analyze_simulations_downsampled_detected_before_after.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "af4f886c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/p7/5y4rzfc927v9625g5xrx460crwqrl3/T/ipykernel_48242/1872962086.py:7: DeprecationWarning: \n",
      "The `fooof` package is being deprecated and replaced by the `specparam` (spectral parameterization) package.\n",
      "This version of `fooof` (1.1) is fully functional, but will not be further updated.\n",
      "New projects are recommended to update to using `specparam` (see Changelog for details).\n",
      "  from fooof import FOOOFGroup\n",
      "Warning: no DISPLAY environment variable.\n",
      "--No graphics will be displayed.\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.gridspec import GridSpec\n",
    "import scipy\n",
    "\n",
    "# how to change this from fooof (1.x.x) to specparam (2.0.0)\n",
    "from fooof import FOOOFGroup\n",
    "from fooof.sim.gen import gen_aperiodic\n",
    "\n",
    "from model import create_model\n",
    "from scipy.stats import linregress\n",
    "from scipy.signal import decimate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1d6a67d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_trials = 100\n",
    "n_electrodes = 25\n",
    "\n",
    "# @Carolina, how to change the colors and shapes of the neurons and electrodes?\n",
    "net_ds = create_model()\n",
    "_ = net_ds.plot_cells()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3cca474a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# load and downsample model LFPs\n",
    "srate_orig = 40000\n",
    "srate = 2000\n",
    "dwnsmpl_fctr = int(srate_orig / srate)\n",
    "ds_trial_signals = np.load('shank_ds.npy')\n",
    "ds_trial_signals = decimate(ds_trial_signals, dwnsmpl_fctr, n=None, ftype='fir', axis=-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e5a86154",
   "metadata": {},
   "outputs": [],
   "source": [
    "winsize = 128\n",
    "overlap = int(winsize*7/8)\n",
    "fft_length = int(winsize*16)\n",
    "freq_lims = [0.5, 250]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b10e551b",
   "metadata": {},
   "source": [
    "**Compute power spectra over whole trial**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1a4ac7a3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100, 25, 1025, 58)\n",
      "[0.00000000e+00 9.76562500e-01 1.95312500e+00 ... 9.98046875e+02\n",
      " 9.99023438e+02 1.00000000e+03]\n",
      "[0.    0.008 0.016 0.024 0.032 0.04  0.048 0.056 0.064 0.072 0.08  0.088\n",
      " 0.096 0.104 0.112 0.12  0.128 0.136 0.144 0.152 0.16  0.168 0.176 0.184\n",
      " 0.192 0.2   0.208 0.216 0.224 0.232 0.24  0.248 0.256 0.264 0.272 0.28\n",
      " 0.288 0.296 0.304 0.312 0.32  0.328 0.336 0.344 0.352 0.36  0.368 0.376\n",
      " 0.384 0.392 0.4   0.408 0.416 0.424 0.432 0.44  0.448 0.456]\n"
     ]
    }
   ],
   "source": [
    "# Compute power spectral density from STFT - detected stimuli\n",
    "freqs, times, Zxx = scipy.signal.stft(ds_trial_signals, fs=srate, window='hann', nperseg=winsize,\n",
    "                                      noverlap=overlap, nfft=fft_length, detrend='constant',\n",
    "                                      return_onesided=True, boundary='zeros', padded=True, axis=-1)\n",
    "print(np.shape(Zxx))\n",
    "print(freqs)\n",
    "print(times)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9286cf83-9029-4b9d-bcdb-c8ba50c06504",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100, 25, 1025, 58)\n"
     ]
    }
   ],
   "source": [
    "ds_layer_psd = np.abs(Zxx) ** 2\n",
    "\n",
    "f_idx = (freqs>=freq_lims[0]) & (freqs<freq_lims[1])\n",
    "freqs = freqs[f_idx]\n",
    "\n",
    "ds_layer_psd_before = ds_layer_psd[:, :, f_idx, times<=0.128]\n",
    "ds_layer_psd_after = ds_layer_psd[:, :, f_idx, times>=0.128]\n",
    "\n",
    "# compute means\n",
    "mds_layer_psd_before = np.mean(ds_layer_psd_before, axis=-1)\n",
    "mds_layer_psd_after = np.mean(ds_layer_psd_after, axis=-1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0faae39",
   "metadata": {},
   "source": [
    "**Parameterize power spectra**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7f6b0ec7",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.49\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Parameterize detected spectra\n",
    "ds_layer_offsets = np.zeros((n_trials, n_electrodes))\n",
    "ds_layer_slopes = np.zeros((n_trials, n_electrodes))\n",
    "ds_layer_aperiodic = np.zeros((n_trials, n_electrodes, len(freqs)))\n",
    "for t in range(mds_layer_psd.shape[0]):\n",
    "    trial_psd = mds_layer_psd[t, :, :]\n",
    "    \n",
    "    fg = FOOOFGroup()\n",
    "    fg.fit(freqs,trial_psd, freq_lims)\n",
    "    for i in range(trial_psd.shape[0]):\n",
    "        ds_layer_offsets[t, i] = fg[i].aperiodic_params[0]\n",
    "        ds_layer_slopes[t, i] = fg[i].aperiodic_params[1]\n",
    "        ds_layer_aperiodic[t, i, :] = gen_aperiodic(freqs, fg[i].aperiodic_params)\n",
    "\n",
    "# Parameterize undetected spectra\n",
    "us_layer_offsets = np.zeros((n_trials, n_electrodes))\n",
    "us_layer_slopes = np.zeros((n_trials, n_electrodes))\n",
    "us_layer_aperiodic = np.zeros((n_trials, n_electrodes,len(freqs)))\n",
    "for t in range(mus_layer_psd.shape[0]):\n",
    "    trial_psd = mus_layer_psd[t, :, :]\n",
    "    \n",
    "    fg = FOOOFGroup()\n",
    "    fg.fit(freqs, trial_psd, freq_lims)\n",
    "    for i in range(trial_psd.shape[0]):\n",
    "        us_layer_offsets[t, i] = fg[i].aperiodic_params[0]\n",
    "        us_layer_slopes[t, i] = fg[i].aperiodic_params[1]\n",
    "        us_layer_aperiodic[t, i, :] = gen_aperiodic(freqs, fg[i].aperiodic_params)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c4b6dde",
   "metadata": {},
   "source": [
    "**Plot spectra and parameters**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b1b70e2a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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YgXLofx3nyS9rg4GVV2F8RfM7zznSnhQeDgm7QuCIfs23U1xfGr7fr80fvAbekOenVu+D3THoScH6+eez265zs+FM6iywHFFxKQrJEKQiHL/cMjnbp0u9h05WVfljBShfCRRUzW+gs1iWMXasW9qMZHXi8kRE2Bs7fqQrcEGZB4rcms+ScKA3PXk3zW3gujLDOyrV/WCxnImczmOdiLAnBncMCK9GdQe80afTnxPRn4aHhtLsSeqmmxGHHU4bl7k7KWFm9R8CDBFgJJ3h6r6fcWPPj6hIdI7foHgF1J0LlZswrpnteUs6CrE+TCqCeIOYkmZMw05M1VYoWYk52ROzWBaA03kMmQpJRXFe/S9oewQpbZ5/9zknC+27oP1xQNSRtP5mTMmKuR9THBjpxCSGoGwNrrVvgoaLNIB8gTm2G+hgRsO2T9QNdKbsj8OdA5ASdR69twpq8/yUetM6b/zrZkNlHuaGVmiaBWfaYLJcECcDiWFIDsFEW7XLqy4lbxA8gVy3hOPfNJJNqfspFVahCgCjIXWF1XbyYjnjsGPd0kNE2B+H3wzDE2FhYmOQNQHYETRsKFDHUtkUTqWsCO1JeCkKj4aFI7m6fq+B91cb3lyBHessZxyn61g3lBF+MSA8MAxxB9YGwH8S889wRjsZvRwdF6+3BTJc7hyhYmS/zo+8QfAFYRpfkwP0EqSPICUkeQNdXMFRNksvrvBh6H4eBvcx9gieQqjZDnVvwIwGA58E3VQcgVgvJh1DfMWYsrU5p9NWCNbbscyyaJyuY8iJkHRcxaajDyElqzD++T9vCR+FAz+D5DBgoOkSaLoc43LP/ZjZNESOYjJJqNqKa92boWb7gjghRYQDCXhwWHg6AqEM1Pmg2nNycf/kx4bHI/BALvx7lR/eVQnBub8007InBleUwu825Oc1skLTLDgTB5OljGRTEB9QB9PopMW41ZHkL9U6/9keM5OEeF/OEQW4A1DcZMvpLGcUdqxbOogIz4/AnQMqNI2yyg/XlBkuKIaqOew67Y4K3+sT9uaOeXbQ8AcNtpzOcmZxuo11WRGeDMNPB4TDCXUwVZ1k+jKShUfD8PwIjPaS2hiAq0rHd8slHUVCLdo2PBNTgWiC4JTB0EkxIQJUEeNSjnIJ7TQzfNwiS1IR6HlRv1Lh8SvK1kDtuVCxYcYLQRHRY8R6MZkE+Euh4ixM/XmYqq2YwuoZHcdimSun2xgyUySTwHntW9ByH1KyAuMvzcsxOfJr6HtVLyhqUHfTaJbTnI8bx4RaEePG1O/Ete7NmLI18z5fAEeE12Nw/7DO1aJZaPBBRR4EJtAmDr8Ygldj+vu5QXhj+fxL8KZ7rP0J+KNGw4Ul+XkAKzTNgjN1MFlqSDYFsb7JExRPgTqQfMV52cmSVARGurSFp8sDxSswnhO36LVYThfsWHfqEVHb9Z0DwtFcgK/XwGUlhuvLtRXtfMc6EeHeYbi9R0iJTo4+t9JQbUvpLGcIp9NY15YU7uwXnoyAF2gOaCeh6Ug48EQEnoow5pBs9sM1pdA0TXKApKMQakVCRyATJeEppd1XTxIPjUS4ihYuop1qEzvp+Yo4MHRAXU7Dh8av8BVDzQ6o3TErp4SIQHIIE+uHbEqzWqq24Kp7A1RtxQTKZ3wsi2WmnE5jyGyRbApn97fh8K+R4sa8vcekfzccugeyCa1OWX091OyY/5wnGcaEW1WQXnklruYbMMGaOR0rK1qSfP+w8FJUx9Mmn5a05ctQGc7ADwegM6WS/hvL4fwFjJvqTOk88yurDUV5UrKs0DQLzuTBZCmgDqb+nIMph68YApVzci+d/PHSEGmDbFKdUiUrrdhkOSOwY92pQ0R4MQrf7dU6f9DMpRvLtbxtqrK4+dKWFL7YJvSndRfuC6sMdT4rNllOf06HsS7hCPcNCb8c0qDY1X7tHjQdKQeeGYHHw5DIrQAafXB1qZbhzoRQIk5HqB+J9bIu2cLVrjbOL4hRbLInv/MUSGIIel6AnpfUMQWAgYoN6nIqWzOrRaaIA/FBTLxf8zgLKqBmO67aHVC1Zd65MhbLKKfDGDIfJJvG2fM9OHw3EqzHFMysBPakx02G4MDPIdyiF1RsgLVvwXhP3kjghMcVgXg/JtoFhXW5wPArZzwmZER4cQTuG1ahKSOwwgcleW6v1pGEH/TDiKNzwHdVwuoFXoK+FoM3lcOH6/JXWmiFpllwpg8mpwpxsiowJYYYK5HzFecCuxf2XSfiQPgoZOIqNpU2L0qYnMVyKrFj3alhX0z4dp/asEEnF2+rNNxUDsGF8ElPYDAtfKFN3VN1PvjyKkOpLaOznOYs57FORNgdgx8PCK+OQLnnxGHfGYEXRmBXGKK5HijVHri6TEvlTqbjiMBABrrTEHDBtkK4yj/M2QMP4m17EKI9SEEVFNXNOQNFnAwM7oXuFyDcOn6Fvxzq3qD5Kt7ZdbrSOeSAik4AhdVQ+wZcNds1jHyeC1fLmc1yHkPyhTgZnNd/AAd/gQRrMAVV+TmuCHQ+CUcf0sZN3iJY9xZM+bo8HHt2geEpRzv83jesczRBBaaiBchJeiUKPx/UUuYaL7ynSsf3hSThQEsSPttkOKcof3M/KzTNAjuYLC4iAolBFZlGO8N5izSgexGdRSIOhFrVwun2q9hkW+paTmPsWLe49KaEb/dqFzlQ6/JN5Ya3V0LxIoo9wxnhf7UIvWlta/uFlQbvfNukWCxLmOU61g1lhJ/nwr4TJwn7dgReicHDIQjlDEflbriyFLYWnrwTUlagJ61uqXIP7CyGK0oNGwvAlVOnJNaHtD2CtD4EsW4kMD/BafSY9LwAvS+rsxx0w69yk3asK14x61IayabVzZAY1A7EhTVQfz6u6u1QsdF2G7bMmuU6huQbcbI4e++Ag3chBVV5zUeTaDfs/6muBwHqzodV1+QlP/dkgeHxrPDMCNw7JByIazbSCh8ULoDA5IgGfj+RiwneGIC3V568kUM+OJqEUg/8TbPBn8d5nxWaZoEdTBYPSWq4I05aL3AHoLAG45vdTlbezsfJQOiIdrXzFWOKm07JeVgsi4Ed6xaHeFb46QD8fFC7yBng6jLDe6qg4hTlJHUmhf/VKoxk4U3lhtvqrNBkOX1ZbmPdaNj3Twa0c+SJwr5F4PU4PBSC/lxD3iKXdhTaETx5mGzK0cyOcFZdjpeXwiUlhhX+6e8osf6c4PQgxHqQQAUU1c9PcMqmoH8P9DwPI53jVxRUq+BUvW1Om4+jeZ8mMYS4vJiieqjfiat6G5Svt01gLDNiuY0hC4mIg+z/CbLvTiRQjgnW5u/Y2TS0PgDdz+oFBVWw4e2YYF1+jj8pMPx84qvfwlPu1dw3JBxKgN/ACr+6OReChAM/GYADuY7Al5XAVSX5y3s6Ga9G4d3VcGt1fp+gFZpmgR1MFh5Jx1RgyuRaIbk8KjDloZvBfJF0PGflFm2fGyg71adksSwIdqxbWBwRHg7Bd/uE4dwCcGshfLjW0Bw49cLO8yPCl9t0avAnTYadxaf+nCyWhWA5jXVHE8KdA9o622s0uHsqsUgEDiXgwRB05fbqClxwabEGyXpPso6IZaE9BSkZ7255YfHsxG8VnHYhrQ9AtBspqIRg3bxalQPISJeGh/e/Nr4R6fJC1RaoO0/ForkcN5NQ0SkZQtw+TPEKTMMFmOqtULpm3udtOX1ZTmPIYiDiIAd+juy7A/EVz/k9Oe3xhw7CwZ9DOqquxJVXQ8OFeWkEBTCcTPFkvJD7A+dxNLiBwuJaVhYG8C2gq2ggrXlM/Rlt4PC2Cp0TLhbRrG4q/PlKw1mF+Z3vWaFpFtjBZOHQnaVeSOX8gsYFgUooqJh3mZpkkjB0ABnp1FK8ZEiP7/aBrxRTukqDJmcgZkl8QM/TuHTyYXe8LKchdqxbOHZHhW/2qhsB1Cnw2zWG84vm30Uun3yrR/jZoFDmgX9ck78OJBbLUmI5jHXxrHDfsPDLQehPa2D3dLkgHUm4LwStuUozn4GLivXrROUXIlpW15HShc7GAnVXnlcEhfN470t8YFxwGulGCsp1o26+glMmoS3Qu58bL6cBCNary6l8PcY3t/ZMuuHZh0mGEW8hpmRlTnTapk1hbHSCZQLLYQxZbEQEOXQ3zuvfB28Rprghv8dPR+HgL2Fov15Q0qzZTfMwAAxKgMdYyQOspoNiijNhGlPteL0FmLJ1C5bRezgBdwyoo6nYrXlMDYscBXw4oZ1Gv7DK4M7zPNQKTbPADib5R5wMxPohOTR+ob8cCqswrrkln4kIhI8iHU8gvS9BqGU84+lEVG3GNF2mXyeo05dQq3ZF8QYxJSvndI4Wy1LGjnX5pzuXw/RULoep0AXvqjK8sZwlmYOUdoQ/PiK0p+DaMsOn6pfeOVos82Wpj3X748J3e4VXolDl0QXIdOuAlAN/2wnpCbP6DQHNb6r3Qa2XKXflhzPQloKgC84OqoNpWxA8eVxwSHxwguDUiQTKwF8GvqL5ldWJaHfg7udh4HWQCV3vCqqgtFm/SlbNOvRbRNQ1EevFpKOItwhTtgbTsBNTsQlKVljRybLkx5BThYggLb/B2f1ddR0WN855XTfd8el9EY7cq+5G44Ka7dB4MSYw8853cfFwN+t4iNX0EKSMBPVE8CCAQGoE0nEIlGMq1kPxyrxtCqYc+D+d2qihyQe3Vi1MuPiJEIFX4/DhGsNbKvM/z7NC0yywg0n+GG09S2LgmKDvmjmHMUoqgrQ8gLQ9ApH2yVcWVKlzqaASAuX6zsqmIN6HhFq07n/0rVBQgdn4Lsyqq6ecREg2BcOHAYHiJtsm13LaYce6/BHPCj8egF8OCplcDtP15ZrDVLLEu7q9HhP+rFXHxS+tyr+l2mI51Sz1se6n/Q73DUMoA4nc+BF06c53sXuyS0kEfjkEe+MQm2JvzaBiVb0v9+VVR+XRpO6ml3q0RfeaAKzyG+p8UOeFWh8E8iSGS3wQaX9URafEICYdBRHEUwD+YnWZz3UOmI5qcHjfaxDrOf4GhTWThadZ5DqJiDruY72YTFxFp+JGTO0bMBUboXzdojapsSwdlvoYcioREeTog8j+u/Q9adxIsAb85XkTayQ+AIfuntCl0mgpbdMlmMKak96/VUr5Gheyn0q20UOQ9BQP4mg1jGShqAlTtWXOjsmJOAJ/06GbA5+o1fF4MXEE9iWg2gv/q8nQeIL8vblihaZZYAeT+SMikBxWq7OTCyfxFKjANMcWsxJpRw7djbTtUvEIwOXB1O7ANFwIlZsxhSdutSmxfqTjceTIvVoaB1B5Fq5z/+eU95Vor4pkLi+UrV1SJS8Wy3yxY938cUQ7Qn2vTwjnNtm3Bw0fqoGVSyCHaab83y7hgWFhQwF8eZWxY53ltGI5jHXRrNCZ0gyNtqSwPw7dKYhkGWsiUJQTnopdWvoWyUJnGrpS418j0xi7Kz3qdqrw6DECLnVNGTTbqcitZRVr/VDvN9TmBKpS99zLfcXJQLQHIu1IuA0Z2gfhdiQVxmRTYFyIrxj8JdqAZZbOIUnHdOEZalVXe7zv+BsF63KiU7OWxM1Q4BoTnRKDmFQEcfl0nlizHVflZqjYgCmonNX5WpYvy2EMOdVIMgx9r+B0PgMDuyEZQrxFEKyd89rvuMcIH4X2x2H44PiFFRuh6bKT5kS1Sik/YAvP0UAFceqJMOXIlk1BYlidmJWbVLCe55zo9l4tdX5rOeyYv3Y1YxzRTYl6H3yqfuE2Eq3QNAvsYDI/JBWBaC84o2KQDwqrMf65vZYS6UD2/gjpfHLcjVTajFnzRkzDhXMavCSbRlp+g7z+Iw0k9xXhOv8PtTZ/4u3EgeFDKpYV1mIKZm7TtFiWOnasmx+vRoVv9shYTkqDDz5Ua3hDcOFymNKOdkZpS2qQ72AakqIL0SIXVHi1Q9XWQp1YzPQ8hjLC7x4Skg78caPhohIrNFlOH5bjWCei4nVHTnxqTaj41J9WgckBXEBJTnwqcmtoeCQ7QXjKiVDh7NSPUe5WManSo4JSgZvRQhJ8Ro9Z6YV1AWjyG+py4lO1lzlnfEhqRIWnSDsSOgKD+yE+oOVr4iCeAIyKT+7ArMZSSUUh3KLCU7hFjzsJA0X1E4SnFTPOY5FMEhIDmMQwIFoSWLEeU70dU7HB5jqd5izHMeRUISJaOtv7km7uh1ox2aQ2CyisyUtpnYx0QftjMLh3/MKytdB06QnjTlLi4j7W8DM2MkyAtQwSYKoBUtTd5GSgeAWmcsu8OqLfNwxPROANQXjLIi0ls7mOpCv98Dv1hnUFCzevs0LTLLCDydyQVFR3k0Y7yRm31s4H5madlGiPCkztj44JTKZ+J2btm6ByU14WcjLSjfPc32uJnMuDa+cfYerOm3ybxDBEu/T5lK+zEwnLaYMd6+ZGe1L4bh88k8thKnLDu6sMN5bPffF1ssd7PAwvRYXdMa33nwnVXriuTM+rxnfy8/pBn3BHv9Dg02Bwl3U1WU4TTpexTkQYyGgYeGcKjiSEgwkYysBIVnevfRNK7oIucBntNjQqPHXnhKvhacSnUreW0tV4tcyu0KWiljDuqir1aKe61YFx8anWCwVzCBQXccZdT5EOZHA/hFuQZBiTTeZcT0Xgy7meZhEwLqmIOp1GhafE0OQbGBcUNYwLT8VNM2r+Ik5WM0fjA5hsSkvsihowdeeq6FS2DuMtmM3LYFninC5jyGIjTgYG9+H0vACdT0OsT9/ThTVzXh9OOn6sDzoe11JaclJHyUpovFQbQE1z/ENSzg/YwkvUUUmMOkamdzclh3Xsqdw05+ym12PwowEdJz9ZN+u7z5pMzsm0JqAi00J3OrZC0yywg8nskNSIlsiNCkwYzUgqqJyTKCPpGLLvTuTwPWNld6b+fMxZt2r+Up6RbBp57u+RrmfB5ca1848niU0iokKUk4KC6pOW51ksywU71s2O3pTww354JCQI6ia4sdzw7iooznMO01BGS/IeDgkH45OvK/XA6gA0+QzVXi2BGS2jGczAobiwL64TDdDymJvKDb9VA6UnOM94VvjkIWEkC3/YaLjEupospwmn81iXFaE3reJRR1Lf/4eTmvcUc3TpFTDjzqeCXMlc3Bl3PnXn7j+Ymfoxit2a9VTjhXKPuicdGEs5KcyV3tX7NJS8wZfLfvJB2RxK7yQdG3c9hY/CwF6dZ6Yi6npy+3NZTyXgKZjx8SUZmiw8JUOTb2DcUNyoolNp84yCjTVMfERFp9QI4vLqPLH6bFxVm6F8g503ngaczmPIYiGpCPS9itP5NPTvhsQw4gvmSuvm7hYCkMQQdDyh+W2jzQKC9dB0KVRsnHKMSIib37CWX7CBCD7WMoT/pO6mlZrdNMtqmnAG/r5LxfrPNk7dsCFfpB3Ym4ANBfC79YamBchkOhYrNM0CO5jMDElFtJNcNte/G6MB3AWVc7JFipNFWh9A9v4QkmE9Ys3ZmE3vw5SvzeOZT/PYL3wdaX8cPH5cl30RU9o8fn0yDCMd1tVkOa2wY93MGM4IP+6He4eFbO6T9IJiw/uqyesHuIgKRD8bhEdDMiYUuQy8oQh2FhnOCcIK/8kXbilHeCoC9wwJL43oZUE3/H6D4YrS6e97R7/wgz5hpR++ttpmNVlOD860sS7tCF0551JHSrvaHU2qGJ3IiU+TwsaNik9J53jnU/804lPQpcJSXS73qciti6iETC69q/Co+LTCPy4+VXtn1+1OxNH5ZqRNXU9DB2D4sGY9ZRKAUdfTaNbTDOegkhgaF51CLSpkTcTlgeKmceGpqOGkjqrxEruce8pfBuXrdT5bniuxm4Ury7I0ONPGkIVERCDapaV17U8goRYtrQtUaNTKDFyF0x47GYbOp6Dn+fGM4IJqaLoEqrZMuX7bJ5X8kC28Qg01RKkhOo27KanZTf7SXHbTyqlvNw1f69Qx+EPVsGqBegqkHHUybQmqk6l+Bm72fGCFpllgB5PpGQtHjPfrGw7Ueuwv1y5uc6y7lcF9OC//u37gAxQ14Nr221CzY9EWOuJkcZ78otovCypxXfnVSblSMnRQW2sG6zCB8kU5J4tlIbFj3YkZyQo/G4C7hzS7CDTo+33V5LXWXUR4MqKla/snuJfOKtTSt8tK5te57tWo8I1u4VDu2G+uMHyyfuqFXjQrfOKgEHe0O8l5xVZosix/7FinjsVjw8a7cmHjSVGH5qj4VOIGb249lnLU8dSVyolPaehLjxWpTKLAlety51UxqTiXGxUTLeszqOBd4obmXOldbU58qvNC4SxK7ySTgEgHjLTjhFrV9RTrg3QEJIu4vOp48peAp/Ckc0kRgcTgZOEpHZ18I5cXSlZMEJ7qT7jxOF5iN6gLaW8QUzTaxW6DClC2xG5ZYMeQhUFL6/bj9LwEXU9pGa0xudK6irk3IkhHtVSv+7nx9WqgHBovgeqzjxN7Y+LhbtbzK9YRw8taBvExVU6BqNgkjgpNlZtn7G76Ub9mJl1bCpcswL9QMicynVOkIlO1d/Hmb1ZomgV2MDke/bAc1vp2J2eWNi4IVOhAMMfdGUlFkN3fRVof0Au8QcxZ78KsvvGU7PhIKoqz609hpBNTfx5m52fGBjlJDEG0G1xeTPm6RT83iyXf2LFuakIZ4e5B+NWQjLUP31AA7682bA3m74PbEWFXCL7fL7TmjKFeA1eWGt5aCevzKGZlRfhOL3y/T6cCO4vhz1YYfFO0M/9Wj/CzQWF70PC5lVZosix/7Fg3NZGMjIWNH82JT71piGQgi7opiyc4n0Z1oLSjt5vY8a43zZTLMr8Zdz7V+VRk8hmIOpDKuZ8KXFqOV++DtQUTSu9ypXozWWyKiIZ/R9qRkXZk8CAMH0KSIUwmrotXb1CDxn0lJ3VN6PH6JwhPrZCJTb6R2wfFK1V0Km3WEqBphKfjS+w8mIIqqDk718VuYy5ywo65SxE7hiw8khrR0rquZ6DvVUgOI95CKKybcxC3ZBLQ/ayKTqMRL74SaLxIzQzHjAO7pZofsoU9VFHHCNXEpjgq4+6mQBmmcrPmu53kXB4Pw/0h2FQA785zNW3CgX1xOK9Iu8tVLKLIBFZomhV2MBlH0nEVmJIhxvavXB51MAXK5y4wiSBHH0J2f2fMqmxWXonZ8gGMvzQ/Jz9HJNSC88j/AieD2f5RXKtv0MvFgaGDWvtb1DjnLnoWy1LBjnWT6Uurg+mBYSGVG+5W+eF91YZzi/LXSU5EeCwM/90rtOc22grd8NYKw82VUJbnvKeJPB0RvtQmpBzd9fr8yuPFpt6U8DuHNIfq62sMDYtQ32+xLCR2rJsZIsJQZrzTXUtCOBDX7KZIVmeBHsaFpyK3ilGgmXB9uayn0fK7nhRTJp74zLjwVJ8Tk/w559NorpQ3V3pX7tGud6Old7W5rCjvFCL5cc8nk4SRzpzrqQ0GX4dojwaNk0WMJ1duV6IbnScY40VEHVOjbqdwK2QSk2/k9msQ8ajwVFg77TElm1SnU2JIG94EyqB8LaZmO6Z8oy2xW2LYMWTx0NK67lzXuieQ0BFMJokEyrVr3RxK6ySbgp4XtKxutETWUwgNF0LdeRiPf+y2I+LlF2zgN6wlhZs1DOGdSkYX0TWyOFDSjKnahPFM71BsTcDtfTp2/mHDrJ/CtMSycCABFxbDJ+rNgs4hp8MKTbPgTB9M1L0U0jfPqN0QwB2AggrdCZrHgktCrTgv/5u2tAUoWYFr+8e03nWJ4Bz8BfLat8ATwHXNP2AKKoFcd4N4v4ZPTshwsliWI2f6WAc6odkbh3sG4amIjE0l1gXglirDzjwKTAAvjQj/1TNeIlfigbdXGt5SAUVz6Ng0F16NCp9r1fK4K0oNn206/jn+dZvw3IjwpnLDbXVWaLIsb+xYN3ccEfrS4+LT4YQ2KAhl1JUkqEg0GjZemAsbB22v3T8qPuVyn7rTkJ5iReKZID41eKHKo40O4pLrqJe7XZELij3asntNYNz5VOeD4EnGUC2PGxp3PQ0dhuEDSCKEybmVxFM4FjRu3L4THyvWkwsXb4Hw0clzZgBPwbjwVNKs+TNTfJ6MVQ3EByaU2NXnSuzO0mzQWYYPW/KLHUNODeJkYegATs+L0PmkltYBEhwtrZtdZq44GQ0M73hC33Og69v686F+59j7TAReoZYfspl9VNJIhEriUx80m9Rj+ctz7qbGKd1NKQf+pkPHzD+o1/nffIlm4VASLi2Bj9WavDemmSlWaJoFZ+JgIk5WLb3JcK4mffTfxehuj79s3h9yko4j+36EHLpH1V+PXzvJrblpye3aiAjOo38Gg/sxjRfhOv8P9fLcgAcCpasxngVKc7NYFoEzcawbJeWoq+ieIeHIhE3pbYXwjirD1sL8Ckz748I3e4QXc8HcBS59nHdUzq0l+Hx5eUT4360aOP6easOHas1x13++TShwwb+vM6fkHC2WfHEmj3ULQUaE7lzQeGcSDiS0/Dec1W52ggpOo86ngBkXnxyBgcy482k0/yk1xSrFjTqY6nzQkHM/FblhxFHxafQ+gVzpXd1o1zu/GROfKk5SeifZtLqeIu04kTYY2AfRTiQZwThpcHkQX7HOhb3BE5TGORqvMNbV7qh2K56IpxBKV6nwVLYOEyib4jijJXaDmFRkvMSuehuuqi1QsQEKqmyJ3SJjx5BTj6Si0P8qTmeutC4xpKV1wVqMr2h2xxJHM3k7HtOSW9AMtrpzoeGiseOFxcddnMV9rMHBsIZBPFMl1IloHpvk1oeVm6ZcI/6/bh3z3l0Jm+apHUeycCQBV5bCR+rMSYX2hcQKTbPgTBlMxMmoqHScuISqu4EyTdafZ4c1EYGOx3Fe+5buJAGm4ULMtg+NOYWWIhJqwXn4MyCC6+I/w9Rs18tHOtXx5S/DFNWf4rO0nO50dHRwxx13cM8997B37166u7upqKjgkksu4TOf+QwXXHDBnI99pox1o4iok+ihEDweHs9f8hp19txUDqsC+f2g7kgKt/dqFznQXfs3VxjeU72wJXIz4f5h4W/b9by+sMpw/oTgbxHh9w9rePDH6ww3lNtFjWX5cqaNdaeCpDMeNt6ey3vqGO10NxoE7oJKz/E7+SJanjfR+dSV0vsdyzsrYUvh5PvGnXHxabT0zkOu9M4La/ywMmCo98HZhScuu9OmN2F1PUXakOEjMLQfSQxjcnNl8RSom+IEjWHEyUK0a1x4ihwd74IF2sV4x6dO2lxmcomdo3PzsrWY2nMw1edgiupOeH9LfrBjyNJCRrqRvpdzXesOYzIJLa0rapiVCCsiMLgX2h5VhyKArxRz3u9PuA28QB0/YgsHqWAlw5SRnPqAmYSuEQPlmKqtx60TfzkIz0fhkmK4tmy2z3qcUAaOJuHacvhQzanfDMyDOcuy3BERDUJLjaiwlJ2ittyXaw07oVZ1Xo850qnd5Ppe0wuCdbjOvg1TuyMvxz/p44szZ6HMlDZj1rwROXQPzu7v4Ko+Wwcvf7kOIqkw4tQsOTeW5fTi61//Ol/5yldYu3Yt1113HTU1NRw4cIC77rqLu+66i+9///u8+93vPtWnuaTpTal76aGQLoRGqfbCjeWGa0rJu914IC18tw9+PSTabcnANaWGD9ZA7SK1mz0Z15YZ9sXgF4PC33YI/7qWsQBJYwzXl8HtvcLDIbFCk8ViOSF+l2F1AFYHgFzhSDQrY66ntqSwO6aBtduPWZUYA5Ve/dqWu0wEhrMqOHWk4InI1I9rjGbcFbo1u2mUVE58GkrDIwlIDQuVXvh0g2HrCXKFdZ5XqhutVVv0XJyMupWGD+G0PYaJtMPQAaTu/GkXtcblhuImKG5C6s7TbJj2xxjb1A2U6bz7JBi3H4rqoahexauRDkzLfcjgfiQ2gHvL+096DIvldMMU1WGK6pBV1yItv0HaH4feV3KZa8WzO1g2PTnoP1gz+bEMnEs3a2WI/2Y7u1hFGT1TH8sTUEE53o8MHdBO5RPGiNGM7vm6f9pScEUp3FZr8M8gr26hsULTGYiIA+m4ikuZuL6J5JgwM3cg14Ejf+ISaACj7L8TOfhzcLLg9mI23IJZ97Y5hbid8LHEgdQIEj6qZW2hViTWDZkkZFP6QV5Qjgk2QO0OqNyMyzuzkjez4R1I60O6I9XxBDRdgvEWIG6/1uSmwtou02JZIHbu3MmuXbu47LLLJl3+6KOPcs011/CpT32Kt73tbfj9+Xv/LndEhKNJeGZEw68nlsb5XXBRseGqUt0Vz3f5QSQj/KgffjaogdugAY0fqjU059ktlQ8+VgevxdR+/c9d8LmV49ddVgrf6oX9cehMig0Ft1gssyLoNmwo0K6dYPjHDoeWaYwAx2KMBoGXe9QJ+kRES443Tp+1OwmfCypcWjoH2vZ7pX/m95+EOBBqxWl5AAb3IW4f1Gw/6eeHpGPQ9TR0PTuhxXoFNF0KVVtnvFEpudBhM9Kpj918La5V10DN4mzaWixLEYn24Bz+NbTv0uqcig2YWYhMEmqFlvvUeQgqMK+6Bio3T3n7MpPU3H4yU16vWU0hXVtXn40pW3vcGBHNzQuD8ysWAlSYXwoiE1ih6bRHxFFRZUxUShwfSgjaMc4bHPsyrvz+a4gIdD+L8+rt2p0DMLU7MNtuy6u9V8RB4oPQ8QTS/Sz070Fi06jLo/cBeO2bGF8x2aZLMWe9G1f5+hPex/hLMOvfirz+Q5y9P8TVcKFODALluruVGLJCk2VBueWWW6a8/LLLLuOqq67i3nvv5dVXX+W8885b5DNbWiQcYV8MXozCMxGhJz1+nQE2F8KVpYaLihcmEynhCHcNwB39QjTXZmlLoe42bQkujYnAVPhchj9pgt89JDwRFp4Mw0Uler5lHsM5RfDCiPBwCN5Xc5KDWSwWyzSMZLXxQvkcTOAv5LLttheq6DT7x9bPgZvKzYy61Y0i2TR0P4dz5DdaXmM8SNnak27MSmpEHUzdz4GT+zAqqM4JTJtn7LQXEYj3YaI9mhPVdBnulVfN6hgWy+mGJMPaufzIb7SLZFE9FK+Y8cahxAeh9QF9TwO4fdB4KTRccMJ1cULcHKKCEo6pCJIsJIb15+KVmMqzpu2gPjo/DM6zGMY94VhLASs0nSaIk1GnjpNSYSmbc+046anv4PJq1wtPAXgLFzS8WiIdyO5vId0v6AUFVbi2fUhT/PPVFjyTQPpeQQ7/GjqfRlKh3DUG3D5M8Ypcd49VGuTm9mt4XLwPhg8jA3uQVAQO/wo5/GtkxeWYcz+NK1g97WOaNW/SAPORLu140HSpqt6xXsgmkXTMdgOxnBK8XnUHejxn3hA/Kiy9FoPdMeFgQjscjeI1cE7QsLMYziuCkgXKQ8qI8Osh+G6vtgUHLR25rdZwXp471i0UzQHDO6vgh33CP3cJO4ogkFuMXVWqi7xHwsJ7q5fH87FYLEuPwwkYTGtY92wIZ2B/bl137uzyfsc4mtT77pjh/cXJQM+L6pYY2APGheQawJxoBJRkWOeJPS+M5zEF63TeWHHWzBfCThZiPZh4PwQqYe2bcDddDmVr7BhsOWORTBLpeFzXZOEWJFAB1VtnLtxm4tD2GHQ/k6vwMVD7BlhxBcZ3gnraHO2UMEyABsK5A+by3LIpDeiv2AhF9SccI0YdTUXzFZrM+LGWAmfeKmSZISL6oeRkVDQa/Vkyky8/tvRtIsattaGjwpInkHfH0pTnngwhe+9AWu7T83O5MWvfgtn4zryV4znJEWh7BDlwFzL4eu5Sl4YxNl2Gq/FCqNlx0q4Dkk0jnU8h++5Ael5A2h5Bup6F8/4nrrVvmvI+xluAWXuTupoO3IWr8RKMcSG+Em1nmRgCKzRZFpmjR49y//33U1dXx7Zt205+h2VM0tFSuNYktCTgUEI4dIywBFDlha2FhvOL4JwJYslCIKIun2/1Cl253Kd6H/xWjeHK0uUnyLy/Gh4JaQjvnf3w/px76fwi7R7Vn1ZRb9vJ52IWi8VyHIcTkBYtaZsNL0bVkb7Kr2P8bAll9DFvqjC4T1bq5mSh9yV1MPW9BgakZJXOA090v8SQxiv0vqzuBoCiRmi6DMrXzVxgynXAM8mwdtI661ZM06WYooYZPluL5fRDnCz0vIBz6G4Y2IN4CqFy04zXuKP3p+0RrfoBKFsLq67FBGdu1W6jhAQeCshAOgbpCPhKNMutpHlGpbBjjqZ5GhI9hrGGNksBKzQtICKiAsukr+zML3My4x9MM8HlU5uf2z/p+2KHUks2hRy6G9n/07E3rqk7F7Plg5jixrw8hpMcgUO/QA7+Aokc1QtdXkzDBbjWvhnqL5hV5pNxezErLoMVl+H0vIg883dIuAXnqb9GBvfhOvd/Tvk6mtU3IAfu0s4hvS9p1pO/TIWmVARxsjYU3LJopNNpPvjBD5JMJvnqV7+K2z39/96WLVumvS6bXUK+W9QdNJCG9pQKSi0JaEmqkDNVcOKosLS1UMvUahYhZFtEeDwM3+sTDud22cs98P4aw43l4FlmAtMoPpfhtlr4cptwR7/wxnINBve6DJeUwH3DGqhuhSaLxTJbRISXRmTW5SKOwAtR/fncOYw9Ihqae2kJbD3BfqCIA72v4Bz5DdL3CkaySMlKjDd4YoEpPgDtj0PfK4x9SpWsUgdT6eqZC0yZBEQ6MNkEFDdhNt6CabgYU1Ax4+dqsZxuaEe4fTiH74buF0AkV7o6M1ukiGh2b+v9EB/QCwuqoPk6TPm6WZ9PK2UYJ41J9Orau2ITpnwdxjOz4DeRCRlNeXA0xZfQFN4KTQuAZJIQOsL8s+NHMZqh5PJoydvYzx4wHnB7VWQ5xQsZEYH2R3H2fB/i/Xph2WpcW34LU701L4/hpONw5NfI6z9ARjr0Qk8hZu2bcJ317uPaRc4FV+0OnJtuh+f/CTnwE2T/T3Bifbgu+8JxKrnxFWNWXavC2uFfae6UtwBxB7R7XzIEdkJgWQQcx+G2225j165dfOxjH+ODH/zgqT6lGRPPCn1p6MuoQ6Zv7EsvH8pMP5qWuLXEq9kPzQHYVLA4wtIo2ZyD6Yd96q4C7XL07irDzZUL655aLC4rgbMKYW8MvtcHv5fbRFehSYPVP17HSV0BFovFMpG+NLQlVZSfDQcTEM5qCPimORjHhzLqHLipwkw5dxYR6H8N58i9SM+LGCcNJSvBV3RigSnaCx2PQf8exj61ytZA02WYkpUnuOcxx0lFMZF2DI6Wxa26BlN/wUnd+RbL6Y5EOnAO/wppfwyTjiGlGoky09mHRLuh5f7cOh3wFMLKK6F2x5zyzbLZNHtSborNkOZBVWzEzDKjN+6Mz3EL5+towjqaTn+MYfKyyIDLDbjAHPvlPv6y0dvmxKSl7ogREeh5Huf1H2oXNtAcps3v1Q/XPCw+xMkgRx9GXvsWEjqsF/qKMRvfhWvjO6YNV5srLrcHdv4hTvk6nGf/Dml/FOfRz+XEpsl/D7P6RhWael9Coj2YYK22px0NBbdCk2WBERE+9rGP8Z3vfIcPfOADfOMb3zjpfXbv3j3tdeFwmNLS2b2nRISYo/bfqKMhq1P9PP5dGMnCcGZm9eReA7XeyaJScwDK3KemHC3tCPcNw4/6he5ciVyRG95aoQLTQmU/TUXSURfV4QT05kS6kazgoDtlJR5DtQca/OrwavLN7jUzRl1Nnzki/GZIeF+1upo2F6rQF87Ca1HYbtdAFotlFhxKQCgLDb7Z3W8+IeAi0J6G68tgfeDY6wQGXs8JTM9jsikoWaHzzRMdc6QL2h8bDxEGKF+vc+BZOPklGcJEOnT+X7VZO8jVviGv3Z8tluWIJIaQlvuR1vshNgDFjUhp88zdgakROPow9L6oFxg3NFwAjZfMKadYxIFIB30pGKiop6y0AVNSO6f56OgcuMCljqT54DaQdLQSYCk46a3QtBC4vFC2bkw4OtVOo4ViTGDa+yMYHlWGCzAbbsGsvQnjnuXMYZrHkIG9yEvfQHqen/QYrs3vx/hL5v0YJ8K1/q3g8uA8/RWkfRfO8/+E+/w/mHQbU1SHqdmO9L6MtNyH2fKB8VBwJ2VDwS0LiuM4fPSjH+Wb3/wm733ve7n99ttxuRan68zTEeH2Hu2mFnPm5+EsckO1F6q9hiqP/lzlHb0MSk+RoHQssayGfN85oOV8AKUeuKXS8JYKKFyAznVTMZgWnhvRnJKWhIpK09GfEQ4DjMBPB9Q9cFWpOpVmer7bcmWIu2Nw5wB8LOdguqgEfjMkPB6xQpPFYpkd++P6qTGbYXO+IeB9Ge1w98bycTeTltLsV4Gp+zlMJg7FTeAvPbHAFOmA9ke1DGeUyk3QdCkmOLOOytpBbgAT7dZcz4YLcK+8Gqq3LfmNZotloZF0HGl/FDl8D4TbkcKqXND3LPLNup7SUtbRBlmVm2HV1bN2HkHu/ZoYwIx0QrCe9tXvYSR7NiuCHuY6Rc1XPhPoWJoRSDngWQLDhxWaFgBjjJaznaaIk4WOx3EO/mLcweTxY1a/EbPuLXkTf5xYP/LKf2ibSicNxo1ZcxOu7R/FFFTm5TFmgmvtTZBNqrNp/09wytfjWvfmSbcxq69Xoan1QeSsWzFu73goeHLYhoJbFoSJItOtt97Kt7/97RPmMuUbEXXQTMRnVDQqdOn3oNsQdGndeZGb434u8UCVBwoWSaCZKx1J4eeDcO+QEM+pOpVeeFeV4Y3l4F+EErm0IzwzAo+HNfh8IhUeWB8w1PtywpwHRucsw1ktSTwYh71x7YL3kwHhnkF4a6WKTq6TzJCMMbynGv68Vbh7ULi1Sp1SFxfDb4ZUdPyELZ+zWCwzJCPCK1F1Rc6G+YSAi0BXCm6uhFUBo4vG4UMqMHU9g0lHVWAKlJ1YYAq1qsA0Wn6DgaotKjAVTt+tePK5OBDNdZDzl0HzdbhXXgnl65fEporFcioRJwNdz2oO0+B+xFsEVZtnLL6Olr/S+qB2gAMoaoDm6zElK+Z2TqkoJtSC+IKw9q241ryR9ngV9M3PiTSSp3wmUIdn0oGkwFJYeVqhyTJjJBVFWh9QVXk0PG0hBKZMCvbdgez5HpIKAQZTcw7mvE/jmkNIWz4w62/GhA4j+3+K89zXoHIzrvI14zeoPVeD5OL92sJ2xeXjoeDJMFJYO+edKcmmIBnOiW0u7RzoK7YTkTMcx3H4yEc+wu2338673vUuvvOd7yyqyATqcPnrZkORS3OJgi7wngaZRKNkRHg6Ar8aEp6LjF++wq8OpmvLFuf5DqSFR0LwWFjGLNYGFZbOK9Yw20rvyc/jhnJIO/DcCNw7DJ0p4Uf9wnMjho/UClUnOcZ5RbCuQAWrnw7Ab9fC5kJ1m4Wy8GpUu/pZLBbLyWhL6kZF7SzEovmGgHenVYi/vtwgw0dwWu6DzqcgFTlpKY6IqLDU/iiEc01ojAuqz4bGi2e8ASpOBka6MIkhKKyG9bfgWnHZnBe/FsvphApEu7WTXO/LYFxI+fpZVclIuA1a7oWRTr3AVwKrroGqLXNaO0k2DeEWjJOF+vNwr38blG/AGMPeQYfAPKeBeXU0AVlUbFoKWKHJclJk6BBy9EGkbRdkcn7lQJkKTKuvw/iK8/M4Ikj7E8hL/4qEWwAwRQ2YHb+LWXH5KRVWjDGYHf8Dhg4hfa8gT3weufHfxzrbGZcb03wt8voPcFrvx73i8nmHgouTgWjPuBI/EZcXKWqwJXlnMJ///Oe5/fbbKSoqYsOGDXzxi1887jY333wz55xzzoKdQ7HHUHwafoq0JoTfDMMDw0Ioo5cZAzuL4G2Vhh3BxSnj60kJ9wzBM5Hx0rhKD1xRarigGMrmkAPldWm524XFwqNhw539wuGE8Dft8Dv1sOYEMyZjDO+pgi+2CXcPCe+t1q50F46Wz4Wt0GSxWE6OiLA/DrEsBE8QP+SIZs61p6A9qZ3i5hoCnnagN+XwnmA/NXvvwel4HJIhpKgBSlZOGtMlm4JYH8R6INqb+94D2VzHB+OGmnNUYAqUzej5kklAtAuTjkFxo27QNl48YweUxXI6I9kUhNtwWu5FOp7EOKmTdngUEd3Qj3br10juezoX4ubyQdMls+5EPnb83DrMJAahfB2udW/VY+WMA5GMcDShDvK5IqKiO+TP0ZQRKzQtGB0dHdxxxx3cc8897N27l+7ubioqKrjkkkv4zGc+wwUXXHCqT3FZIKko0vEo0vLAeHkcQMkKzNo3Y5oum9Obdjqc4SPIC/+MdD2tF3gKMVs+iGvTrXnJesoHLo8PZ+f/B/d+Chk+iPPqN3Gf8/Gx682KK5C9P4T+15FoLyZYM+dQcEnHINIOkpO5vUXqZJKsCk9OGsJHVWxa4Jwqy9KkpaUFgJGREb70pS9NeZvm5uYFFZpOJ7pSwq4Q7AoLh+Ljl1d44boyww1l0OBfHLG7KyXcPQjPjchY7tVZBYarS2Fb8ORlbiJa3pcUXVwV5MoYJy6kjDFcnjvev3RCW0r4uw7hd+thc+H0x7+4BGq86kR4JATXlTNWPvfMiPBJseVzFotlMmlH6EqpUNSaEF6PaQmb38WkXJNYNicq5YSljhSkpgj/u6R4+hBwAZx0gmgqTjiVIpLJks6kcGeirE53c2X8Lkj1IMF6KGqCVAgG9yFjolIvJAanPrjLC7VvgIYLTzj3EiejLqlUBJOKYEQQtx9T3Kgd5E5yf4vldEUyCRVx431IrE87NYZbIdqNpEYw6REoXnFc+aqIo9U0EwWlaLdu5h+HUSF45ZWz6tQomZwxIBnGZJPaha6gCrP1tzErr8b41EYZzwovROHhYaEvA2fNPkscUEHorgHYnZtzrp3jcSbiNpCVqcfNU4ERkSVyKvnhs5/9LF/5yldYu3YtV1xxBTU1NRw4cIC77roLEeH73/8+7373u+d07NFOTKFQiJKS0+8DQjIJ6HkB6XwK6X4esrlWSi4PpuECzKproGrmAWwzwUmENYfp0C/GSsNM8w2YHZ/CtUS7tTl778B5/h/B5cP9ptsntazNPv5X0PcaZtN7cG18hw6MQwdVICpumpH7S1IjKjIh4A5AUcOkjiMiDox05ZxORnfirLPJkkdO97EOVIxpT8ETYXg0LBycIC65DVxQbLihXMvFFks4GcoIPx+AJyPjAtP2oOGmcu22NxUiQlsS9sS1pK0zJfSkNQhyIi6jJSPrA4azCuH8ovEg8KQj/Ec3vBITfAY+3WBYWzD9c/5hn/DNHmF9AfzTGoMAHzsoDGfgz1YYdhRZocmyPDgTxrpTQSQjtKV0p/5QXNiXgKH0eNvtoAuKXSqGd6bGxaXBzPHH8hlo9EGTXztmNvm0VFucLGRiSCpGMpMklEoTSaeIp9MYJ02hxCjNjrA+081q6WOFDNCcbKM4PaCLyVivCktOauon4S2CYC0U1kCwBgprddF5TAyCiEA6mhOWwphsLubAVwyFVVCxCVO6ElPUqPO1OXS4sixd7BgyNZKOQ7wPYn1IvA+J9kCoFaI9SDqqgfu5mY54CjTL1hvU951kc+/PCaJSrAecKQYI48q9R+v0q6geCmtOalIYe98mQ5hUBJwM4vZpF/PSZkzFWVrOWto8Fhren9Y4hQeHhaNJnSs2+XQjb7bEHfhhP7QmNU/zrRWwfQ7lwMeSduBQEv5ipWHTCTYNF4vTztG0c+dOdu3axWWXXTbp8kcffZRrrrmGT33qU7ztbW/D77etQiE3EPQ8r+JSz4vj4hKoe2nVNVq2lqfyuFEcx4H9dyKv3p7LYQJTtU1zmCo35vWx8o1Z/zZM64NI/6s4z/49rqu/Nia+mRVXIH2vIW2PIBtuwRgX4i+DxIAq8Sd5HSUVHReZfMUqMpnJRbvGuDRLIIKKTSMdSOka253EYjkJI1nhpRF4fgSeH5FJQeYuox/yl5cYLinRoOvFYrST3YMhIZ1TmHYEDW+ugKYpXFRZEXbH4OkIvDAijGSnPq7LgDcXDOkI9KS0HO+xMPy3gfOLdXLT6Dd8ol74v12G3THhn7uEP12hHQCn4sZy+E4vHIjDvjicVWi4sBh+PSQ8EYYdtnzOYjljcETF7bYkHE0Ie+P6cyirO/ZuAyUuFZdSzrio1JlibLybSJVnXFRq9EG1SeDKxiAdg0ScdCjKQDpBJCNEHA+OOPjJUOLE2EiI9dLPusxRViTbKY934I716CI1GZr6CRi3ZiUV1o4LSoU1Y+6FY5FsSudeyQgmHcUA4i3UBWr9BZiyNZjiJg0VL6iyeZqW0xYVa2KTBaWRbnUoxfpyglICFZQM4i0ATyEUViOeAozLjWSTWpYaPqqb6NFuzbuVKWq/XN5xQSlYB0V1UFA9o/WPOLmKkGQYkx5Rl6G3UEWk2h2YsrW4SlZC8YpJ730R4WBceDys85u+jI5n6wPgm2OmUigD3+3TY/kM3FoFa/KkP7uMzvcyS8RGdNoJTbfccsuUl1922WVcddVV3Hvvvbz66qucd955i3xmSwNxsjB8UMWQvldgcP9khThYi2m4CNNwIZStWZAPSKfzaeSFryO5kjwTrMPs+B3MyquWxQeycfswOz6JPPBppPt5pONxTNOlel3Dhcgr/6GD5dABqNigJXOJQcjE1RY6jY1Ty+XaGBeZGk/8ehTVw3BCd+Nivfq7xWIZYygj7I3B3ji8GtUFkDPhw9djtHTsspy4VLqI4hJo2PjDIbhncDzke33AcEvV1FlJHUnhwRA8EZ4sLvldsLHAcFaBBpXX+bQbkyc3fmRECGd0cbc/riJbe1KP82QYriyFd1fDJ+vg7zsNhxPC/+uCP2mSKcPOSz2GK0rh/mHtxHdWoZbP/Xq0+5yMP7bFYjm9iGfVDdqWhCO5MriBDESyupwsyHUeDRjoyYyXwQ1PIYj7jYpKjV6HJneCRkYocKK6CRoOI6kw0awhIh7C+EiLB5cRik2aKpPgGucoGxMHaIofoTzaijfWpYveqZwPoKHAYy6l3PeCyuM29EYRcSA1ok6lZESdFi4vxl8Mpaug8ixcxStUVCpqWDJRDxZLPlFBaSSXWzYqKHWpQyk+oILSWAmbSwUlbyEU1iLegvH3VzqqQtLQQS2Vi3ZPX6bqKZgsKAXrIFAx7Xv1uHPOpsbL4DJxvZ8v51KsugpXabOW6BU1ThkFk3K0K+bDIf0+4kCNB7YWqJgzV7pTKjKNOFDshvdV6ZwtX7gABy2fWwqcdkLTifB69R/J4zlznrY4WQi3Iv27oe9VZOD18UDvUYoatF684UK1CC7QAsEJtSLPfx3pekov8BTg2vQ+zJYP5DXvaTEwVVsxzdchh+9BXv53pOEiDQT3BDD1FyBtu5C2RzAVGzAuDxKoUFdTrBfxBo97jSUdHxeZvEUnF5lQZ5MUNUC4BZLDSKDcWrItZyzxrNCaVFHp9RjsjQs9U1RENPnh3CLDeUUqMgVOQZc8EeGZEfjZgDCQWw/Ve+GWKsO2wslZSlkRnhuB+4dhb2x85lDigZ1Fhp3FsKHgxOV9HmOo8Gre1NlBeEclHEnCLwY0B+qhkPBKDD5VZ/hEHXyxTTObfthv+EDN1Md8S4We02Nh4XeyGsxb5oHhDLwShTdYV5PFsuwR0TGqLalf++LC4QSEM5BwdMFV7NbFhBHoTKuo1JWeeke9xuPQ5EnRaGI0mTCV6SFMIgSRGDhpklnoNQEipoCYqwBMFYXuLOUS55LUa2yJ7qYhdojyWCu+WJeWq02Fyzu55C33s/EUnPC5avOWsGYrZRIYY3TOFqiAuvMwpc24Rt1KvpJlsTlqscwUEVHXz5ig1I9EOtShlBia4FACMa5cqVshFNUjnsC4CCSiIk+kbVxQinZP/371lRwvKs3i/aVh+/GcsBTCOBmNffGXQuXGXBncSihZqW7FExw3lBGeiajD/HDOjFXvg9XuyXlyc+FQAn7Ur/lJ1R54f/X8gsSnwhgV/K2jaZE5evQo999/P3V1dWzbtu1Un86CoDtALUjoCAznvkfaj9/Z8RVjqrZA9VZM9TYI1i/oh6WTGEZe+S/k4M9BMoDBrL4ec87v4CqcWTvYpYZxuTGb3gdtjyDDR5DWBzCrr9frVlyuQlPHk8i229TSWVilnRGySXUfBWvHjqUi01G1iXoKNctphn8P4y1AfCXjHwy2Pa7lNEZEGM7mSjSSo4sfzSjqSx9/e2NglV+DtDcVwo4g1PhO7cLg9ZhwZ78KOQBlbnhrpeGi4skh3ylHeCQE9wwJ/bnn5jLwhqDh6jLYUnjyUPDpMMawJgD/sxH2xeDfe1SU+1Kb8OFaw0dqDf/YKTwaFs4r0tK4Y9lQAM0BaEloKPibKvQ5/CpXPmeFJotl+ZF2hI6cW6k1KeyJacltOOdW8hktgXMBI1kN6x7tBHcsBcah0Z2giREas/00Zrrwp+KQTYNkyWIImULC7iJGXLVkvV78PkNDupuLYs+wJbabhughSmNH8ca7MVOV0gD4y3OC0gSXUqD8pM6HaQO7/SXaBr1iI6a4EYoaIVhn4wkspw1j3dqOE5RaIBFCMlFMRluhicutgpKnEIoatOTNmLGgbg3pHoThw+OCUrRbhZ+pCFRMzlMK1s06Z1adhhF1K6UiGHFU6PKXQcNFmIp1uIpXagSMv3RGr0dbUvMxd4WgOw2FLljth8Acy+OO5eUo/HxQ3UbNfi2Xy9exj8VghaZFJZ1O88EPfpBkMslXv/pV3O7pPyy2bNky7XXZ7DRBGIuIZNOa9RPrRWK9Wsca6dAytGj31HfyFmIqz9Ig76qtC+pamnSuqRGc3d9B9t85NuCY6m2YN/w+rqpNC/74C40pXQmrb0T234m8+k1k1TU6Eanept3mEsPQ+xLUnZtzH9Wr8JcY1J2AQLnunMV6AdFBvGTF7P82hdUqNKVHkEzCuposyxIRIZLVEoyBtH4fzEB/GgbSwmBGMz2myyMCddRsLFBhZFOBiiGjgdenmvakCkx74vrpHzBwY7nhmjLwTXBVxbLCvcPwm6Hx8rhiN1xbZriyFCqmyU2aKxsLDV9cBd/s0VK6/+oR3lVluKLU8HBI+E6f8BcrOK6EzhjD9WXwb93Cb4aEN1UYLi6BX+XK5z5py+cseaS5uZnW1tYpr/vEJz7BN77xjUU+o9ODUEbG3EoHE8L+uLoSY1kV6oMGXC4tw+hMqbDUlYJjh2GDUGPiNMkQjZl+mpw+KjLD44tR4ybmDjLoqiDsCZJ2efE7SdbF93NB5Em2xHZTH1NRyTPamvxY3L4J7qTanKhUjXGfPHN1qsBuMxbYXQ1Nl2NKVqhbqahx2nwmy/LlTBxDRBztej3W5a0fibRBuA2SoVzJm1q/xeUZdygVlCPuwCRBCXJVMhMdStFuzVdyptrpc0FB9WSXUrB2Ru/X455HNj0hXymq6yRvERRUQuPFmLLVKiwVN01qnnQyRvMud4WEF0ZgKKMZcZsLNFsuH4jAoxF4KBcRt7UQ3lYxfdfMfHHqFQvltBeaHMfhtttuY9euXXzsYx/jgx/84Kk+pSkZC1RLR7UONhlCYn0qJMV6x39ODOl/7XQUVGJKm6F09dh3CqsX1d4r6TjO6z9A9v5Qnwtgildgzr4Ns+raRbcay6iFM9qtCr6TBRwdUAuq1UY5i4FpFGNcyMZ3Yo78Gol0IG2PYlZdiTEuTOPFyKF7kPbHMHXn6u19xUhBlf4dR79G8RZBceOMa48nnYfbh/hL9TkmBqGoYdbHsFjyQdrRrKFYVrsLxY75OZqdfFk0K4QniEsz2YExBuq8mkW00m9Y4defV/igeJEzlmbCYFr42aCKLwK4gStLDTdVQNGEmUw8JzD9akiI5mYINV54Y4Xh8pLJYlS+CbgMn6wTqryGnw8Id/QL765St1VfWrOX3jKF+fTqMvjPHs19akkIZxVAuUcnay9H4VzrarLkkdLSUj796U8fd/mZmrk5W7IidKdGHaGardSR0mDaDLogCLq1a1E451ZqTwoR5/ixp1BSNMogTdkBmrL9NDiD+MiC2wsuL0l3gAHvSsLGT1w8lKf62BDdwyWxvWyM7qE+dojieBeGaVxKBZUqKE0M6PaXzryU5oSB3TsxZWttYPcZyOk6hoiT1fn/REEpfFQ3t5NhJBPLCUoGcXvGHUoFleriO0ZQAn0PSbRngqDUpcefMqTbMzmkO1ina0/X7GUGLWFNjpfBZVO6ie8ryeWibdbQ7pKVc3YaRrMaSfBQSNgX06YE9V5YUTj/8riJOAJ3D8ELUf394mK4tjS/jzEV1tG0SIgIH/vYx/jOd77DBz7wgRmp1bt37572utEWlid93GxK39zpKKRGkPSIikipkXEhKR3VNvbp2NjvJxSQJuL26Ru4sHrsg9iUrlJxyX/qWmtKJoHsuxN5/ftIchgAE6zHbP4ArHszrkW0HUu0BxnYA/2vI0MHjs+lmohxYSrWQ/XZmlU1CwunKW5EVl4Fh36JvP5dZOUVOmA3XapCU/ezSCY5JmSZwmrE7dPB2kmDywcFFWOtM+eMv3ws9E4Ka+Y0uFsss+WJsPDv3ePiUj4+2Eo8uqNU6YUKj6HSo8HWFR6ozXUhWkjRJV+MdpJ7ICRjr8v5RYabK6Fqgisp4Qj3DWmJ3KiDqcEHb680nF984uylfGKM4V1VGs57R79wRz9cUwZPRODeYeHy0uPD0ss8hguK9f/g3mH4eJ12nxstn7NCkyWflJWV8Zd/+Zen+jSWDbFszq2UgsNxYV9cBf2R3DoxYLQELu5ATzJDewq6M26cSUtOgxGHOmeYRmeQJmeARglR7krpPMPtJev1EqGeHvwksw6N8UOsjr7A+tjrrI7toz56CH82OvVJegI5Mal2XFgqrJ5VbqcN7LbMlOU+hoiT0TK1eJ8aEGJ9SLgVIh2QiiDpGCbnLhK3TwUlXxCC1YjLN6WgBLlmRJNcSt1aPTMVnsDxotIJAvVP+pxGg8aTYUwyjJEs4vapKFz7Bs26LV6hwlKgfF6icHdKeCosPBLWLDmv0e6WwQVYnqYc+PEAHMgtP99YBjvz28D9hNgw8AXGcRw++tGP8s1vfpP3vve93H777bhcC1QMeSwjXTgP/8nc7uv25gaG4nEhqaAaU1iV+xCuXnIBhJIM4xy4C/b9GMl1DzCF1Ziz3gsbbsa1SB/qkooi3c9A51NI6OjkK40LCisxgUpV3o0LUmEdqFNRZGAfDOxDDv5Cu981XzsjwckYF2b925Ej9yKD+6HnBag7F8rW6eAb7YbuZyHXlQ7QwdNfiojk7e9ovAWIp2A8DK9geWZfWZYXWdEyimMpcEGhW2vcC3M/B13muMsKXVoWVuWFSo+6YabqcracmKqT3IaA4R1V0ByYLDDdPwx3D44LTPU5gemC4rnnL82Xt1TAcMZw37BmRNX51HH2y0F4/xTB4NeXwRNheGBYuK0WLsmVzz0TEdLO8v97WizLARGhL62iUltSGwe0JNSZlBB1UgbIksgkGUpl6Ui7aM/4iDIq6IwvB4okTmN2kCaGaSJMvYnhdbnBbRAgRhE94sWfHKA+to/m2H7WRPeyKnaAqkQ7eqtjMVBQNe5OGhWWfMWzmgfNKrC7qHFWLiiLZakwFpOSE5Qk1gfhozDSnjMwxDTw2hgVlDy6biRYi7i80wtKIlo+Gu0aF5RGeiAVmvpEfMXHi0rzfE+Jk51QBjeCkZzbsKBco0bK1qhjqXjFrLObpsIRLQl+LCw8HdE4hnIPbAiAd4FkgZEsfL9PmyN4DNxSoQ1TFgsbBr7ATBSZbr31Vr797W+fMJcp7/iKtaW9NwjeIMYb1JaK3qCWSHkLtcX92O/BnLhUtKx2WmSkC2fvj5BDd0MmBoAJVGI2vhM2vAOXb3HeVTLSibTcj3Q9Ox58PupSqtyEqThLy9KmcflItBfpewU6nkBGupDDv0I6n8S19bc12+okmLI1mKaLkaMP4+z5Pu66c8ddTft+rOVzE4Smsfvle/LjL7NCk2VR2R6Ev19jJglHBa5TJ5KcSrKik5i7B4X+CZ3k3lFl2Dqhk1zSER4Yhl8OaiYVqJjz9kp1A53q184YwwdqhO604dWoBpFn0UnaDeWT3VgA5xePl8s9E4GLiieXz523iDt4ltObZDLJf//3f9PR0UF5eTkXX3wx27dvP9WndUpIOUJ7TlRqSWgZXG86F9qdTeHLJsFJEEk7dGdcdDgBeiSImMnzMpc41EmIJkI0MkKTa4RSk8TkpkspXCQzLgIjR6mJHmFVbD/Nsf2sjB0gkI1NfXLe4ISSt1yeUkHV3MpoZhLYXdSgbiUb2G05CUttDJFsKheRMioo9ULoKEQ7xwWlXHmpuP363vKXQrBejQkwpaAEOVEpMThBUBoN6Z7mfRsoP05UMr7525Ilm1RhOBnKCcO5bLSiei2DK12lbqWihrxWYyQd4cUReDikOUyxrLritxVqY5WFYiAN3+2DoazOh99bpfEOi4ktnVtAHMfhIx/5CLfffjvvete7+M53vrO4IhNgCipw3/D/FvUxFwtxstD1DM6BnyFdT48FwJmiRsy6t8G6t+DyL87KQoYOIkd+jfSNlzuakibtOFB/PsY3s/MwwRpM8FoN8+59CefATyHah/PcP2LW3oRZ++YTikLG7cWsuxk5+gjS8zwSasGUNmOaLlGhqfclJBWZ8fnMGX+Jfohkk3kNBZdsCkTmlGNlOb0p8RhKTrtPkdkxlcBU6oa35sKxR4WjRE5gunuCwFTjVYHpopLFK5GbCS5j+FSd8L9bVTDKCng8cO8QvO8YV5PbaKD5j/uF+4bh4hLDxcVw95DwUMgKTZb80d3dzYc+9KFJl9144418+9vfpqqqatr7LfUmLzNh+JjQ7n1Rh1AyQSyTxpVNEsxGKUkPE8xEeIl6XnKtYMQc8+YzUCIJGgnTZCI0EqbeRPAYXZE4QAQ/HZQQwYcjwh8c+CwXDtw79UmZXEfdiQHdhTVzXpyOZZWmwjaw27IgnKoxRLJpiPUcIyi1QrQLSUchHVMnoIB4A5qfFCiH4katwmB6QWnKxxvphD3fn0ZUMvp+miQq1eZvzZCOjecrSQaMV4Xhys2Yyk26TiteuWD5wYNpnZM9FFJXp8tAgxdKFrhPkiPwUhTuD2k5crkb3l+tMRCnAls6t0B8/vOf5/bbb6eoqIgNGzbwxS9+8bjb3HzzzZxzzjmLf3LLGIn24LTcDwd/rt0GRAdWU7kJs/5tsOLqxXMwhY8iB36G9O/RC4zB1JyDab4OU7Z6zsc1xkDtDlyVm5H9P0HadiGH7lElfvN7T1h/bKo2Y6q3In2v4hz8Je5zf0+DJkubIdSCdDyJWX39nM9tZufvQnzFOUtqSOuo54kMH4aRDv05WI8pXzfvY1ospwNTCUzFbri+zHBFKfhd4wLTfUOaWzRRYLq5UoWopSQwTaTYY/hUPXy5TUsAMxl4PCK8uUIFxolcXwY/7tdyueGMZjvdnSufG0znv1Oe5czjtttu44orrmDLli34/X727NnDX/3VX/GrX/2Kt771rTz++OOnXYlUPCu8FtP30ctRDe3OoqUYxUN7qI21UZiNAkKrq4b7vevY59quXW0BNw71RGgirOISYUrM8bXOWQydFDNEAaUkKCfBeXRySe/P2DIqMvmKJwdzB2sgUJlXB5EZPowgmllZtxNTbgO7LfnjVI4hzu5vacOgTFzDtI3RuAuvBnJTvAJy76W8nMHQQRWZjDvXobFOXVCjId2zyECbDZob1Y8J1mg3uPJ1Y8HdC7nZLiK0JDUv8rEw9KR0PrY2AP5FSM1pTcCvh6E713yvwadOpqJTYLAcyeWlLpXUgtNOaGppaQFgZGSEL33pS1Peprm52QpNM0CSIaT9UaTlAS0ty6YA0VLAhgvV6VO9LW8q+EnPJ9qLHPwZ0v2CXpDr7maar9NBbar7ZFMwfBgZPpQLtxtERmuRjUd33ooaVWGvPhvjL8V4/JjN70WKG7V7Xvtj+sGw5QPTfggZbyGm+Xqk71V1WZ39EYy3ANN0GRJqQToegwUWmgC11I4KTcHaeR1KIh1jIhOgOy/eIKaofp4nabEsXzI5gemeYwSmG8oMl08QmOJZdfj8akLI93IQmCayqdBwdRk8OKw7g6VueDAENx9TmbsyYNhYoGHDDw7DLVWGswqEvXG9/Tun3yheMET075MVqPYuj9fbMj2f+9znJv1+wQUX8Mtf/pIrrriCxx57jHvuuYc3velNU943H01eFgtHhEMJeGFEeCICXUnN26j2wrpcpoiko0jsCCnj5YWCs3nWNNLHuLtnFcOcTwfrGcAzZV6SksHQQQlh/DQQ4a3s51y6qGMEVzYOR3+kN2y+DtNw4YI+b4l0Ylwe3Ns/qjlLyyhGwrI8OKVjiNuPSYWRqq1j4uyCfiJl4vq94QLMqmsW8pEmYWJ9sOIKXGd/ZFGqIDIivBaFR0LCi1EIZzTzc0shuBfhI384A/cNw57cy+03cEUp7CxanMc/lv40dKXhqlK49NT1BpvEaSc03X777dx+++2n+jSWLRIfQLqeQTqeQLqegUwSJAMYTPl6TOMlOukozm8t7QnPKZPQDm5HHwQnqw6m+vNV6CqsPv72sX6k5znofh4ZOjTmvpry2AB9r+amYka7G6y6RtvfrrgclzeI88p/Ih1PaJj4mpumP9HGSzGvfUtfw7aHMGtu0vK5Pd/R7nexfg11X0i8Qd3BkKzWds8xSE+yKQi36i9la7UjYugwhFuRYO2cu0tYLMuVaFbYFVI7dig3pEwlMMWy2oHt10NCdEIG0825DKblJni8pwpeHIFBj5btPBZWV5PnmOdxfblhX1y4d1h4eyXcUG7YGxfuGxZuqVy87KmkI/xkQDOwBnK7i8VueFMFvKcaAktlm88yb1wuFx/+8Id57LHHePzxx6ddJC4HelPqWno8rEJTNKtZZ+sC4Dvm43YgMsyzro287F1DMjeN95LlbHo4jw5qmCaDJUcKFx2UEMXHCkK8k9e5hDZKTXLsNtL+qDoiCiqh7vy8P9+JSGJQ85e2/Ram8eIFfSyLZSKLNYaYwhrEuBcvQ2xUaPIULM7jodEqRgRXzfYFF5lGssJzEXgwpEHfWVEX0SofLMZUI+XAo2F4MqIuUwO8IagCz0J0sDsZItoIIuHAOys1G3SpdGc+7YQmy+wQcWBgL9L9nApMg/s1d8nJAIIpXoGpOxdWXI4pWzfv1pKzOzeBzie1o10yAoCp3oJZ/3ZMcePk22ZT0PUscvRBZOjg5AMFyjFla7WDQUE54ivVrnNORjstRDqRof1a4ja4DxncBwfuwrX5fZi6czGpCPL6D5EDv0CCDZjac6Y8X1NQAU2XIgd+iuy/C1n9RkxBJVRugv49SMfjWma4gBhjEF+ROppSEbXlzoVIhwp03mJMUYP+LUY6IJuEWN+83VIWy3KhM6mtcJ8IC6mcOaDMDdceIzANplVgeigkxCZ0kbt5iYR8z5UCt+HWavjXLuHVqD6nF0c0BHwiV5TCN7qgJQEHExoK/l9u3WF7LAyXL4JpZG9M+D8dQkduvew2+hXOwje6hNt74K2VwsXFhp3L+G9iGWc0VyUWO7G4shSJZ4VXc6VxL0VhMK3hsXU+KPJPXjA5ou+rZ0bgUKKR0WZxFcQ4j062002AE2fFJHHTTgkJvDQzzLW8xkW0U3xMOZ3E+6HrGf2l+foFXRxLOoaJdMK6t2CaF8H1bbEcw2KMIaawGjEuFWMWQ2xKjwpNi9jqLDkEgTKo2LhgD9GdEp4KCw+FoSMJPgMrfdqMZjEQgZdj8MAwjOS6Cq/2ww1lGjR+KnAE9iegyAUfrTNcVboAzabmgRWazjAkm4KhA8jA60j/bqR/NySGVHRx0oDBlKzUbh71OzFVW6CgctFtzDJ8BNn7QySUc9UEq3FtfDemeuvk28UHkZZ7kbZHIT2Su1SdSdSeC1WbwVeCcVI5AS2LEWf8AIVVULERs/p6DbDrfhZpeQBGOnGe+VvMyisxm96rAX6tD+Ls/jau0mZMoOy4czYuN7L6Rjj4C2ToAAwdgIoN2n2uf4/uEC6w0ARolsKo0DQHQUjE0dBCgJIVQE7ACtZDuMUKTZbTnrQjvBCFXSEN3h2lyWe4rkwDrkcdPYcTwq9zeUSj4YsNOYHpgtNEzLi4GO4b0ondkYS+LscKTUVuLQl8JCTcOwS/22B4SwV8r0/4Ub9wyQKXCz4SEv62XUiLhm/eVmu4rATak8JnW2BPDFICLZ3wcKGwOQifabT5Ucudp59+GtBIhOWAI8LBXGnck2HoSqmzusYLW6fohhTPwotReHYEhkd1JBHWSy/nu3pYw9BJS3ASuGmjlDRu1jLItRzhQtopNJmp79Byv8YFlK9f0FxGyaYxwweh8VJcZ73bOqUtp4RFGUMKqzWTKRPTOfpCMxoC7l08RxPxAah9Q94rN0TUtfRYWHgqoptX5R7YmCslXiyOJuE3Q9CZc0qXe+D6UthYsDguqqlIObAvDisDOufZFlx68xkrNJ3GiDgw0gWhI8jAXmRgj7p9ssmcsJRR14qnAFO1VUWlmrMxxSsgULbwXdKmOudkCDlwF9LxlF7gCWDWvBGz6upJpXoy0oUcultL2kZL4woqMU2XQd35KoxlEzpZSg6f4AEFsmnIpnWyVnc+1JyLtD0IbbuQow8jw4cx5/4+ZugAEm5DXrsdzv2fUyrGpmw1pvYcpPs5nMO/wl2xAdNwEfLKf0KoFQm3YXLizYLhDeYcW+m5dZ+LD6go5/ZDoGL88oIqFZqSw4iTWbTSSYtlMRARjiThmYiKRtGcHu0CtgcNV45NKAyOCM9FhF8Nwf74uBC1qdBwYznsCC6tHaX5YozhPdXwelx4aQReiQm9KajxHVs+B4/kygs/Xgc3lcMvBnUx/ctBeFvlNA8wD0SEOwfgP7r173BRieGPGlX4OhAX/uKoWtsvKdHSv3AWDiTU6fRnrcKXm6HMc/r8rU5H9uzZQ0NDA2VlZZMuf+yxx/ja176G3+/nlltuOTUnN0N6U+paGi2Ni52gNA70PfPsCLwaG29THXDBDm+Ec4cfozwQQEen6YnhoY1SHAwbGOA6DnM+nQTMCeIEhg7qJplxQfO183jGJ0bEwQztg8otuLZ9aNGyPi1nJqd8DCmowniDuqG9KELT4pbOiQgmm8LUnJO3Y6YczV16eFibIsSyUOuFbVMI8gtJKKOd5F7LaXc+A5eXwAXF2pjhVBHJwuEE7CiCj9QaGv1Lcx5jV4qnAeJkIdoF4aNI+Kjm6ISOwkh7rjW9kxOWsiAZFZAqNmJKV0PZGihbpwq0v+yUtYsVJ4O0PogcvkdzoQDTeBFm/c3aFnP0dtEeZN+dmh81GnJZsRGz8iooXY3JJlV4Gh1kXW4VTNx+cHm1TajLjVbUyvhrk03pfTIJjMuFWXUtUrYO2ftDfV2f/DJm24fhlf9EBvZhup6GKcIxjbcQs/IqLUVsuQ/Z/nGMrwhTuwPpeg5pfwyz+b0L+loa40K8QXU0pSKz7z4X69PvhTWTFsvGW5DbkYlDYljdYBbLMqcrJWPiUv+EDf5yD1xWYrikZFyIGMoIj4aEh0JCf25Xy23gwmLDG8thVWBpftDng7MKDduD6uA6moSnI/CWY4SjHUEN4uxPw1MRuKzU8Fs18C9dwvf7hLODsDqPr5GI8J898ON+/Sy4udLw8Tp1kXUkhS+1CUlHg0H/uNEQysKnDwtDGRjK6GT1ax3CX6xcftlZZxI/+tGP+OpXv8o111xDc3Mzfr+f1157jXvvvReXy8U3vvENVq5ceapP8zhiE7rGjZbGFbq0xOLY0jjQnJHX4yp2t02oZqvzwvlFusBy9x4AiYKZviRmBC/tlGKATfRxLYc5ly58xpn2PpCbS7bkuszV7cQULMxnvIhghg5CUSOu7R/VLnMWywJyqscQ4wloJcDw4QV7jEksdkZTMqTVI5VnzftQwxmdkz0YEo4k9LJGL5QsshadcuDxCDwRGRf7dwTh6tJT001uIr1p/bqmDH6rxhzXCXgpYYWmJY6Io6Vt8QGI9yO578T6kcSAXh7tASejtxVHhRbJguOAy40J1kLxSkzZGihdDcE6FW98ReArPuU7SdL3Gs6+H0FUBQ5Tugpz1q2YstXjt0mGkAM/Q44+PO5gqjlHS9sKqvR5Z0eDOXyaTeQpOEnJn9FdO5dHxRh/iU60cgKNKW2Gsz+C7P42JAbVydR0KbQ+iLPvTlzVZ08dtt1wEaagCkkMIu27MKtvwDReOiY0yab3LLzbwVc8LjRNEZg+HeJk9f8NoGCK+/nL9QMsGbJCk2VZMtrV6dUovBIVutLj1/kNnBPU/J7NhSpYZER4YUR4OAQvjchYD6ciN1xdZri2DMqX8Id8Prm5UgMwDyfg4Vwo+MSxzGX09fhBn4aCX1aqeQFPhA0vRlX4+bMV0JwHsckR4eud2tUP4ON1hluq9LgDaeHzbUIkq46R/9VkKHAbSjzwR43w+aNCQrQN8O4Y/GwAbrHD2ZLlqquu4vXXX+eFF17gkUceIZFIUFtby6233sof/MEfsHPnzlN9imNkRTgYz5XGRdSZZJi+NA50Z/r5Ef0ameCk3FyoAtOKXMCtZNNIrGfaxWMYH+2U4sHhbHq4lsPsoBuPmb7z3CS6n9M5pacQVlw2p+c/I0Y6wFOAa9uHNarBYllglsQYUroK0//agj+MiAOZnEKzWBlN8QFtHFTUePLbToGI0JaEJyLadKUnDUGX5h8FFrmiVkSdpPeHdGwGWJXLYao/xc0wRaA1CWmBd1fB2ysN3iUS+j0dVmhaBMTJQDoG6ej490wMGft99LoJl6dGINYPiUEVUcj5d8RhzIkz9iVgXJhgHQRrtf18YS0U1UOgQsWWnKi0FISlUdSddAfSl2sb6i/Gtf7t0HDh2OJF0nHk8K+QI78eF5KqtmCab8AUlOtzFxXU8BaBN4hxe+d8TsblhkAZ4iuGRC774OyPIS99QwW+rmeQQBkmMYwcuhtz1ruOP0ZBJdJ4MRz8OXLwl7D6Bqg7Dzx+iPWOZTctKN4iwEA2iWRTM8/YSgwCjop0U7nb/CUQ7dQQdYtlmTCcEfbF4ZUo7IkJsQkb+y5ga6GKS2cHNdzbEWFvHJ4KC8+MjHePA9hQoGV0FxSzZLp6LBabCrRt75GEBoIfScKaYz5OriuDH/TBcyMapN7gN/xBo/BnrZpx8NkW4cZyLas7tvRupmRE+D/tmstkDHy6wXBDuR5rJCt8oU0dZw0++N8rVGQa5eISw9sq4WcDQtxR6/uP+oWLS6BujudjWViuuOIKrrjiilN9GiekZ0Jp3OFcaVyFB9ZPUxo32iXomYi6mEaHpCIXnFukX8XH7ponBjR75RgH0DB+OinBR5bz6eBajrCNXtwzFZhA551tj+gvq65asHmixAcw6Rhm24cxNdsX5DEslmNZCmOICdZqY52FZlRkgkXJaBIRTCaGqT931pvoWRH2xGBXSHhuBIYzUOWBzQXqFl9sOpLw62FozzlKy9w6p9l0CnOYRsnmQr9L3XBbjWZQLoeIBis0LQASbsN54vPjAlI2deLbIzrrGN0rH/15VEgCjK8450IqBX+phlH7S8FfppOOQAXG5QJ3YMzNg6cAvIVLLktHMgkVj1of0HI+lxuz8mrM2pvGJjdaSvcAcvAX6soBKFml7qDiptyBRN1LvpK8l/wZlxsKq5BUgb6Rz/4I8uK/QqwHE6zXD4u2XUjztcfZvo3LjVl9A3Lol0j/a0ioVV1a9TuRtkeRtl0aVr6AGJcb8Rbq/18qoi2KyYmenU9rad9IB7i8mPJ1+vqXrhp3MwXGa2Ik2qO7FYEKKMhlNqWjNqfJsiQRETpT2qHpUFzDvAeOybwNulRcOjuoroFCtyHt6ITnpajw3IgwPOE+pR64pMRwRQk0LNE6+MXAGMM7q+DeYaErBY+FhDXHuJMa/Ybzi4VnI3DXIPxOPQTdhi+sgn/sVKfHLwaFXwzC2oDo61o685yklCN8sU2t9R4Df9JkuKxU75t0hC+36c5ohQc+t3JqS/lHa2FvTEM0+9LgNfD/uuFzK2RZTNwsS4NYrmvc0xHhlREYzGhpXJ0PiqbRadKO7pY/M6K79qOs9GnA/qYTLLAk1qtzQuNGgCECdFJCIWkuoo1rOcJm+uaWX3L0Ed3MC9ZCHnNWJiKpEcxIF2y4BbPqmgV5DItlqWIKqhFjNJ9sIYPvR4PA3f7FCdhPxxBPIa5ZdJuLZYXnRzTPcW+uUUe9F1YWnhpBJ5yBB0LwymiGuoHLSrR77lIwrCcd2JeANX74SJ1hU+ESOKkZYleJC4BgkFALTBSQcqKI8QRUDHL71eHi9mPcAS3d8gQwnoLcz4XaJtJfqi6k0cHCGHD5VGAZ+/KPCUtLeZIsItD1NM7+n0BSxSNTvQWz8V1a3jd6m44ncPbfqeIGaIhe8w3awW30+XkCKrgtsDvL+IKI24vBwNbfQl74Z2SkSwUWY5DDv8Jsft/x9ytbi6nagvS9qqHgOz6JWXFFTmh6BNn8vqnL7vKJr3hMaJJABbTvwnnlm+qqmoD0vIjsvQPTfJ12jHC5xnZMZfiwdtADiLRhyjfo/1s2qcf2L0LPcotlGtKO0J2GzhR0JtUhcDihTpWJGLRj3Nag5pysDmiZ12BaeHYEXhwRXotpns8ohW7YWWS4qATOKjg9usflg62F+no8FoZ7huCDNceLM++oNDwbEX4zJHywGoo9hiK34U+bhJeihp8NaHbNoQQcSgjf7YNLiuHW6hO7ioYywl8d1YmpzwWfW2E4r1hvnxHh7zpUPAq64M9XGKqn6SjndRn+fCX87iEhKXoeBuHJiHbOGyXpCA+F4OGQ0JpQC/95RYZ3Vc3djWVZ3sylNA40E0zHGhhtZOkxOh7tLFJx6kSIk4WRLsQTYIACuimmiBRX0sI1HGEjA3NeoEm0B3pe0F+ab1iQxalkU5jhw7DySlwb37Gk56oWy4Iw2nkuHYeFzMNNj+YzLVbZXL9W0pSuPulN+9LCU2EVmI4mVdBp8kHwFGUepR3NYHo8ouVoANsLNfvoOEfpKSKcUff4eUUqMi0357UVmhYCXwmusz82Jh7hKVBByXWC/1pjwOSCqo1bc4Pcvgmikl+FqnmUhZ1KJNSC7P0hMtyiFwSrcW18F6Z6m14vAn2v4Oz9EUTa9TbeoO561ewYf+28QfCXzLwULA8Ytw8J1moZ3YZbYN+PIRNF3AXQ/jjSfP1x7TyNrwiz4kqk71XkyK+Rsz8C1WdDcRNE2pHWBzDr3rKwJ+4rhmg3Eu9HXvkvzV8ACJRjVl4J5evUbdf1LNL5JM6RX2PaHobtn8D4S5BkeExkMoEKzZwaPqjuOdDyTis0WRYYEWEkq629e1LQkdLFXWdK6E2P+UAn4TcaOr0uAOsKVFgKuAwDaeH1GDwUgtdjDr3pyfcr92hG044i2BYEj10MHYd2oBOeiMDrMWhLCiuPcTVtD2pJ3eEE/HII3ls9ft8dRbCjyDCcEZ6O6ITzQBx2hYXHwnBdOdxaBaXHbCO2JoQ/b9W/ebEb/nKlYUuulW9WhH/ogOdHBK+BP11hjjunY6nyGv73CvjTFmHIwJ4YfL1T2BHUXIb7huFng0L4GDfcLwaF+4fhY3XwxvJx67qIilaBM6yc8kyhe0Jp3JEExB0od09fGjeRXwzCC9Hx38vdumjYEYSCGS5mJD5Ib8ZNj28NpaS5jkNcQwtrGJq/A6D1fkCg4ix1NucZEQczuB9qtuPa+tuLOn+zWJYMo53nMtGFFZpGg8DFQZLhSQ2VFgKTimDW3DhthYPkcjEfCwtPhLVZSKkbNsxg7FxIIln4rx6dW4Jm4d1YriX3S4WeFPRn4IZy+ECNbtgtN6zQtAAYXyHUnjMuGE0Uj4x7yt8Xxd54CpBoD3LwF0j383qBx49Z80bMqmvGBiUZOqQi1OA+QLScq+lyaLxYJyTGaOaQv+SUlWoZtw8prME0XIAM7IWBPRDrRbxB5OhDU2Y1seIKzO5vI4kh6HwCs+IKzLo3Iy9+Q1+T5usxHv/CnbPLgzPSjTz/T0h6RDvinXUrZsM7Jj/u6hs0kP2xv0BGOpGXvoGrbI0Kfk4WU9yEqTkbup9H4v2QHFbxMz2yYOduOTNwciLSUEZr84cyWn4y+vNQVjuEZaZSk3IUuqDBZ2jwQaNPRaUVfohmoSUJB+PwwDAcSjhjneJGMejtR8WlVf7lUfM+HUlHSDiQcNRqnRZ97UYLs12oi8JjoMClX0H37N1aV5YaarxCdwruGoDfPyb/0xh1/XylXbijX3hTOceVsJV5DDeUww3lhkNx4Qf96hL5zZCGgb6zCt5Uru6jx0LC1zqFWBYa/fD5leOtfBOO8I+d2tnLnSulO2uGtvKzg4a/XAl/eVR4JQYPhuDiV4TaCfs59T54Y7nhDUX6P/n9Pi2x/KdOYVcYriiBAwl4aFhzvYrcwkdr4La6pR/SaZkZz0aE/+xWkXOsNG6mApHA/ty6zwDvqNTyuNn+axyIJgkIvMnZw9WuLlaZPOYkJob1e6QNGT4yqRFLXoi0Q2ENrk23Lvii12JZqhhvIQTrMb0v6gZZQdXCrP1GKz1SIXjh60j1dl1PjUZf5BHJpgHBiIOkolPGmNw/rJ+bAxloOInzczHpS4+LTFeU6NdSmv4NZfT83lcNb6k0y3bj08iiJJOdHoTDYUpLSwmFQpSU2A/LEyG5sGzpeCKXKWAw9Tsx62/WfClQUWPfj3MiVK68sOFCzMqrMN6gdoQbDTA/kRtsEZF0DBk+gjzzVSQ+CE4GU7kR1+V/jTkmdE+cDM5Tf4Mc+TWm/kLcV/8tkk3jPPBpiPViNr0X18ZbFuY8RZDDd+M8/8+QiWOCdbgu/zKmfO2098m2PoI8+QUVkMrWYpouUwfd2rfiClYj8UGk+1ktmQtUYPwlmNo3LMj5W04tMx3r0o529oo7k79iU1w2+UuIZ8dLSGZCiVtdKA0+xr7qvYIL6MsYetLqdGpNQktCBapjcRntYnJWoWFTAawv0Hym5cqoUDeShahzYkFuOlzoornCw6TQ7JPxV60O3+lT59Jvth4/WRYRfu+wcCgOb6ow/I+Gkx97d1S4vVfDlEHPKejSsGSDusz+fIXmLokIu2Pw791Ce0rFsz9qNOwsnv3fsz0pfOGo8LNB/f2sAjivGN5SYbi0BNwTJniOCHcNwO29QipXapnMiQmZCSVR762Gv15lxaalzkzGuoG08O/dmgu20g9ls9zvakvCd/o0h2SlH95XBf5Zri97YzGGB4/yyeEfcLFph5IVeVukSrwf9t05Xla/4nJouix/x09HMUOHoP48XGd/7DgHuMWynJnN2lBCLTgt90PXMxAfQPylUFSfd5efDB+G9scg3Jq7xEDVZmi8ZCyqJC+PIwKRdkwyBOVrca25STtvT6i+6UwK3+rVsO8yt24ILgXNRAR+0K8B25Ue+HjtqXVYHUtnSsv1/3GNWdYboFZomgVWaDo5ko4hR36DHH0IsmofMNXbMOvfOhbiLbE+5MBdSPvjIFkNBK/ZrkHfgXJ1evlLwFu0JN9ckhhCWh/C2fM9CB2B6rNxbXkfrubrjrut0/28CksuN+63fB9TVI+0P4rz3D+Bx4/ryq9iihrye37pOPLCPyFHH1HLesUGzNYPYWrPmTRxFBEY2IO0P4ZE2mG4BfEFYegQpKOY8rUqDFZvhdI1GLdX86WSEUD0b9V4yZL8G1nmx0zHuifCwn/3zu8jxKAiUrnHUO5h0leZW0uhMBDNGvozaiXuTUNPWh0Gsez0x67zQbPfsCoAzX4to1vupU0iKu6FcwLTxFffoC6lgEsXsl6jXwad2Dk5h1NKVPCLZsdzCUBFnVqfdt47GUcSDjfkOjX/cjNsKDx+hvbyiPAnLfoAX2o2nFt08uOKCA8NC1/r1C6BSVHr9SUlcHOlCoNDGXg1KrTmGpGWeeAzjYaN8wzI/PJRh8cimpvzN80nntx1pVRwakuqAOGgpQAdKe24V+iCP2mCj9cvoZnrDNm1axfNzc2sXDl96/n29nYOHz7M5Zdfvohnln9mOtbFssL3+4TfDOn/22zLK9pzYlNStETj/dWzF5sOx4XCeCefHvgm6yMvI2WrMb7i2R1kGiSbhiO/ht6X9ILS1bD+ZoyvKD/HzyS0fK5qM67tH8eUrMjLcS2WU81c1oYS7UG6nkHadkH4KBgXUtSQd8efhNug43Htdj1K+XpounS8sVI+HiebhnArJpuGqi241r0JasbXHClHeGAYfjogDGZgrX/mZcMLSSwL3+jRMrrthTrHWCp0JCHogX9Ys/zmEBOxQtMssELT9Eg6jrQ9jLTcNxZEZ8rWYDa8HVO+Tm+TGEYO/hw5+jA4aRWiKjZqKV1R/VgHObyFS1q8EBFkpAt57mtIz4uQzWBWXobr0i8cd96SjuPc/z+Qwb2YrR/Gvf0jiIh2Jex7DUqbcV36+ePcUPo4jnYuRMAdmFE+l4SP4jz55bEPLrPtNqg+GyNpKGoc+xCTkW7klX9Hel/R3zNxiPWpi6x4BYQO6/23fwJX08XqKituQgZeR8JHIdaPKV0JtecufKi5ZdGZ6Vj34ojwHz0yVoZV4DITfh7/8rkEj1H3jJvJtuksMJI1hLMQykAoC6GMEM5qCOJMPqDKPVDrM9R61THQHNDvy11UmkhG1KU1lNE2t6P4jGYWBd0qbsx27IznyhPDOdHKoE6iau/Jj3XTaw4HEvDBGvjcyqknQ//SqV3mCt0q3mwomP6Y/Wnh0ZDmILWn1No+Wi5XPoWLxGvg6jLD+6rJS3ZBf1r4/cMaCv/JOsN15Sc/5kPDwj936Xvgn9YYHOC9+4RXolDnhTs2nfg5L0Xcbjd/8Rd/wec+97lpb/OVr3yFP/3TPyWbPYHSuwyYzbwuK8KvB4U7BlSgXeufXQlIZwq+3atOzkYffKBaReGZIgJ74rDWPcIfhn9AZedDiNsHpc35cx/1vgyHf6VzNG+RdojLU26TZNOYwX1QshLX9o9hKs/Ky3EtllPJfNaGko5D74s4bbuQ/j2YTBwprILCmryW1Um0G9of19iPUUqaoenS3PiRn88oycQxoVbEuDB15+Ja+yYoH2/k1JIQftC3tNxNrUn4716d/9xcoRmTS4H2pHY8/rtlLjTZjCbLvJBUBGl9CGl7eFxgKm7ArL8ZqrZijEGSIeTwr5HW+1U4cdJamrXmjZiSVVpP7CuZUmxZihhjoLAK1r9d7akDezXkfHAfHDNxMt4CTPO1yOBeOHw3su1DGJcb147fxXn4MxBqwXni87jO+wNMsAbIffBEuzQLaYIOLN4gFDdOu4MpbbtwnvsHyCSgoALXBZ/FVG9FYn0Q74dkCPwlSOdTOC/8Xw0MdHnUIo/A8BEN+3ZSkEmC24Mcvgep2oxBdyQpqFYRK5urbcnEwQpNZyzFLuH8IjOWC5RwVLDoTctYTlDCmeyamZoT36DIrR+4FR4Vk2q86ryp9aog4juNBKVjSTjCYHpcCAIVWErcUOKZv5hW4DYUuKHaEXrSurM3kIGYA40+OWHp17VlcKAbHg7Bn8vx3edAQ7OPJOG1KPzRYeGWKm0ZXOTWx+pMaaj4nth4yRzo8/vtGsM7K4XDScPemDrZkqLC2toAnBM8PvtpPlR5DbdWwbd6VUBd6eeELql4VvhOn/5V3lVlqMh1uftKM3xgn3ZE/P+OCD8+S/C6ls9kcSb7j47jLOkNoYXAbQxvqjTU+YXbe4Q9cdgYAO8M/7QNPvitGvh2nzrfvt0LH6hRMX4mGAMbC2B3rIhv1X6E36vZhPfAndD3GlK6CpOH5hymZjtS1KBNT+L9sPvbyMoroPHSef+9jdur84nBfTjP/xOubR/G1J8/73O2WJYrxlsAjRfjargQhg7gdDyF6XwS+nYj/iIINuQly9UE62DjO5D4ldDxBPS9AuEW2NMCRQ1I06WTBKE5P46nQNdBqQh0PkW271VM48W41rwRU9xEc8Dwh41w35Bw1yDsjutn+UzHwIVglR+uLIGHwnD3kIpfVUug75Zw6kW4fGAdTbPAOprGkWgvcvQhpOPxsRI5iupwrb4R6neqwBTtVaGibZcKE9k0lKxUgal8/SnpIJdPJDGE88L/RQ79AowH19kfxnX2R467nZMYRn7+HiQ9guvyv8a14jK9/9AhdTalYyr41J2vwps/CIEqHfDdPnUZZSaswIoa1AE2eh5OBnnlv5ADd+kFNWfjuuBPtLQNbSvM8CG9Xeczao8HqDwL147fhWwS6X9NhcLqrcizX0P6d0N8QHc6KjZgzvmkZmsV1iCtD0KkTa8r3zAvC7yk4/qBFChbtv8HpyMzHeueCgv/0jXzjxC30R38gEs7wwVcWgpVmhOSStxM+rkk9919OnzazoLR8rihnOAzSoFL3UbF7oULLY9khM6UloJ5jDrDpiulOxR3ePP/z955h8lRnVn/d6vz9OScRzmjAJJA5IzJeDHGGBswzhnbu951xvau1/Y6fE67DtiADc42BpNzEEFCEeU8M5qcQ0/nrvf74+0JkmakSUrQ53laPequvl1VXX373nPPOe9WHRD9dQ4s8A8/WgwmhO/UaZW5w8EYmJ+mYeMXZY0tM2qyICL8Tz2s6hXSLK1gN3cEsun3LcLf2oViN/y/qQfmMd3VZPOVGj2Py9LhYyXmgCp1JzIsy+LOO+88rKLp9ttv58EHH6S9vf0Y7tnkY7zjupqw8OtmYVOfTpRGGw4O0BRVsiloq+rtvQWQNobXBxOwJwJvz4N3p7Uhu/4GdSsRY0HW1EnJtJREVJVNrap6Jns6zLxW8zMn2rYIdO3BWC7MvHdrcZiT4HuRQgrDYbLnhhJsQ5pWI7Uv6MIugvhLwJM1ecqjSDc0vAbN68BOBlr6CqD8LMifPylqKhGBcAcm0ADeXKi6CGvKxRif+tP2hdWOvC6glThLj6O6yRa1Nu+L6ALm+wtHv4BwtFAb0YXU70w9eRaphkOKaBoD3upEk4hA2xa1yLVuGXjcZFVipl6uOUvGID37kT0PaxB4IgYSh4xKzJSLVeXkyTyhAr7HCxFBmtdjv/QV9T+XnYnjkp8NW3Uh8eq3kL2PYopOw3Hxjwbb6GvGXv+/SOtmiCfVXqArkwWLMIWLMOXnaCh6oEFXGAH8xZiMMiTUjv3af0ObymHNnBsw82855NzazeuRDb9AAg0Yhwcz81rM3JtUNRVs0ff35UPuLCUHN/8WElGI9kBGOdbM6zBVF6m3u3E10rVHP8O8OZjc2cOfn8bV2G/8GvqaMaWnY5Z8/AD/ucTD0L5Nw+Idbsibd9JfE28WjLavq48oedBPHh1MIvVnBfX/fbJWzThWSIgMVNzrV4ENZlgdO+IlZgv7o6pIs1Cyabj3FhHetkWVSLcUwldGsM/1b/tKLzzRKewOa9v9Fbxm+jScfYFfs7qON8K28J/7hW1BJdveU2C4KvdAkqgxKtyxV4iLVrobLoT8s3ts/tKu34EZXrgkW1dzT8RJ9e233z7w9z333MPixYtZvHjxIdslEgnq6up48cUXedvb3sY///nPY7iXk4+JjOu64sJvm7X6YL+6crRoicK9SbKpKEk2+cfw89ce07LXHyw2XJAl0LAKe8dfobsayawYWGiaKKR5A+x7TCej7gy10mWOnN01prZ76yAWxJp9PWbGtanf/xROShytuaHEI9CyAbvuJaR1MyYWQHxJW90kfVck2geNq6BpDSSSoYeeHChboXO6Saj0LSIQbMb0tUBGqYoNys/DuP1EbOHJTuGhDh33zPCOzU48mehNwC+atLDKUj9cOflF+saE2oiOj741JUU0vWXwViWaJNyFNK5S9VJfqz5oDCZ/AabqAshN2sU6dmDv/ucgQy4CebOVoMidg/FknLAB3+OFRPuw1/4I2fYHcGfiOO+/MRWHhqPanbuxH70NMFhv+xXWEIudRANI7fNI6xvQXQ3hdnR6l4QxmKIlmKmXI/4STKBOXxcLIht+DuFOcKVhLfsspuzMQ/exeR326z9Egq0YVxrm9H/HKj1diZ7uar0PNAKCeHMwzes0g6rh1eS+OMCbg7Xii1plrq8Jad0EiYheA0WLD3y/WEjzn/Y+fuCO5M3FOv87Az9c0l2tqql+ZJRPajWMFMaPt2pfd7wQtTUgszuuChhQ9Vd/KPrxIOgSIuyPaGi4w4ycefWtWpu7W1R+/vB886bJxYrYwo8b4LVeHSLN9sH7iwzTfYa4CHfWKhG1xG/4UsXw5FFrTPjILqE+qsGnHgOfKDVclXvinSNriLXPGHNY+5wxhmXLlnHfffcxY8aMY7F7Rw0T7euitvBAu/Bgu+alVXlGvyrfGtNskD5b7cC3jJFsqo1oRtRnywzz0gwS6sDe9QBS8xwGQbKnTc5Esa8Fdv41+XttoPICLZc+Cf2S9LVgQm0w7XKsuTdNik0ohRSOJY72eEkVgHuxG16F+ld1cdiVpu4Gp3dy3iMeVrKpYZUueoNmtJWtgKJTJ8VxIHYCAg1aoS57Gtb0/gp1bvYOUTflOaHEdXzUTXvCqmwCeEeeKqyPF2rCUO6Bb6aIprcO3kqTL0lEoWUD0vAa0r59MCvI5cOUnYmpOA+TVoDEw0j9y8jeJ7SMpp3QJfjCxSqHzp0N7vQ3tS3Kbt6A/cynINCEmXsjjnO+Oex2iSc/hrS+gZl2BdaCW3V1MNKlKiURzarKnq42uu5qpGMH0vAatG8fbCSjDIqXQU8Nsu9xcKZhsqdhrfgSJqPsgPeTcBey9T6V3wL48jDz34PJmqLqpd46sGNIIgKBZgh3gC8PAk2QPRVp24zsfECVVO5MTPZUzDnfxDjTkMbV0NeoFQWT5JaIQNPrmv8UbFGCbOZ1mOKlqrqKBjAL3481+3rdtmWjVh305up7u9IweXOPwieUwljxVurrjif6EkowBYbkKXuS9riso2iPGy1sEWqTZJPTaOW+gzObXu62+dheDXn/4TTDeVknHokyXogIT3XBPS0aEG6AhX5DT0LYF1Yr4/emGordIx/zD+uFlT1CvlNDR9MdcPdMQ8YJoNwaipoaLYMtIkybNo077riDT3/604ds53A4yMnJwe8/QRJTJ4jJ6OtEhJd64L4WoTsOs3xKzo4GbUmyKWBDgVOVgaO14YnA9rBWsfu3ckORO0kQNq1RdVPXbiS9bMCqMhFIIgp7HoG2ZKnJ7BlJK93EZ2IS7sL01kHFuVin3DZplfRSSOFY4FiOlyTciTS+rrm4XdUgCSS9BDzZk0P8JmLQsl4JrWiPPuj0QclyKFmmGUyT8R49tZhERCvUTb8Cik4lKoYnkuqmruOobnqmC1b26sLQh4uHL0RyLFAdhkovfKMqRTS9ZfBmn3xJPAxtm5GWN1SxMiQXyOTMwJSeAcVLweFGunYjNc9B3UplvwVwuLQK2dTLMNlTweU/7hOlYwGJhbBf+U9k+58goxzHv/xD84wOgl3zDPYr/4VxuDFnfRXjGLJy582FrKphfdESaED2PaGh65Eu6NytKiZ3hpJ+538Xk1agq9DRPs1jangN2f+C2t+MwUy7HGZej+lr4IDgZcuNHQtimteCNw9cPpCESuMzq7RiXuceiHSqGq30DDjzK5iG16BjOxSdCkVLofFVZNeDum8A/iINOC9cqMde/RTy+g/B6cV626/A4dHwdOOA/PmDORAFp7ypScmTBW/2vu54whahO5m/FBmSv5ThUIIp7TjkEh0OiSTZFLZ10DfFcyAB1hkXbtqu9rmbCuDrJ/mgaDh0xITftcCLPYN9p8+CfyszLEo//Oe1pU/4aq3gMapW2R/R4PD3F59Yn/NQ3HvvvSxevJhFixYd71056pjMvm57UPhNs7A7pGTTaCdJ7TG10fUmdDX/1kLtD0aDhGig7rJ0+HSpGeg/JNyFveshpOZpjMSRrGmjqlx7OOgC0XrY+7guErkzYfb1k1ImXaJ9mO49ULQUa9EHMGkFE24zhRSOBY7HeEkSUWjdhL3/JR0/R3sQbx74CydHxWgntN36V3QhGMByQ/FpUHoGxp0+8feIhzE9NQgGU3wq1rQrIXc2e8Pwx1ZhXd/xUTfZAve0wP6o5kbdXjj6hYPJxL4wTPPB1w4TSXAyIEU0jQFvxsmXhLugdaOSSx07VJHUj7Q8TMnpmNIzMGkF2IFG2P8iUrcyabXq3y4fU3EeVJ6P8eVPeDBzMsJuWIX9+AfVTnb+d3HMvPaQbcSOYz/xYaSnFjP9Sqwpl6qKKa3giCt4IoLUPIP9yjeTVd9i4C9QgsqVPpgL1R/M3o+cGVrZJXeWthMNaEU7O66y2PQSZM/DEGxTwseOQzyIKVyC8RcidStJvPZtCHVoNTqXX2W0OTOgax9ITK+FaEDfz+HGzLgaM+/mAyS9IoL93OegfTtmysWaDxVoAG8OJnuaXnvRgAaMT8LqawoTw5uxrzveiNlCZxy6Ejo5BDXIZiftcZNVOU9EK/6FbIgKRG2140ny/ZwG3JbmI6VZo1NNxWxhX0T3O8sBpZ4DX/Nve20e7ICZPlXrFB5G4XMyozGq0n4DnJ4Bea4jH6eI8Km9GrB+XhY82qHBz/fNMiccqfhWxGT3dS1RJZtW96rdNHuUc76OuCqbehJKON9aoMUQRoOwDTtDmilyW5EZKJ7Qrxy2d/wFOnYg/uJJIXCkrwl2/E0noMaCygt18jnB2aDEI5iOHZA/F2vRhyYtCyqFFI4mjud4SUSgpwa7YZUu/Pc1IU6v2uomQ20otmap1q1UpwLoAnHRErW9DbOoPub3iPZiemoRZ9pAhbpIejlPdAj/7NAx07FWN3XH4efN2reuyIBLs4/de/djb1gXLL6cIpreOngzTL4k3AkdO5HO3UjnTuhrOXADfyEmGUItGRUQqIOG1UjzWujeNyiGcbjUHldxHhSdiuV8a6tQJB7GfuQWpGkdlJ2J86rfDrudXfMssvp7quy59OcYf+GR2w40YG/4OTSu0Qeyp2GmXaGZTs3r9TP1ZGJIDvJ8eZiChZiKczR8fZjBn4iNMRZ2sBV2PQjGIDOuwzTre5jKC7UUsQj2y3dqPpfDqxXyjIF4slqcw6MV4/wlSjBNfduBgd/hLmjbBJ5sxDiR5z6n7S/7nP5AJXOZpLce+prAl4/Jqhr9iU/hqODN0NedKOhLKMHUO4TDdyfzl7KdYE3CUl1fQuhJQE+ySl3EFhpj0ByF5pha8/oSEBclmjyWvn+hCxamaf5QrsscdqIYTAg1yazQYveBod2/bxF+1CB4LPhMqeHt+SkCZSgebBd+2yJM9+iguTYCHyg2vOMEPU8/+MEP+Na3vsUbb7xBaWnpIc83NDSwaNEivvKVr/CpT33qOOzh5OFo9HXBhOaNPNGp3/HSUQ6POuPw2xa9RnIc8N7C0ds2uuLQGIPbCg2XH5QBJtFe7N0PI9VPYuIhJHv6hJXDkogkrXTJwjA5M2H6VRNWOogdx3Rsh4wKrEUfTNnpUzjhcaKMlyTSjTStQWpfQDp3q5LRXwze3ImTwCLqWKhfqbEbABgoWABFp+lYfqLvEe7A9NSDLxcqL8SacjF7TB5/aBU2BCDfpVU6j5W6aXsI/pSsv3RjPsyZuGtwTNgThnlp8IWKFNH0lsGJ0pmMFpKIqtqkdz/StQfp2KnKlKEwRjN7Ck6B3LmaG9S1G1reUCJjqHLJADmzMZXnQOlZWJ4T30cvYqtaJ9wOoQ4k2qOVFeIRXYlzpamaKK1QK7lNgJ1PbPsz8uIXlER690tYvkNLFogI9vP/plXiihZjnf3NEatHSKQH2fEXtaTZcbCcmNnv0HLAljNZBXAzEguqqslfqPeu0fWGIrZWBmzfDhllmKLTkJb1GFc6pvyswe0CDdiPf0jfZ+olmFhQycpgKyajFDP7nZjpVxwi17VrnkXeuGtQZZU/X6vL1a3UH74lH4WCBZjeeiWa7Cgmayomf94oz3gKRwsnW193oiEhmtXSGVdVUT/8SYJnMvJ5AgmhI6bv0WcL20OwtQ92hKA6qT4y6M1hlGDqf1sblYf371qmA05Lhyty4PwscFjDD2w6YkJzTJVRU72DKqzXe7VKW20ELszS3KK3gm16tOiJCx/YLSQErs2F37dCngvunWVOyEqMK1aswOfz8eyzz464zSWXXEJfXx+vvPLKMdyzycfR6usSIjzeIfylXS2y072D37/DoStJNnUmVHH4rnyoGGU+dn0E4mjg/GkHWTr7qwbb2/8M7Vu1epW/eELfUxGB5rWw70m10jm9MOVSKFg4wXZtTMdO8GZjzb0Jys+elHLrKaRwNHCijZfEjkPrZuz6l6F5PYQ7EU8W+IsmHB6uCqpaJZy69g4+kVaghFPBKRN6D61Q14IJNoO/FFN1IZHi03kiWsw/O6A7AVM9YyuaMBE81gmrA5pBeVOB9uPHCrtDWon3P1JE01sHJ1pn0g/9YrZCoB4J1ENvg94HWwdDvPthgPQyJZcyq5D0ckyoRWXVnbugaw/Eo4PbWk7Im4spXg4ly7HSTnxbk0QD0Lkb6alRci3coeqbeFgJJhlqLzNKfjg84MmEzCq1CuYvGDVh0w870ov9xwsg3IVZ/q84lnxk+P3rqcV++lOQiGKmXII57ZMHkDQSakf2PKIEUzykDxafirX4o4cGfofatVKd5dQOfgyDMelrQRpX6fkpOR1jOZCuvZiMckz+/AO2TWz8tVbWs5xY5/03uDKg4VWwY5iKczA5Mw88FzXPIuv/T/+TWaGS23gEcmYgnbs1SNybAzPfrtciRq+97OmYyvNSg8rjjBO1rzvREUxo/lJ3fJDEsYCspD3OM0F7XEKE1pgGCLfH1Z7zUreSSyFbFUvGaNftMprzkuFQybnbgMvSwOF8l05i90dhW1Dl4f37W+mB2wrhmjwzrNqqJiwEbc0oqkrmNXXGhX/bJ7zcA0vS4c5KwyzfiUegHE98p05Y3StcnQtPdWkuz6dLD1WfnAjIy8vj5ptv5sc//vGI29xxxx3cf//9tLa2HsM9m3wc7b5ufUD4favmNk3xaF9wJPQmlIxsiukE5+2jrH4kArsjam/9dKlhdtowauZoH1L9FLLvMQi2I1mVGE/W2A9saJt9TbD7n6pKBsieBtOunNDCnU5oqzGJGFRdhDX7HQeopVNI4UTBiTpeEhGdFzau0UXl3jqQuJLMvvwRF7lH3X6gQSvVtW3RxXDQuUj+fM1vTS8bN+EsYmuFunCHRoQUL2NP4fn8PTGD9X3gAqaMkryfCBICf2nXMZbTwLvzdZHtWKA+otVqvzfVTFq0wvFAimgaA45XZyJ2HMJdGsgc6kDCHfr/cIcy1aE2ncTr1jrakGQqh9OnLHZGOWRWIq4MJZZ66pDe/dC7H6J9+lLLqPfWnQF58zDFSzFFSyYl9O1oQ+Jh6NiB3bYV2rdqWHa4C0SVQLgywJWmN8sJxgnYqraJh7S6QrRXz5vDox3k1MswZSvGJDFPPHMHsvufkDcX5zseHnl/617Gfu1b+lllVmEqzwMRpH0LNG9Ifn5A9nSsBe+F4mUjWOB0lZJERPc5vXh058tOqBqqfZuqoIqXqvIt3IHJn39IuKcdDyOP3IoEGjBVF2Pm3awrmeF2TPk5mIJTBttuWou96rsgttrp5r8Xuvdhr/yqXqcV58G+x5FItwaPuzMwC9+vtjynFzP96sHMqRSOC07UgdOJiKg9SC7Fhvya9tvTshwTt8dFbKElBvvDwpoAPNsNb/QpQQRKLvkttbQVuWCmF8o8DKhlehLQEZeB7UGJp9MzDOdnCbtC8EinEiD9AeVzfPDFCljgP5D0jdka/G2j1rv+nKIvVNu83KNWoetyDbcfx7DrhAjbg9Ae1/M/N23yMrDGi1d6hO/XCwUuuCwbftEERW749cwTT9Xk8/m44447+O///u8Rt/mP//gPfvSjHxEKhY7hnk0+jkVf1xET/tQmvNCtlYyqPDrcOhyiNvytHXYma7JcmAVnZxzZNiKilo8yD3ymzFDhGf4F0rMfe/dDSP2rGGwka8qBBUrGCBFbK1Xtf0HVTZYLqi4ccewy6nbDnZie/Vqdav7NWsk4hRROIJwM4yVJRKFtK3bzWo3hCLWDw4WkFYIna2Lf0XgYWjfpnCA4ZOEhrTCpclowbpWTiECoDRNsQRweErlzWV14JQ+aueyNOMl3Hf2w8LjAn9tgV1gX8G7Oh6pjQDb1JXSx4etVhmneE2uMMBakiKYxYKKdiYgkw5ZDOqmOB4f8HULiIYiF9PFoAMJJUinSo8SDCLrunPzIpH8ZWtQGlpYPaUUYf7HKJC0XxPowoTaktw569iuZYkzyZunN6VNiKX8uJm8+ZFaeNLYHCTQgLZuQptd1NS3cqYMcTzb48sFfpGRNuvqUcWdooHW/gigRHTjXdnc1NK/TLKpor5JReXMwC27FyqwY1f4k6l9DHn4PGAvrxqewDpM3JA2vYa/+PsT6Dn0yfz7WzGuh7KwjfhbjUTVJoFHtau3bIGuKrj40vKrET9lZw5KL9q4HsV//odotF39UQ9+790HZ2Vily7Xdjh3YL39D1VqV52GWfHxg/+29jyFv/AYwsOBWrTpX/QQSDSixNfVSjAhMuwIr49BckBQOxX333cdLL73E2rVr2bRpE9FolLvvvpvbbrttQu2eDAOn44m4CD1xlXEPJW8sNMA32wG+SQh67ksITVHh9YCW3H2pR0kjEZ2o5jhhlldDps/IgOk+Q55z+IBvEbW9bQ+qFLwx6elLs+DaPMOydOiOC3c36wpe2NYVvNuK4INFBteQmXFXXGiM6vFO84LLMvymSXi8S2iNaij4T6cf+1W4YEL4Uxv8rU0zq/rhd8BN+YabCjjgOI4lorZw+y4hZMNXK+DbdWp7fE+h4T2FJ9bv7Zw5cygqKuKFF14YcZvzzjuPhoYGdu3adQz3bPJxrPo6W4SVPfDnVqEhBjM8Ggp/+NfAk12wKllrY7Efrso5cgUkW2BrSLPX7igzFIwQWt9fRc7e+aDa6TxZaqOfgKJYQu2w52G11wBkVGh2U1r++NtMxDCduzSLcta/qBJ8EiprpZDCZOBkGy9JuBNp2ajVqTt2YKK9iDtzwtY6EVHVVPM6XfAfUDm5kiqn0yC9ZPwqp2gAE2gAO05vxgyeKriOJx3zaTdeqtyjU4uOF3GBP7ZpbpLLwHsLRm9pHi9EYHMIPl5iuDD7xBojjAUpomkMGG1nYgdbkW1/GiSSBgikENhJ25YM/HPg/dDHh340lhM8WYM3V7pavvoHBHYMQm16C7ZBvA+wkjTvEFLJWBraljUFsqYm76ecVD/aGkq3C7vhNc066mtURY87A/zFkDMTK3c2ZFZpxzmGTk3shOZZ7XtS2fl4CFwZmPk3Y1Wef8TX27aN/YfzVPJ5yu04zvzS4d8vGkBqntVcLNDPpPi0MVVbOUDVlAzXPuz2Sf+2RHsgGlALW8ECldZaTg0CH26i2teCve6nSO1zSuRNvQzLjkDBIkzVRdBdjf3KN7TNosWY0//jAGnuQLB40zq1AM57DyYR1hynSA/kTMcULILCJVglp436+N/KmDJlCjU1NeTn5+P3+6mpqUkRTUcJMVvoTaitJTiEXDIokZGVtKlNBknfFRd2BYWnu1VltDesxE+/DW+GF67IhUuzDdO8Y39PEWFnCB7qgIYk4XRquuFd+UrEVIdtvlcHr/Tqey7PgP+eYsgaolPvt9BlOKDcY3ixW7ivRdgRUvvdx0sMZ2Qeu8HRlj7h6/uFpqTzO9OhA8GmqCqbABakwbemGLKPtt5+BPykQXi+W7gsxzDDC9+t03M/Jw0W+Q3X5I6ukt3Rxr/+67/ywx/+kF/96lfcfvvthzx/11138eEPf5hPf/rT/OAHPzgOezh5ONZ9XX1ErXSrejXwu9R95NX41b3weJeODKd64J35R67AFBfYGoRT0+FTpYbMw1zzEg8j+59Hdj8CgQYko2xC1V9FBJrWQs0zWq3WOKDiXK1SNU67jtqAGjCRbig7E2veuyelgl4KKUwUJ+t4qb9inTRvQOpfQXrrNEDclwe+gglZ6yQeUpVT01qdl/bDX6wL2wULxq2g7M8fNpFu9vtn8lDutbzmnkfClcE0r6rJjwZiNvyhDfZFVBH+3gIoP8pk09YgXJQNHy45eeNEUkTTGDBqoqmnDnnhP0ZuyBit4OXUmzjcSTuXA4xTV5P6FUf9SMQgFtBbpAcSYQaiXg0MkEr9xBKoHNJfpF/sjApM9lS1aU2w2sjxgtgJaN+KXf+qqmH6mgFR1VLWFKyiUyFn1gGV3ESS9jg7rkonSQwSeAOqLocy7g7XwEqeiCCtm5Ct9+nKnHFipl+JmXvjEVf74i99FbbeDxkVON719DEh8STYBj01ehwFCw67j/0V3iTSg3E4k0qvTKR9K8aXpza64V4Xj+gqyLqfIsFmSMQw6aUa1JlWgOx6YCCHyTrrTozz0B5YAk3YT34EiQUwVZdila9AElFk9feReBgz8+2Y3JlY0942aefmzYynn36amTNnUlVVxbe//W2+8IUvpIimSYKIEil9CQjYg5ayfvgsJTOynAyUE58IbBFaY8Lz3apeWtWr1acitg5qKj1wdiZcnwdLMibHbpUQfb9HOwQbqPIYPlgMfochlBD+2Cbc1aQk13QvfHeqYUpSwh2xhX1hnfxWeLTi3df3C7VhDbpe7Df8a/mxIU0e7xS+U6dh28Vu+Gix4dws/VxsEZ7pgh82CIFkmeSfTDf4J0FxNlZsDAjf2C9kONQyd18L/LFNBn6S8lzw7Skj252OFVpbW1myZAmNjY2cd955XHLJJZSVlVFfX8+TTz7Jiy++SGlpKevWraOg4OSe7B+Pvi5mC090Cv/o0PDvmaOYHO0MqZUuKpDvhHcXHLkiXcRWG925WfCRYnNElaX0tWDveRjZ/6JWp8uaOuasygPai3TDnkcHF9L8RTD9akx6yfjbjAYwXXshexrW3HdB0aknjQI/hTcn3gzjJUlEoX0bdtNaaHxdCyhZE7fWqcppv6qc2rbqHAwG5ioUnTbu/kCLPbVCsJX1njk8lHUZW71zyEjLotLrOKI9eTyI2fD7Ni244jFwS+Hoq4qOB3URSHfC/0wxx02NPVGkiKYxYLSdSaK3Cdb/WEfgxhrM20Gzk8ROYBLhwepnkmCAHILB5a2hpNFwSKqcjCdbf8D9JUqy+IvVQjeBAcKJBElEoXUTdv0rWl4z2AqWQyXZ+fOwik+DnJkDhI7YCQ3+tmOD0s3RwuEGp09tYaBlgd/4DTS8BoCZcinmlNsO2+kmGtcgj7wXMFiX/RKr4uxxHfdY0F+BjkRUrY8jrPRJIqbbiY1IApOIQOYUiHQjgXpM9rRDgr0PeH3rJuzuWtj/vNoVIz1KmvoLMZYLU7gQs/Szh81Ysjf8UivfANbST0PlhchLX0JaN2GyZ2AqzsWaf/NETsdbEimiaWIQUVtTKEkuBYcEZPcjzRoM2J6sH/24CNv7dNL5Yg80RJW0iQnkOWG6T6vBXZ5jqDxKPv1dIeGeZiXWyt2Gj5Wo9S9qC891Cd9vgI6YZgr9aJphRjLouyUqtMdVSj7NI3yuWoPKAwk9Rz+efvTVQ39pE37SoJ/UBVnw+fLhSaSasPCpvUJnXCvsfX/q8GHnRxMJET64SzO9vlRhODXd0BIV1vfpcbiN7tdk2C4nil27dvGe97yH119/HVDVXP9wcfny5dx3333MmDHjeO7ipOB49nW7QsL9rcIbAShxQ4Hr8Ns3RXWS05usSHdT/pFX1IMJ2B2Gy3Lg9qIjT1ZERCecu/4BLRsRp0/HFBNRIrVt0sp08RBgoGwFVJw37kU4sROYrj2I5cRMuwJrxjVvmvFuCicf3mzjJQl3QetG7PpXJ9daFwtC6xtKOoXaB5/wl0DxqZC/YNxCCIn0EAm08qJzNg/7z6fBP43SjGzyPZ5Jz2+K2nB/K9RGVVl6S4H230cDgQQ0x+AbVYapJ2lO08njlzqJYBkbu7d+xOcPuFSMSQZTo8SR06dkhysN484Cb3bSLpephFK/dc6dpdu8iVdyJBaClg3YdSs1CyjcoUHdOTOgcJESTJlVAwNgiYeTBNNB5JLlHLwZxyCR1x+abscHSalEFBJRVZm50zHuDKzTPonty4U9jyLVT4DlwCy4ZcT9tgoWkPCXQk81svtBOAZEkzEG8Rer+qqvCfHlD39t9DXqMbv8KkEHrbbXU5P8O/uQl0giCp27wI4jxolx+5HpV2KypyF7H4NYAJM5BTPjSkzVRUfOdyg9A+pfge69yM4HMNOuwEy/EmnfjnRsh+Kl2LEQVmrgmMJRRNTWcOx+cik8DLHkTIZspzvUHjcZyqV+BBI2j3XAo50a7B0TnUAmRKtTzfDBRdmGi7Kh2H10+/mZPsOnSuGnjUJdVPhVs+FjJYLbMlyQDRlO4Xv1sD8Cd+wV/t80mOEz5Ls0Myom0JlQG1/QFhxGj+OVHrX4HS38dQjJdGO+4aMlIwevV3kN35sKH98jrA3APc1w++hqJ0waHMZwViY82im81K22pkK34TK3qtXC9uRke00GZs6cyapVq1izZg2rV6+mq6uL7Oxsli9fztKlw6teUxgbZvoMny+DB9uFxzrV4jnjMJWUit3wgUK1bzTF4N5WuC738BXp0hzanzzVBRkO4V0Fhy9OYIzRBbycmUj9y1pNrn2rKhvSCsc85jTGQMFCJGs67Htcs1vqX4H27ciMq8cUEzDQpuWA3Fm66LjjL9hdezUofBxtpZBCCgfCeLOh4jys8nOhpxZp2QD1LyPdNcmqdeOz1hlXGpSegZScrnOV5rXQvl3nJXsegeqnkPxToPhUjH9sP87Gk4nXk8kl8T6W9P2Bx4KzeD6wlCZfKVMzs/CnZR1OtjEmuC1VlN7XCnVR+F0r3FqgC3GTDb+li5414WNX7W6ykSKajgbcGZiKc4fY4zzg8CoT7PQmySSP3ju9A9tNtNTkmwUS7UWa1iF1L2lnFO0BZxrkzYWSZViFpw5UVxMRZcnjoQMzrRxuPcdD7HAjQ5cEVQkVUrIqEdWKfq50jNODNe89iOVCdj2I7H0M25ePNf2KYVszTi+Unwlba5Cm17EDTRpGPgkQO677JwklzZy+wevGlweBRt33ULuGww99bTwy4JUWXz4m1AoYXbHsDyQ/qMyxJGJI7fODz8dDSHopJh7Sz8PhxohoOOdhgs+HwkgcM/0qZOMvkd79mN3/xEy9FOP8mVrygi0q23WVH7mxFMaN+fPnj/hcIpEY8bmTDXERojZERK0k4aQNzh5mW6dRpYDPUmLJcxSkytuCNn9ug2e7BomlvoSWsV2UBhVeWJZuuCIX8o9hXk+R2/DRYvhZo7AvLPytzXBjgVZrW+KHz5Wqsqk+Ap/ZK/x8BpR5DAUuoSGqSqYKj7A5CAVOnQiv7BEuz5mc3KqD8XSX8OMkyfS+IsNthUd+n5k+w7+VwTf3C/e2CAv9sDTj2BI7Z2cqubgqIETswWvM7zD4T8AhwNKlS1PE0lFEmsPwrgLN6fpDq7AlqFXpskcYnWc64X2FgxXp/tquofJnHaYiXaYTSgQe7IB0h3B17pG/K8bhwlSejxQuxt77OKbmaWjbotXpxlGJ2Lj9MPt6pH0+7H1MFw4334sUL4WqC8eV12LSChB3BqZ5HXagHmvODVB+zoTCzFNIIQWFMQayqjBZVci0ywesdabxdejYDsaJ+IvGbK3rb5esKp2/tWxUlVO4Q8mn5rVIeqlmOeXPH5PKyTg9FGQV8B67jdNDj/NgZAbr+2bh9GYyNTMLZ3rRpPQPHgtuTpJN9VH4bSvcWqiVeCcTxmhO5u6wcP6kUWXHFimi6ShgoFx7CmOChDuRxteVYOqt1zB1dwYULMSUnYkpXKTB1SS9ubGQZlX1E0yWI0naeYZkLdlIoAlCrUioLZlvFdHcJkuJGlx+Zc8zyjDenCTxEtBtor2IHddB0pwbkWgv1DyDbL0fO70Uq2jxsMdilZ6OvfcxrV5X/RQseO/Ezo3YWlEvGjj0OU8meLIxxtJOv7cuqWrKO7Dz763Tc+XJwvTbOd0ZmGhAXZ5O36EdettmJZmcXvVUJ6KY7mrw5iEej0pAEhG9jeY4EjEQ0ZWN6Vci+x5Htv8RU3wqpvQMJNCg+VvhLshIEU0pHBkJEeKiqpq4qKw5KsnbMCqlfljoYMGbJJbSrKNXkSwQt3m0E/7RrpkpoESXQXN5lqbrZHCOz3BVrhI4xwOlHsMthfCLJuG1XqHKA2dkqpVrgR8+Uyp8v16l3P9WLfx8OmQ5DR1xVYdlJ4kSp9Hb/oiWBJ41yeLENb3Cf+3XT/b6vNGRTCJCTODibNjQZ/hnh/Cf+4V7ZnFMw8Fn+XQw2hKDNQE46+R3WqQwQRhjWJIOU7xale75buiIqxJpuC7JbcGN+YMV6Z5Jbn/lYSrS5bm0j/xTq2bLnZ89yn3zZuOY9y6kdDn2rn9gGteAsZRwcox9VmXy5iBZU3Rc1LIBmtZAxy5VSedMH3t7Ti+SPx96arDX/wI6dmHNeSfGk/pipZDCZME43FC4CEfhImTWvyStda9Bx3ZM737EnZG01o3tx9640qBsBVJ6hjormtYqiRVo0Fv1U0jBKZrFdoRCR0NhWQ5m++Ezso9V0Q7+2TeVreFi8jvrKMnIx2SWjjuMvB9eC95TAL9tgcaY3t9WCPmTTDZlOTQUPC4yKdmcxxopoimF4w7pa0EaXkHqX1VFjh0FTw4UzMcqO1t9u8nMHxEZrOQ3QDCp5bA/fFoiPUjHDqS7WhVRdvTI+9B/7yvA5M+DwsVKrCTVUoJg3OlYC9+PHWyB1k3I+v/FPu/bWL5DvSEmdy6kl0HHduz9z8Pcm7Ac48wjSMQg2Ax2UmWSVGqRiCnBE+mBRAxJK4C0Auhr0sf7miAZsifhToh0KT2eXqbnp/oZPT+RLgSwKs6HsjMHs65iISRZotgUL9Xg+upntCqNJ1steJJQq2EsNDquvZ+QshOYoiV6XB27kG1/xFReALsfQjp3QrD98O2kMGFs2bJlxOf6MweONWzRUOqEaInuRPLvhCgxE5dDb6MJGXQbnZx5jA4OvJYqdY4morawskf4Zwe82qPEFyi5VOFRxVS+UyeSlR7D1bkMZB8dT8xOUzXVIx3C39uFGT5VVmU5DTN98KlS4dt1UBuBL9YIP5wKRS6oiajFMCHQkYDl6Vq17rEOmFU2efvXFBXurNXg74uyDZ8sHZlkCiaEF3vg9V6ojqiyzW3BNI9K0jvi8K39wnemHB3V1XAwxnB2Jvy9XQmFE5loevXVV3n66adpaGggEjl0McEYw69//evjsGdvTuQ4NYx/Xhr8uU3YHILpyb7iYFgG3pYDuU6tSLe+T4PFD1eRrtgN0Qj8tkVId4xNzWeyp2Gd9mloeh1714OYju2IN29c5cqN0wszrkbyF8Ceh3Vssu33SMFCmHLpmPOWVCExBQl3YfY9ht1TgzXvZkzenDG1k0IKKRwZI1vrakFiiC9/zNa6/u8wWVOQaB+09qucOpWMblqDpJdB8WmQN2/UJLfLwNmebhbJVp5KdPNEtJxN7TaVXdVkZxTpgrYnc9xaIa+l1ed+25q0MyfJprxJJJuynNAaUzV51Ulon0sRTSkcN0hPrZbUbFwNfS0gcfDlQ+5cDdDOm3uAwkbiYSV++tU4llNzqhxuJBZEGlcj7dshcFA+lsOrYem+XIwnJ2lXdCtxEw9qZZRAoxIzoVZk/wuaIVB8GhSeirFjEA8jGIzbjzn108iLX9Bt1/0EOfOrhw60sqeqNLRjh7bduFrtdGM9R/GIWsnEVnLJm3dANTeJBdUOFw9BqB2Tlo9kVGimVV8j4vTqeequ1u3TCmHPP7HX/kSVSq40DaS3o9iBBkznLqxz/0tXA7v2gNhaia4/XDy9GAk0KrnlzU1+FjbEekd3QIl+0k/0nM15F/LqfyKNr8Os65Vg7N0PLeug6rwxn68Uji3iokoWSRJBkrzZcuD9AY9x4PZ28u/EKEmj4eAwOqBwGiWVXEliqf/vY0UixGxhXR883iE8263WuH4Uu3QCaQGx5GOFLsOVuXBK2rHbx9HgoizYETTsDgt/aoWPlej3tdht6EnAJ0qE/6nXbKmfNsJnygwZDgEMaZYQEZibpkTT2oDQHFVr3kQRsYUv1Qg9CZjjgy+UD583Exfh0Q54pFMIHuQCjSYrcXksvY/aakN6R/4hzRw1XJAFD7TDuoCwpU8D4F/oEfoS8IOp5rhfC/F4nJtuuom///3viMgBQeAwGAyeIpomH5YxnJOlGW2/bxFe7VWlYJl7eGvc8gy12f21Xctu/6ZZLR1ZI4zuK9waDv7rZsHvgLlpYyCbLAeUnoGVvwCpeUYtcG2bkYwKnXyOESZ7KrL4w1D7PDSu0qDgrj3I9KswubPG3p43G3H5MR27sFd/T6vYTr10XMqrFFJI4fAY0VrXtGZi1jq3H8rOREpX6FymeV1yLlUPu+th3xNI4SJdGHdnjKrNDBPlX5z7WO5o4yGZwavxAho7O5naVY3HXwCZVZBWMK7fXp9DyaZ7W1WpfG+r2puPVBV0tEi3oNrWxbwU0ZRCCkeA2Ano2IG9/0Vo2zKQGYS/SAO+y86CnBkHeGglEVNSpD/k23KAMw3j9CA9tdjNG7RTkyEzioxKTM4M7Tz8RQd0Hna0T5U8Pfsh0onEQxg7jniy1CMc7tT3qgtj2rYglRdi0gpV2WQ5sDzp2Kd+Ennl69C+Ddn7KGb6lQccpzEWVt5c7NZNar+reXbMRJPY8SEkk0crux3kLTauNMQUQl8zxPqQqA/jy0WiPZrT1LV3sL14GHnt20jrJoj1YdJLMQtug2g30rVXbYttm7Bf+ALmgu8r4QOQPUTOnlkJbdsg0oVJhBCHB4n2alWK5MTjsBiw2OmkxWRNgZLTkYbXoPZZTMW5yNb7oWn1mM5VCscHfQmdJE82HAYc6Kq9I/n//r9dlv5w9duznMeQSBoOHTGdDL7So/f9uUugA42zMpR0qQ5DS1xVWlkOeFuOYXnG4YN5jxeMMdxYIHy3TrMBVvUazkgqb6Z6IJQwvL9I+HkjPNAuzEtT8qQ3oZWzqsPQZxsW+WFjn/BoJ7xv9Kr3YSEi/KAedoX0/H2zygyrStsXFn7VJOxPdjVlHrgoyzA/TSfkHXFVOD3eJVTGYUcIvlMnLPJrhtOxQKnHcH4WPNctfLX2QHo1LkqOHk98//vf529/+xu33347H/vYx1i6dCl33HEHN954Iy+++CLf/va3ufjii/nOd75zfHf0TYwStwb0z+tS9dvWkJKrw1njZvng9kKtSNcaH5zoZAwjKDBGA8e3h+GXTcIdpRqUPxYYdzpm5rVI8VLs3Q/pwlywBTlo7DaqthxumHopkj9Pg8dDbbD9T8i0KzDFp42pLW3PheTN0YDhLfcinbuwTrltXERYCimkMDocaq17A7vhNUz7dujdj3hzk+rH0fcPxhjIngbZ05BoQK22zetVAdm4GprXI6WnQ+mZByzAHw7lppePsp4zXUU86JrF5ngp2YEOynpXYnx5kD0D0kvHPKZMc2j1uXtbtA/+Uxu8v1DHqxPFQE5TSDg368QbLx4JKaIphWMCiUeQlo1I7bNKfkR7NMw6oxyKl2KVrYCMigO+3JrD1KeKG9Bvm8uvaqS2rdiNq5SI6Ye/GJO/QJVQybBKiQWR9m3I/heR1jeQzl2qMOpXRfW/lzHJynSuQbVTLIB4czANryHTr8VUnq95RpYTK28W9vQrkd0PIdv/il28DMtfeOBB586GjDIl1Fo3Yve1HLrNSOdLRCuqiK37cxBZNhTG6UW82ZprFO5AXD4l2IwDQq3aXm8D9sZf6nl3uLHmvgsqz8cULkZqn8NklGNOuQ159rNI+xZY92NMzkw9J0OrP6QVaaZVuB2J9OrnEWgYDFA/UmefOIiVcHgwUy9FGl5D9r+EnPoJ2Ho/0r4Du7taCaxQO6ZwcWqgeALCmbSiGfSHsP8H0Rz0t2WSjw35e+j2jqH3JyDxMhS2CDtD8FqSXNoa1OyTWJIvyHLCEr9mAZW54YUew+qAPplmqd3rnMyjlwc1Wch3Ga7IgQc7hEc7hSXpGlztsgxVXiGO4bIc4Zku+F69MMNryHHqMW8LKtl0VS5s7IMXujUUfCLV8x7qgMc6BQv4epU5RCEVtYW/t8OjHYKgk+ybCw1nZhxIRKY5tCT8Bdnwi0ahPaY2wI/uFv4+FzKHyWuyRXg9AFv69PpdkKYV4yZyrb6/SKX224JKgF2Tq1X7ToTL4v7772fBggXcddddA49lZ2dz+umnc/rpp3PFFVewfPlyLrzwQj784Q8fxz19c8NlGS7PhZk+JYW2hWDuCGRTsVsnNve0aDj4fclKSGkjkE2zvbAlBD9vEj5bBgXjYDdNRhnW4o9A6enYW+7DtG1D8mYP2O/H1lY5suiDWpmueT3sfRSJ9SXDvcdIhBkD6aWIOwtT9xJ2rA9r0Qcxoxx/pZBCCuOHWuvOxSo/R0mmxjVQ84yqH9MKIW3k+cyIbbrTofxspOwsnUPWvai5s3UroWkdUnEOFJ02KrueMbCYZuZKG886p/CAcw7b7HxmhfbiDL0G/hLImQVp+WOy1Pkdmtn0y2bNsXy0C66dpKq7GQ5VYNsiJ/wY+WCkiKYUjiok0Ig0r0PqXlZCIhFWdU7OTCg/G6vo1EFbVv9rhsthcnoRhxvTthlpWKWMNigxlD8fU7gEk16srw21YTevQ/Y9gTSvV/XSQcQSTp9WZXNnaCCc5RrMG4p0qarJ4YVIj2ZHNaxCCpdgln8eK2ca4s2BOTdC0zoI1CEbfgFnfeWAtzA5MzGuDK1WJ7ZWbZn37tGduFCbkjKWY3RyTnemknKJGES6NTQ9swI7vQx2/hV7w8/VBpc7F7PwdkwiDJ5stcABxuXH5MxEVnyJxAv/gez4K8y/BatsxQEdt7EcSEapqp1iQXD5lJTrDwQ/EtFkR1Wh1j8Qdbghf4FmSQUaMZFuDQrtrsZ+/IMYSyXv5oL/gRTRdMLB7zBMPQErZU0m4iLsCcGGPtjQJ2zog0CCgQByWzTEd2GSfDjVr6qlp7oMT3WpcdBl4Nwsw4VZWmXqZME5WfByr6EtJjzbBZcnB03ZTkOOU7gqVwO/d4fhyzXCL2ZApQfiwPaQ8LESw2K/YUOfcF8LfK5sFKrHYbClT/hRssLch4oNp6Yf2Mb2oPDrZqEpyWOfkaGh5hmHCfnOdhr+tVyrcH2nDjYF4Ybtwu9nQ15y0h21hae64I+tQs1BEUWVHvhkKZw+zqp1Pofhm5VKCmQ5wXECDR53797NBz7wgYH/G2OIxWID/58/fz5XX301//d//5cimo4BZvgMnyiBnzaqsmneCGRTlhNuKVT7XEsM7m/TVXbPMKvqllHSamsQftkofLJ0eJL1SDDGQNGpWN5c7A2/wLRtRfLmjKlS1EBblhOZdiW40qHuJdj/giq1p142rkpRxu1X4qtlPfa6H2Mt+jAms2LM7aSQQgpjhzEGMisxmZVIxTnY1c9gap+F1s1IegkcXLBotG3mTEeyp6mdrvZZdW/se0LnaZUX6JxwFO16TILL2cNU6eJ31kK2+mYzNdFKRqABCbZARiXkzhy1PQ+0qMv1efC7Vh0zVrphydiLdB6CDIdW9m2LQeHYu9bjihTRlMKkQ+JhpG0LUrcyWUGsExAdPOQtwVSchylcqNUGDn5tIpq0yfUHX7sQ48S0vgFNr+sKF6h1rmSZViJwepFoL3bTGmTfk5r307Vb2zBJHYW/EJM1DdJLIWuqZhA5verp9+RAWiEm1qe5Sz37kVhIbXTde5G2rcqgN69FHn0v9tybMYvej5Vegr34I8jLX4P2Ldj7X8KqOGfwYDLKlIjxF6vtbv8L2LPegeU8fC8hkW4lcYxJBuod+WtqjNHjCLaoVc+d9Lms+SH2nocBsKZehln2OWjfroSfOxMi3bpdcntTegZW1cXYO/6KVD+BzLzuEEbf+Is1+ykR0bwrbCQWxMTDcKRKL/EI2DEl9iz3wI+BqbwA2fp7qH8JM/0aZNOv1b7oyUp6pyfou3mT4q677mLlypUAbNq0aeCx559/HoDrrruO66677jjt3ckHW5Ss2BmCrSHYGhR2hCCSrF7XH0DuSk7SFvnhFD9M9RrynJoh9FSXYU1AEFR9c3qG4bIcrc52ssFhDFfnCnc3q83r7MxB8qbCDT1xw61FwvfqtMTv9+rho0VqcWyNQWtMuKnAsDmoFroXus2oq131ozMufKVWKwuelwU3DVmX6EsIf2yF57uVhMpxwm1FhxJRhzu+j5UACP9dpwPDSzcL7ykUEmJ4sUfoSjq2/Q44N9MgwEs9Qm0E/m2fcG6W8JlSM0BOjQXGGHJPwPgYt9tNWtrg73N6ejotLS0HbFNVVcU///nPY71rb1lUejX4/icNhyebcpJk090tamv+QxvcnD+8hcNpYLZPqx/+pln4SAl4xympM1lTsE77NPbGX2JaNyI5M8dcgQqSE8nK8xGXX9VNTWsgFkRmXjs+pZTDg+TNxbRvx177Y6zFH1K1dgoppHDMYNIKtHplxTnY1U9h6l6CtkYko3ygmviY2jMG8uYgubOgeYOS0pEu2PUANLyGVF2EyZ46qrbmmHb+VV7lD8znBccUstLSKY23Yrr2IH0NkKX2PeMcXUDSVK9GCTzbraqmErcqTieCDIf25/XRFNGUwlsUIgK9dZrz0/CqZgbZUbVv+YuhYKHa43JmDDtYEDuRVOQkl6SNpeHbLRugaS3Sn+3jzsSUng4Fi5SI6akl0bQG9j6OtGxUFZQxqoTy5UF6OXgyBqx0xIPQvmWwylz/DhhLCaiS5TDjWqxgM9K2RRn34mXYXXug+mkI1CNbf4c0roKzvopVsgy74nyk9hlk2++xS5ZjJVU9xliY7OlqMeup0UpqzWugbOSsJiW4uvQ/3txR+44BjMuHODyQiCDBFg0qr38FjIW15GOYWdfrEUeTwd2eTOhrSP49pMLYvJthx181QLy3DjLLD3wjX76SdJFe7LQiVR0FW4fkLyWPRUSVZMYMrkba0UGiKVlaVPpawJOjWVlt2yB/Hmb+LZBZgTX10nGtjL5VsHLlSu69994DHnv55Zd5+eWXAZgyZUqKaBoGIkJbHOoiGrC4JwR7wsLeMASHiB/7Q8pdBqZ5NQtljk+rxmU4DPkurfrUGlNr17oASLJXWew3XJ4DhZMQgn08cUoaVHkMNRGtknZ1nj7usgwVHiERMdxWJPykAZ7vVmVXqRv2R2FDAC7NNbwjX1VB97QIBS6Y7x/dOUmI8LUaoS0GVR74QrkGZcds4ekueKhDCCTXJC7MNtyYP3bFmDGGj5cafJbNt+qgLgq/bIICl36OBS54Z77hqlxV8IFmk93TDH9tF17s1lDvT5TA5TknVqj7eFFRUcH+/fsH/j9nzhxefPHFA3L4XnvtNXJzJ8kXkMKoUOFRsumnRyCbClyDZbdrIvDndnhX/vDbeizNbHqxBzIcwq1FjLuEtkkvxjrtk9hv/FojB7KmDo69xtpWyTLElQa7/gHtW3Wxbs4N4ypJbiynkk0dO5RsWvgBTOGice1XCimkMH6YjDIcp9yGVJyLvfdxLQLQ24BkVqgAYKztGQuKT0UKFkDDKmh4RfPZtt6nqqeqizBD4z9GQI4J8yFZx1S6+Btz2e4sZ6azHWesF2nbrC6OnJmq0BoF4X12hqq9d4W1//1Q0cjVQEcDp9H5an0Uloy/meMCI0NLiaRwWPSX/O7u7iYz8wSuSXwMIYEmzV5qfA166zUDCMCdAZlTMOVnYwpOwfiGH5CKiKp34qHBxxIxaNsELRu1Eh2ALx9Tegbkz4dYCOnYgdQ+q0RKx85Ba5zTC2mFkFGGGSBPDCYtX1UxvrxkFpMTYiFlwAP1SKh9cKfcGVhT3walZ0CgAWlaA9EAEulEGlZrZZREFHx5WKfchsy+EZ77DER7MdOvwpr/noGm7H1PIDv/gcQCmFgIChdinf7vwxJIkohp5Tux1dI3wjkDkL5m9T5HA0rE+Iu1NGg8gnTtQVZ/D+mpxlhurLO+gilXpZVEunX/LTem9HTs2uchEcGUnD6QgSTd1div/BfSvAZTeSGOC79/0GdmI9v+DIE67Ny5mPYteuxVF2FyZyuRlEgSSgMwCDZ07FZroisdk1YEOTOgdYO2u/UPSLAFU7oCk14CubMPVIilcMxwsvd1IkJ3QgmglpjeN0dhf1Soi+iPdcQe5nVoVlSpG8rdUOGF6V4odGkeT5qlioFsp67810fUWvVGnwyQ1vPSDJdlqwLhzYKtQQ3Ydhv4aqUZIFwAdoaE3oTmVf2lTQdEF2bBG0E4MwM+VmJwGa1Ot7pXcBglbi7NOfKE9mcNwp/ahDQLfjnDkOdSMuvJTqEj+dNQ5oH3FRpmj6F61kh4rMPmh/XQldAA9w8VwRmZZkRb296w8O39wvbkz9cVOYZ/Lz/5yaZPfOITPPjgg9TW1mKM4Qc/+AH/+q//yuWXX84VV1zBypUr+fOf/8ztt9/Or371q+O9uxPCydjX7Y8IP20Q9oRHzmwCzR77XauqMOf64B15I2eAdcWVZL0xH96RP7HKhxLtw958D9Q+j2SUjUuxMNBW117Y/hddpPIXw9x3a1Wq8bQlguncBa50DQgvWzHu/UohhX6cjH3IiQARgY7t2HsfQ5rWYSSOZFZiXOP7fgPqeqlbqUrI/nlh/gKovGDUOa9bJZ/fsZCd5DGNDtIlqnPb5LzP5MwaVWB4KKF5TV3JKrnvzBu+cuhosT0EZ2bCp0onIWH8GCJFNI0Bqc4kqTzqrUNaNyHN61Tx0k8uWU4lc4pPwypdoWUvD+Orl3hYSaZkZyDRXiVBOrYPdhD+Eh0M5MyCUBvSthnZ+wTSuFpJGeMAbPDmqlXNX4IxBuPJhoJTVCKdM+OIkkcJtiEtG5D6lwfsZCZrKmbOjeDLhcbVSNc+JNiKtCetdMEW8GZjKs6D4uWw7X4lcC78PlYyd0q69mKv+h9EEhDpwUgcc+ZXlXwbGnxuJ/R47PgAWTZcJybRQFIxpjYGSUT0NQ6PDuYKFyEvfgHp2geebBznfwdTuHDw9d010FsLvgLImoLsfwEwShIls5ikYRV22xZk4y/B6cXxtl8dIjW3a59XpVnWFCTcgencgyk/87CSdIkFoXsfEu5USX1aoRJ9Di/Gm4XdtA7Z9Q899imXYDIrsKZdftjPLYWjgxOprxNR21TI1qpm3Qnojh943xOHroTanNqSxFLsCL9sFlDkhmKXSpsLXaoEKHQPEiAGlSxnOpRc8iRnabVh4cku2BIcfJNT0pQ8Kfcce5IhkQwo39gHe8Naea0pCgFb1TceS4+jwAVzfVqB7dys0dv5RITv10N9VLgsx/C2nMHXhW0NRLdF+FMbrOpVsinfAZVeuKPMUO5RFdLPm5RsArWiLfEbpvugxAV5LshzDoakP9UpfHO/EBMtHZxAs56iyZ+GXCf8S77h7MzJzTd6oVv4dZMSh8uTWU+HO08JEf7cpsHiNvDxEsONBSc30bRu3Tp+9atf8cUvfpGKigpisRjXX389Dz/88MA2y5cv55FHHiEvL+847unEcSL1dWNBP9m0OzyysglgTxj+0Kq5cYvT4JrckSc7LTElnN5XZLgkZ2LXsMQj2Nv+qKHeaQWHZHGOqa1AA2z9gyrSvbkw793jJq9ERNXaxmDNu1nHPic5MZzC8cXJ2oecKBCxoeUN7L2PQesmMEYJp1Fa1YZtM9wJtc9pMSbQuWLxUig/e9jYloPRIV7u5xReopJcQhQTwEhi0HHiL1bC6QiB4Q1RzcxLABdnwVkTuDwaojqW+8FUc8IXkxmKFNE0BrxVOxMJdyLd1dD6BtK6CYJtmvED+uVNK4C8+ZiSZRqAfYTVJrHjEA0oQQJIqBVaNkH3nsGNMqeogimrCnpqsRtXQ/UzSm7F+gbDpP3FkFmh6iWHW6uTFS+F7OnjGjyInYD6l7XDS2YQWfPfi8mbi3TuUmtgdw107kYSYejaozayvPmIZWGCrVCyDMeyzw0cq/3sZzWkOy1f85HKVmDNv0VVVv3vGWzWbSzniCVAJdCE1L0IiZiy9nYMMLqffU2IcWiZ4WTQt3X217FKTz+wjZaNSgxmz1R7Yst6jDsDM8TOZ+99VJVRjauRhlexqi7COvPAoHNp3YTUPq8lS+0EBJvUHll82mDlPoc7SQQK2An9nDv3IsFWjNODOL2Yrr26zdwboWkt9ivfBIljys/FFCzAmv2OMX+GKUwco+3rAgklNPqrrsUFovZgUPbQ20jPRWy1q4VsIWRDMKGkUv8taKt9bawwqPqo0AX5SRKjwDWoSPI7QIYZInhNklxy6n0/iWGLsKkPXuhRIqf/PRb7DZfkaDnyY4masFZ8e75bWJcMKB8LHAZWZMCthYaLso9cQW1DQLi3RchwwNcqD1T5NESExhjEbeGHDVAd0dW8+WnwxQq13mU4DSLCiz3w97ZBRdLB8Fn6mb/QrdfHFI9W3epHhQfelmNYkXH0Kve92iP8vEmwBdwWrMjQczT1MCq1f7QLP6hX1dd9s82EKuydqFizZg179uyhqqqK5cuXY1kn18rqcDiZx3V1EeEnSbJprk8J3uGwLQh/aVfF5vJ0eFv2yGRTXUT76I+UGM7InCDZZCeQXQ8gOx9AXOmYjNLxtxVqh62/18UpVzrMu2lUlpgR2+utg1gIa84NmBlXjytsPIUU4OTuQ04kiB3XecDex6B9G+Jwq1VtAvEZEmjUinfd+/QBh0fjS0pOxzgOH5AYF8PjzOAB5hDCyQw6cCDJoktdOl/LqMQcITB8TQAe6dTx4q0FUDVO/iyQ0MWA/6wyJ5ViPkU0jQFvhc5ERCDcifTUamWAjm2qnokFGEg0cniS5NI8TNGpoyKXtG07aZNTkkp6a5GWzZi++sGNcmapgsmXD527sWuehbqXVEUktpIX/WqYjDKMw6PqpfKz1XLlGnv45LD7Gu5Ctt6nsm2MDkZKz9Cg8PqXsZvWYkLtiCtdFVh2FLx5YMBYbsyZX8XKnwuAveb/Ie07MGUrkH1PgiQwK76M8eXp8cT69NgszbMaNsOqt079zIEGVXZZTow7Sz+HrAok1AFrf6oqK18+5vzvYuXMUHlnsjMVOwENrwICxcvUete1F5NehilYoNtE+5DqJzWzKmcW9lMfxRgH1jV/PGBFUnr2I3sfBwPi8GFCzZC/EGvqJSOf00CT2hSDrRi3H9tyY9p3gNuvn7mdwH79B0jzOkx6CWbq27BOuW1SPs8UxobR9nVPdwnfqD12PyFeS0miLIdWWMp0GLKdqjjKckCWQwYIojRLVTBhG8K2rigNB58F6RZkOPX+YPIikBBW98LKHg2mBiVpTvUbLs4+thlMTVG1pz3UIewKHficKoRgls8w1Qtlbkh3gN+CqKgarC4C20J6PDuGvH6aF75cYbgw+/DKnW/WqiXxvYUHBm7boqqmiEAwIdxZqzLvqR74ehVUegzTvAeSdtuCug97wxoa3hZXIjJiqyoqLJDvhKXpqoxakGZYnqHE07FQIOwOCb9r0dyufkz3wlW5htPSD90HEeGOvcL6Prgm1/Cv5SfPQPCtjJN9XDdasmljH/yjQ/8+J1PtrSNhT1j7k0+VGuZN0JIqIkj1E9hb/6DjisyqcX9/JdqrZFOwRcehc27EZFWNf9/6mjHhTph+tY7xjjDxTCGF4XCy9yEnGiQegcbXdM7TuRtxp0NG+biKAUC/inGvEk59zfqgOwMqzoPCRUckmTdJIb/jFPaQy3Q68JOMBYmHdeHe6dNiUyMEhoto3/tGUMeYHy7WsdlYYYsWqflcmWHFBBcBjiXelGHg9913Hy+99BJr165l06ZNRKNR7r77bm677bbjvWsnFEQ0GFoCDZpz1LVHCaZIdzIzKTmBNBZ4spW0KFwIBQsxGeWj/lEWEf1CxoNIIg6dO1UZFelKDjiMlqMsXQFOr9rj1v8f0rBKrXnGUjuZvwS8WUqkGAvjL8JMuQQKF0/6apTxZsPij8LOvyENr2Fv/wuWsTQs3JyNScSQ2ucw8SBSeb6G0IXbIR5GMsphy++Qc/8rWYpzBrTv0AymnOnacdY8hZn59sEAbYcb0oavMGf3NiAbfqkkk9iIw42x4+Dy67JkuEeDyu0ouNKgZCkEm5Ds6VpJz5GtDUV7AFGrmtOLRLrV0ic29OwHdwYSSdogPVlY+XORwsVqKdz5AGbxhwZ3ypOlhF+oDXxJci8RRhLRkVcfBsLCk2qQeEhtiS4/RLoRXyEULoSmNUrwRXpJRAJY4XZd1UjJ2084+Kx+u5NOcFwH3ZxGFSH6nBnx+bTkzefQNtOsIfdJ0shtBBtDLKmMiokSKEP/joleIwFbb8Ptb/97pSXbHU7JYyetaK/1wqY+tUSBDg7OzDCclTm+UuDjQVw0hPuPrcKzXQzsi8OoOuGibMOZmVo9anQWMt2mOqyWr/uSZMrtu4TLc4RvTTHkDHNsDmNYkQmPdwovdcOpQzJ+LWOo9Ai7whqY/dFi4d+rlURa1QOl+ZqRVeoZ3H6+H+YPrE+o2qk5KnyuWiu0FLvhx9OgzGPGHU48EczwGe6s1DDPZ7tgVa9m4vyoQTjFb7ilUA5QLRljeH8xfGKP8GinhioXjKMS3YkAh8PBnXfeyVe+8pURt/nOd77Dl770JeLxEaRpKRwTlHsGq9FtC41MNi3yax/5aCe81ANuA2ePMCee5oEdYfhlk/CZUqiawOq5MQamXIbDlY69+V4d/+TMGNfvuXFnIAtuhe1/gp5a2Ho/MutfMHlzxrdv/iJdtNv1D+x4EGv+eyZk10khhRQmDuP0QMV5WMXLtHr5vidU4dQ/D7XGxtIYYyB7OpI1TfN/a5/Xee6eh5MV6i5UkcMIfdIppoXPyyvcxym8QiV59FFMn85LnV6IBQ4bGG4MXJkDjVFojcNf2+GWgpHz8kaCZXT2tD8irDisYe/EwpuSaPryl79MTU0N+fn5lJSUUFNTc7x36bhC7AREujRAumc/BOpUThhsUQvbUFIJ1MrkyYL0Usibg8lfgMmsOKw0cMT3TuYwSSwIbZuR1jfAjikx5HArm1yyHBJRpOE1ZM8jSPNa3S/LCd4cTMEpYLnBoZerSSvETL1sVEz0RGAsB8y+ASwXUvcS9rY/Ybn8mPz5WOVnYceCShj11sH898KW3yKJKLRuQYyF1D6PqboAkz1Dz27XLsy89yKrvwvN65Gpl6n02+EZ0TOc6KpGXv7aYH6TJ0ezqKouwsosx27dgmz/M3TugLRizS7o3Alt28BfBo6Z0B+AF9LlTHH6kIZVyLY/IJ27wJOFWENIw/QyzKy3A2DNvoFEywbs3Q9h5r93UDHmTgd3mvqc7KgWl0tElUwaiWiykxUFRQbVbQ4XZFaBHcFEupDsmZBeooPRHX+BuhewMVgX/wTSxy+TT+Ho4KxMw1nzDv+DZ4sSNbZoL2MLA//vr+qWQO0aCTnwPmBrkGJchre5DQcH6mP3Dr0Zfexw9jARoTEK6/tU6twVH+wTKz1KLp2aPv6KTGNFXUT4Uyv8pV3tif1YngE35quaarQZS8Nhitfw+XL4eAn8uAHuahYe69Rg81/MgAXDVIY7MwOe7ITqiJ6roXbBTKchxyl0xtUyd2YmPN0Fv2+FJenCFK/BH5cR9zkq8K06rdRS6IKfTDv+8nBjDLN8Wm3w5gJ4ogse6RA29QlfqIarc+HSHEhPBuQs9BsW+YWNffD3NvhwyXHd/XFDRBiN2D0liD8xcADZFNQg++G+ZsvSlZh/uhue6QaPgWXDDOuMgVleXT3/eZJsmohy0xgD5Wdjufxaka59O5I3e1zjN+P0InPfDbv+rgukO/6KTL8SU7RkfPvmy1Oyad/j2LE+rIW3j2usm0IKKUwujCsNM/VSpPQMzZPd96RWDfcVqPtjjGMxYwwULETy5mlYeN1KXSzf/mfIqECqLsJkVgz72nwT4uOyhql08Q/msJM8pvdb6Vzp4PRDtEfjXXpqNFd4SGC424J35sOvmrUS6LPdcHH22M+Jz8DO0JG3O5HwpiSa7rrrLmbOnElVVRXf/va3+cIXvnC8d+mooX/CLpFuCLZDqEW/OKEOJNwB4U4tZx8PHVQFLAljqYTQVwBZlZjs6ZpvlFY47soegBIusT6ktx5aNymhYYyyvO5MTPFSpHAR9DVjb/uD5i91bNe8H4cbsqZgKs7VlP9Il+6qJxsz7XIoPm1SCCaxEyAJkn63YVlyYwzMvA7smCqbttyHtfQOTPY0rIpzSPQ1IS0bME2vY876Kqz8mobQtW/H3v5nKDsLkz1Nz3O4G+MvgqIlSPN6ZNsfNBh8BDloomEV8vLX9TNMKrqMKw1caZjufYgnEyI92qlhYSrOxZSfrcqpzl1I4yolpeIR3f/aZ5DWzUnCyUaCrbpfDo+qiqIBpK9RVwpDbYg3BylagvHlaz7Uzr/CvJtVTWYsxJ2pqiY7ARLT6yse1utpOMQj6sG2HGoXNA7N1cqeouHqdhQTD0LZuUhXtV6zsaDaKIMtKaLpBERPXGiKHUoeSf//J/n9DLoS77ZUEeVOKqPc1uDfY83taY6q3Wl9AFqGJIj7LFiabjgjA0qPUcB3XISnOuEPrcJLPYP0f44Trs8zvKtAlTaTCb/D8IUKuDYPPrZbqI7AO7YLv5oB52Qd+F4ZTg0S3xQUXu+Faw7Kga5wa0B7UAy3Fmp2VG8C/l8DfKJEMBi8lgyEqvejOy58oVrYHFSV2femHn+S6WBkOA3vyFfb0b0tqnR7oF14qAPK3MI0r2GRH27I77cpCe8thLSRUppPcrS2tuLrV7OmcNxR7jF8ahRk01mZanF9qQce7dK+c9EwQz3LaKWkrUFVNn2qdOIqTlO0BOu0T2Jv+CWmbSuSN2dcdhjjcCGzb4A9j0DLBtjzMBLrw5SfPb798mQhWdMwdS9ix0NYiz6o0QYppJDCcYfxZGJmXI2UnYnUPKsWuNZNSHox+ArGTjhZTig9AylcrLm2jatUjbT5HiR3Nky5ZNhiAy5jcy07qZJu7ucUtlDIDNpJI67svCdL55ThTp1/+YuVcEoGhue7tBjDX9vh5V7Nm5w9xp/QTIdGIPQl5IDqvycy3pRE08UXX3y8d2FUEDuhKhU7rkRAIqZBzomITrIjPUoSxQKq8IkGlLyJBSHel8w7UhJBSaTDrC4aJXjw5oK/CJNeChnlmnOUVjiqFP5RHVMipqGNbZuRti1KelkusFwYfyGmZDmSUYm0bUVe+aZWjws06pfU4cWULFEGO9QBnTu1UadXK4OUnzsuD73YCbWNRXsHziGJKAdPg8U4lNBxZ4A7C3y5GMupndis6yHYinTtQTb9BpZ+FpM/D1N5AdJbq7bDpnWYs76OPP9vutLWvBZ2PYCZqzkC0rUPOndhFtyKdOyC7hpk412w+EOHEGf2nseQ9T9TksmTBZXnK9HmydL969qDbL0fqX9N93P6ldoxNq6G4tOQ3v0qNd32R4wd1SoroTZtPK0AnH5M1hRM8TLMzOswxmBHA7D2p0jjqxALYr/yTczcmzAzrkE2/BLZ+Q+YftVAB2w8WeqdjvYpiRSPYgbsccPAjup5t9xJX7NDj8lYSHqZVsNzuDEuL1Jxnqqcpl6ONe2yVFDnCYoESiSMBgat9GaZA/92GFUhOZN/D713cuBjk1FdLGarBWp7SENyh5JLTqNV2Zakw4K0oxc2fTD2hZPqpTahfYgT6axMuKnAcGk2uI/yvsxLMzw0T61fL/bA+3epsumCg3KblmfApiCsCQhX5R6oEnNZhjK3sD+q2VDL0jVvKZCAb9fBuwuEi7M1E6r/3K4NCN+tU4WU3wHfmWKYPcFcmKOJIrfh38qE1wOGhzqEmrCWka+NqMWx1K3ZUm1xDQC9If947/Ho8Nvf/vaA/2/YsOGQxwASiQR1dXXcfffdLFiw4FjtXgqjQFlS2fTTRiWb5qUNX43ugkzNQlsdgAc7NNNu2jCOMafRidDaAPymWfhwMfgmOLkxubOxln4ae+MvMe3bkLy54yObjIVMv0oXyepfhtrnkIxyTNaU8e2X24/kzMI0vo4dD2Od+vEJVcpLIYUUJhfGl4eZcwNSfjZ2zdOY2hc0SzirCuMZezaWcXqh6kKkeCnsfwFaNkLHDuiuRqZfhcmfN+zrFptmSqWX37GQVZRRRIB8kjIj4wBfngaGBxp0QT+jAvLnYpw+5qfpeGF1AB7qgI8Xa4zDaJHp1NfXRWD25EzbjzrelETT8YYdaIKt92l1sP7JtR1PTrRjepMY2Lbm44idVNaMV4ZuVJXi9Cop4ckBXw7Gm6tqkLQCtWh5so5a2KEdj0LXbmjegHTu1OOxXKpeypsDhYt1u72PQvU3k+ql+IBNz0y/AjP1cujeq9lMiKqMys7SUvfu9MO+/8GQRFSJob4m6NwF4Q6kr0XzqGLBpG3LoYMUXx4maxomrRD8hZpr1NcEnQbx5an80ZMFC26F13+gHceehzGzr8cqPxO7pwbZ9SCm7iUoWoJ1xr9jP/d5rZa34Zcw5RL17XbtQzp3Y5WtwFr8Iew1P0IaXoVIJ8z6F8iaBsZgb/8LsvlezafyZEPOTEzXPg3ezpmJsZzYLZtg7yMqHUmGikvjagi2ILYN4Q69tW5CsqYoWZZWMEAsSagDgk2Y7MGsBBMLQt5sKJgLXTVQ/wqy+R6Y9x7wZiPBZkztC8i0y9VD7clUyWg0kMyKalfiE5Bgq1a4kwSm6FQ9DhGQuFoi7SQ74dKlVOPyIdnTwZmm4fNODzgywHKkSKYTGH5LA58tM0gcDb03Q/8+ThlbdtIStyesxNLusDDEFYfDwGyfYYkfFvjBe4zIpYgtPJ5UL73WO/h4gQtuyDfcmD/2bJS4CB0xaI8ruZNI2hXTLA1PL3Bx2FWwTKfh1zPhE3uFJzrho3uEP82GRUOCv+emaVZVb0LJunkHDXYKXCTJMkOGQzgzU6+DHSFVAj3WCaemC8VuYUNA2wAoccN3p5gJ5cEcKxijweTLMwxtMaE6rMe3skdoiGrVvKgocfgveZNDkB5t3HbbbYO/Bcbw4IMP8uCDDx6yXb9dzufzceeddx7LXUxhFCjzGD5RAt+rF/ZGYOYwBJIxWnkuZCtp/Oc2uL1ILasHw2PBDC+82A1OI3ygeOJ9pMmsxDr1U9irvqPjnPGSQ8boRDEeguZ1UPMMcsrt4/6tMU6vEl+tm7B3P4Q1gbZSSCGFowOTXoJj/nuR8nOx9zyMqXtJXT0Z5ePLfvNkwoyrkdIzNLept07zeXtqYcrFwxLhhSbIJ2U15czhAeZiIeQypHKIw6WL+vEQdO1GIp0a9+LL59Js2BfWvKZnutWCP1p4jBa32RtOEU0nLebPnz/ic4nEKJfu42Gkac0Y3lWtW1gOJV6MpSSN06fhzi7/wL1xZ+rf7kxVtngywZ2lNjen75j/KNo9tdCyEWnbqoQDKJGQWYlVtATbXwrNa5FV39VzEunWbRxuTP58mH09puICaF2v1qyEhpGYgoWq0hnDipKIreRS21Zo3Yjdvg3at6vtKtID8WByy0PPkTg8SFqB2gYrz8fkz1cyJdSmNjJ3llYUmPsuZMPPkfqXkfz5mLw5mJnXIp071Za25X6ss+/ELPsssvKr0L4F+5Vv4Fj4AWTfk0rCAaZwEdaSj2Jv/BXSvh159VuAaHZW1z5VXbnS1NLY9Lqqsnz5mFhQlUdNrw+SecEWZMfftFMLtSer83mTvmGvVnTLm4/lSdfAO3+REnowmN8EShQBlr8UKT8fMQbqX4Udf8Hkz0caXkW2/BbKVmCcRXr9GaN5TZFupK8Fu/Y5WPsjzeLqP9uWG7P4w7rSqPyhWuhAXzuwnRMyyhFfjpKl0W4INI3680/h2MNtGXJPMB6wL6ET/+oIVIdVaRI9iMPPdhrm+JQ0meU7duQSwM6Q8MdW+Hu70JX8Ghjg/CxVL12YPfocqGhSnbU3rAOXhqgSTR1x6E5AX0Ink/2Ek8NAgUuY4YVLsuGsLHNIYLXLMvxsOnxglyp03r9beHCuTmBBSZNT/fBij7A+cCjRZJLB4NtDkOuEvojKxS/NNvymWWiJaSCxQSexbqNV2j5YfHgS7ERFvsuQ74KlGXqc368XEqLEpsvAC91wYfbx3ssj4+677waUSLr99tu57rrruPbaaw/ZzuFwkJuby4oVK8jJOdRekMLxR5nHcHOBBte3xpT8PRjG6PXaHYfaqGapfaBo+GpI/qTi6dlucBjh9iIOsb+OFcZfiJl6CWz8NWLHx11RCtDqUa2btGBKx3bImzv+/XK4tKDL/peg9AzIH3lOkEIKKRw/mKwqrMUfUbvbjr9B21YkdwbG4Rlfe2kFyPxbYP/zaqlrel2rc8++XoUbB8FtbN4h24ji4J/MwolNJtEDN3L6VAgS7lBhQd58rOxpXJkD97TCuj6tFlw+yl02RnNHN/QJb8s5fgu4Y0GKaDoa8OVipl8NTjdYXmU2nR692BxuJQGc3oG/jdOjBJPl1JtxnLAXj4iNdNdCxzakfRuEOvUJg2YH5c9HcmdjOnZib7oHad6gWVGgDIMvDzPtcqxZb0eyZ2IaV2Fv+NkASWUyqzAzrsFkTx39PsVCmgFV9xJ20xpo2wK99ckcIDN4bp2+pOIrWwk6O64EVLBF7YqBBuitQ+peQvLmwKwbsMrPwiTCSnq0rAd/qeYg1a3UsOrT/x3Lk4nMeRfS+30kUIe95T7Mko9By3pk259g+19IlJ+rn2mwDQl3Yrw5mJJlWJmVyO6HkKa1SNce6K7RffFkgb8oST769JrJKNOqfV17VfmTPR2KToWuPfoB5M/DuFcgibASkSKYjm1IIoFyARb48vV8xcP6Gk/24InsDwt3Z2HsGMx5F+LNgeqnNGsLgwRbYONdyBn/rkQWIDigew/UvaLklC9f87hy54LEkc5dyJofYi38wODKZT/R5DowHMIYk1SZ5UK4VUPsJzoITeFNiZitpEVzTCuaNcegIQqtMTlkW68FVR7D7CS5VOQ6tj/QwYTwaCf8vlVYFxh8vMStwd7vzB99DlRchB1BVSJs7VObWkPy1hJT4WA/XxNPBq0nZPC2Dc1nubtFK/nN8Qk35MP7iiDXpT2F0yjZdP02JYw+sUf4y9xBAmxROrzYA5uDSqocrNjxOwwFTqHUrSqy6gh8usxwVS481yWsDmilwFK3ruadDCqm0SDDafhMGXypRihwQUdMFWvnZx0+iP5EwK233jrw9wsvvMDb3/52rrnmmuO4RylMBKelw5W5qlbKcGgfeDCcBm7Mh1+3KDn9xza4tUCriB6MdIeqV5/uAoPwvskgm8rOQvY9qeO1rKrxt+NOVzVC3UtQ86xa4MZYmeqA9ny50NeEvetBrJxZR80JkEIKKUwMxnJgplyMZE/TuVfLRiSjbNwZa8ZyQNVFSGYl7HpQ3S0b7xrRSucwwrtkCyGcPMl0ptGJn9jBjeq8KNqDtKyHSDeV+QtYlOZiYxAe7oQPFY2+Cl2+E3aHoDUGhSPUXjqRkJq9HYQtW7aM+FxPTw9ZWVlHbMPyZML8mydzt44rJBk4LZ27kY6dmhnVP5dzODE5s7Gzp2J665HqJ5HX/ltljKBEj8uPKT1dCaSK85Rga30DXv8f7GCrbubLx0y/EgoWjnoCaIc6oP5V7PqXofE1JWDCnUlFmBu82Zii0zTfqWgx5M7RAcTBx2fHoWMHdv0ryNbfQ/s2aNsKHf+JXbIcc9pnMZmlmFAb9DWAvxScfg39rnlGibPcmdgzrkG23gcNr0LhYqwLvk+ieaOusL3w78jMt2OivZrfVHq6Hre/CBa+H0kvh51/BcszQDSZrClKgnmyMIWLkGgvsuV3qrLy5cLST+MoWIg0rtHSmokYkj8fq3UT4vQklU0e6NiB+AsxOdMwlgMJaFaT8WYPDMZEZJAQTFaWMy4fZt7NiOWEvY8hLr8ScXsfwzaWEm57H1cCLhZUYs+bi6m6ELPwA1gZZdru6z/A3vk37C2/wyz/vJKuJnkBHUQ09T9m3Bl6iSUiSKgD4y8c1TWRwpsHIkKfrSvuXUmFTnsMmpLEUkdcRjQbF7oMU7wwxQNTvEosHeuJvojwekDtU492qroIlAS6KKleOjdr9Laqjpi292qvsDNJ3tSEIY6qggw6cbTRbhcBn0NVNQa9xUWzWYK2yq/7bK2wt64Pvr4fzsyw+XKFVhP0Owx3zYTLt2hY+vfr4d/LdV+meHTy2pvQCihzh5Fwl3mg0qP7tyWo5yPNYbgyz/C2XKEuovsRtKExKsflMzoayHIa3l0ArVGhJqLH/ssm+HCxnLALSAejX92UwskLYwzX5sKekIbyL/Al+4WDkOaAdyfJpvooPNABN+QNv22GA6rc8FTnINk0kew4487ATLkE3vjNxBeUSldA01qNDGjZAMWnjb8t0MiBljeQ+pcxledPqK0UUkjh6MJkT8Na9jnsXQ/Avid0fpY9bdzRGyZnJrLog7DzAQ0K3/k3pKdGg8IP6qdcxua9sokQLl6kilm04WUYB5Q7Uwsmde5Cor1cnL+EHeEMmmOa2XTGKItdZjuhIaR2/RTRlMJJCYl0Q2890lONdNeoHcuOD+bqOL1I1lRVCvXWIrsegI6dyNAgaHc6pnSF2t/Kzx4IG5euvcjuf+oXNrmdNeVSKF0xqhUoEUH6mqH2GeyaZ1Uu3b1Pc68cLvBkq/Vt1vVKeCStWRLpga492HUrVbmUCCdf406Go5dgzb4Bs+iDSNMa7Ff+E6l/FepfRbo+CYs/DHPeiemp1XDt3JlIwyqk9jmkZLmG1JWfrQHczeth872qMLrqd8ifLlbL4M6/I5XnIZ27MUmiSew4sudRqH4CIr1JsiZbZeX+QqRwIVbWFCg9A/uZz2on5fRB0RJMsBUyqzAZ5cqUhzsxgQYke6qeF28+4sqArmqkpxbxXaumwf5QcN+QlNpob1JlZFQ9BYNWzDk36uN7H0WivVpRYe8jSPUTSuyJrcRX8WlQfAam5FRMLIBIcmJ16icwdS+qKmr/C1B5LhgXODzDDyxdfpWvG5dmOoXbIUU0nfQQEWKiBEf/LZQkO7qTRFL/fVccehKqljkc0iwodhuKXFDkVkKp0nN8K33VRYS/tcHf2oXaIV1ilQduLDC8I29spcKrw8JzXcIz3Urq1EaU5/cYcFrgRjOwMJCVtKKZZC7WFK+ej1K3Id+pk0qn0RLnTVHh6S6tkNYSg1ACnu+GlT1wql/4WqVwYbbhO1MMH9sj/LxRuCQbTk03WMaw0A8v9whv9A1PNDmM4bR04e4WzWzaH5GBSnKOpL2uLQ5tMf28+xJQ6pZJ+eziImzsg9qw2vMW+Qetf8cCKzLgab+hLa6E2u9bhY644fPlMmpb5ImAeDzOjh076OrqGjE64Nxzzz3Ge5XCaOFzGG4pgob9Wk1y6jB5TQB5LrgxD37bCttC8HS3WmuHQ6YTKoEnO3U1/5bCCZJN/aqmQANkVo6/HacHqTgH9j0B+19ECk7BOMY/CzOuNF2w2/2wVt/1HHmROYUUUjh+MG4/1rybIWcm9rY/QusWJGcaZrgF7dG058lC5r93iJVujS62z7r+ENGCz8S5XTYQxslqSplDG+7h6i47ky6nYDNpTSu5KOMMHgnl8Fw3zPNp/3ok9OeebuqTQyoDn4hIEU1vcUgsqFXf+ho1H6ivUSvb2bYSD6Lkg3jzNMw81A7t+2D3g4OZTJA0jmZjSpZhpl+NKT9HLYH979PXjOx5RJU3oBlNledjKi44YLsR91NspKceap7GrnsRmjdAT3WyLS/kTsM65X2Y2e/ApOUj8bDmKNW/gjSvQzp3j+p8mJxZmGlvw1z2S0zdSuwX/h2Czcjq72le0NI7MKEWtYC1vqHZRPuexMy7CeP0IXNugp5aJWPW/y/Wii9hX/wT5PEPQqQL9j2B7c3Fmn8zEmjErnlGQ7fDHfq8O0OD6ea8E8JdGATJmY288g1oWqW5SKe8DxPrw4Q7kD2PYM26ThVStc8jsT5IL1GlUDyg1d2MUfmnCGIntCogHEg09T/mSlNyyOEeIP6UbHqntrPnYSTg02wofxEm24KcGZptFWhAMkr1uokGtM20fIzTg5lxHbL+Z0jtc5A/H+NKG7nzd/kHbaR2Agm2Q6rS8AmJ1piwPajlskMJCB9EJA3ehLB9cJ3H0SHdAVkOQ7ZTM3/6CaVit4aRnwgqkf0R4bFOeLRD2NA3+LjfAVflwDvyDUvTR7+vIsKOkJJVz3YpwRSylURyGSVPHMnBRpqVjEozsNivAdWL/Vot6vAVogyfKoPdIeH3LcKrvapuCiTg9QDctBMuyxa+Umm4Pg/+1g5fqBYenqc5Tko0waagcIMMr0YqdFtM89rsDCmB9e4hE11jjIaTWxqgHROoiUCeU21n4/lco7bwh1a4r1XojB/43LmZwn+UmzGRfOOFMYZ35gu7QkoKRmx4vFOI2HBn5YlxzR4OIsJXv/pVfvKTn9Db23vYbUedXTkE9913Hy+99BJr165l06ZNRKNR7r77bm677bZht+/p6eHOO+/kb3/7G01NTRQXF3P99ddz5513kpk59mpDbyVUeAzvKoD/bdTvRM4Io/4qL1ybq4qmV3q1rz1thBosWUmy6fGksumWwvFX6DSeTM1qmgxVU9Fp0LBKx1KNq6D8nPG3BUp8tW1F9j2BmfPOibWVwqQi1YekMByMMVB6OlZmFfa2+zH1qxBfLviLxxcUPmClq4Jd/9C51Bu/QqZffYiVLsNE+aCsI4KTjRQxjxacw+nujUMzdcNdLOl8gQ2+S6mXNJ7sgneMskptrhM2ByGQENJP8GzLFNH0FoFEeyGYDLYOt0OwXZUiMZ0ViaDh0nZCK7ZJQi1yoU4IteiXyz5oQOlwYXJnQ+mZak8rmH+ITFECjUj100jLBgYqyZWegZly6ajKUYqdUPVT9VPYDa9CyxvQXa1POtOgbAXWog9gqi7W7fe/gL3nUaTuJU37HwLjL9aBQ3qpKp2MExJhpK8Fuvch3fs01HvtTlj3M8zMa7Cu+yv2M3do9bbNd0MiBGd8Uctilp6B7PirqpqqLgRfHpYnHXvezcj6/8W0bkZ2/xPHzGtIrPgy8vLXINwFm39L3OHDGFHlWDwC0aAqfDwZmCWfwJBAEM1UWvcjpPYFsG3Mwtux5t6IRAPIpruheS12WgEULES8GzHhTv0Mc2bCvieTOVXJz6RrN2RWaSU4p09Jq36E2/Ui6H/M6Tvw3BkDs29Qgmn7n3XbzEpVcUV7wY6B5caQVDfFgkpe+vL0tYULMRllmu+1/3mYce0BtjmJBpTccrj1cePU9yKRymk6gbE/oqHWY4FB80K8lsFrDVZEy3bofVb/vRMyHSduxa594UFyaXNw8HEDrMiEG/IMl+WMTV0lIqwLCD9rhNd6VWlkALel5yXNAbbo+TNGz925WXBRlmFF5vhCzWf4DHeUQWErLPYLm4Jazrw7oeV3N/WpRSbXqVLtu5rhoyVaicrvUCXS7rCGqg+H5emwKwRbQ6qiKj6I6ElzGKZ5haZo0h4Zh4Ct6qaxHM/OkPAf1YMqshynrhAGbNjUp5lSm3YKP5oG89KO/jU1J81wih9AKHapPfG5bljYDtePcjB5vPDNb36T//qv/yI7O5tbbrmF8vJynM7J63+//OUvU1NTQ35+PiUlJdTU1Iy4bV9fH+eddx4bNmzgkksu4aabbmLjxo388Ic/5LnnnmPlypX4/eNbsX6r4KxMJasf7lBy3j2Cm2ShX7OaXuiBRzrVojF9BBVUllNJ1Ec7wUJ4b9HoixgcDFN29uSomiwHUnkB7HpAF/CKThtQ04+vPSfiL9ScypLlGmeQwgmBVB+SwuFg0ouxTv0UkvO4EkQd25HsGePOWzM5M5BFH4Kdfz+slS7XhPmQrOXHLGc7+cyjleG7WwPeHEwsyOXBl/m172K2hAxLwiP3uUOR64Q9ER1bLRlbUfZjjtTM7U0A6Q+1jvYM3Eu0R61Y/Y/Z0YNek9DJfaRbyYhYn24b7kpmMNlJk/6Qr4grDXJnYQqXYMrOhOJlWM7hpcnSW49UP3Vg9bGCUzDTrhxV3o7YcaRrH1Q/id2wSgO+u/cBRvejdAWOpXdA2ZkQqEfW/Uy9uf3KHJRYMpUXQMkyzWoaJp/pgPcMdSD7X0R2/h1pWY/sfADZ+zhm0YeQvY9B3YvI9j+D5cSc8UVMyelI01ro3oe95T4cyz+HWE6svDnYUy/TXKPtf8LOmY5j8QdJYCMv/Iee3y2/RYqXQkaJZjJZFsaVjjnlNkzuDKT2eVWbVf8BadsCdlSfqzwPQh2YYDOk5SMtG5Htf8LE+zAOD9Jbp3a2/FM0SDwRAcuFsaNI+3YGKu6llxzA7ku/PdKTDZZj2M7YGIOZ9XbstAJk46+gc6fuW9YUyJ2rr7GjGhKeiGkFwVA74s7AADL9Klj/f0jDKphyGcbl10qBDauQviYlxIpO1RB0k6z+kgAT7UFiIYxnlAbmFI4Z8pyw2K+EkccCn9VPIoHXDPl7yE2tXScmeXQ4RG1hTUCriD3frYqjfljA6RlwRa7hsuyxWeMAbBEeaBd+0QRv9GmWUn/mUr4L4raSOsaoZe6ibK3itjxjYraVfmQ6DbcXCb9tMVhGmOpVsmlnSEmkXzVDpVszsn7aqOHh+S7DKWnwWq+wuW9koukUvyG9Q6gNq60w3cEhK3CWMZR6ICMuNMZUAVQd1gp5ea4jH9/jncI3arW6YL4TPlFqeFvO4MS3Oix8sUbYmQw2//VMmHoMAshvyFeSqzmmocv3tcKvmoQLsyHHeeJ+B37zm99QVVXFmjVryMubfDnpXXfdxcyZM6mqquLb3/42X/jCF0bc9rvf/S4bNmzg85//PN/5zncGHv/a177GN77xDb773e/y9a9/fdL38c0Ey2jBgeqIKlDnjZDXBHBeJnTG4Y0g/KUNbi+CwhHmZtlJsumRpI3u3YXjI5uMJ1OzmjbdjdiJCQV5kz9fczL7mqBuJUy9dPxtAaQVQdtm7N3/xDr14+POfElhcpHqQ1I4EozDhZlxNZI9HXvr/Zj2bUhW1bhtsMaTiSy4BWqfh/qXR7TSFZs+PiJr+RGns50C5tI6TK3zJFxplDhiLIvtYrVrFo+2x/loqZMjDQ/clo4LtwWFJekn7lgCwIjI2JajTwLcddddrFy5EoBNmzaxbt06zjrrLGbMmAHAddddx3XXXTfmdvvDwLu7uydVail2IpmBFNNbInkfDx1wk3hYM3r6H4sl74eQSCIJiEeGbBdG4kElm/ofi/VBPAhiOOTqN8nYWFe6KlZyZ2HyT4GiJZA7C+sIAwDpqVWCqW0wVN0ULsJUXYzJKDvyuUhEkY5dUPMUdtNaaN86RMHkg5LlOJZ9BsrOhq692Bt/iex7XIkxAG8O1oxrMFPfphat5KBHxNZz0E+sxYNKhEhC1TlWUkHjTgd3JtJbh6z98SBRVnoW9NZquUunD7PoQ1jLPou0b0dWf1eP87Q7MIWL1HpoOZC1P4a2bWqHO/NLWFlTSLz0VWTDL/T9Msq0DK8dxxgHzLwGa9b1UL8Su/5VpPpp/WzFxsx5p2YxefMGBoiChVQ/BeEOTNY0TMlp2NVPQbgb8mbrddSyCYn1DlrdSlfooK78HEwy9FtiIT2H8SBUXIjxZh12FVASUaRzD7Lzr6r0CrZqlbm8BVC0CKvyAr1+evdrGHl6qZJxIvDqN5H2HZgpl2Cd9TW1JXbsHHL9WZiqi5GGV5GOHZrzlDcHq3QFxp1acTpWOFp93cmEuAhb+mBVAF7rEV7r1eDqfjiNZvH0k0u5oyBEDkZdRLinWfh9q6qXQBVL6Q5VK3mTmUoAC9PgmjzDJdla1e1oIGoL97RATVjwWLCmFzb0QVciSTTF1bJ3ayH81xSLN/qEu5uFApfhixXD71NchDv2Ch0xuKUISlyGOWkjV6yKi6qbepMC2kyHVucbKSj8T63C/9TrMObsTPhGpSFzmFFaMCF8bI+qz6Z54d6Z5gjWwsnBj+qFNQHhVD9sCSl5d32e4dNlJ+7g0Ofz8ZGPfIQf/vCHR/29+ieJw9leRITy8nJ6enpoamo6QHUQDocpLS0lLS2N/fv3j5u8fiv1dbtCwnfrBFug4jCJBXGB37VqHlyWAz5QpH3SSOiIQ2MUrsmDdxeYcalQJdKNvfJrSDSAyawY8+sPaKtrL2y9XxevlnwM482ZWHuRHuhrwrHsM5jipRNqK4XJR6oPSeFIkEg39rY/acSI06P5thNY8JTO3VqVLh7UrN/pV2Hy5x+wzU7J5ScspwMfM2kfmWwCImLxfyyl1/g4z93BeYU5R9y/2ogqt789xYzbunwsMCFF04UXXsjZZ5/NN77xjcnan0nBypUruffeew947OWXX+bll18GYMqUKeMimkYLifaqdctODJJGBxNJEtcqYYlIkuywdfuBv4duHz2AgJJETMOs41ElIuJhVa70b9dPFg3FIaswBhxOTcFPK8BkVmGyp0HuLMidjcmoGFV2EmhHTsd2pPYFpLOfNDCYoiVKMKUXH7mNeARp3wbVT2O3boD27YMKJmcaFJ+mBFP5udC5E/u5zykRk/S/mtIzMLNvwFReoEoYEQh3aHB4qBUJd+u5HQtOeR+meT2y9X5oeFltZzmztIrb9j9r1tKiDyJlZ6pMe88/1QfsTsfYCeTUT8Mrd0KgCXn1v7Dn36rsesdOaF6j6qvqp8Cbi0y9DMubi/3GXcjOfyip5c3BpJfBtCs0gNxy6kfrzoTMSixvDpJZofuXCCNZ0zDTr0H2PKxk04JkueqWN6B7ryqpMioxeXMGSCYgaZuzwakh3DgO/dwlHk7a45Ih3mkFsOgj+pmt+wkEGpHWjdC+RYnTU27D9DXqdZkMfjcODzL1cmjfjjS8gh3qwHTu0edKlqt9MdgKnbvUmmg51U7nzRnm+k0hhclFe0wDpN/og3UBYW3fYKW4fuS7dMX/vCytGJc9DlVKb1x4oksJkld6Vb0j6C0rWYa8P3epwAVX5hiuzoWqY6DAcVuGmwuE/200dMWFK3O11PnGPmiMQa4D6qLwuxb4ULEwy6dqrtaY0B5jWPWR0xhm+WCzrcHYBS4tzTsnTYadkDqNodwDnXGhOQo9CYhEoMIthwymftss/LhRfwPelW/4bNnIhFSaw/CDqXDTDmFvGH7YAF+c2Hx2VHhHvqrD1vWpwul79fDPDuGWohNX1TR16lR6enqO926wa9cuGhoauOyyyw6xtni9Xs4991wefPBBdu/ezcyZM4/TXp48mOkzvCMfft0k9Ca0itxwcBoNB/91i5JIf2iD2wq0LxgOuU5A4KF2cCDcWDB2y7PxZGkEwuZ7ELt0Qqomkz1NC9Z079MCJDOvG3dbum+ZEGjE3vUQVt78A8dPKZzQSPUhKYD2L9aiDyC5s2D7X6BtC5IzQ+ca42kvZ4ZWpdv1gOby7vy7Fs+aeumAlW6W6eCDso6fsYx95DCNzhHb8xibS9jH35nHykgWC5q2klc487AFDfKc0BCFfZGRFeUnAiZENK1atYozzjhjsvZl0nDPPfdwzz33HLf3t7v3I698K5l5FE+SR4lBImkooSQ2HBIWlvyBHkoYDfxoJx8zw9wblAgwRskCZ5qWqnf6wJOFSSvUoOiMSrU7ZVZieTK1ytd4VqDiEWhajdStVIIAVJFSdBpmysVKRhypjVgIadsENc9gt26Gjp1DLHJ+KFyCtfTTaoFr34r9zKc1ULr/bFRdhLXoQ5j8eapaCraqGinQkKyiNgSWE+PNVrWNy68stOXU9+on9KK9WnUv0o2J9mrQ9SnvR7bcq/vlyQFvLgQakF0PIGkFmFnvQFo3Q9ceaN+MZE3HpBVgubzI8s8jr38PehuQjb9AfPlK+jjTNBAuoYolGldjN69V66IkwOXHmnMjUrQM07ZBz6snW8t1ppcOHn9mpeYxde6CxtexZl2H3bkTgq2Ynmpk1vXqI+5Gg8v7GtSnPPS8hNr1+P35mrs1ZIAndgKCrUoY9cPpRSyntlGyFObeBC1vaA5XqFkJt+69MOt6lZn3q82cbsieBhnlaql7/X9g6uUYb7bmN1mu5Oe3H/zF+nl5sjD+otTALoVJQ1yEfWH1tu8KwbaQEkyN0UO3zXLA8gwN2D4zQ6urjURkHOk9V3bDQx3CU11qTQnbkBCVQDuNWr5cyb/Py1T10hkZxz6jyu9QsukXTbpi9tFi+H8Neq5CojlRrTH4r/3CL2daTPXCnrCwPQRnjWCxWZgGW4JaYc5lNDR+bxhmeGXE354cp8FrhLqoknE1Eaj0yIBV8IG2QZLpQ8WGDxYd2ZKZ6zL8ZxV8dI/w93bhihxYfJRl52Uew1mZsLJH2BbUa2hbEP7WBh848hrMccEnPvEJvv71r9PS0kJh4fGr+Llr1y6AESeA/Y/v2rUrNUkcJS7O1u/yM10wP40RLRppDnh3vpJNDVENCb8hb2TLXa5LR7L/aAfLqL12zGRT+dlIzVPJrKYJssBVF8Ebd6nquvQMzeicACR7CqZ9K7L/ecy0yye2bykcM6T6kBT6YYyFqTwfyZqqExCskAABAABJREFUVrrmdYi/eFRz1WHb82RqVbp+K13zWgjUIbPfgfGqlW6haeF2Wc8vOI39ZFLByAs482hlAx3sNbk8Fsnj3Q2vYhUuHtHql2ZpkZgdwTcx0TR37lyqq6snaVfeRIiHIFB/kLLIHPj/foIDDnrcoQREUs2Bw5NUkbjAcifvk387PRrq7PIr+eHNAV8eeHPV+uT263OudK3wZTknnI0iItBdjTS9jjSvHyQgnF5MyRmY8rMwviNnOkikG2l5A/Y/j92+XYmSrr16LlxpULAIa+mndIWrZSP2kx9D6lcOnEsz5RKsxR+GnJkacN68HgnUq+qrHw6XkmtphVphbZSEmkHtYQQaB9Q4LP4IsuHnEGzW8xwPQfN67OoncWRVQckypGG1VsNzeBGxMQ43VkYpsuLL2Jt/C22bMYFGzdSy41C2HMrOxiRCeux9TYivAJNVhVn6GXBlYLb9HuJ9kDcf8uYNmzNlys9FOndBxzYkdK5mR+15GGnegClcgjXtKuxoQEk8sbU91yCLL6E2PW/enAPUTGLHoa9Z99UYre6XSNo37Rh4sjEYJZByZyK5MzCNq/W8BRqR9f8L5eeondCVBpYHk4jAtMs166ppDfhLMAtu0TdMK9BrPhHV68o4k3/HDj7kFFI4LCK2VjLbH4G6COyPqh1sVxj2hdUacjAMGsK4yA8L/YbTM/THezzEEmhfuSUID3bAY51CW0wVUkFbJ3cOdDKX69L/T/fCtbmGy3OPv9Kl1GO4NEeDzl/uNXyrSvjwHiXI3Ghluvta4cPFNnPSDHvCSp6cNYJrYFG6qiKqI1DkEhqihp4Ehy25Dlo1b4pHA76jottXeoRXeuC/6/RDvLXQ8KHi0Z+vZRmG63LhHx3Ct+qE+2eNv2LWaPEv+fBqr1aJuSRbz9UD7cLNBUeqDHh8cNVVV/H8889z5pln8tWvfpUlS5aQlTX8YLeycvzhzUdCd3c3wIjv3W9T6d9uJMyfP3/E58ZTNe9khsMY3l0AtRFhdxhme0cmj/Jcmi32uxbYFtJr+MzDOIPykmTT39s0IPyG/LHl8Rlvto75Nt2LpE9Q1ZReMrgI17QGpl817rYgqcj2ZMOeR5DipeOenKZwbJHqQ1I4GCarCmvpZ7B3PwR7H9VF+Ozp46tKZyyounBIVbpm2PUQnHLbwDanmwaC4uI3LKEJP8X0Dd8W8DZ28wuWstdRTH14K+X1r0DBwmGjZ/oLwqwLCFflnrjZpxMimj75yU/y8Y9/nK1btzJv3rwjv+AtApNZDnPeBQ6XKj8c7iQ5lCSMTPK+/3HHIIFkjAMsCzCDrxn62iH3A6GExlJiqp+gSpJVk3nRSbgLaVkPjavVjtZ/rGmFmPJzoHjpEa12IqIV3prXaAZP515VAXXvpV/BZAoWYE77tAZDNq3BfvyDSOOqgeM00y7HWvQhzf3pqUGqn9QKZ/1wuNVullEO/RXPxgHjcENWld7CnZj2bdhLPoas/ZEqfJw+JW1qnyORVoQ17XJo36ZqnMRSTPc+xFiaz+TLxTr149CxQ9VGDauhdRPGX4i14L1aKUVspPppTKwPkzdHq83tfkhJIU8upuzMEav0GX8hkj0DunYjDa9iTb8SSSuEYAs0r8WULse0bFBZZ1+TnvckGSjxsIaHiw1p+QNEk4jocdpxvab8RVqBJRFNkk8JJNKjn7nLD9Egxo5hsqYg066Aju3QvB6pfV6v2XnvxnTtQeJhXVmccQ2y/U/IvsexF7wPK9IDrjRMWqEGmkeDau1MRA4Jsk/hrQkRoc9WNU1bTPOC2pJ/t8aEtrg+VxcZzDsaCX6HVk2b6YNZPsMiv67uT7RMbEKEdQF4ugue7hIao2CjxEzY1iB0C/AZyHJpmO5lOYbr8mCu78QaKJyZAduChn1hYUOf4YdT4f27BSzd7644vGcn/HWOEj67QkJchg8DznEaqjxQExE2Bw1L02FPWG05zohQ4Rn5uF2WYYpXyaawDc91Cd/Yr+f17XmGT5SM/dg+VapV6PaGlTB7X9HY2xgLClyG87PgmS4lQMs9ep0+1AE3noDz1SlTpmCMQUR43/veN+J2xhji8fiIz6dwYiLXZXhvIfy/elUMHi6vqcoDl+fAw53wXI+S7/mHKdyU79KcuUc6tBrSzDGutJuMcmyHW+MlGD/RJPEI9Nbpf9LLx93OAXD5kEivZn2miKYUUjhpYVw+rDnvhPQSEht+oXONcdroAEzOdGTqZWqlO8SlBOdTQz2ZPMSsEYkmgDxCTKODXeTT6K2gvG890ls3YsZxvksX4BqiUDa6tJtjjgkRTVOnTuX888/njDPO4MMf/jDLli2jqKho2MHyueeeO5G3OqlgfPmw/HOHDf4afWNGCSRjJW9D/7YmVp3jCJBwF7RuRFreQLr3DT7hcGMKFmmuTva0I06OJB7RqmINryJNa5WM6dwDPdWABc40TP48zGmfgimXYhpXYT96G9K8ThswDszMazCnvF/9tN37VA3V/2W2nPolTC/XvKlJnqwZbw6UnYmVPR3bWMiq70C0T8mZaACa1yGeLLV79TVpNpG/CLr2aMW1zHLNPipYgKNgAVK6AvvlbwwGtLv90F2jIeUON5JeBk2rNUzbuNTzOwLJNLCPZSuQrt3QthmpOBdTegay+yGkZSOm6FRMyTKkcbWSRK0bsYsWQ/3LyJb7kea1+pl278Us/ojaK8MdqiYy1gDJpB+FG/Hmaqcc7UE8mRhnGmI5NRTPJCvWnfJ+yHxG7YU1T2PcGZAzHRIhsLwa5l77PIRaYfM9cNonwY6rtbC3TrczTkgEU4qmkwQiQgK1OUVsiAhEh7s/6LGQrcHPehMCicH/Bw66H06JNBLSLJ1AlXug3A0VHsNMH8z0arj0ZPUTYVtY1fv/2TvveDnqev2/v7P99F7Te4V0OiShhF6kSBVQULmo2MBrQdTrtaDoTwXUK4INKdJ7TwIEEgIE0ns9vbftu/P5/fHZPSU5JzknPbDP67XZPVtmZmcm35155ilKLL3Roqof0GXtiOsoFU2omNwWFDrguCw4P88wNwe8h2mIozGGC/OF31fBuqBwTKbhhmLDX2qEHAe0xVQd9j/bVZWUtMP1JeE+IQu21cNbrcLcbMMwj2YL1EXBZYSS3TT1OYxhqEdY7hd+UaHr9ZRs+O6gvduOWU7D18vgh9uF+2qEeTmq4jqQOCcP3mhRC+EZOXB/Lfy7Xrgg//DbBz73uc8dFqRnUoXQl9ogmSPVl1ohiVWrVvX5WjLI99OGyemGK4s0r6khunvyaFq6Kpo2hVSheX0R7G6XLXRBbUDHxFHegf0ftWvex0is16zIAaF6sSrPfflQdNS+TQtVeJv2Khh1PuSM3OfppXBwkBpDUugLxhgkZ6ReDN85amVvEEtUEbt2LS4yBrIl1K/JFBJgA9BAmhYt7aYxPduhiv01wU8o0TR79uzOq1533XXXbn9MPm3Swh5rYpc8JaubXW6nv3u8xzqoB3siolWNTeugcTWSbHtLfo3s4dq4UTx1jwFqIjYEm3QaNe8hjWtUzdSySUkVy6mWvvxxmGk3a1ZP5dvYz1+DXb9CJ2K5sMZcBOOvwthhpGkNEu3WKe7NxWQPh8zyTiLkQMKkF2NNuAqxo9jv/i/EEzlbdcuQvDEYn17hkrYtUDwF016p69HpxaQVdE0noxSTWYa0V+lny45FGlfrixmDMA2rsFu2KNHjzcQ0rUP81ZAzss/2FJM5CMkcAu3bker3sIaeiqQXK7FU877mZmUN0YymbfORbW/otoh2KNnl9CKbXyC+YyHWCT/BZA/VCfsKdlm3xp2ORNIg3A6hZsSZGAyx9YpAPKLKrDEXYrvSkNUPIhuehLLjVK3ny9Rw81HnIyv/hmx/HRl9ISZrMGIMJplb5XAnAvFTiqbDFc83Cd/bKp3Ekb3nj+wz0h2aZ5Tv0vsClypGChJ/l3uUYMpxHBiFUEyEFX5Y3A6L24WPOiAqydd0HRhU8eNAh/R0J0xNh0sKDGfkQNFuSJXDCQUuw/FZSg493wz/VaK2tZV+DQBujMG7HWoHHOHV7Je+iKZZGfBYg4aKrwrApHRDTIQdEaiMgNMIBbtp7osL3F2tKqgSF9xYrM/tLUdzVq6eNH/QAb+uFH4z4sBuk0KXYWYmvNcuhG0oc+tVyMcb4KpDF4PUKw5lxmV3dM9P6Q17yl9JYfeYm60q0P80gMfqOxzcGDgvF+6t0TKAJR3auNkXjNH9+712ODN39/bY7pBAA9S8rxECA/86XdOJBqBqsf4xeHaX+n8fYFq2QO5IrNEXHBYkbAr9Q2oMSWG3cPowlgux98MF7WhCqeTK6PVlqxelU28oTCie6iWR5evJ6fO9xoALWNYhnJZzeI5L+3R2/sMf/jA14PYCYzkQb24naXQ4ryMJtUDzeqRxnTbGRbtL+gwmZzim8CgoOrrPQLIe04v4Vb3UsBIaViAtm7XxrW2b3iwXuDMwRUdhpt4MQ+dq3eSzV2A3rtGJODyYMZ/BjDwHE/Uj9cuR5H9QhwuTCDPfk8rnQMA4XJijb0T8NcjH90G4RQeCqsXI0FMx4XZ9Xyyk0upggzbymfE9s6tKZ0L700j1UiWPkllEkVbs9h2w5RVE4hqS3b4t2a2HKZyMGXmuZnDtvGxlxyLrtkPtR0j5Cfr3hqeR+hWY4qnIkDmw5SWoX6mqJV8hpugobdMrmKjZA/UfYy+4FWvOrzBFR/cZwm28eUocRv2I06cHhbYNDp9+l2gHANbwM7CjfmTDU9qGVzwNk14GsYCSbaXH6H6y8WmYcCXEEkopk7B/pjKaDmsI0NrHNQSn0ZMXT0LJ09u9x9KWtUwHZDoMmQ6t0U7eZ+30d7ZD28MOJuIibAgqsbSkXVjaAYHEdxY0O8iFhlx32Eo2SeL7l7rhgjz4XBEM9x2ZzYlzsmFZh6Exqra3O4fDRWsEYyvp1xSF9UFVp43YjU3G59CmvtdahMcbYXyaUOQ2REWoiWrYt9NIn01+v6mCj/xa5/uDwdqQtz0MQ73Sq11vTzDG8N+D4PK1wptt8GarcHL2gd235uXqyfd7HXBFAdxVBf+sE07NYbeKrk8rRo8eTVlZGYsWLcLv9+9STf7mm29SVlbGqFGjDuFSHrkwxnBxPjTFhFebYZxPx+TekO2EeTnwbDO80arK0N2poPKcUBmEN1qEL/QzQ01qP9Bykp1qwgeMynf0OCS9BPLH79u0SBwnIzjGXqKFMikcMUiNISnsFk6fCh/2h6Kpk2jaVdEESjT1ZyQsRONg6knTi/e7IZpAx+F1QY2QKNzNxbpDhX0imn70ox/tp8X45OFAWtr2FhKPqGKpbRu07dCMo9BOdYsODyZ3NCZvLBRO6h+5FAtpIHd7lVrtGtfolalgo5JLgVqVQbsz1cY17Stqndr6EvL0ZRpkDcosj75AM58i7dCyuZP/NWkFkDUM9iEgUkSw/XUaDNm8EWndDMEGTKRdr4BZTg1YTy/R+eSOwRROhoIJu1wRs479HnbtR0jVYvXrt2yGwsmIHcZEjNrSJl6HEVtziRpXqyUue5g2H5TMRDY8gzSsRlyZqthKL8U0rER2vKXf2Z2h83dn6/pt24rUL4fWrTDpOkx6z8vgJnck4itUO1rtMrXTZZZDeyX2lpcx1UuVBJQ4uLMxx/8AE6gDhxcz7HRk+Jnwyk1I3UfYS3+D44L/9LkujdOLuHyapZQcoMXWkHE72oOwNKMvRFq3Iltegh0LkYLJWJYFdhwz4Wrkzf/WLKfykzBp+TpIh9sQK4SROBIL7h8bagr7HadkweuTDB5L84c8Fp2P9zZE+1DCFqEirDLk5X5Y7tdA71BCqpUklgyQbqldzGvUDtiWIJ+K3Zr3dG0RnJZzcC40+OOaYVQVgcaoqn464l0KK49Roi7XqWqvoZ7+W8U8luGUbOH5JpjfCt8s15a331cKLTHwWRAFPvZDgUuI2HQ2w+2Ms3PhnTaoigiPNhguLxDKPapsaoip9W60V8jciWx6qlH4T4MepP3vUG3j25YICN8ehqEe2at2vuFezar5W53wqwphZsaBDece7e1SMmU4YFKaBoT/okL4zfDD8//MO++8w0cffURraytZWVlMmTKFE0444aDM2xjDDTfcwE9+8hN+8pOf8Mtf/rLztZ///Oc0Nzfz1a9+9bC+mHe4w2UZPlcEzVHhgw4du/r6LzA1HVYnLHTPNMF1u7HQGQOlLv3/fkbu7nPYQK1pUvE24krbJwWShNugZqn+MWTOvhfg2HFM23YYPg9KZu7TtFI4+EiNISnsFk5vooQovOf37gmJC+y4+yaa+oMCAoAQMB787kIyHbth9NHjujVBWBuAwsPQwXng/UYpHHSI2BrwHKiHQK0qT9q2q/1Kdja3GEzWEMgbo+RS1tB+ETkS6VDbVKAOmtZpHlHrNiWd/LXQuklDuh0ecGdhhszBOurzSNFU2PgM8vi52hIHmtE04kxM6UxVrwQb9XmHG5M1VMkZd+9SxD2tB9tfDzvmw463kPoVSnrt/L5u6wJQ66BxqKrGckFaIdbQOZjRF2Hyxug7LQfWnF8Tf/IzOrjYcaj5EAadiDSsVNLMXwk5o8BfA5EWbSIMNiDpJeDOhNzRyJaXMeEWzVVqWovdVqGWyZwRmKNuxMruavSRjipk7X+QYL3W9k750i4Nf6Ys0ThXsxRKZ2GGzMX+8G5k1T+6muUsFzjTkKYNupz5ExGHGxNshJnfRF6/BTqqkDUPYyZds9M67VZH7s5WoimpOJK4NtPF/BDp6HyvMQYz8SqkchGEWjA75sOw08GdgZU/FrvoaG0wrHwLJlyJuDIwkQ7dlwDsKBKPavZTCocVMp2GzCPwVyQuGsq8PazkxvqgsC4IG4NdpBIoSRNO/J3m0Kwlr6XkUlyUyImIWrkGe2BmBpyVZ5iQduBJg9qIsCYA60MaiL47hAXCMbW6bUz8t8p3ClMy9OSxL2IoiZkZ8FaboSUmfNBhuKEYnm1SQisqkJmo2X2rVVVfJ/WhDEp3GK4rgntrhAWtQjBuuLxQGOLRddkS15PYMT7pVK5pLpOO0jeVmM5pD/EI28K6fbYn2uj2hmz6QjG83KyWvt9Wwfd206oesYXNId1Hyj0M+OqhMarqerheeLvd8L3B8PkNGiD/73q4+jCy0C1ZsoRrr72201rSfewfPXo0DzzwAMcdd9xeTfu+++7j7be1RXbFihWdzy1YsACACy+8kAsvvBCA2267jWeeeYY777yTZcuWMX36dD7++GNefPFFpkyZwm233bYP3zIF0BKEG0qgtVJYG4QJvt6b6Lpb6Hb0w0JX4IQVAVjQKlxTtIf/K41rkZbNWuSyL6h4Wy9+ZQ7eP1lKbdsgeyjWmM+kyIjDCKkxJIX9AWOMEkP+jn2fWGTPiqb+wIVNLiGa8dHgLWU3QyygFwYs9Fipr2OvQ4n9coqwbNkyHnroIdauXUsgEOC1114DYNu2bSxZsoTTTjuNvLy+w6xSGDgkHoVIm6ppQk1IoF6JJX+tEhF9yQA92UosZQ1REidz8B7b4jrn1zmvBujYAa1b9cAgFkbiIWirSAR8C1geSCvCjL0Ya+LnIK0AWfMw9sL/TrScAe50zLDToGCytrzFo4DBpBdD9jANoR7glS3bjiMdNbDlZWTbK1C/Yqd1YbSxLmuIttOlF4ErU5U48YgOFKEmJdHatmkjXtt27NUPwbrHMSUzsaZ+WS1sOcOxpnwJe+ldGmDdUQHtlUriNG+Aynewxl4KWYNAyqFlo7Lmbdt0UZw+CDcjoSaoWw7eHIwRbfArP74HyQRgMsrg6C/CigcQfxWsfhCmfFnXXRL5E2DHQlWENazU2s6NTyt558qAub+D1f+C9u3QuBrKjkW8uVjBBohHMd5crOm3YC/+OfaKv2JGnYfx5ijJVb1UlUrZw6D0GHBngVWn842HAYNYDoxtA7YuQ8LeaLAwQ2Zr+HjDasgbiyk6Wj87/Gyo+QCpeBsm36Cf8ddg4mHAkchpimrbYgop9ANRW6iLQm0UaiNQE4XqiFZ6bwtr41d8p9/8qOjNFvA5lHaOiipP3In4PF/C9pfr1OdK3ZoFNcpnOCVbc4oO5MmIPy585IcVfiV5uqMoQXYVutS2kuVQO59llBjpiOv62JEg1xpj8HoLLGmH2dnC5LS+l91lGU7OEp5rgrfbYEYG/HCw4Zp1wvaITqvcBdsj8MNt8NIkwdMHeXV0huGqQg3CXtIhrAnClYXa/LcxpKHvG4IwLk1ojcGtW7TNbm52z3Y4t2U6yaaQrWRh2BZqo4ao6DqYlKbB37uDz6GEz9c2C080CsO9cEVhz8+sDwqP1MNLzZpHlsQEn3BjN/KrPzgxCx5tgI1BwcLwjTLDzys0lHxKumZXHWqsWbOG0047Db/fz7x585g9ezYlJSXU1tayYMECXnrpJebNm8fixYv3qnH47bff5u9//3uP5xYtWsSiRYsAbb1LniSmp6ezYMECfvzjH/PYY4+xYMECSkpK+MY3vsEdd9zRwwqTwt6j2G24sQR+UylsDsPIPnKVsp0aZv9cwkI3xqt5eb3BGCh2wZutcFqOULobe6hd/Z5a5XuJBegv9Fhqmf4xdO6+q5ki7Zh4BGvMRT1yNlM49EiNISnsN7gywa7c9+nsp4wmgALx02x8NFg5DO/H+/OdelzYFpM9HvMcbBgRGUCPz6647bbbuOuuu0hOxhjTGfy9detWRo0axV133cUtt9yy70t7iJFsFkhKyPcnRGwNZY6H9T4aUCIp0qZS4EiiUjXShoRb9T27g3Fg0oqUSPEVYDIHqVqpn/5yiUd0fsl5hppVkdO6HWnbrioTjKp12rYpOWO51X6WNRhr0rWYsZeAvwZZ8wj2xmf1O0lcCZXyE5RQSZIkrnRM9jAlgAZYMamWuHqoeAu2vIjUfKANaEmkF2PKjsUMOkVVPmkFPQ5ARGxVetkxEFtrccOtEG5RxVbjGqRqCdR/rN/R4cIMn4c169vg8GI/eaGSMBKHwqNVNdS2Tdf3yT/DSivU54xRMjDUhASboOZ97Mp3oGmNDkzF06B4GlZmOaZkZp9NAxJuQz76ox4ElR2LNfLcnq9XLcHe9jo0re8KGffkYAafgvHlIbGQLq/DCxOuwsoqxzh9YDkgrQgsJ/bz1yJN67GO+gJmzGeQra/2UMOZnOFQMgNp3a5NC/XLIR5CvHkYiStZmDmkM1Rc2iuwty/U6bRs0iD3Y7+PlTsSOxZAXv4ShFqxZt2KZA/F1LyPhNs0IypzkC57KhvhoOFAjnUDgYie2Afi4Le16awlrkHbnbc4tMTUxtUUUzKlqQ+FTyyhQoomcpR8Vheh5DSqVkqSSkkMdsMonxI3QRuQRBmogYlphpOzoPwAN5ZtC6mtZX2wK3DdafRkcHwaDPcMzPIVsdUS+G67rkPQaZ2X13cGVsQW7qyAoC1cVWSYkGb48kabh+p1XV5ZCC806XuvLYafDNm9bXBDUPhnnVCb2FbHZxouLRC2hg1BG4wIv6mCtUEY5YX7R5tdlk1Em+ieb9aAchvdpu7E9QkLOCXbcFE+fRJfSTxQK9xTrccx5+cZ5uWqDfG5JuG9bhc7sxKZYdWRrm1xaYHh1vL+q9h+Uyks6xDOyTN8tgB+ugNebVGS64HR5pBb6C6//HKefPJJnnvuOU4//fRdXn/ttdc455xzuOiii3j44YcPwRLuPxwuY93hgiXtwr1VgsdSm2dvEIF/1cPmsI6Pu7PQicDyAHy2EC4v7P3CoQQbsd/8PmIsPXbYS8iGp/TiYs5IzIQr93o6oMeFpmEVDD4Fa+p/HZZxGCkcHkiNIUc24h/eg1QuUlfPPkAW/0Ivik+9udfzt/kylD8xgwnU73Far8cH8Y5jJDPT4pydv+exJyaa03TrIMOszMOLaNonRdMDDzzAr3/9a8477zz+93//l4ceeohf/OIXna8PGzaMWbNm8cwzz3wiiKb+QqIBVZPEQmr/iYcTBFIY4qEehJIkiaW9Sby3XBqI7clR9VB6kRIFaUV6It9PNZDEIxDpUAtY4l6iASVFOirV4hZoSNjJLLWftVeBv0qDsC1Xwh43GzP2Us1fqliA/epXkZr3lYCxY5BWiBkyB4qm6o+2w6WqoszBe3W1SCJ+7JbNsOkZZOsbqigCwGjQ9YizNFQ8f9xuT3hMouEPy6l+fGOB06MkXe4YyB+PVTINu70CNr+E1HyAbH4Ju3op1nHfxRxzG/Lyl6FtOzSvg8mfV4VT6xZk1T+RGd/AxCNKmqQXI55szcoyDlU1efN1f2ivVMuaOxPZsTCxTC5M1lBM8TTNzDKWbvMxn0FW/h2pWoIUTO5qiQMkfwLy9g+hcQ14c7EmXgNT/ws2vwTtO1RRFmkF2qH6XSTvc4n9KKtznzGTr0MWfg977aMYXz5GbG33yxmhOQotWyB7OLgzdL8xBsGh38OZuCIZaoQk0RRuV1Iyf6LmWQUbkeolSEYpFoI99DQNLt/8PBzz3/r5eBjJG4spnJAimQ5TNEaFjSG1lCUVQRHp+jsi3Z63d34sREXVKAFbyaSArYRS8nHA1hOV3cFGVUg2qlKKC8QARPOiHPqQGPrYY0GmUaKm+7DgMdqONMILo7yGsT7BbcGGoGFVQAjZSkp5HIZpGXBsJrttSdtX2KI2lsVtqshKYpAbpmbAWN+eLW99wW0ZpmbAUenC0nZ4s00ta3+thc8WSK+teG7LMCtTWNiqqqYJafDNcsPzTUoWLWmHEzJhQZsSTmN8cM1urGCjfYbbB8PzzaoUeqdd2BSCG4qFuA2/q9Hw70IX3DW8J8kkIizz63x2RHT7g4bFD/JAmqUqq8qITnulH24sEfJdBp9Frxa764ogKob/qxGeaRKeaep6zQJOzYHPFqjyyhhDc0z4Ry38qz6ZH2W4rZ+un5OzYFkHvN0mXFpg+HoZvNMONRHNnupvS9eBwvz587nkkkt6JZkATjvtNC6++GJef/31g7xkKRxoHJNpaCgQ/lEPvpiqN3eGMXB+Xv8sdMbo/+EFrXBqTu9htVL7YSIEfODquM5p+OuUZAIYMmevp9OJth2QXoo19pIUyZRCCp9kuLP2OQxc4pGu8/g+ol4GpGiKN4MD6uP9G3ucRo9zV/jlk0U03XvvvYwfP57HH38cp9OJ273r5Y9x48Z1Wuk+NQi3Ya/Zy6t8lhOcXozDC55s/Q/gydIgbU9Wt+eyNbi7n1c+RURJgGhAFSjJWzQAdqSLWArUqYon0KBnVZZXax+DzQmCaUeCXHJqiHTeWMzYSzCjL4B4FFn/GPY7/6M5TXYMsKFgEqb8RMgdpa1tGaWQMQjSiwZsjRM7Bh3V2PUrYPOLSOU7iQA2o77YIXOxxn4GU3rMXh0cGMsBlkPnE4/oiWhaIZJRhtVRqWHbg05EVv8bCdQSn38bZsKVagtb9zjEwphAHTL4FNj0LGx8GttXgJl4FZbTC4E67Jr3oGop0rxBCaLSWWAsZMvLat8zlq7v5HfuqFFFVVo+1qjzoWSmBrYXT0dqP0A2PQ9Tb8IYg4RakAW3KemF0WysWd/W6Yy+AGo/QKrf04yo1q1Q/Z4Si8PPxJTM6BwgzZA5mKwh2kS47Q0YOgdTdpzaLHNGIs0boXE1pvBoxOFBHB7dl+IR8Obp9oj6kYhfpfAdFfq6KxNKpkPVu7DtdaRoCiZ7qKqmNj+PNK7VgHJjKUGJYOw+as1SOOR4tx1u27LnH0/pdi8JNVHyObvbc8nHCeEQdrfnnehVcwd68iIJdZKVII0cCVubK/k3u+aMOI1epR/khkEeQ7lbiYkRXih365BXF9Vg6wVthrZY15IWuzWEeko/Mo32BXERPvZry11SbeQ0cFQ6TEunVxJoT7BFuooVkjdjcBjDsVkwwis82ajkzL/q4bICYVAvKq1jM5Vk2hYSaiMwxmf4bIHwh2q1u83KgGkZSpb8oUoY5YXjsvpeXpdluDBfA4jvq1HC6teVqhp6t00X9OYStSiC/o6tCsATjVAZ0W/kMXBMluGETCHDAU1x02mL3BTUhrv1IbizAr5QIqRZhiyHUOzuSTgZY/hiiX6Hh+qV9Mp0wMxMw4V5u4an5zoNt5TDuDT4wTbh0QYNE5/Tj4rhqRmQ5YTWmO5r0zIMPx2qyq3sw0D23trayrBhw3b7nuHDh9Pa2npwFiiFg4qz8gwNMSVb3UbbJXfGQCx0JS7NanqzVbi4YCdVoh1HdryNOL37FALOjgV6nz9ejzH3ARL1Y6J+zMSr9nlaKaSQwuEN40qHAZBAvSIZBG65esaZdIPV1Z++RxTF9RywfgAalDwnLPNDIC4HvZ15d9gnomn16tXceOONOJ19T6a4uJi6urp9mc2RB3c6Jn+8WpOcXg3EdnqUGOr8u/t91+O9blSLR/QkPx7u/T4WBERtYpH2RA5Ri1q4gvWqtnK4wXKpasmOYvw12lIWbFJiyVhdrXQjzsKMPBvSy5AtL2O/dosGUNtRDcb2ZGEGnwxlx2HSC7XJLb0U0ksG/B1FRFU47RXYVUuQ7W9A3Udq5bKcqoiacKWGNe4n5YuxnLoeYmEQG2NHdT6+Qow3BzujFDa9oOqe1Q9C3lglBDuqkW3zMRc+jjStgeaNsP4JqH4PO2e4rpuOKgQbkzUEU34CZsRZ0LwBO2uwngAWHqUki9gQDSBNa5VQCzRiL38As+0NGH85Zvg8aFiJ+Ksw9SuQzEHYr3wZad2mCrfCyZj0YqS9ApM5SNd76SysoqnYGMThSwS3b0W2vaEKqKFzlTw0FmbCVcjC7yDVSzBTvtSV5VUwUb9XRw2SO0YJPsulyxwL637mycGEm8FfrURdqBUkBp5MSJ+lpGa4FTa/AMfchuXLQwbPRra8AltfRrKHgXF2qf9SOCyxPSy09sIDSuKfJE1jUEKok+QgYT/r9pqDrlBDa6f75Pv7gtvoiU+2Q6teC12GQpeG0Ra6et52tiWJCJUReLUFVgVUpZWEzzJK8GQkiKgDaGlKEkzvtHU12KVZmoc0LaNvS1t32AmVWNIiGLCF+oTFy6AnjNkO/R4GwWGUmMtxwueKhP80GCoi8FA9XF20a6ZKltMwzgerAsL7HXBOHnxrkOHvdbofrAro8uYlWlC+t034+2gY4t39so/2GX4wGP5SC6+3qMoqwwFfKoHhPsPmoGCM8HSTYV1Qt4/XwNwcw2k5GjKeLHPIF6EjrjbH7AzDUI/wxxq1WD7ZCFcUCK1xgz+kAeI7W+qmZBimZPR/O8/LNawLwj/qhN9WCSdk7ZmIdBjDiVnwQpOwoFW37/QBzPNAo6ysjMWLF+/2PUuWLKGsrOwgLVEKBxOWMVxeCE0x4c1WGO/rsqN2x7R0WB1QC93Tu2mhs4xmiLzRAnOyhbzuqqamtUjLJsjc+31J2iu1lAYDg2fv9XQgEXrfshnKj8MMPmWfppVCCikcAXB5SR4/7DX2EAQOA1A02THy0fiXpMI/rR+nzflO2BLWiIUpA+/POmDYJ6LJ6XQSiUR2+56qqioyMg6jb3wQYNyZmKNv7Pf7xY53ZgRJPKKPk3YzO6Yn6PFo12N751uU7mys2HENJYtq+xeRdiTcAqGWRHaR2sSwXOBwIpYbYs2YZJC4v0anYxJ7ttOLKZ6qOTnDz0C8ebD5Zex3f4ZUvatkQNLfkjtK85cGnYSVWQ7pJQkb38D/E0ssBO2VSNs2pHIxsmOBZh8lLGUUT8OaeLVa9qz9X31ljIU4PZ1kE/Gw2t9KZmC1bEEsF2QNQdY+ogc5lkfJulAjZscCzDH/jb30N9C2VRVjTevBcmI82Zjc0VijzsXkj0eiQaRtB8Zy9prNZAonIaPOR7a9jmx5Wdv9ltyJGTIHKZ0FFW9hb3wG6lcgrdswaYVYp/1Bia66jzUXadJ13baBYEpmqlUw3A52RC2SrnS110X9atUrma4kaLhVrYBFR+nyuDOQjFLoqNbnc0Zpex0GiQV1Fr48DTrvqO5S0TnTMQjG5UXGXoqsfRhp36Hb1JeHNeYzxLe+gux4E7KG6zaNBVJE02GMUV5DqXtgV4IMSm4kb25Lc3V8lhIr3uRjh9qcvInnfVYXUZKdCLvOSjzeU/7OzgjGtT1sY0h97a2xru/gNEp8TElXtYrzAOflxEVY7odF3QimDAccnwlHp6vqZ3eI2oI/Lnzghw869PusC0BFRAPAd4bPgsEeYXqGtsmdkq1EjcFwXp7mHW0PGx6th2uLhZydFDYzMpVQWtYB83KVjLq0QLivVtU5UxPEnMtoNsvNm4T7RqsibHfIdBpmZNj8qVp/zQpd2gT3n3qhKabfJdMpOA3MzTaclds7+WaMNiEmnTxlHsP3BmtzXV0UtoR0u0ZE2+qGeWSP63hPuLFYbXxVEXiqES4r3PNnTsnSz3zUITTHVCF1uOCCCy7g97//Pbfffjvf//738Xq7vHyhUIif//znzJ8/n6997WuHcClTOJDwWIbrizX/bmUAJvp2JZGM0Vy3PyYsdO+2wwl9RNSUunXceLtNOD+/a0J29VIt/tjNCdruINEgbHpO/yg6at9Du9srtGl47KUH5LgyhRRSOMzg9O37NMIJF8r+IJriYdxOFzkOoSVuaIjBkH4QTR5LYytWB2RAF8sONPZpFJ08eTLz58/Htm0sa9fLHckGuunTp+/LbI44SCwMrVsShJHdRRz1+NvutAb1a5oiCYVSz4wntcMFkWgHRIOJ18MJe5ulqhBLrW7iSlOiKtyKiYU1ZDxQq954y6Hh3qCfTS/GlJ+IKTtGFSzBeqh4m/jr31DlS3c/a1oRpvxYzLAzMYUTVbU0wEDvru9pg78OOiqxW7dA5TvIjrdUhWU5tTVv+JmY8Zdj7YOfv79QssmbINM0KNw4PRqG7c7QZUorRD7+iz5OEFL28vuwrl6sJFFGGRRPxXiyVBGVNRiyh3cpu1o2AqJZSH0EgBuHGzPiLKT8BGT940jVe6pC8mTpdqx4S9+XPQxr3p80/D2tCGlcq8Rh9RIoO1YnFgtq817DSkx6McbpQ3wFapsUN+x4SwmmQF3C5rYYWfMQ9tDTsJwqCTVZQ5VE6qjG5I7W3KnktCFh/czRJkJ/rSrkfDmq6AJMzggYeirsWIi96l+YWAhpr1JLX7gVGlZARnlin949mZ3CocP0DLhnpOm0q7l2ujkNuKyezx2KoOOoLeyIwKagkkuVEemR/eS2DGN9auEa4xs4cbU3sLsRTK07EUxTMnZPcEVtoSIiPN+kzXEfdGieVXckNT5uS7dDXCBsaybWhqDeHq5X4mlervD5YiXY5mQLTzZq49t/GgzXFfUkYpL2rtaYsCZgmJwOdwyBv9fptFcGwOOAXwyDL29SMuemTcIfRuw+NP2VZuFH29VSNjtbScR2G1psJeCcRpUV1xQZ8neTjSUiLGqDF5uF9UEllEZ59bPLA/BCC0zNEIwYwraSQ9lOoSah/CpyDTx7y+cwfL4Y7qwUHmkQLinY835e5jGM8Wmj3VutcH7+gGZ5QHH77bfz3HPP8bOf/Yw///nPzJo1i+LiYmpra1m6dCn19fWMGDGC22+//VAvagoHEDlObaK7q1LYEFJ73M67dY4T5uXAswkL3TAPlPdSZOwwmvf0UjPMyBDKPEaPIareRdIK90pPILGQtu8G6vQEbx8USGLHVclkLMy4S7WdOYUUUvjEwxhrj1mgu4OIQPVS/SN7WJ/vi9EPa7DYKhDJGQG2jooDGRszHHqx8XDCPhFNn//857nhhhu46aab+MMf/tDjtba2Nm644QZqamr43e9+t08LeaRBEvao3tVHSYVSb+okJaOkU80UTZBLyZAxo2qeXm+OhDopXR9H/ZhYHOIRJNIBwQa1McWjmgfUfYEtJ+SMwORPwOSNhuzh2qZT+zGy4SlkyS+VLOiEgYwyzKDjMcPmQdlxWJ4+kiD7u87CbdBRhd1eCS0bkYq3oHaZKqUcqhwyYz6DGXsJ1kGumTXGIA63knoSR+yYqo/SChP5Sg6YdjOy7E/gzIBwowZJ7piPKT8etrwMgQa19u1EJEm4Demo0j9yx+x5WTxZmMnXI6WzsNc8hLRVwfbXdGBKL8Gcfq+STIBxp8OQOciWl5DtC5T4yRkJ8agSgZnlmsWVPQwTC0J6cWJfi2FvfgExTiiaCg2rNDup9kOkZDrG4YLMQRoAHmnTeScti3ZE9+N4CMkerhY7SGSPZahlDsCdgRl+poaANqxC3JlKWOWPg62vQ+UiZNSFmsUTD++rqDWFA4R8l+kzl+NQwRbN+qkI660yArVR6QyMTqLQZRjlUxJilO/AK5e6L98KPyzqlsGUbsHxWZrd09dyxEXYFhKebdKTtfc7el6myHUqSXVUumFCmn6nYpfmDCXVjCFbqAxrk9viduGVZtgcUhXO041wbp7wrXI4Nw/+XQ/VEeHVFsPZ3YYtyximZQjzW3QZJqdDsdvi2Eybt9o0i+XodGiPG/44Em7YIGwPw7Xrhf8ZumtmU8RWNdT9tfpt5mbDz4bpe9YFNDcqJoLbKKET2olQ645lHcLPKzT8uzs2JA68St0atP2fBsOXS7ThbnNICNqQmVBHNUZV8TVsD3a/nXFuHtxdrflUSzvgmH78JM7JVpn7Ky3CmbkHNvtrIMjLy2PJkiXceuutPPzww7zwwgudr3m9Xq6//np++ctfkpfX+4WRFD45GOQxXFsEv6sSqqO9N9FNTddxZFUQHmtUy6u3l3OqcjesDMIjDcJXy8Bse02PQQonD3i5JB6G1f/W41qnDyZcjUle8BrotMJtmNatkDMCx7jLoGTGXk0nhRRSOPIgoX3MGmzdouf8lhNKj+nzbU2k7XlawUZIK4D8iXQkTrszBpiocxjFMwH7gWh6/fXX+ctf/sJDDz1ETk4OALNmzWLNmjX4/X6uu+46Lrnkkv2xrEcOws3IhqeVAMIkLgH1576XaTlc4HB1hnkbSdQwJYkoO4pEA5hwGxJu1hP5eDTRAiZdYSmIfs44tD0sYxBklKrqJaMcEw9Ca8KituYRbUUTOxGkkshmyhsDQ+ZgRp2LyR2zz3klEg2o/cpfjR1qgdoPlWBqr0yEjXswBRO1yW7YGViuQ1fFYywHgruT+BNjaY6ROxMSweP2tK8gS++C+iaI+rE/vAfH+Y+o8qh9O9K2XbOrEnJsEYGGVTr99FINe+8GEdFBJ+rX/CdPTuc6NwUTMdO+hjx9aZfix5UOTWsgu+tKnCmeqq2B9SuQDU9C5mBIKwaXD2JBpHWr7lfDToctLyGWC+PwQONqCDZryPuo85CNzyDrHsUUHYVYDozTg6QVQns1BGoxGWVguRMJzUENRXfFkZyREKzHxNIQO4qxXJ3LaoyFFE1F6ldC3UeYMRfrZ6vfVwXb9jeQQSdh4lHNTTjEld8pHF6wRS1H9VFoiEJDDGojSo5Ee7k6lekwjPTBSK+SS1kH2arUF8F0XJZazfoimNpjNi80K/HzTltPcmlaBpyXZ5idLRQ6oT5mqI1CW0zDtIMJUsYYwZvIscpzwqQ0zRb6yRAli+6tFp5rgmebtIHue4NUpfBEoxJSwz3C+PSuM8dp6TC/BTaFhJaYKh9uLYe3Euqs6oieeJ6ea/jraPjWFmFNEL66WTghU5iXa8hxKsnyRKNQlRjCrizUBrakGmhipwrdUBdRVVpNFISeYeVRW7inGu6rVULRZ8FF+YbjszS/a2EbPFwvVIRVwWQQVgUNGZZQEdF8sJFeVW5VhmFHGLIcO2XJ7AFpDsO5efBog/B8k3BMP5pfjs3SE/PGKCxshdNz+z27A468vDz++te/8qc//Ym1a9fS1tZGVlYW48aNw+U6zNjlFA4opmQYLskX/l6nY1b2TmcOxijRWpnIQnuuCS7O31X9ZBkY4dGxaTL1zNnxJpJeMuDfdolHYM3D0FGpOacTr9bW5QFCRKBtu15oGzoXa9xn9916l0IKKRxRkEAtYll7f0G74m29L5qqF/j7QBUZONjNlbJQM7jSMEVTiTh8JBMd0nsh7fuCjToHDifsswH5wQcfZPbs2dx9992sXLkSEeH9999n/PjxfO1rX+NLX/rS/ljOIwrG6UM8mfojhum28ybIHpJkUTyhYuqWx2RHteUtFkpkLLVDpE3v7Xj3JKbEnST+Sk478bwnG3z54MvHePOVVMooR7y5mGCj2qn8NWqtSmYIdaqjjIaXZybCqsuPw5QduwsRsjfQdrs6nXe4FQk2QsUipGqxqmEsF3hzMENPxYy+CFM4SVP8DwOSwVjORJ6WKsVI2AONy4eUHoNlnNjH3Ia8+jUINcD2+aoEKp6GVC7SVrncMRh34r9d2zZVBFlOyB/XOR+JtCM7FiLV7+u2T87fm4cMOgEz6GRtipv/Td1P8sepWqm9Avvdn2tb3shzOhtczIiztRmuagk0rtM8KadP95eGlUpCBeowOSMx4RbseFSvMtox8Ndixl+JbHxWg8/bKzDZw8DhxqSXalh8oA6yhnUG6kmkHcJtGMuhVxhzRkLdMs1jcnh0IDWWWjW9ueBwYcTGGLAyB2MPPQ02PKXZTRsakZwRGsbeR5NDCp9MxBOhzu3dbk2xBKkU1aDaeC+EEqj1bVCiUW6QR6+kZ3VT9hxMxBME0zvdCKa0JMHURwZTXIRVfuHBeiV7mrs5lWdkwAV5cFoOxDBsDsFbbYbIbo5fAALo+tuCWu2cRrOKpqTDA2MslvuFb20RPuqA72yFa4pUZbWsA55qgqFemzSHjil5LsMwL2wNaQvcCVlKKhW51IK2pB3m5MDpaEveX0bDPVWqZFjUDovae264PCd8Z5Dh1N00thW5DcaoOqo2qutoiEdtdV/dpOHkABfmw7fKe9rrTszW9XXzJm3LW+bXZrlzc8GFtmUVuPQzBiWkNocg1zkwgvvMXHi0QavcQ7bg3YNCyWkM5+XB32qFZ5uEU7IPH1VTEi6Xi8mTB644SeGThTPzDBUR4aVmGGdpHkh3eC0llx6oU2XTCL8S4Tsjw6EnTo9X1DMmAmV5/Qg06waJR2HNI9qs6/DAhKu0bGaAkGgA07IJ0ooxk67BDDp5r8t4UkghhSMY7ZV7ndMkbTu6soPLj+v7fQLbySaNPmrkEq11pvBojDcXf+JtyRzTfi+P6LHd4YT9knR34403cuONNxIMBmlubiYrK+tTFwDeHXZbBbL634msJLp5P3s7K5Len+4LTo/m2LgyNCPIlaEEkC8ffAXgzUPcWZhou7KjoRaItCJN62DHQgjUJwoWrS61EkbVMgXjtfGs6Cjd2TPL93FNJK4YRdoS5FIdEu3Qq1F1HyPVS6F1cyKY3AkZwzCjz8eMOEctZg73vtXdHgg43F15TQkLHWiGkpTOxHK4iE//KrzzE7WgPf85rIufhpr3dTCq+xAGnYiEmpGm9frZvLH6eRGoWqzB3skAbMuJcWUo+RRqgo3PIjveVnKobRvGm4s170+IKx37pRtVibbmEVVKTb5eM5iMBUNPg8whmq8VD6n6KKl6a1oPLVsSxCiYWFAfGwcmHsKEGjDlxytZtu4xzIyvaxB6ejEGCwnU6zycaUq+xSIqI/XmJIglnxKM0UBiv014SgJ1GgKaPwHCLci212H4WZjWLcioc2Dj8xBqQj68BymdqYq6FI44iAgx0aycZEZQRLruA3ElC9p3ugVs2aNv3mWUIChwJdrmnFDm0ba5Q01OJ0O+3+mWwZRuqYqlL4KpNWrzRCM83KBkUBJFLriyEC4vBMGwJgAvttDDDuix1CpX7FbiJsOhhJZBr3IF4qo2qI2ovasjDiv9ehvrE07KhhcnGn5fBb+oEP5Zp8HZx2To9ni2CS4pEByJ9To5DbaGYIVfiSaHMVxWINxdrUTQ4nbhiyWqTvJahm8NgksKtJ1qhV/w21p7flKW4aw89kjKgNodDcK2sCrYtoSFX1bAtpB+358ONZyR2/t0jsk03DUcbtoobA3Bhw61G56QpftNUwzynEpe1UZUDdYQ01Dy/mJyGpQmQszfblNya084JVsVIA1ReKVFlSGHGqtXr+a1117jiiuuoLBwVyKgrq6Ohx9+mNNPP53x48cfgiVM4WDDYQxXFakN+WN/7+HggzxqB329VcenwZ7e//8MlhZWBII8knEmX2MVzv5mldoxWPcotG3VY5gJV6qaegAQEfDX6AXX0llYE67sjBtIIYUUPl2QeESdQHuZK0zlIr0vPGq31l0/Lprx9k40JbKWTcFkjTQBOhIXDjMGeAr8iVQ0dYfP58Pn2w/p7Uc4jMOhTRjQRSI53N1unp3uk489mG6P8WR3WqbEk41xeDAST7R46Ym7RP1K5AQboWUTEqiHUAvSw5bXDQ635uPkjIbckZjc0ZiCiZA3rqu+fh8hsXCC5GrU5YmH9ce9dQtUv4fUr1C1jMOlbWUlMzCjL9I6WeNQhcth2vaheU2uhIUuihhHl53NciLF07AsN/aah1Q51LoVe/6tmPFXQMVbyPoniWeUY1o3A4JJL8FkDlLiac0jSHOCfMocjBl2GuSP1+nGo1D7AfH1T8LahzUwO3c01hn3YrKHqWpu0nXYm55BOmrUBvnu/2KGna62uHgE48uHIaf0sODJkDnYG5/VLKVYQJsGG9erOsmbi7RsQgINUDhRrWzrn8QefwVW1mAlNy2nKu/CLUqCenIROwLtO5RoKpmOiQYAtX7izQNnQlravkO/68izkTUPI7Ufwcjz9DlvPjLpWlj1dyXG2rZDimg67FAZFj7yK4EUThBJuz7eNR+pv7CMWt4yHZo1lONUEilJLGUfIpXS7hAXPRF7p1uLXNIiN7UXgkkJKeHvtUrCtCc+Yxk4NRuuLTbMzBBWBwyvtug6TaLQBSO8mjtU7NrDunDBEIDEf7/kttsQ1PDITSE9SfxmuWFSGnxxo/B2mxJS0zJguR8mpwlj0/Skc2IaPNcMO8Jd9rnPFhrur1Ul2tJ2zcca3O1nZajX8LUy2Jcq4QKXwWWEt9uE27cpiTfIDfeNNoz27X66p2QbrimC/6tREjDdgkvylQyLik4rx2kocyuZVRMZGNFkjOGMXPh7nfBys3DabhRaSTiN4eJ8+HONqprmJFoADyV+8Ytf8Prrr/OVr3yl19fz8/P51a9+xbJly3jggQcO8tKlcKiQkQy9rxA2hWF0L+dmJ2QqQb05rLbQG4q0ECIJAWjdxIhoJUvSxrAAP6exZY/zFjsO6x6Dls2qfJ9wxYAJIolHVMXkysBMvAYz4kw95k4hhRQ+nQg16znGXuS7ib8GmjcABsqP3+17G0gjgIsSdmrRlrgKQnJGQt6YziMjf/LYcYAiS+ETRjRNnDiRuXPnMnv2bE455RQKClLeZgDJGo45/6FE41vCvmTH9UQ7Ge4dDysBk3wu2SCXbJOLBvTkOtyChJoh0oaI3b/rPpYDHF5MRqm2i2WUYrKHY3JHaRV9WuF+PTlTYqkpQS41KflFokGubTvUr0QaV+t7LJcqZbIHwYizMENPx2QkZM+W87Cxye0OaqGLaTvATpYuYyzNMZrxTeS1m5VQq/1QFT3546C9EvPO/yAjz8HKGozkjYeKRdibntNtbzkxI87GDD65h5rLOFxI/gRM2+813N1yQdHRaj1LvmfQCZja9xFvnpJArduRTS+oZa9gkhKKxVN7tCEZbw5WznDEJJRJdcsQiYCvHJM3VpVRLRsStjdtopNFP0KOugEz6ARIK1RbZ7BRrzAGamDjM6rAcmfq1cYpXwZj9P8AgDsTiUeRjmoNVS+dpQqthlVQsxTj8Og+ZSyYeC1W+XFYZX0H7H3asXTpUu644w7effddIpEIEydO5Otf/zpXXnnlAZ93Ywzeaes/i+SxDB4LPEYVOG4DaQkSqbdbmnX4EUl9IWQrwfReexdZlOGA4zJ7D/luj6l66V/1ak9LYpAHri6Eq4oMMdHX/lnX9dkMB4xP0xa1gWQI7Yxyj6HcA3URYUGrZhe92qKNfKfmwGPjDJetVTIqYKvyZmEblLghxylkOg3DPLAlpOHbJ2arrW+oR2vMd4ThxSbhi6X7f/v54/CrCiWGBrvh9iFgAcG44NsDSfP1MlUQrQlCRQRebTFcXgh1URKEmarCtoX177AtA2ohnJerDXyL2qAjLmT0gzQ6PgteaIZ8p4adD/Tgcn/jrbfe4tRTT+21TRjA4XBw6qmn8uabbx7kJUvhUGOQx3BtMfy+UqiOaMB+dxgDF+XDn2r0/9QrrXBO9+yxYBO0V5Du9pBBlCcZxzhpYJBp73OeYsdh/eN6Umc5YfzlA26Fk2ADpr0aCidhTbhCj29SSCGFTzdCTSoM2Qv7LRUJNVPBBL2Qvxs0kEYIJ74eiqZEDm96KabwqB7Hup2KpgEeC9jyCSOaGhsbueeee7j33nsBJZ7mzJnDnDlzOOWUU8jNPYySLQ8irI4K4q99tcdz+9Cc2BOudJXneXM1l8eTrTt4Rpm2jmWU6WNP9gE5QROxlVgIt6mSKtTcSSxB4oCgZSM0rdOQ50iHEl8YcGdhDTsNRpytSp3kh4x1eNrkdoekhc6OaYD2Tuvamnwt8ffuVBVXpB06KnR9pZci8SBm0/PYxVNh0/OaaQRKBo6/XNvsdoKEmrFf+yrSsglyR2NKpum8V/4dpn1V85DSCjF546BpLeRPxAw7A1n3GHTUQNUSbXhb8zB2Zhlkj8DkDIfsEUjJTM1kShPEmw+xoE5r+JmQOxLZ9BwmGtBGuFAzVL+HXTARKx5Wu6bZqllbCWsdElPVktOHdFQjb34PJl6NlQwCd6erJxoBd6buv8NOU6Jpx1vI0NlKtEYDWN5syB5+gDfmkYsFCxYwb9483G43l19+OdnZ2TzxxBNcddVVbN26le9973sHdP7FLlWJdCeP+nrsNkcOaTQQNMeEpe3wsZ/OEPLMBME0ZSeCKZm99I86eLIJWhPZSw4DZ+TA54sNJ2cJ2yKGha2qqEliqEenN8yzf9djkdtwaYGwtENDelcHVMV0Xh48Nt5w4RphXVA1SLOzYUNIGOszZDuESWmqXlgRUKLJYQzn5QubQrou/lEHXyzdb4sKKDF2/QahLgpjffDLYRARQ0scWoKQYQn5Ls3k6i3vyGPBZ/Lh/1XB9jC81yEclwVpliFodxFL2U6hNaZB3WUDEPuO9sJwD2wJa2D6eYnjz2BccFm9h75bxnD7YPZIkh0s1NTUMHjw4N2+p7y8nOrq6oO0RCkcTpieYbi4QO21GYmLAt2R4VCy6V/1WjYwwqPkuADSslHzOJ05DKaVlRTxCBO5RZbgNLseKYvYmtnYtE7LbMZdpjmR/YTYcVUxGQeMuRBr9IUY96c32iOFFFLohmATJnEeNxBIsEFLkwDKT9jj+xtIS4bW9Jg3nmxM8VRt8+6GTkXTAE+LhU9YRlNNTQ1r165l/vz5vPHGG7z55pv84Q9/4O6778YYw+TJk5kzZw6zZ8/m/PPP31/LfPije6iY5QKnB5PMr3F4wdXtsdMLLh/G4dXPOX2J59J1B/TmKKHkzdW/D5LMV0QSyqoOJYuiHRBpVzXNTrSZhFsxbTuQ1i1qi4sF6bRGeDIxg07EDJ6NKT9e14fdjdG1XLv8BzsSYIylNrPOYPCeZyLGcmCmfw2Z/y39vp68BDHXBKWzgISVEMCdgTXsdCg/oVeyTTqqsN/4JtKyRTOZzrgXvLnYS+/SJrvNL2BGJSxn5ScgTWuh+j0o/iJmxjehdZOGvrdshEAj0lYBbRXIjsTVaFeayjbTSzAjz4Ga9zHY0LoZa+ipSP4EZN1/IB5TYrF1K2x6HtuVjpVr6z6x5mHNZQLIn4A5+kbM4FOQ9+5ENjwDK/6GTLxGFUwOD+KvBQwmK3EyUzRFVVjBRiXGLFdXTlUsuF+33ScFsViMG264AWMMb775JlOnTgXgjjvu4LjjjuOOO+7g0ksvZfTo0QdsGYrdhjM+pc6DHWFhSbs2pyVR6IJZGdqWliQURIT2uPB0E/y7DpZ2Uy+VuzV0++oiQ7FLp/VQg6EhMUQ6DUxMU4Ip9wAePRhjmJUJxS5tn9sehicb4TMF8JdRhs+tF1YGlFgscmlzX0ecTvtcRTf73Fm5hvtrlAhaG4AlbTbHZO2fiwhNUeHzG4QdYVV+PTDaUOw2hGxtrmuO6ZXAjsTQ4TaCL0FyJjmn6ohQ4tLPbwmpxe8PVXB5gZDlhOYolHgMeU4lAptiAyOajDGcmQt/rBFebhHOyzdUhoWaqB5kjvP1rro6XEgmgPT0dOrq6nb7nrq6OrzeQ9cEm8Khxdl5hsqI8Eqzqit3Dqwd6YXjM7UE4ZkmVT5lR+r1OCFhUzHACJp5j3LmM4zTd7LQKcn0tJ7QGQvGXYrJGdnvZdRj022QPQLH+MuheNon8mJHCimksHeQUFMiZWaA40LFO3qfOwaTXrzHt9eT1jMwINym579FU3olvjv20jr3icxoGjduHOPGjeOmm24CYOXKlSxYsID58+czf/58fve73/H73/+eWCy2hyl9gpBRhuPqxeD0HtYtFmLHlEyKBfUWDXTeSyyoJEpvn4v6MR01aqdqXIt0VGqDWALGm6vWryFzoGSGBl3bCUImSTIZR0LFdJj9jxgIHC6IaQudiL0LSWQd9Xni7/wEwq2Y3BFK1LVVaPj2sbdhOdM0gyt7eJ+ZVFL7EfbC7yChFkxaAdbp92Kyh+r0x30We8UDyPYFSNEUTNZgJHOwklodlVDzIWbIbCiZiVV2rE4v1AytW7C3zYetryDNGyAaVKIsvVQl6cPmwdYXNU+reKpaMMuOhcp3keLpEGxQwmzl37HTS/X7xEPgzcWMvlAJK6dXbYQn/Jh47ceqcNvyEqZ0pu53/ppEALwGeRpjYYbORdb+R5VwRVPUdgiaR5bCLnjjjTfYtGkT119/fSfJBJCZmcntt9/O5ZdfzgMPPMDPfvazQ7iUnyxEbGF1AD7sgJpufPkILxyTCcO9XeNZOG7zdpvmlLzUvGv20hdKDHMSsQBrA/qeZCud24Kj0zXTKe0gEhBDvYbPFAhPNaqV7sUmDae+fbDhx9uF11rVOrclJAz3GtItGOIxbAup6umYTL0VuZWgiQK/roRHMwfW3tYb2mLCFzYIm0Nqbbs/QTKBBomP8Or2aYwpQeRPhM1HdvoZ2xCEoMBlBfD7Kt2O1RElzE7M0sD0U502+U7DFnSbxKUrBL0/OCMX/lijNsrqsE1NVD9ro7lVow7zKMvp06fz1FNP8atf/YqcnJxdXm9ububJJ59k2rRpB3/hUjgs4DSGqwqhJqLNkxN9u0aCzs1WC2plRNszPxfbiGXHNIM0gXSiZBDmKcYxvpuFTkRg43PajGssGHsJJrd/F02SsQ0mFoKhp2ONu3SP1pYUUkjh0wcJNCA92uH78ZlQCzSs0D8Gndivz+wgCx/Jc5og2FFM0VRMWlGv7/fvZRi40HvRzKHEfk1cjkQiNDQ0UF9fT21tLX6/HxHB7f50XfI2lkPtQQcZYscgHlXrUjyqpI4d1cfJ/KdEBpTEI30SSZ1INtIFG1SB0rZNm9IC9T01TcbC5I3DlM7ClB8LRVM6SRcRW/N2OudllGA6jAm4/qKHqsmO9chqApRsGfMZZMUDyJZXMJ9bCq/cBB2VyMLvI8fcqpLJ3lRM8Qjy8X3Yq/4BIpi8MVhzft2DOTeFkzHF05HaD5B1jyFH36gHVqUzkQ2VSMMKzMhzeq7r9grsj/6MVCbYeGeaqoeiAc0/WHIntGxGCidjgvVI5TuYEWdByUw9cANk5Lmw9VW1vwUbdP/KHAwzvq7qtPYKnXYspNt64lXIoh9D2w6kdhkmo1yzyVw+zXhKfp/BpyDrn9RpBhu6SMloStHUGxYsWADAGWecsctryecWLlx4MBfpE4tkcPbqQJc9zmm0ZWxmpgZUA0RtYV1QeLQBnm7UE6wkytzaHHdNkaHcY4iJsMKv7XJJEspraZ7TlHQGlAvUHSJC0NYg8oANcdGby4DPSuRf7UYdVeo2XJAnPN6oAeFvtsHNpbCkXZvnnm9WEmy4Vw+GRnmEbSEly47J1BPQ03P0ubCt1pkl7dq2t7fwx4UvblQyK9+lSqZBnl2/g9sylLpVPRFPrIegDVFbSZ6QLaQ5IMsJFyQCzt9uU6IpwwH/roej0lW2fkGeWujCtpJcVRF4o1XVWzlOw6k5MDOj9yuhgz2GCT5hdRCeaoRZWWohDScCx2MivVroDhfcfPPNXHjhhcyZM4ff/e53nHzyyZ2vLVy4kFtuuYXm5uY+w8JT+HQgy6nh4L+qULvszgSqw5AIuocdEVgYzWWOp2OX6QymrdNC9zV5Dydx2PwC1H8MGBh9Ub8zlSQawLRshvQSrMnXwaCTjqxYhhRSSOHgoaOipwupP6h6VzN6s4f3q509KhY1ZGo+kx3VOJW8cZDTdyzI3oaBIzruHk7YJ6IpFouxZMmSTuvc4sWLCYfDOJ1OZs2axXe+8x3mzJnD8cfvPo39kwYRUfJBbBBJ3NuA9Lzv/jq9vM+Od5EYEu/6e6fHnQTT3iRBWU6M04dgQagRgk1IoA46qpCWzV12qO4wBpM7BlN0FBRPxZTMxHh6nkWISILo6qZkO0Q2uST7LHXLE0RZrRJndgwsh9oas4ZicoZjyo+D0mP6b1FMqpr6yGoyx/8QWfVPiLRjtryIOfMvyJvfR+pXYL/zU8zaRzBjLsYUT1N1U6AOqXxHiaNAg05j+BlYx34P49p1MDSjz0caViEtmzA73lRbXuFkqFoMkVaoXgyDTkIa12J/eA+yY0Higw7MiLMww+dhsoYgDWuwl/4aGlYhax9V4ilrEKZ+OVJ+vOaCDZ+HrHoQg8CMr2vQe9USxADF0zGeHIi2J/ZhEpY30SuJg05EdrylFrzcMboPpZf0DDx3Z2LKjkW2vq45U5lDVCkWC/WqGPu0Y8OGDQC9WuNyc3MpKCjofE9vmDhxYp+vxeN7IKE/BaiPqnppVaBLaQSQ71Qr2+Q0JW4itvBeu/B8k9bTb+jGi2Y44NxcuKLIcFymZvFEbOH9duFDPwS6HUxMy4Cj0gZ+NSouGspbHYHaKNRHu8iwvuA1QolblVjDvLvmBpV5DGfm6nda1qEk2e9GGN7rECoTbVInZglFbg0UF2BzSIjYSvacmWv4R50QS7QP3lUpPJzJgFRBSYRs4aaN2hKX7VQl0zDvnqfjMIYMR88wze0h3X65Tih0G/57kPCZtUJLXLOYABa06DqM2zDaK3wYUNKwvVt1Yktc+GstbA4ZPlvQu1rrnDzD6krhiUaYkSmUeQw1USW+2mKQdxg7xs8//3y+/e1v8+tf/5o5c+bg8XgoKSmhpqaGcFhbZG+99VYuvPDCQ72oKRxiDPUarimGu6uE2oiqDbsj1wnn5ApPNBnedo5FTBonsxVnt+PVXSx0dY9D7Yf64ugLMAUT+rUs0lGFCTZD2TFY46/o10lgCimk8OmE2DEI1GtcTX8/E49A7TL9o2RGvz7ThA8/LrIloLlMWUMw+RN2q6JKKpoGmtFkDBxuMo59Ippyc3MJBAI4HA6mTZvGLbfcwpw5czjxxBNJS0vbX8t45CHqRyoXHZp5G0sJHculJEiiyU3EhnA7hFu7muyCjeCvQdq3d5IavU4yo0R9qPnjMIWTtcHM1ff2laSaqnMCB9cmJyLa9LbtdWTbG0j9x0ro9fV+0PcDLAWcPsyo87AmX6cE0G6gqiYrQQzGdJ13g5VRgl06Cyrfwf7wXhxHfwlm3wnrHkPWPoo0bUAW/6L3aacVYmZ9C2vInL4XwJWOGXwysvEZZPt8KD8ey5uDDDsVe/0T2OuegDWPdiOYLMzIc7GmfLkzH0niUUx6CVbpTOSVm5CKt2Db60j5sVAwESoXaROeOxOGnaYB5k0bMKPPh+yhUPuRhoEn7ZaWC7FjmEh7V75S8QytJQ63IKv+gRl6qgbX7/ydh56G2b4Qadumtrp4NGG5jIMjRTR1R2trKwDZ2b3XsmZlZVFRUXEwF+mIR21E2BCEtUFtTErCZTR4emqG5ioFbWFxG7zQAq8291QuOQycnAVXFBrOyu3K3gnZwrJ2VUaFEwcRWQ6YkQkT0noPie4LUVvYGoatIW1O25lYMijBkm6p8soyqupJKp1Cgn4+DM5WmJguHJ2uFrQkRvsMMzKE9zu0je6qQrhruOGqdcK7bapu+mIp5Dl1PgFbFVDj09SCluVQIi0mStY92QiXDLCYNmQLN2/SZchwwH2jDKN9e/870pAgDAsTw/TYNMOp2ZqfFQdGedVKt7QDVvj1JNkyqkYqdcNJ2YahbuH1Fvg4APNbhVynYV4vvSfn5cGfqnXfWNyu+04gsQ064oc30QRw5513Mnv2bO655x6WLl1KRUUFOTk5zJ07l5tvvpmzzjrrUC9iCocJZmVo+Pd/GsAf0sKC7nz5JHeAing97zmGsYghrKGA81jPEFo735NOlEzC/JtJpDmW0xWv27//7xIP6zHt2Euxxlx00PJMU0ghhSMUdkzFFv5aJK2of04bY4E7E8ItsP0NJHPQHssFOnATwYEr1qHnlzkj9zivTIfGD1RHYegAoxBb40J/x82DgX0imvx+bRs76aSTuOCCC5gzZw6TJ0/eLwt2RKOH8sLo30bvTdKO1v2+2+s9n3NoY5txdD4WTMICF+m6jwUg0oFEOjAJIskONet/hFCzBjhHdpUr77LY3lzIHqa1sdnD1A+fN3YXtVJf2EVZdZDb5KR5A7Lucez1T6japjuyhmh9ZMEEyCiH9CKMw6NKpEgbtG5DGtdoQHagDln7KPG1j2KGzMY64UeY/HF9zzgZXG3HEMu5awPdcd/HfuwcaN6A1H6IyRuDGXcZMup82D4f2f4G0roFokGMJxMKJmOGzlW10W4OlpQ8bIOiqVD5jsoxq96FEWch3gKkeinUfax5CJ5szPB5WFP/S9vmuiOhOjO+PMy8PxF//HwNDm/elCAqnUj5iRhPFiZ3FFIwEeo+Rra+pm0LTes1EyrS3hV0Hw9rgLwIYkcxTg+MvhBZ+Q+oXqoNdhm71lGZnOGQM0K3X3uFvsdO2jwP8zOzIwyrVq3q87W2trY+CaxPEqK2sC2sKqSNoS4LG2hw80gfjPcJwzz6g/9yM7zVBu+0afB0Eh4L5mTDuXmGM3Igr1saY3tMWOZX4iJJCOU51XI31qcqp/6iKiysD8LmEHSbPWkWDHKrmqDYBTnOvqcbF6ExqoHfG0NKPH2csAXOzBAmpnXZwY7P0qymqoiSTRfnK4HyZCP8Xy1cV6zZRcO9qjhaG1CiyWOpfe7BelUhxQV+WymclqOB4f1ByBa+sklJLZ8FfxplmJi+9wdPgbjgj+vhV35iKBER5mYraVYZgR8P0XXyYpMqxFri2ph1VDrcWAz318FPtuv3CdhdirbRPhixk8oqzaF5V3+shofr4eqihAw+qp89EnD22Wdz9tlnH+rFSOEwhzGGC/O1KODRBi0OGO7taqMzrnTOLPQztOFjXmQMTVYaf2cK06niVDbjQQfeQbRRTxq/zb+eeGklJ1c/imx8BjxZely6u2VI5j6JpEimFFJIYY8wTi/WlC9hL78f07AayRuj5yq7+4zlRCZeDSv/ocT2qn9q0dFuyKYSOsgkQocrl7TAVi1n8uTs1uEz3qf5dqsCcGxm/79TgRMWt8H5eUL+YZIKbkR2I/XYAx577LHO4O81a9ZgjCE/P59TTjmFuXPnMmfOHMaN280J+hGG5MlXa2srWVl9ky92xA/1yxN5SUlFRjI3KbLTffJ1fY/EIwkSKUEgRf2dVe8S9evzewtXGia9BNKLNesn+ThzCGQPVcXKXmBX697By2ESEWTHAuTDe1WJk4QrHTNkjipnhsxRVVY/p0fN+9gr/4FseEq3j3FgTf8qZta3+w7tjoVU1eRw9/qe2P+NhvYKzLDTsS58TAkiY2mAtjGddsu+pr/rctqqTrPjYCykbTuy6h8IYHz5yLrHdb8JN0P2MKxjvoM15jO7TseOJfYp02nNsze/iP3aV3UZ88ZhSmeqfW/4PP1MPIq9+kGVnOaPg45qzXzKn6Cqt6g/sRx5+v5wK0YEvNnIlteQ9Y9DRjmOKxf2uo/Y2xdiL/qxBoyPvwJH+fGYkun9Wi+fJlx66aU89thjvP/++0yfvuv6KSwsxBizx/ao3tDfse5IQ9QWKiKwLaRES1VEs3uScCIM9eoVeYeBj/yaMfRBhzaUdUe2A07PVXJpbvauod0NUeGDDlgXhKTrqsilBNMob/9bTuKi+SfL/XqFK4ksh05nqFcPLvZWMbo9pIqhpNqnxAWn5kB64vu0xrTGPCYwN0eVPZM+FDri8I0y+O5gw6qA8HA9FLjgu4MMxhheaBKuXq+tb8M9uuyn5sDvR5g9LmsgLtyyWVjUprlV/zfKMCNz3w6atoeUVMxz0klYVYWFFQE9OX6nTdVqfx4FwTi80KxKtgKXWgefaIT5CQHGcC9UhNVi57U0WPzHQ80uuVpbgzY3boLaCMzIgN+OgI0hDR6dmr732yyF/YdP6lh3qFAbER6pF95uUwJ8SDd1k0SDBOtW8Vokj2XOEQBkEeIsNjCGps5pxDBskyy+sv47zGyaT9yZhmPy9Z3HFH1B2iv15PHkn+1RZZBCCvsLqTHkyIb4a7GX3w817yPZw/olrpBQE6z8p7aJ+wph4jWY3WQz3ynHsZxiRtv1mkGbO1ozevt4f3scfpNIrvl6qV6w6w9sgZUBuKHEcHbe4XF8sU+KpksuuYRLLrkE0KrbN954g/nz57Nw4UIef/xxjDEUFxczZ84cHnzwwf2ywEcCTKCW+OtfP7AzsRxqX3OlgysDvLmqWvHmJh7ngDdH//bkQFrRfv/h7Z1gcvWbLNmnecejyIansJfdC41rErN3YIbOwYy5RNVAvWQa7QnGGCidiaN0JjLrW9iLfoJsfgH7/f+HqVyEdeZfMem9tARYzi5CsZfvbx31BexFP0Z2LETC7aryEls/4/TofM3ekUx4sjFFRyMr4rDhSVW9ebIwg0/WtrjWzUjth9iuDEzpTN1n7DhIDIn4wZ2JcXZdATTDz9Rg7q2vqtWt7mPwFSDlJ2DcGRiHCzPsdGT1v1XNlDMC43DpwJtslIl3nZUbLHA4MO5sZPg8DfkMNSLrHsOM/+yuX7DsWJWmtrdCyxbYg33x04pkNtOGDRt2IZqam5tpaGj41OXjdYctQkNUc4tqEqqc6m7Eki2CAGkGclxqaaqLwuMNsDwADdGe07OMhnTPzoY52YYZGb3nKVWEZRdiarAHpmfQr2yhJMK2sCagBw1JBYzLKLk0xkdn49rOCNlCc0xoimrwdMCGUMLCZqP+fY+lapwcp6p7zs2FjWHDkna1jj3ZCGfkaAZTttNwQpawsBUWtcF1RXBTCfyqEu6rhW+XCyO8umzNiQa3Mg+ckq0nmm1xrTl/qQVeb9HA7at6L1oBoC4i3LRJv7vXgj/vB5IJuki6/G4XETcnttE3y2BHWMmj31TCTaUwwgfVYdgYhAfrdXt6LPjZMMO5eYb1QeHa9Wq1fLVFM7YuK+w5zxiGr5YKd1boPvWzHXB5gWAbQ8gG3+EWppBCCvuIYrfh5jKYlA6PNwgrgzDSo2o+4/LhK5vGec2bmNj8Ds87j6LZyuARJjOROuaxkXSiOBFGmlaeHPXf5K6qY5R/FR1rHscx6VrSdlculFakpSb1y6H80/vbl0IKKfQfJr0Ya/pXsVf9C7P9DSRe2GcbXOdnvHnIxGtg1T8gWA+rE8omV+9k0zgaWUq5upQ82dC6We9zRvT6/kwHDHHD9gisCfZf1WQZ/ez8VmFuTs84hEOFfVI09YXa2loefPBBfvnLX1JfX48x5hMRLttf1lr8tdjzv6WWKoe7272z87FJPr/LexL3Drd6OTvJpMS9M02VSYdIGqwh37GE3aobwWQ5D0rQt0TakVX/wv74L11B5a40zISrsI7+Ymfu0P6Evf5J7AW3QqQDsobgOO8hTO7Inssl0pVH5PTuYhe0wx3YfxoMsRBm2lewTvyxKo4sJ8ab0+9l6Y1kAkE++AP2R3+CUBO4s7WhbvQF+pnNzyNVi3v5YonweacXUzwNM2R2J5MvdcuJP3uFSkNzRmJyR2Imfg5r2Gmd31c2PIk0b8K4s5CmtUjUjxkyV6WnxuoK2LNtiIcweWOR5o3Ym19Qq58vH8eFj+1SOyxiY7/zv8jGpyGtEOuY23afU/Upxcsvv8yZZ57J9ddfz/3339/jtUceeYTLL7+c7373u/zsZz8b8LSPpCt0IkJ7XK1sjTFVj9RE9cp6THSUEjTcud1W4iUmqlppiCmB0F0plIQrQSwdmwnHZhmOyezb9hWxhbVBVR0lCSqDtjDNyOibFOoNbTG1nqwNdNnj0i2YlKa2NPdOBw4iQktMqIwoodYa71JQ9RcOo5a7QpequFriBicwLxfKPaq4fKheibij0uGETGHMh/pdP18Mvx1h+EuN2vrOyYXTcnX8u3SNzcstcFIWXFpguLNCsAz8IkHW7Iw3W4UfbFOCMNcJ94w0TMnY9wOlqC0s1tZ0jsnUddgYVSWX0ygpttwP163XfWZ6BlycB6+3KkEWtpWU+8towzHdSK8l7cKV65TUm5MDvxneM6h8uV+ICoTiwre26n53YR6clWcY6e2/jTCFA4cjaaw70lAZFh6qF5a0qwJzkFtTIgAkUEekfiULY2Usdo1FjMFHlDPYyGTqOq/0p0WauH7lLeSHa9iaOZmWCV9gitVIn2LAxrVQOgNrxjdTisEUDgpSY8gnA2LHVMCw4Smw3Bq5socxRIKNaqOLdijRPfGaXjOMl0kJv+AExtCgRQiRNhAwZcdi0gp7mbK29b7UAoPdepzVX4QTeZnfLDccm3Xox8D9QjQ1NTV1WuiSNjrQA+Di4mJmz57NQw89tM8Le6jxaR5Mdkcw0Usu0X6ff0cNsvwv2EmpIigJcdQNmEnXDois2av5t2wm/uyV0LpVCZLPPKUZVt3f003R1BsRGHvmctjwNHhzsT6/UtvbRFR91A/iUOy4fvfuJFOwAXv+rUidtiCY3DFI5iCswklYR9+onxOBxjVIxVtIR2Wi3ZBE7hFd+WHONMyEKzHZwwCIv/pVZMtLqlByZ2KGnop13Pc6B1G7vQpZ828tSeyoVCvdoJOw0gohvQTjzdZg8PYqtfCVzEC2vKzrqeItaNmMGXEm1nE/SNgOXZ0EXXzLa8ib3wU7hjnuezjGXboXW+2TjVgsxtixY6msrGTx4sVMmTIFgPb2do477jjWrVvHqlWrGDNmzICnfbiNdSFb83VaYkJjTEmlpqgSRM0xPYGPizZ1tMWhNab3AVt/dP0JIiosvUckWomw76PS4OgMw9Hp7BKO3Rsao5pNtCYIkYTqyGk03HtaxsCIhLqIsDygxFdyhM1z6nKM9O6audQRs9kW1trwjliPUZl0hxIjOQ59nGaB29LXYqLroSOxTuqjXVW6oFfDGqK6Lp3GcGaCbKoIC4816DSuLoK/1Qo/3K6qo7XTDav8Gqo9xAPfKNf/xw/V2Xx5ky7L8inw6ypVjIHaza4oNBS4NIfgkQZhfou+NtIL944yDPbsn9+VuoiwLphs99NpLusQ6qK6vOPT9LlXmoVvbRHCtoaDB+NK9uU64FfD4fz8XfMGf7TN5v9qVJ10bSF8f4jBYQxRW7cnqE3u2Sb4nx1CXDQLalamoWQABGQKBwaH21j3SUPUFt5ohScbhfoojPJ0KfkkFkTqV1Dd3saznpnUWpoLOJImzmY9OYQBKAxs5bqVX8cX9/NOwZmsGvVFLjDrKTb+XeYnoWZMpF2zNQ/AhccUUtgZqTHkkwMRgYq3sFc9CJE2JHf0HmNgJNigNrpoB6QVw8SrdyGbGsXHf3MqaUTIIyGlDjaAOwtTfnyvSqi2GPy2Wh9/oxSyBmAWWhvU445bB5kB5YAeCOyTx+mb3/wm8+fPZ8WKFapwEKGwsJCLL76Y2bNnM2fOHMaPH7+/ljWFQwCx40qeSLczEWMpmXIwLHKNa7GX/RFZ/0RXk13OSA21HnvJHoPb9hdMzggcFz+H/ezlSP1K4k9dhuPip3sGVFrOTjJOLNeuoeDHfAd70/MQakGW3YuZ8Q1VQUUDqmDbDSQe0bBtEZVeurOg6l3iC7+roe+udKwTf4Ipnoq95E4NNm9cg8kfr8tRMAFTMEEVUXZct6vEwRiMvwbZ/CLir1Zm/qgvYDLLsabeRHzHAgi16PxqP8CuehfH0FN1nfjyIGcU0roFI4IYoxLStAKwI5iCiTpoN63T75DYl4zDA8d9H3npBp3viHMwhZMgZkPC7mgySpH0YmjbAQ0rgRTRtDOcTif33Xcf8+bN46STTuKKK64gKyuLJ554gi1btvDTn/50r0imgSJ5rSKpHKL7vfT82xZVeEQSt3A80cKVIIP8cVXkNEaVBGlJkEYhW8mRUEKRFIx3NXgF7S5CyaCkkYXypzvTAk4DQz1qPRvjM4z26eMJvq52uD0hJsKmoFqhKsNdz+c6Ve0zIRGG3d91ty2sapqabla9QW4lmMp3IlpsEWoimtlUF+1SLjm7ZQmVuCHN2nMOUnc0R202J3Kr2uOq5uqIg8cSXmkxnJ8nDPIYRvmEjUFY2ApfKoE/12iI9p0VwvcGwTNNakFrjNjkuy3OzjO4NgvNMc03+tEQQ5YDHqgVHm3QbKTusAxcXWj4evn+lXwnFWt5iZ+siK0nvaBEUxJn5Boe8cBdldoq6HWq7XFSWtdnd8ZXywxPNQo7ItpW92oLnJmr+ypoY51ldB0ubIXXWuBf9bp9U0jhkw6Xpa2MY33wcL2wtAPyHDpWGacPSmZS5tnIF5re5F1rOG86x7PJ5PEnZjKXLcygkvq0YTw25odcufZ7HN/wElWeIfx0yLWcK+uZzTY8ptvxqScH2iuQ2mUpoimFFFIYEIwxMPhkLF8+9vIHMI2rkbyxuxUDGF9Bl40uUAurH0QmXN0jviWPIKW0s53sLqLJmw+Beo0nKT1mF0Iry6lqph0RWD0A+xxAmUtjFzaG9Bj3UGKfmIL/9//+H3l5eVxwwQWdxNKkSZP217KlcIiQJCN6qpdINN85D3jIt4hA1bvYy+7VZrPk7EtnYab9F2bYGQetya47TFoB1vmPEn/yQmhaT/zZq3Bc+kJniLoxFpLMXpL4LplLpmgKFEyCuo+Qj/+CTL5OD7RszUrqLUhOxFYiKpYYmBwuxJkGH96Nvfw+nW7eWKy5v+kkvczgk5Ht85ENT0PumB7byxgLsQzGjuqZuMODyRkBR39R2xNaN8Oah2HazZiCCZhBOi1iASRkY9Y+hpQdrwOosaBoinqN7ZjuM4FGyItrkD1omL0d030n0p5Yj4VYhZOwR56DveEZZN1/lGhCEDumBKYrTb3LrVuRhtWISEoG3wvmzJnD22+/zR133MGjjz5KJBJh4sSJ/M///A9XXXXVAZ//e202TzXpSXXyFk6QQpFu9xHRxrVIQikSEyVJ4kDU7iKekq/3BtPtZpnEPQlBHpo5ZBkNsx7kUbJmiNdQ7layYJBbQ5x3tp71ByJqTVsTgA2hLvWSQZvpjk5nQOqbmKjNbIVfiTUS32WUV8mqvJ3aQuIibA4KG0Jd6iODkktDvVDuAo9j78fEXJfFdBdMTBdWB4QtIV1fqwKQ7hBebILPFKgFbkuCkGqJGz5bIPymCv5eB7eWG8rcup5WB+F4l5DtNExJF97r0DDtCwsMtw7SUPG/1qilJmjrSecp2Yari2D4AHKs+gMR6WwITJJFtVH9ZctydIWeJzEhzfDX0YbNIaEpKrzZChURzZ+K2LLL/pPvMlxbDL+vEtYE4bkmYVp6VwCyN7FZoqJWxOebYFkHfOQXhu7n75pCCocrhnkN3yhX1eDTTbAqqOOd1zKQNxqnN4cT65czLriD533Hst3k8jKjWEkR57EOcqbx/Iivc/6mu7ik8v9o85bw16KLeZ8yLpK1jKdBfwuMQdyZUPk2MuLMVANdCimkMGCYgolYs76J/fFfMXUfITkjdptzbNKSZNM/wV8Dq/+FTLxaz/HQ49QJUs8aCrp9yIAvDzoqkcbVUDh5F8X9xLQE0TTA9rlMB2yLwKJWYYzvCFY0LVu2jKOPPnp/LUsKhxCd5JLElSjpxEG0x9lxZPMLyIf3IHUfJWZvMCPOxpp6E6ZkxgGdf39gfHk4zn+U+H/OguYN2K/chHX237vInN2EghtjsGZ+C/ulL0CwEfvtH2Odfjcm0g6xIIKAM0Hg2DGIh/WWlIU4vUjEj7z+daTmfZ3duMsws27roewyw05HapYigTrY+jJmxE711EllmLE6l9s4XDDhSvjwHiTcDFtexoy+AGvKl4hXvKmEkTMNqV+ObHsNM+o8wGDSixBfoaqe2rdBxIvEQhjLpQqmcKvOy5OJCTUqbZn0I4+7DDY8g+x4Cwm1qP3Rjut6c/kgewTwBgQbkJbNu+RipaCYNWsWL7744iGZ95tt8P+quv4e6Ahhut0boyfnjsTfXkt/LDMd2riRlbCDFbigwKmWK31M5+NcJzj20zglIlRF9IrQxqAqfZLIdKhyaXI6ZPRTCQUQjAurg7DKD6HEf2t3wmo3KW3X5rq4CBsTBFMwMX+XUeJspBeynQNTLu0JXsswLcMw1GPzQQeM82njXsiGV1uE8/IMk9LgYz8sbofLC+GRBg0A/12VcEKWoSYibAwp+ZblhAvy4L0OeLsNYraN07KYnmGYPkqzn2z2zzaL2sLHflgf1KwuV0K9NiFNiInBabrq1qsT5a2luzkHzXJoiLrX0gyruqiSYu5e+LzPFcEDtfqe2ogqli7NF8DgSbx/S0iVZsdnCfNblZy7IH/XaaWQwicVHstwXr5hfJpmN33kh0Kn5sOZtEIoP4GC+hV8ru11PnSP4TXnBCrJ4v+YzolsJ150FrmhKk6qfIhrN/8M25PN69lz2Ugec9jCubKBPBPSRuXWbdCwCoqnHuqvnUIKKRyBMBllWDNuwV75T0zFQiS9GOMr6Pv9aYXIxKvVRuevgVUPJsgmzasdSisGg003tb3l1PKj5g3qHMke2mOa432a07Qjola6/trnjIEiJ7zbDufmC4WuQ0c27RPRlCKZjmz0TS5x0NRLoJW3suYh7I/+DG3b9EmHBzP+s1hTvqyKm8MIJqMEx9kPEH/iAmTra8hHf8RM+0rixWT4gI2IvYvyyoy+ABb/TJvytr4Cm56DEWcrkRMLdSmXusNygisdqVyE/dbtapVzpmGdeAfWziQSaL3v6M9gr/oHsvV1JHs4Jl8trLrNE5f3HW4lgwJ1So758jFjL0aW34fUvI+UzsIUHYUpPwGpWASWEmDy8X3Yg0/p9BSbvLFKakVD4I4goVZVecWCnUST8WQjzZt1vonwb5M9AlM4GWlYgWx+HjPhqi6LpjMN4/QpiZVerN7nFA47jPWpD9xjJW5Gb14H+IxmcXgTDWc+S7OCfJYSKl5LSRafBRkJQil5n+7QfKCDjagtVES0jWxTCALdyCW3BaO9Gshd7h5YNX1LTFiRIEGSk8x0wOQ0XYc7t9fFbJsNQVVPhRNDs8+C0T604c3qn3opJkLI1vwqUIudKr92v+z5Los52cJHiTDrJR0aTFnkEmZkGFYEtKFtZgacmg3/qIf7a+G8PMFl6foL20LEhmuK4Ec7NHj92Sa4qMcFPcO+/sLERavUX2mWzna+JNYF4T8NMNQjnJenik5t5dPXS3ZDNOU4oSFqyHOqwqshBu1xVWntur4MZ+UKTzXqd89zCasCUOjW/T/azap3Yb5aD5f74cN2m2mZB1+dm0IKhxKjfIZvl8MLzcJzTZpxN8oLbqcXSmZgPDlMb1rL6GgFL3hnscEU8CbDWEMhNYPTyQ1VM6lxAVetu4PIpGzWpo3jacbyMSWcL+s4wbEDp8Swq5fiSBFNKaSQwl7CeLKwptyI7cvHbHoOiQYhc1Cfx38mraibsqk6YaO7CuP0MoQ20onQgZssIl0fcvogHkEaVmgeri+v86Xu9rk1QS0z6S8KXbAyqMdu5+bt+f0HCvslZGfbtm08+OCDfPTRR51haFOnTuXKK69k2LBh+2MWKewHiCRaxuwksbRTDrxxaP6PcRwUm5IE6pEVD2Cv+Ju2pQF487AmX4eZ/HlMWt/M8aGGKZ6CdcrPsd/4JvbiX2IGnaykjDGIcShhYsdhJzuLcbiwpt6E/eYPINSM/e7PceSNhbyxajeLd6mNcLjA4YV4CFnyS+y1j+hLuWOw5t7VGdrd1/KZ5vVI1WLsFX/DGn8FFB0NsbDmPbVs1oDwxlU9yC2TNxYyh0D7dmTrK5hJ12JN+SLxykWqWvLlI4FaeOencMovVJGSMwJTvRhxuJSwCjVB1iAlz8ItAIjDh0QS6iZfQtEkNmb0BUjDStj4DDL+Sl1/dlwJOocbKZ6ijXiZg/Z9o6Ww33FevsV5R7AqQ0QJgG1hvVVFeja2eSwldkZ51aI2EPJLREmrFX61XiVR5FJ73DDProRP1LZZF1QVVTRBmqQ5lIwa7gHHbgim9phQmwhIb4rp1a9IH1UfPksocOmyDPb0rspyWYYZGZBuCX5bVUzPNippMzHNsMIP73cYzs0T3mjTxrtnm1QV5Y/rsjgM5DoNx2QIb7fD3+p6Ek37iuqI8M86vQfIcxqmZUCpS3ixGR5rhA1B/aW7uxrm5dpcVajrPce5+xwopzFkO3U9gYaj10bUltkbri4yPNskNMTUWrmgFS4tVOK1MRHWnuHQ4PEp6cIyv2Zc/XkAB44HCiNG7N3FHGMMmzZt2s9Lk8KnAT6H4eICw4SEummlXxWGhS610uHNIat+OZ8NvsFq7zhessZRTzr3m2msGv0X7otdzrjWD7hi7Q/46+Tfk+vKYxvZ/JEZLKWMi9JjjKz9AAk0HNbHkimkkMLhDeNwY43/LJJeCKsfguYNSO6oPiNcTHqRKptW/VPb0Vf/G5lwFSUOQwEBWvD2JJpAy50C9Uj9R1B2XKflDlTxnrTPDYRosgxkWTC/RTg1u/85pPsb+9w6d/fdd/Ptb3+baDTKzpNyuVzceeed3HLLLfu0kIcLjqRmAd0WksgLSpBLOxNLmESw98EjlwCkbjn28vuQDU8pMQGQNQRrypcw46/otRrycISIYL/4BWTzC5A7Csdlr2JcPlUJxcOA6REG1/m5SAfxh2ZD80aVTGYNwXHqbzGlszqna4xBYiFk47PYH/4BQs0AWBOvwcz4er9b6mTF/UijtkDizdPQcX9Nzzc6vaoeSswDO4ZIDOPNw5pyEyaznPiLX0Cq38MUz0CadHpm7KWYcZdhfPnI5hex1z0G4TbIG4spnYVVOh1p3qhEVu5YpGoRxuHVzzg9SDSAxCPYT10CkXasU36JKZsFlgvsKLLhaaSjBjNsLiZ/gtr7UjgoOJLGuoEgbAs1EbVOVUegOtqVt5RElgOGJcilQb2QQXtC1Far20q/hpknMcyjBFNvTWORJMEU1PwqUFXXOF+CkOqFYBIRaqIavl0V0fDu3uBI2hGNkld2L+8pdKlEe7Cnd6XWlpDNP2s1+HuYB24sgX83GGyBk7KEP9bAw/VqXfzuYFU7HZ8Fx2YafBa81CxcvwG8BtZN10yofcW7bcITjUJMlMA5O9dwTCZ85Ic7tgkrEjFx7XFVhVlGFXUOA5cXwFfKzB7zoCK28GGH8EITtMTgzDw4O6/vZb9otc3qgK7HbCd8uUSzpzaHtN1viAfKPXBPlfC7Kt3X/j7GcHTGoc1QGDZs2F7//m/ZsmU/L83BxSd1rDuS4I8LzzQKLzVrrt9ID7gs9BiofgW0bSPgzORV99EspwSATAlxQ83/8V/VfyBHgiwvPJ2VBXPYljaKLeSSTZB5bQs5a9xUskfMPcTfMIVPMlJjyKcHUrcce8X90F6ZCAnv+7xE/DWw6l/q7kgrhtHnc3/ambzCCCbQ0MsHbG3vzhqKKZ3ZSWR1b5+7pVTV1v1FxFZl/DfKDcdnHYFE0wsvvMC5555LUVER3/jGN5g9ezYlJSXU1tayYMECfvOb31BfX88zzzzDOeecsz+X+5DgcB1MRLoRSsnbLqRSAsbRSS4dzEBtsWPIlpc0BLtqSdfilEzHHP0lzMizD0qL3f6GBJuIPzwH/LWYKV/CceKP9floEBC1APZiP7RX/1tVTZE2SCvS7TH0NEzZsYAgjWuRba91Wc+yh2Md+11M+XEDWz47jmx9Gdn6BtgJUs84ML58KDwKUzgZsvUkQ4KNyNr/IM3rkZbNSv6VH481/nKkeinxFz+vJNDIc2Dra+DwQO4otckZC6n/GBrXKcnm9GGKp8Go8zDeXMgegVQvxmSUY0acqftgLAQY5KM/Ya95GDPoRKyT/idhPxRk80tIqAFr8JxUPtNBxuE61g0EHXGhIapqkoao5uc0Rnd9n9tSafJQr2b69GaN6g8aosLaRMtHUknkNkoWTUyDzF6mG7Zt1gbUbpUkmDIdMC4Nhnp6z19qjGrr3PZwV7MZqOc/mVWV59SDkXSry5aX/KmPiDb5NcSUoKqNdP1a5DjVDlfcCxm2LmBzT7WSNidkKTm1LmgY64PNIeG3VaqkuqwA8p1K0l1aoNPJsISxH2qT4FdL4X+H7f1vj4jwTBMsaNWlHp9muLJQQ9J/WSE80ajvy3DA54s0AL4uCu+1w4d+JcEsAz8bCl8o2fNy1ERsHqxTRdeMDG3bc/fR6vdArfCrCsFn6f50UhZ8o9xicZtaEI9K1/3ryUabf9TqAeAp2XDPyJR97lDhkzDWfRIgouTwQ/XChqCOneVuSLMEWjYhTWshFmSTs5znXVNpNYmQXbE5rfU1vlB7P+c1P0uTbzArC+awoOBs1ppSyung2EyYVpjPmJLhuLypbZzC/kVqDPl0Qdp2YC//K9SvRDJKNF+ur/d2qH2OWBAwbCs7k+8PuoNRjvZdWpEBzdANNUPmEC1kSpRN/aMOtoRhStrAsx3XBvWY8jvl5pComvaJaJo7dy4rVqzg448/pqysbJfXKysrmTJlCkcddRSvv/76Pi3o4YBDNZh0qZO6q5R2eq5XJBRLidvByFvaGdK6DVn7MPaaR6GjUp+0nJhR52MdfYOSEUc47K2vYj93DRgHjs++iimYoPa0RCB4b+ojsWPYj52LNK/X4MpEI9vOMOmlmEnXYsZ/dq+JOBEbCTZD+w61q2WWQ1pRrydKnSqomg902UqPxXHMbRhvDvHnr0VqP8SMvVQHw9pliOXE+AqRaLuST5F2VU15cwED3jzM8d/X+s/GtZjCyZjy43Ufjod13+yoIv7MFWAM1gX/SQzaBtn2OtJRiVV+AqZgwl599xT2DkfKgVMwLrTF6by1JkilxlhXttHOyHaqRaPMrff5zoGrlpII23pStC4RQJ1EViJ/aUwv+UsAgbjN+qASTMn8pKwEwTSkF4LJFmFHWA8Y6ruRZR4roZJxQ7ZDWBkwfOSHj/3CxqAqtmoiui4EzQsqcSuxNi0Djsk0HJ8pVEUMa4PajAYaND4zc1er4JutNv+u15+dC/JgfchggLFpwkP18GSjqpouyVfL39dKVSHlNHBXpap48pywahqk70VLXkyEB+u0sQ1UxXRylvBAneEP1YI/rkHylxbAbYMM/rgScrlOVUu8365EYEVEFWP/Hms4JnPP2/4/9TZPNWrGVk1Uv8O3y+Ga4p7foT4qzFkhdMSVYBzsgd8Nhw/8BsvA8Zm6Pha02LzfoVZCrwW/GW44OTvVQHcocKSMdZ8WdMSFpe0wv1XH1qhok2hevA0TqEHadxAPt7HOKuFD1yi2WF0neYXROj5X908+X3c/Y0Ib2J45kUW5c3kj+zRCriyGWe0clwlTC4spLx6F5c0+hN80hU8KUmPIpw8SbsPe+KyWI0WDSO4IjKN3X71EOmDLS5rNC9R5B/HvEd+hLXtc7xOPR5RscmdonEn2cKoiFvfV6ctfKt59vuTOCNuwLqRK7ssKD0Fj+74QTTk5OVx11VXcc889fb7n5ptv5sEHH6SlpWVvZ3PYYH8OJj3JI/p4vCciqRuMxS7E0iGqg5doANn0HLLmYaTyna4XvHlYk67BTLoOk1F6SJbtQCH+4heQTc9jSmZgXfyMPplQ7PRmnwOQmveVYBEbM/1rGLFVSWQ5VPlTfpx6dfeBIBSRxHKI7hOJ9oPdfiYaQN77NXblO+DLw5p8Pdaw05HKd4m//EUwFtbxP4Tm9djxKORPgPd+pa0J0YBa9IadDo2rIFCPKZ4C46+CUBNm6FysvDFIPIrEw9BRg4m2Yy/6CdK6GTPlJqxJnwPLhexYiLRsxiqdiUkFeh5UHMoDJxEhLNrwFYwn7hO3jm6kUlusixjpDQYlPTrb6Vx6wrJzs9tAYSfa6NYFtUksyWdZqHpmnE9JrN7GX3/cZl0Atoa7CKYcZzJgfFeCKUlkrQ/SGXRtoWqZEV5oiwkvNBveaBHeae+pcOovfBackwdfLFZSbH1Qn89yqNpmZ4XXfTU2S9u17a/cAxExjPZq5tBfa3UbHZ+lLXqfLYByj0HQ7Xr0MuiwdV6/HjGwA55gXPhrLWwKCQ4DVxQa2mLwkx0a1g0aTP+jIV1WtPfabP5eBy82q4WuI64KtiFuaLd1O70yyeyxOfCNZpvrNkBrXDOXXJZuh18Ph8/udOD2xQ02C1o1xHO0F75WBjExZDpgSmK5lrXbfOCHDzu0kS/PCQ+PNeQdwmaYTytSJ4mHJ2IirA7A263CBx2qlsx1QonLxhVqRPzV0FFJcxSWOYfzsXMYHabr+Obk1oV8oe5+Lmp6Eo8dYWP2VN7MPZ23sk7B5XAwzjRzTLaDKUWl5BSN1dbbFFLYC6TGkE8nRAQaV2OvfQwaViK+PEgv7fPcW5rWweYXO4UFHxadyWtDv0jI2UfwUrhNL8inl2AKJvKEP5eVARjh0ZKVgaA2osfQ3x5kmJR+cI8z9oloSktL4ytf+Qp33nlnn++57bbbuPvuuwkEAns7m8MG/R1MRKSrQr47UdRf0qhXGA3Z6CSTTOdzB9MC1xdEbKheir32EWTjMxBJtIQZo0HZ46/AjDgL4+wjSfUIh3RUEX/wJIj6seb+BmvClXu0zwHY7/8O+4Pfg3FgzfkV1ugL9t8yieggJTZgNIupn+Sj1H2MvfQ3SPMGzLDTsY7/IcZyEH/ze8jGZ8GTjRl6qmYwVS0Gpxdc6RANqh0wcxAMPRXWPKQZYOXHY0pmYcZdjuXLwW6vRLa9AVE/xnIgdcuRzc+DNx9zyfN60Fe1BGlcjVV0dMJSmMLBwkAPnGxRa1DnzVYrWPLv7o93fn1nUilkD2yUTHcoKZLl0JP7fCfkJ+xjjv1EtosI1RFtotsSglC3Bcx3alj3aJ/Wd/eG9pgqmLZ1I5jyXElSaleCqTmmNrzuhJTXUoWUEyWXHm8Ulvt7zqfIBdMz4Oh009mOV+pONs0p0VITUVXP0nZhfquqqpI4JRu+Uw6NMUPABpeBOdlQ1M1K1xq1+XWl2tEGeZTQy3cZnAgL2uCFJlUzXVkAx2UZzs7T+RrgN5XC3dVqD/zdcLiwwPRrG7XGhD/XaOi319Kmu3/Va+A2qI3vvwcZLsrvUqdtC9l8Zo1uM5fR/aQtrhY7C91HHMBlhfCr4X3/hvrjwnmrhWWJn7Qyt+Y81UaVJFx0lKGgG0H0XJPwjc2CDRybocqxWZmGEjeM9un7tgRtXm9Ve9+TjbqMJ2fBXcN7t+QdKlRUVDB//nyqqqoIh8O7vG6M4fbbbz8ES7b/kDpJPPxRGRaWtAsL26AyrP+fy92QThQCtUh7FXawjg2SwzLnSDZaJUji/1F2rJWr6//JF+ruZ3JgJTHjYnXOMSzIncfSrGPJNBFmmFqmZXuYVDwYT+F4tfunkEI/kRpDPt2QaBDZ+iqy6TkINSM5I/rMGpZYmOZt75Bb+zYAHa5cXhz+FdbknZQ4r98JdkzVTQ4PLdkTuDc0gjiGqwpgVO8ahj6xJqgXKL87yJC1lxERe4N9IpqmTJlCOBxmxYoVOJ272npisRhHHXUUbrebjz76aF+Wc8BYunQpd9xxB++++y6RSISJEyfy9a9/nSuvvHKvp9l/osnuvaZ+F5huO1Zvj7vuD6eDzyTEjkPVYuzNzyObXugZMp01FGv85Zhxl35qGsPsZX/CXvQjSCvEcfVitZDZUc1E6oNgExHsBbci658EwEz6HNaMb2A8+/5jJbHQXpFMncv1wR+Q9Y9BegmO42/HFE5GIn7sl27Qpjg7rq1yYkPxNKzjf4C95NfQtAZ8+eArgKIpSjbFQpjpt2BN/yqEW7E3PKUkmCtd2/PiUezXvw6xAGbaVzDTvwa1HyK1y7AKxmMGn7LP6yOF/qO/Y93agPBKS8+mtv0Ft6UESffbzqRSpmNgTXADQcTW1rjtyTykbt/Ra/QHe1waPUiG7hARmqLC+pAGj8clobJyaYtIiavnuJ5sqVsbUBIjiTwnDPII77YpufJhR9drDgOzs+HMXMPcbCW8Bvr/fJkf/lIj/LteyT+HgZtKlPhojhscBk7JgjJP13QXt9k83giRuJKCg71KaG0NwQO10BzXrKe5OYbbylUJFBOI2cLclWpdm5wGZ+cZjs3UDKtiV+/LvjmkzXItMcFCp/Ncs65Pp4EvFBu+WtazOa8yLJyxSqgMq1Xyt8MN83KFN1rgpztgeUBJJrfR/egvowyn5+4675gIX9wgvNIMTYnv6jY636Ct+991RfDLbkRVyBZmfiS0xODodJ3/F4pgfLqhNEHYNUVtnmhU6+OMDPj8BiVdfzDYcGH+4fFbf+utt/K73/2OeLwrZT5ZVNH9cffXj0SkThKPHPjjqm5a2KpEfFiUXC9wgon5wV+LtO+gLRTkI2sQH7lG0Gq6Tvim+j/iyzX3clnDf8iw/YQtHx/nncQbufNYnX40xdLGcVYVU7J9jCwZgVUwQfMsU0hhN0iNISkASMsW7HX/gZoPEFc6ZA3uVQhiC/yzLYdTN/+B8uBWANblHscLw79Ku6ePvKdIB8QCvOo7lsVmMEUutdDtpjh3F0RtWB2E8/PguuKDxyvsE9H029/+lm9961vMmTOHO++8k+nTp3e+9v777/Pd736XN954g1//+td84xvf2C8L3B8sWLCAefPm4Xa7ufzyy8nOzuaJJ55gy5Yt/O///i/f+9739mq6A1M0JQI7ehBGcLiSRv2FBBuR7fORbW8g2xdolX0S7kzMiLOxxn8Wyo49LJRWBxMSjxD/98nQuhVr5jcxs25NBMCh4dh9ySnFVqvaR3/WJ9xZmDEXYo2+CAonD3h/2VXJ5NmrbSGNa4m/dTt0VGEmXIVj2n/p8xE/suweZMvLiB3TPKbSmZgJn4NFd2jLncuHyRyKlEyHba9DzVLIGYV12cuw8WkkUI9JL4GR52Al7Hzxt3+ErPw75I3FOufv0F6FVC/B5AzHGj5vwMufwt6jv2PdhqDwfLchwKC2Ipfpujm7PXZZPf92GrUi+Rw9CSWvtf/USP2FLRoeXhVRIqQm0rOhzWPUGjfCq6qWvnKdYiI0RNXyVpeYhjFq3RvngxJ3z/+LEVvDvdcFu5rjDDDYLUSAJxrgPw3drHMJ4ueSAsP5efRptxJRVY3a1nq+ZozOw6KL3NkRFv57q/BUIkx7RgZ8pQzCtpJNp3ZTNkVt4V91SlK5gYAocdQUgxUBeK1Fp//5Yvh6uaHQpa1tAIvbhC9u1O9zfJaSYwC5TsM4n67jfBcE4tog92GHkjZbQrA90qXwOjNXVUzDdmqOa44J564S1gZ1O909Ak7JsaiOqAKsOSo8UAdvtekypluqzHplksECVgV0O5S64clG4W+1SpRFE8TWVYVK9q0JaqNLqQuWTIHCbtv1ixtsXmuBYrfaNc/KhcsLu64ihmzhkXohLnBZoeHJRvhdlZDrhKfHm322d+4r/vKXv/ClL32J008/nS9/+ctcfPHFXHfddcybN48333yT++67jwsuuICbb76ZU045si8CpE4SjzzERVgXVFvd0g4tech26P9Zl4UqAPw1xNt3sCWWxoeOYax3lGEnjoPS7CAXNz7Bf1X/gen+DzFAwJnF0ry5vJE3j+2+kYyM13GsVc3RORmUlIyF/AmYtIJD+r1TODyRGkNSSELiUY392PA0dFQh2cN6FQ68KUP4kz2FGyp/z8mVD+GQGGFHGq8NuYEPis9JxOHsMnGCoQ7u9p5JyLg5LzvKtKyBtXE3JTJMbyk3zOpHPuX+wD4RTfF4nMsuu4wnn3wSYww+n4/i4mJqa2sJBoOICBdccAGPP/54r/XMBwKxWIxx48ZRUVHBu+++y9Spmu3S3t7Occcdx7p161i9ejWjR48e8LQ/jYOJhFuR6vegajFSsUibxbrvMp4czIgzMSPPxQw+udfg608T7I3PYr90Izh9OK5+F7w5SvhYrt3WYALIjjex3/kp0rKp68n0YszQU7GGnaZ5TXtYv/uLZEpOy178M2Tjc5A7Esfc3+7SriAi2B/fB/5qTMEkpPZDZNvrkDsS48oAO4bkjITlf9WMqPGXY7IGI8aBGX0RxpvTdYW8aT3xx88HO4Y5/W5M1lBkx0JMRul+tRSmsGf0d6yL2pqnlCSNDjY5tC+IJYil2oiSSzXRXTOfsh3aRDfEo+GLfZFLIkLQhtqIsDWsJz6CrpMil5IpBTsRTG0xJUO6N855LChzCR/7Vb30cTdr3Bifqnc+WwiFvZBLcRFsUWLLlv7bDw2qYnIa/X7PNgpf2iS0xlRl9IPB2rLmMnBGrhJCAKv8wmstGjrut1W5M9yjpMy/6jSI/KQs+M4gDboOxIWArfP7vxrhTzVK1ExOT4aZKwEmCTtlU0yJum1hzVdKc+hnp6bDfw/uPcQ7ZAsXrxHea9c8l18MgxOyDMVuwyq/KsaGuoXXWg3/qhNWB/UqX55TbYMXF4DGm8MrLcLTjRqkmdTsfCYfTstWVdoXN6p9MNMBXy9TNZIxBhHhX/XCHduUFBzr06ymu0Z02QRtER5p0PDy8/LUenjZWiHbAf8z1DDIc2j/H82cOZPGxkY2btyIZVlYlsWPfvQjfvjDHwKwcOFCTj/9dP79739zySWXHNJl3Vd8Go/rPkmoiQhL2oQ321R5ahkod6lSUew4BOuRjmo6OhpYTjHLnCNosjI6Pz86vIUv1vyJ62v/Sna8DYBWVwHv5J/BwtwzaPaUcFR8GzOsOibnZJBZelSCdOq7aSqFTxdSY0gKO0M6arDXPw6V7yDG0nbvboVOHeLie8wliJOpgeWct+m3DOrQsPDtmRN5bsQ3aEgb2uu0F8eLeNUxngwJ85WcRtxZZQzkiGFDSC+AfXew6VORvz+xT0RTEv/617/429/+xrJly2hrayMrK4upU6dy7bXXcs011+yP5ew3XnnlFebNm8f111/P/fff3+O1Rx55hMsvv5zvfve7/OxnPxvwtD/pg4nYcWjZiNSvQGo/7MzI2eVyeMEErKGnYobMhZIZeyRQPk0QEezHz0Nq3sdMuBJr9p3aILCbUPCen7eh4m3stf9BdizQcO0kXOmY8uMwg0/BDDoJkzV4l3nvL5Kpc5pVS4gv+jHEQ5iZ38Ix8pxd3mO37UBWPACWA0krgeX3aXjd+Mth+wIN7cwcDNteVUvp+Kuwxl+GyR29i4859sRnoG4ZZuQ5mJnfQra8jPHmqkouhYOGT9pYF7WF5pg2ttVHoT6mCpudf/w8pquRboiHPfrYI7bQHlMCozqihAio7a/MBaPTDDndppHMelobVHIriRynvvZSM/ynUXOEQImnC/PgCyWms7Gs+7TiqMIn3sevuJVQLu38LYTeySgrQThVhOGytcKqgNoUvztIlVNpFpydB17LJMgSqAipIiuUCNfOcBo2BFUZ5bbgx0Pgy6U6DrXEhJiAC+FPtYY/Vu+64CFbyR1DQvFm6XRmZ8OXSgwzM3q32MVF+PwG4YUmPcn88WAY6jXMytTsrLdbBb+tmUltMfh9lfBCs7YUJm1wszLhykJY1gH/rNfcsDiQZqmSabBHs7WOSjc8Uq9kWdRWEvClSVDqtgjbwnK/8JVNSpblJULT/zradJJ0AE832NTHVJ02Os2iISrkOwdmfTxQyMzM5JprruHee+8FwLIsfvCDH/CTn/yk8z0XXXQR1dXVLF68+FAt5n7BJ22s+7QiGFeF5YJWYU1AFZNFTs1vs4xmoxCowW6rZFtYWGYNYo1jEHGj+ZluiXJ6+5vcUvFrZre+3jlm1nvKeavgLBblnkrMmcms/8/eeYfLVZXf/7PPtNt7T25L76SRCiRAQhUIEgQEpfr9ISpYQQUVFBC7KCpKR6SD1CAESAIJCemF9HJzk9t7v1PP+/vjnduSm5CEVJj1PPNMO3POPmfO7Dl77bXWG9zMGEctgxOTcWWPxqQO22cV3wi+GIj0IRH0BhEbyj7G3vIyNOxA4vv0sOK+IEN5luGMpApLQoyveJ0zdj2Kx24naFx82PerLMq5DNvqOcYOYnhQTqbeRDMtsIHTYtoxqUP3mQu1J0ICn7TBzGS4McscctXlA8Uh1UtfsmQJt99+O8uWLQN09uvee+9l4sSJh7Vxh4L58+cDcNZZZ+31XsdrCxYsOJpNOu4gItBeCw3bkfptSM06qF6H1KzvPVsqqRCTMxmTPVFJjriso9/oEwTGGKypvyD00gVadW/UDZpBhCBifyrxY4wFuafhyD0NCfqQssUaMlf8HrRVIzvfRXa+q8smFqhFMWM0pI+EuL4YK1x98DCQTABkjFYFUtUaKH4PKThrL2LRxGYhiQXQtAtjBxCHGwItkD4CatZ3VaPLmQw758KWF5FhV/TaPjPkUqRqFVK6GDlZB5tyQHlnEXzR0aEqaghCQyh8H4T6oCpuekOspQORnHBodsoBDPRDIrSF1KJV5ldFlF90MBPnUBtWvqdn2GLAFnaE7XFN3SJtMlyqCHq4ApZ1y14aGFYvXZm+tzUuJErW7EkudSiTLKOWuAO5eOiw14XCge226L5kueHt4XDZZljUBPeVwE/6qnTtw0aYkSRYxjAuTmgOGTJtrfy22weZIhRG6XEt8WvFt2szBY+lldcaghDAcEsOnJloeKRSeK9Btwtqm4y29PsYGwdT4g3nJO/bItixHz/eqSST24K/9YNYhyHKUpLJZ0vnOZDkUEXYkBjwhcm9YEBJwuXNap0DPRZBVK33rWw4KwkWN3dt89xk+HcV1ISUZHy5Bi5KFdpsJRPHxsHb9arwykUfX95NBBHrUMKzOdyuozGzeDBISkrqfBwbG0ttbW2P9wcPHsy77757lFsVQQS9I9phmJIAk+Jhazt81CQsbtYBVbwDctwePAn5WAn5FPqaKGyrpLV5Eev8Saxy5lNtJfJmwpm8OexM+gSrubzuJW7ZfR/ZvlK+XPowXy59mJKYASxIO49/JU8ntslmSs0STnK8Rd/kDKyssUo6xWZGSKcIIohAxzh9JmOlDsHe+hrsel/HcUn9MA43EyjjLQbQQBTJxsuy7FlsTpnC+TvuZ2DDUk7f/QTDaxbwRv/vURI/rHO9ToTTTREvM4yPnIMY2ziHuPZqSBkCCfmf2v84jKrPFzRqPua0xCN8HA5W0bRu3TomTpyI19tz8BcTE8PSpUsZNmzYPj55dHDppZfy4osvsnz58h6ZUR1IT0/HGENVVdVBr/tEYq0l6NNw7tZypKUcGouQhh1KLjXsAF9j7x90xWDSRmg2UM4kJZdiD7KOYgSE3roe2f6mVmw79xHN7LKch2wtFLGh+hOk5EO9Va7qygHTBcLf3TCVdacMwiQPgKQBWiHOcqhizVsP9VuR+q1q0WsogmAbRCVj+kzBDL4U447rse3QxueQVX+HqGQcU3+ByRzTs212EKnbrIHmYiNlS8DXhJnyM0x0MvYHt4PlgrzTYctL0FYDSf2wvvQU1h7nlu1vwX7yZCU8p/8O014DDg/W8Cu/8LbMo4njra8LieCzdZa6NVymvtUO34egJfz6PvgkQMmL9HBwbLpLbweahdNBLrXZUB0QqgPqdRdUcZPgUPVMtrtn5bn6oGY1dbfHuQx4LOHDRniuRomwjtcvSoUbMg2nJPQkvOxu5FL3P2zLaKi1wxwYsbQ/SHgbwW7b8NnC7E2wpFmP1619IcGhFe3GxalN7IUaJfY+aRGaQkoYDYxWQu2hCh3k/W84nBSnxHJ7SEkfg9rtnMYQFKEiTNg5UaLLfRApl38sFX69WzAGHhlgGBGrqqyOSm8VfrUjxjtgSoKut9gr/LlMqAyTYQGBvm49polO2N6uFr4JcfDPAWrze7Nej8OQaHBYhr+XqarLACfHax5UXVBtmF4bfl6s5+moGBgUA3fnd6maljbbrG1VW920pOMrz3DIkCFMmDCBJ598EtDCL06nk+XLl3cu86UvfYnly5dTUVGxr9WcEDje+roIDh9qAmqjndcoFHvVmpvj0v5abbo66Wq3VFDa2sJKstjg6EvA6By8Q2wm+tdzfeUjXFH2EC7pqtKwLW4kC9LO45OkKeRIIxP9mxjlaCA5pS8mcywmbbgquyOk0+cekT4kgk+DiED1OuzNL0LNBiQ2HYnJ5C9MZAl9GUpN94UZXjufc4r+TmywAcGwNOsi5uVdi9+hqiUBHmMMpSQwljLO9y3TMWFcDiZ1+AEVlCry6jXRT3NNj2IvhxsHrWi677778Hq93H777XznO9/BGMP999/Pvffey3333dd5YXKs0NioBEpiYu8UXUJCAiUlJfv8/PDhw/f53rGsriKhgJaN9zaArx7xNYK3Uat+tdeqPam1Qkml1sqeId29wRhVwCT1g7RhmPRRmPSRkNTvCxfifSRgTfopoR3/UzVS2VJM1liwQ4glh3ThYYwFGaMwGaNg7LcQfwtS+hFSsQIqVyG16yHYps8rVuydz+LwqK1uP5Di92Hl37Cm/wYr/8yufekzmdCWl6C5FLvkIxx7EE0YCxIKwBWr4eeWGyQEdZsxedMwGWOQui2qZhpwod63lCILfoyc8xDGcnStyhWLyZ6A7P4Atr0OuacCYUtghGg64RDqRl50qGZ63FDrkU+6LFM9Htv6OPipW1IY9I8zyakZPUnhx0nOngTQgcBva6ZQuw3NQc1zqg1qe1zhCnjpLujrMWF7hunc510+2NKuNr0OxFpKprxRD/O78fy5HlUvXZ3RFbbdgWD4+HWv6tdhKTsc5FJ3GKM5TE4RAuHvx2MZnh4sfGkDbGiDf1fC/2UJG9sM2S4hx2MYHy+826A5S14ftAS0+tyIGD3udUFV/pwU5q+jHYaACH5RFVGSQ3AaQ9/eC3N+Kp6qUpIJ4N58wwWphlUt+jwx3LV0kHkp3a548qMMw2KgNiBMjFcyrTao5822cA2H0xLgqgwo8RsKo8BltN2xDq1CeEEqvFqnKq0t7ZpLlebU7yvbDZPjYX6TKrsKPPBaLVydqesO826diqbjCVOnTuXDDz/sfH7RRRdx9913c+ONN3LBBRewcOFC3nrrLS655JJj2MoIItg/0lyG81LgzCQtLLCgUfikVXPf0l2Q4TI4YtJwxKSRGwqQ21bFWc1rWe9zstLKpcJK5iPPSD7K+zM/yr2Hc1s+4Kayv3By3fsMaFnHgJZ12FisTzyZhWnn8krCuQxr2M24qncY5nyBqORCTNY4VTrF5URIpwgi+ILCGAMZo7CS+iNF/4Mdb2FqNjAlKZUlzr74cODpSIM0hvVpp7MjcRwzix9kdPVcJla8wpC6RczpdwtbkydigJls53HGsIpsJnhySA81QnMJ0l4HyYN0PN9tfLUn8j3wSTs8XS3ckgOug7xGPuB9P1hFU15eHgUFBXzwwQc9Xj/11FPZtWsXxcXFh7WBB4uzzjqLuXPnsnXrVgYMGLDX+/3796ekpASfr/dB96cRTZs3b/70qnNBHzRs10F30IuEvOHHPlVqdD736vsdj0O+bq+3Id4G8DUpmRRo3ef29gmHG2Kz1eqWWKikUlI/TFJ/fR6u9hXBkUFo/m3IJ09gMsdgZr2MQcDh7hEI91kgIX+nqkkwmKZitT/Wb0HqtiL1W6ClvOeHjIH4XFU8JfWHpH7gjtfOaeMzSEMRGIM17bdYg7+s6xbBXnw3smMOpAzBcdq9mLjsrnaIQLBdKy1UrkaqV0PjLr3AGnAB0loFJR8g9VsxKUMwY76F/da1EPRijbkJK1zNrvO4bXoemX8bODyYwbMhqQBrwKxIxZejiAOdoSvxCStbeiGQ5MDJoQOFQW1VcWGSJ86h1reOx3EOzdI5VPIlYIsSXGGiqy2kuU61QVVLuSyIMhpKneU2ZLl6ZjjVBtQet9OnBFlHmw16jF6t68plMmiw9jcyDWcl9wxR35d6qSOw+2gFrodE8Nvahp1eYeZ6JVTOT4YLUw3RlgZZuwy8XKvqgSKvBmRXBdRC6DLwSKWSL1vHgydcFMQWrSRno7lY8Z+ShbUvvFYr3LBNEIFbcgx35Kk6arFm+jIxXpVRi5qElhCMjoXMbmResdfm5h1KDI2IgSerVbnkNHB9FvwoB95rNOF1Ca/VqXj0/BSoCaqi67adaqmLCivSfppraArpRdzHzcJN2/W7zPdo8PkduRr2vctn8069kmGXph9fkzvz58/nN7/5DQ8++CD5+fm0tLQwbdo0Vq1a1Rl4XlBQwLx588jP7z2w9ERBRI3wxYGI5sktbhY+aoLKgP6H9HHrf0vncoE2aK2krLmeVcFk1jn64jcaGWAQzgmu56bqhxhRM4++LZs6PxcwLp7Ov4X/ZX+VnGAtk71rGe3fSn+XFyupHyZrvKrO4/pESKfPESJ9SAQHC6nfhr35BXyV6/hZ3FVUebIppKHXZUdVz+WC7X/AIUpEfdjnq7ya9//YRSLvMIBW3AyhmkvZoB/wNyuPEJOJSRvWIxdqT7SGoMink53nphyZPumgR7yVlZVcfvnle70+adKkzsymY4kOJVOHsmlPdHQI+8L69ev3+d6nfbYTjUWEnj3j05c7FLjjtdKbJwE8SVrVzJOkA//YbIjLwsRmQ2yW2qEif2bHDNaEHxLa/AJSuQpT9DYUngWhAHxGoknEVtKyYxjqcGNZTkgdgkkd0nNZO6hkZbANnDHgjt9neLsM/zr2wp8jm57HXnAbJiZVM7mMwfSZipR9DC3lSOlHmMFdM9nGGAQDqcOgchVYHrXQNeyAlkq17eVMhvpt0F4Dlgtr0k+wF/4Ce81DmIIZmJRBXetLH41kjtHcsO1vYE7+AURI0eMSPlttQp+GDhVOjxtKnrgM4Syd8L3p9rjbc7c5fEHJdlhR4w8TSz5byYDWkNAYUgVMm63bdoctd6kuQ6YLUl1dZE9LSMmVIm/P7CURocgH7zf0zF5Kc8HVGXBdpqEgau/spcA+1EvOw7jvBwqHMURZWlWwIMrwz/7C5ZvVPpYfJZwUa1jWolXdxscJbzcYoi2hj0eVXI0BGB+n5F9NEH5fArfn6botY4h36LH2CbhsIeogZ9PebxBu3K4k09cz4Ed9hOXNsKRZWNuqFri1rYah0TZtts7WJe/R9TqMoa9bs7YGRcOmsYatXlUfdWRCJTuVcGwK6TnYZGv7Ex3QGDJcnCqsblUb5/sNMDVBGBOnRFyayzA7VfhvrebGuC0l5W7OgfjwwNYr+t0fTxUbp0+fzvTp0zufx8XFsWTJEl599VW2b99Ofn4+F1xwAbGxsceukRFEcJAwxjAgGgZEG85PFpa1wDv1WvRgZIz+PgEN1U0qJCepkBxvAzNbtvN6ayLrrWwEw3ZnFkuzv8zS7C+T1lbMlRt/QqK/GpcEGNe8nC3Z51HlTODZuJnM4VRmB5ZxXs2HULEcicnAGn4V9D3l2B6MCCKI4JjAtm3qiGFn2kyKg/3wtHtp9IfADYiQ5Ksgr2kd+U3ryGteS4q3jI3RQ1kYP5VFCVOZn3gGZWT3WKefsHJJbB1jGgPNu5BQO2SdjIlK7lxWRK87moKaIem1tcru1IRPL4BzKDjoEW8gECAuLm6v1+Pi4ggEDmDEcYQxcOBAALZu3bpXRlN9fT01NTVMmTLlyDbCFQsx6eCIAmeUKoecUeCM7nwNZzQ4Pfq+o+N59/eiwZOA8SQpoeRJ1OeHSQ0TwZGHiUnHGv1N7GV/wP74Pqy8MzAOJ2KH9itn3BdEBOxAt2ymTw/9NpYTolOAlH2vs/xjpPh9pK0aEgugYCbsnEvove/jmP06Ji5HZ+Li+yBVa7BLP1ICqrvCyBhMTDoSnarh4DXrVYUXaEXiMjEhHyQWAoLsfBsz6gbMrvnI7vnYi+/BOu/xroF0VBLkTgvbRBuQNf+CrHGQdmzz3yLYG1lumJnUk0BysDepdKSrWuwPQRECtmbwdJBLgTCZ47eF5pBmDDUF9b/ZFSaX4ixIchnSnEoQdWQGtYeE3X4lmLpb4wLhnKGVLfBeY5eqyTJ6jK5MN3wppaeFr7dcJDg86iURJYnaQmHrYvh1l1HCJM7x6d+LMQYPgg84I8nwoz7Cb0vVCpefKxR5lajJjzKkO3VfitrVDljqU1n2OclKrvylHG7Ikk5FkcsyxIp0Zm05jVroDgSv1SrJFLBVRfTlVPh9melUoXlt3b8yv2ZktdrwpRTBbfXsK3f5NLS7pRHWtsGpARgb17MNmW4lHhuD4EKPZ31A6BdtaGyHk+P0/PCGbZb/KIcH+gsuA37bcGGyfp8v1MDqFj3nZiTq5x1GVWM+W5VyxzNcLhezZ88+1s2IIILDgniHThRUB7RKZW9Z/AawLQ8f++JZb7QITgH1XMBmALJbNjNr229J9FcDsDLjHN7JvxEPIdJoo55o+tLMKFeLXu9LENKG66RcBBFE8IWAHQpR3VhJcX0VRY2NrG/2URpy02i7sMmlX2AnVzQ+z+DmNeQ3rSU60MDK2DHMi5/Kwvxv8FH8ZGpdPR0dBiGLFvKkntxQDf2DJWD70HFhFESnYqIzICoJ251Ia3iyrDHUpSRPdMLoOBgSrdEA8UfoGuRzx1pMmzaNX//617zzzjt7Ka/eeeedzmWOJExCLs7r1h3RbURwYsCM+SZ88gQ07kQ2PYcZfqWSRQdBNO1NMKGMteX6TCoHqVmPPf9WzXXqDodHySlfA/bcb2Nd+BzGk4DJGo807dZ8pZ1zMcOu6LajFoiNSRmshJXlhJAfaa/FSioEqYU+k6FihVaia6/BmnIHoRcXI5Urkd3zMXmn67rcCRiHGxlwEVQsheYS9i7EHsHxgFiHofAYD5BFhBBdOVCBjpu9N4HTHhKabc0Gag//4TrDxFKKE5yW6cx3SnV2kUuNQWFru7DbDzWBnusr9sPaVvioSYmGDgyNga+lGy5LV6tdd/RWOe6zqpdaw4Om+nClvebQ3pXpusMA8U4h3alkSoard+KpO9n0vT7wToPmnbxcC9dmCEtbDJluYXw8vFVvMEbIdastxWfDsGg9lrVBuGm78MKQru10z2tqCkKSU/ZLfokID5TDr3arkumcZLW8zakHEFKchoIoIdUJw2KgJWR4rkZoCcB7DTAhXsgOfxc+W4PAk52GM5JUlfRUlfD9Pj1n9TJdsF60Mt7qVt2vTe3w1XTI8whey3BxivBwpZJNZT74by2MitV1uB2GH+QIMRb8s0Kzrm4vhpeGCG7TEWovBxxMH0EEEXw21AWEp6qED5ro7P/2hACBphJeq3ew3uoDBsZTyllsx2UHOLX0P5xa8jQWNs2uFN7o/322Jmvl7Sbc7CSJiZRwXWgJafXrICYdM/QKTN7phzTRGEEEEZwYCIWCVDZUUFxfzY7GRta3BCgPuWkWF4iDgd4yZrauZkjLWgqa10IowJL4SbyccAqLMm7l47iJtIdDvzvgJERfmsiVevJC1fQJVOIRn469HFEQnYKJSQdPIgF3Ik1E0xQuYINXLcKpLi1a0j/akOvWCcGjcd1x0BlNlmUxYMCAvfKPtm3bxvbt2zn77LP33ogxvPnmm5+tpQeIYDDI4MGDKS0tZcmSJYwePRqA5uZmJk+ezObNm1m/fj2DBg3a/4p6QcSHG8GhwF73GPaCn0B0Ktbl8zHu2APKahKxlVzqTjAZBzhcnymwXQJtyNLfY6/+p4Z2O6Mx/b+ESSpUZVPF8rD80gXOKKxR12NN/ilSuRp79YNI3WboMwXH0Csw6SN0nXZQiSVfI3zyOHbxPLBDGgaePQGad2Myx2KXLILqdZA3Dcfwq7CX34+99mFMYiHWxf9Vm10ogL3xWfUZZ0/AYLCy964gGcGRw7Hu60QEGyVKbNRO1vG8I1Q81O35nrBFaA9XqeseMm7QmevuaqFYhxJLyU7NyzHG4LNVnVTu11yltm4EUl1AKPbBmlZY3tKljgLN4bkoFS5NM4yJ7UkYHW71kogSS2V+JT9ae6lV4bVV1WShs0rRDlVq+cT0aDeoVTHfAwOiew9O71BIbWwTzvxEj+mNWTAmzlDggVMSDa/WCkVeVXuFwuoxh9G2vVSn+/nTXMNtfXsel4YwKeYykLgP6XZ1QPj+DuF/9fr83GS1uIWAaMswMxlOihGWtejnJ8Wramp+g83Ltfrd9/UYvp2tBNcOr7C6Rb/3qQnwh1KoCgiZLsP1WZDu0iyiT9qE35SooskC6kNKnBVEQWGUbqclCNdt0+BzBzpT+PIQaLUN8Q4lvbZ74YEy4ckqVc79vZ+2fZdPLYaDoiHJaUjtTVpxlHHdddcd0HLGGB555JEj3Joji2Pd10VwdLGlXXisUtjUBv2jVPm4JyTQTmPNVp7351JuJWOJzTlmG+MoJ71tJxdt+y05rVsBWJ86jTmFN9Pu0nOnhmgqied0dvC1tveIayuFzDFYw67EJJ7YeWYR9I5IH/LFRjAUpLy+nOL6GnY0NvFJS5Aq20mzuHBIiKHtmxjVupohLWvIa/qEJiuGRfFTWRQ/hYUJp7Am9iRCpud4MJoAuTSSZ9eRF6oiK1ilGU3GoYqlqBRMdCriTsLrTqRJ3DSGq/46UJVmtlsn+vKjDHkefX4sLPqHRDQd9EaMOaoV2+bNm8fZZ5+Nx+PhiiuuICEhgZdffpmioiLuvvtubr/99kNab6QzOXEhItBUjNRtgpYKaKuEkF+VN65YSMjXcOzUoYd9tklCAULPnAYNRZjx38Uad7O+4YzqlTASsTXLSbr9Zg4HwSSCFL2F/eHPwyohMP2/hHXqrzrDvUUEWflX7MX3dh0fdzzWOf/C5E7DXnQnUrsZYtKw4nIwo67HxOUgdkjD7I2FbHga2TUPaavGpI/szF8ygy9FmnYhK/4K7lis038PwXZCL5wLvkasab/G6v8lJBRAtr+BtFZomeCk/srWR6ohHjUcaF/XQQgJ6vsWlBDqeCy9vbfH+x0kUvf7A/lT6iA+fLb+uQalyx4XsLtZ+br9sVpGS1snOPSPON4BTmM6LRQdt/pu3G67LWxv15DvT9o0j6k7BkfDRamGWSkwqhdyqUNtdTiyl0SEuiDs9kGpv8ueFxRt4y4/lPiU1NjlU7XMnvAY6Bellq+xcTAmFppt07kup4GB0Up87HlRIqKB6X8pE365W0man+fqrNj0RN2vN+thbYuQ5YYdXiXyMpyqOlrdqhaxX+UbvpnVte+hcDi4EA587zbL1hpScub3pUJTUEPZL07pIAWhf5Th0jQNFK8O6AAy1qEWuKAI7zeoemlDm0rHR8UaLkvXgPBKP4yIhUHRhtqA8NcyzY1yhNfbFIIKv1Aarh0yKV6/S9DA8xCQ54HTEg1v1wu/L1VyLdEBkxLglmytJDgkxvBxk82aVvhbuX4/fT0aNl4WUDVZYZTmgA2NPjqzjPvDp13ndQSCH+1ruyOByHXdFwO2CAsa4Zlq7WsGRWtf1x0C0LSbkroynjejaLGiiSbApaynQOqYVP4yp+96DKcEaHPGM6fwZjakTe/8fCnxtOLmAnsDlzS8gcvpxvQ/X2+RnMnPLSJ9yBcLgWCA0roydjbUsqOxifWtNtW2kxZx4rZ9jGjbwKi2NQxuXk3f5g3sdvfpJJUWxZ/C1uiBe60zifYwsVRLbrCKtGCtFpAKT/gTnYaJSsF2J9LsTKRZnJ2q9ShLJ7f6R+m1TJ5H1UrJzqOf7dkbDto6V1RUdCTacVhx+umns3DhQn7xi1/w/PPP4/f7GT58OL/61a+48sorj3XzIjgKEBGo3YjsnKukR+Uq8NV/+gc9yZi86Zghl2IKzz0spJNxuLAm/RT7f99AVv8TGfwVrQQY9CHdMpbEDql66TASTCICDduQkoXI+qc0OwkgPhdr2r1YBTN7ttUYzLibAYO9+B4ItIFxYs+7FcesFzAZY8DfCoEWJOSDtY8i+TOgtQLx1mHShkPKELXHNe3S8G8GQWwWJioJcUZp3pi/CarXYTLHYI24GnvFX5C1jyD9zg8H5cSFtett4R2xVSIawXGFNrunlexwQMKh2B2qJXsP9VLHe0FR4shBT8uX24DboeqYWEf4ZnXdt9pKJO326X1NQDotbyKa8bPDq6TN9nYlBboTX5ZRBco5yUouDY7Z+4+8N2scHLp6qT0k7PTBTm+XPa8hKKxoUWXVqtaeqqvuiA4HqYdQZZFPYGO73p6sVuLpwhTh2kxVMjUEYWObElZj46SHwsYYg8cSbsyCZ2tgSzt80KQWto+btQpdtgvqo/TzbkuPebQDJsRrFtN2H/y8WKs+3ZELQ2IMjnA4eFM4mNJv26xrM8ypE16u1Wp3oKTexHi9sLIMzEgynJbQdTHVsVxS+MqmPkxeJTkNV2XAPyqEta3C6Fihyq+fyQnbZlJdhu/2gWerYXO7sKVdvzyngVMT1FoZY8EOnxJDM5M1q2prO6S5hDOT4MUaPV9abD0eaxLhwiglAqsD2rV9Oxt+uFPPv5WtWvEqKHpsBkcLMY5j38/t6zqvsbGRlStXcs899zBmzBh++9vfHuWWRRDBwaM9JDxfo2rIKANDo/W32B0SaENqN7K21eYN13hCxkE6LVzGegq9Rcza9lvymj8BYGvSBF7v/31a3FrNSYDtJOPC5mr/QmY2vYdJGYLVTfUdQQQRnJjwBfyU1JWzs6GGbY3NbGwTam0nreIgKhRidPtaZrSsYWDzGrJbtrAheigLE6by74wfsnDAVCrcPYO7ESHDtJInjeTaNeQFK0kIhUvlOlxauCluACYqiYA7iUZHAs22Rautk3lxoqrqyQlQGFYr9XWrUvt4xEErmr7IiLDWxz+k+hPsTc8iW/4Lzbt7vmm5IGUQJq6vVuVzanU0fI1IYxHUboJAtxJRcX2xJvwAM+LqzxzCLiLYL1+IlC/D5J2BOfcRZasB7Tr2+BlaTrCcB00wqXJrF1K6SMml0kXQWtm1gCsGa9QNmPHf1coq+2vv/B8h658Cf4sGdMf1wZrwA+zSxdChYCpfAs2lyrhb4RFbzkQN/q5YDp5ETO6pmCGXY1pKkdrNSPUapKUcK2ci1phvIv5mQs/NhEArjpkPQJ9TkPKlWq0vsQDTdyq4YiNB+EcRB9rXtYWVQIhgh0/jDtVShzLJFhCjKqYej7st090KZ4ctbgcSIG4ZJR2iTFelulgHRBnBJ4bmEJ23xnB2UYdlzBahNqiESLFPbXJFXg0G33PL/aLgtESYkWiYnqS5PnsiJNJJhu1JTHUEpB+seqkioG2q9Os664PCsmZY3gqrWvQYdiDVCdMSYVycYVSskjLZ7p7qIL8tlPphfRt82Ci8Wa+POzArBW7tC/VBgzd8UTMiFgZG92y3KoWEizeqnexX+VphbUAU5EfB63WwukVIcaq1L88Do2PhhWrY4FUCz2XpZ/tH6/GNMvr9lPqVUOt+DPtFwYykrufJTs2+yvX0bNfyZqEpKHgs8Iphp1dJxAlxMCHB4rVa4eNmwW3BiGjNYpqZvPd3UuYTSvzgMkKaC8p9SuYFwnbMFJfaIxc3w9v1QmtIM5t2+eF7O5Qsi7Z0hvG/Q8HG8EmrqtFGx8L/bVOSKcsFD/RTpdXIWL1oPNZqpgNBZWUlI0eO5Be/+AXf+ta3DvrzTz31FB9++CErVqxg3bp1+P1+HnvsMa655pq9lr3zzju56667el2Px+PB6/X2+t6BInJd9/lGuV94vFL7zb5u/e12R4eKKVS7kfftPBa7tXLvIGqYJRuZXPUaZ+38J27bi8+K5p2CG1mVcW4nUxXCsIVUUmjj6uY5TAhuw+SfiTV4tlaHjuCIINKHRHCk0O73sTtMLG1tamVjm1BvO2gXB3HBJsa0rWVE62oGNq8lqW03K+PGsih+KgsTprI4bjLNzp7ngENsckwzudJAnl1D30AF0XYbYMDh1on1mHRwJ9HuTqLRiqPJ1ngDJ6q+7+PW3M98jyHXo4V4jqdKtftDZOQWwQkPCbQjG5/BXvMvqN3Q9YYjCtP3VEzBDEzOJEgdhnF69r0eOwgVK7C3vYZs+A+0lGC//z1Y8xCOGX/RrKFDhDEG6/Q/EHpuBrLrfdj2OmbQrHD+UjfCyXIcdMi3iEDdJmTba9hbX4OG7T0XcLi1alze6ZhhV2Kie69At1d7p92H3VqJFL0DviYlERb8BIJtEPCqwijk68qQSh8ILWVQvhSq10L6SRCXBZ5k2PU+0lqJ2EHEOKFhB2IsZPhVGHc81uBLsT95HHvDM1h9TwV3HB1mK+NJPOBjEcHRRautygzZi5o5NBhU9dNhLXNZqkzquHkscCKdtruQmM4spsZwTlFzCNpsbY+I0GZrEHV1QMmkcr/ansr9arPr2G4HnOEZ76kJMCXBMDWBzgDp7uiwxfWWE9WxH4dScW9P9VJQVLm0oBGWtvQkYE6Og9lppjMU+9O25ba0ukhhFHwpxXBfgbCqFf5cKvynGl6pg7kN8Ot8YWI8lPgN61qhKSSM7WYLdBrDtES4OFX4b60SS9dkCNu8hvwozXpqDKrax22U3CsPwNWZ8ESVkmLFPv1OtrYr8dSBDvIs3QWnJSgxUx/U7ws07+jCVCHJabClKzy8KWizrBk2tGuAt2X03PTaUOEHMcLMJFjdaijyCokOmLkPrj3HY0hzCdUBQ1Ag0alneIdVszmo92clwcY2Xd/8RpidCldnwJNVqlAq9sK7DWrTMcYwPEbtZjfnCNdu1WyttW0wLk6/u7YToPocQGZmJhdccAEPPPDAIRFNd9xxB8XFxaSlpZGdnU1xcfGnfubqq6+moKCgx2tOZ+QSNoJ9Y3WL8ESVZuoNitaJiO5QFdMGfE1l/Nc9ga1urSw3lWIu8C3nou1/YEDjcgB2Jozitf4/pCGqS53gx2IzaRSGqrih6WUGxzixRn0bciYdF5aVzzMifUgEhwutPi+76sooaqhjS1MrW9qhIUwsJQdaGNu2ihEtq+nfvA63v54lcZN4J+EUfl7wLVbEjiPQMckehkeC5JpGJZZCVeQEq3Da/nBwtwei4jHRhdieJJpdSTSaGFrCxWmiDSRaMDEGBsUoqZTrgSTH8WGDOxREfmERnLCQ9jpk7UMaat1eoy9abky/czBDLsPkz8C4og94fcZyQs5EHDkTkSk/Q9Y9jr3k11C7gdDzZ2NNvgNz8vcO2cZmUgZhnfx97CX3IR/8BDJGqs0MAcyhkUtbX8Xe9npPcslyYjLHYPpMxfQ9BbLGH1I+gLGcWGf/C/vVS5GKZRBogqBDs5tCfp3Rc0aHK8z5oGo1TPwJbH8dGotU0ZQ9HuOt0xU6PJiscUoyVa1GmoqR0sWYwrMwQy6FTx5HyhYjrdXK8IOqqSI4brGnFq+DYOlQ8TiMqlYcJkwgiXSxOnra98x06sxy0tmc9hA0hXOX/DZ4BXxhEikoQktIaA6pIqQpXL61Nqh2vrog1AaUaCBMXu35C/OE84jGxMHYWMOYOBgZs28Jsh1WLXUEk+95LDr281CCvSvD6qWKsHqpwi/Ma4T5jVDTLTNqUryqaS5J1ZDHzwJjDGPj4MnBhh/nCjduEz5sgpuL4Kp0+HFfYUu7odirx39CvHTum9vAz3LhzTpY0gwXp6plbUkTTEsUdvvUZhdrKeETE1b43NIHHqnQnCx/mCTssNiluCDLCaluJek61FcGXebMJBgerQRjbQDqAKex2dqux6nUr4PJVJehMEpwGT2eLqNV5xqDMCleWNeq6/16Rvgk3APNQem03TmNKo22eqHcJ7SE1KLXFBIy3BZXpgu/K9WywS224c48mNsgbPcqEfuXMvhZnhBtGYbGqMpuQrxhRIywvk1JqQnxut22EODaqznHJeLj49m5c+chffbhhx9m4MCB5Ofnc9999/GTn/zkUz9zzTXXMH369EPaXgRfLARFeKtOeKlWCeER0fqf1AFVMe1CajdS5w/xXPQZ1Jg4nIS4QDZzec2znFv0ANGhFoLGxXt51/Nx9sU97PttONlGCqN82/hG61vkZA/BGnYFJjbzqO/vFxGRPiSCQ0Wzt43iunKKGuvZ3NjKNq+hwXbgF0O6v56xrasY3qrEkjdkszDhFJ6NP4OFWT9nfczeVtg4fOTRSJ5dT26oioxgNVZHcLfDo/lKMWn43Uk0OZNoxEN7SIdQ8QbSXHBKAvSLUmKprweieinIcqIiQjRFcMJBGoqwVz6AbHgKguGp8IR8rDE3YYZ99bAoYIwzCjPmRszQy7Df/z6y5SXsj+7C1KzHOusf+1VG7Xe9Y76F2f0hUrqI0JtX45g9BxOTdkCf3S+55HCrJW/ABUrcuOMPqX17tdcVjXXR89gLfoxseh4QJZaMpba4PlNg0Gxk+R81l2nZ7+BLT8MHP4bGYqhej93nVKyUAZA9STOvUodC9Tollba8jBTMxCTkYTLGIFWroGgO9DtP9znQelj2I4Ijg2A4iwjCdjhjCNl05hOF9shXslEVSkdwd1BUJeK1Vb3jtTseq+Wp3e75XmsHqRQKD8oJ0wSmiy7Y8+/ZCv+R53vUTjYk2jA4BoZEa+Uw535IIbt79bs9LHEd6+4k1A5htslrC8VeKPLp/gRsYWmLkiYru536GS64JgNuyDJ72dgOF4bFGOaPhPvL4EdFwlPVsM0Ljw4QNnsN5X5Y3ARTElRFZIxhYDRcnyn8o0KVSrf1EVptw3av4aRY/d6Wt2j58N1+MC2GUxLgj4XCW/Uwrwmqw5x1ikMVbM02NHu7LI4eCybHq3Uu3mkIhCsINoeEVS2wokW3UxNQjmZIFOS6haJ2Va6lumBQlOYuLW8xYeWXnkPVgZ5WGr+tQcEdOVjRlp47ljEkOoQ2pxJXftRy2T9KyHAbzk+GV2qFl2qFHDf8pC/ctD2s+PPDfSUwO1WYmqBV5VJd8L0c4RvbVNm1qgWyU7q2e7yjoaGBV199lczMQxtUz5gx4zC3KIIIFI1B4T/VwrwGzVUr2GOuUQJtmlXZvJsiRwYvxkzEi4t4fHwtuIT/t/2XDKv7EIDS2MG8OuBH1MTk91hHAx522/Gc0raUa80akkdejMk/M2LvP4qI9CERHCga2lqVWGqqZ2Nju0YkiJOgLeT4K5nQuorhLWvIb/6ESiuJRfFT+HvCpSzq+2d2efL3Wl8qbeTRSK5dR16wkqRgPQYbjFNjROL6QFQqbe4kGh2JNIuLIOGKtBYMCtvg8sL5SpmuQ7t+PFEQ6RUjOGEgFSs0NHrrq3QaLNJPwhp/C2bgrCPyJ2+ikrHOfRTJnRYmnF7Ebq/GuvC5/WYc7XN9DhfWOQ8ReuEcaNpF6OULcZz/JCZ5QK/Li4iSMjvmHDVyaa82u2JwzPgLMvbbSNnHGlYXnYYUva3B5bWfwEn/Dxb/CtqqYfE9WOc8gv3fWdBSCttfg0GP6fEK+TCuWBh2JVL+MVKzAanbgkkdjOl/PlK1Cil+DzNotm7cDiFB3yETexEcWSxqgj+VdlV9C3YjkTqIpO7h3YFuNrPe/lbNHg/2XKb78w7lVJpTbVbpLiVkcj2Q5zHkezQbqK8HYg8g98YW6VEFb0/FUsf2rQ7VEocmZZZwMHSRD8p8Sl6V+4X3G2FeY1fFO4Nas76RZbggRW1vRxqWMXyvj1aiu2STsKQZrtoCTw8WNrcbqgKwrAUmxKkFzDKGW/uq7W5DG1QEVNW0uR3OSBSy3Ib+UUKZXzOYqgLCwiYlokbHqkJqt08JoaaQVklRMhIcRohzqOUlyWGID+diBdAKcsuaDU0h6cz6AlUv7PZDZVBVR/XBDgJPrWwBEf7bDnGWBna/VQ9xDrXF7fmdJzs1w6kDCQ6oNoZoS/CHutaf4oKpCcK7DWrv+189TAxX81veosuta4UNrRpG/s5woV+0xdREw6BoYWM7PFYJ5yUJlkMr5e2P/Dwa+OUvf9nr68FgkNLSUl577TXq6ur4+c9/ftTa9OGHH7J06VIcDgdDhgxhxowZeDyR/4UIurDDKzxWKXzSCoUezTbpQHcVk/ibWB41gretIQiGHJr4cf0TfG37r4gLNBAyDj7oexUL+1yBmJ5e1kpiqQ1anNf+AV9NaCZm+M2YpH5HdT8jODRE+pDPP0SEuvYWdtZWsrOpng2NXnb5hAZxEgpBoW83p7atZFjLWvq0bGKbK5dFCadwd+qNfFQwmTpXao/1WWKTZVq0IlyoltxgJbGhZuheES4xH9uTQrMrmUZHPK3iVBucpddDI6NhQFitlOeBxF4yPj/PiBBNERzXELGRne8gy/+ClC7sfN3kz8QafzP0Pe2I+1aNMZiR10BCLvYbX0N2L8B+42tYFz6Dcbg/9fN7rS86BceFzxJ69SvQsIPQczMwI76OVXiuhpQHWpC6zUj5MmTnu0rWdMDh1pmz/hdgCmceMXKp13anDMKkDOp8LvF9sDc+C/5mTM06JH00FL2llrnmUqyZf8Oecx2UL0Pm3gQjr4OciRh3AlbmaCRlKFK7XpVpp/4KkzcdFt+NVK3F+Js0JE9EM6EiRNNxiZZQT+XNnuiNKOr+H2vQP+MEJ8Q7dDDf494J8Q7T+TzRqbM/HcRSsvPQbGrdA8u7ExW9td/qZv/7LLNOfluzQoq8etyCogG185pUldOBPm64LhOuyzQUHKI1TkRotcN5VSG1p3UQfoLuj9PosY8JXwzFd8sAmJ5kmDcSZnwirGyFa7fCM4OFVa2GUh+sNmo3BMhwW3wvx+au3WoT+9cAocRvWN5imJYgNAbDhJDoNkt8aj8s96uZ0RbpDB6PdWjltcIoQ6LT4DGqbNsREBpCQrkfPmlVYqo2oIohJ0r6NdjhQpWoHTLTCekOWNmmhFK7rfva161kZKylFeKqA9IZ7m7QCnlJDnDtQewlhq+WjNEcpY48MKcR2mzDGUnC09X6exgQpVlNJX7NYepQYRV54ez1sGWcZkRdnQE/KVZV0/wm+GbO8XEBeuedd+73/bi4OG677bajSjTtua3s7GyeeOIJZs6cuY9PdGH48OH7fC8UCu3zvQhODIgIi5rg6WqhKgDDolUd2fl+oBWp2aAFYozF+zET+Yg8AEZQyZ+Lf8i0sucAqIou4JUBt1IR17MEuQC7JR6fv53LQquZVZCJc8B1BxXPEMGxRaQP+fxBRKhubWZnXSU7Gxv4pNlLqQ8abSc2QhSQZPx8u/QBRte8T2ywgQpXJjf2e5D3+59Ou6OnYMAlQfqYZvKkkTy7mj7BStwhLyA6JnHGQPwAAp4UGp1JNDri8IqFQa9bM1yaI1ngMeRF6fWc53NkgzsURIimCI5LSNCHbHoee+VfoW6Tvmi5MIMvxRp3MyZt2FFvk5V/JuaiFwi98mWkeC72O9/EOufhQyK6TFI/HJe8gf3ezcjuD5DV/yK0+l+9L+yMxuSfgel3/lEnl/YHkzoUa8rPoWE7Ur8VotcgVauhpQx74R04rl6JOfWXyMI7dR9dcZj6LTDiGozTgxl6GbLw50jpR9ht1VixmZjUoUjtRihdhHHGIIEWCLRBVPKx3t0IesHUBMMfC7sqvrlN12OP0Vydjopw7vBrUVb4udHsnMNNFIt0hYV32N26P98fOkilrvvP1jZbdODTUdXOFlX1zGuA97tlLxngnGS4MctwXsr+7Xy9QURoDCn5UhfUvKDeFFn7g9NAukvIdqtKbFSsYd4IOGWtsLgZvlcE9xcKy1oMRV5IcAj9wza+m7LhoUrNSFrWolXimkJQ6lernI1hS7uSTfkeJYoEISBd6rCmELR7YWObtiPBqcclKFDlh10+VSq1hrOTXGGizBglctLdGhzeP9oQsIU59RqgHo7oIihQC+z0wRgbZqep2qjYB0Ni9Pve3/mY4Og41nru2qLHvT6oyw+MNgyNFnb5uo7Bz/rCB826rMvAI5Wwwwt/LRO+lWMYHGMYFiNsaoPflsJl6TYp3UfIxwjz5s3r9XXLskhOTmbw4MG4XEcnTGr06NE88cQTTJs2jczMTEpKSnj22We59957ufDCC1myZAknnXTSUWlLBMcnFjbBvypUTTs8urMgHBC2ypV+BO21EJ0CDg+b6IgrENJpY3jNgvAzwwd9r9qLZAKoII6Qr4kLnCVcMvwUTOboEzac94uGSB/y+UR5u5+H1q2iqDVAk+1AEGIQEq0gme5A53XUabufZmrFywAEjJvrBj3J3ITTAYgRP7mmSa1wNJJlWnD4GyHo03wldyxE52M8SVp92xXHZq+uN9EBQz0aw5AfVixlfM5tcIeCCNEUwXEF8TUiax/BXvUgtFXoi654zKhrsUZ/ExPf55i2z/SdinXB09ivXIpsfgFJG445+fuHtq64LKwLn0OK30U2PodUrdFQc3ccJiEPMsdg+p6GyT3tkMK8jwaM5YCw0kkKziLUWg1rHoTaTdg73sIx+v9ht1Zir30Eds5FnNFQ9D8Y9lVVMMVmQWuFVvkb/11M7nSVtu9agCk4EwLNEMlpOm4xINow4AhO6HaQRkCPe+lGIO352oHACmc6Weig5HCQSt3REFTCYbdP7Vwh0epu7zfC0uaudma64PpMtccdrHpJRKgNQmWHamaPnXcYJUdiLCVkPJaSSR02sUA4+6rVVgtYULqq8sVYUBglDIuBV4cZZn6i1eXGxxm+kgZrW/WW4BTSXYY4p8XtuTbf2g5/LIW5I4TVrYb1bTA9UavjgaE6IFQEIN0JMWE7ozecx+U0UBFuS0m4wly7DXUBvXeEickYh2avJDt1PWkuPcYuo0TT5AThrt3wToOuo68bbs5R4ufnxRoCvroV+ker8mhtq+Hc5E+3JsaHiSbLUhLP7VD1UzBMIiU74axkw6OVwro2yHHpcb40zXBqgu7vhjabj5rhj2Vwcx+14V2SAn/w6n7/oAgeHSjHfAA7bdq0Y7r97pg1a1aP5wMGDOCOO+4gMzOT//u//+Puu+/mhRde2O861q9fv8/3OkqTR3Dion+UDvZWtmhfmOnqRjY5oyA2U68j/C0Q5eIy8wlzGEQxScyjkNFj1vLnHbcwu/oZZm+9mzUNH/O/gpvwOeM6t5GIl1pHPO+E+uItruGcqBpyktKPzQ5HcFCI9CGfP9T4bf6+YTOfNNv0tXzkuMHRGdbf9f/Zr2E500r+DcCcwu/wTMbXmGuNxsLmKtaSZxp7Ku9DPggFMOmjIL4PuGJ7vN8a0omxG7M1hzLhC2aDOxREiKYIjgtI027sVX9HPnkCAmEfSWwO1tibMCOuwXgSjm0Du8HKPxNO/x32+9/DXnQXZIzGyj/jkNZljMEUzISCT5fuHu8wDhdm6i+Q7a9Dcwny/veRfudiJt+OaSlFdvwPtr+BuOOQ7ImY5P5YA2Zhr3kQdi1AhlyOyT8DVv8DKV8ChWeHvTBtx3rXItgHOmxonc97vLfHsnt+tpfHHZ85SDHOXjB0EUgdj7uIpSNzYdAQ1CyiMr9WwAPY6RUWNsGHTT0rx52RqBcqFx1k9pKIUBdUMqhqD3LJaSDVqeHXyU61hh3ovnYooir8qkpqs5WQKfbByFj4e3/DDduEnxULk+M1wHKXDz5u1iymGIfhqnR4oAw2tsO/q+DLabC1XdUGZyUp0fVRkyHNKapesgWHUdKmg/yKdaiyyRYlwEKilrUko6RS/yg4KVZzm4bFQLLLotJv816D2tJ8GO4u0cwoB0pyXZSqCrExsfDdbOHP5fBJG7xWqwHrKS4lxSZ8ilDUZWkVPbfRi82ArZL4zG4XmsNjhHiHEowb2jV8PqUbqXZPPpz+iQaJf9hg4zC6f7NS4YUaeLMe1rUKo+KO7cXrddddx6xZs7jwwgv3ucycOXN48cUXefTRR49iy7pw9dVXc9NNN7Fo0aJjsv0Ijh/keAw/6Atv1glv1GkfNCBKVbTGWJA+CmIyNAS8rZo0j4+vOdfwCRnMpT+VVhJXDHiCf2V/k0c3XcFJ1XMpbFzF6/2/z/akkwGIIchwVwu1IRevtUSzeM0Wzsqs5sz+Q44LFWIEB49IH3Jioiko/GtLMesa2xliNeJ29R6tkeCr4stbf41BWJFxPh9lzeIthgAwkRLyaez5AbHB2wBJA3QCvZd11gQh26PVf/e010fQOyK9YwTHFFK1ltBbNxB6bBSy6m9KMqUOwzrrnziuW6s2ueOIZOqANep6zIhrAMF+55tIe92xbtJxAcsdC1N+piP7pp3Yax7GWA7M6X+CzLGAwLbXsXd/AIAZcD5EpSDt1dhbXkSSBmDi+qhstX6rLh+MEE3HK0KomqTj5u926wgE7x4M3v0W6nazpafNrTsM3bKSwkHczrC6xd1hyQvb9aItHdRHOwxRlsFtGVyWwWkMjnCltMMFEaEmIKxtFf5XL7zfAJvaYJdXeKNO+MlO4Qc74b91enGS6oQf9IHN4wzvjbS4NM0cMMnktYXt7cKHTRowXerXY+o2mjd0cpySV6PjDLkeQ5zj4PbVGEOS0zAkxjA9UdUBLqNZUkub4dREuDZDyaCrtwr9o4Qkp37PS5pVseW0LH4VLtDyUAVkONWGFxSY26B2vEvT1NqW7NTqa0lOQ7rbkOPRanqjYjX7qY8b8t0aonlZKjw3GF4fbvH7foaLUtVyFsLQGhIq/JDr0cD0xU3CY5V6Tl2RDg8PgKHRBkEHoQ4Lzk3WQM6gwNsNSm4ubgoXXvgUxDn0uIjRAHzfHlXiLGMYG6vr3NSu522fbjF+pyYaMl16jt9TopUUgwKnJSgpNTMJMt3H/uL18ccfZ/Xq1ftdZt26dTzxxBNHp0G9wO12Ex8fT1tb5P8hAi0Hfkmaxa19taropnatRAnh/5DYLEzfUyBlMATbMe11jJQKbmIpEyjBIMyLncSQsZu5O+8XRAcauHLjTzl/+59xh9o615PmCDLS0w5BL/8pbebnKz5hTnkjrQfrVY7gmCPSh5x4aA8JDxVVs7SmnkFSuU+SybIDXLLlHmKCTZTFDuR/hTfxAQU0EkUiXk6juJeV10FMOiZ9eK8kE+hE2Pi4CMl0MIgomiI46hA7hOyYg6z6R8+A79xpmHE3Y/JnHHPrwIHAmnYfodKPoH4L9rvfwfrSUydEu48oLAfW4NnYy/8EtZuQxXcjgy7W6n0z/4r98ixo3Ils+I+qneKyMAUzkc0vQdlSSBuOKZiBrHscqVqD6TMZCbTts9OP4NiigwDqeLzne/t6vufPxHR7v/P+OPwt+WytGFcZUFWRP0w01ASEZS1q3Vjd2lkTE5eBC1Lg6xkHZs/qDgnnO5X6dcDUMYxxGsh2Q1ZYuXS4j5PDGPKjIMctbGlXG1uRF67KgPmNWi3vtp3w535qBWwIqo1uTByck2w4JUFVXL/aDf8coJX0qgLwbgOMioXTEyGYoMevMQhBwsfVD+Vh20thstrlkpy6n67wPjqNIdkptIQ0XLs6IJT4INohfNIGT1Tp+TMmFsbGQqrLkOPRCnMrW7Ttp8QrSfdAue7b2jY4yQg7vIb+n2IDbQmphbA2AGckwZn23ssMj9F9qvbreZ7uEjrOamMMF6UK/6qAj5r1AiyIklaPDoThsSfO3J/X68XpPHaXkFu3bqW+vj6SrRJBDwyNMdzWF16pFd6uh9qgKiGdBozDAxknQUw6UrsB2quJcidytnM7J1HBWwykxCRyV5/beTL9azyy5RpOrXqTfo0reK3/DylO1HPNYMj2GDJCDZQ2N/PwFpv5NWmcn5vD5IQDn0CI4Ngi0oecWPDbwmMlLSwsr2KAfxdRMfu2K87Y9TC5LRtod8Tx4qCfUWols4S+AJzLVtzs8eftb9ZiS+kjtZ/oBd6wRX9YTOT3fTCIEE0RHDWIrwn55AnsNQ9B00590TgwAy9W5VLm6GPZvIOGccXgOOdhQs+diWx/HdnwNGb4lce6WccUxoTTeU+7F16ZDa2VhOb9AOusf2KiUrCm/Rb7jSuhajX25udwjLsFq/Bs7LKPkaZiKF/eVdmucgWSPgoTbD+2OxXBPuEwBsfn+D/Xb2sOUm1AyZKGbva3Up+wvFUVRhv2mBCdEAdXZxouS1Oy42DQGlLypMyvBEQHkp2aN5TpPvhKe4cCl2UYHqtEyfo28Ivh5hzhe0Ua/D07TZVUi5qUiEp1CnlRhnvzhdPWwfM18J0c4cwkw6ImtdqtbtVjleVWm1xQNIOpNhyoHedQVdrIWLW+dORcbW0XSnyCjaExpKSbxwhVflWzbWqBu3br65ekQo5bycAWG6IdhjMShQWNWiXOYcHpSYb5jcLaVm3/4GhY3EwPoikoQiCcHeWyDCtbhOu26jkgwLo26Bcl/L/snt9ForMrUN5vQwhD99jsG7Pg4Uq1333cogo9n62KjOMJ+yIwRYSSkhLmzJlDTk7OEW1Dc3MzRUVFjBo1qsfr9fX1XH/99QBcccUVR7QNEZx4iHMYrkxX0veZau2/8j1KXBuAuBxVUtduhMYiCLaR5RGuMatZQxbvUUiRO48zRrzP7NqX+VPRLVy94Yd8nDWL9/KuJ+jQzEyHw01elBDw7WRXVRN/bfXxfno2F2REMybu6PTTEewfkT7k84GgCP+pCDC3tIwC7zZiovftdR9au4BJ5Rr+/eqAH1Eflc0cBiEYhlDNQPZwoIT8EPRi0k/CRKf1skZFTXgibFCk0ORBIUI0RXBEISJQtQZ7/ZPIxme6gp09yZiR12Kd9I1jHvD9WWAyR2NNvh170Z3YH96O6XcOJjr1WDfr2MI4cORNJ5Q3HXa9D1tfwU4agGPCDzB5p2EGXYxseh5Z+Q/skTdgkgcquRRsU7WTMxpSh0D1Otj5DnICnx8RnDiwRbODGoJaua02oMREB7y2sKFN8z9WhdUxHTDA1AS4ONVwcSoUHmSwd0jUAlbi70lmeQzkeNR+FXuMGL0MtyHeIaxsVbXArBThlTq4cZuwYZxhaIxWilvVCklOYVy8xZdTbV6u1fDt14bBaYmGHV4ldlpCSiDtibTwBVy+p2uAVhAF1X6bBc06m5jkFCXaMOwM6IVfkRdeqFW73MWp8N1s+LBZyZslTfClFMEvUODR3KkyH8xIFk5JgG1ezYJa3KyqqLoApLgMXltVUx3wBmyu3KznQ2GUEknbvPCLXXBpmpDSjUxsCWkIe30QGsJZTlHdhEr9o1SlVeaHl2rhq+maibVnmPvRhmVZPcilO++8kzvvvHOfy4sIt9122yFt6+GHH2bhQlUzr1u3rvO1+fPnAxreO2vWLGpraznppJMYP348I0eOJCMjg9LSUt566y1qa2uZOXMm3/ve9w6pDRF8vmGMYUyc9iEvVgvzGrW/6BcVLgbhjILMMZrdVLsB2qswniRGOyoYTA3zKGQF2byY+mXeSjqbu3fdzo0V/2RAwzJeHfAjSuKHd2wIV1Qi/YOteJtWs8nXxObmXMampvClVBgafXyqc090RPqQLw5sEV6qFt7cXU7f1i3ER8WA6V39m9q+mwu3/QGARTmXsSVlCivJppQE3AQ5m209PyAC3npIyIfk/vttR0NIYwSOt0mh4x0RoimCIwJpq0E2PYe94Smo6VatIWUo1phvYoZ8BeOKOXYNPIwwY78Dm1+AmvXYH/4cx1l/O9ZNOrawnBAKYc5+CPn3BC0rvOJ+QthYk27HnHYvsuMtaK9BPvol1vTfQN50pKUMaatS4in/TJ1trFmPrP4HUng2JjrlWO9ZBJ8DiGiVs+aQ3jrIpY4Q6g6022od2+FVcmlda0+FkdPAmYnw5TTDhSmQdQjZOg1BodQHFQFV90A4B8Sl6qV01/ExSIl2GCbGC6tb4OoMDfgu8sGfSuHHfbsUXx83w+lJwl35htfrhPcb4d0GYWayoV+UodAj1AShyq/WNweQELbHRe9BpIVEWNUCu/2GRIdgi5YTjrYgygg+G9a3qnIqIBr8/ftCzZTKcWsge2MItnpVPZTtNrTZghhDsRfGxgkfN8OKViUOT4pRa+CFqV0kk9Ooqu2b25QcK4yCH/dRYu2paqgOwP1lur8d2O3TEscVASW1/LZQ6ddg9XZb9/mcJHi0SlVR7SEIoETm3obTo4fTTjut81xbsGABeXl5FBQU7LWcw+EgJSWFM844g2984xuHtK2FCxfule+0aNGizlDegoICZs2aRUpKCt/61rdYsmQJr7/+Og0NDcTGxjJy5EiuuuoqbrjhBhwOxyG1IYIvBpKdhhuyYHgsPFcjYSWiVpE0oJWlolOQmg3QVAymjWhPEueZrYymgjkMoNyRwPcK/8yjmTfw9+03cs0n32dxzmzm515NyAqHsDmjiHK4GezdTktNKUt9w1nXnMOkJBfnp3DQVUUj2D8ifcgXAyKaeflySTUZzRtJdllguXpd1hnyMnvzL/HY7RTHj+T9vGtpwcV79APgdIpIwN/zQ946iEpWy9w+yCvQCSMDDI/Y5g4aRg4kATMCoKuEZWNjIwkJx19A9bGGhAJI8Vxk/X+USJDw1LzDg+l/AWbE1zWH6RgMnERECY+GbUhjsYaOB31KisRmqaoqfSTG4f70lfW2/rKPCT2vleMcs9/C9J16OJt/wkGCXhAbu2od8tJ54G8FhxvGfgvHafciy/6AveQ+cLhxXDEfEvKxP/gJtNVAbBYk5CExGbDgVrCDWGc/hNX/3GO9W18YnOh9XVCEtpAO7NtsaAupcqU5pIqTPXNbgyLs9ikZUOKDze16C+2x3nyPVlCbmWyYmQRJh1Da1muHq9P5tE0diLGgT1i95DlOZ8xsEVa3wnPVwm9LtbLdlnGGVBe836DHu68HJsQbfrDD5sEKVSktGgUxjgPPH/LawuImVQUZYGC0Zkbt9Blaw1/KlnbhJzuh2YaRMRq0nupU0sthQa4btrQrWeS2NFdlaIzwYZMe25ExwoPlmh1VG9Tv9tJ0JdLiHbDLCwEM/60R/lGhwevvjYSdXsO6VmGnF56pUavc9vEawC4i/KdaycPVrUqKzUjqOQNaH1TL3127lSC7NBWGxuhyUxOPj4wmy7K48847+fnPf36sm3LEcaL3dREcOKr8wrPVmiEXa2lRgI7LUQGtlluzAXwNEJUEDg82sIps3qcQb9gEe23lo9y763ZsVxyvDriV8rhBPTcUbAdfEw0xfSmJH05STCLTE+HsZHNchP1HcHgR6UOOHN5rEB7Z1URc7Wqy7DrwJPW+oAgXbf8dJ1XPpcWVzL9G/YMWdyovM4T1ZJJNE9exqmcFtEArhPyYnEmY2Kz9tqPcrzb33xbqf30EB46IoimCzwQJBZDdC5BtryHbXgdvbdebmWOxhl2FGTwbE5V09NtWuwnZORcpWYiULoLWiv1/wBkFWeOxBn0ZM/QKTEz6AW/L5EzEjLgW+eQxQvNvxfHVDzDWF3iWxOGGoBcrYyT2JXOQVy9REmnF/djueFWBbXoeGnYQmvdDHF9+BZM7DdnxP6RhGyYuGyt5APaob2Dqt37hibs98cEHH/Daa6+xYsUKVq5cSVNTE1dffTWPP/74sW7aEYGIEJSuSl8+6VbtTjQLxydqr2oL7duGFBIN8y71ayW4Mh/s9MHWdv38nijwwCkJcEqC4fQkGBh1aAqj7tut7Rbs7TCq5unj0Zn34x2WMYyOFUTg9XAZ8R8WCU8PsZgQL3zQqERdmku4I8/wUq2qwv5UCj/NlQM6dg1B4aMm/S7dlpYRTnNpXHyKSzOsVrYIPytWom5aAvypEDa1G7Z6heagBpMXRqnqakc7xDg0iHxojEWpX9jhVQVbvkdJrLpmJRm3tsF/a6GPS0nGze3C3ypUXf+NLHivAVa2qJpqSJRmTVUH4MUauCYTmoNCbUDbPToGFjbDimY4JVHznxId8EGT5m1luPR8WNQMg2N6ko7HGo899hhZWfu/8I4gghMNGW7Dt3JgRCy8GFY3DYjS/kHVTX01u6lmAzTvAtOOFZXIOMoZQg3vUcgasnks8zpeSZ3FPcW3c+26m1nU9wo+7PNV7A6lhTMaHB6SvBUk+qqpSRjOf/2FfNTs4Kwk4Ywkc0iTFBFE8EXCR03Ck2Veoho2kRWohP2MycZUvcVJ1XOxsXhp4O20uFPZTjLrycQgnM/WniSTHYRAKyZ1uE5ufwrqgjoZFCGZDh4RoimCg4a01yHF7ymJs+Mt8Dd2vRmdjhl6mRJMacOOftuqP8He9Byy9RWo3bj3AvF9IbEQ40kEhwdCXqS1Ehp2qISyZCF2yUKYfxtm+NewpvwMk5B7QNu2pv6c0JaXoGYdsuk5zLCvHt6dO4FgjIU4oyAUwMo8CfvKxciz06G5FFnya/C3wMgb4KNfQMVyZMMzmt20+wO94KvfBokFeuxj0iHQBp7ITFEHHn30UZ544gliYmLIy8ujqanpmLTDFiEgajmzUaWQjT4P0fW6Ld3e2+N5SNQ2Fgjfd3/ccX+glaMlnLNUHejKyKkN6POyABR7eyeUQEmAsXEwLg7GxxmmJkBfz6FfVNgi1ATUQlUV6LkPyU5VLmUdpWDvwwkrnH1ya1/h2q3wbA38qMVmTJzFiFhhXatWoZuWCL8tMFy7VfhDKZyfIoyO2/++VvrVzhYUtdRNjt87m2pLO1yxWW1xk+PhxaE6w5jiEh6rVMKm0g+tURBv6Uykx4KvpKk1bWys2iGLfYZxccKqVrXSFPlgQZOeHwUefe3hSj1X+4bDxcWoQqo6BMtatbLd/xrgkUrhmkzDdp+2PcUFLie0Nep5NyVeyPRY2CKcFKOZUFMSlKCq8GsbW/eUzx1DfOMb3+Db3/42Z5999rFuSgQRHFY4jOGMJFVaPlMtLG2GJIfabY3RIi9kj4fYDLXvt1ZBVDKxDriQLYyhgjkMpMqZwk39/8FjGdfy16LvcH3dd3h1wG1UxRbqhowF0amYQBvpDatI9ZVQmTSapwJJLGgUzkuBUxMgJjJwjSCCvbCqRXi0PITdsI389qL9kkxZLVs5t+gBAN7Pu5bixJMIYPEWAwE4mVKyaen2CdHxXmwOpAz+VMN6SHRycGRs5Ld6KIgQTRF8KiToVTKg5ENk57tIxQroXhoyJkOtcQMvxPQ5BePo3T97xNrnb0Y2PY+99hEoX9r1huVSq17eNEzfUyBz3D5zoUQE6rcgO+dir39K93fdo4Q2/Adr8u2YibdirP3/XEx0KtaEH2Ev/Bn2ol9iBs763ORQHQqMscCpZUIdibmEzrwfefcWaC1D1jyEyZmEZE+EkkXYH9+HI/9MrIEXYa99BKlZh8Rk6jnljIqQTHvg29/+Nj/60Y8YMmQIy5YtY/LkycekHSU+rbp2JCCiIc4d9rf2bha4lm75Sk1BqA9p9bLqoCph9geP0SpjQ2I0qHVYjGFcnBILn9XWGxKhLqjkQVW33CXQQOgctxJMJ/rgwjJa1enxSmFBE3y/COaOEAZGG2oDag1c0gTnJwtnJcE7DXD1FlgwyibJ2bs9bKdXM5kEVftMjNdqb90xt164covQGoIJ8fDfoV0y9igLBkTDpjbwOJTM8dka/JvkhMaQIQcN+y70iIa5G83D8omSkQ1BzZ/a7oYnqvS8S3bq+dIYgi/H63aeqlLiyR/OXFrZAkua7M6Q81y3ngMG3Z+OMPCAQKLTkO0Wzk6CN+p0G0ubVZkVEjkuiMesrCz8fv+nLxhBBCco+noMt+Ron/JKHaxvV8WqxwqrmxLyIDoVqVkPzbs1ZsGTSC5NfIMVLKcP8ylgWfwEJo9czC3l9/PrdTfxdsFNrMi6oGtDrhhwerDaa8j2f0Bm0kBKzEAeqnDyfgN8KUVVm3v2dRFE8EXFxjbhXxVCa8MuBrRsgOiUfYZ/p7UVM3vLr3BKgM3Jk/go5yvYwHsUUk808fiYzs6eH/I2gjsOkzHqgJwntUFIcarFPYKDR4RoimAvSHsdUrkCKf0ISj9SYsne46IzdRimYCZW4dmQM/mY2MSkpQJ7xZ+R1f8Ef7O+aDkx/c5Tu17/81W5dAAwxiiznTIYa+y3kdKPCH14B+z+AHvhz2HHHBwXPPOp6iYz+v/B2oehqRhZ+QBm4q2fdTc/N7DyTieUPQ6qXNBejVQsU7uiJw68DdiL78Ga8Reo/gQad0LphzBktoaDf5FtiL1g/Pjxx7oJADSHhO3eLlVSh/ooxN6KpD2VSh033x45Sq2hLiLpUEUe2W61RXXeogz5HhgSrVWIDudgvi2kyqXqoJJd3XmuKEvL4Wa5Dy3P6XiGyzL8vlCYsEZDtJ+vFq5IV0VYc6N+fwubDX/tL0xfp1Xa/m8r/GewjcvqumgU0fLjW9r1eZ5HlWVWt+9IRPhrOdxRLIQETk+EZwYb4rsd0xIfxDsMM5IEG0OFXxB0ENcSgg1tMChaiZyxcapgqgwYBkcLVQFVF7zTqORlY7sONjNccHmaZi2luSDTDbEOmJSghFRrCHI9uq4/lGp+V0y4q4pxGDLdQpSBDe0w2dVFPOZ7IChqQ/yoGTa167kfFLVTHmvMmjWLt99+G5/Ph8fjOdbNiSCCIwK3ZTg/1TAkRrPVVrfCAE/Xb9i4YiHrZIjJ1Mp0bTUQk44FTKCUAup5hLEEjYP7s2/hx6W/4dTSp3sSTQDGEVZmt2LVfEJeew2B7Mns8jn5S5mwIBa+2ydiy4ngiw0RrUz7aJmX2oZqBjetwrjjew3/TvRWMK3kSUZVv4eFTb0ni1cH3EqRSeFt+lNNHABnsw1P55WkgK8ZxMakjtB1fwraQmpxPyPxxIg3OB4RIZq+wBARaC1HqtZA9Vqkao0+bt6998IxmZg+UzD5Z2DyZ2h49jGCNOzAXvp75JMnIBSeQk4ehDXqeszwqzCxmZ95G6bPFByXvYds+A/2uzdD2RJCT03BccmrmMyx+/6cMwpr6i+w37oOe/mfMCOuPizt+TzAuGMxhWcjTbvUwuitg6ZdEPKCgGyfAxNvxRp5DaHdC/Q8XPcoctqvMUSIpuMRq1rg1p1HdhsGDWdOcKgyJdMFGW4lAdJdhgwXPW59PUc2TDsoQkNQS2VXB5Qk644oS9uR7VY73vFQNe5IYXy8xSWpNi/Wwl/KNRtpaIzhlARVOrWGYF2rkk1f3QRv1sM3tsFDAwSXZWgNCSta9FiCqsyG7VHVpcgrfH+H8E6DPr8iHf7e3+Du9h13BKwDDI4xJDsNtkDQFhpCMKdes522ew2DoiHVZSjwCDt9SiA5jRKF12XA+jZwGRgeA19J1yozJT74oFFVUONi9TseHqMEUa4btns1VHxqAhR6NM/BaWBiHKxp1XVOTujKDstxazbYpWmwpFmzxxY1wVcz4HigdX71q1+xaNEiLr74Yn73u98xfPjwY92kCCI4YuioQCeiv9sesP2Ir1GvNbtNeBWTyH9lCEHjwGN7ub/oFlzG8MqA2/a9ITug63DFgnEQQosMpLtUaRtBBF9UNAeFVyrbeae8Fn9rJYN82zHOGM0764ZYfx2nlD7D+Mo3cIQLTm1MOYXn8r/Ly86JbEQtdtEEOJMdDKVGPxho1SJQrnhM6lD4FNGA19bcRgHGx8GXUiI/0ENFhGj6nENEwNcIDduRhu1QvxWp347Ub4WG7frD6w2J/TWJv88UTJ/JkNT/mA+YpGot9tLfIpueBwmP7nImY026TVVM+ylNeSgwxihx1fcUQi9fBDXrCT1zOo7Zc/YbTm0GXQIr/waVK7CX3IfjzD8d1nadyLDyTie08TkItsHUOzGli5DVDyrZ1F6Nvf7fOCb/FGvE17CX/AapXocpegcGnH+smx5BL0hyGfq6BY+lloMoQ+djj9EBecdjj7Xnc0OUpWqRhDCRlODsIpU6nsdYPdUtRxteW2gMauZTfVCVOt1jngxqr0pz6YDhizYrfXe+4eVazVZ6p16IsVRBdmqChno3h/T7+2WecPsueKFGK8bd1kfAGELhwd3YuJ6ZWNvbhQcrhEcqVfXmsTTz6frMvcm7Le2qJEt2ds06Wsbgdhg8IgyJFj5pg09aoX+UqprGxynZExQ913Z4VSL/rwHQL7rrv8RnC+kuwWmptc7XbTA6I0nDvle2qmpqp1cJRqfR83pqghJNG9vUFtehaPJYhlQnhDyG/LCNb25DT6vlscSYMWPw+XysXr2at99+m6ioKDIyMvY67sYYtm/ffoxaGUEEnx27fcKD5cLGNlW8usM/fQForVDrXHut2ved0djAh+TzoeQhxmJI2yb+s/VKTHQaD570L7yuXmz+dlAn1lxxkD6Miuh8arxqxbkkzTAm9vM9IRFBBPuCiLCuoZVni8vZ0NhKjq+MNIcfotO7SkICUcFmppQ9z4TyV3DbXgC2J47l7bxv8FLcmXxELkEcGITxlDGNnUQThKAX/E3giIKUYZik/hhX9L6ag8+GXT6dFBoSA+clG8bHgzPy+zxkRIimExRih5RA8tZDew3SUq7qpJYyaCmHljKktQJaynRQv09YahnLOCl8GwXpJ2GOo0wcKVmE/fFvkB1zOl8zhWdjTbwN+p56yH/QjY2N3H777bz++uuUlpYSCoUoKipi/vz5XHvttTz22GNcc801mMQCHF/9APuV2ciueYReugDHZe9gsnq3LxUXF1P41fl87WQnj175ODLmm5iUQb0uuz9Mnz6dBQsWKFn4eUFiISZlMFKxDLPrfawz/ojEZqk9MdiOrH0YmXgbJmMMZIyGqjXIjjlIzkRMTNqxbv3nCvtTKYRCB2Za+1KK4UsTPh9/wCKC14YWW3OfGsP5T72Fh0dbkBoml1Jdx/9FyIH2dQeLnTt3MqSwkP4Xf53t33+Mp6t18BTjENJdhumJqlgq80Mfj+E72cLfyzXT6LLNMDpWmJwA73ztDDZ8tICnKm02tAnvN2qgeAemJ8IfCw2DY/Y+zsVeoTychzSkl+vHWIdWoNvUDi0hYVu7YXCMZjUNihK2eA1B0Up6pT61wgH4bWFxM2xuBzBU+oUEh6qv3EbPiywXnBxv2OwV5jeqcmp0LCQ4DTlu3W6cQ8m2da1qoQQlotJcmuM1KxX+VKah8RvbhMkJx/5csm0bt9tNXl5ej9f3/C/6XP03RfCFw5Z24Z/lQrEPhsV0EcgS8iG1m6Fxh05qxqSDsWjGzX9lCMUmGQx8veoJfrPrDuYX3MCGtOm9byTQosVMYnNoSx3FToknSeDKDDgn2exV7CCCCL4oaG5v5rXtW/lfbQBfwM9Q04ArOgZM1x+5K9TOhIpXmFL6PNEhFUaUxA3hvbzreStxBu/Sn0aiAMingbPZRiatqh70NaptNaEQkzJwv1EqARt2+TULdGC0EkwT4+mhnI7g0BAhmo4CxA5BsF2Z1WC7qjcC7Z2PJdgOAa++HmwPv9eGeOv1h+JrAG894m3oIpcCzQfXiJgsTPIASB6g90n99T6hAOM8HsT6PSEiSNFb2Et+A6WL9EVjYQbPxppwKyZz9Gfexo9+9CMeeughLrzwQq6++mosyyIpKanXZY0nEevLrxJ68Xwo+VDJpquWYBLz97l+E98XpBZ74S9wXPjMZ27v5wHGGEy/c5GqVUjdFqjfhhl3s4a4b34RmkuwVz6AGXkNJPaDpl06s9hWCZ8zoiktLY3a2toDXn7evHlMnz79yDXoC4KQCG2hroDx1pCSS82h3qvbGZQsSHJ2KGYg6gS7+DiYvu5QMCrWUAQsbdHBm2UME+OEeKdhUoJWk9vhhUnxhj4e4T9VSjatbYN1beAN5zP937aeX8BZSfDtHMMZ4evDtpCSgV5biZ66YJftbkC0Ejx7wmkM0RYMjdb8h0/aYEA4q+nkePikVQiE85EsA6tboa9HiaPmbnyroJ/NdnepHtptODdZM6YWNqnUfmmLKp36ePQ8GRsnfNgE7zXA7HDlO6fR8whUlh9t6br+UqYWu2ONnTt3HusmRBDBEcXqFuGhCqE6AMOi9bffQ8XkrQV3Qqd1ZxvJvCaDaTUeYkMtPLDjO0wKbObJUX+mxd3LtYnYqmKyXNipI9kVOxCvOJgYD7PTDIVRJ9Z/SAQRHC6Iv5lPilbxbHk760MJZJtWCj0GTFznMpYdYGzVHE4r+Q9xgXoAKqMLmJd3LR8mz+AdM4CdJAOQiJcZbGcoNRgJgbcBEB33pgyCmPR9VpYLCuz2aUZivyg4N9kwOeHEu8Y7nhEhmo4ApG4LoRfPU8Io5FVm9UjBFQtRKZi4bC3VGJeNicuBuBxMXFbXaydI9TOxQ8jmF7E//i1Ur9EXHW7M8K9jTfihkmOHCXPmzGHw4MG8+uqrPV6/+OKLmTRpEtnZ2T1eN64YHJe8RuiZM6BqFaH/fhnHVz/AuGN7LNenTx82btxIgl0Dcy9AdryJlCzar93uWEHqtmAv+yOyewHYIUzuqViTfoxJHnjEtmlyJukMYUsF9q75OFIGYZ31D+yd74KvAVnxF0zIq5UhMkarLTLt85cRcsUVV9DcfOCEcVZW1mHd/vr16/f5XlNTE4mJBxakfzzBFsFngzccMu619d4Xrl7XHupdodSBDlIpzqH5SolhK9/xUAnss+Bg+7oDRUdfl5iYSEwT/KcaXqyBn+SqnWxSvOCxDJluQ2ZYzSMCN2TChjZhTj2sboG3HdCEKpcGRsPEeMOMJC07XubXyoYNwZ5B6x0wKMnUbz8Dt5huqqbWkLC21TAmrsOWqVXqEp16vvy1DE4Jn/rxDg0ej7HgmWrY2q5WuEnxevHktSHaYTg7Gf5Xr4TT2/VKPqU6DQKcHAcfN8Mun6q7xsWpciIxfPUVFK12tbYN3m/QSZaIjSaCCI4MRIRFTfB4lU44DI1Wh46qmDZBY5GSRNGqYgphmCcFLDZ5YGBU6xqe2HYtxZln8HTmvT3sPZ0I+XSCOCqV+pTRlFip5Lng4lTDKYnHvwI2ggiOBMTfQsvuxbyxq4y3Qrm0W4kMcbfjNl3ZZ0ZCjKx5n2m7nyTZVwFAnSeb+blXszxtBvNNf5aTg2BwEmIKu5nCblwSAn8jhAIQnapjmLg++/wvDYmGfDeEtDjHlcmGqQlEFIZHABGi6UjAWNBW1ft7llsrbTmjw7cocEZhOh9Hd92ikjCeJPAkQVQyeBIxUR2Pk/S5w3309usIQoI+ZP2T2Et/r9lRAK44zOj/wxr/XSXPDjPKyso47bTT9no9MTFxn4Ns447HcfFLhP49CarXYL/7HRznPdpjGZfLxZAhQwAIlV+NrHuU0MKf4bjsveNmACEierzn36oquo7XN79AaMccrPOfxCqYeUS2baJTMDlTkC0vIbsXIEMvx4pKQib9GFnwE1U1+Vsx7TVIyK+zgp9D/PWvfz3WTTiuICKd1epC3SrVhej53N9Rsc7uqlzX8VpviqTe4DJKHsQ49L6DXIq1Pp9ZGYfS1x0Iuvd1tycKT1drCPg1PiHbY1jZAifHS4+BlTEGt1GL3aBoJYrOjYUFwJvDVSoUErWzrG3tmVtkoeqfjqyvGEsVRjGfcnHYoWoaE6tZUhvaINEpNAW1ylu2S29vN6iiqX+UcHqSYXK3suOnJwqLGmGXVxUQLksJTa8NE+OEkeFw8N1+vb/AGAyaMzY9UfigSQPDB0cLlrHCeWaC39aA8bVtUBeCre3CoF4sghFEEMFng4gWFfhPlWBQghcDsg8VUwMeXrEHsdtKAeCm8r9xc+3jvDXoB9RF9+19I74GsEP4EwZRFD8Ml9PN+YkwK9WQ5or8riP44kH8LUjpIjYUrea5QCHr3MPI8oTIN+1dSiMRBtct4vTdj5PRXgxAsyuFD/pexYqMc1hh5TGPQtrRCnRDqGYm20nCB/4WDfv2JGHSRkJCHsbqnd6wRSevaoNqk78kzXBaAj0q2EZweBEhmo4E4nNxXPkROD1dpJEjTCidgGXaX3rpJf7yl7+wceNGmpqaSE9PZ/jw4dx4443MmjWL+fPnc/rpp/OLX/yCO++8s8dnd+7cSWFhIVdffTWPP/545+sFBQUArPz4A279f1/h9feX0dRuMyIbfnpuIhdd/UPMmJsw0SmdnxERHnvsMR555BHWrVtHMBhk2LBh3HTTTVx33XU9tnvnnXdy1113MW/ePIqLizvbP2HCBAoKCnjiiScAWLBgQefAsqONjz/++D5zS4qKivjNb37D23OEsrIQiVGPMWzYEq656dbOZbvv82N/+w2hTc9BxXKW//ePPPG+5qLs3r0bv9/PgAEDuPLKK/nBD36Ay7V3Cc8jAfE1Yb93C7LlJQBM7nSsCT8A48RefA9SuhD7jasws+dgssYdkTZYBWcS2jkXWkqxSxfh6HcuZsxNyKI7IeTDBFrAkwg161Vt1f/cI9KOCD4bmoNCeUD/vAW9t+n5uPM9el+ug0TqTa1yKLDoIiKi9ggljwmHj7v2IYs+kn3dqlWruPXWW3nttddoampi5MiR3HHHHVx44YV7teO46uvefpuysjISExMZNmwY11xzTa993eOPP87sNOGFGvj3whXEv/04qxcuoKZsN6Fe+jqPZfDZot+9dO13iR+2t3cpz+Id0MetmUYxB0kEigirWjVnKckhDIvRi8vKgPBRkyEggo1Wl0tyQIlfA713+OBbMZqhtLXd5oNG2NgOm9uU+Iy2YFAMnTY+LMOkBGFJswaMP10NP+yjyiSnUVXTlnYo8mqO07AYfS/RoRbOXI+SnGkuVUgdbfzyl7/EGMO3vvUtUlJS+OUvf3lAnzPG8LOf/ewIty6CCD47QiK8XCO8XAtxllpb96ViAthIGnPs/rRZUSQF63lw+zdJjk3k6eG/QUwv1/HhwG9xxVGROppadzbDY+GSVMNJkbDvCL6AEH8rUrqI1qJ5zPGmMidqMq0xSQwx9bg7rvhE6Ne4ktN3PUqf1i0AtDviWdTnMpZmXcQORwb/YwCVxAOQTitns41CGnSS3NcErlhM+khI7LfPKBhbNAexOqCTU1dnwPQkQ1KEYDriiBBNRwDG6YH0Ece6GYcF//jHP7jpppvIzs7m4osvJjU1lfLycpYuXcorr7zCrFmzDm3FEsLf2sCM8f3w+kN8bayhIRTH86sCXPJQE/8+rZArp/Qkma666iqefvppBg0axFe/+lXcbjdz587l+uuvZ8OGDfz+97/fazO/+93vmDdvHhdeeCEzZ87E6XQyfvx4CgoKuOuuu8jPz+8cNI0ePXq/TV68eDHnnnsuTU1NnH322XzltGbqt33E6oot3P+n3/capmtiM7HGfgf74/t46K+/5s0tHk477TTOO+882tramD9/Pj/5yU9YtmwZL7300qEdy4OAVCwnNOc6aNoJxok19eeYcTd3Vuyzvvwq9muXI8VzCb11HY4rF2Hccftf6aEgfRQmqR9StRp2vIXkTsNyxWCnnwQVS5Edb2HOfQxq1kP1OuyqdVgZIw9/OyL4TGixdfB8OGFQlYnTgKP74/C9q9vNbe39/FBtCUesrwP8fj8zZsygvb2dq6++moaGBp599llmzZrFv//9b6688srOZY/Hvu7yyy+nvr6eVatWcf/99+8zOPyOXMMLNcL7Tz1M+tI3GDH5NE6eeS4hbxubPlqwV1/nNuCjq4rfB42CV/T7i7bURpflOvhBmogOKH+yU9ja7fxMccKduTAiFsr8qmoYGwsjYgwxDsPvC21u2aG5T78oFpKcWo2uKZzV5DBQG4BVrapoGhDdZdEs9Gh7S/ywqQ3+Vw/npuh56TOGc1OEf5bDdi+saIHx8aqiswK63msy4MupkHsM6pzfeeedGGO47LLLSElJ2YtE3RciRFMEJwL8tqot36yDDJcSuvtSMQUxvGfns9TKBwsmNi/h/t0/YUX+VayP3Ud0Q6AVAq20xuRTlDCC1OgYvp4MZyWbT1VbRhDB5w0dBJPsnMvmFh/PRk9nXdxAMqx28qjtVDH1ad7AGbseo7BpNQB+K4ol2ZewOOdSqp3JvEs/1pMJQBQBprGT8ZRhhfyqHHS4IXkQJnnAPscpIjphVBHQ3/4V6XBGUkRdeDQRIZoi2C8efvhh3G43a9asIT09vcd7BxNk3AGpXI29/M/QXEJ5PQwZAG/eMQzP1FsxQ6/gh1t3MHbsWL797W9z4YUXEh8f39mOp59+muuvv54HH3wQp1NPXb/fz+zZs/nDH/7AFVdcwbhxPRU4CxYs4OOPP2bkyJ4kxaxZs7jrrrsoKCg4oItqn8/HZZddRnNzM3PmzOGcc85B7CCh/5wCFcspTdt3dpQZdzOse5TbTq3gb7/9Ba6Tv9N1PES44YYbePTRR1m0aBFTpx6ZHCcJ+ZGPf4u97A8gIUjIx3HuI5jsCT3b6nBhnfcYoaemQGMR9vxbcZz198PeHmM5MQVnIfVbkcYipGQhpvAszLDLkYpl0LQLE52CpAyB1nI4AZWARxILFy7k4YcfBqC6urrztQ4CYMiQIfz4xz8+4u2Is6DAozk3Br232M/j8P2e73UnlaxjNPN7uPu67igvL2fo0KEsWbKkU7n4/e9//4Tp67qjpKRkn58dFWuYlSK8ctWPmXHvAzw02MmKFs3HQoR/fe8GXn7ysc6+LiBQ5ZdOIqcxBLGWMDDa0NdzaOdCU1C4dqsSTaAqqJPjlOAp8cPNRXB7X/huH113hx0PoK/H4jvZNg9VaLB3iV/JqYIomBCnlrv/VEFNUFVXcWFFUkcu2IgY/dx2L/y6RDgnuauSVZrTcFqC8FGzWvTGxglxDjAYMEKCE9qPURG3efPmAXRWmet4HkEEJzpaQ8LjlcL7DdDXA0nGh1T1rmKqIZrXQ4WUOLT//2Hp7zg3sI7/DfkpIauXmIpw4HfIcrMreSK+2D5MSXAwO81QEAn7juALBgm0KcFU9A7tjaW8FTOJN5Om0GI8DKIeD/pHn9FaxOm7H2Nw/WIAgsbF8swvsbDvFTS5UlhCLgvJI4ADEMZSznR2Emu3K8GEgfg8TMpAzSjurS2i/9NlfiWWZ6fBjCTNi4zg6CJCNB0DiH1gpcOPJbpb/FwuV6+2rtTU1ANenzSXEHpuJrKr5wXsL+/5DVGX/rBTUTNkyBCuu+46/va3v/Hqq69y1VVXAfDAAw8QGxvLAw880DnwAnC73dxzzz28/vrrPPPMM3sNvv7v//5vr4HXoeC1115j9+7dfP3rX+8ceBnLieOsfxD690T61LyBXfQ/rMJz9vqsccdhTb6D/PduhqW/RgbPwiTk6nthu8Kjjz7Ku+++e9iJJvG3IFv+i730d6piAsyg2Vhn/mmfpT6NJwHH2f8k9OJ5yIansAde2Ot+fVaYvqdgtr+O1G7ELnoHkzUOq/AcQo6fQsiHbPkvZsTXtDxpYr/Dvv0TGdu2beu0RHVg+/btbN+u+WbTpk07KkRTvNMweD//IqGDLH8uh/CZz4ruQd+Ho6/bF371q1/1WPeJ1Nd1R9+++8gmCeOOPMMrdfk8Vwd3+WFyvFZrqwoYTr/2W7z85GM89MZc/MOn4BcA06lo6helxGWM49BIph1e4dz1wpZ2VRLd1hdu62uIcxiCIty9S7hrN9xTAv2ihFmphgRnT8XU9CSLFJfa4AK25khNCYeEjmm3ebsBSn2qctrYBo0BwYehJaS5UyV+tc8tb4G5DUKCA9a1quUu0aFkak1AA8k7AtI7DkDbMbo0mDZtGsFgsPN8mzZt2rFpSAQRHEY0BLWy3OJmJYvj28uR2g17qZgA1tmpvM0A2h1RpAeqeGDn92nOmMD8xOt7X3k48Ls2qi9l8cMpSEzk4lTDlIRI2HcEXywowfQRsvMdaNzJZnchz6dcx1ormzRatRockOwtY9ruJxlZ8z4GwcZiTfpZLMj9Go2eDLaQylz6U4/+LnNp5Gy2kS1NWnHdDkJMhlaSi83aJ8FUF4TSgNrhL0xRZWGfY6AUjkARIZqOMsQOQdlHx7oZnwrJmYKxHHzlK1/hxz/+MSNGjODyyy9n+vTpnHLKKQdUGluadhFa/md9XPw+sssC48AMuRRi38fVUsOU2V0kUwdOPfVU/va3v7F69Wquuuoq2traWLduHTk5Odx33317bScQ0Kp+mzZt2uu9CRMm7PXaoWDp0qUAnHXWWT1eN5ljMONuRpb/GXvudzDXrun182bE1wmsfYoHXljI838+ic2VQVpaWpBug+qysrLP3E4RG2o26KxCySKkeK7KugFiMrCm/QZr8CWfuh7Tdypm7LeQlQ9gv3sL5msfaxD9YYSJzYC+p0JrBTTuQLa+AsOvhrgcfb7pWRzjbgYEnJ+P0PvDhe45OccrQiJ81HSsW/HpmJKgpe4/S1/3aXC5XEyaNGmv10+kvu5AMS7OcG6cj7ce/htTbnoO385Ne/V1VeVlYZJJM5hiwn8BA6INdrhioMeSgyKbPmkVzlovlPuhrxteHGqYGN/1eacx3JlvaA7Z/LEMbt0J5ycLzj3+f0CVWaNi93qZgmiLQVE2TUG9mPU4YE2bWujabJXmj43TnKdVrXB7MXwrW0sng1rs3EY/O78RrlNXQCfR1n64gsoOATk5OXz961/nuuuuY9iwYceuIRFEcBhQ6Rf+WSGsaoGBbh9RtZuQxh06Eu2mYqoVD6v98Xzk0cq2pze+zw/rn2Bl4VfxO3vpBAB8Dfhsw46EcUQl5HJBipuLUg2pETtOBF8gSKANKVuMFL0DjUW0O+N5O/lC3rCG0oSHgdTiIYQz5GVm8b8YWzUHh+hsyvrU05ifezW10Xk04eZ1BrMDjUuJx8eZ7GAElRhfs1Zvj0rWSnLxuXuNGTtQH4QSn15TnJ0EZydHlIXHAyJEUwT7xa233kpqaioPPvggf/zjH/nDH/6A0+nkvPPO489//jOFhYU9lpdQANn+BrL2YaToHaQufOXscGPGfwdr3HcwCXnw7QJSU1OxrL07jMxMvfpubGwEoL6+HhGhtLSUu+66a59tbW1t3ee6PisaGhoALee9J6ypdxLa/BI0FiEr/gJZl++1jDEWl/3b5vW3fQxK9/OVGaeQOfRUXC4XDQ0N3H///fh8voNulwTaoHIFUroEKVuClC/VEp/dkTQAa8TVmFE3YNz7uHDqBdbknxHa8TY0bMVecBuOs/+59/YbdmAvvx+pXotJG441+XZM3IGXSrfyz8SuWI5Ur8Wu3Yi1+QXoMxUadkDdFuyyJZjsib3OXEQQweHEwfZ1B4PPS193oGj+6VfgrdepyR3EZbO/Qv/szB59XbL4mRIP0Q4lgKLCh8YTzmw6WLJpWbNwznqhLqj2tQYSWVgAAJpqSURBVLkjDFn7kMj/usDwXqOwphXu2AUPDTy4fTs9UUmkoAAC68JEE6gNbmK8sNsHK1u1at4uL5yRpPa8bV6IdcB/a2Fdq1AT0E85DITCWU8ickyCgxsbG/njH//In/70JyZOnMj111/PZZddRlzcEcjoiyCCI4T2kLC2DV6pFTa3BBhil+Oq2dpDxdSGk11+B+sljQ2eAeABS0L8pOy3DIo2LCm4bu8Vi0CwjbZAgCp3Fi1J/RiRms7sdMPImEjYdwRfLEjlSuyNz0PDdsQVQ3XySTxkTWI1maTSzjCqO6/bz975D8ZVzQFgW9LJzMu9hvK4Qboe4GWGsZtEHNhMYjensAt3yAveenDHY1JGQ2IBxtF7waSgaKXXGAtOT4Jzkg39oyK/yeMFEaLpKMNYDiRnyrFuxqeiwzpnjOGGG27ghhtuoLa2lg8//JBnnnmG559/nq1bt7Ju3brOH7N/+9uEHnwI2io719OUfDLwMdbgS3Gc/rse26itrcW27b0GYJWV+vmOstsJCQkAjBs3juXLlx/cfhymjqZD1VBaWrr3NtxxWKfdi/3m17A//g1y1sy9llm2bBmvvz2PsyYP4bXZJTic63HM/i0mZxJLlizh/vvvP6B2iAhUr0N2ztVb+VKQYM+FXHGY7AmYPlMxedMha/whHQfjisZx1t8JPX82svEZ7LzTsYYqiSZ2EFn5N+zF9+hsAyCVKwjtXoDjsvdUrXQg20jMx6QNh2Ab0rQLcUbp/hgLQn5k+R8x/c6DgRep0imCEwYOY5iScIxCZw4CHda5A+nrOvqqYDC413o6yKLe8Hnp6w4Ey5YtY+Fbr5M69Sxq73mDxD4O7hmg+93R17lM7+WEjTF4kE6yyRsmmxz72bf5DcIFG4WWEEyMhznDDCn7URa4LcPf+8PUtcKjlfCDPsKQmAM/dqcmwt/K1ZrntTU4vMQndJjNx8XB2/WQ49Z8iEXN8O0cQ3MI+kXDljZhZQvs8sG8RshyQ5QBr1HizQYc+2vAEUJ5eTn//ve/eeyxx1iyZAkff/wx3/3ud/nKV77CtddeyymnnHIMWhVBBJ8OEWGHF1a0CIuabMpamjHeeoa0bcIZaAbjJBSdwa5QLNu8Hla4hxJw66DVIUFmNL7HRW0LacwYzzZXUs+VB734Aj6qTSwNziw88fHkpmQxLS2eM5LMMakSGUEExxLibcBe/x+kpRRSBmEcbv4nQ1lJNoOoIYouD3hhw8pOkunZwXexJaXn+HcNmewmERchbmAFabSHs8/qtYpc2jCMK2a/7dnuVdv9tZmGIdERgul4Q4RoOgYwJ2iwcWpqKrNmzWLWrFnU1NTw/vvvs/nZb5Ow5X8AlG76GEZZEJOJGXk11sjrWPvqQuDjXsOcA4EAS5YsYcqUnh3Phx9+CHRVRoqPj2fo0KFs3LiRhoaGw2JlOVh02FLeeeedHhWiOmCGXgbL/wSVK7FX/m2v9zuyc86//Js4+69Atv6X0KuX4fjyq537uy9IoB3Z9T6yfQ6ycy60VfRcIDYbkzOp80b6SIx1eH7aJmciZvx3keV/xH77RqR2IyaxEHvNQ1CzTpfJnYYZ+lXsj38DjTuw5/0Qx5eePPBtFJ6NNGzHOKI04C86A9n+pnqyazciGSdhToBcswj2xv4IguMZvfV127ZtIzk5GeidhFm1atU+1/d56us+DR193VUXns/9DgePVcIduUKux3xqXwd6kRhlwGcLobCyyWkEt7X3ufRmnTB7k+C14YxEeGWo6ZXA2hNTEgwXpgiv1cHtxcJLQw/8PE13Gfp4hPqg2uCCollNExM0WyrWYRFl2fSPgnI/LGxSBdPXM3T2tl8UDI/Wi+P5jTA7TXBZkGFphb1j9ZtJSUnhlltu4ZZbbmHlypU8+uijPPPMMzz22GM8/vjjDBo0iOuuu46vf/3rh009F0EEnwUNQWF1CyxqEjY3t9Pc3khSeyn9vSW4xY84Yyj35LEz4GSZPYBGZ2LnqGd06yrObllInitEVdIIypNmdK04FCAQaKNGoql1puKKiSU7Np6ZaUmclBLPwChw9dIfRRDBFwGaxVQMacMwloNiSeQD8smmuQfJ5A61ccGOPwKwNPPCvUimNpy8S38AprFTSSaA9lqIScdkjMQ4PPttS3VAJ32uSDcMPYgJowiOHno3OkYQQRhvv/125+y9BNqxd8zBO+dGarfogCFq/b8YHLWLOA+8sdlFw7THcNy4E8dp91Llj+fuu+/e7/p/9rOfdeaOgGaPPProoyQmJnLRRRd1vn7zzTfT1tbGN77xjV5tI0VFRezcufMw7HHvuPDCC+nbty9PPfUUb7/99l7vl5WVY03TTBXZ8J+93s/Pzwdg0aJFWDP/BpnjwFfP2r+cya/vvnOv5aWtBtq0mljoX/2wX78C2fBvJZmcMZjCc7BO/wOOa1bjuGETjvOfwBrzTc2MOkwkUwesqT/HDP86YCPL/4T93s1KMnmSsGb8DevLr2ENuwLH+U8CFrLtFaRy34PuPWGSB2CSBoArBhOVjGP8zZgRV2uJsuYyJBTszFOIIIIjhe59XQcCgQB1dXUAREdHM3jwYOLi4njttdc6XwdVJn1R+rpPUzp19HXlKxYxPRECAvfsFtavX8+vf/3rA26HxzKdFduCopaYYLecp2erhVkblWS6IBleH6aKoKAIIZEemVC94d58gwFeroWVLXsva4vgt4WA3bWuOXXCpDXCm/VQFQR/OJcpCDQFIdmppdQ9llrkTlGBGjfvEC7eKCxuVlvcKYlaza4+CJvawGWBP0yqHQ8YO3YsDzzwAOXl5Tz99NOceeaZbN26lR//+Mfk5uZy8cUX88Ybb2Dbx0mDI/jCICjCulbh0Qqb27YH+euOOtaWbCW5ciEj6j4k17ebdncKqx0FPMloHnZM5N2ocTQ6Esnxl3Jj1cM8UH0fl7mLcWeOoiJlDLblAgkR8jVT1e5lQyierZ5+uFIHcUFhP348aij3jcrlir4JDIsxEZIpgi8spLEY2fkuEpuuDh2Bd+hHA1Gk0dZj2TOLHybJV0m9J4v38m/Ya13zKKQdF+m0MIHwdYW/CZxRmPRRn0oy+WydzDk3GUYfeCpIBEcZEUVTBPuEhPxc9pXZxLgNUwfEkBdVRyAY5L2twoZK+MpoJ/knX4gZ8hW+Vb+U3/zuj4z/ys+46KLlNDc38/rrrzNt2rTOGe49kZ2dTUNDA6NHj+b888+nsbGRZ555Bq/Xy0MPPdRZ7hvg//2//8eSJUt44oknWLRoETNmzCAnJ4fKyko2bdrExx9/zNNPP01BQcERORYej4fnn3+ec845h3PPPZdzzjmHk046iaamJlavXk1bWxurVq1CCs+GFf/b6/MTJkxgwoQJPP/885SXlzPx5LHs+ngrry8t5bxhTl5aA7JzLqGXLkCadmsYdl240w60QlxfTP/zMf3OxfSZgnFGHZH97A3GWFgz/orkz0A2PQv+ZrXlnfQNTExXGXiTMQoz5FJk03PYK/6C47zHDnwb/c5BVj6AlH+M5J+BmfIzZM1Dastb/28Y/GWIP/TMmAgi+DRcdtllxMTEcMopp5Cfn08gEGDu3Lls2LCByy67rLP0+7e//W3uu+8+xo4dy0UXXfSF7ev2he593ajd5VAwkX9W7uLxxa9zwfnn8+KLLx5wW9yWwSGC31Y1kN+GAMKjlcJ3duhrl6fBg/0BDP49eI99KaEAhscarkgXnq6GXxQLrw/vWi4k0oP0CQq8Vmfz1c1qbQMN7t4sMDlBg8A3t8NpiVDkVfIp1lLl0uhYeKhSbXIfNMHf+wtnJcGwaLXVrWyFyXFKyPn3z40ddbjdbi6//HIuv/xySkpKOtVNr776Kq+99hpZWVmHbLGMIIKDQblfg70/aBSKm1vwextIbd/NEH85DrHxuRPY5C5kSyietY7Bnf7TmFArX2qYw8TAVpzxfajJGEgl4WA2sbGDbdQHHVRbiYScaaTExHFGchxj09MZEWcRF7HGRRABoBZVe9vramtL0/D87SSzmL7k0NwjSzW/cQ0nV74OwBv9v0fAEd1jXSXEsxLNcz2PrTgQreQY8mMyxmCi91/pV0QzD0fFwUWpJmKXO44RIZoi6IS0lCMVy5GKFVD+MVK6iLvPbOWdzcKyzc280QyxHov+uRn84ztf4frv34MjWgdI9/x6Np7o/8/efYdHVaUPHP+eOzW9V0rovVdRqih2xbIWLICCXXd1d13XFcWK+nOVVdcuYMW+NhSR3ovSe2+BhPReZuae3x83CUQSSDCN8H6eZx7InTP3nnsJZ2be+573BDJ16lTefPNNWrRowYQJE7jsssv46quvKjye0+nkl19+4R//+Afvv/8+WVlZdO3alQkTJnD55ZeXa6uUYtq0aVx88cW88847/PDDD+Tm5hIdHU3btm158cUXOe+88yo8Tk0ZMGAAq1evZtKkSfz888/Mnj2bsLAwOnXqxJ133gmAcfZjRwNNxTllr7XZbPzwww88/PDDzJw5k1WrVtG2bVv+729DGBG0jK/W7UHnH0EfWHD0gA5/IAfbDQsguke9DqRKKVS7kdBu5AnbGb3uw7f1M/TO79EFaSd9syjbf2grVHh7dPo29K4fUJ1vQXW+Cb35EwhuBhEd//hJCHECkyZNYubMmaxcuZLvv/+egIAA2rRpw1tvvcWttx4tDvv000/jdDrP+LGuMr8f62yrV+Fr0pbYv/wfz427qFqBJrCmkrkNjVeDx9S8cAgm7reeGxcDL7cEQ1nZSaUxJY1V48mrwTQ1LlVx3YbHmik+TdH8kAErczT9ghS6JLBlHdvaz7YCzW07rCDTmGhr+ttj+yHDZwWWguyQ4wWF5kCxwq4U3QI0OT64OExxfzz8dY/mxwz46x6Y3wX6BFoFTLN9VgCqrRuK6u7+QbU1bdqUCRMmcO211zJu3DiWLFlCUlLSyV8oxCkqLey9PFuzLruYzPws/AuSaFJ4AH9fHqbdzT5nc/Z4nPxmtKPQcIMdlDYZkr2QcwtWEONykRjejUxVWjdSo72FZHtNjhBMob0JoUH+9A0JpF9MFF2DnCes8SbEGevIWvTh5RDcDKUUWsPPtCYbF805WqPS4Svgsl3/BuC36EvYE9Kr3G5M4EfaAoruJNGcbKsuU1EmhLSGkJMvvHKoGELscFOUwl+CwQ2a0ifLLxdlsrOzCQkJISsrq6xo6+lI+4ohYyc6fRukbkInr7aCS7kV3Jn0i7Bq8DQbimo+BCI61UjAo/RufG1OAakvvi8uRu+dhep2W4Urtf2e1qY1gGfttyL6ATGo6B4od2jtd7YWeD8eBCnrMAY/i9Hr3iq/TuccxPx1MmgTo+0V6IJ0zFl3QWQn7NfPrb0Oi+M0lrGuIWjMY11VHCrSdFhtBV2eTVD8s9mpvX8UmZrbd2o+OGL9/Pcm8EyCFYhSHB9I8h2TCWUocFeS2TRmu8n7R6zlkGd2McpqQ5W+Js9rctZ62JhvrTj3SxdFqgcGb9BsL7CmwI2JsqbSXR0BeaZCA82dmp8zIcapuC8Osryay7bA6ly4IQrujYMFmTA/25oCkOOD6yLhnviGd3c2Ly+Pzz//nClTprB06VK01vj7+3PNNdcwbdq0+u7eHyJjXcNSrrB3llXYWxemE1Own3DPEZSykeyIYY8ZwBqjOan28LLXti/YxuVZM2ln5HAkvAeF9qOZotpXRJ7HyxECyLMFEeRy0zY4gP7RUXQLDSDGIUWExak5E8YQ7S2y6rCmbYGIDgBs0ZE8xzmEk08oR1fNHrHndc5K+h9Zzije6P4Oxfby89pW0oSfaYMbD3ezigA8VqkQv3BU/Dko+4mnzOX5YE8RjI2GSyKkrEZDJxlNjZQuzoHsA+icg5BzAJ2+HdK3WcGlzN2gKyiurAyI6IiK7YOK6Y1qNggiO6OkPk61GGdPwLd3Fnrj++iz/okKaXHC9koZENMLFdPrhO1OF0aXWzDn/RVz00eonvdU+cObCmqKankhevePmDu+BXcEmF5I3Vyt7CghRMMR71K83BLG7dRM2KcZGAyDQqr3hW5Xgeam7ZrlOdaMmMmtFPfGn3gfNqVwGdYUOFNbtZMqmkY3oZnioyNWUGhRlknvQKuNs6TpX/daQaYoB0xra+033K45PwR2FEC615ryFmCDZTnQxk8T61D0DVLMztIkF2uSPAq3oZjQTHPlFvgi1crGcttgUDCsyYMsn3WcIlPjbiB3aBctWsSUKVP48ssvyc/PR2tN3759ue2227jhhhvKTfkU4o/I9FpT45Zka7bnFJCTn0Vo4UFaFybi1MXkOkJZ52jLZh3OLnvzstdFeFK5MuM7epv7KAxpS3psD/aXPml6KfAUk6LdZBnh+LldJAQGcnZUGF3DQ0lwN7ygrhANkT64CFI3okNbo7DeU2fSmgLs5YJMzbI30j/pG8CaMvf7IFMOTubRAoBz2WMFmYpzwO5CRXU/aZDJ1LCrCM4OghFh8n/3dCCBptOE1toqklaQDoXp6MJ0a55sQTrkHykJKB0s+5Pi7BPv0BkMEe1RYe2tAtKxva3pWc7AujmhRkw1GYBKGI7eNwdzxQvYRrxe312qU6r9n2DBPyFtM6Ssh+juVX9twnBQCr3nZyhMs6YPFmWh98xCdbqhFnsthKgtt8ZYNYo+ToHLN2t+6QJ9gk7+IdGrNW8nwUN7NHkmhNjgiw6K86v4AdNQCmdJsMmrwab1cau6tfZTjI3RvJsME/bBjE4ah6EwlGJ6iuatJFDAe20guiT65DAUXfw1kXZI8cKCbBgdBRsLrNoRfaLBz6bo6A8b8zSrczT9gxW9AhVDQjQLsuDzVOhW8hm8f6AVrAp3QLpXEV+PC9MmJiby/vvvM23aNHbt2oXWmoiICMaNG8dtt91Gly5d6q9zolHxmJqtBbAqR7Miy0tqXjb2whTiCvaT4M3Ea3Ozy9GUnb5A1ttb41PWVxaHWczFmT8xuHAtQf6hHIzqyiFlrV6FNin2FJJiOshQwTgdTuIDArkkIohu0TG08VOn7WqoQtQHXZiB3jUD7Qgoqw+7kWhWE0ezY6bM2X2FXL7rRRSaNVEXsCu073H7+oVWFGMnnmx6cRh8xeAtQsX0qNLN5L1FEO+EUVFSlP90IYGmWqB9Hsg/At588BSANx/tLQBPPngLS/60tuMtQJf+7Ck4ur0492gwqfRRURbSibhCIagZKqgJhLVFhbe3gkvhHSAgVu7k1CLj7An49s1Bb5hqZTUFN6vvLtUZ5Q5Ftb4UveNrzM0fY6tOoEkpK0gX1w+duBRdlAUoiOlZex0WQtQqpRRvtoE9hZqlOTB8o+aVVnBLdMXTVfJ8mi9T4bmD1hdRgCHB8H47RYK7eu9bNqVwKG0V2zbBbejjjvloM8X7RzQLsuG1w/BQU/g5QzN2u1VZ4F9NYXiowtTWTR+lFB38ob0fpOTApnzoFACLcyDLC6E2DSh6BsDGPPgtD3oEavwMxT1xigVZms9SrbuyHtOqWTE0xFqiOdReP+/Ln3/+OVOnTmX27Nn4fD4Mw2DEiBHceuutjBw5EofDUS/9Eo2L1pokjzWFdNGxhb3z99OhOAlDaQ444lmt4lhta0meLaDsm0r/nOVcnDOP5g4vB8P7kBk+lExrr3g9haR6DdKMIGy2EKKD/BkaFkj36Fg6BDoqXRRACHFi5p5ZkLMfIqwC4D6tmEkbirERTHFZu2EH3ieiMJFsRwSzWhxfy3EPoWwiBoXmYnagtGl9tw1pZT1OIstrLZpxbaQi3iX/n08XEmiqDenb8E3rUTv7dviDOxzc4Sh3mPV3v0grmBTUFIKaokr/bMDZSY29XolqOhDVfCh6/3wrq+n8V+u7S3VKdboBveNr9NYv0IOeRtmc1Xu9MwjV8gJU/FmQvg1VMidciNNNYx/rqirQppjZGS7bbAV0xuzQvJAIV0do2vpZHxoPFllFuedkWTWLACLsMLG54u44K0PpVDgMhc/UmNr6oOr83W4S3IpJCZq/7YWH98EnKZoN+VZ9pyvC4fEEhU9jPbA+OMW7FB38NOvyrb7OSIdgG+T6YEs+tPSDdn4Q5VAcLtaszIHhoXBhGDRzwYEiWJcHLdzWqnXtXIqAepylfv311wNWTbGxY8cyduxYmjZtWn8dEo1Kvs/6P2UV9i4iIy+bgMIkmhTux9/MJ90ezq+ONqxXcSTZj65mm1C4l6syvqMbyaSHdSUz/mx2lzxneotI8ypSCcC0BRMZ6OKCMH96RsfROcRPigQL8QfprL2wdzbaPwZlWKm2a4lhHTE0LwnzAjTJ2Uz/w18DMKP1Xyiyl//+6UWVFACHPiQSRy4UpoN/JCqqy0kTH7zayma6MAwGNs4yWI2WBJpqg90PDDvY/a2/O479040q2+53TBs/sPtZzzn8wBEA7giUX1hZYAl3WJ0uay/+GDXgUfT++egN76HPetgKBp4hVMJw8I+B/GT0np9RbS47tf24QiCuXw33TghRH4Lsitld4cWD8NQBzeZ82JwPVkinvFZuuC1GcU8chNRAlo9TQaGueAqdqTV3xkKSB15MhPX51vZbY+D11tYqclprfFjBJruCSDtEO6GZEzYXwPRUeDDeqtu0Kg+GhWr8bIrhoVYB8yU50CNAE2w3uC0GJu7X/JQJd8VCYckqd0Ua6itv6Prrr+e2225j+PDh9dQD0diYWrOnEH7N1SzNMjmUmw2FGUTn76OJNwWt7KxztmGHL5htzoSy1wV5s7ky41sGFG/GCGrCwdhu7C75/6pND5kezRH88RgBhLkdDAz1p090DF3CQ2pkrBBCWAsVmTu/h6IMiLSmTHtLsplMIBAPADazmMt3vYiByfrI4ewIO+u4fS2jGen4E0AxQ9lr1WUynKioblX6XruzENr6wbVR6pRvOIn60egCTQsXLuS7777jt99+Y/Xq1WRnZzN69Oi6XRkltBX2vxbW3fFEg6SaDYGmA+HgYsyVL2Ib/nJ9d6nOKMOO6ngd+rdX0FumwykGmoQQjYtdKR5uBnfFWXWKlmVrDhRbtY2auKCTv2JoCPQNPPUMpooYSmFXGm/JFDq/Y+ogebQ1he/pBLg9FtbkQpcAqy+lbMpqZ5bExELtEGaHBBfsLrSKgid7oJUfFJjwbrKmmQuaODStXLC9EL5Lh/viNaOj4ZkDVpBtX5EV/AKrX9RTfaZPPvmkfg4sGh2f1izLhvlZmm15XnJzUwktOEjrokSc2gMOf9L9mvO9bs1+IxJsYGgf52fO5vy8xUS7nOwJ78ch29Gi315PPvt8AeQZoYQ6FT2C/OkfHUmXyCiinbJgjRA17sg69KHlEJxQlnH0G3FsJLpcNlOrrNVEFRwg3x7EzBZ3V7irlVg32gdwALevELyF1urafpEn7Uaqx7pRdEOUIkwCyaedRhdomjJlCu+//z7+/v40b96c7OyTFMWuBVL7SID1e2AMeBTziwvR699B938IFRhX392qM0anG/H99gp690x09n5UcPOTv0gIcUYIsSvGx8L42Lp7v3QoKyNJc3QVOp/W+PTR59v6Kdr6Hf9aK+il0Vh1ZgylSHBpQu0Q57SWW56TCVPaWnWetuXDeWGaIx5rlTq3YWVMLc6GwSGKy8M1X6bBwiw4O9jqT5GWzw7i9Jbh1XyaopmfBaoom9icTbTIP2hNn3cFog07a3UMs3VLCg0XId5M/n7o37SyF3Iwoj9ZYecdU14Y0D4yCgs5YI+lbYibc6OD6BrdhCZum3zWFqIW6fwUlLcQ7Ty6umgRdkwUJkf/7+U4rWCR3fTgNSpeNa4taawjjtXE0cfcjsMRAMEJFbb9vXwTQuzQ/MQL0okGqtHdBrj33nvZuHEj2dnZTJ06tb67I85wKmE4xJ8F3kLMVf+u7+7UKRXR0crq0l7MpU/Vd3eEEGc4pRSlyQ9eba16VVwybc2uTp5BVVpPuOQltHFDkA2iSua7bS6ANI+V0VSswaWs7I5ED/QJtD5wzc3U5Pk0t8VYq9n9lmv1pUhDkVnBQYU4TazP0zx3QDMrwyQ+bzftUhcQnJ9orSblCiXfcPM/sy0/qA4UGi4GZy3g+1034hfdmS3xl5Ljiiq3P5+ngJ1FdlL8mnNJ8yb8q2dnLkpIoKmfXYJMQtQyFd4e7Qq2prmVOJsDDGQ/ewjDVxJsSvJvTZYzCqdZSMvstRXuawS7CKKIdPyZa+9sLXxVlFmlfjRxWvUbv03T1grs4rTS6AJNffr0oXPnzths9bg+sBAllFIYZz8KgF77FjrvSD33qG4ZA58AQG/9zJrrLYQQ9cimFKXZ956S7CZDWdlMJ1P6gak0A6qdvyLSYWU0RZXkh794yLrzGmm3Ak4tS+7CKg1NXAqPtrKaBgZbxcI92ioeXhqcEuJ0U2Rqvko1eemgZm9uPh0zVhCUthqUAf5RoGzsJoz3zG5sMuJxmMU8ve9RHsr9nNnt/kqm+3eZ3tokpyCPTTqKqNBY7u/UlnGtYuttRUYhzkjBzVDBLaAgpWyTXWluYCOtyGAn4dZGpdgWNgCAdulLK9yVGx+Xsg2Alao5+1SYteJcFdgUNHXC/KzSmo7idNLoAk1CNDSqxQUQ2we8BZgrnq/v7tQpFdML1eteAMyf70SnbKznHgkhznROw8psspUEmFyqalPef5/RFGBTXB5uFS7v5G9tW5QNzR3Q2g8yvOAq+ZR1yAMDAq1I0socK1g1qiSBY00eFPoko0mcfhKLNJMTNZ8c0bjyE2mfOh973kFwh4EzEC+K2WZzPqYbmUYQHfK38t3O6wiJbM2KJteiVfmbwtpbyL4iSHQ15dwmcTzStR1nh/tJBpMQdUwpAxXXB+XJL5dJFKkKuJGNuPCRRAAA28NLAk0Zy0FX/EbWhgx6cgiA75z9KMpLrmAZkIpFOKxFM75K0xSZckfmdCKBJiFqmVIKY+BEAPTaN9CZu0/8gjqiPfmYv07G99XleD8Zgu+X+9BpW2r8OMY5E1FNzgFPDr5vrkZnH6jxYwghRHXYlcJlKByGqvKX2NIPTMdm7/cNUvQPUpwfCiE2axrcwhwrW8mnrTuwkXZrmpxDQZhdUWhqNhUo/hQBTgOOeGBXoWQ0idOH1pol2ZpJBzUrMotolbWGmNTlYHrBPxoMO8kE8IGvE8uMlgDcmfQmk1NfYEWbuzkS0Or3OyS/MJeNZgR+wXHc0bEN97RrQoxLvqYIUV9URCe0IwA8ueW2d1fJXME2UgkgHzv7grtRZPMnyJNOfO72Svd3PrsJoZBMI4DZvmZQnFflvrRyw/o8K7NJnD5kBP+dzp07V/ro10+WWRenRrW4AJVwHviKMRf+q177ok0v5vr38L3bAXPe39C7f4TEJei1b+Cb1gtz/ZQaPZ6yOTEumw7hHSDvsBVsKsys0WMIIURtK63hVFoQvHTb0BBIcFvBJoC5WbAlD9K8cKgY/Euyp3YXKfoEWm1W5UKoQ3FuiPXzylzJaBKnhxyvZmqy5rVDmszsVDqlL8Aveyc4g8EVggZWmrFM1d1JtEUSXZzMxzvH0Nvfy5Lmo/EZznL7074iEgu97HE0Y0BsNP/q1oHhUYHYJItJiPoVkmAt5JOfctxTF7ODszjILsIpNlzsDO0DQPuMZZXuzoWPy0qm0P1ma8Hu3KoHmtwGBNvguzRNktyVOW00yEBTZGQkSqkqP+bPn1/fXRbihJRSGENfABR62xeY++fVeR+01pg7vsM3rSfmz3dA7iEITsAY9m+MSz9GtboITA/mz7djbvywRo+t3KHYrvwaAuIhfSvmd9ejvYU1egwhhKhtv58+BxDjVNwYBR+2g2gHZPlgUwFk+6xHiscKSCV7oGuAxlCwr1CTUqy5NNzKdtpWAPk++fAsGrbtBZoXEjXfp3qJzN5Cq9RFGJ48K4vJ5iQHJ1/42vCz0R6PcnBxxgzeP/Q3dre8jv3BXX+3N01RUS6bvSEQ2IQxbVvylw4JNHM3yK8mQpxxrOlz/VCevOMKcTuVyU1sIIEsdhPG9tI6TScINAG0JJM+JALwXV4ohdW4wdLUCYeL4RspDH7aaJCj+Q033MDo0aOr/IiNja2xY2/atKnSx8qVK2vsOGea+fPno5Ri4sSJVX7N0KFDqzUvf9q0aSilmDZtWrntSimGDh1a5f3UFhXdDdXjDgDMn8ahi7Lr5LjaW4S57Wt8H56F+c1VkLYF/CIwhv0b222bMfr8GaPjdRhXfYfq/Werf7/chU7ZUKP9UEFNsV35FTiC0IeWYs68HW36avQYQtQ3Gesat9J/pd+XiVBK4bYZ3BdntViTB00csKfQymqyodFAlk/Ryd9q82ueVRTcbUCeCRuk0KloIPbu3YtSijFjxgDg1Zqf0jUvHNBszciifcZiwjI2gMMP3OGgFFt1OO+ZXdlma4KfL5+X9v6d6/V6lrYYR7HNv9z+tekhOb+I7famdIuO4eHuHbksPgSncXplMVV37BbidKMiOqLt/uA5PvsoRuUxig3Y0CwLHYqJQUz+HkILD59wn8PZTZjOIxsnP2dUPdJkKGuxjUVZsLbqyVCiHtnruwMVefXVV+u7C0LUCmPIJHx7foasPZhz/oJx0Xs18iFFaxMK0iEvCZ13GPKSIXsfOulX9IFFR5cRdfijet2H0f8hlCuk3D6UUhjD/g8zfRt6z0x8P9+ObdRilFFzKziqyM7YLp+O739Xond+gzknGOO8V1CqQca8hRCiHAPwQaVFTO+Ig6cOWDWXijQE2SDFC+FeCLDD/kIYEAQb86xHn0Do7G9NpVucBQ80qcOTEaIKUjyaj49olmT5CM7bT4fs9SjTW7KinEERNuZ541llbwUKeuauZuKRyYx+aBZaGdz/xdnl9ucpzmOnDsMvMJgbmsVzWXw4fraaC9ZMnDiRJ554gnnz5kngXYg/KqQlKrgZOjcRnIHHPd2LJC5hO184OrMnuButs9fSLmMZK+OuqnSXTkwu11t5n16szTfo6G/VNayKUDskeeDrNE17P/CvwbFD1LwGGWgSjU+/fv3YsmULkZGR9d2VeqWcQdgueg/fp8PRmz5Ah7VBDXikyq/XxTmQvBp9eJUVRMraC3lJVmDJ9FT+wsB4VJdbMHr/GeUfVXn/lIFxwVv4pnSFw6vQa99E9bqnGmd4cqrZYIwL3sb86Tb0pg8wTS/G+f+t0YCWEPVFxrrGzVCALj917lhRDsU1kZpPUmBvkbUa3YY8CLNBnKE5WKwYHKyJcyoOFGlW5UDXkkDTb3nWFGfJkBANRZoHnjug2Z2TR8ucDQTmHwBHALhCATiog/jJ15wkeyRKm/z18Mv0tmfwa8tb0Wp2+Z2ZXtKKijnkiKNjaAg3tE6ga5Cj7k9KCFFlyrChYvvCpm0Vvj8pBZfr7ewhjEVh59E6ey3t008caAJobuTS37ODFY52fJ8Od8eBXxXvObdyWQttzM7UXB4h75cNmQSaRJ3w9/enQ4cO9d2NBkE1G4xx7r8x5z6IufgxdO4hjCGTUM6gcu20zwOpG6yg0uFV6KRVkLqZyu+lA34REBCL8o+xgkvR3VHxZ0FcvyoHclRQE4zBz2DOvg9z0QRUu6tRgTU3PRXAaH81oDFnjkdv+QQTjTHiTfmCJU57MtY1bqWfg0+0wvKdsYpPUjQzM2BwMAQYVnbT/kJw+0O6TzEiDKYkWQEmE2tKXlIx7CrQtPGXcVDUr8KSemGb800CMw7RKWsNNm++NU3OsGMCy30xzDfa4LPbaV60j+cSn+JQ/Plsdvc5bn8+Tx67fcEovxiuaBLL1c2iCLLL77kQpwMV2QnT4QeefHAGHPe8W/m4Wa/n3fC+sA8Sstfj9uZQaA+qYG9HDfNtYYejKemmPzMzYKQ1C/eknAaE22BGBvQK1DR1yVjSUDW6+SqLFy9mzJgxjBkzhqeeeuq4bc8991w99/D0cmy9kaVLlzJs2DCCgoKIiori7rvvpqCgAICZM2dyzjnnEBAQQExMDP/4xz/w+XwV7uf3Fi9ezJAhQwgICCAiIoLrrruOAwcOVNqn9PR07rzzTmJiYvD396dv377873//q/a5FRcX89JLL9GrVy8CAgIICgpi0KBBfPfdd9XeV3UZve/HGPwsAHrtm/jebIHv+xvxzfkLvhlj8H54Fr7/hOL7oB/mL/egN06D1E2AhqBmqHZXYQyehHHl/7DdvBzbnXuxPZiP/d5k7GPXYbtuFrZLpmH0fQDVZEC1s4VU99shtg8UZ2Mu+EfNXwDAaH8NxkVTQdnRW6ajN9TsandCVIeMdaIqjg2Gm5UUIx0YbE2HyzetGk0t3ZDqsYqEe0zNviJo56cYFmq1T/VAF3+Y3Apa+MkHZlF3fD4fzz//PG3atMHtdtOmTRv++dSzvHPYGtPsRRm0TVuKDRP8o8nLymHWK//l5etHM+f8nvgui6fp38/i/rUT2dpyFFnuWDIPJ/HUoHPJSkomKymZpwady7PnXsan5w8h4IfPGd3iaJBp4cKFXHbZZURGRuJyuWjbti2PPvoo+fkVFyxbtGgRV155JTExMbhcLpo1a8ZVV13F4sWLAatm0hNPPAHAsGHDyhYNatGiRbn9HDlyhAceeIA2bdrgcrmIjIzk6quvZuPGjRUet7pjtxCNSmgrVGATyE+utEm8ymWEO4ODfq0wMLlxyyM0zdl0wt067C6uKP4NhWZ9PnycCkdOMDmj3PGc1kIbX6dqik5050fUq0aX0bRz507ef//9ctt27drFrl27ABgyZAgPP/xwfXTttLZixQqef/55LrjgAu644w7mzZvHG2+8QXZ2NldccQWjR4/m8ssvp3///syYMYMXXniB4OBg/vWvf51wv3PmzOGiiy7CMAyuu+464uPjmTNnDueccw5hYWHHtc/Pz2fo0KFs2LCBAQMGMGTIEA4cOMB1113HiBEjqnw+RUVFXHjhhcyfP5+ePXty22234fF4mDFjBldccQWvvvoq9957b7WvU3UY/R+C6G6Ys/8CmTvRWz87vpErFBXXF+L6omJLHjWcXVQRZdiwnf8avg8HoDd/jO52K6rZkBo/jtFuJOQmYi78J+bCR1AtzreWUhWinshYJ07GUFZGU2UfbZVS3BkL9+3W/JwJt8fA7kIIMWBfEUQVaHoHKs4LVUQ7NG8nWVlNW/IhywsRMptI1JHbb7+dKVOm0LJlS+655x4KCwt5/T8v456zFAC3NwecQWB3k56YyIf3P0h2SioxfQeQP+hPuNP2kb7gKx5Zu4GbJvenSeeOuAMDGTz2FlZ88RVoaHvVnwjyC2RgdDgXDx9WFqx98803ufvuuwkLC+Oyyy4jKiqKVatW8cwzzzBv3jzmzZuH0+ks6+t///tf7rvvPvz8/Ljyyitp3rw5iYmJLF68mC+//JKBAweWFS9fsGABo0ePLgswhYaGlu1n165dDB06lMTEREaMGMHIkSM5cuQIX331FT///DNz5syhf//+Ze2rO3YL0dgow45qNgS99VNI24IOTkA5/I9r159EFjW/iogdr9Mkdyu3bvwLGyOGMqf5bWS5K/juYnfTNO8wI+zb+MVoz65CxZtJ0DsQhgWD/wnukSsFLV0wPwtSvZrLwq3XGTIzomHRosqysrI0oLOysk55H6ZpatNb1PAfpqm11nrevHka6/O0/uabb8rOo7i4WHfr1k0rpXRkZKReuXJl2XPZ2dk6OjpaR0REaI/HU24/jz/+eFk7n8+nW7VqpZVSetGiReWu0ahRo8qOe6zHH39cA3r8+PHltv/8889l7adOnVruOUAPGTKk3LZHHnlEA3rixIll51ra9z59+min06kTExOr/g/7B5imT/v2zdW+5c9r78JHtW/Zs9q39Sttpm0r17f64P35bu15waY9U7pp01t83PNmUa72Lnpce6YP094fb9Vm+s5qH8M0fdr7+UXa83KQ9s4YWxPdFn9QTY11Rb6G/5Cxru7GusaiyGfqPK+pi32Vj8+ZHlP7L/FpFvn0Q7t9+s+7fPreHT5941affjXRp7M8Pm2apk4pNvX3qT49dptPP7/fpwtOsE9R82pirCtlmqY2i3Ib/uN3Y1737t11bm5u2XnM2X5Au8IiNaC7XThCT5j1hZ6waK5u2qWzNmw2feNLL+h/LpqnnQuLNIt8+uPHe2p/t11Ht2qlJyyaW/YIiY3RIbEx+v5fZuib5q/QO1OTy46xadMmbbfbdc+ePXVaWlq56zhp0iQN6BdffLFs2/r167XNZtPx8fF6z549x133Y8ew0rFz3rx5Ff47nX322dput+tZs2aV275t2zYdFBSku3btWrbtVMZucWapyTGkITNNU5spG7V32bPa++112vP9zdqz8FHtXTyx3MOzaKJeP+c5vXLaJbroBbv2vGDT+f/n1vM+ulE/Ne/7cmPEhEVz9YSFs/WE2V/re2b9oNsvStIsst43XYt9esQGn350j08/vrfyx8O7ffq6LT59wxaffvGAT2/LN+v9u5M4qtFlNDV4pgdz6ZP13YuTMs5+DGxH7yQNHTqUK664ouxnh8PBNddcw/r167nsssvo27dv2XNBQUFceumlTJkyhYMHDx6Xslxq8eLF7N69m8suu4yBAweWbVdK8eyzz/LZZ5+Vm5IC8MEHH+B0OnnyyfLXcMSIEQwfPpw5c+ac9NxM0+SNN96gTZs2PPbYY+WmQgQFBfHYY49x+eWX8/XXX9fJnX6lDFTzYdB8WK0fq7qMQU/h2/4VpG7CXPY0toFPlD1n7puD+fOdkLUHAH1gIb5dM7CNWogKb1flYyhlYAx5Dt8ng9Dbv0T3fQAV1bXGz0XULY+GJ/Y3/HTmx5srnMfcAJOxTpzMyQqCA4TYFaOiNO8mw08ZcG0E7PaCT0OeD3YWQK8ghULjb7Om23X1B/dptry7OIYnH99/Qk7erp7Z/pwFzgA++OADAB577DECAo7WXTm7dRN6jLmfFS8/hnIGA3B46xYObtxEj0suplXfPoCmnUpjIzEs7zya2/s+wORFuzmyew/RrVqWO16w283+Ih+/bV9Gq34XoWxO3nrrLbxeL6+88grh4eHl2j/00EO89NJLTJ8+nb/+9a+Alf3k8/l4+umnjxtnlVLEx8dX6dzXrFnD0qVLue222zj//PPLPdeuXTvGjx/PSy+9xMaNG+nSpcspjd1CNEZKKYjsjBHWDg4tw9z5g5Xd5BcBAXFlny+Ugk6uQopb9+fX2LMI3fsd7bJXM/DQp/RImcn8ZmNYE30hWpWkKykDXKGEm16uLVjEXiOSWa7eJOsAZmXCr7kwIhTauSuu3+QyoIMf5PhgWQ5syNMMDoGLwyHWKe+n9U0CTaJKevbsedy2uLg4AHr06FHpc4mJiZV++Vq3bh0AgwYNOu65hIQEmjVrxt69e8u25eTksGfPHjp16kRs7PEpmIMGDarSl69t27aRkZFBfHx82Vz+Y6WkpACwdevWk+6rsVN+4RjD/o3542j0smfwaR9Gi/Mx109Fb/7IahTUDKPf3zE3TIUja/D9OAbbjYtRquol4FR0N1TbK9E7vsb87RVsF75TS2ckxInJWCdOpvSj68nKQvyrmWJ6imZDPgTYoLMfRDog2QNbCqBXkBW08jOsPwu1fCgWdaeyccltKAYNHMiKlwGHPwTEkrhuJgB56eksmDINAI0/EM27ZgFDrKGEzD07jws0KRQhDoOlOYpLd8zAr/1Ili9fDlg172bP/t3qdFgB/mPHpZUrVwJUa9pwRUqPm5SUVGEdvdJjbt26lS5dulR77BaisVM2BzQbjBHTE713DuyZCSkb0MHNUO6jU0mdyqR/IKR3uoqFGcNpt+8zYgv3c+nuyfQ9/A2/tLiT3aG9j+7YsINfBC18RYzL/5F1jrbMc3Qm3evg01RrmtwFoRDjPL5PAEEl77FpXvg+HVbmai4I1QwPVQTLwgP1RgJNdc1wWNlCDZ1RvkhEcHDwcU3sdvtJn/N4Kq/qlpWVBUB0dHSFz8fExJR7A69K+6pIT08HYNOmTWzaVHmhury8vCrtr7EzOt+ITt+KXj4Jvfw5fMtLC+orVI87MYY8i3IGodpejm9KVzi8Er39G1T7Ey9tetxx+tyPb8fX6G1foc+ZiApqUvMnI+qMQ1nZQg2d43ddlLFOnExpCL1kzkylq2W2cCvebQujtmmW51iZTFeEW3WaMrxwuMjE36ZwG9a+Ck6UIiUaPoe/lS3U0JXUVsnKysIwDCIjI49r0qu5FeDWgAprR0GuVZx7x7Ll7Fi2vFzbAmBmyd9bH5oNlM8UAogxitjtjGP93hn0D2tZNjY988wzVepyZmYmSqmywP6pKj3ujBkzmDFjRqXtSsfE6o7dQpwplDMI1W4kOr6fld2UuARyD6NDWpSr3xRuFDEkws2u0HuZn7yDPgc+I6ZgLzdteZgdof34JeF2Uv0Tju7Y5sTwj6an9zCd8naz2N2dFbaW7CkyeCsZegbAuSHWzZvj+qSsmznhdjhcDB8egcXZmkvD4ZxgcErGcJ1rdKvONXRKKZTN2fAfdVBMLSTESjE/cuRIhc8nJ5df3aD0S15V21emdD9XX301WutKH1OnTq3S/s4ExsAnMS77BOL6QnACqu1IbDctxXb+qyintXypCmqK6n0fAObKF6p9DBXTCxU/ALQXvfmTGu2/qHtKKZxGw3/IWCdjXXUppcqymk42OfT6KMW7bawsqA35MDcL7AoKTVifb30IcxmgtbWtsUtMTGTy5MmMGDGC5s2b43Q6iY2N5eqrr2bFihUVviY7O5sHH3yQhIQEXC4XCQkJPPjgg2RnZ9dx709MKYVyBjT8R8mYFxISgmmapKamHncu/lnWGFNsAv6RuMKtGz8X/uU+JiyaW/botigRFvkYPnsVnhdsTGyzhqY5m4/bnwsf2u7Hr6oZ5uaPCQ60vohmZ2efcGwqFRoaitaaw4cP/6F/o9Ix8dVXXz3hcUePHl12jeCPj8Wi5jTmMeR0pALjMbqPx9bv7xDdHZW9D52xC216y7VrbcthcFwcW3s+zpK4q/EqO20zV3Lnutu5cPer+Hl+F6S3++MKCGe4bwt3FfxERzMJDazOg1cPw5Js8FbyBmwoaOKCTv7WynSvH9Y8e1CzOldXulqsqB0SaBL1pnv37oC1XO3v7du377ilY4ODg2nZsiU7d+4kKSnpuNdUtJ+KdOzYkeDgYH799dcTZiGIo5RSGB2uxX7TMux37MI28ktrNbzfMXrdZ2XDJf2KTl5b/eN0sT7cmZs/LvchU4jTmYx1jU/pjdGqxIZujFbcXTIDcnkO2LCWcN5dCLk+jUtZAaszIdD06quv8sADD7B7927OP/98/vrXvzJw4EC+/fZbzj77bD7//PNy7fPy8hgyZAgvv/wy7du354EHHqBTp068/PLLDBkyRLLx/oATjUvrl1rbirQVJG064CIADm5YX65dJ6w5cytcnfkt6gIUmst2/RubWYxhGGjz6C91FHms8e9GSlYq/VpbN6hKp7KdTL9+/QCYNWvWSdvabFaqQ0W1k0pXk1u2bFmVjlvdsVvUPhlDGh6lFCqqC0a/v2P0vBsVEINK24LOPVTus7xNafo6M+nZojuLuj/D+rCBGJj0S/6O+9aM5qxDX2Azi4/dMziDCHP7c03xckYXzieWHIo0zM6C1w9bq7VW9nXBrqCVG1q7YWs+vHhQ859Dmp0F8v2irkigSdSbgQMH0rJlS3744QcWL15ctl1rzSOPPFLhh4Sbb76Z4uJiHnus/PTDWbNmValmCVhTXe666y727dvH3/72twq/gG3cuLHSO1iicso/CtV2JADm+veq//o2V4AjELJ2W2m4QjQCMtY1PqUfnk5Wp6m0zS3R0MXfCkwtzbGCSqaGrQVWRpOpoVjT6APs/fr1Y+HChezcuZP33nuPSZMm8eWXXzJv3jxsNht33XUXRUVFZe1feOEF1q5dy0MPPcSsWbN47rnn+Omnn3jsscdYu3YtL7xQ/exZYbnlllsAePLJJ8t92U5MTOSVV14BrOL1WkPTvkNp0qUbG+cuZNPsuWVtW5GBGw+5poMnMy8k1xFGVMF+Bh38BHdwMPmZWXiLrC+OEeSTrvxZGzqAOwcFYLfbuO+++yoM1mRmZrJmzZqyn++8805sNhuPPvoo+/btK9f295lOpcXFDx48eNx++/XrR//+/Zk+fTqfffbZcc+bpsmCBQvKfj6VsVvULhlDGi5lc6CaDcY45zFUp5tQKFTqRnRhRrl2AcrDuf65RHe4jBmdnmC/fzvcvjxG7Hubu9aOp0PaovLRI2WAO4zmTh/jCmZxefGvBFJMhg8+T4P3U6ypcpVxlxQMj3VYmVDPHNBMSzZJLm7c77cNgdRoEvXGMAzefvttLr74Ys477zyuu+464uPjmTt3LocPH6Zbt26sX1/+7tlDDz3E119/zTvvvMOmTZsYPHgwBw4c4PPPP+eSSy454Zz7Yz3xxBOsXr2aV155hRkzZjBkyBCioqJITExkw4YNrFu3jmXLllU6L19UTnUfh972BXrLJ+ihL6AcflV/rTMA1e4q9KYPMDd9hK3pwJO/SIgGTsa6xqcqK88BmFqjgXgnXBwGm/JhcwH0DbRqMm0vgLZuCC+pK+HVx9cNa0yuuqri2n2DBg1i2LBhzJo1iw0bNtCnTx+01rz77rsEBgYeF3D95z//yauvvsp7773HxIkT62QKbGMzdOhQxo4dy9SpU+natStXXnklRUVFfPbZZ5x11ln88MMP2BXkmRBog6te/ZQPrh/K1088zYovvyaufVvsTifu5H9TuGktP2Wm8OPnj3Dt9ic559CndO46jNlbt/Hpw/+iebeu2Bx2jG7nsLRbWx7t0IrX7srlntdX0L59ey6++GJat25NdnY2u3fvZsGCBYwZM4Y333wTgK5duzJ58mTuv/9+OnfuzMiRI0lISCApKYmFCxdyySWXMHnyZACGDRuGUop//etfbN26lZCQEEJCQrjrrrsAmD59OsOGDeP6669n8uTJ9O7dG7fbzf79+1m2bBkpKSkUFhYCpzZ2i9olY0jDV1a/Ka4v5q4ZldZvilO5XBICm7rdzQ8p+zln/weEFx3i2u1Psi+oK7Na3MnhwGNWsTbsKL9IuvvS6Zj/A0ucnVlub8u+IoO3j6nfFFhB/SaAYDt0tkGqF75NgxU5mgtDNcPDFIE2+fevDZLRJOrVeeedx5w5c+jfvz9ffPEFb7/9NgkJCSxevJiwsLDj2gcEBLBgwQJuv/12duzYweTJk9m6dSufffYZ11xzTZWP63K5+Omnn3jrrbeIjY3lyy+/ZPLkySxcuJC4uDjeeOMNunbtWpOnesZQzYdBSAsoykLv+Kbarzc63QiA3vkd2pNfs50Top7IWNe4HJvRdKIspNJAVKTDKg7epeQz9pYCKPBZGSPbC+HcUMWwUIXjDC5W6nBYi5CUFtjfsWMHhw4d4pxzziEgIKBcW7fbzeDBg0lMTGTnzp113tfG4p133mHSpEkopXjttdf46aefePDBB8uCNn42SCtJhAxv2Z7bv/iRgaOupDg/n7UzZrL62x/w7VgP3QfhePx9NkcMYkv4QGzaxytn7aHXZReTsmcvC6d9wNy33iXn14XsIoydAR0Zd34Ci18bxRWXXsiyZct4+eWX+fLLL0lNTeWBBx7gL3/5S7m+3nvvvcydO5dhw4bx008/8eKLLzJr1iy6d+/OtddeW9auU6dOTJ06lfDwcF5++WX++c9/8vzzz5c937JlS9asWcOjjz5Kbm4uU6ZM4a233mLt2rUMHjyY6dOnlztudcduUX9kDGlYVFCT8vWbsvahM8vXb1IKuhhpXBAdxMaeE5nd5GaKlIuEnA2M23Avl+98gaCi39WRs7lw+kcwTO/mroIf6WweAmBNSf2mRSeo36QURDmgqz94THj/CDyxX7MgS1NclRRlUS1KN/Y87RqUnZ1NSEgIWVlZFa4+JISw+JY8gV76FCphOLZrf67Wa7XW1up1OfsxLv4Ao93I2umkqJSMdUKcXKGpMTU4DbBXcje82NRlWUo/ZsBP6Zq3ksGl4M9xkOACtw2uiFBENOZUppPYv38/7dq1IywsjIMHD2Kz2ZgxYwaXXnop9957L6+++upxr/n73//Oiy++yIwZM7j44otP6bgy1p3Y9CMmX6ZZX8oAtOlDH1wEhengFwGAD8XLDKAABzexjq7Fu7hr7Tj8fLn80nw8y5pcW26fG4jmGjZznV6PSt0MzYdh9LwTZcgkC3HqZAxp2LTPA4eWYe78HjL3oP0jICDuuEyyTO1iUVEIkftncFaqtZ5lseFmafy1LIu/Bo/t97MkNBTncMAMYJarN4eUVcA/1AbnhUInPyu4VBmPCfuLrensXQPg8nBFtwAwJMOtRsioLoSocUbnW/AtfQq9by46ez8quHmVX6uUQrW/Cv3rZPT2L0ECTUKIBsiGlbHkMcGnNL6Swsku4+iHVF/JrTxDQZwT2pXUiUjywMYCq9hykB0OFWnC7ZyR0zc8Hg8333wzRUVFvPDCC2XFnEuXli9d+ev3Sr/UlbarTOfOnSt9TmrsnFgHf4U9XVNsWgFVZdggvB360HLwFYPNiQ1NB1JYQzybiKKlM5NZLe7kil0vMvTA++wN6VFu+ksYBSynKZer7fiFtkIdXIQObYVqfWpf9IWQMaThUzYHNBuMEd0DvW8O7PkZUjeig5qAK6zsvS9UFXGZ+wh72p7Pp7Hn0Wvfh7TLWcfQgx/QJ/k7lsZfy28xlx4TcFLgDKaZNrm1aB4bVDxzXd3J9Ln4Mg3au+GKcCs7syIOwyoWXmBaU9u35Wv6B8FlEdDSfea9H9c0mTonhKhxKrQlqvlQQKM3flDt1xvt/wSA3vMzukiWnz1WXl4eH330Eddeey3t2rXDz8+P0NBQhgwZclzKvxCi9tiVFVjSHA0oaaCoZL6cLqnPBNaHrTinFYAaVHLTe3UuJBXDb7nwehL8kK7xnWFJ5qZpcuutt7Jw4ULGjx/PzTffXN9dEsdo62fVDss4dqXygDgIjIfCTNDWl+zOJavPbSEKH4p1USPYHnYWDl3M9VsnEFSUUvbyGPI4TBBriEU5A9GuUPT2r9Gpm+rwzERjIWPI6UW5gjHaXYlx9gRoMQIKs6yC4fmp5aaht1SZXBeURVbnO/is7QSSXU0I9GQyYt/b3L/6FgYkfo7DV3DMjg2UO4xujhzuLviJwd4t2DDZVghvJsP+ogo6cww/Azr6QbQDFmTBswc0P6ZrPDKd7g+RjCYhRK1QXcag98/H3PgBasAjKFWNuHZkFwhrBxnb0bt+QHUaVXsdPc0sWrSIm2++mYiICIYPH87VV1/NkSNH+Prrrxk1ahRLly6tMEVcCFGzlFK4DGtqnAJsygoyacBjakrLLRnKahvr0CigewB8n25lNTkU+BuQ77PupvYPgmhnPZ5UHdJaM378eD766CNuuummssLPpUqzECrLNsjOzi7XrjKbNlUewCid9iIqFmhTtHFrfs2FmJJtSimI7oH2FUNeMvhHkqAyCaSIXFzsIpx2Ko2v2zzMrRv/QnTBXq7fOoFpXV7GY/PDgYkdk3m04CydiBEYB+nbMDd+gNHv7yj/yHo9Z3H6kDHk9FVav4mEYZj756MOrYCUDeiAaPCPRikDQ0E/dZgOkU4+DZ+MmbKRqxLfIaroEOfvf4ezD33OsvhrWBV7xdEMJ8OO0y+MIb4DtCtI5GvXWaQTyLQjmqEhioFBcKJSiCF26GKDxGKYkqzZnA83RkOcU7KbToVkNAkhaoVqdxU4gyBrN3r3j9V7rVIY7a4EQO+eWRvdO23FxcXx8ccfc/jwYT777DMmTZrEe++9x9atW0lISOC1115j1apV9d1NIc4IhlI4DauIt/V3a7tHWw+wptgBOAxFlAMCbIpLrBXYSffBwGCrNsQl4RB9hnyYNU2T2267jSlTpnDDDTcwbdo0DKP8R9K2bdsCVkHfipRuL20nakdHf8XvVwFXdjcqtjf4R0BBKobWZVlNG7FWsCy2BzC9w1PkOkKJy9/FVTsmoUoyoJqQzRai2Eg0Sil0WBvI2Im56SOrlosQJyFjyOlPKYUKa4ut+3iMcx6DdleitGllOOUkok1rvAhWxdxmbKB5TCse7fElb7V+nDRXPAHeLM7b/x5/Xn0T5yROx+k7ZgEhm4s4PwfjzOV08e5Do5iXBR8le8k5yWxHpaCpC1q6YGkOPHNAsyhLY55hGcc1QQJNQohaoRz+qB53AGAunojWJ1sI/Hevb3E+AHr/vLI3GwHdu3dn1KhRZaurlIqJieGOO6zrvWDBgvromhBnPJtSlK6SXJpxf+yqyXEl2UojQq0/Z2VCtteahtfaXVe9rF+maTJu3DimTp3Kddddx4cfflhWU+VYbdu2JT4+niVLlpCXl1fuucLCQhYuXEh8fDxt2rSpq66fkVq4wamsYrnHUo4AVEwfcIVCYRpdSAZgGxEUl3y9yHLH8nn7J/AqB+0zljF833sABODBi8ECmqM1KMOODm0NiUvQu3444UqOQsgY0vio4ObYOt+EMfBJVMcbUDYnKnUzOns/2vRiU5qL1U7uMVazK/pc7u75PV+0/gdp7nj8vdkM3z+F+1ffxMCDn+D0Hv23dtkdjLTv5XLfBhzayx6PnbcOediRU3jSPgXYoIuf9R79+mHN20majMqWsxMVkkCTEKLWGP3+bmU1HVmLXvdu9V4c0wucIVCcBcmra6eDjczvl/YVQtS9YxePs6nyq9eUBpr8DBgQZC3BvDLXKiqefgYkcpRmIUydOpU//elPfPTRRxV+QQTrbve4cePIzc3lySefLPfcpEmTyMjIYNy4cWdkAfW6lOCCUDtkeY9/TrmCUbF9wBFAXME+wsnHi41tHJ3+djCoE9+2+TsAZx/+gp7JVoZzHDmsIY49hFr7cgag/SMxd3wLR9bU+nmJ05OMIY2bCojBaH+NFXDqNgblDEalbUVn7kb7iumukvkby+ijkvk8ehRP9/iE/7V5iFR3U/y9OZx7YCp/Xn0zgw5+jKsk4KSA7rZ0blNriNbZ5OHgk0w3vxxOxespOGF/DAWt3NYiHj9nwKQDmjW5WoLhVaS0XKkqkyUshag+87dXMOc+CI5AbGPXoUISqvxa3/yHwFuI0fMuVETHWuzl6c/n89GzZ082btzI+vXr6dKlywnbn2wVlW3btslYJ8QpMrXGBOy/+wJT4NO8nQQmGqeCe3dDmB3+2RQuCINuAY37/t/EiRN54oknCAwM5M9//nOFQfGRI0fSo0cPwFr8YODAgaxdu5bzzz+f3r17s27dOn766Sd69OjB4sWLCQgIOOX+yOe6qvn3QZNfc6H971cWL6HzU9BJq5ivWrLI3pG2pHE9G8u1GXzgQ4Ye/ACfsvFJx2fZHdKLjURzOdu5Ra0/2jB9BwREW/WaAuNq8azE6UjGkDOLLs5BH1qO3jsbsvaiDQcEN6PIFsBXdORH2uLERwudRpfU+Qw++DGRhQcAKLAFsiLuKlbEXUmRPRAADwa/0IrfaAJAUzODqwIyCA1rgrK5TtgXr4ZdhdbNpIvC4IoIhb9NgpQnIre9hRC1SvW6F7Z9BYlLMGfehnHtrCoXBrcNfaGWe9d4TJgwgQ0bNnDrrbeeNMgkhKhdhlIVpoz72RRNXZoDRYrWbk2UA1I8ViHwvoF13s06t3fvXgByc3N55plnKmzTokWLsi+JAQEBzJ8/nyeeeIIvv/yS+fPnExsbywMPPMDjjz/+h74giqrr6K9YklP5fWnlHwXRPemSvJVFdGQXYeRjx5+jaVALm95EROFBuqbO5ZptTzGl63+I9gtgCc24UO8kWln1VXRYa1TKRsxNH2L0vh9lP0PmlIoqkTHkzKKcQagW56ObDISkVZh7Z0PGDtzADUHZNHNk8ymd2aRi8USdz6bIoXRKW8Dggx8TVbCfoQc/4KzDX7Ei7iqWx10F9kAuZictyOQH2nPQCOPt/AAuzd1Ep9BgCGqOsjkq7ItdWcH2FA98kQrbCjU3RkFbPwk2VUYymqpBotZCnBqdsRPf+73Ak49x7ssYve+r7y7Vu8jISNLS0qrcft68eQwdOrTC595++23uuOMOevbsycKFCwkM/GPfWGWsE6L27CzQ/JAOPq1ZmgNfp1n1mZ5vAVdHNu6MpoZGxrqq2ZKveXK/JsEF7hP8iurs/bydEUySEcrFbKc3h8s9bzOLuWXz32mWs5l0Vzzvdn2FlY523MI6rlDbj+7HW4DK2AntrsboeL1MbRINlowhdUv7iiF5Dea+OejUTSjTy86g7nzgPIdNRNGSDIIoRmkfHdMWMfjgR0QX7AOg0BbAirgrWRF3FYX2IDJw8z86koj179bHs5PzjX04wlpBUDOUUXk+TpEJOwshxAYjI+CCMGtREFGeBJqqQQYTIU6dueYNzNn3gd2NbfRvqPD29d2lenXfffeRk5NT5fYPP/wwHTp0OG771KlTue222+jSpQvz5s0jIiLiD/dNxjohatcP6Zot+ZoUD/xfolVDYmJTeDRBlavpJGqXjHVVk+/T/HWPRmuIdVbeTgPLjqTxS1EEzc10Rhsbjmvj78ngtg33E1aUxL6grjzX6XXcBjzFfIJU8dF9FaRCYQa2nnejmpxdC2clxB8nY0j90KYPUjZg7p+DTl5Hlqn4OOhSFjg6EE4hceSWNqRj+iIGH/iImIK9ABTa/FkZeyXL464izxHCPFqyjGYAxJhZXFW0jEi3ExXaBoKaVjoLQ2s4VAwZPugfBKOiFE1c8v59LAk0VYMMJkKcOq015hcXoffNhrh+2EYtQhkVF3AUVTNlyhTGjx9Px44dmTdvHlFRUTWyXxnrhKhdWmu2F2jSvHDdVjhYDOcEwdyu4DQkq6muyFhXdS8fNFmRCx0qqdNUKssLkw9rQHG/dx4h9uN/n6Py9zJ2459x+/JZEzWCSa1f4E71G8PV3nLtdOZulDMYo9/fqlXfUYi6ImNI/dJaQ/pWzH1z8Sat4Sfdmq8DhlJs96cN6UensGuTDulLGHzwI2LzdwNQZPNnZewVLI+7hg2OBL6lA/k4cWgvF3nW0t27F/yjrIBTYHylmZX5PthZBPEO+FOUYlAwcsOohHyaEULUCaUUxoXvgDMYDq9Er3qpvrt0WpsyZQrjxo2jQ4cOzJ07t8aCTEKI2qeUooVb0SNAcUu0tS3ZA2kVrOwlREPQwV/hqcKt6RA7JJTc1d9kRoD3+GXEU/xb8FW7RzEx6Jkyiz8deod5tKRY/+5rSUhLyEvC3PgBuji3Jk5DCNGIKKVQER0xet6N8+xHuKxZDPcX/0JM/j42eYMppOSGtjLYGjGIt7u9wWftHuewf2tcvnwGJU7n/tU3cfu+F7nfM48WZOBRdr5z9uFbv3MoLshEH16OTlyCzkuioiHQ3wZd/CDHB28c1rydpEmvymB5BpBAkxCizqjgZhjn/hsAc8lEdOrmeu7R6em9994rF2SKjo6u7y4JIaqp9H7nFeHWn4eLIdwud0FFw9TCDU4FheaJ2x0uPvq7vcXVGoqzwVd8XLvEwA7sDu0NwJ/2/xcjZz9riS3XRimFDm8LR9Zibv0crU9ycCHEGUkphQptha3brfQecBt/j/fR27efHUV20ou91jw3AGWwLWIg73R7g0/bP8ERvxa4zAIGHvqUf669kduL59OVZADWqzim+w0BVwjkJ6MTl6ITl1mrbP7u+IaClm6Ic8DPGTDpoGZ1rgSbJNAkTtnevXtRSjFmzJj67oo4jaguY1AtLwRfEb6fbkWbcgu/OubOncv48ePRWjN48GDeeOMNJk6cWO7xzTff1Hc3GxUZ60RtKP0y3j0AElxwdrC1mo0QDUmBT7MyR/NzhkYD+RXEegpN+DUX3k6Ct5Nhb5G1PdTwgiMAirIAUNpH64xVrP3Hjfxr2BXYd68EoFi5KFYOthNebr/aVwz5KaB9cGQt5B6qxTNteObPn49SiokTJ9Z3V4Q4baigJjjbXk6Xpm1JcGp26zC055iMSK1plrOJjmmLCC9MBCDHCGRa1M28YR/CBmLKmtrQYDjAXTI2Ze1Gp6yD4rwKj+1vWAXC1+fB9BRNtvfMDjZVXk5dCCFqgVIK44K38E3tBkm/ole9hOr/UH1367Sxf/9+SkvrvfXWWxW2GT16NCNHjqzDXgkhqksprOrJSrGzD9ilpoNoILTW7C2C33I0S3IgsSRwFOOAMFtpGzhQDGtyYVMBZdPqbGjak0qv4u208BwCu4tw8umx/z26pcwmuDiVOUVWtOqgX0uWtriKlMh+XOzIoReHraylgnRU/hGrJkpAHHQ8DyO2FwQ2KevjtGnTGDt2LFOnTq3zmwBKKYYMGcL8+fPr9LhCiMoVmZoNGdmsTDrEbxl5pBf78DM9dLLloByBuLx5dEv5hV7JM4gp2IsGVgT247/xf+absMspNFwAGJi0I42eJNHKlwTFuVaw2xEAYe1QQU1QzoCy42oNmT5r+rtPQ7wTLgqHfkGK4DM8S1kCTUKIOqeCmmAM+zfmzHGYS59CdbgWFdKivrt1WhgzZoxk1gjRCJR+/NRIkEk0DNlezdo8WJqt2ZJv1RwJtUMbNzhL5kDk+2BdvhVgSjkmITmSAnp699CteAf+yofTZtAp9zd6pPxM85xNZe1y7CEk+oUCu1nb4QEuivPRik0oTy7kJaO8+Vb2QNNBGPH9ILILyuFfp9dBCHF60Fqzr8BkdfIhFqdkcjC/ENPrIUrl0tmuMRwO4vP20nvfD3ROm4/TLCTVHsHL8Q/wZuzd7HYdXWQgnHx6cphuJBHoyQRPPhh28ItABTeHwDiUzVXWvtiEJA9keiHYDr0D4ZxgRfcACLDJezpIoEkIUU9Ul9Gw6QM4sBBzzl+wXfVNfXdJCCHqTFmg6czOrBf1zKc12wvg11zN8mzrrrxdQawDWriszDutYXchrM6FrQXgK3mtHZPOOomexdto6ktD2d20KN5D95RZdExfjNO0CoGbGKwNPYdl0ZdQENYRx6xngd1cqrfQIrcYVZiBtrtRIS1RTc9GRfdEBcRU2mchxJktx6tZm5HD0qQkNmflklXsJcTMoaWtGJfLhdP00CV1Hr2TfyAubycminkhw3g97l5+DL0Qr7JCIHZ8dCKFniTRzExFFeeC6QG7v5W9FNjECjSV3AzSGjJKspe0hiYuuCQc+gQqmruodGW6M5XUaBIn5fP5eP7552nTpg1ut5s2bdowadIkTLPiooxHjhzhgQceoE2bNrhcLiIjI7n66qvZuHHjH27fokULWrRoQUZGBuPHjycmJgY/Pz/69evHd999V6PnLWqXUgrb+a+DYUfv+gF9cEl9d0mc4WSsE3Xp2IwmIeraq+9NRSnFVf+eytP7Nd+kWdPfOviBe+18/tPGxqyXn2BRNrx6GD7sYGPTuHPxZaTgN2k0zssiYXgAqbcPx71mLkPSZnLfxru5ZctDdE+djdMsZH5GPH2mNyfocTtDH1jB189N4YK9M4j2ZQCgsvai7G5oeyW2AY9gnPM4368v4rzLRxEWFobb7aZLly68+OKL+Hy+sr6PGTOGsWPHAjB27FirEHDJ41g5OTk8/vjjdO7cGT8/P0JDQ7nwwgtZvHhxhdckJyeHJ598km7duhEQEEBISAg9e/ZkwoQJeDyesppJAAsWLCh33GnTppXb17fffsvw4cNPeB6lCgoKePjhh2nWrFlZ23feeeeU/22FaIx8WrMl18eHuw7yj9VbmLxpB78lHyGkKJmutgwS3AbNiw9y8Z5XeODX67l092R8ngKebvovWvbZx4WdZvJd2KV4lZ1YcriI7TzAMq7wrKF5/k5UUTa4QlAxvVEJ52JEd0f5R6KUosiEfUWwoSTTs18gPNhE8WyC4upIgwT38eOPkIwmUQW33347U6ZMoWXLltxzzz0UFhby0ksvsXTp0uPa7tq1i6FDh5KYmMiIESMYOXIkR44c4auvvuLnn39mzpw59O/f/5TbAxQXF3PeeedRUFDA6NGjyczM5NNPP2XkyJF8+OGH3HjjjbV+TUTNUBEdUF3Gote/g7lkIrbrfqnvLokzmIx1oi6psiJNVvq/fEgVta3Y1GzOhxU5mq9Srd+9Ix5o64TAktpLZkntJYDlOUDW0df75RzBcVdvAvxdJJx7DvaU3SxbspkpDz/LHX82CItVFNgCWBxxId/nd2fKE8/gKSjgssGd6RAfyKpN+xh61zt0axkBgNFtLEavC1DOQAAeeeQRJk2aRNOmTbn66qsJDg5m4cKF/P3vf2fFihV88cUXAIwcOZLMzEy+/fZbrrjiCnr06HHcuaanpzN48GA2bdrEoEGDuOCCC8jKyuLbb79l2LBhfPHFF+VqGaampjJkyBA2b95Mjx49uPPOOzFNk61bt/L888/z17/+lRYtWvD444/zxBNPkJCQUG4a+7F9qOp5AJimyeWXX87s2bPp2rUro0aNIi0tjQceeIBhw4ad2j+0EI1IikezOj2XxclH2JWdS2FxAeFmNu1tHuwuP+wmdE6bS5/kGTTJ3YpH2fkx9GLejLuLucHDMJWVV+PCS1eS6UEScWYWeHLAWwwOPwhpiQpqCv5RqJL2WkO618peUgqaOuHycOgTpGjqlOylKtGiyrKysjSgs7KyTnkfpmlqsyi34T9MU2ut9bx58zSgu3fvrnNzc8vO4+DBgzoyMlIDevTo0WXbzz77bG232/WsWbPKnfe2bdt0UFCQ7tq1a7nt1W2fkJCgAX3uuefq4uLisu1btmzRfn5+OjQ0VGdnZ5/yv4+oe2bWPu150a09L9i0eWBRfXdH6Job63K9Df8hY52oT/leU+d5Te0r+T0UdasmxrpSDXXMy/H49PY8n/78iE//eadPX7vZp6/e7NPDnntPA/qK/3tPP77Xem7QOp8OWurTvDJHA5qxj+lmC9P05XNWWD+DHnLJQL1syiU6999B2vOCTb91jdKAvnpwjH7p6+f0A/Pn6umLPtP9erTWgH7/oXO193/XaM93o7R3wT/1w3f+qWxfe/bsKbt+s2bN0oC+6KKLdF5eXrnreuedd2pAf/nll2Xbp06dqgE9derUCv89Ro0apQE9ZcqUctuTkpJ0s2bNdFRUlC4oKCjb/qc/Wf165JFHjttXUlKS9ng8ZT8DesiQIRUe91TP48ILL9Rer7ds+/r167XT6dSAfvzxxys8lqh/NTmGiKMKfab+NcurX9+eqG9bvlVfOe9XfcMv8/QDv3yvJ8yfqScsmqtf+XmKXvzB1Trn38Ha84JNb36lvf7bp8/riHkpmkW+skfzRWn6ikUb9cOL5usJ82boCT9/pifM+lxPWPCzfmzNVv3Y9mz9+F5f2ePh3T49eqtPX7nJp8du8+nJB316ZbapC3zyPl1dktFU1zz5+P4TUt+9OCnbn7PAGcAHH3wAwGOPPUZAwNEK+02aNOHPf/4zEyZMKNu2Zs0ali5dym233cb5559fbn/t2rVj/PjxvPTSS2zcuJEuXbpUu/2xnnrqKRwOR9nPHTp04NZbb+W///0v3377LTfddFONXQtRu1Rwc1SXW9Dr38Nc/Rq2pgPru0uiBuSbELis4U8Kyh2gCLAhY52oF6X1bxr+/xRxMqfLmPeXOAixw9qSDKbEYthwBHYXHW3jxEsx0Nuzk4uLFhBEAd8B/k7FN2ctJTDVupN/xNUE18jLMP73JsuSgvhzVCS3spS0/btYuXYX3VqEcON5HSG2H7bYXhDRgX/1KuTNT38hMzOzXL9ee+01wFpN1d//aPFvpRTPPfccb731FtOnT+fqq68+6Tmmpqby2WefMXz48LIpdqViYmL4+9//zv3338/s2bO59NJLSU5O5ssvv6R169ZMnDjxuP3FxFS9XlR1z6P0veeZZ57BZrOVte/atSs333wz7733XpWPLcTpTGvNgSL4NSOXJclpHMjNwSzOJcqXQSe7ieHyx6YddEpbSO/kGTTP2UiB4ear8Kt4O/YOlgYNKNtXAMV0I4meJBGhc6E4D7wFYHdDUDOruLd/NMqwlRwb0kqylwwFzVxwZZCVvRQv2UunTAJN4oTWrVsHwKBBg4577vfbli9fDkBSUlKFb9Rbt24t+7NLly7Vbl/K4XBw1llnVdif//73v6xdu1a+fJ1mjF734lv/Hnr7/9DZB1DBzeq7S+IMI2OdqA9Sp0nUNT8DUj2wMd/6+ddcoCTI1NJMpadnJ+6iZXwCtPAkMmrPC7TK/I2HgLaRGoefPwsizmd+1BVkB7flbHWQqPCPcOemMiB7Mao4h3nbMgE4Z/AwjMHPolzBZccPDAykR48ezJ8/v1y/li9fTkBAQKWBFT8/v7Kx8mRWrVqFz+ejsLCwwjF3x44dgDXmXnrppfz6669orRk2bFi5wP6pqO55rFu3Dn9/f3r16nVc20GDBkmgSTR6OV7N2lyTZckpbMrMJrsgh2BvJi3Ixe1wg9OPiIID9Er8kO4ps/D35rDGvwf/1/I/fBx1Mzk2a+qtQtOGdHpwmLakY/MWgCfXiiK5glFhbSEw3vp7ybELTThcbNVdCrPDkBAYEKzo4g8uQ4JLf5QEmuqaw9/KFmroSpaSzcrKwjAMIiMjj2vy+zs86enpAMyYMYMZM2ZUuuu8vLxTal8qIiICwzi+jn1pf7KyToPrK8pRUV1RzYei98/HXPcWtkFP13eXxB/kb1jZQg2df8lQImOdqA/lVp5r+P9dxAnU55iX5dWsz4flWbCtEPJMCLVBtB2cJUOIx4SthfBRSkkNJmtBONx46ePdSg/PbsIMH3HFh/ClzeYToFPaQtpkHh2D8sJa8GCfD2hjy+MCDtJNz8U//xD/wIPPq1D+0ai2V5KTshuYQ0yrHuWCTKUqyhBKT0/H6/XyxBNPVHqevx8jK1M65i5ZsoQlSypfaKR0f6XZVU2aNKnS/k927OqcR1ZWFs2aVXxzrTqZVEKcTnxas6MAfk3PZVlKBkl52diKsokx02huB+UKwNB+dEhfSu/kH2iZvZYsWzAfRl7P2zF3sD6gW9m+QiikB4fpTjIhugA8eeApAJsTAuKs7KWAWJRhhT1MDaneoytsJrjg2hBFr0CIc8obcU2SQFMdU0qBM+DkDRuIkJAQTNMkNTWVqKiocs8lJyeX+zk42Pow8eqrr3LvvfeedN/VbV8qLS0N0zSP+wJW2p+QkIY/NVEcT/W4C71/Pnrjh+hznihLZxWnJ6WsKWmnCxnrhBB/RF2PeT6t2VYAq3I0K3KsL01OBbEOCLZZ0zIBkophdR6sz4OiktQ5hSaaHJKBcwvXMsgbSreMBXQ/8jMxBXv57rDVsMAWwP+a3MiCqMuBS3A6/PiHbRXNig+i8pJQPi/4RVjFdG1OjEFPoWxOQrd+D1grbVbk92MqWOOkUorU1NQ/fG1Kx9y//vWvvPjiiydtHxoaCkBiYmKNHLs65xESElKt6yTE6SzVo/ktx2RJcio7s3IoLMwi3JtGe/KwOwLAFkho4WF6HfqMHikzCfBksiTobJ5q/R5fRP6JQsMNgA2T9qTSkyRakoHyFUNxDmjT+p4d0QkV1ATcoWX3cApKspdyTQi3w7kl2Uud/cEp2Uu14vhbpUIco3v37gAsWrTouOd+v610xaRly5ZVad/VbV/K4/GUTUWpqD8VrT4iGj7V+lJwh0FuInr/vPrujjjDyFgn6oNMnRPVleLRzMrQPLFf88x+zXfp4NPQ0Q/a+1n1l5SCPB98eATeSoZVuVaQKVTnM7R4I/cX/MjQwDQA4vbO54G1NzNi31vEFOzFoxz8kNESgF/irmdf85GM8rMCMJG+DBJSl6IK0lGRXVG97sIY8iw4AsFwomxO4Oh4unjx4uP6n5uby9q1a4/b3r9/f9LS0sqmtZ1MaT0jn8933HN9+/ZFKVXlMbdPnz4YhsG8efPweDwnbW8YRoXHheqfR/fu3cnPz2f16tXHPVfR+5EQp5tiU7M6V/PG/lwe3nCQNzdvZefh7cRmb6SLPkS8y47dHQo2B+ckTuf+Nbcw8NCnuD05DOsyn2Fd5vNh9M0UGm4iyWMEO/kLy7hab6ZV8QFU/hEri8kvChXXF9V8OEZUZ5Q7FK2tlTU35sO+ImjigvEximcSFHfHG/QMVBJkqkUSaBIndMsttwDw5JNPlkv1TUxM5D//+U+5tv369aN///5Mnz6dzz777Lh9mabJggULTrn9sSZMmFDuw8DWrVuZMmUKISEhXHHFFdU7SdEgKLsL1eE6APSmj+q5N+JMI2OdqA+lWScSaBIno7VmYZbmsX2aNw9rdhdAvBO6+kOc05oCUirFA+8mWwW+DUw6+Q5yY+EC7vXMYZDjCMF+gfRq6kApWLJkC55iL4mBHZje8u9cF/s+n8y1MmmGqv38mWX0yy4J2Bh2VMdR2M55HOOshzGaD0O5w47ra/PmzRk8eDDr16/n448/Lvfcs88+e1whcID7778fgFtvvZW0tLTjnk9KSmLLli1lP4eHhwNw8ODB49rGxsZy7bXXsnTpUv7v//4PrY//H7ZixQry861CVTExMVx99dXs2rWrwilvR44cwev1ljt2Rcc9lfO4+eabAfjXv/5VLni1YcMGPvzwwwqPIcTp5NMUzfP7vczZuxN72kY6F26jja2AQP8QK0h9TKHt+NxtAGQ5o/i83QRWBFo36hLIZCxruJNf6U8i/nihoOT/V1h7VNNBqGaDUMEJZQFvgJ2FUGzC+aHwz6aKJ5srLgpXxMgUuTohU+fECQ0dOpSxY8cydepUunbtypVXXklRURGfffYZZ511Fj/88EO59tOnT2fYsGFcf/31TJ48md69e+N2u9m/fz/Lli0jJSWFwsLCU24PEBcXR2ZmJj169OCSSy4hKyuL6dOnU1hYyDvvvENQUFCdXBtR84zON+Fb+yZ6x9fo4tdQzsD67pI4Q8hYJ+qDZDSJqtBaMzMDPknRGEAXf2tlpIrsLIAv06wMpjCdz3UFC4lyGeB2AcHYzGKG7p/C2clfsLqb4rN1mvZvRhF0di+KM9ZzeNHLXNivNd8u2EywLwcjZRMExgKgQlpitL+qSn3+73//yznnnMMtt9zCN998Q9u2bVm1ahUrV65k0KBBx2XrXHjhhUyYMIGnnnqKNm3acOGFF5KQkEBaWho7d+5k0aJFPP3003Ts2BGAAQMG4Ofnx+TJk8nOzi6b8vzwww8D8Prrr7Nt2zYeeughPvzwQwYMGEBISAgHDhzgt99+Y8eOHRw+fLhsZbjXX3+djRs38swzz/Djjz9y7rnnorVm+/btzJo1i+Tk5LIpdueeey6ff/4511xzDT179sRms3HJJZfQtWvXap/H6NGj+eSTT5g5cyY9e/bkoosuIj09nenTpzNixIjj3nuEON108Ff8lGEj1qEJKcwGv+hK2/4aezkd05cQ4MkkKagD/VUiS2hOPg7iyS5fytDuAsNAhbdH2V0V7i/IZr3PXhOpiHBIcKmuSaBJnNQ777xDu3bteOedd3jttddo2rQpDz74INdee+1xb4AtW7ZkzZo1vPTSS3zzzTdMmTIFm81GXFwcgwcP5pprrvlD7QGcTie//PIL//jHP3j//ffJysqia9euTJgwgcsvv7xWr4WoZXH9IawtZOxAb/8fqsvN9d0jcQaRsU7UtXLFwIWogE9rvkrV/C/N+tIU76y87aoc+ClTo1E096XyJ8/KkkCK9ZsWm7uDkTtfILpgLwD33nUee352s27BUpL/9xktm0Xz9t8vIT4ykG8XbIaibGh6LUbHa4H/gqr6RIguXbqwZMkS/vGPfzBz5kx+/vlnBg4cyJIlS3jxxRcrnBb25JNPMnjwYF555RXmzJlDZmYmERERtGzZkokTJ3LjjTeWtQ0PD+fLL79k4sSJvPHGGxQUFABHA03h4eEsXbqU1157jc8++4yPP/4Y0zSJjY2le/fuTJgwodziD5GRkSxfvpwXX3yRL774gtdeew23203Lli15+OGHCQg4Wl+1NMt17ty5/O9//yvbb9euXat9HoZh8O233/LEE0/w8ccf85///IfWrVvz0ksv0a5dOwk0idNen0AYHAKzilrTOX8fhrcA7H4Vtt0T3JMDQZ1olrOZsw99QWqLaH4jjhQC2EAM3TmmbpkjEApSIOcAhLWpcH8xDmva3MocuCi8Ns5OnIjSFeWTigplZ2cTEhJCVlZWWaFBUbdatGgBwN69e+u1H6L2mEufwlzyBKrFCGx/+rG+u3NGkrGu/slYd2bQWlNgWn/3t8nd1rrW0Me6YlPz8RHNjxkQ7YAoR8XtTA0/Z8LKXOvnbp49XKJ2YC+5y2+YXgYmTmdQ4sfYtI9cRyg/tHqAleHD2E8oPUliDGtpqnLQxXmozF0QGIdqdyWq2ZCy1ZqEEOU19DGkoUgu1jy5X5Obso2EnPXgX3lWU+uMVdy49RE8hov/9PqQ2Y5uzKEVIRRyNyuxH5sDXJQJdn9U82GVjlN7CiHGCU8lKFxSj6lOSY0mIUSDojpeD4DeNwedn1LPvRFCiNqjjqlNIff9xLHyfJp3kzU/pFtZTJUFmYpMmJ5ilgWZzvVs5HL73rIgU2T+Pm7deD9DD36ATfvYHD6I17u/y7zwC0giiIvZwV9YThOy0Vn7UNn7oelAjLP+iZEwXIJMQog/LMapuDJSkRfQlHxbEHgLKm27K7QPiQHtcZhFDDj0JX1JJIgisnDzG/HlGzuDrWBTTsU108AaP/cWwprcGjoZUWUSaBJCNCgqrC3E9AbtQ2/7sr67I4QQtUrqNInfy/RqXj+s+SUDWrghrJJYT6YX3kvysrPIwK69XONdzTmONJQyUNrHgENfcPv6u4jP20GBLYiv2v6Tz9o9xjpHK0wUY1jLGNYR4MlEpW5E2f1QPcZj9L7PWhpcCCFqyJBg6BsWwG7/9uiinMobKsXCZjcB0DfpO4I9GQxmHwCLaU4RtmPaGmDY0Vl70NqscHcuw6pptyBLY8oNnTolgSYhRINjdLRWnzO3fFrPPRFCiNolK8+JYx0p1rxySLM0G9q5rbpMFdlfaPLOYS8pPjuBZgGjWUNHu/XlLazwEKM3/Y3z972NXXvYEdqXN3q8za+RI9isomlCDn9hBSPYhZGzD5W9D5qcgzHgEcliEkLUCoeh+FOUIiwoiiRHNHjyK227I7Q/hwPa4DQLOevw1/TgMOHkk4+T5TQt39gZDIXpkHuo0v3Fl9Rq2llYaRNRCyTQJE4re/fulZolZwDV4VpAQeISdPb++u6OEHVOxrozh2Q0iVIHijT/OaRZmwsd/MCvkiDT+qwCPkiBfOzEmFncZqwlXuWD1vRO+p471t1B85yNFBl+fN/qAaZ3eIZ9zmbsJJx+JPI3ltHZs9fKYrK5Ud0li0kIUftauRUXxwaS6t+S4uLKA00oxcImVtH8fknf4O/NYRh7AFhOU/I4Zi6xYQcUOnNPpVPQg+2Qb8LiLHmnrUuNKtCUl5fHRx99xLXXXku7du3w8/MjNDSUIUOGMH369PrunhCiilRQU2g6EAC99fN67o0QQtQeWXlOAGwv0ExO1GwtgE7+1nSP3zNNzbzkTP6X7YcPg3b6CGOM9QRTTFBRCjdu+SeX7HkFp1nI3uDuvNn9bVbHXMw+FUo6/oxkK/exguicLSVZTGdjDPgnRovzJItJCFEnLgxTdA4PY4+zOXjyKm23Lfxskv1b4vLl0+/wN3QklThyKMbOEpqXb+wKtlagyz9S6f6i7bA8B1I88mZbVxpVoGnRokXcfPPNzJ07l549e/KXv/yFq6++mvXr1zNq1Cjuu++++u6iEKKKjJKi4ObWL+q5J0IIUXtKF8GpuLqEOBOszdX8J1FzoAg6+4G9goWRiosL+OpQOguLQwEYwH6uVVtwah9dU37hrnXjaZ31Gx7lZGaLu/ig0wukuePYSiQufIznN0Z5V+CXur4ki2kcRu/7rRs7QghRRwJsimvig7H7R5LuPUFDZbCoJKup/+GvcXnzOLckq+lX4snEdbSt4QBtorN2V5odHOWAVA+sOEF5KFGzGtXti7i4OD7++GP+9Kc/4XAcTal79tln6d+/P6+99hq33HILffv2rcdeCiGqQrW5An65B5J/Q+enoPyj6rtLQghR40rv+Jlyk/WMtCRbMzVZk++Djn5Ha3aV0kBudhKfZbpJVBEY2uRitYOeJOHvyeDSXf+hQ8YSAA4GduDbNg+R5teMPBzsIpwOpDKatbTNWYcqzoUmZ2F0uE4CTEKIetM9AM6NjeD7gjhCig9jcwZU2G5LxEBSDjYnqmA//ZK+pajpKFqQwV7CWEgLLmfb0cauYMhLhoI08Is4bl+GgmAbzMvUDA8BP1sFEX1RoxpVRlP37t0ZNWpUuSATQExMDHfccQcACxYsqI+uCSGqSQXGQlR3AHTi0nrujRBC1A6jJLKgodL6EqLx0VozK0Pz9mGNx4S27gqCTL5ispI3815mMIkqFLf2cKNaT0+SiM3dwV1rx9MhYwk+ZWdus7FM7TKZNL9mHMGfPYQxmH086J1Du9SFx2Qx/VmCTEKIeqWUYmR8CAmBAewzA6isSqFWtrKsprMOf0lwUWpZVtN6Ykgk6GhjmwtMj1WrqZLjxjthfxGsrnzGnqhBjSrQdCKlwSe7vVElcQnRqNkueAPb7bsw2l5R310RQoha4zLAz7A+fIszw4IseP+IxqGgZYVBJg/60FLm5AeQpfwJJ59b1RpakAVac8meVwjwZpHk34p3u77G4qaj0MrGYQLJxs11bOSu4rlEZG6GJgNKajGdL7WYhBANQoRDcVWzaLz2QFKKKp9DtylyCCl+zfH35nDrxvvpmbeejhxBo/iYbhwg+GhjZxDkJULu4Qr35TTApmB2pibLKzd2atsZ8W7j8/n44IMPUEpx3nnnnbBt586dT7gfIUTdUXH96rsLQghR62wSYDqj5Ps0MzI0BtDUVUmj3EQOFXrZ6E4A4Cq2EEEBAB3SF9MkdyvFhpuPO04izxkOQDEGafgzig1cwVaMrD3QfBhGj9tRNkclBxJCiPoxMDqMpKxQ/ndIU1yYRROXAap8HoxWNj7p8Ayjtj5CVMEBxmz6C0b7PJ4PuZH9hPIx3biWjbQiE+x+4ClAJ/8GukeF2ZstXbA2F948rLkrDoIrKoonasQZkdE0YcIENmzYwNixY+nSpUt9d0cIIYQQQpyhluXAnkJo7qz4ea1NzKw9zHZY08e7kkwcuQAYppdz90+x9hN/TVmQCWAPYXQglQvYhco9BAHRGO1GSpBJCNEg2ZTi2rZtGNu6KR5XOLsLDbR5fHZTljuWqZ0nsy+oK25fPrdt+RvPpvyH1qTjwcandGUbJXWZ/MLB9KGTf0Nn7T1uGp3LgPZ+1gp0byVpciSzqdY0yIymyMhI0tLSqtx+3rx5DB06tMLn3n77bSZNmkTPnj35z3/+c9J9bdq0qdLnsrOzCQkJqXK/hBBCCCGEKJXv0/ycofEzwFHZ7d7cQ+wodrLPFYUNk6ElNUkAeqTMJLLwIHn2UJbFXVO2PRMXBpqRbMXPzEMVZqC6jEYFNanlMxJCiFOnlOKCZvEEu/2YumMv2/JzaWfPw7CXT/csdATzUafnuGLn/9ElbT7X7XyG0KIk/tbkSbaqKL6gM1ewla4cAXcoFGWjj6xB+Tzo8LYcm7fkNqCdG5Zmg0JzZxwESnHwGtcgA0033HADOTlVX3swNja2wu1Tp07lzjvvpGvXrvzyyy8EBgbWVBeFEEIIIYSoluU5sLvQ+pJTEa01vsyj2Uz9OUgoRQA4fAUMOfAhAAub3kix3VqpyQQOEMJ57KYXSajMPRDZGZUwvNbPRwghasKAqDCCnX68vW0nm3PsdDDTsP9uNTqf4eTrtv8kyxXDOYc+44ID7xFWdJi7W73BOhXHN3TAg41eHLZWoSvORaduQGkvOrxDuTqIfjZrEYYl2WBTmttjIUCCTTWqQQaaXn311T+8jylTpjB+/Hg6derEnDlziIg4fplDIYQQQggh6kLBMdlMzsqymfKPsKY4kDRnMH54OIf9ZU/1P/w1QZ50Mlyx/BZzSdn2RIKJIY8r2A5FGWjDga3dlSiHXy2fkRBC1JzOIW4e7NaJt7buZkuGnbYFh3D7BcGx+UjKYE7CODJdMVy05zX6HfmRT4quYWyHT1hpJDCDdhRhYwAHwRkIHgOduhlMrxWAP6YGlH9JsGlRSWbT7bHgL8GmGtMoazRNmTKFcePG0aFDB+bOnUtUVFR9d0kIIYQQQpzBSrOZmlVWmwkozNzHAkdHAAazFzfWQjR+nizOOfQ5APOajcU0rLpLRdjIxsWlbCeWbFT2AVSzwRDVrdbPRwghalqC2+DBzq3pGxvHdmcCufk5oM3j2v0WexmfdXiCYsNNu6xVfLnhAob6tgIwm9bMJ8Gqz+TwB2cApG9FH1mLNssv7uVvg9YuWJgF7yVrCnxSs6mmNLpA03vvvVcuyBQdHV3fXRJCCCGEEGewAp9mZobGpU6QzVSQxrLiYPKUm3Dy6c3RJboHJU7H5cvnsH9rNkYOLdu+hzC6kMIw9kL2AQiKx2hzebkpIkIIcTqJdCjub9eEc5s2Y69fazIK8sH0HNduR9hZvN/5RXIdocTl7+bLtcO5tPg3ABbRgl9obQWb7H7gCoHMXejk1Whf+X0F2KCVG+ZlWsGmQlOCTTWhQU6dO1Vz585l/PjxaK0ZPHgwb7zxxnFtevTowciRI+u+c0IIIYQQ4oy0Igd2nag2E5CdmchyWycAzmUPtpL1kkIKk+iT9B0AcxLGlS3/nY4bJz6uZCsuXy7Kk4vqdAMqQG6yCiFOb4E2xR0twwl2uZix30FR3h5iHQVW0OgYhwPbM6XLK4za8i8iCw8wfe1w7uj6Pz7xG8YKmlKMjYvZjmFzgSsUsvZYK9vF9kLZXMccD1q6YW6WVbPp1hhwGRKw/yMaVaBp//79aG29Kb/11lsVthk9erQEmoQQQgghRJ0oNDU/Z2rcJ8pmKspiflEIHpudpmTRgdSyp4YeeB+79rA7pCe7Q3oDVgHwg4RwCdvpTLJVADy6B6rZkNo/ISGEqAMuQ3FzkwBCHC35Yq+D/bn7aObLRrmCy7XLdMcxpctkrts2kYScDUxZdwmhnT7kjeCrWEMcRdgYyVZsNif4RUDOgZJgU59yteyCbNDSBbMzwUAzNgacEmw6ZY1q6tyYMWPQWp/wMW3atPruphBCCCGEOEOsyIGdBdDMVXmbpMxk1hrNATif3WWlb2PydtEtdQ4Ac5rfBiVT4g4QQhOyuYwdqIJUtMMfo91VKFslBaCEEOI0ZFOKkdEOxrdvgRHWlp1GNLogDSg/va3QEcxHnZ5jY8RQbNrLfzbdwL/S3sLQJpuJ5gs648EAww7+kZCXhD68Al2cW24/QTZIcMKsDHg/WVMs0+hOWaPKaKptpdlS2dnZ9dwTIURlgoKCpDbFHyRjnRANm4xzNaMuxrpCU/PtAY0qAnxQVFE/PHn8kmYDI4d2pBLF4bJ2/ba9RU6hyZbwgexVTSEvjwLsZFLMFazDqVPJSdsPbS7DsMehZNwWVSBjSM2Qz0t1p7cBttggPiyKYUOGhza5u7H5hYGylWs3Pf5+hvjCOCvpax5Yfx8BzffxaMxD7FAOPiGBK9mCCx9oP0jdB7nZqJieKGdI2T5cQIwXvj8IRblwQ5TCIZlN5VRlDFG69H+IOKmDBw/SrFmz+u6GEOIEsrKyCA4OPnlDUSkZ64Ro2GScqxky1okzlYwhNUPGEHGmqsoYIoGmajBNk0OHDpVF8Pr27cuqVavKtTl2W79+/QBYuXJlrfetor7Uxmur0vZEbSp77mTX8vc/ny7XtrqvP1nbxnZtK+vfH3mt3KX742Ssq52x7lS2nS7Xtrqvl7Huj71Wxrma8fux7nRU17/HjdWZdh1P59/5huR0GkPOtN/xhqgx/RtU5Xdeps5Vg2EYNG3atOxnm812XCTv2G02m5XKVxd3DCrqS228tiptT9SmsudOdi1///Ppcm2r+/qTtW1s17ay/tXFa0XlZKyrnbHuVLadLte2uq+Xsa7uXisq9/ux7nRU17/HjZVcR3EqTqcxRH7H69+Z9m/QqIqB17V77rmnStvqwh85bnVeW5W2J2pT2XNVuZan47Wt7utP1raxXds/euz67PeZRMa66rep6jVrLNe2uq+Xsa7uXiuEEEIIUddk6lwt6ty5MwCbNm2q5540PnJta49cW1Fd8jtTe+Ta1h65tqIxkN/jmiHXUTR28jte/860fwPJaBJCCCGEEEIIIYQQNUICTUIIIYQQQgghhBCiRkigSQghhBBCCCGEEELUCKnRJIQQQgghhBBCCCFqhGQ0CSGEEEIIIYQQQogaIYEmIYQQQgghhBBCCFEjJNAkhBBCCCGEEEIIIWqEBJqEEEIIIYQQQgghRI2QQJMQQgghhBBCCCGEqBESaGoAXn75ZZo1a4afnx/nnnsu27dvr+8uNRpff/01559/PuHh4Sil2Lt3b313qdGYNGkSffr0ISgoiJiYGK699lq5vuKEZKyrPTLW1R4Z64QQQgghqkcCTfXsk08+4ZFHHuH5559n1apVhIWFceGFF1JUVFTfXWsU8vLyGDRoEM8880x9d6XRWbBgAffddx8rVqxg5syZZGZmctFFF+H1euu7a6IBkrGudslYV3tkrBMN0apVq7j44osJCwsjICCAfv368cknn9R3t04biYmJTJ48mREjRtC8eXOcTiexsbFcffXVrFixor67J0SNkbGifn300Ufccccd9OnTB5fLhVKKadOm1Xe36oTSWuv67sSZrG/fvgwePJh///vfAOTk5BAdHc3777/PtddeW8+9azy2bt1Kx44d2bNnDy1atKjv7jRKBw4coHnz5qxbt45u3brVd3dEAyNjXd2Qsa72yVgn6tv8+fO54IILcDqdXH/99YSEhPD111+zZ88ennnmGR555JH67mKD9/DDD/P888/TunVrhgwZQnR0NDt27OCbb75Ba8306dPlvUmc9mSsqH8tWrRg3759REZGEhAQwL59+5g6dSpjxoyp767VOsloqoJTiURWJXpcXFzMmjVrOPfcc8u2BQUF0b9/f5YvX14bp9Ig1db1FXV7bbOysgAIDw+via6LeiBjXe2Ssa72yFgnzhRer5dx48ahlGLhwoW88847vPjii6xbt47OnTvz+OOPs2PHjvruZoPXr18/Fi5cyM6dO3nvvfeYNGkSX375JfPmzcNms3HXXXdJxq04rclY0TC8++677N27l5SUFO6888767k6dstd3B04Hjz76aFkkMi4ujn379p2wfWXR4xtvvJG9e/eWRY9TU1Px+XxER0eXe310dDTJycm1dj4NTW1dX1F319Y0Tf76179y8cUX07Rp09o4FVEHZKyrXTLW1R4Z68SZYu7cuezatYuxY8fSs2fPsu1BQUFMmDCB66+/nqlTp/Lss8/WYy8bvquuuqrC7YMGDWLYsGHMmjWLDRs20KdPnzrumRA1Q8aKhuG8886r7y7UG8loqoLqRCIlelx9cn1rT11cW601d9xxB3v27Dlj5hw3VvJ/sXbJ9a09MtaJM8X8+fMBGDFixHHPlW5bsGBBXXap0XE4HADY7XI/Xpy+ZKwQ9U0CTVVw3nnnkZCQUKW2pdHjUaNGVRg99nq9TJ06FYDIyEhsNhtHjhwpt48jR44QExNTcyfQwNXW9RW1f2211tx9993Mnj2bOXPmEBUVVaP9F3VLxrraJWNd7ZGxTpwpSoOgbdu2Pe65sLAwIiMjJQj9B+zfv5/Zs2cTGxtL165d67s7QpwyGStEfZNAUw2rTvTY6XTSs2dP5s2bV9YmNzeXFStWcNZZZ9V+Z09DEp2vPdW9tlpr7rnnHmbMmMHcuXNp1qxZnfRTNAwy1tUuGetqj4x14nRWWiMsJCSkwueDg4PL2ojq8Xg83HzzzRQVFfHCCy9gs9nqu0tCnDIZK0R9k5zQGlbd6PFf/vIXxo8fT58+fejSpQtPPPEEcXFxXH755XXW59NJda9veno6+/fvZ+/evQBs3ryZzMxMmjdvLoVcf6e61/buu+/m008/5fvvv8fPz4+kpCTAKpDrdDrrptOi3shYV7tkrKs9MtYJIX7PNE1uvfVWFi5cyPjx47n55pvru0tCCHFak0BTDatK9PjgwYNlP994440cOXKEv/3tb6SmpjJgwAB++ukn3G53nfT3dFPd6/vdd98xduzYsp8vueQSgDNmWcnqqO61ffPNNwGrcOax5s2bx9ChQ2unk6LBkLGudslYV3tkrBOns9Lf28oyEbKzsyv93RYV01ozfvx4PvroI2666aay//NCnM5krBD1TQJNDcADDzzAAw88UN/daJTGjBkjX7Jqida6vrsgTjMy1tUeGetqj4x1oiEpzcTbsWMHvXv3LvdcRkYGqampnH322fXRtdOSaZqMGzeOqVOncsMNNzBt2jQMQyqLiNOfjBWivslIWsMkely75PrWHrm2ojrk96V2yfWtPXJtxelsyJAhAMyaNeu450q3lbYRJ3ZskOm6667jww8/lLpMotGQsULUNwk01bBjo8e/Vxo9rqguhKgaub61R66tqA75faldcn1rj1xbcTobPnw4rVq14pNPPmHt2rVl23Nycnjqqaew2+2S3VgFpmly2223MXXqVP70pz/x0UcfSZBJNCoyVoj6JoGmGibR49ol17f2yLUV1SG/L7VLrm/tkWsrTmd2u513330X0zQZNGgQt99+O3/729/o3r07mzZtYuLEibRr166+u9ngPfnkk0ybNo3AwEDatWvH008/zcSJE8s9jv1yLsTpRsaKhuHdd98tK2/wxRdfHLftm2++qd8O1iYtqmXSpEka0FOnTq3weY/Ho1u1aqVdLpdes2ZN2fbs7GzduXNnbbfb9bZt2+qms6chub61R66tqA75faldcn1rj1xbcSZYsWKFvvDCC3VISIj28/PTffr00R999FF9d+u0MXr0aA2c8FHZGCLE6UTGivp1srHm8ccfr+8u1hqltVS5PJl3332XxYsXA7BhwwZWr17NOeecQ5s2bQAYOXIkI0eOLGs/b948LrjgAlwuFzfccAPBwcF8/fXX7Nmzh6effpp//etf9XEaDZZc39oj11ZUh/y+1C65vrVHrq0QQgghRANS35Gu08GpRCIlelx1cn1rj1xbUR3y+1K75PrWHrm2QgghhBANh2Q0CSGEEEIIIYQQQogaIcXAhRBCCCGEEEIIIUSNkECTEEIIIYQQQgghhKgREmgSQgghhBBCCCGEEDVCAk1CCCGEEEIIIYQQokZIoEkIIYQQQgghhBBC1AgJNAkhhBBCCCGEEEKIGiGBJiGEEEIIIcQpmzlzJmeddRYhISEopRgzZkzZcx999BE9evQgMDAQpRQTJ06st34KIRqWoUOHopSq726IWmCv7w4IIYQQQgghGoZ58+bx5ptvsnTpUo4cOUJAQACdOnXi6quv5q677sLtdpdrv2fPHkaOHEl4eDjjxo0jKCiIHj16ALB06VJuvvlm2rZtyz333IOfnx9Dhw6t1f4rpRgyZAjz58+v1eMIISqWn5/P5MmT+fLLL9m+fTter5fIyEhatmzJwIEDGTduHK1bt67vbopaJoEmIYQQQgghznBer5d77rmHt99+m4CAAC666CLatGlDVlYWs2bN4sEHH+TNN99kxowZtGnTpux1c+bMoaioiJdeeonrr7++3D5//PFHAD744APOOuusOj0fIUTdy8nJYeDAgaxfv542bdpw0003ERoayoEDB9i0aRPPPfccrVu3lkDTGUCmzgnRwBw8eBB/f39eeOGFOj3uzp07sdvtvP7663V6XCHEmUnGOiEaln/+85+8/fbb9O3bl23btvHFF18wadIkXn/9dbZt28Zjjz3G9u3bueiii8jOzi573aFDhwCIjY09bp8nek4I0fhMnjyZ9evXc9ttt7F9+3befPNNnnvuOT7++GPWrl3L7t27GThwYH13U9QBCTQ1cnv37kUpdcKHaFgeeeQRAgMDueeee8ptb9GixXHp6r/ndrtp0aLFKR23TZs23HjjjUycOLHcB0ghTgcy1p1+ZKwTouHYsWMHL730EuHh4Xz//fc0adKk3PM2m40nnniCUaNGsXPnTl588cWycffxxx8HYNiwYWXj7bRp01BKMXXqVABatmx53Fg8b948LrroIuLj43G5XP/f3r3H5Xz+fwB/dRbiLsdCR+cdGtZCOjgWKj1MDhsrNc02ZmOOX2QHIZNhPDCiZD1mlLNozL3otHk4b21tDskYyYqbSPf1+8Pv81m3+67u6ibm9Xw8ejxyfa7P9bnuO737fK77ut4X7Ozs4OPjg3Xr1mn17/z583j77bdhb28PCwsL2NraIjQ0FBcvXpTrHD58WG5fqVRqxP+NGzca+i0jIh0yMjIAABMmTNB57+Xk5ISOHTtW2c6DBw+wdOlSuLq6wtLSEo0bN0bv3r2xZ88erbpSvNm4cSOSk5Ph5uaG+vXro2XLlnj33Xdx8+ZNndfQJ65QzXHp3HPCxcUFo0ePrutuUBV+//13JCQkYO7cuWjQoMETv/7UqVMRHx+P5cuXY/bs2U/8+kS1xVj3bGCsI3q6bNy4EWq1GhEREWjRokWF9ebMmYNvvvkGsbGxmDx5MiIjI3H48GEolUqEhITIA8CvvPIKIiMjsX37dpw8eRKTJk2CQqGQ29mzZw8CAgKgUCgwZMgQ2Nra4vr16zhx4gQ2b96Mt99+W66blZUFX19fqFQqBAQEoG3btrhw4QI2b96Mffv2ISMjA87OznB0dERkZCQ++eQTODg4aCQkl3JGEdHjZWNjA+Dh7OGa/t4JITBixAgkJSWhffv2eP/996FSqbBlyxb4+/tj2bJl+OCDD7TO27p1K1JTUxEcHIx+/fpBqVRi9erVyMjIQEZGBiwtLeW6+sYVqgVB/2nnz58XAISvr29dd4X0MHnyZAFA5Obmah1zcHAQFhYWlZ5vYWEhHBwcatUHV1dXYW9vL8rKymrVDtGTxFj3bGGsI3q6+Pj4CAAiNTW1yrp2dnYCgMjLyxNCCBEZGSkAiB9++EGrbkhIiAAgzp8/r1E+dOhQAUCcPHlS65yCggL5+/v37wtHR0dhZWUlTpw4oVEvLS1NmJiYCH9/f41yAMLb27vK10FEhrd9+3YBQDRq1EhMnz5dHDx4UBQWFlZY39vbWzw6JBEfHy//Ht+7d08uv3TpkmjevLkwMzMT586dk8s3bNggAAgA4vvvv9doa+zYsQKA+PTTT+WymsQVqj4unSMAwLx582BkZITDhw8jLi4O3bp1Q/369TV2Brl16xYiIyPxwgsvwNLSEgqFAn5+fjhy5IjONs+ePQt/f39YWVmhcePGGDRoEM6cOYPQ0FAYGRnhwoULOq//qPLTIR916tQpjBw5Era2tjA3N4eDgwMmTpyIGzduaNSTpneHhobi3LlzGDZsGKytrdGgQQP069cPJ0+e1Pkarl27ho8//hgdOnRAvXr1YGNjg+7du2PJkiUAgHPnzsHY2BiDBw/Wef7NmzdRr149uLq66jxenlqtRnx8PLp06aKRZLM29FlOVP7nAADDhw9HXl4eDh48aJA+ED1NGOsY6ySMdUT/unr1KgCgTZs2VdaV6ly5cqXW1y0/w0DSpEkT+fvdu3fjwoULmDZtmlZ86dWrF4YMGYK9e/dyGSzRU2LIkCGIjo6GWq3GokWL0LdvX9jY2KBt27aYMGECcnNzq2xDug+Kjo6Gubm5XN66dWt89NFHKC0txebNm7XO69+/P/r27atR9vnnn8PMzAxxcXFyGePKk8Glc6Rh8eLF+OGHHxAYGIj+/fvD1PThf5HCwkJ4eXnh7Nmz8PT0hK+vL4qKirBjxw707t0b3333HYKCguR2zpw5Aw8PD9y+fRtDhw5Fu3btkJ2dDQ8PD70eRPSxc+dODB8+HCYmJggMDESbNm3wyy+/4KuvvsL+/fuRlZUFa2trjXMuXLgAd3d3dO7cGWFhYfjzzz/l1/Drr79qTBfPzc1F7969cfnyZfTq1QtBQUFQqVQ4c+YM5s+fjylTpsDZ2Rn9+vVDSkoK8vPz0bp1a43rbdq0Cffu3cO4ceOqfD2nTp1CQUEBgoODDfL+AIBCoZBzJ5R39+5dxMTEQK1Wa+VC6dGjBwDg0KFD6N+/v8H6QvQ0YaxjrGOsI6oZIQQA1Cr33fDhw5GUlAR3d3eMGjUKffr0gaenJ5o3b65RLzMzEwCQk5ODefPmabVz9epVqNVq/P7773j11Vdr3B8iMpypU6di/PjxSElJQXp6On7++WdkZWVh5cqVWL9+Pb799lsEBgZWeP7x48dhaWmJ1157TeuY9MHgiRMntI55enpqldnZ2cHFxQU5OTm4desWrKysGFeeEA40PSf++OMPnb9Ifn5+GtvNKpVKZGVl4aWXXtKoN3HiRJw9exaxsbEYO3asXB4VFQU3NzdERETAz89PvpGfMGECiouLkZCQgDfffFOuP2vWLCxYsKDWr+fGjRsYM2YMmjVrhqNHj8Le3l4+lpiYiDfeeANz587FihUrNM5TKpVYuHAhpk+fLpfNmTMHn3/+OTZs2IAZM2bI5aNHj8bly5exdu1arYen/Px8+fuIiAikpqYiNjYWc+fO1ai3fv161KtXT6+cMenp6QCArl27VljnwYMHOn+O5Y+Xp1AotOoLITBy5Eg8ePAAixcv1toJRgqoUn+IniWMdf++PsY6xjoifbVs2RI5OTm4dOkSOnToUGldKS7UZie5ESNGwMzMDF9++SXWrFmDVatWwcjICD4+PoiJiZFzuxQWFgKAztkL5alUqhr3hYgMz8rKCsHBwfKHSkVFRZg1axZWrVqF8PBwXL58WWO2UnnFxcUVzq6U4k5RUZHWsUcHqiUtWrRATk4OiouLYWVlxbjypNTx0j16zKS8JRV9LV26VAjx7/r6jz76SKuN69evCxMTE9G3b1+d11i+fLkAIHbt2iWEEOLixYsCgHj55Ze16t66dUsoFAqt9fqVre+X1t1u2LBBLouJiREAxKZNm3T2qWvXrqJp06Za74OTk5NWPg7p2NChQ+Wy7OxsAUB4eXnpbL+8+/fvixYtWghHR0ehVqu12hg9enSVbQghxMyZMwUAsXPnTp3HHRwcKv1ZSl9V5S2ZM2eOACDGjh1bYZ169eoJZ2dnvfpN9DRgrNN8HxjrGOuIqmPWrFkCgJgxY0al9X799VcBQLRq1Uouq0mOpvKKiorEvn37xLhx44SxsbFo3ry5uHnzphDi33xuUtzVB5ijieippFar5b/xP//8sxBCd44ma2trYWlpqbONzMxMrXsZ6f6pfB6m8jp27CgAiOLiYiFEzeIKVR9nND0nfH19kZKSUmU9XVMUf/rpJ5SVlaGkpETnJ8zSWtucnBz4+/vLOUB69eqlVbdhw4Z45ZVXdOYnqQ5pymNmZib++OMPreMlJSUoKChAQUEBmjZtKpe7urrC2FgzNZm0BOSff/6Ry7KzswEAAwYMqLIvZmZmCAsLw4IFC5Camiqfs379egDQ2DmlMlKulUeXwJRnYWGBkpKSCo9XtSV4YmIiPvvsM3h6emL16tUV1rOxsUFBQUEVPSZ6+jDWPcRYx1hHVB0hISFYuHAhvv76a0yePBnNmjXTWW/+/PkAgLCwMINdu1GjRvDz84Ofnx/KysoQGxsr7wjl7u4O4OGW6f7+/nq1Z2xsjLKyMoP1j4gMw8jICPXr16+yXpcuXXDo0CFkZ2dr3a8plUoAuneSTEtL0yr766+/8Oeff8LFxQVWVlYAUKO4QtXHgSbSoGtLW2l64dGjR3H06NEKz5WmF0pTGSubvlhbUp9WrlxZaT2VSqXx8NW4cWOtOlJulvI3JdKDWKtWrfTqz7hx47Bw4UKsW7cOAwYMwJ07d5CYmIj27dvD29tbrzakhJh3797Vq351ZWZmIiwsDM7OzkhKSqpwuqrUB33+EBA9qxjrHmKsY6wjAoD27dtj0qRJWLp0KQICApCcnAxbW1v5uFqtxvz585GQkAAXFxd8/PHHtbrewYMH4eHhoTVofO3aNQD/xokhQ4bA3t4eMTEx8PX1hZeXl0b90tJSZGVlaQz429jYaCz7JaInZ82aNejatSvc3Ny0jiUlJSEnJwcKhQIvvvhihW2EhITg0KFDmDlzJlJSUmBmZgYAuHz5MmJiYmBqaqqRrkCSmpqKgwcPaiQEnz17NkpLSxESEiKX1SSuUPVxoIk06Ers2KhRIwDAlClT8MUXX1TZhvSAI90sPOrvv//WKpM+eX807wagew2u1KfTp09XGqhqSqFQAHgY0PTh5OSE/v37Y8eOHSgoKMDu3btRXFyM2bNn631N6dND6cHSkPLy8hAUFARzc3Ps2rVL44H0UWq1GkVFRXjhhRcM3g+ipwVj3UOMdYx1RJLo6GgUFRUhNjYW7dq1w+DBg+Hi4oLi4mIcOHAAubm5aNeuHfbu3SvHppqaMmUK8vLy4OPjA0dHRxgZGeHIkSPIzs5Gz5494eHhAeDh7MatW7di4MCB8Pb2Rt++feVYmJeXh7S0NDRp0gQ5OTly23369MGWLVswbNgwdOnSBSYmJhg8eLBWTj4iMrx9+/Zh/PjxaNu2LTw8PGBnZ4fbt2/jxIkTSEtLg7GxMVatWgULC4sK2xgzZgySkpKwY8cOvPzyy/D394dKpcKWLVtw48YNLFmyBM7OzlrnDR48GIMGDUJwcDDatGkDpVKJjIwMuLq6agyO1ySuUPVxoImq5ObmBiMjI2RkZOhVX9ppSddW4FKgeZS0hELXw87x48e1ytzd3ZGUlISMjIzH8vAlTdM8cOAA/ve//+l1TkREBA4cOID4+HgkJyfDzMxMY/S8KtINkD7bflbH7du3ERAQID8Udu7cudL6ubm5UKvVvCGj5w5jHWMd0fPM1NQU69evx6hRo7B27VocOXIEycnJaNCgATp16oTx48fj3XfflWcb1cbMmTORlJSEY8eOYf/+/TAzM4OTkxOio6Px3nvvwcTERK7r5uaGkydPYvHixdi7dy+OHDkCCwsLtGrVCkFBQRg1apRG28uWLQPwcEfJ5ORkqNVqtGzZkr/rRE/AokWL4OHhgdTUVPz444+4cuUKgIczp0NCQjBx4kR069at0jaMjIywdetWLFu2DHFxcVixYgXMzc3RtWtXTJ48ucId64YNG4bw8HDMnz8f27ZtQ6NGjfDOO+8gKipKK25VN65QDdR1kih6vKTkr76+vpXWqyyRoxBCjBgxQgAQ0dHRGklgJZmZmUKlUsn/9vLyEgBEQkKCRj0pCSweSQyZnp4uAIg+ffpoJLBNT08XpqamWglyr127JqysrESzZs3EmTNntPqjUqlERkaG1vsQEhKi8/VBR+LI1157TQAQa9eu1aqfn5+vVVZaWipatmwp7OzsBADx+uuv67xWRQoLC4WxsbEICAjQedzBwUFYWFhU2oaFhYVGgtyysjIREBAgAIhly5bp1Y+4uDgBQKxZs0bvvhPVNcY6zfeBsa5qjHVERETPPl2bqVDd44wm0suqVavw22+/Ydq0adi0aRN69OiBxo0b49KlSzh27Bhyc3Nx5coVOdfFypUr4eHhgbfeegvbt29Hu3bt8NNPPyE7Oxuenp5aydq6d++OHj164NChQ+jRowe8vLxw8eJF7Ny5U84VUF6zZs2QmJiI4OBguLq6ws/PDx07dkRJSQkuXrwIpVKJnj176pUUuCIJCQnw8fFBRESE/JpLSkpw9uxZHD9+XE5oKzE1NUVYWBiioqIA6J8YV2JtbQ0vLy+kpaXh3r17lU4p1dfWrVuxa9cu2NraorCwUGeC4w8//FBePgM8XN9sYmLC5Hj0XGKsY6wjIiIiolqq65EuerwM9Sm/EELcuXNHREdHi27duokGDRoIS0tL4eTkJIKCgkR8fLwoLS3VqH/69GkxaNAg0bBhQ2FlZSUGDhwoTp8+XeFWt9evXxdjxowRNjY2wtLSUnTv3l3s37+/0lHqnJwcER4eLhwcHIS5ubmwtrYWL730kvjggw9Edna21vtQnU/5hRDi6tWrYtKkScLZ2VmYm5sLGxsb4e7uLmJiYnS289tvvwkAwt7eXmtrcX0kJiYKAGLbtm1ax2ryKb/03lX2Vf7noFKpRMOGDUVQUFC1+05UlxjrNN8HxjrGOiIioucBZzQ9nYyEEOKxj2YRlRMaGoq4uDicP38ejo6Odd0dg9qyZQtGjBiBTz75BHPnzq32+ffv30f79u3RqVMn7Nu37zH0sHKxsbEIDw+HUqnU2oGBiKqHsa5ijHVERERkCBs3bsTYsWOxYcMGhIaG1nV36P8Z13UHiP4rhBDylpvh4eE1asPc3BxRUVFISUlBVlaWgXtYuQcPHiAqKgqBgYF88CKiCjHWERER0dMiNDQUQggOMj1lmKOJqJZOnz6N3bt3Iz09HVlZWRg/fjxatWpV4/ZGjRqF/Px8FBQUGLCXVcvPz8fo0aMxZsyYJ3pdIno2MNYRERERkT64dI6euP/achJpuqZCoUBgYCBWrlyJhg0b1nW3iKiOMdYRERER0fOIA01ERERERERERGQQzNFEREREREREREQGwYEmIiIiIiIiIiIyCA40ERERERERERGRQXCgiYiIiIiIiIiIDIIDTUREREREREREZBAcaCIiIiIiIiIiIoPgQBMRERERERERERkEB5qIiIiIiIiIiMggONBEREREREREREQG8X8l7X8kMqSHbwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams.update({\n",
    "    'font.size': 14,\n",
    "    'axes.spines.right': False,\n",
    "    'axes.spines.top': False,\n",
    "    'xtick.major.size': 6,\n",
    "    'xtick.major.width': 1.2,\n",
    "    'ytick.major.size': 6,\n",
    "    'ytick.major.width': 1.2,\n",
    "    'legend.frameon': False,\n",
    "    'legend.handletextpad': 0.1,\n",
    "    'svg.fonttype': 'none',\n",
    "    'text.usetex': False\n",
    "})\n",
    "\n",
    "fig=plt.figure(figsize=(12,4))\n",
    "undetected_color=np.array([0,76.5,99.2])/100\n",
    "detected_color=np.array([98.4,54.1,1.2])/100\n",
    "\n",
    "gs = GridSpec(1, 4, width_ratios=[.275, .275, .225, .225])\n",
    "\n",
    "ax1=fig.add_subplot(gs[0])\n",
    "#m_detected=np.mean(ds_layer_aperiodic,axis=0)\n",
    "m_detected=np.log10(np.mean(mds_layer_psd,axis=0))\n",
    "ax1.set_xscale('log')\n",
    "#ax1.set_yscale('log')\n",
    "for i in range(n_electrodes):\n",
    "    label=None\n",
    "    if i==5:\n",
    "        label='superficial'\n",
    "    if i==12:\n",
    "        label='middle'\n",
    "    if i==24:\n",
    "        label='deep'\n",
    "    ax1.plot(freqs,m_detected[i,:],color=detected_color,alpha=(i+1)/n_electrodes,label=label)\n",
    "plt.legend()\n",
    "# ax1.set_xlim([.1,125])\n",
    "ax1.set_xlabel('Frequency (Hz)')\n",
    "ax1.set_ylabel('Power')\n",
    "    \n",
    "ax2=fig.add_subplot(gs[1])\n",
    "# m_undetected=np.mean(us_layer_aperiodic,axis=0)\n",
    "m_undetected=np.log10(np.mean(mus_layer_psd,axis=0))\n",
    "ax2.set_xscale('log')\n",
    "# ax2.set_yscale('log')\n",
    "for i in range(n_electrodes):\n",
    "    label=None\n",
    "    if i==5:\n",
    "        label='superficial'\n",
    "    if i==12:\n",
    "        label='middle'\n",
    "    if i==24:\n",
    "        label='deep'\n",
    "    ax2.plot(freqs,m_undetected[i,:],color=undetected_color,alpha=(i+1)/n_electrodes,label=label)\n",
    "plt.legend()\n",
    "#ax2.set_xlim([.1,125])\n",
    "ax2.set_xlabel('Frequency (Hz)')\n",
    "\n",
    "ax3=fig.add_subplot(gs[2])\n",
    "m_detected=np.mean(ds_layer_offsets,axis=0)\n",
    "se_detected=np.std(ds_layer_offsets,axis=0)\n",
    "ax3.plot(m_detected,np.arange(n_electrodes),\n",
    "         label='detected',\n",
    "         color=detected_color)\n",
    "ax3.fill_betweenx(np.arange(n_electrodes),\n",
    "                  m_detected-se_detected,\n",
    "                  m_detected+se_detected,\n",
    "                  alpha=0.5,\n",
    "                  color=detected_color)\n",
    "\n",
    "m_undetected=np.mean(us_layer_offsets,axis=0)\n",
    "se_undetected=np.std(us_layer_offsets,axis=0)\n",
    "ax3.plot(m_undetected,\n",
    "         np.arange(n_electrodes),\n",
    "         label='undetected',\n",
    "         color=undetected_color)\n",
    "ax3.fill_betweenx(np.arange(n_electrodes),\n",
    "                  m_undetected-se_undetected,\n",
    "                  m_undetected+se_undetected,\n",
    "                  alpha=0.5,\n",
    "                  color=undetected_color)\n",
    "ax3.set_ylim([n_electrodes-1,0])\n",
    "ax3.set_ylabel('Virtual contact')\n",
    "ax3.set_xlabel('Offset')\n",
    "ax3.legend(loc='lower right')\n",
    "\n",
    "ax4=fig.add_subplot(gs[3])\n",
    "m_detected=np.mean(ds_layer_slopes,axis=0)\n",
    "se_detected=np.std(ds_layer_slopes,axis=0)\n",
    "ax4.plot(m_detected,np.arange(n_electrodes),\n",
    "         label='detected',\n",
    "         color=detected_color)\n",
    "ax4.fill_betweenx(np.arange(n_electrodes),\n",
    "                  m_detected-se_detected,\n",
    "                  m_detected+se_detected,\n",
    "                  alpha=0.5,\n",
    "                  color=detected_color)\n",
    "\n",
    "m_undetected=np.mean(us_layer_slopes,axis=0)\n",
    "se_undetected=np.std(us_layer_slopes,axis=0)\n",
    "ax4.plot(m_undetected,\n",
    "         np.arange(n_electrodes),\n",
    "         label='undetected',\n",
    "         color=undetected_color)\n",
    "ax4.fill_betweenx(np.arange(n_electrodes),\n",
    "                  m_undetected-se_undetected,\n",
    "                  m_undetected+se_undetected,\n",
    "                  alpha=0.5,\n",
    "                  color=undetected_color)\n",
    "ax4.set_ylim([n_electrodes-1,0])\n",
    "ax4.set_xlabel('Slope')\n",
    "\n",
    "plt.tight_layout()\n",
    "# plt.savefig('aan-e_i.svg')\n",
    "# plt.savefig('aan-e_i.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9e1d4543",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure()\n",
    "m_detected=np.log10(np.mean(mds_layer_psd,axis=0))\n",
    "m_undetected=np.log10(np.mean(mus_layer_psd,axis=0))\n",
    "im=plt.imshow(m_detected-m_undetected,aspect='auto',extent=(freqs[0], freqs[-1], n_electrodes-1, 0))\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Virtual contact')\n",
    "cbar=plt.colorbar(im)\n",
    "cbar.set_label('Log Power Difference\\n(Detected - Undetected)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7d46c89b",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_rel_power=np.zeros((n_electrodes,len(freqs)))\n",
    "for i in range(len(freqs)):\n",
    "    ds_rel_power[:,i]=m_detected[:,i]/np.max(m_detected[:,i])\n",
    "im=plt.imshow(ds_rel_power,aspect='auto',extent=(freqs[0], freqs[-1], n_electrodes-1, 0))\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Virtual contact')\n",
    "cbar=plt.colorbar(im)\n",
    "cbar.set_label('Relative Power (Detected)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3716a116",
   "metadata": {},
   "outputs": [],
   "source": [
    "us_rel_power=np.zeros((n_electrodes,len(freqs)))\n",
    "for i in range(len(freqs)):\n",
    "    us_rel_power[:,i]=m_undetected[:,i]/np.max(m_undetected[:,i])\n",
    "im=plt.imshow(us_rel_power,aspect='auto',extent=(freqs[0], freqs[-1], n_electrodes-1, 0))\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Virtual contact')\n",
    "cbar=plt.colorbar(im)\n",
    "cbar.set_label('Relative Power (Undetected)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8b3dbc38",
   "metadata": {},
   "outputs": [],
   "source": [
    "im=plt.imshow(ds_rel_power-us_rel_power,aspect='auto',extent=(freqs[0], freqs[-1], n_electrodes-1, 0))\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Virtual contact')\n",
    "cbar=plt.colorbar(im)\n",
    "cbar.set_label('Relative Power Difference\\n(Detected - Undetected)')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce8bd35d",
   "metadata": {},
   "source": [
    "**Compute power spectra over whole trial after subtracting out mean response**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7e54e193",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compute power spectral density from STFT after subtracting mean - detected stimuli\n",
    "ds_mean=np.mean(ds_trial_signals,axis=0)\n",
    "freqs, times, Zxx = scipy.signal.stft(ds_trial_signals-ds_mean, fs=srate, window='hann', nperseg=winsize,\n",
    "                                      noverlap=overlap, nfft=int(winsize * 20), detrend='constant',\n",
    "                                      return_onesided=True, boundary='zeros', padded=True, axis=-1)\n",
    "ds_layer_resid_psd = np.abs(Zxx) ** 2\n",
    "f_idx=(freqs>=freq_lims[0]) & (freqs<freq_lims[1])\n",
    "freqs=freqs[f_idx]\n",
    "ds_layer_resid_psd=ds_layer_resid_psd[:,:,f_idx,:]\n",
    "mds_layer_resid_psd=np.mean(ds_layer_resid_psd,axis=-1)\n",
    "\n",
    "\n",
    "# Compute power spectral density from STFT after subtracting mean - undetected stimuli\n",
    "us_mean=np.mean(us_trial_signals,axis=0)\n",
    "freqs, times, Zxx = scipy.signal.stft(us_trial_signals-us_mean, fs=srate, window='hann', nperseg=winsize,\n",
    "                                      noverlap=overlap, nfft=int(winsize * 20), detrend='constant',\n",
    "                                      return_onesided=True, boundary='zeros', padded=True, axis=-1)\n",
    "us_layer_resid_psd = np.abs(Zxx) ** 2\n",
    "f_idx=(freqs>=freq_lims[0]) & (freqs<freq_lims[1])\n",
    "freqs=freqs[f_idx]\n",
    "us_layer_resid_psd=us_layer_resid_psd[:,:,f_idx,:]\n",
    "mus_layer_resid_psd=np.mean(us_layer_resid_psd,axis=-1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94b234e0",
   "metadata": {},
   "source": [
    "**Parameterize power spectra**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5a2bc0df",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "ds_layer_resid_offsets=np.zeros((n_trials,n_electrodes))\n",
    "ds_layer_resid_slopes=np.zeros((n_trials,n_electrodes))\n",
    "ds_layer_resid_aperiodic=np.zeros((n_trials,n_electrodes,len(freqs)))\n",
    "for t in range(mds_layer_resid_psd.shape[0]):\n",
    "    trial_psd=mds_layer_resid_psd[t,:,:]\n",
    "    \n",
    "    fg = FOOOFGroup()\n",
    "    fg.fit(freqs,trial_psd, freq_lims)\n",
    "    for i in range(trial_psd.shape[0]):\n",
    "        ds_layer_resid_offsets[t,i]=fg[i].aperiodic_params[0]\n",
    "        ds_layer_resid_slopes[t,i]=fg[i].aperiodic_params[1]\n",
    "        ds_layer_resid_aperiodic[t,i,:]=gen_aperiodic(freqs,fg[i].aperiodic_params)\n",
    "\n",
    "us_layer_resid_offsets=np.zeros((n_trials,n_electrodes))\n",
    "us_layer_resid_slopes=np.zeros((n_trials,n_electrodes))\n",
    "us_layer_resid_aperiodic=np.zeros((n_trials,n_electrodes,len(freqs)))\n",
    "for t in range(mus_layer_resid_psd.shape[0]):\n",
    "    trial_psd=mus_layer_resid_psd[t,:,:]\n",
    "    \n",
    "    fg = FOOOFGroup()\n",
    "    fg.fit(freqs,trial_psd, freq_lims)\n",
    "    for i in range(trial_psd.shape[0]):\n",
    "        us_layer_resid_offsets[t,i]=fg[i].aperiodic_params[0]\n",
    "        us_layer_resid_slopes[t,i]=fg[i].aperiodic_params[1]\n",
    "        us_layer_resid_aperiodic[t,i,:]=gen_aperiodic(freqs,fg[i].aperiodic_params)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6c23ac1",
   "metadata": {},
   "source": [
    "**Plot spectra and parameters**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "29af8e65",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams.update({\n",
    "    'font.size': 14,\n",
    "    'axes.spines.right': False,\n",
    "    'axes.spines.top': False,\n",
    "    'xtick.major.size': 6,\n",
    "    'xtick.major.width': 1.2,\n",
    "    'ytick.major.size': 6,\n",
    "    'ytick.major.width': 1.2,\n",
    "    'legend.frameon': False,\n",
    "    'legend.handletextpad': 0.1,\n",
    "    'svg.fonttype': 'none',\n",
    "    'text.usetex': False\n",
    "})\n",
    "\n",
    "fig=plt.figure(figsize=(12,4))\n",
    "undetected_color=np.array([0,76.5,99.2])/100\n",
    "detected_color=np.array([98.4,54.1,1.2])/100\n",
    "\n",
    "gs = GridSpec(1, 4, width_ratios=[.275, .275, .225, .225])\n",
    "\n",
    "ax1=fig.add_subplot(gs[0])\n",
    "#m_detected=np.mean(ds_layer_aperiodic,axis=0)\n",
    "m_detected=np.log10(np.mean(mds_layer_resid_psd,axis=0))\n",
    "ax1.set_xscale('log')\n",
    "# ax1.set_yscale('log')\n",
    "for i in range(n_electrodes):\n",
    "    label=None\n",
    "    if i==5:\n",
    "        label='superficial'\n",
    "    if i==12:\n",
    "        label='middle'\n",
    "    if i==24:\n",
    "        label='deep'\n",
    "    ax1.plot(freqs,m_detected[i,:],color=detected_color,alpha=(i+1)/n_electrodes,label=label)\n",
    "plt.legend()\n",
    "# ax1.set_xlim([.1,125])\n",
    "ax1.set_xlabel('Frequency (Hz)')\n",
    "ax1.set_ylabel('Power')\n",
    "    \n",
    "ax2=fig.add_subplot(gs[1])\n",
    "# m_undetected=np.mean(us_layer_aperiodic,axis=0)\n",
    "m_undetected=np.log10(np.mean(mus_layer_resid_psd,axis=0))\n",
    "ax2.set_xscale('log')\n",
    "# ax2.set_yscale('log')\n",
    "for i in range(n_electrodes):\n",
    "    label=None\n",
    "    if i==5:\n",
    "        label='superficial'\n",
    "    if i==12:\n",
    "        label='middle'\n",
    "    if i==24:\n",
    "        label='deep'\n",
    "    ax2.plot(freqs,m_undetected[i,:],color=undetected_color,alpha=(i+1)/n_electrodes,label=label)\n",
    "plt.legend()\n",
    "#ax2.set_xlim([.1,125])\n",
    "ax2.set_xlabel('Frequency (Hz)')\n",
    "\n",
    "ax3=fig.add_subplot(gs[2])\n",
    "m_detected=np.mean(ds_layer_resid_offsets,axis=0)\n",
    "se_detected=np.std(ds_layer_resid_offsets,axis=0)\n",
    "ax3.plot(m_detected,np.arange(n_electrodes),\n",
    "         label='detected',\n",
    "         color=detected_color)\n",
    "ax3.fill_betweenx(np.arange(n_electrodes),\n",
    "                  m_detected-se_detected,\n",
    "                  m_detected+se_detected,\n",
    "                  alpha=0.5,\n",
    "                  color=detected_color)\n",
    "\n",
    "m_undetected=np.mean(us_layer_resid_offsets,axis=0)\n",
    "se_undetected=np.std(us_layer_resid_offsets,axis=0)\n",
    "ax3.plot(m_undetected,\n",
    "         np.arange(n_electrodes),\n",
    "         label='undetected',\n",
    "         color=undetected_color)\n",
    "ax3.fill_betweenx(np.arange(n_electrodes),\n",
    "                  m_undetected-se_undetected,\n",
    "                  m_undetected+se_undetected,\n",
    "                  alpha=0.5,\n",
    "                  color=undetected_color)\n",
    "ax3.set_ylim([n_electrodes-1,0])\n",
    "ax3.set_ylabel('Virtual contact')\n",
    "ax3.set_xlabel('Offset')\n",
    "ax3.legend(loc='lower right')\n",
    "\n",
    "ax4=fig.add_subplot(gs[3])\n",
    "m_detected=np.mean(ds_layer_resid_slopes,axis=0)\n",
    "se_detected=np.std(ds_layer_resid_slopes,axis=0)\n",
    "ax4.plot(m_detected,np.arange(n_electrodes),\n",
    "         label='detected',\n",
    "         color=detected_color)\n",
    "ax4.fill_betweenx(np.arange(n_electrodes),\n",
    "                  m_detected-se_detected,\n",
    "                  m_detected+se_detected,\n",
    "                  alpha=0.5,\n",
    "                  color=detected_color)\n",
    "\n",
    "m_undetected=np.mean(us_layer_resid_slopes,axis=0)\n",
    "se_undetected=np.std(us_layer_resid_slopes,axis=0)\n",
    "ax4.plot(m_undetected,\n",
    "         np.arange(n_electrodes),\n",
    "         label='undetected',\n",
    "         color=undetected_color)\n",
    "ax4.fill_betweenx(np.arange(n_electrodes),\n",
    "                  m_undetected-se_undetected,\n",
    "                  m_undetected+se_undetected,\n",
    "                  alpha=0.5,\n",
    "                  color=undetected_color)\n",
    "ax4.set_ylim([n_electrodes-1,0])\n",
    "ax4.set_xlabel('Slope')\n",
    "\n",
    "plt.tight_layout()\n",
    "# plt.savefig('aan-e_i.svg')\n",
    "# plt.savefig('aan-e_i.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b8698eef",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure()\n",
    "m_detected=np.log10(np.mean(mds_layer_resid_psd,axis=0))\n",
    "m_undetected=np.log10(np.mean(mus_layer_resid_psd,axis=0))\n",
    "im=plt.imshow(m_detected-m_undetected,aspect='auto',extent=(freqs[0], freqs[-1], n_electrodes-1, 0))\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Virtual contact')\n",
    "cbar=plt.colorbar(im)\n",
    "cbar.set_label('Log Power Difference\\n(Detected - Undetected)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8c6dad7c",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_rel_power=np.zeros((n_electrodes,len(freqs)))\n",
    "for i in range(len(freqs)):\n",
    "    ds_rel_power[:,i]=m_detected[:,i]/np.max(m_detected[:,i])\n",
    "im=plt.imshow(ds_rel_power,aspect='auto',extent=(freqs[0], freqs[-1], n_electrodes-1, 0))\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Virtual contact')\n",
    "cbar=plt.colorbar(im)\n",
    "cbar.set_label('Relative Power (Detected)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7c3ede10",
   "metadata": {},
   "outputs": [],
   "source": [
    "us_rel_power=np.zeros((n_electrodes,len(freqs)))\n",
    "for i in range(len(freqs)):\n",
    "    us_rel_power[:,i]=m_undetected[:,i]/np.max(m_undetected[:,i])\n",
    "im=plt.imshow(us_rel_power,aspect='auto',extent=(freqs[0], freqs[-1], n_electrodes-1, 0))\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Virtual contact')\n",
    "cbar=plt.colorbar(im)\n",
    "cbar.set_label('Relative Power (Undetected)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f28237a3",
   "metadata": {},
   "outputs": [],
   "source": [
    "im=plt.imshow(ds_rel_power-us_rel_power,aspect='auto',extent=(freqs[0], freqs[-1], n_electrodes-1, 0))\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Virtual contact')\n",
    "cbar=plt.colorbar(im)\n",
    "cbar.set_label('Relative Power Difference\\n(Detected - Undetected)')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c9b9323",
   "metadata": {},
   "source": [
    "**Compute power spectra over whole trial after regressing out mean response**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f2c970e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compute power spectral density from STFT after regressing out mean - detected stimuli\n",
    "ds_mean=np.mean(ds_trial_signals,axis=0)\n",
    "ds_trial_resids=np.zeros(ds_trial_signals.shape)\n",
    "for t_idx in range(n_trials):\n",
    "    for e_idx in range(n_electrodes):\n",
    "        # Regress out ERF\n",
    "        slope, intercept, r, p, se = linregress(ds_mean[e_idx,:], ds_trial_signals[t_idx, e_idx, :])\n",
    "        ds_trial_resids[t_idx,e_idx,:] = ds_trial_signals[t_idx, e_idx, :] - (intercept + slope * ds_mean[e_idx,:])\n",
    "freqs, times, Zxx = scipy.signal.stft(ds_trial_resids, fs=srate, window='hann', nperseg=winsize,\n",
    "                                      noverlap=overlap, nfft=int(winsize * 20), detrend='constant',\n",
    "                                      return_onesided=True, boundary='zeros', padded=True, axis=-1)\n",
    "ds_layer_resid_psd = np.abs(Zxx) ** 2\n",
    "f_idx=(freqs>=freq_lims[0]) & (freqs<freq_lims[1])\n",
    "freqs=freqs[f_idx]\n",
    "ds_layer_resid_psd=ds_layer_resid_psd[:,:,f_idx,:]\n",
    "mds_layer_resid_psd=np.mean(ds_layer_resid_psd,axis=-1)\n",
    "\n",
    "# Compute power spectral density from STFT after regressing out mean - undetected stimuli\n",
    "us_mean=np.mean(us_trial_signals,axis=0)\n",
    "us_trial_resids=np.zeros(us_trial_signals.shape)\n",
    "for t_idx in range(n_trials):\n",
    "    for e_idx in range(n_electrodes):\n",
    "        # Regress out ERF\n",
    "        slope, intercept, r, p, se = linregress(us_mean[e_idx,:], us_trial_signals[t_idx, e_idx, :])\n",
    "        us_trial_resids[t_idx,e_idx,:] = us_trial_signals[t_idx, e_idx, :] - (intercept + slope * us_mean[e_idx,:])\n",
    "freqs, times, Zxx = scipy.signal.stft(us_trial_resids, fs=srate, window='hann', nperseg=winsize,\n",
    "                                      noverlap=overlap, nfft=int(winsize * 20), detrend='constant',\n",
    "                                      return_onesided=True, boundary='zeros', padded=True, axis=-1)\n",
    "us_layer_resid_psd = np.abs(Zxx) ** 2\n",
    "f_idx=(freqs>=freq_lims[0]) & (freqs<freq_lims[1])\n",
    "freqs=freqs[f_idx]\n",
    "us_layer_resid_psd=us_layer_resid_psd[:,:,f_idx,:]\n",
    "mus_layer_resid_psd=np.mean(us_layer_resid_psd,axis=-1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb1aabb2",
   "metadata": {},
   "source": [
    "**Parameterize power spectra**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "157e3500",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n",
      "Running FOOOFGroup across 25 power spectra.\n",
      "\n",
      "FOOOF WARNING: Lower-bound peak width limit is < or ~= the frequency resolution: 0.50 <= 0.50\n",
      "\tLower bounds below frequency-resolution have no effect (effective lower bound is the frequency resolution).\n",
      "\tToo low a limit may lead to overfitting noise as small bandwidth peaks.\n",
      "\tWe recommend a lower bound of approximately 2x the frequency resolution.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "ds_layer_resid_offsets=np.zeros((n_trials,n_electrodes))\n",
    "ds_layer_resid_slopes=np.zeros((n_trials,n_electrodes))\n",
    "ds_layer_resid_aperiodic=np.zeros((n_trials,n_electrodes,len(freqs)))\n",
    "for t in range(mds_layer_resid_psd.shape[0]):\n",
    "    trial_psd=mds_layer_resid_psd[t,:,:]\n",
    "    \n",
    "    fg = FOOOFGroup()\n",
    "    fg.fit(freqs,trial_psd, freq_lims)\n",
    "    for i in range(trial_psd.shape[0]):\n",
    "        ds_layer_resid_offsets[t,i]=fg[i].aperiodic_params[0]\n",
    "        ds_layer_resid_slopes[t,i]=fg[i].aperiodic_params[1]\n",
    "        ds_layer_resid_aperiodic[t,i,:]=gen_aperiodic(freqs,fg[i].aperiodic_params)\n",
    "\n",
    "us_layer_resid_offsets=np.zeros((n_trials,n_electrodes))\n",
    "us_layer_resid_slopes=np.zeros((n_trials,n_electrodes))\n",
    "us_layer_resid_aperiodic=np.zeros((n_trials,n_electrodes,len(freqs)))\n",
    "for t in range(mus_layer_resid_psd.shape[0]):\n",
    "    trial_psd=mus_layer_resid_psd[t,:,:]\n",
    "    \n",
    "    fg = FOOOFGroup()\n",
    "    fg.fit(freqs,trial_psd, freq_lims)\n",
    "    for i in range(trial_psd.shape[0]):\n",
    "        us_layer_resid_offsets[t,i]=fg[i].aperiodic_params[0]\n",
    "        us_layer_resid_slopes[t,i]=fg[i].aperiodic_params[1]\n",
    "        us_layer_resid_aperiodic[t,i,:]=gen_aperiodic(freqs,fg[i].aperiodic_params)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec64bbef",
   "metadata": {},
   "source": [
    "**Plot spectra and parameters**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bededd35",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams.update({\n",
    "    'font.size': 14,\n",
    "    'axes.spines.right': False,\n",
    "    'axes.spines.top': False,\n",
    "    'xtick.major.size': 6,\n",
    "    'xtick.major.width': 1.2,\n",
    "    'ytick.major.size': 6,\n",
    "    'ytick.major.width': 1.2,\n",
    "    'legend.frameon': False,\n",
    "    'legend.handletextpad': 0.1,\n",
    "    'svg.fonttype': 'none',\n",
    "    'text.usetex': False\n",
    "})\n",
    "\n",
    "fig=plt.figure(figsize=(12,4))\n",
    "undetected_color=np.array([0,76.5,99.2])/100\n",
    "detected_color=np.array([98.4,54.1,1.2])/100\n",
    "\n",
    "gs = GridSpec(1, 4, width_ratios=[.275, .275, .225, .225])\n",
    "\n",
    "ax1=fig.add_subplot(gs[0])\n",
    "#m_detected=np.mean(ds_layer_aperiodic,axis=0)\n",
    "m_detected=np.log10(np.mean(mds_layer_resid_psd,axis=0))\n",
    "ax1.set_xscale('log')\n",
    "# ax1.set_yscale('log')\n",
    "for i in range(n_electrodes):\n",
    "    label=None\n",
    "    if i==5:\n",
    "        label='superficial'\n",
    "    if i==12:\n",
    "        label='middle'\n",
    "    if i==24:\n",
    "        label='deep'\n",
    "    ax1.plot(freqs,m_detected[i,:],color=detected_color,alpha=(i+1)/n_electrodes,label=label)\n",
    "plt.legend()\n",
    "# ax1.set_xlim([.1,125])\n",
    "ax1.set_xlabel('Frequency (Hz)')\n",
    "ax1.set_ylabel('Power')\n",
    "    \n",
    "ax2=fig.add_subplot(gs[1])\n",
    "# m_undetected=np.mean(us_layer_aperiodic,axis=0)\n",
    "m_undetected=np.log10(np.mean(mus_layer_resid_psd,axis=0))\n",
    "ax2.set_xscale('log')\n",
    "# ax2.set_yscale('log')\n",
    "for i in range(n_electrodes):\n",
    "    label=None\n",
    "    if i==5:\n",
    "        label='superficial'\n",
    "    if i==12:\n",
    "        label='middle'\n",
    "    if i==24:\n",
    "        label='deep'\n",
    "    ax2.plot(freqs,m_undetected[i,:],color=undetected_color,alpha=(i+1)/n_electrodes,label=label)\n",
    "plt.legend()\n",
    "#ax2.set_xlim([.1,125])\n",
    "ax2.set_xlabel('Frequency (Hz)')\n",
    "\n",
    "ax3=fig.add_subplot(gs[2])\n",
    "m_detected=np.mean(ds_layer_resid_offsets,axis=0)\n",
    "se_detected=np.std(ds_layer_resid_offsets,axis=0)\n",
    "ax3.plot(m_detected,np.arange(n_electrodes),\n",
    "         label='detected',\n",
    "         color=detected_color)\n",
    "ax3.fill_betweenx(np.arange(n_electrodes),\n",
    "                  m_detected-se_detected,\n",
    "                  m_detected+se_detected,\n",
    "                  alpha=0.5,\n",
    "                  color=detected_color)\n",
    "\n",
    "m_undetected=np.mean(us_layer_resid_offsets,axis=0)\n",
    "se_undetected=np.std(us_layer_resid_offsets,axis=0)\n",
    "ax3.plot(m_undetected,\n",
    "         np.arange(n_electrodes),\n",
    "         label='undetected',\n",
    "         color=undetected_color)\n",
    "ax3.fill_betweenx(np.arange(n_electrodes),\n",
    "                  m_undetected-se_undetected,\n",
    "                  m_undetected+se_undetected,\n",
    "                  alpha=0.5,\n",
    "                  color=undetected_color)\n",
    "ax3.set_ylim([n_electrodes-1,0])\n",
    "ax3.set_ylabel('Virtual contact')\n",
    "ax3.set_xlabel('Offset')\n",
    "ax3.legend(loc='lower right')\n",
    "\n",
    "ax4=fig.add_subplot(gs[3])\n",
    "m_detected=np.mean(ds_layer_resid_slopes,axis=0)\n",
    "se_detected=np.std(ds_layer_resid_slopes,axis=0)\n",
    "ax4.plot(m_detected,np.arange(n_electrodes),\n",
    "         label='detected',\n",
    "         color=detected_color)\n",
    "ax4.fill_betweenx(np.arange(n_electrodes),\n",
    "                  m_detected-se_detected,\n",
    "                  m_detected+se_detected,\n",
    "                  alpha=0.5,\n",
    "                  color=detected_color)\n",
    "\n",
    "m_undetected=np.mean(us_layer_resid_slopes,axis=0)\n",
    "se_undetected=np.std(us_layer_resid_slopes,axis=0)\n",
    "ax4.plot(m_undetected,\n",
    "         np.arange(n_electrodes),\n",
    "         label='undetected',\n",
    "         color=undetected_color)\n",
    "ax4.fill_betweenx(np.arange(n_electrodes),\n",
    "                  m_undetected-se_undetected,\n",
    "                  m_undetected+se_undetected,\n",
    "                  alpha=0.5,\n",
    "                  color=undetected_color)\n",
    "ax4.set_ylim([n_electrodes-1,0])\n",
    "ax4.set_xlabel('Slope')\n",
    "\n",
    "plt.tight_layout()\n",
    "# plt.savefig('aan-e_i.svg')\n",
    "# plt.savefig('aan-e_i.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "09146e21",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure()\n",
    "m_detected=np.log10(np.mean(mds_layer_resid_psd,axis=0))\n",
    "m_undetected=np.log10(np.mean(mus_layer_resid_psd,axis=0))\n",
    "im=plt.imshow(m_detected-m_undetected,aspect='auto',extent=(freqs[0], freqs[-1], n_electrodes-1, 0))\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Virtual contact')\n",
    "cbar=plt.colorbar(im)\n",
    "cbar.set_label('Log Power Difference\\n(Detected - Undetected)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "41effcdb",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_rel_power=np.zeros((n_electrodes,len(freqs)))\n",
    "for i in range(len(freqs)):\n",
    "    ds_rel_power[:,i]=m_detected[:,i]/np.max(m_detected[:,i])\n",
    "im=plt.imshow(ds_rel_power,aspect='auto',extent=(freqs[0], freqs[-1], n_electrodes-1, 0))\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Virtual contact')\n",
    "cbar=plt.colorbar(im)\n",
    "cbar.set_label('Relative Power (Detected)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "edc8fd73",
   "metadata": {},
   "outputs": [],
   "source": [
    "us_rel_power=np.zeros((n_electrodes,len(freqs)))\n",
    "for i in range(len(freqs)):\n",
    "    us_rel_power[:,i]=m_undetected[:,i]/np.max(m_undetected[:,i])\n",
    "im=plt.imshow(us_rel_power,aspect='auto',extent=(freqs[0], freqs[-1], n_electrodes-1, 0))\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Virtual contact')\n",
    "cbar=plt.colorbar(im)\n",
    "cbar.set_label('Relative Power (Undetected)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "edb16923",
   "metadata": {},
   "outputs": [],
   "source": [
    "im=plt.imshow(ds_rel_power-us_rel_power,aspect='auto',extent=(freqs[0], freqs[-1], n_electrodes-1, 0))\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Virtual contact')\n",
    "cbar=plt.colorbar(im)\n",
    "cbar.set_label('Relative Power Difference\\n(Detected - Undetected)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "164ea153",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e3a3c711-91ce-41f9-9c52-e4b19fb77ed6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "285ded5a-cffa-4b4c-b110-22dee5873c67",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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