eval_nn_tres_param.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fb39d67c-145a-411e-875b-85425d96fb39",
   "metadata": {},
   "outputs": [],
   "source": [
    "from jax.config import config\n",
    "\n",
    "config.update(\"jax_enable_x64\", True)\n",
    "\n",
    "import pickle\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import scipy.optimize\n",
    "import seaborn as sns\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "from hyperion.utils import ANG_DIST_INT, cherenkov_ang_dist\n",
    "from torchinterp1d import Interp1d\n",
    "from tqdm.notebook import tqdm, trange\n",
    "\n",
    "if torch.cuda.is_available():\n",
    "    device = torch.device(\"cuda\")\n",
    "else:\n",
    "    device = torch.device(\"cpu\")\n",
    "\n",
    "torch.set_default_dtype(torch.float64)\n",
    "\n",
    "import sys\n",
    "\n",
    "sys.path.append(\"../olympus\")\n",
    "from glob import glob\n",
    "from itertools import product\n",
    "\n",
    "import awkward as ak\n",
    "import pandas as pd\n",
    "from olympus.event_generation import (\n",
    "    Constants,\n",
    "    Detector,\n",
    "    generate_cascade,\n",
    "    make_hex_grid,\n",
    "    make_line,\n",
    ")\n",
    "from olympus.event_generation.mc_record import MCRecord\n",
    "from olympus.event_generation.photon_propagation import (\n",
    "    PhotonSource,\n",
    "    dejit_sources,\n",
    "    make_generate_bin_amplitudes_nn,\n",
    "    make_generate_photons_nn,\n",
    "    source_to_model_input,\n",
    ")\n",
    "\n",
    "from olympus.event_generation.lightyield import fennel_total_light_yield\n",
    "from hyperion.models.photon_arrival_time.net import PhotonArivalTimePars\n",
    "from hyperion.models.photon_arrival_time.pdf import make_exp_exp_exp, sample_exp_exp_exp\n",
    "from jax import jit\n",
    "from jax import numpy as jnp\n",
    "from jax import value_and_grad\n",
    "from numba.typed import List\n",
    "from torch.autograd.functional import hessian, jacobian\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d66686ec-f57c-415d-aa0a-e7d4a38f312f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fbc74de9d90>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.stats import qmc\n",
    "\n",
    "sampler = qmc.Sobol(d=2, scramble=True)\n",
    "\n",
    "sample = sampler.random_base2(m=3)\n",
    "plt.scatter(sample[:, 0], sample[:, 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "12ab462a-aff2-4b9a-a27a-321e7f8e6279",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8e8eb8ca-4271-453c-aec8-5bd37553f8a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\nlc_links = {}\\nfor i in range(60):\\n  \\n    links = list(range(max(i-1, (i//20)*20), min(i+2, (i//20+1)*20)))\\n    links.remove(i)\\n    lc_links[i] = links\\n\\nheight = 1500\\nradius = 200\\n'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "\n",
    "\n",
    "\n",
    "\"\"\"\n",
    "lc_links = {}\n",
    "for i in range(60):\n",
    "  \n",
    "    links = list(range(max(i-1, (i//20)*20), min(i+2, (i//20+1)*20)))\n",
    "    links.remove(i)\n",
    "    lc_links[i] = links\n",
    "\n",
    "height = 1500\n",
    "radius = 200\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a0eae685-3ee9-4927-874b-bc78b0c4d09e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def sph_to_cart(theta, phi=0):\n",
    "    \"\"\"Transform spherical to cartesian coordinates.\"\"\"\n",
    "    x = torch.sin(theta) * torch.cos(phi)\n",
    "    y = torch.sin(theta) * torch.sin(phi)\n",
    "    z = torch.cos(theta)\n",
    "\n",
    "    out = torch.empty(3, device=device, dtype=torch.float64)\n",
    "    out[0] = x\n",
    "    out[1] = y\n",
    "    out[2] = z\n",
    "\n",
    "    return out\n",
    "\n",
    "\n",
    "def sph_to_cart_np(theta, phi=0, r=1):\n",
    "    \"\"\"Transform spherical to cartesian coordinates.\"\"\"\n",
    "    x = np.sin(theta) * np.cos(phi)\n",
    "    y = np.sin(theta) * np.sin(phi)\n",
    "    z = np.cos(theta)\n",
    "\n",
    "    return np.asarray([x, y, z])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "69e8e658-be39-42d2-9324-67fe74f62c8b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def source_to_model_input_torch(\n",
    "    module_coords, source_pos, source_dir, source_t0, c_vac, n_gr\n",
    "):\n",
    "    \"\"\"Convert photon sources an module coordinates into neural net input.\"\"\"\n",
    "\n",
    "    #source_pos = np.empty((len(sources), 3))\n",
    "    #source_amp = np.empty(len(sources))\n",
    "    #source_dir = np.empty((len(sources), 3))\n",
    "    #source_t0 = np.empty((len(sources)))\n",
    "\n",
    "    source_targ_vec = module_coords[np.newaxis, ...] - source_pos[:, np.newaxis, :]\n",
    "    dist = torch.linalg.norm(source_targ_vec, axis=-1)\n",
    "    angles = torch.arccos(torch.einsum(\"abk, ak -> ab\", source_targ_vec, source_dir) / dist)\n",
    "\n",
    "    time_geo = dist / (c_vac / n_gr) + source_t0[:, np.newaxis]\n",
    "\n",
    "    inp_pars = torch.stack(\n",
    "        [\n",
    "            torch.tensor(angles.ravel(), dtype=torch.float, device=device),\n",
    "            torch.tensor(np.log10(dist.ravel()), dtype=torch.float, device=device),\n",
    "        ],\n",
    "        dim=-1,\n",
    "    )\n",
    "    \n",
    "    \n",
    "    \n",
    "    \"\"\"\n",
    "    source_targ_vec = module_coords - source_pos\n",
    "    dist = torch.linalg.norm(source_targ_vec, dim=-1)\n",
    "    angles = torch.arccos(\n",
    "        torch.einsum(\"ak, k -> a\", source_targ_vec, source_dir) / dist\n",
    "    )\n",
    "    time_geo = dist / (c_vac / n_gr) + source_t0\n",
    "\n",
    "    inp_pars = torch.stack([angles, torch.log10(dist)], axis=1)\n",
    "    return inp_pars, time_geo\n",
    "    \"\"\"\n",
    "\n",
    "\n",
    "def expon_pdf(x, a):\n",
    "    \"\"\"Exponential PDF.\"\"\"\n",
    "    return 1 / a * torch.exp(-x[:, np.newaxis] / a)\n",
    "\n",
    "\n",
    "def expon_int(x, a):\n",
    "    \"\"\"Exponential CDF\"\"\"\n",
    "    return 1 - torch.exp(-x[:, np.newaxis] / a)\n",
    "\n",
    "\n",
    "def weight_param(w1, w2):\n",
    "    weights = torch.empty((w1.shape[0], 3), device=device)\n",
    "    weights[:, 0] = torch.sin(w1) * torch.cos(w2)\n",
    "    weights[:, 1] = torch.sin(w1) * torch.sin(w2)\n",
    "    weights[:, 2] = torch.cos(w1)\n",
    "    weights = weights ** 2\n",
    "    return weights\n",
    "\n",
    "\n",
    "def triple_exp(xs, parameters):\n",
    "\n",
    "    scales = parameters[:, 0:3] * 100\n",
    "    scales, indices = torch.sort(scales, dim=1)\n",
    "    w1 = parameters[:, 3]\n",
    "    w2 = parameters[:, 4]\n",
    "\n",
    "    weights = weight_param(w1, w2)\n",
    "\n",
    "    res = torch.log(\n",
    "        weights[:, 0] * expon_pdf(xs, scales[:, 0])\n",
    "        + weights[:, 1] * expon_pdf(xs, scales[:, 1])\n",
    "        + weights[:, 2] * expon_pdf(xs, scales[:, 2])\n",
    "    )\n",
    "\n",
    "    return res\n",
    "\n",
    "\n",
    "def triple_exp_integral(tmax, parameters):\n",
    "\n",
    "    scales = parameters[:, 0:3] * 100\n",
    "    scales, indices = torch.sort(scales, dim=1)\n",
    "    w1 = parameters[:, 3]\n",
    "    w2 = parameters[:, 4]\n",
    "    weights = weight_param(w1, w2)\n",
    "\n",
    "    res = (\n",
    "        weights[:, 0] * expon_int(tmax, scales[:, 0])\n",
    "        + weights[:, 1] * expon_int(tmax, scales[:, 1])\n",
    "        + weights[:, 2] * expon_int(tmax, scales[:, 2])\n",
    "    )\n",
    "\n",
    "    return res\n",
    "\n",
    "\n",
    "def uniform_triple_exp(xs, parameters):\n",
    "    log_usf = parameters[:, -2]\n",
    "    usf = 1 - 10 ** (-log_usf)\n",
    "\n",
    "    unif = torch.log(usf * 1 / 2)\n",
    "    texp = torch.log(1 - usf) + triple_exp(\n",
    "        xs + 2, parameters[:, :-2]\n",
    "    )  # TODO: Check +2!\n",
    "\n",
    "    out = torch.where((xs < 2)[:, np.newaxis], unif, texp)\n",
    "\n",
    "    return out\n",
    "\n",
    "def uniform_triple_exp_int(tmax, parameters):\n",
    "    log_usf = parameters[:, -2]\n",
    "    usf = 1 - 10 ** (-log_usf)\n",
    "\n",
    "    unif_int = usf * tmax / 2\n",
    "    texp_int = (1 - usf) * triple_exp_integral(\n",
    "        tmax, parameters[:, :-2]\n",
    "    )  # TODO: Check +2!\n",
    "\n",
    "    out = torch.where(tmax < 2, unif_int, texp_int + usf)\n",
    "\n",
    "    return out\n",
    "\n",
    "\n",
    "net = torch.load(\"data/arival_time_pars_net.dat\")\n",
    "net.to(\"cuda\")\n",
    "net.eval()\n",
    "\n",
    "\n",
    "def eval_dist(\n",
    "    times, amp_exp, pos, theta, phi, t0, module_ix, module_positions, mod_eff=0.3\n",
    "):\n",
    "    cdir = sph_to_cart(theta, phi)\n",
    "    model_in, tgeo = source_to_model_input_torch(\n",
    "        module_positions, pos, cdir, t0, 0.3, 1.35\n",
    "    )\n",
    "    pdf_params = net(model_in).reshape(module_positions.shape[0], 9)[:, :7]\n",
    "\n",
    "    twindow = torch.tensor(1000, device=device, dtype=torch.float64)  # TODO: Improve\n",
    "\n",
    "    nnoise = dark_noise_rate * twindow\n",
    "    amp_meas = times.shape[0]\n",
    "\n",
    "    log_nph = pdf_params[module_ix, -1]\n",
    "    surv_ratio = 10 ** log_nph / 300e7\n",
    "    n_ph_exp = amp_exp * surv_ratio * mod_eff\n",
    "\n",
    "    times = times - tgeo[module_ix]\n",
    "    tres_lh = torch.empty(times.shape, device=device)\n",
    "\n",
    "    noise_term = torch.full(times.shape, torch.log(nnoise), device=device)\n",
    "\n",
    "    trespdf_eval = torch.logsumexp(\n",
    "        torch.stack(\n",
    "            (\n",
    "                uniform_triple_exp(times, pdf_params[module_ix][np.newaxis, :])[:, 0]\n",
    "                + torch.log(n_ph_exp),\n",
    "                noise_term,\n",
    "            ),\n",
    "            dim=-1,\n",
    "        ),\n",
    "        dim=-1,\n",
    "    )\n",
    "\n",
    "    tres_lh = torch.where(times >= 0, trespdf_eval, noise_term)\n",
    "\n",
    "    return tres_lh, n_ph_exp\n",
    "\n",
    "\n",
    "def eval_likelihood(\n",
    "    net, event, amp_exp, pos, theta, phi, t0, module_positions, mod_eff=0.3\n",
    "):\n",
    "\n",
    "    cdir = sph_to_cart(theta, phi)\n",
    "    model_in, tgeo = source_to_model_input_torch(\n",
    "        module_positions, pos, cdir, t0, 2.99792458e8 * 1e-9, 1.35634\n",
    "    )\n",
    "    pdf_params = net(model_in.float()).reshape(module_positions.shape[0], 7).double()\n",
    "\n",
    "    likelihood = 0\n",
    "    for i, times in enumerate(event):\n",
    "        if len(times) == 0:\n",
    "            continue\n",
    "        times = torch.tensor(times, device=device, dtype=torch.float64) - tgeo[i]\n",
    "        twindow = torch.tensor(\n",
    "            1000, device=device, dtype=torch.float64\n",
    "        )  # TODO: Improve\n",
    "        nnoise = dark_noise_rate * twindow\n",
    "\n",
    "        log_nph = pdf_params[i, -1]\n",
    "        surv_ratio = 10 ** log_nph / 300e7\n",
    "        n_ph_exp = amp_exp * surv_ratio * mod_eff\n",
    "\n",
    "        tres_lh = torch.empty(times.shape, device=device)\n",
    "\n",
    "        noise_term = torch.full(times.shape, torch.log(nnoise), device=device)\n",
    "\n",
    "        trespdf_eval = torch.logsumexp(\n",
    "            torch.stack(\n",
    "                (\n",
    "                    uniform_triple_exp(times, pdf_params[i][np.newaxis, :])[:, 0]\n",
    "                    + torch.log(n_ph_exp),\n",
    "                    noise_term,\n",
    "                ),\n",
    "                dim=-1,\n",
    "            ),\n",
    "            dim=-1,\n",
    "        )\n",
    "\n",
    "        tres_lh = torch.where(times >= 0, trespdf_eval, noise_term)\n",
    "\n",
    "        likelihood += tres_lh.sum() - n_ph_exp\n",
    "\n",
    "    return likelihood\n",
    "\n",
    "\n",
    "interpolator = Interp1d()\n",
    "\n",
    "\n",
    "def eval_binned_likelihood(\n",
    "    net, event , energy_exp, pos, theta, phi, t0, module_positions, mod_eff=0.3\n",
    "):\n",
    "    bin_width = torch.diff(binning)[0]\n",
    "    nbins = len(binning) - 1\n",
    "    cdir = sph_to_cart(theta, phi)\n",
    "        \n",
    "    \n",
    "    model_in, tgeo = source_to_model_input_torch(\n",
    "        module_positions, pos, cdir, t0, 2.99792458e8 * 1e-9, 1.35634\n",
    "    )\n",
    "    log_pred_amps = (\n",
    "        net(model_in.float()).reshape(module_positions.shape[0], nbins).double()\n",
    "    )\n",
    "\n",
    "    amplitude, tshift = event\n",
    "    amplitudes = amplitude.detach()\n",
    "\n",
    "    tshift = tshift.squeeze()\n",
    "    # prediction is always relative to tres = t -t0 -tgeo\n",
    "    # thypo = t0 + geo\n",
    "    # histogram always starts at t0 + t_geo\n",
    "\n",
    "    # offset > 0 means tshift > tgeo, ie data start *later* than prediction\n",
    "    # hence the 0 data bin needs to be evaluated against the +offset bin of prediction\n",
    "    # or prediction has to be shifted by -offset\n",
    "    offset = torch.floor((tgeo[0] - tshift[0]) / bin_width).int()\n",
    "\n",
    "    offset = torch.clamp(offset, -200, 200)\n",
    "    print(offset)\n",
    "\n",
    "    photons_exp = fennel_total_light_yield(energy_exp, 11)\n",
    "\n",
    "    # pred_amps = 10**log_pred_amps / 300E7 * amp_exp\n",
    "    log_pred_amps_rsc = log_pred_amps + torch.log(photons_exp)\n",
    "    target_low = torch.max(\n",
    "        torch.stack([torch.tensor(0, device=device), -offset]), dim=0\n",
    "    )[0]\n",
    "    target_high = torch.min(\n",
    "        torch.tensor([log_pred_amps.shape[1], log_pred_amps.shape[1] - offset]), dim=0\n",
    "    )[0]\n",
    "\n",
    "    src_low = torch.max(torch.stack([torch.tensor(0, device=device), offset]), dim=0)[0]\n",
    "    src_high = torch.min(\n",
    "        torch.tensor([log_pred_amps.shape[1], log_pred_amps.shape[1] + offset]), dim=0\n",
    "    )[0]\n",
    "\n",
    "    offset_pred_amps = torch.full(\n",
    "        (nbins, tshift.shape[0]), dark_noise_rate * bin_width, device=device\n",
    "    )\n",
    "    offset_pred_amps[target_low:target_high, :] += log_pred_amps_rsc[\n",
    "        :, src_low:src_high\n",
    "    ].T\n",
    "\n",
    "    eval_grid = binning[:-1]  # [:, np.newaxis] + tshift\n",
    "    fractional = (tgeo[0] - tshift[0]) / bin_width - offset\n",
    "\n",
    "    interpolated = (\n",
    "        offset_pred_amps[:-1]\n",
    "        + fractional * torch.diff(offset_pred_amps, dim=0) / bin_width\n",
    "    )\n",
    "\n",
    "    interp_log_amp = interpolated.T\n",
    "    llh = -torch.exp(interp_log_amp) + amplitude[0][:, :-1] * interp_log_amp\n",
    "\n",
    "    return llh.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b133a89a-e1b6-4bf1-ad2e-23fde449987d",
   "metadata": {},
   "outputs": [],
   "source": [
    "rng = np.random.RandomState(31338)\n",
    "oms_per_line = 20\n",
    "dist_z = 50\n",
    "dark_noise_rate = 16 * 1e-5  # 1/ns\n",
    "det = make_triang(100, oms_per_line, dist_z, dark_noise_rate, rng)\n",
    "module_positions = torch.tensor(det.module_coords, dtype=torch.float64, device=device)\n",
    "\n",
    "side_len = 100\n",
    "\n",
    "theta = np.radians(30)\n",
    "phi = np.radians(10)\n",
    "event_dir = sph_to_cart_np(theta, phi)\n",
    "pos = np.asarray([50.0, side_len / (2 * np.sqrt(3)), 0])\n",
    "t0_gen = 20\n",
    "\n",
    "energy_gen = 100e3\n",
    "n_ph_gen = energy_gen * (5.3 * 250 * 1e2)\n",
    "\n",
    "\n",
    "gen_ph = make_generate_photons_nn(\n",
    "    \"../hyperion/data/arival_time_pars_net_w_arriv_pos.dat\"\n",
    ")\n",
    "\n",
    "# phsrc = PhotonSource(pos, amp_gen, 0, cdir)\n",
    "# samples = gen_ph(det.module_coords, det.module_efficiencies, [phsrc])\n",
    "\n",
    "theta_t = torch.tensor(theta, device=device, dtype=torch.float64)\n",
    "event_dir_t = torch.tensor(event_dir, device=device, dtype=torch.float64)\n",
    "phi_t = torch.tensor(phi, device=device, dtype=torch.float64)\n",
    "pos_t = torch.tensor(pos, device=device, dtype=torch.float64)\n",
    "n_ph_gen_t = torch.tensor(n_ph_gen, device=device, dtype=torch.float64)\n",
    "energy_gen_et = torch.tensor(energy_gen, device=device, dtype=torch.float64)\n",
    "t0_gen_t = torch.tensor(t0_gen, device=device, dtype=torch.float64)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "44dde87c-c59a-4645-82a9-f3e68bf95f5c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "../olympus/olympus/event_generation/photon_propagation.py:430: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
      "  return (samples, torch.tensor(time_geo, device=device))\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'\\nevent_amp_noise = event_amp + dark_noise_rate * torch.diff(binning)[0]\\n\\nbinned_net, _ = torch.load(\"../hyperion/data/arrival_hist_net_0tts.dat\")\\nbinned_net.eval()\\nllh = eval_binned_likelihood(\\n    binned_net, binning, event, energy_gen_et, pos_t, theta_t, phi_t, t0_gen_t, module_positions\\n)\\n'"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amp_gen_func = make_generate_bin_amplitudes_nn(\"../hyperion/data/arrival_hist_net_0tts.dat\")\n",
    "#binning = binning.to(device)\n",
    "#generate_cascade_amplitudes = make_generate_cascade_amplitudes(amp_gen_func)\n",
    "\n",
    "event_data = {\"t0\": t0_gen, \"theta\": theta, \"phi\": phi, \"pos\": pos, \"energy\": energy_gen, \"pid\": 11}\n",
    "\n",
    "event, record = generate_cascade(\n",
    "    det, event_data[\"pos\"], event_data[\"t0\"], event_dir, energy=event_data[\"energy\"], particle_id=event_data[\"pid\"], pprop_func=amp_gen_func)\n",
    "\n",
    "event_amp, event_tshift = event\n",
    "\n",
    "\"\"\"\n",
    "event_amp_noise = event_amp + dark_noise_rate * torch.diff(binning)[0]\n",
    "\n",
    "binned_net, _ = torch.load(\"../hyperion/data/arrival_hist_net_0tts.dat\")\n",
    "binned_net.eval()\n",
    "llh = eval_binned_likelihood(\n",
    "    binned_net, binning, event, energy_gen_et, pos_t, theta_t, phi_t, t0_gen_t, module_positions\n",
    ")\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7bdcb583-e0ab-4a3d-b349-4faae376bd89",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n"
     ]
    }
   ],
   "source": [
    "print(len(event_amp[3]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b954be5a-7763-43f7-89fc-285ed2e0aef6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.step(event_amp[30][1].detach().cpu(), np.append(event_amp[30][0].detach().cpu(), event_amp[30][0].detach().cpu()[-1]), where=\"post\")\n",
    "plt.semilogy()\n",
    "#plt.xlim(20, 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c18befc9-08b5-4f8c-ba14-1143cf667176",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor(-30254.8362, device='cuda:0')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ttt = torch.tensor(21.0, requires_grad=True, device=device)\n",
    "llh = eval_binned_likelihood(\n",
    "    binned_net, binning, event, energy_gen_et, pos_t, theta_t, phi_t, ttt, module_positions\n",
    ")\n",
    "llh.backward()\n",
    "ttt.grad\n",
    "\n",
    "ttt = torch.tensor(21.5, requires_grad=True, device=device)\n",
    "llh = eval_binned_likelihood(\n",
    "    binned_net, binning, event, energy_gen_et, pos_t, theta_t, phi_t, ttt, module_positions\n",
    ")\n",
    "llh.backward()\n",
    "ttt.grad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7fae992a-8724-49e1-8001-55158a981eea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ts = np.linspace(10, 30, 50)\n",
    "\n",
    "plt.figure()\n",
    "for t in ts:\n",
    "    plt.plot(\n",
    "        t,\n",
    "        eval_binned_likelihood(\n",
    "            binned_net,\n",
    "            binning,\n",
    "            event,\n",
    "            energy_gen_et,\n",
    "            pos_t,\n",
    "            theta_t,\n",
    "            phi_t,\n",
    "            torch.tensor(t, device=device),\n",
    "            module_positions,\n",
    "        )\n",
    "        .detach()\n",
    "        .cpu(),\n",
    "        \"ok\",\n",
    "    )\n",
    "\n",
    "es = np.logspace(4, 6, 50)\n",
    "plt.figure()\n",
    "for e in es:\n",
    "    plt.plot(\n",
    "        e,\n",
    "        eval_binned_likelihood(\n",
    "            binned_net,\n",
    "            binning,\n",
    "            event,\n",
    "            torch.tensor(e, device=device),\n",
    "            pos_t,\n",
    "            theta_t,\n",
    "            phi_t,\n",
    "            t0_gen_t,\n",
    "            module_positions,\n",
    "        )\n",
    "        .detach()\n",
    "        .cpu(),\n",
    "        \"ok\",\n",
    "    )\n",
    "    \n",
    "    plt.plot(\n",
    "        e,\n",
    "        eval_binned_likelihood(\n",
    "            binned_net,\n",
    "            binning,\n",
    "            (event_amp_noise, event_tshift),\n",
    "            torch.tensor(e, device=device),\n",
    "            pos_t,\n",
    "            theta_t,\n",
    "            phi_t,\n",
    "            t0_gen_t,\n",
    "            module_positions,\n",
    "        )\n",
    "        .detach()\n",
    "        .cpu(),\n",
    "        \"or\",\n",
    "    )\n",
    "plt.semilogx()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ee4604ba-b6ff-4fa6-91b0-c37100777d9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def dpsi(zen1, azi1, zen2, azi2):\n",
    "    v1 = sph_to_cart(zen1, azi1)\n",
    "    v2 = sph_to_cart(zen2, azi2)\n",
    "    return np.arccos(np.dot(v1, v2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0bbf05ef-bc9e-47c9-982b-69227ae84245",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'gen_ph_binned' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[0;31mNameError\u001B[0m                                 Traceback (most recent call last)",
      "\u001B[0;32m/tmp/ipykernel_209/778250191.py\u001B[0m in \u001B[0;36m<module>\u001B[0;34m\u001B[0m\n\u001B[1;32m     33\u001B[0m             \u001B[0mcdir\u001B[0m\u001B[0;34m,\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m     34\u001B[0m             \u001B[0mn_photons\u001B[0m\u001B[0;34m=\u001B[0m\u001B[0mamp_gen\u001B[0m\u001B[0;34m,\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0;32m---> 35\u001B[0;31m             \u001B[0mpprop_func\u001B[0m\u001B[0;34m=\u001B[0m\u001B[0mgen_ph_binned\u001B[0m\u001B[0;34m,\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m\u001B[1;32m     36\u001B[0m             \u001B[0mpprop_extras\u001B[0m\u001B[0;34m=\u001B[0m\u001B[0mdict\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m,\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m     37\u001B[0m             \u001B[0mseed\u001B[0m\u001B[0;34m=\u001B[0m\u001B[0mi\u001B[0m\u001B[0;34m,\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n",
      "\u001B[0;31mNameError\u001B[0m: name 'gen_ph_binned' is not defined"
     ]
    }
   ],
   "source": [
    "def make_obj_func(net, event, llh, module_positions):\n",
    "    def func(pars):\n",
    "        pars = torch.tensor(pars, device=device, dtype=torch.float, requires_grad=True)\n",
    "\n",
    "        val = -llh(\n",
    "            net,\n",
    "            event,\n",
    "            10 ** pars[0],\n",
    "            pars[1:4],\n",
    "            pars[4],\n",
    "            pars[5],\n",
    "            pars[6],\n",
    "            module_positions,\n",
    "        )\n",
    "\n",
    "        val.backward()\n",
    "        grads = pars.grad\n",
    "        return np.asarray(val.detach().cpu().numpy(), dtype=np.float64), np.asarray(\n",
    "            grads.detach().cpu().numpy(), dtype=np.float64\n",
    "        )\n",
    "\n",
    "    return func\n",
    "\n",
    "\n",
    "results = []\n",
    "all_n_photons_gen = np.logspace(8, 11, 10)\n",
    "for amp_gen in all_n_photons_gen:\n",
    "    for i in range(20):\n",
    "        event, record = generate_cascade_amplitudes(\n",
    "            det,\n",
    "            pos,\n",
    "            t0_gen,\n",
    "            cdir,\n",
    "            n_photons=amp_gen,\n",
    "            pprop_func=gen_ph_binned,\n",
    "            pprop_extras=dict(),\n",
    "            seed=i,\n",
    "        )\n",
    "\n",
    "        minfunc = make_obj_func(\n",
    "            binned_net, event, eval_binned_likelihood, module_positions\n",
    "        )\n",
    "\n",
    "        best_res = None\n",
    "        for _ in range(5):\n",
    "            noise = np.random.normal(scale=[0.2, 1, 1, 1, 0.1, 0.1, 1])\n",
    "            if phi > np.pi:\n",
    "                phi_seed = phi - 2 * np.pi\n",
    "            else:\n",
    "                phi_seed = phi\n",
    "\n",
    "            seed = (\n",
    "                np.asarray(\n",
    "                    [np.log10(amp_gen), pos[0], pos[1], pos[2], theta, phi_seed, t0_gen]\n",
    "                )\n",
    "                + noise\n",
    "            )\n",
    "\n",
    "            res = scipy.optimize.fmin_l_bfgs_b(\n",
    "                minfunc,\n",
    "                seed,\n",
    "                bounds=(\n",
    "                    (-1, None),\n",
    "                    (None, None),\n",
    "                    (None, None),\n",
    "                    (None, None),\n",
    "                    (0, np.pi),\n",
    "                    (-np.pi, np.pi),\n",
    "                    (None, None),\n",
    "                ),\n",
    "                factr=100,\n",
    "            )\n",
    "            if best_res is None or res[1] < best_res[1]:\n",
    "                best_res = res\n",
    "\n",
    "        results.append(list(best_res[0]) + [amp_gen])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e5047e99-4ce5-4d3a-b56e-c7d7bd39dc43",
   "metadata": {},
   "outputs": [],
   "source": [
    "results_df = pd.DataFrame(\n",
    "    results, columns=[\"log10(E)\", \"x\", \"y\", \"z\", \"theta\", \"phi\", \"t\", \"amp_gen\"]\n",
    ")\n",
    "results_df[\"log10(E_true)\"] = results_df[\"amp_gen\"] / (5.3 * 250 * 1e2)\n",
    "results_df[\"theta_deg\"] = np.degrees(results_df[\"theta\"])\n",
    "results_df[\"phi_deg\"] = np.degrees(results_df[\"phi\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "3d52dfc4-dc6f-46f0-9f43-07a4529b5287",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(results_df.groupby(\"log10(E_true)\").describe()[(\"theta_deg\", \"std\")])\n",
    "plt.semilogx()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "ebc9f71a-e973-412a-96a1-a31a1964b01a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(results_df.groupby(\"log10(E_true)\").describe()[(\"theta_deg\", \"mean\")])\n",
    "plt.semilogx()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "708f5472-bfab-49d2-9485-ec596557dc5b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29.999999999999996"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.degrees(theta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "307fc1bc-f36e-4adb-b3cd-5ad5b6190268",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10.122215878272826 [50.         28.86751346  0.        ] 0.5235987755982988 0.17453292519943295\n"
     ]
    }
   ],
   "source": [
    "print(np.log10(amp_gen), pos, theta, phi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "2fb5b0bf-f1e4-4f83-8111-97f75fa37487",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0005827871394104359"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scipy.stats.circstd(results_df[\"phi\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "c8ae39e5-d95a-4783-b284-8a10fc34cb9b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/seaborn/distributions.py:2619: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x7f1f6138f190>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(results_df[\"theta\"])\n",
    "plt.axvline(theta, color=\"k\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 365,
   "id": "a685901f-8785-4b99-9fe2-a2c91c606ad5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'LLH')"
      ]
     },
     "execution_count": 365,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xs = np.linspace(300, 700, 1000)\n",
    "xs_t = torch.tensor(xs, device=device, dtype=torch.float)\n",
    "pdf_val, p = eval_dist(xs_t, amp_gen_t, pos_t, theta_t, phi_t, t0_gen, 30)\n",
    "\n",
    "plt.plot(xs, pdf_val.detach().cpu())\n",
    "plt.xlabel(\"time (ns)\")\n",
    "plt.ylabel(\"LLH\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "b5079f6c-dddd-4465-8e41-afd033642734",
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_wrap(event, module_positions, lh_func, net):\n",
    "    def wrap(logamp, theta, phi, pos_x, pos_y, pos_z, t0):\n",
    "        pos = torch.stack([pos_x, pos_y, pos_z])\n",
    "        res = lh_func(net, event, 10 ** logamp, pos, theta, phi, t0, module_positions)\n",
    "        return res\n",
    "\n",
    "    return wrap\n",
    "\n",
    "\n",
    "def make_wrap_no_t(event, module_positions, lh_func, net):\n",
    "    def wrap(logamp, theta, phi, pos_x, pos_y, pos_z):\n",
    "        pos = torch.stack([pos_x, pos_y, pos_z])\n",
    "        res = lh_func(net, event, 10 ** logamp, pos, theta, phi, 0, module_positions)\n",
    "        return res\n",
    "\n",
    "    return wrap\n",
    "\n",
    "\n",
    "def unpack_hessian(hess):\n",
    "    hess_len = len(hess)\n",
    "    out = np.empty((hess_len, hess_len))\n",
    "    for i in range(len(hess)):\n",
    "        for j in range(len(hess)):\n",
    "            out[i, j] = hess[i][j].detach().cpu().numpy()\n",
    "    return out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 423,
   "id": "8c484959-f5be-4a6e-8ffc-aee42a1788ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "hessians_f = []\n",
    "for seed in range(200):\n",
    "    event, record = generate_cascade_amplitudes(\n",
    "        det,\n",
    "        pos,\n",
    "        t0_gen,\n",
    "        cdir,\n",
    "        n_photons=amp_gen,\n",
    "        pprop_func=gen_ph_binned,\n",
    "        pprop_extras=dict(),\n",
    "        seed=seed,\n",
    "    )\n",
    "    wrap = make_wrap_no_t(event, module_positions, eval_binned_likelihood, binned_net)\n",
    "    # hess = hessian(wrap, (torch.log10(amp_gen_t), theta_t, phi_t, pos_t[0], pos_t[1], pos_t[2], t0_gen_t), strict=True)\n",
    "    jac = torch.stack(\n",
    "        jacobian(\n",
    "            wrap,\n",
    "            (torch.log10(amp_gen_t), theta_t, phi_t, pos_t[0], pos_t[1], pos_t[2]),\n",
    "            strict=True,\n",
    "        )\n",
    "    )\n",
    "    # hessians.append(unpack_hessian(hess))\n",
    "    hessians_f.append((jac[np.newaxis, :] * jac[:, np.newaxis]).detach().cpu().numpy())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 424,
   "id": "8e415d78-3ffb-42a3-9a19-2068d605c105",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.00640608, 0.0417094 , 0.04962471, 0.61193063, 0.58673644,\n",
       "       0.07276148])"
      ]
     },
     "execution_count": 424,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hess_mf = np.average(hessians_f, axis=0)\n",
    "np.sqrt(np.diag(np.linalg.inv(hess_mf)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8ba1d74a-8299-4abf-8e69-f07109ba5335",
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_llh_func_builder(lh_func, net, binning):\n",
    "    def make_llh_func(event, module_positions):\n",
    "        def llh_func(log10nergy, theta, phi, pos_x, pos_y, pos_z, t0):\n",
    "            pos = torch.stack([pos_x, pos_y, pos_z])\n",
    "            res = lh_func(\n",
    "                net, binning, event, 10 ** log10nergy, pos, theta, phi, t0, module_positions\n",
    "            )\n",
    "            return res\n",
    "\n",
    "        return llh_func\n",
    "\n",
    "    return make_llh_func\n",
    "\n",
    "\n",
    "def calc_fisher_information(n_events, det, event_params, gen_func, llh_func_builder):\n",
    "\n",
    "    fishers = []\n",
    "    for seed in range(n_events):\n",
    "\n",
    "        event_dir = sph_to_cart_np(event_params[\"theta\"], event_params[\"phi\"])\n",
    "        event, record = gen_func(\n",
    "            det,\n",
    "            event_params[\"pos\"],\n",
    "            event_params[\"t0\"],\n",
    "            event_dir,\n",
    "            energy=event_params[\"energy\"],\n",
    "            seed=seed,\n",
    "        )\n",
    "\n",
    "        module_positions = torch.tensor(\n",
    "            det.module_coords, dtype=torch.float, device=device\n",
    "        )\n",
    "\n",
    "        llh_func = llh_func_builder(event, module_positions)\n",
    "        # wrap = make_wrap(event, module_positions, eval_likelihood, net)\n",
    "        # hess = hessian(wrap, (torch.log10(amp_gen_t), theta_t, phi_t, pos_t[0], pos_t[1], pos_t[2], t0_gen_t), strict=True)\n",
    "        jac = torch.stack(\n",
    "            jacobian(\n",
    "                llh_func,\n",
    "                (\n",
    "                    torch.log10(torch.tensor(event_params[\"energy\"], device=device)),\n",
    "                    torch.tensor(event_params[\"theta\"], device=device),\n",
    "                    torch.tensor(event_params[\"phi\"], device=device),\n",
    "                    torch.tensor(event_params[\"pos\"][0], device=device),\n",
    "                    torch.tensor(event_params[\"pos\"][1], device=device),\n",
    "                    torch.tensor(event_params[\"pos\"][2], device=device),\n",
    "                    torch.tensor(event_params[\"t0\"], device=device),\n",
    "                ),\n",
    "                strict=True,\n",
    "            )\n",
    "        ).detach()\n",
    "\n",
    "        fishers.append((jac[np.newaxis, :] * jac[:, np.newaxis]).cpu().numpy())\n",
    "        torch.cuda.empty_cache()\n",
    "    return np.average(fishers, axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ac720dd2-07da-412e-8c8f-f41756af8312",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f21719ead90>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX8AAAD4CAYAAAAEhuazAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8/fFQqAAAACXBIWXMAAAsTAAALEwEAmpwYAAAN8ElEQVR4nO3dz2sd97nH8c/n2iSLUmiCVcfXNlem6C4sTE0ZTBddtDTUvxZKCg3O4tb4BtRF8gcodJFCCZjS0t6WNOBe7LqL1vUmRNSmbeJNViU+ghBbaUNFomALJ1Z/UAqFFKdPF2ccjaRzZMnSzBzpeb9g0Jln5mieM3POx6M533PsiBAAIJf/aLsBAEDzCH8ASIjwB4CECH8ASIjwB4CEtrfdwGrs2LEjhoeH224DADaVqampP0XEUK9lmyL8h4eH1el02m4DADYV2+/1W8ZlHwBIiPAHgIQIfwBIiPAHgIQIfwBIaFOM9sHWMTxxaVlt9vTxFjpBFcclH8780ZheAbNSHc3guORE+ANAQoQ/ACRE+ANAQoQ/ACRE+KMx/UaPMKqkXRyXnLwZ/g/foiiCL3YDgLWxPRURRa9lnPkDQEKEPwAkRPgDQEKEPwAkRPgDQEKEPwAkRPgDQEKEPwAkRPgDQEKEPwAkRPgDQEKEPwAkRPgDQEKEPwAkRPgDQEIbEv62z9q+bft6pfaw7Vds/7H8+VBZt+0f2p6x/abtz21EDwCA1duoM/+fSjqypDYh6UpEjEi6Us5L0lFJI+U0LunFDeoBALBKGxL+EfGapL8sKY9JOl/ePi/psUr9Z9H1O0mfsr1rI/oAAKxOndf8d0bErfL2+5J2lrd3S7pRWe9mWVvE9rjtju3O/Px8jW0CQD6NvOEb3f8oeE3/WXBEnImIIiKKoaGhmjoDgJzqDP8P7l7OKX/eLutzkvZW1ttT1gAADakz/CclnSxvn5T0cqX+9XLUz+cl/a1yeQgA0IDtG/FLbP9C0hcl7bB9U9Jzkk5Lumj7KUnvSXqiXP2ypGOSZiT9Q9KpjegBALB6GxL+EfFkn0Vf7rFuSHp6I7YLALg/fMIXABIi/AEgIcIfABIi/AEgIcIfABIi/AEgIcIfABIi/AEgIcIfABIi/AEgIcIfABIi/AEgIcIfABIi/AEgIcIfABIi/AEgIcIfABIi/AEgoQ35bxxRr+GJS8tqs6ePt9AJqg6cG5XshUKErp2abq8h8FpZA878B1yvJ/NKdTTj4+BfMh04N9p2a2nxWlkbzvyB+3E38JfWgE2CM38ASIjwB4CECH/gfkR0p3vVgAFF+A+4fiMVGMHQrmunphfCvjIx2qc9vFbWxrEJzlSKoohOp9N2GwCwqdieioii1zLO/AEgIcIfABIi/AEgodo/5GV7VtLfJX0k6U5EFLYflvRLScOSZiU9ERF/rbsXAEBXU2f+X4qIg5U3HiYkXYmIEUlXynkAQEPauuwzJul8efu8pMda6gMAUmoi/EPSb21P2R4vazsj4lZ5+31JO5feyfa47Y7tzvz8fANtAkAeTXyx2xciYs72pyW9YvsP1YUREbaXfdggIs5IOiN1x/k30CcApFH7mX9EzJU/b0t6SdIhSR/Y3iVJ5c/bdfcBAFhQa/jb/oTtT969Lekrkq5LmpR0slztpKSX6+wDALBY3Zd9dkp6yd3vOd8u6ecR8WvbVyVdtP2UpPckPVFzHwCAilrDPyLekfTZHvU/S/pyndsGAPTHJ3wBICHCHwASIvwBICHCHwASIvwBICHCHwASIvwBICHCHwASIvwBICHCHwASIvwBICHCHwASIvwBICHCHwASIvwBICHCHwASIvwBICHCHwASIvwBICHCHwASIvwBICHCHwASIvwBICHCHwASIvwBICHCHwASIvwBICHCHwASIvwBIKHtbW3Y9hFJ/ydpm6T/j4jTG72N4YlLy2qzp49v9GawBgfOjUr2QiFC105Nt9cQJHFcBlHd+dXKmb/tbZJekHRU0n5JT9rev5Hb6LXjVqqjfh8HzJLpwLnRtltLjeMyeJrIr7Yu+xySNBMR70TEPyVdkDTWUi9oyt1guVcNzeK4pNRW+O+WdKMyf7Osfcz2uO2O7c78/HyjzQHAVjewb/hGxJmIKCKiGBoaarsdANhS2gr/OUl7K/N7yhq2sojudK8amsVxSamt8L8qacT2PtsPSDohaXIjN9DvXXFG+7Tn2qnphVCpTIwqaRfHZfA0kV+Olv51t31M0g/UHep5NiKe77duURTR6XSaag0AtgTbUxFR9FrW2jj/iLgs6XJb2weAzAb2DV8AQH0IfwBIiPAHgIQIfwBIiPAHgIQIfwBIiPAHgIQIfwBIiPAHgIQIfwBIiPAHgIQIfwBIiPAHgIQIfwBIiPAHgIQIfwBIiPAHgIQIfwBIiPAHgIQIfwBIiPAHgIQIfwBIiPAHgIQIfwBIiPAHgIQIfwBIiPAHgIQIfwBIiPAHgIRqC3/b37I9Z/uNcjpWWfas7Rnbb9s+XFcPAIDettf8+78fEd+tFmzvl3RC0qik/5T0qu3/joiPau4FAFBq47LPmKQLEfFhRLwraUbSoRb6AIC06g7/Z2y/afus7YfK2m5JNyrr3Cxri9get92x3Zmfn6+5TQDIZV3hb/tV29d7TGOSXpT0GUkHJd2S9L21/O6IOBMRRUQUQ0ND62kTALDEuq75R8Sjq1nP9k8k/aqcnZO0t7J4T1kDADSkztE+uyqzj0u6Xt6elHTC9oO290kakfR6XX0AAJarc7TPd2wflBSSZiV9Q5IiYtr2RUlvSboj6WlG+gBAs2oL/4j4nxWWPS/p+bq2DQBYGZ/wBYCECH8ASKjuT/hiAwxPXFpWmz19vIVOUDV67oDshfkIafrUtfYaAq+VNeDMf8D1ejKvVEcz7gb/0mn03IG2W0uL18racOYP3Ie7Yb+0BmwWnPkDQEKEPwAkRPgD9yGiO92rBgwqwn/A9RupwAiGdk2fuvZx2FcnRvu0h9fK2jg2walKURTR6XTabgMANhXbUxFR9FrGmT8AJET4A0BChD8AJET4A0BChD8AJET4A0BChD8AJET4A0BChD8AJET4A0BChD8AJET4A0BChD8AJET4A0BChD8AJET4A0BChD8AJET4A0BChD8AJLSu8Lf9NdvTtv9lu1iy7FnbM7bftn24Uj9S1mZsT6xn+wCA+7PeM//rkr4q6bVq0fZ+SSckjUo6IunHtrfZ3ibpBUlHJe2X9GS5LgCgQdvXc+eI+L0k2V66aEzShYj4UNK7tmckHSqXzUTEO+X9LpTrvrWePgAAa1PXNf/dkm5U5m+WtX71ZWyP2+7Y7szPz9fUJgDkdM8zf9uvSnqkx6JvRsTLG99SV0SckXRGkoqiiLq2AwAZ3TP8I+LR+/i9c5L2Vub3lDWtUAcANKSuyz6Tkk7YftD2Pkkjkl6XdFXSiO19th9Q903hyZp6AAD0sa43fG0/LulHkoYkXbL9RkQcjohp2xfVfSP3jqSnI+Kj8j7PSPqNpG2SzkbE9LoeAQBgzRwx+JfTi6KITqfTdhsAsKnYnoqIotcyPuELAAkR/gCQEOEPAAkR/gCQEOEPAAkR/gCQEOEPAAkR/gCQEOEPAAkR/gCQEOEPAAkR/gCQEOEPAAkR/gCQ0Lq+zx9Yq+GJS8tqs6ePt9AJqjgu+XDmj8b0CpiV6mgGxyUnwh8AEiL8ASAhwh8AEiL8ASAhwh+N6Td6hFEl7eK45OSIaLuHeyqKIjqdTtttAMCmYnsqIopeyzjzB4CECH8ASIjwB4CECH8ASIjwB4CENsVoH9vzkt5ruY0dkv7Ucg+Dgn2xGPtjAftisbb3x39FxFCvBZsi/AeB7U6/IVPZsC8WY38sYF8sNsj7g8s+AJAQ4Q8ACRH+q3em7QYGCPtiMfbHAvbFYgO7P7jmDwAJceYPAAkR/gCQEOG/hO2v2Z62/S/bxZJlz9qesf227cOV+pGyNmN7ovmum2H7W7bnbL9RTscqy3rum60sy3Ffie1Z29fK50OnrD1s+xXbfyx/PtR2n3Wxfdb2bdvXK7Wej99dPyyfL2/a/lx7nRP+vVyX9FVJr1WLtvdLOiFpVNIRST+2vc32NkkvSDoqab+kJ8t1t6rvR8TBcros9d83bTZZt4THfSVfKp8Pd0+WJiRdiYgRSVfK+a3qp+o+56v6Pf6jkkbKaVzSiw312BPhv0RE/D4i3u6xaEzShYj4MCLelTQj6VA5zUTEOxHxT0kXynUz6bdvtjKOe39jks6Xt89Leqy9VuoVEa9J+suScr/HPybpZ9H1O0mfsr2rkUZ7IPxXb7ekG5X5m2WtX32reqb8k/Vs5c/5bPtAyvmYewlJv7U9ZXu8rO2MiFvl7fcl7Wyntdb0e/wD9ZzZ3taG22T7VUmP9Fj0zYh4uel+BslK+0bdP1O/re4L/tuSvifpf5vrDgPoCxExZ/vTkl6x/YfqwogI22nHkw/y408Z/hHx6H3cbU7S3sr8nrKmFeqbzmr3je2fSPpVObvSvtmqMj7mZSJirvx52/ZL6l4O+8D2roi4VV7WuN1qk83r9/gH6jnDZZ/Vm5R0wvaDtvep+6bN65KuShqxvc/2A+q+8TnZYp+1WXJ98nF13xyX+u+brSzNce/H9idsf/LubUlfUfc5MSnpZLnaSUnZ/pru9/gnJX29HPXzeUl/q1wealzKM/+V2H5c0o8kDUm6ZPuNiDgcEdO2L0p6S9IdSU9HxEflfZ6R9BtJ2ySdjYjpltqv23dsH1T3ss+spG9I0kr7ZquKiDuJjns/OyW9ZFvqZsnPI+LXtq9Kumj7KXW/iv2JFnusle1fSPqipB22b0p6TtJp9X78lyUdU3dAxD8knWq84Qq+3gEAEuKyDwAkRPgDQEKEPwAkRPgDQEKEPwAkRPgDQEKEPwAk9G8mcf9/NGc7PQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "hex_det = Detector(\n",
    "    make_hex_grid(3, 75, 20, 50, 16 * 1e-5, rng=np.random.RandomState(0))\n",
    ")\n",
    "positions = hex_det.module_coords\n",
    "plt.scatter(positions[:, 0], positions[:, 1])\n",
    "\n",
    "triang_det = make_triang(75, 20, 50, 16 * 1e-5, rng=np.random.RandomState(0))\n",
    "positions = triang_det.module_coords\n",
    "plt.scatter(positions[:, 0], positions[:, 1])\n",
    "\n",
    "rhombus_det = make_rhombus(75, 20, 50, 16 * 1e-5, rng=np.random.RandomState(0))\n",
    "positions = rhombus_det.module_coords\n",
    "plt.scatter(positions[:, 0], positions[:, 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c85e1ed3-5d63-4c5f-bbb4-86a3c79d4ef5",
   "metadata": {},
   "outputs": [],
   "source": [
    "spacings = [75, 100, 150]\n",
    "energies = np.logspace(3, 6, 10)\n",
    "oms_per_line = 20\n",
    "dist_z = 50\n",
    "dark_noise_rate = 1E-6 * 16\n",
    "rng = np.random.RandomState(0)\n",
    "tts_grid = [0, 2, 3, 4]\n",
    "\n",
    "\n",
    "event_params = {\n",
    "    #\"pos\": np.asarray([50.0, side_len / (2 * np.sqrt(3)), 0]),\n",
    "    \"pos\": np.asarray([0, 0, 0.]),\n",
    "    \"t0\": 30.0,\n",
    "    \"energy\": 1e5,\n",
    "    \"theta\": np.radians(40),\n",
    "    \"phi\": np.radians(30),\n",
    "}\n",
    "\n",
    "fi_data = []\n",
    "\n",
    "detectors = {\"tri\": triang_det, \"hex\": hex_det, \"rhomb\": rhombus_det}\n",
    "\n",
    "\n",
    "for tts in tts_grid:\n",
    "    net_file = f\"../hyperion/data/arrival_hist_net_{tts}tts.dat\"\n",
    "    binned_net, binning = torch.load(net_file)\n",
    "    binned_net.to(device)\n",
    "    binning = binning.to(device)\n",
    "    binned_net.eval()\n",
    "    \n",
    "    llh_func_builder = make_llh_func_builder(eval_binned_likelihood, binned_net, binning)\n",
    "    amp_gen, _ = make_generate_bin_amplitudes_nn(net_file)\n",
    "   \n",
    "    generate_cascade_amplitudes = make_generate_cascade_amplitudes(amp_gen)\n",
    "\n",
    "    for spacing in spacings:\n",
    "\n",
    "        det_triang = make_triang(spacing, oms_per_line, dist_z, dark_noise_rate, rng)\n",
    "        det_hex = Detector(\n",
    "            make_hex_grid(3, spacing, oms_per_line, dist_z, dark_noise_rate, rng=rng)\n",
    "        )\n",
    "\n",
    "        det_rhomb = make_rhombus(spacing, oms_per_line, dist_z, dark_noise_rate, rng=rng)\n",
    "\n",
    "\n",
    "        for energy in energies:\n",
    "            ev_par = dict(event_params)\n",
    "            ev_par[\"energy\"] = energy\n",
    "            \n",
    "            for det_key, det in detectors.items():\n",
    "                fi = calc_fisher_information(\n",
    "                    300, det, ev_par, generate_cascade_amplitudes, llh_func_builder\n",
    "                )\n",
    "           \n",
    "                fi_data.append((spacing, energy, tts, det_key, fi))\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "37ee1f84-e150-4932-9c30-197e74a2d8c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "cr_data = []\n",
    "for (spacing, energy, tts, det_key, fi) in fi_data:\n",
    "    cr = np.sqrt(np.diag(np.linalg.inv(fi)))\n",
    "    cr_data.append([spacing, energy, tts, det_key] + list(cr))\n",
    "   \n",
    "    \n",
    "df = pd.DataFrame(cr_data, columns=[\"spacing\", \"energy_sim\", \"tts\", \"geom\", \"log10(energy/GeV)\", \"theta\", \"phi\", \"x\", \"y\", \"z\", \"t\"])\n",
    "df[\"theta_deg\"] = np.degrees(df[\"theta\"])\n",
    "df[\"phi_deg\"] = np.degrees(df[\"phi\"])\n",
    "df.set_index(\"energy_sim\", inplace=True)\n",
    "#df.groupby(\"spacing\")[[\"theta res tri\", \"theta res hex\"]].plot(subplots=False, legend=True, logx=True)\n",
    "#plt.semilogx()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "60260d21-6926-414d-90fe-b79496e2f72a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-0.50526238  0.57269658]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f74bc0c1a10>]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sel = df[(df[\"spacing\"] == 75) & (df[\"tts\"] == 0) & (df[\"geom\"] == \"tri\")]\n",
    "\n",
    "fitpars = np.polyfit(np.log10(sel.index), np.log10(sel[\"phi\"]), deg=1)\n",
    "print(fitpars)\n",
    "plt.plot(np.log10(sel.index), np.log10(sel[\"phi\"]))\n",
    "\n",
    "xs = np.linspace(3, 6, 100)\n",
    "plt.plot(xs, np.poly1d(fitpars)(xs))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "70568baf-bbee-410d-9888-30ba49a0ba45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.49714399,  4.66173696])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6378aa20-93b9-4dda-b330-b0f5f3dda129",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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fJzWZ9055jt6LpvyMA/x47B5arepxoChKzqtboiBnh9VlemvPp9dGB/hm9011baQoOUg1Pr2EEALrap0zekFVaEn42jHc+7Y2yQ+v07V4Rc63G46vgzOi8DV+fbif+ocrkth4L4YWzoRv7UjEnx+hTc75Cz5FyYqoqCh8fHzw8fHByckJV1dXDAwM8PHxwdPTEzs7O9zd3fHx8aFRo0ZotVoGDx6Ml5cX5cuXp0qVKgQEBLz0HDNnzsTT0xNvb2/8/Py4f/9+Dn07xdBAw5A6xfEf1YBmpR0Zu+MaFWceZO8t1TNT0T8qj7JHTkw4/jIajaB/rWJcHlmf6kVsGbDhMo1+Oq56HCh6S2VR9tBlQ/g/GRloGF6vBNdHN6RtOSfG/3mDyrPUYi2K/smzWSSlzHM/lStXlm+bVquVMcdXyev9C0r/j0xkxPapUpueJlPS0+RnZ3ZIg8UjpNFPX0jT8avkkuO3ZNTRL+Xd2Sby/i8lZHLEpbdej5I3+Pv767oEKaWU48ePl9OmTXtmW8+ePeW6dev+er1y5UrZoUMHmZ6eLqWUMjAwUEZHR7/0c/ft2ycTEhKklFL+8MMPslOnTi/c70W/B+CM1IM8+S8/2ZFFb2rr1VBZYtIeKUZskZ2WnpYPHj3RdUmKHtGXLJJS5VF2/OhDFmm1WvnLifvS+rMd0nzMNjnz4G2Zlq7VdVmKnlFZ9DeVRdlvy5UQWXjCLqkZuUUO2nhZxiWm6rokRU+oLPrb28wi1fMpi4QQWFfvktELyrsF4WtGc29ibbSht5hYuTm7m32CvaUBqUXO8eG+3Qy91xabd/aBNo2QtQ1JDDyo66+gKP9JSEgIzs7OaDQZseHm5oatre1Lj2nQoAHm5uYAVK9enaCg/LEqpL484funVp6FuDKyPl81Kc1W/zDKfrefKftuqe7mSq6k8ij3EULwUbUiXBlZHz8PB0Zs8afO/KP4hz7WdWmK8sZUFuVurcs5cWVUffrVKMb8owF4Td/Pdv8wXZelKK8tt2SRanx6TYbWhXAb9Duun6wkJfQmd7/0IXLHNOoXcufSOyNpWaQMwvkOKyJ3Um1NHHENdmBQwJnQTS2Jv7lO1+Uryhvr1KkTW7duxcfHhxEjRnD+/Pm/3uvduzdnzpx56fGLFi2iefPm2V2mXpA6HuqSGVMjA75sUoqroxrQpLQD43Zcx3vGAXbdCNd1aYryWlQe5V5uNmZs/rAKy7tV5FZEPJVmHWLinpukpquGcCX3UVmU+1mZGjGvfXkOD6hFAWNDWi8+RfcV5wh/nKzr0hQly3JLFhlm+xnyICEE1jW6YlG2ASFL+xG+ZjSPz27EpfcSNvl9wI/XjzH85BYC0g7hu7IsC/2W0yh4MBE7epCeEIp1xUG6/gqKHoo6MIKUiItv9TONHSpQsP6Mt/JZbm5u3Lhxg3379rFv3z78/PxYt24dfn5+/PLLLy89dvny5Zw5c4aDB1UPQH3gXtCcDb2qsPN6OIM3XaHZzydpX96JmW3KUcTWXNflKTqm71kEKo9yOyEE3Sq50aikA4M3XeHLnTfYcCmERZ19qOiqX432iu6oLFJyUs1idpwbXpcp+24zae8t/rwRzozW5Xjf1w0hhK7LU3RIZdHbk6d6PuX0UBdDGyfcBm/A9ZMVJIdc5+4XPkTvnEm/0tU51WYIHrY2pLpdpNfhQ4xPm4xJ8TZEHxxB9OExSKme8Cm5j4mJCc2bN2fatGmMGzeOTZs2vfKYPXv28O2337JlyxZMTEyyv0gly5qVceTyyHpMbF6GP66HU3bqfr7dc5PktHRdl6Yor6TyKPdztDRh9XuV2dDLl9DHyVT9/jDjdlwjKVVlkJJ7qCzKO0wMDRjfpDTnh9WjtEMBPlhzgaYLT3A3Si2SoOi/3JBFearnk5RyK7DV19e3T06dM6MXVDcsyjYkZOknhK0eSdyZDZTus4SzbYfy8dH1rBTnWBwRz8mQ3mwo60Ds2ZmkJYTg0PhnhIFxTpWq6Lm32fqdHc6dO4eTkxMuLi5otVouXbqEt7f3S485f/48H3/8MTt37sTR0TGHKs19pDYdoTHQyblNDA0Y51eSHpVcGbHFny923mDpmSBmty1Hi7KFdFKTolv6nkWg8iirhBCtgdYeHh66LuWl2nk5U694QUZs8WfKvttsuhLKL50qULOYna5LU3RIZZGiK55OlhweUIsFx+8zdsc1yk8/wNdNyzC0jjuGBnmq74aSBSqL3h711/OWZPSC2ohL32Ukh1zj7ucVSNwzj6W1OzGjahs0VlFcL3CMiqcaElR8FAnXVxG6qQ3a5Dhdl64oWRIeHk7r1q3x8vLC29sbQ0NDBg4cCGQ+lnjUqFHEx8fz7rvv4uPjQ5s2bXK67Fzh4cKeBP/ci7S4CJ3VUMTWnHU9ffmzb3UMBLRadIp2S04REPVEZzUpSmZUHmWNvs4/9yK25sYs7uLDH32q8SQlnTrzjzJ08xUSktN0XZqiZEplUd6l0Qj61yrGlVH1aVTSgdHb/Kk+5wjng/VnMRlF+b/ckkUiY6W8vMXX11e+alKt7JQaE0LIko+Jv7AVs5K1cBuwloOJ8XTet4zHKWmk3S/DDyUf0jT6G4ztPCn0zlYMLZx1Vq+iO9euXaNs2bK6LkPnXvR7EEKclVL66qiktyIrWSSlJHz9Z0T9MQ0DUyscO0/Fps4HCI3ung2kpGmZdeguE/fcJF0r+bShB6MbeGBmpJveWUr2U1n0t7yYR7q+Lnpdj5PSGLvjGj8cu4e7nTkL3/XGr6SDrstScoDKor+pLNIfUkrWXwph0MbLRD1JZUS9EoxvUkpdF+VhKov+9jazSPV8ygZGNs4UHroZl76/kRx4kYCvqlArOY4zbYfiaWePptgV+gdZMVlOICXmDiGr65ISfV3XZSuKogNCCAq9O4niEy5g7OpJyOLe3Jtcj6SgKzqrydhQw6cNPbg2ugFtvZz4etdNvKYdYOvVUJ3VpChK/mFpasi89uU50K8mBhpB459O0HfdRWITU3VdmqIo+ZAQgncruOA/ugHv+7oxdf9tvKcfYN+tSF2Xpii5imp8yiZCCGxqvUexz44iDI24920d7Pz3cLTlQN51r4AoFMBSjZZu0V+TlJxAyNr6JD08ruuyFUXREVO3chQbexCXjxaT8vAad7+sSNjaMWiTdTfJpZuNGat6VGbPxzUwNdTQdslpWi86yZ1INfGmoijZr26JglwcUY+R9Uuw+NQDvKYfYJt/mK7LUhQln7IzN2ZRJx/2fFwDgEY/HeejtReIfpKi48oUJXdQjU/ZzLSIN+7jT2Hq7kvwD11I2DqJFXW6MsW3JekFwrnkHEP9h5/xKL0Aob83JeHOFl2XrChKDvv/8Geh0WBT9wNKTLmOTc33iNr+HXfGlePxhe06ra9hSXsujKjHtFaeHLwbhdf0A3y58zpPUtRcLIqiZC8zIwOmtvLk+KA62JoZ0WbxKd5beY7IhGRdl6YoSj7VsKQ9l0bWZ3QDD347E4Tn1P2svfCQvDidjaK8TarxKQcYWjlSdPQebOp8QOTmCQT/2IURpaqyvUkfTM1TeVQimHoRI7ijdSd8WyfiLv2s65IVRfkPhBCthRALY2OzNinlsJObGXdmBynpGY05hpb2uPReTNGxBxHG5gTOakXg3A6kRgdlZ9kvZWSgYUT9Elwf3ZAO5Z2ZuOcW5aYdYNOVEHWxpSh5xNGwAHYH39R1GS9UpYgNZ4bW5cvGpVhz4SHlph5QN3uKouiMmZEBU1qW5dSQOrhZm9Fl+VnaLTlNUEyirktTFL2lGp9yiMbIBOePFlGoy3Qen/mde9/WoaGZBSdbD8HDxpaEondpm9SbIymVido3gEfHxqsLKkXJpV5nhSmt1JKYnsp3l/dRc9tc/GP+nlfJokxdSnxzAceOk4i/uIM7Y8sS9edsZLruehy5WJuyvHsl9vergaWJIe1/PUPLX05yMyJeZzUpivJ2TLt8gGa7FtJ+76/cfRyl63KeY2yo4aumpTkztC5FbDNu9josPUNIXJKuS1MU5S3Spj4hLe6BrsvIkoqu1pwYXJtprTzZcyuCctMO8MPRe2i16j5OUf5NNT7lICEEBZuPoPCwbaSE3Sbgqyq4RNzhWKvBtCvqRaLjfQZZtGfFk0bEnJpMxO6+yHQ1uaai5GUaoeGnWu+yoWEvAhNiqLJlNnP9D6OVWgCEoTH2rcdSYtJVzEvVIWzlMAK+rkrinVM6rbteCXvODqvLrLblOHb/Ed7TD/L1rhukq4stRdEbr9sLc02D95hUuQV7Ht7Ea+M0Pj/7B/Gp+je8zdvFiuODajOlZVn+uB5OuWkH+PV0oHpopyh5xMEDXzNudU8iL/6SK/6uDZ/2Dr88sj7VitgwcONl6v5wFP/Qx7ouTVH0imp80gHLCi1w//IEwtic+5PrkX56PesavM83lZoRbxbKLOeaTEzoQoL/UoI2vYM2RfUoUN6+qKgofHx88PHxwcnJCVdXVwwMDPDx8cHT0xM7Ozvc3d3x8fGhUaNGaLVaBg8ejJeXF+XLl6dKlSoEBAS89BwLFiygfPny+Pj4ULt2bfz9/XPo2+U+bYt6cemdkTR0LsnQk5tpvusXghP+vmE0dixO4eHbcRu4jrTYMAK+qU7IbwNIT4jRWc1GBhqG1CnO9dEN6OjtzNe7btL4p+OqF4Ly2lQeZY/X6YUJYGJgyKfeDbne4VM6FvNm8qW9eG6Yyso75/TuBtDQQMPoBh5cHFEPLydLPlxzgRa/nOR+9BNdl6bkYiqL9MNui4rMMKpMrdNH2bK+E2mPA3VdUpYUL2jBn32r82sXH66Hx1Np1iG+2X2T1HStrktTcpk8m0VSyjz3U7lyZZkbpMZFyIBJ9eTV95Gha8dKbXq63PbgqrRZ9pm0XPqZbDxpsLw100Te/LWKTEsI03W5Sjbw9/fXdQlSSinHjx8vp02b9sy2nj17ynXr1v31euXKlbJDhw4yPT1dSillYGCgjI6OfunnxsbG/vXPmzdvlk2bNn3hfi/6PQBnpB7kyX/5eZMs0mq1csG1Y7LAb2NkweWfyzV3zz+3T9qTWBmyfIi82lMjbwxykjHHV0mtVvva53rblpx6IM3HbJNOX/0p99wM13U5ymvQlyySUuVRdvxkNYtiL/woI/cPk+nJcVJKKY+GBsgqm2dJzeIRsu72efJcZFCWPienpadr5dzDd2WBsdul5bjtcu7huzItXfeZqLw+lUV/y89ZlHj/gjyw7nPp/tsoqVk8QnZa2EYGnFuoF9c6WRUWlyS7LDsjxYgtssL0A/JM4CNdl6S8BpVFf3ubWaR6PumQoaU9RUftwqZeH6K2TSZobgeaOxThROvBFC5gxQFnYzprRpIS7c+1pbVIeXRb1yUr+VhISAjOzs5oNBmx4ebmhq2t7UuPsbKy+uufExISEEJka415gRCCj8vU4Gyb4ZS0sqfrgeW8f2glsSl/T2BpYGaFU/fZuI8/haGdG8E/duXBtKakhOk2I3pVKcypIXWxMzOiycITahiekm1UHmWPtMcPiLswn6BlPjwJ2EHNQsU40XowC2u9y43YcKpsmc0nR9cTkaRfPbI1GsHA2u5cHlmfGkVtGbzpClW/P8Txe9G6Lk3J41QWZY/Y4ytw2DqRP/23MctUwyZDD3zPXWDOmh6kxuWOXlCOlias6lGZDb18iUhIpvqcI4zZfo3E1HRdl6bkQbkli16r8UkIYSGEMMiuYvIjYWiM8wc/Uaj79zw+v4WAibVwT03keKvBtHDz5IJVEu9afkrck1hu/FaLR4EndV2ykk916tSJrVu34uPjw4gRIzh//vxf7/Xu3ZszZ8688Lj58+dTokQJRo8ezZw5c3Kq3FyvlLUDh1sOZLxPE1bfvYDPphkcDL3zzD5m7pVx//IETu/NI/HuSe585kXEpglodThHSzknS04NqcN7ldz4etdNmi48Qagahqe8ZSqPsodVheEUarMDjVEBwja3I3xHD2RiJB+Vqsb19mMYUq4OS26doszv3zHX/zCpWv26iSpmZ87OPtVZ3aMy4fEp1Jp3lA9XXyD8sf7NW6XkDSqLsodjp+8oPGQTIj2VRjuncTb0LPVJYXiiM3XXjuXMmQVkdL7Qf+28nLkysj7v+7oxdf9tKs48yJEA/VvQQcndcksWGb7sTSGEBugCdAeqAMmAiRAiEtgO/CSlVN1x/iMhBAWbDMbEuQxBP3Qi4KsqFB68kQ1+PZl4YQ9fX9hFd8eBTI9YhsH6xoTVW0qZSu/oumzlLRt2cjMXo4Pf6mdWsHNlVrW2b+Wz3NzcuHHjBvv27WPfvn34+fmxbt06/Pz8+OWXXzI9bsCAAQwYMICVK1cyceJEli5d+lbqyUvSEkLQmNiiMTR9ZruhxoAvKzahqVtpeh5ahd8fCxjhVY8JlZphYpAR30JjgF2jAVhWfoewVcOJ2Die2OMrcO75IxaeDXXxdbAwMWRJFx/qlijIwA2XqTTrECu6V6KBh71O6lFej75nEag8yi6hywby5OYRnHrMJj3tOjGnp5D4YA92daZi7fkeM6q24aNSVRl2cgtDT27m5xsnmFWtHX4uJXVd+l+EEHTycaFFWUcm7rnFrEN32HglhAnNytCvRlEMDVSn/9xCZVH+JYTAslJbCng3J3rfj0Rs+poJNw7Tz6sJfS3dqH3pBv1ufciE5uOxtCmm63JfydbcmEWdfOji40rfdRep98Mx+tcsxqTmZbE0fentuKIHVBa9Pa/6P/B+oAQwFnCSUhaWUjoCtYETwHdCiB7ZWmE+UqB8E9y/OIGBuTX3v2tI3NFlfFmxCRsa9uKRSOZjh87sFOUwONiVXTtm67pcJR8yMTGhefPmTJs2jXHjxrFp06YsH9ulS5fX2j+/kFJL+JaOhKyuTUr0tRfuU82hKGfbDKNP6WpMv3KA6lu/53J0yDP7GNm64NZ/NUVG7kSmp3H/Oz+Cf3qPtLjwnPgazxFC8GHVIpwcUgcbMyMa/3Scb3bfVMPwlLdG5dHbZ9d0GAYWdgTNfZf40xco1GoHRnZliNzdm9ANzUmNuYOnjRM7m/RhQ8NeJKan0eTPn+i4byn3HuvXELcCJoZMaVmWiyPqUbWIDUM2XcF39mEO31U9DpS3S2VR9hGGxhRsMoSSU29j13gQzv572HZuDdMjLrMgwRrv3yez6ei8XNMLqnEpBy6PrM+AWu78cOwe5acfYNcN3VynKXlPbsiiVzW1NpJSpv57o5QyGvgd+F0IYZQtleVTJi5lcP/yJEHzO/Hw514kB1+lzbuTOd5qMO/sXcLY9DrcfuLEyJujWRoaQKceMzAzVi3mecHbbP3ODufOncPJyQkXFxe0Wi2XLl3C29v7pcfcunWLkiUznohv3779r39W/iaEBptq44jY3YeHK6tjV28mll4fPjfu2sLIhB9rdqRVYU96H1lL1a2zmVS5BUPK1UEj/n6OUKB8U0pMukLk1klEbv+Oxxe2UajTd9jU643Q5PwT//LOVpwaUod+v19i/J83OBIQxbKulXC0NMnxWpSs0fcsApVH2cW8RDWKf32WyD+mEbl5Agn+e3Ds9B0Wpbvw6OhnBC+vhE31L7CuNJS2Rb1o6lqaWVcPMenSHnYEXWOUV31Gl2+AhZH+/H2XcbRkZ5/qbLgcwvAtV6n3wzF6VHLlu1aeOFuZvvoDFJ1RWaT8n0EBO5y6z8bWrz/ha0bT8NxmTlpfZbarNx1uFKBNwCfMaTqcwg6ldV3qKxUwMWROOy86V3Ch99oLNPv5JL18CzOjjSe25sa6Lk95AZVFb89L70T+2fAkhLAVQpQTQhR/OhzvuX2Ut8OggB1FRvyBrV9/onZMI/D7dpQyMeNEqyE0cS3NT2YlGGjVk2pxC1k6vzN3wuN0XbKSD4SHh9O6dWu8vLzw9vbG0NCQgQMHApmPJZ43bx7lypXDx8eHmTNnqm7lmTAv3hLX7mcwca5B1N5+hO/oSnrSoxfu27KwJ5feGUkztzKMPL2Vpn8uJDA+5pl9NMZmOHb4hhITL2FapAIhv37MvW9rk3j//As/M7sVMDHkt64VWfiuN4fvRlNx1kEO3onUSS1K3qDyKPsIQyMcWo+j+MRLmBapSOivn/Bo+yocm27ErEgjHh0Zx8NVNUkOP4+poRFjK/hxrf2ntC9anokX9+C5YSpr7l7Qq54IQgg6eLvgP6oB4/xKsvZiCGW+28+sQ3fUEujKf6KyKGeZOJWi8JBNFB2zjwLWToz038W+K+sIjojBa+t8Zu6bSVq6fs1Fl5la7nacH16PMQ09WHYuiHLTDrDxcsirD1SUF8gtWSRednEghLAGBgBdAWMgAjAFCpEx7O4HKeX+bK/yNfn6+srMJtXKbaL3/kDo8oz5oAoP3YKhQzHGn/uTSZf24mWg5adHS7ib7AG1FtC1ZiW1YkYuc+3aNcqWLavrMnTuRb8HIcRZKaWvjkp6K143i6TUEntmBo+Oj8fAwhnHZr9h6lork30li2+dYtjJzRhpDJhXoz1di1d84X6xR5cRtnok6fGR2Nb/GIeOEzEsUPCNv9d/celhHJ2WneF2ZAITmpVhTAMPNBqVW7qmsuhveSmPhBCtgdYeHh59bt269drHSymJObSYsNUjkamJ2Lf+DLPSpYg+NIr0xHCsKw3FpvqXaIzMATgSFsDQE5s4Hx1M3ULFmV29HRXsXN7yt/rvbkXEM3TzVf64Hk65QpbMfceL+mpOOr2gsuhveSmL/u9t3qNJbTqxR5cRvn4caTEhnHEszmfuDXEsYMJPDXrjW9jnrZwnJ5wLiuGjtRe5+DCOd72dmfNOeQqpHuI6pbLob28zi141BmM9EAjUkVKWllLWllL6SikLA1OAtkKIj173pErW2fn1p8jIP0mNeUjA11VJvHGEbyo3Z22D9wkQprSz7Yswe0SpE035atH3RD9J0XXJipLvCSFaCyEWxsbGvuZxGmyqjMKl00GExpiQ9X48OvENUpv2onPwUalqnG87nLLWjvQ4uIJuB5bzKPnJc/vZ1H4fj+9uYtd4MI8O/szt0SWJ3vsDMv35z81u3i5WnB5Sl04VXPj8j+u0XHSSiHi1EpWiZAcp5VYpZV9ra+s3Ol4IgW29j/CYfA3Lim2J2PAlYcsmYld7EZblPiD27EyCl1Uk8f4eAGoXcudk6yH8WLMj/jFh+G6ZRf9jvxOZlPA2v9Z/VtKhANs+qsrGXlVISEmj4YLjdFt+luDYRF2XpihKFgmNATZ1euHx3U3s242nSkwIf5z+leY3j9Hoj58Z+Md3xKXkjr/pSm42nBpSh2+alWbz1TDKTdvP8rNBetWDVFHehlcNu2sspVwmpYx5wXtnpZRDpZSLsq06BYAC5fxw//IkBpb23J/qx6MDv9ChmDfHWg3CytyGXpbvsNqqOj3jR/PrvE7svfZA1yUrSr72X2/4TJyq4NrtJBaluxBz4htC1jcmLe7Ff9clrOw50KI/Eyo24/d7l/DZNIO9D5/v4WBgYYNT99kU/+YCpkV8CP1tAHe/8iXh+qE3qvG/sDQ1ZEX3Sizo6M2BO1FUnHlITQKsKHrM0MYJtwFrKDx0C+lPYngwtSlpoUY4tt6CMDAkdGMLIv78kPTEKAw0GvqWrs71Dp8yoEwtfrl5kjK/T2G+/xHStPozHEYIQVsvJ66ObsAXjUux8UooZafuZ9r+26SkqaF4ivIqQggLIcRSIcTPQojuuqpDY1oAx3e+wuO7m9jW6Ea3wPPsPrWIyLN78FrxKetvHMoVjThGBho+a1SKc8PqUsqhAO+vOk/rRacIjMkdDWiKkhUvbXwSQvgLIT4XQpTIqYKUFzNxKon7FyewKNuQkCV9CF0xjHJWDpxqPZQWhT2ZZViGAY4DaWS8h/Rt9Zm0bgPJafpzkacoyuvRmFjh2OxXHJouISXiIsErfEm49fsL9zXUGPCZTyOOthqEhZExTf78iRGntpCU9vyUfKZuXhT9dC9uA9ehTXjE/cn1CPqxG6nRQdn9lZ4hhKBv9aIcH1Qbc2MDGi44zpR9t9Cq1fAURW9ZVmxNiUn+2DUaSPSeeQTP64uV1zdYVx1D/I3VBP3mTfz1VUgpsTUxZ3b1dpxvO5xKBd0YfHITlTfPYn/IbV1/jWeYGRnwddPSXBlZnwYl7Pl0+zV8Zh5k760IXZemKDlOCLFYCBEuhLjyr+3NhBA3hBC3hRBjnm5uD6yXUvYB2uR4sf9iZOeGa9+luH91GofiVfny1h4WnlrG99vm0GrTNwTE5Y6HXJ5OlhweUIuZbcpx4E4UXtMO8NPxe+r6SMkTXjXsritgAewSQpwSQgwTQujf4P18wsDChiLDt2PXZAjRu2bzYFZrLNNT2NCwF1N9W7E3xZAOTsOJNzOhfVAPJs4ZxpWHMbouW1GU/6BA2e64dj+FoY0H4du7ErmnH9rUFw9h8bUvzJk2w+hfpiazrx6i6tbZXIx++Nx+QgisqnSkxORr2Lf9ksdnN3B7TBkit05Gm5qzQ+B8XK05M7QOHco7M27HddosPkVkghqGpyj6ysDMEqcecyj2+TEMzKwImtOBJ+dvUKjVdoysihGxsydhm9uSGncfgHK2TvzZtC/rG/YkPi2ZRjsX0PfoOhJyOGtepYS9BZs/rMrWD6uSkq6l8U8n6PzbGdXrQMlvfgWa/XODEMIAmA80BzyBrkIIT8CNjOlZAPTmibeZuy9Fxx7EbdAGiptZ8tOl33nn4GLa/jaMKWe3kKpHPTAzY6ARDK1bnEsj61GlsA39fr9Mo5+OcztSv4YwK8rretWwu4tSyrFSyhLAYKAIcEIIsV8I0SdHKlSeIQwMceo+G+cPFpLgv4eACdVJDb/DiPL12dvsExIx5H2rtqwv2I4PNQs4t6wpC/adVK3lipKLGdl44NLpANa+I3l8ZTEPV1YnOeLiC/c1NzRmbo32bG/cm6jkJ1Tb+j3TLu8nXfv8MBKNiTmO7b+mxORrFCjXmPD147j7mRePL2zP7q/0DCtTI1b1qMT89uXZcyuSSjMPcTQgOkdrUBTl9Zh7VKf4hHM4tP+Gx+c28WBae8ycP8C27gySgg8TvMyH2PNzkdp0hBC8U7Q8V94ZzaflG7L45il8t8zmbGTO9rjMipaehbgysj5fNy3NVv8wyn63n8l7b6ne5Eq+IKU8BPz7f8BVgdtSyrtSyhRgNdAWCCKjAQpe3aEhRwkhsPJ9h5JTb+PYZTo1EsJZeXoZieu/pP6ykRwNC9B1iVlSvKAFuz+uzsJ3vTkXHEuFGQeYceAO6eq+TsmlshwUUsoTUsphwPuADTAvu4pSXs22fh+Kjt5D+uMIAiZU58mtY9RxKs6ZNkOp7lCU8ekufF70M3xMbuB7viWjf5pFSFySrstWFOUNCQNj7GpPwqn9DrTJsTxcXYvY8/MyncegmVsZLrYbSavCnow5s51GOxdw9/GLu5wbO7hTeMhGioz8EzSGBM5qxYOZrUgOff3Vsd6UEIJ+NYtxbFAtjA011P/xGNP231YN54qix4ShMQ5tP6f4xEuYFvYmZEkfYnZtxKHpRkxd6xB9cAQha+qSEnEJADNDIyb5tmBPs49JSEuh1va5TLu8H63UrzmWTI0M+KJxKfxHN6BJaQc+++M63tMP8ueNcF2Xpii64MrfPZwgo9HJFdgAdBBC/AhszexgIURfIcQZIcSZiIicHc4qDI2xbz6C0rMCsa3Tg04hl5h9cD6/LujJJ3t/eW6RFn0khKB3taJcGVkfPw8HRm3zp9bcI1wNfazr0hTltWWp8UkIUUUIMVMIcR/4CvgJUMPvdMyiTD3cvzyBgYUd979rSOzJtTiZW7GzaV/GevuxOuYxvYp8SqhlCQYkj+G3H7qw6ULuaOlXsl9UVBQ+Pj74+Pjg5OSEq6srBgYG+Pj44OnpiZ2dHe7u7vj4+NCoUSO0Wi2DBw/Gy8uL8uXLU6VKFQICsvbf0++//44Qgre1vG5+ZlbED9ceZzEr0ojog8MJ2/IO6U9efDFnb2rBugbvs7h2Z85HB1Nh03S+v3rohb2gAAqUb0KJiRcp1GU6T24c4u5nXoStHYs2KT47v9IzKrnZcHZoXd7xcuLT7ddou+QUUQlqFc+8TuVR7mbiXJqiY/bj/MFCku6f48GUZhgYVMe+8WJS4+4RvKo60Ue/QJuW8RCsvrMHF9qNoPXTxvFmf/5McMLrrQ6aE4rZmbOhVxV29K4GQPOfT9Lh19Pcj9b/G1blzagsyjopZYKU8gMpZT8p5YqX7Lfw6Wrpvg4ODjlZ4l8MCxTEtfcySnx7GevCJRl29zAd14zggwUf6t08dJlxszFj84dVWNG9Enejn1Bp1kEm7LqpFkjIo/JsFkkpM/0BJgF3gNPACMDtZfvry0/lypVlfpL6OFLe/aaWvPo+MmLbd1Kr1Uoppdz24KosuPxzabvsM/njhiHy7iwjuXNqcTl2+Tr5OClVx1UrUkrp7++v6xKklFKOHz9eTps27ZltPXv2lOvWrfvr9cqVK2WHDh1kenq6lFLKwMBAGR0d/crPjouLk3Xq1JHVqlWTp0+ffuE+L/o9AGekHuTJf/nJzizSarUy5vw8eXeOhbz/U2H55N7ul+4fGP9Ittr1i9QsHiFrbp0jrz4Keen+qY9CZNDCnvLq+8gbg11kzLEVf2VLTtBqtXLu4bvSZPQ2WeSbXfL4vVf/t6a8OX3JIilVHmXHT05eF6U8eigfzO0or76PvP2Zt3x8dZcM3/mhvDvLSD5YUlY+CTz4175arVb+cuOELPDbGGm/4gu54d6lHKvzdSWlpslJe25KizHbpfmYbXLh8Xu6LilPUln0N11lEVAMuPKP1zWAP//xeiww9k0+W1/u0R4dXyzP97OQl99H9v+yhhx1bK1MSss990bhj5Nk12VnpBixRfrMOCAvBMfouqQ8R2XR395mFr2q51MS0ExKWUVKOUNKqX+D8xUMCxSk6Og9WFXrTPjaTwld2h+ZnkbLwp6caTOMktb2DIgx5PtyM3AyTeL98J58/f0wTt5Tc6ooWRcSEoKzszMaTUZsuLm5YWtr+8rjvvjiCz799FNMTU2zu8R8RQiBtc8AXLocRWNiTejGFkQfHotMf3EvITcLG7Y0+pBldbtxKy6CyptnMfHC7kwn3jS0ccK1z68U++IYhjbOBC/ozv1J9Uh68OK5pt42IQQDa7tzZGAtDDUa6s4/quY5UP6i8kh/Gdk4U3jgOgoP2Ux6fBQPpjYlPdISxxa/gzad0PWNiNw7EG1KPEIIPipVjbNthuNewI6O+5bysR5ORg5gYmjAWL+S+I+uT213Oz5ef4lP1l9SvQ7yuXySRaeBkkIIdyGEMdAF2KLjmv4Tm+ofUH5GMCYlvRlw7zgl1n6K35rP8Y8J1XVpWeJQwISVPSqzsVcVQh8nU2X2Yb7ZfZPUdJVH+VVuyaJXTTg+QUp5SwhhLoT4QgjxM4AQoqQQolWOVKhkicbYFNdPVlKw5Rge7V9A4Ow2pCc+ppilHYdaDKRfmZrMDbrPYPdRhBZqRH/jn7i+ujlTdxwjTQWVkgWdOnVi69at+Pj4MGLECM6fP//Xe717935hV81z584RGBhIy5Ytc7LUfMXEoQIu3U5i6dWb2LMzeLi2HqkxL+5CLoSgW4lKXHlnFO2Klmf8+T+p+opJf809auA+/hTOH/xMcsg17n5ZiZCl/UmLz5kli30L23B2WF1aexZi1DZ/fGYcZMPlkP8/fVXyKZVH+s+yUhtKTPbHtmF/onfP4eGCgVhXmIxVpaE8vvwzwcsrkxh0CIBS1g4caTmQ0eUbsOjmKapsnc05PZyMHKCIrTk7eldndAMPFp64j9+CY4SqOTXzrbyWRUKIVcBxoLQQIkgI8ZGUMg0YCPwJXAPWSimv6rLOt8HAzBqPzy5g3+5Taj26x9cHfuC9ZaOYd+VArrnGaOvlxOWR9ejo7cz4P29Qc+4RroTE6bosRQdySxYZZnG/JcBZMrpdAgQD64Bt2VGU8maERkOhTpMxdixOyNJ+3J9Ul8LDtmFi58q8Gu2p6ViMj4+to6thReb51KHGha+Ju9aGIbfHMKJ7P4oXtND1V8jXQlcMJenBhbf6maZFfHDqPvutfJabmxs3btxg37597Nu3Dz8/P9atW4efnx+//PLLc/trtVqGDx/Or7/++lbOr2ROY2SOfaMfMCvaiMg9nxC8oioFG87BsmyPF+7vaGbJqvo96OLuw4DjG6ixbQ4jvOrxpU8TzAyNnttfaDTY1u+NVZUORGwcT/TeH4g7uQaHjt9iW78PQmOQrd/PxsyI9T19WX8phPF/3qDj0jNUdrNmQtPSNCvjiBAiW8+f3+h7FoHKo9zCwMwK5/fnYV2jGyGL+xA0pwNW1brg0HQtj06MIXR9I6x8BmJbayLGRuZM9m1JE9fS9Dy0iprb5zKxUjOGe9VDI/RqIS0MNIIpLctS0dWKj9ZcxHf2YX7v6Uu1oq9+yqxkncqinCel7JrJ9h3Ajjf9XCFEa6C1h4fHm35EthBC4PjOFCw8m6OZ3YrFZ1fybVwY2wPOscSvN07mVrou8ZXsLTJ6QbUv70z/DZfxnX2Yr5qWYmS9Ehga6Fd25lYqi96erP4XWUJKORVIBZBSPgHU1b6esq3fhyLDt5MSfpuACdVIepCxyky3EpU42XoIdibmdLkXxtpqP2Fs5cJI7ThWL+zObydu5ZqWfkU3TExMaN68OdOmTWPcuHFs2rQp030fP37MlStXqF+/PsWKFePEiRO0adMm106smRtYlGyPa/czGDv6EPnnh4Tv7Ik2OfMnYG2LenHlnVH09PBl6uX9VNw8g8OhdzPd38DCFqcecyg+4Twmhb0JXdqPgPG+PLl5JDu+zjOEELxbwYVLI+qxpLMPUQkptFx0irrzj3LgdmS2n1/RPyqPXk0I0VoIsTA2VreTeZuXrEnxb87j0H4Cj89uIHBmN0ys2mNZri9xF+YRvMKXpIfHAGjg7MH5tsNpVdiTT/V4MnKAzj6uHB1UC2MDQb0fjrHk1ANdl6TogMqiV5NSbpVS9rW2ttZ1KS9kUboepaYGYOlega9u7qbe4V+osmY8m+9f1nVpWdaxggtXRtantWchxu24Tu15R7kWplbEy09yQxZltedTihDCDJAAQogSQI4MyBdCtANaAlbAIinlrpw4b25XoHxTin12hAczW3Lv29q4DVxHgfJN8bRx4mTrIfQ9uo7x189xsuggvkm/QtcbP3Lj8BWG+H/LV13ewc7cWNdfId95m63f2eHcuXM4OTnh4uKCVqvl0qVLeHt7Z7q/tbU1kZF/NwrUr1+f6dOn4+vrmxPl5luGVkVw7rCLmFOTiTn5LckhJ3Fo9humzlVfuL+NiRk/1+5El+IV+fjoOur/8QP9ytRksm8LLI1ePP7btHB5io7ZR9ypdYStHsG9b+tgXaM7jp2nYmSbvQuhGhpo6FmlMF0rurL41AMm7rlFwwXHaVTSnm+alVE9D94Cfc8iUHmUVVLKrcBWX1/fPrquRRga49D2C6xrdCd87Rgit0zC0MYFmwbDSYr6nZC1DbCqNBTbml9R8P8rdd46xdCTm/DZPIOfa3WiXVEvXX+N51Rwseb00Lp0XX6Wj9Ze5GxQLLPalsNI9Tj4z1QWKTnJ0NIe9y9OE75+DK23T8c7PpT+T+LYVq4Os2t1xcLIRNclvpKjpQlr36/MmgsPGbjxMpVmHeKbZmUYVrc4BhrVb+RNqSx6e7L6f8bxwE6gsBBiBbAXGP2qg4QQi4UQ4UKIK//a3kwIcUMIcVsIMeZlnyGl3CSl7AN8AnTOYr0KYFqkAu5fnsDIwZ0HM1vy6EBGl7sCRiasqNededXfYXfIbdrHOxLYYDlFzBLoH/shX88ZwZ4b4TquXtE34eHhtG7dGi8vL7y9vTE0NGTgwIFA5mOJFd0QGkNsq3+Bc8e9SG0aIevqE3N6KjKTycUB/FxKcrHdCAZ71mHB9eN4b5zOn8E3Mj+HEFhX64THlOvYt/mcuDPruftZeR5fyJnR2MaGGj6pWYxbYxsys005Lj6Mo8bcI7RdfIoLwfrZS0J5e1Qe5V7GjsVxG7iWYp8fxahgESI3fkfqXTNM7JsRd24WD1dUJSnk1HOTkXfY9yufHF2vl5ORF7QwZkfvaoyoV4Ifjt2j8U/HCX+sf3Uqb5/KorxFaAwo1GkaRYZvxz0tmY1nfyPg1EYqrp/A6Yjc0bNRCEGXiq5cGVmfZqUdGL3Nn3o/HOVmRLyuS1OyUW7JIpHVYVZCiIJAdTKG252QUr5ynIMQoi4QD/wmpfR6us0AuAk0BoLIWEGhK2AATP7XR3wopQx/etwMYIWU8tyrzuvr6yv15ResD9IT4wia34mEy39i33ocDu2/QTydCf9UxAM67/+N0MTHzKjoR0P/OZiE7uJAYkXulJ7GF21qYWKYvfO55GfXrl2jbNmyui5D5170exBCnJVS5upHgfqQRelJj4jc248ntzZgXMgX+0Y/YuJQ4aXHHA+/R58ja7kWG857JSozs1pb7EzMX3pMcuhNgud3JunBBQq2GIVjh28RL5g/KrvEJ6cx50gA0w/cISYxlU4VXPiqaSnKOFrmWA25mcqiv+XFPNKHLHoRKSVxp9YSvnYMqZH3MCtVDWEVjNRGYO07EttqXyAMTUhJT+PLczuZfuUgpaztWVGvBxULuuq6/BdaeS6IPusuUtDcmA29quBb2EbXJeUqKov+prJIt1Ii7hH4fWuSA6+wqrAPM9zrM87Hj7EVW2CgyR09G6WUrDgXzOBNV0hOS2dSi7IMquWORvWCeiWVRX97m1n00r8cIYSBEKIAgJQyCogC4gBPIcQrr+illIeA6H9trgrcllLelVKmAKuBtlLKy1LKVv/6CRcZvgP+yErDk/I8AzMrigzdik39vkRunUTwgu5oUzJWZqnqUIQzbYbR0Lkkg87u4lvnrmhqTqeWuT9tAzrQ7/sZatUERcnFDExtcWyxCodmS0mLu8/DldWJPjIObeqTTI+p4ViMs22H81mFRqy6e55yG6ay/t7Fl57HxKkUxb44jm3DfkTtmMa9yfVIjcq5p4QFTAwZ51eSu+P8+KxRSXZcD8Nr2gE+WH2eu1EJOVaHoihZl9GDsjMlJl/DsfNUkoOu8+RcCDK+ODHHviN4VXWSw89jbGDIlCqt2NW0L49Tk6mxbQ4zLh9AK/Vvtd5uldw4MrA2BhpBnflH+e1MoK5LUhSd05f5516HsUMx3L88jU293nQNvMCai8uYc2Y79TZNJuBxzqz4+18JIehR2Y0rI+vToIQ9wzZfpcGPx7gTqa6LFN14VbPtd0D/f7xeCYwEvgA+f8NzugL//D9x0NNtmRkENAI6CiE+yWwnIURfIcQZIcSZiIiINywt7xKGRjj3WoBjp++IO7ma+9Ma/7VUekFTC7Y2/pBvKjVjdcAFWgUnk9R2JwWsnfnC4HM2LO7JunP3dPsFFEV5Y0IICpTpilvPyxTwfI/YM9MJXlaRJ/d3Z3qMiYEhEyo142TrIbhZWNN5/zI67ltK6JPMG6M1xqY49/wB1/6rSQ66wt0vKubYMLz/szEz4ptmZbgz1o+hdYuz5sJDyny3n36/XyI4NjFHa1EUJWs0xqbYtxiFx9Tb2DbsR9LtmyTfNCLp1j2CV9Tg0fGvkekpNHQpyYW2I2jpVpbRZ7bRbNfPPHyifzezFV2tOT20DjWL2tJr9QWGbr5Carr+NZQpSk7R9wnHM6MxNsXlw59x6b0Ej4R4dp5ZAvfP4/P7ZH67cSLXLNTkYm3K1o+qsrizDxdD4qgw4yDzjwag1eaO+pW841WNT37AzH+8jpVStgGaALWyrap/kFLOkVJWllJ+IqVc8JL9FkopfaWUvg4ODjlRWq4jhMC+5Whc+68mKeA09ybUICXsDgAaoWFchUbsbNKXiKR4ah/ezoV6v2BYrj/vWWwndVd7pv95OteErJL3CCFMhRAdhRDfCyHWCSF+E0KMFkKU03Vt/6avT/gMTO1waLwQpw67QGNA2MaWhO/sRfqTzBvsfQq6crzVYCZVbsGOoGt4bZzG0lsvzwLrap1x//osRgWLEDirNWGrRyHTUrPjK2XKoYAJ01uX4/ZYP/pUL8riUw/wmLyP4VuuqrlYFEVPGVra4/zeXEpMuopFucak3I8h5aYhkX98Q/CqmiRHXKSgqQXrG/ZkQc2OHA+/h8+mGWy+f+XVH57D7C1M+LNvdYbUcWfO4QCaLjxBRLzKHkXJjWzq9MJ9/EksrV356eJGBt7fzwdH19F513weJWfek1yfCCHoVaUwl0fWp7a7HYM2XqHxT8e5F5076lfyhlc1PmmklGn/eP0pgMy46yjwhucMBgr/47Xb021KDrGu1pmio/eQHh9FwDfVeXL7+F/v+bmU5Gyb4fjYudDjyFqmFqiLWcOfqWJ6g4qX3mXUiq2kpKmnd29Tfm/Qy8r3F0J8DRwFagAngZ+AtUAaMEUIsVsIkfmSDjlM35/wmRWuj2uPc9hUHUvCzbUE/ebNY//fMv13Yagx4FPvhpxvO5xytk58eGQNLXb/wv34f4+q/puJU8m/h+H9MT3Hh+H9n4u1KfPbl+fGpw3pVsmVOYfvUmLyXj774xqPnqTkeD36LL9nEajfgb4wcS5NkaGbKTpmP8YOpUm9n0788UsELqzGo5OTQJtGn9LVOdNmGEUL2NJ+36/0O7aeJ2n69TdtaKBhVlsvlnb14cT9R1SZfZhzQTG6Lkvvqb9D9TvQR6ZFKlD867NY+rSi+91zbLm6gl0PruG97mv2Pryp6/KyrLCNGX/0qcZPHb05HRSD94wDLDxxX/039wLqd/L2fwevanwy/ufcTlLKXQBCCGvgxWtwv9ppoKQQwl0IYQx0Aba84Wcpb8i8VG2KfXkCjZk196c0JO7073+952phzd7m/Rherh4/XD/GO/djEK024WL6hG5hvRj8009Eq5u2t8LU1JSoqKh8G25SSqKiojA1fWWcnHraA3KElHKllHKPlHKblHKmlLI10B0wzv6K8w6NoSm2Nb/GtdspjGxLErmrN6EbmpEaczvTY0pbO7K/eT/mVn+Ho2EBlN84nfn+RzKdd+XvYXhrSA66wp0vfHJ8GN7/FbMzZ1EnH/xHN6C1ZyEm771N8Ul7mbjnJo+T0l79AXlcfs8ieK08UnKIRdn6uH91Gpc+S9EY2pNyM5mwFZ8TuLgKKVFXKW3tyNGWgxjlVZ+fb5ykypbZnI/Sv+eZ71UuzOGBtZBIas87yopzQbouSW+pLFJZpM8MLGwoPHgjjp2m4B4VwcELyykRfZumf/7EyKMrSU7PHdcTQgj6VC/K5RH1qVrYlk/WX6LZzycIjFHTE/yfyqLsyaKXrnYnhBhOxnxLn0gpHzzdVhT4EdgnpZz+0g8XYhVQH7AHwoDxUspFQogWwGwyVrhbLKX89r9/lb/lppUUdC0tLoLA79uReOc4jp2mUrD5CIT4ewWEjfcv0+vQagoYGbOmaiNsd/fG8Ml95qYNYegHn+Nhb6HD6nO/1NRUgoKCSEpK0nUpOmNqaoqbmxtGRs+ujJbbV3SB3JNFUmp5fOlnoo9+Bukp2FT7DOvKwxEGma9Wdz8+mo+Prmf3w5vULuTOwlrvUtraMdP9U8JuEzTv3YzV8JqPxLHjpBxdDe/fLj2MY/yf19l8NQx7C2M+beBB/1rFMDPKn6t7qizKkFfzKLdk0ctok58Q9ecsIrd8g0xLxsDBEIc2n2Nb63OExoB9D2/R8/AqIpISmOLbkiGedZ65ntEH4Y+T6bzsLAfvRjGsbnG+a1kWQ4PcsWpWTlFZlEFlkf5LuLafoB+6kJ4Yyyb3snzh4kd5czNWNBlAOVsnXZeXZVqtZMHx+4ze5o+hgWBmm3J8UKWw3uVnTlNZlOFtZ9FLG5+efvAnwDjg/60M8cAUKeWPr3uy7CaEaA209vDw6HPr1i1dl5NraFOSeLjwfeJOr8O2YT+cesxBGBj+9f7VR6G8s3cJgQkx/FClBdXPTcA08jBLEjvSpPP31C6u5thS3r4XhZoQYivw79CKBc4AP0kp9er/ELntIist/iFRB4bx5PZGjOy9sPf7EVPnapnuL6Vk6e0zjDi1hcT0VL6o0JgRXvUw/kd+/JM2JYmw1SN4tPcHzEpUx23AGowKFsmur5Mlpx/E8OWf1/nzRgTOViZ827wsPX3d8v1Fl/IsdcOnP9JiQglbN4rYI8vBAExLuuP60WZMHMsTlZRAn6Pr2PzgCh2KebOodicsjfSr90hqupYRW/2ZdyQAv5L2rOpRCXsLE12XpeQSuTWL8uo9Wmp0MEHzO5F4+xihRdzpXqQxcYYFmFy5KYPKN85V1xJ3oxL4cM0FDt2NpkUZR3561xtXazNdl6XoqWxpfBJC1ABOSCnl/4ffSSkfv3mZOSMvXWTlFKnVEr5uLFE7plKgQgvc+q9BY/r3tF7RyU/osn8Ze0NuMaRsLT6O2IHxnaXsTKyBTaNf6FqlpA6rV/KiTBqfvgccgFVPN3UG4shokLKSUr6Xs1W+XG7NooQ7W4jaP4T0+IdYVeiHbc0JaEysMt0/9Ekcg05sZMP9y5SxdmRu9Xdo6JJ5JsSeXEvI4t5gYIhrn6VYVmydHV/jtRy6E8W4P65x7N4julZ0ZUEHbyxNX9yIpuQ/WbnIEkK4kTGVQB3ABUgErgDbgT+kzGR8ag7IrVn0MomBlwlZ/B5Jdy8iTAS2fj1x7PgzQmPArKsHGXNmByWt7FnfsCdlbQrputzn/Ho6kH6/X8LZ0oSNH1Shgot+zhGo6Jfc2vj0f3kxi2RaKmFrRhO9azYUKsLnRcqz2aIMjQo68GujfjibZ379pG+0Wsm8owGM3XENE0MDvm9Xjh6V1AM55XnZ1fj0I1ANuAnsBHZKKUPfuMockheDLadE71tA6G8DMC1SgcLDtmFk6/LXe2nadEae2srca0do5FKS2QXiMD79OZdTSnDD62dGN6+pwkl5azJpfDotpazyom1CiKtSSr1a+S43Z5E2OY5Hx8cTd+EHDAq4ULDB91iUaPPSY3YEXmPIyU3cfRxF1+IVmValdaYXXSlhtwma34mk++f1YhgeZFx0Tdl/my93Xqd4QQvWvFeZiq7qhlB59UWWEGIJ4ApsI6MnZjgZc2OWAhoAlYExUspDOVDuc3JzFr1K7OlVhP72CelxcRjYWuHSaxGWPh05GHqHLvuXkZCWwi+1O9HJ3UfXpT7n9IMY2i89TfSTFBZ18qFLRVddl6ToOdX4pL9iT67l4aIP0RiZcNCjBEOta2JhYMhPdbrRvnglXZf3Wm5FxPPBmgscu/eItuUK8XOnCqqHpvKMbBt29/TDywDNgaaANbCfjMaoo1LK9Nc9aXbLy8GWEx5f3EHQ/E4YWNhRZPh2TAuXf+b9RTdPMuD4Bopa2LKsZDGsD3xMZKoFGx1n8W23jpgY5s85U5S3K5PGp2tA03/MQVcE+FNKWVYIcV5KWVEXtWYmL2RRUsgpIvd+QmrkFcw92lGw/iwMC2R+g5SYlsp3l/fx3aV9mBoYMaFSU/qVqYmh5vlc+PcwPNf+qzG2L5qdXydLDt+NotuKc0TEpzCjjSf9axZTDev5XBYan7yklFde8r4xUERKmfmM/tkoL2TRy2jT0whb+zExe5cgUyXmZavhNngXYVLS5cAyjoXfY2i5ukzxbYnRC7JIl8IeJ/Pub2c4EhDNyPolmNyiLAYalTfKi6nGJ/2W/PAagXM7kBJyg0TvanxoWYIrhoV4v6gn39fuhpWxfg0Dfpl0rWT2obt89sd17C2MWd6tIvU97HVdlqInsrXx6V8nMiPjKV5zoIY+BmBeD7ackHj/PIEzW6FNjsdt4HoKeDV+5v2jYQF03LeUpPQ0llSoTsmD/dCmxLLQ6EvGfzhItY4r/1kmjU8tgAXAHUAA7kB/4ADQR0o5O4fLfKm8kkUyPZXYc7OIOTERDIyxq/Utlt59ECLziXJvxUYw6MRGdj+8iY+dC/NrdKC644sblvRxGF5kQjIfrL7A9mvhtC/vxC+dfLAx023PLEV31A1f7pASeZOgn1qSdPM2BpZWFBmxG4MilRh1ehvzrh2hTiF3Vtd/Dyc9GwaTkqZl2Jar/HjsHk1KObCyRyXszNUCrsrzVBbpP21SPA8X9ybu5BpMPCqx0NacmeZVcDOzYGmDXtR1KqHrEl/L+eBYuiw7y+2oBD5vVIovGpVUCyUo2d7zaQawSErp/ybF5bT8EGw5ITUqkAczW5L80B+nHnOwbdjvmaf/D+If0X7vr1yIfsjE8rVoeWECZo/9+Sm1D717TqJ0IUsdVq/kdpmFmhDCBCjz9OUNfZtk/J/yWhalxtwhct9Akh7sxcS5BvaNfsC4YOYjHaWU/H7/EsNPbiH4SSy9S1VjUuUWFDR9fpXMfw7Ds2s2gkLvTtb5MDwpJbMO3WXM9mu4WZuyqkdlqhW11WlNim5k9SJLCHGZzBdFmCiljMqO+l4lr2XRy0ipJXxzf6K2/gRagWPnb7FvNpaVd87x8bF1WBmZsqbB+9Qu5K7rUp+z6OQDBmy4jJuNKRt6VsHbRb8ayRTdU41PuYOUkkd75hG2ZhTCwJiHxZz40L4uQYY2jPCqz4RKzTDJZHEWfRSfnMagjZdZeiaIOu52LO9eicI2ajLy/Cy7G596Ax8AhsASYJWUMva1q8xmeXUlBV1KT4wj+MduxF/cjk39vji/Nxdh+PfTuCdpKXx0ZC1rAy7QpVh5RoZtxCZ0B2uTWlCt/QLql8o9S40q+iWTnk/mwHCgqJSyjxCiJFBaSrlNJ0W+Ql68yJJSEn99BdEHR6FNicPGdyTWVceiMcy8K/nj1CQmnN/N9/6HsTE2ZbJvSz4oWQXNv3pO6eswvJP3H9F1+VmCYpOY3KIsw+oWR6OGxeQrr9H4NBVIB1Y+3dQFMAdCgdpSSp1068uLWfQqj/03EPxjV7RxKVj4NKTwgO34Jzyi476lBDyOZlqV1gzyrK13Q2pP3H9Ex6VniExIYUxDD8Y09MDUSL+GCiq6k1sbn/LrPVpy6E1ClvTlyfWDaBwLMde1JAusq+Ft48iy+u/hZeus6xJfy7KzgfT//TLGBhoWd/ahrZe6z8uvcmTYnRCiNBmNUF2Bo8DPUsr9r3vS7JYfL7Kyk9SmE77+c6K2T8G8VB3cBq3H0Mrx7/elZMqlfXxxbieVC7oyyygI5xtzOJzkg6j3K+/V8NRh9UpulUnj0xrgLPC+lNLraWPUMSmljy5qfJW8nEXpiZFEHxpN/LXlGNp4YO/3I2aF6730mMvRIQw8sYEjYQHUcCjK/JodqGDn8tx+cafW8XDRR3o1DC8mMZXeay+w4XIoLcs6sqSLjxpenI+8RuPTOSllpRdtE0JcllKWz+zY7JBfb/j+LzX2AQ++r0PynQcY2tlTdNRBkuzd+eDwGjY/uEIndx9+rvUuBYz062857HEyw7dcZdX5YEo5WPBjB28aqLlWFHJv49P/5eXrosxIrZaYQ4sIWz0KbcoT7jvb8JF7Bx4ZWTKpckuGlKvz3MM4fXYzIp6uy89yPjiOAbWKMa2Vp2ogz4feNIuy/F+6EMKAjKEuZYBI4CIwXAix+nVPquQuQmNAoU6Tcf1kJYkBpwn4qgpJ9y/8/b4QjK3gx0a/XlyPjeDdWEuuVZ5OTdPLOB5pxeTNu9FqX29uMUXJRAkp5VQgFUBK+YSMuZ+UHGZgZo9D08U4tf8DpJbQ3xsTsbsv6UmPMj2mvJ0zB5r3Z3HtztyKi8R3yyyGn9xMXMqzIyetqr5L8QnnMLYvRuDsNoSuGolMS83ur/RSNmZGrHvfl3nvlGf3zUgqzjzE4bs6GUGl6DcDIUTV/78QQlQB/n9VnpbTxUgpt0op+1pb589VG42si1D8s9vYNO5AWmwkd77wRp5czu8NezK5cgvW37tIjW1zuBEbrutSn1HI0oQV3Suxs0810rUSvwXH6bnqPBHxybouTVGU1yQ0Gmzr96HElGtYVmxD0aAIdp1bQreoM4w8vZXGO3/iQXzm1076ppRDAY4Nqs2QOu7MP3qPGnOPcCM8XtdlKblElhqfhBCzgBtAC2CSlLKylPK7p93H9Wp1KSX7WNfoSrHPjiClloCJtYg7te6Z91sXKcexVoMwNzSmw91g9lZbQGHjWBrf7sqYpUtJTNW7hRGV3Cfl6aIHEkAIUQJQV+M6ZFbED9ce57D2HUm8/zKCl/mQcHtzpvsLIehZsgrXOnxKn1LVmeN/BM8NU1l99zz/7IlrXMiDYp8fw9ZvANE7Z3BvUl1SIu/nxFfKlBCC/rWKcXxwbcyMDGjw4zG+3XOTdNW4rvytN7BICBEghAgAFgF9hBAWwGTdlpY/CQMjXHqsx7X/AjQm8PCXvgQvfJdRnnXY2aQv4YnxVNv6PRvuXdZ1qc9pUtqRSyPrM86vJKsvBFPmu/38cvK+eqCnKLmQkY0zhQetx23QBowMbRhxcT+brv/G5YfXqLBpOsvvnOV1RiTpkomhAbPaerHlw6oExSTiO/sQS08H5pr6Fd3J6pxPHwBrpZQJL3jPWt/mf8qPXTpzUlpMKIFzO5B4+xj2bb/Aod1XCM3f7ZhRSQl0ObCMfSG3GVzCi/evTMQsOYSfNaP59MMxOFrqV/d2RT9lMuyuMfA54AnsAmoBvaSUB3K+wlfLb1mUHH6eyF19SIm8hEXJjhRsMBsDc8eXHnM64gEDjm/gbFQQfs4lmVvjHUpbP3vMP4fhFXp3Mjb1eiN0vFz646Q0Pvn9EqvOB9OopD3LulWikMq2POt1u5cLIawB9OX6KL9lUWaSI67w4PsGpAZGYuRUhKKfHiHM2JLOB37jZMQDRnrV59vKzTHUcb68yLWwx/T7/RKH7kZT292OHzt4U85JLeyS36hhd3lDekIMYWtHE3PgZ9KNNcws04Tf7MrRsZg3P9bsiJ2Jua5LzLLg2ER6rDjPwbtRdK/kyg/tvbE0zT2TqStvJrsnHK/0gs2xwH0pZY53I38VFWzZT5uaTOhv/Yk5tBjLSu1w6fsbBmZ/XwSladMZeWorc68dobGTO1+ErsUl9ji/pvSg83uz8XRWK7goL/eS1e4KAtXJGG53QkoZmePFZVF+zCKZnkrs2Rk8OjkRjVEBCtabgUWZbi+d1Dddq2XhjeN8du4PnqSlMsqrPmMr+GH+j8UNUsLu8HDRhzy5cQiTIhVw6jYbi7L1c+AbZU5KyeJTgQzedBkrUyOWd6uIX0kHndakZI/XmPOpEDAJcJFSNhdCeAI1pJSLsr3Il8iPWZQZbeoTghe34PGJgwhDY1z7rcSkQltGnNrCj9ePUd+pBCvr96CQmf417Egp+fV0IKO3+ROblMaI+iX4olFJzI3VjV5+oRqf8paE6wcJXtidtKhgbjsWonepjhhbOrKoTmeaupbWdXlZlq6VfLvnFhN236B4QQtW9ahEZTcbXZelZKPsbnw6AVQCLpFxw+cFXAWsgX5Syl2ve+LspIItZ0gpid49l7BVwzFxKUvhIZsxdiz+zD6Lbp5kwPENFLOwYbq8TrngVexIqkeZtovxK1tYR5UrucE/Qy2TBvC/SCnP5UxVryc/Z1FK9DUid39McsgJzIo1x95vHoaWL/+bD0t8zOjT21h+5yzFCtgyu1o7Whcp99f7Ukoen15P2OqRpEY9wNK3A4W6TMPYQbdLpl8JiaPL8rNcC4/nM7+SfNm4FIYGuWfyUOXVXqPx6Q8yVgX+TEpZQQhhCJzP6YnG/y0/Z9GLSCmJPjiR8FXjkUkS28Yf49TtB5bdPUe/Y+uxMzFnbYP3qeFYTNelvlBkQjKjt17j1zOBuNuZM799eZqVeXkvUyVvUI1PeY82JYnwdSOJ3v0DaQaCuWWbs9iuNAM8azPFt+UzD+L03aE7UfRYeY6w+GSmtCzL0DrF9W5FUeXtyO7Gpw3AF1LKq09fewITgNHABn1ZaSq/r+qiK/FX9xA0vxMCgdug9ViUbfDM+0fDAui4bylJ6WnMLKih/o0pnE0pTXyNpfSq89I2BSUf+1fj0/9X1TQFfMlY8EAA3sAZKWUN3VT5cvn9Iktq04m7+AOPjn4BGgPsak/GsnxvxCtWdTkYeoeBxzfgHxNG68LlmF2tLcUs7f56X5uSSNQfM4jcNhlkOgWbjcC+1Vg0pgWy+ytlKiE5jUGbrvDr6UDqFrdjRfdKuFqb6awe5e16jcan01LKKkKI81LKik+3XdD1dVJ+z6LMJAYeJXBOc9LCH2NS1JMiIw/gn5ZKx31LCUyIYUaV1vQvW0tvb54O3I6k3++XuBGRQKcKLsxqWw5nK1Ndl6VkI9X4lHcl3jtL4NyWpEWGcdfelY89WmBdqAS/1e2Gr33ueWAflZDCR2svsOVqGC3LOrK4sw8OBdS0BHlNdq92V+r/DU8AUkp/oIyU8u7rnjA75fdVXXSlQLlGFB9/CkNrJ+5PbUz0nvnPTDhXq5A7J1sPoYRlQfqEJrKk3FS8jANwP9mGyRu2qokzlVeSUjaQUjYAQoBKUkpfKWVlMhY8CNZtdUpmhMYA64qDcH3vPCaFqhC1byCh65uQGnP7pcfVcyrBubbD+c63JXtDbuK1cRpTLu0lJT1jlLfG2AyHtp/j8d0NrKq8S+TWSdz+tBQxR35DarU58dWeY2FiyOLOPvzWtSJng2LxmXGQHdfCdFKLolMJT4cG/39RhOpkTFOg6CGzwrUoPiEA84oVSH7gz53RxfAIu86p1kNo4lqKwSc38f6hVSSk6ue6FvU97Lkwoh5fNy3N5quhlJ26n/lHA9QiCIreEUK0FkIsjI1VcZgZs2KVKTktGBu/9ygeHczO04tocGMftbfOYeKF3aRpc8fCTQUtjNnYqwpz2nn9tTrwgdt6O0OGksOy2vNpLRAFrH66qTNgD7wHHJFSVsm2Ct+AalXXjfTEOIIX9CD+wlZs6vXB+f15iH90FX2SlsKHh9ew7t5F3nUqzMhb0zBKi2e11bd88f7Has4C5RmZTDh+VUpZ7lXb9IXKor9JKYm/+ivRh0Yj05OxrfkVVhWHvHLi8Afxjxh+agsb71+mjLUjP9fqRM1CxZ7Z58ntE4SuGELS3VOYFq+KU/fvMfeono3f5uVuhMfTZflZLj6MY2T9EnzbvAxGahhervYaPZ8qAXPJmJ7gCuAAdJRSXsrmEl9KZdHLSaklYscQojbNQ6aCfduxFGz7DVMu7Wf8+T/xsnViXYP3KWmtv3O63YqIZ8CGy+y5FUnVwjYs6OiNj6t6GJvXqJ5P+UPCzV0E/diB9Oh4Am1dGeTRCPtilVhap6te59C/XQiOpcvys9yKTFDTEuQx2T3szgzoD9R+uuko8AOQBJhLKeNf98TZSQWb7kitlogNXxC5dRJmpWpTeNDvGFr9PQ+BlJIpl/bx+bk/qGzjyMSwNbgnXmWx7E+v7l9TupD+TfCp6EYmjU+rgARg+dNN3YECUsquOV1fVqgsel5a/EOi9g3kyd1tGBfyxaHxQoztvV553B9B1xhwfAOBCTGM8mrA+IpNMDH4u8FaarXEHltO+LoxpMWEYF2zB47vTsHIzjU7v06mklLTGbHVnx+P3aN6UVtWdq9EMbvcs3qN8qzXuch6Os9TaTKGBt+QUqZma3FZoLIoa+JvbCb4xy6kP0rCrHQ1igzbxd7oELofXEGaVsuvdbrQtuir80pXpJSsOh/M8C1XiXqSyuDa7nzdtDQFTNTDvbxCNT7lH+nJcQQvakb8meNotRp+da/F4mLVmFK9A31KVdPb4cD/Fp+cxqCNl1l6Joja7nYs71aRIrbqeii3y7bGJyGEAbDn6ZCXXEEFm+7FnlzDw18+wNDSgcJDNmNa1OeZ97c8uMp7B1dSwNCIqWmXqBm1jU2JDXFsNJ/uVUropmhFr2TS+GQK9APqPt10CPhRSpmU0/VlhcqiF5NSknBzHVEHhqFNjsGm6hhsqnyKMHj5pJpxKUmMOLWFxbdOUd7WmV/rdMGn4LONS9qkeCK3TSZq5wwQBti3GkvB5iPQGOtm/qV1Fx/SZ91FNEKwqFMF3invrJM6lP/mVRdZQoj2LzteSrnh7VeVdSqLsi71cRCB8+qSdD0AAysbiozYQ7i9O532/8aZyCDGeDdkQsVmGGj09+n9oycpjN1xnYUn7lPYxpQ57crT1stJ12Upb4FqfMpfpJQ8Ov4dEes+Jz06nRDLQozyaIBruUb8XOtdnMxzz+rhy88G0X/DJYw0GhZ1rkA7L3U9lJtld8+nvUB7KWWuGKirgk0/JN47R+D37UiPj8S1z1Ksqr77zPtXH4XSbu8SghJi+NJWQ+e7M7iSUoL9brP4tmMjNQwvn3uTUBNC/C6l7JBdNb0ulUUvl54YSdSB4STcWI1RwXI4NP4ZE6dX/yvfHuhP36PriEp+wpc+jRldvgGG/xq+lxIRQNjqUTw+8ztG9kUp1HkallU66uRJ4d2oBLosO8uZoFgG1nZnasuymBq9fLihol+y0Pi05Ok/OgI1gX1PXzcAjkkpW2VziS+lsuj1yPRUQte/z6Ndq0GroVDXqVg0HMyQk5v45eZJ/JxLsrRuV5z1/Mbv+L1oPvn9EpdDHtO2XCHmvFOewjZqIYTcLJMHcxqgAuACJAJXpJThuqjvVVQWvZmkhyd4uLwtSbcikCmwzq0iS0s3Zla9HrTT496Y/3YrIp6uy89xLjiWAbWKMa2Vp7oeyqWyu/FpMxkT++4mY8gLAFLKwa97wpyggk1/pMWGETi3A4m3jmLf5nMc3vka8Y+nhVFJCXQ7uII9D2/S2NaWzwJ/wDwlmRnyMz7v0RtPJzUML796w8anv1aY0gcqi7Lmyd3tRO4bSHpCCNaVhmJT/Us0Ri/vkh2VlMDAExtZG3CBqvaF+bVuV0pbP7/UeMK1A4SuGEJy4CXMS9fFqfv3z/XEzAkpaVrG7LjG7EN38Xa2YkX3SpRT+ZZrvMacT7uAnlLKkKevnYFfpZRNs7vGl1FZ9Gbizv3CwyX90MalUaBSM9z6beDXe5cZdGIDRhoDJlRsRv+yNZ9r/NYnqelaZh+6y1e7bqARgq+blmZwbXc170ou9a+VgEsAnwKNgFtABBmrApcCngA/AUullLpZieMFVBa9ufQnEYRt68bjU/tIi9ASbWbNlyUaULxGF2ZXa4ulUe5Y6TI5LZ2xO64z+9BdKrhYsapHJco4quuh3Ca7G596vmi7lHLp654wJ6hg0y/a1GRCfxtAzKFFWFZqi0vfZRiY/R0yWqnlx2vH+PTMdkw1GsYmn6RN3BFmx7+Hb5PP6VW1SK4Z16y8PW/Y+HROSlkpu2p6XSqLsk6bHEv04bE8vvILhjYe2DdagJlb3Vcet+buBQae2MCTtBQmV27JQM9aaMSzN1VSm07MwV8I//1z0uOjsKnbG8eOE5+Zjy6n7LgWxodrLhCXlMa01p70r1lM5Vsu8BqNT9eklGX/8VoDXP3nNl1QWfTmkiP9CZzXkJSAMAwLOlF01AECLQoy+MRG/gy+QQU7F+bXaE8Nx2K6LvWl7kU/YdDGy2y/Fo6PixULOnpTtYitrstSXtO/Gp9WAT8Ch+W/buiEEI5AN+CRPt2vqSz6b6Q2nZgTE4je/y0pwcbIhER2OZRilXc7Zjb9hFqF3HVdYpZt9w+j1+rzJKZqmd7ak77Vi6LRqOuh3CJbG5+ensAMKCKlvPG6J8kpQojWQGsPD48+t27d0nU5yj9IKXm0Zx6hK4dh4lyGwkM2Y1zo2bmdbsZG8MHh1ZyIuE8zowS+jlrJ8YRKXCz2LbM7VFUTZuYzqvEpf0oMPEDknk9Ii72LZfm+2NWehMbk5UNbQp7E0ffoOnYEXaOBUwkW1elM0QJ2z+2XnhBDxOYJRO+Zi8bYHIe2X2LXeNAzq3LmhLDHyXy45gJ/XA+nRRlHFnf2wdHSJEdrUF7PazQ+zQNKAquebuoM3JZSDsrO+l5FZdF/o01N4OGytsQd2QvCEJcPf8a6Zk823r/CsJObCHoSy4clqzLZtyX2pha6LjdTUko2XA5hyKarhDxOYljd4kxsVkYNe8lF1JxPCsCTgD8I39GT1IcJpISkkoTgx2LVcWk2ki98W2Ckx70x/yk4NpFeqy+w91YkdYvbsfDdCpRyKKDrspQsyO6eT62B6YCxlNJdCOEDTJBStnntSnOACjb9FX91L8HzOwHgOmAtBcr5PfN+ulbLjCsHGH/+T6yFlq/jtlE0MZVp8itm9WiDt4t+z6+gvD36NuxOCGFBxiqfKcABKeWKVx2jsujNaFOf8Oj4V8Sdn4OBhQv2fvMxd2/+0mOklCy+dYrhJ7cgBMyo2oYPS1Z9Ya+i5JAbhK0aTvzFHRgXKkmhbjMpUKFljvZAklIy/+g9Rm3zx9rUkCWdfWhetlCOnV95Pa+52t07/GNRBCnlxuyrLGtUFv13UkoeHf2OsJWfIRO0FKjYDJcPl5JkZs03F3Yz++ohrIxNmezbkg9LVnmuB6Y+iUtK5dPt1/jp+H28nCxZ1q0iFVysdV2WkgWZzPn0DfC1lDLt6Wsr4Hsp5Qe6qPFlVBa9Pamx94j44z0S758gOcIKIqK5bV6Q9b5dGNfhS8rY5Hzv7jchpWTxqUBGbr1KUpqW8U1KMaJeCYzU0GC99qaNT1n9t/oVUBWIAZBSXgCKv+7JFKVAOT/cx5/C0MaZB9ObEr17Lv9sADXQaBjt3ZBTrYfiau1Mf4uW/GJTnq+NRzBqwWwWnrhPVnvrKfnSp6+zsxBisRAiXAhx5V/bmwkhbgghbgshxjzd3B5YL6XsA+hlw3teoTEyp2DdqTh3OoTG2JKwzW0J39mL9MSoTI8RQvBRqWpcbDeCygXd6Ht0HW33LibkSdxz+5o4l6bI8O0UHr4DNBoCZ7XmwYzmJD+8lp1f67l6B9Z25/SQOhSyNKHlolMM3nSFpNT0HKtByR5Syo1SymFPf55peBJCHNdVXcp/I4TArvYY3McdwbiIHfEXdnJrRBGS981nSuXmnGs7HC8bJz4+uo462+dzPipY1yVnysrUiB87eLP9o6pEJqRQ9fvDfLfvNuladX2VSxkCJ4UQ3kKIxsBp4KyOa3qGEKK1EGJhbGyuWLsqVzCyLoZz54M4tl5MgdIFMC5ugBvJjDk0n+2TG/LL6S254p5JCMFH1YrgP7oBLcs6Mm7Hdap9f5hzQTG6Lk3JBlnt+XRCSln9n70KhBCXpJTe2V7hG1Ct6vovPfExDxe+x+Nzm7Gp1xvn9+c/N/QlJT2NiRf3MOXSXhxlIpPid3ImuiZRxQfx47s+WJka6ah6JSdk8nSvJDAZ8CRjUk0ApJRv1BguhKgLxAO/SSm9nm4zAG4CjYEgMi7iugJtgT+klBeEECullN1e9fkqi/47mZZMzOkpxJz+Do2pHfYN52Lh8c5Lj9FKLfP8jzL27HbMDY2ZX6M9ndx9Mvn8VKL3zidi01dok+Ip2HwUjh0nInKwy3pSajpjdlxjzuEAvJwsWdG9EuWdVS9PffK2hrroalEElUVvlzY1gYgdg3i0+1e0jyXGLiVx7bsS02KVWX7nHKNPbyUyOYEBZWrxdaWmWBvr7wpzkQnJ9Ft/md8vh1Db3Y6lXSriXvDlCz4oupNZFgkh/IBtwCOgrpTydo4XlwUqi7KHNiWe2DPTiDk9k9hQiSY0iURhwF6fd+j1wQ+4WD4/FYG++v3SQwZtvEJEQgoj6pVgfJNSmKmhwXonu3s+XRVCdAMMhBAlhRBzgWOvezJF+T8DM0vcBm3Avs3nxBz8hXuTG5AWE/rMPsYGhkyo1IwjLQdhbeXGBwXaEVsohBrBw6k7eyfng9XTk3xoCRmTa6aRsYT5b8DyN/0wKeUhIPpfm6uSMUfLXSllCrCajIanIMDt6T6qL3AOEYYm2NYYj2vXExgWcCV8W2fCd/YkPelRpsdohIbB5epwts1wPCwL0vXAcrodWE5UUsJz+wpDIwo2HYrHd7ewqd2TqO1TCJzVmvQnOZcvpkYGzG7rxY7e1Yh42gvh+8N3c8UTS+W1qX+peYDGyIJCbRdTdNxxzLyKkBJ+i4CvqhCy+CO6OZfgWvtP+aR0DeZdO4rnhqmsvHNOb/+e7S1MWPt+ZZZ29eFSSBwVZh5gyakHeluv8rynD9LmABOAA8BcIYSLTotScpTGuAC2Nb/G7YMruNRpi3lpwROrArQ7u4YzYz3549AyXZeYZR28Xbg6qj7v+7oxdf9tfGYc5OCdSF2XpbwlWb2BGgSUA5LJmEQzDhiaTTUp+YTQaHDs8A1uA9aS9OACd7/yJfHu6ef2q+pQhDNtRzDYsw7LTSoww6EMfcy+pscPq5h/NEBdIOUvZlLKvWT02rwvpfwKaPmWz+EKBP7jddDTbRuADkKIH4GtmR0shOgrhDgjhDgTERHxlkvLv4wdvHHpfASb6l+QcHMdwcsq8iRg50uPKWPjyOGWA/mmUjN+v3cJ703T2RH44qF1hlYOuHy0COdePxF/dTcBE6qTHJqzC1c0K+PIxeH1aFzSgWGbr9Lyl5OExiXlaA2KomSdmUs1ig2/RaH3x2HgaEjMoSXcGlkUTq9jTvV3ONl6CIUtbHjv0Eoa71zAtZgwXZf8QkII3qtcmIvD6+HrZsNHay/S/tfThD9O1nVpStZMB96VUk5+2iv7Z2CfjmtSdMDIqiiOLVbg9t4BSlbxILq4FbYp8RRd9D5rvq3Po6jAV3+IHrA1N2ZRJx92f1yddClp8ONxPl5/kdjEVF2XpvxHWV7tLjdRXTpzn6QHFwn8vh1psSE491qITe33X7jfgZDbfHjgNx4kJvBByiXuP/TFxqMDC9+tgI2ZGoaXl2Qy7O4YUBtYT8aFVTAwRUpZ+j+cpxiw7R/D7joCzaSUvZ++fg+oJqUc+LqfrbIoeySHnSNi14ekRvlj6fURdnWnojG2fOkxF6KC6XloFVdiQvmoVDVmVG2NpZHpC/dNuH6QoLkdkFKL24C1FCjXKDu+RqaklCw4fp8RW65iaWLIos4+tPJUk5Hrkhp2p7xKStRVQtd3J+HCJeQTiZlHdVw+XIShcxl+uXmSz87uID4theHl6vFZBT8sjPRzhUutVjL78F3G7biOjZkhP79bgdblnHRdlvJUJtdGBlLK9H9tKyilzHyiRB1RWZRzpNQS77+MsEOfc/I+eIU+JMnQBE2rcfi2GZuj0wv8F09S0vjyzxvMPnQXJ0tTfuhQnjYqk3QuW4fdCSFKCSEWCiF2CSH2/f/n9ctUlBczLVIB969OY1ayFg9/7knoyuHI9LTn9qvv7MHFjuP4oHh5FptU4EGRUCwefk+VWfs5/SAm5wtXctoQwBwYDFQGegAvbql8c8FA4X+8dnu6TdETJoUq4dr1JNa+I3l8dQnByyuTGHjwpcf4FHTlVJuhjC7fgCW3TuGzaQYHQ++8cF+LMvVw/+o0RrauPJjejOjd83K0h6UQgn41i3FmaF1crE1ps/gUAzdcJlFNRp4XvKfrApTsYVywHIX7nMW590yMi5mRGHCSO5+XJ3LdWPq4e3Otw6d0L1GJ7y7vw2vjNDbdv6KXPbc1GsHweiU4PbQOzlamtF1ymj7rLvI46flrMkW3hBA9hBCafzc8AUgpo4QQJYQQtXVRm6J7QmiwLNeT4h/507x1Tx54uRJgboPFxi848mkZ4m6f0HWJWWJubMj01uU4PqgOBS2MaLfkNF2WnSVM9czMlbI64fhFYAEZKyf8FXBSSr1aSeH/VKt67iXT0whbPZLoXd9j4emH64A1GBYo+MJ9d9y/RO8DvxKVLmmXGMT+wHcY16I6Q+q45+iS6Ur2yOTp3rtSynWv2vaa5ynGsz2fDMmYcNyPjEan00A3KeXV1/1slUXZL+nhcSJ2fURazG2sfAZiW2siGqOXT5Z7LOweHxxezZ3HUQwpV4eJlZpjZvh8z8n0xMcEL+hO/IWt2NTvi/N7c59bGCG7JaelM27HdWYduotnoQKs6F5JLYmuA696wieEOCKlrC2EeMyz8zoJQEopdTqDvMqinJUaG0D4jt7En9pPerTE0MYZp/d/wLJSW46G32Pg8Q1cfhRCC7eyfF+9HcUtX3ydo2vJaemM//Mm0w7cxt3OnN+6VqRmsdwzcXFe9M8sEkIMAT4k4/7sLBBBxmIsHkA9IBIYI6XM2THkL6GySHdSYwO4f3Asqy5do+79OxRMSUBT831Kd5+FQYHc8XedkqZl6oHbTNx9CwtjA2a2Kcf7vm7qvk8H3rTnU1Ybn85KKSu/UWU5SAjRGmjt4eHR59YtvclZ5Q3EHP6VkKWfYGjjQuEhmzEtXP6F+0UnP6H/zumsi46jbHo0yYGelCtWl8WdfbAzz9mbROXtyqTx6ZyUstKrtr3GOVYB9QF7IAwYL6VcJIRoAcwGDIDFUspvX/NzVRblIG1qAo+Ofk7chfkY2njg0GQxpi7VX3pMQmoyY85s54frxyhj7civdbpQxaHIc/tJrZbw3z8nattkzMvUw23gegwt7bPrq2Rq141weq2+QPSTVCa3LMOQ2sXRaNTFVk55W8PudEXd8OU8KSXx/r8RsX0oyXfjkIlaCni3wOm9uQj7osy/dpTx5/4kTaYz1tuPUeUbYGJgqOuyX+jw3Sh6rjrPg5hEPm3owfjGpTE2VOtu6MK/s+jpCr0NgVqAM5AIXCNjdd4HuqkycyqLdC8x6BBrd3/NvVuRtA++TLppAYp2n41N7V4ITe74u74W9pi+6y5y9N4jmpRyYEFHb4rZqVU6c1J2Nz59BYQDG8mYdBwAKeW/V4nSCyrY8obEO6cInPMO6YmxuPZZilWVDpnuu+r87ww6f4AEDCj1yJCYxKas7lGZGuoJXa71r6d7zYEWQCdgzT92swI8pZRVdVDiK6ksylmJgfuJ3NWXtPhArCuPwLb6lwjDl8+rsufhTT46vIaQxMeM9W7IZxUaYfyCG8DY4yt5uOjDjAbxoVswdfPKrq+RqciEZHqvvciWq2E0KeXAki4+OFu9eN4q5e16nYuspzeDhYC//kPS9U2gyiLdSUsIIXLvIB6f2EhqKAhhhH2bzyjYYjQhKUmMOLWFdfcuUtLKnjnV36GJ6xtPYZit4pJSGbblKktOBVLR1YrfulainNPL59pT3j7VEK68DVKbzp2Li5hwaCNNb1+iYtxDNMUqUuyjJZgWqaDr8rJEq5X8ePweY3dcQ6uFb1uUYWAtdwzUg7kckd2NTwEv2CyllMVf94Q5QQVb3pEaE0LQ3A4k3j6OfevPcGg/IdNW+YdRd/lo+2R2pVvjnppE8P3aTGjky4h6JVQPgVzoX41PFQAfMpYR/vIfuz0G9kspH+V8ha+msijnaZPjiDo8mvgrizEqWA6HposxcXz5/M4xyYkMO7WZ326foVJBV5bX605pa8fn9stoEG+HNukxrh+vwLJSm+z6GpmSUrLwxH2Gb7mKuZEBizr7qIk3c0BWL7KEEIOA8WT0pNQ+3SyllN5vsRYL4AcgBTggpVzxqmNUFulewq0NROwcSPLtMNJjtBgV8sD5/R8o4NWY3cE3GXRiA7fiIulYzJuZVdviaqGfw2s3Xwml77qLxCWnMblFWQbXdlfXWDnoX9dGc3l2mO8zpJSDc6ywLFJZpF/Sk2L5fvdETl2+wOC7R7BOS8bOrz+OHb7FwFw/M+jfHjx6Qv/fL7PjejjVitjwSycf1TCeA7K18Sm3UcGWt2hTkwn9bQAxhxZRwKcVrh8vzzQQtWkp/LhzHOPCk0nDEE1oUeo6Vmdp14rYW+jnyjLKi2Uy7M6IjN4ERaSUN3RTWdapLNKdJwF/ELnnE9ITI7CpOg6bKp8iDF6+Iuam+1foe3QtiempzKrWjo9KVn1uHoHU6GAC57Qj6d5ZHDt8S8FWY3Qy18C1sMd0X3GOCw/j+LhGUWa09sTcWD+H7OQFr9H4dJuM1TFfa5UpIcRioBUQ/v/5555ubwZ8T8YQ4F+klFOersAZI6XcKoRYI6Xs/KrPV1mkH9KTHhF9aDSxJ5aQ9tAAbWIKVlU7UajrTLTWhZh++QCTLu3BUBgwsXIzBpatrZdzmYQ9Tqbvuots9Q+joYc9S7r4UNjGTNdl5Qv/anzq+XRzLcCTv3uGvwv4Syk/0UGJL6WySD/5B57lk90LaHDrNJ0eXkRjYYNz97lY1+yulxn0b1JKVp0PZujmq8QmpTK2YUnG+nlgYpg7VvTLjbJ7tTtzIcTnQoiFT1+XFEK0et2TKcqb0BiZ4Pzhzzi9P5/4yzsJmFCd5JAXtztoDI0Z0Go6Jyr7UkkbyhPnII4lb8V79i4uPozN4cqVbNAMuADsBBBC+Aghtui0IkUvmbs3x/W981iUepeYExN4uKYOKVEvnzO+XVEvLrQbQQ2HYnx8dB3v7v+N6OQnz+xjZOdKsXGHsKramfD14wj+qQfalMTs/CovVLaQJccH12Zk/RL8dPw+lWcd4nywyjg9EAi8yb+IX8nIt788Hb43H2hOxo1lVyGEJxkrcAY+3U0tgZiLGJja4tDkZ1x77sTctzCGzhrizv7OnTFliN89l3Hl63PlnVHUcXJn6MnNdNi3lJjknM+XVylkacKmD6qw8F1vTj54hPf0A6w4F6SXq/flZVLKpVLKpYA3UF9KOVdKOZeMBVN8dFqckqt4Fq7M3l4LSGvaj+6VunFDGPJw4XsEfFOV5GB/XZf3SkIIulVy4+qo+rzr7cKE3TepPOsQJ+7r5cCIfC2rs4otIaN7d82nr4OBidlSkaK8gBACO7/+FB29h/T4KAK+rsrjizsy3b9shZ7savMpE+RlUs3iiXE6QO1fdrL/dmQOVq1kg6+AqkAMgJTyAuCuu3JeTAjRWgixMDZWNQbokoGpHY7NluLYcjVpjx8QvLIaMWdmILWZ36+7mFuzs2kfpvq2YlugPz6bZrA/5PYz+2iMzXDttxKHjt8Sd3wl9ybVI/XRw+z+Os8xMTRgaitPdn9cncfJ6VSfc5jpB+6g1aobwJwmhBguhBgO3AUOCCHG/n/b0+0vJaU8BPx7Hs2qwG0p5V0pZQqwGmgLBJHRAAVZv45T9IhZ0Ua49bxIwebDMCmtQZinE7ZqOHfHV6ZQyHW2NvqImVXbsD3Qn6pbZ3MhKljXJT9HCEHvakW5MLwe5ZwseW/lebouP0f0kxRdl5Yf2ZIxB+b/FXi6TVGyzEhjwLf1P+bHLt8wuuaHTCjZiJh7F7jzuTcxR5fqurwscShgwvLuldj6YVUeJ6dRa94Rhm6+Qnxymq5LU57K6kVLCSnlVCAVQEr5hIzlgxUlR1mUqUfxr89g7FiCwFmtiNw2JdMnbWaOPozptopdVg+w5zG4nqD50j2suaB/F3FKlqVKKf/doqN3d9pSyq1Syr7W1rljvHxeZ1GyPW7vXcC8WHMeHRlLyLqGpMbcznR/jdAwonx9jrUcRAEjYxrv/ImxZ7aTkv73xYsQAofW4yg8ZBPJD/0J+KoKiXdP58TXeY5fSQcujqhHq7KFGL3Nn4YLjuEf+lgnteRjlk9/HgC7AeN/bHvTySdc+buHE2Q0OrkCG4AOQogfga2ZHSyE6CuEOCOEOBMREfGGJSjZRWNkQcF603F9/zDmFT0wdjcgNeo2976tTcji3gwo4sn+5v1JSk+j1va5LL55Stclv1AJewsO9q/Ft83LsOFyCOWnH+DPG+G6Liu/mQKcF0L8KoRYCpwDJuu4pmeoh3K5R41CxTnXaQKWdXvRtFofrhcoyMOFvQhdMzTX9G5s6VmIKyMb0K9GMeYcDqD89APsvqn+P6gPsjrh+DEyunAelVJWEkKUAFapFaYUXdEmP+Hh4t7EnViFVdVOuPRejMbE4oX7Sm06Z/YMp3VgCmkY8/h2Naa2qM6QOno5X77yVCZzPi0C9gJjgA7AYMBIH+c1AJVF+kZKScKNVUTtH4pMT8GuzmQsvT9GiMyfwySkJjPi1FZ+vnmCygXdWF6vO6WsHZ7ZJynwMoGz25AWG4rLR4uxrtE1u7/KC0kpWXI6kFFb/XmcnMaI+iX43K8kFiZqLqj/6nXnNhBCWJEx0XiWWwGFEMWAbf+f80kI0RFoJqXs/fT1e2TMJzXwtYpHZZG+k2nJxJz+jkcnppAeriE1NAkDCztc+/7Gk5K16HFwJXtDbtGrZBXmVW+PmeHL56/TlfPBsby38hz+YfH0r1mMqa3Kqrno3rLMskgI4QRUe/rypJQyNGcryxqVRbnL5vtX6LP/Vz6/uoVG4bew8K5HkSG7EXqaQS9yJCCKPmsvciMigV5VCjOjtSe25sa6LivXy9Y5n8hYuWUnUFgIsYKMm7/Rr3syRXlbNCbmuH6yAsfOU4k7vY6AibVIibj3wn2FxgDfxrPZWKoIkjTsPY7x+Y4jjN7mr4an5D6DgHJAMrAKiAOG6rIgJfcQQlCgTDdc3zuPqWsdovYPIXRDC9LiHmR6jIWRCQtqdWR9w54ExEdTectMFt08+czTP9PC5XEffwoz9yoEL+hG+PrPkFptpp+ZXYQQfFi1CNdGN6BHJTe+23cbr+kH2HJVL+9B8iQhhK8Q4jL8j737Do+qWOM4/p303gNp9N5C6L13qUoRkCoIYhdQUbGBXAuogAWk2AUEQbr03nvvnSSQSnrPzv2DiKCEJMhms8n7eZ48lz3nZM975ub+7tnZOTMcA44rpY4qpeo85NuFACXueh2QtU0UMsrKFvdG7xIwcC8OgYHYVlSgUrn2WSf08g9Z3XoI42u25Yfz+2my6ksuxBXMKQRq+bty4JXmvNK8LN/sukLNz7byx/EbZjNawlwppTZqrW9qrZdl/dxUSm00dV3C/HUvVZ2tPV5jet0BzC7VgMRjW7nwdhnS48znvqJpGU8Oj27BuNbl+flgMNUmb2HpiRumLqvIyvVqd0opT6Ahtx+326O1Lpj/z4f0qhc1CcfWEDyjH8rCkoAXFuFYpVW2x249MJuux47jrVNJvFiP9tVrM6dPEDZWMm1GQfOwPeoFiWRRwaW1Jv7Ed0Rvew2UwrPFZzhVHfzAVV1CEmMZsn0+m25c4IlSNfi2SW88bB3+fs+MNG789DwxW+fgXLs7fiN+xtLedMv9br8UxXOLj3MyLJ6uVYszrUd1Sns45PyL4l/ysNrdMeB5rfX2rNdNgW+01oG5+N3S3DvyyQo4x+2R5yHAfqC/1vrBM+ffh2SR+dCGTOIOTydqx3gyQi3IuJmAfbkG+I+az8bUFAZtm0+GwcB3zZ7k8VI1TF1utjZfiOSlP05wMiyeZmU8+KxbNeqWcDN1WWbvH6vd2QEOwGagJX9PieICrNFaVzZJkQ8gWWSeIlMS6bXpB9yPrmTC2bVYO9hScsyfOJRraerS8uRQcAzDFh7laGgcvQN9mf54DYo7y2roD8MoI5+yboQA0FpHaa1Xaa1X/tXxpG4LyPYNhMgHToEdKfPePqxcinP103ZErZue7bdsLeo+w+I6zbmh7PEst5vdJ3bS7bt9xKfIRHTmQClVUSk1Sym1Tim16a8fU9clzI9SCpcaw/AfcAjbYrWJXD+CsOWPk5GY/bdh/o6urO0wgo/rdmb5tZPUWvoZW+6ajFxZ2eA7dBY+A6YTf2QlVx4wIjM/NCvryaHRzfm0S1U2XYik2uTN/G/jedIy8n9UVhGS+VfHE4DWegeQ4//BKKXmA7uBSkqpYKXUMK11BvACsBY4DSzMa8eTzLNifpSFJa51XsW/3w4cqpbEprQVKdePcOmdIJqEnuBAt1eo5OpNr00/8vr+FaQ/YAEFU2pV3ovDo5szo2cNzoQnUH/adgbNO8T1mIK3ep8ZGwkcBCpn/edB4ACwDPjShHWJQsbLzpF1HUbi2WwozwT2IiE1kyv/a0301k9MXVqe1A5wY9/LzZjYsRLLToZRbfJmfjkoK3XmpweOfFJKLeJ2B9UybgdaBGAHlAdacfvbuPe01uuNX2rOlFJdga7ly5d/5vz586YuR+SzzOR4QmcNJP7QMlybDsF38AwsbOzue+yKk6vpvXcDNQwRWF6tSoZHE1YNbyC93wVINnM+HQVmcjuP7txxa60P5nN5DyRZZF60NhB35Btu7XwbZWmHR4spOFUZ8MBRUAcjgxmw9VfOx0Xyeo1WfFC7A9YWlnf2J5xYT/DXfVCWVgS8sBjHys3z41KydT0mmVeXnWDJ8ZtULubEV4/XoHUFL5PWZE7yMPJpKmDP7ceCNfAkkAL8AqC1PmTEMrMlow3MkyEtgagtrxB3+EcyQu3JjInHvdVI3J6czOtH1vPNmV00K16GeS0H4OdQcBe4iEtJ5+NNF/hi2yUUMKZlOV5vWR5nO5kPKq+yuTd6F5iqtY5TSr0D1AYmmipvHkSyyLxprfni5Fa+2fIjc44vxjs1HrdW3fAb8DvK0nzmgQI4dTOe4YuOsufqLTpXKcY3PQMp4WZv6rLMxsOOfMrxsTulVFXgKaAJ4AskA6eA1cDvWuuUvJdrXBJsRZc2GIhYNoHIpR9gX64BAS8uwdrd777HLjy1kaf2rqZRRjCeIWU4btuONc80pLzX/ScuF/krmxusg1rrh50/Jd9JFpmX9FvniFg/ktTQndiX7oRXm6+xcs5+cG9ieiqv7lvO3HN7qesVwC/Nn6LCXZORp948x/Wp3UgLv4jvoG9wb/lMflzGA60+HcZLS09wKSqJp2r7M7lLVXxc7t9JL/6Wh86nzQ/YrbXWrR9hWbkmWWTeEs7MI2L982SEppEemoRtQHUCnvuNxSkpjNy1CGdrO35t8RStfMubutQHuhqdxNt/nmHe4RCKO9sysWMlhtYriaWFLKCdW9ncGx3TWgdmPeY7EZgCvKu1bnDfNzEhyaLCYcW1k7y4fhZTjiyiStwN7CuXocTzW7B2KWnq0vIk06D5audl3l59BksLxaddqvBMg1JYSCblyGidT+ZIgk3EHfiDkFkDsbRzJuClJTiUb3Tf474/tYXhe1fSLv0iFSJ9WJjag5XDGlCvpFv+Fiz+5R/zGnhkbX4JCAf+4Pak4wBoraPzv8KcSRaZn79HQY0HCys8m0/GqdqQB46CWnzlGCN3LiLNkMnUBj0YWqHeneMzE2MIntGXxONr8Wj3EsX7fYayNO23/cnpmXy86QKfbLqAnbUFH3aszKjGpeUD4AOY+xx0kkXmL/3WecL/HEjyhQOkh9iAAXwGfsWNGp3ovflnzsVFMLF2R16v0QqLB6zgWRDsvXqLMStOsuvKLWr4OjOlazXaVfTO+RdFdp1Ph7XWtZRSHwHHtdbz/tpmojKzJVlUeByLDqX32m95/tBvtA0/i1Vxe/xHLsaxXCdTl5Znl6ISGfn7MTaej6RlOU9m9a4pgxFyYMyRT5WB7oB/1qYQYJnW+kyeq8wnEmwCICX4BNendifjVjA+g77BvcWw+x43/cRmXt2/iu5pZ2gQ58CkW4NYOKg+HSsXy+eKxd3+0fl0mduPsNzv07HWWpfN1+JySbLIfKXHXCRyw7OkBG/FvmQ7PNt+g7VLqWyPD06MYci2+Wy+eZFepQOZ2bgX7lmTkevMDMJ+e53otV/gWK0dfsO/x9rDP9v3yi/nIhJ4YclxNpyPpLa/K9/0rEH9ku6mLqtAyukmSyk1AJintb7vhFpKqXKAb9YcUPlOsqhw0JlpRO8cT+zeL0gPtSczOh6Xhv1weWoazx5ay2+Xj9C5RBV+bNbvTv4UVFprFh+7wRurTnM5OonHKhfj0y5VqepjukUazEE2nU8ruf35rB23H7lLBvZprWuaoMQHkiwqXMKS4+m14Tvq7ZvH8Gv7sHBWePd+A49mH6LumorAHGitmbvvGmNXnCI908CEDpV5pXlZ+WIuG0bpfFJKvQH0AxYAwVmbA4C+wAKt9ccPUavRSbCJv2QmRBP8TV8ST67Hs8ubFOs16b4jGP53dAPvHFpD/9RjdEzOZOSN5/mmTz0G1S1xn3cV+SGbGyy7fz7qe79tBYVkkXnT2kD8sVlE73gTUHg0/QjnwGdQ2YwqyDQY+OzEFt45tAZfBxd+at6P5j7l7uy/te07bv70HFhY4d1tPB4dXsXC2rTzzGmtWXT0Bq8uP8HN+FRGNCzF/zpVxt3BxqR1FTS56Hx6GXiavyf9vXuOzBZAJDBOa52vk8DJ/HOFU9LlPwlf+zTp126RHpqOtXcZ/EfN5/uUVMbsX4G/gwsLWw2mjlfBXxMoNSOTL3dcYdKGcySkZfJMg5K8374SxWQOzvvK5t7IAejI7VFP55VSvkANrfU6kxT5AHJfVPikZKTzzM5FpOz4gffOb8DCFlybNcPn8YVYOhY3dXl5FhKbzHOLj7PiVBj1S7gx98kgqkmn+L8Yq/PpHFBNa53+j+02wEmtdYU8V5oPJNjE3XRmBjd/foFbm7/Ftckg/J6ejbK694OV1pq3Dq7m0+ObGZF6gO5pCfS9PoZxneryRqvyD3zkRhhHNjdYh7TWtXPaVlBIFhUO6bFXiNw4ipRrG7ELaIlXu5lYu2Y/2G5/xDUGbJ3HxfgoxgW25r1a7e9MRp4WdpGwBWOIP7QM62Ll8HlqKk41O5s8Y+JS0nlv7Vm+3HEZTwcbJnetysA6ASavq6DIzU2WUsoSaM29c2SeBv7UWl8zfpXZkywqfDISQolYM4TEM5vICLHFkJpO8T6fcKH24zy55RfCkuOZ1vBxnqnYwCz+dxyZmMoH684xc/dVHG0sebN1BV5uVgY7a/MaPWFs8giwKIi01nx8bBOrNsxg6qmV2Kl0HKsVw7fPIuz8m5q6vDzTWvPbkVBeWnqC2JR03m5TkXGty2NjVbAfac5Pxup8OgN00Fpf/cf2UsA6rXWlPFeaDyTYxD9prYlc8T8iFo/HsVo7Al5cjKW987+OeWHPEmae2c3o1L30Sg/jieBx9GxUny+6VZNhl/nsH4/d+XD70d9fgP78/fidCzBTa13ZNFXen4w2KHy01iSc/J6oba+DIQP3ppNwqTkq21FQCempvLJ3Gd+f30d9rxL80uIpyrn8vbpcwvF13Pz1ZdJunMEpsBPF+3+Bra/p/y/1SEgszy85zu6rt2he1oOvnwiUb/yQD3yiYNKGTGIPfEr09g/ICLUmIzIBp5qdsRv0NYMPrWNdyFkGlKvDN42ewNHEoyxz60x4PG+sPM2KU2GUcrfno8eq8GSQn1l0oOUHySJRkC2+cowPVk9n+tHf8UqLx660JV6d/4drndHZ3i8VZBEJqbyy7CTzD4dQw9eZuX2CqFvCzdRlFQjG6nzqCHwFnAeuZ20uye1h5C9ordc8RK1GJ8EmshOz/QdCvxuOXYlASoxehbWb7z37DdrA0O2/8cvFg7ybtpeeaRfpE/om1as04qd+teQbuHz0j86nwcAQoC6wn787n+KAH7XWS0xSZA4kiwqfjPjrRG58nuQra7D1b4p322+xds9+EPCiy0d5dtfvZBgMTG/Yg0Hl6975EKUz0one8BURS9/HkJaEZ/tX8Or+Dpb2Lvl1OfdlMGi+33+dN1adIi4lg1ebl+WddhVxsi26y6Ln4rG7L7k9L919aa1fMkphuSRZVLilhO4ibPVA0q5cJz3EgJVLcfye/YUvUtP54PB6qrkVZ2HrQVRyNZ+5LDedj2TsipMcCY2jYSl3PutalUalPXL+xUJOOp9EQXcoMpihq6fzzv6fqRJ3Ext/C1wadsOr/XdY2pnnvJIrTt5k1OLj3IxPYXSLcnzQoRL2RfwzoTEnHLcA6nPvhOP7tdaZea4yn0iwiQdJOLaG61/1wsrZi5Jj1mDrd++gmQxDJk9u/pml104w2XCALolHeTpsLNb+rfhjaD3c7K1NVHnRks1jdz211otNVVNeSRYVTlprEk7/TPTWseiMFNybTMAl6MVsJ9e8nhDD4O3z2HrzEn3KBDG9YQ+87Zzu7M+IDSP897eI2f49li7FKN7nE1wbD0RZmPZbwsjEVMatOsN3+65Rws2Oqd2r06O6T5EcgZCLzqfBWf9sAlQFfst63Rs4pbV+1sglPpBkUeGXmXKLyA0jSTj2B+khthgSk/Hq/g5H6vZhwPYFpBkymd2kD73LFLg5qLOVadD8dOA649ec4UZcKn1q+vHRY1Uo41mwJ1M3Jul8EuYgNCmWJ9d+S+8dc2gbeR5Lbyvsq5SmeJcF2BavY+ryHkpMcjqvrTzF3L3XqODlyOzeNWleztPUZZmM0TqfHnBCJ611wkP9spFJsImcJF8+yLXPH4PMDEq8ugKHCo3v2Z+amUG3Dd+xKfQ8X1kco23MDl6Pfo4LLp1ZPbwB/q72Jqq86PjHyKcBwK86m8Ay9UpS2ZEsKtwyEkKJ2vQCSZdWYuvTAK/2s7DxqHLfYzMNBiaf2Mx7h9biZG3LhFodGFm5EVZ3dVglX9rPzV9eIvniHuzK1sd3wJfYl6ufX5eTrZ2Xo3luyTGO34inc5ViTOtRnbKeRWsJ4tzeZCml9gBNtdYZWa+tge1a64bGrvFBJIuKBq018cdmEbV5DOkhmozwJBwqNUcN/Ib+RzexJ+IqL1Vtxid1O2NjaT4jGRNSM5iy5SKTt1wg0wAvNSvD220q4FoEvwyUzidhLpIy0hi2dT4lNn3JkOCDKA8HbEuBV6vPcA4cabZfZG08H8GIRce4HJ3EqMal+fixKjjbmU+ePiqm6Hy6prUu+VC/bGQSbCI30sIvcW1KR9Kjr+M/aj4udXrcsz8xPZVO62azL/Iac20v0PjmSqYmDGIpfVjzTCOqFJd5UIzpH51PBXIlqZxIFhV+WmsSzy4gasur6PRE3Bq+c3tuA4v734icjgnj5b1L2Rh6nhruvkxv2OOeFfG0wUDsrl8IX/gGGbE3cWs2lGK9/oeVm09+XdJ9ZWQa+HLnZd5be5aMTM1HnavwYpMyWBSRufDy0Pl0FmiktY7Oeu0O7DHVHJky/1zRlBZxjPA/B5B84RQZIRZY2LlQ7Om5TMiA6ae208i7FAtaDSTA0c3UpeZJSGwy4/88w08Hg/F0sOG99hUZ0bAU1pbmN5fMw5LOJ2FODNrAxCPrObNqMm+f34SFqwt2JRJxqvYkXm1nYGFjnp+lElMzGL/mDNN3XCbA1Y5ve9WkY2Xzeaz5UTDWnE+js9sFvK21LpAPX0uwidzKiI/k+hddSL60H5+BX+LR5rl79semJdN2zUxOxYTxq0sYNa/8yu+pnfk0YTjLhjWiscw/YDT/DLWCvJJUdiSLio7MxDAiN79E0oU/sCleB+92s7Hxqn7fY7XW/HH1BGP3L+dqwi36lq3Fp3W74O/o+vf7JccTufxDotZ+gYW1Hd493sOj3Yv/Wqkzv929BHGbCl5892QQJdwK/0jQPHQ+DQXeBzZz+16pOfCB1voHoxaYA8mioseQnkjU1jHEHZhLRrAtmfGJeLR/he31+zF8zzLsLK34tF4XBpSrg6WJH/HNq0PBMYxdcYotF6OoUsyJT7tU5bEqxcx2JEVeSOeTMEcLLh1mztL/8cmJ5dja2WFfIhlbv4oU67wg23slc7D7SjTDFx7ldHgCQ+qVYGr3arjYFY0RmcbqfEoBJgMZ99n9qtbaLa8nzA8SbCIvDKlJBM/oR8Lh5Xh2eZNivSbdcwMTkZJAq9XfEJwUy+LiGZQ9+QU7MxvzYsRL/DCgMd2rm3ZEQmFl7jdYIFlUFCWe+53IzS9jSI3BrcFbuNV9HWV5/xuRpIw0Pj2+mU+Pb8ZKWfB2zba8Uq05tnc9DpN68xxh814l4ehqbHwr4dN/Kk6BHfPrcu5La83cfdd4ddlJrCwUXz9Rg/61A0xak7HlJY+yVudskPVyr9b6pvEqyx3JoqIr4exCItaPIv1aEhlhKdiVrkPawK8ZfHo3ByKDqeJajPdrd+CJUjWwMKPVqLTWLD8ZxusrT3E+MpG2FbyY0rUagX6mXbDB2Mz13khGYYq9EVcZ88fHTDzwK96GdBwqOGLhmI5n6y9xrjrI1OU9tNSMTD5Yd45PN1+gpJs9P/arRbOyhX8uKGN1Pu0CXtRaH7zPvuta6xJ5PWF+kJsskVc6M4ObP7/Arc3f4tpkEH5Pz75nhEFIYiwtVn9NbHoKy0u74bPvTc5SlQE3XmNSj8aMbFTadMUXUv947K5ArySVHcmioikzKYKoLa+SeG4hNt418Wo3G9tiQdkefzk+ijH7VrDs2gkquHjxRYPudAq4d+6o+COrCJv3Kmlh53EK6opP/8+xKV7eyFfyYBcjExm84DC7rtziySA/vn6iBh4Oph2ZZSx5GPm0UWvdJqdt+U2yqGhLj71ExOqBJJ3dS3qIFcrCBp8hM9noW533Dq3hdGw4tT39mVi7Ex38K5nVCKK0DAMzd1/hg3XniE1JZ2j9kkzsUAkfFztTl2YU5tr59BfJoqLtekIMg1d+wfPbZ1IpMRLHahXB+iKOlfvj2fILs10ND2DXlWgGzT/M5egkxrQox8SOlbC1Krwr4j1sFuX0FcdQ4Go2+8w2+IT4J2Vphc/gGXj3/JDYnT9x7fMuZCbH39nv7+jKuo4jsbO0ote1eOJbf0clywus9HuXSUs38N7aszzs/GkiVw5we64nO6A2cD7rJwgocJ92lVJdlVKzYmNjTV2KMAFLB2+KPfYLxbosIjPxJqELGnNr9/vozLT7Hl/G2ZMlbYawuv0zKBRd1s+l+4bvuBgXeecY56DOlJ10nGJ9PiHpzGYuvlWNsIVvYkgx3bof5bwc2fpcEyZ1qsziYzcInLKVdWfDTVaPKSml7JRSHoCXUspdKeWR9VOav1cLFsIkrF3L4ttnCx5tXsOmQibKNpPQmU9Rf9l77G/8BN8360t0ahKd18+h5Z/fsP3mJVOXnGs2Vha81Kws599szUvNyvLTgetU/GQTkzacIzm9wC7MLUSRVMLJjeU932JR1w/Y5lGa5BNn0Jl1STizgJCfa5F0eY2pS3xojUt7cGR0C4Y3KMmULRepP207x0LjTF1WgfPQE44XRDKkUzwKMdt/IPS74diVCKTE6FVYu/ne2Xcq5iatVs/A0dqGdbXrYbVuIPHpiv433qROYHO+6VkDB5uit+KBMdyvR72griSVHfmGT2SmRBO9dQwJp3/F2rMa3u3nPHCZ4bTMDKaf2s7EIxtI15mMrd6ScYGtcbhrJGb6rVDCF44jdtfPWLn5UfzJT3Fp1N+koxUOh8QycN4hToUl8HyT0nzSuUqhysKcvuHLWhThFcAPCOH2fE8aiAdmaa2/zo86syNZJP6SdGUd4WuHkn41koxwQCs8O43F5bHX+P7aSSYd2cCN5Dg6+FdiYu1O1PEyr0dqz0ckMG7Vaf44cZMSbnb877Eq9AvyLzSLI8jIJ1EYGLSBd/avQi99jwEhh7EqWwc73yQyky7gVG0ons0/xcLWNec3KqBWnQpj+KKj3EpKZ0LHSoxpUQ7LQpJBfzHqandKqRX8+5GXWG6PRvhWa52S1xMbkwSb+K/ij/5J8Ne9sXL2ouSYNdj6Vb6z71BkMG3WzMTH3pn1jdthWN2HlMRInot4mSj31iwaVJfyXkVrGXJjyKbzqUCtJJUTySLxl6TLq4nc8ByZSTdxrjEC90bvYmnvle3xoUmxvLF/FfMuHaKEoxtT6nelZ6nAezqYki7s5ubPL5Jy5SD2FZrgM2A69qVr58fl3FdyeiZvrT7NtO2XqeTtyM/9a1O3hJvJ6nmU8vDY3bvAVK11nFLqHW6P1JyotT5k9CLvX498KSf+JSPxJpEbniXp7Coyo11JvxGFlbs/xZ+cjFXdJ5hxZhefHN9MdGoST5SqwQe1O1DVxCtu5tXWi5GMWX6KQyGx1CvhxmfdqtK0jPnPwyKdT6Iw+fH8flb//i5jz2/C1tISt/otyUjciJVzAN7tZmFf0qRPrP8nkYmpjPr9OIuP36BZGQ9+6FuLMp4Opi7rkTF259M0wBuYn7XpSSCO2x1SLlrrgXk9sTFJsIlHIfnyAa593hkyMyjx6gocKjS+s29n2GU6rptFBRdv1jbrQdqffUmLOMKC5C5MSxzErH4N6VbNvG7UCppsOp8K5EpS2ZEsEnfLTInh1u73iD82CwtrJ9wajsel5iiUZfZPjm6/eYmX9y7laHQorX3LM61hj3s+BGqDgZjt3xO+6E0yEyJxaz6cYr0mYeXinR+XdF8bz0cwdMERbsanMr5tRd5qUx4rM18KPQ+dT8e01oFKqabARGAK8K7WukEOv2pUkkXin7TWJJ7/negto0mLCMMQ7UFGZBj2FZviM2A66b5V+OLkVr44uY3EjDSeKlub92q1p4yz+XTgGAyaXw8H89bqM4TEptAr0JePHqtCOTP+glA6n0Rhcyw6lA82zqXzjjk0jLlGWulaePglkpl8GecaI/Bo9jEWNk6mLvOhaK355VAwL/5xAoPWTO1enaH1SpjVvHrZMXbn036tdb37bVNKndRaV8vriY1Jgk08Kmnhl7g2pSPp0dfxHzUflzo97uxbH3KObhvmUtszgD/bDCJ97wTijnzJNUoz8uZLPNG8DRM6VDL7D12mkl2oFcSVpLIjWSTuJy3qFNHb3iD56lqs3Mrj2fxT7Mt0zvZmJMOQyeyze3jn0Bri01N5oWpT3g1qh6uN/Z1jMhNjiFg2gegNX2Jp74rPoK9xqd/HZDc4McnpvPjHcX49FEKDkm781K8WFbzN8+YR8tT5dFhrXUsp9RFwXGs9769t+VBmtiSLRHYyU25xa8fbxB2fjU50Jz0kDUNyHG4tnqFYzw+JsXHg0+Ob+Pr0TjK1ZljF+rxdsy1+DubzSExiagafbb3Ep5svkGHQvNi0DG+3rYCbvfktiS6dT6Iw0lrz26XDbFn8PsNPr8HS0grbes2xS9qEtWsZvNrPxj6guanLfGjXbiUxZMERtlyMolu14szqVZNizramLus/MXbn02mgg9b6WtbrksBarXWVgnBT9U8SbOJRyoiL4PrUriRf2o/PwC/xaPPcnX1Lr56gz+afaOFTlhVth2EI3kTE2uGkJd/io5inuFZ8MPMG1DH7gDGFbEY+FciVpLIjWSQeJOnyGqK3v0569BnsSrTGs/mn2HgHZnt8ZEoi4w/+yZxzeylm78RHdR5jYPk69yyPnhJ8ktA5Q0m5vB/nuj3xHfwNVi7F8uNy7mvhkVBGLT5GaoaBKV2rMrJRKbP8xi8PnU8ruT3nUztuP3KXDOzTWtc0cokPJFkkcpISspPIjaNICz8NqeVIuXARCzsnvB//AI/Wo7iRlsSkoxuYc3YvVhYWPF+lCa/XaI2XnfmMIgqNTeGdtWf4Yf91POyteb9DJUY0LIW1GX1JKJ1PojBLSE9l+vZfCVj2PnVjrhNWogYl/JOxTL2KS9ALuDf5EAtr83x0zWDQTNtxibdWn8HF1opZvWvSvbr5PiVj7M6nx4CZwEVuP+pSBngO2AI8o7WemtcTG5MEm3jUDKlJBH/Tl4QjK/Ds8ibFek268wHql4sHGbJtAfW9SzC7SR8q21oQsX4EyZdXsz21Fp+lj2bGgHY0Lu1h4qswL3eHmlLKDnDg9uN2LbmdQwAuwBqtdeX7vomJSRaJnOjMdOKPz+bWngkYUmNwrvY07o3fx9Ih+w6jg5HBvLTnD/ZEXKWhdymmN3z8nkmBdWYGUX9OIeKP97Cwd8F30De41O+dH5dzXyGxyQz77SjrzkXQqXIx5vSpia+ZLYOeh84nB6Ajt0c9nVdK+QI1tNbrjF7kA0gWidzQGanEHJxCzL6PIN0GHetHypWT2PpVpfiAaThVa8ul+CgmHF7HLxcP4WRtw+hqLXilWnNcbMznf9NHQmIZs/wkmy9GUcnbkcldq9G5SjGz6BiXzidRFJyPCWfRL6/S/uBCtIUVMbWbUy5tE9buFfBuPwc7v8Y5v0kBdfJmPAPnHeJIaBxD65fgi27VcLErOqMwc73anVLKFvjrA97ZgjbJ+N0k2IQx6MwMbvz0PDFbZuHaZBB+T89GZa1AtejyUZ7fvZi49FTeDGzNGzVak3ZyLpFbXyc205Y3op+nS/tBvNi0jFnc3BQE/+h8KtArSWVHskjkVmZKNDF7JhF3bAbKygG3+m/iGvQCyur+oyYN2sDPFw7y5sHVhCcnMLxiAz6s0+meUQgpwScJnT2YlCsHcanXG59BX5tsLiitNd/susLrK0/hYG3JzF6B9Az0M0ktD0M+8ImiJC36LFEbnyc5eCuWVpVJvRxLRtR1nOs8TvF+n2HjXYaTt27y3uG1/HH1OJ62DrxRozXPVWmCvZV5fIjSWrPyVBivrTzFuYhE2lTwYkrXqtT0K9iPE0oWiaJk7ZE/if/xOapGX+G0bxX8Sil8Ui/gUvsV3Bu/j4WVfc5vUgClZRj4YP1ZPtl0gZJu9vzYrxbNyprPfHpg/JFP1sAobk/uC7dHPH2rtU7P6wnzgwSbMBatNZHLJxGx5B0cq7Uj4MXFWNo7AxCRksCre5cx/9JhqroVZ1aT3tSxTOTmqoFkRp/gp4SOXCz1Bt/0aYCTbeFZgtxYsnnsrkCtJJUTySKRV2nRZ4ne/gbJl1dj5VoWj2Yf41Cue7ad1rFpyUw4sp4vT+3AxdqWCbU7MqJSQ6wsLIHbneaRqz8l4o/3sXRww3fwDFzq9czPS7rH2fAEBs0/zP7rMQyqE8C0HtVxNYN5V+QDnyhqtNYknPqR6G1vkJmWgLVVIxKO7AadiWen1/DqMg4LW0cORF7nnUNrWBdyFj8HF96q2ZZhFepjY2ke9znpmQZm7r7KB+vOcis5naH1SjKxY6UCOzpTskgUNSnpaSz/5VXKb5tFqoUVRwNb0NywFReP8nh3+A5bn3o5v0kBtetKNIPnH+ZSdBJjW5RjQsdK2FpZmrqsXDF259McwBr4MWvTQCBTaz08ryfMDxJswthitn1P6PfPYFcikBKjV2Ht5ntn3+rrp3lu92KCE2N5vkoTJtZsTdq+icQfnsb59ACm8xZTBj9J5WLOJryCgi+bzqcCuZJUdiSLxMNKvrqBqG1jSY86hZ1/czxaTMa2WPbTK56Kuckre5ax8cZ56noF8FPz/lRy/fvRvZTrxwmdPYSUq4dwafAkPgO/wsrZKz8u5V/SMw1M2nCeSRvP4+9ix4/9gmhRzjS15JZ84BNFVWZiGFHbxpJ49jcs7cuiE0uQeHQDVh4BFH9yMi4NnkQpxbabF3nn0Bp2hF2mjJMH79Zqz1Nla2NpYR7zKd1KSuPDDef5audlbCwteKN1eUY3L4uDTcHqRJMsEkXV1UsHODOjPyXCz7OrWEUsyrjSMv0YbnVfw73B+GxHihd0CakZjF1xill7rhLo68JP/WoR6Odi6rJyZOzOp6P/nCzzftsKCgk2kR/ij/5J8Ne9sXL2ouSYNdj6/T3tUHx6CuMPruHr0zsp4ejKN4170iIzmJDVQzGkRDMtcRCtuoynd1DAA85QtGXT+VQgV5L6J6VUV6Br+fLlnzl//rypyxFmShsyiD/xHbd2v48hOQqnaoNxbzwBK8f7T1CptWbRlaM8v3sJKZnpTKnXjRGVGt4ZNaUz0olc9QkRyyZg6eiO7+CZuNR9PD8v6R57r95i0PzDXIhKZHTzckzsWAk764L5jZ+5fuCTLBKPStKVtURtepGMuCvYFutE8qkrpF4/hkPFZhQfMA37UrXQWrMm5AzvHFzD4egQAt19+bZJb+p7lzR1+bl2ITKRcatOseT4TQJc7fi0S1X61vI3dVl3mGsW/UU+o4n/QhsyOfD7eKz/nEKihRVLqraig9VBqnr43R4F9YAv6Qq61afDGL7wKNFJ6UzoWIkxLcphaVFwp2oxdufTIaC31vpi1uuywO9a69p5rjQfSLCJ/JJ8+QDXPu8MmRkEvLQEx8ot7tm/K+wKI3Yu5HRsOP3L1mZyYFNSNr2Evr6abSk1OV9xMu91b25WK63kl2w6nwrkSlLZkSwSj0JmSgwx+z4i7shXKEtb3Oq9gUvtl7Gwuv9jIaFJsQzd/hsbQs/RtUQ1Zjftjbed0539KdeOETpnCClXD+PSsB8+A7/Eysk0cw0kpmbw2spTzNx9leo+zvzcv1aBnHNFPvAJAYb0RGL2TCT20DQs7Dyxde1M7I4lZCZE4d5yBN49P8TK2QuDNrD4ynHG7FvOjeQ4Xq7ajA9qdcDR2nxGJmy/FMXo5Sc5GBzLgNr+fP1EIM52ph8FJVkkBCSFnOTYl71xuXGa9V4VuFi+DMPT91Ki3mjc6o9DWdqYusSHEpmYyqjfj7P4+A2alfHgh761KONZMFf3M3bnUxvge+AStyf6LQUM1VpvzusJ84MEm8hPaeGXuPZZJ9LCzuPZ6TW8n5iAxV03WKmZGXx8bCMfHduEq7Udn9fvRqf4/URue524DBt+sn6NcYNfxs+1YM4vYCrZdD4VyJWksiNZJB6l9Fvnid7xJkkXl2PlUhqPpv/DoULP+84HZdAGvjy1g3EHVuFu68Dcpn3oFFDlzn6dkU7kyo+IWD4RSydP/IZ8i3Pt7vl5Off483QYwxYeJSopjYkdKxe4b/zkA58Qf0sNP0zkhlGkhR/C1q81JPgRs/0nLOycKfbEBNxbj0JZWhGblsybB1bz7dndlHHy4NsmvWnjV8HU5edapkEzacN5Jqw/S1lPR+YPqE2dADeT1iRZJMRtOjODays+Im7ZBGItrZlWqTX1Ha7T19WG4h2/w8arhqlLfChaa345FMyLf5zAoDVTu1dnaL0SBW7Bqvxa7a5S1suzWuvUvJ4sv0iwifyWmRxP2IKxxGyZhW1ADfxH/oxdyXsH45y4dYMROxexN+IaHf0rM7VqIKlrRuCYcIolqZ2o1+NLmlcyn6HpxmbuN1ggWSSMI/n6ZqK3jiUt8ji2fk3wbDEF2+J17nvssehQBm6dx4mYmzxfpQmf1O1yz2pUKdeO3p4L6toRXBs9hc+A6Vg6eeTXpdwjKjGNZ38/xuLjN2hc2p2ZPQOp7lsw5j0w9zySLBKPmjZkEnf0G27tehe0xqnSSBIPHSTx1EZs/atR/KlpOFVrA8C2mxcZsXMR5+MiGVqhPpPrdcHdtmB+m38/2y9F8dSvhwhLSOXjzlV4pVlZk30QlCwS4l4pwSe5MKMfFsHH+dO7EsvLBzE6Yw8t6j+La92xKAvTj1h8GNduJTF0wRE2X4yie7XifNurJsWcC87oUaN0PimlnnjQL2utl+T1hPlBgk2YSvzR1dyYO4yMhCiKPTEBz8deQ1n8PYdJpsHAN2d28vbBPwGYVKs9ba8vx+7sV1xID+BytWk806lLgevdNgVzv8ECySJhPNqQeXslql3vYkgKx6nKANybTMTK6d9zk6RkpPPmwdVMP7Wdqm7F+bl5f4I8/z5OZ6QRseJ/RK6YhJWTF75DvsW5drf8vJy/a9GaXw+F8OqyE8SmZDC2ZTneaVcRexPPBWXueSRZJIwlI+4akZtfIvnyaqy9g3DweZKo1V+RHnkF53q98B3wJVZuPiRnpDPxyHqmnNiCt50jXzZ8gidKm8/IhKjENIYvPMKyk2E8VrkY3/cNwtsp/z8IShYJ8W86I52IVZ8QvvQDYq1seb9CGzxd03jTOYkqHWdi41El5zcpgAwGzbQdl3hr9RlcbK34pmcNegb6mboswHidT98/4He11vrpvJ4wP0iwCVPKSIji5g+jiNu/CPvyjfEf8SM2xcvfc8zVhGhG7VrM2pCzNPIuxacl/HHY8gL2hhjW2D/L4EEf4eZQcHq3TcHcb7BAskgYnyE1jpj9HxN7eDpKWeFa7zVca7+KhfW/RxWsCznL0O0LiE5NYlKdTrxSrTkW6u/55lKuHiFk9mBSrx/DtfFAfAZMw9LRPT8v547IxFReX3GaHw5cp6ynA988UYP2lYrl/ItGYu55JFkkjElrTdKFJURtfpXM5HCcazyHIcaJqNWfYmHjiM+A6bg06o9SisNRITyzYyGHo0N4vFQNvmz4OL4OBWOEY0601nyz6wpjV5zCw8GaX/rXplX5/F2pU7JIiOylXDvG9VmDSL9+lFXFqzC9XFOG6eO8UOcJPGu/bLZzQZ28Gc+QBYc5GBzLk0F+fPl4dbwcTfs50eiP3ZkTCTZhalpr4vbM58ZPz6Mz0ije7zPcW428Z0ST1ppfLx1i9N5lxKWnMq5KI1qenE2p2PUcyqxFxR4/UaNcpQecpXAz9xsskCwS+Sc99hLRO94i6fwSrFzK4NV2BvYlW//ruMiUREbsXMSyaydo41uB75v1xd/x7wm+dUYaEcs/JHLF/7ByKYbv0Fk4B3XJz0u5x5YLkTy7+BjnIhLpX8ufz7pVo7gJhp2bex5JFon8kJkSw62dbxN/fDaWziVxqfYqt9b9QvLFPTjV6obvkJlYu/mSbsjkixNbef/IOuwtrZlcrytDK9Qzm1HfR0Nj6fvzQc5FJvJWmwq8164iVvm0cIxkkRAPpjPSiVzxPyKWf0icjQNvlW/NDXdXJlqep1PzcTiUNc8nTDIyDXy65SIfrDuLm521yUdBGWvk0wBgntbakM3+coCv1npHXk9sTBJsoqBIjw4mdM7TJJ5cj2ONjvgNm4u1+71BEZGSwKt7lzH/0mGquhVnjJ2m/pmJpGgbblafwmPth5qoetMy9xsskCwS+S/5+lYiN44iI+YCztWH4dHsYyxs7109TmvN3PP7eHXvUmwtrJjZpBe9St87R13ylUOEzh5CavBxXJsOxqf/VCwd3fLxSv6WmpHJx5su8NHGCzjYWPJJ5yoMq18Si3yckNzc80iySOSnlJCdRG4cRXr0Gaw9q2NhqErs9sUoazt8BkzHtfEAlFKci41g5M5FbAu7RBu/Csxs3IuyzqZZeTOvElMzeHHpCX7Yf50mpd359analHQ3/jxWkkVC5E7y1cOEzhpMavBxNvrV4MNSjWmignnPQ1O5xSRsiwWZusSHcuJGHEN/O8LB4Fj6Bvkx3USjoIzV+fQy8DRwMOsnArADygMtgEhgnNb6/MMUbSwSbKIg0Vpza9MMwhaMRVnb4TvoG1wb9v3Xcauvn+a53YsJToxlSIlKPHHyS6ro0xxxfIKOA2Zjb+9sgupNx9xvsECySJiGISOZmN0fEHtoKpaOvni1/gqHsp3/ddz52AgGbpvH/sjrDC5fl2kNe+Bs/feqm4b0VCKXTSRy1cdYuRTH9+nZONd8LD8v5R5nwxMYtfgYWy5G0aS0OzN71aSaT/7kornnkWSRyG86M42EMwuIPTCZ9FtnsbAOID3YgrTQizjV7IzvkG+x9vDHoA3MOruHcQdWkakNTKzdiRerNMXSIn9GEv1X8w4FM2rxcawsFHP61OTxGr5GPZ9kkRC5pzPSiFg2kchVn5BuYcmsgDos8g/kufT9jCxfG+8mH2Dl6GPqMvMsPdPAp5svMGH9OdztrfmmZyBPGDl7/sloj90ppSyB1kATwBdIBk4Df2qtrz1ErUYnwSYKotSb5wmdNYjki3twafAkvoO++deqUvHpKYw/uIavT+8kwMGFgUmhDIn5jhsqgBJdfqFU+UYmqj7/mfsNFkgWCdNKvXmAiPXDSY86hWPlfni2+BxL+3tHFaQbMpl4ZD0fHdtIaScPfmrej0bFSt9zTPLlA7dHQYWcxK3ZUIr3+9xko6C01vx0IJixK04Sm5LBa63KMb6t8SckN9c8Ukp1BbqWL1/+mfPnC9T3hKKI0NpA0sVlxOz/lNSbBzDEOpF+PRFl7YBP/y9wbTYEpRTBiTE8t3sxq66fpr5XCWY37UN19/z9MPWwLkYm0u+XgxwIjmVU49JM6VrVaJlkrln0F7kvEqaQevM84QvfIP7gH9xycOfjUo247OnF+xl7aVtnCC61X8bCyt7UZebZ8RtxDF1whEMht0dBffl4DTwd82deK5nz6S4SbKKg0pkZRK7+lIg/3sPK2Ru/Yd/hFNjxX8ftCrvCiJ0LOR0bTisnL8Zen0lZFc6timOo3+k9s102NC/M/QYLJIuE6emMVGL2f0zM/k+wsPPAq9U0HCv0/NdxO8IuM3jbPK4nxvJ2zTa8XbMtVnet1Hl7FNQEIld+jJWbL/7P/opj5Rb5eSn3iExM5bUVp/jxQDBlPR2Y0TOQdhW9jXY+c88jySJhalprUq5vJmb/pySd30h6MBjiM3Cs2hq/4T9g7VkCrTW/XT7Cy3uWEpuewrjA1rwZ2AZby4J/z5OWYeCtP0/z+dZL1PB1ZsGAOlQp/uhHZkoWCfHwEk9v4eb80aRePcxpV38mlW1GeftYxlldoWKTd3Gs9KTZzQeVnmngk80XmJg1CmpGz0Cjj8AE4z129yWQ7QFa65fyekJjkm/4hLlIvnqY0G8HkhpyEvdWz1K872Qs7JzuOSY1M4OPj23ko2ObcLK0ofets7yWuZRwu0Bq9p6HvWdFE1WfP8z9BgvkJksUHGkRx4hYP4K08EM4lO+BZ6vp/xpqHpuWzEt7lvLLxYM09C7FT837Uc7l3pWcki/tJ+TbAaSFXcC750S8Oo9DmfDxmM0XIhmVDxOSm3seSRaJgiT15gFu7fuY+D1/kH7DgLK0oVjviXi0fw2lFJEpiYzet4xfLx6iqltxZjfpQ8NipUxddq78eTqMIQuOkJiWybQe1Xm6folH+mFWskiI/0YbDMTu/ImwRW+RGXuDtcUqMatMI/pzjCHuDni3nIKdbwNTl5lnx0LjGPrbYQ6HxNGvlj/Te1Q36igoY3U+Dc76ZxOgKvBb1uvewCmt9bN5PWF+kGAT5sCQlkLEkneIWvMZ1t5l8R/xEw4VGv/ruBO3bjBi5yL2RlwjSNkyNXoO3hZJODT4kBINX0Qp85gXIa/M+QZLOsJFQaQNGcQe/IKYPRNQVg54tJiCU5UB//pg9NulIzy3ezEZBgPTGvZgcPm69xyTmRzPje9HELd3AY41OuI/8mesnPN3ufG7paTfnpD8403Gm5DcnPMI5L5IFExp0aeJ3vweMZsWY0gwYO3jh98zP+JYvi0AfwafZtSu23Nhvli1KRNrd8TJ2rTLi+fGjbgUBs47zKYLkfQN8mNGz0Bc7a0fyXtLFgnxaBhSEohcPZnI1ZNJz0znx4Da7CpRgddTt9G0fAvcm3yItYt5dHr/JT3TwMebLvDhhnN4ONgwo2cNelQ3zigooz52p5TaAzTVWmdkvbYGtmutG+a50nwgwSbMSeKZbYTOHkx61DU8H3sd78ffx+IfN1eZBgOTT2zm3UNr8bCyZ2TYLoZYbiXRsxmVe/yAlXMJE1VvPOZ+gwWSRaJgSos+S+T6EaTe2I19qQ54tfkaK5eS9xxzPSGGIdvns+XmRXqWDmRm41542P69kpPWmlubvyXs15exdClGwHO/3bfzPD+dCY9n1O/H2Xrp0U9Ibu55JFkkCrL0mCvcnD+M+H2bAHAMqkXxPjOx861PfHoKbx1YzTdndlHKyZ2ZjXvR3r+SiSvOWaZB88nmC7y39iwl3eyZP6A29Uu6/+f3LWhZpJQqC7wNuGqte+V0vGSRKGjSo4MJX/QWsbt+5paNI9NLN8bSy4qxafspXftZ3Oq9joWNeS36dPcoqP61/JlmhFFQxu58Ogs00lpHZ712B/ZorQtk+kuwCXOTmRxP2PzRxGydg22JQPxH/IxdycB/Hbcn/CoDtv7KtcRbNEjUfJU6G1srK3zbTMWl6r9HMJizgnaD9TAki0RBpQ2ZxB2dwa2d48HCEo+mH+NcY9g9IykzDQY+P7mVdw6toZidE98360sbvwr3vE/ylUMEf9Wb9OhrFOv1EZ6dxpg0h7TW/Jg1IXncI5yQ3NzzSLJImIPk6wcJ+aYXaaFXsHBSODVsimeL97Ar0Zqd4bfnwjwbG8Gg8nX5rH63ezrEC6pdV6Lp/8shQuNSmNSpMmNalPtPozIfZRYppb4DugDhWuvqd23vCEwDLIE5WuuPc/Fev0vnkzBnyZcPEPLry6Sd38U5Ry9mlm9OC9tL9LWOxqvx+zhVHYSyMO7iJo9SeqaBjzbeHgXl6WjDzJ6BdK/+6Fb2M3bn01DgfWAzoIDmwAda6x/yesL8IMEmzFX8kZWEfjeczIRoivWciGensf8Kuti0ZJ7fvYT5lw4ToNwYF7GcjtZHsCjZlYCOM7F0MN6ku/nJ3D/sgWSRKPjSYy8RueE5Uq5vwi6gBV5tZ2LtVu6eYw5FBjNw2zzOxIYzuloLPqzT6Z4JgDOTYgmd+zTxB5bgVKsb/s/8gKXjf/+G/7+ISEjl9ZW3JyQv5+nAN/9xQnJzzyPJImEutMFA9IbphC8ch85Mw9pPYV+tHu71XseidGf+d2wTnx7fjIetA9MbPk6v0oEF/ou3W0lpjFh0jMXHb9Chkjc/9K310HPTPeLOp+ZAAvDTX51PWaucnwPaAcHAfqAftzuiPvrHWzyttQ7P+j3pfBJmT2tN/IElXJ8/GhV1jW0eZVhZoR4jMndSx90HjxaTsS/RytRl5snR0FiGLjjCkdA4nqp9exSUh8N/HwVl9NXulFI+wF+zb+3VWt/M68nyiwSbMGcZ8ZHc+OFZ4g8sxr5CE/yf+RGb4vd+GNRa8/PFg7ywewloRdOwW3xh9QMWtq74tZ+JY/nuJqr+0TH3D3sgWSTMg9aahJPfE7XtdTCk4954Ai5BL9zT8Z2Ukcbr+1cy48wuanr48VPzfvcsg661Jnr9l4QtGIu1ux8Bzy3Evlx9U1zOPTadvz0h+fnI2xOSf96tGsUe4kOfueeRZJEwN2mRV7kx92kST23C0s0BK780bH0q4Vr3NS4Wa8mI3X9wMCqYbiWr8XWjJ/BzcDV1yQ+ktebb3VcZvfwkrvbW/NSv1kN1iD/qLFJKlQZW3tX51Ah4X2vdIev1m1n1/7Pj6Z/vI51PotAwpKcSvX46N5Z+AGlJ/OZXk4hS/jybshW/Mu3waPYx1u7ms/BTeqaB/208z6QN5x/ZKKiHzaJczVSslNqotb6ptV6W9XNTKbUx72UKIXJi5exFwAuL8B/5C6khJ7j4Tk1ubZ7F3R3FSikGla/LwW6vUtnNm7VeDnSwfZtjCW6Er+xN+NphGFJjTXgVQghzoZTCufrTBAw8gl2JVkRve40bC1uSFnXqzjEOVjZ81egJlrd9mhtJcdRfMY0vTmzFoA133sOz/UuUeXsHAJcnNSVq3XRy+wWXsbSu4MXRMS14p11FFh0Lpcqnm5mz9yoGg2nrEkI8mI1XKUq+vgHfobPRKZaknbckLTSeiHXD8VjWij/9FR/Xase6kLNU/2Myc8/tNXnePIhSimcbl2bvy83wsLem4+w9vLn6NOmZBlOX9k/+wPW7XgdnbbsvpZSnUmomUOuvjqr7HDNCKXVAKXUgIiLi0VYrhBFYWNvi9dhrVJlyGZcWw+kbeoyn921gTnxdfgoJ5trPQURtHUtmSrSpS80Va0sL3mtfif2vNMPX2ZbHf9jPoHmHiE5Ky/daclrtzg5w4Pbjdi25/cgdgAuwRmtd2dgFPgzpVReFRXrUdULnPk3iyQ04BXbCd9hcrN3uXbUgLTODdw6tYcqJLbgpFzrfuMC79guxdPTDp8Mc7Eu2NlH1/425jzQAySJhfrTWJJ6dT9SW0RjSE3Bv8DaudcaiLP9eqSkiJYEROxex/NpJWvmU47tmfSnp9PdjdpkJ0YTMHkLCkRU41+2J37C5WBaAUQlnwuN59vdjbLsUTdMyHszqHUjlYrmbRNTc80iySJiz9KhrhH4/gsTja7EtVQPbso6kxxzEws6TqKA3GB1tzfawy7TxrcDMJr0o6+xp6pIfKCktg1eWnWTO3ms0LOXOvKdqU9ojd/NX5cPIp15AR6318KzXA4EGWusXHsX5JIuEOUoJPsmFX17C4vQmrtm5sbRSU7pYHaKGTSZuDcbjEjjynvukgiwt4/YoqP9tPI+Xow3f9gqka7W8j4Iy1sinkcBBoHLWfx4EDgDLgC/zejIhRN5Ye5ag5Ni1+Az4ksQzW7j0dg3iDvxxzzE2llZ8Uq8La9qPwM5O85uvL+3Sx3MlTnNzSUeitryKIT3JRFcghDAnSimcKvcnYOBRHMt25dau9whd0JjU8MN3jvG2c2JJ6yHMbtKH/ZHB1Fz6Gb9cPHhn1IGlkwclXllGsScnE39oKZfeq0Py1cPZnTLfVC7mzOZRjZnbpyZnwxNITMs0dUlCiFyw9ixJyTF/4jtsLunhV4nfeRQH/+ew9grEfc/r/HzrJ6ZVq8u+yGvUXDqFaSe3kWkocCOK7nCwsWJW75osGFCHU2HxrDtXoEYDhQB3L6EckLVNiCLLLqAa1cdtpMSYP/F2cueloyuJumDBTF2fK1vHEfJLLZKvbzF1mbliY2XB+x0qse/lZhRzsqX79/k7Ciq3E46/C0zVWscppd4BagMTtdaHjF3gw5BedVEYpYaeIeTbAaRcOYhbs6EUf2oalvb3fmsfnhzP0zt+48/gM7ikejEsej/PO6zAyq0C3h2+x87X9HOw5Ja5jzQAySJh/hIvLCVq04tkJkfiWu813Ou/jbL6e86ky/FRDNm+gB1hl+lZOpAZjXriaed4Z3/SuZ0Ef/MkmQmRFO8/FfdWIwvE5MDJ6Zl5WgHP3PNIskgUFunRwdz4YSQJR1djX6EJbm36EH/iMzITbxJXdQTjdTVWh16goXcpZjftTVW3R7e6kzHciEvBx9k217mYDyOfrLg94Xgbbnc67Qf6a61PPorzSRYJc6czMwjd+A03F7+DbUoc63yrY1fanY4pe3Gr9xruDd8zq1FQkzae56ON5/F2smFWr5p0rlo8V79r1DmfgF5ZHU9NgdbAHGBGXk8mhHh4tn6VKfPObry6jSdmx49ceqcmSed23nNMMXtnVrQdxhf1u5Nif4uZvlXpmvA2YTFx3FjYnOhd76Iz8//5XiGEeXIs3wP/QUdxqtyf2H0fEzKvHik39t7ZX8bZk00dR/FRncdYfu0kNZd+xprgM3f2O1RsQtkJh3Go3JKbP44iZOZTZCbHm+JS7pGXjidzppTqqpSaFRsrcwCKwsHaI4ASr67E75kfSQ05yc3v3sSx1Cs413wel9Oz+fLqh8wuX4rzcRHUXvYFHx5ZT1pmhqnLzpavi53JOuSVUvOB3UAlpVSwUmqY1joDeAFYC5wGFj6qjichCgNlaYV/+5cI+uIahlajaBN2mvp7dzM/oS7H983gxqJWpMdeMnWZuWJjZcEHHSqx9+VmeDvaci4ywejnzO3Ip8Na61pKqY+A41rreX9tM3qFD0F61UVhl3R+FyHfDiQ98gpeXcbh3eM9lNW9y2YeiQrhqa2/cjY2HLtoXyZlbqSbzQZsvGvi3eE7bLxqmKj63DH3kQYgWSQKl6TLa4jc9DyZ8cG41nsd94bv3vPt3pGoEAZtm8fJmDBGVW7MJ3U742h9e5SUNhiIXPUxEYvfwcanAgHPL8KuRMHOoLuZex5JFonCKD06mNA5T5N4cj2ONTrg1f1VYg9OJPXmPhL9WvGhWzcWhVymhrsvs5v0pp53SVOX/J+ZaxYppboCXcuXL//M+fPnTV2OEI9MStgF9s8Zjue5rVxw9OJqGX86O16nWOuvcKrcz9Tl5VpahgFLC4WlhXFHYea282klt4detuP2I3fJwD6tdc28njA/yE2WKAoyk+MJm/cKMdu+w65Ubfyf/QVbvyr3HJOYnsrofcuZc24vdulu1L6RzLcec7HXCbg3fh/X2q/es5x6QWKuN1h3kywShY0hNY6orWNIOPUjtj718e70E9auZe/sT8lIZ/yhP5l6cjsVXLz4sXk/6t/1gS/x9BZCZvQjMzkW34Ff49Z8qCkuI8/MPY8ki0RhpbXm1qYZhC0Yi7K2w2fgV1g4JXFrx9sY0uPZXfEl3oix52ZKAqOrteC9Wu1x+MeXdeZEskiIguny7vmE/vQC7knRbParQhXvcGpU645nq6lY2ORucRNzYuzH7vpwe/hlB611DOABvJbXkwkhHh1Le2f8hs0l4KU/SI++xqV3axO9/qt7lhp2tLbl2ya9+a3VQGwdUthfMpMGsW9xiIbc2vEWN35vQ3rMRRNehRDCnFjYuuDdfjbenX4hPfosIb/WI+HMvDv77aysmVK/G+s7jiQ5M52mq77ig8NrSTfcntzbsUpLyk48gn35RoTOfZqQ2UMxpMqCCEKIh6OUwqPNc5SdeARbn4qEznyKuO0b8O21DadK/Wh05nPWJC5gkI8PU05sodbSz9l6U+57hBCPVplG/Wj4+RXCGj5F89AzWJ9OZsm+bVz5pQGpYQdNXV6BkavOJ611ktZ6idb6fNbrG1rrdcYtTQiRGy51elDuw+M4VmnFzV9e5NpnnUi/FXrPMb1K1+RIjzHUL1aCJP9r9DV0YHzyaJLDTxDya13ijs0iN6MghRACwKlSH/ye2o+NVw0i1gwhYu1QDKlxd/a38i3Pke5j6Fe2FhOOrKfZqq84GxsOgJVrcUq9tg6vHu8Ru/NHLn9Qn9TQ06a6FCFEIWDrU5HSb+/Au+eHxB1YzJUPW2Hv2xufXhtxtbZh/Jk3WegSSqYhjdZ/zuC5XYuJS0sxddlCiELE0t6ZVqN+we3NLSQ7F6PZhQvsPRbH9l86E3vwc7QuuKtw5pfcjnwSQhRgVm4+lBi9Cp9BX5N0dhuX3q5B3P7F9xxT0smdTZ2e5b2g9uAazmIvGxpFTiDUpgZRm14gbGlXMhJCszmDEELcy9q1NL69NuDW8B0SzswnZF59Um/uv7PfzdaeH5v3Y0HLgVyMj6LOsi+YcXonWmuUhSXFHn+fkmPXkhEXzqX36xG761cTXo0QwtwpSyu8u71Nmff2YenowbXPOhGzYR6+Pbfg3vR/1LmxmhXh03jO04HZ5/ZQ44/JrLp+ytRlCyEKmRKVm9N28nlCO75GhbgI3E9EsXTpdK7/3pmMxJumLs+kpPNJiELiztDzCYexLlaW4K96ETJ7CJnJf49GsLKw5N1a7dn82HP4uNgQXeoyzSL78Kv1yyQHbyd0fiNSww6Z8CqEEOZEWVjh3vAdfHttRBsyCF3Ygph9n6CzHrMD6F2mJkd7jKGZT1le2PMHj62fQ2jS7dXXnKq3u/0YXqnahHw7gNDvR2JISzbV5QghCgH7UrUo8/4BPDuN5daWb7n0fj1sXBsTMOgYHqVaMfrSxyxRe3BWBrpt+I4BW38lIsX4qzwVZbLypihqLCytaNvvUwImHeNqQE3qXbvKyU172TqzMUmX15i6PJORzichChlb30qUGb8Lr27jid35M5fG1yTx7PZ7jmlavAyHe4zmiVI1wOcK72s3noz/iFSDJTcWtSbx4nITVS+EMEd2/k3wf2o/juW6c2vXO9xc0omMhJA7+/0cXFndbjhfNXqC7TcvUXPpZyy6fBQAa3c/So3bhGeXN4nZMovLExuRevOcqS5FCFEIWNjYUbzvZEqN2wKGTK5MakbUmhl4d/yV4t3+ICgzjMWhHzHWOYnfrxyl+pLJLLh0WKYgMBKt9Qqt9QhXV1dTlyJEvvLxrcQTEw8Q0m8q9oYMih+7zKoZQwld9yI6I9XU5eU76XwSohBSVtYU6zmR0m9vB2XB1Y9aELbwTXRG2p1j3G0d+K3VQL5t0htblwQOFw+mUcQYYu3KE76iN7GHpspN2EOSb/hEUWRp5473Y/Pwajeb1LD9hPxSh8QLy+7sV0oxqnJjDnZ/lXLOnvTd8jODts0jJjUZZWlF8d7/o8ToVWREXefS+EAi/vhARkEJIf4Tx8rNKfvhUdyaDSVq1cdc/qA+FlYl8B94BO96r/Fs6I8sT15KKctMntr6Kz02fk9Iovx/txDi0WrX8WWqf3qeg1U7UDksjMsL57J1ah1So86YurR8JZ1PQhRiDhUaU3biEdyaPX37pmtCQ1JD/p7fQCnF8IoNONjtVap6eHLL/zL1bvXnnGMbore9TtSmF9CGDBNegXmSb/hEUaWUwrnaYPz778XKpRThK3sTufF5DOl/r2hXybUY2zu/wHtB7Vlw6QhByz5j840LADjXfIyyHx7DufbjRCx9n4tvVSP+8ApTXY4QohCwtHfBb9gcSryynIzYm1z+oB7R677CvdH7+A84QA2v0sy7MZl3rK6wMeQs1f+YzOyze+QLOCHEI+XlWpzBb6zh5qgFRNq5UOz4STZObMbNHZ8WmbyRzichCjlLe2f8hs0h4KU/SI++zqX36hC1bjra8PeKC5XdirG360sMr9iATK9QHkttyCKbgcQfn03Y0u4YUuVbQCFE7lm7V8Tvye241hlN/PHZhM5vRFrEsb/3Z80/t6PzC9hbWtN2zUzG7FtOSkY61h7+BDw3n1JvbERZ23F9ajeufdGVtPBLJrwiIYS5c67VlXKTTuAU1IXwhW9w5X8tIN0Gn55r8en4PUOT97Ay9nsCLZN5dtfvtFszk4txkaYuWwhRyLRr2IcWk8+zpX5fisXGEjr3bXZMqUdGYuHPG+l8EqKIcKnTg3IfHsexamvCfn2Za1M6kh7995wsdlbWfNukNz8374+NUxJvWhfjdYtXSL6+mdCFLUiPu2rC6oUQ5kZZ2uDR7GOKP74KQ0o0oQuaEHv4q3u+3avvXZKD3V/lucqNmXpyG/VXTOVI1O1ccqzamnITj1K87xSSzmzh4ltVCV/ynjyKJ4R4aFYu3gS88Dt+I34mNeQEF9+pScyW2ThW6kfAoBNUr96X78O+4n8ZBzgYcYWgZZ/xzemdGGSJdCHEI+Rm78xzz88ndsyfHPEoheeJg+x4rRw3d39r6tKMSjqfhChCrNx8KPHqSnwGzyDp/A4ujq9B3L5F9xzTv1xtDvcYTWkXV5Y4GejAWJJiQ7ixoOk9y6gLIURuOJRqh/+Ag9iVbEP01tGELetBZlL43/utbPiy0ROsajec6NRkGq6czodH1pOSkY6yssaz0xjKfXQG5zpPELlsAhffrEr8oeVFZoi6EOLRUkrh1mQA5T48jkO5htz4YSTXv+iCISUZr9bT8e+3iwGOKay6NZt63OLFPX/Qcd1srifEmLp0syVzYQpxf22qt6HXR8dZ3eIZdLqByJnPsvuj+mQk3jJ1aUYhnU9CFDFKKTxaP0vZiUewKVae4K/7EPLtIDKT/r4hqOxWjOM9R9OjRBAXXZKoo57lqsGZG4vakHh+iQmrF0KYI0uHYhTv9gceLb8g5fomQn6pQ9LV9fcc0zGgMkd7jOHxUjV47/BaaiydwrKrJ9Ba334Ub9Q8So3bjIWNA9endef6F11IC7tgoisSQpg7a88SlHxtHT4DppN4ahOX3qpO3L5F2Bavg1/fnVRvOYm5cb8xMW03e25epObSKfx04YB0fD8EmQtTiOy52Ngz9ulZqNfWsCqgJs5n9nPwVX9Ct8wodHkjnU9CFFG2PhUpM34nXt3fJXb3r1x6pyZJ53bc2e9gZcPidgOYXr8XKfZptLLsxirbBoSv6kvMgSmFLgyFEMallMI16Hn8+u7Ews6DsD86E7XtDXTm36tweto5Mr/lANZ2GIGdpRVPbPqBTutmczomDADHKi0pO/EIxft9RtLZ7Vx8qxrhS97FkJqU3WmFECJbysICj3YvUnbCYayLlbv9hdzMARiS43CpOYqAAQcZ6mHH8tjvqahvMXT7Anpu+pHw5HhTly6EKGRaVmzC8+/tZUm75wixciLm++c48H5t0qOumbq0R0Y6n4QowpSVNcWe+IDS43eChRVXPmpJ5KpP7pmM/PlqDdnX9WVcrB14yaom4x36ErXjLSI3PIvOTDdh9UIIc2TjHYhfv904B44k7tAXhP7WjLTos/cc09avIoe6j2Zqg+7si7xG0NLPGLNvObFpybcfxes4mnIfn8G5Xi8il03k4ltViTu4VDrFhRAPxdavMmXe2YX34x8Qu+83Lr5dg4QT67F2LYtPr/XUavoOv8b8wriMQ/x5/SSBS6fwx9Xjpi5bCFHIONnY8u6Ar/F85Te+K9cIde0EJ18rz/UVk9CGTFOX959J55MQAofyDSk74RAudZ4gfOE4rk/tRkZC1J39tbz9uNr/dWo7V2SBdTE6OzzL1VMLuLm0K5kpMaYrXAhhliysHfBq/SXFuv5ORtxVQuc1IP7kD/d0HllbWPJi1Wac7TmOoRXqM+3kdiov/oTvzu3DoA1Yu/sR8OyvlHpzCxa2TgRPf5xrnz1G6s3zJrwyIYS5UpZWePd4lzLv7MbC3oVrk9tz46fn0WnJuNZ+iRJP7eN55zSWxv1M8Yxb9Nr0I0O2zScmVRZBEEI8Wi0qtmLCG+tZ2mYoe1wDiP99PIffrELKdfPu9JbOJyEEAJb2Lvg//xs+A78i4cQ6Lr1Ti6QLe+7sd7axY1+vZ3i+TAfOW9rRyvEZtt24wI2FzUmPvWzCyoUQ5sqxXDf8BxzE1qc+ketHELG6P5kp906y6W3nxMwmvdjX9WXKu3jxzM6FNFo5nd3hV26/R+UWlJ1wmOL9Pif5/E4uvV2d8N/Hy6N4yCS/QjwM+zJ1KfvBQTzav8Ktjd9w6Z0gks7vwsajEr59ttCg4assvPU9L2aeZN7Fg9RcOoX1IedMXbYQopBxsHXkwwGzqDb0Ez6r0oqkqGDOvxPEtYXjMKSnmrq8hyKdT0KIO5RSeLR9njLjd6IsLLnyv2ZErZ16ZzSCUorpLduxoMlw0rQD/R16MD3Zk+AFTUkJ3ZPDuwshxL9ZOfnj88SfuDf5kMSLywj5tR7J17f+67jaXgFse+x5fmren9CkOJqu+ooh2+ZzIyku61G8Vyn3yVlc6vchcsUkLr5ZhbgDS4r0o3gyya8QD8fCxh6fp76g1LjN6MwMrkxqRtjCcejMTNzqv0GZfjt5zS6CRQkLsE+LpuO6Wby4ewmJZvqB0NikI1yIh9cssDdfvjCfFS16s8a7IgmrPuHYuEr3DBIwF6ow3pTVrVtXHzhwwNRlCGHWMhNvETJ7CAmHl+Nc53H8hn2HpaPbnf0XomNp/Pt3RFmH0DTzJl8kr6Fi+29wqtTnkZxfKXVQa133kbyZiUgWCZE3qTf3E/7nIDJiL+JYqS8ezT7Cysn/X8clpKfy0bGNfH5iKzYWVowPastLVZtha2kFQOKZbdz8+QVSg4/jWKMDPgOmY+tT8aHrMvc8kiwS4uFlJscTNn80MVvnYBtQHb8RP2FfqhY6M42YvZO4uf8zPndqw3cWFSjv7MUPzfvSqFhpo9QiWSRE0bb1wFy+3byQ4ed3UTw1Eac2z1HiyU+wsHXM1zoeNotk5JMQ4r4sHd0p8fJSivedQvyRFVx6rw7JVw7d2V/ew5WrQ16krlVddihfOjv0Ze26scTs+6hIjzQQQjw8W596+A84gGv9cSReWELwj9WJ2T8ZnXHvaAIna1sm1XmM44+/Rivf8ow7sIrAP6aw6vopABwrN6fshEMUf2oqyRd2c+ntGoQtegtDaqIpLksIYcYs7Z3xe3o2JUavIjMhissf1Cdi2YeABe6NP6Dsk1t4z+oSvyQsJjUpguarv+atA6tJzcwwdelCiEKmRd1hzB4xi9VNu/KbXyCJG7/m+GsVSDi5wdSl5UqB73xSSlVRSs1USv2ulBpl6nqEKEqUUnh2GkPpN7eiM9O4MrER0Rtn3OlcsrexYs+AJ3nW73HCM1zp59ibKQeWErF2+D3LpwshRG5ZWDvi0XgCAQOPYl+iJbd2vk3wL7VIurzmX8eWd/FiaduhrGo3HEsLRbcN39Fl/RzOxUagLK3wbP8y5T8+i0v9J4la+REXxlUhbv9i6SAXQuSZc83HKDfpBC71ehOx5B0uT2xMaugZbH3q4vfUPtrX7MPy6G/pra/yyfFNNFwxjaPRoaYuWwhRyDi6lmLywF9p3XUw4wMfIzgthWuftuPKrMFkJt7K+Q1MyKidT0qp75RS4UqpE//Y3lEpdVYpdUEpNe5B76G1Pq21fhboAzQxZr1CiPtzqNCYshMO41ClNTd/eo6QGf3JTI4HbndQfd2pMd/XG4ZO8OYj+2YMvBbNmcVdyUyJNnHlQghzZe1WjuLd/qB49+UAhC3rRtjyx0mPufivYzsGVOZI9zFMqdeVHWGXCVw6hTf2ryQuLQUrNx/8R/5Eqbe2YengRvBXvbg2uYOsiieEyDNLJw8CRs0j4PmFpEdc4tK7tYha8wXKwhbP5p9QsfcaPuEYsxJXcDPuBg1WTOOjoxvJKARLpAshCg6lFC0bv8qPgyezoWFb5pSoR/yunzn5egXiDiwxdXnZMvbIpx+AjndvUEpZAl8DnYCqQD+lVFWlVA2l1Mp//BTL+p1uwCpgtZHrFUJkw8rZi5KjV1Gs1/+I27eQy+/XvWe5z0G1y7Ln8ZG43KrERqtydIwvxZoFXUiPuWDCqoUQ5s6hTEcCBhzGvckkkq9vIeTnIKJ3vYsh/d5H6GwsrXi1egvO9hzHgHJ1mHJiC1WWfMKP5/dj0AYcKzXLehRvGsmX92Mo4N8OCiEKLpf6vSk36QSO1doSNn80Vz9pTVrEZez8m+L/1AG6V23Pqluz6GAIZvyhP2mx+hvOxUaYumwhRCHj7FWVzwfNo3PbLrwW1JXzWBD8ZU8uTXucjJibpi7vX4w+4bhSqjSwUmtdPet1I+B9rXWHrNdvAmitP8rFe63SWnfO6TiZzE4I40o8vYWQGf3ITIrBd9A3uDUfemdfaGwK7X5ayyXbnRis0nk74xCvPTYJ+4CmeTqHuU+qCZJFQjxqGQkhRG9/k8SzC7B0LoFHs49xrNALpdS/jt0XcY1X9i5lb8Q1GniXZFqDHtTzLgmAISUBCzunXJ/X3PNIskgI49BaE7v9B27++jKgKd7vc9xaDEcpRfLVDUSsH8GyVEfed+pAqrLm47qdea5KYyzUw33/L1kkhMhObOh+3l0ziZRrkYy6ugdLW0dKPDUN16aD73uf9F+Y04Tj/sD1u14HZ227L6VUS6XUdKXUtzxg5JNSaoRS6oBS6kBEhHyzIIQxOVZpSdmJR3Co0ITQuU8TMnvInYl8/Vzt2D+yMx1tu2OV6MIH1vXotfozQk78YuKqhRDmzsrJn2KdfsK392Ys7TyIWP0UNxd3IC3yxL+Ore9dkh2dX+D7Zn25mnCLhiunM3zHQsKS4/PU8SSEENlRSuHWfChlJx3Hrkw9bnw/guufdyb9Vij2pdriP+AQfSs0YFXMXBoabvLy3qV0WDuLawky8lII8Wi5+tXji0Hz6d2oIa/W6sYRG2dC5wzl0iftSIu4bOryADOYcFxrvUVr/ZLWeqTW+usHHDdLa11Xa13X29s7P0sUokiyci1OydfW4tXjPWJ3/sTlDxqQGnoaAAcbKxYPbMyYCv2wDfNnnVVZmu7ZwtYt78tEv0KI/8zOvwl+/fbg2epL0iKPEfJrPaK2vEpmSsw9x1koCwaVr8vpJ95gbPWW/HLxIJUXf8IXJ7aSJitRCSEeERuvUpR6fQM+A6aTeGYLF9+uTuzu+VjYuuLdfg41uvzE3LQNfJiyhb1hF6m5dAo/nt9fZO6JlFJdlVKzYmNjTV2KEIWahZU9bTtMYUm359lbsxaTyrfm1rltnHuzGlHrpqFNPP+cKTqfQoASd70OyNomhDAzysKSYo+/T8mxa8mIC+fS+/WI3fUrABYWigkdKzO3Qx9srtckDkc6Xoph97n1Jq5aCFEYKAtLXGqOJGDwSZyrDyPuyDcE/1iV+BPfobXhnmNdbOz4pF4XjvUYS5PipRm7fwXLr580UeVCiMJIWVjg0e5Fyk48gq1PJUJm9if46z5kxEfiWK4rAQMPM6xkBVbGfE+VjAie3vEbT2z6gbCsBVwKM631Cq31CFdXV1OXIkSR4F66DdMH/MLgoHK8XLs7O519CPv1FS5MbExqyCmT1WWKzqf9QAWlVBmllA3QF1hugjqEEI+IU/V2lJ1wGPtStQn5dgCh34/EkJYCQL9a/mwc0hWrG20pFuuOrWM9E1crhChMLO098WrzFX7992DtXpHIDc8SuqApKTf2/evYiq7erGw3nE2dRtGzVKAJqhVCFHa2PhUp/fZ2ivX6H/GHlnHx7erEH16Bpb0XxTrPp3bHb/g1ZTlvpe5m7fWT/HbpsKlLFkIUQha2rrTvOovl7ftxrGpF3qzckcjrx7nwThARyyaiM9LyvyZjvrlSaj6wG6iklApWSg3TWmcALwBrgdPAQq21fP0ohJmz9vCn1LhNeHYeR8yWWVyZ2Ii0sNsr3TUs5c7+F9rQsUQPqvu4mLhSIURhZFusFr69N+Pd4XsyE0K48VtTItY9Q2Zi2L+ObeFT7pFPvimEEH9RllZ4dX2Tsu8fwMrVh+tTuxEyeyiZSbE4VepDiYGHed7Xm1VxP/JU4h5TlyuEKMQ8Kz7B9P4/8lwlV16u3Y0/PcsSseRdzr9bh+RL+/O1FqOvdpeflFJdga7ly5d/5vz586YuR4giK/7IKkJmDYTMDPyGf4dLvV55fg9zX9EFZFUXIUzFkBZPzN7/EXt4OsrKHveG7+JScxTK0vqh3s/c80iySAjT0RlpRCydQOTKj7By98dv+Pc4VWuD1prEM/NwKNsFC9vcPY4mWSSEeFhaayJPfM/7u+dzNsaBdy9swjMtCa+Oo/F+/AMsbB1y/V7mtNqd0cjzxEIUDM5BnSk74TC2/lUJ/qo3N395CUN6qqnLEkIUERY2zng0+wj/AYew821E9LaxhPxal+Rrm0xdmhCiiFFWNhTr9SGl39mFhY091z5ty42fX0SnJeNU5alcdzwJIcR/oZTCu8bTTH1yFqNLGnipdncW+VQn6s8pnH+7BomnNxu9hkLV+SSEKDhsvEpR+q1teLR/hej1X3JlUjPSIq6YuiwhRBFi41GJ4j2WU6zrYnRGCjeXdCRs5ZOkx101dWlCiCLGoVwDyk44jEf7l7m14SsuvRNE0oXdpi5LCFHEWLuWoVOfpaytU4vwMp4Mq9mLa4m3OHrQ+NNwS+eTEMJolJUNPk99QcCLS0gLO8eld2uRcvWIqcsSQhQhSikcy3XFf9BR3Bq9T/KVNYT8FEjS5TWmLk0IUcRY2Drg89RUSo3bhM5M48qHTbm1ZY6pyxJCFDHKwpLi9cYwted0xntF8mpQFza62Bj9vNL5JIQwOpe6j1P2g0O41O2JjV8VU5fzUJRSZZVSc5VSv5u6FiFE3llY2eHe4C0CBh3HsWIfbH3rm7okIUQR5VilFWU/PIZ7q5E4Vmlp6nKEEEWUjVd1HntqLeuqlmB07a5GP590Pgkh8oVNsbL4DZuDhbVtvp9bKfWdUipcKXXiH9s7KqXOKqUuKKXGPeg9tNaXtNbDjFupEMLYrFxK4t1+NpZ2HqYuRQhRhFnau+A7+Btsipc3dSlGp5TqqpSaFRsba+pShBD/oCxt8Gs2CceApkY/V6HqfJJgE0Jk4weg490blFKWwNdAJ6Aq0E8pVVUpVUMptfIfP8Xyv2QhhBBCCPMni0IJIaCQdT5JsAkh7kdrvQ2I/sfm+sCFrBFNacACoLvW+rjWuss/fsLzvWghhBBCCCGEKCQKVeeTEELkgT9w/a7XwVnb7ksp5amUmgnUUkq9+YDjRiilDiilDkRERDy6aoUQQgghhBDCTFmZugAhhDAHWuso4NlcHDcLmAVQt25dbey6hBBCCCGEEKKgk5FPQoiiKgQocdfrgKxtQgghhBBCCCEeIel8EkIUVfuBCkqpMkopG6AvsNzENQkhhBBCCCFEoSOdT0KIQk8pNR/YDVRSSgUrpYZprTOAF4C1wGlgodb65CM6n6y8KYQQQgghhBBZlNaFZ0oSpVRXoCvwJHD+rl2uQOx9/g3gBUQaoZx/nudR/c6Djslu3/22/3Pbg16bWxvldFxu2ymv7WZu7VTQ/5ZKaa29c3lsgaSUigCu3rVJ/n4KZhZlV9uj+J3C1E6FqY2gCOWRZFGuthvz7ycvClM7FaY2ym7/w2yTLPqb/P3k799PXkgW5awgfZY1jyzSWhf6H2DW/f6d9fqAsc/5KH/nQcdkt+9+2+/TDtm+Nrc2elTtlNd2M7d2Kkx/S+byI38/BffvR9qpaLWRMdvJHH7k76fg/v0UpnYqTG2U2/bIzTbJIvn7+S/bJIty/tu5T5uZVRs9TDsV5L+lu3+KymN3K7L5d36d81H+zoOOyW7f/bb/c1tOr43BWG2U03G5baeHaTdjkL+lwkP+fnLeZqq/H2mnnEkbFR7y95PzNsmigttOpmij7PY/zDbJor/J30/et0kW3X9bYfpbyuk4c/tbuqNQPXb3MJRSB7TWdU1dR0EmbZQ70k45kzbKnrRNzqSNckfaKXekne5P2iV3pJ1yJm2UO9JO9yftkjvSTjmTNsqd/GinojLy6UFmmboAMyBtlDvSTjmTNsqetE3OpI1yR9opd6Sd7k/aJXeknXImbZQ70k73J+2SO9JOOZM2yh2jt1ORH/kkhBBCCCGEEEIIIYxHRj4JIYQQQgghhBBCCKORzichhBBCCCGEEEIIYTTS+SSEEEIIIYQQQgghjEY6n+6ilKqilJqplPpdKTXK1PUUZEopR6XUAaVUF1PXUlAppVoqpbZn/U21NHU9BZFSykIpNUkp9aVSarCp6ylIJI9yR7IoZ5JFOZMsyp5kUe5IFuVMsihnkkXZkyzKHcminEkW5cxYWVToO5+UUt8ppcKVUif+sb2jUuqsUuqCUmocgNb6tNb6WaAP0MQU9ZpKXtopyxvAwvyt0vTy2E4aSADsgOD8rtVU8thG3YEAIJ0i0EaSRzmTLModyaKcSRZlT7IoZ5JFuSNZlDPJouxJFuVMsih3JItyViCySGtdqH+A5kBt4MRd2yyBi0BZwAY4ClTN2tcN+BPob+raC2o7Ae2AvsAQoIupay/A7WSRtb848Kupay+gbTQOGJl1zO+mrr0gtU3WviKXR5JFRmknyaKc20iySLLov/z9SBZJFj2qNpIskiz6L38/kkWSRY+qjYySRYV+5JPWehsQ/Y/N9YELWutLWus0YAG3e/fQWi/XWncCnsrfSk0rj+3UEmgI9AeeUUoV+r+jv+SlnbTWhqz9twDbfCzTpPL4txTM7fYByMy/Kk1D8ihnkkW5I1mUM8mi7EkW5UyyKHcki3ImWZQ9yaKcSRbljmRRzgpCFlk9qjcyM/7A9bteBwMNsp75fILbf4Sr87+sAue+7aS1fgFAKTUEiLzrf8BFVXZ/T08AHQA34CsT1FWQ3LeNgGnAl0qpZsA2UxRWAEge5UyyKHcki3ImWZQ9yaKcSRbljmRRziSLsidZlDPJotyRLMpZvmZRUe18ui+t9RZgi4nLMBta6x9MXUNBprVeAiwxdR0FmdY6CRhm6joKIsmj3JMsejDJopxJFmVPsij3JIseTLIoZ5JF2ZMsyj3JogeTLMqZsbKoyAzF+4cQoMRdrwOytol7STvljrRTzqSNsidtkzNpo9yRdsqZtFH2pG1yJm2UO9JOOZM2yp60Tc6kjXJH2iln+dpGRbXzaT9QQSlVRillw+2J2ZabuKaCSNopd6SdciZtlD1pm5xJG+WOtFPOpI2yJ22TM2mj3JF2ypm0UfakbXImbZQ70k45y9c2KvSdT0qp+cBuoJJSKlgpNUxrnQG8AKwFTgMLtdYnTVmnqUk75Y60U86kjbInbZMzaaPckXbKmbRR9qRtciZtlDvSTjmTNsqetE3OpI1yR9opZwWhjZS+vXyeEEIIIYQQQgghhBCPXKEf+SSEEEIIIYQQQgghTEc6n4QQQgghhBBCCCGE0UjnkxBCCCGEEEIIIYQwGul8EkIIIYQQQgghhBBGI51PQgghhBBCCCGEEMJopPNJCCGEEEIIIYQQQhiNdD6Jh6KUylRKHbnrZ5ypawJQt21SSrlkvS6ulJqnlLqklDqolNqtlHo8h/e4pJSq9I9tU5VSbyilaiilfjDiJQgh8kCySAhREEgWCSEKAskiUZBZmboAYbaStdZBj/INlVJWWuuM//g2jwFHtdZxSikFLAV+1Fr3zzpHKaBbDu+xAOgLfJD1OxZAL6CJ1vqqUipAKVVSa33tP9YqhPjvJIski4QoCCSLJIuEKAgkiySLCiwZ+SQeKaXUFaXUB0qpQ0qp40qpylnbHZVS3yml9imlDiulumdtH6KUWq6U2gRsVEo5KKUWKqVOKaX+UErtVUrVVUo9rZSaetd5nlFKfXGfEp4ClmX9uzWQprWe+ddOrfVVrfWXWe9hqZSarJTar5Q6ppQamXXYfODJu96zOXBVa3016/UKbgefEKKAkiwSQhQEkkVCiIJAskgUBNL5JB6Wvbp3SOfdQRCpta4NzADGZm17G9ikta4PtAImK6Ucs/bVBnpprVsAzwG3tNZVgXeAOlnHLAS6KqWss14PBb67T11NgINZ/64GHHrANQwDYrXW9YB6wDNKqTJa6+OAQSlVM+u4vtwOu78cAJo94H2FEPlHskgIURBIFgkhCgLJIlFgyWN34mE9aEjnkqz/PAg8kfXv9kA3pdRfQWcHlMz693qtdXTWv5sC0wC01ieUUsey/p2Q1fPeRSl1GrDOCqB/8tBax9+vKKXU11nvn5YVZu2BQKVUr6xDXIEKwGVuB1lfpdRJoAfw3l1vFQ74ZXPtQoj8JVkkhCgIJIuEEAWBZJEosKTzSRhDatZ/ZvL335gCemqtz959oFKqAZCYy/edA7wFnAG+z+aYDKWUhdbaAJwEev61Q2v9vFLKi9u94n/V9KLWeu193mcBsA7YChzTWofdtc8OSM5lzUII05EsEkIUBJJFQoiCQLJImJQ8difyy1rgRaWUAlBK1crmuJ1An6xjqgI1/tqhtd4LlAD6c+8Qy7udBcpm/XsTYKeUGnXXfod/1DTqr2GiSqmKfw0z1VpfBCKBj+9zrorAiWyvVAhRkEkWCSEKAskiIURBIFkk8o10PomH9c/niT/O4fiJgDVwLGuY5MRsjvsG8FZKnQI+5HbPeOxd+xcCO7XWt7L5/VVASwCtteb2cMwWSqnLSql9wI/AG1nHzgFOAYeUUieAb7l3NOB8oDJ/D1H9S6us8wghTE+ySAhREEgWCSEKAskiUWCp2//dC1EwKKUsuf2scIpSqhywAaiktU7L2r8S+EJrvTGb3/cFftJatzNSfbbcHubZ9BEsOSqEKKAki4QQBYFkkRCiIJAsEo+CzPkkChoHYHPWMEsFPKe1TlNKuQH7gKPZhRqA1vqGUmq2UspFax1nhPpKAuMk1IQo9CSLhBAFgWSREKIgkCwS/5mMfBJCCCGEEEIIAYBS6jugCxCuta5+n/2K2yufPQYkAUO01ofyt0ohhLmROZ+EEEIIIYQQQvzlB6DjA/Z3Aipk/YwAZuRDTUIIMyedT0IIIYQQQgghANBabwOiH3BId27P36O11nsAt6w5fYQQIlvS+SSEEEIIIYQQIrf8get3vQ7O2iaEENkqlBOOe3l56dKlS5u6DCHEf3Dw4MFIrbW3qev4LySLhCgczD2PJIuEKBzMMYuUUiO4/Wgejo6OdSpXrmziioQQ/9XDZlGh7HwqXbo0Bw4cMHUZQoj/QCl11dQ1/FeSRUIUDuaeR5JFQhQOBSiLQoASd70OyNr2L1rrWcAsgLp162rJIiHM38NmkTx2J4QQQgghhBAit5YDg9RtDYFYrfUNUxclhCjYCuXIJyGEEEIIIYQQeaeUmg+0BLyUUsHAe4A1gNZ6JrAaeAy4ACQBQ01TqRDCnBSqzielVFega/ny5U1dihBCCCGEEEKYHa11vxz2a+D5fCpHCFFIFKrOJ631CmBF3bp1nzF1LULkRnp6OsHBwaSkpJi6FJOxs7MjICAAa2trU5ciRJElWXSb5JEQpiVZdJtkkRCiMCpUnU9CmJvg4GCcnZ0pXbo0SilTl5PvtNZERUURHBxMmTJlTF2OEEVWUc8ikDwSoiCQLJIsEkIUXjLhuBAmlJKSgqenZ5G9wVJK4enpWeS/4RTC1Ip6FoHkkRAFgWSRZJEQovAq0p1PtzbPIuX6cVOXIYq4onyDBXL9AL8fDWXrxUhTlyGKOPnforTBlguR/H401NRliCKuqP/vEKQNhBCFU5HtfDKkJBCx9AMuf1CPqHXT0AaDqUsSIl9FRUURFBREUFAQPj4++Pv7Y2lpSVBQEFWrVsXDw4MyZcoQFBRE27ZtMRgMvPTSS1SvXp0aNWpQr149Ll++/MBzpKam8uSTT1K+fHkaNGjAlStX8ufiTEwp1VUpNSs2NjbHYw0GzcebLtBqxm5e/OM4iakZ+VChEAWL5FHB8NXOy/T5+SD9fzlIVGKaqcsRIt9JFgkhhPEU2TmfLOycKDvxMKFzhxH26yskHF2N3zM/YO3ma+rShMgXnp6eHDlyBID3338fJycnxo4de2f/kCFD6NKlC7169QJg/vz5hIaGcuzYMSwsLAgODsbR0fGB55g7dy7u7u5cuHCBBQsW8MYbb/Dbb78Z7ZoKirwsfmBhodj6XGPe/PMMX+24zJ9nwvmuTxDNy3nmQ6VCFAySRwXD/AF1+GTzBSasO8eWi1HM6l2TLlWLm7osIfKNZJEQQhhPkR35BDA79AJRA2fgM+gbks5t59LbNYg/tMzUZQlRIN24cQNfX18sLG7HRkBAAO7u7g/8nWXLljF48GAAevXqxcaNG7m9Oq+4m6OtFdN7VGfzqEYAtJq5i5eXnpBRUEJkQ/LIOKwtLRjftiL7Xm6Gt5MN3b7bx9MLjhCbnG7q0oQokCSLhBAi94ps51NieiofHd1Ig5XTmeJaCr939mDtWZLr03oQ+v1IDKmJpi5RiAKlT58+rFixgqCgIMaMGcPhw4fv7Bs+fDgHDhz41++EhIRQokQJAKysrHB1dSUqKirfajY3Lcp5cXR0C55rXJovd1wm6POtbL8k7SXEP0keGVeQvyv7Xm7Gm23K89PB6wR+toUN5yJMXZYQBY5kkRBC5F6RfezO0dqWIz3G8Nr+FXxyfBNLXLyYNeJXKu38gag/J5N0Zgv+z/6KfZm6pi5VFBGvLDvB0ZC4R/qeNf1dmNq9+iN5r4CAAM6ePcumTZvYtGkTbdq0YdGiRbRp04Y5c+Y8knOI26Ogvny8Bj1r+DJs4VFaztjFS03LMKlTZRxsimxki3xU0LMIJI/yg62VJZM6VaFbVR+GLDhM+1l7eLZRKT7tUhUnW8kiYXySRUIIUbgUqpFPeZnkF8DD1oG5TZ9kbYcRZBgMtFo/lw9K1Mdr9J8YUhO5PLERkSs+QhsyjVy5EObB1taWTp06MXnyZN566y2WLl36wOP9/f25fv06ABkZGcTGxuLpKXMZ5UbL8l4cHdOCUY1KM237ZWp9vo2dl6NNXZYQBYbkUf5oUMqdQ6Nb8Grzsny756qMyBTiHySLhBAidwrVV1d5meT3bm39KnK0xxjePbyW6ae2s8rehRmjFhK4firhv79FwvE1+I/8GWvPkkaqXAge6TdxxnDo0CF8fHzw8/PDYDBw7NgxAgMDH/g73bp148cff6RRo0b8/vvvtG7dWpYPzgMnWyu+eqIGPQN9GfbbEZp/s5OXm5Xlw46VZBSUMJqCnkUgeZTf7K0t+axbNXpU92Hob0doOWMXrzQry4edKmNvbWnq8kQhJVkkhBCFS6Ea+ZQXWmvCV/Un9vCXaEMmjta2fFa/Gzs7v4ibjT1ddy3h9WpdcRo8g5Srh7g4PpDYPQtMXbYQJhMeHk7Xrl2pXr06gYGBWFlZ8cILLwDZz2swbNgwoqKiKF++PJ9//jkff/xxfpddKLQq78WxsS0Z2bAUU7ddotbn29h1RUZBiaKrKOeRUqqsUmquUur3/D53s7KeHBndgpENS/HFtkvU+WIb+67dyu8yhCgwinIWCSFEXqnCuLpC3bp19f3C/m6G9ETCV/Un+cqf2PrUx6vtTGy8bn/DkpaZwSfHNzHp6EZcrG35qkId6v35MckX9+DaeCA+g77C0t4lPy5FFHKnT5+mSpUqpi7D5O7XDkqpg1prs550LTdZlFebzkcybOERrsUky8gD8chIFv3NFHmklPoO6AKEa62r37W9IzANsATmaK0/vmvf71rrXrl5f2Nk0fpzEQz77QihcSm80bo877ariK2VZJH4bySL/lYY742MkUVCiPz3sFlUZEc+WVg7Urz7Urw7/kR67CVC5tXn1u730Rmp2Fha8U5Qew52e5UKLt70O7Gdl+oPwfqx14nd/SuXxtck6dxOU1+CEKIIal3Bi2NjWjIia+RBrc+3sltGQQlh7n4AOt69QSllCXwNdAKqAv2UUlXzv7T7a1fRm+NjWzKobgk+2niBBtN2cCQkd3NuCiGEEKLoKbKdTwBKKZwq9yVg0DGcKj1JzN7/EfJrXVJCbncsVXP3YdtjzzO1QXe2RlylTpolB/t/BUpx5X/NCV/yLjoj3cRXIYQoapztrJjRM5B1IxqSkm6g2dc7eW3FKZLTZXEEIcyR1nob8M9e5PrABa31Ja11GrAA6J7vxT2Aq7013z0ZxPKn6xOekEr9adv5cMM5MjINpi5NCCGEEAVMke58+oulvRfeHb6neI+V6IwUbixqReSmlzCkxmFpYcGLVZtxrMdYmhQvw5CQizzXdBTU7Unksolc+V8z0sIumPoShBBFUNuK3hwb24JhDUry2daL1PliG3uuyvwrQhQS/sD1u14HA/5KKU+l1EygllLqzex+WSk1Qil1QCl1ICIiwqiFdqlanONjW9Ir0Jd315yl8Zc7OHUz3qjnFEIIIYR5kc6nuziUbo//wMO41HqJ+GPfEvxzEEmXVgFQ2tmD1e2G80OzfhxJiqeOcxn2PfY2qTfOcvGdIGK2fU9hnD9LCFGwudhZ822vmqwd0ZDEtAyafrWDN1aeIkVGQQlRKGmto7TWz2qty2mtP3rAcbO01nW11nW9vb2NXpenow3zBtTht4F1uBydRJ2p25iy5SKZBrk3EkIIIYR0Pv2LhY0Tni2m4PvkdixsXQlb/jjhq58iMzEMpRQDy9fhxOOv0aNUDYYlpfBcsxfI8K9B6NynCf66D5kJMveKECL//TX/ytP1SzJ5y0VZhUoI8xcClLjrdUDWtgKtd00/TrzWik6Vi/H6ylO0/GYnFyITTV2WEEIIIUxMOp+yYedbH//+e3Fr9D6JF5cR/FMg8Sd/QmtNcXtn5rccwB9thnLe0pq6JRtzoNFg4g8t5eL4QBJPbTJ1+UKIIsjFzppZvWvy5zMNiE/NoPGXOxi36rSMghLCPO0HKiilyiilbIC+wHIT15QrxZ1tWTy4Lj/2C+LEzXiCPtvK1zsvY5BRUEIIIUSRJZ1PD6AsbXBv8Bb+Tx3A2rMqkeuHc/OPx0iPvQRAt5LVOPH4azxdqRFDbb0Y3XgkKVY2XP20LWG/vY4hPdXEVyBE9qKioggKCiIoKAgfHx/8/f2xtLQkKCiIqlWr4uHhQZkyZQgKCqJt27YYDAZeeuklqlevTo0aNahXrx6XL19+4Dk+//xzqlatSmBgIG3atOHq1av5dHVFW4dKxTg+tiVD6pXk080XqDt1G/uvxZi6LCGyVdTzSCk1H9gNVFJKBSulhmmtM4AXgLXAaWCh1vqkKevMC6UUA+uU4PjYljQr68GLf5yg/aw9XI1OMnVpQmSrqGeREEIYk5WpCzAHNh6V8e29kfhjs4ne+RYhP9fGvfH7uAS9gKuNPTMa96Jv2VqM2LGIxpW7MjvyNDVXTybxxHr8R83D1q+KqS9BiH/x9PTkyJEjALz//vs4OTkxduzYO/uHDBlCly5d6NWrFwDz588nNDSUY8eOYWFhQXBwMI6Ojg88R61atThw4AAODg7MmDGD119/nd9++81o1yT+5mpvzZw+NekV6MuIRUdp9OV2xrWuwLvtKmJjJd87iIKlqOeR1rpfNttXA6sf9n2VUl2BruXLl3/Yt/jPAtzsWT28AXP2XmPMipMEfraVL7pXY2i9EiilTFaXEPdT1LNICCGMST6B5JJSFrjUHEnAwCPYlWhJ9LbXCf2tGakRRwFo4VOOIz3G8GJQewb7BPFu7b4kRF7l0ru1iVz5MToj3cRXIMR/c+PGDXx9fbGwuB0bAQEBuLu7P/B3WrVqhYODAwANGzYkODjY6HWKe3WsfHsU1KA6JfjfxvM0mL6dY6Fxpi5LiP9E8ih3tNYrtNYjXF1dc3V8WuRV0iKuPPI6lFI807AUx8a0pLa/K8MXHuXxH/YTFi8jxIV5kywSQojck86nPLJyLkHxbn/g/divZMRfJ3R+I6J3voMhIwV7K2s+qtuZPV1e4nLperSt+SQnfasRvuhNLn1Qj+RL+01dvhAPrU+fPqxYsYKgoCDGjBnD4cOH7+wbPnw4Bw4ceODvz507l06dOhm7zAJBKdVVKTUrNjY2V8cbe6VMV3trvusbxNKh9bgZn0q9adv4eNN5MjINRj2vEMYieWQcN39+gUvja3Bryxyj5FJpDwc2PtuIz7pVZe3ZCAKnbOGP4zce+XmEyC+SRUIIkXuF6rG7/BperpTCqWJv7Eu2IXrb68Tu/4SkC0vwbDMT+4Bm1PYKYE/Xl/nsxBYGHHahd7EqjDu/gcsTGuLR7iWK9ZyIhZ2TUWsU5idqyxjSskbSPSo23jXxbPnZI3mvgIAAzp49y6ZNm9i0aRNt2rRh0aJFtGnThjlz5jzwd3/55RcOHDjA1q1bH0ktBZ3WegWwom7dus/k5viweaNRNvZ493gPC2tbo9XVrZoPjUu789zi47y1+gzLT4bxY98gKnhLHom/FfQsAskjY/EZ8CWhc5/mxvfPEH9wCb5DZ2Pt4f9Iz2FhoXi1eTnaVyzGoPmH6PnjAQbXDWBq9+q42ls/0nMJ8yZZJIQQhUuhGvmUl+HlWmsGzjvEd/uuPfT5LO088G4/B58n/kRnZnDz9zZEbnweQ2os1haWjAtsw8aOz7LRuzxta/XjVt1eRK+bysW3qhF/9KGncBDCZGxtbenUqROTJ0/mrbfeYunSpTn+zoYNG5g0aRLLly/H1tZ4HSvmShsMGFLiiFr5EZffrW30EZJejrb8NrAOvz5Vm7PhCQR9vpWvdsgqVML8SB49epaeJSn52np8BnxJ4pktXHy7OjE7fzHKKKhqPs7sfrEZ49tW4JdDIQR+toVN5yMf+XmEMDbJIiGEyJ1CNfIpL5LSMglPSGX4wqPsuXqL6T2qY2dt+VDvZV+yDf4DD3Fr9wTiDk8j6dIqPFtNw7F8d5oUL8P+rq/Qe/OPNMeCz3pNpsuu77n+eWdcGvTF56mpWLkWf8RXJ8zRo/wmzhgOHTqEj48Pfn5+GAwGjh07RmBg4AN/5/Dhw4wcOZI1a9ZQrFixfKrUvCgLC/yGzcW5bi9ufP8Mlyc0xPOx1/Du8T4WNnbGOadS9KvlT4uyngxfeISXlp5g2cmbzO1Tk5LuDkY5pzAfBT2LQPIot/I6Inzi0fUcigpmdtPBlK3RgdDZgwmdNfD2KKghM7FyebTtZmNlwYSOlelcpTiD5h+m7be7eblZGf73WBXsH/KeTBQekkVCCFG4FKqRT3nhaGvF6uENeatNBebsvUazr3f+p+V/Lawd8Wz+CX59d2Jp70n4yt6ErepLRuJN/B1d2dzpOYZVbMCYyJuMbv4Czt3GE39wCRferELMtu+NPueLEP9VeHg4Xbt2pXr16gQGBmJlZcULL7wAZD+vwWuvvUZCQgK9e/cmKCiIbt265XfZZiE4MQaram0p97+TuDUbStSqT7j0bi2SLu416nn9XO1YNbwB3/YKZO+1WwR+tpUf9l+XPBIFnuRR7uR1wvFidk5sDD1PzaVTWJeWRum3t1PsyU9JOLqKi29VI27/YqPU2aCUO4dHN+f5JqWZtv0ydb7YxoHrMUY5lxCPkmSREELkniqMHzLq1q2rc5rg727LT95k0PzDWFko5j1Vm/aV/tu3EDozndiDnxOz90OUlQNe7WbhWL47Wmu+PbubV/Yuo5SjO0uqNcZhydskn9uBQ9XW+A35FpviplsOWeS/06dPU6VKFVOXYXL3awel1EGtdV0TlfRI5CaLDNpAo5XTSUxP48fm/anjFUDC8bWEfjecjFuheHYag/fjH2BhY2/UWi9HJTH0t8NsuxRNt2rFmdkzEB8X44y8EgWPZNHfCmMe5eW+6FTMTQZunceR6FCGV2zAZ/W7YRV2gdDZg0m5chCXRv3xHfAllk4eRql1/bkInv7tCDfjUxnftgJvtamAtWWR/a60yJEs+ltRzyIhRMH1sFkk/2/O7Ul497/cDH9XOzrN2cukDef+0/wnytIat/pv4PfUAazcyhK+sjdRW8ZAZhrPVm7Mxo7PEp+RSqMDazjU70t8h8wk5fIBLr5dg8gVH6Ez0h/h1Yn/s3fX4VUcbQOHf3ty4h6SEEMS3ENIcAnu7t4Wd6tTSoWW8kKxAgUKFHd3l+AQwR2CxN39nHn/CE2hLdKSA0mY+7pyfZyzMzvP5nvzdHd2RJLyMpWi4nuPliRkplN791ymXDqE0R+joBoMJHrv9OxRUPfO6jQO10ImHB1aO2cXqkozjrP5cohO25QkKe8pb+XA2Taj+bRSQ5beuUC1HbO4bGiG66Sz2HX8loQLG7k/saLO1q5sWtqOKxMa0MPdiW8P3qHuvNPcikjUSVuSJEmSJL09svPpqVJ2ZpwZWZdeVZ2ZtP82HZdfJC71zTqBDGzK4NT1OBbuI0m49AshGxuQGf8gZx2oitYOdDuxmp8tiuL6w3XMqrQmYvOXPPjGk9T7F3LpyiRJyuuaMgIVzQAAwQJJREFUOZfhcocJdHGtwuSAA9TfO5/7Gek4fbiIop8cRGSk8nBKHcLWfYw2I1VncfyxC5X/uPq42pjQbZUffdb4E5OSobM2JUnKewz01Ez1bM3RlkPJFBrq7ZnPd1ePYt1uIq5fn0fPrBBPZrYmZOlANKkJud6+tYkBq3p5sKFvNe5HJ+Mx04df5MYIkiRJkpSvyc6nZ5gaqlnZsyq/dKzIvlsReM324UrIm91UKWpDCnnPxL7NRrLiHxC8pjrJd7c8tw7U1CtH6OS3H/PBqygyZjuapGgCv69J2JqxaNOScunqJEnKy6wNTVjToDdrG/ThTnwkHjtm8uvN05hWaILbD9ew9h5CzP6feTDJnZQ7p3UaS7nC5pweVZdvm5dh4+UQKs84wb6b4TptU5Kkdy/l4UESr6/MWfetvkMJAtqPp6dbVb67dIj6e+cTZF0E1298KdT6c+JO/s6DiZVIun5EJ/F0reLE1Y+9aVTSljHbr9H8t3M8idNdB7wkSZIkSbojO5/+QlEURtRx5fjw2qRmaqn1y0lW+wW98XlNS3bAqdcFDKzLELGnJ1FHR6MvslhUuwvza3XiSOhdauyaw2PXGpSYegPrRsOJOTSX+19W0NnQdkmS8gZNcjhCkz3SsrubO5c7fEzdwq6MPLeNVoeWEC60OH7wK0U/PYzISufhj/UIWzMObfp/3yThVfT1VExqWppzo+tibaxP66UXGLzpMolpWTprU5Kk3KUoSltFURbHx8e/VvmkGyuIOjSQiF2dyUoOA8DSwJgV9Xuy3rtvdsf4zpkseRCAfdcfKf7VaRR9Ix7/rwmhq0ahTU/O9WtwtDBi14DqLOpSmXOPYqk84zir/OTGCJKka4qitFAU5baiKPcURfn8H44XVRTlmKIoAYqiXFEUpdW7iFOSpPxDdj69QO3iNviNq0/1Itb0WxfAyK1XycjSvtE59S2L49jtGBYe40i8spDQDfXJirv3/DpQu+eyPfwhjv3mUXziKVRG5jyZ2ZqgBT3IipcjDySpoBFCS/ie7oSsr0NG1FUAnE0t2ddsEPNqduRk2AMqb5vBhgeXMKvQGLcpV7FuNIyYg7N5MKkKybdP6jQ+DxcrfMfV4xPvEiy98Bj3mSfwuR+t0zYlScod/3a3O7uWq7CpP53UR4cIXlWV5Dubc451da3C5Q4fU8u+OMPObKbDkd9Jcq6A23cB2DQbQ+zheTobmakoCoNqFuPyhAZUdDCn/7pLdF3pS1Ryeq63JUkSKIqiB8wHWgLlgZ6KopT/S7GvgI1CiKpAD2DB241SkqT8RnY+vURhc0MODanJhAYlWHDmId6/niHoDYd7K3oGFKo/jcLttpKV+JjgdTVJur3h+XWgjq3kK799GJaoidt3/th1+o5Ev23c+6IcsT7L5Ns+SSpAFEWFpcdYspKCCV5bk7gL0xDaLBRFYVi5Ovi3H08pC1t6nVhN7xNrSFDp4dhvPsU+P4rQang0tQFhq8foZMTBHwzVekxrUx6f4XVQKdBw4RnG77xOaqZGZ21KkvT2ZeejMTj1voDasjgRe3sRsbcPmrQYILtjfH+zQcyq3p5DIXeosv1n9kY8xKH3bIp9fgyhyeLhj/UI3/Ap2oy0XI/PrZApx4fX4afW5dh9I4JKM06w+4Z8MSdJOlAduCeEeCCEyADWA+3/UkYAFk//bQnIXUokSXop2fn0Cmo9FdPblmdj32pcC0vAc7YPx+5FvfF5Tdza4NzrAgaFKhK5ry9Rh4fjaGjw3DpQ7Q4vI16jwa79JNy+v4yRc0VClw7g0U+NSA+7mwtXJ73PoqOjcXd3x93dHQcHB5ydndHT08Pd3Z3y5ctjY2ODq6sr7u7uNGnSBK1Wy+jRo6lYsSKVKlXCy8uLwMDAl7axcOFCKlWqhLu7O3Xr1uXGjRtv6eryF9OSHXDpewkTtzbEnplE6EZvMmJuAVDa0o6TrUfybdXmbA68TJXtP3Mo+A6m5RpSYsoVrBuPyJ6iO7EyybdO6DTOOq42BIxvwNBaxZnt8wDPWT74PonTaZvS+0Hmo7zFwKYcTt1PYlXrG5LvbSV4pTspgdlLAKgUFaMr1ONC2zE4mljQ/vAyhp3ZDCVr4TblCtbeg4neO53AydVIDcz9LdX1VAqfNizJhTH1KGxmSLtlFxgkpwRLuUTmohzOwJNnPgc9/e5Z3wB9FEUJAvYCo95OaJIk5VtCiAL3U61aNaELN8ISRLlpR4XexzvF/47eFVqt9o3Pqc3KENE+n4sHs/RF0CoPkR59S2i1WvHrzdPCcPmnovSmqeJqTEh2WY1GxBxbLG4OtRQ3BhiKiJ0/CG1mxhvHIL07N27ceNchCCGEmDx5spg+ffpz3/Xv319s2rQp5/PatWtF586dhUajEUII8eTJExETE/PS88bHx+f8e8eOHaJ58+b/WO6ffg+Ar8gD+eRNfv5tLtJqtSLx1nrx8NfCInCuuYjzmyW0mqyc4xcjH4vyW6YJ1bIJYtTZrSI5M10IIUTSzePizgQ3cb0fImTlSKFJTfxX7f4XB26FC5fvDgr1J7vE1/tvifRMjc7blHQnr+QiIWQ+0sXPm9wXpYX7iycr3cWDWfoi4uBgoUn78/eYlpUpPruwS+gt+1iU2TxVnI94JIQQIvHyPnF7jLO4/oGeCN/ytdA+zVW5LS0zS3yx54bQ+3incJ1ySJy4F6WTdqS3R+aiP73LXAR0AZY887kvMO8vZcYDE57+uxZwA1D9w7kGA76Ab9GiRV/6u5EkKX/4r7lIjnz6F8oVNuf86Hp0quTIZ3tu0nWlLwlpmW90TkVPH5t6UyncfgdZSSGErKtJ8q21z60DVXv3L2x5eAVFpcLaexAlpt7EzL0tkZsn8mByNVIf+ufSFUrSi4WGhuLo6IhKlZ02XFxcsLa2fmkdCwuLnH8nJyejKIpOY8zvFEXBrEx3nPsGYFysMTE+nxK6uQmZcfcB8LQtgm+7cYwuX4/5N0/juXMWFyMfY1q2ASV+uJK97sqR+dz/qjLJN4/pNNZmZey5+rE3vas68/2hO9T65STXwxJ12qYk/UHmo7fH0L4qzj3PYen5CUk3VhC02oPUJ9n5xVBPzU9ebTjScijpmizq7pnH95cOYlSxKSV+uIplzV5E7fiOwG9rkPbkau7Hptbjx1blODG8DnoqhYYLz/DJrhukySnB0ltSgHNRMFDkmc8uT7971gBgI4AQ4ixgBNj+9URCiMVCCE8hhKednZ2OwpUkKT+QnU//krmRmg19qzGjbXl2XA+nxpyT3MiFBy4T15Y4976IgZ07kQc+JPLQYGrZFH5uHaiJfnvRaLXoWzlSZOQmiozZgSY5hodT6hB/fkMuXJ0kvVi3bt3YtWsX7u7uTJgwgYCAgJxjAwcOxNf3n6dXzJ8/nxIlSvDpp58yd+7ctxVuvqY2dcS+7VZsmy0hM+oawaurkXD5V4TQYqzWZ1aN9hxsPoTkzAzq7JnHtwEH0OgbZa+78sUJFJUej35qROjKEWjTknQWp5WxPst7VmXrB54ExaVRfY4Pa/3ffHdQSXoVmY/eLkVtiE3dH3DsehxFz4CwLc2JPj4ObWb2jpsNHEpwqcMEeri5803AQRrsXUCgRoPzkJW4jN5GZlwIDyZXI2rXVIQm96fH/TEleFCNYvx84j41557ifpTu1sGTpD8U4Fx0ESilKIqroigGZC8ovvMvZR4DjQEURSlHdudT5FuNUpKkfEX9rgPIjxRFYXyDElRzsaT7Kj9qzD3J0m7udHN3eqPzqs1dcOxyiNiz3xJ/8X+kh13AvtVajrUczqhz2/jpylEuRYewukEvrA1NMPdoh3HJWjz5pRPBC3qQHnQNu47foqhkn2J+NO78Di7H/PWl0pupYuPMrBp/XR/yv3FxceH27dscPXqUo0eP0rhxYzZt2kTjxo1ZsmTJC+uNGDGCESNGsHbtWqZMmcKKFStyJZ6CTlEUzMv3w7hII6IODSH62BiS723Htuli9C2K0dipFJc7fMzo89v47tIh9gXdYnm9npQtUw+37y8TseUrYg7OJunyXpwGLMW0fCOdxdqhoiM1i1rTfZUffdYGcO5xHDPalMdALXNRfpTXcxHIfPS6FEVpC7QtWbJkrpzPyKkmzr19iT39FQmX5pHy8AB2zZZh5FQTSwNjVtbvRWuX8gw/uwWPHTOZWaM9AzzaY1KqDqErhxOx+UsSA3bgNHA5hk5lcyWmP5gZqlnYpTJtyxem37oAvOacZG1vD1qUtc/VdqS3R+aid0cIkaUoykjgAKAHLBNCXFcU5Tuyp9vsBCYAvymKMo7sxcc/eDodR5Ik6R/JJ4M30KCELX7j6lPFyYIeq/0Yv/M6mRrtG51TUamxqfM9hTvuRpMSSci62mTcWsui2l2YX6sTR0LvUmPXHK7FhgKgtrCj+GdHsKr/EVE7pxA0v6tOd72S3m+Ghoa0bNmS6dOn8+WXX7J9+/bXrtujR49/VV7KpjZ3oXDH3RRqvID0sIsEr/Yg8Vr2rpdWhtkPexsa9uV+YjTVds5k3o1TYGCEQ6+ZFP/yJIqePo+mNSZ0+VA0qbqbFudgYcThobUYW9+NeacCabzwDCHxub/blST9QeajVxNC7BJCDLa0tMy1c6r0TSjkPROHzgcQmgxCN3kTc2oiIisdgO5u7lzuMIEadkUZcnoTnY4uJ9bAGJcRG3Eeto6MsLs8+NqdqL0zENrcnx7XunxhLo6tRzFrY1ovPc+PR+4in4clXSqouUgIsVcIUVoIUUII8cPT775+2vGEEOKGEKKOEKKKEMJdCHHw3UYsSVJeJ0c+vSFnS2OODq3Nx7tvMNvnAX5P4tjQtxoOFkZvdF6TYk1x7uNL5L5+RB0aSFrQcQY3nEsla0e6HltJ7d2/8Hu9HnQuXhlFbYDjR0swdKlE+LoJBE6pQ9GxO9EvVDSXrlJ6G3LzTZwu+Pv74+DggJOTE1qtlitXrlC5cuWX1rl79y6lSpUCYM+ePTn/lv4dRVGwqDQQ46JNiDo0iKjDQ7NHQTX5FbWZM12KV6GOvSsDT21kzPnt7HxynWV1u+NSug5uUy4TsWUSMQdmknR1P44fLcWsQmOdxKmvp2JmuwpUL2LFwI2X8Zztw4a+1ajnVkgn7Um6kddzEch8lBcYF2mISx9/on0+Id53OikP92HXbBmG9u64mFpxoPlg5t44xZd+e6my/WeW1OlGq5o9MC3rTeiKYURs+IRE3y04DVyGoVO5XI3NrZApp0fWYfCmK3y17xZ+T+L4vYc7Fkb6udqOpFsyF0mSJBUsBWrkk6IobRVFWRwfH/9W2zVQq5jboSKre1XFLyiearN9OBUY/cbnVZs64tBpP1Y1viLp5hpC1tXCSy/pH9eBUhSFQs3HUnT8HjIjA3nwjRcpd8/kwtVJUraIiAjatm1LxYoVqVy5Mmq1mpEjRwIvXtdg3rx5VKhQAXd3d2bOnJnnhpXnN/qWxXHofAAb71mkBZ0geFVVEm+uRgiBo4kFu5sOYEGtzpyNeEiV7T+z7kEAKgNjHHrOoPjEUyhqQx7/rwmhy4fpdBRUj6rOnB9TD3NDNY0WnmW2zwM58kDKVTIf5Q0qQwvsmi6icLttaFOiCFlfm9jzPyK0WagUFWMr1Od8mzHYG5nR9vBShp/ZQrqpNS6jt+I8dC0ZYXd48HVVovb8L9fXgjIxULOqV1VmtqvAzhvh1Jx7itsRulsDT3o/yVwkSZL0+pSC+EDg6ekpXrTAn65dDU2g8wpfHsakML1teUbXdc2VXSxSnxwjcl8/tOnxFGo4G/2yfRl9fjtL75ynTZHyrPPug4naAID0kJs8md2OzOjHOH64GKu6/d+4fUk3bt68SblyufvGNz/6p9+Doih+QgjPdxRSrtBlLsqMvUvkwYGkh57FxK0tto0XoGdaGIB7CVF84LOOs5GP6ObqzvxanbAxNEGbkZozCkq/UFGcBizT6VpQ8amZfLjhEtuvhdHD3YnFXatgZigH3OZFMhf9qSDmo7dxX6RJjc5em+7ORgwKe2LXfBkGNtnrOqVrspjkv4+Z13woZWHLyvo98bIrSlZ8OKErhpHotw0jt+o4D/wdQ+fyuR7b8XtRdF/lR1qWlpU9q9K+okOutyHlDpmL/iRzkSRJedV/zUUFauRTXlDJ0YKLY+rRupw943Zcp/caf+JTM9/4vMZFGuLU+yKGTrWJOjyUhEMD+NWzOXNqdGDPk5s03b+IqLTstZ4Mncrh+vV5TErXI+S3Dwhf/4lO1lWQJOnd0bcuhWPXo9jUm0bqo4MErXIn+c5mAEpa2HK81XCmeLRk68MrVN42g/1Bt/42CurRtMaErhiusx3xLI312dzPkx9blWXj5RBqzT3FnUg58kCSCiI940LYt1qNfau1ZMUHErKmOvH+cxBCi6Gemv95teVwiyGkajKps2ce3186COa2uIzagvPw9WRG3M8eBbX7p1wfBeVd0hbfcfUpY2dKx+UX+Xr/LbTagvfyVZIkSZLyMtn5pAOWxvps6e/FDy3LsulKKJV/Ps7hO2++86ja1AGHjnuwqjWZ5DsbCV1fi0F25mxs2I+AmGDq753Hw8QYAPTMbCg6YR/WjUcQvW8GT2a3Q5Oa8MYxSJKUdygqPSyrjcOp9wXUlq5E7O1FxN7eaFKjUKv0+KJKY861HYO1oTGtDy1hxNktJGemY1KqNm7fX8KmxXhijy3k/sRKJN84qpMYVSqFzxuVYv+gmoQlplF9zkl2XAvTSVuSJL17pqW74Nw3AONijYnx+YSwzU3JjA8EwNuxJJfaT6C7qzvfBBykwd4F3E+MxrJGd0r8eB0z9zZEbPqCwO9rkxZ0PVfjKmJljM+IOnzgVYQph+/SbtkF4nLh5aAkSZIkSa9Hdj7piEql8EXjUpweWQcTfT2aLT7HyK1XSU5/s7d5ikoP6xoTceh8EG1GEqHr69I0OYCDzYcQnppEnT2/EBCdvS2totbHsd88HPotIOnqAR5+V4uM8Pu5cXmSJOUhBjblcOrug3Xt70i+t53gVVVJvr8TgKqFnLnYdizjKtRn0a1zeOyYxZnwh09HQf38/I54K0fobBRUk9J2+I2rT2nb7JEHX+69iUaOPJCkAklt6oB9263YNl1CeuRlgld7kHB1Sc4unasa9GJtgz7cio/AY8dMfrt9Dj0Le1xGbsZ5+AYyowIJnOxB1K6puToKykhfj6XdqjC/UyUO3Y3Ea7YP10LlizlJkiRJehtk55OOVS9qjf/4Boyp58qCMw+pOsuHMw9j3vi8xi71ce59EUOnOkQdGkjFR+vxaTUCfZUeDfct4HDInZyyNo2HUeyTg2TGhxL4bXWSbx5/4/YlScpbFJUaq+qf49TzDHomhYnY1YXIAx+iSYvFSK3PjOrtONJyKFlCQ4N985not5d0TRYmpetkj4JqPo7Yo79mj4K6eUwnMRa1NsFnRB0G1ijKT0fv0fK3c0Qlp+ukLUmS3i1FUTCv0A+XPv4YOtQg+shwwre3JSsp+wVZdzd3LneYQE27Ygw9s5kOR34nIi0JyxrdskdBVW1HxOYvCfy+FmlB13I1rmG1i3NsWG2SMzTUnHuKjZdCcu38kiRJkiT9M9n59BYY6+sxq31Fjg6tRZZGS/35p/ls9w3SMt9sHSY9E3scOuzEtGxPYs9MpvClqZxsOYxipta0PriENff9c8qalm+E2+QL6FkW5tH0psQeW/SmlyVJUh5kaFcFp55nsKrxJUm31hO8qiopDw8A0MChBAHtJ/BBSS9+unKUmrvmcCUmBJWhCQ69ZlL8Sx8UPTWPfmqks1FQRvp6LO5ahd+6VuFkYAyes05y8XFcrrcjSdK72wX4WWqLojh02kuhhnNICz5F8KqqJN3eCICLqRX7mw9iVvX2HAq5Q5XtM9j5+DpqC3uKjNyEy4iNZEY9InByNSJ3/Ziro6BqF7fBb1x93J0t6LHaj0933yBLo82180uSJEmS9DzZ+fQWeZe05fIEbz6qXpTpx+/jNfsk/kFxb3RORc8Au+a/Y+ExjsTLv2LgM4JjzQdQt7Ar/XzWMuPqsZwtzg0Kl8R10lnMKjQldPlQQleNyvVFPSVJevcUPQOsa32DU49TqAwtCd/elsjDQ9FmJGJhYMRvdbuxvfGHhKclUWPXHP535SgarRaT0nVx+/4yNs3GZo+C+qqyzkZKDqhRlJMj6gBQb/5plpx/pJN2JOl9JoTYJYQYbGlp+U7jUBQVFlWG4dzHF33rMkTu60PkwYFoMxJRKSpGV6jHxbZjcTaxpOOR3xl8ehNJmelYVO9KiR+vY+7RgcjNEwn8riZpT67mWlyOFkYcHVqbobWKMeP4fVouOS9HY0qSJEmSjsjOp7fM3EjN4q5V2DOgOjGpGdSce4rvDt4h8w3etimKikL1p2FTbxopd7eSvrcbuxt0o2vxKnzmu4fxF3aiFdnn1zOxpMi4Xdi0mEDs4Xk8/rklmuTY3Lo8KR+Jjo7G3d0dd3d3HBwccHZ2Rk9PD3d3d8qXL4+NjQ2urq64u7vTpEkTtFoto0ePpmLFilSqVAkvLy8CAwNfq60tW7agKApye923y7BwNZx6ncfS82OSri8neE110sMuAtC2aAWudPiYNkXK84XfXhruW8D9hKjsUVC9Z2WPglLp8einhoSuHKmTUVCeRazwHVcP7xKFGLzpCgM3Xn7jEaFS/iTz0ftB36okjl2PZo/MvLma4LU1SA/3A6CCtQNn24zms0qNWHbnAh47ZnI24iFqCztcRmzAZeQmMqMf82ByNSJ3TEFk5c5i4QZqFQs6V2ZJtyqcCozJlReDUv4lc5EkSZIOCSEK3E+1atVEfhCdnC56r/YTyoSdwmvWCXE9NOGNz5l4c414MMdYBK3yEOkJQWLcue1CtWyC6HZ0hUjNzHiubOyJZeL6h/ri7ielRFrwzTduW/r3bty48a5DEEIIMXnyZDF9+vTnvuvfv7/YtGlTzue1a9eKzp07C41GI4QQ4smTJyImJuaV505ISBD16tUTNWrUEBcvXvzHMv/0ewB8RR7IJ3/8AKbACuA3oPfr1MlLuSg16KR4tKSEeDDbSMSe/1FoNVlCCCG0Wq1Yfc9PWK+eKMxXfiEW3jwjtFqtEEIITVqyCF09Rlzvr4g7E1xF0o1jOoktS6MVX+27KZQJO4XnrBPiYXSyTtqRXiyv5CIhZD7SxU9eykV/SHniIx795ioezDEWsRenC61Wk3PMJ/S+cN04Rah//1hM8tsnMp7mq8yESPFkfg9xvR/i/iQPkfrocq7GdOFRrCjy3UFh/NlusdL3ca6eW3o9Mhf9SeYiSZLyqv+ai+TIp3fIxsSA1b092Ni3GoExKVSb7cPME/ffaAcos7K9KNx+B5nxDwjf6M3UkmX4n2cbNj+8QqtDvxGXnppT1qr+hxT//BialDgCv69J0tUDuXFZUgEVGhqKo6MjKlV22nBxccHa2vqV9SZNmsRnn32GkZGRrkP81xRFWaYoSoSiKNf+8n0LRVFuK4pyT1GUz59+3QnYLIQYBLR768G+ISPnujj39sW0dBdiz0wmdEtTMhMeoSgKvUt4cKXDx9S0L8bws1tofWgJISnxT0dBzabYFydAUWWPglo1Cm16cq7GpqdS+L5FWbZ/6MXdqGQ8Z/tw6E5krrYhFSwFMR+9b4xd6uHcxw8Tt7bEnvqSsK2tyErKXvi7noMbl9pPoE+Javxw+TB19/zC7fgI1Oa2uAxfh8uoLWTGBvHgG08id3yfa6OgvIpa4Tu2PjWLWdN/3SVGb7/2RiPTpYJP5iJJkqTXJzuf8oAuVZy49klDmpex4+NdN2j06xkeRP/3hzuTYk1x7HIYbVYKYZsaMsLWhFX1e3Em4hEN9s4nKDnuz7Kl6+D6zUX0CxXj8c+tiD44549RHpL0nG7durFr1y7c3d2ZMGECAQEBOccGDhz4j8PG/f39efLkCa1bt36bof4by4EWz36hKIoeMB9oCZQHeiqKUh5wAZ48LZYv54bpGVlh12Ilds1/JyPyMiGrPUm6vQF4uvBvs0H8UrMjPmEPqLxtBusfZP//2LRMPUpMuYJNszHEHpnP/YmVSb51Itfja1fBgYtj6uFoYUSL387x45G7aN+gM14quApoPnrv6BlZY996PbZNFpIeeo7g1dVIvr8LAAsDI36v14ONDfsRmBhDtR2zWHDzNEIILDw7UeLH61h4dSFy69cEfleDtMeXcyUme3NDDg6uydj6bsw7FUiThWcJT5TrQEn/TOYiSZKk16d+1wFI2QqbG7LtAy9W+gYxZsc1qvx8ghltyzO4ZjEURfnX5zMsXA2n7icI29aGsC3N6NB6HYWbDqTz0eXU2f0Le5sNooK1AwAGtsVw/eo0wYv6Er5mLOlB13DsNx9FbZDblym9RNiasaQ9vpSr5zQq6o5D79m5ci4XFxdu377N0aNHOXr0KI0bN2bTpk00btyYJUuW/K28Vqtl/PjxLF++PFfa1wUhhI+iKMX/8nV14J4Q4gGAoijrgfZAENkdUJfIxx33iqJgVq43hk61iNz/AZH7+pL68ACFvGejMrRgeLk6NHEqzYcn19P7xBp2PL7O/FqdsHk6Csq8WidCln7Eo6ne2DQdhX3XqagMTXMtvlJ2ZpwdVZchm6/w1b5bXHwcy/IeVbE01s+1NqSXy+u5CApmPnpfKYqCecWPMHSqTeS+vkTs6ox55aHY1J+GSm1M5+KVqW1fnAGnNjDq3DZ2P7nB0rrdcTS3xWXYWhK8uhK6chgPvvHErt0kbNt8gaJ+s3yh1lMxs10FPF0sGbTpMtVm+bC5vyc1i716RIuUe2QukiRJKljy7QNUQaQoCv29inD1Y29qFbNm2JartFpynuD41FdX/gf6ViVx6nYCfZsyhO/sRPXYsxxvOZwsoaX+3vmcDHuQU1ZlZIbLqC3Ytp1I3IklPJrWhKwEOe1Fep6hoSEtW7Zk+vTpfPnll2zfvv2FZRMTE7l27Rre3t4UL16cc+fO0a5du/ywsKYzf45wguxOJ2dgK9BZUZRfgV0vqqwoymBFUXwVRfGNjMy7f0P6lm7ZC//WnETSrbUEr/EiLeQcAKUt7TjRajhTPFqy7dFVKm+bwb6gmwCYlq1PiSmXsWk6mphDvzwdBeWTq7GZGqpZ1asqczpUZM/NCLzmnORaaEKutiHlf+9JPnpvGNiUxan7qezde68sJGRdLTKisne2czSxYE/Tgcx7OjKzyvYZbH2YfczCs2P2KKjq3YjcNpnAb6vn2iioXh4unBlVF0O1Cu8FZ/jtnNyVU/o7mYskSZJejxz5lAcVsTJm/6CaLDz7iE9336DSjBPM7VCR3h7O/3oUlJ5pYRy7HCZ8dzeiDg2keJ0pnGo1ktaHl9D84GJW1e9F5+KVAVBUKuy7TMHQuTwhSz8i8NvqFBm7E6MilXRxmdJf5OabOF3w9/fHwcEBJycntFotV65coXLlyi8sb2lpSVRUVM5nb29vZsyYgaen59sIN9cJIZKBD1+j3GJgMYCnp2eenjOmqNRY15yEcdEmRO7vT+imhljVmIhV9c9Rq9R8UaUxLV3K0t9nHW0OLWVwmZpM92qLmaEpDn3mYO7ZmZAlH/JoagNsmo7GvuuPuTYKSlEURtV1paqzBd1W+lFz7il+61aFnlWdc+X80ovl9VwEMh8VVIrakEL1p2FctDFRBwcQsq42NvWmYV5lGIqiMKxcHRo6lqL/ybV0PbaCfiU9mVOjAxZmhXAZuiZ7FNSKoQR+W53CvWZj3Wjofxo9/qwqTpZcHFuPXqv9GbL5Cr5BccztUBFDtV4uXbX0IjIXSZIkFSxy5FMepVIpDK9TnEsTGlC+sBn91gXQdaUvEf9h3QGVgTkO7XdgWqY7sae/wsL/B3xaDsfDxpnux1Yx/8ap58pb1upF8S98EFnpPJxSm0T/nbl1WVI+FhERQdu2balYsSKVK1dGrVYzcuRI4MXrGuRTwUCRZz67PP2uwDJyqoVz74uYle1B3LnvCN3UmMz47K2i3Qs5c77tGD6u6M1vt89TdcdMToVnHzMtW58SP1zBpukoYg7N5cHXHqQ9upSrsdV1LYTfuPpUc7Gk9xp/Wiw+x4XHsbnahpT/vEf56L1kUrwZzn38MCrSiOjjYwnf2RFNSvZI0rJW9pxqPYqvqjRh9X0/3Hf8nDOS26JaB0r8eB3T8o0JWzmc4IW90aQmvnE8NiYG7BlYg88aleS3c4/xXnCGWxFvfl4p/5O5SJIk6fUpBXFxaU9PT1GQkr1GK5h54j6T9t/G0kjNwi6V6VjJ8V+fRwgtMT6fkhAwF9NSXTBtvIjepzaz68l1PqvUiB+qtXzuDWFmTDBP5nYgLdAXm+bjsO/yIyoDuStHbrp58yblypV712G8c//0e1AUxU8IofNXgU/XfNothKj49LMauAM0JrvT6SLQSwhx/d+eOz/moqRb64k6mn3jbNtoLmZle+UcOxn2gA9PrudhUiwfV2zAtx4tMNTLHkCbfPMYwQv7oEmOpnDPWbky4uBZmRotc08GMu3YPaKSM2hbvjDfNi+Du7NlrrXxPpO56E/vMh/lNkVR2gJtS5YsOeju3bvvOpx/TQhBwqX5xJz6HD2jQtg1X4Zx0cY5x89GPKS/zzoeJMbwSSVvvqnaHEM9NUKrJXrPNCK2fIWBQylcRm7GyKVirsS05UoIH224THJGFr09XJjUtDQlbXNv3bv3ncxFfypIuegP+fG+SJKkv/uvuUiOfMoH9FQKnzQsie/YerhYGdF5hS/91wUQl/rvthZWFBU29adjXXcqyXc3k7CnCxvrdGRwmZpMu3qUD06uJ0OTlVNe38aZ4l/6YN14BDEHZhH4jWeuj2qQpHdJUZR1wFmgjKIoQYqiDBBCZAEjgQPATWDjv+14UhSlraIoi+Pj43M/aB0zK9sD596+GNhWInL/B0Ts64c2Pfs66jm4EdBhPANL12D6tePU2DWHS9HZg8JMyzXE7ftLmJZrRNjK4QTN74bmmZ0135S+nooJ3iW4/0Vjvm9RhpOBMXjM8qH7Sl9uhMkRCJL0T4QQu4QQgy0t82cnraIoWFYdiVOP06gMLQnb2pKYk58jNBkA1LIvjn/78XxUujr/u3qMWrvncj02DEWlwrbtFxT77AialDgCv61O3KkVuRJT58pO3PuiEeMblGDzlRDK/e8YAzZe4mFMSq6cX5IkSZIKKtn5lI9UdLTg3Oh6TGpamrUBwVSacZyDtyP+1TkURcHKcwK2zZeRFnySyK1NmVu5Dt9VbcHq+360O7yMxMy0nPIqA2Mc+82j6IR9aJJjePBtdaL2TENo8+VO85L0HCFETyGEoxBCXwjhIoRY+vT7vUKI0kKIEkKIH/7DefP1A5++ZXEcuxzGqtY3JN/ZRPBqT9KCTwNgrm/Ewjpd2NVkAJFpSdTcPZefrhwhS6tBbWFHkXG7se/+PxL9t/Pg66qk3r+Qq7GZG6mZ2KQ0D75szFdNSrHvdgSVfj5Ov7X+3ItKztW2JEnKGwztquDU8xzmlQYT7zeTkA31yYy9A4CZviGL63RlW+MPCUmJx2vXbOZeP4kQAtNy3pT47hLGbjUI+e0DQpYORJvx3zZxeZadmSH/a1Oe+180ZkSd4qz1D6b0T0cZuvkKT+Le/PySJEmSVBDJzqd8Rl9PxbfNy3B2VF0sDNW0+O08I7ZeJTXz33UGmZfrQ+F228iMvUvYRm8+LVaM3+p042joPRrt+5WwlOd3ljKr3AK3H65iXrUdERs/5+FUbzIiA3Pz0iRJykMUlR7WNb7EsdsJUOkRurkxsWe/QWizR0e2KlKOKx0+pkPRikz020eDvQu4Gx+ZPeKg1ScU/9IHhJbAH+oQvX8muT3F28pYn+9alOXBl435uEEJtlwNpdz/jjFo02UeyREIklTgqPRNsG08D/s2m8hKeEjw2hokXl+Rk1vaFa3A5Q4f08SpFOMu7KDL0RXEpaeitnKg2KeHsnfz9VlK4Hc1SQ/LnSmIDhZGzG5fkbufN2JQzWL8fvExpaYeZdS2q4QmpL36BJIkSZL0HpGdT/mUZxEr/MbVZ2x9N34985Dqs09y9V9uRW5SvDmOXQ6hzUwkZGMDeluo2N74Q27FR1B3zzzuxD+/TbzarBAuIzfhNHgl6U+u8OCrKsSdXJ7rD5Xvm/f99/e+X39eZ+RYPXsx8nJ9iDv/I6EbG5IZdx+AQkamrG/YlzUNenM7PgLPnbNZe98fAJOStXD7/hLm7m0JXzeBJ7PbkZUUnevx2ZoaMu3pCIThtYuzyjeI0tOOMnLrVULi5cPfvyH/FuXvID8wLdke5z5+GBb2IurQICL39kaTFgdAYWNzdjT+iBlebdn95AZeu2bjHxWEoqfGvssUiozfS1ZsMIGTq5FwYVOuxeRiZcz8TpW481kj+nq6sPDsI0r8eIQJO6//p41i3nfy71D+DiRJKphk51M+ZqSvx8x2Fdg3qAZRKRlUn3OSeacC/9V/sAwdvHDqdhyVvhmhW5rirXnCkRbDSMxMp96eeZyPfPRceUVRsKrTF7cpVzAqVpWQJR8S9EtnshIiX9CC9DJGRkZER0e/tzcZQgiio6MxMpIL2edlKgNz7Jotwa7VGjJjbxO8xovEGytz/nfbw60qlzpMwL2QE3191jLo1EZSsjLQM7XGZdQWHPr8QvK1gzyY5E7y7ZM6idHBwog5HSpy94tGfOhVlMXnHlFyqnz4e13vey4CmY/yE7WZMw6d9mFdZwrJ97cTvObPqcGKojCuYgOOtRxOhiaLOnt+YeGtMwghMK/SErfvAjB0rkDQ/G6ErR6NyMrItbiK2ZjwW9cq3Pq0Id3dnZhz8gFuPx7h8z03iU7OvXYKMpmLZC6SJKngkrvdFRARiel8tOESe29F0KZcYZZ2r4KdmeFr189KDiN8e1syoq9j23Qx4c4taHnwN0JTEljfsC9tipT/Wx2h1RC9fxaRWyaiMrXGacAyzKu0ys3LKvAyMzMJCgoiLe39HaFhZGSEi4sL+vr6z32f33d0gYKZi7ISHhN54EPSgk9iWrorhRrNQ8/IOvuYVsO3AQeZeuUo5a3sWefdlwrWDgCkPvQneEF3MiIeYNfpO2zbfI6i0tNZnA+ik/n+0B1W+QVhrK/H6HquTGhQAhsTA521mZ/JXJStoOajgpiL/pAedpGIff3ISgjEqvqXWNX4EkWVvQtnVFoy/XzWciD4Nj3cqrKwdmfM9Y0QWRmEb/ycmAOzMHKrjsuIjRjYFsv12G5HJPH9oTusuxSMmYGaMfVcGd+gBFbG+q+u/J6SuSibzEWSJOVl/zUXyc6nAkQIwS+nAvl0901sTPRZ0bMqTUvbvXZ9bXoC4bu7kvbkGNZ1p5JWfhDtDi/DPzqYMRXq8b1HC0zUf39wS3t8heBFvUkPuoZ1w6EU7jkDlaHcdlh6M/n5Biu/b2/+KkKrId7vZ2LPfoOeqSN2zX/H2KV+zvFDwXfo57OWxMx05tbsyIelvFAUBU1qAqHLh5Jwbh2mFZrgPHgVaisHncZ6OyKJbw/eZv2lECyM1IyvX4Kx9V2xMJIPf9Lry8/5CAr+fZE2I5HoY2NIurkaQ8da2LVYgb5l8exjQsu0K8f4OmA/pSxs2eDdj0o2jgAk+G4lZMmHoNLDefBKzN3b6CS+62GJfHvwNpuvhGJppGZ8gxKMqSfzkPTvyVwkSVJeIDufnvG+J7YrIQn0WuPHjfAkJjQowQ8ty2Kgfr0ZliIrncgDH5J8dzMWVcdgUOs7PvPdy6LbZ3EzL8TiOl1p6Fjyb/W0GWlEbPmKmAMzMbAvidOQVZiUqJHblya9R/L7DRYU/FyUHuZLxP5+ZMXdx9LrU6xrfo2il/0wFZaSQF+ftRwNvUcvNw8W1O6UPeJACOJ8lhG2ehQqYwuch6zGrEITncd6NTSBbw7cZtu1MGxM9Pm0YUlG1C6OqaFa521L+V9+z0cFPRf9IenWOqKOjkJR9LBruQqT4s1yjh0PvUfvE2uIz0hjXq1OfFDKC4CM8PsEze9K2qMACrX+DPvOU1D0dJMXLofE882B2+y4Ho6NiT6feJdkZB2Zh6TXJ3ORJEl5gex8eoZMbJCSkcXHu26w8OwjPJwtWdPbgzL2Zq9VVwgtMSc+JuHSPEzLdMeu2VJORDxm8OlN3E+MZlDpmkzzao2lgfHf6ibfPEbw4v5kxYVg2+4r7NpORFHLN3vSv5ffb7Dg/chF2owkon0+JunaMgwdamDfeh1qcxcANFotP105yjeXDlDS3JZ13n1wL+QMQFrQNYLndyc99Ca2bb7EruM3Onvge5bvkzgmH7jNvlsR2JsZ8EXjUgypWQwjfd1NAZTyv/yej96HXPSHzPgHROzqSkbUNazrfI+l5ycoigJkd4r3ObGGY2H3+aCUF7/U7IiJ2gBtRhrha8cSe2wRJqXr4Tx8PfrWTjqL8dk8ZGdqwGeNSjKsdnGMZR6SXkHmIkmS8gLZ+fQMmdj+tONaGAM2XiItU8ucDhX5qHqRnJuwlxFCEO87ndjTX2FUpBH2rdaQrm/ONwEHmHXdB0djCxbU7vyPa0FpkuMIWz2K+DOrMXKrjvOQVRg6lNbF5UkFWH6/wYL3Kxcl391C5MFBKPom2Ldcg3GRBjnHToTdp8+JNUSnp/Bz9XYMLVMLRVHQpicTtno0cT7LMC5dF5dh69C3cXkr8Z55GMPX+29z9F4UzpZGTGxcio+qF33tUaLS+yW/56P3KRcBaDOTiTo0hOQ7GzEp1Qm7pktQGWS/gNNotXx76SA/Xj5CBavCbGzUjzKW9gDEnV5N6PIhqAxNcR62VuejMs8+jGHygdscvhuFg7khXzQuxeCaRTFUy04o6Z/JXCRJUl4gO5+eIRPb84LjU+m3NoBj96PpWtmRhV0qY/2ai+4m3lhJ1OFh6Jk6Yt9qDUaONbgQ+ZhBpzZyLS6MHm5VmV2jPXZGfx9VFX9+I6ErhiIy0yjc42esGw19rY4vSYL8f4MF718uyoi5ScSubmTG3cOm7o9YeIzN+ZuPTEviA5/17A++RefilfmtTtec0ZPxZ9YQumIoitoQp0HLdbbuyj85ejeKrw/c4szDWIpbGzOtTXm6VtHdiAcpf8rv+eh9y0WQ/RItwX82Mae+QN+mLIXbbELfulTO8QPBt+l3Yi1pmiwW1elCD7eqAKQH3yBoXlfSQ29i1+EbbNtN1OnmCAA+96P5+sAtfB7E4GJpxMQmpfjQS3aGS38nc5EkSXlBge18UhTFFFgAZADHhRBrXlVHJra/02gFM47fZ9L+WzhaGLK6lwf13Aq9Vt30cD8i9vQiK+kJNnV+wMJjLJlaDT9dOcqPV45gqW/EnJod6O7q/rfOpcyYYEKWfkTytYOYVW6J04BlOl9gWCoY8vsNFryfuUibkUjkwYGk3NuGaaku2DZdnDPiQCu0zLx2gol++yhiasU67z542RUFID3sDsHzu5P2+BI2LcZTuOtUlH/Y4EAXhBAcuB3JxH03CQhOYGitYsxqX0GOPpBy5Pd89D7moj+kPj5CxN4+oM3CruVKTFxb5hwLSo6j5/HVnIl4yNCytfjZqx1Gan206cmELh9K/JnVmFZshvOQ1agtXn8Dl/9CCMHRe1F8vf82Zx/FUsbOlE39PKnoaKHTdqX8ReYiSZLygv+ai97JKxVFUZYpihKhKMq1v3zfQlGU24qi3FMU5fOnX3cCNgshBgHt3nqwBYSeSuGzRiU5PbIuhmo9Gv56hq/33yJLo31lXcPC1XDqdR4TtzbEnPyMiF2d0MtM4OuqzfBtNxZXcxt6n1hDxyPLCU6Of66uvo0zRSfsw6HPXJJvHuP+xIok+G7V1WVKUp6gKEpbRVEWx8fHv7pwAaMyMMe+9Xqs604l+d5WQtbXJiPmdvYxRcXHlRpyvNVwNEJLvb3zmXPdByEEhg6lKT7pLNaNRxCzfyaBU+qSERn4VmJWFIUWZe05N7oeH3uXYOHZR9Sbd5qHMSlvpX1J0pX3ORf9wbhoY5x6nkVtWZzwHR2IuzAVIbLvfVxMrTjachgTKjZg4a2z1Ns7jweJ0agMTXEavBLHDxaRcvsED76uSsqd0zqNU1EUGpey49TIOuz6qDrxaVnUnHuKNf5BOm1Xkl7kBc9lfy3TTVGUG4qiXFcUZe3bjlGSpPzlnYx8UhSlPpAErBRCVHz6nR5wB2gKBAEXgZ5Ae2CfEOKSoihrhRC9XnV+2av+colpWYzZfo3lvk+oVcya1b08cC1k8sp6QggSLi8gxufT56bhabRa5tzwYZL/fgxUav7n1YaBpWv8bRRUeshNghf2Ie2RP5Z1P8Chzxz0jOUbPemf5fe3eyBzUeqTY0Ts7Y3QpGPXbCmmJTvkHItJT2HgqY3seHyNtkUqsKxed2wMs/NQgu9WQpZ+BIDTR0uw8OryVuPefi2UD9dfQqUorOhZlTblC7/V9qW8J7/no/c9FwFoM1OIOjKM5FvrMCnRHrvmy1AZmOcc3/HoGh+d2oBAsKxuDzoUqwhA6qMAguZ1JTPqIYW7TcOmxfi3soRAaEIaPVf74fMgRo7GlHK8rVz0oucyIcSNZ8qUAjYCjYQQsYqi2AshIl52XpmLJKlgyFcjn4QQPkDMX76uDtwTQjwQQmQA68nueAoC/liBVk5+zwXmRmqW9XBnbW8ProcnUnXWCdYFBL+ynqIoWLqPwKnbCRRFj9BNDYn3n41KURhf0ZvLHT6maiEnhp7ZTLMDi3iQGP1cfUOncrh+fRbbthOJP72SB19VIfn2SV1dpiRJ75hxkYY49zqPgXVZInZ3I+b0VwitBgAbQxO2NOrPnBodOBB8C48dMzkdnj3SycKzE27fBWDgUIageV0JXTEcbUbaW4u7Q0VHfMfWp7iNMe2WXeDLvTdfa5SoJEl5l0rfBLvmy7GpP4OUB7sJWV8nZ1QmQPtiFfFtN5ZSFrZ0Prqcjy/sJFOrwbhYVdy+9cPcoz3h6z8maG5HNMmxOo/X0cKIw0Nq5YzGrD//DI/kaEzp7XnRc9mzBgHzhRCxAK/qeJIkScpLnTnOwJNnPgc9/W4r0FlRlF+BXS+qrCjKYEVRfBVF8Y2MjNRtpAVEj6rOXBrfgIoO5vRe488H6wJITMt6ZT1DB8/saXiurYnx+ZSIXZ3RpMVQ0sKWwy2GsqBWZy5GPaHK9hnMue6DRvvnQ5uiNsC+yxSKTzwJiopHUxsQvvFztJnpurxUSZLeEbV5ERy7HsW84kDiL/6PsO1t0aRGAdkd2iPL1+VU61Hoq/RouO9Xpl05ilZoMbBzxXXiSQq1/JjYo78S+H1N0kNvv6K13FPC1pTTI+sysEZRfjp6j2aLzxGW8PY6wCRJyn2KomDpMRqHTvvQpEYRsr4OKQ925xx3NS+ET6uRjChXh1nXfWi4dwFPkuLQM7HEZeRmCveeTeLlPTz42oPkWyd0Hq9aT8X/2pRnS39PbkcmUW22Dwduy+d76a140XPZs0oDpRVFOa0oyjlFUVq8tegkScqX8lLn0z8SQiQLIT4UQgx72WLjQojFQghPIYSnnZ1uF4UsSIrbmHB8WG2+blqa1f5BeMw6wYXHr36jp2dkhX2bjdg0mEnKwwOErKlBWugFVIqKIWVrcbXDJzRwKMH4Czupv3c+N+LCnqtvUqo2JaZcxqr+AKL3TOPhD3XJjH6sq8uUJOkdUtSG2DZZgG3TxaQHnyR4bU3Sw/1zjlezdcG33Vg6FavEl357aX1oKRGpiShqAwr3mE6R8XvIigniweRqRO+ficjKfCtxG+nrsbhrFX7v7s75x7F4zPLB5370qytKkpSnGRfxxrnnOfStShK+sxOx577PWQfKUE/N3JodWefdh2txYVTbOZN9QTdRFIVCzcZQ/MvsEduPpnoTvLg/WQm67wzqWMmRi2Pq4WxpRKsl5/n24G202ry9YZD0XlADpQBvspdK+U1RFKu/FpIDBCRJ+kNe6nwKBoo889nl6XeSjqn1VHzTvAzHh9cmUyOoO+80U4/cRfOKGxtFUbCsOhKnbidAUQjd5E28/xyEEBQxs2JXkwGsrN+LuwmRVNsxiymXDpH5dMoNgMrIDKePfsNl1BYyQm/zYHI1kq4f0fXlSpL0jphX+ADHbscBCN3YgMTry3OOWRoYs867D7/W7sKJsPt47JjF8dB72fWqtMLt+0uYlqlP+LoJPJjsQfItn7cWd3+vIpwbXQ8LIzWNF53lf8fuyQc/Scrn1BZFcex2DLNyfYg79z0Ru7qgTf9zYfZuru5caDsWZxNL2hxayld++8jSajApWZMSP16nUJsviD+3jnuflSHmyK85U4p1pZSdGWdH1aWvhwvfHrxD66XniUqWo8YlnXmd57IgYKcQIlMIEUj2GlGl/noiOUBAkqQ/5KXOp4tAKUVRXBVFMQB6ADvfcUzvlbquhQgYX5+OFR2YuO8WzRadJTg+9ZX1sqfhXXg6De+Tp9PwYlEUhd4lPLjW8RM6FKvE5IADVN85G7+o53dusfDshOs3F1Gb2/N4ejOi9kzjXSyEL0mS7hkWroZzr3MYOtcl6tBgog4PR2RlP0ApisLgMjU512Y0FgaGND2wiO8CDqLRatG3caHI+D24jN6GNjWBR1MbELyoL1l/GVWpK5UcLbgwph6dKjrw+Z6bdFpxkdiUjLfStiRJuqFSG2PbbCmFvGeT8nD/03WgbuUcL21px5k2o/moVHWmXjlCswOLCE1JQGVoQuGuP1JiymWMilUlbOVwAr+rRWqgn07jNTFQ83sPdxZ2qcyxe9F4zjrJxcdxOm1Tem+9znPZdrJHPaEoii3Z0/AevMUYJUnKZ95J55OiKOuAs0AZRVGCFEUZIITIAkYCB4CbwEYhxPV3Ed/7zNrEgPV9q7G0WxUuPImjys8n2HY19JX1/pyG9/PTaXjVSQu9AIC9sTnrvPuwtdEHRKYlU3P3HD6/uJvUZ6bOGDqWwXXyeSw8OxOx8XOC5nVFk5qos+uUJF2S25u/nJ6xLQ4ddmPp9SmJ15YQuqkRWYl/Li1R2caJC23H0tvNg28vHaT5gUWEpMSjKAoW1TpQYupNbNtOJOHCRu59Xobog3MQmlevV/emLIz0Wd+3GrPbV2DfrQg8Z5/EPyhO5+1KkqQ7iqJg4T4ch04H0KTHEbK+Dsn3duQcN1br81vdbvxerwcXo55QbecsjobcBbI3Uin22RGch64hM+Yxgd96EbpyJJrkOJ3GO7hmMU6NrIOiQL35p/n1zEP50k7KVS96LlMU5TtFUdo9LXYAiFYU5QZwDPhECCHnpkuS9EJKQfqPlaIobYG2JUuWHHT37t13HU6+dycyid5r/PELimdQzaLMbFsBU0P1K+ulh10kYm9vspKCsak7FYuqo3K2JY5LT+WTi7tYdvcCpSxs+a1ON+o5uOXUFUIQs38m4Rs/w6BwKYqM3oahU1mdXaOUd+X3rc1Bbin8OpLvbSfy4AAUPUPsW63BuEjD546vuHuRkee2Yqo2YEX9XjR3LpNzLD3sDmGrRpF87SCGRSrj2G8+JqXrvpW4zz2KpfsqXyKSMpjToSKDahR9K9uvS+9Gfs9HMhe9nqzEIMJ3dyMj3BerGl9iVfNrFOXP97TXY8PodmwldxIiGV+hAd9UbY6xWh8ATXIcEVsnEXtkAXoWdjj0+BmLWr10mheikzPoty6Afbci6OPhzK+dK7/WfZqUf8lcJElSXvBfc1GB6nz6g0xsuScjS8vXB24z/fg9Stmasqa3B9VcrF5ZT5MWS9ShQaTc34mJW1tsmy1Bz8g65/jhkDsMOb2Jh0mxDCtbm6merTDXN8o5nnzzGEHzuyMyU3EauBwLr866uDwpD8vvN1ggc9Hryoi5TcTubmTG3sa6zhQsq0147oHtZlw4PY6t4lpcGEPL1mJqtdZYGGTnCyEEib5bCVs7jqyYJ1jW7U/hbtNQWxbWedxRyen0WRPAwTuR9K3mwoJOleSDXwGV3/ORzEWvT5uVRvTRUSTdWIGxayvsmi9Hz8gq53hSZjrjzu/IeYm2uE5X6juUyDmeGuhH6IphpAVexKSsN479F2DoVE538WoFPxy5yzcHb1Pe3pwtH3hS2s5MZ+1J75bMRZIk5QX/NRflpTWfpDzIQK3ip9blODykFskZGmrNPcW0o/deuRi5npE19m02PZ2Gt5+QNdVJD7uYc7yJU2mudPiY0eXrsfDWWWrsmsOd+D93wDAt1xC37/wxcCpP0LwuhG/47K1Mq5Ek6e0zsCmDU4/TmJbsSOypL4nY0wNtxp/TbstZFeZc2zGMKV+PRbfOUXHbdHY9zp6VrSgKFl6dKfnTTQq1/pz4s2u593kZYg7N03nOsDU1ZM/AGnzTrAyr/YOoOfcUtyOSdNqmJEm6pVIbYdt0MYUa/kLqo4OErK9NRvSNnONm+ob8VrcbB5sPIUurpeG+XxlxdgsJGWkAGLtWw/Xrszj0/5W0x5e4/1UVwjd+gTY9RTfxqhQmNS3N/kE1CUtMw2v2SbZcCdFJW5IkSZL0JuTIJ+m1xaRkMHTzFTZfCcW7RCFW9KxKESvjV9ZLD7tIxJ5eZCWH/G0aHsDx0Ht0P7aKTKFhTYPetHT58w2hNjOd8DVjiD22CJPyjXAZth61hdwp432Q39/ugcxF/5YQggT/2cSc+hJ9q5LYt92Egc3z027PRz5i8KlNXIsLo5urO7NrtKewsXnO8fSQW4StHkXy9cMYFXXHof8CTErW0nnsh+5E0nuNP2lZGn7rWoXu7s46b1N6e/J7PpK56L9JCz6d3RmemYxd86WYluz43PHkzHQm+e9n7o1TuJhasqBWZ1oV+fMeJishgvANnxJ/agX6tsVw6D0Xc492f20m1zyOTaH7Kj/OP45jXH03fmpdDn09+Z65IJG5SJKkvECn0+6U7AnvVQAnIBW4JoSI+NdRviUysemOEIIVvkGM2nYVfT0Vi7pUpmsVp1fW06TFEnVwICkPdmFSoh22TX97bhreo6QYOh5ZzpWYUKZ6tuLjit7PdVDF+fxO6Mph6JnbU2TUFozdvHRyfVLe8aKkpiiKJ1CPZ/IRcEgIEfuWQ3wlmYv+m9QnJ4jY2wuRlYpdsyWYlur03PEMTRbTrx5nyuVDmKoN+Ll6O/qV9MzJGUIIEi9uzp6KFxuMVf2PsO/6k847roPiUum+yo+zj2IZWdeVGW3KY6CWD34FgXzge39lJQUTsbsH6WHnsfT6DOta36Co9J4rcy7iEYNOb+RGXDi9S3gws3p7bI1Mc44n3/IhbOVw0oOvY1a1HQ6952BgV1wn8WZkaZmw6zrzTz+krqsN6/tUw8nS6NUVpXxB5iJJkvICnXQ+KYpSAvgMaALcBSIBI7K30kwBFgErhBDa/xK0rsjEpnv3opLps8afC0/i6O/pwtwOlTA3evlaJ0IIEgJ+IebU56jNXLBvtQZDhz87kZIz0xlwaiObHl6mp1tVfqvTLWchT8heRyFoXmey4kJx6DsPa+9BOrs+6d37a1JTFOVDYBQQCPgBEfyZj+qQ3Qk1SQjx+B2E+49kLvrvshKDiNjTg/SwC1hWm4B1ne9RVM/nmFtxEQw5s4lT4YE0cSrNwtqdcTUvlHNcm5ZE5I7viT4wE5WhGfZdfsS64eC/PTjmpkyNls/23GS2zwNqFLViQ99qFLU20Vl70tvxujdZefVlncxFb0ZkpRN9fCyJ15ZiXKw5di1XPvcCDSBdk8WPlw/z05WjWBsaM7dmR7oWr/Jnp3hWJtEHZxO57RtAYNduEoVaTkBRG+gk5nUBwQzaeBlzIzXrenvgXdJWJ+1Ib5fsfJIkKS/QVefTOuBX4KT4S0FFUeyBXkCsEGLFv21YF+Rud29XpkbL94fu8OORuxS3MWF1Lw9qFrN+Zb200AtE7u2dPQ2v3k9YuI98bsTCtKtH+cpvP1ULObG10YcUMbPKqZuVFE3wgp4kXz+EVf0BOPSdh8pAvtEriP6h82kEsEwIkfqC8u5AISHEkbcU4ivJm6w3I7LSiT4xgcSrizEq0hD7lqvRM3l+9JJWaFl0+xxf+O5BI7R8V7UFo8vXQ0/154ij9JCbhK4cQcrNYxgV88ieileihk5j33IlhI82XEZfT2F1Lw9alLXXaXuSbr3qJiuvv6yTuSh3JFxdQvSxMajNi2LfchWGDn//n8SVmBAGntqIX3QQ7YpWYH6tTjiZWOYcz4x+TNiasST6bcPAsSyO/RdgWq7h386TG66HJdJlxUXuRiXzQ8tyfNqwhNyVM5+TnU+SJOUFcre7Z8jE9nadCoym79oAguLTmNSkNF82Lon6FWsMaNJink7D2/2P0/B2P7lBnxNrMNbTZ1Oj/tQt7JpzTGg1RG79mqhdP2Lk6kmRUVvQL1RUZ9cnvRsvmXZXRAjx5C/fOQghwt5edC8nO8JzV+L1lUQfHYHKxB67pr9hXLTR38o8SYpjxLkt7HlyEy/bIiyu05XKNn9OCRZCkHB+A+HrxpMVF4pVg4HYd52K2lx3owHuRibRdaUfV8MSmNi4FJOblUFPJR/88qPX6HzK0y/r5H1R7kkLOUfE3p5okkOx9BiLVa3JqNTPr3+ZpdUw+7oPkwMOYKinZrpXWz4qVf25jp/ES3sIWz2KzMhALGv1pnCPGaitHHI93sS0LAZtuszGyyG0r1CY33tUxcpY/9UVpTxJdj5JkpQX6HrNJz9gGbA2L66r8lcysb198amZjNx2lTX+wdQubs2qnh64Fnr5VJPsaXhziTn1BWqzIti3WY+hfdWc4zfjwul45HceJsUyt2ZHBpep+Vz9RP8dBC/uh6Knj/Pw9ZhVaKKTa5PejZd0PmUBm4ABQoiUp9/5CyE83naMryJzUe5JjwggYm9vsuLuYVa+Pzb1p6FnZPNcGSEEGwMvM+b8NmLTU/mkUkO+qtIEo2em72pSE4nc/i0xB2ejZ2yJfdepWDUYoLOpeKmZGkZsvcryi09oXMqWNb08sDc31Elbku78i2l3hkKI9Fd997bJXJS7NGlxxJz6nKRry1BblcSu6W8YOdf5W7m78ZEMPr0Jn/AHNHYsxcI6XXB7dmpwRipRu6cSvWcaioEx9p1/wLrR0FzPR0II5p4K5JNdNyhmbczm/p5UcbJ8dUUpz5GdT5Ik5QX/NRe97kqo3clev+CioijrFUVprshxu9IzLI31WdXLg1W9qnItLBH3mSdY7Rf00jqKomDpMQbHrscQ2kxCN9Qn8drvOcfLWRXmbJvRNHQsybAzmxlxdgsZz2ydbu7RHtdvLqK2KMzj6c2J2v0TBXEkn/Q3V4GTwKmnU10AZD4q4Aztq+Lcxw9Lz09Iurma4JVVSL6z+bm/eUVR6O7mzvWOn9K7hAdTrxzBY+dMToY9yCmjZ2yOQ88ZuH1/CcMilQhdPoTA72qR+uCiTuI21tdjWXd3lnSrwunAGDxm+XD2YYxO2pLyhLOv+Z2Uj+kZWWHXZCEOHfeCJpPQTY2IPj4ObUbSc+VKWdpxpOVQ5tfqxIWox1TZPoM5133QaLNnX6oMjLHv9B1uU65gXNyTsFUjCfymeq7nI0VRGFPPjWPDapOaqaXW3FMsv/jk1RUlSZIkKRe9VueTEOKeEGIi2WsXrCV7FNQjRVG+VRTF5uW1pfdJbw8XLo1vQGVHc/qtC6DPGn/iUjNfWsfIsQbOvc5j6FyXqMNDiDw4CG1mCgDWhibsbjKAjyt6s/DWWZofWExEamJOXUOH0rhOPo+FVxciNn1B0LwuaFITdHqN0jsnhBALyF58fNfTKW6y1/E9oFIbY1P3B5x6nkXPzImIvb2I2NWFrKTg58oVMjJlWb0e7G82mHRNFt77FjD8zBbiM/5cLszIpSLFPj+G89A1ZMU8IfC7GoQuH4omSTcdQx9VL8rZ0XUx0lfh/esZFp97pJN2pHdDURQHRVGqAcaKolRVFMXj6Y83IFecL6CMizXBuW8AFu7DSbg0n+DVHqQ+fn7ZQZWiYmjZ2lzt8AkNHEow/sJO6u+dz424P2eKGzqWoeinh3Aevp6s+FACv6tB2JqxiGdeuOWGOq42+I+rT61i1ny04RLDtlwhIytP7RkkSZIkFWCvveaToiiVgQ+BVsABYA1QF+grhHDXVYD/hRzS+e5labT8dOwe3x68g7OFEat6VaWeW6GX1hFaDXHnvyfu/I8Y2FbGvs169K1K5hxfc9+fwac3Ym9kxtbGH1K1kPOfdYUg5sAswjd8ikHhUhQZvRVDp3I6uz5J914y7S5ACFH16b8dgY1ANSFEnnvAk7lId4Q2i4SAucSe/RZU+tjUnYp5pQFkbzb2p+TMdCYHHGDOjZM4Glswr1Yn2hWt8FwZTWoCkdu+IebQXPStnSk6YR+GzuV1EndMSga91/hz4HYkA2sU5ZeOFTFU6273PSl3vMaaT/2BDwBP4CJ/jsZMIHuh8a06D/Kf45Lrz70lacGniDw0OHtqcMWPKFRvGirD56e2CSFY+yCAcee3k5iZzsQqTfi0UkMM9P7cyVOTmkDEpi+JPTIfsyqtcBm+AZWRWa7GmqXRMnHfLaYfv089Vxs29fOU04HzCTntTpKkvOBtrPkUBywFtjy7doGiKFuFEJ3+bcO6IG+y8p7zj2Lps9afwJgUPm9UisnNSqP/isXIUwL3E3ngA4Q2C7tmSzEt2T7nmF9UEJ2O/E50egpL63anu5v7c3WTbx4naEF3REYKTgOXY+HVWReXJb0FL+l8chRChD7zWQ3UFkL4vNUAX4O8ydK9zLj7RB0ZTtqTYxg516NQ4wUY2JT5W7mLkY8ZfHoTV2JD6Vq8CnNqdqCwsflzZVIDfXkyqy3azDSKjNmBadn6OolZoxV8feAWU4/co0ZRKzb398TZ0vjVFaV35l+s+dRZCLHlbcT0b8hc9HZos1KJO/sd8f6z0DNxwLbxfEzcWv+tXERqImPP72BD4CUqWzvyW91ueNoWea5M7LFFhK4YjlFxD4qO243asnCux7suIJgBGy5hZ2bAtg+88HCxyvU2pNwlO58kScoLdL3mU1chRGMhxNq/LpqZVzqeAIQQu4QQgy0t5SKKeUWNYtb4j2tAf68i/HjkLnXnneZuZNJL65i4tsCp13n0rUsRsbsrMSc/R2izh55Xs3XhQruxeBRypteJ1Uz025uzdgKAaTlv3L71w9C5IkHzuhC+4dNcH7YuvRuKovRRFEX1bMcTgBAiSwjhoyhKCUVR6r6r+KR3Q9+qBA6d9mPbdDEZUVcJWeNJ3IWfEJrnp/t62RXlQruxTPFoyc4n16mw9X/8fvfCc2tGGbt6UnzSWdSWDjye3pT48xt1ErOeSuGHluXY1K8a18IS8Zx9klOB0TppS3o7nuYn5UUdTzI/vR9UamNs6k3FqfspVEbWhO/sSMT+/mhSn//7tjc2Z613H7Y1/pCo9GRq7Z7LZxd3k5r1Z96ybjiEImO2kx58ncDva5MedifX4+1Z1ZlTI7MXSq877zTrAoJfUUOSJEmS/ruXjnxSFKUP2Tvc/eOE8KeL/ToKIU7pKL7/RPaq502bL4cwZPMVMjRa5nSoyIdeRZ7bdvivRFY60T4fk3hlEUbO9bBrtRq1qSMAGZosRp3bxpI752nlUo7VDXphafDnyAFtZjrha8cRe/RXTMo3wmXYetQWdjq/Rin3/LVHXVGUMcBHgN/Tn0jACCgJNACigM+FEHlm2KPMRW9XVnIY0cfHknJ3Kwa2lbFtugjDwtX+Vu52fARDTm/iZHjgP+5ApUmK4fGc9qTeOUXhHjOwaTH+pbnqTVwPS6TT8osExqQwq30FhtcurrO2pP/uNabd5en8JHPR2yc0GcRd+Im4iz+hMrLBtuEcTEv9fTR2XHoqn/nuZsmd85Q0t2Vx3a40cCiRczz1/gUez2oNQlBk3G5MStb82zneVERiOl1X+nIyMIaPvUswtVU59FQyD+VFcuSTJEl5gU6m3eX1m6kXkYkt7wqKS6X/ugCO3Y+mcyVHFnWtjI2JwUvrJN1cQ9SR4agMLLFrtQZjl3pA9toJC2+fZey57ZSwKMT2xh9R2vL5Dqa4UysIXT4UPXNbnD78DbPKLXR2bVLu+qekpiiKHtAIqAM4AqnATWCfEOLx24/y5WQuejeS7+0g+thoNCnhWFQdg3Wtr1Hpmz5XRiu0LL59js9995Cl1fKdR3NGl6+H+ukW59qMNEIW9yPh4iZsmo6mcK+Zub79+R/iUjPptzaA3TfD+cCzCAs6V8JIX64DlZe8zk1WXs5PMhe9OxmRV4g8NIiMiABMSnagUMO5qE0d/lbuaMhdhpzZzIPEaIaUqcVPnq2xMDDKPkf4PR7NaEFWbDAuw9dj7tH+b/XfOM4sLWN3XGPh2Ue0KGPHmt4eWL/i/kx6+2TnkyRJeYHO1nzKyzdTLyITW96m1Qp+PnGfr/bfwt7MkBU9qtKolO1L62REXSNiT3cy4x5gXWcKltX+HIlwIuw+3Y6uJFNoWNOgNy1dnl9oPPVRAMELe5MRchPL2n0p3HsWarOXL34uvXv5/QYLZC56lzRpccSenkji1d9QW7hi22QBxkUb/61ccHI8I85uZdeT63jauvBbnW5UtnECQGi1hG/4hJj9MzGv1hHnoWtQGehmbSatVvDtoTt8f+gOni6WbPnAiyJWch2ovCK/5yOZi94toc0i3m8mcee+R1GbYNNgBmbl+vxtlOOzGyQUMbVibYM+1LQvBkBWQgSPZ7Yh7aEfDn3nYdN4mE5i/e3cI0Zuu0oxaxO2f+BFeQfzV1eS3hqZiyRJygt0uuB4fiMTW/7gHxRH7zX+3IlK5tOGJfm+eRnUL1mMXJueQOThwaTc3YpJiXbYNVuas5PMo6QYOh5ZzpWYUKZ6tuLjit7P3dRpM9OJ2vUDUbunomdijUPfX7Co3k1Ob8nD/mHa3S/ACxOWEGL0WwnsNcjND/KO1CAfog4Pzd6Bqnx/bOpPQ8/I5rkyQgg2P7zC6HPbiM9MY1b19gwuUzMnP0QfnEP42nEYl6hJkbE7UZu/vLP8Tey4Fka/dQEYqVVs6FsN75K6a0t6fa8x7S5P5yd5X5Q3ZMTcIurQENJDz2JcvAW2jeejNi/yt3JnIx7S58QagpLjmebVhjHl66EoCtr0ZIIW9CDp0m4Ktf4c+64/6uQ+5nRgDF1W+pKSoWFVr6q0q/D3kVrSuyE7nyRJygt0Ne0uT99MvYhMbPlHSkYWY3dcZ8n5xzRwK8TaPh44Whi9sLwQgoSAX4g59Tlqi+LYt16HoV0VIPuN4YBTG9n08DI93aryW51uGKv1n6uf9uQqIUsHkBZ4ETP3tjj2X4C+jYtOr1H6b/6h86n/03/WAcoDG55+7grcEEIMfcshvpLMRXmDNiuVuPM/EO/7M3rGthTynoVJqc5/e2iLTEuin886DgbfpodbVRbW7oy5fnY+Sri4heBFvdG3KUrRj/djYO+ms3hvRSTSabkvd6OSmdG2PKPrusqO8nfsNTqf8nR+krko7xBaDQmXfyX29Feg0sOm3jTMKw742994bHoKA05tZMfja7QrWoFldbtjbWiC0GQRtmoksccWYVm7D04DlqKoc396XFBcKp2WX8Q3KJ5vm5dhYuNSqOQ6UO+c7HySJCkv0FXnU56+mforOdog/1rl94Rhm69ibqRmXW+PV77tTws5Q8SeXmjTYijUaB7mFfoB2Z1T064e5Su//VQt5MTWRh9SxMzqubpCqyHm4BwitnyFoqdP4e7/w6rBIBTV627+KL0NL0pqiqKcA+oKIbKeftYHTgohcn8V1jckb7LylvSIS0QdHkpGhD8mbm0p1GguajPn58pohZZpV47xdcB+SprbsqFh35xpeCl3TvNkdjvQU1N03G6M3bx0FmtCWiYfrL/E9mth9PZwZlGXypgYqHXWnvRyr3uTlVfzk8xFeU9m/AOiDg8j7ckxjFy8sW26EH3L5zu1hRD8cuMUn/ruxsnEgvXefaluVxQhBFG7fiRyy1eYlm+My6gt6Jnk/k7PqZkahmy6zGr/YDpXcuT3Hu6YGco89C7JzidJkvKC/5qLXvq0LYRYIYRYAVQGvIUQvwghfgEaA+7/KVIdEkLsEkIMtrTM/f8AS7rVt1oRzo+ph5WRmiaLzjL1yF202hd3jBo51ca59wUMnWoRdWggkYeHos1KQ1EUPq/cmO1NPuRuQhTVd83mVHjgc3UVlR6FWoynxA/XMHL1JHT5UB5Na6STbYwlnbAGLJ75bPb0O0l6KUN7d5x6nMKm3k+kPj5M0MoqJFxZzLMbuqoUFV9UaczhFkNJzEyn1u65LLlzHiEEJqXrUHzSGVQGJjyc6k3ipd06i9XCSJ/N/Tz5rkUZ1gYEU3feaR7GpOisPSnXyPwkvRZ9SzccOu2nUONfSY/wI3iVB/EBvyC0mpwyiqIwukI9fFqNAKD+3vnMue4DgF27iTgNWk7y7RM8/LE+mTHBuR6jsb4eK3pWZUbb8my7Fkqdead4EJ2c6+1IkiRJ74fXHeohb6YknavgYM6FMfXpVsWJiftu0f73C8SkZLywvJ6JPQ4d92Lp9RlJ15YRuqE+mfEPAGhTpDxn24zG0sCIJvsXsujWWf46ys/A3o1inx7GccBS0h5f4sFXlYnaMw2hydLpdUpv7CcgQFGU5YqirAD8ganvOCYpn1BUaiyrjce5jz+GhasRfXQkYZubkhFz+7lyDRxK4N9+HHUKuzLk9CY+OLme5Mx0DB3L4DrpLIZO5Xgyuz2xxxbpLFaVSuGrJqXZ+WF1AmNS8Jrtw+E7kTprT8oVMj9Jr01RFCwqDcCl72WMXBoQc2ICoZsakhFz67ly1e2K4ttuHC2cyzL+wk46H11BbHoKVnX7U3TcHjIjHxD4fS3Sgq7rJMbxDUqwb1BNguLSqD7nJEfuyjwkSZIk/XuvteC4oigfAt8AxwAFqA98K4RYrsvg/is5pDN/E0Kw4MxDxu+8jpOFERv7euJV1OqldVIe7CHywIcA2DVfholbGyB7zYReJ9ZwMPg23g4lmF2jA5VsHP9WPzMulLBVI0n03YpRsao4DliKcbGquX5t0ut72XBORVEcgBpPP54XQoS9vchen8xFeZsQgqQbK4jx+RSRlYpVjYlYVpuAovfnWnEarZYfrxzm24BDlLW0Y0PDflSwdkCblkTQgu4kXd6Lbdsvses8RafrMt2NTKLj8ovcikjip9blmdDATa4D9Rb9m+HleTE/yVyU9wkhSL61lujj4xFZKVjVnJS9s69K/VyZOTdO8tnF3biYWrLeuy9edkVJe3SJxz+3RJuZRpEx2zEt20AnMd6PSqbD7xe5FZnE9DblGVNPrkf3tslpd5Ik5QU6mXb3ByHE72TfSG0DtgK18mrHk5T/KYrCiDqunBxRByGg3vzTLDj98G8jl55l4tYap17nUVu6Er6zEzGnv0Jos7A2NGF3kwHMr9WJK7GheOycyehz24hJf376ir6VI0VGbcFl1Bay4kIJ/MaL8I1foM1I1fXlSv+SoihHhBBhQogdT3/CFEU58q7jkvIfRVEwr/ABzv2uYOLWhtgzXxOyvjYZUVdzyuipVExyb8bB5oOJyUilxq45LL97EZWRGUXG7MCqwSCidv1IyOL+iKwXj9R8U6XszDg7qh4dKzry6e4b9FrjT3K6HKWZ18j8JP1XiqJgVq43zv0uY+zaitjTXxG6sSGZsXeeKzO2Qn18Wo9AKwT19s7nlxsnMSxaheJfn0Nt6cDj6c2IP79RJzGWsDXlzKi6tC1fmPE7r/PRhkukZWpeXVGSJEmSeM3OJ3kzJb0L1Yta4zeuPk1K2TJy21V6r/En6SUPW/qWrjh2O4F5xYHEX/wfYVtboUkOR0+lYmjZ2tzu/DlDy9Ti11tnKLvlJxbeOoNGq33uHBaenSgx9QZWdfsTvecnHnxVheRbPrq+VOk1KIpipCiKDWCrKIq1oig2T3+KA86vqC5JL6Q2dcC+9Trs22wiKzmU4HW1iLs4/bm1Vxo5lcK/3Thq2hVlwKkNfHRyPalCi+OHi7DrPIX4M6t4/HMrNCnxOovT3EjNxn7V+LFVWTZeDqH2vFPcj5Lrr+QFMj9JuSU7H63HruUqMmPvELzGi/iAec+tTVfDrhh+7cfTwrksY8/voMvRFaSY2+P61WmM3KoTvKA70ftn6SQ+cyM1m/t5MrlZaVb4BuG94AzB8fJFnSRJkvRqL+18kjdT0rtWyNSAnR9VZ0rL7Iet6nNOciMs8YXlVWojbJsswLbZEtLDzhO8tgZpwacBsDE04ZdanfBrN45K1o6MOLuV6rtmczLswXPn0DO1xmnAUop+egihzeLR1AaELh+GJjVBp9cqvdIQwA8o+/T/+gG+wA7gl3cYl1RAmJZsj0vfS9mjoE5PJHRTQzJj/9w51cHEggPNhzDJvSkr7/lRc9ccbsVHPF34d0X2wr8/1CMzJkhnMSqKwueNSrFnQI2c9VcO3I7QWXvSa5P5Sco1iqJgVqY7zn0DMHLxJubEeMK2NCcz/mFOGRtDE7Y1/oAZXm3Z/eQGnjtnEZCWTLFPDmHu2ZnwdeMJWzMO8ZeXbLlBpVKY3KwMWz/w5EZEIl6zT3L2YUyutyNJkiQVLK8a+SRvpqR3TqVS+LJxKQ4NqUVMSgbV55xkjf/LH+7My/fDqftJFH0TQjc3Id5/ds5bw8o2ThxuMZT13n2JTk/Be98Ceh1fzZOkuOfOYVahCSV+uIpNi/HEHl/M/S8r6HR3K+nlhBBzhBCuwA+A+9N//w48AM6+0+CkAkPP2Bb7Vuuwa7GCzJhbBK/xJOHSgpz8oadS8U3V5uxrNoiItCRq7JrD6vt+WNXtR9Hxe8mMepi98O+Tq69o6c20KGvPhTH1cLEyotWS80w9cvelU5Ml3ZL5SdIFtZkThdtvx7bJItLD/QheU43Ea7/n/K0risK4ig043mo4WUJL3T3zWHDPF+fh67FpNoaYg7MJWtAdbUaaTuLrUNGRs6PqYWqgR8Nfz7L0/GOdtCNJkiQVDC/tfMpvN1OKorRVFGVxfLzupj1I707Dkrb4j2tANRdL+q4NYNiWKy9da8DArjLOPc9i4taGGJ9PCdvSImc3PEVR6OpahRudPuVr96bseHyN8tum8ePlw6RlZeacQ2VoikPPn3GddBY9EyuezGpL0IKeZCXIkQbvUBchRIKiKHWBRsAS4Nd3HJNUgCiKglnZntmjDpzrE318LGFbW5GV8OeDVVPn0vi3H0+1Qi7091nH4NOb0CvrTfGJJ0Gr5eEPdUm+cVSncZawNeXMyLp0f7pDaLeVfiSmyXWg3jGZn6RcpSgK5hU/zN6h096DqMNDCN/RgaykkJwyteyL499+PM2cSzPm/Ha6n1iDcdepFO75M4kXN/N4ejM0SboZmVTBwZzzY+rRoIQNgzZdZtS2q2Rqcn+0lSRJkpT/vdaaT+STmykhxC4hxGBLS8t3HYqkI06WRhwZWotPvEuw6Owj6s47TWB0ygvLqwwtsW+zMfutYYQ/was8nls7wURtwOSqzbne8VNaOJdlkv9+Km6bzvZH154bRWBcojpu3/ph1+k7Eny3cP+L8sSdXiVHGrwbf/Q4tgZ+E0LsAQzeYTxSAaU2c6Zwh50UaryA9LDzBK32IPH6ypy/eycTSw61GMLnlRux9M55au+ey2NLJ1y/Poe+TREezWhB/Nm1Oo3R1FDNmt4eTG9Tnm3XQqn1y0nuRCbptE3ppWR+knRC37I4Dp0PYNNgJmlBxwleVZWkW+tz8pGNoQk7Gn/EdK827Hx8Hc+ds3no2Q3n4etJfXCewB/qkhH1SCex2ZgYsGdADcY3cGP+6Yc0X3yOyKR0nbQlSZIk5V+v2/kkb6akPEOtp2Jam/Js/9CL+9HJVJvtw87rL97J+o+3hi59L2Hk0oCYE+MJ3dT4ubVcipvbsKlRfw41H4KJWp/OR5fT4uBv3IwL//M8agPs2k+ixPeXMHAoTcjifjz+uZXObuakFwpWFGUR0B3YqyiKIa+fyyTpX1EUBYtKA3Hu44ehXRWiDg0kYldnspKzc45apccP1Vqxu+kAglPi8do5my3xURSfeAqTUnUIXtibqN0/6bSjWlEUJniXYP+gmoQnpuP+8wl+OnpXjj54N2R+knRGUVRYVh2Jc++L6FuXJnJ/PyL29kSTEvn0uML4it4cbzWcTK2Gunt+YbW5M0Um7CcrLoSH39ci7dElncSm1lMxo20FVvasytlHsVSfc5KAYDkTQZIkSfrT694QyZspKc9pV8EBv3H1cbMxocPvF/ls9w2yXvKwpTZ3yV47odlSMqOvE7y6GvF+s/6+o1X78cyp0QHfqCe4b/+ZCRd2Ep/x504uhs7lKT7xJIV7zyHlzknuf1mBmEPzdLKop/SPugEHgOZCiDjABvjknUb0F3IKcMGjb+mGQ5dD2NSfTuqjQwSvqkry3S05x1u6lMO//Xiq2DjS+8QaRl0+QuGxu7Co2ZOITV8QtnLEc7lGF5qUtiNgfANalrXny723qDbLhzNyEeC3Lc/nJyn/07cujWO3Y1jXmULK/V0Era5K8v1dOcdr2RfHr904mjiVZvT57XwU/gTbT4+ASo+HP9Yn6dohncXWp5oLJ0fUQaMV1Jx7kskHbr90iQRJkiTp/aG8zttYRVFMgBbAVSHEXUVRHIFKQoiDug7wv/D09BS+vr7vOgzpLUnL1DB2x3UWn3tEfTcb1vWphqOF0UvrZCWHEn1kJCkPdmHoUAPbZosxsCn3XJnItCQm+e1nyZ3z2BqZ8EO1VnxYyguV8me/a0bkQ0KXDyH52kFMynrjPHQN+tZOOrnO942iKH5CCM93HcebkLmoYMqIuUnkgY/ICPfDtEwPCjWcjZ6RDQCZWg2T/PYx/dpxqto4s65BbywOziR6zzTMqrbDZdg6VIYmOo9x5/UwRm27ypO4NAbXLMbUVmWxNpEDlv+r/J6PZC4quDIir2Tno6grmJXri02Dn9EzsgJAK7TMvHaCL/32UczMmg1Vm2D5+0DSQ27gNGAZVnX66iyuyKR0xu+8zhr/YErbmfJr58o0LGmrs/beFzIXSZKUF/zXXPRao5eEEClCiK1CiLtPP4fm1Y4n6f1jpK/Hwi6VWdHTHd8n8XjM8uHYvaiX1lGbOmLfdjN2LVaSGXePkDXVibv4P4T2z8V67YzMWFinCxfajqG0hR2DT2+i1u65nI14mFPGwK44RT/ej+OApaQ+uMCDSe4kXT2gq0uVJCkPMLAph1P3k1jVmkzy3c0Er6pKSuB+APRVevzk1YYdTT7iYVIMXrvn4OPVE4e+80i6tJuHPzUkPezuK1p4c+0qOHD9k4aMq+/GkvOPKD/9OOsCguU6dZJUwBjYVcap5xmsqn9B0q21BK/2IPXRYQBUioqPKzXkeMvhZGiyqHNqM0c6/w+TMg0IWdyPkKUDyIp78bIFb8LOzJBVvTw4MLgmGq2g8cKzfLg+gKhkuRZUfqEoSgtFUW4rinJPUZTPX1Kus6IoQlGUfNspJknS2yGnzkkFRt9qRTg/ph5WRmqaLjrL1CN30Wpf/KCVvaNVD1z6XcbErQ2xp78iZH1dMqKe3yLdw9aFE61GsKp+L0JSEqi7Zx79fdYRmpKQcx7r+h/h9q0vasvCPJ7RgvCNXyCe2TVPkqSCRVGpsa4xEacep1EZWRO+ox1Rh4ehzUgEoE2R8vi3H08FKwd6HF/FN2ZOOIzcREbIDe5/WYGwdRPQJMfpNEYzQzU/t6vAxbH1KWplTO81/rT87Tz3o5J12q4kSW+XomeAde1vcerug0rflLBtrYg6OgptRvbmA7ULZ++G19ipFMMuHeKLar0wazaWuNOruPdZaaL2TEObkaaT2JqWtuPKx9580bgka/yDKTftGCsuPpEd4Xmcoih6wHygJVAe6KkoSvl/KGcOjAHOv90IJUnKj2Tnk1SgVHAw58KY+nR7uvV4u2UXiEnJeGkdPRN77Fuvw771erKSggheW5PYc1MQmj87jxRFoVcJD252+ozPKzdiY+Alym6ZxvSrx0jXZI+WMnQqh+vkC1g1GET0np94ONWbzOgnOr1eSZLeLUP7qjj3PI9ltQkkXltG8OpqpAb5AFDUzJpjLYcxrkJ95t88TcvQx+h/fR6rOv2IOTCLe5+VIubIrwhN1itaeTNVnS05M6oucztU5OyjWCrNOM7UI3fJyJLr1ElSQWLo4IVT7wtYeIwl8cpigtd4kRZ8GoBCRqbsbPIRP3m2ZkvQLZoY2pMw/gAm5RoSsfFz7n9ZngTfrTrpFDLW1+OHluUIGN+AMvZmfLjhEk0WnpU7c+Zt1YF7QogHQogMYD3Q/h/KfQ9MA3TTeylJUoEiO5+kAsfcKHvr8V86VuTQ3UiqzfLh4uO4V9YzLdUJl76XMC3Vmbhz3xGyrhbpEQHPlTHTN+SHaq241vETGjqW5HPfPVTeNoM9T24AoDIwxumjxTgPXUt60BUeTHInMWDXPzUnSVIBoagNsak3Fcdux0HRI2xzU6JPfII2KxUDPTUzqrdja6MPuJcQjdfxteytN4ji31zE0LkCYSuHP52uq9uZ7HoqhZF1XbnxqTetyxVm4r7sBclPB8oFySWpIFGpjSlU/384dDkEQkvopkZE+3yGNisNlaLik0oNOdZyGJlaDXUu7uFHr77YjN2FytCUoF868+inhjrbEa+Cgzk+w+vwa+dK+AfHU3nGCb47eIf0LLkgeR7kDDz7BjXo6Xc5FEXxAIo83QVdkiTplWTnk1QgKYrCiDqunBxRByGg7vxTzDsV+Mo3enrGtti3XIl92y1oUiMJWV+H2DOTEVnPr1FQwsKW7U0+ZE/TgeipFNodXka3YytzdsWzrNUT12/90bctxpPZ7QhbOx6R9fIRWJIk5W9GTrVw7uOLeZWhJATMIWRNddLDshdWbV+sIr7txlLF2okhpzfR4vpZkoasxWXUVrQZqTye0ZzHM9uQHnJLpzE6Wxqzqb8nOz70IjE9i3rzTzN402ViXzFCVJKk/MXYpX52Pqo0kAT/WYSsrU56uB8AdQq7crXjJ4yrUJ9ldy9Q9ZYv5z9YikO/BaQHX+fBZA9Clg0iKz481+NSqRSG1CrOzU8b0qmSA98cvE3VmT6cfBCd621JuqMoigqYCUx4jbKDFUXxVRTFNzIyUvfBSZKUZ73Wbnf5haIobYG2JUuWHHT3ru4XdJXyh+jkDD5YH8CemxF0q+LE4q6VsTDSf2U9TVosMSc+JunmKvQLlceu6RIMHf6+lmKGJouZ10/wtf+B7N1kvPviYesCgDYjjfANnxB7eB5Grl64jNiAgZ1rrl9jQZTfd3QBuavL+yz18REiDw5CkxyKldenWNWYiKJngBCC5fcu8tnF3cRnpDG+YgO+qlCf1GOLiNr5PdqMFGwaDceuw2T0zGx0GmNSehbfHrzD7JMPKGSiz8x2FehZ1RlFUXTabn6U3/ORzEXvt5SHB4g6NARNSjhW1T/HqvoXKHrZu19eig5m2JnNXIh6QhOn0syr0hjzYwuIOTQXlb4xtu2+wqbZGFT6hjqJbd/NcEZsvcrD2FQ+ql6U/7Uph43cmfOF3lYuUhSlFvCNEKL5089fAAghpj79bAncB/6YO+kAxADthBAvTDYyF0lSwfBfc1GB6nz6g0xs0l9ptYLpx+/z1f5buNmYsLFfNao4Wb5W3ZTA/UQdGY4mOQTLauOxqvk1KrXR38qdCX9Iz+OriEhLYmaN9gwtUyvnIS7BdyshSz8CwOmjpVh4dc69iyug8vvDHshc9L7TpMURc2ICSTdXYWDnjl3zpRjYVgIgKi2Zz3x3s/zuRYqbWTO3ZkeaW9oSufVrYo//hsrEEvuO32LdcCiK+tWd5W/iUnA8Qzdf4cKTOJqWtmVBp8qUsDXVaZv5TV7KR4qimAILgAzguBBizavqyFwkadJiiT4+juRba5/mo2UY2FbMPqbVsuj2WSb67SNdm8VXVZow2taJmE1fkBSwE307Nwr3mI55tY466ZxOTs/iu0N3mOnzABtjfWa2r0Av2RH+j95i55MauAM0BoKBi0AvIcT1F5Q/Dnz8so4nkLlIkgqK/5qL5LQ76b2gUil81qgkR4bUIikji1pzT7Hk/KPXWljTxLUFLn0DMK/wIfG+MwhZ40VayLm/latduDh+7cfTyLEUI89updeJNSQ83T3GwrMTbt8FYOBQhqB5XQhdOVJnO8tIkpQ36BlZYdd8KfZtN5OVHELwulrEXZyO0GqwNTJlad3uHGs5DGM9fdodXkZP331ouv6E2/eXMC7mQdjq0dz/qjKJl/fqdGcod2dLTo+qyy8dK3LuURyVZhznR7kg+VulKMoyRVEiFEW59pfv/2mr807AZiHEIKDdWw9Wypf0jKyxb7Ec+zYbyEoKJnhdTeJ8ZyC0GvRUKoaXq8P1Tp/Qtkh5Jvnvp+b53TzsMZOinxxEZWD8dD2oRjpZD8rUUM20NuXxHVsPt0Im9F0bQIvfzsmdOd8hIUQWMBI4ANwENgohriuK8p2iKDLvSJL0n8iRT9J7JyIxnT5r/Tl8N4q+1VxY0KkSpobq16qb+vgIUYeGkpX4GAuPMVjX+gaVvslzZbRCy/+uHmOS/35KmBdiQ8N+VLFxAkBkZRC+6Uti9v+MUVF3nEdsxNChVK5fY0GQl0Ya/FcyF0l/0KREEnV0JCn3tmHoWBO7ZkvQty4NZE/d/fnaCaZcPoRa0eN7jxYMK1uLtCv7CF83gYzwu5hWak7hHj9j5FJBp3GGxKcxdsc1Nl8JpXxhMxZ2qUxd10I6bTM/0HU+UhSlPtnTV1YKISo+/U6P7JEHTcle7Pci0JPsHaf2CSEuKYqyVgjR61Xnl7lIepYmJYKoIyNIub8DQ6fa2DVbir5ViZzje5/cZNS5rTxMiuXDUtX5qWpzVOfWErl1EprkGKzqD8S+8/eoLQvnfmxawaKzj/hy300ysrRMalqaCQ1KYKCW78sh/98byVwkSQWDHPkkSa/J3tyQfYNqMrlZaVb7B1Fj7kluhie+Vl3joo1x7uuPeeUhJPjPJniNJ6lBJ58ro1JUfF65MUdaDCUpM4Pau+fy2+1zCCFQ1AY49JxBkXG7yIx+TOBkD+LPrtXFZUqSlIfomdhh33o9di1WkBlzm+A1XsQH/IIQWgz01HxRpTFXOnxM7cLFGXdhB7X3/MItlyqU+PEahXvNIvX+eR5MqkLoyhFkJUbpLE4nSyM29vNk10fVSc7QUH/+GQZtukyMXJBcp4QQPmSvl/KsF211HgS4PC0j7+Okf03PxB77Nhuxbb6MzKjrBK/xJOHK4pwRlq2KlONqx0/4tFJDVt3zpcKOmewu5kWJaXexaT6OuFO/c+/TUkTt+R/azPRXtPYvY1MpDK9TnBufNJQ7c0qSJBUw8qZFei/pqRQmNyvDgUE1iUzKwGv2SVb7Bb1WXZWBObaN5uLQOXsb47DNjYk+NhZtRtJz5eo7lMC//TjqFHZl6JnN9D+5jqSnN2nm7m1w+/4ShkWqELywNyFLB6JNT8n165QkKe9QFAWzsj1x7huAUZGGxJyYQNjmZmTGBwLZu2jubTqQdd59CElJoNbuXxjjuwd1wyGU/N9drBsOJfbYIu59WpLo/TN1uoNm6/KFufaxNx97l2D5xSeUm3aMNf5BOp3+J/3Ni7Y63wp0VhTlV2DXiyrLHaakl1EUBfNyfXDu64+hY02ij44kfHtbspKCATBRGzDVszW+7cZRysKWD0+up8XJ9cS3+owSP17HpKw3ERs/4/4X5Unw3ZbrucHJ0uhvO3MO3XyFuNTMXG1HkiRJenvktDvpvRcSn0bP1X6cDIxhYI2izOlQEWN9vdeqq81MJvb01yRcmoeemTM29X7CtHTX5xbJ1Gi1/HjlMN8GHKKMpR0bG/ajgrUDAEKTReS2yUTtnoqhU3lcRmzE0Lm8Tq4zv8nvQ8tB5iLpxYQQJN1YSfSJ8SC02NT7H+aVBubkjviMVCb572fBzTM4GJszs0Y7uhavQkbITcLWTSD56n4MCpekcI8ZmFVtp9OFeS+HZC9Ifv5xHE1K2bKgc2VKvmcLkr+NfKQoSnFg9zPT7roALYQQA59+7gvUEEKM/LfnlrlIehkhtCReWUTMyc9R9Awp1HA2pmV65uQVrdDy2+3zfOm3l5SsDD6v3IjPKjUi6+YxwteNJz34OiblGuLQaxZGRavkenxJ6VlMPnCbOScfYGdmyOz2FehWxem9XJA8v98byVwkSQWDnHYnSf+Rk6URR4bW4rNGJVly/jF1fjnFvddc5FKlb0oh759x7HYCPRM7Ivf1IWxLMzKiruaU0VOpmOTejIPNBxObkUqNXXNYcfciAIqeGvsuP1B0wn6yEiJ48I0XcSeXy9EFklTAKYqCeYX+uPQJeDrqYATh29qQlZg90MXSwJi5NTtyru1oHE3M6Xl8Na0PLSHYojDFPt5HkfF7QU+fJ3M68Oh/TUh7fEVnsVZxsuTUyLrM71SJC0+yFySffzpQ5indCwaKPPPZ5el3kpSrFEWFRZVhOPf2Rd+mLJH7PyBib080qdlTfFWKiiFla3Gj06d0Ll6Z7y4douqOmVy0dcPt+0s49JtP+pMrPPjag5Dfh5CVEJGr8ZkZqvm5XQUujKmHi6URPVf703rJeQKj5YhxSZKk/ESOfJKkZ+y5EU6/dQFkaQVLu1WhSxWn164rtBoSry0j9swktOnxWFQZilXNyegZWeWUCUtJoPeJNRwPu88Hpbz4pWZHTNQGAGTGhRK8sDcpN49hWbsvjv0XoDIyy+1LzDfy+9s9kLlIej1CCBKvLCbm1OcoihqbBj9jVr5vzlv9LK2GBTfPMMl/P1lCw1dVmjKhYgP0hSD22CIit01GkxKHVf0BOlsE+A+hCWkM2niZvbci6FLZkcVdq2BlrK+z9vKKdzTy6V9tdf4yMhdJr0toNcT7/Uzs2W/RM7LBtsmvmLi1ea7MweDbjDy7lfuJ0fQtUY3p1dtio8kkcvt3xByZh8rABNt2X2HTdDQqfcNcjU+jFcw/HchX+2+h0Qp+bluBIbWKvTejoPL7vZHMRZJUMPzXXCQ7nyTpLx7FpNBjtR/nH8cxqq4r09uU/1e7rGjSYog98w2JVxejMrLBps4UzCp8gKJkn0Oj1fLdpYP8cPkIFawKs6FhP8pa2QPZN31RO38gcvu3GDiUwmX4RoyKVtbJdeZ1+f0GC2Qukv6dzLj7RB4aRHrwKUzcWlOo8a+oTR1yjgcnxzP2/Ha2PrpKeavCLKjVmXoObmiSY/986NM3xq7Td9g0HY2i0s3gZq1WMNPnAV/uvUkRK2PW96mGV1ErnbSVV7yF3e7WAd6ALRAOTBZCLFUUpRUwG9ADlgkhfvgv55e5SPq30iMvE3XgIzKirmJWvj+FGvyMytAi53hqViY/Xj7M9GvHMdc35CfP1nxYyovMsLuEr/+YpEu7MXAsg/PQtRgX98j1+J7EpTJ402UO3I6ku7sTi7pUxsJIdoTndTIXSVLBIDufniETm/SmMrK0fLbnBnNOBlK9iBXr+1ajuI3JvzpHesQloo+PIz3kNAaFPbFtOAdDB6+c4weDb9P3xFpSNZn8WrsLvUv8eXOWfPM4wQt7oUmOwaH3HKy8B783b/X+kN9vsEDmIunfE0JLQsAvxJ6ehKJvQqGGczEr0+25Mnue3GDUuW08Sorlg1JeTPNsg62RKemhtwlfO46kK/swrdAUp8Er0Ldy1Fms5x7F0nO1HyEJafzUuhxj67kV2DyVX/ORoihtgbYlS5YcdPfu3XcdjpTPiKx0Ys9/T7zvDNRmRbBt9hvGRbyfK3MjLozhZ7ZwMjyQeoVdWVC7M+WtHEi6sp+QZQPJSoigcLdp2DQfm+v5QasV/O/4PSbtv42rjQkb+lajqrNlrraR1+TXXPQHeV8kSQWD7Hx6hkxsUm7ZejWUjzZcQk9RWNGzKm3K/7vpLEIIkm+vI+bkF2iSQzEr3x+bOlPQM80+T3ByPL1PrOZkeCCDStdkVo32GKuz39xlJUQQvLgfyVcPYFG9G44f/YaescXLmitQ8vMNlnzgk95URsxtog4OID3sAqalOlOo0S/oGdvmHE/OTGfK5cPMvHYCSwMjpnm14YOS2Z3bccd/I2ztWFSGpjgNWIZ51bY6izM2JYMBGy+z/VoYbcsX5vce7tiYGOisvXclP+cjkPdF0ptJCzlH5MGPyIq7h4X7KKzrTkGlNs45rhValt/15TPf3SRmpvNJRW++rNIE/bQEQpcOINF/B2aVW+I0aDlqC/tcj+9UYDQ9V/sTlZzBzHYVGFqAp+HJXCRJUl4gO5+eIROblJvuRyXTbZUvAcEJfOJdgikty6Kv9++ms2gzEok7/yPxAXNR1MZY1/waiyrDUPT0ydJq+Nr/ANOuHqWKjRMbvPtSytIOAKHVEr33f0Rs+Qp92+IUGbMdI5eKurjMPCe/32CBzEXSmxHaLOL9ZhJ79ltURtbYNprP/9u777iqq/+B469z2RsFZDpw5VYU98I9cufeZVma5iib5si2OcqRWaZmuVJz74F7gVszU3EACuJAEZB1fn9Afc2fCgqXy3g/Hw8e3fv5fPh83udwe3vv+57POXYl2//nmJO3rjF4/3L2RV6igXtxZtTpRDlnDx6EnyXs+x7EXzlGgcaDcO/+DQarZxu9meE4tWb63kuMWnMGdwdLFvWuRp1iBY1yLVPJ7flIcpHIrJTE+9ze8xF3j8/EokBp3FrM/c9oboAb8TG8e3gtv5wPooSDCzPrvEQTz1Lc3v49EYtGYrB1xnvgAuwrNMvy+KLuP6DvwqNs/OsGXSt7MbtL3rwNT3KRECInkNXuhDCSEq527B1Sj9drF2Vi4AWazNpPWHTcM53DYOlAwfpf4N37CNaetbm16x3CFlYn7uoOzA1mfO7fmjVNB3D1/h2qr5nK0pBjACiDAdc271Psg53ohFguTajNvSOrjdBKIUROowzmOFd/F++eBzC38yJybRciN/YnOf72v8dULOjJztaD+aFuF07evkbVVVMYd3QTBo9SFBtzgIIt3+b29u8JGVfdaCviKaUYWs+XvUPrYmFmoOHMfXy1/TwpKXnvyy0h8iuDhR0ujabi0WkDKYmxhC9pwO19Y9HJCf8e42Ztz9z63dna8g3MlIEWm2bz7uG12AcMxHfsYcztXLgysTkRS95DJyU85WrPztXOirUDavJF67IsP3kN/6m7ORoWnaXXEEIIkTl5qviklGqrlJodHS3/2IisZW1hxvcvVeLXnn4cDYvGb/IuNv/17EsJWxZ8AfcOqynUdjk6MY7ry1sQua4HSXev0LpwWYLbjaCCswc9An9l6P4VPEhOAsC2dF18xx7G0rMMV7/rQNSaL2SZcyHyCUvXinh134tzzdHcP7eUsAV+xF7a9O9+gzLwaumanOn0Ll2KVWbCsS0ErJ/JpfgYPHp8Q5FRm0mOvU3I+Orc3DQVnZJilDir+TgTPLwBL1X05IP1f/LinINE3ntglGsJIUzDpkgTvHsfwb5MD+4c+oLwxfVIiDr1n2MaeZbkaPuRDC5Th8mnd1Jv3XRCnTzxHXeYAo1e5+b6rwn5tB4JEReyNDaDQfFe45LsGFSbuMRkan+3h+/3XZL3S0IIkUPIbXdCPKOzkffoMj+YM5H3GN20NGOalcbM8OxzC6QkxRMdPInow18D4FT9PZyqjSTZYMGHQeuZfHonVV28WdKoL8UdXFJ/JyGO8DkDuHtgEY61e+L1yk8YLG2edplcK7cPLQfJRSLrPYg4wo3Nr5B48wz2FV7Bpf7X/1mBCmDJxWMM2r+MFK2ZXrsTvUtUI+nuDcLnDCDm2BrsKrbA+9V5mDt7POEqmaO1ZvaBywxfdZqCthYs7FWVhiVc0//FHCy35iOZf04Y0/3zq4jaNpiUhGgK1B6PU9XhKIPZf45ZefkUr+5ZQmJKCjPqpOaju0ErCJ8zAFKS8Oj7Pc51e2d5bFH3H9Bv0TE2nI3MU7fh5dZc9A95XyRE3iBzPj1EEpswttiEJIasOMW8oKs0KeXKrz2r4u5g9VznSrx7mVu73yP27xWYOxWnYIOJ2BZvw5qrZ3h592I0mjn1utGxaEUg9YPdzbVfErnsQ6x9q1P4rT+wKOidlc3LEXL7GyyQXCSMQyc94PaB8UQHT8bM3ge35j9iU7jRf465HHOLvrsWsScihJ7FqzK9dkccLay5vX1W6twr1g54vToXhyovGi3O4+HRdFsQzPmo+4xp9gIfNS31XIX6nCC35yPJRcJYkmMjidr2JrEXVmHlVRe35j9h4VziP8dcjblDn12/sTsihD4lqjG9dies7kYQOqsXcef24FSnDx59Z2Bm45ClsaWkaCYGXmD0xrMUK2DD0r7+uX41PMlFQoicQOZ8EiIb2Vqa83P3KszpWpm9Ibfwm7yTwPNRz3UuC8eiuL+4GI9OG1FmVkSueYmIle1o5WBBcLsRlHZ0o/P2+Yw4uIoHyUkopXBt+wGFh60k4dqfhIyvTtyFQ1ncQiFETqXMrShY73M8u+7EYG7F9eUtuLljOCmJ9/89pqh9Qba1fIPxfi1YEnKMqqsmc+DGZQo2GUTx8cGYF/Di6pQ2XFswlJSEZ5vDLqMqezkRNLwBPf28Gbf5L1rMPsC1u/FGuZYQwjTMbAtRqM1SXJvPISHqJGG/+XP3xOz/3OpW2N6ZrS3fYEyVZvx28Qj+q6dwUhso9v4O3DqMI3r/b4SMrUpcSNYWJf65DS9wUB3ik1Ko/d0eZu6V2/CEEMJUpPgkRCa8XKMIB96qj6O1OU1+2M+YjWdJSn6++VRsijTGu1cQBRt8Q/y1/YQu8MPx2EQCm/ZjaNl6fHdmN/XWTePv6BsAOFRtT7HR+1DmVlz6ogHR+xdmZdOEEDmctWdNvHoextHvLe4en0nYb9WJD9/3735zgxmjqzRjZ+vBADRcP5NPj23B3LMMvmMOUrDFCG5vnU7I+BrEXz1plBjtrcyZ38OPOV0rs/9yaqF+y7kbRrmWEMI0lFI4lOuDT5+jWHnW4ub2IUSsbEdSTNi/x5gbzBjr14KtLd8gNimROuum8d3Zfbh2GEPRDwJJSXxAyITaRK3/JsvnpavrW5CjIxvQtJQrQ/44SfcFwUTHJWbpNYQQQqRPik9CZFIlL0eChjegbzUfPt36N42+38eV27HPdS5lZoFT1bco3O809mV6EB08ichfq/CpcywrGvfjUsxt/FdPZcH5YACsC1fEd+whbIrXJGxWLyKWfmC0yYSFEDmPwcIWl4bf4NF5K6Qkc21pI27ueo+UpP+NZqpdqBhH2o+km28Vxh7dROON33P1wX08ek6myNsbSLp3I3Uy8s3fGWVEgFKKl2sU4fCwBrjZWdHyxwOM3vD8hXohRM5k7lAYj47rcGn0LfFhuwhb4Me9M7/8J6809CjB0fYjaeVThpGHVtN26xxii/pRYsIxHPzaEblkFFcmtSLpzvUsjc3VzorVr9TgyxfLsuLUdfyn7uJI6J0svYYQQoink+KTEFnA3sqcud39WNDTjxPX7lFl8i5WnLz23Oczs3PHrflPeHbbjZm9Jzc29qf6oWEcCuhIVRdv+u9eRN9dC7mXGI+5oxtF392SuoLMui+5+m0HkuPuZWHrhBA5nY1PA7x7B+NQ8TXuHplC2K/ViA/b++9+J0sbFjTsyfwGPTh+Kxy/VZNZcvEY9pVaUuLTE9iVa0rEb8O4OqUNSXeffSXPjCjn4cDBYfV4uXoRPt/2N41n7Sf0jnFu+RNCmIZSBhwrD8K7VxAWLuWJ2vwqEas6kHQv9N9jXKztWNG4P9NqdWT7tfP4rZzMzrs38RmyDM/+s4j9axcXPq7MveMbsjQ2g0HxbqPU2/AeJKVQZ9peuQ1PCCGykRSfhMhCvar6cGREA0q62NJ5fhCDlp8gLjH5uc9n7VkTr+57cW06i8So06gVAazw1Iyt0oxFF49SbdUUgqKuoswt8ej3PR59phNzYj2XJtQmIfJiFrZMCJHTGSztcW0yHY+XNkFKEtd+b8zNwJH/mQuqd4lqHGk/krJO7vTc+Suv7F5MnI0jhUeswaP3NO6f2caFjypm+Ye+f9hamvNT18os6OnH0bBo/CbvZN2ZCKNcS6SudqeUmh0dHW3qUEQ+Y1GgFJ5dtlGw4WTiQwMJXVCFe6fm/lvoUUoxuGxd9rd5CydLa5pvms3HRzZi3/BVfMcFYe5YiKuTW3N90dukJD7I0tjq+hbkyEO34XWT2/CEECJbyGp3QhhBQlIKozee5ZvAC5R3d2Bxn2qU98jcKi5JMeFEbXmduMubsC7ShL+qjKV/0Faux93j82qtGF6+AQZlIOb0NkJndEEpAz5DlmFXNiBrGpXNcvuKLiC5SJhOSkIMt/eO5u7xmZg7Fce16Q/YFG747/7ElGQ+PbaFz09sw9e+IL827EUNtyLEh54i7PsePAg9RcFmb1Go61cYLK2NEuO5GzF0WxDM8fC7vN2wBJ+3LoOFWc78Tiy35yPJRcKUEu9cIGrL68SH7cKmSDNcm36PuWORf/ffT3zA8IOr+PnvQ9R2K8qvDXtRxMqGiMWjuL1tBtZFq+I9eBFWHqWzNK6UFM2knRf4cMNZihawYUmfalTzcc7Sa2Q1yUVCiJxAVrsTIgexNDfwdZtybHitJjfuP6D61F38sD9zQ7vN7b1w77Aal8YzeHDtAL4b27KrrA8v+pRl1OG1tNkyh4i4e9iXb0LxsYcwc3Dj8sRm3No+KwtbJoTIDQyW9rg0mopH522A4vryZkRtf4uUhNRbci0MZoyv2pLtLQeRkJJM/XXT+erEdiy8yuE79jAFm73FrS3fpU5GHnraKDGWdrNn/9B6DKpTjEk7L9Bgxl4u3Xq++fKEEDmXhXMJPDpvxqXRd8Rf20for37cPfHjv++J7Cys+LFeVxY27M3pOxFUXT2ZFeHn8Ow7ncLDVpIYdYmLY6pyZ8/8LL1FzmBQjEq7DS8hKYW60/YyY2+I3IYnhBBGIsUnIYyoxQuFODayIfWLF2TQ8pN0/SWY27EJz30+pRSOlV5LnUvBtQLJ2wYy4/46pldrzs7rF/BbNZktYeewdC+J75gD2FdozvX5g7j2y5voJBlSLkR+Y+NTH+/ewTj6DePeiR8IW1CVuCvb/t1f36M4R9uPpGPRinwYvJ7mm34gPDEej97fUnjkOpLuRhAyzp9bW2cY5QOZtYUZMzpVZEmfavwZGUPVKbv4IxPz5QkhcqbUuaDewLv3Eazc/bm5/U2ur2hFYvSlf4/pVrwKwe1HUMapEN12LOCNvcswq9SK4p8ex8bXn/Af+xP2Q2+S4+5maWypq+E1pFlpV4b+cUpuwxNCCCOR4pMQRubhaM2GV2vx1YtlWXX6On6Td7E35FamzmnhXALPzlspWP9L4i5voPX+lwmsXAkXK1tabp7N+4fXkmxlR+Hhq3FpPYrb22Zy+ZsWJMXczKJWCSFyi9QV8Sbi2TUQZW7F9RWtiNo6iJQHqfMAFbCyZVFAb36q15XDUVepsnISKy6dxKFy69TJyMs24vqCIVyd2o6kuzeMEmOXyl7/zpf30vwgBi8/wb34JKNcSwhhOhZOvnh02ohLk5k8iDhM2K9+3D3+PVqnrn5Z3MGFna3f5N2Kjfjx3AFqrvmWs5hR9L1tuHWawN2DS7j4cRViLxzM0rhc7CxZ9XINvnqxLH+cuk61qbsIltXwhBAiS0nxSYhs8M/Q7j1D6mJupgj4fh+fbj1HcsrzjyRQBjOcqo3Eu8cBzO29cd3Rn7XWZ3mtZFUmngqk4foZhNy/g3u3r/F6bT5xf+8lZHxNHoSdycKWCSFyC2uv2nj1OoxTtbe5d3ouoQv8iL20CUgdVflyqRoEtxtBCUcXuuyYz+t7f+eBrTOFR67Dvde33D+1mYujKxFzcrNR4ivuYsfuIXUZ3qA4Pxy4TMVvAtl41jgr7wkhTEcphWPFV/HpfRRrzzrc3DGM68uak3jnApB6W/AX/i+ysflAbj6Ipdbab5l17iCu7T6i2Ie7QKdw6bN6RK39Ep2SkmVx/fNebefgOiQmp96G9+3ui6Rk4r2aEEKI/5HikxDZqEaRAhwZ0YCulb0Ys/Evmv2wn7DozC01bulaAa/ue3Cu+SEp5xby4bmPWVDBj3N3o6i6ajKLLh7FuV5fin6wk5QHMYR8Uot7x9ZmUYuEELmJwdyGgvW/wKvbbgyWDkSsbMuNza+SHH8bgFJObuxuPYT3KjZmzrlDVF8zlaM3w3Bp/ha+Yw9jZleQK9+0IPKPcVn6oe8fVuZmTG5Xnt1v1sXW0ozWPx2k/6Kj3Lz//LcrCyFyJnPHIrh3XItrs9k8uHGMsF+rEX102r+joJp5l+Zo+5E08CjBkP0r6LLjF+KLVKH4J8dwrNqRyN8/4Oq37bP8Nrw6xQpyZERDmpd2Y8Sq0zT6fh/nbsRk6TWEECI/kuKTENnM0dqCX3v68XO3Khy6cocqk3ay5vT1TJ1TmVlSoPY4vLrtwmBuQ+29L7OtUAwVnd3pvfM3BuxZQkpRP4qPPYyleymuTm1H1LqvZVJNIfIpK4/qePc8hFP194j58zfCFlQh9mJqUdrSzJzP/VuzpeXrxCQmUGfdNCafCsSycAV8xwfhVK8fUSvHEzq9MynxxvlAlvrhrwEfNS3FwqNhlJ+4g9+Ph0vOekZKqbZKqdnR0dGmDkWIx1JK4VC+Pz59jmHt05BbO9/m2u9NSLz9NwDuNg6sazaAidXbsPbqGaqumsz+mNt4v7kEjz7TiTmxgZBPapEQcT5L43Kxs2TVK9WZ07UyJ6/fo8qknUzccZ6k5KwvugshRH4hxSchTEApRf/qhQke0YDCzja0n3uYYStPEZ+YnKnzWnlUx6vnIRyrDMXp9AwWRM3m/RLlmP93ENVXT+UUBop9tBvH6l2IXPoe4bP7kZIQn0WtEkLkJsrcioJ1J+DVYx9mNq5ErO5E5MZ+JMelzg3XyLMkR9uP/HdFzVabfyIiKRGvV+fi3nMK946sImRCbRIiLxolPmsLMya0LMPh4fUp7GxDtwXBdJp3mPBoyVkZpbVeo7Ue6OTkZOpQhHgqcwcf3NuvxLX5HBJvnk4dBRU8BZ2SjEEZGFkhgD0vDsHSYEajDTP57PhWnBoPouiozSRHR3BxfA1iTm/N0piUUrxcowinRwXQskwh3lv3J3Wm7eFEeNaOtBJCiPxCik9CmNALhezZ/1Y93qrvy7Q9IdSZtoe/IjM3ksBgYYtLwCQ8XtqEITmeV48O5o/ClsQkPqDO2u+Yfj4Yr0GLcOs0geh9C7j8ZQCJd2R1KSHyK6tCfnj12I9zrY+5f+53whZU4f75PwBwsbZjWeN+fF+nM3sjQqiychJrr57BpcVwiryzkcTbYYSMq879M9uNFl9lLyf2D63H123KsemvG5SfuIOfDl6WUVBC5DFKKRzK9cG7zzFsijbl1u73uLY0gIRbZwHwdy1MULsRdPf1Y+zRTTTbNIs7RavhO+4wFgW8ufJNS25u/i7Lc4OnozXL+/mzpE81Lt+Ow3/qLsZu+ouEJBkFJYQQz0KKT0KYmJW5GVPbV2D1KzW4eieOalN2MffQlUy/ebIp3Aif3sHYl+1DhVMTWZ+0gWZunow4tIr22+ZCi+H4DF1BfOgpQsZVJy4kKItaJITIbZSZJQVqfYxXj/2Y2XkSubYbket6khx7A6UUA1+oRVC7EfjYOdFh21xGHFyFZdlGFB97CDMndy5PbM6tLdONVhAyNzPwTkAJTrwTQBUvJwb+foJmPxzgQtR9o1xPCGE65vZeFGq7HLeW80m88zfhv1XnzuGJ6JQkHC2t+aVBD+bW705QVCjVVk9mZ2ISxUbvw6FKGyJ+G8a1n18jJfFBlsaklKJLZS9OvxtA9ypeTNhyjmpTdnHoyu0svY4QQuRlear4JHMbiNysTTl3jr3dkBpFnBmw9Di9Fx4lOi4xU+c0WDnh1vxHCrVdjmPsVaZeGM0Xng5sDT+H38rJBHlVwHf0XpSZOZc+q8+dvQuyqDVCiNzIyq0yXt33UqDOeO5fWEXogsrE/LUUrTVlnAuxr81bDC1bj+/O7CZgw0yu27ngO+YA9pVac/3XoVybOxCdZLzJwUu62rHtjdrM6lyJoNA7VJoUyKTAC5laOVQIkfMopbAv0yN1FJRvK27v/YjwJQ1IuHkapRR9S/pzqO1wClnb02rzj3x6dh+eby7Dtd1o7uyaw+WvmpAUHZHlcbnaWfFLz6qseaUG0fGJ1Jm2h3fWnCY2ISnLryWEEHlNnio+ydwGIrfzdrJhy+u1mdDyBZYeD6dqFn2rZleiLT69j2Ln25ouZz9jteUJHMwMNN80m09vhOPz8X5sitcgfHZfwn7om+Urxwghcg9lZoFzjQ/w7nUIc8di3NjQm8h13Ui+H4GVmTlTa3VgSaM+nLkTQbXVU9gUFUbhYStxbfshd3b+xKUvGxvlQ98/DAbFwFpFOfVOAE1KujFq7RnqTNvDyWuSt4TIa8ztPCj04hLcWv9G0t1LhC2syZ1DX6CTEynjXIj9bd6id4mqfHJsC623zYHW7+I9eAnxl49wcVx14i4dMUpcL5Zz59SoAF6tWZTJOy9SedJOAs9HGeVaQgiRV+Sp4pMQeYGZQfFR09LsHFyH5BRNvel7+XrHeVIy+c2+ma1b6hu4FnMpfTuI5ZHf0svFgS9ObKPZnmXowb/j1mEc0ft/4+LHfsRdOJRFLRJC5EaWLuXx6raLAvU+Jy5kQ+ooqLML0VrTuVhlDrcdTmE7Z9puncPooxsp2OkTvAcvTvvQ509cSLBR4/NxtmHVK9VZ2KsqIbdiqTYldR6WB0mZW7hBCJGzKKWwL90Fnz7HsSvejtv7xhK+pB4JN05gZ2HF3Prd+bFuV/ZGhFB11RSOF61GsdF7Abj0WT2iDy41SlyO1hbM6lyJbW/UBqDxrP28sewEd+MzN2pdCCHyKik+CZFD1SlWkKMjG9C+vAfvr/uTVj8dyPQqT0op7Mv2wrvPUQp4VmfcxU+ZaRvG6dvXqLbuOwKrdKDYh7sgJYmQz+oSteYLdIp8kBMiv1IGc5z938Gr12EsnEtxY2N/Itd0Ijk2klJObux9cSgDStfkyxPbab7pB2Irtkr70KdSP/TtX2Tc+JSiu583Zx6Zh+XAZZmHRYi8JvVLtIUUenExSTFhhC2qTXTwFABeKV2DfW3ewt7CkqYbf2Ba9G2KjT2IddGqhM3sRuSy0egU40wQ3qikK8ffbsiIBsX56eBlKkwMZP2fxhv9mV2UUi2VUn8ppc4rpd5/zP6RSqkzSqkTSqltSqmipohTCJF7SPFJiBysgK0lS/tWY1bnSuwJuUWlSYGsOJn5lenMHXzw6LgOl0bTaHFjA6vvL6aUpYHugQsYeeMaHuMO41itE5HLPuTy181IvBWWBa0RQuRWlgXL4Nk1kIINJhJ3eRthC2sSH34AG3MLZtftwtz63TkcdZVqq6dwwNKB4uMOY+3rT9isnkQs/cDoRex/5mFZO6AG9x4kUXf6HkasOsX9BzIPixB5jV2pTvj0OYatb2tu7X6PyHXdSXlwl8oFvTjUdjgdi1bgg+D1dA5aj+PwNTg3GEDUms8IndaJ5Lh7RonJ1tKcSe3Ks3dIPZysLWgz5xB9Fx7h5n3jzYFnTEopM2AG0AooB/RQSpV75LCjgL/WuhKwDPg6e6MUQuQ2UnwSIodTKnV+k+ARDfAtaEvn+UG8svhYpod1K6VwrPw63r2DKFGgMAvCvmaI7T1+PHeAutvmE91jKp4D5hB34SAXR1fi3pFVWdQiIURupAxmOFUdhme3XSgzK64ta0z00dQV7vqW9OdAm2EUsLSh+aYf+CrkJEXe3YJzwEBurvuSq1Pbkxxr/MVAWpd15+Q7AbxRuxjf7g6h4jeBbD13w+jXzalkIRaRV5nZuFKozVIK1v+S2AurCV9ch4Sbp3G0tGZxQB+m1erI5rBz+K+fwdW2o/Ho/R33jq3l0oTaJEReNFpcNYsWIGhEfT5uVprFx8IpP3EHvx8PN9pKoEZUAzivtb6otU4AFgPtHz5Aa71Dax2b9vQA4JPNMQohchkpPgmRS5Qp5MC+ofX4sEkpfgm+it/kXewNuZXp81o4l8Szy3YK1f2E4RELmJ+8m8jY29RY+y2/u5fDd3wwFq7FuPptB67NH0xKQlwWtEYIkVtZFaqCV48D2BZrya2dI7mxoTcpCTGUL+DBwbbD6OZbhTFHN9J2xwIsuk/Co+8MYk5tIuSTWjy4/rfR43O0tmBGp4rsHFwHS3MDzWcfYMDSY9yOzZ0jEDJDFmIReZlSCqdqI/F4aRMpD6IJX1SXmLOLUUoxuGxddrd+E4NSNNzwPb95V6HI2xtIvBNOyLjq3P9zh9HisjI3Y3yLFwga3oDCzjZ0WxBM5/lBXLubuakTspk3cPWh56Fp255kALDhcTuUUgOVUkFKqaAbN/LvlwFCCCk+CZGrWJgZ+LRVGXYOrgtAw5l7Gb3hLInJmZvHQBnMcK7+Ll7d9hBgcZ/VUd9TyzKZQfuW0e+vQxR4dxsFW77N7e3fEzLWn/irJ7OiObmKUqq4UmqOUmqZqWMRwtTMrJ0p1HYZBep+xv2/l6eOOrj1J/YWVixo0JOZtV9ix7Xz+K+ewl8VW1N01BaS790gZHwNYk5uypYY6xd34djIhrzfuCS/BIVSfmLW3LYshMhZbHwa4NXzIJaF/LixsS83dwxHJydQ3a0IQe1G0ML7BYYfXMXLkeG4fbgLcycPLn/djFtbZxh1RFIlL0f2D63Hly+WZcPZSMpPDGTuoSu5cRTUUymlegP+wMTH7ddaz9Za+2ut/d3c3LI3OCFEjiLFJyFyobq+qZOR9/UvzOfb/qbOtD2cjcz8PAZW7lXx6nmQ4hV6Mfv6t7xvdpGVl0/iv2EGl5oMpcg7m0i6f5OQ8dW5tWV6rnkDpZT6WSkVqZQ69cj2p06m+bC0oecDjBupELmHUgacq4/Co9NGkuNvEb6oDjF/LUEpxetlarP3xaFYmpkTsH4mP6YYKDb2EBYFC3NlUmtubpiULfnD2sKMz1uX5dCw+ng4WNF5fhBd5gdxPXeNQBBCpMPc3gvPlzbjWHU4d4/P5NqypiTdC6WAlS0rm7zM1/5tWHXlNHUOrOXekOXYV2rF9QVDuDbvDXSS8UZFmpsZeLdRSY693ZAKHg4MWHqcVj8e5PKt2PR/2bTCgMIPPfdJ2/YfSqmmwEdAO631g2yKTQiRS0nxSYhcytHagp+7VWFZP38upS0zPnPvpUx/oDNY2OHaZDoebZczMO4Ai+//QUrCPRqsn8FMbY7vhGPYlWvC9V+HcnVqO5Lu5ooh1POAlg9veNJkmkqpikqptY/8FMr+kIXIHWwKB+Dd8yCWrpW4saEPNwNHopMTqOrqw+G2w2lTuBxvH1pNz5O7KPDuNhyqdSBi8TuEz+5HSkL2FIH8vJ04OKw+n7cuw9o/Iyg3MZDtf0dly7WFENlDmVng0uBrCrVeSELUKcIW1iTuynaUUrxdMYAdrQYRl5xInW3z2NTyfVzavM+dwNlc/qopSXcjjRpbaTd7AgfVYVrHCuy7fIsK3wQyfU8IKSk59ku8w0AppZSvUsoS6A6sfvgApZQf8AOphSfjdqAQIk+Q4pMQuVynip6ceCeABsVdGPLHSdrMOZQl3+rblWiLd+8j1PYqy8ob02llEc0Hwetpe2A1Fq8vxL3Xt9w/tZmLoysRc2pLFrTEeLTWu4BHJ8h67GSaWuuTWus2j/zImyohnsLc3hvPzltx9BvG3WPT/x114Gxlw7LG/fimelvWXj1DzS0/caPbFNw6jid63wIufdGQxNvh2RKjhZmB9xuX4tjIhtT3LUg5d/tsua4QInvZle6MV499mNm4cP2P1tw59BVap1DX3Zfg9iOo716cNw78wSj3iri8Np+4kMOEjKtO/OVjRo3LYFC8WdeXk28HUM+3IG+tPEXA9/v4KzLGqNd9HlrrJGAIsAn4E1iqtT6tlPpEKdUu7bCJgD3wu1LqmFJq9RNOJ4QQgBSfhMgTPB2tWf9qTb7rUIEd56OoNGknK09lfm4TczsP3DuspljAV0y9tZDPkg6z5/p5qq6eQnD5FviOPYTBrgBXJjYnYvEoow5dN4JnmkxTKeWilJoF+CmlPnjKcTKxpsiXlJkFLg0nPjTqoAZxV7ahlGJEhYbsaDWYhOQk6m2cyYoyzfAeupwHYacJGedP7IWD2RbnC4XsWfVKDTwcrbPtmkKI7GVZsAxe3fdhV6ozt/d9TOSaziTH38HN2p71zV5lvF8LFl44SpPI6+i3/kCnJBPyaV3uHjb+tI5FC9qy/tWazO1WhdPX77HvUuYXjzEGrfV6rXVprXUJrfVnadvGaK1Xpz1uqrV211pXSftp9/QzCiHyOyk+CZFHKKUYUs+X4BENKOxsTad5Qby69Dj34pMyfV6nKm/i3fMAfWxiWBH9CwWS79Jq84+Mjwyl8JiDFGj0Ojc3fEPIhDo8uH4ui1qUs2itb2qt30h7E/bFU46TiTVFvva/UQduXF/RmjuHvkDrFOq4FyO4/UgaepRg8P7lvHk/DvcPdqIsrLn8eQPu7Jlv6tCFEHmIwdIet1YLKBgwhdhLGwlfVIsHkccwMxgYXaUZm1oM5OaDWGoe38mRl+dgXaQyodO7ELliLDolcwu5pEcpRb/qhfnr/Ub0r144/V8QQog8QIpPQuQxZd0d2D+0Pu83Lsncw1fwm7KT/VnwrZqlS3m8uu/Dv0pflkXNope6ytcnd9Bo21ziX/oMn6HLSbhxkYtjqnJn19zcMBl5hibTFEI8u9RRB3uxe6Ert/eNJWJ1J5Ljb+Nqbce6ZgP4xK8lS0KOUf/oNhKGrcGmVF3Cf+zP9YUj0cmZK5gLIcQ//vkCzbPzNnTyA64tacC9M78A0MSrFMHtR+DvUpheR7YwseEQ7Ov2JWrVJ4RO70xKvPFvh3O1s0IpZfTrCCFETiDFJyHyIEtzA5+3LkvgoDokp2jqz9jLmI1nSUzO3Dd5ytwKlwZf49tpDZ8mHuS7uE38efMqVVdNYaNLcUp8egIbX3/C57xC2Pc9SL5/J2saZBzpTqYphHh+Bkt73Fr+gkujb4m7vIXwhTV5EHkUgzLwUZWmbGo+kNsJcdQK/JXdHb+gQNMh3No0hSuTWpN8/7apwxdC5CHWXrXx7nkQK89aRG1+laitg0lJisfL1oktLV/n/UqN+eHCEToUqoSh4wTuHVlFyIQ6JNwIMXXoQgiRZ0jxSYg8rH5xF46/3ZA+1Xz4dOvf1Ju+l3M3Mv9Nnk2RJnj3DqZzkbKsujOXEim36BH4K0P+3I/b2xtw6/wZdw8v4+KYKsSe25sFLckcpdQiYD/wglIqVCk14EmTaWbR9doqpWZHR0dnxemEyLWUUjhWHoRnl+3olKTUUQenfkZrTWOvUgS3G0F118L03/c7Y4s3wLXfLO6fDeTC6MrcO77B1OHnepKLhPgfM9tCeHRaj5P/KO6d+olrSwNIjL6EucGMz6q1ZnXTV7hy/w61YuK43Hs6ibeucnFMVW7v+jk3jOYWQogcT+XFZOrv76+DgoJMHYYQOcqy4+G8sfwE8YkpfNO2HK/XLprpod5aa2LOzOd64EimWtZglnkFyjm7syigN8VvXiZsVk8Soy7j1mEsrm0/RJmZZ/jcSqlgrbV/pgI0MclFQvxPcuwNIjf2I/7KVuzL9cOl8XcYzG1ISklm3NHNfHFiG5ULerGoWDnMFo8kIfxPHGv3xKPnVMwdTTt/Wm7PR5KLhPiv+xdWE7VpABjMcGs5H9tiLQC4HJP6ZdrBG1f4yKsE/YMWEn9uD3blm+H58mws3YqZNG7JRUKInOB5c5GMfBIin+hc2YsTbwdQ17cAg1ecpN3Ph4i49yBT51RK4VC+P8V6HeIjhxjm3f+DG3evUXPNtyxI0viOP4Jjre7c+GMsl75sROLNK1nUGiFEbmNm64ZHhzU41/yQmDPzuba4Pol3zmNuMOPTaq1Y03QAV+/foebJ3QS/PBfX9h9z99DvXPigLHf2/iojD4QQWcauRDu8eu7H3N6biJXtuH1gAlqnUNS+IIGtBjOsXH0+C79AjwodSen8OXEX9nPhowrc3PwdOiXZ1OELIUSuJMUnIfIRLydrNrxai6nty7P17ygqfRPI6tPXM31eC+eSeHbZQZtqfVgTPZfqyeEM3r+cHgdXYf/yT3gN/IUHV45xYXRl4i8fy3xDhBC5kjKYUaD2ONzbryLp3lXCF9bm/oXUqdZaFy5LcLsRlHf2oOfe33ndyRf7D3Zi6V6S8Nl9uDKpNQlRl03cAiFEXmHhXBLPbruxL9uLOwcmELGyPclxN7E0M2dyzfb83qgfl+5H43/rDut6zcKmdD0ifhvGpc8a8CD8T1OHL4QQuY4Un4TIZwwGxVv1ixM0vAHeTtZ0mHuYgb8fJ+ZB5laYUmYWFKg9joqd1zFfH+Dd+H2svnySqqsm8Wep+hT/5BiO1Ttj5V0ui1oihMitbH1b4dXzIObOJYhc05lbez5EpyRRxL4AO1sP5mv/NmwJO0flg+vY0mUShXpNJfbcbi58WF5GHgghsozBwhbX5nNwaTKTuNAdhC+sxYOIYAA6FavIqU6j6FS0Iu9eOEqnks1I6DGVhGtnufhxFW6s/gydlGjiFgghRO4hxSch8qnyHg7sf6se7zYqyZxDV6g6ZRf7L93K9HmtvepQuFcQI4uXYXHMElJiI2i4fgZTIi7j8fIPKHPLLIheCJHbWTgVw7NrIA4VXiU66Buur2hF8v0IzA1mvF0xgOMd3qaaizeDDvxB12QLDO/vxPafkQef1iM+NEvWBxBC5HNKKRwrvopXl0A0mvClDbl78ie01rhZ27MwoDfLG/cnIj6GGtfD+L3HNGz92nFj+Wgujq9O3KUjpm6CEELkClJ8EiIfszI348sXy7LjjTokJKVQb8Ze3lp5invxmRsFZbByxK3FzzRrPok1cStokXiBD4PX03LTj1yPvZtF0edcssKUEBljMLfGtelMXJv/xINrBwlbWIP4sNQVMks4urKl5RvMrtuFY7fC8dvzO4ubjcL9tfkkRPzNxTF+RP4xjpTEzM1dJ4QQAFYe/nj3PIiNTwA3tw0mavOrpCTGAtChaAVOdRxF7xJVGXv+CC96VSe23w8kR0cQMr4GEUvfJyUhzsQtEEKInE2KT0IIGpRw4eQ7AQyuU4wZe0Oo+E0gG/6MyPR57V/oStneB/jB6S6fxW7jTMRZ4uJuZkHEOZvWeo3WeqCTk5OpQxEiV3Ao1xfP7rtR5rZcW9aUO4e+RCc9QCnFgNI1Od3xXV70KcuHRzbQ/GYUMaO24VijC1Erx3NxjB+xf+8zdROEEHmAmY0L7u1X4VxzNDF//kr4otrEXd0BQAErW36u3531zV8jJimBWpf/Zl7nSdjX7cvNdV9x8eMq3P9rt4lbIIQQOZcUn4QQADhYmzOtY0V2v1kXO0szXpxziN6/HeFGTOZGFZg7FMaz8ybeqNGT7bGL8TGTuVqEEP+flVtlvHrsx7ZEO27vG0Pogsrc/3sFWms8bR35vXE/ljXuR0RcDLUCf2VatR4UGraSlPgYLn1Wj2sLhpIcd8/UzRBC5HKpCyOMwb3DGnRSHNeXtyBibVcSoy8C0ML7BU50eIfXy9TiqwtHaOpcijuvzkcnJXD58wZc++VNyUVCCPEYUnwSQvxHnWIFOTKyAWObl+b3E+GU+3oHvwaHZmqZc2Uww7n6KEq+8hcWziWzMFohRF5iZu2Me5sluHdchzK3JnJdd64va8qDiNQ5VToWrcipjqN4pVQNvjkVSJ2LZwh7axUFmw7h9rYZXPiwPPeOrzdxK4QQeYFtseZ49z1BgTqfEHd5C2G/VObW3o9JSYjB0dKaGbVfYlvLN9BA/fMnmNH+M+ybDuH29u+5+FEFYk5sNHUThBAiR5HikxDi/7EyN2Ns8xc4MqIhpdzs6bvoKK1/OsilW7GZOq/ByjGLIhRC5GW2RZvh3SsIl8bTSbh1lvBFtbmxaQBJMeE4W9nwQ90ubG35BgpF08Df+LhYPVze3YrB2p6rk18kdFYvku7eMHUzhBC5nMHcGuca7+PT7xR2pTsTffgrQueX596fv6J1CgGeJTnWfiTDyzdg+oWjNLRyJ/L1hSgrO65MakXY7H4kxeT96QaEECIjpPgkhHii8h4O7H6zLt91qMDeS7eoMDGQqbsukpzy/KOghBAiI5TBHMdKAync/wxO1UYQc24JofPKcfvAp6QkxtLIsyTHOrzNqAoBzD8fRNUTuzkx4BdcO4zl7qHfufBBWe7s/TVTozaFEALA3N4btxZz8ey6CzN7b6I2vcK1JQ15cP0wdhZWTKrRjt0vvomtuSVNzgYxseVH2L/4HtEHFnLhg3LcPbxMcpEQIt+T4pMQ4qnMDIoh9Xw59U4AASVcGLn6NHWn7eHktby/at3zktXuhMg6BisnCtb/Ep++J7Ap1oI7Bz4hdH4FYv78DWszM76s3oYDbd7Cw8aBLrsXM8ixGA4f7sLSvRThs/twZVJrEqIum7oZQog8wNqrFl7d9+Da/CeS7l4mfHHd1FGZ969Ru1AxgtuN4P1KjZkbcpw6KbZceX0xFgULEzq9C6HTXiLxzjVTN0EIIUwmxxeflFLFlVJzlFLLTB2LEPlZkQK2rBlQg996VeXirViqTdnFxxvPEp8oE4g/Sla7EyLrWTgVx73NEjw6b8PMthA3Nr1M+OJ6xIfvo6qrDwfaDuOLaq3ZGHaWygfXsrXLN7j3+pbYc7u58GF5bm7+Dp2Sv/KVFMKFyHpKGXAo1xef/qdx8h+VNiqzPHcOf40lyXxWrTX727yFm7UdL57Zz5iAt7DrNIGYExu48EE57uyaK6OghBD5klGLT0qpn5VSkUqpU49sb6mU+kspdV4p9f7TzqG1vqi1HmDMOIUQGaOUooefN2feDaCnnzefbf2bqlN2sSdE5jMQQmQPG5/6ePXYh2vzOSTHhHNtaQCR63rCvau8W6kxx9q/jV9Bb9448Addky0w/3A3tqXrE/HbMC59Wpf40NOmbkK2kUK4EMZjsHSgYL3P8OlzHJvCjbi9dzRhC6pw/8Jqqrp4c7DtMMb5NWfZldPUjE3kr9cXY+VTkfA5r3BlYnMSboSYuglCCJGtjD3yaR7Q8uENSikzYAbQCigH9FBKlVNKVVRKrX3kp5CR4xNCPAdXOyvm9fBjw2s1iUtMpsGMfQxefoK78YmmDk0IkQ+kjjzog0//0zjXHE1syDrCfqnIrT0fUcLaii0tX2dWnc4cuRlGlV1LWNp8FB4DfyEh4jwXx/gRuWIsKYkPTN0MIUQeYOFcAvd2y/HouB5lZkXkms5c/6M13D7Lx1Wac7jtcIraF+ClU7sZVbM/tt0nEXfhABc+rJAvR2QKIfIvoxaftNa7gFuPbK4BnE8b0ZQALAbaa61Paq3bPPITacz4hBCZ0+KFQpx8J4DhDYoz+8Blyk8MZPXp66YOSwiRTxgs7ChQeww+/U6nrkQVNJGr88sRc2our5aqzulOo2jhXYb3g9fTPCqK2He341SjK1GrPiHm2BpThy+EyENsijbFu3cwLgFTSYg4Qthv1bm5YzjlbK3Y++JQvvR/kfXh5/C/dZtjAxdhW6YhEb8N4+aGb0wduhBCZAtTzPnkDVx96Hlo2rbHUkq5KKVmAX5KqQ+ectxApVSQUiroxg1ZXlmI7GJvZc7kduXZN7QeBW0t6DD3MN0XBBNxT0YVCCGyh7mDD24t5uLVfR8WziW5uW0QYQurUyAqiOWN+7G0UV/C4+5Sc8evTPfvgeeHu3Hwf8nUYQsh8hhlMMexymB8+p/BodJA7p6YRei8csSenM075etztP1Iyjm70+tEIIMrdMT65Z8o0OgNU4cthBDZIsdPOK61vqm1fkNrXUJr/cVTjputtfbXWvu7ubllZ4hCCKBGkQIcHtaACS1fYOWp65T7egdzD12RSTWFENnGysMfzy47KNR6ITohhusrWhGxuiNtHa043XEUfUv68/XJHdQ6uYegqKvpn1AIIZ6DmY0Lro2+xbvXYSzdKnNzxzDCfqtOkehTBLYezLc1O7Ar8iJVQy+yMlJW4xRC5A+mKD6FAYUfeu6Ttk0IkctZmhv4qGlpjr3dgAoeDgxYepzmsw9wIeq+qUPLVrLClBCmo5TCrnRnvPueoEC9z4kP203Yr36k7B/ND/5N2dzidazMzHCytDF1qEKIPM7StSIenTZSqM1SdGIs11e05Mbabrzu7cXxDu9Qy60oReycTR2mEEJkC1MUnw4DpZRSvkopS6A7sNoEcQghjKRMIQd2DKrDzE4VOXTlDpUmBfJN4AWSklNMHVq2kBWmhDA9g7k1zv7vULj/nziUf5m7x2cSOrcs/hEbOdr2LUo7yShpIYTxKaWwK9kB777HKVBnAnFXthL6SyWcT0xhfaOeVHcrYuoQhRAiWxi1+KSUWgTsB15QSoUqpQZorZOAIcAm4E9gqdY6/6x7LEQ+YTAo3qhTjDPvBtCstBvvrj1Dre/2cD6fjYISQpiWmW0hXJvMSL39xb0at3a+zbXfqhJ/7ZCpQxNC5CMGc2uca7yHT7/T2JfuSvThrwmdX57YkPWmDk0IIbKFsVe766G19tRaW2itfbTWc9K2r9dal06bx+mzrLqe3OoiRM7j7WTDH/2rs7RPNZK1pqCthalDEkLkQ5auFfHouA739itRZtaY2RQ0dUhCiHzI3N4LtxY/49ltN+b2PigLe1OHJIQQ2cLc1AFkJa31GmCNv7//a6aORQjxP0opOlf24qVKniilTB2OECKfUkph69sam2KtJBcJIUzK2rMmnt33SC4SQuQbOX61OyFE3iFvsIQQOYHkIiFETiC5SAiRn0jxSQghhBBCCCGEEEIYjRSfhBBCCCGEEEIIIYTR5Knik0w4LoTICSQXCSGEECI3U0q1VEr9pZQ6r5R6/zH7rZRSS9L2H1RKFTNBmEKIXCRPFZ+01mu01gOdnJxMHYoQIh+TXCSEEEKI3EopZQbMAFoB5YAeSqlyjxw2ALittS4JTAG+yt4ohRC5TZ4qPgkhhBBCCCGEyJQawHmt9UWtdQKwGGj/yDHtgflpj5cBTZTMoC6EeAopPgkhhBBCCCGE+Ic3cPWh56Fp2x57jNY6CYgGXLIlOiFErmRu6gCMITg4OEopdfmhTU6kJsRHHwO4AlFGCOPR62TV7zztmCfte9z2R7c97Xlu66P0jstoPz1rv+W2fsrpr6WiGTwux0onFz36XF4/6T83Vh89Kbas+J281E95qY8gH+UjyUUZ2m7M18+zyEv9lJf66En7n2dbvspFSqmBwMC0pw+UUqdMGU8WMOZ7keyQ2+OH3N+G3B4/wAvP9Vta6zz/A8x+3OO050HGvmZW/s7TjnnSvsdtf0w/PPF5buujrOqnZ+233NZPeem1lFt+5PWTc18/0k/5q4+M2U+54UdePzn39ZOX+ikv9VFG+yMj23JDLgJqA5seev4B8MEjx2wCaqc9Nif1w7RK57w5rq3P0Te5ug25Pf680IbcHn9m2pBfbrtb84TH2XXNrPydpx3zpH2P2/7otvSeG4Ox+ii94zLaT8/Tb8Ygr6W8Q14/6W8z1etH+il90kd5h7x+0t8muSjn9pMp+uhJ+59nW27IRYeBUkopX6WUJdAdWP3IMauBfmmPOwPbddqnUiGEeByV33OEUipIa+1v6jhyMumjjJF+Sp/00ZNJ36RP+ihjpJ8yRvrp8aRfMkb6KX3SRxmTU/tJKdUamAqYAT9rrT9TSn1C6oiH1Uopa2AB4AfcArprrS+mc84c2dZnkdvbkNvjh9zfhtwePzx/G/LknE/PaLapA8gFpI8yRvopfdJHTyZ9kz7po4yRfsoY6afHk37JGOmn9EkfZUyO7Cet9Xpg/SPbxjz0OB7o8oynzZFtfUa5vQ25PX7I/W3I7fHDc7Yh3498EkIIIYQQQgghhBDGk1/mfBJCCCGEEEIIIYQQJiDFJyGEEEIIIYQQWUIp1VIp9ZdS6rxS6v3H7LdSSi1J239QKVXMBGE+UQbiH6mUOqOUOqGU2qaUKmqKOJ8mvTY8dNxLSimtlMpRcxBlJH6lVNe0v8NppdTC7I4xPRl4HRVRSu1QSh1Ney21NkWcT6KU+lkpFamUOvWE/Uop9V1a+04opaqmd04pPgkhhBBCCCGEyDSllBkwA2gFlAN6KKXKPXLYAOC21rokMAX4KnujfLIMxn8U8NdaVwKWAV9nb5RPl8E2oJRyAIYBB7M3wqfLSPxKqVLAB0BdrXV5YHh2x/k0GfwbjAaWaq39SF1Rcmb2RpmueUDLp+xvBZRK+xkIfJ/eCaX49BClVFml1Cyl1DKl1CBTx5OTKaXslFJBSqk2po4lp1JKBSildqe9pgJMHU9OpJQyKKU+U0pNU0r1S/838g/JRxkjuSh9kovSJ7noySQXZYzkovRJLkpfHslFNYDzWuuLWusEYDHQ/pFj2gPz0x4vA5oopVQ2xvg06cavtd6htY5Ne3oA8MnmGNOTkb8BwARSC3/x2RlcBmQk/teAGVrr2wBa68hsjjE9GWmDBhzTHjsB4dkYX7q01rtIXcnySdoDv+hUBwBnpZTn086Z54tPTxou9rhhcFrrP7XWbwBdgbqmiNdUnqWf0rwHLM3eKE3vGftJAzGANRCa3bGayjP2UXtS/8FOJB/0keSj9EkuyhjJRemTXPRkkovSJ7koYyQXpS8f5iJv4OpDz0PTtj32GK11EhANuGRLdOnLSPwPGwBsMGpEzy7dNqjUW6QKa63XZWdgGZSRv0FpoLRSaq9S6oBS6mkjdEwhI20YB/RWSoWSurLk0OwJLcs86/8reb/4xGOGi6mnDINTSrUD1vHI0qL5wDwy2E9KqWbAGSCnVZizwzwy/nrarbVuReob0vHZHKcpzSPjffQCsE9rPRLID9+oz0PyUXrmIbkoI+YhuSg985Bc9CTzkFyUnnlILsqIeUguSs88JBflSUqp3oA/MNHUsTwLpZQBmAy8bepYMsGc1Nu9AoAewI9KKWdTBvQcegDztNY+QGtgQdrfJs/K042DJw4Xe+IwOK316rR/GHtlb6Sm9Yz9FADUAnoCr+X1/0ke9iz9pLVOSdt/G7DKxjBN6hlfS6Gk9g9AcvZFaRqSj9InuShjJBelT3LRk0kuSp/kooyRXJS+fJiLwoDCDz33Sdv22GOUUuak3nJ0M1uiS19G4kcp1RT4CGintX6QTbFlVHptcAAqAIFKqUuk5q/VKudMOp6Rv0EosFprnai1DgHOkVqMyiky0oYBpI2Y1VrvJ3VUqGu2RJc1MvT/ysPMjRpOzvW4IWI1Ver9551I/QcxP3279ySP7Set9RAApVR/IOqhNxP51ZNeT52AFoAzMN0EceUkj+0j4FtgmlKqPrDLFIHlAJKP0ie5KGMkF6VPctGTSS5Kn+SijJFclL68nIsOA6WUUr6kfhDtTmph9mGrgX7AfqAzsF1rrbM1yidLN36llB/wA9AyB841BOm0QWsdzUNFDqVUIPCO1joom+N8koy8hlaSOnJorlLKldTb8C5mZ5DpyEgbrgBNgHlKqbKkFp9uZGuUmbMaGKKUWkxq/orWWl972i/k1+LTY2mtA4FAE4eRa2it55k6hpxMa70CWGHqOHKytMkaB5g6jpxI8lHGSS56OslF6ZNc9GSSizJOctHTSS5KX17IRVrrJKXUEGATYAb8rLU+rZT6BAjSWq8G5pB6i9F5UkeFdTddxP+VwfgnAvbA7yp1nvQrWut2Jgv6ERlsQ46Vwfg3Ac2VUmdIHSU4SmudU0bPZbQNb5N6u+AIUufE65+DirAopRaROrLXNW1eqrGABYDWehapX0i1Bs4DscDL6Z0zvxafnnmIWD4l/ZQx0k/pkz56Mumb9EkfZYz0U/qkj55M+iZ90kcZI/2UvjzdR1rr9TwyUlJrPeahx/FAl+yOK6MyEH/TbA/qGaXXhke2B2RHTM8iA38DDYxM+8mRMtCGM+TghTy01j3S2a+BN5/lnPnmnvRH/DsMTillSWq1PUdXgE1E+iljpJ/SJ330ZNI36ZM+yhjpp/RJHz2Z9E36pI8yRvopfdJHQoh8J88Xn9KGi+0HXlBKhSqlBqQt6fnPMLg/gaVa69OmjNPUpJ8yRvopfdJHTyZ9kz7po4yRfkqf9NGTSd+kT/ooY6Sf0id9JIQQqVQOuq1QCCGEEEIIIYQQQuQxeX7kkxBCCCGEEEIIIYQwHSk+CSGEEEIIIYQQQgijkeKTEEIIIYQQQgghhDAaKT4JIYQQQgghhBBCCKOR4pMQQgghhBBCCCGEMBopPgkhhBBCCCGEEEIIo5Hik3guSqlkpdSxh37eN3VMACrVdqWUY9pzd6XUQqXURaVUsFJqv1KqYzrnuKiUeuGRbVOVUu8ppSoqpeYZsQlCiGcguUgIkRNILhJCCCGeztzUAYhcK05rXSUrT6iUMtdaJ2XyNK2B41rru0opBawE5mute6ZdoyjQLp1zLAa6A+PTfscAdAbqaq0vK6V8lFJFtNZXMhmrECLzJBdJLhIiJ5BcJLlICCHEU8jIJ5GllFKXlFLjlVJHlFInlVJl0rbbKaV+VkodUkodVUq1T9veXym1Wim1HdimlLJVSi1VSp1RSv2hlDqolPJXSr2ilJr60HVeU0pNeUwIvYBVaY8bAwla61n/7NRaX9ZaT0s7h5lSaqJS6rBS6oRS6vW0wxYB3R46ZwPgstb6ctrzNaS+CRNC5FCSi4QQOYHkIiGEECKVFJ/E87JR/x1e/vCbkiitdVXge+CdtG0fAdu11jWARsBEpZRd2r6qQGetdUNgMHBba10O+BiolnbMUqCtUsoi7fnLwM+PiasuEJz2uDxw5CltGABEa62rA9WB15RSvlrrk0CKUqpy2nHdSX3j9Y8goP5TziuEyD6Si4QQOYHkIiGEEOIp5LY78byeNrx8Rdp/g4FOaY+bA+2UUv+86bIGiqQ93qK1vpX2uB7wLYDW+pRS6kTa45i0bwHbKKX+BCzS3gw9qqDW+t7jglJKzUg7f0LaG6vmQCWlVOe0Q5yAUkAIqW+quiulTgMdgLEPnSoS8HpC24UQ2UtykRAiJ5BcJIQQQjyFFJ+EMTxI+28y/3uNKeAlrfVfDx+olKoJ3M/geX8CPgTOAnOfcEySUsqgtU4BTgMv/bNDa/2mUsqV1G/o/olpqNZ602POsxjYDOwETmitIx7aZw3EZTBmIYTpSC4SQuQEkouEEELke3Lbncgum4ChSikFoJTye8Jxe4GuaceUAyr+s0NrfRAoDPTkv8O9H/YXUDzt8XbAWik16KH9to/ENOifIetKqdL/DHnXWl8AooAvH3Ot0sCpJ7ZUCJGTSS4SQuQEkouEEELkK1J8Es/r0bkNvkzn+AmABXAibcj2hCccNxNwU0qdAT4l9Vu66If2LwX2aq1vP+H31wEBAFprTerQ8IZKqRCl1CFgPvBe2rE/AWeAI0qpU8AP/Hc04CKgDP8bLv+PRmnXEUKYnuQiIUROILlICCGEeAqV+u+QEDmDUsqM1HkL4pVSJYCtwAta64S0/WuBKVrrbU/4fU/gF611MyPFZ0XqkPN6WbD8sRAih5JcJITICSQXCSGEyCtkzieR09gCO9KGfCtgsNY6QSnlDBwCjj/pDRaA1vqaUupHpZSj1vquEeIrArwvb7CEyPMkFwkhcgLJRUIIIfIEGfkkhBBCCCGEEEIIIYxG5nwSQgghhBBCCCGEEEYjxSchhBBCCCGEEEIIYTRSfBJCCCGEEEIIIYQQRiPFJyGEEEIIIYQQQghhNFJ8EkIIIYQQQgghhBBGI8UnIYQQQgghhBBCCGE0/wem6XBHBL79oAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1440x576 with 8 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(2, 4, figsize=(5*4, 4*2))\n",
    "colors = sns.color_palette(\"colorblind\")\n",
    "for i, (grpn, group) in enumerate(df.groupby([\"spacing\", \"geom\", \"tts\"])):\n",
    "    if (grpn[1] != \"tri\") or (grpn[0] != 100):\n",
    "        continue\n",
    "\n",
    "    for colname, ax in zip([\"log10(energy/GeV)\", \"theta_deg\", \"phi_deg\", \"x\", \"y\", \"z\", \"t\"], axs.ravel()):\n",
    "\n",
    "        ax.plot(group.index, group[colname], label=f\"TTS: {grpn[2]}\", ls=\"-\", color=colors[i%4])\n",
    "        ax.set_xscale(\"log\")\n",
    "        ax.set_yscale(\"log\")\n",
    "        ax.legend()\n",
    "        ax.set_ylabel(f\"std({colname})\")\n",
    "        ax.set_xlabel(\"Energy (GeV)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "23314ace-79de-4c42-8d5a-2e05891e918a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x576 with 8 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(2, 4, figsize=(5*4, 4*2))\n",
    "colors = sns.color_palette(\"colorblind\")\n",
    "for i, (grpn, group) in enumerate(df.groupby([\"spacing\", \"geom\"])):\n",
    "    for colname, ax in zip([\"log10(energy/GeV)\", \"theta_deg\", \"phi_deg\", \"x\", \"y\", \"z\", \"t\"], axs.ravel()):\n",
    "        if grpn[1] != \"tri\":\n",
    "            continue\n",
    "        \n",
    "        ax.plot(group.index, group[colname], label=f\"Spacing: {grpn[1]}, {grpn[0]}m\", ls=ls, color=colors[i//3])\n",
    "        ax.set_xscale(\"log\")\n",
    "        ax.set_yscale(\"log\")\n",
    "        ax.legend()\n",
    "        ax.set_ylabel(f\"std({colname})\")\n",
    "        ax.set_xlabel(\"Energy (GeV)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "5dea3039-ad06-491e-9573-497153996b90",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x576 with 8 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(2, 4, figsize=(5*4, 4*2))\n",
    "colors = sns.color_palette(\"colorblind\")\n",
    "for i, (grpn, group) in enumerate(df.groupby([\"spacing\", \"geom\"])):\n",
    "    for colname, ax in zip([\"log10(energy/GeV)\", \"theta_deg\", \"phi_deg\", \"x\", \"y\", \"z\", \"t\"], axs.ravel()):\n",
    "        if grpn[1] == \"tri\":\n",
    "            continue\n",
    "        if grpn[1] == \"hex\":\n",
    "            ls = \"--\"\n",
    "        else:\n",
    "            ls = \"-\"\n",
    "        ax.plot(group.index, group[colname], label=f\"Spacing: {grpn[1]}, {grpn[0]}m\", ls=ls, color=colors[i//3])\n",
    "        ax.set_xscale(\"log\")\n",
    "        ax.set_yscale(\"log\")\n",
    "        ax.legend()\n",
    "        ax.set_ylabel(f\"std({colname})\")\n",
    "        ax.set_xlabel(\"Energy (GeV)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "22ea257d-9caf-454e-bf7e-16f937caf3e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f29c82d2650>]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xs = df[(df[\"spacing\"] == 100) & (df[\"geom\"] == \"tri\")].index\n",
    "ys = df[(df[\"spacing\"] == 100) & (df[\"geom\"] == \"tri\")][\"theta\"]\n",
    "\n",
    "plt.plot(np.log10(xs), ys)\n",
    "\n",
    "ytest = 1/(np.log10(xs)-2)**(1.75) * 0.12\n",
    "plt.plot(np.log10(xs), ytest)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "4068d2fe-e055-4f07-ae39-5588083ebf60",
   "metadata": {},
   "outputs": [],
   "source": [
    "event_params = {\n",
    "    \"pos\": np.asarray([0.0, 0, 0]),\n",
    "    \"t0\": 30.0,\n",
    "    \"energy\": 1e5,\n",
    "    \"theta\": np.radians(40),\n",
    "    \"phi\": np.radians(30),\n",
    "}\n",
    "llh_func_builder = make_llh_func_builder(eval_binned_likelihood, binned_net)\n",
    "fi = calc_fisher_information(\n",
    "    100, det, event_params, generate_cascade_amplitudes, llh_func_builder\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "5f5bd241-b026-4ab7-a7bc-a1cffc8036f0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.00388254 0.00329877 0.01236468 0.49744192 0.82622378 0.14601518\n",
      " 0.6610854 ]\n"
     ]
    }
   ],
   "source": [
    "crao = np.sqrt(np.diag(np.linalg.inv(fi)))\n",
    "print(crao)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 438,
   "id": "2074176c-0829-4711-bcac-9d9b211f3cda",
   "metadata": {},
   "outputs": [],
   "source": [
    "spacings = [75, 100, 150]\n",
    "\n",
    "all_spacings = []\n",
    "for spacing in spacings:\n",
    "\n",
    "    det = make_triang(spacing, oms_per_line, dist_z, dark_noise_rate, rng)\n",
    "    module_positions = torch.tensor(det.module_coords, dtype=torch.float, device=device)\n",
    "\n",
    "    all_hessians = []\n",
    "    hessians = []\n",
    "    hessians_f = []\n",
    "\n",
    "    all_n_photons_gen = np.logspace(8, 11, 10)\n",
    "    for amp_gen in all_n_photons_gen:\n",
    "        amp_gen_t = torch.tensor(amp_gen, device=device, dtype=torch.float)\n",
    "        hessians_f = []\n",
    "        for seed in range(300):\n",
    "            event, record = generate_cascade(\n",
    "                det, pos, t0_gen, cdir, n_photons=amp_gen, pprop_func=gen_ph\n",
    "            )\n",
    "            wrap = make_wrap(event, module_positions, eval_likelihood, net)\n",
    "            # hess = hessian(wrap, (torch.log10(amp_gen_t), theta_t, phi_t, pos_t[0], pos_t[1], pos_t[2], t0_gen_t), strict=True)\n",
    "            jac = torch.stack(\n",
    "                jacobian(\n",
    "                    wrap,\n",
    "                    (\n",
    "                        torch.log10(amp_gen_t),\n",
    "                        theta_t,\n",
    "                        phi_t,\n",
    "                        pos_t[0],\n",
    "                        pos_t[1],\n",
    "                        pos_t[2],\n",
    "                        t0_gen_t,\n",
    "                    ),\n",
    "                    strict=True,\n",
    "                )\n",
    "            ).detach()\n",
    "            # hessians.append(unpack_hessian(hess))\n",
    "            hessians_f.append((jac[np.newaxis, :] * jac[:, np.newaxis]).cpu().numpy())\n",
    "            torch.cuda.empty_cache()\n",
    "        all_hessians.append(hessians_f)\n",
    "    all_spacings.append(all_hessians)\n",
    "hess_mf = np.average(all_spacings, axis=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 439,
   "id": "4fbf82f9-92c5-4237-b884-ba78bfc035bc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.29203663 0.15352676 0.07936085 0.04020268 0.02459871 0.01465636\n",
      " 0.00941159 0.00619484 0.00422443 0.00296597]\n",
      "[0.35885288 0.17311612 0.08284528 0.04271057 0.02532418 0.0168706\n",
      " 0.01103634 0.00736033 0.00469894 0.00315145]\n",
      "[0.33953496 0.14922656 0.06687566 0.03574517 0.02119206 0.01353288\n",
      " 0.00803545 0.00567125 0.00387631 0.00295389]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(1, 2, figsize=(8, 4))\n",
    "for i, spacing in enumerate(spacings):\n",
    "    all_inv = np.asarray(\n",
    "        [np.sqrt(np.diag(np.linalg.inv(hess_mf[i, j]))) for j in range(10)]\n",
    "    )\n",
    "    print(all_inv[:, 1])\n",
    "    axs[0].plot(\n",
    "        all_n_photons_gen / (5.3 * 250 * 1e2),\n",
    "        np.degrees(all_inv[:, 1]),\n",
    "        label=f\"Spacing ({spacing:.2f})\",\n",
    "    )\n",
    "    axs[1].plot(\n",
    "        all_n_photons_gen / (5.3 * 250 * 1e2),\n",
    "        np.degrees(all_inv[:, 2]),\n",
    "        label=f\"Spacing ({spacing:.2f})\",\n",
    "    )\n",
    "axs[0].set_xscale(\"log\")\n",
    "axs[1].set_xscale(\"log\")\n",
    "axs[0].set_xlabel(\"E (GeV)\")\n",
    "axs[1].set_xlabel(\"E (GeV)\")\n",
    "axs[0].legend()\n",
    "axs[1].legend()\n",
    "axs[0].set_ylabel(\"sqrt(Variance) (deg)\")\n",
    "axs[0].set_title(\"Zenith\")\n",
    "axs[1].set_title(\"Azimuth\")\n",
    "plt.savefig(\"figures/cramer_rao_example.png\", dpi=250)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "06ddd1fa-1788-4000-a5bd-9db12de74291",
   "metadata": {},
   "outputs": [],
   "source": [
    "fisher_results = {}\n",
    "\n",
    "spacings = [75, 100, 150]\n",
    "\n",
    "all_spacings = []\n",
    "for spacing in spacings:\n",
    "\n",
    "    det = make_triang(spacing, oms_per_line, dist_z, dark_noise_rate, rng)\n",
    "    module_positions = torch.tensor(det.module_coords, dtype=torch.float, device=device)\n",
    "\n",
    "    all_hessians = []\n",
    "    hessians = []\n",
    "    hessians_f = []\n",
    "\n",
    "    all_n_photons_gen = np.logspace(8, 11, 10)\n",
    "    for amp_gen in all_n_photons_gen:\n",
    "        amp_gen_t = torch.tensor(amp_gen, device=device, dtype=torch.float)\n",
    "        hessians_f = []\n",
    "        for seed in range(300):\n",
    "            event, record = generate_cascade_amplitudes(\n",
    "                det,\n",
    "                pos,\n",
    "                t0_gen,\n",
    "                cdir,\n",
    "                n_photons=amp_gen,\n",
    "                pprop_func=gen_ph_binned,\n",
    "                seed=seed,\n",
    "            )\n",
    "            wrap = make_wrap_no_t(\n",
    "                event, module_positions, eval_binned_likelihood, binned_net\n",
    "            )\n",
    "            # hess = hessian(wrap, (torch.log10(amp_gen_t), theta_t, phi_t, pos_t[0], pos_t[1], pos_t[2], t0_gen_t), strict=True)\n",
    "            jac = torch.stack(\n",
    "                jacobian(\n",
    "                    wrap,\n",
    "                    (\n",
    "                        torch.log10(amp_gen_t),\n",
    "                        theta_t,\n",
    "                        phi_t,\n",
    "                        pos_t[0],\n",
    "                        pos_t[1],\n",
    "                        pos_t[2],\n",
    "                    ),\n",
    "                    strict=True,\n",
    "                )\n",
    "            ).detach()\n",
    "            # hessians.append(unpack_hessian(hess))\n",
    "            hessians_f.append((jac[np.newaxis, :] * jac[:, np.newaxis]).cpu().numpy())\n",
    "            torch.cuda.empty_cache()\n",
    "        all_hessians.append(hessians_f)\n",
    "    all_spacings.append(all_hessians)\n",
    "hess_mf = np.average(all_spacings, axis=2)\n",
    "\n",
    "fisher_results[\"triang\"] = hess_mf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "0a2b035f-51a3-4a2c-94ef-8b2d4f99f8ec",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.26548343 0.19476233 0.1293747  0.08379738 0.05960499 0.0406361\n",
      " 0.02742459 0.01802186 0.01207399 0.00877168]\n",
      "[0.21949468 0.15528418 0.10474151 0.06984114 0.05282469 0.03552592\n",
      " 0.02304198 0.01563723 0.01022622 0.00712899]\n",
      "[0.30585934 0.20972301 0.13949619 0.09349603 0.06681366 0.04516109\n",
      " 0.02937323 0.01990406 0.0133326  0.0094935 ]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(1, 2, figsize=(8, 4))\n",
    "for i, spacing in enumerate(spacings):\n",
    "    all_inv = np.asarray(\n",
    "        [np.sqrt(np.diag(np.linalg.inv(hess_mf[i, j]))) for j in range(10)]\n",
    "    )\n",
    "    print(all_inv[:, 1])\n",
    "    axs[0].plot(\n",
    "        all_n_photons_gen / (5.3 * 250 * 1e2),\n",
    "        np.degrees(all_inv[:, 1]),\n",
    "        label=f\"Spacing ({spacing:.2f})\",\n",
    "    )\n",
    "    axs[1].plot(\n",
    "        all_n_photons_gen / (5.3 * 250 * 1e2),\n",
    "        np.degrees(all_inv[:, 2]),\n",
    "        label=f\"Spacing ({spacing:.2f})\",\n",
    "    )\n",
    "axs[0].set_xscale(\"log\")\n",
    "axs[1].set_xscale(\"log\")\n",
    "axs[0].set_xlabel(\"E (GeV)\")\n",
    "axs[1].set_xlabel(\"E (GeV)\")\n",
    "axs[0].legend()\n",
    "axs[1].legend()\n",
    "axs[0].set_ylabel(\"sqrt(Variance) (deg)\")\n",
    "axs[0].set_title(\"Zenith\")\n",
    "axs[1].set_title(\"Azimuth\")\n",
    "plt.savefig(\"figures/cramer_rao_example.png\", dpi=250)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "0c4b23a4-df1d-41aa-a716-9d4ac8a5d909",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.12461976 0.08538367 0.061878   0.04293092 0.02906864 0.01896312\n",
      " 0.01287025 0.00940793 0.00626487 0.00433612]\n",
      "[0.22017373 0.14380359 0.09953116 0.06781219 0.04670058 0.03223904\n",
      " 0.01981022 0.01387001 0.01014153 0.00640564]\n",
      "[0.44161591 0.30613019 0.21346263 0.14128561 0.10170861 0.06946233\n",
      " 0.04703779 0.03149673 0.02178245 0.01412427]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "spacings = [75, 100, 150]\n",
    "\n",
    "all_spacings = []\n",
    "for spacing in spacings:\n",
    "\n",
    "    det = Detector(\n",
    "        make_hex_grid(3, spacing, 20, 50, 16 * 1e-5, rng=np.random.RandomState(0))\n",
    "    )\n",
    "    module_positions = torch.tensor(det.module_coords, dtype=torch.float, device=device)\n",
    "\n",
    "    all_hessians = []\n",
    "    hessians = []\n",
    "    hessians_f = []\n",
    "\n",
    "    all_n_photons_gen = np.logspace(8, 11, 10)\n",
    "    for amp_gen in all_n_photons_gen:\n",
    "        amp_gen_t = torch.tensor(amp_gen, device=device, dtype=torch.float)\n",
    "        hessians_f = []\n",
    "        for seed in range(300):\n",
    "            event, record = generate_cascade_amplitudes(\n",
    "                det,\n",
    "                pos,\n",
    "                t0_gen,\n",
    "                cdir,\n",
    "                n_photons=amp_gen,\n",
    "                pprop_func=gen_ph_binned,\n",
    "                seed=seed,\n",
    "            )\n",
    "            wrap = make_wrap_no_t(\n",
    "                event, module_positions, eval_binned_likelihood, binned_net\n",
    "            )\n",
    "            # hess = hessian(wrap, (torch.log10(amp_gen_t), theta_t, phi_t, pos_t[0], pos_t[1], pos_t[2], t0_gen_t), strict=True)\n",
    "            jac = torch.stack(\n",
    "                jacobian(\n",
    "                    wrap,\n",
    "                    (\n",
    "                        torch.log10(amp_gen_t),\n",
    "                        theta_t,\n",
    "                        phi_t,\n",
    "                        pos_t[0],\n",
    "                        pos_t[1],\n",
    "                        pos_t[2],\n",
    "                    ),\n",
    "                    strict=True,\n",
    "                )\n",
    "            ).detach()\n",
    "            # hessians.append(unpack_hessian(hess))\n",
    "            hessians_f.append((jac[np.newaxis, :] * jac[:, np.newaxis]).cpu().numpy())\n",
    "            torch.cuda.empty_cache()\n",
    "        all_hessians.append(hessians_f)\n",
    "    all_spacings.append(all_hessians)\n",
    "hess_mf = np.average(all_spacings, axis=2)\n",
    "\n",
    "fig, axs = plt.subplots(1, 2, figsize=(8, 4))\n",
    "for i, spacing in enumerate(spacings):\n",
    "    all_inv = np.asarray(\n",
    "        [np.sqrt(np.diag(np.linalg.inv(hess_mf[i, j]))) for j in range(10)]\n",
    "    )\n",
    "    print(all_inv[:, 1])\n",
    "    axs[0].plot(\n",
    "        all_n_photons_gen / (5.3 * 250 * 1e2),\n",
    "        np.degrees(all_inv[:, 1]),\n",
    "        label=f\"Spacing ({spacing:.2f})\",\n",
    "    )\n",
    "    axs[1].plot(\n",
    "        all_n_photons_gen / (5.3 * 250 * 1e2),\n",
    "        np.degrees(all_inv[:, 2]),\n",
    "        label=f\"Spacing ({spacing:.2f})\",\n",
    "    )\n",
    "axs[0].set_xscale(\"log\")\n",
    "axs[1].set_xscale(\"log\")\n",
    "axs[0].set_xlabel(\"E (GeV)\")\n",
    "axs[1].set_xlabel(\"E (GeV)\")\n",
    "axs[0].legend()\n",
    "axs[1].legend()\n",
    "axs[0].set_ylabel(\"sqrt(Variance) (deg)\")\n",
    "axs[0].set_title(\"Zenith\")\n",
    "axs[1].set_title(\"Azimuth\")\n",
    "plt.savefig(\"figures/cramer_rao_example.png\", dpi=250)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e1411285-dacc-4318-8a67-b5ef7a814061",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 552,
   "id": "4c70474f-0db4-4562-9b6e-26af3122a56e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9208471"
      ]
     },
     "execution_count": 552,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.degrees(np.sqrt(np.linalg.inv(hess_mf)[1, 1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 553,
   "id": "ba384b33-6d22-4d66-b56c-39575ca3161b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.3092561"
      ]
     },
     "execution_count": 553,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.degrees(np.sqrt(np.linalg.inv(hess_mf)[2, 2]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 449,
   "id": "4554fde6-66ec-489f-8514-ee2c00570d7f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: RuntimeWarning: invalid value encountered in sqrt\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "nan"
      ]
     },
     "execution_count": 449,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.degrees(np.sqrt(np.linalg.inv(-hess_m)[2, 2]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 339,
   "id": "af4af04f-2770-4d21-80a9-685efdf60582",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "source_to_model_input() missing 2 required positional arguments: 'c_vac' and 'n_gr'",
     "output_type": "error",
     "traceback": [
      "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[0;31mTypeError\u001B[0m                                 Traceback (most recent call last)",
      "\u001B[0;32m/tmp/ipykernel_139/3734230258.py\u001B[0m in \u001B[0;36m<module>\u001B[0;34m\u001B[0m\n\u001B[0;32m----> 1\u001B[0;31m \u001B[0mmodel_in\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0msource_to_model_input\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mdet\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mmodule_coords\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0;34m[\u001B[0m\u001B[0mphsrc\u001B[0m\u001B[0;34m]\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m\u001B[1;32m      2\u001B[0m \u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m      3\u001B[0m \u001B[0mxs\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0mnp\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mlinspace\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;36m0\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0;36m100\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0;36m1000\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m      4\u001B[0m \u001B[0mxs_t\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0mtorch\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mtensor\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mxs\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mdevice\u001B[0m\u001B[0;34m=\u001B[0m\u001B[0mdevice\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mdtype\u001B[0m\u001B[0;34m=\u001B[0m\u001B[0mtorch\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mfloat\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m      5\u001B[0m \u001B[0;34m\u001B[0m\u001B[0m\n",
      "\u001B[0;31mTypeError\u001B[0m: source_to_model_input() missing 2 required positional arguments: 'c_vac' and 'n_gr'"
     ]
    }
   ],
   "source": [
    "model_in = source_to_model_input(det.module_coords, [phsrc])\n",
    "\n",
    "xs = np.linspace(0, 100, 1000)\n",
    "xs_t = torch.tensor(xs, device=device, dtype=torch.float)\n",
    "\n",
    "plt.plot(\n",
    "    xs, torch.exp(uniform_triple_exp(xs_t, pdf_params)[:, 30]).detach().cpu(), color=\"r\"\n",
    ")\n",
    "\n",
    "# times =\n",
    "# sns.histplot(times, bins = np.linspace(0, 100, 100), stat=\"density\")\n",
    "# plt.semilogy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ac472e0f-6d3f-4ae6-80b8-67335bffc876",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "58185f53-8388-4305-9790-941427b6efc7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Y2vp9oVDwl42b5YRr+hnUSv2+WCw68M1yxKGfMeVymcnJyVQXW5VKJfbu3evAN8sRl3cyZmpqirNnzzbcx/V7s/xq2tOXtF7Sk5JekXRY0lTSvkbSQUmvJj9XJ+2SdK+kOUkvSrqu5rkmkv1flTSxfKeVP9WSTrMefqFQ8Lx7sxxLU945B9wVEZuAG4E7JG0C7gb+KiI2An+V/A5wC7AxuU0Ce6DyIQHsBD4K3ADsrH5Q2NKkLem4fm9mTUM/It6KiOeS++8AR4C1wBZgf7LbfuDXk/tbgAej4ingKklXAzcDByPiTET8EDgIbO7kyeRRdYZOs5KO6/dmBi3W9CWNAtcCTwMfiIi3kk3fBz6Q3F8LvFnzsONJW732i19jkspfCFxzzTWtHF6utLIccqlU4vTp0104KjPrd6ln70i6AngUuDMi3q7dFpWJ4Ev7xuyfPdfeiBiLiLHh4eFOPGXmtDJDp1gssnv37i4clZkNglShL+kyKoFfjojHkuYfJGUbkp8nk/YTwPqah69L2uq1W4vSzNABl3TM7FJpZu8IeAA4EhFfrdl0AKjOwJkA/qym/TPJLJ4bgR8lZaAngJskrU4GcG9K2qwF5XI51QwdL5ZmZotJU9P/GLANeEnS80nbPcCXgUck/RZwDPhUsu1x4FZgDjgL/CZARJyR9CXgULLfFyPiTCdOIi+qg7aNFItF9+7NrK6moR8RfwOozuZfXWT/AO6o81z7gH2tHKBVVOv4jZZV8AqZZtaMr8gdANUefrPA9wwdM2vGa+/0uR07drBt27aGge8ZOmaWlkO/j6VZC79QKLiGb2apOfT7VJq18L2sgpm1yqHfh9IM2rqHb2bt8EBun0kzaCvJPXwza4t7+n0kTQ+/uha+A9/M2uGefh+Znp5uuLyCv8vWzJbKPf0+cuzYsbrbPGhrZp3g0O8T5XKZyjJHl/KgrZl1ikO/DzSanulBWzPrJId+jzUbvI0IB76ZdYwHcnsozfTMkZGRLh6RmWWde/o9kmZ6ZrFYZNeuXV08KjPLOvf0eyBND9+Dt2a2HNzT77K0PXwP3prZcnDod1mz77d1D9/MlpNDv4uafb+te/hmttwc+l00PT1dd5t7+GbWDQ79LimXyw2XWXAP38y6oWnoS9on6aSkl2vaPiLpKUnPS5qVdEPSLkn3SpqT9KKk62oeMyHp1eQ2sTyn05+qg7f1lEolB76ZdUWanv7Xgc0XtX0F+P2I+AjwheR3gFuAjcltEtgDIGkNsBP4KHADsFPS6iUe+0CoTs+sN3jr77c1s25qGvoR8S3gzMXNwD9I7v9D4G+T+1uAB6PiKeAqSVcDNwMHI+JMRPwQOMilHySZk2Z6puv4ZtZN7V6cdSfwhKQ/oPLB8c+T9rXAmzX7HU/a6rVnWrPpmSMjIw58M+uqdgdytwO/ExHrgd8BHujUAUmaTMYJZk+dOtWpp+26NNMzvcSCmXVbu6E/ATyW3P8fVOr0ACeA9TX7rUva6rVfIiL2RsRYRIwNDw+3eXi95+mZZtaP2g39vwX+ZXL/k8Cryf0DwGeSWTw3Aj+KiLeAJ4CbJK1OBnBvStoyydMzzaxfNa3pS/oG8HFgSNJxKrNw/gOwW9JK4P9RmakD8DhwKzAHnAV+EyAizkj6EnAo2e+LEXHx4HAmeHqmmfWzpqEfEZ+us+n6RfYN4I46z7MP2NfS0Q2YZqtnenqmmfWar8jtEE/PNLNB4NDvkOnpaU/PNLO+59DvkEYDt56eaWb9wqHfAeVyGUmLbvP0TDPrJw79DpienqYyhn0hSZ6eaWZ9xaG/RI3m5EeEA9/M+opDfwmazckfGRnp4tGYmTXX7oJruZdmTr4Hb82s37in3wbPyTezQeXQb4Pn5JvZoHLot6jZYmou65hZP3Pot6DZwK3n5JtZv3Pot6BRWadYLHpOvpn1PYd+CxqVddzDN7NB4NBPqdFSCx64NbNB4dBPqdFSCx64NbNB4dBPwUstmFlWOPSb8FILZpYlXoahAS+1YGZZ455+HV5qwcyyyKFfh5daMLMsahr6kvZJOinp5Yvaf1vStyUdlvSVmvbPS5qT9B1JN9e0b07a5iTd3dnT6DwvtWBmWZSmpv914I+BB6sNkj4BbAH+aUS8J+n9Sfsm4Dbg54F/BPylpA8nD/sT4NeA48AhSQci4pVOnUgnVefkLzZF00stmNkgaxr6EfEtSaMXNW8HvhwR7yX7nEzatwAPJ+2vS5oDbki2zUXEawCSHk727cvQ99cfmllWtVvT/zDwK5KelvTXkn4paV8LvFmz3/GkrV77JSRNSpqVNHvq1Kk2D699npNvZlnWbuivBNYANwK/CzyiemsUtCgi9kbEWESMDQ8Pd+IpU/OcfDPLunbn6R8HHotKDeQZSeeBIeAEsL5mv3VJGw3a+0azVTQ9eGtmg67dnv43gU8AJAO1q4DTwAHgNkmXS9oAbASeAQ4BGyVtkLSKymDvgSUee0c1+3IUD96aWRY07elL+gbwcWBI0nFgJ7AP2JdM4/wxMJH0+g9LeoTKAO054I6IWEie57PAE0AB2BcRh5fhfNqSpqzjwDezLNBis1T6xdjYWMzOzi7764yOjtbt5ReLRffyzWygSHo2IsYW2+YrcvGXo5hZfuQ+9P3lKGaWJ7kPfX85ipnlSe5D/4033li03RdimVkW5Tr0y+UyK1Ys/p/AF2KZWRblNvQbrZfvC7HMLKtyG/r1rr71KppmlmW5Df16tfzz58878M0ss3IZ+o1q+ddcc02Xj8bMrHtyF/qu5ZtZnuUu9F3LN7M8y13ou5ZvZnmWq9B3Ld/M8i43oe9avplZjkLftXwzsxyFvmv5ZmY5Cv01a9Ys2u5avpnlSS5Cv1wu8/bbb1/SvmrVKtfyzSxXchH609PT/OQnP7mk/corr3Rpx8xyJRehX6+ef+bMmS4fiZlZbzUNfUn7JJ2U9PIi2+6SFJKGkt8l6V5Jc5JelHRdzb4Tkl5NbhOdPY36PDffzOxn0vT0vw5svrhR0nrgJqC2G30LsDG5TQJ7kn3XADuBjwI3ADslrV7KgafhuflmZhdqGvoR8S1gsTrIHwKfA2q/YHYL8GBUPAVcJelq4GbgYESciYgfAgdZ5IOk0zw338zsQm3V9CVtAU5ExAsXbVoLvFnz+/GkrV77Ys89KWlW0uypU6faObyf8tx8M7MLtRz6korAPcAXOn84EBF7I2IsIsaGh4eX9Fz1avau5ZtZXrXT0/8QsAF4QdJRYB3wnKSfA04A62v2XZe01WtfNuVymXffffeSdtfyzSzPWg79iHgpIt4fEaMRMUqlVHNdRHwfOAB8JpnFcyPwo4h4C3gCuEnS6mQA96akbVlUB3Dn5+cvaC+VSq7lm1mupZmy+Q3g/wD/WNJxSb/VYPfHgdeAOeBrwA6AiDgDfAk4lNy+mLQti3oDuFdccYUD38xyTRHRfK8eGRsbi9nZ2ZYft2LFChY7L0mcP3++E4dmZta3JD0bEWOLbcvkFbkewDUzW1wmQ//WW29F0gVtHsA1M8tg6JfLZfbv339BeUcSExMTruebWe5lLvQXG8SNCB5//PEeHZGZWf/IXOjXuwq3XruZWZ5kLvQ9iGtmVl/mQn/Xrl0Ui8UL2jyIa2ZWkbnQHx8fZ+/evYyMjCCJkZERX4VrZpbI5MVZZmZ5lruLs8zMbHEOfTOzHHHom5nliEPfzCxHHPpmZjnS17N3JJ0Cji3hKYaA0x06nF7KynmAz6VfZeVcsnIesLRzGYmIRb9vtq9Df6kkzdabtjRIsnIe4HPpV1k5l6ycByzfubi8Y2aWIw59M7McyXro7+31AXRIVs4DfC79KivnkpXzgGU6l0zX9M3M7EJZ7+mbmVkNh76ZWY5kMvQlbZb0HUlzku7u9fEshaSjkl6S9LykgVpyVNI+SSclvVzTtkbSQUmvJj9X9/IY06pzLr8n6UTy3jwv6dZeHmMaktZLelLSK5IOS5pK2gfufWlwLoP4vvw9Sc9IeiE5l99P2jdIejrJsv8uadWSXytrNX1JBeC7wK8Bx4FDwKcj4pWeHlibJB0FxiJi4C44kfQvgHeBByPiF5K2rwBnIuLLyQfy6oj4z708zjTqnMvvAe9GxB/08thaIelq4OqIeE7SlcCzwK8Dv8GAvS8NzuVTDN77IuB9EfGupMuAvwGmgP8EPBYRD0u6H3ghIvYs5bWy2NO/AZiLiNci4sfAw8CWHh9TLkXEt4AzFzVvAfYn9/dT+Z+079U5l4ETEW9FxHPJ/XeAI8BaBvB9aXAuAycq3k1+vSy5BfBJ4H8m7R15X7IY+muBN2t+P86A/kNIBPAXkp6VNNnrg+mAD0TEW8n97wMf6OXBdMBnJb2YlH/6viRSS9IocC3wNAP+vlx0LjCA74ukgqTngZPAQeB7wN9FxLlkl45kWRZDP2t+OSKuA24B7kjKDJkQldriINcX9wAfAj4CvAX8154eTQskXQE8CtwZEW/Xbhu092WRcxnI9yUiFiLiI8A6KhWLf7Icr5PF0D8BrK/5fV3SNpAi4kTy8yTwp1T+MQyyHyS12GpN9mSPj6dtEfGD5H/U88DXGJD3JqkZPwqUI+KxpHkg35fFzmVQ35eqiPg74EngnwFXSVqZbOpIlmUx9A8BG5NR71XAbcCBHh9TWyS9LxmgQtL7gJuAlxs/qu8dACaS+xPAn/XwWJakGpKJf8sAvDfJgOEDwJGI+GrNpoF7X+qdy4C+L8OSrkru/30qE1GOUAn/f5fs1pH3JXOzdwCSKVp/BBSAfRGxq7dH1B5JH6TSuwdYCfy3QToXSd8APk5lidgfADuBbwKPANdQWTb7UxHR9wOkdc7l41RKCAEcBf5jTV28L0n6ZeB/Ay8B55Pme6jUwgfqfWlwLp9m8N6XX6QyUFug0hl/JCK+mGTAw8Aa4P8CWyPivSW9VhZD38zMFpfF8o6ZmdXh0DczyxGHvplZjjj0zcxyxKFvZpYjDn0zsxxx6JuZ5cj/BxUIrddLW/91AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "thetas = torch.linspace(np.radians(0), np.radians(30), 180)\n",
    "for theta in thetas:\n",
    "    plt.plot(\n",
    "        np.degrees(theta.cpu().detach()),\n",
    "        eval_dist(event2, 0.3 * 1e9, pos, theta, phi).cpu().detach(),\n",
    "        \"ok\",\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c6982636-7e37-412a-bb19-d809106c9679",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "5805eac4-2dec-4f0c-a883-505f37f2b39a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def wrap(theta, phi):\n",
    "    return eval_dist(event, 1e6, pos, theta, phi)\n",
    "\n",
    "\n",
    "theta = torch.tensor(20.0, device=device)  #\n",
    "phi = torch.tensor(0.0, device=device)\n",
    "hess = hessian(wrap, (theta, phi), strict=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "af54b89d-2c85-4b65-9fb1-a9e88fdcbd65",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((tensor(-3.4984, device='cuda:0'), tensor(1.6891, device='cuda:0')),\n",
       " (tensor(1.6891, device='cuda:0'), tensor(2.5304, device='cuda:0')))"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hess"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "43cf9dab-cd19-4abb-a725-3a389d37ba14",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((tensor(0., device='cuda:0'), tensor(0., device='cuda:0')),\n",
       " (tensor(0., device='cuda:0'), tensor(0., device='cuda:0')))"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hessian(\n",
    "    lambda theta, phi: net(\n",
    "        source_to_model_input(module_positions, pos, sph_to_cart(theta, phi))\n",
    "    )\n",
    "    .reshape(module_positions.shape[0], 7)\n",
    "    .sum(),\n",
    "    (theta, phi),\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "id": "41e796b3-07fc-4689-8462-a99ea758f00d",
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "too many indices for tensor of dimension 1",
     "output_type": "error",
     "traceback": [
      "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[0;31mIndexError\u001B[0m                                Traceback (most recent call last)",
      "\u001B[0;32m/tmp/ipykernel_449/3315566254.py\u001B[0m in \u001B[0;36m<module>\u001B[0;34m\u001B[0m\n\u001B[1;32m      1\u001B[0m \u001B[0mxs\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0mtorch\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mlinspace\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;36m0\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0;36m200\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0;36m1000\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mdevice\u001B[0m\u001B[0;34m=\u001B[0m\u001B[0mdevice\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0;32m----> 2\u001B[0;31m \u001B[0mplt\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mplot\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mxs\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mdetach\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mcpu\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0muniform_triple_exp\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mxs\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mpdf_params\u001B[0m\u001B[0;34m[\u001B[0m\u001B[0;36m10\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0;34m:\u001B[0m\u001B[0;34m-\u001B[0m\u001B[0;36m1\u001B[0m\u001B[0;34m]\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mdetach\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mcpu\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m\u001B[1;32m      3\u001B[0m \u001B[0mplt\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mplot\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mxs\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mdetach\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mcpu\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0muniform_triple_exp\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mxs\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mpdf_params2\u001B[0m\u001B[0;34m[\u001B[0m\u001B[0;36m10\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0;34m:\u001B[0m\u001B[0;34m-\u001B[0m\u001B[0;36m1\u001B[0m\u001B[0;34m]\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mdetach\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mcpu\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m      4\u001B[0m \u001B[0;31m#plt.semilogy()\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n",
      "\u001B[0;32m/tmp/ipykernel_449/491382807.py\u001B[0m in \u001B[0;36muniform_triple_exp\u001B[0;34m(xs, parameters)\u001B[0m\n\u001B[1;32m     49\u001B[0m \u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m     50\u001B[0m \u001B[0;32mdef\u001B[0m \u001B[0muniform_triple_exp\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mxs\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mparameters\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m:\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0;32m---> 51\u001B[0;31m     \u001B[0mlog_usf\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0mparameters\u001B[0m\u001B[0;34m[\u001B[0m\u001B[0;34m:\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0;34m-\u001B[0m\u001B[0;36m2\u001B[0m\u001B[0;34m]\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[0m\u001B[1;32m     52\u001B[0m     \u001B[0musf\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0;36m1\u001B[0m \u001B[0;34m-\u001B[0m \u001B[0;36m10\u001B[0m \u001B[0;34m**\u001B[0m \u001B[0;34m(\u001B[0m\u001B[0;34m-\u001B[0m\u001B[0mlog_usf\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n\u001B[1;32m     53\u001B[0m     \u001B[0mout\u001B[0m \u001B[0;34m=\u001B[0m \u001B[0mtorch\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mempty\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0;34m(\u001B[0m\u001B[0mxs\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mshape\u001B[0m\u001B[0;34m[\u001B[0m\u001B[0;36m0\u001B[0m\u001B[0;34m]\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mparameters\u001B[0m\u001B[0;34m.\u001B[0m\u001B[0mshape\u001B[0m\u001B[0;34m[\u001B[0m\u001B[0;36m0\u001B[0m\u001B[0;34m]\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m,\u001B[0m \u001B[0mdevice\u001B[0m\u001B[0;34m=\u001B[0m\u001B[0mdevice\u001B[0m\u001B[0;34m)\u001B[0m\u001B[0;34m\u001B[0m\u001B[0;34m\u001B[0m\u001B[0m\n",
      "\u001B[0;31mIndexError\u001B[0m: too many indices for tensor of dimension 1"
     ]
    }
   ],
   "source": [
    "xs = torch.linspace(0, 200, 1000, device=device)\n",
    "plt.plot(xs.detach().cpu(), uniform_triple_exp(xs, pdf_params[10, :-1]).detach().cpu())\n",
    "plt.plot(xs.detach().cpu(), uniform_triple_exp(xs, pdf_params2[10, :-1]).detach().cpu())\n",
    "# plt.semilogy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "id": "18f3c85d-227e-4ccd-abb2-06d0ddf1727b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcc104dbb10>]"
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xs = torch.linspace(0, 200, 1000, device=device)\n",
    "plt.plot(\n",
    "    xs.detach().cpu(),\n",
    "    poisson_utr_exp(\n",
    "        1e5,\n",
    "        xs,\n",
    "        *pdf_params[\n",
    "            10,\n",
    "        ]\n",
    "    )\n",
    "    .detach()\n",
    "    .cpu(),\n",
    ")\n",
    "plt.plot(\n",
    "    xs.detach().cpu(),\n",
    "    poisson_utr_exp(\n",
    "        1e5,\n",
    "        xs,\n",
    "        *pdf_params2[\n",
    "            10,\n",
    "        ]\n",
    "    )\n",
    "    .detach()\n",
    "    .cpu(),\n",
    ")\n",
    "# plt.semilogy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "bdd786a7-0d5c-4c19-b6f7-0360a2e732e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor(0.0153, device='cuda:0', grad_fn=<RsubBackward1>)"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "torch.autograd.functional.hessian"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "52fa6cfa-595c-41ba-a352-37136bad4a7f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([ 0.1407,  0.4384,  0.7594,  0.7884,  0.6862,  0.0066, -6.5473],\n",
       "       device='cuda:0', grad_fn=<SelectBackward>)"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pdf_params2[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "4d16a30c-3a11-499b-b3bf-93d598b11a29",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fcc104c4f10>]"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xs = np.linspace(0, 300, 1000)\n",
    "plt.plot(xs[xs > 20], 0.9 * 1 / 100 * np.exp((-(xs[xs > 20] - 20) / 100)))\n",
    "plt.plot(xs[xs < 20], 0.1 * 1 / 20 * np.ones((xs < 20).sum()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "id": "f7f62c59-fada-47a4-8692-95dadc8cb139",
   "metadata": {},
   "outputs": [],
   "source": [
    "def func(xs):\n",
    "    xs = np.atleast_1d(xs)\n",
    "    out = np.empty_like(xs)\n",
    "    out[xs > 20] = 0.9 * 1 / 100 * np.exp((-(xs[xs > 20] - 20)) / 100)\n",
    "    out[xs <= 20] = 0.1 * 1 / 20 * np.ones((xs <= 20).sum())\n",
    "    return out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "id": "6ef3d8a6-77e9-4dab-9e28-bf6e9434eb4a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.integrate import quad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "id": "b7bd888b-3367-4bda-beb7-5016cd6a6fa0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.9999500936055827, 1.4619977228846892e-08)"
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "quad(func, 0, 1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "id": "ce42b69f-a5d2-4825-8eb4-c50804db939f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.8143128162955776, 1.7995457225188243e-14)"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "quad(lambda xs: 0.9 * 1 / 100 * np.exp((-xs / 100)), 10, 1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6602915d-49d9-4d89-8fa8-da98a02e0c22",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}