gTmgWuY+lexDd/DnXuKJ5e/9pZ99AnWocfYhp/gGnuZn+XJ/kBo+m+Izv2/ROd+X6j4BKd+iz/3HvfIK2yDzzH1P8PY9xRD31N0XU8wfEhj5jHqzvvo0vfQx+9gitxEH7yOyrOIzHERmeMiCvelQoptZ1H6FlH4LqGJXEUTWkIdXETuu4DUcw6x+zQCxwkEjmMIPSdptM1Tbz1Ko+MoDa6jNLqP0eI/hSR6FmnbReSJJVTJK2jS1zB03cDUcxND1w2kbZdo8Z+myXuCKscsh2w5Dlqz+Z1ahl7K1Z3sVechs0viZ6fAzcEPV0evNiSoMyapNSQ4pItTqY6yXxlml8jDN/VGvqk3srPRws5mK7ubHeyot/BNjYnvqk3srLXwbZ2Fb2vNfFNj5bsGFxWKBCZPmnA0ykjaUEDPcMeHtuZWLc9N0PM51Z3PyV96IvlW17zbDuJK6CnF50QJPaX4IvGbr76iJyqkJyqkt01EX0xMf0xWgM969GyGn3wrbOOK0HbRUwyegaTyI/hshZjNwPOp1ynOzdAzmFQzkVIymFSTy0hJt5kIR0LY0/Oo0peQJU4hieSQhEaQ+UaRuMYQesZp8Y3Q6h1EHBlHkchXfCSxebSdl7EOrmIbuY178jHu3FPcuac4x59gG36CfeQp7vFXBKZ+IDidb21FZn9PaO53BGf/Fv/0b/FN/Yh38j3usTe4Rl9jGXyBaeAlpoGXGHtfoO9+hr77GYbMU/SZxxgzjzG238cYuY0uuIrCfRWJYwGx/RKyD3M+MvclJM4LyHyXUQavoAhdRR3Ot8ikvguIPecQOE/TZD1Oi/0kQs856uzHqLMfo8F5gmbvGVr952gNnUMcuYAstoAydRV1xzLazHX03atoOldQpq4iil6kNXSORt8p6lyHqXLkwXPANMReTYY9iiTl8ijlsgBlEh+7xV4OaGJU6RPUGJPU6NsLeVAZplzkYUeThR0NZnY1Wvi+wcz3DWZ21FvY2WDlr6v0/M9Der6rs7CzwcmOJhdf1zvZ0eynUtWB0ZMgEg0z9gE9oxndRxBef87U2vfbHWjOdhk/mduFzGa3/9qDOTc7FX39fSX0lOIPHSX0lOKLxBp61io9vW0i+mOyIvisVXvkH1WAtkLPRjj6qA2W2joHkspCFld/iqFTfNt67Pwh0dOfVDORUjOU0jDbJWEgaSYejWFPHUXffRVt5hLy9lmUsSxS7wgyzwRS3zit3mEanb0IfEPI4jOI2+YQhKdRxE9j7L2GeXAVx8SDj9DjHH+Ge+Ilgel3RA//LW3zvyM69/uPqjveiXeF9GV/wJ19h3XoJca+l5j6X2HsfYGx6xn6zifoOh6jTT/C2PkEU+oRxvb76GN3UQSuI3IvInAuIPZcRuJdROy5jMB5EZF7AZFvEbF/CWlgAYn/Un5nl+c8AvdZBJ4zCD3nEAcWaHadpcl1llbfeeTt11Aml5EmriJNXEWeWkbfdQtD922MXbfQZW4ii19B0raIMHyJZv85GrwnqXXOUWWf4JBlhL3aXvYokuySxdglDrIXJJoSAAAgAElEQVRL5KFMnG9tVaiiHNTGqdbFqdK1UauPUaNrY6/ExffNZr6t1bKn0UpFi4N9LQ7KGqwF9HxTY/rQzjKzo9nLLkGA3cIw5eIY9YZ+9J5Uvr2V0jPRqWKkU12Y6Vl/3lRxG/RTLa+f4GD4ZG6nOvMp4BRD5ZPnUm3xnrdznbyJjL6EnlJ8VpTQU4ovEsXoWYNPMXr6Y/ksRs/HMz+KLdGzvt31OejZLDdrf/1h0KNlLKVmKKljLiNiOGkkHo1haz+CoXsZXfdlZInDKNtyyH3jyL1ZJN4xBL4hGhw9NLv7kcVySNqmEQQnkUSOo+9awtx/HdvYPVzZJ7hzT3FNPMU18RxP9hXBmR9om/8dsSM/tbRC039DYPLHj8DjyeXRYxl4VUCPqfs5hsxTjJ1PMHQ8xtDxGFPmKaaOx+iTD9DF7yEP3kDgWqLFuYDAs4DQe5lWzwItrosIPHn0SAJXEPsXEfkuI/JfQuS/hCR4GUngAtLAJaTBK7R6L9HqvYTAdzF/Da3EMrLEMtLUMsrMKqaB+xi6b2PI3ETbeRNZ/Cri6CLCcP6K6nVr6LGOUmkcpEzdyW55nF3iKDsE+Wtk7Ra5KJf42KcIU6GKUqWNUaWJUKOLUKMNs0dkY2ezkR01Wva3WKlsdVLR4mBXXb7Ss6M+3876ttbMzgYbuwQBykQRysUx9kuTNFuG0bvTBINBRlN6xjuUjGRUhfZW8TlS6+e+Njtc8+fzPr8MPcXI+dyTxtdjZj1qtpsbYaqEnlJ8TpTQU4ovEhuhp69NWoDPdtCz3Szg6FegZ7hDs+n69dvci9GztmazNlrhOTYYzB5OqhhIaRhNquhPaplKtTDcriMRC2NNzKLvuoauawlp4hjK6BSa8BTqQL7iIw4O0+jsptHZjTg4ijicpdk/hiAwjSJ5Fk3nZfT9N/Jb2Mcf4c4+w519gTv7At/kG8JzPxKZ+5t8m2vqt4Sm/6aAn+DUb/Flf8A1+hrnyCucw29xDv2Ac+gH3IM/4Ox9jb37JdbMcxzdL3H2vMKceY4u9RBt8gGKttuIAisIfNcQBq4h8C8h8C/R4r2M0LeINHgVRWQFeTi/I0wRWUbVdh1d4hbaxA00iZto2m+hiK0ij11HHF1GmVpFkb6JPLWKtvse5sEnuMZfoOm6iSq1gjy1jCx5DUn7FVrCF2kKnqfWc4JqxzSHTENUGnooU6YoV8Qok0bY0epiV6udMqGTvVI/leo2DmhiVCrDVMj9VMq97Bc72d2k4/sGDWUNeg4K7BxsdVLZ4qK8yc6OGjPfHDLwXZ2F75sc7BeHKBOFKBNG2StNU6Hoptk+gc6dxOPzMZE2MNGpYuxDpWej85o+dduGp4t3mj6Zm1VxNmufbVSZWQ+0rd7XVoeDbnSo6EbPV0JPKT4nSugpxReJ33z1Fb1too9aXH1t0iL4yOlrk20JnvW3b7V2O+jZDEEboWij1td68GwnN0PPYCr/nvuSWrLJFgYTOmJRN5Z4Dm1mCXXXIrLECdSxGTShGQzRGVShLOLgMC2ubhpdXbT6BhAE8hcnFXgnkbYdR95+DmVmCdPQLSwjd3CMP8I18RRP7iX+qbeEZt8Tmn2PZ+I1/tx7grn3tM3+jtjc74lM/w2+8bc4Bp9jH3iGZ+Qd3uEf8Q78WACPresFju6X+Hve4e9/h733NeaeF5h7XmDpeoE+/SiPoNR91Im7yOO3kUVXkQZXkIeuo4nmL2uhS9xGn7yNLnELTXwVdfxmPhO3UaV+SnnqFor0bbS993GNvsY9/grH2Et0vfdQZlaRJpYQxy8jjl+mNXKBGvdxDjiPUGkcp0LTxV5Vmu/lcXZLQnwvCvB9q5O9Eg8Vcj9V6iiViggHVW1Ua9qolAbYJ/awq8nE7nodu+s17Gk0cEDooKLFUQDPzloL31Wb2N3sZK8wwEF5G3uEQXYLIhxQ9XNIN0yDI4fG047H7yXXaSLXkW9bDaXVBWCMpNSFSmUxDjbDQDEixjt1jHcYP5mbXWZlO1WYT50x9UvQs9HZW8WzecU/GyX0lOJzooSeUnyR+M1XX9HdJqErKi5kd5uEnpj0o+yNy+hrl9PXLqc/oShkX7uc3riskGtrNlpbnMWI2arKs9Ht63P9c2xW0Vm/fiilKVqj+CgHknIGknIGEzIGUh8yKWcgrSaTtOFs70PbdQ15x3XkiSV08VNoonNoohNoYxPIwoMI3H20unoRuAYRuoYRuoaRe7OognPIosfQdCxh6buNbeAutsFHOEae45p4jXfmHcH5HwnN/4hvKn8ic3DqLZGZH/M5+QP+sVd4Bl/iHnhBcORHgoPv8fa+wZF5hr3zKfbOp7h7XuLpfYW37zXuvtd4B97iGXyLu+819q7n2DLPsHQ+xpR+iD55B3X0NuroHRShm8iDq2ja7mBIPMCQeIA2fgdF+Aby0HVk4WVEkWvI4jdQp++i7ryPLHELWeIWpv5nOCfe4hx/g3ngOebBZ2i77yGMLtIauYQgehFB5AzVzjkOWnMcNA5yQJtinzLG91IfO8QuvhM5+brVRrksSIUqygFNjL0yH/sVAao0EQ4pfFRIXOxq0LOn0cDeZhP7WszsbbGyu8nKzjoz39UY+brKzO5mD5XSKAdl7ewXtlHR4qdCEGS/ZoT9xilq7OOonVF8PgeDKQNjnWYG2rUMdqrI9mqY6tEznlAzEVMy3q4im9IWBp23e8TC+vOmNsrtnie13WMeiqs1xcdHFG5f91ybtY23+kOhhJ5SfE6U0FMKAP7xH/+RP/mTP+Hrr78u3Pb3f//3VFVV8cd//Mf89//+3zl9+vRHj/n973/P999/zx/90R/xl3/5l9y+fXvbr7dd9KzBZyPYFKNnu/jZrHKzfs1Gudl9G8FnKzT9fN3H4Mmn8mMEpVR0tFtwt/dh6llGncmjR99+GlXkMKpoFnVbFmV0DLFvEKFnAIFrEIFzCIFzCJl3DLl/CmloDkXiPPrMCqaeVWyDD/Nn9GRf4Zl+Q/jIbwkffU9o7geCMz8QnvmByOx7olPvCWXf4ht9iXfoJd6hV/iH3xEYfId/4C2evpc4u5/h6HqKo+sp7t4XePpe4u59gaM7n5aOJ3nMJO9jSj/EmnmCtesR5o5HGJOP0MXvo4rcQhu7W1injd9BFb2JKnoTWXiZFt8CsrYVVImb6DL3MfY8Qt/7CNPAU2wjz7EMPUfVeRd54jqS2DWaQxdoCZ6lOXCGeu9RDtgmqTRPUKHrY7+qnXJ5lO+EHr4R2PlGYGen0Mk+RZhKdRsHVW3sVwSokPvZK3Kzp9XK941GvqvWUNZkZG+zifImI7ubrHxfb+Gvqwx8W21gR72DCkmEKkWSg4ok5cIoByRRqpUpKo1TVNiOUG0dp0ZspKWlDof6AD0xPWNdTsa6TQwk5YynNeTSOnIpLdlkvtW59nnaqMK4EXy+BHo2OjR0/VlZG82/FR/8WUJPKf4jo4SeUgCgUCgoLy//CD3l5eXYbDb+5V/+hQcPHvBf/+t/5f379wD827/9G3/+539Od3c3//qv/8r58+f5b//tv/EP//AP23q99ejJRER0t0k2zGL8bISh7eCnGECbIWaz6lBxdWkrGG1WPVr/mGIgbVpNSqg+PC5f6elPKOiImfEnunH2X8fUs4omfQ1j4hzKyDzy0DSKyCSq6ATy0BjSwAhC91ABPRL3CBLvGKLgJJL4CTQdC+gzV3AM3cc9lp/rceVeEj78jrajPxKde0945gdC0++ITL0jPPmWUPYtgfHXBMfeEhp/h2fwBZ7+Z/gGX+Afeolv8AXegee4+57i6X+Gd+A5rp48ghwfqjuWzsdYM09w9D7F0fsUV+8TbJ2PMScfYko8wJi4h/5DGlJ30SfvoEvcRtu2ijp2A3n0Koq2ayjarqHP3MHc/whz/yOMvQ+wDOa/VqZWkUSvII4uIopeRBA+jyB4hgbvPDXOaapsOSq13eyTtbFHGuDrZgffNFv5ttVCudRLpTLMAWWUKnWUg6oA+6VudjaZ+KZGw9fVar6t1VLebGFvi5U9TebC0PI3NVb2tHjZKw5TpU5SperggDxJmaCNKlUHNYY+9lvnqXafpsmZZV+1iN07/poD3/0ZekU1YY+agbSV3nYl/XE1E2kdk506ch1aRpM/fU42qoxsp/Lza/IXH+i5yUnphTbVFugpzhJ6SvEfFSX0lIJbt26xZ88ejh49WkDP3/3d3/Ff/st/4Z/+6Z8K6+RyOV6vF4C7d+/yp3/6p/z7v/974f5du3YxNja2rdcsRk8mIvoZeoqrP5tVgD4FoK3gsxGA1mCzVX6qIrQZeDaCz1bo6W9X/gw9nW0m/PEu3APLWHpvok3l0aOIHkMenkUenkQVzaIM55AFxgvoEbqGkXiGEXtGEfjHkcTmUSfPoelYwDZwB/f4EzwTT3FnXxCae0v0yHuic++JTL0jlHtTyGD2NYGxV4Szbwln3+IZeoZv6BnB0ZeEx18TGHmBb+gZrr5HuPsf4Rl4grvvKa6e57h78pUgZ/cTnN1PcPU8xdn9BHvXQ8ypexja72JM3MOYuIcpeR9T8i6m5F2MiTvo47dQR1dQx26gal8uXPJCk76JufcBhp776LruYui9h77nLsrUKtJYfpu6PH4ZceQ8gtApGn1HqHfPUmWfyM/zyCKUSfx802Tn22YTOwVW9sn9HFBFOKCMckgd5oDCR7nYzs4GA9/UaPi2VsvOBgNlLRb2tObbWt/VWfimxsquJjcHZFEOKtup0XRSqUixX5qkXBTnoLqHWuMQlbZj1HjOIHSMc6BaQNnXf8XX/+N/o7biW5TSBhJhPd0JDb3taoaTarJpDdkPhxUOJtUMJDbfVfhLgbIVlrazbqvdiL8GPaVKTyn+M6KEnv/F45//+Z/5i7/4C373u99x7NixAnoWFxf5sz/7s4/WDgwMcODAAQBGRkbYt2/fR/fb7XaMRuO2Xne76NkMPhtVgjbCz6cQs5122frvN4PMGmY+VT1aa1cNplT5X2QboKe3XV14rcFUfhg7HTHga0vj7ruCtec6uo5rmFMXULWdRBY+jCw0gyoyiSoyiSKU/Rl6BK5BWjxDNAdySKLHkMdOYexexjXyENfYY1wTTwnNvSV25D2xw3nwBHOvCEy8wj/2At/oc7wjzwiMvSI4/hrvyDPCEy+JTb2lffo90ewbwuOv8Aw8xtF7D1ffQ+xdD7F2PMLW8QRrxwPMqXtY0vexdz3E2fMYS+cdzKl7mFMPsHU+LqwpgKf9JuroCmLvQn77emiBZvcZxL4LKBLL6DK30HbeRJlcQRq7UkhJ2xLi6OUPpzCfosl3jAbPHDWOKQ6ZR9mnTFEuDlIm9PJNk53vWsx8L7RxUBXgkCrCwQ+7tcrFdnY2G/m2VkNZi4VygY19Ige7m6zsarSwu9GW35Le5OaQKkGzqZsmUx81+i72SdvZJ0lwQJ6hWjdMnSlLtesMjd6zSK1DiFoVNO7bxf/9f/wx/+f//if8X//jz1BIDhKPKOhJ6hhIaRiKyxlJKPNDzqk8fLbaGfgplGwnP+c5PnUh4O3AaQ09m7WZS+gpxedECT3/i0coFCIajQJ8hJ6TJ0/yV3/1Vx+tnZubY8eOHQB0dnbS1NT00f2xWAyJRLLh66TTaX7zm98U8qsP6FkDTyYi+gg4xejZaOZnqzbYVvjZqh22vn22fpB6u1Wj7bTLCuvaNQwkVB9l/4f2Rn97vuIznFQxlJTTHdUTiLTj7DqPObOEoeMKlvQCmvhFJMHjyAKHUYcmUYVnUIamkfrGkXjH8hUe1yDNzgEaHT3Uu3ppdI/T6p9C2X4OS+9NHEP38Iw9Inb4Le1HfiB2+C2hqZcEsy/xjj7FPfwYz+AjHD33cfXlqzjewaf5yk/uDe3TPxKfek80+5bAyAu8g0/wDj7B2fsQR+YBjs6HWDruYUzexpi6iSl960PexJBcxd71EEf3I+xdD7Gk7mBK3EIfW8lnfBlFeBFFeBFp4BItnrOIAhfRJFZQtS+jiF1FGb+GMLyAwH8Bgf8c4tB5xJELCEOnqHPOUmefpt45SY11lP3aXsokbZQLvez5sEV99//P3ns+t3mg690+82Z2JRJgEyVbXttrr3uTVazO3kmwoPfeGzsKARCNALt6I9Usy5bVSVGi7PV6vd7dk5PkzZucmZOZ/A05f0HO5Evyez+AhEiZkuXVSfwhuGauAQiCD/kBBH7PfV/3/cjdVCu9NBsGadIO06AepFri5XCPmf0iA/tEFuqVfpo0/dQp+9knyu3gOST2U6sK0qCJILJP0OObQeI5SqtlgnrtGPXaMVrNM7Q7TyPyX0A8dAPF4Ofo7OO4tXqc3Q0cfrOciqIiSoTl7N75Dn5bD/GgkZkxe34a8XjCwNGEkZnRFfBJ/HhK8GmrEZ7kZ4WZZz3W0y74+zj0PH78tfefNkBQgJ6CnkcF6Pm/WP/0T//E22+/zb/8y78A/KjS88Ybb6x7/uzs7LpKT319/brv+3y+n1XpWVvleRL0rD6+9ntP87O0v54ENj8Xen4qL/SkdtnToGcVdGZGTXnwWd0zNDFiZTgUwz92HWd6AefYfVzpexhH76AOfoE6cHkd9GiHT6+Dnh7fNF2+LCJvBpH/KN19J1GGrmLN3Mcz/R19x/9CeP4/Ernwn4he/EcCZ/8Dw6f+HX1H/4J/9i/4p37AM/5H/Nkf6B3/MwOz/0Dw+H8ifPIfiZ39L8TO/heiZ/6J4PH/xMDsPzAw+w+5VtfE39M/+W/xZ3/Ak/4jruQfcCa+xZn8Pfb419hHv8Gf/Qv+bA6QHPE/YIt9jSWyjDW2jD3+NdZY7r5hZAn18B304XuY4g/RR++jDi+ijSyhCi4iH76NdPA6qsANVMHryIauIPKdo91zik7fKVpdszSYM1QpglRLe6mR+jgsdVOl8FCj8tGg7aNO2U+too+D3Xb2d+rYL9JzoMtKvdJHo7qPBmU/ezsc7BO5qJIP0KSP0mJK0+WYptszS6dzlhbTJA26DA26cdoss3S65xD3XUE+fB3NwGXMljh9OjVDsiZEH77EluJiiotKeP21bejk9QT9ambTNqZWNpPnlnDqnwo9a8Hhp1pE/zugZzZpeGp762hi/XXtnnbcAvQU9L9LBej5v1jHjx+nqKiIF198kRdffJGSkhL+zb/5N7z44ov85//8n3+U6dHpdOsyPVu3buV//s//mf/+4cOHf1am51mg52mTXWuf+1PwsxHwrH3eT0HPRqHmnxqPfxogrYWe6ZjxqZ5dAZ/pERvh0Ai9iSs4EzdxZ5fxjD9EP7qAfOgqmsDnmEMXMATP5xyaz4WX+44h9k0gcmcQeZN09qbp6p2hyz9LT99Z1OFrGBJ3cE5+i//oDwyc/HuC5/5f+k/8PX1H/0LvkT/jn/0B/9QPuLPf4ct+j3/8TwzP/gdCx/+R0PF/JHLqn4ie/i9ETv0Tw0f+P/om/x29E/+AN/sXesf/TN/kn+mf/Cv+8T/hzfwRz1juOL7xP+LLfo937Ps8EK2FHGtsGdvoQ5yJh7hT3+Ae+xZbfBl74iHm2DLq0ALK4G1UoTuoQgsoA3eQD19HFbyGKnCVHt8FOj3n6HKfoc1+lFp9hip9in2SYQ50e3OW+KhReqlT+6lTeHPTWF1O9neYONipoVpsok7upFa+0tqSeNnf5eGwpJcGfRSRfQKRYxqRY4Z22xQt5ika9FmajVO0mKbpcJyko3ee7uEryAY/R+efw6INElTLiMmb0R54j+2VW9ksqKRUKKBq3/uoJXXEg2qm0komEkqmYyqOjlo4ErXlsz2Pt1SfNEH4fxJ6Ht+SPhPTrr9kzJrf+SyTkQXoKehfWwXo+b9Y//2//3f++Z//Oe8TJ07wySef8M///M/8r//1v6iursbr9fIv//Iv/PWvf91wemtycpL/8T/+B7dv30YoFPLf/tt/e6bf/Xd/Q3trLeg8qcX1LNDztMmwjdpka2FlbZvsaRWfZw5EbwA5U1FDzjEdUzEd01ENs3ENk1EzwVAAf+IirsQ1nGP3cWQeoo/fQx74Ck3oS4zBi+iCF9CHLmCMXEQTPINy6CTd3qlH0ONP0uUfp8s3QZfvGJLBS6hCX2JMLmAfX8Y19Q19x/5M37E/03vkr/hn/4Jn6k94J77Hk/0e3+Sf8E/+mb7pv9I782/pnfm3DB399wRP/EeCJ/4jgeO5Sa7+6X+Xy+5kf8Cf/QFv5o84Et/kQCa+jDf7HX3T3zMw/Vd8mT/hHfseV+pbrNGHmML3MQTvYQwt5S5AGlxAH1zAEn2AObaMZfQhhpElNME7qAO3UQRuoArcQDZ8DcnQl0iHryId/Ixu/1lE3pN0uI7RoE9xWB7ikDLIwR5fLpMjdlIt99Kg8lOv9HGox87+Niv726wcbDdTJzbTrHDSpPByoMfBge7cluUaRZAGXYx22ySdzlm6XEfoch2hxZyl3pCiVpuk0TRFq/UYXa6zSPo/Rzx4hR7fGTTuadx6NxlNF+PqRiwNH/L6y1sRCoWUCYp587WtfLrzbVw2EeOjWiYTeqZGtTn4XVsZXAsDKSPTSQNTCT1TCT2Tcd0zg8q/hvMA9tii0LUXEZ4d1a2DtJ8aCnjSyUQBegp6HhWgp6C81ra3ILenp6Wlhc2bN/Paa6/9aE/Pf/2v/5UDBw6wadMm3n333b9pT8/ztreeVOXZ6LHHoWftz/4UED3rfqBnhZ6818DNZFSbd/6xmIapiDoHPTETgeAgvsR5HMlrOMbuYR9bRj96H2XoBrqRrzAELqANXkAXvoAxeglt+ByqwGmkfUdzeR7fGB3eOJ2+LJ3ecTrcs/T0nkM6dBlt7CaWsSVs2Qf4jnxH77Hv6Tv69/hm/owz+0fcmT/iHf8TvdN/pm/mL/hn/pr3wOw/MHT03+c9OPsf6Jv6B9xjP+Ady1VyvJk/Yo9/jSV2H+voAzyZP+Ad/5a+qR9wp77DmfgWS/QBxtASuuEFdMMLGIL3MI88QDt0F83gHfThJcyxh1jj36AP30MduI06cBvl8HWkA1cR911B1HuRzr5LiPwXEPWepN1zhFbnJHX6GIfkQ1QrBqkSe/LLBZvUXpo0fdQrfRzstLCvNefDIisNUivNCicNMjd7RXb2djk4IPbTqB+lxZKhwzFDh2MmDz7N5jEaTWlq9EmaLTO0208g9s6j6ruOvP8Lul3H0TjSuDQGpjQiZnR1uNp38M6rW9hSWkSZoJjtlcX87vWtqOVVpEcMTI6aV3JeKo4ktI9aoWvbqSkj0ykjkwk9kwk9E89YOfnXAJ21kLJa5dkIemZi2idCTQF6Cvo/pQL0FPSLaCPoWQWcx79+Uqg5Dy9hFeMj6h85G1aRCW08Hfa0KbFnCUf/rSPzP5oYWwM4G3oNTE3EzEQj/fgTx3Emr6BL3kMd/xpz8gHG8JfoAp+hDF5CFTiPcngebeQC2sg86vA5ZEMn6RmYobNvgnZ3kjZXgjZnklbHGG2uKTq9R5EHL2FO38SWvYNn+iG9x/5I37E/453+AWf2j7iyf8I3/Re809/jmfojvUd/wDf7PZ7p7/DN/AnP1J9wjX+Pe/wHfFN/xTP+V2zxP2AeeYh55AGO5NfYEvexxpewjj7Amfw9ruQfsMaWscTuYxpZwhzJ3RrD9zCNLGGLfY0z8S222O/RB5dRDS9hiC5jiC6jD99DG76NYeQ2muA1pP6LdHnmaXCdpsF9iibXcVpds7TaJmgyJ6lXD3FY4s1NYfXYqZPaaJA7aFR5qJE4OdhpYWezjt2thtwuHomTZpmDRomNw1129omcHOj2UqOJ0eaYQeQ+Sqf7JF32k/Q4T9Nhn6beGKdWH6PZkqXdcYxO5xmkvsuo/ddRer+k2TWOxD5MTCHjtKqVk+pG/F2fsuO9rWzf9mvKywSUCAS8VFnK3l3v4DS0E/AryER0TMZUTEblTMdUTMdUzMQeAfhqhWcqaWAqaWQ6ZXrmhZvP4idBzpOO/7Spx59qCz+tfTw1qi1AT0HPpQL0FPSLaDXTMxaSr3MmrGAsJCcdlOW//in4eVboeZqfBlXPsifop5YlPnFq7Amwk4ehlQ+P6biOyVEL0YiPvtg07sQFTKkFdKmHmFP3MYS/QjV8CW3kczShyyiHL6AMzKEOz6MZOY8icBb54AnkA8eQeidotydotY7SbI7RYByl2ZKkxz+JPjqHKXEZU+oGjoll3BNf45n4A65Mzp7xP+IY+xpbahnXxB9wT36PI/sH3NnvcI19hzP9Hc7U93jG/4on82fsie/QBxbRBe6iD9/GMnoPa/we1vgS9sRDLJHlHOxEcyBkHX2AbfRhLuC8xo7EN5hjD1EHF9GO3EMXWUIdvosqfBNl6AbSwc/o9M3T5jlHk+sUDdZZ6s2T1BtS1GgjVKuCHBb7ONht50BX7hIS9VIHdRI7h7qs7GszsadZz64WPQe77VSJPTTIfdT02KnqsnKwy0mNfIBGTZAOxySdnmN0eY/T4z+NxHsGiec0LeZxarRxanUJWu3TiH1zSP0XkPVeQub9AqnnIp3WGGqTm4hCxJy6kTlNPaGeg1R9/Cpvv1JKWYmQEmEpW0pLeGN7BbWfvoOkdR8jvSqmRs1MRY3MjKo5mtJyNKXlWFrHsdSjhZbrAvH/itDzt8DJk04Afs7/0EYnCgXoKeh5VICegn4R/d0LL/wIcJ4GPU8Dn2x4Pfis3n8e6HmWys/fCj3rLq3xM6BnatRMPOylPzaJOz6PJbWAIfUAc+o+5uhNdKEvMMSuoR+5ugI+86hD51GHzqMKzaEcPoVy6CSK3lm6HGna7UlarXGaTFGazTFEriTyoVlUwVNoo59hzd7Dkb2Pe+L3edCxpZaxxpcwJ3KtNXvmW+yZb9dBjyv9J7zZv+DJ/Bln6vtcPie0iD58G1P0LubYAubYIrb4ci6/M7KEcWQR6+gD7ImHWGliF6oAACAASURBVEcfYIndzweWHcmv88Fl7ci9ldDyHRSBG8gCXyAdvkpX/wVaPWdocZ+m2XGMJssU9cYMdbo4VYogh2X9HOp2cajTxsFuO3USJ3USO9XdFva1G9ndpGNPs559IgtVYg81Uh+1Mj8HRVYOtNs4LPbRpA3RaorT5Z7JQ4+49wwS32nEnpM0Gyeo1Sap0aVodx5F1ncBed8lJL2X6PJepsd1FrElgM5oJaZqZU5bx7y2gZj4MI0732DHaxWUCIopEZZTISzhNxUl7HjrZWr2vodT30Fq2MBY0MRsXMPRlJYjydzt0aSOY0kTRxNGjsQNzMaMzEQNG0LKvyb0/C17rzaqkv5cACpAT0HPowL0FPSLaKNKz1oIedLjG4LKCvSshZ088DwFep4EOc+aH3raG/Uzv7H/jPbWZMxEPOSgL5zCEzuFLX0bc/oBtvQD7Kl72NOLmOLXMUSvY4hdQzNyBWXoAorgeTSRS2hGzqMOnEM1cAqZ/whS3yxS/wwiZ4o2W5wW2wgtjlHaXSnEfScxRL7AmryDM7OELbGEObaAKXoXS+wWptFbmOJ3sacfYs98i2/yT/gmfsCT/R5n+jvsie+wRL/Flfwj7sS32GPL+SqPZXQRw8gdTJF72CLLWCP3MYZuY4vdwz66hGboGqqBL7BE7+JILuIeu481toAxchd1+C49A1/Q3X8V8eBn9AxeortvjjbPCVocR2h3ziJyTNNiSlOvT1CtGOaQ2M+BLjcHRVYOd1pylZwuK/vbdOxt0bG7ScenLQYOdFiolfmpk/dSK/Ozt8PB/g4Hh8U+Wg0RuhwZOh3jdHmOrFR5TiLpO4vIcZR22yyNhnEa9FmaLFN0eU4h7b+EbOAykt5LdLtOI7ZNoTe48OkUZDU1zOtruKhrICutQ/7pu1S/sY3yYgHFxeWUFAvZUiLkpdJiXq0sY+9Hv0MracJtkpIKqJmM65gaVedbpNMrIedVHx+1/KxJw58LOBst7vy5ftI05k+1lgvQU9DzqAA9Bf0i2jjILM87E5aRCct+1P7aCITWQs9aZ0JKxoIKxoKKFfjJHXPt7xmPKBiPKJiIKvP3J0dUG3oirGQirNzwe1ORjaFmKpLzuuOsfj+iWRde3shTMR0TUXU+V5EMGBkMRPCEZ3BmbmNNPsCauocrex/PxDLGkRtoRr5CP3oDXewassBFZIGLqCKX0UY/Qx28gGpoDuXQWVTD51AHTqMYmEXin6TTnaLZHqPZlqDNNYW0/xy60EXMkS+xRm5hGbmJZeQmxthNTKM3MY3ewpFewp1dxjf9Xb4NZhl9iC32eyyRr7GPfosj/nsciW9wpJaxJ+9jGV1EF7qFPnQXS/QBjtGHuOMPcSYeoA3eQOy7TI/vAtrAl+hDX2EIf4Vm+AuUQ1eRDX5Bj+8CPf7zdPfNIe4/R6f/BM22CepMKZosKdotceqUQxyW9OZgp8vJgU5HrsrTYeKQyMzuBg276tXsatTyaYuBqk4bNWIXNT0eDokcHBI52N/polYVpFk/itg1SZdjGpFjmm73EWR9p5ENnKWn/zQNpiyNhnGaDJO0WI7SaT+F2Hsesf8ikt5LSHznkdpmUJlG6dMbSOmamdTVcM5Qw1ljI5OSOoz736P53W1UlAjZvLmU0iIBQqEQYXERws2b2CYs4sPXX+HQJx9ikNcR8ssJ9UrJRgxkwwamo1qmIhpmI1qORXUcj+kfTUyNqpkZVTM9qsw/tgoy60LGK35qPm2D0P2qJyKa/Ot9KqJmOqphOvrkY/1U9edJJxYF6CnoeVSAnoJ+ET0OPWMh+bqqy0YVn+eBnrHgxhWep1VunhR4/lszPxueuW7wwbHWk1Ftfo/Q1KiWZMDIQCCIb2QKV+Y6tvQDbOklnCs7e3Th63no0Y9+hTx4aR30qMIXUQzNoQqcRxWcRxuaRzmUy/pI/BN0erKI3Bna7BN0eY8j7T+DavgSuuCX6ILXchAycg19+Ev0ka+wJhZym6HHHuJMP8y1oSL3MYwsYQrfxxb7Glt8GVviPs70MrbkIsboLVRD19CHb2OOLuFKfo0nuYwjsYQueA2Z7zxS7zzqwctohj5DM3AZZf955P0XUfRfRuKZo8d9hh7fGcTeU3S6jtBsytBgTNFoStCkH6FKkqvuHOjMAcyhThuHOizsa9VzoEXPrno1uxs07FsBnmqpm2pp7vn7RXb2i+xUSfy0GEfpsGUQe6bpdM7Q5ZpF7D+ObOAs8sFz9PSfps6Ypk6fpME0QbvzNN3uOSS+C4j9F+n2X6TTN4/KmsJsDBDQaRjXNjOlq+O0oZZT+kamJA1YD71H+/vbqCgtYtNmISWbi3Mj7CVCyoUCtgg289rWct7+7cu0Vu3ArGzCZWojEdAzNWpnJm5jKmJiMqRjMqzNeQN4WQWbn2pBPTVbswo9T6ncPMuxfgp4CtBT0P8OFaCnoF9Ea5cTPq29tTbv80TwCSmfCXqelBFaO7a++ib8tEmvx8finwY3G4/TK9b/3ArgrAtih7X5+5mQMgdAET2poIm+wX584Qzusc+xji1gSS7hGPsaR+YhhvhN1OFraEa+whC/iSbyBcrQFZThz1CPfoEy+jmy8GXUkc9zHrmEduQiusgljCOX0YfPow6cpqd3hh7/LF3uo4g9p5H551H0XUA9eBnVwAVUAxcQ959DHriMeuRLdCNfoQtfzzl0E93IHSyj93IZnegS9tEl7OlFzPHbaEJfIu29gnroJrrgHcwjixiGb6Duv0qP8xwS7zlk/nnk/nNIV/IyXa5Zul3H6XGdRGQ+SrtxljbdBM3aFI2aOI3qERrVYRpUIWokfg522NnXauFAm4mD7WYOt5s52Gpgb6OGT+tV7GvScrDVSE2njTZFP02Kfmplfg6InBzq8VIt7UVkiSP2z9LjO4rYf4xu71F6fMeQD55DPngOSd9p2p1HqTenqTMlaLHNIPFcRjb4OdLez+lyX6TNfZ5a52n05mH69DamVD2cUtZwXF/FlK6OaU0r09J2fPUfoNhZyZYtv2ZT8WaExUUISoVsKS+jsqKcyopytlSUsKWihJcrKvjozd9yYOf7qHoa6HdriPSpSQS1jEXUZKNqJuIqxtcARR6q/9bA/aj6R+2tp7WsnhRCfpRPWx9q/jn5uQL0FPQ8KkBPQb+IHg8yPw43q4897g3hZyW78zjwPA49Gx3j8eWHj1dffgQjT/DjFZq1lZoftaxWtz+vHDuzgcfDWrIhDeNhLWPBXDVrckTNWMBA/0AfvkCa3swN3GNLWBJ3sI/dx5F5gGNiGUPiDproDfSJWxhTd9DFb6IMXUEV/QJl5CrK6BfoEtfRxr9CPXIVTeQLTPHr2JN3MMevYYh9hiF6Hk3oLJrhORR955B6zyBdmVJS9M+hGDhLh3uWbt8J5IPnkA1eQD50EfnQRWQDl1APXUUfvIEpvIAxfA9rbBlP9htsiSWMkTsoB79EMfAlst4vkXiuIHGep8c+R5f9DBLPHBLvObqcJ+iwH6HFPE6dNkGdKk6zZowWdZoWdZpGZYwaaZAqySAHu3up6vZxSORkX5OOQ21Gajqt1Pc4qOowc6BFz556FXvqVRxo1VItslAtslIlclDb7aZB7Ke2y8O+Vit10n5adGGknlwrS+SaycFO/xkUA2dRDM3R7TuVAx7TFPWWcRqsE3Q6jqPpv4Jq6Bqy/q/o9n1Gl2eeFtsMdoOfhE7NSWUrZxQHOak7wLi2lnF1I1OKZgItOzDu285LW3+NsERAWWkxm0uLEAhyba7iEgElpbnKT4WgnC0lZbxYXsHvXn2ZvZ+8R0fDhxhVNQz7uogMScjElGQjGrKRRyAyFVEzHl07PaVkMqb6kcdjmh957d6ojfI8+XbUmtd9frnmqH7DnNrjJxgbLSN9HNIK0FPQ86oAPQX9IlqFnifBTTooIxWQPhF61k18PQV40gH5Iz8Felb3+KxCz1pwWTsV9viU2NqvnwQ+j38ITMR0jEe1ZCMaxsIaMiPavLMRHdmILg892ZAmDz3TIxLGwiqGhvx4Awm8qS/xji1hS97EmV3AllnEnv0ac3oxBz6x6+gTt9AnbqGOfZmHHs3oNfTJG+gS19FEvshDj3VsAUvqBsbEF5iTn2OJX8GauIox8hnawCVUg+eR+s8g6TuNtO8kne5Zur1HkfSeQNE/h3JgHtXg+dxt/3k0Q5+hHrqKJnQLQ3QBW2IJbfgayuHPkQ1cRj5wBYn/M0SOM3TZT9FpO0GX4zgS10mk7pOI3Ufodk3TZkxTqwxRKwvRJB+hWRamSRqiTjJEVXcvh7v87G93s6/Vyt4WM/ub9VR1mKnptFLTZeZQu579LRr21Kv4tEHNgVYthzstVHXaqBI5ONxh51CXO+ceH036EdotcSTeGXo8R+l2H0XqP4ly8BzKwXMoBs7S5TpOq2Waw7osDdZZWmzHEXvOoh/8DFX/l4j7ryHyXaLbfQ6RMcOg3sS0vpvT6mZOqw5xXF/FpLaWSXUDU8oGQm07sRx8lVe2FVMqFLClTEBxaRGbiorYXFxMkUBAaWkplaVlVJTmoKdCWMLWMiGvbC/nw7dfou7wRyjF1Zi0zfS5JQT7ZIQHFCTDWrJRPeMxA+NR7ZoKkJKpDbwh9EQN6+E9pmFiNHesbFRNJqJibES54ev98anEx6tCT9rA/viC0AL0FPSvoQL0FPSL6O9eeIGxoILUsCzvtYCSfzwgzftJlZ+ntrQeB5+AfH3OZ3XCK6RkLKz6UcVlLKzKOx1Skl553kZ+/PkbfZ2N5D4k0mHFyrE0jIV1jIV1K+CT+70TQW3u7wqqmYwYSI/ImIx2MxlXEAg4sfeGcI5+hTu1iC31FfbUl1iT19CnFzCPLWBK30Ud/QpV5Brq6FcYkrfRjt5AO3oDQ/wmpmTO2uiXqMKfo49fwzm5iGNiAWv2Jq7JOzgnbuOZXsA9dRfX5B3s2ZvoYleQDc8h6T9Fp3OGbvsU3fYpehzTSN1HkHuPofAdR+HL3XY7T9DpOo3YN4e49wwdrmO022YROY7S4z2O2HuMFnMWkW2Sbvsk7YYUbfok7cYE3eYkXaYEraoADWI/dd1e6rvd1He6qGm3U9Vm52CzhX1NZvY2mvi0wcS+JjPVIgtVHQYOtmrZ06Bgb5OKT5vV7GnRsadFx74WA3tbjRxot3Gww87+Nhv7O91USftotyTpcc/Q7Zmlx3MUuf8ESv8JlH2nUPbnql4S7ynaLLM0GSap0oxTY5ujxXUebd8cmt5LyHxXaO39knbPBWTOIxg0Q4zrujlnrOeMtppj6npO6WuYVdcwo6llWlNPpH0XvoNv8uo2IVuLBAiKf82WMgGC0lyVZ3NxMWUlJVQIS6gsy+3xqSwrpbKslHKhgDJBMZVlpbz+ym9476032fPJDpob9tDZfgidqgm/s4dBn5yRIQWJkJqxiJqJuJrpERUzETUT4ZUqTVSdA5mIJv96HY/qmRjRMzGSg/HV12l2VEU2rmQsJicdkZMeUeZfv7mf0/7IExHNhi2tx4Fno/bz6s8UoKeg51EBegr6RfR3L7yQh5vkkPSZoOeJ4PMEyHkW6FkLPmuh53GgWQWep4HPajth1avVnNXjPf7zmZFc/uLHb/xyJsIrZ94RNVNRY26CKyZhIqagt9+GwdmPJfw51tgCuvhNzMnrWJI30SdvY0rfxZJZxJC8jSpyDeXIl+jiNzGm7mBM3cGUvI0xcQNjIjfhpYtdw5i8jmNiAff0Eu6ZRfqPL+OZXsA1eQfX5B18s/fwzd7DM72Adew65vgXqANzSDxH6XJM024Zp9WUybtJn6JeE6dZnaBZHqNJHqFNHadDm6Rdk6BVFaNDPUq7IkyDLECjMkyjKkSdfJjDXX4OdXo43OniUJudfY0G9jcZc27Ws79Zz74GLbvrVOyoUfBJrZI9zfpc1UZkZX+bgT0NCnbWSvm4RsauBhWfNmvZ22pkT1tuJ8/OJgO7mkx82mqlqttHgypEsyFGhy1Dpyt3tXSx9xgy33Fk3hMoe08j859B4j1Fhy0HPE2GSVptR2h1zSPyXEDuv4DEewmR9wrt3kvInLOYbKP0a4xM69o5a6jjlLaa45o6TulrOKKp5YgmBz3Rtl34D73Fq9uEVG4uzkNPcYmAImExm4qKKBUKKRfkrs9VLhSwpbSEreVlbC0vo2Il8LzqihIh27YW8/L2Ut56cyv7dv2Ow/vepbN5F0ZlLQ5jM8PeHqL9MuJDKjIjBiaiRsaj+tzrdUTJ2IhyXQB6OpqbzlqdcsxEFYxF5I/8E9CTXa18/kzoeXxwoAA9BT2PCtBT0C+iv3vhhTzwrELPWvD5OdDzONRsBDc/BT1jQcUTYeZx4HnS8/KVnMegZy345J73qKIzFpGTjcjIRmRMRuX5FsPEiJzJaA5+MkEN2bCK2ZiSTESFx2tGbfFhGr6U210zehtD8jaW9F30iVuY0nexZu9hySyiiV3PQ89qBcicupOHHkP8OsbEDSxjt3BOLuKaurcOehzjt/IVn1XwcU7cxpm5iS35BYbwRXTB80j9J+iwT9FmnaBOm+CAPMw+cYAacZAG0QC1bV5q2300dQ/Q1D1Ag8hPY2cvzZ291Ik8VHV6OChys6/Nwd4WC582m9nXaGBvo5bdNUr21mvYW69hV62SnTUKPqmW80m1jE/qFOxqULG3zcDBTgv7O0zsblTzSZ2MHbVSPqlVsqtRy55mPbtbDexqNrKjQcfuFhO7Wix82u6gWtpHoy5CmymJyD6Rq2C5jyDxHUfqeQQ9Eu8pul3HaTJM0qAbp8U0TbfrJGLvfG5ay3eZdvdlml1f0Oq+gMY+htM8SFSj5Ji+hbOGOk7rajipreW0oZZj6hz0zKjXQ8/aSs9G0FNStJkyQTEVJcJ8taeiRPgjl5cJKC8vZlulgNdeqeDN31byyQe/oeHwB7TX70QlrsJpbsdr62GkX0c6bGIiZmYybsq/ZnOgoWA2rmFmVM1UVMlkdOW1GVUyGVHkVzlkwoqf/D+YiGh+8nIwG0HPWhegp6DnUQF6CvpF9MILL5AckpIYlJAYlPwIfJ4EPRvBzyo4bQRPzwI9+edsADfP4sfBZz3gPDrzffS9XJYnG1aRGZEyHpEwHpEwEZGt7A5SMRnR53YHRbVkQyYyQSPpkJohnxiFooeWLiU6z1EMgWuoE4toU0uYx5Ywpm9hHlvAPnEf59QypvRdDCvVH/NYrvVlSd/FnLqFOXUL69gdbJm72Mfv4phYwJa9g33iNt6ZRTzTC+uqPWtbXp7pBbyTd+mdXWTw6BJ9s0u4srewJq+hGJqjw3OCTtcROkxJGsS9HG53srfRzL4mS64VVadnT62OT2u17KnVsbNen3ONlp21GnbXqdhVI2dntYydh3vYXS1hd7WEjw518dEhMR8cFrOzVsqnzWr2tWrZ3aJmZ5OSHQ1y3j8s5cNqOTvqVOxuNLCzycAnDQY+qtfzUb2eDxv07O/yUC3rp1Y+TIN2hGZjgjZLZmUPz1HE3uOIfSeQeU+g8J1B7DlJq3mGRv1EHnja7SeQ+c6j8c8h952nw/8FzZ4r1Luu0mE7jtPYT0iv54SulfOGOuaN9ZzR13JaV8MZQ8M66Im176bv4Fv89qVSthULEQo2rYOe1fZWuUDIltKSvFerOqu3lWWlj6o/peWUlZZTWlqarwBtKS1iW4WQl7YKef03FXz4wet88vGb1B7eiayzGqOqhYBHRjJoyAHQqJGpUS1jYQljYQnjYVkOyCOK3MVERzRMhVRMBlfayk84Acj/H4Q3zu9sBD1PWihagJ6CnkcF6CnoF9Eq9MQHxMQHxOvAZ23bKzks+UnoWQWnx4/xJMDZCIDSATmpvxF8NsrxpEPKHx0vFVTknR5Wkg7IyYTEZFc+ULIjynyGIh00EB9WMDqooN/SjUleh7J7P/VV7/LBB2/x9gd76NGEMQxcRJtYRJVcwpC+jyF1M1/pcU4tY5+4j218CfPYQh5+7Nl7WNK3saRvY88u4BhfxD5+F1v2DtbMbWzjt3BP3cU3e4/+48v0Hr2fhyD31F38sw/oO/YgX/3pP77M4Mmv88/1TC9gH7+LZ3oBS/QC3Z4s7fYkLaYILYYwjdoA1Ype9ve42Ntu5eNGPR/VavmoWs37+2V8cFDGjioZu2rk7KqVsqdGyt5aCbtrxHxS3cPuRmXen9TJ+LBWwntV3bxd1ck7Vd18WKtmZ6ORXU0mdjeb2dlo5OMGAztbrHza4WRvl4dqxSDNhhjt5hTdrklEzik6XdOIvceReE8h8Z6ix3MSqS/X1up0HKVem6VamaJRP0GH4yTdnrOIvefR+c6i9s3T7rtOi/8LRO6zKMwJhnU6xrUirhkOc8VUzXlTA2cNdZwx1HBG37gOeuLtu+k/9DZvvFzOi4ISSoSb12V6ioVCyktLqRCWUFGSA5+1sLMKQKXFRZQWF1FStJmSolKEgjJKhOWUl5SxpaSMUqGQ0pUMUJlwM6UlRZSWFFFRWsRL24r53W/LObz7LWTt+zEq6hl0ikgGlGRjSjLRNeskVlZATAQUTAbVTIU0G8J/Lqy/5vEnbEh/VujJhBUF6CnouVSAnoJ+ET1e6UkMSjas9CSHJeu8EQA9Dj2PV3zywBNQMRZQ5YBjWElqSJH/fmJYRnIFfFLhjeEmE1KSDitIhRXrQCYPPiOrAJR7o0+HFfnAcjIgzx13ZOUDYOVvmQg/mlLJjKhJh7SMBlQMuSQ49G1YVM1IWg7QcuAjqne9y1tvVbLtpQpe+e1bSNX96AePok3eQZ26jy55D9PoLQypu5hSC1gzSzjHH+CaWMY6vpALMSdv45pYxpa5i3XsDpb0bWyZHPBYxu9gH7+LfeJ2DnqmFug9ej9v/5ElvDOL9B5dou/YA3qPLNN39CEDx37P4Inf03f0If7ZB3im7uGZXMI9uYgx+TldQ8fo6J+lu28WkW8KkWeCFluCWn2YQ5ohdnU62dFo5MMaDe8fUvDeQRkfVcnYuQI9u2ol7K6TsrNWyo5aKTsa5HxcL+WjWjnvHRbz9qEe3jkszrlGykeNBj5ptrCzxcquNis7Wi3saLGyS+ThgHSAGkWQas0ILdYsHc5pujxHEDlnETlnkfhOI/efQ+Y7i8R9FlnvKWS9J2mzTFOlSFKlTtNomaFnZZdQl+8MGs8ZlN4LtPReo8N7hU7XaczmIUY1PRzRNnHLeIDPzTVcNtVzVt/AGV3u9qSmjuOaOo6o6xnt2EN/9bv8bnsZLwpKEBYXUVYizENPkUBAeWkpZSUllAoFlAoFlAhyk15lJcK8SwTFuS3OxUVsEVawRVhBubCC0uIySovLEAgE67ypKDchVlz0K0oFv2ZL2SbefqWC/Tveov7Ah8ja99Pr6CY80MNoQMlYWEc2qicVVpIJyBgfljMdVjMb1TAelj1qB4cVZCKqXGh/HfirGA/L8l7bGlvdkJ4dUTIWUK2bwFybvStAT0HPowL0FPSLaG2m53HoWZv1+TnQ81Ntrg3H2NdkiFbBJw8/q1WZkHrFK2/cT4CiR9CjykNPKqjKezysZTKiJxPV5OAnoiY7YiY1pGN0QE2frQe9vBGpqIr6wzvY+cFv+fCt3/Dm9gre2FrOS9uK2bb117yypYh3X34FvcKKxz+FJ3ENY+oO+uRtNInbubDySjvLklnEmr2HNXsvF2ZO3MIxvoQ9u4B1LJftMadu5So82Ts4JhZwTCzgnLiNa/IOjvGbuKfurIDOfQZOLOcBqO/4N/Se/D3e41/jW7H32ENcs/exji9gnbiLcew6mvhVNLEryEfP5xydRx45izxylp6h03R5p2kzjFKnGGRvq509LZZchaZBw+5GNXsbNexqULGrIRdcfv+gmHf2dfHWvi7ePSjm/cNSdtSp2NmsZVeLnl1tVva0O9grcnGop59qeYBaxQi16ij1mjiN+lGazGO0u6cReY7Q6c4Bj8hxFIn3DMr+86gHLqDsm0fqO02X6ziN+ilqtRM0GKbpcp5C2nseSd8F2r3ziF1n6XbP0eE7T4/zCDprjJBBx0ltM3P6Bi4aarlkquWCsY55QyNz+gbmDY2c0tZzXFPHMXU9SdGnDFa9y5svl/Hi6uUnSorYJCxmk7CYYqFww/bW2jbXatVn1ZWlZZSXluZhaS0wrVpYXEyJIHdfULQZ4eZNFG/6f6hYaYO98do29u56h8bqnWhlTQy5lUQHDWQiFrIjZjIjhlyrNqIjHdKtC+mvBaBUSJ73RgtGc/dXLxGzfmnp4/u7CtBT0POoAD0F/SJ6fHprLaj8XOjZCHY2GoPfCHo2en7yMT+Cn/VtqsdbV6sTL48C0GoSASmJgDR35rtS8k8Nywj3ihhytWJTNCBp3Utb/Q4+/fg13n5jG6+9UsGLlWX5kOrW0jJeLq1gW3kZL20t441tFex447fYdHr6+2P405exZG5gytzCnH4EOfkMT2YRx9QytvElTMnbmJK3cU7cw55dwJy6hS1zNw87q/DjnV7KBZYnbuGeuoP/yL089PQde5Cr/pz8Gv/J3+M78Q2+E9/gOfYQ15EHOGaWcM7exzGzhHViEWP6LprRG2hi19HErqONfokuehXD6JeoRz9HGTqP2DNNhzVFnXKIWsUgVZJe9rSa2dGg48NqOR9UyXj/kJx39kt5f7+M9/fLeO+gnI9rNOyo17OnxcLediv72u3s7/RRJR+iVhWkURehXhulThOhXp+g2ZKh3TFFq2OKVtcMHa4juSume07R7T2N1DeXs3cehf88Ys9p2q1HqNVOUG+aotV6DKl3HnHvBbp7cxNbHe45mt0XaHWcQ2RMY9D4GVN187m+lquGOs7pazlvqOOCsZ55Yz3zhkbOG5s4pa3npKaOE6oc9PRX56Bnm0BA8eZNCAWb+FXxZn5VvJnNq3BSVExpcdGPAGcjbxMWsU1YRKWwiG2lAl4sIeVGYwAAIABJREFUE+bH3VdbY2WCYsoFwnVgVCwUUiTIWVAspKSkhK0VQt58/SWq9r2PqGkPNkMLoV4po0E5Y9HcJFcq9PjJwqPqTjKgJBlY+T95ysWE17a41i4pXdvWLkBPQc+jAvQU9Ivo7154gWRATmJYRnxISnxISmKl2rL69eig5JmgZ0NvAD1rW1ur7a3V3/c0+MmfpYYfAc+Ge35GlOvAJx1SP/oQCKlJDKuIDcgZcohw6uowyQ7TfOA99nz0Kh+/8yKvvihgW/kmtpRtYmt5GS9VbmF75Va2b6nk5fJKXiorp3JLKa9uLWHn716hT6ckOjRMX/J8DnjGFrCnF7GNL2GfuI8ls5iv+DimlnFOLWNJ38UYu4E9u5BvcTnGc1NbjvFFLGO38tDjmsiFmN1Td3OVnWMP8tmd/uPL9J/8mr5T39B76lv8J77BNXsf58wS9qlFHNMLOKbvYZ9awpxZRJ+8jTF+G0P8JrrYdXSRLzBEr6KKXUG9Aj0iW5pa1TDVsn4Oir3sbDTyYa2a9w7KeO+QhHf2S3jrUwkfHlbzUZWGj2p0fFJvZFejmd2tNvZ2ONnf6eaQZJAqVYRaXZRGU4J6wyh1ujj1hhTNtgk6XEdocc7Q4jhCm+sY3b5TSHrPIfHPI/PPI/HMIXafQ+qdp8t5ghbTNPX6NK32WUSuE3T3XqDHdwGxdx6F/wJt3nmaPefpsh5HqQ3hUlmZ1LTxuaGGK4Y65vW1nNc3cMFYz0VTA+dNDcwZmzitrefUCvTERZ/SV/0ur28vY1uxkOLNmygp2sxmQRGbBbkWlKCoiJLNRRRt2oSgqAjhari5tJTy0hLKS0vWtbq2CQRsEwioFAjYKhSyVShct9+nsqw0XwkqFQrzVZ9ioRBBSSnCkgoEJaW5xYiCTVSWC3jr9a3s/OBV2ht3YtM30usUERtWkAytQP9KSH/dycFKfm0sDzzSNZbnLyWzzmEFyaAsf9KQCEhJBmUkC9BT0HOqAD0F/SJ64YUXSAzLGB2UMDooITYgzt9f/Tra30NiSLzO8cEfP/Y06FkLPvEhJYlhVd6jg4r871ptjyUG1wNWIiAlERTnHJKQXDnrzATkZIMKskEF4yEl4ytl/FXoSYeUpIMaon4lQbcUp16EuPUQbTWfsvuDN3ntxUp+U1nOi+W5M/BtpQJeKi/hxdJSXiorY3t5OS9vreTlrZVsr9zC9sotvLytnJKtm3h7+69pfv8lztokXBxwMRo5hTG5gCl9D2vyLo7MA5yTX2MZW0IXv4MufgfN6M3cRNfEfcyJG5ji1zEnbuDMLuCeuId7chFH5m7O2Vy2xz29hGfmft6+I8v0HvuagePf0HfsAUOnvmHo1DcMnHjI4Mmv6Tv2AP+RpZVlhrdxTS/gnl3GOr2EeXIRQ+Y6muRVVPErKGLnkYbOIA2cQjF0kg77GI3GCHvFPnY0m/ioXs+7h+W8c0jG+4elfLRa6TmgYEejiV0tVva0Otkv8nKgy0+NbIh6ZYh6VZQGfYpG0xiNpjGajVO0WGdz+3TsJ2hxnKLdeYpW1wlanMdpd51A7D+LxD+P2DdHt/scYtccYtccLZbTNBpnaDCM0e7IIO07inTgNKLhy4g880hcc0jdl2jxzdHmPonVFGREp2Ta0MK8uZrL5houGOs5r2vkvL6Bi8YmLpoamDM1cMbUxLy2gXltA6c0jcS69uKve59XtpdTWVxC8ebNlG4uyrWgSnLZm82bN1NUVERJSUk+k1NcXJy7Lyz+kXNtq1ylprS0lNLS0jwQrUJS6dqc0GoIWiCgTFhK+UrwWVhcRGVJKRUCIRVCAZXCIrZvKeHdN19j786P6WxrRKfooM8lY3RATmJopcITkpMMSUiFuhmLdJONiclEu0mOdJEM95AMiR+1vAIqxgJqxgLqHCQFZcSH5IwO5m6TASWZES2jgwXoKej5VICegn4RPQl64kNSYgPivB+v9Kw6MSR+es7nsXH3+LCC0SE58WFFvoKTGM6VzrNBOZMjKrIhKZnhHlLDXaSHe0gO95AKiHNnnEExyZCY+HAue5Qezm1Lzoa0ZMI60kENyYCGaL+csE9Gv7UTVecBOmo+oubTN3n/jUpe2Spge3kRW0qKqSgrZUt5GS+WCfN+qbyE7RWlvLyljFe2lPHyljJ+U1nO9orS3O22cioqS3jjpWJadrzCaWsb1wbsRCPTWBJ3MCfuYU/ewb1yxXXL2BKG5AK6+B3Uo7cxpe9hH3+Ae+IeluRNLMmbWFO3cGYXcI0v4hlfxJldyHlyEefMYm5Z4fQSrql7uKbu4TuyjO/IMv6jDxk+9QcCZ75l+PTvGT79+3wVyDuziHvqDp7Ze7hmHmCbuI8lew9D+gbaxBdo41dQReaQDh1H5JuiyRqnWhvkkGKAnW12PmzQ816thncOK3nnsJJ3Dyn4uEbNJ3U6djfZ2NPqZG+HhwNdvVRLh6iRBmlQx2jVJWjWJag3jdFgmaLJkgOedscx2p2naHOdod11LnfrPkub+zTtnjN0+ufo8Z+nyztHp/MsIscZRI4zNOqPcViRpU6Tods1SY/vKJ3+EzR5L9DimKfdfg6F4zQixzQqSxKf0ckxdRdn9I2cN9ZwyVzFBVMt8/omPjc287mpkXlzI2fMuUrPeV0jF7QNnFI3EBbtwVX7Dq9XVuQmtIo3ISjOVWBKVuBm1Y+HkZ/kkg2cm95a60eh6NUA9FqvhqUrhAK2lOSgp6y4iJLNv6Jk86+oKC3m1Ze38vZvX+LQ7rfpadmNuucwfmsHkQEFowEVyZCceFBMPNRDKixlLCInPbLyP7Xyv5walJAelJMelDM2pGBsSEFqSJGDoCE1Y8MaMkEN8f4C9BT0fCpAT0G/iNZCzyrgrAWgn4Ken+vVlll+OmwFhsaGpbkplLCMiZCUbEBMJiQmPdxDaqg7B1cr2aJ0cKXSE1SRCqhJBzWkQzqSwzoifiX9djFmVSPq7ip6mj9l34evsvudl3n/9S28WlnMFuGvqBD8mnLB5jz0vFRess5Pgp5Xtlbw8rZyyrcI+d12Ae27fss5Wztf9FlIhLPY4zewJhZwpO7mocc+dh9TahF94i66+B1M6Xs4Jx/im36ANXUrDz6OzF1c44u4x+/nqz2uqXs4pu/lgcc5uYhzchHPzH28sw/wHVlm6OS3BM/+geDZHPysVn1ym5tzLTH3bG5s3pK9izF5HUP8KvrRK2hG5ujpnaHZluKwepj90l4+7fHycbOFDxt1vF+n5f0aTd476/XsbrKwr8PD3g4v+zv9VImHqVNGqFdFadLGadYlaDIk89DTbJ2m1XaENsdJ2p2naHedo8M9R4d7DpF3jjbXGVqdpxF55+j2zdPpOUe77RTNpmM0GY9Sq56hTjtNq3kGmf8YEt8JujynaLCfp8l+nlb7HDLHMWSmGFb9MGG9mTOaDs7p6rlorOGSqZoLxjrOGXLQc9XclIeeeVPzOugJdezGUf1WHnq2CDbnoadUKFwHPc9q4Qb+MQQ9HXpWXS4opmIFfsoFxZQW/ZqSzb/Kt71erBTw5qsV7PngFar3voVUdACHsQOvvYtwn4zYsILRgJJkUJVvKef+p1ZWTwxJGBuWrlhGJiBnbFBJZkhFekBJekDJ2KCSRK+0AD0FPZcK0FPQL6IXXnghn9t5Xuh5vN21kZPDErIBMdmAmPGAjOywlGz+TVZKNignG5STCeTegFODubPP5KCc9LCK9HBuxDwZ0BAdVhPsU+CydGDWtCDrqKK56hMO7fmAj956ldde2sLLW8rYItjM1uJiKgUCtpWX5QOkFaXFlAg3UyLczEvlJby8Ajgb+TeV5WzfUsIr28p5ZWsFZeVC3ny5DNHu3zFn7+Bqn5bJoSDe0Ys4kjdwphbxjt/HM7GMI3sfy9g9zOl76BN3MaYWsY8v45l+iC2ziCV9F1PyNvbsPdxTy3inv8E6toA5dQd7diEHOxM5O8YXcYwv4py4h3vqPp7pBwwc/yZX7Tn9HcGzf8hXe1ZH3HNVn+XcxVDTtzGNfolh5DKG8EVUAydotSSpUYfY0+3hkw4HO9rtfNBs5qNmU85NZj5qMvNJs4XdrU72ibwc6B7MWTJMvSaeu+SFcYwGfZom4xgt5nFabDO0Oo7R7jpBp+csPf7ziP0X6en9jO6+K4j7riAduEqn9yId7jm6fBfo8szT7jhDvXGWWs0ktZpJGvSzKPyX0A5dQjc0n8v4eOaptl6gzjFHk+s03fYUHo2ZkFrFtFrMBW09V3Q1XDZWMW+q5ZypjrP6Fq6aWjaEnou6Rk6q6hlu/QTroTd4raIsDz1CQVm+0iNYU+0pKip6Jgs28I8h6JHXQo6gaHPexZs3Ifj1JkqLivNTYmWCYkqKf01J8a8pL9lMeclmtpQWsbVcwEuVpbz+8hY+fu+37NnxNm0Ne9Gr2rAYRAx6VcT79cQHtCSH1CSGFStVWXGuqhroJjXUTWpQQmpAlqv4DEpID+VayulBeQF6CnouFaCnoF9Eq9CzFnAez/PEBn4aZlZzPo87Odi17uv0YCfZwW6yg91khiR5p1Z3/AzIiPdLifZLiPdLSQ0pSQ+pGe1TEfDIGHL04NK0oJPW0NO+j7qqD9iz47e8/85LvP6bCrZvEbC1rJStJeVsEZRTISinsmQL5cVllBWV5s+qy0qEVG4ppaxCQEWFIFfV2VrBbyrLfwQ7q/e3bynhtW2lvFpZTnl5OW9sr6Bt1+84Z2/jWp+CE/8/e2/13faBrX/nHWjj2BbLdqDcaQc6ncK004YdTszMDLLFlszMzHYSQ0yJg2a243AZ06bTgbPe3935B87Nuf28F19JkRU5zUzPeXPx017rWXVkgTtr6nzWs5+9tzYTY3ErWZXDaGpn0TTMom5YQNUwT5oVfKqFjc0p1bOk18ySUjlFcsUkiWXXyKidI6thEU3zChm1c8K19apJ2+JCK/hk1s+gapglu2kedfMChvYlTF2rmLvXyOtdx9S1Sk7nCrpWYaxd17pAVv0MqeWXSS25SHz+MJHG04RqO/FLrcY3poC9IUb+7J/F2ycz+NMpQW/5ZfLWqSzePqXmXX8t7wcZ+CBEAJ0PgnP5IDSfPRFFHEms4URaI8dS6jmSWM+J9Db8VJ2E6QcIzxkmKneMuMKLJJVcI6lsmoTSGRJKZ4gvmSWueIqI3MuE5owTbBzDL7uPE+k9HEpq5ZSqlwD1WSKNw8TmjBBj6Cc0qxv/zF4CsgY4mt6Pf3o7Iel1RCfmUBt1ktbYI5yLOsGlhANcSjjAaPJ++pMPcjbpEH3xxxhJOMJI4iHOJPrSk+S7AXo6Iw9iOvYmKR++yE6xcGrC6vRYHZl/FXi2OQEcZ06PPfRYwcceeKzQ47nVDZHbNtv0mNh9G2KPrTZJRcJEmdhDJLyv2zbbfbBd25W8/trL/PH3v+HwvneI9j9IfPAR1AkB5KnDKTZGU2aKpCz3YXC50hwmtL3ygigxHafEdJzyvFNUFQS5oMdVP6tc0OOqp1L/LvQ4CzI7g55KU+AGAKrK8afGGECNMYjqnGCqc4Kpsu4IMoZRYgylSBdCkS6EEl0wJfpwinVh5GYGkx53nJTIQ4QdfZfDH/6WP/9xF6++JGPXdnd8FG7IJVuRidyEsKe7BJm7DIWnAm+JNzJ3GRIPKWIPEZ4iIZQqk3oiV4pRKoW2lVX20LPdCj0KMTtlD6FHJpPx0nYZx996iTPpJ7hkCKdbk0pOYQPqynNoaqfRNMyibZzbAD1ptfOk1MyRUj1LatW0DXgSSq+SXjNLVsMi2c0rZNQvWDY2C5Nd6bVTm0NPm53TY4EeY8cyutYFtC3zaFvmyaiZJLXkIslFY0SbBgjVduGf2czR+FL2RZjZHaTnLwHZvHMqk3dOZfK2v4q3/bJ5x1/NnwN0vBdoZHdYHnvC8/kwrIAPQgvYHV7I3shijiTVCtCTLOR3AtU9hGj7iM09T0LRFZJKrpFSNklm9RyZtUukVS+RWrVMatUySeULRBdcs4FPgGaAE5mnOZHRTaR5lLjCiyQUXCRaO0i4upeAtDb807sJVPVzMv0sIalNRKZUkBCrpj3yMN0xBxiLOspE4n4uJ+63QI/vptBjzfRYnZ7NoMcKK/8q8DhCj7N8jzPoEXm4O4Ue8TZ3RG7C9Jiw7dlN2OjssRWJp5sAPWKxAD3uwiSYxN0DibvgDPl4Kdnuo+C3L/lw4N3fceSDN4n020dW/CkM6cEUGaIoyQmj1Bxiy81V5gZTVRBEcc5RinIOUWI6RmWBvwt6XPWzygU9rnoq5Qg9Vsix/3OxwQFmjM4B5xEZg6nMEZ5rbX9Vm0OpM0dSawqj0hKSrDBHUayPpEAXgVkTjj4zCG1aEBkJx4j0343/kXfZ++5veOOV7fz2BSW75NvwEj8jSLoVhehZpJ5bkVp2nYg9PW2bb8XuEtvqf7nI0rKwLJLzkkkFqFHK2OHE5bHP9OxQiNklF/OC3JOdcgVSiYLnfJQc+tPLnE0+ypTBj7O6SPKNeaQV9qKuu4yucQptk+D2ZNYukF49R1rtEqnVC6RUzZNWPUNS+YQNeqzbm1WNy2Q1LaNqXCKtZtpyl2uazPo5shqFtphVmpZljO0r5HavU9Bzg7yeG5i7rmPqXEPfuoSmeY6shmmSyy8TnT9CdP4IYcbT+Ge1cDyljv1RBXwQksNfQgx8GKJjd4iGD0I0vB+i5b0QA++HGtkdUcC+mBJ8Eyo5GFeJb1wNh+PrOZxQx9GkBo5ntHMqq4uTqk6CtH3EFI2TWHaN9KppMqpmUdXMk1W3SnbjOtmNN8lquEFq1SrJ5SvEFc8RkXeNkJxLBOjOE2wcIyz3PIll18iqmyOrbp7kksuEq7oJSGvlaGIjfhk9hGSdJiKzjaQEM+q4NApi/eiJPci5+H0Mxx9gMu4glxJ8GUry5WyyL31JBxlO8GU4QRhX700QdDb5KAPxAvh0Rh4k5+gfSXhvF17iZ5B6iJBv88TD89Gcjtu/AD/OMzzOg8z22R57x8fdbaugrcL7WV/nbNGh2FNow3laJsas4/AyiXAF3poHkonc8JZ6CC2w13fx3psvcGTfG4QH7SYu6gCZScfIyQggXxtIqTmEkjx/inP9KM0PoKLAlelx1c8rF/S46qnU46DHCjxF+kBKjf4WBT4qQ9CjsnyvzBhMqTGQEkMA5YZAqs1hVOWEU24Mo1AXglkdhDY9gPTYE8SF+xIesJej+//I/r/8ljd/t4MXd4jZoRTGc6WeHsg8RXhL5PiIZXiLpCg9RXiJxHiJhOWBSrFw5FEhtmR3xO4opB7IxNuErIPIHR+xB9vFYnxEIrw9PfEWubPTElx2KoVYgB6FJ88rPHleKkcq2YG33Ifdr7/AmeQDzBuPM6YPJC8rkyRjM4lVF9A0XMPYPIOxaYnMunmSa2ZIq14ipXKB5Ip5UqpnSa4Ssj5JdkqtnUfdsoam9TqqxiXSLQsOU2tnyGiYJ7NxgazmJTQty+jaVm3Qk997k4KeG+R3r5PfvU5u55pwkqJ5geSyq0TkjRKZP0JU3jCB+m78sls5nFzBvpgCdkeb2RNpZH9UjqBIE7sjc9kTlY9vUjVH0hs5oWrnWGYHp7K6CFCfIUjTS4j+NOE5Q0TlXyCm8CLJFZNkNiyR3bBMdsMqqrplVLUrqGrWyGq4QVb9TTJrbhBXtEh0/hwR5mnCTROEma4SlTdJUskcqdULGNrX0beskF0/T1zBKKHqdgJUrZzKbMIvq40AVQsRyZUYohOoiTzBcNxuelL+Qm/yXxiLPcBArC+DccLG5TOJvgwkHmQs4SDnE30ZSfK13N46xOnkowwmHBXaW+F70R/6PdHv7MDb8xlk7iKUHg/351gzPZ6enhuyPT8l+xyPFXocQch+r49E9Og0lxV6tj3jjuc2oX1llS3vs80NT3dhvF4iFQuye0+5xEPYCySWIJNINgCRVOKBQuqBl9KdXbskvPSCgj/97nkOvvdHTu1/h5igfaQnHEGdfpw8Ywi5Olemx1U/r1zQ46qnUk8CPcV2EPNY6Nn0OQIwleUEUW4Mo9IQTrE2CEP6SVQJR4kL28vJw29xcPfrvPPmLl57RcHLL0jY6bMNhWwrMvGzyEXuiD1ESDzFKERyFJ4y5B5SvEUPpRCJkXs+PAUg2P1uyKVC60shccdb4skOqYidMjE7pVJBMvFDR0cusU1uOULPc0oRLyhF7LJAj5fMmw9fe57epP3M5JxkTONPUWYayfo6kirOo2m4irFlFkPzMpl180J7q3qJpPI5ksrnSK2ZI7V23qbk6lmSLBCU3byKtm1daHXVzZJaPUV67YzN7VE7QI+pc43c7nVyu9fJszg+eT03yOlYRd+6RErVJBEF54ksGiO6cIwwUz8h+h5OqerxTSplb2weu6NM+MbmcjA6l4PR+eyPLeJAXBnHMxo5pW7HX9eLn6aXAN0ZQg2DhBr7iTQNElN4kaTyCVIqp8ioX0TTeh1N63XUzetk168JLk+dxeWpv0lG9TqxhQuE50wTZp4msmCGmMIZksoXSKteIrN+BV37OtpWAXri84cJyW7DX9WKv6qV45ltnEpvJDI2n9zwCJoijnA14UN6U96nO/l9hmP20xcn7OU5G3+IvkRfzlmhJ+kgo8nCY2cSDtOXcoyBhMMMxh2iM3wvOt/fE/mn7fh4uiHzFGBaIpFYHBVP274dz39hkutxAWYr/DhCjxV8HKHH7dfbcN+6DZG7pw16rK6Qde+PTCIAj1S80QWSS4Rsj0IsQeQpxtNDhMhTbLsALxJ7IpW6I5W6I5d7sstbwevPPcebLz/P7rde48TBPxFy6i+kxh0nPSHQBT2u+lnlgh5XPZXasmULZTkRlBrDKTGEUawP3QA7Vgiq0IdTrgulXBdKmS5YyNvogm2wU5YTRKnpFKU5foIsrlBFTjilhiAKNEHkqkLIiDtFTPAxTh5+nw/eeZ23//Air7/ozYs7ZTznI8ZLLjgzCqkHCom78Iva8svadt/IQ5BcJH7o6Ig8hYvVFkk9Hl6+Vso88ZKK8JKK8JZJ8ZHL8JHL2CGTsVMuZ6dcjrdMjLdMapP9c4SvhVDzCwoJCrkSpdSb5xUK9ry+i/akI0zkBHJVd5Lq5GAykzVoSrvQNUygbZknvXGZ9LoFMqvnyKhZJLV6gdTqBdLq50mrnye9YYGM+gVSqmdIqpwisXSC1KppMmrn0DQuomtZRNe8jLZpCU3j4iPStS1j6FjF0LGKsXMdU/dNzD23yO29jb5zHU3bKun1c8JW6MqrJJaNE5k/QHjOGYK17ZxMr+dIcjUH40s4mljOoYQKDsVXcjy1Fj9VEyG6DsIM3USYzxCV20903jmickeJKjhPTNE4qVXTZDUto25ZRdt2HW3HOrqOm+g7bpJZv0JG3TLaphtomm+T1XCD5LJlYgsXiMlfIK5slaSaNVJqVsmuX0PTto6m8wbZXeuk1M4SX3aNCMNZTqY1cDylg+Op7QQnlBEVayA3KpjWaF/OxO7jfPwBBhL20Jewj3OxvgzF7+Nc3AEG4w8ymHCAwYQDDCfsZzjxACNJwimKgYTDDCYdZzBJcH96Ivah3vsHQn+3A4XnNiSewiJADzvgscrDaYtKACJHSTaRs9fby9MOmNzd3ARo2ubhNCMktlx/f7jZ+SFIWc9hiD0Fp8dbLkMhk9l+PrFIYluaKPb0RCwRIZFa2mGegoPqLZOy01vGi7u8+e2rL/D6yy+4oMdVP6tc0OOqp1JbtmyhRBdCqV6Ylio3hgmZHUtbyqpyXSil2iBKtP4Uak9RrA2iWBdAod6fIkMARYYASnP8KDL6UWoKptwcQZEuhFxVCJnRh4g4/h6nDrzNu79/iVde2MFz2xV4yTxRSNw3SC62LA20/KJ2dtTR/q6R/ZFHK+RY/6mQiFFKxHhJJRvkDG7sH7N/3Ecmx0cuEzYxyyU85y3DS+mNXObFS0oxh994jrbU41zIj2BBH0Bj0kk0cRHoTc0YGiZQNy2T3rhKRu0cGTXzgmpXyKxbFYCnTlBa7RzpNcJEV2rVNEnlEyRXTqBuWEDfskJO+3Vy2q+ja162wY6QeZnDYIEeXdsy+vYVdG2rqFtXULetktWyQnbrKlnNS2Q1zpFZO0VK5WWi86zQ08GpzCYBfJKqOJZcy4nUevwyBNiJyOkhNr+PuIIBYgoGiM7vJyZ/iOi888QWXSKh7AoZtXOoW1bRtK6h67iJsfsOhu5bAgC1XUfXfgNjxz2b06OqvUl23V3U9feIq7xFUvk6qup18lvukddzD9Ppu2S0rRBZME6YcQj/9G4OZbbim9FCUHw1WVEZ5EbG0Rt9iHOx+xiI38/ZhIMMxh9kKP4gw/EHGEp4VMOJBxlK2sNg0h6G4w4yHHeEs4lHOZd8iKHkg/RF7iPrwz/g9+pOdoiENpanyONhTswKNnag4Syj4wg3jsdG/1XocXdzY9vWrbYsz2b5IPvPc/wcwU0SIZdKUcrlyKXSDZDk7OeVSYQ2mP3zZBIJcqkUuVTqgh5X/axyQY+rnkpt2bKFMl0w5YYgKozCTpyN01gBgvSBFOv9KdL5UaTzo0DrT4HWn0K9PwU6PwoNgZSZQygyBlGoD8ak8icr/gjJEb6EHH6LA++8zPu/f57f7FSww0uKl8wTmchNmLaSuKOUCAAkE7kh89z2xNBjhRzH69bW20aPA55/B3p2eUlRKryQyxT8xlvKiTdfpCP9JON5ESwZg2hKPIkmJhStoRZ97WU0jYukN66SWTdPZu2C8M/6FVQNq2Q0LgpTWnXzpFqAJ71m1hZwTq6cILt+Hl3zsg169C0raJuWhFH42llUtbOCE9S2bJOmZZms5iVUzUtkNi2hahb+nN00T3bDLCmVl4nK7Sc85wxBmnYb9BxNruZEaj2n0hsJym4jIqeHmLyzJBYPkVw6QnzxENH5/UTlDhJevzlVAAAgAElEQVRpHiW6YJz40suk18yS3bwiOD3tN8jpuYux+w669nWMXbcx9dzF1PUxuta76FruoW26h6bhIzQNHxNTfp2Uypvo6m5T2vkZ5ac/I7/3IzKblogynydUO4h/RheHMps5kt5AdGwhOZFJlEZG0hclQM+5+P30PyH0DCfvZTBpDyPxvk6hJ+OD33Pi1R0boEfmKXIKPT8dTnYOQY7As9lrRR4eNqfHHnp+CracQY/1+3KpFIVMhlwqfQRoHKHHCjku6HHV/0a5oMdVT6WEK+uBVJoDqDD5b6pi0ymKc/wozvGnyBhIkTGIIkMIJnUA2rQTaFJOkp0aSELkYSIC9+C7+w+8+8ZzvPHKdp73FuEjcUPpsRUvsQdeUpEAOWIPFGKPh19L3B9OYdlBjDPosQcd++cqJGKUUgleMineFphxBjtPDD128paJ2a6Q4i33QSoW88ddckLf/w1nNYFMFUaxbA6lM8UPU7Q/Gel6dGUDaOqmyGxcFkbRG5dQNyyiaVpF3bJGVssKqsYlMhsWSa2ZJaN2jsy6eVT1C6RWCUsLVbXC9JeueRlz5w3MnTcwtK6ibliwOT3ZDbOomxfQtCyibl4gq3GBjIZ5UutmSaufJ6NxkazmJdTNC2Q3zJJccUkAHm0XfqpmTmY0ciKtjmMpNfhnNhOkaSfKfIb4wkGSSoZJrRgnveoSSaUXiMgdJFh/lmDDOaLyLxBXfJn06jmymlaEHFL7DXK6P8Lc+wn5Zz+hqP9Livq/xNT1KYb2jzB2fIy68TapFaskl66RUH0dY/snVPR8TfPAj9Sf/Y6izs9JLV8kXHue0MwhAtK7OZleT0hyMcaIaLrDT9IfdZTxmAOMxB5gOO6gU8h5BHgSDwonKZL3MhLvy0jcEQYSjzGcfIiRpIOcjthLyge/4/ArPmyXWG5leT4KPbYW108sHLS2n55sI7NzSLK+3t3NDU9390dgxBlMbQZZEpFoA7RYnRx7sHGEHmuI25kD5IIeV/2cckGPq55KCZmejQsErSHmQl0A+Ro/8jUBmDUC3GQlHiMx8gAxQfuI8NvNiQPvcPD9N9j7zm/50+9e5rUXt/PyLm98FGIL1AiQIheJkYsE58UeeOQid5sePua5YbTcEXY2ZHfs3B0r8HjLZfgo5Jbr6PJNgedfgZ7tCrkw4q5U4C33QbzNjfdeVpJ04A1GjCHMFEWzkBvKucwAquP8USfGo89vQ1c1TnbzCtkty2hbBZdG376Gtu066rY1NK1rqFtWyWxYJLNuXmiDWVtdtTNk1syQUT1Ndv08Oe3XMXfeIKf9OtqmJXTNywIANc7ZFhiqGmZRNczboCelVgCf1NoZUqqukVx+mZjCEYJ13fhltXEqswn/rBaC1K0EZrcQrO0gRNdJhPkMcfmDxBcNk1R6gaSScWGKyjBIiH6AcPMo8WXXSK6aRtO0ir79Nvr22xi77mHu/ZT8s19Qeu4bCs58QU7nJ2iab5PdeBNV/TpJZYvEF8+RULyA4fQnVI18S93Q99T1/Yi54yuyGj8iomiGAPUQAZl9BCc0kRhtQB2ZSn3kEcZiP+B83IeMxO9jMNqXoVhfRhP2P+LwnIvfvwF4hhMPci51P0NpBxhLPMxYwjGGk08wlnKY0WRfuiP2EPv+a+x5SYm3xNN2GNT6F/+/Cj1WoLH/3pO4RPZwYQUW63tIxeINbo1j+2wz6HGEGSv4ODo+js+zf09HGHJBj6t+Trmgx1VPpbZs2WK3kDDMogiK9KGYs/zRp51Al3qclOgjRAXsIfTEXzi69032vv07PnzzNd569UV+99xOXtvpzfPeCsEJkQlwoxALYWOZWIpMLEUhlqLw8LABjlLiaZP1MQGABEhSSAQ5ujvWTbT20CMXizY4PNuVCkEKuRPH5iHYOPt6M+ixvq9S6oXUzY29r/uQceQtxkxhzBRFM2sOYUwdRHNyAPrEKDSmetRlw0Lrp20JbesSupZFDB3XMXRcR9N+3ZZ7yW5eIbNu3tbeEtpgc6hqZ0mvmkJVO4uhddUGPfqWFYxta5g7b6BrWSS9dsqmjLpZ0upmSa6ZJql6muSaGZKqJkkou0Ri6UWi8ocI0nbhn92On0pwdkJ1HYRo2wnWdhCo7SDE0E1Ubj+xBeeIKxglrmCUCNMw4TnDRJhGiCu+TFrtHFlNy+R03MHU/RE5XffI6f4Yc++n5J35nPzTn2Nov4u66RZp1SukVa+QWrVMYtk8aVWr6BrvUDjyNTUXvqVu5FvKe75D1/wZKTW3CM2fxE91hpMpHURGl2AIS6YkLJzOqH2MJr7HSNL7DCTs42yMAD3n4/cznLDfqcMzYgkqjyT5MpR2gOH0g5xPOsJ44nHGUk5yPvUIo8m+dEbsIfLPr/LeC3K8pCLL1JYnMonkJ4PGj4MaZ6Hjx7XDHPM0EpHI9hmOLSorjNgDkjMHyBFYNmtzOYOezbJJLuhx1c8pF/S46qnUli1bKDSEY84OwZAeSFbCSZIjfIkL2kfIkT9z7MM/cPi93/He71/mjZd38vouH172UvC83Ivn5V7skCrwEcvwEstskGKVTCL8MlbIZCjlctsvWYVYtCFgrJSILYAkLE6zfl8plWyAHqu7Y4Uee+BRSMQ24LG6PBvkpF3lI5dYprYEecmkwntYoMc6uWWDIrkMhUyKRCxF5r6Vk+++hDHkA87nhzBTEsqMOZILuiBGswPJiQ9AlZ1LdmE32pZ5stuWyGxdFjYlty2j77iBrn0dXecN9F030XfcQNW4RKolyJzVsIi6eYns+nkya2ZQ1c6ibVrC2LaGsW0NfcsKuV03KTh9i/zTN8humiejbpqk6mskVU2SWDlBXPlVYsuuEl8xQULFNRLLL5NQMk5U/hAh+tMEajoJ1nQSouskzNBOsLYd/6wWTqqa8ctqI8R4lnDzgA12oszniSsStiuraucwtt8kt/sjCk5/irnnY0zdH2HovEtO1z30bXfIbrxJauUKiWWLAuhUr5BRu4au9TYFZ76geuxv1F75jsqLX1E+8jV5nV+QUXeH1KpVQo0jhKTWEByXT2ZoEt0Bpzgbepi+hPcZSn2PvpT3aU/cTU/cfs7FHeBCwkFGEoQ212DCAUaSfBlNPsRYymHOpx6xaSTzGOezjnAl7QRXk09xMdWPC6nHOJ96hLbwPQS8+wp/eF6Ct0IAA6lI8ojTY996epJMz+NyPo4uij3EWGX9LI9t2xB5eNj+e7JCj1X2kOQso2P9vthTADn7/yYdwcf6OkcQs293uaDHVT+nXNDjqqdSW7ZsITxwDycPvcuhPW/wwVuv8KfXnuP3L/nwso+U52Qidkk92SWRsEMiebjbxjLqvV0qtQsJi22j4V5SEQqpJzI7SSUeSCUPL0TbX4yWizxRiEUbQscKidhpS8sKPFbYsW9rWaHHWy7bAEHb7eTM9dm07WX/XKkMuUiMeKsnPmJ3Yg+9SVXSIaaLwpkvCWfOFMlVcyjXckIoTDxGcryKJE0D6oZFDG3CWYjcrlV07Uto2lbRtF/H0HkTQ+dNdO3CTp6shkVU9QtkNy6hbV3B0LqKpnHRlusxtK5iaF1F37KCufMGBadvUXj2FoaOVbStS6gaZkmpmSapapLY0stEl1wmtuwqiZUTpFRdI6XiCjFFQ4QaegnSdhGs7SBI00ZAVjN+qiZOZjXhr2klxNhFZP4AMYUjxBaME51/kfiiSZLLZkmvmCO7bhFj+03MXXcwd91D334bXett1C03yWpaR9V4ncy6G6RXr5FRc53shlvkdH5CXu8XlJ37nprzP1J94Ufqxr+nevgbKga+Qd/8GUlli0TnXyQss4HshDRyoiNpDD3OUMQ+zkXvYTBuL70J79Ob8AE9CXs5m3iAAYubM5p8iOHkQ4wmH+J86hEupB1lPP0YlzJPcFl1ksuqk4zrTnBRf5yJTD8m0wKYUAVzKf0446lHaQvfjd/bL/K7XR74KIVTIxKxdMNf/o+bvnIMDf8rsoKHPXAoZMJoufVx6xSXdQLL3oFylr+xd37sAepx0OPYIrMfh3d8Dxf0uOrnlAt6XPVUasuWLez+8+u89fsX+MOrO3n1OQUveit4TiFlu1iMl7snym3CBuMdEgnbpcKphu1KCT4KMd5yEV4yT7xknvhIRfjYQY+XVIRc7olM5mFbeiaVutugR+K+zQY+ju6PPfTYuztW8LFvaW0ILlvkJZPaHvdRyNlhaXX9u9DjLZPiLZUJbY1n3Ngu3UbyyXdpSj/BQmkUS6URzJkimcoLZS4vhNLEwyTGpBKvqiazbh5NyyKa5jnM3Wvo2+fRtq5sgB5t23W0LatomldQNy2jbhIWD5o61m0TW7rmZfQtKzaZOoRlhIVnb2HqXsfYuSaAT9Mi6fVzxJdfJab0CnHl10ioEIAnsfQikfkDhOh7CNR2EKztEBweVROnMhsJ0LYRmtNNVGE/ieXnSSwbJ7boErGFV4krnCChaIak0hmyahfQt66T03GLnI476NpuoW25hbrpBpkNa6gabqBpvou68Tb6prvkdH5G3ukvKTz7NWXn7lM99leqz/9A3egDqvrvU3H6Prr6T4nPmyJCN0h4Yj4F0RHURJ5gIGo/5+P/wlDCbgbiDtAV9wE9sbs5G7+XgcSDDCYJ5yZGUg4zknKYsZTDXEg7ysWM41zKPMGVrFNczfbjmtqfi/qTXDKc4JrKn6n0QCazg7mccYLxtCO0he/m1Dsv8rtdIrwUcmQyGVLLaLenp6ftrINIJHq40+YnoGezVpGj02MFD3tosbagrKCxbetW3J59dsPjVihxdGF+DvQ4G3V3bLm5oMdVP7dc0OOqp1JbtmzBR+aJQuSGQuSGUuSOt1iCj0TKdqmM7ZaTDwqxhw1ulHJ3vJTuKBXbUMjdUFqksExmCUsAxXjJBSllgutjk6VlZe/SWGXfHrPu4LFCj32Gx35Ky5kcYcja5rIHI+v2ZesGZseMj49chlIm3OhSSqTIpHJ+tdWNbc/8mtd9xJhC99CrDWK2PJb5smim8+KYyAtnPi+MxqQTpISFk5hiRF1/hayOZdJblzH1rqJvt+zWsQCPvuMG+rbrG6RtWUXXtkpu103MnTcwdaxjbFtD17y8AX6sx0Zzuq5j7FyzwM86urZV0upmSaqeFsbha2eEo6OVV4krHiPSPECY8TThxh5C9V2E6DoJ1XcRW3CO5LLzpFZdIaXiCsllV0kouUZCySTxRZPEFlwjsXQKTfMKutY1YXNy8zraphvomm9iaLmLof0jTJ2fUXTmPvm9X5Hf+xWFA/cp7P+Kwv4vKRv+muoL31N3/lsqzt2nsOdr8tu/JL14kaiUTqKjCtAEh9EedpD+sD1ciP0zw8kfMJi4VzgrEbuPvph9DMXtZyTpIMPJhxhOOsyF1GOMpx3nUtoJLmWc5ErWKa6p/ZnQBDCpDWRSG8iEPpCrBn+mNKHMZIcyoQngcuZxLmQeozFiD4f/+BK/2SHDW7YRCJy5N5uNjj+J0+P4XMcWk2NbWCGTCVfe3dwQe3puyPTYw5W96+OsXWbfClPK5U539jgCkGMeyJXpcdX/RLmgx1VPpbZs2SLAjGWM3PpPq6wAoxBLUEqEv/y9pDIUUjlyiQylRV5i2Qa3xUsmRe4AMfYgYwUXe+ixvt4xvPy4wLL1szYDHpvk4kdkPS+xXS4SvracnbBlfORi4X8DmTDl4imTs+XZbYh/tQXfV3zoTjjBlZxIZopimaqIZLI4kSu5kczlxtKTGY05xI/MqDjyagbQdVwnrWUd45k1DB3z5HatkttzB2PXLQydNzF23Nggfdt19O1r5HbdJL/nNgW9d2yuj75l5WGbq3UJY8cyxs41DB2r6NtXUDcv2cbW0+vmyahfQNUwj7pxDnX9DOnVEySVjBNfNEpc3hDR5j5i8/uJzhsgqWScpNIrxBVeJDLvPFH5F0gouUZS2SQJZdMklE+QUTuHuUdYPqhpvY6u5QbGtjuYOz6hsOcryvu/p2LgAZVDf6Nk4HsKB76jYPArSkbuUzF2n+oL31F5/huaL3xFYf9XZLV8RFr1GuGqARIjVehCgukIe4/h6LcYi/kTI7Efci5mP0NRBzkXs5+RGF9GYg8wknCQ0URfRhMOcSH1GFcyTjGR6cdEVgAT6kAmswOZUgcxrQm2aUodxBVtEFO6CGa0EVzKPskl1VHOq45THbKHD197gecUgqvnJZUJ/58XC4dqZZ4iYdO3RU/azvqp3T3201RWwLECj1XeSiUyicS2rFAhk+GtVKKUyze8jyOkOO7ZsX/c+t4KmWwDDFmBajPYsYKVC3pc9XPKBT2ueiq1ZcuWDe0oe+jZkM9xgBNHwHB0bBxdG3vosbo8zp6vlEqc7uKxhyQr8Gzm8tj/XEqp5BHY8ZFL8HF2VNTytY/c8hqZFIVMitISyvaUy/jls1sR/2oLx17bTne6PxfNEcyXxjFXGsdUaTxTubFM5cYxrosmP+wk6ugoDEVd6NtXyGhdRd2+TE7XEqauVZvTY5Wx6xbGrluYum4JBzfbrmPqWCev+xZ53bco6L1DbtdNctqv26DH2LaGqXONnM4VISTdskhm/RxpNcKen4TyCZKrpkmunCC5/DLplVdJLb9MUukF4otGiTQPEJXTT2xuP/H5w8TmjxBXKLS0ovPGiC4YJ7F0gpSKaVIrZ0itmSOzYRF9+xqG9nVMnbeFMHPvZxSd+YKy/vuUnfuBssEHVPZ/T9XAAyrPPaB0+Aeqzv9AzfgDai/+QNXYAxqHH2Do/Zr0yhtk5F8lOa0CU3Q0lVEn6I78gP7oDzkXs5vB2P2Mxu5lJGYP/dF7hYWEsfsYSTjIeOpRLqUf52qmH1cyTnE104/JbAF4rKAzow2xaUobzKQ6hAlNKJPaMK6o/LisOsr5jMNUhu5m96vP86pSjpdEikIsAIPCAj1SD08k7h42/TuLCDdbJmgPO46ygolULLbt7JGKxTZoeZwr8zjZf4Y9HFkBzBGaHEHNBT2u+jnlgh5XPZXasmXLIwFkK/TYHA/po62ozQDDGfTY79qxfx/H93BsaTlzd54EeB7RE0LPToWUnQqpMNWlkNimtbykwkK3bRIxv/z1r/Fx/yWR7/6GIW0o1wpjWSiLZ640jrnyRGbyopk3RzFljqQmwQ9jTAgZ2SXktC+g67lJetMSho5VzD03yOm8ibn7Nubu2+T13iX/9D3yeu9i7r4tOD5ta7bdPAW9dyjp+5iiM/fI675lCzMbWlcF6OlYxdixjLphgeTKCRLKrhBbdImY4svElV4lrvgy8UUXSSy5TFLZJeILx4jOHSLCJGxYTigcIrV0nPiCC8QVXhRyPAXjRBeMk1ByjeTyKTJrl1A3r2PovEXemY8o6f+ciqGvqRz9nvLh+5Sdu0/50HeUDn5HWf99Ks5+Q93QD9SP/o2m8b/TePEfNFz4J3UX/oOKwb9T2vdX1I23SdGdJSO1FH14AM0xB+iN28NA3IeciTnAmZgDnI3xZSB6D4NRuxmK2ctwvODyXEw7xrUsPyay/ZnWBNtgx+ruzGhDmNWFbpA99ExoQrmceYrLqqOMpR+iJOA93n9xBy/JJDanRyET3B5nTs9mDoqjHgczSrkcL4XCJnv3xeq42O/TEXl4sG3rVkQeHja3ZjM356dkfV/7FpfV7XGUC3pc9T9dLuhx1VOpLVu2bBjdtocf+8cc3ZnN3B5HWZ0bq5y2nuygx5m7Yw0jO4aUN7g5Du+3IdT8BNCzUymxQc92hRQf5cPPtELPVnc3tj37C16VPYvm8NtcMUczXRLHbEks86UJzJUnspgfzVJeJEtFEQxogqlNCSA7KQNT7QXyu5fIal5C07qGsXPdtmE5t+smBb13KOi9Q37PbXK7btoyPMa2NZvbU3z2I0r6Pqbw9F3bgkJt0xKmjnXMXdcxdQqj7Om1MyRXTJJQepW40msklE+SXDUtbHmunCKl/Box+eeJMA0TZRomrmCUpJJx0iqukFB8mYTiyySVXCO+6BKxRZdILp8io2YRQ9stcns+pbj/a6rGHlBz4a/UXfwbdRf/RsXId5QNfUtx/9cU9X1FUd9XVJ37lurR76kceUDJ6AOKx36kZOzvFI/8E1PXt6hbviQ1Z4S0GDWGsFCawt5hLO4NLia+w7n4ffRE+dIT5cvZ2IMMxAjuznjyYS5nnOCq6hRTmkCmtUGC7FydWV0oc/owp5rRhzKtDdsAPRczDjOSepCCk2/z3gvbeUUhY7tcwXaFEi+FAm+Z3NbqUoglD/UYkHEmx+fZw85m4GMFDvtMjvX4qEQksgGL/fOeBHjssz72n2X/uP3WZhf0uOp/ulzQ46qnUj8FPbaTEU/g9DiDHnu3Z7Pwsf1rHe9n2QeRrRCzmbP0vwE9PkpLpkMi4Zltv0bk/kv+6O1Ovt8HTObFMltsgZ6SeGZLE1kujGWlIJrlknAu5ITRnhGIPiYOQ/Fpitqn0bUsom1ZxdAuTF7ldq+T13OD/N6bNuV1XRecG4vTY+pYt4FR8dmPNrg91vMUed23yO26ibFtDVX9Auk1syRXTJJYMUVK9SzpdQtk1MyTVjVLUulVYvIvEGkeJSZ3lPiCC6SUXSKt/BqJJQL4JJdOkFwmZHkyaubRNF0nt/sjivq+onzoO2rO/0jN+I/UXfo7teM/2qCnqP9LCvq+oGTwa6rHvqVi7D7Fo9+RP/aAwgt/o+jCPygafoCm+TaplStkZtShi4iiIPQI3eFvcT7uT1xIfJf+uH2cjjpAX/QBBmP329ydS+nHmdIEMqUJZFYfwowumGltEFPqoA3AM28IZ94Q/gj0zBrCmNGFM6EJ5Zo6hEsZJ23Qk3/iLd5/cQevKuXsUCjZrlDirVTiI1fgZZ/xsehJocfZ2YfH5XfsAcn++Vb4cHdz2xBodgxAPwn4/FSg+XHQY32OC3pc9XPKBT2ueiplDz2OLS77r58EeJy1sZxNaD0Oepzdz3J0eZy9p/372r/WSyYVJrB+Anp2eUmdQs8ObzkKkfBL/pmtv0ApfYb9r3pRH3WIuaJ4ZovjmCqOYa4klunieJaLE1gpimO+JJKZ/EhGDGHkRYWiyizGVNZHbquwWdnQvk5h703yu9fJ714nr+u6Tab2lYeyAI9VRWfuUdr/CeWDn1F4+i7mzhvk99ym8PRdm1tkDUKrm5ZRNS6T1bSCqnGZjPpFUqpniS+8TEz+BWLyL5BQfJmUkqtC26v0KqkVk6RXTZNdt4iuaRVdy3XMXfcoPPMZlcP3KR96QOngd5Se+57KMSGnUzH6PeUj31E2fJ+iga8oGPyCspFvqLr8PUXj98m78ADz+R8pGP87xed/oKD7Fmm5g8RkNWIIj6I+fB9tUR8wHPUeA7F/oT9mN92R+zkXs58L8Xu4murLNZXg7kxqA5k3htlkhZ7J7EAb7FgBZzPomdVHMKEJ5Wp2MBfTT3Ax4zDDKQfIPfYm772w3QY9PnLBdfGWyR+Cjp3T46wN5Ez2uR77aS9nQWZ7GHJ0h6zvZz1A6rFt2yPuzr8KPdZsjzNnyRF6HOWCHlf9nHJBj6ueSjmDno3TW5a9OQ5TUY7Znc1gxxmcOMv8OGZ97J2an5rS2gykbI8/zumRyR46PZbdQz5yGTuUCnYoFfgoBOgRe3qwdesveO05OcFvv8zZ1ACWimOZL45iqiSKyZI4FkqimS9OYKYwgcncEJaLoriWF05jSijqRDUadTmm2gvkdixS2C0AjhV47OHH3LGKqWUJU8sSuR3r5HQK7S5z5w0KT9+lpO9jKoe+oPzcJ5T0fUxJ38c2B6jozL2H2aCuOxi7bpPTLezRUdWukFa5QHzZBHGlgoujqplHVTtHZs0sGdUz6FtWMbRcx9R+k7yee+T1fEz+6c8p6vuK0sFvKer7irzTX5J39mvKRh9QYdP3lI9+S9HQVxSOfE35+LfUXf2GivHvKL7wV3LP/4PCc1+T33MHU3Ef+pRs1BGJNIZ9wGDch/TH7udcgi8DcQcYiPVlKP4gV1KPMJVxnFm1P7P6EEGG4Ieyc3rs8zs2wLH82T7IPK0JZsoCPFeygriUIUxvjab5YjzyBu8+583LSjk7HFpacpH4kVzPZjt37N2Qx4WL7V0cZ3LmJDkuKhR5ePzbQWb7xYjO3B5Hh8rxZ3dBj6t+Trmgx1VPpazQs8HVsbt+bg89P+XwPA54nsQZ2mzJ4GZ5nX9ncutx0LNDIbT4BOgR5CMXtjCLPDx4Zusv+MPLPkR9+FvGskJZK4plriiSydJopkrjWSqOZaEwkemCeC6ZQ1ksCmWmIJw+dQyauExSU3LQFpwmt2WOgs5V8jvWKOxaF9R7k8Lem+T13MDUuYaxdQljq5DXMXXcsAWara5OSd/HlA18Smn/J5T2f0Lx2Y8t+oiivk8Enf2U/D5Bpu6PhMWBdaskV82QVjVLRs08uqZV9C2raBqX0DYtk9t526a8no8F6On5lMLTn1Pc/zV5vV9g6v6M3DNfUzT4HaXDP1Ax+oCyse8pGfmG0rFvKLz4HRWXv6f96rc0XfqBqgv/IG/o75g672KonUOfXU5BVChlIac4G/4u5+N2cy7uAAPxRxhKOMJo0mEBeFQnmcn2s8CO4NLMGUKZ0QcJ0gU7hR57WUHHOq4+oQ5kwgI8l1WBXEw/YYMew+E/8M4uL15SyNhu186yhx7HkXVnepJwsz3sOAaWN4MeewCxd3t+6vP/3RbX466xu6DHVT+3XNDjqqdSjtNb9tAjgI+wJdkRNOzbUdb8jbOFg86AxP5qun3A2Vlg2dneHWeLBp0937Gt5SW3Qs2j0LNDISwp9JFL2G7b4CwsKpSKxWzbtg33bVvY/4ddZBx5i0u6cFYLopkvjGC+Mp7psgSWS+KYL0pisiiJSwXClub1yhjmi1MojI8jJTSS2AQT2eVD5DRPkt+5Sn7XMvk9qxScXafozCBKe90AACAASURBVDqFp6+T17uOsWMZQ9syxvYVTG1rmDtWyeu6bltWmNN+HXP3bQrOfGQHPIIqBr+kYuhrqke/p2rsAdXnf6D03Dfkn/4cc/cnGNpuoW1et7Su7lDQc4+i0x+T332XvM57mNvvkNN6C33LLXTNN9E138TYdoe83s/I6fpUWDx49lvy+76hcOh7ike+p2TkPqWj31J/9Uc65v5fuqb/g54rP9I4/gOlo99h6v4Mbf4wmqxG8kKiaAn6kHMRf+Zi7J8Zid/HQKwvfYl+XMwIYDLLj0XtKRvszBiimNGFM6MPfej4WFweG/jYjabb7+Wxws5kdiATWQFcUflxReXHxcxTXM48xaX041zJOsZomi9q39/yx50KnpdJ8JHJbQFm+1bW42BmM8dmsxCxfRvJPitk1Wbvp5TLbYsKrW6PPfQ4CzU/bsmgVCy2Baudhac3kwt6XPVzygU9rnoqtWXLlkeWEW7M9Uhs0GMPPPYuzeMgZrPszr/q7jhze4TzEjK2W3M4tjad5JFAtr3s9/EIpymk+FgWFe70krPLy1tYtiiWIZPJcHNz49fP/Iqdkl+QcuB1ymIPciknkvmiGBZKorleHstceQKzpdFcK07kalECE3mRTBWEs1gWzY2qFC7mZ9GeEU/kiUDiUvPJzuuivH0Bc88yub0r5PVdp7RvnfK+G5T2rZPbvURO+wKmtnlMLQuYOpbJ7VwTprQ61tG3r2HsuiWMu3fdIa/rDoXddyk+8wnl/cLkVNXw99SN/kD92F+pOHefkr6vKDz9ObndH2HqvIu56x75vR+R3/sRud0fYWi7RXbDKln1K2TVrZLduG6Ttu02eWc+p6DvS4r7v6Xy3AMKzn1L/vB98ke/oeriDzRc+Rvt1/5Jz+W/0XbpH1Rf/D+Uj31D4Zk1tMVt6OKTKAgPpjlwP6MRe7gQ/QFjiYe5kHaKS5kBTOgimDNE2kLI84ZI5o1RzBujmDOEsmCwuDfW8LImkCltwAZN6zY+Nqnxt2lC7ce17FNcUZ3gSuZJrmYe51rGESZURxhLO0DWgdf47Q4FPjJLmFihQOYQFN4MepzBhD2EOD73EZBxAj328pIKW6J9vLzwViptMGV1fNzd3DbcyXKc+HJsvzmGkxUymQt6XPX/a7mgx1VPpazQ42xMXdDG9pazlpb168326jib8LK/jG5/Df1xLS3793o89Gxctugl83wi6NmplLDLW8FzXttRiuQoPRVIZDKeeeYZfvHL/4cX5b/EcOINahKPcN4UyUxxDIulMdwsi2WuLIbZ0iiulsRztTiR2YIopouiWSiPYb0qkZnSLPrV8cQePU5IWAZpqhqqmmcxdi5g6F7EdHqFotOrlJ+5Tlm/BXo65jG1zWNunsXctoS5c8UGPYYO4W6XqevWBugpOv0xZX1fUjHwNVXn7lM5+C1V5+5T3v81xWe/pPD05+T1fExutwA6eT33MHXeRt96E3XjGhk1i6RXLZJRvURm3SoZ9auoGq+jbbtN/tkvKDn3LeVD31E9/FfyB7/BNPg1eaNfUX3przRd+wddV/5Bx8Ufabz4DwrP/x/MZ+6hrbtIptaMMfIU1eGHOBu+hysx+7kYv58LqQFcVgm7deb0EcznRLCQE82cPopZfQTzhkgWjFEsWKBnWvfQ4bGHnkmN/yMAZA88VuiZzD7B1ayTXFOd4JrqBFOZR7mW6cto6n5UB17jtR1e+MgVyOVyZBbocRYQ3myXzU9Bj2Pr6HHQY50YswGPXIGPl5cNTqzQ4/bss7g9+yye7u6P3NpyhB4r+Ligx1VPu1zQ46qnUo4bma3tH3t48JaJnQKPMz3JWLrjVXR7h+eJnR6Z1AIt0g3QY5Wju2Mv++cJk1oStnuL2e4lY6ePQvhLTyRB5ilGJPbEY+uz/PLZX/De82Lygz+gLcOfa4XxzBdEsVQSzWJpDHMl0cyUxnOtJJ6pkiQmCmKYLY1moSKK25WJrJRnMVmUQVFMGEf2HeLYiVjSc7rIaZvB1LOIun2ekt4bVJy+RWnPGgVdy+R1LGBum8PcNo+pdQ5z2xKm9hWM7SsY29bQdwgLDnPabmBsXSe3/Sa5nbcp6P6Yot5PKTnzBcWnP6f49OcU9X5G4enPKTz9Ofm9QotL33oTbfM6qrpF0qvnSCqbJrFkmrjiKRJKZ0iumCeteomspnX0HXcpOfctFef/SunYj5j775PT/w05/d9Qfv4BTZf/Ruflv9M0/jdKxn+k6Px9ck6voTG1oEs1URYeSmvUKU7HH6M/5QgXMv25rApkQhPKtD6CGUMk86ZYi6sTKQCQFXiMUQ/37GhDbC6PI9T8lCbUfkxoTjKhOcG1LD8mVf5MZR3nWuZhhpP2kbbvN7zqI4yny+0yLs6cnied3PqpFpg1r2MPOBsgx7IvaLtCKUyROfxc1mWFbs8+a3N8nIGWY+bH8d9pswkuF/S46n+rXNDjqqdS1kyPPQzYA4T1e5ttWHZcPLhZsNgRhnwUcrYrFWxXKjaAzpO2uazQY/8zbyb75znTdoWU7Uoh9OyjsByaFImRenji6b4N0bO/wt3jl5x68zkak48waAhlsjieucJo5oujWCiJZqEkmtniOCYLY5kqTOBafjQzZTHMl8ewXhbFnep07tZlcakglfRThznywX6OBWaQVTWIuWsaY/cyJT03qe67R82ZjyjuXCOvY5G8jgXy2uYwNs+Q0zKLsXWJnLZlYSNz+xq61jWy6xfIrltEXb+ErmmVnNZb5HbcJb/rYwp7PqWg+xMKuj8ht/NTzB2foG+5RWbNMmlV86RUzJJUNk1y+RTxxRPEFlwjpnCC5Ip5VPVraJpvYu79lIK+L6kYfUDJ0APyBr7FcOZLCoe+p3z0R+ov/geNl/+Dhsv/oPz8d+QMfkpO7zJZxjKKYuOoCQviUpwfy+pwlvRhXNAGMKYLYionjGlTBLOWFta8UcjuTGvDmFKHMKMNY1YXzpw+whZMFqavAh+FHnXAk0njz6T2lLC5OSuAGfVJrmUeZihxL8kfvsIr3nK8pPL/Ueh5kpDydsuIvKO8Ldki69i81SWyv49lbXFZwcc60eUMbjZ73P5ncgwvu6DHVf8b5YIeVz2VskKPM4Cwf+ynoEchETsPEzuMlVuBZrtSwQ4vJTu8lBu2LD9prke4hi7eFHqs01dPAj32/47ectnDlobIE5H7s8jcfo1U9AwR771MZ/pxRnMimC6JY64okgWL0zNfHCXs7CmKY6owgenCWKbK4pirjOV6aSR3KhO5W5vOYnUmxfF+hPruZ+/hcFIL2jC3XqLg7HWKu29Qe/Zj6vs/paznBsVdKxR2LpLXNkdOy4wFfBYwti7ZTlDoW1bIqpsnq1YAH23jCsaWm+S03sLcfpfcjnvkdtzD3H4XY+s9DC130TSuk1a5QHLZLImlUySWTgkHRUsmSSyZJrFslsy6VfRtdzB1fUxh/1eUnPuWsuHvKBy4j7nva0xnv6B8+Aeqx/5G7fg/qbv6T2qu/Z2C4U/QNc+hrxnBmKGiIS6c3pggFrPDuGOO4aY5iqu6IC7pApk0hjJpFILK1nbWtDaMKU0ok9nBTGtCbeCzceT8Z0KPxl94/6xgZtX+TKiObIAeb5kChWUzsv0EkyPwbJbt+VehRymXs0PpxQ6l1wb4sQaprbLeArN/vdXtsYaarW2uzRydx/3M9jDlgh5X/W+XC3r+L66kpCR+/etf4+7ubtM///lP2/f/67/+i6ioKDw8PPDx8aG1tXXD6//zP/+T48ePs23bNl544QXGx8ef+LMdoWczl+RxB0StUGPv2tg/xzG346OQs8NLyU5vL3Z4KdmuVDzxOLoz6HHm7lihxz7zsxkA7ZAL25i95UKuQSKTIZaIEHm64eH2K3w8nuEFLw/Uh/7EoPoU46ZwZopjmC2OYq40irmSaOaKIpkrjmO2MI654iTmShK4UhzN1dIoVspiuFEay+3KRO41qblYkERtShgn9h4iIDyNVGM15WdXqD59h/qz92gc+Ii6wdtUD9yi9PQKRR3z5LXNYWiaxtA0h755AX3zApqmedQNC2ibltE1raJtXBFG0JvWLbqBtuE66rpVsqpXUVVfR1V9ncyaZQF4SoR2VnL5DMnlU6RWzqFpXEfbcgtT18fk9nxKXu9nFPZ/RdHA1xQNfE1B35fkD3xJ6fDXNI/9QNv5H6kf/4GC8S8wjd0hr2GYvNQySpK0DGWFMWmIYNYUy6w5hmVjNAt6YaHgvM6fSUMAk7oQpvWRTOsjmbKciJjWhjGtCbVpRhu2KfTYMjyWxzZIHfTIlfVpbZDwfHUIM9mhzGsDmco6znDiAZI/fIXf+HixXeGF0nLB3BECHAPC/8r+ncdtb3Z0d5xugLZMkdmfsLBeSBd5eNiOkXps2/ZIqPmnnCrrY/Zuj7Pskb1c0OOqn1Mu6Pm/uJKSkjCbzZt+PzExkcDAQP7rv/6LBw8eoFQqmZ+ft31///79ZGdn89///d/cvn0bDw8P7t+//0Sf/STQ49jecgY9XjLpI9BjH1a2trKcQY+92/NT+3kcoWezltaTQs92yxbmXUrL5melEolMhkjsiafHVjy2/pKdns/yko8I/fG3GdYFcDk3nOmiaGZLIpkrjWK2OIrZwggW7KBnvjSRy0VRXCmJZLkilnUL9HzcqGaxSsWgMYWwg4c5fDSYqBQTZd1z1PfdpaHvIxoG7tAwdJfaoduUn12jpEtwe/SNU+gbZ9E1z6FrmkfbOIemft62UFDXtIq+ec0GPdqG6zboyaxcJr1ihfQKYUFhUukMCcVTJJfNklY1b9nbs4ih9TaG9ruYuz/B2HEPQ/tdTD2fkHv6M/LOfE7emc/I6/+M8rFv6Lj44//X3ntHx1XfidvOG3BVGWmabLkBBpsSCMGAg2OwqaG5W7J616j3XqeqS25UYzAYDLhJllVH0qi6UkPC7i+7J+97kpzdzdm03XAWyOa38fP+cede3xmPZIFZnNjf55zPQZpRuyc55Mmnsvvgz3Ec+JislwdI3tNOfmUr9oRimmKT6S7YRm9xGD0lkRzN287xrG2SbORuoivnWdpzn+VY1kaOZW/jaE4Yh3M2SaPp2VvdoiOFJD5TS49yg0sVFwmPW3ras9fTnrmZ4xlb6MrecJH0LNAbFelR97n4kh7v3ThfJbujDnUvj/pjdVOzPMau10r/PZXvdAUFBirbnv3mzsVv7lyPpubpiI/8uVr0hPQI/jcR0nMNM5X0fP7558ycOZNPPvlEea2iooKNGzcC8Itf/ILrrruOP/zhD8r7kZGR5OXlTet3y8sJp+qLkTM96gksX9uQfe3LUY+Xq8VH/thbhr7KBXXvvp7Jeny8J7y8BWiBVsNCnY757v+n7R8chF+gP/P8ZjNvzgxu1gewcsVCajev4d3cDRwtDeNY+VY6KrfQUbGNjvLtdFRE0FsRQ29JDD3l0Zwoj+TtsjDeKQ+nsyaGkdp4RmvjGbWlM1KXR39tBpaoDTz90BqeeOxpTGV7aHhpiKa9I9S9PIxl7wC2/S7MLzuxPOekfFcPeU3tZNUfJbu+g9yGE2TWH8fkaCe9rovM+l4yHH1kNfSR0zhIbtMQec3D5DQOkd0wSKZjEJN1gBSzk/iqE8SUdxBT3kGSuQuTvY/0+n7S65xkt4yR2zZG7o5RTHVOkm29mBoGyGwZJmfXBIUvnKX85fewHPiYhnc+pfngp5hfcFJUu4eSUgdtuVl0lGTTXZrOWEUEfcWbOVawmYPZGzmcsYn2zM305G2jq2ALh/OelbI7OWG052xzLx8MUxqZpV6erRdlehSxyV4vRc4z0kSXavOyVBbb7PP4qPx6V84W+rK30Z72FPvj1hJ7/w3cbAwhVBeKwWDAqNdh0F2c7fG1tE/93mRX1X3Kjltc1Oct1CPq6qZm5eq7+vtUgiKfuJAbmuUy12SLC32V7rwzPZMJnJAeweUipOcaJi4ujqCgIIKCgrjjjjt48cUXlfc++ugjvvvd7/LXv/5Vee3w4cMsW7YMgPb2dpYuXerx85qamnj00Uen9bunXd7yHqn1IT1yVkeWHO/wlhxvGZJfVwuTt0B5Znqm7tfxzvhMlfWZr9MSopX+hT8nIJDZ/vOYO28WAfO+y71LQ3j2gdvZHf8k7cXb6CwPo718qxId5WEcr4iipzIWZ0UszsoY+muiOFoTzZGaGDprExg0p+Iyp+KypDNel8PpumyOlSWR/MzjPPXDH/H4U4mU17+F7bkeHK8OYn21H9trTupeG8L2Uj/Ve3opajlOdv1RshzHyHZ0kO5oJ81+jDTrcUw2qa8ns67fLTwuClpHKWgdoaB1lJzGIdJtTtIsTlJqe6Sw9JHuGCSz3kV6nZPk2hOk2/ukZYS7xslqHSG7ZYT8nRNStsc9sm557RMsb35C8b4Jcp4fJKN2P805Dl7NqaG/NIexmjiGqmJoL93O4fzNHMuVsjudeVvpzNvKsZzNHMndzLH8rRzPC6cjN1ya4MrZrGR6ZOGR46Klg6qMTkfOBmlhoZfkyPt+uvK2KXEiX4ru/DB688MYyNtOR/rTvBa7ltj7lnGT3kCobr5HJmUqwfF1L8ug02HU65WfMZXwKBHke4LLO7wPkspyIpe4Avz8mD1zprKtWZ3t8TXBJT+b90kKeSTee1u0+nMhPYLLQUjPNcyHH37I7373O/7nf/6H8fFxjEYjBw4cAGB8fJzAwECPrx8YGMBoNAJw4MAB7rrrLo/39+7dy/333+/zd5nNZr7zne8oIUlPECHaYCWk3TVaRQSMkzQm+7ql5T2ZNZn4yFkh+TW5t8cj2+N9QsJLeCYLX88i39JSP5v6GUO0klQFazRu6fFj3tyZaOddx9oVC4l65G72Jj9Ne/E2jpdJ0V6+lfaybXSUh9FRHkl3RQx9lVI4a2LpsMTRXhtHZ20C/bUpDNSmMFhrYtyRyZn6dIZsGVRGb2H7Iw+zevWzpBXvoKThIHWvDWB7pQ/r3l4a3xihft8QlhcHKGs7QV5dB7mODnIcJ8hydJBpP47J0kGquQOTRZKfzLp+shsG3OIzQtGOMXIaBzFZe0iz9ZJh7b3wsaMfk72PFGsPptoucuqd5LcMU7DnJLk7x8jbOSbt9XnuFGUvv0ft65/gOPAPWA58TP6ubrIa36WobCevF9TSUViOqzKd0aoIBiq2c7hoG+/kbuZozkZOFGzlRMFWjudu4UjWRg7lbKWjYDvH8yThuZT0eJ+UkMVH3tlzPHsznbkX4kTeFrrytyrRXbBNivwwegrC6SkIp68gnIHC7RxLf4ZXotcSe+8t3GTQMV9nUJYAqoXE18Zk7yyOLDHK96qkx5f8eEuPWnB8iZB334+v22DzZkp7e+SFhVNJj3epTn2HS+7xkcXIu9FZSI/gchDSI1Coq6vj6aefBi5kes6fP6+8f+TIEY9Mzw033ODx/c3NzV8p0zPV1mPlc++Ffz7CGBzEfJ2WUIOeUIPeQ5pkGfElHrKQqEP63ql37swPDrykACkbpVW/X/075KOiBm0ggZoA5gT4c52/hrl+fgTMmcmSwP+H6FW3ULRxFW9nbeBIwWaOF2+jsySMzrIIOsu201G+nc7KSHdIl9dPVMXQVR1Ld00c3TVx9NfG018bT19tIsOOVE7aUzjVlMfhUhM7U6J5ZvWjPP5UNJvjCyluOojt5R6sL/bSdGCUpjcnaHhlFPMeJyWN3RQ39FBQ10teYw95jT1kWI+TXHOU5JqjpFQfIbXmKGnmdrLsJ8ip7yK/sY+cum5yHF3kOLrItHRiqmkntfoYCRVHiSs7THxNB/kN/ZTvdFGyy0XWLhdZu8cp2D1B+e6TVO4+ieWl97C+/jH21z+mes8QNvvL1Fe3ccRSwSlbBmcsyYyWRdJdGE5XQRjH87fRWRBGZ0EYHXlbOZa7SYqczRzPC+d4Ubj0es5m2nO3KJmgzrytXtfSw+jOD6Mrb5uyq0cOObvTnbuVnnwpegu20Vso/bOvMIy+wjD6i8LpLwpnoCgcZ/F2eovD6CsJZ6A8kkOm9Twf8QgRK29hiVFDSEgwIQYDIXojC/TGiyaqvLMu6pjqXpavHh/5e7w3L6tLW7LcqHf3+Ap5n0+Qnz9zZs1SMj7qhYWTlbq8r67LMqbOBKnLYZqAACE9gstCSI9AoaGhgaeeegq40NPz05/+VHm/srJyyp6eqKior9TTM60emknOOlwoEQUr0nNxFsV3FunS4nPxviDP3x18SemZKou1QK8j1KBngV6HQRuIn2Ye/v7+zPUPIsBvHsFzrufuBfNIfexurBFreSd/I8eLt3G8eBsnSsPpLNuuSM/xigg6KyM5USUJz4mqGHpq4uitjVeivzaewdoEBq2JDDqSGavPYMyWz/HKHMojIvnxmid47NGtxGRasTzXg23fMJb9QzheH8f26hg1z7koaemlpLGX4qY+iltOSNmfxh6y606QU3ccU+0xkqsOk1x1mKTKQyRWvkNi5Tuk1h7BZD5KSs1h4ksPElvyFnGlB0mqPkpKbTsm8wmympyYmnrJbHFS/NwYlS+cw/byhzhe/QT7/k+wvPoBZS+do3r3CPaG13neuou9Vjvd1hLGa1MZr4imt3Ar3YXh9BRt53j+No/oyNtKe+4WOvK20lkQRpf7a9pzt1x43Yf0dOVto68ogp6CcEV81CWsrjwpi9NTGEZPYZjycW9ROL1F4fQVb6e/JIKBsihcJVEMlkQxUBJBf+l2BsojedP0FLvC1xF573KWhgQxf77UKByivdDnpRaRS93GUselFhN6S496E7O35Mi/XxYcecxdHnWX5UwXqPEYYZdvc6lH2H3Jj/yxnO1RS493f09QYKCQHsFlIaTnGubQoUN89tlnnD9/ntOnTxMSEsK+ffuU92NiYtiwYQOfffYZP/vZzzAajR7TW2vWrCEjI4MvvviCsbGxrzy99XWlx7MHSOtTaqYjPBcOfHqXojwnyNQnMozTyPJMV3pCDXpJegL98ff3xz9QQ4DfPAx+1/PDJUHkPHMvjbGP8G7BJiXLM5n0dFVHTyk9A5ZEnDZJesbr0jnXVIzLXkybKYWNDz7GugeeYENEPuVNR6h9vp/aVwaw7h3Gum+UqhcGKd/hpKytn/KWPkp3dFHWdoKi1j7yGnvIre/EVHuMxIp3SSh/h7jSg0QVvU5U0evElBwgtvRNoovfICLvNSILXie25C1Sze1k2LvItveS1eQkpamXzLYBSveMY33pA+pe+Zj6/T+j7o2fYX/tQyr3jGFu6aa1bg+vWuo5YK2m25zLaFUcI2XhnMjfTGdBGCcKwz2ER872dORt5Xj+Nk4Uhl8kPcfzL/TcqKWnOz+MvqIIegu3052vvs3lFp78MA/JkeVHLTzO0kgGyqIYLo1mqDSawdJInGURDFZE8WbqM4r03DA/+GtLz+UsKPRVypqsrydEq1NkJ9Rg9NjvYwyWmqLVCwu9z1MI6RH8LSCk5xpmzZo1BAYG4ufnx6233sru3bs93v/Tn/5EWFgYfn5+GI1Gn3t6Hn/8cebMmcPixYu/8p6eryI93rKzQB9MqOFCSetCaWryDI93iWkyOfJeMOh9F+zrSI/6c3UpzhAchH+AH5oAf2k6zX8mNwXP4dm7FuKIeZSXM9ZzpHirIjxdZds5UR7hU3rkspYsO33mBPrMCTjNCfRbEnFakxi0JnHSkc77zdmca8zHWZmHZXsY8U88zbq1W4lKspBW+pK0v2ffGNZ9o1S/5KLy+QGqnxugclcPZTvbqdjRTunOfvKbesmv7yTNcoyEireJLX2T7fmvsjXzJTanv8CG1D1sSnuezekvsCntecJzXyWu9CBZdd3kNzspahogs8VJ5s4hCvaMYn7xDPUv/QTH3k+ofe0Tal//iJoXRnHUd/Cc7TXaG6roNhfSY86ktyKGgZItDBZv5ETBRg7lbuZw3hapUdkr2yML0InCcE4UhtPpLoPJr3e5Qy5ndeVtk/pv3NLTUxBOd36YEj0F4fQWbqe3cDt9RRFK9BdH4iyVYrA8msHyaIYqYhguj8VVFqO8NlgZzVumZ9kZ/jDhK92ZnhB3X06w1uPaunpfjrwocDrbmScTHvlj9Z6eqXp55uv0hBqMhBqMLDSGsNAYQqjhQvlN3XsU6O+P39y5Solr3pw5UzY1q6VH7uXxng4T0iP4JhHSI7giTFd6vLM7spBIwjO19ExWypqqDCZ9n+f0lVzqUh9D/SrSI/f4yK8r0qM3YAgKRhPgj14TSKjGjxuDZ/KDUD9SHlrOc2lP80beRo67Zae7PILu8ggP6ZH7emTp6aqOVTI9atEZtCbitCQzaElmzGHibH0a5+oz+KAuh84SEzsTo9jy8NM8tnYb6zdnUtr8FnWvumjaP4Jl7xClu3oo291L5a5uanZ3UrvnBCU7+iho7KWoqZtM2zFSa94luept4krfICL/FcJzX2ZL5vOE5bxEZME+YoreILHyHdIsxyhsHaRk5zCFrUMU7Bii8qVTmPeepX7fx1hf/ZiqfR9S8soYVS8N0Nj6NvusezlmbWWiPp+BylT6K6LpKdxIf8Gz9BWup6twK4fztijTWXJ2R87wyD0+svTI0VW0na6i7fS4Qy04k4mNLELy18qvOUuiGCyLwVURh6sijuHKeIYr43FVxDFYFsdgWQyDFbEMVcUyUBXLW6nr2RG2jm13L2eRToNO796F45Yeb+HRBgRKZ0q8hGeyTM50lhT6amD2zuyEGowsCpnPopD5ivyo+43U3xes0RDo769ke+Qyl3cfz2Rbm+WdPd7Ta+qslpAeweUgpEdwRZgxY8a0JrOmIz0XNyJfuqzla1LsgqhoLho3/7rS493UrEiP3qBIT1Cg9DMXBc1juWEOD9wQRN6P72Jv1rO8lb+JzrLtdJdFXlJ65CZmtfQM2JIZsiUzZEvCaUnGaUlmxJbCk/w1XgAAIABJREFUKXsK5+oz+Lgpl8GaDA7kJJLx7EY2rFnPM49HkFXaSuOL3TTtc2J/ZZDS3d2U7e6lek8v5ue6MD/XRWlrLwVN3RQ2dpFTd5wM61HSLUdIqX6HuNI3iCt9g9iS10mseIvkqrdJqTpEmuUY2XUnKN7honTXCEU7R6jYPYrj5bM4Xnmfhv2fSA3Lr71P6UtOLM+382LTXo7Z2hiwWDlpScVVkYCzPJz+ok30Fa6nv2gT3UUX+ncu6te5hPB0F0fQ6w610KhDzuLIIYtOd2G49H0lkTjLohmqjMNVFc9wdQLD1Qm4quJxVcW7pSeOwYpYBqvjGKyO403TBnaGPcLW79/CAl0gWl3wtKRnOuPr6lMWUy0onKy05SvDI5e0FugNHk3MakmSszHz5szxuMIui85kx0e9FxWqL68L6RF8kwjpEVwRLiU9yoHQSfbfyNIjSYlnc7Bafrz7drwzPOqP1Tt41CW0BQbpMOiF/p7pl7e8szyy9CzQ6wjVGwgJMqAL1GAMDGSpdh73Lfbj2e8ZcISt5mDuJo4VbaWnLIyuikh6K6PoqYjkRHkEHeXbaS8LV0mPlOU5URNPT02cVNayJjHkSMVVZ8JlS2XAmsKQ3cSAPZVRu4nTTVl8vCOPUXMa3SXJPGeKJu/Zp4h7/Ck2rY+lsmwXjpaDOF7sxrynH+vzA1S9MIDtxV6se7qpbHNS1OykqLGXwqY+8uq7yXGcINfeSaGtk3x7J4XNPZTuHKC4rZ+8xi7yGnsobOmndOcQJbtclOyawLJnHMfeM9S/9gHNb3xC/f5z1L86RvPuI+zZsZdDLTWMOkoYNecwWhHDUPl2BkrD6C8Lo7dY6qHpL9xOX34kPQURivx0evXxdBdHeIhOT0kkvaVR9JZG4SyLpr80CmfJhVBndpwlUQyURl8UigiVRjFYESvJTlUSI9XJjFQnM1yVxFBFwoWolmKwNoG30jbTFvYI2+5eTqguCK3Bs7ylFh/1EkFf0uMtNL5G1r2/brLpLXWGRxYd9ZSWd6h7e3Q6HVqtFj8/P2bPns0s1Qi73Ngsh/founp5YYjBIKRH8L+CkB7BFeGrSo+vcw8XGo6DPZqDvaVn8jLWZJkf3wsHZcnyNb1lCNL4fF39vvcI/QKdHmOwNPWyQKNhuXEe627VErlqKbuSHuVw8VY6SrfSV7GdnqoYD+nxzvR0VkqZno7KC43MsvQM16cx7Ehl0JaKy5GGqy4Tp8OEqz6NMy1ZnGvKYcyWybHiRHanRGKOCifix1uI3ZZOVkYN5tZ3MO/ppnpXN2W7uqjZNUTt7n7K2voo3tlDya4uCtu6yGvqIKfhGLmN7RS2nqBkZw+Vz7uo2j1IWVsf2Y4OcuqOk9fYRXHbAMVtA+S19VG+a5CqvRNUv3oa2/6zNDw/yI62dt6ue5HuuhbO1Bcz2hiLyxpFf0nEBXkpvfBxd/52+nOlO1tyZkfO7nQXR9BbGkVfWTS9pVGK7PSVRdNXFk1/eQwD7hgsi/EpN+oYLIthqDzWHfEMumOoQhIe73BVJjIii5BZCpclSZGerXcvZ5FBizHEoDQyL/AaV1efhJhKetTiM53tzL5kxrtB2XtDs/fXq8tcsnAFazTMnT2b2TNnKlua5btck+3rUUuP0X2OQ0iP4JtGSI/gijBjxgyl7CPHdKTH9/ZmSSIWGg0sNBomlR61dExd7vIcV5c/l7NL83XaS0rPZAsNZeGSpUcfrMMYHMTCIH9uN8ziyTt1JD50My+YnuBY6Va6yrfRXxlBd2U0fVXRdFdGccJd4uoodzc1u6WnszKajsoYuqtjFelx1ZkYrk9jpM7EkN2Ey5HGSEM2/XUZDNSlMdGUwQdteZxtyKWnNI43cmN4Pi2GvM3hxKyPJikmjxLLPspbj1PScpzc5nZqdjox7+qnorWf0tZeytu6KWrqIq+ug3xHO4X1xylt7qbMLTSFzT3k1B0nteZd0i1HyGs4QXFbP0WtTgp39FO8c4iSlyYo33cSx2unadzdxfPNBzhmb6bfYeVUfS4j9dsZsUQxUB7DiZIIjheFcbwkgs6iSLoKIxXp6c/bTreqhNVTtJ0+L8mRP+4vj1FiUCUvg2VxDJTGXihJuWOgNFZ53VWRIEVlokcmZ7AykaGqpItitDqZ0ZoURi0pjFlTcVmSOJi+hdbtj7L5B8tZEqJnQYiREIMkHFNJj68m5qlOUEwlPerxc++L6776fLzFSP21eo3n9JVc4pK3NMvTXN43w9R9PrL0eG+lFtIj+KYQ0iO4IsjSM9VCv5BJzkpctG3Zawx8soblqaTHOwM02efS11/c6KwueyknLLTByiZo9Y2wBTo9i/TS3xmk1bEoJJCbjfP40eLriVu9iOJnv8/+vE10VUfTXxOFyxxLb3UsfTWx9FRF01URqUR3ZRRd1dF0y+Wtqli6a+LpNSfSb01m0GFiqC6NkYZ0RuozGKnPYLwpm5GGbIYbMhhpSOe9tnzOteYxYcvkSGEkB7PCeDk+nLIt20jYEE1EXAkJpa9gsrxNVmM7VS2HsO48Rk2bk7LGASqanJQ3OCmydZNXe5wCcyc1DX3UNDsprHOS7t68nFz5LmmWQ+TUd5DX2EWG9TgpNcfJaxii4rkJLM8P07a7g2OtLzHQ2MxZeylnbXmcNCfhqopnoCyOvtI4ekuj6C+LpLckRglnSQz9BVH0F0RKfTjuPpv+4kjpnyrR6S2Po68inr6KePorE+iriGdIVZKSRWagLM4jpsrouCoTGXTHUFUSwzUpjNSmesS42cSENZXTtjRGaxJ4K2MrrZGPs/4Hy7lxvoFF80MIMRhYoJIeWTzk21jqO1nTDbW4+MrmeGd0phpf97WcUD1lpv4+eVuz3NsjT3J53+XydTxVPm7qqyFbSI/gchDSI7gizJgxA73Gd3+MR4ZmGuEtOJP190xV1vJV/lKER+6x8JKeCz1F0pSZ0uisDUSv02DQBymnLuQ7XkZtMIv0Bhbppc3RgUHBLJ0/m9sWzmTDHfMoefYOGqLXcLg0hv6aBJw1sQxb4uivlaK3OobuyiiP6K2WSlo9NXF0VcfRU5ugSM+APZVBhwlXQzZjjVmMNWZxuimLUw05nGrIYbwhk1NNeZxpLmTMnseJynipHJQZxe7YcEq3hbF1YzSbk2qIyd9Jlv0ARQ3vUNr4Ntn1R0mxH8FkP0RabQcpVUdJLD9EUsVh0qzvkG49TFLFYVIqjpFSfojYwteJKXmNpOoDZNqPkmHpIN18nGx7L6XN3Thaj7Cv+SWOtVpxtpQyYU9j3JLCaGU8A6WS9AxVxjFSEs9YSTyu0jicbuFxlkTRXxxLX3H0hdFx9zTVQGm01LNTHoOzIpb+ygScVYkeMVSVhMudjfElPUPurI6rMtFDdkaqUhipSsFVncJQVTJDVcnSzzGbGLemM25NZ9RsYsSaxpgljVNWE+fs6UxUx3MwcxstkY/z9N03s9Soc28T1ys7euRGY++eHrmhWY7JJMi7LOW9QVndhOwtPN47etSC5L0h2iOCggkJlhr152t1hARr8Zs7l1nXX8/smTPxmzvX5/i696ZmXXCw0tfjvZNISI/gchDSI7gieJe3JsvCTDfTc6lNy5cUGx/7dCb/es9Mj3IRPvjCHp8QbTB6VabKoHq+UIOeUK30PySBmgBuMMzmrsVz2H6vjtptq9id+iQdVYnS1JUlgSFrHL3mOJzmeElwqqLpcZe65OhSzk/Ee0iPkulpzJSkpymTUy3ZnGrO4WRTNuP12ZxqyuN0cz5n6nPor0qltzSRjtxwDpjCaUoMI3VzOFFR2cSlVpBbtY+SuiOUNnSQ1vQupoZDpNveIaXmXRIqDxFf8S7R5W8TXfEm8dVvkVzxGulV+0mr2k9C0ctEFe8luvx1kq1HSLUcI8F8jCzrUeoa3mZ346u83thKb2MVroYiTtlSOWWVsjx9pbEMuMtKg2VxUi+NquQ0UBpLf3G0Ekp5qjxeERdneTwDFQkMVMYxUJ3EYE0y/dVJ9FclK2UolzvT46pM9MjwTCY9ctOySxUjtamMmk2MWdKUGLVmMGrN4LTdxHv2VEaqkjiYtYWWyMd58q6bWKiXsoJyT486w+N9Cd2X7Ex1L8tXZsZXqPft+Jrk8vUzvEfWF+ikVQwLjSHK9wT6S+cpZl1/PXNmzSLQ33/S3T3qfh+5Gdt7CaOQHsHlIKRHcEWQD46qy1m+tiR/XemZquR1KfG5dHhOkqmlRz5TcSnpWaiTe3oCuHXBXNbcoiHnx7ewx/RjXs/fRpc5FZc9BZc1EZctXtqmbE2kvzaOvppYRX6+rvScbsnlVHMOEw05ivScasxn2J7DYHUKx7M3cyRjGwczwtiZGE5ReCTp2xJITjSTWfk6eXWHKW9+l+q2dylvO0Sh/SDZtW+RWfMmpqoDJFS9QVL1G5gqXiW7+g1yag4QU/0G0ZUHiKs5SFbdEfId75JrfROL9UX2N7RyqMFBR101I3X5jDsyOWVNYMIsjXf3VibQX+kuK1UmMuzOxshS4yyNpb8kRgm1rAxVJDCg6reRhWeoNoWh2hScNReEZagqybO/R1XSUkuPXAobcWeH1GUsWXjkTM+4NZ1RawbD1ixO29J4z25itDqZNzO20hzxGE987wbmBwe6S6IXLyX0nrCabMR8qiZj7506Ux0a9ZYedVnsUje4FhqMUhhDFDkK1mjwnzdPKXPJ/T2Xkh71kkJ1/5KQHsHlIKRHcEWYMWOGR5+Nt6RMR3qUi+mThPzzFhoN09rcfLnSY9AG+pQe+YCq/IwLjQZCtVLJbJHWjx8tC2bzylDqo+7jzaKtvFseSWdNMi57CqOOFMbqkxl0SLt2BiwJivioMz6y9PTUJijS02dJ8pCe8aZsxpoyOdmc5ZHpmWjI4WRjLmdaChhvLGS8LofBsgg6sjdyLONp3jFt4Ln4LViiwknckkZEYgNh2XsotBykpvUYJTs6KGvqIN92lBzLUdJrD5FUeZCU6ndIsR4iznaEaOtRwmuOEGvrIK2hi6rWdhyNB2ipe5nXHI0MNlUx0ljGSH0RZ+pMnLEnccoWz7g1niFzIn1m6Vq8qzpZkR5XZaJP6XGWxiqiMliZKGV3KqSS1mBNsofwyDFck6JIjyw36iZldVZHFh05xrx6d0bNJo9Mz7g1nRFLOi5LJqesJs7YpEzPmxlbqd/+CI/dthSjxh9tkJTd8JWN8RYab9m4VOlqsp6dqaTnUr08cm+QerR9kTGEhQajVJ6Ty3LBwWgCAhTxkRubvbcy++rtUUuP3OQspEdwOQjpEVwR1NLjfZpBLSdyI/A3LT2Xal6eKozBgXiPzsvSIx9BnUp6Fhsk6TEGBbNUO49Hb9UT86Mb2ZP8IEcqIzhWFa1Iz1hdqiI9LnsyA5YEnOZ4+mvjFOnpqYq+SHp6ahOmLT2y+LzXWsiplhJONxUwWhtPV/5W2jOf4a3kZ3g5cQst8RFkbU8hKrKCbQkOUkr3Udh4jLzm4xQ0nCDHdpwMSwemmqMklr9NcuW7JFkOE2k+TFjNu2yvfIdkyzFy6juobznIrvoX2VfXzBGHhZON5ZxuKmKiPpdTDkl4xiyxjFriGDIn4jSnMmhOVZqG5cyLh/QUSzFQGs9gWQJD5YkMVibhVMVgtSRPQ7UpuMypSqilRylZqX7PZMIzlfSoxcdlSWfInMFJSypnbNJzHEjfQl3Yo6xbsdgtPdLUkq+MivrQp6/3pyM4U93Vmkp6JjtEKv896rMU8tJNeZpLFyhlbIICAwnw82Pu7NnKeQrvvT1q6ZH3+KgnuIT0CL4JhPQIrgiy9KilQy0pspwsMOh9io8sPFNJj7dIeUuPeqx9uj09RvdpDO/RebX0yD9PFxzkIT3y8y026gjValkQHMwKvT9h999IwbN3c6hkPT3WBHqsifRYpd06svQM1aUw7EhRsj0DlgTPMpd8d8uc6JHtGbCnekjPeHOWIj1yeUuWnvdb8jjXVsHZtjImHCb6q+LoLw6jPSuCQ1mJvJ6Vgi0xlazwVOI2pfNkTBVb8l4kquh10mqPkWnpJMvWSa69k0z7UTLtR8mxHSK7+gCZpftJKd5LbsVeKmr28pythYPWGnpthYw6CvioqZCPGnM4V5fChD2RMWs8LnMsLnM8Q+akC9kYt4CoMzGK+JRIMViWgKsiieHKZAaqkhXh6a9KxlmdwmCtSRIoi4lhi4kx6wXpGfTq2ZF/j1p4xmpTlZA/V4uOt/SMW6Usz1BtJhOWNM5YTQxXJrM/dSO2Let48OZQ9Bqpedeo9xwHV09byeGr/OWrydnXpNd0pGeyDJA64yRneBYaQ5TzFOpGZvXX6rVaNAEBBPr7M2/OHGbPnKlMc3nv7/GWH/VmZiE9gm8CIT2CK4IsPZfsxZlCei7s8rl4MstbZnz190yW9ZlOpseX9Hi+Lv2N6p4e+W9YFGJkvlbHgmAtq240UvT0SloSH6OrNgxXXRwDjmSctgyGHamcrDcxWpekSI/LLpW55P4eeaJLXkg4WaZntCmLieYcJlqyJelpylOyPRONWUw05HC6tYj3dlTx/q5KTu3Ip782FWdtOgPWXAbrKzlhq+TNsmKey86kMS2FhPgMEkwVZGfXUl6xA2vt89RbX+T55n282LqXF1pf5BVHEwes9ew31/N8tYOXax28YrbxrqWM3roiTjbm8n5zAe81ZnO2MZuxeum5B+0pOC3JDNRK/TKj1WmMVqcq2Rg55DHxgQopsyNnd1xVJoar0xisMjFYZcJZbaK/Jg1nrZRxGbZmMGo3MWo3MWbPYKQ2VZEqX+EtPONmE+Nmk/LxhFtuJmwZjFvTPUpbEzapn2fQksmELZMztixGqpN5JXkDtRvW8MDS+Wj9A9AG6zBopemtBV6ic9ESQK9+n8mmur6u9PgSH/WmZvnw6EJjiOdun6BgKVR9QOpsjf+8ecokl1p8fN3m0gQEKGPr8ue64GAhPYLLQkiP4IrgS3p8laUuR3rUmRull2aSrI+6v+irSo9ykFR74fUQfRB6nUb5u41q6TGGMD8omIVBWh69dQnm8Ad5MXM9/ZZIhhzxOO1JOO3pSqZn1JEibVZ2Z3pk6XGa43Ga46X+nkmkRx5ZH23K4mRLLidbc6TpLXmCqzGXcXdMtBbxUWstH+2qZmR3Nm/kxvBq+nbeLUylx17FCXs1R63VHKsp4Z2qQuryc7EXFdNSWsLOGgcv1dp4rdbMkQY7R5rNvOuo5HB1Hn3V+fTVFnGitop2czlHa0rotOQy1JTDudZcPmrN52xjNqcachitz2awPp2BujT6bWk4rSZc5lTGatIV6VGHt/wMViYxVJXMcHUarpp0JQZrpRgwSwIyYstkzJ7BmD2DcUcmo2YTwzUpUrOzu4/HW3q8hUcOtfDIITcwT9gyOGnPZNiaxZA1S5Iee6YiPdUb1nDfEiNa/wAMWmlZpXf5SJYKX2LiS368sz+T7ey5VCnMV1+RLDyL5y/wuMelZKXcY+ry1xuDLzQjy709s2fOVGLu7NmK9HhvZ9YEBBBiMCjlsaDAQPRarZAewWUhpEdwRZClx9eOHXXIu3DUZyfkvTgXtiX7vqjuS4Z8/Q51c7Mv6bm4lKYh1KuR2ahT9fTogzDog9Dp3U3aQcHM12iVUd5FC4JZqJ3D8pBAkh68jRdNT/NOcTgDlgRJaOwpDDkyGK1LZ6TOxLB8P6s+lUFHMgP2JJy2RPqtUpmrtzZeCnOiUt5ST28NOkzK9NZESzZnd+Rxpi2XM63Sfp6TzcWMtxTz/u5C/vGlIs7sqsCeXckTqzdw7z1PsO7+H7P1oSeIfvhhSsKeZFd2FPsKUtiXY2J/ejpvpGRyIiOJvqxo+nOj6CmIoDN/PYezn6U9ezuukixGqgoZrS+g35JFT20ag7YMzrbl89HOAj5sK+BUQw4T9bmM1ucwUpfFSF2WJCTWdEkqLFKWZbgmxSO85UdaDJiqyM6I5UK4LOkMWzMYs2YzbsthzJHNmCObUXsWw+Y0hmtSPTYqy7ez5H4edVlLFh7vMtaoLd1jaksWnxFbNi57JiftkvSM1qTwQsIz5D95H7cv0aMP1GAI0hKi1U+r0XiqJYRyTHZtXR2T9f14l7TkZmX1AVK1kCklONWeIe/lhXJzc+DceQTMmcvsmTOZdf31zJ09m4CAADQaDRqNBn9/f+nzgADlDpdRrxfTW4JvBCE9givCjBkzPLYUh0zStKzeh+MhGWrpmcZYu3GSTI6vm11GL9HRu8OoCFQQC/XBLJT/HkMwRp1GCYNBg86gIdigYUFwMKGaYEIDpQzP4vkLWBjizzLjLH50iw7L5vt4u2Ar7RXR9FuTGa5LZ7g+DVd9OmONWYzUZ7g/T2O4Po1BewoDtmSc1iTpirol0UN4emuTlcktpy1FKW8NN2Qo0nOqJZszzYWcaSngdGsOE60lTOyooae1gX1FxVQkl7Lyx40sXm1Gd78F7R1FzL8xiiVLnuW2G1bzyO1r2LLyESoef4hdm9fwUvjDHE58lJ6UtXQnP8ThhHW8lfgY76Q9Q2dpMsOWQkbsxYw4Chi05zJcX8DZHRW8t6OSczvKOdtWxsmGPE7V5zJRlyVlR6zpTFhTmbClcNKawoQthXHLxbLjM8ypksTUZkj/NKcxYpHGxsdsmYzbsyTpsecxXpfHqD2LEXMmrlqTslzQ+/eoRcuzYTlNCfXv8I4RWyYueyYTtgxO2zIYrU1id/xTpD52N8sWS70w8zVa5gdf2EJ8qT083lfYvSVosivrHicpfGSAfE1nLQqZf1Epy7vBWi096imzi5YgaoLQBQTiN2s2M6+7jlnXX8+8efMIDAwkMDAQf39/NBqNsssnxGBgvtFIsPs1IT2Cy0FIj+CKIEuPLD6Tb1u+POmRJcrg4+jnRaW0ryk9Ifogn9KjCQkgVBfEwiAtCzUGFhnmu8sCAdwWOo/HvhdKS+SDHC4Np7M6DqdVysgMN6QzXJfOeFM2ow2ZjNRnKNIz5Ej1kJ5Ba5KH9HR7Sc9QXZoiPeNN2ZxszWGiKZMzzcWcaSngVEsWoy3FnNxt5lVbI2URRWx7spBF6+pZ+tiLLFz3Cjf86AVWrLSy4s5cli5+httC1/PAsvUk/2gN5vU/oH7b/byVuobO9AfoTFrFobjVHE5/luOFEbjsuZxrKuZscz5jllzG7HmcbCzmgz01nNtZydm2Ss60lSvSc8aRJWVHrKmMWZIYtyYzZk9mwpasSI8v0ZFfH65JuSA9qpCFZNyepUjPuCOfcUc+o/YsRi1ZDNdmeEiP98/3PZaeroSHVKliMunZFfckyY99nxsWSX0wC4J0ivSohcRberzLUWrpUYuQ+lin/DMNOp1HqGVJlhK1xKiFR13Kmkp6FniN1qtLc3Lfjz5Qg//sOcy6/nop2zN3riI9AQEBBAUFEeDnR7BG45HpCQoMFNIjuCyE9AiuCDNmzEAbGKAcF1WLj5zxma/X+ZQe9b2rEK3mIkmZNHxkerzPVkz1/bL4qKVHFh+jzn2kVKeRTlAYNOiNQSzU6VgSrGOx1sDi+SEsCjGyWD+PNbcaiX3oNl7N3kR3TbyU5XGLyXiTdDJiojmHieYcRhszGG3MwFVnkhp83cLjEeYk+iyeoc70jDRmMtqUyUhTLqdaCni/OZtzzdmcbc1mYmcVR6y1JG0q445byrjhJis33f0ioXccxPj9dm6+Z5AVK49zy33vcOOqN7jp/rdYvvI17lll46l1WWx+JJ3UJzdj3/4EuxOe5nhpDKcb8nivuYSxtiJcu4oYaStivL6UD5sK+bCpmDMt5Uw0FTHUUsSgu7R1qj6XU45sRm3pDFtMimCMuTM+E9ZURsyegiOHejxcLTpyqIVEkpBsRm25SrZnzJrNqCWLkVrTRSLlK9OjntCSlw+qpWrCka3EuD2LIVsGQ3Yp63PSms5wVRKN4Y+QuO5uls7XoAsMwqjRExLkOX7uq4TlXTqarMw1nUzPZJNZ6oZleRzd136gi6THq+Tlfa1dvVcoyM9fKXFdP2sWfn5+BAYGEhQUdNHxUfmIqZAeweUipEdwRZgxYwbBAf7oNIEXiY+6zKXeh6O+d6W+gv5VpGey0Xalp2eK0Ml/o1YzLenRGTSEarUs0gQTqtWx0KhjoSGIm0PmEvbDZZRvWc1Rd1lr0GFiuCFDajZuyVXkZ7wp+yLp8RYepzUJpyWZfmvylNIz1pzNaFM+J1ty+ajJxActGZzeVcVzJTZSthbzveU5rLylhvtub2bFPQdYfm8XS37g5Oa7JvjeqrPctvoMS1ePceMaF8vWuFh672luecDFbQ/2sOahg0Ssf460yJ3UFbbRVmlnR4WV2pwCciNjyN2ymRey4jj3fA0/ebGa93eX8f7OPMZbCxhtzOFUYz5nGgqZsOdeEBPrhTMO4zZptHzUfEGG1BKi3oA8as24SHi8szCjdqm8NWbPY6I+X/q9thxGzWk+s0lTSY/6zIT6d8jCI0vPgF3K+JyyZjJUnoht60NEr76dUH0AusAgDAGS9KjFwPv21qWakL3vdE12l0v+eu/R+OnsAJpKeHz9PF/j9/N1enSBGmWE/bvubI9c2lKPqKt7k0RPj+ByEdIjuCJMJT2eJyaCLhIf9ULAr5LpmdY4+jQyPdORHr0+EK0+kFCtloWBQSwI1rLIoGWRTsMdC/1Ifvh26qMe4bg7yzNgT2WkMZNTrXmcas1jojlHyfhcKtPjtCYxYE1RpKffKgmQd0/PaEsOrqY8Jhqz+LgpiZ/uzGawzUJGZDnrVmdx501ZbFpZzfr7rdx2925ufeAQt67qZcUPhrjlvmFuWu1iwZohbvvxCHc+fZLbHvtHbl77Ibc8dIq7ftjD44+2s2H9USK272NLZDNhUQ08/UwBK+98lruXPUDCw49woq6YM8/X8OHzZXzQKh07PdWUx6nGfE41FnKqroAQY8Q2AAAQq0lEQVSTdTlMOLKV6aoJWwbjNpMkPpY0RTZk8ZElRJYetfBMV3pOOvIuS3p89fPI8jZmy8Rly2bQkcOoPYuT9iyGyhMxb3yQiFUrWKDzRx+ow6gxekiPuiykLl9N1ejsPb4+1ci6rwmx+Tr9RYsJJ7vFNV3p8fU1clOz/7x5zJ09m+9efz2zZ89m3rx5UnlLlelRZ6uE9AguFyE9giuCXN6SpcdDTiaRnsnim5AeJQs0RX+QvGF5OuUtWXoWaDWEBklltUXGYJYaAll9s5baLat5NXMD3apzEWPN2UpJa6I5R+nnGW3MYKQhXenpcVqTPGLAlsygLRWnLUURnoulJ52RplyGGnM52ZTNT/bkc7K1gPKkYm64NRfd0gJW3llJzqNFZDxawt331nHrD/ey4keHuHVNN0sf6eTGzf38oOATVpf9nAcK/5FV+Z/yg+RPuSP8I5aucXH7j85y19oPueOhUVY81MWKh45yw6p9BN9Qjf+CVJYseZbkTck05xUxtNPGuZ0VfNxSyLnGfE43FXC6qUgSn8Z8TjfkKfIz7shURstP2jMVuRmzpF1070rOukwlPr7KW7L0jFnSPU9SXEJ65CyT/Ht8NTGP2TIZtucwVJfLmCOb03U5OMsTqHz6h2xeeRPztX7ogwyEBIVMKj1qafHuw/FV6tIFanyekPCVcfHO6Kglx1c/ka8bX75Ex3viSy6TqZ9J3tQ8c/ZsZs2axaxZs6T+HncTs/rmlnyLS0iP4HIQ0iO4IsyYMeOiLI8v8VFndLxlRy51yTV/j5S8IihSqJuY5QjValXNyVqf0qUOg07nIT2LDFpCDVplesugDXQ3MwcSotcQotewUKcjVCP9jlCDPzct0PDsvTfwXNKTtJdE0GtOoMeSxGB9Oifb8iTJachUMj2jDZkXJrrqTAy5F/cN2JKlsCcpHzttkuioQ5aeQUcWY41ZjDdmcHpnOR2NpTTlZnLHHZEELspDc4OVpd+zsf7+Yp5ZU0HIql0sf+BNQlYdQnv/Ib4XdZrVeZ/wiOMfuSOjk+Xh+1mYfJT7an/Gg5U/Z8W2s9z00DjLVp/mzgfOsnLdGD9YN8rNP+pl+bo+lj14nCV3NrHollTuWWnCklHHYGsLZ3aZ+bC5nPGmUkZaS5loKFLk52RDnjTKXpfFqDtr4r0LR33JXF3ecrlH1NUCJIvPqMU9veXIZcyRy6g9R8ryWLI8Mj3TkR4l02NNU3p6TtozPZqYx2yZjDhyGa4rZLROatjuL02k4sf38exdi9EHzyVYY8CgCSUk2EiI1vdhz6m2Jvv6evkO1kKDUTkPoUxXuffpTFb2mqx8NtlZDEV09Abl4Kgc6gZo758pZ2/m+vkxc+ZMZs6cyWz37h71vh55R4/Y0yO4XIT0CK4I05UeuX/HO2TpCTVM7wq7IUhzUSwI9hSjS/0cb+mZbGTdqNMo0rNIr2dhkNQvtMjgz7LQILauXs6+jPWcqIjBaUumz5bCUEMGp3bkM9qQ6SE98ti6q850edJTl8lofba0gXlnFS+WZpETHsWCxRvQ3ViMcXk9C29r4p6VNaxaZeemH7zMzauOsHRVN/qVHdweeZp78z/hocb/w21x73LTxpdZmHCYB2z/xCPm/5dbI86xdO0YNzx4ktsfPMOdaye4Y+0EN68d5dZHXdz68ABLV77B0turuf3OAtK3lXHUYWN8l4UP2yo41VzMREspZxuL3cJTwER9LhOXkB5fIYuOyy073hNcvqRHbmSeTHrU4jNVT4+39MilNFl6xurzFekpfeJenvneYvRBfmiDjBiDJemZTGa8T0L4+jq1jMiyo0xUqWRH3pw8VUZnqjMUk0nPQoNRki33eYrF8xcQ6j5A6qsXSe7Vmefvz6xZs5g5cyaz3JfYhfQI/jcQ0iO4Iqilx7u8pe7vUUuPMThQyaaopUeewPJ1mFRpQtYEKuU0WXrUI+uL9NL01nSlJ9QtPvLIunpsXf48RO/ewqyV/rYbQgL53hItph/fw6HicJzmeGkRobvf5vTOAsYaszwmt8abshmpz2BIXlDo7uvxEB9bsvS5PYUBe6oiPPLdrSGHlD0aa8jhVGsRRyzFbH50I3fd+jB+IdtZcruNpbe3Mn/FC/jftYeQ7+/l+3cc4+Z7+1i+6iRL7h1i2ZNj3B55mvvKPmFd0XusyR3nvuIPebj6VzxU+P9x84bTLHl4nCWPnOLmH5/l1nXnuHXdOW5Ze5alP3Sx9IdObn3oNN9b08Ot973FvSvtmMLNNOXVMNRUw5m2Yk63lHCuMZ9xWXjcMVaXxZg8DaXK8Ki3IJ90L/6T3r+Q3fEYKTenMa6SnnFbjiQktmxJeuTvqzX5XILoW3qkn6n08dhylKktWarG6/IYsecx4pD6lc7U59BTkkDuwyt54tbF6AL90AYbMGpDMAZ7yo2vq+khwVoWuI97ygIzX6sjVHXlfKGXaEy232cqkZpMvrylR71BepExhMXuEXf1XS7vTJFSSnOLTGBQEHPnzmX27NnMdG9qVh8kle9wGfV6IT2Cy0JIj+CKIEuPIiJu0VHv7pmqmVjdo7PIoFVKTXK5SRYefZAGbZAGjbtpWhEqlfAsNhhYbLiwp2e60hMqn6GQJWfSpYhajHody0ODuP+mEMq2rKG7NhaXI5FBRyrDTVmMtuQw3iJJjlp4xhqzGK5Lx1Vnkv7pSGPIbmLQlsqgLZUBa8qFj+2pHtmeQXs6Q44MhhwZDNdnMd5QwMnWMupNiSwJXclc/3sIWJKGYZmdBbe0sOSO51h29yssW7mfm+5/h1vua2fxA70s/5GLm1c5WfZAP99ff4o78/4PN2f/lDszf8YdYR9y05OnWP7gOe565Cfc8vAH3PLYe9y29iy3rT3L7Q9OcNeaEe54oJ9l9x5j2X1HuOm+DpbedYgV39vDs+tsvFVj59yeKs7urmSiNYeJpnzGG+Xm5nxONuQpI+0n7ZkeJS115kctPbLonHQ3Dk/YMhk1pzFmSWfCq99GztKMqDJDrlrTRQ3T6vF4n9Lj3vQ8apeySCN2SXZGHfkM2/MZsedzxpHF2fpMOotjMK39AeuWLSLYzx9dkPQ//nJpVvrvqO8pqpBg7QWxCdaiD9QwX1XOWqDTEzJNmbloWaFW6zO8MzXqrJJahpbMX8CS+QuU1+fr9MqeHXUZWuk/UkmPn58fc+bM4brrrlPucqkPkArpEXwTCOkRXBFmzJjBjBkz+M53vnPNhHjeqzvE8357v1cg+LqI//YIrhjf+c619f/YxPNe3YjnFQj+9hHSI7hiXGv/0hTPe3Ujnlcg+NtHSI/ginGt/UtTPO/VjXhegeBvHyE9giuG2Wy+0n/Ct4p43qsb8bwCwd8+QnoEAoFAIBBcEwjpEQgEAoFAcE0gpEcgEAgEAsE1gZAegUAgEAgE1wRCegTfOn/5y19IT09Ho9EQHBxMcXEx58+fv9J/1tdiz5493HPPPcycOZMtW7Z4vPenP/2J8PBw/Pz8CAkJoaWlxeP9f/mXf+GJJ55g7ty5LFmyhLfeeuvb/NO/Fn/+859JTk5m6dKl+Pn5sWLFCvbv36+8f7U9c1VVFYsXL8bf358FCxaQn5/PX/7yF+X9q+151fz2t79Fq9Vyzz33KK9d6nn+4R/+gR/+8IfMmTOHFStWMDAw8G3/2QLBlAjpEXzr1NTUcO+99/Lv//7v/OpXv+KWW25h9+7dV/rP+locO3aMjo4OMjMzL5Ke2NhY1q9fz5/+9Cd++tOfotfrOXHihPL+gw8+SHp6Ol988QUjIyP4+fnx8ccff9uP8JX4r//6L6qrq/nFL37B+fPnOXPmDBqNBpfLBVx9z/xP//RPfPbZZwD87ne/Y+3atdTX1yvvX23PqyYqKooHH3zQQ3qmep6//OUv3HTTTTgcDv785z/z7rvv4u/vz29+85sr9QgCwUUI6RF86yxcuJDOzk7l87179/L973//Cv5Fl09tba2H9Hz++efMnDmTTz75RHmtoqKCjRs3AvCLX/yC6667jj/84Q/K+5GRkeTl5X17f/Q3xKZNm7BYLFf9M//ud7/j4YcfJjExEbi6/zN2Op2sWbOG1157TZGeSz3P0NAQOp2O//mf/1Hef+CBB9i5c+e3+8cLBFMgpEfwrfLHP/6RGTNm8Mtf/lJ57b333uP666//uy1xwcXS89FHH/Hd736Xv/71r8prhw8fZtmyZQC0t7ezdOlSj5/R1NTEo48++u38wd8QX375JaGhoRw9evSqfeYXXngBPz8/6UiuTseHH34IXL3/GX/++ecsX76cTz/9lP379yvSc6nnaWtrY+3atR7vZ2RkkJyc/O384QLBNBDSI/hW+fWvf82MGTP4j//4D+W1f/7nf2bGjBl8+eWXV/Avuzy8pWd8fJzAwECPrxkYGMBoNAJw4MAB7rrrLo/39+7dy/333/+//8d+Q5w/f56oqCjWrl3LX//616v+mX/+859TXV3Nv/7rvwJX73/GxcXFlJWVAXhIz6Wex2q1smHDBo/3KyoqCA8P/xb+aoFgegjpEXyryJmeX/3qV8pr77///lWb6VE/05EjRzyyADfccIPHz2hubv6bzwLInD9/HpPJxMqVK/nP//xP4Op/ZpAyOU888QRwdT7vT37yE26++Wa++OILgIsyPVM9T1tbG+vWrfN4PzMzU2R6BH9TCOkRfOssXLjQo9nzlVdeuWp7en76058qr1VWVk7Z7xEVFfV30e9x/vx50tPTufvuu/njH/+ovH41P7PM22+/zY033ghcnc+7Y8cO5s6di9FoxGg0EhAQwHXXXYfRaOSDDz6Y8nmGhobQ6/Ue5b7Vq1eLnh7B3xRCegTfOtXV1dx///389re/5de//jUrVqz4u53e+r//9//y5ZdfUllZyaZNm/jyyy/57//+bwBiYmLYsGEDn332GT/72c8wGo0esrdmzRoyMjL44osvGBsb+7uZ7MnIyODOO+/k97///UXvXW3P/Nxzz/H73/+e8+fP8+mnn3L77beTlpamvH+1Pe/nn3/Ob37zGyV27tzJXXfdxW9+8xvOnz8/5fPI01v19fX8+c9/5vDhw/j7+/Nv//ZvV/ipBIILCOkRfOv85S9/IS0tjcDAQIKCgigqKvq7LW3V1tYyY8YMj3jooYcAaYdLWFgYfn5+GI1GnztcHn/8cebMmcPixYv/Lna4/PKXv2TGjBnMmjWLefPmKWEymYCr75mffPJJtFotc+fOZenSpRQWFvL5558r719tz+uNurwFl36eTz/9lFWrVjF79myWL18u9vQI/uYQ0iMQCAQCgeCaQEiPQCAQCASCawIhPQKBQCAQCK4JhPQIBAKBQCC4JhDSIxAIBAKB4JpASI9AIBAIBIJrAiE9AoFAIBAIrgmE9AgEAoFAILgmENIjEAgEAoHgmkBIj0AgEAgEgmsCIT0CgUAgEAiuCYT0CAQCgUAguCYQ0iMQCAQCgeCaQEiPQCAQCASCawIhPQKBQCAQCK4JhPQIBAKBQCC4JhDSIxAIBAKB4JpASI9AIBAIBIJrAiE9AoFAIBAIrgmE9AgEAoFAILgmENIjEAgEAoHgmkBIj0AgEAgEgmsCIT0CgUAgEAiuCYT0CAQCgUAguCYQ0iMQCAQCgeCaQEiPQCAQCASCawIhPQKBQCAQCK4JhPQIBAKBQCC4JhDSIxAIBAKB4Jrg/weBkQ1s/ZMsaAAAAABJRU5ErkJggg==\" width=\"639.85\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.image.AxesImage at 0x7f26cec6fd30>"
-      ]
-     },
-     "execution_count": 132,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "im[100][10] = (255,0,0)\n",
-    "plt.imshow(im)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 148,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pickle\n",
-    "from slugify import slugify"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 149,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Help on function slugify in module slugify:\n",
-      "\n",
-      "slugify(string)\n",
-      "    Slugify a unicode string.\n",
-      "    \n",
-      "    Example:\n",
-      "    \n",
-      "        >>> slugify(u\"Héllø Wörld\")\n",
-      "        u\"hello-world\"\n",
-      "\n"
-     ]
-    }
-   ],
-   "source": [
-    "help(slugify)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 138,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "f = '/data_store/datasets/gov/output/senators_obj_04/boozman_john_mesh.pkl'\n",
-    "with open(f, 'rb') as fp:\n",
-    "    data = pickle.load(fp)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 139,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "colors\n",
-      "width\n",
-      "keypoints\n",
-      "triangles\n",
-      "texture\n",
-      "vertices\n",
-      "uv_coords\n",
-      "save_vertices\n",
-      "position\n",
-      "pose\n",
-      "camera_matrix\n",
-      "height\n"
-     ]
-    }
-   ],
-   "source": [
-    "for k,v in data.items():\n",
-    "  print(k)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 147,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[[[0.37254902 0.30588235 0.24313725]\n",
-      "  [0.44313725 0.53333333 0.59607843]\n",
-      "  [0.0627451  0.05882353 0.04313725]\n",
-      "  ...\n",
-      "  [0.65490196 0.51764706 0.44313725]\n",
-      "  [0.60392157 0.4627451  0.36078431]\n",
-      "  [0.33333333 0.25882353 0.23529412]]\n",
-      "\n",
-      " [[0.38039216 0.28627451 0.19215686]\n",
-      "  [0.43137255 0.53333333 0.59215686]\n",
-      "  [0.09803922 0.09411765 0.0745098 ]\n",
-      "  ...\n",
-      "  [0.38039216 0.31372549 0.25098039]\n",
-      "  [0.23921569 0.20784314 0.15686275]\n",
-      "  [0.28235294 0.23137255 0.19607843]]\n",
-      "\n",
-      " [[0.32156863 0.25098039 0.16470588]\n",
-      "  [0.10196078 0.10588235 0.08235294]\n",
-      "  [0.11372549 0.11764706 0.09803922]\n",
-      "  ...\n",
-      "  [0.23529412 0.19607843 0.16078431]\n",
-      "  [0.12156863 0.10980392 0.08235294]\n",
-      "  [0.61960784 0.49803922 0.38823529]]\n",
-      "\n",
-      " ...\n",
-      "\n",
-      " [[0.38039216 0.45882353 0.50196078]\n",
-      "  [0.35294118 0.43921569 0.49411765]\n",
-      "  [0.23529412 0.2627451  0.30196078]\n",
-      "  ...\n",
-      "  [0.72156863 0.49803922 0.39215686]\n",
-      "  [0.10196078 0.10196078 0.13333333]\n",
-      "  [0.0627451  0.06666667 0.08235294]]\n",
-      "\n",
-      " [[0.         0.         0.        ]\n",
-      "  [0.0745098  0.07843137 0.09803922]\n",
-      "  [0.07843137 0.0745098  0.09803922]\n",
-      "  ...\n",
-      "  [0.10588235 0.12156863 0.1254902 ]\n",
-      "  [0.10196078 0.10196078 0.13333333]\n",
-      "  [0.09803922 0.09411765 0.11372549]]\n",
-      "\n",
-      " [[0.         0.         0.        ]\n",
-      "  [0.07058824 0.0745098  0.09019608]\n",
-      "  [0.06666667 0.07058824 0.08627451]\n",
-      "  ...\n",
-      "  [0.10588235 0.10196078 0.13333333]\n",
-      "  [0.07058824 0.08235294 0.10980392]\n",
-      "  [0.07843137 0.09411765 0.12941176]]]\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(data['texture'])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python [conda env:megapixels]",
-   "language": "python",
-   "name": "conda-env-megapixels-py"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.6"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
author	adamhrv <adam@ahprojects.com>	2019-01-06 14:29:35 +0100
committer	adamhrv <adam@ahprojects.com>	2019-01-06 14:29:35 +0100
commit	2efde746810a0264ad2cf09dc9b003bfcd17a4d5 (patch)
tree	54efdf68339210d931ce130ab07e0369208e392a /megapixels
parent	374dc54d049766fce225ca84d31fdf51f40f292c (diff)