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{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "59f50187-f73f-471b-b668-9126e6f48501",
   "metadata": {},
   "source": [
    "# Learning high-resolution data from low-resolution\n",
    "\n",
    "This is an example notebook showing how to use the `pes_to_spec` infrastructure in this package.\n",
    "\n",
    "We start by importing some modules. The key module here is called `pes_to_spec`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d44af0b6-9c00-4e70-b49b-d74ed562e92f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "# add the pes_to_spec main directory\n",
    "# (change this depending on where you started the notebook if needed, or comment it out if you have done pip install in pes_to_spec)\n",
    "sys.path.append('..')\n",
    "\n",
    "# you meay need to do pip install matplotlib seaborn extra_data for this notebook, additionally\n",
    "# for this notebook the following packages are needed:\n",
    "# pip install \"numpy>=1.21\" \"scipy>=1.6\" \"scikit-learn>=1.2.0\" torch torchbnn  matplotlib seaborn extra_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "da002d3e-c0da-419b-922b-0ab5c6deece8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.gridspec import GridSpec \n",
    "import seaborn as sns\n",
    "\n",
    "import lmfit\n",
    "import scipy\n",
    "from extra_data import open_run, by_id\n",
    "from itertools import product\n",
    "from pes_to_spec.model import Model, matching_ids\n",
    "\n",
    "from typing import Any, Dict"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "494a729c-dff4-4501-b828-fba2aaae5a23",
   "metadata": {},
   "source": [
    "# Input data\n",
    "\n",
    "Read data from two runs. One shall be used for training the model. The second one is used for testing it.\n",
    "Note that the data in the training run must be large enough, compared to the number of model parameters.\n",
    "\n",
    "Only the SPEC, PES and XGM data is used for training, while only the PES and XGM data is needed for testing.\n",
    "However, more data is collected here to validate the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4a301f2a-dedb-46e4-b096-fc9c6cf5b23a",
   "metadata": {},
   "outputs": [],
   "source": [
    "run = open_run(proposal=900331, run=69)\n",
    "run_test = open_run(proposal=900331, run=70)\n",
    "\n",
    "# useful names to avoid repeating it all over the notebook, in case they ever change\n",
    "spec_name = \"SA3_XTD10_SPECT/MDL/SPECTROMETER_SCS_NAVITAR:output\"\n",
    "pes_name = \"SA3_XTD10_PES/ADC/1:network\"\n",
    "xgm_name = \"SA3_XTD10_XGM/XGM/DOOCS:output\"\n",
    "\n",
    "pres_name = \"SA3_XTD10_PES/GAUGE/G30310F\"\n",
    "volt_name = \"SA3_XTD10_PES/MDL/DAQ_MPOD\"\n",
    "\n",
    "# PES channels\n",
    "channels = [f\"channel_{i}_{l}\" for i, l in product([1, 3, 4], [\"A\", \"B\", \"C\", \"D\"])]\n",
    "\n",
    "def get_gas(run) -> str:\n",
    "    \"\"\"Get gas in chamber for logging.\"\"\"\n",
    "    gas_sources = [\n",
    "                  \"SA3_XTD10_PES/DCTRL/V30300S_NITROGEN\",\n",
    "                  \"SA3_XTD10_PES/DCTRL/V30310S_NEON\",\n",
    "                  \"SA3_XTD10_PES/DCTRL/V30320S_KRYPTON\",\n",
    "                  \"SA3_XTD10_PES/DCTRL/V30330S_XENON\",\n",
    "              ]\n",
    "    gas_active = list()\n",
    "    for gas in gas_sources:\n",
    "        # check if this gas source is interlocked\n",
    "        if gas in run.all_sources and run[gas, \"interlock.AActionState.value\"].ndarray().sum() == 0:\n",
    "            # it is not, so this gas was used\n",
    "            gas_active += [gas.split(\"/\")[-1].split(\"_\")[-1]]\n",
    "    gas = \"_\".join(gas_active)\n",
    "    return gas\n",
    "\n",
    "def get_tids(run, need_spec:bool=True) -> np.ndarray:\n",
    "    \"\"\"Get which train IDs contain all necessary inputs for training.\"\"\"\n",
    "    spec_tid = run[spec_name, \"data.trainId\"].ndarray()\n",
    "    pes_tid = run[pes_name, \"digitizers.trainId\"].ndarray()\n",
    "    xgm_tid = run[xgm_name, \"data.trainId\"].ndarray()\n",
    "\n",
    "    # match tids to be sure we have all inputs:\n",
    "    tids = matching_ids(spec_tid, pes_tid, xgm_tid)\n",
    "    return tids\n",
    "\n",
    "def get_data(run, tids) -> Dict[str, Any]:\n",
    "    \"\"\"Get all relevant data.\"\"\"\n",
    "    data = dict()\n",
    "    data[\"int\"] = run[xgm_name, \"data.intensitySa3TD\"].select_trains(by_id[tids]).ndarray()[:, 0][:, np.newaxis]\n",
    "    data[\"pressure\"] = run[pres_name, \"value\"].select_trains(by_id[tids]).ndarray()\n",
    "    data[\"voltage\"] = run[volt_name, \"u212.value\"].select_trains(by_id[tids]).ndarray()\n",
    "    data[\"energy\"] = run[spec_name, \"data.photonEnergy\"].select_trains(by_id[tids]).ndarray()\n",
    "    data[\"spec\"] = run[spec_name, \"data.intensityDistribution\"].select_trains(by_id[tids]).ndarray()\n",
    "    data[\"pes\"] = {ch: run[pes_name,\n",
    "                           f\"digitizers.{ch}.raw.samples\"].select_trains(by_id[tids]).ndarray()\n",
    "                    for ch in channels}\n",
    "    data[\"gas\"] = get_gas(run)\n",
    "    return data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "210c0550-1abb-43a0-99a5-7c35d2766be0",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# get the matched train IDs\n",
    "tids = get_tids(run)\n",
    "\n",
    "# we don't need the spec for testing in reality,\n",
    "# but it is nice to plot it in the test run too,\n",
    "# to check that this works during validation\n",
    "test_tids = get_tids(run_test, need_spec=True)\n",
    "\n",
    "# get the data\n",
    "data = get_data(run, tids)\n",
    "data_test = get_data(run_test, test_tids)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "017865a1-057f-48c7-8bef-a6e40490de2c",
   "metadata": {},
   "source": [
    "Now the `data` and `data_test` dictionaries contain the necessary information about the training and test runs.\n",
    "The code above also selected only entries with train IDs on which at least SPEC, PES and XGM were present.\n",
    "\n",
    "Note that for training, it is assumed that only one pulse is present. For testing there is no such requirement.\n",
    "\n",
    "First output some general information about the conditions of the measurement device."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "956105a6-d37e-453c-bfeb-2b1c876ee3f2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gas in training: NEON\n",
      "Gas in testing: NEON\n"
     ]
    }
   ],
   "source": [
    "print(f\"Gas in training: {data['gas']}\")\n",
    "print(f\"Gas in testing: {data_test['gas']}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4654f205-edc6-45f7-97bd-0d088c38edb0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Voltage in training: -116.00 +/- 0.01\n",
      "Voltage in testing: -116.00 +/- 0.01\n"
     ]
    }
   ],
   "source": [
    "print(f\"Voltage in training: {np.mean(data['voltage']):0.2f} +/- {np.std(data['voltage']):0.2f}\")\n",
    "print(f\"Voltage in testing: {np.mean(data_test['voltage']):0.2f} +/- {np.std(data_test['voltage']):0.2f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "fa662544-3caa-4404-bb61-fa41add82642",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pressure in training: 1.29e-06 +/- 3.95e-08\n",
      "Pressure in testing: 1.29e-06 +/- 3.91e-08\n"
     ]
    }
   ],
   "source": [
    "print(f\"Pressure in training: {np.mean(data['pressure']):0.2e} +/- {np.std(data['pressure']):0.2e}\")\n",
    "print(f\"Pressure in testing: {np.mean(data_test['pressure']):0.2e} +/- {np.std(data_test['pressure']):0.2e}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9b62e3a-aff9-4436-905d-ea02c11aecf6",
   "metadata": {},
   "source": [
    "## Using the virtual spectrometer"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5962e483-60da-4c70-bb09-dce5fc9745e0",
   "metadata": {},
   "source": [
    "Now we will actually train the model. We do that by creating a `Model` object (from `pes_to_spec`) and calling the `fit` function.\n",
    "The `fit` function requires the PES intensity, the SPEC intensity, the energy axis from SPEC (stored as a reference only), as well as the energy measured in the XGM (which has better resolution than the integral of the PES)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a0adb57b-7496-4781-9511-ac2a8d05658d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Checking data quality in high-resolution data.\n",
      "Selected 7165 of 7165 samples\n",
      "Fitting PCA on low-resolution data.\n",
      "Using 1000 comp. for PES PCA (asked for 1000, out of 7201, in 7165 samples).\n",
      "Fitting PCA on high-resolution data.\n",
      "Fitting outlier detection\n",
      "Fitting model.\n",
      "Calculate PCA unc. on high-resolution data.\n",
      "Calculate transfer function\n",
      "Resolution: 0.9825132876894322\n",
      "Calculate PCA on channel_1_A\n",
      "Calculate PCA on channel_1_B\n",
      "Calculate PCA on channel_1_C\n",
      "Calculate PCA on channel_1_D\n",
      "Calculate PCA on channel_3_A\n",
      "Calculate PCA on channel_3_B\n",
      "Calculate PCA on channel_3_C\n",
      "Calculate PCA on channel_3_D\n",
      "Calculate PCA on channel_4_A\n",
      "Calculate PCA on channel_4_B\n",
      "Calculate PCA on channel_4_C\n",
      "Calculate PCA on channel_4_D\n",
      "End of fit.\n"
     ]
    }
   ],
   "source": [
    "# this is the main object holding all\n",
    "# information needed for training and prediction\n",
    "# the default parameters should be sufficient in most times\n",
    "model = Model(channels=channels,\n",
    "              high_res_sigma=0.0,\n",
    "             )\n",
    "\n",
    "# this trains the model\n",
    "# the first parameter is expected to be a dictionary with the channel name as a key\n",
    "model.fit(data['pes'],\n",
    "          data['spec'],\n",
    "          data['energy'],\n",
    "          pulse_energy=data['int'])\n",
    "\n",
    "# save it for later usage:\n",
    "model.save(\"model.joblib\")\n",
    "\n",
    "# load a model (you can start from here if working on an existing model)\n",
    "model = Model.load(\"model.joblib\")\n",
    "\n",
    "# and use it to map a low-resolution spectrum to a high-resolution one\n",
    "# as before, the low_resolution_raw_data refers to a dictionary mapping the channel name\n",
    "# in the format \"channel_[1-4]_[A-D]\" to the 2D numpy array with shape (number_of_train_IDs, features)\n",
    "# all names and shapes must match the format in training, except for the number_of_train_IDs, which may vary\n",
    "pred = model.predict(data['pes'], pulse_energy=data['int'])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0286ae3-1a59-468f-ae40-c3ed94b7b301",
   "metadata": {},
   "source": [
    "Now we can try it in the test dataset:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ffc06362-3479-4cb9-b102-b438a83d2950",
   "metadata": {},
   "source": [
    "We can predict it in the training data itself, but this is a bit biased, since we used the same information to fit the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "917156f3-9476-48e0-9121-5f75f185045f",
   "metadata": {},
   "outputs": [],
   "source": [
    "pred = model.predict(data_test['pes'], pulse_energy=data_test['int'])\n",
    "\n",
    "# add the references in this array in the same array format, so we can plot them later\n",
    "pred[\"energy\"] = model.get_energy_values()\n",
    "\n",
    "pred['spec'] = data_test['spec'][:, np.newaxis, :]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77866435-1cb6-40ac-a9a5-8f2ae37017b7",
   "metadata": {},
   "source": [
    "Let's try to predict in the independent run in the test dataset. The performance of the model varies a lot if the beam intensity is very different from the training one. To ensure we take a train ID to visualize that is relatively high intensity, we sort the train IDs by XGM intensity and then choose the highest intensity one.\n",
    "One could try other train IDs.\n",
    "\n",
    "For train IDs with close to zero beam intensity, there is a relatively larger error, since the training data did not contain any of those samples and the signal-to-noise ratio is relatively high."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ed62606a-4ea7-4e0a-8b61-73e682cacf04",
   "metadata": {},
   "outputs": [],
   "source": [
    "# choose train ID of the test dataset by XGM intensity\n",
    "test_intensity = np.argsort(data_test['int'][:,0])\n",
    "example_tid = test_intensity[-1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f931e9e0-84a7-4e4f-bfad-588bfe77267c",
   "metadata": {},
   "source": [
    "Now we can actually plot it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "fd42984c-554c-4c69-bf8a-119eeb0cca62",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot(data):\n",
    "    \"\"\"Plot prediction and expectation.\"\"\"\n",
    "    fig = plt.figure(figsize=(12, 8))\n",
    "    gs = GridSpec(1, 1)\n",
    "    ax = fig.add_subplot(gs[0, 0])\n",
    "    ax.plot(data[\"energy\"], data[\"spec\"], c='b', lw=3, label=\"High-res. measurement\")\n",
    "    ax.plot(data[\"energy\"], data[\"expected\"], c='r', ls='--', lw=3, label=\"High-res. prediction\")\n",
    "    ax.fill_between(data[\"energy\"], data[\"expected\"] - data[\"total_unc\"], data[\"expected\"] + data[\"total_unc\"], facecolor='gold', alpha=0.5, label=\"68% unc.\")\n",
    "    ax.legend(frameon=False, borderaxespad=0, loc='upper left')\n",
    "    ax.spines['top'].set_visible(False)\n",
    "    ax.spines['right'].set_visible(False)\n",
    "    Y = np.amax(data[\"spec\"])\n",
    "    ax.set(\n",
    "            xlabel=\"Photon energy [eV]\",\n",
    "            ylabel=\"Intensity\",\n",
    "            ylim=(0, 1.3*Y))\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "bbbf77b5-f914-4b47-8ab6-fd3a89d0f983",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# select the correct train ID for the data to plot\n",
    "# except for the energy axis, which is always the same\n",
    "plot({k: v[example_tid, 0, :] if k != \"energy\" else v\n",
    "      for k, v in pred.items()\n",
    "      if k in [\"expected\", \"total_unc\", \"spec\", \"energy\"]})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a9c996e-1462-45a3-a9af-7ccbcc37ad69",
   "metadata": {},
   "source": [
    "## Further studies and validation\n",
    "\n",
    "The next items show methods to estimate the resolution and improve the results.\n",
    "\n",
    "They are not done by default, as they make further assumptions, which cannot always be applied. The code for such analyses is shown here, for reference, but one should be careful about how they are used."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eca3a06a-d613-4206-b128-6d81031de1d1",
   "metadata": {},
   "source": [
    "### Resolution assessment using the autocorrelation\n",
    "\n",
    "We establish the resolution of the virtual spectrometer using the autocorrelation function, which estimates which level of detail can be observed in the test dataset.\n",
    "\n",
    "The autocorrelation function cannot assess which effect are physically relevant and which are simply noise. Therefore this method can only provide a rough estimate of the resolution. It is not expected to be very precise, but it can be used for a quick assessment.\n"
   "execution_count": 15,
   "id": "1491550c-6940-425e-a557-f2cd381d287b",
   "source": [
    "def fwhm(x: np.ndarray, y: np.ndarray) -> float:\n",
    "    \"\"\"Return the full width at half maximum of x.\"\"\"\n",
    "    # half maximum\n",
    "    half_max = np.amax(y)*0.5\n",
    "    # signum(y - half_max) is zero before and after the half maximum,\n",
    "    # and it is 1 in the range above the half maximum\n",
    "    # The difference will be +/- 1 only at the transitions\n",
    "    d = np.diff(np.sign(y - half_max))\n",
    "    left_idx = np.where(d > 0)[0][0]\n",
    "    right_idx = np.where(d < 0)[-1][-1]\n",
    "    return x[right_idx] - x[left_idx]\n",
    "\n",
    "def autocorrelation(x: np.ndarray, y: np.ndarray) -> np.ndarray:\n",
    "    \"\"\"Given the energy axis in x and the intensity in y, calculate the auto-correlation function.\"\"\"\n",
    "    mean_y = np.mean(y, keepdims=True, axis=0)\n",
    "    e = x - np.mean(x)\n",
    "    Rxx = np.mean(np.fft.fftshift(np.fft.ifft(np.absolute(np.fft.fft(y - mean_y))**2), axes=(-1,)), axis=(0,1))\n",
    "    Rxx /= np.amax(Rxx)\n",
    "    return Rxx\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "45fc52a4-5716-42b9-adbd-a307d16c0c34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.17591992514901664, 1.05)"
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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MTERKSgpOnDiBm2++uc1jXBVEaZydOc8bo0ePxsGDB70+b+rUqbj//vsxZMgQ2fqeSy65BKtWrYIgCN1aH+XiWhf47LPP4vPPP+/0ed2Z2jdmzBgYjUZs3LjR3c3wyJEjyM/Pd0+v64irMnjs2DH8+OOPePLJJwF4qkDS6h4gJsCuBLulIUOGnPd33XXNuXPn4s0330SfPn0QHByMX/7yl62O279/P1JTUxEXF3fe5+FLqiZS3377Lf785z9j586dKCwsxEcffXTevQ9ycnKwcOFCHDhwAGlpaXj00Udx2223KRIvERER+U94eDhuuOEGLF68GFartct/3zMyMvDtt9/ixhtvhMlkQlxcHC699FKcO3cOzz77LH75y19iw4YN+Pzzz2GxWNznDRgwAP/4xz8wduxYWK1WLFq0yKsK0A8//ICNGzfiiiuuQEJCAn744QecO3cO2dnZ7mPsdjvmzZuHRx99FHl5eVi6dCnmz58PvV6PiIgIPPjgg1iwYAGcTicuvvhiVFVV4bvvvoPFYsGcOXMwf/58vPTSS7jxxhuxePFiREZGYtu2bRg3bhwGDRqEjIwM/O9//8ORI0cQGxvb4XS6RYsWYenSpcjKysKoUaOwZs0a7Nmzp91OeJ21bNky3H///YiMjMTMmTNhs9nw448/oqKiAgsXLkRCQgJCQkKwYcMGpKamwmw2IzIy8rzneWPGjBmtmlR0hmud1OrVq7Fq1Sr341OmTHGvi7rnnnu8vm5bnnzySSxatKjT1Sige1P7IiMjMW/ePCxcuBAxMTGwWCy47777MGHCBFx00UXu4wYPHozly5fjmmuuASA2fYmPj0ffvn2xb98+PPDAA7j66qtxxRVXuI/v378/fvvb3+K5555DbGwsPv74Y3cDmLZ05nfdZe7cuXjiiSfw+9//HjfddFOb/5/cvHmzOx5FCSr67LPPhD/84Q/Chx9+KAAQPvroow6PP3HihBAaGiosXLhQOHjwoPDSSy8JBoNB2LBhQ6fvWVVVJQAQqqqquhk9ERER+dr3338vABCuvPLKVj9bunSpMHLkSPf3c+bMEX7xi1+0Om7r1q3CiBEjBJPJJEjf6rz66qtCWlqaEBYWJtx6663CU089JaSnp7t/vmvXLmHs2LGC2WwWBgwYILz33ntCenq68Je//MV9TEfvVw4ePCjMmDFDiI+PF0wmkzBw4EDhpZdeahXvkiVLhNjYWCE8PFy48847hYaGBvcxTqdTWLFihTBo0CDBaDQK8fHxwowZM4RvvvnGfczevXuFK664QggNDRUiIiKEyZMnC7m5uYIgCEJJSYkwffp0ITw8XAAgbNq0STh58qQAQNi9e7csXofDITz++ONCnz59BKPRKIwcOVL4/PPP3T9v67xNmzYJAISKigr3Y2vWrBEiIyNl13777beFUaNGCcHBwUJ0dLRwySWXCB9++KH756tWrRLS0tIEvV4vTJkypVPntfc82lJWViaYzWbh8OHDHcbZlvT0dAGAUFhYKHs8IyNDACAUFBTIHm/v97Dla9XWayf10UcfCf5+a15fXy/cc889QnR0tBAaGipcc801rZ4nAGHNmjXu71988UUhNTVVMBqNQt++fYVHH31UsNlssnOOHj0qXHvttUJCQoIQGhoqjBgxQvj73//eYSyd+V13ueKKKwQAwvbt29t8TpGRkcLWrVu9eCU8upMb6AShxYRhleh0uvNWpB5++GF8+umn2L9/v/uxG2+8EZWVlbJ9DzpitVoRGRmJqqoq2adQRETUewiCgFNldcjd9h8YK3NhHn87RmUmITiIu4KQ/9x2222orKzExx9/rHYovcKiRYtgtVrbXFNDPcerr76Kjz76CF988UWXzu9ObhBQa6S2bt0q630PiKXb3/3ud+2eY7PZZD3lrVarv8IjIiKNEwQBb245ibe25iGrcivWBj8LAPjvkc0YrfsdLs9OwmM/H6JacwYi8p0//OEPeOWVV+B0Olut36Gew2g04qWXXlLl3gH1W1VUVORuu+mSmJgIq9Xa7sK75cuXIzIy0v3VsssKERH1DrW2Jtzz9i788dNDsJUX4Hmjp1XxbMM2XOn4Gv/ZW4CrXt6Cvacr1QuUiHwiKioKv//975lE9XB33HEHBg0apMq9e/xv1uLFi1FVVeX+On36tNohERGRwvLL6nDNK9/h8/1F0MOJvwS/glhdteyYJ4xrkaU7i8KqBvy/17fiw13tty4m6oq1a9dyWh9RDxJQiVRSUhKKi4tljxUXF8NisbTbVcdkMsFisci+iIio97A2NOKW1T/gaLG4b8n9pk8xSd+8z0pEMjD8egBACOx4M+wVmGCHvcmJhe/uxdeHi9u7LBER9XIBlUhNmDABGzdulD325Zdfdqr3PRER9T6CIOCRD37CqTJxn5NhcTrcH/RR8091wLWrgNkvAvFie+qMppNYnuXZe2bhu3txtrL9PVuIiKj3UjWRqqmpwZ49e9wb4p08eRJ79uxBfn4+AHFa3q233uo+/q677sKJEyfw0EMP4fDhw3jllVfw7rvvYsGCBWqET0REGvfW93n4bF8RAMBiDsJbkyqgdzSIPxwzB8icDASHAlf91X3ONeadmD5EXI9bWdeI+f/aBXtT25tKEhFR76VqIvXjjz9i9OjRGD16NABg4cKFGD16NJYsWQIAKCwsdCdVAJCZmYlPP/0UX375JUaOHInnn38eb7zxBmbMmKFK/EREpF0/nanEU58dcn//5/83ErGn/+c5YNgvPePUC4FIsRmR7uQ3eO7nGUiNFqeM786vxLMbDisSMxERBQ7N7COlFO4jRUTU8zmdAn6x8jvsO1sFALjj4kw8OiMTeLYf0FgHhMYC/3cUMEh2AdmwGNj2iji+5m/YGzMDv3ztezQ6BOh0wKf3TcaQFP7dICLqSbqTGwTUGikiIqLO+O9PBe4kanBSBB6aORjI3SQmUQAw6Ep5EgUA2bM940P/wci0KCycLrbUFQTgGValiIhIgokUERH1KLYmB/78vyPu7xdfmY3gID1w6L+eg6RJk0vaeCA0Thwf3wjYazF3Ugb6RIlT/L49eg6bj53zZ+ikgry8POh0Ovd6bepZNm7ciOzsbDgcDrVDIT+x2+3IyMjAjz/+qPi9mUgREVGP8o+tp3CmQuy0N3lAHKYMjAccjcCRz8QDgiOAzCmtT9QbgME/E8dN9cDxjTAbDVg0w7PR49OfHYbT2atmxCuqqKgIDzzwAPr37w+z2YzExERMmjQJr776Kurq6rp9/dtuuw1XX3217LG0tDQUFhZi2LBh3b6+lmktYVQqnoceegiPPvooDAYDAHEvL51O1+rrjTfewOHDh6HT6bBt2zbZNS666CKYzWY0NDS4H2toaIDZbMabb74JoO3fLQDIycmBTqdDZWWl7Pvo6GjZ9QBgx44d7nj8qaGhAffeey9iY2MRHh6O6667rtX2Qi3ddtttrV6zmTNnyo7JyMhodcwzzzzT5Tiff/75Nl8nAKirq4PFYsFf//pXBAcH48EHH8TDDz/c5Xt1FRMpIiLqMarqGvHS18cBADod8MisweIP8rYADZXieOAVgNHc9gWyr/KMD38CALhqZAqG9RHnzR8qtOLjPWf9EXqvd+LECYwePRpffPEFnn76aezevRtbt27FQw89hE8++QRfffVVu+c2NjZ2+b4GgwFJSUkICgo6/8GkSe39+2/ZsgW5ubm47rrrZI9bLBYUFhbKvm6++WYMHjwYSUlJyMnJcR9bXV2NXbt2IT4+XpZgbd26FTabDZdddlmXYo6IiMBHH30ke+zNN99E3759u3Q9byxYsAD//e9/8d577+Gbb75BQUEBrr322vOeN3PmTNlr9s4777Q65oknnpAdc99993U5zltuuQW1tbX48MMPW/3s/fffh91ux69//WsAwM0334wtW7bgwIEDXb5fVzCRIiKiHmP1dydRVS++qbpmdB8MTYkUf9CcFAFoe1qfS+YlgKl5sfGRDUCTHXq9Dr+fle0+ZMVXx+BgVcrn7rnnHgQFBeHHH3/E9ddfj+zsbPTr1w+/+MUv8Omnn2L2bM+/m06nw6uvvoqrrroKYWFheOqpp+BwODBv3jxkZmYiJCQEgwYNwosvvug+5/HHH8dbb72Ff//73+5Py3NyclpVRlwVg40bN2Ls2LEIDQ3FxIkTceTIEVm8f/zjH5GQkICIiAjccccdeOSRRzBq1Kh2n19FRQVuvvlmxMfHIyQkBAMGDMCaNWsAeKoz69atw8SJE2E2mzFs2DB88803smvs378fs2bNQnh4OBITE3HLLbegtLTU/XOn04lnn30W/fv3h8lkQt++ffHUU08BEDsfA8Do0aOh0+lw6aWXus954oknkJqaCpPJhFGjRmHDhg3ua7pie/fddzF58mSEhITgwgsvxNGjR7Fjxw6MHTsW4eHhmDVrFs6dk099feONN5CdnQ2z2YzBgwfjlVdecf+svXjOd54rnvXr12PKlCkwm814++2323zN161bh+nTp8Nsln9wotPpkJSUJPsKCRGn8E6dOlWWSG3ZsgUDBw7E7NmzZY/n5OQgPT3d/Ty8NWfOHKxevdr9fX19PdatW4c5c+Z06XqdVVVVhTfffBMvvPACLrvsMowZMwZr1qzB999/36oS15LJZJK9ZtHR0a2OiYiIkB0TFhbW4TUrKytxxx13ID4+HhaLBZdddhn27t0LAEhISMDs2bNlr5PL6tWrcfXVVyMmJgYAEB0djUmTJmHdunWdfSl8Q+hlqqqqBABCVVWV2qEQEZEPNTQ2CWOe/EJIf/gTod/iT4X8slrPD1eMEISlFkF4Il4QGqo7vtD788Rjl1oEIe8798O/WrVVSH/4EyH94U+E/+0v9NOz6J1KS0sFnU4nLF++vFPHAxASEhKE1atXC7m5ucKpU6cEu90uLFmyRNixY4dw4sQJ4Z///KcQGhoqrF+/XhAEQaiurhauv/56YebMmUJhYaFQWFgo2Gw24eTJkwIAYffu3YIgCMKmTZsEAML48eOFnJwc4cCBA8LkyZOFiRMnuu//z3/+UzCbzcLq1auFI0eOCMuWLRMsFoswcuTIdmO+9957hVGjRgk7duwQTp48KXz55ZfCf/7zH0EQBHcMqampwvvvvy8cPHhQuOOOO4SIiAihtLRUEARBqKioEOLj44XFixcLhw4dEnbt2iVMnz5dmDp1qvseDz30kBAdHS2sXbtWOH78uLB582Zh1apVgiAIwvbt2wUAwldffSUUFhYKZWVlgiAIwgsvvCBYLBbhnXfeEQ4fPiw89NBDgtFoFI4ePSqLbfDgwcKGDRuEgwcPChdddJEwZswY4dJLLxW2bNki7Nq1S+jfv79w1113yV6j5ORk4YMPPhBOnDghfPDBB0JMTIywdu3aDuM533mueDIyMtzHFBQUtPmajxgxQnjmmWdkj61Zs0aIjIxs99/pb3/7mxAWFiY0NjYKgiAIixYtEu69915h3bp1wiWXXOI+bvLkycJtt93m/n7OnDnCL37xi1bXc/0+VVRUyL4/cuSIYDKZhFOnTgmCIAj/+Mc/hJEjRwofffSRcL635zNnzhTCwsLa/RoyZEi7527cuFEWj0vfvn2FF154od3z5syZI0RGRgrx8fHCwIEDhbvuusv9u+mSnp4uJCYmCjExMcKoUaOEZ5991v06tmfatGnC7NmzhR07dghHjx4V/u///k+IjY11/z58+umngk6nE/Ly8tzn5ObmCjqdTvjiiy9k13r44YeFKVOmdHi/tnQnN2Adm4iIeoT/7i1EaY0dADBzaBLSYkLFH9SVAxV54jhlFGAK7/hC6ZOAfe+J44LdQPpEAMAdF/fDd8fLAABrvsvDFUOTfPwM/Oj1KUBNifL3DU8AfvvNeQ87fvw4BEHAoEGDZI/HxcW510fce++9+NOf/uT+2a9+9SvMnTtXdvyyZcvc48zMTGzduhXvvvsurr/+eoSHhyMkJAQ2mw1JSef/t3vqqacwZYq4lu6RRx7Bz372M/e6mJdeegnz5s1z33/JkiX44osvUFNT0+718vPzMXr0aIwdOxaAuJ6kpfnz57unob366qvYsGED3nzzTTz00EN4+eWXMXr0aDz99NPu41evXo20tDQcPXoUycnJePHFF/Hyyy+7qxpZWVm4+OKLAQDx8fEAgNjYWNnzf+655/Dwww/jxhtvBAD86U9/wqZNm7BixQqsXLnSfdyDDz7o3rfzgQcewE033YSNGzdi0qRJAIB58+Zh7dq17uOXLl2K559/3j1lLDMzEwcPHsTrr7+OOXPmtBvP+c5z+d3vfnfe6WinTp1CSkpKq8erqqoQHu7570B4eDiKisSNu6dOnYra2lrs2LEDEyZMQE5ODhYtWoSLL74Yc+bMQUNDAwRBwPbt23HHHXfIrvvJJ5/Irgug3SYXCQkJmDVrFtauXYslS5Zg9erVuP322zt8Pi5vvPEG6uvr2/250Whs92dFRUUIDg5GVFSU7PHExET3a9CWmTNn4tprr0VmZiZyc3Px+9//HrNmzcLWrVvd68/uv/9+XHDBBYiJicH333+PxYsXo7CwEC+88EKb19yyZQu2b9+OkpISmEwmAOLv48cff4z3338fv/nNbzBjxgykpKRgzZo1ePzxxwGI69zS0tJw+eWXy66XkpKCU6dOtfsc/IGJFBERBTxBELB6y0n397dfnOH5YeFezzhl9PkvJj2mYI97OGVgPPrFheFEaS22nijDoUIrspMDZF+pmhKgukDtKLy2fft2OJ1O3HzzzbDZbLKfuRISqZUrV2L16tXIz89HfX097HZ7h9PtOjJixAj3ODk5GQBQUlKCvn374siRI7jnnntkx48bNw5ff/11u9e7++67cd1112HXrl244oorcPXVV2PixImyYyZMmOAeBwUFYezYsTh0SNxUeu/evdi0aVOrN+oAkJubi8rKSthstlZvLjtitVpRUFDgToZcJk2a5J5e5SJ9PRITEwEAw4cPlz1WUiIm67W1tcjNzcW8efNw5513uo9pampCZGRku/F4c15b//4t1dfXt5rWB4jTz3bt2uX+Xq/3rHTp378/UlNTkZOTg6FDh2L37t2YMmUKEhIS0LdvX2zduhWCIMBms2Hq1Kmy606dOhWvvvqq7LEffvjBvY6npdtvvx0PPPAAfv3rX2Pr1q147733sHnz5vM+rz59+pz3GF9zJdqA+O8+YsQIZGVlIScnx/07t3DhQvcxI0aMQHBwMH77299i+fLl7kRJau/evaipqUFsbKzs8fr6euTm5gIQ1zDOmTMHa9euxdKlSyEIAt566y3MnTtX9u8GACEhIT5pSuMNJlJERBTwtp8sx8FCKwBgRGokLugrmbtfsNszTh51/oslDAEMwYDDLjtXr9fhtkkZWPJvcTHzmu9O4tlfjvRF+P4XnqDp+/bv3x86na7VOqR+/foBgHv9ilTLtRfr1q3Dgw8+iOeffx4TJkxAREQE/vznP+OHH37oUujST/VdXdScTmeXrgUAs2bNwqlTp/DZZ5/hyy+/xOWXX457770Xzz33XKfOr6mpwezZs2VVOZfk5GScOHGiy7F1RluvR8vHXK+PqzK3atUqjB8/XnYdV/WiLd6cd761N4BY0ayoqGj1uF6vR//+/ds979JLL8WmTZswYsQIDBgwAAkJ4u/xlClTsGnTJgiCgP79+yMtLa1VTC2ve+bMmXbvM2vWLPzmN7/BvHnzMHv27FYJRUfndZRwpaent9t0ISkpCXa7HZWVlbKqVHFxcacqtS79+vVDXFwcjh8/3m7yPn78eDQ1NSEvL69VtRkQ/72Tk5Nla89cpLHdfvvtWL58Ob7++ms4nU6cPn26VTUaAMrLy92VTqUwkSIiooC35rs89/j2SZny9sGFezzjzlSkgoKBxKFiElV2HLBVA6YIAMB1F6Tiz/87guqGJny8pwAPzxyM2PDWn7RqTiem16kpNjYW06dPx8svv4z77ruvU2+SW/ruu+8wceJEWaXI9am2S3BwsE/2Exo0aBB27NiBW2+91f3Yjh07zntefHw85syZgzlz5mDy5MlYtGiRLJHatm0bLrnkEgBiFWbnzp2YP38+AOCCCy7ABx98gIyMjDY7DA4YMAAhISHYuHFjqylngPjcAflUM4vFgpSUFHz33XfuaYyA+FqOGzfuvM+nPYmJiUhJScGJEydw8803t3lMW/F05jxvjB49GgcPHvT6vKlTp+L+++/HkCFDZE0wLrnkEqxatQqCILSqRnVFUFAQbr31Vjz77LP4/PPPO31ed6b2jRkzBkajERs3bnRPIz1y5Ajy8/NlFdHzOXPmDMrKytzV2rbs2bMHer3enYi2dMEFF6CoqAhBQUFtTnV1ycrKwpQpU7B69WoIgoBp06YhPT291XH79+/H6NGd+G+8DzGRIiKigHamog5fHBTn9idEmHDl8BZ/2F1VJWMYEDegcxdNHtV8ngAU/gRkiFOfwkxBuPHCNKzafBL2Jif+9UM+7ru8k9ekDr3yyiuYNGkSxo4di8cffxwjRoyAXq/Hjh07cPjwYYwZM6bD8wcMGIC///3v+N///ofMzEz84x//wI4dO2Rd1TIyMvC///0PR44cQWxsbIfTzDpy33334c4778TYsWMxceJErF+/Hj/99JO7gtaWJUuWYMyYMRg6dChsNhs++eQTZGdny45ZuXIlBgwYgOzsbPzlL39BRUWFe93Mvffei1WrVuGmm27CQw89hJiYGBw/fhzr1q3DG2+8AbPZjIcffhgPPfQQgoODMWnSJJw7dw4HDhzAvHnzkJCQgJCQEGzYsAGpqakwm82IjIzEokWLsHTpUmRlZWHUqFFYs2YN9uzZ024nvM5atmwZ7r//fkRGRmLmzJmw2Wz48ccfUVFRgYULF7Ybz/nO88aMGTPw1ltveR27a53U6tWrsWrVKvfjU6ZMcSepLad2dtWTTz6JRYsWdboaBXRval9kZCTmzZuHhQsXIiYmBhaLBffddx8mTJiAiy66yH3c4MGDsXz5clxzzTWoqanBsmXLcN111yEpKQm5ubl46KGH0L9/f/e6ua1bt+KHH37A1KlTERERga1bt2LBggX49a9/3WZ3PwCYNm0aJkyYgKuvvhrPPvssBg4ciIKCAnz66ae45pprZNM3pdM9pWvxpDZv3ownn3yyy69Nl3jdniLAsWsfEVHPsuLLo+5uei9+dVT+w9oyTwe+N2d0/qI/rvWc991Lsh/ll9UKGY+I95v8p68Fp9Ppg2dBgiAIBQUFwvz584XMzEzBaDQK4eHhwrhx44Q///nPQm2tpwsjAOGjjz6SndvQ0CDcdtttQmRkpBAVFSXcfffdwiOPPCLrpFdSUiJMnz5dCA8PFwAImzZtardrn7Sr2e7duwUAwsmTJ92PPfHEE0JcXJwQHh4u3H777cL9998vXHTRRe0+tyeffFLIzs4WQkJChJiYGOEXv/iFcOLECUEQPJ3o/vWvfwnjxo0TgoODhSFDhghff/217BpHjx4VrrnmGiEqKkoICQkRBg8eLPzud79z/w46HA7hj3/8o5Ceni4YjUahb9++wtNPP+0+f9WqVUJaWpqg1+vd3c0cDofw+OOPC3369BGMRqMwcuRI4fPPP3ef0/L1ae81aqsb3ttvvy2MGjVKCA4OFqKjo4VLLrlE+PDDDzuM53zntRVPe8rKygSz2SwcPny4wzjbkp6eLgAQCgvlHTozMjIEAK06BXrbta9l1zyXznTt6676+nrhnnvuEaKjo4XQ0FDhmmuuafU8AQhr1qwRBEEQ6urqhCuuuEKIj48XjEajkJ6eLtx5551CUVGR+/idO3cK48ePFyIjIwWz2SxkZ2cLTz/9tNDQ0NBhLFarVbjvvvuElJQUwWg0CmlpacLNN98s5Ofny46rq6sTIiMjhZiYmDav+f333wtRUVFCXV2d169Hd3IDnSAIvWozDKvVisjISFRVVcFiCZBFwkRE1CZBEHDpczk4VVYHnQ747uHLkBIlWU9zfCPwz+bOXuPvBmY907kLF+4FXhenWGH4/wOue0P241ve/AGbj4n797x/1wSMzYjp7lOhADd9+nQkJSXhH//4h9fn5uXlITMzE7t37+5ycwxq26JFi2C1WvH666+rHQr50Q033ICRI0fi97//vdfndic34Ia8REQUsHblV+JUmdilaUK/WHkSBbRYHzWq8xeOzxYbTgCyzn0u14z2TK35cPfZzl+XeoS6ujq88MILOHDgAA4fPoylS5fiq6++8vtmquS9P/zhD0hPT+9WoxDSNrvdjuHDh2PBggWK35uJFBERBawPd3k6Yl17QWrrA6RJUGcaTbgEBQOJw8Rx2TGgwSr78YyhSQgNFruIfbK3AA2N3W9gQIFDp9Phs88+wyWXXIIxY8bgv//9Lz744ANMmzZN7dCohaioKPz+979v1Sqbeo7g4GA8+uijbXb39Dc2myAiooBka3Lgk58KAQAhRgNmDmujda8rkTKGAbHttztuU8oooKB5r5min4CMi90/CjMFYebQJHy4+yysDU3YdLgEs1o2uaAeKyQkBF999ZXPrpeRkYFettKCqEdgek5ERAFp0+ESVNU3AgBmDE1EuKnFZ4O1ZUBVvjhOHgno29+/pk2yjXl3t/qxtAL2wS5O7yMi6m2YSBERUUCSJi9tTusrlCQ/3qyPcpFu3tvGOqkJWbFItIh7SOUcKUFZjc37exARUcBiIkVERAGnss6OnCMlAMS9oyb1j2t9UFfXR7kkZAOG5s12pU0rmhn0Olzd3HSiySng032F3t+DiIgCFhMpIiIKOF8dKkGjQ1xTctXIFBj0utYHFf3kGUurS51lMAJJroYTxwFbTatDrh7l6d73+b4i7+9BREQBi4kUEREFnP8d8CQtbTaZAIDSY+L/6o1ATL+u3Sg+2zMuO97qx4OTIpAeGwoA2J5XjvJae9fuQ0REAYeJFBERBZQ6exO+PXoOABAfYcIFfaNbH+R0AGW54jg2CzB0sUlt3ADP2JWYSeh0OswcKiZyDqeArw4Vd+0+REQUcJhIERFRQPnmyDnYmsTNNacPSYS+rWl9lfmAo7n5gzQZ8lbcQM+4rHUiBQBXDPVUxL44wOl9RES9BRMpIiIKKBuk0/qGnmdaHwDEdieRklakjrZ5yOi0KCREiE0pvj1WihpbU9fvR0REAYOJFBERBQx7kxNfHxK79UWYg3BRv9i2D5RWj6RVJW9FZwD65mmBpa3XSAGAXq/DFUMT3fF9c+Rc1+9HREQBg4kUEREFjO9zS1HdXPGZlp2I4KB2/oxJq0fdmdpnMALRmeK47BjgdLZ52Myhye7xBk7vIyLqFZhIERFRwPjfAU8zhxnNVaA2yab29e/eTV0VraYGoOp0m4eM7xeDyBAjAGDT4RLYmhzduycREWkeEykiIgoITqeALw+KiZTZqMclA+PbP9iVSIUlACFR3btxnCQRa6fhhNGgx+XZCQCAGlsTvs8t6949iYhI85hIERFRQDhQYEVpjdiJ7+L+cQgNbqeleX0lUCuuo+rW+igX6TXaaIHucsUQT4WM66SIiHo+JlJERBQQNh0pcY8vHZTQ/oHSjXO7sz7KfY3OJVKT+schqLkVuzRWIiLqmZhIERFRQMiRJVIdTevzUaMJF+kaq3ZaoANAhNmIMeni5sCnyupwsrS2+/cmIiLNYiJFRESaV1lnx57TlQCA/gnhSI0Obf/gUh+1PncJjQFC48RxWdst0F2klbIcVqWIiHo0JlJERKR53x4rhVMQx5d21GQCkFeNutuxz8VV2aouBBqs7R4mrZTlcJ0UEVGPxkSKiIg0L6ez66MAT9XIYAKi+vomAOkUwQ6qUoOTIpBkMQMAtp0oQ0Mj26ATEfVUTKSIiEjTnE4B3x4VqzuhwQZcmBnd/sGOJqAsVxzHZgF6g2+CiJUkUh00nNDpdJjSXDGzNTmx9QTboBMR9VRMpIiISNPEtud2AMDErDiYgjpIjipPAc5GceyLRhMuss597TecAICpgz3T+9gGnYio52IiRUREmtbpbn2A7xtNuK8lndrXfkUKkLdBZ8MJIqKei4kUERFp2jdHPVWd8yZS0iQn1ocVqah0QG8Uxx1M7QPkbdDzyupwqoxt0ImIeiImUkREpFm1tiZ32/N+cWEdtz0HgIpTnnFMpu8CMQQB0eniuDIfEIQOD79E0lnwu+NcJ0VE1BMxkSIiIs3afrIcTc19zyf2jz3/CZX5nnFUum+DcXUAtNcA9RUdHjoxyxPrd7mlvo2DiIg0gYkUERFp1veSJGRSVtz5T3AlUkFmIPw8bdK9JW2lXnmq/eMADO8TiQhTEABga24ZnM6OK1hERBR4mEgREZFmuabF6XTARf3OU5ESBE8iFZkmnuRLskQqv/3jAAQZ9BjfHG95rR2Hi6p9GwsREamOiRQREWlSea0dBwutAIAhyRZEhwV3fEJdOdDY3NjBVxvxSkmnCp4nkQLk0/u+5/Q+IqIeh4kUERFp0tZcT5OGSf07M61PMt3OL4lU5ytSgDzm73PZcIKIqKdhIkVERJokbdIgre60S9ZoQv1EamBiOOLCTQCAH06UodHh9H1MRESkGiZSRESkSa6KlNGgw7jMmPOf4O9EKiwBMJha36sdOp3OnQDW2h346Uyl72MiIiLVMJEiIiLNKaisx8lScb3T6LRohAYHnf8kfydSej0Qmeq513n2kgKASZKW7dxPioioZ2EiRUREmvPdccm0vs7sHwX4P5GSXrcTe0kBwERJy3bpcyIiosDHRIqIiDRn6wlP9WZiZ/aPAjyJlMEkTsPzBy/2kgKAtJhQpMWEAAB251eiodHhn7iIiEhxTKSIiEhztp8sBwCYgvQYmRZ5/hOke0hFpYnT8PzBy4YTAHBRplhRszuc2HO60g9BERGRGphIERGRppytrMeZinoAwAV9o2EKMpz/JH/vIeXi5V5SANwb8wKeBJGIiAIfEykiItKU7Sc90/o61a0PAKoUWB/V8tqVpzt1ynjJc2AiRUTUczCRIiIiTZEmG+M7m0gp0Wii5bU7WZFKjQ5BcqQZALDzVAX3kyIi6iGYSBERkab80JxIGQ06jO4b3bmTZIlUevvHdVd4ImAIbn3PDuh0nn2w6hsd2He2yl/RERGRgphIERGRZpyrtuHEOXGt04jUKIQEd2J9FKBcRUqvByLTPPfsxF5SADA+k+ukiIh6GiZSRESkGdIko9ProwDlEinp9e3VndpLCpA/FyZSREQ9AxMpIiLSjC41mgCU2UPKpQvrpLLiwxAbJk4J3JFXDoezc5UsIiLSLiZSRESkGa71UXodMDa9k+ujpHtIRab6bw8pl6g0z7gL66SqG5pwuMjqj8iIiEhBTKSIiEgTKuvsOFJcDQAYmhKJCLOxcyfWVwD2GnHs72l9QJf2kgLYBp2IqKdhIkVERJqwI6/C3bvBu2l9pzxjRRIp76f2AcA4ScOJH04wkSIiCnRMpIiISBN+POVJLi7M8CaRkmyMK5125y9dTKQGJ0UgwhwEAPjxVAWETnb8IyIibWIiRUREmrAzz9MBb0xn10cBQNUZzzhSgUQqPBHQiwkRrGc6PlZCr9fhguZ9sUprbMgvr/NHdEREpBAmUkREpDpbkwM/NW9UmxEbivgIU+dPtp71jC19fBxZG/QGICK5+d4FXp0qbaDxY17nWqcTEZE2MZEiIiLV7T9rhb3JCQC4wJtqFCBPpCIVSKQAT8JWVwY01nf6NGml7cdTTKSIiAIZEykiIlLdTsn6qLHpXqyPAoAqhStSgDxh86IqNapvFAx6HQBgFxMpIqKAxkSKiIhUJ53mNjajixWpsHggyIspgd0hTdiqOr9OKjQ4CEOSLQCAoyXVqKpv9HVkRESkECZSRESkKkEQsCtfTKQs5iD0jw/v/MmOJqC6UBwrVY0CxI1/XaRTCzvBNb1PEOB+3kREFHiYSBERkapOldWhtMYOQFwfpW+e+tYpNUWAIK6tkiU3/iarSHUtkQI4vY+IKJAxkSIiIlXtlCQTY71tNKHG+iigxRqpzk/tA+RTF9m5j4gocDGRIiIiVUm713nfsU+6h5SCiZRFUv3ysiKVHBmCPlEhAIA9pyvR6HD6MjIiIlIIEykiIlKVq2OfQa/DqLQo705WqyIVFgcYmhtbeLlGCvAkjPWNDhwurPZlZEREpBAmUkREpJqq+kYcLa4BAAxNsSA0OMi7C8j2kFJwjZROB1hSxLGXFSmgxca8ktbvREQUOJhIERGRavacrnSPL+jr5bQ+QN56XMmKFOBJ3GxVgM27qpKs4UR+pQ+DIiIipTCRIiIi1ezO78b6KEBSkdIBEUm+CaqzXBUpwOuq1OCkCJiN4p/gPafZcIKIKBAxkSIiItXsllRjRnu7PgrwJDARSYDB6JOYOs3S9c59QQY9hveJBACcLq9HWY3Nl5EREZECmEgREZEqnE7BPbUvLtyE1OgQ7y7QZANqS8Sx0tP6AHmXwC6sk5I21pBOcSQiosDARIqIiFRxsqwWVfWNAIDRfaOg03mxES8AWAs8YyVbn7tIW6B3oXPfqDTPVEYmUkREgYeJFBERqUI2ra9vlPcXkCYvFgU79rl0tyIlec5MpIiIAg8TKSIiUoW00cTotK507JO2PlejItX1NVIAkBJpRnyEuBfVntOVcDoFX0VGREQKYCJFRESqcFWk9DpgRGqk9xewqtj6HABCogFjqDjuQkVKp/NsQFzd0IQTpbU+DI6IiPyNiRQRESmuzt6Ew0VWAMCgJAvCTF5uxAu0qEipMLVPp/MkcNazgOB9RUnacGIvp/cREQUUJlJERKS4n85UwTWTrUvro4AWa6RUqEgBnimFjXVAvff7QbFzHxFR4GIiRUREiuv2/lGApyKlDwLCE7odU5d0s3PfiNRIuJoVMpEiIgosTKSIiEhxskYTfbvQaALwrJGKSAH0Bh9E1QXd7NwXYTaif3w4AOBQoRUNjQ5fRUZERH7GRIqIiBQlCAJ2N1dfLOYg9IsL8/4idslUOjU69rl0s3Mf4Jne1+QUcKCgygdBERGREphIERGRogqqGnCu2gYAGJkWBb3ey414AflmvJYUH0XWBdIkThqTF6T7SUmnPBIRkbYxkSIiIkX9JFkLNKqr66OqNZJIRUjubS3s0iXYcIKIKDAxkSIiIkXtPeOZvjYiNaprF5FVpNSc2pfsGVd3rSI1KDECIUZxjRcTKSKiwMFEioiIFPXTmUr3eGRXNuIF5IlURHL7x/mbOQoIChHHXaxIBRn0GN5HfB3OVNSjtMbmo+CIiMifVE+kVq5ciYyMDJjNZowfPx7bt2/v8PgVK1Zg0KBBCAkJQVpaGhYsWICGhgaFoiUiou5wOgXsa65IJVnMSLCYu3ahaknSoubUPp3OU5Wq7loiBcjXSe3hOikiooCgaiK1fv16LFy4EEuXLsWuXbswcuRIzJgxAyUlJW0e/69//QuPPPIIli5dikOHDuHNN9/E+vXr8fvf/17hyImIqCtOlNai2tYEQNxDqcu0UpECPOukbFbAVtOlS4yUTHHcK6nYERGRdqmaSL3wwgu48847MXfuXAwZMgSvvfYaQkNDsXr16jaP//777zFp0iT86le/QkZGBq644grcdNNN561iERGRNsim9XW10QQgqf7ogIik7oTUfbJ1Ul1sOCGtSHGdFBFRQFAtkbLb7di5cyemTZvmCUavx7Rp07B169Y2z5k4cSJ27tzpTpxOnDiBzz77DFdeeWW797HZbLBarbIvIiJSx0+yRhM+qEiFJwAGYzej6iZpRayLLdBTIs2IjzABEBMpp1PwRWRERORHqiVSpaWlcDgcSExMlD2emJiIoqKiNs/51a9+hSeeeAIXX3wxjEYjsrKycOmll3Y4tW/58uWIjIx0f6Wlpfn0eRARUedJp62N6BPVtYs4moCaYnGs9rQ+QL5Gq4sVKZ1O526DXt3QhBOltT4IjIiI/En1ZhPeyMnJwdNPP41XXnkFu3btwocffohPP/0UTz75ZLvnLF68GFVVVe6v06dPKxgxERG5NDqcOFggzgrIiA1FZGgXK0m1JYDgFMdqNppw8UFFCuB+UkREgSZIrRvHxcXBYDCguLhY9nhxcTGSktqe7/7YY4/hlltuwR133AEAGD58OGpra/Gb3/wGf/jDH6DXt84LTSYTTCaT758AERF55UhRNWxNYgLU5f2jAHmbcS0kUj6oSAHAaFkiVYFfjkntRlBERORvqlWkgoODMWbMGGzcuNH9mNPpxMaNGzFhwoQ2z6mrq2uVLBkM4iaGgsD55EREWua79VFnPWMtTO3zUUVqeGokdDpxzIoUEZH2qVaRAoCFCxdizpw5GDt2LMaNG4cVK1agtrYWc+fOBQDceuut6NOnD5YvXw4AmD17Nl544QWMHj0a48ePx/Hjx/HYY49h9uzZ7oSKiIi0yfcd+6CNilREEgAdAKFbFakIsxEDEsJxtLgGhwur0dDogNnIv21ERFqlaiJ1ww034Ny5c1iyZAmKioowatQobNiwwd2AIj8/X1aBevTRR6HT6fDoo4/i7NmziI+Px+zZs/HUU0+p9RSIiKiT9jZXpPQ6YGiKpesX0tIeUoDYNTAsXly7Ze16IgWI66SOFtegySlg/9kqjM2I8VGQRETka6omUgAwf/58zJ8/v82f5eTkyL4PCgrC0qVLsXTpUgUiIyIiX6m3O3C0uBoAMDAxAqHB3fjzI6tI9elmZD5iSRYTqZpiwOkA9F2rJI1IjcK7P54BAOxjIkVEpGkB1bWPiIgC08HCKjia90bq1vooQF6RsmigIgUAEc1TDAUHUFPS5ctIX5t9Z6s6OJKIiNTGRIqIiPxu72lpo4mo7l3MlUgFRwCmiO5dy1ekCV111xtODEqKgNEgdpzYd4aJFBGRljGRIiIiv5M1muhOIiVIGjpopRoFeCpSQLfWSZmCDBiUJCaHuedqUGtr6m5kRETkJ0ykiIjI71ytz4MNenei0CUNVUBjnTjWQsc+F1lFqnsNJ4b3Eaf3OQXgYKG1W9ciIiL/YSJFRER+VVXfiBOltQCA7BQLgoO68adH1rFPQ4mUj/aSAoDhfaLcY07vIyLSLiZSRETkV/slTRNGdrfRRLUGG00A8uqYjypSABtOEBFpGRMpIiLyq72S9VHdbzQhSVK0sIeUiw8rUgOTwhFsEP88S9eWERGRtjCRIiIiv/rptC8rUhrcQwoAzJGAMVQcd7MiZQoyYHCyuI7sRGktathwgohIk5hIERGRX7mqKmHBBvSLD+/exbS4hxQA6HSeqlQ3uva5DGue3icIwAFO7yMi0iQmUkRE5Dfnqm0oqGoAICYHBr2uexfUarMJwLNOyl4N2Kq7dakRXCdFRKR5TKSIiMhvZPtHpUV1/4KuZhP6ICAsvvvX8yXZOqnuVaWGMZEiItI8JlJEROQ3eyXtu0d0d30U4ElQwpMAvcb+hMn2kupmw4nECHebeCZSRETapLG/QkRE1JPIKlLd7djXZAPqSsWxltZHuUinGnazIhUcpEd288bFJ87VorqhsVvXIyIi32MiRUREfiEIgnsPqahQI1KjQ7p3wZpiz1hLrc9dfFiRAoDhkgregQJrt69HRES+xUSKiIj8oqTahtIaOwBgWEokdLpuNpqoLvKMtZhI+bAiBQAj+kS5x/vOcHofEZHWMJEiIiK/kL75lzZP6DKttj53sUgSqW7uJQXIX7OfuE6KiEhzmEgREZFf7C+QJlKW7l9Q6xWp8ERA1/xn1dr9qX0DEsNham44sZ+JFBGR5jCRIiIiv5C++R+W4oOKlHTdkRYTKUMQEJYgjn1QkTIa9MhOFhPQk6W1sLLhBBGRpjCRIiIiv9h/VmyQEGEOQnpsaPcvqPWKFOCZclhTDDiaun05act4VqWIiLSFiRQREfncuWobiqwNAIChKZbuN5oA5FWeiKTuX88fXA0nBCdQW9Lty8k25mXDCSIiTWEiRUREPiddHzXcF40mAE8nvOBwwOyDNVf+IG2C4YN1UtKKFDfmJSLSFiZSRETkc/t93bEP8Ezt02o1CpBPOfRBItU/Phxmo/inmokUEZG2MJEiIiKfk3fs80EiZasG7NXiWKvrowCft0APMugxpLnhxKmyOlTVseEEEZFWMJEiIiKfczWaCAs2IDM2rPsXDIRGE4DPK1IAMCI1yj2WJqhERKQuJlJERORT5bV2nK2sBwAMSbFAr+8ljSYAn1ekgBYNJzi9j4hIM5hIERGRTx3w9bQ+wNNoApAnK1rjl4oUO/cREWkREykiIvKpfb7eiBcInIqU2SJ2FQR8VpHKig9HiNEAAPjpbKVPrklERN3HRIqIiHzqQPP6KAAYnuqPRErDFSnAU5WyFgKC0O3LGfQ6DEkRG06cLq9nwwkiIo1gIkVERD7lqkiZjXr0i/NBowkgcCpSgGcvqcZawGbt+NhOGpri2TfrQCGn9xERaQETKSIi8pmqukbkl9cBAIYkWxBk8NGfGVnXPo0nUtKKmdVHDSckUyQPFvgmOSMiou5hIkVERD7jl0YTgCchCY0Fgky+u64/WCQNJ6p903BiiKQitZ+d+4iINIGJFBER+YxsI15fNZoQBM/UPi3vIeXih4rUwMQIGA1iG/kDrEgREWkCEykiIvKZfZJGEz6rSNWVAc7mBguBkEj5oSIVHKTHwMQIAEDuuRrU2x0+uS4REXUdEykiIvKZA83TzoKD9BiQGO6biwZSownALxUpwFPhcwrAoSJWpYiI1MZEioiIfKK6oREnSmsBANlJETD6pdFEoFWkfJdIDe0j6dzHdVJERKpjIkVERD4h7SY31KeNJiTT4ywBkEiFJQC65j+vVt9M7QOAoZI1Z/vPsiJFRKQ2JlJEROQT+yWJlM8aTQCBV5EyBAHhieLYhxWp7OQI6MR+E9xLiohIA5hIERGRT0jbcg/3ZUVK2rAhEBIpwBNnTQngaPTJJUODg5AVL647O1JUDXuT0yfXJSKirmEiRUREPuFKpIwGHQYm+ajRBBB4FSkAsLgaTghATbHPLjuseT+pRoeAYyXVPrsuERF5j4kUERF1W529CbnnagCIex6Zggy+u7hrepzOAITF+e66/iRN+KSJYDdJ10kd4DopIiJVMZEiIqJuO1RohVMQxz5dHwV4WohHJAF6HyZo/iRt0+6vzn0FXCdFRKQmJlJERNRtB6SNJiRv9rvN0QjUnhPHgbCHlIvFP3tJDU2WdO4rYEWKiEhNTKSIiKjbpK3Ph/iyIlVTDKC51BUo66MAv1WkIkONSIsJASBWAR2uMiARESmOiRQREXXbwUIxkdLpgMFJEb67cCA2mgCACElFyoeJFOCpStXZHTjZvAEyEREpj4kUERF1S5PDicNFYge5jNgwhJmCfHdxaRISSFP7/FSRAuRTJ7lOiohIPUykiIioW06U1rr3NBqS7MP1UYB8fZF03ZHWmSMBY6g49uEaKaBF5z6ukyIiUg0TKSIi6hb5+igfJ1KBWpHS6Tzx+rD9OSDv3CfdBJmIiJTFRIqIiLrFtT4K8ENFSpZIBVBFCvCs6bJVAXbfrWVKiDAjPsIEQKxICQIbThARqYGJFBERdQsrUu3w06a8ADCs+XWuqm/EmYp6n16biIg6h4kUERF1mSAIONRckYoNC0ZCc6XEZ1wJSFCIuO4okPix4QTXSRERqY+JFBERdVlJtQ1ltXYAYjVKp9P59gauRg2WZHHdUSDx06a8ADv3ERFpARMpIiLqMtm0Pl+vj7LXiuuLgMDaQ8pFoYoUG04QEamDiRQREXWZrNGEz9dHBehmvC5+3JQ3NToEFrO4Xxen9hERqYOJFBERdZlfK1KB3GgC8GtFSqfTuatSJdU2lFQ3+PT6RER0fkykiIioy1wVKVOQHplxYb69eMBXpCSJlI/XSAEt10mxKkVEpDQmUkRE1CU1tibklYn7Iw1OikCQwcd/UqwFnrElABMpYwgQEi2OfVyRAlp07uM6KSIixTGRIiKiLjlSZIVrL1ifr48CAr8iBXjiri4CfLxxrrQiJV2rRkREymAiRUREXeLX9VEAUC2pSAV6IuWwAfUVPr10Zlw4zEbxz/hBTu0jIlIcEykiIuoSv3bsA1pUpAKw2QQgTwB9PL3PoNdhUJL4uueV1aHG1uTT6xMRUceYSBERUZe4qiA6Hdxv6H3KlXiYo8T1RoFIurbLDw0npJXAw5zeR0SkKCZSRETktSaHE4eLqgEAGbFhCDcF+fYGguBJPCwpHR+rZX5sgQ7IK4FcJ0VEpCwmUkRE5LWTpbWwNTkB+Gl9VH2FuK4ICNxpfYBfp/YB8tf+wFkmUkRESmIiRUREXvP/+ijpZryBXJHybyKVnRwBnU4csyJFRKQsJlJEROQ1/3fskyZSPaUiVdT+cV0UGhzk3gj5SHE1Gh1On9+DiIjaxkSKiIi8xo59nRSeAOia/9RKNxj2IVcia29y4sS5Wr/cg4iIWmMiRUREXhEEwV2Rig0LRkKEyfc3kXa4C+RmE3oDEJ4ojv1QkQJaNpyo8ss9iIioNSZSRETklZJqG8pq7QDEN/E61yIdX5JtxhvAFSnAM72vtgRw+H6vJ+nUSm7MS0SkHCZSRETkFemb9Wx/rI8C5BWpQG42AXgSKcEpJlM+xhboRETqYCJFREReka2P8lci5apI6QziOqNAJq2o+WFT3oQIM+LCxemVBwqsEATB5/cgIqLWmEgREZFX/N5oAvA0ZohIEtcZBTKLf1ugA8DQ5n+HyrpGFFY1+OUeREQkx0SKiIi8cqh5al9wkB79mltv+1STHag9J46l7cMDlZ/3kgJaTO/jOikiIkUwkSIiok6rtTXhZJnYYntwUgSCDH74M1Ij6W4XyB37XJRIpJK5ToqISGlMpIiIqNMOF1XDtQTHb+ujpPst9bhESoEW6KxIEREpgokUERF1mqLro4CeMbVPukbKT5vyZsSGIcQoriVjRYqISBlMpIiIqNOk1Q7/deyTbsbbxz/3UJI5Cggyi2M/VaQMeh0GJ0cAAPLL62BtaPTLfYiIyIOJFBERdZq02jFYkal9PaAipdN5WqBX+6ciBcgT28OF1X67DxERiZhIERFRpzQ5nDjcnEhlxIYi3BTknxv1tDVSgGdT4YYqwF7nl1sMTYl0jw8UVPnlHkRE5MFEioiIOiWvrBa2JicAP66PAnreGilAvilvDRtOEBH1BEykiIioUw4osT4K8Ex/C4kGjCH+u4+SpJU1q39aoA9KjIBeJ47ZcIKIyP+YSBERUaco0rHP6fQ0ZOgJjSZcpBUpP+0lFRJsQL/4cADAseIa2Jurh0RE5B9MpIiIqFPkHfsiOziyG+rKAIddHPeUaX2AIpvyAp5Kod3hRO65Gr/dh4iImEgREVEnCILgTqRiwoKRaDH550bVPaxjn4sCm/ICXCdFRKQkJlJERHRe56ptKKsVK0VDki3Q6XT+uZGsY18Pndrnp015AWCoNJHiOikiIr9iIkVEROd1QIn1UUDP7NgHKFaRypY0AWELdCIi/2IiRURE53VQsY59kvVDPakiFRwKmJvXlflxjVRcuMk97fJggRWCIPjtXkREvR0TKSIiOi9FOvYBLab29aCKFODZlLe6EPBjguNKdK0NTThbWe+3+xAR9XZMpIiI6LwONSdSwUF69IsL89+NeurUPsCzTqqpAWio9Ntt2HCCiEgZTKSIiKhDdfYmnCytBQAMTopAkMGPfzpc096CQsQNeXsSBTblBeSt6dlwgojIf5hIERFRhw4XVbtnovl1fRTgqUhZkgF/dQZUiwKb8gKsSBERKYWJFBERdUjWaMKf66Ns1YCt+V4RKR0fG4gU2pQ3PSYUYcEGAKxIERH5k+qJ1MqVK5GRkQGz2Yzx48dj+/btHR5fWVmJe++9F8nJyTCZTBg4cCA+++wzhaIlIup9pG/Gs/1ZkZJOd7MwkeoqvV7n/nc6U1GPqvpGv92LiKg3UzWRWr9+PRYuXIilS5di165dGDlyJGbMmIGSkpI2j7fb7Zg+fTry8vLw/vvv48iRI1i1ahX69OlBLXKJiDRGWpEanBThvxtV9+COfYA8kfLjGimA0/uIiJQQpObNX3jhBdx5552YO3cuAOC1117Dp59+itWrV+ORRx5pdfzq1atRXl6O77//HkajEQCQkZGhZMhERL2KwyngcJH4Rjw9NhQRZqP/bmbtoXtIuViU2ZQXkK9lO1hoxYSsWL/ej4ioN1KtImW327Fz505MmzbNE4xej2nTpmHr1q1tnvOf//wHEyZMwL333ovExEQMGzYMTz/9NBwOR7v3sdlssFqtsi8iIuqck6W1aGh0AlCi0cRZz7intT4HgLAEQNf8Z1daffMDVqSIiPxPtUSqtLQUDocDiYmJsscTExNRVNT2J3UnTpzA+++/D4fDgc8++wyPPfYYnn/+efzxj39s9z7Lly9HZGSk+ystLc2nz4OIqCeTbcTr70SquoevkTIEAeHNf/P8PLVvYGIEDHqx6yEbThAR+YfqzSa84XQ6kZCQgL/97W8YM2YMbrjhBvzhD3/Aa6+91u45ixcvRlVVlfvr9OnTCkZMRBTYFOvYB8g34+2JiRTgeV41xYDDf00gzEYDsuLFjZOPl1TD3uT0272IiHor1RKpuLg4GAwGFBcXyx4vLi5GUlJSm+ckJydj4MCBMBgM7seys7NRVFQEu93e5jkmkwkWi0X2RUREnSOrSCmVSOn04jS4nsidIAp+Xyc1NEXcmLfRIeBYSbVf70VE1BuplkgFBwdjzJgx2Lhxo/sxp9OJjRs3YsKECW2eM2nSJBw/fhxOp+eTtaNHjyI5ORnBwcF+j5mIqLdxVaSiQ41Ispj9ezPX1L7wRHEaXE8kbaJh9fM6qWSukyIi8idVp/YtXLgQq1atwltvvYVDhw7h7rvvRm1trbuL36233orFixe7j7/77rtRXl6OBx54AEePHsWnn36Kp59+Gvfee69aT4GIqMcqqW5AaY0NgFiN0ul0/ruZoxGoad76oqdO6wPkz03aXMMPpBXEA0ykiIh8TtWP/G644QacO3cOS5YsQVFREUaNGoUNGza4G1Dk5+dDr/fkemlpafjf//6HBQsWYMSIEejTpw8eeOABPPzww2o9BSKiHku2PsrvjSaKAAjiuCd27HNRsCKV3aIFOhER+Zbqcyfmz5+P+fPnt/mznJycVo9NmDAB27Zt83NURESk6Pqo6h6+h5SLrCLl30QqJiwYyZFmFFY14FCBFYIg+LeqSETUywRU1z4iIlKOvCIV6d+bSae5WXpyRUq5qX2Ap5JYbWvCmYp6v9+PiKg3YSJFRERtclWkgoP06NfcSttvpPsqRfTgNVLSaYt+rkgBLTbm5fQ+IiKfYiJFRESt1NmbcLK0FgAwKDECRoOf/1zIKlI9OJEKMgGhceJYiUSKnfuIiPyGiRQREbVyuKgaQnPvB783mgBarJHqwYkU4Hl+1YWA0+HXW7HhBBGR/zCRIiKiVg4p2WgCaDG1rwevkQI8zTQEh6flu5/0jQlFWLC4iT0rUkREvsVEioiIWpE1mlAkkWqe2meOAoJD/X8/NSnYuU+v17mrUmcr61FV3+jX+xER9SZMpIiIqBXpNLDBSRH+vZkgeKb29fRpfYDinfuk0/sOcXofEZHPMJEiIiIZh1PA4cJqAEB6bCgizEb/3rCuDHDYxXGvSKQk+2RJ14b5iaxzH6f3ERH5DBMpIiKSySurRX2j2ARBkUYT0ultPX19FKDaXlIAK1JERL7ERIqIiGTkG/GyY5/PSStSCrRAH5QUAb1OHLNzHxGR7zCRIiIimYOKd+zrJXtIuViU3ZTXbDSgX3w4AOBYcQ3sTU6/35OIqDdgIkVERDLKd+yTtj7vBYlUcJjYnRBQZGof4Kks2h1O5J6rUeSeREQ9HRMpIiKScVWkokONSLKY/X/DaklVxtIL1kgBnsqbtQDunY/9SJoQc50UEZFvMJEiIiK3kuoGnKu2ARDbZut0Ov/fVDq9Tbp+qCdzJVIOu9i10M+kLdDZuY+IyDeYSBERkduh5rbngEKNJgDP1D6DCQiJVuaealOxcx8bThAR+QYTKSIiclN8fRTgqUhZUgAlKmBaoHDnvvgIE+IjTADEqX2CAtMJiYh6OiZSRETkpnjHPnstYKsSx72hY5+LwhUpwFOVqqhrRJG1QZF7EhH1ZEykiIjI7WCBmNQEG/TIam6Z7Veyjn29pNEE0CKR8n9FCuA6KSIiX2MiRUREAIA6exNOlNYCAAYmhcNoUOBPhPWMZ9yrKlKSqX1VClWkUphIERH5EhMpIiICABwpqnZ34las0USVJJGKTFPmnlogS6TOtH+cD0n/TQ8VMZEiIuouJlJERASgxfooVRKpVGXuqQVmC2COFMdVpxW5ZWZcGMxG8c8+K1JERN3HRIqIiAC07NgXqcxNpUlEb0qkAE8FzloAOB1+v51Br8OgJDFBziurQ42tye/3JCLqyZhIERERALEttsvg5AhlbiqtSEX1oql9gCdxdDYCNSWK3FJaaTzM/aSIiLqFiRQREcHhFHC4SNyMt29MKCxmozI3diVSweGAOUqZe2qFdE2YUuukJA0nDjGRIiLqliBvT6itrcUzzzyDjRs3oqSkBE6nU/bzEydO+Cw4IiJSxqmyWtTZxelliq2PEgRPAhGZ2ns243WRTmWsOg2kXej3Ww6RVBoPMpEiIuoWrxOpO+64A9988w1uueUWJCcnQ9fb/vAREfVAim/ECwB1ZUBT88awvW19FNAikVKmIjUoyQKdTsxh2XCCiKh7vE6kPv/8c3z66aeYNGmSP+IhIiIVyBpNKNaxrxc3mgBaTO1TpnNfuCkIGbFhOFlai8NF1WhyOBGkxH5hREQ9kNf/9YyOjkZMTIw/YiEiIpWoUpHqra3PXVSoSAGeRNnW5EReWa1i9yUi6mm8TqSefPJJLFmyBHV1df6Ih4iIVOCqSEWFGpEcaVbmppXSilQv69gHABFJgM4gjhWqSAFAtmSd1AFO7yMi6jKvp/Y9//zzyM3NRWJiIjIyMmA0yjs77dq1y2fBERGR/52rtqGk2gZArFYotva1t1ek9AbA0geoyle2IiWpOB4stOIXo/oodm8iop7E60Tq6quv9kMYRESkFmkbbMXWRwEt1kj1wooUIO6dVZUP1FcAthrAFO73Ww5J9my2fKiw2u/3IyLqqbxOpJYuXeqPOIiISCWqrI8CJFUYHWBJUe6+WiKtxFnPAvGD/H7LRIsJ0aFGVNQ1snMfEVE3eJ1IuezcuROHDh0CAAwdOhSjR4/2WVBERKQcWcc+NRKpiGTAoNAGwFrTci8pBRIpnU6HISkWfHe8DKU1NpRUNyAhQqF1cUREPYjXiVRJSQluvPFG5OTkICoqCgBQWVmJqVOnYt26dYiPj/d1jERE5EeuilSwQY+seP9PLQMANDYAtSXiuDeuj3JRsXPfd8fLAIjT+5hIERF5z+uufffddx+qq6tx4MABlJeXo7y8HPv374fVasX999/vjxiJiMhP6u0OnDhXAwAYmBQOo1J7ClnPesa9OpGSrA2rVK5zn6zhBKf3ERF1idcVqQ0bNuCrr75Cdna2+7EhQ4Zg5cqVuOKKK3waHBER+deR4mo4BXGsbKOJXt6xz0WlilR2srxzHxERec/rjx6dTmerlucAYDQa4XQ6fRIUEREpQ1qNyFYtkeqlHfsAsf25i4KJVFZ8OIKbq48HC6oUuy8RUU/idSJ12WWX4YEHHkBBQYH7sbNnz2LBggW4/PLLfRocERH518FCz5toVqRUYLYA5uZ25Apuyms06DEwSVwPd7K0FvV2h2L3JiLqKbxOpF5++WVYrVZkZGQgKysLWVlZyMzMhNVqxUsvveSPGImIyE9kFSlFO/ble8ZRvbgiBQCRfcX/tRYATuUSmuwk8d/bKYhTPImIyDter5FKS0vDrl278NVXX+Hw4cMAgOzsbEybNs3nwRERkf84nQIOF4lvoNNiQmAxK9iCnBUpj8hUoHgf4GwEakoAS7Iitx2SYgF2iuODBVaMSotS5L5ERD1Fl/aR0ul0mD59OqZPn+7reIiISCGnyutQ1zylS9FpfYAnkQoOB8xRyt5ba1o2nFAqkZI1nOA6KSIib3UqkfrrX/+K3/zmNzCbzfjrX//a4bFsgU5EFBhkG/EmRyp3Y0HwJFKRqYBOp9y9tajlprxpFypyW+lUzkOFnNpHROStTiVSf/nLX3DzzTfDbDbjL3/5S7vH6XQ6JlJERAFC1mhCyfVRdWVAU4M47u3T+oDWiZRCLGYjUqNDcKaiHocKrXA6Bej1vTypJSLyQqcSqZMnT7Y5JiKiwCWrSCnaaEKSLDCRkrd/V7AFOiBO7ztTUY86uwOnyuuQGRem6P2JiAKZ1137nnjiCdTV1bV6vL6+Hk888YRPgiIiIv9zbcQaGWJESqRZuRuz0YScSpvyAvIE+hA35iUi8orXidSyZctQU1PT6vG6ujosW7bMJ0EREZF/ldbYUGy1ARCrEjol1ylxM165iCRA3zxBRMGpfYB8E2ZphZKIiM7P60RKEIQ2/+Du3bsXMTExPgmKiIj8S1p9UHRaH8BEqiW9AbCkiGMVpva5HGRFiojIK51ufx4dHQ2dTgedToeBAwfKkimHw4GamhrcddddfgmSiIh8S96xT+FEqlKyGS+n9oki08TXpb4CsNUApnBFbpsaHYIIcxCqG5pYkSIi8lKnE6kVK1ZAEATcfvvtWLZsGSIjPa1yg4ODkZGRgQkTJvglSCIi8q2DmqhI6TyVmN5OmlBazwLxgxS5rU6nw5BkC344WY4iawPKa+2ICQtW5N5ERIGu04nUnDlzAACZmZmYOHEijEaj34IiIiL/clUfgg16ZMUrU/1wcyVSEcmAgX9LALRuga5QIgWI66R+OFkOQJzyOal/nGL3JiIKZJ1OpFymTJniHjc0NMBut8t+brEo/MkmERF5paHRgdxzYtOgAYnhCA7yerls1zU2ALUl4pjT+jykr0Wlsg0npBXJgwVMpIiIOsvrv551dXWYP38+EhISEBYWhujoaNkXERFp25GiajgFcaz4+ijrWc+YiZSHyntJubDhBBFR53mdSC1atAhff/01Xn31VZhMJrzxxhtYtmwZUlJS8Pe//90fMRIRkQ9pY30UmEhJqbiX1IDEcATpxQZS3EuKiKjzvE6k/vvf/+KVV17Bddddh6CgIEyePBmPPvoonn76abz99tv+iJGIiHxI1Y590iQhqq+y99YyFRMpU5AB/RPEdXLHS2rQ0OhQ9P5ERIHK60SqvLwc/fr1AyCuhyovFxeoXnzxxfj22299Gx0REfmctCKVzYqUNpgiAHOUOFZ4U17Ak1A3OQUcL6lR/P5ERIHI60SqX79+OHnyJABg8ODBePfddwGIlaqoqCifBkdERL7ldAru6VtpMSGwmBXumidNEphIybnWSVkLAKeyVSFZwwlO7yMi6hSvE6m5c+di7969AIBHHnkEK1euhNlsxoIFC7Bo0SKfB0hERL5zqrwOdXbxTbri0/oAVqQ64no9nI1ATYmit85OlnfuIyKi8/O6/fmCBQvc42nTpuHw4cPYuXMn+vfvjxEjRvg0OCIi8i35+qjIDo70E1dFKjjcM5WNRC3XSVmSFbt1Njv3ERF5zetEqqX09HSkp6f7IhYiIvKzg4VV7rHiHfsEwVORikwFdDpl7691skQqH0i7ULFbx4QFIznSjMKqBhwqtEIQBOj470NE1KFOJVJ//etfO33B+++/v8vBEBGRfx0qrHaPs5MjlL15XRnQ1CCOOa2vNRU79wHiVM/CqgZUNzThTEU90mJCFY+BiCiQdCqR+stf/tKpi+l0OiZSREQa5praZzEHoU9UiLI3Z6OJjqm4KS8gTu/beFhcm3Ww0MpEiojoPDqVSLm69BERUeAqq7GhyCpWhIakWJSfuiVrNJHW/nG9ldoVqRR5w4kZQ5MUj4GIKJB43bXPxW6348iRI2hqavJlPERE5CfSaX3qNJpgItWhiCRA3/z5pop7SQFwt8gnIqL2eZ1I1dXVYd68eQgNDcXQoUORn58PALjvvvvwzDPP+DxAIiLyDVUbTQBsfX4+egNgSRHHKlSk+saEIizYAICd+4iIOsPrRGrx4sXYu3cvcnJyYDab3Y9PmzYN69ev92lwRETkO/LW52okUlwjdV6uSl19BWCrUfTWer0Og5t/L85U1KOqvlHR+xMRBRqvE6mPP/4YL7/8Mi6++GLZ/PqhQ4ciNzfXp8EREZHvuKoMRoMO/RPClQ/AXWXReSovJCdNMK1nFb89p/cREXWe14nUuXPnkJCQ0Orx2tpa7jlBRKRRDY0O5J6rBQAMSIhAcFCXl8h2XaU4FRwRyYDBqPz9A4E0kXK9XgqSTvlkIkVE1DGv/5KOHTsWn376qft7V/L0xhtvYMKECb6LjIiIfOZocTUcTgGASuuj7LVA7TlxHM1N3NsVJXltKvIUv312srxzHxERta9T7c+lnn76acyaNQsHDx5EU1MTXnzxRRw8eBDff/89vvnmG3/ESERE3aT6+ihpdSWKiVS7pElm5SnFbz8oMQJ6HeAU2HCCiOh8vK5IXXzxxdi7dy+ampowfPhwfPHFF0hISMDWrVsxZswYf8RIRETdJH1TrEpFqkKSFLAi1T5ZRUr5RCok2IB+8eL6uWPFNWh0OBWPgYgoUHhVkWpsbMRvf/tbPPbYY1i1apW/YiIiIh+TVqSyValISZICVqTaF5kK6PSA4FSlIgWIvx/HS2pgdziRe64Gg5NU+H0hIgoAXlWkjEYjPvjgA3/FQkREfuB0Cu7GAanRIYgMUaHRg3S9DytS7TMYAUtzwwkVKlKAfOon10kREbXP66l9V199NT7++GM/hEJERP6QX16HWrsDgErrowB5UsCKVMdciWZDJdBQ1eGh/iCd+slEioiofV43mxgwYACeeOIJfPfddxgzZgzCwsJkP7///vt9FhwREXWf6uujAM80Nb2Re0idT1Q6gM3iuOIUkDxC0dvL9pIqYiJFRNQerxOpN998E1FRUdi5cyd27twp+5lOp2MiRUSkMap37BMET0UqMhXQG5SPIZC07NyncCIVH2FCXLgJpTU2HCywQhAE7hNJRNQGrxIpQRCQk5ODhIQEhISE+CsmIiLyIWlFSpVGE/UVgL1aHHN91Pmp3LkPECuX3x49h4q6RhRZG5Acyb/5REQtebVGShAEDBgwAGfOnPFXPERE5GMHCsR1NpEhRqRGq/CGWNpoguujzk/lvaQANpwgIuoMrxIpvV6PAQMGoKyszF/xEBGRD5XW2FBstQEQ3xyrMkWrkntIeUVWkcpTJYTs5Aj3+BA35iUiapPXXfueeeYZLFq0CPv37/dHPERE5EMHJNWEoWo1mmDHPu+EJwIGkzhWaWqf9HflIBMpIqI2ed1s4tZbb0VdXR1GjhyJ4ODgVmulysvLfRYcERF1j2taH6CBjn0AEJ2hTgyBRK8HovoCZceAynyxWYfClcTMuHCYjXo0NDo5tY+IqB1eJ1IrVqzwQxhEROQPB2UVqUh1gmBFynvR6WIi1VQP1JQAEYmK3t6g12FQkgV7T1fiVHkdamxNCDd5/ZaBiKhH8/q/inPmzPFHHERE5AeuRMoUpEdWfNh5jvYTV0XKGAqExakTQ6CJatFwQuFECgCGJEdg7+lKCAJwpMiKMekxisdARKRlXfp4yeFw4OOPP8ahQ4cAAEOHDsVVV10Fg4F7gxARaUWtrQkny2oBAIOTIhBk8HpZbPc5neL0NEBMDrgfUedEt2iBnjZO8RBadu5jIkVEJOd1InX8+HFceeWVOHv2LAYNGgQAWL58OdLS0vDpp58iKyvL50ESEZH3DhVaIQjieIha0/pqigCHXRyzY1/nySpSeaqEMIQNJ4iIOuT1x5P3338/srKycPr0aezatQu7du1Cfn4+MjMzcf/99/sjRiIi6gJtdOzL84zZaKLzpK+VSp37BiVZ3AXEg4XVqsRARKRlXlekvvnmG2zbtg0xMZ4Sf2xsLJ555hlMmjTJp8EREVHXaaJjHxtNdI0GNuUNNwUhPSYUeWV1OFxoRZPDqc70UCIijfL6v4gmkwnV1a0/maqpqUFwcLBPgiIiou5zVaT0OiA7SQutz5lIdVpINGBqno6pUkUK8CTgtiYn8prX2xERkcjrROrnP/85fvOb3+CHH36AIAgQBAHbtm3DXXfdhauuusofMRIRkZfsTU4cK64BAPSLD0dIsErNgFiR6rrovuL/Vp0BHE2qhCBtOHGA+0kREcl4nUj99a9/RVZWFiZMmACz2Qyz2YxJkyahf//+ePHFF/0RIxEReel4SQ3sDicAFddHAS3WSDGR8oprnZTgAKxnVAkhW5JIHeI6KSIiGa8TqaioKPz73//G0aNH8f777+P999/HkSNH8NFHHyEysmtdoVauXImMjAyYzWaMHz8e27dv79R569atg06nw9VXX92l+xIR9VTS9VGqJlLlJ8T/DYsHTBHqxRGIojM9Y9frqDB27iMial+Xtynv378/+vfv3+0A1q9fj4ULF+K1117D+PHjsWLFCsyYMQNHjhxBQkJCu+fl5eXhwQcfxOTJk7sdAxFRTyPv2KdS63N7rdj+HABi+qkTQyCTvmblJwEVdhdJspgRHWpERV0jDkqScyIi6kJF6rrrrsOf/vSnVo8/++yz+H//7/95HcALL7yAO++8E3PnzsWQIUPw2muvITQ0FKtXr273HIfDgZtvvhnLli1Dv37840xE1NJBSSIlXeeiKNm0vsx2D6N2xKhfkdLpdO6qVGmNHSXWBlXiICLSIq8TqW+//RZXXnllq8dnzZqFb7/91qtr2e127Ny5E9OmTfMEpNdj2rRp2Lp1a7vnPfHEE0hISMC8efPOew+bzQar1Sr7IiLqyZxOwT0NKyXSjOgwlTqqSt/8syLlvZYVKZVIK5psOEFE5OF1ItVem3Oj0eh1klJaWgqHw4HExETZ44mJiSgqKmrznC1btuDNN9/EqlWrOnWP5cuXIzIy0v2VlpbmVYxERIEmv7wONTaxy9sQtab1AfI3/0ykvGfpAxia/95WqJlIeSqa+89yeh8RkYvXidTw4cOxfv36Vo+vW7cOQ4YM8UlQ7amursYtt9yCVatWIS4urlPnLF68GFVVVe6v06dP+zVGIiK1SZsCaKLRBCCfpkadozd4WsaXnwQEQZUwWJEiImqb180mHnvsMVx77bXIzc3FZZddBgDYuHEj3nnnHbz33nteXSsuLg4GgwHFxcWyx4uLi5GUlNTq+NzcXOTl5WH27Nnux5xOsb1vUFAQjhw5gqws+Wpck8kEk8nkVVxERIFMMx37KliR6raYfkDZMaCpHqguAizJioeQGReGEKMB9Y0OHChkRYqIyMXritTs2bPx8ccf4/jx47jnnnvwf//3fzhz5gy++uorr9uQBwcHY8yYMdi4caP7MafTiY0bN2LChAmtjh88eDD27duHPXv2uL+uuuoqTJ06FXv27OG0PSIitOjY10fNqX3NFSlzJBASrV4cgUy2TkqdhhMGvQ7ZyWLr+tPl9aiqb1QlDiIirelS+/Of/exn+NnPfuaTABYuXIg5c+Zg7NixGDduHFasWIHa2lrMnTsXAHDrrbeiT58+WL58OcxmM4YNGyY7PyoqCgBaPU5E1Fu5EqmoUCNSIs3qBNFkB6qaN5GNzgR0OnXiCHQtO/dlTFIljKEpkdiVXwlA7Ag5IStWlTiIiLSky/tI7dy5E4cOHQIADB06FKNHj+7SdW644QacO3cOS5YsQVFREUaNGoUNGza4G1Dk5+dDr/e6cEZE1CuVVDfgXLUNgNj2XKdWAlOZDwji1GtO6+sG6WunkYYTBwqqmEgREaELiVRJSQluvPFG5OTkuKtBlZWVmDp1KtatW4f4+Hivg5g/fz7mz5/f5s9ycnI6PHft2rVe34+IqKeSb8SrlUYTTKS6TANT+wB5w4mDbDhBRASgC2uk7rvvPlRXV+PAgQMoLy9HeXk59u/fD6vVivvvv98fMRIRUScdlCVSKq6PkjWaYMe+LotMA3TNf6pV3EtqYFI4gvRidXN/ARtOEBEBXUikNmzYgFdeeQXZ2dnux4YMGYKVK1fi888/92lwRETkHc107GNFyjeCgsVkClC1BbopyIABiWLDidxztWhodKgSBxGRlnidSDmdThiNxlaPG41GdytyIiJSh6siZTbq0S8+XL1AuBmv77heP1sVUFeuWhiuxNzhFHC4qFq1OIiItMLrROqyyy7DAw88gIKCAvdjZ8+exYIFC3D55Zf7NDgiIuq86oZG5JXVAQAGJ1lg0KvYKc9VkTKGAuGJ6sXRE0inRmqo4QQRUW/ndSL18ssvw2q1IiMjA1lZWcjKykJmZiasViteeuklf8RIRESdcKjQUyVQdVqf0wFU5Iljtj7vPg02nDjAhhNERN537UtLS8OuXbvw1Vdf4fDhwwCA7OxsTJs2zefBERFR50mrBEPUTKSsZwFn86atbDTRfdHSvaTUq0i5NuUFmEgREQFdSKT+/ve/44YbbsD06dMxffp09+N2ux3r1q3Drbfe6tMAiYiocw5opWOfrNEEE6lu00hFKsJsREZsKPLK6nC40IomhxNBBu7zSES9l9f/BZw7dy6qqlrPja6ursbcuXN9EhQREXnPlUgZ9DoMToo4z9F+xEYTvhWd4RmrmEgBngTd1uTEidJaVWMhIlKb14mUIAjQtTHf/cyZM4iMVPETUCKiXszW5MCxYnGNVFZ8GMxGg3rBlB33jKNZkeq24FAgIkUcl+eqGsrQPp4po/vPsuEEEfVunZ7aN3r0aOh0Ouh0Olx++eUICvKc6nA4cPLkScycOdMvQRIRUceOFdegySnuMaTqtD5AnkjFDVAvjp4krj9QXQDUlYkt0ENjVAmjZcOJay9QJQwiIk3odCJ19dVXAwD27NmDGTNmIDzcsz9JcHAwMjIycN111/k8QCIiOr+DsvVRKjaaAIDSY+L/GiWVFOqeuIHAyW/FcekxoO94VcJgC3QiIo9OJ1JLly4FAGRkZOCGG26A2Wz2W1BEROQdWce+ZBUTqSa7p/V5bBagZzMCn4gb6BmXHlUtkYoLNyHRYkKx1YaDBdZ2p/sTEfUGXv+FmzNnDpMoIiKNkXbsU7X1eUUeIDjEcSyn9fmMdIpk6VH14oBnep+1oQlnKupVjYWISE1eJ1J6vR4Gg6HdLyIiUpbTKeBQoZhI9YkKQVRosHrBlB3zjKVVFOoeWUXqWPvHKYDT+4iIRF7vI/Xhhx/KyviNjY3YvXs33nrrLSxbtsynwRER0fnlldWi1i5WgdRfHyWplrDRhO9EpADGMKCxVgMVKWkiZcXMYckqRkNEpB6vEylX0wmpX/7ylxg6dCjWr1+PefPm+SIuIiLqJM1sxAsApZKOfbH91Yujp9Hrxc59hXvF6ZNNNiDIpEooLTv3ERH1Vj5bBXzRRRdh48aNvrocERF10sFCDXXsk07tYyLlW67pfYJDvumxwlKjQ2Axi5/Dci8pIurNfJJI1dfX469//Sv69Onji8sREZEXZBWpPmpP7WtOpCJSAFN4x8eSd2K10XBCp9O5q1Il1Tacq7apFgsRkZq8ntoXHR0tWyMlCAKqq6sREhKCt99+26fBERFRxwRBwMHmBf/RoUYkWVTsqlpXDtSXi+M4VqN8TlOd+yzYeqIMgNhw4tJBCarGQ0SkBq8TqRUrVsi+1+v1iI+Px/jx43H27FlfxUVERJ1QUm1DaY0dgLh2RdU9faTd5Nj63Pe01Lmvj7zhBBMpIuqNvE6k5syZI/u+uroa77zzDpYuXYoff/wRDofDZ8EREVHHpGtUVF8fxY59/hWbBUAHQJCvRVPBMFnDCa6TIqLeqctrpL799lvMmTMHycnJeO655zB16lRs27bNl7EREdF57JMkUsP6qNyxr4wVKb8yhgBRfcVx6TFAEFQLpV98OEKM4t6R+9hwgoh6Ka8qUkVFRVi7di3efPNNWK1WXH/99bDZbPj4448xZMgQf8VIRETtkFakhqudSElbn3ONlH/EDQQqTwE2K1BTDEQkqRKGQa/DkBQLdp6qwOnyelTW2dXdCJqISAWdrkjNnj0bgwYNwk8//YQVK1agoKAAL730kj9jIyKi83BVAyLMQUiPDVU3GFdFKsgMRKapG0tPJVsnpW7DCWnivv8s95Miot6n04nU559/jnnz5mHZsmX42c9+BoPB4M+4iIjoPEqqG1BsFVtPD1O70YSjybO3UUwWoOffCL/QUOc+6VRSTu8jot6o04nUli1bUF1djTFjxmD8+PF4+eWXUVpa6s/YiIioAwckVYDhqSpP66s8BTgbxTGn9fmPhjr3ySpSbDhBRL1QpxOpiy66CKtWrUJhYSF++9vfYt26dUhJSYHT6cSXX36J6upqf8ZJREQt7NNqxz42mvAfDU3ty4oPg9kovo3Yz4oUEfVCXnftCwsLw+23344tW7Zg3759+L//+z8888wzSEhIwFVXXeWPGImIqA37NNVoQtr6fGD7x1H3hMUB5uZ/a5UrUkEGPbKTxQT+VFkdquobVY2HiEhpXW5/DgCDBg3Cs88+izNnzuCdd97xVUxERNQJripAuCkIGbFh6gZzTpJIxTOR8hudzpOoVp0G7LWqhiNN4A+wKkVEvUy3EikXg8GAq6++Gv/5z398cTkiIjqP0hobCqsaAIjT+vR6FRtNAJzapyRpxa/sePvHKYANJ4ioN/NJIkVERMrS1LQ+QQBKj4hjSypgClc3np5O1rlPOw0nmEgRUW/DRIqIKABJp1ENUzuRqikBGprj4bQ+/9NQ574BCeEwBYlvJQ4UcC8pIupdmEgREQWgfVpKpGSNJgapF0dvoaHOfdKGEydLa2FtYMMJIuo9mEgREQWg/c17SIUFG9AvTuVGE65pfYB82hn5R3QGoA8SxypXpICWDSdYlSKi3oOJFBFRgCmvteNsZT0AYGhKpPqNJmQd+1iR8juDEYjpJ47LjgFOp6rhDOvj2cOM+0kRUW/CRIqIKMBoalofwKl9anBN72tqENugq4id+4iot2IiRUQUYPbLEilLB0cqxJVImaPEDWPJ/zTUuW9gYgSCmxtO7C9gIkVEvQcTKSKiALNfS63PbdWA9aw4jh8kbhhL/qehhhNGgx7ZSREAxIYTNbYmVeMhIlIKEykiogDjmj4VGmxAv3iV92ySTetj63PFSDc9VjmRAjzT+wRB3pqfiKgnYyJFRBRAKmrtOFMhNpoYkmyBQe1GE9JpZWw0oZy4/p6xxjr3cZ0UEfUWTKSIiAKIdA2KJhpNnJO2PmdFSjEh0UBYgjjWUEUKYOc+Iuo9mEgREQWQ/ZJ9elRfHwVwap+aXK93bQlQX6lqKAMTIxBscDWc4F5SRNQ7MJEiIgog+7Xa+jzIDET1VTeW3kbaua/suHpxAAgO0mNQc8OJ3HM1qGXDCSLqBZhIEREFENf6E7NRj6z4MHWDcTQC5SfEcewAQG9QN57eRkOd+wB5w4mDhaxKEVHPx0SKiChAVNU1Ir+8DoDYaCLIoPJ/wstyAWdz5UFaHSFlSBOpc4fVi6OZrOHEGa6TIqKej4kUEVGAkDaa0MT6qJIDnnHCEPXi6K0SBnvGxQfVi6PZcDacIKJehokUEVGA2Ke19VHSN++JTKQUZ+kDmJp/D0rUT6QGJoXDaBDb8bMFOhH1BkykiIgChOYaTUjfvLMipTydzpPAWs8C9RWqhmMKMmBgoqfhRJ2dDSeIqGdjIkVEFCBcn/KbgvQYkBCucjQAipun9gWHA1Hp6sbSWyUO9YxLDqkXRzPX9D6nABxkG3Qi6uGYSBERBYDKOjtOlYmNJoamaKDRhK0aqDwljhOyAT3/nKhCWgksPtD+cQoZkRrlHu9lwwki6uH4l4+IKAD8JHlTKn2zqpoSSZc4TutTj6wipf46qRGpnimne09XqhcIEZECmEgREQUA6ZvSkWlaWB8lqX5I38yTshKyPWMNdO4blBQBU5D41uKnM5XqBkNE5GdMpIiIAoB0mtRILVSkitn6XBPMkUBkmjguOSjuhqsio0GPoSkWAEBeWR2q6hpVjYeIyJ+YSBERBQDXp/sR5iBkxIapGwzQovU5K1KqciWyNitQdVrdWCCfevrT2UrV4iAi8jcmUkREGldU1YCSahsAcQ2KXq9TNyBB8EztC08CQmPUjae3k+7hpYHpfdKpp1wnRUQ9GRMpIiKN2yN5M6qJRhPVRZ49i7gRr/oSpA0n2LmPiEgpTKSIiDROumhfE+ujSrg+SlM0VpHKjA1DhCkIABtOEFHPxkSKiEjjpK3PNdGxT7Y+aph6cZAodgCgN4pjDbRA1+t1GNH8e1pstaGoqkHliIiI/IOJFBGRhgmC4P5UPz7ChCSLWd2AAPmbdU7tU19QMBA3UByXHgWa7OrGg5bT+ypVi4OIyJ+YSBERaVheWR2sDU0AgJGpkdDpVG40AXhan+sMQNwgdWMhkSuhdTYBZcfUjQXi76oLp/cRUU/FRIqISMNkG/FqYX2UoxE4d0Qcx2YBRg1UyEi+Vq1ov3pxNJO1QGfDCSLqoZhIERFpmHRa1Ii0KNXicDt3BHCIrdiRNFzdWMgjaYRnXPSTenE0S440Iy7cBED8MEBQeaNgIiJ/YCJFRKRh0k/zR/TRQKMJ6Zv05JHqxUFyyZJEqnCvenE00+l0GNXccMLa0IS8sjqVIyIi8j0mUkREGtXocOJAgZhI9Y0JRXRYsMoRQf4mXVoFIXWFJwARyeK46Cdx02SVyaf3VaoWBxGRvzCRIiLSqKPF1WhodAIARmphWh8AFLIipVmuf4+GKqDylLqxABghaTix9zTXSRFRz8NEiohIo2T7R6VqYFqf0+mZ2heZBoTGqBsPySVpa3ofK1JE1NMxkSIi0ijpm88RWujYV3ESsNeIY1ajtEf6b6KBRComLBhpMSEAgP0FVWhyOFWOiIjIt5hIERFplGs6lF4HDOtjUTkaAIV7PGOuj9IeWcMJ9Tv3AZ6W/Q2NThwtrlE3GCIiH2MiRUSkQQ2NDhwprgYADEyMQGhwkMoRgeujtC4yDQiJFscaqEgB8r3POL2PiHoaJlJERBp0oKAKDqfYeW2EFtZHAfI358msSGmOTuepFNaWANVF6saDFg0nuDEvEfUwTKSIiDRI2uVME+ujBMHTaCIs3tNqm7RFY+ukhvWJhF4njveerlQ1FiIiX2MiRUSkQdJpUCO1kEhZzwJ1ZeI4aYRY/SDtkSVS6q+TCjMFoX9COADgSHE1GhodKkdEROQ7TKSIiDTI1fo8OEiPQUkRKkcDro8KFLJEao9qYUi5PghwOAUcKLCqGwwRkQ8xkSIi0piq+kacKK0FAAxJtiA4SAP/qeb6qMAQkwUYw8SxBipSADBCspk0p/cRUU+igb/OREQktU9rG/ECnvVRACtSWqbXA0nDxXFVPlBXrm48kP8Os3MfEfUkTKSIiDRmr9Y24hUE4MyP4tgUCURlqBoOnYc00T27S704mg1OsiDYIL7dYOc+IupJmEgREWnM7vwK93h03yj1AnGpzBfbaQNA6hix6kHalXqhZ3xmh3pxNAsO0mNo84bSJ0trUVFrVzkiIiLf4F9DIiINEQQBu/IrAQBRoUZkxoWpGxAgfzOeOk69OKhz0qSJ1Hb14pAYnRbtHu8+XdHBkUREgYOJFBGRhuSX16G8+RP70WlR0GmhzfhpyZtx6Zt00qaodCAsQRyf2Qk4nerGA+CC9Cj3eHfzBwVERIGOiRQRkYbskk3ri+7gSAVJqxp9xqoXB3WOTgekNVcObVVA6VF144H8d1n6O05EFMiYSBERaYj00/oLtJBINdYDRfvEcdwgICRK1XCok1IlCa8GpvelRJqRaDEBAPaeroLDKagcERFR9zGRIiLSEFcipdMBI9M00Pq8YA/gbBLHnNYXOKRr2U6rn0jpdDr3OqkaWxOOl9SoHBERUfcxkSIi0oh6uwOHCq0AgIEJEYgwG1WOCPJqBhtNBI6U0YDOII5dretVJl0nxel9RNQTMJEiItKIfWer0NQ85UkTbc+BFh37WJEKGMGhQNIwcXzuMNCg/v5N0nVSu5lIEVEPwESKiEgjdmlt/yhBAE43J1ImCxA/WN14yDvuCqKgiarU8D6RCNKLXSh3sXMfEfUATKSIiDRC+im9JhpNVJ0GaorEcR9uxBtw0iRTMTWwMa/ZaMCQFHFj3uMlNaiqb1Q5IiKi7uFfRSIiDZBuxBthDkJWfLi6AQEt9o/i+qiAI52KqYFEChD3RnPZc7pStTiIiHyBiRQRkQacrazHuWobAGBUWhT0eg1sxCudDsb1UYEnOgMIjRPHZ3ZoZGNerpMiop6DiRQRkQZI14xociPeVG7EG3CkG/M2VAFlx9SNB3C3QAe4ToqIAh8TKSIiDZCvj4pSLxCXxgag8CdxHDcQCNFIckfe0dj0vrSYEMSFBwMA9uRXwMmNeYkogGkikVq5ciUyMjJgNpsxfvx4bN/e/uaBq1atwuTJkxEdHY3o6GhMmzatw+OJiALBbmlFKk0DSUvhHsDZ3AyA0/oCl/TfTiMb845q/v22NjThRGmtyhEREXWd6onU+vXrsXDhQixduhS7du3CyJEjMWPGDJSUlLR5fE5ODm666SZs2rQJW7duRVpaGq644gqcPXtW4ciJiHyjodGBAwXiPj9Z8WGIDNXCRrzcP6pH6HOBZGNe9StSADfmJaKeQ/VE6oUXXsCdd96JuXPnYsiQIXjttdcQGhqK1atXt3n822+/jXvuuQejRo3C4MGD8cYbb8DpdGLjxo0KR05E5BsHCqxodLg24tVANQpgx76eIjgMSBwqjksOAQ1WdeOBvOK6m+ukiCiAqZpI2e127Ny5E9OmTXM/ptfrMW3aNGzdurVT16irq0NjYyNiYmLa/LnNZoPVapV9ERFpieb2jxIET/UiOIIb8Qa6NMnGvGd3qhoKAIxMi4SrKSU79xFRIFM1kSotLYXD4UBiYqLs8cTERBQVFXXqGg8//DBSUlJkyZjU8uXLERkZ6f5KS0vrdtxERL4kWx+lhUYTVWeA6kJx3OcCQG9QNx7qHo01nAgNDsLgJHFj3iPF1aixNakcERFR16g+ta87nnnmGaxbtw4fffQRzGZzm8csXrwYVVVV7q/Tp08rHCURUcdc60TCgg0YmBihcjSQv9nmtL7Ap7GGE4DnAwNBAPZyY14iClCqJlJxcXEwGAwoLi6WPV5cXIykpKQOz33uuefwzDPP4IsvvsCIESPaPc5kMsFisci+iIi0orCqHoVVDQCAkWlRMGhiI15powkmUgEvph8QGiuOz+wQsxeVSaewcnofEQUqVROp4OBgjBkzRtYowtU4YsKECe2e9+yzz+LJJ5/Ehg0bMHYsN4kkosCluWl9gLxqwY14A59O56lKNVQCZcdVDQeQ/65zY14iClSqT+1buHAhVq1ahbfeeguHDh3C3XffjdraWsydOxcAcOutt2Lx4sXu4//0pz/hsccew+rVq5GRkYGioiIUFRWhpqZGradARNRlmms00dgAFO4Vx7H9gdC2G/lQgNHY9L7MuDBENbf5351fAUEDVTIiIm+pnkjdcMMNeO6557BkyRKMGjUKe/bswYYNG9wNKPLz81FYWOg+/tVXX4Xdbscvf/lLJCcnu7+ee+45tZ4CEVGXST+NH5UWpVocbkU/STbi5bS+HkO61k0DDSd0Oh1GN/++V9Q1Iq+sTt2AiIi6IEjtAABg/vz5mD9/fps/y8nJkX2fl5fn/4CIiBRgb3Ji31lxI96M2FDEhptUjghA/jbPmNP6eo6UCwCdHhCc8n9jFV3QNxqbjpwDAOw6VYHMuDCVIyIi8o7qFSkiot5qf0EV7E1OABraiPfkt55xxsXqxUG+ZQoHkkeJ43OHgJpzqoYDABeke37nd7LhBBEFICZSREQq2XGy3D2+MEMDa5EcjUB+82bo4YlA3EB14yHfypzsGedtVi+OZqMkXSql/18gIgoUTKSIiFSyI8/z5nFcpgYqUgW7AXtz456MyWK3N+o5Mi/xjKWVR5WEmYIwLEXckuRYSQ0qau0qR0RE5B0mUkREKnA6Bfx4SpzOFB1qRFZ8uMoRQf7mWlq9oJ4h7SJA37w0WgMVKQAYK6nEuv7/QEQUKJhIERGp4Pi5GlTWid3xxmbEQKeF6o/0zbW0ekE9gykc6NPcQKTsOGAtUDceyKe0Siu0RESBgIkUEZEKtkvWhIzTwvqoJpunm1tkGhCdqW485B+y6X3qV6UuzPBMaWUiRUSBhokUEZEKfpS8aRyboYH1UWd+BJoaxDHXR/Vc0imbGlgnFRtuQr94se35vjNVqLc7VI6IiKjzmEgREalgR564HsRs1GNYn0iVo0GL9VGc1tdjpY4DDM37leWpn0gBnopsk1PA7tNcJ0VEgYOJFBGRws5W1uNsZT0AYHRaNIwGDfynWLY+io0meiyjGUgbJ44r84GKPFXDAVo0nMhjIkVEgUMDf72JiHoX6bS+CzM1sD7KXgec3i6OY/oBkanqxkP+lTnFM9bA9L5xbDhBRAGKiRQRkcI012gifyvgFDsIIoPVqB5PWnE8kaNaGC5pMSFItIjTDXedqkCTw6lyREREncNEiohIYa7pSwa9DqP7RqkbDAAc/8ozzrpMvThIGX3GACZxI1zkfg041W3woNPp3NP7au0OHCqsVjUeIqLOYiJFRKSgyjo7jhSLbxSHplgQZgpSOSIAx74Q/1dnAPpdqmoopACD0fPvXF8BnN2lajiAvDK7ndP7iChAMJEiIlKQdDH92HQNTOsrPyluzgoAaeOBkChVwyGFDJjuGR//Ur04mkm3APiRiRQRBQgmUkRECtpxSrI+KlMD+0dJp/UNmKZeHKSs/pJ/62PqJ1KDkyyIaK7O7sgrhyAIKkdERHR+TKSIiBS046R0I14NVKSkb6L7T2//OOpZLClA4jBxXLALqDmnajgGvQ5jmqtSpTV25JXVqRoPEVFnMJEiIlJIQ6MD+85WAQD6xYUhLtykbkCNDZ721+FJQNJwdeMhZUmrUrkb1Yuj2YXSNugnOb2PiLSPiRQRkUL2nK5Eo0OcsnShFqpRp74DmsSNgdF/GqDTqRsPKUu6TkoD0/suZMMJIgowTKSIiBQi/ZRdExvxcn1U75Y2XtIGfaPqbdBHpEYi2CC+LWHDCSIKBEykiIgUIv2U/cIMDTSakLU9n6puLKQ8gxHoN0Uca6ANutlowIjUSABAXlkdSqobVI2HiOh8mEgRESmgyeHErlNi6/OECBP6xoSqG1DpMUnb83Fse95bSRuMHPlMvTiaSSu10q0CiIi0iIkUEZECDhdVo9YuTp26MCMGOrXXIx342DMe/DPVwiCVDZoF6JrfChz8GFC57bi0UrudDSeISOOYSBERKWCH1qb1HfzYMx7yC9XCIJWFJwDpk8Rx+QmgaJ+q4YxJj3H3PNnBdVJEpHFMpIiIFCBLpNRuNFF6HCjeL477jAGi+qobD6lLmkhLE2wVRIYYMSgxAgBwqNCK6oZGVeMhIuoIEykiIj8TBAHbToiJVIQ5CIOTLOoGdPAjz3jI1aqFQRqRfZVnet+Bj1Wf3je++YMGp8B1UkSkbUykiIj87GhxDcpr7QDEN4kGvdrro/7tGXNaH0UkSqb35XqqlSq5qF+se7z1RJmKkRARdYyJFBGRn22TvBmUvklURVkuUNy8DiblAiA6Xd14SBukCbW0EYkKxkv+P7KNiRQRaRgTKSIiP9uaq6FE6oBkWt/Qq1ULgzQm+yoAzZVSlbv3xYQFY3CSuE5q/9kqWLlOiog0iokUEZEfOZ0CfjgpJlIWcxCyk9VeH/WxZ8xpfeQind5XdhwoPqBqOK4PHJwCsINt0IlIo5hIERH50ZHialTUiZ+oj+8Xq+76qLJcT3vrlNFAdIZ6sZD2SCuUKnfvk62TyuX0PiLSJiZSRER+pKn1UdI3x0OvUS0M0ijp9D6Vu/eNz/TsJ7XtJBMpItImJlJERH4k/TR9gtqJlLSJAKf1UUsRiUD6RHFcdgwoOahaKNFhwe5tAg4UWFFVx3VSRKQ9TKSIiPxEXB8lru+ICjW6F9CroiwXKPpJHHNaH7VHuq+YtDGJCi7qJ+4nJQjA9jyukyIi7WEiRUTkJ4eKrKiqb14flRkDvZrro2RNJq5WKwrSuiHamd43geukiEjjmEgREfnJthOeT9FVXx8lndbHtufUnogkzUzvG58Z614nxY15iUiLmEgREfnJ98dL3eMJWSomUuUnPNP6kkdxWh91TDa972O1okBkqBFDmrcLOFRoRXmtXbVYiIjawkSKiMgPGh1O9/qouPBgDEpUcX0Uq1HkjSHa2Zx3Uv8495jT+4hIa5hIERH5wU9nKlFjawIATMyKg06n0vooQQB+etfzPbv10flEJAF9J4jj0qNA4R7VQpEmUlskFV4iIi1gIkVE5AffHfd8ej6pv4rT+s78CJw7JI7TxgMx/dSLhQLHyBs8411/Vy2MCzOiYTSIH0J8n8tEioi0hYkUEZEfSD89l36qrrjdkjfBF9yqXhwUWIZdBxjDxPG+9wF7nSphhAYH4YK+0QCAU2V1OF2uThxERG1hIkVE5GN19ibszq8AAKTHhiI1OlSdQGw1wP4PxXFwONueU+eZIoCh14hjmxU49B/VQrlY8kEEq1JEpCVMpIiIfGz7yXI0OsQF+hOzVKxGHfgIsNeI42HXAaZw9WKhwCOtYKo4vW+ibJ0UG04QkXYwkSIi8rHvJd3FLlZ1Wt8/PGNO6yNvpY0D4gaK41PfAaXHVQljZGokwk1BAMQtBZxO9boIEhFJMZEiIvKxLcc0sH/UuSPA6R/EccIQoM8YdeKgwKXTyRNwaWKuoCCDHhf1iwEAlNXacaS4WpU4iIhaYiJFRORD5bV2HCy0AgCGplgQExasTiA/rvGMR98ivikm8taIGwG9WA3CnreBJpsqYUgbtnzHNuhEpBFMpIiIfEi6GF61bn0NVmD3P8VxUAgw8kZ14qDAFx4PZM8Wx7XngP0fqBIG95MiIi1iIkVE5EPfHj3nHqu2Pmr3PwF78/SnkTcCoTHqxEE9w0X3eMZbXxE3eVbYgIRwJFpMAIAfTpTD1uRQPAYiopaYSBER+YggCPj2qPhpuSlIj3GZKiQwTgfww2ue78ffpXwM1LOkjQP6jBXHxfuAvC2Kh6DT6TB5QDwAoL7RgR/zKhSPgYioJSZSREQ+cqykBkXWBgDA+H6xMBsNygdx5HOg8pQ4zrocSBisfAzU81x0t2e87VVVQpg8wFPhlVZ+iYjUwkSKiMhHpG/uLhmg0rQ+6Ztc6ZQsou4Y8gsgIkUcH/kMKD+heAiTB8S7e6Z8w0SKiDSAiRQRkY98K2l7fsnAeOUDKNgNnGqedhU3COh/ufIxUM9kMALj7mz+RlClKhUTFozhfSIBAIeLqlHSXP0lIlILEykiIh9oaHTghxPiRrxJFjMGJIQrH0TOM57xRXex5Tn51pjbAGOoON75FlB1VvEQLhng+YBi8zF27yMidTGRIiLyge0ny2FrcgIALhkYB53SScyZH4GjG8SxJRUYdbOy96eeLzQGuPAOceywAZufVzwEaaX322Oc3kdE6mIiRUTkA7L1UWpM69v0lGd8yYNAkEn5GKjnm/Q7ILi52rrr70BlvqK3H903CuEmcYPgzcdK4XQq34qdiMiFiRQRkQ+4Ph3X61TYP+rUViD3a3EclQ6M/rWy96feIyzW01Lf2Qh886yitzca9JiQFQsAKK+140CBVdH7ExFJMZEiIuqmwqp6HC2uAQCMSI1CVGiwsgFIq1FTHhYbAxD5y8T5gEls+oA9/wLKchW9Paf3EZFWMJEiIuqmnCMqTus78Q2Qt1kcx/YHRtyg7P2p9wmJBibcK44Fh+JVqUsl/x/bdLhE0XsTEUkxkSIi6ibpm7nLBicod2NBAL7+o+f7KY8AhiDl7k+910V3iwkVAOx7Fzh3VLFbp8WEIis+DACwK78ClXV2xe5NRCTFRIqIqBtsTQ5sOS62YY4NC8aI5n1uFHH8K+DMdnEcPxgYdq1y96bezWwBJt4vjgUnkLNc0du7PrBwCtycl4jUw0SKiKgbtp8sR53dAQCYMigeer1Cbc8FQb426tLFgN6gzL2JAGDcb4DQ5sYqBz4Eig8oduupgzyVX07vIyK1MJEiIuqGTYc9n4YrOq3vyGdAwW5xnDgcyL5KuXsTAYApHLh4gef7TU8rduuxGTHuNujfHD0HB9ugE5EKmEgREXXDpiPip+EGvQ6TByjUaMLpAL6WVKOm/h7Q8z/npIIL5wHhSeL48CfA2Z2K3DY4SI/JA8RqWEVdI/acrlTkvkREUvzLS0TURSdLa3GytBYAMCY9GpEhCrUd/3E1UNI8jSrlAmDQLGXuS9SSMUTcANrls0WA06nIrTm9j4jUxkSKiKiLVOnWV3MO2Pik5/uZzwA6hdZlEbVlzG1isxNArEjt/ocit710kKQN+hEmUkSkPCZSRERdJH3zJv103K++ehywVYnjkb8C+o5X5r5E7TEYgSv/7Pn+q8eBunK/3zbBYsawPhYAwIECK4qtDX6/JxGRFBMpIqIuqLE14YcT4pvFPlEhGJgY7v+bnt4O7PmnODZFAtOX+f+eRJ2ReQn+f3v3HR9VlfYB/Dd9kslMeu8hFOm9l+CCIIqyirgWBEQXFV3b+qqr++q+u667orsuwqKuu+DaUFAEKyDSBKR3pCSBVNL7JJl63z/OZJIxlEyYEpLf9/OZz8zcuXPvGZjMvc89z3kO+jjK7zdUuM5v5kXXtriA8T3T+4jIxxhIERG1w7bTpTDbxFiQa3tFQebt9DqrCfjisebnE38HBPmwSiDR5Vz3J0AlJsrFvv8Aubu9vstrr4l2Pt54otjr+yMiaomBFBFRO7Q8aZvcO/oSa3rI1r82F5iI7gcMu8/7+yRyR3A8kPGM44kEfP4AYDZ6dZf944MRpdcAAH7ILIPRZPXq/oiIWmIgRUTkJovN7kwj0muUGJkW7t0d5u8Dfvi7eCxXAb9cBiiU3t0nUXuMfAhIGCYeV2QD33k3/VQul2GS40KG2WrH9jOll3kHEZHnMJAiInLT3nMVqG6wAAAm9IyEWunFn1JLA7DmAUBylJSe8DQQ0897+yO6EgolMGMZoNSK53veArK3enWXLXuENzC9j4h8iIEUEZGbfJbWJ0nAN08D5WfE87jBwNjHvbc/Ik+I6A5MerH5+ecPAnXeKwQxuls4dGoFAFFwwmrzzTxWREQMpIiI3CBJkjOQUsplyPBm2fM9bwMH3hWPFRrgl28ypY+uDsMXACnjxOOaAmDlXaJgihdolApMcMwpVVVvwb6cSq/sh4jo5xhIERG54WRRLfIrGwAAI9PCERyg8s6Osr4Hvn22+fnNS4DInt7ZF5GnyeXAre8A+jjxPH8P8OXjopfVC1r2DLN6HxH5CgMpIiI3+CStrzwLWDUXkGzi+djHgf6zvLMvIm/RxwB3fAgoA8TzQx8Au5Z6ZVcTe0ZBIRdTEGw8UQzJSwEbEVFLDKSIiNyw4USR8/EkbwRSlkZg1RygsVo873E9cO3/en4/RL4QNwiY8c/m5xv/1yvzS4UEqjE8JQwAkFtRj1PFtR7fBxHRzzGQIiJqo7yKehwrqAEA9I03ID4kwPM7Wf87oOioeBzeHbj1XyJNiuhq1fcWYOwT4rFkA1bPA+orPL6bKX2aL2x8c7ToEmsSEXkGj85ERG307bHmk7Np/WI9v4NjnwL7/i0eK7XArHcBjd7z+yHytYnPAcljxOOaAmDNAsDu2ep6U/s2/022/FslIvIWBlJERG309bHzzsfX9/VwIFV0FFj3m+bn0xYB0X08uw8if1EogVv/DQRGiOdnNgBb/+rRXcQEazE4KQQAcKq4FpkldR7dPhHRzzGQIiJqg8KqBhzMrQIA9IrRIzVC57mNV5wF3r8VMDtO/Pr/Chg023PbJ+oIDLHALW8DEEUhsPUvwN5/e3QXLXuKv21x4YOIyBsYSBERtYHX0vrqSoD3bwHqHNUA44cCN/4NkMk8tw+ijiL9F8B1f2p+/tWTwPHPPbb5qX1jnI+/YXofEXkZAykiojb4psXV7Wn9Yi6xphuM5SKIqsgWzyN6AnetAtQe7O0i6mhGPwyMedTxRAI+ux84vcEjm04IDcSAhGAAwPHCGuSUGz2yXSKiC2EgRUR0GSU1jdiXUwkA6B4VhPQoDxSAqC0CVtzQXKHPEA/M/gwIDLvybRN1dJP+AAy8Szy2mYGVdwIn1npk09e36DFmrxQReRMDKSKiy1h/vAhN83te39cDvVFVecDy64HSn8RzfSww+3MgOOHKt010NZDJgOmLgT6/FM/tFmDVPODwx1e86ZZ/o98c5TgpIvIeBlJERJfxxZHmk7GpV1qtL+t74F8Tm9P5gpOAeV8DkT2ubLtEV5umSn4D7hTPJRuw5tfAht8DNku7N5scrkPvWAMA4HB+NXLL6z3RWiKiVhhIERFdQmFVA/acFZOHdovU4ZrYdqb12azA938C3rsFMJaKZWHdgHu/AcLSPNRaoquMXAHcvBQYOr952c7FwPJpoue2nW4c0HzB44sjhVfSQiKii2IgRUR0CV+2OAm7eWA8ZO2ppmeuBz6+C9i2CIAjRzB9MjB/I9P5iORy4IbXgCkvA3KVWJa/B3g7Ayg82K5NTu8f53y87hADKSLyDgZSRESXsLbFSdhNA+IuseZFNFQC7/0SOP2teC5TiIH2d34C6MI91Eqiq5xMBox6CJi/HghJEsvqy4AV04HsrW5vLjEsEEOSQwGIyXlPFtV4srVERAAYSBERXVRmSR2OF4oTsP4JwUhxdxLeyhyRopT3o3iu1gP3fA6MfUxchSciV/FDgAXbgKTR4rm5FvhgJnB0tdubannhg71SROQNPJITEV3EusNX0Bt1dDXw5lig5IR4rosE5n0FpI73YAuJOqGAUDEVQI/rxXObGfh0PrB2IWBu+7xQ0/rFQiEXqbjrDhdCaiq9SUTkIR0ikFq6dClSUlKg1WoxYsQI7Nmz55Lrr1q1Cr169YJWq0W/fv3w9ddf+6ilRNRVSJKELxyBlEwGTG9rINVQCax5UJz4mRzpRKGpwL3rgdgBXmotUSejCgBufx8YNLt52cH3gbfGA3l727SJSL0Go7uJ9Nn8ygYcyK3yQkOJqCvzeyD18ccf44knnsALL7yAAwcOYMCAAZgyZQpKSkouuP7OnTtxxx13YP78+Th48CBmzJiBGTNm4NixYz5uORF1ZkcLqnG2TFz9HpkajmiD9tJvkCQxB84bQ4HDHzYv7zdLpCqFd/Nia4k6IYUSuOkNYMYyQOVIqy3PBP49GfjycXHR4jJuHhjvfLzuUIG3WkpEXZRM8nNf94gRIzBs2DAsWbIEAGC325GYmIhHHnkEzzzzTKv1b7/9dhiNRnz55ZfOZSNHjsTAgQPx5ptvXnZ/NTU1CA4ORnV1NQwGg+c+CBF1Kn/44jiW7zgHAHj5ln64Y3jShVe020QhiR2Lm8dCAWI81A2vAQNu935jiTq78izg0/uAwgPNy3SRwIgHgKH3AoFhF3xbbaMFQ/70HcxWO8J0avz47C+gVvr9GjIRdSBXEhv49dfEbDZj//79mDRpknOZXC7HpEmTsGvXrgu+Z9euXS7rA8CUKVMuur7JZEJNTY3LjYjoUsxWu7Nan1opx7QLTcIrScDBD4A3hgAr73QNoq65CXh4D4MoIk8J7yamC5jyMqAOEsuMpcD3fwT+1hv46kmgvqLV2/RaFSb3jgYAVBjN2HLqwtkuRETt4ddAqqysDDabDdHR0S7Lo6OjUVRUdMH3FBUVubX+yy+/jODgYOctMTHRM40nok5ry6kSVBjNAIDrekcjOFDlukJZJvDudGDtQ0Dl2eblET1EWfPb3wMM7SiVTkQXp1CKEukL9wB9bgHgmNPN2gDsfQdYMgw4skpc5Ghh5pDmudo+PZDvwwYTUWfX6fu3n332WVRXVztveXntnymdiLqG1fubT7ZubXEShprzwIbngWWjgXPbm5enZQB3rQYe2g30mOK7hhJ1RcHxwG3Lgd8cBEY82NxDVV8GfHYf8N+bgLPbnQHVuPQIROo1AIBNP5WgvM7kr5YTUSfj10AqIiICCoUCxcXFLsuLi4sRExNzwffExMS4tb5Go4HBYHC5ERFdTHmdCd+fFOk/UXoNxqVHAOePAOseAf7RH9j5BmBznIiFJAF3fwrcsxboPplzQxH5UlgqcP1fgIf3iXTaJme3Ae/eKIpSHPsMSsmCWwaJohNWu+QyrQER0ZVQ+nPnarUaQ4YMwaZNmzBjxgwAotjEpk2b8PDDD1/wPaNGjcKmTZvw2GOPOZdt3LgRo0aNcm/nXz4J6NSAqQ6oLwcaqgBdOBCSDIQkioHiSg2g1Dbf261AQ4WoFKQMED/ioalikKtSI5YpWvyT2m1iXbsV0EXxJIvoKrD2UCGsdju6yQrxdFwRlO/8ETh/yHUlhQYYsQDIeAZQuzlJLxF5liFWpNOe/Ar49lmgKkcsz98LrJ4HBIZjQfdbcVgehYP2dKzen495Y1L922YiapvGGsBcJ+aXUwU0L7fbxUVNS4OYX64qV6Ta1xYBGoM4N1cHiXWsJsDaKO4tDUBdMVB5DqjOE8dztL+Txa+BFAA88cQTmDNnDoYOHYrhw4fj9ddfh9FoxLx58wAA99xzD+Lj4/Hyyy8DAB599FFMmDABr732Gm644QasXLkS+/btw9tvv+3ejo9+DGhknv44gFwpAiq5XPznw5GrrdAAocmAPkaUcVUHAnKVmKBGkkTAZSwFGqvFOiFJgD5WBGgKlVhXoRaBmrlepDDUlwPaECA0RQR12lCxXVWg+PKoA0V7TLXiS6gMAIIiPf+ZiTqL84eRtO1F7NPsQ4SsBsj52esaAzDsPlEpTB99oS0Qkb/0ugHoPgU4vgb44e9AyXGxvL4cYYffxko1YJYUOFjWHQVbH0T82LvE8ZWIWrM0iKBErRPnlAqVCFgs9eK+6VadD1RkAzX5Yr3ACCAgRJzb2syA3QLYHLeGChHwVOWJ819dJKCLEOe3kgRIdrF9S704L67MEe9pogoU7bA0NmeGeIKp/QXM/V7+HACWLFmCRYsWoaioCAMHDsTixYsxYsQIAEBGRgZSUlKwYsUK5/qrVq3C888/j3PnzqF79+545ZVXMG3atDbty1ni8Bk9DC0DKZkCkGye/FgdU2AEEHWNCLx0kc23wHARvcvkoidNqQHC03mQoc7PXA9kbRKD1bO3XHid2IHAkDlA35mAlunBRB2eJIkUvwP/BX5aJ07ofs6QAIz4tShcEcJCVNTJSRJQUyAu2ssU4nzPXCeeG0sBY5m4rykESn4SvTuS3d+t9i6ZHJDsqDFJCP5LbbvKn3eIQMqXnIFU1j4YggJFpB0YLqLchkrR1VdT6OgCbGzuCrQ2ApCJYCMgVPTyVJwVKQSmWvG6pVFUD7I0inS+gFDH3BYysV7lOcd2LkImF9G8qYOUaFdqgbhB4iQyNBkIThQ9ZSGJoidM5oUePSJvkyRx9ezsNiDzOyBzk/i7baFGCkBN1DAkDJwEdLsWiOnnp8YS0RWrrwBOr4cpazvOH9mEFNkFqvzGDgB6XA+kTQDihwJKte/bSeQJVpPoJarKFalrVXlAyQkgfx9Qd+EK1z6ndExwf6lzYsgAQ7zIugoIEefo9eXi/FoZAKi0juE3WvHYEC+G2xjiRE9ZQ6W4//kwHaVadCqEJgP6OAASaopyEJzQnYFUW/h1Ql5Jcu0WtdvgTP3TBouATq4Q47aq88UX3mb9WdeoWXwZdJFAQJj4UlWeFX8wplpxdd1idNzXi/dogkSA1lgFFJ8AjB6YR0OtF1fm5QqRthjVC0gaDSSNBCK6Axr9le+DyBPKzgA/fSHuq/OA8kyg9vwFV82VovG2dRq+kk/E1uemwaBljyxRZ/LYRwdQeOR7/Fr5JSYpDl54JVUgENnTceEwCUidICpzMkODOgKbRRzLCg4AOTvFWEBTjTintDaKXqUrpdQCkb1E9pLVJM4vbRYxZEStax6iogoUw1DCUsXFdmuj6NlqrBJDS+RKx7AUlbhpDKIWgS5C7MdUK9or2QHIxAV6VUDzEBWFb0YgXUlswECqKzKWiRNJZ1euozu3oQLiiywXfwQF+0UvWnsEhIloPyRZ3OsiRVeyXCH+6BKHi7FgRJ7WWAMUHgDy9gI/rQWKjl56fV0k0HMatipGYN52A+yQ4/ahifjrzP6+aS8R+cyesxWY9dYuAMDNCUb8o18OcPLL1gVlfi4wXFQGTBkLJAwTARazMsjTLA1A4SExvs9mEQGG2SjGClXliPuagvYNRdEYgPghQFgaAEkEXuogUWit5VAPXYQIiuQKT3+6DouBlBsYSLmprhQoOyW6hqtygWrHIMHqfNHjZbc297K5KyQJiOot7oMTgaAocbDSGMR2bSbRfRt1jejWJQJEz27JTyJYMhvFgaehEig7DZSeEml7uMTPmjYYiBsMpI4Xt7hBgFyBm5f8gMP51QCAtQvHYEBiiE8+DhH5jiRJmPz3bcgsqQMAbHx8PLpH68Ux7ew2ccvZIY5zl/odCQwHIq8BInsAwQniWKXUiCvziSPF1XoiQAREZadF4QaFSmTx2Ewio8hYJgKjqlxx7Co6JjKQ3CFTiKEkcqXYflB08zCMpiEZoali3DurR18QAyk3MJDyArtd5N/m7AQKD7peNbnUgcgdwUlARLrIa9VFiNRBVYD4QTLXNefCBicC4d1EL5jGILqgm3JxZTLRW1FbJNIbNQbxQ2NIuHA+vNUsPkN1vvgchniRe9tUfrOpwoxkF93ZVXniszdWi6s6+liR/mi3icCw6WYzA9UFIiWzplC0Qx8tPhskx3ot3mMsE9utyhM/koY4kder1FygzY2ONheIH+OQJEc3eqTjB1zd3NUuk4teyLpi0b0enCh+aEOTRbd6U+5xU9e63SbGGjRUOIqThHvuiqzdLoL0upLmCkGQxIGmvsKR750DlGeJ71l9Wdu3HTcY6DdTpOeEJF2wWMSxgmrc+MYPAIA+cQZ8+chYyHi1mahTWr7jLP7wxQkAwNzRKXjxpj6tV2r6/S86Chz/DDj1bauxlBclV4msi+g+zVOq6KIc5Zh14lhlqhO/yRHdXUs6XylLgzhWqALE777KcfxrWSraahLHwLIz4uTdbhMXMoOiRNt/XmnNWVr6nEgh08eKSZEDQgH87HdSsjUHB/XljpP6ZLG+QuNI91I0p32Z60SGTF2pOK6HpYoxMeqg5nWa1rdbgNpisb5kb8540YaI45lMLo5JMpn4THUl4hjbWOloc4K4kPZzkiSycqrygNpC0Y6gGPHv0VRZuemisdkoziEqssTxqGk8fFOVOmujWKe+XNyq88QFvgsVO2kPbYgjMEoWqXfJo4GE4WIIB7UbAyk3MJDyIavZMdAxR8zTJdnFj07pSSBvj8jvbeuByescP74t7y96VUgGjwWIVwO5UgRUlnrXCj7aEJEioNa1DtKsjSL4qSkUB8HgBHFTO37sJXvz3A/15eJAYzFeeVuVAWJsQ8JQMWA8eZQ4KF/Gs58dxUd7cgEAL/2yL+4akXzlbSGiDqm63oLhf/4OJqsdBq0Se56bBK3qMmlMpjpxEadgnxi0X3xMXIS6UjK56C0ISXRMW6ITv6OACGJqz4vf0voKMX2JIV5cTLRbmwMdm9kxbiZfHHNbHp9UuuYMjy7jEsdoedM4t6YLodLF1/WHiJ5A4jCRgqcxiO+HUtPcs8TsHK9gIOUGBlIdiN0uropV5YpbUze3qVacmCs1oqep6Jg4aJnr/N1i6gg0BiB5DJAyRlw1VGrEyUd4uiOv273UhdpGC0b+eROMZht0agV2PzcJQRq/T7FHRF705CeH8emBfADAopn9cdvQdpQ/b6gESk+LHnJrowi2Cg+I9MCKbA+3mK5KMjkQ0QOI7it62+xW0SMoV4qAODBCTCgdkiyC5KYeRPKpK4kNeLZA/iOXi4IT+hiRBnEpkiQKYBjLxUHLXNecoqAOEl3rSrUIyMozRWqb2Sh6Oaym5qtOap3o4tdFihS8qlzRa2K3iteb1pMkcYJuiBc9KTKZWK+m0NFFL2uRSiAXvS6GeNHdHhAq0gRqi5qDQrlSXAlrSlEIihY/qoZ4sU5dkbji2DLloemxxuAo3JEi2llTILZ9oR4zuUr8KBvixXubyu431rimatgtIvUhIFT8W6iDgKpzIlWhZfl/S4tpAJRakeoQECbaW5YpJuC7GJlc/FtLdtHei171k4leo6je4t/a2iBOSACRChMYLv69nMVLUj1ayWfVvnwYzWLg7s2D4hlEEXUBd41McgZSK3aew8whCe6n8waEAkkjXJcNmSPua4tF+nZljuglairdbDaK31tNkPjtL/lJ9MhfKjtDEwwEhopUtUuNR9YYxAWlsDRxnDKWiv3KVa6lopUa0bMR1k2sr9SIbRtLxO+1XOWaZaDUit/m0BSRGtfUS3axi5uB4SIFPTDc8e9wThwzmtLWbRbHY4voMdNHi9THxurmKsRWU/NxqinNXSYXxwJ9jDhGN12ENRvR3MNkb86c0EWJlEJtsDgGNf0/NGWeyOTNjwPCRI+PIc6RblgkLuwCjnUVjrRznTguhaeLfz+VVmyzoVKsowoQt4AwR6AUzmqPnVyXPWOoNJqhC5KgkHMcxFVBJnPkIYcCSL/4enGDfNYkv9FHt33dwDDv/pvYHAfDptSSpjSTpmCxKeCxmkXuubVFnnhT6VR1kN/mbLHZJazYec75fN7oFL+0g4h8a1BiCAYkBONwfjWOF9Zgz9kKjEgL99wO9NHiljTy8uva7Y5pS4wtpkaBOO4FRTWP65EkccLeWN0c6ChUroGPL8Z2ag0ihbpN6waLghxEnVSXDaTGvbIZck0g9BolDAEqBP/8FqiCQatEcIDqgq8bAlRQKVj9hLo4hVLcLjdYWqlu01glX9v0UzFyK8QV3nHdI0T1LiLq9GQyGe4dm4pHVx4CAPxnx1nPBlLukMtFgYPLzb8okzl66cN80y6iq4zNLqGu0YqaRgtqG62obbSgzmRFrWNZVb0F1Q3N9zUNFlQ1mFFRWdXufXbZQKpJrcmKWpMVBVXuFz3QqRUIDlAhSKtEkEYJnUbcuzzWNj1WIEijgk6jcK4TqFYiQKWARiWHRilnlTAiH1u+45zz8b1jUv3XECLyuev7xuLPhp9QXGPCxhPFyKuoR2IYy5YT+YLVZkej1Y5Gi63Fze68b2ixvN5sQ60jOKpxBEi1LvficVOavrvspvZXVeyygdSY9HA0QIOaBhGVVjdYYLW7V3fDaLaJ/7TqK2+PTAYEqBTQqhSOe3mLx47lagW0SjkC1ApHAOZYTyle1yjljnXl0Cibt9H0XON4rlHKoVYwcKOu7URhDXZllwMA0iJ0mNAj0s8tIiJfUivlmD0yGa9uOA27BLy78xyev7G3v5tF5BeSJMFktaPBbEOjtTmoaQpoTC7Pmx+bLDZnQCTee+HgqOl9Yn0bLLaOUetOq5IjSK1GXjvf32UDqbdmD3WpzCFJEurNNmdQ1TLAuuDzRqvzcV2jFQ2W9kXBzfsH6s0i6vYFmQyOAMw16NIo5Y4ATQRtGsd9U0AWoFZC7+hpa+pxa/lc7+h1UzLtkTq45TvOOh/PG5MCOcdLEnU5dwxPwhvfZ8JktePjvXl4bHIPFpyhDk2SJDRa7C3OR0X6WoPjHLLebHWeTzY4HjeYbTC2eFxvFoFNg7lFoGS1X37nHVCgWmR66bVK6LUq6LVKGBz3LZfptSqEBKgQEug6TEerUoiqfX9s3/75a+Egk8mgc6TkxYW4Pzme1WYXPVQmK+ocN6PJirrGFo9NVtSZbKgzWWA0iS97U/elyRGtOyN9x5fb3V6ytpIkOPcHuDmLdhsEqBTQa5UIDVQjJFCFMJ0aoTo1QgNVCA1UIzRQjTCdGpF6DaIMGoTrNCz8QT5TVN2ItYcKAQB6rRK3DE7wc4uIyB/CgzSYMTAeH+/LQ63JipV7cnHfuDR/N4u6CEmSYDTbUFprQlmdCaW14lZeZ0LVBS/oW1HTYIHZdvUEPQq5zJlN1fLCfXPGlbhoH9AiyypA7ZppFahWtAiImgOlII3S7xfuGUh5iFIhR3CAHMEBni1zabHZL9A12vIqgh0mq6PL1dqi+7VFt6zJ2ryNVutaXbfvqSsSTUFaSW3bJgFUyGWI0msQZdAiWq9BtEGLmGAtog1aJIUFIiksEFF6DXsNyCPe2Z7tPBDdPTIZOl6BJuqy7huXio/3icSet7dlY/aoZGiUl5mgl6gNGsw2FFTVI6+iAfmV9civbEB+ZQOKahqdQdOVZjS1h1rRPExEBDjyVkNLtC0CHZGlpECAuvmxRiV3HX7SYt2Wr3X2wmw8e+jgVAo5VAo59D6ao60pR9bkCLoaWwRdjRY76s2OnjVHT1ttY4vn5ubldY7Ux8p6c5uCM5tdwvnqRpyvbrzoOmqlHImhAUgKC0RKhA7pUUHoHqVHelQQwnT+KZ9NV59Koxkf7skFAGiUchaZIOriukfrMaVPNNYfL0ZJrQmf7i/AnSOS/N0suko0Wmw4W2ZEZkkdMkvqkF1mRF5FPfIr61FW1/4iBj/XVGVaVJJWNqenaVWOjCoFAtRKBDp6cAI1SgQ6gqVAtQKBaiUCNQoEqjj8wpMYSJELmUzmvLoAeKZ3rcFsQ0W9GZVGMyrrzaist6DSaEaF0YySWhNKahpRVNOI4hoTyo0mMSfuBZitdmSVGpFVagROlbq8FqZTIz0qCL1jDegTZ0CfuGB0jw7q9FdCyH0rdp5zjkW8fVgiIvUaP7eIiPztoYx0rD9eDAB4a1sWZg1N4MkmuZAkccH3eGENjheK+cdOF9cir6Ie7RmFERKoQmSQBpF6xy1Ig4gW9yEtptzRa/2fwkYXxkCKvC5ArUC8OgDxbRh7ZrHZUVprQrEjsCqoakBeRT3yKuqR67hdqIerwmjGnrMV2HO2wrlMrZCjZ4wefeODMSQ5FEOTQ5EcHshqhV1YncnqnIBXKZfh1+M5FoKIgAGJIRibHoEfMsuQU16Pr46ex80D4/3dLPKj6gYLDuRWYv+5ShzOr8LxwhpUGNvWwySTAdF6LRJCA5AQGoDEsEDH40AkhgYiOljD9NFOgoEUdSgqhRxxIQEXLfghSRJKak3IKqlDZmmdsys9s6Su1Xgss82OowXVOFpQjY8cqVwRQWoMTgrF0JRQjEgNR9/4YBa56EI+3J2D6gZRXOXmgfFICOWcMUQkPDSxG37ILAMALNuShen94zgutws5X92AXVnl2HuuEvtzKnCmpO6iGTJNAtUKdIsMQnqUuDU9TgwLYKDURTCQoquKTCZDtEEUoRidHuHyWlW92dnlfqxA3GeXGV1+CMvqzNhwohgbTogUjuAAFUZ3C8eY9AiM6x6BpDD2WHVWRpMVb23NBiCuFj6Ywd4oImo2Ki0cAxNDcCivCieLavHt8SJM6xfr72aRl9Q0WrA7uwI/nCnFD5llYtjAJYTr1OgTH4w+cQb0jRP3SWGBDLa7OAZS1GmEBKoxJj0CY1oEWEaTFYfzq3AgpxL7cipxIKcSNY1W5+vVDRZ8c6wI3xwrAgAkhAbgF72iMLl3DIanhkGtZE5yZ7F8x1mUO9IybugXi/QovZ9bREQdiUwmw6OTumPe8r0AgNc2nMKUPjHMWuhEskrrsPFEMb47UYyDeVWwXWRwk0IuQ+9YA4YkhzpvscFaXmilVmSSdLmOy86lpqYGwcHBqK6udpmQl7oGu11CZmkd9pytwM6sMuzILHemev2cXqtERs8oTO4djYyekTBoPVvannynut6Csa98j9pGK+QyYOMTE9AtMsjfzSKiDkaSJMx6axf2nqsEALx62wDMHMJ55q5WNruEg7mV2HiiGBt/Kkb2RXqdFHIZBiaGYEx6BEamhWFAQginxehCriQ2YCBFXZrNLuF4YTW2nynDD2fKsC+nAhZb6z8JtUKOjJ6RuGlgHH7RKxoBauY+X01e+fYk/rklCwAwa2gCXpk5wM8tIqKOand2OW5/+0cAIkvh+yczmJ1wFZEkCUcLqrH2UCG+OFx40fks0yJ1GN890hk86XmxtMtiIOUGBlJ0KbWNFmw9XYqNJ4qx+WSJSxpgE51agev6xOCmgXEYmx7BEusdXGmtCeNf2YwGiw0qhQybf5vBIhNEdEn3/GcPtp0W02z88eY+mD0qxb8NosvKLKnDusOFWHeoAOfK61u9LpcBQ5PDMLl3NCb1jkZqhM4PraSOiIGUGxhIUVtZbHbsPVuBDSeK8dXR8yi9wFWtSL0Gtw5OwO3DEvmj3EH9/vNjeO/HHADA3NEpePGmPn5uERF1dEfzqzF9yQ8AgIggDbY8lYEgpnp1OEaTFV8dOY+Ve3NxILeq1esqhQwTekRiSp8YXNsrCuFBnDeQWmMg5QYGUtQeNruEH7PLse5QIb4+dh61F+ipGpEahl8NT8T1fWMdExqTv50sqsG0f2yHXRJlarc8lYEovdbfzSKiq8BDH+zH10dFIaIHM7rh6am9/NwiAkTq3uH8aqzck4svDhfC6JhgvYlMJiow3jQgDlP7xiAkUO2nltLVgoGUGxhI0ZUyWW3YeqoUaw4WYOOJYlh/VvXHoFVi1tBEzBmdgsQwppD5iyRJuPvfu7EjsxwA8NSUnlg4Md3PrSKiq0VueT0m/W0rzDY71Ao5Nj4xHsnhzDzwl0aLDWsPFWD5jnM4WVTb6vVeMXrMHJKA6QPiEG3gBTNqOwZSbmAgRZ5UVmfCZwfysXJvXqtqQHIZMOmaaMwbk4qRaWEsm+pjG44X4dfv7QcgBox/98QE9hQSkVtaFqqZ0icab80e6ucWdT3nqxvw3q4cfLQnF5X1rlV2dWoFbhoYj18NS0T/hGAeZ6ldGEi5gYEUeYMkSdiXU4mP9uTiyyPnYbbaXV7vFaPHvWNScfOgOM527gMmqw3X/X0bchwDjpfdNRjXc2JNInJTncmKia9ucY6R/fC+Ea0mgyfvOJRXhX9tz8a3x4pazfc0MDEEd45Iwg39YlmmnK4YAyk3MJAibyuvM+GjPbl478ccFNe4FqiIMWhx37hU3DE8iT/+XvSP787g79+dBgCMTAvDR/eP5JVKImqX1fvz8dtVhwEA3SJ1+PrRcbwg5iWSJGH7mTIs25KFXdnlLq+pFDLc0C8Wc8ekYmBiiH8aSJ0SAyk3MJAiX7HY7PjmWBFW7DjbqppQcIAKc0anYO7oFITpOBDWk84U12La4u2w2CQo5DJ8+chYXBPLv3Uiah+7XcIty3biUF4VAOA3v+iOJyb38G+jOhmbXcK3x4qwbGsmjhXUuLwWEaTGnSOScfeIJERx7BN5AQMpNzCQIn84mFuJZVuysOFEscvyAJUCd41IwgMZ3RDBsqxXzG6XcNtbu7A/pxIAK20RkWecLKrBjYt/gNUuQaWQ4ctHxqFnjN7fzbrqWW12rD1UiCWbM3G2zHWccWqEDg9MSMOMQfHsASSvYiDlBgZS5E+ZJbVYtiUbaw8VuFT7C1ApMGd0ChaMT0Moe6ja7b+7zuF/1x4HIA7C3zw6jgUmiMgjXttwCm98nwlAjNH59MHRUMiZMtweNruEdYcLsHhT6wCqb7wBD2WkY0qfGP77kk8wkHIDAynqCAqqGvCvbdn4aE8uTC0KU+jUCtw7NhX3jU1DcKDKjy28+uRV1GPq69ucc4qs/PVIjEwL93OriKizaLTYMG3xdmeF1uemXYP7x6f5uVVXF5tdwpdHCvGPTWdaVbodmRaGhRPTMTY9gmNayacYSLmBgRR1JCU1jfjnlix8uDsXZltzQKXXKnHf2DTcOzYFei0Dqsux2OyY9dYuHHSMRbtjeCJevqW/fxtFRJ3O3nMVuO3NXQBE8YM1D41B3/hgP7eq45MkCRtOFOPV9adwpqTO5bWRaWF4fFIPjOCFL/ITBlJuYCBFHdH56gYs+T4Tn+zLg8XW/CcZEqjC/ePSMG9MCgLVrPJ3Ma+uP4Ulm0XKTVJYIL76zVgGoETkFX/++ie8vS0bAJAWocMXj4xlFdZL2J1djr9+e7JV0aXhqSKAGtWNART5FwMpNzCQoo4sr6IeS77PxOoD+S7zZkQEafCbX6TjV8OSoFbK/djCjmdnVhnuemc3JAlQymVY/eBolsYlIq8xW+24ddlOHC2oBgDMGpqAV2YO8HOrOp4ThTV4Zf1JbDlV6rJ8SHIonpwsAiim8FFHwEDKDQyk6GpwrsyIxd+fwecHC9ByHsLEsAA8ObknbhoQBzkH4aK4phE3LfnBOV/X/0ztiYcy0v3cKiLq7M6WGXHD4u2od4zJfO22Abh1SIKfW9Ux5FXU47UNp7D2cCFanmH2iA7CU1N6YdI1UQygqENhIOUGBlJ0NcksqcVrG07jm2NFLst7xejx1JSeuLZX1z0gNVpsuP3tH3HYMbfL6G7heH/+CAaYROQTLSfqVSvkWLlgJAYnhfq5Vf5TVmfCku8z8cHuHJcU9bhgLR6f3AO3DE5gFT7qkBhIuYGBFF2NDudVYdH6U/ghs8xl+ZDkUPzPlJ5dbpCuJEl44pPDWHOwAAAQHxKAtQ+P4VxcRORTz39+FO//mAsAiNRrsO7hMYgNDvBzq3yrttGCf20/i3e2Zzt76AAgNFCFhRPTcffIZE5DQR0aAyk3MJCiq9mOzDK88u1JHM6vdlme0TMST03piT5xXaN61NLNmVi0/hQAMQfX6gdHdZnPTkQdh8Vmx+x/78aP2RUAgH7xwfjo1yMR1AWKT5isNnzwYy6Wbs5EudHsXB6gUuC+cam4f3waDCz6Q1cBBlJuYCBFVztJkrD+eDFe3XAKmT8rIzt9QByenNwDKRE6P7XO+z7YnYPn1hxzPl9212Bc3y/Wjy0ioq6swmjGzUt/QF5FAwBgVFo4ls8b1ml7YWx2CZ8dyMfr351BQVWDc7lSLsOdI5Lw8LXpiNJr/dhCIvcwkHIDAynqLC51MJs1LBGP/qI7og2d62C25mA+nvjksHMA81NTemLhRBaXICL/Ol1ci9ve3IXqBgsA4Be9ovDm7CFQKTpPldWufhGPOi8GUm5gIEWdTVN6xZLNmahokV6hUcoxd0wKHpzQDSGBaj+20DO+PFKIR1cecpaFXzAhDc9M7dVli20QUcdyMLcSd7+zG0bHOKFp/WLw99sHQqO8+numdmaW4a/rTzmL+zSZ2DMSv+1CaeXUOTGQcgMDKeqs6kxW/Hv7WfxrezbqTFbncr1WiQcmdLuqJ/V9d+c5vPjFcWdP1OyRyfi/m/swiCKiDmVXVjnmLt8Dk9UOABiTHo437x5y1U4QfiivCq9tOIXtZ1joiDovBlJuYCBFnV2F0Yx/bs7Ef3/MgdlxMAeuzkl9JUnCqxtOYenmLOey24cm4uVb+rHMORF1SFtOleCB9/ej0SJ+f/vEGbB83rCratzQ3nMVWLzpTKsAqme0mHrjF5wLijoRBlJuYCBFXUVhVQP+8d0ZrNqf5zKpb1ywFvPHpeFXwxKh68CVparrLfjt6sPYeKLYuWzhxG747XU9eQAnog5tf04l5r+7F1X1YsxUjEGLN+4chGEpYX5u2cVJkoSdWeVYvOkMdp+tcHktITQAT17XAzcNiOdcUNTpMJByAwMp6moyS+rwt42n8PVR10l9DVolZo9KxpzRKR3uSumR/Co89MEB5FeKIhoyGfDCjb0xd0yqn1tGRNQ2mSW1uOffe1BY3QgAUMhl+J8pPXH/uLQO1aNusdmx8UQx3tmejQO5VS6vJYYF4KGMdNw6OOGqyWQgchcDKTcwkKKu6kh+FV7/7gy+P1nislytkOOWwfGYOyYFvWL8+zfRYLZh8fdn8K9t2bA6utFCAlX426wBuLZXtF/bRkTkrpLaRvzmo4POeaYAYHhqGF6a0Rfdo/V+bBlQVmfCyj25eP/HXBTVNLq8lhahw0MT03HzwLhOVXmQ6EIYSLmBgRR1daeLa/H2tmysPVQAi831z39ocijuHJGE6/vGIkDtu0pTTWV1//TVCWcvFAAMTgrBG3cORnxIgM/aQkTkSVabHf/YdAZLNmc6C+Yo5TLcPz4ND0zohuAA3xWikCQJh/Kq8N6POfjy8HmYbXaX13tG67Hw2nTc0C+WKXzUZTCQcgMDKSKhqLoRy3ecxYe7c1HbosofAOjUCkztG4sZg+IwMi3ca1ck7XYJ3x4vwhvfZ+Kn8zXO5WqFHA9mdMPD16bzaigRdQo7MsvwuzVHkVNe71ym1ygxd0wK7h2TilCd96apyC6tw5dHzuPzgwXILjO6vCaTAZOuicacUSkYkx7OMajU5TCQcgMDKSJXNY0WrDlQgA925+B0cV2r1w1aJSb2isK1vaIwKi0cUR6Y5DertA6fHcjHmgMFzvEDTcakh+OPN/dFWmTQFe+HiKgjabTY8M/NmVi2NcslI0CjlGNy72jcOjgB47pHQHmFF5AaLTYczK3CtjOl2HiiuNUEugAQHKDCr4Yl4u6RyUgMC7yi/RFdzRhIuYGBFNGFSZKEfTmVWL0vH18fPd+ql6pJt0gdBiWFonesAdfEGpAUHohoveaiB/6aRgvOlRlxprgOe85WYFd2OXIr6lutNyAhGI9c251ldYmo08str8c/t2Ri9f5853jQJkEaJYanhmFUWjh6xxmQGqFDjEF7wQIVkiShqt6CgqoGnC6uxYnCGhwtqMbBvCqX6S+ayGTAyNRw/HJwPKb3j/NpCjdRR8VAyg0MpIgur9Fiw6afSrD+eBE2nyy5aFDVRC4DwoM0CFApoFWJgKqu0YpakxW1jRd/r0Iuw7juEZg3JhXju0cwgCKiLqWgqgHvbM/G2kOFqDCaL7qeWilHcIAKeo0SaqUcJqsdJosNFfVm53xVFyOTAUOSQjG5dzSmD4hDHMecErlgIOUGBlJE7jFb7dh7rgI7s8qwK6scR/KrW11BdYdaIcegpBBM7h2NmwbGdbjS60REvma22rH1dCm+OFyInVllKKu7eFDVFolhARiVFo6RaeEY3yMSEUEaD7WUqPNhIOUGBlJEV6bRYnOmkJwqrkVhVQPOVzeitNaERosNJqsdkgQEaZXQa5SICNIgLVKHtEgd+sQFY0hyKLQqppMQEV2IJEnILKnDvpxKZJfWIbvUiPzKBtSZrKhptMBstUOjlEOrUsAQoEJssBbxIQFIDtehT5xIuY7UM3AiaqsriQ2UXmoTEXVSWpUC/RNC0D8hxN9NISLqdGQyGbpH6/0+zxQRXR7rChMREREREbmJgRQREREREZGbGEgRERERERG5iYEUERERERGRmxhIERERERERuYmBFBERERERkZsYSBEREREREbmJgRQREREREZGbGEgRERERERG5iYEUERERERGRmxhIERERERERuYmBFBERERERkZsYSBEREREREbmJgRQREREREZGbGEgRERERERG5iYEUERERERGRmxhIERERERERuYmBFBERERERkZsYSBEREREREbmJgRQREREREZGbGEgRERERERG5iYEUERERERGRmxhIERERERERuYmBFBERERERkZsYSBEREREREblJ6e8G+JokSQCAmpoaP7eEiIiIiIj8qSkmaIoR3NHlAqny8nIAQGJiop9bQkREREREHUF5eTmCg4Pdek+XC6TCwsIAALm5uW7/Y1HnUFNTg8TEROTl5cFgMPi7OeQn/B4QvwPE7wDxO0DV1dVISkpyxgju6HKBlFwuhoUFBwfzD6aLMxgM/A4QvwfE7wDxO0D8DpAzRnDrPV5oBxERERERUafGQIqIiIiIiMhNXS6Q0mg0eOGFF6DRaPzdFPITfgcI4PeA+B0gfgeI3wG6su+ATGpPrT8iIiIiIqIurMv1SBEREREREV0pBlJERERERERuYiBFRERERETkJgZSREREREREburygdRNN92EpKQkaLVaxMbGYvbs2SgsLPR3s8hHzp07h/nz5yM1NRUBAQHo1q0bXnjhBZjNZn83jXzopZdewujRoxEYGIiQkBB/N4d8YOnSpUhJSYFWq8WIESOwZ88efzeJfGjbtm2YPn064uLiIJPJ8Pnnn/u7SeRjL7/8MoYNGwa9Xo+oqCjMmDEDp06d8nezyIeWLVuG/v37OydjHjVqFL755hu3ttHlA6mJEyfik08+walTp/Dpp58iKysLM2fO9HezyEdOnjwJu92Ot956C8ePH8ff//53vPnmm/jd737n76aRD5nNZtx222148MEH/d0U8oGPP/4YTzzxBF544QUcOHAAAwYMwJQpU1BSUuLvppGPGI1GDBgwAEuXLvV3U8hPtm7dioULF+LHH3/Exo0bYbFYcN1118FoNPq7aeQjCQkJ+Mtf/oL9+/dj3759uPbaa3HzzTfj+PHjbd4Gy5//zLp16zBjxgyYTCaoVCp/N4f8YNGiRVi2bBmys7P93RTysRUrVuCxxx5DVVWVv5tCXjRixAgMGzYMS5YsAQDY7XYkJibikUcewTPPPOPn1pGvyWQyrFmzBjNmzPB3U8iPSktLERUVha1bt2L8+PH+bg75SVhYGBYtWoT58+e3af0u3yPVUkVFBT744AOMHj2aQVQXVl1djbCwMH83g4i8wGw2Y//+/Zg0aZJzmVwux6RJk7Br1y4/toyI/Km6uhoAePzvomw2G1auXAmj0YhRo0a1+X0MpAA8/fTT0Ol0CA8PR25uLtauXevvJpGfZGZm4o033sCCBQv83RQi8oKysjLYbDZER0e7LI+OjkZRUZGfWkVE/mS32/HYY49hzJgx6Nu3r7+bQz509OhRBAUFQaPR4IEHHsCaNWvQu3fvNr+/UwZSzzzzDGQy2SVvJ0+edK7/1FNP4eDBg9iwYQMUCgXuueceMOPx6ubudwAACgoKMHXqVNx22224//77/dRy8pT2fAeIiKjrWbhwIY4dO4aVK1f6uynkYz179sShQ4ewe/duPPjgg5gzZw5OnDjR5vd3yjFSpaWlKC8vv+Q6aWlpUKvVrZbn5+cjMTERO3fudKtrjzoWd78DhYWFyMjIwMiRI7FixQrI5Z3yGkOX0p7fAY6R6vzMZjMCAwOxevVqlzExc+bMQVVVFTMSuiCOkeraHn74Yaxduxbbtm1Damqqv5tDfjZp0iR069YNb731VpvWV3q5PX4RGRmJyMjIdr3XbrcDAEwmkyebRD7mznegoKAAEydOxJAhQ7B8+XIGUZ3ElfwOUOelVqsxZMgQbNq0yXnibLfbsWnTJjz88MP+bRwR+YwkSXjkkUewZs0abNmyhUEUARDHA3digE4ZSLXV7t27sXfvXowdOxahoaHIysrC73//e3Tr1o29UV1EQUEBMjIykJycjFdffRWlpaXO12JiYvzYMvKl3NxcVFRUIDc3FzabDYcOHQIApKenIygoyL+NI4974oknMGfOHAwdOhTDhw/H66+/DqPRiHnz5vm7aeQjdXV1yMzMdD4/e/YsDh06hLCwMCQlJfmxZeQrCxcuxIcffoi1a9dCr9c7x0gGBwcjICDAz60jX3j22Wdx/fXXIykpCbW1tfjwww+xZcsWrF+/vs3b6JSpfW119OhRPProozh8+DCMRiNiY2MxdepUPP/884iPj/d388gHVqxYcdGTpy78p9HlzJ07F++++26r5Zs3b0ZGRobvG0Ret2TJEixatAhFRUUYOHAgFi9ejBEjRvi7WeQjW7ZswcSJE1stnzNnDlasWOH7BpHPyWSyCy5fvnw55s6d69vGkF/Mnz8fmzZtwvnz5xEcHIz+/fvj6aefxuTJk9u8jS4dSBEREREREbUHB4MQERERERG5iYEUERERERGRmxhIERERERERuYmBFBERERERkZsYSBEREREREbmJgRQREREREZGbGEgRERERERG5iYEUERGRGzIyMiCTySCTyXDo0CGPbvvcuXPObQ8cONCj2yYiIs9iIEVERF4zd+5cZ2DQ8jZ16lR/N+2K3H///Th//jz69u3bpvWnT59+0c+8fft2yGQyHDlyBImJiTh//jyefPJJTzaXiIi8QOnvBhARUec2depULF++3GWZRqPx6j7NZjPUarXXth8YGIiYmJg2rz9//nzceuutyM/PR0JCgstry5cvx9ChQ9G/f38AQExMDIKCgjzaXiIi8jz2SBERkVdpNBrExMS43EJDQ52vy2QyvPPOO/jlL3+JwMBAdO/eHevWrXPZxrFjx3D99dcjKCgI0dHRmD17NsrKypyvZ2Rk4OGHH8Zjjz2GiIgITJkyBQCwbt06dO/eHVqtFhMnTsS7774LmUyGqqoqGI1GGAwGrF692mVfn3/+OXQ6HWpra936nJdq44033ojIyEisWLHC5T11dXVYtWoV5s+f79a+iIjI/xhIERGR3/3hD3/ArFmzcOTIEUybNg133XUXKioqAABVVVW49tprMWjQIOzbtw/ffvstiouLMWvWLJdtvPvuu1Cr1dixYwfefPNNnD17FjNnzsSMGTNw+PBhLFiwAM8995xzfZ1Oh1/96letesuWL1+OmTNnQq/Xt7n9l2ujUqnEPffcgxUrVkCSJOf7Vq1aBZvNhjvuuMPtfzMiIvIziYiIyEvmzJkjKRQKSafTudxeeukl5zoApOeff975vK6uTgIgffPNN5IkSdIf//hH6brrrnPZbl5engRAOnXqlCRJkjRhwgRp0KBBLus8/fTTUt++fV2WPffccxIAqbKyUpIkSdq9e7ekUCikwsJCSZIkqbi4WFIqldKWLVsu+pkmTJggPfrooy7L2tLGn376SQIgbd682bnOuHHjpLvvvrvVPl544QVpwIABF20DERH5H8dIERGRV02cOBHLli1zWRYWFubyvGl8ECB6igwGA0pKSgAAhw8fxubNmy84bigrKws9evQAAAwZMsTltVOnTmHYsGEuy4YPH97qeZ8+ffDuu+/imWeewfvvv4/k5GSMHz/erc/Yljb26tULo0ePxn/+8x9kZGQgMzMT27dvx//93/+5tS8iIuoYGEgREZFX6XQ6pKenX3IdlUrl8lwmk8FutwMQ44imT5+Ov/71r63eFxsb67Kf9rjvvvuwdOlSPPPMM1i+fDnmzZsHmUzm1jba2sb58+fjkUcewdKlS7F8+XJ069YNEyZMaFe7iYjIvzhGioiIOrTBgwfj+PHjSElJQXp6usvtUsFTz549sW/fPpdle/fubbXe3XffjZycHCxevBgnTpzAnDlzvNbGWbNmQS6X48MPP8R///tf3HvvvW4HbURE1DEwkCIiIq8ymUwoKipyubWsuHc5CxcuREVFBe644w7s3bsXWVlZWL9+PebNmwebzXbR9y1YsAAnT57E008/jdOnT+OTTz5xVs1rGbyEhobilltuwVNPPYXrrruuVXlyT7YxKCgIt99+O5599lmcP38ec+fOdXtfRETUMTCQIiIir/r2228RGxvrchs7dmyb3x8XF4cdO3bAZrPhuuuuQ79+/fDYY48hJCQEcvnFD2OpqalYvXo1PvvsM/Tv3x/Lli1zVu37+TxW8+fPh9lsxr333tuuz+hOG+fPn4/KykpMmTIFcXFx7dofERH5n0ySWtRhJSIi6sReeuklvPnmm8jLy3NZ/t577+Hxxx9HYWHhZSfyzcjIwMCBA/H66697rZ0vvvgiPv/8cxw6dMhr+yAioivDHikiIuq0/vnPf2Lv3r3Izs7Ge++9h0WLFrmMgaqvr0dWVhb+8pe/YMGCBZcNolpuNygoCEePHvVoe3NzcxEUFIQ///nPHt0uERF5HnukiIio03r88cfx8ccfo6KiAklJSZg9ezaeffZZKJWiaO2LL76Il156CePHj8fatWsvWL785woKCtDQ0AAASEpKanPw1RZWqxXnzp0DINIPExMTPbZtIiLyLAZSREREREREbmJqHxERERERkZsYSBEREREREbmJgRQREREREZGbGEgRERERERG5iYEUERERERGRmxhIERERERERuYmBFBERERERkZsYSBEREREREbmJgRQREREREZGb/h8devSEJu0Q6gAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10, 8))\n",
    "R = dict()\n",
    "res = dict()\n",
    "for instr, title in {\"expected\": \"Virtual spectrometer\",\n",
    "                     \"spec\":\"Grating spectometer\",\n",
    "                     #\"pes\": \"PES\",\n",
    "                    }.items():\n",
    "    e = pred[\"energy\"] - np.mean(pred[\"energy\"])\n",
    "    R[instr] = autocorrelation(pred[\"energy\"], pred[instr])\n",
    "    res[instr] = fwhm(e, R[instr])\n",
    "    plt.plot(e, R[instr], lw=2, label=f\"{title} (FWHM = {res[instr]:.2f} eV)\")\n",
    "\n",
    "plt.legend(frameon=False)\n",
    "plt.xlabel(\"Energy [eV]\")\n",
    "plt.ylabel(\"Autocorrelation\")\n",
    "plt.xlim((-3, 3))\n",
    "plt.ylim((None, 1.05))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d571f045-a877-42fd-9934-d9686bac4283",
   "metadata": {},
   "source": [
    "### Resolution assessment per energy\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ffd654f9-8175-45da-9ae1-09c184a7e520",
   "metadata": {},
   "source": [
    "### Resolution assessment using deconvolution\n",
    "\n",
    "Here we attempt to establish the resolution of the virtual spectrometer using a deconvolution-based method. The idea here is that the virtual spectrometer can be seen as a *linear* device that somehow *worsens* the resolution of the grating spectrometer. Within the context of linear systems theory any such device can be modelled mathematically as a block that applies a convolution between a function $g$ and the grating spectrometer data.\n",
    "\n",
    "That is, if the grating spectrometer data is $y$ and the virtual spectrometer result is $\\hat{y}$, then we assume that there is a function $g$ such that:\n",
    "\n",
    "$\\hat{y} = y \\ast g + \\epsilon$,\n",
    "\n",
    "where $\\epsilon$ is zero-mean Gaussian noise.\n",
    "\n",
    "Under such an approach, one can calculate the function $g$ exactly, by performing a deconvolution between $\\hat{y}$ and $y$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "7ed071e5-4f60-4195-830a-73ab8e5c2577",
   "metadata": {},
   "outputs": [],
   "source": [
    "def deconv(y: np.ndarray, yhat: np.ndarray) -> np.ndarray:\n",
    "    \"\"\"Given the grating spectrometer data and the virtual spectrometer data,\n",
    "    calculate the deconvolution between them.\n",
    "    \"\"\"\n",
    "    # subtract the mean spectra to remove the FEL bandwidth\n",
    "    yhat_s = yhat - np.mean(yhat, keepdims=True, axis=(0, 1))\n",
    "    y_s = y  - np.mean(y, keepdims=True, axis=(0, 1))\n",
    "    # Fourier transforms\n",
    "    Yhat = np.fft.fft(yhat_s)\n",
    "    Y = np.fft.fft(y_s)\n",
    "    # spectral power of the assumed \"true\" signal (the grating spectrometer data)\n",
    "    Syy = np.mean(np.absolute(Y)**2, axis=(0, 1))\n",
    "    Syh = np.mean(Y*np.conj(Yhat), axis=(0, 1))\n",
    "    # approximate transfer function as the ratio of power spectrum densities\n",
    "    H = Syh/Syy\n",
    "    return np.fft.fftshift(np.fft.ifft(H))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a1c5137f-fe6b-4930-aff5-90026ad5f3c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# centered energy axis\n",
    "e = pred[\"energy\"] - np.mean(pred[\"energy\"])\n",
    "# impulse response\n",
    "g = deconv(pred[\"spec\"], pred[\"expected\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "75d3ddc3-a4b6-4869-bc1c-f08320089845",
   "metadata": {},
   "outputs": [],
   "source": [
    "def fit_gaussian(x: np.ndarray, y: np.ndarray):\n",
    "    \"\"\"Fit Gaussian.\"\"\"\n",
    "    def gaussian(x, amp, cen, wid):\n",
    "        return amp * np.exp(-0.5 * (x-cen)**2 / (wid**2))\n",
    "    gmodel = lmfit.Model(gaussian)\n",
    "    result = gmodel.fit(y, x=x, cen=0.0, amp=1.0, wid=1.0)\n",
    "    return result.best_values[\"wid\"]*2.355, result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f9bbd13c-d972-4af1-a6c1-0fe12509317a",
   "metadata": {},
   "outputs": [],
   "source": [
    "width, result = fit_gaussian(e, np.absolute(g))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "26641ed6-47cd-418d-ab3c-e63c83962387",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2b5378c4e700>"
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 8))\n",
    "plt.plot(e, np.absolute(g), lw=2, label=\"Virtual spectrometer\")\n",
    "plt.plot(e, result.best_fit, lw=2, label=f\"Gaussian fit, FWHM = {width:.2f} eV\")\n",
    "plt.xlim(-3, 3)\n",
    "plt.xlabel(\"Energy [eV]\")\n",
    "plt.ylabel(\"Impulse response [a.u.]\")\n",
    "plt.legend(frameon=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00a1bdb9-b52a-4f8b-8c03-30407f486595",
   "metadata": {},
   "source": [
    "Note that this response function does *not* tell us the resolution of the virtual spectrometer. It tells us how we can smear the grating spectrometer data to transform that data into the virtual spectrometer. That is, this is how much worse we do with the virtual spectrometer, relative to the grating spectrometer.\n",
    "\n",
    "As a result, if we approximate the response functions with Gaussians and assume that the previous autocorrelation function gives us an estimate of the grating spectrometer resolution, we can guess the total resolution as:\n",
    "\n",
    "$\\sigma_{total} = \\sqrt{\\sigma_{grating}^2 + \\sigma_{VIRT}^2}$\n",
    "\n",
    "The same relation is applies for the FWHM. This relation assumes independence between the two systems and assumes we can approximate the response functions as Gaussians."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "2f466226-fbad-4f64-86d3-9b5d0685678b",
   "metadata": {},
   "outputs": [],
   "source": [
    "total_resolution = np.sqrt(width**2 + res[\"spec\"]**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "051d329e-3527-4ce1-abfe-6da441ce2e4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0442815003593549"
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_resolution"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c85f6fd-c2a5-419f-ae61-8fe77289cf7d",
   "metadata": {},
   "source": [
    "The previously obtained resolution of the virtual spectrometer using the autocorrelation method was:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e8d3b2f8-09ba-4e9f-9b54-b48867dadc89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9825132876894713"
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res[\"expected\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "efac989d-34e1-4378-abe1-b215bf58c05c",
   "metadata": {},
   "source": [
    "Notice, however, that the response function is not Gaussian and therefore, one could use the full function. to actually simulate the virtual spectrometer.\n",
    "\n",
    "Furthermore, this ignores the uncertainty effect, which could be seen as an extra noise level added on top of the virtual spectrometer."
   ]
  {
   "cell_type": "markdown",
   "id": "dd1f6722-472f-488d-a0eb-e362732fd364",
   "metadata": {},
   "source": [
    "### Validation: compare grating spectrometer and simulated virtual spectrometer\n",
    "\n",
    "To check that the resolution estimate is correct, we take an example grating spectrometer pulse and smear it by the impulse response function $g$ above. If it is correct, we should get a similar result as the virtual spectrometer itself.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "36e25952-b295-43d1-bffc-d62dc1cd0a95",
   "metadata": {},
   "outputs": [],
   "source": [
    "# smearing\n",
    "sigma = width/2.355 # convert FWHM to sigma\n",
    "# create a Gaussian with the requested width\n",
    "g_simple = np.exp(-0.5 * (pred[\"energy\"] - np.mean(pred[\"energy\"]))**2/(sigma**2))\n",
    "g_simple  /= np.sum(g_simple)\n",
    "# smear the grating spectrometer data\n",
    "y_simul = scipy.signal.fftconvolve(pred[\"spec\"], g_simple*np.ones_like(pred[\"spec\"]), mode=\"same\", axes=-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "e25f2828-fb32-4747-b7ea-24752c390625",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2b53789a2ca0>"
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10, 8))\n",
    "plt.plot(pred[\"energy\"], y_simul[example_tid,0], c='b', lw=3, label=\"Smeared grating spec.\")\n",
    "plt.plot(pred[\"energy\"], pred[\"expected\"][example_tid,0], c='r', ls='--', lw=3, label=\"Virtual spectrometer\")\n",
    "plt.fill_between(pred[\"energy\"],\n",
    "                 pred[\"expected\"][example_tid, 0] - pred[\"total_unc\"][example_tid,0],\n",
    "                 pred[\"expected\"][example_tid,0] + pred[\"total_unc\"][example_tid,0],\n",
    "                 facecolor='gold', alpha=0.5, label=\"68% unc.\")\n",
    "plt.xlabel(\"Energy [eV]\")\n",
    "plt.ylabel(\"Intensity [a.u.]\")\n",
    "plt.legend(frameon=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db3ddff6-dad5-40f5-af6c-680ca2657a24",
   "metadata": {},
   "source": [
    "## Improve the resolution further: Wiener deconvolution\n",
    "\n",
    "If we know the impulse response of the virtual spectrometer, we can undo that effect. This assumes however, that the resolution function is very accurate. This may not be true, as approximations are made previously (such as assuming the same resolution for all energies and linearity).\n",
    "\n",
    "Given the limitation created by the uncertainty, this is often not very reliable.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "cb27ad10-5cb0-4f77-a6d6-8a1a41b6853f",
   "metadata": {},
   "outputs": [],
   "source": [
    "dec = model.deconvolve(pred[\"expected\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "a52d01fb-878f-4f3b-940f-c47013df24ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2b56166ab340>"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10, 8))\n",
    "plt.plot(pred[\"energy\"], pred[\"spec\"][example_tid,0], c='b', lw=3, label=\"Grating spec.\")\n",
    "plt.plot(pred[\"energy\"], dec[example_tid,0], c='r', ls='--', lw=3, label=\"Virtual spectrometer (deconvolved)\")\n",
    "plt.fill_between(pred[\"energy\"],\n",
    "                 dec[example_tid, 0] - pred[\"total_unc\"][example_tid,0],\n",
    "                 dec[example_tid,0] + pred[\"total_unc\"][example_tid,0],\n",
    "                 facecolor='gold', alpha=0.5, label=\"68% unc.\")\n",
    "plt.xlabel(\"Energy [eV]\")\n",
    "plt.ylabel(\"Intensity [a.u.]\")\n",
    "plt.legend(frameon=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "76eaa0ed-d4c5-426d-9b10-c58b14ffb059",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "pes_to_spec",
   "language": "python",
   "name": "pes_to_spec"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }