{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calibration of a 2 theta arm with a Pilatus 100k detector\n",
    "\n",
    "The aim of this document is to explain how to use pyFAI.goniometer for calibrating the position of the detector from the goniometer encoders.\n",
    "\n",
    "Those data have been acquired at ROBL (ESRF-BM20 German CRG) in winter 2017 by Christoph Henning using a Pilatus 100k detector and LaB6 as calibrant. One hundred and twenty one images have been acquired with the detector moving between 5 and 65 degree with a step size of half a degree. The motor position is registered in the filename.\n",
    "\n",
    "A prior manual calibration (using pyFAI-calib) has been performed on four images locate at 31.5, 33.5, 35 and 35.5 degrees. Those images were the first with two rings. The control points extrated during this initial calibration has been used as a starting point for this calibration. Then more images have been added to make the model more robust.\n",
    "\n",
    "The raw data files are available at: http://www.silx.org/pub/pyFAI/gonio/Pilatus-100k-LaB6/\n",
    "\n",
    "## Initialization and loading of the libraries\n",
    "\n",
    "Initialization of the plotting library, matplotlib, to be used with the jupyter notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using pyFAI version 0.20.0-beta1\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "# %matplotlib nbagg\n",
    "import numpy\n",
    "from matplotlib.pyplot import subplots\n",
    "import time, pyFAI\n",
    "start_time = time.perf_counter()\n",
    "print(\"Using pyFAI version\", pyFAI.version)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['LaB6_gonio_BM20', 'del_45.0_0001p.cbf', 'del_08.5_0001p.cbf', 'del_20.5_0001p.cbf', 'minimum-mask.edf', 'del_09.0_0001p.cbf', 'del_53.0_0001p.cbf', 'del_60.0_0001p.cbf', 'del_63.5_0001p.cbf', 'del_56.5_0001p.cbf', 'del_12.5_0001p.cbf', 'del_53.5_0001p.cbf', 'del_42.5_0001p.cbf', 'del_16.5_0001p.cbf', 'del_05.5_0001p.cbf', 'del_47.0_0001p.cbf', 'del_39.0_0001p.cbf', 'del_47.5_0001p.cbf', 'del_57.0_0001p.cbf', 'del_35.5_0001p.poni', 'del_07.5_0001p.cbf', 'del_41.5_0001p.cbf', 'del_51.0_0001p.cbf', 'del_33.0_0001p.cbf', 'del_22.0_0001p.cbf', 'del_43.5_0001p.cbf', 'del_64.5_0001p.cbf', 'del_35.0_0001p.cbf', 'del_13.5_0001p.cbf', 'del_08.0_0001p.cbf', 'del_29.0_0001p.cbf', 'del_45.5_0001p.cbf', 'del_63.0_0001p.cbf', 'del_61.5_0001p.cbf', 'del_31.5_0001p.npt', 'del_11.0_0001p.cbf', 'del_46.5_0001p.cbf', 'del_11.5_0001p.cbf', 'del_56.0_0001p.cbf', 'del_18.0_0001p.cbf', 'del_06.5_0001p.cbf', 'del_46.0_0001p.cbf', 'del_58.5_0001p.cbf', 'del_35.5_0001p.npt', 'del_30.0_0001p.cbf', 'del_15.5_0001p.cbf', 'del_36.5_0001p.cbf', 'del_13.0_0001p.cbf', 'del_55.0_0001p.cbf', 'del_27.5_0001p.cbf', 'del_31.5_0001p.cbf', 'del_24.0_0001p.cbf', 'del_38.0_0001p.cbf', 'del_48.5_0001p.cbf', 'del_16.0_0001p.cbf', 'del_52.5_0001p.cbf', 'del_38.5_0001p.cbf', 'del_54.5_0001p.cbf', 'del_48.0_0001p.cbf', 'del_31.0_0001p.cbf', 'del_28.5_0001p.cbf', 'del_21.5_0001p.cbf', 'del_06.0_0001p.cbf', 'del_25.5_0001p.cbf', 'del_40.5_0001p.cbf', 'del_44.5_0001p.cbf', 'del_39.5_0001p.cbf', 'del_35.5_0001p.cbf', 'del_62.0_0001p.cbf', 'del_36.0_0001p.cbf', 'del_57.5_0001p.cbf', 'del_28.0_0001p.cbf', 'del_17.5_0001p.cbf', 'del_24.5_0001p.cbf', 'del_35.0_0001p.poni', 'del_50.5_0001p.cbf', 'del_18.5_0001p.cbf', 'del_27.0_0001p.cbf', 'del_19.5_0001p.cbf', 'del_21.0_0001p.cbf', 'del_17.0_0001p.cbf', 'del_50.0_0001p.cbf', 'del_44.0_0001p.cbf', 'del_30.5_0001p.cbf', 'del_51.5_0001p.cbf', 'del_62.5_0001p.cbf', 'del_05.0_0001p.cbf', 'del_26.5_0001p.cbf', 'del_31.5_0001p.poni', 'del_23.5_0001p.cbf', 'del_33.5_0001p.poni', 'del_37.5_0001p.cbf', 'del_19.0_0001p.cbf', 'del_29.5_0001p.cbf', 'del_10.0_0001p.cbf', 'del_40.0_0001p.cbf', 'del_58.0_0001p.cbf', 'del_49.5_0001p.cbf', 'del_09.5_0001p.cbf', 'del_15.0_0001p.cbf', 'del_43.0_0001p.cbf', 'del_60.5_0001p.cbf', 'del_34.0_0001p.cbf', 'del_20.0_0001p.cbf', 'deviation-mask.edf', 'del_41.0_0001p.cbf', 'del_07.0_0001p.cbf', 'del_54.0_0001p.cbf', 'del_33.5_0001p.npt', 'del_33.5_0001p.cbf', 'del_32.0_0001p.cbf', 'del_59.5_0001p.cbf', 'del_14.0_0001p.cbf', 'del_32.5_0001p.cbf', 'del_59.0_0001p.cbf', 'del_65.0_0001p.cbf', 'del_25.0_0001p.cbf', 'del_61.0_0001p.cbf', 'del_34.5_0001p.cbf', 'del_52.0_0001p.cbf', 'del_22.5_0001p.cbf', 'del_10.5_0001p.cbf', 'del_42.0_0001p.cbf', 'del_64.0_0001p.cbf', 'del_14.5_0001p.cbf', 'del_26.0_0001p.cbf', 'del_49.0_0001p.cbf', 'del_35.0_0001p.npt', 'del_55.5_0001p.cbf', 'del_23.0_0001p.cbf', 'del_12.0_0001p.cbf', 'del_37.0_0001p.cbf']\n"
     ]
    }
   ],
   "source": [
    "#Download all images\n",
    "\n",
    "import os\n",
    "from silx.resources import ExternalResources\n",
    "\n",
    "#Nota: This may be useful if you are behind a firewall\n",
    "#os.environ[\"http_proxy\"] = \"http://proxy.esrf.fr:3128\"\n",
    "\n",
    "downloader = ExternalResources(\"pyFAI\", \"http://www.silx.org/pub/pyFAI/testimages\", \"PYFAI_DATA\")\n",
    "all_files = downloader.getdir(\"LaB6_gonio_BM20.tar.bz2\")\n",
    "print([os.path.basename(i) for i in all_files])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Loading of a few libraries\n",
    "\n",
    "import os\n",
    "import random\n",
    "import fabio\n",
    "import pyFAI\n",
    "from pyFAI.goniometer import GeometryTransformation, GoniometerRefinement, Goniometer\n",
    "from pyFAI.gui import jupyter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Display of an image and its headers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "List of images: del_05.0_0001p.cbf, del_05.5_0001p.cbf, del_06.0_0001p.cbf, del_06.5_0001p.cbf, del_07.0_0001p.cbf, del_07.5_0001p.cbf, del_08.0_0001p.cbf, del_08.5_0001p.cbf, del_09.0_0001p.cbf, del_09.5_0001p.cbf, del_10.0_0001p.cbf, del_10.5_0001p.cbf, del_11.0_0001p.cbf, del_11.5_0001p.cbf, del_12.0_0001p.cbf, del_12.5_0001p.cbf, del_13.0_0001p.cbf, del_13.5_0001p.cbf, del_14.0_0001p.cbf, del_14.5_0001p.cbf, del_15.0_0001p.cbf, del_15.5_0001p.cbf, del_16.0_0001p.cbf, del_16.5_0001p.cbf, del_17.0_0001p.cbf, del_17.5_0001p.cbf, del_18.0_0001p.cbf, del_18.5_0001p.cbf, del_19.0_0001p.cbf, del_19.5_0001p.cbf, del_20.0_0001p.cbf, del_20.5_0001p.cbf, del_21.0_0001p.cbf, del_21.5_0001p.cbf, del_22.0_0001p.cbf, del_22.5_0001p.cbf, del_23.0_0001p.cbf, del_23.5_0001p.cbf, del_24.0_0001p.cbf, del_24.5_0001p.cbf, del_25.0_0001p.cbf, del_25.5_0001p.cbf, del_26.0_0001p.cbf, del_26.5_0001p.cbf, del_27.0_0001p.cbf, del_27.5_0001p.cbf, del_28.0_0001p.cbf, del_28.5_0001p.cbf, del_29.0_0001p.cbf, del_29.5_0001p.cbf, del_30.0_0001p.cbf, del_30.5_0001p.cbf, del_31.0_0001p.cbf, del_31.5_0001p.cbf, del_32.0_0001p.cbf, del_32.5_0001p.cbf, del_33.0_0001p.cbf, del_33.5_0001p.cbf, del_34.0_0001p.cbf, del_34.5_0001p.cbf, del_35.0_0001p.cbf, del_35.5_0001p.cbf, del_36.0_0001p.cbf, del_36.5_0001p.cbf, del_37.0_0001p.cbf, del_37.5_0001p.cbf, del_38.0_0001p.cbf, del_38.5_0001p.cbf, del_39.0_0001p.cbf, del_39.5_0001p.cbf, del_40.0_0001p.cbf, del_40.5_0001p.cbf, del_41.0_0001p.cbf, del_41.5_0001p.cbf, del_42.0_0001p.cbf, del_42.5_0001p.cbf, del_43.0_0001p.cbf, del_43.5_0001p.cbf, del_44.0_0001p.cbf, del_44.5_0001p.cbf, del_45.0_0001p.cbf, del_45.5_0001p.cbf, del_46.0_0001p.cbf, del_46.5_0001p.cbf, del_47.0_0001p.cbf, del_47.5_0001p.cbf, del_48.0_0001p.cbf, del_48.5_0001p.cbf, del_49.0_0001p.cbf, del_49.5_0001p.cbf, del_50.0_0001p.cbf, del_50.5_0001p.cbf, del_51.0_0001p.cbf, del_51.5_0001p.cbf, del_52.0_0001p.cbf, del_52.5_0001p.cbf, del_53.0_0001p.cbf, del_53.5_0001p.cbf, del_54.0_0001p.cbf, del_54.5_0001p.cbf, del_55.0_0001p.cbf, del_55.5_0001p.cbf, del_56.0_0001p.cbf, del_56.5_0001p.cbf, del_57.0_0001p.cbf, del_57.5_0001p.cbf, del_58.0_0001p.cbf, del_58.5_0001p.cbf, del_59.0_0001p.cbf, del_59.5_0001p.cbf, del_60.0_0001p.cbf, del_60.5_0001p.cbf, del_61.0_0001p.cbf, del_61.5_0001p.cbf, del_62.0_0001p.cbf, del_62.5_0001p.cbf, del_63.0_0001p.cbf, del_63.5_0001p.cbf, del_64.0_0001p.cbf, del_64.5_0001p.cbf, del_65.0_0001p.cbf.\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\r\n",
      "# 2016-05-17T18:12:57.232113\r\n",
      "# Pixel_size 172e-6 m x 172e-6 m\r\n",
      "# Silicon sensor, thickness 0.000450 m\r\n",
      "# Exposure_time 9.9977 s\r\n",
      "# Exposure_period 9.9977 s\r\n",
      "# Tau = 1.991e-07 s\r\n",
      "# Count_cutoff 1071182 counts\r\n",
      "# Threshold_setting: 4024.0 eV\r\n",
      "# Gain_setting: low gain (vrf = -0.300)\r\n",
      "# N_excluded_pixels = 1\r\n",
      "# Excluded_pixels: badpix_mask.tif\r\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\r\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\r\n",
      "# Image_path: /ramdisk/\r\n",
      "# Wavelength 0.7749 A\r\n",
      "# Start_angle 0.00 deg.\r\n",
      "# Angle_increment 0.00 deg.\r\n",
      "# Omega 0.00 deg.\r\n",
      "# Omega_increment 0.00 deg.\r\n",
      "# Phi 0.00 deg.\r\n",
      "# Phi_increment 0.00 deg.\r\n",
      "# Kappa 0.0 deg.\r\n",
      "# Oscillation_axis PHI\r\n",
      "# Detector_distance 0.157 m\r\n",
      "# Detector_Voffset 0.0 m\r\n",
      "# Beam_xy (542.41, 732.4) pixels\r\n",
      "# Flux 0 counts\r\n",
      "# Temperature 0.00 K\r\n",
      "# Blower 0.0 C\r\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "Image headers:\n",
      "_array_data.header_convention: PILATUS_1.2\n",
      "_array_data.header_contents: # Detector: PILATUS 2M, 24-0111\r\n",
      "# 2016-05-17T18:12:57.232113\r\n",
      "# Pixel_size 172e-6 m x 172e-6 m\r\n",
      "# Silicon sensor, thickness 0.000450 m\r\n",
      "# Exposure_time 9.9977 s\r\n",
      "# Exposure_period 9.9977 s\r\n",
      "# Tau = 1.991e-07 s\r\n",
      "# Count_cutoff 1071182 counts\r\n",
      "# Threshold_setting: 4024.0 eV\r\n",
      "# Gain_setting: low gain (vrf = -0.300)\r\n",
      "# N_excluded_pixels = 1\r\n",
      "# Excluded_pixels: badpix_mask.tif\r\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\r\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\r\n",
      "# Image_path: /ramdisk/\r\n",
      "# Wavelength 0.7749 A\r\n",
      "# Start_angle 0.00 deg.\r\n",
      "# Angle_increment 0.00 deg.\r\n",
      "# Omega 0.00 deg.\r\n",
      "# Omega_increment 0.00 deg.\r\n",
      "# Phi 0.00 deg.\r\n",
      "# Phi_increment 0.00 deg.\r\n",
      "# Kappa 0.0 deg.\r\n",
      "# Oscillation_axis PHI\r\n",
      "# Detector_distance 0.157 m\r\n",
      "# Detector_Voffset 0.0 m\r\n",
      "# Beam_xy (542.41, 732.4) pixels\r\n",
      "# Flux 0 counts\r\n",
      "# Temperature 0.00 K\r\n",
      "# Blower 0.0 C\r\n",
      "# Lakeshore 0.00 K\n",
      "Content-Type: application/octet-stream;\n",
      "conversions: x-CBF_BYTE_OFFSET\n",
      "Content-Transfer-Encoding: BINARY\n",
      "X-Binary-Size: 95035\n",
      "X-Binary-ID: 1\n",
      "X-Binary-Element-Type: signed 32-bit integer\n",
      "X-Binary-Element-Byte-Order: LITTLE_ENDIAN\n",
      "Content-MD5: darooj/7FEQRNdNzNDo0XQ==\n",
      "X-Binary-Number-of-Elements: 94965\n",
      "X-Binary-Size-Fastest-Dimension: 487\n",
      "X-Binary-Size-Second-Dimension: 195\n",
      "X-Binary-Size-Padding: 4095\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#loading of the list of files, and display of the last one with its headers\n",
    "\n",
    "image_files = [i for i in all_files if i.endswith(\".cbf\")]\n",
    "image_files.sort()\n",
    "print(\"List of images: \" + \", \".join([os.path.basename(i) for i in image_files]) + \".\" + os.linesep)\n",
    "fimg = fabio.open(image_files[-1])\n",
    "\n",
    "print(\"Image headers:\")\n",
    "for key, value in  fimg.header.items():\n",
    "    print(\"%s: %s\"%(key,value))\n",
    "    \n",
    "jupyter.display(fimg.data, label=os.path.basename(fimg.filename))\n",
    "pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Definition of the geometry transformation\n",
    "\n",
    "This is the most difficult part to understand.\n",
    "\n",
    "The next cell defines 2 functions, one for transforming the geometry and the other one to read the goniometer angle from the metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "filename del_65.0_0001p.cbf angle: 65.0\n"
     ]
    }
   ],
   "source": [
    "#Definition of the goniometer translation function:\n",
    "# The detector rotates vertically, around the horizontal axis, i.e. rot2\n",
    "\n",
    "goniotrans = GeometryTransformation(param_names = [\"dist\", \"poni1\", \"poni2\", \"rot1\",\n",
    "                                                   \"rot2_offset\", \"rot2_scale\"],\n",
    "                                    dist_expr=\"dist\", \n",
    "                                    poni1_expr=\"poni1\",\n",
    "                                    poni2_expr=\"poni2\", \n",
    "                                    rot1_expr=\"rot1\", \n",
    "                                    rot2_expr=\"rot2_scale * pos + rot2_offset\", \n",
    "                                    rot3_expr=\"0.0\")\n",
    "\n",
    "\n",
    "#Definition of the function reading the goniometer angle from the filename of the image.\n",
    "\n",
    "def get_angle(basename):\n",
    "    \"\"\"Takes the basename (like del_65.0_0001p ) and returns the angle of the detector\"\"\"\n",
    "    return float(os.path.basename((basename.split(\"_\")[1])))\n",
    "\n",
    "basename = os.path.basename(fimg.filename)\n",
    "print('filename', basename, \"angle:\",get_angle(basename))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Definition of the detector, its mask, the calibrant\n",
    "mask_files = [i for i in all_files if i.endswith(\"-mask.edf\")]\n",
    "mask = numpy.logical_or(fabio.open(mask_files[0]).data, fabio.open(mask_files[1]).data)\n",
    "pilatus = pyFAI.detector_factory(\"Pilatus100k\")\n",
    "pilatus.mask = mask\n",
    "    \n",
    "LaB6 = pyFAI.calibrant.CALIBRANT_FACTORY(\"LaB6\")\n",
    "wavelength = 7.7490120575e-11\n",
    "LaB6.wavelength = wavelength"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Empty refinement object:\n",
      "GoniometerRefinement with 0 geometries labeled: .\n"
     ]
    }
   ],
   "source": [
    "#Definition of the geometry refinement: the parameter order is the same as the param_names\n",
    "epsilon = numpy.finfo(numpy.float32).eps\n",
    "param = {\"dist\":0.8, \n",
    "         \"poni1\":0.02, \n",
    "         \"poni2\":0.04, \n",
    "         \"rot1\":0,\n",
    "         \"rot2_offset\":0,\n",
    "         \"rot2_scale\": numpy.pi/180. # rot2 is in radians, while the motor position is in degrees\n",
    "        }\n",
    "#Defines the bounds for some variables\n",
    "bounds = {\"dist\": (0.79, 0.81), \n",
    "          \"rot1\": (-0.01, 0.01),\n",
    "          \"rot2_offset\": (-0.01, 0.01),\n",
    "          \"rot2_scale\": (numpy.pi/180.-epsilon, numpy.pi/180.+epsilon) #strict bounds on the scale: we expect the gonio to be precise\n",
    "         }\n",
    "gonioref = GoniometerRefinement(param, #initial guess\n",
    "                                bounds=bounds,\n",
    "                                pos_function=get_angle,\n",
    "                                trans_function=goniotrans,\n",
    "                                detector=pilatus, wavelength=wavelength)\n",
    "print(\"Empty refinement object:\")\n",
    "print(gonioref)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:58:02.580029\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_31.5_0001p Angle: 31.5\n",
      "Detector Pilatus 100k\t PixelSize= 1.720e-04, 1.720e-04 m\n",
      "Wavelength= 7.749012e-11m\n",
      "SampleDetDist= 8.058209e-01m\tPONI= 5.700310e-03, 4.599931e-02m\trot1=-0.000000  rot2= 0.560707  rot3= -0.000065 rad\n",
      "DirectBeamDist= 951.518mm\tCenter: x=267.438, y=2975.017 pix\tTilt=32.126 deg  tiltPlanRotation= 90.000 deg\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:58:33.361867\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_33.5_0001p Angle: 33.5\n",
      "Detector Pilatus 100k\t PixelSize= 1.720e-04, 1.720e-04 m\n",
      "Wavelength= 7.749012e-11m\n",
      "SampleDetDist= 8.061475e-01m\tPONI= 1.998418e-02, 4.623309e-02m\trot1=0.000061  rot2= 0.577898  rot3= -0.000000 rad\n",
      "DirectBeamDist= 962.435mm\tCenter: x=268.511, y=3172.837 pix\tTilt=33.111 deg  tiltPlanRotation= 90.005 deg\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:59:37.224041\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_35.0_0001p Angle: 35.0\n",
      "Detector Pilatus 100k\t PixelSize= 1.720e-04, 1.720e-04 m\n",
      "Wavelength= 7.749012e-11m\n",
      "SampleDetDist= 8.053432e-01m\tPONI= 5.551240e-03, 4.624546e-02m\trot1=-0.000016  rot2= 0.622009  rot3= 0.000012 rad\n",
      "DirectBeamDist= 990.936mm\tCenter: x=268.944, y=3389.181 pix\tTilt=35.638 deg  tiltPlanRotation= 89.999 deg\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:59:37.317526\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_35.5_0001p Angle: 35.5\n",
      "Detector Pilatus 100k\t PixelSize= 1.720e-04, 1.720e-04 m\n",
      "Wavelength= 7.749012e-11m\n",
      "SampleDetDist= 8.061272e-01m\tPONI= 5.998339e-03, 3.450065e-02m\trot1=-0.014779  rot2= 0.630136  rot3= 0.000007 rad\n",
      "DirectBeamDist= 997.856mm\tCenter: x=269.857, y=3453.432 pix\tTilt=36.113 deg  tiltPlanRotation= 88.839 deg\n",
      "\n",
      "Filled refinement object:\n",
      "GoniometerRefinement with 4 geometries labeled: del_31.5_0001p, del_33.5_0001p, del_35.0_0001p, del_35.5_0001p.\n"
     ]
    }
   ],
   "source": [
    "#Let's populate the goniometer refinement object with all control point files:\n",
    "\n",
    "ponis = [i for i in all_files if i.endswith(\".poni\")]\n",
    "ponis.sort()\n",
    "for fn in ponis:\n",
    "    base = os.path.splitext(fn)[0]\n",
    "    basename = os.path.basename(base)\n",
    "    fimg = fabio.open(base + \".cbf\")\n",
    "    sg =gonioref.new_geometry(basename, image=fimg.data, metadata=basename, control_points=base+\".npt\",\n",
    "                              geometry=fn, calibrant=LaB6)\n",
    "    print(sg.label, \"Angle:\", sg.get_position())\n",
    "    print(sg.geometry_refinement)\n",
    "    print()\n",
    "    \n",
    "\n",
    "print(\"Filled refinement object:\")\n",
    "print(gonioref)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n",
      "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n",
      "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Display all images with associated calibration:\n",
    "nimg = len(gonioref.single_geometries)\n",
    "fig,ax = subplots(nimg, 1, figsize=(20,nimg*5))\n",
    "for i, sg in enumerate(gonioref.single_geometries.values()):\n",
    "    jupyter.display(sg=sg, ax=ax[i])\n",
    "pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function before refinement: 4.6762802794818724e-05\n",
      "[0.8        0.02       0.04       0.         0.         0.01745329]\n",
      "     fun: 3.473034229473271e-09\n",
      "     jac: array([ 1.55799982e-08,  6.20957747e-08, -8.86843207e-09,  9.37828842e-09,\n",
      "        4.54540993e-08, -2.83664178e-05])\n",
      " message: 'Optimization terminated successfully'\n",
      "    nfev: 127\n",
      "     nit: 18\n",
      "    njev: 18\n",
      "  status: 0\n",
      " success: True\n",
      "       x: array([ 0.80587908,  0.01626749,  0.04374863, -0.00299852, -0.00217975,\n",
      "        0.01745341])\n",
      "Cost function after refinement: 3.473034229473271e-09\n",
      "GonioParam(dist=0.8058790848800199, poni1=0.0162674931897931, poni2=0.04374863086696927, rot1=-0.002998518469094807, rot2_offset=-0.0021797516602028453, rot2_scale=0.017453411729232846)\n",
      "maxdelta on: dist (0) 0.8 --> 0.8058790848800199\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([ 0.80587908,  0.01626749,  0.04374863, -0.00299852, -0.00217975,\n",
       "        0.01745341])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Initial refinement of the goniometer model with 5 dof\n",
    "gonioref.refine2()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This function adds new images to the pool of data used for the refinement.\n",
    "# A set of new control points are extractred and a refinement step is performed at each iteration\n",
    "# The last image of the serie is displayed \n",
    "\n",
    "def optimize_with_new_images(list_images, pts_per_deg=1):\n",
    "    sg = None\n",
    "    for fname in list_images:\n",
    "        print()\n",
    "        basename = os.path.basename(fname)\n",
    "        base = os.path.splitext(basename)[0]\n",
    "        fimg = fabio.open(fname)\n",
    "        if base in gonioref.single_geometries:\n",
    "            continue\n",
    "        print(base)\n",
    "        sg = gonioref.new_geometry(base, image=fimg.data, metadata=base,\n",
    "                                   calibrant=LaB6)\n",
    "        print(sg.extract_cp(pts_per_deg=pts_per_deg))\n",
    "    print(\"*\"*50)\n",
    "    gonioref.refine2()\n",
    "    if sg: \n",
    "        sg.geometry_refinement.set_param(gonioref.get_ai(sg.get_position()).param)\n",
    "        jupyter.display(sg=sg)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:58:33.361867\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:58:02.582382\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_32.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# c ring 7: 36 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:57:32.432726\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_31.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# d ring 6: 36 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:58:02.580029\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:00:40.700773\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_37.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# e ring 10: 30 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:00:09.326905\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_37.0_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "# f ring 9: 36 points\n",
      "# g ring 10: 30 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:00:40.645355\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_38.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# h ring 10: 30 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:59:06.597806\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_34.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# i ring 8: 36 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:59:37.224041\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:00:08.831529\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_36.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# j ring 9: 36 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:56:59.409568\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_30.0_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# k ring 6: 36 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:59:06.546917\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_34.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# l ring 8: 36 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:58:32.966935\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_32.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# m ring 7: 36 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:00:07.604638\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_36.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# n ring 9: 36 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:01:11.953191\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_39.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "# o ring 10: 15 points\n",
      "# p ring 11: 30 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:01:11.369300\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_38.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "# q ring 10: 30 points\n",
      "# r ring 11: 30 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:59:37.317526\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:58:32.868105\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_33.0_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# s ring 7: 36 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:01:41.982449\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_39.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# t ring 11: 30 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:57:32.480631\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_30.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# u ring 6: 36 points\n",
      "**************************************************\n",
      "Cost function before refinement: 3.766592152779999e-09\n",
      "[ 0.80587908  0.01626749  0.04374863 -0.00299852 -0.00217975  0.01745341]\n",
      "     fun: 3.766258223807482e-09\n",
      "     jac: array([-5.46393989e-08,  3.22711980e-06, -4.29656113e-07,  3.46971975e-07,\n",
      "        2.59749645e-06,  1.56865397e-05])\n",
      " message: 'Optimization terminated successfully'\n",
      "    nfev: 9\n",
      "     nit: 1\n",
      "    njev: 1\n",
      "  status: 0\n",
      " success: True\n",
      "       x: array([ 0.80587909,  0.01626717,  0.04374867, -0.00299855, -0.00218001,\n",
      "        0.01745339])\n",
      "Cost function after refinement: 3.766258223807482e-09\n",
      "GonioParam(dist=0.8058790903439598, poni1=0.01626717047781262, poni2=0.04374867383258055, rot1=-0.0029985531662923056, rot2_offset=-0.0021800114098476826, rot2_scale=0.017453387887374935)\n",
      "maxdelta on: poni1 (1) 0.0162674931897931 --> 0.01626717047781262\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Append all other images bewteen 30 and 40 degrees\n",
    "\n",
    "images_30_40 = [i for i in all_files if (\"del_3\" in i and i.endswith(\"0001p.cbf\"))]\n",
    "random.shuffle(images_30_40)\n",
    "optimize_with_new_images(images_30_40, pts_per_deg=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:00:40.700773\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:55:26.748303\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_25.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# v ring 5: 14 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:02:46.685371\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_42.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# w ring 12: 10 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:04:49.737761\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_47.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "# x ring 15: 9 points\n",
      "# y ring 16: 9 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:07:51.745974\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_54.0_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "# z ring 20: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:03:16.919311\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_44.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#aa ring 13: 10 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:56:59.409568\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:53:21.833734\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_21.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ab ring 3: 17 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:51:49.460937\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_17.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ac ring 2: 10 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:51:16.466087\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_17.0_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:11:56.968950\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_63.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ad ring 26: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:09:22.227947\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_57.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#ae ring 22: 8 points\n",
      "#af ring 23: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:51:17.713326\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_16.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:11:26.796947\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_61.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#ag ring 24: 8 points\n",
      "#ah ring 25: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:09:22.286232\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_56.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#ai ring 21: 8 points\n",
      "#aj ring 22: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:58:02.582382\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:56:59.074224\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_29.5_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ak ring 6: 7 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:01:11.369300\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:54:25.658620\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_24.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#al ring 4: 16 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:47:07.437556\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_08.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:05:50.748445\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_49.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#am ring 16: 9 points\n",
      "#an ring 17: 9 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:05:19.857851\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_47.5_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#ao ring 15: 10 points\n",
      "#ap ring 16: 9 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:03:49.393539\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_45.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#aq ring 13: 10 points\n",
      "#ar ring 14: 10 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:07:21.158164\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_53.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#as ring 19: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:08:21.938398\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_55.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#at ring 20: 8 points\n",
      "#au ring 21: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:48:11.751042\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_09.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#av ring 0: 14 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:11:56.972388\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_62.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#aw ring 25: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:12:27.104873\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_64.0_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#ax ring 26: 8 points\n",
      "#ay ring 27: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:52:51.449325\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_20.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#az ring 3: 17 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:46:36.466476\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_05.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:48:43.384293\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_11.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ba ring 0: 30 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:47:40.148257\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_08.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:08:52.082984\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_56.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#bb ring 21: 8 points\n",
      "#bc ring 22: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:59:37.317526\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:54:56.039040\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_25.0_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#bd ring 4: 16 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:10:23.107378\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_59.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#be ring 23: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:05:19.835968\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_48.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#bf ring 16: 9 points\n",
      "#bg ring 17: 6 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:52:19.459627\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_18.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#bh ring 2: 19 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:04:19.581993\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_46.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#bi ring 14: 6 points\n",
      "#bj ring 15: 10 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:10:53.630595\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_61.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#bk ring 24: 8 points\n",
      "#bl ring 25: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:10:53.311728\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_60.0_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#bm ring 24: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:47:07.379855\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_07.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:59:06.597806\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:48:42.669772\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_10.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#bn ring 0: 29 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:06:51.043790\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_51.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#bo ring 18: 8 points\n",
      "#bp ring 19: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:00:08.831529\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:48:11.777647\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_10.0_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#bq ring 0: 30 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:47:07.895049\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_07.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:57:32.432726\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:01:42.171908\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_40.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#br ring 11: 7 points\n",
      "#bs ring 12: 10 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:04:49.733151\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_46.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#bt ring 14: 7 points\n",
      "#bu ring 15: 10 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:01:11.953191\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:49:08.474805\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_12.0_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#bv ring 0: 11 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:06:20.898004\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_50.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#bw ring 17: 9 points\n",
      "#bx ring 18: 7 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:50:13.843265\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_14.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#by ring 1: 10 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:00:09.326905\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:59:37.224041\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:50:43.940233\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_16.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#bz ring 1: 24 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:53:52.164598\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_23.0_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ca ring 4: 11 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:07:21.138279\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_52.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cb ring 19: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:54:56.024349\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_24.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cc ring 4: 16 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:10:23.130977\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_59.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cd ring 24: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:02:46.794703\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_42.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:01:41.982449\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:55:58.657692\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_27.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ce ring 5: 14 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:58:32.966935\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:06:51.042664\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_51.5_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#cf ring 18: 8 points\n",
      "#cg ring 19: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:56:28.921493\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_28.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:57:32.480631\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:03:49.396898\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_44.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#ch ring 13: 10 points\n",
      "#ci ring 14: 9 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:50:43.944463\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_15.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cj ring 1: 24 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:10:53.308754\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_60.5_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#ck ring 24: 8 points\n",
      "#cl ring 25: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:52:19.395986\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_19.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cm ring 2: 19 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:06:20.873277\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_50.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#cn ring 17: 9 points\n",
      "#co ring 18: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:05:50.711407\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_49.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#cp ring 17: 9 points\n",
      "#cq ring 18: 3 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:59:06.546917\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:47:40.172838\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_09.0_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:07:51.740210\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_53.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cr ring 20: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:03:16.929475\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_43.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cs ring 13: 7 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:56:59.183698\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_29.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:51:49.000269\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_18.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ct ring 2: 19 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:46:36.390007\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_05.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:58:02.580029\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:49:43.103540\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_13.5_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:53:52.155580\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_22.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cu ring 3: 17 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:53:53.197702\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_22.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cv ring 3: 17 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:55:27.317792\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_26.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cw ring 5: 14 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:08:21.925094\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_54.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#cx ring 20: 7 points\n",
      "#cy ring 21: 3 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:50:43.943389\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_15.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#cz ring 1: 24 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:53:21.829650\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_21.0_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#da ring 3: 17 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:12:27.101423\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_63.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#db ring 26: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:55:59.059808\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_27.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dc ring 5: 14 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:01:41.972219\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_40.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#dd ring 11: 10 points\n",
      "#de ring 12: 9 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:09:52.928746\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_58.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#df ring 22: 8 points\n",
      "#dg ring 23: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:05:19.864716\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_48.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dh ring 16: 9 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:02:15.504419\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_41.0_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#di ring 12: 10 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:46:36.167174\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_06.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:12:57.232113\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_65.0_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#dj ring 27: 8 points\n",
      "#dk ring 28: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:46:36.193634\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_06.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:12:57.267417\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_64.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#dl ring 26: 6 points\n",
      "#dm ring 27: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:08:52.117818\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_55.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#dn ring 20: 8 points\n",
      "#do ring 21: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:50:13.842304\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_14.5_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dp ring 1: 24 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:03:16.948608\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_43.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dq ring 13: 10 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:48:42.929032\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_11.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dr ring 0: 32 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:49:43.698077\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_13.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:07:21.128270\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_52.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ds ring 19: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:04:19.559281\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_45.5_0001p\n",
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#dt ring 14: 10 points\n",
      "#du ring 15: 1 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:11:26.772890\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_62.0_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dv ring 25: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:52:19.446852\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_19.0_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dw ring 2: 19 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:09:52.932036\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_58.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dx ring 23: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:58:33.361867\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:49:08.629752\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_12.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:02:15.493007\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_41.5_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dy ring 12: 10 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:54:26.138958\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_23.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#dz ring 4: 16 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:56:28.910072\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_28.5_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T17:55:26.939117\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_26.5_0001p\n",
      "ControlPoints instance containing 1 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 1 groups of points:\n",
      "#ea ring 5: 14 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:00:07.604638\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\n",
      "# 2016-05-17T18:09:22.316089\n",
      "# Pixel_size 172e-6 m x 172e-6 m\n",
      "# Silicon sensor, thickness 0.000450 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.300)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Start_angle 0.00 deg.\n",
      "# Angle_increment 0.00 deg.\n",
      "# Omega 0.00 deg.\n",
      "# Omega_increment 0.00 deg.\n",
      "# Phi 0.00 deg.\n",
      "# Phi_increment 0.00 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0 counts\n",
      "# Temperature 0.00 K\n",
      "# Blower 0.0 C\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_57.5_0001p\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ControlPoints instance containing 2 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 2 groups of points:\n",
      "#eb ring 22: 8 points\n",
      "#ec ring 23: 8 points\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\r\n",
      "# 2016-05-17T17:58:32.868105\r\n",
      "# Pixel_size 172e-6 m x 172e-6 m\r\n",
      "# Silicon sensor, thickness 0.000450 m\r\n",
      "# Exposure_time 9.9977 s\r\n",
      "# Exposure_period 9.9977 s\r\n",
      "# Tau = 1.991e-07 s\r\n",
      "# Count_cutoff 1071182 counts\r\n",
      "# Threshold_setting: 4024.0 eV\r\n",
      "# Gain_setting: low gain (vrf = -0.300)\r\n",
      "# N_excluded_pixels = 1\r\n",
      "# Excluded_pixels: badpix_mask.tif\r\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\r\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\r\n",
      "# Image_path: /ramdisk/\r\n",
      "# Wavelength 0.7749 A\r\n",
      "# Start_angle 0.00 deg.\r\n",
      "# Angle_increment 0.00 deg.\r\n",
      "# Omega 0.00 deg.\r\n",
      "# Omega_increment 0.00 deg.\r\n",
      "# Phi 0.00 deg.\r\n",
      "# Phi_increment 0.00 deg.\r\n",
      "# Kappa 0.0 deg.\r\n",
      "# Oscillation_axis PHI\r\n",
      "# Detector_distance 0.157 m\r\n",
      "# Detector_Voffset 0.0 m\r\n",
      "# Beam_xy (542.41, 732.4) pixels\r\n",
      "# Flux 0 counts\r\n",
      "# Temperature 0.00 K\r\n",
      "# Blower 0.0 C\r\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\r\n",
      "# 2016-05-17T17:52:51.784421\r\n",
      "# Pixel_size 172e-6 m x 172e-6 m\r\n",
      "# Silicon sensor, thickness 0.000450 m\r\n",
      "# Exposure_time 9.9977 s\r\n",
      "# Exposure_period 9.9977 s\r\n",
      "# Tau = 1.991e-07 s\r\n",
      "# Count_cutoff 1071182 counts\r\n",
      "# Threshold_setting: 4024.0 eV\r\n",
      "# Gain_setting: low gain (vrf = -0.300)\r\n",
      "# N_excluded_pixels = 1\r\n",
      "# Excluded_pixels: badpix_mask.tif\r\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\r\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\r\n",
      "# Image_path: /ramdisk/\r\n",
      "# Wavelength 0.7749 A\r\n",
      "# Start_angle 0.00 deg.\r\n",
      "# Angle_increment 0.00 deg.\r\n",
      "# Omega 0.00 deg.\r\n",
      "# Omega_increment 0.00 deg.\r\n",
      "# Phi 0.00 deg.\r\n",
      "# Phi_increment 0.00 deg.\r\n",
      "# Kappa 0.0 deg.\r\n",
      "# Oscillation_axis PHI\r\n",
      "# Detector_distance 0.157 m\r\n",
      "# Detector_Voffset 0.0 m\r\n",
      "# Beam_xy (542.41, 732.4) pixels\r\n",
      "# Flux 0 counts\r\n",
      "# Temperature 0.00 K\r\n",
      "# Blower 0.0 C\r\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "del_20.0_0001p\n",
      "ControlPoints instance containing 0 group of point:\n",
      "LaB6 Calibrant with 97 reflections at wavelength 7.7490120575e-11\n",
      "Containing 0 groups of points:\n",
      "\n",
      "# Detector: PILATUS 2M, 24-0111\r\n",
      "# 2016-05-17T18:00:40.645355\r\n",
      "# Pixel_size 172e-6 m x 172e-6 m\r\n",
      "# Silicon sensor, thickness 0.000450 m\r\n",
      "# Exposure_time 9.9977 s\r\n",
      "# Exposure_period 9.9977 s\r\n",
      "# Tau = 1.991e-07 s\r\n",
      "# Count_cutoff 1071182 counts\r\n",
      "# Threshold_setting: 4024.0 eV\r\n",
      "# Gain_setting: low gain (vrf = -0.300)\r\n",
      "# N_excluded_pixels = 1\r\n",
      "# Excluded_pixels: badpix_mask.tif\r\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\r\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\r\n",
      "# Image_path: /ramdisk/\r\n",
      "# Wavelength 0.7749 A\r\n",
      "# Start_angle 0.00 deg.\r\n",
      "# Angle_increment 0.00 deg.\r\n",
      "# Omega 0.00 deg.\r\n",
      "# Omega_increment 0.00 deg.\r\n",
      "# Phi 0.00 deg.\r\n",
      "# Phi_increment 0.00 deg.\r\n",
      "# Kappa 0.0 deg.\r\n",
      "# Oscillation_axis PHI\r\n",
      "# Detector_distance 0.157 m\r\n",
      "# Detector_Voffset 0.0 m\r\n",
      "# Beam_xy (542.41, 732.4) pixels\r\n",
      "# Flux 0 counts\r\n",
      "# Temperature 0.00 K\r\n",
      "# Blower 0.0 C\r\n",
      "# Lakeshore 0.00 K\n",
      "# Detector: PILATUS 2M 24-0111\n",
      "# Silicon sensor, thickness 0.00045 m\n",
      "# Pixel_size 0.000172 m x 0.000172 m\n",
      "# Exposure_time 9.9977 s\n",
      "# Exposure_period 9.9977 s\n",
      "# Tau = 1.991e-07 s\n",
      "# Count_cutoff 1071182 counts\n",
      "# Threshold_setting: 4024.0 eV\n",
      "# Gain_setting: low gain (vrf = -0.200)\n",
      "# N_excluded_pixels = 1\n",
      "# Excluded_pixels: badpix_mask.tif\n",
      "# Flat_field: FF_p2m0111_E26000_T13000_vrf_m0p30.tif\n",
      "# Trim_file: p2m0111_E26000_T13000_vrf_m0p30.bin\n",
      "# Image_path: /ramdisk/\n",
      "# Wavelength 0.7749 A\n",
      "# Detector_distance 0.157 m\n",
      "# Detector_Voffset 0.0 m\n",
      "# Beam_xy (542.41, 732.4) pixels\n",
      "# Flux 0.0\n",
      "# Start_angle 0.0 deg.\n",
      "# Angle_increment 0.0 deg.\n",
      "# Kappa 0.0 deg.\n",
      "# Phi 0.0 deg.\n",
      "# Phi_increment 0.0 deg.\n",
      "# Omega 0.0 deg.\n",
      "# Omega_increment 0.0 deg.\n",
      "# Oscillation_axis PHI\n",
      "**************************************************\n",
      "Cost function before refinement: 1.517800057716375e-08\n",
      "[ 0.80587909  0.01626717  0.04374867 -0.00299855 -0.00218001  0.01745339]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python3/dist-packages/pyFAI/gui/jupyter.py:79: UserWarning: No contour levels were found within the data range.\n",
      "  ax.contour(ttha, levels=tth, cmap=\"autumn\", linewidths=2, linestyles=\"dashed\")\n",
      "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     fun: 1.2414040557448947e-08\n",
      "     jac: array([-4.44688063e-08,  1.00231909e-06, -2.02577827e-08,  1.05803497e-08,\n",
      "        8.09666953e-07, -9.25612549e-04])\n",
      " message: 'Optimization terminated successfully'\n",
      "    nfev: 43\n",
      "     nit: 6\n",
      "    njev: 6\n",
      "  status: 0\n",
      " success: True\n",
      "       x: array([ 0.8058814 ,  0.0162719 ,  0.04328121, -0.00262068, -0.0021759 ,\n",
      "        0.01745341])\n",
      "Cost function after refinement: 1.2414040557448947e-08\n",
      "GonioParam(dist=0.8058813979197966, poni1=0.01627189950015672, poni2=0.04328120973866541, rot1=-0.0026206837097791915, rot2_offset=-0.002175895268095377, rot2_scale=0.017453411729232846)\n",
      "maxdelta on: poni2 (2) 0.04374867383258055 --> 0.04328120973866541\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Append all other images\n",
    "\n",
    "all_images = [i for i in all_files if i.endswith(\".cbf\")]\n",
    "random.shuffle(all_images)\n",
    "optimize_with_new_images(all_images)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "First & last rings\n",
      "Total number of images: 121\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Check the calibration of the first and the last image with rings\n",
    "\n",
    "print(\"First & last rings\")\n",
    "\n",
    "print(\"Total number of images:\", len(gonioref.single_geometries) )\n",
    "\n",
    "fig,ax  = subplots(2, 1, figsize=(20,8))\n",
    "for idx,lbl in enumerate([\"del_10.0_0001p\", \"del_65.0_0001p\"]):\n",
    "    sg = gonioref.single_geometries[lbl]\n",
    "    if sg.control_points.get_labels():\n",
    "        sg.geometry_refinement.set_param(gonioref.get_ai(sg.get_position()).param)\n",
    "    jupyter.display(sg=sg, ax=ax[idx])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function before refinement: 1.2414040557448947e-08\n",
      "[ 0.8058814   0.0162719   0.04328121 -0.00262068 -0.0021759   0.01745341]\n",
      "     fun: 1.1201428917916492e-08\n",
      "     jac: array([ 6.84361876e-08, -9.89309304e-09,  5.37037353e-07, -4.40259184e-07,\n",
      "       -5.62483551e-09, -2.50305180e-08])\n",
      " message: 'Optimization terminated successfully'\n",
      "    nfev: 32\n",
      "     nit: 4\n",
      "    njev: 4\n",
      "  status: 0\n",
      " success: True\n",
      "       x: array([ 0.80588143,  0.01622651,  0.04328057, -0.00262015, -0.00221247,\n",
      "        0.01745601])\n",
      "Cost function after refinement: 1.1201428917916492e-08\n",
      "GonioParam(dist=0.8058814330950826, poni1=0.016226509518190272, poni2=0.04328056976869554, rot1=-0.002620154555017879, rot2_offset=-0.0022124664981937373, rot2_scale=0.017456012555286927)\n",
      "maxdelta on: poni1 (1) 0.01627189950015672 --> 0.016226509518190272\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([ 0.80588143,  0.01622651,  0.04328057, -0.00262015, -0.00221247,\n",
       "        0.01745601])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Final pass of refinement with all constrains removed, very fine refinement\n",
    "\n",
    "gonioref.bounds = None\n",
    "gonioref.refine2(\"slsqp\", eps=1e-13, maxiter=10000, ftol=1e-12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MultiGeometry integrator with 121 geometries on (4, 66) radial range (2th_deg) and (-180, 180) azimuthal range (deg)\n"
     ]
    }
   ],
   "source": [
    "#Create a MultiGeometry integrator from the refined geometry:\n",
    "\n",
    "angles = []\n",
    "images = []\n",
    "for sg in gonioref.single_geometries.values():\n",
    "    angles.append(sg.get_position())\n",
    "    images.append(sg.image)\n",
    "    \n",
    "multigeo = gonioref.get_mg(angles)\n",
    "multigeo.radial_range=(4, 66)\n",
    "print(multigeo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of bins: 5070\n"
     ]
    }
   ],
   "source": [
    "# Calculate the optimal number of point for integration\n",
    "over = 1\n",
    "npt = int(over * numpy.deg2rad(max(multigeo.radial_range) - min(multigeo.radial_range)) / \n",
    "          numpy.arctan2(pilatus.pixel1, gonioref.nt_param(*gonioref.param).dist))\n",
    "print(\"Number of bins: %s\"%npt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Integrate the whole set of images in a single run:\n",
    "\n",
    "res = multigeo.integrate1d(images, npt)\n",
    "jupyter.plot1d(res)\n",
    "pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save the goniometer configuration with 1 angle\n",
    "\n",
    "gonioref.save(\"ROBL_v1.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.1201428917916492e-08 1.1201428917916492e-08\n",
      "Cost function before refinement: 1.1201428917916492e-08\n",
      "[ 0.80588143  0.01622651  0.04328057 -0.00262015  0.         -0.00221247\n",
      "  0.01745601]\n",
      "     fun: 4.784268978670502e-09\n",
      "     jac: array([ 4.83580818e-08, -1.22536698e-07, -7.04560715e-09,  6.03399075e-09,\n",
      "        1.99023001e-08, -1.01915002e-07, -4.04191697e-06])\n",
      " message: 'Optimization terminated successfully'\n",
      "    nfev: 108\n",
      "     nit: 13\n",
      "    njev: 13\n",
      "  status: 0\n",
      " success: True\n",
      "       x: array([ 8.05856713e-01,  1.62114876e-02,  4.17434732e-02, -1.37737776e-03,\n",
      "       -1.29828173e-04, -2.22389622e-03,  1.74564328e-02])\n",
      "Cost function after refinement: 4.784268978670502e-09\n",
      "GonioParam(dist=0.8058567125358187, poni1=0.01621148755332537, poni2=0.04174347321241412, rot1=-0.001377377760925881, rot1_scale=-0.00012982817291904377, rot2_offset=-0.002223896221623935, rot2_scale=0.017456432797639122)\n",
      "maxdelta on: poni2 (2) 0.04328056976869554 --> 0.04174347321241412\n"
     ]
    }
   ],
   "source": [
    "#Can the refinement be improved by freeing another degree of freedom ? what about rot1 ?\n",
    "\n",
    "goniotrans2 = GeometryTransformation(param_names = [\"dist\", \"poni1\", \"poni2\", \n",
    "                                                    \"rot1\", \"rot1_scale\",\n",
    "                                                    \"rot2_offset\", \"rot2_scale\"],\n",
    "                                     dist_expr=\"dist\", \n",
    "                                     poni1_expr=\"poni1\",\n",
    "                                     poni2_expr=\"poni2\", \n",
    "                                     rot1_expr=\"rot1_scale * pos + rot1\", \n",
    "                                     rot2_expr=\"rot2_scale * pos + rot2_offset\", \n",
    "                                     rot3_expr=\"0.0\")\n",
    "\n",
    "param2 = (gonioref.nt_param(*gonioref.param))._asdict()\n",
    "param2[\"rot1_scale\"] = 0\n",
    "\n",
    "gonioref2 = GoniometerRefinement(param2, \n",
    "                                 pos_function = get_angle,\n",
    "                                 trans_function=goniotrans2,\n",
    "                                 detector=pilatus,\n",
    "                                 wavelength=wavelength)\n",
    "gonioref2.single_geometries = gonioref.single_geometries.copy()\n",
    "\n",
    "print(gonioref2.chi2(), gonioref.chi2())\n",
    "gonioref2.refine2()\n",
    "gonioref2.save(\"ROBL_v2.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "First & last rings\n"
     ]
    },
    {
     "data": {
      "image/png": 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dqwLg+47O3NbmneZUtFcFzXkiKKWm8LdjCgF1nddOobvQOfdzVrm39cxG537u7+/X8HB8vzHeGaGAULB1HS4o3au9bYselnugbnPeY32fPTwHfa4VbeIZjsj4XNd90rvLLdYDj2CwbfX3n98ewoic866HZdVzNXByKickrJOfL9MWawmlOMgJqaEmjlbtR9ZmhsFUDMnY2zkVe84x0ALP3QaEkrkWM7xzpc85n3S47rOk7TRC1yU8V/bn3eU00kE69pJ1zRWd22atGsKO9V1hSJtswvDGC5ekbZ0kc+Cc11gnf0Nr7HFB5hltH6UhjxgLc+VVjDtHAfk8ihEjUZIelrue14s+uZ50psqLl+nkm+2YVOo7ntdLZ7T4GUIHOC6s/XG5qyjp/e2qZdpCb2EghGGJIYVsPLL2ajSAKsJ3Ug3ZHeeeXOc15ESp5x18WtFJnKicStCAy6BUeeQ4krY9a56OFiat735aL/qy8VEYFs6In13usdnOpEv1FHIq4Vlu+9RBhxzMCCNdchPuoAlASxzqceQQYBCLW5hYhCAAeFUwB0zGPJZp1+e3h1Agbcwx56wS4R6UMYx432Yt86ZFWzDWpw9Peq4H+u56O4XmdNO9Ih7vLrfwEp7Xi5Zp07rPSkcJBQdx9XM6ifS6rLEe9hIBEGdUle/dFLl7UOybMztvOowwYT7+cP7bPmmpAiDrFAqfXG5api0UMuM4sh4u94AcefdkAv2+zR2EXUpSrgJ6L+dnEYx4bks+wmBx4wS6Q3i5IoEeUcZ8x3cZ2sT7PL3pU0GhREG6oINtn2Jt/CyEZ907vDbmCy1BRwitqdIt3pN72VNuSt291G2f9HC5x2f3I6scuVMMy7yFEnq+X/rQQqUFRwE9vwHheJk23ff5BUztiAbDQ5WSdJk3Pa+NNqVTKf3g06M+ud5eoG7vLjdtx9SQi/VEC5/WS+zL+9u1C+MQ+mI9hHFO43fXlI4Qtpw/3jrGakolHJLX9iXX76TBQ41wrsk5fo7SdJn47nrTfmR9cn3W58+PsY6T7+9h3G571kVSMSOYvYUnr/OqL24PeljuVYHlCHccRvPwACjndWo06+HqoyTNucl2h/dxhOaKDJ3EcipV5EhA+eY8Pl7upyKvdHuZttABczp0ySetEgJP+dAXtwcthlJi7F7nVVM69B2P7/X+dj3pezr5EmOSdV2XNdDaoxoi6z6fz6gOqNPqfZ+70BYyBkPfQ82OfsIHc9pjj0FBGMzD9+R5XZSKheNKMw7YCw9BITdv26yH5dyH67WhO0/bEuGuJf85gFgQgpCal05uw1rzDmB4SYFeBJxblT0KGMaCOc4wxtEZCtkUikrqIFRJnbWN8N2O6VTUw3zdaucQ1m2OxJen24PeXW4n1Gtxr72cwuWxGlMYFq44IISlEn4YOBW23Y4p0BJgdUkR2mEcJZ2ox15jhFVQQtQQFd+/b3MYKVjhCDT2w2OwzJcdJqQiKbw9lA0wOO+77zVMdOTwbM8YrELZvr9fA1J3Q+S2LqdSnvbwANgjwkUPFfrMqYQ3EvHF+m/mk1PRerSwESgRioQzIfcA+kJookSWGoZ4AZHXd3FWGAZz2cM4dIPlMgghoE4E7M2MYZ495UPHPnUG+l7XA888r4u+8fgUhsuBV1gaVAx9e04I544nzD4heHOFZj1kspes40iayhEe1/1oIR72TWq5JR5+cTrm33iMDBT2dkzV0Fj02cNz/B6am/Kh/+j9p3pc7qHQ4P3H5a6nioiBBPCsvX4X2nJBvh9ZJfXIRIQKa+6EG9L83hHOiI3v6oz5MVQ0TQ3BkRRyks++u970VPNDlvqcpe6xoyuEuzyvQHs/98u86f3t2pyN6qEjox8qz+bUQn25HCFDwxGrjtvTetFS+Zkxp/OzuRr0yB837C/zpnWfdJjh7nvPmTxURV+UIiwSNFTXzBkgHzmXbz0/hhEwoo33bQ5HAiOLcA20lypCtBiapWpMgLCq/tyRYknBpxgX6z4FquXnD70wd85zO6YIjygfESLyc8FwYB6fXJ+DjuA9ZB1O2F6ytJ/78Pntqu94fIp8kT8nQiFHScHQwDkIUIeqgffCOq7M+LQu+uz6fBL0kfW8Lp0lj1GRUtFkMJN7PMTDXHECtXmiESEOLGwEoSv1ZdqlKgBQnsD7xLNPwt9fwPmujIBys30GIn9aL6Foz3Wd8cs57eG5bfsUVmkpSc91jp4MFvkZ0yZVL4qxqsHHLsxc4KXqfd+3OUIG4QVXwc+anRgxhvYj69NK5J6U5fDs43Tv3u9edilJF216Xi/K6RZrBUad865vPr/Tp9fnEyk6SIi0xL7hvDmH27bovp35JuugXB0ZYU45lfCGEWDsH8/l2cwz0KlqGHHGy7RHGA4akBQGGMoY6NoHe42xmyoNznnX+/tVy7RHnPz0XnrEhzVyFsnoSVII1ZyKpvodFGYo+Kqwl2nXRVvE2ZVaIqmH0lDAnqvDHvNz9/6WGhN3ZXEakfcOxZzzXsOJqcb3pU+vz/Hu+z7rs4en2PNLTTi+rUvkMsHDJxK5xZlcppaf5EgV+0jYihwRRygutk8YohgAfC6nE5rGC3a0ykOvGGJnGHGJeXz+/KhDKWiX/DUPk6AwQU89MfvpfumSMZ9q/s487YES7OrDzfCCowB52rWbgpsHbxfHDyUe4TNJeVnPMIC9A8OZvXBngn9LCvovrDM1pcvZjM4Y4U4S6j28BwqEYYDsOIze4FMcFMIxIJH7ceZSgLJ6vtRe0RnkkudyeCjVje6jvmMeUgcIh855D1konVVg0B2IqSOsnrv2qRkf7+p5w//uLL02PgrDImKfZsXvR9Zl2bRtrwhpqVNAWSW81XnalaVgBpQyn59qycxare5IgpF6AVafDbyGgQHROxwonYTjMCUDuCwU2HAgpSR9frvqs4dnPV7uen+7dslF7M8jGe0gA6lEwlEpSQ+Xe2cU+N7ybveopJqBfDTFJylgcoSp/5tESpJECbcwcm4ejdTyUxBgLjBhGA+NXPKhbz0/nuutChSFRmyQqh3me51Xfev2eCYsmZLfKy3c1qXF5KvHxx47GsNZIAyP0gSqMzTKH6MIep3yoZRP2kLxP17unTeOYCRp0xGEMSb9tF7O6oS1rRcBEQqgJoGmVPQwbyG4Hq/PKkqdknBEy0MSt+0Mw5Xq8TE3qiNcaUEzCCWSefm586mjG1M+wvgkBMgesndxbvV5KA+E3fN6CbpgL8YQVPG5ppYHsu6zHpb7Ce0ua0tWzkckgqNs9pJ1TWuXo8PfJIuyJ1s6qwKWvGs3BJR1OVTteTfkKvg+EVpFmbiSuuY1/r/bfJARhNV4PgbZWv+NwwYfb/sURtnz/RKowlp/jvGxH1nb1mgXA2yy96AAQwYMHraHDxxtGNEY9hljjxAFOQDwYDZ5wd8gxNPl3uZ9THpe27NBle77rMfLPRw4HFZ/3n2b9dnDc2dUgoigdJFLVBtel7XSj6G3Fakhx8tRCUfjjnKGmDynYq0oH0meHnpkH0pqCa370SfQEupHXvl5eE4MqITTOCF3cozWbdFC1ICcvVd0jY+Pw7BQn59AQpV0wlcIHA52hOjd0h1hW0kqZgk+75cXsPy6T1GhgAem+jeQvOdQ8EwSnJIxuupnMVoQKAhcsspTOZN0To/9XOtaEQSUDNajdBIAsCw5InjHngxHUiGxM/e+GBAzCnvKh2SG21KNIYd7PfwjqeZ/NKgcQcF8l2nXVNekfOjThyf91O/+9/T+Bz/TH/7+nxRGiecz7NsciXu+X4RrvnV71GfXpyrMzz0H6YowhnlyzlTrNuvhcleqsUlHijwkIr3MGYmzTUVP90sYcgg+qaEnz1Xw4JHyLH/2WN48paMp/frO69wUIMIZer9XupynPQzXz28PkfRJgtgn12fdj5o3Ur1vvDGQBUIC+5H1/nbVoaRPr88n6ofXbuEyh56XfEjTy/K/0/Cu+6aWLA0qwlpGhM6VHuf3/n5VWVMYtCME/lRjxcgGeK2UFJ4xWf6jofh8v2ipBlnROZdL2jq5Au2DgJK7Qsz8s4enOFsSyMMIqOe0G2wOnbiST6kvjwy5ZEbKiCTlep6SwvvmnN/XtZ5IwB4ywCF+nKzFqh2W6UxkR/EcdQ/JKeEc3eHy4TRylBS5Ih5iJaco9qek8KJdbvE8pw88bJylbZ+Ul7VDsgm/kJzo/COdiB+84kgH/OjJl1M+OtrnWYfpi6f1Evl5GIQgGlKTj+sxaSoWppYi4ZY95p0gb46GMpDXxfYhEkfrXC9zCzHGHtf5b8eksqZIcCW3aU57ICgup27rEig9pbNfZ3wUhoV0IgyuUKJ0rBLh7Zh0lO1c3P0SVqbDp66EpFZ/7QybUomSxqwSSVmHMQToyT5Y44/LPWBuPHiSDCV1sBzxSDd2JIUHjSDmM7w7ckv2uSqDWZ9eP9d9n8OoQOm8v1/DAkUxkdSJIpVaox+UwZTPBLHn9Uy0u6iVza41Ns/cpL7vAgp49LDZW7fwqQfPqejpftXv/7d/ZgsH1Gqc9wbzOkpyho8WXS+3IHbPiObvyOOowu5SvXiUFwMkZitTwOAwXE4l6IyYs9MiNIT3hNG7lWqYUN1Tww981+OggYqYMHXPc/RkXMmyhxhPVC+4AUrJ4mcPZ2mtJ+xhOKFct33SXgUQAu22Lbrvkx7nNYSr9zvAeDxKUkHZVsMjFK0lobn3zLm6F87c3HNDWOJhSwpEDCNx3afIgbkuqx7zPRwLvrvurUKMOXx6PfMt8MIcnSpKHW8RkoBn1m0OYyub08Cz73X+XV5UPjSls8pm31vfFhAGkFPeW0rLbfHeDNC1K1MPK7pBdjiasp9Jtxg7r5XJYiwRJr3MmxaToQ2ePw3Xx+UeztVi9OWhOleQzJPfQyvIbPYr0JzSQk5h6Ax8yJp51ulFqzNUogSe+a2LSqXhpfKKo8Hv79cwRDCOp3xEmSk8Cu1g1EuKcD3ns9ak+w7puNx1LX2YBqMNmQO64A6f57C5IYHs4h0exuwMoaOF/1kr8932qSsYKCWFU/P+fm3hMnNKIpSTe7342vgoDAvviOYC4bYt+s7HL4IB2HCp1TDf95ag5wdByARLn+Q0V1wQh3sPUrMKUUAwK+Wg7sE7AZ8VDfsJv26z1u1sYIWxMHotKPqnahTAfPfqufOd9/dr84TUIMGnmsDmlvdzhdhZ232bQ5nwbBhymbZI8nGvnbJbxovY4d43m4GZ2V9gaZLzVM9hsvVzDte8dkJ8t1wKhPgy7frW80M0EVu3WarMm3XGoR+vzxEfdciZEJF7TLFOs/7dG4J2bjVRKd4FBFm70035COTGUaAx3DOpeR1e4eEGzdN6iXwOUIgpt9Jm91qI3075iLJIPD0qG6jwua8t6ZCEPUfQeM+UDr1b9k45urHHwBhhP+AP5yNo0cMC8K//O8qh86HFenHAd6yV5xF6xHvysEmqCuH9/RrJ38S+HfkrJUWyNGhX5EIl70/QlM887SfSVfcGI4Oy7Yc6d+cZ+BuDYqy4uO1L0IknWq9VabhydLTJPfoIBR1ndRTKGCOF/QclIC+FPcWYeH+/6pPr7URYyxQhWfZ/zrsea+5KlqJ5GO90A5XzGOkM3kAGuZwHQeEcrvOqMlW6MbQZAwWDmnWcSapTx+fMnZAE9P/57UHrMenTuj/kRaFYPTT6ybX1c7nXuWNssyb+5uTJp7nVXiuez+Hh4KWGO0EMQUtOGXX2GUJ540RHXxbjTw8fwjORo1Vawig8QSiQvkFSM97JwQse4HwqDT+tlwAAxjDWOD4Kw0JSeFMI3HfXWzD/Mu16zGfG9mMtl5IUsfPLtAeKgSC7rcuZyS91sXG3xH2DSD5EsDqkPiIgrnxALiLbvXrgzbJv1qTKmaeRrcIAj4CkS+LCCBMXplQ+SApBi/B3puN9CJr9yF0sn+EekXsIzB1vgs+C5ji86X0+JIWhJzUlxJ5D8AiG48hd5zrCDZxvKJhUdJ2rUNxLVGgcJUXSH0bFlFufiGyCy6t3YCAEHELdKyvwfh31IkzmiaRBCxgKGGkmdKAdSWHsPiyrnmpp5nVe9bjcdZ1Pj2czJYKwdI9YavF7lNC6T5EA5ygAa/uhp3dRcYJwz0YrlO1GYvHU+leMybIeI8fYciXCYD88NOCep9MVQpXnoLBccNIhEB4kh8bzh6Z8BOJBc63rvOrz20PQXoTZaiIm+VnQG3P08El0J5zOHJ3FPFkX9Oyn00MkpE5nAuGu2i1RNfRlioFzd0+efb/MW8ffKGQ80V05ULtS5QNra+G089+z2plEPlMtRX9eF63HpEdCJmpo5F55Dj54XO4B6UPn95qnARocpfm5QfjuZQcadpyJluPzYp/V+mtA+3M623Gzd+SIuHwr9Qw+vz1oyoe+8/GLqGK65Na9k7w7lD20Ak9BByjiKGm1BHlkIX1DptRC/OSIXaf1/E5FANgP6ByHFT6BN+Dz0Xhin0o9m2XqHcNtn6L5IuE/b3TFGRKWXqZW3jzlI0qz0QtfZ3wUhkVS33SFOFaUGZVT4NIsBwVARQNeSFKRltb4yWPo7vExjr3vdufZrqOnlnJL2IEQQukmz5LvkxWl1rRmyofmGk7h55Jl+qvVo0cs2Txbh6av86r7Pkfp15x3TVXQXpdVl+Ue8Lb00jBgYJB4NQfjBYJTWiwdovO4pocR3LggIx50JGLy9n9COS5w8HKu86qnclr3UhNUkVuSWmgDzxPGxOjiPL26xiFMnwPD49v8v/OSBybz2PxSlUhJrYHViTg1dOPc0xJrui5rKCe8FGKgyi0PIyDdVLo5uWJn3Sjnd5dblLMiJNZ9inp3X697LCOKKCnK+twYgIbGvWM+jmDkquylFspyYx84OaWifW+5GB4ier5fIscEo+BiCKSkgPXdQHLIfFTSkQRqdOd9J8I4rn07ItO/9P1ufA5SX8J+19wZPx468O9LLZHTw72OHnqZYkmNDgiVkUiMPCR2j9HkTtVckVZkKmGPKLVMJbzdcAJ0OoRjxcYltyTWMRfDFaMbrNAp8hzaGZUouSPsuCMyJ2LcPGpkG/tGzoA7h3t1bkpJelju+pTmWHZ2R0n64nbVPB1dmC7nQ9eplaQu0x75S7JneKgaY6+ooXvu3LHuvWSlo6HE0C9740nmI925vAOJCUS6zgG+u8xbOGWqRkSglUcOQ2vMp3Hj77XxUdxuWnR2PePwN7zvCj/m1JqBYI17jJdDeX+/dpnbMOzjpaEcHFJOJWKSMY/S8is8xo5CvMzb6QFVSxzB5qWDMOtrSV+0rnZigAHOUrFLvBNPjHjiw7Ke1vEr75hzK//Cm+dugIgFVs+M2KQToocEMJ78s+zttk+Rg8H+ODzHvqI0busSyY4wH4I+jMOjxacDyTAlf13WuBsm9vFotfdTVbivGTT3fe7ivwgIPue5IXwHhe7eo3sA7AlGD88lLMG57JUp/Zz9XYTVHI3wZ7FfT+sl9pfPkHAHfIrHx7mR3FxK0g89vWvGUA2b8ZyHZVWShblyuwdHai2ZPbwBvYZxWOkKDxaauO+z7jXXwYUhXf7iwq/UypnZ81yNaIS1I3XA8NAwdwlJ1kbd+NjDMquFDJ3/d5MDI1Ly+e0hzhQaAaUcnRDo240KNz4d0diPHAYyYSv4fd3avuWB1x0ddCMdBJDzLyWdbeur0vdQEDF0j92DljpvLFMzNDibh9qyGvqFHl2mePgjEu3rmjyh2tfEvjlK4AbI4TQ08BLve7jcO5oFoXIjghARThBoDygEvIoMYq/fXe7KOg0z0AYcFWTYure25+Rs+HuznZ+vD3oIw4ycqWNqHZZNn4E88DPkg9P5PtA2POvhD6/kgmYxIk6DLQc65OkEzi8fGh8FYiGpWxzJcMfUhCzhjIDcK8yJEYJy4eA8u/dmVjbEyEbFz4yot2OK/ANGRxAQqxSesjfIAk7CS+TnHAohl5SP8Mj2I0cIxT03YOulohQIEfcu3WtDodEy9v39GkabV4Hsak153NAZ90+qxtjRvPutvsPvcFkGJjlKivPxUI4neTE89wWG9nWzH2ePgjmajZGH4slSGICS4iI7xumxtQoS9jDCOuXM8WBfJGk+dhU+ax6UC7eIL5uB5owHfbkg9wqbrpVzadDvVD0gh0QjmbMKsCkfIXzcyEYhX46teSCVTnkPtfrsgbfG98oAjIkmlGq48Mhx7ghphJ8n3nkMGmHveTqnwmq9Hngeaz4bnB2acoowIuNiqAROyalc28VbKDZPrmafHX0pw1r3o6+aCbRy2rSVmi+wz90FVW5UuDGKcc0esm4GCpd3uIeIgwAfTLHnW5cAChqBMQEdhczLvWHD3DAKUareUZfKttPTPS/8O893O0so59MBJKkdNM3nXqqxmI0+UipR6uoy3h0O9ozvQEt8zn8GDTP/tTpBKHfPORvRtOBDow0MkjPk3C7CO0qvVHukoIXT3fCA71fTA2tFKHEYXD+VQqM5Q4XtLJdp1wHClVpTLfjBc3Q4b7/Ik/wKvz8JpAZZJbVkeW+QWErSPI/dpF+Oj8awgPm9IQsH4rF36vuxwD3m5oozlRZ7diL04b3oixE4Fi4Kwz3L8KpSK42VpNvRbpkDNYg7GjS0mp5e1shDzFGfn0q0nKYZDAlvhF4cVYGBJUVbZgTMaOE7VMbgWQg4GNJj3KzlvCCnJyzmw789Exnls+5TtA+WWjfQ5+oZHEfWu+utMy6k2rL5ftH7co39ieub69/vrcGa1LL/EVCUzKmeGfHZJR+dNxdth4/67iq8EbYIPd9P6Mazuad8NqQCZn2NEcMbNbSGz4EsOBoEDeLtkkMS52qVQGFUb3M00QI1IwclGmilHmqf8hEl4Fxg5x4uKxlbui/GZ85rCHanV2iJ74FUMXdo/TKdhkOU0lal8ny/hKcP1Hy4t1mTflfbU1doOR96qBe6McdLFfQebj1Ky605ypkMd1f7fUnlpSI15cf/XwszsteudJAB4QhUWP3sqqi4T4XB5wnN4tSwryBf59xy7CPzQblweZajIu60wHfeQIn8N97J/rpxzXk4/fP8yI+yc3X+4vtjzoA7Xx6SZWCMew4RCrxUuUznSfaS23aR8d3tpUdroe57NFWHNlCeGko6Smvf7UhlOXLosamWqyPrPKk7dFVqeVWe9Bk5O4Oj0xnytvajpM6ojHOoTRW59BMHhbPwxPeo3DE6/7LxlYZFSuk3SPolkv5kKeXn1J/9Fkk/s37kOyX9YCnl56WUfpqkf0fS76+/+1dLKb/qq94BEWKlUVI6QjXLvAVjoJBom+3JbBx6UumE4ijsUAJSUw585jXPwq1rwhVSa4I1a7hquMbYqXumm+J+5CgF4l2sczNDKBVr0VxSSyCbmwCHEb1LpxNbCEeY0bwGcjfYI+bCmlfr0RDW9NGSXkPRmFHiHjEKnMoHCBREaDHDYdvPfheRJ2H7z55IrQX5rSIxjg45ZOjJfB4D3ra58xCkVgK4HzlKCjlrh9lTKlFpwDnzWU/Uy1XIuAL18AjdG1kfz2dOeKigL9AZChPvAhqIhONjUq70ghf+yfXWDNo6n+u8dom1rhwYQOA+v0BVEEA2h5Ra86acWlt09qdTBOxval41qAYlb9ydwtpcmfrFSYxW6bRHX4p1byWXHobw878fZ2fLT67PkcPloZBH7zhoghWhDL3CD+w1mfdxod8rn2N8SEi7IEcB0LdGaqgfa/K9fM0pwnjDwy0ldRfexV7m03Cb6t456nff5kjydGOCs3U5y+8cNdmPHEbrZOtLr/x7RBb8M+xz6I6phYi9iop9Zt2+Zoyl+z5Hh1IPEczV8H5/v+qzh6duv0f+lSoNbs0JuG+zHgxRO0qK3ItAJtLZjJHfT/lMlh0NdN4XcqLyLKjGlM8W5qWc/UM8dOR9ZEo1ZAohI50yl1YKyBinH9B89hZe/rLxdRCL3yjpH5L0j/GDUsrfzL9TSr9G0g/Z5/9QKeXnfY3nxnBmO6Qog2rXG8/6pDaRQkC7svc4pMOit33pLGCpESQxJ6l5D9mYIKBENY/SrXDePRonqgKdRjMQtLfRBpFwBnLLm/nvlKtOwLWtNAgr18tHz7hYU0p4zbQ0JusaQnSPgPVITYlw7TJrSyrSZOeFIho8DPYXxci5SCehe/mUzHvyezFKSSHUEdCOMBEG8fyJcrQqG9AL9gEDhTPxRl4jzOwKBKXodMZNg1JrdkP1QzlyKFVHo2iyhlJnv3gndwOAwPh78ezutY3703rRZ9enLgFvyq2LJIYYtA+SAb1c5i08GBIA2ZvRM+RirHWflKd2H4vPkXNwBfMX/Kg/rW985zf1p/7DH60f+NY3ImbLPSceCnN65F0o5P3IXbLZSKduOEJ3Md9E+++9o7/IeK/nD9+TDA2S5omb7omnVCLMcuYhNAPbe9rAR+wjNOKKyQ0uQmkelkG+rFUWeukpt+EGXF5OFC566QzGC3kh5GHchjAbIYTn9RKXs0WCtJrTtky34FmQQT9H1jDyJNUOrpii62WVA0c1cB05ZrgziCHv9MCeYeDA6zxfau3ouTSPvCrOGKXqyfefPTzF/nrlIGt2B8V7Q9D9k+9AT44KhfySusRuDFsPo40ohBtxoAwM9sJRfPaKHEHPP6Ors4e0cT5Ovsj67OH5hcH2ofGVhkUp5bdXJOLFSCklSf8NSf/lr3rOV78ndYoJ5V5KisuE1n3SNLfWplh7bT7N00ypdEwxEh8xbwjYvTU+x2F6mGHK7VKcTnGUpK0y2TL3dceX+byHA4EMhI0wu85rXKKG5YlAuuSaOFoVKcmVzgx4iL5GFIh7tAih/Tjvjxg9gYj/vQKJngSVXuyn1GLIrLfbt6pUmYczB4rP69slRW39U43Behc93udJfH6ue8nh0bsS3Y5JuzOo7QXzgQbcW4Aux3AaCapOu/GZmlTpisFRjqf7pUOGoMH9yJrtLFBYKdUKDkNoEIpz3qMbHs2h3HDRkaOTqoxeMTb5nJ+roz05HdGsjc/Cl1J/L4Qb6D/0rc/0xft3kfNwlKRZfRdFhtMGiFQk/e2tE6d7eZ4oxzNobc0+e+4KZ4EhRYiE5yDIafU+Cm7WASrlZeWuJHxvnF5ib+u/3bDi54F4pFamGz+r++FIWUkNbeJcz0TEFkoBIXL51sHzpYWbQWwOKSpsfERvCrXW154MSdUaTpTL8evUrinAIOLODK7kZs8wBPYjdyWqUWpveVvsRdC7msOXVFRKQwIcDfXcGD8rnkXoFN7A8PL38G7OZDQa6E9C6NvlbPBcag3HVjsvRy8dfWBujnQwn9tg5PE3CBZGJbQRdA1aXcNsGNasaUqHprl1/v0qtEL6kedY/Bck/YlSyh+0n/30lNK/Iembkv6uUsq/8lUPSWrJXw7lQZQ0snH0AQWBx+Jx3tegNGKUbuFRpuTWl8O2/hyIxQ/a48BA3r4G3gUE6ZZuKWe9N10VEVgIu5vB/24d+7yAzaiZlppVTyLfureWzrwXT86Hl66NxtlI5KNn4F4YxgXW7wizMiB49p9mX8yR/h28m32da6IY95XctkWfPTw1RGLqE26ldo8Lewlqwx7wd8DD1qBqr4ahn797TTB2eC6phaJ4lyu7aHxUTu92bPQUis8UsiMtpwd+JiaSgMtwRciZXOZNn98e9Nn16dwLTd1nMZI5981yErxDrKROQOHlK/fxdMZ2TB2qU3Qau/CcUnlhnDtSCGzsxu1rRq23mQ7eMmPVnQvV/R6NW/gTYZpU9P7+0N1EjHHHs7zXDPyGwFfqUQl6tcBLfm1ArNVo1gU/tOZGxm4/h6aQNzQbnNKh27HEfTWOjoFUICPc24X32T/3jpkb9Hldzn4MfB+jwcO5EXqpRgjPh+7D+JMixu/ziPMuvXfuNO7hAEf6yFFb10UX67cR/FoNyuf1IqnPF4rchmPSdLS8JxAuDA2nv9GL96aNhM4wosntOkrN2zlaCGVEurbSo4Oe/5NtvY5cQTvIe4xFQiG0Z6ByC2dF9RxwzHgOezPlI3otfdn4kRoWv0zSb7b//zFJP6WU8qdTSj9f0j+bUvrZpZRvjl9MKX2PpO+RpB9/eWyhhpKitz95CTQWQYFLiiTAgLpLq/Bw4XedVxWlUC4wGIJ6HC8s5zrY1GRMeiYxmieVj47hOXxnojAO8qFZL2uR4x6HkjWVZuVGfbStGaXmBIaBwlpowuLrQHnyLKkpPI+Ju5UtvbxTw+FankUvA4wQZwjQi1MpHbpvlxBCjgBILekTryUPcwIa3q1Elz1xRcE8OKdc50bM2xmdvRmNLPY46MPeJakTopzjb/+jP0n/zg/N+lt+1h8OFIrh0K+HXxxV8MqjULiVljws4F75lvqrkTmvx+Ueip21u0HhhhB7n1PN9C8N0cmpdYZ149YNs9GT8lDVKAg7YyD1CNlrI/hKzQjDC0N53rZFS83NcNpjj9eay0MfmOiVYzJDUjTP8rAPCnfKZ0K190RxXoozroNuuezRi8+YHBoNNC/nhtbgI9Y9VTm0lQahK7fQIgqR5+EU8N5A/dQaCd6r4nze2v0TDGTKtk+1S/B6hhpyS3B3VJVQMGfFOjvHwRwer0JIas3v1qPvPIphK728doDf7yWFPOX50CzGAfdR8fM9taTJh+V+ylvbu1JS3NPEmbvBBY1wm3BK5VWn1gdnCYLkybyO9IaRaPJpdKT5N7oF+vC9Bc0lVHiUpG3IpyGkHHRdESZ6LX3Z+GEbFimlWdLfIOnnt8WUm6Rb/fe/nlL6Q5J+hqTvHb9fSvl1kn6dJP0ln35XgXncOsJzPAVsO0CPDTp0uu5TJJYJJquCMRi05Ej4dKKQ+ngnSY4uAD0vQlKnEE4vobcaMUQ8S5mwBcIRIfxcq11Q8F7p8q7el3Fbl0hGu5sHQEMhRk4lBAKK5thb9rsTdVj3JoAdZkSA8DtnAJQy/84mzH1ffI9hqv24RMnqZd6UVKLFLYqTNZ6C/WgGp3lI3gwLI+797fqC2WDInEoYrEqtzwioRClJiH7gZvmZ2/p7eu4TOv/S7/wh/eR3F/NY+hwNb+DGnpCbQzVBPHdQ0pKiGQ9rY4/prDfl1lBtnOfpxZzlm7En9gwPXyGIpTMOvDgd732ysCsN9iH2Lb/eDMiN0lF5y2jJDX5JutTcIfgFOsypRBydd8S9B+Z4THPjXQwmv3HWvWUEuxu38AE0sh/1ssLSx8Id9fOzgq9GyLozglML46CkMb44I6ldQsa/URx0d3UjJ8IJRsM8M2lIRDxax94OQTva+Y0o7FFa63vW6vD+lI7wkjkPN8h9f/CJc+o7dY5wvKO4JIc7WsIzQJTHc+D3yEZkRTOKVh2lhQDZgy4ceLQwGj/3HCjnI94JYugDeuH3fM/Pa9RXTmvsuyOsfhYMd3RTKqE3wyEsKfKcRrTFDd0PjR8JYvFXSfp9pZTvb5uSfqykHyil7Cmlv0jSd0v6d7/ySZXArst6ZiPnlzG3OFCzuJ3R3fuTFETpm5/SmbMQm4kRYUKOOwfYRJ7hKAGfk9QpNohxmXbd75ezMZfUNUrib5gKgYfx4AILIXu2kd11L5bYyZwG6D8UO0qyesfuYZfS32yKokbow6h+Bm5QBRw8tfsPvJ06e8YewtyjcKVsljp4mAxPnfWH0DimLsOfVrTv79dIXMz1xsb9yJ1QRbg7I54Cr+1ZB72qeZcwFwaPd0vs9tz26Md9+k392NJCBPuRw6N05AljAqEk9UmsqSrKbZ+6CgX+dkUhtfweyjH5HZnmKCou6jpK0rKsDcEZeA46D0/KwiY+HO1woXZOoCFNNL1j/T539ybdGKZDq8wI4jZSL9FNlY+k5nA4KhLhtJoMytl0ZeomnIvx4X6ckDuK1D83oiyj4YkwdsQs9jc1Lz320s4gbghWLz/YL0ldLkAY2FOruOIsnK47I6u+C4Xv5+9hLhw2SXq8tHwf77XC/Dx86bxBtZGvAcfQjapAY804iz2sBgD7ST8V1pPVJ0B7wjahMBLTkYV0XR5DGud+ti7AnJ3nLHCfSaBZdjZhSKtH93wEAqPWMsENoMOSLH1/deRwTNlTnFnnK6904ufso/8diZv1PWHMWWdZzmQZDKJxfJ1y098s6RdK+jEppe+X9PeUUn69pF+qPgwiSX+lpL8vpbTV+f2qUsoPfNU7IFYUIgMGdQJxgYEQ87iaGx94Og6rT0aAAV8dPezvEKPUmmCRUCRZF73SvPIW9zq6GvasU5DntEbVRr/HpTUvqYbGUZKuedc+NWNlHKP35H0UnIDZF4QYysez6c+1NA8WC1/GIE6YkR1d+ux1Ps9+YgS5V8XvCwiH7aF3ZPRqDYwznknZ237krvXyUcxbTn1YCEEQhoAUiY1Y6S5YXchEI7Ej9+s9+pCGC0yUTo/W9Lc2BkpSDUBO2Wkfoy2nI65BH9GC8JRzX17rnoULTt45mxJljlxW5SE8fkd2uz8rPB0TOAhvpxmVpJLsPNSMXNC3oJ3Se/6y/XaDNaeGVnLREvNyD5h3rkeOO4ZeQ0JCcVWDxcM+XnrphtOUj46nUYqjh0p4qxgNSQ0J8jNfpj1i4MyLwb6s9g5CULeuRPzQWlpCoCt5Nz6klpjpqBNhDU+QzqkEktjkXcsTwxDa1eQo9FGO3gBz9NbzV9wJgp48N2msmgl0ou4TVVSVMVp4KN7b9ox38Hv39i/zFgmNrIFqmuuyxoWJHpJI6WxDz147asJng/emVnnSyWHTMew3uxbGaOrDWSNiLakzZs7z3rSl832eKLoOhgt7jQNFRU8Yrvr2VIX8sg/8/Fe88rPfKum3ftUzX3xPrQyTQw5PtxL3dkyaSw8pLvkIZSi1Ot2R0aUmCLycSaWVeJ3zt9vqUu+RSQoh7wIDgsCyP0rLuPe4Xy5Ha9IkdYJcUpf5Hh0QS7tC3kstkwlZ9sJRgWNvd3a4d+KoCvAvg2f4fR7Fnh/vsr1woYLQcSQI5tqrRx7PUg9BuhIeG+7c9lYGN+VDDzVs4ln1MJ8/1zOoA50whRx7VZrnU2w9LoA9aYt1JVcaRjcYHjzHE63OMEszYL33wAhbRuxatRRwah00fa0eM31c7irmXby/X+N+Fc/vIf4tKSpvnEae1/NncgFvRgLvZd/D2Mh9qe5r8O1hdILn6WMMkZTS86Ird4Qj8+IeBn8G3ltUT5TU9WHgFk+Uxl69T0faAvI+cqdoea57jPwbergMnvGI9LBHntQKL/j+uRHqMg8e9wZW/NznxLswFveaO4KsGZEaRyPDcavKSbNViOzt0jPOgW6m5KfgZLnxVkrLVfI9dock/m8hGjco/GduwLNGN85a58zaIbP0SZqeD+LPVeoduCkfnfPrcgxnZDTOWEcghEOeiaQIFbkB5E3UfN/26oCMe5BSj6DxvEDtptYXKJyLeqMtYUf2xN8X97MM7/uy8eWBkj9LI6knGBewCH7v5e6/xyDxQwG6hrmcyaQeWkQBZGMgDs+JHeudOcGMMFQ0MRrQDxjzwe4YceKBABCSQGdjExwXyFuFz3m+e7YQEj/jMzzLBfW4Rh+jgEdBjyEqPuuCwwVZGHRmPJA979BueD1q3v5RUkCuo4Alict7cMCkKZ1Z8TAUUPEIvUstthrQc25hsnVv96L4dxij0kPw+J74e9JAY+ypDz9fV5p7yXFviDcm2vYpwodSC5+MrcxdsaV0hiTi6nfzSMf9cfri946WYGg7euj75WjNSDckuoGgOZrC3ni/GRewnK8rc5QQaFdktae+lNCRHC47g7ebQbBFct/Iz8gTkhc9POV8k+2sxz1ln50P3Lh0Ie9Gjn/X0UmXlTzvti2dswDqxefWfYomgh06t79sBMXA2XHaHdfH8y/z1hnPcXavOH4M9s11wX2fXzheYyfJ2QwR/t6P1pp/7JwbSjs12RMeuslWyrp976Fh5Dlz9VCJIxhjIvF49i6PMZBYu9Ml33OndDSESqn9isz45DuebMoaMLL93LzKkhAttOCRgS8bH0VL76L+roHjyLqbopJ6jwnCk86GJ57xXFCwlrTZfd42VnpZXooX5Uw+lk65kuMwc+5v5oTQHLmQTHjbXMb4Gd0d3bP1Ow6O0nrlbxUCBqJiTQzmC0H4PuL9YEU7isMgAdDbRztsK7XkLB+dpWxrB4VyQh3PoiuzRdDklhBG90HOiM+v26zJE+9UOoTIIWoXdGNZlUrry8DzR7qJ+anlOfie32tuDFfCO/2NTBlGGQaz+rg5BhmCKFAXY/SxnHjKR1TauNEe37MryAkN8HsqWPyd7N1l3uJMmDt5AzwPBMh/5nD0bs/OxrvsTwhX4zVHPrZ9UsnVmdjaleDSGUpjj/lsnntFzpz2I3flyby/DGcUnubcKkXgRYYbXj4+ZJTyLudxN+BGeUUyLetEuXLvg9PJw4AOEnKQ1CVeclbemv0MUfUN5NxjDw89Hx0fOT24x8wZsBd+jq7A3anis26UeijgnGdTwuxZOAnpODuvmpO1HrlDCuAHOrSC5qz7FN4282EuXl3jPTKyFHJ0DB0xNqPvlEpUbXVywego1f27bYsm9SXdbpSByrkx6L05wqAHNbK9h9c8Addl2n60HI4wRKqceC0x3MdHgVhIfVzt4XLvLD6E3+jlQuxOXBD2frQGJS5QOJhR2Eu9EIBpQCcg+NF7wvp2hS31XvsLITEIJNpIS610DRTEy6v8ux1xpWbdso6AusybHBX9uG/M2xXKPO1dA5sRHnYPiWz/Ea3x+XNujmZwVwj/p6wYL2JsTvV0v7zwQklyZY6USiJYUAjO7CBbfmYwcCBFR39LoAuwNPw5BvqhrTcGqxuQLtx8T5M9m7+PwaNkDSAXCAG/n4A1dOeZ2mVabhSyT5wZwz1H/u1JhiPtsK4XvS5kWfe2h9AX/y+lRwIRem6MQQfQGqiJC3/2yB0Ovhf8XA0SPDaEJjTmtxJzFr7v7nB42IBn8ftx/0b+4d+l1Cx8i/+zt34DbeekmBHFc9hj9sbloVTboZtxte7zCzlA2M0rbnjPlI+uKo938KcM5844jN7cYfN5Ow/y85FPeIfLnfH5e8khU5D3GAkuj4rNZUSbRqRmRFSf1suLNXnFnCNZyB/XOc4rPn9/RykpLgJLw34yH3fw/Hcj4gztPa9L8L/LNObocsZRP6klRI/reG18NIaFN8sZ4amUWhKTpI7RHVZmg7y01KHe/AqBcigO2zlcN3qCkjoF4vMPa96YFMHnisjfy5z445akv5O/I/aYWvjEDSUXns7EbuCM4Q/+9v1hDzynxNfP+3wtTqCSIpbvHRJdQbii5EzxIhxuc+iZ75Jd7utDKHNd9LZPerpfYr6vMQRKNdv7PaSRbS0uSJiHn88okPz/r9GMCzM3in2v2BuaGY2/92dJfRzWPwOk7HTAvF3wsVaeybrdiPN3OqQ7evH+fqd9X4PDv3zO5+L76/vhNMp7/LnwkitzPy8fjlg53fm6yKofS0Q5O8aoBJyu/GdH6TvVohChfQZyzJ/P35GAl/tQlMshjDDfLzdW2TfnJWThKC/GvCY/Xz430ji0BU/By25AjPvOz0YZ4ciUGxzuYGIgSs0ALCV1fXI8d4k1+PpRoG68es8XV8b+x+fhtDPukcuxcT9HhxqUrJicZ87uPEBD7KPz2ugAjA6RpNB1oJ+jM1hKK7EdjbrXxkdjWEhNyNzNinYoDY/EmVGyHgW5j5Pf1qWL0bp1x99+KE4k7qU6E/nv3NJ1BbsaYZfh3RyME4+jKg5LjZCalzm6QoQI3Ftyz2E/zvASrbpfG6OSHteZbA/8//59HyHszAPzZ0CYS40h+/8dYWK45+hoDJ6IhyNQBOQksGevlZw65MrPnOHcs2Zu7o34cOEwMt4oUEehzffHufn3EXA8e+QFzv+2LtH8yT1q/rxAbQajgH31yinfP+bHnJ1X/JxGBMjXfbyyF/4ujHF/pu9FGBdq3/EEPZ8jwpbnXuZN7+rdQ689c6RlnoXAHdFLEE1HgpweRjRwNIicT13J851tn7pQkRt6bgz7vruj4h0tI9cgU5ba9pln8G4qudh/jBYS7KGZke4djZT6plwjspdSjxb4cKTPjfnReEK2jGgja96PHNVmfh6+V3zfn4MyldTuWyotubWbT8nNo0/NgXHjkXfjJH+ZITWuz3/vax4dNXeij4GOXnsWc7xvc+RcudHijiZJnF7i/aHxURgWrhgldQfrG0XCDkLkNaHkAggikXrPyRUbG+fE7QQJgzhM5B6IW808e4S+vBJhnnb9lJ/wx/Tjf9QPhDeI0HCBhYXvz8HadaiLvdmP3PpCpD7ck1JrGsTeupHljPaa5+M/cyb24Z91GI7GKm6s+HtHBS7RXrzvtun04d7plM94Hwmv/hw6MDJQ7tTrx94MRg9M5XO71CS/0et1WhkbP0UWue2ff2f0ZEcvMQ177e8ekZFRIZI7sFiuyGseOXPHWBpjtXmYM+97zWt3o+9DimI00pijzycQqIFm/Tk5FT3dLypqBjG050YxssLhXw9/jV7luk+Rt+BOBQYdYQI/o+iGafvvCnSc/4gQuTLhHHAyfA/4zMiXo+c/ZULHR2e4O+1E9YjaPntI0g0t3yvfE5/LawhEKD+jK84XeT56+K85La8ZfC7HxrADcgCDzJ01/77ncoHSjI5G8FFuF9K5nOHPnPdGZ2pIga8Hozarlx8jWjMapC533JEYke/X0D1/z2sIMP8+jhzOKoUPI5Ljw0Oir42PwrDwXgkwXSl9a9ejpBcZrFKzxBy+gYg5SCAxfvehTFsXdG448Pdrmcx+oPyfzzlM7MqkHEn7bhD40Sc6usLB8MhmHLgB4t61d6yEkF7zUnlv1wDKvNYRvh3DTCN8n4Y1OoJDtYzvkSvf0choZ9GEp7fJXfe+RlxqMB7eKsYBvRGAsUOhqnTzcE9y9JBe87AxMnxdLmRfU4QuZNwocCOJvXf4UlJnFLIHGJ9On3iG3GQaHmt9BwiHN9XCIGKOyfaWEk3O3JUKax8Na6cD5uV7P3r0ryE3/p5sv3dPHC9xVBgjgsde8vdRznJw7xczvscbLEnqKow8TAetunLkGS70fW7suyuE0YP34XQDjbs88/N1RJS7Whz9caOZ4Yiu7zl8w3ruQ7Ke8+5ro5QUZaLer8H3gGvnP2RUuFIbDawR6eC77lQ5suMOJD2DGGMOE/uKwZHSmQTOPo7eOj871GTPaDSen2vhVUcexr10WnKD47D9cIPfZYA7wc6b4+dHo2XMp3C966iO64kvGx9NVQgCU+pj+Pxfaj3vo/zQLLgpt6x6DgaicqHGwfjvynB4CCG+40rkbkz5miXnv5vSy+qH/cj643/qxwbjYgFLLxtzuQfGz90zCKu5XrA2Zqu7sQSRdAiPBkbf5heELOnFfvgYPdqcirx/vwv5o9QKAjWv7ZC67H+HDCHkEZ3qlMtBVUS7Q8NpQNVDJU4NKlCGtcVeICRKn1OD+uIcR7ryvRih4JGGcqqVB3ZG9Fvg8rVcf+/7yUCBTLnPCOf5+3FW05CH45n9CEvesR4tl8fPeMr1Lo6jtfF1Q3MU9EdJwX/Q4KhAg+4Gmuk8xHnrFAa/55lTPqKnCreL5nRWco3IU7SlNkQkT2fvCg8zlpIiaz6l04Cn1NRp/yitG6jvR9zXol4RZJubh0BKSVGloXwE7dFQzA1T9+bP/i0tnLnkI84PWkmpKK4zMMcMeTd6xy5TMADcK7+b4cHnOffR6BmdPZJLO7qa9hd8MzZoOhfe1uIVS+yL9/WhF8qo8JwOGZuFTXMq2tXyqPiud1f1xF/unXI0zOWBFwuMg7CKG82+L0dJUW3n9MPv92Ed0CodR3OqYcGpGapuvNAnhflCg91cqjF43+eguQgrqTk28NaXjY8DsagDb9+9EzbILVUX4C7cpL7M0YWCe8ls8DoYCeO/seRyet2C9DmNHosLRuaCQP7R3/GD+o5PPo/nuWfl30HoeQ22J0E59IbntFpWPZ9zK973GiHhgtP3zhXYlE9Y1ZM5/bu+dz5PzvCw5zgaE4Q/QIeu+Odp18Plrim1WxFZA3MlBjoaBZK6vv58b7TmHY52oeGWPXv5GsQ97oXTgitY92RGejkFQN9Uh/c6rWEY+Ludbry6wQ307izS2ZmR37vX6yjGUiFifj8aTE7nbtCNe+Fn78jIiPQwT1+b9yp57Z4R51dHC+AJ6CFxR1D14t2wGaF8nuVyZJRDfrZ+WZif12uGhisUf+eI9LCXQWulyZFxru6Vj151NKrKvYHoSCZrc8Pb5SufHeXcyP9jqIQcmPGCRh+ONozPc9nLM6HBH/tdP6Cf+5/93qBflx0u95GVyKB1cHikHrlB1o3rBGFxXnD6ZX0fyrXxn22D7nEZMMqKMWl7NLwlRf8WDADedwzPGn/O8/wzTsfR1uBoSP9XoRXSR2RYvNaVzjcbAQOT+90UCAaHFUeLzYl2FCJpOEwO15WgK1sI53jlgPw9QZD14MIbmLeuNz3QHAwM47j3PjLxUc56c88KprzRieg1Ae5CjP1ZKsTqSIBnL7tScAUyCrJQCOoTIBGio6J2794vlHPFGd7KkB3PHyxrh3rXfXqxj+ytC2NHg/jcmC3Outwj4x3h5do+uCJlPaOBC0zsKBIhH4dSJXUhHk+odKE/Ktn9yNEQ5zVlspdc28z3d3fE2mqo4DJtHW9xHn6OfNeRnNdQQIYrfvhi3OeUPCzWBCVCehsUObTgBqwbgIcpZt8LqaFEvAdecAN2fC/rZL6vGQi+RyhsN7w9ZOoyyemJ4RUKXZ8XvTQsR2MgeLo0A855z/kM48M/x++4CHE8e5+zG4XQoM/tQzfBjuv1d7gMGw286fHe8fG4f9xq7QYHKJbT5NhriPe4EzLKxJE+R13jjojPe0R2fN9c5o+Oje+R/3s/clTJQeNuwGLg+VlJLeRPe3bfL+ZAjsmIWn2VcfFRhEKwsth0kAtpaLRkUI4LbmDbuHLaBMdo2UlDyWMNIzgxST3zMXhW1Kenl9Zh3OKHR3r0ddjrPulP/sCP7jwafu8Z/x3B1vd78xXeMZZgeiv0o6RoVe0CNwiy9N60GzCpElkuhzxNp5TWrGYcLvhv2xJogz9bMtTJBIavxc8OhqOpktQuH3NEx1GuOKts8GlqqMh+nHFWYM0pH626oMYaET4+d1f2vp7XvFiEXTA4n7d1HfZMvueNuZhDTq0xDaE4YFCHgV0A+zwcwUFo4MWSh1LqHs1TX5Xjl0alkl4Ix9GbZA9e4zv38B1FcwVJ2MqdBBntjkYXa3fIGmHoa87qnZdOqVju1thXwJUE3z9KikvbIuHPnBB4xOmX+bgydpnBO92A85/t9fuH/e1r5HZc5sS7/YZgbxPv+7qti1S/k6cjysQ5T89ZWC1R0hW684Cfy/2VSjT4wPeZwbMXO2MUusuulIr++J/+Mfrj/9KP6Xj/NVRkdBrXqmiRj8gixmiosZ85naGhuHG5pE7m8d7oq2IK2B1GH26AQCs8jxCRh33ckeH7yHju4Qn9llpzMHe+cyra6hnAcyW1FgUuS8rUztbDH+OZjuOjMCykFAlqrqwZvtlSTyi+yaMw80N8zcIqpZUTeXdFt45H+M9js6+hCpIJNPXJeikVPcybfsbP+v26P131B7/vL1Ypqbv+2de0rUvAtkdpDbNgHgRoSq00EKb1taM4Ro8SxgqE5Wid5KZ86DiO7nOwujdAYi58Z9z704pu+RTsD/uLMnULnPXvNmcvtyO0wQVoo0fL8+a8B3yZhrNxo+IoLTE4vNyjv9IY4eJCwIWKDxc0Ds9LCoNmFDBHSR3k7+GMS42b0hFz26cuLpxSOZV+NZKZA/SAcDnb4lseSj5eKFtgYIdhUa5L7sNavh/QiZf9csbMBWPJz9q9/yxpKzVJd3i207Wvjb3jMzzXYenrvGorrQ/Btk/d8yXrD2PfO0rSu+XeLqBTnwPCOUFv7v2P8LejfOwN7/uQBxh8KpN1Rlf+nPid/Yzv+xyRSSO/uvJ+qG30r/MaNwo7ihPGBLwmRc5IljrDJtl55EqnGAKOdjHKoNQZI+Ks0vOeI8PM7SgniuvPmfLR8c6hPtfBjUOMIr+fxh07LiFzQ3PUA/e90Z33EymVV9woQk77xY5ujPr5d+c+0FTceXO0O1DgDTd0MS5xrFlXnEmdszsC4xo/ND6KUAjk4RDaCOf7Rh+lVTSwwIfa05zvOdQttWuzpZbLMXoP920Ob9WhPTcMIAQ/LKkJplJai1iHHgPtyLsef8Kf0ic/7gc6xnPjySFPLtJhTQ69AnW7EuZzET44+gvHPAbna3clztrHMrXX6umdyCgHPkqK8q3XGu34WfuzePa2T00ApiJKT6fc51igBL3BkcOArtTXmtjq0Kobhl79kFN/14bP02Hb0XP2n43QduyBetiUeXs7eGfyUlIkwfm8+F14FmZcUW/OXRa+/07THqJh7zwz3FGuke75Q57PaPy7svd/Oz+NcK9/l+HoCM/xDq/MwT1skuRQlhgGngTsqOcYentNaPJs9+DxTH3vfc2cvfMS63DEx9ElfuZr5+zHM5AUXmYZ9iwMX6PHy7xFPpbTKU4dz5MUoTASeKENeMu9aPaiS5JNLeQwGt+vebsu48f+PV+mxPwcR0fPzyzOsMo/ekm4jjiGPXVnc857dBx1ee6KnXlgRDtN8S7ozd83GmD+eebtZ84Y0XTnJZ+7f88dA1+/OxWeH+eIJ/S4Dkn+r42PArFIqp6oZ1ynQ+/Xa8cAQUAjXFlSlIS5JzMaDvG+9OF+DP6+8eZFh4LwzhzavS7rWZlhh+DKfpnO3v6/81/4hXF4AXGWBqsiPLH895L1fL/ok+uzSu3jD2ROf3uf/wnrt1CHjpYJrKRX1+3ow7heF5Td/g0E656d7yXr4/nurUitiYwjFt7QZjum7jbN0Qsu5cw2d09SJelWlthHlOxsws/RKDLy3WMJGjLB7fThZ48gZS8Yo5HsAonhBsK4d6wR1AqPkmfhWWDIuifNc4DSveW3ozg+Hy/h9Gx8X4vfpePDwwb834Um+868uGLbFd1rUDaIFb9zxcmAruap7zdAqGfJrd8JvNfRaird9+DFdX95LwgK8yipu656fu25Ztw6asOcj70voXdh7mWaCPfR058HJRUOTOpRJqohqByLShaj6+V6CwPiMFQt55ddTHn/uAbJkNr0snQ7ZKP6BnWEaHb7bCTylz4U5nTEKKWV7XMWno80hjr8PFg/v8s2b+bAFQEo4W2f9O56C/plTVJDdMfcKtcZrIWbdH1ujlBAk9386j7xfDf4oIXFnDA3wnkGe0ZliKO37mSyJviC1hBfhVh8FIZFkYJJcyq6HedNjggloLzRs3Ylcz/mUBbOOFIPC7tl67FNqSUvAZ9LzfrvBJ8xUjBOPWguByo6yzdHRsipdBarK11X4KMntJccCMhRDal7ad6KMwswP++777Me871TPj53V9IMf57vw2xG0/jZ2zZHUyWELwzlwtmVja+fs3Gh4QqMc53sPIPg1RRZ27O+dHfKLX6M0HBBPZZ7QVsl9QjH6JmPdMRcEUCsQ1KjndLCAocUoSoGF0wF9Ml+yNA4Oz8EgqM5zMnRBFds8f7SSlZBO9hDPufe2Nh0zN/rZ+w/67zGVKJk1PmoQ+OsVPKceJ/IG3tvxobnbPC5ZdrOa7J1XuzmCnikS57/gr5RsKlvUsfPgi7UI3GjZz564M4DLvjZoykd0tR/3j10hhs6o5fq/EPzr7nU0I2dO4pxymdeRFbRUVqeEQaJhzMx9nh3Su0CSORFUunmNso3eMxRF+gSI9bXu/G5VDoFLinaX4/oGbSC8zP2POI7GF7juaG859yQrZRKlxA57jnyNBAOMyZGg8Zp35FMqXVv3o+sqerHlTNFJh1nPplKLycxoEE5/SI2PrdvsyY3TkvL7eLc+V3kuQz099r4KAwL6WxS4gTyvF50nddQHG6R8W8YLQRlJVRPNvTvjPXk8fti8Fnp41Qe3zwhNHu6MUTn7aoP1QBDYhCE0BqMgnWf9FBvtZTUxfYelnsw97mWJrTnqcF01CFDHFM+dFHrW9AJNxfQZniN+8X6UjktYaWGViDEXfgV+x6fYXB2/GyZdk11DlzGllKJG17doveSPgRgKSluMJUayuLCCYt+ZFhJupvXtA1rkNSVJbJvJGWNe+kKz2nvNes+BGucZ7tEy8Mi3P6J8Amj0IT1lI/uPEa+kF7mI7Gfedq7s3Nafw3Nc8RlSod2tYRmVxDOY75mvCk3Brp9M2Xnl0d17zZ66/YaGrf9ZJ0owGSGFcjoVqYQxE6/7iWjDMZwF/wITbuh7vzme+jolhtcvm+lJG2lb141pUMl99VTxeZ0WO4TjlU0pqrvBdn1u09AdfDwPZY+GvauYBxdYY5+zig+1vNstD3lo0tUHp0qkAv22JV40LLtfRhdNRHR0QaG99qYUolumcydEIjf8Mz33TjC0bvvc5dwDvIyNhNzBML5yh0sN3jn6byM7r7P2tWQHj7HmfOd63AXE7IPhJZzGw1S6MhREkkVee7L+qXWXHI0vF4bX5ljkVL6DSmlP5lS+j32s783pfRHU0q/q/75r9rv/o6U0vellH5/Sumv+coZ1IkDKbaDb0l1vokuXP0+AX43ohT8/r7Nuq2LntZLMLEzZRme7wxGGaCXF45CEwXmjOiHydy8p8Lo9TDGHhCuhNfKnA6P0aJ4rfFkXz/Jd85gHnLwvhhO+KzDkwjdO5NazD4PxDnb/PmzDjeL8n326dzfhsCEV5D60tfRKDzUunvyTErmXDC6gmAQb30Nunaa8n2D6d1gZQ0+B/7vrcBRbvz7anlBvDe84mPqaBi6Y7hioqMf31/MuEIgYuhC36MBwHuc1l/ch2CoDXN8TUiOgsdpxBEGX8toBIXCVnsm+TqOyji9cqbOc3iozseOPqbUGhtBZ7y7oR69gmIeGBsuzMktGj1maMS7/rLn3gnSYXj2CXqiFBC64TOcL/kMTjPLvJ09YAxtwqNFiTntQn9uoJeSOjqmo/FI985v3o3U5ZyfFefK3EaZ5zx43+e4RM9pBHoII1896uEO3zKdiAYl1Oyn0wN5M6uFF9zYls7bt5dp63jQkTToAmSLP857gcgcfaiDQS6M6yh/Pvvp97u8oJca/n26XyK/CB3WGXG2fzmVcOi9mVgYcvnDSes+vk7y5m+U9Itf+fn/rpTy8+qff+58efpZkn6ppJ9dv/MPp5S+vKm4zlDICKVijV7nNRiPA/BachhtbOOKR+WMn9JZl++E7ITavT/1oQCIAWNmrCt35dzFqEypcesmwwWDfx4GcC8wjIt5C0+dNW3HpMcqPLx/A8Ot6lGRucGGNepE7gKQ/cFyZQ2e9IrXMN6QRxKZ77cbDacSbK2HiZcGU5Z2RTbWuD/bLyIba+f9HI6j3emBYOGs3ft1+hiTQ0n8Gu9yGI0LN1pHQenv9Ut9XEi8BjdiDJLtvu1TlPYyR2gMAcHPHZlwYeat89njDgk8WgjOhSnz5Hn+eTfene5cILkB7nvmXvx9P684h0bcWApv1ujEb3D1tfP8lEoYomFIq30eY5z1uwKGjpz+HeVjTu6EsL9OG1LfNMz37CgpjCOeOcoq389ubZbk7U31mOPovfNz0NnrvL7YO7/1uXdO+mZko9K8myPBvEeDjO9AK5wh63L+4v0uV1wmSQoZBP07X54dm8/f7yV3vDEq9su8haPLWfo5T7Wx3HGc1wb4nMK5NOTQ5cnIK6OBwXpAXNgrpy/fI0fYWDMygjn5Z90Y5/N8pkNg63nhmLruQwd92fhKw6KU8tsl/cBXfa6Ov07SP15KuZVS/j1J3yfpL//qd/SJSS5kJXWNfii1C+Fba/zdUqY6YTtOocshk5S1DNY47xpRDlf4rtSkhio4IuLCGM/HDQCI0X9eSgoLunmFrWMd48Hiw8wXlIQ/o8cq6YWACkGZm0cxeijHQGB8f1Qs41zC66tZ+TBjeJ+mMMbnJJu3M2Pk0Vg1i4eZLtN5LTveLcaJP8/zHHLu0anxWnifm3e8Q2C9ZliNhpwba1zbTv4N/3akzb3P8UKukU5P4XvERVleBht0X4Xh2QSrxVqlhvK5EHlc7h09dkaiGbgINT6bjX74t0PLLhBROG7k80zm7goHL3zK59XRfJ9z8dgzZddOW6wLNC+lEldnsxceP3YB74PnOU0hS9xwZB+geTxfD8O5IeC8hJcdRsaQB8W6eZcbNXTDTal1hnRaCYWS+usAeJ4rac7EQyx8zo0GR0bdsPkyFAoDnTn7fvl+8A54f6z+G+Wzo268d0Rhvevmtk96vl86tO18Z1+h5wjPWukk0BGqtMw549wDLVJzKJkvDpcnXSJXfP5+hi5vXBa5bhrlr//M58V3WbPT8FFSyEIP8XhHY5dJIyo5jh9Juen/MKX0u2uo5Lvqz36ipH/fPvP99WdfOpJ6a8yVs9SIdPTg7tsct/Ottdb6qB4Im3+Ztugs5t36ONDRsvaujaNFjbAbPSGHL91IckvxMjX4UBqqAkywOKTHGqglh2kYXHnMcC8XQnClwjrwBN0ji/ii+kY+7hW4V+5Cx9c0wnW+D6PQZi6O1jws984ziOY0uSXySqehhUAFtj+91dwl7iZbi3sZI2OOBsZrHrw/jz1zBQDUyDMd7XFhgFfKmSFM3SPmdxh9fq6HddeTzvyko6QwJNyLcWV2zrP9P1qDlzNZmvX5eTzfL3GOnaLKrazO3zF6R37WbQ59VdY87QH9uoftSpt3e+Kz7zF0uUx7dNKUGm9dprPUcqlx/fDi1Rpfvbu0q9Q5R6cDP1+8VqdrRzfhldfoR+pRRJcno3HrNOlOyoegaM70uaIyzPe2LXG3ikPhGArecTOpdInNObX/x/Pqleq8w9eC0vI1SifPel8JFLcrrZEH+JnvQyBNg8HqNOmJnThgrAc04mG5x3uQsa+dg8tqQkdOi6zF83TYTy8HLjr5nvV7+3TCDtCKI3LIOTeuoEWX6VJzeJ33Xb6MjotXjsTZWQfnJbfQ2dP90hksXzZ+uIbFPyLpL5b08yT9MUm/hv195bOvckBK6XtSSt+bUvreH1xvXRbqWEvrAmqZm4cqSU9V8KF49iPreV0CPh3DDbFhU7sRcyQc3vmwrHpYVj3W2yJHY4Ph/yaRhsOI2zhrsiWlgv55j397++YpH+FlgbS4UNiOSe8uN7273DrCc48bITHWTku9N3Sp++oE6564w3kMGNC91heQoAlDr2nHC3A051IvEnMEZYRsERZu2fMZ77PhisYFBVY6z0QIuSXPfNxDdOMj9vJ4CUv633zWjZv9qHc9qHk67t1j6LLP3qAm2zN4LwlaIBGjYh5RAowSb5wjnd1M3dBiDZ446/vqMLiHRNwL8r/HeTuiNKJEnrzqoQinO+RETiUQzXhWDZvd97l+7jQqntez/BgehbckhUdPPxx6N7CXLrjhPRyNcW1ujLNncXGi1J3n8cq/3aNneDgFY8AN8Ou8hsEEWoM8jFCytcT37q77caKM7+/X+JxD3b4PGBnIGzfa+Rnzd2cg+FW9UYOyA23zfXQ0xufC+8ZRSurCZijcce/HNfmz2A+QJmQRn3eUhTPhZ/BUrrLCy7U5C8Kvjvr5+5FHfvYjmu7rHdFA/jjtIdPdKfY8NJfdfu6jU8NZflUYRPphGhallD9RStlLKYekf1Qt3PH9kn6yffQnSfoPPvCMX1dK+QWllF/wHcu1g7w6gq8b0nnGatnzeJ+OBoweE4k4KAq3mEfI2QnSoScPNbin7Alh/ixXjKzDoS9HZ9ww8Z+dzJhD6EGcLpzv+xxeF0Q1V6+tlBTxd0cgfB9QBgyUJwLktavn8QqAKl8zstyaZ3SEbQLavUeeLykEHOfkaAAoFQacQ3tuNLgh5t7alA89r4ve368h9HivhwVQrngfMCxhNcboubvSHQUIDOxCjoRQDJGRH6ALaAjPlGd4Ux9XzH4u5BacyFdLPkNBsD8uhP3/0A8/d0SGefk7Hd5248ONOTe4fA9ROk6vrsQ9bOa05YoMWrltS9AOz3Gvaz+y3t+vwStOYygVaOjZEoVv69IZju5pQiO8Z6QpRzH8d9nO3kNDzHX8DkbTUfpbWN3Yuu+NT9kb5uX736GopeVaOA8h77whIHNDZjDP0SlwNPrF+izp0mF5X/eDGUvuOHSGfM0JcWOez7hBjQE6D+vAmcNzZ78x0PDmaRzmiHCHVKdmGPE7aAbaGL3+0SBwnuf/PlymO4rje+yf8/3FyOTZjhKxl3PedZ3XCPNP+eiSyr9s/LAMi5TST7D//tckUTHy2yT90pTSNaX00yV9t6R/7es886jMs9TYJMobwYW3Ueqm0K99VJRYexDmlI/IybhXa/b9/RoWqQt+z6p2gnLF44rXBYhbr6MwdkHqApMQiXcKZOAleaOs27po2yc9LCfqwTMRRB4/92vCIbixMZDPB8U5zoF9deEi9TX5oejN0uayIp4rqfNQ2cvHuhaHDFEcwM0oA/qZSCdSRZkc586eORNO6USeYLxATGCi1F/Cg8fKuUF/CEd+54rxNeN09IRcELqnwdlyeyD7jtH07nI7jUj13RvPRmytsoQzvK1LCCOfU04l0LHrvOq2LTEvzx1xGNWVJXTvdM5zGes2R1c+9sGhfzfcXaDzOVBE5sz8OFMQK6d7SpS9CsG/jydPf46jpAgdYXCwrxjnz+sSCmjbJz2tl06YupeOwZLTy74GDFd8ThejkgWtdLriTLxXS4daDkgGSA7PQSbAR4+Xe+yRo0vQELRwrWXv+5HD4HJkjnO4b7MeL/dO0eBwuJc8GgTOKyO95NSHDud8dh8m+dIdnOu8NmQh7y/4eERYpSYnyU07jYBNj5d7GBxLDa068pZS6xE0T3skpHN2yBRC9H7GrO26rFEtwnl7eAGjCD50pAS+9pwR0Du+64i7Vzs50ppTCUcG9N/3KWTJtpw5imZ0jXrgQ+MrMY2U0m+W9Asl/ZiU0vdL+nsk/cKU0s/TGeb4w5L+FkkqpfzelNI/IenflrRJ+ltLKV9+cbtOBGIZWjWfz2vM4UQotZAJjDBPu8rRZ+I6fLcfZ0+Kedo1181B+DpRHCWd9fBT31VzMWHg8S8OFsGUUtG+n/0B9uNsXLJMu3YzRBwKK1OK2K5D+TyL919qJu6UD922pVuj75EbAy4s96HywAWEe2kNdmsWKk2dnOGd2HIqYcmjNMdSxcu0aVlW7fukL24P8ayn9aJ3l9uZI2EJsDybOb3WvOq2LmFgugc2VUN0mXbdj7k7ozA46ucvFfHy/hEwLcPhRs8Q9zOAJmHgzrjpmPaIviNOozTfIbRxtXAfcD/eFH1SEPjR8MsEhAuSZN5ITnY1ezr7hUA7KAvohtLa27ZEfwDoKoxo9a3OGaM31iFm0+u3147Q/VFaf5UROsYQic/l1sfB9/wo/cV0y7Tr6UCwb8FLh1olmnJ/4dlFbX+OauBj1PIukmWDXsyrx4k5FVpt7re3ngnQrZfCsmcednC+xikiN0ZStx/rNgcNhTKuxg8w/XVqLcm562PJfafUKfd5JPy9TK2r6bMhN1NV2H4ZI/zM75ERnYNmRqy/P6l0RncYaXWf3UCmuod5uowOJzDvsffs4X2f9bjcdRSFI/Sa8Qet8HN3ZHAOPMQwdjnl/+ib15wP7oOK80qlQ5nc0XHkUOrvcEr5iPzDyfYjaHJv+tN5iH44OBOncd0Ml3OfXva4GcdXGhallF/2yo9//Zd8/ldL+tVf9dzuO0P/eod1icWXytQuyFM6L21xpVSMAfxzbuHtR47bHHkfFqRbeLPKiy5y93rVdJ72zit06JAKjofqIboAIpZ4Zt7Oel4VMcbbsQThOYLxUAXBmQdx1xe3h+6dQOfbMUVslY6N/HvyPSop1s5apbNpDLdLSknbNiSYwQj138zBDSYEPN+5zJtSSbpc7vqZ/6V/Tfc//R36Xb/j5wdxkrkPc2/HpJIaLL/kQ1t52QL40S6HcggYBoiYZP0eEN5kSj8ZU493g+CtEo9H+Lq3RIfVEMrmVY40GIq0koxb/9zhAA2eUOzLhOVApmo58vP9EqW2fg4OW7NfjqZl9e26QXKK7SN08rRdwph1A4T5Z50Nq6bUIwUoEanW2w9dL/1zMedS82XUoxiSOjSNd/v+oNxGtMidEcJul6ka6ZfWx+JpvQQyhuI9StKkFrbLqej97RpQeIQaLF+I+eVUzpyF1Oep5NSHJZlbKInSI4uOjKKkWBt04oJ+P7IeL/eQWYEOTlvkUPDudW/JisfeQieOnCHTpnwEgngiRA1pZW0Ys5xD96ypGc45lbjg7DD6pIGZD29DP6Iq7AcJuc6b3d9qiKrnJBHSQT4gqy8uf+se+h1FrGsvuUNJULqcGQms2zF1+TwMp1+cRwwbX+9r9yP5Xo4XjUEPq823nXmT6Wvdi/VoDQdxUvj8/cj69PoceYuSOhDgQ+Pj6bxZvZPTmm+38S3mid+2Re+WW+dRAvXDjBCKeyRlYLwO2jJCdqvYhTRMLjWvlfgZz7ttiz65PjdGSkfXHVNSIADu5S9Vkfh7H5Z7dNJEgK7brOV6073ehAqB5FQ0zdtp6ebTeCDvxAUXDMx+hYGgho5g0XYeQyrR5hUGh5FcOYwwNEoSa/2HvvhUv+O3/VWh8JepXU8Os2Nhu2LzHItd7Q6AgCklXS83fXF7OI2D1GBRrPK4+VMKmJtzWY+zXHGaqsGpFF0/2RPWMg7KAvHuaQfvCJB7LA7zTvm8rtrL9lwB4rm45xteUslRdv2aEnX65jlRrlwaEnTf5uj06kY3Bg8G73ZMSub1+Ts95FSUpNyX4KHYRmMLw5ufBVJWjXf/LELXhTb04RVA0PmlOgHs7TLtum1LhN1Yw32bQ8E5agK/XuZTGWcVvav3aASqoZdxckcQuaoa/sqVVg9JfjNnTu0q9IdpE1VN+zZ3cs7nDX1hLHuIkD2A7qQThcBLX6azq/F+ZL273CIchKLFobtv82lUWb8U3ruaYejvdcVOmOJ5vYTj46gWRgWOQNCP+tyeKR8dwlXSyxbh4cAYHdzWRUs1EF0Jhiyu7dIdgYNvQO5AQ3GiAmGR9Gj39fgY5+SOhfPM+/s1Qtqum8YcKb/plOewN4G4WDMv1zV0Pt2Ps6/GMm9aqnN73+dIJH0wNJz5ZZPdPO+o83N9+qHx0RgWUmuXHAeqc5FAjyhOYkNS33AppyOs6HnaIztc6psCRZzIGNyha/+/M7K/z0MwU+5v3XTYTblBVLM9Y2QM1g8xBtxbCeFJl3gvhELMnBwCGI59c6+xlKSSLFRhVjwIScRm95Zd/lpnPjz1ZM8+ofyXio3fw5C+v3xmRGg4J4cLvSnaUZIuVemdggtvaYs5PK2XF9eeS6eQde/+Mm8RR3QmQpht+xQWPb9zaBLakhQK35Xo2DPFjbF311ucKQaAe4YhyM1D4/vXeQ30DMQHVG8isfPo+3R4iaCkMFC3qlgIZ/n16Dm1JOd7FbYoARAOwiu+dta6l6xJTTmCFBGfD+9dp9Kd7bzxxsijOMoZosTY+dbzg77x+BRCnPcy71BcuTVauq2LHuu14PuRA4m510v+JOnz58fI9ZrS63H6qAxSUyYYwsiuOe8dDfrPd0OkCA+se/NUS2mXxHno7din8DSv8xoJiCiGq8nFyfaZyjA3Dr/1/Kh3l1vHsyCzyDMMA4y7qcpYaBoaRQlC2yBhGHDsme8lc3HZ6oZnM8YPSbkhl4QYjpeoHg5dtnPCyEAWYmgeNr8IJ6qo1Bw+eNNle576HCDm7TI767zThPkHjxztbqBArq3ElbAHshzjn/AUtOVK3fNpQPx0tL5KkTRrjt/TeomybHdeWQu0gMEarcEv9wjXuRx5bXwUhgXNoALWvF/0UOG8ZWq95T2ejrC9zJueCUnk5rW5x4+l5QjDVC10LDY2d5n2ztvh3RAGh7qYMoRYJMVh+OFHL4bqkXnZF0lCj8td12WNZM6AMfMpxC+2DzkVrWreBHA6h35bT5QmV4MHIgNq3Y+sPTe0IicSV2t5ZZo6yGwUBu55nwjLGt5TQOXqKxrCg61/b6mEIOcGSYj7cblHaAA0J+LassZX1et5f7+eoaRtCeYBHn1aL52ninJE4Ced/Que1ksoWN8nEBtJ4R0izBAEVOFI0p5yGMgqLc7qDIzwIbQCXJpSCbjxoTIxisaFMF58KUlLTcTk3LkBF6Psqd65Iyli7g6/u0dFCAID8DQYamWL0QG8EQbn0cIjblSdXpM6gelIl/NL7O8xnfdZzI2WHpe79pJ1qQqZqvZPrrfzvE0IplT0fL/o04cnTbmGeNQcCc4Bo/mkv+qxVxr+xuP7WON1cGAYXtnF+eBguLPj4VhH9Xywz454wOdjqG/Kh0pdJ8jWYkYVyd2u8PsqobmnX7L81dr/59Sab0mKCohtn86LD4+sh8td13k9r0io6wjju94hQ/6DGzhuoHuVD3vDfT2eV+ehkHMz+xyQMDolPW2XqGJDZrgBP+WzGmzKhy51fST2woPsJci0I5D8jNCbhxhTaWFGPstaMAyYsxvPPkBv6kLDgfYybMZ9m7VbaAfa8dAYzoKHh0IXGC+ioz69Pgdi6BEA9sT358vGR2FYeLmkt5Cd864vbg9xHfl5c17S57eHU1mkM+ZJvTSlYKcCy0qlQZYhiCfrVDjt3WHAYF2M1xTCCHvxfQ8jANUDsUqV+C184dAzmeQoB5Kx+D3K2OE6LkKDccO4KScMzP4xZ4jY43YOU0c8OTcmcSvdQyCH1D0LoerC0BNfIdgR+UFIuCCV+o6TCHtgSQTTZdo6ROI6r114KAwCKaoqEBQw+KfX5xOROCbte6MHrHOGr9EheTw31sy/vconjMBX4r8eohpLV9n7+37Ok+8jDKZ86P392pXzQdNuVISgsByAez2D67xq10n37y63Vy/OQ6n6pWG8x2HtlM5cp0MtTydPTVGN686p5brwvkOKEJTf6Eny6GHrjPnbLcSc8TLtUt2XuJgvtZCEI4IgmwxQI+iZ712mrXsXw5UN9OuIFOt14+IMFTXUYD9OT5z9JGmaM0deYZyxHgzApSpRqXmv5E4gM5mLV5bgEPAeQsZOr/uRA3UJdDHv8XyqZdhb6fTooX/CaUdJcfOoKyc3eLIkpT7kRQI8RiF7xtoYIGfc3skcudbckR8PTwR6O7d2377HODi32/UMyZtyd2NyH+gCZOeL24MeLi2szX6/v187tCD2up4Pcj2l0hn5IIW+tz6QD4sZbYSDt+rseJ8cNzChW78egA6c7643Pd0vTZYbCvqh8VEYFkmt5tvL0iilg7H4+afX59hciMdLbvYj63Fud2d4MpI0VGUYURxqyUJSn5joyu/Yp07Yw1yEFW5rK9N5WFY93S9xl8etxvhPQXJ2UfSGT444oMyXmr1NZ0VJkaMQil19chnzdwOFn7EHUz50rbBygx5PQY6XMjZIAbLO6fUsdt8z7+XhSAOfBWYdE6MQojAbVnwYI2pNeEYCdw/uNAAa0uQW/37kMPzmvIcyC6988LDx7uN22/oXnkqDJBvS490Mnf54jysqFOZi+TF0kCzlTLZ9XO5RoREeXWn9KTC+eBZlljwPxUviXan0eaJDh0qpHmVVNGlrZdHLtAf07Elm0JejiHsyiDtbuZ4Z7dC7G/fkqXhS4DJtnbJ3GuCcEH68/5Prc6Bg0KSXXcK7oHmH8QmK1b1RQk54qqGcUt/mPOWXeVugEQxH8fz/5Ds5CrYfWckclykfsT9bXRPVcUD67CMOSIeWQhM194AcE97rXrYb6dDpuSetaqeFIls3S6dnnpvVFDHDPX32YkRq+Bk/dyPSQwX+XUKyPgf+Tc5XnFEqUdZNVdaUjyjFvG2LLtOmT67PETJzRNQ7UVKlwjlsmqIZIkh70F1FSMKhNUdwyi153wcIWXTmNETZ+YKk0ikdmiudhvOSd+250YK/wx0+R45TdbYDbas6+s8Jw6JI1YK+y6G6UQCzaO+XQNndZdp0qEF4R0mR6ezNhMZmWxBDZySk/t4ShyMd/gR+4zlArXiArmCf1yW6eO5Ha3S0l6ys0hFf5DxUQYU1HY2a9lmPucH7zJ3vuULnXb6XWL9KLZzAGkrNS0lVcOGZw4wok1Sf5cmFxc6J/ISxjXkI0tLCC8/reZ8Ln0EhQAN4XqABT/dLRxcRYrI9akZZK6lyGP6L+0OHjO1HTZCd2wVc7pEjdD0MEfS4vWy3fs6veabA1OF5GyzsBobHO2/b0so+K0rhvKB8VoaQa0O+CqhZSmci5Lua3Mq+YlQECni0RmnAsCQWexgNLzLixLbX0uCBmqCCroPf7TutL0vfo6BVoDQjBQ92yocuNTEQQQu8fd9n6fYQHp0bhwhnzg2jxZ0ScnkctmdN0BAQezRJMoWD/HBa79CM1Lpsjl74bV0iIZdnubzxfeN7j5d7vaXXzrB+nzkyp8gDUDOWn9ZL572iMCebx/vnh/C2G2raqjsktXwfexZnjfEtKYza4JG9hdWgWWQBIUt4Itue8Hw3qqQmz1B+4146gnuUFDlDt20Jp5B9vm2zdO3bZIM8j44KcyFkgUzxTqMYM2FMF+tPsc/KKtIrfZKcRjBOfF3k7KjO+5JbC/Bk9LbWM9qP8xI2co1yXSvJrqwVGi3pZXXSiN6N46MwLKRzssTIsdrw7imVAr5LOq3J+z5rzmdtLTF2rE/gJBLvguCNSdkoDllS5124sKC81GPeQPSeQ7DtU3izHg7xHgkuHCjlQThySVnAlOrrtad86JpOZsaA4bm8h3XR7txj2MdgXAXTGtrgXumuJoh5locrIN6xDTPvIvHOk5j4HWclSbt5VOs+Rca6GydArwjMpSrbd5dbCDb3gEg8xZuMNeRd6dKqR6hGUV0zsd6pIi1UA5GX48p/NAqYw2aKNOaQGrTtXpgLCof8311uZ8gjnevHc9qPDInp4XLXZdr6nJh0nB5TRT+e10soTfa8pBRG7rZPWuragnZrGOST63MgCAjOVFp56lgG7HwTHlkakCWjH5nh3D0n91U8voenp3ruA6XJkUtU0Zzn9bwb45tP7/Tpw5OUT8V9qWuep+bZYhAib0aewSBgTa6wL9ai35EB8gxypTdCTfQNIRYvWe+IuV2gh/FWjqzbNofB4WE2DENHb1y2Xee1KxGWTvlB8l7wXukTi0/5c9f7+1XbMem73n0RIVo84neXWzgdPMfPnP3D2fDE4VC09n/4mu8gR5iPh1fXbdZ0uUdvFZrHSS18TtLwUVLd3yOQHt6FLKYc9Ivbgw6dOT1nbtKAcFYE0PNzvEEZ9HLfZmlul+X54OwcfToN5a17DrkRjqp3oUcz1j28AyJZSnqRZOv7f9/n7q4pLlTD0PacPVA+xrG3S+g+ND4KwyJJ3QKm6omd8cNWMoogxqtGwUrS+/u1xdCsNfSUWrUElipCMlXv47af9wlgtMBodI5zhYUCRli6kmUgYN7fr+FReUkiRoJ0EtDDohew8n6cZZCUVZLESs298hHzjKxnvlctTyxSEjO3Y9KSj7iQqfN+9bItNfvtsCYZ7N5cjBi5N6FyeBCDqysJK+2MgCE9XOMdVJ+rF+GlTvSx+MbD+2ASLvmRFAmyCDrWkFOJvimSon4dge6JS+eZ9zkmrIu5e0IwP8tSJOPlVDSnVkrJvrsgGWF+h+LfXW5x5kdJus6r1n2OmCfthyP0YVUuaxWEl8vWlXC6kJFOoYLBQzz4Mm/R7XDKh0pqIYITaWsNdZi7h+A83utjDP84UpAGXkJhudLLRmeR+FlaaOxi+Vjv79eAtPcj65Prc1SKlZL0vM2d0UNXROBwb0QHvb+73FpvG8vleKgdLd3LSxiZRx9WY91rlTsoijBKK4JC8jW0CE04mnfS9KEjte6o7JUnibvHiex7Wi9xP9DYJG2bWv8FDG/O6JIbknnfZh3TmUC95D06djK3edq11b3zEEfHK8eZn8O/+R1VHMwJ+cQ5bZUTPdyz7nP83vsS8Qfj5SSsmlNSEYPuDNUjrPd97jrWUqrt86QLqcuc83r2uZsnRuFsYUnnm6nKdhwcRx0C8VVD8D0cVqojgQEJouSIOkguOvNQ0n2b9LisgXhhfO/HGY7bjkmf1mT797ervmp8FIYFoRAWQ5Y/cHIpKQgip6KnCkVORjTe1IbN7xqdqL9gis+BjmBp4lXKCCynIpnwdKtTUkCRhxEBSueEHZvl6DXH12UN1MW9V0nBsKWkqJLJVUiSJe8K3pWbe70w+HNVTMwZxe19QpgXgtznc5SzDNXRBs8N8dJdVxSEF8Y6c54Do3p+w1Fq8m39zONyb3HueQ1rHCPUY9o0AXpY7qeQmddIdGSuKENuUp3zWT0ypRLVHZ4g53vA3xiZ7qVi9DiNcTY8hz1AqEpnzgrrgC4dbtfccmpQmghwGmndtuVUekdrzCPVEthtaiV1znel5R4QGiBcEF0CzduOEGPpWzCPBvZeUrcnkuU3mZHg/QjoE8Fn133SZdki54m5ouRv29m3BfoiV2L0zJy2MBSCZ0oOYfmt50ct9QZijE/eBa0TbmKe9Iyhgi2l1vOF84YOptTCVPDbZw9PL5CanEr0SGANGL7rfpaagl60cO9LxQkdzXnXNLUS0Ut11Nh/D++FkpzPvji0Q+dMpnzmf0GvlLrux7mPhFnwbh+W1j4cZ85pCxkBDfmas1pjQxQijorU0GCQBEfkCH97TxSMZc8dwdjvaKLSyzce3mutl9ilKhd452vVHI64sJazYVYL3XtS/VFlN9V5l2mL0DSfKamF5LOFuEZHp0Pejf4flxbq8IiA1PIBoYN9aTTNzxgn0t9QC+j8y8ZHYVhIzUMkoSi8uMrsbBjxv/f3qz69PutSPVcUNrkDbDyeltTHysZ3RymQGRgIxQiTmAKGiB3S5sBReHP1LnMq4eGBxkjSqhPKfq6ljnM1aGAMhPop7Krin0tk+vJMqQ9R8CwMHaBJh+fxvBguBN0ACUOpWNts867c63Con++Tte6xen8fEKnHJ+/b3JXt3vYGh1Me57HAlE50CMF9hgba3SMkj0rqlPZ2TEE7KDn2KaeiqVYD4C25IPa9Yf+JdY7JwhHjP/ok0kCIjJ7WSnsYDpyTzxFFRCv4+zYHsnHfz3bKjqSsbnhXwwOBznksdc/Yf9bndM+/L9OmW1m69TPc+CoGwbuR6udP7N0V3L3yeND50bdPPg3HVe9v55lTokuy9yRFeFFStLeGXxxy//z2UKuKzntryOSf0hFeOHvpBr13XfTw5mXaIpwEcrquPeLqhhg87jIJmnaUjXDVw+XekoJzOxvCiMhNQql7yeeaqhFNSINQzIe6QoZyvNyD5uD/y7xFxUBKJZDeohSI0H7k2gRqDV5ibSPvuHxmLtD8cZw9KSh3dtTm7FuzdJUcR0la69mDYjlaxBxKOdv5c538Zw9PZzO0VCvfaq4GRt5puPYhTA8jE7YK2VlO1OpEpC3XpQ5H0cmbizCKWiWj93Ti3dHgypV7eokGSYqQBpWKoHHevNGrgLwfzJSOuE2M3weqrh6JHMdHYVgUNTgfBgTalloeQEpn74Pn9RLlgrdtCYI6FXjuCDanMxnoUFMMUtsoDgALzePEr8Hokl7c6zCrKcZ1O8ucApI3YnaIySFWIMyxbTHCYson1IlCdQ8agyJX6Pa53r3hcTJPMoOwqIHfy+m5e6UA8yTss5vgdOiPdWEI3be5q+8GYZGah8HcfS94znZMmo52l8J1XnU/5thr0B2gvP1osW+8v6f1oi1NAcPDsEVJj5ebnmqujtQnm9JojLl4eARlhbClLNFL40BZeB5GhiMY3q7YM6vxuqZ86MGg1HnaO++SnhxOKygGPkf47Iv1ojnvUW6bqyAGuTr21lnw5J9W0ujCeJk37WsOTzxVHmMOHjY5eUTnmRwtXOICNZRUNZaP0u7Ggb4cvSLz/nG5B/oEb2MgPCz3UPaUnAP3l5L06cNTyAnCQxgGn16fA9q9bUvEmnfl7oI8Gu5h8D5UhwY6CiPMurHC13jnhMCY/7k36vjB+SqSLXNLZsZwQF45DSELlqroXVE5csBzMKT4P3M+ve8TJXReweHyHC13rnjP/WjN9kYnLZDc1F8e6Igxc3Ul58jzya/tvg/omP3C0/fQgpf05qndIDxPZ56D9wr61u0xLvj7/PYQIY2oejKDwlFIT2Z2lAxD7DHfw5DE8MZQ90sjSQbH4CjlDIHGnpXecWnOgcnSvTXa8oReZCufp8rNnWcQe3oJJRV96/54nolaaO7LxkdhWGQdkUwTmapT9b6Plu3uCSnelTHQirD+7DKieQu4370mPDYOQaI5SW8QhJeeShAAGcTB1KZQVN/1tF6UVfRwucedAd5BUVKsZyntRjsUtEOmDRps5XAplVAoU+04eZ1bAzHegbe1qkGfu1riKcbNc/VkHKL34YLBmTans5Ni64XR+vcfJUWcHEQB5vYQ1lGtY+K5n98eQkFKrWEW60UobMekx3yPUMCUz7azRz605JanAoP/4Befap72SPakgyECH0WJl0ZHS4QHxsa762m4kefAfQKSXUuvhmCBWLGPJDy6opFauMkTPCOcss21Pn/qlNhtXXTMqd0hM7cKq5xafw03YCdJc91TYE7PNdn2KRQsysFpk7lCYx5C5PPBD8OANkt1CjwcGcK6PmepZ4EccGXG3oJ4TakpuHWbNVmPhi5Mc2Rp6lvueyXGZdojv8vh9bHKoPVyaIib5zoxR6cJDwVyxk+W0+LIJ99lH7bSqibCkD1aqNNh/nNel1g7SgmU65vP74IHJHVGELxEUrQbkJ8sJ7qKcszp0OfPj9HlEvngyCnIK7liztcuv6ngc/mAp8350NDKQ5/sb8h8k9uSoqfDiKx5PpejQ7e1lXODAF2mLQxVd6RALQjbOLL5recHfXK9xc++8fBeR8lBx3M+6QyDlXl4CCKnork0VKyYAed7HTlftbEjTglohK/5TBHYoqUAz4GW5mnX57eH6H+DAY2hNTrbHxofhWFRlCJeifCEmD+vFvVjvT/Dy+lO660lwnE4DvuTjBbx8KndhZHTmenP54jbunXHZkc8a28C3597lNoTIFljptrQ5HG5x3q4VppwAjXTpaQ4xFBGtkfE2iMcsJdQ2lRPXGvyTVKJxmJAi+7lskfsuUOtF0MuKJtz40tSs4TrPEeDiTJV0CP3kiBIKnkipqjmvXx6fY5r0e/brC+2hwipoIAu86ay9i2An24PkWcQUGXJuq/14jgUWDXCJHXKkOzq97UhjnKrGHJlse4vS9moGrpVJTsaUSAoETOtBh2CihyD6+UWe4JgdsW+7lPQNLRDo6x3l1soW/ckyZrvhIyaAYAhCHzMHrsX6PFowksYXzzL0UCGo2ucUwjpvS/fdY+L72D07EfuElBRmqH053YWIJilJD1cbl1oCpTHKxm2Ywq42umbTrRn/s0RvLZMW1yI6LFuQige2tiP1mcE5eM5BdDK2JGX+cY+5JYztVeZ1K6C750mRytdTr2vIdjPrk+nQzO9TI6VZM9NutbeByG/LAT5vPfhsA7VzP1lii6zR5pwhMzlqfORG1I8nxmv+xQIp/MkyfdjpUQYoqXROAr3mFt+mTc6hI+m6XQ2nm4Pyir69OEp0F+p9ay4BvJD58yGsOxH1tN2CccOx2M/sm5uPKoZX9Cf93iBltzoRb54Ir3L5/3Ier9fg+cw3HE6MUSpxnIU23PIRuNuHB+FYSHVctN16WDmpKJPr8+h3ICJafnr8Vs2kttOX3j85jVgAZJUNaUjsnl5XilniaIzAbAUz+EzUz50cUGRaRVc42V5111zJEOFR5JKV0ssNQgUL1BqSXbA61OqVyPvTRDSjAUCpGENxhKZ3Z5DwPv4eSkpkh8dmk2pLwXjeymVuBRIarfSSor4L4SIIgeyBvV5vNy01jCHpNaWuqQOJqWRTSlnuVkx2JHSVPIMvPInavKnvjOne9VbDYMkFW1lCq8Tz4TvEdsG7vb9gCYQFmFEGTpFe2wZPUYPltIQGb9FkP306pjohbLPIRjwUFMqEVJscegqzLM10anzjy6f9Z2X6bxTYZrMo6882nXA3F6/JIsQZoT1cl/ajTJ2T5vKL/ZAmsPLLanxG/d8QHuSQqEQZpvzrmOqBk9OETfHiI8y6tIM0neXW3c/BoKZECGKiPmXUu8sIRxhSuq2t7JwngVNuGFFlRayYFdLJnzaLp3gBlVzY/a+zSq5IYIYoZR3Q7vQ/37kcNzwau/3sw+Id2T8jndf6OneFA8VNRim5JlI6rz40XN3A+K1hk8MN7DYRzekkKc4T94zRLJS1XkN2lv3KfIPcAScVj2vi/8zSklR8p+rQ0tF1vv7mY/j78Ng8LPBIPIqKspZIw8skFrPc2pVLCmdYWR6W5TUEruhfTeiAvkp7Y4gjDMcWkd/QE3g63l4txuyHjFw1O3LxkdhWNDSG2XYoL4GQ0oKxVfv45LUrDbgcixNqV0m5a2+PdGH0AaedSAZOvtfeBkPiiKn0jEKQtONALKJo3kN5VrHWQLqlRySQqF41vrDclqNtE9F+E/5hKSe7xfdzXMhHur7hVF15iUcWsukHSVZjRqPlQHNO+Gu+xTlfAH9pVY3vh854EepIQBxjuqvaMaw4xKtbW83lSJ493KWBiLcntbzenCaQSFcYADO/VvPZxzwcbkH3AdDIHBRTu4luYU/IlHuXZaSIu+H/7tixsvzEmfog32LJFS8jKMZdYQG6CLJfoJu8D6are0VJTjzLmp/g2qEvbvelFNr/X0mZ7YW8CAgnAl0RO5BZxQfcyS5ESokZBaGd90Tb5TkeSkjjyDccgLmPpUCmevwpIcHENb+b5AvWrwHuqGWW+BIxejZY5Tm+VTqcWFZRf1SOpMTvY/MrSJ9yJ+Sz/VQvurrDeQIOjIjDp6DfyibfjDImcFzZjVl7Xy/H2d+yXmpWH/7qJeyg4bBw560e9Lx0iETl2nT57cHqZyILHkmbsQEH9o5bft5I24kTlcRsR/ZSuAbsiRJJadu3TybnB5oASPkfpw8QXIy4ZmcztwrEFmX3SSIuzz9xuP7KL3EUA0Usu7N8/0SSCqOGDTBGnBu/NwD4Sm5c1iet1btFEbP0V8bgMMB0u50NTYlhKd15GjwiGEAD4KKIvdA7kZD31Gm9/frqZ8qbSGzkf8fGh+FYeEtQ4+qSN5dbi8EKh6NE+SUj4gnn8TTLOTVLGd/PsP7SYyel5dGnQzYNtIJIpVmSeKNSM3LmPPRed5kq7sX9/7+SUtAO9q9H8dxZnST/Q+TYGlSq/+43LWohWsmeyfVHE9r84KWyvi8g8vAtjJJ6bzEabySOxKXjDBZN3D9XnIk94TyqHsW4aPEVb9nkuc3n9/pMm2xTsJPt32J+yD8fOgZwD7d6tXjn9RyN0I5MAC9+jGYHIkh34GqgaOcaEhe1siDoNqDZ3r8F2/NLfp1by3k3XBpXVRba15vWEUTK1oS0z6aRkZ49ShnBBb8sh85envQQe9x2aM6AG/J4dEopauGWstfmuN9XqboBhbnyRXleOwMh30dpfAwlSSt2zWuIndjlaz4SJCuaN3N+If25ns+94uGSaBV7NNSjWqGl+B5eR/nhVHHpYCRr2WePw4AZ00oFCeG8KJ7ecg5pwuHuK9p7UIBoHw4KiP/YhjBe4/zPRDHnFqyLv8/v9vKTU8e5hx3baU1f0NR3bYlwj5escAec65eRr9Me9AizxkhdBQ899Awoi/OYJAHOn2c+WKe14GRgmydqhNyqM1rsTkjyz65Pusw9FRqTt5TNaT5nq/fczJY3zTt0tauEZjSEWXyyGOXm14s4Iam84yHJPmZO37F+Mj5MkJQ3iTM8gxVUpTVjugHRh9ndZ3XQFBd/nho/LXxkRgWjViBJgNKVrtH5Kkm9bknCPGHZzAcIgPiZrhHwQbzPoQOwszzBHjGKRQawR42n7DAS4pe+vuRI6vfCWnKh77xcN6mOFeleKgdXBgV5EpMZ0Y0sb13NSaPJc0zEXwptSxgh+xggMvcMpJDoC0tVukQNmfBz8gZkNrNmfwfbxSo0IW9e5HEe/2mVroTwpTvLrdzT6fWOTDOaNqjOySK4jAGk6xjpeUSHKWVndI46ZL7WnFoiZg1e+hVPb7mQCWsCQ/Kx5EPciLw7JxGpnTuG3MgpADK4hAz9IYi5JzdQGefMLgwGnMqerjctFp4zwXzUXKgCJPOJkygCacX32r0r/OqLEenpjDa4K1sAgyRBK2NTfFYG3lDjjDwf6o7xnjvU4X38d6n3EKGGMGEyOZpj9ArUP59n8Izo70zFUMYOQ1Rbe28z87AfedMz/06w0KN5wkXsN9TPrRYPsky7REqGUORnDfoKAoMhQVNcA37bVuiX8dh5aCgM8/rojS3UJB38AzDbjorYX7wi09jrwM+NxTIkQHGWo2tiyXEMn/MA8Ig/n7fP7z5sXrP+RM5sR0n5D8GX45y0jLhMMJnHp7EuHqsN8RG3kFFiXM+whEhB411l4oybMekL+4PrZutXl6e5nwbMiS3yrHoQ2M0sh85ylppAT5PPeJQSmu9j25ijRhzGGGSwjHljqlSaegMufb5Sfdtjn4sJPt/aHx5aqeklNJvSCn9yZTS77Gf/W9TSr8vpfS7U0r/TErpO+vPf1pK6Sml9Lvqn//TVz1fOhtkEUOjT3woL2MUugyyicBRDnWNBonqs8dkkzFRyA+QQ/AKFAhsbLWKJ3EiJ2sk1IG2wHyXeYtLXWBUtywXg6HdkoS4t2PqPMijNAZEIQDF8x2vgXZDIeC1QSiDzLC++3YKVy9Zg3D5nCtiSg4lRaWJn42kqkjbDXp7yWcVSBUijxW5YR/wpP2qbtb6dD9RmC9uDy2eW9Ec4GQEiKTIU1n3luVMeGPbp1bjn0r3Hi/twxN1j8oNBuL17vU12L+vDuCc+T1e+PN6CS8qpVI9q76kDDgapYwBihcDqgZCguHFFdLk6HjSJfRBhYV3Z4U/ebeHFbjDhNwflCsKlfK50TtiIACB9z3hGMVBTwSeiVzgT6p0QiXDIy2pTUk+LPdo4IRy8SvH4X2+F9VB+ejm7+FABO7Dcg8YnDljFHp4zWUX8qnxbI9MuOfucu21ddOe+ZQ9RyQyIrMYhOFyOjtvsq84AMzNDW8Qox/84tNWoTG3pmTMKRl9Q3/8jnACxp1D6YS+nGeksxeJG2AjIgskj37w1gPsn8sN74IMX3DtAWfv6DNneVtbfod0GjWUPTP/edr1jcf3Ub2Gc/buctN1XkNvMKZce3Ic+YV+4t3ztHdOHvOfKyKUcwsTMq9Uz9Ud50B9qtH2dL8E/1ymLQzkKR+Rq3eUpG8+vYtnoy/hBTpBf2h8pWEh6TdK+sXDz/5FST+nlPJzJf0BSX+H/e4PlVJ+Xv3zq77G8yO2+XC5B9y/THsX73HCmk35UWL5GqyDV/hJLZ2BmA77LHkXWMqucPkZVtzzuuhbt8fOCqQLIgxMTw48W49xOWFxUJIqobd8A/eI+bfDw4cRfszBhDE/A3JnuOXrsUD2weE91sBFQDAjXo4bVhAxyAdzQ4BwZwVzWGx9kvQdj+/Pfaj15BiMGHj3WmqJcUU81NeKYuPmU/ofMEbl9sXtQV/cHsJodMPQlQkGVOQSlNZ1FCMDQ2mvQsL3wZ/lnqYLMWjZ4U7GMp13H7SE3alL/mIf/DZPBt4J7+fPYw0dwksufBz1AUZmfxBy0LV0Jo0ewLUW20fJQcMIadYw5g+wB973xOcGshFwtFpFiKRoOgd/UoO/Gc97l1f22mnRcxEiX6YKX+cL985BPCTFGaAAeBe8Dq3xXZQsihF681DuyLdueECXfk3AlFq3YmQe9JTTYCDVfYF+4QcMsU8fnk7vtu4tyCDDjQfmX8rZKdhpij+fBGqSYn7IFWTsA4aMhZ9d5nn3xzCcpna1++fPj8ETkTdUjVvmSd6EG8DcnlxKCuQDA+Hhco/5sJcnYtc7q996ftRRznJ56MQdQkdjOF/0E/NxnhiNDfQO877MZz6OG3OU0zPPOe9Bv95lmZDHQ3V2w8mpiCnO4w8+faJSUvR6YY4+19fGV4ZCSim/PaX004af/T/tv/+qpL/pq57zZeMo+eywls523TDWw3IP6xphzIYvlWiwUsMjSOVF22KEYqlW+HFkZUu+cgV7zqfPYj9/mIPwEbocEN99qh00k20+n+NZELgbD1RFUFI72UVJ5AcQJpnyEe2Csfm3fdLtOBUaCV1csX2dV63V84imUlJnyTM3GgJtR7vyd9yHMQHOkRDW7MqSvAJi/TCLNwq6H+f5wwBh7JWsKddYbcnR+/6xMnV0kywpchhgAGKR5CyQ4d1ag296Zx5jxCdzy6kAOj2VZg0jVWTJvYpxjLFPqSW1gjQcJsBRKJwPMCX7ihfihihJZm588x5i71/cHuLsvKGT94QYw4YIPX4PffO5YgJl2ydllfCcSOZ0RC+8a8I7Sh1/HSUFb7Ef0NpZvrtoya318DLten+7as3tkrWprnGt84mwkhlBPL9df30q4KTWD2auZ1tMzsy5JrAta4RD4qZii6GHcX30JZGsA352p8VzBzhHxR62UCw/bwZC6dBBaIM55FSigyi0UVLRrv4G3zGPClpBGZP3s8xbVC99en0OAwfjlrNhwBOeyH3sLbcINPKYmjdMOWhXoWDOmSNh8cxy5rixn34GGAIuJ0A4QBA8jBT8XmkEPuY8WdMZIjhlYyjbAcXJ6azAgk50tIRU0CDnDddjjla5o0wr/LgAEPlS6YwwWuyFWtgY2vI1MFaj35xKIJO0qQcJzba+UlJ/keAr49uRY/HfkfRb7P8/PaX0b0j6pqS/q5Tyr7z2pZTS90j6Hkn68Zczm38/cneBTNzkCPGb1+Ue/AMlgUZcND+S+lsniYk6Ibq1J/WwaFiHdodEUvPumDfJMFKL4VEZAqwotQufeNZ7672QUokD5fne0tiTodzISql0F47RaIrQy+X6HBd0kQXOOhFENM7i55T7kgzHfInjeviIPWAvETj7kbWuiw6l6AiKCPMkR+LHNJ3C4HqY78F4pSR9dn3qehlIFvvLZxdHjCs8Nd8zD8tgsMLwHhdeKqxcUmvXTIla11eiKiL3YNkD7lVxo5LLyUbk4gzxNbrGe3FY1te5HzluxaXLoN98el3WuIDLaRq6TtYcCq8dRVhKCsOtlKT70YuIo6SuGiE8PhNOJFGuR1apgrnkpgwCBZxboq/T2Gq5IhhPfuYk7h1V8KGMkBte+YVBhELls/sxh9G0VBOdcvLZ+HM7msfv8fGTbvpcL5QQ+/2icV+tMlumLcqAXZ5xhXe0xrZcm22fVIinV4PZO3/Oc7uZ9ygp9igQheNs843DMDYPc14mtALcH6GGskQHyodl7XjVoXfOgWfyezeeHO04m8e1XCyptbSG/qO6RHqR0A3POQ1LdodTfR9lyeRBgGSdtNjKQSWZsbnH/jsPRJv442XvkZyKjhqa8QoPEugf7Qz2I+ub93cdUun0Ah8gp1138Ww6K6Nbwkmo5dWe7+MXUEIDVCGiUzkH5NsXt4dA/THWQbE+NH5EhkVK6e+UtEn6v9Qf/TFJP6WU8qdTSj9f0j+bUvrZpZRvjt8tpfw6Sb9Okn7mp99V8AKz+pIXry0f4eKn+6Urf0qpdZnLVRkAhyEkHGIcvU08lHkGimylXLfSEtv8uy5U+f3odUH0eFh+yRr10HfNHUSLIuE933p+DGvfURoXao5ISE0gbGWqxHCNRlNSf0U8AgEldhJXrxxRCl71MM2tZwKWNGV387SrVEJdptc9ewQQTMPtlCTQ+Wc8hgr8jjAl8Y/qBZKgiBMDS5Zy9h6JJMBaeeHnM14JjHfm1xx7yEC5NatyQci5HKUlhzksjQL13iFuqCHAHqyJzWJCEQP2LDFsZ0mnVwxTqXWw9QZHl+Wud5ea/Gw0h1HCfFn3iHYhZNxgk1oSKe8ewx6h/FIP/XpoyM+dM6BCZqre4LnXOZRgFzasfTBOYbprqtVB3u4efkHAutJ7qF0mOUv27URFFGeE4sypxN1ArO0SfFTRk7peKjX4rs+bvh0nf/aoj+8ZCetz3pUW4PHmfBxHjl4eks5GV6WhJJRGIvOm1LxbSXFHEcYZcphya5d3fnbsoSM0bkhHz5sBKXNHYeS9hkg3GcTzPFy15xyhIWgUZegJ7CSKszaSEVkvVx2gT764PXS5DNdllQi/5tYO3VGqnIo+e3gK+cTez/NZvgt/7tUgINwsNaPKnyX11SiB0CF3U1+s4PqOecY9LEdrC8/1FPxRla3eQA06QY958cGHxg/bsEgp/XJJv0TSLyqllPOgy03Srf77X08p/SFJP0PS937V83zRHudzKAsiZrP4OYcS5Ymlls2AHFifhJzOXvoeznAjZLzW3AWCe5Ewk8cw+TzDe1Z4YxnuuzgF2BrxYDyBZdr0refHUJjknpSq9BBw4SHW/681rgfa4B0cp3xEf4T3t2vf9c1haal7rucWcOW61EIirNnvwQghVNoFapLCoy7ljJlnm8MaguZkMowINyrZs0s1IJgH8zs7xl3iZtN1bxn+uSplmQEntSY/GEzEIV2octZPa6u8wQg7aT1p0/RCKI7hEGD/UzFeImS1cGHU0fKJWKfPFRqk5JLKDL8B9ChJn16fW6WIVbSgnIFqUcZeXYGHBt1eaw8HeO++zVKli2SCbz9yoFENGbF6+qpAgbgdTj3KeXHUceS4Z2crUyi8vbRcF0JZeFgI1xHVoGU7N58Sg3eDHC+WpkruDT5bIi+eMvzJuFWlVA7yFnqjG5nFc3m/KwhCACBD5GE8mDfMd/EgXYmlVFSOpFxDfqCkUz6Rj7jkbOjqSW8CLuNz9ALkM5pv1ToemkXBr4Td6JBbTB64Ack+QpP8LG4+nhqvsV7nHaoU7pVHQNkctX2/XmM/SOrmVuWjpGb4Hy3/xg2bW6UROk6yFuiAsnwSvNdt1qEUDRzRRcyf9SBLvBsql2zCX3zHjQY3tPznHrKkK+1RWndoN3b8s6Ci0DnvHKujcjpR8/s2V7pPNcH3HufoqNCHxg/LsEgp/WJJ/zNJ/8VSynv7+Y+V9AOllD2l9BdJ+m5J/+5XPk+t/hfIeFRsrgAhFnrzI+RJ6uOeg5yKlFr5mw+In9ghsBYQL8pP6pUI3su53gb9HeXsxgdTQLjAsFM+oje8G02tyuQSeQgYTVj9xANdiOK1YUyRc4FHn1O73jYbsuFQr9QSDCFEoOQxN6QJtXZRUOS+qHkPHlc9z+2Iq4aDMTBo8OZILpqsMdPUvAq6h7JWh6Ql6fPbgx6Xuz5/fowQWk4lSsZKSdETIqXWOwDPxlEZjD0/Q0dkwtCSotOgexb0dNiPHJ6tP/soZzmtw+3edEd6WUYKjPqwrGeeiZVgujGCYCTMRJdKD6W4kYL3l+emUM/kwUZfpbTQh3uceDdjPkFDu871e+5EKWd4xL115p5TkYy3pmr4cDZHOXsteKOlKR+adWboP1pvE9a71IZAhA4wyKA1ku0CXSt9aax0Kll6p/iez/XW0+gQWloipucEkCdBLkhOrf07yZXQGQgTP3d+RTGqNN5oPXbOfhWEjZJKGA14/N6Pgf1FpgL1eykojf1I+JynPUIjhJ9dpvBMRy7pBVNK0mQQOwPnZmw0BS+N+RUkaXIuvIcwEv/2UOxu7zr7wexxK67TIPkoGHQpFW3VSGP97lhczRmQTvQXFAhep3GX5068u9z0ea1ic7TD949nuly6b/NJ+kaD96PJ6P3IcdGa80Gj4xZW4Z1ccQDtEvZlrk/rJQxMPwfO/cvG1yk3/c2Sfoekn5lS+v6U0q+U9A9J+kzSvziUlf6Vkn53SunflPRPSfpVpZQf+Kp3FPWWEMruOrf+/WM4pJRUuws2b5aujMu0t4ZHZqFJDWYKizC1MiOYjsxshCFMj4BbTAG4IGOEZ5SOOECEh1uSkkLpHiVF6RMxaDw/6tG3Y9KnD08dQQPxMW++LzXokRa11CqPBC21GnPm5oxXqtGGkIKB8RhjLXurkGgNilrJnQuHEU5Dkfo7Wf+lXmmNt+TlcFLr9YEhd1sXJRV98+nd2eOD71liJp+X+v4eIyLBzy7T1u2JGx3eKAnDxw3ZiPma0mJtMLXvK++PfICSY43QHbkyKJf9yHp/u0YCLuGROL/btTMUgct5HvkAGOh4zVM+Okj+PNOXhjqDc+ZZfPZUmlt4n2HU2F4y+Bl7zc/gFb6PTCCPiUZiq50HXvdRWiUU3jPZ87SCd4MHHpvyUAVzP8MjRefevr9f4/6f1ebm73bjyB0HN8agBfjC4/p7haY9qTAbrXOpWNCeWhUN5beEXFzOOs1H6Sy3Cu9nvhPGhKNQtCTHUAW9wFjx+5b4+3ldYp+8ii0a9Zl8YC5eMcLfoEeXaQunzGkB2Yacpcz/vs3B9557d9/mKNV1NJz8BPhmDJuzDs70vs1RoQiP4Bx6aTuGjxsEOAVu9HmTKvgE3cXn2MeHmpjvRn0kkRr9+R5B01TLIeO8Ks6d6Pj83svOD42vUxXyy1758a//wGd/q6Tf+lXPHEdSf2Oh6uHc99YmWWqKMyC6GkPyio8pH1oN2dj2Kaw8GDFg0dJ3dWNwOKUSpt+Yd3a56zfeIWusW0kqqd1eOeddj5d7GA+n4VHisi2SelL1wCCS+3rRZ9ensIa/qE3CaHMrVUFcuzdO+eiqYo6SwhqP9rZmLO1H7sIKqdbAo0xyOqtsXMAr9UmcHutEMY5x65z6a5E9uQsFivKm1NQtY2K+J52laOGOZ3XWsbdmPtAO5zZPrdKjQb4tARHUhD1DsDGA5cdOjZw11QLE7td9ihi71ASorx0hI51Nb9bDYupT39wGWvc9g478voj7foY7vLEbPU0YzOXd9abLvOpuHfV4pit/SZ1y9f/vxkO5GtN48GEsheJohgzrcIchpxZ6ktSqhOzukRDmFYK/1Q6uGB54n9AgyvCkp1MBss8gZ6CUp4I510dyIhVZ8AfhTQw6EAU3Nqe6DmBz6N+N0pyOCNMRomLv/TvsF6EkqpySSiQHYhCAUjlKISlK5cP71JkHBZ27QT4ZwvholWF07KSCwUPRfCY8bgu7NHkwd6XqyA9HrfzzUkOmoUH4gH3i545E7mr5LMgvEnChxRFho0EfIfOsFuqlDTYOgM+RMLU7I0qUbJbO2WD+bqSPjRJTaa3+/Xp1UG93YMOhSe169JTO0LmvLxkNSacjnXKR1CoRCb+R2MnZk4uiKmP2qTU/c9n42vgoOm+qQndSg5YRHLkKDSdAv4/AvUYY3a1yvw8DT9KRD4d+HJV4jdBdCMqYw2OHeAVAoIQAQBbeXW5dR0SqYHiu52xghZ5dOZvF/P5+beGQ+yUQAuJghE3OrT3nuNv8pOb1UD7JvoyZ8RgI7EdYs0bg/H3Y3vL5Ed7nGbTw5kI5+k48aO0+T/xyzud1vu8uN+1qiZxRATJtWt6dn6Ek9Z6rsK1ly/O0n3elZLvDoNJclKFWwcn7EYS8z0MB7mF2deiD53SxWC9CKqcz14f7Fg4TXIzZaMtDg3hBt52s89alcsqHfujpnT57eNJlXvX58+MLbwVP6ul+ieQtyiofllU3yw0AcXPUBbieTHRKcldDpmR74YaKe8keBtmqoqcyYi/tFlKfO4rbk+dGiD2EaG5hDwwXhCLCndJeKqio/snpvNyuKEXHXIQ9NE4c3/eGqg5Cuo6CrXu7qwclj1cdYRj1w9G/k076RllLTVx1yDxCGql0uVBRml1RQ5wxL0XPqZY2q3U3lVouUyRQ75NW29uQDanlqy3THpfQ0bDLnUJHOx3J9VyP5k03Y7xzQtUM4ZJ6BxEDZsz5YZRK9yW1HJSOdo/TgPOwFpUjVLlBBz5okkWPF8JTuxqS4GuZ8hH5DCC3rIs5ufzPqeU3wVcYjvDqUVJc5wCvgn6W43TEQI0irK0UzhFGXEPaWpmpt67/0PhIDIsU3rRb/hAFPyfJy3ssTPmIW0KTSndJCkIfAZTTWcXgsO9RlfpYmsq/HcbnIDQprkb20IiXYRKPoxwuGKI2cHLCckgeT9zjgEdJXU99F8qEfKSTWb3EzZUfTO1tn4EXWTvVKg5XI4A854C5YqhRG+49CmBESS0j2lCBqPwpfbe9z28P+vT63C5hq4KaLGU8VKojSCwEvcAr+ubTuy50ISk6u4YnWJoVzz0phI+KreM0wFr2NDkaoFPQFj+TWljGPTSe5QLVYfAW+pq6n+1HDqibZ+2lCSyv+JjzHmETT/JzOBnE5DJvUQEC3LoaPxzlJV+yPgT7aAyxB/75MMiOFsZ0rwoPO/I2UlPmIDKeUI1BTJXPnHftas2/4AXQk11NQeN50jUSXoSfI0zXGZt7GDlRoorhDUq6nXfMbKXFy8PgqKia9ypJVZB3RpHJntE44ju+XzRPg5ccNdJkRslxtot2Y5d1eG+C2eZ3tpC3fBFxCeRFnz08R/6Gh5pdVjuKtRu6QRkt5bY+OBNUKHvvzh+yh/mWkqIibEmH7lvrpIkMDF1ie4hhfpRUjaeGFoTsqzTG81z+0QUaesbI5F1ztpt0jQe8Og4n5tyjxhusmT1IyY0PhXw5So7KPnjNc9y4BXqZdskcvOCh3PJn9iNrkiK/DGSMz7aS/lMHv8b3Pj4OwyK10pnn9RLKAWLsYrCWNOSDGNdlMiia0j61jPijtOQ8DgLCdej2hL7LeXOh+vKd2RRPSkX3o5XFhpKpUPotLeFFkLxJPC0QkCrwL3O79pcKjikfull83CHkazUUUAgQbkqtJAgCAvmYcmtW5DHbOe/Rv4B3uBCc6nxJWEQRoYzxZGg+QxdNhBjwPHPCSyWGCNJzTWucuTMhAmIKxdwa3qwVdv70+hxzJjEsSkWnPbyz/cidYgERAjaV+koXPFX2iiuuo8rhyK1pGcLLBKGjZK7M2BeHFR3uZ90YfhgKR90fqns4r620ypWTJuYQCieitQa07AbXlI9WAl1/5ldJJ3sGwz2oYmfD8zzuLfV5GS6UPAwZHS5LjrJxsvIdjcSYCuNZLTTpjYbCsN5nfWpt0T0EhREFzR1qSimZjDjqczjjzQwrLwv3uHiE1I7+Aio+87y125Md9XCHIxvdEK4hoTAQXKtuc/StKZumIBmv3Z7s533SZvs88vSzh+cwGKBTQi28U4PCgn4w1Hdl7XuTBe7MSepkshsEnA9/B/r3imFOJV85+rJXDBLOBHqj/JNbU/k5BQLsC7oFxIk2AZyP0xbyEVnjfTyoYDvfUx3f6ewY7Otyp6X12emNrSn3N1pHhd7c310DAkQ40M98DGdyOZ2fvTu2XzU+DsNCrSkL2dbulUes3xZ2xkZbPBavlUMcmdXhYFdcbnVKfTOtgCdT6YQxqAC/mypU/9oc+bcrO0nBgBB0tCamM2gq8f9Prs8RB0a4T/MW8XQSk+LAS197zzujH4FeljJ5zN6HxzJhUGcUqTF4Ke1inz623hCDlFr3xqOct2Nel1b6dqne6VwrEb64PXRJunO9hdEToM49aQoWFGrDoDmaIRBxwzo4r6yziZCjPUv1EmBiaA564imcuxu8o6AeB2iNeycYqwx/Fq3OS0URjpK6Gx75HpfS+fookUSweNiGfBqMzWvtxYBx70iBC1TCZ1FZU+dLVYyMd3x9J6zaQhEgO46Y+OAzIC7nZ0/6ix4l+Wx45b0R7tXo9BwYN4bcAAjDu37Hz8tDfdC05xZ4S29CAawpc85qcLYbCi6g4UWvxuK7Ugu1se9HaQ2fPI5+sfW2EMzc0SZzpWx7T+2a+fGMkTkd0mRKzW9KxVvH2IHfr9PWhXs5I+bhexQKbqBrldTKnOveIt8eqnFHdRCJzTg6UusJEjKi9KgHYRRHl3MqcTsyFWvQjYdWkBkuayjtJG8Mo4P50++EPjXIJW+e5TSQU4lk63s9B4xSkOFbrQiDj1gnsg068/VLTS6zx1M6nZaHyz2M5zGnYgz/jOOjMCxIxvNeFQH35SPKEp0oQ2nKIMWtNadxwo08A/s+3xs3CKZyhGI/zjLUi1plgEOVEMVZmmUMbcT0sKwRqslTS3rEOqaEkI5v1IeTkOe5I57wmdMRAnQ/cghHNyhYL4LCvaejtN4KDAwCkomkPpPaE/nCi3TovgydGC0sxTNgRG8gVsp5XbrnZXRCuyq6/Thjn1MVtIQnaAHvcV8MDeD0p/USrXaJf0IrJPO6AVpsLTyP4dCy1DetcXgaQTXlMx8B5Y6iD5rM9R4cncpzfM+cd71frx3SQI4Eex8oVGphC49Vs767zQn6O5X3+d77PmsqvSfLZz0p0dcOkuJhM+bFZ6bU0LRLfV5JrXMs+TTkCS3VKEpcjGbKjXeRVOjr9TDLaZzfYg9AYzC6MDocuSTmTUjIkcLgqXoOtOn3G0h5DjcAu6PBZ+C1KbeE6wiTlpY/wvscAQJpAzEY+xOApIQjgjwoKVC8z2siODC+NxoDXcT5ikTtuhYMD5I5r/PaOWRepYChG86OGe/cEO1GL/szGqDuLIaM3qdIsm37ZUnCagnQKZUwvDlLcmpAyAMZtb2/VtntiaNPhj47L3BGrldGZ4bwBkYhRjXGIO/fTJYwL/YGw9rDkfAQshJavy6rVM7ux994eB8I35iYjf64HUs4e46yuCH1eb0u4EPjozAsuA1Saglr+5GDCDish3rzpbdRxmtno1yguwfoFiYW4BhegPlHAaJUdFF/CyItvMPiLjnuKXBhIHsWcPpoLQaMqfZdNwKkHnUJZVA9Fub0vM0d7MeeOKG5F+nQdbQSNsZAsZNM55D+uaAenTnUPKVJrYR0VumMkaOkuILYz40yt9u6RJMfnuHI1LZPNedi032t75vajZzO4L7XXk57HHa3gynDQ+oEnjMVf/s6mBOjpJZoHHRlwtLPMkIM5pUfJUm5DydMdV/3nEN48F4SgR3BWfdJuRqb920ODxPvc0RQPKwXc1BLHpa8g+EUn/MQDTfzTvMWYbMyojaldUpFYU/1TgwqDTqlbCGjnM4qiIflHsqShF9Ci8yLkE8pZ0LpZw/PMYfu3cZP+5E7fnq/XuPSLXjUPxtNrKSAyvH2nV78346Cet+MkBVGY2GEQMuyBGq1pGrOzs/jtXwEHBanvWj5X0NQXM7FfI5yJvM9Lnfd9iU+85jvHZL17nKLK+ZV9yMbD7iD4MbtKYNae3nm7siHrydCVSarJHUVDHtpe7Wb07ITdiTUWdvO7yVrTiTHno6ho2cYnjTAO/VQy2tj/ynTDd7IPR10jltFpkaDJs7raAnfGMbLtHehwlKS9mTomOkdl9Pu/ExmzDBosocTvJcc/X884Xzsx3GZ/hzIscCCooEMjT4cMSAuNllCkUNbWOced/J/Q8wo1f3I4an7oYMquIAdFXJOhy5T+xyJY0D8Lkgu06an4xLzRTHyXgSCJ2RhWe9Hu5ytvf8kFMqKIHRgYt7rijgZY5bUyj4pjeQMgC8Xs/6x+kcjjeHKekSKziStlgfiwyFnPD1q5q+11I+fk0T1+f16lgRmax5luS1+t4HUktemfAqiKR1VOa1dtYV3pwxP8ugbznB+7qm6MvBM7lL6rpKebzFVqNHhcPeUuVsjPptbdZP3L2E/8fb4XSmtvl6lhas6I9qUNol7neA4GlwMD4yGlSN387RrKj0f8dlOsBmKFoZ1Mcdh7u+SOPm2KXSqnthvR7bwkp8NDt6P8zroh6UpQr4X+21n8/5+bSXt9TO0xeasPL/A55rsZ/7MlI8IE0mK8lxHusawCPvLGQevlL7N9z7IL5+HV3PBP8DinvuwH1ll6mUdhhO84+3SmS8ohiuw0QnBy3ZDyUONjiiEc5Vai2qnO0bkbxWq2vrWA5IiKdMdRC/HfLjcu1JLeOg6H4ECMFfv4xDG9ZEbAl0R6nfTLZQ7+SR0u5T0wjj1yh3nB6dv9uwyby1hfNjboCU1nedGAYgI9AQNcAaEdzj7sjdagNYjhFwTxp/XpTMGXxsfhWEhtaxnPF2HoiDobZ+06WQQWmSPcdNcn0F5D9bvXK1Ykoyk0/JPVXiMiZmep+HKBoNnhP35rFvhJCx6opjXZJML4MgECgLhVYyAgL3JSCar/761y7+o/HAjgFjvUS3pNTVvJxnBuuB0gwRFOULcDu8iKMlNyKmVupWSWtJVaeWI7DcGgAtYfwfoDR6WMynnRQ26138/WrtmSRFein0ZBPfo+YH2+P/ZDw/bOcrlYSEXUG6cuMccyis1geAleUlFKZcW+503XfJu9NKqgEaEyssqPeYOxOmKP4SU0fPz2lp5u/LirL2bKnwGrbHHKAANRofzrIe73ADZj6y11Jtc09oZ+x2ilo8XMWDezzxHgcseg3RB/7R2z/nQXQ2aLkcOI8FzKQgNxKViJq8coXAonLm5sephhNE45Zyd/+A55TPU5zlgJJbyea9uAS18d72FM+ahMoyGnEqcP3F/zie6UdY99BpZRxLgLxBB6MFlnCt/QkfMwY1h72/iihC+Qj4yz2ngiVT5dDFDu0Nyq5IlD85DvdLZsyJCXeaMuI7YSwtPbEdL6A/dlltlDt9BFoyo7EjD+4tC5BaOc2TQQ3eMyIVDl6XWh4hzBw1CnoIOTvmIPk6jAfNl46MxLNybgWif79doUCIpauL3IwcUTmjEKz0kS8pDYai/bTBCDkdWnvoSSubDOEq7kVFq+QbuMS35iAzgPDcjwa1eLFX3WDhILj3yBkvE8c457i8SLFFKJzKyd8pDavFRrPJTcTSGTlX5e+VNlCuZsTPlvrYawyCllquCgvCWwCmVrg2tZ96TqOtXvdNOt5RWN+0QaqrCAyFDTwJCKKMBSEtih175PIqBa4NP72eLcBXfA3kheVJSd4EQcPtrsDZXOjP/Sa1FNOfqsKkbmOF9Vfg6EqxUIevafwSBFe9VE4ZHSZHHwNmRYQ/Mm40e53kNI8YFIev3rHromv9zL8J1WTtv3vlwVLRuxEILQe9qfWeyyotnTdOZQY9SZk2upNmXru+NinJqP4Mf3DsECh8ToF1hunE7rjX48zghZi8BZA7QGT/z4ajqGJ6SmoHrPVUc4aAE0aFsmdLKkbfS3y3Bu8nPQYHggT9e7nE+ksKAH0e3b2ooBAYDdH9I4UjyM1fC4agNirZUBb5Kga4yn9damLusdxQBlKtVrdXk4nXRu+vZjZWyZ4zzaEhW8/l8HKUlVruj9LReIgeI9ROKJQROmwHni5HmOLMRvWC4MZTc0XmFlpB/PDOnM0fKHQl0BzIKdNedgQ+Nr2zp/WdrAMtCfPd9jjsuEBrumYTVp1Yr7nd6SI0BU7W+ue3QvR6eJTUv1gV0WLTV2vUMX3/P57eH8IicGEAScjpjmTBpePdTax+ejPk86coFiFvTfsAIAl8Ha8BifX+7drA3e+vlS8wdL0FqV5zn4TP3bQ5jB2JnXpwLBDq+577P0eUNtAFIn1AQQsRzaHgm1TP+Lj9L9mvdWzXAg1Xl0AMjEKaj3RPD96Ax+oMEuqD0gmYc7sVAfb5f9LSef9hrBNPSKYLew8eD9sxwP1Pmz3zce3QhHIJAZ34S902EkLLcpjDm1Asq1u97SudJ/i+pSyD2RF1HtNwbn/LR0aFD2fAczySx1BMC8aZ93Z4/giMQ9FnpC1nQBGyD5fmbOxS8RHakLRfKHiYo1QlhD5iTn8vY9h3+YM08h785M+iMZ50K8aQnLvLyvfDwg8959NZPx2bt5JL30IFux2Zu0A9yAdplbUfpO8YiQ5CnGBReyReos90W7Psf+5FbW2pCuE7L5Ku5vjjP/hIJjvCxG25TPgLVAHV+Tb50aJz65ovsEesm94K9WqY9dAnzIGF/lCtjWJR98ZAIZ4vu4DvsNWfjusavIdj2KXQDxgT7iBEN+hxVK9uXYxIfjWHhROhWE0pNOr1IqTGvMyjeG8RNKMEZiCu1szExwgpmdNjXrWs3OKQ+t0BSdKqLJi9HjrmXkqKLnzPrOZfmVbnn6UrFD5v9waNnPRgf3NXBsyEsh/Td+HJmcMZ2VMR/R1IR/05Vefkto27guZfpqMe2n/eKRLlXaaV/UkN3UipR2y2166I5g+aF9sLbveNtn/Sw3ONzUUkyQHrskxtPft5SS6pljB6G7+VSE1KhO94htVssuV8Azy7Wn1r5mu+HrzPZOXn/DdYVnnY1XID7+QNa5UId1MsN1aBxM5IZbvD5Xrni9SRQBHyH7kjGD31YwEMjvG/kRd+j6MRaeZ+8DJTiF7eHjscptXX0yJ/tCuc4WjIi7+Q+FZoXuVzxdSLYfQ+8HHarSNat8i/f7d5feWQ1/oqwrBrfgSR61RFGqIcjcQbccXP64/NhMB/tTonzaoO+4sJpgjWTXPxUr6BnQBOcuzsdNNJi/9k7R35Qku5Y8e4pH0HrLuNZK+vj/x6qvlU6CUfCnFvkDaXYnA+OgBvNbZ1N5zi9ejjE8+P4G/nAPnLmdKT1KwIYoScNcQDl5Z3+eWjMjWlH4+aBhjmP7Wjn86HxURgWZPFS+uRKBoH9UK/3RUGSeexCzAWQH4xbs1Jfww7zeQKcIxoQjgsIqSnKmKcJbBjFCda9SmfW27Z0go25R/ysEs+jJa6diEaDOV34uAA/TIGO3hDPHQ0AGMmZynsLjPAfBOw/PwoNxpriPgaGmwchixeEosIzXgbBMa73+X5pjb9yy8VxxAbjhe6JKCwPXzgDsV4PjfE+N0Q8XIBH5h4G5+xn4rSEckcQOlqBl4Qw491egicp7kFo8HgrYz3/v3fn7eiKK1FoGSXj3pDvN3MavWiElu8R63TFMyKCbvDGvqpVb7hz4CEHbzvse4ui5Wd4ffQAeHe5dWe47VMX5rrvcyROM1eUzNgoCeTkvs1RgutwM3InztX4yvmMuUKrGMPuwSb1Tfym3FqznwqmdXrMqeXksAb2pnMq1LelR6bldIZIQXilM2mS67TPEGOjYe/rw0A2ecv4B0vGdo/fjcqYmxkQi1UgjJ9xFNMNFc6W30HrgWC8clkgIU6pySd3FPfj7KgMzTkCQ9mt74Gk6KzJPMaB4ezGD+frsg8eZr5eBcazyQHhvC+GvEitzwUyxR1SzoM+Uh36Y3t6W+tt4HO7e+i18dHkWKzbHPkUDkuOMKJvxLpPel4v3V3x4amZ13nC3Q1WguH9uWX8/GD1IQg4DIQfXUMhLgTbXpU/zx77MzgyAKMeJb1q6Y1NgzzGuh9Zl3rz5+NyV54MGVBRKVn3fYrbLsdmOe59cdGRC0f2FaZlbeyHKxRJ1oyptWl2AcCY8tG1GR7DT3PelZfSZf87ZMt++XXWEUay8r9gkqwX5xvrV2MiBgLCM+iJU6PoHGpmHUdJkezkqAnPP8qZD0MX1kOKsjjmg4Jhn0A03CjhbH2eT/eL0uWkq4fl3qEYY9dTknbdGGfv3XhOqURVC+8cUYdLTRh2+nWDcoTij9L6ISAES+kbT7mHSXI1MkE6Bb7nVZWSuqZYDhHvR9Zay+xiv2gWZ3ImZM/cG1K7Kd5Mwtu0tw6HNpzOx8oOHyNShqxhpFS6+3i4XMvRKDe2vUNpGHJmgEbflJpP4N2O3YETBsG0azEjn7CBVxucfNXOkLOlFPEoqSulDg98yM3w3zGgpUNSUg/RM+fufFDeNVTpBts8r/EOR7WPcvbq4Rzve7tvClrwTsY0cWRgVEFXGC84Y8geR5sxmHFIg35Tf7EjnwcpQXZw/uSD+B76592odaPLac+dtEAJ1ZJ3eac3SHvNOHptfByGRVLcwClVT67GQUtJ0rxFprOkaCs95aN1VjvaDYA5lWhExPMcipeaxecxqdc2zWFZDvScR694c2qx/vbM2l9dfXMRhNlWWrJPCArz6FyQ8H+MgjlZpnW9S+PuiYj56OLWo2CWXsLUzB2D6fxQUwbZPnOYVxuCKfp4tLsIOBv23AcNsjwhrHnmTdlGPwMzgtjPx+XeXR3POwLOy/3FdDA8e4zwkFqzIhdxCCIMQbpz+rpcyI3DY6589r7NcXmVM+ucd93KEhU0fiYeKsNQOErSpSY9TrVRGtDz2MKZxDMSB72enVCRhxTd0GtGZjtv3xePQTtPMKBZ98i4MbGoJgqbkPVz4bycZvb6eRIxSz0XPDb6ouCB3dPZ0jul0m7OLX2NPwY1l7r571xO8Dc5Hj6vo6Su4RL7kW2vqBgbw2eS4j4Oz7ni88wjqYV4USZXS3qOu3VKK2tlLjkV7WrVUU6X/nv2P1t+SMy3Gpd8nr1mPtAeCB5n4srRZRD0zDtHfunCzWagYhTMedeeLem5kPzdkmtXy51yZGVEeKFNpznmdPazOPf+6X4JHujk4tEQYj+fuH9Gfeh0XNOSW5K8f9d1B5+VFH2IRiO1Q0nrehy5OtT3TwoEstKGpLhdueNZO6vREBzHRxEKiWvS66LoqiYp2haP8Dw/83BBeCd7K2dyJAJC8vLCMR+AP648gAt5HyVpAR9V5ezvdQvbrUa/gyGWX3rPxwnJmXEbLN/OKjeI32OrHkfb7OceRiE+LL30BsYwh0O67GuEhY4pwi8o65xaXgbvO4Y1OdTn+846fV+jQ9+0BXrBe8Z9ydXIYR1jnorUx3odUXJB47D2lxkRfn4O77r3DITt7+WdhEXcAxz3xeknp6L39+sLQe09GFg3IZHxSmvmxt0ufq7sW3hJw/oPo7fX6MdROR/83hNU/VzYI3+XK7jwvNTzK8iYywgXtJ5g7Mauh3VcibLGSL62v9kT/5z/jj+evOlKFxp1ge3PZY5jMi1GidOZD08C9NAW78Cg9LDKMtA9a/G1e1US/M1ekdfFdwNZMBTGEVB3Dnge/3eDlud5tQRzjj9KHc8UowdXxI70uGzyc/Auo/w+wtlqVXC+hg/JD0f/vMrIlfnI/46+cV4p9XLeZa9/dtxPD9+4boSfna+chuEdz7WCx9Gbzh8fGh8HYqG+fGvKZ7zo/f2q67R2wskJzj16LMTRm5KaVciNbcdwUDAI10A7YjDC2T4ilFFSlHhhYEDogRigHBG6xhw8IypOLMfC7yIYLVeeP0L7CAUaMXk3wFHZIWz8/zyX7/Hz8NztZzxzHkroCD95aZSHNFgLDOY/89DToQEq5qzV0wExaF+HrwUP1pWi7ynf8fsm+FxOpbummLP2AfOdCqxvxuZhuDAU7bsjbQFlsjYMBUmVPg+t+9KHWWo4barNdO7HGff30OHT/dJdYOUC13tScK4oJ/aevfOy5mL7CBIx7u/Y24I6elfM4/7kVOKSrnAoZL1kTNFhNEDHxyvhFKdjqRnDJAWGkVXneUiRH+BhqKB5o5F9a1dKs65IRK77ctja/Nx47n6ciGvQuRQ9M9ino6QIZTAXXw/l7l4O7wah1PIbQENKbn0lSukrxgildMZ7oBXnRVXj+XV7rJfDEVufOzLRx1H6hG4frMFLnkNOVCUID+Z03h0DeuK0vB85el5QLTQiGRh0bsg4TzIImbAfGGaeF+Uy0GkCfeEytwsdltTJpZB1+XghZ3xe3hgLVMSrQaC3JZ+XGKoaPatdj+FzHhGXD42vRCxSSr8hpfQnU0q/x372o1JK/2JK6Q/Wv7/Lfvd3pJS+L6X0+1NKf81XPV/SCyj1bEN8dLE6h3ewOseQARa8e3xOIEBi/i73LBbzJGODUisZRSnjXfjvpQaHukVKXM+VOvOKcqOBgb0agPd4RYB/1hVjqcaRE6ArisXmxCAb3QW7C/wI85RWbcMcOgt9CAORyEiPCz7npYrsk89fUtfXAeMjvKgjvyBq/u9JRwxXKtdl7RKXHBp1BOfrDDdg+Ns9ktHz9++M++qoF5/h/wi2ZHToJZR4lM9ru6mWhLHD3p/UBIR75bTUdqOCuTlM6oaEo1hu8LPGMVmanzsy6EYgzxm9fI83c4W3IxOOTEF/D8saidPQZXh3GpQ0RoQpfP6N4TLlo3uGo2uUNDqa4s8YaWo0BEa54I4Ie+LyBTpfjWf9/KCb0YBmvt7xdz9ytGF3I3iUDZ7g7g6Hhxe8pbrTAvMfverRY5b6BEX2Ktv+LNMeZzsPMnqkP6cRP2efh9M4Zw3dOKIdqAk8qF6Ou3xxAwx5zR543xpfr8vqUab783zf+PPaHKhY8b12GvBz8g7GvB/EZpm3Llw6ytzXHG0fXycU8hsl/eLhZ3+7pH+plPLdkv6l+n+llH6WpF8q6WfX7/zDKaUvD8ZIHRTf4t19syAXbq8uZCBiJ3JKdcYwh9QsX1cyUg+dOzTGs50InJFdaOElI8z81lYnMveKOFyPSbKOlEpYkhhFDrHN094hLuM+uHBfBkXmkNtosSM8vQKHNbJeqmqYp8Pk695qpo8jd82svOzL93zOe8SBN3tutrkR/iEM43TEgHbIXEeAj8qNnzuEys+95tsZm+e78hjpDeHs9DLlUxnMee89mJK69Y7QPHu2WinclI7wvNlDN05CuFtC21HOJFgUEmgHZ+v0jQHvfOUGNsZN0N+gKMtAb6PR7jTa8WXqlQ/nz34gINk3L9k7SgoB643OvEzTh2f3Oy+v+xzhJE/E5P1jWMn5Z+wj4WgFz+BdbmTwc57nFUoh9N3olOV/HS0U4IYgRlbnoYKOlmZURBO9ajygwFG4PBfeHg0ld/58r45h7aMsH2WKn/X4HPZ6HXgEPh8NVubL+ZdKG04LTmc8YzRC2EvPVfO/R5nrcsPPlOc4DYy6irWwp8cwHy9tdkcAZMXRIJedHcKXjyiVHg1BPkMpPLIPNGw0Fl8bX2lYlFJ+u6QfGH7810n6TfXfv0nSX28//8dLKbdSyr8n6fsk/eVf9Q6pn2TEdWi0Uv/vjVT8c/47qbXF5jMkso2eJEaFE+/YZMuf10GClbj9vX6gPM8Jnd+PjCSdMW6/cnwxhROoSUVwPLSBEvCySFec3vHNGdF7P1C668zrKBB7FudiytINHB8IJgYEnCvB8nygxdizI796FbMbPvyMeHVOlggodfvdoNB2LbQjPu75OvO58nIGdtpwo8wNDIy98Tmcp9RQOhQXcXFH3vj9Mu2dJ+KlcL5PCGU8/ZSGFvImuBilpC6xjD1zevLhhiz/92d5uABBiRB/zevBOHIlCs+iCEpJcdkgzwHWZr6jsD5obmT06agSf6DfZGfboVh2pTxjs3m5B8qeOy05PeH9v2aUuiE1yh/OFTp3tHPdp0AFnRfdEw2vn+TdQWk6XA6fjr1h4FlkH+iGyw03lqTeCGdPHU5/zaAceWk/cpT0IudK6eUqezby54h++HvOEIiVa1qHXudrN2b5ntOZz9/lmOsM6Msrdka5Cl24Mcoew1chg8tLNNDl2VgiH7K29LkneVhzM6ibE+VNJZnzazpyHD/c5M0fX0r5Y5JU//5x9ec/UdK/b5/7/vqzrzVGbwYBmvPx4hDZSDqAjZa+IwOM0SsYvVcYhve41+WCyC3K1yxvtwRJPvU+9s7YXUgn9UaJe7c5nYlfnhDl3jDM5t3VpNa73y1jFC3MyBrcYHF0x5nADZ1RaHTQnyWTuoeCcGcgnHzuI4rk75D6SoVoTGNlUk4jYSilo4t/IpxdEfA7VzBSU+RjJ0afmz+D83bacK+SM6NfhSu/8AQxOPazc+ZpdDbjZiOOXFrrZRdizG28N8bfI7UadzewvVnSyEPsq/e68H0e92bkD/9e/K3eE3VB7kKz82aTNQF7BZ52Icy+OF2MiAo/97Ab+zpW2IzGg/ODP8+VqPPGyHfF9sDXOcouqTdI/X3IBz/j0cnhvEe08TUeLWpG6GHn7HvJfm6mRMeuqyNvjHTiRj3fGWH2ziGy37kB2IfNmjOCAeHGHLkh0D7GmSMmo5y+TFugNhjX3nDQ370fOZqJsVfLtEd+i+sURyY8TMt+eu6T8+IoC8ffjfuKrnAjkMR2z8VhfZzldV47wwke+arx7a4Kec2MeTUYk1L6npTS96aUvvcHt1tnFfkCjpIi7iXpZdvT/DKLe8pnfgbeCZvDAbtl65vG70ZPeVQQfoijtz56hCE81LyB8d183i/I8uezLpTweCeIC/Bl2qLtq0PaDhM6Ub5GhG6ouAfq73PYtFMSpiwQQu6phaA5VeoLL4NxlJ6pJHXKhHmAyDiEOO6JCxl/liMLfh7u9TtduXfK3rhQeY02fA4+v7bO1jLZvWbi3wxCSqzhWkMZ45p9v4B9+f1l2sLokxR3K7ig6Om63z9XRE4vjNELc/TLFfloNOAheahwREReGDd2TwrK0hXmNMiFbBUyPGtU7q8hb25gO93RAM5p4zV4uHRzeNkIin3xHg0dYnL0cfngtzF8pRIQP/TkyNG4Lj8vvFBHvhyNyPaMUe6wl75+NyIwgt2Ry2YYusHixrEbJOM63Oj1eZSBrsg/cv5w79yNMtBnPyOn15RafoXTpv/BWeGd4z5wZj4czRj5ppSWe8X7nOdc9vjnloGfQ9/k1t7bz4p28Mh1nnPex2Xh1JJeyOQPjR+uYfEnUko/4ZxY+gmS/mT9+fdL+sn2uZ8k6T947QGllF9XSvkFpZRf8J3ztfOOHFVwCOf8Xh+ni7p2Ix4OcfSYpH6jHb5L6aWl7EJt9CDG5+GJOZO4B827YFje38G/QzY7kGQ03TIr2C1eNwi4A8OHW7yvCQjfBxeOI3zfCTLbqw8JCF/L+C7KG8d3+XPcG96P5t0743VeX+l/D4044/v7R0UDyhA0VHrPZaSP8IqPPi485eEG3EERO63H71TC2Gl7ReOnOc4PIUSDJ4S0KwD3SrqEUrvjhD31/XMlyvv9Gc6fvItn+f/HAf2zRyMv+5mN9OLGltPbfrTmRa4cecd4l8lRcjd/N7DDs81Hh0rxXPd2Y+1K8qZjPl9fkxsIoaDsZ6Ni9nmNho+vfx0EPErAac7l3KgMvHJtdCj8LEKpqxnnPhfmx7ocLfLPjR6990vxc2EeIw2MKOQos9wIc6Tk5OXGf47mOjKGweP05g7VbVsCEeL30YgwNTQKp240atz54TuHndUou0Ynwc/Dh3+HfR7P29frqFLsn9IL2SMpHBfWzDrHd742friGxW+T9Mvrv3+5pP+r/fyXppSuKaWfLum7Jf1rX/ehLhykVi/tTOnJbrGIQdnBeG4xj0qAz7nHPTKv9DI5j/c4w48M+Zow9OGenSs8j4ePf/uzX/Oi+T+QF3Nnjq89a9xH38+RIUalwLOXARZzwcjz3dtlnz32Pp7lCC07OuBVJC6sXKjhgYzCzZWQGyevnQ/vGNGn0bByw8EVgXv2bph9yFglLDLu0eg1xfdLD31mm7MLFJR+qndHYHQzRzdS+a4LW1emvqbXjFGnUd+Pcc9G3nDFzVlzjjzf795gTf43z+WMMcacdhyxYs4u7Eel7M/js9DaazkMDn2P48t47jWk0PnLDVKeNXrn/o7RaGEfnJZp5jQ+G4ON5/h3/Zk+d3egHMVkrb4n/h6+7w7Aa4prRAD8uaOB7OfxmgPpzoWfBejAa47AiMx2+/iK7mCd7tS4zH7t+y7L/N2jo+Xr93+/Von12hk5PY9negznDGr7miH5VePrlJv+Zkm/Q9LPTCl9f0rpV0r6X0v6q1NKf1DSX13/r1LK75X0T0j6tyX9C5L+1lLKVwdk9P+n7k+jbVuq80Dwi1hr7b3Pued2776O5vHgAQIhQKgDAZIAoaasKrlNy6DGvaShTLmcSmeOdDqrPDLtctllW87MUVaH0s5hl9W6LDndyZacqEMgJNQrAQHv8Rrgdbdvztl7NRH1I+Kb8UWccx+2kF031xhvvHvO2XutFREz5vzmN5uom10pHaZtWNsNq+VeaggqD14UwEkJaWrIgONlcS2VpsKin0njd8f+42da74fPrs5dEE8ZSEqFXqm+67R01amOLW2sHqXOq2vekwKkBlGV8EksQLtmuiFOQsj8WY3OScCM86QKgf/WMboT5l2fxfVTUHGSIaNB5fvwpFZNGNT173yoKlgUEPKeqhRbD1WNrP6nc9YmagH1mQAtYCrja5S9JOjxfU6iYU/yUFXx6NXKuf4/xONJoe2ce5FJXQMFHhy7yqbOIe+j76/7RcEVQ0BkNfn3lgLXfalMxjT3t5Wh1lioLgCOM1vxhLnj5ygDXPPQrEc7Zo67NSLt/mi/q8ZVdeRJ+16focZGAS4/z/DBSWvdzkM7Ll0HvsNJulTvqSBFn6vjLIdWls/FWIMLoGYc2s/zd9ovhffnXqUsqWxYzhLq9VTw1MrCSXuOMtM+43Z7k3/XJmsnyQjDNZqwSwap0l3BV6wWwUsLgG53fdoGWTHGd97mT2+/zef/GoC/9unuW30n/3/oFoyxlHb1vrQoVkrGUG+sKWgAleLgxFJptLE6xV4qwLoJ+f2TrlaRKHJukXermE+iqlqwQoW9N4x2qqfehy2P2dpVPUNF3ao4T/KWWgWg41P0H6Or5qz1RDsfABHmFtCod2mC6UrOyEnv0YKT9mei6t4vxnadRGvqu5qH3yiueekQTjDAyhKcBA5VsTiXGkLFZqytAVU54bv6PB82Vld7g6qYYzxuxFqvjfIYY2nq1c4jf2fjFMDFe/I+nQ/WfEqZAL1CdID8Tu9FA2XG4YS561zA4rw1h9LqqGOeVyjrYb+PBZS3XqICOr5PO04yBBOSV99Ju2rTP/mebHIX8s88/8Q1a39S0zCI7HHNT1pD3YOu+ZyFTqkHmpBNDB7I4+3kHTjWkwyWymnrPeszgVId00nipK5Vq2PZ3E5BAsfHJmqtHliCRwdYK/pW55iei6UdfytTHLPuP76/Ohm8Op9yaE5qBGfrGOtGWSE6BAEbmmOmV+VQqF2TudP30PnROWkv1c2c9xBT46uTbI/qyXb8zkU7coCywjmlvr0dO8Lr9zp583d9ceB65DBj6ipMivja7nv6f6BOfhkEpQGolOtJJXiquFvUr56S1vmrB8xFOYlp4TPUG+C7s/eFPpeZ/6ogj6aVeabKSqjRUuPVes0cT+tFAnWjF76TKrbWA9OxtxtYhfok1N1uej6XCJmCzU2gmyH9u8wxN2EIvlrrlvGhx6HvsBnGdJpmVzf7Uc9NS2w1TGDz3cQpW4+cY1ean+vDz/PZbIymXmLrKevlXDke2Uozs6FUpq71vHWsCczUmeqc53ZMus+4v1oFxWe1zIPuIV1bL/Og54O0+4TvR7ZPc2M4plRJVWr5OV4+q2XaGCYacoLrkJNpdX7Ve4wyBg3fcs14b6A+oqDa16HkZy0is+xVweuk+SdwdC6FubQEVi+uKSsjlMFRZq/13tv19S5W1RUqly3QVvZQ3+kkT1oBTisLKucME+ozVLfwd5QF1TVteeTtDL7+vtWl2slTWROOkwwXx6b6hfeYl67SESoTJ+0rzg1l/SRw6dp5kvnV3+vBfDo/Wtmia60hOH6GCea3c7T1umOAhXojFMijcWV/1z79em4HJ6JFoSG66ihzNcLKRujz9d+KZE8yiGoU1OArra+G1rysWBgMKgN+tveLNT/RRM6WjuP35tBVGf264Nq5sUWdqviczLduVI5tCXWNNY2DGtxW8et8njR/red4ElNBwKF9QvR9VAmMQlt3PliJL8fI//NdOfetYuy7xer1OZ86Dj359bkuBXKUzZbab99PP8PmWS2Y63w4Ftuvyo2lZE7nsb30ndQTJyXKSxvEtQp8kKOvVdGpPOpe5nM0tNOeeOtcrKhkXVu9YnTH+jG0YJEhxJDXjcCHR1u3oKpyJlDKCVuQ0AIt3qc1CgrKtI8O10TnKp2yWoBzy+pV+0pKa7USgLLBHjNeZJD3VyaXsqlxdP5dP6fhZD24rWIFUBtZ1QfaiEpDDPwbgOqd23XRxm98R9VTanA51wpAud84DpVJzdczHZAra3Ss3kXsDWNVKca/qS0autQK24CY7ivanZzf1Fax6bxzHk8KeXGtVc44DwTI2kK8vVjNpOCdY9Rn67/VIW0B1+2uOwZY8NKqCScLqMaMKG7VzdVinOQtGhqOx+OXraeuQKU1dsoq8D9VPNZzw9WdOPV7LZrkpiBoiijVLO1cEEzQ22BpKnC8zvskL8GoflHAKhwKjvTdVdlw87SdSP0J32nnUAGWecPiAbFFMddI70nlQqqam9S7aBUwWs6r76KgTd+FXT3V+HMNdNy6hhxrCwzMUIbSCErfuaVg1WNWJVl7xXUDHwWt+r0Q04maVCj0SJeQTr2M0VXePw2Qc7HyYmaRNQUdCj5N7n0py9b3a9kvyqIyF0BqtjRkZkifofPOKgcFBbwH59TuG48nZY9zb03ReOZHiA4e9f5Upq3zQUBAKXlXBlE9RD5PGQBdHxqzXT6ki++vcuCzbJ7U4ZMGW0ELZVmP6Kax4vxzLpMczma4teKF80F50VwvypZ6s655J14ELtSbfAe2k1cmq93XLZBRAHISU9ca20H0rwIZ1UsFCJdeNArQafypiwjwVF75boMcmd6yupR36nT+rMwK14tNvvh9zoHKj8olf25tnT5bHVfKt+4Re++YwFfa7zV7wvnl77SlAN9BW8A/13VHAAsmunBSqPgoDGxJS8Fh8kmbGa8epgIH3cwqZEptAXXJXbuwvCoKXOjFVslyLFQubctr9db1bIwgG0p/BxRloNnL+s4trQjUnhZ/5ndZu63ef0v1ORHgllprwZMaIbIC7fxUNHgs3pCTjcHNSCXQ+5oabjcUj43eDKOtI8doa4s67KPUqXOlYZgqTq0mup3nr+NWxazjVEXTgt+TWDR2neRnVDEzr4YXQYOCPd0DuidaBadjULDUUqYqV8aohduf9qrKsqX+VVm33iiNrMq0Kuhaxup+ByexTOqI8P/rYaocDP5+Wjqs+yl1Llx6MCGWY+BneenZLgqG9VJd1a6/6pG2kynnmEZOjZOVMUsFUev0UCYIlOhpq1NU9kGZNwUVCvpUzlltoxcNJddp1c9VY0DVw8o+tnOquuuYQQx1TsgS/ImnMmsOAJP7gToMy75GZAdjdFXDQLay1menxO6+2uvtuVI8Qp7PpR5Sp4+/X0m3Y51fXi1I1Tlqr9sxQuocMBxGVgNAdQwCbSHn2BgVxIpZ0rLj57ruCGBBb5ONsPSlVbn3OW4MlNiZeVOu0FYAqoTA1hPjhm6VGj+jXhkv9cD4f3qo9JAU6ek7k3XhhtNnUVmo58i/ATUVxfvoZQpnKadhctNo1Qwp1HajsUMcvWwAtxV0NZjA8eqI1gCowl3kOcqiqPBzjrSroK0VCgugYzxpndR74NyoAh3n/ljpJd+5rZ5Qr1lli+NfgrdjozlPKmdULjo3Om+UQWU4+LM2QeK9qDz5+86lVs1qGPRodZUlyo/ObeeLwtEwjwJsvc8SUw6Hhqj0cyexMwoCkxFPhtuhlh+CTb0HgbmCjFU3mzHbyljV69JnLvE408XnKjDT/cw1UIPENVD2ovUQdT46X2fgM3/lJJDqbG66qjum7kOCdcqsvj//zrVVA+NctG7ANBrrfKBXiKWcfJCTT1We2/CWeeKiRynv/N4ms2UtU6wHzLVh3Dbez3lXZ4v7nucDqYypbgBwrJupPoO5bIsASKBmZGiPuJ5aCaLvyfu65rnqDCtjNciacc/qHKqzy/tzfKpH6BiqDKlz17Ip1KP8Pd+JIIef08MqCWQ1xQA4HsZsrzsGWCiq5cafls7yJEh7DX05+0LZB6DErVrlzgWf80S1Sp+brWIKTtgQwPFKkHSWw1wpRzIuwPGSJ36O76fJh0DxHFThcQwVY+BLfFDfUQ28bhqlS6mQuCFaL+okxcf7cOwtNacXN8tJv9dL51uNFNeIBn03D5WHNkqiFFtWn+T9q2EIsShBCz3le3FdqAT4ufbQNSodNTIK+LTFOuVY78G5SyBubjyuknegypSg+XbAconeymTVS6q+L15qG54Z575qEz3k8CLlhHuK9+e4dExk5G63xhy3KsUllNwDzql6eJw73l/nlfdTkNAyEGpwgbRfNKbM71IGleIl2Go9wdaIAoW5aBN3lcIHYICBAL71dvXS7xkbIWGxtqkbn6eKX5kPjpPdLo0lPJYbUQN1cwRcDURtTrul2jttLwXVgWpYW51FA94eVKc6nJ/l36iPaQzHJnmy7cGgwI+eOp0M7hEgh9WkDTy/r7lBqot1jGoDVFdSztUxaGVJ35OfUVvBS+fupEsBNdnYJO/ZFiAxNpQXhn752eS01HmLe6vR7k29qvv/pOvTlpv+x7gYCqHXz3+T9vUulc+0SYxAnXjS+YAptyjWvu6JwusMfRZPpkbjnEj1lNvnLJC6dFdXroQMhIjuTkpOQyMU01IjTkXDS/CIWcHa2RBLZ8aWgseSIo3JAllBdXV5kG5aM0CSYMVxcv5i8JjEmFBtKIWnG5PjWEJptDPOffqdePoA0Lm6+qH3i1GtKthqzPgsLa+jYtO4PewZAZBlOGlt+R1VfnwHBaDR1U3ayBjoCZGmBATgKL1c5g5VoqS2MFePMclZUWaqVMwLk54myo4QOOlesDkTYGFeOZoeB67ka9i7oC4DVZk6iU3Td9W1b9dDWRtLGvUB0ZX+Lrz7bh5sDagrdI7tJE4XMMeUia/eLSWVDEDng82xsVzZU2sPfONYue9KS3RX7ZEQa0qf8uQQq1wcjoE/U7EHSR5ULWLgkkbJJbnfTqsC9nnfWFfALAKuY3SYYx1yTnuqgDtlLVp9xt8pwKKsszSUe1jlwvKAOI+oL74v9StlhoyBroHqOe6FgNrIO5cYy80wmsMy5DA6kEDGus/t8WN9AuwoiZjeBXS+APAx9OhcOTVZmR6+F+dk3ZejGtRZ5dgU4KqOMBAGWBm1fR5I5cSyHvxpFt3IawkeviPwFDuXn6vsDkEI89DIJPN9NNfkdtcdAyxoNIgMuagUXg5uOw3H6D+l/vSkTv1M1ygnXuZ1dnPVJCQppjpmzg3Xd4ttHgIf7yI2q7FiSYY+nVdCZULDwfflWElFrvo51Z3LxuQckPai4SLQWOXWztwsim4dSkxUjacyPqynpxLleFVZ23xGh+jiMaFVD4uXdkXTDaXMjX5/ZOZ5BlOrfq68YPUMAgBko8CYZpKf2psNAvBW/Wxz1noeCrrU6+Pv2qsq14vHDSbnlspA2RSOgYZu6Baj89VgU4bM08q371wwJdAm9JpSy89SBbrqZjOW+llSwlSsKj/MjKf8aYgi5HdpS6F1zlQm9N+6/gGJNl10PWQeQ0xHvOvcMtSjYUYv99b3pzem8tyWnUP2A8fG++s7E+Cv+8li8jYf0dl7tx6mhT/EUMfoMIU6vNWCrs4FRFfuZXs+K3kAJkcKuskw0UHgnuf7b4bJgFJbPbYdV0bV0zDyXpQDG5srVXqhmXebkwZs6jjb+Yvye86bybboKM4F35sGmTqqE91h9yZYQt1PZc+Px955kx0U3jtGl1p65xCSd+JcyqUGncBzoczx9OUMhCsW0Qes8t+npTM5muY+MfZiM3hvXY9Bnsk5ImPDdWaoj3pB9XF7KYDTyjAEjyUmRvn/EIyFXprMF2I69puZ/+r1VNRcVkhsSqShBipPNghSI6dGQ8uU+Dmif5t8V44KHpeaQqenQkU/ZWMGFE9wCR77q12VAMWFnnIegDIYFFTWqSso2axGeJf6WfB9dW46XxK3lGoL0VUUptJ9arT5swE2onAaoODhfInrU4FzLvkuum5GrTYbgatA8DjOfRV2UO+U79VJvw+gGDmgGGuuTd+VXg5UzrwP76tUqd6XoIXvSyCi4amaGi30Yifzo/NJOpoeFteobY9evpvj10gAgXOpyo/AgePjmh6st+YlqqeszNU491h8nZhIMDZlhowATUtux1CALseyBA8080lPnYAooFZe/Kx6q3YwWR4X94EnISQAu/MBk8gY70GmjM9YZYeFz1FQZt+RMfIyxi3Lp3rjapT1Oxp2UhlwLlojrb75u0cyoPAlR4yAxGh8fb94vJKLDsp2Gir2hwyO74v8Mp+JYd9pGkyvMG9I83k0PHAsHNDIlVZn6DozpKPNDSkjqifcCYBex9iyA3puDEMyXJPOlTJmfQ6yvKp+WfU1ALc1llwGzvlJTOTKl/DFSeFBygvltu+OH2YHlByQ9hl8d9o6zc3iWniZU9oWgi79G8E87xuiwzbLOud0FmBMGT6p22p73RE5FkDZ4BSKISs3XlZW2KCsEEsG60mxOBq9lv0w2q7Z9Lx0M7GiA6hpODYMAUpddqtcmCjI77R11jVNWBbVuWiZ1fQKNduawClGZ33/WTKopZUUGI6VbJC2hmZ8jYIdm/lQqs5icrIhVPA5vjaspPclXUpFRPDgXDyWeMj5VlqS70lFFeFwOK5tnTWUoWzKEnx10i3Bi4YfDnfrVKooioTlgC11rfLV5ugouNXP6XdVZnXd+TuCxmnpkvcissUx7mWWTA+eUy+Z70Gwpx6e7ZtYN2hjDw0+Q99Tf9akSj5Xx8U118xzACfOJddDZarzhZ0J0ZnsETBTPygd3eZi+GZeaaw1H6BlpWicFHBT9rjWuq68WmWrukr3AXURv6MAVcMLVS5R/je9UL4/c4xiLAnsQCnFjLJXCCy5f102uJyXNkmT17qfqnvXgLpmpygXNHicOwuLLn0VOmyNbjun7R5RedF9xzkm601wrHqHF+dZWSp+ZjuuUmVQZofJxpx0pDnnVQGx6hTvpDU8XFVhsb/a2fjYZgAoCaO8B+eDQLbdYwk4Ha9MPIkt0jnkfFPWjdVHceRCLBU0zHNSoP5c153BWGSD0neLUe3mWefyllPrbWWYgOJpqjHlhLPUi8IG3RQ4nr2uaNG8qLxZgQRsuCD0AHXxWm+TCYK833Yaqmxbhlr02VPwifZtEKjSeXPo4JdoCTitkVqCR+jqXg4GhrJ30sYVNXmWIRpeqqAZk+O/51iYCbI4HDvDMBq/VcGfQ2f0IIVdla6d3OlLWGwJHtPcYz1MOJpW2BtG2xDrYcIuzzFzZ9RrtRghSuyUDclU6WtvB/XQKnHNXpAaVFWAVAAWvxQw0bnipVI+7R2H0eaD3tZuGlIG/3pnXuguszFKVYbo0LsSAiLdve4nRF+AJQ1y3y3Y5NLLltYk1ameFZlBjrEXWebYaUCo8EyGmnCRJlDbHgUwZ2Ct4DEAx2SZsk9GhUZRQyzKJBJUKQhSI3oSCOT8M6nT9gFKLkZbKt3KuO7dymHI4zNF3RgENXrMF5mXDn0O5/Ey3ZcZOX1/9TD3hhHXt/s4vTmy3+/1k+Wq8J0t9BFKzkuIqRST+0A9Zj7fu5QPQX2oobmhW0w3ewfMea4Z+lQgpeuoe0qZVYJmY6Nc3cHWo7Bh3Mt0vKgDWr1pVTsiG7s57TvKWMucEphxf5hjHKQ7L2DFB2qrQt4TnQtY4C0PivcGUHJFsh1RkHCMxfU1AIviKLV9RHgNLmAJfQmJ5Pvur3amC+elw+JKIrqG1T5dKOTOYCxiyo3g4qu3pGiNBgRIQri/2pmQ3C7uYwapyVgG6uZGCioU1cV8PDJjm/bKLQgRxcF7Ko2uLAq/o4vVd4uhWC72JvdnUHaELadTlUTZxDo3BEGqmHRuWLtNz0EZFQqgsjg6ppO8de3+yN/zIoja5E2qLFBEKhfcTQO8K2DppBAKvT8qi71hLB04XbD4J70C3QCqpI7GlT2f66tKXJVMYWzq5kxqwKjoVLkoO2R0tqy7ltrxs168Rz5r6BZrckUZSvHe4r22Ia29YTRgl0KA9am+vV/MC+Gl4IG5PD7LGsslaRxo5Phcriv/o9FV4K3sFbPxaUSUadB9peBC5UDPbwgxxb5DdNiOK3MmVt1soTBeHO8491blwH2gcqWshjoGWskxiRFnPNvCljKvfHdlPPjeGgbgnrMujihzr7LD//diLPh9ggDqKNLg/B4TCI1ZiMfPNVK2cNXPVZKe5vOo7IxLb4wn2VPek/ffzUOlk1Q/cA6VMdXvax8Q/jxkXameM/XQtHTYTisbO9eW5a8ETDoXnQtVP5/OJfDKPaYsl84X702dRn3jXLR5UCaKYKjkjRxnM9u8MmVIaCcYJuHnqCtoOzmPmnitOoKOG79P+axYmAYQ8T05/k933RHAIsJVG1MHo5txm7sz8mfGXgEc27i8tL3pSYqGYQ4qRKCunzej64oHBNSxLH02hWOc+4rKZsim3VTbbFRTXHNlYzwc11VSn3eJ8iIrwPca597q+peQYoQHwu7w/ZRC04ssgLaYJUtDynU+YY54Xydz0NJsbI+t866ArD3DghuNm0izqal4Wpqw88E8r5i9Kyo/DVOoIVg3yYB8L60L53tqvTyfqV6V0sK6tsoy0SgRILdxUAWaGn5ix8TWuKyzAln3UxpPX8ajybqstnJZtkh9E0xRrjinbbiP/WX4b+Zb7K3GypMnXawKsB2bzUvTN4RjU+OiCYI0uPw3lTT36N4wYjNMpghpHDUEAZR91vlg45+WYsj5DIL7Ve5YSYNIZoTKneBQw4R6tWBS15aypMZfQYKGC8hoteCf/1ag3o5Z17Jt37zLgJ4gS9kcsgzTUjfP4xqt+tkYT3tf2V+21o1zolcvhpDvRJlvwRjXOrG8wfJ1CALU8NHhpBFXnaR5KwoW1I4AyeBvhtF0Lt9FQ4vK6Gn4jYBjf70zY8955/81DE3bxPBjlRguQEPnj/LQypSGndROWYioK/Ot+q0FRhrK0jJbldW2nLu97oxQCFKt7Dj32E0D9lc7HE0rDNljdy4lB4XgAaGAdCOptwEAXV+jbaXSlILWKgEqcV0wCq/GoSlQRmui1Jkfjmvsr3bHYtNLSGEOhkSWkJLx1GiSyqNHTrqViXRASsZzKN4tgYah8+w9sHLFWIngzUsZ5G/ORTO0SlXzHtxErSHlmI6BQPEgmOTGtXHyb4aKmD+gxogbXze8CnPM78BKD26MloFSTy4p8dlCMLPrDNCG4NHncjSe7skxcF5TbXfpCRIgAFSAa4vq+WwFuGSp1PvWMIONI3h7Tsge9gKPvdVowFq9bhq9pIy63Do7ydr+aldKlgX8AaXmn4mSpJrbS8N9mivUAnZVvso4AKgUonexKsvl/Oha65hoiPVZfFfGgftusTGYkyL7jCdsMqnN1klp4+AsObulydvxqrOh5fBL8EZJ88RNGiCyKnPs6gRTuT8BFmWQ1DRZJTJ8VsmTP8fv7OWw2rR0iE7yovJnuLeZuKnPRfBwPukSbbWvBjxKEy9lPnR+jO100fZQiCm5l2Eu7lWI8eYz9J6JmSz6zCGi9ynZnXtKgb2uEfdL39gOMoA2N9lxSzrY2x4buhmrLmLxJVy66mYLERH0aAIpHSPVz20Fh9qG2RXbw9AEZZTvRxngOCk7/DfXaOgWLHNvuoPPGJGrUVxhQsgWxpjO1trlcCtlke/Y6oRP1yDrjgEWR+PKELFWTYTojvV+AIoh1eoLbkBuPN30ilYtxt6VbHejwXydBBNjyiWgIPBvVAYUeCbPHay3GLoZIRZqi0Z0Cf4YOlaKdn+1w5SpxSX6kneSx6TMS6LOE4LXz/DdlpBibzGmTF8+i8adsX6gLlPkmHWMVCzqcZPp4OePgY4cQzzK9fVU7IwbLsGj7ycMWT6nHGfUZ3ODUnHQU+F704vUXAygeFbmUZpCpgzQiy9li8xtiKFUe1ioR+Z9kb/Dpd4cIaajtBUY6D3sUCiRT46Rcqu0uCrroSstvPnejMmakUbp35BegJn5tdd2kuIdurQW22ldUcSth6lesJYfKmisKpAaI9MCR5YuU4lqSEiPGSf4b40794zKqJZvAxnsexjTovOqOU9L9NisRvO+OV4FhUDJKzhpbtTzBgCfn0cFrHojRoejaZXAjHjtOle231wJFdneFRZJQ3GdD5hyOT73H+eb8kJYturmkgy7dNhbjaZjlsikxGDzshmmiiVl+Me5aPdSL7tlT46ywVJv2rz1BizqPNi/UZprAaVqgsxcWu9Y9aKgXrKwlswzDTTXg/O5BI8hj5XMju57An6CCpNxggufSkwJWs3pRcp1MWAUS3M+rfIBUK11KxecAy0T5v5Qfc73UrDk5X0oV52sg+YrcX4qkJ8/x4P8nuu6Y4AFUASHSng7DSbQnEwaRX7eNjRgCJEKg0qpSkDD8WxtLhInazuuEOAqihmoz6Jfkdp2NT2uiNu5dCoegdK0dMlTEbTXd0uqvc4eutHVokA4TqJqLRvkWJjsA6QDvfZWI7wL2Eo5qoaZuImUclSlNc5JGGcx3nymMja8LzfxEp2d2TFJ8iYN4oKiPG7tNik239V9Seg583vc1LFhjXRjH40rnN4cYTcPx5KhFGS2FPWSPVX2R6m9stqY0gtxLmKSPgaqeDRxbStt5VUh2saXZDKVZaUx9f1bNoXrwGd0ed5Usa9zkt6qn0tliWNcdrZxaOnh0biq9kProceYau97X2rjW8CtjA1/b1csrKBHE55zJUTZ+URrH45r7K3GKm+CIRzvUsn1wXpbGeQleAO1PEsGKIbuYL21HA39vc0lDQhZzTw3uywnZCnnyP1x3Fkwzz2zg51PCeHKnKoMq3FQ54ZrrT1+uJ/MqIjzARTjb/MvXThXeX8SkBoDRqCQvf9xXplOcDKvXV57esDGjMTCBlGOP50B4v0YZuAeoMyoZ0/Z1TBejA4LCjOsel4BJfV02524hCRD1XSQ4GN/vTOn1wNWUk2jrdVYupYM2yzwlmBK/c65VlBIPU4nynSzOFuaMNoy6ry43rwH5XOc+9TAsdmf3DMdCvDRi5EEhq7S+v4HbJDlnHsFgB+RXz0E4C8DOAfgmwE8m3//l2KM/+rf5Z6cDE4EvTVNQtFY7l7eIPDlgByg5E0ooiMlagIozz3JC1919SExvFcUgVYqzxYoe8aJAizlpaTvtY9CyhtZmSHW91n3E64f7WM9TFgPk4ER7dXAxj9JabhK2JbgMcXSi4DvGGNKdNOEKF5zRtBqDOhhD4KQgdLrgM+DzC3PH+A8UvHws22oiRUg3pXmSC1rwGfynkTNRjtm46FjHbqlUgRAXYOtDIslpfFvNH65uVmXP596eBRWTL0FGhjKkx40xHeipwxkgCWUKr9HABBkzRiuolJdezlYShQck86MnVsKu6HGngptNw62JhGFAeM1zT2QG715V8BvUcipu2tpD+2MkdB1VvBAr5BjYXIo5WboFvRILOAuDLZurGIx1ggll4dAifLXygyA0qQoX8w70bnnnk0H380W+hqXvtq7fN/OB6ssMtAnIAWomYVB9lAF6DNwaWn5yitGXZFGRc//CD56v2DxuTfF3KdjEPK9h2EyNsPWzwU4JBlj+TaN6aorZZsEGOroEJQrEFK2MElE+Zmesc1Hlh3v6tw4OpCdC/BdYY3o2VOnhpi6A3PsBFk0zLwn520SB0J1AX8XozPwSJuguTTL0mF/tUOINWvB+R/JsGa9p+NJwlDsCde588HkS4Et2Tx9hsqNPVd6gnjUYJ6MOnWVhuMoh9Tt1KlszKU9MOg0Uu4qZ+CE63cNLGKMvwPgdWkArgPwSQA/DuBPAfgfYox/+9/1XtyYHPTeMGJEb0hJKdEW6ZeSqbQ5eOAQAQGTGqnM1YNW74+/4+mHVIoaE6NCVsZBvVQaoxAdZimRjNFhFzoDQroovV8qIaS3feXwIAtw2jgUBIIOjn1vVVAmKyO0a6UmwrVxZfV4FcXq/DlfYogsmzRPrDEcSjsOXQI92mGSc6p0v9LZQAZFcnQx80u4cdlBbsq5Eey0CsBKaZlPQJaBwHTVzdjLuRRUcBwbFZwmKXLubH0zyCATBaDy1gBggWTFm/KGxZCrjSpKi2ulXswgDdNiTDkWvivUM70qlpMCwM3dBnvDiKNpZYaYLJAybi116vN4eU+CWd1r26l4sDd3Gzt1lmyS0s9pPY4nNVIpqrcdM8DmPkvyUypS9H07n9p8M5yw6mZjZYC+inUjJkZibxjNsyazEKKzNs98X4IrylKHtCeOxpUlrQ6ZcWQMnt+xcEksYTM+x3IUshGHr3MHluCxXQrYZ/iV809DxBwhvq+yDDW4Zyy96J/eL/CD5n9IDgwKWzaG0hMEyKwM0tHvbJ4VXbS+MXS0CPaU+eJ+4ZWYvvogLwVZ+jlqSK1qgg9maE8CZ9xTLZOqbBXzKnqfKkXIJmlojPuUIMVK1zOTp12Ug4yD4IRAn0aa3r4yiRzT/mpnjhVQH3DYAgrKKEOq1olZQBHHeRLzpQws9w8T7KsWCtFj3ZX8xspmhron0e2u36tQyNsBPBxjfMy5537gbV8ko6kplCxd/ndztyklci4nFc0DfBcrBU7PwDw9F6vNSiqVx+Kyc6AqI0tekQ2iRrOU/A22KHZWA2CZ/EBOwlwVMKHGu6IN6U0Ijb4ZRltIo7eyp06Pis+gMmMvB5YoqtevPSZo9KkEtNUrN6MaIUDaUs+l6sBoNUR0XVZssRxTrYlGRvln43lqvbWcB3q7pCKVbl33kyWBznnO1n1KguVJsWq8CCo4X4svSZLj0lsoQ8/QUGB5uFtXXiyAYx4W35XzohQtIBUJ2ZCp/HAumHi6HVfwPuBgvU33y55q+mwd+rHSWAEFc/ageNHD5nMsQbSDGfTOB6tYIuiiYdSkZK5ZGnuwtSD4N0UU6nCTKn7Ohxo+shS290WWO8fKkN4AHtd4FiC46mecXh9ZcyGCBESHw90a++tUjuiXGtjc3O5hf70zEGkdEH053ZT7Y3EFjB5NqZzVIRlVVkYswVuoU4EjQmFfuIZpjE1L/Sx3zLUACqumpcbORdsfnQ+ma/RclAVp/jmW6Eo7dIa8+H2ul3qv3qUkb9LvS/DohnDsO/re09xjsxqr9WUbcufrY8G5D1o2IU1M3c2WcuMQjZHm3AClR8UgMqjsKPergeP873U/JVDkfa6omhEXZ07O3mq0kDqd2BhTbw8CJ4ZN1Xh3okvhYHOq1U6UccqzOlFa7kogo7lMOvZ1P1lyrTqVvDefnexI0pVBZE6Ttan3fZbTaRqqQ8q4zm06QbV2J1y/V8DiHQB+SH7+dufcHwfwAQB/IcZ45bm+zMQ55yL2V6kRkBpPlkTtshCHbLwswSbHkEM8TrlTYICC5LRtducDwtKZB6UepFaCxOhSwywfsL/elUV39USfFMPiPeidE3VSeJAXeZTOm9PcY3//VgJA0wpxSgBif72rgRZKHJ0hAd0QfDbBFCljeqbpEKO6ht/W5QSvgpS8GksFSboZ1sNUAT8as6QU6vIrE3ZfH3W/RI9bebyk9rbTqhJyKhGWyJmSi3WlSFJmpSGNysoScia8eNEKnrQB0UkbrPPBaG4aSHpsCirastP1MNnhawS7nMddVoqBQJWUdF+HpJhX4oYyVia3sYV8e4iWdlLUMehZJKc3R2Y0mRSngIBj1TlWg0nZjq4kj6762c5F4HMJVvS7Kn80FGZos+wdzSujnS2clul5hge1lFbHu+TunVZiLsmHGhqdXWmA5Fw0+jtk50JlhHOo+44gUhNAKYs0sJVRjvXZL/p/yg3PGOFYYnSIruRtKEWv+R3juIJ3Eac2W4xTj+0ymA7r+yWFZXMn175LFSEEW9oqvs9huLZUlmvIJEnqAk255bwOw2ShaQ2JacvvJB9Nx15hRXiq7yLzocaQ+4NXn5047nHvEkjUddtOieFKBno2G3BqvcWYe6ao3qUtSYxKCbdRFjXBfIGwwYCFXS38JSxq3W6xDicleS5n33D+eBGYcjyH4wqb3GeGAIThHiaf83vMaez9gsNxXYWNlQH6dIzFZ9zHwjm3AvD7Afzj/KvvAfBSpDDJkwC+8zbf+xbn3Aeccx+4Nu3MGFMwDtZbQ9s0jJvVWPVUiM2E0nOn8mZfAk4KY4IUev6fhoIoT5UQf3fSJqcXobQghZ/vQ4VONK73pGCQiWCII8R0PPzhuMa0dNb0iJt+b0jzwFLDoxwr1qoKKkcqHiowKkTOYeeDnQvQjpdhGoK3JaTYLH/PzUAWhMqGNe40xuPSJ4bJlSOjmQejQupdOaPgcLfG4bjOuTZlU6intcufJQOhVRCcA94XKP1EqJi0HBPAMdpWM9iVQdNkKSoo/Z4pEgnp8HPt2i/Bm/wQ2Cl75bO3oGCE7JPG1/lem2G0JmBAMpgMg/AefE8+j55LbXg9bu42dnw4PSFVZM7WsxwBTy/Twjkyh0M2HAQS2v9C57MNJ6gB0/izNoCiwgwxMRbabKywCSnfQPtimCHLDJvW55OV4V7huynr5032SmMx1SV8V36Xe4J7SGVVlXWQfcxxcs24FnQWQjb2AOzYc64bD8/a5jL+EB1ubTcI0Zc8guhxY7tn1Dr3BI2yhhWcKwckqhdu753nnHPEfcv35v5vPXjK55JzF1pavwXmlGEA2AzTiYmwrRHUEAH1E9eKLOdmmEr+Vu7SeziucZT7Cum86NwAKWl+iaXNuOm/WU7fRa0vaEd0D/BdOUZ1Whmq4M/8v/busZBM3n/7q7HK52Ae1bR0diSAOsh0wIDSYZd2gOPVOTjp+r1gLH4fgF+NMT6dJiT9P02K+34A/+KkL8UY3wXgXQDwyoNzkfH4jauVPZDRpAizR/J+T2+O8r1K8yytBojRocv3ooG1EtNpwLik1sdE1aw2UdrPhMDVndDIcBgD4ercC60SMVQe6ox/Xozbz6GrKiKA+rAZevaHuzWGrBTGuS/VEBIn088DxVhwDslYADAl6WRjzg24YkOko7CyxFFjXHxJoJtDaShlnRgz+g2NAfHdUilehrg6HwChY/suJYidWm+tkoTsEdfDKGfJ7m7pbf69tAP38C5g3Ut8EuWo8ZT74y3j3pQVjnejoyep4SGgfI+XeV050XCQQ/a0b8jhbm1shhvqpFzO13YacGbvyDyNiGRgTmLvpizr/K4CzSV0OL05wrT0lewpOLIYdiyhtyWkUlxeKXmubv2sjFZYusrYKujgviUo8S5UxpT/trwDlDyp6BgiytSyyLYeYkjgbqFWluK54t2SYVgC+7AEAKUMk5/R/C+CAv1Z15L6hTR6y9Tw+WrAue/a/TouPdZuSi2YnTPGlcaQJcmWoNmlKrf99c50aAvkqANMnhsmRfUqQM92tL2o1D7XSL/PpFAa3bQP62MLgJIPpsCj94uxAOpZs5cEcznakleGFBja4/joaJLlZuIpE4iZ6xNjSc5f9/URAlwbduykAdfcNM6ld6XfiI6Xcs0qIa4/782fuf60Ebq3eCmg6mmjRAZ5H8rIETuT5vFrTlZ6wWi2Q8H2lOVs3U/HKibb6/cCWLwTEgZxzj0vxvhk/vEPAfjtf5ebqIeymwbsr3cmJDwfggK47idT/EzkUyMDwKg19oIgcqbB7bsF3td9L3Qj6ZHGpsDy780bjIVq5eYrPewDjuaVlZsOPmBxJeaosWjmUtDoabnWZhiN9hq6BTd3GzNK9DqqsJEPFq+chC1hoiMv76Llf+j862mHBBB6tgNQPH/dCCP6Y6hXwZPWnQNyKqX8n/NZvLJSPkkgYE2+sgHTsRNQEOVzLvlOBKghswQALHmKc0DPm+/Ftdc++Z0P+WyLOq6pRx9zjjk/vJf2bKBMqaJYQoqLbvLajEtv68jf8V32M4NXN14ripHPdIjHklapzOilHqJubkXQTAVLcMB1Za8WDe8BhfWpDFVzb86DyoGWS6c92ZsTwX3Nfcy90bmA3VJyXQiCdH+l8vM5e+IJZJxeH1kHUiApeh4Xvu6n0mALMYPPYvjVoeDFiiT2PHCu9CRgzojug87VXWo5L9Rpt8YNQmaalNHofMDaTXl+k0FneBFI4dMYneV+ETRtcjmp9u+hTGqIjHNH2R/HFfZXOytLVqco5JACnQFeHMuYdTbZE11ryiCfG2PqtUOgqeBzlLA158hyo3iAWlea6emZUXzWbhqqnDjuPyaAd8Kq6D6flw4+r+e6L6C8PYyL86Lyrfc6mlbmZHGvHI2rSkfwnVu9Sl6A60MHVxkN3Vucy6TLS68KhlsV3BiAjSWJlDlbrApSPR2CN9uja37S9RkBC+fcPoCvBPCt8uu/6Zx7HYAI4NHmb7e7U+XdJ4EM2E5ri61SUIYcU9aJ4ZkaAIwKOhzXFUOhXQ6VxuRCAXVfDKPqltqDMyUq3+E9+XwyKhQ6ImuifCebuO8nhOhNoVGBUFAYQliCt8ZHbdMspYW1B8FmNSagkBMY6XUBuR5bKjI0fqdx3p3EFbmhW4/K6GjxdrmxiLZjrOPnVhOta+PKoU8WnoqlEiRkpZko79LBkUmZlB+CR87DukvykBJlnYWUOh+sUyrHqhnclWcHHJOXtq0tPVD1WHU9mbhKkGXsDJLiSPlFue+IK/38+U4OEdGXMTKJTNe/7JPZgNcCn/NPOmsdrF669hGhwqDyVAp8kPvzc05ks8vvze8oIFWv0dbXCQMDAC6a16keKGXscLc2Z2CdyyaVwSBbpaylAbjMRHGOyeBQ3hlm3c2lHJjGmcl8NEhexpJkMFQyS9BDo8hwCXUBDXNb0UHqfH9dTr40xge1Yeb869r169xYT5I8tZcP5ZH7t/cL0BfgxvdWx4kyyERRBcNkMLU6qwPQZw94CTmBPgNu6hiHaN595wLGUEJT1gyRIZWsOwmAqjCWLy2wCRSGDgbwOL/rfCAfWdGrR6cyYFqstHudgTcdC64DGbQp5ynxkC7NiaPDqYminOO9YbRwFBlmOiLqaCE6KxxgyN7J77yL5tRqkr2GVylLWpYNX3KQmOCrzDGLEQ7Htcnubk4hnbWfgH62goDgb380RHt9RsAixngI4ELzu2/6974P8hkHiNbzn5vNmrUsPVaYq3glAIsVVWGOrEBpDHUxiBSpfJS6clnZabYtDQWBBpU3FTs7NfJiPIqeBGvlvSvZ5AwfIHgE5yrPl+9FI8YNRICzv9qZIDAJE5CMYTlsJ1HVhc1RSo6ewnGPss4FScqwbIK1lLwphanxYQo46TSHWDWxUdZik+PYu2lAyIakdELtDAwM3WxGl15VdKXz6iRnZLD6p1CJvjotlYCOClgZCypxXWdLgJO27Uv0JmNK62v4iPLFMmRmXlOelU4kzcjvqvdDBqat9aes7ebBPBKWii6hPueBR42X+GzpRMoQClkBnrfBboze1Seqkh5dQqG2lc0x+UXTcCr/XtkmlRmNRWvSYOeD5RgxTnw4rtF3Cw42Rznk2TQ4cqXFuip0yhDpX+t+KbpCe+fwXdhXh3JhYIltqvO6ckTaYVdBB8fV+VJlo/Q99zKTlVlqboyGixWLyOes+gnbaWUe+7x0xtZaaE/2NZlOk9HsiUdfKtCYnLjLYUgglVOvZe9YUniswUiMJeGzbbqkfVvG0NueVD1KMKbNmbinvIsGPNhEkUY2yDyp8WPDwGnprTnatHR2+CXHw/Vg7gH3JvMWjqZVFVZQZwlgDkgJBx4u68qeeQEFENDuXTRGmYwPQRHH3EGOPJBnK3uyBG+9e2gn6RyqQ0F9zf2tVZHroQ51UCcQ1KsTervrjum8qWWCaUFL18Z56UpnvaXZsLkuXBVfjKmBEKkffp4hEP0+gAqssK8+F3boltSDIL8nBRgolLQm4KjC1Gdz0/BnKhMrW6sS/RKKV4ptmnt0WbEezSsLB/FyKK3QA1AfH8z3E7BkdLErx6G7Ruh0nghCdrGmezlvpCFjAw7SeBjHLa3OOX9sikSvIsZ8dG/uckhqVxUyS3p1w1qowUXrIJc2bWI9GB8lE0HD3vZJmJfOaOi+K70t5qUDuuQVkzbU8WkSsIJQZcDK+mYQl2P4/A69XypezQEggOB4NRnPlEYoikhzXuhhOZ8Mq3XjzCCRLBb3GsuWKT9UNnrpGrYyNc69lXoDJXeJshxiKcl2MicK9ttcI8ql83WXUirmGEreB5NRWb1Ab4zPY+4Iw0NU9KMkaZINIm2trBONjMvOguYpKMWveQQGhmOppPJ9tDwevhvnTDvPahiKQIfzzbkfs1fMk345l9oIie+xRFcOOMzASk8/nZbO6PvOl0qwwzGVYtNwzwLAlMnsfLBunmn9C6Bio0C+B9/f1jHWLBXXVJ0BhrlVv5oj4wNcfh71UudTiJMlzKt+tn4Ytu8yU3Fjt2fywzEN3YLtuErh+FjywW7tNtZDYpDnWMhxKkCX8kwZMoCQ5YTy3fkSFlTQ0oYRNQfEWDNxCjlvvK+xRS4AQ2nOuASHU8KQsYqMet0KC3K+F4EVGfvbXXcMsKAHAMAYA+vCxwzW3NuBnydVOc09Tq23FiOyXvmZCqRiLGVoOJGeB4ox5ubR8qfWG9U8CQ+hj6OzuLce/GTeVGYr2MkMUC89VBuKCUbs2b+gPsCH3pm+C+eQYIf/EahZcpQoAhV0Gl8N/TBpj4rPFJsoQ87RqptTSaSclxJjKVPTMJOOl+tBQ0725cZuz6hLbmiGM5QOpIzQMBPorHIopG2wRiNoiYMuVn8DindFOnyBJPQClcJnTLTNJ9DPtgr0cLdnzyXtynECwIDS8ZLvMEvOCeeSVTtV7FQMihrpW7uNGQsFe+t+wuLLGTX0WDVReNXPVct2AgSlnUnF6sW19Twt0pW4OJWx7pGb88YYAlY/JdkpeoFdINfdXI1Z9ynzKJRlIT0/Lr0xrYaWwwABAABJREFUF2QZ94bRFOhBl3QKu1ky+ZGhuxjq5k66x5bgsR1Xtra69gq0uFcZqqG80GAvIXcpzfNLDzN5mbPR7KfWW2NEOKdkoGgIOY9AcjbmpcPB3iGW4EsCcT/h9OYIN7Z7pvvIkPBwSO45hueor+mlk7nh/oy+dO3kZ7jfPKRsGbC8DTpoZFOSPJVnqKevFwG+9qJgUzMA1hRrtyTGgYCBuo/MnR7w1vmAg5zcTMau88EYBjLOnQ8p32Mp/Xs493PorCEVx66sAyAgfe6t6MBk3dXdioPMpdoLkzFhgSyULvfgvOyv6vBk2wWYzjn1NtMIWrvZXncMsNhOq0K3ZUVH9MxNdmO7ZxnGu2WwTTP0c5VMon0RvIuAT1T7IGWRqdwxea1MkCTdw1giQwlAWnQiZj6DVDQP+6piuxJHJKDRluPc4BRcGgTSTvRGHepeHNzQFCT+nhUyVJjjko5T910BDAwDGT2ek5MIEDQmt3hfeZWa1MSf1YDyczE6XD06ZYovxkIrasghKcfcn2QZTJA1cZfCT7BnZX95Pg7W28qgkt613Iau1Lor+8NYI1BijL1f0HWlOyNj7ezyuMDbplJ2h3NJZav0KBWoenXJe1nMQGllERWpdotcQmrNrgaNio3XOufp0DM6kpAR5+ZwXOPUepvkmM+XkxdDdFWfEea1dD4lyt7c7pkitcZmMlYFY1wvzgtlIwGBvvq8NjOyqoxuttMeB19avjM/gVU8fZYDdRKouJU5Y20+55tjZN6Ed4mVYpMyzj9Zxd00wK0KGBzyHmUIhQZcqxAIUDXMoXOkRoHODkMjCrRovBUwTSFVvqg+0HyW9TDh+nYf5/dvmoepZ9uoXNzcbSp5nUMKyYUMyjTMDCTDzDJkdv3V1thAaeNveQFMJvQlWZ1OD43m4bhG54KFNanLOB+0Ccrq8JlaJWLz4HwOP68s4V2dDQKPMxlY6Xyz+oayS0DgMxijXqZ9IrvAfbmEdALx0biq2sizUy0Nt8o+QQTvxbUiUKXMOFdYLs0j0z2njF7nQ8mri+n8F+5H7btDm8cx8vNa0k09RoD5XNcdASy8S9UP2jddu6h1PsW2mF/Ao6OHbsat3aZqPUyWgYJNZGh5FHlRvIs4td7apnOujnG1FxV8e93abcwj0Yx1o6UExQN1yIbsQAfYgTchlsS0zpckLUt2ysqUhtfySkjN+5JkarQVcimSxMb4s5bIzhJioMJVwXYi9GRNCADJgPTdgn23qxSNjp/eFr1woGTV88AbTRS7vt1PRt+VRC2flQurPqalsw6lCZANZqBDdOZ509NnhnhEinPSYHuXwJd5tvTuutJjnzk/3kUrz2XyljIvDKsM/fG++goM+BlNxmK7cLIWTuQxxNS11IncTpLtzaoXrQBI65iAJ1kHlgxuc5Kd5ooc5UZKBYyVhEJ6kFSCyiDOYkCK0JQQk5b+0ehTrujZce+qc0CWge/H94ih9CSBg1G4li/iF3Q9E6ilVM+nA/CARO8roGj3GABjC52LWGXgPvR1CEgBBfMLzPHIW0xbQZtHidJ8jONjgi2NEnUBgJKI54MxFozJa9Le/mpXdYe1g7Ty/HDOtQpNm3eZsZPW6/ReaaR58Yh26gWGlxRMmEfvS1WS6pK9YazAHw0sjb6GzDjvbG3Nd+EBlC66Igvdgs1qtFLSEg7uDMzf3G3gEa3HCe/Hd7N+Ifl3PFxxCSWcpr2VGAZSW2YgKtsfjnMJHoMPdqJqBThFh7bjJKCkjmpBDhtgkU3iuJTlsedEOVtJwDMtA79H2VKAfrvrDgEWwXIsdvNgDIJ5dIg4t3fLvNOSyNObYW0nUD0lTto41we9xJhKc8g2qGdJA8hs7NbQcJGtCydKxzMtcwVKmIeKhrFKLqh3sYpt8fk0ikTtrDqg8tEafAtNAJZJvCdlZnqOCZBat7aeNOdLFfhJZ3n0KPkavMc095bgqEqXc73KvSxolDaZeToc11X8ftXPxqwAsBIxVS7Ia8IQmRppVtFwPLd2qflUCDnL25VKEm0EFKJD7wszo5tWGx8F2eDW7EnmywxQLotrwxNco8NxjXU/GZjkSZlcAzY4mpZEQd/KnqXL3nV2cg1Q2LMQK8bHm/zPZjgV5LFGH8IiMcG488GOjFcPqvcLZlfCZfoOaiy4XloabqBY9kTKazkO6Ck/MToc5sREpXpdNpIxpjyKOXQ4m/UEANMH1ZkpkpfE8MjN3cZYCO/TWSQJjMzSedRlD3idc5KKrFMhq5xwHrTdNxkF/jtVeblKwYfoKsaWlz1DumqyAy2rUjT8ZPt8rlW8Jn7qPOucbIbR5PbUelsBPe5JTUrn/QgaAViCutLzzFXheKknu8wSVxR/LEmt/LyGmXgZUMnhC84PdcASUjVey67qe3pEHOReQJpDx9OHmRzN0MWq3xa92+hBtgVnDxHOD9+ToHdvNSad3jlbEzLHQfYc3zvEkgSuzovuP1v3LOdsC6Dyp3uZLc7JXLKnR5tbBJRcKM2xea7LxfjcH/iPcX3+/UP86TN34+MPvhYAsCzsTuhNOIBy6ifpakv8s4NUipeh1CGAajG0A6cafU0c4j1aOkgFnZ9VRE6PgoCGoMdKB5u675L3kChAdg3Uo2l1QylYMQSMOm7JuRoyiAFK/E49BY2PByRvX0931CO4+VmWYKky4fuQQdF5VE9OlSUpW743PSlSbCwL5AahcqJh44avQI8rWdtGPYtBY129Jtjx2Qx/+GbdNKkWkPbSTdMbHT9LANvuj5wrgk6VKZVPjrlK+MreEcspK4+nWyomQteAZzm0Mk2DzvdlxRLX7SjHnikvylCQgeB8AtIWXDprtvtL54AMhp7aqkZX2ThNYm3DC0zw3UhPFsqZesvMz2LZMR0Qglx+juPVteceoywR+M0hGWFjqEJXGXfbo6503awq17rC0ADlaHMDMzIfxpK5kiytrNQobNFJIUoDfzlUxpydvWHE9aN97K935kSw/HordLcywW2oSx01fc9WR7HXCj97UkOs9h5cR51TyoveW88QoY6lw6h6Wr9L54zPZY4Wc5A0p4kXgfgmJ5tzL7FKUGWcck4mdtPkReneafcn5+Gk9eTnrQQddXt37g8NxZ8EJDWPhGuiTpCyhnT8WUnlfcDb3vfjvxJj/EKccN0ZjEUXcPrUM3jV1/wcdk/ehUsPPx+b37mKy+fvw9Fw2qjeJTrrD9H5cohKyvYthte71JedykmFkwqSNeOMNWnypB2d7UqilW7uEFN3uhCddY/skE8bDCWUANTU3RLS2QPIn9V6YocSc+9RWBjLpqaidXrMeOlvD9QAhF6+Mg/cZC57yCwtW4JH78rZIRQwFfgSX++OGV8A2MUBzpfjgo2KVlrch2otVAlrVUWUeWwNecje6bqfzDAReVeJdqJUnStncsTorDaeG4xncvBSb1MVOy8mB+tmpbdBD0WpX84xvXQqXYtFZwXpfETnj/cQUBqU70YFYHX+kvdAw2ohn+isKytQulHquBR4BpTwFBUV14jvQkZH7wvADqAyuRZQoRdLCKkEvYtWikdlZol6zlUe5tAtWABraqUVJHa/zGaRddDkUJ5wyqY/09JZSKTL39PTYVmC7R2wlwEvZfz60X7VS4Rl4d5FO8yLc6hzyvDajHKCKQ2pDyU8R9YSQJVvYOWIWe4pG2QAANjfePT4dhowu5IEf2u3wc2wsTAX16rtUULDVDUjCyWfQ8E6L22XzXtpKJOdSIEajMLFqqsu11QZMKBU4FB2OP8t68XPKMigXDmUQycBWFgjHRk+V+EUDd/ur3aWB7IRtpUhIc4NQSTnQBOoCVZ0zyq7AJQ8HLI3fBeCoLasXsHjkvUIk2N17kzPovTJoFPMMWvYG0ghf5NPAYK3u+4IYBFjRPi6PfiXHmDvFcADex9E92OHuB8fw3xujRt3X8Cls/fj2sHdcF2OIWd2gh4DE2yMfu2ieTsAKsXCidZaZfUgVdk5gpCYy9go5D6VCWlyExeXgkIvpfXOFeXS4LM5U5qPUhbJ7wKwOCc/0/tUsqjvPUtDnGQAC/VHoxBjOpaZ77q/2hkQsa6kWYCW4I0ittAJSpMubcZj1HY2rIzJUrnRA9Z1oBfeZS+ddeB6UJwpyLzhGS89lZM3mdMC1Ge5aHkUQdosIEIBkoIpVWLqOeh6avillR8ziLEk46akyZJ0O4euyiECHHbjYDLJueR6kH5X1ophkVU3Y+4KmEnGYMYgBldBjlaYKMiicj7KHReZ+Gs5IfkeqbqnMB/8DOdP54D/hswn34dtz9WAsBSv2guhVKrQO9c519yKzgcLuSGv47qfcHO7Z4myLMnkiaKdDzi3d+tY8mx7cBs9VLItDINSllTZUgk7OYCP+0+NjbIWLIdUA0Kgqh6lGh/NZ+BJuc6lU0f5/369GJiibMQMdHgd7tal1DWvJZO/1TNPumQGj2ZfgrdTh8nsWjfdzBLyucruKYPJluwqOwS4ymBwTzkXMeU9paGNwoT0VXm2l71EMN8yxz4DLfZRojNLvUZQQcDP0nhlkLk3plh6sPCdyRq2+SUhOqz8gjnWOUtsHKbyUn0nhytYFLBwj7tSjcd31/mnHlM7aMAkevs3S/qV/UQsR0W0AK697ghgsb15gKd+8+U4d+1JrF94EVj3CG9aw/36iP7qDuevfgrn8SnElcPRvWfxxOd8DnZxg3nu7ThYhkMYDwMKEm69Ms3HAIqRBLLCE+My5LCJloKpAWEWMVDaiLO3BlD69FMYYnTW3AWA9QwgPbrqZ4xL8Sq0a1uX2/gyTMIyQRpjAFVHOHq2gMQlG+W3BI/Yld9xU2tLc3bVq4+3DuadKrMxh85yJDTEpI27WnBhrEc+bZFVEJ0PVmbHz/F8giV4UwSrJsziXcSN7R5OrbcGhgiaKC+6iQlImdej/RSAuvSvLbdV0KdhO5URYy2ixzx3laLg/PR+sY6zTBLWcAdzfiirKpMaPiGLYYBCulFS2Zmn6ENp/JVFgB5Z20W1kpdYwiwcPyl5rmWMzihalRHOqVK4fAbBiwKztnuiVkQBxQhyjhn6434+HNfptEpRsru5NPuh3mA5MgCrCGFoKcRUCsmESMaY2UuE80Y5WEI5QbdzJZ9nWrrkjaNcMbqqeRx7sLQNuTTPQxMc2bthjs7ClHbf7JTc2O3h9PrIGAPqlM4HO3+Ha7QEb+FmzcUIwgzQ6FYlmVk+WA23hNQfQ3MzgNLaX2VKAZl3EZ0wVgAs5KElrXo/XlwrVjRp7wY6JpR3rQLhviZo49pxrxGssG0BdZMybgQRY+6/1GXZIaOqJy+zsR51Ep0f1aPRl1wTAgSCTj3zhj1Q7HsoTjEd1BB8qrjsMhD1wcJSIZSQCYscFMABqGRNnarnuu4IYBGiwyc/9Txcvnwe3W8EnDl7HWe+6CL2/sDT6K4scB8e4H5lhHtixt7uGh762l/C9MxZ3PzEvfC/dAtX1xdw/eBuxNwVTmmmZBA6i3vTm2+9EaBsDD1uWQ1FZTiyktdSK6K9OZSud+35HKS12FCF76QxMcb1WH7Li4mtjAHSQ0nehKu6L/IckJOSWTsfjiUksrzKEDpgXqbS2J1PPTi0VJGeISlozjHng164xeF9iWEztDVkalzXgoaSiWJ6nVpvDVgpbQwko8Xy2yXUZVxAqWW3rofRw+dQFJOq6M0DmYJuqEGNd6f3DfAO1nadm7PryiFKACyznAmjvKg0p7wOyphwPb0LWEJvc8d5pILSPv5sgoWuHA7mXQK6CmhCTGW5XP956eBWaWza9VLXxbvSME7XFIBVqvDdORfqjXY+VCE3XRvKJhPQFBBxP3P+yHiNS38MzNJB4DzwGVTgu2kAXKmK0PwXJnLTSNP7JQNHw55CJd4OQOR5Rs6ljplsqkZlrcqeY9ecCaAwEAQiyqDxMwSRY/DVaaIKimkwN7naon0W5ZcJoNprh0aY1SOUE03qpUHsRN69i1hcAcwh56+058mo86Z6SZNgdS2Z26K0vYF9lBwNy7tw5fwMhgt0L1ufmwwcCJDolBEgVzoOsOqtsg9yK0JfcrXICIXoyxHk3WK5PQQgXsZBud6wn07WTdQ31F9ASaZfdSXka2XB4jQhO6BcQ3XilnzGVOcCls6bDqFDqetnuizPqZP1fq7rjgAW+UxD3Dg8lQznU/fh0qUL8B96GU7tH+LM3Vdw8GefxtDfBJY13EvOYPVgwF0PfAL937+Ou/EY4uCwvecMrp69FzfvvgvX+/NpQlBilEkJlJa+QEF4vDSZhf0OSAmxnfVWDpBhLLtzAehniz/RcPDOFHSlq5VSokJg97x1Pq1yNw/wiJhCl0uykvJgYxd2WCSVyqQeLS8Ksnl50XPgJlQD3JYSEVBNAhZUoZCCg4d5LBbzcyU8RLaEdPNmGNENNXUHwPom7K93ONytS/OzwCznHLpAafyjjV3YQMsSTrMHrgCJCap01al8SQlTweqcdD5gEVr4pCQ50pPRCf0vpXhqiBW0agMnzkMAKkUeY84LGuoDuKyNcygVT8xH4RodzUlehj4l751eH9nfNSRCuacXxbXThDzmL1GetAsqlSHHqmMkvd3mXbTgve2cSqDPJM5p7oF+tooHshbcZwAs72h2JcGSeSWdP94ZksBKk0nRAEo7mjwbHnqgHIsCAI5XQ2m61xhS5btHmWd62QzDqvOj4aWhWzABdt4FP08g2feF7qfh4HzNS2cJrwxBcd9OwWOvn+xQMzOmKCGFzgcLUZq3HAvTtBlGDN3xCg564Qo0jeVF7tLaFfmykmsXLZxAoMHvUt4ISvtuAfKe8hmwMD9Fn6vAPkaHo7mc3NyCCv6bVUarnGx/UnhHGVmuJ2WoekddcwnxcbwatvAuos+9Mxj6J+Oieo3vn/R+1gERBq71mmM5VZvhMaAcWbC/2mV7kpz1aekthKRn1Jx03RFVIa84OB+/77VvM+OqsaNVN2PoZ2xyqeDZ89dw+nkXsb7/EvwQ4H/aw/3aBPdYPdDlTI9nv/jluNLfi924Rgiu2uhEepUHijIXBBz6dwqZ1rjTkANsrVu8BuZ9GDWYF0M3OVBnbevvlaalYKoyNkMsh8xwQzDTnw3FOCYaSioHemb0TNpchbaUTmPCNDrcTJoc1V5q/DQeCdQN0dImKhU+5eyL8hmW5jLWTyRO71NzBThvdTw2zc3pzRG20+pYaIRjPwk48PdqDNX4UsGocqHXZYY4HI/Le1e3kVZlyUqhU+ut3dcaJ0nlAtswt/FjyhUpbsqinZUi4IUgjJ41x6TZ9QoYtMumvnfLUJyUs8KfLe+haeFdYualesAAf6a0GWY4yl0uNzmcxHsdjmuc2RyakuX+OdytrZW19nsgFU4wEgV4ktJn9j/XVtv/6zPajH2VGQMY6iEKO6G5BYV5LaWTei4K51GZMQuJoJRMA7DGe+y/M+c1PxzXdjaM9hlpG0+pbHFNtd/INPeWUEtGI733ZO/EtWt1LOdG9yB1C1Byaji/DMnynqpDaTu0soMhLGMTfUp2JWChnmudTq4Rc80IfAGYLKpca08SJ+usOoZAXnWLfq7dM5ynEDyCNNzSfcSGh8r+GZMUSr4ek937rlTPpL1cuhlTBmkztOv1ajWi7xa86l/97G2rQu4IYPHKg3Px+1/31ope5mAohJpYBAAH+4fYbLY4c/cV7N97Gav9K/CPObgPOrjfGIHDiOV79xCPAsanzyL+RMT2xh6unr8bh2fOYQorzEtXxXnb0k3zHMWz4NUqEXrRWmrK8TDZkBQWUHuxVOpDl45FP70+qg6p4n2VFuRJe/Qslf5T4QSKgtacEh0fn0GPp6Wm23nhnOiGV4FUYedntWfGSc9WpdoKNxWK5g4Q3B2stxiXPp3ZkI03KVttpsRNpiGAtG45jpiVMk/QJDjcTYOxG6RPTzIKenGNWmaDCocgRw0s78n5ptLRxFnnUoJZ54J5mwo0gGIAyzHqpVLKoeTsAKl0mKCI+SuaNNmurclNAyz1PdRIapnepwMXXH9rxjQzOXsy0EAZUDBlzctiOeqaAINyorkA3LNkArTXCC/eg2vStnfeTkN1zkhpyEeP3FfyAUj/j6aHhIYIKKu6H/VdNZRBo8p30ITLVle0wIzhHtWxNKg87VcBFdeF4AUo/RtaZkGZIX5HwReBKCv6CFICdZycncP31UZqumf5XDJHdp8MiLZjaohlB7rFkjejCe78HsEQ78/5YYWQOlKtU6B6i2WlWtZOAKSlqtqgsAU86ngBNbPePpdyrmCXjiP3ZduR1phVSSBXQKz5FV23ADHi7HgZFw4/hf2rl4CvBvrvmu/sctOActQ1+/4H8RbMmAiDcePwFLa7NW7eOgX3+AuwGiacOriFg8+7gv2veQbdsgXuWsOtN1i/OKL7u8/i4HrE3XgccXAY7zuF62fvxtUz9+DW/jks3PCxeNekz7zDMQWU+mh0lZIBioFi3I3Jc8zHiJ07xnj0frFDr3gvxtv13BSgNuhALjHLqJNeKPNMuDktOa8vikzRPkuJmJgUYun1r5tDFaAaB+9SeS/nhxtbAYLS6txoVE5tDgRLePk3Kmg9TIrAi4qaxxkTTLQskJ5EqhuNSXvaBZSfoSJaoW6h3npNaAwTu/pZBrUribSdK7kLlJcgoSAydVQOnEeOQ89A6P0CuNIDZehmrDpSm4W2X0LK3GecnQzQ4W5tlQ1sp8x5U/ZJPdYYHWZ0lbLufID3C4DeDCrXoGU4LAyCEkKxPi9UrpRBX9ojW1gnG/gxe9oMA7KkkoBf6Xr+nedD0OglercGoJR1hj7Ug6aBZLmxAfZQQgZqKNQwkj0jSNZeMDyll/pAQyJ8LxdTXhZ0Pj299pK7YCGwUJc8chy7abD8K6Do1pQ03htjxXfkmFtP3pjTWOhzY+f4N8q0K43nOMYUQgkNE1bCs6p7tOKD4WSf55Xj0TwEAOaM+lgcJEDYJhcwoysATartmEfAVukKItRZ4vhCTA3furw+nFNNbtZumcbE9hP6YbG8JHV6FERo8it1iF58DzoSDsWBdT6i98UxNRlDadxFXchqqCG/8/54AxeuP4XTN55F/8lDuJvlmeFFz93S+45gLBgKmXMeAal9q5LIhlirOrjAEc7iQ+PSY3+9g/cLNusRB2du5LDJs+g+GeA+2sH95gz3eB022X7ZWVx58Ytw8+oZHB2uMM0rLLGmq3k0MpszKdOh9dS6mYFi1Nj1sG1WQuPYei5ATZ8yfNE2PWHCIenb9D4lD4DzpKxIS9FqBrqOxYnCAooAayigDQ9QGdArZ7xSlTc9S3o0J4ENDYfphlOP1XoaCEVLg0FFpGMgE8YxcLy2jpnRIZ2oVCIViIaIuPatx0JjQkPdsl18HzJImyquj2PrPc7pkD3GdKlYNbdEu+ipfK362TxUMlIErwQkBK9MBubFzymboN0vKWcEdJo8rMZMAYbSuibnoVTbULaVzWs9VW0pzM+oIlYgxGe3Z9DoMdAaLlPZ0z2ijax037RVDhwv5Znz1F4KYk4KIfFSDxYgEE0JzcpEaTiR+5QAUZObdU41/MQKBu5NVsC03m/lmPi6Lbk6G/y37pM2/MV/K1upc6IhJk14VcaC+o3zTyDNkIyGjrX6T79PWdD7aiI0v8uTgTfi/PF9NMzD57M8egneZJJnzLRj4BxoFRTfW9lCdUoU2GjIzGRWxqTOGysIY3Spc2x2KIdpi/VdI87efxl7L3gWq3fdgntEnMkLDvGzHKb793FteCHu+9EP39mMhQPyaaAsP/LmnSX6LMXAxlwOGLtWaMsBXYe7VG623a1xeLSHi89egPutz8L+3hFO33sNp77xIlZ7V+A/6eB+x8H95oT+/wLc86JHcc+1HeI/duh+Zcb27rO4cnAPrp65F9PeHkIodcmK/oJsfBVaUnT0xlb9bAllFAYAFodc+aXKHmaW/24pRsHGm3spbIbJPOx56YCB9y4ZvTpPNFZq9Iiild5v80ba0IF3Ac6X8EiIDsTUnAfb8BJH1HtYqEE6Yqri1pI6IHnljC2H6NB1JT6ucUqOjcmYNOBKLU5LZx68GgZueGNFWGrYgMH23z4bVc6vz4qBiuKk63BcWwzYSj6F7mRdOuXr1m5TKeAue5jMZO98aYhGpWxAnDHwPDcqvzrWTW5FbFQ+GaW5nI1BurqViZCBPVCXAHKOxgasava+GYWcdKbUtjJdajwITJ0YOSAdy8E+BXw/ygIB6AJvDdM0dKl5Ctoun/c+GlMvClZ/ENRyXFTstu5d6iLMcfBqw0S6dzxQGQoCHOaNaGdZXn23YBzrBFzu5RBLbk2Xx8Dv3tjt4WC9TZ/J8sryeueiAVXvSiOuce6xXu0QorfzR8w7zt40n61GX42hd+XcllZvcu7I7qhjxGRMziGPSB+XOqG670u/nGGYMNgx6N7KN6elS+e+hKR/FPhQlpmkSJaB/X6UYdB8G2U1Kr2cZTIxe3m8sheM2fElBGQh9q40Ahu6pcqTItgY6BBK91VW3YQse8bk5vBh389YzVvcvX0SB89exOrpm/DPBMx/+xTwitMADhDeOMOd3WF5cMB4/jyubp+Ha1fPYTn0GMcVgA/jdtcdASzgChXIMk0VPCJvChYFWJPXuKgalyLI6FzAOK5w7foZDJ+8PyWD7m1x6qXXsf/Fl7DaXIULK+C+M+huXIe/sWD/xmXs4zJegN9BONthe/cZXL9wDy7d9QLsxhW8j5jnYrx5UioVsnVNzALFagnNY1CaOwnpyu7HEIf20DdP1YBCAE+r67sllyqmnhZDlxO4PColszeMJWEtAwJFuuot0Bgnwye0LEriK+ddO3zyc/Q8NXMbKCwHEzNV6ZB9WlxJhGUd+M3dxqhaAlA9+wViYFSRs1OenlRLmUmAtTTNohdngBHHjzvXZ3h6EtmDKfKZKor4DKNxM4Ahrcz78JlV+/bMwhhL5UuvBn6OSkbDB71f4IZc+uaDKSdSwGPoMWWFmMZ93Evm+gAlF4PvSuCh66kAgO/Pn4duqbLeTQlHZwCPc0CgMIiS5zupx83fcVxMZuVhhdx/89Lh9ObIDCTDSE6ep/LLmPMSvPUiYNtvGjuCa+Y+cbw6d/yd7i3dF8qGqYxo+EC/s53WZvRbYDvOCXS6PgKxVFoU8D5UFUf0WvVYdC0TTmA55KMFlgywvX2eFVtMFOZBgcomKPDh7yhP7JFDcOdcZ5UqJ+WcBPG2FWAmw11ONk22IBgwdTFpqmnpc0g79YjhOUk6L9xjlIUleNujqluoR2Oow5+ct6FbMMhZKnRs+M488G7MfTEoUwS5HCPlC4B1z41Z7/pcgUebGV2dOJyq5UpeovepB1LnA/b6m3jeYx/B6pmb8E/VuWFxDbgnJiz9VYxPnset1Utx+NABdts1dp9YYZ55psiqsrMnXZ8RsHDOPQrgBhLonmOMX+icuwvAjwB4MYBHAXxdjPHKc94ows40ICsA4JjH1QrWgvpQFaXY1VCyEx/7nR9Gh1uH+7h27Qz8E89H5wP2T6Wy1s1XRQxvvQb/BOA+6uA+OMNfW7B/7Qo2d13D+bc8id2z53D4xGnE35lx7cwF7Db7NpTOB8SQBVRiV6tuqRRyyO9Lw0lDYkY3lFABKUHG/xgX41kFCkjag8k4Z2R/Qkx5JC2NqQrQwgOh7ngI1E3HSPmlJlVzFUstyVwlZGKeVKY12fSI89Zn1ub60X46w2DatzyHELn5fcVacXy3MuhQ+p0g4XBcW/IVk9MgSkETuDgXg5xFQ29JkwtDY0AU1ACFqVEjSCBCj4XrZXItoa4QXTlMSwzQ0C2W2b/Kp/v2+XdMMqUM+C4lcW6GdCaEhbJCtAOW2rBU15UxMKxB9oysCJDDBUKPEywvIZWjaq4A55ZGraLLUbe9p5ypl2Y0vhjUtvdLUiPOektYLkTI7c6zZ8u5NFYwK/Qxh5KYP+AzK8JkQ+ZSad6XsmkaMmjBldLe2q1XwxPsMsmLRpjxb21hraW3yvzs5sGqnaozSFw0dqHvEkBnQ7a0trECaDRy2pDMulZGZ42vOC6GYE8CFQAqB3AJHr0rCa/aGZaXsmgmPyishQIxS/a1JmSlBwalJc1x6Sxbs20BwZXwLIEAD8I00MyxuFI2D+TGYXkNEus+VPbId4tVc3FPkd2kfCpA5b5ow2fpO4UN9i6kE3uzm0f2DgC6LvVPWs9HOHvrWez7q/BfHdDfewicXqH7s7fgDiPiAMSXecQXO4wXTuNwcw9ufPI8jj66h6PtxpxnZS+p59uqs/b6jHIsMrD4whjjRfnd3wRwOcb4N5xzfxHA+Rjjf/1c93nlwbn4va/98srrZUc7hgoYU9ZsZTYOYiwekHa02SvVOnAFJVpmmeizxTpbdt2C9WaHg/PXcOr+ZzHsrsE/HoGXrRG/YAOEAPfeI3R/Jx8lfeAx3nOAG6cv4Nrpu3F9dR7T0pT7ZQHgRZDBFrMUZmbta0fHw93aQJf2mOD3GQvVeB0pcipfjp8bU5tE8V5KKdN7UiXJ92mVgJa2aTdIjQ/r74DSzY3Kq61iWHXp1MlKKWfFomEhviPzRFovkYcGtaVfBBrtpWW4lLEYHaZsSDbDmMaUFWPbzIehBL6nUuXqnerzgJIcrE2p1OunUmboRHMluN4R7tiJhAqwGV4EID1BSkye86nr1a4755ZAcA5dVa6sYRZ+96QcCc4Xn6/vomEFjZXrOCvl7Uq+DB0UNdzMP9EySd5fc3QInHjAIWVSc5sY7mrj3gp0OBe9Lyf6UqbMOEhVjR7uRVnRMIIyuApsuf/10vbfKmsKHPQAR64ldY6yUHbcwFT0C/esVYmIztbv0iGg7AEpcZIHWGn4lZ/hmFr2FKjzjzQva9XNGYh7G5d2SQZQsTzGiObPMb+HoFLzd9ik8HBc27u2B39p3xANyyr4o+2iY0d9ybAumUNdY+bn6KXf5fw4FzEME3o/YzMd4uyNZ3H61rPonz6Ev5j1cg8sP3wf0C/A4RHwb7aY4wEON3fhxtULOLqVHLhxGrDdre25BFas4GETsSuHB9hf7fAl7/ln/1FzLP4AgLfmf/8DAD8D4DmBBcMFSidSOZtQCEqiB6LfB2CxKU4MY+QuOtvUGkMGmlbDU/Get7sNrl8/nUInw4R+mLH/qZs4FS5hdd9V+CEgvL6H+/ACfz1gc/M6NriOe/BxxD2Hy+98KW7ePIfDm6ew260sb4RKqIsBwRf0ydgdaXv1ZDar0ZJGtW6680khWfy4k5P94CxmChRQsYRybokm3nHcmkQF1P0sqDCUUlVvgLRe5wJGFKDHjce1BUqCnMv/V08dSJvuYL3Fje2ePQsoBpgAgMqZCZB6QupmqM8YYbiqPT5clSDvwdCGZa2HYAmKraeliWhsc67G1BQ9CuVOA6MKk945f0+WhwqWDAcVHPdNWMq5Ixqy4T0pS8z8b5PglPXTd1/307FSvrRWiUGiV9syEfRQ7Z6xhMX47gRRymTwXThvc2a1uM4xj9/2OSJ8VxpirfoZS2bzCHJsPlDPs4XBpClRSVQtOVvORWMqmLfUJhqu+8SSqEfN+dI8gSV4BFc3zQKa0k2uNUrXXO+iVcywCqINw9n987go513We8byBg/ni2zOsYRm2KafgIqymDqRpjXX9wZKMmGMDp//hl/B+u5r+MjPfwGu3jxdMTOUYz6X86PgvpX1FnhoCNUAkZTTdt5ZuSr/ruflhFjO+Ri6xUpJyWTurUbLK+FZK2x37rJuO9ytLceGuic9P4FXnhIcY2nV7slWL/XBhdpzhQBZ+wQZs+xDbqm+oO8XOBfQ+xn7q5s4dc8h9u+7jM3jl9D/QDn7BQDiBogvdQgv6rD9hYjtzQu4eeUspjEBiBA8YvQYpyLvAExPDt2cDtyLxZlP7z3i012fKWPxcQBXAEQA3xdjfJdz7mqM8Zx85kqM8fwJ3/0WAN8CAPet9r7ghz7/95nC0fi8ejH0HoBi8NialF6MHjaVnhOPZQi3cc9WeCnY7emczkVs1jv0/YJhNWL/zE2cuucSVriM7skA93EH9+EFOOWw/K1TwM0dwjWg/ysTwnrA0fmzuHFwF67u341x2MeypHGxLS8V0pxbkJOJUA9BFTffXcdFQeUY2r74bQa5GhRebaxXDZF6Qa33zfehkaFiZiWB9voPWWGp58/fMfyjDXs4LqJnxtLbg4TUWyaY4HorxUvvTMenniMBoLIg2imV89HOC70mGnP12hVk2M8oja049y3T0NbbKwui86lJZBb2cBF7qx3GeagYGPbB4DjpiU9zjwBXtcDX8Z30fA076V7l+3LO+O/W61Y55GfbBFC96JEqgDiJnSGYtjwPV1ru8+I+304r89q12sgMtC/5CFZOuNTnYPB3ug5qWNv92nrhHHfLHlJOtPcNx0m51r3VVsywDH03DViit4RNIOW06XwTQChbpswB343vpbqaMrMEXxnzNkRyrDRU9qzeG0Al4wrg+TfqNbJS3L/8nAJAglmOlbpJ83GUSW31H/USHbOTGJWWgavCflzjzLop86H/ppz2/QKfw8N9GHHm8BLOHF7E+sp1+E9OiG/yCN92AKw3wDMB3XdcQnwZEF4wYLzrNA5XF3DrxhncunFgcziOK/T9gnHqzU5QhoDCpJPR19C67t8Y3X9QxuLNMcZPOefuBfBTzrnbp4k2V4zxXQDeBaRyU24G7U1ApUAFbweniDAz+zrds3TXpNANPtgphkCOe8519joXfwkpVu67ckiMdsnsMnIEklBeu3YW3afuw3o1YbXeYf3QEU69/irWZy6ju7YFTg3wywB3dYc+7nD6qWdwGs/g+QDCuQ7Tvft45vkvweXhXssWPtpuLI7FJB42XHHGtnSmVLuulGiyAZIqJMbwQ3QWZx26FPZJZ2SgjE02sFZk1BHTusSSc8HkK/bT78RrVlDBe1PQF5RMf+YhsF99TX0nr2LpvRkAygm7wmk/iM4Ha2NLdsLCBtKF07uIo3wGgVK3ZJd4BQGqCnSWUBIno4sIjgAjVnkcvLxL58UsoVRKUC65aZn4yfuwZLCi8HPs35gsX+rYB5lf+HTKpENRwjQaXI/DcW11/0zUVADPBEvmTgClPJH7bI6dlVnz+wpIOl8y1Xnfzocq6dRkJdQNpowuzsqPVT8MKRCkMUF0XjqMS191CwRQ5dpw3y+hHBxFxW+NpHJPmM4HKxPU/hUngRcqXzoDpYQ1VF6sGiUAxlSwdwRCSZasWKpYn4zJsRCIU8bUyZqWtYXXOPccP+eSgERzFBQAahiIuQQQZiBGVyq2xBlSA4VQwpSdNKDT7sAtOGaSpDp9yr5wHpVV4z7iXtA8Lt1vrJCyMze8M3nnPtlNgyX/cg7JBNdgIFrV0Kn1tjBkEoKhTbHws7QwWA15bRaP1WrEZr3DwZkbOPf441h/5Drc0+GYOolXHHBli+VyxHjxDI7+6CtxeOM0pnHAfCmxLtM0VHudNo3rQ9aY7M8S6lAyQ57G3LgS3n2u6zMCFjHGT+X/P+Oc+3EArwfwtHPueTHGJ51zzwPwzL/LvQ7HtVVVGP3s634C3LCdD5bspImaXDjdcDy4hn8nzaieBmuM1bNKJXXF86yASU5E2k4J6R0e7Vk/je5Tz8NqGLG3f4TN3hH2776K9X+7YLh2BPc4gIcB97EZ/uqC9dUbeN7XfhD3Pe+jmK+fQvxFh+VZjxsHF3D91F1wwyk7jXOVe/evutmA1JIVK73FOXYGzGxjCigClBrPbEksG0BpbUDOFqES9akcLoqnDtShBCpcq30P3g4mavMsGNKiYgLKeQSmPGKpAad8kG0w45cPEaMCZBb5Ejx2+XscTyfvzPdhCIfrzGfTM2kZG83bIcDiyYAaQ+e8qzyGpT66nd9dQjpQqvPBGi6R/raunzkME4K301uV1dKqI4Jvzo82COPFenw2x7JTgUVJc7/Q02Pope1BQiDAy5Q4mS9E208QGdkMkyXKVkyEJB4ilrNqSNEDpYugtrLnXCiVq7LJEJOySdzXlGcau/3VzuauWxemkKDRQKAriYm632iIvYt2jo5638qGJvBdM2h8lhpEOhshFiNAUEywZWGCWMIyKsdkwSgrLPe2M3iyHrVzOnLob8pzZEmdLuAorMwZ4Dg0GVjDOdQ3lBeOjYBLc0P0fXnxnVvDxyoJlT3de2TUrLFcBnw81E97FGn+DueVc8EKrWnpgOAtJ45zR1ukDB4vhhc4p96HFKbyAXvuCAe3LuP00SWsr15H+COAfxmSY/pDC/xTAbED4oMO4QGP+d49bA/O43A6j+1P7mG3XWNZOkzzgGUpyaBtPk85MyvNyZblwn1itDQq4F0JeZpOz7pUwdrtrt81sHDOnQLgY4w38r+/CsBfAfDPAPwJAH8j//9//bT3QjLuLbqkcLFErj2kiSh/zF6rokRmvZu3JAJK46LPohBacyXXHKIEKtpc5kZklxViQvErbDBiG9bY7tborp9Gf/ECvA9Yb3bYO32I9ZccYe8PXUR/6xb8JxfgVQP8+T2sEOD/xXX4D804g6fxAgDhTIfp7n3cPHUXrp+5gBunzue5T+GTPjc1Yt2+NpcCSi+EzgUrtTSk6upmNA7RpKHQ+nnOfN2boqUuzbj6+vRP70rlgBpTfoeJV0p7Oxfhkbxj5pNouEN7B/Df9DKY9LmbB8siVwCgxoNAYZuTzizWjzIHwPGzLnyWO811UVqflUqcHwW1fC6/AzEYq9xaWb0xa1ctBhBISsnFkrDK+1LhE6xojgPXyGhOF6uk3xBdVbpNAMF3Z5I0AXiIDp2EsqI7HoqgsXHRAeLZGauEcqZFENki/crwE3VBWDosAmoJ+udYsvm7fpYcopLYS1nQtdZQloYThr6ct9L51LEzee+lnJ0KlwqZQK4CBgQariR8Olc63HLcCmj1UDLda5QJvbi3AeBoXtlpmsqk0EnTw6O0CsxAVnSYYq7W6kujLCZWb4YJIa8FnTWyatwnZDmWUJwBXVu+PWWAZd4a4ggxHdyoOTkt6FJmk0YUgAF0/jv9P+BwXtt8LaHoa74zZaz3AUdj3b67NPiD2SdlfuwcppjZ1c7ZHvXRIbic99GlQ+FWw4i91SEuPPsE9m5cRff0Du7Zmo1Yru8jnu6AGzvMr+gwn7oHN1cXMI772B5tsLuxxny1s/JPABW7iryvtIQYKMmiXAOgMBDKgiUmvC6k2KxGYFwZWP5012fCWNwH4MddSlbrAfxgjPFfO+d+GcCPOuf+DIDHAfzRT3snQaFs39u5svG1fXOILiuqJKhseKIGvmoR7epGJHb5+pwAjaurBw0UdmMJHl13nOpn4iA/Q5Tolw475A5n2w2uXz8D5wL6R1+I1WpE1y/Y/7mb2Dt/HZv7rgBvBvCCHvh4ZjWuL1hfv4E1buDc534Cu7fdhflwg+1Tp+A+tMP1/bsQhrvQrwKmaUAXs7LI9NbQ5bI9Kfn0suEs4S97iUDybofGA1UvVxU6AKPgGZ9nsp169hpnpUGl18Q5s66gPtebz6WBlJ3pEur8G9bAc93pUbJ9urJdTOLimIbMAOwNxTPUtul8P3qlnBtbYydNv8xzLInBBlR4roZ4kkbtCnihMaXh51HzqnT5fVVs/DvzTTRswHJRzrt3EbtQYsxU/t6VE3otPIgaQC5zXV3FI5619p5/U/mggVMvnfvN9mjMre0z9b6gUPtkamhwaeyOchn0rd0a6wwmFEQS6Kh3Ti9a2UoCjIgCfgef1kw9UHYvDa6c+cKKgjaHhPtM26hHWfsY6zJbA3ZGmy+2JwjuqJMUQM5LB9/Xzb1IzxOYFqMheikbZQ0Ldj6d3Mv29gRqbU4bgRFBH9dSQ6fI+thAUag7rXItWrnWv1f6BoUJpSFUcEkQoRVJTColi6uywTAM5yLm9Z193b6bcqEOE9eK4ZOhr3OjgFTuGaPHXn+EM8tVnD26iHV3E3irQ3fuEP7Ugu7bJ7hUVIjYA/FFDuGFHss9G2ync7j1r+7C7nAP89Rjt1unPbR0xmAneasZN86JthAIIptdZpz58ybrGOqwJHul/YHztVx6H2y+db1Oun7XwCLG+AiAzz3h95cAvP3f72bFQyMd6rs6OU09KQDVz5onwIsARGNy9JwHUcyKkNu4OjesbgoalyqjPf+NXiAVQ3AlzrlMRNJJuRxtU8zq+vUz8E/eh83DI/phwvr0DntfchObP3gZw/YG/LML3BMeeM2A1esmrMIOp977JLofnFMFSg+EewZsT5/FrYMzuLq+B/PZDbbjBtups3wNoGT5T0sHeFgYgiEkh1hV2+gGU5pS51oNiSkZv1RgbGiUCMEBlZmuKxPx1kMqq5ynsh6kKgutLk2bsnK6sd3DkEu7ttMKpzdHiAIC6XHRqBrj0pRx6forpayxRYIDetOasOgpu8LRaliElCyV/BI8puAtH0jzXTiH6lkA+bhs6SCpYJgKke/cmVJIYOfWblPOCfHBerwoqCIQ0JMYCaqrsy0QAXle2idlvttQEn+va05ZIuBg7xrKTduaeoke+90OU9ebEWxLzE9kDyBJj2R7sjFWCpvfHQSkqlKlbjHZ7E4+pGsWYBBi6n5q89LoNG2+FVx9cB7ZP9VlnCPuF+YRTZKgSOOv4Tvuv9aoB/nZu2hOmpZrsrdEiKV1ujpulH3Ob+WIiByqbOvZF5oDoQwY5YlhKMqJlzVuWWc+l2Ei0vsALETGfc+wl7GJBlqCNZsa5wErqYjoh9kaTzkXsZq2uOvoSewfXUV/6Qj+qQlum/fjClj+s7NAvwG2I8JXBYTQYzx3Brf6Czg6OsC4XWM+6jHf7LAsPUIg+5H6SWgfljYc1PlygnIJXRTdYwx0njtjDX2o5IDVTZxP70qenjKzPAvrdted0XkTMMqOfQeUOieL4PLG1XJMVbo6QZwwUrrcmDphAZn1ECHWg5i4EKqwgTp72eg7V5LLtrnu26NkMPNdWEY0Z8+WXvTRNjU66rqA4fI5dE88D5u9LbpuwerBLTa4idX/fh393VtgDwhv6uAeiXBPBXRPTjj15EWcwkXci0dw+BcuYLc7i+3VA8RHJmyxj6vDBfgOcC6VOFn4IrMcLOMLzVg5V2yRTGOuXqmGC2IspcLKVFi8VgAKPR2utRpIgggaXbJCxkrkz/Z+QfRFOR+st0VZzqVESjcHk9yobNQIqqLVttosmdSqG45dlSFQg486FhzN86eszrG0px9FKbcsEddI6/+Hvj4Yr7AzxdNmYysNJx1N6UwQDaUwV4DvpodDcT1VmVnH0yzT6rXzXdSws5MmZK9pW+4qRCJz3ILgEFNXTvbwaDu3OlcYEdUBTvZxoctzbkbWv0O3WHIm5QMouonftTk+AbTo2SoKtOiA6NqTbSU40+ZbvJ+GTDwKQ8h34T45GlfAUBIyyZSxNDd17ZxNdy4obbE592QvdK05d5bLFp01j1IQo3NAljgxcelebAiossqydHUeAZhc6sFl7eVd6bZq4Tkcr2jj3NEY2mF9eU0t5yrnqiX1nFoAOJTwDpDK/rtuRu9nnBqv4/TRJQwP7tB91gy/GdF98Aj9P6yrhOL5zEbc32P81QHbm2exu7mP7Wofu+0a8YrDNPeY5zIPrCpjw8B57qzSsVoT6esEZDAbcexzbdhN5UqZFjrj/JlhPu+iNUoMSzqa/XbrwuuOARaaDEKDDhQq1bwNNg6RjUvUqXQdBZXtrRlbI1JXNNfScC2S15glPwPAEgoBKlRvXg43ptb6F2+wxL4M9HAxxwG7MfWh8DcP7P32Nlus1zv4LmAYJqxeucXem65j2FxDf+0I7skI94QDbgGrN0esxmdxevtJdN+xg7sCRA8sd60wnd/H4akzuLE5j1unzmL2K2AasOdHGwcVjZZC2fxY74nUs8Eh2mbkiajqjdNIarWKen5UrJxP/p3hCVLjS/AGOpOQ1B4SY8hKsdPLZViBykd7mTARVb2ytmSXsrAEjynH8zW3RMGDyqF5Cfmi0jeqUppp8X0pfyyRLi2VXToWHoWeRfCWWKmATVkivg+9evWOFQxYUiKKl8t9MnSLfZ7f0Z8Z61Ylpu/jActJYqMgM66hbuBmoTpfTtckuFGGiH8flx4ue5Y6jpj3a+r5UM538C5l7zMpj6yPMhgco1XQNCG9KGP0rvSTUMWtIVu92vkrzCqqexgod4XloWHW53Mu9QCx9I6l5X6QUBTvsxkmq7TT+5h8SBdgiIzt5XObOF9DV6qYdNwqB3QqGJqjc6dtATpfwtbMVdFEbjV+1UFcsZSCE3jpKc3ch5aU2C2V4daxsgGVdwHr1WjveXp7GWd3z2JzeB395S380zNcJi7C6QHhVXsAPOAHhNcExPs7zOf3cXTqHLbhDHZHG8zjgOVDPXbjgCk3CmPyuj7b9mNgoqyv1r/6e1cf7Kc5bE7nEuWQuKNpZWXB2zHpUg1fKytN/aWsWkACo+z2fLvrjgEW3KQ6SfRYSM16Xze3skSloRxLDZQwSaFf0zN08ngRvauB44JwMgl62jiiGg2N0VPJqsfODR5FedVo0iMudU3+3pB7cswd5ludhU+6Lh1T3T95bzpkZzVhtR6xeu0R1uduYPU7N+APdnB7QPzsHng0AE8G9BdH9BdH7OEqLuBxTF+xh+3nXsDu2inMn+wQnom4vncOu/U+enR28Brfn3OohoGhCW6Kao5dKZ2DzIN9t1kHo+5ROtqRKel8qFiHikqV2n+g7iJKz0Qb5Vh72hynNgWf33E7rY5R9lWYoZE1xtKtZK6rExL1IqgiKPEZqJl37BdE5+puk5nKpUfN9x26xc49MHZAAA8NMt+TniYp3jHkHh9L06DHa35JMUaWEyHrTEPBeWHlAJ9vACevN3NTNBSieyjNWdPfogFsnC9mqIfozDun0iUTsgSfuur6JgyVG6lpszgtG2XDLYaqOpSEQiptrqMaOyYra26E6oK28qAFngrMydxMon8U7HkXrSqB8sPwSMjzw9AF94z2cUhO12IH4tGIK3OkfQyABP6V1QFQzX2M+awVlIZv2s5bnTWdH9W/rIZiCJLHBmjTLn2+NtizEF23VEBp6GYr+WRb7c6npErnAhwCDtwNnNpexanDa4hf2KE/s4XfGzF8zyH8x+vyyniXQ3wAWA46TL+9wnR9H9trpzG+aoNpGrC7ucbu8hrOBexyGaoyfsyDSbR2CTGZvhEdx+8y/9Dyl5DOBGGZvbGDAjC07LvzwfJNWnZfEzItfUDsr4bTb3ewol53DLBQ5c1/k9pihiqASpEFmXh6Ei1Fo+ct6MJSmHWClZLTGB1QNoImXZFKBIpXr3QrE+KUEgZqb4UKp6215lisRz9K//gYFyxhqO7Ha70asdls0a8mDMOM4VVbbN50E8PmBrrrR/AXF7hPObjHAvwbHfY+5xr2xotwPzah+8CC5wOIK4flrhXGs/s42juDm3vncP3MBUzTcMxrVYCg5X8LvHkcBAfa/z4ZsXyseOgsC77dgMDx0mBuOA+Yt0gDqmExuJLEqNQf17+N4/L36s0riOLPBRwEMwI6fl5tCM2ea0mgfSVj9OKMtqds+wXenXyglSoFggd6gloSSrbF5iEnrnWuJN9aWaaLVvmSQgU1iE7v3jT+osKX/bJEqbbxdWxdvSPOYQW2fSlJbOeSf9cS1V7637TeN1CU8LSUBEVdEwVQOkZWLvEe3gGjGH/m++ge5DueRDdz7etn10ey23hdWmPmT7QMmR4UqIbBEhdDHQ7iWnCOpiWxiHrYFg2cni48dDOcKwCcIV7zboVRoGFToE5dzn3MhHHqYAM0sudsP0aH2BX2RD1zAFVOGNnNpEPTCcw0is5FO4xr3x9h39/A+StPYX3rBoarR/AXZ7hbAqC+4TTwwg4IHeIX9gj3Loj3OUxnTmG7Po/J7eHwesqLWH4lJVWO08ryIoIANCDtN+axlW7AdasEjktlkPZO2S9laxCLfFUhfJTQKGVHmR7OMc+Q4qGV6nSpo0YnjN8nU3+7644AFlE8lDYuSbSusUyr3GDuhXgOWrposfysfDiZLWuhFL3R30t9RC83qLIo9jcnh+zI5mXToRidJV4pXaXKjz9rXFGVkVLGphQjz+fwJhTjXPq9h5CarQyfmrFajehXU6pGeWjG6jVHWMWb6D9xE/5sAO73CK8F3OMB7mpE/9QO/VM77OMK7jr/OLZ//jzmm/uYbu5h+IVr2K1P4XDvNA43Z7DDBnM+wa/PmcQdQtVwh23L1fCosuCccc4t4Sp7/6bUBZxwXXyzoZQBAMq5MEwwrFC/yIQaz9Z742cpH0m2fHUvxpH5/dYrVS8LqLs0KvhUOp0nu3Ke2PsB3C/djDlXxjhfd1lNslNq2G/tNsnrkZBe24WSxsvKSGOJPQMlV4V7i54tkA4FpEp0jWfKeZiCryokWIHUslcG5nw5SpwAiOEQgkpzLNQJyGs1LV1qnZ9zm0KsO38yrMr3WwCrblIFP0nOkMocGRilkDm3qk88YJ449z3XmqXgHLc5PSjP01N29d2dK8l1HIOGdKrOoDl0xr+pk2BhHVeHXroMxtp3Swe4pffSzsCUNeosZaboKCrj2OXQoIKQ9JwMCOCADie8pyaZe7z3nofwgw98MS6tTuPu8Qa+6cn34Csu/3bKhRivYO/oOnABwJsAvzfCX9ph+H/V3V3jPoAXOoTnOyyfDJiePoXpxj7Ggz1ML1knJuLK2kAEQwnmVGb2Vlu009mg/lZgqXpe80VudykroevU5T1iibWoGfEleDu8Eihgpc/v4xGt0R5lSEPAMRZGTp/5XNcdASwcJHEOMO/JIVblPGrctSEQlQw34Ta3qaVC142mk66Kw6MupaxoX9SG5pj3BBjNSApWUbd+Vg0VKUtS9ky6KS1v64PVSr11OebY6qhRDCOPtY1wWLYbjD7g+s0DSw4FgK6b0wl4mx3Wmx261YThTSOGr76FHrfQ3zqEvxjgngJwpsPw6oBhvIK9a8+i/94dTsu4wukO8/k1poM9XHvgflzvLxgg7JaAec5lwtlr1E2hRlSNlHMRq65Q6tp2tz17hLOsG1WT1YzhEOXV+YAeEYv31bqrd6fhGV0z5mZUMpzv3/5ewYoqR6B0eLQy6VB3QmVyq82zAFuLc2dKt9DbMTMMxWNFZs80C96YsHyy4yafNGvgxxdPhWNTUKdjUuOq43aI9jdeagA5xxpDt/ACSjVLjKVdNBNo0x4NBkDHpa/Ah7F9fWryoyBO10TzTgDYIVlA3Zr6pFbbS47Zt7qkmguROwO/ohvI6ticoK4eqoFsnT+j4ID6xgxYKOFisg7KWCkwWUJKyozZwOmzjaXI781+H1otwznluzN/SEOC6lU7F6sDz9K65zXIv/r5Cy/HD7/oDbi0PsCF3U183ePvx5dd+hh+4e6H8EMvqgFE5xd83wvfip1f4et+4yfx9od/CZ916XG8+Mqnqv4Q4VUdwmefSqHZCx3CFwWEezyWc2uM+2cw+gNsbx6kEz0f7rE92qQ1Dz7lRcg66Rkl/J0eVkc7wfyu1mlxKCG0VT+jelEUHdHaELUrBNzt/blWZIGoV+emqRrXdo4OoauZRsp6agFQqsQ8Cmh+ruuOABbcfFp7Tm9gCeUYZgqvZiKz+Q83kqI6o2nzpDM2pErCNwtw0kVBUM8VqBu60CBxgbm4RWGKokeim5EXzPrcR1cJlAmBvJd6ZvPSIXpnHeD4HNKgFIzdPBgYmRei61Ua061TBQh1C1bDZIeurTdbDK/YYdjfovuVHfqDgM5PWP5QB/cU4D4ZgU8F+BsLVjcOscIh1m+5hgsv2sNytIb/hRHdh0dMp/ew2zuFw/UZbPcOsFvvYQ49QujKeSkx9ZqwGKR67+rhKKOVD02iDHGTrZo8FspJJydBhujQ+3TEvSV0ouQvqNJTsKHhF2Ug9LwaoABVPouyodn/fGc1PBp20KRG50ovBKWSramT5JBQRirwnY0gk914RsTeMFbllkx4BGAVK4DHHArg5juxokqbWPG907jqRmOUa84JPdwQHVaaHCp7wMJqWUYUMJEx4ni5T/Vq9x33mpYWEnAw7MD345pYBcEJ7ArnW8vvqJz1UjZIw6+dDxWD1Do4zFnRfBd9N3q7KrNL8NY9lPNoB111PARP8mJyojAgB/BVukvCL8ZAxkpXsYoCLjGsdeJ3SbyPSDkzXQ5V/PyFlxlQuDDewNc/8YuIEXjXQ2/B2CUZvbg5jb/30JfhyqbHJ8IZfPUH34OHLn8SL7v0BF526Qn8ua/7r7DziT147VMfxVd/9BfTPDgHfz8Qn+cQ7wXCvSuMv77B7vJZLHOH+bMH7A73sBx22F1ZYwnpLA3qDfbPGXI4jAndPF9Lzxah/HANY7ZVFRCljYqlD4aGWStjncE0dVIU+VHHzFobyN6h3q+fWQ6dpKy1YeFjjG1OGrdmbZm5ZBTgua47AlhwIVVJhOiskRKQN0dWYMZO5C6LFt8VBaMxWz4DqD1IoCB3ozczpa8gIi3i8VIdfkaPUdZYo3oTfNbgCrUIlFgWY+s0BhoLrVpAq2HKF4WNpXm9XzDFrmrPCtQ0Pb3TASVrGBOw3a3tvn23oO/nlP09zOiHFErpz4zo754wvH6L4fRN9ONN+MsL3KUIvHpAdwHo/Aj/7kP4T84YsMU+ruA817sH5hft4fpXPoDxaI3d4R7wqRHjsIdDfwA4h3nO9DDfJYcD4I6XhTJ2yc53pBSdT8mRqiRLHkis1pMUJcEDaXpAejI04EM7Wrb5FSofYSnlcIDQ4yJH5h240nOA68e226SEFcB2LnWGBErlgnqw+p4m0yhMQIjlHBeuOanpk4C2zh0Vmu0JLzFdHPfGXQZWeiZBK8d8hgE8SC+Y4NH5mkrX71EWKOsMJ4SYcqEspElDpzS9rB3vTa+aP1P58ue28oaAiv+p8Y3BW2WMhTIa8KrAgOMig6MXv9+CIA298Psmw8J+6LwzKV7ZQp2/dq+pDmHjq2kaLE8DQM6pSiDQu5g2sTteifTzF16Gdz30NuwIINZn8I9e8Aa8/PIT+OynH8FvPP8VAIAXXnsaP/H3vx2nxyOcdN337OUU5gDwT179dvzSA6/GR+9+AI+cfwF+4cZfwjwO2B1tEI88jn59D7txnc5KWnqMU29snB7B3soD85ZW+bwYhrk5z9Q/dOgY9m0ZJAOFsTS7O6mTZYylo2gLOKpsHsqirBVPBefVAn/uBzrTzqVy0jbky/fg79iSoAXWJ113BLAACpughlQ3JlC6HPbiEQE1BasInkpQaUreo9ogKCWIAI6h0Jbm5EWh0E2nuSIao19cUt6awBhjSkxd5r5q8EMwo4qT951jV/2+VYyscmgVTMrFKO1oFfmyTbkaSCrQOedrdLtiiPpugfcR3i/Y22wxrFJlij89Y/j1EcP+Fv2pI3RvCuhfs4W7EuGeccBTAe5TEe5qRHduxNk3PgbsIsJFh9X/N7Whi2uH5ewK88EK494+dnuncOOuC9h2pzBKiVOYnB3cpgdxmfzkszFijDmsUg7f0k2n8uVdKR3Ui+vR6bwLAPYoAKgyHKgBqF6MEwc234ols573qBRCI4I0vvSmXKyT6LiHKDcue/NkJng8tJXVAgaolujRoYQsCBaOhfEEDGkConrm6mVpLN289Tz2k86pWeVwXmt01eumrGpIg6CJ72ksodyj88GqPZgjwL8BJeTCcnE7CjvWmfe6nqonuIZ8R64FWSn1VFVGlKL2rpRqajWcglJlwViW3XcLIP1OFKTqHNCB6VCcpTaplc8jQFnlo8a5595/70vwwy96Ay6uD/C8eAXf0f9jvOY3ruPW4T5+7sLL8UMPfDEu5rDFH3/y5/H26x+C9wE/d+Hl+OXxPnzz+/8JXnLlU3jwypN48ZVP4e7DawCA9z/wavyxr/8bAICnD+7C/rTD1c0BHrnrBXj4rgfwyIUX4OG7XoiPXXgAj5+9z975117wSvzaC14JALh3vIZPfPxBAKmMn8wNw4AE1JSXo2lV6U1+xpppOTmRt4t2fEBiCorTQhmlM0zgMHRLdRAf9TqdDt0rCtopu60zwnXss6w6lDNXuG4h1nl7GuZN75RChbbOkmDbylqMztIM2mTl9rpjgAVQJ7kpBa5niHCjkNEAauVRTslL2dt6UYlBlRqK4TU6tfHIdKHVe1BaVKmlrqGnlCHoXd0Pg/FgCgO7j+rBSYWNyAYqFmYnJeyUzG8K8tAtxvC01KzO10mCCtBQShLS4sxwTLOzRKXtbl280XyvYZiwXk3wfsF6s8Nqf4v+5RP61+zgVxM67NCtDuFvLXCnHPzaIT7kgScD3FFE/8wO/TM7bHADAHD2zzyJ5YE9zDf30X/gEP6REdOpNabNPnZ7ezjsT+PWcBpTXKOXXhCcz7jUNHwFxvJy0jDS+LGES4FHojlLMml0zpLqVIZZKdDmF3AuIRs1NjJVciRipYSUtbLn+NIpj3uErJmGIJwPBqyAdCBSAV4l0XGUiquuK0aeRttyj3IIyguo4HwqILc5E6OrBpSgx0slDxWogjGCoVVmLk4COdW/XTkRloCZ+kOPBjDmCfVetpLNWIxsy4i27JRerUNEHcYSSI6fnzXWVCrIbJyxTtgzNiPvdQ3r8N3L4WHlPexEYplX/t0Mh1R1kcHQUlK+36qb0fcLfv7Cy/D9L3mLMQ5Purvwl5c/if/y/D/HqeEWfsufw1d+6BfwwNWn8cDVp/CSq5/CE1/7Qlx/wT7+zvb34b/5qf8Ff+JX/2U1d0f9Go+dux8P3/UC+93UDfj8P/cDuLHeQ/DHTdbp6RDjAnsPAFgtE77+ifdhnJIMRLiqOkzb8y/BG9CmoTamOZa5sgPIgGPyV3Xt9KHkCYou4ve47ywELWtC/aHPSIxqk4smDISFVKSiIyW7l5wvBflk7xTE6iGMfAaZD2O7AMyZ2bld2gCvOwJYaP4CUZNu+Jbi1Xhim+8QXV3jrJ9TlE+qij+39+LPnQgBojumEFqw0flgaH7oFhzmsEfLvCidrahZBY3Ilx6S0Vx9adNNmk4v7bzI5/HdKJD23o2nZd+LKZlLww28BwEGq3nIGtAjmJfUc0OBWtcFDP2UDtByEZu9LYaPT+jXI4a9LbrfP6Hb7NDHI3TbLfy1Be4ygGcB/wUe/u4ZQ7gG/95D+McXrHETwKVq3PML17j++1+IZRwwHa6x/vAV7IZ9HA0HOOpPIfRZycR8BL2UaR6PM6YYMGlPrpN6/QlAFCajvVrZMKPZfE69iHRGTqqiAVLuj3dR+kMEHI5r7K92CbAu7FNQ1tY7Hu1eAAbDRaa0GsVq/T7o3Uu4TQEZlaiGVfh5ZQk014lwSPdMZG4FY/vi0RNAtd1gLU5s65a9tOZcCgPiKPlRiysyzgTENmykilxDiPTi1MCWPA9n63JSOIzrroyazmkLLDmXJ8kOL8qqhV5jCU1o7B4OFThwiDWL5SI6FEANpHyKX7jnpccqLN5y+SO2Tj1G7M238Ag+D3/wt9+Nm6t9/MvP/lIAwIXr1/Cnf+AfwCPincdmAvjBy/8n/PT9X4QtNvjZl3wBjoYNHjv3PDx6/vl49Pzz8NTpCzgTD7FD3YBpu97gqy/9Ft5916uPAYg/+eh7AAA/9MAbLdnzHY+/H1986dGS80HZBI7pazaEW3Wz5ZCk9UoyoxURDHnzM7wUOGulk+ZrtMw3QQSrglh5pE6fOm20RbqvgbrBnbVc8Kjk2jVj5tkgrCgikOAedK70tFlCyaNSJ+K5rjsCWAD1ItGDUq+LRkrDExw4UEIpbB6jiLKg1LrEkYit7cKpYQx+X9GfAhTIM0w5xpJoOAi6o4Lh99s4LL0t7cVA5GuAADUY0p4YBD58ttLRGifWmCzjpC2o0c9onLntJsgNS5BBoba1y3Xd0wI70jdEh8OjvSoDv+sWrFdj6iq6TuemDPft0L1ogv/IDP/xGcOZQ/g3reBfNcFdi3AXAVwE3LMReDbA3zfjzOs/ASwR8dmI4QfrWuu4dlgOBoRTA268+j5s7zmLaRyAGzOWXYdxvcHsUle8GD1CcOgFZIYM4jRB8CTvVb1brULi3/j53pdOlEEy9r2rPXEafubCaMky3420OZv/0FiEUPIC+FkaVipV9VJ48VnKQBD8tuM6CZgTtAKyt13dE4Tgx5SW7KVKRvOl+1HDgYilvbU6HgQVXKfk+aXPIaLaF1V/nOiMBtc11f3aOhidq/M+dM0ttClzqEbFdFIu/ePcGAiUOJg6GXYEtyshE/2cgRhXAM1qNeJ/O/0q/MAL34SLOWHyG554H9527Xfg/YJfOP8Q/vnZV+HBZz+BW/c+hGfXZ/DdD34FvvSTP4fXfPQj8Ddm+MO0Tv9v/DoA4AMv+GwDFk8f3IWp6/DsqbvwibP34omz9+Pxc/fh8XP344lz9+Ojd78IN8d9wAHvftnr8e6Xvb567/Uy4U8/9h6E4PADD7yxSup887MP46UXLuKHX/TFAiB+EV96+WOYlh5vfPbj1YGBAQ69L155xYKJvksG3Rs4pwxQ9tjCWh3C24XHeTF0xmeorFGOGIbWdwJqkKI6nA4qw6/t9/jerY3RShUNBauDruNR8Gt2MpQ0gZY9Pem6Y4CFcxFTpnIVrVt7VzXcoZxaWClDmYBqg/uSH8CkMuDkXgWMgaqxVTprCaUNNAFHAhMljqpnMPCMi+hKDX+i1NM1BX9M4DUTnCwFP9MqkKohVL7acx10Poh89XmciwrVNkaBG0SrH5SK42cUsOnPfC9jO2IR2iV4THOPXT6Wl5f3wZraAMBmvUM/zNjsHaE/O6K7sMC/ek5Mx94RvJvgrs7wexFu7RDe2gGXAHcxApcC3C6i343ApRHnvu5xhAc94q6D/18D+p9POR5h4xFO9Qj7A+b1CtOZPVx92fMRlg7z1GO5AYzdCtF1iHZqbCk/tLkIpYqB7Xrb0IgCELIO/H2boMtQhjW+yn0ZTJFmQOtl3TofTCmqIWRIh+Wamqug7ID+3LIWSs+2sqRypLJFEMEzXhRIKBBoa/0pd11Xyx7zQ9runwCMCel8sDbwTPoOmYWKviTXbaehSuh1PiIGZxQ5wymbYQJPCq2SU7ui8KkzWsYjRKkGyPwRP6chODK4P3vXy6uKiXc89n586aWPYcil6Ryvd/mz9NjHG/imT74Xb7nyETgmGcaITTzC+86+GN/z4Jdj51e478ZF/Ln3/gied/MiHrj+UZy/dR2vvvVufBu+HwDwB7/pO/Hrz38Ftm6Fj+7ux+c9/dvpmR2Auxx+be+z8PEzL8AH733I1mvuerz9O96FxfV40t+F9rp3vIbNdAPPrs4c+5sPAX/m4Z/FGy49Cu8C3vTsI7VMR483PvtxvOniIyY3QGHXvIuiX4oRpnGlvuJ+0Py7FD6uww+ts9W5kqCppaXsg8LERoJuXXvrYin707lorDDDEfru/JyCcWVLWp2tgET1tgIItRMMjSlr6V1Eexotn+vlXrH5e3vdIcBCQg+iwJbc9IeXHq5i3hYKumwxpFKQ6m3opKjSU/qKHhc/38aIgbrJVZDvaRhHF2joUhvh3pVsYsaslHkwMBR8RQUzPmZ5EKLY1HhT+NgK12hPCb8o6DgJhbderFK2DhFLc5omP9PGC/W4cKWKVTECpbmMboIQHbAAcUzU543DUxb/BWrgsVnv4H0oPTnWI7pXT+g3KVu92ztCF7fw2xHuWgQe9HDne7i+g7tvh3i3A65E+G2A3ybwscItxAeuYu8bLyOOPcJRj81fvQpEIO55hL0BYa/HsumxbAbcev7dODpzJjEeRxFhcpi6FeaYErwIPFoGY8nGgfM7Z5qeoGHdT+j7BctYmg8RhFDetNKCBitEh72cbLc3jLnXCU+zdTnkUk5xXOBr45pLBTVMVJiKxMbRSKocMhGa49QD6IbueBVYHbKT8lsUttL5zNDlsmkmKjJUyPsXwF8SJLXdsxkNlH3b+wWbobA0aR8Wxaxenu699moZUo6vrFWtzDWMxvdmKePPX3gZ3vWSumLi+1/6Vgz9grdd+1DKJULAahnx6/vPw997yZfisN8DALz9w+/D8z71Ydx9/YO4//Ai/OECd7jABeDRVwbsXpKAVh8CvvHXf6IaQ4DDUwd34anTF+Bj2cvf97l/GH/g89+LsLfG3G2wjBt8EK/D/2Pvj2HrSthiHSZ83RMfQFg8vufFbz8Wtvhjj70/3e+ht1k5Kf/2Zx/+Wbz52UcQnINmK7ehtUGYqLRe3kKT/B1QKiva0AEv683g6nN26NQBperKDlrj3goekCTiSoZFrlt5ofyNufpQm7zx/3wnfZ+TQvAQcKEOYozl8DfvSsUHP6v2SYEJbYDuE2SgYUAnVxF9urbedwSwiKhRGlDiTW0CYjsR+m9SRYkelX/nS2lrUpPM1K1iS7KwVE5FSUgJWXSWWd7JZGtmLalkoCjdylgjVslCgw/WQc2qY2SuyNzw0jMdvAgY5yLG0hKd76tKUjuVqvBzLhRwUPHzXvQEKm+YpZ6yHtxonM8QHXhiJT3tzh0HNxafzB7uvHSp5DKHVxC6pLSn3urPTR4y6Bj6CVM+7ni93mG1HuG7gP5XU26H7wK6l+zgXh7Qrbbw0wR/NMEdBribEdh38HcD6CO6WyNwAOAG4A8D/OEOwM6eufm8q1hes0bcDfDvmbD6t7eSbO95xE2HsOmxrAYsmwE/+qX/Z3zv2a/EM905fMVjv4yvufbreN34KYx+hdGvkVq2C4By0X7+6bOvNCr77vEGvv6J9+FNzz5iCZdpXUplxGaYqi6oXK++W7CduqrMkH9nQyoXc2In+oq+j8hgJDoDIJQB+382qgrae7+Y1tG8Ej0DBTlE1PlyT5/lgNUq635KTeJymR+/r+GBJRsWJmxG2dd8T2UCvQ9wmRZ3iPiFu1+KH33w9bi4PsDd4w183uXH8KvnX4zLSsNf+ph5yZyzEB1+7q6XF8p+vIFv/MR7AaBat2/85HvxtmsfynskYggThmXEsOzw8fhqPHj5k/jIPS8GALzymY/j29/3o7j/1kW86vBh+KMZ7ijAReAVAP6nb/saHJ5JwOItj/wKvuYj70V7xVPADb9vPz9zcB7/3du/BU+dvoCnD87jB8//DXzl+m/iE939x75788wZPPHw6zBNQzq5OHi8Ol7Bt579afzgA2+0sMo7H/9FvOHiYwCAJfw0fuiBN9r8vfPxX8Qbn/14epfoqwZY/8mjv4w3X3qkMtC+0T+82pATnco5din0jGAhJjo7TEBWBjrEnFMk8qmOpobiNZSgOTqqy7tusYrDTkqPKY/RlfAof0c92doKNJ9py47VDjGZmvqVicrKVuictfOp9kAd92Pyk8e7nVbg8fO3uxwR8v8/r1ccnI//8+vecixWBMDOA+Fi64A1PkpEOS691VQvDaJTBMgcDZ7DEWRB9FAnfZ82psxnhFhKehRhth58a7j5d9bpqyHnuJRt4fc1ZsY50Rgg78133l/tqqPMeeS0votevLcBuuArKkwvfobovN2cGqtXBkdZEt4fqBsaVadx+qUyHs5FTIucGiunBHLcemqhevhcm76nJx1yV9Lct2OYsVqP6FYTun6GH+YEQDY7dHsjvJ/gdhP8dk4A5CgCN4D4hg54YQ94B/cTM/w/HeFuHN9f29MrvO4/+0FsYzpU7r3f/Sfx/BsX7e8RQFx7xI3H9rXnsH3VXYjBwV2a8amH1/jJM5+HK5szuLHex431KWxXK/yBa7+Gz41PI7rOTrgEgCk3TnMu4GfOvRL/6AUltv7Hn3wP3vT0xzEME/7t6VcZlX4wbwFE3Oz3LL79JRc/Vs0dZfQ9d7/MEv0O5i0iIm7l733DE+/DW658BD9318vxj174pmOUfqGwQ22Idzfx9Z94H9787MN4z90vLeGA/PsQHH7kwTekceTfxYjq/e09djfxzifeZ/H3997zEH7ghW8yg//1T/wivAv2fnePN/ANGQR894vfXnnViBGQcNY6TPhzT/wk3nLld+AR0PUBXbfgvasX4ydWn4PNOOL07hZOj4c4d3QDp8dbWE8T/spXfAsAYBNHvPtHvg33P/Ms3C6gwXf4X77ga/Hff8W3AgA+/xMfwo/9wH91TJbiPvDo+vn4s3/4/46H734AAPDWh38ZL7j+LJ49dQ5/9/7/EcuwRtj0CHHAV7m/jifdhWP3uXe8hn/wO+/Cvz39KvzdF30Vdr5mE771kZ/GWy5/1BwBAriQ/83ft/pCjZw6F9rhkzoEKM5f+3OSk9qLb/Mm9DNteLYFCvo+qjP1VGY6Xoe7NTar0Y4O73zAdlxVXaGpV8elt/toSDzNVR1CUFuijHhra1q2XBOTW0eX7837V8BH7s01YphR147OJteO9o33ubHdYN3P+PJf/LFfiTF+4TFhwmfAWDjnHgDwDwHcj5Rs+64Y4//knPvvAHwzgGfzR/9SjPFffbr7kW7kxKyHdIoaUZ7GkzSGz8HaJC4NXZknaom1R2UK0rL+i/Fuz3BIDznes4CUGcvavEt5FDOchTdaxK0lS4YgY8k+BkqCjIaFAGDI4R+WrnY+VP0ZKpQfS6IYhd1ijNoAJtRVN51PGcNta2qNHfI5vD/npVUqVu4WcUw5kGkhqifo2V/tTB4MkftybgK9UCoMKgWCBM3bUIWlXfMMgEzlb2zq45DayKti8j4iBJc6knZLOV12mBMQWY/oLszoHl3QPTnCdQHu/gXdn5/g+xFunOG2AW6XvMy/fulPGqgAgN++/2W4eOocLmyv4fnjs3CHgNsFYBewef41rN94AwiA++UFF35sxmvwwRP30K0/fzfiZkCYeuz9+CV0T24RB484eFwezuALN8/gs1cfwPsfeDX+3hf9QXz3i74CF1b/GK/80Iexm2/gq269B9t+hW2/xrZfYdev8Fv3vwzf99DbsF7t8JUXfxNuDkDnEHqPnzn7Kvz9B78EN/s9wDncGPbsXS6uz+B7H/pyfOzyPfi3d73GDJVS+swB+Jlzr8T3P/jWQvtvTuP7XvI2fPTsPVUVwMXNaXzXQ18OB2DOZYcXN6fx3Q99OSKAJf/uxrAHxIg+LLjlB/zQC16P8+EqurDgX51/JW50K0TncHF9Bv/67GfhgatP4Qsf/S1s5hGbaYdb0yEOpiP80es/hR/4vK/hBsD3/NO/jlPjEfanbfpv3OLMeAvnxxvYffk5zK/ewK8nPPX+l+GH/81fOnGNAOCvffmfweI7bN0KV6ZTeP7R0+kRawAHDjhw+IB7JR49/3z7zsMXXoj/69f+l3CngL91z3djGVaIqx7B9fj6pQYLP/PSLwIA3DddxeMPvw5H240xqu88/3581wNfeSxE8Y7H349bh/t4w63HMM0/jR98YV1h8caLH8fsSk8G7fvDUBwvZR0qL1mYW83PUqOnjLJvdFAqoUSVRE/dr+E1zTEzXdDPlgvB76Zco2J0rQ0ASoJuiKVfjgIQNhXTfA3qWd4fKI4bczK0pFvz/dpwBsGQ/s0182GhU0kR4PwxP4/3a8PWajujK0xycthKSW3Kz3HH8gaf60wT4DMLhcwA/kKM8Vedc6cB/Ipz7qfy3/6HGOPf/ve5mRo+vdrJtOOl+9laCqsXRS813bSc/tgmxGhOwoz6gCHzrMPxEjF/wqbRPIiAFN6wUIJUrjApRhfc6stdrIBBiKkscQkprr6bB6z7yWK03JBWRpg3CT17gjMA2I6rigKkESeypoho/I3ARTcuUJcFuuZ9nYtVaIWn73F9dawW23Sx6s/B55gsCIOjm81O/cPxDohcMz0ZlnkBZDrSWMv5I8oURXr5nNeQnrnbrTGKDLWJw2waFkI6cj5VueQkwm5G1ydG5B++4msrmf6WP/x/s+d9cP+Pw8UAjAv8LgBnFrhrAPoIPN/hb37ZN+HM7jB5wvL/g90hXvZFl4HVCISI7l/u4LYB2KZ3vBcXcS8SK3LUp+6qW7/CP9t/Db7hAz+EL8Cv4aTrne/4f+J9D74W/+hFb8S3PPIPMby/dD98Bd6Lb8X/DAD42F0vxFd88/fa3372+/4sNvOIxXn8Rd9hcR7BOQTn8T1f/EfxQ696Pb7xrp/E8NhN7P3MR/CV7l9WCasOES5GvPubvhMU0P/xn/8tvOapj6ELAV0M8CGgiwu6EPATr3gz/vJXfRsA4LOefRQ/+fe//cTx/An8AP7IN/xN/MoLX5XG9xv/Bn/qV/75iZ/9yIUXFWDhHN72yAewmccTPzvcd4j+82YgBHz4gw/iV5//Ctxc7eP6+hRurPdxfXOQ/r8+BR8DuOu++Q/8t3j3me9A6AZEdAhTj7h0+MjyOfiR9Vfb/a/tnca/eeWb8F889S/x2GOfhxg95jntgXce/BK+60VfcUI+wy/h4pW7Kkbvzc88gmlK4YvLmbX5usd+CW++9LA1V/qSix/DG55+1HQJgKqBH6nyeS6t1S3cKwxly06maayTbKuqNhyvvgG0qq9pdIgCLjR02yY1sseL6tkOxSFdgrdzNxhy43u3oZQW7Oj7ncTm8vc6/sohE104ZZ3auSYkEks4Xp3NFsDRBuhZNLQTaltYHNCOpc2xM8fVp4KE1qF8rut3DSxijE8CeDL/+4Zz7kMAXvDc3zr5ckBl+NI92TSmab0M5HLAgrCI1FoESnNj6JjoUpAzULpVdsyKvc1GUMOrseTUcSAtMM/84HcUSAA4FitjDNi70vWxNVpavqpeAoBc/ikGWRo7WY6GbBALSUj4QcGZzpc+h+MhM8N6ae1UyaQh52KVhX3MAIvS4BwO3YzttKpa4pKKAxKQ3OXxaF4HQ19LKP08KDdAyRh3LlolhT5Xyy0VeJIlsdAWasXAz8VYKjgSECkNeWJ02O7Wx6jYC/ffwMX18az4u8cb+Phvfi6ci9boi2Ck6xd0qwk/9vqvxFPd8Wz75+Eifup//4spmbFfMP+xA7gwAVOEDwve+am/gv1xh71ph2cOyvcfGV6A7/7iP4K9acR6HrE37bCeR2zmEetlxKX99J5P4S74BxbEj6aEWswRR+MawzJjCMuxipf7bl6+rRE+u72Jp7tzOPuln4BzMz7rX5/8OQDwEqp93vWLeOnlT574uTO7m/bvxWfA6DymbsDU9Ri7HmM3YOwG+zsAfPTuF+GnH/oCbPs1dv1gbM12WOOpgzpk8O2//7/G7Dscrja4NWxwa7WHg/UR/vGZ/x7RdQi/0SPOHh9+6KX4wy/9ztuOSa95s8Gjv/06LE2fg88J1/Bt59+N/88LSojmHY//Ij7v0pO45s6g7xeE4OB9xJueeQTj9DNVKOk/efSX8YZLj2IMySCOIXucAfjiZx7Fl1x82Jg/lidHuLrCRlhcNtxrS53V4LUhYgDmyJgjIfqETKeGY1XfLJk55d/b3IrW6eSliefsLFk5Jk043caRx0JdSGeIHUr5PJ6tws8w909benMcyk4ro6A6Sv9OkDQ08wwkW8ESfeoezmsbqm7ZD+YuAXWZdXpIfbimOtJk9BUkfbrETeD3KMfCOfdiAD8H4NUA/gsAfxLAdQAfQGI1rjzX919xcD5+72u+3EIAXNj2pD0aG2UKKDA8PElj9naMLJEoG6E0R5OrV66orJ1Mo73EUGvcS2N2vCcXgQu+yccxW6KN5IRwA+u78dL6bBUqxvU4Vr009wOo8wu4YfTiJlAarwUWHD9Zj1UTNuB7qPHVeWpzQXhpGEyBSPue9KIS4g7WRXKJ3uKebd5H276Xa8WkPn0nhkT0+a3S1KZQurYGRnMTLcahted/jOmMhL//8i89lhX/LQ//LN565XfsXVQ2fa6KePfZV+L7pFoASLX//+lj/xveevXDaS772fqDeB/RDxPe+eJvx9PDObTX/ctlADgRrOj1PFzET/m/mFgfHwEf8fbd38aTuBuIEV0MlcG++9YVdGHBKkyJOQwLfIzwMeDiqXPYP7XDz1z4T4GjgG/++H+Di+F8+qLkMTgEfPCehxDyfV947WmsMwuy+A7B+fxvj6Nhg5vrfbtHKu/11fsDSO/773CdCTcxYoWtl0ZNt8mx+PJrHzKDEKPDz5x7Jb77wboiogszHBxmmSPmLrzt6u8ASA4TryV4A7adD8aeEbRqLxUAZtBU36lctvF6p/owt6buuwW7aahYRzXkygZa+DX4JG/iiC3NOOjEtEnnwO3Pa+F3+RntVlyFKUWn8f/c47QJWi2iQEK9f9oQ5t0xrDEuvTl+tEUMnepct84T50zHQvsWosP5gxvYjcmR0nw4fl8ZByAXM2RQoX+jzeBcMFeQ79QCDZUJBR06Fl5tfhvlm3bwbe/78d/7HIsyie4AwD8B8J/HGK87574HwF9F8g3/KoDvBPCnT/jetwD4FgC4b7VXDSRGh93SY4VyVHKISVGHrq7UYN+KOXTYTkMlADQw/N1JaJsCyb/pggRJglP6nj+H6Kq2ywy5tIk4rDxRD5k5G+t+so3A/AvtsmkGBs5AlbEkrk4yUgQ7LZ2xNyawIvwnJQmZ8KFGtdy86oUQcZtHnz+nwOikebodXXhSgtKQ2QllVJTNYPti1pWTzdhOQ9XfQ7tC8hlLSIm+nSR1JtmoSz2BclQ7ZUdP7dT5UMChG7YN8b354sPwLuJHX/xFxxIa4VPL7RiXyoBw/F/01GOI8aerngXveOz9eOPlR7CNa0Q47EY5kCgfYPZH4wfw/S99yzFA8o5Hfwnex2NUul7rZcI7H/9lPHL1c+xdAOCdZ38Z3/XgV2DnByyu9mIunjqPdZjwlVd+Ez91/rVVMuA6jPi2J96NJz70OsTo8KbTn8Dfed5r7YRKfuarrv4mPooFuxw2+MTZ+7KBLjkWANCHuTazru4Dsl4mfMMn3o8QHb7rRV9ZvQu/u8j91suEP/XxXwCAqknT519+FL9614urpk2vv/gYbmK/Aspf/PTHMc0/W1U9vOPx9yMA+NHmKPAvfvZRTL44S5p8zLk2hwbiaUdf6RPn0gm28KFqEKh5T0AJaahh18RxDcnyWnUzjqaVgQBWBuneJWRQfQKkfbVZ7ypdq9402RILC0AOWRTKXfVzy1xwnugw2dp2S5UAriFxDXcAqBzatlS6BR5FzMohb5wHDVeQeeBzNTR05swNXLp0l+lvdUoVpBTmZcHiYnXfACAsHSaOQ8MnJ1xk9LvmnYFsG8Qu9vm9V/1cgVaWsbJD6W2f9ZkwFs65AcC/APBvYox/54S/vxjAv4gxvvq57vPKg/Pxe1/7NgCoFOLeMB4zKDHWBrbvFmzHFabQWbkXNxoNEIVcT9fjgrLbnXbxNAE7wbAqU8FzPpRN4fP1PpohrJtCQwJa2cJ78z7j3BszwbDBbs61ydKwihUVatBa6rB9pl7KyKgn0DI1Ojb9rm4o9R5aA0uFopnIXHcL+eS5npcOp9Zbq2rRuWvZoiV4bHLFi25qejwtc6Lv2jJinFt6Lt0Jm1YNwEmszEmxV51/PZ+Eyp3fp8yz/wQBlHogQzdjWnor/WKVTHpOfbBS5wPed89D+OEHX28VFu94/BfxZZc/CgCpKuPBN5TqjgjcGjYGXN565SOVZ5jG6PELdz9kVRttVcg7HvslfMmlj+E9F15WGdl3PvG+BKJQmoHpffjdL7300aq9NL8LoPrsOx//RWj54vH3/yV82eWPoPOp+sTAQp4DwDXz8n58yaWPHeuLUO09SV4ke0ZjVXmebHqG0g5ePUQ1YDG6Kpynhkz3Fw0w94Q6CezQ2ir+1jgq66r3pg6jdz0vHfbXu4rN5LhIky8xHdPOsffiQfP/uq/4uXYvtmxEq184Ds1NUMdGkxiVWQVQMbdt2EWBmDp2rb1Q3dOGgFSntnq0BRyt06bt401ufDnMUOegBW6tQwYUlpU6hAwLL2X6VTY4VgVZ62EyR31ogNpb3vtPb8tY/K6BhXPOAfgHAC7HGP9z+f3zcv4FnHPfAeANMcZ3PNe9XnlwLn7va78cnQ/YzYMdcsLFaMMJatxJv6ugOlcS+o5y4qLG5XlxUXlPoIAPFQZOfGtsW6pJF1GFTRGpMh6t4ZmXzo5qbsMFpOf0PZiYyGcQ/R+NK0uy5LjZJKUV2hYM8f78HcNALWXZAhVlilrPhPOqsdaWfmsZG87RvHQGFnTtaYzZxrpt477NlC6fYedrSGkVx8KNztCbjq0FCbp2/BsvvkOrKPRSGdQ4qs47gCpcQ6/SjrrPrAxZKsaRt/n4apYDTlledC11rFxvGgr15IASfuN5AtWai2dpnpgAJbI2KucAjhlXyq3OKb9rsiNJhL1fTEeoYVMgpsAWQBU6U5nkMwlE1XCE6KqzIyijJ+05XvreCh75N8qWypjKQktbc900RMh9rxUI+jw14pQpZdt0jxCsKqW+nQYzKHTi9lalfJ/vvhlGsIqKMqIgW99LnS/dM61xbIGFGmYtsWyv1oHU7+oZFzwaPaJmNhRsLcEbQ2Mgyteh1ZNaZKuupA7sxeYwL4PjpUPAEP0Sve11Y7kzeNQQhM6B6lJ1MhU4qbxp6EfnvZLXPFaGXgYJi+l8xuieE1h8JqGQNwP4JgC/5Zz79fy7vwTgnc651yGFQh4F8K2f9k4O1aLSo1VvazcNljDDqgigIHmd9OJRNZnGqL1M9QZut0l5Xy4gz7FXpWChCaDqommb2IdjSkrRKmOB3CDKzFDwPJVgdBgzm6PZ1+Wdg4UEyGpQfEj9q3JhqESBEOdRBVLZAcaC+24pLcllwxP589/qgbPEiu9g654FWEEGWR4qfhtrdFgINCTBUmWhTX5qW6HbOsdiAI/FJ/P7szpHPZRq7aOrNj4Vj3ocLVhxro6Bw9c5JzZvSHHetlMpQ1cEHWp45rlOGGvHvO4nmzfOPXuHUKlwPZT94dkfrcIzNtEOACwGpu6QWIfdWGrHY9qDfI7fHZe+ov31ijGVyrFrqM8yDqQmakZl54O2OHd28BICxlBKy70wfut+kn0XjA0ia2hMoAAp7RxbMVix9pSV+ePntWKKyptHt+tR2J0rzkzl/NAou3L+BeWQYUPvUvJ7C9YV5LWsJEvCaTBZuq+ARMOoJaST2QAf4AU06Txo11RzWlADqzbkyHdsGVk+m6BTwQJL8hnmaJ0fBRWqm/lM70oHYX0XoA5Hc09rbuBAZ241mgyzN1MIKfl96Gf0seTDUferY9sC0SX4pLt0bpw/ppvgyonadO5atladMnUiW8Bk+tD/B+y8GWN8D6hB6uvT9qw4frNyvgUAO22O/way1yGCPy499vyY30W8+4buU9ChF71h80YF7QI17bSEUoOt8TLPCoUTEqu6LrEvXDxV3CE6E4pVbotMxUKD2HVLYh546mTOOOZx0Baakfem506l3LlgLAH7gijwalkeVXyWuyCsh3kemQloGSBdQyrr9phhbkgm2qrSY54EUBSoHsJGoKFJuarQEkMREJyzjQfAcjUSKI1YlswC+cXOn1CjpcZY46KWT9OMm8BSZcvL/ytPVLwgTRRVcMc109DZElL5sDZTo/dO5UlPuu2DYjRsLOV0ZAn0TA1lyZRNU7YjCKjzLlreDpkDBekaYtI5UsVm5yPkfUOmRcsb56XD/mpnBjxmA8KL3RYX+Gqvp7kvPV5UeSaQ3pmMprEoY1ROuYQ/XqlFB2AQFoRVFBAAzDbearSq+XYl1EsdQicC+f2di9WpszRkOh7KEOWCTCQrFdKYOjOS01IMV4ypR82U9QoNHNeOxuikQx+B0otBL8quAgOCzLY8XOdEc9bse67O3aI+VgeO499f7arfAahkhfOyGaaqIkz7NGgI1/Q1akdTGS0+b9XP9UGV4ryF6Cz/hWNQoD3JXFEOBplvPShT+x21AEvDRBY6buaD+qcFZcpOm80LpUGl5pr9H6Sld0ms3E4rK9mkYKdFn0ur7FBoIwRvKJcKTOOO9oys1IlQd9NQUUlAXULKyWWWMD0pUyjZwHFx1TtjzwmNu3Eh9d6MqZrSEuFY8iYvQl6UplZiUFlQqI2672pvVb0hPS1V6Uh+hiEdo+RkQ1WhjHxvFepelUTjjehFMEbKlfkqgxgafnfJ6z2ix7R02AyTGR7NYp+WDus+GLOz6mdMS2dhgyV4UzL8PxVrjO5YWRXHFzII1LlSpQzU3VB5JLjSlG1c1IyR/J1/A2B7YFx6DBVjxPLBVA0RYkoy5nPGOSXZEVys+hlTTmYd1VhkoHs0lqQ8APC+rHcLzFsqPcoYq2ObYx0HblkbXpw/7lWe8EojG2JJcCZTQIPKip50/0LRazhqlVk9KkzuA46JoMLGk9uUj0uPMf/dDigTABJQSt5b/aFhDrIyJzFHyjpwnqgn2jJwnfuTwovWkC7rv908GMCwZnh5DtZDodtN7vM6c1743N004NR6ixkZgM19afUue7sab/DWe4bG1hg91CEqAglebVhax8k9EmPp76PGknqKwFtPA24ZGdoUW5fgMYvx1b8DqPIKOB4AxtrwPsoc81kKTgjqYizVdC2To+wTdaLKDmVS95Q6i7x0r3FdGQri3w2U+GDA1TfrOsr+0KZbrVPZXncEsKBBnpdybgEFp++WajE15tVSUMiokPQdJ5R/71An19CQclIpBJzMVe4loElzXET1MHasUJByIhouKl0ePMacAI5lNw1Y5xJUpTCXkJqlEAhoRnMbo1WFrwzBvHQWPtLkKyqzNiYJFEZGlY2xOvIszmHn02Fpq362zaKhDD6zZRdYybEZJkPjnQ+mxAkAuflC9HaglkMxDqfWWxyOawNXu3mogJ4CB1708IG6DEsPLFJKkHLSeuP6XVYQ8XnzNKTwmA/H1sq7WOWcaMVMpTSyB8xqqO24SudZ5LXjO2o8lt5FYReKcrfkYHlnAoyyPr15sPRWdvNwLMGZMqTKmGCRho6f40WwpnPZdzVNroCtcwF9X0JhUfbdSSegqulmKHDVz+i6uiQ6RIfNMGGbEw6NJo4lrBNEoXM/ck5X3QKfk9pUL0R5d849/4YT9oB+j2N30Zk+WkT5G+uEusyQeUlLKInL5skK2NPwFi/TiwIeOc4EqEqVDnVhe5R859K5HGpwdNxt+2kA2Eo+RGU0hXXjuzBUrGELPof7Dch6K/hKrsgWIbMu62EyZk1ZwRBLK2+ypPurnYXMdtNQ2JxuRox1xU3r/atu7ADLB+N4W11AudDk05q1qsO9C447a5pjomCWPZoAmDNOp1rlaSsheAJ5yjYdcdriFuycdN0RwKJ0RizCNs4ptkrPlKWNnatRGP+vJZp7q7Gmn/M1CgCw8ANwjNrWSxMOgZIfQEHp/YKQ4+C8NPlwnEteQ8jCwVNHOx8wZKVPNEglz5MjZ5cMFj0oKsEleOytxsrj2+3WWA+Tbe7NaqyEnOOhcHJ+KCxUVhoWCFl5OB9zGWTtYatSVKWkG9xCAvme3CDJYCzVmnEtt/mwI86jJmOqN1aFc3IXTgVHVTxcZIFjdi6W9eF3UBSAKgx6hQXs1NUefIZ6LhqztRCJAF6uibJYITosvlClTNqlEVYPqAA/VN5rKpPLvUaaihI+JzFXW3tPxnX1+GbvIg7WW1tj/o5N5NQgVV6rzKExgRkAcTxqVHkZY4SSe6EGW4Efe8A4l5JJd7kkkiAKSMnbLK/UPcZYN7PeeX7OtaN9DH7Bfi6R9C5YKIQJi0nYoh1eqDkGlFdthKfetc4H55Tjpt5TQ8+dyPANZXIQ/ce50WRdrsW6L+yerbNQ6Xw3slsheKzyXuRJuppnwXsoUCDdzjkYc2+ZVTasPMlzFtAWXQ08bQ83c6n7Sks9Tb6yPDE5UsMEnF/u7UTv5/sKGxWjsy7F2r7AZ93Av3c+WL8PDUkSMHM+6eQqk8PL/m4DDLYX+XfdF6pHeF+VD/5Nc8p0v/BztDtgWFkYQALtJXhMmdngxRA6ndv5BIB60nVHAAsA5lntpsHQNTdEjCkLmXFBUoxE+BozWkJpP0o0al4E5PCrRjHH5j5AnTikjAE3gdHH4h06F7HK97TwAgVF6DIiUvXe6OnTo+f4l+AtWZPKlZu9paQ0fKLvqEmJVFY2lzQKjQLk3Ggc0bmUDKTJYmpwlCUiELK1ESo5GdlY5dPw+1P2pNnKfG8YLRRhhoylqijxVXo7nPNp6TDNvZXLKZXHOLSGKjhPDBXpBnayVnxeayRUls1jUQ9WAA/lnUqdskaj6DOY4mm3TJ5cRLb5XXrrqiTIRAAlrMQyydtR7XwvgmkFmy1Lxj3IuTnp4piNQXIpsVPpXKWo2ytGZ3kQ49xb6aOLLlU5OaHvUZiZQeaXRk2NkgJ0ygu944P1tjCgSKFZAg/mXSjr2OqVCvg1+Vd8FudemUAFi7p/+Tn2FShOSwnjUJ/pnj/MTgbDAuxsS5k8HNdV0iKNZehrdm87rmz/UCbm/D7Rldi7sjFa1Uf54Dsy/KmyRz2ozCLvl05uLtVGACyZWeeMTlSMzk4D1tJZNbKml13pCaTlw5zD7TQkeZJSVQVxCq5437aHCAAzypxrDbFyT+l88Dk6BzE6QMAEIE6vyLZ30UL+QMplU9aHTq3Pc6kyQN3Bd0OeFx55QTndTYM14LvddUcAC0VnU+gwAFhE0BLVlw5tUmS/txpxuFubcHc+2ER2LhoYoFAThXIBqUAM1aE0h1JgQDqxAiYocfVZAIExIbK4Sl2qkiMCJc1LBafZwfy/UoHa6loV88HmCLd2G6yH1CmO8XPOW+sdqqfc+VAS+bgW4qEQycZYvAcvG8IMo3wHMtca4nIuYjNMFifnfXq/2HHY/HxKcKz79W/FM93LuRc0xJthsv4OALC/3lVzT5lSFgCAZZMzyZP357hI4fNSup/jqsCkAMZKgfoSYqIM6OamfGlWP3NKTlpDgqV1NyP2NXvEdee1NxRWSE8r5PzqO3HfeMfGX3XeAD3dvlsw+BIuW0RWW69LGUbme2iI5qTPcj8pkwIAp9bbHPYqjEIVLgglXBdlfGQQoy8dGtl5kuCn9wsOxzVW/Ww0MOdFWRjOpTJmsWlwxUtZtJPAma178NUZRWQDvIsYGoN8LEFSxry/3tlz0zj7Kll9M4zHuhwDNeul4FpDgwq4C+tX9xtKTGd5T67hSb1oFFQr0OK7lSPQy1jJMPA+fB/NIVGqnw4VjX8r60fTyg5AJBjl56bMjvVxqe55EiD2LoHm3i8ZDJYTs1XG29YCylaTdVHGVtkhyh7LgNWR5r0VWHNetrkNAfdSiA6bvPe03L/zwWSe7zkzVy0z/qGR7/a6I4CFUqiDJI+xhlY9XypYLgKpTG5keqltbNuJ4OuCDd1S9YjQ80SqCgtfEpu6vABcNG7utuWqHeU+91iLcVB6Kr1zj1PrrSlRdo7kggIlgWgRMKAJg1QeptBdrIw/lRY7gNIoqKJTY7Hy6fyHJaTk2OT1LAaaqPRbRanom+Oclw5jPH58csixWYZ5IlxFZeom5qXe9qpLrav7mOLpZT56W2fKjdaI8/0oEwyHaEMcNc58b435p+/VFSXepYoZvt+cm7a1bJiVR7o61MLv2VrkeTdmBQkojXOPgBL7TKGiVfGMXCm7I2XLMZCiVQaKz6MHGmXcxrBBDmmT9TiRyhYF6mUsBNsqo62C578VaHUiM0ACqdtpVZV+skJG6V0mBna+lK8DuQLFlfAa50AZgY0YLtvPXZ3Dw4OsuM+0B4hS8EAxLNV8y/vpPCzB2707nxN15W8pEbeMfcgMhYbuuC7aF8i5iP3VLp3Jkw2G5ngBMGPVgiPdd+u+eLWLAI45h5cWFys9Z04TCnA0ZyQbNQWhdA60zJzPZvhL2QoeqqXGm7pU105DF4swk/w89zWBvOpW9ibieyjIV/0XY2pmd2u3qRqLKevH72j3U76HFShkgEcbNeQSWuaHcOzcn13+dwx1SFIZdtogrvsSPaal7jniUYMJjndeOqwz0FZweLvrjgAWADCFDn1McfPBl1P0Dsc1DrLR5YCYlEhDqNeqW9DlzUHUpfQ3Lwq+NjNSL87ea6kbyOj9jOITj1/BjGb1di5gk0HQdlqZsvY+4OzerYSa52QctuMKO3oeq11VwWAGPRuczieDuO6zN7NK80OFQY9fEyqV/eCG5/018Yu/0zlT9LyV5loU8sEHq07hXJLO3M2DsQC6burx7abB6O7Opd4IQe5DxQqfKhvm8bnLnkiPcw5V+bbxWw1vKCJnoidDQtYemWCUa+5TdrVDRHTlrBC9ZwweM+o+E6oESOGq98JYN5UdlSvfn/XwHMuYs/dDVpa3dhtshhGxYaZadkCBVr0HetsHbRm3nm/BdVfmJQBVcrRzpX0+laYpSdRVBpxbMyCUdyrKfjJadn+1s3fi71R2j6ZVMdQ514q5F8eYvNBVBte5WIWWKBvKwDBngHLViX6q4t+hVJvoPgixVCUVh6MYJc6HgdFYytbhgzlhbYly7+sW+wRk7PRJZooJlcogTALKyfLNS4fdPJTGU77kvqixURCruVUtWDEZFpCVmJ80H74rOTXOxepcJT47RmehT2UR1RFaeAKr2AzvApjFwtwJC/dkG0PnhEnwlEnVpfxd54MxHwwVcP01KV8BrMmchGqpB/h/2hHdQ2S6Wf2iTduci4iiDxQIcL4UVPH5Gi7nuDfZlk4oibmfDlQAdxCwoPJm0iLzEph85FzEqfXWlPmt3Rp9lwz2qfUW22lVtaFtFaCyHIr01JvipbSqggp+R0MdiywSFQkV5hhKD4jSVtUZ5cbn8yAtPo9CDOREqCzEFGAKk8a+Dse1jY/Km14cUPcpUCVlJXSNclWFrvNBD4HvR7qcF40fn2kAw7uKEeDm0njdiISmSb1HpCTW69t97K92tklv7jbVwUCcEz571c9WqXISZTt0i4WJqjBFY2hnGlnJ3SDI4ebWJjL0kpShUC+cc6rJTwQfIRa6nQp3nRNUmZ2ue0UNJJPQgJzkR1lfOmzHVZkrnQcfsO5mq6jhGmpSLBk59XpKblCAG+oKAKCO2ZoyzH8fRNlyrrWsT+lenTcqu81qtCRG7gkyk+wZw/1GEN/9/9j71yjLkuwsEPy22TnnPvwR7uERkZEZmVlZlapSqar0atGS1kDTIIpRMVIDA8O7eawFEqKhgJaGGZ6DaGA1AwPdvEE0LOhmhoYGMSBegpagRTNIQq+SVFJJqmdmRmZkRHqEh7tfv/eec8xsfuz9mdn1fFRJqlIG0rW1MiPC/T7OsWO2be9vf/vbErFYTxW+haZQzlazvPZFUhbfY0oHVXCQI0xXeBsxaYUO0dLLPBt+Bp322pHZ2GOxKGPGVDhC3GvUWuBr+Rw4t5wXJ0ru5txO2wHONGxqvYbGa/uDebfO884IvpA7I7QXjsOupZuAIjxWVyXVyGttP2IqZfmXHfUasudn1CmFMfgNoad6fV22UU6UiJptgK1nrsP6UK+RUM4v18UwFsQYKGgBULpP15V6tB+zrt+wI9kBDg3G6HGx1mtfGnKZ5yA6DCgohndRkVf/6hbyRURuM2XJOaW9qe+PwbezIOKyDeRzkOp7sn6Q20QwauIvgFc5xK83HhnHgpNDNjaAV10863CD2yTfMBKuoXka9xqS5MLRsqNXK83Vi7hzrP3d5CFItZnrISjS4jX7nGU6jde8bW2ka34FUDYoc9VAYYPXo45IslxvNY/cvGR092ODaPBWLdDkJOXFlQWdLhkMsudpwJlDzxvPPF1fLeJgcJu3fOMQfDZul/OwEYZycLG6mMvk1OkzNVZLHwDYrKVPpUKDipJLM/q1p845r9NURLR46NTMdhpizjfXUN2pkffDQ72zw4npuLaCDrn+eGDzcKQ+SR1dAYq2LdHBS8y52Nqx44Yfgs+VD+fr6YZyLaBcJR6e067PRDgAG2Q+Pusken3zbo3oZeOw5poASjfNGs3hQVcTCTl3NYrBwbmuEQqgHD61/PJgaQs+6zq64nNkmqLOW/exyb1mUpLMnWB6M19z5XgCm0a/tg29ra26osK7mFVt67JFBhi1HasPjryGgYwghFii01Q5WJlb5SregC8l7K0v+h6q3eA3Dgk+O2fRaGvXWcvCr8e2qsKLOF9PQeVbTRH0uQSVKa/6QIWLcBXKU0fy9f3niL1yJGsUtUaSL6dkhmod5ege6rwtkzrRw6hVIrS5O5PVBjnz8rPl3KzGJldHcOxNlwjR4WI9eVVVCh2Qeg0xvUdnvka3OR916ok2od7bfH1dkch5qCtzOC/8WR2QTq1isD7TavSDn8czhNfG1HEtxMhAvV7zl8+ky+ORcSxCcoY8lB4IIboq0tfBKDc/SKfCLXxYOWK1jV03LOOh+ioCkS8kqBqGrB0VjpqJG5Nko6ZSty6nJEamIswok2xKo8hRR2k5d+aLJgYPlboKgBu8hmZpYEnc5LUxom2smdXFegLnSlqGi4QL5jJ7PqdeKi85w782x0RsaPQBY177YnTcJQPLZ8l76poxk6vqQzOnBEi8NT2FelPlfKVlRernf7lcmNd20U8waYYNFKcW2yJqwvmpI6CYNhXq3KV1VZPiiKAxeqhRnBoNCmMpwZy2feZG8LlQdA0oYm+1s8bae84JI1028+N6Sk42em9kHYTqemqHqka4AGw8R+9KbwIat3otZPTu0gHHUQcATorA08oqw+pUAK+Pa56oZr03Oz8WvYUqaGBemveUkuR01OVriUmyPanRyRrpqZ0Dfj8hev7MwVBEiZm3wPuh4B5JdroW3EbfHu439v+peV7exey4c9CZ9C5iuVbbUFDgkNd0vadrDgFTPbXjuGvoTtboiT4jxnVwUe8t79QhAYpuAqu7AOTULj+jPuAA5Mqp7KDZXsprJJW0ixOtkrq87pyhNDV65rzOJR0jojfTrs+vrx2BOv1Y3xs/7/K9ExVhQQHJpXXanvYzkotyaa/V67PmmHkXs/ZMbWvq/ZnnC5t8EodNvgwRLAaSawsiQlShLPINGSzx/bXD9VoI9+XxyDgWe9MlevMYAc3f8yHVB3a9wSnfHY2MxYjjtWpteTDUhgxAgUF9QBibjRpvPkC+57U20mVYOx/2jHCTCd4YdE0S5GV0oHG60AHNZ1FwKh8QoeTla0jdSYJHgdSJgNREUedDjihpJLhwXitF8lpqmzlCiptdRhmZsxqkjlAESWFVFPnmlAoEx8j0MlHKVffL/G2WXa489RyxmHPDe+J9KUSua4rPX6O2gLlp/4RR+QM8fLkJSdYiaY7aFgA2yI28nstoWbj0mjplwp/xOmGRDucnpdLlktE1UBRdeS9T5lddUSPkM9aURcwoWX5eofSHCNFtQLkkdnF915wjzn1dooskmXib0apLziNRLt47S15rmXbm4YNFsmx+VB/gFAGrIV9GbXSevYu25kqevM5b87VZsyFtqqPyIGM+no4bD+aL9SSTc8n8r9NGlzlabIhWr0kAG07F5Yqg2jZxPrtm3FgPBd2ry56t/XmqmncZ8seUaL02ORd1eiWXrwK5aoTPHigChvycgnJVTnuS7ADzmdB+s+8N1z+f0Rg9WnMKa5vIOcvIUDPmUk0GlfwcOiAMDsifqde9k5KmXhmCRw7TcuheRbDlmr9cRVKvm5prUgcNtCN1AQL3NtNi9X3y3xtibHaflyvt+Hm8llp52EnhA9XXCmAj8OSePJhfZDEshwp5rNbyOLQ4X09VLt3WY21rX2s8Mo5FTVCh+mI/NhnSuZyTrRXdxtHnqB4oRCAertwg9YOvve76IdRQeB0h1QsmmNNzuSwow2K+RKa1AiVzsoBBgraAtPMmNqJ/RpFAYaPTUNHw1V7rIH7jWmtyjkDTRUxj8HooSyyiEtjcCLXzVt83D6GcC4RCbtnApM329pdJp/WgAeFmqx0SfsbMFOA4v+Q3cNRoS12emcy4Ucyodkb0OgsXI6c0cIl7kwrTvE5jxGot8uf1vxkJcC3wUCcywWdbt0OvR2/GkGiKXrPOwe5ktRFB5W6msUDPJPWqsmSX54fXwmfD9cq1Qh5A7cDmw7aad+9i1mnhIILC51znYOu58S5mVIXG7jI6Uu+TOh8/BkUuZ12Pk4s55l0PMRvB9BTJj1wznMcsiiRFgbKvIt18mNn95r4kl+wI07SXnac6+s4oSWVfKOJUr5XLc1WjCmP0G3ubRpzpi6VVAvFzakeb7yOC21Tr6PJzJU+Az55rXImQDQQpH76cK0bjThLOVrMc7dJJque47rDL8t7LqaGuGdGh6LlwHklKZYqlXn8AcgRff04/KrcBY0nrDnaG8BrrSgxWVHHv87Pp7NZnRW0LAWBW8f24B9hluG3GjW6meY9U652KpXWVBc+Ky+uiRghrFK/mO3Cv0Nmt5dFry3s5bc3Uy+X75/1O2mEDcbnouw1n5fXGI+FYCAoEVMPevIHeIg8ePjwUOOHzTrUKWLrkXcylTXQqajXJumb7cg6P4ip8ILymGunoK/EqPlhGTXUlCDcZUIgw1GigYUhJyZy1gBNRFBq8PjTYn15sSOxebi/Psj62/KXx1/lTZ2w1dDnX2LiQ7xVAztcCyPPNTV3Dz0wDbBCMYpFeh11HLdPN+fAuZi5DzSdomzHDd/XmZXRzWSyNG4k8CRFli2uem1oihZwGIJcbMpKhwA3hYpYikk9Sy2Rz/WRnLrncxbZ2Wjl4z7VDyUFjsay0OOr5rA89oOh/EE1Zj60efPadJPempCk0GtfVUFRVef+AiWVZZM48dD82GfrlM+XgGhqiy4TEy8YPAEZLu9Wj3q+M6oFixOo0Rv5OOrRjk9Uw+bwZ6XdVGrJrxqx5Mya/Yew5P7xmfl/bDhtpKa5Fpg5rOJwo0cLg/boEkHud98P1XKNvKQnWod1Yi7UzUBvz2o7wEOEzJPJA5KJuargObb4fRsRMw9FurYZOuSaxlJ7zO2jXuL5FEtaWWuP7c2WDVa21zYipObXrsc0IB++BB/lFP0HrCjGQKYOUJJOMGaz0Y5OrZrgmuKs4v6yAqO1Ea04l56jeV/XzBBQtYqzNtMzFeqLOgF0X55DO4OH8XJG2ClXIDjOdD2yWwzIgrtO5tX0kglQHcXRMiWISLeV31WuN81uno3l21ucVHW6mRrg+633Hz+Gzq9dpRm6Jnl3a4683HgnHIqFAequ+22gNTPSCdbeTZsDUoJh6c3IC6/w3sFleCNiGjNYN0m02cLqch6dRzQciNvuZrIZ2A7bkZq4jwxoib+3wXayn8NCf7UxWGqHEolBZk+y8i3i4nGcPOHuSlr+kd91ZlFfLsdIA5APcKm52ulW+F246Rhhc8EBJZdT14MyFXzaMIboM2dN75vxnSNuMeIwulzHxGonCEM7k55NzQuPHCoNGSklWtA3NCCkrI9pmodPBw82JCgR5Fzcg5swxyByEkraoxc0mrvBY6rXCe67Jma9a66kwvYexyT0nOLeEmOlI0eGhI703XWZH8mw1Q+u0bwUdBzXcLiMD60EdkbrDJdc6o1FGbXwefDb1QcmSQ/ai4LoDSiVI7Tx0zQhvDgCdPQqvZWi72qM8DGloiTowOh6rvZWRvWqP8JBvfYC3w497RVzccAJJ7uV3Mf1KB8P5TcJxHwqHi+nJOiVEp6Q1qL52qJrq3niddVOrXJ7sKq2Tqi19jeKxzLNO1XEP1muwvjb2fZh36wyFs/S7Ds6G4E0LRvfBrOuzLaFGTN7nl6Jrpj74XGoEjXwSfgc1hsiFqbviKoxf0j8cehCXqhT9rCZ36CXhu7b1lGvnqA93OjdcX011L3RGnKQcPFA8DUA+7OtyzMupJZbMkwwqSFmin/tqfQmNr9O9ta5H7UyIXV8dJBNNIGJLOgD3kiJxVYMzV84uBl+7k9VGyv1yMML9Ql7af1QcizoXSo+dLPeLfqLELF9EmpiHZW07PXfvlCxFh4SRfD2pKUmOXhn1bsCRtuApq11vcB7UdTnV5TIhRp1D0K6sHFyQRFiY1hhCIahSz52LgbB+rezJQ44kVm7GGpbjIUgnixuOm428BG6y8/U0GysaSx5G9SIdo8+Qc83gBjaraoZqgdJQZEIQF3ffqbMoJS8+2Gbn92p5lx6wq6FAyHSK2Cyo9t4Z0dBx4CEVksPEDxvRXM0XYC8Dfl59/XlduJgPNCING86VlPRJLdS28f4KTaoRs2DXRYNTw7aU9a5Lavemyzxv3sW8pl1lsHlI08EiitcTribvBWqQ5pP1RjdYrluuAd4rUzm8Z66pyzX3HHU6ioOv4zol6hUTJbQLWsHDc2apt4WVHHN4FxVVsfuhkJgIU43rPN9Mk9HBU+en9JVheoXl7Zl0V68XlBRoTIXpH1E1yMKrEU/OUx3I0M6kJEg+5DJyvobznh1cKZ2Ka1SKEb1IytVJrILhc3LVeqjnNkWXnQpFONq8Vvks+F392OTvWb8GUlVfT41Y8VmXOU8biFRtG7g/eJ1EETm4F4bQYNous1NF5LPxRTGVwlA1GkiRKD5Hpmm4hkkSZ0DbuGDOut/YWxf9ZEMqgGs9RJcJ8mPYPGajoTVA4TxN2eU5VhWP1evZ5JD3Xu8vfndND6htPtdPjTDq2ho25r62Y96ctX5osj1mT6UAvGovXx6PhGNBDkBdRrgaFIJcDR32psu8MXmgT7s+s67pzfP9PBQuR0a5Lt9pTX0NQddpCyrb1Yadn8t/80Gh2gBEG/gZ/NwaSuQhwc8IcTP/zSYxlF9djy32pxelBLOKuGokpobVRBKW1n6e3wEU4ldOF9X3g03yEVAiODoKTlKWhWZ0zc+toxP+vHa2aigwJcne79BPctqA0SkjK2pcLMzp8U4rgC6s0kEuOT/ehwxr8iCkJn6yw6qOCFnKW1IyCn3XiBcPdM7vGDxGlFxwvTb4WTQKLHOsq0SGyqBzeIvgeO11lAL+nVGEGTuuod5QDDpadMo5L3VUe9ErEZpEVR6gEQWRkGo+uE5Y9kmnRDk5PhtzIky8dtbpO3t9tHbkvA7OJe+HCI9GVxUTvnKoCPPygNubLrMDxOfU+FKyWx/iFNKad2udA3NC92cXmTwY4LIjktEX9sjhc64cWhrby0FLdsKqdc/rqPdWvSYYDNUo6cSqQYhO0fHinPG7RxMWrIOBmvNS24e2sjd0RGuOjq+eL20BvzeTZ+3zqQFB/QXeW+2s1KX2te2uUd68/l3ciNTJ9eB6qedPnedX83lgThOAvP/Is2IDOc45HQJ+H7UpaIPqYKXmQdXrIqd+XHgVF4L7h8+rrkqqU0V8Xz4TUFJpREGyvsqldcR9xPXe+bDxewZg0YKmmk9YXy/PRfL4KCuv81Z0UGrdjjdq3Al8Bh0LEXkfgD8L5dn8DymlP/F6r2V3Uy7i9dBmzQoakGkFXS6HDruT1UbEwnIv7+JGj4yaHKPXtdld1FeGhFBtTdypvfEa8gXwqkXA/2jc+PD4Mx4sNeSbF+HYYAAK6coXTXamJ+rFwXuuc2q81pQEDq9uM1wvTn5GfT+E05gKYKTmURZpDdvxs2hcqScCFLVAB2BpP68NHSNIwnAsyasrM2r5akYb067HJJVa+NoZrMlmnMeax1Ff5+V5qSFGGtKaxESDX6NTtaNGQ8j5J/qSYcMqKnBSyubqdMp8ss5OD+eYTl39nJjmAFRU7Gw1y59bkx45aMRE0oYDyfVDiHp3ukS0fgw0hMPYbMDDjDTrZ1zL/zKi5nWIJHSm/tiHBhMZ0LpNvQcehEAxctGul+XW5BNxXpgK5cG8a+gCnSMeil0z5rmuW4pHOxy5B2tS28V6kgOEHL3FwrugMiefZ70OLyMUdXo1H6ippEcz6oVSVqivcRsHRO1M8P4YYWe7Y859dnJC1YfHb+bKvYuYyLDhUBARqnlivHe2GSDK2o8euz5szA33E+eBzteq7zKfq0YxqCVUQ/u83zqlzfshwqrrdZJTL3QqUT0rXkd9LzUfITv6wW/sdVbmZd5CFTgs1tOsFzPv1tmx4vUSdcpBX9oUVqxtwxh9XuM864ASgNW6Nt5F9H2X7XntuNDxr0nutUOhv6/OoVjUcsdsXxRZZ2qpfqbcj+pQ+Y327280PiOOhYh4AH8RwC8E8AKA/yAi/zil9EOv9x6mBwhR17kcph5yqsGP2Rg2PpRSJpuEkBwQywQDZaGnJAiyCRHx78Bm+eVY5QTpFfIB1a+7zObl5/Dza4SiLstMqejSO1dqyTdaDZMDkMux9PNqIhxz2zSM3Fjr6kDngs4iY7GkTep7AZDrzOuosYbVki0+wo6X55AGLEc/BjMPYyFUkjNCB4wCNDTKMRVth5rxr+ur5HjrskVeA40w9Qhq9EEqBIOvVyTIAakIFdXpHe9i5mvUDmftYNTRXX1gijmvG/NdG0Guaz730Lzm2uH18rCkoSeaURP7+PyoGih2f40UkRsaaLLLg6Scc+Wa6Cuyr8SUWfo1X4CHfe2A1wdk7ZBxnfEwc5KA6DYd9uqgdtV+45pejdqt9nLUW0P7uTywGTcOfO5VVtPQKa+DgN7WZU0WrgONZSzluRkNGTdJn060LDDEzTLimrDM51vblEzAqw6I2knhGgNKyoCD97mMXV6PNYqb178UdHTJEsJUZNx533y/pl43D7rGBcznpRqkRmzz/k+FE8ODlkJ9tJHcP5yTOsAhibpOAVAPpvXhVYgRzwI+l/XQIjWS90idsuF8A6UnDDky9eeerabYmaw3DtEQVZGU956SiuaNVQCje6uxjtx+4/v43GqUY+b6PHe0FdRtiUkyUbuu2KqdrtK7aLNHCKr31Wddza3SPTFmBy3RCa/sWu2szbs1RLQi6I3GZwqx+GIAH04pfVQnQv5nAL8EwGs6FlzQ2ct3m3K2QCl12tjANrEkuDGC4iG8NC9vYp9FGd7sAFSHBb+7btJVjzrtUR+ydSvqGpajAa3hVf6O0TOjRWCz30YdZZBfUZO+pu2A8/U0ozQ1vKalhj0eLncyosNN513Mi7g2XvU8k2dQH5bcrBQw0measmHmMyTcyp/VqZp8oHCTugIdU0QGQEaQ+L2Z4V41JKoNdF/dW33w0wgR8pxYJQAhfUbUPPxJbktJsLbKHa4vfm+Wpq6eR0qCUdLGpmYlDVG4mluRc83mCDACzoY3lbTe5UOPuXxKmjPHTUl7fs/eZJlTTepENFkFtUb06uh1am3B64OF6ZFGQnZyGDXVHAAeBFLtjXTpefMQYYlzTkva2qJTlszpoQNb8ytaF3O+nGs37037rM6HnO7o/JjJiqzq4DOv0yo1qjBpBpyttYySUV9Wp62jbVsHlNLPKRvbjzwYOb81nM61wmth6oTPmD9nEMAS5NaHTBZcVb1PaPTJmwJUtZPPH0BOJ5IQPFglUG6LXpWwkshJ++Gq58B7ZfoqRocRhUxaO6Z1yqtGDdZjm1ObRL8uO011dQLnivu8drj5Gr4+RNXtqRusAdqLijam1p7IzhGDL3vWy6GzZmhhQ7QxYhOlpo2izXKSzLYVvZPWBxUas6ClTt9xvupgiPsmAhtOG8n7tCsAkHzpNMqglffJgBwowTb3HoUnuW74PIcKleD+CNFllGddcW/eaHymHItbAJ6v/v0CgC95vRc7i4qYD68hu9FgchL/Sg7TwUtEnzY1LviwVxXphiOiRA2XD3uglA7BFjbzvyQs8nvoLdbkK6BA6CTuXeZAcKzHVhuQmeAP895DLO2JGfkuh25jI5J3QJ0DRpA8/LxTqJ+lZTy0+ZpM1qsOrLoempuVZZw1j6Hz4wZkTeNZRxSccy4+OjEKRb9aA6BGlPqgxs5LxDqWEjpG1ywVrZU112MLhE3BKX7mrO0LfBsdxuoA4vNhlLge2izUU5PYasPIQUesFlmqHYs6Aq0jUl4XDUrNZSDLvX4+jDhqxroa400FQBrewcr+mibkeyS/obVroTGpI1clwVXPoapaiEnQ2XdwnWw4l5eM2eVBCJXGs7ODsTZOtTPIUeu/MIIiwsLryloGqehdEOlrbS4BTbXS8a4PoJoQXaN8POy5njo/YjFOtfqgOtBocLPugWzmv/l+ACazbbwa/glkO1MjLnRiOzduRNm0XbVc9GViKJ2CvP4tJcg0UIhqZ4kWOreJ0DIwS21ByMjveS0Era62oU7OGD0mUmToRRJGe5YMlrg2agSwFpOiM0PypBc9aGPYLEmnoxKTotx1SXpKRX248+OGTebveN8sBOB8k59Wl5lv2AMrOee98x7oYJLgmMmiTUFCiI5w76KyEZfLPQFsqGcyBVcHK2ysVp9p9RlysZ5srLfa9tTBAtc9dZMYzLWuEGG5XlK1hl9rfKYci9f61g22h4h8NYCvBoDHutmryF3ZYFeREmBCJM2IOLavMmYkijUSs2SqQ0LPiKMqh8w693Y41gd/DfHFWMg59YRygXW+artcpU0Y7WYvkDlrO0B0DtLGwcfomRHgpB1y1MFNiktlWEmSeuMARggmMmyUUhEGo3NEo8XFCrw+wYzXVxN9alSgblnPRS2pUj607+QBzMOMRiMTmpKDpFKDvrSGcmS102CwSyeNzaztM9LAiBmSdA24kBnxXFecl8YiPxog3j83P/s+zKo8e/2seKDS6298AJJsoFdEjzjo38foNgwlnakxbpYt0wjWCFidY2WEQV4BnZthbPJ1cB6A4syOfjOf3VcOVo1W1Gmr+j4Ic4dL+4dOD1GJ+lnnn5uhbX3I+/qy80WDPcTS8KuOyOvINkjKqcQ8TxXSwtef9ZNMWKVDwc+sSXy0LZNm2HBk12MV+YbC16JjUTt3tA/1a2pnrA6MgEpfpHIOiLbV+7Den0RUcmBROXrD2GTHgVy0aIdFHVzwXupolQfZ6WqeNSqYxlj1HVJ1+NT3V19nSmXN8ZCr08T1gUZklLaA+yJV/279iM4VUv8YPJbmODHN4yVi0uh3kvTOg/XyIch7rMmUl1GPjJxYYFd/F/cc75HfUZdZ1xVcjQ9V35IOXeVI1s+UCAXJuryOy45jRttt1PuB18Kfc085FyGpoGCc47YZN1SEeWZEe4Zc10TORguAWq8aJm80PlOOxQsAnqr+/SSAF+sXpJS+AcA3AICI3Puyb//GBYBXPkPXsx0/sXEN22fyKI7tc3n0xvaZPHpj+0w+s+Mtr/cLSemNy0Z+IkNEGgA/CuAXALgN4D8A+LUppQ++wXu+K6X0sz7tF7MdP+GxfSaP5tg+l0dvbJ/Joze2z+TNG58RxCKlNIrI7wDwzdCqzL/xRk7FdmzHdmzHdmzHdvz0GJ8xHYuU0j8D8M8+U5+/HduxHduxHduxHY/ecJ/8JT9l4xve7AvYjleN7TN5NMf2uTx6Y/tMHr2xfSZv0viMcCy2Yzu2Yzu2Yzu242fmeJQQi+3Yju3Yju3Yju34j3y86Y6FiLxPRH5ERD4sIr/3zb6en0lDRP6GiNwVkR+sfnZVRP6ViPyY/XlY/e732XP6ERH58jfnqn96DxF5SkT+tYj8sIh8UER+l/18+1zepCEiUxH5ThH5gD2TP2I/3z6TN3mIiBeR7xWRf2L/3j6TR2C8qY5F1VPkFwF4F4BfIyLvejOv6WfY+JsA3nfpZ78XwLeklN4O4Fvs37Dn8qsBvNve85fs+W3Hp3eMAL4upfQ5AL4UwG+3ud8+lzdvrAF8WUrp8wF8AYD3iciXYvtMHoXxuwD8cPXv7TN5BMabjVjkniIppR4Ae4psx0/BSCl9G4D7l378SwD8Lfv73wLwS6uf/88ppXVK6WMAPgx9ftvxaRwppZdSSt9jfz+DGs1b2D6XN20kHef2z9b+S9g+kzd1iMiTAL4CwP9Q/Xj7TB6B8WY7Fq/VU+TWm3Qt26HjsZTSS4AecgBu2M+3z+qneIjIMwC+EMB3YPtc3tRhkPv3AbgL4F+llLbP5M0f/z2A/xuKYj6wfSaPxHizHYtP2lNkOx6ZsX1WP4VDRHYB/AMAvzuldPpGL32Nn22fy6d5pJRCSukLoO0JvlhE3vMGL98+k8/wEJGvBHA3pfTdn+pbXuNn22fyGRpvtmPxSXuKbMdP+XhZRB4HAPvzrv18+6x+ioaItFCn4v+dUvpG+/H2uTwCI6V0AuDfQPP022fy5o2fDeAXi8jHoSn0LxORv43tM3kkxpvtWPwHAG8XkbeKSAcl1/zjN/mafqaPfwzgN9rffyOAf1T9/FeLyERE3grg7QC+8024vp/WQ0QEwF8H8MMppT9T/Wr7XN6kISLXReTA/j4D8F4AH8L2mbxpI6X0+1JKT6aUnoGeG9+aUvovsX0mj8T4jEl6fypj21PkzR0i8ncA/DwA10TkBQB/GMCfAPD3ROQ3A3gOwK8AgJTSB0Xk7wH4IWjlwm9PKYU35cJ/eo+fDeDXA/gBy+kDwO/H9rm8meNxAH/LqggcgL+XUvonIvLvsX0mj9rY7pNHYGyVN7djO7ZjO7ZjO7bj0zbe7FTIdmzHdmzHdmzHdvw0GlvHYju2Yzu2Yzu2Yzs+bWPrWGzHdmzHdmzHdmzHp21sHYvt2I7t2I7t2I7t+LSNrWOxHduxHduxHduxHZ+2sXUstmM7tmM7tmM7tuPTNraOxXZsx3Zsx3Zsx3Z82sbWsdiO7fiPcIjI3xSRP/YpvO7jIvLen4pr2o7t2I7tALaOxXZsx3YAEJG3icg/EZEzEXlFRP5k9bt/IyIrETm3/37kk3zWfy0id0TkoYj8DRGZfArff1VE/qGILETkEyLyay/9/heIyIdE5EJE/rWIvKX6nYjI/1NEju2/P2nS6Pz9HxWRHxCRUUS+/sc1MduxHdvx4x5bx2I7tuNn+LA+Pf8KwLcCuAlt0PS3L73sd6SUdu2/z36Dz/pyAL8XwC8A8AyAtwH4I5/CZfxFAD2AxwD8OgB/WUTebZ95DcA3AvhDAK4C+C4Af7d671cD+KUAPh/A5wH4SgC/tfr9h6Httf/pp3Ad27Ed2/GTHFvHYju24z+CISJfKCLfY4jC3wUwrX73lSLyfSJyIiL/PxH5vB/nx/8mAC+mlP5MSmmRUlqllL7/J3ipvxHAX08pfTCl9ADAH7XPf90hIjsAfjmAP5RSOk8p/e/QplG/3l7yywB8MKX0v6SUVgC+HsDni8g7q+/80ymlF1JKtwH86fo7U0p/K6X0zwGcvcZ3/yYR+Xci8ucNYfmQiPyCn+C9b8d2bAe2jsV2bMcjPwxR+P8C+J+gEfv/Aj2IISL/CYC/AY3QjwD8VQD/+FNJP1TjSwF8XET+uaVB/o2IfO6l1/y39rt/JyI/7w0+690APlD9+wMAHhORozd4zzsAhJTSj15637tf6zNTSgsAH3m9319676cyvgTARwFcgzbi+0YRufrjeP92bMd2VGPrWGzHdjz640sBtAD++5TSkFL6+wD+g/3uqwD81ZTSd6SUQkrpbwFY23s+1fEktPX0nwPwBDRl8I/MoQGA/zs0pXELwDcA+CYRefZ1PmsXwMPq3/z73ht8/+X38H17P8HfPwSwW/MsPsm4izK3fxfAjwD4ik/xvduxHdtxaWwdi+3Yjkd/PAHgdtpsRfwJ+/MtAL7O0iAnInIC4Cl7z6c6lgD+95TSP08p9QD+X1D043MAwJyWs5TS2hyXfwfg//Q6n3UOYL/6N//+qjTEG7yH7zv7Cf5+H8D5pfl6o/Fac/vjmb/t2I7tqMbWsdiO7Xj0x0sAbl2KwJ+2P58H8MdTSgfVf/OU0t/5cXz+9wP4VA9h2GtfDw34IJREyfH5AF5OKR2/wef9KIBGRN5+6X0ffK3PNE7Gs6/3+0vv/VTGa83tiz+O92/HdmxHNbaOxXZsx6M//j2AEcDvFJFGRH4ZgC+23/01AF8jIl9iZZc7IvIVIvJGqYfL428D+FIRea+IeAC/G8ArAH5YRA5E5MtFZGrf/esA/FwA3/w6n/U/AvjNIvIuETkE8AcB/M03+nLjTHwjgP/Grv9nA/glUE4JAPxDAO8RkV8uIlMA/w8A359S+lD1nV8rIrdE5AkAX1d/p4i09j4HdWCmdp8cN6Bz24rIr4AiNf/sk8zZdmzHdrzO2DoW27Edj/iw9MQvg1Y6PADwq6AHMVJK3wXlWfwF+92H8UmqMF7j838EwH8J4K/YZ/wSAL/YvrcF8McA3IM6G+8H8EvtPRCRp03b4mn7rH8B4E8C+NfQlMInoITITzb+KwAzKN/h7wD4bSmlD9pn3oOSVf+4Xd+XQDkhHH8VwDcB+AEAPwjliPzV6vd/DZru+TUA/oD9/ddXv/8OAG+3+/vjAP4vnwRh2Y7t2I43GPKppyG3Yzu2Yzt+eg0R+U0AfktK6ee82deyHdvx02VsEYvt2I7t2I7t2I7t+LSNrWOxHdvxM2CYRsX5a/z3+3+Kvv/p1/n+nEbZju3Yjp8eY5sK2Y7t2I7t2I7t2I5P29giFtuxHduxHduxHdvxaRtbx2I7tmM7tmM7tmM7Pm2jebMvAADmbpb2m314SXAAhiTwkhCSZNWeVhISVJknJYFIQqp+7yXBVRI3MQFO9M+YgMYBKQHB3kuPSviZ9l+I+iGN09dE6Hs4nCRI9b6QJP+9/l1MgIh6bn0SpAS0Lm14csnuVey9/B4vCSyy75Ogk4SYvx9ZyigC+RoTNr1E3n8CEG0++Z5kvxvturwUxSOxe+A81/PrBRgT8nt4D7DPFLF752dV18LfUYZoiHpN9Vx5SYjVfPL5QKr7SchzEZOgtblxdu0pCaJdr4i+Bvaecp/Jrr3cuEPCmASNJDi7jmSvEX1lvqD6voDq3pDy6/n+Ri6lGuubQ3k/5y9V0lPOPsflZ1cmXb+T91jN1cbnco8IvMSNaxObHyRbHy6W+ahG+ae86l8iZR7znKZLVyFlvss1purj8k821h6SlHvnHOY/pHx3kjzvzmzE5astn8kLSva+S+vMroufifx/viiVz6uufePiXks2rPrejXckzp2+qL6v8hq7Fl5svr7qmuzzY5I83yIJSJKv+fJzESREODiJQCp3myBISeAkIsJtPDt+hpOEWD3zWF8PNtfFq9f65vWIpHp3VdfAydz8/svKbJJtiM5dbT/KPi17CKCt39z7wOX9tbl6YipWQO2W2usxOTjbh3wFP8fZs+EnRYjuaQiinTMBartctZ/V9pb75e+qSVJ7UX1u/nf1WtqgmIBG9LvUHkme65HPFMWuumrWyzlXzpMxCiYu4YX+3isppet4jfFIOBZH7R5+7fVfhSttwJAEQxTcnA44HfR4XQWHCD2M5k3Ufydg3uhUnA0O+21EIwmL0WMVgJ1Gp6ZxCXMfEQEsg8NeE7EKgnXUYzgkoI+CVoDdNsBLwsQleEkYkmAxepwODp3Tg7V1yR6U/pvXNXH6+lUQ3Fk6HE3U0dlrAl5cNrjaRXiXcDE6/Xz7vLPBoY+CziVcaQNmTcSHzzrcmo24CA63Zj0e9A0ugsNBG7AIDkPUOeqj4GgSsNMEvLBo8eTOgAfrBusoaF3CfhvwyrrBbhMxRsFOE3G/90gAZj7lQ9rbQj0bdR45J9PqnvaaiJ1GfxchmLqYnS5fHejBnh+gG3CMgsYltC5hFRxWoZiFkICjScBi1GfxoHc47PSZOgA7TcQqqvMwJL2eVRTs+Ih76wZX2gAA6FzCIjic9B7P7PR4OHg0knDQjTgbGjx/0eBoEuFEr8FLwk4TsRwd9u0zVtGhczFf/8S+SwBMfcRi9DjpHSY+YeZ1bU19xNRHhCi4CA6trbXF6DAknTMA+jtJCAn5dZ1LOB88dpqQ19HURxyvGyxGvcbrk4DWJZyPDnOvn+VdwungseMjFsFhx35+e9ni1mzIf/Z2TQBw0OoaGZLglVUL71J+33Hf4LAb4ew6x6jP8aANOBv9xpydDg43piE7qTtNwCo4LEaPqY8YomC30XtYBeBwEtFKyq8fzIjtNCHv69YlLEeHqU+Y+WDrQnBn1aJ1CXuNfu616RqnQ4tXVi2OJiPObR/V1xGS4KAb9IAF8NKyw+FkRB8cZk3A3VWLp+ZrHK9b7LcBEcArqxY3Zz1iEgxJ8GDd5PufNwGvrFtMvdqcqY+YOD20F6OHtz+vtAGrIPk1U6/3vI6CpnL8QtJ96SXhbPRoJen6setdBb2GmARzH7GOgoPq2bRO99kQy+esgoOIrrv7fZPnc6eJmDUBKQmO1w0OJ6NeQxTcWze4Ne+xHD3u9x7P7KwxJMH54PNeCmYvGOCFBMyaiImLWAWf9/jURzwcPPbMdnL/OKitPBk8BMBBN2KMDo2LWI4eYq9djGpbYa+fmH1lcLnXBIQkuN83WAeH3Tbk9QgAcx/RR8G+/fx08PAubezbK23A1Aec9HrcjUn0rImCEztjFjZnnNvF6HB9MuKwG/HxxQQ3Z4PaqHWD/TaY7R1wvG6zPVsFh5uzHuejx/ng8aOngrfsAtcnYz7XxihmGwJ2zD48HDyO13odzs6YdRBMzM50FpA2dkZEAHdXLUICDruAlICTQZ/J3Ov63G8DGkE+66Y+IiVkmyiS0Ec9S47XDkeTiKPJgJeWHQ7aAJGETyxaHHUR+60+A9pi7uWv/8Rf/AReZzwS5M3HuxvpN9xQvZsrbcBFUEM6JF0wLyxa3JqPWAXB2ejzAXfYjThe6wRPvS4GbuIrbdCIHDCnQA35OupBOfEJ+23EXqMH2711g51GjQKgCMlFcFgGgRdg3xbiw16N9eEkwiFh6hOGqBvvzqrBtUnIxmcVHBpRr/DllcfMJzwxG3G/93kB00HoI3BrNqJzCb0tvlYSdtuAPrh8kN5eNjjsIvaamDdD56MiPVFwZ9Xg2d01AGAZPM5Hh9PB4WiiRns5OnQ+5UM1JN0Qz184XO0SDifqeKVUHIKzweU5BUpkrZtfDWdf3Q83TCsJq6jfv2vXGxJw0gsemyZc6UacmyFozVEDgFUUXIzODLbLh0MwpGSnCTg1I3gy+Hzo3l6q4Xh8FtAHwXHv8OzugJPeY7cNGKPgxWWD1gGnA9A54GqXsrFajIIb0xGr4Mz5itmY31k1mPmEiYu60QVYR40ULoJDSoIr3YhkG5DGAFAHakiCPjicDHrYHE0Crk8GrPLmbtBHjWgah+yUcngBOh9xOnic9vo8IwQvLT12m4TrkxF9FDw0QzlvYnbILkZ1Xt++t8LF6HFq++CJ2YCdZsTzF9PsMF+bDLi3btG5hAe9x9Sc4GAO4tTWWoRGLiL6nHs7aOjMzH3MiB0PkfPBY0zA1U4dppPeZwTLScqHGQ3Yy6sGj03HHAHutyNCEnzsXB1vgPMq6tiY89l5dRq9AM9dNHjrjjpanMM7yzYHJVOzDQtz3EUSXlp2OB0EnVPbcTTR59q6hIfmDDLiPh08GqcH4MqCFW/zwWvpg8M6SnYspk4PwzGJGfzilC/NqeQe5TgfNYiYuIS9dsRJ32Axehx2Og88IHWPC/a7iNPeYb8r93m/95g3EXdX+trP2uvzd3Qu5cNjvw348FmHt+4MCEnQ2f7ia72hi61LeP6ixdUu4H7vMXH6rK92Ie+N0Zyki6A24Gx0OBscrk90rkc73Gk3pl4d8M4l8GiaVQf+2aCBHqCH5rxRO965iD66bLsYMERbi7eXLS5GwY1pwNVuxIdOJ3hqPmJFB6kKWj62aPHZ+2s4e760xYA6AVc7daI+tmjROQ2AWpdwd+Vx2EWc9A7zRgOQK7amGHwsLSi+0gaso4Mzu9c5dVojgDOzaZ2POB88TgaP1s6gVRQcrz12moSDVuf5fHQIEZg1aqsbSXh8NsKJ7kcvCcdrjz4Krk0Cdm3tH681qLi9bOGQsNOoLTwfPA4nI04Hj5Nez9vbFw7v3B8RUrFHv/djf+m7U0o/C68xHgnEIkFwPgoOO/V+uekvRo3IiD58/wOPL7yqjkDnE55bdNhvdWOGpAYuim7QdVQPf6cJWI4O56MaAB4iD3qPB2tdoHeWutFal/KiFejCvdJqVNpHjSSudBEPel3c+23EENW4dS7ioI1I0MV4NupDbFzCEASPz/S6Gf0DyAatjYIdAD921uCpuX5fKwm3lw1umKdLNOfGNORIZx0F++2Il5ZdNv5Hk4CPnE/wtt01zsYS0YYkOB0cWtGDncZ9ZgflO/cjTgaPPqgBvL9WYO/mNGJuG5vpIUb3ktTYMLoYzHgP0dIIgjzHty88nt0bMPURz+zo9Ty3aLHb6obcbdRQBTMKH18JAI8xAlPvssf/oHe4NdOFXaeoAGC3SZg30aBN/d1ZZZzPRo9b8xFDFBx0Gr3pZtUNfnOq0cBeG/Cx8w47jR42rVMj4czZHJM6Fg4pr7NW1AgAGlk86D1iAg66mCMVLwnP7o7ZCN5dt5j5iLurBqeD4OkddV6vdiPWUcwICV5ZOxx1EQfdoM5CbPFw8IZ86L3dM8fkmZ0e99YNLsbiDM6bCIwOn1hMMG8UOXusC/j+kw5v2VEjFhKw10Y8HBrsNRF3Vg1aATqvDgeN+8O+wW7lYB6vPaZeEaA+CqY+oXO65hQ9FBxNRuw1GuVJFKzNcR6SYDUKDjs9MLs2YDGa0+0TDrpo0Wyyw6fFQTfiHXtrhKRO1MQlBFfQkLPRIQweN6cDXly2eHmZcGNaUL55I7g+UWPKCJWH1io4nAzeomH9vD4qapmSzkVKwMQlXARFtQ67EYvgcpTfOIXNp9Uh0RgKenflMCSHmdeAYOISHvQN+oCMPDIlp0iWrqNWgGd2+4zcXoy6zp6cr3F33WKIguWotumgGzH1ActRn+P56LDXBkxczI45nTIGLNcnY95LQ1QH+On5iJeWDRoHzJuyz6bmXK6Cg4eiarNGn9vEK2p80vsMq7eGegZDPkMUTJw65XutzsGsifm5L0ZF95xLOB3Vju630ZAJdU6cReKt08NWUQ91IBz0AO8M/SMqEiKw1yZ7pg7vvrLCcxcT7DUayIYoakPNxj7om/yzH3jg8LmHMc9BSMiv22siTnp19j9rrzeURRG8i+BwPqo1WgWHvSbg/lqw2yTcWTXYb6OhOAmtCB4OrqBaLuXf0blfRZ2/G9MScDhR1KI1R2+/VWf1dGgw9xFXuwHnozoiPihqz/d1PqrtQ8KVLpqzIzkIAtTGzX3Es3t6zTenGhi37o0BiUfCsWgk5aji3tjgikX7VzudwMUoWMcGn7Wvi3SniXj+QiPPicHPNZJBmHLqdAPcXjYYI3Bzpk7IMjgzgPrep3dihuwZNe80ASEKTgePe+vGfqYbYerVoDBCj1HwiUWLt+wMeNA3mPmIzgOvrD2uTYAPnjjcmAqemut7bl802Gl0g3oBTs2Tfud+NPjOYdZEfNZen9NBenAUVCPavPUGcwHAtFEDfDRRCBdQFGUZBE/OR8y8Lr4bTcDDQVNGL55PcHMWcnpgMK99FfR76bDwINecYMLDvsGYCswXUklZnPTODu+Io4lC6tebiAd9o45J0ENpt01YjIJndwesDBm6CA4/etpg3hSExAtwe+lxazZib64Qb7DF37qUEa7WIP5gh9ZuY+mrjOjoBlcnEbg177EYva0fB+8S5i7ibFBUaOL0WawtNdL5hJkZVb3eEu20LuFsFFyMet/7bUQ0Z7dPgnXUnOmsEcSkBqSzw+xoEnC1K7nSC4N095qAzu4rJODlVYe5Qe00wjtNzBHhU3M9fADgI2fA5x7GjCBcNyic6ZPz0WHqFQJuu2BpvghYqu2oU1SICGArCT0Eu21B5IYouDUfzIFwmLiImTnNIWqkOnHGM4p6YLQ+ZZSic+aQBI26OldSf4AiImejx+0Lh4Mu4cZ0zFD82egMWdI91Ae1CzuGXHzfgw7P7AY8u+cwNXTk6Z0eHz7r8Dn7I96+t8InFpMcfQLA3BCiqY846TVoOZoMOOkb7HUakOy2+vxTQk7rtZLQuITkJKfP1hXsreinZISvsVz1sSGXTAVMXETyun9eWLS4Ng3ZkDP1QKSudQl3Vh32moDT6HGls8M3OJz0DZwALy09jjpFuS7GNtsrjuuTEQddyGmWjBKaw31jWtDDW/NeU0tdj71mREgdzgaPMeo9z5pYUhgu4WJwuDEdMRpSs9cE3Fk1mDh1UldBsm0j6kke12CB4pVuxG4rhesWgZdXDV64AK5NNIhKSVOoRGX3mojGFQf1uQXwOVcSjnZ0/TvAArwGT83XuLduN9KuGiA5POg17Td1Cc/uqQNzvG5wPgretjvgInh0UbITNWsSHqwbLAwtEhFD99R+HHVqJ9+yM2JMktN4Z6OlRi2APra1Tzs18zEjwOso6HyCg9q8HpLT3lOfEFEQ1uXocGfpMfUN5l7PmqudnpNDFCwN5TvpHW5fAI0radC7K8Feo3tYEWxFjc8Gh/u9x/XJmM/E1xuPRCrkie5G+h23fgW86EEIqNGZNxFTy3d5p9APo4uHg8cyOJwNgiutPphV0LzYRdCI+nTwOJoobKgRieBsUJjq0GD4GurL32uHE6FaGnZGIUQvDjqFzYcocAKc9A4HnUbMP3Di8cRMF5wDcDQZcz5xEUoUfTE6zJtoaIO+5sa0xyp4LCwH+sRswL11Y9GsRjaL0WduAqD8kJQUVtxvgxk+nTdyUgBs8BI4FhYZE5ZbjOqsML99v/dYBsGBoTeNefY0chMXMSaF5fsIPDmPhvaEfNBdBMkLXKR48A/6BjemAx4OHs8tPN6xr9yaqU94aelxYxpw2jscTmI+PJhaOO0dZk3KqZDvue/x1I4anD6UTchrWJtRJVoz2hzNzXN/fuHx2DTi8VmPjy8mANTgLEZNk9ycBcQEvLzyBnOrMazTZ0RWAGRuDqFSb45g5yIaQ3bODLKv0x4RwPfeb/A5V+IGl+f2RYOn5mOG2jmO1zpPXA+cYwc1XOQmHXUjbi+7fM2ENQ9tHTOffWaOeWOQ9711g4M2ZDL0KuqcdS7i9rLLEbe39FBIYmmSlPkkgDqmUxezI7oYdf96UWfTCXBzpg79OgpOejXEvtxq3sed0wjqidmYUalWNPo9XjeGbOl77/eaZz9eezw+G3Oq8WJ0eGI2ZLJvSIK7qxangzriRAofGvx+tQs4GTSledCN2RadDsqX6Fx5/uvgMDEOzung4QUbBEIeprVzqFwCjwe9IoUrS6d4pw7tucHyTNM8NR8stessjQY8HARPzMzZNweBzuQiOJzagUnnoTWeCFAQ1B2vqNYDSw97SXhp2WDWaJqDfJLO0s+3Zj3urFrMLVDi3mKwlpKu86nXYI9ROdcSOUXcx40ryII+07I3FqPHnWWDBOCgjRmB7qMiIkMUXJ+GTPbugzrDi9Fnu3l9onwJvm+niXjR0mN0riIUNSKngvvqdPC4vWxwy+b4tHdoHHBgXAcGuIvR4d5K8M79QVO9+1O8/bf9fOw9fRXOFRI1T55GatJqTaY3m2A/F5R1RHKmYJOsCpB8WojN9ag/q37fJiFcfxpCwuL5+/jIX/lWnN4fcppy1kR87Yf/yuumQh4Jx+Lx7kb63U/+imzEmB/2orlDEuSOJqO9poWzjeygxmzqFXUA9D07jWZm99qQ4XryJBajx/HaGQyXMp+AB6uSEXXzMw/4sjk8e23Mnv/UYOKQBC8ZYZNGYjC048zQiJCQodKJOSpekB8UD/T9NuQFvApqdA4nPR6sO5yNDk/MetxZdjiuPGpuUh42nSt58d4MDyOTkJQ70EeXnaXOSE4kg3EeRyPIcmOdGfTc+YiTvkFIsAMm5Zw7v/9k8NhrNGI+6DTSfHnVYRUEYwRuXwC35up4KYS/xsWofIuJi7gYPRbB5dzw+ahG9vGZ5v4ikI0c566zw/K5hcdn7w9wUHLi47MeHz6b4JmdAS8uCUGq48ED8u6qzY7IQ3NsvGiVwX6rhx0PQ6kOiZkvqTgAOUWxZw4QULgorRH6OIdng8c6KDp1Z6lw5WiWJkLX11E3Zn4A87pHXczOw/fe93jHfsJT8zWG6HBn1WKv0d+/uFTUig46uUhnBjcrCgVDAFvcmI4bRMzTweHmdMxkNhJSebDMLP0hwAaZ0Nm9AsgcHua6I8RSRMpbWNs+SYbqKAEzaABgjujDwePmTB1OgRrhxiW8vGxwOInZEb4wB/AJIz4/6B3esacozsqiywNDQbl/r096vLzqcLUbswMgxsfabQMe9k1GYWJSKFnvUw+Bw4nud62W0nWwji4TCkliJA9r6o27NSpcT4I09+ViVBRg1ui6TLbmjnuHJ+djDmoAdUYZ9RO1JFGcnBOgBC/k2pCI3Xklih8ZD6MmeHKtTy1i5vMP5pRNfVlT+23AydBkbgQRNKJYdDZWQTk5JHiS3E0i++0Lr7ynScjky2BO6OngsA76zCYuZXt2Z+nx9M6QSfZPzQeMlq46GTyOjIOicxRwZzXBv70b8b4nCoflbPSZ4HxnpQjGfhtw3Dc4slTXhTmAHzv3eMf+mFMPJ4PPacfWggiiIjMrNOij4Mv+8Hvxli98O/baGUTU8S5Ve+WsSRbgpQQEq1xxFljEVJwAZzaIa4GOlBNWPKX8+boPdb3SaSM6kav7EnJFCjlTjUuIETgflvj49/4ovv2P/8vMSeqj4A98/BHnWDgzcD961uLxWWHKXu0C9ozNvtvqQye71VtO7YcednhsGtE0wNQ2cuM02lqbF38yeBx2wTa3RiFkBQNq+D98qujEE7OEIQHrIFgFYN4A+23EblPQiqtdwJiAB32DVVBD+PhMN/MrK4+F10hVq0xcJhsOSbDrQ85zjXawA8BeOwJoctTE6Hqx8ri7mmEVlaexjopCHHZqKGAHGImqZKZLUKdqZjnMVvRAOV57PDnXf9Mp22lSjth2LGodomAcHQTKo1D2OQCokWT5bITggZEjgdpwKiHx5kzZ2DSWLMk9nAB3Vx63LPI7Hz2eW7R4aq5EzbsrjcLv92o4mVf8zuMG7z6IODJ29KxJuLtqsdcEHHQjLkaPaxN1jo7XHs9fAJ1r8eR8sKgoYWlEPRKfxqgHDg+Hm7PB+Bya/+7tMJk1MR+mXvAqEt5i9AgJaCwVoxFcsooKj+NeD66Drtc0lnM46PTge3ZPSbqng8eFQex9QN7ge03AvbWm2zLEjoTPO4w4Gxwugs+poXr/8FDrjLfz8UWHlGCkPq1OYDpmtAj9fFSS2c2pGtVVr/d/YL9rbU3tNAFDr1UszJU3op9J4zz1CfvtgD66jACGpKz2fYskQxIcGARPx2HiNAW6ih43JmNOxy1Hh+94EPCLnxwzanbUjbnU/LFprJA9nf8PnTa2hpQk/HBQOPelZYOYOjT2fIhs6X7u8cLFJO8dQs7rAOw1EXtmOUNSEhyJztH2BVNz93udC++SkTiTpXgEYdA1zoqGB32D47VybQDgFYObFxaccN3tWSqTsPlOE3Ft2uPuaqJ7mTaFHBKn9321C7nc/H7v4cTjyfmYD5IzEn99zPvv7spn5PO5hcfRRNOXdEburRscrzUVE6JgaY5iNCeKcwpgY++wvJ7zu4oOj89C5k84AKfRZ87VQRtwAiUgkjgNALfmmm7Rip2Ij563OB+Az7miKNz9XtENlRFQR/tnX3c4G3SdTX3C8RpYecFi1eJHTwVfcGhVH92I477BW3eXeLDu0PmIg85jOTq4JuJ0rYHQY9MRjYt4ZdXmNcH0RUrqIO2/5RD77QzRijnrA752KhRhgJbBGpyQUEpSNxwIIAc/LLdWlEMdjj7qa2mDAiQjWyzdJwIyJA34Jj7lNK2uZWCvneLKW67iYnSYdiE7zW80HgnHIiQ9BI4mGuk9d6GXdT42eMder7mt6HFjOuRoFtBD9OpEc9/qJLh8ODy/bHDYBZwlj6MuZI+7cwlD1Mkj8/aib3BjloyJrKWnbZNw0KVc9gVXUiLrWFjCykhO6CPwoNcNRhLi0lI4J32D65MBQ9LNu2fs6Ie9y8TUk0GJRMdrj1mTcGuuuWaypVlR8YMnHT57fwBQDhEiEmLG/yPnHQ67iAfrBieDw15DgpQeFoQmh6gEquO+yQYdMM0QQYYEG5dw4PXgJYv9YRIsekFjPJc+KjeDn9t55O/caSJuzXv86vd+Cx68eAN//wNfiDurpqqkGfGwb/CuKyu8slZI9XCiPJrrlgq5MRmMD6ERAqHnU0O0jtceo/FnSBg7nERcm6bMCQDU6Xxx4bDTKFz98QXw1t2Uy7KutAFng4cT4MiiWJZ5LUaHMQkOuxGnQ5NJrN6ickARLc7hRXAK/YpGaocWLb9w0eHWbMCFkQUZ5XU+Itr62G9LNMp0TYI6syT31umgs8FvSAYUWDni9kWHznvMfMRBp4jDcwuPt+7q9RxaupBlZ87IwUQjbk4Vcu+j7pkHfYOJ/dk5NWyrKIChRjEBiyAANC03JpcrSIIdvJ1TB+90cLmK6XTZoTF0RHPsupf6qM9mGZT78bOvA3dWnZar2nNlkMDSXCKGt82W3JrH/Jp5o2v+cKJO+YtLdYABXbP31g0en6nj1Dl1lM4HPdx3GiUr/sjpBI8bN4nEVq51JfXqd+1Y1LoYHa5NRkxcwovLFnuWjgUUCXzY69rabxMerB28QyYtstKHRGwAeGza42L05hw5nPQzzH3aQHs/+LDFQZuw3+n+eHJn0HLTXrkCn72/xvngcREdXjYC9cQl+FYDhmCIzIO1wyo6vGUnGIKHvDYPuoLmMO3KyrbzQfkG5L28svJoHCxgjNnhDUkwha6nk0Fw0CbsdoUTQcTvhvG5VsHlaoWQJM/LAEUDd2ZGDm00MNlplPj4WXtLLMYmO5GtJKyCrrNvuxfwy5+MOJq4vHZmzWgoxQw3pwMWo8PjswEvLxsc9w12mwREMadFKyleWbWKcFkmYNdK/gMcxuRymoG8Hlc5DmJOAlMUwKaSipNkzkVBrcZU9JJYXeSwqefCVH0f9XXeq+PBNBWJuyHZ50ja+C6nngwOupAriupU+muNR8KxECuxe2I2YBUU8jsx5uli1Nrgj55PAMv5ASzxs1Ifiyg6HzGxqJp5bWpUAMiw2IO+wStrwa25pkJYUkponeWDqyBwIhnujgBOjEh10GnOemWwJxc+BbhSAnbbaMQlzW2HBDw575XzIQnXpgEnfSkTOxs9Dicagb6yUtY64cuXlg6PzyKOJhrx7PjCwr990cC7Unt+0EZjmKuhfNB7iN0jPWXlc2hueO5T1n6oCODKL4EuvtH+PF63GvG2AY1T6DkkQYzAc1b6+9g05FQBU0MPhwb/07/8hUr6S1q9wBQWAMwtxbMYBakD7q08rk8Dnpyv8IP9Dr77/hRv3xvxWfshk+a8Szk9dnc1AXqHCM0/ty6hD2rsb8314LzSBuy1Ac/uKVrjmoCjSYPWOCIp2fMlvOiR2d13Vm2GAB/2HTqv97YMDn1wGX5FNhwxVz6EqFVDDspnedgLZr4xHovmtVnlsxgFRxMlWbFENqGQ9oaYcG/l8cRsxI6P2JtHfOS8zVyUxgH7syGXrH3gwQTXJinzbrwAi6SHREjA47NeKwYa/W5AORtv3e0B+97WRZyNWpLmDYmrU4UHhkysgtg6UoRpiILjnukL5Kj+YnSIXlGYbqrlnYOhd87QCvJ4ENVZuDYZAficijpeO1y3Cqnvvt/gi66OAPR53115vOvKyngEmta4MR3wsXNFIFbrJpOkn56vs1PAUtqpj3hp2WGniTgdNDjovDrjp4NDa5yWaa5+cUZG1DTrQRvReT3MoqU5FqMgJiXSAawcajCYDbvSleot8lOmTtMhV7uUEQ0vyVCHBrfma1zpNNXYm5N6YVyQqY+Z6zR1CehiRt6OJiOm3uOkb/CDJw5ffDTiLTu6lp9beAANHp8N6qSL2uZDQ6OO1x77XcSLS4d3H+gaCYbuiaSsz6BpCKs6EGAiCUdWJTdGyftpJ5WUiEjCtUlBe+g8B9vHJ4MFFLb36KxGW1+LQQnJ5F2cm+3cl4ijLuIT57Oc1rw+GTFaauvuyuPd+x4ffKiVI2eD2neWuNepoDEIntzRtByDvqURvO+uWvQB6Dxwd60p1x2J2V6NCeikiAeGnPaQjb/TOWCZakIJ+mqUIprDlbDJlRiTOhLkbdCBmJlDkZLgv/vLfwY78x2cnp/jS77oS/CffenPQeMsZWKfQ/FHpmE0lVL0o95oPBKOhReN9H7srMNT8xFTH3E+NrgxjfjoeYO37wFP7/Q5r+8FefEdrxt4g2VSEpyMesAymheoE6J5cY3gZk3ENShisAxdJkg9HHxRlZSEfa8VCMvR5zK01qnn10fBIjjMjNsRQU6FerX6b4ejicJpi1Hw+EwPuIRSC/7YdMzRzSsrj5tTzS9zcx5YKdFbdvSwXK58jtTVe085z3zUjZg3AevY4u6qwfWJOhcsRyKE2ErK/91deXQeRSiqErAqGhu6KHeakPOeJOY5EUx8zKjFSV/SAnuN5ikdgHObW6pbXgSmiBpNv0AjZ5Eml6tOXcLti6nOhcHxi1HTLA4mWuaVH/H4TB0Oii/NvfIG3rLb4wdPJnhmRx2Qs1Fh2jFqeu3J+ZCJlCTj0rkiQjNrIr77uMNOI7g5ixhF+QDUTZn6hE60htybs0ei4sng8cLC4fG5rpUQBc/uDTmH3bmEFy88/I6mVp6eD5YOc0hJ0RJWolzvBnhR/seYBEetvvbJua69w0nEfjtiOXrcXXlc7SRD83RqmB4gKTQkwffcn2G3SZmA2TdacROhUfLZ0OB0UL6L1sXDHATJxNUxKenrwKoseivDZWni+SDYdcD1yYBzrwJC99YNGtEKrHVUVONiUKM4jErEXoweF6PggTS5zJoRPKDR7Nv3lFzYeRiHwuOj5xNcn5QIi44CANxeOsy8iuidjVY6F0u+uZWEU0uBXeliJm5+YqGVWfst1XLVEZ16TTNcn1DgCrn83VtwdNTFzAGaG2LTi6YbWaYNmHqvIO877wQn5lDsNCGT+SaGhI5R8P0PJnAC3JhGtJZ50FJcRaiWRPisaqTzWlrYuIi5n1h5vjrAn7M/YBFcLp0O0NRgiIK5CZEdtAEHB5pKfNg3VlYraJ2mUF9eNbg6CVmX5eHgc6AxBn2+JH1TJM2hEH1DQq6wIMIhlbOqwYzLIm5j32AddR9SS0YDFrXFQ1QNFSKoIsAPPWzxhKXdjyYRL1w4fNYeOSxqY15aNnh6R0uAGSAsRkX7Jl4Jx/odEddN9+FopoT0a5OQ7cnTloZluo6qnVTW5XPXszDlwxzYVCymZS6/K2ecKnzqZybRICmKrVMoCkFkgiXNEcDv+e1flx0JFSfT94xJKmVSGIqZ8HBQBJUK1a83HgnHYkyCBwbDkuT49FzFOD7vcI2TvsG9RYejSTAFQ40CjleqKkmo59hU8xamiXHSF3U+QA/NcdRbfsXqiami1ttBR2b7aFEMGeNkzvcR8KLfH3N0AXSiC9mHlKPYK8Yf2PER0CID9FFrzu9FEpGUlX8RHB6bjTmtQdJqK1qCdHcluDFViPK4b3A2SBZ4WYwOfcBGtQnLtijidWHVKykBc4vyd5qAt+4qp+LFpaINy6AR/14T7f3IpZOs51c4T+uzDzvqhOgh+Vl7Y3Y+FlU1ykUQnI+N5SOTKQR6I38NuG0iTRRI27UUkZZXAn5HD6DWJey2epBmCXSXTDypyXD3w+hxY6qR3JPzkKNrzsFFEOw0ysKfetUvCUkNwmg5xDEKktM5eNeVMSMZatwlI0IK+7pcQeSENedqNN+2p5/F3GQjOs9a+ix4ZnfE3ZXC7yTPzgy+PVk5vHVXHcC1rVHukYtQIN0+AFMPPGccihvTgIe9wxMznet7pjehwlQO6JA5NjdnMaeljtcJz+4mHPfeNFc0P0uCLlMsJChSKGoBRreKp2qUrvoBnVe42Qkw2JyEJBnlWJheAdVtnQCzNmIdlQDXeXVweDA6Qa58uBgdjteCZ/dGU5xUx/LuSrkfu61+R0yqcts5j91GdSEA4CNnHa5PgzmryCW1s4apNtWrOehGiDkSeybINPMBK6/XPSbVBQijA0SyTPQqluok6gN4SVgZQjY1gqqWRnqc9Am35irgRyeOyKkzW6QEZ7UF3iU8MYu4NtWy2Ae9w/FaD8QhCVbG09htA25ftGgdcAB9PveXHd6xP6LzEXttxL11iw+dtnhqRzkmp4POISsjoh3YRDdXwWUdiYOulO9fBIeXlh6Pz1SMSUS1Hqg4TGdvv0UOANnagPtLq89MkhpFrXXqACcuoxkUNVsGhxcvCkcEKFUch53yMDqXMHVM5yqPzQlw0AQ8u6vPYOoSfKskzZvTcnYw/Smi/L4DE2B8eeWzUzj1ET961uL6RKuGVBDO0E+7P3LZNN1ROEURxXGgzDdRVPIhQlXdQbvqKoeDXAu2MxhTkTcHgD/71/48/v43fSOevPk4rh4e4XPf9R7813/oa/Hen/sL8L73fsVm9YjZ+cbmOSbJ/Cru2zcaj4RjkQBcm5bqjdXgMvGLhpYP72z02dOlAiIZ1t6ixlIXzvIzj+sTjbbv9yoc8tSOfp8eUFTgQz6oO5eykFUfnREY1UDuG0xIOWONjHQqqXExRj1UH/RNdljOB48rnUK606RwKOu5dxpNt9B4HnZjlmTdaSJuzQS3lw7P7o5WseBzJQQhdb1WwZ5Vljzs1SDc772JpeihvRgd7oyqrnhz2pt0M7JQzn0j2U2dzl2Eyzl3Za8n7Bn5laRMMYPpAJz06vBNveZXI5CRl9Hg7VcMKjwbHI7XHV648Lg1D9lJHCNK5UxQAavjvsVJr4aefJeTvlHVvJwzVcescVqeR3Srj4IPnkzw2FQRiJdXDeZeoc7zQeeY6+bM5pX6KFqiHPMa3GkD/ERRI1YJ7DS6mWnUQgLayqGj1v4r68YqcRTqPDDy7fXJmJni3iU00Gf/zn3V+HhqrnoG5HJ0XssBaVwjlO3fGUqwtEP1fBBEKFv+eN3gpPc4msQsHqeEQl3jj89G3JiqkuVhF7KUNCXnmXpcR8FDKxOlvPZidBrdGApCNGe31fetg7P1rhLUrIiYe91zs6RI0ZCUtKpl3IoqHE3GjG6xNHE0Ut/UJSR4W7cOU+9xNlKmWbk+T821HPLte4M57Am3L1r0sZRm7ralasbZ3C9HwbVpsJx+g5dXjaFYqmFyd90iRCV5Uw5fyeZW6i0pp1HXUVOq5BZwnAyakmgk4fo04dZcK4NKSwFde0RGmUI5Gxye3uk1yIqlimOIwPWJiZr5iOBK+e+DXvCOvRHf98Dj7XsJN6ejBToOK1F79rZdnY+TocFy1L10NjqrKJMNkjjRr8dnPe6u2+wkXGkD1rZuyDM6moxYGjdizxQe6+oDDeQ8lgGZo3ExCq4a6vqSVTjtt7qXuzZAkq5PVqjcmitHjarNx4buChq8cOHx5DyY9o+3KjY9d1qXsOi9CWRpRH80Sbg2HfDPXxR87pUGbBXx9I6W/o9JEelrk8Kp61zCk3PloXzkbIJb8wFTKZL2q6BBKVMZtHUJ7IFkvUGQ8M8+doK/8oGXcfdiwI15i9/2+Y/hfW87AMDeJ+X8ZL+ULBiYgNGcFqIaH/ihH8A3/Ytvwrf8vX+KGEe891d+JT73Xe/JiElj5M4mp6Us/WHOhUAdJycOD9ZF0fX1xiPhWAg0l7tvpaERumDm0M3E0iLCWY1LmEIXz3LU/LZY+oO9DLRGXg8I9qNY2UF4lqgvELIOBVGQqUsILmUFspiAh72Sqa5YGdfSoKDFKLlO/mqn+cOl8TMuQiEHeXGlRCu/v5BBCZECyL0QyKCnSNPUR3zW3mhKgUW297mFx9M7IZeLepcAK3/ab1WU5vpkVKh50EW0tkiDxDfmlXtL6UzsEDkzB4sRFWC69eZAqMF0pvEfc7R5xSBKCrk86HUDitOcoX5/yR+PUfDMzoiPnqsw1s3piCudpsGe3gl4buHx1E7Ag7USFTmPr6xa/NiZ4IuujlkIqvMpl5SemkgP4e5btulVMz/h5qzHmBRq1vtXB3LPDCaAnEpoJWUoPaKQBSnqszKI11spGXs10GiyzHJthtALsEwuV4ow983DXHksGh16SdhtR1y3yOZB3+DAB5wNyhWamcej0uAeN6ZajaDy5E3mb1AL5iPnnVYZhKJ7UWt5PLOrDua57UUeIIvR5edK+WFW7bT2b0pSH7Qho2Z0OEl8Xga9J5bwMU0nkjBzgG/0u/aahMPJmFHKVdSSc4r8cJ9xLV1pVcDn5lQPx5SQezBc7bSSgmnSK155NavgMhL1+EzTrZ2PuSImJfbR8bjSRitL1wh6avYnQnDorCTb+qsQ3qexp3DRhaUHqGfTSsL1KVFXrRxZBYXnd8TSuDAOQXSYet23AwSngyJ0nzh3+OwrI8aoLP4xAevBYR0cbhjxdoySI/DrU8GQkIOIuSmn0v4CwG3jOK2COkTLoEKDM6+cNDr3DwefhZzYF4Wly+dZxbSUot+cqu5ISkoiHILDWa/E4llVor3XRBy0ul4ugqbFyA9brtXpodT/kAQfOfd415UBVztdHzEKnp6rXoWWnFOxsygF73eawn1o58pHzhpcnybcnA64vWzwsfMOP/dGgJeAV1Ze9zDU9roGmZs3tbQ8+9fcW+vcsb8Q2ynMfGnQ6FA4ENHSGAmacvjmj57gT3znbaxtMl6+GPDffudtJABf/tbDV2lW8AzN6IRoRUmtm/Lt3/0f8L4v+3LMZjMAwHv/8/fq5zA9I0CKlqrONILCsRBRUcTDbsSVDrm1xeuNN/7tT9HwUnoQLEbCxZRPFky9RrIzIwK+tGxxvNbobUx6kO2YV7/XlLLSRlKWqNY8oNuAc1fBWRmZRkoPTR9hvw04sPLUZTABFCP+jZaLFIFFKBGLURv7vHChKMDdVYvl6PDR8ybnnWMC7ts1U2ciJuCp+Vpz/kbEudKNFukpA/1+r1Cellwpq3wdNfeouW6dQ40CUzak09yMJpp2hkHYQeFlOiGL0WeUBlDNekrbDlENyEEbLCWh88+KB/IsmCZZRckEvpBKAzj22OBzbpzWkI9RHROtmBhxdZJwbRKs/j3h2b0Ru03Es3tabnili/jImWSlx8UouD41ZT9DaeZeVS9fuFCDqToAunsmLuG+VY/MGyWUkrHvABy0I65NB3Q+ZZIuiXkng8edVWvwvuZso5GuTmyTMRKho3huyoSEiAFgbbl8ko13Gl2zVzs1RPfMaK6jM8lnl+c8JMGHzzRym/lgjnTC1U7VWNf2vB70Da52AS9ctLg179FKyjnzddQ0IYmtne0ZOgXzRu/jeO0xGJKy346ggNHUiK48MFm+BuhBxXsiMja3fX2/94Y2avrxahfwzM4aE6fow8yXPj27jR5SMyPGHffK5H/xonCdKL9Dpy8lrda5auVwKj6mVQhno7c8vzo6rUv4+KLZaLgWE3BsUfdHzia56mFG5M0qEJbBYb8d8fKyw8fPu0yAptT0xFnFThTjlvhsj9bmVIioMJQAhpRF20c6f9emwYSw1CE+6Mr8f/Rc9Vb2Wq0+SQl4fJ7wkbMGDwfJ5NCJU7Eslv7e733e99cmWuK6tnSsd8kalpmtgjo2zy88DroxC2g9Phux16pTzHLE0pW3CMNdt4N019LMi1A0MLS5nqZ8H6wbLb+2vUt+QR9c7nGxazbfC7KKZ+d0DokE9kHwtt3R9mmTAw+ux4M24Ggy5P5IDsDdlTO0SatXWtGU0sfOdI8ctAl7TTKRNA10bk616uPx2ag8vUlRwR2iBmQMFPqg64ykS2fIBffKmAQB1s1WSmdUAPgrH3g5OxUc65DwVz/wstp6UFZcf8e5Zymxpl1Stk8crEjhJ9MRUXJmSSsHS32sQtEcEWiqjyrHVz4JYvGIOBZ66HtRzXLmbRPUyNzv28ISjoKzAXawax8ENsViJz+SgETILtfvaZ3Cg2ymtGsOxMwOI9XzbzL7escYznNLp3z8vDMdf43u7yx1+uZGfGPqRqXBE3ZNqe4iKPnr5kzhbm5A5YW0KkpivIMXLlo8d9Eq/A+LtPoGr6xa3F52GfFgWZs2Soo5/3rTRI6O141JlyvqozLROsckL66Cy11Bd000xwE47RUef8zEkdjgiA7F2pQX9xrVGWEExyj15ZXH/bUaxcYlky9PmRcxt2ew37I/gsn4RlWrnHrti/Gg91mLxNsze8d+yu85mgQcmmRxsI1NwuXRRB+6Quc6N3dWDeaNRpz315pKSklLbr1LOBkanA0eHz/X0s0zi0CudgGzClXitUycRnmPTUfrhxG1fjwoge0TC3Vc1ClprBSyStP5mIlZ93uPe5Z7rsXGrk10/dxedlhH1TiYeVW81KZMgh87m+CJ2ZCh6IM26Nq2qqQ7qwb3e2dS7Q4vLV0WUDrptWyWHUkpiHVzOuLQ1u4rqxYP+wbr6LLDsLIy9oM2YDFqh8RgzvOdVZMN3bkx5vdymkAyt+OlZYcTO/AbS2OeDg7PX7TK2B/ZR0FTmk/thFxaGKHyzkfdgJDUsX7+ogXVe19Z+4wwUSFzr1EHonMJ+23RezjuVYBrpwl40HtcnQSt6gis+JHMs2LLgFkTcX0acDQZ8eKywb11Y9dBm5ZwMug+un3hcftClWU/et7gQeW03lk1mQ/CBncPep8b580tlbIy0uX1acBJr4JNIjBS44B37A94dm/Mz8VLMg0ZZ+nYoii8NCSGasGd074UY5Is8NZHwfVpyhotZ4MpDEODFaa8VlGyYB2gDtN+O1pErsHbxajE5QhN/dRy0H0oDdhoE+l48jPPRocXl5qOOLe0MflWrArRP9VBIFlVbZ6mCz92PsmBTQTw7O5oOkPAD52qA7TbBrznsFQAUqvlfPR44cJnVD1Cg4bWkF0e1HSEWO5OVIRpi2QlvLmFPf+eSqv1mAQvXwyvOiMBRS5og3IL82RkTvMScmt0+wpyfb70i74Y/+Jb/yUuViucni/wv37btxhyYs6cTbaASIpytvQz9LpC1LXwwEjDbzQ+aSpERP4GgK8EcDel9B772d8F8Nn2kgMAJymlLxCRZwD8MIAfsd99e0rpaz7Zd6isasrdG0OSEmFHZdc/6Bs4qyt/ZjfkPgyDzeC6IoWRq7HT6IN+/qLNcJ9DKn0LXKmZZ7SkTc2UCHrFNvZJz2gc6KNyAbwkPL2j1+gtatXNoNDW6ailTyeW52fZ0l4TsbaHSH2FJgpeWTe4MRmxZznls9GBzdTIxUAStC7m+1B+h2pAUNIcQK7SIBP5fl9avz8cVHacpaoC4MZUy3BXRg48nChZk5AYG115SWhTMoPYZseA0rzsOfDkXBnSD9ZN5iowOuqDIDq2VNboXISOXsqphXXUhmla1gXrzKd/jsZbWUdFLXYazTsfWnS1DBqJ3JoF/MBJgyudNlK6MR0z7H5zlnIUSREpLadEdkp4IJX+MeqMPugb3Fl6HHR6WLEFNomcDsDN2ZgrjNjttDESJHUZJi6a40ylT0W/qPpJXgbLS1d2jS7D4glXOz0sKLs9NR2Nj51Pcj5fpZTV0Krh1r1wZ9Wg65L1fAAem414edlgv6vUYI2kxWiXLP6JUwdLu38G7CcxRE5L9hhRU/qZok5jFMy7mInWTMlpqrDwHLRc2Bl3wGelz7skIxon6fZS1Vw1soyZpAogp6+Yt15HyZ03V0Gw1+ozTYPHnWWLx6ZjJuUdZME64MNnHk/N1Ulml15N7WiLgN1G9zFF54L9bmbX8di0tEYnyqc9IJDt3X4bMtH85rTwVhb2WTtNhMTSV4TrjAECU7mHk4gPPfR494EirkeGACZLQw2WtoDNydyi8jvLBssA3JprOSZTgCvjku23EXutps+Y9gSAa5NRheSiZDL7AzRZM8hBq71UkwfZxq4NbZ7bumJpq4plseOpBoODCT2t7d8vLRsTdEuZMM1KsiE6s9/KjwmpcIZaQ2gPuxF9dIgWjLxjrwGgzhAP4oM24N7aY4i695RYLWDJ+cRbR9VQUpn31o2te+3/NPNK3H/Jui5T2TnZMxUp/AgHCmQBN+btazoXN+bthppmLXUvUD6ET5qOiqwQgaYEP+9z3oNf/OVfiff9yl+EW4/fwpd84X8KNlNzooT9mIrGBueePLdkNiAlwZhUmPCNxqfCsfibAP4CgP+RP0gp/ap8QyJ/GsDD6vUfSSl9wafwuXkkmMpe6PCgFxxNTFRqai1cuxERsNRHsjrzFmvvTF5aoffBaqbnvnABxoQsSCWiUCEnKwvmZBaxLjyFAovkcGMRjkAPsVYSdiYhG9rbFx4fOl/hy260uf2wdvDTDbEY1cjQKNy1LnEiCWyCRU93vw1KLDSSHB0S5ZfoIjxoR9y3JmDUpmCXzKtd0EOmCwBUQElb7MYsPrTThNxiWOuWY+4VMk2SEYGFQfL0shvz0NnpU0s/ndVdF3XBEHWOV8HhyAdDSTRCIylVe5+QFa+fpU6CNsM6HRo8Nutx+6KzRlEwgS/t7UDi4n4bcW0y4BWDsVMCWgGOZrpm3rJTuDTOpSzIQ1IoRZey2hy09FkhVj2811Fyj5U+aNml9uzQ9TtEAE6wa4ZRRCOalfXQAHQD9+acPhx0nR50CU1Kme+ja9AZFKn59b2G0SFyu+T7a8G1ScKHHnq8bTdCDCa/azovPOynzt4bgf2J8m2IrJ2Z3gLTR/rdCsPDnmdrnAw6QkHUOI7RYWbkXZIhW0m5xfkQBf+Hx+7gs5/9KL7nQ+/ED9w/1MqlWBrNHVpTJqoYUiabuXlWHExcQm+pIMCIw9Yple9bjooyhKhkTIpieVEHh9L23GtTH3FTU83ZIfSivBQKfp0OPkPnh50JEVmq4NjWXkwaHKyiYNcQjpAkI5Y7jVaV0PntzGGsK9t4ndRzIQmZ3UBbp7ZMiY4qyHY0Ubu4joJr08EiYL3+k9HhnVeCNUvUYIPVZSxRP7BKDtW8URTpsalWvVBw7qjV72DQsg60rRGnFeKw0wTcmGqaYREczkbBmIp0umrMNFZJo46HVk6VZ9pHRYaiXTOriXYaSuADu+1Y0l/i7Luj9bVBVhZmI8Vr05jLJJfJYd/rmrmIRv41u66pJp178oQoSEdkhhVnB100fSFVbibyQi7ZnvG6DrsA71J2xB6zbrKsBlHxqQQP3dcFrdDz4rd9wWP4E99xG6sqHTLxgq/5/McAbPb4EBR0AuasMKnCzxWoU/n+r3o/fudXvT87MykBv+H9vxn7+wf5e2qnhc4FP4McrsemY652eb3xSR2LlNK3GRLxqiEiAuBXAviyT/Y5bzQ6MwCL0eXW0SuRjWiYkeFhqw+Jzcb2bHPcXWn/kN1G5WgPTFSGVQk0uMxvn/Qu53Frkpk2z0EWWIlJF/heEzDzko28ytcqmvDYNOJ4PcEQtbsmUZTrBmN7UUO906i8NaDwa+cU5Xh51WRt+xuTwbrsqeQ1dQ20y5wS35jK4BzofQekSSGzsYfIEMWEeoCjRsvKmG/35vQAprGQxJroaFQ3mvFrHZsHFU8YAC7MOTnoYt703rgeRDuAgtrQuLExF4liRI0oV9y4iC4BY3QmTuNxbTrk1+63miO+CKqUedI3WAeHe5aDvTHVuvsLElqlEBB5aB33muPea5MJU7lMSCQUejGyWkCy/gcbWEUjB2olSDGQFNS6sBzrRSjNlxjtnBnbHjAhr4gsPd9KkYUm1LwYgb3G5dz2E/OIHzv1eGKuXTMPOp2jxSjonOTPYApr6tk4zITBoBD0QyM3nxhf5IEpsJLIebL26INWdrAXiANwNgCzRLIqNspSAS3p+5EHR3j++67g4aCckIgSYRNqB9QpXkd1+K92WoorAuybo8X+CLV+hmp2aHnpxFJtrKtXASmN1LXMtslpVN4De08AwFJUa+ahCYpR/h9Ahr2nXsugWS76oFddisYn08ZJVvEg2Gu1oofyy6yoGZJAIuCcsu9blxANOemjoHW6R2JSBclV0AMVUHvDfiLHa7UVE9uvd5Yaxe41IWvRKPE1WICjDtsALXudIuLjiwYHnZKcuXd3WrWTtLNUy4xJiaA7Rqgl32YdJTfe4txTSGneFITmcDKiM7ItyerHhio5n2xNRyzh8j1rCWmJ6rkX+lAI8EzLUVZ/FSWL8b3Yt1qFZjyQXbMVa+OF9VGrZ/ZcMmVOqyi0CrDrk1FLepPe5711i4mhHY0rGhBs7ieiwd5i9PmMPzCRrrsrFRSjxoQqmlppraOWjKIVytESvO+tBwCAv/x9pSrkaz7/MfzCtx5mmyrVX4qoVi0Nzl/rd246Izq+9g//HixXS3zpF/4ssESVAlnc2xRkc+aMHU1CtudvNH6yVSH/GYCXU0o/Vv3srSLyvQBOAfzBlNK//WQfEqGHjkAX3cUIXOnUGJzTs7Y0A2FTkiDHpLB55yOuUVVtykY62Iimp8ZcnkJbLzN6yBvCa3Mb6tEPFmFOHNA6yc2PSPoak+Qo5t0HqvEQLCe5tFy0LlrJkKUTjWKXlvu/Z4ZCc3+SS+qOuoD9NuZ7/cS5wzv2R7y8UlGhCNWtIEISk2CvHXE6qGBGcECMCrH+8MMWN6ZqGK5PRqxd0R8gaxuAGbiUiWutJDS2+UUSvKV5FqPPMOZeq8aI6M1p1KqBAK0JX9lhz+8hatNKwklODqo0cOdi1uLgIbAOKh9N4hejKh4YB0ZcvDDY21uONcIEhqQYj8XoTSdDcG2iOX8evjumLKjPwGrePSxVo9679wlrc6Z2rDqpZpmTwHVQiY2xSVtdr8/uqxdBS0SnLuYulcHmKVceeFVfHQwOv9qpoNq88dhv1TlTgmSCiDoxjUsYguD7HiR80VXB1YlWBnQOWXtjOToTxFJzM3XaTfO8cvZal3BoSoh8vtoDJeV7I5pGMjDlkldR/+MzvwhalbLjSjluhO6zLE9u+fOJU/j42iRgGR0+dCp4+x4QkHC1CbgQ5YT0UbAPNex3lg7P7qlM+tEkZD2F5SiYTvS57TQaSfZG5t0xTszZqM45028pAbeXjfauMBXfaOv59rLBQavpSpGUW5SvguQUEzUetAdKNARLFYCZ5lLuiod3pQ9OKwlRVCtjFXSdnI8OwZpvdS5BmphLvbWxlMuiZNw3HRI+ct7hmZ0hI64q/Kb3eH0SrclZUe3MmjBSmggediNeuGjx9HyoNDXUpsVRuVnzRiXtWR0RksuaQNyrADISofOuETsrY4KhCDysaNP6RHG3svYuei3vT0lRQSUfRyCovV4kl9fkwr5jtynE8YlLeG7RYuqV18feT43TqjCSVwcjkLMJ5ccXKvtOu8T7AvR7X1mpM8MAeTk661ys3CEGIS6lHO1LMpJjupQeAfALnznEe99yCAjgUTqU0nHIaFeFSrAKpE5SZBXOS2zKmAR/9o/+KatIKboYQFYjV+XPVPqXUNEUl17/WuMnS978NQD+TvXvlwA8nVL6QgBfC+D/IyL7r/VGEflqEfkuEfmuRVhiMZKUow2/bk4V7p+6lHUKonnuLaNiWyzBIgl6ziRoas2zogoCio7AKkY0Wj8ZfIZpz430s2ObYIjA1U5rrkNiTb/LcsMJMLElZ5F2yqVd9KzZ0rnz6ilPXcwVLpS/JTRPXQ0ekCScPeid1rcnesgmo2wQeudU3OZsaHLNP5v7LEYtP2RjpOO1MuxFyC/RJmKnJpf7YK1lujFJlqTmfQPIIkhjRO5QyDLEVXSFSGUHxYWVrLKzYR/1+457j1NTWWydHqLng7eOiWKMbYVWG0mZLPaJRZs1AmhAIhTBag25YU8Kip8ddAoN12RS8hcAa+8spcskHQGSOslV0cMC+bO8lKoBL2UtaFM7wf/24DS3CL8wprtD6fy51yoK9aBv8PKysfSHOhxsxLS0fbGBYgSHnQbmkCi5bW2cC1YyHXUj3rLjLQWgTcV4GL9wofyGiUsW8Qd05gAxtTRvSgUQhcUigOcXygloXTKRLOsPAk0TdS7lioHeyI9EJ4gMkuRIHsli1EN2rwmmrqn7PyR1Rh6facWHcoR87tDpRfknYxTcmmtvFVZhcN9NrbX9995XtOXDZ10WDopJ+0mEqPbjY+fK43g4qLjT2aD8gpdXPqdNDzvdmx9fdHh52cEJTKch4KYRaNe2D4janQ+SSZ1nozbGCknLxZnmmGaHy1rcG+JSV0CkhOy01N2PlVCt64JNDdWhSTnYcRbEOFGniDy2s8HjuYsmV2F8fNHkMvpgqUZWApCATU0LKtQq2pjyut5pQkaoqN3BtuZetHJmaqhVRpqcOqZDEnNKNaXWB8lOdSvK7TkbHW4vC4GYhPIHvVb/JGiV34Pe4WPnSmQnJ4aiaTemAw66iMdno6HULqNYJNgr4uQszaHn0NIcqhodYqfknWbMiNjJoI3O9lpFiek4qICV2R5D42LBHwBsVm6Q2Fmf485scNbAQJEIZ4qNDgMbvvE/8ip4n+B7IZmkTLtYVEH1Vb1VqnUuZcT19cZPGLEQkQbALwPwRXkOUloDWNvfv1tEPgLgHQC+6/L7U0rfAOAbAODJyY00ayJuX3hc7VImhiQo8c1Hsbw+cPuiNUKSeusU8thpgsG9JtuK0tltMLngiSuHB6AKajEBDnrQx4TcdKoVbULm7TBsJWHWmgaFGXetxS5RP/PVPFCZlx8NqmsFmHYakTUGu1N86c6qwWIE3ro7Zu+8cwk/ejbBfhuzYiN5GWx1frrscDQZDWWRDJvConbKKp/0HoM1krnf+8yZoFIkQDTBmSJdaSG/HDUX3tuCnriI1Og1Hq99TjWQEMoSw9OoEQ27birEros3xEKSZPkZqyNgz+6wG3FvlbDXeLy41CZQN6w/xEHHZlcO69HBWXT/cGjwXccOX3ItmIPCKF05BoyIRUrDKvI3mOfmMyX0z/SI2Pyw7XmIonnNvCeAuVXoPL0LPBauQKDKgMlSSxzku7T2WRdBe3JQ7ll1V5yhIBE3ZwMerBsTydL0iDdHIEGNNcmsgMBLg8eMvMbulIRtb5nC6zpaXxvj0ZyNqifwcGhy1IikaQYnwI4PuDkrnWM1paXf3UeXSykpYLe2w4qVIOyAO9iBQsEt8RHeucwHsMxSfh7zRiN8IkrenJ1VENycKSeDFVDHa+01xIOE/JrPPRAMSbsCJ2i6807vMN2NuDAI/vpEnayzoTiQjUs4aDVqHZx+HvcOZdHPTEG2FWcogq4X7yIgwJBcbhvAFdAH/Yyrhja8uNTqMOW0lEoabV1gB0GSrEGjOjLlsyi8RONPomK0VMVo+65zRUyO1Rz7RppuXcLRJJo0v8PRxPRqoKk0VtSog6t7h05PtMN4HQTdRDtED0kwlWQqpXqtFLFjJV+TP0/yYXhvpc7BtUnI5Zospx9M/+fGVK9tiIJVYkl3ymicpr7F7Blyw0AIEJFy+TGg6SXAiLzm9E5EURsN4FQLg3owCA5ng8dJL1aerSj4/V6DnqNuxE6jqAX3sqCU5gJsFKZ6IrVbkZGHpCJX+triQMD4NMUx1/XGD6FTERMw8cXp0JJUWD8Q5PO15X6yL5fqOvTPwsdYjg5tqzaFTuTrjZ8MYvFeAB9KKb2QJ0Xkuoh4+/vbALwdwEc/2QcJCPvWlQhqVGZeEQTN7Tq8tNR0yenATqbmNdrNXgSNtskLoF7CxODcmKBNkICMkHS+kHcAPXCGJBb9qWFm1E6DSFie/TQIqS9GLbej5K7mvfQ+mb7QTo0uRxwCmEJccVLurhrjZSQ7tJXzQQGi3NUxIUNuU4voNHWh36lVMGLkqZSNQ0iqaXFqeX2BQrAkL05t/tj2lygI+4BcmHDOQac6+SyXZf5VzPh3Ltncl2e932od9CqIISCK4jAqotJgSqpT0dn3TFzCkUWuFG9io6CQBN9/MkEfBe/YL/XbOw3hTO3seqUdM4rAg+HCDt4IjSwdFClieV4fFdZk51R1jPTz11GNPY08EYsn5z2e2e1NRVSySiy1HdjwjRUCc+sv8vzC5whfkQZG+1rRAyBX86wMDVB5b2d6LhrVOejBt7SIj5Gx8oj0M3dtXalwlcvcHUb9lKFeGIP/eK3t6VeB6qsx33NIWv7JLrMiWvfeGYTP8lEAhlIZudC+L8uBo/ApqEdx0Gr0XhQ1XdZ4+MB9Rd/OTIuAZNkIkiL1M3eNjEi1zt024UqneiUU56L67ypotcdxr2yih4MeAHeWHs8tWq3OMQSL38MUYo3G8IDfs+o0EkP7KFkumQgqiZRAQVQ7V7Q9BCydTrk888zmYRXV8b+7UkXOj5w3GQ2iQ0En5qT32dnTckvVlQD0gKV2zdQnrO3+7iwV1eVB3Bpiyv5IqnwZrUyce0ayhhARLoE6R7tt0NJaT+es9AohYnVgAlwRYi29Jc+zg+6ZdVQ9is4VdUvq55z2DneWDgetfh7J0YAeuo05PFTqpUAYCcO0/xGFbMxS3Agti786KdfcOCWpUtPGQZHu08GX8lL7g0cySZQcNVKQbRHtuCEOwkoPvs48B4eCrApURp8OAxuZURrcVZfjpFABVkGfj+7f0o59MASFOhZMYb3R+FTKTf8OgJ8H4JqIvADgD6eU/jqAX43NNAgA/FwA/42IjNCqq69JKd3/ZN/BiHC/jVgGwQ1T1+uNbEMi1LyJuDktpVVzy30C2rKcERNleTsfIaMHm76Qk6ARfpGgJqFHZVW1oU4fVSmNbaRhk8/a8cYObI0o9T6WQdMIB62WJRLd2PEBrdMOl2MUrI0T4SVllUqF3vVznBlIlmHyOtdmgGhgW0k4sr4iFwZf0tgfr72ViGm57cRpGWoyiHMZSuc+5ronFey6tPkJqQiTUd5ZRCNVRpCEGB2AU4uGvFOkY4jaW4F10kSRmKtrXMLpoKW9rIIBJKMbhwYX07DSqNKR4dByRUszeBIlXY6SqW9BGFwjRs2Ns9EYDYB2RXRoTLhosLQE4Ub2/KCRbwxFGqI6bXqANpi6mOHUiJQbli2Cy+mw5ajRLLk7V9qUCZRj0vQcD9orRrBz0LJAap0MBumz+RUduYgSYZJESOn5nSZVjapGfORsgmtZtVabmN2ajxjscGCe2ItCyYzc765UQE45KSVlRU2GIQmiaEoipSJj3NlB1AeHB6HJXVGTIUFzHxFiQZHozLPE78IqJt66p8/fixrFqdMcNImzDilro5yNgnVsTORJNWBOeu2Syjb1nUu5woSkUEZ4O41F11EAu7d90ZL3mDR44bXSRvEAJ/GXBwlLkfvo0NvP2FyNrQjoxLNkmNfNoILaGr2hYfuO86/CXN4px+laq89KxBASp4Yul7GKOhGrgEwSZ+mvt2e31wQjhodMpo+IiF6DKR6wigYmxORMUl2wWDdobA2qaBTQeDu2RJ/XacWtYv+UPuq62zdRrpB0XwxR8t7cazXAIbFyZWnp0KhacudLSrhOD6yjw8kg2G0iPmYKv9rE0ltVDkxszeyUOcOvrDymXu3Y6aD9ptRB0rL947XPhF4tOS5dWFkdp+eIdoTuDUXwUkpdeaZtHN22BjVgLM3LcvkqBA0SPPSQ8pXgVgTgUa7JSwJsfRLREGg1Hb+T6RhyxwTI3Vx7S7u90fhUqkJ+zev8/De9xs/+AYB/8Mk+87UG0YchShaoUpVCyXLNqkwHvHQBXJsWKeUrRiohvAxoCmWa9NB4bqECMftt2ZTsL0KdfUZXV30h3jHKZ566FTohmpNtXEJriMMYzbg4GCdDchtrQsxTH/HcqsslcGOSzMgvB4DLG8ULI8uAh0NjbYubrI62GIuK5mIUPDbVw2g0Z4eHuEYRuohIYpvawmT/Dy+W55RCrFPugT4fqgZ6V+qnqdlxd+1xPmoJJFMHIZBAqUgTP4fOCiMIVd/Ug5EHAmvZ9xrlhEy7iJQcXjFjSVKsgxq6k8GjcwGdK2JY54PHce/w+Exz4INBiHSqCqQrG04FHVlNFzUZzaKgFDkYlMMWi1auWG28aqgAGB3aViOy5AhRSo64gs2dRj8eEx8xbyMOuxKRpqTQOFVOF6MYz0ZJkPfW6rjOPR210vY7JY0mNc9NyfeY4eLWoN7GJZyPWspMY6FlyEUr4WTQ75x6jWK0CkQrHLiGWlsrnVdC5JgEHZJ1ClWnS6tX1KE97Iomxo4dWlOfMinsgVVPkSzLjphUgZz7lKs2VkFL/dhi/qANWo5tztu+CYWxOyYrevoouDkLGdmkDsVt6yvBqqr9llwUdexeWXnsd4qeOYsqeyvN85Kyw80UiW+LRDwjdEAj4ZPeYeI1pUVBLxLHH/RNvqbeCMMhaTXWhR3+5q9nEqym9FJ+7cwX8uGtecCeObOUENdUWWNN1LS0snMu9ykiJ4IlmA7qFFJZlKlfVrPEpKTxvSZg4vT9g5B3Rp2aYqc7V3L+y1GQzLisYMisnV9akaPpLKYbArQFQ913iKJcXmBl5DDydikxFRQnb+IKafTMhLwohDVxCcOonKK1IdPXpkocfTj4rO+jyslFpfJ43WDWaBPM69ZOIqVygHvRFAP1IxSZYDVH2vg70xN0SGoiJ9Mp/FyGWcq9IOWS34esGA0Af+Yv/3eYz+f4lm/7VvzBr/sD+Lx3fR46UypmAM3+JUT0KIpIddM3Go9MrxBtwJUw9MDOREVqXJTcvObCNsx+GzDd0wV70ptBMc9bo0f9OT1TRnGATvjZ6HP0w3E+ClzwkA5ZgbJ1xUtjW2OKMgHIZLd6EOLtDVZuHLJAz92VN1TA7lmKdPJRlUs8Xmvvj+MgAJwJdOljejh4POglK4iuo6BLegAPE10xefMkzVUypcQKjZ3GNkyk2qW+nsJL2pIb2QAzRx0NRQCQy6ZaSQgA9ruIqWmKEMpcBUFEYU7ToASbz5BUaIcyzyRGEi496TW/qe3JtRTwsIu5v8RidBicrQcfc8WNVtFo1csYdT73GrE+BILbF02OnnuLjM8M4gQMXTAHQLtiSibRrSwVQekaPWT9RtUHZYyjRYgwozl1CRGlZ4YIckSg6p8BZ4MHoOTWvSZmp7FNGhFpQy89DO6tvZE/TThq5fHOWY+zocnlxDPTH2AjP2os0Cklj4KtsEMSHBvH5cY0bkRFpVxboyXqV8yszHRlhNPrDTLETN2KywxyRlKrUAh4e42m2+73TeY8jEnbbE9NN4VOYx0tpaSBxWDpoGVweM4c+tNB8HSbAKfr4OZ0xF3rJeIFOFupQFtnOgas7tlpLB1h+a29Vg/SdRQjjBckiGJbTJGxsmM0bg9JiFMH04GRrPtBfpPKWyvv4MgqHihOBCCLuF3Yc1xZo66jTlMYEZoKWcB6ULjicCxGQduJKfRq6oeE5HVQB+XGdERKuo5eWbWYGQ8pwmHmS/8Q8kkmzpr4NSk3l9P0TcyHk5LqNbVaC9Apylv4DWeWqqZjQ9RnHRxWtve4dnetl8nZINhpnNl2RalU7Kvo8bA0uZOE/SS4u1LnIkbVrRmjQBws9UtnRx2KzlCVeyY5zmoSEnjvm2z30zt9dnQZVFydhLyviHDN7QwAYOkMVoAkOEhGbfgs+eIErTpkIzHlhxRHgt5E5L+ZckGpEGG6hXs5Xd6L5rgyhTJedoAk5fNZBPjYuXYZ7/ylD7o0frJVIZ+WwajNC5uI6cTfmGgLbnIdvHlNO740xaKAECdopwkYotWQBzXSNBSDGQGAB7sazKNJyGIoZDwzx8volh4aqwH4M5I4WRvPDcR6/YVFQoBG7lc6NfuMsJEAAQAASURBVGp8z82ZMrRHQy06XyAnAHhxqf1GKMByfaJksnqwPwOdnit22E58UbQLhKFBjX3ZIE8BZSFNXMp8B7ZmnlqpJVVNKcXL8igiEBFqJOg4zXzMaA1LdGHXEKH3PDMBM1WgVP7BoTWNOhv0mV0ELY3baTQy4Wcsg2qZENZlrjYC2G1KJQhLlwnjz5qYGfSj5ajpEDhJWWI+E+TMAfOWJ9f0nGReQm+tucmEZyS3ji5rilANlagQ19HMnnUfBa9YCotNtLhuqb0y9Qo1kwfzsTNC4hFnQ1NFw7r+Zo1Cxvd7yaJnJF4CyNfkKiOyDvpdi1EdsidmI3YsvcQyO76f+0Ah7pTXGKWvh6RIBp3Ni1FRhVdWHg9765gZS6+a1uD8sQoG5peiI+abqSlSp8YKT2FTmTAmJfDemKpA2JAEj88GTCwK/8RCy7zv2fyT6EiHgQx69icC9JDVlCq7I1t1THQZQb0+GXE+qDIqSdl9UDI391zhUqVsC0T0GqkoTIRhpwm40mn5vVZ0NVYtpwfglW7UNKIRJFkK+0Ql0jS1Z9X5iEPridT5cnCe9B73LZgJUfIzpp7BkDSKJSGXnCByIbTSzlsDQp8JyN72zBiLFg736sRpWqf0+wm5Moncm5DU5sybgmydD+pwDGazyTWLSVOaJ32Tq5+csCS22D9V9NW5oSLpXqsiaCRXc48QsUlJ0/C5aiWjvtoRm+XfY9RU5p6h2kwv8D8e9sWRqPgX1bplkMJ0bAIyqglgQzFUUxuplK+iOAp/7q/9efznv+Tn41d+9a/DRz7x0ezcJQApRrz/D3wd/tRf+FO5jxUdmroCch21RcBPOhXyUzUugmDi1dMlUceJkvO48Y7XyhZWRrPDrdlgPQc8rk0ErFW+OYv50JxbXT+FaBpBZnRHUDyqSIizLTAfrEMp8wPUYNGIUNEvpVLFAQDsNDr3ESuokbk+DZuLBZr3SnYwTQxx4WewhIklhCSvsonTSVWWuhi9Md21VHG3Nd6Ad5Y+CnkeV9Hh4+ce16f6OY1F0RdRhX+mXolmY5TcRrizzXWeHJwRA1fJAaNyGHorVRqiYKcNWUSMbGaBGp0hFOdur41Zy2HukRGCCaMfJJMz5wGsxnK3iXhl7fH4rCg0AgrXzprSN6SVhIOpIhsJRVGQwi+tU0fjfHSlD0jkMy7RBktq6XSQQNZajr6P2mNjpzGlUtFGchfB4e5KZd2v7GhJcEiC87H0S/EC49sgpy0Ou5gbP0VoOm3X4OubszGXCC96NVg3ZuVQPqZyZJKsJsjncLUrzs1o5zSd5XWew5Rz4ENSxU4KG0V7vqx2IDcoJMEEyVq2S04bAvoZ0RxrlhrPDeGgCNQqIOfz6dSr/Lga/iMTmWMKiR2Ohyh42frRoCuObUilVTsrlEg87IPL5Mw+quT7GI0nYxVipQ+G7hVWbVF9kmV+DCi6jKYURIG2gocpBcamtgYG0VTqhRkEEsFJYkSlexOSpnZGp/N6NBkxFVWZJOpEmwkAD/smkyM1x1/aYKeE7MRf7QKmRvi7s2ozGnU4GfHSslVnOQqW0D0uona39SmX+7JxJB2vximatxgFMRUHlAgCUAKqMRXytK5Z5Ko3coemrvTnEakaSpoT5QCsvctps5lXZICcOTqbQxLMmsJ5oBgVg6LF6LNzzIqZxiXsu5TL8Lsm4iQoknjFiOSUFdDrA1ZJcmmuIqfKpTheN4XAXx32HCRjjknPBBFg9tw/wd4H/xz88g7C7CbO3vM7sXzqKzfKSyW/v0hxJ6vjiPTFDQD5/h/6Afzjb/4mfPPf/WeIccCX/6qvxOe/6z0ABMM44rf/vt+Fd37WO/A7v+r9QNI9IRZk8bsYuNbX/nrjkUAskJBrnQFk0tqZRcedT3h81uN4zQZZegB6R0ltJRypVyUmnKSs/ol5wOyA2hkpiCx5QpJAqUihwwAUTgANHyfVGzS53wbTRoiZ0NdZGdaYxKoN8m0CKLlrhRsFVzptCcxumLyexejw2HTMTcf2Wi2NWwTWket7nJF5xqS5XrZu5z0wn87FPalKv1ghou2RE1opnjB/n8z7J+mOXANGm63llVuXsLLqFQBZXncZVM/gtHdG4CpzSNXKHR8z5ExUxImiM4SLvRlUqniSK3AxmsFHEeqh0zW1nD8b0t1bedN9kAz/OUvfMPr1Lln1g2TUgnl5wLhASczh1R4nU0N4lKSmh86Nacw6ACzvDHZfAHKkRoP20EiGNG56b3qdEaWcmZU9nU94ej4YAqZogOaDq7I+qKG6YsJau632gmHUxpbR5LqwimfmtYHSwur2Sbw7tIiYyAgRwFIVBJwMKkw186WbbY1ecT/uWeO/1pyhh72mJlQOOeLQhJwmLmadGCWv2n4V5SZoQy9vokTeHGQ9KCi7zOcwJt1XD3uxbsZWCtuY/HeSrCnBqpKzQXPvvGfuicKmt+qcZIGKvdeJpkLmds/cN1oREfPcARp51zYoQnkKU6cCb31U+7YYvZEjxXRsYk5/DlGrV47XPhO8+awGQ3cUSStcGpKuJy4aYVbL4tm8cUjInIy5CYxx7Y52kBLVmTh9Pxs67jQxVzAxoq/tIezn3A9rc1xTggnrFUTVgTwvE9iC2uNZEzNKCNv/YyR6AWsV4LKdo/PC+2N/lrvWOA/Qyr2cSrB7PRka3F153L5oMrLNihWuFXIEuY+ISgHqpDPqTygj2Rwk8xhEgPnz/wRXvvePoFm+BEFCs3wJV77nj2D63D/N18RPJsrIJmxAKTJgFQgS8J3f8x1435d9OeazGXZ29vF//HnvzVfw+/7Y78c7nn0H3v9b3m9oSCEZx8SeI8gtCYgEv9F4JByLZJUFD3qXPeWVqRJObAGkJLg6KQpiR5328pi4iLfuappg5nXDTo2ZTAgnL1Azbky1iHmthP219K5UQWQVQ4tWgQLH9aGUX+02aiROB68HrBRtCKAo/PVBS8JYDkoiJQmFdHzWFmF09t1UJjxoR8x98fK9RZbMxV9ptdsnoItLCVSWwhHmKoGjTufquG9w3DemH6CGYGIGmY4RgEwI1RJGvXft7aL3wE3MCIOOCaG0mLRkb0yqK6E/K4aUsK+SNl12Bshr6Vxh9t9dKSdlFUv1ydSnjHQArBDR3hnenu/cl0MsJMlkPUbjU6ti4EYNhkCxMyxH7fRpaXNZx/odMUdU+22wNI3C5iS7UUtgZaRMTXeUMjA6siEBV9pkwmlaO69S84rsUDBuynXvS5MzlmMmmIS3re2HfZPTRb3tNd4D54YGiWgFycreng8/n70NVlGhfpbS7jQk+Saw+RrLSxvbc4AiCrutqltOLAiA7S1BcY4i9BmcDz4fIPp5heSq6604wyLsmFwO67k5r1T2zciRrSEil6zCmTjdUwddzAhiThva/qP6aOlqiizgx0aJEeRH+SxF3dP5Nz2L3TblxmrUIeD3HK8VLaJDQ2VLijRRZbZ1KVfWsYKGe7CUeyoqRk6KCDLPhXtn11KprQCHXcilsavgM9+LtpXicKyWm3oKrYWNFNaJ9SmZ+UKIZ/qCB2Mf1dnL6o5GICd5MiRN+3rRyiot2TfyNW1zKsEF05NsPKgcEZdl0dk2oV77fRRLpchGkKfIraJP1LzREk9ee6lAc7bWdpuUER1yqoZUUh5EHpx9RuP037s/+Ofgwgr1cGGF/Q/+2YwgAAWpYIqKQ/Kc8gykPa6whvxywc/6/C/Ct3/Xv8eqX22kTtj5NF97BB6bpizd8EbjkXAsnCS8sjZvC7KRQ1+b93lvXRooOWH7bn3PjemYo5jh0kHAMjTmex2KBDVfxff0VQSRoTsgaznsWfSUksLOqyAZWv3YuWA5irVkT/m9lKIGYIc28F+87SP4+bduY2JiSic9e3do9L0M7CBoPQZsAwQ7RHgwAMiKdIQXeSCSqBchWdwFKB5466iOqPdJbYWJQc6MuOjF04AMUcvqDrsIbwQz/hdt3iauRJE8qFYBmHg9DIgk1GMxOjw0HYCXVzRehMnFWP/aSXLf+sXQaCY7uM9GZdlPXRGl0c2l38H1sm/QLjvIspabUed5hWjwUNLcsREhU1HPWxtcDZvXtSn4vbxq8MJFmzk2wVCfVSzaJqrB4k1Vs4qELQpem7EaEyM7vebdJuG4d3jhQo0wHV8t61Wk4Gw0HQrbQ6sg2eFm5ErU7nRwGa3hGJLkg3nuUxZku7vyFvlLjiSZ+khJyZ+LUbJzdm6owNwcVjr1aytnhs0F1/PMUoLZSYylQoVpCMAc5QQs7WBpLfXI50UUgX8HNLXhkLDbaJm2lh/D9pFWgey2SuwjX4prhmuyt4oZBg9cxSe9oo07Fek22TyqeJ06Dk4Kl4GcnblXqXaRotw7xtKT5vo0ZZsUgSxwd2Lps6mlXJgCZGnkQ6uMUf6X19SfcdlYPXKlHbFjAmRMRQGUsi+Irjogeh/r6HIJOO0W04a0QdH2A5HkIepaWFilTLI9BNQN+pzxqfS+2VeEfXxYpeeqe61VXrmeuC67XB0judKJDStvLxvsNQH3eyJxilDynliCTtRViez6nBaj5OdB1WbAyLpBidUPB58bSXLdehSdCUEhUpLYnudzeQevNeqf81hPhnZcJmdKtbcECV/yRV+Cf/Gt34yL1QrLizP8q2/7lvz6X/1//lX4+T/n5+Nr/q//FWIYsiPEzyGytteWdvXLT8KxeCQcC0AN61EXc+nOTpNy90M281Fjpa+nzO6YKFjF6KXkJ1kiyYV70jvcWzeq+xAoeqVwIJ0Z5tPpaAiQYXZGhSR+0lsdk+CgUx0FQpWMuCLY2lhRiZmPOF3OsbLmTKzfz86AFIGUdXB4aVlylaxzf966N0ZoCmkxet3wQWXIaRRIKO0tMpn4khfto0a9+13MUrrc9Po8NOJhOd3aZHZ5wE19UjVU6O+UyFYQjlomXNGUZAQ6kpt0fpaWl64JjfmgThqpEYpmPf/SqkRYwRGSPls+E7aQ5+Zbm8CVljfqvasgW8oRcF8fdDCNjlQg/saVtFBC6WEAwEpsS3qLiEPuQwOxSFbF2WCv84aINIakLYMqWgLIkDNzz1RH1LbkGg1xrnhwMRpkd9ZaaKqzNNXRZDTHKmUDog6kGkXm6r2kzIcgp+F0cFiHEhGmBNxbFxErklB1/vTaV6FA6SyF5ZpQ8lxBQILBrszLd+bsquR1SUlGY9LPm4L+cM2wKZm2UldZ51Mj4rK6a7dVmDql0suCB+Ny9IpMCGxPuOzc0HkGNAK/s1Rn4mxQFGlIm4qtndNnwrQWo+Z5E7EKmv4IUbLCKknVfPbkIylyBksJarUTD2eA+1EPsTOrTNBrFLy41NLHVRCc9EVWn3oGZ0ODQxO443550Hs8f0G9IMnPi7D/6aDpj7WRMymG1VdOEWwNrIKiXXNf1FIZ9OjetIAy6T6iyFut10G9nZmPG+gUHVLK0gNFVO2+kUZD0ufCxlyUreczV67ZqF10o4BtGOiM1M3rDjK3rTTRG6I6Ky8tNXDda8s1xuzQmBorNM1UhK42hyIYCWF2E681+PNaWIvoBKp/cw9mBwaC93zO5+IXf/lX4st/5S/Cb/7a34Yv/k/+0433/dbf8FV4zzvfg/f//q9FiEVknGcuz7PSKLF+96vHI0HepJfMsqXDLmZyW08YB8VxECTbXGVjIaknXcvM1qmQC4PutQS05OKYD1WZ5rKQATXuqo4nllNDNhpTyxdThvjxWTHMSyMMMlITsdbn5t3+mxcfN+at5PxoSoAYhBgS85estY6YdMgMccq2OqgTpv1FAi4SDOp1WCyb3IuABogLmWJMISnJRyMH6+yarDfHq54RcsqEG2dmErhKXGVJpf65cPoJFPnZ76wkFEaassiKh7IaCDXkV7uIuyuHZ3bGrG/A6pyVkT3J+QAUgbjf+5LLtjn1FjFT90PhcyWnxVZwNBmwMkh1OToVEEMylEnnZGX5Vi8Je22JhlvRA2ziYxYXYrdGVhWwpXZvDbgmPmECg6UTsDbNC1bjrALQNsVYrquUw8TWSOese2UbcbVLWQNjjIIVdH3QSWZ1Bsm3zO8PBsfXB1cwNO/+IMYZAeY+KM/JjGjnEryJuPV2GLZWUq33lLDbAFMneX0zdckyxZkJMo3RYbSKI1YeXGlD5ucIStdM9n5ZjILrk5hz5Ts+Al5z4oPB5URG2BSs7jJKVCRH1/X6joXZr8JsWq0VjDysJYlAVzlZKpGsDo4K4KXMWVDF0WgpV5bWSs7pE/EhQXq4ZKi9S5AkWCVgHC0VYCgagxtyTqg3wVL7p3cGLTsVj8WovKjOOURP9FSw046KzIweXSzEZDpg1MUgsqnCgS4rAatTmhCqKjs6gGdj0a2homxn9jxzJSokUbU/SmqavDa1MSkT2rnmpj4iWADGdgtTQ+nobDd2gGsPKaBrEhpoQNG4hJtTnbujTontJM4z/UH+yXIUPDYb0RoHqw+qwjlGwW1rlMeWDbrnVMG1r+7xfKBSpj2zJJvOQfXcIwRn7/5duPK9X7+RDol+iofv/l25aq0uZY8ogmvOkLL8OpT05u/8qvfj/b/l/Rupma/+jb8188x+z2//2o00C23C1Os1XtgaJrfujcYjg1iwJppdE+kzXQSN3Oe2mLVhjOBKl3JFRb0xSfpbGjTGXP280YPhsIu4Nhk3uAeEGKl5Uef2CXkD2Cir6u1ASqD2gT6Ie2tFUXpDPNjbgLnYuY/4zx5/GT/r2jEmLuJ8LCWwJNCVwz3h6Z0hGxJ65U/OwwbpqDGokhHcXhtNvKroe/RR1OEYFRIloW6wCEMAZZz7Ir/N/g+cI0ChZ8J73mDRU+PGAEW2+YrJMA+Jzhu1NxSOVXKpiXW50uyKdfhttTKvdmPmmrR2WK8tz8zN27qUYW06ETwcGO1y0Dnjxhmi4HwsjX60jLbAv4ycuJb6AEtR6XPdtdp3cgGYOqMsMFAqUZocddZIG7IQkyofMrWgh+n5WNjnrPZYWincw6EYdvJgxqgOCN/DUtKDbkQ0J3lppDbmmmOyvjzCtJ8qoXJ9aKoMOZqMloY4aFMmlNbRKp2CqTf+hPVnYd8KRsMU7aHCLKPDRhRhqdVFqe1AiXBKse8YJ4cGnroSB13AUTdmh4Lwes0poZPBNZrJs65U/4RU0qdMI3Qu4TFLUWx0r7U9TNLynaXKnNe2QwS4Pg242oXM+SLnhhE3bdDRRCN4pgSndl90FBdGdF5FyYgq98DVScD1qRK82diMHX8pWw0g9/JpzXnV3kTm3Egy7Z9S1kvHQkulTbaf6Rib2yHq/uhMF6eOsOt0FueOInVEGkNSEjqdnJq0S1vwtt0L/Ip3fRAngzYay46QEeIpoKZpR8moSzBEOKXSHJBprFz2b/95s0ODBSlMMZBf1Yg+jxuTEXeWTX6ORKD2WpUQEBSJbdoZb3+LqHt6AMunvwIPv/DrMc4eR4JgnD2Oky/8eiyf+gpQaE+yjSrpFToUqL5DJ738oQ6FtVFPDNrp7OpnpvKWIuxlP9hrkpHf8YbjkUAsFMbVRXFc5aeGqND1OirhiFGHdwkt4bRYJjU7C65wB+j9KqlIMgwPFLnX0ZAQrc1ORdshFh0BllM1AiRJWEJhbbKMWUMNIxyNSb3tPqg4DgWF9ECOaFzJ0zPVQKPVugTnFV05t7LSuUGdp9YYB1Dv9s5S8M4ret/7Jt27jjDRG2RERUWSgCUUEt1t9NBaRTVWYyIhCejNUdNFSjRBozJGa8u1x8y7nEceR6BxLl8jSa9EdwDkvPHFKGhcKXFk7ltbHGuu82iiEsszE8NKSSw1Jghecu7TS5FCHqOgh+QNH1AUPpn+mboiP7005dKQRPkfhhIEM3BNPugIgSfjhxSxI+dYRsjcsUZkMnqcD5oe68wQ1+RHkmVXUeHqK606hCoipKmbVrTPBFB6XcDm86KC6Bs7iIdEjg/gxfo9RIAlya1LWWk2JMlNttjPZDTEiyWlVDDsk3FBbI+RH0KkRR0qK9OuIk5WTozRwTURU4mZC0RexCoWITqqLSYx2eWghEmdO7Vs6+ggEvNeIQFTDwZ91t4XbhCdu0aA1g7e87EIWsXkcjkmCdghlQoEEUDMmTk19Ks8v7DhIJG7xNQrIFn4buZjnhPuM9V94IEpuTqJELoXCk1JDg7Ic1LbVnqBnPRaQnrVxJ/GJK/S+wGA5y9aTCcqRDZxEdEcorlVqbCJXEisHFHe0sGuOmhE9pyreuAAODMyKp9LSoIjV2TsWd5PW59gP3dFC0jXYnHWmOZTxK/c9zI4HFqrcxFtaLhKKshXk3s1aFBHieXzysXQfVa3EGhEA1uWrDMo0ZRdUWdu7d+ng8ONqfZLIYmdhzm5YVSZpSZRgoBSWZRYR+Uo1IHN4umvwPLpr9hAIATIkoNZ6CqjFCVNLaAqp/0+1aqcpq6JkuJIwsZ5JWWUy0xtjZHMfdCV1ulvNB4NxwJGkHQRe41k7sD9nh0UCfnpobvXRNwZHToQJhXcWTo8tRNyrTgNVwTQj6LQa1KJ8GUwiW3z2usFoTXk+u9GmAIw8psH5l4X2CxpymNMCvfRU3xyHtTjNkYytdVpjJbB4Z8+94RFISp0I9CH11o9fwv15ucmBtV5wRSlpLBzWpUxNzLk3ZXqOixHk9E26J0CUK0kBEkYhOxy3bDKuga8rQI6IXWkvRwFs0Y9VaSSVlEmud7TYRcLW16Krzw1Z7EPgp4bCciOCqCQsJbflpK5e+tmA74/sVbZjdNc9mNZnMZnRj87bl6bBlAi/cz0RFahqPZdmBN5OijJEaM6oWxWRug2V+mYs1F78Z2PmQTL7rgUMFIhIZdZ7zsSM5oFGJwNMsU1dqD0OlCY9X1wmLYBh10B7CNUKG6/LQTh1pHvk7AwRUCAjiGNnLaXJ6PfS8qIE6sdrnRa1hyikldJstXXlyoZrUTSLznqxrwvecCvc3WLOnYw50KjTMnRGa8jWNt1chgEktVTWbFFJIqEyVNztrm3WC1Qq2HC9GOcpdzUzqScVtIUncucDWeW+mz0ECha1xlRm/n3CMpVx5w2ZaVP26TMF6D9YN8i7sOI0sY8we4ZRc6fzjXLk4v4Xkn7RhQxwc6zSkSVSvnsI1SxdHCmO0Litjm3Z8aRABSJIfHZC9BJxCIoj6AVVercbdQxpb1sDMVpnB7GTmKuIPKOVTkppyudBW+KAJnjDaoa+ywaxhQ21xydEDpumvZAJh2/sJjjAx/4POw06kDXSBQPP6IjyjNxufJovw24t27VuTcO2tkoEKFtcIYkC4JXe7UIHmI8NTZpyy3iJeHmdMxnVB/E0ryFiwcUlIB/p+om0dpABwFqcCiqpVdSbCu1L/ijWlGTJaL2EYBo6pUoDV9DfkayveGkyIgzlcL1BAAPesG8EeO3FVXl1xqPRCpEoDlJihhxYXYu5e6ONcSqTbCi5RwVil0HTo5+Jol36rRIboLz0BQFGT0PkQQqFSMitJiyYS6d4QAjy1Vlhq1jK+KCegDA3ZVkY3RheT5CeL/uc34UX/m2jwIoMCR5FlOTxNXGUjHrPJDjccWIR6eDOg+35hFDLLruzy98rqNm9YWWswWwF8Neq5UAO03ErXnAYacqd5xnlsKpg1band83xv/cJ2sxXVIkmjpSsufEIH86i2tLNRBanjjkhkHs+8GhgmW62A8nY+Y78CCdN8hVDotRcsOqxqnx4iHXWvSTe8cYbH4+lHwvI/mVwddLm2OuQebIMyk1FjKbrgV9TmpAU9Y0SfYaksSSrVvyfjiO1w1CEtyajUYYtF4rSUr+PDosrNSyJlExzbTTaNTf2p6Jif06tN9GHyWnp4io8H4YoQGKjJFYSlVFzmNXrfF1LOWpEcjscLLFVYiqzNleo107lWukhwQjqiEp0nHSq2Q/Kyj6oFLTTNWRtCmC6nlqNH99MmrZti/aHOeDRx80qhQgd60UAT6+aPUebE+RQ7Bjpe1FKElTdYM944fmzPDwJFpWC4Ilswe7pplDXYd6cL+wsogRfx/E1qIexkwl1q9jh9TGrpMOx5BKUzwiJp1P+bnfX3vT71DHM0HTnuwDQQRsak0SnSRLhTkjDgdrBhYMzXG5+mlIyPvV2Tq/0gYctCEfWH3FPWPFDxE2kiwB5YfQQcmaMfasIxR5IJr8oG9wv/cbPzvogmn4qLLr8VqdISfIXa7rrqus0CHSRX2MnUbtxioUBeSH1ujx3ILJGjWmQ0jNJS+FlEpkNUXFK3Ib8mpNCMoP6hJWEjy13breBwWw6saYbJtO3kT+NyqHw+xd3eKC6Xa9HrH5ltwNlWmQGLWVAPldQ2UDX288Eo5FgDKN11FzXsdrzZmRzc5ab+bLVqH0OSCx5y270RoqubzRGRXWZUje6SFVEzVJOGR3TMJwZ6M3Jjzh9UKYIjzpoIt2GbQMkw16aJhfWjZYjpJLM2dNxGd9wQ/h6Weey9c4mMNDbzfaZ7LskYI2S6uf9gaRs8TqrbvavWLqIuZNYYlTJCclyZr2bAREJCZBo8LShl0yl0W/RzeWHuDKAWDuUpUKVStjYXlYJWdqzpQwO/UjvBgh1mnjoPu9s/JWZGi+Dw4HXcTaHLWdRnP7h13AMhS4r4+S0xaENK9PLe1heeFYwf1LI8LudyViAWAErqKfQL0HRnSrsNnZlOIzbCalPAiXm5IRjeBcU4+E6azOytg46r41zPeeD4WrwAOMqnd7rTpqy1E5PIfdmJtPURxOADw2HZUDYzwfQumsCnCSTKGxMP4bez40PIzqEyijDbB7qc6N7jWFSq3fQ06VFOPHaoXzweNscHnfTn3MolQsIeQ8Ej7nHItdfxYHcylXYNHJ4hyu7PsOupD3fdZJCfpv7gdWFZHw21v6R6sZNE3Yh9Lpkd/NdIkiDPp9AuRAhnLc6hxaUJSKY8YDjjaACBKdNpIhl8Hh3spnQm9jwULRzSil22xvfzZoh0+mpSam0aOVadah0pCWlSmcKnndgpa+oCX71gSPXC2qlpL/s98quE/iNoAs503tDaYbX1y6nGoCigZI5t/Y3uZ+2SHhU8q+Yjrofi94ZV2CEHJQqO1C2XERZL7QOiKvv2PTuAEUnVqM2thMhGeBpiapvxISch+Qc5Pq1464zgIuQ3xc0UDqvBL2V0Fw9tx9nA1LwOxj2f+U+RZzIEoaglwISHkdB1EJJ4WfYS/NSISiHZbStnkqKCsr3CQ7MJsuMBGOhFVY4vQT93HD7OvSyubfaDwSqZCUdANTVEY7nbJhUlFfo3gJOQ+qjVA2J8k+fRQc+GhdL8vnTh02NPH5Z0qCxkd4pGxo6NWSdEfPj1UGzIcKkJnshNCnPuGtewEXo5bnzTrgetUK/i/+w/+iKp/Vyowxaf4tRm58JSiqQdPvXkWBd+pR3pgqY//cCHisiX9mp8f9vskiVtpBj70VSlXHY9NSnnVWlZl6Abznwaiw351VC28RuR68RdfCobDyp5YiQCyNe0j0PDLjwjlXBEcdrXWUHA0BarzmTXH8xA6Xma/KeA36fTgIDqQwua9ajxFvsLmh8Rl9ohPUuZDLPKc+YuhVmptEKy1PbsC+LdS0aKTe3vqzA+u3wGiLWgiUdk9JnWfqq+xYuumx6Zijsc7y2mcD9VkS9ltkKJzGxiFhEXwu26Qc8cQlPByQOQqNi2ical6EpOvvE4sWXpQJzwonQMvlrk/GTGJbjAJ0yK2+Q9JyUuamVXPD+ibADqLo84HApmDM466JBDWbfR881HHloaSIQ8rrkDLwreW/962L8dL4B4paeLC5FQmcu1aBRVIqyapdp3L/y9Hhfu9yz4m9Nmak4HwUXJ8qn2i3DbnTMh3cuQ/5OT7snVXQJLDpHeXAc3M/C4SGWDr/5vx/EmB06G1OamJjSqowP0RgaXwxOv0haYnrY9Mxc3HI7+qtpFjTydZDw5yYlIri8P3e53x544qKLffU4UQDmHV1gDiw4knXzlNzRYvIjyAn4d7SYe5Vjp/aQUosVTtzNjj4CTD1IdtWLwlHk5hTpIzQ+yCaqpwUjZe5VeGxgkMD0GhkcK3S0oaVRQjsaDLilXWT7crKUOpr9vOYgNiWbs+HnSJAD/rGEK/SiKxGXFQzR7lfXjRlfL9vQLXgfSv9/vY/+2+x/h2C6289RBR51SEul39gNouOAp0Ojjr1UYESrzkYAPO1RJdESvpIqtfx+/R7Ek4+/gA//Jf+N7UxUdsQEDl/vfFIOBZeVKNePSGnehbQMp2dJuUHutMUXgQ9ptal3HTnxaUunB0zYC8u9N8HrXZjWySV/W0M/mS+s24y1ltk2LhSSrVji3EZrKlMW/K5QxSsLZKmXsWVLuZo+dY8ZnW/uXm+ADKv4pW14G27oVJ5FNyYDjhJDQZDSg67sCHm1Uc1SAdtUOXMqKREL5pLn7ho8LgSTKddUETClw6VAKNKXVxng25GcYXsSs5DH4DOS/bsZ14h3mhOiAjQWpkmI2IvatDZJ0AdkHL4Ng446JIJaTnsTkfjCKgxuz4ZEZNG6iT8abVCMsEvnS+iIapz4bMTwlrr81Hb3bOldYRkxKBxCWurlFGUxmX1xWVyFpHZszdtEBrV2mEnQZUtm+mYno+CeQM0Se/xdFCWOEl8WmLqMTNSI1Gjo0nMRjMCkFR651AbYbeJaFzExUqfSdsGXLEOpbtG4iWhkZougJIIaUAe9k3VPE4PNa0E0NeOSXLprJeUu4fOvCJmgznHJNYtTFJciW9WAQF1Hikkt9fEXCnEMj8vCS6p3gB1KYZYxNbGJDgZBLstcmqUe99LwivGHWkFRegsFm5U65C74D7sG9y356CHlFYPEcGYGClzaWWj99eCa5NS0knC7CoomXsVFOkZk0Z4wcSTJl41OIgaDgYvt1Iklztzfltbl1lt05yHFgkHXcRBR8fTkFBoKvTmTNfCYvRYBTYE0/SFF+3HsjTUc6eJCIZOjGabJi7hQRTs2D5fBj34n90bs705twqYxahNADFoOvRqp/bh3topt8BsnxPJ6dsxIvNcZj7ixtTSRaLBycNB9XdIVgWQSaMpKQKcJQVQ+HAXRqweIfaslfjLvj/afyhlWxlSaQTGCj1AG8+10mT0+3jd5D12OnjcmA7W2FDPCZazJpQy3P02YKfR8yhYkMZUBJthhiiID1f4R3/wf8UzuwEvLa3Taiop3owMJ/ZXUVG2iQUu56Pec2NoG6USWKFz0vtcSMD7YbUcO0KzlQQ5TCosidImwaXsuJGWQGdG0aCCDtfp69caj0YqxB4q4V7Wo9dljSSWAXoIshMoUxIhoUS5NoEJql+hE1nSIwoFq8Gb+ZiN68O+yWmHqZUR6sIJhQTYaOS+aw9qHTQqfHKuynm7VjtP+JVcDubya335zusBqyp5agAmDnnhdK700mApIGV7G6dGq3MJ1ydDNkaU4QY0YpmbIV9HZ1C/ZDIbRcAStJ17DXOuo8uL97HZiKNO1U3pgHHhDrF04SQ/YW6HF6HjusyL+derXekVsWMCPjuN9kI5GyRXTygbWa/X2TWf5RLLlA/O3Sbg+mREbxEYS1LJORii6Zakgl5Q54E8gquTkGHpvSbg1jzgaKLs8MbRQY0Z8l1Z6oTPl5Cog1UuuYQ+aMQ+xiJ7rmvc5cOsFc2HH6+9SbYzalcjuNcEsE/LvXVjB5bLVSLMq7Md92LU69DnkXBtOmgZWygaDusodi+SHSIHE3TKjoL+bG7o32KUnAZgRYbqHahhPOwU/eGc1ON8FHNe1RCy3FWJzeX13KckPAPq8Bx1MSsb0tE+MB4CbJ9z/f3/mfv3GMmyND8M+53HfcQzIzMrs7Iqq6qrp3t6Xjv74FJL8SEShER5RduiLVPSErAgywJowpIBCzZg2DJgAbYBm4Ylw6JkgwZkQZYsW7ZhwRZpmeZSJmmKK3J3uZzZ3pntmZ7uqep6ZuUzMiJu3HvPOf7j933nRs3Og6AkuwNodHdVPiLuPfec7/t9vweJncqvEn8FIbD2sk8sioC7dY9pEfIoSX93iAZ3Ry3trUVee9awKD5vmblzOu5wt+7hDYsIlXHqvdP3PhcC7q6sFRgcE1WhNBhraYSA8rkGVZqOdmMCjqqYJdsAcNHaLA/vE5HVm87llFv6abCAUampFkt6jZtg8KrxmcBN5EVJ2KB5mB04UpU8N+p1Uks2zLSg8V4p/D4DcnEUUR5JhkhKgyxZx2xKLtxG4M2W6rLjOrzVrV+1Vp5/fn/p6IGSwyHTkI67X/b5OV/IutH9cFEmvGpM5kso6VZHKpdbnzNelEM0dtyj1M+hjUNRsS/N0L6kpR7IKE7HofdHRPzujQKJ4xj2NV0XWlRwnUYpaAbPHuXAMM8nCmdNkbFB/VbZiMOKSdpj4QbpFEC5SbuqlZkPWBTc6xoZ4Sm6WLuYOSqLMmJe8J7/uNfnorAwSPlAp5yRB+T9EQOPVoFBSAqb124wqQKQ9c8vNwYX28FO9rimz7/mZKhN61Vr8HLjsm58Iwxs9ZTIpKiormncQPfLIUFzd364J8x9QsHhLZKMk5lcLUSu3dyRJhgcim9/nwzGgrRotciQsuG9dJEIxLzo4Q0lZtrBOVk4qgnXRMmJoCRXLRfLuieyswlM31S537QIUOdK9bzfRivOiESSVv3g479X9jmuXCFaJaIZgxyopqOAm87mv1N9vM6YaxdJjhIIU1EUJartkuTIxNa5p5HvYWR4F/kQ1o6EweuOM+VGeBtNNFmaSVa9jnOSFB0GrxpHN9A0eBGozFnlmknWhN4Xi0Hlohp5Ncoaidpk4hMOSqoJ1PHVgvfqsvXoEzJ0vA0WpYs5yyGkwbm1kIJy2dHtVAmxmbwJ5Lh2zdw53xbok8FhpZ1NwqvGCZ9oWGN9YpZILTLFwaiNRcSsiJJqmWR0x0N7Kq6bc/HzUO+PiSPy0kXKhw+rIEFTg5rLYJj5rnom7IbEa3dcdxwPIOFQRjVqd65rVJHMk5Gkm0aT16QW7srLArjJzmV2rjJUhsYZHJR9lr23ga6S+1WUokRM5SKEHGrfKiQWZcjr1duETT+MwhQVXWTfiiTJxUNAmMpQ1RJbJejaWCkSpj4PSiAtbRQp+G44G9GTy9bmhkEPQoX4tRudFwFXLQ32lj0l8Tedy4Uuv6bP6qjCpuxsu+xdjm9XTo0ies5w/KbcHI7xBuv22vK6XnW854WMWnUN6SiD+9BAss/5NNooSqHbSYGhiakJQ0S6EfQ0Je5tN0LgnxURswLZGr1LhkqnRM7Jq0Yde4eEXwD4wnSLgzLgxWaw9w/SXFy3Vky5TB6d1m4I2Fz1TooBEvPVQJG8jSG7p5LnWtVOpewvqx3umPp7aBGle6sFn1tmCw08xD0pcKM86xZEjTa97hU27yeKCANEFmmfEDPyNvuPi1gYY/41Y8xrY8xv7vzZv2CMeWaM+Q3554/u/N1/1xjzXWPMbxtj/jM/6ecDXCgjkfSorHMrhKGxGFW1kYfLi43Ldsg3rW406lNBeJ1zN5vlcTkWVzolSulUt865dh9pKLMQ50pCeMrSHTTV2tU30QhcyoVDD3p2EGPHmXwtsK5K8IIgGDMfMsEH4IJelDEjCuokaQzw2YqfcdMTzVAHTFp0U47VBCdMes6StQtogsVV58ShjgjGXhHwpqFZVu24gc+ExOcN8gJro8FtN3StuzJSYPCk2P1z3dALqaj1gWGA2nAQaKd/KJV9H/mQn28tjqoe84IIlc6y1QqZpDyiHmPHg2xRhAzvaxemwWHHdcCdimtqI5CuphIm6eoUGlY+T2mHTcuahIutkxnqkKXQRPod6GxY1SgZapS1oWiMdmHqyaAzdiW4bSNVAGNRUKhiRknAuSMU1EQ3V7XwXgfCwF00+GxdkGhW9pgXUcyDyODXDn/ZO4HveSDMCxJjh66bvIO5ECt1LBCi5lcQsbjtBpKebpzqbwG8ncjaRtq8K/FNEUG1hY5gYb1fxsyN0OuoJM1eNjV9r8yRcDKu48jubGvF3p3X+p3JNh/ewEDave5cVs+seotlb8RrJmZSsBaNAPD+PMnhy85/HZhtMy3CW7wbRfK0W9exhB6orRS3xc660Q561TtBD9khsnGwee0MhxP3J459JAFaIPJtlDTaYHBvFHJ20cSzS9VRguYL6c88F57B/VGHZUdZ5nFNJdlGCthrua61TZmUyDgE8t30PgCQMeaAMBNpDfk+rOQ5nMs6U4t4lSOXNjHaXfZSRV06Ke5ICGXjVMsz8HTl8p40lYPvUjKdLICXDfNB7o56sQgAAw0DUZSZ17C8hOvO4k7FAvN8a3HVerzZWskB8VBn18vWSRozhAA8qC60wNeAxHXgP50U61SjWewJEprAIuey9QO/T9bWbUd/py7tRh5gaH7CYIKo6M4QlbCD/mG4ltNiyMeJ4JrXPKGsejRDSuvEE2UOEb/jPPjB198JYvGvA/jFH/Ln/1JK6Wflnz8PAMaYrwL4JQBfk+/5V40xP17wCmTFhTFk3l5ukaVpF22BwjA+e1B7iIFOHMyMnAG+MO0zzL8RqHbmA+edluZERjpJ7YyPa3W3G1JPE5A7yghuOLywXKwKZ5MpbfCmKXDbEy7r4vD1qjy5ao3MYPlSWZ1K6M63TghiIRcOCpW+O6Nb3sgPSasDox1yMHKzWPVWiKW8Pjc7evWDkg+ftwlfXXB2eCiZAmo3rKE7ABfUvIz5M+pCXBRBKuWB3a6LUF0wVetuBTXhxk0YOkFDczDMn5PBvOhxXId8j+fCF9CZZ2a+9/zdpWy+AzlOF78Y8WCwwZ6IjbQe+qve5mA6vUe7MGwXIbkr3DDVFVQLSi0WlZcAyOhMECfNyNAuSTNanFEFDL9Hkz/Hju8Z0J/Jz6uHyqbnoWuMdosG163J4zh9iDfBYuZTLgicYSEy9ikXDUQcIg7EhVGvq86StcAay3te9QYXLS3LARba+ow837D4ZLdmcSlcB+U83XROrrPNnZOy3rXALB07t9LygFAnXZ9HOgavmkF/7w3h+ZgMvnebcqFP8jCl1JVcEJIcPRZlj/Mt0bbzrc/FpxOEZ+QjTupeFE6acsyu7KpzeaNW908d02yl0FSEStc896iUEVbNLrqSQ65PJq8B/bwbkU+rImHkI/YKFgOFpQmbgYTeyUbSyWeoBU0rBSEaUkYHxEi5Cq0gHloQakhiK8iPogPK79F1w5wISnl1LKsFI00MJW7BkNT6RtxGVdWhhfn5liqXIEWjHuSq5FASbgKLv1VvofEFzpBz8mDSoTAsPLSQIyI9FLXqMcHGSZsQMcOzg0pLu/OzhsXrsncMMhTH2NJRkk/pvErsU0ZV9kueL7pvzoqIRdlnewNtclTGeljRa+mw6vP3dJHco5nsvyNP75at7PV8TuhrpOeUHvZaMOyVLMrVkVnR+V0n1DbarPx53dg8btfRz03ncC7PsDUscqgiMTnVOgqyqr/3R71+InkzpfRXjDGPf9LXyeuPAfg/pJS2AD4xxnwXwC8A+Os/7pvUIVFv3hdmQVjuPHgutx5LIdId1wyJWfUWJyN2bze9RYTNpM3CJDzbGhzBYlxF8VSQXPlkpItChnrbMMx+Rz5inud0Q8rhyajPBYxuHkpOBIAH4x5t5GgiRIM7NT+PBchED+yY9zStEgYmAZpDsZH3MPWsXO/UMTPgr1uDL0x7VrXJZ3+GSlQumSsg3eb51sMYOWDiQKh7vfXDHDbuhAHZwTxoG2w+hHWcog97NMgH2cRHbGUjMBjgZt2cl4KclIJEKZEvJIMOHMkUNgEOeLmhYVkfDbaJm7p2eQdlh4u2QBd5kN4bBbzYFCgMw5Web7iEF2XMVsttMGjATnxa8OvvjZgLUsuIQfkjXTR5jDHxAcbYDJOHRIWA2iyr8U4n6BlJvDE7HV5KSq2OQDhmo5YelgXVhYSMHVbsFtjB83AbxnsWz9Z049QNREmzKse97QZ4WD/TZWtxbxSyd4gFXT/7ZHBcEdVRiaQiECoZPSipMlJ3RfUXKOzAQVGmuxbnIRL1YuKvzXb0IxkHKq9m2Vuse+BuHfNaSEA+MOdFGIplACO5zt4mzMuUHV1LF7Gwg4z1q3tEGroIHMvPfrr2mBc0YmqDwU20uGNSZrHPRDb5uvEZYbTgKM4Lajd2Qyy0t5LvIQTUhZB5+wQx9jKZWNhK46I5Ryob13U2lsNKxxxZUhzE+EkOdmBQPt3K+M/Js1i5mPc6zR7RfBIDSMFrsFck8XsZ3BMvWubKjF3EZfCAoaKBMfcpEwQPqpAhb0DGLsHgvSlJrtdbK++RUvyjOkgSLr9jLuR1yOdWonsbNOuFHjyljEOjGUi5BuQ61G5AQ5Os2y5RQXclSh3NM4ngM+CsZgnxvmiSK7kxLChLGZlqdAOf1yBjAYuDskNITq6tKLZ8xKKMqJ2aCg6FFdcsf97rhmeSZjqNZJxwuSU6sy+FzFIQ9BDZrIVkcNXyzzRrZdN7jkGUKJ+GoMouIiMaIRm0PfcCHR1dtjyXWLyZXLztou/zgoV75SIuxQ/EmAQHnh8TH3HdGiwKuS8m4WzrsVcEeIO3JPM/7PUfh2PxzxpjviGjkn35s1MAT3e+5jP5s9/xMsb8SWPMrxpjfrWNa96wNJjNRAgjPNIDYl6ws9srAjY9rUWdzMs5X0RWRNQu4XQc0IRBTkNJX5LudegaNXysSwZvGoezhnCaFhVWUBQeEiSVatLmVUvt+qofDhV1DFQJFuOmBxdAZdbrQUXzoIRlZ/Bs7cTAiyON1w1hxvtjtouXW0+Gt2xcEx/yHE45FM/WDt9fcTE4ww3jZWMoCY38TDofLx1jnNXgZVDGsODYxsEBkKQhZPmu8lAmuYom4ZGzW5IAR54H71QgUHbn1KfrYd0Gg4OSi3y0U/VPBf1pgkCZZpjP6kstlZV/MfEs4FQVcdl63HaDrC5BLaf5YLRhJ3BOCiOVjenhovHOYyH6HlU9juseiyIKTMq0XL0WXeR6mPmIk7rDohiIZ6VNOKoDKkHL2khoVDv+Ve/yYX8iMDbfK7vSm87hbOtBjxVBAiI5R6VNeGfSYeJDlojqbL6wTCXUIoKppDofHzbYnIkCojezgp9HyV2jTIwcpMGKBo4EaudY0OffR+Z8xP0xP89F6/B0xWTQTg4LHd21YZD2rsPQYWsXpiRMA2Re0GEVcDKil4q3CQdlyv4V1zL+0QweVaOcb132slDUbU8s02MCnm+8pFjGzF2xgCB6lOpetkMAlvoGOPs7R4ZqTKe+BgkDp0fXsEbAqzFRI0Wvl8Nzr+wZYmc5tpwL4VR5P84mXAk6qaTVPqkpHD/f91dGDpwhOfeg7OGEiBnkYHq+8dlLpA28ftpkqKJqr4g4qsmXURt6bep0D9GAv9fNkCCdeTUm5WcfGJ7BqR8Q0m0c+ALrfvA+KSw9aRTNU9LvUrgL+hzulX1GcdXXZ16wOLyUPbawGszHe7gnCqhZIURuS5fSG+EqqCxfGxRAbAKSStT5LCUpFFophg8rEstD4giVibvkVHgz5CupeEGLUj4/JvvmQNZOKY0Px/hs2MZChlUhg6LXqmgkl4oS+pEjYnJ31FJ9tlNgDdfY4qAaQuGWncWLDd9LKWTOH/f6uy0s/lcA3gPwswBeAPify5//MHzkhw5jUkp/NqX0u1NKv3vsRtmtz9m0U1yYPAdl7oGBtxF36pD5EhpStI2UJ+lm5gzhIfVpUBY7wLnbtW584IYWIscNsyJmYpFu2IoEqNRVH+gE3nBN/FMC6lHFTfRWImbnRcS6N2I8w8JgV3+toVtNgCAzEftVj3enHd6ddpkos40sqM62/q3Qn5uOZi+bnnPVhxMe4Lc9iUTvTILAeDE7+GV+Rxz09sow35fZ5lUrG0NAJpGxe1XS7ECWK+ThDFHj102Gu2+74RDZRrKOAbKmj+su/+xL6ahmnoeTcm66SEWBHnz7ZUATDV43BY7rXuby/Ltlx98/8Rxv6ajjxcaJrI0zzcIk7En6qxpIKXlO2fJODjj92XpAKc9iKQSwqWeBlvNmzDBf1oAmhcOdYSfDDo9/f1hxxLRf9iSSCSKlMPm8CLgSLtBR1WNRBBxVPFAWRcBzCbrqI2ekEfz32dZzA9VNyQwGRPNiUF0dVh2uWidZLFaMtJLkInBG3iUSO89bJzwhPodbub8atFVZErGHjdtkJHImhcDDScDDMYnZKXHerrJIVUGocVaXlDtj8arxmaOgB/NCvC3OBI27aIc/Z6fLQpoFYZdjvqeedvkawvaq8TCGbqWFZfGhELbC+GrLzwaFv6OTzzcrAuf9UvQrYqQb7KrnZzDynprA511Jptbwa3TdARp2KKFt8nmV76Iku172utNRLyhmzKM37ahHLuGdScKjcY9LQRvOtgYX4tNSC0eJMQIpKzJOx9vcFOjotraDBJF7wPC8b/K4x+Z78HDcY+RiVugAgzGWk3HLzEccV33mIuw+E072WXVY1vFDIQ1RSINxIIBMylbTtrEbTAv1WdovI/cQkT/rs6qj5uO6y4jL3ZoGdEoSV47OWsirKgtXjpqqzsY+4uWGaLgW2QPxVYr1gkjjq8biZWNlHGazJ4+SPNtI59ebzuV4g70iwIKGbzr+X/Vcnw/GPe5UPWrZk1W8oNwsjoiHEarucRbA95YsqNciZFCVyd26x+NJzBy8H+a7sfv6uyosUkqvUkohpRQB/G/AcQdAhOLhzpc+APD87+RnNtFkeY5WIiorUgOaPdlELEjIvOosnqwI3WuXoh2PSgqV+ayzdf2aBK3uONtcyYXUA1Cd6rqdB1orfWXm1o6doC7MeRFxTx7wc0EX1AZ7URIeV4c41QWvepdVCl+e9ziqJFsjUI9eySK76hzu1n1+QJY9fy+TNdlBzEXupw/CyKXsTKhd9e6iNXJt28hNW+FM2j4Li17cNjU4STcQ3peYZZXKdWnlcLtsHbaBMC5AcqLBYFY1doPET4l9Ux9z+ie9+112hLxqDUc50sE+WzOMjbPhkIlOYyFg9UJEmnjGIj8c91iUDGb7dFXg2zdFlh3rjHmdCbtD5a/dgW40ii4UhuMM/d5lx3V4pwo4lPRJ/XlGEBIdM9x0Qxeuc1ZFXtT8qJRNKMr13gZkJ0D9zLvqovsjSsuWQmY8b6nJX3ZK8htiwaPcD2cSXm083jRFll0ue4upwOyli9ivYrYlbgL5Db2gIYpOqQ6egUw2ozpKfIzyfCt3yAAi0SW6FBOLtJCQ7cnV22DqY7bnX5TSOIDSPuXMrHuDyy27NHWhBXh/rlqLVw1nxTpu2S9ponQgqCdAKa4eyjpDf9OwQ52K5LwNLH72ipCLW2Dw3mji0Ine9jxQaIo3hM5Zowot+t3kvcUM3WVOLY3Dc7DquT476XqBIVcmJuDJ2ucDaCaInUpvr1quF52vk7CbsoTSG+RikPbmLDzPtgVebEo0kQoRgEUgvSe4dvuEnL+hr9ImvG6KrPJqIzlmtUD7y56ER3baQ86QMRpXbjI61wabO2p1IVZEVQvz47qDM8iGiAzMY3F80Tq8Eev8XQ8fLY51Pz+pWxyUffbFUI6NPruUOlssO+aqXEmO1cmozZlG98d04lwL0pAS8KohIqDPeUwGjye9/DcLtXcmPSYeON8a/NU3LV5sXOZCKSKjXC7ldtSyL9+V+HdnEk7HfW76buV96ksbYiXVKp+CRTsyifiDeY/bzuH+iM/wWp6TXppCgNLun8Sx+LsqLIwx93b+978IQBUj/zcAv2SMqYwx7wL4IoC/8ZN+Xhcpg2KmBjeUT2995gjwsAc+vvWZiV66iEUR8aW9XoiKLh8Ou+Qs3cDvCjmrEfhy6nVEYTAvqb2mXhy5S6ssPfUvWodXjUpFkat8nXMmIIdF3XQOF5I0qAeuqjk0UXN4gEMmvHHGxd+37C1GkvK5jSZ7CPRScc4EsjvfOmEre5SWnf5ly87r5WZgYjeBFr8AN3VFajSmvt0ZNaiF7+tGCh7LTedGrntmJAs4ZaDyMs7gn208zrZe2N4h29fWLuGdyQZHVcf5p5gp3XQOMx9wXPP60TVz5xo7Fgcno5hZ6N5GHNcxJ7B6M0TKzwsiR7oR0hqds9FV7zKMfFglkdoNXVYhnZIGFtHDhEFxOsZSEqIWMwA3x4MyYCYFqzK+bzqHq5adhsLsI/l5OXdhp1tfyvtT8qGTg6O2CQ8nLKKebQrOzJPJB5QSytQRtZIY+sIknI47OqCGgeOiRmdPVgUaKaSvW587ewDZYlu17be9FTIvYdIrQaH0YJgIUYyELy14RNIsnaHKjamj78QUz0HDpo6qgDvy+ymhHFIwU4I4egIf3dA+fhs57joZ9fipRZd/5ye3PEgmLuLhuMPEp2wGdqfq85hLD+iQgJOaY4CtvOfLlgx/LcgB5DV70bqMBtQ76B2LLaIPCzHkApBJz84MaOzY8bOteuaiqMcFu1CO5G66gYdh5Pk0GGR/VOw4QbeQTcFuOofv3Zbi+WJxtyahkBwefs1ly4L1TkX318OKJoI5CdTwEFx2fB8vm8EmWiXLuyRWRVA0TI65MQmvGo9na5uJnPwZ7K61QNDuv5Fm6qhm3L36ewB0h131FrWMbSDP2a476Lo3+OTWZdQAYJGkEttna2ax/MobflZtHiY+4MWmxLJ3eNl4zMsOR3Jd1NXU24R1r06fPE+YGs1CkoqTKHs9964P5j1ORiymboSIqoFsl1u1yh98Lt6b9vjDxwXenXR075V1p/urjvItWDBZqGQ+ZQm/Nn9ZdhqHfboStLoJFtedNsMB90ZBrN5DHhMrP4q8Mzrfno7b/EzpuOxHvf5O5Kb/Nki+/JIx5jNjzD8N4E8bY75pjPkGgD8M4J/jw5U+BPDvAPgtAP8+gH8mpRR+0u+wBhkuP28tDiuaEyn/wRvgTtVj5HQcIL4R4q6m3bSSGLtkss79fOuzMY4+8Gr8odK6Wh6CA9Har2UeP/LqgAicjjmX0lnXSgqE4zrkjgXgAjkd9ziXzYchSRxTfPvaYdmb/Pt7KZgUtWhl1GOR8GJTZkJkFw3uVCF3aFpp36256R+W7FDOt16IlQETD1xuB6Z+aVM26tlK96hz7P2qx0nd8We0XixzqdKobcpjFKo5yFynEY/Jm6N29fMi4clquA/Uv1vcqRv80j/xf8Iv/QO/nM2atNN51RCy3+wULloQvhBy5suNxUJkaRuBXi/lGvcJ0nW5TGL67rKXhw2ZXLaL9DwctxnC9XLYXcnPU9i2FZtnRVaUlLdV6F3Ic5wJWwlQGx5knTuXO/dbibAqR54WZJUXen8Eyn22trmTpb6+Q0xcv7pJbQJHPMrX+HTF+3/RUu1SOq7Lq87hnUmXWfAxQeSdSXJYeoy8GpuJAkgQFuU67XoKOEMZns3rajCqKswg7Zx4FoATT2KgjlduOod17/LzqkF8KhPnYSHmWUGyU2Q2f9UaHFVcw+dioNRFNeqiJPLBmPP/37gs4OT9TeW6tUKs+87SZCKlSrtrR7+Me6OIiUfed15sClEdpOxQuw4WN63Fp6sCq2AzH0lf22jxbE3EIyUm9l5KlzsrBldb7fyHJF2b03bvjXrJH0q4P+qzxXqRD1uLJ2sS6k7HASPPPcyAvLDzrcNNZ/C9W4uzbSEOnNz/5gULx90isQ0cMw35PySBntQ9Hk/4ubRBuWgJmWsEg6IrE08PDy0Exj7ivRmL6DMZ1+0VAbVTfxaqN1Rhoq8sfbY81HfXmCo6Jp78mdeNx+XW4nyb8HA85HsM3hpUQ52MIg7KDnfrAgdlh04Q5U2w+PhW/G6KiJu2wLWMHSJUcRJz/o6RPWvT2zxurB3RluuOSMWljBYPZGzjLXlnrxtHh1Cv9ul8Dk7HrRTnHBWHNPD52CjRe0P3ch3xKxGbaODAN2uFa2Zk/3iycoI68p7vqunUBl9l3a+bYT2ouqsS7tSnq0LGIT/uRAdM2jUd///T6351nP7E4S/h3qjHs02BRRnwdOXw3oywzGHV49naS9XOzXXkySS3QHY+K+XBPyg5+3yxodXtfsmHeSRzx7NtkcmH6guvG15IJm/0akxUyOGqhJpCDtahM+PX3LQWe2XMeQG6ALKuP1ESqH4CWm3rHGvwnrdZjz3xEYuix2Xrs4+COlEeVQP7HpA0SpPyAfe6sTiqYvaRMGZwMF2U9Mo4a6jXVtMe7ci9kLU0UZMHOccrizIIP+Rt+eSu8kP/ftDeG8x8ylbHF60TgishwPsjmuXslzG7aSYQOTqsWGR+uipwUvdZ6joVKNYCYvMds3GR2oLr6EJ/9qLs8WRV4nTU5Wt2I4oA+j8QKdLkS2eAv36WcDr2eDRhgWINN9heCoQ2kHOhxKddkFBdDhWivGx5+N+pu8xB8WZQ3yhJcxvZ1dYu4nzrcG/Uo4nkS3x863FcRykiSPQ8FzLmrpJHEYU+0fzpxaaEt2lwtZUNj14ZTqBbi8ICD8d9Ngc6KIMgIwFBurOJH2yNEwYTHfXX8NKZAYPSyMkYgGofgVeDzRJd1for3PtyYzEr+HfvTFkIKpdjUUThNbmMjIVk8OGVx+866PDtmwJP1z3+ofsBr5sij1dSYiGtybJdpOvsnboTPwI+Q7917XF/zEM1Wx5rURS4tug66bJSSt+Djm7SzsioTwa/fmEw8QbvTlNWUylBVMm22qHTywA4rnjfaxs53gLQJeTxgAbsHZYBZ1uXx8alFJHeDmNKRRVWvcXZlgqiXvaCV43PZld8XolyljvvTfckOrXyYFPelaKiur6erktBA1JGiPQwHOSaQyJtkKZFX9ppqxlXG6g22bVVVydJzY36dJXw/oz8nELQUxZoLV5tyryvA8Be0WPdc1SlSiUmuMb8vio7RL93kdJqLZ7+L29e4w/NTnC35jW86mht/rLxeDDuoD5IWmR//9bi/flwGr/YMI6eZmbDM6MpzMDAX1POzGXrsRYeRRupfpkWIVsr6Fq42Bo8nlIddiNyaWt4Nup7rKw6F8csLGgDvYWuWpft4fX5vhKExFtkqsGffvYv/1pK6Xf/sDP9c5EVkhKZ7wCype3dmhe5ko60SwbHVcCntw4xOcxkEd70lP+pN/ysiBj5gG3rsznSXjGQKXXOqg5xKl1TlEMfQp9SHnuEZBBiyoz4lAyebTyerxO+vMcN8yZbcvNQqy0X9kw+V5+Gccg2UpLnTcLZtkQTDE7qHtdbh8YQnnq+9DgZJelaHZ5vPBbiK1GYhO8sPY4qSKaKE9tqA+cHI5p3p8KIl8p7bBMKy1lxaSMWBTcIgOgPiU7DQ73sLK5ag0WpJjspF0HaPelrUYSc/+AMD9FGuk8eBCkTfpzh/PtcNsKDapAvXYnz4qanLv2mM3g0IWNfH9iEweBMHQn1wRyVvZAsaTRz3RmcjAJOHFGuTc/NQwuHNho8XRs8mqTM8dHIej0o/sAxkBILGh1xLaUrUOLTrGCZWcghqcQ/jSbW6xYTMJfQso3OYgHU8uAv5bNpcbzsnSTj8mD/bFXg8YTS5+cbi/ujKMRnbkQTQRY20vUYA1RGA5HEml6QmD4ZNB0/w7yIsBZ4OAlZPnm+tVmxU7mYydK1qII2orqYFgHn2wImIRcyah3Njk+gWiCPCnQcN5X3xHtmEXqTE1ePanZr+yW7qZcbj9NxB7W8L2Qkpetu5CJ+er9DEwzen3U4rh1WveQBIeG2M5gWnP9bsDiMMJLdMKANtUt4bza4YjI23OV8mGUHOONwXPdCfFU0giiHEmSBlDlGYxfxuw5I0FO5Nt1+bXb7zF4TkWZffWIRx2JI+RQGUzmoN8HiYuto8iRIXR8Nagkf6xJPLeXPXHUON1E5NHyfyp/ZPQQTNIMC+RDaK9ncHZTqZqmW6Vo0y32PA9dKi6/LltJwRXusFCNcH1xf6374OzoRQ2zwtTgTT4ydHM6JDzisOrxqSow8cFglfLryaCPlk4uCirRV7zKCrWjPsmPG0sQTCe6DwVFFZGUTLI6qDm+2BZE2aI4OhPge8YuLu5lkPSsi7tiAl43HouBafbHhPvbBjIXpg4maPybZLwfp8cuNw0wQDCX/novKcCTNhcbXzwtksYKXe9BE8lIejTlGnXjyy1ayN161BnfFr+n11mMsBmD3R0T2bjuDs63Fl+e9+FRwLc6LHt9dVrhTBVGHITdVagXxo16fj8JCDI1ULrXqDe6O2FU8WRmMvcOp+KyPPWetmqrH5EZu9udbPoRP2hKVBe6N2nzw7Lopnm8dRwuCLCgjVv++llFLGyxmoy4fAoAGjXEEsiiGYkQfuGtxZDzfOiyEZ/Cy4c30gkZo9K7CzkcVN0f1C9j0PDAAZDj7qA4Znip8wqMJP/N153C2NTgd63zV404V3iJY3nQG3ri8YW+jQZAufex44F+1FqEYjLUAQvWn4yhjH3Gr7A0qx+sXExflPJPq+NLOow1GElG5CG86K3PIlMlqNHHi77gSI6ZZQefCdWBRsenJu7gV/sqijFhLEVm6hNpyI61kDTBUiv9/UMY8tlGSlZIo28hN7HQ8jCu0WLlpWfx46Tw7iJeFFIaKXJzUPUayObXieqgz002w8DJWuGo1twE5E0SdQjVh87Bi93HdWRxWiVWjoxvnsnc4Wxf4rZuAL87YFZ0A2dQIAJ5vbEY4jusgBDSiP+ctXQfPZGMBeH1nRUQN5IPgQlQRVKDEvL4BPidzG4SkaLOiZtWrCykPQxZMZMar7b2+ZgWLczV6U37J2MfcxW8jkYvaMexMfUYKm/BG4q5nfghmuhWoVsdnam1P9M1I/gmzhW4luXMspEdd6wDwjUuH92aQ4o4b+nXrsW+GUDCmbvJ6qGmQHtApGezlbApVQQEucF1rgJO1BqWMHLQIbUW94y0LRGcBJzJOgAXxVJQAejWdjPlIlvY4rjvyt6CuoQAs8GJT4rjuMlF93TvMCj6fVszZNHNCR5htMKiLKO6XvJazImUp96q3WFR9Lkb2yz67/45dRChM5kjslT1twgPHjhrLcCOS3tLSI0ID48gFSegN36+3kLgF8nwAJSPT2VIRuLFPeH/Gz/ly40lMtZo5xHvzsvE4rvssJ65dxOumQCOFRWkTlq3Dy02JeUGn4jPJDPl05RETS5ujKmRERBN/T+o+Z6j0scikZS0i2ZANdvIs4AL2Co7SJj7AiCFjiCxklCeoUnF93lc90YWxEKhr63Au46laGqZ1b7EoAyrHr98rQh5pzmQVbYLFvVGPBxMiFipnP67Jf3ow7uANsPI2n0+KiP641+eisLAyS+O8LcLZIVzn64sgc2KLE8dZbyew/Omox7506mp3qqmDEcjs41KMSpxlUVHKzVcoNySDNg36YSvknyYyGU/5CFfJ4OG4Qymbqy4YhbDIPOdm/Xja4uWGM955wW76w2uHe6MBHtdxSRMNnq487o84g3s47qEZAxctR0HnW5/JlbvqjrGLeDxhlTuqe6RkRBESMx/k8YTcirOtx71RK0E6Fp24bdLRLgm5bPCXHwnBlRkR5J7Ucp1bgdnrGnmmp4RE3aiUkKidyvkWmBfitCmH8UqIWzMfUI/4mVSLvuzIqB+XJNYdlAGPJiGT7lqxx33ZOXy07PD7j0hKmsumdliJLM0AfSLs6OQwUVc6HdloMi1/7qBiGBnllvBQqiw/H8mNwOvGoU9M0dXPrPbtnXAElNeyEWRBibqrzmDkUkYnWuk8xl5Do4AzybQhCdfgj5wkxNTlWao6ZDrj8MUZg/BUraIqjV3r9YVszMwp4VokXwS4si5LAu+POj5DHQvSb994cW/lZ5h6desUvpKMGnTNFTJTzs+4PI+MzS5w2ZIdr8mnvdzzWhqhKPPxdscX5tkaOKiIBkZv8oGuo5mrjh4Z90dRNt6Qf/eqtzgseyzFu2LZ0wGyCcDYs9jbrwyMIfL02drhpDZid8wD4LYjWx818uhjJUXvqrfD6C2QdMn8lIhrIdlqto6+tGG52BpUjs9pF012fS1lBKsET4Dv91jg903PddxGI6ZfBZGlwCJFixJn2EXzfljsl724qrpMAv/+LfDVhcHrxuGoZkH9yarAcR3QtFZGsgM8HpLBszWVb8d1gJN1pvc/JPIwNF9HZbQjHzGVr1EvBIXi74/4+VcyrqXHixZYCXcq7m9dGjhROmJVJLiySci7gDUG161kCwmPY1ZESegdRq4h6biP607jB5xN+N5tST+XZPC1vTY7KxsAjyddVrDxOksWSNln3yQdDVc25oK0T2B8QR2y86na/NOXJsKZITzuuqPVO11mHbbB5Oum6J1yuRZFkMbHo4/knS2KAFvEPHocCRr1G5cORzX3y8vGZ3NDgAVHLefksncZ0ZoXAR/dFKh+gp/254Zj8V+//4/BQrtnl0cKDLKBkEoKLDuD03GfF+NENq+bzmW2tFaEikhEgZGvWzpS1jI20ZnjTaephzFrrpUb0ckBoXDtVIx0CJezmidfwGSXNG9TjrC+7XVWz4Vz2XpcddwcnSWT+VA6qCaavBnrezjbcvapHchcNrqbzu2Q7WiMtV/S9vXZ2uH9WScWu0n4CSWOqj4TQrWo8WZQOyhMp1CbSpwshihnhUBLcXJTAxXdzNRDQa9bSCZvsmrqA5C0tCh7LDuXNyN2SjxE1QoZQCYWXncOd6oOz9YV1sFkiXFteagUJmVpmEr+NDNgI0XrxAdctUS2NHRIi1rVwytxUBU1IQ0s5yBdqBaLOhNVv5N1sPhszafudBzyoQOwYIkweDRp82GaMMgVlbB2I54dOs+tLDv/lw2LK5p7UbmjksWZzFrvjrZ43VR4tvbiFiicncguRDt+dmM9rlqP685ldOHDK4/3ZjFHrl91hJXPtw5dJMdp5onEOStZCq3LYw5d6zo3V7OxdbC43FqUbggP1HutHbLOddVwSS3RvaA/a1E/AIOt8EwIsjQ5YvH4N954fGkviTqM6bxJEIRF0WfJpvrTjDxHOR/dGDycAPdGfHY+XRVYFDGvD0CskgWaVhMqTU7VZwJAfi5UutxGmw2hgMGSWfldVx33kAiV87GY3SvF1A+q+CEqd95avDvpqGIoBrTmdcNIbr3G3lJSPPEp713Kr9oIGlDZlCF4lSafNS7LGg/KkJ/7p2t29w/HfY4uUOt4vefTgmo3TRpWknojyqQTIaJeyn4MIPNR1DRKR8eV5X9X0ugowqN7vDaJuyFjymNaCxq4KCMuW4vHky6jXLVLOdhSrQRuWnGSlWL91cbjojU4rodiWQm8q95gE4CTOmU06gsidX6+8bjpDCaez9wuh6EXxFR5e7oOIHv7snN5L93dbzRFWDlqOspvos1ZJcdVj3nZoQkOLzZl5rIoB0hHHBsZferZqKjHa1lLU08PJCWtdokKq/PW5z32pnP4n3z2OedYIHHOdFQHrDtuHvdHPV42hei++TAoW1rZ7QAXGe2/OXM+GXFupZu+6s5rF3EJHkKFSXjd8gFkiBN18CPvMCtszuBgmh+7or0iYuQCNoFQd9OTiNVFjbrlvPdGzIJICrR4NGnxuinyvDYBmArx7apl1fpk5VA7xq8rUem4DuKUBhxVCWtBSADg1cajdFyI376psCgj3ptyw7RIOKm50bxuvFi28nsjDBzEWa0buAlKllOiTiedszN0o9MHetk7RHnwQyL8R1c65A0qJIMgnv1qlsREWZIClVCmcj3V3McElGChSCUCnQGXvSPD2rMbuWo9XjbCvxCy7FYKssqyyBv7iKcrJ4oVKiIA4MMriy/vIRdRDuzWd70kAN77LnLd7RUD4YqjLHaoyvPw8hknPmFc9rCRQXi6zhQRCok8k1I6RXV/PKl7/NZ1gUXJrux1Y/HleYuXTZFZ5CejhPOWM/02WjxbF3g47rBfGSnmeF2XyeC6LbFX9GhrHg6Lkgeh8hQutgbvzajXf74psRGmeRROxVf3OAYcO95b5RntlyH7y2i085MVCXp3ZBS5UXWQXB/dMjspUkob8WbrcdU6HFU9omysI+nQLCBOmINL4+66UDvkkaMPxXmnxOwg69Bhv+zxlQWvW22J3kx9wNm24AaPQc48r/h9622BN1uLn94nZH8jHamOZWs3ZKroiEut3StLM6l7oz6PZKyhTXe1U2Brp62viy2LHgMikguRed90FnuiGlHbeTVW88ZkK/6J56GiB4GO4HSdKk8IUL8VjhLnRcDfeOPxwZwGcdetzXbntYuUMwM4HfeY+YCn6xLXncNtZ3Bv1OOk7oXkzmdEeUlqk+9swpuGSO2hjEqM7HdLsQRogkWwSXhvHPtQjgv4OKAe+lJenAXySPJSPI6UGL/qgZ9atGilgbjpuI8/HHe0J7Bv+60se5L9FfXpImMYvrv0+NJcSMFlxFbGuNroWvCQPxkx1+i6472YlwHP1h4jT47VB7NO7ievObldNLOrXcKntw6HFZ//VvlFggIDyPeeI/IBIdOiSB1j28BGdi7fd74tUZiU4+JvukHg0Amq5owisxaaxt1Ei9Nxh8utz2ZgEFSi6Sw6O8j/bzqXZek/6vW5QCxOq+P03370XxIZms3IgTL2D0uiFmdbMv9vWpvdN5e9w926pdIjcrEoK/t149FGZEmoKhjWweK7NwbvzrRbJAyrTHatGLWaBQZXxjYOBj6ayMeD04sWOObvDTukqCYaXGwdbnvguE4ZqjSGM3w1M9FDTg/y1w15BusdqPVKFutxvcVn6xqFSfjmlcNxzUwThb3fbH0OLPJSIN32NkOKrxs+PLXMVpVw6GzK5MUuMjFz2fF9H1Z9DtbRYKi9crCr7SIfdjWaaqQYPBm1uO2dxI1zs7hTd7AAngjkqqoVyr5o6PNkVeLZOuHnDyQwLbJ6Ptt6HMr1UM4GH3SXVStapJ2O+1yB71c9vn1donZSfEaD01GfOTtzUewY6TCcQLmXrUcTOPcszJDcqb9jr2SXf95alJadqKIlqjJR0t6FIHL7VZ9HT6ro0fmlXjuAbPggm/ZaZquX0j0QgeK6PKl7vG4cpgXX9N2aHixzOXhfbCzenQa0YZhdzwqRDMpGpgoAzQ6ZSWGkyA0dLun0uNs1KRqlGTG75lE6h+8jO3kdxxCZGdZPEvhcSdh6XVTBcy4ZER/dGDyacM69kjky5Y7kWyhRVDsudcLUw8HLvtFKQfzF2Qa/cTnOSheAfjIhmizjfXfa59yPq9ZirxgQgK0UGMYoAVrUIdB0X64Hhd5VmXXdsXver2Iu6ktLa3yV3epITYdK6iCs0fYpmfyMKbKzX/aCGGh6p83uun/ldcQ/dD+Jf0zM+47mtXzj0uLhmBynG0FWI+hzsRJET/euTvcB8JlXdVgrpPttIC9EFSmaRaRFU+miuEMOiFBIg/pC1UjalOgzPhZ79BCpxtgG4E6VMs+mdBGfrQrZy+lRos+OjheUe1S6hJcbhy/OWqbb7qCfziYclmxw749afLyscHfUZ9SIe0B6C4nS+6TrKMie82RVAiDx927Ng19dW6/loF7LWF3TjZU4uuvqPJMoAWNSfjY1OEyvj5J4KxdxUPYobMSyk6+RAk+N53Qa8MltidNRj0a4GapqUlGA7gtaLN52Dv/Dp3/m841Y9Mngu8sS+2UUJjDwYlPAInF+JxfDCeFJH3jIYuuicAq8oAyykYwloGvVW6xB0uerhh/5S3txIL64QVqUMCRrKvR4LWqSuSAffTS47i2cGZIVJz6gspyHXbYGhyLh1Fhqtd8FkGWvpYv4/m2ZFTEA8KZx+bCb+YCjvYSPbwvslzFv4IuCD/mbpsJNa3E67vGz+yF7a4RkcNYYfHne5cWr8b1jSUtsAmejegBso81ciBSHvAwLYFFQQTLyQ5jaoRyKAB+iCiqtHex/J0VElyyWvUXdekQMFfZ+2YvihYdNlwyanoevFpIvNwVKm/BwTLj6pvOs6quAfuNx2RJyVAToqOpx3Tm8kYKJrHR26grvARBUi2jVp7ccBVSWG4kWEKXjfSpSyijLXlY0kP3eBpHklfxeelB4vNgQkdCCxxleI3VuHDw6CqoxQFmdN2S1PxiTmPho0uFlU2AmxchSJF+3ncNxTTXCk5XF6TjitueDP/IJT1YWD8csvgDg+6sCADffyy3Xy6r3eR1oMdtHA0iBoNHat72VeHKy7pnRgzyfV55FI/d85CJuo0MhaI4ayBUGmIgUe9kN3H49bLUTr8Uoq4kGZw0RSJUSKzrDUc5gzKXGbWeNx+NJl0d2yQ4pogdCIFQEyhmgcZSpn21LPJ50eLHx5NpEg9q5XKCfjlmoXokNO0DIfSxKmcNqyL4BqIZ6saFKZF5ETCxHJXrAKoR/UA0z9k3PAgQCM5MUa3G+NXh32uOydTgd8bNteo4U9Pd5S84IeTM0AzuqevEO4cGkss3/7P3BpOuqdZkL0EX6gnxxlvKBXxibRwtqFtVFg1k5BIkhqCPlgO4e11y3OZK+Gwiumh90vvW43RKldrL2Vj3Ri/1Ku2+Hi9ZgVvB7KxuFoOoyv+hYFEqdINOr3uKT2xJ3qpALnlZGMJugVvEpo421JUftXJpWZxJO6i6rHl42BZ6tLVZ9jZnneORQyPbP1hbHNcfPkOu4yxsZgtGkQLcJMy8JyZHKvAQ2qprl5B2LFi3CSZK0WUZswDOP/BMn9vyDykyVNXsiHb5ofVZnUR1FV2RF2WYu4KNlhQdjrq21GApOPPDrlx3+3kPavh+UAectz8FlZ/Nn/lGvz0VhYQA8Gqvj5LDw79QhV6bA4DnQJYNVS+e9w4qLonQJyQyHOeeGPa5XBU6Eba9mSfS3MEiJv8cYYNMP4TxXrcseCgmE6Q7KmB/kLpnc6dEkixC1yknfm5LEmP0EZIb8aNzj6doLn8IKK5q/UzvIkU+4V3ATVILSoXR4Lzb873kRxLWQEHyfOFvdr6JUrMySMCYBEVgGh4Oyl9TTIWeAfAKXK/SjOuTP1EUmhKoDG5GV4eFRUqwz7OgDyAy/6bwoPCipOpVUUQBAIjOfBk3cLJ6uCxxVIf+eWjZWvRdjH7HuLf7WRYXjOglLu8C9EaG4mR88J+jdz432puUhoB3ZlRSmy87lokJHU1QMJFkjCcbwQArJwMr1sADaxA5RodOrjoS66CMQ2bGFaFBa4OUmoY0kPGqEMv1H6BprACyEI0PjG97/RUmDmoNyKAyUBW5BaL8TMtibrc3z3+M60G4ZRJbmBVVP3ka0oYS34tEhXSaAzL940ziMRKasB+Cyo024Nwknoz5zHZRwuxX5mTEJpQEQB/mqtwlTxxGXyq3VwlsPAI3Q9oZzbm8Ttj39KbZS2J6MeJhoQuwWjOT+YM61q9D2J7cOjyYBEz9INl9tPN6ZtryHYCGk9035M+gd6iLgZVPk0erIJ+ie+bcvHB5MGDj2/qzHo3En9tQGLzYe90Y99ivO0GMa/Go6GRcuypDJdGqnzSLCYiWsHSXRMoQMQgAmWsEAN76veRGHzAmjyblEEtpgcRuBkSP/RQtDa3g4n4ix02drj9qyWVOL7XUgD+njWxafT1fAl/f4QQ4rduta1DFd1GR+xnG9K+E0OK57qJuw8pNSAk7HHfpIiX5pgSY4LMqUVVAvG/X+AEoLRNmXveVapoQ3QYMCVz1HRp+tLO7UKatNZl7HGpSFnm195rlYQyv3m46x84V446x+AJ1e9iy0p4LYnm89Hk9DHsc7q2MVhifqAbvuLRqDjJAak3C59Tn7qosGkLV/MqKHxm7QXRMs1j3VZpUo9axBlrqyIB3GtZUlh2TVG9ypVL7LtUZCOhtKHdOqEqsJFvtlEDNCg7NtgQfjDpctR8LWcM2NXMQfuWvRiHJu2Vv86kWLn1lUGSH8ca/PRWGxyyS/aSl/+fC6AOBxUve5y1uULTa9A8CZ7L6LGdZVWLkVSU5IQNNzxtwGEmCuhdD2YNxnot4ubKkkG0YRG5SOc8SzrUdpO3ZbPUlkXog0mioHIHvfayHhbcoP9lTYyLqYAeT3OS0CTkzC2bbAuh/mcishtwEQXTHRm9dNkaG8/HXyOe+NWtp8Nw61G0xQrjtquftoMpy9X8ZcZGgQ2KYfGMjKJ1CyUZcY9a7zZiV7GikuXmxKrHtCzV+esyi8aD1uOhZfasE9SJXI0r4SW2/KKiVkyaTsTrkYdRh7h9eNA+BwMurwclNgVlAb30Zuap+tPY5FljsrZLwjqhaFxD+8spgXfBinRcC9Ee2l22iF8Juy8U6SokLdEWeyWZ5vqZ64U+mY4G1ylEXCowkw9nRB9CYJVI4sqbQy6y1txLxEJud6mxCTzbbimx5oZDPrI8dVXTR4Gip8MGvxZFUAojjIjHLLcdmztcVX9mhpzU4/4azxSOB7v9xaTCVinMWNy5BnZbnuLQjVLzubxxOdHPyaLgs5dNQG3yRk5j2APEPWNe9tQg0mkZZOZeSEx5XX4gxQSOF6KKqZPjJfY+wiXmw89sqIedHjvSk34jVYQB6WPe5JUfSmKbCUPQGC6Gna7aonmrYoOKZ4KUZaRBQi3p2R1HxvNEDOOjLdBohHgIcaW9Ein7JKLTILG3HdFZnUbQEZqQIHJQ8oyoM5nmwioX9vEu+NPJefitJhVgDzOuCyFdO0wMPwThVx25mcl/FmS1b/o0mHJ6uCeT825Tyh0g1Ota8aj8OS3KbaGjxbEwW7EkWBGvB1kWjJVCLZP1p6vD/rcdMRtQEYab7sbB536TMx8hF3ax5oCwn/I4EZeDCO4mOi2UXc0zXcMUqnTqWWE4VKh5vCSaIq+UFdMrhqCtSOa10RLoDNzOvG4qpN+LkD8mGmRcCTlcedKuHNlrHw+z7iu8sSpeW+rWOANtJtc+zpD7EoAlAgjw5eNwZf22O68Me3VTb/g3wWNqh8TtY9c1DUE+fjJSXexzXVd6WLON8W9F3xatuN7KNSS0MyEU7eNljUjutH7djVHG9eSIhZ6/HNq4jfe5TynqYmaNk/RYzfNIRREUgtIv7QscfrBjlm48e9Phcci3vlcfpvPfzjWAWLiXArdIMAhuCnVU/PhLPGyY0gu/hl47O0UKH/q85lxcXEB3y2LsQZkazrhTxgAG8CWceD/Ehh0F0Nv87/SyEd3amHOHA1YamsRCDLzFyr99fN4C2QnTJl/qbz801vs5/CJyuOP7TD0m514gdUQhUJl1uPC5FVjf2Q8MrOTJNaY95IZj5m9viiJEpxJSQfANnBFOBMTzcAxmibLKkduUGfrQWIhRiGiUpHnTt3FTqr3uRuBRi8GCqbsszzuO6wFOj6o2WJqU/5wHEm4cPrAmOPXEh8+9rg7shgXza0j24MfmpBctrTNfB4OgT4XMm1aqPJREBNcSR/ZLhut53Dh9fA6ZiscoAIgqIdMQ1wu8a7z8WXIySiXX0y2cmU9sIBF63PXB6Vau7Je9Cf1yd6YHx4XWBRJDyYdAJZc4PTh78wA1H5dEwC2yerAlOfcNsTKdMY5ZGLeTSyX0Zseqb6TkRNsxIk6rWoAlR6B/D66X11wmfYRQFWvUUbWbQo/6SPNDtSp8D9shfL4oF4FxMys/+w4jVOyeDj2xKHYlENsPtSsqAWPerGuOuIqogMwA7+iRSc2nXulz1++6bCcR1w01q8N9vi6brCyw1DmHYJfa8bl0cdZ43BV/c6eBvxretKnA/ZMetzlTtKF98yS6OVdxDVj8+f+0bGK/TsCDmyXvcJ9ZX53hL4ew5DRuDUNfRb1wG/+9BmOexgRBbzOpm4mHOUAGSFFQm3Bg8mg+vovCAC8u0bj7EngnDVAl/ZY4FyOu5xvnUcKUQqs24FQXBm4IhZM3Bo1GhOnWmdoJ8qf9Q5PpEI3rcHY0m+lT1fE6FVLlwJEuBsymeGOg6TrE+vo6vW46Ds8xp1hsXATctmTJ+d0/EWz9YVZe69xbM1x4nOJhxVHTqxbFeb8bDz81a9xXlr8WDcv6XGUqflZUcJuT5LxgBPVj4HPBK1ipk0nCCGb6KGU2l0G4GZT9mHpU/AtagM1ZitCSSWljblc0LHsMYoIZjX+kz4e1PZf9+IyswaxkF4S16Ueoeseyu+JkSD/sc/hmPxuSgs7lfH6Z84+iUAPJzGLubZXqGz8FWBhRy0fQQeTLp8IP/aeQlvgAcTzuBuxcZUcxdebcrcsQGAertPZINUSdhG9OKE5CR8xpDQuZLZ0916CBfS71O4VS11tahQGdyqp2Lli7NeuB8xd5SnY5FDygavBloPx1QGLASR2C9ZkWoX8VKUJht58HalS0rq+QsvLO6NPCpHctdCjMX0wFOfDHWgJHs/QnNBdOO/6ZhxUkgXZY2oHuQwuNwyJ+OwjHmEoZubGvdojomiRPOyQ4gWm8AUPiUivmlcZrFrUJRKnl43DqcjIh9XLTuKRjb/0kKqbZsh3k2v0uTBXlwRqmebAd3QsYdKmZUYp+MtlTRHAL95VWDiaXndy/hG7XJfbOh6d28Us8RODWvUDMsZznqVBQ9AZtpRpMicpY98jyYwZG6voOwzJpP5E6VLeY7PlMUuF6ZnW87Yz7YeJ6Mub4JNsHi6tliUGNKAHX0gFNnTkVwfke/pogxDRoggD6WNmVioeSoqxVxJsJgeikE2J93E12GQMutGeliGvBECg6RQpYBG9oYm2NyNq3RV7/nEsZtUlOpyS56KyiJVDqzPlB6iziS82Hh4i3wQawGV5B7qQTwWFG4lgWQK/28kwComoJIwr8IkmUuz4J0JH8TKdbjpmK2j45LLlgorRXI04bWNBvdGHWoX8aYpEJLBm63Bw0mQpogcnKMq5P3l2aaQPYqjD404mPqUR2IAMnFbx4aqJPn2jcfpmM/BUdXjWzcF3hc1kUbVj3zAZ+sSI0EZlDSvLzVU0tG2M8jIxFhCwM63lHiqFf7YU9q87onOODOY+Ckfp5V9SrlKSyE5qsHX2dbjdER4XxsGXSeZ92QTfvOqxFfm3VvxA4oItpGkYXofkY+k/IOpNHC6zhSd2l0v+nMSaAUwcoMcG+BY8qp1GdFRlCYk5HG3NcD3bgskIJ87WqyrLLi24swpP0fH1Uoc1sZRm2Vyhdh0zwoWs9ybiDDeqTo835Q52l7PIzUzAwYBxOe+sLhb3k3/leN/HAfl0NErQfG6czgoQ1YwBLkBqk0nx6HDVcf0QjWImhd0DlM55GiH8R3kxpQ2ZXmlGvr8IMlOGcsacrSN7CLXgU6RYwl7mvggs0/Cq+dbJ8z5lG+cVs7ND0SyWwMc18J8l0X86a3D6ZimNFfCGn4um4XGx8+LkOHZwiQ8XfsMuRkpOiIMvjhr0ASH7ywLnIwYLKaEN0U+gCE7xRlIxPgQlasPiT7ApRti1PUhqiw9IGaebqMhUalA3wCqUTKRKJqsi3Z2UA5ctnQ1VTSniwYvJD8GYNW8t3MoX7QuKyKW/UCOe7a2+PmDbZb/qjsoD3qS2V43hTw0FkcVu0FFjJS9boUwvOxc/rMmOwhqp6lJq8M1VHnhSOB8leJp9/2qcbhugYcTJX3y0NLiQ9d7sbN+DkU9AQzcEb1e+2UvI7L41qHxZO3xakPref07PeA5QtRRocmzUz3A1aVUzYoOyiDBX5DCnGoTfWa6xC6cB8jQcdeCVKjrosWA2mma526nrTwO1djfdA57ZZ/VFLqRnm+9jEgp9du9XooQ6ucBhgIR4OGjXA8A+UAFBtTGIuF7tx7vzfp8WBvgrUON3gZ0oVX+l760SFpKYUMlBNfbWcOvG3vkg0p/90ndZ/OtVpQxEcDTlcE7Ez57y87mA/flxuKre+1b3byqX379wuHuyOCe5MmUlsifFqD6GaiicxklBWiSZmScFHf2yU1PtFZ5VrUd0ITXjRPid8oFhIZFagG/kiaFiFxCJ4ehIhq6PpT3Aog76U6BoHve843HXhGzU6uSzsPOsVY7kpAVgVTPinujPvO5dN3oc1M6jkS+Mt/i49tKTOESXjcGY0+0T5Gf3ZdeH+WA3eyMoHdzQPRe6+fQ3CFtdFURpOgKZayUySpSyUIs5esUgbz/6TOpqc+6zilbRd7DFEFsg8l8oe8uPX5uf4t1sPjWdYEvznoZ4di31su/8P1/5fOtCnGGkO3Ym6xxvxLpqTJ9vZUYaR/hLeUuv3Ie8MHMonZOZmhFhptebErMJPJ1vxJHx2jwbGNFasiF4kzCx0uD2lm8O2XqZogkLb5q6Iw4dkQDtmGoQF83EV+cs6szBvj0tsReoYQydgnKF3ByQGm4GDCMX+jMGaS78VmjzRAZLvAiWHy0pFxpX6DfiZCT2M1wEb83oxQpQ4S1+E90Huetw1EV3xpTHOyMfgBufBctIeuQvLg68qFUxzaNRl529JdghDBn1G204i5J29ybzuEbVw53Km4q57LctEhb7HSnatazX8YMUz5ZlfiNqwaHhceiRJYi64PVJZOhfvUJWRQBZ73PP7e01OtXNuGsYQe+DjZLF0ne5DpUC+KUgCDdTxtZJM4ld4CySjFxwpA5o0F4Tqr7ZUdyoxr4WImr7qLBYdXjnUnEquKhfCnz4VacUI1JeLYGjKG2vBTIVZ0QAeRr10XV9ft8gH56y83u8TTg/VmLR2NVCyFf2/OWvil0SLTZpO0ieLQSD11Yzl0nPmK/ivjGZYkDMWxiBDSlr99dlni1STgZGTya0AL4unOwJuZiHQAutz4XMLrxB/D50ZHSZ+sC+yUJe6WL+GjpMfWgm6olgfObVw5fXwQcVlxjLxvCwaeihHl3usG6H3HDtUNXrkQ9LUp/ELXSw2wr97GNFl9ftPjwusTpOOCkpspoKQ3Ldceur3Y2m0Gp0uamG7poPSx13DPxEff2Bya/jgqdSSilk1XSX60FjEk4HatijWt1WgS8bjxOxyE73FZWnGajQeUTvrrHwqeTIh9g/se70y1ORh2+cVnidMzf8WqTMPUmHxzPN0UePY0dfQ2cATa9y2MljjMtIliwPxIEVgsN/v0wViaqNSQ7X7REiKeiOLvpKEdugsGTxmFeJJyOu8xxUSmkQvUziU2gJbjFQtQ/Z43DrODzvOy5Lyjx+rZzuOoMJt5lxcz51r+FVLTB4tG4F8VfxESuQRvZyB1WPWob30IdAZ5BipJetFQIvusGe4GQqMCzhomtMx9gTcK6d1gFK+qUlFFTC+SmqIvI+SdU0TCNVLNCtNCoLdc4DeeMPFtELF42FqfjIMZ7gwO0RhdctQ53qoRv3VQ4LCO+PCcqrMUKHa9DLkp/1OtzgVg8rI7TP3v6j2aIRQmQhXSLn9yWmYSk8x6aB/kM/yUMSEQt3cZcOhKVRdYya6wt9fZXrRX1CN9H5dQ7wwpxZTCySuBDpSiE2mrrpqQOhW0wEvDS40xIWTqaURvXG7WZFcgeQIba1Jte2cK1JfejEi3ymcxNlZxDS2Myt3VEMvFRwrxoQX4t44TbzmHiA56uPRYlN9ur1mC/HJCbRUm0QB3wVNHwuqHB0zvTFr3Y+lojnUQw2YVxG7kxvNg4XGx52CxKmoCNHPLDri8lpd6IhFLhfPXwn8v1OKpI6F2wvnoLyv9kVeCDGXNhdDTyQEYaiowoTLvbdR3Xuj6GRER9KdFSEQyF/BWV2IiETb9P57sqUW7CkFYLIJODz7e8348nXe7C5rJR6O/SLmrdc33OZYPYdQvcJap2kVkb8yLgpRwGCmurAc5l6996P8AwarqQ9T3xSeSvHONdS4jbcT3MYdW3RT1aAAiHwoq+naRndT686UQdJF4ies/ZUZFt3kUy6V83Hp/cRvz0QjY6II+5AKCNeGsEYqCbvclGVFqwq2S8keedtt8xGxCNvHAQXMyKgOvO4bY3eLVJ+Noi4aAkcvDdZYVaxhvcM/j9MRE9VFXax0tmcMyE23JYBcyUfC3vUX0vFoKuqD29Sgg1x0U5Uwo//2CsuDru6prrdpBULTDu1B1eN0VGIHTf+Pa1wd97h2ON624gyz5Ze5yOBpv17yw93psxiwSgj0gjjrfK43qzNZh67rnkNiT5LBaXEqQ13eGeFJa+EXsFUSy9R+p9kYBMAt7LgYJ2OGilKbloXQ57U9uAYudZVXJuAjM8zrdcyw+lWHi5cfhgvkXtAprgxGmVm8uX5xusA9/77nhRD1YAuDdibsv51gmRknwlRQAvWouxTxjJdXnZeJxvSRrX57O0Ca8a91YgGYtNA3XHbaVhUUTUSwGqsus9GaPxeRvOEgCoZVyp/MRaTBXPW45CVJHYR/rwTH3Eq4ZjvkeTDt9fFSgtn7t3J10WHRSG1+N/8eJ/+fkehZxWx+m/sP8n8rx4r2B62sdL4GcPYu6aFMZ1hnwGZ7ixX7VD3K2Gkb1uiEzUjjfXGo46FJJS4LO07MidYRd43ro8EzZAnltN5fALMqZh+qPDjXSmqrBYdhZvttQBa9DZSpjn22jwm1dERnSRqvxLLbZXweK44nzwO0uPXzhssm3r2dZnO2gAGc6OIvWaicPgbWeyN4aiP2pXu43Dxq5JfbfdUHipckNflY1CaHIibw1ZzWCBPL8GBq7JYdVnguM2DBki7GL5tWcNZ8Ta1alf/tnWZ27E03WRN1YWeO4tqZMeCi9lRKQb52Vr8c6EMleF0hXafr7xeDShFl4ttHX2vepN9l2YCrFVXQb3y5ALBoYRAfdHMRsPlTZmS+Zd7o0y09VFUkltz9eEtddirsPQK0aF63U5KMVAK/5OGHLiJOsgslu+kE2clt88zJRcCbBYUah7kQtumw3PtJBXwug6cKR1JYRfhVYPxR9Biae7a0YbgmE96CbPhMU2KsLDa6fjH3ZSRXbW1ULzuhsOBjUNupFoa820WPcsztqIvH+8bmjDrLN4NYLSwpJjjWFEtOotHo47IVO63JzomHUso45v39RvOdFqxzhk29jfMSZZywGsxkw6NtB73iWTn+dSOsiX4s54t2bna8wwhtDiYiL8pW2kCZYW0R/fFjwIxAjtTt3hb11UmeiskL8+SwDyNSxtys/QYdXLeLXkXL4F3pvxOVZHVzXJSvLe1STt+aaQRg+onXKIkpiLObzYGDwcq/1+yoqhJEW72nmP3ZCKO3bDIdnJPvNsbfDNzSV+/94+1EV5dwyivjnPNhZ3BLV+sUk4qk0et0521oY2druo8q6J2KWgfCejDt8VQrnuO/p6snKZeJq9IyxVhgfl4KOkPBwShIkYWgxBdRM/JG8DA6KnUuZSuGoqZVWSvfqraNOSLRLkPtG3JuF8S+JmGwyebyweTYIQRR2+dW3wB45bsXAv82fUAl35KJ/7wuJeeZz+G6f/aO4Y3p10uUKcCXykM543W4MH45gjkHUG/qYpcKfmYXLbuWxGpZLEo4qzJI2TNYDEB5u3NgjGwyYpUOgkuSechdollDZmi+DzrcP5NuGk5gOkTHJd3Loh6MEZQbOi2qa3EAs1WtENR5nsyurfF6/792etuIvSWCtiyMtQ8pCqVADkuR1Dwvi5VJZ701E3nUBkRjtvbwlDq0Wwuov2Uozo/FNhQwDZ/+BsS2MwnS1rqJkShHShq6zSGuSMiFXvcFK3edNQ/oW60mUCnmxgmvEAEJrVbkvf24msBeWgtMHkGeQuwbCRAxTgYaJVvzoh7m4+SvwEBl29RdrhmAxuqtetRy9ELk0W1DGUwqYatKXyvE1v8aoxeLbp8Yv3orhDDn79tR04Ph/fFng0Hpzy9EDQDVILkHkR8I3LEl9fdBlFUY5FKYenIkjqIqjdzeC9wGKIaAHZ7neqDgZ0h93lLq0Dx2a7z0sh46Hd2bhCwkpEYwFAtczLjcVRrSO/IalXGf/rYHFQdlj3jgWQmOapyZASDp9tikzAeyJZOUoK3+VgjB0Jg7sOrWpstF+SF/Rsw87/4ZiqkEsZW+rBsxFzp5HIzxsZX6mzrxL3lPT6pmGne76lPf6DMTIB0psh5ZnW3Oxob0UmyFBAIkgTH9BHCy+FrZpwXbROPE26LKNd9xb3Rx0+XZW4ark/fnHWZ5T4unN4PNni01WVizPdfwDkglRtpW975tU8kiJeC1QNQNSi9L3pFs82ZTYGVLfH3VGQqkV0f9GmCeC+pSjxlSABu66z3iCjLE3gXqyJqsCwByuC/cktpfjn24RfOOxzJ67kcD04n22GPaW2A9KqBGHl/o2EGK8E4D6S07fpTR7Dqttw5WIu3HWP1P1Vzdl01K3PsyrtAE3j1qh0m9eY8uW0sVYivoZFrnqi1T/oLH3VKv8H2QdpJl+nxZzuMWoup3vsjyNv/kSOhTHmXwPwnwPwOqX0U/Jn/zMA/3kALYCPAfxTKaUrY8xjAN8C8Nvy7b+SUvpTP/l3IJNgSkv9/xEEEjaDyuK2J+N+V953WJFYt1f2eLEZYD+VfjGEJmQy2KZnfoYSIL1N2X62DcCyN7l6D4lFxZ4QzwDkbm0mN76WOz4thq5h171Ru7qzrYc1NAKb+JA70bGL+OIs5hu27m0m3419xF7Bg+uReG/oAT3xCc4OzORalCDJICMySsycFwEvew9noxhEcQNUJEcdO6N0CcYA31kaLEqDd6dcZAA3PvXwUE2+VuUTH7BXUoJ42br8s0qJB1d1hwoBVca3FJhur4xoRdKl4wwtrACPj5fA7z/uaPsum+dSyIoAobqbzuG3rg2+vj+MUVhQIftY6IiFhSe7CCWyAkNaZ+lEAWFZVCopjGxsXqur1oqNO68lZM0qGc3CZBneOvDf2wgYw/V1VHX5zzs5JBalw+OpeQsJ0pTS0nIjO5j3+Mp8K/NRmwuvZ2uLsUcuzPWQ/dn9Nm/yC/FCocmTw7viVAmwWxr5iHWQGXSiokMLWFUpMNmyQpdYnL/Z2owMVDbBG2Wa03eglAZB2eUAszLaCJyMBufEi9ZTceRYyCwKrgl1FrztnIxOhpwTb5Ehd+4fvA/0wQHayH/r2Eu70anMonVjjTAYuUE+rh34q43HtODXrnsjXy8EwE6D7SJSUk8FrvGpFJebQCdgHpoDEdxbFhD3FjTXU3n31A/7zbQYvCYqiKeLcDB++6bAO5Me59tCrNr7jHz81rXBrDBYlECzLokOjiMejls8XbOo+PJcpfzI46HXjcFeQd7Wzx9sAbDAn7iYZe103BU3XcsALt0Po4yyFZ4fOV7Hc1GGXbU+81z6NBDim6CjZu7zq97mPU6DCNkgqXMmRw0no5BRR+UJ7Dn6ifQ7B6uSkXXvVLfMsdMoc+5RxzWj0AEi0FM/EFyVn7IKNivSXjckMkP2wOOaz+ddyY3RP49I0rQMe+3JSJxzNw4Tz73SWxYo2sCshOQ/K+hIraF7pYtooiD2PmTPGw1fU6KzNpX0IFKVn8qazSCJL6NI8IVs3NPq4apzWXWoIXDfXZY4rsNbMvQf9vqJiIUx5g8CuAXwb+wUFv8ggL+UUuqNMf9TAEgp/XeksPj39Ov+Tl/3yuP0p+7/Y2/Ni7Ui1CrxXGxqv3dboLCE/67EXXFX4hR2KuZVz1CipeQxaIKjEloAQv27kp/8ucGOVRMVvR0swVc9D6s9ST40QPYp0I4DQO7+n619npcqEUZJnTetxYNJhyerEjMfsS/hLnoD9TDQKhng5z2SKHXtZj+8sm95NSjLV70ZtFuMoIaaXAfkEY1Ctbs+FBoWplJcYDD12sYhtfUtnxHppgqb8KoZUCc9aFQu7O3AebCGNt71TmX9WrgitYv4SOzeFeLTlxYV+h5eNpSZfXhd4PE0ZDIlQPj2ofg5LEqO2jTx9rDqs8veQmRevcDitRCvdjsEdXcFkF00XzXcSO6NBn8OVZDUbtggvRSs6sMfha8RIgvsD68Dfv8RswyerIrMJ9hdMzoqmIhSQQ/1lw0N5XTsdDpmAB4AfPva4Pcd9Zh4Hka7xacFdoppk+XRi5Ld1J06ZKWBMwlPVkXmHFy3Fk7Id8pDqi3XDD0s5HPL3F21/7vNwcxLNov83VVr8GjSQ1M2Z+IEqAiXt4M7qeZ1OPkzVT8sJDVUn/fvLD0+XTd4PK7xtb1uODCEwPh4OmyUOjJ6sbE4qVPmmWhKr9r8X7bcmL2huyRJgTaT6DSzQzlD+vl0T9MOXZ9tfc+vtx7rnt4HLzcGp+OhQ+8jOTkjH/BqU+Z0WEVenqzpbklr9D5nt2hBoM+PEl917PFkVWZSomY26Uj6/mjgtymPTfdp3i+blUARwx46diySyCshsqBFekpc14paARA30MFwUNNu1YCuS4MXBvd68jEOq4A34stzXHc5uPBQUlx7QaG1uVAzN33/+t/azADIn13PhEeTNiMBwCBLXgWbJZ+qoCll/1U/GF3fWuDM/KDK2SsGb6JnG5/XjiroOBox+OjGo4vAF+chWw+8bgoshbRZuSG/ZeIj3kiBY0GLeWdSRslerBOORwZ3qpCfXx2NYOfMU5df/XwfyZmkxfiPG4X8RMQipfRXpGDY/bO/sPO/vwLgj/+kn/N38lKd+HXnsi6/iYO23duI4zrkSle10BpSozyLs8bhbt3jUA5paxKsISdCD6hzIeFUFjmSWReR5jvspg6qje7JqMeVeD/o/NqC8j9KKkP2Yxj5JM59fZYh1jZlAl2X2HFtRHakioIuEn4sTMJ+zc1JCy2Fp1c7B/13liW+shczH+J1U+C47vA3z8n4JkIRcd4Ocd6lwLkRTGfUccinK4+JR7YBVinoSBb/jRzILFY4StmKL4HaMashkWrw50VAbRJJUhCYOCE7z932NMl5ui7z2GheBMzLDm+aEu9OOizKDldtgXVArtrbMDgnjnzAowkr6sfTkD0KNJBo4lPedFkoGdx0BV5uEiI4LlGiKAl5Di8b4PHEML+htdivYjZgUi8UjVA+LGM2jrJ+GKnMhNDbJeZlECkzOVY7JIOx4/o5qnoc17SLvtwyuZVcHIfzLZ39Pr4tZDNn4msbgba1Waao6a5HVS9ZJsI92mdxfbatcVJ3GPmIy+1g0tUlAw+RTduUFQ63ncOztcfpuM98kYlnVszUB9TOZVlyF424A9qM/FjD9f2q4waoqhb1Q1gFzahBHrUcShaFIm6apqqkv8Ni6JqfbSy+Mu8wFrk3CyV+nl3m+pfnPW46rg1Fg24Faj8dx+xRsF9GfDBr8XRd4N6IndxhRdfVF5sCdRoyOjjTTzJSIiI3l/1A+V4T6eR3XVwrqY31sHGGxclrmV/vlwGHJQvb92ckofbR4HS0xXVHEq4JlPcak2DlQN5Gkwvbl43BvCDCYsE1ruTCFxuHTV/gsAqYVyRnLsqA46rDp6tKnkmDvWIo/jW3RtVXyiv48IoW64p6KFF4KuTZ227walj2BiMHlD5iWojXjDQbijTtBkJqHg33O5PVETedzXHz84IcMU0sXd5WAJhqqpYBqoAgIheAQHLrzMe3ZMrvz9q8XoI0Ww/HLb51U2VS9K6MVdGX143D07XDF2dECy5FcfZy43B/1GNeBFx1dE7VYlcVfVedy2i9M2B+h6fK56KliyubYj53BsD5lvdhr+zhrUMfWWzrXlRY8va8UbdUEmP3qygIBXBUdTjbFrnhvW49vnVl8XMHAaOqx/dXRSb2sqny+Mqc8v2TusfL5j8BVciPQyKMMf93AP/HlNK/KV/3IYCPANwA+O+nlP7qT/r5qgrZNWUBkJnuKlPrI7snrcaaYHHd2gxHacV8XPdZ2qXub7diNV07ZIKdOiyqHe9EYKXPVgWuO4M98enXORmZvcB+CXH540F6IJbDqiFXhzMqKvQQinlevxtEBdCLQbXlKinUa6DKECXN3B91hOOFsHdXNO9tIIu7sFReHEvypzNJ/CsiNkIU1BGIegJcd3TSs0hZQXPdCZIgzofabVV2qPotkvjms7JXUyYdP6lZjHpdKOTdSlFyUveZYLUoA/bKFpfbEl0y+Gzt8WjMwLSPbwu8O+nwibCUtTIHkB92vXYA4WSdGSraoL4Yz9YF1KJ3UfAgLW3KVsi3vcXF1uCgSnlervd2t7vYJbC+3pItf6cKmb2/7En6DMK49lKsapqt5rMMtC9kRKINNsOZnXQs8yLgl19F/Px+kU16AOC92QaX2zJ3TJ/c0j3wUlJWT8TA6RPh5Dwc071TFSHKO9HX7uy+EUXVi43FgzE/m26majQF+fwaOqZOm7p2VW4bdz6j3o+L1mITgNMR/3YqkkDGQ2ugYMqusCoNVEdW9YRpw6As0vW8qxCArN9dpdVFS3+cJ2uPe6OAo6rF+bbA//bsM/zx/Xeg+RiK7NRuMJJSErMTEt1G1sOyG7gtV63LssGRi9mDQ3+WHsTL3mZzIlqCcz6vCZxGft+1dOYAsrrmTsU1Qg8Nm51Id1/6+UPi83nVDnEBVyIXPx0xvG+XhKj7bu0iFmWPl2IyWAjKenfU46ObAg8n4S1zKKb1cp+2oLRV0RN93+pFoWuE8d82x6gDg9ujIqETn7ANPDRVAgtw7KvXxu9wh5SbtGuspWOqp+syq/00tE4LcnXxHInp2S6HSdeDIh8AMsdC/V7U1+PJupDUZJPfVwQy+bh2g6W5/t7L1r9VbCoXSRVqer+6SIn8HXGV1vurBa3e93WwYhXAN6tZUMr56JPJyJ9+Xynn5m5IpjqfajGkReCffvYv/6fjY2GM+ecB9AD+LfmjFwAepZTOjTE/D+DfNcZ8LaV080O+908C+JMAMHczvG4cHk85o3p3MrihKUehdsDzDQOu9iuqOzbBZkhdN5Lz7VDlAhDiHmWeAB/Sq1Zdx2L2MqgcY9GvWpmpugGyvNlJ5zup1a6ZUrl9UQ6oXOi8dXnDVRh0UYQcEqajkNXOiAWAKF14O9Tg6af3Cb/tlz1KS5VMYSmRW5SD8sIZ4JdfJfz0QsYbEhv+6crj8aTH6ZgozyYYXGwN7tbcvNpkcuqpwsf6EC7KlIlBSoYtPa+RSgSPRPWShMX9XNjsc5mDvtwQntxNGSVPg9dfJXMAN8uRI7HxxW2ZuShP14Tf2mjwlfk2k9Oeb0hIUzvd01GPeyP1eKBZ1EHZ5Q2xiwwQKyzgUkJpgVeNwenY4qpjkdMEepWoKkNJh8vO4KgO8DbholUvDhZhlWVH2gQiPwZOSJMxzzivBe1ASmh6kmKV0LqWRNkgo5FK5tYaNjUpBhna33fkUNuAxxMScM+2Hp+tailUbY5sn0lhcVjx4AQ8Ppi1YDicE0viQVFU2kFWXYx4Q65amq3NfEA9Ffa6FBCdSZnYpVHTerCrZFLJeV006AXdUzM0Zww6a3Ai0kSV1PVRciuqkGFjuJjnxFOTcNV6XIpMXC3AbyHBhL2BsniU5DuvBz6TPltK3Fz1Fq82CT+1R8vm0ib8I4t3chMAy075Ts0iubBUo038ELu+jR6f3Pb4yp7N0vJW1qj+PgOLi63Lh2IvqgwGTaU8ilKzIrVvjknXUsCiZHBYH40oydhxUonD50/3uO/dMjirFVOzp+tC+B0mh1QVZuBrAEPYn+bwAINL7sfLCnfkGSxMEo8ZGic5kzCre7xsyoxsTnwSPow4SUqmjirsrNslzg+JsZcyUpnJQQsQlp8KQkbTOd2zeLgf1x0WJcclgB6wfA/a4HH/YoF+WLW4P6IT8H1BkhWhuT/i+PG4HoLUluKJo/5Ky97mZtKZBG+H4k1t2am2CtlPSIsrg4Gr0SeTXUEvW4enHYPZrDHZfM5Jw+hswtghN3i7L5KIuRc7Q1TmpnP49rXBF+fI6rOJ52gnAairHkgseAqLzHOblxHrjkTk2YSIryKMIRl8vAS+vj/45/y41991YWGM+SdBUuffnwT2SCltAWzlv3/NGPMxgA8A/OoPfn9K6c8C+LMAcFzcTd4Os021H+4SN3aVGC7E6vQzqQafrIB7I6A2yr7mZpySwTZBINGhu8jx5o4Qvs6OtrKpKQ9AA8b08NfOV2fMqhKoHTArhi5V45y1On25MSiswfuzkCvw3Tme/lknkNheEXB/xE28q7nZapHycNxiUbrs1vZ0XSEm4DdvgS/OgK/tGTwcE8r7+LbEzCdJEuTCJGs4orbsmlQN0EatdFOe8+omphW+dqharpUCLyrHYuQjXBzmvKr+uO0YrLMUmNiZhEURcVjyXny8ZObLBzOiMJ+uqow6kRjFQqSSTf6T2zJrr297g+M6vrXAL7c0f3rdFHCWh1CXTP4cP4imVJbjLwPIpmvfOtT+9rnByYg27oVNWZ1gjbplamQ31TDaiVkwhTNKJHIvY7CxT/A24Nm6oAnahCF2GniXwA54teE46nu3Ho8mIXf8T1YO7017PFkT7lXb6pGofbaxwFgURX9+9V38M5N38GisSBsfdeX5qHV3YWMuABalpq1aucdBUmEH5ExHJKrgWPf8WfoZSiki9CCpbZRsEK6zy8Zn7k4tJOaRi+gN+RgJwGdrh+N6kMUeVX2G+gcFT5Q8E5fdQHeRS4BrXzvM143L0m7Nyrk36vH3HTP8byMITGUHVc2dsoeBz7binRQXmriqOQ8nI/p16HOvaiBdC3002CvEC0LeqxUSl4WgGDZltZoaRCV5ThVtSNJZ1y7h2abMEu1la/F6k1AYds/qy6MHBnNKBjTiunN5TanEtTAJHy+Byvosubw32uLpusZFa3Cn5vfuckT0EGuiFddUIgXseNMOaZrQ/0wUU6swOKiqpwP3ThZZUyEYr0RxpFyrm24YEQLcQ142BW46i5kX75XOIIL7zWEZsEouc8QqG/CmKbN51PnWD+FjJUfKX5RxyEXL4Lhd7pLys2aipnB2UM2oRfdV4npeSoP58a0XpSGRhiiEbkqoadE+dlyXlaVq6KL1CNFgE22W6BOxC/Aydqucqk0sJuVQUGjA2y/cCYKKF/I8Iid1q6/SouwxCdwbFXE6rJlou+xcJjErEvjebAiiU/TsR73+rkYhxphfBPAvAvhDKaWzna87AnCRUgrGmC8A+KsAvp5SuvhxP/9BdZz+mw/+eJ5vA4NRlm4MH98yhe5uTThPiTwqO9UO7fna4WTEeFyABCJlryd5kPQjr3qH5xuyp0ubsjGJfp/C5MBgDjMvhkRQJaOpsZKSqyY7EKZKQKdSjNy0zC9gNoDPkGvEwNLfzS348MpiVpDJrMXNXhHy19+pYq7WVWv8unGYFgOsCHDT3cj7Vwb6XRlFbPohXKeWUU4SZGKXvDiSLvXJig/LyWgI20lAntWrBXRl2cmvA2e/GvalWSmqMtB7bgzwmchsdSNcSvBUSMif+af2Gix7h3//RcQfOvZ5jnx31OfD/6jq8GZbZPVJSsidxo0gMHsFUQiVnqoRzWHZwwoUr1IwNce6bpXbokWpzetJzZiUUKdmSAflYJuu5NfSchatRkuVPMB7ZZ8L592UXC8F7fNNgTdCtNK8Fh1taPDYogx4ufEi+aOS6plkhDDwKGXSnuYJaMS0emTsGhr1QjYt7GBxr+qJl43P61eflU0Qx1r/9jhB7+eecKH0ugJEBdWQTrMXVj25KGOXcN1ZnIgF80SkhYcC7TuBjl9sBtLlTy/aTDabuJht9FVJclj1gyuuvLfrzuH7KyeS6YhF0eMbVxUmnvftk1uDkxrZ0lxTcWNCliwCw+GrZGh1t1Ve0K5PA9NMDd6d9lk6et053HZUSiXQLZV7IkMVNVr7w6uAn913Ite2+WCf+IjfuHT46X0edn2kQm1RBMwKZtA04vJ60/EAVJMv3h+u14vWZr+KlFgUMSWVe2AE8KvnBX7hcFAhaZLnHXnmVH6q6KKqHFRFshTUjxwul3loCtUnUGasz++uaZ8+R0qkHnm+t6vO4ayxeDzl+kgATkddfga59/O/F1LY6BqJaSDI7oaW/aBVvN6TXcR8UQR886rEF6aD74pmRWnsgzZCN1Kwk6uGXAyqW6Ye4KUjP07HSGpgt40DSqMjRwBiH8DnV8ft+nVKjNdcGH3G1Zfp5WYYi+yX3H8+uqmyqWOEyeO2wiT885/+qz9yFGJ/2B/uvowx/zaAvw7gS8aYz4wx/zSAPwNgBuD/ZYz5DWPM/1q+/A8C+IYx5m8D+D8D+FM/qajQi0FYk7wJzjHfhlq+Mh9iy510yhMfcFgNEN3IRYH9edipaoAQt82BQ4Tz1QGPD/lG2OlHVU9egeHNu+kIOe+XPe6NOlTS4T3beLzZkuGrxEtrWDVrUfF8w++3hhkgMx8x8jQDuu2cQOi8BSEBD8Y9zlufF2uIBl+cIcc2K2tbD5z3ph0WZY/VjkT2qnMCwxHmrh0JQS825AnULuHhuMNRrcQ4LiJN7FOn0sHXf5C/ttEKlyLi/mhwMQSQlR/0l4iohCTppDub+og9Satd9k5CdobEUoUFP5i1EpceJdG1z6Y4l1tC/U/WFSqb8MdOTeatRHA09uEVr+cbgYknPuGzNYl+ykdZ9spQB56tC5JeHdVB6ob4svGiix9Y61PPma0xkA6Wf+6lS9fwnxwG5BSRcPnrIrRrcZIHYSVRlbyKVxuPkdudc/JrLlr6QNytezya8LBUcxzdJLUgSwKLz8uIn1rQ6ObRJOK47qWj5aF/K66bfFZY8KnJ0VLu+8vG585RlTIpUeVhFCmMLDpqkdwe1yEn4RoDMScbYNyJdFDbQPfbyy3nznp4XbU0NKsdsOyMFH98pmrHA+m47sAES5M3+annePOBRH6/2qQ8frFg86HPFrs9g0tBcr6zpBHUg3FEiHwebzqHd6d9lq4f1zzsZ0XEgfgkbIXnoYRsAxZvDPGTgstR0g4g/9vKc3JYBrw3ZRbJm6bAd5Y0uNtGg2drIpQjP2RJXLYcy96pevz+I6CTolS9WrwlkvZzB1RZ3a177Fcxo6y/dlHn8cdSTNOUA6bEXQB4trH4wrTDTBQG62Dx7rTNBO4mWLxpCrw/S6KwYgdd2YT/cHmBv3S2FfdQIpg3wpPRhuGidThvB8B806vkm2eBjjzV+2LiY25AdA2EyLWkNvivG/7MTW+w6nn9K5twsTWZdzMvOL5RGXwTzFvZSdetzSq5hexXANflzEe8N+0wcRF3R8Pf1Y4N2XXn8N6M4YSXrX9r77xqmbR6KyaLunfeCn/kZcMCw5khT2gk/h1vtg5bKdY3vc3P49hH4cZxDKvFh75Umg0Mah0lLo9dzOifRswfVhQ1fO/Wo4n0gypkktBEohTecjy1W6T9sNfnwiDrpLyb/rkHfxxP1x5HdcjkKu3MC5MwK3q82RZi2MTN9ONbg/dnKSsPVr3F60bje+kxfyUM3dfiFncis0m1ZPYG2XdAORd6YCjBTY1OVNmhi8KYwV0xyKaoFWZhEz5b85BQnfDD8ZC0qDdcf3btIl4JUgHswLnaBUuGhiZ/KvnvUAiTAMOIPph3SMnkWbC6hqr9uRJXd2PKnWHxpc512kVei+vkXGRflIYOgWGldNJ6j142Huse2CtJfFRzLUWdtANR+97vrxgTfDomZ0SZ2IoE3bQW78+2+O6S0P9FS+QGAL4wbXDVFllO9s60xUYOcD1oNVFWH+6lhI2pgZWqevT+KXoBsNAspZv1MgZRgpO64F217BJ3nQ8V5tWRwfmWhWUQ0xy6uw4SRDUJUlmkShCvOvJG1K1QDX7UT2Be0HXzUizCSwfcdINl94NJl78uyzg7h5uO6JGSIpVYqM6fJ/UW37oeZQRi4kkqvJV5+f0Ru7HP1sVbsPii5LOjKN3u+KyV7weQ0YoumbeMkRRpCtHk7p5Olmwgvrss8GgSMoFy1dvspKtqHpUVXrS01AfYMT9ZORzXlH9ugs2W+k66zPOtzwZos4IH2fONxxemW1y0BUrL32MMD3F6brjsgNgKIrM7dlDFQcSQ0aEE4crGLHnUGb/uPxpPYGQdJwyqq8NqMPRaikosJmQ1mSrbQqLr7y6Z8eWGTqWvGyJ+SipXYqDmKAEkNTuL3Egpx0KJt2cirT6sYkb6AOTn6VaK5rPG4mREtVqfDG57m90mGcgW8/1Wqam6TepoW9GMK0mUPa77t8ifGgO+FB6cEl7peBmFO0RFRhsNjqv+reTPgXNk3gpDnHkWp20YUImr1uLnDlZ4tq5xLZk7w/3guEBN7DT7Zdfe/997fYuvjPZwMhKDP8dnYRPIwakc3ZDViFD5eEreDmkgCCuRXsnvalxX2MFwS/dBjrsT7o363IAueypO7ohy8rZzGbGayKhQn3X1cNKRlp5f/6mRN/+TfG2joeFJMIBNWdN901kUPuG68+wc3RBP/sGcm49uNE0weDzpYQwvlMKpZOKyQznbFtwkQJ/7eUF46bK1OaRGHc908U6LJGQxgxcbC2+sqAa4KCaeEtepJ/Fu1btsgXvT8n2lxIN6JAXExDNEaOL5d3sFfSkORb98tvUy6xaWeDQiX7VZwhYNcvrrbc8I9j6StHlSc9G+3HjsVz1NtFzMyaJjl95KY9QFnoAs/6pszBa0Mx8hiFruarQk7aLBpSxIgPfDGkZRvzdtc7bEsuXDVzpCvA/GfE/VzsZ4vqUap3S87h/fVnksdFglPNt4fGlO2R0wkM5ebMqcBKubwaNJkG6fkO6iFHM1UctwHmx2dPMp6+udeTttsI8pF2BUGrHC100gJSN6cZJcm2CR4tCh6eYbAXEOlX8cD9WUkNdT7SMm8qbGLqIeURq6ChZLKZzVaOpOrUVjh5h8llgDRArWopzS0c2i4MZ3JgFJX5lzbDgqkgRseUHs2EV6k+B9QJfcWwqDwyq8lWFASa3NB8KbjiMHXSNHNcllV63DVecx8/o3ER0GiLl0CedbC2MMXmyAk9rgqi2wUqkJ+LtmnmOs3hh8W9QJMRm8EVRLC6mZD3hnwsJvsPM3giZRQXKn7rC6LXHbG7wz6XDdeaQE/MZlLYc0VQEhGATHw+dAPBJcNJI74rAQu+8gh6iOMnSkOBL+kTFAbRLWRuWcGh+eBL2SzBOXECK5Oc4k2UcMgh3Q2CsZZbD5ill1NSsCnqxKvFgn3KkpmT1rODr9+LbKmST67K+jxWHFP9svqbwrBLXdr4Zi4E7dYV4E/I03BWaFEYmzzwiPcq4sEqwhGvdm66Ept1eCuOyXg98Li1N5PhJTkkOi1fWmtzgesQCc1Wov4LPi7aYjabawRB++fePxcEzUhiMoDU20eLNNOCxNDpnTQ9JBsjd2ziM1ujrf+hyNfjIK+Nb1GCkBd0e0wm+SzUWF3g9yupIQxvnzDIA/dneKVT94q7zZOuyXzNepxYdC5faqhGojCeXOEMFU7w0AWY6rnCbNRylsQkwcOcUEHNjhekRxaFJ06Nm6wMNxl4PNZkUUHp84z3pBmYVzoRlLZkcg8cNeP3EU8v+Ll861Zp4byzYO/vldGlwIp2LmM3Zqv00YSdP+lh1HFM/WHq8ado+V5ShhUUa0wjdhPgLnWvqA1S7houUGtyuLtECGjDhH4+9TcpV2u5VLAskB2wC04rJGMqHFtOBD0EdqyUmWMdlN82xbYlGSjfzxLY1vlCCz6Y1U1zanHpJrYvPsf+rZGWjcdSOVbmHZRbYyF7/c+hx1XTuSYffLXgKrBsOY143DNlocVCFD/KVl5/PxUl3fojgPhjwj1IjskYu4N+pRiNXwsw3RJiM/Rzcq5Y2cNUQePph32CujjG3I4dAQM4BJqq2MJ1a9zaiNVuv7ZY+5wNVqzTwR+P91Q824wtMARBJL3gGtrHkNz7dOnCO5DverHkdVi+O6w4Nxh9LxMHi6cjiTr9V1k+FH4Zsos9sLr+LJirbXTHN0mVCqSNivvCHEu5ZRlQaF1TbhRKTUd+oOpchhT0eUkN4Vz5PbjnNrCx5UUykmdFRGCWHEl+a0u1Z5tjfDaM4ZFr4R2hGymFBS4sWWnd7MB+wVQYpkdrATzzGMzsAXBTvrWzEcu1PRj6VylOF6k3CnYvHJ0Rxlpyc1i729IuKnF9J0AHjZ0OjpszURK+WbjF3Eo3GPNo8yTCat9dHg+YZ+JaVlUanP8KtNKWhSwrIjZ2S/ijiSg5ajTLp+Xm6J7py3lGjvV6KM8BHXHYO3msC1rbPqhYz5etlTNH9mVkRR5ABH4jFAA7SYnUGvu8FBkp4abJxuxIU0pcF+vA0mZyJ9tipw1QK141jgt6+5V1pBpj66YUF0WPVYlGw87o26jNI9mgiy2w+Bg9Mi4Kr1+NXzAvOC6+l7t2VGu/R5vemseBHJ6ELGZEEK7f0yyNfGvG7I6+JB+qrxGa2qZF+hgozXUDOOxi5mHwvy8YhoagrxVgr2iY84qgO+tsf3U8nI86iix8RNO3gl6TjvjhiiHVY9LrfMb3q54Rjj7ojP2fmWz64e6qWgigZEb9TW3MuerWeLjh6UU7RXRtxKA/xaxk4LcXJeyDnA6ytOplumt+rhftk6fLYuYA3eGk9vdsasm52xqY6l5lIwDWIJjpvbwPt9Ot6iDRavmwLXLflxd2o2bzoe/lGvz8Uo5H51nP7E4S9hr4wZcj4TKCZiIJVod92GwRXMGeDb10wVBNQSXI1yIGY/1AgryVIJdxHsbHS80ScjUKJ5Kw0TgFTZtN9Vk5hVTztt7WIXBef0lR108rswPOVIMf9cLZgWBUcU6tCp0b1aNDSRC+792Vbswsn2frlJeHc6xJBr5zQr+G9KKHlQRCB7BOh72c1PUXjw+caicmRoKydj1Uv+hniH3HaU4KlpmPoXaOaK+ky82dJ1TkPJNgK9NoFuk9r1AsO44bjupBPxmTBlkbKscSIQ5ZH8TIX9EpBd7RTBKkXO+PHS42SkWQrDSOLj2wIno4CRPIz6EGq2gBYfqpJQcmOQB1A7coX022hwvjXYBuALU/Ju1M0yJM4mVbasPzMk4LOVxQfzHq8aj71icIK9bGm4phbHzpAfs5ROxWLIDnAm4dcuPN6b8T3vJiimxLFdscPIXweDR5MWNx25JKUjz2Qtz9+LDQ2UdKShJFu915piqYWsFp+64ahroQXRJ5XX6hhJNffGQPgIEOt3sUDvqVJRt8tdgvAu/FtbvuffvrH42l7ICpbv3RYY+0RlgHAItnFITtYxZyvroXYJh2WHz9ZVJjIvOxo4KZFWiaj3Ri2erKs8ZhrJePZlw7GrFgyqRlpLAamJybqZq8pG9xwtalsh8zkz/L2iqSEBn946PJpwzOhsyshCH012Gn62trhbk9uhKAibq4EUOy84gnyyKpESuTHcJ/AWmXLkohSFhPz1GfurZwZfXzBPRQ3CKF33uQlc9jbD+kxqjtk0a+JDJhB2MgLStaweL7vurYoOqsRcVSQq9b9qbUYIVZGzV/aZRKnr9Mm6EAdJngNXncHpKGYS8ydL4OcOQlbgXUgRqc+Cqulql/CblxbvzagEuluzwblsGRuhNgXadOyr2keaGX0RSeazonsZx/QsktowBK8Z83Zek/K5dB3oeaZnpcEQ8qguxEt5No/rTsYrA+KiI2/dV9T/RQtjHWEvioR/8cXnfRSSkGHDmDQOlhfhqqWWtrAJIwAvJBhmN1b7a4seKZEUqDPxJHdnGw1iGjZYZWh7m1AabpLqNLiVDby2hKhDHHgIbeBFB5RoRDjUGMo6dU7KYoMjjt0kvnnBoimCRE5W+THPiS9aJ+ZW3ETPxfe9cpx3JdBxTUPXmuDxwVzY/UIkeyE+EiEaPBh3sAA+urF4NIlCBmWBsVewkFAWtHYJsyLi4STkjaqRDkjRCJ15TsTrQEOfQq8dOoA0uO2p++b3VwVmRcxzQmCYEx7WHa46kYFKRzTxAwdAU1BDBJwnpDcH8Km4aS4KHqBtQCapPV0Xb0nfHk5C7oCmFnixYad3UCZcbB28seJdIv4PZczOmMCg51cXu62MpdT/QcPWRi7hdMQZv8Zez+oe3gbcdD4Xiha8h2qX7oyHMcBBFaR44nU635acGxcxz4s/vC5xUutmx+IwJkrR3pu5bJle1hEhOmwEtQnBoBC2/1lDAzB2I3zf285mzsyqd5jvyBPVDr9PBluBWteB6MKTtcdhGeHMYPymRGMrBcnFFgCchL+ZXDxvd2SPijbVlmgE5XkshGtBbbysGaSEl43DY7H9tgZ4d8pifl7waz+Yb/HRTYWpN8K5iJIWa4XkqCRSI6FnCTddxQLSprxe9Dq0weI7K4PDCrjualROx1kDqsX9yiAlridVhmj6qcbRf3dZoIvA42kUSB8ZOl8UAWvL66aFLRn/XBfLzuFklLID7DZYFJ7d7SpZrILFZcuiQg3/LrceizLmAmuvTCJhfPteux2+hELfkyLi2boQZQEVbdfyjH55rmtmCNPSzJuUACP3q3YRU5Ny+m/pothG+3zgqc/MRD7Lm6YQFQy5IgP5MmAdaBBHR1Y60z6atDhrHJ6tHUaOz1JMBtdiOrUVcrTueeAyomrI23xQLzuDn97vd0aqXPttMGglM4emgyXOtwnvTFm8WLC4+HhZYOyBPgniYiMmo4jv3ZaC7g5jAlW6LXvGmGsMvDol98ngpqNvUYrAVc9QzN0XFSR0U1bUQZFnDQ4kSkbyLflOlipJ+cw6JtQ1cCUN88hFNFuPlxvuNYdlj09XBQ4rNps/7vW5KCwSMLjzSXdyp+6w7Iha3PY2R8KOnPpJGGhiaBNszls4rPjA9UIIquRG1Tbmyk9Da5J0CarlBnhjNc5Zu1e1t172hL5GAk12yWDTObxsGNZVmJSlhRo0cy4prWPHVLuJ7/FszQ4aYEWu80cGynA2Wjsemk3kfJRa7ZC9OKwYMRXy+YAhFlkJml0y+MKMEN820NlubKVzEwKZVrm1MPdDNDCi1QdstiAvrMlS1CyxE17LvhD3NPVQZbXOEi5Vwp4yvdXWWiVSbeDhp+Y9rRRVEx9RTzhyURmtVvIz4agACtvT5+HeaLiereR0AENccErAUZUyjDj1DJ473xJGvVMRYm0EIWikw3+xdbk4dXIotVJoOHl4Nc9hTw4VRWdi8MLmJhJ2WPG+bQWCVL5FbflZXmwYVVzZlDdBejIgz8EVzVOF0oMxcuR6F8klUnOnNprsDdAG4Kt7lDuvg82ErkJQuHPhL+0JIbK0RJyUwLWUg7l2PBTvjWiqRoMrdmidHKaFSYCj94Ma0WUeQBh8XBANJi6ijywqdISlI8jvyGbdBODdaYc+2ryRAlr4QcynkNGrUwnuW/VUIeR0SSEjayx6G2mRHGV0qFbiNK1i5/39rcHDCeOmT2q+72vpTL+/crhTschblERlKPV2Ob115CJgDK5bh/1ykOKuZdyqo69GDuaQXI4gCGlwm03ybJ+3HjMf0ApS+ckt18xhxT2yFHRhK5EIa0FaVj2Lz5iAuYycguVa//i2xElNxENzTrbRSv4MEZnP1gUDDH3EWJ7nWyGZ7hZYH17TDn8iLqLKv2CgHL/+qjMw0FgA4EDWtjqbVm7oyr1RS4AB+QW4B90bdQDYMB0JuVv5F5rrMy9ofnXVMm9D1TZBzho9ZAtLBJQjP4dNoI+KIhW1C2gCJeyHFdfem63HNhDR3SuTHNYsenR8tCgjPlt7LAoW0HyPQ4AeFWuCtMhe2smoXKkChUmwltblM897QI4hv06dpBX50IKxi1SUXIkKR72Rnm0KGAg1IA0FhhLc9X5q7k0r66+0CUWBH/v6XHAsAKoYste/XODCslK96Sz2JRxnrwiMs06cfymEWNuEacHN/LDqcVD28IaHnFpeG6MukDwISscOYghHYhUc02AnnBJHFC+bQghJfG9LsdCtXMSdikjFXztjroJCSbo5KWmLmznzDtowfM1aCJnbaHC+LXBUhSy3fd04QSlihr36ONj7srIlUe+m42Z523FOdytOa7uhPVfygCuXohP2cC1eAWdbm+HHXjrGZU83wCuRmVkkgaVZzIwdlQPrYHG29bjYUoa3X3J+yjk0K2jyBchzWEmhpw+UFk9tILJyUHY4FxkVO1aZl4tqgAeoy0zouXh3HAgxjCQyDRli96AhXhpn7YW3oBC6ygRVdtpGxgZvJXZ+XkaM3DAi83bYyCJYkO2XPcnHlqjLkOuiM1HyXJ6tC3xy63JheCXSZM6dQ07ALGT8MCuEANmxcNY19GDcoY8GizLtzIpjdgVcdjajTXsl0Y7bzmXSKL9eRihiEBZh8uzcC0l4HajEKB03LkV0lp3LROA2GHxy60iiFNhfeTUGyIWsMZADjtD8k3WBW+mo1RDv49sC563HO5Me+2XAyYhIzlbm2SoZ7JLB//XsOssEZ3LfOymoTsdRjOuQN882GJyOWj5/PT0D+igkv6bICFofmTlyIAZoRxUPi6mMhawB3pmEPCZS4nKEyZ42R1Wfi1DlNaizpPpB6KikCTaHvBVG3FAtnSyJNjlpLJCbD+WajeR7Vj0LRAvgu0uTo+1vOvICbjorRmQlXje87hHATGSty24oeIkI+MzR4ZjRyPiMhN+ZcBqc3JOQDO5UVrhL6lQ8HDbkdQUclkxvfjDu8d6sx2FJLkEv95Ty1YGsGGSUpmO4rY6pQSLjtAhM7kyDG/CiCGgCr++sSDisILwnFv3qyKlGd2MhU69EwXJY9vjtmyJLu59vyjzO2BOzqZFLOKoDLluHqY9Y9epPYfHJbUUzRhdxbxSwJ/4QOlKFPBM6nrcm4fna4dmGhFctQkJSvhg5FypbPigDTkfM/qGRXMxBeedbh00/8Ez25PqoPN/IGrrtuMfuFb2Mvi3eSI7QUdVj5FK2gXh3QvLuq+bHIxafi8JCcxQA4NPbMrPmLYCDss8M1ZlolmOil7sTmFQ/hDVEBirLMYl2dMBgWKObjxJXVOY2cYRKtRO76RzORYqkpDWd91c24kgO9rEQlgqT8LMHCXdqJsYd14THFgL/v2o8LluX8wJUndFJscBFxc+wjQanY1bJxzU5AHvFILXTbp8EQ+qa1RCsSyrdilnOVUjlbIFsqhRBieCum6I3CYuSxRkNmfgZVfZWygGnJlidwPr0s+dhu1/22CsiZkXK1fhV66V4SnlzagM3iTcNO2vC59xU9kpqrL95VePRuMNNZ6VYDJmMp2mXp2N2K6VLeDRpcyf+qmGY10VrcTrucCIdwUhm7N9bOlRWrzdNm1TffyXeJSTukkD1UJL/gqAqK0FltkHlzTErIpb9ECw08YQU2RGzuLDgAcJrPJCXuyg+LVJgj33MRjv7VY8rQXLenbaoXcRFa7M8tgkWjyYtuyPZ8PaKgE1gEboJFs83ZbaV3kbyHrYS2d0n2qqreZqiPdakbOhENKXA+ZadeFJ1TdQ5Od//vKCMm5LQwW5fZaY3HZEuhcn3q4j9MuaivZdD6KAc5L5Tz/ujttGK5syLgKOqwz98Z5ELHeV3vJH3OZHudm+XswHkLvSoDtgrWXTNiyiIAcRFk59tLodnl4BPbgt4eVaVXa+eN2pRvV/yENGRIrlB/OxJDrJttMI5MTvdPK+jM9x31BBQ98kDQXm0sOYItMj8hrOtx8NxL3tWwEk9kPNa4Vlctiw271Q9KiFRfnpb4k7dYa8IeDzppBAhf6KUZ+2yJffrdEw+kAWLTmZekKSs6+T+OEizw5HCXBQzjJIfCsg+IUeMl/KcqKT3qiPiQrMsiLcOsrFWwoD0XG4t2mhFocKGYeSSoHVJRtaKqvJgbcLgyqucnzt1x1BDRyKyswkHVcqcmdJKUS3vUffag7LDvVGHS0Gk9so+iwpGjoZuFjzEiS6o3JeN2yawgFUL810OhjUcia977i26B2mjqMosRTiWncP3bn1GLErHz72NLDKHc5dFoppNnm1LIbeT4zSTkaxGz+v5wqb/d57ju6/PxSgEsjHPih7vzUjumTjOFZVMlBJQi5Trbt2iixYfPryHv/K1r2I1rjFZN/i93/w2Zp89RwgO+1WP2kaU1mXjJy+HSO14cKmsdCKSmquW1r7q/ldIsXPRupxiqLN39a2/2roccavIx52aleFN59Enpkaq3G43XMiZhFcbDzgDr52YI6FKiUKFFFh8DzGni77eMr59XvAAUJ21uvi92njcqQM6IL8vdcm8EjLSprdozBCIVDux0zWqv2b3VFgGFfWJttceYl8dXTbHqd0gh/My0w8QC1h1YpRiR0mZl1svHT8fcvVCaIKVsREf7MoOLph6mHz7usQ7k16yPGgh/Mm2wtjz93xhGnMBpFHUQcZIziTcHXGzCdHg6ZqH4aIUXX4YECHNPxkLE72LBqtWC1TAmWHoqU53hXQWTbCZNKzGadYMslVnDTrpbnrw832ydPjCjPJjkqfohPjdZYk7VcRVZzHxPBCVpKzEvluZQzfR5iCwkbzneyPOV9VkTuPcv7+idFqLbS1aldGuG4raa59KCN7gNeHywR1h83xd3TavWiuZI+Ie6iKKajAkAlicN1BDt5iLew30W/UOVpJ7N0LKs0iSzcKDjbkOLCS2EUiOZOpXjUfl+NlKG3Pio6pbAPInAK79JuwWi7y2KjvWfaqLDk/XBY7rPqu6Jj4yZdTQjCvC4HzrszwwgoqmXhAwFvhRkEUD6/h5H47pEKnhVZrXo6nG+1WPZedwISTt2iUcOia6BpCTELmlsmCWADy1ap+YiKlH5qJYAMkaHFT085gXRKxKE7EorHAw+Cw8nlBCflgFHNVB9gP+nqvWitzeZoR2JWNeI/voZUs1mQHw8bIUgjQdRZvgUDqupSBj1rGMh7Wz18A3vW+rYOGEuzYv1fdEra5NlrqSoyfPg1e0jBD/deuzC+9F6/G6sTiuo5A6bS5+yZ9z2U0UAGa+zyhnFzmuvzfq8vqdeBF3yn/rSEvR5IuWKOOiJB8E4N/rs9cGg8IMxFVNSlbSsqKvm36IW2iiQZHIQaksM7aUf6gOv0/XBe6PON43vTbsdH1dw6JCQigG6e5CzoTXWzYtm8AsqR/3+lwUFiPf4/fefZ036TY4hGThbcS292jHrLK20cnsNuJv3X+Iv/j1n0Hn+RFWkxH+37/761iULb722XOULqANWgkHzJPBpveoE+dkBuRKbHqPdXCYeFbmEdzobJnQRYUIh+wDNaRxJsLpAu8drDwAMx8xcpzh0s1ukMaSONlnT44AdfILWYnA4ByLZCgTndUdLloSePZLQlXGsGo+lJurpLmjKiAkLz9nML5pImEvDc5RqanKI3spalQWNfMR68BOSgPAAAjJ1KC0NNtRs5kglbIWOLsJj9tgxSSsF1WGRQNkFKUJFmOJUNb8iUXJyO/avc0wX0nnnhIfyJGPWG9p/HUm0i9K2npctAWVMgXZ7d4mmMQO9NXG5XCdkYtYlDyo32zVkImHkF4jbu4xk3cnPqFOyH79GnbUJF5nOpayu1aIWGWVAA/dlCibm3rkTIiRTxiJGdJFS8KczsfnQi7dLwe7+yA1jXpa6Cx/E5hxo8Zkv3Xt8fUFUcC1HJr3RwxUOhmRUNnK9W8CkbWJSImNvN8+0uJ9PCKJtOks2qiBWyGvcR37ANwMT0Z9VgUQjUiZsBh2itxF0WdGOuQavmxYtA8FecxFcp8M7o166dppVz52EcECU8PN9EI6/UKKhBebAncq+g9cdS6jln1CfiZqObwAYCMjBAvyij65dZgXLGq0MVA+00RyT3ROz3XCTv/p2mPs0yDbtEnI2kSPylHMpnUAhP/DEeE62OxOq6igF6SE13zI42C4Xszmb31EJpkCCZfBYjbuUbeqArC5G9VU2JQMXm6kILLpLUjbGORU6ZUonAoruTuyLzkQWfEuwYK8OJVmKhq0EfRSCe+FYaGuY8teHDVrGXXRzttm8zBFrHRPbQNNvYKgLCd1Dwc+n4dmUO3oqKm0bGLoFRIB4eRVNmLi2bg2wYlkH1lhN3YR37zy+GAeMvqtz7qODi2I0I5dzMFl+nsVSdGCNYLjf41M2AZDBBNDQaYFJjlzvA96BjEA0cDKGH3VO0FWEnlv0hTQ8jxkBVaXnPgf9dIAu9y8Fjbhpqdk+nTMe6pNgKqItDn/ca/PR2FRNvi5d38NKTnAMtWv7z2ir+gTHy1SlMOyrQAY/Evv/4O5qNBX7z3+8k99Gf+k/WuIcgikZGFMREoWbecRkxXvednA5OucjQgCTcZo0UUn3w900YlNuBjUCC8AADadR0gWzsTs+Eao0wm8RriZ0kB+71RGDFFQj4Oyxbr3+ObpKf7K176C2/EI880Gv+cbv40vvP4UXTSYlx3a4FDa4YZOhBluDYlVX9lb52pZpYKdNZgAEtcc4G1EaW1OVVSEYCOHlW6WIRK6c3aIgi+R8HDcZ2mUqhzUYbNLTG3UbAEN+1Jr3KvWZ2g5GUn4U5jaBpQ2Zma5drOf3lrcH/PrIvTv+PeXgkJEII9FOItmkXHTOzwYt3jdFGLLnKCurC83LqehPhx3uO0txs7kuTFALktMVD80weLZ2qF23ETpsBgyeqUID+Ra06V04GAAg1PrNhp8cgs8nmr4UsBECGJ6X8+FOPn9VUEnxHyfWNxugttR65CAem8Us/ugK3g/vE34wpQdiRrqvG483p1uM8F31Rfc2KLLJEFnhoyGaRFQlxF153K429hFnG3FXwaDy6AqGYj4DQgOAKyTyQVWhEEjcrxVbxGTzyqZm465PMvOYF4Qwj+s6InCLYvX6XzrcFz3uG5tjgNX6FZHZScjKsaKfCgDEHRGu3x2q072A40Apw30xMihjoQHYxJ7NcFYfSlqSw6XFiDqbqhI3f3RcG/1WvidtZAdXeMwt9ZVo1/fRIPSIstXKykG9B59f11kS3NnqGo5GZGUqHyxOzWJhJraO3YR05KozlHVY+ojvrMsMCtI2I5AJsoDwziZoWoB3195AC5z0wDkYmDmyWlpo80kXmtSdj5VVdWtjI40+KzEICkOiWhS6VJ2mYwyJjM6PpfRaZeo2BhF2mmzIQywjuPuWnhDSkwcO+T7dNNZROgYh3EAs4KN09N1kYP12mDxtQWLWVXlrMQwSi0IghjrKV9DR5Wli1i2FofC/2nTMM5lwB4RlMJQJNBFHZvyep5L2GDtBuFBl92Qka0VxjLyCMmgNqr+4/1b9RYndZd5JRHAhbhZrwWpV+7PnSqKA7CT6IUoo1KShu2wVH/o63NRWBgTcaf/Hv9HTKwSDN7MvpTZ+/vX34MLHVDyoftLT38VrSnQGo9/c++P4s8c/BIA4Die4cuLv44ElnwJBskYAAYxOdwWdxEtP3bV38DHLb8GFinZ/O8+lWjtlO8lAiXWCMkiRSfRzAYhOYTeI8IiJQ9jIkJwCMFlaCtGm0O9+FkTum6g1Kq3xH+w+BL+4ns/jdbx727GY/zlv+en8N53LvHzL57CW16YPjo4E7HqSpRO/8zishnhaLzKaE8fLJyN2AYvXYXBOvBzF76TGaEkc5qIo9qJkoGIyVY2hMLGXGgEea9tYKIhoOY3ATOPoSCRIkyLNSsb0lQ2fqpxyA7fleRZk/Bo0mAdHJLlofh4qjBgwOuGs21vyKfQLvmg7FCYIpPaNAHysCTXYCYEsoXIgw9LYOK5oXsDolWW89nCJDxZFTgo41umVave4qhmt07SEwOPAGAZhkAf9YzQw3OwGeZ1XfbclL88tznlk9kcLhMwFf2ZeDqqbiPtk/cK8iyuZPywX/Z4ti5xd9RjmpMgqdDQr0my4Wq6qKaF3nYu+w+4fLhzM1PNPsl7vJ6tFJpa8ADY4Vaw8BsLgqXruhM+Tp9k7JTYjdHMiBuqytwSKH/WIq60CY8nvcRky7MDFkI6ElQJ912Jv1Z/k1Vvs016YRKeNXymTkcd+sTDrrbc1F+tPO7WPSpRQhnLos3bCGtsPhidSTmr4nTUSWw6CcpaXEaYLB+nk2rKUnYXhzEYn6uQZevKu9KuWpsW5V7wvplc8Ol115TNRlDB2c5MfSIFhgZarSIPjqOqQx3YsZK/Q7KzrpcjGbdpl6rKNB0dQ5DGNlrcqXggzuRg10RcDalTZKENLmd+AEBdD3bvhWFRDLBYG3waIIT7ASGCID6UaCd0MJkIqUqXyiZAEE5nElbC5ZoVHda9y/bnx1WHpi1QWJrprXub7bj1ml22HieCimkIH91puf9VwheLieOquiCn7dOV+OPIPVCzxcMq4KDk+zAG6GWs0QsvpbQQAjSl8/OCz6dJVFDpc6f7nhdUMQgSrJw4Z6RoaH22CB/LiB2AFDO8n0dVR0TXcC9vIgPZ9qsWm97jVBoSbyPGjtd+Xna4aX+8LORzUVhs2xKX2zmsibAmwJqIBItnnz6CtVxs0/FnMKaHNdzYp2kDpA0AYBKb/LPe616g6Dc/8nfd2mMpNIC6u8Io3PzQr2v9GNfTRwAAm3ocXn33d36RAVAAN5N76EYzAEC1usJ48yYXNdgtbKzFzfwRQi822ZtncCkgGYOz8gb/ozcfojMerSnw/xn/LH558nvw777/c/ivTv486nANGCAmFjV98DCWb2KVFuhDBed7uLCFRUBKFjBACA4pWUFqPLpYkXTnAgwSevl7gBtbzAfkTveUTP6avnfoBc0x0lclmIzmdDJ+KtwOKiOfN8IgCPu5dAFNPyy/NnqMPKWEIVqpxh1q36MPLM5Oxxarjl4eleNhWdiIke8wLwtseo/DusG8JQH4b91/gL/81a/hejTCbL3B3/+tD/G7Xj7BpvcY+T5X/aUL8NHicdkSFRLSqzMJpWwOOuPWQkhfShhWPoe1yMVwYZIcJizijKFs66OH9/GXv/oVLMd8X3/gw2/h3e+/RBcdDgsSiPXwezBmjHPtQoY+1XQrJZOZ4BYcAcVk0MJmI7ZpwWt6ti0wEmLzSPgFbRw2oyaabNSmZkc6+uOBR4fIgc3O7AFFKpSQrJuwkSK1luvV7WzMIxdgjEUZU2bkR/ldSjijRJC+A5oQSoJvyMmm19JNVZZKGSXP6uiqMeQszXcMqz6+rXA66ngARhJ7NbdCR5/rYNGJGk1l4A4GUThfXsYjE/FVoQJFDjv5nLtmRqoW6tOQXxGigZMDMP+MNPgKzDAgnDEhrzFmwVgU4vOjBcSiRD5clZ81EZibHAkrkm+XRz+LssPltsS86LGNDEac+IB9GfMwfZU/x5iEJjoGxgnpGz5i3w5Sco4lhtA+Yzhm2q96cSjmgYcoioqexfWdipwMHfE5R76KE/6QMQPnazerSdNjLeg8PHJBdiQehFSBOUH7BpIz0z2dFAQRBjQzHHk2L/dHrRyk7OTHhaBAvUMXHRZy4Jcu4nQ0NEZTG9DB4r1Zm5VlTbSoHXlAXJ8OY090NlYDKlrtFA3KaSBSwNGDZpk4kzCBkut7lDYgpKHp41oc/t/L2Dwlg9IF1C5gr+T76yOR9on3mBRd9jABgEnRZSrBsexf87JBQsLId7jtKvy41+eisFh3Ff53v/2PsMtLBhPf46orUNuISdGRqOkfYtN7zIotnA341aMH+Itf+xqMAzaGH7Loexx/0uKv3/xhGCQ4E+BMQOF6lK4DkPBq/RDbUMOZiKPRCHvVZf46LWqsidisp3jx6l0AQF2sMZq8gkGCMRFWjY5NgkHE8mofq8tDGBOxbxtMXRywTCD/d4ge29UYKRoYm1B2K3hQ1fCL3X/49jWxNX558nvwyi1QuA3m2xe/88IJuoP5FxBMDVf0mF4/R9XdqvX+Wwb4rR/jeqbFUofDq4933p6UCVIE3Yzuo6smSNGiaq4w7s6Ri6SkaBAQ4XFV82cakzDdvISGZGtOX5Q30WCOrZ3zXpkNqv5GihKiRNZFhMBx1SoeICYP6yJKrODQIUaHrveIUe1sDaJxCKZGjAZd7zAuVgjR4q/NP8DfuPcukouYpA26kcX/82e/jvc+e40/ePGdfE26roD3Ab0QBLWg6oN7q2AKUhgoCqMbHjCgTlqY9dEhRCJGSqvqIolff/PkMf7Cl38GreOjt5yM8cs//zP4pdEGP/Pss8zfSYL4GCTUvkfTe/TRYa/aIsjhrYhU5XqsuhIjz7WkoUoskrhI7tQ2c5i66NBLQRWTwanrsexKTHyHJnhRexB6TsngdByxDh69oFSljTksypgh90SLHf6OYcRIFQxRD3JXAibyZwBwuPP1tQsYOxZ8tQtSuIWs+JjZiLXlRvidR4/x137qK7gZjbC32eAPffhb+Irwq3QvaYLDw3GTf957Ux70s6KDC7xPpeMB30byuuZFh9uuQO2EPC0dXmljRuy0U6xtROmCbNIJq96jsBGV/JkiVbe9Qy3FVhssRj5k0ri+6mQyj0d/F0cPFjY4+MQiZy5jrtopEukw8+So7ElxfNMVOKwavkcXMCsAbyNWvcfcBVy0TPWdFxwxPRw3aAIVBgvTY1p0eLEe4bDsMl9tXtDAbF4ynGzVe8yLDr967xH+0le+JvdhjT/8W7wP2Z/F8XO2cTjkSxcwD044X1q0x/x12uDYnZ/hXUQfLLZRQ9CGa1dYmrR10aFyvfwej71k8JsPTvHnvvgzuKzH2G/W+KMf/W28/+wZJerVFod1SYWLiziuPca+g5Of14QCtevQRSLBNDkLGU3Sfc6ih7MBI9/Cyuewho2AMQbrfiIj0wbz+gqCpYshJM0hvQ04b+7Cydho6t+gdpt87hjwubMmoAkTXHcnsDaisC1O6u9KMR/Bt5XkfSS83j7GJs5R+B77xXPsuVdA4u+HEbzeRPSpwJP2Z3k9iw6P7K/DoZNz7m2y5iUeAL+OH/n6XBQWIdGt8XzrMPIJM+9y93PV+fzApmSwCQ7LzuN0fY2vt0/xH339S1iOR5iu1viFb/w2Zs83+Kvxy7mrVIdLxp1bUYcA06LDd6/3AWhHRsWDMwkz32c4H+Dm+Jv2MVIC1rLxTmXzKWzEtGjRBMqvCvsYhe1RuY431kSUrkfXGziX0PQzjjNsxPFoDm871L7F//4Lv4Bt4VGmHkXq8I3qiwCAg+0tnnz2GJvavVXMUArVw5qIF88eoI88XB+Mt5h6y8ViQ15AxiQ02ymuNodIyaIqVjiAdJa8Cvy3GBt0TYk2jBCDRRUvUcTtD7938EA0MC7C2IRRvIJL/Q/9WltFYMwlV3ZL7LXPfvCH8WWA84P3EG0B6+JQLDm8nRQEoPUTXE3ekcNwizvXRJY+6H4F/9STf+Otr/2vnfz38G89/H34pdl/gHHzBuPN+e4nH4ol43E5e49ITTTYX38Cm3op1gSJSgYwwNrtY+2O+JnSLabdq4xU6Yfhc25w5R7if/DgH0brPP7L138OX9l+wtmusRgdt/gj47+NGC16W2GZ7vKaocfCPM/Fl67XJOS+ZX+I3tToe4+xu0Ztl4DZRZkMjImIyWGFw/znE3MBAxZJzgUEWdcwCW0aoY0Tvv3YY1LcIEQn38uCJsrPWfULwADWRtR2BQhapr/HGGoU+lig6SfsRm2H0jToe48QLYqiRwwWfXDC2K9gLIs5ZzoUtpPPYHNB8yuLd/Ebjx7hphwDAK7HY/xHP/MYX1l8hp+7+FRSN+1wb2EA4zInofIN+uBhTYRzATFahOhgkJCMQxsI9Ra2RYxGCqjIYq73UjB4WMtnLcihERTNM0ksqsXEr6thrY50ehS2kwNK+E5STCYYbPpJ/hmVXcOYhF/bf4g/d+9nsCxHWLQr/OKzb+Lnrp4jpBJt8Bj5DUq7gXdB1FM2H1gpGaz7OZSKOfJLOPQoixYhyDWSc6OLJdo0hbUR7zYl7o6f5z1CVVTOsvm6aQ/xlw5+Cv+Pd38W7/VP8dXl92AQUb7f4/397+BL65cAEhIsrsK9XIAv3HN408uhJoHehijQMuxj2d0BANRuiYPiOazhvmcNGzZ+JuB19x4iClgbceCeYGRvMRyo/JrLYozL+e/F5ej38XkqOvzjB/8O7k0vMY+bnaef++QZvoAGezAmYZ6eY2FeyBOc3vrakAo88z+T95YH4Tfg8MP3vRt/gqW7x/sZrnHYffJDvw4AXo2+jGgLXqfN91GH5Q/9uq2f4bLuYGyC6XscrZ/+yJ9pFgW66hrWRdS35xhvrn/o1znb4vDea36PSXCXPWwaOH1DA2rgq/ZH/j7gc1NYkPU7L6OQVygbum59dhMDgBebAu9Ot7kS/sL3X+DRpy/zzHVaBFwJv0HnbtpJtYakKs1ZWPYWBsJgtuw2NUK8Fea5surVurmwEdedJzlMZkwWwMtNnXXlADIZSzu4Unw1dvX3tYt4tpqiDQ61C3iT7uIv/q6feYuQWvQ9fu83P8Kvv3wfbfyAMLjTDJQIb6lqYXeyhTMRv5nuC7xKCdo6eBRGGd6s4iF//zfxNfTJoDAB43ILJHECtQHbUMKZ/y91fxpjW5alh2HfHs5wp4gbES/iTZmvcqjKquqq6oE9cLLVbTUpmKBk0bbEJgHbEiiwDXiGbUCUYBgwCBr6YcMDBP+QDVuCCdC0YciSTZmGLYCUTDUpsZvFri52TVmV+TLfFPHixY24ce89097bP7619rmvOjPLaFJC6gKFrBcvXsS95+yz91rf+gbdiN7EvNwQqTEJKfHhLX2PIXi82N7HpGC3fFrP4O2Ayne5oDEmwpmA69UJbodjVuPVFdrCyzKNRIJMRIwG3gW8ePIATT9FVXY4K1tMLTfzFHmI6cPedAus20N0XYnKb7EsSiAlrPwMNkV4BLgU4BDRG48XdolmPUOVVrkKz9W4FuXJIOzrvVPLYun1oh1IQOvm7BJchAsd6vjJGwEAbCd3cO4OAQC/vPlN/PHtf/h7v8mwWIrTKYyNsKnH4epZ/rvX/gugOOrR13OkaFgsbS8/8XdH4/DqiIeMdRHLyx++XgDu7QSb6g5uq7vcCIcbHG4+/tTPdHn4LgIqGBtxcPsxC8BPeLV+juuZoGWxx5319z/x+wBgNXkTbUFka9aeY95e/J7v+Qb+Jv7Uk/8bfvHtv5y/9m89+e/jnnlFCOTHXpv6BGt/HwBQDWscNR9+6u8/n34Z0fL5Pmo+QDV88mdq3AJX9Vv5M93dfedTf+ar8gtoiwMYkzDrzrHozj/x+4LxuJh9JSM/Z5vfhcOAPwDgz7/Y+0YPfPONb+BN9bXo1zjaPf7U338xfw8BJYxNWG4//PTPZBdYTb8AYxPQh8/8TFeTR/ird/8cWlfgn1j9Bv57V3/l9W+YjJ+pXo4Pz/HqB5/afEyrDeZ1lz/T8jMOzHi84CFsIw5uL1D1m9/zPfN4hS93H+Q/W0T8dCtj7U8gIM4X1yg8961q08C1n/w+jY2YHa4Rg4OxEena5jH1fjGbDGB8gvNaBCT0YYIkxFNyAaVkSRbJjOhnaxeI8FIQmr3SxmAwNYJw9dJQ4Mq+QWmrcAu1uYjJotkt0G8mlG6nKVbpLqIgssYBYeD/D9EjvKilGQBW6RhDcPDFgGEo0A8FYhQO4uAA/D8/9d58LgoLsuU5L2TKacwOkaXondREJdsGRw4krjuLzo+yH9oxkzG+r2nW3wNI8Fg0mbHfiQlLkBGFmpfw31j0KcEEYOrEjdCOzqAJZE6XFLSgiergNlZ6mnPQ7RU6YXAZ9uyTwXsfPcNmcPjNn/kyNtMa002DP/I738FXnj7Fk77OP6swXljXQchZFk93Pht/AVRfHBYhW0brHL12I9QPiBeBRBSb3fw1gqkWRZzbyfhCOlWFtAsbM5x9UPTok8Hvxjtoo8XMj3PViR/y9yr02YV7COmn0EebIdVF0WEtpNQmuAy3evsOZ+5lR18KG/PD513ErvdZ7vUfxK9j4nv8xX/sn8JqOvs9a+1ot8Fv/+BLcOZtDNES1i5bWBBGnXipxE2RO/MfmofwZoC1Iwu/dD28C+jCBG2cyr1pMfUPYE2EdyxERhgx4eriPk6Wa7ysDvCXD/8k/ubsF2BShEPEwbDDn33xGwiDw2BKXF8SsTApYqgJaeZCDUk2DuD6/B4GO0GMFlNT4bAoc8em3VtKHBldvbgDK7BzYVawGKAxaoRa+W9ut0vcbg84mkJCCfKHflyzYJCwuT5AcsJ1CFOQSfPjFRjQhwnaDU+aNFToUeVR0t6P5Pd2FULiphlCgQFF/t1Jfu9Ld4BX7uC133HlDuBTwFG8lXeb8n9j9Hl9x+DyeO7TXnHwGen5pO/NY8MoyJDtEeD2rpJ+IPmdySMFB+MHJFgEI1uvPo9K2IRHCqPIM5gSz9wxBuPywaKHy787/Rn82e3vEEVKJXpTjz8rKVLGPw9dCRQGsfPo0hTYv/aKxCWgwxShZ8dskkFjx2u8j5QlAP1Q44VbAgD+QfUO/q+Lfxw6KE4w+Cc3xMojHNrbab7+t+ZUGCtGCPP6+w3adoGmXfDZRolB0C/r0jhalVHkZnWEJPemg4NFn3+OXqN/6c1fw0t/lD/DlTvAn3rjf46YDP5XP/zL8vOc8NcM0Hl0fcWxaLyLGL8KJJ4LQyA60nacwUxu28xRexzegvcDQuC4NsHk5xUg6V7Rtpi+8Zoa0ZmIkCzannuOMcp9e29cB6Jm5H2QMzOO46KQviLImX1NuZgSR2A6xuyjQ2GDNN8x8ygA5pvQVt9h6gIOyjb//aqrcFLvcNlMyH/bO0c+6fUT002NMf97AP8kgPOU0tfla8cA/iqAtwB8AOBPp5Su5O/+JQD/Aghs/3dSSv+vz/wFAO6XZ+nX7/9aJiiVkkY6JhqOkelKSmLEM8cXerEB+r5v9rrNkEzONjCGJi0Tp6Q6yRCJDAG76Q0OiiSZAybLKTW7oNh7GNs4wrJ9pN+A5oJosmpIJpsRHRQxx9oqWsL/r5bdZN8qUY3XEqK5N3hv0eHxpsCdOuC88eIkmTIjmLInVteaYbCfz7ETu+TaUeKlZCElnOm1BZBZxE0gwqOpgGqcBPD4KGV+rqZXjZCM1NtCbaS9kNlqcbMzIPN+EGLgqicj/E7d4lY2tf1006mjTnvqmLXyvKmycc7MD3i6q8QzJGRXy++8+QB/4xe+gWEPAfLDgF/5u9/CN548EZg5yqyZzGyVOxLWZhGhGRde+Be63gBk1YwSrZQkpdbDTv4O0OwV4LfuP8L//Wd+7vcgU/+lb/1dfOWjZ3Dye5Qf0ESL+5NdntfnICfhOejm0suG4oXXQfMlj2XZ4rKZICSD+7NbrNoahY0oLKXHXXB5jk1yrcGqq3BakwCtCFdMBlPfZy5EIfK/kVSmioSAwnIm34XxM+ooQaF/rwWOkLO74OFU5hssvIt587XCawjSTBxWO/wP/+CfxmU9/z17yfHuFv+zv/N/QUgsGr2NmJYtNm2Fadlh15fiu6HmWA4T3+c/A0BddEjJoJPxZoRB6QaEaHHbVZiXbT4w1m0Na0hoi3h9sy0dybQ6lhmig5fPO34uL/ctCJnYZW6OFoH//H/2z41d0f4rJfzv/ua/gduuwsT3KEQ5putEDyPl0xSOI95BlGPk4Xgc1Ds0ffHar6h8j0HGX3qgqeKstNxnEgz+R3/0T+Fq8nvvw9HuFv+Tf//fxqTosZNnWq8DwAO1k9FXXgdI+UAmIdGiGTxSAuZll8nWyh1yNsnYx+T1WNpBum+LJnj8T3/5T35ig7HcbfAv/42/hk1foIsWJ1UD7yKuWxa8u8HjpGqw6iohbwdsBo9K+DObgc/WTVdlRc+rrsDC06jtUIjUU8//6vfULmAra1mfO2fI3Wrk63x22Vi10qgqKVo9SwAg7n0e5fgAr0vyjRkbSi9NpCLrcx+wHZxYEcRsja5eTurd0wRm2ByVA3aSYH3VefwrH//DpZv+6wD+VQD7A+u/AODfTSn9K8aYvyB//heNMT8F4M8A+BqABwD+P8aY91JKAZ/xSqA2urdGrH5NHj/c9DYfTAzAMqiTyRKkwmqKJU1Pnu3KfBCq5XCEWCjbEaTqo5GRPnXyhQUmDtlWWA/bbGccTdaOAyPLWxnB37spcFoncYyLoo+mu9pJFfGydbhTMXxLRzVqTrMbLFCEjB7MPEOwYiKq4g0P+KOK7opMP3U4KfkJ1Jn0slVzLEltLRKaMKI9GoqVMMYZa7T3vmyrk3uwET117caiQvXlTPqkEU+zZ2yk7pohGAlYM9gKux7y+9QjQIPLSnnPbXCCstCSGY7W0qUdNf99x8Coa8lB6SONpBZ+RJ/6ZPDmB8/xx0zCv//1r2Zn1j/yre/gncfPEKzBdnAi57LorMYNUxa2kAAiZanTmMjiuqck1Mu12I9nPyn7jJo1kQeurk+LMc749P0L/HL/rcwNOtjt8Cv/4Nt45+MXuJG5vhaDTWBxdtkustaff29EhsdXBLIR176U97L1OKkqiT3nBvWdmwn1/o7us8phontnyN932dIZ8VrySw6KASlNsiWwXpcx3tq+poLQ9VDsFbDqfKtSQGtSXvMh0VzM7n3PZnCYSNJtJ4oN8psm+MPf+i7++s/9zO8pHH/pt7+Hv395itpyXU6FoKotgSo/9Gf6XByzGFJ1z1HVoQ1qzDeSdddiLKSETZVlq1GW/ndfDbSP8O0TXdeDFwSO1yEBkoUR5NqRF3aw3eFmNv09++Ziu8P3ro7RBIeJC/n7E1h46kGzCw7bwYnUuM/ftws09LpTT/CyqVC6iKn47ixLyg1rF7Dqyuy3oWNYLbD/6O988n34A9/8Ph7fLqChXdlvBsjXQa+rvvYNx3op0nUdzdo6ey3oGldMSg/uQZBSBmgxD+dn//738f/9xa+/9v7cMOCPfOs7eLKd4lKs+5Vke9EWOK16vOoKXPcemkXVNZXsoaN6IyWD1Z7s8krsyguT8HTH5me/yWXTUnL/6jyOygHWIFvYj2uH9yU4Gtdx3YtqKLlMCHcGObRv5gMGKY41wIxFJc/AXbAwoAz7VWtwt+Zztxts3qca4RIVgHhhuOx4XJiE3UDL+iPJ2/qs108sLFJK/54x5q0f+/I/DeBX5P//GwD+BoB/Ub7+f0optQB+ZIz5AYBfAvAbn/U7DLCn+bW5u+UYAzkQygtq0EeDJnGRFSahweh2FxN9zuEhhCP5oDK2mEpS5lqCd3JVZ2PObdDQnMKy0Bgi4C1ygaKeDFPpKDbBQo1i1ON9Gyh1WxR6qMac/LgZDKaOP/O4HHDVcrE1iXkDJ+WAmGj1e1hGZj1I4l+fGBSlLofzIuCys7R77hh3a0Fnv1ke18QcAT/wrcA52i3baAC1nt27J+o+qJKuqcgP26DZJiYXXTGZbNykx5364AMYA5XEIlqDjGoHeNX6G+BFU6J2USyV+W+ve/pPwNKzwAnqY+XeqflLnwwQGButeST+d1/iv/z+34QxkLwR6vWnnrr10o5dqkrLohQw+vuHBCCZ7J+hp7kx48hoNxhsrMte/caMaFNhNSgLGc159/EzvPXhc6yl4KpsxLVl56qFCiI3jnkRcN15dAlinx7oj5ESohk9DWABmyASPiI8T3a0/z5vPKYu4bqnPfmr1uFQ/OpfNg6HZczjwpBUS0/O0lhMciPdiURwCwmpEsdGQLJupMNXl8lB4lm1EFLjM5UnqixWsw66aLAVOakiaOcDOU8nEuy2GTwe/ugFfjV+C3/r61/B7bTGYrvDH/rWd/H24+fYJIcdeB/W/ejv0QWb5avJychTbIpDMvjeusT9ScjBX0HWeBcZkGfAdNb14NCLSVgXDdaCbu4XGDqaTPnzOnirMDXvrfpzFCnlYlLzPwZB6qwBfuG3v4t/7xe/8XsPx9/5bk6sHJJDZW2Wp27BtaL5Gbe9wcQnrPrRiKwXiedm8LjsHI5K4GVT4LAccL6rqRApTEYftQDUxq2yCe98+Bz/uWDxG9/4Mm6nE0w3jFZ4+/FzNNbmBGXtoiOAjViH62G6EQ+W/fGxOnFqsJ3y8IjyWFTOZvRUTd3C3kHfRjqyfvHxMzgk/O2f/go20xpzWSdffvIsxxEARGOe7EpMxHSMYW5SRNqI5zsGw+2C+nWw+dB3vJM9q48Gtef3pURERo0HdR0dlWOIGIBsM3/Tu8zVcwbQoDVFuhF4PXTYqPtvE4B5AXiI/b0fR7YRXL/a2PQRqJzu6/JcmhElB3ieWUOzLHWEptQ55vwX3R8/7fX75VjcTSk9A4CU0jNjzJl8/SGAv733fR/L1z7zpeEyWgWpwVEfU4ZfAOTKTF9NMCgLbkxOfsayDEjguEM764Sxc9LuWNGM2jJYSDd5HRdwjq6FDTvEnQQnqY+AohcmAKd1yjdqMzisB4NlEaGBW8AYD652rXroGMOkQYAPyU3PBenF9bKXQqaXzbVPBjMxrqlswkExBj2pmQ+gLG569+uYmN0i8uyolM1M33sTRq6GtwmlbPhNJLKjCx1AjtJmAiEPRUWe1GNfHSO3AunZCBhLjbyiJlq8aBE5kUhpYLQKbqRavj/pse5d3lSc4TXqokEPI5U1D79a0msrSwQnpHHqbg2kk2TB2YTR7VPfcwI3jF7GMGp41QWDW9GlV1JwrcQOOQIozXg/mmCywx815uMBrvkuITF9tZauAQDWcYxrvjvpiFTJAd9JBDy9NegLshsslLrWBSv2vuO6byMP84MiCG+An19HfvrZvU3Y9mMQWCGZPbRMkbhspxs5sqEQwM1vSJJxYSEbm8yBU0KTRrTOWZnhR7EKl3+7laJ+IyM4ZxJ2g8F1b1Bbm62eK5vwUx8/wTsfPqNqLNDYB4IiNdHirBqwizYnTSoviamhPFS0WyXfiA3GQaEdLBEoQvjAvEjZWAuyhraBa1jt6a3hddLvUVQzJSAGvLYuAAk6ExRMpbtNtHIdeK3e+vA5rAH+thzei+0OP/PN7+P0wxdYRSZqbiUnQw/+v/fK4A8c25xcrK6NmhuhiBNA6/JGDLh0nTzZOrw1p19DL52vuqSqgVNM/Jxf/fgp3vjgefaZOKsGOMkNYRPDgquwbHgYymbQpfGZ07WkxZlmsGhapxZohUnoALTBIlgW5WMyaZT7kSSwjSPtdx8/wxc+fJ4RlyZaXCfuJ3R0TbnhW/gRHRuEz3XT+9yMhAgEY/J11Ouro22KQpED0GZSxD3fFWLYJggzxqZA7eF1395IYFkli6iPBr2cQU7+PETakTtD8ywddzQh5ecmiNpHixm6/MbXhA1ce0BKSYq40bSwKBLCwKaothyNX0nsgRbFn/b6R03e/KTf9omljTHm1wH8OgAs7AIxmRwd3EWDqSc0yA1mhNEUDqNlrs2+9Tp6mHka4uhhyYMA2UYWoDNZL12D5icMERiMQbIQCNpgaUarapuQiwrdHNaSoqhf14TKHJseOdaIyeCysTipImY2jQiBFD614+bJBQZstUqVavqjjcNXDjvc9gW8IXpRl1HGQRKdnAyuO2BIHg8nAxYFXSVvghENOm2LZ55dFjMekK/js8bgpOLhpijPENmpVzJvA0aHSWdSjo0eE+9S3thq4V10kQfNoIerUV+AmA/RJgDeWvn7sVKvpDPo5B7rnFGhvkKg9M3gESMfbG+ZmdAGi+MyjIqfwACipYwTCpPwbOfoqW+AAXiNH6Kfw5nRLEz5NgAzSXoY+Xu9/wCkYHWCboSg3YeuNWYxHFdBChNuNhGKnNEW+1oi5ttocG9C2L2XJifIgRwFNdgEh9JxJGgMsivqQZEyv2cXxk1KY6dDAk6qIAc5x1bU5LNobOOYM5M7cjkAajER6+KYzqlrJlmgQBrt2wEEjOMhRbmUA8SRINfHsmQnux4sdgMPoJknCrLqieYU0pX3kfkRy5J5NqVjLsw2GFTSgM0l6XUzENpdFiG/Zy3Yh0j2PnMdGE+/6nyWNdLy2aCynJ9rgdIEdsU6hkvggUgHWyAaIkgGOhIbbc6j4eFg5HtbuQ7LItB+eu8eAcA7Hz7Dgx++QEgGh+WA644kbsa0j/uqOpfOvUUXx65Yc1b0e1cdEeD9po7N0lgUpQQ0iQFjznCMqQX4ZrCIblTA6VsIkSMBddmdyoE3jjBoO16Kko+eHtyvm2AAQYFUoVcYNns3vSbVsqDW3zcIisbnQnmo/FlndY+rzrNJgxyWLuKmpctsYblep2JIdybBauojAxAl2QpXbOZHNFUt4J0gcRPZq0v5twsfMoKJPQRPvw8QVFtG+aU897RHSGBSsJO9ZA+ZjSY/w14KgBDHmHv1sDFmbPhuegakOZtyoZNk36a9ecyjE7837idSNTaaEQbrwVC9ic9+/X4LixfGmPuCVtwHoNqpjwG8ufd9bwB4+kk/IKX0rwH41wDgQXWWdBakVVVteZEvWp/d5XQT10NZg3j0pQ+7Qu2FFYKdJ6ReWB52bbR5A4+QeagdN0d9KR9BI93HOHdumkMkDH4gh5NawVokHBRjF8iDdoQ/nUDGQzKYKGEtGcyddNvy+7S7Vd4HwEJrSDw8NCr9VeewLCPOJuysNMRmyAcjPd+VuEOrZQiqw0WvV7F2UWaf7NoKy8hqnUXDIx+4UTplY1RCm1BIHald2la65ImJGZnQz1tL4RCSy1UygFz4eBNkw+PGXFkWHKVlCJZzHFNtBpJuvYxUmE3AjXQmxaG3I1TdR5MDepxAgQBkoxYERwqg0iYkK+/XRQxGu4yRNBwxjkmcdEtJuobCAi6NnBzdtDMHw0AilnlI65a5KGitbIAM7+qYRLlC2i2xA6S7YkbpEjLMa2VEpygPu52UN8y8XjKaYvIGuBNL8U42dSJM3HwKm/LmqJ8vAjDJZL2JQrD6eZW8qzbvKbGYomupkkiliHfYQ0MSbgeu3QbmNVb6rSB8OwkBA4TnIaOlwiZUskmiGNckuy6DJ1vmxiSowotjty6wG3TWoDTjM69ZHX3SYCuglDEdwEOAKBfX0kwSTtXeW8nB1owcAg0Y08OkkGuxkTGQkwapdmPoXCHPj6Ivo/28wZcOwmtFpK5VcnfUwk5HmizENL03JuDhlCM3HTHoYTN1I0eklT0pyTOle22fDK46h9omiEg9p3JqbMBOMkJ0JKBk+l6e/ToftETgKLUfgwC1Q9eRiZMRCbkGbEBueyZbJynedA/V0UktP3/Ve3TB5HvTylpV3w4rhcRZPUizO8aGT1zMnXOQ5lh/R20jdiAKeLcepGhJ+X6u5dBWtKiyCd5Kkq5VF1VkHp6egZAGTe9jSAZBxqRG/uyQcuFZyBjfpLGg1j1unyuxC6Prp65zb7gHdIb376AQxP0ncCzsZ/7tp7/+bQD/nPz/fw7Av7X39T9jjKmMMW8D+BKATxDrv/4yoBe+yj8LgQWtIcytQS3AXrKdQFfkNUTpNOJr+QMAu8DS7ecf8OuExYTkKF/Xh612CXM/Vu5aUOhNVLmVywtBvd5HNMOZhIkbg8umokTpBM3QTQryM3eB14DvmVW5Vs3HZZJDJWZr6V46yY3AmCEB9+oBb8z6jJjouEcfJO1K9m+6jgfu1vw+lSjpdagzdGvzwUtYn9dOIfOpoDC5I5PPqCqNam8havKqHg6KfCiCoyx0YCQtUREyWh87KTg060LREnbUNm9SWqwsZT4f5HAvbcKJxLQbIN8XStUg93B8vwA/p65RK5t/KRwR7c41QGmQh7cLNn+GBG4UiyIKymMy5K7vQ18LTwLw1Cfc9k4k0SZD6FY+n3YUt73LRWMTjNhIp8w30XAhHcNpQa0kvKnn/HTMqeBnUbh1O/BgU9KlojuKPuk91bUV0lhAG4yzXECSRC2LUSOdMDCO3HZCSCstn5+tfJ5lGTMnaitIwEQK4SYQ4eGewVlyEvQzJjW4Qi5a9FknCZkjr3HNmZw4CWjSZsxomiKo/P0c+0Qpmku5XnqYsxHR/7JrV7lgYfhn5eIop6zdey/Ka1r3RtQpMRdbutdshnHfaKPynUz+2bV0qQDXPVUAKT+TCSOBEPIs6HsZpEBSVLaS53CfI5DvtzwPRGlH/kQTTE4KVX8gNSOsZC8xkEYlWKLJduTd6Bilznvr+Hu9jOd0lKTjwpkgBlzrRkijSUZiMfMetBnVIhQg4qJrQ9eLBouV8r6U/FzZ19WCXQBueiIVtPMezytFwLowkt21CRgiC9Jhr1DSUL+8liydV/UsHJUm/Pw6htTR3v7vAXgvW7kPWuxrIZW5izJW0qTeykXhcowNj54Zn/X6iYWFMeavgOTLLxtjPjbG/AsA/hUAf9wY830Af1z+jJTStwH8nwH8AwB/HcB/8ycpQvZfbRg7Lh5IJneYengqRB2iIfQM3vgmmAw5AoJ6uDEtc+bZUT1vfJapNoEwlx5wGiS0P2tXmFqLiiHudRkYYUidh+oooQnsShQ21ZdyGjYDJaKZ6+FGhENf+yoWrWpnUiEPkeFBTQBOawZPDXLQdvH1a8GOGjkcyQjaoIeUxm9/EtM3QkdDNj8E+nLSMZUyYwzS/eh7VvOxXeDMXn+OQtH75MsgG5F20YMUCIM8IMqN4bWQLAzDECSN9yaEajOapeiFbjbA6xyU0vG9jR0XBH0x8tBB0lJtzsNo9taLrgNn9lwL5NoqAtHsrX6D8WCyYIegZNadwNSV1bETD0j1AtEiRNG4Po4QJZGDUa2jCE8QxGg8DPl3VjYRfemzM7LNmf560ztUcuAVFnCWa1JZ+JqnopwUPXCVV6KhY/q59BroobWT8VmUA2AjXZmuZRZ6436ggW16GCT5WRpvrzI55dcYAyFmIsPxChnz+eN+c1QJt8hokajPA3Jhtv/SfchKkagjPh15kdyXMgqhB+Mgm7iuR2PYKGkxokVqL8+KHjA6nuhJIUFtX0ettPkahE8S4p4qRYvlNBb0ugdpZLyR/SHKM5QJx3IfKhdzkmsr61+fbSufuY/IzwzzPMYANivvWRsGL8WpFtya+qv3ownk2rSBEL6OkIRRlNfbZhgLlIRxj9SGTfNh+jgengA/c5/GPeGgCFiIhQHXBj9rl5/vlAm+/P6xuNM1rtyn/UZz1Vkplg3WPVNd95G2medz6eUULswoD9UmsAnqm8M9ThVNtR1RrdqOxFfl7nG0OjZ5G0EedZ9KUghak/b4aimjbYMUlTqS1xBBjm5+Mh7x/48q5M9+yl/96qd8/18C8Jd+4m/e/zeAbAQJzvAmKDSrHV3lIm56K10j/92dKmWYaEQKuHAOFKoEcqVMSI3FgBIxCzlItMJWRm4SOWvCOM9P4Pe0Il3VQ3bVkdBSC3lHIf8hGXjIyCWNECgsMux9LZ3mwqc889TN6WVjcVDy6xrRe1wGbAYzklPlvQWwytTuF0DeIAmLEyLcBYsYkeFNSu24qPTzqKKhCYDFKJsEhIwnCxVgcqeiL6VLWRXA32/yotVXSEZ+//g5uyhIhwWe7xzenPLBrZ0GWI2FnRYkUR7o2vEBPq1DJuCqWgh7PA6tyBW+7oKVOfAIkSoaoZswC1agBBUsamak369jGhZkY+HbStelhdpaRhYKZdZ2ZLFD1ueqIzP+TjXIPYQUVzIuEHO2ykY86z2OS0LVu8HipuPmlFNHpZunHI33Rtc2nxcjEdojGz+CRd+qt7hTBewGoHFAlaPkR8spvY8JYyejG60qP/TAySoRjFwNXUcW/PtdYDqnHhjciEfl1LIcpZNawHqBvtfyDDdCaL0dbB4DWezxYECvmI+2BZbiVtlJw5Fk7+n37q+zSfgnfJa7aGlZ76PItxOuWksSo1HJI+flWkho8fE6ijN+z8InwFAJR4TFiPKN36+8DC8H96JIuXNuAzDz/Nkzn7JEfBsYemVkPRey3hUhG6LDxGshRi7bZeswF2SsUkTEKjLJl35deR8cI0vxKntBL8+2oiJ+b++dSfBdwQqWPi2yZrwdFVRanPWyR1R25IA4AFttHHS9GZXIs2GpItd8G5l+u4/KFDYhDXKuQPgwBT/3QUHF3VyfIWlyOZYeEcnL1knTylCyiajYmgDcDgaLImHhWZyUTmPfIwrh7ilapmdaKZ+9g8nXU/d0CDFcJdBagGmzoV9T/mEXSSpX6gD3VpORNkCue+C+qcqRWjhClQVWvcFBIY1oGptdLVx2g8U2MP/ks16/31HIP9JXSio/TNJVICcOavW3L92iNTfnpPo1NaDSfHqFfGoXc3diTMqbSogjAbGQDkd/v85/NwN/DzBuoCqR0hulqEjSLgbcLA/KKFX0fpARfzePIR5aOyGKli7m6toaHozG8MBxJuGgiJk4xyRFHtwLnzLzvJFxkl6D687jsuXMb14ELIqAPvIBUMMrYIR6AeQHSD0JlLFc2iiEufEw7CNRhZ10MQyYGguJLpr87/fHU6pM0W53lFchjze0Cxwii6irzufDSx8YPSgTJEU1kqikRU9pZUYdKD3cj9/Wyp/dG6vyjFTZkcBUOq7Nq87lbo5FCvLP0usDUDFy3XPtlDZhLl4iW+mCUnqdEBrimPy5HQQRSyYfzjoy8nYcU3DdsYjbBiMbWszeGl2EELuEZCf3WLtBZ9VXgj9fCyodxXmTcFhyw9eNTLkc2q1oJ66R0JF1YYblJ24cPYYkc9o4oipOxiwbSZnUznzVWem4+fs1dn4f5UgJmPhx7eh9q50WpHuka+hcXwjDgiCVduQKKAFaZ/ldNLkL7OX6tFIIKj+pE/g8pj2OjuxLOkMvLImKxux9ZvlZ695mREbl27ofAOM4WBGNmIi+bAaL657jjkHe03XPpuOmd9gN5Mdo0VcJQTYmk7lbXRi9MwyAG7rxYz0IKTcRMdDOV4vllPj5lESt1/GmH5u0fXRHGwEd26ryQz97LwjOdTdKj2c+CMrLe68qwMwJAQsZInQ8XHeBe3stnDlFDAH+DkXLFLlowihV3QwW60FN51QdlGQNc43sZHTDIph7DGMkTL5PwPi8lC7iuieBs406MqOoYB+91pFNJWMZPYzJnRjXMVVO3N9ve4eNFN8A195N73DZsUHdDmLOZ0bliQWLhn01k917H5B7UzqxYuht5tdt9/ZSbVQU8fus1+ejsIDBdhjnkaf1OA+ubMyVWu246X+8segi8LzxuGi9EPqidBYiOQw8UNpocdMLhOjG4kTJlAnIPg0LH9i9Jc51b3oe4mSp88E3ZuRSqOKDBC8iJ6VLKB0Xkmq9FR5W4miIfMijdFaHomK56hxuB5Njjx9MBvSRm8xxOWDuuZFOHERTzWpY2cZaqV62I2rRBHYmt70TTT9hyUoOZI3i1UMrAXnOp0WBso8VHrQgf6SSans7GOkwCKEVhoeedly1EAWToA9agBHWd7nLDQk4rfi+F0XEq5bdlcL6dArUOSLfb4gG9ydk9i/LiDbo6MzisnUy32dXosVX7SKWBSOlS0vpqxqqAaNGf1+C2go8CxA6ncpaUmKtbt5b6UrmfiSjHhTkSjiDvDErhKmfY1kELIokcc7S2UinNnEpz4Q3g8NBwc58/54VeRzBta5s9lUn82kXyTOyCuVaHJUDnIEcSBxl3J8MtIwvIqZ+3zl0VCgosRUYCcsKI2vxRsdYjlNWHZUa5MerMyT/LUdZIzeJEDtwtw44lbjty85Typy4ziJMLohGDo5ESnvKE9eDy1HV5C9QWbAoeC1bIVvqOFIPYQDYyUFz0XopVF0uiq46h0KKVG1murDvwovMNdLmQMcIquYhIXpEAJ2MDJxlw7MNI89I4fu5Hw/twyJlsnKfgJ2QOvvIgqvfO3SebB2ue5vdfRmBTtRMUafTmoejSi0nMlqyGAvgVa9S1PGAjlIU1W7k2igXZSYS0cLw+fJmHOtWMi7QyAUnIz/6mIycn9qmPLK+7jwuO//aCLBPeq24luYyHl0UEUdlQO1iJonq+M4ajl9pvsbG9aQK8jmUKM41SlRwREf4nPL6XvcuExsLm3BURdypIpZleI0rxTVmM5Ks5Fgva1JHfAfF6FAck/pTjAWEKubaSGuELow5ViEB6573ch/dC3Ec7xpB9TaDEZ8kRUKJ6rbR4lXrMPOjAKK0JEwbcKSqHKYTUbR91utzUVgAXNxkoJOZuh4Mnu9GeaRurK9ah4t2wEGRsO6VTDZq8pswMoU/3BhcthZHZcoVulZcfu+wGtJIJGzjOKNblgknVUS7hxBop63z5JGPMULp2nVrh60Pw1q+NvMR8yLgwTRgJmSowqbXuA6bgQfD1I+VrBK3lEDThbFTL/YKAIVf50XAaT263CkUOy/ERwBKIBsPR51vq8HMZetydopW81uBHVV3X9iEdW/y4a0E04nImCxS7vwUqVHy4MwHunfK79curQsktE4djb/U4+FVx6uhG24pSppBHpK7dcT9SY/aRZw3vP4LmRE6o0Upf89mMGLXrbNO/szdYLHqXHb+OyhY/KmRzTaMJli9wI87OVxUsndYhIxGTZX8B27+VtbfURUzp8CYEb5XpE03isomTHyAlU1iWRKFywheGAmttUu46dn5Tl3EsiR8e9l6IRhKByQdt67l9aBjpT1nTehs1oiEcyQnRlkzCuGr1O2sDpmcyveFPUSCn0UPq9qlvBHqiEv9FhTy16+vZXOeuiRGbDwkVj0LOn1+Vx0LaD6TKassluVANZh0tSvZiK3hWrzpnRhSJWkiLC5bg6uWo04A+f6VTotddt+K9IRkMJUiSQnaO+HGKJJ3Iz/rsBzyKCsIkqXcDCWgr6U7XXUuy3SXRcBJNeTn7qQMOK14X06rkFHcidy/l21EJeTLPplsvKV8E/VWKGzCYTngqh2PhFae2cImHJUsGB7NBiJvYEF70XoclUHUBMjjkj5yhNZGSnr15yxLvn+1jFZ7gFIUNOpfMXH8mhI/mzCOEmrHMdVBETEVpHndq6oK2ViMZ4KOXVMeDxgg81gUEXne+LyPrwWBUcfaUpoICgEipp73Z1FEbGSt7PaQKi3YekGJbvpRxg4gF+EsDJWDlDICpahMSETOJtL4KHJYWHmuRLXD4kjRfWmWtSFwo2JxO4xnkZNCbv/M0rPspAr5XPVmbDadSWilQVYX4E97fS5CyBT6b+M4t1UvCiVbDYmHSOqB+xOP0kYcV8D9ST8ywgGse+CE7qvYDBEPpgZHonMfosFVZ+CNwZ0q5cNlEIMilVIqLKY+EoU1WLgwzuJlgW6E0KgqiSTQaIhAAwNrDAAaq1Brj9ztAMg3XGd1B2XE0DqZIYszphkhxCC/ayed6d3JIF24xaV0UpWLuFfzIN2pIyKQMztuxYlQN2eGo/GgUQKXdgT6u4N0inlU1ds8PgJGxcPtYOCtzYUMELEWSewujKOuBIUJ+XdNsHjRWCyKhEkhrGsfMXHcGA6KSPmaS2LOYsWXggXJsIccHFUDrlqP2kUclWRbGzPmtxxVLts5n1R8ONpo4c3Yfa4Fzp/5lJN1qUZIMs4wIpkzYuIzwvLaIdPqGaNbrDzEh4WSFKXDsyOZ8za7q7IjinIoA8h2ukq8S0C2RZ8VYx5OKQdGHwmJL1PA924sZp4FXhtJrPvhrcXdmpv2skj5M2wHi6nnpqWmYuohMvf8LEMalTNTp0SxUYJsINwbx81+kkecAqs64cCkkVj748RlYMyumTgW3b0UtoMU54VJuFcPchBxbe+CwWHBUdVJHbJx2cu2yHp9layz4JERihBJy8TOvbIRy9JIIWzySMPJOtNC6aJhFxeTOmXyOVXjLO3sLNSgSi3TvYzw2PEfiz2/ogE3vcXt4PJ8nEUUEbjDInDtRYOTirkdRLmo/nCyBjeDwbsLg3v1kAtJAxZpNLpLmfm/nwHURXa2ldURBe3O2zCOelV1tU8Q339diQSWsn+LZREyiVTJ8yrVTtKMqAQ3RIMbySlRZYRem1ESK+ouKUjUs6WyyL4YSohWIipgZSzC393Is3zTWWwlxLQLuteRS5MsC/MuAg/3lDCKCqjVgHLGVp1lMQlIY5ygXhd6H/W/SmTvbMoeEs4kDIKMqs/LTvgzOn5VlQ6fSyIsMx+zJFURzGhU3s7xxrIkmnPZeqwH7n9EIpOspYjjkjEH2nQsy5E0OnURzxs2vPsqqk96fS4QCwPCy4dFyBKjhY84FHKdVvAWCQ8nA04qLqKY2Gnc9i5Lqu7WhLD6BPzUIQuUzcCu5rp3mHtamurYpZUOXVUSWsUrpLUVpzmFJoc4EmYMeJhedQ7rwWUbX5dZviOPoQk2y2qvO5vd1a57h/NGCH+RHY8muzoD3KmGbEDVRCMLkszvXbC5w3XSzWbHvzjmSbQCdd30LsuqNoPNFSkwznSBsVPUcc4+O18JTTpTBXjtDoRYdtVZUVJo7LzA09J9JKnCARY73V54zrLkBqdM/8qJPKwIefSks/6VEHkBnbuOh9OqF1Mbl2QePSb+TaWLUkb5uJFy065cxFEpXZQdR2dTF7PZD4muJiNYtU25SARGOZwS3ZzhWhki+RAhjiZReh0aQQXU/e66Y7F32RLKbiIRgMt2tJeupLjTmfK13N93F3xmNoPDt1cWqy4ImYzdDufT7MwPCpnjS8FyWhPm1NC645JIyXEVRM5o88alDpr7hFqFw3UdqZJIn2uVBK96l/kV1vAg1/l+J52rdqCbgeTUmSeisBIoWE2UusCZ96uOxNOJjzJHhhxuvGbKu3rVOUw9R3kz+ezsqIkYHcphcSQS5U6KGmtoaLZVPphJufjUQ1IlfDr6AAANr1OTokpGDeoxoChrlOJVkRRVguiaqu2YHxPBvYYGUOwgb0TBVBgSW5flgKMy0ABQnntvyGPRGbmiFyuB9qeOxbOui1qKMd3b1oNF6cZnYiJ7862M07RjB0a/hySIUi/XXvNmzN73KuqkB+w+aXuUWI8j2Rvhadz0vLderteQIBJvk8cO6729Ahh5S6VN2QTu3oRNUBsN3pyxEZ0XQfxrkozqR+USVUxGVDpRGhcexLWsmU7u3Uk1joiUQK7qFVXDqMdIYcWLR8YiVImJuZodfXO0WDkuA05KVkXqkBplb1JFItVXyPfkumdB0gWD500hcRExr619TpDy43YDf6YGg35SI7D/+lwUFjERUlNLXKZq2vzA683gXI5GNpetEb26dGYFw4oO9g6hfV+MynLGPPcpd6oRlGoui/FABpBvuJXFczuMm6MSbQbpGmsr6MVAyFtHHZthXEA6urjpLV42JmcitNFi6iMezYIwtVmRX7Yma811oWh3C3AznHlC6E00mbBG5YtK/mzeFLpocNuPHgN9HB9WZanrw6dyTEVGlMhWi1nRRsYOqjRgVRsIzwmqoV28oh9TF3FSDRiEMOssCyr1eqhdxLuLPsPrlx03qe3AomDV+VzghMSH6Z4kuSpkr2hIHw3emPb5sy4K5CAf7TeIfkSBmy1WHRNkN4PNnbg+5AA3tP1xWUgGzxsd1aTcadR7KI41o8HPvsSMh93I3+jl505cxL16yJbmpUPOnbnqXofJLdh5TKTQOq1Gf5N9HslusHjRtTitfB57Kafkp48CHs248ax7K4xybhxXnZPrNa4RdmB0YWwCA9k4UlEXw/F6qbRVC5OJjxn90OJ3Oxi86ky2TFfYWTlNXP8jAVQltr0gIN6mveKC6GETkD/3Rxt25iqhKywL8ZgMzhuuaeVUKIHyoi3yAbov0y0s8KpV9BRS8HI/ujfpc/OgOTF8xkyea+vYQsePgJDpwPvK/cGIRbTLBSf/HaH5ieN+tizjSO4Fx2AMw3LiYWGzrHV/JFRZjS/gur036bEVYu9540kclpHBdhgbGGAsmGunpGn5jEkPeI4qNgMtn/tocJqRFIgM3mb0R6X4KY3r4LK12fNFJbFLQRkBDVUbG8IsxZYifSaEz9rRzIpp1RaHRcBJFXBUDeLXIZyMoAomcrR0n556FhgsRvkzZj7i0Szmz6NclewcLDwQJfNqVs69mvdL7er7aLDqLE7KIXNdCsNRhx7mjSCmOyHjMrF1PMVrx/dtTcK8GM8NvWal3KPzxmXUwYLj55BIM3gwGdjE2bG53gxERtT8TT1QNtJgqGv11LPZVvO9T3t9LkYhCQarjqMD3UyBscMhC5eSTYCdxMybTFij5pubzNxIwJhAk0ZgbyXbDAkowa6tsEAts659lQGALMm5NyGKQlKZppKOfhvAaDYTk8FVR+ncoki5SgVYNc99whuz0fVNnSlPqyGPQwDK0JwZI9YXAvkTgZAZWzTZpncmkrHNAByVSo5MMMZmmNdZjDbZ5eveA200eNkmFNbsQf+6KPkBJj7CmNGgKSTADGNCKiE4VvCq6NBZeiOjltrJ3Fa+/mzn5DoJ78Uk3ASL79xE/OKJ2qMr5EoHS+20dJPxhhvzbiAPQ2HyjREdu015HREOFo29SaiLICgQP8eqZ9S0M4A3JKtZQwlaG8bQurD3TA0JmAgUqkE9el2XRcioAjM1xvRPgOjDSRXlsORaNTAokHBW99gMDpU1SODP28qa7AW900wUHQnp2iVawev0h44rnDdjLo0zlCYn6eSmwutQ0qmVzjgCuGopXQR4aMw8u7CFrIs2coPPDolRIVv10lCPBFXZ6L3jfbvsDU6rtGc6Rl6TKk1qm2BchBncOHaTvyOaaSWQipvrg0nMJmZP2xZvhUqaDVXEcB0+nI7w+mXrsPAMbXu5szirE3aB8P9O0MuDScCT7bhVNmJYpR1sE00eQwJAk0bp5Koz6LzBIvE+WZD3se55eC8LIpxWtGL5gBB0orAJd2vuLxtBPChHVUtyft8g49NtYLQ4ie/q8WEygRcAtgOfTTUWPCoDrjqH88bj4bTHeigzqfBV5zICdyVhhzc9i8lWrk8ERwJKHtb5vna3Q4Qc0KMqz9uEEgnzlPC84b5xUo0IoTVjRpI3Y0GisvwYWSSUDrjcAsuCpFP1RlFvoz7RNVWRHJXYKkG+CwYnVQ/AIybysZ5uHe7WEZfCh6nDyPEDkEnfoyUCEAyfp8ICH9xG/PSRkHaDQbCiZBte9wjRkXRlWQwNkXk0haEAgFw07uHGJMwEnVQ5ugWw6jzOGz6n9+qBXCw4WAnF7CKfj4OCEQel/H4LZFl8kOf44WTI59o2GEw8nzMdrQKQ0c7oSfJpr88FYmFNwqEQJQktElFQqeVpxQpviAavRFYTBV7cDHKRos26ZYVxlIiphCTtljpBRnhw8kIdCClq3xBnM7BDux0IPSphZTfYTKSZF0lyCMxeHgYr8e1ghQjI1NHDctjT+afsOGgNu0GVSio68Eokjip5vektE0Kl84zgvFXfLzvQET5NAre3ccw40eLkNec3AG9M+T7aYDN5dSryPHU4XQhSUlnVl49zW3rXcyNVdzlVyqx7i6uOSIceflo+3qlIBlO3u6lLeHPqZAxEeddlO3ZJVy2LCpV9vWh8/iz64KuNswXnqLpJqnunvhopzs7qPhPwpk7nn/zcIY4hUUo0u1MHvDsf8HAasnpk1bn8HgEeqK86J8oMJ+6ZJlf+C3F2fbLlWlQy4G7gPT5viozUTdy4TpS8G8E5uJdNMyVkQtxJOcj6U9krMnysKNxF62XDtlnWpnNztet2VkdDQzaDOq1iXheXrYx2kqYKWzzbOVkvGoZmmQaaiCw6KeIPyogHUz4Du6B5P0rk5Bq+FAJtSpD5O3lPz7ajV8o6XwN+1suOMdj/+FmRIevaEu1b+IBVZ3AgtsUcCUJyWQwezUKWy173Dq9al5GBkypm18WQlCw3PsMzzyRYzfxQxcSDiYyZEqFnGr5pl81NftWNRk9qrKSIaYjIPjYqldRCTsdRh0XICFYfiXAMkZ9L11QryO517/CH7vS4FTKs/p7vr+noqDwuJazXLmXZYmn5jN30kIJkgDdiQhZHpZciq8uSB/i8GFOfM4m1H50dvzALOCz4rGsTkP2EpPFRdETdKXVce1IOeO9gyPehEASuEfWYWqIreXw3jIfkqrMi8eb3nzdO5MIs0O5UEcsiCYLhcNGOxSXHRaNTsYEEfMko6/mOh/ZEEJBxDxq5RrWNmc8w89xXdH8sLYPjqBIxWR6t+6aaXmmOy1QULav7FndpAAEAAElEQVTOwxmSg9XM0cvITs0gLYi6qOGeIvhKnH/e+CyrVxM35RvqOXLZfnbp8LkoLPTGKAnmXA4Lne2XciBqEt2VGPsM0eCoosJC+RhKmtJwGWNYTWtnplW7MqE1gpZObi4bqajcRv3+9dBfdQ59YiETE3DbcySzDYTHK0tGtsrJ1lJ0lDbhuvP5Yd+Kv0JIJO0BfOiOy4B5QZa1zoidYQFx2fJ6XbT+NQi5CwYPJzIa8BEPJgOORPqkcKqG/5xUfZ5t6kFMaVbCky1w3Zu8+bfR4rCMmBfjHJ1jKi00glTFSh5MuDfh/YgYvQ50FsnrzELnTjXgS4s+zxhjYuhOEw1OK877jKHKQI1yUgLeEEhy5jnaAlTaOMY76zy5dKPSRvkjCituBoenW5ch75Mq4KzW9y0McEtt+mWnqNgouWykYFj1fLjVQroXqPim54HIB1geWjeOSoaEbBvfhZEQeFAEdGFU6/RxzDYACMlPHXMIJn6UM5ZO0TsWdJuBxVFlE5ZlwhvTPnfuDyZUFTzd8T5e95Q5bwZkhRAwZsn0Mq89rQYcCefHWekwMRrzhARseuC8Ge32a6deISZ3jZQN83dsB4t1r3bPI7teuTnapTeBcrguWHz9KOZuPluWZ3Il+QLjQccxyVo2cG/Hz/iqNfjKQY+TKuCkonS8DQKTG94fVUFZMyIIdyqOoC5bR1Kc3ONWVAg63igdC4+pG+2o+ZyTk5T3Iiv26tJtT33K3I+DkgjBLrCg7MI451e7ZyIcREPenA44rhLu1AGVqHye7GwmCBeCfLSyTnQU+u6cRdx567EsQ94f1J57M/BztcFmDsD+iE8jGU7KIe8rdIwcHTGVD6Sy9ZSQ7dv5zJrcNHHMw+bqVkY6RyXvkZLJmXPDZ3Um6HDpKOUtZHSoqZ5Evl2W5ffJ4MFkwKNZn9/fYcFOvJCmiRlLPJhX4k2jJFsAuVgAgOvO5rHQF2ZsDlvx2jgoIi5F2aO8lZ0IDhQh0OTYzWCledOiY1Qh7mT0uF9ceZNwWHCsZwz2uETKqxuJ4oqwnTe8nlocKtekizajzM93JpOn1QsIsn62g8372Ke9PhejEAga0CeDly0TJxvxkTgugcvOZwh+5iOebBOWJSU3ZaIRVOWovijLkBPelGvQBMq+SksnukLHJbCZXR7NGIATMcJ4teWh00fq8uPeITckg0ORYQ3J4k7FA8SbhGAZ5Z4wPpDkI/CG7ILBy5aLuLIWd4SQCliR27p8CCp34O25LmIDgASr5zuPuzUhLJVkDokE0VBC2MCjskEDm2hINpKnUgLuVKMrJTkWZGjP/NgFdKJlLy3fqzKT1adBNwtAteqE5jTtUNEkdZvbDTa7iN70Nn/mq84KA15HU0CfLJZFxPOdxcNpyJt/5SLc4DKaM3URT7YOy4IPzMxHPN8VkpRqcjd2OyTxb/DZo0LlXPo7h8gCw8rBodenCYRNWTiRiOvsHiIjz91G5I5JCjNNBdTi9dEsZrnhzeAk+XH0ELEyN+dsN6IJLhdsq04jsXmoqIPhy6bAzPPA8vKebmVTJbGLn3PqNS12dHUEJERrYNSylxntJowhW1E6rJvO5hnx8x3RkPvTkbDaJ4OtbMzq7uptwoENuGg9Vh1HIQ8mjOduwjiyMuDaXPckNOsMfIRkY+5qdeyjfzd1LNCUvX7eEAF7NO1xVkPGDMDdmlD/wsc8bj2tY1b9cJatyiL+d4h85jeDxXUH3KmloIhMHU3JZah7K2igJmlqIeFtgkkkek4EHXrZOKx6g0czFqOqPlJjtaV0w+w81YGXa6uuBmx7h52gT2pIpuTFd+dDLpD0ubw76fBsV8KAYyCOE1kw3vQOJxUVNfo8HBRJ9uOEO9WogiJc77AoxsRRVctt9p4pPew3wp16zWHTGBwWfJbaSOVe7YA7VcjkzZfiDlo7QYeixfPG46wmadIKCXYj61ZVSJetw2kV0CRFOVjo7QaSXDw4htCG7mVTYOLG1F8D4E5NCS9l2w6HZZRmxmY0WZUy173BcTkiGbWNaKJFGwxeNg7eskksBUHzlkMwHVvsOypbsMiaC9IUMTpFK/n0QFAmXf8LibJQeaiS8oOocKjO8VgPVO14Q2T1djConcF1dIL2CsdCVExamChip+nBn/b6XBQWIRF63AWDN6ZDho23g2qJeeF+Y7XG12cL/NwxZZYTN2qxdZanHXCIQBs9O/UiQtkCSgJcyrzpRg4j7fx0kwbUVXLUcqtOWbX8upF1weDZjsZVhyWQksswk0oQh4TM0N4FmztpmkeZXDw82wG/cJIyPE1DrdFEaDNYnNajFHdRkGdxXIZsvqSOj2P1Pdru6gioiybLohYiz1sUmhgIkaOxu/JWw4VGIpd6Q2j+ADBW1oijYsSZ0b2vFqmX5qQ8nAxYJ3Inpi7iorFYeOUq8KAuXcTbc/E4kPtyp2Lx9tHWSyaDxCnblBNfT2sqLW56iPKEsmGNuaaMlTa6qn7RMVUTOO+cCslSpZiaB8H/ariTwbonYWsuZMOQbdCRIUWAY6ZVZ4SvkMSK2ea1pt3CaTVgG0YeT+0jLjqLmec6WIm0+t1Fl+e9LxseBosq4O+9KvHzxx1+eFtidH9MuQC/bD0WRcQb0wFPth4PJgPWjc/jtYlLUsQYDBhVUJrjYgVijjBZqTEX9KSQkZnax6uHgj7nKRl0iUjK/UnKYybmTiT04liaQEi/CcCb05AJiyoZrS0Pk9YgR7svpbuH2vDLPX133pNsGmxGGCaChvAZjAjJw9so8LnLUs4mjES1CJNHZcsioK95oKpLZRdpE99Fi4825A9ploiugfXgcNlyFr8sQ86puVMHnFQjaqsybR4UXDNRuDZXncFZrenPFhM/etRsZQ9Q74MEKnDuyGd5f23wjSVw05OwuSxYmLxsPUqJQX++c5g4rt1ORpGnVcJiEnDZOiyLkTAYYTBxAW1Qt0bei6kbE10BCaMzQFEEJLi8/5HPBPme163+E2S9RCOmVWzcFN1QEnRpkcdH2wEorMXcR9z2RKiUZAlwH4yJ42W1KqgsD1c1K3vZJpxUY66NGh/OPIv4w2LARVvkrl1ly5qoXUpxsAkWvYzmpiLVVlS1jQaHBbLTrjMRd6pBmjIdL2sDZLM7a4Ca1RlBI5RDxGsydQnJ8pkdAp8TbwDYiJjsHgpBhOJA/OPviHLlVtbKQWEznwN7I+aJ0+L+PwWIhTOc1+pDNvMBEQ50kzNYlrSy/eXjOSobJeOesNJV5wHPA/qwZFFwpxpwI6x1JUPp/OuVjFGU/DIRNYVCp1wQ47ycBzVn8ZqLoWE5yzLm7vH+JGWEg1UsN93TisY8sAkfbIrM7C9kRBMiIeiDIiJ6wBt2gbs0RnVne9o4+sQvy4DdwMPosBxwKzCZevO3Uoyd1oTuptJh3p1wnLQs+BBxJpdoxiPyw8oSDZo4zm+VNcxREje0tcz3KqteBCSiGTuGfOn8H5Cu3o98liZQS62psxctN2JnEpAMvjDvsOo8rjuLs3o0bHm64wwxwjDaWRCS7WAQpSs+kYO5dhFvTglPL8sg8dJawZtsKjOSTI2oL+jMqMiGSurWPTtFZwAIqhDjOIdWxIlqHCcjDcZ873s1nFQxE29Vc7/q2AH3E5e7FhI1KZ+9NwkyK6Xt8ZNtIcoZiy1YcGwGbo5fXBDxSmBnz2Ahiydbg4dTFqGjaZAUjgLfP906LMuxIz0sAp7uPOflMpIUPqeMhgxsBI6qmKOxtVjORFc7EnDbaDJ6p9K5zeBkU+b1XfUOCx/oYxKpfJo42n8bm9ANozukfoYf3lp8YcaiTOfIxoyeL5WQaqeOhdlHG+4vtTQnqmJ41Tm8bDQUrcCiIJlzWQSO36TIIPrAkYseMOeNw0HB331HTKtCNOh4sXIBvixZwIdoMqFanxH1ktHRQWES2mRwUvF5ZxFncN15RJDsqmuLyItDIa6XyzLgg1uPyo0BhPcmhLjPG4u3ZoM0HW5suqLJX3cGuOgptwdY7CgvxCcWkDvhuGiuhRZr1rEAX/ds09QeW3k+84L/f92ThzKR994LQmrNSIac+bEwi2CBbs3YvCRwDTskTL34+cgo5NvXwB+8ExGik3Ep/66LI1r7sjWoHH0nTuuAOxW/bmWf2Qrf6tGsx/OG3J0gaJCS3TnGElO23mKILAyawHHQSTmgiTan1Gblo0vwibkz3o7csCTP5RANboWbU8g5VmVkmtdB955dMLIPcMyVYy0C0fa57Gtr4UVdNAn3JxEfbz2WRQIcsjNyYRJuxJ20C6Of1GXLa6RN9ae9PhccCyMjgonTmfAgLndGHg4nygc+8NswGqUUAlkqW5zEPh646symTmMhjXVWLd4BL1uXbcCbQMKoQqBXnREJmy5q3tyTashSV2dSRlQmMhdWEtZSHOd2gfKhzcCHvXYxj2uMUY95VvelA543BT7ceNwOViyEWTVP5d/NfMDLxuX/P0TlgHDBLkVi9WAyYDcoQmAzhKf5FPuGX49mPe5PSAKb+YDacuO/HcaEQWXva7Lgoki4O6FW/qCIeWY7RBKhaDyV8j1SJUdlUzYt+2jjcNEScl33Bu/fMmvDgr+7dMDEB2yClWIhvWYmpGZld2sSDA+K0c55MziUjp7+t72jLFbey8yPOnFFo8ipEZth4aYs5XfdSjeyn36rBLJdoKrpZWvwsrW5IDSGksfdYPIBqI6SyvOkuodjnXcWIRM1x8j7hPfXtOBdiTvkZnAZqbpsiSzdn3Q4EB8YLdCXRcx8JQD48uGAIY3GUynR9Oq685nUfFim7HarnfppzTHWZevwsqEEj6RCQcOCFtsaW08ZbxvGcLSpo9SylWJKo55pj05SsPpbXDQmB9vdDurr4TMiZvYK1g82DE57Zx7RJ/FGiAYXLUcDC4GRKUHkhkuPByq3nu9Gb4v14FBZoI28V8syZq6DegfoXJxIRsq5MtbQnVIJt96ORZvBaH0OQEjAIStTWtm7FBLX/UfvsUow1yIPPSzGbAm95wDXGvNX+H27weLBNMhomdfrXj1IY5KEAMz7eVxSQrmWpon7LAuxrx4OOCwHaNCiNjcR9PxQ3wlFx1IyeLxxwheIOWE2JCMyeRY6B0XEcTVKLS34mZWTogFkfRRUyozcMOVN6P0GIDkv45ly3Vu8NVM/HTpm3puEbOVtwbPi4+2AgyIKcsuf9aJxgtYAasy3FY6Q8hzU8wOgy7EWGor0vmw5Npu4mJF3evpEce20eX/WkWUtvJwgiHIrn2dIHK20whfS+6kNQJL1qdwLAGLJz2cK4Kh5SCSO360DfumEDbg3o/vwUsZwT3aez6nlvr4WDps205pp82mvzwViQZ8GLiRj2EU3wpz+eOtRWFrhLgpkhUVp2e54y4fr6c5j6sesglIesCMhIqm0cyIyz0YyO2aeuu1Vx4Nj7smIfrwB+hjx7oKzrlXvsr77Xj3kcYLOCrsoIT8OWbtcu4CLtkBM7OgeTmOeyancqBMyVIiG8kfZSN6aDzhvPO7Vgzzs7Nqebh3emQ+YeImbVqjRAD+8DXgw4YE+EpsSCvAg3Q0WO4hXhfzuVW8w8+Nce+6pjwYoI9VMkXVvEQZuNIM87IXMYzfCpJ55WgyHRCKUpik6k3Cn7tEpUQvszu7VA2rr8KJhwfDuosd159GEEY6eFNwUl0XAd25KhATYGsLsH2fy2tV4w45qlIYavDllJsZWNgTmnKjxj0XEWDApUVfnleoh8nDKmfZlS57NVNCXJJvlQTFar1ujZlFphIAt5dK3UqQxdZAb6EXr8aPbiHt3EiAZK7cCaR+XAe8uPLpIO13ygIg2nVYDNkOZD1yF/99fe7y7GLIsVREZRfoKGT00gdC9znc1kVetqhdFRJssDssBE5nbKs+kFlnc7157HJSEvrMFd2AXrt03ry3/WxejTFaRrYvWkegqLn+PZix2rwL5FUflgJVwCAAdV5Eo/dXDQeDsiNKZjFKuOs6MVx2Rm5ueMPlxSSmdFgzvHdDOed1DCsmEk4rrV8cuStDeyfWPcJkYqmZ4yhdQKaMelvsHIazKIG2WT+phYgHMRf45cwHO2IwaKEGQGQ0sLD/ekiBYOim8epqb3Q42oxuQQ0ddGVe98gGAm8Fg4ijnbIITzw+ujSc7jzsVEdqNID6vWk81mHiIVMLZ+NGtRR8tzmru4USAeLCqJNXKtVb57sSnrPYpzCg/bjFGEZDIy/wPgD8npBGlAFjsV24cm2zEh0XVZydVwHnjsBDzsO1gYGDRS+fP8yDi60sWi+rqelIFvGiYb/P1ZY9doPfE6OA5ItMLH8XvJ+GwiFlRN/ERxyDHg8VSROHHQoQKEY5AJzYJOXzcs3gujlksRxXTm697g0Whzpr7nC6DUlJXS0skXwtU5fZsBouXrfBXxDqBz4HJ8QOqfFQjwtry/ah0+cnW4agcSfGf9vpcFBYGyDPN2kU0YAV34IPMRHlArnt2/YcF51f36i53E4T3CdtnBqsZNcfK9LUyf912PDheNQwpO62Y3aAd38MpteYpJbxoPH0sDKv8y87lLsSC+Qa3g7LQ7Wuw92aw2cxlELjyNm9+Fm/N+mxipaiLzrE0c4BTYzKPbweOc+5Neny8KeCMkYhzg59ZWhyVfZ592kRY7rgKWHUsCu7KAa9d652KK0QRhIvGYUisYieSCqjz6+wWKQvfgBAxAFghZKlh17o3eLwJeHPmsCyA86YgsiSbyWERcsGkxNXSspsFSMzqIh/A88ZL1wY8nBAJuGh9HsvsAuf53tIjQDf9PlJB4W3CZevzmAgAhuiEcc37tPD8/MpbWYmsORhyLhj6ZvYKBv0vC59XncVVl3BUkm3u7J4XiM6QZaxizaiUMILg3J9YtDHlMdui4OjqUFxACYOmzGthV+5z53rRFhiiwZ26x71JzGjOXNQH540XElbCeeNwVnM9PZpRmXMlJNyFbI7XHVUf3sRsLLUL9Gs4LDkLboLFo1nM6IwqOoD9qHBe44OSXASdQ1OSaUaHTGkWVmLdrkZM9C4gkVH5UQqXVxI/rwevzrrvT3oYFHAG+O61wdnE4I1pEF8Yl6+ZBqstC0LEt0PCW7MAwGX040YQqEF4HZTVGpEIIxeqCx9w0/ts6heSkSRTCeoLasFNZGDVFXQ0LYN4UIwjRfV4WIuj5BbjXPy0ksyNgqNfzeawxuDp1uHBlM/6SRXwOyuHezW5RW00OJJclm1PXgLJshbfuQn4+tKhSSxe/vrVK/wT7hQzT8Kijm9VZddFomdNMHhrRvInfX7YtP3wNuGnDmVsEQEjHikLHyTMiuNN3jOB+6MVR1NgIvbzpUjEIXvtbjBCNGVRO/WjcdpC3FbfnA541Tk83xUkfTYJhS2hgWfWAA8mHbaDw2XnM8qmRn7REbWuBWW77R3u1D0+2pboIo2/XnUO31oN+KlDUdaACMN1b+lcC4a/LQoiqateggN7h3Kv2Uhp3KcAcsuuW5sLM82JaiMwyAjpWFC0Nu+z5G11kXvzVw6DoFB8RlqRwjeBz/PEQQj4JjughgScySjwovWUbbcJDyaMUL+WJqOPBvfqKNLlscD7pNfnorBgPDY3o8u2yOOFqR8rp8IavDntcdV5Qo1I2AYSsoBxXqZGRlr5avqcjk1Kl+AS2cWKWMz8OO5IGDXJM4/smjZEjdyFxHizy65tkiAkQponLgjEaPF06/DWfJAu2OGwHHDR+pwBUdmE89bj/qTHbvDohF8xdUQbFoJgTDznYHOf8LVDzqBXnYezHBeocmXVOVTB5muwFH27VsDGAC92JW4HkztuawjVKt/ktOY96QLllFOvMjyTiwJnmHkx80Qn2K26nOjYyX1974DR9rcDyVRz4RPo5mkSs10AbtJXncNFA3xtOaAJDs4Q/lVb9omQyy5bl6VVJ1XAZZtwUPCaL0sWoweFKnGohBmEB8Cocb6vZ7sCs5Jx2VcCtUcAa+Hh7FsqpwSR3o3TQ+bKCHpQBzyc8kDRn38snba6oerGeE+c/naBHikhslPeKXqVSDLr5XDaBYsUjKhxkshLI/pghb0+8n4sIBkLMXMLVM57VofXNvU2qtKJhzit8ElgfmfBwqN2yETkmY9SUGsUfcpscYAI16Yz2QbZG66XkAx2HWFrtVQfIgvyqYtoo81rMIGbfNMz3ZdW+YT4bweL687gtCYx7xZONljgrRm9buhCyW3tsAi4Py1wJvA/wDWjIzFFSo6qiK8cdnjZFLhsHe5O6M9w0Xo8nA741qqAN5aydQClqEKWRcgwMxVKMWdAcPbNTnor6IpaUgM8wLto8Lzxon5Sgig5J/ozme9jRG7PkcJusJgXSQphXutHsjcakLE/dRFvz8dgrIfTDh/eluT3SHLwEAFrDP7oKaRhoxHYnzg6ZbKsTVjuGeZRdQVctAb3JxH3Jx1e7EoMEVjW3GufNxaPZsC8GCSTh2Ohj7cFakdUVBtJVeJ4y330YMLCRwnQaxkTzD0L66l4iWxF7XFYRNyreZD2ske1jj/zorUy7qFHx88suZZpK17gqrU4quj70kX+vGc7iy/MaMhV+YTvrw2+tox5PSnCtuoMvrH0vJ/R5HGYyn8rm/BoxkJCUfJdsHi8YfPwznxE1HV0rqmuheWIbimSfQoZbOZ+qcpDPVy1MD+t2ETo/qpjOfqcEIVOguSeN17OAO4nx2XMdvwAi5dFoRECHm/NO5w3hfDZxAk0/qdgFAKQ4LLqHc6ko348OBxXrKx0bsXv40FJ/3JCWU2wOKsHNDKT3QXgjWnIszX1UC/dSDALCTlrQKFCZahr6iYwBsXoDLGQqnzhhUHvuaBueouTkk6Or1qHXUCuUiN40yxYtW8GHth9NDhvLB5OOCt+OE24aAyORD7mzSivM+ACetW5PLbQzmk7sIrvIhGSy9bg4ZQ2zzPwUAzJZVXD3ZoBYF00KMED+KbnhkS7blbMOqvvZczDAshmVEC7P459CAF7S2SGLnsCq9mE687iZesY8OQionRaypf44a3HcZXwpYOIl40TBnbIXc51x5l2BN32DmQT7KPBTy8DXnUud8fLMuLbK4tlaXBYppxEWtsoxjbkuaiMGGBXcFxyHn8qDHpnEyxsDmlSjofOlzsheFaWB8DzncNlyyKpqzXpUBQEyaAQV0kluG1EAVE7GlGplv2g4O+zhgenkt6WkqZ4rx7weFvgoIh55l/bRFldsDir+zyDfbrjKPHBZEAbDc6qIcsB378dcFrTLfZATLfeXzu8OWW3+HBKEqyu06ljAfu88Uw4FOl0IyjhNhgZlbFRGIBMOiNsz/lyHZlrUlrNxYF4fEQ8nERySXzMh/bCB1yKrfvdmmO85KS4kmfzVeeAzmGaiaMm8wUKQySksermanAjh7PaxHNdk5dy3fls0vfBpsB5M+DpLuGXzwx6QRV07l/IXnE7kKTYBcnoMRwr6UjpoAhY9y4nEBN95ObOGPvRx8Fb4AuzNh+A1z0hf0CC3gC8v7Z4ax6zCVUTrRAgrcSN87kd48NdXg9ndcBmAB5MeFhdtA5n9YCUuI8wv4WHijHAy9bi7VmPCODjbYFHs4AukLdEPw0jxEuIM+aoEHuy8zn2gPyv0WxJfVXUUKyNdMWU2ouS5p7FtzPAjRAhdXSihyWdZ8kbUbL7/UkQ8rZHhMN1TwRAEVZv1XkWubA+KpMQSzkefO9gHJEALOwKk3BaczxnIb5Jsr/cdBzvPt35nDS7n810NlHXVBl9W5IhX7Xcbx9OI0rllQgHzktxp0ZmFBrYPGKcuIRCQjdve5PHTADHf8uS12kXLGaifqsdz5llYTFzg3CWHBrJAZoJsRxSvKREHthl63Bfgi+vfoJB1u+7sDDGfBnAX9370jsA/scAlgD+PIAL+fq/nFL6dz7rZ6lOto+EPNkBJpFCRlx3JPE1Yhc8k85gXgSsOo82WCTELIU6qXjDpqJ7vmmtBC6xw9sMFh9vOG5ZFIAz7AbJ0AbmBbsyTTW0hjcJ4gF/KOE0XTR4tvPZ+IUVLTfSuWdHv+rJ8r/pLHqBdHXBwZKV+3RX4GnT4auHTKFcdT6jLDq7Xpb0b3hrHsgAHjgHPih4qF40RjTe9DoobMJV6zNBTC28yfC2mfnrTcKlIBili5gY4Hs3Dk1I+NKCFTR5LeS+dJGLTM1xNKhL/eO3PTfMo5KHnprRUHufcqaFjhnUZvewSFh1lL8NyeDpzmBZiqmSHEx9Gm2om0A77Nuen3uI1L3rjPLBhMWCzt9tYTKaAMlXCHIvm2AA2XiHyOKNZK6AVTLZkE0Pv2wHHGlhnX05IpN179ZDHg2o6sDJfD2A/yttwqweofwIZNvmyo6BcOrI+Z2bHv/5+0BoPX60KfCFWY/L1uO84eH0d286/PKZx3nj8Gg6svpnMtf9/tqDKZqEbKc+4RePLQoTsSwinsra+soBPSW6YPFcunKSDYkybAaXA9rIlxkDqlT+RzVJzDkGNPYBtsHhBnyWVTK3LFhokzBWYCJjkHt1j4Mi4Ee3ZZbX8vAg6nTRGxxCUkZFIj4kgxeNw3uLDh9tCxQm4f5kwLMdpZQWyJ4u6m6rBlvOENEhP4JdpxusuAE7IbKOrsCvWgdNqT1vfEZ7IsCKPJJDo03RRpJKtaA/KCNmntdO5+2AywTz695jN7CoeDBhQbnqHCrLQ+G4gqBUfE9EMQJetQb3JimPDznjN5i5iMOSqI83NLKbSAd8WgXcyrOqEQArSSc9bxxKIRa+6nz205C6VVRCKT+jXbBCNGSxpzlDlYtZNddLwaWEQx0/A5LrYznmYtHGEZoSrlsZIZPXZrMqTMn5ylF73li8MSUqFpIWPDwXVDashNwmUCGmaa8/2jr83FGbPR564Rg0wWJaDlh4Xi/1/wgJeLzxgm7yuk+kgZzJOJ+8Lqo57lRDRhmbABxLYbAL5JQoev7hLZ+V+5OY4x70+nIMz/WtfLkIh52Mk4bEsVAEi77L1uLhFEBkQ/PmjNfj2Y7F48hv5Gj6tqf55G6weNU52Qe4PylP5rNev29VSErpuymln00p/SyAnwewBfBvyl//L/TvflJRAYyHXhMMnu4KfLwpaB5ikhxYnGFa8KJsBovfuEh4f11hM1h8uDG56zFCVlFXxhsJu1JDJZVoTjyTUFVmVjqy3+dFEktqk7vLtaRJ6ohGu8GddBiFIaHzeeOxLEQhId37mVhWG1nAcykqmkD3zduei/ML0xLPd55BZa3N0PazHWu/kIhC6Ix54pncGQRhOK1TJm/RcGjMtvjOtcvEJi0IvDzgbbS4NxkyzM35LPBwyu8rDP39lXk+8+xsFdJUx1JvkIlLJ2XMBxKzGALemg20JlaFitgA6+84qWiT7WXufW9CbsGthIPdn3TYDEaCzFidrzoWhztZI9cd5Zca4nUsM2gA+N6NBi7x/r9/67HqnIRpuax4qd1oZrTqPK5kXs00WXZpa2HSr/vRoGriI+5PAt6c9vCW/ijrgX4GjzcjizvK563FPbMJBo+3/jX1xmbgaKYwSQhXFiclTeJWPa/9Ltjc+c19wp2yRIhUeWgIXK8cBiS8Naez6EER8P9eP8XE0ZlV18Gi4PpUT4km0B3VyaHoDTJS1MlMXQ9ZHV9QUQPcDsBFazNZtHS8HySNIvMQtKv3Vt0gxyya697hY5FnK4RLdn6QYhOy/kcEaCejLyUGO3neD8qYlVi64Smf67AIUFtlTcy87R0+2hY4qYbscaKEzPfXRbaf14OYh5QRVYIkQUaqrx5vHM4bh9rGjOzNZLx42dFKfCucp5Aou79sjXgnRDwQTtFhue8YyWJw3ROtBHhfUqKhXGETzuoBtQNOK7HbllHNduDaD4lr+XnjsRUSr5H99u6kk2wgtZUmsvRkOyp6ohQOl62a5HFdzjzNqbYy1pv4sUg+kGwejrljVox4A1w0mr+iSbcpPwsJLExmnmv2rI44LEYpKxEnkxvUeRHyM6IjBF1jRCroqHkgTQX3Ka6My9ZSeglyLRStLh0bLEXRNGzug1uH7WBznEKIlNKuOi+NAgu0RRGx6jnWuRZuB1NmiUhoBpDuVxynREFReA80ZLOyGmoHXHUsQNVx+qQKRPUTMgdr5qNY0secnaPig5lPuFcPOKkGLIuAt+fkT03ElO66N1Djuic7sTcoAnbDfzKjkF8F8H5K6UNjPvsXftJLrUX/7qXHW3MSvZ7uPHYBNIKxSWSZKWu+/zNnQEjc2H7qkF9blgGPNx5nNSvmZ1uDL8wjFjJT1kP+eeNRWog1tRXpUcJF40gQnFJuORfW/1YkqTMf8yxUddJBNsarjlr/DzYluki3xpmP+Gjn8ea0h0YT60MIINv38uCM+MGNwUnNw+H9NbAoPO5PolTcVL6c1gGDwO+LgkTONhocVXSg+2gD1JbIRO0MgISHU2YsdDKTX3gWCoS0kavQSrgatLJ1uGgN+sSugz707HQ1pvd54/F4w4P4vYOYbbu7YHHRemi2hnZpgFqLjzP+CCsdA4m3NDRL0CRV9Q4IyWT3Po6zgFVDc52pVM8TD/GE4EG4LHnNjsuEn15yUzuroyAELsOireFBeS2bBtdRgWPpbp/vHA7FY0PHaje9wapLCMni4ZQPakxGUjY5gjsoEg4KktUYZc0HNIF8ktKS9DvzREM0UO5Htw736pQhyfuTgNpafGvl8Nacm8uNwNCaM/LuwuTN7qq1QMX/ntUBG8M19/HW4ssHEf/M8T1cdzxsrlqOBNay0T7ZFvl6vmy9SKhDtl3W5+imd/hIlAn3JyTKqAHXw8m4GauCRUdaai+cEguWymnXTNb9TceRSiwYuhcTOQoPJCDppqdslNkTtNE/qRJ+eOvxznzAQSHW6qI6UKSoE4l6IddZRzzfvi7w9pzFxSvhDjSB8kuVLH+wAc5qjmJOax5wRyWbIbXj3waTGfyTQsap0mUaw/fTBZNdW2c+4eFkyOqRXeAIY+6JnjbR4E4RYN1oR33di7eF4887rVkoPZPxBhUrlAU/nKQxD8JSwWAAPJxSgj7xET8QFGsj6c0bcd687emUe9V5rORaGwDvzPncbwb6aTyY8PnSnJkbyVx5azZgSAZJ7vVWeF+FHbNItHtvZPz81jzmQlAPxEUR81inkv+qC+3MR4ZJyueKoOrnqCS3581ZyEiDEkZDYgM48yz4bnolL6Yso7w3YbHx0ZaEz4stkbzNYHE7AIvC4PFOlWHIzV4TGLd+UARctR4vBeUsLd0tXzRUOqrF9lq8ac5q8gKXxRgQptEAH20tLlsS4O9UMdsmUM5NBJieT/R+6qLN42klWyqJu3bkuWguSBcNTsqxqO6EO0G3VpMLBxUXPN3R6+L+pGNg5n9C5M0/A+Cv7P35v2WM+a8B+LsA/gcppasf/wfGmF8H8OsAcOAWeLYrcFarJ73BO/MeF62XebfJD4NWUsp9cIYs90ezgF1P6FKVJV8+pN/DKnkkkNAydaz2r3s+4CvYTKSkvXaSbJKUxyHWjA+Oci0uNjyw9hMNdzIfv2xtPhROKj6gZ3WfJWfaYQFUidSW44yvLgn7DRE4qbjIV5IuaA1zANbSgZ1WPW4FvlcTIBiOAGoXseo9mh6460g2uh0cTsqImaON8Wk14F7NeftEIEKVm6nz3Vk9dovaxasuWkm1BwXZxuzKmO1RWx7iL8RKebEXLBfk8KXmmhtsaWlNvhmAdxc8UJ/thMA2GAA2K2c0pdFEiy/MYoajm8Do5UVBKdQmGnjL9/n+bYE7VZTDEXgqHeeyGBN0py7izSlJSk1gJ9RG8hleNB7Xvcks9PEzsVt62bgM90ZhmQOK5vA9XwureylkUS2/h0h4eN83gsFA3MQvt1zT9ycDDku+r91gcVQOeLFj4bkbCFs+29H2+E4dJBchiUdMwLevCylSiZptBk+viWgwh8oEyQc4b4gIND2N34A97ws+vbx+wrFQ5ZUeZJtEad+qd3lmzLWesAlAF132sVATNWc5XihswpcWfYbsjYwaHku6aB8JDd/2HFOWlk6Ub83JG2oCEcBm4D1dC0GwdJruyu72SpIrl4WakUW8d0Dot08Gr3Z0JD2re5TO4Xs3Fvdqfnb9HgA4KYOY7o1mXUlIvTc9SYUFeH+pKklYNSoPNRmZVU7Cshxlno83BR5OB1F5QcZAXBsRGjhFJZQebszwSVKkcxyZEsO+SHz2mAqn7NEsZNfQg4KmhM92FhNncb1lp/3OvM/k6//o0uOdOXllQYqykyplztpUXI7XAw9eNTYsbMJFQ6g+JDBWwYY8UqRazGBSBEyriKHxQvxN6MH9d6XqPpPg3biHEhXhfT5vDN7EmE0y8wGXrZd9JoppGm28H0xGL5Xxe2hUVcqY7NRFLEsJfSwCasdz56BgIzrxKbsXDxHorSKOBo+mPc5bNm6Muw9YltwTMqcpSeijNHm1ON6q8/OXFgMOCp5d6nYL8LOEZDPHLwjScVAMKAxdn+c+YDuQPPqqI2Ktqj5nqAJs4kjm7CIR/7N6wONNkY0VozzfL3YJP30UBIl12TTt014mpc+uPH7SyxhTAngK4GsppRfGmLsAXoJ70F8EcD+l9Oc+62fcK++mP3n4Z3LnoOxUrbju1gNWcnG2weTDg9kIZHUDkhio0jOwg+oTt0GFjYHRNjfKSMKbMfI4gTefFWnM1rr3ajqnFUZjZ7kZr6Xbp2HVePAclTSa+nhb4Egg+UIIRz+6LeRGcg5WuoiXTSGkR872f2dV4qwmd+N2YLe+KMb3ow6Fmt+h+SqrjiOTJGSojXAx1EEtAtn3QQmtW5EJav6CQs4A8sa0DQarDjgogGOBV9WvfuapsHi25eKjKRgzGu5LB5ASYTVGvrNQ2Qwk2Z43Ls9fAQhJk/d/6kfL5J10994mvGgc3p7x4VXezbMdO+ijkmS5x5sidzrHZcRJNeB5U2CyR5TU5NS354T4b3oriqCRROotxyxOYPzzxoqKgpK/eS4I+P5fdR63/Xh9CoscvhQSu4BW+DkTl3DZsmhZdcDXDjlS6yMdOpWs+aNNgSaMCbaqbtGuLIL5KhpsdiAQvz5HunbUCln9E/TQ167+/VuDN6aQEYHDQTFC23r4xUTE5aCIWaaraIl23yRNIj+LVv67HUYZrBWURzdNNZybujE1tAuWiImS14R8rSz2Qe79eVPkhFp9Ht6cttAwpsvW50OOkH3MOT43/bhR3qlHXw9FzH73mvP6QfYcJUcreraSjJt1T7JwKc2DBrA927FQOypHboq3Ke81ymsYhDTZBYhnAtcYk1gV1SOHQAm6EURntdAh28zgt68s3jugeu2iSfi544CPtx5H4qAK8OC+FsfdzUB0mCGPXEd3azZ1EexoJ/JMqJnT8x2LE4DNzUSKlx/dFpg6Nhm9NFzGEJV6vClyXICSp3U/pvurNCByWGoOi5G1p/wuVTrR0GxsfGYu5hRS5al5w++ZyqhcCzc9X9jIBZEz81o+2zmc1Sy8TqsB374usCwhxGmPNwT5ebJjoaEW+HfrAZetz9EQWjBoI8EMk9HEirJa9a8AnB2txAHJ7dnbm70RR9mBPB3luDWBxlm1I7FUkRqAPJupS3gliLMWNYWs/dIyrfRYRoZ8Zg2ebPnv7k8GsfMf3WRveoe/+NG/+psppV/4pDP9HwVi8ScA/FZK6QUA6H8BwBjzvwXw//hJP8CahHfnZOLrwlE52xCRq+/N4PD+bY+fXnpMJAFwN/AACwkZsrsVWNMZklju1UnmZZz/B0C0wIAX8p163TvDzS8k2mur5fQ2WCHbmKwvboIsxMiH+aQYUFori5WH6cMJYeOjkn78lxvq6zUY6LLzOLUJ318DX18SUemCxdcO++zWVloe9pfiUKl2xjMf8f7a4ksLdfNLOBU72iYaXDXs5nXmpmx5jb2d+YQYbK669TBtYFDZUatOB1OgrMXyfLA4E+j6VpzbONN2+HDjWfgl5r5okuFBEYXRjXwo7AKVIo9mfU4w1AOl3TsUAR6aSq5jMA/Row9uSZhclglfPejzpkIyGkdAR+WA37gocdGWaAJwULjMPXhjSrbz7WDFj2BExKhkSJkD0ook7OGe4sgbGlwVJmV77tveyNglYOYYQqTIlwUJYWrXnED4vLQJX1yoVwiwC5z3ntbcBHWTUy+ILy26MVTKJrSD3SvMeB81dplFGb/30azPh2ZMRAs06Ku0CW/PuWlph/hkx8NIPSyOSnbL9JaAjKxctvAuLQsbZZ/vv/poAM/3N3Vj5oCa2qllcWH4e5tAdMJbBvr1QuzWkdKt8DKebBMOS5LOhgjMZST2w1tqp+/JqAYAfrgG3pwZPCgCnu4K3MihsjUjivhCeE0Pp4OEeGlWhxEPCofvXhsclBZndcSqA+5NgAdTFtya/bMdDCZVxNsyQtAiVxVGjaho9BmdyJoc3Ovfc1xGRFi8aDyOqyBSa0qurzpaNV91Lqus6GA6ICTeO4CowLJIGamZ+5RRsbdmPQ3IBi2sOaLrtgXuT3p8uCEMrjP5UhCDk4q8GrXPv+ktfveavj2l5eGjRmgTUfnMiwQf2LQFOTSdGGvd9BYvGiKrOkbTjJilV4QLKNPIv5j4CC8Fe22ZZKsFvDdsyuhtMkAt6tvIkRu5N9xX22jx/q3Fe4sB768dzuTMUB7NWc3fGRKvnUrx356TnLkL5MYcFoxYsOCzcX8y4Eq4GtMfex7YnI6N44GkOidBUbW56iJQJxYV2zD6v2wGi5tI5VUCsp/KZnA4H2Rspgi0S7mo0PHnwnHsbQxHPBNBdUoXse55Xj6asXHQ0ZUxbBx+EuPhH0Vh8WexNwYxxtxPKT2TP/4XAfzOT/oBYU8poXPmb10B7y5Yla06h4dTznZ+7shnVcCqo6vZHcsZ8GYw2RfgpBIL70Td9cyP81rO/XlllETmMXYQGltcCNN4M5BvwI6RM//zxqF0LEpSMjlg7EBc43Tj5NiARdF2MDgpSSLrk4FLtGK+6jxOay76i9aLKQrfH/09Eh5vLJYlcjW6HhjZfFobeMuDJIIW6HpY6KxzPx3zsnV5sdpg5LA2WZ5WO6ptpiLjNUBOPQRGJr3OJ28Hg/VQ5NS705qL87IzeCIhYTEhKwP0579sSUa8Vw8ZztwJ+tPtHTTadWgMPRMzSVxcD+zKnmwNnu8cfv64zfDzQTkAEp/9vZsKxxXNwL53Y3LY00lFiZ2a2FQ2YuGlUJDfTWIYuQBqdKRrowsWvUl4tjW47hPeXTg8nPZ5s03gAeCsBkLxIK9l9npUcdb6cDrgZcPNZyM26Ecloe8mmNxB3kr8/GnNe6wz0T5SZn1SRlx2FgA3zQ9uHd5dcOP7j151+OpBBYAa9i8uOvydiwJfP+LB88Et8JVDbrIhASUIl2qHTfM5btrXvctpxK3IHG8HQsY3vXba3BSvOtXVy/2LBjHx+eCIyOFWzHwuO4s+OrG9TzCQWPfO46gcsqR4UUR8dEvi22kNHJYGj/JMnYWWRkOf1Rw9bQaLjzYJdydE3lYlFRaayrsbDF51Bg8mJEY/lFnyVefJlylpelQ7i+Mq4d6EDHp6pqi6gA0NoAd3wFz4TFGeaSXo0WsEmWOhfhQ6ZtLvOalC7ip53wX9k2fpSMYNz3cJ7y5IFnzRGPyhE3b5N0I875PB99fAL530uOw8ugA82xV5/2WhEPBq7XBSJbw9Y0P04aZAaYHnjcFB4QSGJ6rCvA+XLaidAd6ZA0MSN1GT8ErUeXMhuTdxNA9s8h5HK3xK2olYKDGTUk8WrxMf8UIUfup0eq+O2MIiBM2m4V482hPwa0G4UVs5N0qR79JgigqT+xPGPByX6n5r0HUcgU1lz18UJiM+ShQeIvDRFng4JWFS5amLIqIb+H6eS7GqiCibXEpie7kPanZ1WDLyoDBSKAkyNci4qRRl2pgny/11EORiXgRUVlCxZNAIIjTzHB2vBe14f11mbkntEp5s6dvyg3WJ2lKxqA1KHxlZcFA4WCS86j67sviHGoUYY6YAPgLwTkrpWr72fwTws+BU4QMA//W9QuMTX3fLu+m/8eCfxXnDyPSrzmI7AG/NA246K0xi4ItqUyyQqHa3yyLgVedx2XIxntUBExelwrOZAaukoZiA928LrHvg4XR8CFQKpV2yFZZ0EzibX8vMWVNGaS7CDVZJTiHxwGKwks1ERZWk5u4VrCJV5672vqvOkfswUKJYC/z021clHk7HawOQOKQb1UkVMkwMIL8f2mojdxoqS/txd9DtYDIPRR8MfWkgFxMN2fnMRNc8JEoL1S9EX6vO4YPbiJ875s86bxzUc1/llQrjf7T1OWpYRzI6J9XORh3rnAEeC6Sr94A/n3N2Ze93kRI7+ty7vMED2CNz8aEHaCikXbraaasbacrdAyQ/hQ9/YVTSys+tc8n9EUTt2LkOaZR/llK0jH4B7A5U8rjwNMdZ9+QcvGy4Eb45pbdBSNTMvz3vsBlc9lNwhrNai4SDcvRAUaOcqYt4siNxeVkGXMgIii6O7LIUul3IATIkhoZxTjygCxbfW3scFLTpbgJw0QY8nDg8nIYxrdSkDNtf9/RJOSj4HNwOOn4cR5ojR4D36LgK2U59f4RxJcXFfUECFX7/cFPgoEi4VzMoauEDrnuH88bgS4uBBYx0hueNwbIEHk56/GhTZFLwVWcz6XrVkVxXGDX0ep2MGmSdfrDxYvKEPXSV92LqR0Iziyz+fI0EUAM0b0dZLvM5YjbZUx8UprHSbA2yd6gh2HXvRGFAguWQDO5UPb6/rtFHrstSUCtFKRoZVapJ2bUkSivUnxugOD7TeqD2keS+fdS4TwYXjSAHDsJ1SzkhU91INc9o6hkHrtdGvRduB+4xB8XYGB6IV4c+u7vBYF6Q36DhZlm9IRws5T3dqXs83xV5jLWQjl1zT9Tt1BlkpOKwCHiy83g0HXLxo+nQGhK2ljGZphfr3heiyU2SIphzH/G88VlKreOLeUHZqrpw6nOjJGcniKZGL/SRyOzMj6aHrRSlp3XI60VVH7oPKcdGf7ZaDehoZDuQz/eanbjccz2nmkDX0ae7Ag8kFfYv/Oh/8x/PKCSltAVw8mNf+6/+fn7WdrB4OBlw2ZLw9d5RJ7OqhKYz+PqykyoNeLYrOSOSf/u3XxZ4MOEm9+5igGYWPNt5IRFx86kszZvOGy9JmlxUai/cyeiEuSXS3Sc+bBE0FJl4ynZ0jjp+7rGb7wQh6CMkJZGzfDVYUQ04+RFkcQPARxt2HQA3N33AARJ5AGBnDc7m/Np547AdgHWfcFqxQ+Jmyvngy9bhfJfw3kHCD2+JeByXERq5C4xzvbdmPZxsPmpRzY5htGWe+YgD2Wc2AzklDjQk2ld33Ipp06/cHTLr+LQO0tUQUvvejcXPHA2C1vAQ+Xhrca9O+O0ri4dTQtw/f5wAm3IxsSxCRi9yPkk1ACg4iywi/sNLj5PK4OEUmFke9so0rx078EUxBjPpPNMZ4GXrshnZrTDOdR7vDAmBJxX2Hn6VQcZctKpZ1FktxLvEa7kduPnOvMkHpzVKnOTGERJD6DQIbCdjkO/ceNz0NWqb8Pa8Q4gFLjuaD31w6/ClxZClZVNH+evl3qwZgBgJsXgM0WTkg52ty79zWdI06UCsru/UvWjhmSy7X+A3weDNqYGzIXtubAYiSjqvBWjDPxcnWcDmWfEmUmFwLIifdlYpATAstC9bKiAmjhvmvTpkwiVHbQ4PJ3xGn+4KHJeU3DXB4s3pGKE+9zz8v3bIkdlF6/HFBfcZ/n3KfC61sN8Iy76PJnOWjksW0a86h7Na3kPgc3RaEjlhMqfZGxUk3KliLij6NFqR76QJWQ+abmlzQJsiokkOg0XF5No+GrxsCsx8ENkuDx31T2kCGxRjSE48F2+Zp7sC543Bzx+3OKoMvvnK4t2Fyx36q25URj3ZerzqDPeXmpJ9Te68U/PvFzKi6AN5J7WLGfoH2KGrDYAqT2Z+lDwq4qaF77zAayZy3kqBrohl5EjqquOYuZGCQg3G3p0T2aIrscGBEJI3g8WP1sAX5pRSUgFDyf95w/eqjQnJ63htz/ng1mHqibzVjoj3VWfx7rzPiFPpuFdpl1+YhMKpRYERNVEQbpDNHhlTKVDaaLEL5PEN0eC8I8rbRa7dt2Y8A7aCViZAcqBk1C3jD+XheR2DR7roApRoP5zG3LykREPJdW9F6RizHYLel3Wvqj6ind9bl3kP/rTX58J5U1mwqqJQPsNZ3ePJjh/i+a7AsuRMCNC5MWfZU8+C4J35gFvhM/TSjQ5ymAGcbadEAuHERdyrWanrTQeAYbAyhxTylUn4zo3HR7sGp2WFdxcWjWGuCQ8bqTCFuLmKBm/PAwA9WKyQkEw20Fl1Ln/20lJaendi8O6Cxcnjrc+2y0cVoamfXu7ww9saE08UQxf9drD48gGhzsebAvMiZSvkwiS8u5CMgZqIy0Vr8cFmwL2aig5rWBxEAKXAa03kNVITmV7QCu0UmH6YMHfjqIJpp3yASYS1+PZ1ifMm4g/e4SbycvDYitnWewcRtzImUr7CnSph1Rt85YDE13s1O2g+kERrdLETUeDXCusyyXMTLL62jJmYBrBjqh2zNzgzTUJYYlcTQVSGFuUaV86NSguRSxlHlAL/sgsImQG/GSwupeOmj4BAmeJmV9uESaUFTMpeHhth9L8977MPyKvB4NnWYRsSzmoWIsuShdSBJFXOPNU9WwBfOeAG24dxQ9YgOUXBugjUzuG9BYu9gyLksaOO/J5sPQ5Fw8+RhqbOuoxqOQNUziBEjhgPCnbEhaGyZ0jkMemYJkFtqm1WpFjpxrxNKGR0xxEWC92UmErLpGGaOVm5jySKJvQSIljahA83Do9mNKHzFnI4Orw57fL1LVxCb0cUSzvP57siZ0BUNuWDVdGFs3rIHfqqNyRUAzkz4rbns50ATAyRjKkjefhl69FFomAcZ3K9ndUxHzZ6QCj3yYCjHIXyrzteU65jYD1QCVS7iNvo8KKhLP/tOQsi7dS/fV3gC7Pw2gGwkPHhwym5Xf+Hyx/g1w7fy4f6xlo8mPT45lWJF43HQRkx8XxfNx0bB0V9aJ/P0cFHG4c3ZyFzfAC1vzdoA9AG+qRMXcKjGUmP9OOxmbvD6+Fe4+UoqTMEBsopwqoFsBaiV53FR5uAnzsefVAKA5xMBrEhp+Pmw6kTjsUYvjj1EQ+no7wSQA6KPCpVFDAiXJqyfFiEPO5rZG9vxZNIyefPdh5ezoUEqp4OhdFcu4jvXHu8s9AcKXKWTkqSt59sgT4mPJzSvEsRwI28T+VsLYuQC/bDYjSr03VV24THjcOrluF6u0B0/kqCPmc+4e05id1r4W/pe/7KQYvnDQv1tZyLup7UMfnTXv/QqpB/FK/75Vn6bz/8Z/Ps9snO4/6E1fFxyar9g02BBOANmUcfluwQF8WQSXWNMFeV1KaHgzWjcYnCSzqjWnWsWEtx4VxIgbGVmaeFxv0STtzIjA5gUXBYUEfcxxG27aLBVipzJbLd9DaTR/chRmWeF5a69ye7Iv9ZR0P6fV852GHVMUvlR5sC9ycBz3ZELR5MqDh52Ti8Meszq/p542VMYnPqnzL7d4IwKBRpBFK8ljmfGlwxY0VY2z7gyU7HSDG7TvYCW68lGfS44kbTRJPj4XfBZNXMHUkePJbrsR1473S8NZPRBMdJMVflzvDguJUHTD3x7036HD6n1+tSxkaPZhEfb0k2u1MNWaf/N1+YnGz4ZAt89TBmQx4lOR1Idx+Skbhl3rv9nANFqvah4lt5SCdOCHV781A9UFSOO/Oc12sCqDPIDqsqkXvZWpIoZT6qa2VZktT55rTD86bIv/+4JMrxcMr1o3A3gAxlbuQ9zsVUadVZnFYBl52TzZ7GTMotmbqUbfCZVkkV0kQSfa3hAUSSY5Rxz7gRNoHrQgmtKgm0AB5vC1w07IwVQq/smEuho6qZqJu8pYLg+Y7Kn6OKY5pX3ZgLo12Xfl5ltOszdlIN+HhTYCKo17p32QGyEBlnF2jyRMmky8jbxEc83nicirx9M7isXNgIF+akCmhlTQ4JOZ6aJllE9i4kHO9ATJKuWpuvMbt6FlR3Jx12g8PTHZ9nL511L8+yNynbdZ83RFyIhrLRUSmyFgYAckF1LSM3XSOHRZB1GfBE0OGFyCAn4oejo9qbbswt0VGjPuOndchKpP2Rm6r15oLyAWxUzhsxgeuo8nhrzn1LCaD7KIiOMjTSYYhGpJE2I8N36g6PN3V+7tRAS4mbIbJBVML3k63FWZ3wcMprrVkl2nROXcRvvXK4O+F5QRVLFJQj4a8/T3h3VuJOJWRVyZNaFgHnrcdHG9oITL2O9Wi57QzX26WMrx+J7F3TaDW5mf8/5kNeTSHViVqRk10wWIiTcpT1SJtzuvUS5QN+sO7xs0f8M8cs45r56sFI6FWeI9fMWHD9pf+YVSH/0C9rkGeghbV4JH4NACvWxyLZvOoszhuPVQf8vdWAL84rvDvnnOm7N7TDPqmSVMvkGWj1NpOLkf0v5HuWZcSyHOF+3Yw0Mvu2pzFQE3hhVarXyg30hqSiwyLkbnrVsZpPyaCNLFbIHufPKEzCQRXyXFEX70qIawBRjbdnhGxvB4P3Fh1+ezXJ8/G3JZWytgnzGtndTsleFw3VFvcnwlAOWjmbHB1PhQYPIfpAUElxNKc5UBdGyZx2U0zU4/XS6PHaRXj5LM4APZSkx6+teouF5zz9QGzILah82AwGR8LmryxyMbLqXWaw1+K9AYyEzu1g8HPHLb57U9HCeq+Iqi1JjPTU4EP/3iJiWfb4zVcTPJwGnDceb80NXraEPd+ccePSyHNnyFPQ4paSU/pZLIVNvn6t6DFU1ESDO5VKUNnlf7hhgJweGEtJK/Vmn0vAQnRZkiTGBE6TxwlvTOlJcFSx4EHJjW0rYwcl02owls6GlZPzs0eDrF+OSErH+3BSJXy0LWj0Nemzcc5F68T+3uWCU0c+z3ecRZPcaXHZsvM8KiPO6oAPNh59tJkYpootJto60dKzIH2xY6jgsoh4a0ZFw03v8HRHkuR7C2ZUDNEIfGuy/fjHmwK1Az7aWmyGAmd1yKTSb76y+Moh3/cHm1L4UJLdUgYclQOebEsqA2zCx5siX1uVU2pRoU1AJZwn2CQ8j4AnWweA73UhvghHpXrLUM6tPKCrzmHVWiwLFoxDGsdlWpAbw+ZjKyTN2gdMS7rAWhm7Kcr3Spw779URL3s+77tgc7GuKajK3dH9R6Oxr4XorMqtpUiLL1pPErgQV0mElWYtmdc4T6WjekkR1iEaLEU1FYRDpKZTFsCHm0IOQzZdGkh4Ld4yZ3XI0fYqPwbGmPEbiUhQX5zN4JhgbEiM1rE1OSoez3Z00jwoI6YmZkT2ADqWsVkZclwm3JtQoaYcC+X3bAeL3hr84knIyMmTHRGp+5MetYv4yqLCUor/IdlsP/94W2BZRPz8Mcn5x+IhMfMQHx7y396Ycoz/0bbEqjO46RNm3gjfRCW3EP+WlHly5yKLJ/ePo42YDKqgaxmYSVK1SswfTgIeTQ3aGDF0Fg8mKg02+PLByD3aN8Ka+YgyjgTkz3p9LgoL1fhrQaEd6dszQk9zn/IGGR2wLIFHswKVZQLfZefwxhQo7Ogn0EeZV8oc/LzxWblQ2ZSVEKpx1vFIIR3oK0nP0yh1fXmT0KexI3iyNfiqOH+eizLjqks4LAzWoj3/4a3HmzOBgC0h+ouWBRI7UxZBD6fsRDWxVe1jj8qI761LlJYV46pzWMGJFWvIuSgWzKGYuYh6OgagPd9ZvHfQ406d8L2bEpUdVRgkd7KDcFYlqU4CjQhT6saopFWtshuRHV0L2qCaaw1aUqIju6+AIfHzNEKenDhu3GvpQGae0GptuUm8t+iw6mm7raFtT7YWX1oM+Nohi5O551ho7hnC9mznUFqRrsqM8eNNgTt1wAebGo9mdCg9rXh4AlwD+7NehfG3At+rm10EOSpKgl11hHMXclAeVSOqshts7tq2goLM7GiAo1Cy2gAflbRjf7J1kkcz4ONtDQOLN6eDGB9xfDERuZuSkenZUQLgpqPjkLfmI1z5dFdkPwpAMldqFhm6AXLsNCIv79963KlY4BwpciHW8EkKgEZ8ZZZi9R0TA6ASRv7JVUvr+mnNZ1MVAIsi4rDktVj1Ntt2N5GdnIaU8TkD3p2TcPZoFvB85/DWjJLs9w54PbQZAYB3F8jKk+1g8e5ih2e7iuqznlkoXTToOodVR8LhKyHvQd6HwuOLggqbZUmi8VSK5KOK739UW6kFNHJGxlyIzS8bysw1x0ULv07W2Y1YtU8996ODgrwevZeVHZVYSRQOyzKisjZ/bgs+q6vBwiaiRtqNWyQ8FNmtNiu633ZChVEE7F49khYLw7HeB7cOD6cxkxgjJGwvsDnbBbr9RlDhF2Sv6ALFrhHA4y1HZ5Xwtj6+dUIEJ5JizWgYRR4Y38NMbOo7Qc5SYpFW24QnO4svLmLmK5QyxlRL/pkHPtwAhz3dbO9OOhYLIiHXkDqLJHspfXEeTobX1pMWYwDw/bXHW/OALy6ILNz0Drtg8daMXCQl8JaW9t1ndcDjjRNFWcK3Vh7vLmL2UCKZUtU2HDclQLhYCZpQO7Ep70UcGSUAJqsY9ZhaFimTcgFkZaALVjJ9GCBZWmaCKBrd9BYfbYmqKCrxnWuDdxdUG9YyKtQsqM96fS5GIQ+rs/SH6z+DbxxJVWVThnH/g5c9/qmHRhwReVA/3zmcN+QP1DLP3CdZ6SfSSFu3x7w/KJLYXSNnaRhwI1ELYACZsLLwZF9vBnI3mmjxbOcyca+LHM/cCF9Aq/l1b/GjW+CsloAteUhKSyOk4/L3BrkoFKfVoB7oXTT45qrBr94tUNuIZzuSqpY8S4SZzdnYsuSBu+odfrSmBEpnZmpRvRV3QgNk/waFpMccBBJBlXOg7Gc1rNEgHL3mXQROKyo71AHzqBzwbFegtISad3sjqmc7flaVQKl/iZKnnEitdEO76l5Hsp6I1e7fOO/xS8dVLnpWHY1+jsuA76093p6HUeM+sMsrLDfuwyLguzcF3poz4vn92wJndUQl5NwIwtdOvCpWHQsoDUTTdcNocochcQPS66YR4apsUR8RTbNUJEhNlk4qKjUWgupctiweAWTjHlURvb92We2gv1NnoToa0k1S4W9VPuh6bYRgqutWpbrO8PcPkX4ezxt6etBxNGY5p0LbT7YFvIwWnRlt4a97h10YkSx1pmTnPSKIquBoAhVGSmJ0BvjmVcB7C86Dv3zQowlGJNmjORmdBW220l91bD6WZcCyCPjmVZmvFYA8XgVYHEVZT/o8dZ+wZ96RkCrdU3R/WYmc0xrgvEk4KEYDv1JCAcnA16J6jJTvEyWHEx+E8DtC+oqSvGwZzHenDnmEWdmURyBqcnTRGLwzZz7KR1sSorVYBgRtkWuuxYbuMVMfM1JY25RHAKp60yJDR7O6NjiWidlcSQvuyskI1aasMNLRSR9HRdyqo2pIfRhOqpCVP/q+1AyujTYT8NtIdDUlkkg1PfRePUiirabE0thuIpwQ3f/zdWgc3pn38tyHvDdpMVdajkWuOp+RQUVAOxmHaZz41HPEclTxfl+0I4qgyhj6M7GBCxHZzVf3g6WEW+pLFWml4+81ew2bjv/Vbr+No4GdIsk6pnqyJaI2cQkfby3mHng45XhQU6MVAWqizeTPIRJBogeSzddF9+z/5bP/9aeOQj4XhcXd8m76589+LR8Op9WA33rlZN5KtQQAfPmAs8pFEfE7VxZvzEboXzcKALlapE04uz3G+o7OZWokc9n51xAJJevpTFRhKjXHUhe8ZZny7FGhodKOhjFPthanNZMI35wR7r5s2X1qZ68EMZXtAeI/P+EGoTJCAFkOpvM+JVR5S6nlVw9J/rtsHVa9wRcXQ05ePROJGbBnjSvdbhMIv+r3qoRS+QOq//bCr9A4aoW4pwLNkqnO+6Ezz30CXuleR4QASHotN1VlIu+/tJhRbsu3rizuTkx2D1TH0NNqeM3/4rp3eSa8loJQ0wgL2Sw/FNvafX+Nv7+KeDBxmHkSVs/qkLv3kOiVoXHT+xHVE89ibzuQmR+kW1QvkFLWY0qjadAQx7jnkEY/FM2DWIlN9Waw+DuX9KBQPomOg9TAZ/86KS9lWY6WyftywpMqZPvjR7ORu6DPj46pzluPOxXJx07m38oRUiKr5pwYjGx/ZZHPPTk/Ks07b0ZXVFpeQyTWEEtn8RYpmdbIMSI30RcN83ZUQaXoVkjskJU/MJVDfOIjngtCA3AcpB3WfoG67+yqiNiDSYdV59EEcnSYtjuuSS1KusgR6U1PQ6jKxZwbUtuRK6ReB9rAAETx1P7+g43HqkuSxmvyyEihbkWYKhuz9HdeaI4J98eDglH2HCNxD+G6HN+4xZjboXus7jHnjcu8Cx0lfXDrskpCn6e1JBeXFrnbv2j4TJxUKUuF95s0dVRVvw0tshXaV3m37qW1FPR6iKmnjzcQCbYRtJTOvQDw1jzmNX63JmdiIkVIBPCDtc/maWoad2/S4aIlinTROPz2dYM/fpceFKWL+O5NhdKSpDsvAs6Fv3Sv7vGbryqc1Vz/6sC5X4tqptJmMIIeUEk4RIMXjZfU7Zgt7Ck9TVnlFIXTtws2r01VsB2VtDIAkF1vGYpoMleD94D8pKNSyMFS6CqXgzYGyAXYeePwYDLkEe9qr7irLdFMYCy6j8r4+edYeHlQeehwjkeFBBfwk63FVw9Tjrjuk8F7Bzzwn+28oAoRz3d0prvYMzI5b5g3QlY5YB2AxBushcNBwc1OH2JvqQbRm6SdWGkhZExkOKowCUEgX/rAexwU4zJ7c8+P/7ikTEnZ03PPxX5v8voIRB/+mY847ygdVcLNDMiduXbyZ3XCi53P1uZvTDnmKAyr1CbabMmr4V593N8A+F7bYPC8I4kVAGbSWfaGG8FK1BBDGmOO+2SwaRmQdFhw/LLqTZb/aTZGI3HtSR5BRXamjpvX99cVnu0SvnJAadq3VwZfmJE41AfCq//YXRYIamUNiCxu5/NBp50HZcQW76+BmMi+PpCI4/XAB/+q5WGn1rjHpcejWZCNN2R3OSfkrDenKW8gq85lPs6F/JyTioRGWl3zXjfR4FVnUVl+j6aoqsb9QBjdarSj83FnbJb2/bG7DrVjZ3UgYweFrQF2kiqb1Dn5/mF5HV32buD3G8ktoHOqekI4O47PjsqA685LhgS9F9QTZikk6FuYrIEvrMkFlR6K9GUgwZPcBjLS90cyR+WQCy5d+z6m7FdwOxh8SXgWrzqHO3WQ9FFmeQA8RPUzA8gBeHqA9p5KjT6N60PRm9vBvTZL/3BTQbMztGC+HQzenfcYEvCxzMv3XWwvWoNlaTN3qU8GL7YWdyr+HLVj1peO2y47h5s+YeoNAFq/H+6x/CkHJHl3K6Mbyl45ij0oAi47D43fbgLX/XfXHX7msMBU+B37BffUR3xz1eC/8JAcKpX56/dpAaqkX0U3pm4csekzoX+aeu6LQ+SBpp4kU7k3CtNrE+YtDQkfbzheqiwwAFB7b103+nsqC3F7DZLTwWe47mkmpxynqZCraxfxQuLe+wh8YRby/VdPmOuexeNJOeC4Av7onRJPdjYXE0rOvGiZ/roU88LffFWJQsvkqAZt9s4bh79/3eOP37Ui//TQNN6ZFG4P5FlTHt9FY6lqjMAmjb48ABsx5bVFaXQ3A1HAEAGAKDm9kpzwdngvIojOMBF2wKrzNEoE8vvWIDNvEu5NyH+a+T4XiABtIGbSuJ03RFg08O6zXp+LwgLgzZz4iKmzr3Xn697iZddhF0rc9l7Y3qxwn4hXvSog3pwyie2k4ubad05gOIf1QIKYdq3qCKnQWgKJb5vADT3ITVYUZSrwpTHcALRL3Mrc6rJ1+N7NgJ89cvnGWBA6VrkapXAWX1p0CMmKdtzixKTMVFfCIgCsZDQycxG9N3hUDdmamYY4/P96rcZUTJITJ56mRs92BZbipvnx4HHRJNROSaqEbc8kIyHBi1f9qCC56cd0UnaEKcsqAdr3Hoo/hjUJ88R4Ya2SVdlQCndCD56pC7hoS5xWXe6Y1IToG0fsJFU/rhCtzg21K++jEe6JyfLb04rZGm9MB7w5JeGRVrcMAtP5IsAiaSbEr3cXPHSebQ3s1OWYZ+0QNA9A14OuIY325rXgbL6wnJk7g9fMv256K/JqcnBOK6pBSilwLkQpc1LRAp4Od9TFl7I0nB1NclSK+4N1KbAl7yuLB5cPDJXLMQlzzAq5am1WW9z0DiflIKFWNNVRCPtV63A7sGi97kk8ezih5PKmt7hTDXRQbGj44wxVQCExynsQ6F6fh1IOVw36OyoHfLQtsB6chGjxeswLk7MhGATI92oMRyJ9JDlQdfgnFSWGfTS56FS0QkcDvUDyDycDnogjoiqTzhuSk0/rAm/Pe0nAdfjhbQHN+0jSXWu3S0Iy18bCM2585lnMP2989myYOl7jzWCxAZ+ft+djCJoBC4jL1uFVRzTiuExwSNklVjOTdoMFPPIY6544VjbBogsktX7vxmMbWKzrGGFZBPzq3QI/WDt8+aAFJOTwb7/0+Io0b/smgV0EtgPwzVXAceHwxpRr7mVDe+4miH8GOHJVEvk9QQ4URbruxzwga/n81o7NTTYCkzHuhRAQF55FBSPPDb5343F/Oo4y7k0GIaEnXHVMK9aCdVlwDS1r4QbB5v1KA/yIuvCevX87quy+v+aa+MoBA+b+1ssOv3Rc4bDgvqr7jv5vC0gMfMKv3rU5guLBhDEVisC9lFAyY2jkVtiI04qNEonfNtuZAxDH5NHpczcYeCnedfzGImUsJhZ7e5SeX1edzyMoNV8DgLLknroVB+TgyMWqLInZ6gStqPBhQQRNkeLPen1uRiH/3Yf/zGvwv8LfAHLHn41+9mCuEA2+t2Ynp5CSSsOmPqEXtYGm++3kYGPnyyJEK+Q+ckMkKSpmsxny+yEZABDSHBngFshOfBetz5IyHYVoZa9kSSUo7kPX+3Nwdb8Liazj9xYdPhBi3sNJnztLhSq3A+HJL8x6pGQk+GuQDZoyp4k4i657K6xliw83BsfV3jy6iHgiIV7LQnwtbMKxRKSrPfl5YzHz3ASizPOMEDkBQuKaJgkAT7YOj2ZDRn828rBMRekREnBaaT4MUZWPxcdj/74rcfOtecC3rizenHGx78/+VDqnkOe+k6LGtW8Gm61ulXNxXMY8K5/7lEcVH21p/63X/UVDiN9ZiFRyVP7MPNcEIOO0hDx+qd3YNermF9IITw9pdFlcFDH7Auh1103+pmcRohC1FrX6/9WnoJeNwNmEx5sSX1o0Gd4n6Y5jtDuChBVSWGm418uW8Pa6p7kazZ5o161W+fvFc8R4MKp6RMcFBsjsdY1MX0gXtw00BLrpqaRRPo8y5S34LN0OVNcsCn7WpzuLdxdDVjno4QXwd+xzBM4bqocA5Fn5aTVkieh6IDKim20XxxyN88ZnFEbh7SBd+cS/bvnP4L0RjVRewlxGVZWsYc2+UBn33ckg2RDj2GS754cyExhc1QAMgxJ1QxhDtBTi14C+2vJn3/butWJLnyUdHeieqoU6MPrs6MGkzw6ArCh6vnP40qLLKatdNOJ2nEayoBktxRmMxwJLfUzU90RRW/IQgLNqyD4V6sZ6KGqnVUeVBDCO0mhuxiL4qqNKRl0sjYGgch2e7EosBYlSE7rNQDRCeT37n18lyd+7KXEiseU6ftQ9G0D2rHm681kVomMobTqXRczjsadbutQeFgHv35ZZnfi3XnZ4UFe4U5FrZAxyUF8TTObJqHMw36PmVo0k133pe0zcg++JZPuyc9kKYRALhtveCCHcZvdgbVpeSSaKSnRnMq65aP1nciw+F4hFKaQuwkeEcK9l/rQ/U2ZkrUgFZx3WvcfzHeG0k5LhMh9vWYGrpexNzwd1XvAw2Q4WwTLufEjchCc+onKE92MymUugh9B1xyr0rKayYzdw5LEUxvdKoFe9mQsfcFKZTKYppPOzP/a5NWHvtBqwKGyOClcDo7lPeLwp8G+uv4v/ytGXeCgDiLJp6Yx4iBbPdgX+nZvH+GPzR/IAsrufCxdAo8CPwdn3Vw45rz4qpfuyCY9mnO3qpn7ZeTwWGd5BwewNJT7Wlo6bLxq6Fi5L+gtMnc64ubQOioTfWTk8nBJeV8vYpzuPL8x6vOroFHpUEap0PwYZ6/1/sqVqZtU5fOMo5Bkgu+fR3vu0YhT8zZ6KqIssCJSEq+mAZ3XAUmKvL9uEN6bIB6IzCY9m5KB8IMFxhyVlxn0Y02vpMkpi2BDJVZj4AbUUJ9vgcgIngIy6bEVREyUWWrXzFy3JqkpqLFwCHL9viBZvzcLeIZ0yv2CfZDf19LhQzfn76+o12eSyCGicxd975djNSjHV7fmMfGFGZce6t6KOGnAWDS5bj6dbdtPLUvkqtNM/rohkpMRrPZHO8rrzWA+KeBk0BYl4y3JAMTise49dMDkllpwnol/esMs2oKdE4emuqx4cDyZDzhi66izenjGrRf1oFgXHPbp3LAsy/7VAn4qZ28KP3AmmFwMfb4BfOKHy5N4kYCVkuJkPuftkTgohYq5HK4UEm5kbIduqamrVvc4HA4hS6ObOdU8uAcBuWl2AS0t32oljkdOIX8EAKkVWg7hRBgax3cpnXPXuNYfJdZ/wjaNxX53J9XrVOdybKEozhnz9YF3CTVOON297HnKPN0WW5h4U4iqcRodS5RgcVTFLRxVdPSwGsbMe0b4DLR56J2NajhVVSjrzEWcVR8aXrcMHm4C3ZkTXLluHiSPK0SeDi50kEFe8TgeDy7L1LpIv1AWLu5MhR8lvB0rLl6V4gch+flJFPJh0+HBTobQJf+tlh59d1q8lxTqDbEx4pw54f00lYGGIbCpi+3zn8XAa8n2/U1ENtuos/uidUhphlRsD3pqMhly2LvvOTNxY9PXR4La1eLrjep95FveKPh5X6bX3eSIeL6VjcfbXbp7gTxy8gV0Ym/hnO4ufXg44rdjgT3zKIYj6sz7r9bkoLHRu/VuvHL5ymHIXflbzxp1WPf7BdY2lbOaXrctmQMsy4vnOYu652N+acbZ/Iw94L/MpdXdkh0HfALUkdmbMNqDNts8zrZNiwFRmrZqZ0UeTF3DMnbrNVfOznac6QrT4F43DSRVx23ND1kwSNYUCgKt29F0AkPXOIQH/dPoyFn7IVt2Ptz7nhDzbWXxxMeAHa49fO34DbUx5A1UHt0czXieAc+qpGzXQmwEoLEdJc6/Xt8g+/BOxpF33RE3mfpwjZ5c7q1a7HNHUgeiLoh4Pp5wJrjpNFWUReSsFVEg0CQoJeLyhO+T+ixbLY1dV25Rd8EYJLGG7yibcm3QwKDDxZoTEtx6rzmfi25064OnOoxIDm7mng2EnRDNvlLxKLX9hEz7aODQBuCd5Mbtg8cGGY7kvzAhxMn2T3dqQTD5grASQXTQWd6TofL6zORHzKnkxKkOWwKkd/JWQrY6q+FqOg3bpXaQVs/IG5p4FVp+MHBomO7Vy06Cr4sOpQxuBuZCb910P1YDJZNmjy6PDN2dCBBw4RrlbR9ypDNqYslW6rjOAh68Rns5JyRnz853H3Zpzf2eQ1QAnVZD8jJTvQWF5LT7eepgATET/v9sz/9MxIr0+Bly1vG+1jfhrzwJ+5azInZaiR6sOeHchFtwDEZ+Jj3i6LlFOidbc9A6vOps346lLUqgYlOI0uyhibngU7QS4iVeWe09hEv7eK4OYAr625HoNwtkg6TnmfBZjgIkjaVpVUA+nA55sfR51AsDGUIn0xUXL+wMvCBlRgMICiAZ36h7nTSW8GqB25jWVwybYTODs5P9rwaAZGDoCUB+TwyJJ2BU79dIaqKCBYX4kIc4LzcRhgrQGiO2GEm1k4Uq/Bou7Nfekm54jgZNqEPSJz12fLC4SRyp3qog/ciehCTHv5w+FK3NSDXDG47whGrGCy0oZHRXMQCJvEm4GPyPHjuTAyCFrqGpZ9z5fr185K7AdRjvyqaDQesZUNuEdSevWbpKfi9yYQ+EtOZPwYlfS8lzOEB0/6/7soWRMRgko+hUS+W5N4PXyFvhDd8RePNqs5LAmSb4MG68o/BdFuQoD/Lm7d9HFAAuLu/WAFw3dXb+/LvHmdMhCg32J6Y/nSf3463MxCjlyd9Ov3/+1HBBzf8L53LuLHb57PUETqY2/ainn2QxM71R4SmG1ucxmlZAYIju9ozLkjqEJFs93nDmrXa/KeozMQUubcjplYVKWsgIMVAoJmVCpKMRa4NvCAj9aM3Hxuku4P1V0AZnAA4ySu/O9mGANxzmRsJdDCR/Sh12lP7/1isjGzx7zRnfBSFASsrzokXScH21cNnR5NIvZvAuAqFt4PS9bg6e7gAcTh6MyZZ95A+TALv18Otdd9ewKDgrCm3oYqjV15SI+3jr8nc1L/ML0DiYOudO6I8mPq87lsDXNNahswlndZ6j6ydbi549bdOLW+J0bjzenMcsE313wuihMqa6WF03Clxb8HH/rIuLtWYFlmbAsiTS8aEhSU0fQiSPyctValG5kYDfB5G7vrE55I9qff2qRpVa7cx9xLQF6+26rWrhwtGalaLWZh6JhdPq9qw6SUTDyBIY4WnufVtwIlLiqyJ92kJciH96Ht5WZP/GvpxfS+p2mT2o7veoM7goDfuoTXrXszlXlUDmiOMcVAwOfNzwU79Zk1+t7BvBa4aJjqeeNRxuAZ7uAt+f0jlGXT11LM5Ei68Ydk8F5Q5ToTsW1NxNk7oNb4GePQpaWAsAP1kxKfXfBCPWN2N1rMQYgOwxeiNmQXqMI5CJdSdk6RrE63hssjsqQk4N3AXi6C5g7iy/MeRhMxTxLx2MA8GxnsB0S3ppzb9DMkSGNLqwkvI5s/yZynV6JTLCQYlbfK6BOwSxSlN+V5+o24cGkz5wVlfXrmhu5FSYjgIVN+P66xKPZ6NhaWKJ+6t2y74DJ4D+LZzvgjSmLUXXeVRhelTHOIqvyOvlsiu5ps6eF4HYwuRFQ3pNmwlw09HxQ7pGzHCGERCWHPgd6PeYF/VQMgDentNFWubIioBrIpkaFOnLTEfY+YVivn6rRnjcedyrmNamMVkeMumYBtT4XXw5R2Gnwpp4XBwXHGNnZVHgOtRtH1Zetz27Rmkis6hr6rIwo17KIWd7+ZOvw7pxKxa1w0Bae6cKvhKMIsCHVhOSjMuLJ1uJfv/ycj0KqvQhbVTZMfcTzHSHcI+n4DuQQdCaJrI+OYpvB4WWbkGBwXwgzz3cWpzVHFYx55ez9pAoINS2L+SDz50WB5DTOXPkYyoRXj4XKcXO9ysRQk3XYqpH+6pJjlC8tyAG47iyOS/IOvr2y+MUTVuK6KCnVi7hTB3y89bjsStyfcHO8bB0OyjHt8KAI+Nlj+hjo7BtQR0rgu9cGZxMylA+LhMMi4cmWbOFdYES4Eqm0ozyre5TWY+GJyKhaZitws5J5AIbZrMWnISbgrfmQDcWmnrkjpVjtDtHgjWnAUXmCkFIOtWrAsZOa2thkUFvKqwpLMu37txWebGnx/Nac6bXX4qZ5VpPMdVIFfPWQ/+7bK3I/AAv4KJI4g4fTBi+aEhEJd6qEN6YtfrSpcKca0EZaCAfZkXfBoBj4wD3dedSOB5kzVCF10eCicWgCD8B5EYQYhXzohDQWmxE87LNLHpD//+1Ai+lWNnDlWKjMdzcQBu6j3SPmsegYhBcxKQd8+7rA2/OARTEGCVGW5zLRVc2ASst8lu1gcW/S03/CIhOLd4Gz1c3AEaIzVAiVLuKhGGQt5c+rzmOILMZPZAxTO+DtOe/NNtB90MsG2qex6DJgMRxBa/cE4N0FEb1Vb7NJ1sQlvGw5XjHgelMn1PsTFo96Xc4bh4MCeGuexA+CCaghGXx9aQFIRkLrszQ2E5Kl6ZhEIXGXlLD/aA28MQMukycsLU3Gx1J4KQxd24THG0+yZcV7dX9iMgK2lOApTQHVz/TeQcgF3aoj8nFWc48bks0BhLXwIRLGQ1hVOk002Ip19FlNdPW8KfDtFTNzVoPNIzFylCJoJKjNCtfak47qBB2rrWUs0EeDy8ajsBDCdcTjjcPXlj2ehCI7at5G3ov3bw2OSh5i7x0QhbloPWwa3/utjEhyIRSRXWkr6ci1kSttyIGAGgLIEDfmgayl6Xk45V4MIBfx5w0brFcdw/NUZaXJv0fioKsvNSCcyZ8bGX9fdiwq9onkRxVHv4O899LSE0b9NSbCFbpXU1GxlkLoCzOOPmY+4tnOZak991NBFhxwJFELRIttfl5qxzA+dTV+JfyWVy2J6I9mRExuBzbQb05TVjCue/4eU7KQdQZ5LDNxEWdVj8tOItz3RveagvuHT0qcVD1eND+5bPhcIBZ3y7vpz9/705lHcd4Y3KlSlsvpYtJ4Wo0AdvL9p9WQs+gVbistH7Qhmgyl3akDlsWAXXBYdZzNRSCTNpUnobbfzMhIcphQOqpabiUXAuOMsYs2E+9mYnpDDXbC3zhPeDQt8M58wNOdzySZmAweb2w+LNUG+Ue3wGltsoV3aRN+sPb46kGf4TK14QaQI4w1R0Wd8LwdzVto1pRyoqmShvQhVg311JHZ/uGGccN3a4F29+D3JtjsZd8GFi4PJzHPVxXROSg0E8HiS4s+ExcN6GGx7h2uxOtCCZdzT0j9prfZqRJAjjjWUdlDKSJbmdtqBPlJRXTroy3w1UMeKIpmqJd+KVyRK9mUg2w4I9t6jJKfiyZ9UfChfrJ1Ig1M2fNjXlCe2UZyVvTeKux4UI5fs4YIzXlDAvHDKSXSD8Ttbzdw/qnwuvr4ayeqh2sbeVBrlLbamCsv5UA8QhSpO6t77AaqrnStaaCTZnxoVLySFZcS2mQNN8paus+VqJe8YddJi3sSG+nnwvWo7rHqGqqE1RcNiXsTl/L9eLJN+IUTokQaI61pjytxZ71oDB5MVJJLAbMxwPOdxzNJ8gWQJdULKfa3g83R2Yo4aUGnRDwNHbvpXZYBH5cDXnUsQI/LMUeldDGbfqVEBQbjBEbzKmDs1kc/lNEsrI/0pTBm3wOC90M5BVrg3fTjz7w/CbjqaCXdBIvHG/Jy7tUddsHlgv2kGqWNuk8VlrD71MVs9qcHLD1CRrO9zWDwzpxunS8aj5cSOrfq/n/M/VmMZFmaHoh9Z7mLmbn5Gu4RkZERudXa7K6uqmY3m82hSIoSh5gRHwRJFAbCYB4GoiBA0IJ50EBPepEwELQAGkDCUBi9SYAkSIMRBIoSh6So4ZC9VXdXd1dXdVdlVlRmRsbqq7mZ3eUsevj+/1yLqqxsTjc5SgcKWRHhbm5277nn/P/3fwvTln/vyuHtPfJBdF9RiflvXxj8/BEKabyLVK6QwB7LKFjfVysW4ec93YtPmwBjgA/F5+MrB6mQlLfB4GKgDwuhfnJB1NgJwGv3mp47RFwVZXm2pTmWNnjq8fIPngd847Au70FJzUM0+GjD4msTgHVg08N1xLXEZxG4EpKzAfDxBvjZQyKUH9yy+OT4mT8397peDTaBnBBV0ykyrONVVdyoUVoGeWuVcFdU7abXpHYJmgM189r4MAytiwzt/P7K425LhHiU/eRicIXI+eHalbPYGeDZdjL++iwfi89FYfGgOct/ff9fw4NZEtOgaXaukF6UA8tb4G4bCvSslaBKkFqby+G1Gi3Oe+DdvQleBaa0Ra3kNbZaIT6dHy18KgYtmiGhbGedbxkDmeOnoogAgA9u2R0QGjVlw6drminFgR4Uu4xshU5VQ37aBLx/60VjzSJLEYFeIPObkZu6mgcp619d7NRZDeC8XLXmjUWBrBW9aWXTjHlyeANQoF8ApQPQjmxXpaAKjkeLVLpCJxCickqYxupwr+UhoYx3YNcNNRUCmrKS1d1OO6U+cUyhCZ/qDriVrlTd7thVsAhoBI3SjcZZdj/KCdk191JYNmfq7xs7HZYzR0Z1l2jgo6jRzLHIWY3s2Bu3S/KixFIVMJpGqQWJwpEKx1ZyP9ReuyqHIYqTqq4ngAeGSijvtrGMpTTb4XcvHe7PjfhUcI0oZ+aloFz1zv1fB8LFk7SY/9Vwre+vKDc+aYCDKok00L5GLNOvxiaB0k3JIQFQgty0gGLxw0PteefL2HAmI4hffRXxxWWFZZWFdDmRYrXxeNFNVtb79VQEAJONtnbm+xUN09Ts6Inwlt5fedyOGV89TIX8eTO6cpBqGFtZp2aSQu4aeWkQH589kjQPq1hcDr2QQMlFgGzwfP0hij316NBHFrqqQujTZNDVJ0jmDw9CfYYoL0RRw73qXCGiNzYXDodK7cdk8E9ejfjqfoP7s1gC3/7gioaEH6+Bd5Ysep9sfFFl7CrPFkosrVLZM/Wz6SgrZ67J8164O24qrrShU0Werjldp/pnNe7TJnB3nau5nyqTNF9FidOVNKcXMlJSSWWCwfsrrst7M3b7WqA9vnV4tOC+exsMnm4zvnrAz6qF6ZCAtxYjvn3p8WcOmG2jipEhTcRJ5bCpnNYaNhokZU5jZd13tUnRtaLCAN1TVBzQJVOutQb5AcDzzhR579yxUL/Xssl9OA/yLHu8MZsCH9VZ9dVOFozK179zZfF/uf53P9+jkJypj5+7hI82JEAtbUJd84H9ZCvJlOKUeDU4POss7s/STyzCMWW8FJe/wzphWXExqskKb0AWx05Wv8qv0Gpe4THtri6GCjcj3TZ1JlbZhMZRVmWNJhby0GhtwlsLQnFnbRJjEzsdFvJg3Iw8CO80+bWuYkwGzk/zcD5MXJQzn9APDtfSMd5pmWhaW87yVYLbC/+jMho/bPDxxmNfJHsn4omxDu41F9Ak4yD9nNs4dUqVNaJJJ4ag89AhWoyy0G3iIXxcC3FPCiCVMqotNY2kuMDvz7jAF17ZyD2+d9Pg4ZxZAA9mqXxOb3WmHYqpErsAuR6SNrlfsYg57z0GEHrVB1iLise3Fm8teJCuBB3RxNGTnfHccRNRGR4YQa6Nbv4zDyQZW6i8TnNoFPLNmLqMFxJXDACnYGH6wS3HNpW1pcO97Pl5kjUYM+egLJgn334lrV4ME/Hy/VuPLwj5lQMAOajAIovJjLlwdnJmNP2RpAVfjwZVdLI5oxwYakn+4dpiWfE6A8DDuSluuAALDk091Y3sNgj/xxu87Al5e8uiTX1k1sHi0XwskrwEWyR254PF710BXz8i3+XPHntcjygjygtBnS4GOkS+6vja+1XE022FGzk8xmyLUuWHt0CY08ytsgyAUun4fkWi3YM5PSsAFAO+xnG8qPbKtHO3eNWTV9IJtO0tC74kG36CEpxZQN2M4hViuS6vBls8FRSdUeMnHYfGRDRWx8EaHlbZjG9d9rgwt/hXjk8Qg8EHt8AbM2DwBs+2lmPROmFfvF70umtTBTBjKFqDP3dSY+FjWYOAwUzI8Y/2VMJIWuHSp1LIRHm9gyqishbbwNGqNWz4ojz7Og4DUBAyzfdwUlhdSXpnY3MJgtTXvh5dGbHdjhM3Zi7qpnVkkddFI9eRBeHVYLHwvFczx8L8wTzgHz7P+KUTV9Jhv3ZE91VNq/7OVY139wJax9931FBR+PYeD31y1ly5lj9YVfjCkkXwy97gtMm4205k6pfJF/Oqy96iG20x87rTsJjpo5p/cbO4HEhw94aqREUg9NxbjTRQNGBDsPAs9J2caXdbi4OdPfOkifiDa4939xI+2XrcmwU0TqzWR7oV7+YGqRfJS4mGuD8zwPWnneb8+lMVFsaYxwBWYPZVyDn/WWPMMYD/E4C3ATwG8Ddzzpef9TrWsJuJAu8sRJ3w/m2DkybiwXzyxNfEwdOd7u2qsyVy+axNWEqwjVapgESFywZbO96QPa8xsRbWTJXeOnCRMClPIoMNH2bNasgZpRufSWf2tPdCpuIhdd+aAm2OyZQH9ajh6ySZO65FrqYqjzsNb+5t4AGt82sdKyizuZWCCgDO2lTIXydNxMN5wrIKcmhyMakbps7e98Wb/vevmJOwJ53GeW/wvWuDezOL04Zd6J4cpishDWWgELhCJsx5IyOPZUV4nK55/J8e/AnqzMeMFR6kU9fx9oL37KRhp7caM9IMpagovzNNjOwMW5QAvJ90ZVwHMvozgIOaRKqZ084beGsxPbg0QMt4IPLFmUtwDTu+q8EhmUkup8VpdHSvqyw3mJB2kyITqlpUSdKxEQbPnBXLeKWXAuVUuBg6hmsdGGJXadFF0tmdlp2i5ol8suX8X+3D35ynMhu9GmkaNCaDD24ZnKTOtA+FQX8j6N6TDTkqxzIeSSChTGHVVz1Ru7cXPOw0Erp2wMxMUtqUWRAbkdF6wyKE6Bpwf5aLz0UG0bJNJIHz8XrKbABQFAlHdULKDjHzZ6OsNy2OrCHD3wB4YzaNOdSMjaoZU9I/Fy7h/owOo1/eH/F861FLIVkZet/M3RS6V5tcxoYk39KA7aQm92HhE/lFgnYaKa4APtPecL0HIfvq57/uLQCiN/sVUS6OIbm3xMzrM2YesnsVrzfJ2AZ/cJ3w5SXv9i+fNDjvW4wpi1FghUpGVsuKYwFtRvZr7rU/WvND35fR0qXI5lNmYatGeHxuWUBGIYivg8F5l3HeGby5MEWyXhuORSuTYX3EpvelANTwOspu+RkWXsfQfFbOd8YZJLzzvS8sG4ZRruF5b/F7qw1+8XAu0eDA43XCu3uu2Aw4AyyQ8buXFR4u6HxMhU8ue/82WPzSCfB0a/GlJZV3c0dlT2VY8B03WThXHHMsvClBXF20pVH4oxuDw5pjEDqmZtR2GkMQEX49t8VZ4EgKyNbtnIeOf6dk3yBjpoRcqABkyrB5c4boVSvIjyJ5WtC+6g30uF+LMui9JUfBdxrx9zHAd68tvnFEMqtGYxxWtjR+GVznN+OnHuXl6081CpHC4s/mnF/t/N3/DMBFzvnfMcb82wCOcs7/w896nbPqbv437/3XAfBCLTznuq96W0LD7s4CvMx/6DLp8eY8FsXCaRMEFpvMcbo4ZQHszhdVBaLmLDwEBfqPpkDatc3Fj13ZyTOXSvyzFhk67/pwTVjbgA/KvdmIV12FhY/lvWkgjcLX+xU18ec9n+B7Lc2VfnTLRfGVfT6Uv3Ex4j9/ZguJUyty5Ug83XohDFHb/7zzMoObNnUNVQNIplPfAEVRVFaroTokFqEsVIDyQO2qY34dGg95QlxCQoFcdY4MoMw6ARY2xfk0G3x/5TH3JKbNfMKljIIuBiYHKjNbTVr0vShc+iOZB+pDvxDViSYTqunaQj4n5a0WX9mfJMpJPq+a+Ow6Ay5EbnYxOFwOphhq7VW5KG9ocsTiLGYS9HR9pGzKaMJbyk1fdAnfOJ66z6uB98hZ4Fy8/pXprfCml+7hdy4Dvn7EYuqdvR5/dNPgtGXhoHbttePcd+Ezfu084hdPXLmfg3TQx/WITXAlhEyVBpXJeLL1uD+L4qOQCydDZ9XnMq9dimmRAUqyKYCicmhdLs6Kq2DlueX6VCXWKDI7i1xC1V72rkD9pw0Du55va6wCX7MyJB+rxPWgisW4jnbbvoxktJipTMbvXNL2/61FlE09vTYmqCyvH51FeQAe1bEoNDRfReHomSi8sqwJHWctvRA0I71kRpGBduJKul+lsoErR0yzSdZqly5o6m2wQphl0F9jM95cjFjJc3AlYWRv/BjXSTM6lFOiLquKPmqj0snIdtcO+4EgOaoa0D3rj27o7aK25XREnUK0fnjr8M5eLB4UqnoDiDBqoaWpzF4OW4X0dwPLdM9Q8uI22KLo4usl4XGRrzSI3w8VYgkvOvqk8POwID3vpnPvrT0URHrXqnwUefTLnntpvbNHLnd4IhrSCLAg85bcitryPdJIjzyVEznEIevzsOKaCjIy+mjNrKIMcjFmToPAiCrPHFFsHU8+2Xi86jLe2uPn3ZMxycXgS6GxCWqtADxahIIOXQ++5JhEUV0BLLIWXsInTS7Gifqsvn9L2fP/9OOfPgr5F1FY/CGAv5xzfmqMuQ/g/5Nz/vJnvc79+m7+7775Xy2LXv3xO3Fe0zl3L4QUI/9fA8GOGkLZV4PBQT2546klsd5ADdDS7oaHEqHhpeRIKHlRv9TlbOnFadMArU2FLFNgRBlzXA3q3sn3dn/2kxsXv5+vNXMJS+kqX0nHMCaDlx1VLfrQXg2sjN+YpTIX1AP0rB1xM/rCc9DrdzvSaruyZK2ftZyXaaQzH1TCj9+9tjhrOXt/JYdIzuya9ysyxZU4FbIS/yKebz2cQOaVnRILbwPvhTOvy8mGhCJRVT8NgJ3Zi465DUbY90r+pAMiSqaFzugBhlY96xg4pazthefDdFynYta1rBKOhccS8uumTTOBWBPIMyAJlIqIQ4G99UAFplh0/Rql6NCCRdUS05zZ4HbkiOmOjOBU8qwzT11xahak90ZzVhY+F7LyKJJqgOid8lOWAvl2MlfWda9yQeW31I5FywPx0NiTZ2MbbFFlqEumcmkylHCbCuNeR4P674q+rUaVyGphZqDx6noYb4IpnAx255PzbWMznncWfQQeSD7Lf3R+g79xtodKeAJKVlaJ48Lz/g3RCCF2xNXgi/TaS5H4ZMPOi/AxCapD5OZ9MUzKC51Dq8rsXKTgd1v6SSSwADprY7FEby3vv6IVAIrU/fG6wostr/9Rw0NsE4yYWbE41X1HR0PLipu+PgtPN+yGQza4DTTBUhK4RpQ7kUvuBiO+vzJ4ew/FYVLHcutAtE0NoTYBBSHdU66W7Kv3ZqkghMpjux1N4Z+1LuPf/ht/F4u3n+Lf+/f/G/inL2uctqZILfU55/OTC4qrMQkaamgNURFjuNY0sEzdcOl7wwbn+dbg7oyI6Eb4Yvpau/L3yk4JozoO1+amKHsc0UuVEq+lYHjRsQDbr+mIq9LvSzHgO9mRjrZuEhtwnzESAEYC5vsrh9OGv1f3TCejWeWe6J6hFgqQ51iRUSX3q0ttlqJLuRWHgkbpZx+E3xPzFKx5MRDheXsxoUAXPcnjL3tXlGm7oXErOZvfmA14smlgzL9A8qYx5ocALsEC69/LOf9tY8xVzvlw53suc85Hn/U69+uz/N9+42+WWO3dr5SB37+K+NlDdjCVzM07GYnoYq9MLqoB3VRVIZFBJYEu3JcSpnIiGQ7q468dUxdNsWXVDvTJBhhSxptzmohoZd5LVw+wC1FDKbW2/cEq4P7MY+FJOlXiX5SO/ljY/gAKgrJfp9fUA2pRrBXnxxuP1uaiNKBSgWmdHDNMC/Wgivjglv7vCvdq3LIzlKfen0/ulbwW/EBdMvjwFph5g4dzXitl66uVtDKWNVNCuwULFHKrzv+d/LzCc42lS6du9pqWeacJ+HBdiZ8FN3w1Cxsz3QtPmohnWxqPHUp0NzBtTE6Z2vI5YmKxkwG8OY9lTSyrhG+dG3ztCIVYG3ZY2UxSNKUDB8TAylIhopW+brKvJTyCs0/aGfMAuxg43tKNhRwHdggb0bjfBsqCz3sWohrV/nhNOSeA4pS4rFJRS324dni0mPxeNGRN1+d+RTa85juoJ8lFT4TjcjAy46YE/KTmxvPRxhcDpy6ZUuw4UdaoFC5nQsS3AdLhp5LKmYESOb2RznzmqfgJeTKrs+Cc92a08twlfPXASCYL1/sriZNXK+1XPYutey1HONpxVfIMzj3v1aveFXnrjSho/sHzjJ8/YnibZmQ823J8cCiJnF1UAmAuaN23L4F39mx5VgAWx0O0heTrLXMaaNTFUe4mkmitcPy5XHtl3QMcX9yMlGpb4We96Aze2YuleOEaS+Xg0DGMFuGUE3JsqM9gzgYHdSj7zccbHlxnbcTjW4eH0l0rIfy4jnjeedk7ssh6yRu7ER8EVR10UpztVwEv+gpXgyuIBzlcrjRn2knrSIh7J8dH+qy1hb9lhJjLAv9qsHiySbg3I5qtvhF9mgj7hzX3hMve4wPhUTU7hGpgIiPvVxEfrkkEVivslDk2qh2K3fztyL0pZqptzntfUJHVaPHhGnh3DziRWAGNMw+CUj5ek0exjRl7nkX2WkwgAZTProhEEuLpy86gcWJMiGlvW8j3xDyNz7SgAkha1iydN2ahBDfq2mhdKlQBTQfXguh6JCL7SFx+dz1STprJ2+dfZLrpX8g5f2KMOQPw94wx3/tn/UFjzN8C8LcAYOmW4gMRiyriStzuKpvxtSOFHWlnrdkMehjql0UWWImHzyoYGMMFe1QnhEDW0LKi9WvMBn0EAFMQEC8PaJSQLisz0bOW81B1o9vtWjn6SOgjL/iBhJ0tbMLbe17kYjQxOaiBi56JhjpT21evepk1VvLwjcngaDEU29ubcUqBZAAQq8jWJSyr6VooQmBNxkebCsc1H2jCa/yelUDR2o0XzwMpDkLmQfDOkvNQdSa8GLiJn4orKiJRHp0jOp23i5X6aUNy19VAU7M7DR9ylYDNHQlUMRssK0KJt2Id7izzUvarVJCYMVN5M0TOzBn7PWU6zKUY0JGZjogO6gRnCSWe9w4P5yNmLmFIFu/uGfzo1mC/lnUhxaQG0WlxoUdITEB0psgdu2gKSqBhahcDH/LDOpe4+NEZeGvLw6n3+f4syYbmxP+B799blfiyGHtnLwu5z2HmI6pAdclVtPjOdcTbC6oIdA58NRocgkWJWna/vaBZkB466r1w3nNEctYmcf+ULlGu9zYYdFH5PSzqc2aUvI5BKpNx2ibclY0+Z5TciPUOOsRnCDDRYDVOsdsK3W/lWfAGuD+zaF0sZD/a0HM9G9kTNLr9/VuDP3syYumtdHAGztCobL/ifdT8iNaxofiZgwondSh+IquR1vHnvcUf3Vi0jmsW8ozrM3S3nSrNg5q5IpvoJBmTe4v6wdwMFkaI1ZXNeDCbVFpbT6RBI7QbOxnp6eF9WEU4IwenoBdXg8Fpw+Lng9tKUpepiGg9i8N784DHocYYVXFk8P6Kkneiw1xb5z09QJyMIyrLNajoKoBCpnxzzjBDRUVal/FHNxanTRZfjarsQbtoSslkGoksqPGSNiFDmgqKTgjjXMsWH60TlpXFacNm5e09FraVjLuHRAQ6CFF0Gw1aGb88XExGbc7kksD6orP40nLkHuSJCDyY8z3Wjs/MXhVRGa7jg5qF6csu46jmv533TlQ7dBd+2RvsVQY/vLXYr1jgWHDPuj9Tfpag6RZYtKlYue9XCXt+Cn6MiQjTzLEoUzK0jr77SOUUmzWijt5wb1NTvrM2yGfm991I4aJqLyv3RgscRecrk7FfibzcpZINQ+TUFvL8Z339qQqLnPMn8t8Xxpj/AMAvAXhujLm/Mwp58VN+9m8D+NsAfSwAetsvPCHx0zZKl+FxRwKBLGzRryv5pZaqV7t4Yyi7amzGYU1VBM1pTEnanNWan8GHWHMuroWxrFDSQZ1wORAiPKinJMtO9PheOrAQyOA9qFLxvZgLdH1/Fot09Ps3QOxZ2YZM85/aTexsTTl80XnO2isgJIvrweN6pDJk6SMsXInSHaLBdzcNztqEFx1nwbpBaq7HzUivD2eAaDlXPZUN/LBmIUUPfZnvGxqBZQC9HD5qXEW3t1wgtJSnTJSp+2CXPXescGM2iBVJsao6OG0C+mRR2YQX6xoP5yPtZpNDP3BDU+a0ojbqGkoPBYOjJuBq9EXKqsQ4Y1i4LXzE0svvlLRR9WdQ4zJvSQ57MOcGFJPB3LH619dU1KqyKEY0exlImYgH0QuULoyIECFUTV7kYTNBwue9lfk5ZMPh3x/W1I4bKC+Bz0NtM45aemUMEbgZaVms3gnfPHLYRD4PRzKG4/XkGrNSQCYod4OKIvVScAZY1BnfvuRhvhqBhwtd59ysj6okPAuOEtTpbyXZEc5PG9ZepdkbLM5qUQkpF2Uh3KfrgQVkYzPWOwX++WDxySbhZw4MPtk4vOgSvnJgxGqcr6vduBIf35xzU1wlU+SeLMqMEFxpVDTueI1YEElIABobCzfluE44rgFv6VvyYM6N+8mWvgoxZZy2LK62kYf01cAO1cl1VyffnB2ebFgoHsl4Tufqh1XExpIcGyJRyj6YUpS9EifQnA0McjFIO5NDqU++eCGol8iDOuLDtUXrPOYuY7STXH8po733bw1+4Zid7CYS/lYjJ0YWENlRPhkbJvI8znuH4yYW+e/bi2lMrC6SleUYYUws1s97h8M6wkt8gBoP8n2zuGodyv7eRTZStQW+tE/1Df1qpjNEJeUp83nd8xnGsLFQLxD9Um6Tjs0Pd9YjEW42ip9sGR7JtcGi4PEt8I3jSEttw5yoMbM4GLMBMt/vfpWF3Et/ipedxd02FSIlnVC97JGASSwqnm2tyIgzbgOLb5UY61hOVYO6LmqXcGxM4ZftohUGEyq8TVQp6RhN+RmvpJEgZ0WRo2n/1/0jJhr7nbZEiJ9ufXGj/qyvn5w9/DN+GWMWxpil/n8Afw3A7wP4vwP4N+Tb/g0A/+Ef91paaS08iX7LKotLGiu3LOMJY/hBLwcuzARhH4Oz8H96tcbNSKJlLx2kduQK//SJi4xkRR6IT7cO5wOLA904j5pUKkxvp8V3Oxph9nPx6dxd0QOLjOOGszra3E7f/9YCeLiQKt1wIQ2RG9OLjpvP9UC5LSOaI4whmfO0jUUZkoACDStzHiDR50XHw0078spm3J+N4lYnXb1YAY+ZC0BHUJUgNrMdmZtyXAwICwKTpfFGRic6lwZY6NQCnZ611NXfih8DzYr4jRsZ16xGZhCoh8V+lTH3/F+WhQ2wWHzV5fL+557JnUq24gFnGb0tqM4f3jToIh9yPdA18dabiXTZSAetUkFjUEhlrSWxrrLMElhWGW8tIhqV2GUUgtk6UGLnDeXM7IpVocDD4rBmCJYmXIZMgmNleY8rw+570o0nHFYJc8cD8KwdiwPtkRSFl4NF4xL2KxZdx3XEQZ1w1jLzwBmiJp0UqVp4PNt64QpNVsBf3ifXYS4buEKgd5pYjMb0s6bMImVMfEZqOxmo0UPAFg5SSGpMNvlbbKPBUcPngPeYvB1jqGD6pTvkGL21CPiFEz6/B3Wia6lNUN+WyrKYX1ZMrXwlaZKHVYSzGd+74ehy5hMe3/JnfuOcz65Gf3+4lmRlQSSfdwyJa+zU4V2NVKG8vSBP4ma0+GhDc7GtuIqe9074ClZm9Y6HkIyWWOCzUL4ePAsxk3GnSSTpJU3OpVLICFql+82YTJGnGoOS38EEUF6Ti97h0UIdVdW4is/I1WBwPVBltJL1etYG7FfqAmrxdMvDs7IZzzsvBbaMQOXZ0Ah7ne/rHtJYqumWVcJRnfDeXkAtpmmDKJ6UCL6NTLetHd+3GoW1LuGojjiuWVifiFlWBgtC3c+9pafDskq4DcA/Oe8xJEqi1ZPnQkjxTgofHcPMXMaTbYXDOsg4g0XCg3mi8tAlfHDrMXMJ92YcZ6jhIRtSmgiuxLhM7bK7SHn6UR1wV5yfP9l6rIJFnyj7bQVB1dHMsiJpfyb8wavB4v1bOsQ2lgjvcZ1wMwIfbSyuJVQSgKg5cmmItUjPMn68Hi0ueoODGiXkbhuteGgQdTqokzTuvMfXI8P2WieGlELiPBX79pMmlnPvp57pn/mvn/11F8B/YOji4QH8H3POf9cY8xsA/s/GmH8TwIcA/mt/3AsZUAmwLxrlrczZQqZGeRMtzvuMxprXwsmU3KlOer9ytIC6KxaW7mDFEIcdJ8AuZM+lUv1pl7Qnck5mYHCud9rQXRGQIkZGJK96g7OWB50qITT0RT331VUz5wq3xRSI0NO+dLqbYPHxhtX6YZXxvDO427KbbWQuGxIX+mLGmZgzNEzROOmrIeOkoSXznYaGUY2digUlBKqErIsGL5PDq87ggSR6bpJF49gNdbBlAW2E37H0CfdnRD+eyWajRcKuy1uXDGZGQodko9ZAq9aqAoTvyQI4HxjxvE4GVjw2Disyj89aFgSUemXcafkzKhUDUDJiXvUGb8w5SstgkaCWyOtgYISktg0WbaWcjwnyXGRTHCq1q25dEjY8D603JfclAzJSsQAI8/ZyUJLtzsImJACRygtdj2PiA39c5zKj1Tm+KnbuzZTtPt27BODxrcXSW0RBU2JmB7Pw7IzX0WLuIOQ+IgW8FgbO0M1SxxjLaso32Qj7fC0FxrIiAVM5Jue9QyNz/MpOCZVDMogDEZxG7vNtsuKdksv8PYKFtTHsThOIvP24Rh4gc/7hgh3emA1eyIhA0cL3VxY3Y8RXD7gmhmRK/DY6jrgUYYqZSoE3ZoA1NHt6e497wt0W6CLRg5AcFt6UrtKZjOsBuNvy8GzcZDikBVXMwFmd4AwPm0M53LVTU1l17RJqMD+FKhNfpIzrjCLf3heuTPQTcpnAscE6WFz2wJ1WPRMgHgd8Pl50Dg9mhKbdjnKjabKsS4fHtxYP5nztkKmO0L1k6SOedVXxfbjXssG4GBialTNHFycNSeLKxYrZluhwvSa7yieOJaX7lwJpJmtKeTFHdZZRMt/P5WAL8ZAoCdOJrXzeQ2msrgZf9tpNsJg54OuHLWLKOBGlSszA3Fspvik1v+gNjhsl1SbcBocfrBy+cTxwb3AZN2NF+/qanBqqaTgKcGbyzXFG1RumIN/bYHCvnbJqlOMzJoPaJ1SC3iAwX4ZmcETPazdZmlcCP4zZwInh137F51fHXrx3wg2U59PI7zyqR3RJ+SRT4TMkSuQfzkMx4FJEVfeixnFNrAXJ/GjtChF/4Tnm/PGE3h//+hMXFjnnDwD8/Kf8/TmAv/qf5rWsIWFEZTtqHasV5vVg8O6edrpccCu5GXeajN+7tPjy/pTXQA2zEdUFH1p2aYRPndEwIMJMQWb3aWRi3MKrS6T6YPAwGEXd0QDlxi88mfWr7PCjW4uDGkWaxIeBB5cxtmz21oiNrc0wPmHhHZUuiaRSL9X9wgV00cFZPlwAoVt1B+2jxYN5wLKi9vrtBT//B7e+ZAu0MkZipU/p0EnDfIf9yhQHukYg/BHksah7pDfAOtEumgZaLAR1E2XHNYUkVbJYK8Nv3Ahr/6AOEirFLvcL+1HgUFbVBxU30j4ZnG98URSknDGK1HcuMN2Tjcdpm3A10OjG24w7De1mnWHHtudzeV1v8RpRTP0P2IEAS2+ggU0p83tveovKEMEICSWYTA3Z1EdkFNi9dbn4FSizW22ABilMo/BkNEzuycbh/RWNdnTmfC0+JTpeuhgc5j7BgygCzawifrByeDDPeNETglU5o24O37mK+KU7LABuR/pRnA+EVseRhe3LzuBwP5cN9EpcHC04ShqTAWStJQCtyah9Rh6dkAaB04ZW7LWbisdRFCYJKOMAVXltE4pRmqJRyUjEdp0w97wHV8FJcQAALNioBgKOGwdIsTImg7f3Qvl9PHSseLKgyORUSqzjwXstN2TdVCtrijV6zAZv7fE9roPBI/H8SGbKegE4HjppYskiskY6Y6iXB4o53Mzx4CQR04tyjPJAlVyvpAsd5froKO2wZlro9WjxZONwNdC6XNHQ+zNKbLvIBqBPvP7nkfkVtc14e48HR2PZ2MRk8OEa+NJ+xrcuGjyYsyFTQubuZ9zzRIluR4ebkQdizhwLnqrdv2GDsZGm7mVncNaaIrlVcmUGC5CZy9jziggJudcl3BHekXIuSAA3xRH3anT0eok0UVNL9Uqe8f0qyjV2ZUySZc9qbMJxw3X98cbjgXjdPJxnrEYHb7SYivj+DRUgGa6kVifxZnnZs0nd8+QiQO73i45o+3nvMWYqWJQPoc+zNmy6F+1VsZBl1Xa+dkRotUEAeJ2OG6p3iJhIaq7N8BC0LbPJbiwTTp9thRhsGeCm5+uJcIZUdaJKL13Dyk3Tc1CDGxlWadE5U87an/b1uXDeVBmM2vcuPIpX/CYwta5x3BwO6yzaeG60B3XAWwtfDEWsdKHKIFe3N4XQKkvYTuU6nK3ucgZQYo9H6WIrO72eZnOoQ97VUIsZk+bbEzl4OGf1ftZOGQ/bziGayX5WrX6dAa6GjLPWFPKRAfBkWxV/DkVoLqXD99KVqJ/FzeiLRKxxarqlChqDuSPB5y15QHXeH2XEpHO6ddCCbBpvHEhgUMwose4JQiwER1Wr4ITok8TkaUqEnflJMgcARw0mcmodAdjCBahsxt2W3hs0MxPzLDWsGV0x8jqsCc2GJKFEdmLDxyxoiaUULedpXEVomZ/hh7cZzkzZGRksMFYjMCaut70qF8WIbv7A61JRdW9tnQEw2cKrf4IiFZXJxSsDAOaOs3OVkh5oNofc8/PewhuLvSri/iwVRcrDOQ9OVQ5UJmMTUEYCf+bQIaaMyiWsgsH9igW2SiznLuG0ZWH3/irj7T0rKCEKOXkhqoVB0Bjl0dQuYVH4NHJQCQL1qjci9Z7UNJXNcJgIeilTlWGMFPaJ6qi9iiZhXkiZR/WUBaFEZ2BKnfUmi/+AwcueQX8hmSKbax2w7/iazAciT+COHIYLOz3T+1XG714BX96fVEHseik9pBrJ4J29ER9vKhYYicXscc2E3NZmWBkZhGRKJzr3QG05R+9lZKLoqc7FvckYYMTHZ7J219FY6xLOB/7dGzNyH5yxJROolsA8yH52LcTPkKhwO+9ZLGlq5vPOijuklbRaI3weL6mXNIYiiZYjlD56nPfAfsU9tZERRwaLitvA0fF5n3FYk7zaR4sbkRFneU6iFEsx8+fIHRHOWmbhx/GqkX2AP9sng7llN90Zi02ciK6VwPqQZ3vMBs6SaAwwSRagYdwmWnTiqZEzisW/ErXpTMzC78mGqOSdhj5KH9xW0LyPN+eTa6g1WVAgjtyutx5d9IVAqRyUQYrBK2kYps/KtXBHMpZGGUWzkbOIckYdiUlbliLFZu43BuQ8jdkWM0NFwraRnLrL3iLDoDIkxdNVV87ghCKhZpQBG4SZpc/Kq87h7izIWWULWv3Tvj4XhUUUotN6pARs5sRlLNF4x4KL+7iO+GhDP4a+F7Z6tBKCxDlzxjSPtACGPMFG6nqoB49Cwc4AfVJzmyQeEEQ0NEuD8siEk4aLxwk8O/fKMlcoTBJCLQ+jmU/STRESp/Y5FU01QBfIt/dYlBzVsQSpKezURRRdsY4BgpB1OoGlb7YWtTXIUuEu/EQWXHiOeQDg6ZabqLOm8CfWQSPiWUQAE/S7e63mbirAvNyTShbYmE0xRxoiJGab9tMxk4Wtc9HKanYDisdHki5XGdxXo4ULtKxWpYoRIyV4lA34yZbxxE4e8KWnRE6h4j0hytU2ifTUFs+LN2YJD+YWIeWy6SmZ8qydxggsYiIOXCoQp6psKhnzXAwOnUCpIaHMQPW6eBkNXQcqNnqBWusd9Il8GiOSXCpmThpuWrciVVzKpjFmeozcaXNRy6hDbMxkfz/b2iJD1G72SlQ9xkwJmccNu/m7bcAquBIMdjVoLsbEn/BWJZdTNLMG2lU246CGfF6gFrKnSq9V3qaFs0L5XNsGxvDabqPFty8D/uX7PEwWLhTkSwsYkoktlp4d7tyJdHnLTjRmgz5xDbzoPB4tBuxXTAuuDGWgmgejMfMP5lw3a7m+taiIYgauBiMyRC/kaAMNFFNFUJ8MFuDnzVI4BBkRqEwVALxwUqIgIjOXxHjJYB0nEjQDoWiE1SXKHtfBlMMsCqqRLN/LzUAE85kglOyQWeidzfg5iDIQRWPxFrEJJARvhIR6M9JD52bHx2MUdKpxU+jdWUvzt9ZmGCR4y0TbRwuLbZR8IJeRwmQ8p/4hmy2VQBlESGM22MJCjbOmcWQGYLAvhfZF70ognxKqdX/XvUgD8mgxzryjo1qsBnovoyI1OQNmNmFIfI2nW4dtsHhzQam0M7Y0U7eBn+tECi4lKsdskKMRpQTlm8clnZRNE5Ipr5PlWYnJ4ErWk0rPFe3SsQyg/j9TYa+vU1nymwY5A4mOGLTWFGVLhhr7JdRuCrYzkKRv2dvVquGoSRiF2Alw3Vok/OY5cNRY4RsBh/8CORb/3L70gXNS4SqB63zHMOp6dLjbhjIe0QKitRmrDNQ+vYZEAJIOl51Ud+a1QCRCYzIDtRM0FJMt/hD6OtrpahV5KNLOAzH8aWxGlFFC4xI2kfbDVKLwdzcuYd4EXAzcPOnaptCrjhXYDXy0oTxpEwzqmgfSLrICsFOJgQWZBRe7fr4+AuvRYCEGT9T6++LAFhIfusqyMLsZRfoq8G1jiQjspujpKGEjBCwAYrSVhKCYig+AdhHOMlRNuQz697ympmj3z8WUxRg+bBqZrbr0ZZWoxLCqCGAwWSdcg7lLuEkO+xU9E+5KuM6ZZ0Qx7cINPpIgIKYKoigKxmRwR5JOl17Dn6b1qYeqkdFQwo5Zm2wwITFIyRtggCm/ZyFkUWuAuZ2MydSQS5NIhzS59ylv53bHe2UlvBw92G3FdbDwEVeDx+Xg8M5eDwuHazFUu9vys1EiStt6QtFmSoqMlFMSvZvSaJcySrg3S9K9Tp04i9VYnhEd77U2IY2OibE2Y69CcV5cS9ibM1yTq0AuEGOoUWb1WiS9Oa/wsuczMCRyAowBHIgQPdvSljxnbtz7NX071LBKVVYve19Y9Sq1frr12Kty8e+YO4irLk2S+uSKwdSzrcFpmxmnLWNKmohNxTfAgnwV1IDJyUgMRS1E+anA5g5lPNBFksetcbjTJNyMbBruNHweDiq6jh5WHK3uS/bM+eCKLPNMwuY6cJ+sDAulSzm0nMlFsn3aqj05yvXeRuCgYhN0M1ocViQdzl0qBM2H80RJvJ3QS+V6XYmLZwLJ1zNHNR0wdeiKXKVsEB3gjCncNPViedZ5nPckHHNtiU9KmjJRMqioOqyTZLoYHFaMbb8YyB3Y8zpCiuIlQpRzIw2Cqk4sIGijyMkzydnHNfkh60Ap9cwnnPdE00+ajOuBChRNXx4TxMzP0MVSVGWa2PqiYzbIbkBaC4ljyFMjrNkyOZsiJeW14fPRJxYTek83oylIaIiUjW8COT/7VYSV9RAzLRZ039VzYr3jj6SpxNbQiFBHM1eDE5k0r3VM3BP+RZI3/7l+zcUls3Y8HBqTsRppevN47QVVMLgegOOGP/PRxuLtPS7a3RAb3UCUCU72uisXrrYZVuaaLtGrIoEzszHTOInhW4ROtfC4Ghz6CPRSzqnBT8qSMSAz9S6y+LnXZjloJSIdPHR1nmhhyxgoZHr2Xw0Wm5BFPcDZuDeqVybXYtelsDLkKMx9xrMeeHvB+fjVwIOND5YtiIpyA4ApvbUWoiclWqZovSuT4YQRHDJZ8OqnlgRS07mcwojrQGOdBP7Ol50rVbgzE/TWWG50znHTTtngRJQ4WlTMZeOpbcYos+vbcbqPFuxILwcvM2YqEQ7rWMY33mRYIVvdBioQFCHRdMRLmeWr1Op64Kw0ZqCWwi1IpzxmoDbk1iiXoE+mGNR0gpCd1LmksqpyRxGdV53BzNNbISRushbkhmTwoBijkTEEEa6YUZwUmaFC9cfN6EmIzBAFgilKhj5N0dmVoWqGh6cqH1yZEVc2F3JvnwgD6wz7oMplrt5nEoZ33RPVDr5LkmnhdzstVxAS+jGgvJ/DWh0EUQqmLpGstl/x3h+KJX1lMs7l3s+yKaqZvSqi771YK7MJ+GRj8HAhXWVS9YfBR2sWMvvV5Fx6ULEQ6SUaYBPJM9GxwjZMxcOhFJ/ecBO/GcgpaJxKR5miDPDzHjeyZgPh/9nOc6LIVwZKEbqNHB94KT6tdKiNlest5ls587mfCbFSeRzXoxVXTAMfpmReHeXoCNSARGYWW/SwWHgSDmeO6/ZcRkmr0RRDrJSBZ1uDtxeTWyqwk8SZd1KmRVEAaDy9KXbuVUGQgbZiQaio78wZGbFIErEUBpc9MBNX3ZxR7AMWPpc9fuGpvDCGv1tdQV92wLKidFWbRNr2c0TnLZ8JazL60aL2qcQFHIsXxToYnIrKbe5JgBYxEypRYvy/nkW8NW/wSPJ0tkElx5PZV4LB0iSxA8jFvryLtoxhFz7h1E2joJD5TO2mDisSHfPkvqmj7AzK3bU51C/lC6n6AwAu01RUkFvhcCI+MVVpZIEvLCVnSUacfnrZT/36XBQWCilWshETwklYBwkZGxgw9qpzOKyn0JqZVIZqlGIBOIHrY5pscQeZ12s6nMJsmjOxCpMvRS1V+O4oQFnplc04biZLWtpsm7KZqt14JZ2Zmka1bnIL5azYiM4/lYJI4e9llfDu0shBQHWHbibKpr8eHV50fM9fPoi4HCyebkhk1AW3lDurm4m6utmdBcHRgCmHVh8NGunu+sSHasyTHly7SUp8s4xoUKyirWyCCabMAY8bJnG+7DmrVl+ILOiGFoHK8FdCZMyEBpQgGrMpdrNq/a7o1X6VymhIRws3A9UZmqD5dHA4FNUJ+SRcK+UBTZMvyYkkpO4mzmoBURmOdQxsSSLkWgL6lMWPQhAdcAOqs2Z88LrXlhu2qlQyIN0UN/AP10wzbR2hZ4bkoTgYLjxn+uc9xyMP5wG1Y2BRAg/w553HcZPLdfaGHfahBM+96lzp7LLwkDSDYuGnGOY+agw2UYfSYUr3qAqolVxrawhdK7Jj5XnYdYRtXIIpI0mx8Ta5RIDrzJs8IXrDsJgCjeVkLLKNwL12xIHMzVWWvqz4e/tEVO1WfCHemGuAE/kPxw1RI4V9rdFgQ4OFI3r31p6R0EG+n3UAHsy4v3jL7k0L1MYmdMkVFG0deD+CHARGjKpm4m2hRcihhCbSDI0k1E2YiqqQuUcdVry+n2ypVDlpEmCYUXSvzQV50NjrQz/BbpURZNfSX+GgyjCWnA/t4p9sGEz1omPR4+TAbazKg4Gjms/JTOTdjeX7LpwQGQVZoOQDreX6d7IP7wm6nPPkjhoS9/STJhdH3pxRrMaPmunwK1wFeV/KT1ArdY6rbRm7TbJkFJl3QS7d1DjeDBwpXPSuhKoZgzIyGQUJSNnJWTPtEWMG9n1VPu9cCqtnGwY8epPRi4pGiwNtnIyMflpLVKO2JFyrtw0ABJCsqtJ/qsEoeVWprxHExQKC8ABjELl9MoV7svAJzzoaD9Izg3vyxxtajsds0AXd+0wxz+siCv/oYvjsysJ+5r/+Z/Sli84AxSp7HSz2KyNabaZFHjWpdJKcWwobOZliVjIm6o2VvDcmjWnWjhz4eE1ZkzLZtajQQ0L5GNaw8xik8qvtZMbSRSW0cVGrJFUJV8pIHgR6MiaLnJEdzFbmjiReKtOZN/2ojnjRe1SWr3szWpwPlomooLlJysB+zc16Tx5IZWgDtH9eScV8p0nooxp/8d+1O6vMlN0ATP+uhY4BD721GGXdaaJonDnq0MOShiqim5euqE9Ef1RD78204OjyR1RKN/8uTkx49eDo5Fqrzl4lrAxWIzqhZFsNCrsdmSXByl2SCS1ttMn5MNM4x6XSxcfMa21lHXg57G4lf2MbmUOxX2Xcabj5zXwqiBO9/CcETQ+sXaRGdfeH9XRYzxwJUo1NxTNApai65lqbcd4Dq3Ey2aodcNnzddQTY1+sqfVLLcEBvkYnxmBdUmSD92wrUsPKTi6NuqbV9r6yvJ5ZeCCrkWM0LwWdGurwuVGJKYu5Pho866xEXmfhophy35TY2ThVdsn7S8xv0WRI7TSvR67JlaA0RJX4fu/NIm4DFThGin7txtkhQkiGdE58tmXBSE8Cvg+ad3HEtQ68Xs87dr214wFwUMWy+YdkCj9lLqhrgqiIpPjmgWgxJCujBq4VJ3yLlLm+KJNkoX0rbP6jOpWDVOPsV6PF9645L6cdPl9nKQ60lYwWLTI+uPWy3jOOm1xGeI2gd+Rq8XMYWStT8e7QOKoDrIEgehzbeDt5l+weJl1kAX4z0nHXSKPWJcr7x8Q9QFVlrTQc20h/jTHRbIwW/+pFxM+Vsq5JRSJtQZUWct1+eMui4jcvBhxUE0+MTsW8nidNRMjA+yuPV0X1xbWxDhabYOXZmiSjGiGRwHsJTIhWytNzfjGod4+gQ9lI8GMu+0tMEwrcSoFmoRJ7omG1Q0FmKsMGJ0gzOubJP0QzSuidxPdwVHMspHv83BH9OR9UDq9jTe61C8/9Sf1EAD7jlJ5zP1W/GjUY+2lfnwvEQhf5SU1r6yGR6LKxTHQ7LJp/Sl504dPeOeFm9BihsypGh++JCxqg7neq6c04AR9m/fM6WIxx2uQAJaNNrogzl4tbn7LMnYFYBWc82VjE7Ei+TNyUW2eKsuRKgsOuB4O7bSppftyQLEYjDoIAfvfK4bCeuAo5U8McM/B0WyFl4KThTP9qsHhjFgrstw2mKATenMsBJ5tCzvTfuNNMUJi+j5gn/4G5QLvakagGXX+mdQkdLPrArsHLPF2toLVjVRTiVeeEjIqyyarGWguUEIBW+CQ3wqvQboA2v5TE0jrdYr8m0VATG43JcNBDlPdJUay5n8YfAAqsC+iGT7mmok1qU62wtTEZvWxelcyrMxTREu6BHAgzx25OY6/VQ8XKRmhk7KHRziqj46iPCNihrKlRuukDeYg3IeN0MaEfM5fgLUnGBvy7F53H0qeyoTTy+joqaqTA8lnd+QArLp/WZHn/CYArTH0dT+m94EiIxcV+RWKwSilbl7FwJCzrmC/KPWhE2aHJskqsvRK1A/1nuHm3dvJpUAOzPSFKGwBPtwlfWBq0NuHxumL3DuGnGLrgNiKLU7Khk+74gxVwdwYxSbLCt8llfdRSaCkfRu2UT1uIvbl9LR04yWvP7JQ5tA08PG+kIKqFSAdIs5EnGWGXzBQ6l6b3OiRTvGU0OZSkZd7X84F6iYMqF4UNgOJqOSQaxrUiqZ8LUXvmNJWWlvs/XLPTPqj5ffSuYKEzk/e0kvGgyln3q4A0g9w3W/aITbCCOGRcjdyLop2eY4ANhxZZM59wZGNJbX0RDH60GbB0Hm/MbTngZo4opxag5NcltI48pCBrZh0MnDE4bVjofmGvwbevB7w9r7GsUJyCK5tLIxKzFSv1iJe9x71ZwrMtOUknDZ8RdeFVhJoFXCwcHgB4MHdyb1j86nhnEGK2vsaYJk+lhZ+4F1206LLyBFHI4xYZlfB7xsjxyCa68vP6eXop2ry8tiJmjc1oDYvdECYeokqZt8EW9KyLPHP3q1zC42qrLqQQjp4pKM9P+/pcIBYW00jj/ZXBiy03woMqo4984Cqb8fG6KhfDW44KCNWjXKzaZmFcK49hIk/pSOCoocxH/7yRbnkjUG+UuWwUCFs36EH8MyrZ9BbizqjqEiXfOTMdZvrnpcypWzc5/FGiyGuw8Bkfbxhd/WghAVDyGVVPvCfyJGZQsNNuBHLT90eSj8Eb8ykqPsqmoqML1X6vg8DnmWMQgEVeIx10zIpE8DMQfraFnRyzKbNbrcKVwKa/w4KhagYSbiVwX5JrS7IVD0IdjdAemRtfH1k80ptAr6fkEggapNAfCXEGS/HN126rtiTq0RBtUnpQXcEN1ACFRDaI14KFsqJ5qFErjzKWCInXL8gIhw+iIBSYkAWVWK5GlHvO90AZ3CqQS5Pl8FROziDX9aJXx0oj8e4kAjY2Y+71QOZGrk6Ie0I6uxgcjJmM4jQoLYN/B0zEyZthcspciqJD7e0p2zblnqdMxz5FrBqbZOzEjjLkKXqe5N1UusWUqU54unXl+vTRlAjxSg6mTSSJrdW5rkVBOmaOaMIup0QhXYDdcEz8uYvB4lln8UpC3Q5q3m8NXVMjNe0mNXRMi25NAKW0mwheTPQhUXhdFRhKjFV3STr+Tu60IU9upkoebK2OaKzMytlotVbk1NKh69hhJogJmx16T1BBNqEnQzI47315Ds7aKUH0w7WTzptBVfSUyIJokRtwNfI1nmxIfq8tcD3w3megoMIxs8ttBSEB2K1bsKj0gmoOia/bSLN20TNbQztwRdnuNBnHVTWRzPNUNEOeKW1gOrGLrwzXARVn3IfvtBzv3J8lHFdVkSuf97bsM4PI9+cuFwnzkMj30yKYKclcF1ZKQ1UJQe6pMVkQbxQSuqZ065eibQaTGy9HStN1Wwc2xWo2Vlvyb0ZBv1RBl2VvmMuzwnZ62m802kARwRtx6syyn22jEQt1Ihwqx1c03gAFIdqv0k5WzoTov+o/u3T4XBQWTqDR22BRWYOZn6JtlZBlgJJVodCywkO1nWbrOasbmi0Kg1UxGUFRh6hjmz5gOgaJMgLQDg2QkCNZ2K3M+GvLzaMW/4y5x2ud6moUWZzRm5LKwQaIaYvhTV56WhlrOuNhFYvfwnHN372NpmxO+1WSGRstgDV4ZhUsPt4khCRpeDK+WfhU5od3GrpJXsihoiZAjaNXSGNTGTXETCa/XlMtGKzMUdVO2BiUGb1yQzaR1x5Q9QgLC/3SjcOY6SDJmObDSyFYMQyJRlca0FM7ysK8wLIqpQXICfjhbY0x0yNDSUjecFPOmQfYaRvL9dTCq7b8LEd1FsUQN+sukQS8lHtCnwsrNr08aKyhD38UeLKMAkCrZU0oJcOa61eh8CHyuvXJiKrIyrjBlBGABXBQoxxuzvJ5uNcmNPI6mzDFQO9uaktPL4eN5AbpGtqT7qrZmTN7k0uhtJWibibcCX2v2nkRhlZuhxLNps1N028Bwr6bwBRYRQXXgevGG3WSTGUvyNkIqsMOVzlOUQqzd/cSnGW+w0wKfABiUc6Dc79Oheg7c9O6u9OooyLJ4VpsHdTc5HUdMlLAlEIX4KiWMkoeYhbKqGGhdiXmYUoI3B2J6ehUk3ETiDB2aXKrzFl9LniRSEDmM3g+OET5Xr1Oh/Uk5VUH4pdiYx1kL6P527RHdnEy8SNRe0ptVVRhTDx4NGDusE44bSl3rQxl2zED3zpn8b4OFv/6N34b/9a//PfxaDFS+VTzWjYyx6+FpLv0OlabeBjc07kG3tkD3ltSeVFbiQrPKOOvPrGrHgUJ1m1FE1F1f1Wb62VlioIPcj1ZjExjjLWMFLSAYUHI994nIje9kJN1TYVshKek958ImN47lX3XblK23ArPTIujFx1HE1ejK3ECOpJ0JosXCFG925F8tz5qo5Ggbqfcd0w5jxiBMaGMrfD/9qsoUfWYroVl87fn+ftOVUYsiPqtjNQXnn+v3MHP+vpcjEJgpu5w5lDCXFpHSPNqtEjZFkKlwma6EZ22tOu9lsPTACUHhIvPFQXEUZ3gdzpezYSwBkX7DeC1mW2fhK0tC0pTISvLjWdMr/tGAHwwL0Qjn8Aq+Lx3AmFzM0hJORWhBLB9tPFFpUEXUBLTWkti615FW9vv3VQ4kXnr0y1gYTEkBkhdj5S/HTSUtIWdALZOui0ABQYj4Y2FnXbuOhIBCGXHBBjLB1Ilp3uij66MAaBIDhDGSS0AA7wUspQerCmjcDpuittppEom8UBNUjyq0qSygJOibWETrHEwJmPm9TqlYtKF4KQjZbz2raAgQ7TYhIlnoZCmFoBZRmtdlHyHDHkIX4f9rMkCy2dBciBkvlyg45x3HnKdi3vNn7HFHv7hPAmDnQesGodZoGR4UG5qC2lZHpkCC6Os38mQi54KKlV14lzKAmqIdKDV9NkuGgzis9I6JdOZMudWkyaSGEUeG01xQ9WxmVp9Kzk3AoiRs2Uda5F3NPFRlJ9iBF0aE0QaaWQEw8+n90rD+fZ8wp4lcc0CgMm4lVl+YxWlhMyduTZXoy3sfG9MycRRA7Clz4h2Opwal0ruyCYbUVWRH7ERubkiM7XNSG4iIyZBmybeFgvswguLRIAygIUcROrAOCTuH2ciDR0S0DhTipS0cz0NJvfbpY+I4pVDVVooAWJDAhpri7Eg3R8ZMR/y5Mqo60PX9mFNBcORjwWRMWaSti8rNUgDPnp+DzerZTHlUrTiauR4r5bunKMK2SezKQWFxYTmLnaeFS26tNG4HAzWgeNhfTIVMRmzxrjbghwCU1aKemmsZWR8INLadeBI8UAk3ZWhYoWKk9cDtyqbC8pFJIF/f6cxeLqVglA4FUnGiFrAcKckxkCeHu9HZYBK9pRKii/IudE6iZPfGd8vxal4I6MNoq2m8D70umyETL7wCY0U+poVlcCioTJEq2KSIspM4Xz6+4ZELqDeE1V+/bSvz0VhEdMU1HXacvNqpIu/HSfDHoVwjVHmLbDKhJFXgYfG3E/zI41CzpgMSazAZgpv60NSlWo9F++GGlwg26hENtU+G1yPKBXsspoITFsJvToQ3bBuOqvgUDvg2Zr2wSRaQfgfk52qVtkTSYgPykxcAHOm98bcTwuaWnngvAf2KjX84sOoh7ISp2KmLG6GaWE0diKlKvxdO0qZxkQESWFPheQ4OrGFPORMxk3vxA6acK7OHokSTGQwi/zaIbUOatDCQCwDwBpTGNuNJSowyPwwyMOahXj4wa3Hg3ksIzW1m42JB3LS8UOgnfhhze97ujE4m4nraDaYCXztxajJGhTTNSWOZlmvMz/ZblvDQyuKoZczQATXW8qE+b3hIXg1kFl/WHOROZuR0uQAaMSK3snm0qcpV4RcjYx7LRMn9bBUcqd6JmR5XfVH0bHLUuBuNTDzFni8tmUeXcu/aYLkcqf7+3hDbwsdS8Q8oYf1DqqlxY7C/CR0QjxedM2ZAtdqWFLMBg12Quok/O+4USSSIx5rgA9vgS8fGLHc5zphjLopnBgdDylHo5ciqLYJzhBlAYDvr4CzluiJMzRiqi0NybqIIi+3Rg2XJldDazI2gyuwc0j0QGzBJoSQMj8PHRlVkWSKu2khLtoMRIssm/gmQJBQFjGDrOucgbXM2UsG0GBwVOdikT/3CtFjx9iOhSpj64mKvuy9dKy5FGJaOO1XuRCfdXzBNRELR8YCeGdvIhz+/SdvIMg6cHY63BQFUMWffmnsfcqU/eu4wMkaoBkeFTiatxOikWwbIyTvLHbVKoHPGGXvD4lr6KRR/xvub8zL4H1PIOK7V2V8tLF4b8kufa+iYsuC9tq3o9tJXuUYKCUd+fID3psFAL5kJ/WRSKs1KMol5VJ52XP2pUjOctbQaVY9K4CFSxIHYWCTAezUWKhFerlWSHjZudKM6Nmyiabc17Xw0raRe+Iga1q5jUb2OlVY/dFNwp8/pRfH9cA9QwMVP+vrczEKMXLYK6PZmIkQxpk5+QEK5en8PmGaHyWpxNXiWjehRmatKXNUoLM1ZcOrzBUgrLoVaSMwEX2UsQxw/LCUWbHC+c7QNIezRlafxrBCP6yiHADkACy82XHOzMWkhBHBfFDWYQrCUjfKMU0dVhctjuqExhJeXVYcYywqdjoHkgp4PboiS2IRww1kJl0l4fyJ56FjE/pj5PKg698re3jmUsk5oEmOqEwCYdjVyI23TwZXoxVWcyqyXUU89NqqFz/hNiGaCeHspImTQ6mbNim9H0E68SGZYq1N4hXhvSjdqMLXexUKR0S/dGPYymhMSaqV4QhlEHQrY3JaHORhpeTYloIJIKKhXARrUGKtNwEYYpa0VRYSukk5S/fNbTBFnaDd8MJrBDnX5PngcSvEOOUPJUw+JKOMwJ53nqO1OmLhxSETIluusvBaskiGxaFPNn5KK0kG47MgLqJy3az8TxUiSqrUAsWZiTxaO0XBuGk1biJmhszn5aiOWPiIkyZIR0YvC+UpXQy2zLUXIl3SsYt+KUdD72dr6a6oxmato2JIXXVvRouFZ+Gth09jUxl73AaDg1oK7Z0NnSTYVAovCxTyWx9V2cH1cjNOHaWiLrq2FCUYZeS18BFHdcRhRVm7+u9cDpNB1MynwqcwZorB9oZw+VpI0jS5s4UDMBPY/GowgqZ65GzwcBELVK6fBUBRZrRStPUSv90nW/hRlPGaohrSL80TqoyuNVr91w7iMSH203LQkx9mcdnbUigDmt0jqdZ5N8sHeGM2jW1jRrEX6BPHiDrayXJPOCqc7lFt+b6eCWLDfRLF8KuxbFZvRic5Jxx/6shms6MwofcSSuaSNkHPt1ms4G15zpX/oknaeo6gPL+2uKuuRoOXEslQW+7teqirh4wB90oLFElpZXmtNlLgqDxd9zfNTsk763ot/6b7lwZlOjkcOkEZd31wPuvrc1FYWNmErkTW97Kz4gg5dcNLkRG96Dy2Ubwu8tTVHtaUb+mfazkAvXQrrLD591fjJOsCWNmxguSfy3zYTDNdleyFzGpWD1ZjpoNJDb5qx5S7q8Fh5tlJH4gD5mkzoRv63/Pe4bDOwrWYEgHHZPDBLQuAPk7EOp25asWum9XdNuKOOHBaoBhdbQVGbxwJoUOaFqd2TTr/pbHLZOpkZeYMcOEOcoi2Lsn/pgTA44byKk3bZAdE6JvduhOpGSHtdeAhqIWdBTuimRCgtnJ40/xJZn4ZpXtxhhutemM4k/HJ1hTUB0CJjQb4842l+U8fLe7OeP2SfLaLwZVslZCnGOdxpzOoDGFShdCtmezFT5pYlCQAChFLi5qDKuPNBV9DIV5F6pKgNc86lbsZ4cqwQFRH09YxfK1PSnTVg0EKbnmfo2xe6gqoRes2WBzVgZuRAY4bIyggi6j9KpZ1acw0pni4iIVEvLuZAijPEgt5EjlrOZBUjqjPlEUucm21uvZ2UlOsgxO1CR0NFTG8Haf94v4s4XY0EjSV0CcWmF42/VpI2+pKq7JXAxTFlsrHlZ+le0ef2B2ugrqCEjE7qOj8eT3wgOiT8LPkc24Cr5MWELc740AdyeqBoddHyebcVya5fMLEf7gZgHWYGirlb4Q0ecEc1llUaLl0kgqbn7ZU0m21W44kBd6IdL22SbJEXCkilNyo47elj8UGehuJooQESS3OhRSs60GbNY7ApiZA3TxnTlGOyeZ7lHVmjUbP++Jlos9yBg/R03YaVxFR0OvJPUcjFVR5ETLvhx64c8/CdYj8u9OWpO/7s1gI/dMYXJ05+RypQd+uKqKSsa3a9+t7CJl7wIvOlHA65QuNebIroGCAhMpB+FOHFZs35aWdNqHcP5UnK0GWz42atb2euK17QcosznVcqE7S6k0DkFyuBSnAz/v2nhUBBIpgIWe8xkH8tK/PRWGh82n1QugjCvynX/u1XizeuCAb9mInfjkBRXapbFklogHseK2Z5l3suAhNARCVxURMUZKNOtvVQmZR63DlZcx8wmHFB1RnXOe9KTBZl4wEGnHBersT9iSFz+GO/4AmkbYu42qMuBrYnWgB420qNt86Uwf4oOss8Xok30RZ7NtI4pAxKDatC59wWEfsCaIBuV70ACCSorp+AIWlr3bHt6Mrsb/KKj6sMk6aUCKf9ys1N+IiVqj0ZuDnViKtEv2ux9cd47ghiG+GFEDsHCZ/BT2k2BEzHGgj7z2D0uNeCMBmB1mYSxE3JhS/DF82wUlJpIqc1ip5NJX57WwHAdLrpEoi3pOpSwWEET9w/WyiKYeLmgVpB62BatqRNTbjXhtk5srZ90Ygcdr3cr2ocmZIJC8ufMaz7WS20ycjr5GK2qcyOuqxUI+YvYrZPCqxTlmLVVM2Qn3mdPTRCZ8CQCkmdmWISugdEko2DRNvSbi8EAmkopeNjL0qA9ydZSbeWr5uyJP77G5XrZJRJ/dKib0q6wXEyl+vp+dzfjHYYlmu93EpjQOfOa6zPlH+Rw8Ni1c9kUe7s27m8nPkdLFQ09+t60L3rqUqKiyLy0GaAjWjO2qA+zMJ8co73ArDZ1vVPnqIFudPWW/OZKyFtHve0+9G3YRZvGp4IqW7QZ4DHdnovjBIIQFM6/xAMjsUdWgsOTNzITqPshcDk9pAVWRqZ69R3pTuMwk1AzIKmn5Wr50xlFkresIRZirPvzZK6idU8qB2eDcWSsKnq6gabHFUQGL+K5GRRhklfLSBRAag7B1XgxPpsCkk8KWgZq3LuDszgkZNjaqeTU82Dn1UDqAljxDiWyHI1NInHNcTKZehihPhVM8Ti4mfw1HNpOxQM67KohBO7c4a3LX41udZY+BVNaaoh5f9Vr2EPuvrc8Gx4IfhhwjJ4Gym+vtJN68Ek0WbygMIiGLETDNA/fBqnqLGPjEbyX+gL4byBVRGqd7sSmyZHs3J7MeCEc83A+H9mSAAyubVDg9SXCyrhIuBHbARMpLOfvW9j2kKMotpytbQLuleW+GgyoUMmDIP9MkQh9a/H64djmVWftpEDNEVw7GlFD0xAYPhxqgVpXZVe36KY1eUQDeQZ1sHjSW2ZoqT101Ml9g2skBodtAmJZwZTOxz5X8shakdksH5YPHe3oiL3pUCoS7XaZr9qdEWwK6LgUJJyIIZX9yn1DSDG0XOEI8TKkbYBbAY0xyL1chxkjKxg6Ao6jh3IKmb0epsPGMAMMqm2EVTNib9PZvI66w+EF2ka+MmcI3eabNsXCysY+YMPshmodA0Z6N8HS1598WBcUzMAtANM8umUdtJb6+Hu6JSBtS3K1+ptiymX22cuMrys/CwMkK2tGXzZNw5CuFPP/MQTeFT6CxZEb9dHoXO9NUzRVVUJk9ycer0+fpXA/M/GrnfAIuUufA9BimsdISpZGf1N1FDrcpkPO1dIVk3dlI5Ka9o15V2tyMzZioyS/esHW1UXk8uMmRrcuEXDeXeJnFgNQLXT2Rw3di1EXEu0eci0XOkMpNzqcV0T7vE67kayZ85Hy00iZmE9Fz2mNYl1NZhTwrFPpB3w7yciDE5aCbN0udidLf0CetIX4Mxk6NBIz8d9/EQUQm5+gFp42Llvi2FR7AJFpcD9y4lBeq+w6A+5vUoabeR5ghgY6j8N0UWmJfiCj+upMyCSrNrWTMs3rW4JvGeIX4RTzZ0RZ45W/giMQNGrgFAwvBJM+J3L2sc1/re+Ew6+awkEufJ88VmfLQBFp5oKLlPMk6N5Fn1wn9q3MRpAhhdoIipGpiRr4eyT+16noyZ961xzGlRakAJf8sohNCYTCm8NXQymozTlmtxJqjHlVy7V1312nOgxnqf9fW5QCxUldE6BvkciYyxlsWlttLOqt32BEUxiVQWc2Z2wJ7AuVqdamEy81MFq7wJJ9Cpxp3vSuT09QHtNB1e9UQCCEPJTdmBANV18J1lLDN4L8WLkuiUiKqypfI+5IFgtwI86zwOaybObeIucmCL2+HcsyMZEjd1RWd0LqkPLRNO2Z0rb6GT7nM12sKY1g5GF6NaJ69G/lnnisAUaLMv9rcMyZpGLDEb3IzsvI+bWObJGcCbCxZm5JgYrEeIOiUVc6woHIUbub9PNjww9PEbysyR8HZtNT54MtbpZPQy5skV9OONLaZRY2YHvZWZKTsqSCFgStF0MzqBhvlQ3Qy2eF3chskDpYtKlpqkfgqd7lcZd9uMhQYCJYNnW4frkbLVMRk83/Je3YjTqqqjuM5MYY0DwPOtKR4UADfMKZZZFS6mHKaaE7OJhMHV4t0a4LRNpfPUjtxi6rRnTjsWwqJzP70PiyzZGLE8Y9tIZG83sO5QEJDKTjbXwJSfcVjTKOl5ZwsfA7I3eCm2nYXYIvMzPtlMeS2NFDm8X7zvysFSsiSAYvy1Dg4vOlOkv5WMTPSZVglfZbOol7jmAF6D1jHNlYx5UwLEknBeElDyRLSADPI/zu/JK7gZya25FVRHCyI9hBKmjVp9HCrD+6fqDh7kRAy14ItS5BzWPJzuzbKQPmWfgiJNtkghVyNwUIfigfOic2Wv4rUT/wVB+5yZPH804jwmNU+L5fnqE5+ZkEg2P6xjKb6uBt4n5TpwLKf7by5NG3NrIuWVO2tDOS+KvvFZEOJlE3FUs7EKeWp0tOFU+XYX2YjSWBE4awPOez4vJ03EWatOuVwLq9GW8Qb9K1JRpikiwNGhEe6fSpX5/u7PJuR8z+fSxnZJcocyR+CUmPJfDdSaYfqsOhJyhsgCGyqqXYxcH72XzijJmb/rojelOVTU0ZppTKJoh+4xdIm2xab+s77+xIWFMeahMeYfGmO+a4z5jjHmvyd//z82xjwxxvyO/O9f+Wd5vZQJGzoDiYzVjm2aTypSobCg6uuvxRhoGw0+XHsMyRYEJMqh43YKiSFONtV9tCVe96jOhfUNTNHnpWqUA6O1E/R6NTrhHUwx21HIWEPkRqQPR8wkgwWBgmmIlLBfRVxLQmUCO9ejmiOQXb6HjiDGxAwOlUzWFvjCklbb5ASIPfLO3aWFMxnKOh+eCXlMyaScDU4Hlc4KTxrq5QfZNDmnNqVz0ANi4QnbkVMSy+hKN5ub0RYzspuRuRdrIY8+mEuV7zhvZzSy2lqzGKosod9NMCUXQEmbCru+6l0hmOqBosoTK1yGTSDZdkhWIGmUQu2w4uGoBjS6oW4iJXQ0+rHFo6N2CUeiAQemw7AYI8lmORcOxt1ZwH6Vy2xTNxemTBp0KZdNaC3XygknYxssrgaPF52TIiYXq/apG5tGdSoXa22W2XouHiW6lqKQGA+rWIqI856sf87dU3kWea3SThGMssHrOE5hZlOeBXm+d571IYpaSiSC/JlUSJBDmtCtY1kHxT/CZhwKgsfPnotEcS4eIGpgp2onZ6jQOW1jgcgXnp/3ULxBlJOgRSAdEZN0lLyetAdHCWqzyOWA1oKDKEQuzyavSRb54dTNW0x23vrMKvIFTFbz+n78zv/0ENGCc+553ZXwzN8xHRpLP5kBXonJ2Z5PuNvyekXpZi8HBpIpv62LtoxFFQFTorYW/QCLTvVSSBClE8zO85XL9fOWYzwdAQHTgbnbBevYQMmKymnS+X8CSsL1skpFAaMHZ8xT47TwqeSRKJG6knWkoWLv7iWoq6RGmHeR720bLF52lFu+s4fSBKhSTPfAiTtmCyL+YJ6LU27jpswpJW16WXtDmozXCnE/Tpb8ajA3d1xLP67KoJkhhQm1pfhBOSfKuVNPH/2qBA0a8ySrH6IEN2LiADF7hZ9Rz4s/pq74U41CAoB/K+f8W8aYJYBvGWP+nvzb/yrn/D//Z32h3UWyX5GYtV9NECeLiFw6g9YRelsH7er4OpXJuApk7Gu2xcwnXG0dAHbl+xWhos0IsT7NAKaHpBNzIhSYlrNHgA/EiXl90a9FHnlg1MFTFx0YW51VmsdFUatPQppCv+40AX0iL4ORwYQO77WpKGas0Rkr3+cgG8KeMPm1M9SuWRfQLkSrXJKrgSMBhV6VwIg8SfMqmzG3ueikKwu0hr/8VvTMrWwgk0nLdD81Z2Thtbo10ByMMbFavhky3lnyZ+60IyxQoH1nEm6MxY1YCa+DxTt7I354W2FeUWLmDWVzfbKYNamw1aniIC/nsEol1lkj2N+YGazCFNc+F5Mb5QModyJIaT9mU0YoBhD1ynQfKEnNhdiqEmclEHbJoMoGBgnLOmLrEsbkcNYmLD03QGeAfgTOWouYifDUljKvJxum+94GGvKsRqAyBu8sgZuRxdbdNsKYKdPm0SLhh7cOD+fclB4upDCVw0Y3vy4ZuMygJRrhcNYL8Pft19O6WgeLIxvLOES7w3VwaKRDHvNESNP7kQz1/Fp0qBpAr23MwAxTGOHDeRLSHjvGtcjc6K6a4MUT5mzG+zYT7lOXNDEyo/XptZHSJlpEQbLGbHA9iGJGPFv2/PSsNnZSiql0WpOB9dnqInkhS4GM77V8toGp2IqZe0wGHR+HBBkzTE6aCVPqrY78+IzytTVuvjJGivy4g9jx/R7W7OK9YYiiMv/VNrtPk+pn09kiGd+rIn60rnB/FjmSBRHfJxsu7mWV8WAeiz/QNlgc1AHPtx61yD0Vub2WeTxN8gw2cvhU8jzEPEUj0HZ7h5hfofBptEBVuSjAEchGCM3Rkv8TsynKhjGpb4U0GhlSWKtNPx2KV6PB/dlYzL1ug0HI3CvOs8VJnXA9cm/sk8XDhb4XdcLMZay2Dm4yZYsWKXNEfFhzHHw9WgltI0E45Ml/pHWTTwzDynit+51924ANo44qdO8eswEyZKw/NYnrwD36tEnCp3IlQ+k2GAyWv0vNrVJmQrB6F3FtJVwNHprUXJmM2iuXg3uPynDPh8/GJP7EiEXO+WnO+bfk/68AfBfAgz/Ja1kjWl6p2vfrVAKy1pJH4QxwUgfaw4o0S41hTho5DHzGO3t80KkRjgWuU56Fhq7cm7HT3N3oWpelqs5FvjemCT77cSawM5PhFqs56u4zplyDo5qBTq1lquNMOlz9isJoP64j3phNgTtKRNUHRMl3yl4fMw8/Hcfsjg50k9Lrcyn2q9awk1SnUS2mVEWxFhdAhc46Gbkc1kRVVOmhndBCkBW1clZS3zaoVS+KHWztksiXeN2+chDh5Q2kzE3ranTYRouXvccmThtVFwn5k6iYJdyH110RiSgb67JiN8nxhC2eBpvIawwokYufvU+8jqN0oCoT5aGgybamGEIBQpaKk69HH9kp6Oah3gSqWNGOjOM0j7WYKxVr4qLIITpkQAh9Ky59lwMLjZAw2XjvHM6tVetp9WDgGOSspfVzJ10MO+TJhIcFJw/XXdkZkRqI0yI7V4VjFaWi/bM6o/IajMJjUmdAVUjoGlM4W8loHBUakbZarIMTpjyfJVVxqVqgsvw8aiJFN1FTXFU/WqshnZCEZUN83nleFxlZOUE5AeCoCeVZ1HvcOJpoaRJuJYcq+Q3TyFPdCQ3Y9SmXSAmGmm3Bz4rStSti1yfzWnPSR3pSXA4G5z0kQ8QI+kN1gXbtq5HciT6aUljpiFi7WU3snavyKRvcaZRPMqVixsxx8sJHsfpHkUR7k0sEQshEM2aeiKAeHl20JHXL/qNEwnWgbTe7eX4+LRYUgdD/Xo9sypydbKqdRXFVpXuuZK5klMaCxmpG8mb4vRlTgdE4olVG1qCzk2fL3HNNpAysR0HNDAt1oji6t2Ea+cg9GTMKArWJ/P06giKvik1dxhTASORSLONNLlJgAMKHUxt8FQaQM6F7RBf5fI1J1zgLSHVg1TNOn5U+TblautfpVxbkRH/XqiDIbLhuRqKy6r6pSI/e8+sBn/n1z4VjYYx5G8A3APya/NV/xxjzu8aY/70x5uiP/XlMHVQjG3HG650vjWGswF5cLHNBIHRW54zOVlFmyS86D8aIT/kLCueqEQgtlxVSxs5cecoD0a8bmXuPmbay6ogW8jQrPqoTZsKq3QoqoYQ4zZYAJEpXXisIB0ArSt0cyIGYGNWKfszclJJ3JeZaK/E2OKwijusoDpPCBBboVRMzg0D6a/FNqMxE1tS54ZTax9+xCpO7zdxlSRadKmpl9AMoHIOEyZlSiXwaXf/eMpWN4GJwZYzQCNzmTMaD+Vjg1POev7920z1Rgu6LzhY4ee7YaVU2FyOkk0bhUrVj5/vXyPXDegqP0mwMAEWey/XFQk6tj398Lr/7pWm5Or/WzeFycHQxNcD1yDCrXroPTcQ9qCK85b8bAF89SFOSIqYcGbX8XXgeEhtB927DVGQOkYomQrsGqqJQiP2wng5rZbPXgq7djFaY61yPR3WEAfBiawph2RtIVsW01mKG6ObZdSrKFgT1ANSXYBohqH+IAfCsk3waywNQZbb7FV0g18FKyrER1RORrcshl/XAkC4ia4d1ggZ6aTCekhz1uuozrTPsmU/lgNwdIailfR/ZkffJ4rSNEoBFvZGVInIjHWhrMx4uIo7q6dDX8ZuTA4QFfBYjOeC0mbIn9BmzUOTI4P0VO/DTNmIQw6WYKBtNIFKrdvy1oASr0YgPBtEl9cO5GhzuiOnaKjgc10Rw+sh96WXnZDwZKY2XMaeOTZ3NuDcjOljtFF06pnWGdgAP5rEolXT0oVC7Or5qk3dYRUFj+XwpbyBlFi57Ppdibr8SJ0rlIMmanHuGPm4iJbKH1VSkqPstADxaRNxpeb2XPuFmgCAsrqzLB3OO7TrZN8973gcNW9Q1rCOhuZtCK0+bAGMy9utUbAB+9nCFu20giidN7VE97esxT0RVbQTmwjvUa7S3kw9zXEecNLHsRWOaxsUzP5kTFo+QzLNIx5BzD0FMJmXLTJoSrUdql8oYvPpjKoc/dWFhjNkD8H8F8N/POd8A+N8CeA/A1wE8BfC/+Ck/97eMMb9pjPnNddyisYSXtLK+EVORpZ8QgXXgLFiRh000on+ftPQ3I3B/Ri+Ey8HiRkiBtCueCgoAZRNVsozOCAGBzyy/f/JVn6xnt1IIabehHR0wpWo6w+CePZ/K363Fd92CRirPtoTQtdhYB45iSKTkTT5pUklvfCU5AOq6eD26YpMMaAdsi/SO1sOpvLameSbwmvXJ4FjGIvfaUBjNSvzUn7sZTcmJ2BeJ7UYMzPQzazFwIJsHDxyOavTQV/OzIU6HYLvTZdFFj9dYSZwLnwsXAyBa9Lxj56RFJyFAKyZgqSTw7UpGc54+10yMhXqBimnMQ7h5dw2s5LMrQqAFlPov1G6agWtXpbp2tUvXe60Hk3JhFFKvLLvLuUgVNfNAr58SjPe8HvzsItW7QUcputl7i4L4XMt8vE+2oA061jis+JxoIUUr4Vg6cBYIyofgtfKGNupqy03imy3aeHUaXAeU96JclU2kR43OgblGJuJaZXl4dFEzEoykZaYy+tMY8Uo6/62s+zEbfGU/40SK3VVweNmZotJQstvdNmBMRARiZkE7JIv5zt4wiCFSL79zLrPxWkhz3jJGYFYObPtjI6BpJFUpSgR21uc9Cxw9BPRe6/VupWCfKWcnQzpHYL8mIZIdqaJnVGk0lgTv1TihGrvum2NCWZOQfWgTjJDbSUjcSPERZCS6Fe8GzctQDwf1TeDoiu9TvYB28ynUi6F1TCJV7pkSPbmnTmov7aC5t9sy61dioZq2aXYFi7IJqdPQw5XI/vtoSgG6kGLxvPe4GR22ggDvy79rI9q6hAdz5YRwr1TCrbcsKGnzjVL0ALy2G9nT9Jq87FzZk2vL1F/6jQDvHr8sknZgknE7QZU38jkHGc3rulJjNW/URmByo9b7oO6iRs/ScVLp9YL2677SOBaW6oZcWxZXlZwTaiOwu280NuON2U82U7tffyq5qTGmAouK/0PO+f8GADnn5zv//r8D8P/4tJ/NOf9tAH8bAO7Xd3PtyPI+rjkT368p36lMLgt2ZnfMfnzE/dmEVOjGeq/NBdpn1cUOuDJqgCPM5ay8BCPJjOQbKOGNTGsjBJtU5s5FT57xmv+9N4wG56Fn8PZelkPV4E4z4nlXc0GC8PZoDaoMfHmfG1VjpxmvEtsAh9omWExyJY3Q1tFHZTPemIXSbVGuOknzlp6hY50gNZ3AefowKZHqVgiJzGHJcCB/wdmM1ejgjS0zZO1+AX2QuVloUaJSOIAz2zWIIimkqA+Tk0q9l+JB2cZ6KC5cKoZCrTU4a4M44fGBOu8t7s8iknjhd4PDQR1wOfjCz9lEg3str89CzKZ0tEFp6bR25i7hQDJTmN5nxeI6CydmktgCU4aMM5NShT4OBjFnMUQC9is6bgaB+BW+7KIRgzNeG3Wb3URbul+iSOKuKJD8fsU5u7fsmCuw+Fv6iGApIVNSnkKYJH9lPN1WXBPRCKJncVxPCbG1ZWH3qnc4El7Jskp0kAQP8OM644NboHVqoU2Z6iDdzX6VUNvJo8AbmmbRp2Cyhee82sghzWIyZYv7M15jzfFZiQ0xsz5Y/FwMDpswsdkfzALdA7NBFyaS320wuA0Od9uIhYzCjuqIyu4aPgkKJlD9EM00Ek2mjLgMqGboIpN2N2BoopXfM/e5FLNJ0Fct9DciD19IZ3glsenMsDHl/6tirLIZLvM51jGV2oPXNuNL+yzqriRjSPfA95YjbkZXUKOlFHpf2h+g0fZ6bW5G4KAiMsTXEIdPQ+Lv2wtmjRzVsRQkrSPJczUaPJjz7x1yCaFTUrAW+CwoLS4HkXQKn+lKZvQkeE+qNB0LWhD9UrJ6SPzzPTGxMuC9IslQvGnspEhTU7vGAmOeTMrGzIKK0fBUpOxXRAnJ7+Lea2SkW9dT7AOiIFLIeDhPhRyqY2pA4ybISbnt+fqttbL3o6AY/8/H78DI/ng1uGJmGGT8sPA8xxox9VM0EFKoaqGx518f0xgrKkhHdG8rSrCFT7joHRZNLGh17XjGKjp4OVjUFrjdceFU12V1ELWGaNjl8Hp+yo9//YkLC2OMAfDvA/huzvl/ufP393POT+WP/2UAv//HvZZaW99rOe88qiOGZHDWjnjRVWXm31p2ZzmLZh8o8LyF6IDl8LAmC/veFiRCq1yZ3nMGmoGYLeZgRbsHrTBTifPtRLqkMsbTJqBOtpgAXUsx0kdg0QCnLd/fnqAryuJtXWLQUjAi6+GBxKwTEgxn8kB20eKo4Zw2gYv3sCZrV73tT5sAtT0H2JHdm40Yk6I5ucQyL9qJtJOAEthjwIUEoPxcbaexSJbOjS6ffI1gaHvbRUpN1VchZZXbscNbBSszfhZAuzCd+n2ExA7j/izDyiG/Gi2Om4jzwZdN5KSJ0MTLZ1uHB/OMp5sp8XWTJGAqTYoiY5Qpz0NvdAmnDYuMq+hQOxJUn2wcDmthY6fp3iiEvycMdmaT2LL5FblaIhF3z2uEMzAz3Ci6pP4WE3JyOUw+D63LyHo9gLJxXQ4GJw05BLWdgpmedw6NI1Kh7HIlWumBYd1EQF0Hg7bKEnIXi1Ok+pbEDBzVgRHUmUXhrRBodWQSM4uFLrI7147ZGXKKmGFisS9QNYCicFB58hCV3xQL6mONKVylnA1GKIfDwJgESLF80VuotbAzQPATOfHhPEEDzBqX8KJzxbVTTdUWXtJ67fRzM8f5975A6PNyf6ekUSoEWHQz+ZHX8Xo0sDMJ/5I9jAmzYlOezORxIB1vxkT61s8x8ac4MtCMG0UcdNyoBEx9BtSj42owOBUIv0tG/CFsKWxOJEBs7rQ50PFKhK8z9irhtCTeLx2PrQO5VSQGTsUsgLIX/tE2Y7+yhfNmZPyjLrebaJDgiqQ8JOVHGMBM3LDKsst2NheeUswGXQIgBZeOFhoXUYuHDsAC9UIaKQ2JrG1GFM6UFmKAqqWMRAhAuvWMx2uLB/NURnjrwCJnyBrw6HBvFgsvRtNklasH6Fhrt8llQXR/rnwIIfSD62nithiEYPDDW+DezOCs4t6kTVCWtaC5H8YkQZYm7hugVu4M8DttkuQ8TcX7UU3uTAZH0pvE+6HEz5OGJM67kvjMwpAEVmtoe3DWBrQuY/tjaraf9vWnQSz+AoB/HcDvGWN+R/7ufwTgXzPGfB38HI8B/Lf+uBdqbMJX9tfS0U2W1iqhW/iA45pskZQNnE1YjxUO64BldCTu7fzcmBosfCwQ51iqwIBVoEd+ZRNmPhbzH1o1Z1iXyoYQrUEKDkM2MALdDomHasxcJOrCeBVovHVUBzSW9uQkJFrUlkVLZWiZrOYnwCQBBEiQPO895i7ho02FkyYWJ9GzNgkKYwrCsSc2wzpGuBodWkF0qMP2aCxHD5XNuBq8QHsWziX0wYjVL99X6wi15jxJqC4HR/6IyxikmNIqFpCxjU04kI1HZ+gLn3EzGjzZOJz3GQ/nQDbqPJpLh0C0ATisA1YjkySVcazOigdVlFyIXDg0MQNns9eLTWenzlLHHtejwaHhLP5y8KXYo7qIB9dHm4CF98LnUVMcCOw9RYnzc0fMHbt97S5LhykkwiTeGftVRMiMuuZ9TnLP2c2fzqIQsF53iNQH97QJ6CtTXBjVVdKb/BpxC+A1fdE5nDQJT7cOZy3dRxee93YtCNwqMFROUQO1yrfIxSq4TwYXvSnKF3ZCWojw2j2cZzzrNBeGoxz1Q7FSMM1lbENfDCsjG+EDZE0UlTHeTgPE8UPCy94DjtwD5c6cNAEbIRAeyMYaksHjNdG/qwEAbCFm50x+xN02Seer5kBASFT08Jn2Zaat2TpddBiFh3QkSKoWTOe9w9UAHNZsaJzh4TVCpXv8SFpUv+i43k6bJNbd7KaNzegMC4/VSJjZmddzUlIWGbkUPConbhzKwa8/k+X69dHgoIq4Gn1xmGxdwpOtZQieZedPgiefe9rd+2m0AElwzgZzH3E9embkJIMvLEX1IpD8US0ujxao7ORgyfuDIudN8mweNbwfjU3iBskCl52xcGMkaVT3FB3FqcpNpajZTNLltTSahahtNJTOTmMpafK20eLeLAv3iSZgalLVCvLZiQv0NvLeKUn8xWjwUBrXBCBgyipSR8uTJhblYuMmouQmTM9Jlyw2MaG2LM4qeS4zJklrFw2uYIudtpXmpRuN+Lrwcz5asPDSUfpJE4s82CIX0QDH4UbsDIAXMrKZORYUm2ABR8SrsZPAYZSRnCJSn/X1Jy4scs7/GLv2lNPX3/lP+1qLpsNf/eKvIYSKkFqskJJHl/aQkkFVjYijQUoOITuE5BGig3c8BFM25c9j8Hhzz6F2AVnIPH3wxVhriDxA1NZZvzhT9cKWTQhZbKph0EVeeHWGs+BinbuAdajQ2oSH864gIzkbnNmEl31VXCFp0MVN8aQJovgwOG0GPO9qHNWhHNoxc1GeNANuxwrOZLz76DH+4je+jYPFGrebOf7Rb30dn3zypmSs+DLHIzmPC+i4VlIdr8PSK4LCkYkiRCvhdbBUeN2gZswqfZqC3/QMWPhUKvAuWswkt0IRo5Mm4mqwuDcj2VA/M8CDcOETDuSaanJkWydcjU1RFWgMdR8toiUS8sY8ipcDcFgBF73Du3tDGQ+dSxdzVAeon4CXjU19E/5g1WG/arCsMv7yGZAQMJkPZdQylmhdEujdYyOwtKIFgKo9gFHSWR0mN9EN2JmHBBhjRO4cxWOBHQPdSoFXncNJE7mRJouHiyhcAFfgU0CUQDbjfEvUKmeDB3PC38o49wYiP5RANCkctCtLmXLf1gF3Wq4Rkkwtnm6dHMrTOCFmoC2/X9EXg/f2Qum8KUGdtgNNE94GBt2tA6V3XTJ4uSHkqqGBGxk9ECFkUdoni5MmFul4zDRuCnky+jqsOBq7TRZnrcH1YPFwTsWHusM6l/CmkPZiBuYVTYxal5Hy5PyoY7MHIke0yKWg7aPDvqyHJCOMwzph4ScTIWDK5tGcGz1YhzQhC7XLBbHUa1tZ9dZIuBZXX/XT0bU27HTvAAQp5KFwNQD3ZhmnDaXAJ3XESuz7ebjwwCAvC7jTkAhPhI9jk5x5na9GW8ZKanPvDHA9emhq7sxAFCRGiKKmkCEnFRSK3HGvmnJsdByBiJKXcjXY4gSpI5elqOoq2QeGyOI7JI4x1axu4cmD4j7mijRYx4lLGUEsfGKysSBStzJCipbS0Is+44PbiL9yN8soiY3jVw8SrgcvihSO6xtBTq9GV0au11JUaxrtWRvEx2Nyc+4FWQyJDsiV4bP4iyeAAQPyNKtlEBR0WSU0skeHNO1pV6NDJ/sNzbuIsutaKTboduJxaJJp7TIWoCPofhUQElHvZ1uPXE3P855P4oeRC+LDZ9Ki3nEJ/bSvz4Wlt/MBb9bfYU65fCVYnB98CXH0cFXA0c0H8JmoBR9XgwyDDIttfYSVu4ccHaq0wX58Uv4dMNwMjEHOFhd4E7D82G26RIUOOVuE6BGTQ84WxhqMucY6HCMlCyChNStkWPkegxA9rMsYQ43NMEcCi5kkD2mGkAHHioWF5yEeosMQ+fv1QX1zz/GTmIzldoGZH1G7iJAsHixucefuM/zCN74NL8qW5WKDv/7nfw2//lsDfvjRI9Qu4nascNZuMSSHxkVc9g3O2g6VpW8GGeWESQ+zwaNFKvDdkSQCbuT7NMEvZfITjKA5taOj6ZAslhW/7+GbH+HP//y3sVxssNrM8Z/89s/jdz54D8f1iJQNWuvE2yHBiXmRqiUOKiIyh/WALtLKPGd2Kmdtj9uxKlJH7eitoZfBYkFYcE/inxNQIsjvSEImCamjdEamWCh3yeBfOmlwR/6NXbgrAVwa4OMkQE65LL2gFKow0rWo8PGzjj4UlP9N5j2jQOPOEkqv3WTmBABPNgZ3Z5Pz6X4VsRV4+dFiwNNtjcoQeTptOO65FZ8W3eCvBidGNmTAq/plIxs+LX8Tqjnv5XFjC0qnG5pKgWOeeA83oysplWNiAcBulmtHu0lvJ8datbkfoY6yACQDZeYSFnuQJ1i9HCbyciWHVpBxZBdpw93JPrYVNIjZFnRr1BHCzWixV0WcNGJpbnO5Ls4mhGQxSpe7DbYUt43NuAUQMp+P1qbCmbnoWNipdLSxHN2pZHErB/Q6WDHxIjJwXE+MfVUmJaiJ0YQSKOlTEYl6B7nR4uNqsHjRGXz1IMDnjEoQr8Mq4rA2OO8tnmwsvrTPtbYvjcvkNUNOGkDDJk0ZvhpcIfitxb30pGFRUtuMQ5fQCT/gvKet/1EdmBEkSpyDmsFigxSbfVD5N987ZfzspDfRYjV67FepdPqtXAeVeW/ixDHjzyasxonUf94zqPKk5qF33vvCMRnEu0YLpSjjWM38CHlSBcZMhFdJrfdmBieNhzdjIYAeilpnr4pwRlFIFn8LKXxuR+5bJ02UkTF5OEMi5+ll71GZjCMZW2sxpNJrRWTUuO16sDQRq2K59uoGHeWeGqOFqDRBLhf5fCcE0q+89Rh/7Rd/CweLNVabOf7Bt76BH370FhqbsBo91AY8pClNdlkl4eKpKSNKc6UoYGUyjOM9/6yvz0VhEUaPdZzBmgQgw5qEDIvbywOkaOHrEQfZFqiazxvLCiDB5IwcHYxJsAho8vonf4lcvO38GLniKGK5foFmvOUO92NXYvBz3OyNHMfEjNPbP/yp7/+6fYC+OgAAzPtX2BteyLtjYZNhkI1BhsPL6ivl5w7Hx7CZsYjshKQQgsEmH2GDE4TR460v/AH8+WYSyRu+3T/31q/ii7Mf4nq8hzHW8D7AhS0sAmCAMVSwNiElDxhgCA1uhwM4myQoqwcMEJNHHzxgDIaxRoRFznpgcEPajpVozCOi/NvZvaf4Mz/3+/BSve4vNvgv/vKv42y2xZMnbwLYIWoaJVA5IY9arIOHMRbHTS92ySRW7lcjZj6UwkfjsUOy8DbhZqxQGeCdvS1iNvjissNR3ePhmx/jaz/7HSznG9xu5vi1b38Nr57dx6uuRWUNWhfhbcKJybgYarR2crLTA9qYjINqxCZ4Gi5JQdUKTKgblEVGuwPvHtbAfmXwzffex1/55m+XQuv/+1tfx/cevzNtDEYcDEGdfM4O7y4T7s16xGTRJUvPE+k0LIB77Vi4QpVlYfFgTnXAYR3QRe3AiVKtgpWiwOKNWcDM8QBrXUTX1dhvRnZ32aBGLuOhpY2FS3IxONoRO3KWNG+mA+XZSj7thby28OzWbgaLtZ0s8wHZsAS+VzTtRqRuTA2d0k3V7Ij32+BFZ/Gl5YgjuX61zdhAlV6SQ6GvnyA25jzkDVA6OGcMDuuAm9Hjk87i7b2AZ1uPY4lLr2zG3TbganA4agIWNmEb6Qz7YD4WNGavihgzD9bThmPPYsrlptEYgIIWVmZSHChJdiKDk1uQpMNvHa/NEA3utCO6aHHaRJw2wM+88wH+c9/4NvYXa1yvF/j73/o6fvjh2zisyEdSWfTN6Euh9omgedvApGXl7NxtB4RUl4I9JIMjUZ4921aTGkkQOJ3nqyGXMxwbqJPkfhXRieOxytqNjB5edJWMWIF7bRCPhlg6cx2FACjGfcDkxupNhhfo/aghb6RLBia4Murdyj1/2bEQ9Yayf6b/UlX0aJ5LIbcv+T+7e1MjRNM77YjW8YwIgmDeZINnG4O/+fU/xJ//+u/iQO7BP5LnW9OBveXvVqfKVlVXcj8SgHuzQVykWaxUZWyTUTs2UjNBC3S0AgCuypi7iFEcTfXnW5twWI98v8ni4Zsf4r/wy7+OWorJ/cUG/+qv/Cr+498I+MPH75Sx0dyz4ANQmsraJRxWIxFwx8aqT0a8o3os6wFdsPAqQ/kpXyb/uDfo/x++3mpP8//kC38DwJSHAACVqDEaGzGvBmTQvdCZBGsiGj/C24gMgwQJYEgR++0VDJL8e5CCI8HahPPtfRhn4VzAvn+BuV/B2YicuTkY+b4RLa7SAyGJBtyvvssj32RY8QpVzOTSPcTg9mFMwl54jmV8/qmfMxmHF7OvAuBs9c76D+Fy+NTvXTcn2M7uwNiM48VHMB9tf+r1uzx4B9EQ7lnePkETbj/1+wY/x2X7DgDA5hGn6z/66a/p30Jf0xZzPr7CYnwJ/Fix5OsA4wG8vZh+8OMN0gh02wVytmJpzaHzOh1jFU+Rs0Vtb7FvXsDYjJwJMRuTESOLoLW5g22/wDDWWPpXqGwHgLP+EDysHIB9mGMdDnF45xXe+uIP4PqxDOhisnjyo0c4f3WKIVQYUgurs0w7AEgYQoUMIESPkByszTDZIGQvfikWTh4+Hakpr2RMYpntRsRs8cYbT/BzX/v9giwBQAgOv/3tr02FlhRVMRm0PmATuG4byw1jHSrMPMd4tYvl+xOI+vTR0fPEZLzsGhw1RPEqm3Az1OVnN9HhpOnRRYfKJlQmYSNI2cIHbIOXQs+WbnHhgxidyb2Qgu7H/45EUYcu2QJ3A5ODZJLN0Mm8d0yTFh4AvvDoMX5FNufbzRy/9/s/g+/+6B0M0cFZmq1tAvlAfZr8BpQAeT16GhGZXDbGl32NgyrgqO7xrJvhavB4tNjieqjlHkXcBoelj1gHh2UVsBqJdO2JxFa/FN1YjSQP3531uB5q7FcjNtHhavBFRZTk+iji1idTDgNl7/Og4WGhG7WqibRQ1THcYR0KirARqeHMRzx880P8q7/yq+WwAIAxOPzDX/9F/Cd/+CVUNuO4HnEbHCa/DR5kB1XA43WLe+1YiJ1HzYCQWNyPyeCwHsv9ftlXmElXauVe32k73I5VIS62UuCqkeHcx8IBsiYLMhHKa1qT4W1CTK87HFSytgAUC3BrMm6laAA44lj4iMNqFNm6Qytj8HXwmLkJkTLyu8pzEDxaF4XUHbHwI152M4zZ4N5sizFZbIPH1VBJ3tGIRpqXo7pn84OMvWrAG/c/xi9/83dQ+Ui42VuE4PCr3/oGVi/36Sdi1FeExRdtslushiW9LKpbHLUXMGDR0vqA2gZ00SPnjGfrhwi5QusC3tj7EI3fwCEJETOi8QEGGathH09u34FBxqzq8MXD3wUE9T67+6w0hMgAThtg5tBtGzz+1pu4v3gMZ5Og5Ilnn0kYU4PvXv1KuV8/d/wPUdm++CXtfj1ZfxFv/p3vfyvn/Gd/4h/xOUEshmTxomuxEvbxEC0uBhKlDuuEe+2Am9WyyPqGZLFfEVqarKtHbANzQoCH1IjbVJgUuul52Yi4OX4Bbof0WRXiCy2lRzkYaeH8pfJwACijgtrtwOIZ8O5LyBlo3ABjEpyNqFzg7N4FbMal/FzARbMEshZKCc7FUrysLg5gqprIys+8RH2WpoCRzA8To8XtxQGuXt1Bkltp3QbBVLAmwpgEfjQWQENaIPQ1cjKoXEZEhQn52f0vADstJvK7p8853TgU5nb52kTYkDHHtQIw5cvOMrxICathjYPNk598TVmRF/sGS3sD4LOLpd4vcLN4iOO7z/kef7Qp/+YAPDJ/gEen/PNl/Qhjs4cYHJbxGfaGl5/6mhEOz+ufK+Thu+N34DAWrGwqsIAb3MWtvYeUDR688Yfwj9f6Lfw4BviFw3+Mn2tbPE9fxhjJVji2H6K1qwl/y4Q4U7Lo0h7Ow1ssLnyHO+6HdOpLnJtrcZOyxXW8j/VItGy/eoWFu5DvscjJwtiEEDyMA172b7MosxnH1UfwlkVtTBbW8vUzgG08wHV/Is9Cj+P2OTQdgOLnjJQtxuDxsnsDKXs4m3DYvERleziTAEyGaIBBH1tc9Xdwevc5vvLV78D1A3ALLHGNP/eVX8PD+RNcnJ/A2IzL7gRDnAnvZo29egUnTYY1GWN0MIb3YD0ewZiMt6LHQX2OjIx3AQzRy6Y7AgC6MMftuBTy24jj9hJd8KjcFNZF/wmL9XCAMXOEud9cYVFt0QWPmR/5uZOV6+Fx2R9h5kdsRof95hKVibDCR3IW6INDhsHl9ghjruFsxkF9jXl1W9ZXygbeRuGZOFx2XLCVSzhqXgJI+Nmf+Tbq7et2h1Ud8Re//jvoXt3BYXuDZX2BEB2AjFqyUJx8rq+Mp7gdZqhdxNxf4KC5QUwG3iVR2bGg6sICL7f3WRSmhDf2HsPbWApshc1rF/Fi8wA3wwFiMjibP8dx+xzW5sImV6vDlD2erL8oP2/wcPE91G4QNFULD+57l/1dXPT3AQAzd403934Aa5Icbq8PwX9w83XAeMRk8Wjvu1hUl2Wd6vcbZKzGYzwbvoiub7DX3uC9xW/yNczOnmf4jj/c/Cw26RghOrwx/z5O6x+9vjm8j+nB/tIS3kf8ua9/G+YHN/Bm/NT95CK+iYv4CNYltOkKb1Tf+9TvA4CP8TVky2bjTvo+Zrj51O/bmn2cPuB6cBhwb/zh9I8/DtgfVQAcmrbHg7MnWIbLT33NCiPefu8xn3sfUF2PsOVeArqpZRjsH336+9Kvz0VhkSH21UL2Uv+IbQTmiQ5o7996YTaTaJWyRwbwqrd0R4wWKyHrUEec0VkrfuxppwPg71SpEOdwrti3anCV2gkDhPpedS28JYTE36udZpa5WSwzq+vR4bgOqORBAoCLgWqPtVT4lPM9wJgsZp5wdpa5cu0iPljN8YXlBpdDjW9Gj7/wi99ipSxfrJS/iY8+fpO/BwZDdPD2S7geapw0HWbViJgsGh9kQ7aI2cKZhMolGPMzGGTj8zudZ2XJq3CWXWdlH8LZsVw7bwOsSfjKz/8e6vrHvF0fzDAOHk8/eMR7m1GKpWG9wIAFnEuozAaD83BSWecEWMvvywm4fHUH1htYF2HSCQbMyuvwcGChNcY5QlfDughEAHM3FWDynzBUMAASeI2tS0ijQ4QvG9HupgVjYKXjcT7CBI7bPi16p657zOYsepwJk5XkzpcF0Jo19g6vkSwLn8XtFZr4KcWSBWrXwyxZgJgYcbB6wX/7FOl4vZdx4FcAgNnmHIvh1U9+U0O0zN5pYV1EThYnt9//TLTsuL1GThZ1WOFw+9Gnfh8A3JmvkGyFnAwOux+hTatP/b7O7uGyeQdnDz+GyxHYQeAcgIfuD/HwjH++qN9Cbw4Am7HoXmI/P/vU14zweDn/CrKMTs76P4DDp3+mlb2Llb+PFC3m5gLH4fFP/UzPqp9BMjVyNjiJP/jpn8ns46X5IqxLsHnE/fDTlfXn/h309oAKoPAMB0WR/5Of6an7GozsPffG3+NnevEp33ynRnva4Re++l206Ron8YM/9jMZk3A4PMYsf/rB0NklLpsrpODhTYe7w3d/6msen91gi2MYF7E3PMcyftqb5Gea37cMjbEZZ937P3XtLQ46HDVcG/W4wlH/yU/9/W+9/SOoBeTy9gWa8CkjcACuzTCLOQuJFNDcdD/1NU/OXmFZ8d/n/S2w3TlUzWSWWGY3AHw9InhXeCXZ7DQg2cA3Efv1FayL8GGLoZsXRyvl42kj0rZbZDtwrNHPsE2OPD8jKslsAGsQbQXvB9kvM27s/YImL48uYV2eGjvJoI/BYeOO0JslSnNkgZyIKGdYjJuWcfFDhWfuZ8HO1BBJlq9xrJBuLYBPR+aBz0lhYUDIUO2s1yMP30cLVsjPOi92uFQ01OKseG82oDJemMWuOA+uCrM4SdIeCXsqD4T8OSZTQmdUtle7hHXvCT8LyafOtNUdosVaoOBDYecO0WK9Y3uqpCFmH1Qlwp3x3w7nQvyZJc7zDquAmCxuR8cMgGDxaDHgTjviaqxw3nv89gdfQJ8cfvnnv439xQaXtwv8nV//Jj568hY0nngVHM57h/f2eozZ4PurZTGvOmlCgawNGBq1FnJfZTLOBw9NriTClwt864RMB0zQrUKWj/MCf/1XfhX1DpoxNg3+0bd/Ed//0dtlhEB/AELX6qMBTJyJ03aLm6HBohrQBV57RYIqG9HHP4PKThyILnosqwFXQwNnMo6aLf7y/eeYz7evj2UA9NsW/+Qf/UUAQCPda8oGY/hK+TMAjKL8sQJfEslKcDbhY/MmnIvISdz4bEISpCYbkn0BYP/rr1C/J1DvTr0yDh4ff/9ddOs9qIvKyi7gMMK7gJQsnIv85mwwphqhm/Pv7YjRfLF0VtZmWL0WyNjcHGGIM25u2aDPM1ibuFkARK1MRswOw6Yt6qhbnMHIfTOWRVPOLO76uEToaqTkkHPC2h5z3xNyrYEUjCYjBo9seO0Gs0C25AqxoJSLYDKCnfH6usgDZu/1rSdnYNi23ECNg60icjLItcMQFgByuf96YbNxcFVAdoLMxBliijvfI7chA7lysC6gno9AbzCmGTKmrAZkvlsDwNYRzndI0SH2NUbMZIPFa98bbYW67Xhg5YBhM3vtM+lhYQDYJqLyHVGkkDEOsx0EbPelHZrFBrmETs0Rc0TV9NN71YOrtojRoZ5vYcaMfth7/RoZea8GcE2AAf8tmhZdmMpkY6bDM9iGpGWXgAhsqmNoUKNeHyPoVnQ83ABgTHOszJncS0F0LA/iBAvnI1K0yNFi5e/CIr32+TOI2A1mhiTE5dHMcOnZoMBmZBCFU3Sv7+ewgaPUG/cG1zAMkT09MAFkOITbhmPXCHyMnys3x5ZRLA/adOthbIb3EevxbeT8HsahgvMRD7/8fVT1T6ISYazwePNzHKGPlTzLXFvjWMmekRGCg/cRKb2NGJ0gNhYhks/hHZEhRbIAjk9DmJ4V/bcQpy4jJIfKsVBL2eJO9xzvfOX7cDsEyxgtvv+9L+P5U6JBfahQ2Ygu+NJYNn6U88uSU2dS+bchOsRsMcjvJWfkn/zEtdCvz0VhQR4FpWjrQKOdZ1uHZZVxUvOC3QaLi8Hg7UUu4Sir0eNqdKgj/Q3O2ojWJtiGTOorceozoHaYGREyLxc9uzKYrwaHTZxY32MCTg2/Zx0sOpmJ3go5SWU/TzYeVwNw0jjs+YyLweDRImAbbJmpng9eDLZ4UN+fjQK/Ai86EqW8zWiR8LK3xf1zEyzuih/Ftz94F9/6wXtwhoVWbVns1I7+CI21eLY1mLsaJ03ApTC+j8UpUDX8er1rS1nVRW/QOACgs9ppG7EQ+91eZujng6QdikOnusN99zH5Gn/pm7+D/cUaN+sF/sFvfR3f/9HbAICQfEk/1SyFdWAs/EkTMESL88EJGTPjo82sEN2O64CLgajUwiUsq4A+0cGPfv41bkYvKNUc/W9+E/+lX/nV11CdMTj8/W99E//wozfwYD5iIchQFykZHoWwpTp3LdLoWkmkayZqHp0MD8lKBLMVeVcqPIXnsPgrv/QbP/Ee/u5v/jn86KO3yvxY579BCJXr4Ms8XP8LoEiUL/sGziYs/YgEEjhj4n97USk5kxCFp9K6UFRFAA8OK9CvIlbr8WexqAbEbMu/ASzkjAEaP2Iz1IjZorKxKD6G6OAME0Yt6Liom50xXyLnKRsE4Z8Yk+FtFNmrxdG952hnHfBo/toe0G8b/Po//gsFLnc2YQgcsVh5jSDkXmeTKLB2x0gZIX0R3kakbAt8XxA6HzAGX2yajfly2cQzTIHbrVXuDhHJ2j1CFH4JwHGBjgX0c1qjfhpfLsWoMbkcGLuHPf//2+V66Pfu/v8g6CX//Ag5GxzceYV3P+WwePyH7+Hm/AQpWXj/RQyjh98Zz6ad9w7wQPFWn0/+nsoFjFGv9WR2l7LFGDkCrlwgD0oOb/q9cH05kzBEv3MgTn5D+jn1cwGAd++Ua2xk7KxGgHqN9HVLSJdcx+1YlcaDyaZOLNv5HnT9KLeHAZZsEvroyyFpTcaYnIztgC56zP0IY4DtyP1uVvHZX48Vhujwzu0e/qVf/NZrHKoxOPzT3/46PhR13quuLfvMQT0IwVJjGrhX34wVeiFpawPVR4deOSayB7ROibW2XFMlOAMo6jTlOhlwf0qfvImvXh3jV77+bSznJJH/x/Ie18GhdQlX8hk59qf/x0kzopXiZkgW573HmCm7vdsOuBoqSZ01+Elc9vWvz0VhQbLSFLCz8GB+hRx+6t44iIvhy77CvTbgidgT146L52qwcMaWwJXDSvzp5RB/srE4bY04RaoRD5m8rUtYhQove+D+jMSli8HhdrBFPlfbyS5cGfsHFT0J1CfhuCYKsAUZ6rfB4sM18ED20UORH8ZMxMTvHGzeTG6PamP70aYSDbbHaRPweC0bngU+2dLv4GKoMHcJby34WZ5sCf1r2NfMU7IFcHSjxlOHVYSFKweaM/Sz303T48GSBd2RjcFmYfkb/PYH7+LXvv8FzBTdETUD+TAcbV0MtOJdB8rpKptx2ZOA11oadx3WLMZcFeEFRVHzq5gNPtk2hUT0eF3hnb1J0jZmg995/z1UJuOXf/7bOFmucbVe4Ne+/TX82h99AXOX8ftXNd7bsyUH4SZYXAxWnP9ykXW96Cr5LCxyL4a2yIKpRWeo2Go0BenSz/3bP/gCuuB2Cq05/qNvfQO/+YMvFB37Ohi8MeOG1bqMJ4E+/mq+piZcQ7J42Tl8cdnj8bqmrbarMArJb+YTnm0rvLXocTFUsOBn6CJNlrToOe9pJAfQN2M1OhzWQYyEFlh6ol0q9WUAGd0x18HhViS9Sx9R2VTuQ2U0jG2S0+qGp0WIyuMUARuTweZb38Rf++Vf+5QC8Bfwgxf3ChlzGx2uBj77p82A1eiLbf2JEA9jNoXkp2jazAdcDVVZs6pCUR8F5oFw/Ph82+CkGTEmW4iiMRksq4CXfY19OVh2yZBXoxeTtCgbsi+/e1emrfLImExR+uzX5IH1yeC8JzH00WKgXHh0aG3GsgqFzFjbVJRJ6ckjvHtxgr/0zd/BnhwWv/7tr+FHHz+UterRipLloB4ETXW4Gj3O2h4WNPxKQCmKN7JWErCTF5MKH62LTrJ6aCF/XA/ok8WrrpG04hFr6aYH2Q+MyUXRpGTWbbQ4qgO2wUnhO3HZ1PdntwBTsu6VeGeohb0FUV82Hq9zvozJxQNDY7/VaXQmiq+XvRflw/TMqvLkvPdC3pyQ0XZI5XNcDh7rH76Hy7HCXxXV1816gX/yO1/D9370jjQK3NvCWGEbHDbRiWuqKcFndLPlmpy7jCG60iDNHQPizkeH1cgG+8M1PXlO2yQqE0prU56anS5ZdMYWRVQC8Ovf/wL+3ne+hP06lUZqv4pFHq5hfRaU8itd4Om2gZGzq3UJLvM6frRpcCxqoFV2EyL7U74+F6qQ+/Xd/D94+F8p4TBHDbuhXh74UW7My87htI349VcZv3SHldSTTYU9T8fLl70vvgG7emUAxW7a22n2roYrzyQB9bCK+GTLLvmwYq69t1Os+MypS5vBUZ1xbzbiavB4trWYexQb2dMm4MNNhbOWi381MsiKCyRKsNIUXHUjZi37FR8+RW5mLhcOCbX81K4D1BdrQaTJlh+ugbOWB9daTFtUvnXeOzQuFxSjFglW6xIer2usRpr7nLaxHKCXg5VodqI4qrdXqSFlWyxUyCynA2cXKVfcRoM7TcKLjlLDk2Y6kOj2CNxpRwzRFt/91jH++rDOxdbWGTod7le8n4ei/3+y8WI2Revj22DLg6N20ko2O+/pZ0BpIEdELzrKNrn5M0MgA7jTsNOiHbETZjxDu1Y7Tnqt1RAybpRPth6rkZ9zWaXC7g/JlEjkmeM1ipkju8pkPOs8w8BsLrLR1qWSeaIbW8pgwqGgVR/cVnh3b+S6lwJB7befbR0eLUZ8uK7w3nLAZU8HxqOGZkOHdcSzjp4CraVp1IGgNbrpaMGzDkZShHkYbQMd/5heSeM1a4CXcljWopioLZ0FtWFQx8WvvfNBKb6u1wv8v3/jm/jO43dKAecM0Fp+/icbeq4YQ2kqR6ZUdqhMVP0BYjZ4IZ/pR7cWiwp4NA9YSfbBqbh2avaCmlupVl+vvXoF3IwOZ7I+N5Ebt+aRWHD/UEkpfVkCXvUVtvp6MpoN8nqUu9KSmUFtRiz8p4yQmWRDOJOxjhLY5ibCuTH04FAfBAAS4GiLV4IWegnA063HA8kS4j1JeLKtcdqE4lex8BFbCYDUAvFCEpN3199RHaThIl+s2+mwNdVYC1wWTqb4r1wPvuy9AGPaa6eoHA8xpi3zvmpBGHTsVArUXLpo9ZvRz6rXRfNCLHLhz9GZ1uO45hqnAR+LCDXuU+Mtfb68fI/ef+aoqNEf8HA+luyVMRvcnw0iW0143tU7IYMsNp9taRZ4WAe86KoiD78SLwyqjNiM6X6hPD9dryptTmDBsxX/kYWEdepn06LqyZbuobqfvuxcyQ9SQ8WQpviJIbJ4uR4dDmsWIidNwNNthZn477zoHGoH/Dsf/7ufb1WIMbSSDYkbj7rRverpAncTLOB56DkDfP3IoTLULmu6nZUDT9MMNTiqsRwz5GxgfMbHG8Lu+zXNf9TFr5buWF0OE+hKWJlcTILoXmfgxZb4VVfhajT4zu0Gf+lkhtFSs5/AinI10gSKccMe+02WICCDqp6i1GubcdlbxOwn3kNvsCf2l96yyj4fLO61dJpzsni20Zaxytt7hA87gaoezseSEnjcsCDZBPI4tmLjulexMj5rE55tPa4GHuCtSzhruQE/2zKcR3korWUccSMOgZUx2IDF2idbXzbN04acDZoF8V6r1E5hvJgI77VSOJ40CT9cj/hG7fG8ozU1C8WdzchmPF17vLs34mJwMDIeWgfmdQzJ4Eg6GkoSM5Z7ES+6CkPKJZaZiZd0ujxrAs6NKGuMkIHlYD3v2TX0zshGi3JYAOSshERb43stNwdNNjxuoowvsswv2TltA4uZBzN68N9ILPeDOV9f0aal5/s+rKIopSwOqxFXI4vsjRg0OQOc1AHfua5QGYsHc47Q7s1YOB01AQke62DxwxXw3tLj/mzEee/xbFvh0WJEysBHa4fjhhuIHhiVFPfr7ERGiZIrQXthDulb0cfrAa3BT9w0UTrjX/v+F/DbH7yLmUtiCc1nQj1FNsFgdAYnTcBJgxKY1icamV1IaJPG1wNcE5tgJanT4jZknDR8Ty86h5ln4XFcs7iAHIRjZpEVMrtWLbj1MFcyuRZuG1Gqvegc+uRKBgsRHkpbtTg4H4hCeEu0xIJjPZo5Gcwc73OQ9epkrwGEcwAUJHCIFkkOmVY8P27GyfyJrpl18W5QpPao5n7AZ8sgZyforBULbFs66eN6xCfbGlcDi68HUpTFxEJpEEg/JIMngpJ5i9cM2VrJJVEnYG00WPjxeWHTxyJJ0d/V6JCBcv37xL0z5YwXvUcfDe7N6BtiEopzpjYIhxL1HqKR9FWxq49AZywQp+yQbTBoZS/e7mRJaTGjuTwfboiqdokmZCdNkrBIJ4V5Bc378TkXlWIXuR90kWm2DxcRN6PFnSbjvLfImcjJvtzzMQFtRWfcFx2bg8Oa6MnN6CafGPGjGZJmMNniKgpQhKCFsa67peYXyRqoLPfmPjIe4qDKOJCC18prPes8U3MTg9hiZSTF1+DBnGZcJ82nk2/163NRWAxRQ5ZY4W2DQdXEklO/V00Wyutg8R9ePsWvzN7AcZMRE400P9l6aAQ1wCAz7TRrSEy5WL4uakBjhbWz3MVt1oGb9e3IxNL9SjkHhIUSePjULmORLf7qacsxjWUF+bhjx/1kY3ByxPdw0mTcBoOLPuPRQpwd5cG6GogsjIkL653FiEeLiO9cWTyUEUonIVcvZYTgDPC7lw4P5nSba00qXcOYWB0rJ2IjyYsxEXm419JG+aydpLMxs6hScqva62rMr0ZKdxEYncFxkwsixIcy42q0pUhbViwinm7ZcZ40qSQV5mzwydYLR0RgPUFzZi7hl08cEmhApZG+ez7juGa+wdXIg+JiIFR7GQxedhkP5tyoBwDPO1pTVxZoTcYPb2vEzMyVm9HiemDexCqQi6IbOrtIdc3kQXdY8dpag2L01EWgloLBmQzrJjRmlHvVOI7cLLTo1YIrwsLiYIdQu19N44NWIukXnvwW2vAmhORwUCcesPL+N4LmOU/of+6BZ53BA2Nl5GRxUANLS3v1kybhrT1Cvc+2FW6lGLscWNS+MWdB9qzzBZGq5XqsRot/er3CLyz3cdqw4AqZKb99muKvVwGlY1eHPu00E4AzMfwakkU0WUyWuO4UqckAttGXYLOTJqAVVdazzpdI+e+vajQ2o22y+B7wadaod01K3khnh+AKobkTp8SrgX93MwJvzg3eXwFf2Kffg67TPrGQO6xpQX3eZ+x5g84CgHutc+fekNBaInH9yBCztdGE24y9KsHHydNBIffjOpbDYSOusxp2p2idokCNnXJNqsYIVwZ4vuW27i1TV09qxpe/kjTg3Sh59bUgp4gFwWkbsZDiA5h+xyo4vOgM3pwnrAPtEdRsyZV8lSk6PGdy4+iwa5Gl4VmIkyfTpzO+d+1w3NDG+5MtQxDfmE/OtEc1D9gXHflVxnBv2QgKeU/85l90zCXScXcXGT3+YB5KA3kx6HPOYskY4JONwVf2Q1kD9Lxg9oruC2dtxPPO4UvLIOMg7kHK0XMGeLqtSlGyV0U83XqcNESJ39nrcTs6PO88PtpYHNe5uMqeSNN33rtiNJcy3XRbl7HKXJOnLa3Fh8TCQ8fXatt9Ko6rYzJ43jmc1AljpqW6elzomEmLEmdYpCmv46ONF7SGTai34i0F/t4uGnyyNZj5ae1+2tfnYhRyt76b/5v3/iYWPhV1x1k74smmlljwAc+2dTnAHt+yq0pZYXKmzqnj221g8h9949ldqY//KB93Jh71jSxuhVIvB5qsnDRMekuZ3crN6HA9WgyJFzgmRny/MefPK7R/MfBBfTCPuB5sySXRKk/jrG8Gbjq1pQXsJtjCutbMAG8nr3eqNyzenIfiwti6hIVIWJdy7XYjfAEuKnYbBhfyIA6J3c6hoDO1y68lNWrI2To4XAx8j8cNnequZMSRMuXAJ82EYmgk8Z6n+cuBdPdXo8PTDS2JV8EWf5J14HhBoTUN71EnxdYRuns4D/hw43G3pYueRn9fCNlUOSspAy86g8MaBS48a+khwvfGkdT9GQOXRimerkfCrQspvrQL07TFVlJCqYSQ8CiTS8T0LsSr36fx0ArXAjwshjjNgE93ELGrcbpvBprICRzUqRBMtyJV1uA5tTc+khTLuy3X11IKEz1I3l85zD14X9JE3tX3e1gzAO9FR7TJgJ//olc4PBUUJ2TC5avAZ0ELvgQe0LrJ+p3rYk3GRc+O9MEslGA9VU8ZqA0y1+hSCnnyAlggLH3EzKfXRgmnTcDF4GTtZtxpGUF9UEU82XrcKR0m7/1xHdFJUXYl4WknyuWSZ1XVwl0E7jS5jNQ0q0Ofr71qKppUjaZmUABw2dsSvAVg5/Dms5HlOR9l3zBmCizbyu8whlB5L5yLVz2f/1FGpV5GFcZkPN/60oBpXL0B80v2a67lZx0jwq8G4KwlmtC6XAIPh0hInZbZQTKISNpW1GhMtIzfryJWYu191hL50pHXvVnEk43DWZvKe9HgwPmO/XTtpqZOrwMwWZ+/7Jgcelf4BWPWcLVUrte5hOUdVCy4LweD+hlGAAAAIqdJREFU04aF3Y3krtB6nXvTsuKIc8+TQ7caLW4D8OX9EU+3VTkrdO940dEy/I3ZgE+2PI8e3zo8WqSSvaGJzK8kf+fBjHHzQ4RYpE+jjl8/t3i0sFjKHnkoyOr7K4+7LcdCT7cOh1UuGT6dIBDqMDrZbKMQmNVNtIsWezv3a+4SPtl6XA5svLSoO2sjVqMto1Mdqdc2l5DMdWDzfbcN2JdAuy4afLzmmPF/8/x//VNHIZ9ddvxn9EV2r8GHa19ILi+6CkEe8ouhwjqYMj/XQJ9HiwHLKuG0zZLUNsUSnzbMKGCKISvcH61Zze2JrFIh29uRAUZdNLg/C4WjoNX3y97jeuTvfrQI+Or+iJ85HPHWYuran2wMvr/i73sw52xq5icvjL0q4nnn8WzLKOH9OuFOk3Azojysj29RHP1mngjHNpBX4WzG/RkDb7aBG8DNYPHr5x6Pb9k5Xo0We1XGzGcqZBxdAc97JxB3LKMBRSbWgYcr52oGr3odvxCKO2k09pqSWE0+bF3G/Rnn6PvVlNjYChn2pCFBsBMo/ME8Q1Mrl9JNAITB9eG/GizutQELl3B/NqAyGafCU9Hu97wnTHfSBDyYE44bk8FZO2LuE+aehd9+nbAaUeaf+lnfvx0REtGnD9d8gMZEXsXM8ZrrLPJVz47nauBBpjHstWwmh1WUVEglHLK7NAZ40TFXZDVafLieujiAhclJQ/SlSyRMntQJZ20scd4ZLIYOKvJhznuPF53DOpDU6Ay7qCNBup5us/BO+Hm/c8UCbzWS/8OC1BSSMa9Vwr0ZeSfnPWXbm8CDYL+KuDcLwvtIr8mEn3eSJSFZCl0yeLr1+HjDa7ysEhEGMV8ilyfjsBKOhnbishZfdAY/vOWY5vD/1963xViaXWd9e/+3c6lz+lRVV1X3VPdMT+aS8QyWx4xijPISRUSeACJ5iMVEECIE8gMJJAIJxbwQHhARD8hIhAcUIiyBiCyBhBVFgSjGihQlOHEmZjyem9vT0901XV1d93P7z3/bPHxr7f/0MGOS0D1VGu8lWVN1qsp9zr/3Xnutb33fWin5KiQPs8kUsySWbDjUSWYWGJ4/C5Y25zKoaZRWWE8b3JzywyqhVXk8w7TBcxdY+kmllLKe8ZJdiekTHu3XLGMK4U0z7Ymomqw4XiN1bcLGLJ8dLTh4bVGzxLGa1hgkDQ4WwHcm9BH9mMqevdxiZ2798DjIut9bcB125uxAao3DetrIcCp+ztKxhj4pI0wqgzdOuFfJU2JQouXc3dzg0X4NCw6t0udyVxRmeW1kZgdfPyhijEtyt/Ja+WoklJeNwfWxdPqNa7x2ksIC0mKeXJz1jC0BWCbhz3bnHAQ2qQxePyWXSrNhdovluZwLn2stAwYJkeFurAgE1XW7c57JR7oN1rMaq9JefV2Cimll5XxUPtjd7NRYTysMhKfWiRwmFTBMgJ1ZwnJrxf3RiRxui+KP5cuk9UMxz7f2PTpaWOEhAZe7tVe30OdEuJcz6NzNYzy+wuF6OzOiuTcmMfbzCE8PS1SOLeoPcocbUyJEJ6WVc8s1G8v349LKNOHGJ8XTioHeYRHhRMr89xYxrvYqPDlgqUgD+cgQGemJvyka3ndHRYTrY5lbYx1ePS04cbaM5d9mmbGzlEy9n50LxGI12nKfu/zXsZcbXFthCWA9Y+Q7k2BiUjFzTuXScs54R6EwIgBhMTdY1Ba51NU6EUfzagveSsoQs9p6Frc1fFg6Gnk9qwUlIAoQSSYXG5ZmlGxViPNbyKa/l9f4+MjinanB86sl9hYxDhcG6xkv44NFW/YAWIq5M488N0CzGICR4mHBWuJcuBHrWY1RUuHtSeozz0vd0me+Sq5bNMYra8Zl+28mQtaaVhF2ZuQ0lEJG2shq3JzFHkVpBLbVn0fCndByx9sTlpbWM2YMseWgLlVYKBvayd8qCzyvqYQYJixLMOPlZaIEwVL4LkcLBkvWsIZeNAbX+gXenSfYywn9r6YNdma8QC93a9yZR7iYNVjPSsyryNfYtbzVlctI+S6xQMpO3tswqUX5QeelJTOAl6R+Dl2nZXVR7ciin9cWt6YRDhYNtnsWPZE9z2uWVrSuXzUG44pQ5BunzPRXM7lUDXBJgrfEOhwVEf7wsMAnR6m/MKYCF+slPRUiL8ALWImQr54keGJQe7RsNWuf7c6M6pirPe43Rf5OS+63sjGYVNYPI5tWRgav8QxwwBqwIrVevcSVm9KJnLSyZlB1IWUZQsc1O8CjLsqvUrJ0JQhS1QDvzskj6oraSjk1mQQ/LdHN+Cz+QtpgLa28ZFr3EPcv8PTQyftjYHZaWNyaAZ++WPnzcrCIUTm5dBIGHkqWu5uTMK5Q8rjUYIa+7bF+q8jRYFov6d05nXRqDQZJSxifVOQvXRR0MbFUawGcSjqtmJVqmfNCwomuqiwigbIdGQ/Aj2EfCC9BEZzDgkHJrAKeGNS+pAOQ4JzYFj5fnmDLUey1fG290gLgvt2ZEdZXxEWRMVXKaQtztpJvmBw1wGrW9phLLbPpQVz70pD6o+NCmqJ1OPwLYAmQZVvuJ/03dTJqXlMqr63WASZyx0WEW1OHZy44T0wfCNcAAK71C3xh9yZ+fPAkLndLHBUxducGmx3nz9ggrvHWOMXVXoVj4X8cFxa3p8CF1OBi5mSUAJO0vCaCrgj3Iz0iCKWgef245Tipik/bwGviUjvgUofozaQ0wv9pS7JTSRIGsfOcIb0jdXBibICTkoT/2DrcmSfoRQ55DWx1SdoE4Pk0aol1+Oe3/s0HIhbnIrC4GG+5n7/6WVwfR36xFG6alMwQjgqLWUW0Qh0tI17g2oqONGZZRFn5jcDFys9ILHBacmodZw6w/KAZeE8CEDX9GXtQWBwXFvOaaMgwqXFQRDhYtJnGVqfxB0zn1ytp77AgzKqjphWSHcpwn35E57/d4/e68QE6tO1uhT86jDBIOIJ5JAdFL8bH+gvsLxLs5REuJFTJvDlO0I3QjtWOGpmmF3kYrysyo28ckq8RWXh4Xw9x1RhksjG1PKROUhGWaolMlmqZyao0lc9IG21pbwu1XPgEu/MI270Kt2cx1uW5RNbhlSOLra7Bo73K19ctnK/B6vqeLpWPdmYW271GLkXjM/tLXUKeK3GD27MIw+R+56dwNuWK7fOYCUy9nhJ6Pili7OYGK0Iq1ombc1HLaHCmk0UNmLXNKxIDcylrRNb5sdYqzeuK1OuoiHFjAvzAOkmZV3oNbs8sPrG6wBunGVZEgaTBRNFwj6nDPy4iFA2h2ZMy8j//5OoMh0WCu/MYsQUudUvs5Qk6EbPoRj6/EvKUAwTQsa1I8KtlvdS2Utm2TGK85HlSGczFkXaW1DSlkOKUQ9CJRBEie7KomTwoz0Kfye7cSIlG0KmkRQ5nlUUvbvDKkcWzF1hSPRB1jaqPZlL3V0j5RJA4lageFNYrKSJDlG03j3FzwkuiFwObHaKaWrYYy7TZTsT3ohe4AfzFt2jof3jJOwmkuT/GJQP2zMJzc+YV4fXEAo90K99XZtGQsKhlKx26dSISaB35/c1jyutXYvrD6+PInwlNYg4WFk+slHj1JMEoBW5NHa72+bOjgll/X4L9vTzCE4MC88ri3XmMzU6Nm6LgymsGOHphphLEqJRe/YiWOSycn3nDfi7t2HhOPG4Dap04rOdjVnG671aHCKwR7tP+gpyZoQR66sO0fLs3d3hyyFJTbOHPQ2pZHtruMaM/LninHBeRL430Y+dLZlf6JY4WseegaECriZCqGsdVhHFpfFKhd5OW5AD4IEMJ3om4ffURihZZQHh+/Lny/rQsHbXXBfdfUmN3nkjQyztzN6d895snFZ69kECnsk7KCCelwXrWYHducX1a4IXVxJeo1IcADHSOJdn9boHFuSBvxpYBwHavkTJAg80OIeTtHrPRR/sNioSXYV5bHOX8mZZOGil5bHUc7kndbSVm3Wi56ciWkPd6EZB52SQzxNTqCO2Wab+X0zkvatb7BlKi0P7Kw4TOZCOrcDePveohtg47OacqXu3XGCQWhwtGznt5IqxgksoS6zB9T1WKGSoPdiHNhp4YAJMK+M4Y+Pgqd1JXmM5fP+xgXDo8MWBkfGceI7FEEoqGkxjvLWKUJTejqmYMqBp5bIVBw7jks3ikq4GA9WiQss/nPvNygmJEyKIGG1ntZXIbWe3RCY4ad56cpJM+I8sDNxII9pFuhaIx0uiMTmFWWwwS4zd2P6aDfGpQCQEQ/hLY6la4O4+xR0YdOiLhvCDEyO/MY2SW/TH28ggbkkUcFhEyefyDuMFJyf00kZpsY+DhYpWGxdbhyYGSyshd2cg4ZXJWMWvUjBxQxAYYl8CFxOJihwc6hmPjsogXUD9u8PYkQj+O8ORggcaluDVLMEy0jgq8fJj5C0IRCx3YtJHxwhwLAVn7kOoUzj6Am9MOIkuydDemZJuoH9e1lFJIV/sNCNdgXlnYyHn1RCa9ECqBr614ExLfao8qrkkWWchZOyktqgJ4rF/eJ8UFIPyfGKO0xt3c+ox/N4/xlcld/OjwMq72Gs8FAOicv7pX44XVBKOUXJFBwmZWt2apZOQMOGZVexZ6ceN7f6hipZ802Jlb3JrF/j1dzBjcPD0kcU0hcKp4KnH+FrPa+IRCRxTEghBWjoqmQQKPAKTyD+zOrEe2rHHIwB4WiIHvS4j+KDIyrbT+DTy/StXXnXnky7670tvGgejO3hy4lwMvrDmMUviA+/oYGCQW49JhmMTY7DA43JJZPr2owREsbkwijNII1/oFVWiVFek2Eb4LifPy+2opWRiX1gdl+3kkUvk2c04jQLOLlZgByWlpfTDnnMFpSYLqSlJjXEQ4LqxHqOqId4aiIImU5lYEbVy2WFDHj40YOG92aq9EZGNASLsABsebHSZ6M8sS2oaQK6c1gwoNvosGmFVAL1Z/qGedzykyDpe6VBBFhneTMU7Kw5BSHLke61kjyYX1k34t6HeOCj7LixlL08cFuyxr8uwcsNGpvMBgUSsHj+jauIpwWhpc7VW4NYtxtZdIl2WD/TySciP9/Ups8MJqgtgAv3dQ4AfWUqQWOCkjbGQVyvfOhvoAOxeIxaV0y/2D7Z/wGShreMAgIRGvaAhxa5ZbNwa/f1Djk6uxJ3rmQmo5La2wpSnFOy2tkNGc7zOhsjgGEeQnzKWmu56R3KOZee0gWmf4EsDyxlVyksq8VIbIFt0tjLuetWN6pxLBK7dCI2N1fD3JCPXi1Ey9LzUygBfsSA6ROkZyIbi59hdG2qADxyWhuKOCF7ySvA4WDJouisRXo2LtjzGt+Pxqx8PfIj/Ok62mIpsEmD0NBC3Rkb5k0ANX+5RUMluFJ+YN00aCE4tLHY7zXi4NpZaB3Ganxo0JAwrttXCpU/lyGAC8fmLwwnqN27MYK8KuVsRALxR9/zORmpVCzn1nGiOLCEfrwVcyqR5SLQdFwqhfLqPNpL7flYDNoe2TkBh40iOlfpH00iAEPUjg4WtAVSS89MrG4KSI8e68JaWuZ7U/KwMhoSmsnVh2l/3N3Qo/shV7+BiAV5K8d99oph5Z5yVppyUbxSXW4d1Z5J8Ng31eIkVjcLAgQVozcM08jwuWydbSxssj9bWNTu07vx4XBmupE4a6u++sOSHsrabkFmkg2okanBQxTkqWSxU1efM09v5iVgHPDCv/TI4EhQDgSW33FuQXrIlef7mHxv/YBZ4ZJh59Oi2B7S5LiweLCF853cUz8RYe67doBQNt5y/UBnT6d4UUO0waT/KOpZSUWMLoy6PDldSq+0aVBs7BI4NF06rVNPB3jhLde4tY1CMGu/PII6UNWJ764+McP7SZ4MaEpF61u3Pnfa76OUXdAF4uk8rgSq/y/RPWswonhUwCFgK1kp17UZtE3FtY3JxWuNSN0Y3gfW0tvje1LCdqp81xSaLwekqofy5B26yCR42V8D2X8tHVPhObnVmMUdpgLa1xa5ZgWgE3piVeWGt9qPakAYAjaYK4nOjpGdHnsFyGIdcr8q0RVA319oQB3nrGc3NasJSoPUGU5L9MJr0xrXExjXyvlptTi1Hakjo12Mmsw61ZjEnJchH9hBPFB59DbJxwkRyyCFjPxG9JOdGK79qdU6WoiA1A7sjFTu17Ku3OIzw9XODlwwwj0mmw3WXPHEW7zqQUYox5EcC/BlP7X3HO/dIH/e5msuX+xsZL6MeNj9b2ci6SOolH+41nTSukDcBnW9o9saiNb82tJJ51aYpyJMSmacULrhsTkkwka12Gc9n2NMKiNkvKA274kwK43Gtrj1NpGLS8gNp4ZlpF2F9Yz8gfpiRdaoCjF4TacuAA0EHtzHlRTiqWA/byCLHFfZeJHobf30/w3IilpH4MUV8QZYgNURqF+LVLZmIcduast/XitjeAQvLaREbfmxI4VUKoPJf1tII18E2kxiU3bmLpCGa18bW6m1PgqQEz/3emZEErq1837lwCit08xq2pwxODtsyhJTMAHtoeJjVeO81wuct65SBpvFZ/Z25xUjg8NYRHvYqaqouFqB0U8rwn8HxeE2ZPLDyB8bRs1RDWQNjurdRPG4VxlDbLK4tGAxOD0xJ4WoIjdZb6t+PS4PtWWKNVnoeqhQ4WBtvdxmv3tW+D8pJuTNoyYl8uTXUcq6rASQlr35nH2OqSp6R7SffQeIn7Yg1Rv6oxvuvlzanFrHIYpXyvy0Q15SlEhgG3NtrSIGFWG0wrPjMlEDrw3OglUTQGtSi4NNNXabATZHElYeO41bTxl8Jq1gjD33glzGbH4ZFuiXdFBngkGe9ebjwSCsAjpQeLCC8fF/jzq6nvidMTIm8i52UqZR31TaPEYSw9E9i4qS2rKnRfNvQJNyc8d1dEQq6MfA1Cisb6TLd2JPVqiY1qCpYHlC8ylRKfNm5S7oA2jRqltedT6D5RnwW0PUreGse4tlLjlSPryyBaQlCffH0S46Tg337/UOZgLPEU5hVbcg+FJ6IlxXHZ+pRa1BYapA+Ft6RlVW3l3Y2ZiU+r9jJXbldk2tYA3aj9LAcL6yX1ygWglJ+l472c56cj5eDTUqScpfV+5MYkwrWV2pcVAfxfiaT25gAYaA0S7jsN/nQdvrafsLQsXId5zfE4b44rPDOMfeCgfXyoDKJfXYkbSXYtdmaRqKbuv6dJAOYdc1TEPqgvJJnNrDYqI0FWS3faFJBNv8jfeH1c4PsHqT9PK5LgKIdN7b3J5S++88sfbmBhjIkAvAngRwDcBvAHAH7SOfet9/v9rXTL/b1HPutrZ0BbJy4b4x1AJ4I4O9YMi9rgsGiJcSrN1AxA4SJd+MzCyydVnlRIwDCr4Ilj/bh1cnnNnwHMzHpCAlw2bbR0XBJy6sesxe/lkSfolA28I87lQtFABoDfrBxMxktFs7xRysDmqNCaHnwt/cYkwsdHJY4Lds47KixGUuvUDFjr5eOS0H4pemRtSa394vclg+tFDe7msa+LD2KH45KM8EHivJxSGyQpKsTBZfDkVi1FKQJ0KH0PUgufzXbjBkdCkF1PyVHRS2EtJZlU94POEdHNfyGpcVJG3mkei0adfTR4yN8ck4xqDdexE7GXxcHC4kLihHDX1kFV9lg2xkvRVmI+w0HS+Exb9eOKaim6xOCMjrMWBGMsXJ5I3oO25x2XzFgT63y3zAsJnzXfC2urkTh5AF4BoYGEyms12Pna4QLPjzq+dqymAcaRSJbVWSqnACAyVkvGuWio1CCRk2jTKGVjNKB13koKnAmZUhUAKinUmvt6VntZnpI+HdqmdomlbFsRQraR5hm2cpXs5sAnViu8PUkEugUudWscLCIcLw3ZHaXwl+OeNFnrRw125ok/Nx2pOY9SnqFOxM+iz0UTmk5EtJSKHP7/P77CLq+HCyE9d4jWpNZ5XtFyJ03dT3o+VEaai3NXZEv3rAb8p2XkVVpK/ruXW2xIOXckssvT0nokSHkxk9L4DFx9qgaYyp/Y7hLd0M+rJcXjIsJ2l7yLcUnOhSKqy+W9UcLL68YkwkaH++BgEXk+kQ6B1IREW/Rr92BtJGcNJKg1Im91uJA2UpqlRHxcsj/FZqf2QeuyNY7PlmqSlnB+MeParaXsLaE9Pr58+g7+9sYVn8Q2DriXO2x1GawBwO/uF3h22EEq5G7tJjutrQ+6NMlZDlz1eQPAEyuU4lIpV+KdSUpVEajiU5JyJKhMYlruCRuItQGOqulOhSBMZIxnY1kemtcqZ26fjQN8e4HjkmjvvUUsQT57dKzIOT9YODw95OdZJsbrHgJ4L//LnQ/uvPmwAou/COAXnXOfke8/DwDOuX/xfr+/lW65vzx8Cb24vTSXo6NlIuMorWVRImms07K62X0RGJcOzwzbtrBsecysQDW46jS0G5uSX9gzgIe1cczwtY51XBqcFA692GA9Izzajfg3lTPYXzhc7jJKXsso3dvo1H5mQV5bvH5qcLXXXvpHhfVEP92sSiDSi0OzOwC4Pgau9pmJXulV+PY4xuMrNd6eRL599UbHeQ37zoy1RR0ABnAjj9LGb7iittiZGWx121a2tWMZQwOyyvHQZpZclVnFzX9YGOR1e+gPFpHUHdtLVB0r0EL+yn5OjMO3Tvj14yva6puXZz9i2+A788iXg7Q+vpFVHppVYiYAj3YM4gZfP4wEDuSe6kswdFxYTzQjv4fEs9hSNsxaqEK61h9qlk5acqtegvsLHkaFkRl0QCTShNB1T93LgUtdPlPt0aCKiX7MC0EvbUUQ7swdnhuxF8Ebp+TaqJPX7AKAD8S0W2kvavDWOPZ8jOXfm1bci5e7xje5OpFARyH7sfT3GEp5y4Itoo9Lg2np0E+MDyDWJUh0TuWKVuTH/FzjkmjNZsd59YKfllu3iIVeCHndNnVL5d+4MzOY1Q6bHePJpOofKnGQg6TCW+OO/5leiBqYv1+AqiVIDSqOC+CpQduL4HK3wpGUXvZzOt3Ykhszq40nUWoPhUwCaQC+5wYA3/OAUmaHbsTn58D3rkGrBXwPA/Z9YTBcNW3ApSU6LR9lUYP/fUTU8WMjyZwNvDpmq1vhnWmC9ZSolzaKWiYSdiyR2+tj7rFlU+XI08NKupECd+YW210izOp7OpETn8YEZDcnR0Ul/KrY0bKJosOVY7Cg5OdpybOpfXIcqLwDWtS1GzuRyBop69IXEFljkH5rxpL6MGmDcgD3lUjf+zkBloWUbwLgvoBhWcGnyKEiK3ofKWLciWTcgJTGI9uWRLQHxyjl2s8rDs40AE4KSBv4Vqa+HGQcF/Q5qjjRZ6TnhUkf+8esZbUn3NeOSETZODwqBCzteK2l8eUA44U1cuW+fsD9crXfPpMv3PngPhYPK7D4CQAvOuf+rnz/UwD+gnPuZ5d+53MAPgcAw2jwwj+88rfw1b0Sn1rL/KIp0SixrW52KrU9laENEsp62MKWzvpSh50Ata41rw2OC7KxmbkqXMsLpxe3UaPW0fdyg6JxuNbnpbq/YNT8aP9+Zve8oqSrG7UyubxmL4vGEZUYSb/9BmwbrAGTQv16yPVzqwNUnsWlTuXrgQrPvnJk8dyIh/fWzOKRrvPw5P6CmnVVyuhmL2rjo+TYANOK0T376sO3Igfg+++TSEVVhMoGda7GwcJhmBg/J4WXd5uBqwPPa15QGtioHGx/wVkkN6dtUKGcCr0w9ete3HjHpxeFoj6aXaqiRp/T8kWhDW0UKiQXgDMM7ubcD5VjUHpYlnhqJcVmp8GrxwZrGddbL9pBTAelpZFp1QamDBKZUc4qQpiZQOiTSgfpMdMG4BsXdSMS4RYN/Lyb2pFrtN27H5bVoFMhXEW1lhEb3U/Lig2VbCvipm3FAdyHcu3OWQpS1EMRH4DQ9iBhptSA+yaT5jqatcemDUQVEdR1B3gJZ9IzgzNkWmQmry3u5QanJcstKqc7La1vNHdSMmBXvgXbHluPWiicrdycV45IAFbb7vGMfes0x2PdDlYzeCXAcoa/nNyokuDmlMRmgOv4jeMGj3QjXOq03Bx16gD8HBqdBbOsptL5RTobQwPlTflsJwWH5o2Ep7LcDTezDEZ7ERvnKb9Jh8JpsNWN29KhJilrMidG+RNvjUneVF7bsi2rSJSPdbBQNR1/586M5O/EOrx82ODRfuwDzrLhhaf+NTbsv7FcRplWJHZmUYM3Ti06Ed+nNttTPkrtDC4JpN/IPtdp09fHwCg1Hl0dJS1nSZHH4RKX6ahom8eNUuBoAUwqojPasFCFAZc6lZeeKvLHM9O23M4b44OPWdWS+qcVZf+lM7gnJbhKkHAlsk/lM+jdk9cG4xLS6ZfJq/qRftx4gqYGaDqrKa/bhK4X8283ssYrq2oHfyfpPtFnc7nLz6SJlJaclV+hfmQZ+fxuDbIeVmDxWQCfeU9g8Snn3N//gN+/B2AKYP+Bv5lg/z92EWFNzqOFdTl/Ftbk/FlYk4drjznnNt7vBw9LbnobwNWl768AePeDftk5t2GM+cMPin6CnY2FNTmfFtbl/FlYk/NnYU3Ozuz/+1f+TPYHAJ4yxjxujEkBvATgyw/p3woWLFiwYMGCnRN7KIiFc64yxvwsgP8Oyk1/1Tn36sP4t4IFCxYsWLBg58ceWudN59xvAPiNP8Wf/LuH9V6C/ZktrMn5tLAu58/Cmpw/C2tyRnYuOm8GCxYsWLBgwT4a9rA4FsGCBQsWLFiw70E788DCGPOiMeYNY8y3jTG/cNbv53vJjDG/aozZM8Z8c+m1NWPMbxlj3pL/ri797POyTm8YYz5zNu/6o23GmKvGmP9pjHnNGPOqMebn5PWwLmdkxpiOMeZrxphvyJr8M3k9rMkZmzEmMsa8bIz5dfk+rMk5sDMNLKT19y8D+FEAzwL4SWPMs2f5nr7H7D8AePE9r/0CgN92zj0F4Lfle8i6vATgOfmbfyvrF+zBWgXgHznnPgbg0wB+Rp59WJezswWAH3bOfQLA8wBeNMZ8GmFNzoP9HIDXlr4Pa3IO7KwRi08B+LZz7jvOuQLArwH4sTN+T98z5pz7HQCH73n5xwB8Ub7+IoAfX3r915xzC+fc2wC+Da5fsAdozrk7zrk/kq/HoNPcRliXMzNHm8i3ifzPIazJmZox5gqAvwLgV5ZeDmtyDuysA4ttALeWvr8trwU7O9tyzt0BeMkB2JTXw1p9yGaMuQbgkwD+F8K6nKkJ5P7HAPYA/JZzLqzJ2dsXAPxjcBqBWliTc2BnHViY93ktyFTOp4W1+hDNGLMC4L8A+Hnn3Ol3+9X3eS2sywM251ztnHse7CL8KWPMn/suvx7W5CGbMeavAthzzn39T/on7/NaWJOHZGcdWPypWn8H+1DsrjHmMgDIf/fk9bBWH5IZYxIwqPhPzrn/Ki+HdTkH5pw7BvBVsE4f1uTs7AcB/DVjzA2whP7Dxpj/iLAm58LOOrAIrb/Pn30ZwE/L1z8N4L8tvf6SMSYzxjwO4CkAXzuD9/eRNmOMAfDvAbzmnPtXSz8K63JGZozZMMaM5OsugL8E4HWENTkzc8593jl3xTl3Dbw3vuKc+5sIa3Iu7KF13vyTWGj9fbZmjPnPAH4IwEVjzG0A/xTALwH4kjHm7wC4CeCzAOCce9UY8yUA3wKVCz/jnKvP5I1/tO0HAfwUgFekpg8A/wRhXc7SLgP4oqgILIAvOed+3Rjzewhrct4snJNzYKHzZrBgwYIFCxbsgdlZl0KCBQsWLFiwYB8hC4FFsGDBggULFuyBWQgsggULFixYsGAPzEJgESxYsGDBggV7YBYCi2DBggULFizYA7MQWAQLFixYsGDBHpiFwCJYsGDBggUL9sAsBBbBggULFixYsAdm/wdE8+d88V3Q9gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Check the calibration of the first and the last image with rings\n",
    "\n",
    "print(\"First & last rings\")\n",
    "\n",
    "fig,ax = subplots(2, 1, figsize=(10,8))\n",
    "for idx,lbl in enumerate([\"del_10.0_0001p\", \"del_65.0_0001p\"]):\n",
    "    sg = gonioref.single_geometries[lbl]\n",
    "    if sg.control_points.get_labels():\n",
    "        sg.geometry_refinement.set_param(gonioref2.get_ai(sg.get_position()).param)\n",
    "    jupyter.display(sg=sg, ax=ax[idx])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MultiGeometry integrator with 121 geometries on (4, 66) radial range (2th_deg) and (-180, 180) azimuthal range (deg)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Create a MultiGeometry integrator from the refined geometry and display the integrated image:\n",
    "\n",
    "multigeo2 = gonioref2.get_mg(angles)\n",
    "multigeo2.radial_range=(4, 66)\n",
    "print(multigeo2)\n",
    "\n",
    "res2 = multigeo2.integrate1d(images, npt)\n",
    "\n",
    "#Display the 2 curves with a zoom\n",
    "fig,ax = subplots(2, 1, figsize=(15,10))\n",
    "ax[0].plot(*res2, label=\"rot1 & rot2 rotation\")\n",
    "ax[0].plot(*res, label=\"rot2 only rotation\")\n",
    "ax[0].set_xlabel(res.unit.label)\n",
    "ax[0].set_ylabel(\"Intensity\")\n",
    "ax[0].set_title(\"Azimuthal integration of 121 images merged\")\n",
    "ax[0].legend()\n",
    "\n",
    "ax[1].plot(*res2, label=\"rot1 & rot2 rotation\")\n",
    "ax[1].plot(*res, label=\"rot2 only rotation\")\n",
    "ax[1].set_xlabel(res.unit.label)\n",
    "ax[1].set_ylabel(\"Intensity\")\n",
    "ax[1].set_xlim(10.5,11)\n",
    "ax[1].set_title(\"Zoom on first peak\")\n",
    "ax[1].legend()\n",
    "pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With the first model, the refinement was not perfect on the very low angles and indicates a miss-fit. Relaxing the constrains on *rot1* allowed to spot a non (perfect) orthogonality between the goniometer axis and the incident beam. Releasing the distances is also possible, for example to cope with the sample not perfectly mounted on the center of the goniometer. \n",
    "\n",
    "## Evaluation of the peak-profile\n",
    "\n",
    "For every peak, as listed in the calibrant's definition, the peak height can be extracted and the nearest minimum evaluated. The the full width at half maximum can be measured an ploted as function of the scattering angle. \n",
    "The FWHM can be fitted against Caglioti's formula: \n",
    "\n",
    "FWHM² = U tan² $\\theta$ + V tan $\\theta$ + W"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Line profile function...\n",
    "#Peak profile\n",
    "\n",
    "from scipy.interpolate import interp1d\n",
    "from scipy.optimize import bisect\n",
    "\n",
    "def calc_fwhm(integrate_result, calibrant):\n",
    "    \"calculate the tth position and FWHM for each peak\"\n",
    "    delta = integrate_result.intensity[1:] - integrate_result.intensity[:-1]\n",
    "    maxima = numpy.where(numpy.logical_and(delta[:-1]>0, delta[1:]<0))[0]\n",
    "    minima = numpy.where(numpy.logical_and(delta[:-1]<0, delta[1:]>0))[0]\n",
    "    maxima += 1\n",
    "    minima += 1\n",
    "    tth = []\n",
    "    FWHM = []\n",
    "    for tth_rad in calibrant.get_2th():\n",
    "        tth_deg = tth_rad*integrate_result.unit.scale\n",
    "        if (tth_deg<=integrate_result.radial[0]) or (tth_deg>=integrate_result.radial[-1]):\n",
    "            continue\n",
    "        idx_theo = abs(integrate_result.radial-tth_deg).argmin()\n",
    "        id0_max = abs(maxima-idx_theo).argmin()\n",
    "        id0_min = abs(minima-idx_theo).argmin()\n",
    "        I_max = integrate_result.intensity[maxima[id0_max]]\n",
    "        I_min = integrate_result.intensity[minima[id0_min]]\n",
    "        tth_maxi = integrate_result.radial[maxima[id0_max]]\n",
    "        I_thres = (I_max + I_min)/2.0\n",
    "        if minima[id0_min]>maxima[id0_max]:\n",
    "            if id0_min == 0:\n",
    "                min_lo = integrate_result.radial[0]\n",
    "            else:\n",
    "                min_lo = integrate_result.radial[minima[id0_min-1]]\n",
    "            min_hi = integrate_result.radial[minima[id0_min]]\n",
    "        else:\n",
    "            if id0_min == len(minima) -1:\n",
    "                min_hi = integrate_result.radial[-1]\n",
    "            else:\n",
    "                min_hi = integrate_result.radial[minima[id0_min+1]]\n",
    "            min_lo = integrate_result.radial[minima[id0_min]]\n",
    "\n",
    "        f = interp1d(integrate_result.radial, integrate_result.intensity-I_thres)\n",
    "        tth_lo = bisect(f, min_lo, tth_maxi)\n",
    "        tth_hi = bisect(f, tth_maxi, min_hi)\n",
    "        FWHM.append(tth_hi-tth_lo)\n",
    "        tth.append(tth_deg)\n",
    "    return tth, FWHM\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 2.17390968e-07 -4.91366782e-08  1.69257348e-07]\n",
      "[[ 4.04651222e-14 -3.04640275e-14  4.75794383e-15]\n",
      " [-3.04640275e-14  2.39007253e-14 -3.95477893e-15]\n",
      " [ 4.75794383e-15 -3.95477893e-15  7.26507512e-16]]\n"
     ]
    }
   ],
   "source": [
    "#Fit against Caglioti's formula:\n",
    "# FWHM^2 = Utan2 + Vtan + W\n",
    "tth_deg, FWHM_deg = calc_fwhm(res2, LaB6)\n",
    "\n",
    "def model_Caglioti(tth_deg, U, V, W):\n",
    "    tantheta = numpy.tan(numpy.deg2rad(tth_deg)/2.0)\n",
    "    FWHM2 = U*tantheta*tantheta + V*tantheta + W\n",
    "    return numpy.rad2deg(numpy.sqrt(FWHM2))\n",
    "\n",
    "from scipy.optimize import curve_fit\n",
    "fit,cov = curve_fit(model_Caglioti, tth_deg, FWHM_deg, p0=[1e-6,1e-7,1e-8])\n",
    "print(fit)\n",
    "print(cov)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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888/vlee45ZZbOPzwwzn00EM5/PDD+cUvftEr+9WuodSL42TmTVSCdXXZF6seJ/DuTradD2w3x2FmrqTS8y1JkurNfdfBbR+FZxbD7lPhhA/CrNf3yq4zk8xkyJDt+wxbQvfZZ1d+VB85ciQf+9jHeOCBB3jggQdq2v/06dNZuHBhp+v33HNPfvSjHzF58mQeeOABTjrpJJYsWdKjY9Gux8vAS5Kk3nHfdfCjf4JnFgFZuf/RP1XKe2jhwoUcdNBBvOtd7+Kwww5j0aJFXHDBBcycOZNDDz2Ua6+9FoCLLrqI3/zmN8yZM4fLL7+cUaNG8cIXvpCRI0f20sHB3LlzmTx5MgCHHHIIGzduZNOmTb22fw1uhm5JktQ7bvsoNLe7LkXzhkr5TnjkkUd485vfzD333MO8efOYP38+9957L7feeisXXHABy5Yt49JLL+VFL3oR8+fP5z3vec9OPV8tvv/97zN37lxGjBhR+nNpcCh1eIkkSdqFPLO4e+U12m+//Tj66KMB+O1vf8tZZ51FQ0MDe++9Ny9+8Yu56667GDt2bI/2/e53v5vf/e53ACxdupQ5c+YA8LrXvY4PfOADHW7z4IMPcuGFF/Lzn/+8R8+pXZOhW5Ik9Y7dpxZDSzoo3wmjRo1qfVw5Haz3fOELX2h9PH36dObPn99l/cWLF3P66adz9dVXc8ABB/RqWzS4ObxEkiT1jhM+CMPaXYF5WGOlvJccd9xxXHvttWzdupXly5fz61//miOPPJIxY8awZs2aXnuejqxatYpXvOIVXHLJJRx77LGlPpcGH0O3JEnqHbNeD6/6HOw+DYjK/as+12uzlwCcfvrpzJo1i9mzZ3P88cfziU98gn322YdZs2YxdOhQZs+ezeWXXw5Ueq7f+9738vWvf52pU6fy0EMP7WDvXfv85z/PggUL+NjHPsacOXOYM2cOTz7Z4TX6pO1Eb/9MU4+amppy3rx5/d0MSZIGnIcffpiDDjqov5sh1aWO/n1ExN2Zud201/Z0S5IkSSUzdEuSJEklM3RLkiRJJTN0S5IkSSUzdEuSJEklM3RLkiRJJTN0S5KkurVw4UJmzpzZpuzDH/4wn/zkJ7er+9///d/MmjWLWbNmccwxx3Dvvfd2uM83vvGNHHjggcycOZO3ve1tNDc3d6tNTz31FCeeeCIzZszgxBNP5Omnn259/pb5u+fMmcOQIUO6vMLl17/+dc4666w2ZStWrGDixIls2rRph+34x3/8R0aPHt3p+gsvvJCZM2cyc+ZMrr322toOrsrPfvYzDjzwQJ773Ody6aWXtpbPnz+fo48+mjlz5tDU1MQf/vCHLvfznve8h8985jOtyyeddBJvf/vbW5f/9V//lU9/+tNttvn1r3/NYYcdxtChQ/ne977X4X7XrFnT5vXec889+Zd/+ZduHeNf//pXjjrqKGbMmMGZZ57J5s2bAbjsssta9ztz5kwaGhp46qmnurXv9gzdkiRpUNh///35n//5H+677z7+4z/+g/POO6/Dem984xv505/+xP3338+GDRv4yle+0q3nufTSSznhhBP485//zAknnNAaSN/4xjcyf/585s+fzze/+U2mT5/OnDlzOt3Pa1/7Wm655RbWr1/fWva9732PV7/61YwYMaLLNsybN49Vq1Z1uv4nP/kJf/zjH5k/fz533nknl112GatXr675GLdu3cq73/1ufvrTn/LQQw/xne98p/XiQu9///v50Ic+xPz58/noRz/K+9///i73dcwxx3D77bcDsG3bNlasWMGDDz7Yuv7222/f7gqf++67L1//+tc5++yzO93vmDFjWl/v+fPns99++/Ha17625mOEyheT97znPfz5z39m/PjxfPWrXwXgggsuaN3vJZdcwotf/GL22GOPbu27PUO3JEkaFI455hjGjx8PwNFHH83ixYs7rHfqqacSEUQERx55ZGu9devW8ba3vY0jjjiCuXPncsMNN3S4/Q033MA555wDwDnnnMP111+/XZ3vfOc72/Vitzd27FiOO+44fvSjH7WWXXPNNTvcbuvWrVxwwQV84hOf6LTOQw89xItf/GKGDh3KqFGjmD17Nj/72c8AuPvuu3nxi1/M4YcfzkknncSyZcu22/4Pf/gDz33uc3nOc57D8OHDecMb3tD6ekREa4B/5plnmDx5cpftPfbYY1tD94MPPsjMmTMZM2YMTz/9NJs2beLhhx9m7ty5bbaZPn06s2bNYsiQ2qLqn//8Z5588kle9KIXAbB8+XL+7u/+jiOOOIIjjjiC3/3ud9ttk5n84he/4IwzzgB27r2sxdCd3oMkSdol/Ncf/os/PfWnXt3n8/d4PhceeWGPt//iF78IwDvf+c425V/96lc55ZRTuty2ubmZb37zm3z2s58F4OMf/zjHH388V111FatWreLII4/kZS97GaNGjWqz3RNPPMGkSZMAmDRpUoeXgr/22ms7De3VzjrrLL797W9z5plnsnTpUv73f/+Xl770pZ0eF1QuR//qV7+6tQ0dmT17Nh/5yEd473vfy/r16/nlL3/JwQcfTHNzM//4j//IDTfcwMSJE7n22mv5wAc+wFVXXdVm+yVLljBt2rTW5alTp3LnnXcC8JnPfIaTTjqJ973vfWzbtq01UHdm8uTJDB06lMcff5zbb7+dF7zgBSxZsoQ77riD3XffnVmzZjF8+HA++MEP0tTUxKtf/eodvm7tfec73+HMM88kIgD453/+Z97znvfwwhe+kMcff5yTTjqJhx9+uM02K1euZNy4cQwdOrT1GJcsWdKmzvr16/nZz37G5z//+W63qT1DtyRJqlstIaqz8o5C6S9/+Uu++tWv8tvf/rbLfb/rXe/iuOOOa+0d/fnPf86NN97YOl5848aNPP7449td5ntH7rzzTnbbbbftxqJ35JWvfCXvete7WL16Nddddx1nnHEGDQ0NHR4XwNKlS/nud7/Lr371qy73+/KXv5y77rqLY445hokTJ/KCF7yAoUOH8sgjj/DAAw9w4oknApVe847Ce2ZuV9byml9xxRVcfvnl/N3f/R3XXXcd5557LrfeemuX7Wnp7b799tt573vfy5IlS7j99tvZfffdOeaYYwD46Ec/2uU+unLNNdfwzW9+s3X51ltvbR0OA7B69WrWrFnDmDFjajrGFj/60Y849thjd3poCRi6JUlSjXamR7qnJkyY0HqiYounnnqK/fffv8P69913H29/+9v56U9/yoQJEzrd70c+8hGWL1/Ol770pdayzOT73/8+Bx54YJu6b33rW7nnnnuYPHkyN910E3vvvTfLli1j0qRJLFu2jL322qtN/VqGiLRobGzk5JNP5oc//CHXXHMNl19++XZ1TjrpJJ544gmampo4/fTTWbBgAc997nOBSk/sc5/7XBYsWLDddh/4wAf4wAc+AMDZZ5/NjBkzyEwOOeQQ7rjjjjZ1Fy1axKte9Sqg8kVm9uzZLFq0qHX94sWLW4eRfOMb32j9deB1r3tdm5MiO9Myrvv+++9n5syZTJs2jU996lOMHTuWt73tbbW8VJ2699572bJlC4cffnhr2bZt27jjjjtobGxsU7f6tfzyl7/MqlWr2LJlC0OHDm1zjC26817uUGYO+tvhhx+ekiSp+x566KH+bkIefvjheeutt2Zm5sqVK3PGjBm5YMGC7eo99thjecABB+Tvfve7Lvf35S9/OV/wghfk+vXr25RffPHF+e53vzu3bduWmZl//OMfO9z+fe97X15yySWZmXnJJZfkBRdc0Lpu69atOWXKlPzLX/7SZpu///u/zzvvvLPD/f3kJz/JWbNm5fTp01ufu1ajRo3qsHzLli25YsWKzMy8995785BDDsnm5ubctGlTHnDAAXn77bdnZubmzZvzgQce2G775ubm3H///fPRRx/NTZs25axZs1rrPf/5z89f/vKXmZl566235mGHHZaZmYsXL87jjz++w/bcc889uf/+++cJJ5zQWnbYYYfl3nvvncuXL+/0+M4555z87ne/2+VrcOGFF+YHP/jBNmVnnXVWfuITn2jz/B0544wz8jvf+U5mZr7jHe/IL3zhC63rVq1alePHj8+1a9d2+twd/fsA5mUHebTfA3Ff3AzdkiT1TD2E7gcffDBf8pKX5OzZs3P27Nn5rW99q3XdFVdckVdccUVmZp577rk5bty41nrVn/+nnHJKLlmyJDMzGxoa8jnPeU5rvY985COZmbl+/fo877zzcubMmXnIIYfkK17xig7bs2LFijz++OPzuc99bh5//PG5cuXK1nW//OUv86ijjtpum9mzZ+fjjz/e4f6am5tzzz33zAsvvLDD4+pKdei+66678txzz83MzA0bNuRBBx2UBx10UB511FFtQuc999yTL3rRi3LWrFl58MEH55VXXtnhvn/yk5/kjBkz8jnPeU7+53/+Z2v5b37zmzzssMNy1qxZeeSRR+a8efNan//lL395h/vasmVLjhkzJj/wgQ+0lp1zzjn5vOc9r3X5P/7jP/KGG27IzMw//OEPOWXKlNxtt91yjz32yIMPPri13uzZs9vse//998+HH364Tdny5cvz9a9/fR566KF50EEH5Tve8Y4O2/WXv/wljzjiiDzggAPyjDPOyI0bN7au+9rXvpZnnnlmh9u16E7ojsq6wa2pqSnnzZvX382QJGnAefjhh7s9plltrV69mnPPPZfvfve7/d2UUn3+859n33337dGJkANVR/8+IuLuzGxqX9cx3ZIkSSUaO3bsoA/cAOeff35/N6GuOU+3JEmSVDJDtyRJklQyQ7ckSerSrnD+l9Rd3f13YeiWJEmdGjlyJCtXrjR4S1Uyk5UrVzJy5Miat/FESkmS1KmpU6eyePFili9f3t9NkerKyJEjmTp1as31Dd2SJKlTw4YN6/Tqj5Jq5/ASSZIkqWSGbkmSJKlkhm5JkiSpZIZuSZIkqWSGbkmSJKlkhm5JkiSpZIZuSZIkqWSGbkmSJKlkhm5JkiSpZIZuSZIkqWSGbkmSJKlkhm5JkiSpZKWG7og4OSIeiYgFEXFRB+sjIj5XrL8vIg6rWrcwIu6PiPkRMa+q/MMRsaQonx8Rp5Z5DJIkSdLOGlrWjiOiAfgCcCKwGLgrIm7MzIeqqp0CzChuRwFXFPctXpqZKzrY/eWZ+clyWi5JkiT1rjJ7uo8EFmTmo5m5GbgGOK1dndOAq7Pi98C4iJhUYpskSZKkPldm6J4CLKpaXlyU1VongZ9HxN0RcV677c4vhqNcFRHje7PRkiRJUm8rM3RHB2XZjTrHZuZhVIagvDsijivKrwAOAOYAy4BPdfjkEedFxLyImLd8+fLutl2SJEnqNWWG7sXAtKrlqcDSWutkZsv9k8APqQxXITOfyMytmbkN+HJLeXuZeWVmNmVm08SJE3vhcCRJkqSeKTN03wXMiIj9I2I48AbgxnZ1bgTeXMxicjTwTGYui4hRETEGICJGAS8HHiiWq8d8n95SLkmSJNWr0mYvycwtEXE+cDPQAFyVmQ9GxDuL9V8EbgJOBRYA64G3FpvvDfwwIlra+O3M/Fmx7hMRMYfKMJSFwDvKOgZJkiSpN0Rm+2HWg09TU1POmzdvxxUlSZKknRARd2dmU/tyr0gpSZIklczQLUmSJJXM0C1JkiSVzNAtSZIklczQLUmSJJXM0C1JkiSVzNAtSZIklczQLUmSJJXM0C1JkiSVzNAtSZIklczQLUmSJJXM0C1JkiSVzNAtSZIklczQLUmSJJXM0C1JkiSVzNAtSZIklczQLUmSJJXM0C1JkiSVzNAtSZIklczQLUmSJJXM0C1JkiSVzNAtSZIklczQLUmSJJXM0C1JkiSVzNAtSZIklczQLUmSJJXM0C1JkiSVzNAtSZIklczQLUmSJJXM0C1JkiSVzNAtSZIklczQLUmSJJXM0C1JkiSVzNAtSZIklczQLUmSJJXM0C1JkiSVzNAtSZIklczQLUmSJJXM0C1JkiSVzNAtSZIklczQLUmSJJWs1NAdESdHxCMRsSAiLupgfUTE54r190XEYVXrFkbE/RExPyLmVZXvERG3RMSfi/vxZR6DJEmStLNKC90R0QB8ATgFOBg4KyIOblftFGBGcTsPuKLd+pdm5pzMbKoquwi4LTNnALcVy5IkSVLdKrOn+0hgQWY+mpmbgWuA09rVOQ24Oit+D4yLiEk72O9pwDeKx98AXtOLbZYkSZJ6XZmhewqwqGp5cVFWa50Efh4Rd0fEeVV19s7MZQDF/V692mpJkiSplw0tcd/RQVl2o86xmbk0IvYCbomIP2Xmr2t+8kpQPw9g3333rXUzSZIkqdeV2dO9GJhWtTwVWFprncxsuX8S+CGV4SoAT7QMQSnun+zoyTPzysxsysymiRMn7uShSJIkST1XZui+C5gREftHxHDgDcCN7ercCLy5mMXkaOCZzFwWEaMiYgxARIwCXg48ULXNOcXjc4AbSjwGSZIkaaeVNrwkM7dExPnAzUADcFVmPhgR7yzWfxG4CTgVWACsB95abL438MOIaGnjtzPzZ8W6S4HrIuJc4HHgdWUdgyRJktQbIrP9MOvBp6mpKefNm7fjipIkSdJOiIi72013DXhFSkmSJKl0hm5JkiSpZIZuSZIkqWSGbkmSJKlkhm5JkiSpZIZuSZIkqWSGbkmSJKlkhm5JkiSpZIZuSZIkqWSGbkmSJKlkhm5JkiSpZIZuSZIkqWSGbkmSJKlkhm5JkiSpZIZuSZIkqWSGbkmSJKlkhm5JkiSpZIZuSZIkqWSGbkmSJKlkhm5JkiSpZIZuSZIkqWSGbkmSJKlkhm5JkiSpZEO7WhkRU4E3AC8CJgMbgAeAnwA/zcxtpbdQkiRJGuA6Dd0R8TVgCvBj4L+AJ4GRwPOAk4EPRMRFmfnrvmioJEmSNFB11dP9qcx8oIPyB4AfRMRwYN9ymiVJkiQNHp2O6e4ocEfE+IiYVazfnJkLymycJEmSNBjs8ETKiPhVRIyNiD2Ae4GvRcSny2+aJEmSNDjUMnvJ7pm5Gngt8LXMPBx4WbnNkiRJkgaPWkL30IiYBLyeykmVkiRJkrqhltD9UeBm4C+ZeVdEPAf4c7nNkiRJkgaPLufpBsjM7wLfrVp+FPi7MhslSZIkDSa1nEj5vIi4LSIeKJZnRcS/l980SZIkaXCoZXjJl4GLgWaAzLyPylUqJUmSJNWgltC9W2b+oV3ZljIaI0mSJA1GtYTuFRFxAJAAEXEGsKzUVkmSJEmDyA5PpATeDVwJPD8ilgB/Bd5UaqskSZKkQaSW2UseBV4WEaOAIZm5pvxmSZIkSYNHLbOX7B0RXwW+l5lrIuLgiDi3D9omSZIkDQq1jOn+OpWL40wulv8X+JeS2iNJkiQNOrWE7j0z8zpgG0BmbgG2ltoqSZIkaRCpJXSvi4gJPDt7ydHAM7XsPCJOjohHImJBRFzUwfqIiM8V6++LiMParW+IiHsi4sdVZR+OiCURMb+4nVpLWyRJkqT+UsvsJe8FbgQOiIjfAROBM3a0UUQ0AF8ATgQWA3dFxI2Z+VBVtVOAGcXtKOCK4r7FPwMPA2Pb7f7yzPxkDW2XJEmS+l2XPd1FcH5xcTsGeAdwSHFVyh05EliQmY9m5mbgGuC0dnVOA67Oit8D4yJiUvHcU4FXAF/pzgFJkiRJ9abL0J2ZW4HTMnNLZj6YmQ9kZnON+54CLKpaXlyU1VrnM8D7KcaSt3N+MRzlqogYX2N7JEmSpH5Ry5ju30XE5yPiRRFxWMuthu2ig7KspU5EvBJ4MjPv7mD9FcABwBwqV8b8VIdPHnFeRMyLiHnLly+vobmSJElSOWoZ031Mcf/RqrIEjt/BdouBaVXLU4GlNdY5A3h1cZLkSGBsRHwrM9+UmU+0VI6ILwM/pgOZeSWVK2nS1NTUPuxLkiRJfaaWK1K+tIf7vguYERH7A0uANwBnt6tzI5WhItdQOYHymcxcBlxc3IiIlwDvy8w3FcuTijoApwMP9LB9kiRJUp/YYeiOiPd2UPwMcHdmzu9su8zcEhHnU7mwTgNwVWY+GBHvLNZ/EbgJOBVYAKwH3lpDmz8REXOo9LYvpHJypyRJklS3IrPrkRcR8W2gCfhRUfQKKr3Yzwe+m5mfKLWFvaCpqSnnzZvX382QJEnSIBcRd2dmU/vyWsZ0TwAOy8y1xY4+BHwPOA64G6j70C1JkiT1p1pmL9kX2Fy13Azsl5kbgE2ltEqSJEkaRGrp6f428PuIuKFYfhXwnYgYBTzU+WaSJEmSoLbZSz4WETcBL6Qyr/Y7M7NlgPQby2ycJEmSNBjUMrwEoBFYnZmfAR4rpgGUJEmSVIMdhu7ixMkLKebNBoYB3yqzUZIkSdJgUktP9+nAq4F1AJm5FBhTZqMkSZKkwaSW0L05K5N5J0BxAqUkSZKkGtUSuq+LiC8B4yLiH4BbgS+X2yxJkiRp8Khl9pJPRsSJwGrgQOCDmXlL6S2TJEmSBola5ummCNkGbUmSJKkHOg3dEbGGYhx3RzJzbCktkiRJkgaZTkN3Zo4BiIiPAn8Dvknl4jhvxNlLJEmSpJrVciLlSZn5/zJzTWauzswrgL8ru2GSJEnSYFFL6N4aEW+MiIaIGBIRbwS2lt0wSZIkabCoJXSfDbweeKK4va4okyRJklSDWqYMXAicVn5TJEmSpMGplp5uSZIkSTvB0C1JkiSVzNAtSZIklWyHY7ojYgSVKQKnV9fPzI+W1yxJkiRp8KjlMvA3AM8AdwObym2OJEmSNPjUErqnZubJpbdEkiRJGqRqGdN9e0QcWnpLJEmSpEGqlp7uFwJviYi/UhleEkBm5qxSWyZJkiQNErWE7lNKb4UkSZI0iHUauiNibGauBtb0YXskSZKkQaernu5vA6+kMmtJUhlW0iKB55TYLkmSJGnQ6DR0Z+Yri/v9+645kiRJ0uDT6ewlETG9qw2jYmqvt0iSJEkaZLoaXnJZRAyhcnGcu4HlwEjgucBLgROADwGLy26kJEmSNJB1NbzkdRFxMPBG4G3AJGA98DBwE/DxzNzYJ62UJEmSBrAupwzMzIeAD/RRWyRJkqRBqZYrUkqSJEnaCYZuSZIkqWSGbkmSJKlkOwzdEXFsRIwqHr8pIj4dEfuV3zRJkiRpcKilp/sKYH1EzAbeDzwGXF1qqyRJkqRBpJbQvSUzEzgN+GxmfhYYU26zJEmSpMGjyykDC2si4mLgTcBxEdEADCu3WZIkSdLgUUtP95nAJuDczPwbMAW4rNRWSZIkSYNILaF7bmZ+OjN/A5CZjwO71bLziDg5Ih6JiAURcVEH6yMiPlesvy8iDmu3viEi7omIH1eV7RERt0TEn4v78bW0RZIkSeovtYTu/4iI41sWIuJCKuO7u1QMQ/kCcApwMHBWcVn5aqcAM4rbeVRO2qz2z1QuO1/tIuC2zJwB3FYsS5IkSXWrltD9auD/RMSLIuLjwJFF2Y4cCSzIzEczczNwDduH9dOAq7Pi98C4iJgEEBFTgVcAX+lgm28Uj78BvKaGtkiSJEn9ZoehOzNXUAnZXwAmA2dkZnMN+54CLKpaXlyU1VrnM1SmKNzWbpu9M3NZ0bZlwF4dPXlEnBcR8yJi3vLly2toriRJklSOTkN3RKyJiNURsRpYADwPeB3QUrYj0UFZ1lInIl4JPJmZd9fwPB3KzCszsykzmyZOnNjT3UiSJEk7rdMpAzNzZ+fiXgxMq1qeCiytsc4ZwKsj4lRgJDA2Ir6VmW8CnoiISZm5rBiK8uROtlOSJEkqVS1juomI8RFxZEQc13KrYbO7gBkRsX9EDAfeANzYrs6NwJuLWUyOBp7JzGWZeXFmTs3M6cV2vygCd8s25xSPzwFuqOUYJEmSpP6yw4vjRMTbqcwiMhWYDxwN3AEc38VmZOaWiDgfuBloAK7KzAcj4p3F+i8CNwGnUhm+sh54aw1tvhS4LiLOBR6nMuRFkiRJqltRucJ7FxUi7geOAH6fmXMi4vnARzLzzL5oYG9oamrKefPm9XczJEmSNMhFxN2Z2dS+vJbhJRszc2OxkxGZ+SfgwN5uoCRJkjRY7XB4CbA4IsYB1wO3RMTTbH9CpCRJkqRO7DB0Z+bpxcMPR8Qvgd2Bn5XaKkmSJGkQqaWnm4h4ITAjM78WEROpXMDmr6W2TJIkSRokdjimOyI+BFwIXFwUDQO+VWajJEmSpMGklhMpT6dyGfh1AJm5FNjZC+dIkiRJu4xaQvfmrMwrmAARMarcJkmSJEmDSy2h+7qI+BIwLiL+AbgV+HK5zZIkSZIGj1pmL/lkRJwIrAaeB3wwM28pvWWSJEnSIFHT7CXA/UAjlSEm95fXHEmSJGnwqWX2krcDfwBeC5wB/D4i3lZ2wyRJkqTBopae7guAuZm5EiAiJgC3A1eV2TBJkiRpsKjlRMrFwJqq5TXAonKaI0mSJA0+tfR0LwHujIgbqIzpPg34Q0S8FyAzP11i+yRJkqQBr5bQ/Zfi1uKG4t4L5EiSJEk1qGXKwI/0RUMkSZKkwaqWMd2SJEmSdoKhW5IkSSpZp6E7Iv6ruH9d3zVHkiRJGny66uk+NSKGARf3VWMkSZKkwairEyl/BqwARkXEaiCoTBkYQGbm2D5onyRJkjTgddrTnZkXZObuwE8yc2xmjqm+78M2SpIkSQNaLVMGnhYRewNHFEV3ZubycpslSZIkDR47nL2kOJHyD8DrgNdTuRrlGWU3TJIkSRosarki5b8DR2TmkwARMRG4FfhemQ2TJEmSBota5uke0hK4Cytr3E6SJEkStfV0/ywibga+UyyfCdxUXpMkSZKkwaWWEykviIjXAi+kMl3glZn5w9JbJkmSJA0StfR0k5k/AH5QclskSZKkQcmx2ZIkSVLJDN2SJElSyQzdkiRJUsk6HdMdEfd1tgrIzJxVTpMkSZKkwaWrEym3AQl8G/gRsKFPWiRJkiQNMp0OL8nMOcBZwGgqwfvjwCHAksx8rE9aJ0mSJA0CXY7pzsw/ZeaHMvMwKr3dVwPv6ZOWSZIkSYNEl/N0R8QU4A3A6cDTVAK3F8aRJEmSuqGrEyn/BxgDXAe8BXiqWDU8IvbIzKc621aSJEnSs7rq6d6PyomU7wDOqyqPovw5JbZLkiRJGjQ6Dd2ZOb0P2yFJkiQNWl0NLzmsqw0z84+93xxJkiRp8OlqeMmnqh4fDtxdtZzA8TvaeUScDHwWaAC+kpmXtlsfxfpTgfXAWzLzjxExEvg1MKJo4/cy80PFNh8G/gFYXuzm3zLzph21RZIkSeovXQ0veWnL44i4p3q5FhHRAHwBOBFYDNwVETdm5kNV1U4BZhS3o4ArivtNwPGZuTYihgG/jYifZubvi+0uz8xPdqc9kiRJUn/pcp7uKtmDfR8JLMjMRzNzM3ANcFq7OqcBV2fF74FxETGpWF5b1BlW3HrSBkmSJKnf1Rq6e2IKsKhqeXFRVlOdiGiIiPnAk8AtmXlnVb3zI+K+iLgqIsZ39OQRcV5EzIuIecuXL++oiiRJktQnujqR8v/ybO/y1Ij4XPX6zPynHew7Oihr31vdaZ3M3ArMiYhxwA8jYmZmPkBlCMrHinofozL2/G3b7STzSuBKgKamJnvJJUmS1G+6OpFyXtXjuzut1bnFwLSq5anA0u7WycxVEfEr4GTggcx8omVdRHwZ+HEP2iZJkiT1ma5C973AvZnZ017iu4AZEbE/sITK5eTPblfnRipDRa6hcgLlM5m5LCImAs1F4G4EXgb8F0Ax5ntZsf3pwAM9bJ8kSZLUJ7oK3V8B9o+IPwK/A24Hfp+Zq2vZcWZuiYjzgZupTBl4VWY+GBHvLNZ/EbiJynSBC6hMGfjWYvNJwDeKGVCGANdlZkuP9iciYg6V4SULqVwxU5IkSapb0VVHdkTsRmUWkmOK2xHA34DfZea7+qSFvaCpqSnnzZu344pq4/p7lnDZzY+wdNUGJo9r5IKTDuQ1c9ufCytJkqQWEXF3Zja1L++qp5vMXA/8KiLuAu4EjgXeTGV8tQax6+9ZwsU/uJ8NzVsBWLJqAxf/4H4Ag7ckSVI3dTplYEScHRGfj4jfUhl7fSJwP/DCzHxOXzVQ/eOymx9pDdwtNjRv5bKbH+mnFkmSJA1cXfV0Xwn8Cfgi8OvM/N++aZLqwdJVG7pVLkmSpM51Fbp3B2ZTGcv94Yg4EFgG3AHckZm/6IP2qZ9MHtfIkg4C9uRxjf3QGkmSpIGt0+Elmbk1M/+YmZ/PzLOpzDLyUyozjNzSVw1U/7jgpANpHNbQpqxxWAMXnHRgP7VIkiRp4OrqipSzeHbWkmOA4VR6uf8vlSkENYi1nCzp7CWSJKm37Mozo3U6ZWC7+blvz8zH+rJhvckpAyVJkvpX+5nRoPIr+iWvPXRQBe+eTBl4+kAO2pIkSaofXc2MNphCd2c6HdMN/LDlQUR8vw/aIkmSpEFqV58ZravQHVWPnZdbkiRJPdbZDGi7ysxoXYXu7OSxJEmS1C27+sxoXY3pnh0Rq6n0eDcWjymWMzPHlt46SZIkDQq7+sxonYbuzGzobJ0kSZLUXa+ZO2WXCdntddXTLUmSJPWbwTSvt6FbkiRJdaf9vN5LVm3g4h/cD9Bp8K7nkN7ViZSSJElSv+hqXu+OtIT0Jas2kDwb0q+/Z0kftHbHDN2SJEmqO92d17u7Ib2vGbolSZJUd7o7r3e9X3zH0C1JkqS60915vev94juGbkmSJNWd18ydwiWvPZQp4xoJYMq4Ri557aGdnhhZ7xffcfYSSZIk1aXuzOtd7xffMXRLkiRpUKjni+84vESSJEkqmaFbkiRJKpmhW5IkSSqZoVuSJEkqmaFbkiRJKpmzl0iSJPWh6+9ZUpfT2tVruwYLQ7ckSVIfuf6eJVz8g/vZ0LwVgCWrNnDxD+4H6NeAW6/tGkwcXiJJktRHLrv5kdZg22JD81Yuu/mRXn2e6+9ZwrGX/oL9L/oJx176C66/Z0ldtGtXZk+3JEkaVOp5mMTSVRu6Vd4TPem17ot27ers6ZYkSYNGS+BcsmoDybOBc0c9vTvzfN3pUZ48rrFb5T3Rk17rvmjXrs7QLUmSBo2+HCbRk4B/wUkH0jisoU1Z47AGLjjpwF5rV096rfuiXbs6h5dIkqRBY2eGSXR3WEpXAb+z7VrKyxz+MnlcI0s6ON6ueq37ol27OkO3JEkaNHoSOKFvx0G/Zu6UUsPsBScd2OZYoLZe67LbtatzeIkkSRo0ejpMYjCNg37N3Clc8tpDmTKukQCmjGvkktceaqDuZ/Z0S5KkQaOnwyR6Og66Jz3KfcFe6/pj6JYkSYNKTwKn46BVNkO3JEna5TkOWmUzdEuSpF2evdYqm6FbkiSVrp6vEtnCXmuVqdTZSyLi5Ih4JCIWRMRFHayPiPhcsf6+iDisKB8ZEX+IiHsj4sGI+EjVNntExC0R8efifnyZxyBJknZOX18lUqpHpYXuiGgAvgCcAhwMnBURB7erdgowo7idB1xRlG8Cjs/M2cAc4OSIOLpYdxFwW2bOAG4rliVJUp3qy6tESvWqzOElRwILMvNRgIi4BjgNeKiqzmnA1ZmZwO8jYlxETMrMZcDaos6w4pZV27ykePwN4FfAhSUehyRJg0pfD/XYmatESoNFmcNLpgCLqpYXF2U11YmIhoiYDzwJ3JKZdxZ19i5COcX9Xh09eUScFxHzImLe8uXLd/ZYJEkaFPpjqEe9XkRG6ktlhu7ooCxrrZOZWzNzDjAVODIiZnbnyTPzysxsysymiRMndmdTSZIGrf4Y6tHTq0RKg0mZoXsxMK1qeSqwtLt1MnMVlSEkJxdFT0TEJIDi/slea7EkSYNcfwz18LLkUrljuu8CZkTE/sAS4A3A2e3q3AicX4z3Pgp4JjOXRcREoDkzV0VEI/Ay4L+qtjkHuLS4v6HEY5AkaVDpyZUXe4PT8WlXV1pPd2ZuAc4HbgYeBq7LzAcj4p0R8c6i2k3Ao8AC4MvAu4ryScAvI+I+KuH9lsz8cbHuUuDEiPgzcGKxLEmSauBQD6l/RGXikMGtqakp582b19/NkCSpLgyEC9VIA1VE3J2ZTe3LvSKlJGmXt6uFUId6SH3P0C1J2qW1TKHXMqNHyxR6gMG0A7vaFxSpt5R6GXhJkuqdV0usnZdzl3rO0C1J2qV5tcTa+QVF6jlDtyRpl+bVEmvnFxSp5wzdkqRdmlPo1c4vKFLPGbolSbs0r5ZYO7+gSD3n7CWSpF2eU+jVpuU1cvYSqfsM3ZIkqWZ+QZF6xuElkiRJUskM3ZIkSVLJHF4iSepXXuFQ0q7A0C1J6jeD4RLsfmmQuuG+6+C2j8Izi2H3qXDCB2HW6/u7VX3C0C1J6jddXeFwIATX/v7SYODXgHLfdfCjf4Lm4mJKzyyqLMMuEbwd0y1J6jcD/QqH/XlZ9JbAv2TVBpJnA//19ywp/blV5b7r4PKZ8OFxlfv7ruvvFtWv2z76bOBu0byhUr4LMHRLkvrNQL/CYX9+aejPwK9CS8/tM4uAfLbn1uDdsWcWd698kDF0S5L6zUC/wmF/fmkY6L8SDAq7eM9tt+0+tXvlg4yhW5LUbwb6Jdj780vDTgV+h0T0jl2857bbTvggDGv39zmssVLeW+r4b9sTKSVJ/WogX+GwPy+LfsFJB7Y5iRNqDPy7+MlsvWr3qcXQkg7Ktb2Wv6+yZi+p87/tyMz+bkPpmpqact68ef3dDEnaac5WoWo9+nu4fGYnQXEavOeBcho6UHR3Orv2IQ8qPbev+lxdhLxdSfPWZhZ9fi5/3bSChcOGso3gH55ZXVnZx3/bEXF3Zja1L7enW5IGiP6enk7l2JkvUj36lcAhER3rSS9p2T23aiMzeWrjUyxcvZCFzyzkr8/8tfJ49UIWr1nM1nEBTATguZs3Pxu66+Rv29AtSQPEQJ/Tuq710wU7+uWLlEMiOtbVSZFd/S3Mer0hu5dt2LKBx1c/zmOrH+Ox1Y+1BuuFzyxk9ebVrfWGDxnOvmP35Xnjn8fL93s5+99xJdOfeYLpzc2MqR7JUSd/24ZuSRognK2iJP04DrRfvkid8MGOh0T05slsA5G/APSpLdu2sGztMhauXtgarFvu/7bub23q7rXbXuw3dj9Onn4y03efzv6778/0sdOZNGoSDUOqTmQeuk/lbzs3P1tWR3/bhm5JGiAmj2tkSQcBe6DMaV23etrD2Qv65YuUQyI65i8AvW7Lti0sW7eMRasX8fiaSs/1ojWVx4vWLGLLti2tdccMG8P03afTtHcT+43dj+ljp7Pf2P3Yb+x+7DZst9qesM7/tg3dkjRA9Hi2CnWtH3s4++2LVH8MieinITw18xeAHmne1syytct4fM3jPL768db7RWsWsXjt4jbBunFoI9PGTOOA3Q/g+GnHV8L17pVwPX7EeCJi5xtUx8N9DN2SNED05/R0g1o/9nDuMl+k6nwqN6Due0n7U/O2ZpasWdLaQ/3Y6scqj1cvYunapWzJtsF6v7H7MWP8DE7Y9wT2G7sf08ZMY9+x+zKxcWLvBOsByikDJUm7tn6e9m2XmAbSaQrr3sYtG1mydgmL1ixqDdaL1izi8dWPs2zdMrbms18MRw0bxb5j9mXfsfuy75h9mTZmGvuN3Y99x+7LhJETejdY1/svJB1wykBJUn3q7w/Vfu7hHMgXB6qZJyn2u5bp9havXVwZ+rHm2fvFaxbz5IYn29QfPWw0+47dl0P3PJRTn3Nqm5C9x8g9+qbHeiD8QtINhm5JGkj6O6D2tnr5UK3jcaCDgicp9okNWzawdO1SlqxdwuI1i1mydklr7/XiNYtZv2V9m/p7Ne7F1DFTecHkFzB1zFSmjZnWet9rY6x3Rj+e5FwGQ7fUXYMt9GjgqJeA2psG2YeqOuFJir2ieWszy9YtY/Haxa3hesmaSrBevHYxT218qk39EQ0jmDx6MtPGTOOIfY5g6uhng/WU0VMYOXRkPx1JjQbZLySGbqk7BmPo0cAxGAPqIPtQVSc8SbEmW7dtZfmG5W16qatvT65/km25rbX+0BjKPqP2YcqYKbx02kuZPHoyU0ZPYcroKUwdM7X3x1f3tUH2C4mhW+qOwRh6NHAMxoA6yD5U1QWH8LAtt7FiwwqWrl3KsnXLWoeBtPRaL123tM0Ue0EwcbeJTB09lSP2PoIpY6a0huopo6ew1257MXRIL0a5evsld5D9QmLolrpjMIYeDRyDMaAOsg9V7dqatzXzxLonWgP1srXLWLpuaev939b9jeZtzW222WPkHkwZPYWDJxzMy/Z7WaWXevRUpoyZwqRRkxjeMLxvGl+Pv+QOsl9IDN1SdwzG0DPA7RLTrbUYjAF1kH2oavDKTNY0r2HZ2mX8bd3fWLZuWevtb+v+xtK1S1m+YXmb4R8AExsnMmn0JA6ZcAgn7ncik0dNZtLoSUweNZnJoyfXfrXFstXrL7mD6BcSQ7fUHYMx9Axg19+zpM2FRZas2sDFP7gfYHAG78EaUAfRh6oGruatzTyx/onWQF0drFser2te12aboUOGss9u+7DPqH04atJRTB49uU2o3mfUPn3XU72z/CW3dIZuqTsGa+gZoC67+ZE2V/ID2NC8lctufmRwhm4woEo9sGXbFlZsWMHf1v3t2dv6yv0T657gb+v/xsoNK0naXjBw/Ijx7DNqH/Ydsy9HTTqKSaMmsc+ofZg0ahKTRk1iQuMEhsSQfjqqXuYvuaUzdEvdZeipG0tXbehWuZ61Sw3L0aC2aesmnlz/ZOvtiXVP8MT6JyqPi57rjoZ97DZ0N/YZVemlnjF+RuvjfXbbh31GV4J149DGfjqqfuAvuaUzdEsasCaPa2RJBwF78rhd6IOyB3a5YTkakDKT1ZtXtwbolhD9xLon2oTspzc9vd22jUMb2Xu3vdlrt704atJR7L3b3s+G6uI2ZtiY/ptOr95mCQF/ye0Dhm6pm+whrB8XnHRgm/AI0DisgQtOOrAfW1X/dslhOaorLcM9WoJ0m/uqUL1x68bttt1j5B6tIXrWxFnstdte7L3b3q0he69Re/VvoN6RepwlpIW/5JbK0C11gz2E9aXlNfdLUPf05rAcv4RSn72W/WRbbuOpjU+1Burl65ezfMPyNvdPrn+SFRtXbDfcY9iQYa0B+uAJB/OSaS+pLI96NlBPbJw4cE5M7Ey9zhKi0hm6NaD09we8PYT15zVzp/jad1NvDcvxSyj13WvZi7Zs28JTG59i+YblrNywsuMwveFJntrwFFtyy3bbjx8xnj1325OJjROZMX5GpUe6pYd6VCVQjx8xvn57p3tTX80S4pfBulNq6I6Ik4HPAg3AVzLz0nbro1h/KrAeeEtm/jEipgFXA/sA24ArM/OzxTYfBv4BWF7s5t8y86Yyj0P1oR4+4D1xrw75wdJtvTUsxy+hDPhey/XN61m+YTkrNqyo3K9f0fp45YaVreue3vj0djN7wLNheq/GvThg3AGV3ujdJjKxcWLr/Z6Ne/Z973Q9/7/QF7OE7CJfBgea0kJ3RDQAXwBOBBYDd0XEjZn5UFW1U4AZxe0o4Irifgvwr0UAHwPcHRG3VG17eWZ+sqy2qz7Vwwe8J+7VGT9YeqS3huX4JZS6nNt4ffN6Vm5cycoNxW3jSlZsWNHh4w1btn+vhg4Zyp6Ne7LnyD2ZPHoysybOag3PExontD7ulzBdi3r/f6EvZgkZ4F8GB6sye7qPBBZk5qMAEXENcBpQHbpPA67OzAR+HxHjImJSZi4DlgFk5pqIeBiY0m5bla3Oegrq4QPeE/fqjB8sPdYbw3L8Ekqf9Fq2XAnxqQ1PsXLjSp7a+FSbx+3D9Pot6zvcz/gR45nQOIEJjROYNXFWmxDdcj+xcSJjR4wd2HNP1/v/C30xS0gdfhlUuaF7ClD9P9FiKr3YO6ozhSJwA0TEdGAucGdVvfMj4s3APCo94tvNFxQR5wHnAey77749PohdVh32FNTDB7wn7tUZP1j6lV9C6XGv5aatm3h649OVAL3xqdbHLT3ULWG6ZX3ztuYO9zNuxDj2GLkHezbuycwJM1tD9YSRE1pD9Z6NezJ+5HiGDRnWm0devwbC/wtlzxLihW7qUpmhu6OzIdoPCOuyTkSMBr4P/Etmri6KrwA+VtT7GPAp4G3b7STzSuBKgKampu0HoqlrddhTUC8f8J64V0f8YOlXfgml9f/Djbd9lKfXLuOp3Sfx1NyzeXrUSJ5+8BttQnV1yO6sN3r4kOFMaJzQGqSfN/55rct7jNyjNVDvMXIPxo0ct+sE6e7w/wUvdFOnygzdi4FpVctTgaW11omIYVQC939n5g9aKmTmEy2PI+LLwI97t9kC6rKnwA94bccPln43GL+Ebtm2hVWbVrFq4yqe3vQ0qzatag3NqzZVyqqXV21axYY9AvaYXNnBo9+BRysPhw4Z2hqYx48Yz7Sx0xg/YvyzZSPHt95PGDmBUcNG7RozeJTJ/xe80E2dKjN03wXMiIj9gSXAG4Cz29W5kcpQkWuoDD15JjOXFbOafBV4ODM/Xb1B1ZhvgNOBB0o8hl1XnfYUDMYPeO0EP1jUhcxkbfNantn0TOtt1aZVPLO5cr960+rKctW6VZtWsXrz6k73OXrYaMaNGMf4kePZs3FPZoyfwfgR4xk3chzjR4xvDdEtQXr0sNGG6L7m/wsVXuim7kTlHMaSdh5xKvAZKlMGXpWZH4+IdwJk5heLcP154GQqUwa+NTPnRcQLgd8A91OZMhCKqQEj4pvAHCrDSxYC76gK4R1qamrKefPm9fbhDW7tx3RDpafgVZ/zH7GkPpWZbNiyoRKOi8C8XZBuWW63fmtu7XS/Y4aNYeyIsYwbMY7dR+zO7sN3Z/zIZwN0dZAeP2I840aMY1iDwzkkdS0i7s7Mpu3Kywzd9cLQ3UN1NnuJpIFt67atrNm8hjWb17B682qe2fwMqzevZvWm1ZX7zasrIXpjpTe6OlR3diIhQOPQRnYfsXslPA/f/dnHI3ZvvbVZHr47Y0eMdTx0T/nZIHWps9DtFSnVOX+aklQlM9m4dWNrcK6+tYTm1ZtWs6Z5TZsg3fJ4bfPaLvc/fMhwxo0Y19r7vN/Y/dos7z68bXhuWTeiYUQfvQKqx5mtpIHC0C1Ju4gt27awdvNa1jZXbms2r2Fd87rW0Lxm8xrWbl7LmuZng/TazWvbhOuOLvFdbWTDSMYOH8vYEWMZO3ws++y2DzPGzWhdrl43dvhYxgwf01o2smGk45/rXR3ObCUNFIZuSapzW7dtZf2W9axrXse65nWsbV7Lus3rOgzPa5vXPvu4KmCva17X4dUH22sc2siYYWMYM7xy22PkHuw7dt/WgDxm+BhGDxvdujx6+OjWsdFjh4+tzysUqvfU4cxW0kBh6JakXpaZNG9rZn3z+tawXB2aq29rm9eyvnl9m8fV97WGZYBRw0Yxetjoym34aHYfuTtTxkxh9LDRjBk+hlHDRlXu//YQY/74TUY3b2T0tmTMtm2MaRjO6FM/zbDZZ5X86mhAq9OZraSBwNAtaZe2LbexcctG1m9Zz4YtG9rcWkLz+ub1bR9XBekNzRvaLLfU3dEwjBbDhwxn1LBRbW4TRk5gvzH7sduw3Rg9bPR263cbtltrj3NLwB41bFTtl+7+2UxY80zbsi1b4BcfB0O3uuIc2FKPGbrL4JndUq/ITDZt3cSmrZvYuGVj5X7rRjZtqdxXl23csrE1KLcPz53d1jevZ+PWjd1qU+PQRnYbuhu7DduN3Ybuxqhhoxg7Yiz7jNqndbllXfv70cNHt96PGloJ0P0yBZ1DBNRTzoEt9Zihu7d5ZrcGsW25rRKCi9BbHYarH2/YsqHTsFy9vrqsOkxXb9cTQ4cMpXFoY2tAbnk8dvhY9t5t79blxqGNNA5rbLtcdRs1bFRraB41bBQjG0bSMKShl1/VfuAQAe0MZ7aSesTQ3ds8s1slyEy25BY2b9387G3bZpq3NrN52+btytusLx5v2rppu/rN2yrrN23d1Fq/ffht87iHIRgqwyhGDB1BY0MjI4aOYETDCEY2jGTE0BGMHT6WiQ0TK+uHNrZZV/14ZMNIRg4duV3ZiIYRbQK08y/vgEMEJKnPGbp7mz/b1oXMZGturdy2bWVLbmHrtsrylm1bOiyvpV5L2ZZtW9iSW2je2kzztma2bNtC87a2j1vLtjb3St3eMjSGMqxhGMMbhjN8yHCGNwxn2JBhjGgYUSlrGM7uI3dn74a9K+G2XchtCbgjGkZ0uL6jYDyiYUTt441VPocISFKfM3T3tuJn2weHD+Nno0Y9Wz5iDMz7VP+1q4cyk21sq9zntmdvnZRty22tgbd1PR2XtWzXpmxb2323btNBWVeBuatLP5cpCIYNGcbQIZVg2/q46r768W5Dd3u2vKHzukOHDG0NyK23Ic/eV4foEQ0jKstV9YcNeXb9oBgeoZ3nEIHBwXOIpAHD0N3bip9tFw4Lrh07uigMGDocHrm2X5vWU0NiCEMYQkRUHrfcOiqLIQSdlzVEQ+s2QdAwpKHyuKUsgoZoqOn5hg4ZSkM00BANzz4esv3y0BjaYXmt9arLq5fbB+iWbQbsxT388JYGFs8hkgYUQ3dvK/6je8VtH+UVjxleNED44S0NPJ5DJA0ohu4y+LOtBho/vKWBx3OIpAHF0C3JD++SXX/PEi67+RGWrtrA5HGNXHDSgbxm7pT+bpYGOqd+lAYUpxOQ6t1918HlM+HD4yr3913X+8/R2Ye0H9477fp7lnDxD+5nyaoNJLBk1QYu/sH9XH/Pkv5umga6Ez5YmeqxmlM/SnXL0C3Vs5ax1s8sAvLZsda9Hbz98C7NZTc/wobmtrPpbGjeymU3P9JPLdKgMev18KrPwe7TgKjcv+pzDgmT6pTDS6R61ldjrZ23uTRLV23oVvmA46w3O29nXkPPIZIGDEO3VM/6cqy1H96lmDyukSUdBOzJ4xo7qD3AOOvNzvM1lHYZDi+R6pljrQe8C046kMZhbS9I1DisgQtOOrCfWtSLuvolRrXxNZR2GfZ0S/WsuNhSmw9lx1qXrjdnG2nZblDOXuKsNzvP11DaZRi6pXrmWOs+1zLbSMvJjy2zjQA7FbwHRchuzynrdp6vobTLcHiJVO9mvR7e8wB8eFXl3sBdKmcb6QZnvdl5vobSLsOebkmAF3BpMehnG+lN/hKz83wNpV2GoVtSKUMqBqpSZhsZzNPqOevNzvM1lHYJDi+R5JCKKr0+20hfXeBIklTXDN2SHFJR5TVzp3DJaw9lyrhGApgyrpFLXntoz3v8nRJOkoTDSyQxyC/g0gO9OtuIU8JJkrCnWxKD/AIu/c0LHEmSsKdbqnt9MavIoL6AS0/05omPXuBIkoShW6prfTmryKC9gEt3tZz42BKSW058hJ4Fb6eEkyQBkZn93YbSNTU15bx58/q7GVK3HXvpLzocaz1lXCO/u+j4fmjRLuDymZ1cIXBa5eJEkiR1ISLuzsym9uWO6ZbqmLOK9ANPfJQklcDQLdWxzmYP2VVnFekTnvgoSSqBoVuqY84q0g9O+GDlRMdqnvgoSdpJnkgp1TFnFekHnvgoSSqBJ1JKkiRJvcQTKTU43HddZXaJD4+r3N93XX+3SJIkaYccXqKBo7fnT5YkSeoj9nRr4Ljto22v6geV5ds+2j/tkSRJqpGhWwOH8ydLkqQBytCtgcP5kyVJ0gBVauiOiJMj4pGIWBARF3WwPiLic8X6+yLisKJ8WkT8MiIejogHI+Kfq7bZIyJuiYg/F/fjyzwG1RHnT5YkSQNUaaE7IhqALwCnAAcDZ0XEwe2qnQLMKG7nAVcU5VuAf83Mg4CjgXdXbXsRcFtmzgBuK5a1K5j1enjV52D3aUBU7l/1OU+ilCRJda/M2UuOBBZk5qMAEXENcBrwUFWd04CrszJZ+O8jYlxETMrMZcAygMxcExEPA1OKbU8DXlJs/w3gV8CFJR6H6sms1xuyJUnSgFPm8JIpwKKq5cVFWbfqRMR0YC5wZ1G0dxHKKe736ujJI+K8iJgXEfOWL1/e02OQJEmSdlqZoTs6KGt/+csu60TEaOD7wL9k5uruPHlmXpmZTZnZNHHixO5sKkmSJPWqMkP3YmBa1fJUYGmtdSJiGJXA/d+Z+YOqOk9ExKSiziTgyV5utyRJktSrygzddwEzImL/iBgOvAG4sV2dG4E3F7OYHA08k5nLIiKArwIPZ+anO9jmnOLxOcAN5R2CJEmStPNKO5EyM7dExPnAzUADcFVmPhgR7yzWfxG4CTgVWACsB95abH4s8PfA/RExvyj7t8y8CbgUuC4izgUeB15X1jFIkiRJvSEqE4cMbk1NTTlv3rz+boYkSZIGuYi4OzOb2pd7RUpJkiSpZIZuSZIkqWSGbkmSJKlkhm5JkiSpZIZuSZIkqWSGbkmSJKlkhm5JkiSpZIZuSZIkqWS7xMVxImI58FhJu98TWFHSvlUe37eByfdt4PK9G5h83wYu37v+s19mTmxfuEuE7jJFxLyOrjqk+ub7NjD5vg1cvncDk+/bwOV7V38cXiJJkiSVzNAtSZIklczQvfOu7O8GqEd83wYm37eBy/duYPJ9G7h87+qMY7olSZKkktnTLUmSJJXM0C1JkiSVzNBdo4i4KiKejIgHqsr2iIhbIuLPxf34/myjthcR0yLilxHxcEQ8GBH/XJT73tW5iBgZEX+IiHuL9+4jRbnv3QAQEQ0RcU9E/LhY9n0bACJiYUTcHxHzI2JeUeZ7V+ciYlxEfC8i/lR83r3A963+GLpr93Xg5HZlFwG3ZeYM4LZiWfVlC/CvmXkQcDTw7og4GN+7gWATcHxmzgbmACdHxNH43g0U/ww8XLXs+zZwvDQz51TN8ex7V/8+C/wsM58PzKbyb8/3rc4YumuUmb8GnmpXfBrwjeLxN4DX9GWbtGOZuSwz/1g8XkPlP6Ip+N7VvaxYWywOK26J713di4ipwCuAr1QV+74NXL53dSwixgLHAV8FyMzNmbkK37e6Y+jeOXtn5jKohDtgr35uj7oQEdOBucCd+N4NCMUQhfnAk8Atmel7NzB8Bng/sK2qzPdtYEjg5xFxd0ScV5T53tW35wDLga8VQ7q+EhGj8H2rO4Zu7RIiYjTwfeBfMnN1f7dHtcnMrZk5B5gKHBkRM/u5SdqBiHgl8GRm3t3fbVGPHJuZhwGnUBmOd1x/N0g7NBQ4DLgiM+cC63AoSV0ydO+cJyJiEkBx/2Q/t0cdiIhhVAL3f2fmD4pi37sBpPip9FdUzqvwvatvxwKvjoiFwDXA8RHxLXzfBoTMXFrcPwn8EDgS37t6txhYXPwSCPA9KiHc963OGLp3zo3AOcXjc4Ab+rEt6kBEBJVxbg9n5qerVvne1bmImBgR44rHjcDLgD/he1fXMvPizJyamdOBNwC/yMw34ftW9yJiVESMaXkMvBx4AN+7upaZfwMWRcSBRdEJwEP4vtUdr0hZo4j4DvASYE/gCeBDwPXAdcC+wOPA6zKz/cmW6kcR8ULgN8D9PDu+9N+ojOv2vatjETGLysk/DVQ6CK7LzI9GxAR87waEiHgJ8L7MfKXvW/2LiOdQ6d2GypCFb2fmx33v6l9EzKFy4vJw4FHgrRT/b+L7VjcM3ZIkSVLJHF4iSZIklczQLUmSJJXM0C1JkiSVzNAtSZIklczQLUmSJJXM0C1JkiSVzNAtST0UER+IiAcj4r6ImB8RR3Vz+3ER8a7OlnvQntt7um1ZImJtN+pOi4hfRsTDxev6z+3WN0TEZ4t19xfzSrffR2NE/E9RtzEiPh0RX4iI/4yI4RHx64gY2hvHJkndYeiWpB6IiBcArwQOy8xZVK6YuaibuxkHvKuL5VraERExBCAzj+nm89ebLcC/ZuZBwNHAuyPi4Kr1FwOPZuYhwOfo+LV6G/CDzNwK/COVC7y8G3h+Zm4GbgPOLPMgJKkjhm5J6plJwIrM3ASQmSsycylARLy56P2+NyK+WZRdHxF3F7205xX7uBQ4oOglv6yDZSLiTRHxh6LsS0UP7vSiN/j/AX8EphV111at+3LxXD+PiMaWRkfEf0TEnyLiloj4TkS8r/2BddTWXtrvdsdSvT4zl2XmH4vHa4CHgSnFtqOA0zPzs0X1vwLP7eB9eSPPXu76EOD+iBgOrC/Kri/qSFKfMnRLUs/8HJgWEf8bEf8vIl4MEBGHAB8Ajs/M2UDLEIm3ZebhQBPwT8WltS8C/pKZczLzgvbLEXEQlV7ZYzNzDrCVZwPjgcDVmTk3Mx9r17YZwBeKHuFVwN8VbWsqHs8FXlu0pSMdtXWn9ruDY9lOREwv9ndnUfQyKq/3/IiYD1wFPNVum+HAczJzYVF0HXAl8FngkqLsAeCIzp5XksriuDZJ6oHMXBsRhwMvAl4KXBsRFwFjgO9l5oqiXksw/KeIOL14PI1KgP3bDp7mBOBw4K6IAGgEngR+DTyWmb/vZLu/Zub84vHdwPTi8QuBGzJzA0BE/KiT7Ttr687st7Nj2U5EjAa+D/xLZq4uiucAH8zMLxZ1vgLc127TPal8GQAgM38C/KS6QmZujYjNETGm6E2XpD5h6JakHirGDf8K+FVE3A+cA9wCZHW9iHgJlZ7aF2Tm+oj4FTCyhqcI4BuZeXG7/U0H1nWx3aaqx1upBNyW/XX9hF23tcf7pZNj6eD5h1EJ3P+dmT+oWjWeypASihMhXw58vN3mG6jtdR0BbKyhniT1GoeXSFIPRMSBETGjqmgO8BiVE/Ve3zIkIyL2AHYHni5C7POpnCQIsIZKzzidLN8GnBERe7XsKyL224lm/xZ4VUSMLHqTX9FBnc7aurP73eGxRKUL/KvAw5n56Xbb/29VW94D/CQz/1pdITOfBhoiotPgXbwvyzOzuYbjkqReY0+3JPXMaOD/RsQ4KrNuLADOy8wVEfFx4H8iYitwD/AO4J0RcR/wCPB7gMxcGRG/i4gHgJ8W47jbL/878PNihpJm4N3seFhKhzLzroi4EbiXyheEecAz7ar9rKO27ux+M/OhTo6lejz6scDfUzn5cX5R9m+ZeRPwHeCnEbEAuAM4j479nMpwl1s7Wf9S4KYdHZMk9bbIzB3XkiQNChExuhiPvhuVseHntcwYUo/77UE75gLvzcy/72T9D4CLM/ORvm2ZpF2dPd2StGu5MipzX4+kMsa6t4JxWfvtlsy8JyoX2Gkoxty3KmY3ud7ALak/2NMtSZIklcwTKSVJkqSSGbolSZKkkhm6JUmSpJIZuiVJkqSSGbolSZKkkhm6JUmSpJIZuiVJkqSSGbolSZKkkhm6JUmSpJL9/57eEAvFhaTRAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = subplots(figsize=(12,8))\n",
    "ax.plot(*calc_fwhm(res, LaB6), \"o\", label=\"rot2\")\n",
    "ax.plot(*calc_fwhm(res2, LaB6), \"o\", label=\"rot1 + 2\")\n",
    "# for lbl, sg in gonioref2d.single_geometries.items():\n",
    "#     ai = gonioref2d.get_ai(sg.get_position())\n",
    "#     img = sg.image * ai.dist * ai.dist / ai.pixel1 / ai.pixel2\n",
    "#     res = ai.integrate1d(img, 5000, unit=\"2th_deg\", method=\"splitpixel\")\n",
    "#     t,w = calc_fwhm(res, calibrant=calibrant)\n",
    "#     ax.plot(t, w,\"-o\", label=lbl)\n",
    "ax.set_title(\"Peak profile as function of the angle\")\n",
    "ax.set_ylabel(\"FWHM of peaks (in degrees)\")\n",
    "ax.set_xlabel(res.unit.label)\n",
    "ax.plot(tth_deg, model_Caglioti(tth_deg, *fit), label=\"U:%.1e, V:%.1e, W:%.1e\"%(fit[0], fit[1], fit[2]))\n",
    "ax.legend()\n",
    "pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "\n",
    "This notebook exposes the how to calibrate the goniometer for a small detector moving on a 2theta arm. \n",
    "Once calibrated, the geometry can be saved and restored and stays valid as long as the detector or the goniometer is not unmounted from the beam-line. This configuration can subsequently be used to integrate the data acquired with any  sample, in minutes instead of hours. The resolution limit is now the pixel size. Fortunately, pixel detector with small pixel like the MaxiPix or the Lambda detector exists and offer higher resolution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total execution time: 31.152 s\n"
     ]
    }
   ],
   "source": [
    "print(f\"Total execution time: {time.perf_counter() - start_time:.3f} s\")"
   ]
  }
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