Spatial Upsampling.ipynb

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 "cells": [
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   "cell_type": "code",
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   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import os\n",
    "from scipy.io import loadmat\n",
    "from scipy.optimize import curve_fit\n",
    "from scipy.special import sph_harm\n",
    "from scipy.signal import hilbert\n",
    "import sound_field_analysis as sfa\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def spec_diff(x, y, axis=None):\n",
    "    if axis is None:\n",
    "        return 20 * np.abs(np.log10(np.abs(x)) - np.log10(np.abs(y))).mean()\n",
    "    else:\n",
    "        return 20 * np.abs(np.log10(np.abs(x)) - np.log10(np.abs(y))).mean(axis)\n",
    "\n",
    "\n",
    "def sph_harm_all(nMax, az, el):\n",
    "    # copy from sofia\n",
    "    degs = np.arange(nMax + 1)\n",
    "    n = np.repeat(degs, degs * 2 + 1)\n",
    "    elementNumber = np.arange((nMax + 1) ** 2) + 1\n",
    "    t = np.floor(np.sqrt(elementNumber - 1)).astype(int)\n",
    "    m = elementNumber - t * t - t - 1\n",
    "    mA, azA = np.meshgrid(m, az)\n",
    "    nA, elA = np.meshgrid(n, el)\n",
    "    return sph_harm(mA, nA, azA, elA)\n",
    "\n",
    "def iSpatFT(spherical_coefficients, position_grid):\n",
    "    spherical_coefficients = np.atleast_2d(spherical_coefficients)\n",
    "    number_of_coefficients = spherical_coefficients.shape[0]\n",
    "    order_max = int(np.sqrt(number_of_coefficients) - 1)\n",
    "\n",
    "    spherical_harmonic_bases = sph_harm_all(order_max, position_grid.azimuth, position_grid.colatitude)\n",
    "    spherical_harmonic_bases = np.asarray(spherical_harmonic_bases)\n",
    "    return np.dot(spherical_harmonic_bases, spherical_coefficients.reshape(spherical_harmonic_bases.shape[1], -1)\n",
    "                  ).reshape(-1, *spherical_coefficients.shape[1:])\n",
    "\n",
    "def spatFT(data, position_grid, order_max):\n",
    "    data = np.atleast_2d(data)\n",
    "    spherical_harmonic_bases = sph_harm_all(order_max, position_grid.azimuth, position_grid.colatitude)\n",
    "    spherical_harmonic_bases = np.asarray(spherical_harmonic_bases)\n",
    "    if position_grid.weight is None:\n",
    "        spherical_harmonic_weighted = np.linalg.pinv(spherical_harmonic_bases)\n",
    "    else:\n",
    "        spherical_harmonic_weighted = (np.conj(spherical_harmonic_bases).T * (4 * np.pi * np.asarray(position_grid.weight)))\n",
    "\n",
    "    return np.dot(spherical_harmonic_weighted, data.reshape(spherical_harmonic_weighted.shape[1], -1)).reshape(-1, *data.shape[1:])\n",
    "\n",
    "def sh_spec(Pnm):\n",
    "    number_of_coefficients = Pnm.shape[0]\n",
    "    order_max = int(np.sqrt(number_of_coefficients) - 1)\n",
    "    degs = np.arange(order_max + 1)\n",
    "    n = np.repeat(degs, degs * 2 + 1)\n",
    "    \n",
    "    spec = np.empty((order_max + 1, Pnm.shape[1]))\n",
    "    for i in range(order_max + 1):\n",
    "        spec[i] = np.sqrt(np.sum(np.abs(Pnm[n == i]) ** 2, 0))\n",
    "    spec /= spec.max(0)\n",
    "    return spec\n",
    "\n",
    "def phase_correct_vector(r, az_lr, col_lr, grid, freqs):\n",
    "    k = 2 * np.pi * freqs / 343\n",
    "    cos_theta = np.cos(col_lr) * np.cos(grid.colatitude)[:, None] + \\\n",
    "                np.sin(col_lr) * np.sin(grid.colatitude)[:, None] * np.cos(grid.azimuth[:, None] - az_lr)\n",
    "    C = np.exp(-1j * k * r * cos_theta[..., None])\n",
    "    return C"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load HUTUBS\n",
    "\n",
    "According to the paper, the SH coefficeints of measured HRTFs are already time-aligned, and this brings some inconveniences when generating sparse sampled HRTF, so I used the simulated data for the following demos, but the same techniques can be used on measured HRTFs, of course."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp72_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp94_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp22_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp10_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp88_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp21_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp18_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp27_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp65_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp23_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp62_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp44_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp7_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp78_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp70_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp30_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp28_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp77_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp96_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp51_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp33_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp87_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp56_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp42_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp20_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp93_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp48_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp41_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp49_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp24_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp80_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp52_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp71_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp60_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp32_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp75_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp92_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp13_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp45_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp47_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp34_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp14_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp38_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp40_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp54_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp25_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp89_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp6_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp64_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp69_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp66_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp26_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp29_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp2_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp19_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp79_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp82_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp95_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp11_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp57_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp58_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp86_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp91_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp3_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp61_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp15_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp39_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp43_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp59_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp74_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp68_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp12_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp9_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp55_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp31_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp73_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp67_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp50_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp4_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp8_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp76_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp53_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp37_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp63_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp35_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp5_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp83_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp17_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp16_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp36_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp85_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp1_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp84_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp81_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp90_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n",
      "\n",
      "open SOFA file \"/home/ycy/data-disk/Datasets/HUTUBS/HRIRs/pp46_HRIRs_simulated.sofa\"\n",
      " --> samplerate: 44100 Hz, receivers: 2, emitters: 1, measurements: 1730, samples: 256, format: float64\n",
      " --> convention: SimpleFreeFieldHRIR, version: 1.0\n"
     ]
    }
   ],
   "source": [
    "hutubs_dir = '~/data-disk/Datasets/HUTUBS/HRIRs'\n",
    "subject_name = []\n",
    "subject_hrir = []\n",
    "subject_sph = []\n",
    "\n",
    "for dir_path, _, files in os.walk(os.path.expanduser(hutubs_dir)):\n",
    "    for f in files:\n",
    "        if f[-5:] == '.sofa' and 'simulated' in f:\n",
    "            name = f.split('_')[0]\n",
    "            subject_name.append(int(name[2:]))\n",
    "            \n",
    "            hrir = sfa.io.read_SOFA_file(os.path.join(dir_path, f))\n",
    "            subject_hrir.append(np.stack((hrir.l.signal, hrir.r.signal), 1))\n",
    "            \n",
    "            hrtf = np.fft.rfft(hrir.l.signal)\n",
    "            \n",
    "            sph = loadmat(os.path.join(dir_path, name + '_SHcoefficients_simulated.mat'))\n",
    "            *Pnm, max_order, n, m, freqs, sr, _, _  = sph['HRIR'][0][0]\n",
    "            subject_sph.append(np.stack(Pnm, 1))\n",
    "            \n",
    "            max_order = np.squeeze(max_order)\n",
    "            sr = np.squeeze(sr)\n",
    "            freqs = np.squeeze(freqs)\n",
    "            grid = hrir.grid\n",
    "            \n",
    "            \n",
    "\n",
    "subject_hrir = np.stack(subject_hrir, 0)\n",
    "#subject_sph = spatFT(np.fft.rfft(subject_hrir).swapaxes(0, 1), grid, max_order).swapaxes(0, 1)\n",
    "subject_sph = np.stack(subject_sph, 0)\n",
    "# subject_name = sorted(subject_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculate Time-of-Arrival"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "subject_hrtf = np.fft.fft(subject_hrir)\n",
    "log_mag = np.log(subject_hrtf).real\n",
    "min_phase = - np.imag(hilbert(log_mag))\n",
    "min_hrtf = np.exp(log_mag + 1j * min_phase)\n",
    "toa = np.argmax(np.fft.ifft(subject_hrtf * min_hrtf.conj()).real, axis=-1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fit the data with a rigid sphere model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "def toa_func(P, r, az0, az1, incli0, incli1, delta):\n",
    "    E = sfa.utils.sph2cart([[az0, az1], [incli0, incli1], [r, r]]).T\n",
    "    R = np.sqrt(np.sum(P ** 2, 1))\n",
    "\n",
    "    PE_cos = P @ E.T / R[:, None] / np.sqrt(np.sum(E ** 2, 1))\n",
    "    path_length = np.where(PE_cos > 0, R[:, None] - r *  PE_cos, R[:, None] + r * np.arcsin(-PE_cos))\n",
    "    y = path_length / 343 * sr + delta\n",
    "    return y.ravel()\n",
    "\n",
    "P_xyz = sfa.utils.sph2cart((grid.azimuth, grid.colatitude, grid.radius)).T\n",
    "subject_sphere_params = []\n",
    "for i in range(toa.shape[0]):\n",
    "    popt, _ = curve_fit(toa_func, P_xyz, toa[i].ravel(),\n",
    "                        p0=(0.0825, 0.5 * np.pi, 1.5 * np.pi, 0.5 * np.pi, 0.5 * np.pi,0),\n",
    "                        bounds=([0, 0, np.pi, 0, 0, -np.inf], [np.inf, np.pi, 2 * np.pi, np.pi, np.pi, np.inf]))\n",
    "    delay = toa_func(P_xyz, *popt).mean() / sr - popt[-1] / sr\n",
    "    subject_sphere_params.append(popt.tolist() + [delay])\n",
    "subject_sphere_params = np.stack(subject_sphere_params, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average of rigid sphere radius: 9.096461934867667 cm\n",
      "Standard deviation of rigid sphere radius: 0.373705942562396 cm\n",
      "Average of IR offset: -2.8728041928910244 ms\n",
      "Standard deviation of IR offset: 0.005354444926929321 ms\n",
      "Average left ear position: 89.35630731025347 94.02739959473963 (az/co)\n",
      "Average right ear position: -89.23086905515441 94.20537617960434 (az/co)\n",
      "Average delay: 4.295712421692891 ms\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Average of rigid sphere radius:\", subject_sphere_params[:, 0].mean() * 100, \"cm\")\n",
    "print(\"Standard deviation of rigid sphere radius:\", subject_sphere_params[:, 0].std() * 100, \"cm\")\n",
    "print(\"Average of IR offset:\", subject_sphere_params[:, -2].mean() / sr * 1000, \"ms\")\n",
    "print(\"Standard deviation of IR offset:\", subject_sphere_params[:, -2].std() / sr * 1000, \"ms\")\n",
    "print(\"Average left ear position:\", subject_sphere_params[:, 1].mean() / np.pi * 180, subject_sphere_params[:, 3].mean() / np.pi * 180, \"(az/co)\")\n",
    "print(\"Average right ear position:\", subject_sphere_params[:, 2].mean() / np.pi * 180 - 360, subject_sphere_params[:, 4].mean() / np.pi * 180, \"(az/co)\")\n",
    "print(\"Average delay:\", subject_sphere_params[:, -1].mean() * 1000, \"ms\")\n",
    "\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(14, 14))\n",
    "ax = fig.add_subplot(111, projection='hammer')\n",
    "ax.set_title(\"Estimated ear positions\")\n",
    "ax.grid()\n",
    "ax.scatter(subject_sphere_params[:, 1], 0.5 * np.pi - subject_sphere_params[:, 3])\n",
    "ax.scatter(subject_sphere_params[:, 2] - 2 * np.pi, 0.5 * np.pi - subject_sphere_params[:, 4])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# SUpDEq"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get equalization datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "custom_eq = []\n",
    "nfft = len(freqs) * 2 - 2\n",
    "for sphere_param in subject_sphere_params:\n",
    "    ac = sfa.io.ArrayConfiguration(sphere_param[0], 'rigid', 'omni')\n",
    "    left_eq = sfa.gen.ideal_wave(35, sr, sphere_param[1], sphere_param[3], ac, NFFT=nfft, delay=0)\n",
    "    right_eq = sfa.gen.ideal_wave(35, sr, sphere_param[2], sphere_param[4], ac, NFFT=nfft, delay=0)\n",
    "    custom_eq.append(np.stack((left_eq, right_eq), 1))\n",
    "\n",
    "custom_eq = np.stack(custom_eq, 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Redo Figure 2. (c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4 4.915667321958767\n",
      "7 4.48408401490741\n",
      "10 4.1064677788115205\n",
      "4 3.1148652584175327\n",
      "7 2.02727438941457\n",
      "10 1.4488453300314659\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "max_order = 11\n",
    "target_grid = grid #sfa.gen.lebedev(max_order)\n",
    "\n",
    "target_hrtf = iSpatFT(subject_sph.swapaxes(0, 1), target_grid).swapaxes(0, 1)\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(10, 6))\n",
    "\n",
    "for with_eq in [False, True]:\n",
    "    for N in [4, 7, 10]:\n",
    "        sparse_grid = sfa.gen.lebedev(N)\n",
    "        lr_hrtf = iSpatFT(subject_sph.swapaxes(0, 1), sparse_grid)\n",
    "        \n",
    "        if with_eq:\n",
    "            lr_hrtf /= iSpatFT(custom_eq.swapaxes(0, 1), sparse_grid)\n",
    "        sparse_sph = spatFT(lr_hrtf, sparse_grid, N)\n",
    "        hr_hrtf = iSpatFT(sparse_sph, target_grid).swapaxes(0, 1)\n",
    "        if with_eq:\n",
    "            hr_hrtf *= iSpatFT(custom_eq.swapaxes(0, 1), target_grid).swapaxes(0, 1)\n",
    "\n",
    "        diff = spec_diff(hr_hrtf, target_hrtf, axis=(1, 2))\n",
    "        print(N, diff.mean())\n",
    "        mu, std = diff.mean(0), diff.std(0)\n",
    "        label=f\"order = {N}\"\n",
    "        if with_eq:\n",
    "            label += \", w/ eq\"\n",
    "        else:\n",
    "            label += \", w/o eq\"\n",
    "        plt.plot(freqs, mu, label=label)\n",
    "        plt.fill_between(freqs, mu - std, mu + std, edgecolor='none', alpha=0.3)\n",
    "\n",
    "plt.legend()\n",
    "plt.title(\"Spectral Differences across all subjects\")\n",
    "plt.xscale('log')\n",
    "plt.xlim([200, 18000])\n",
    "plt.ylim([0, 8])\n",
    "plt.ylabel(\"dB\")\n",
    "plt.xlabel(\"frequency (Hz)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x1296 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = subject_hrir[0, :, 0]\n",
    "hrtf = np.fft.rfft(x)\n",
    "Pnm_before = spatFT(hrtf, grid, 35)\n",
    "Pnm_after = spatFT(hrtf / iSpatFT(custom_eq[0, :, 0], grid), grid, 35)\n",
    "\n",
    "fig = plt.figure(figsize=(10, 18))\n",
    "ax = plt.subplot(311)\n",
    "plt.imshow(sh_spec(custom_eq[0, :, 0]), aspect='auto', origin='lower', extent=[0, sr / 2, 0, 35])\n",
    "plt.title(f\"SH spectrum of the rigid sphere model\")\n",
    "plt.ylabel(\"N\")\n",
    "plt.subplot(312, sharex=ax)\n",
    "plt.imshow(sh_spec(Pnm_before), aspect='auto', origin='lower', extent=[0, sr / 2, 0, 35])\n",
    "plt.title(f\"SH spectrum of subject {subject_name[0]}, left ear, before equalization\")\n",
    "plt.ylabel(\"N\")\n",
    "plt.subplot(313, sharex=ax)\n",
    "plt.imshow(sh_spec(Pnm_after), aspect='auto', origin='lower', extent=[0, sr / 2, 0, 35])\n",
    "plt.title(f\"SH spectrum of subject {subject_name[0]}, left ear, after equalization\")\n",
    "plt.ylabel(\"N\")\n",
    "plt.xlabel(\"frequency (Hz)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Phase-Correction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4 4.915667321958767\n",
      "7 4.48408401490741\n",
      "10 4.1064677788115205\n",
      "4 3.7850795105072357\n",
      "7 2.2644712611240703\n",
      "10 1.4910603650980805\n"
     ]
    },
    {
     "data": {
      "image/png": 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TU8NNN91EeXk5jz/+OCtWrODRRx/lD3/4A88/r2rJKoqiKJ9fV1RwdSns2rWLDRs2YLfbAbj99tv7gpKioqK+KbOdO3eyYcMGbDYbAOvXrwfA6XSye/duNm7c2HdNn8/X9/3GjRtjAiuAGTNmcPjw4WH1saGhgVdffZUPP/xw2O9r5cqVbNmyhRMnTjB79mw6OztpbGxkz549PP300wD86U9/YuvWrXR3d9PV1cWqVasA+MY3vhH1fnq9++67nDhxou/nnp4eHA4HO3bs4LXXXgPg1ltvJT09fdj9VBRFUZQrzRUVXA02wjRepJQJX+sNuHrFW9mmaRppaWkJA6WB1+g1kpGrQ4cOUVVVRUlJCQBut5uSkhKqqqoS9j0/P5/Ozk7efvttysrK6Ojo4JVXXiEpKYnk5GTcbjddXV3k5eXR3d2d8DoD3+uePXuwWq0xr6lVf4qiKMrVQuVcDaGsrIzXX38dt9uNy+Vi27ZtrFy5Mm67bdu24fF4cDgcvPnmmwCkpKQwefJkXn31VSAcrB05cmTI+/aOXMX7GjgleOutt9LU1ER1dTXV1dXYbLa+wGrfvn3cc889ce9x7bXXsmXLFsrKyli5ciVPPvlk33v74IMPWL16NQCpqamkp6ezc+dOAH75y1/2jWL1t3btWp555pm+n3sDyrKyMl566SUgPNUYL19LURRFUT4vVHA1hNLSUjZt2sTSpUtZtmwZ9913HwsXLozb7s4772TBggXccccdUQHYSy+9xAsvvMD8+fOZM2cOb7zxxkXrf01NTdyRJAhPDQaDQUpKSigtLaWjo6Ov3/3zrQB+/vOf88gjjzBv3jwOHz7Mo48+GnO9p59+mv379zNv3jxmz57Nc889B8D3v/99duzYQWlpKdu3b6ewsHAc3qmiKIqiXB7EYNNeF9vixYvl/v37o46Vl5cza9asS9SjK98jjzzC3Xffzbx580Z0XmlpKXv37h2XPf2Ki4vZv38/WVlZw2qv/gYURVGUy5EQ4oCUcvHA41dUzpUycj/60Y8u6LyDBw+OcU8URVEU5eqggivloquurr7UXVAURVGUcaNyrhRFURRFUcaQCq4URVEURVHGkAquFEVRFEVRxpAKrhRFURRFUcaQCq7GyWOPPcaTTz550e63cuVKFixYwIIFC8jLy+PLX/7ymFz3gQce6NuAWVEURVGUoanVgmNASomUEp3uwmPVYDCIwXDhv47e6ukAd9xxB1/60pcu+Fr97d27l2effXZMrqUoiqIoVwM1cjUMTz31FHPnzmXu3Lls2bIFCJcTmDVrFps3b6a0tJTa2lqeeOIJZsyYwZo1a6ioqOg7//Tp06xbt45FixaxcuVKTp48CcCmTZt4+OGHWb16Nd/97nfHpK8Oh4P3339/yJGrzZs387vf/Q6ADRs2cO+99wLwwgsv8L3vfQ8IF++cPn06er2ew4cPs3z5cubNm8eGDRvibmHT2trKHXfcwZIlS1iyZEnfiFd7eztr165l4cKFPPDAAxQVFdHW1jYm71dRFEVRLjdX1sjVW/8ITZ+N7TUnXgM3/1vClw8cOMDWrVvZu3cvUkqWLVvGqlWrSE9Pp6Kigq1bt/Lss89y4MABXn75ZQ4dOkQwGKS0tJRFixYBcP/99/Pcc88xbdo09u7dy+bNm3n//fcBOHXqFO+++y56vT7qviPZuLm/bdu2ceONN5KSkjLo2y4rK2Pnzp2sX7+e+vp6GhsbAdi1axd33XUXEL0Fzj333MNPfvITVq1axaOPPsrjjz/eF2j2evDBB3nooYdYsWIFNTU13HTTTZSXl/P444+zYsUKHn30Uf7whz/w/PPPD9o3RVEURbmSXVnB1SWwa9cuNmzYgN1uB+D222/vC0qKiopYvnw5EJ6W27BhAzabDYD169cD4HQ62b17Nxs3buy7ps/n6/t+48aNMYEVnN+4eaR+/etfc9999w3ZbuXKlWzZsoUTJ04we/ZsOjs7aWxsZM+ePTz99NMA/OlPf2Lr1q10d3fT1dXVt1nzN77xjaj30+vdd9/lxIkTfT/39PTgcDjYsWMHr732GhDeZDo9PX3E70tRFEVRrhRXVnA1yAjTeBls78XegKuXECKmjaZppKWlJQyUBl6j14WMXLW3t7Nv3z62bduWsM+98vPz6ezs5O2336asrIyOjg5eeeUVkpKSSE5Oxu1209XVRV5eHt3d3UNeD8Lvdc+ePXE3io73bBRFURTl80jlXA2hrKyM119/HbfbjcvlYtu2baxcuTJuu23btuHxeHA4HLz55psApKSkMHnyZF599VUgHKwdOXJkyPv2jlzF+0o0Jfjqq69y2223YbFY+o7t27ePe+65J277a6+9li1btlBWVsbKlSt58skn+97bBx98wOrVqwFITU0lPT29L2n+l7/8Zd8oVn9r167lmWee6fu5N6AsKyvjpZdeAsJTjfHytRRFURTl80IFV0MoLS1l06ZNLF26lGXLlnHfffexcOHCuO3uvPNOFixYwB133BEVgL300ku88MILzJ8/nzlz5vDGG2+MS19ffvllvva1r0Udq6mpiTuSBOGpwWAwSElJCaWlpXR0dPT1u3++FcDPf/5zHnnkEebNm8fhw4d59NFHY6739NNPs3//fubNm8fs2bN57rnnAPj+97/Pjh07KC0tZfv27RQWFo7VW1YURVGUy44YbNrrYlu8eLHcv39/1LHy8nJmzZp1iXp05XvkkUe4++67mTdv3ojOKy0tZe/evRiNxjHvU3FxMfv37ycrK2tY7dXfgKIoinI5EkIckFIuHnj8ysq5UkbsRz/60QWdd/DgwTHuiaIoiqJcHVRwpVx01dXVl7oLiqIoijJuVHClKIqiKIoyiJp2N+c6XNjNBkx6HTohSLEmDqFUcKUoiqIoipJAl9vPqWYHAL6Av+94Q1fic8ZttaAQYoYQ4nC/rx4hxN+N1/0URVEURVHG2ulWF0gt/DVM4zZyJaWsABYACCH0QD0wdHVLRVEURVGUy0C3y0Og7jBZniakMOBOLsZjnwRDFMa+WHWubgROSynPXaT7XXKPPfYYTz755EW73zPPPENJSQlCiKhNkaWUfPvb36akpIR58+aN2SrAPXv28M1vfnNMrqUoiqIol6P2mnIsniYAhAxi76kitf0g+oBz0PMuVnB1F/Dri3Svi05KiaYNf7gwnmAwOKrzr7/+et59912Kioqijr/11ltUVlZSWVnJ888/z9/8zd+M6j693n777agio4qiKIryeaL5PTibqmKOG/3dpLd+itndlPDccQ+uhBAmYD3waoLX7xdC7BdC7G9tbR3v7lyQp556irlz5zJ37ly2bNkChMsJzJo1i82bN1NaWkptbS1PPPEEM2bMYM2aNVRUVPSdf/r0adatW8eiRYtYuXIlJ0+eBGDTpk08/PDDrF69mu9+97uj6uPChQspLi6OOf7GG29wzz33IIRg+fLldHV10djYmPA6+/bt4/bbb+8712q14vf78Xq9TJkypa/de++9x5o1a/B6vfzlX/4l11xzDQsXLuSDDz6Ie90f/ehHLFmyhHnz5vH973+/73j/Z/a1r33too72KYqiKEoinWcPooVCCV6VJHeVJzz3YqwWvBk4KKVsjveilPJ54HkIV2gf7EL/777/l5MdJ8e0czMzZvLdpYkDmwMHDrB161b27t2LlJJly5axatUq0tPTqaioYOvWrTz77LMcOHCAl19+mUOHDhEMBiktLWXRokUA3H///Tz33HNMmzaNvXv3snnzZt5//30ATp06xbvvvoter4+674Vs3BxPfX09kyZN6vu5oKCA+vp6cnNz47YvLS3l0KFDAOzcuZO5c+fy6aefEgwGWbZsGQBtbW0YjUZSU1P58Y9/DMBnn33GyZMnWbt2LadOnYra33D79u1UVlayb98+pJSsX7+eHTt2YLfbEz4zRVEURblk2qroam0YolHikOViBFdf4wqeEty1axcbNmzAbrcDcPvtt7Nz507Wr19PUVERy5cvB8KByIYNG7DZbACsX78eAKfTye7du9m4cWPfNX0+X9/3GzdujAms4PzGzaMVb3sjMUginsFgoKSkhPLycvbt28fDDz/Mjh07CIVCffsObt++nbVr1wLh5/Otb30LgJkzZ1JUVMSpU6eittvZvn0727dv79uT0el0UllZicPhiPvMFEVRFOWS8TnwtVTi8F54us64BldCCBvwReCBsbjeYCNM42WwvRd7A65e8YIWTdNIS0tLGCgNvEavsRq5KigooLa2tu/nuro68vLyBj1n5cqVvPXWWxiNRtasWcOmTZsIhUJ9U3ZvvfUWDz/8MDD48+klpeSf/umfeOCB6D+DLVu2DBroKYqiKMpF13ycDqdn6HaD5FqPa86VlNItpcyUUnaP533GU1lZGa+//jputxuXy8W2bdv6RnAGttu2bRsejweHw8Gbb74JQEpKCpMnT+bVV8MpZ1JKjhw5MuR9e0eu4n0NN7CC8GjQL37xC6SUfPLJJ6SmpvZNCd54443U19fHfS9btmzh2muvJTs7m/b2dk6ePMmcOXOQUnL06FEWLFjQ1/all14CwlOcNTU1zJgxI+p6N910Ey+++CJOZ3h1RX19PS0tLQmfmaIoiqJcEt11aK4O2p3+wdt5fIjKxAUQVIX2IZSWlrJp0yaWLl0KwH333cfChQtj9scrLS3lzjvvZMGCBRQVFUUFYC+99BJ/8zd/ww9+8AMCgQB33XUX8+fPH9N+Pv300/zwhz+kqamJefPmccstt/Bf//Vf3HLLLfzxj3+kpKQEm83G1q1bgfCIWlVVFRkZGTHXWrZsGc3NzZSVlQEwb948cnJyEEKwf/9+Fi5c2DfitHnzZv76r/+aa665BoPBwM9+9jPMZnPU9dauXUt5eTnXXnstAElJSfzqV78a9JkpiqIoykUVCkBrBZ2eAEFtkFkZhwtdTcOgI1diONM6F8vixYvl/v37o46Vl5cza9asS9Sjz69jx47x4osv8tRTT43ovB/84AeUlJRw1113jXmfHnvsMZKSkvjOd74TdVz9DSiKoijjrvEI9DRwssmBN5BglaDHh+5MTV9gNf/hxw9IKRcPbKZGrq5Sc+fOHXFgBfC9731vHHqjKIqiKJdQdz30NNDtCSQOrIIhxLn6QUeseqngSrlsPPbYY5e6C4qiKMrVJhSE1nDNquYeb8Jmoq4JEQgM65IXq0K7oiiKoijK5afjDIQCdHn8uP0JRq26HQjH4Fve9KeCK0VRFEVRrk4BL3RWo2mSxq4Eo1aahmgc2Q4yKrhSFEVRFOXq1HEGZIh2lx9fMH4ulWjrRAQCaBIGW0TYn8q5UhRFURTl6hPwQnctmiZpcSQYtQqGEK0dbHNN5BfOfDQEBXovs0xOZhoTTxOqkatx8thjj12STYi/9a1vkZSUNGbXe+CBB/j444/H7HqKoiiKclnoqgGp0ekJEAglGJLqdvC2M5OtzkksNPWw0d5Ijt7Hbm86T/dMTnhpNXI1BqSUSCnR6S48Vg0GgxgMo/t17N+/n66urlFdY6C9e/fy7LPPjuk1FUVRFOWS0jTorkFKScsgKwSd7S5+7pzGfFM3/7+0SvSRHds0CXUhC3+W4Dw1cjUMTz31FHPnzmXu3Lls2bIFgOrqambNmsXmzZspLS2ltraWJ554ghkzZrBmzRoqKir6zj99+jTr1q1j0aJFrFy5kpMnTwKwadMmHn74YVavXs13vzu6fRNDoRCPPPIIP/zhD4fVfvPmzfzud78DYMOGDdx7770AvPDCC321rMrLy5k+fXrMxtKtra3ccccdLFmyhCVLlvSNbLW3t7N27VoWLlzIAw88QFFREW1tbaN6X4qiKIoy5hwNEArQ4Q4kzLXCH+B/2tJIkV38vXUvBs6XYdAJKDQkDsquqJGrpn/5F3zlJ8f0muZZM5n4v/5XwtcPHDjA1q1b2bt3L1JKli1bxqpVq0hPT6eiooKtW7fy7LPPcuDAAV5++WUOHTpEMBiktLSURYsWAXD//ffz3HPPMW3aNPbu3cvmzZt5//33gfB+fO+++25MADPSjZufeeYZ1q9f37dv4FDKysrYuXMn69evp76+nsbGRgB27drVV339rbfeYt26dTHnPvjggzz00EOsWLGCmpoabrrpJsrLy3n88cdZsWIFjz76KH/4wx94/vnnh9UXRVEURbmouuvQNElzd+IAydXaya2B1/l3y0HwQchnpNZ2Ez3GaUNe/ooKri6FXbt2sWHDBux2OwC33357X1BSVFTE8uXLAdi5cycbNmzAZrMB4Q2TAZxOJ7t372bjxo191/T5fH3fb9y4MSawgvMbNw9HQ0MDr776Kh9++OGw39fKlSvZsmULJ06cYPbs2XR2dtLY2MiePXt4+umnAfjTn/7Utxdhf++++y4nTpzo+7mnpweHw8GOHTt47bXXALj11ltJT08fdn8URVEU5aIIeMDTSYvDiz8Uf9RKH3SRV/1zCnVnqDBcj9mUQbZvP8Xu31Nn+QId5sH3B76igqvBRpjGy2B7L/YGXL16NzPuT9M00tLSEgZKA6/RayQjV4cOHaKqqoqSkhIA3G43JSUlVFVVJex7fn4+nZ2dvP3225SVldHR0cErr7xCUlISycnJuN1uurq6yMvLi/ue9uzZg9VqjXkt3jNQFEVRlMtGTwOeQIhmhy/uy2Z3I1OO/QSd1s3/lZtYY0/DBzgMxRS5/0CB932kMNBpmpPwFirnaghlZWW8/vrruN1uXC4X27ZtY+XKlXHbbdu2DY/Hg8Ph4M033wQgJSWFyZMn8+qrrwLhYO3IkSND3rd35Cre18ApwVtvvZWmpiaqq6uprq7GZrP1BVb79u3jnnvuiXuPa6+9li1btlBWVsbKlSt58skn+97bBx98wOrVq+Oet3btWp555pm+n3sDx7KyMl566SUgPKXY2dk55PtUFEVRlItJ9jRQ2+km3tiJPuBgyvFnCAYCbPR/n3Rb4fnzhIFztttw6CeR73kfc6gj4T1UcDWE0tJSNm3axNKlS1m2bBn33XcfCxcujNvuzjvvZMGCBdxxxx1RAdhLL73ECy+8wPz585kzZw5vvPHGRet/TU1N3BEmCE8NBoNBSkpKKC0tpaOjo6/fifKtAJ5++mn279/PvHnzmD17Ns899xwA3//+99mxYwelpaVs376dwsLCuOcriqIoyiXhd9HS1obbF3+bm6JTP8MY6OGR4Ldo1+VTauqJel0KPbW2dWjCwCTP2wlvIwab9rrYFi9eLPfv3x91rLy8nFmzZl2iHl35HnnkEe6++27mzZs3ovNKS0vZu3cvRqPxgu9dXFzM/v37ycrKuuBrgPobUBRFUcZGR205tacOxx21Su74jKkn/oODGV/m9oavsjm5mnW2+NvepPlPUuh5C/F4zwEp5eKBr19ROVfKyP3oRz+6oPMOHjw4xj1RFEVRlEunucdL/dkqdPHGlLQQ+Wd/i9c6gae6biRJBFltbU94rS7jDNIC5cDRuK+raUFl3FRXV4961EpRFEVRRkNKSVWLg+PVjej88besyWr8EIunmRPZX2K3O4ObrK2YRYL6VwBC0Gy5LuHLauRKURRFUZTPJY8/xGf13fR4Alg9LXHb6ANOJtb8gZ60Wfyi5RoAbrU1D31t/YSEr6mRK0VRFEVRPnc6XX72VXfQ4wlXVrd4muK2m1jzJvqQh6rc2/lTdxorLB1k6QNx20bREo9sqZErRVEURVGuOD3eAHUdHtpdPrKTzUxItmA3G/AGQ9R3emjo8vQlruv9DvRBd8w1LK4Gshp30pZbxrb6CXikntttjcO6v27fZwlfU8GVoiiKoihXDE2THGvopqXnfBHQug4PdR2ehOdYPHGm+aQk7+xvCekt1E64hd/vS2WhqZspxsTX6SXqmtAfSbwdnwquxsljjz1GUlIS3/nOdy7K/VauXInD4QCgpaWFpUuX8vrrr4/6ug888AD33HMP119//aivpSiKoowfTWo0uhpxB9x4gh58IR+BUICQDCGEQIcOg86ASW8i1ZxKljWLZFPype72iIQ0yZG6Ljqc/uGfJDXMcaYEUzqPkdJ1gvrJG3mv1kqnZuTh4Yxaudzo3/8EmZaSsIkKrsaAlBIpJTrdhaewBYNBDIYL/3Xs3Lmz7/s77riDL33pSxd8rf727t3Ls88+OybXUhRFUcaHlJLyjnJa3fHrMhGZHvNrftxBN12+Ls71nMOkN5FpySQ/KZ8kU9LF6/AFaHF4OdXkxBuIXwA0EbOnBZ02IBiTIfIipReaJt7AtkorUw0u5pkcg18spKF/ZzcEQgT/7DrYuy9uM5XQPgxPPfUUc+fOZe7cuWzZsgUIlxmYNWsWmzdvprS0lNraWp544glmzJjBmjVrqKio6Dv/9OnTrFu3jkWLFrFy5UpOngwPJW7atImHH36Y1atX893vfndM+upwOHj//ff58pe/PGi7zZs387vf/Q6ADRs2cO+99wLwwgsv8L3vfQ8IF++cPn16zMbSra2t3HHHHSxZsoQlS5bw8ccfA9De3s7atWtZuHAhDzzwAEVFRbS1tY3J+1IURVESq+isSBxYDcIf8tPoauRgy0GaXPETvi81byDEkdoujtZ2jziwArC6amOOpbUewOJpprHoy+yqFTQELdxub2Ko7XF1nxxG19xOaNUSSE9N2O6KGrna+cop2mrj16i4UFmTklj51ekJXz9w4ABbt25l7969SClZtmwZq1atIj09nYqKCrZu3cqzzz7LgQMHePnllzl06BDBYJDS0lIWLVoEwP33389zzz3HtGnT2Lt3L5s3b+b9998H4NSpU7z77rsxAcxINm7ub9u2bdx4442kpCQeroTwPoA7d+5k/fr11NfX09gYHgrdtWsXd911F5B4C5wHH3yQhx56iBUrVlBTU8NNN91EeXk5jz/+OCtWrODRRx/lD3/4A88///ygfVAURVFGr6KjYtSBkSY1TnacpNvXzZTUKRj1F747x1jRNMmZNhc1Ha7BFuYNyuDrwhAYMBolNSbUvYXHlkdT6nx+fiyJqQYX15kT7xUIkFRbj+9YJfoFM9GmFxHSEu9wc0UFV5fCrl272LBhA3a7HYDbb7+9LygpKipi+fLlQHhabsOGDdhsNgDWr18PgNPpZPfu3WzcuLHvmj7f+SS8jRs3xgRWcH7j5pH69a9/zX333Tdku5UrV7JlyxZOnDjB7Nmz6ezspLGxkT179vD0008D8Kc//YmtW7fGnPvuu+9y4sSJvp97enpwOBzs2LGD1157DQhvJp2enj7i/iuKoijDV9FRQaNreKvbhqPR1Uirp5XilGLykvLQiUszwRUIaRyt66LTNYySCIOwuWpijqV0HMXqbqR6xl/xm7MWOoIG/jH9FPpBRq1sbjf+dz7BVDCB7HXXIvQ6gqHPSSmGwUaYxstgey/2Bly9RJzxRE3TSEtLSxgoDbxGrwsZuWpvb2ffvn1s27YtYZ975efn09nZydtvv01ZWRkdHR288sorJCUlkZycjNvtpquri7y8vLjvac+ePXE3hI73DBRFUZSxN9aBVa+gFqSqq4oaRw2TkieRn5R/UYOskCY5VNPVV5/qQumCbkze2C1sshs/xG9OZ7d+CW/UmFlrbWWmyZXwOnoB4qNPEQY9mbevRuh1SCnp0hLPpKmcqyGUlZXx+uuv43a7cblcbNu2jZUrV8Ztt23bNjweDw6HgzfffBOAlJQUJk+ezKuvvgqEg7UjR44Med/ekat4X4mmBF999VVuu+02LBZL37F9+/Zxzz33xG1/7bXXsmXLFsrKyli5ciVPPvlk33v74IMPWL16ddzz1q5dyzPPPNP3c2/gWFZWxksvvQSEpxQ7OzuHfJ+KoijKyDW7msclsOrPH/Jzuus0+5v20+XtGtd79XeioWfUgRWAzXmOvkz+CLO7ieSuk9Rnl/HvJ5KYYAhwb1Ls6FZ/9pp6/DVNpNywGH2yHSkltb52Gn1dCc9RwdUQSktL2bRpE0uXLmXZsmXcd999LFy4MG67O++8kwULFnDHHXdEBWAvvfQSL7zwAvPnz2fOnDm88cYb49LXl19+ma997WtRx2pqauKOMEF4ajAYDFJSUkJpaSkdHR19/U6UbwXw9NNPs3//fubNm8fs2bN57rnnAPj+97/Pjh07KC0tZfv27RQWFo7hu1MURVEAAlqA092nL9r93EE3R1qP0OwaekuY0apoctDc4x31dXRBL2Z3bB5aVuNHaMLAP7d9kU6f4O9TqrDpEk/vGYMhfB8dwJiXjX3hDEJS45y3je44BUn7E4NNe11sixcvlvv37486Vl5ezqxZsy5Rj658jzzyCHfffTfz5s0b0XmlpaXs3bsXo/HCkxqLi4vZv3//qDdvVn8DiqIo51V2VlLvrL/o9xUIZmXOIseWMy7Xr2hyUNsxeNAyXEld5Vjc0SN7upCXOfv+kYOGBWzs/jbfymvmi6HYUSuJwG/JImhIJmffLvy7dpH20Gbcdi8djnoC8vyKxes3/+SAlHLxwGuMa86VECIN+C9gLuGxuXullHvG855KtB/96EcXdN7BgwfHuCeKoijKaDn8DhqcDZfk3hJJeXs5QS1IXlJsPu4FX1dKyhsdNHQNXRl9OHRBT9xRq/SWfehDXv7VvY7bCnx8MVQX2xehw5U0Gc2YRHLAjX/3bgKLZnM2TQNpBIMJAkP3c7wT2v8v8LaU8itCCBNgG+f7KZeR6urqS90FRVGUz5XKzkokl27GSSI51XkKb9DLlLQpo75evK1sRsvuOIsY+IykxFr7Ece0YkJpk/nLjHpojp0O9FonohnDxVTNB3eiaSHcK+aHXxQCkiZCdy1owUH7MG45V0KIFKAMeAFASumXUnaN1/0URVEU5fOsydVEj7/nUncDgBpHDVWdVaO6RiCkcbCmc0wDK33AiXnAPoL+EOw4cY4sfz3vmW7kn+a5MLTHLrgK6m0ELNkEND8uby2hPZ8QmDUZLaNfsVCdHpImDNmP8Ry5mgK0AluFEPOBA8CDUsqo9Y5CiPuB+wGVAK0oiqIocQS1IGe6z4zonJAWotXTSru3HYfPQbe/G4ffgcPvIN2SzqTkSZSklZBqTlxpfDB1zjp0QndBI1iaJjlS20WXe/SrAvuz95ym/wrBBreOHx218ve+D3EZ7FxbOh9TdzciGDvy5LNOpMffTlegleKTVeg8PrzXLYi9idEa/hpkenA8gysDUAp8S0q5Vwjxf4F/BP65fyMp5fPA8xBOaB/H/iiKoijKFammpwZ/aOjNiqWUHGs7xtvVb1PvrCcko7eLsRqs2I12jrYeJSiD6ISO+dnzWT1pNZNTJ4+8X44a9Do9RSlFIzrvZJNjzAMro68Tk+98XasdTQaeLbeSq+vgFv2ntOWuxqQ3IFpjK7E7hZ6GUAc+zYNRSFI+PUawYAKhwonxb2ZJu2TBVR1QJ6XcG/n5t4SDK0VRFEVRhskT9FDnjE2+HqjV3cpvKn5DRWcFObYcVk9aTa49lyxbFimmFFJMKZj0JiA8qtXgauDTpk/5pPETDrUcYn72fL409Utk27JH1L+z3Wcx6AzkJ+UPq31Dl2dUyetSSlqdPhzeIEJAqsVIht2Erec0nT7BZ516/lRn4niXgZmpQf4j4210jSHacssQLW0xo1ZOzUut0URQC/cpt7YRfWcPzrXLE3fCZIfIs4xn3IIrKWWTEKJWCDFDSlkB3AicGOq8z4vHHnuMpKQkvvOd71yU+z3zzDNs2bKF06dP09ra2lf+QErJgw8+yB//+EdsNhs/+9nPKC0tHfX99uzZw4svvshPf/rTUV9LURRFSazOUYcmB99cr8HZwE8O/YSQDPGVaV9hRf4K9LrYrdV66XV6JiVPYlLyJG6dcisf1HzAOzXvcKztGGUFZawrXofNOPw1aJWdlYS0EIUpg6f3eAMhTjU7Bm0zmIYuD7/ZX8vxhujcs0ybATMhGtzJ4Z/NGvdO93JrrpOiAx/RnTEPv0xB1xZdeqEr5KJVegkawlOjegGpn35GKD2ZwKwhRvIsibd4G+/Vgt8CXoqsFDwD/OU43++SkFIipUSnu/D1AcFgEIPhwn8d119/Pbfddhs33HBD1PG33nqLyspKKisr2bt3L3/zN3/D3r17419kBN5+++2ERUYVRVGuagEP9AZDQgd6M1zg50NACwy5KXOto5b/OPwfGHVGHlr40IjrUJn1ZtZNXse1edfy+zO/58PaD9nXtI+bJ9/MirzBg7T+znSfwRP0MCVtCkZd/BqJJxp7CIZGngEkpeTDilZ+s78Wk0HHHaX5FKTb0KSk3emnqqYWGdT4Yl6AOelBpiZr6HWQ2fgJhqCTlolfQNQ20JuP5deCtGk9eDQfAev5BPWs9g6Mtc24b7l+6N+ZOSnhS+MaXEkpDwMxxbWuNE899RQvvvgiAPfddx9/93d/R3V1NTfffDOrV69mz549vP766/zqV7/iF7/4BZMmTSI7O5tFixYBcPr0af72b/+W1tZWbDYbP/3pT5k5cyabNm0iIyODQ4cOUVpayo9//OML7mO8qvEAb7zxBvfccw9CCJYvX05XVxeNjY3k5ubGbb9v3z7+7d/+jddee4033niDu+66i+7ubjRNY/bs2Zw5E06ofO+993j44Ydjzv/Rj37EK6+8gs/nY8OGDTz++OMAPPHEEzHP5mKN6imKooy7UAB6GqC7DnxxVvTpjGAwh6eS9Ibwz/0JEQ7ETEmQVhj+mfAKwYF5U/21uFt45tAzWAwWvrXwW2RZL7xoc6o5la/P+jqrClbxWuVr/PbUb9lZt5O7Z9897JyqRlcjze5mCpILmJwyOWq/2YYuDx3OofPGBnL7g/x89zkO1HQyNz+Fe6+bTIr1/PPTB5x8NaU79kSpkd3wHu6kQtzdSQi/CymhS3PSGXIggZDeSshwfheTzIMn0CwmfAsHL1ztkj62B48mfP2K2rj5g589T8u5ka2WGEpO0RRWb7o/4esHDhxg69at7N27Fykly5YtY9WqVaSnp1NRUcHWrVt59tlnOXDgAC+//DKHDh0iGAxSWlraF1zdf//9PPfcc0ybNo29e/eyefNm3n//fQBOnTrFu+++i14f/X8GF7Jxczz19fVMmjSp7+eCggLq6+sTBlelpaUcOnQIgJ07dzJ37lw+/fRTgsEgy5YtA6CtrQ2j0UhqavQKk+3bt1NZWcm+ffuQUrJ+/Xp27NiB3W5P+GwURVGueJ3V0HoKBgmC0ALgH2YCd089TJiLNCdT50ica+UL+vjpZz9FCDHqwKq/guQCvrXwWxxrO8ZvK3/L04ee5pvXfJOZGTOHdb4mNWp6anD6nczOnI1BZ8Af1KhsSbzRcSJn2pw8v+MMna4AXyktYO2cCej6BWwAVmf8vQFT249g8TRTnXcXwunCrwVpCXXhk+d/D35LZt/3SX4f5pPV+JbNBXP8kTcpJQdCZ3g5sBsnibfpuaKCq0th165dbNiwAbvdDsDtt9/Ozp07Wb9+PUVFRSxfHk5427lzJxs2bMBmC89Rr1+/HgCn08nu3bvZuHFj3zV9vvM1PTZu3BgTWMH5jZtHK972RmLAH2Z/BoOBkpISysvL2bdvHw8//DA7duwgFAr17Tu4fft21q5dG3Pu9u3b2b59e98omtPppLKyEofDEffZKIqiXNGCfmj6DFwtY3tdbzec201bUiY+LX4NKCklL518iWZXM3+74G/HLLDqJYTgmuxrKEwp5NnDz/Lckee475r7mJs1d9jX6PB2cLz9OPOz53Oq2UEgOHjeWH+alLxzopnXDtaTajPyD+tmMDU7dhpOF/TG1LUCQEpy6rfjM2fS45pIQIZoCLYT4nwfAqY0pO58GDSh4gxC0/AtmR23T2e1Fn4b2EuV1kShyOJB0y3cxbG4ba+o4GqwEabxMtjei70BV694QYumaaSlpSUMlAZeo9dYjVwVFBRQW1vb93NdXR15eYNvW7By5UreeustjEYja9asYdOmTYRCIZ588kkgnMcVb0pQSsk//dM/8cADD0Qd37Jly6ABnaIoyhXH2QpNR2EY5REujKSucT8YzZBWHJP/82HdhxxqOcSXpn6JGRkzxqkP4anCB0sf5JnDz/Cz4z/jO4u/w0R7gvIEcXR6O9lbU4nDmTLsczpcfl78+CwnmxwsLExj07XF2M3xwxWr81xsNXbA3lOF3XGWuvSbCYQkjQMCKyn0BIzn+2QQkHToJIHJeWhZ0YnqndLJ/wT28WnoNMlY+bpxBdfrZ6AXiXOyxq1C++dFWVkZr7/+Om63G5fLxbZt2/pGcAa227ZtGx6PB4fDwZtvvglASkoKkydP5tVXXwXCAciRI0eGvG/vyFW8r+EGVhAeJfrFL36BlJJPPvmE1NTUvinBG2+8kfr62M0/y8rK2LJlC9deey3Z2dm0t7dz8uRJ5syZg5SSo0ePsmDBgpjzbrrpJl588UWczvDQb319PS0tLQmfjaIoyhVHC0HzcajfP46BFfQEPXQH3eDphNaK8ChZRJunjTdPv8ncrLncWHjjuPWhl81o45vXfBOjzshPP/spnuDwyyg4PAH21p/AG3IN2VZKyafVHTz25nHOtLm459oiNq+amjCw0oV8WNzx91nMqfsTQYOdlkARDYHWqM2WAfzm9KiAdUJjM/ouB77Fc6LanQ4184T3dQ6HqrnFsJAfWL5KmWHWoIEVqOBqSKWlpWzatImlS5eybNky7rvvvrjJ46Wlpdx5550sWLCAO+64IyoAe+mll3jhhReYP38+c+bM4Y033hjzfj799NMUFBRQV1fHvHnzuO+++wC45ZZbmDJlCiUlJXzzm9/k2WefBcIjalVVVWRkZMRca9myZTQ3N1NWVgbAvHnzmDdvHkIIDhw4wMKFC+OORK1du5Y///M/59prr+Waa67hK1/5Cg6HY9BnoyiKcsXw9sC53dAVP8dnLNX7+hW6DLqhtRx8DqSUvHrqVXRCx1enf/WizQqkW9K5d+69tHna+PnxnxPSBskvi9A0SV2XB01KalwVBLXEOWf1nR5+/M4p/nPHGXKSzXz/ttmUTcse9P3Zek7HHbWyuOpJ7TxGs7WU+lAPQaKnIzWdiZDx/BSj3aQn/WgFmt0SVX7hrNbCFv8fsQoj3zPfzpeMi7GIfrWtTPHzsgDEYNNeF9vixYvl/v37o46Vl5cza9bgWfvKyB07dowXX3yRp556akTn/eAHP6CkpIS77rrrgu890hpg6m9AUZRLrqsWWk6cL7EwjvxakE+6K9FiAgfBoVAPL1b9D3dMu4MbJt0w7n0ZaGfdTl459Qor81eycfrGQYOfNoePun7FQm36ZIqTZqPrN+ojpeSDilZe2V+Lxahn/fw8yqZnYRiiDII+4CS99VOIE1wVVmwltf0Q201/hlfEBkBe60Q0gwUAi0FHLkHStryE77oFeCKFQ0+FGnnO/w42YeYR85+RKmJrfoWKcylb9tUDUsqYqghXVM6VMnbmzp074sAK4Hvf+9449EZRFOUypWnhoKq7dui2Y6TB1xknsAJPyMdvz/6RSdYcyvJWXLT+9LeyYCXt3nbeq3mPHFtOwgBP0yTNPdGr6dwhB42eM+TbSvqO/e5IA28ebeSa/FTuvb6YZEvi0aD+bI5q4gVWwttCWtunVFpn4pWx1woZrFGB1YRUC5YP9yM0iW/xbEJS40/BI7wZPEC2SOFbpnVxAytMRkI5mbHHI1RwpVx0jz322KXugqIoytCCPqg/CN6ukZ+raeBsCte+CnrD+VlaEMwpYMsAawZY00AX/TGsSY0GX2fcS37QeZyekIf7s29E11YB6ZPBNPwq6r30IrxCfbD6WYNZP3U9Le4WtlVtoyilKO6ehM0OLwEtNvjp9Ldi0lnJtuRz4Fwnbx5t5LqpmWy6rjimxEIiIuTH5G2NOhaUIdpD3UyqeQMknAlNjZv45DeFk9XNkcBKp0nMB8oJlEyiO93I/+f/Pae1ZhbpJ/MXxpXYhDluH4JFuaBPPLqmgitFURRFGSgUgLpPwTeCrVq0EJz9CE6/F55GHDLhXYAlFezZULAEilfQotfhl8GYlu6Qjw86TzA/qYgia1Y4YGs9CfYcSMmFQaqom/Vmkk3JpJhSSLOkkWxMRghBSAvR6mnlTPeZYW0K3UsndPzFrL/gh5/+kK3HtvLdpd/Fbjy/8t3tD9LqiF9CAqDZW0OHK8CLH3cwJcvO3cuLhh1YAZg9zfg0Hx2hHtzSR1CG8Gg+jEEPX2g7yjnbFLwydiV+0JCE1JuwGvXkpJjRCYGxshpdj4vGm0v5oe93dEoX9xm/wBLD1IT3l6lJaFlpg/bxigiupJRqKf9V6nLKCVQU5SqhhaD+wPADKynD7Y/8OlwANL0YStaEK62nFoDRFq7MrjOEq7e728OrAN3t4O6A7ho48t9w9NdYs2dgnnUTPmt0keb3O4/j1QLcnDm//43B1QyeDkieCLasvhVw6ZZ0JtomkmZJw6yPP/qi1+mZaJ9ItjWbZnczLe4Wun3dyDjTbQPZjDbunXsv/37g39l6bCt/M/9v0Ov0aJqkpt1DnEGrKK8daEGTOh4om4JxkBGguJzVnPLXEhyQ/zaj7TOMWoDTclrc0wLmNGwmPROSzX0V8M2fniCQbOWxooOEpOAh061M1U+Iez4AOkFg8tAbVF/2wZXFYqG9vZ3MzEwVYF1lpJS0t7djsVgudVcURblaaFp4KtATf2ouht8FnzwbDq6Sc2HFw+FRqESfV9a0cNA1UE8DwbMfYq94m8W7/5OT13yJ9pxw/SpXyMtHneUsSCoi3xK7whstEM4JczRB2iSyM6YzO3P2sD8z9To9eUl55CXl4Qv5qHfUU++sH3LasDClkDtn3slL5S/x6qlX2Tjtq9R2evAGBz/vXIvgdJOO62aGcHGWdDk9Ksl9MNLbwTlPZUxgJaTGrJbDNFrycZAac17QYMdmMZPdL7DSdfZgqKzh99eb0BlMfMd0Kzm62HP7CxVOBGv8YLW/yz646i0v0NraOnRj5XPHYrFQUFBwqbuhKMrVovkzcLcNr21XLez8MbhaYeHdMH3doNNzg0rJo2nGOuozC5l95H+45uBvqC1axpkZX+S9juP4tAA3Zy0Y/BpagCxHK7OSpyKkBmLkfTHrzUxJm8Kk5EmUd5TT4Q2XhPAHNdz+IJ5ACL0QmI167GY9y3OX0+Ju4Z1z7yBDNmallA16/ZAGHx3Tk2qTlE7V6Al2Uus6xST70AFWUAvQ0rEzbkmHoq4qkgIOjpgWMaDyAjoBGVkTsFoH/I/6gc+QAj6Yr+PbpnVDBlZaVhqh3OxB2/S67IMro9HI5MmxyXKKoiiKMqYckQT04aj5BPb+f2Cwwo2PQvboq6S3Bnrw2DM4uPwvmXryHSad2wuuNnamSBYkF5NnTh/0/AmmVGbYctH11IenHwuWgsE06DmJGPVG5mXP42BDJQcbTuL0x45GCcBq0jPdtoqzyS3sbn4Hp9/L4swvJhw1O3JWR4dTsH5pEEMk9nMEO6lxnWSSfUZfsv1AQS3AuZ6jGD1NcV+f3XIQhzGFllBOuGMRZoOOlNR0dFZrVPsev4OMA8c4PFXHXdnryNPFGRHsz2wiOCV6OnCwYPCyD64URVEUZdyFAuHK68Nx+gPY9zxklcD1D4VX/42STwvQE3QDIHUGqmbfjCs5h89qPsIrM1hrnTTo+YWWTKZY++UK+RxQuxcmLbugAMsbCHGyyUGHIwWzyMFJY0wbCbgjQVfZhNsx6Mwc7dyJJ+RiRc56dAMCJZcXPqnQUZyjMWVidFKWM9hNVc9hJliLSDVGpwH5Q17OuU6C+3zxVp2gL68rw93MRGc9h5KWQCgc8Jj0AovJgNWoA1t0UFoVaqJy71v8uUtDXLeUafrcIZ9HYGoBRPYBthqs5NhyyLUnPk8FV4qiKIrSUj687WxOvx8OrCbOh5V/f8EjQwO1+h0xaeSNkxbxK381Uzyd3HHk9xxZeg9eW+zo1STzgMCql98ZDrAKFoPRGvt6HL5giHPtbuo63WiR6bWJliJ8ITfOYHfC84TQcV32bVj1Ng51fIgr2M2NE+/CpD8/FberXE9Ig1Vz4+dkBaSfOnclLboaUo2Z6IQeb8hDT6AdKUMk+9pJtxlJtRoQQuANaHR7A8ypPkRAZ6Q+NAm7WY/NqEeniwRnRhsYwjlSUkreCx3jd55P+MmeEK7CbIqnlg75TLTsdGRqElaDlcmpk8m2Dl45HtT2N4qiKMrVztUWXuU3lKp3w4FV7gIoG7vACsJTggPVezs4HXSwLHMOhpCfBft+gcUdnWhv05mYbB0kD8jvhOqPoSd25AnCAUeLw8vRui52V7Wxq7KNmvbzgRWAEIIC2zQMcaqd9yeEoDTzRlbmbKDRfZY/1P0XrkA4IGvoEJTX6lg4RSM9adDL4Nd8tPoaaPbW0h1oQyIx+7vIsRtIt5vQ6XQIIbCa9Ewyh5jacZJG+zRS7EkkmQ3nAysILyAAAjLETwPv82rgE+45nEaaU6KtXp544UEvvY5g4UQm2CawZOIScmw5w1oooIIrRVEU5eqlhaD52NDtqj+GT/8L8haGR6z0YxdY9Z8S7G939ykMQsf8nIUcWfIX6OMEWDPseUOvtNMC0HgYGg6HC6NGtPR42X26naO13bT0+HD7QySqfmPQGcm1Di//eXpqKTfl3Y0j2MXv6p6nx9/Nh5/psFskS6ePfPsgnQ4KzU6SLbGTbXm1B9DJEG2m6Rj0A4IevRmMNoIyxH/63+VA6Ax3Bkq5cZeDwNRJBKcOvVgqWJxHRsoEZmXOGvaKRlDBlaIoinI1az8NAc/QbfY9B9mzwqUW9MPboiVMgCkpXKYhsyRc98qaDrrz14g3JejXgnzac4YFScXY9RacKbmRAMvXF2DlmdNJNYygQrujEc7uJNBezbHado7WdeOJk6ieSKopk1Rj4i1f+su3l3BrwV8RCHl5u+Y1Wrph5ewQphEmIxl1gmkpGnZd7ApBoYXIq91Pp3USXkOclX6WNEJS43n/e3ym1fB14wpu3eNDeH14brp2yHtr6SkYc3OZlTHyvW1VzpWiKIpydQoFoOvc4G3cHbDzSbCkwYqHhhlYCbBlQkoeJE0AfYKPWr8LvN201e+BAfHdIUc1Hs3PdWnnC2KGA6y7mf/pL1m47xfo1zw2jL4MeDteD9VH9xIISVLM6YQMSUidHinCX5rOhN+SCQlGaXKtk3EFewjK2GBnoExzLnOTb+ZQzxvkTNrNjPxlI+prkllPYboNU8fJuK9nN53A7HNyOi3OdXV6NJOdFwIfcEQ7x13G67jBkY/5kx34F8wkNHGIIFGngymTmJ89H+OIgukwFVwpiqIoV6eOs+H9/hIJ+mHXjyHghjX/GywpQ1/TlgUT5w4vgdxkJ2Aw0Z2UFQ7Auqr7+vNJdyXZxhRKrBOjTukNsEo/fQndu4/DtX8LE68Z+l5Au8tPfacbTYarFZh8HeDriGknhQGfNYeAKY2AKQWt3+iYQWck3zY1vHpvCCENyk8uQ0s9iS/pbVq8uUywximgGmE16jEbdJgNOmxmA6lWY7g8RtAb21hKJlV/gtuYSpcpTsV0cyrbQ0c5EDrDBsMSVhvmYH33HdDp8Ny4ZMi+UzCReZOWYDOOfO9GUNOCiqIoytUo6B961Gr/i+EpweV/C+lFg7cVesiZBZOWDHtlHkC7pz283Yw1FXJmgzmZNr+DKk8zy1Knxk2etmROR7fm8fCmzR/8Cxz+NYQSB4luf5DKFge1He4ht6UBEDKIxd1ActcJMlo+IaPpY5K6yjF5mhFagGRjOhmmQbaIITxld+CURmu3jhU5t5NkTGV7w6/o9LXEtE0yG5gxIYkZE5MpzrKTm2YNB1YBT8JE/Iy2KpJ7GmmwzomTlC44Zurh9eB+FumncJNhPvraZkyfVeG9bj4yZfCMeqPJwtx5N5JiGkYwnYAKrhRFUZSrT2f14KNWDYfg7Icw+8swaeng1zLaoOi68J6CI9Tm6VcNXm+EzGl86mlEAEtSYjcP1qNjmm0ipE2Cm/4Fpq6G8jfgj38P53ZDv21hQpqkrtNDZbMTl2/4uVUD6TQfFncjKZ3HyWzaRWrbIYpDeizagOR0qWH0dWLrOYu/oYq9lUbmZHWwIM3Jurx70As9f2r4Rd8KQggX+ZySZcc6MBlLC4YD24Hl1gGkpKhqB15jMq2WKTEvnzH7+c/AB+SLdO4xrgwXO/3TbrQkK94VCwZ9rzaDjdlzbyAlTsmLkVDBlaIoinJ1GWrUKuAJrwxMyYe5dwx+LWt6OLAyD1FfII6QFurbXqaXBPZ1nWJaSjEZxuSYc4qt2Zh7k+ENFlh6P6z6x/DKuN1Pwzv/DF21OH1BKpodtDl9w9iGeSQkRn8nKY7TzHS1k9x5nKTuSmw9Z0jpPIHVWYve7+APpwsx6DRumlyL2dPERG8nN0/8Gn7Ny9sNv8AXCieZFaRZo0snQHgasK0SQr4494f09rOkdtdTb78GOaBQaYNw8Yx+H6nCxoPmm7EIE8aT1RhrmvB8YSmYE6/ytBgsFKdPxlZYPKonBCq4UhRFUa42nUPkWh39TTiRfen9gyewJ+eGt5i5gIRngE5fJ9qADYhPd5+mzdvG0vwVkDGF/h/TenTkmtNiL5S3ANb9GyzfDM5W5Nv/iPPAK/gDQyedj0aaPok0YUEX9GAIOPtGzXbWTaS6O4U1xfUkmcLPWR9wUeTtYV3WenoC7bzT8BJ2MyRb+z27UDC8/VBzeTjPLYGi0zvwGZNoMUWPWjUIF09bjqJHz4Omm0kRNtAklvc/JZSZin/hzITXNAoDxSlFWCbmIUyjL7OhEtoVRVGUq0coAF01iV9vq4RTf4JpXxx8v8CUPMidP6qutLpbY47ta9yHSW9iQfaCcGXx7OnQXgVakFxzGoZEmzHrdDC5DEfGHEL7XmTiud+R0n6YmmnfwGuPk/A9RiYZs3FpHoKRwKqiPZUPa/K5Jrud0gkDNsCWGiVB+GLqKv7U9T7vn9vKVNaF60dpoUgNrsHrYKV2VJPWWcPp7OujRq326Bt5yXQKizDyoPkWsnXhfCnjybMYmttx3XEj6OOPJwkEk1ImYdSZMOaPzbNSI1eKoijK1aO7LvGoVSgYrsBuS4f5dyW+hjkFJgxvhV4iUkrave1Rx/whP4daDrEgewHmyJYtmOyQPROhM1BgGbx8QKfbzxmHnuqZ3+TszG9i9HUy/fC/MPHcm+gSTLGNlkkYKTKGk9treuy8dmoyeUkubpt6LmHx89m6TL6YvJBjjjO8Uvsu0ueAoIehAiuA4tM78ZvstOrCBU29BPmF6SQ/M59kspbCP5s3MEkXeU5SYvnoQHjUam5Jwmvm2HOwG5PQpySjT7nwJPb+1MiVoiiKcvXoaUj82qm3oLsWyh4JJ6nHozOGq7TrRjc20eXrIjggyDvaehRvyMuy3AF1mwxmsvOXYXF2QYIMqlaHj4YuT9+r3VmLcKbOoODMb5hY+wcym3fRWLiejgnXJqxhlUhQg90tBhrdOtxBQZJRkmvVmJ4aIscqSdUn4Xbl8t/HJ5BiCnDnrCqM+sEzvb6YNReMQd7p+IxUg42bsxYM2Y+09rOkt5/ldOEN+HxwQN/E68YzdAkftwSKuE3MQa87n6emr23G0NiGa/2qhKNWSUY7OdYcAIx5ecN/KENQwZWiKIpydfA5wBe7hx8AfjeceCO8IXP+osTXyJ0fLoEwSlGrBCMOtR4i1ZRKSVrsKEtB9mywtkNrbH2pVoeP+q7YKvMhYxLnZvwVbbmryDv7PxRW/ZKMlt3UltyNzzYxpv1AQQ0+aDTy6lkzLd5wcGLSSfza+SGpSfYQfk3Q7Ekh2+rnL+acItk0SD4bYDHqsJr0/FlWKd1BN39sP4xH8/Ol7MXoEwV+UjLl1Pt0W1L4udHAdt1uXCJIvmbnm745TNVSISl61Mm8/zjSbMR/zbS4lzQIPQXJkwAQBj2GnJwhn8lwqeBKURRFuTp0D7I588k3w5scDzYdmDEVkgbZJHkEBgZXvpCP8vZylucuj9nDLsWUEq65lJESDg77jb51efw0xAms+nOllFA57x/IaNlD3tnfMuPQD2jPLaMlfw0Bc0ZM+4FB1bSUEPfPdLMgI4hBB94QNLh1fNZh4HCHAYte4+YCPzfkBnAKOy3BrkH7k24LJ4wLIfjziddj1Zn4oPMEZzwtlKXNYrY9nySDJeocXdNnvIKDX+Rm0amdYq6WwZrAJGZo6egQ4dE40/kVm8LtxXTsNL7SmWCOXXBgMVgoTC7EGFl5acjJQRjGLiRSwZWiKIry+Scl9CQIrjxdcPKPUHgtZCTYnNhoC+8NOAacfie+ATlQ5e3lBLQAC3IWxLSfYO9XsHPCNeFSEZ5O3P4gNe3u4ZVaEIKOCdfRkz6X3OptZDV8SGbjR3RnldKZtQRH+iyCwsgHDUZerTbT7NFREgmqFmUGo/KnLHqYkqwxJdnPl4r8UbdJIxu/DNAVcsXthjUyatVLL3R8ZcIyJlkyebv9CL9s2glAst6CWWdEJwRISUvAARlpzDRlsKknj5nagDpUltSoYqKmwxWIYAj/4jkxfbAZrBSnFqMX50Mg48ShR/JGQgVXiqIoyuefqw1C0YGApkmc/iDWo/+DQQsg5n018fkT5ow6z6pXvCnBw62HsRvtTE2NLhyqE7q+nKDwAR3klRI4+zFn25qHVXG9v6Aphdrp36Cp8DZy6t8lvXUf6a2fEtDbeJ/FHPZcT4ptBvfND7I4K5gwKX0wxcaJVMhaPJo/5rU0e/wyB8tSS1iSMpVqTwvV3jaa/F0EtBAhNCzOVu7q6KJgyhqSvbnoNOeAswWY+23cLCXmA+UEC3Ji9hC0G20UpRSj77fSUGezok9LG/kbHYQKrhRFUZTPv36jVk5vkA63n26PH727jZln36d9wvW0Ou2khDxMTLGg71/YMnki2LPGrCsDg6uAFuB423EW5ixEr4sutZBuTo/dONhg4qR+OgHZjo4Lq2UVsGRSP/VO6id/hXNnTyHrD7JG7OMm0w4CIpmunlK6TItxpUwdcQK8TuiYasrntL8+KsCym/VYjQlKSQA6IZhim8AU2/mROou7iyXH/z86sqZyPHsOumN1sSea7FGbY+trm9G3duL60g1RzZJNyRQmF8ZMuxpyBt/K50KMa3AlhKgGHEAICEopF4/n/RRFUZRLo9sToKXHS0hK7CYDSWYDdrMBk+EyqPgTCoCzmZAmqW534fCeT7jOP/cmCB3Nk24hENRodfhweIIUZdnCgYDOANmzxqwrvpAPZyB65KWiowJvyMv8nNi6WVFTghH1XR6avQZ0WYtI7TiKPpi44OZgXEF4/qSdj5qWMTN1EfbZd1Li+Yy0tv1kNu8mu/Ej/KY0OiZcR/vElQTMw98SxiQMTDMVUOWvx635EJzPtRo2KZl+/PdIBFUz1yKc3vBu0AMN2FDbfOAE0mSMKr+QYkqmMKUQEacClTF3bKcE4eKMXK2WUsaOgSqKoihXNJcvSFOPl+ZuL25//L3rTAYdKVYjmXYT2clmLIOMXIwbRxOBYJAzrS48gfP9NHuaSW/dF0nsPh84eIMhKpsd5KfbyCyeCUZLvKtekHhTgkdaj2DRW5iRHl201KAzkGWNHjFz+4OcanIAoBlsdGUtIrnzOCZf9DY6Q2n1Ch47aKPRo+NrU7x8pdiPXmeg276Q7qyF6EJeUjo+I71lHxNq32JC7ds40mfRnbmArsyFhIxDb/djEHomG3M56a/BbtGNONDOrTtERvsZTs2+GZ81DUNre2wjnQEM/TbK9vowHTuNf960vkT25EECK0NGOjrr8DfaHi41LagoiqKMSCCkcaS2iy730FNS/qBGm8NHm8NHRZMDm1lPdpKZrCQzaTYj4kKSekbI017D2RYn/mD0qEdWw/tIoac1/4sx52gSqnugO5hF7NbAF67dEx0ghLQQR1uPMjdrLgZd9EdytjU7ZgrrREMPoX6JVlJnpCdzAWZ3E3bH6WEVC6116XjsoA1PSPB/St3MSY8NjDW9ha7sJXRlL8HkbSOzaSdpbQeYVPUS+ad/Q3fmAjqzF+NMnYHWG9zIEEndVZi8rRiCLvzmTNxJhRSas9FsCUpgJJDSWcu08rfozCimYdJikBJdd5xVkeaU6ET2o5WIQBDf4tkAWCOrAuMFVsCYVWQfaLyDKwlsF0JI4D+llM8PbCCEuB+4H6CwsHCcu6MoiqKMRkiTww6s4nH7QpzzuTnX7sZk0JGTYmZCsmXcAq32zk4aztXEzCbpAy4ymvfQmb2EoCl+VW53UjGdbW50Oh3FWfZR9yWoBenydUUdq+qqwh10x10lmGOLrrtU3+VJ+Nx9ton4LNnYnOewOs8hEqwhbHDr+F/7bRgE/MsiF8XJQ1dF91uyaCzeQGPRl7G66sho3k16y17S2/Yj0eG15eKzZmPvOYMxEBtETc2/jtNz1tAy5J3C7I4W5h56BZ8lheMLvgJChKcEgwODQBEOrvoxHygnODGTUF42OiEoSCqICVB76awW9Fljl0vX33gHV9dLKRuEEDnAO0KIk1LKHf0bRAKu5wEWL148tpt3K4qiKGNG0yRH6i48sBrIH9So6/BQ1+HBZNAxMdVCbqqFZMuFbYTcn5SS060ums9VYY8TP2Q270Kv+WnNuzHu+SG9BZ81nO9U1eJEJwSFmaMrHtrpjd2o+Vj7MQw6AzMzojcVNulMpPXbpNkf1KhqGbhKbgCdHnfKFLy2iSR1V0amCs9/rDoC8IPD4VGmJxa7ybMNHVhFEQJP0iTqk+6kYfLt2HvOkNR9EquzDqurHndyMR05y3EnFRMy2DB7W8nuOkxGzdvMaj2K5ZovU5M9yDiglOTWHaKk/G1CBjOflX6NYKRgq64rTl6ZyRadyF7fgqGxDfetK0EIMq1ZWAyJp/xMxcXjNnI6rsGVlLIh8s8WIcQ2YCmwY/CzFEVRlMuNlJLjDT10OGOX1/fSpAQJOt3IP7D8QY2adjc17W6SLQby0qxMTLVgTLBtyWB8wRDH6rvpdAVI9cRujowWIqvhQxypM/AmFcS9hjupOGq66VSzAyFgUsaFB1itA/oipeRY2zGmp0/HrDdHvZZpzYz64K9scRAIDi8Y0gw2ejLnowv5MHlasHiawOfgh0dttHh0/O9FFxBYDSB1RpxpM3CmJd7cOpBSSNK0OTD7C4hP/oMpB35Fcn4pp6dej9d2PsdNaCFSO2sprvqQtM4aOjMnUz5vA37z+bwufbwpQWt0gr15z1Gk2Yhv/jTMehMTbIkrruuS7BjGuLZVf+MWXAkh7IBOSumIfL8W+N/jdT9FURRl/JxsctDc4034+vGGbn75yTnanH4MOoFRH05gNhl0ZCWZ+MKMHOYXpA0r8HJ4g1Q0OahscZBqNZJmM5FhM5FqNQ56vtsfpN3p52ybC39QQ4T8GP2x01Rp7Qcx+Tupm/q1uNfR9Oa428NUNDkIafKCpgillHR4o5POW9wttHnaWD1pdUz7/lOC3e4AjV2Jn30imt6MN2kSHnsBW3dW8llnDw/O9jA7Lf7ig7EkgMJMWziJPTUf1vxv+OwVsir+SFbDYTy2dITUEJqGIeDBEPITMFqpmHMbjQULowJb4faDf8CWOgYr9KviLrqd4Yrsy+aCxUxeUl7CPCsA87Rp45rvN54jVxOAbZHOG4D/llK+PY73UxRFUcZBVYuT+s74W6x4/CFePVDLjso2JqZYWD8/j0BIwx/UCIQ0fEGNyhYn//HhaXKSzayZNYHrp2ZiHsaqQU2DTleATleAs7jQ6wRJFgPmSNBmNugx6gU9niAdLj/eQHTQYPK2EbPRsZRk17+H15JDT8bcuPd12wsT1naqanES1DRKcpLjvp5Ip68zZqPmY+3HAJibFd0Po84YNSVY2eIY0b0G+p+D9eyu7uFLC/IonW5B6y4fVuL7aOSlWUnpP72rN8CCP0dMX4fv5Js4u2uQQiCFnqDBRFdGMZ1ZUwgZzDHX0nXGqfZui962x7L3GEiJb/k1pFvSSTIm/v0YJ07AkD78shIXYtyCKynlGSC2aIeiKIpyxajrdFPdFn8rk+MN3fx8zzk63X5umjOBL83Pj7vcPqRJDtZ0sv1EM/+9r4bXD9dzw4xsvjhrwojyq0KapHsE+V5mb+yUoM1xFruzmropd8UNoDSdCa998BVk1W1uAiHJ9AnJ0cVGBxGvBMOxtmPkJeWRYYkOFLKsWX2jKq0O36hy3N4tb+bt402smp7NbdfkEhCCTtMybI4zWF31xASfYyA/zUp2cmyQBIAtA3PpN8DfTblrkL0ee2kSfceAvz9zChj75VL5Apj2HycwezL6zExy7bkJLyf0OkwlY7ON0WBUKQZFURQlLrc/SGVzbBK1LxjiN5+eH636x3UzmZqduO6RXidYUpzB4qJ0Tre62H6iibc+a+K98hZunJnDF2ePLMgaFi2EMU7tp+yGdwnqbXRMWB73NE9S4lGr/uo7PbQ6fBRm2ChIt2IYIjdsYHDlDrg5032GNYVrYtr21raSUg6dxD6II3Vd/ObTWhZOSuPrSwv7AjapM+BKnY7POoGkrgoMwQu/x0CDBlb95JhScYf8VMcJgPvT9XiiVwnqDDHV8s2HK9B5/QSuW0hhSmHU1jYDGfPy0JlGWMz0AqjgSlEURYmrvDG6phKEP/B/vvscn1Z3DDpaFY8QgpKcJEpySmjo8vD7o428dayJ906OfZBl8rXHlCPQB5yktR+mNfcLaPrYwqBSGPDa8oZ9j94VfNXtLmZOTGFiavxioz3+HvwD9jU80X4CTWoxU4IGnYF0S3jKqqnHi8s3INdomGo73Ty/4wyTMmzct2Jy3Fy1oCmVruwlWF212BxnETJxLpZeB3qdDk2TBBNsaJiTYh5WYNWr2JqNK+SlNZB42lPXPiDwS8qJDn41DfOeowQLJlAwdxk2wyALDnQC40Uq+aSCK0VRFCVGbYebTlfsdNSOyjb2VXdw+8J8brkm8fTLUPLSrNxfNoXb5uX2BVnbTzSzuDidVdOyKclJGlXCsdkbOw2X1nYAITU6cuKPWnlteUjdyD8WgyHJsfpu3P4gU+KM4MWbEjzefpwkYxJFKUVRxzMtmeiEjkBI43RL/OnYoXR7Avzk/SqsRj3f+kLJ4PltQuBJKsRrnYjNWY3FVR8VlOp0kJMUDpr0kY2rNU0S0DScvhA9ngA6HaRYjCPf3gaYYc/D3VONS4uTA+YLoHP0S+Q3p4AxOngyVpxD39GN5bZbsA9RNd6Ym4vOPPzgbzRUcKUoiqJE8fhDVLXGThXVdrj59b4a5uSlsG5u4mXsep3oWylo0utw+0MJR2D6B1kfVLTwyZkOPjnTQW6qhbJp2SydnEGqdYSjWVJGktmjpbd+Src5j/edRbi7dbhDAl8IJlg1piZrmLNHV627d3udWRNTokaK4lVlP9F+grlZc2MKXGbbssMlGuq7YxL0h8Mf1PiPD6pw+oJ896YZww54pN6EK3U6nqQizO5Gkn1N5Fg1spJMGHTRfdTpBGadHrNBT6Z9dFNsBqFnYUoxp93NNPq7ol9r6QEZCfQMFrBnx5xv3n0E0lPJXHLdkPcyTZo0qr6OhAquFEVRlCjlTT2EQtFTP95AiOc+Ok2S2RCeZoozqjQl205hhi0m/0hKSW2Hh9Ntzpjr9spLs/L1ZUV8pbSAT891suNUK7/ZX8tv9tdSmGHjmvxUrslPZUqWfchyDkZfJ0KGg7mABp916Kls6uZfe6r4YeCrPHssfikF86flTM6ys27ORObkpVzQyFljlxdfUGNefioGvQ53wI0rED0CdbbnLO6gO2ZKUCd0pJvTqWpx0j5IPbFEpJRs3X2WM20uNt8wlaLMkZeM0JutFOTNpSBtCXpHHbRXQXB8VxYahJ4Z9jymWHNwa340KRHBEB63B7dJT7vmJZicG1WeAUDf0IrxXCOpd9yB0A+++tSQlYnONroisCOhgitFURSlT32XJ6ZQqJSSX+w5R4vTxyNrZ8TNi5qak8TkBPWfRKS6eU6KmaoWJ03diWs2mY16VpRksaIki/pOD0fquvisvpu3jjXyh88asRh1TEq3MSndRkGGlYJ0K1ajHp0QkS/oqG/kdLOZ8i49lT16/JrgW8Z3QQ/ZUxeyJcOJTS+xGSRGHTS6dXwmSzjbE94zcct7lUzLSWLDwnymTxhZyQWADqefgzVdLJiUFjNqBVDeXo5O6GI2as6wZNDi8HOuPU418iFIKXn1QB2fVndyR2k+pYUjLzVgMuhYOjnj/ObaaYWQkg8dZ6HjDAySkzUWjDoDqZFpWV9zM3qdhSSTheysJTiExOl3ENACBLQAErDvO4W0WLBfN/SolfEijlqBCq4URVGUCG8gxKnm2OTi3jyrRMFGSU7SsAprWox65uankpdm5WRTD27f4B/W+elW8tOt3HJNLm5/kBMNPVQ0O6jt8PDx6TZ8FYmrjOuEianJGjfl+5mXEeLrtbtw6qewsDAdiD4vPzOFpKwCrgU2LipgZ2Ubf/iskR/+qYJlkzP4xrXFw07a79XjCbD/XAd6a+yOeuUd5RSnFGMbkD8U8Nk50TqyDY4hnAP10r4aPjrVyuoZ2aybM/LK4zodzCtIPR9Y9b2gh6wSSC2AnnroaQD/2K0ujEcGggSaIys9U/IQ5mRSgJR+e0AGOztpOnyMpBtuQGdNvMUNhPcQHO+6VgOp4EpRFEUBIqsDB0zb9eVZ5aZwc5w8q2kTkkY8/ZRhN7F8cianW53UdLj70moGYzMZWFycweLicE0oTUranD7qOz34QxqajGy/4/cwJXSGaakhLJE4weKqx+auD9e2isNjPz+qYdTr+MLMHK4vyeTtY028ebSRNqeP/2d1yYhXMjo8Pqra6inKsJFkCX/c9vh6qHXUctuU2/raSSlp7PbhEyZGuttPSJO8+PFZ9p7t4Oa5E7l9Yf4FTWdOn5BM2mD5WUYLZE4Nf7naoeM0uGNH5caCv7ENGdLAkgrJ8QNF10cfgZQk3XDDkNcbz21uEt7zot9RURRFuew0dnti8nx8gRDP7TiN3Wzgr+LkWU2fkHzBmxnrdIJpE5LJSbZwvLF7yFGsmPOFICfZQk5ydPkDm+MsNkf0tdJb9yHR0Zm9KOY6Ib0VvzVOorRBz5cW5FOQbuO/dp3hX/54km/fWEJu6uCjJP05gl3hVX+tTvIi9Z/KO8oBmJ05O9zGE6DZ4YOQnZykkX0khzTJC7vO9o0q3nqBqzenT0imIH0Ev0d7Zvgr4AVXC7jawNMBpmRIyQUtBD4HOJtBG1kpCc0fINDSEd6UOWMK4Y10BrTxenHu3Il1wQIMWVmxF+lPhFcJXmwquFIURbnKBUNa3GKhv/+skeYeH99ZO52UASv2SnKSLjiw6i/VZhzxKNZgYlYJSo301k9xpM8iFGdLlKGqsS8qSifdNoOffFDFv751kgdvnDZowdT+HIHOcBcI57L1eAMcbDqGzZCEIZRBeWMPvshmzLnWkU1baZERq33VHdxRms/Ncy88sLrg36PREs7LSktQO0oLQXckKT40vAR9X00T0pQM6ZMTFnN179+P9HhI+sIXhryePi0NnSV+/bHxNPLtxhVFUZTPler28EbH/TV0edh+opnrpmYyc2JK1GtpNuMFbV6cSO8o1vUlWRRn2TCOML+plwj5MQwoSGnvOYPJ10Fn9tKY9hKB1zr0lNGU7CT+182zsJsNPPXOqbh5aTHXlhJnsDPqWLfHz+nuCvKsJTQ7An2BFUCyMWPgJRIKhDR+uusMe8+GR6wuNLAqzrKPSYCckE4P6UUweRWkFw/ZPNjlIBiwQmZJuBJ7Au7duzHk5mKaMmXIaxqyc4ZsMx5UcKUoinIVc/uD1HREr06TUvLf+2owG3R8pbQg6jWdDmbmRgdbY8Vi1FOSk8zKkixm56XEjJYNJX5tq31oOiPdmbFb3fqtOUj98Oo0ZSebw3Wj7Ca2vFvJ8YbuQdu7Qz2EBqyua/PV49M8FNinRR236u2YdMMrbunwBvjx9lN8Wt3JV0oLLngqcGKqhZKc4Y3AjZreADmzoGAJmOOvvpTCiM+VDCkFxJsK7BVoaMBfXY39uuuGzi0TYMiJnfK9GNS0oKIoylWsstmJNmDR3b7qDk42Ofj6ssKYAKcww06SeXw/OnQ6QV6albw0K25/kFaHjxaHb8hNm82+2CnB1PZDdGfMj7vdjdc2ssAkzWbiH9bO4Kl3T/GT96t4oKx39WEsR6Ar5lidqxIQ5NuiNw4e7qhVu9PHj985RYfLz1+XTelL7h+pFKuR2eMUIA/KngX2FeG6WZ6ucF4WEoxWfHXdaMSurBzItWcP6HTYlsaORA6kT027KPsIxqNGrhRFUa5SHS4/rY7oApFuf5BX9tdRnGlj1bTo/+u3mfRMGcPpwOGwmQwUZdpZUpzBimlZzMxNJjvZjEE/YNRCahh90dNwdscZjAEH3ZkLYq4b0lsImEcenKRYjXxn7QwmZdh49sPTvH2sCRknUcwRiN00us5dSbYlH4s+eiou2ZA25H07XH5+tL0Cpy/Id9bOuODASqeD2XkpQxZiHVcGMyRPCJd4yJpGwGci0Dx0YCWDQdx792KdNw998tD1xww5l2ZKENTIlaIoylVJShk3d+h3Rxro8QT41uqSmA/gmbmX9kPZYtRTkG6jIN2GlJJuT4B2l582hw9vV0vMxsMp7UeRQkdP+pyYa41kg+aBkswGvrN2Ols/rua3B+to6PZw9/IijJE6Cr6QB58WXSjVG3LT6q1nYcYNUccNwojVMPj0XJfbz4+3V+DyhXj4i9MTFmsdjqLM8R95HIlgayu+8vJhtfV+9hma04ltGEVDEWC8RFOCoIIrRVGUq1JdpwenN3qZfE2Hm/dOtrBqenZMwvrEVAsZo9xHbiwJIUizmUizmZianYSvvgEnNno8ARy+AJoGqR1HcaZORzMMLJ8g8I1wSnAgs0HPA2VTyD3SwJtHG2l1+Nh8w1SSLca+VYL91burABmTb5VkSB30Pt2eAE++c4ouT4CH1owusLKZ9Uy+gC1xxou/rh5f5SkY5gpR15496NPSsMyePWRbQ3o64hJNCYIKrhRFUa46gZDGmbbo/e40KXlp7zmSzAY2LIwuT2A06C5oG5iLyexrx2w3kWk3oWkSd3sdFk8TXfk3xLT1WzLR9MNLIB+MEIIvLcgnN9XKix+f5Yk/lvOtL0wjYOiKaVvvqsKss5Jljn62ScbEJRgc3gBPvXOKDqefv1szbdQJ6AM3lB5vgeYWfJWV6KwW9OkZGHJy0CeFgzvfmbP4q6uHfa1QVxfe48dJXrsWoRs6o8kwYcKFdntMqOBKURTlKnO2zUVgQOmF3VXtnG518ZfXFWMfMG00LSdpxNu/XFQ+JwQ8fT/qdIKktsMATJx9PRnmFFy+IA5fEJcvSM8opgTjWTo5g6wkE898UMW/vlXOutIAxf0+26XUqHNXkm8rQdevdpNAJBy5cvqCPPXOKVocXr79hWmjDm4nplpIv0gjjzIYxFdZSaCxCYCQ30+ouwd/dTUiMnUqQ4m3LorH9cknICX2a68durFODF1cdJyp4EpRFOUq4vIFqeuMLr3g9AX57cE6puUkce3UzKjX0u1G8tKGX5X8knDFSYauPwBpRWDPxgSYDKZwcGEwM3nSDLo8QTrdfjrd/hFXh49nSnYS37t1NlveO8nre0MsKoFrZ2gY9NDua8ITcsZMCVr0dgy62HITZ1qdvLDrLO0uP//P6hJmjXJln0EvmDbh4pRdCDkceI8fR3N74r4+0qAKwvmB7j17ME2bNqwkdUNmFsI4sjIeY00FV4qiKFeRypbY0gtvHWvE5Qvy50sLo7a4EYLLfjoQAGdr9M++HmirgDm3x7ZNzsViMjDRZGBiarg8QyCk4fAG6fEE6PYE6HD5CWkjLxWfYTfxlzfYeOOQlwNVes616LhpYZCGUCVAbAmGAasEg5rGHz9r4vdHG0izmnhozXRmTBz985+anYTZoB+64SgFOzrwHjuGDI4+WO3PX1VFsLWV9FtuGVZ748RLOyUIKrhSFEW5avR4A7QNKL3Q4fLz/skWlk/JZFJGdImA3FTriDcrvuhCAfAMSCCvPwRSQn7sXoLxNgI26nVk2E19CfshTdLu8tHq8NHc440JRgfjl92smR9i6kSNdw7r+fUOA5nTq0gz52IzRAdKScY0IBxU7T7dzh8/a6TN6WfZ5Ay+vqwQm2n0H9HJFgMF6WMz8ihDITSPF6HXISyWviKeMhQiUFuLr7oaLiAoHYpr926ExYJ14cIh2wqjAX1m5pDtxoLXlbjumgquFEVRrhLVA5LYAd480oCU8KUF0XlIer1gas7ls7IsIVcbMcvN6g+ANSO8P11/BgsMYw8/ve78ptBFmXaO1XfHrKyMxxtyEZDhPfQmT5DcfUOQnScD1IgaHE1lfOjQMSlbkp4kSbMYONOscbyxlgPnOulw+SnOtPHnSwuZV5A2zDc/tJkTU4auZD4Ize0m0NRMsKUFzd1vOlmAzmpDl5REqKsL6R/e3oEXcn/PwYPYli0bVkFQQ3b2sBLeR8vvDdJc3ZO4H+PeA0VRFOWS66103l9jt4ddp9u4cWYOWUnRq+eKM+0XZSpp1AbmW4X80HQEisvC85r9JY+8/EKS2cDS4gzOtDk51z74xtIDq7JbzTB96ilqGzXyrdM4Uq3j8Nn+farEoBPMmJDM3cuLmJs3ukBooNw0C6m2Cxt51Hw+/NXVBBoa4pdKkOHAJyrgGgfOnTuRgQD2srJhtTfmje1ihXi0kEbLOQdaKPEfgwquFEVRrgLVbbGBwbZD9Zj0upj96cxGHYUZ47ih71iRElwD8q2aj4e3VxnmlOBw6HSCkpxk0mwmjtZ1JZwmdMbZ8qbWVYlRZ+bWefn4ZwfpdAg6XaALZjIjJ4fpE8YnH8qgFyMu3SCDQQJNTQRbWgh1dw+7/tR4kcEgzg8/xDxzJqaCgiHb61OS0aeM/7Y+HY1uAkMsglDBlaIoyuecNxCiqSd69daZNicHa7pYPz8vJq+qJCcJ/aXcHmW4PJ3hnKv+6g+Ep/8mDKjKbrSCNW1Ut8tKMjO/II2jdd0xCe8hLYg7FF3xXkpJvbuSfNtUdEKPxQi5GZLcDJieUjjszZovREnO8IM2zesl0NBAoL4eGRh6+vNice/fj9bdTfLddw+r/cUYtfI4/Tg6vEO2U8GVoijK51xNhztqtEVKyWsH60m2GFg7O3plVYrVSG7qZV56odfAUSuphYOr3HmgHzAddgFTgvFkJpmZPymNI7VdUQGWM9iNHDDU0+VvwRXsYaEtugSDSWce18AqK9lMQfrQI4+hri78tbUE29ou+SjVQDIUwvGnP2HMy8M8a9aQ7YXRMO6FQ6Umaa+PzVuM5zKuCqcoiqKMViCkUd8VPWp1vKGHk00ObrsmF4sxenRj+kWqhzQmnAPyrTrOhkez8hfHtr3AKcF4MuwmFkxKo3/etDPYFdOuzh0uwVAwILiyD7HlzWiYDDpmD1EXK9jejvvgQdwHDxFsvfwCKwD3vn0Em5tJue22YeWhGXNzEfrxzRHsbvMMOR3YS41cKYqifI7VdrgJ9Uu81aTkfw7WkZVkYtX06I1tc1LMpNkun/0DBxXwgN8Zfax+fziJPW/Akn2jDSxjG9Ck203Myk3heH14xVi8fKs6VyXpphzsxuh7j1dwJQTMzkuJW01fSkmwuRl/TQ2ac3ijL5eKDAbp+eMfMRYWYpk/f+gTBBiHkZM1GsFAiO6W+IVR41HBlaIoyudUSJPUdkZ/IOyv7qS208NfrZiMQX/+Q1inY9R7111UA0etIDwlmDUTzAMKb47RlOBAualWXL4gJ5vb+kow9ApoPpq855iTujzmvCTD2Cdd63QwJy81ZtUnQKClBf+Zs+O+sm+sOD/8kFB7O+l33TWsUStDVhY6i2Vc+9TZ6EYbQQ0vFVwpiqJ8TtV3eqL2EAyGNLYdrqcg3cqyyRlRbQvSbWNStPKiGZhv5WyBrhpYGCf5eQynBAeamp3Ema5aiM5lp9F9Fk2GYre80Vkx6MZ2dFCng7n5qeQknw8wZChEoLGJQF3dFRNUQbjKe88f/oBl7lzMs2cP65zxHrUK+EK4unxDN+znCvo3SVEURRkuTZPUdER/qO6qaqPV4ePbXyiJ2uZGrxMUZV4BpRd6aSFwt0cfqz8Q/md+afRxow0s47c8XwhBdqofe48el/98Pk6duxKDMDHBUhTVfqynBA16wfyCtL5NmWUggL+ujkBd3WW18m+4ul59FTSNtDvvHNaolc5mw5A+dGHY0ehp84w4LW3I4EoIUQS4pJRtQojlwArgtJRy23BuIITQA/uBeinlbSPsn6IoinIBmnq8eAPnP+w1TfL28SamZNm5Jj/6Az4/3XplFAzt5WoLrwzsr/4ApOTHTgGO46gVgCY1HIEepmYnUd/lod3lR0pJnauSPNtk9Lroj9mB+VejYTPpWVCY1jfiGGxrw1tefkUGVQCeo0fxHjlCype/jGGYW9gY88e3/EIoqA2r9MJAgwZXQoh/BjYBUgjxMrAG+BC4VQixSkr5d8O4x4NAOTD+lb0URVEUpJRUt0cnLR+s7aTN6WfjoklRIwJX3KgVxFZl97ugpRxmxvn/96Scce1Kj68HTWrodIJJGTZsZgPHm2twBDuZm359VFuBwK4f3UehEJBmM5KdZCE3zYIxkjfnr67Gd+bsqK59KWk+H12vvIIhN5fkL3xhWOcIgx7jxPENnh3t3kGr8icy1MjV14BZgA2oASZKKd1CCANweKiLCyEKgFuBJ4CHR949RVEUZaRanT7c/ZaMSynZfryZ7GQzCyelRbW94katIDbfquEwyBAUDKjKbjAPay/B0ejwdUT9nGk34dfXAFA4MN9Kb48ZyRouu9lAfpqViamWmNWA3ooKAvUNF3Tdy0XP739PqKOD7IceQhiG94yMeXkI4/htLC41SU/78FcI9jfUO/BKKf2AXwhxWkrpBpBSBoUQw9mlcQvwD0DyEO0URVGUMVLTHp1rVdXq5Eybi68vLUSnu8JHrbzd4e1t+qs/AOZUyCiJPm4f31ErgE5vZ8yxyq4Kcmw5LCsqps3pw+UN4g6Ehr1KUKcDq9FAitVAms1EmtWI3Rz/49pfXX3FB1aeo0dxvvce9pUrMU+bNvQJADqBsbBwXPvl6PQSCl5YEbChgqs0IcTtgABSI9/T+/NgJwohbgNapJQHhBA3DNLufuB+gMJxflCKoiifdw5vgC539JYw2483Yzfpua4kOo/lihy1cg4YtQoFofEwTFpKVFVPGPd8q4AWwDmg1pY/5Keys5Lr8q7DqNeFq92nhnPeJqcUQSiJTrefHk8Ak16HxaTHatRji/zTatJjNxmiguCE929uvqKnAiFcJqLj5z/HOGkSaV/5yrDPM+bmoTONX002qUm6my9s1AqGDq4+Am6L872I/DyY64H1QohbAAuQIoT4lZTyL/o3klI+DzwPsHjx4suwTqyiKMqVo7Yj+gOhucfL4doubr0mNyqQuiJHrSA236q1HALu2KrsOiNYo8tNjLUub1fMljenu04T0ALMzowuI2DQ6ylMzUKv0zMZ+6jvHezowFtePurrXEqB+npaf/IThF5P5je/OfwpPgGmwknj2reedg/BYIIduodhqODqWL/vJeGgqvf7QUkp/wn4J4DIyNV3BgZWiqIoytjxB7WYDZrfOdGMXidYPTN6iuyKHLUK+sPTgv3VHwjvIzjxmujj9qzYkawx1uHtiDlW3lGOQWegJC16ijLFlIJeNzbPO9Tdjfezz2AERS0vN76zZ2n7j/9AZzKR9eCDGLKyhn2uITsHnXX89r8MhTS6RlCNPZ6hgqvecr0zgCXAG4QDrD8DdozqzoqiKMqYaujyRG3Q7PAG+Ph0G8unZJJqPT8qcOWOWg3cqFmGt7yZOC+cvN5f0vhu4gvQ5euKOVbRUcGU1CmY9NFTVumWsUmsDzmdeI4eRYYufFTlUvOePEn7f/4nupQUsr/97WGXXehlKhrfFKKuJjdaaHSB66DBlZTycQAhxHagVErpiPz8GPDqcG8ipfyQcAkHRVEUZRxIKakbsNXNhxWtBEKStbOjA40rctQKYoOrrppwzas5t0cfFzqwR++bONY8QQ+eYPTz7vH10OBqYP3E9THt08xpo76n5vHgOXzkiq1jFerupuf3v8f18ccYcnPJ/va30aeOrO6XISMdffL4rZHze4MXVNdqoOGuCS0E+q8O9APFo767oiiKMiZanb6ooqH+oMb7FS3My08lL+38FIpOB4UZV+ColZThQKq/+v2AgLwBVdltmaAf3w1IurxdMccqOisAmJkxM+q4XuhJMY2uvpXm9+M5cgTpH85C/cuH1DS8R4/i/OgjfKdOgRAkrVlDyi23XNB+gKbi4rHvZD/t9a4Lqms10HD/+n4J7BNCbCOcb7UB+Pnob68oiqKMhYGJ7J+cacfhDbJ2TvSoVUG6DYvxChy18nSCFr0KkvoDkFkC1rTo4xdhSnBgfSuAkx0nSTImkZ+UH3U8zZw2rK1cEpHBIN4jR9Dco8sDutj8tbV0/vKXBOrq0GdmkrxuHbZlyzDmXFiJDH1aGvq0tLHtZD/OTh9eV2DohhE+d+K2wwqupJRPCCHeAlZGDv2llPLQsHugKIqijBunL0in6/yIhiYl2080U5hhY8aE81MoV+yoFcSOWrk7oOMMzP/agIZi3KuyQ+zIlZSSkx0nmZ4+HZ2ITqRPs6SN6l7e8nJCDufQDS8j7v376fzlL9HZ7aR/4xvYFi9G6EcX1JsmF49N5+LQNElno2vohr3tQ5KDb59L+Pqwx02llAeBg8O+s6IoinJR1HVGFw09WtdNU4+Xb66cHDVikpNsuTJHrSA236pvo+YBVdmtabHJ7WPM6XcSGDCK1uRqosffEzMlCJBuvvBkdv+5cwRb24ZueJnQXC66/ud/cH/yCaapU8n85jfRp4x+9zt9Wuq4btDc3eIeUemFir2NdDa5E74+vpPSiqIoyrgKhDQau6ITcLefaCLDbmJRUfSH0aQrddQq6ANfT/Sx+gPh6b+U6Cm48U5kB+j0xVZlP9l5EoAZGTOijpt0JpJMSTHthyPY2YnvzJkLOnckNI+HYHMzgaYmQh0dYDAgDAY0txvN4SDY3k6otRX0enTJyRjz8rDMmIF5+nR0tvDflAwGcX38MT1//COay0XyzTeTcvPNw97KZijjmWvl9wTpHkHpheaz3Zw93EbR3MSrHFVwpSiKcgVr7PIS6lfvqLrdxalmJ19dXIChX52nVJsxqhzDFWXgqFXAA83HYNra8E7G/V2EfKt4W96c7DhJji2HDEt04dJUy8hWw/XSPB68x44Po6rk8MlQiEBDA/4zZwg0NvYFVFp3d8JzdHY7+owMjJMmgZSEenpw79mD66OPQIS3oBF6PcHmZjSXC1NJCWkbN2KaNHZFPvVpqRgyxqcgrNQkbXWOYT9md4+fI+/XkZJtZeb1uQnbqeBKURTlCjZwSvD9ky2YDTpWlEQXZbxic60gNrhqOgpaEAoGVGU32sB8YaNEw6VJjW5fdDAS1IJUdVWxbOKymPYZ5pEHBTIYxHP0M2Rg+MnVgwm2teF4913ce/cifeF9GYXVinHCBCyzZmGYOBHjhAkYJk7EkJmJ1DQIBhFmc9w8KRkI4K+uxltRge/UKYROh2X+fKwLF2KZPXtUyfvxmKdMGdPr9dfe4MTnCQ3dkHBx0UPbz4GUlK4tRK9PXKRWBVeKoihXqDanD7f//AeD0xtk39kOri/JwmY6/593s1FHTvL45iGNGynB1R59rO4AmOyQFT0FdzFGrRx+ByEZ/WF8tvss/pA/fr7VCIuHSinxHjuG5hp+cnUi/tpaHNu34zl4EPR6bIsXY5k1C9OUKegzMhIGQQJgkH37hNGIedq04W+yPAqG7KxxWyHo6PDi6PAN3TCiYk8T3S0eStcVYUsd/N8nFVwpiqJcoWo7oketdlW1EdQkX5gRvVquIN025qMJF83AEgxaCBoOQd5CGLidzEVYJRhvSrCiowKd0DEtPTrYsBqsWAwjq+Xkr6oi2BF7j5EItrfT+etf4ztxAmGxkLRmDcmrV49rGYNxoRPjNmrl9wZprx/+Cszms91UH22j+JpMJk4ZeqpXBVeKoihXILc/SLuzX/kFTfLhqRamT0giP/180VC9TpCfNn77sI27gSUY2k6B3xG7UbPeCNbxW03WK96WNyc7T1KUXITVEP2cR1qVPdjRgb+2bhS9A/ehQ3T+6lcgJSlf/jJJK1eO6z5848lUUIDOPvpNrgcKhTRazjmGXSzU4/BzNJJnNeO6xHlW/angSlEU5Qo0cKubYw3dtDn93FFaEHV8QooFk2F8NzAeV66W6J/r94POALnzo4/bc2KT28dYSAvR449etegOuKnpqeGm4pti2g9Mbh+MDATwlpdfcN+kptG9bRvO997DWFxM5r33jmgz5MuNMJnGZYVg0B+itcZBwDe8PCuAYx/Vo2mShV8cPM+qPxVcKYqiXGE0TdLQFR1cvV/RQqrVyMLCtKjjhVfiBs29Al7wOc7/LGU43ypnDhgHjMZcpI2aNRldC+lU5ykkMibfSiBGVDzUV1WF9F3Y1jYyEKDj5z/Hc/Ag9lWrSLvjjjErgXCpmKeVjOl70DRJR4MLZ4d3RAsw2+octNY4mHltLva04ectXtlPX1EU5SrU1OMlGDr/EdHi8HK8vofb5uVGlV9It5tIMl/B/5kfuEqwpwGcTTDzlujjQgf28R+liTsl2HESi95CcUpx1PEkUxJG3fBKXwTb2gg0Nl1QnzS/n/b/+A98lZWk3n47STfeeOXm10UYJuRgnDB2wXIopNFU1Y1/BKNVEKm6v7sRa7KRomsS17SK5wr+t05RFOXqVD9g1OrDilZ0QrBqenQBzSu6/ALEqcq+P/zPgVXZbVmxye3jIFEye0l6CfoB9x/uKkGpafgqKy+oP1LT6Pz5z/FVVZGxaRO2pUsv6DqXE2E2YZk+fcyuJ6Wk9ZxjxIEVQMOpLnravMxfMwn9CKfWr+CJeEVRlKuPwxugu9+Gsb5giF1VbSwsTCPNdn75vM2kJysp8XL6y56U4f0D+6s/AOmTwTZgFCFp/KuyB7QArkB0eYQ2Txtt3jZmpl/4ljeB+no0j3fohnH0vPnm/7+9/wyv7DrvPNHfOjlH5AxUROUqFoukRFIkRYmSLCrbkhXsdttSu91uj0NP9+1+nnl6eubOc/vD3L7d0zPublu2ZLdt2VZqK5OUxCyGqmLlAKAC8gFwcg777L3uh4NCKIQCUAAKBa7f84A8e5+1917n4NTZf7zvu/4vxTNn8H/qU9tCWAE49uxBWNfP7DYTK1LMrd4vTK8a9L01ga/eScuuwKqPV+JKoVAo7iNuj1qdvJmkUNF5cjvZL8BCC4ZiCmIDC6NWUCtm32BSpRTytmqdq4nFW96YhAm//c7L9WtmnEs3/12O/BtvkH3uOdyPPornqafWdI6thqWxYV2L8KsVndTkytvazOXaqUlKOY3e9zSv6d+RElcKhUJxn6Abkon0bJRDSsnP+6ZoCTjY3TjrTG42C1oCq/NX2nLcnhIcPwPIha7sDj9YN/61LtZPsC/RR8AeoNE1vz7Ib/djEne+vVaGh9fkwl7u7yf5N3+Dfe9eAp/97P0toqcxOew41tmUND6exzBW3z8oEy9y42yU1j1Bwq1rc/xX4kqhUCjuE24vZL8RyzOcKPDknoZ5N9gWvxPLCpeMb1kW1FudrqUDA53z92/CKkGoRa7mYkiD/mQ/e0N7F4iblbS8McpltNHVe1ppU1PE//RPsdTXE/6t31q0Pc39hrCYcRw6hFjGFX61FDIVCpnVr76UUnLxpTGsNjO9K/S0Woz7/F+fQqFQvHsYu83b6sW+KRxWE4/0zK9Bag/dn6aRM9xuwVCt1PoJtj6wSKPmjU8JVvQKhep8N/zh7DCFaoE9wT0Lxq+kmL1y/TpSN+44bi5GoUD8j/8YhKDud34Hk+s+X7AAYBI49u3D7Fm/npDSkCTGV+6+PpfhS3FSkwV639uCzbn2NX9KXCkUCsV9QLakkSnOppAyRY1Tg0ne01OHwzobvQi6bfP6Ct6X3B61mrwAemWhK7vVBXbvhk9nqVWCsLDeymay4bEtLxT0dBptYnJVc5BSkvjLv6QajxP+ylfua4PQGUwC5/796/5aMvESWmV1whWglNPoe3OCcJuHlt2Bu5qDElcKhUJxH3C7I/utPoJP7Jm/Uq49eJ9HrWARV/bTYHFCw775+zcrJbiEv1Wbpw2vbb64u5NxqJRyTdYLuZ//nNL58/g/+UnsO3eu+vgtxy1hVb++Kz0N3SA9VbjzwNuQUnLptTEMXXLgfa13XcemxJVCoVBscaq6wURmtpC91kcwyt4mLy1z+gbarSbqvSt3kd6SGMZ8CwZp1MRVy2Ew3xaR24SUICwsZi9Xy9xM31wQtYI7t7ypRiLomeyyY26nfOMG6e9+F+eRI3iefHJVx25FhNmE89ChdRdWAJlYCV1ffRH7eH+KyRsZdj3YiNt/9/+GlLhSKBSKLc5EZv4N49xoikS+ssB+oTXgvP9XjhWTYFRnt+PXoZRepFGzbVMaNRerRUrV+T5U11LX0KW+oOUNLC+upKZRvn5jVdfXczkSf/ZnmINBgl/84v3/+wXsvb1YQivvu7hSdM0gHV299UIhU+HSq2MEm130HFkfwafElUKhUGxxFhayRwm6rBxpD8zsE4J5Uaz7lsVc2YUJWo7M3+/Z+EbNsHCVIMDV5FUsJgs9/p55+91WNzbz0iveyjdursp64ZYDu57NEv7yl7dFAbutuwtrw8ZEHFNThVVbL0hDcu5nwwAcfn8HwrQ+nyklrhQKhWILky5qZEuzkZyJTInLkQzv212Pec6NoN5rn1fYft+ymAVDfS/cXiS+SfVWS/lb7fDvWCCklnNlryaTaGNjq7p29qc/pXTpEoFPfxpbR8eqjt2KWFtbsHd3b8i5K8Uq2fjqne4HTk2SjBTY/1grLt/6WUEocaVQKBRbmNujVi/1TWE2CR7bNT990Ra8/6MaaEWozFlCn52A9OhCV3aTpdZPcBO4vZg9XU4TyUcWTwk6F091yWqV8pUrq7pu+do1Mt/7Hs4HHsD9+OOrOnZJxJyfTcba3IRjz8IatfVASklsNMdqK61Grya5dmqK1j3BNa0OdHqWbtNzn6/XVSgUiu1LVTeYnFPIXtZ0Xr8W54GOIH7n7Be7y24m5L6P+wjeYrGoFUDb7Y2aw2Da+NhAQStQ0ecbUS7b8sa2eMub8rVrGKXyiq+rZ7PE/+zPsNTVEfz85++uzsoksNTVY21qxBwKIabfN6NcRhaLGIUCRrGIUSgiyyWMYhGpVe9w0tVhDgaw710oRteLTKxEubi6OUeup7jw4gjhVg8Hn1j96kAhWNa9XYkrhUKh2KJE0iX0OTUkb91MUNR0ntx7u/3CNohaweLiyt++MAXobdqU6SyVEvRYPbR6Wuft99v9mE0L07LVeBxtPLLia0rDIPH1r2Pk8zWjUOfa6+gsjQ3Ye3oWPYfJbge7HXMgsOD61WiMamScajLJqsNBt1/H6cC5f/+GFeKvxXohcj3F2eeHCTS6eODDnZjW0M0g1OzGal86Da/ElUKhUGxR5jZpllLyYt8U7UEnO+vn9BE0CZr993kfQVhowVDOQvQq9H7stoEC3Ou/hH8xbjcPlVLSl+xjd3D3gt6Bi7W8McplSleuruqa2eeeo3zlCoHPfx5be/vqJw01D6mDB7GEw3ceexvCZMLa2IC1sQGjVKI6OYlRKiGrVYxMBqO48romk9OB8/DhdW1rczvpaHFV1guRaynOvlATVg9+tBuLbfV1ip6AHV/d8qJXiSuFQqHYgqQLGrk5hezXojlGkkV+7eHOeVGAJr/j/u8jCFCIz7dgGHun5nHV9uD8ca4QmJeudVkvpJQL6q0i+QiZSmbReqvbW95IKSldvoysrLy/Xamvj8wPfoDrwQdxv/e9a5q3MJtwHDy4LlYHJocDW+f8Xo56Lkd1aorqxMSyqU6Tx43z8OFahGyD0KsGmdjKxd6MsGpy8eAvrU1YOT1W6tru3KpHiSuFQqHYgoym5qc6XrwaxWk181D3/Jtm23ZwZAfI3dYOZvRkTUiF5tsdbJZxaFbLUjXm1/Hcqre6XVwt1vKmcnMQPZla8fX0dJrE176GpaGBwK/+6prSaMJswnHoEJbgxvl/mT0ezB4P9p4eqskk1YkJqvHEjIgUVgu2zk6sbW0z9V0bRWpy5dYL6yGsXD4bDR3eFdk1KHGlUCgUWwzttkL2dFHj9HCSJ/fUY59jt+B3WfE6Nj6KsynMbXlTLcHEOeh5apFGzZtTb7Wov1XiKg2uhgVRqttb3lSTSSpDgyu+ljQMEl/7GrJYJPx7v4fJsfo0r7CYcR46tKCGaiOxBIMzQs7I58FsXtPc14JW1skmVha1mhzM3H3EymtdsbCCDbRiEEI4hBBvCyHOCSEuCSH+3UZdS6FQKLYTkVQJY07f2VcHouiG5InbHNm3TdSqlIbqnBRT5Dzo2sKUoCMA1s25ed9ezK4ZGtdS1+7oyi41jdLly6sqBM/88IeU+/sJfO5zWFtaVj1XYbXgPHJkU4XV7Zjc7k0TVlCLWskVvMeFTIVzPx3GW+dcs7Cy2c00dPpWZTC6kZGrMvCUlDInhLACrwkhfiylfHMDr6lQKBT3PaPJ2ZSgbkhe7o+yr9lHk2/25mW1mGj0boNCdoDcbasER9+umYY29M7f790c41BDGqTL6Xn7bqZvohkae4MLxVXAHph5XL52DVleRZ1Vfz/Zn/wE18MP437kkdVP1iRwHDiA2edb/bH3KVpZJ5+6s7WFrhuceW4IhODYM51rElZCQH2nF9Mqnds3LHIla9xyg7NO/9zlok6FQqHY3iTyFQoVfWb77EiKZEHjyT3zV8i1Bhyr/sLfssyttzKqMHYGWo/B7dYGm5QSzJQzGNKYt68v0YdJmNgZ3Dlvv8viwmGpidxqPI4WmVjxdYxSieR//++Y6+oIfPaza5qrY/fuDa2x2oqkpgorEhNXfxEhHS1y6Mm2NbuvB5vc2Byrj0NtaLWZEMIshDgLTAEvSCnf2sjrKRQKxf3O3KgVwIt9U4TcNg63BWb2CbFNHNkBtBKUM7Pbk5dBy0Pbifnj7D6wbc5rXszf6mriKl2+LpyW+anYW/VWslql3Ne3qutkvvc99ESC0Je+tKZVdbb2tjWlEe9ntIpOPnnnqNXkzTRDF+J0HaqjqWdxc9c74XBZ8NWtLTq8oeJKSqlLKY8AbcAJIcSB28cIIb4ihDglhDgVjUYXnEOhUCjeLZSrOrHc7I1jPFXk6kSWJ3bXz4tSbZs+gjC/kB1qqwTNdmg6NH//JhmHwsKWN3ktz0h2ZIErO8zWW5WvX1+VC3t5YIDcSy/hed/7sO/ceecDbsMcDGBbw3H3O6mJO0ettFKViy+P4Q072PvI2j43FouJ+k7vms1PN8UcRUqZAl4CPrTIc38ipTwupTxeX785xnAKhUKxFRm/rZD9pb4oFpPgsV3z++htG0d2gNwccSUNGDsFzYfBclsaZ5PEVdWokpkbSQP6k/1I5IJidoEgYA/U0oFj4yu+hlEuk/irv8JcV4fv4x9f9RyF3YZjA13PtyqVUnVFtVaXX49QKVY59FTbmtzXAeo7vFju4g+YjVwtWC+ECEw/dgJPA6uzqlUoFIp3CVLKeU2aS5rOL27EON4VnGe34HFYCG6HPoIAhl4zD71F/DoUkwtXCdo8YHNvypRS5RTytthIX6IPh9lBp3e+oabX5sVcNVbtwp7+9rfRYzGCX/zi6tOBApz792PaQNfzrUoycueo1dRQhrG+JD3HGvDXr+2PEF/YgWOZpswrYSNXCzYDfyGEMFMTcX8vpfzBBl5PoVAo7ltiuQolbbaQ/Y0bcUqawZO32S90hLZR1Cofq0WrbjF6EoQZWo/OH+dt3rQpLeVvtSu4a0HvwKAjSKmvf1Uu7MUzZ8i/9hreD34Qx+7dq56ffceOe2q5cK8o5ioUssu/z1pZ5+JLY3iCdnYeX5vZrNVmIth890J+w8SVlPI8cPSOAxUKhUIxr5D9Vh/BjpCLnrrZL3qrxTTPjuG+Z+4qQSlr4qpxXy1SNZdNsmCAhcXs0UKUeCnOUx1PLRjrT2lUV1ErXE0kSPz1X2Pt7MT37LOrnps5EMC61n6D9zFSShLj+TuOOf/iCOWCxrEP7cS8hnSgAOraV2+7sBjboCGVQqFQ3N8UKzqJ/Oxf5ZcjGcZTJd7f2zCvrqY14Nw+9gtSzi9mz4xBNrJIStANdu+mTKmiV8hr82/ifcnaCsDb663M5SqWwciKzy0Ng8Rf/AXoOuHf+A2EeXX1PMJixtG7911XZwWQTZSolPRlxwyejzN5I8Oeh5sJNK4tuhtsduFwr0/HAyWuFAqF4h4zlirOc5t+4cokPoeFE12zzt81+4Vt4sgOtdoqXZvdHj1Z+3/r8fnjNsnbCiBZWtyCIWgPUu+cs+DKMAjcjCF0Y8H4pcj88IdUBgYIfPazWBpWn7Ky79yJybmNfv8rRKvoJCOFZcckJ/JcfWOchi4f3Ufqlh27FN6QY801WouhxJVCoVDcQwxDMp6aLWQfTxW5OJbhyb0NWOekNhq8ju1jvwCQvy2dNvwG1O2qNWueyyamBG+3YDCkQX+yn72h+REjy+A4nsrKb5/FCxfI/vjHuB55BPfDD696Xpa68LvOz+oWsZHcss2ZK6UqZ54fxuG2cviptjVF9hwuC+GW9V0wocSVQqFQ3EOiuTKV6mwE5KdXJrGYBE/snm9Ns60K2WF+vVVqBFLD0Pne+WOsTnCszQByLSRKiXnbw5lhitXiPH8rUzSJaTKBx+q5/fBFqcZiJP7iL7C2tRFcgwu7sFqx713YcufdQDpaoJTXlnxeSsm5n45QKVQ5+kwn1jU4qVvX0DdwJShxpVAoFPeQuYXs2ZLGGzfivGdHeJ79gs9pxe9an1qQLUExBZU5tU1Dr4EwQcdtvfU2cZVgQStQ1ud7KF1NXEUg2BOsiStRKGG5MYZVWHBY7pyik5pG/E//FKQk/OUvI9Zgn+DYu+ddabtQKVZJTiyfDrxxJkp0OEvvo80EGlb/x4fVbqapx4fZuv5SaCOtGBQKhUKxDPlyleScv8xf7o+i6ZKne+enwtpD26zWJjunEFwaMPQ6NB1cGKXaTAuG21KCUCtmb/O24bF5oKpj6RsEw8C9ggJ7KSWJv/ortJERwr/921jWYJJtbW5a03H3O9KQRIez8+oQbyc1WaD/rQmad/jp2B9e9TU8ATvhNs+GLRBRkSuFQqG4R4zOMQ2t6gYv9kXZ3+KjJTArpmwWE43ebWS/ICVk5riZx/prfledj84fZ/OAw7dp07q9mL1YLXIjfaO2SlBKrP1DiFJtRedKUoLZn/yE4smT+J59FuehQ3ccfzsmhx37rl2rPm47kIjkqZSXXh1YreicfWEYh8fKgSdWX2flCdqp71gfy4WlUOJKoVAo7gG6IYmkZ8XVycEk6aLGB26LWrUFt5H9AtSElD7HDHLwdTDbFlow+DavgFtKucDf6mriKoY02B/ej3lwHJHOzTznvoNbfOGdd8h8//u4TpzA+6EFXd9WhL23F2F59yWXCpkKmXhp2TGXXh2nkK1w+OkOrPbVLfJweqzUta2sXu5uUOJKoVAo7gHjqSJVvZb3kFLy/OUJWvwO9rfMRmtMJmjdTvYLANk5USujCsNv1uwXrLdF5zYxJZjTclSN6rx9l+OXcVqc9JR9mCdmW/TYzDZspqVb1lSGh0n+xV9g6+kh+IUvrGn1mq29DUswuOrj7ncqpSrR4eyyY8YHkoz1Jdn5QAOhVTqpmy2C+va1N2O+nejQzSWfU+JKoVAoNhkpJcOJ2WLdvsksI8kiT/c2zvvib/A6sFu2kf2CoUN2zirByDmoZKHrtlWCziDYNm915O0pQSkll+OX6fXuwj44Me85j3XpG7qRzxP/0z/F5PEQ/if/BGFd/SIEk8uFbceOVR93v6PrBpODmWVtF/LpMhdfHiPQ6GLn8dVZdAgBDZ3rV7weHR4kE5ta8nklrhQKhWKTmcyUKVZma0p+enkKj93Cwz3zC3Pbt6P9gpxTSzP0Oti80Hx4/rhNjFrBwpY3o7lRMpUMh8p1cNvNfql6q1sO7HoqRfjLX8bsXb2rvDCbcBzYjzC9u27NUkqiQ1mqlaVNWfWqwZnnhhBCcPSDHatOlYea3evmvp6cGCcTnVx2zLvrN6hQKBRbgMH4rA3BZKbEudEUT+yux2aZ/UoOuKz4ndvIfgHmF7JrJRg9DR0PgWlubZHYVHFlSIN0OT1v3+X4ZQD2GwvnsZS4yj73HKWLFwl85jPYurrWNBd7by9mz8bXA20lbvUNLOaW9rMCuPqLCJlYiUPvb8fpXZ01hSdgx1e3Pun1Yi5LYmz0juPefdVyCoVCcQ+J58rkSrP1PT+7MoXZJHhy7/yWKN116+sYfc+plmvF7LcYPQl6GbpuWyXorgPL5vk6pctpDDk/YnIlco4OUYdPzI8cOiwOzKaFt83S1atkfvADnMeP43788TXNw9bdhXUNbXHuZ3TdIDqcpZhdXlhFrqUYuhin+3AdjV2rW0Fqc5gJr1MBu1YpM3l9AFjGI2IaJa4UCoViExmMz9Za5ctVXr8e40R3aF6Uyue0EvYsXTR9X5IZZ95Naej1mpCq2z1/3GanBG+rtyokotwojvIRy5EFY72LRK30VIrEn/85lqYmgp///JqKpS2NDdi7u1d93P2INCTVqkE+WSYdK2LoywuVdLTAhRdHCTS62PPw6j4bFouJxi7fuqy2rWoakf4+9OryQnDm2nd9RYVCoVCsiExJI5mftSF4ZSBKuWossF/oqttmtVYw3zi0lIaJ89D7bM2Z/RbCDJ7N6yUIEC/NrgREqzLQ9wYSyQFz+4KxHtt8cSV1nfhXv4rUNMJf/jImx+r9yMx+H47e3lUfdz+gawbZRAmz1YQQglyydMf031xyyRInv38Tq8PM0Wc6MJlXLpKEgIYuLxbb3S8I0colIgN9aOXlLSLmosSVQqFQbBJDsdmoVdUw+PnVKfY2eecVrrvtFhq2k2koQDlXE1S3GH6j5sx+u3Gopx7Mm3dbqugV8tp0/ZuUWAeGuVgZxI2dLjHfGd0kBO7bVgqmv/tdKjduEPrN38Ta1LTq65scdhwHD95XBeyGIZG6xGQWS/bj03WDbKxEOlpcdvXfchQyFd7+3k0QghPP9uD0rC5VHGp2Y1+HllGVUpHxvisrjljdQokrhUKh2AQKlSpT2dm/fN8ZSpEsaHzhoc5547ZdrRXML2SXEgZegFAPBG6LDnk3zzgU5jdqNo9Fkaksl/QR9pvbMIn5gsdldSPmrAErnD5N7uc/x/PEE7geeGDV1xYWM45Dh+6bvoGGbpCJl8hEi+jTqTxPwE6gyYV1OjpUKVXJJcpkk6U7pvuWo5TXePv7N6hWDR7+eA/uwOpS5J7g+hSwG4bO5PWBVQsrUOJKoVAoNoWheGGmV9ot09BGr51DbbP99Fw2M42+bVZrJeV849DJi5AZg4d/Z/44sw3cm9tH75a4Epkc5tFJBmWMLCUOmDoWjJ1bb6VFIiT/6q+wdXfj/9SnVn9hk8Bx4MB9sTKwWtFJx4rkkuUFgimXKpNPlRFmgYAZ0XU35FJlTn7/BpWSzolnu1ctkuwuC3Wtd/++GobOxLUBKqXinQcvghJXCoVCscGUq/q8VjeXxjMMxgt86eFOTHMKoDvr3OvmHr1lyE2CNucG1fdjsPuh45H54wIdNUv6TUJKWStmr2hY+4dBSs7rwwgE+8ytC8Z7bDXfKqNQIP7f/hvCbif85S+vvkWNAEfvPiyh0Hq8jA0llywRH8svm9qTgFwHUQUQG81y5vlhhICHP96Dv2F1tYc2h5nGLt+S6cqVYug6kWv9lHKZNZ9DiSuFQqHYYEYSRYzp1f5SSr53bpyQ28Z7d8yahjqsZpp926zWCiAxp0VIdgLGz8CBT4F5Tj2MMIF/YQH5RpLVsmiGhmVwHLSaNcY5fZAdpka8Yn60xGqy4jA7akahX/861ViM+t//fcyBwKqv69izB2vj1rZcMHSD+FieXKq8KdeTUnLzbJSrb07gCdh54MNdq04F2p1mGrv8mC13J9D1am1VYLmYv+PY2Mjwks8pcaVQKBQbSFU3GE3OFrJfjmS4EcvzpYc7sZhnbwSdYdf2atAMUEhAKTW7PfBcLTq18+n54zyNC3sLbjDJUhKRyWGK1wrtY0aGUZngM+aHFoz1Tq8SzPzoRzWj0M9+FvvOnau+pn1HD9aWza0rWy3lYpXoUAZtGbf09UQr61x4aZSJ62madvg59GTbqlf4uXw26ju8d/3vp2a3cGVFqcDxgauc+v53l3xeiSuFQqHYQMZTpXkNmr93bpyQa37UymYx0RrYZg2aAZJzolZaEW68BO2P1HoHziU4v6h/M0gU41huztaCnTNqUYjD5oVz8Vi9FM+fJ/ujH+F65JE1GYXa2tuwdW7+61wp0pCkpgqkp4orsMi8ewxdMnw5zsDJSbSyzp5Hmug5Ur+qtLgQEGxy46+/+3870jCYuN6/ImF188xpzv30xwSblvbdUuJKoVAoNgjDkAwlZtMLlyMZrkfzfPGhju0ftarkIRed3b75Sk1g7fnQ/HF230KxtcFohkZu6CbmwuzqzbP6IC0iSIPJP2+sQOBI5ol9/etYOzoIfu5zq66LszQ2YN+1a13mvhGU8hqx0RxaWb/z4LtEGpLJwQx9b06QT5UJt7rZ+56WVQsks1nQ0OnD4VmfFlFTQzcp53PLjpFScvW1l+l741Uae3by4Mc+Df/pTxcdq8SVQqFQbBATmRJlrZZeuRW1CrqsvHdn3cwYi1ls06jVIDOO7NKA/ucgvLP2M5d7ELVKZqOYRydmtnOyxDVjgmcshxeMdepmkn/6ZwiLhfBXvoKwru5mbgkFt6xJqGFIUhMFMrGNj1ZpFZ3RK0mGLsQoZCq4/DYe+HAnDV2+VYtVm91MQ7dvxgLibpCGQXR4kFwituw4wzA499wPGbpwlo6DRzjyzC9hWmYBhhJXCoVCsUEMzWl1cyWS5Xo0zxce6sA6J2rVEXLNi2JtC6oVSI/NbkfO1+wYHvnd+ePM1k33tgJI9F2A6myU5oI+jIHkiLlr/kApcXz3Z1QnJqj7vd9b9Qo/c8C/ZU1Ci9kKsbEc1Q2qrdJ1g6nBDJM3MxSzGtlYkapmEGxysefhJhq7/atyXL+F02OlvtOL+S7/zUgpyScTJMZH7+i8nk8lOfWD75IcH2P3I4/S++gTdxSESlwpFArFBhDNlsmXa6vQpJR8/3wtavXonKiV2SzmubNvG1LDIOekmPp/Ao4AtD88f5x/c+0XAPRsluzIjXn7zulDBHDTIerm7be/fhZ5/jL+T34Sx549q7qO2evBefAgwnz30ZX1RK8aJMbXthLw1rGVYu1z7fLb8Ne7ZkSSlJJMtMhYf4qx/iRaScfmtOAJ2mneFaC9N0Sgce2fd1/YQajl7u1K8qkk8dERtPKd66tiw0O89T++iZQGx5/9JG29B1Z0DSWuFAqFYgMYjM/WWl2dyDIwlePzJ+ZHrdqDznnb2wLDgNTQ7HZmHCJn4eAv39baRtS8rTaZ9JXzaPqs43ZFVrlkjPKIedc8zzHL9VGcL7yF89hRPE8/vdiplsTkduM8fHjVKcSNJpcskRjPr8rsU6/WIlBj/Slio1mM6vxjzRYTTp8Vi9VMLlmiWjEwmQSN3T7aekPUtXnu2ndKCAi3evCG1r6itKpppCcnyCXjVCsrE5ZD589y9vkf4g4EeeTTn8MdXHnkUokrhUKhWGei2TLpQu0GPrfW6rFdc6JWpm0atcqMgT7bnJq+H4PJDDveP3+cp2HT7Re0yUmS0dF5+64aY1SozlslaEplcX/zBURDmOAXv7SqSInJ5cR59AhiC7W1qZSqxMfylPIrb+Ni6JLhS7Or+exuC+29IRo6fbj8tprxfrxEYjxHKa9RrRg07wwQanZT3+nF5lgfeWGxmqjv8OJwr02oGrpOMjJOOjqBNFaWApWGwaWXf861k29Q39XDgx/7NLZVNuVW4kqhUCjWmRvR2VVHfZNLRK1CTuyWrZUyWhfm2i/ko3Dj59DzJDgD88cFuzZzVkhdp3ztGtlydt7+s/oQDqzsMU3XfmlV3H/7HEI3cP/mr2NaxU3V5HTgPHp0y/QLlFKSniqSmpptvbQSpoYyXHk9Qj5Vpq7NQ8+xesItCyNQnoCd5h3+Jc5y93hDdoLN7jXXV1UrFSLX+qgUC3cePI1WLnP6B99l4voA3UePc/D9zyxbuL4USlwpFArFOjKVKZEtVWe2v3dunIBzftTKYhZ0hrdhg+bsRM2C4RYXvwOYYP8n549z14Nrc9u/VIaGqBTzFKqzN1pDGpzXhzlgbscizCAlrh+8imU8SuHzH6GtrXvF5xd2G84jRzDZt0ZvyEqpSmwkR7lYvfPgabKJEldeHyc2ksMdsPHAR7po6PRuaksmATh9Nvz1zjVHqwAqxQKRgX6q2spry/LpFG995+/IxqIcevpD9Bx7cM3XV+JKoVAo1gkpJdejc2utMvRP5vjVB9vnRa2669zbs9Yq2je7nZ2Amy/DrmfAFZ4/tm735k6tWKQyPEy2Mr9X3DVjkixFjpi6ALCfvIT9zFWK73sAx+FDCFb2OxJWC66jRzE5t4alRjFbYWo4u6DR8lJUilUGTk4yfCmO2Wam973NdB4IY9rEz6jFZsLtt+MLO1bt0H47pVyOyLU+DH3lwjI2MsTb/+NbGIbOw5/5VRq7d9zVHJS4UigUinViIlOaWSEI8P1zEfxOK4/vrp/ZZ7eaaA9uw1qr9Ahoc9IvF78FJgvs+/j8cd5mcPg2dWrla9fAkKRvE1cn9evYsHDI3IHl2gjOH71GZXcnpSeP02Bb4RwFOA4cwOTaGr/TTLxIYiy/It8qQ5cMXYwzcGoSvaLTsT/MrgcbsTk3RxpY7WY8QTtuvx2rfX1S5MVsholr/RjGyg1RB8+9w7kXfozbH+DhT38OTyh854PuwIa9g0KIduAvgSbAAP5ESvmfNup6CoVCcS+RUnJjTtSqbyJL32SWz90Wteqp92w/N3a9CvFrs9vpURh8HXo/Or/WSpg2PWqlTU1RjcbQpU5Bm/396NLgHf0mh8wdOGM53H//PHp9kPwvP43JbMZj867o/I7du7EEN9dhfjEMQxIfy5FLriwNlpzIc+HFUXLJMnXtHnrf23JXq/FWgxAQaHThr3eua8oxNREhPjYCK7RETUbGGHj7Dcb7rtDQvYPjz35qlYXrS899I+VpFfgjKeU7QggvcFoI8YKU8vIGXlOhUCjuCWOpIsXK7F/L3z8/Xota7ZqNWrntFlr8m7tCblNI3py/QvDCN8HigN6PzR/nbwfb5kV49FyO8pUrAOQqWYw5Vd19xjg5SjxSbsfz1z8Cs5n8Fz4CdhseqwezuHMkxdrairW1dcPmv1K0ss7UYIbKCtrX6FWDvjcnGDwfw+GxbnpdldVmoqHTt67RMa1SJjp4g2I2c8ex0jCIXOvj2sm3SIyNYLHZ2fOex9jznsdXVbhuNlto6Fm6efeGiSspZQSITD/OCiGuAK2AElcKhWJbYRiSm7HZqEj/ZJarE7Wolc0y+4W9o+HuDRC3HNUyJOasEEwOwshbsP9TYJ8T/TFZFra+2UCkplG6cAGp15bfZxZJCbp1Cw998zKmdI7sb3wcI1Cbr89+5xVw5mAA++573y+wlNeYHMysqL4qlypz5rkhsvESHfvD7H2k6a7rm1aK2Szw1Tnx1TnWrZarWqmQmhgnE4si5fI2C1q5zPCFs1w//TaFdAqXP8DB9z9Dx4HDWFe1CEHgq28g1NKG2bK0hNqUxKoQogs4Cry1yHNfAb4C0NGx+YZyCoVCcbeMJovzegh++51RArdFrQIuKw3ebRi1ig3Md2O/8E2wumHvL80fF+wGy+ZYFEgpKV26hFGstTWRGGQrsxYMmtQ5W73JH77gwDYYIf/p96N3NAG1Rs0+6/IpQZPLifPAgXsulPOpMtGR7B1tFqSUjFxOcOUXEUwmwQMf6aKxa+Pr3gRgd1nwhBy4A/Z1S4dLwyA2MkQ2HrujqNKrVa6dfJOBt35BtVIm1NrOgSefpnnnnlW3JXJ6fYTbOrC77rzSd8PFlRDCA3wb+H0p5YKYnZTyT4A/ATh+/PhG945UKBSKdUU35Dw39neGU1yP5vn1RzrnRa12NnjuxfQ2lnKuVl91i9gAjJ2GQ58F25wbkNm2qb5WlevXqSaSM9t5LY8+5yZ82RjlyZNlDp0pUnz8GJXDs3VgbqsLs2npW6OwWmptbe6x+3pqskBy8s7+TflUmQsvjZIYzxNudXPoqXac3rWLXJNJYLIIzGaBMJkQJpC6pFo1MAmB2WbC7rTgcFuxu63rXl+oVzUmrg1QymfvODYdneTkP3ybXCJO86497H74vQSbV5/GtTvd1HV04fCs/N/whoorIYSVmrD6aynldzbyWgqFQnEvGE4UqFRrN+6qYfCdd0ZpCTh4z45ZX6s6r52Aa2sYS64rsT7mFQ+f//taKnD3h+ePC++8rfXNxlEZHaUyPDJvX6Y8/+/6xNVzfOnnBuXebkpPnZj33LIpQQGO/fsxue+dR5k0JLHR3B17AxqG5ObZKAMnJzGZBQefaKWtN7TqaJvNbsYdsOP02bDazfd0MUalWCByrX9F7WuGL57j3PM/wmJ38Mgvf35N1goms4VAUzOBhqZVR7k2crWgAP4MuCKl/A8bdR2FQqG4V2i6wdCcqNWrAzEms2X++VM7MU/fhITYplGrQgJyU7Pb42dh8gIc/dL8tjY2z6b1ECzfuEFlcGjB/rn1VvrEFB/+7hixRgfWT78f5ogFkxAEbEuLK/vOnVhCm2t+OhddM5gaylAqLO/flE2UOPezETLRIo09PvY/1rpqQ06b3Uyg0YU7sEVMUYsFxvqu3NG7ytB1zv/sOQbPnqauvZPjz35qVRGnW3jD9YTb2jFb1hah3Mg/Jd4LfAm4IIQ4O73v30gpf7SB11QoFIpNYzhRoDpdSFzSdL53bpzdjR4Otc7eoJv8Djz2bWgpONcw1NDhzF+Bp6lmGjqXhn01hbmBSCkp9/WhjUcWPFfQ8mhG7YZsSmZw/PUPKdpg5Fcfo8c2/8bptfqWTAlaGhuwtbev/+RXSKVYZXIwQ1VbusZIylo/wCuvR7DYTBx7ppOmVbSnEQLcATvekOOu3NHXG61SZnzgzqaglWKBUz/4H0zdvM6uE4/Q+/hTq25dI0wm6to68dU33M2UN3S14GssZwKhUCgU9zGVqsFwYrbm5blLE2RLVf75U20zqReTCXbUb8OoVSYCpdTs9vWfQ2YUHvuj+ek/bxO4796QcTmkrlO6dIlqLL7o88lyrfZKpLJ4vvY9tHKF//tXXfyzQM+CsQFHYNFzmDxuHHv3rtucV0s+VSY2msMwli5LLherXHhxhKnBLPUdXg491YbdtTKBZLYIfGEn3rADs2VrdQ6olIpE+vvQtcqSY6SUjF25xPmfP4dWKnHkmY/Sdfjoqq/lDoQIt7Vjtd/9wpNt+OeUQqFQbDxD8Tz6dNQqVajw/OVJjncG6ambFVNtQRcO6zZrzmwYEOuf3a4UaisEG3qh9fjsfpMF6ns3dCp6Lkfp8mWMXH7R5yUG6XIGkc7h/dr3EKUy//vnzLS17sIk5osIq7DgXcQ4VFgttZWB5s3/PRqGJDGeI5tYvsYoOpzl3M9GqFZ09j3aQufB8Ipqq8wWQaDRhTfoWNCUeStQLuSJ9F9FXyZilYlNcf6nzxEbHiTQ1MzRX/ki/obGVV3H7nJT1766gvU7ocSVQqFQrJKSpjOaLM5sf/98hKou+eTR2ZVIFrOgazs2Z04NzW9zc/m7UM7C0V+bn/4L75hfe7WOSCnRhoYoDw7CMtGcTDmLkU7j/dr3MBVK/OyLvQw0XOJzlj0LxgYcAcQiyRZHb+89aW1TymvERnNoyxiDSim5dmqKgZOTeEJ2TnysG194Zf0NPQE7oVY35i3a47KYyzIx0LdkGxutXKbvF69w/fTbWGw2Dn/gI3QdPrriwnOzxYrLH8AbrsPpXX9bCiWuFAqFYpUMxvPo0zf1SLrIqwNRntjTQKNvVkx0ht3zrBi2BboG8euz27kp6PsxdD8Goe7Z/TY3BLo2ZApGPk/pyhX0zJ2X4qf6LuD92+9jKpbIfOmj/EPDK3TTQJtpYaoy4FjYwsbW1YWlrm7B/o1E1wwSkfwdVwNqFZ3zPxth8maG1j1BDryvdUUpPSGgrs2DJ7h1PdcysSix4cElPawmb17nzI+/TymXpfPQUfY9/hT2FQpgu9tDqLkVp8+/oT5lSlwpFArFKihUqoynZqNW33lnDJvFxLOHmmf2OaxmOkJbo5HvuhK/DoY2u33ub0CY4dDn5o9r2F8rOFtHpK5TGRqiMjy8bLTq1tj0D76P6fkXMAIesv/oY1xt0pmspPl16/sWjHdZnDjM88WGpS6Mvad7wdiNJJ8qExvL3dFtPTaa5cKLo5Ry2urSgGZBQ5dvSxWrz0VKSWJshNTkwoUJAIZhcOXVFxl46xf46up56JO/vGLfKqfXh7+hCXdgc/pAKnGlUCgUq2BgMocx/Qf1wFSWMyMpPnGkBa9j9oa1q9EzY8WwbagUainBW0T7YPhNOPAZcM2xJ9iAInZtcorytQFkeemi5tmxkyS+9jW04WEqR/dS+Mh7wW7j1crPcWLjuHmxQvb5N1yTy4Vj3751m/+dMHSD+NgKolVlnatvRBi5nMAdsPHQJ3YQal5Z6tnhtlLf7tm0djerxTB0pm5cJ59OLvp8MZvl5Pe+TWJshM5DRzn0/mcwr8DI1WyxUtfRhSe4uRYaSlwpFArFCknmK0SztRuglJJvna61ufnAvtkC2oDLOi89uG2I9cOtNI004MxfgjMIvR+dHSPM61rErudylPsH0FOpO46tjI6S++lPKZw6hcnpRPv8RynsrVkn5GSJd/SbPGbuxSbm3/ZMQhCYYxwqLGacBw8glukbt15IKckly6QmC8taLECtaP3Ci6OUChrdR+rYfaJpxWnAYJMbf/3KarHuBXpVI3Ktn3I+t+jz6egkb37rb9FKJY5/9JO07TuwovPWvKo6lu0BuFEocaVQKBQrpH9yts7nVpubX3ukE7ulFg0QAnY3Ld+X7r6kmILsnFTN8Ju1FOFD/xQsc4TkOhWxG8Ui5Rs3qE5OLTtOSkm5v5/sCy9QvnwZYbfjeeIJbE89znVjcmbcG9V+qhg8Zllop+C1+TDfElwCHPv2bbgDu6EbFDIVUpMFtMryoqqU1+h7c4KxviSeoJ33fGgngcaVpZzdfhuhZveWjVbVxGWcxNjooq7rUkqGL57nwk9/gsVu59HP/zqBxqY7ntditVPf1Y3Lt3KPr/VGiSuFQqFYAeOpItlSbUl41TD4zplRWvwO3junzU2z34nPsTXrWe6K6NXZx7oG5/62VrDe/djsfquz1pz5LpCVSq2uamxs2boqqesUz5wh+9Ofog0PY/L58H3sY3gefxyTy8VEfgKmy+KklLyqX2WHqZFW08LUUJ1jNoXp2LNnwwrYdd2glNXIp8sUMpU7NlvWqwY3z0a5/k4Uw5DseKCBnccbVrS6z+YwE2px4/RszZZLWqlELhknG4+hlUuLjikX8px97odEBvoIt3dy/KOfWNGqPpcvQEN3z5qd1dcLJa4UCoXiDuiG5Hp0NmXx6kCMycz8Njdms2BHwza0XshOQnFOHczAC5Cfgif+Dcz1iqrvXXMRuzQMtNFRKoODyOrS1gNGpULhjTfI/vSn6PE4loYGAp//PO6HHppppCyRpMqpmWP6jQiTMs2HLUcWnM9lceGy1n5n9h09WFta1jT/JedrSHKJEvl0hXJe4w56CoBqRWfoUpybZ2NUilUau33sfU8zbv+d29CYzIJQsxtP0L6hK+FWizQMCpk0xUyaQiaDVi4uPVZKRi9f4OJLP0Urldj/xNPsfPDhO74em8NJuK0Dlz+wzrNfG0pcKRQKxR0YiucpT9fELNXmpqfOPZMe3FbMMwzNw6XvQNMhaD40u99VB97VGTfeoppIUO4fwCgUlhyjZ7PkXn6Z/MsvY+Tz2Lq7CXz60zgOHVrga5SrZNHmrGh8Rb+CCzsPLFLIXuesRa1sHe3YOjvXNP/FMAxJNl4kHS2iV1ciqSCfLjNyKcHIlQRaWSfc5mHX8QZCLSsztnR6rdS1ebBsIdNarVwiE4uSjUXRq9qyYw1dZ7zvCtdOvUlqIkKgqZn3/MoX8Ncv/7kSJhOhlnb8DY1bSlAqcaVQKBTLUNJ0huKzN/6fLNLmxmUz0x7chtYLmQhU5hQZX/5eTWAd+fycQQIaVt8axiiVKA9coxqNLjmmGo2S/dnPKLzxBlLTcBw8iPcDH8C2Y8eSN9JYMTb72Mjwjn6TpywHFhSyW01WfHY/to527Dt3rnr+S5FLlkhE8isSVYYumRrMMHwpTmw0hxDQ0O1jx9GGFddVCQGhZje+uq1TsF7MZUlFxilkUnccW8rlGDz3DoNnT1PK53AHQhz98MfoOHDojmLJ7nLT0L0Dm2PrvPZbKHGlUCgUy3A9mpsxDJ3KlvjJxQlOdIXmtbnZ2ejBtN2sF6SE+MDsdj4G/T+Crkch2DW7P9gJ9pUX8ctqlcrwCNrIMFJfvJi7MjRE9oUXKJ45AyYTrhMn8D79NNbm5kXH36Kg5clps61wnquew4TgacvBBWPrgq24jx3DHAiseO7LUSlViY/lKeWXj9AAFLMVRq4kGLmcoFyo4nBb2XWikfbe0Ko8qGx2M/WdXmyOe38rrxQL5NMp8skE5cLi7YjmkoyMcf3024xdvYw0DBq6d3Dk2Edp7Nl5R1ElhIlAUwvB5pYtFa2ay73/jSgUCsUWJVPSiKRqBbdSSr7x9ghmk+BXjrfNjAl5bDR4t6H1QjZSi1Ld4sI3a4Lr0K/M7jNbIbyyqI+UkmokQvnGTWRloV+VlJLy5cu1lX/9/QiHA+8HPoDniSdWLICixdkoWFLm+IXez3vNewiKObVwQkBzA60PfRDzOqxslIYkNVUgHS0uW6QuDUl0JMvwpThTQ1mQUN/hpeNAmPoO76rEudks8Dc48YadGyrqDV0nG49SyuXQSqXpVjQCkEgpMZnNmC1WtFKJqra8R5eUknwqSWSgj9ErF0lPTmCx2eg+epyeo8fxhFbmjWZ3e2jo7Mbm3NqRYiWuFAqFYgkG5lgvnBtNc2Esza8cbyPgqq3CEgJ2N25D6wUpITYnapUcgpuvwN5fAnf97P66PTWBdQeq8Tjla9cx8gsjGlJKSufPk/nhD9FGRzEHAvg/9Snc730vJufK0z0lvUSmMvv7el67gIHkg5bDYBIYPg9GyIcR9NEa6sK2DsKqmKsQH80ta6dQLmiMXEkycjlOMathc1rYcbSB9n0hXL7VreazWEz46h0bKqoMQ6eYyVBIp8gl4kv29lsp2XiM4QtnGeu7QiGdAiDQ1Myhpz9E+/5DWO13LtQHMJnMhFrb8NVvrdqqpVDiSqFQKBZhKlsiOZ3iKVd1vvH2MC0BB0/tbZgZ0xp04rFvw6/RzNj85sznvgE2F+z/xOw+uw/8bQsOvYU0DKqTk2ijo+jZheaQM6LqRz9CGxnBUl9P8EtfwvXgg2sy8IwVpqNWFgtpe5VXS1d5yH8Y/45DVLxumLYwEAjavEvPeyXo1en+f8mlozWFTIXr70wxejWJNCThVg97H2mmsduHaZXNkm12M756J56AHbFBoqqQSZONRcmnk0hjee+tO6GVy4z1XWb4wlkSY6MIIWjo3snOBx+msXsH7lW6pbv9QcIdnVhtKxNiW4Ft+K2gUCgUd4dhSK5NzgqCH1+cIJ6v8D9/cA+W6dVpFrNgR/3KVnLdV0gJ8Wuz2xMXIHIWjnwBbHNeb0NvLXR3G0a5jDY2jjY+vnj6zzAonjtH9ic/QRsZwVxfT/DXfq0mqswrW+km7DbMXi8mjxeTx03ZAlNJHWlpA5OJ56/9A9WYztO9zyJd8yOL9a56nJa1F0DnkiUS43n0Jfr/FbMVrp2eYvRqAoGgfV+IroPhVTdKFgLcfjvekAOHZ+M8mwqZNInx0SXd0VdKVdOIDt5gfOAq431X0DUNTyjM/ieepn3fQRye1f1bEcKEy+fH39i0In+rrYYSVwqFQnEbo8kihUotHTKZqRWxP9QdYs8c9/Ud9R6sq4xA3BekR0G75cBpwNm/qVkt7H5mdoy7YaafoJQSI5dDTybRk0mqyeSiBqBGqUT+jTfI/fzn6PF4TVR96Uu4Tpy4o6gSZhPmUAhLfT3mUAiTbX467WayH2mr3c7yWp5Xx17lWOMxGlwN88aZhIke/0JLhpVQymkkJwtLFqxrZZ3r70wxeD4GEjr2h+k5Wr8qI0+TSWB3WXAH7Lj8thUZhq4FKSX5ZILU1MQdRZVhGGSiUyTHx8gl4xTSKaqahjQMzBYLZouFfDpFJjqFNAwsdjttvQfoPHiEYEvriorTLbZaRM5kMmOx2XD6fLgDoXvStma9uH9nrlAoFBuAphvciNVuOFJKvnFyGItZ8MsPzKaS3HYLbcGtt/z7rjGM+VGr4TcheRMe/h0w25CGgSxXMbxhjNHRmqBKpZBadclTVuNxcq+8Qv6115DFIraeHgKf+hSOw4cXeFTNRZhNmOvqsDY0YA6FlhRgFb1Sc2Sf5qWRlyjrZZ7pfGbB2DZvGw7L6iJIhUyF9FSBUmHx12joBkMXE1w7PYlW0mndHWD3Q004vXcWVRarCafXhtNrxea0YN3gNjXFXJZ8Ik4ulUTXlm6CLaUkPjrMyKULjPVdplqupT/NFgsufwCL3Y4QJqqVCrpWweHxsvPBh6nv7KauvRPTCiKQLn+AQGMzDrdn2c/B/YoSVwqFQjGHG9E81emUz9mRFBfHMnz2ePtMETvA7kbPfVFUu2rSI1AtIbUqei6P+cw3kM4mSoUWjDN9NRHlCkHi5rKnMYpFiu+8Q/7tt6kMDIAQOI8exfP+92PvXr5FjjkQwNrUiKWhYUW1V8OZYYzphtLZSpaXR1/mUP0hmj3zbRtsZhud3pUZhepVg1yyRDZRRisvXtAtpWTiepq+NycoZCqE22o1VXdqkGwyCdwBO96wA7tz42/BhqGTS8RJT01SKS5t1Aq14vORS+cZuXyRYiaN2WqlZfdeGrp3EGppw+UP3NXn3mp34A6G8IXrsTq24QrbOShxpVAoFNMUKlXGUrUbULmq842TI7QGnPOK2Jv8DsKe+6ewdiXouTzVqUmMKy+i57LIShVr5gyWYpRS06+g56cLt4UA3+ItYoxikXJfH4XTpymePw+ahqWhAd+zz+I6cQJLeOml9sJmw9rSjLW5eVUrBPNanrHc2Mz2j27+iLJe5tmeZxeM7fH3YDYtHVGRhqSQrZBPLd/7T0pJbCRH/9sTpKeKeEMOHvxoN3Xtywvu2ko/J96QfdUF7WtBK5fIRKfIxKIY+tKRxXI+z+jVS4xcOk9qIgJC0NDVw77HnqR51x4strvrT+j0+nEHArh8gW0vqOaixJVCoVBM0z+Z49ZCqR9dmCCRr/Avn9kz0z/QajFtG+sFo1BAm5ykOhWtWSTkJiE93UPQqGJLvIJub6Xq2j17kLsezDVhKXWdyvAw5StXKF25QuXmTTAMTG437ve8B9eJE9i6upYVHOZgAGtLK5b6ujWlhgaSA8jpjn3juXFeH3udx9sep8ndNG+cx+qh0bV4G5VyQSM73f/PWKJIHWZF1cDJSVKTBRweKwefbKNtT3DZFXxmi8Bf78IXdmzYSr+5FLMZ0pMT5NMpWKKboV6tMnGtn+FL55m6eR1pGPgbmjjw5Ado6z2w6uLz27HaHbh8fnwNjVvSPX0zUOJKoVAogKlMiVi2FqGZyJR47tIEj/SE54mpPY1ebJb7tz5EVipokQja5CRGbo7nlDRq4moaa+YUJj1DoeFjMysC9XyJSjRKZeQslaEhKjdvIotFEAJrezvep5/G3tuLfceOZdN5JpcTS0MD1sZGTO61N7qeKkzNNGiWUvLtgW/jtDj5cPeHF4zdGVjo+q2VdRKRPIXM0rVHAFVNZ6wvxdDFGLlEGYfHyoH3tdK2N7hsBGomUhV2bKjRpzQM8qkk+VSSYiaNvkSUqlZHNcLIpfMzdVS3aqXa9x/EV9ew6HG3I4SpVlM15/00WyxYbXacPh+uQPC+skzYKJS4UigU73o03eDqRM2AUkrJN94axmo28Zk5Rexhj40m//2Z1jDyeSojI2gTE4uu5CMfBX16FZxRxpp4nXyxk/TFPOXhn6KNR9Gz0/U6JhPW5mZcx45h37MH+969mO8Q6bglqCwNDXccuxJ0Q+daarbw/mLsIv3Jfj6z6zO4rfMFW5O7iYAjMHts1SA1WSAbLy0R16l9BlITBcb6U4wPJKlWDHz1Tg4+2Ubr7sDyospmwl/nxBva2EiVXtXIRKdIR6eWLU6vahqjly9w/fTbZGPR6TqqXjoOHKKuvXNFEUOb04XLH8Dp9eH0eLdlAfp6o8SVQqF419M/maVSreUD3xlOcSmS4VcfbMfvrPkLmc2C3ub7z2unmkyijYxQjcWXHiQNZCZCNZqkPDhOZeACkTEfekUD3sIc8GLvbMG69zC2zi6s7e0LrBAWIMDs92MJhTDX1a2LoJrLUHaIil4TFFWjynevfZdGVyOPtj46b5zT4mRnYOf0y5SkY0XSU0WMxQQmkEuUGBtIMT6QopipYLIImnr8dB4IE2h0LZvitDvN+OtduPy2DVvsIA2DcqFAJjZFLhFHysXNPmvicJyhC+cYvXKRarmMv6GRox9+ltY9+1ZUR2W22vCG6/DV1WO1359/VNxLlLhSKBTvauK58kz/wLKm83cnR2gPOnliz2yaZGe9B4d1Y5fJrxdSSqpTU2jDw4s6o89Fi0QovPEyxTPnqMbTAFjdOq5OO5be92DvbMbi80CgY37bm0UQVgvmYAhLXRhLKIS4y0LopShoBUazozPbr4y+QrQY5bcP//a8gnWBoDfci8VkIZ8uk4jkqS7SpqaU0xgfqEWoMrESCKhr87DreCNNPT4sd7BHsLssBBpcq25lcyf0qka5UEArldBKRcqFAuVCfklBBZCJTjF69RJjVy6RTyUxWyy07Oml89BRwm0ddxR9JrMFdyCIJxTG6fVtzxWxm4QSVwqF4l2LbsiZdCDADy5ESBQqfPnx2SL2gMtKe2hrN4mF6XYzExNUhocxCsUlx1VjMQqnTlE8fRptrLbSzt7ZjOfEAXzBQVzGSQrt/wTDNi0uLXZw1y16LrPXgzlcE1Mmv39TbsbXUtdmrBcy5Qw/GfwJ+8L72B/eP29cl78Lc9HO+FCKcnF+HZI0JFPDWUYuxZkarjVR9jc46X1vCy27/Nhdd3ZEd3qs+Oqc6yKqDF2nlM9Rzuco5/OUCvllU31zySUTjE0LqkwsCkJQ39HFroffS+ue3mWjTkKYsLvcODxenD6V8ltPlLhSKBTvWq5HcxSnndgj6SLPX57kPTvC7GqoFbGbTGz5dKA0DLTxCNrwEEZp8V53UtcpnjtH7qWXqFyr1SrZenoIfPxDODuDmL0uRDWLa/i7VD0HZ4UVTFsv1ETTTHQqHMIcDt85PbjOxIoxEqXEzPY3+7+JZmh8auenZvZJKXFV/JgjXqbK2XnHl4tVhi/FGbmUoJTXsLss7DhaT+veEJ7AnYuwrTYTnqADT9B+x4jWndAqZQqpFPlUgmI2y1Ir+xajkEkzdvUyY1cv1ewTgHBbO4ee/hAte3pxuJdOw5otVrx19bj8ARwutxJTG4QSVwqF4l1JuqgxkqgVaeuG5Ou/GMRuMfGZY7NF7N11HtxbtDGz1HW0sTEqwyOL9vAD0LNZ8q+9Rv7VV9FTKczhML6PfxzX8eNYggGYvABGTVzakq+CNCiH3jd7ApsLU307lnAYSzi8adGpRV+LoTOQHJjZPjt1lrPRszzb8yyN7sZaOjQLespMq7sZzTSbPsslS9w8F2OsL4mhS+raPPQ+2kJjlw+TefnXYzbXTD/dATsO99p6/EkpKeWyFDJpyvk8lWIBvbp4G53FMAyDVGSc6PBNJm9cJzE2AkCgqZn9TzxN6959uHz+Zc9hd7nxNzbhCYSUoNoEtua3hkKhUGwghiG5PJ6ZMYr80YUI16N5vvJYD77pInaPw0JXeOulA2WlQmV0DG1sDKktfoOuDA6Se+klCu+8A9Uq9t5eAp/7HI4DB2ZvrNnIjLASWgJr5gya7xjSWotkWQJeLAefwhRu3ayXtixD2SHKei0yl9fy/H3/39PmaeOp9qfQMpJKEowydPhasZqsGIYkOpRh+FKC6HAWk1nQuidI96E6PKHlC7RNJoHLZ8MdsOP0WNe06k+vVimkUzWLhGxmWSPPuRiGQS4eIzUZITURITUZIT01iT79u/Y3NNL76BO09u7HEwwt/zqma6i8dfU4PdvDn+1+QYkrhULxrmMwnidfrt3srkdzfP/8OA/3hDjRXbtZCQH7WrZWQa9RKFAZGaE6MYHUFxY1S8OgdO4c2Z/9jMqNGwiHA8+jj+J+/HGsTU23nUyf52tlj/8cTBbEoU/jbmzDZLPWmjNvEWF1exH7dwa+Q76S58vd/5TSiBk5HbgLOoJYK076z00wciVBOV/F7rKw68FGOvaHsbuWvuUJwYygcnltaxRUGvlkklwyQSmXXbb4/BaVYpHE+CiJsRHioyOkJsbRq7XPptlqJdDYVCtIb22nrqMLu2t5wW+22nD5/LgDQVw+v4pS3SOUuFIoFO8qcuUqg/GagWZJ0/nqqzcJumx8/kTHzJiOkAufY20poPVGT6epDI9QjUUXLcsxymUKb7xB9sUX0aNRzOEw/l/+ZdwPP7x0K5n8FBg6Zq8LqzmG9foVOPjLWNtv9f0TUL978WPvAQOpgZki9ouRS7w98TZP+D5IXb4NSa1AvTplY3yowrnhqwDUd3jpeDxEfadvSRNPi8WEw2PF5bfh9NrWZPYpDYNcKkE2Fr1j7ZSUknwyQXxshMRYTVBl4zEAhMlUE1KHjxFsaibQ1IwnGF6RODJbbXgCQdyhsIpQbRGUuFIoFO8apJRciWRmWtx84+1hYvky//KDe3DZal+HLpuZnvr19WVaLVJK9FiMysgIeiq96Bg9nSb30kvkXn0VWShg6+7G//GP4zxyZNkbstnjwmIRWHp2Y7Ja4IU/B2cQ9v7S7CBfC9i3xk16qjBFIp9Ay9Zqp/5u+O+otzTypPcZqnlJ7ibkB0EvVrC7DHY+0ED7vhBO78JieyHA6bXh9FhxeKzYHGu/BVY1jUx0kkx0atn6qXKhwNTgdSZvXCc6eINyoSbsrXYHodY22vYdJNzaTqC5BYt1ZYJeCBN2tweXz4fLH8DuWrvTvWJj2DBxJYT4c+CjwJSU8sBGXUehUChWymiySLpQuxGeGkrw+vU4Hz3YzK45LW56m30zNgybjaxU0MbH0cbHF135J6WkcuMG+VdeoXDmDOg6zsOH8bz//dh37FjyvMJqwdLYiLWlFXMpAvHpFXfDb0J8AE78E7BM1yEJM9RtjahVLlPifH8/xQwg4UfJ75GpZviK/q9IvmahNFEb52+1s/NQ06JRqpl0n9+O02u966bJWrlEanKCbCy6ZNqvlMsxPnCV8auXiY0Og5TYnC4aunuoa+8k1NqON1y3qrSzxWqvNUAOBHF4PJiWaUKtuPdsZOTq68D/DfzlBl5DoVAoVkRJ07k2VTPVTOQr/OUbQ3TXufno4eaZMa1BJ0H35toLQC0KpY2NoU1NLdqexiiVKJw8Sf6VV9DGxmbqqTxPPomlfmlzT3PAj7WlBUtDQy2aVa1AZHD6ohqc+xvwd0D3nBWCwU6w3jtHbmlIcqkymViRodgIxWJNDN9MDqJf8fIbsf8Dyk40B/h6oXGPl10t3fPOcasg/W7SffPnZFDMZsjGY+SSCRZL/RWzWcb7rzDed4X46DAAnlCY3Q+/l6Yduwk2Na+q/slis+Nwe3B6fTg8HmzOrbe4QrE0GyaupJSvCCG6Nur8CoVCsRouRzLohsSQkq+9fhPdkPzWo91Ypm94LruZXQ2blw6UhkF1chJtdHRJJ3UtEiH3yisU3noLWSphbWsj8PnP43rwQUz2xX2ZhNWCtakJa0vLwsbIsT4wplNYA89Dbgqe+Nc1Qy8AkxVCPev1EleFrhlk4kWyiRJ6VVLUisTycYoRSfaGgWmigwfowNEk8faAsxmsFis9wfba1OcIqrUWpM9FSkkxmyGXiJNPJRdd7adXq0T6rzJ4/gyx4UEAvHX17HnP47Tu7cUbrl9RdMpqd2BzurC7XNhdbuxuN2bL1qj5U6yNe15zJYT4CvAVgI6OjjuMVigUitUzniqSyNWWlL1weZIrE1l+7ZFOGn21CI3ZLDjUFsBylymjlaDncmhj41SnJpHawhu2UShQPHOG/Ftv1Qw/LRZcx47hfvxxbN3dS96szV4P1tZWLI2NCPMiKaNSGtI1R3YqObj0HWg6DM2HZ8eEe8C8uTd1raKTidZE1S1rjEpR48LpmyQHJHoRNHuZc60vc2jvbjpDs+nPNl8bvqCrZpmwDhEqqKX0colahGqpWqr01ARDF84xcukCWqmIyx9g73sfp3XvPrzh5dsEmcwWnF4fLp8fm8uFzelUKb5tyD0XV1LKPwH+BOD48eMrt6hVKBSKFVCu6vRP1py6hxMFvnNmjKMdAR7bOdvSZV+zD88GmoXKarUWpRofXzRKJTWN0qVLFE6epHjhAlSrWBob8X3iE7gfeQSzd4nicpPAUl+Pra0Ns395E0mmrjCTzrr0XdAKcPQLs89bHBDoWtPrWwuVYpV0tEg+VZ5JsmXjJQbPxxjtTyB1cDSAcTDK10z/H455TrAzuKPWFNoF7Y3N7O/ovOsaKgCtVCKbiJGNx6hWFne5r5SKjF6+yPCFc6QmI5jMZpp37qHz8FHqO5cWvQA2pwuXL4ArEMDh9mwpiw/FxnDPxZVCoVBsJFcjWaq6pFI1+NNXb+CxW/j1h7tmbnAdYddMBGu90VMptEiE6tTUAm8qKSWV69cpvP02hXfeQRYKmLxePI89huuhh7C2ty95Eza5nFibm7E2N6+sQXJmHIrJ2uPcJPQ/B91P1Boy36J+72x6cAMpZiuko0WKuVpUSErJ1FCWwfMx4qM5TBaBuxM8O8Hk0/njqT/Ho3v4SN3HsQXB6gOv08P+xt2YxN3Nt5BOkZyIUMplFn1eSkl06CZD588SGbiKoev4Gxo5+P5naN93YMk6KCFMODzemtdUIIDVdufWOorthRJXCoVi23JtKks0W4tEfOv0KJF0iT94ehee6SX4Qbd13eusZKWCNjGBFpnAyOfnP2cYVIaGKL7zDsUzZ9ATCYTNhvPwYVwnTmDfu3fxlB7TK/4aGrE2Nd45SjUXQ4fo1dntc39bWxF48Jdn97nqwNe88Nh1QhqSfLpMOlqkUqq5wlcrOqNXkwxeiFFIV3C4rex5uAmjLUdZ1N63n2VeYEIb5zd3f5n6tlr9mEmY2Bfet2ZhJaUkn0qSioxTLuYXHZNPJRm+eI7hi+cpZtJYHQ66Dh+j4+BhAo1Lv08OtxdvXR3uQAizRd1e381spBXDN4AngDohxCjwb6WUf7ZR11MoFIq5jKeKDMZqvQPPj6b4ed8UT/c2sL+lJkzsVhMHWtenV56UEj2RQBuPUI3H5q34k4ZB5cYNimfO1ARVKgVmM47eXnzPPovz8GFMjiUiZyZR6+vX2Iilrm5tbtuJG1CdTnXFBmD4DTjwaXBNt04RJmjct/rzrgBdN8jGS2RjJarVWuQulygxdCnOWF+SasUg0Ohi94kmmnr8ZLQ0o9k8wgJTtlFeGnueYw3HONJ2aOacPf4e3Na1+TpVSkWmBm9Qzi9MzRq6znj/FQbPzRanN3Tv4MAT76dp554lxZLV7sQbDuMJhbHa790qS8XWYiNXC/7qRp1boVAoliOZr3B1opbqyRQ1vvaLQVoDTj493ZTZZIJDrQHslrsrJDaKRbRIBC0SQZZnmydLw6By7RqFM2conj2LkU6DxYJj3z58H/84zkOHlnRPF2YT5mCwJqrq61eW9lsKrQiJm7XHehVOfnXaMPTZ2TGhHWBbXxPKSqlKJlYklywjJRi6ZPJmmqGLcRLjeUwmQdMOP12H6gg01lJrulFlSo/gaALp0vjb0/8dt9XNr+z5lZnzhh1h2rxtS112SaSUpCYjJMfHFnhTFdIpBs+9w9D5s5QLeVz+AL2PPkH7gUNLNkM2my14wnV4w3XKwFOxKCpuqVAothWFSpXzY2kMo3ZT/fobgxQrOv/iA3uwThc/72rw4netbVWcNAyq0WitOD2Zmt2v65SvXaul/M6exchmwWrFuX8/zqNHcRw8uGSESthtNTFVV4c5GFwyNbhqpq6ArKXhuPxdSA3BY/9i1sfK6lo36wUpJYVMhWy8NFNPVcxWGLmSYORygnKhitNbS/217Q3N9PkTAjxBO6OMY5c6IPjOwA+I5CP808P/dCZKZTPZ2Bvau+p5lQsFokOzzui3SIyPcu3km4z311KmTTt20X3kARq6dywazRTChMsfwBuuw+UPqKJ0xbIocaVQKLYNmm5wdiSFNp2C+sH5COdH03zuwXZag7VIUZPfQXto9YaMejZbS/vNsVCQuk65r6+W8jt3DiOXQ9hsOA4cwHnsGI59+xYXVALMXi/mUBhLXRizz7f2F70UhcRsc+bEzdoKwa7Hoe347JjG/XddxK7rBrlEiUy8RLViIKUkNpJj+FKcycEMSKjv9NJ5IEx9u3fGf8pmN+MNO3AH7URLU6QSNdf4/mQ/L468yKOtj7IvPJuu3Bvei3UVNhGGrpMYHyU9NcmtVZJSSiIDfVx7+w0S46NY7Q52nXiE7qPHl4xSOdxevOE63EFVR6VYOeqTolAotgVSSi6MpSmUa5GaFy5P8g/nxnmkJ8xTexsA8Dgs9DavXMjISgVtchItEsHI1SIfslql1NdXi1CdO4csFBB2O46DB3EdPYp9/35Mi6TyTC4n5mCwlvILBhEr7CO3JqSEqcu1x7oGb/4xOPzwwK/NjvE2g7tu8eNXQC31VyKXrPlTVUpVRq8mGb4Yp5CpYHOa6TlST8f+MC5f7f0QAtx+O96QA4en9vqL1SIDyYGZx391+a+od9bziZ2fmLlWu7edkCO04rnlEnFio8PoWmX67ZBM3rjGlVdfIj01gSsQ5OD7n6Hz4BEsi/yuzGYL3rp6fHUNWJeqh1MolkGJK4VCsS24OpGdMQp9dSDK350a4VhHgH/0ni5MQmAxCw61+e/YN3CmOD0yQTUWBUPWaqiuX6/5UJ05g5HPIxwOnIcO1SJUvb0LxJKwWmtCKlQTVEvVWG0IqWEo17y9uPhtSI/A+/4V2KZXRpqs0NC76tPenvqTUpKeKjJ0MU7kWgpDlwSbXew60UjTDj/m6TSsxWbCG3LgDTowW03zznc1cRV9OnX5zf5vkq6k+YNjf4DdXLMv8Fg9dPu7F05mEbRSiejwIMVseub8seFBLr/6IsnxMVyBIMc+8jHa9h3EtEjEzu50429qwhMIrW3xgEIxjRJXCoXivmc4XmAsWQTg7ZsJ/vKNIfa3+PjyYz0zYmp/ix+XbemvvNuL06WUaGNjNUF16hR6MllL+R0+jOv4cRx7984XVCaB2e/HEgphDoWWNv7caMpZiPbVHsevw5Xv1TytWo7OjqnbCZaVey/dnvqragaRgSRDF+NkYiXMVhNte0N0HAjhC9dE5K2GybeiVIvVKI1mR0mXa0LozNQZTk6c5MNdH6bL3wWs3HZBGkatYD0yPlOwHh8d5sqrLxEbGcLp9XHkmV+i48BhTIvUszm9fgJNzUumBhWK1aLElUKhuK+JZssMTNWiNOdHU/zZazfZ2eDhd57YMVPA3l3vpt67UExIKdFjMbSxMarJJEioxuMUTp6kcPIk1UgETCYc+/bh/8QncBw6NK+nn8njnhVTfv/6FaKvFUOH8TO1Ina9Am/+F3AG4NiXZsc4/BDoXNHpysUq2fjsqr9cosTwpTij0zYK3pCD/Y+30ro7gMVWe+02hxlvqFZLZV7GPT1XyXEzU1vJGC1E+Zsrf0OHt4Nnup6ZGbM7uBuXdfn6uEImTWx4CK1cE9fJyDhXXnuJqZvXsbvdHHz/M3QdPragXkqYTHhDdfjqG7G7VFNkxfqixJVCobhvyZY0Lo6nkRKuTmT445eu0x5y8ntP7ZqxWQh7bPTUzV8ub5RKaOPjM1Eqo1SicOoUhbfeonL9OgC2HTsIfO5zOI8dw+yppdOExVwrQq+vrepbrLbqnjJ5ESrTq+IufAsyo7XGzLesFoSpVsS+zEq3W4afmXiJcqE6Y6MwfClOfCyPMAmad/jpOBAm2ORCCIHZLHAH7XiDDmzOO99WdEPnSuIKhjSo6BW+evGrmISJf3zgH2Oe7rPX7G6myd205DkqxQLxsREK6RQA6alJrrz2EhPX+rE5nex/4mm6jx7Hclu61mp34m9owBOqUwXqig1DfbIUCsV9Sbmqc24kja5Lrkdz/OefX6PBZ+f3378b53QUJeSxcaittmx+Jko1Pk41kUAaEm1oiPzrr1M4dQpZLmNpbsb38Y/jOn4cSzgMTDuj19XVbBLC4a1bi5MaqbW5gZpZ6NXvw46n5jdmbuitRa4WQSvrZOO1AnVdl+SSJUavJhnrSy5qoyAEOL02PEE7Lq9tZhXgSuhL9pHX8kgp+bu+vyOSi/Dbh3+bsLP2nnttXnYFdy16bLVSITE+SjYeAyTZeIyrr7/M2NXLWOx2eh99gp4HTmCdG2E0W/CEwnjDdTjc6+vIr1AshhJXCoXivsMwJOdH05Q0nZFkgf/0swF8Tit/+PTumdY2jT4H+1t8UClTnhulKhQonDxJ/vXX0UZHa+1nHngA96OPYuuq9RwUNhuW+jos9fWYA4GtK6huUcpMN2YGqrfSgWE4+sXZMf62+b0EqbWgyafL5FNlykWdakUnci3N6NUEyYkCQtRsFDr2hanvqNko2OxmPCEHnqAds2X178tIdoSpwhQAvxj/BW9PvM2Huz48Y7tgMVnYH96/oM5Kr1ZJTURIRyema6wmGHjzdcb6r2C2WNj9yKPsfPBhbI7ZhQMOtxdfQ4MqUFdsOkpcKRSK+47LkQzpgsZEpsR/eKEfu8XEH31gNwFXLU3XEnCy2ysoX7lca5psSCo3bpB/7TWK77yD1DSs7e0EPvc5XA8+iMnpRFitWBobZgXV/WISqVchcrZWZ2UY8MZ/hmwEnvw3NZNQAEcAGvYDUNV0CukK+VSZUqGKXjWIjeaYuJ5m4noKvSpxB+zsfaSJ1j1B7C4rJpPAHbDhCTpwuNduIZEqpbiRugHAcGaYb/V/i95QLx/q/tDMmN5QLw7LrP2BYeikJydITU5g6FViI8P0v/kaUzevY7HZ2XXiEXY++PCMU7rJZMYTrsNf37BkY2WFYqNR4kqhUNw3SCkZmMoxkS4Rz5X5D8/3A/BHH9hDnaeWBuq0abTFJilejWMUi+TfeIP8a69RnZhAOBy4HnqoFqXq6AABlmAQS3MLlvo19u6719yqs5IS3vk6jJ6EY78GTQdrz5ttlIMHKUZLFLIVKoUqWkVnaijL5I00U8NZdM3AYjPRsjtI294ggUYXJiFweKy4A3bcfhumZYrTV0JZL3M5fhmJJK/l+bOLf4bX5uXX9v3aTJSqw9cxkxo0DJ1MNEpqYhytUiYycJVrJ98kOT6GzeWi97En6T56HNu0D5XN6cJf34gnFF50RaBCsZkocaVQKO4LqrrBxfEMsWyZdFHj//tCP6Wqzv/8wT00+R2YUkk6S3EaqFBOp8n+/OfkX30VWSph6+oi+MUv4jx2DJPDgclhx9LUjLWleemmyfcDqeFalApqlgsDz8PeX8LY9RGKeSgWTRRdO6kWShQyFaLDWaaGMsRHchiGxOa00LIrQFOPn1CrG7PZhN1pqQmqgA2LdX1EiiENLsUuUTEqaLrGVy98lUw5w+8/8Pt4pr236px1dPu60atVMtFJ0pMTlAp5hi+c5frptymkU7gCQQ49/SE6Dh7BYrUihAl3IIivoRGn5x5ZXygUi6DElUKh2PIUKlXOjqQolHVy5Sr/4YV+0kWNP3x6F50UsF4eoN1u4MunSb7wAvm33gJdx3nsGN4PfKAWpTIJLOE6rC3NmEOh+yfttxRz66wGX4Nz30BreQ/xxi9SGjShaZAoNRCNpoiNjJBP1QxWnV4rHQfDNPX4CTa6MJkENpcFl9eGO2DHal//qM9AcoBMJYMhDb5+6etcS13j1/f9Op2+miWE1+Zll3cnifFRMlOT5NNJrp9+m8Fz71Atlwm1tnPgyQ/QvHM3wmTCanfiq2/AGw5jtmyg071CsUaUuFIoFFuaeK7MhbE0VV2SLmr8558PMJkp8QcP1NE7OYC5XKK1EIOXX2Ty7Fkwm3E/8gjep5/GUl+PyeXE2tyMpbl561knrJVKHsZOo1UMykMXcJ/6L5R8+7kZ/F0mL1uZjAiSCROGkcRkFoRbPXTsr6O+w4M7UCtEd3qsOL02XD7bmgrTV8rN9E0i+QhSSv6+7+85HzvPp3d9muNNtR6HFg2aKm7Gxi6QjIxx7dSbjF29jJSS1t297HjwYUItrQiTCXcghK+uHqd3A3oxKhTriBJXCoViyzIcLzAwlUVKODuS4uu/GKSsVfnnHXA4O4pt6BqBU69THOhHOJ14P/hBPE88gdnvx+z3YevowFJff69fxrpiFDLkrpwkl9KQyWEc5/6Wy9Vfp7/wYdL9ta90txc6D4Sp6/ARanFjsZiwOS04PFZcXht2t2VTIneD6UGGMkMA/Ojmj3h9/HU+0PkB3tf2PrRMHj2Zo1XUc+3G69w8e5r46DAWq42eYw/S88AJ3P4AdpcbX12DapysuK9Qn1SFQrHlMAzJlYkMkVSJclXnm6dGeKk/RocD/llHie7BizjffAXLxDjS78f/yU/ifvRRTE4nllAQa2cnlmDwXr+MdaVc0MiOR8ldv0w2rRMZLBMddpOq/p8A+AMGu3t1mtrteLp3YXXacXhsOL1WHB7rsm7pG8FwZpjBzCAAr4y+wk8Gf8JDjQ/xAe+jZAeG0RIZGEzw0uVvUykUcAeC7H/iaboOH8XudOMJ1+Gra1Du6Yr7EiWuFArFlqJc1Tk/miZd0BiO5fjqy9cYz1d51lfiC5Mn8fzkVcypBKaGBvxf+AKuEycQNiuW+gZsXZ0zburbAUM3yKXKtUbJ8QQTF24yPAjJhBWBiWbbMO27rdR1BnC5wO734dpxAFfQhdV271bMjWRHuJGuWS6cnDjJt/q/xT7Pbj5UPU7szfNkrw1RHI+CEDTv3E33kQeo7+rB4fbgq2+orfgzqRV/ivsXJa4UCsWWIVPSODeSoliu8rNTN/hWX4oGo8D/E32drhdex5TPobe04fvUJ/EeO4qwmLE2N2Nrb8e0jSIclVJ12i29TCpaYOTCBGMDGaqaCbezwonA9+m1/YTc/n8GjX7cbgNXQz3m9mNwj+0kRrOjXE9dp1oq89Mbz/PDyPMcyrXy+LVGRm7+BEOr4vB62fOex+k6fBRPIIQnXIc3XK+iVIptgxJXCoViSzCRLnFlPE1iZJw/e3ucSCzDvxx+hUevvYGpUkbr3oX5qffTemQ/VrsNa2sr1vb27VOkDhSzFdKxWqPk8YEUI5cTpCYLmEySxmbJ7sB5ehP/Hqwuyif+kIbWnZhMEnytNV+re7wC8npsgGujlyil0rzQ92Oyg2N8brITRx7y5jE8Xa3sOnKCjh37cPsDeOvqcfn896e/mEKxDEpcKRSKe4qUkuvRPMP9Q5y9NMyPL03w0b6XeP/IaUzSoLL3AOLxJ2nZtwuXz421pQVrSwvCuj2W4EtDkkuVyUSLpGNFhi7GGbmSQCvpePwWevfrtLZWaY5/A9/YP2CEd2N67A9xOQO1EwS7aj0D7xF6tUo6McXFG6cZv9ZH5uYI0ZvX6c6DFH5czQ14jrTi29HB/u5jNDZ04A4EVXG6YlujPt0KheKeUdUNLl68SfTKAD8/dZ2ed17mP45fBLOZyuEH0B55nKYd7dS3NWJtba01Tr7f/ammqWq1RsmZWJHoSI7BCzEmb2YAaOzy0bUDwq44HluOUP//hXnqLOx4P6YHfgPM01/ddbshvGPT565XqxTSKbLxGDevnKX/wkkyN0eo5goYQhKrK+Hf186hXSewh4O4ggEe6HkPPufiTaMViu2GElcKhWLTqZbKjA0MEekfZOLUOfTXX+HXpq5RtjkoPvI45QffQ117E227u3B2tGNyOu980vuEcrFKJlokEysy2p9k6HycbKKE1W6m50g9nbsceE0RvM48XmMU8y/+T8hH4cHfgp1P104izLVoVaB90+atV6vkUwly8Tjj/VcZvXqJ0b5LlLNZMAlo8vLOjhzX6tN8qvPjHG15AKvHjcfh5UDdAZyW7fM7VCjuhBJXCoViU5C6TnkqSmRgiOi5i8hLl6heOMueeISkw8eN936YwEMP4mxpZN+BXQQ6WrdNLY6UkkKmQiZWIjqSZfhSnLH+FNWyjjfs4OCTbbTu9OERU3jFdZwOAzH6Frz1X8Fih6f+F6jfWzuZMwRNB8Dm3vB561WNfCpJNhZjrO8yY32XifRfpZjNIEwmnC31BA/18GbdTd7QLlBnD/Pb+3+P7kA3AC2eFnYGds70DlQo3i0ocaVQKDaUajJJaXSM8VffJH/6Hbh6CW98CoBr/lZee/jTHHn0KIH2Frr276C1reEez3j9MHSDXLJMciLPyJUkw5fiJCcKmEyCxh1+OveHqWtz43VX8FauYqUIsX74xd9A9CqEdsBjfwiuMJgstTRgsHND53wrQpWJxRi9cpHxaUFVyucwmc0EOzvwH9uLq7uFMWeKv5j4Pslykifan+DZnmexmW1YTBb2BPdQ79peBq4KxUpR4kqhUKw7Rj5PZWyM9Isvk3zjLaqXLmLOprEKExfC3bx18BGKO/dydEcjD/U00rS7i53NAaybbHS5UVRKVbKJEhPX0wxeiDPWl0Qr67j8NvY+0kzr3iD+OidevwW3dhORGYH0KJz7Wxg7BQ4/HP/HsOOpmqhy1dWiVdaNSa0Zuk4+lSQTnWLk8gXGrl4iMtBHuZDHbLHQ2LOTup07oTOI7rNRdZr40dhzvDr0KvXOev6nY/8TOwK12i+fzUdvuFelARXvapS4UigU64KsVCgPDpL96U/JvfEmpQsXoFRCM1s507iHV3Z9mOttvRzvDvHEzjo8dSECQQ+7Gr34nff/yj+9apBPlYmNZBm5mmR8IEViPI8wCZq6fbTvD9PU48MbdOD2W7GWJyE2UBNVF78FN18GswMO/grs+QhYHWCyQv2eDamtkoZBIZMmE51i8Pw7jF29TGTgKpViEbPVSlPPLlr27KPt4EHSjjIpS4EiFV4aeYmXrrxEqVpaEK3q8HbQ7m3fNosOFIq1osSVQqFYM9VsDu3GdbIvvkj+9dcpXbkK1SoVh4vzrQf4Yd0BztbvZk+zjyf2NvDZznqCHhsNXjuNPgcO6/3twi0NSSFbYfxaiuGLcSZuZEhNFgBw+W3sebiJzv0hQi0ePEE7dosGqWEYHYVCEi7/A/T/BJCw+8Ow/xNg99UK1r1NtTSg1bGucy7msqQnI9w8c5rRKxeJXOtDK5Ww2Gw07dhN6959dB48ij3sJ2nOM1aOkalkeHHkRV4eeZmSXuJQ3SE+1P0h2r3tmISJZnczXb4urOb7XyQrFOuBElcKhWJFGJUK5b4+CmfOUr58mfK1ASpDwxjZLAB6IMSV3kf4bt1B3vR24nXZeGxXA/9uVx07Gjw0eB00+Oz3vaCCmtnn8OUEN89FmbiRIZ8qA+Cvd7L7RCNNO/00dHjxhpw4PRZEIQaJq5AcgrHTMPImRM6DUYWux+DQL4O7vpb2C3SAvx3WUaiUcjmSkTFunjnFyJWLTFzrp1opY7Hbad65h7a9++k6fAxvfT1Vh4mxwjjx4k2imSi/GP8Fr46+SkkvcaT+CM90PUObtw2Aemc93f5uXFblrK5QzEWJK4VCsQBD1ylfvUrxnTOULl2k1NdPZXAQWSzWBphMmJqaKezZz0hdJ897evhxNYSOoLfJyz/ZU8/7dtfTGnRR772/BZWUklJOI3I9TeR6muhwlthIlnKhijBBuMVD96E6OvaHCbW4cXqsWB1mhF6B9Aj0XYbB12HkLZiYFlSuEOx6GnqeqqX83PU1UeWuXzeX9VI+R2Sgj+un3mK8/wqxkSGkYWB1OGnZ00v7vgN0HjqGv74Bq9tFvJygPzfERGqC05OnOTVxipuZmwgERxqO8KGuD9HiacEkTNQ562j1tOK3K98qhWIxlLhSKN7lyGqVUn8/xdPvULx4gXJfP5WbN5HlWjQGiwVLayuFIycYqu/kgq+Nk9ZGbhYMcmUdAJfJzPv31fHs4WaOtAfva0FlGAbJSJ6x/hQTNzLERrOkp4oYugTA7rIQanHT1hui60AYf70Tm9OCMHQoJiEbh+uXa2Jq+E2YvACGXitK3/UMdDxcM/60OMDXUhNV62CroFerJCJjjFw8x+jVS0T6r5JLxAHwhuvYcfwh2vcdpH3fITzhMGannUQpwfXCCKOJUS7HL3N68jSX4pcwpEGzu5mP7fgYDzQ+QMgRwmVx0exppsnVpNJ/CsUdUOJKodjmSCnRYzEqo6NUBgepDA2jjY2ijUeoTk5SnZxEahoAwmbD3NFJ/uH3cbOuk7OeVt4yhxlKa1R0AwBLQdAWtHKsw8XOBg+9TT6OdgZoD7mwW+4vQWXoBvHxPFNDGeKjOeLjeeKjOcqFKgAms8Df4KTnaD0NXT6ae/wEm1yzYqoQh7E3YfQUTF6G5A1IDIKWr13AXQ+7PwIdD0HDvpqlgitU86qye+5u7tUq4wN9jFw6z/jAVWJDg+SSNTElTCbqOrrY+eAjdB95gIbuHTi9XspSI1VO8U76PO8MvEN/op+B1ADjuXEkEr/Nz5PtT3K88TitnlbsFjshR4gmVxMBR+Cu5qtQvJsQUsqNO7kQHwL+E2AGviql/PfLjT9+/Lg8derUhs1HodiOSF2nGo2ijY9TGR6mMjyCNjKMNj5ONTJBNRqdEU+3EB4Poq4eva6efKiR66F2TrvbeLPqZTRT5tbXgstmpivsYse0iNrX4qO32Yffab2vIlOGIUlHC0SHssRGcyTG86QmC2TjJQxj9jvQ7bcRbvNQ3+Gleaefxm4/DpcV8rHayr74dUgN1R5Hr0ByEKql2sEmay0KFeqGYHdNTLUemxVUa4xOSSnJJeJM3rjG1OB1YiPDJCNjpCcjaNPRRZvTRbitg8buHTTv2kPL7l5coRAFo8jN9E2uJK5wLXWN0ewoI9kRxnJjSCRWk5Vufze7ArvYHdxNT6CHoCNIyB4i6Ajisd2dAFQotjtCiNNSyuML9m+UuBJCmIF+4APAKHAS+FUp5eWljlHiSvFuRuo6RqGAkcth5PMYuRx6Lj+zredyGJkMei6LnkigjY3XBFQ0Cro+71wVt498IEzaFybmqWPKFWLMGWTY5uem2UtcLkzrhN02djZ42NvkZV+Lj6PtQXbUuzFvce8pXTMoZCvk02UK6Qq5RIlcqkw+VSafLpNPVcjEixjV2e86l8+Gv95JoMFOuB7qwhp13jT2SgQSN2or+tIjkJ2A3CRUcvMvarbVzDxDO2ttaJoO1sSUMwBWV01ImVYmPqWUFLMZsvEYuXiM9NQEmViUTCxKamKc1GQErVSaGW91OPE3NBJsbqVpxy4Cu7opBASR8iTjuXEi+QgT+QlGsiNE8hGK1eLMsR6rhxZPS01MhXbTG+ol6AjitrrxWD347X7lpq5QrIKlxNVGpgVPANeklDemJ/C3wMeBJcWVQrGZSMMAXUfqOrKqg15F6jroOka1iqzqVDUNXas91qtVjJkfHUOrIqtVdL06/bh2nKHryGptn54vUM3nMKZFkszlkIU8Ip9DFAqIYgFTqYi5VMBSKa9o3hWzlYLdxZQrRMTZTGTHPqacQSZdIaZcQaLOAGWLDahFnnxOK36HFb/LSshpZYfLRtBtJeiyEfbYaPQ62N/qJ+S2bcB7LDGmf6Q+/ViXs/t1g2rl1o+OVtFnHlfL2vRPlWqlilauopV1tFKVQqZCIVulkDNY/G2TOGxVXPYyHnuBjqYYIXuEsGWYkLiOTZuCchZuluDmIodbneBuBG9jTTj5WpC+VqSvDcPfjuFuQTfZ0Q05/RnRqOYr6KkUujaFrmloWoVKoUC5kKdSKFDMZynmcpTy2Zn9hUyaUiaNUZ0vjhECk8uOKeDC2BVGC1ooBARpn0HakierRchW+klkv0355MI3wGP10Ohq5ETTCdq97XT7uukJ9NDoasRhceC2unFanMqPSqHYIDYycvUZ4ENSyt+a3v4S8JCU8neXOqY9FJZ/9MFf2ojZzHm8cWlQxVpZ7ney9Jf/sreFBafcAr93MTsLOb3NItsLHt927EZNbvn3c/ZZMee/t58DOfdM63njlkgkCInEQAoDKXQMoSPn/MzdnjczKQCBkKI2P3lrX+3/YvpNF7f21y4181N7XXdH1WSgWSQVq0HFYqBZDIp2g4KjSsGhk5/+f8GhU7TpyDkBJJMw4ba4cVvduG1uPBYPHpuHemc99a56GlwNNLobaXQ10uxuxm11YzVZlXhSKDaYexG5Wuxf9YL7gxDiK8BXpjdLf/B3//3SBs5ps/AD6Xs9iTls5nw28lrree67PdfdHL+WY+uA2Bqvp1iarfZvda1stdex2fPZqOttpe+cuz2H+t7ZGBZv9iml3JAf4BHguTnb/xr413c45k82aj6b+bPVXsdmzmcjr7We577bc93N8Ws5Fji1Wb/Dd9PPVvu3ul1ex2bPZ6Out5W+c+72HOp7Z3N/NrJy8SSwSwjRLYSwAZ8DvneHY76/gfPZTLba69jM+Wzktdbz3Hd7rrs5fqt9Pt7NbJffxVZ7HZs9n4263lb6zrnbc2y1z8i2ZqOtGD4C/EdqVgx/LqX8PzbsYgrFNkYIcUouktdXKBSKjUJ976ydDTURlVL+CPjRRl5DoXiX8Cf3egIKheJdh/reWSMbGrlSKBQKhUKheLeh3OIUCoVCoVAo1hElrhQKhUKhUCjWESWuFAqFQqFQKNYRJa4UivsQIUSvEOK/CiG+JYT4p/d6PgqFYvsjhHALIU4LIT56r+ey1VHiSqHYIggh/lwIMSWEuHjb/g8JIfqEENeEEP8vACnlFSnlbwO/Aqil0gqFYtWs5jtnmn8F/P3mzvL+RIkrhWLr8HXgQ3N3CCHMwP8DfBjYB/yqEGLf9HMfA14Dfra501QoFNuEr7PC7xwhxNPAZWBysyd5P7KhPlcKhWLlSClfEUJ03bb7BHBNSnkDQAjxt8DHgctSyu8B3xNC/BD4m02drEKhuO9Z5XeOB3BTE1xFIcSPpJTGZs73fkKJK4Via9MKjMzZHgUeEkI8AXwKsKOMehUKxfqx6HeOlPJ3AYQQ/wiIKWG1PEpcKRRbG7HIPimlfAl4aXOnolAo3gUs+p0z80DKr2/eVO5fVM2VQrG1GQXa52y3AeP3aC4KhWL7o75z1gElrhSKrc1JYJcQolsIYQM+B3zvHs9JoVBsX9R3zjqgxJVCsUUQQnwDeAPYI4QYFUL8ppSyCvwu8BxwBfh7KeWlezlPhUKxPVDfORuHatysUCgUCoVCsY6oyJVCoVAoFArFOqLElUKhUCgUCsU6osSVQqFQKBQKxTqixJVCoVAoFArFOqLElUKhUCgUCsU6osSVQqFQKBQKxTqixJVCoVh3hBC/J4S4IoT463s9l/VECPEfhRCPTz9+SQhxfM5zXUKIi8scWy+E+MlmzFOhUNxblLhSKBQbwe8AH5FSfmHuTiHEfdvPVAgRAh6WUr6yluOllFEgIoR47/rOTKFQbDWUuFIoFOuKEOK/Aj3A94QQfyCE+F+FEH8ihHge+MvpCM63hRAnp3/eO31cWAjxvBDijBDivwkhhoQQdbdHhIQQ/0II8b9OP94hhPiJEOK0EOJVIcTe6f1fF0L8X0KIXwghbgghPjPn+H8phLgghDgnhPj30+d4Z87zu4QQpxd5aZ8BVhR5EkJ8VQhxdvonKoT4t9NP/Q/gC8scqlAotgH37V+RCoViayKl/G0hxIeAJ6WUsWkh9ADwqJSyKIT4G+D/J6V8TQjRQa3NRi/wb4HXpJT/mxDil4CvrOByfwL8tpRyQAjxEPDHwFPTzzUDjwJ7qfVG+5YQ4sPAJ4CHpJQFIURISpkQQqSFEEeklGeB3wC+vsi13gt867Z9fy2EKE4/tgHG9HvwWwBCiM7p13frfKeA//cKXpdCobiPUeJKoVBsBt+TUt4SIU8D+4QQt57zCSG8wOPApwCklD8UQiSXO6EQwgO8B/jmnHPZ5wz5H1JKA7gshGicc+2vSSkL09dJTO//KvAbQog/BD4LnFjkks1A9LZ9X5BSnpqeTxfwgznzcwDfBH5XSjk0vXsKaFnudSkUivsfJa4UCsVmkJ/z2AQ8MkdsATAtkBZrdlplfgmDY855UlLKI0tcszz39HP+v9g1vk0tcvZz4LSUMr7ImOKca6+E/wp8R0r50zn7HNPnUSgU2xhVc6VQKDab54HfvbUhhDgy/fAVpuuRptN3wen9k0DDdE2WHfgogJQyA9wUQvzy9DFCCHF4Bdf+x0II1/Qxoelzlail7/4L8LUljr0C7FzJCxRC/DPAK6X897c9tRtYckWhQqHYHihxpVAoNpvfA44LIc4LIS4Dvz29/98Bj08Xl38QGAaQUmrA/wa8RS3tdnXOub4A/KYQ4hxwCfj4cheWUv6EWv3VKSHEWeBfzHn6r6lFtZ5f4vAfAk+s7CXyL4CDc4rab73GJ6fPo1AotjFCysUi5AqFQnFvEUIMAsellLFNut6/APxSyv9lmTGvAR+VUqbWeI1XgI9LKZetJ1MoFPc3quZKoVC86xFCfBfYwexKw6X4I6ADSK3hGvXAf1DCSqHY/qjIlUKhUCgUCsU6omquFAqFQqFQKNYRJa4UCoVCoVAo1hElrhQKhUKhUCjWESWuFAqFQqFQKNYRJa4UCoVCoVAo1hElrhQKhUKhUCjWkf8/4hefLopgKUIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10, 6))\n",
    "\n",
    "for with_eq in [False, True]:\n",
    "    for N in [4, 7, 10]:\n",
    "        sparse_grid = sfa.gen.lebedev(N)\n",
    "\n",
    "        result = []\n",
    "        for i, sphere_param in enumerate(subject_sphere_params):\n",
    "            lr_hrtf = iSpatFT(subject_sph[i], sparse_grid)\n",
    "            if with_eq:\n",
    "                C_lr = phase_correct_vector(sphere_param[0], \n",
    "                                             np.array(sphere_param[1:3]),\n",
    "                                             np.array(sphere_param[3:5]),\n",
    "                                             sparse_grid, freqs)\n",
    "                lr_hrtf *= C_lr\n",
    "\n",
    "            sparse_sph = spatFT(lr_hrtf, sparse_grid, N)\n",
    "            hr_hrtf = iSpatFT(sparse_sph, target_grid)\n",
    "            if with_eq:\n",
    "                C_hr = phase_correct_vector(sphere_param[0], \n",
    "                                             np.array(sphere_param[1:3]),\n",
    "                                             np.array(sphere_param[3:5]),\n",
    "                                             target_grid, freqs)\n",
    "                hr_hrtf *= C_hr.conj()\n",
    "            result.append(hr_hrtf)\n",
    "        \n",
    "        hr_hrtf = np.stack(result, 0)\n",
    "        diff = spec_diff(hr_hrtf, target_hrtf, axis=(1, 2))\n",
    "        print(N, diff.mean())\n",
    "        mu, std = diff.mean(0), diff.std(0)\n",
    "        label=f\"order = {N}\"\n",
    "        if with_eq:\n",
    "            label += \", w/ eq\"\n",
    "        else:\n",
    "            label += \", w/o eq\"\n",
    "        plt.plot(freqs, mu, label=label)\n",
    "        plt.fill_between(freqs, mu - std, mu + std, edgecolor='none', alpha=0.3)\n",
    "\n",
    "plt.legend()\n",
    "plt.title(\"Spectral Differences across all subjects\")\n",
    "plt.xscale('log')\n",
    "plt.xlim([200, 18000])\n",
    "plt.ylim([0, 8])\n",
    "plt.ylabel(\"dB\")\n",
    "plt.xlabel(\"frequency (Hz)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Pnm_before = spatFT(hrtf, grid, 35)\n",
    "\n",
    "C = phase_correct_vector(subject_sphere_params[0, 0], \n",
    "                         subject_sphere_params[0, 1:3],\n",
    "                         subject_sphere_params[0, 3:5],\n",
    "                         grid, freqs)\n",
    "Pnm_after = spatFT(hrtf * C[:, 0], grid, 35)\n",
    "\n",
    "fig = plt.figure(figsize=(10, 12))\n",
    "ax = plt.subplot(211)\n",
    "plt.imshow(sh_spec(Pnm_before), aspect='auto', origin='lower', extent=[0, sr / 2, 0, 35])\n",
    "plt.title(f\"SH spectrum of subject {subject_name[0]}, left ear, before equalization\")\n",
    "plt.ylabel(\"N\")\n",
    "plt.subplot(212, sharex=ax)\n",
    "plt.imshow(sh_spec(Pnm_after), aspect='auto', origin='lower', extent=[0, sr / 2, 0, 35])\n",
    "plt.title(f\"SH spectrum of subject {subject_name[0]}, left ear, after equalization\")\n",
    "plt.ylabel(\"N\")\n",
    "plt.xlabel(\"frequency (Hz)\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}