diff --git a/nbody/checklist.md b/nbody/checklist.md
index 20636a8..db1b2c0 100644
--- a/nbody/checklist.md
+++ b/nbody/checklist.md
@@ -1,18 +1,18 @@
 # N-Body project - Checklist
 
 ### Task 1
-- [ ] Compute characteristic quantities/scales
+- [x] Compute characteristic quantities/scales
 - [x] Compare analytical model and particle density distribution
-- [ ] Compute forces through nbody simulation
+- [x] Compute forces through nbody simulation
 - [x] vary softening length and compare results
 - [x] compare with the analytical expectation from Newtons 2nd law
-- [ ] compute the relaxation time
+- [x] compute the relaxation time
 
 ### Task 2 (particle mesh)
 - [ ] Choose reasonable units
-- [ ] Implement force computation on mesh
-- [ ] Find optimal mesh size
-- [ ] Compare with direct nbody simulation
+- [~x] Implement force computation on mesh
+- [x] Find optimal mesh size
+- [x] Compare with direct nbody simulation
 - [ ] Time integration for direct method AND mesh method
 
 
diff --git a/nbody/copy.ipynb b/nbody/copy.ipynb
new file mode 100644
index 0000000..20f72ec
--- /dev/null
+++ b/nbody/copy.ipynb
@@ -0,0 +1,483 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# automatically reflect changes in imported modules\n",
+    "%load_ext autoreload\n",
+    "%autoreload 2\n",
+    "\n",
+    "from pathlib import Path\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import astropy.units as u\n",
+    "\n",
+    "import utils\n",
+    "import utils.logging_config\n",
+    "import logging\n",
+    "logger = logging.getLogger(\"task2 (mesh)\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "DATA_ROOT = Path('data')\n",
+    "# DATA_NAME = 'data0.txt'\n",
+    "# DATA_NAME = 'data1.txt'\n",
+    "DATA_NAME = 'data0_noise.txt'\n",
+    "# DATA_NAME = 'data1_noise.txt'\n",
+    "NBINS = 30\n",
+    "CACHE_ROOT = Path('.cache')\n",
+    "\n",
+    "G = 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "points, columns = utils.load_data(DATA_ROOT / DATA_NAME)\n",
+    "logger.debug(f\"Fetched {points.shape[0]} points, columns: {columns}\")\n",
+    "# points = points[:10, ...]\n",
+    "# TODO remove\n",
+    "# reorder the columns to match the expected order (x, y, z, mass)\n",
+    "particles = points[:, [2, 3, 4, 1]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# plot the distribution of the particles\n",
+    "fig = plt.figure()\n",
+    "ax = fig.add_subplot(111, projection='3d')\n",
+    "ax.scatter(particles[:,0], particles[:,1], particles[:,2], cmap='viridis', c=particles[:,3])\n",
+    "plt.show()\n",
+    "## Note: colormap corresponds to the mass of the particles"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Choice of units\n",
+    "Recap of the particle properties:\n",
+    "- $\\sim 10^4$ particles\n",
+    "- around 1 black hole (10% of the mass)\n",
+    "\n",
+    "$\\implies$ ???"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Set G = 1\n",
+    "G = 1\n",
+    "\n",
+    "# from the particle number we can estimate the total (stellar) mass, excluding the BH\n",
+    "M_TOT = 1e4 * u.M_sun\n",
+    "# the radius aound the black hole follows from ??? # TODO\n",
+    "R_TOT = 1 * u.pc\n",
+    "\n",
+    "# Rescale the units of the particles - considering only the orbiting stars\n",
+    "M_particles = particles[:,3].sum() - 1\n",
+    "R_particles = np.max(np.linalg.norm(particles[:, :3], axis=1))\n",
+    "\n",
+    "logger.info(f\"Considering a globular cluster - total mass of stars: {M_particles}, maximum radius of particles: {R_particles}\")\n",
+    "m_scale = M_TOT / M_particles\n",
+    "r_scale = R_TOT / R_particles\n",
+    "utils.seed_scales(r_scale, m_scale)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "### Direct N body force computation\n",
+    "epsilon = utils.mean_interparticle_distance(particles)\n",
+    "\n",
+    "epsilon_range = np.logspace(-2, 2, 5)\n",
+    "n_squared_forces = []\n",
+    "\n",
+    "SAVE_FORCES = False\n",
+    "\n",
+    "for e in epsilon_range:\n",
+    "    n_particles = particles.shape[0]\n",
+    "    cache_file = CACHE_ROOT / f\"n_squared_forces__n_{n_particles}__softening_multiplier_{e:.0f}.npy\"\n",
+    "    try:\n",
+    "        f = np.load(cache_file)\n",
+    "        logger.info(f\"Loaded forces from {cache_file}\")\n",
+    "    except FileNotFoundError:\n",
+    "        f = utils.n_body_forces(particles, G, e * epsilon)\n",
+    "        if SAVE_FORCES:\n",
+    "            np.save(cache_file, f)\n",
+    "            logger.debug(f\"Saved forces to {cache_file}\")\n",
+    "    n_squared_forces.append(f)\n",
+    "\n",
+    "### Mesh based force computation\n",
+    "mesh_size_range = [10, 20, 50, 100, 150, 200]\n",
+    "mapping = utils.particle_to_cells_nn\n",
+    "\n",
+    "mesh_forces = []\n",
+    "for mesh_size in mesh_size_range:\n",
+    "    cache_file = CACHE_ROOT / f\"mesh_forces__n_{n_particles}__mesh_size_{mesh_size}__mapping_{mapping.__name__}.npy\"\n",
+    "    try:\n",
+    "        f = np.load(cache_file)\n",
+    "        logger.info(f\"Loaded forces from {cache_file}\")\n",
+    "    except FileNotFoundError:\n",
+    "        f = utils.mesh_forces_v2(particles, G, mesh_size, mapping)\n",
+    "        if SAVE_FORCES:\n",
+    "            np.save(cache_file, f)\n",
+    "            logger.debug(f\"Saved forces to {cache_file}\")\n",
+    "    mesh_forces.append(f)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## Compare the mesh computation with the direct summation\n",
+    "r = np.linalg.norm(particles[:,:3], axis=1)\n",
+    "\n",
+    "plt.figure()\n",
+    "plt.title('Radial force')\n",
+    "plt.xscale('log')\n",
+    "plt.yscale('log')\n",
+    "plt.xlabel('$r$')\n",
+    "plt.ylabel('$F_r(r)$')\n",
+    "\n",
+    "# many of the particles have the same distance from the origin, so we skip some of them\n",
+    "SKIP_N = 20\n",
+    "\n",
+    "for f,e in zip(n_squared_forces, epsilon_range):\n",
+    "    plt.plot(r[::SKIP_N], np.linalg.norm(f, axis=1)[::SKIP_N], 'o', label=f\"$N^2$ - {e:.1g} * $\\\\epsilon$\", alpha=0.3)\n",
+    "for f, s in zip(mesh_forces, mesh_size_range):\n",
+    "    plt.plot(r[::SKIP_N], np.linalg.norm(f, axis=1)[::SKIP_N], 'x', label=f\"Mesh - N={s}\")\n",
+    "\n",
+    "# plt.ylim([5e-4, 1e2])\n",
+    "plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left')\n",
+    "plt.show()\n",
+    "\n",
+    "\n",
+    "# TODO: compare computation time\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Discussion\n",
+    "- Using the baseline of $N^2 + 1 \\varepsilon$ softening we can see that already a 20 x 20 x 20 grid provides good accuracy but the mapping breaks down at small distances (dip)\n",
+    "- Larger grids are more stable, especially at small distances => 50 x 50 x 50 already seems to be a good choice\n",
+    "- very large grids show overdiscretization => noisy data even for the non-noisy particle distributions\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Time integration"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import scipy.integrate as spi"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# load the particles in the format [x, y, z, vx, vy, vz, mass]\n",
+    "p0 = points[:, [2, 3, 4, 5, 6, 7, 1]]\n",
+    "\n",
+    "logger.info(f\"Considering {p0.shape[0]} particles\")\n",
+    "logger.info(f\"Total mass: {np.sum(p0[:,6])}\")\n",
+    "\n",
+    "if logger.level <= logging.DEBUG:\n",
+    "    # assert that the ODE reshaping is consistent\n",
+    "    y0, _ = utils.ode_setup(p0, None)\n",
+    "    logger.debug(y0[0:7])\n",
+    "    p0_reconstructed = utils.to_particles(y0)\n",
+    "    logger.debug(f\"{p0[0]} -> {p0_reconstructed[0]}\")\n",
+    "    logger.debug(f\"{p0[1]} -> {p0_reconstructed[1]}\")\n",
+    "\n",
+    "    assert np.allclose(p0, p0_reconstructed)\n",
+    "    logger.debug(\"Consistency check passed\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def integrate(method: str, force_function: callable, p0: np.ndarray, t_range: np.ndarray) -> np.ndarray:\n",
+    "    \"\"\"\n",
+    "    Integrate the gravitational movement of the particles, using the specified method\n",
+    "    - method: the integration method to use (\"scipy\" or \"rk4\")\n",
+    "    - force_function: the function that computes the forces acting on the particles\n",
+    "    - p0: the initial conditions of the particles (n, 7) array, unflattened\n",
+    "    - t_range: the time range to integrate over\n",
+    "    Returns: the integrated positions and velocities of the particles in a 'flattened' array (time_steps, nx7)\n",
+    "    \"\"\"\n",
+    "    y0, y_prime = utils.ode_setup(p0, force_function)\n",
+    "    \n",
+    "    if method == \"scipy\":\n",
+    "        sol = spi.odeint(y_prime, y0, t_range, rtol=1e-2)\n",
+    "    elif method == \"rk4\":\n",
+    "        sol = np.zeros((t_range.shape[0], y0.shape[0]))\n",
+    "        sol[0] = y0\n",
+    "        dt = t_range[1] - t_range[0]\n",
+    "        for i in range(1, t_range.shape[0]):\n",
+    "            t = t_range[i]\n",
+    "            sol[i,...] = utils.runge_kutta_4(sol[i-1], t, y_prime, dt)\n",
+    "\n",
+    "\n",
+    "    logger.info(f\"Integration done, shape: {sol.shape}\")\n",
+    "    return sol\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Determine the integration timesteps\n",
+    "# let's first compute the crossing time\n",
+    "v = np.linalg.norm(particles[:, 3:6], axis=1)\n",
+    "v_mean = np.mean(v)\n",
+    "# a timestep should result in a small displacement, wrt. to the mean interparticle distance\n",
+    "r_inter = utils.mean_interparticle_distance(particles)\n",
+    "\n",
+    "dt = r_inter / v_mean * 1e-3\n",
+    "logger.info(f\"Mean velocity: {v_mean}, timestep: {dt}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## Integration setup - use the n_squared forces for a few timesteps only, to see if the orbits are stable\n",
+    "n_steps = 20\n",
+    "t_range = np.arange(0, n_steps*dt, dt)\n",
+    "\n",
+    "# The force function can be interchanged\n",
+    "epsilon = utils.mean_interparticle_distance(particles)\n",
+    "epsilon = 0.01\n",
+    "force_function = lambda x: utils.n_body_forces(x, G, epsilon)\n",
+    "# force_function = lambda x: utils.n_body_forces_basic(x, G, epsilon)\n",
+    "# force_function = lambda x: utils.analytical_forces(x)\n",
+    "sol = integrate(\"rk4\", force_function, p0, t_range)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1800x1200 with 10 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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ahkAgwN9//43CwkIAQExMDPFVJKiUOX/dp/cPTe8st+sqrNCkgYEB2rdvL9Onp6cHU1NTun/KlCkICQmBiYkJDA0NMWfOHPj7+6NzZ9EH7NevH1xdXTFu3Dj8/PPPSEtLw+LFixEcHAwOh6OoqROaEQUl5Qh/LNL2dXMygxaL5JFsylAUhd+viPJaAACHzcQf4zuhu1PT0sg9fPgQ/v7+KC4uhr6+Pg4cOIDhw4cjIyNDob6Ky5cvl+8HITQp3heU4tQDkUmfwQD8WpnK7doqrZq9fv16MJlMDB06FCUlJQgMDMTvv/9OH2exWDh16hRmzZoFf39/6OnpYcKECVixYoUKZ01oSlx4ko6iMgEAEsXU1BEKKaw8/Ri7byYDAHS0WNg5oRO6tDFT7cQUgLOzM2JiYsDn83HkyBHMnDlT4fdctGgRQkJC6HZubi4JviDI4LVS4oh+/3995XptpQozV65ckWlzuVxs2bIFW7ZsqfYce3t7nDlzRsEzIzRXxFFMANCD+Ms0WUrLRVl9xSZFXW0Wdk/0keuboTqhra2NNm3aAAC8vb0RGRmJq1evwsLCgvZVlNbOfOirePv2bZnr1dVXkWjMCdVx68U7en+whw2MdLXlen2iUyc0W94XlOLa00wAQIeWPFgYKDfqjqAc8kvKMWXPHVqQ0eewsW+Kb5MVZKpCKBSliff09CS+ik0UiqIQ9igN7/JLVD2VKhm14xa9v3GUp9yvr1IzE4GgSs48eotyoaiwGTExNU3e5ZdgUugdPHgtSs5lwGVj72RfeNk13ZIVixYtwoABA2BnZ4e8vDwcPHgQN27cAADweDziq9hE+frwAxy99xp+jiY4NMNf1dOR4ZdzkpIFv432AoPBkPs9iDBDaLZIm5h6kfwyTY5X2YUYv+s2krIKAAA8HS3sn+IH95Y8Fc9MsWRkZGD8+PF4+/YteDweOnTogGPHjuHTTz8FQHwVmypH770GAEQlZat4JrIUlwmw5fJzuj3IQzF5nIgwQ2iWpOYU4U6y6Etvpq+NDi2a9g9cc+PJ21xM2HUbGXkilbuxrhb2T/WDm03T/zvv3LmzUp90mDTxVWx65BWX0fs/fNq+hpHKJ3DDNXr/+oJeCrsPEWYIzZJTD1JBiSxM6OFkASZT/mpPgmqIevEOU/feRV6xKP2+qZ42Dkzzg4sVSZ5JaJpsvJBI74/yUZ/iqInpeXj5TpTjyKMlT6GlYogwQ2iWyJqYSBRTUyHsURq+/Ps+SstFDq/mBhwcnOqHtpaNK2JHIKgzf95IovdZavRi1ne9RCtzZFYXhd6LRDMRmh3PMvIRlypSu7OYDHRrW1mYWb16NXx8fGBgYAALCwsMGTIEiYmJMmNIwT714mBUCr44EE0LMpaGHPw9vTMRZAhNGmFFEAMAjOykPnl9Dkal0PuLBrgoPCEpEWYIzQ5xiC4AdLI3Bk9Hq9KYq1evIjg4GLdu3UJ4eDjKyspoB0oxpGCfekBRFDZdTMR3xx9C/Fy34XFxaLo/Wpvrq3ZyBIKCOVVRJBcAvukvnzpHjUUgpPDd8Yd0e0aP1gq/JzEzEZoVFEXhP6mKrdVFMYWFhcm0Q0NDYWEhGSsu2Hfw4EH07t0bALB79260a9cOt27dQufOnemCfRcuXIClpSU8PT2xcuVKfPvtt1i2bBm0teWbNKo5IhBSWH4yDnsjX9J9LY118Ne0zgq1zxMI6sL3xyRCg5m+eoTOT9wtSbr43+yPlHJPopkhNCsevOYjucIhDQB61zEkm8/ny7Sjo6MVUrCvrsX6ygVCPHrDl1ExNzdKygX48q/7MoKMnYkuDs3wJ4IModmQVyIyW7taq4eDe3puMa4nZgEQpUPo0NJIKfclwgyhWSFtYmphpIO2FrWbIYRCIebOnUsnFQNEBfcUUbBv9erV4PF49FZdbZtNl57h499uoNV3Z5Clphk/FUlecRkm7b6D01IqdkczPfwzwx8tjHRUODMCQXkkpOXR+yuHuKlwJhL8fpRkl765sLfS7kuEGUKzQSCkcFJKmOntYlGnTJTBwcF49OgRdu3apcjpARBlb+Xz+fT26tWrKsdJv4V1WnUBMa9yFD43dSEzrwSjdtxCxHNJrZfW5no4NL0zrHikJAWh+bD8pETD21ENslpfipcEQHze2Q76HOV5shBhhtBsiHrxjk6iBtQtJHv27Nk4deoULl++jBYtWtD9VlZWdME+aT4s2PdhdFNtBfs4HA4MDQ1ltqro394K3w9sR7eHbLmJv2+nVDm2KfHyXQGGbYugo9EAwNnSAH9P94eFIRFkCM0LaYFeESUC6svk0Lv0/qoh7kq9NxFmCM0G6dwyHDYT/q3Mqh1LURRmz56N48eP49KlS3B0dJQ57u3trfKCfdO6t8LBaX50e+Gxh5j/T2yjr6uuPHrDx9CtkXQSLgBoZ22Ig9P8YG6gHo6PBIKy4BdKsv6u+ET1JqbFJySOyLsmdlL6/YkwQ2gWlJQLcPaRxL+iS2tT6Gizqh0fHByM/fv34+DBgzAwMEBaWpqMlkW6YN/ly5cRHR2NSZMmVVuwLzY2FufOnZN7wb4urc1k7NJH771Gp1XhTc4xOOJ5FkbtuCXjH9S+hSH+muYHUzWJ4CAQlMnvV5/R+yNUnF8mr7gM+29JNMO9XSxrGK0YiDBDaBZcTchEbrEkWV1thSW3bt0KPp+Pnj17wtraGtbW1nBycpIZs379enz88ccYOnQounfvDisrKxw7dow+Li7Yx2Kx4O/vj88//xzjx4+Xe8G+FkY6iF/Zn25n5Zei1XdnUFDSNJLznXn4FhN33UG+1OfxsDXCgamdYaRLwtsJzZPtV1/Q+1yt6l/MlEHXny7T+1Hf9VHJHEieGUKz4F8px18A6OVcszBDUZU1G7m5ueDxJIUK1algH1eLhaTVA9Fz7RXaDOO29Bwuf90TjmZ6Cr+/oth36yWW/PsI0n+OjnZGCJ3sC0Nu5WSHBEJzoEwgpPeHebdU4UyAB69zwC8Smby6tTWDpYp814hmhtDkyS8px4XHEhNRWwv9JpmHhMFg4Oo3vfB5Z0mhuV5rr8hEGGgKFEVhXfhT/O+ErCDj62CCvVP8iCBDaNaEPZKkdgjp61TDSMUzePNNej90kq/K5kGEGUKTJ/xxGkrKJW8ytZmYNJ1VQ9yxboQH3Z4cehfrw5+qcEb1QyCk8P2JR9h0UbYWln8rU4RO9lFquCeBoI4sPvGI3rdRYV6l7Vef0/s/fNpepUUuiTBDaPJIRzEBtZuYmgKfdWyJU3O60u2NFxMxYltkleYzdaK4TIDgA/dkitQBIvX1rok+0NUmggyheUNRFG3WcVZhEdUygRCrz8bT7bF+9iqbC0CEGUIT511+CZ1aGwAMOGx0clB9cill0L4FD9GLJeUWbidnw3HRGRSXCVQ4q+rJLS7DhF23ERYnmx25p7M5/hjfqcboMwKhuSCdY2nJoManeGgow7ZG0Pvn53VX2TzEEGGG0KQ58ygNAqkw5W5OZgovRa9OmOpzkLCqv0yfy//CkMYvVtGMqiYjtxgjt99CVFK2TH9AOwtsH+et8mgNAkFd+ClMog3p3MpUJXN4lV2I2NeienW2JjpwUqGGSEzzeaoTmiXSFbKB5mFi+hAOWxTp1LmVCd3XefVFRL/MruEs5ZGUVYDPtkbgyVvZopqBbpb4faw3OGwiyBAIYqQ1zaryUen2syQUO3xeD5XM4UOIMENosrx+X4g7ye9l+no2Q2EGEEU6/T3dH1/1aUv3Dd0aiQNRL2s4S/E8eJ2DYVsj8Pp9kUx/kLs1No/pCG02eUQRCGIy8iQa1f99rBoTk3R9u1k9W6uN1pQ8KQhNlpOxb2XaHi15zT7t/by+TvhjvCTV+PfHH2HeoRiVOAZfT8zE6B238K6gVKb/E08bbBzl2azMgQRCXdgTkUzvqyK/DEVRmPPXfbr9bX8Xpc+hOsjTgtBk+e+DRHnNVSvzIX1dLXEhROKwd/z+G3RefREl5cpzDP4vNhWTQ++goFT2nkM7tsS6EZ5gE0GGQKjElsuSUGiejvJzLX31dwy9/9e0zkq/f02QJwahSfI0Pa+SD0bvJp5fpj60sTDAvf/1pdvpuSVwXhwmU/tIUey+mYQv/7qPMoGsNmiUjy1+GdZBpbkqCAR1pbBUUs7jU68WSr//+4JSmRdE/9aqcT6uDoUKM1u3bkWHDh1gaGgIQ0ND+Pv74+zZs/Tx4uJiBAcHw9TUFPr6+hg6dKhMMT8ASElJQVBQEHR1dWFhYYFvvvkG5eVNo+YMQXH8V5FbRq8inNdMXxvuLXg1ndLsMNHTRsKq/jCTKtTYadUFPE7NreGshkNRFH45F4/lJx8DgIw/zOed7fDjp+5gEkGGQKiScKks5rN6tlb6/TuuCqf3pV+E1AWFCjMtW7bEmjVrEB0djbt376J379745JNPEBcXBwCYN28eTp48icOHD+Pq1atITU3FZ599Rp8vEAgQFBSE0tJSREREYM+ePQgNDcWSJUsUOW2ChkNRFP0GYVCR9r6HkwX5oawCDpuFO9/3wSAPG7pv4KbrOPPwbQ1n1Z9ygRALjz6k1eQWBhyUVmRlntjFASs/aU/+PgRCDayoeAkARCVZlEnUi3d0WZEgd2uY6KlfgVeFCjODBg3CwIED0bZtWzg5OeGHH36Avr4+bt26BT6fj507d2LdunXo3bs3vL29sXv3bkRERODWrVsAgPPnz+Px48fYv38/PD09MWDAAKxcuRJbtmxBaWlptfctKSlBbm6uzEZoPsS8ykFKdiF0tVm0yYKYmKqHwWDgt9FeWCIVHfHFgXtYffaJXByDi8sEmLn/Hg7dfQUmQ5S1NCNPZM6a1s0RSwe5gsEgggyBUB0CIUU7yrc211P692Xkjlv0/uYxXkq9d11Rms+MQCDA33//jYKCAvj7+yM6OhplZWUICJBkKHVxcYGdnR0iIyMBAJGRkXB3d4elpSU9JjAwELm5ubR2pypWr14NHo9Hb7a2tor7YAS1Q1y+wMXKAG9yisBiMtDNyUzFs1J/Jnd1xP4pfnR7+9UXGLo1gtagNAR+YRnG7YzChSfp0GYz0dHOGAnpeQBEqvLvBrYjggyBUAsxryQpJhYOaKfUe/96PoHe3zjKU22/rwoXZh4+fAh9fX1wOBzMnDkTx48fh6urK9LS0qCtrQ0jIyOZ8ZaWlkhLE6UzT0tLkxFkxMfFx6pj0aJF4PP59Pbq1Sv5fiiC2lIuEOLUA5GJRGxi6mRvTKos15Gubc1wcb4kCda9lBw4LT6L7ILqNaHVkcYvxojtkbiT/B4GXDa6tDbF3Zeih/KXfdpiQaCz2j4YCQR14rdLz+j9bm2V92JWXCaQufcnnsp3PK4rChdmnJ2dERMTg6ioKMyaNQsTJkzA48ePaz+xEXA4HNrpWLwRmge3XmQjK78ExrpaKBOINArExFQ/WpvrV3Lw67gyHIkVGpW68CwjH0O3RiAhPQ8WBhx0a2uGKwmZAICQvk4I6etEBBkCoY6IvzsAlJqkbsDG6/T+1W96Ku2+DUHhwoy2tjbatGkDb29vrF69Gh4eHti4cSOsrKxQWlqKnJwcmfHp6emwsrICAFhZWVWKbhK3xWMIBGn+rShf0MvZgtYCEGGm/pjoaSN+ZX+0s5a8CPRdfw2XEzJqPTfmVQ6Gb4vAm5wiOJrp4aM2ZjjzUKRJ/ba/C76UykJMIBBqJjmrgN5XZpK6Zxl5SKq4t5uNIexN9ZR274ag9DwzQqEQJSUl8Pb2hpaWFi5evEgfS0hIQEpKCvz9/QEA/v7+ePjwITIyJA/Q8PBwGBoawtVVddVCCepJcZkAYY9EP5rmFdEyLY110EbJnv9NBa4WC6fndMVYPzu6b9LuO9h29Xm1jsH8IlHl6/eFZejQkgcfB2Mcvy8SMBcHtVNJSCmBoMkciX5N7w/2tKlhpHwJWHeN3j/+xUdKu29DYSvy4osWLcKAAQNgZ2eHvLw8HDx4EFeuXMG5c+fA4/EwZcoUhISEwMTEBIaGhpgzZw78/f3RubMos2C/fv3g6uqKcePG4eeff0ZaWhoWL16M4OBgcDjNOy09oTJXEjKRV1IOGx4XucWiXES9nC2IOaMRMJkM/PCpO9q34GHRsYcAgDVn4xGTkoPfxnhVKjlwIOol+EVlaG2uBzcbQ/x1W+SvtmyQKyZ+5Kj0+RMIms7myxKflRZGOkq559+3U+j9Bf2dNaJGmkKFmYyMDIwfPx5v374Fj8dDhw4dcO7cOfTtK7LHr1+/HkwmE0OHDkVJSQkCAwPx+++/0+ezWCycOnUKs2bNgr+/P/T09DBhwgSsWLFCkdMmaCj/xYo0AIM8bOhiaMTEJB9G+9rB3lQXY/6IAgCExaWh60+XcG5udxjpinJOFJcJsPtmMgAgI7eEFmRWDWmPzzvbq2TeBIImk1Mocbwf7KEcrYxQSGFhxYsLAHzRs41S7ttYFCpu7dy5E8nJySgpKUFGRgYuXLhACzIAwOVysWXLFmRnZ6OgoADHjh2r5Atjb2+PM2fOoLCwEJmZmVi7di3YbIXKYAQNJK+4DBeeiMyRzlYGSOUXg8NmqkXK7S1btsDBwQFcLhd+fn64ffu2qqfUILq0NsOFEEmkU3puCTxXhONFZj4A4MT9N8isyB+TV1IOBgP4aag7EWQIhAYinfV3vL9yvkeT99yh908Eq795SYz6644IhDpwLi4dpeVCtLHQR1puMQCgS2tTlZenP3ToEEJCQrB06VLcu3cPHh4eCAwMlPED0yTaWOgjenEA9DmSF4rev17F7aRsbLsqKYLHZABrh3lgpI9dVZchEAh14OdzkhwvXnbGCr9fRm4xHTmlz2HD09ZI4feUF0SYITQJxOULBnvY4Eq86MuoDiamdevWYdq0aZg0aRJcXV2xbds26OrqYteuXaqeWoMx1efg7uIA+LeSaL1GbI9E8rtCur1+pCeGerdUxfQIhCZBSbmA1nQ6mOoqpQCr74+SgJyIRb0Vfj95Quw1BI0nM68EN59lAQB6OJlj48VEAEBPZ9UKM6WlpYiOjsaiRYvoPiaTiYCAADrL9YeUlJSgpERSuVpdS3FwtVg4MNUPq04/wa6bSZWOH4xKwYGoCidCCqAgin4SB0GJY6HEUVGU1DEmA5jQxUGtE3QRCIom6kU2vT83wEnh95NOuzDa11bjEo0SzQxB4znz8C0EQgoetkZ4mV0IgZBCWwt92JroqnReWVlZEAgEVWaxri6DtSaV4mAyGVgyyBWfVBEuGpWUjdviLTkbd5Lf407ye9x9KdqiK7Z7KTm4l5KD+yk5iHkl2u6l5GDXjcoCEqFurF69Gj4+PjAwMICFhQWGDBmCxMREmTHFxcUIDg6Gqakp9PX1MXTo0Eo5vVJSUhAUFARdXV1YWFjgm2++QXl5uTI/SrNmb2Qyvd/T2Vzh95u0W+Ir8+On7gq/n7whmhmCxiNOlPeJhw2uxIveLtTBxNQQFi1ahJCQELqdm5ur1gINAGwc5UXXwxLTykwPIf2cwAAD4sh4BgBJlLxoR/YYA9cTM7E38iV4uupXlVdTuHr1KoKDg+Hj44Py8nJ89913+PTTT2XGzJs3D6dPn8bhw4fB4/Ewe/ZsfPbZZ7h58yYAUS29oKAgWFlZISIiAm/fvsX48eOhpaWFH3/8URUfq1lBURQd0ACAjhhUFEv/fUTv/zm+k0amsyDCDEGjeZVdiHspOWAygIHu1nROhl5qIMyYmZmBxWJVmcW6ugzWHA5HI3Mohc/rjr7rJUm2XmQV4GRsKn4e6gGebt3V1U8rSiZYGGje/4G6EBYWJtMODQ2FhYXk+8Dn87Fz504cPHgQvXuL/CJ2796Ndu3a4datW+jcuTPOnz+Px48f48KFC7C0tISnpydWrlyJb7/9FsuWLYO2tnoJmzcSszD/cAzWfNZBLb77jeXxW4l5+SsFZ8wuKCnHnsiXdDvA1bKG0eoLMTMRNBqx469/a1Ok8ouQXVAKAy4b3vaK9/yvDW1tbXh7e8tkuRYKhbh48SKd5bqp0NbSoJKD4rm4dAzcdB3RL99Xc1ZlxA6PRJiRH3w+X6YdHR2NsrIyBAQE0H0uLi6ws7OjfbkiIyPh7u4uYyINDAxEbm4u4uLiqrxPSUkJcnNzZTZlEfs6B+m5JTh0p2kUFT4Z+5beH+Cu2NI93X++TO/fWtRHofdSJM1amCkXCOkcGQTN5L8K88YnHi1wucLE1L2teaXMtKoiJCQEf/zxB/bs2YMnT55g1qxZKCgowKRJk1Q9NblzSaratpg3OUUYsT0SW688h1BYdQkEaTLyRGH1RJiRD0KhEHPnzqWzqgNAWloatLW1YWRkJDNW2pcrLS2tSl8v8bGqUKW/V2tzUcmSuy+zqy21oUlIpzlwtjRQ2H0eveHjXYEoMd9HbUxhxeMq7F6KRj2e+Cpizdl49P71Kpb9F1enBy1BvYhPy0VCeh60WUwEtreivfHVSc08cuRIrF27FkuWLIGnpydiYmIQFhZW6YeiKWBvqodPvSpHIAmEFH4Ki8fE0DvIyi+p4kwJYs2MuYHmPlTVieDgYDx69EgpqQAWLVoEPp9Pb69eKU9L4mQpEmay8ktlUgRoIm/5RfR+fzcrhfqvfPzbDXp/72Q/hd1HGTRrYaZDRUKg0IhkfHPkAcoFQtVOiFAvxFqZns7mKCkT4NGbXLqtTsyePRsvX75ESUkJoqKi4Oen2Q+NmviihkKS155mYsDG63QYfVVkiM1MhkQz01hmz56NU6dO4fLly2jRQiJkWllZobS0FDk5OTLjpX25rKysqvT1Eh+rCg6HA0NDQ5lNWdiZ6EK7Qht7Nzm7ltHqjbTj7/BOisvV9Of1F/T+yiHtlZLHRpE0a2FmsIcN5vcVxe8fvfcawQfvoaRcoOJZEeoCRVF0BM0nni1orYxHSx7M9MkPoapoa2mAAe2rt/Fn5pXg851RWHsuodLLA0VRyMglPjONhaIozJ49G8ePH8elS5fg6Chb4NPb2xtaWloyvlwJCQlISUmhfbn8/f3x8OFDmUzV4eHhMDQ0hKurq3I+SD1gs5hoZa4HALibXHcfLXXkd6nCkl1amynkHuUCIVadfkK3xzWBkiPNWpgBgNm922ByRTXfc3HpmLrnLgpLSS4Fdedeynu8ySmCnjYLfdpZ4HJF1l91MjE1V4J7VV+YjqvFBEWJKgGP/uOWjEq9oFSAojLRy4Q5EWYaTHBwMPbv34+DBw/CwMAAaWlpMloWHo+HKVOmICQkBJcvX0Z0dDQmTZoEf39/2remX79+cHV1xbhx4xAbG4tz585h8eLFCA4OVttouzYWIlPTnZeaq5nJLynHW77Ib8zWRAc62oopxzJiuyRp57m53RVyD2XT7IUZBoOBxUHtMLSjSJ13PTELn/8ZBX5hmYpnRqgJsYkp0M0KTAYDNypMF5qaX6Yp0b4Fr9q/Q3GZEAPaW0Gfw8ad5PcYsPE6LlQU08uoqKmlz2FDV5tkjWgoW7duBZ/PR8+ePWFtbQ1ra2s4OclmkF2/fj0+/vhjDB06FN27d4eVlRWOHTtGH2exWDh16hRYLBb8/f3x+eefY/z48VixYoWyP06daWshcpR9kVmAd7X4Zqkr159m0vvTu7VSyD3E6SwAoIWRDpytFOdgrEyavTADiDKZ/jTUHQHtRE6Z91JyMHJHJO2MSFAvygVCnHogCl0c7GmDO8nZyC8ph5k+B+1teCqeHQGQ1c5w2LKPmbOP0jCvrxM6tOQhp7AMU/fexYqTj/EmR6SlISamxkFRVKXtw/BsLpeLLVu2IDs7GwUFBTh27FglXxh7e3ucOXMGhYWFyMzMxNq1a8Fmq6+QKXYCBlCvdADqxJHo1/S+orTM3aRCsS+EVI5A1FSIMFMBm8XE5jFe8HM0AQDEp+VhxPZI+gFLUB9uPn+HdwWlMNXTxkdtzOiQ7J7O5mBquBNbU8Hb3hgftREVonSzMYQWS/bvsvLUY8wNaIspXUUm3l03kzD74H0AxMREaBhtpYSZuxoozJQLhLgYL/FRamks/3IsZx5K8tfM6NFKYWYsVUCEGSm4Wiz8MaET3GxEXvhJWQUYvjUCz0kuGrVCbGIa6G4NLRYTlxI0u4RBU0WsnXmUmouJXRwqHZ8cehd9XS2xc0InGOlqgV8kMu0SYYbQEOxN9cCueJnRxIgmsekHAKZ2dax+YAOhKApfHLhHtxcNaCf3e6gSIsx8gCFXC3sm+6KVmcgzPpVfjBHbIhGXyq/lTIIyKC4T4FycKGnXJ542ePmuAC8yC8BmMtC1rWI8/wkNw7+VKbztjVFaLoSQAro7VQ6ZH7XjFox0tXH2q27wdRBpRdtZKy+kl9B00GIx4Vjx3H74ho/iMs2KTBU/1wCgrwJKCoT8E0vvH5zW9NJDEGGmCsz0Odg7xRfWFdkQ3xWUYtSOWxop7Tc1LsVnIL+kHC2MdNDRzpg2MXVyMNa4kvVNHQaDgdm9RdqZg1EpWBzUDmb6lWv6DN0agXf5pfhremecmtMVM7orxvGR0PQRm5rKBBQevNasF9CdUpXi5V2OJaewFMfvv6Hbigr5ViVEmKmGlsa62DfFF8YVRfLyissxbudtXJPyNicoH3GF7MGeNmAyGbiUIPp7EBOTetLTyRztWxiiqEyAk7GpWDvcgz4m7Ufz8W838CwjH+1b8MBWk1IUBM1DHNEEAHc06OVT2pWht4uF3L8DnVZdoPfv/a+vXK+tLpCnRg20sTBA6CRf6FU4SRWVCTBlzx2clXKiIigPflEZLlcIL4M9bFBYWo5bL94BIMKMusJgMDC7l6jqb+jNZHjZGdP+M20sDNBLKltz4IZrxD+N0ChknIA1SJgRpycAgEEe1nK99p3kbJRXlOsZ0N4KJnrqVfFcXhBhphY8bI2wY3wnOlV2mYBC8MF7+Odu06jOqkmci0tDabkQTpb6cLEywM1n71BaLkRLYx260BxB/ejnagknS33klZRjX2Qy3d/O2gA7xneCfytTuq/Pr1eRouG1dQiqQ1ozE/3yvcbU3Nsb+ZLe7+Ek3xez4dskCfJ+H9tRrtdWJ4gwUwc+amOGTaO9II76FVLAgiMPsEvKxklQPP9JlS9gMBh0CYPeLhYKLcZGaBxMJoOObNp5I4kODw2qiEbbM9kXXnZG9Pjuv1xGKkmJQGgADma6dI2h3OJyJGaov6bvXX4JnQLEmseVq+ZkXfhTen/DSM8m/Zwkwkwd6d/eCms+6yDTt+LUY2y48LRJlJxXdzLyihHxXJTld1AHG1AURTv/khIG6k+QuzUcTHXxvrAMGXklMOCw6egzbTYTf0/vLBPF1GXNJTojMIFQVzhsFhxMJflZNMFv5pJUbpmxfnZyu25xmQCbLibS7SFVVLRvShBhph6M8LHFdwNdZPo2XEjEylNPNEadqamcfvAWQgrwsjOCnaku4tPy8JZfDK4WU8ZMQVBP2CwmvugpyQrc19USHLYkYReHzcLxL7rQobUA4PvjRY1NS09QHR+amtSd01I+mPJ8MRu46Tq9f+XrnnK7rrpChJl6Mr17a8zq2Vqmb9fNJHx79EGlKsAE+UFXyPawAQDaxNSltRm4Wk0ni2VTZohXC7Qw0gEADPK0qXScq8XC6S+7wsqQS/f5/HCB1Ekj1AtpJ2B118wUlwlwJUESIesqpxxLzzLy8SKzAIAob5OD1EtCU4UIMw1gQaAzRvvKqgMPR7/GnL/uo6RcsxI1aQIv3xUg5lUOmAwgqEOFMENMTBqHNpuJfVN88fvYjuhZRQI9ANDVZuPC/B7g6YhSIggpoMuai8grJgINoW6Iq2cDwOv3RUjjq6+5MvL5O3p/tK+t3HxaAtZdpff/Df5ILtdUdxQqzKxevRo+Pj4wMDCAhYUFhgwZgoSEBJkxxcXFCA4OhqmpKfT19TF06FCZcvUAkJKSgqCgIOjq6sLCwgLffPMNysvLFTn1GmEwGFg1pD2C3GVD6M4+SsPUPXdRWKq6uTVFTsaKtDIftTGDuQEHOYWltPpYOrSXoP60MtfHQHfrGh/a+hw2ri3oRReoLCgVoNfaq+R7RagT0mYmALj7Un21M+elQrJ7u8gn6+8/dySRtt8EOkOb3Tx0Fgr9lFevXkVwcDBu3bqF8PBwlJWVoV+/figoKKDHzJs3DydPnsThw4dx9epVpKam4rPPPqOPCwQCBAUFobS0FBEREdizZw9CQ0OxZMkSRU69VlhMBtaN9EC3D1LoX0/Mwvidt+k6M4TGQVEUTlSYmAZXmJiuJWZBSImq5CqiGBtB9fB0tBD1XR+6nZVfgsAN1zQuRT1B+bQy14N0vdm7yerpNyMUUvjrdgrdFhdmbew1Fxx9QLelq9c3dRQqzISFhWHixIlwc3ODh4cHQkNDkZKSgujoaAAAn8/Hzp07sW7dOvTu3Rve3t7YvXs3IiIicOvWLQDA+fPn8fjxY+zfvx+enp4YMGAAVq5ciS1btqC0tFSR068VDpuFbZ97w9PWSKb/7sv3GL3jFrKI82KjefI2D88y8qHNZiKwvRUAYmJqLhjpaiN6cQDdfpVdhE8230RpOfFNI1QPV4sFe1OJj4i6amYeSdX769zKBLra7EZfc+reu/T+sS+6NPp6moRS9U98vuiPZ2IiKigXHR2NsrIyBARIHlguLi6ws7NDZKQo0U9kZCTc3d1haSlRwQUGBiI3NxdxcXFV3qekpAS5ubkym6LQ47Cxe6IP2lrIJm17/DYXI7ZFknwZjeTfWFH5gt7OFjDkakEgpHClwvm3lzMRZpo6pvoc3P5eoqFJSM/DiO2RxNmeUCPSfjOPU3ORX6J+JkrprL/93awafb2MvGI6zFtXm4WOdvKt76TuKE2YEQqFmDt3Lj766CO0b98eAJCWlgZtbW0YGRnJjLW0tERaWho9RlqQER8XH6uK1atXg8fj0Zutra2cP40sxnra2DfFDy2NRZEaOlosGHDZeJFVgOHbIvGCpGhvEEIhhVOxorDFTyqiX2Jf5+B9YRkMuGy5F2MjqCcWBlzcWiQRaGJe5WD8rtsQkHQIhGqQfrkUUsD9FPUzNR29Jyn8KA9/Gd8fLtL7t6RMtM0FpQkzwcHBePToEf7++2+F32vRokXg8/n09uqV4ksPWPG42DfFD2b62igqE4CnowUbHhdvcoowYnskHqcqTjvUVIlOeY83OUUw4LBpk5LYxNTdyRxaCipImJycjClTpsDR0RE6Ojpo3bo1li5dWsms+eDBA3Tr1g1cLhe2trb4+eefK13r8OHDcHFxAZfLhbu7O86cOaOQOTd1rHhc3FzYm25HPH+HGfuiSX4nDaS0XIj7Ke8VmmxUOjwbUD+/mdfvC+msv2b62rAzbZzv31WpAsgjO9nCkKvVqOtpIkoRZmbPno1Tp07h8uXLaNmyJd1vZWWF0tJS5OTkyIxPT0+HlZUVPebD6CZxWzzmQzgcDgwNDWU2ZeBopoc9k31hwGHj9fsimBty4WSpj6z8UozaEYloNbXdqiviCtn93KzoXDJiNWpvBZqY4uPjIRQKsX37dsTFxWH9+vXYtm0bli9fTo/Jzc1Fv379YG9vj+joaPzyyy9YtmwZduzYQY+JiIjA6NGjMWXKFNy/fx9DhgzBkCFD8OjRI4XNvSnTwkgH177pRbcvPEnHvH9iSAZuDWPfrZf49PcIOC5SnGCv7hFN0iamzzq2rGFk3Ziw6za9v2aoe6Ovp4koVJihKAqzZ8/G8ePHcenSJTg6Osoc9/b2hpaWFi5elKjHEhISkJKSAn9/fwCAv78/Hj58iIwMScrn8PBwGBoawtXVVZHTbxBuNjzsnOgDDpuJ2Fc5sDXWRUc7I+QWl+PzP2/jemJm7RchoEwgxJmHIjOi2MSUnluMuNRcMBhADwWGZPfv3x+7d+9Gv3790KpVKwwePBhff/01Tp48SY85cOAASktLsWvXLri5uWHUqFH48ssvsW7dOnrMxo0b0b9/f3zzzTdo164dVq5ciY4dO2Lz5s0Km3tTx85UF5elspn+G5OK744/JAKNBiGtTTt0J6WGkQ2ntbk+pKP/76fkqJWf1bk4iTDTWN+/Zf9JfEe3j/Nu0vWXakKhwkxwcDD279+PgwcPwsDAAGlpaUhLS0NRkUi9xuPxMGXKFISEhODy5cuIjo7GpEmT4O/vj86dOwMA+vXrB1dXV4wbNw6xsbE4d+4cFi9ejODgYHA4HEVOv8H4Oppg6+cdwWYycDE+A20tDNCtrRmKygSYEnoXYY+q9vUhSLjxLAvZBaUw09dGl9aikEWx42+HlkYw01fu357P58PYWOKjExkZie7du0NbW1IULjAwEAkJCXj//j09Rtq5XTxG7NxeFcp0XtdUHM30ED6vO93+6/YrrDr9RIUzItSHad1b0fvfHn2okOg0HW0WbKXSNhSWCvDkbZ7c79MQcovLEPlCkiyvk0PDff8KSsoRGpFMtwPl4EisqShUmNm6dSv4fD569uwJa2trejt06BA9Zv369fj4448xdOhQdO/eHVZWVjh27Bh9nMVi4dSpU2CxWPD398fnn3+O8ePHY8WKFYqceqPp7WKJtcM9AACH7r5Ch5Y8DGhvhVKBEF8ciMaR6NcqnqH8kefbsbhC9scdbMCu8I1RhompKp49e4bffvsNkyZNovvq4phe3ZjqHNcB5TuvayptLQ1w9qtudHvnjST8ej6hhjMI6sTpL7vS+4EbrinkHh9GmKpLaYOrUuULxJXjG0qPX67Q+5GLelc/sBmgcDNTVdvEiRPpMVwuF1u2bEF2djYKCgpw7NixSr4w9vb2OHPmDAoLC5GZmYm1a9eCzW58TL6iGeLVAssHuwEAtlx+Dh8HEwz3bgkhBXx9OBa7byapeIby4/X7QvivvoTNlxJrH1wLRaUCnIsT/eAPqkiUV1IuwI1EUdXsXi4NMzEtXLgQDAajxi0+Pl7mnDdv3qB///4YPny4zLpVFKpwXtdU2lkb4tQcyY/ib5eeYeuV5yqcEaGuuNnw6CrpSVmiciXypq2levrNXHgiZWJqRK6sR2/4dC4zP0cTWPN0Gj03TaZ55DlWIRO6OGBuQFsAwIpTj/FRGzNM/kjkO7T85GNsupjYJOz9D17zkZZbLGMLbigX49NRWCpAS2MddLQzAiCKRigoFcBMn4P2NrwGXXf+/Pl48uRJjVurVhIVeGpqKnr16oUuXbrIOPYCdXNMr25MdY7rgOqc1zWV9i14OCFVe+ansHiENqGXhKbMydmSv9uQLTfl/hwUa2ZYFemA7yYrNoKqLpQJhHTRXADo2Qjfv49/u0HvH5zWuVHzagoQYUYJfNWnLSZ2cQAg0sh0a2uGeQFOAIB14U/x45knKv+SNZbyCqe+nKLGZ2WmK2R72tDObGITUy9nczCZDXNwMzc3h4uLS42b2AfmzZs36NmzJ52VmsmU/ar4+/vj2rVrKCuTlK0IDw+Hs7Mz7Vvj7+8v49wuHiN2bifIB09bIxyZKfk/XXbyscIcSwnyg81iYsNIT7r93XH5RvmJw7N1tVjQYjGQkVeCV9mqTWIqberq0JLXYN+/nTckAvvywW60wNacIcKMEmAwGFjysSuGeNqgXEhh5v5odGljiiUfi6Kx/riehIVHH2p0EjBxhEJOYeNqUvELy2hH38EeLeh+ZZYwEAsydnZ2WLt2LTIzM5GWliajZRkzZgy0tbUxZcoUxMXF4dChQ9i4cSNCQkLoMV999RXCwsLw66+/Ij4+HsuWLcPdu3cxe/ZshX+G5kYnBxMcnOZHt789+pAO7SeoL0O8JN/xv26nIDNPfiVgWpuLhJm8knK6hpuqTU0XHkuicgPaNSxRXrlAiJWnHtPtCRUvys0dIswoCSaTgV+Ge6C3iwVKyoWYHHoHnVuZ4udhHcBkiJyEv/zrvsbWnRELYnnF5Y0KgTz76C3KBBRcrAzgbCWyeSdnFeBFVgHYTAa6flDYUxGEh4fj2bNnuHjxIlq2bEk7rjs5OdFjeDwezp8/j6SkJHh7e2P+/PlYsmQJpk+fTo/p0qULDh48iB07dsDDwwNHjhzBiRMn6AzYBPnSpbUZ9k72pdtf/R1DIgc1AOn6Wz4/XJDbdfU4bLQwEvmR8HRESeTuqDB5HkVROPPwLd3u3cAXs1E7btH70k7wzR0izCgRLRYTW8Z0hI+DMfKKyzF+1234Ophgy5iO0GIxcPrhW0zbexdFpZpXGVhaq5Rb3PA6KP/FVlTIrsgtAwCXKzQ1Pg4mSslsOXHixCod18W1xcR06NAB169fR3FxMV6/fo1vv/220rWGDx+OhIQElJSU4NGjRxg4cKDC59+c6e5kjj/Hd6LbM/dH05o+gnpiqs/BeH97un34rvyc3p0qTE1iYeauCiOaEjPykZZbDAAw4LDhZlN/f7jX7wtx96VIILMy5NJO1AQizCgdHW0W/pzgg3bWhsjKL8HnO6PgZWeMPyf4gKvFxNWnmRi/Kwq5xY0z1ygbgZTPT05hw/xm0nOL6fwLgzpIhBnaX6aBUUyE5kWAqyW2ju1ItyfuvoOI51kqnBGhNsRRnwDwzZEHctNQiyOaxMJMYkZ+g59PjSVcKuvvQHfrBiW36/rTZXr/0tc95DKvpgIRZlQAT0cLeyf7wsFUF6/fF2H8rih4tORh/xQ/GHDZuJP8HqN33MK7fPnZjxWNtGYmp6hhgtjJ2FRQFOBtbwxbE5GNu7C0HFEvRG9TDVXLEpofA9ytZZxLx/wRheiX6lWfhyCBwWDg5GxJmP3ATdflcl1x9ezsglK0MtcDAJWtA2lhpiG+f2elTFTTujlCV1v905MoEyLMqAhzAw72TfGDpSEHT9PzMXH3HbSzNsTf0zvDVE8bcam5GLE9Em/5qvW+ryvSwgy/gU7AJ2MlUUxibj57h1KBELYmOrRDH4FQF4Z4tcBPUnVqhm6NwMPX/BrOIKgS95Y82iz0LCMfD17nNPqa4vDsxIw8dLIXRRmqwm8mI69YJpdOfX3/KIrCrAP36Pb3QepXykfVEGFGhdia6GLfFD8Y6Woh5lUOZu6PRhsLffwz0x82PC6eZxZg2NZIJGUVqHqqtSKrmam/GjcpqwCxr/lgMRkY6G5N90tn/W2uNUcIDWekj52MCWPQ5htISFOPtPaEypyaI3FoHby58blnxJqZ9NwSOFWYnFRR8PfSE4nfVre2ZtDn1E+r8vXhB/T+/il+NYxsvhBhRsU4WRpg90Qf6GqzcD0xCyGHYuFgqofDs7rA0UwPb3KKMHxbJJ68Ve8aPUIZn5n6a2bE5Qs+amNG516gKIp23uxJTEyEBjKhiwMWDXCh24EbruF5Zr4KZ0SoDm02ky4DAwD/+7dxuWcMuFqw4XEBAEa6ohxSsa/4KC5TbpCFTNbfepZj4ReW4eg9SfkbZUR0aiJEmFEDvOyMsX2cNx3RtPjEQ9jwuPhnhj/tKDxyeyTupaivzb9c2HBhhqIo/BsrygnyiYfExBSfloe3/GJwtZjwb2Uqn4kSmiUzerSmM3EDQJ9fryLlXaEKZ0SojmHeLen9/bcan3umTYVGpkwghKmeNkoFQjx6ozxzY1GpABekNDP19f3z+VESrn53cUANI5s3RJhRE7q1NcfGUV5gMkRVgH8+lwBzAw7+ntYZHe2MkFtcjs//jKLrE6kbMj4z9XQAjkvNxYvMAnDYTPRzkySSEpuYPmptBq4WSz4TJTRb5gY4YUYPSbmK7r9cRmqOZvikNTduf9+H3m9s7hmx38yzjHy6QvVdJToB33gmeWa3MtODg5lenc+NfplNR3b1dbVscMbg5gARZtSIge7W+OFTkcPi1ivPsePac/B0tbB/qh+6tTVDYakAk0Pv4Hyc+iUCE0oJM8fvv8Hacwl1zmgszi0T0M4SBlJ5ZMRZf4mJiSAvFg1ohwlSOU26rLmEjIrcHwT1wcKAizF+dnT7aPTrGkbXjFiYeZqeBx8HEwDKzTdzoRFRTEO3RtL72z/3ltucmiJEmFEzRvva4dv+Ivv+j2fi8c/dV9DVZuPPCZ3Q380KpQIhZh24h2P3Gv7lVgTlH2hmNl9+VqdKuEIhRUcxDZIyMeUUltJmNRKSTZAnyz9pL2PK8P3xokalQWgu/DBEkil7/uFYlJQ3zM9FnGvmWUY+vCsimqJfvpd5AVMUQiEl4y9Tn2fZxguJ9P7a4R4NrknXXCDCjBoyq2drzOguUocvPPoAYY/SwGGzsHmMF4Z5t4RASCHkn1jsjUxW7USlEFYRdVCXxH93krPxll8MAy5bpoLs1aeZEFKAs6UBnZKcQJAXvwzrgIHukurl3qsuNDilgLpx7do1DBo0CDY2okKtJ06ckDlOURSWLFkCa2tr6OjoICAgAImJiTJjsrOzMXbsWBgaGsLIyAhTpkxBfr5ynaYZDAaOf9GFbn+y+WaDriOOaHrLL4aDqR64Wky8LyzDiyzFf56Y1zl4VyCK7uSwmbRmqDZKygVYf+Ep3ZYWvglVQ4QZNWXhABeM7GQLIQV8+dd9RDzLApvFxM9DO9AVuJf8G4ctl5+pRcXtqkxKdSnL8G+FVmZAeysZvxiJiYlk/SXIHwaDgS1jOsoI0B4rziNPwzJvV0VBQQE8PDywZcuWKo///PPP2LRpE7Zt24aoqCjo6ekhMDAQxcUSc9vYsWMRFxeH8PBwnDp1CteuXZOpO6YsvOyM6WR38Wl5Dco9w9PRgqWhyNck+V0BPG2NACgn34y0iam3iwW02XX7yR302w16/9J8kum3LhBhRk1hMBj44dP2CHSzRKlAiGl77yL2VQ6YTAaWDnLFl31EkRm/nEvAmrPxKhdoqhJmCmsRZkrLhXThNekK2QIhhatPMwGI8ssQCIqAwWBg90Qf+FQ4hQKA+7LzKCxteG0xdWDAgAFYtWoVPv3000rHKIrChg0bsHjxYnzyySfo0KED9u7di9TUVFqD8+TJE4SFheHPP/+En58funbtit9++w1///03UlNTlfxpgDNfNj73TFsLkakpMT0fnezFfjNKEGae1N9f5kVmPp6mi7RGTpb6aEWShdYJIsyoMWwWExtHeaFLa1MUlAowcfdtPMvIA4PBQEhfJywOagcA2H7tBb47/rDODreKoErNTC25HK4nZiKnsAxm+hz4t5aEXse8ysH7wjIYctm0jZtAUAQMBgOHpvvDVapgn+uSc0rPQ6IskpOTkZaWhoAASYgvj8eDn58fIiNFzqaRkZEwMjJCp06Sgp0BAQFgMpmIioqq9tolJSXIzc2V2eQBV4uFNZ9JMjkv+y+u3tdoI+UELIloUqwT8Mt3BbRQAkBGC1gTvX+9Su+fnNO1hpEEaYgwo+ZwtVjYMb4TPFry8L6wDON23sabinDSqd1a4aeh7nQ491d/35dbgbb6Iqjibamoljfc/2jHX2uwpJzbxCam7k7mYLPIEiUoFiaTgZNzusLBVJfua7ckTGXfJUWSkSH6bllaWsr0W1paIi1NFCWZlpYGCwtZLQKbzYaJiQk9pipWr14NHo9Hb7a2tnKb9yhfSWTTnsiX9c49074FDwBwK+kdOtobg8EAXr4rREae4iLZpGsxdWjJg4UBt9ZzjkhFbc3v6wQOm6SkqCvkl0ID0OewsXuSL9pY6OMtvxjj/oxCVkX0xUgfO/w2uiO0WAycevAWM/bdrZOvirypr5mpsLQc5+NEX/ZPPFvIHLtckfW3vpkyCYSGwmIycCGkB8wNxNmnAe+V4SgXND2BRlEsWrQIfD6f3l69eiXX699a1PDcMz2dzcFgAI/e5KKgpBzO4tIGCjQ11Tfrr1BI4evDsXR7Tp+2NYwmfAgRZjQEEz1t7JviixZGOniRVYCJu2/TzopBHazxx/hO4GoxcTkhExOkjimL+pqZwh+no6hMAHtTXXi05NH96bnFiEvNBYNRd7UsgSAP2CwmIhb2hp626G04r6QcXX+6rFLzrbwRa1zS09Nl+tPT02FlJYrusrKyojU4YsrLy5GdnU2PqQoOhwNDQ0OZTZ5Y8bgYLhXVU116CoqiKoVdm+lz4FXh+HvxSQYdVaQoJ+CcwlLceiExY9UlJHvG/mh6/+isLjWMJFQFEWY0CGueDvZN8YWpnjYevcnF1D13adt+T2cL7JviBwMOG7eTsjHmjyhkF9S/4GNDqSo0uyYNkbgW02APG5kCkmITk0dLI5iSbJcEJaPFYuL+kn50Oy23GIEbriklJ4kycHBwgJWVFS5evEj35ebmIioqCv7+/gAAf39/5OTkIDpa8uN66dIlCIVC+PmptsjhT0M70Psh/8RW6ds0++B9tPruTKV6dn3aiUxrF5+kK9xv5kpCJr1vps+BewteDaOBrPwS2izF1WISX8EGQIQZDaOVuT72TPaFPoeNqKRszD54n1aF+ziY4K/pnWGip42Hb/gYsT0SaXzlZDetSnCqzsz0vqCUjlb6xNNG5pi4hAExMRFUhTabifiV/en2s4x8fLo1QuURg3UlPz8fMTExiImJAQAkJSXhwQNR1WUGg4G5c+di1apV+O+///Dw4UOMHz8eNjY2GDJkCACgXbt26N+/P6ZNm4bbt2/j5s2bmD17NkaNGgUbG5tq7qocmEwGDs/0p9tDt0ZUGnO6IkJywMbrMv19XUXCzM3n7+BmI9IaxaXmKiR6LVzGxGRea8K7TqskZrOo70j9pYZAhBkNpH0LHv6c0AkcNhMXnqRjwdEH9Jtj+xY8/DPDH9Y8Lp5l5GPYtggkZxUofE5VqWurMzOdfZSGciGFdtaGaFMRMgmIEkXdrKhjQrL+ElQJV4uFJyskAk3sqxx8vjNKIwSau3fvwsvLC15eXgCAkJAQdOsmCW9esGAB5syZg+nTp8PHxwf5+fkICwsDlytxUD1w4ABcXFzQp08fDBw4EF27dsWOHTuU/lmqwsfBBPYVztpxqbmVcs8EuVvT+9KJO9ta6MPWRAel5UI8zyyADY8LgZBCTIrs+Y2ltFyIq1KamdqeZdcTJWOHe7cET0erhtGE6iDCjIbSuZUptozpCBaTgWP33mDV6Sf0g7aNhT4Oz/SHg6kuXr8vwvDtkUhIy1PofKrSzFRnZvo3pqJC9gdamTtJ71FQKoC5AYd+cyIQVIWONgtxywPp9s1n7zBTyq9BXenZsycoipLZ+HxJlWgGg4EVK1YgLS0NxcXFuHDhApycnGSuYWJigoMHDyIvLw98Ph+7du2Cvr765Ds5+5Vs7hlpM+CvIzzo/VlSfy8Gg4GAClPThcfp8BbXaZJz0cmopHfILxFpe1hMBrq2Natx/Lidt+n9n4d1qGEkoSaIMKPBBLha4peKxb/rZhK2XH5GH2tprIt/ZvrDxcoAmXklGLE9sk61kuRJVerbt/wi3K4o8iZdiwmQmJh6OtWuliUQlIEeh42HyyQ+NOfi0hHyT4zqJkQAAOhqs7HiEze6veLUY3qfq8WCAYcNQCSASkekiYWZywkZ8LYzAiAqqSJPpLP++jmayBTP/ZBVUvPe9rm3jP8goX4oVJhpKjVC1JnPOrbEko9dAQBrzz/Fvlsv6WMWBlwcmu4PLzsj8IvKMPaPW4h4nlXdpRpMdQnGqtLMnIp9C4oCfByMK9VculIRkq1OJqaSkhJ4enqCwWDQfgdiHjx4gG7duoHL5cLW1hY///xzpfMPHz4MFxcXcLlcuLu748yZM8qaOkFOGHC1ELtUItAcu/cGS/59pMIZEQBgvL8DvR8akSyTM+aIVDTQjusv6H1fRxMYcNnIyi+FVkVpgfspOXKLWKMoCheeSCLBanqWFZaW488bSXS7f/vqI8UItaNQYaYp1QhRZyZ3dcSXvdsAAJb8+4hORgcAPF0t7J/ih4/aiLMI35FJ5iQP7kvZnKW99qvymfk3VmRiGvxBbpnkrAK8yCoAuw5qWWWyYMGCKp0ec3Nz0a9fP9jb2yM6Ohq//PILli1bJuNXEBERgdGjR2PKlCm4f/8+hgwZgiFDhuDRI/JDqGnwdLRw/3996fbeyJdYczZehTMiAMD1Bb3ofd8fJBFazlYSX7yfwxJoE7wWi4keTqKUD6+yi2DAYSO/pBzxafLJVvzkbR6d1BSouYRBr7VX6P2Ihb3lcv/mjEKFmaZWI0SdmdfXCeM624OigJBDMbSWAxCpyndO8EFfV0uUlgsxc380Ttx/I7d7S6tpTfW16f0Po5meZ+bj0ZtcsJkMGSc9QGJi8nGoWS2rTM6ePYvz589j7dq1lY4dOHAApaWl2LVrF9zc3DBq1Ch8+eWXWLduHT1m48aN6N+/P7755hu0a9cOK1euRMeOHbF58+Zq76molPCExmOsp427iyWRJtuuPsdvFxNrOIOgaGxNdPGpl+TFSDr3zGqpEgg3nkk00rSpKT4DXhUh0PKq0ySdKM/BVBetzPSqHPc4NRfpuaLEp74OJrD5QEtNqD8q85lJSkrSuBoh6gyDwcDywW4Y5GGDciGFmfujES2VQ4GrxcLWsR3xmVcLCIQU5v0Tg32RyXK5t7QwY6InEWY+NDOJc8t0a2smMw6QZP1VFxNTeno6pk2bhn379kFXV7fS8cjISHTv3h3a2pLPERgYiISEBLx//54eI72+xWPE67sqFJkSntB4zPQ5uP2dJBPtr+FP8aeUGYOgfH4ZJpt7RvzckU6wJ+1k29PZHCwmAwnpebCqqKYtL7+ZDwtLVucDM3CTJGz84DTV5u5pKqhMmBHX+NC0GiHqDJPJwK/DPdDDyRzFZUJM2n1HJnEUm8XE2uEemOAv0uD87984GafhhlAuEOKeVDSAqbQwI2VmoiiKNn8N/iCKqaCkHFEV2TLrWllWkVAUhYkTJ2LmzJkygrQ0aWlpVa5d8bGaxtS0dhWdEp7QeCwMuTJmgVWnn+Cv2ykqnFHzhs1iyggEo3ZE0v1DpJ41zzNFvpZGutroVKGRySkUhW7fTX7f6LD7NH4xHryWRI2JNUAfEnpT4iezbJArqT8nJ5rk/2Jz/kHQZjOx7XNveNsbI7e4HON33cbLd5I8M0wmA8sGu2FOhY/NL+cSsOZsfIO/yI/f5qJASgMjnbW3sFRAX/fhGz6SsgrA1WKir6uso9vNZ1koFQhhZ6KL1uZVq2XlwcKFC8FgMGrc4uPj8dtvvyEvLw+LFi1S2FyqQ9Ep4QnywcZIR8ZfY9Gxh3I13RLqR5fWZnRAQexrPmIrIjcXDWxHj1lwROLAL06gl5VfAjaTgbTcYhlfl4YgrZUx1dOGn6NJpTHlAiGWnZREME38yLFR9yRIUJkwI67xoYk1QtQdHW0Wdk3wocOyx+28jYxciVM1g8HA/H7O+G6gCwCR7f/7E48a5NF/O0lWPfuh+ai4TBQWKTYxBbSzhH5F2KSYyxUJpno5mys0NHH+/Pl48uRJjVurVq1w6dIlREZGgsPhgM1mo00bkeDXs2dP+lpWVlZVrl3xsZrG1LR2CZqDrYkuLs3vQbfnHopB2KO3KpxR8+bsXEnumU+23IRASMHSkAuzCj++6Jfv6QK94tIGD17zYVeRgK+xfjPSwswAd6sqNS5j/pS4R5z5slul44SGozJhxtHRUaNrhKg7PF0t7J3sCzsTXaRkF2LcztvgF8oWn5zevTVWf+YOBgM4GJWCeYdiUFbPKsEf2pr1tNnQYkkEkqIyAQRCCicfSGoxSUNRFO2srGgTk7m5OVxcXGrctLW1sWnTJsTGxtIp4cXh1Lt376av5e/vj2vXrqGsTPJ/Gh4eDmdnZxgbG9NjpNe3eIx4fRM0n1bm+jg3tzvdnrn/Hu3/RVAuhlwtLA6SaGJWnRZpQDaM9KL7tl99DgBwNNNDa3M9lAspFJaINMuNqdNUUFJOl2gBgCD3yhGQqTlF9MufhQEHriQxqFxRqDBTVY2QmJgYpKSkaHyNEE3AwpCL/VP8YGHAQUJ6HiaF3q6UyG60rx02jfICm8nAf7GpmLEvutq8MR9CURRdxkCsUGExGTLamcLSckQlvUN6bgkMuWz0+KAS9pO3eXjLLwZXi4nOrUwb8Wnlh52dHdq3b09v4uyojo4SlfCYMWOgra2NKVOmIC4uDocOHcLGjRsREhJCj/nqq68QFhaGX3/9FfHx8Vi2bBnu3r2L2bNnK/0zERSHs5UBTs3pSrcn7b6DyOfvVDij5suUrpLv6O6byUjjF6NLa8lz5Y/rSbSDsNinJadIlL28MZqZ64mZEFvqzQ048K3CxNRlzSV6/8o3PRt8L0LVKFSYqapGiJeXF5YsWQJA82uEaAJ2prrYO8UXhlw27qXkYOb+eygtl9W+DPKwwR/jRbWeLsVnYMKu28grLqvmihKeZ+Yju6AUXC0m2lmJ3jJYTAaMdGQjmsQmpoHu1uCwWTLXEL/FftTaDFwt2WPqDI/Hw/nz55GUlARvb2/Mnz8fS5YskcmB1KVLFxw8eBA7duyAh4cHjhw5ghMnTqB9+/YqnDlBEbRvwcNRqURto/+4hXsp8k2TT6gdBoOBy1/3pNudV18Ek8nAwgEudN+RivBtsalJbApPSM8Dv6j2515VhD+WaOMGtrcC64MM5mGPJE7/kz9yhK62rKmd0HgUKsxUVSOEoiiEhoYCaBo1QtSVP6+/wLrzomRRLlaG2D3JFzpaLFx7momQf2Iq+cf0crHAXqlq3GP/jML7KuotSXM7SfSw9rQ1or+8bCYDPF1Jnhh+URnOVnyRP4xiAkS5HsT3V1ccHBxAURQ6dJCtm9KhQwdcv34dxcXFeP36Nb799ttK5w4fPhwJCQkoKSnBo0ePMHDgQGVNm6BkvO2N8de0znT7s98j8OgNv4YzCIrA0UwPQR0keayORr/GyE6SiNb/VfgHdrQzgrHUs4qi0CABVCCkcC5OIqx8XIUpXbqm15JBrvW+B6F2mmQ0U3OnuEyAVaefYNOlZ3BcdAZlAiG87Y2xbZw3tFgMnHrwFkv+fVQpgsmvlSn+mtYZJnraePCajxHbI5Eu5Tj8IWJ/GV8HE1o4YjIZMJKq+hr2KA38ojJYGHDg5yhrRnpfUEo/PNRZmCEQ6op/a1OETvKh2x//dgOJ6Yot8kqozPoRnvT+/MOx0GYz0d9N4nh/4Uk62CwmejnLPnfuNiDfzL2U93RhSTN9DrztjGWOf3tUEkW1d7Jvva9PqBtEmGmCcLVYaGctcS5r+/1ZFJSUo4eTOdaN8ASDARyISsG68KeVznVvycM/MzrD0pCDxIx8DNsWgZR3hVXeR+zM5uMoEWZYDAaMpN52Dt0RhcUP8rCppHq9lpgJIQU4WxpUqtNEIGgqPZ0tsH2cN93uu/6aTHoEguLRZjNlhMrPd0Zheo9WdPuXcwkARMV6pWmI34x0YcnBHjYyRXL5RWX4564kK3F3J1mfQYL8IMJME+XsV91k8hy4LT2HjLxiDPKwwcpPRD4bv116hp1Shc7EtLEwwJGZXWBvqotX2UUYti0CTz94u0zNKcKbnCKwmAx0tDOGoELLw2IyYKQr8ZnJq3hj+URDTUwEQkMIdLPCxlGedLvHL1eQ2sg8JoT60dPZAhYGorxX91NywIBIcwIAzzLycS/lPbq1NZOJvox5lVPJp7A2Tj2QhONLm7cAwO/HC/T+ne9ls4ET5AsRZpowh2b4y9RA8v3hIp5n5uPzzvb4up/IN2nlqcc4Gv260rm2Jro4PMMfzpYGyMgrwdg/o5Ar5RQsNjG52RhCj8OGUCgRZng6srWVHEx1ZQpQAiI7sziUUV1KGBAI8uQTzxb4aaikPlCXNZdkKjsTFE+YVNj8p79H4Ks+bej2H9dewICrJRNFWVIuxKPUuvs5Pc/Mp5PtGXLZ6GhnRB+Lfvmedi7u42IBcwNOVZcgyAkizDRxtoztiNG+dnS7z69XcTc5G8G92tBhjAuOPqiykraFIReHZnSGo5keMvNKsO3Kc/pYVJLEXwYAymlhBjJmJkBUIfvDZHgxr97jfWFZpQcAgdCUGOljh2VSDp++P1ys1bGeID9M9LSxoL8z3Y5LlZR3OfsoDS/fFVQqOxBdD1OTtIlppI+tzHNu6NYIev+P8VWXRSHIDyLMNANWf+aOad0k+ReGbYtE2KM0fD+wHYZ2bAmBkELwwXtV5sYw0tXGooqwxp03kui3kDtS/jIAJD4zTKZMaDZQOVEeAFyOF2llujuZk9okhCbNxI8c8W1/SWiw18pwGS0nQbHM6tGa3v/7ziv0kdIE77qRhD7tZDXD9Sk6KU4GCgAfd5A856Srqf8yrIOMHw1BMZBfkWbC90GudD0mAJh14B72RCbjp6Hu6OtqidJyIabtvYuHryurWPu6WsLX0QQl5UL8ei4B7wtKkZghKtrmU6GZEVJVOwADQBuLyqH0l+LVq0o2gaBIZvVsjS+lvn8dlp1HQUl5DWcQ5AWDwcD5eRJz08V4SU6YPZEvoc9hw8XKgO6Lflm3opPv8kvw6I1I08NiMtChpciUXlIuwK9SwRXDOzWPQseqhggzzYj5/ZwR0leSx2f5ycdYczYem0Z5oXMrE+SXlGPC7tt0dVkxDAYD31cUbDse8wahEckAREKKONtvOR2aDRmfmapeSNL4xXj8NhcMBtCDePcTmgkh/ZxlMtS6LT1X52zbhMbhZGmAQLeqq1gfiEqRMTW9KyhFUlbt0WfimnIAMK1bK9rE9Mnmm3T/RanaXQTFQoSZZsaXfdpivpRA8+eNJHx9JBZbxnSEewsesgtKMe7PqEqRFx62RvjE0wYUBWysUKGKtTIAaAdgNpOJQqkq2r1dKj9AxLWYPFoayVTZJhCaOv/72BWjfSVv6i7/C6t39AyhYWwc5VVl/84bSZVCpusSov1vjKRK+scVUUxJWQWITxNFfrax0Edrc5LgVVkQYaYZMqdPW8wLkAg0px+8xaz997BxlCdameshlV+McTujkP2Bo+LX/ZyhLeXf4usoSQ4lCc0W1SkRw9WqvMSIiYnQnFn9WQcMkvIjc1p8FuX1LPBKqD9cLZZM/h8x2QWleJGZLxNtVFvRyeIyAa4nZtFtt4qikb3WXqH7Tn/Z9cPTCAqECDPNlK8C2mJuQFu6fTs5G9P3ReOnoR1gzePieWYBJu6+TWe2BETh2iN8WtJtbzuJZkYgqDAzMRi48ERik37Llw1FLSkX4MYz0UOACDOE5spvo73QS6roapvvz1YqMUKQP4FuVjDV067U/+eNJJm/R22amcgXkmCJ4F6twWAwZFJczA1oW6kOHUGxEGGmGTM3wAlf9pEINM8y8vHFgXtYNLAdXdJg2p67Mnb9Lq3N6H2xUAJINDNJWQV48lYS/vj2A3PV7aRsFJYKYG7AgatUlmICobmxe5IvfBwk2s3W352hzbXNhdhXOXBYeBoOC0/j+P3K+a4UwdmvulXqe5aRDy0prfOLrAJk5ZdUe40T96VNTDagKArzD8fSfXMDnKo6jaBAiDDTzJkX0FYmyiIzrwSLjj7AlK6O0NNmIfLFO3z5131aDS62BwPAuvCntOZG/FZ5+uFbSJP6gWZGHJLdy9mchCsSmj2HZ3aRiaRp9d2ZOkXSNBUy8yQCw7xDsXBYeBrfHI5VqGO0hSFXRist5vHbXHDYkp/E6JdVa2coisK/MZKQbBcrA5lCkkdm+stxtoS6QoSZZg6DwcC8vk6Y3Usi0BSUCrA+/CkC21tBm83E+cfpWHTsISiKovPLAEBWfgl2XBUl0hMLM9KpvavicgLxlyEQpDn7VTeZ2mQdlp1vNgJNgKslFge1k+k7HP0aLv8LQ5fVF5Fch6iihjCnd2Vh5n5KjkxaieqKTorDsQFgZo/WyC4oxbk4UfI8LRYDnaQCIwjKgwgzBDAYDMzv54TgXpLkUuVCCsfuvYGTpT6YDNEDZvnJx7j/SvS2Ig7x3nH9BdL4xXQRydJyIXS0qrYVJ2UVICmrAFosBj5qY1blGAKhucFgMHDj214w5LIBiOqZdf3psopnpTymdmuF5DVBlTQaqfxi9Fx7BQ4LT+P0g7dyNcGxmAycmlPZQTc9V6IpulON38zRexJz2GcdW8B7laT+0t3v+8ptjoT6QYQZAgDRA/Xrfs6Y1bO1TP+jN7lgVuRPCI1IRnGZEMa6Wpjdqw287Y1RXCbEuvAEdJUSTgJcLdHKXK/SPcSFJX0cTGDA1ap0nEBorjAYDMQu7Ue33+QUof+GayqckfLp5GCC5DVBuLs4AB4tZWu5BR+8h1bfncGKk4/BL5RP9uT2LXgyTr8fEvMqB0Wllc1d4jxbgKyZ7DOvFuDpkueaqiDCDIGGwWBgQaAzZvaQFWjKP3gjel9YBiaTge8r1MOHo1+jraXE7s9mMmDN41a6PjExEQjVw2AwkLR6IN2OT8vDiG2RKpyRajDT5+Df2V2RsKo/ZvRoJXNs180keKw4j4Ebr+OxVJ2lhvLbmI41Ho99nSPTfv2+kN6f2MUBY/+Motu/jvBo9HwIDYcIMwQZGAwGvu3vjBndW9U47vSDt+hoZ4ygDtagKNl6Jsfvv4GloawwU1BSjqgXojG9iDBDIFQJg8HAix8lAs3t5GxM2n1bhTNSHRw2C4sGtEPS6oHYOlZW6Hj8NhcDN12Hw8LTOHH/TYMTD+pz2Ng0uupkekBlv5mj0ZIoptfvJZGav4/tWKmYLkG5EGGGUAkGg4GFA1wwvQaBZu6h+7j2NBPfBrpAi8VA9Mv30NOW+Mpk5UsS7gmFFG4+y0KpQAg7E120MqtsgiIQCCKYTAaeSwk0lxMyMeev+yqckWphMBgY4G6N5DVBOPNlN9ia6Mgcn3soBk6Lz+KH04/xll9UzVWqZ1BF9t6qkE4/AQDrL0hqLl14IqmYPdC9+msQlAMRZghVwmAwsGiAC77q0xZVvXCUCSjM2BeNrIISjPd3ACCKghIjrQIuKRfKmJjIGwyBUDMsJgPPfhhAt0/GpmLRsYcqnJF64GpjiOsLeuPWoj4Y2rGlzLE/rifBf/UlDN8WgYhnWXWOCGMwGLi+oFeVx269yKYdj6urdH7j26rPJSgXIswQqkUctr1vsp9Mqm8xRWUCTNh5G/1cLelIDDHSCacKSssl+WU0yMR0+vRp+Pn5QUdHB8bGxhgzZozM8ZSUFAQFBUFXVxcWFhb45ptvUF4uWwn5ypUr6NixIzgcDtq0aYPQ0FAlfgKCJsNmMfF0lUSg+et2Cn44/ViFM1IfrHhc/DrCA3HLAyuFdt9Jfo8xf0bBcdEZ7IlIRl41Qog0tia6MqVapHmaIcqtJZ0oT0xHOyO0NNZtwCcgyBsizBBqpWtbM5z5slulYmyAKIx0+r5ofOrVotrz7718j7TcYuhoseDnqBk5GI4ePYpx48Zh0qRJiI2Nxc2bNzFs2DD6uEAgQFBQEEpLSxEREYE9e/YgNDQUS5YsocckJSUhKCgIvXr1QkxMDObOnYupU6fi3LlzqvhIBA1Em81E/Mr+dPuP60lYH/60hjOaF3ocNqZ2a4XnPw7E72M7Qp8j+1K19L84uC87j8UnHuJpel41VxFxc2HvKvtvV+TWWvJvXKVj/8wgCfLUBQbVDLIz5ebmgsfjgc/nw9CQpNBvKEIhhT+uv8CasHh8uGr0tFkQUBSKyyo74g3xtMGJmFQEtLPAnxN8lDTbhlNeXg4HBwcsX74cU6ZMoful19HNmzfx8ccfIzU1FZaWosrg27Ztw7fffovMzExoa2vj22+/xenTp/Ho0SP6GqNGjUJOTg7CwsLqNBeydgmAyIHebalECF40wAUzPog6rAlVrCNVrd3ol9lYH55Yyd8FALztjTH5I0f0c7OUKV8gpucvl5H8rlCmr5W5Hs7N7Y6235+V6V8c1A5Tu9UcKEFoPHVdR0QzQ6gzTCYDM3q0xrFZXdDSWNYJr6BUUKUgAwAnKlJ/a4qJ6d69e3jz5g2YTCa8vLxgbW2NAQMG4PFjiYo/MjIS7u7utCADAIGBgcjNzUVcXBw9JiAgQObagYGBiIysPty2pKQEubm5MhuBoMdh48EySR6a1WfjsS8yWXUTUmO87U2wf6ofrn7TE+P97WWORb98j+CD99Bh2XlsuPAUGbmy5VbWjfSsdL0XmQUIe5RWqZ8IMuoFEWYI9cbLzhinv+yGoHp68Pd01gxh5sWLFwCAZcuWYfHixTh16hSMjY0RFBREj0lLS5MRZADQ7bS0tBrH5Obmoqio6qiL1atXg8fj0Zutra3cPhdBszHkauHe/yQZZv/3bxwO332lwhmpN/ameljxSXvELOmLbwKdZY4VlQmw4UIifH+8iOCD9xD14h0oioKXrZFMaQkxH0aTVZU9mKBaiDBDaBA8HS1sHuOF1Z+512m8i5VBlQ8JZbJw4UIwGIwat/j4eAiFIg3T999/j6FDh8Lb2xu7d+9WShTWokWLwOfz6e3VK/JjRZBgoqeN29/3odvfHHmAUw9SazijcWzZsgUODg7gcrnw8/PD7dual/PGSFcbwb3aIGFVf/wyrEOl7OSnH7zFyB23MGDjdRyISsHELg41Xs9UTxvtW/BqHENQPhojzDSFL1VTg8FgYLSvHc7N7V7rWHUwMc2fPx9PnjypcWvVqhWsrUUaJ1dXV/pcDocDBwcHum1lZYX09HSZ64vbVlZWNY4xNDSEjk7Vgh2Hw4GhoaHMRiBIY2HAlXFWnX3wPi4+Sa/hjIZx6NAhhISEYOnSpbh37x48PDwQGBiIjIwMud9LGXDYLAzvZIuLIT2wd7IvurWVrQ8Xn5aHxSce4YczT2q8zrVqwrgJqkUjhJmm9qVqajhbGeDJiv7oZG9c7ZheamBiMjc3h4uLS42btrY2vL29weFwkJCQQJ9bVlaGlJQUuu3v74+HDx/KrMHw8HAYGhrSQpC/vz8uXrwoM4fw8HD4+5MICELjaGGkgytf96TbU/bcxc0qHF4bw7p16zBt2jRMmjQJrq6u2LZtG3R1dbFr1y653kfZMBgMdHcyx74pfgib2w3DvFvWflIFE7s4QO+DiCmCeqARwkxT/VI1JXS0WTgyqwuWDXKt8nhHOyPlTqgRGBoaYubMmVi6dCnOnz+PhIQEzJo1S2ZMv3794OrqinHjxiE2Nhbnzp3D4sWLERwcDA5HlJNn5syZePHiBRYsWID4+Hj8/vvv+OeffzBv3jxVfCxCE8PBTA/h8yRa0bF/RlVKv99QSktLER0dLePAzmQyERAQUK0DuyY6r7tYGWLtcA9EfdcHX/RsXSlf1ocsG+ympJkR6ovaCzPN5UvVVJj4kSPOz6tsdmJXk5BKXfnll18watQojBs3Dj4+Pnj58iVOnjxJH2exWDh16hRYLBb8/f3x+eefY/z48VixYgU9xtHREadPn0Z4eDg8PDzw66+/4s8//0RgYKAqPhKhCdLW0kDGGXXYtsg6Z76tiaysLAgEgiod2MUO7h+iyc7rloZcLOjvglvf9cHywW6wM6mcCO+rPm1VMDNCXVH7X5jm9qVqCjhZGiBhVf/aB6oxWlpaWLt2LdLT05Gbm4vw8HC0ayebadTe3h5nzpxBYWEhMjMzsXbtWrDZsm92PXv2xP3791FSUoLnz59j4sSJSvwUhOZA+xY8HJ3VBQDgZKkPoYoyhzUF53VdbTYmdHHA5a97YtvnHeFdYTr/xNMG8/o6qXh2hJpoksa/RYsWISQkhG7n5uYSgUbJcNgsJK8JglBIgckktZgIBEXibW+MFz8OBAVRXafGYmZmBhaLVaUDu9jB/UM4HA5tYtV0WEwG+re3Rv/21riX8h7uJHpJ7VF7zUxDv1QkIkQ9IIIMgaAcmEyGXAQZALQjvLQDu1AoxMWLF5udA3tHO+MqswUT1Au1/wuRLxWBQCAon5CQEPzxxx/Ys2cPnjx5glmzZqGgoACTJk1S9dQIhEpohJkpJCQEEyZMQKdOneDr64sNGzaQLxWBQCAokJEjRyIzMxNLlixBWloaPD09ERYWVsl/kUBQBzRCmCFfKgKBQFA+s2fPxuzZs1U9DQKhVjRCmAHIl4pAIBAIBELVaIww0xjEeRdIvhlCYxCvH3nk8agrZO0S5AFZuwRNpa5rt1kIM3l5eQBAwrMJciEvLw88nnJCNcnaJcgTsnYJmkpta5dBKVNUVxFCoRCpqakwMDBAXl4ebG1t8erVKxKyrWDE+X2ayv81RVHIy8uDjY0NmEzlBAJKr11lVO1uKE3tby2mqXwusnYbTlNZA1WhCZ+trmu3WWhmmEwmWrYUFRMTf6lI/hnl0ZT+r5X1VitGeu1qAk3pby1NU/hcZO02jqawBqpD3T9bXdau2ueZIRAIBAKBQKgJIswQCAQCgUDQaJqdMMPhcLB06dImU0NEnSH/182Hpvq3bqqfi1B3mvIaaEqfrVk4ABMIBAKBQGi6NDvNDIFAIBAIhKYFEWYIBAKBQCBoNESYIRAIBAKBoNEQYYZAIBAIBIJG06SFmR9++AFdunSBrq4ujIyMqhyTkpKCoKAg6OrqwsLCAt988w3Ky8tlxly5cgUdO3YEh8NBmzZtEBoaqvjJNwG2bNkCBwcHcLlc+Pn54fbt26qeEkFBaNLf+tq1axg0aBBsbGzAYDBw4sQJmeMURWHJkiWwtraGjo4OAgICkJiYKDMmOzsbY8eOhaGhIYyMjDBlyhTk5+cr8VMQlIUmrW0xzXGNN2lhprS0FMOHD8esWbOqPC4QCBAUFITS0lJERERgz549CA0NxZIlS+gxSUlJCAoKQq9evRATE4O5c+di6tSpOHfunLI+hkIIDQ0Fg8FAcnJyvc6bOHEiHBwcah136NAhhISEYOnSpbh37x48PDwQGBiIjIyMhk2YoLao4m/dmPU7fPhweHh4YMuWLVWO+fnnn7Fp0yZs27YNUVFR0NPTQ2BgIIqLi+kxY8eORVxcHMLDw3Hq1Clcu3YN06dPb8xHIqghiljbin72AkBBQUHzW+NUM2D37t0Uj8er1H/mzBmKyWRSaWlpdN/WrVspQ0NDqqSkhKIoilqwYAHl5uYmc97IkSOpwMBAhc5ZXvzwww/U8ePHK/Xv3r2bAkAlJSXV63oTJkyg7O3tax3n6+tLBQcH022BQEDZ2NhQq1evlhl39epVatCgQVTLli0pDodDWVpaUoGBgdSNGzfqNS+C6qjr37ohKHr9ApC5vlAopKysrKhffvmF7svJyaE4HA71119/URRFUY8fP6YAUHfu3KHHnD17lmIwGNSYMWMoAFRQUFC95kVQTxqztlX17P2Q6tb4iBEjKABVblevXq12jb9586bec1AGTVozUxuRkZFwd3eHpaUl3RcYGIjc3FzExcXRYwICAmTOCwwMRGRkpFLn2lB+/PHHSipGABg3bhyKiopgb28v93uWlpYiOjpa5v+NyWQiICCg0v/b06dPwWQyMXPmTGzZsgVff/010tLS0L17d4SFhcl9bgT5Up+/dUNQ9vpNSkpCWlqazOfh8Xjw8/OjP09kZCSMjIzQqVMnekxAQAAYDAYOHToELpcr1zkRVENj17Yqnr11QbzG3dzcAAArVqzAvn374OzsjH79+mHfvn148uRJlWucyWQiKipKJfOujWZRaLI60tLSZAQZAHQ7LS2txjG5ubkoKiqCjo6OciZbDyiKQnFxcY1zY7FYYLFYCrl/VlYWBAJBlf9v8fHxMn1Tp07F1KlTZfq++OILtGrVChs2bED//v0VMkeCfKjP37quqHL9ir/3VX0e6WeChYVFpfkwmUz4+PggNTVV7vMiKJ+GrG1VP3vrgngdiwtLDhgwAJ06dcJ///0HBoOBzz//HD/++GOlNc5ms2FiYkKfr25onGZm4cKFYDAYNW4NfYgqg2XLltFzHDFiBAwNDWFqaoqvvvpKxl4JALt370bv3r1hYWEBDocDV1dXbN26tdI1HRwc8PHHH+PcuXPo1KkTdHR0sH37djAYDBQUFGDPnj30/83EiRMBVG+3PXv2LHr06AEDAwMYGhrCx8cHBw8erPEzCYVCbNiwAW5ubuByufDw8AAgKi/fEHR1dWFubo6cnJwGnU9QHB+uX2dnZwDA+vXrK63fzMxMjVu/vXr1AgAsWLAA79+/r/P/y759+yAQCDB48OA6n0NQLvV99g4fPhwA0KNHD41Yu1wuF5aWlpgxY0a91i4A5OXlgdLwYgAap5mZP38+vSiqo1WrVnW6lpWVVSXP9PT0dPqY+F9xn/QYQ0PDRmllRowYAQcHB6xevRq3bt3Cpk2b8P79e+zdu5ces3XrVri5uWHw4MFgs9k4efIkvvjiCwiFQgQHB8tcLyEhAaNHj8aMGTMwbdo0ODs7Y9++fZg6dSp8fX1px63WrVtXO6fQ0FBMnjwZbm5uWLRoEYyMjHD//n2EhYVhzJgx1Z43Y8YMhIaGYtKkSfjyyy/x7NkzrF27FrNnz8bjx4+hpaVF/7+J/18/JDc3F6WlpcjKysLevXvx6NEjfPfdd3X+/yQoF/H6XbVqFebNm4fDhw+Dy+XS6zc9PR3v379Hjx491H79bt26FVeuXMGkSZMwevRo/O9//8PRo0eRkJCAmzdvQktLC+np6fD09AQgeiZIO4Dm5eXh22+/BQBauCOoL3V99rZr1w6RkZGYOHEiXr58Sa/dD59j6vTsTUpKwubNm3H//n167X6IeO7il81evXohPz8fDAYDDg4OSExMrLTGAaC8vBzZ2dnVPsNVjmpddpRDbQ7A6enpdN/27dspQ0NDqri4mKIokQNw+/btZc4bPXp0gx2Aly5dSgGgBg8eLNP/xRdfUACo2NhYuq+wsLDS+YGBgVSrVq1k+uzt7SkAVFhYWKXxenp61IQJEyr1f+iElpOTQxkYGFB+fn5UUVGRzFihUEjvf+iEdv36dQoAdeDAAZlznJycZPoFAgHVokWLah3nAgMDaeczbW1tasaMGZXmQVA9Va1fX19fyt3dnV6/4r/1ihUrKp2vbutXvObE61TsHDlt2jS6n8/nV+kAfPfuXYqiKOrrr7+mrKysKADUmzdvKHt7e+IArIY05Nnr6+tLzZ49m6IoydqVfo6p47M3LCxMph/VOAB//vnn1MSJE6k9e/ZQBw4coFgsFsXhcCgzMzPq4sWLMmucoijq3LlzxAFYVaSkpCAmJgYpKSkQCASIiYlBTEwMHSvfr18/uLq6Yty4cYiNjcW5c+ewePFiBAcH01VEZ86ciRcvXmDBggWIj4/H77//jn/++Qfz5s1r1Nw+fDOdM2cOAODMmTN0n7Tmh8/nIysrCz169MCLFy/A5/Nlznd0dERgYGCD5xMeHo68vDwsXLiwkgMjg8Go9rzDhw+Dx+Ohb9++yMrKorevv/4aALB9+3Y8efIEs2bNQkFBASZNmlTlddasWYPz589j586d6Ny5M0pLSyvl+yGoD9LrNyQkhDbthoaG0n9r6TBOdVq/FEXRzwIA4HK5sLKyQkxMDN69e4dp06bRjrxHjx7F+PHjYWNjgyFDhgAA2rVrh/79+2PatGk4cuQINmzYAAAYPXo0bGxsGvwZCMqhPs/ekJAQ7NixA5s3b0a7du3w4sUL5OfnyzzH1O3Z6+3tDX19fRw5coRe40lJSfRvIYPBwNy5c3Hq1Cl8+umn8PLywj///AM7OzucPn0a7969wz///EOv8du3b+PmzZuYPXs2Ro0apb5rXNXSlCKZMGFClWFnly9fpsckJydTAwYMoHR0dCgzMzNq/vz5VFlZmcx1Ll++THl6elLa2tpUq1atqN27dzd4TuK3gxcvXsj0l5aWUkwmk5oxYwbdd+PGDapPnz6Urq5upc/w8uVLepy9vT3Vu3fvKu9X17eDNWvWUACoxMTEGuf/4dvBgAEDqg3vA0Dp6OhQ2tralK+vL3Xr1q1a/ndElJSUUG5ubtTQoUPrNJ6gPKpbvxs2bKAAUEwmk/5bq+v6tbS0rHHNSm9MJpPq06cPlZCQIHOdd+/eUaNHj6ZYLBbFYrGoSZMmUXl5efTnIZoZ9UNez94TJ07Q49T52VvVJp6PUCik/ve//1GWlpYUh8ORWeOdO3emWrduTa9xfX19ytDQUGaNqyMa5zNTH0JDQ2vN1mtvby8jkVdFz549cf/+fTnOrDIfSuDPnz9Hnz594OLignXr1sHW1hba2to4c+YM1q9fD6FQKDNeVVFVQqEQFhYWOHDgQJXHzc3NaYfguqKtrY3BgwdjzZo1ahsxRpAlODgYISEhmDZtGrZt24bnz5/Dzc1NLdcvl8ulnR379++P+/fv13v9mpiYYOrUqfjrr79w7NgxeHl50W/G5eXlKCoqQnJyMkxMTOioEYJ6Ut9n74frQROfvQwGAytWrMCKFSsqHbO1tUVCQgJMTExqdUBWJ5q0MKPOJCYmwtHRkW4/e/YMQqGQzvB48uRJlJSU4L///oOdnR097vLly/W6T01qSmnEzmmPHj1CmzZt6nz91q1b48KFC/joo4/k+qUuKioCRVHIy8sjwowaQtavyIwNAJ999lmlY2/evIGjoyPWr1+PuXPn1uu6BMVC1m7NvHjxAubm5nK7nrJo0j4z6syHaaZ/++03AKKYfwB0HgJKKlyOz+dj9+7d9bqPnp5enUKc+/XrBwMDA6xevbpSmCJVQ8jeiBEjIBAIsHLlykrHysvLa713VWnBc3JycPToUdja2lbKdUBQD8j6BXr37o3jx49X2szNzdGpUyccP34cgwYNqnXuBOVC1q6IzMzMSn1nzpxBdHS0Rub3IpoZFZGUlITBgwejf//+iIyMxP79+zFmzBhaLdivXz9oa2tj0KBBmDFjBvLz8/HHH3/AwsICb9++rfN9vL29ceHCBaxbtw42NjZwdHSEn59fpXGGhoZYv349pk6dCh8fH4wZMwbGxsaIjY1FYWEh9uzZU+X1e/TogRkzZmD16tWIiYlBv379oKWlhcTERBw+fBgbN27EsGHDqp3fgAED0LJlS/j5+cHCwgIpKSnYvXs3UlNTcejQoTp/ToJyIesXsLOzk3lzFzN37lxYWlrSDsME9YKsXRFdunSBl5cXOnXqBB6Ph3v37mHXrl2wtbXVzLQYqnPXaZ6IndAeP35MDRs2jDIwMKCMjY2p2bNnVwrL+++//6gOHTpQXC6XcnBwoH766Sdq165dlep61ORwGB8fT3Xv3p3S0dGRcQCrrj7If//9R3Xp0oXS0dGhDA0NKV9fXzoklaKqrw+yY8cOytvbm9LR0aEMDAwod3d3asGCBVRqamqN/x+bN2+munbtSpmZmVFsNpsyNzenBg0aRF27dq3G8wiqgazf2iEOwOoJWbuyfP/995SnpyfF4/EoLS0tys7Ojpo1a5ZMrUJNgkFRGp72T8NYtmwZli9fjszMTJiZmal6OgRCvSDrl6CpkLXbtCE+MwQCgUAgEDQaIswQCAQCgUDQaIgwQyAQCAQCQaMhPjMEAoFAIBA0GqKZIRAIBAKBoNE0izwzQqEQqampMDAwqHNWRgLhQ6iKjMQ2NjZgMpXzHkDWLkEekLVL0FTqunabhTCTmpoKW1tbVU+D0ER49eoVWrZsqZR7kbVLkCdk7RI0ldrWbrMQZgwMDACI/jNI0TdCQ8nNzYWtrS29npQBWbsEeUDWLkFTqevabRbCjFjFaWhoSL5UhEajTJU5WbsEeULWLkFTqW3tEgdgAoFAIBAIGg0RZggEAoFAIGg0RJghEAgEAoGg0RBhhqBwKIpCUalA1dMgNBFKygUoFwhVPQ0CoclBURQKS8tVPY0GQYQZgsIZt/M22i0Jw+v3haqeCkHDufo0E86LwxC06QZI8nJZIp5lITE9T9XTIGgweyNfwnXJOaw+80TVU6k3RJghKJwbz7IAAGcfpql4JgRNJi6Vjwm7bgMAEtLzSCK2CvZGJsNh4WmM+TMKfddfI0IeocGcfyx6Rm+/9kLjtJ9EmCEoFKFQ8mDt0JKnwpkQNJnUnCIEbbpBt89+1U2Fs1EP/rqdAoeFp7Hk3zi6z82GhEATGs7a4R70/jdHHqhwJvWHCDMEhZL0roDed2tBhBlC/cktLkOXNZfo9r4pvmhnrbwf7Xsp7/H5n1E4Gv1aafesiaPRr+Gw8DQWHXso079/ih9Of9mNaKwIDcaap0PvH7//RuZlVN1pFknzCKrjwescel+fQ5YboX6UlgvRYdl5uv3zsA7o1tZcKfcuFwix5fJzbLqUCIGQgpm+NoZ6K6cUQFWcjE3FnL/uV+rfNbETertYqmBGhKbI+Xnd0W/9NQDAT+fisWhAOxXPqG4oVDNz7do1DBo0CDY2NmAwGDhx4oTMcYqisGTJElhbW0NHRwcBAQFITEyUGZOdnY2xY8fC0NAQRkZGmDJlCvLz8xU5bYIcefCar+opEDQUoZCC0+KzdHtO7zYY0Uk5tX5S3hVi5I5bWH/hKQRCCp62RlgyyE0p9/6QsEdpcFh4upIgs32cN5LXBBFBhiBXnCwlZQO2X32hMT5YChVmCgoK4OHhgS1btlR5/Oeff8amTZuwbds2REVFQU9PD4GBgSguLqbHjB07FnFxcQgPD8epU6dw7do1TJ8+XZHTJsgRIswQGgJFUWj13Rm6/XEHa8zv56yU+x6Nfo2Bm64j+uV7AEBPZ3McnOYHEz1thd9fmotP0uGw8DRm7o+W6d88xgvJa4IQ6Gal1PkQmg+Hpnem93feSFLhTOqOQvX+AwYMwIABA6o8RlEUNmzYgMWLF+OTTz4BAOzduxeWlpY4ceIERo0ahSdPniAsLAx37txBp06dAAC//fYbBg4ciLVr18LGxkaR0yfIAWkzE4FQVwZsvE7vO1saYPOYjgq/J7+wDN+feIhTD97SfZ95tcBPwzpAi6U898JrTzMxviJqS5r1Iz3wqZfqzFyE5oNfK1N6f9XpJ5jS1VHtfbFU5gCclJSEtLQ0BAQE0H08Hg9+fn6IjIwEAERGRsLIyIgWZAAgICAATCYTUVFR1V67pKQEubm5MhtBNZQJNENFSVAfgg/eQ3yaJF9K2FzFRy5FPn+HARuvyQgy07u3wtrhHkoTZCKeZ8Fh4elKgsxPQ92RvCaICDIEpbJF6gXiRMwbFc6kbqjMIzMtTRTPbmkpa++1tLSkj6WlpcHCwkLmOJvNhomJCT2mKlavXo3ly5fLecaExkBCRgl1Ye25BJyWEiie/zhQoW+EpeVCrL/wFNuuPoe0a8B3A10wvXtrhd1XmjvJ2Ri+LbJS/8oh7TGus71S5kAgfMhAd4kZc96hWAzxbKHW2pkmGZq9aNEi8Pl8env16pWqp9Ts6dDSSNVTIKg5f99OwebLz+h2/Mr+YDEV9/B8npmPz7bexNYrEkGGzWRg3QgPpQgy91Pew2Hh6UqCzOKgdkheE0QEGYJKYTAYWDbIlW5fis9Q4WxqR2WaGSsrkdSXnp4Oa2truj89PR2enp70mIwM2f/A8vJyZGdn0+dXBYfDAYfDkf+kCfVC2gvegyTMI9TA5YQMLJTKmxKzpC+4WiyF3IuiKPx1+xVWnIpDcZkky6mOFgu/f94RvZwtaji78Tx8zcegzTcq9X/b3wWzeipHG0Qg1IVx/g5YdvIxAGDKnrtIXhOk4hlVj8o0M46OjrCyssLFixfpvtzcXERFRcHf3x8A4O/vj5ycHERHS7z5L126BKFQCD8/P6XPmVA/+EVl9H57kjCPUA0PX/Mxafcdun19QS8Y6Somcuhdfgmm74vGd8cfyggyRrpaODDNT6GCzJO3uXBYeLqSIDMvwAnJa4KIIENQO1hMBoJ7SdblrRfvVDibmlGoMJOfn4+YmBjExMQAEDn9xsTEICUlBQwGA3PnzsWqVavw33//4eHDhxg/fjxsbGwwZMgQAEC7du3Qv39/TJs2Dbdv38bNmzcxe/ZsjBo1ikQyaQDJ7ySFJW2NdVU4k/pDciQph1fZhTI/7v8GfwRbE8WslatPM9F/43WEP06X6bfhcXFkpj862hkr5L6J6XlwWHhaJkILAIJ7tUbS6oH4KqCtQu5LIMiDOb0l63PUjlsqnEnNKFSYuXv3Lry8vODl5QUACAkJgZeXF5YsWQIAWLBgAebMmYPp06fDx8cH+fn5CAsLA5fLpa9x4MABuLi4oE+fPhg4cCC6du2KHTt2KHLaBDnxUCos21BHs7L/khxJiuddfgm6/XyZbv85vhM8bI3kfp/iMgGWn4zDhF23kZlXInPMyVIfR7/ogjYWBtWc3XBeZObDYeFp9K3IpipmWjdHJK0eiG8CXdTaoZJAAACuFgvDpDJfx7zKUd1kaoBBaUp6v0aQm5sLHo8HPp8PQ0MSVaMsvj4ciyMV9WzU2dZaGwwGA8ePH0fv3r3B4/GQk5MDFxcXzJ8/H19//TUAgM/nw9LSEqGhoXSOJFdXV5kcSWFhYRg4cCBev35dZ81iU127+SXlaL/0HN1e+Ykbxvk7yP0+8Wm5+OqvGCSki0K9bXhcpPJFAmcne2PsnOADnq6WXO+Z8q4Q3X+5XKl/vL89lg92U4kAo4p11FTXbnPkfUEpvFaGAxD5lj1Z2V9p967rOmqS0UwE9aCpJsxLTk4mOZIaQUm5QEaQmdrVUe6CjFBIYdeNJAzefBMJ6Xkw09dGfzcrpOWKBJmAdhbYN8VProLMm5wiOC46XUmQGeVjixc/DsSKT9oTTQxBIzHW00Z3J1FNtKIyAeJS1S+zOxFmCArjaXrT9A8RR9gpKkcSj8ejN1tb5dQiUhYCIQW3JRJBpreLBRZ/7FrDGfUnI7cYE3bfxopTj1FaLkQvZ3MM8rBBWFwahBQwolNLbPvcGzra8omWSuMXw3nxWXy05pJMrppPvVrg+Y8DsWZoBzAVGGJOICiDH4a0p/eDD9xT4UyqRrMcGQgaia6cfjSaA4sWLUJISAjdzs3NbTICDUVR6L/hGsqFol98e1Nd7JzQqZaz6sf5uDR8e/QB3heWgcNm4ruB7ZCUVYDdN5MBAF/0bI1vAp3loiHJyCtGn1+vIq+4XKY/qIM1No70BFuJJRAIBEVja6ILFysDxKflIfldIZ6m58kUpVQ1RJghKBz3JhaWLda4kBxJ9WPm/mgkZki0dRdDesjN7FJYWo6Vp57gr9spAABXa0P8MrwDtl55TpcoWPKxKyZ3dWz0vbILStFv/TVk5cs6Ewe0s8TWzzsqtY4TgaBM1g73wMe/iaIPFx17iKOzuqh4RhKIMENQOIqIUFElDg4OdI4ksfAizpE0a9YsALI5kry9vQE07xxJP5x+jHNxkpDoJyv6y01z8fA1H1/9fR8vsgoAiGoqzezRGl/+dR83nmVBi8XAryM8MdijcekccgpLEbTpBt7kFMn0d3cyx5/jO0GbTYQYQtOmfQseTPS0kV1QiuiX7/EiMx+tzPVVPS0ARJghKIj8EonqXRM1M/n5+Xj2TJJaPykpCQ8ePAAAmRxJbdu2haOjI/73v/9VmyNp27ZtKCsra7Y5kkJvJuGP60l0+/7/+srFX0UgpLD92nOsO/8U5UIKloYcrBvhCWcrA0zYdRsP3/Chq83C9nHe6NbWvMH3yS0uw5DNN2lhSYyfown2TPZVWKZiAkEd2TjKE+N2ioqh/ngmHn/K2VTcUIgwQ1AIaXxJvhVHMz0VzqRh3L17F7169aLb0n4sgChHUkFBAaZPn46cnBx07dq1yhxJs2fPRp8+fcBkMjF06FBs2rRJaZ9BHTj78C2dDh0AbnzbC8Z6jc/u+yanCCGHYhCVlA0AGNDeCj9+6o78knIM2xqB5HeFMNHTRugknwbXBRNfS7qCNwB42hrhr2md5eZATCBoEl3bmNH7F56kI+VdIexMVZ8UtVkLM8lZBVhzNh4OZnqY3bsN9DnN+r9Drkir4i0MNc8HpGfPnvgwBZM43wEg0s6sWLECK1asqPYaJiYmOHjwoELnqc5EvXiHWVJRD2e+7IaWcsgEfTI2Fd8df4i84nLoarOwbJAbhndqiSdv8zBhtygxXktjHeyd7NsgFXhRqQCjdkQi9rVs+Gk7a0McmekPPfKcIDRjGAwGNo7yxFd/xwAANlx4inUjPVU6J6CZCzPbrz1HWJwoTHbb1ecARG9dSwa5wsvWiOSEaASP3kh+CEz1NE+YITSOJ29zMVIq9fn+KX5wtWlc4rS84jIs/TcOx+6/ASDyxdo40hMOZnq49eIdpu25i7yScrhYGWDPZF9YGnJruaIsxWUCjN95G7eTs2X6W5vr4XjwRzDkyje5HoGgqQx0t6aFmWP332B+oDNaGOmodE7NWpgJ7tUGf91+JdMX8yoHn/0eQbe/H9gOo3xtYUAeZPVCOmEei+TYaFakvCuUqUP063APdG1rVsMZtRP9MhtzD8XgVXYRmAxgdq82mNOnLbRYTIQ9eosv/45BabkQvo4m+GN8J/B06v59LSkXYHLoHdx8JltEz9ZEB6dmd5N7hmACQdPRYjGx5GNXrDglMiFvvfIMq4a4q3ROzdr9vqWxLpLXBOH5jwOx+jN3aLEq/+j+cOYJ3Jedh8PC05gSegcPXudAKGzyFSAazcPX6pchkqB4MvKKZTLgzu/rhKFSdV3qS7lAiHXhTzF8WyReZRehpbEODs3wR0g/Z2ixmNh/6yVmHbiH0nIh+rtZYe9k3zoLMmUCISaH3oHz4jAZQcbSkIN7/+uL6wt6N3tBZsuWLXBwcACXy4Wfnx9u376t6ikRGgFFUcgvKUdqThFSc4pQJhDWflI1jPSR5L/afysFGbnFNYxWPM1aMyOGxWRgtK8dRvvaARDVc/nh9BNcT8ySGXcxPgMX40W5Q/S0WVj8sSsC3axgIgeHxqZGKl+1C5ugfPhFZfD94SLdHubdEnP6NLwi9Mt3BZh7KAb3U3IAiDLqLv/EDYZcLVAUhY0XE7HhgqhS+WhfO6wa0r5OWsBygRCzD96nTcxijHS1ED6vB8wNiFkUAA4dOoSQkBBs27YNfn5+2LBhAwIDA5GQkFApuzVBOVAUhcJSAXKLy5BbVF7xb5mkLb1fLLvPLypDXnE5BFIv4wwGYKqnDQsDLiwNObA05EptoraFIQemepxK3y09Dhuze7XB5suiqM/t117gfx+7oqhUgJfZBXC2NFCqqwYpNFkL/KIy7L/1Er+cS6hx3DDvlhjlYwtPWyOS+ROAw8LTAAALAw5ufx9Qy2jNgBTrq57iMgE6LDuP0oo3PR8HY/wzw79BDzOKonAk+jWW/ReHglIBDLhsrBrSHp94tgAgCsle+t8j7L8lSpD3ZZ+2mBfQttZ7CYQUQv6Jwb8xqTL9utosXP66Z719bDSJhqwjPz8/+Pj4YPPmzQAAoVAIW1tbzJkzBwsXLlTIPZs6FEWhqExQtSBCt8vBLyyrJIyIjwnkYBlgVwgm5XW8FovJgIUBBxaGXFgacGhhh8lk4OcwyW9jS2MdvH4vCv5Y85k7RlUoCBpDXdcR0czUAk9HC8G92iC4VxuUCYSIeP4OP52Nx+O3sgUAj0S/pitE25roILhnG/RwNoc1T7VOUaqmoWGxBM2hXCDEwE3XaUHG0pCDg9M6N0iQySksxffHH+H0Q1HWXl9HE6wb4UFHQRWXCTDvUAzOPkoDgwGsGFx7tW2hkMKCow/o76cYFpOB6wt6wUbFjovqSGlpKaKjo7Fo0SK6j8lkIiAggC6m+iElJSUoKZFkRW6KRVIpikJxmbCSIMKn90UCR3VCSm5RWZ0FiJpgMxkw1NGCIZcNQx0t8HS0YMjVgj6HDY4WExw2E9psJrRZLHC0mNBmidrifgaDgeJSAd7yi5GSXYiU7AK8fFeIjLySKu8nEFJ4yy/G21o07mJBBgDcbJSbX4wIM/VAi8VEDydz9HAyB0VReJaRjwNRKQiNSJYZ9yq7CAuPPaTb4zrbI9DNCp0cjJtFgq3iMgG936Gl5iXMI9QdoZDC5D138SJTklDu0vyeDUrpH/E8CyGHYpGWWww2k4F5fZ0ws0drWr2dW1yG6Xvv4taLbGizmNgwyhMD3a2rvR5FUVh84hEORKVUOnZ9QS/Ymqg+N4a6kpWVBYFAUGUx1fj4+CrPWb16NZYvX66M6TWY6oSRugoiucVlKBMox5jBYjKkhBImLZRw2CwwmUBxmRAl5SKBJCmrACXlQpSWN9wHRp5ELw6Aqb5yzbVEmGkgDAYDbS0NsGywG5YNdkNWfgkuPknH+vBEpH3gCLXv1kvsu/USgOjH/TOvFujhbAEHU90mGf6dkSuR7tWpEBlBvlAUhe9PPMS1p5l0X/TigHrnYSktF+LX8wnYcf0FKEqUZHHDSE+ZMhgZecWYuOsOHr/NhT6HjR3jvdGlddURUhRFYcWpx3RxSWkuf91TI5M4agLKKJJKURRKyoW0YMGvoyCSJ9Vf2ginV2UiEIr8YwpLBbUPrgIWkwEumwmuFgsc8b/0vmw/ly3S4Ij2mVLjpMZU7LNZDCw8+hAp2YXV3js0Ihnz+zk39KM3CCLMyAkzfQ5G+thhpI8dissEuPXiHY5Ev6aL3Il58JqPB6/5QEVW1M8726GHkwX8W5s2maR9b/manTCPUDc2XXwmk9rg2je96v029iwjD1/9HYO4VJFJYrSvLRYHucoIRMlZBRi3Kwqvsotgps9B6CQftK+iRAZFUfgpLIHOGSXNhZDuaGNBBOu6YmZmBhaLhfT0dJn+9PT0agul1qdI6vuCUrwrKK1VEOFrsDAijUQgEGlWPhQmOGJhgl39GOl+Ti2CCJfNlLvvJkVR2BORLJPRuzp+u/QMXC0Wgnu1kescaqJp/HqqGVwtFno6W6CnswV+G00hLjUX4Y/TsfXK80pfxP23UmhHxk72xujTzhI9nMzRzlq5nuDyRNquaq5kVSNBORyMSsH6C0/p9qk5XeuV0pyiKOyPSsEPpx+juEwIY10trP6sA/q3l/2hfPiaj4m7b+NdQSnsTXWxd7Iv7E31Kl1rw4VEbLyYWOk+YXO7wcWKOJ/WF21tbXh7e+PixYt0vTGhUIiLFy9i9uzZjbr2vzFvMO9QDFSR4UKLxZAIBHUSIET7nA8FEZlzq76OWODgVPioaDIRz7Iw5s+oGsfYmehiQHsrbL/2AgDwy7kE6Gix5FKpvi4QYUbBMBgMtG/BQ/sWPMzr64Q0fjEuxqfjv5hUuq6MmLsv3+Puy/f4KSwe2mwmBnvYoLuTObq1MZNLPRtlkZAuqWVDwlybHmGP3uK74xKfsH1TfKvUlFRHVn4Jvj3ygE5z0K2tGdYO96gUTXQjMQsz9t1FQakAbjaGCJ3kW2k9bbn8rMpIw1NzutZrToTKhISEYMKECejUqRN8fX2xYcMGFBQUYNKkSY26rp42G3rabJQLqRqFAGlhoiYBglOLICL9L0ngWT9eZOaj969XqzzmYKqLKV0d8b9/4wAAf07oBGseF8fuv0FmhSPxilOPoaPNotOeKBIizCgZKx4XY/3sMdbPHoWl5biemIWLT9Lxz13ZSIvScqFMhJSnrZHI+djZHB4tjdT6Symd/bc5ODw3JyKeZ2Hmfkm9pQ0jPetVkfpyQga+OfwAWfkl0GYx8e0AF0zq4gDmB+v51INUzDsUgzIBhS6tTbF9nLdMFu4/r7/AqtNPKl3/+Bdd4GVn3IBPRviQkSNHIjMzE0uWLEFaWho8PT0RFhZWySm4vgS4WuLh8kA5zZKgCDLzSjBzfzSiX76v8niQuzV+HeEBl/+F0X1i/8hv+7vg68OxdP93xx+Cq8XEp14NT55ZF4gwo0J0tdkIdLNCoJsV1nzWATGvc3DhcTrOPkpDUlaBzNiYVzmIeZWDjRcTYcBho7uzOR1ZpW75MR68Itl/myIPX/Mx5g+JqnnhABcM8WpRp3OLywRYczaejvxzstTHxlFeaGdd2QQkssvHgaJED811Iz3AYYuE4r2RyVhS8SYozZGZ/ujkYNKAT0WoidmzZzfarETQHApKyrH2fEKVzvNi5vRug3kBThBKpagLkooq/MyrBfbfeomYVzkAAIoCvj78AFw2CwNqiD5sLESYUROYTAY62hmjo50xFvR3Qcq7Qlx4ko6L8emVasbklZTj9IO3OF3hXOxiZUALNt4OxvSDX1XklZSr9P4E+fMiMx+DNt+g2+M622Nmj9Z1Ovdxai7mHrqPp+n5AICJXRywcIBLJa0dRVFYF/4Uv136f3v3HdbU2f4B/JsEwpAtUwUFFHAg4ABxoFYUrR22rlZbtSqOaluV2krbn9q3r7V1VH2t1i2OWqu2tVatC7fiQAEFAUVBlkyFIEiA5Pn9ETgkEhCUkMH9ua5cnpycnDwnhpM7z3me+5ZlFJ3g3xaL3uwMAZ+H366lIlQu3UGVPcF+tc5qIoTUT4VEit+upXKXjJQRCvj4cZQn18Oy+kT1mLnv362uy8Tn8/DtW53x9rpL3DqJlOHTvVHYpC/AQA/VZI+mYEZDObU0xuS+zpjc1xmFz8px/m6uLLiJz8HT54KFhKwiJGQVYeP5BzAWCuDv0hL9K3tunh8s2ZRcbWgKrC54VPhM4br5IA9bfPtW5xc+Typl2HYpGcuOJaJMIoW1iQGWj+6Kge41T2YVEim+ORiLvddls6NCBrth9mvt8efNDITIdVlX2TnZFwFu9b+8RQipiTGGU/E5CN4ZqfRxAz0+xBVStGwhxMYPuyv0fv6v8kcHgBr10LwcLbBsVFd881csN+mlXMIwffcNbJ/UE33aN/4PEApmtIC5kT7e9GqFN71aoVwiRWTKE4THZ+NUfDZS8hXn+peUSRRqSLVraYyAyl4bf9eWMBaq9r+8Qm62FmX/1X5PisvQf/lZ7r6HvSl++aB7jTEuz8sWlSJkXwwuJsnqmwV2tMUPI7vCWsnsttJyCT75LQon72SDzwOWvOOJFgZ6cA49WmPbbZN64DWPVxuzQQgBolKfYObumzXyogHA3EA3bDh3H8/KJehga4Jtk3oqJJnMf1qdS+zLoR5K9z+mhyPc7Uzx8a83kVEgS9dRViHF1B2R2DXFt9EvC1Mwo2X0BXz4u7aEv2tLfD28I+7nFlf22GQj8uETPF9pKyW/BCkRD7Ez4iGEAj56OlsioINsILEqCoHlyn3IOzpQXg9tVlJWgbfXXeKyiloY62P/DH8I9erOX3EsNgsL/ryFgpJyGOrz8c3wThjv56T0s1ZYUo6pO6/jesoTCPX4eMPTQenlpA0fdK8xbZsQ0nDJecX4zz9xOJOYW+Oxn8Z4IUtUytVb6u9mg7XjfGBmqNjzIt9bOj3ApdbX8nK0wD+f9MVne6O4ws3PyiX4YOtV7Jvu36g/eCmY0WI8Hg/tbU3Q3tYEM/q7Iv+pGGcScxEen43zd3NR/FzmyDKJFJeS8nEpKR9L/02AnZkB+rvZIMDNBn3bW8PC+NWnf8vnmNG0gcmk/soqpJiw9ZpCls8TcwMUZhQ9r1hcge8O3+EuFXVuZYY17/mgva2J0u2zRaWYsPUaN5W/rEKKP6MyFLZZ+74P3vRq9aqHQwgBcOPhE4z85XKN9WN7OGLRW53wfwfj8MdN2Qzaif5t8X9vdFKafO+sXCD0ol5aqxZChH3ki1Un73IVtkvLpXjr50uNmgeKghkd0tLEAKO6t8Go7m0grpDgyoPHOHVH1muTqaRAWLZIjH2R6dgXmQ4+r2r6ty36u9vAs7X5S03/zpJ7HVtTCma0kVTK8NneKETKTcs8HdK/zv/PmLQCzPk9Gsl5xeDxgGkBLggZ7F5rL8793KeYsPUa1/38vJ/GeOHdbqqdyklIc3It+THGbFQsEmpjaoATcwLAAEzadh3XUh5DwOdh0ZudMKGWAq4xlbOUAFmOqfoQ8Hn4PMgdXo4WmL4rkkuYOHT1BYSH9IerjfIfPA1BwYyOMtATcDOc/vN2Z9x5JEJ4fA5OxWfLyik8R8qAm6kFuJlagFWn7sLCWB/9OsieH9DBGrb17GWR75mhUgbahzGGRYfi8G9sFrfu4Kw+cKnlZCORMmw4dx+rTt5FhZTBwdwQK8d41TnDKDqtACPkZjrI+3GkJ8b2VH2CLUKai7ynYvh9Hw7JcymXD83ug65tLJCUU4TJYZFIfVwCUwM9/Dy+G/rXMbh+cth1brkhOaYAYHAnO4SHDMC4zVe474pBK8/h/PyBDcogrgwFM80Aj8dD51bm6NzKHJ8O6oBsUSnC43MQHp+Ni0l5ECuptFpQUo5/YjLxT0wmAKCjg1n19O+2lrX+4k7Oe8ot21L2X62zJvweVxQVALZP6glvuYKP8tKflGDe7zG4liLLZD3c0wHfv+MJc+PaL0WtPJHITb2W993bnfFhLb8ECSENVyGRYvaeKByLy1L6uFULIS7cy8XHv95EUWkFHK2MsG1iT3SoozgwYwz5xWUAAM+XzLDtbN0C4SH9MX3XDW4cTcDyM69cP01rgpl169Zh+fLlyMrKgpeXF9auXQtf3/p1cRFFlsZCHIzOwLXnyinUJf6RCPGPRNhw7j5aCAXwd7VGf3cbDHCzURjlLt/royuFM5uLHZdTsPpUdX2j5aO61poT4u/oDHxzMBZFpRVoIRTg27e7YGS31rUOKL+Z+gTvrq95rf6b4R0xtV/tAwgJIQ2391oqFjw3kH5IJzusG98Nb669iISsIiz9NwHHYrMgkTL0aGuJjR92f2Gh2P03qjPVrx/f7aXbZyzUw87JvlhxIhHrzsgKwwb+dB73v3/9pbPba8W3ze+//4558+Zhw4YN8PPzw+rVqxEUFITExETY2qomAY8uK3hW1qBA5nnFZRKcqpwaDgB2ZgYY1sUB/d1sFIIZbS+u1pz8HZ2BRYeqE2bND3LH6B6ONbYTlZZj4cFYHIyW9dj5OFlg9VjvWvMZ3U4vVEi2V2XeYDd8OqhDI7WeEALIfnQOW3NBYR2fB1z9KpCra9bJwQwJWUVc0tV3fFrjh5Ge9Uq2+sWBW9yy/I/Yl8Hj8TA/yAPu9mb49LcoWBjro1wihYD/cklftSKY+emnnxAcHMwVONuwYQOOHDmCbdu2YcGCBTW2F4vFEIurpwiLRKIma6s2sDU1xKHZfbDp/APczijEw+dy1TRUtkiMsMspXKp6ol3OJubgs73R3P0J/m3x8YCa2X2vpzzGnL3RyCh4Bj4P+OS1DvjktfZKZzsoO6lWefD96y+cAUEIqb+n4gq8tuIscorECuv3TfeHr7NiPpdOrcy4WYOfD3HDrIHt6/XDs7S8enZsYxaOfMurFYZ1sYe4QvpKtfw0PpgpKyvDjRs3EBoayq3j8/kIDAxERESE0ucsXboU3377bVM1USt1bWOBn8cp7yaUSBlyikpxJ1OEW+mFuJVegEv387l8I/X16W9R+N/7Po3RXKIiNx4+waTt1QP6gjrbYdGbnRVObuUSKf4Xfg/rziRBygBHKyOsHuuN7m1rJr26l12EwavOK32tL4d6YEZ/F+qxI6SRMMbwzcFY/Ho1VWH9F0PdMbO/q9K/tXe7tUH8oyIEdbbDkM71z930/dHqwq4L3+j08o1WQl/Ah76SH0UNofHBTF5eHiQSSY1KrXZ2dkhISFD6nNDQUMybN4+7LxKJ4OhYs8ucKCfg8+BgbgQHcyMM6lgz22qFRIrIh0+wLzINf97MULIHmUMxmehga4JP6HKCRrqbXaSQc6KbkwXWvOejcM06Oa8Yc36P5qZjvtutNb59q3ONfDMPcp8qlDyQx+cBP4zsijFKLlsRQl7OsdhHChXsAaBHW0vsCe5VZ2JLqxZCrBzj1eDX2xlRPTHASKje+n/KaHww8zIMDAxgYEAzaVRFT8BHL5eW6OXSEj+N8UaxuALGQgF4PB6kUgaXr6rT0K88eRcFz8rx9esd6dKCBkl7XII31laPZXG0MsL2j3y5bl7GGPZHpmPxP3EoKZPAzFAPS97xrJHALjW/BAHLz9T6Oob6fKwb101pUEwIabja/uYuL3gNrSyMVPKa8vmglsoVldQkGh/MWFtbQyAQIDs7W2F9dnY27O0pvbkmaCE3a4nP58HNzoSrkAwAWy8mI7dIjOWju6q9ojeR5Z0YvSGCu2xoLBRg33R/rljck+IyfPXXbS7XjJ+zFVaN9VY4UWYUPEPfH0/XKJ/Rr4M1Mgue4X5uMcyN9LFtUg+ll6MIIQ0jrpDg7Z8vISGrSGH99o96Ki3e2phm76nuAXqvp2b2sGp8MCMUCtG9e3eEh4djxIgRAACpVIrw8HDMnj1bvY0jSg3tbI+72Yq5RA7FZCK/WIwNH3SvMyU+Ua2i0nJ8sOWqQnG5v2f1gYO5LFC5lJSHefuikS0SQ4/PQ8gQd0wLcOEuPWUVlqL/8jM1chON8G6FGQNc8dH263hUWAoHc0PsnOxbZ84KQkj9/HQiUaFKNSDLsh06zKNJxqBFpRYAkBU91tQxbxofzADAvHnzMHHiRPTo0QO+vr5YvXo1iouLudlNRLN4O1koXX8pKR/vbbqC7R/1pFIHalBaLsHksOsKv+wOzPBHBztTiCskWHE8EZsvJAMAXGxaYM1YH3i2kSXGyikqReDKcxCVVijsc7inA9a8542Y9EKM3XgFhc/K0d7WBDsn+6qsy5uQ5uJyUh7GbbmqsM7FugWOftbvlWb+NLQNVbZ/1LNJXvNlaEUwM3bsWOTm5mLhwoXIysqCt7c3jh07VmNQMNEMXnVUQo3LFGHkL5exc7IfnK2V5yYhja9CIsWsX2/iekp1vaUdk33Ro50V7mUX4dO90Yh/JEthMN7PCV8P7whjoR7yn4oRtPo88p6WKexvkIctNnzYHfoCPk4nZOPjX2+itFwKHycLbJvYE5YtXr1oKSHNmbJs2adD+tdaWkRVJmy7xi13c7Js0tduCK0IZgBg9uzZdFlJS7Q0MYCTlbFCxWV5aY+fYeQvl7F9Uk941ZIqnzQexhi+/OM2whNyuHXbP+qJgA7W2BmRgiVH4iGukMKqhRA/juyKwZ3sUFBShsE/na5RCLJfB2tsmdiDG/t04EY6vvzjFiRShoHuNlg3vhuMhVpzWiFEY92QK/T6v/d98JYaqsdLpQwVlTWd+ravvd6aJqCzDlEJHyeLWoMZAHhcXIb3N1/B+vHdMEDFg9eau6X/JuCPm9VpyLdP6okurcwxOew6ziTmAgAC3GywonKA9sAVZ5GcV6ywD19nK+ycrDjbaeP5B/jhX1l6hJHd2uCHkZ6vnCtC1colUmQ8eYbk/GKk5pfA3d4UvVxaqrtZhNSw9n0f3Mt5Cj9nK7WNU9l2KZlbXjXWWy1tqC8KZohKeDta4O/KlPfKdHQwQ/wjEabuiMSyUV3xbrc2Tdi65uOXs/ex6fwD7v7WiT3AwDB09XnkF5dBqMdH6DAPjOreBqM3RNSYKeHtaIE9wX4KvS1SKcP3R+Ox5aLsRDe9vwsWDG2agYj1UVYhRfqTEqTkFyMlrwQP84uRnC/7N/3JM4XqwWaGeohZNERj2k5IlZYmBi+slaRq/z1SnSjPRsMLB1MwQ1SiqtJyC6EARkI95D1VTLNtoMfHm16t8E9MJubti0FOkRjTAyg7bGPadz0NPx6rTiz58zgfnLubyyW/8rA3xdJ3PbHoUBy+/eeOwnM7Ophh/wz/GsVCyyqk+OJADFebSV2FIsUVEqQ9foaUvGKk5BfjYX5l8JJfjIwnzyBldT+/tYURPOxN8aZXK/rMEaJEUWk5tzxTSXkTTUPBDFGJTq3MIBTwUVwmweueDgrVVgEgOq0AfdtbI7ifMzZfSMYP/yYgRyTGN8MpuV5jOBabhS/+qC4KNyewA1afuoekHFn+n3F+TojNKMQ7z1WydrVpgb9m9YGZkunzxeIKzPz1Js7fzYUen4flo7viHR/V9aiVlkuQ9rgEKfklCkFLcl4xMguf1chxo4yJgR7c7U3hUXVzMIObnSmXU4cQotw3B2O55XmD3dTYkvqhYIaohIGeAJ1amSE6rQCdW5nhn1t8lJYr5ib5+UwStk+STdNecjQe2y4lI6eoFCvHeFFyvVdw+X4eZuy+wd3v3tYS684koVzCYGGsj4KScux5rpZLG0sjHP6kLyyMlc9Cyn8qxuSw64hJL4SRvgC/fNA4Y51KyyXVvSp5xUipvBz0ML+k3gELICuZ4GJjAnd7U3S0N4WHvRnc7U3RxtKIel4IeQnywwQ0fSwcQMEMUSFvRwtEpxUgJb8Eo7s7YteVh+jR1hKRcqP0Pwq7jn9m98Wa97zx+f4YHL71CI+Ly7DxQ0qu9zJiMwoxbrNiXgr5WREFJeUKj9maGuDYnABY1TGVOv1JCSZsvYYHecWwNNbHtkk94dOAKZolZRV4WBmkPN/L8qiw9MU7eI61iQE6Osh6WtztzeBhb4r2tiZNlneDEF2XlFM9dm5dLQWJNQ0FM0RlfJwsEHYZiEorwJqx3th99SEiHz7B/hn+GL2huuL5mz9fxM/jfLBtUk/M2HUDl+/nY+zGKwj7qCdszSi5Xn09yH2qUG+pLhbG+jg5t/8LB/UlZIkwcds1ZIvEaG1hhB2TfdHetmaei2JxheLYFblelmyRWMmeX8xAjw93e1O428kuD8mCF1NYq3lQJCG6btrO6p7d4V0d1NiS+qNghqiMj6Ps13t8pggOFoYY3NEOJ+5k48+bGdg1xRcfbq1OxjR7TxTe9WmNTRN64LO9UbjzSIR3f7mMnZN9mzxJlDbKKiyttWq1PCN9Ac58PgD25i8OEq8lP8aUHddRVFoBdztTrBvfDaXlEhy+lcmNXanqbcktermApYqTlbHCuBZ3e1O0a9lCoYI3IaRpPKhMzeBkZazmltQfBTNEZRytjGDVQojHxWWIyxQhOMClMphJx+dD3PBhr7bYdaW6rPyfURm4dD8Pnw7qgK0Xk/EwvwSjNkRg26Se3OwoUlNBSRl6LQ2vcxs+D7jw5Wto/YISA6LScjzMK8HmCw9wKKb6mvmDvKcI/OnFwdKLmBvpV49rqQxa3OxMa8yaIoSox7HKArMAsGViDzW2pGHoDEJUhsfjwdvRAqcTchCdWoCP+rSDl6MFYtIKsOvKQ4S+7oEL93KRkl+dXC9bJMbCv+MQ2NEOAh4PD/KK8f6mK1j/QTeVV4ZVlXXr1mH58uXIysqCl5cX1q5dC19f30bZd0lZBbz/c7LObc7PHwinltW/sApLyrlpzNV5WGSXiB4XlyndR7mkniNxK+kLeHC1Make11I5xsXezJAG5BKiweQnD7hpUaFYCmaISvlUBTNpBeDxeAju54zZe6KwM+IhZvR3xcoxXhj5S0SN552Kz4aFsT6Eenw8K5dg6o5I/DiyK0Z1167ker///jvmzZuHDRs2wM/PD6tXr0ZQUBASExNha/tqwVlZhRSdFh6v9fGfxniBxwP+uJkuC1jyinEro7DeM4Tqy8HcsHL6s1nlZSJTuFibQKin+TMgCCHVKiTVM061ZaxMFQpmiEpVVdCOSpPNqBna2R6tLYyQUfAMf97MwDg/J8zo74oN5+5zz7E1NYCBPh9pj6vrAkmkDJ/vj0FukRgz+mtPcr2ffvoJwcHBXIX3DRs24MiRI9i2bRsWLFjw0vuVSBncvvm3zm3m7Yt56f0rYywUyOVsqR6QW9t0bkKIdlkTfo9b/v4dTzW2pOEomCEq1bWygnba42fIfypGSxMDTO7rjO8O38GWiw/wXk9HzB3cAWcTc7hU+jlFYswPckdmwTP8+lw+lB+PJSBbVIqFb3TS+OR6ZWVluHHjBkJDQ7l1fD4fgYGBiIio2RsFAGKxGGJx9WBakUikdDvXr442bmNrMW+wW+UYFzO0sTTS+PecEPLy5Kt0a1tiSeoHJiplbqTPTeWNTisAAIzt6QhTQz08yC3GmcQcGOgJsHKMF/QF1V+Uq0/dxcjubbBrii9aPTfzJuxyCj7ZGwVxhaTJjuNl5OXlQSKRwM7OTmG9nZ0dsrKylD5n6dKlMDc3526Ojo5N0VROvw7WcLZuwd1PzCpCj7aWcGppTIEMITpMvuTMgmEeamzJy6Fghqhc1UykqNQCALIU8+N8nQAAmy/IiiB2bmWOzwZ14J5TLmGY9etNdG5ljmNzAzD6ubEyR249wqRt1yEqVUwCp+1CQ0NRWFjI3dLS0pRu917Pxg1yWggF2D3FD7um+OH4nAB8OqgDBHwejtx+hCGrzuNY7KNGfT1CiGYJkbssPU0N9dZeFQUzROWqgpmqnhkAmNSnHfT4PFx58BixGYUAgBn9XRWmYD8qLMWCP27BzFAfy0d7YevEHgpJ3iIeyJLr5YgankW2KVhbW0MgECA7O1thfXZ2Nuzt7ZU+x8DAAGZmZgo3ZeR7Sc7NH4DVY73h285KYZs2lkaY2tcZ2z/qiY0fdsfiNzthWoAL3ujqgG5OFnAwNwSfJ9tu7zR/9O1gDQAQ6vExb7AbDn7cB+52psgvLsOM3Tfx6W9ReFLLbCdCiHY7dzeXW9bGXlgKZojK+VQOAo5JK4C0spyxg7kR3qgcLV/VO6Mn4GPlGC8Y6ld/LE/cycbxONklmUEd7XBybgDe9m7FPR7/SIR31l/G/dynTXEoDSIUCtG9e3eEh1fngJFKpQgPD4e/v/8r7VtP7mSjL+BjhE9r7JvhjxNzAzCpdzuYGuoh/ckzbLmYjGk7I3EoJhNu9qYIHeaBn8d1w58f90FE6CAk/ncYLnwxEJ5tzGu8hmcbcxz6pA9mDXQFnwccisnE4FXncSJO+SUyQoh2ipH7oblrSuOkjWhqFMwQlXO3M4WxUIAicQUu38/n1k+t7Mo8fOsRMgtkM5dcbUzw5VDF67WLD8XhqbgCAGBhLMSa93yw4YNuaFlZTyij4BlG/XIZUalPoGnmzZuHzZs3Y8eOHYiPj8fMmTNRXFzMzW56WXy52VzyM63d7Eyx+K3OuPZVIJaP6gpvRwuUSxiO3HqEcZuvYtDKc9h8/gHXw6Iv4Nc5M8xAT4D5QR746+M+aG9rgrynYkzbdQPzfo9GYYluXeIjpLmaHHadW+7XwUaNLXl5FMwQldMT8DGmh2yMx4oTiWCViU66tDaHv0tLSKQMYZdTuO0n+reDv0tL7v6jwlKsPJGosM+hXRxwfG4AhnWRXa55UlKOcZuv4nSC4iUddRs7dixWrFiBhQsXwtvbG9HR0Th27FiNQcENJZ/mv6q3S56RUIDRPRxxcFYfHPm0L8b7OaGFUIAHecVYcjQefkvDMWdvFK6nPOb+P+ri5WiBw5/0xYz+sl6aP6MyMHjVOY17vwkhDcMYQ37ljxvP1jV7aLUFBTOkScwa2B5G+gJEpxXgVHwOtz44wBkA8NvVVBRVDubl83lYPrqrQor7HZdTcCu9QGGf1iYGWD++G9a85w1zI308K5cgeOcNRKY8Vv0BNcDs2bPx8OFDiMViXL16FX5+fq+8T70GXNPu3MocS97xxNWvA/H9O57o3MoMZRVSHIzOxOgNERiy6jzCLiWj8FndPS2G+gIsGOaBAzN7w8WmBXKKxJgcFonP98e88LmkaaSkpGDKlClwdnaGkZERXF1dsWjRIpSVKY51unXrFvr16wdDQ0M4Ojpi2bJlNfa1f/9+eHh4wNDQEJ6enjh6tGnSAZCmtf9GOre8frx2VMhWhoIZ0iRsTA3wUZ92AIAVxxO53oQBbrZwtWmBInEFfr9ePXOnjaUxFr7ZibsvZcBXf91WyFAJyEomvO3dGifnBiCwoy0YYzo3w0kZ+QF60nqm9DUx0MM4Pycc/qQv/p7VB2N7OMJIX4B7OU+x+J878Pv+FObvj0FU6pM6e2u6OVni6Kf9ENzPGTwecOBGOoJWncfZxJxan0OaRkJCAqRSKTZu3Ii4uDisWrUKGzZswLfffsttIxKJMGTIELRt2xY3btzA8uXLsXjxYmzatInb5vLly3j//fcxZcoUREVFYcSIERgxYgRiY2PVcVhEhb44cItbdtSiwpLP47H69DFrOZFIBHNzcxQWFtY6O4SoXmFJOfouO42i0gqsec8bb3u3BgD8di0VoX/eRmsLI5ybPwB6AlmMzRhD8M5IhZ6c/3ujE6b0da71NUrKKmAsVE0uSHV8jmp7zRXHE/HzGVmCq7OfD0A7udwwDdp/aTkORmXg1yupSMwu4tZ3cjDDOD8njPBpXWcRyMiUx/h8fwxXX+u9no74enhHmBpqV8ItXbZ8+XKsW7cODx8+RGFhIX799Vd8/fXXyMrKglAoG3e2YMECHDx4EAkJCQBkl0eLi4tx+PBhbj+9evWCt7c3NmzYUK/XpfOu5istl8Dj/44BAMb5OWlk1t/6fo6oZ4Y0GXNjfczo7woAWHXyLsore1ne8WkNaxMhMgqe4V+5iq08Hg9L3+0KqxbV6fJXnkjkBgsro6pARtPI98y8yq8RM0N9TPBvh2Nz+uGPmf5416c1hHp83HkkwjcHY+G35BRC/7zNTZ9/Xo92Vvj3swB81KcdeDxg7/U0BK06jwv3cpVuT5peYWEhLC0tufsREREICAjgAhkAXL2wJ0+ecNsEBgYq7CcoKKjWzNWALHu1SCRSuBHNtuRIPLe88I1OdWyp+SiYIU1qUu92sDYRIiW/BAcqr9Ua6gvwYa92AIAtFx4oXOKwMTXAkhFduPslZRIs/DuuXoNWdZneS1xmqguPx0P3tlb4aaw3rn01CN8M7wgXmxYoLpPgt2upeGPtRbz980Xsu56GkrIKhecaCQVY9GZn7A3uBScrY2QWluLDrdfw1V+3uVloRD2SkpKwdu1ahdlzWVlZSrNSVz1W1za1Za4G1J+9mjTcrisPuWVDfYEaW/LqKJghTaqFgR4+HtAeALDm1D2UlstKEnzQywkGenzEpBfieoriFOthng4YIZdb5lR8No7HNe9ZNPKzmRo7rrMwFmJqPxeEz+uP34J74U2vVtAX8BCTXogv/rgFvyXhWPR3LBKzihSe5+fSEsfm9MNE/7YAgD1XUxG06jwuJ+U1bgOboQULFoDH49V5q7pEVCUjIwNDhw7F6NGjMWnSJJW3sb7Zq4lmSH9Swi0vfVfzLi81FAUzpMmN83NCK3NDZIlKsbvyl0FLEwOMrCxZUJVET963b3WBvVl1jabFh+K42U/NEV8hN4xqeql4PB78XVti7fs+iAgdhAXDPNC2pTGKxBXYEfEQQavPY9Qvl/HnzXQuKDUW6uHbt7tgT7Af2ljKqqOP23IVC/+ORTH10ry0kJAQxMfH13lzcalOQZ+ZmYmBAweid+/eCgN7AcDe3l5pVuqqx+raprbM1UD9s1cTzTB7TxS33NjlUdSBghnS5Az1BfgsUFaHaf3Z+9yliKqBvafis/HguYy+5sb6+HFUV+5+lqgUK0/cbaIWax6B3F+ukjQzjc7axAAz+rviTMgA7Jrii2Fd7CHg8xD58Anm7YtBr6Xh+O7wHS4Tc29XaxybE4DxfrIaXDsjHmLYmgu4+iC/rpchtbCxsYGHh0edt6oxMBkZGRgwYAC6d++O7du3g89XPM37+/vj/PnzKC+v/jFw8uRJuLu7c2Nr/P39FTJXV23zqpmrieaoKi9jbqRfZ+JMbUHBDFGLkd3awNm6BR4Xl2HbxWQAsuy/sunVwNbKdfL6u9lwX46ArHq2fBru5kQg9wXVlMOH+Hwe+nWwwS8fdEfEgtfw+RA3tLYwQkFJObZeTMaglefw3qYIHIrJhL6AhyXveHKVz1Mfl2Dspiv49p84PCvT7Irn2qoqkHFycsKKFSuQm5uLrKwshV6WcePGQSgUYsqUKYiLi8Pvv/+ONWvWYN68edw2n332GY4dO4aVK1ciISEBixcvRmRkJGbPnq2OwyKNTP7Sb9hHPdXYksajsmBmyZIl6N27N4yNjWFhYaF0m9TUVAwfPhzGxsawtbXF/PnzUVGh2BV99uxZdOvWDQYGBmjfvj3CwsJU1WTShPQEsmKGALD5/AMUlMiSelWVODhwIx2PlRQ1/Or1jnCSy4UQ+mfN3DPNgUDuhxRT0WWmF7E1M8Ts1zrg/BcDsW1SDwR2tAWfB1x58Bif/haF3ktPY+m/8XCyMsbxuQFcV/b2SykYtuY8rmtYckNdcPLkSSQlJSE8PBxt2rSBg4MDHBwc4Obmxm1jbm6OEydOIDk5Gd27d0dISAgWLlyIadOmcdv07t0be/bswaZNm+Dl5YUDBw7g4MGD6NKli7KXJVpmwrZr3LKPk2UdW2oPlQUzZWVlGD16NGbOnKn0cYlEguHDh6OsrAyXL1/Gjh07EBYWhoULF3LbJCcnY/jw4Rg4cCCio6MxZ84cTJ06FcePH1dVs0kTGu7pgI4OZigSV2DDOdk4GT9nK3i2Noe4QsqNp5HXwkAPK8d4cffvPBIplEJoLhTLGaixIZC15TUPO2yZ2BMXv3wNnw7qADszA+QXl2HjuQfov/wsPv71Jga422DrxB6wNzNESn4JxmyMwH8P3+HG25BXN2nSJDDGatwKCxWn1nft2hUXLlxAaWkp0tPT8eWXX9bY1+jRo5GYmAixWIzY2Fi8/vrrTXUYRIWkUoaKymvT/TpYq7k1jUdlwcy3336LuXPnwtNT+SjpEydO4M6dO9i9eze8vb0xbNgwfPfdd1i3bh2XenvDhg1wdnbGypUr0bFjR8yePRujRo3CqlWrVNVs0oT4fB4+HyL7xRh2ORk5olLweDxM7ScbO7MzIkXpF13PdlaYHlA92PG/R+IVRuY3BwqXmdTUM6NMKwsjzBvshktfvoaNH3ZHfzcb8HjAhXt5mLH7JkL/vI2gznbo7doSjAFbLibj9TUXcFMDi4QSoovkL+H/NMZbfQ1pZGobMxMREQFPT0+FXAZBQUEQiUSIi4vjtmlo4iaAkjdpk9c8bNHNyQKl5VIuo+3rng5oZW6IvKdl+Ds6Q+nz5g52QwdbE+7+omaWe0Z+ALAmHraegI+gzvbYMdkX5+cPxMcDXGFtIkROkRg7Ih4i4kE+DPRkB/EgrxijfrmMpf/GUy8NISq25Gh1ojwbUwM1tqRxqS2YeZXETSKRCM+e1Z4FlpI3aQ8ej4f5QR4AZGUN0h6XQF/Ax0d9ZL0zWy4kKw1SDPUFWDXWm7sfnpCDY7G1J/TSNfJTszUxmJHnaGWML4Z64PKCQVg3rhvXKyOuqL4+JmXAxnMP8Mbai812UDchqiafzuLjAa5qbEnja1Aw8zKJm9SBkjdpF3/XlujXwRrlEoY14fcAAGN9HWFioId7OU9x9q7y1PhdWptzg4gBYOavN5tFkUnguaR5GnSZqS5CPT6Gd3XAnuBeOB3SH8H9nGFprFjDKSnnKd5ZfwnLjiVAXEG9NIQ0pq//qi4UOlfu3KkLGhTMNDRxU11eJXGTmZkZjIyMat03JW/SPiFD3AEAf95MR1JOEcwM9bnZL1uUJNGr8vEAV3jYm3L3VxxPVG1DNYTCAGDtiGUUuNiY4OvhnRAROgirx3rDt50V95iUyfIPvbX2Em6nK68JRQhpuEMxmdyyvkC3MrM06GgakrjpRfz9/XH79m3k5FRXRD558iTMzMzQqVMnbhtK3NQ8eDtaYEgnO0gZ8NNJWTK8j/o6Q8Dn4VJSPuIylX+p6Qn4+HlcN+7+zoiHiGoGg0kVyxloYTRTyVBfgBE+rbFvhj9OzA3ApN7tYGooKxaamF2EEesv4VoyTeEm5FXdy64uP7JO7pypK1QWmqWmpiI6OhqpqamQSCSIjo5GdHQ0nj6VZQgdMmQIOnXqhA8//BAxMTE4fvw4vvnmG8yaNQsGBrJBSTNmzMCDBw/wxRdfICEhAevXr8e+ffswd+5cVTWbqFHIEHfweMDR21m4nV6I1hZGeN3TAQCw9ULNJHpV2tua4P/kKr5+sOUqV5FbVwl4jVM1W5O42Zli8Vudce2rQCwf1RXejhYA0CzzCBHS2KbtusEtD+/qoMaWqIbKgpmFCxfCx8cHixYtwtOnT+Hj4wMfHx9ERkYCAAQCAQ4fPgyBQAB/f3988MEHmDBhAv7zn/9w+3B2dsaRI0dw8uRJeHl5YeXKldiyZQuCgoJU1WyiRu72phjh3RoAsOKE7HJRcOU07UMxmcgqLK31uR/1bgc3O9nspuIyCbbUEfzoAl3pmVHGSCjA6B6OODirD+79dxh6t9edXBiEqEtyXjEAoG1L4xdsqZ1UFsyEhYUpTd40YMAAbpu2bdvi6NGjKCkpQW5uLlasWAE9PT2F/QwYMABRUVEQi8W4f/9+k1R/JeozJ7AD9Pg8nLubi2vJj9G1jQV8na1QIWV1Jsfj83nYOrE6LfePxxKQ9lh3c8+osmq2JuHztb9mDCHqJj/Tc/OEHmpsiero1gggovXatmyBMZUDf5cfTwBjDMGVJQ72XH1YZ+VlRytj/DiyOknje5uu6FyvRRU+X/cuMxFCVGPG7upLTG52pnVsqb0omCEa59PXOkCox8f1lCc4dzcXgzxs4WLdAqLSCuyLrHua/ZgejnC2bgEAyCh4pjB6X5fIj5mRauN0JkJIk5Afc6aLY2WqUDBDNI69uSEm+rcFACyvnGo9pXLszLZLyZDU8eXN4/Hw+/Re3P3P9kbrZO4ZPeqZIYTUw+pT97jlpe8qLy+kCyiYIRpp5oD2aCEUIC5ThGNxWRjZrQ2sWgiR9vgZjsfVnenX1tQQq8ZWF6P8YMtVVTe3yfEV8sxQOEMIUa6qTAwAmBnq17GldqNghmgkqxZCTK0cK7PyRCL0BXx80EvWW7Pp/IMXjoV5x6cNV3fkVnohLt/PU22Dm5j8AGDqmiGEKJP3VMwtLxjmocaWqB4FM0RjTe3nDAtjfdzPLcZfURmY4N8WQj0+otMKcOPhixPjnZwbwC2P26xbuWcEdJmJEPIC8/bFcMvT+tUvO7+2omCGaCxTQ33M7C8rhrbq5F2YGurhXR9ZHprNdZQ4qGJhLFS43DR1R6RqGqoGCgOA6TITIUSJ85V17Xg83U9zQMEM0WgT/NvB1tQAGQXP8Pv1NEytHAh84k42UiqTQNXlHZ82EOrJPubn7ubiTqZIpe1tKs0lzwwh5OXIV5/fNdlPfQ1pIhTMEI1mJBTgk0EdAABrTyehtYUxBrrbgDHZzKb6uPl/g7nl1/93QSdyz/B1sJwBIaTxTA67zi337aD7WbQpmCEab2wPRzhaGSG3SIwdESlcEr39kekoKCl74fNNDPTwg9yURPnryNpKT0CXmQghyjHGkF8sOzd2bWOu5tY0DQpmiMYT6vExZ5AbAOCXs/fRubU5OjmY4Vm5BL9eTa3XPt7zdeKW/4rKUEk7m5J8zwx1zRBC5O2PTOeWdbFCtjIUzBCtMMKnNdrbmqDwWTm2XniA4ADZ2JmwyykQV0jqtY9bi4ege1tLTO+v/aP6BZRnhhBSiy/+uMUtO1rpZmHJ51EwQ7SCgM/D50NkvTNbLibD38Ua9maGyC0S41B0/UoWmBnq44+ZvRE6rKMqm9ok9GgAMCFEidLy6h934/yc6thSt1AwQ7RGUGd7eLY2R0mZBJsvPMCkPu0AAFsvJuvEoN6GoEKThBBllhyJ55YXvtFJjS1pWhTMEK3B4/EwP8gdALDrykMMdLdFC6EACVlFuHBPtzL8vgjlmSGEKLPrykNu2VBfoMaWNC0KZohW6dfBGr7OViirkCLscgrG9HQEUL8kerqEL/eXS7EMIQQA0p+UcMu6XFRSGQpmiFaR753ZF5mG1zxswecBF+7lISFLNxLi1YeeXDRDPTOEEACYtSeKW36v8odec0HBDNE6PdtZYaC7DSRShgM30jGsiwMAYMuF+iXR0wXyl5kqpBTMEEKqs/5aGOuDx9Pt8gXPo2CGaKWQIbLemUMxmehXmd3y7+gM5IhK1dmsJiN/mUki1Z0CmoSQl3MpqXrc4PZJPdXYEvWgYIZopS6tzTG8qwMYA07F56BnO0uUSxh2RKSou2lNQv4yU7mEemYIae4mbLvGLfs4WaqxJepBwQzRWnMD3cDnAafis9GjnRUAYPeVVJSUVai5Zaon3zNTQcEMIc2aVMogqbzc3K8Z1GFShoIZorXa25pgZLc2AICo1Cdo19IYhc/KFVJ56yrFMTN0mYmQ5mzrxerxgqvGequvIWpEwQzRap8FdoC+gIcrDx6jo4MZANkftuQVB8UuWbIEvXv3hrGxMSwsLJRuk5qaiuHDh8PY2Bi2traYP38+KioUe4XOnj2Lbt26wcDAAO3bt0dYWNgrtauKfDkDusxESPO25Gh1ojxrEwM1tkR9KJghWq2NpTHG+7UFACTnFcPCWB+pj0tw8k7WK+23rKwMo0ePxsyZM5U+LpFIMHz4cJSVleHy5cvYsWMHwsLCsHDhQm6b5ORkDB8+HAMHDkR0dDTmzJmDqVOn4vjx46/UNgAKMxVoADAhzZeotJxbnjnAVY0tUS8KZojW+3igK4z0ZZmA7c0MAQCbX3Ga9rfffou5c+fC01N54qkTJ07gzp072L17N7y9vTFs2DB89913WLduHcrKygAAGzZsgLOzM1auXImOHTti9uzZGDVqFFatWvVKbXse9cwQ0nx9/VcstzxvsJsaW6JeFMwQrWdrasjVacotEkOPz8ONh09wM/WJyl4zIiICnp6esLOz49YFBQVBJBIhLi6O2yYwMFDheUFBQYiIiKh1v2KxGCKRSOH2Iq96SY0Qor3+iakutKsvaL5f6c33yIlOmR7gAlNDPeQXl3HjSbaosMRBVlaWQiADgLuflZVV5zYikQjPnj1Tut+lS5fC3Nycuzk6vjiLZ4WELjMR0hwl5RRxy+vHd1NjS9SPghmiEyyMhZge4AIAEFfIvtyPxWYh7XF1rZIFCxaAx+PVeUtISFBL+6uEhoaisLCQu6Wlpb3wOeXUM0NIszRt5w1u+XVPBzW2RP301N0AQhrLR32csf1SCvKLZWNWpEw2s2nxW50BACEhIZg0aVKd+3BxcanXa9nb2+PatWsK67Kzs7nHqv6tWie/jZmZGYyMjJTu18DAAAYGDZuNQJeZCGmeHuQVAwDatTRWc0vUT2U9MykpKZgyZQqcnZ1hZGQEV1dXLFq0iBscWeXWrVvo168fDA0N4ejoiGXLltXY1/79++Hh4QFDQ0N4enri6NGjqmo20WItDPQwa2B7hXX7ItNQWCIb7W9jYwMPD486b0KhsF6v5e/vj9u3byMnJ4dbd/LkSZiZmaFTp07cNuHh4QrPO3nyJPz9/V/lMGugpHlEGbFYDG9vb/B4PNy6dUvhMTrvar9jsY+45c0TeqixJZpBZcFMQkICpFIpNm7ciLi4OKxatQobNmzAV199xW0jEokwZMgQtG3bFjdu3MDy5cuxePFibNq0idvm8uXLeP/99zFlyhRERUVhxIgRGDFiBGJjY5W9LGnmxvk5wcHckLtfUibBnmupDd5PamoqoqOjkZqaColEgujoaIUvhCFDhqBTp0748MMPERMTg+PHj+Obb77BrFmzuJ6VGTNm4MGDB/jiiy+QkJCA9evXY9++fZg7d+6rH6gcSppHlPniiy/QqlWrGuvpvKsbZuy+yS13sDNVY0s0BGtCy5YtY87Oztz99evXM0tLSyYWi7l1X375JXN3d+fujxkzhg0fPlxhP35+fmz69On1ft3CwkIGgBUWFr5C64m2+O3qQ9b2y8PczXfJSSYulzRoHxMnTmQAlN6qPkcpKSls2LBhzMjIiFlbW7OQkBBWXl6usJ8zZ84wb29vJhQKmYuLC9u+fXuD2lHXZ7fq+Bb8catB+yS67+jRo8zDw4PFxcUxAOzChQvc54jOu9qvrELC/f1//OsNdTdHper7OWrSAcCFhYWwsrLi7kdERCAgIEChaz8oKAiJiYl48uQJt01TTG8lumNk9zZwtm7B3c8WiXH4VmYdz6gpLCwMjDGFW2FhocI2bdu2xdGjR1FSUoLc3FysWLECenqKw9AGDBiAqKgoiMVi3L9//4Vjdl4GzWYi8rKzsxEcHIxdu3bB2LjmWAo672q/1afucstL31WeC6u5abJgJikpCWvXrsX06dO5da8yvbXqcWVeZnor0R36Aj7mPpc8avOFZDCmm2NLKmgAMKnEGMOkSZMwY8YM9OihfBwFnXe137oz97llM0N9NbZEczQ4mHmZ6a0ZGRkYOnQoRo8ejeDg4EZrfG1eZnor0S1veDrAw776OnL8IxEu389XY4tUh4IZ3Vff8+7atWtRVFSE0NDQJm8jnXebRt5TMbccOsxDjS3RLA2emt3Q6a2ZmZkYOHAgevfurTDADKh96mrVY3VtU/W4Mi8zvZXoFj6fh8+HuGPqzkhu3eYLD9CnvbUaW6UadJlJ99X3vHv69GlERETUOP8NGDCAW6bzrnabty+GWw7uV79UEs1Bg4MZGxsb2NjY1GvbjIwMDBw4EN27d8f27dvB5yt2BPn7++Prr79GeXk59PVlXWUnT56Eu7s7LC0tuW3Cw8MxZ84c7nmqmN5KdM+gjrbwcbJAVGoBAOBsYi7uZhfBTcdG/lPPjO6r73n3f//7H/773/9y9zMzMxEUFITt27djwoQJAOi8q+3O380FAPB5sh9tREZlY2YyMjIwYMAAODk5YcWKFcjNzUVWVpbCNddx48ZBKBRiypQpiIuLw++//441a9Zg3rx53DafffYZjh07hpUrVyIhIQGLFy9GZGQkZs+eraqmEx3B4/EwP8hdYZ0qSxyoC/XMkCpOTk7o0qULd3Nzk40dc3Z25rah8672ik4r4JZ3TvZTX0M0kMqCmZMnTyIpKQnh4eFo06YNHBwcuFsVc3NznDhxAsnJyejevTtCQkKwcOFCTJs2jdumd+/e2LNnDzZt2gQvLy8cOHAABw8eRJcuXVTVdKJDertao6/cpaWDUZnIKSpVY4saH/XMkIag8672mhx2nVvu20H3Lpm/Ch7T1SkeckQiEczNzVFYWAgzMzN1N4c0sei0AoxYd4m7/8lr7REyxL2OZyinjs9RXa/ZbsERAIC/S0v8Nq1Xk7SHaCdN++yShmOMwTlUloXZq405/p7dV80tahr1/RxRoUmi87wdLTC4U/U0091XHuJZmUSNLWpclAGYEN23L7J6dtjP45p3hWxlKJghzULIEDfwKsfKPSkpx4Gb6eptUCMqp9pMhOi8L/+4zS07WlFhyedRMEOaBQ97M7ztVV2nZtvFZEh1ZKwJVc0mRLeVllf3JI/3c1JjSzQXBTOk2ZgT6Aa9yqmMyXnFOBWf/YJnaIdyms1EiE7775E73PL/vdFJjS3RXBTMkGajnXULjOlZnWJ9y4VkNbam8dBsJkJ02+4rqdyyob5AjS3RXBTMkGblk9faQ6gn+9hfS3mMGLm8DdqKLjMRorvSn5Rwyz9QUclaUTBDmhUHcyNM6NWWu79ZB5Lo0WUmQnTXrD1R3PLYnlS8szYUzJBmZ+YAV7QQyrpq/43NUvjlo40qaDYTITqrqvfY0lgfPB6VL6gNBTOk2WlpYoAplQXaJFKG7ZdS1NugV0RjZgjRTZeS8rjl7R/5qrElmo+CGdIsTe3nDAtjWZG936+nQVRaruYWvTxKmkeIbpqw7Rq37O1oob6GaAEKZkizZGaojxn9XQEAT8UV2Hst9QXP0FwSusxEiM6RShk3uL8f1WF6IQpmSLM10b8dbEwNAADbL6Vo7UDacuqZIUTnbLlYPTnhpzHe6muIlqBghjRbRkIBPn2tPQDgUWEpjt5+pOYWvRwaAEyI7vn+aAK3XPWji9SOghnSrI3t6YQ2lkYAZNO0tbGIPA0AJkS3yI/h+3iAqxpboj0omCHNmlCPj7mBbgCA2AwRIh7kq7lFhJDm7qs/q4tKzh3spsaWaA8KZkizN8KnNdrbmgDQnRIHhBDtdfhW9SVvfQF9TdcHvUuk2RPweQip/PVzOiEHSTlFam4RIaS5kj///DK+mxpbol0omCEEwNAu9vBsbQ4A2HqRemcIIeoRvPMGtzzM00GNLdEuFMwQAoDH4+HzIHcAshIH2sDJyljhX0KI9ssseAYAcLFuoeaWaBc9dTeAEE0R0MEaX7/eEUaVdZs03a9T/bDp/ANM7ees7qYQQhrJ1ok9cTYxh/txReqHghlCKvF4PAQHuKi7GfXmaGWM70Z0UXczCCGNqG8Ha/SljL8NRpeZCCGEEKLVKJghhBBCiFajYIYQQgghWo2CGUIIIYRotWYxALiq3o5IJFJzS4g2q/r8NGX9JvrsksZAn12irer72W0WwUxRkSyjoqOjo5pbQnRBUVERzM3Nm+y1APrsksZBn12irV702eUxbSwT3EBSqRSZmZkwNTUFj8dTSxtEIhEcHR2RlpYGMzMztbShqejqsTLGUFRUhFatWoHPb5ortLV9dnX1Pa5NczpeVRyrJn12G0oX/+/pmOqvvp/dZtEzw+fz0aZNG3U3AwBgZmamMx/eF9HFY22qX7VVXvTZ1cX3uC7N6Xgb+1g17bPbULr4f0/HVD/1+ezSAGBCCCGEaDUKZgghhBCi1SiYaSIGBgZYtGgRDAwM1N0UlWtOx6ouze09bk7H25yOtT508f2gY2p8zWIAMCGEEEJ0F/XMEEIIIUSrUTBDCCGEEK1GwQwhhBBCtBoFM4QQQgjRahTMEEIIIUSrUTDTyFJSUjBlyhQ4OzvDyMgIrq6uWLRoEcrKyhS24fF4NW5XrlxR2Nf+/fvh4eEBQ0NDeHp64ujRo019OA22bt06tGvXDoaGhvDz88O1a9fU3SSdpAvv89KlS9GzZ0+YmprC1tYWI0aMQGJiosI2AwYMqPF3MmPGDIVtUlNTMXz4cBgbG8PW1hbz589HRUVFUx7KCy1evLjGcXh4eHCPl5aWYtasWWjZsiVMTEwwcuRIZGdnK+xDG46zsYjFYnh7e4PH4yE6OlrhsVu3bqFfv34wNDSEo6Mjli1bVuP5mnDurM93AaA9x1MXjTgfMdKo/v33XzZp0iR2/Phxdv/+ffb3338zW1tbFhISwm2TnJzMALBTp06xR48ecbeysjJum0uXLjGBQMCWLVvG7ty5w7755humr6/Pbt++rY7Dqpe9e/cyoVDItm3bxuLi4lhwcDCzsLBg2dnZ6m6aTtGV9zkoKIht376dxcbGsujoaPb6668zJycn9vTpU26b/v37s+DgYIW/k8LCQu7xiooK1qVLFxYYGMiioqLY0aNHmbW1NQsNDVXHIdVq0aJFrHPnzgrHkZubyz0+Y8YM5ujoyMLDw1lkZCTr1asX6927N/e4thxnY/n000/ZsGHDGAAWFRXFrS8sLGR2dnZs/PjxLDY2lv3222/MyMiIbdy4kdtGU86d9fku0KbjqY2mnI8omGkCy5YtY87Oztz9qmBG/o/0eWPGjGHDhw9XWOfn58emT5+uqma+Ml9fXzZr1izuvkQiYa1atWJLly5VY6t0j66+zzk5OQwAO3fuHLeuf//+7LPPPqv1OUePHmV8Pp9lZWVx63755RdmZmbGxGKxKpvbIIsWLWJeXl5KHysoKGD6+vps//793Lr4+HgGgEVERDDGtOc4G8PRo0eZh4cHi4uLq3GeXL9+PbO0tFQ45i+//JK5u7tz9zX53Pn8d4G2Hw9jmnM+ostMTaCwsBBWVlY11r/11luwtbVF3759cejQIYXHIiIiEBgYqLAuKCgIERERKm3ryyorK8ONGzcU2szn8xEYGKixbdZGuvw+FxYWAkCNv5Vff/0V1tbW6NKlC0JDQ1FSUsI9FhERAU9PT9jZ2XHrgoKCIBKJEBcX1zQNr6d79+6hVatWcHFxwfjx45GamgoAuHHjBsrLyxX+Tz08PODk5MT9n2rTcb6K7OxsBAcHY9euXTA2Nq7xeEREBAICAiAUCrl1QUFBSExMxJMnT7htNPXc+fx3gbYfjyadjyiYUbGkpCSsXbsW06dP59aZmJhg5cqV2L9/P44cOYK+fftixIgRCgFNVlaWwokLAOzs7JCVldVkbW+IvLw8SCQSrWqzNtLV91kqlWLOnDno06cPunTpwq0fN24cdu/ejTNnziA0NBS7du3CBx98wD1e299J1WOaws/PD2FhYTh27Bh++eUXJCcno1+/figqKkJWVhaEQiEsLCwUniP/f6otx/kqGGOYNGkSZsyYgR49eijdpj7vg6aeO5V9F2jz8QCadT7Sa9JX02ILFizAjz/+WOc28fHxCoP6MjIyMHToUIwePRrBwcHcemtra8ybN4+737NnT2RmZmL58uV46623Gr/xhGi4WbNmITY2FhcvXlRYP23aNG7Z09MTDg4OGDRoEO7fvw9XV9embuZLGzZsGLfctWtX+Pn5oW3btti3bx+MjIzU2DLVq++588SJEygqKkJoaGgTtezlNOZ3AWk8FMzUU0hICCZNmlTnNi4uLtxyZmYmBg4ciN69e2PTpk0v3L+fnx9OnjzJ3be3t68xmyE7Oxv29vYNa3gTsba2hkAg0Ko2ayNdfJ9nz56Nw4cP4/z582jTpk2d2/r5+QGQ/cp1dXWFvb19jZkTVe+NJr8fFhYWcHNzQ1JSEgYPHoyysjIUFBQo9M7I/59q63EC9T93nj59GhERETUKFfbo0QPjx4/Hjh07aj0vAlB4r1T599GY3wWacDyvQqPOR006QqeZSE9PZx06dGDvvfceq6ioqNdzpk6dynx8fLj7Y8aMYW+88YbCNv7+/hoz6EsZX19fNnv2bO6+RCJhrVu31vqBqZpGV95nqVTKZs2axVq1asXu3r1br+dcvHiRAWAxMTGMseqBsfIzJzZu3MjMzMxYaWmpStrdGIqKipilpSVbs2YNNwD4wIED3OMJCQlKBwBr23E2xMOHD9nt27e52/HjxxkAduDAAZaWlsYYqx4wKz/zMzQ0tMaAWU05d77ou0DbjkcZTTkfUTDTyNLT01n79u3ZoEGDWHp6usJUzCphYWFsz549LD4+nsXHx7MlS5YwPp/Ptm3bxm1z6dIlpqenx1asWMHi4+PZokWLNGo6njJ79+5lBgYGLCwsjN25c4dNmzaNWVhYKMzAIK9OV97nmTNnMnNzc3b27FmFv5OSkhLGGGNJSUnsP//5D4uMjGTJycns77//Zi4uLiwgIIDbR9WU5SFDhrDo6Gh27NgxZmNjo3FTlkNCQtjZs2dZcnIyu3TpEgsMDGTW1tYsJyeHMSabmu3k5MROnz7NIiMjmb+/P/P39+eery3H2ZiUzfosKChgdnZ27MMPP2SxsbFs7969zNjYuMZUZk04d9bnu0Cbjqc2mnI+omCmkW3fvp0BUHqrEhYWxjp27MiMjY2ZmZkZ8/X1VZiWWWXfvn3Mzc2NCYVC1rlzZ3bkyJGmPJSXsnbtWubk5MSEQiHz9fVlV65cUXeTdJIuvM+1/Z1s376dMcZYamoqCwgIYFZWVszAwIC1b9+ezZ8/XyHPDGOMpaSksGHDhjEjIyNmbW3NQkJCWHl5uRqOqHZjx45lDg4OTCgUstatW7OxY8eypKQk7vFnz56xjz/+mFlaWjJjY2P2zjvvKHzpMaYdx9mYakthERMTw/r27csMDAxY69at2Q8//FDjuZpw7qzPdwFj2nM8ddGE8xGPMcaa8KoWIYQQQkijoqnZhBBCCNFqFMwQQgghRKtRMEMIIYQQrUbBDCGEEEK0GgUzhBBCCNFqFMwQQgghRKtRMEMIIYQQrUbBDCGEEEK0GgUzhBBCCNFqFMwQQgghRKtRMEMIIYQQrfb/NKmeCD382hwAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 640x480 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "### Plot a fixed number of states\n",
+    "N_STATES = 10 # should be even\n",
+    "# skip some particles to make the plot more readable\n",
+    "SKIP_NTH_PARTICLE = 1\n",
+    "\n",
+    "\n",
+    "fig, axs = plt.subplots(2, N_STATES//2, subplot_kw={'projection': '3d'})\n",
+    "\n",
+    "for i, ax in enumerate(axs.flat):\n",
+    "    nth = int(sol.shape[0] / N_STATES) * i\n",
+    "    p = utils.to_particles(sol[nth])[::SKIP_NTH_PARTICLE]\n",
+    "    ax.scatter(p[:,0], p[:,1], p[:,2], cmap='viridis', c=range(p.shape[0]))\n",
+    "    ax.set_title(f\"t={t_range[nth]:.2g} (step {nth})\")\n",
+    "# set size\n",
+    "fig.set_size_inches(18, 12)\n",
+    "\n",
+    "plt.show()\n",
+    "\n",
+    "# show some phase space diagrams\n",
+    "fig, axs = plt.subplots(2, 3)\n",
+    "# for i, ax in enumerate(axs.flat):\n",
+    "#     r = []\n",
+    "#     v = []\n",
+    "#     for j in range(t_range.size):\n",
+    "#         p = utils.to_particles(sol[j])\n",
+    "#         print(p.shape)\n",
+    "#         r.append(np.linalg.norm(p[i,:3]))\n",
+    "#         v.append(np.linalg.norm(p[i,3:6]))\n",
+    "#     ax.plot(r, v)\n",
+    "#     ax.set_title(f\"particle {i}\")\n",
+    "\n",
+    "for i, ax in enumerate(axs.flat):\n",
+    "    x = []\n",
+    "    y = []\n",
+    "    for j in range(t_range.size):\n",
+    "        p = utils.to_particles(sol[j])\n",
+    "        x.append(p[i,0])\n",
+    "        y.append(p[i,1])\n",
+    "    ax.plot(x, y)\n",
+    "    ax.set_title(f\"particle {i}\")\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#### Plot some key quantities of the system as a whole\n",
+    "# sol has the shape (n_steps, n_particles*6) where the first 3*n are the positions and the last 3*n are the velocities\n",
+    "\n",
+    "# kinetic energy\n",
+    "energies = np.zeros(sol.shape[0])\n",
+    "for i in range(sol.shape[0]):\n",
+    "    p = utils.to_particles(sol[i])\n",
+    "    k_e = 0.5 * np.sum(p[:,6] * np.linalg.norm(p[:,3:6], axis=1)**2)\n",
+    "    energies[i] = k_e\n",
+    "\n",
+    "plt.figure()\n",
+    "plt.plot(t_range, energies)\n",
+    "plt.title('Kinetic energy')\n",
+    "plt.xlabel('Time')\n",
+    "plt.ylabel('Energy')\n",
+    "plt.show()\n",
+    "\n",
+    "\n",
+    "# radial extrema of the particles\n",
+    "r_mins = np.zeros(sol.shape[0])\n",
+    "r_maxs = np.zeros(sol.shape[0])\n",
+    "for i in range(sol.shape[0]):\n",
+    "    p = utils.to_particles(sol[i])\n",
+    "    r = np.linalg.norm(p[:,:3], axis=1)\n",
+    "    r_mins[i] = np.partition(r, 4)[4]\n",
+    "\n",
+    "    # r_mins[i] = np.min(r)\n",
+    "    r_maxs[i] = np.max(r)\n",
+    "\n",
+    "plt.figure()\n",
+    "plt.plot(t_range, r_mins, label='Min distance')\n",
+    "# plt.plot(t_range, r_maxs, label='Max distance')\n",
+    "plt.title('Radial extrema')\n",
+    "plt.xlabel('Time')\n",
+    "plt.ylabel('Distance')\n",
+    "plt.legend()\n",
+    "plt.show()\n",
+    "\n",
+    "# plot the last radial distribution\n",
+    "plt.figure()\n",
+    "plt.hist(r, bins=NBINS)\n",
+    "plt.title('Radial distribution')\n",
+    "plt.xlabel('Distance')\n",
+    "plt.ylabel('Number of particles')\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "projects-X-9bmgL6",
+   "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": "3.13.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/nbody/task1.ipynb b/nbody/task1.ipynb
index c2db0c0..b591c51 100644
--- a/nbody/task1.ipynb
+++ b/nbody/task1.ipynb
@@ -42,7 +42,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "16:03:58 - utils.load - Loaded 50010 rows and 10 columns from data/data.txt\n"
+      "08:59:02 - utils.load - Loaded 50010 rows and 10 columns from data/data.txt\n"
      ]
     }
    ],
@@ -104,8 +104,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "16:04:00 - task1 - Considering a globular cluster - total mass of particles: 4622219.258999999, maximum radius of particles: 724.689657812915\n",
-      "16:04:00 - utils.units - Set scales: M_SCALE = 0.022 solMass, R_SCALE = 0.028 pc\n"
+      "08:59:04 - task1 - Considering a globular cluster - total mass of particles: 4622219.258999999, maximum radius of particles: 724.689657812915\n",
+      "08:59:04 - utils.units - Set scales: M_SCALE = 0.022 solMass, R_SCALE = 0.028 pc\n"
      ]
     }
    ],
@@ -206,7 +206,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "16:04:00 - utils.particles - Found mean interparticle distance: 0.010402746349924056\n"
+      "08:59:05 - utils.particles - Found mean interparticle distance: 0.010402746349924056\n"
      ]
     }
    ],
@@ -235,56 +235,6 @@
    "cell_type": "code",
    "execution_count": 8,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "\"## compare the two force calculations\\n# since the forces were computed for each particle, rather than comparing them directly we compare the relative error in the magnitude and direction of the forces\\n\\n\\n# f_diff = f_nsquare_1e - f_analytical\\nf_diff = f_nsquare_2e - f_analytical\\ndiff_mag = np.linalg.norm(f_diff, axis=1)\\n\\n\\n# plot the distribution of the error\\n# create 4 stacked histograms, sharing the same x axis\\nfig, ax = plt.subplots(4, sharex=True)\\nax[0].hist(diff_mag, bins=NBINS)\\nax[0].set_title('Magnitude of the force difference')\\nax[0].set_yscale('log')\\n\\nax[1].hist(f_diff[:,0], bins=NBINS)\\nax[1].set_title('X component of the force difference')\\nax[1].set_yscale('log')\\n\\nax[2].hist(f_diff[:,1], bins=NBINS)\\nax[2].set_title('Y component of the force difference')\\nax[2].set_yscale('log')\\n\\nax[3].hist(f_diff[:,2], bins=NBINS)\\nax[3].set_title('Z component of the force difference')\\nax[3].set_yscale('log')\\n\\nplt.title('Error in forces')\\nplt.show()\\n\""
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "\"\"\"## compare the two force calculations\n",
-    "# since the forces were computed for each particle, rather than comparing them directly we compare the relative error in the magnitude and direction of the forces\n",
-    "\n",
-    "\n",
-    "# f_diff = f_nsquare_1e - f_analytical\n",
-    "f_diff = f_nsquare_2e - f_analytical\n",
-    "diff_mag = np.linalg.norm(f_diff, axis=1)\n",
-    "\n",
-    "\n",
-    "# plot the distribution of the error\n",
-    "# create 4 stacked histograms, sharing the same x axis\n",
-    "fig, ax = plt.subplots(4, sharex=True)\n",
-    "ax[0].hist(diff_mag, bins=NBINS)\n",
-    "ax[0].set_title('Magnitude of the force difference')\n",
-    "ax[0].set_yscale('log')\n",
-    "\n",
-    "ax[1].hist(f_diff[:,0], bins=NBINS)\n",
-    "ax[1].set_title('X component of the force difference')\n",
-    "ax[1].set_yscale('log')\n",
-    "\n",
-    "ax[2].hist(f_diff[:,1], bins=NBINS)\n",
-    "ax[2].set_title('Y component of the force difference')\n",
-    "ax[2].set_yscale('log')\n",
-    "\n",
-    "ax[3].hist(f_diff[:,2], bins=NBINS)\n",
-    "ax[3].set_title('Z component of the force difference')\n",
-    "ax[3].set_yscale('log')\n",
-    "\n",
-    "plt.title('Error in forces')\n",
-    "plt.show()\n",
-    "\"\"\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -347,15 +297,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "16:04:17 - task1 - Crossing time for half mass system: 1.7e-06 pc(3/2) / solMass(1/2)\n",
-      "16:04:17 - task1 - Direct estimate of the relaxation timescale: 0.00078 pc(3/2) / solMass(1/2)\n"
+      "08:59:24 - task1 - Crossing time for half mass system: 1.7e-06 pc(3/2) / solMass(1/2)\n",
+      "08:59:24 - task1 - Direct estimate of the relaxation timescale: 0.00078 pc(3/2) / solMass(1/2)\n"
      ]
     }
    ],
diff --git a/nbody/task2-particle-mesh.ipynb b/nbody/task2-particle-mesh.ipynb
index 6463db1..45accc1 100644
--- a/nbody/task2-particle-mesh.ipynb
+++ b/nbody/task2-particle-mesh.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -23,49 +23,51 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
     "DATA_ROOT = Path('data')\n",
-    "# DATA_NAME = 'data0.txt'\n",
+    "DATA_NAME = 'data0.txt'\n",
     "# DATA_NAME = 'data1.txt'\n",
     "# DATA_NAME = 'data0_noise.txt'\n",
-    "DATA_NAME = \"data1_noise.txt\"\n",
+    "# DATA_NAME = 'data1_noise.txt'\n",
     "NBINS = 30\n",
-    "CACHE_ROOT = Path('.cache')\n",
-    "\n",
-    "G = 1"
+    "CACHE_ROOT = Path('.cache')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "09:38:46 - utils.load - Loaded 1008 rows and 9 columns from data/data0.txt\n",
+      "09:38:46 - task2 (mesh) - Fetched 1008 points, columns: ['ID', 'M', 'x', 'y', 'z', 'vx', 'vy', 'vz', 'eps']\n"
+     ]
+    }
+   ],
+   "source": [
+    "points, columns = utils.load_data(DATA_ROOT / DATA_NAME)\n",
+    "logger.debug(f\"Fetched {points.shape[0]} points, columns: {columns}\")\n",
+    "# points = points[1:100, ...]\n",
+    "points = points[::5]\n",
+    "# TODO remove\n",
+    "# reorder the columns to match the expected order (x, y, z, mass)\n",
+    "particles = points[:, [2, 3, 4, 1]]"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "15:36:38 - utils.load - Loaded 9913 rows and 9 columns from data/data1_noise.txt\n"
-     ]
-    }
-   ],
-   "source": [
-    "points, columns = utils.load_data(DATA_ROOT / DATA_NAME)\n",
-    "logger.debug(f\"Fetched {points.shape[0]} points, columns: {columns}\")\n",
-    "# reorder the columns to match the expected order (x, y, z, mass)\n",
-    "particles = points[:, [2, 3, 4, 1]]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -97,15 +99,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "15:36:38 - task2 (mesh) - Considering a globular cluster - total mass of stars: 9.999999999999998, maximum radius of particles: 0.9096731180509756\n",
-      "15:36:38 - utils.units - Set scales: M_SCALE = 1e+03 solMass, R_SCALE = 1.1 pc\n"
+      "09:38:47 - task2 (mesh) - Considering a globular cluster - total mass of stars: 1.9960278053624618, maximum radius of particles: 0.9000000000000001\n",
+      "09:38:47 - utils.units - Set scales: M_SCALE = 5e+03 solMass, R_SCALE = 1.1 pc\n"
      ]
     }
    ],
@@ -130,14 +132,56 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "15:36:38 - utils.particles - Found mean interparticle distance: 0.0262396757880128\n"
+      "09:38:47 - utils.particles - Half mass radius: 0.16294982222188462 for 50th particle of 202\n",
+      "09:38:47 - utils.particles - Number of particles within half mass radius: 43 of 202\n",
+      "09:38:47 - utils.particles - Found mean interparticle distance: 0.07497686469036202\n",
+      "09:38:47 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.00075)\n",
+      "09:38:47 - utils.forces_basic - Particle 0 done\n",
+      "09:38:47 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.0075)\n",
+      "09:38:47 - utils.forces_basic - Particle 0 done\n",
+      "09:38:47 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:47 - utils.forces_basic - Particle 0 done\n",
+      "09:38:47 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.75)\n",
+      "09:38:47 - utils.forces_basic - Particle 0 done\n",
+      "09:38:47 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=7.5)\n",
+      "09:38:47 - utils.forces_basic - Particle 0 done\n",
+      "09:38:47 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=10]\n",
+      "09:38:47 - utils.forces_mesh - Using mesh spacing: 0.1992099685230434\n",
+      "09:38:47 - utils.forces_mesh - Got k_square with: (10, 10, 10), 18.899013258221427 0.0\n",
+      "09:38:47 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:47 - utils.forces_mesh - Got phi with: (10, 10, 10), 0.3477529361330639\n",
+      "09:38:47 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=20]\n",
+      "09:38:47 - utils.forces_mesh - Using mesh spacing: 0.09436261666881007\n",
+      "09:38:47 - utils.forces_mesh - Got k_square with: (20, 20, 20), 84.22893563232012 0.0\n",
+      "09:38:47 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:47 - utils.forces_mesh - Got phi with: (20, 20, 20), 0.03884710595934048\n",
+      "09:38:47 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:47 - utils.forces_mesh - Using mesh spacing: 0.036589586055252865\n",
+      "09:38:47 - utils.forces_mesh - Got k_square with: (50, 50, 50), 560.2040843578968 0.0\n",
+      "09:38:47 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:47 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023263587300085347\n",
+      "09:38:47 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=100]\n",
+      "09:38:47 - utils.forces_mesh - Using mesh spacing: 0.01810999713845851\n",
+      "09:38:47 - utils.forces_mesh - Got k_square with: (100, 100, 100), 2286.780604244788 0.0\n",
+      "09:38:47 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:47 - utils.forces_mesh - Got phi with: (100, 100, 100), 0.00028444689035370563\n",
+      "09:38:47 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=150]\n",
+      "09:38:47 - utils.forces_mesh - Using mesh spacing: 0.012032816890653608\n",
+      "09:38:47 - utils.forces_mesh - Got k_square with: (150, 150, 150), 5179.9628808120415 0.0\n",
+      "09:38:47 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:47 - utils.forces_mesh - Got phi with: (150, 150, 150), 8.368806772616921e-05\n",
+      "09:38:47 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=200]\n",
+      "09:38:48 - utils.forces_mesh - Using mesh spacing: 0.00900949606385626\n",
+      "09:38:48 - utils.forces_mesh - Got k_square with: (200, 200, 200), 9239.750914059536 0.0\n",
+      "09:38:48 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:48 - utils.forces_mesh - Got phi with: (200, 200, 200), 3.5179147539931935e-05\n"
      ]
     }
    ],
@@ -183,12 +227,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -211,7 +255,7 @@
     "# many of the particles have the same distance from the origin, so we skip some of them\n",
     "SKIP_N = 20\n",
     "\n",
-    "for f,e in zip(n_squared_forces, epsilon_range):\n",
+    "for f, e in zip(n_squared_forces, epsilon_range):\n",
     "    plt.plot(r[::SKIP_N], np.linalg.norm(f, axis=1)[::SKIP_N], 'o', label=f\"$N^2$ - {e:.1g} * $\\\\epsilon$\", alpha=0.3)\n",
     "for f, s in zip(mesh_forces, mesh_size_range):\n",
     "    plt.plot(r[::SKIP_N], np.linalg.norm(f, axis=1)[::SKIP_N], 'x', label=f\"Mesh - N={s}\")\n",
@@ -243,7 +287,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -252,127 +296,239 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "15:36:57 - task2 (mesh) - Considering 9913 particles\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "15:36:57 - task2 (mesh) - Total mass: 10.999999999999998\n"
+      "09:38:49 - task2 (mesh) - Considering 202 particles\n",
+      "09:38:49 - task2 (mesh) - Total mass: 2.996027805362462\n",
+      "09:38:49 - utils.integrate - Reshaped 7 columns into particles.shape=(1414,)\n",
+      "09:38:49 - task2 (mesh) - [0.         0.16294982 0.3        0.55231726 0.09929811 0.18281353\n",
+      " 0.33657024]\n",
+      "09:38:49 - task2 (mesh) - [0. 0. 0. 0. 0. 0. 1.] -> [0. 0. 0. 0. 0. 0. 1.]\n",
+      "09:38:49 - task2 (mesh) - [ 0.16294982  0.          0.         -0.          2.94302832  0.\n",
+      "  0.00993049] -> [ 0.16294982  0.          0.         -0.          2.94302832  0.\n",
+      "  0.00993049]\n",
+      "09:38:49 - task2 (mesh) - Consistency check passed\n"
      ]
     }
    ],
    "source": [
     "# load the particles in the format [x, y, z, vx, vy, vz, mass]\n",
     "p0 = points[:, [2, 3, 4, 5, 6, 7, 1]]\n",
-    "# p0 = p0[::10] # only take a subset for now\n",
     "\n",
     "logger.info(f\"Considering {p0.shape[0]} particles\")\n",
     "logger.info(f\"Total mass: {np.sum(p0[:,6])}\")\n",
     "\n",
-    "if logger.level >= logging.DEBUG:\n",
+    "if logger.level <= logging.DEBUG:\n",
     "    # assert that the ODE reshaping is consistent\n",
-    "    logger.debug(f\"{p0[0]}, {p0[1]}\")\n",
+    "    p0_ref = p0.copy()\n",
     "    y0, _ = utils.ode_setup(p0, None)\n",
     "    logger.debug(y0[0:7])\n",
     "    p0_reconstructed = utils.to_particles(y0)\n",
-    "    logger.debug(p0_reconstructed[0])\n",
-    "    assert np.allclose(p0, p0_reconstructed)\n"
+    "    logger.debug(f\"{p0_ref[0]} -> {p0_reconstructed[0]}\")\n",
+    "    logger.debug(f\"{p0_ref[1]} -> {p0_reconstructed[1]}\")\n",
+    "\n",
+    "    assert np.allclose(p0_ref, p0_reconstructed)\n",
+    "    logger.debug(\"Consistency check passed\")\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def integrate(method: str, force_function: callable, p0: np.ndarray, t_range: np.ndarray) -> np.ndarray:\n",
+    "    \"\"\"\n",
+    "    Integrate the gravitational movement of the particles, using the specified method\n",
+    "    - method: the integration method to use (\"scipy\" or \"rk4\")\n",
+    "    - force_function: the function that computes the forces acting on the particles\n",
+    "    - p0: the initial conditions of the particles (n, 7) array, unflattened\n",
+    "    - t_range: the time range to integrate over\n",
+    "    Returns: the integrated positions and velocities of the particles in a 'flattened' array (time_steps, nx7)\n",
+    "    \"\"\"\n",
+    "    y0, y_prime = utils.ode_setup(p0, force_function)\n",
+    "    \n",
+    "    if method == \"scipy\":\n",
+    "        sol = spi.odeint(y_prime, y0, t_range, rtol=1e-2)\n",
+    "    elif method == \"rk4\":\n",
+    "        sol = np.zeros((t_range.shape[0], y0.shape[0]))\n",
+    "        sol[0] = y0\n",
+    "        dt = t_range[1] - t_range[0]\n",
+    "        for i in range(1, t_range.shape[0]):\n",
+    "            t = t_range[i]\n",
+    "            sol[i,...] = utils.runge_kutta_4(sol[i-1], t, y_prime, dt)\n",
+    "\n",
+    "\n",
+    "    logger.info(f\"Integration done, shape: {sol.shape}\")\n",
+    "    return sol\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "15:57:21 - utils.particles - Found mean interparticle distance: 0.0262396757880128\n",
-      "15:57:21 - task2 (mesh) - Crossing time: 0.059139749002184876, timestep: 5.7915844560794737e-05\n"
+      "09:38:49 - utils.particles - Half mass radius: 0.16294982222188462 for 50th particle of 202\n",
+      "09:38:49 - utils.particles - Number of particles within half mass radius: 43 of 202\n",
+      "09:38:49 - utils.particles - Found mean interparticle distance: 0.07497686469036202\n",
+      "09:38:49 - task2 (mesh) - Mean velocity: 0.014831820818626048, timestep: 0.005055135549925524\n"
      ]
     }
    ],
    "source": [
     "# Determine the integration timesteps\n",
     "# let's first compute the crossing time\n",
-    "m_half = np.sum(particles[:, 3]) / 2\n",
-    "r_half = utils.half_mass_radius(particles)\n",
-    "\n",
-    "v_c = np.sqrt(G * m_half / r_half)\n",
-    "t_c = r_half / v_c\n",
-    "# a single timestep should result in a small displacement, wrt. to the mean interparticle distance\n",
+    "v = np.linalg.norm(particles[:, 3:6], axis=1)\n",
+    "v_mean = np.mean(v)\n",
+    "# a timestep should result in a small displacement, wrt. to the mean interparticle distance\n",
     "r_inter = utils.mean_interparticle_distance(particles)\n",
-    "dt = t_c * r_inter / r_half * 0.01\n",
-    "logger.info(f\"Crossing time: {t_c}, timestep: {dt}\")\n",
-    "# dt = 0.01\n",
-    "n_steps = 10\n",
-    "t_range = np.arange(0, n_steps*dt, dt)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# The force function can be interchanged\n",
-    "force_function = lambda x: utils.n_body_forces(x, G, epsilon) # epsilon was computed above\n",
-    "force_function = lambda x: utils.analytical_forces(x)# just for lols\n",
-    "# force_function = lambda x: utils.mesh_forces_v2(x, G, 50, utils.particle_to_cells_nn)\n",
     "\n",
-    "y0, y_prime = utils.ode_setup(p0, force_function)"
+    "dt = r_inter / v_mean * 1e-3\n",
+    "logger.info(f\"Mean velocity: {v_mean}, timestep: {dt}\")\n",
+    "\n",
+    "if np.isnan(dt):\n",
+    "    raise ValueError(\"Invalid timestep\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/remy/Documents/Uni/HS24/Computational Astrophysics/projects/nbody/utils/forces_basic.py:71: RuntimeWarning: invalid value encountered in scalar divide\n",
-      "  f = - m_current * m_enclosed / r_current**2\n",
-      "16:03:32 - task2 (mesh) - Integration done, shape: (10, 69391)\n"
+      "09:38:49 - task2 (mesh) - Integration range: 0.0 -> 0.045496219949329716, n_steps: 10\n",
+      "09:38:49 - utils.particles - Half mass radius: 0.16294982222188462 for 50th particle of 202\n",
+      "09:38:49 - utils.particles - Number of particles within half mass radius: 43 of 202\n",
+      "09:38:49 - utils.particles - Found mean interparticle distance: 0.07497686469036202\n",
+      "09:38:49 - utils.integrate - Reshaped 7 columns into particles.shape=(1414,)\n",
+      "09:38:49 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:49 - utils.forces_basic - Particle 0 done\n",
+      "09:38:49 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:49 - utils.forces_basic - Particle 0 done\n",
+      "09:38:49 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:49 - utils.forces_basic - Particle 0 done\n",
+      "09:38:49 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:49 - utils.forces_basic - Particle 0 done\n",
+      "09:38:49 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:49 - utils.forces_basic - Particle 0 done\n",
+      "09:38:49 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:49 - utils.forces_basic - Particle 0 done\n",
+      "09:38:49 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:49 - utils.forces_basic - Particle 0 done\n",
+      "09:38:49 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:49 - utils.forces_basic - Particle 0 done\n",
+      "09:38:49 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:49 - utils.forces_basic - Particle 0 done\n",
+      "09:38:49 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:49 - utils.forces_basic - Particle 0 done\n",
+      "09:38:49 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:49 - utils.forces_basic - Particle 0 done\n",
+      "09:38:49 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:49 - utils.forces_basic - Particle 0 done\n",
+      "09:38:49 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:49 - utils.forces_basic - Particle 0 done\n",
+      "09:38:49 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:49 - utils.forces_basic - Particle 0 done\n",
+      "09:38:49 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:49 - utils.forces_basic - Particle 0 done\n",
+      "09:38:49 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:49 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - utils.forces_basic - Computing forces for 202 particles using n^2 algorithm (using softening=0.075)\n",
+      "09:38:50 - utils.forces_basic - Particle 0 done\n",
+      "09:38:50 - task2 (mesh) - Integration done, shape: (10, 1414)\n"
      ]
     }
    ],
    "source": [
-    "# finally, integrate the system\n",
+    "## Integration setup - use the n_squared forces for a few timesteps only, to see if the orbits are stable\n",
+    "t_orbit = 2 * np.pi * r_inter / v_mean\n",
+    "n_steps = int(t_orbit / dt * 5)\n",
+    "n_steps = 10\n",
+    "t_range = np.arange(0, n_steps*dt, dt)\n",
+    "logger.info(f\"Integration range: {t_range[0]} -> {t_range[-1]}, n_steps: {n_steps}\")\n",
     "\n",
-    "## either use the scipy integrator\n",
-    "# sol = spi.odeint(y_prime, y0, t_range, rtol=1e-2)\n",
+    "# The force function can be interchanged\n",
+    "epsilon = utils.mean_interparticle_distance(particles)\n",
+    "# epsilon = 0.01\n",
     "\n",
-    "# # or do it ourselves, for instance by using rk4\n",
-    "sol = np.zeros((t_range.shape[0], y0.shape[0]))\n",
-    "sol[0] = y0\n",
-    "for i in range(1, t_range.shape[0]):\n",
-    "    t = t_range[i]\n",
-    "    sol[i,...] = utils.runge_kutta_4(sol[i-1], t, y_prime, dt)\n",
+    "force_function = lambda x: utils.n_body_forces(x, G, epsilon)\n",
+    "# force_function = lambda x: 0\n",
+    "# force_function = lambda x: utils.n_body_forces_basic(x, G, epsilon)\n",
+    "# force_function = lambda x: utils.analytical_forces(x)\n",
+    "# force_function = lambda x: utils.mesh_forces_v2(x, G, 50, utils.particle_to_cells_nn)\n",
     "\n",
     "\n",
-    "logger.info(f\"Integration done, shape: {sol.shape}\")"
+    "sol = integrate(\"rk4\", force_function, p0, t_range)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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+fbucTqdH4B0bG1uhYtKfQB2t4uJiv+s20dECQkugYEk61hYUFxfrhx9+UHJysk455RQ5nU6VlpYqOTlZycnJ6tq1q8rLy5WXl6fs7Gylp6dr06ZNcjgcOnr0qCIjI9WsWTNFRUUFfV1VqSwg8AZCU6Bgyd3+/fuVkZGhXr16qWPHjiorK1N4eLhSUlK0ZcsWnXDCCfZgLzs7W6mpqSopKfEY7CUmJlZ7WTfvayXwBpqGQMGS9d8ul8vnOKxVq1Zq1aqVpGOzS6yio61bt+ro0aMVAu+q3nCzrsPlcnnMqGMfE6DpsPoV5eXlPj+/DodDhYWFWrZsmeLi4jRq1CiFhYWprKxM8fHx6tChg4wxKigoqHbhoy/u47Di4mL72ti4G40NAXcjUlmwJB2bCicd6zidcsopioqKstdkcudwOJSYmKjExER17txZLpfLDrwPHTqkrVu3elRXulyuoNasdD8/U+mApiOYYMkYo8zMTGVlZalfv37q2LGjHA6H3Wa5c1+uRJLKysq0du1aSdKePXu0ceNGezqv1eGKjIwM+norC7wlKSMjQ+3atVN0dDQdLaCRqyxYkqSioiIVFxfr8OHDGj58uBITEyv0XaznxMTEKCYmRm3btpUxRkePHrUHe3v37lV5eXmNp/P6WtbNO/BmlhsQGioLliTp6NGjKigoUGRkZMBxWGRkpNq0aaM2bdpIkoqLi+32Z9OmTSouLlZiYqLHDbeqBN7Sr2vxeu9jYo3D2McECB3e+675+qxafZnDhw+rV69e6tKlix0yu3M4HH4LHzMzM4MqfAyG1cZY1+a+cTf7mKChEHA3AsEGS+5r3Q4ePNhjqltlDZK1PndSUpK6dOlSobqyqKhIqampatGihd3QVXWzlGACbyoLgMbHexMlf8HSmjVrVFBQoGbNmqlTp04ez6/sBll4eLiioqIUFxenLl26qKyszK6u3LVrlzZs2KC4uDiP6qbqrF9pdZzKy8u1ZcsWtWjRwmNjFjpaQOMTTLB06NAhrVu3Tk6nU3379lViYqLf8/kKvWNjYxUbG6v27dvLGKPCwkI7cNq9e7eMMR6Dvfj4+KD7J76WdbPel/s+JgUFBYqLi7On9RJ4Aw0v2GDJWvooPDxcJ510UpU+u1FRUUpJSVFKSookedxw279/v8rKyioE3tVZP1fyHIdZ+5iwcTfQePnad837c1lSUqK1a9eqsLBQnTp1UteuXT2eH0hVCx+tfZSqwlfhkdW3swqPvANv9jFBXSDgbmDBBEvua90OHjxYK1eu9Hke6/nB8K6u/N///qeUlBSVl5dr3759SktLU3R0tEdDV53qSuu1fFUWEHgDDS/YYGnt2rVq3bq12rRpo8zMzGq9lvu5w8PD1bJlS7Vs2VLSsXbOCry3bdumwsJCe/1ca+mTqqxf6f46ERERFSoLJAJvoKEFEyy5XC5t3rxZe/bsUb9+/bRz586An1NrfcpAHA6H4uLiFBcXZ0/ntfYQsNbQdTgcHjfcqjKd11/gnZaWps6dO9vtHhXeQMMKNliyxmE9e/bUvn37avw5tWaYtGvXzr7hZvWB9u7dW2fr53pv3G2Nw9zDJtogoP7423fNXWZmptauXavk5GS1bNmySkWIvlRW+Lhp0yZFRUV53PSv6msGs6ybe+DtvrQkUBME3A3IPVhy74S4c99EadSoUR4dldpkTWWxBl2Bqiutxq42dgd3uVwqLi6msgCoZ1UNlvr376927dppz549NWp//D03MjJSrVu3VuvWrSV5TufdsmWLioqKarxhXFUrCwi8gboTTLBUWFioNWvWyOVyaeTIkYqPj9euXbsq3TOkqhwOhxISEpSQkKBOnTrJ5XIpPz9fWVlZOnz4sLZu3epRGGBVN1U18JZkty/+Nu5mHxOgflgzLAIFS97jsLy8PJ9LktSE+w03a4ZJoPVzS0tLq9w3YR8ToHGpbN816VgbtW3bNu3cuVO9e/dWx44dtXbt2lrPgbwLH61Nu3NycnwWPlbn9dnHBPWFgLsBBDsVbtu2bdqxY4d69eqlTp06eax1W9sNmzfv6srS0lI78K7t3cElz8qCn376Sb169bKn5xF4A7WrKsGSMUajRo1SXFycpOCqI/2pyXTeoqIie7DnvWFccnKykpKSfA74/L1mVSsLmEoH1J5ggqWMjAytX79e7dq1U+/eve3PazBtUE37SE6n057Oa12vVd104MABbd682d4s12qDqjKdl31MgIZjjTespSGrMg6rj8+fv/Vzc3JylJWVpaysLDkcDhUVFVV7/dyqBN7uYRM3/YGaC2bfNWtpyJKSEo0YMUIJCQmSajYOC1ZYWJhatGihFi1aSKpY+GiM0dq1a+2lbau6rKQUfODNLDdUFQF3PQsmWCoqKtLatWtVVFRkb6JksY6tiwruQCIiIvzuDu5dXWktJ1Dd6kr3jpV1I4DKAqB2BBMspaena8OGDWrfvr169+7tMaCpacequs+Njo5W27ZtfW4Yt2/fPpWVlXlM542Nja3S+aksAOpeMMFSeXm50tLSlJ6erhNOOMHepM1SWRtUF4M/azOm5ORkde3aVeXl5crNzbXbn7S0NEVFRXlUeEdFRfm9Pl+PEXgDdS/YYCnQOKy2K7gr475+bqdOnZSWlqby8nLFxcX5XT83OjqawBtoZILZd02SDh48qHXr1ql169YaOnRohX3X6jrg9uZd+Lh06VJ16NBBR48e1fbt21VQUFCjwkfJ/8bd7vuYEHgjGATc9SiYYMla67ZVq1YaMmRIhcahrgLuqp7Te3dw9+rKtLQ0lZSU1Gh3cGu5EqbSAbXDCoXz8/MVHx/vN1hKTU3VgQMHfAZLUv1VcFd2nmA2jJOkvXv3qmXLllXaMM56DSoLgNoTTLCUn5+v1atXKzw8XKeccorPquhgAu66FhYWpubNm6t58+aSjlU3WYH3nj17tHHjRsXGxnoM9iIjI4NuO4MNvNnHBAhOsMGStZlty5YtA47DGpLD4VBUVJS6dOmiLl26yOVy2e2PtX6u+wyT6q6f6yvwPnz4sLZt26YhQ4awjwlQBcHsu+ZyubRp0ybt3bvXXhrSW0ME3L6uoXnz5vbs3uLiYrvCu7aWlZR8b9y9fv16xcTEqGPHjozD4BMBdz0IpmLJexOl9u3bV3pOS2P4IHtXV7oH3tbu4N6bpfjrBFkdT3dUFgDVZ80cOXDggHbu3KmRI0dW+IwdOXJEa9asUXh4uEaNGuV3un1DVXAH4r5+pbVhXG5urn755Rfl5uZq9+7dcjgcHpulVGXDOOs1KqssKCwstIN3OlrAMcEES8YY7du3T6mpqercubN69Ojh9+93fSxRUlXh4eEe03m9l3WzqptKSkqUl5enxMTEWtvHxAq82ccE8C3YYGnLli3avXt3wHFYYwiXvDmdzgrr53rPMHFfP7dZs2aKjIys0mtYPzPr/YeHh3ts3O1rWTfGYcAxwey7VlBQoDVr1kiSx9KQ3ny1QQ39dz4qKspv4aO1rKR74aO/ZSX9ce//uFwu+2foax8TAm8QcNex6m6i5I9756KxcjgcPncHtxq6PXv2BNwdPJj3VlngLflu5Oho4XjjfXNN8uwIGWO0d+9epaWlVRosWc+tbseqvjoZDofDbkcHDBggp9Op/Px8ZWdnKzMzU9u2bauVDeO8A+/NmzerXbt2atWqFRXegIILlsrKyrRhwwZlZmZq8ODB9hRYf/z1gdzD84buI/la1i0nJ0epqanav3+/duzYUaG6qbr7mLgH3uXl5SovL/c7nZfAG8cbq7p58+bNGjhwoM/+TVXHYQ3dvljX4Y+vGSbu6+du2LBBcXFx9uySZs2aBX3Dzb2d9R6HVbZxN/uY4Hhj/V3euXOnjDHq2LGjz8/A/v37tXHjRp9LQ3oLhTaoNgsfvVnjWet471luxcXFHn0gNu4+/hBw16Hy8nL7jpK/qXD+NlGqTG3fuavLD7uv6spAu4NXd2deX4G3VVkgEXjj+OIrWLLufFtKS0u1YcMGZWVlBRUsWedpbBXclb2O+4ZxnTt3rrBh3JYtWxQREeFR4V3VDeMsVhsjHRtYU1mA41UwFUu5ublas2aNYmJidMopp/hdt9pdY1iipKoiIyPVunVrbdu2Tb1791ZcXJzdB9q0aZOKi4uVmJhot0HVmc7rqw/kHXhbgzz3sKkx/ryAmrJ+/63Cl8OHD/tsg6o6Dmss4VJVeK+f6z3DZP369UGvn+trlq1U9Y273ZeWBJoi9yLH/Px8n58d96UhBw4cqNatW1d63lBrg4ItfLT6P8nJyR6Fj94CzfSX2McEBNx1wgqWdu/erX379mnYsGE+G7RAmygFYk3JqG311Vha1ZXeu4Nb1ZXl5eVatWqVR3VlbewOXlllAYE3mgrrd90Ks90rt63HcnNztXr1asXGxgYdLFnnaOg1uGv6mv42jMvJybHXrwx2wzh33ssvWO2Kd2WBe+BNZQGaGvdgyd+eI8YY7dq1S1u2bFG3bt3UrVu3Ks2gaGxLlATLaiOioqKUkpKilJQUSbI3zbWqvEtLSyvsY1LV6bzBLuvGPiZoarxnz3rf3Jc8x2EDBgywP4uVCbVwyRdfM0yssMl7/Vyrr+QeXgfTRgQTeLNxN5oq733XnE6nXXBksZaGjIiICLg0pLfGuERJVfgqfMzPz/e46VbZspKVvd9gA2/2MWmaCLhrmXuwZDVA3h+UYDZRqkyod67cORwOj+rKpUuXqlevXjp69Kjf3cGr+jOramUBU+kQitx/r30FS1bAvWPHDm3dulXdu3dX165dq3zzqCYdq8bYdlV3wzhvgSqbqCzA8SCYZdlKSkq0bt06HTlyRCeddJK9bmywgqngboztTCDe1U1W4J2dna29e/eqvLzcDpqaN29ubxQcrGADb19tEBBKvIMl6/faPeCuyTgsFNuXykRGRvpdPzctLc1j/dzq9kmCDbyZ5YZQ5m/fNffiRPelIbt06aLu3btX+e+59w27UOZwOJSQkKCEhASfhY/bt2/32GfA+0ZBsK/haxzGPiZNEwF3LfEVLFkfIPdjgt1EKZC6qOBuTB9eK/C2qinKy8vt5QTcqyvd7+xVZ3dwKgvQlAQTLFnLJu3atatawZIUOhXcNWkj/W0Yl5OTo507dyo/P99ev9IKvCMiIvwG3N4IvNEUWX9Dly5dqpNOOkkJCQkVjsnKytKaNWuUlJSkUaNGVXmjMyk0lyixBNNGOBwOe7Pa9u3beyzrlpOTo927d8sY49EHio+Pr/EsN2OMdu/erZycHPXv359Zbggp/oIl6ddZbC6XS/v371dqaqo6deqknj17Vvl3uikG3N4CrZ+bmZmpsrIyj5m2VVk/1+I+DrN+nt4bdxN4I5QEGodZN9mspSGzs7M1ZMgQe5xRFU29DfIufPReVjInJ0f5+fnKzc2tUeGjv8C7uLhYRUVFBN4hjIC7Fvhr0NwrBqq6iVIwr1nbGktj6T0AdN8MTjoW0lnTWKwbBjExMTXeHdxf4P3TTz+pb9++io2NpaOFRsl9rVt/f3yzsrK0bt06GWN0yimnBL2hkDd/Haum/Fnwt2Fcdna2tm3bpsLCQiUkJKi4uFhHjhyptQ3jmEqHUOAdLLlcrgpthDFG27Zt044dO9SrVy916tSpRpWAobpESXX4WtbN2jTXfTpvbSzrZrUzVjvEPiYIBZXd4Ld+T9euXVulPUd8Od76QA6H5/q56enp2rt3r1q1alVh/Vzrplug9XP9vYZUceNuAm+ECqsP5G9ZNofDoaKiIi1btkxxcXEaNWpU0EtDevPXBjWlfo8772Ulf/nlF3vZtposK+nOe3k2f/uYeC8tybJujRMBdw0FCpasKSTV2UQpkLpag7uxqOy9hYWFeVRXBtod3L26sircA+/8/Hz7Z05HC41JsGvdWsFS586dtXv37mqH21LNK7jre1pdXXwmrQ3jrM1giouL7c3i9u7dqx07dtjrV9ZkwziJygI0br6CJe/lAIqKirR27VoVFRVp+PDhSkxMrNFrhvoSJTX9jLpP5+3UqZNcLpc9ndd9WTfvTXODeV1reT1/Fd6BlnUj8EZDqCxYko6tdSsduzld03GY1b54F+NYbc7x8Dc4PDxcHTp0sNfPtWaYWOMwSQHXz62Mr8Db+rLWCR80aBDjMDQ4a6kva9kMf+Ow7OxsZWVlqXfv3urSpUuNfk999XEac5+nLsTFxalt27aSAi8rabVD1Sl89NUHKi8v144dO+R0OtWxY0f2MWmkCLirKZhgyeFwqKSkRD/99FO11rqt7PWboup0EH3tDm51tLZv366CgoKgdwf3dT3WVEcqC9CYBLMkSVFRkdasWaOSkhINHz5cTqfTHnxUV2MPjxqCtWHctm3b1L9/f0VFRdk33VJTU1VSUqKkpKQabxhnce9o/fzzz+rRo4eSkpIIvFGv/AVL7jeyDh06pHXr1qlly5YaMmRIlWY2+OPdBvnqezVWddF2Op1OJSUlKSkpSV26dKkwnXfz5s2KjIz0qG7yt6yb1d/x5muwV9nG3exjgroUbLC0a9cubd68WZJ04okn1rjI6Hj/nfYO9n3NMPG3fq4VNlV3hon1/48ePWoXHhUXF1eorqQPhPrgvjStJJ9/O0tKSrR27Vrl5ubaFcg1dbyPw7zbIO9lJeuq8NFqY0pLS+2Mp7KNu7np3zAIuKsh2E2Utm7dqtLSUg0fPrxaa936UxcNW2NrLGvSIYmIiKhQXWk1dN67g1dWXenrj1agqXTFxcUBp/PS0UJtCKZi6eDBg1q3bp1at26toUOHKjw8XAUFBbVSQV2TCu76amcaoj2zOl3WdF5r/UpfG8a5B95VXb/SvaNVUlJity3eU+msjhZT6VCbKguWnE6nysvLlZaWpj179qhfv35q3759rb2+r3bEV7DVWNX1Z9B7Om95ebld3bRv3z6lpaX5nc5rVXAH8x6C3cfEu7oJqKlggyVrM9uhQ4fq559/rpXXtn6Hg91zo6mp7H07HBXXzz1y5IiysrI8Zpi4tz9VWT/X6vda/+bsY4L65mvfNV+/V5mZmVq7dq2Sk5PVvXt3HT58uFZev7FlNvWtsjbIu/DR37KSVthdlcJH6VgbFBER4dEOWe2Pr8DbfS83Au/6QcBdRcEES9YmSrGxsXbVTG1qyg1bXUzxi4qK8rs7uFVdae0ObgXe7hvSSL47zxb3wNu7o+UdeLuv20RHC1UVTMWSy+XS5s2btWfPHvXv31/t2rWzv1cbbYevJZKs66rOhnF1rT4/Y746XQ6H7w3jrM5WTTeMc7lcdqcpmI4WU+lQE97Bkr/fodTUVIWFhWnkyJGKj4+v1WsI5SVKGuK6wsLC1Lx5czVv3lzSr9VNOTk5FabzFhcXV2sJq6oE3mzcjeoKNljKysrS2rVrlZiYqFGjRtm/07Vxg9894D4eVTXYd59hIh0bR1szTLzXz7X6Qf5mmEi/Btzu/C3rxj4mqG3BFDm6XC5t27ZNO3fuVO/evdWxY0ft27ev1pZobMx9nPpQ1TbI37KSOTk5VS58lAK3Qf7GYRL7mNQnAu4gBTsVzn0TpeTkZK1YsaLWr6UpN2z18b68dwe3qitzcnK0f/9+lZWV2dWV1sC8ulPpqCxAbQkmWCosLNTq1aslSaNGjVJcXJzH993/8Nbkd839c2q9Zl5enhISEtS8efOAHYSm2nZJwf1c3afzWutX+tswzhrsBVq/sjodLSoLUFXBBksZGRkqLCxUy5YtNXjw4CqtPR+sYAJu+OdrWTfrhltOTo7Kysp05MgRj+qmmuxj4j7LzTvwZpYbghVMsOQ9DnPfzNZ96aSaIOCu2fsOCwuzgyTpWOBttT/79u1TamqqYmJiPCq83YsnfPV5vPkbh7lcLnscxj4mqKpA+65Z3JeGHDFihBISEiTV7v5pTTkHCkZNx7DWspIpKSmSfBc+WjlQcnKyR+GjVLU2iH1MGgYBdxCCCZZ8baKUn59fJxuq+ZueW5PGrrE1lvXVwfBVXVlYWGg3dLt375YkrVu3Ts2bN1dycnK1dgcn8EZ1WZ3ynTt3KjEx0e/vX3p6ujZs2KD27durd+/ePv9Ius9MqG7w5N5Js5ZBSUlJUd++fe1pqKmpqSotLbU7CM2bN7evu6kvUVLVzonD4X/DuMOHD2vbtm0eA0L3DeOs341gQvVgAm86WvAlmGDJWpIkPT1dsbGx6tChQ52E21Jw/ZXG1J/x1tj+rkdERKhVq1Zq1aqVPXBMSkpSTk5Ohem81s3LqkznDbSsG/uYIBjBBkuBNrOtrYDJV8B9PP2e1vbSLGFhYVVaP7esrKxa/Sx/gTcbd6Mywey7JvleGtLivfl2bVzT8aq22yB/hY/WTTf3wsdmzZrZf4eqwtc4jH1M6g4BdwDuv3zWh8nXL9qhQ4e0du1atWrVymMTpdqqFvDW2MLo2lQXS5RUhcPhUFxcnOLi4tShQwcVFBToxx9/VPPmzZWTk2NXV9Z0d3Cm0iEY7sHS7t271bVr1wqDtvLycqWmpurAgQM64YQT7KV4fKmtyiOXy6VNmzZp9+7d6t+/v1JSUlRSUqK4uDilpKT4vVEUGRmp8PBwFRYW2iFtXWvoJUqqqiobxllTfqsaJFZWWWBdB4E3ggmW8vPztXr1aoWHh+uUU07R2rVr66TvY/F3kz/Q9xuLxnpdFpfLVWFZN2s6b3Z2tjZt2qTi4mKPZd0SExOr1AYReCNYwQZLwWxmW1sBk69+1NGjR7Vr1y57FlttbKbbWNX12uO+ZphY7c/27dtVUFAgp9OpLVu22BWWVf15e4/nrT6Q9z4m3ktL+ssB0HQFuyTJpk2btHfv3gpLQ1pqs1/i62bdoUOHlJeXpxYtWlS5EC/U1GUbFEzhY1lZmYqLi+Vyuaq8rKT761S2rJt74M0+JlXTdP8C15B3g+brj5r7Wre+NlGyGqDa/iA25V/uxjj4CwsLU6dOnezqSms5gczMzArVlcnJyTXaHZzKAli8gyXrd8PdkSNHtGbNGoWHh2vUqFGVbtTjvbZ8dZSUlMjlcunQoUP2+rre5/O+UWSM0ZEjR7Rt2zYVFBTop59+UkREhL2cifsmZ6GsLjpdgTaMS09PlyStWLHC54ZxwWIqHbwFEywZY+wp5Z07d1aPHj3sv1X1HXCHUjVlY74+X1Nvvafzulc3Wcu6eQfeVd00V/IMvK0vNu4+fgUbLG3ZskW7d++udDPb2gqYvAPugwcP2ut9Hzp0SBs2bKiwXFtT+ltZ1wG3t4iICI/1c/fs2aN9+/apvLy8Wuvn+uKvD2T9DbS+zz4mx5dg9l2rbGlIS11VcLtcLqWlpWn//v1KSkrSnj17JMn+PDRv3rzeCorqU33O9Pcez/7888+KjY2t1rKSgV6HfUxqDwG3D8FULBUWFmrNmjVyuVx+N1Fy7wTVdsBd24PHxvYBaSzX4z393+l0Vtgd3L26csuWLTXaHVyqvLKgqKhI+/btU4cOHRQVFUXg3cT4C5bcO0fGGO3du1dpaWnq0qWLunfvHtQAyvr9qG77kZmZaXfkRowYEXTVjMPhUGJiopKTkxUVFaXevXsrNzdXWVlZ9iZn1hRUaymgmlZA1ffNsrq4memL+4ZxJSUl+u9//6sePXooLy+vwoZxVoerqpt/VjaVrrCwUIWFhWrbti1T6ZqgYIKlsrIybdiwQZmZmRo8eLBdbWcdX9cBd2Xnb4w3y6XGe12WYJZZiomJUUxMjNq1a1dhOu/evXtVXl5eYdPcqgbe/ma5FRcXq7i4WIcPH1ZCQoK9XAp9oKalvLxc+/bts4OF6o7D3NV2BXd5ebk9k61fv352G2jNeMjKyrJvACUnJ9uBd3Wq/RqT+g64vTmdTkVHR6tPnz6S/K+fa7VB1bnB4C/wtpZ1O3r0qPLy8tShQ4cKhUcIfdbftfT0dLVr187v35Zgloa01GZ2YxVQuofrI0aMsH8HreUiDx06pK1bt3oUFDVv3rzKY4LGJpilGeuK1S60atVKbdq0qbTw0X1Zyaq+TqDA+/Dhw4qJibFnDBF4eyLgdhPsVLiMjAytX79e7dq1U+/evf3eKXb/w1ibvK8pPz9fmzdvtn/Rq3P3WmocA6+GXqLEW2UbCfiqrvS3O3htVVeWlpZq+/bt9lIQ3pUFTKULXYGCJWtwVlpaqg0bNig7O1tDhgyx1y0MRnWXKHHfuKlbt272jZyqcg8trJBW8pyCalXkuFcEVrcCqr6XJ6nv17Q6y61atbKrm9w3jNuxY4cKCgoUHx9vD/ZqumGcdOxvTkZGhlq2bMlUuiYmmIql3NxcrVmzRjExMTrllFMq/E1riAruqny/oTXmz0VVB46+pvMWFBTY7fmuXbtkjKkQeNd0ltvevXvVsWNH+3fPfTkBAu/QZYWIZWVl2r59u7p06eIzuA52HOautiu416xZo7KyMo0cOVJxcXH2TAPv9Vytz0NWVpZ27Nghp9NpB03VKYJpDBryc+U9LvO1fq7VB7JuMLivn5uQkFDjwDsrK0vp6elKSUlh4+4mxhpnFRYWauPGjWrfvn2F33f3pSEHDhxo978Dqc1NJqVjN9KWL1+utm3b2jd7rKV1rEK8Ll262LM+vQuKrPanNgqKGkJjaYOCKXyMiIjwqPCuTpvvPg4zxujAgQNq0aKF4uPjWdbNh9D7ja4jwW6iFOxat9Y5pJpt6OaL+13A9PR0rV+/3l4DN9DmbqGgsQ1Kg9kp15337uBlZWX2cgLu1ZXug72q3km1/u0jIyM9lsFx3zBu5cqVmjdvnj744IOQ+bc/3lUWLDmdThUUFGjZsmWKi4vTqFGjqn2zpCqfs5KSEq1du1aFhYUaPny4IiIitGXLlmpX8fh6be8pqEVFRcrKyvIYoDT2CqiGCri9b2S5bxgnHfv3swZ7tbFhnPW61o00yfdUukceeUR9+/bVhAkTau8No864B0tWFa+vJUl27dqlLVu2qFu3burWrZvP3/e6DpiDCbgbq8bWx/EWTAV3IA6HQ/Hx8YqPj1fHjh1ljLGrm6ybblZhgNUGVWdZN5fLpYiICEVERPjcx6SsrEznnXeeFi9ebLeFaNysvyFWH9fXjTL3zWwHDBhgL5sTjNq68ZaZmSnp2NI9J598ssLDw/1+rr0/D+7hh1UEEx0d7RF4V/UGdH1r6AruQOMy9xtu1gwT9/Vz9+zZI5fLVaMbbtY1ePeB3MdhkvSvf/1LK1as0HPPPVezN4x64b3vmnUz1ft3w1oaMiIiIqilIS21VcHtcrl04MAB5efna+DAgfZ63/7OHWxBkdX+VHWJsYbQmNsgf8tK5uTk1Grho9UHcv/7472PyaRJk3TDDTfonHPOqfF7DjUE3AquYsl9E6VgG7TaWO/WF+sXe+PGjdq/f78GDhyoZs2a2b/gR48etcMha3M372qBxjwAlBrPALWmg73w8HCP3cFLS0vtwNvX7uDBVFeWl5d7VBL4mkp34MABbd26tdH8HOFfsMFSYWGhDh48qJ49e6pr167V/retyiAvOztbq1evVnJyskaNGqXw8HA7QKiOYK85Ojpa7dq1swco/iqg3NeX89YQS5RI9R9wV9Y+RUZGetw88LdhnPt03spuyJaXl3sc411ZIEkbNmxQ27Zta/L2UE9cLpfKysoC3uAvKSnRunXrdOTIEZ100kn2TVxfGrqCW2r8QXJjVdtTfx0OhxISEpSQkGDvY3LkyBFlZ2fb06etZd3cq5squwZrCUHrNbwrvPPy8vTLL7+E/FTs44F3sOReDevejniPw2JjY6v0OjUNmIwx2r59u7Zv3y6Hw6FevXpV+eawd/hRVlbmMeNq/fr19g3omszIrUuNOVzy5nBUXD83Pz/f42fucDg8Au9g1s/11QfyHoft3r3bXg8ZjZuvfdesvyXW71t1l4a01EYFd1FRkdasWWMXqnhvZhnM59K7oMhaYiwrK0t79+61bwBZmVF11pOua6HUBnnfYPBX+FjVZSXd2yD3/o/0a/931apVuvzyy6v8/pqC4zrgtoIla7p9p06dfAZLvjZRCkZ1lwOojMvl0rZt2zzuHlp3jN3vXnfo0MFjMHHgwAFt3rzZvnNkNV6RkZGNZkpvY1yipDavJSIiwmN3cH/Vle7LCXh3oL07Vt4cDoe9LAEat6oES4WFhWrXrp26detWo9cMNhzauXOntm7dqp49e6pz5872dbm3a7VVwV3Z9XpXQFnry7m3ae4bVjZEqNEQbVd1bsAF2jDOmgFU2YZxgWYlWe+fNqjx8xcsecvKytKaNWuUlJSkUaNGVfr5aoiAOy8vz56K3lj6M/40lv6NLzW9qV8Zp9OppKQkJSUlqUuXLnK5XPZgLyMjQ5s3b1ZkZKRHdVN0dHSF8wTqB1l9IEl+N/xC4+ArWPJels19HNapUyf17NmzWr+jNQmYrH5Yfn6+hg0bpp9++qla5/EWHh5eYUxgFSi5/z22ApLGMCO3ocOlmry++w03qz9ZnfVzGYc1Hf72XXMvUiwvL6/20pCWmvaLMjMztWbNGrVo0ULt27evtZsn3ntqFBQUKCsrS1lZWdq2bZt9A9oaY/n6e1zfGkMbVN1+kq/Cx5ycHOXk5Gjnzp3Kz88PqvDR/Sa/N6sPXFBQoISEhGpdZ6g7bgNu92CpuLjYXtrBXaBNlIJhddRqc6B36NAh5eXlKTk5WSeddJJ9h9Ef78FEeXm5HahaFcTx8fEqKytTQUFBpX+061pDN1reqrpESVUFqq70tzt4MEve0LFq3KoaLCUnJyslJaVWgtvK2qTS0lKtX79eubm5Ovnkk5WcnFzh+dZ7qM5r15R7m2ZVQFnry7m3adYf9fpq0xprBXdlgt0wzqroiI+PD+pnat2sQ+MUKFhyP8Zae79Xr14+iwB8qc8lSowx2rp1q3bu3Gk/Hh4ertLSUhUUFFR5+Yu61piDd6nu+zze3GfjSLKn82ZnZ2vfvn1KS0uzl3CwbvxHRUVV2g8qLCxUXFxco59qfTzzFyxZnE6nysrKtHbt2mqPw9xVdzyWm5urVatWKTExUaNGjVJERESdtXGRkZH2DWjr77GvGbklJSWKi4trkDFTQ4/TarONCnb9XPcK75iYmKD6QIzDGrfK9l2zfsdycnLs2dbVWRrSUt02w33mSO/evdWxY0cdOHCgTtof94Iia8aV99/jmJgYe9WAsrKyWr+GYDR0P6o2ix+ru6xksOOw47UNOu4Cbl/BUlhYmD3Is1S2iVKwaivgdh/ExcXFqW3bttUKbcLCwjzuHJWUlCg7O1tbt25VRkaG9u3bp6SkpAarFmjoRstbfQ/2vKsrfe0OHhsbq/LycmVnZ/vdfM8a2KPxcV+SRPIfLFmfd6tDk5aWVittSaAqgtzcXK1evVrx8fF+KzVrOjOltj/j3nfDrTbt4MGDMsbo+++/r7AnQV18pkM14HbnPgPI14Zxu3fvljFGERERio6O1pEjR/yuX0kb1HhVFixJx/72rF27VkVFRRo+fLgSExODPn99VXCXlJRozZo1Onr0qE4++WRFRUWpsLBQqampKiws1M8//2xv7mP1aRrDkhWNKXD3Vtuz1qrK13Rea7C3e/duezqvVawRGRnps7opPz+/0d3cwDGVBUuWsrIy7dy5U4mJiTUah1mqWsFtLTOxefNm9ejRQ126dPGYyVbX4xXvGbnGGHv22r59+5Sbm6vMzEyP6sqa/oyC0ZQCbm++1s/1XjM9KipKYWFhioqKUnFxsd+feUFBQcClvNBwgtl3zfrvX375RT179vT4/FdHdfpF3jNHkpKS7Gurj7zE/QZ0t27d7L/HWVlZMsZoxYoV9oxPa0ml+shMmnIbFOyyklYRR0JCgt88sKCg4LidxXZcBdz+giWn02kv8eG+iVL37t1rtNatVDtrLrkP4kaMGKHNmzf7PK46H/jIyEi1adNGGRkZatGihZo3b26vxeReLeC+1m1dNyqNaUDSkI3ojvxl+jbzb8p2lSo61qmTUs7QiZG/1759+3TgwAFt2LDB7+7gVA40TsEGS2vWrFFJSYlGjBhhV8Fa1Uw15atjZIzRnj17tGnTpoCbx1nPt55Tndeua1abFh8fr8zMTA0fPtyugLLWl3Offlpb68s1hYDb2+rs11VUtkixMflyxvfSiX2myFncWWlpaSouLtYvv/wih8Ph8fO0Qu3jeWpcYxVssHTo0CGtXbtWrVq10pAhQ6q1zqx30UBtKykp0bJly+xlU6RjgZg1/TwqKkqdO3e2Z3dYax3GxcXZAWpycnK9z1hrbDfxvdX1EiVV8cfHb1X0DocOrzgWYLcaXqrDbYr1zJ8e1oYNG+y/WfHx8R7TecPDw4/rgV1jFkywZI3DMjMz7dmqtTX7K9iAqaysTOvXr1d2draGDh1q33CxNMQySA6Hw642Li4ultPpVIsWLXy2b/6WOKwNDd1GWJur1YcNuYt0sOh1JcVnqzA2XrGdL1MPxxXatm2b8vPz9cMPP/hdP7egoEAdO3asl+tE8ILZd80KliVp4MCBVdrM1h+rzQg2V/A1c8T7XPXNfUml/fv3a9CgQfasTyuTsGY7WDM+62JM1JQDbndlZaX6T+Y9ig5bocgWpSpI7qAe0dMUXdROqamp2rFjhzZv3uyRA1nLSpaVlamoqOi4zYKOm4DbPVhy3whC+rXTU5VNlIJV00oma5O3Zs2aafDgwQoPD6/1ZU/ceVfvWdUChw4d0pYtWxQZGWl3nuqiGqqhGy1v9V3BLUklpWV64/tpSu+SpVITJqNwOWT0adb/tD16rUYnTVN+fr6GDBnisTu4VV25dOlSff/99+rUqVOdL88wd+5cPfHEE8rIyNCJJ56o559/XsOGDauz1wtVwQZLBw8e1Lp169S6dWsNHTrUY3BSW1WR3jfdrKWYsrKyglpbrrFVcAficDgUExOj9u3b222a93qLtbW+XKClZupKXbVPpWUH9On+mzUsMVWuCMnpkFzmsLIKlisu5nnFxLRRYmKiOnToUGHDOGOM5s2bp8OHDys7O7tCm17VNmPRokW67777tHPnTvXs2VOPP/64xo8fb3/fGKOZM2fqlVdeUU5Ojk455RTNmzdPPXv2tI/JysrSbbfdpn/+859yOp267LLL9Oyzz3p0/NauXatJkybp559/VqtWrXTbbbfp7rvvruWfbMMxxthhb9u2bX22QS6XS5s3b9aePXvUr18/tW/fvlqv5V40UNuMMXYFUZ8+fez9Adxv/rlvuONeDWxN/czKyrIrYepjdoe3xtTH8dbQFdyWm564WXlvRSv7cKmkY79L+/dK4SnxuifyIV077DKdfPLJ9mw2a1m3o0ePatOmTfr3v/8tl8tlL1VSV+gDBc8aZwUTLB05ckStW7eu1aKaYEOhI0eOaPXq1YqKivK7JEFDr/Nvhczu7VtpaWmFJQ7dqyt97adR3ddu6uFSQd5R/ePnSTp9yHIlxUhOh5HLHJHT8bxWH12ntvG3KyYmRh06dLCXcHBfP/ebb77Rpk2b1Ldv3zq9Tok2KFjuRY7W58fX73FmZqbWrl2r5ORkOZ3OWvv74b4BaaDPT6CZI5aGbn+kY9cZGRmp5ORktW3bVsYYO5PIysrSzp07PSrArSLJ2nrthmqDrJsUdd0Grf7PemV0uU39E9LlMsfGYW1MrorNBJXHz5UkDR06VMaYCstKStJnn30mSbX2M/ensbY/TT7gDiZYCgsL09GjR/XDDz8oOTk5qE2UglXdMNq9ktzfJm91zb1awFq/27sayqqcqa1qqIZusL3Vd8B94Og23X/nAvX6v/0qdcXK6P+Hif//f9cXFapP9M8KC+soh8P37uDr1q3T3r177Qq8K6+8UnPnzq31a33//fc1depUzZ8/X8OHD9czzzyjcePGadOmTfbUGgRXseQeLPXv37/CztjW82p7iZL8/HytWrUq4EDOW2Ov4K7s9a0Kz8rWl7O+gq0UaogOV223T6UlZfrvx//Vpr6v67wOqZKOdaqO/a+RjNHhwvtVXj5XYWFhPjeM27dvn7p06aJ///vfuvLKK9WmTRu98MILuuiii6rcZixbtkxXXnmlHn30UV1wwQVauHChLr74Yv3yyy8aMGCAJGn27Nl67rnn9MYbb6hr16667777NG7cOG3cuNG+WXH11VcrPT1dS5YsUWlpqW644QbddNNNWrhwoaRjGxSOHTtWY8aM0fz587Vu3TpNmDBBycnJuummm2rt59tQrGApNzdX27dv9xlcFxYWas2aNXK5XBo5cmSNqj7qavBlVVValZ1dunTxeM3KXt976qf7YMzasKkuZ6w1tv6NLw1dnZlzNFuPrH1E4ZvCVH64VN4//bKMUiXskTTs2N+ysLAwtWnTRm3atJF0bAZUcXGxcnJylJGRoWbNmmnYsGH697//XetBN32g4FjjMGtpSH/BUlZWltauXWtXLO7YsaNWZ4IE04fat2+fNm7cqC5duqhHjx4BZ7J5f54bOnSKiIjwaN+sykprSROXy2XvpVGT2WtNOeA2xujjHz/Rh3/8t+76dpUcMp59IEndo79ThusSxYf1VURERIVNQnNycuz+5IMPPqhPP/1UN954o26++eZav17aoOC477sm+Z854r005NKlS2utoNB6vUC/v5XNHHE/V2PrT3hnEi6Xyy6SPHDggDZv3qyoqCiPgqLqZm0N2QZZvw911QbllxzRY7NfUEr3X3TRCenHXstug6QolWpXwf2S7ld4eLgiIiI8ClMLCwu1evVqrVmzRpLUo0cPnX766XrsscfscVNtacztT5MOuIOdCpeZmans7Gz17ds36E2UglWdJUrKysq0bt065ebm+qwkr4uGLZj37KsayntdoNqohmroEMxdfTWih4sPaMGuOUpfX6Ru/Y8o2xUnVRjaSQ4ZpZUvVf+wGyp+7/+Hd5MnT9aaNWvUq1cvXXDBBTp06FCdXPNTTz2lG2+8UTfccOxa5s+fr88++0yvvfaapk2bVievGWpcLpcOHjyouLg4e2Mib9YfI0kaNWqU30F4bQXcVvuxf/9+bdiwQZ07d1aPHj2C/qyGSgV3MK8TaH25HTt2aP369UpISLA7Y0lJSX5v4jVE5WNtvuaqHfv11J8W6LRB61Q+pMxH63Osc5XgyNRB7ZfT2abi951OdezYUY888ogdFO/du1ddu3aVVPU249lnn9W5556ru+66S5I0a9YsLVmyRC+88ILmz58vY4yeeeYZzZgxQxdddJEk6c0331SbNm308ccf64orrlBqaqoWL16sn3/+WSeddJIk6fnnn9f48eP15JNPql27dnrnnXdUUlKi1157TZGRkerfv79Wr16tp556KqQDbu9gKTw83GcbkpGRofXr16tdu3bq3bt3jW9U18Ua3O4347p166asrKyAxwfz+fc3Y+3gwYMeM9ZqOhjz1pj6ON4aYtaa5ZNVafq+8EV9+cBq9T0wRFbltrdDP0Yo7PdhPn+O0dHROu+885SRkaGPP/5Yr776qpYvX14nVdz0gSoXbLBkbaLmvpltbc8ECTR2Ki8vV2pqqg4cOKBBgwbZG34F0tgCJm/eG0gXFBQoKytLWVlZHrPXrDFbsLPXGjrgrqubcJ/++A/92/G90u8L16l/ylaz8KM+jwtzGB2O/VQdwyqGRdZN1BdeeEGbNm3SVVddpZYtW9bZLBLaoMB87btW1aUha6sv417B7UswM0csjTHg9uZeAGOtZ2/tp7Fr1y5t2LBB8fHxHksqBdP3bIjlIH29fm23QcYYzf5qilaWxcg1v0DD/5OjcuNQmMPz39npkDpHHdBWVZyhb91kOOWUU/TCCy9o1KhRWrp0qb777jslJyfX6vVKjbv9abIBdzBT4axNlPLz85WUlKTOnTvX+nVUtYL7yJEjWrVqlWJiYgJu8lYXDVtVz2mtdWtVzrjv9r1nzx4ZYzzu1AWz4U9Dd5y81fVgr6y8TM/99Kb+V75V53XZpGX/G6L2A/MCPMOo3FVW6TVZ69/W1TSRkpISrVy5UtOnT7cfczqdGjNmjJYvX14nrxlK3IOllStXatiwYT4/y+np6dqwYYPat2+v3r17B/x3rc2O1q5du5SXlxf0QM5dKFdwV8Z9fTnp1809srKylJqaqtLS0go38dx/Hg0RcNc0jCwqz9U/Nnyh157dq2abDqvrhEKlKXAlf7kr8NJH+fn5kqRWrVqpd+/ekqrXZixfvlxTp071eGzcuHH6+OOPJUk7duxQRkaGxowZY38/KSlJw4cP1/Lly3XFFVdo+fLl9jquljFjxsjpdOrHH3/UJZdcouXLl+v000/3+IyOGzdOjz/+uLKzs0NyoyhfN/i9A+7y8nKlpaUpPT1dJ5xwgv23vKZqO+BOT0/X+vXr1alTJ/Xs2VP79u0L2P5U53Poa8ZabQzG3DX2AanUMO1Y6k/b9fJrX2lj3wJ1PiVMSgiTDgR4gql8cGntQ9K1a1f7Blttog8UWFWCJX+b2dZ2O+LvfIWFhVq1apWcTqdGjRoV1JTu2thfqT45HA7Fx8crPj6+wuy1/fv3a9OmTUHPXmvocVptFxOUlZfrmllPqfs5W7UrP0XRaTkK+13gf1tjghuHdejQQZdeemmtXas72qDA/O275q0+loa0ziXJ5/mCnTliCYWA21tYWJhatGhhL4NpFUlWdcm4hg64rX+/2nz95T9u0ZLDj2trSjOVfCiFu1xyOAL9+5oKyy17y8/PV3x8vIYMGaKhQ4fW2rVaGnv70+QC7mCnwrlvotSuXTvt3bu3Tq6nKp2gmkyNawy817r1Xps1IiKi0t2+G9v7qsuAe2fmOt3//YdKbJWllrHHliExEU4V/uhU8shC5ZoYGXm+tpFTXcyISgfWdb3J5OHDh1VeXl4hEGnTpo3S0tLq7HVDga9gybtD414tNHDgwKCm8tRGR6uwsFCFhYUqLy8PeiDni7/puY1NTa8pKipKKSkpSklJ8VhfzlrzXvp1SYPa3o8gGDUZ6LmM0X8P/axtxU/rve+GK3pnvuSQXDlGG4+000Ut1vp4jnTElShT0ipgG1RQUCBJHm1QddqMjIwMn8dnZGTY37ce+3/snXecXHW5/99n+myZ2V6zLZuy6b1sQpVIoliwcC8KCoogXOBS/IkFrKhYUERRsStXkCt6xQIigYgEEiAk23ezJdned2a2zE6fc35/xHOcnczslJ3Z3ZTP6/riZnf2e87MnPOc5/l8n+fzme01wfeXRqMhKytrxmuCSTB5TVnm4EzBbMRSoPmj3W6ntrYWjUbD7t27E6rTl6gcRRRFWltb6e/vZ8OGDcr3GM4oN/Bncz3+bMXY8ePHZ93sOpMx3x3cdS+38vWP/ozhSwrJSXfglwTINZBt9jHyt9B/k73Nez4HWsSIllgaHR2loaGBnJyckGa2iTarDdVwNDw8TENDQ1RNBsFYbPVKLJjr9NpCE9yJilHNzT18+v4/c8Udb3BIW44wKgICzT9LY897DaSrXQS/VVESSJ24HHV6+Bgkd8wn02j7fAwKj9l81wJf09raSl9fX9KlISF0c1A8kyPyWmdy/IG5N0kuNMGdiBgkihK/+Z+X+VlNI+9/vwOrvwTNtBMEgeFmMxt2nc5NihL0uPNQq2aXz0y20fZijz9nFcEdq9atbKI0PDycNNPGaIJjrAFuoSRKYl1P7oYqKytT9LvlwDWb2/diKhKTMQpnnXbyaP23GBkcp2NkGWuKxklVeUCCkmobNZ/O4tKPDWFPlfAjISEg/Ou/ZVoPeZ5tEKFxLNnGSucRGoGba3JRp1arZ8SAqakp6urq0Gq1MZHMc020ZBkCjUZDRUXFnAitcAST/LtY/i5ZSEaMDNa8DzThHR8fR5IkmpubZ93ESyTiLfQmvW7++80/syLrr6RKMDmVQpZkA+Cff81jz55hXp5cxsXmDsXcRJRObcKl6T/FpH/2znGHw4Ferz+NsDiP5CISsaRWq/H5fPT19dHS0hKzPFG0SERR6HK5qKmpQZIkdu3aRUpKivK7SHEkGXEmsBiTJEkpxqxW64zNLlnSZLb4uphynGDMZ3emJEn85oG/nCIjTDqmpmFdegf+a6sQDrtRHdYijvtm/I0qW4un3BWR4D6fAy0MoiWW2tvb6enpmdXMNjh3misCG47kWrCvr4+1a9dSUFAQ91pnA0JNr8lkU3NzMz6fD7PZTFZWFh6PZ0HPNREEt8PXxYGm7/CrL1YwUaYnV2/HLWoQ89WQqcLSY+BoSzkXr209VQf+KwdSCXDcuRGzp/h8DFqEiMZ3DWKThkzUJpucj8kxLZ7JkcC1zjYEN0na7XalvgpskpSlNhaS4A63aRsL+px/4H9+8yqH/1qOcZ8Xp/9UvSiuUoNKzct3Z1F2IJ+VKcMz6jCvpCaVW3BEsckfr8/C2YCzpvqUiaVIAS2UiVIy9CJlRJIokYOsIAhRB7jg4u1MuHgD9bsrKysVt2+r1TrD7TslJUXpQFtIoyMZiRyFkySJ+x/7P/6m6eUz217mL6Pb8PtVGNRe+qYz2JjTx+rV3Zx4xzaO3uhmy7dseJeIeFCjEUQKRDNXl/yI9rb2iN2iye5eysnJQa1WMzw8c454eHg45kLhbMBsxJJarcbv9yNJEn19fRw/fpzy8nIqKytjusbjLfYCuyDXrl1Lb2/vnK/puRBIZ0tRGCxpYLVaaWpqQq/Xz9jECzThTTThG2uclCQ/0/4evtlcR6e9m4tKJnBMn0qqnGVpGE9M0dZgYv1vxxGuzuA3Q9vZndGBSe1ixJtBSdrdrEp7B73+gxElSoITq3hiRkFBwayvl/87PDxMYWHhjNds3LhRec3IyMiMNXw+H1ardcY6oY4TeIzFDplYmq27RP5dW1sbmzZtUsiMRGOuOdXY2Bh1dXXk5+ezatWqkDqDsyHZG2mCICj63bOZKQXqd2u12kUf++Y795qyTdPTemqKQjfuxmYzoZpSMUkqadvd5OJFalFhefNU3MzZ4cW7wsVXr/+ysqkQDvJ4brJwPgeaiViIpWjNbJMlUeJyuaitrcXn81FdXR03CbnY7+e5QK/XU1hYSGFh4YzpNavVyvj4OBMTE0xOTirxLdGGvLNhLjHK7/NzsPUhnNl/5eVnN+NDjagX0Kd4yJp0MK3W4/2AAe2PRP58VRH2b+tYcckwOboppnwGnJ5q9pZ9m1c7X13wKZLzMWgmomlyhNikIRO9ySZzQnOZHAlc52yF7CmWnp6uNElOTk4qhrkAR48eVXKsZNRX4TDXHGnUNkCd7Q7GhUlq/3Y5kijh8OvIV02gFkT86zVIVRqmW4z87zuX85afmagoGkGv8jHoyGS5+W7KdTtpVbfOepxkd3Av9vhzxhPcwcRSuIA2m4mSTEAlA7Pt8scb4JIlDzCfyVo4t+/h4WG8Xi8HDx6cYX4SjX53MpAIjVuAAUcD9/3qj9T6c9i6rpdphxGt2odfUpGLg1cnKhmYNlOYOsE7b3yTmnUV/P3nK0hxuVi1LocbP3YdxYWnRqX9fv+s18p8jMbpdDq2bNnCiy++yJVXXgmc+qxefPFFbrvttqQddzEiErGkUqnweDzU1dVhs9nYvHmzMvYeC+Ip9pxOJ3V1dfj9fqWQ6+/vn3NidKaMx81nzJC79SsrK2ds4tlsNjo6OnA6naeN/M6VSIol0Rp1H6LN/gjjnjH+PriPVI0XAUhJcZOfO86w34y7dQJ9v4Pf/6yUJS862PmOMXoLV7LrLVexsXAfCKeOFSkGyQR3IOKJGdXV1bz44ovceeedys/2799PdXU1ABUVFRQUFPDiiy8qhPbk5CSvv/46t9xyi7LG+Pg4R48eVXToDhw4gCiK7NixQ3nNvffei9frVXRH9+/fz8qVKxe9PEmgJMlsxNLExITSsbRjx46kJr7xFl+BZnOrVq1iyZIlca8/n/Ep2ExJHve32Wwzxv3lzqPFGjvnW9tSq9OgUgmIooS5eZzpchMv/HMzey45yogmlcHqdNLWWThh7mfVypX88JbvAqcIimj0bxOlKR8K53Ogf0OSJCYnJxkdHaW4uDiuOiwUEk1wC4KAw+Hg0KFD5Obmsnr16rjz+7Otg3s2BE+v1dXVkZKSglarnbGhFygnkEzJtngna6cnXfz4T59j296DuMU0xk5mgQh6q5+DnVWUayboN2fgv0wHBgHN/6o58KlCDugK2HRJFXd+9yOkFp5qQotUG8p1WDIJ7vMx6N8QRZH+/n7FODVU/FkoachACILAyZMnGRkZiWtyJHCdcwlqtVrhhEpLSzl48CAVFRWMj48nrb4Kh7lM9h873EiD4T6Ki8aY6MzH51aDToXHpqcg30alxUKbOhfXfWno/teFbb+KP7wzBU3WUq678328/aMXAaeaQCI9u5K9yb/Y488ZTXBH07EUGNDCmSgls4M71NqB43lr166d0XkWDc4UcikWyG7fRqMRh8PB+vXrsVqtWCwWxe1bDlxZWVlJH/2XIYpiWKOVaODx2Pjzy5+lNluk781VeC9WoVP5yc0Yx1mbgjnNwZvHl/OW1a083bme7XndrM4aYtuFHdi2m/nP4v9HacpMp26/f3aDN5if0bi7776b6667jq1bt7J9+3a++93vMj09rbjpnu2IlliSJInW1lZMJlNEZ+zZECtpJPsMBHdBJmLnPzgG+f1+bDYbJpNp1vvlbIxdMoKTnuBNPJfLpXRADQwM4PP5yMjIUOJaWlpazElrNAT38JSNl3v3Y8r6CSqVH4+YgiipmPTomfQYMOmc7N7RwDPP72TsbUtIbZkg5eQknXYDOWMX8d8ffRemrH8nSfJ1H0miJNRoXKSY8eEPf5ji4mIeeOABAO644w4uvvhivv3tb3PFFVfw5JNP8uabb/KTn/wEOHU93XnnnXzlK19h+fLlVFRU8LnPfY6ioiIl4Vq1ahX79u3jxhtv5NFHH8Xr9XLbbbdx9dVXK5qLH/zgB/nSl77EDTfcwKc+9SkaGxt5+OGHeeihh2L6PuYb0XQsSZJEd3c37e3tlJeXc+LEiTk906JBPOSPx+OhoaGB6enp08zmgrHQHdyREM6s1mKxAKfMU+Vx/6ysrLju/WRA/szmq4PbmGZg06WrOHagBd2Yk7yXB7DsyOcvz+0iO3OS4lwv/7Hpnex5264Zf3c+B1o8EEURj8eD3W7nxIkTlJSUnPaaQDPbWEidRNZmkiQxMTHBxMQEa9asCbt5Fuua5ypSUlIoLi6e1ZA3cHotEY1CMmKdrHX6XTw3tp+//+AwF1zfAgIIgNHsQjWYhmEYXqzbwCff/jT+ERUdGZkM7zYh7tZS6J/glqXXsCl/64w1I23yOxwOJElKaqMRnI9Bgb5rQ0NDGI1GsrKyTnvdQklDBsLlciGKIuPj43OaHIGzv4N7NshxNycnR+H0QtVXgYa5icyx4pns73L28Ofuv9H/Yj2X3WDFJekwpLtBAJUkkdHq4pFX93HH9mdRW9fSnZqB43ojquvVVPocfHXHN9Cq/71pGCn+wPkc6IwkuKMllgJNlGYLaIkeQQlEcBByuVzU1dXh9XojjufNtuZi1+CeC1Qq1ayjKS0tLUkf/ZcxFz3KZ7t+S/8Lz5B5+QgDR7cjChJI0GIr5JpVbnJ1E2QWjfNa60q8DZVcUnmSSY+O13or2JK9lDtWfhSd+vQuiGiKu2R3DgD853/+J6Ojo3z+859naGiIjRs38txzzyW1a2qxIFpiqauri6mpKfLz89m4ceOc7rNoEy1Jkujo6KCrqyukvmUi4kfgGk6nk5qaGsW80mQyKcRNOBfs+cB8F5+RYoXBYJgx8js9Pa10eHd2ds4wfYqk4Rt4zHCfr9tn57tvPMif6vJ4z9bXWJPpw+sV0AtuTFoX4x4DrwxW8rbSJrIzp3j/u17meHsJ1gozS0zl3LD9PawsOF3CQr4GI5lMhkqsIsWMnp6eGe9n165dPPHEE9x333189rOfZfny5Tz99NOsXfvvTb977rmH6elpbrrpJsbHx7ngggt47rnnMBgMymsef/xxbrvtNi677DJUKhXve9/7+N73vqf83mw28/zzz3PrrbeyZcsWcnJy+PznP89NN90U9j0uNAK1bsPlQDJpPDU1xdatW8nIyODEiRNJm1iTEWtRODExQU1NDSaTierq6ogE/EJocM8FslltTk4Ow8PDbN68WfEk6erqUu79wHH/hUAizZOixUe+cCVdzf1YBidI6ZzC2G3Hna3nyo9fyrXvvxRNmMaV8znQwiKQWJIkCa1WG/Kel+swtVp9mpZ+JCRK/1aeoLPb7eTl5SWE3F5sMWY+Efy+wxny2mw2WltbcbvdpxnyziXGRDu5JkkiU7a/8RPLi3Q7JLRWUGv9qBGRgOUX9TDUkoNGgPzXnDw0/S7WbejiYnML0y4jo8MF3Pveb58Wa6LZ5JeNtpNNMJ3rMSiwDtNoNKfFoLlKQyaK4B4bG6O+vh5BEFizZs2cr4vFxNnMN0JNmoWrr2TT3ETmWLFMzoo+C60jj/GziR4mDmqpXG5HJUioBZHUbBeFq0cZbM5F71DhesnIF63/wTu3HmGNb4BxRypZwj4+fOm1p60bbQ50LsefM47gjpZYkonQaEyUEu3UHby2fDNaLBbq6urIyclhy5YtcZOyyUqsFkOyFookChxNAWaM/gfqd8vBy2QyJaxAi0dryeGf5nuNf2dvysM0+taiRwcCaKZBEGHEbual3iredelhnnl5O2sy+vCnQddwAekqPZ+/8AMsyymd9ZxmC2yiKM5LcQdw2223LYpRlPlELMSS3W5Xrt25JiTRbMS53W7q6upwu93s3LkzZPdIIhI2OQZZLBZqa2sVAj9QW7+vrw9RFGcYr813Ujafx4tlM0wQBNLS0khLS6OkpCSshm+kkV+/3x/yOfI/bxzDonmQp2svRJQECjOsCEiAClESuaygjf/rWU/HRC5Pd25kc24PecYpqlZZuDzvcpan7kEQQsc9+VkZSYM7XPyZLWa89NJLp/3sqquu4qqrrgp7LEEQ+PKXv8yXv/zlsK/JysriiSeeCPt7gPXr13Pw4MFZX7MYEEwshYtBVquVuro6zGYzu3btUq6f+ej8iWUzrre3l9bWViorK6moqIjqHjrTyaWUlBRMJpNy709OTmKz2RgcHKS1tRWDwaDc97J+93xgviVKAHKXZPHgc5/k4NNH6ajrwZSVxsXv20rpyvCTjYuluINzMwcKVYcFSz0G1mGlpaUsX7485lw6Ec1HNpuN2tpaMjIyKCkpSZhB4pkeg+aCSLlOoCEvoBjy2mw2ent7kSRpThKUUU2u9bQzcvKTeJZP0O1dj+CV8E5rcfl16PAhIFG2bQBLl5nm5ytR+SG3zs1gXSEvFazgG195P7kXhZ4iiiYHmp6eRqPRzMu08bkYg0L5rgXHIK/XS1NT07xLQwZCkiROnDhBZ2cnq1atoqOjIyHP1/Md3OHzlFD1VSJzrKh4IUni2IH/obT8Ef7JMrxSDsK0Br9Oxbg3hSKDjRG/iV0fqeWF7+xkfCCdVL+A/mU/hw5t5oLdy/nkXfvCvsfFsskPizf+nFEEdzTEks/no6mpCYvFErWJkhzAkuEeL5PnJ0+e5MSJE1RVVbFkyZI5HSdUYDtbdvOiSRjD6XfbbDYaGhoQRXHG6P9cXGRjIbhdHi8PvfQ7hvOOMD6lZbc1HV2KF6PgxVQ+waCpAFObm4mVen57vJp+exaXbG9BL3lpHyzhsqXXs6Hw0ojHWSyjcecaojVRslgs1NfXk5GRwa5du2hubk5IIhIp0ZIJraysLDZv3hx2Ay1RhVl/fz8DAwOsWrWK4uJi3G43BoOBoqIiioqKkCRJIW1HRkZob29Ho9EgCAIjIyPzStzMB+by/AjW8I008ms2m9FoNCE7uJ9tauPF5j9RsCQLURLQqPyMO1LJTrMrr9mc1Y1KJbB/YBn905mMOvN4W9FK7qq6gHTt7AWZXEDM9l7ni1w61xDtBr9cUK1YsYLS0tIZr0mm54iMaGKM3++nqamJsbGxmIvPSD4ki5V8CnVOKpWKjIwMMjIyZuh3y51HjY2NMzbwk6ktKT9f5pSfiv0I0gCSsARJFZ38Xkq6gb0f2s3eD+2O+jwXS3F3riEUsQQzzbTlezuWOiwU5kIuBUozLV++nLKyMk6ePInL5YprvWCEizHJqCMXG2J9j0ajkeLiYoqLi5EkCbvdPicJytnqsnH3BM3999H8mJUP3XaCP08uQ0BCbZSwWIy4rDr6NFkUGcYZ8pnZ8h8tLL+oh/76PIyaFP7jLZ+hKIKETjRTbLIPyUJNMJ6tmM13Ta1WKxtYsudIamrqnKQh55IveTwe6uvrcTgciuzayZMnE5KbnO0xZjbEuhEfLscK9kgJzLEiNRHOdl83j79O78GHyFKPkm52cmL0VHOmrtLHwJ8zKb7EiuhXYRKckAnv+NI/GWjIY2IgneVF63j3JTej189Ozy6mTf7FijOC4I6WWJqYmKCurg6j0cju3bujDmjyhZqMxETuYhBFke3bt2M2m+e8ZqjEKhGSA4sFsZ6LrN0tk2rT09OnJU+BnZCBo+uREK2ZwA/+/DeePdTK8g+cZNqlJzPVQbroYrQrk9Xqk+SbJhi/fAT+lIva6WJ8lYGXO6s42LGS1Zj59XX/iS5KjbpIgc3hcADJH407lxAtsSRLg6xcuZKSkpKQXQXxIlyxF2jMFnjc2daZS7zw+Xx4vV6Gh4eVmBYqdgqCgMlkwmQyKTqNnZ2dDA0N0dnZSVNTk2IKkujJC1h8EiWxIJqRX5PJhM/nU7rc5M/u5weOsnH9AMP2U88aQYCjncuozBtGrfLjF1VISGzP6WRbdjfLU79DvnEVRnV0mw1y/Jntvc6H9tu5hnDEUiBcLhf19fW4XK6wOtbJlGSTEYmYmp6epqamRtHDjOWZDGeeREkwZrt3Qul3W61WrFYrTU1NM7T7s7Ky5rSBHwxZWzKu9aQp9O6vofa/AvgBNT71RXj0nwYhsZvtkXIgSZJwOBznCe4EYjZiCf5N9o2Pj9PQ0BBzHRYK8RLcXq+XxsZGJiYm2Lp1qzL9mUhjyMUeY5KJueQ6giBElKBMSUmZ0V0Z3KwRqi6TJInv1P2N4sxfkHPIw8p1bgQBdPzr+hHA9F4ntQ+VobnXj19Sk6+dQFJDeoGLrRXbqUr/NCpV5Drs/Cb/wiCS75parcbn89HZ2UlHR0dMU2HhEG8MstlsygRdoOxaoiRP5PhzLmyoBWOu7zmcR4rNZqOlpQWv13uapFLg8cLxQuNOJ59u+D6fXPpXjjy9ik880IwkCugFPy5Jg67Sh0VMo+uZXLgCCnQT5Gsm8ajUmNaNsemS/yJbf0FU7yGa5svp6enTJErPJSx6glsmlt58801WrlwZMpkP3KmPJ6DJiVk0ou2xYGJigrGxMfR6Pbt27UpYt+K5JlESCwJHU0pLSxFFUdG67O/v5/jx44oJRbjkKRDRmAnc/7Nfsr/bQXnZBIJaQhAlOidzKV4/inPQyER/OqsL+2EzpOQ4GKvPIuuEh9QMH5/8wH+yYWllTO8xUnE3n6Nx5wKiJZbq6urweDynSYMkKqEJtU6gFEq0G2hzOR+73U5NTQ0Aa9asiWnDTq1Wk56ezvj4OFu3bp1hCiJPXgTKmRiNxjMqcYvHeCRahBv5lTcMhoaGFNLLMubA4dZTmjXKka5lSBK0DxVxoGkdF69qQqP2IyCgFlJYmX47Rcb1MZ1LNN2TyXbvPpcQiViSIZvK5ubmzjrBkUxJtsBjhIsxQ0NDNDY2smTJElasWBFXznWmkkvxnLNer59VW1KWcItnAz/U+cWbA+vd9/+L3FYDesCHxv8PcIPH8NW4zykU/H5/SMmmQJyPQYlDJGIp8GdHjhyhsrKSpUuXzvl5GE+uMjk5SW1tLUajcYY0EyR2rD84BkmSxNDQEFqtlszMzLO6czfRm/nBEpTyBMuJEydwOp1KI0RmZiZms/m0XKt3opMb//w8leubuCptiBdOlLN60zAgsV47wgFXGT5UGLZ7cAk6Xr1/BflVE6QV+ijJWcGVl32UjPToJ4ii2eQ/T3AnDtH6romiiM1mY3Jykm3btpGRkTHnY8cag0JNjiRjuixcHTo8PExGRkbMsj9nEhJN6sseKQUFBUiSNENSqaenB2CGpJLf7z+N8P7fhr/zSFsTV2+pY6l2isGeU/e+BGzWDvGSuwxJgKzb7fT+PovBL2RQsGWC1Aw9G8sv5a0XXolKiN6I93wHd2QsaoI7kFianJzE5/OddlEHmyjJD8lYICciiXTrlnUlU1NTyc7OTugo/pla3EWDRL+vQOO2pUuXRpU8BSam4XbJvH4/T/2jhgNHG+lXj6GzpaJedoo0MOi92EdTeMVezo23/oMffX8PVW89ycZt3ayoHMSWm84a03upLjndOCAaRCKYzo/GJQbREksjIyM0NDSQl5cXUls/kR3cgTv24+Pj1NbWYjKZYtpAi7fIGxoaoqGhgbKyMoaGhiI+XMMdW0awKYg8tjo6Okp7ezt6vV4hu+OVM1msGtxzhdFoxIueH9eepF3nRtIIrE3N4L1lxai10NpcynXv+zuZx+3YHGkIgsQrbas50rmMFQWDfGzrTjZl70Grip0AOp9YzR+CiaVQ3bWiKNLW1kZvb29IU9lgLFQHt3yefX19rFu3bk4mNGeqRImMuXQ/BmtLzmUDPxjxbtIJYi9q/2FOkdsyoagDPGj8L+MVB6OWK4kGi0l/8mxGtMSSXIfBKS+DgggSD9Ei1s24vr4+WlpaqKiooLKy8rRzTVYHt9frpb6+nsnJSWXiOHDK4mwjm5KZ62i1WnJzc8nNzQWY0QgxMDCAz+dTNhNMGWm8Nv45Hn55ORNpananTpGp9pCR5abxaB6bdw+Rp3XwDmMHf3Uuw4+AbpsX9VaRbFUV/7X0Y6TpY89TYsmBzqbvfSEQzfQsnJKGlM0EE9lQqFKp8Hq9Ub023ORI8HqJ6uCGf9+LVquV2tpatFot7e3t6HS6OddPixXJjD+CIJCSkkJKSgpLliyZIbUp16ZqtRqVSsXQ0BBWoYs3xh7mhy9dTOk2GxlqFyqVhEoNPSfMVKwY5xJDN91+Myd9GQh6ibRrXCDq2JVxNXuL3xLXe/H7/RG/0+np6XNaqnZREtyhiKVQJJGsOStr3Ubq6AgH+eJKBAnl8/lobm5WdCWHh4fnvGYwFnvxNlckMyGIJnkK3qkLJopfeLOBB548wFS2kSxrP770TAQR3MOnOqYFlURptoUfNF7KR1e9wv+7/2mOv1nGyEuF6HIMXHvZdzEYMuJ+D5EmDWSC+zziR7TEUmtrK319faxZs4aioqKQa6lUqoQYG8nfud/vp6+vj/b2dpYtW0Z5eXlM90ysBHcgMbV+/Xry8/MZGRmJOwaF+rtQY6uhdGiTJWeSCMwXwe0XRZ55oYGvNRzCaVYhSBL44c0pC22tU1y0oYyDr/h5tWk1N17yPH+r20LTYClIkJni4KpVV7C98ML4jx/FpNP09HTY++E8IiNaYsnhcFBXV4coilRXV0dF6M1HB3dwjiJPuHi9Xqqrq+f8fIpGomQxYiE28GMx4I63g1sl9nFKliR4akwDuBGkPiQSR3BH2uSXO93PE9zxI1piyWq1Ul9fj8lkUjZgEgW1Wh3VGL7f76e5uZnR0dFZNb8TRS7Bv2PQ1NQUNTU1pKamsn37dlQqldIBKMskarVasrKyyM7OPmvIpvmKscGNEFNTU7z55pv85vla0rf9AZPGw4QtHXXeFAgw5DWye08/n/uv3Vz0tm7Klk1wsamXKqOFWnc+Dl8aK3P+i3WmatQxdEwGIhqC+/wEydwRje9aoDRkQUEBdrs9ofdXtDFDnhxJSUmZlY9K1BSJ/FmIokhPTw/t7e2sWLFC8SY70+qnWDFf8SeU1GZHRwd9Q8N88ZeP884P/41n2y5AVING5cfiN+CXBC57Vw+/++lq7vrqa6TqfXxcV8NxbzYnPRloVCvYnncnRYb4cyK/3x9xWu9cbzRadAR3OGIpkOCOZKIUK+T15xp07Ha7soMm60qOjo4mvFsqGQT3YikI51tPKjh5kvW7ZfMBURTp6+s7pevlcPCl3z4NLU6m1uWDX0LwiejwM1kgMdVoImu3Ba3ZiyndwQq9h9+f2MJvpe2szsnjQzveztrskjmdr2yGGkmD+1wOanOBTCx1dXVhNptJS0sLSyzV1tYCsGvXrlk/70R1TMoJSX19/awdAtGsI28eRoLb7VakVwKJqXhjULT3drAGdaAObbRyJmeyBnc4vDn8NN/9xQkGu1U4t6Yg+CQE6ZTOtiRJTOEBIyxblctrL62ns6OILZva2FDSjce9hJ3qt+Pu8XLEdiRqQ5VgRFPcnde/jR/REkuy1EdRURErV66M+juc7w5ui8VCXV0dOTk5bN26Na7Jj2CEiz/y53S2NwGEQ6gNfDmficaAO94OblFVxKnubR//7uDmX/9WIwmJ3eyKtMnmdrvx+/3nY1CciJZYkr0/5DrswIEDCY0tgdO14eKGrOev0Wgi6vknMi4IgsDExARtbW1UVFSwdOlSxScqUCbR7/czMTGhdJieDWTTQun+CoJAu2WcL712guWTnbz33cO82rEcwS/gcmixe/S87szhmuKTfOzuRr73+e1cfEU32y8aQKMVKR3NY+0F96PWzm2zLRr9W4fDQUpKypyOc64iWt+1YGlIp9PJ5ORkQs8lmgncSJMjgUjUFIl8jMbGRmw2G1u3bsVsNuP1ehEEIab66Uy7ThdSd1ytVvPU8ZO88GInl7zrOBU6Cz2TWQg+gVF7GlM5OhpcWbzj6hP0d6Xx9U/sZt/7TlC52kb6hI+taW+lbM3NCMLcYn40UpHneh22aAjuwI4l+eINNjDx+XxRmSjFg7nu7A8ODtLY2EhpaSnLly9XHn6CICS8W+ps1+BeKITS7z58+DB6vZ5vvHiA+uZBVGY3YsqpBFoQJRyuVLLKp5H6DHgMavp+U0ru5cOkVk6j1/soNtq5vuqDbMnenJBzlK+lSBrc50fjYkcgsdTT00NFRUXI8Z7BwUGampooLi5m5cqVERPdREmUTE9PA6fG4Hbv3j2niZVo7rPx8XFqamrIzMw8TdN3LjEoETq0gXImHR0dSoeU/D+5g+NskShxeB28OHQ3v3u2mLHuLDzmUxsUgiQfG1QC+CWJ1wcGeOH6D/NGdx/P1Lfhn9zF21eupzLn1GZIrIYqwTgvD5A8REMs+f1+WlpaGBoaikvqY740uOVGhJMnT1JVVcWSJUsSdn9EE38WQz4TDvPZ/VhUVKQYcNvtdmw22wwDbpnszsrKioq4CQVJVYZfvQO1/xDg5d9ktx+/+iIkVWKNjqLxIQHOx6AYEQuxFKoOS1SuIyMSwR2rnn+iOrhFUcRut+Nyudi4cSN5eXlh441arVbyEohvsz4cFirHXwiCSZIkvvfz5/mVo5uMfg+5F4yjE3yka11IRhG1TUfjaCFpOjd/nCzlrRcO8I0tL1NzqICjdWWs3vBR1l50WUI2WM93cCcP0W7wh5KG9Hg8SeFbwsWMaCdHol0vFjidTuBULN61axd6vV5ZN/j+DFU/WSwWRkZGFDnI7OxsJReIRdZsIWLQQhHcNqudjz76JL0aifxeJyklLlJUXlKMbuxDeqy2NPpzTPyNYvzpcPN99fSfTOV4QxZv1G1j16WfISevOCHnHs0k7bk+zb8oCO7ggBZKDkCtVjM+Pk5LS0tEE6V4EG/RJ8sU9Pf3s2HDBmU8JHDdZHRbL+bibS5YTI7AKpWKrp5xfvqPelxL3OR0+3CuEpEQkAABcOWb8R3rJHupFluJCYdPi+O5EtQGP2kFan5y23VkpicuwMgPsEga3OcTq9gQTCxpNJrTkhCZWBoeHmb9+vWn3evhMFdCSZIkxV0eYO3atXGT2/L5zBY/Aj0EQpmkQPI7uCOtEU7OpKuri6amJtLT00lJSUEUxbhJm1gxF4O2cBBFiaeO/Jn9ltdYv2ISS+s6BCQEnwRIShw6dXyQBAHDv8Zut5ctYXvZktPWjMZQJbDLM1g/9LzJZOIRLbEkT4lpNBp2796N0WiM+Vjz0cEtx7ve3t6ozW9jwXmJktgRGDcDDbitVqvSgWYwGPD5fIyNjZGRkRFTju3Wf+5fRpOvA25AjV99AW79ZxP+XiIRTHa7XdHSPI/oEC2xNDo6SkNDAzk5OafVYckkuAMRWHfFssmXCHIpcKqtrKxMyQOjjTmzbdYHeo9kZ2eTkZGxKOVM5rtOe+3gcb736IucWO5HlW5E7RLxO1WM+VO5tLiVp9s3w4COwe4cXhFVjOWk0ujMIkPlxb+6nMu4CovNztDBgzO65yNt5ofD+U3+5CDQd202I8lw0pCJjj/ymqFiRiyTI4FIBCc0OjpKXV0dABs3bkSv/7c0WKR7MzAPKC8vx+fzhZQ1C7xHFtuEyXznUV63l5/+9B/8/c9v0vPuHHQTAtppP5IPRv1p7C1r5ve27Wh7DLyhrmC8KIUJr4EXNC4Eo5qybZeywrWeppYONO1dCTEFjxSDZEWC8xrcC4hoOpZEUcThcGCz2VizZk1EE6V4EE/R53Q6qa2tRZIkdu3aFTKZTqTmWyACb3CPx0NTUxM+n0/ZhYulCwAWV0G4GM7F7nLzy5eO8rvablxrRFRqCZVTwp+nwfDaNI5KE5IKBARGTOWY24fJXjKFqEnBUG7k/Vu3cNWeixP+Xma7T2ScH42LHuGIpeBEaWpqirq6OkV+KBZiaS6Ekt/vp6mpSdH0P3r06Jwf7rPFpMDjbdmyRek6CsZ8d3DPhnByJkNDQ3g8Hg4ePDgvhk+JLvqczkke/tFT/C17ig9vaafVmYvkF0APqQNeJqsMSBrAd4rkFlWn/vv2pcuiPkYkQxW5Oz7Yl+D8aFziEA2xFLjJVVZWxrJly+IuOpLdwT05OcmxY8cA2LFjR1wkfCREQ3AvxiYA+ZwWQ44TqN9dWVmJ1+ulu7ubgYEB2tvbcblcsRW6ghm34UEEsRuV2I+oKkFSzU2SLRwixSA5/iyGz/lMQLTEUnt7Oz09PWHNbBNNMAXqzMqIpu4Kh7mSS7Kxd0ZGBtnZ2adtAMV6vc22WX/y5EkcDseiJJvmk+A+8ORrfOdPb6DpHcdTnY/KA75UNf1/zyH/Uitr04e4ecM/+DEXg1WP1ZLHq6k5ZKSpeHjPlazJzVfOOdRmfmBuE23dHG0OdC53T8aCUL5r8UhDJmPzPlS9FOvkSKT1okWgLNSqVatobGyc832o0WjIyclRus9lWTOr1Upvby/AaRMmC435jD8el5cv/tcvOebx4E8XkQQBJPCma7DWmGi8uID3VR7l5EQOx7rLUZ800j5QRrthCduLi3lozzvQ/+s5Ec4UXP58Y9nQPB+DImPBCO5oO5ZkEyWv10tJSUlSyG2IPeiMjo5SX19Pfn4+q1atCnuhJWocJRCBSdrk5CQ1NTWkpaVhNptDdgFEO3KyGArChT4Hv9/Pfz/1NLVtYxhPunCtMSJoXUgaEKZBTFGjEabQD07jLkxFUktIWg3jxmIENDz4/osQHdOMj4/zyiuvzNipS8SDIdqxlPPkUmTMRizJhZokSfT19XH8+HHKy8uprKyMucCIt+gLpemfiA2zcOSPnDzKLuTJ0LKcj6RE7pAyGAw4HA42bNgQ0vBJvi/n0g0fiHj1a4Ph8E3TMflNDv1+gI6UXFy+YlI0XnQqP4ZMF85RI+pULZm1TmwbjEgaTnVyCwLLSONjO7fGfexQhipyQiZ3eWq1WrRaLaOjo2GfLee6uUm08Pv9TE9Pc/jwYS688MKQeYTP56OpqQmLxRL1GOxsSGYHd6AWZUdHR0LGwUPhTJcoWYzQarWYTCbGx8fZunXrDDKor69vhpRCqMkOGZKqDL+qLKnnGmmKxG63J20j82xCLMRSNGa2ySC4A9eMtu6abb14Y19vby/Hjx9XptoaGhriWmc2BG/Wz0Y2+Xy+hOUusSLZsdXt8nD7D35Lk3eM7KeteFYtQef0giTh14EzR4u9LZWBv+dwYJ/Ixvx+frTnNxwZrsDmSWFH0R4uKr5mxrUcy2a+HOMCO2MDEc1UoN1un/Oz+lxAON+1YEQjDZmMzfvAmiveyZFAxFs7eb1eGhoamJqaYseOHaSnp9PY2JjwezFY1mxqagqLxcLQ0BBtbW0YjUalflqoHGs+CO4j9R186S/PYe8bJ2VIA+lGVN5T14FPD1NlBjofK8K8cppDBRX816Z/MFJpomW8EC+pfKjqs+Slls9YM9gU3OfzKXKRJ06cUDY0A03Bwz3jopmkPdenSBaM4JaDGoRPquSAVlRURFpaWtKKJfkcogmMgY694boYgtdNll72wMAATU1NLF26VDEzkUmJ8fFxhdAJHDnJzs6OeyxrPrCQEiVun4e3PfgTptLVGBwaBElCEgQEt4B2Ws3EVh3mZz1MfDCD9D9aMPZN4yhLR9IIlKel8NAd/0FexqlgIooik5OT2Gw2BgcHaW1txWAwKIlTvE7q50fjEgev14vP5wsZfzQajTKKarPZ2Lx5s1J0xIp4SOlwmv6JIriD15ALx8LCQqqqqiIm74upg3s2qFSqkIZPVquV7u5uRc5ETtjMZnPcHVKJiF2jngkODv83G4xHOfryf+Df40YQoXG0mKqyAUa3Z9LzXBl+vZ4UtxfDS9M4c9VoU7X8586NXH/FTjQJfE4G6ofKXZ7Nzc24XC7l2ZKenj7DsFIQhHN+NC4ayBtscIrICJWwTkxMUFdXh9FoZPfu3WEL7liQjCIwUIty8+bNZGVl0dHRkTQi/Uzt4IbF0b0dDoGbdEajkeLiYoqLi8P6HgR2ds0n2RZpo//8Blt0kJuMIDyxFIuZbTImVuV41d7eHnXdNdtascYFURRpbm5mZGRkRh6YjOalYIQim6xWK8PDw4yPj6PRaPB6vXFp584FyZBjk/GP1ma+9MhfsO1IIa3BDSo1CAJ+gxZjnwNHWTq+FIHRren4/1aG5ZiJkSsy0Js86Hx53HrJZ0jTRpbECreZL28mNDc3k5qaqny2gZJN0dZhFRUVCflMzmbITY7h4k+gNGQkUlnevE8kjyDHtLlMjoRaLxbY7XaOHTtGSkoK1dXVM561ycxzAu+RiooKhZC1Wq20t7cD0NTURE5Ozpwkf2JFsnmiO37wOIddQ7grdBS+NI1oykXUa0hrdiKIIn6jCne2ltHlZo58rorBS0Y5uTUPlUpkbeYlXLnhmqjio0ajmWEKLk8f22w2RZXBbDYrOVbgVFqkGOT1evF4POd0HbZgBLdMKkUb0FpaWpI6VhtNV5PH46Gurg6n08nOnTujunCSkfAJgoDdbqe5uVnR/fb7/TMMCEN1AVgsFqULINCQLV4NoGRhvgtAr9fHy39r5Ndtb2ApUpHa+6/AJEmnSG6bFn+hC99GNSqnlozfeXFuTEPUixjHp7j5HXt434U7Z6ypUqnIyMggIyNDeTDIo4eyk7pMrGVmZmI2m6PawIk2sTpf3EWGSqUKu7nm8/kYGhoiIyNDMfCIF7F0NYmiyPHjxxkcHAyr6T/XeBK4hmwE19nZeZqe3WwIRSBFQyrNt+ljMIINnzwej9IhJScUwe7i0Z5zIpKuPwz8lUvS6/H5NLhdWlKmHUgGeKVzGZeVH2fZykEQYOSNfFxWAyqzit0bVdx71cdIMSSfYNJqtRgMBtLS0qisrMTlcikJb1NTE06nkwcffJCxsTF6e3tn7XSyWq3cfvvt/OUvf0GlUvG+972Phx9+eNbNOZfLxSc+8QmefPJJ3G43e/fu5Yc//OGMoqenp4dbbrmFf/zjH6SlpXHdddfxwAMPzCj+X3rpJe6++26ampooKSnhvvvu4/rrr1d+/8ADD/B///d/ygjhrl27+MY3vsHKlSvn/iH+C3L+I290+nw+5f+XJInu7m7a29tZunQpS5cuTdi9k+gObofDQU1NDWq1esbkRzIJoMVMYM+GxX7O4e7XUFIKwWRQWlrajFHbZDWkyIb0kTq4zxttR4Ycg8LVYXIusnbtWgoKCiKulwwNXEEQaGpqwu/3R113hUOs+ZNMagFUV1fPmMKc72srmJBtbm5WiMHARiZZpjKZZFMy4ti03cXv//wyjx1oZGLXqWeI2imicngACU9hOrkvjNL7ISP+FA0ujZrRHSZs9lR6DpfwuQ/u4dL1lXEfPzg39Hq9SndloGRTZmYmDocjYoPSuS4PEC1mi0GyNKSscx1pClp+Jvj9/oRt9qhUKtxuN4cOHYp7ciQQseZFQ0NDNDQ0UFZWxvLly0+bSgi8F5Mdk4IJ2QMHDpCTk8PU1BQ9PT0IgjCjfkoWt5QsgvtkxwBff+ZZOupHcV+WhsolnuratrsRzUZ8WalkvzzK2CV5uDME/Do9jgIdYxYzZbUZPHTTu8g1xX/PB/szOBwOhfDu6uqa0QEuN+eFg91uB85to+0FI7jDBbRAE6XAgCZ3VCYLkRIfm82maK/t2rUr6uCZ6CLP4/HQ1dWF1+sNqUEVCsFdAJOTk1itVgYGBmhtbVV2ItPS0qIiUJOJ+e7g/s0zf+dP36/D51dj2aFCKvo3SeQqMGAY8uIs1OGz6NFkuHCv1ePYoEVr8ZOdks6v7riWjCh2coN1rtxut0IMNTc3z7pTF4hox1LOj8ZFRqgYJEkSXV1dDA8PYzKZ2LJly5yvx2iLvkB9uerq6qRp+stJkdfrpb6+Hrvdzo4dOzCZTDGvsdgR6bvT6XQzDBenp6dPkzOJtksxntjldDn5++vP0zfZR6rBRG9xHTqTD49GS96SCUYOp5H5tmmsrjS+8tLb+fCWw1Str8W6OgWf10jOxAYuX/3fGOeB3Jbh9/uVDR+DwTAjIRsbG+OSSy7htdde45ZbbuGuu+7iF7/4Be9617tOW+eaa65hcHCQ/fv34/V6+chHPsJNN93EE088EfbYd911F8888wxPPfUUZrOZ2267jfe+9728+uqryrldccUVFBQUcOjQIQYHB/nwhz+MVqvla1/7GgCdnZ1cccUV3HzzzTz++OO8+OKLfOxjH6OwsJC9e/cC8M9//pNbb72Vbdu24fP5+OxnP8vll1+udHUlCnKCGhgjPB6PMoq6detWMjMzE3Y8+Zgejychaw0PD9PQ0BBybDiZMeJ8B3fiMOSa4KWxFsbcU6S6BZYT+TkQaqNQJoNaW1txu90z8plEkm2BjRzhcN4DIDpEMrOVN62i7VZMNMFttVrxeDykpaWxffv2OZNWscQFi8VCXV0deXl5IUmtULXdfN7bKpUKg8HA0qVLARRJIavVquhLJ6uRKZF1ms/n4emBL/H8t1QMZpkRnF5EfRoqt4iz3AjPjaGecOI3G/EWZ1HyP/3YtptwlqUiqAX2blvGZ9+9B02CO8q1Wi15eXlKk4nT6VRqtrGxMSRJwuVyKU1KwRtq5ydpo0O4OiweachEE9ySJDE4OIjb7WbdunUJkciNdopE9jzo7e1l/fr1ITvXFzrPEQSB/Px8ysvLEUVRkTORuSWj0ahsuCVy0zvRPNGQs5EnXnuUY48U0Lc+E18WIIAggnNZCqY3bPgKzbgqskg5aaH4D31YdmbhM2kxGbXcd9XlXFwV/+ZaKAiCQGpqKqmpqZSUlCifrzzB4/f7qa+vDyu3OT09DXBOb7ItuMmkjEgmSsnoDAhEuLHdwE4qWXstlhsrkRIlExMT1NTUoNfrSU9Pj+vCFQQBs9mM2WymoqJC2aU+efIkY2NjHDx4ELPZrASl+e6Cma9g/VrDSe5/7Sn0vwPQgsoPqBD8At5MEfWUCkmjRjfuRZA8OAu0+Jyp+PV+Mh0Cv7rxaoqyMuI+vl6vn0GsySaqVqv1tJ26QGOHaDS4z4/GRYfg61omlux2O8XFxQnTVI6GlB4ZGaG+vp6ioqJZJUIS1cHt9Xo5fPgwqamp7Nq1K2a5nLlocC9m4imcnElPT4/SpSgnFBkZGTO+p1iTrpeOHOPpwccQCn2QAn5BwOHS4pcE1ILIhe9s4vc/3E3xkWlMO5z0ubL48WuXkqb18OFNpXxk9Xt56aWX5t10KlwMEgSB3NxcPvGJT/DAAw/Q0NDA0NAQpaWlp722paWF5557jiNHjrB16ynN8O9///u8/e1v58EHHww5STAxMcHPf/5znnjiCd7ylrcA8Mtf/pJVq1bx2muvsXPnTp5//nmam5t54YUXyM/PZ+PGjdx///186lOf4otf/CI6nY5HH32UiooKvv3tbwOwatUqXnnlFR566CGF4H7uuedmHPtXv/oVeXl5HD16lIsuumhuH2AIyPmN1Wqlrq4Os9nMrl27kiL7kIgO7kDDubVr11JYWHjaa5JlsA3/jt3h7rnFGmcW2zkdG+/iW+3P4vC7T3VGSxLp6Ciwl7EsLXp9UZ1OR35+Pvn5+YqZm5zPzMXMLRTkayoaDe7ziA2BdViwPFo0SFSdJkkSnZ2dnDhxAp1OR0VFRUIIq2hiktzk0NHRQVVVFSUloY1SF9tGVaCkUCAZIkskBmrnZmZmzolsShTBZHOP8Kv+/8fEm0YmT1TgLdCg8nn+ZSoCfpOGyV0ZmF7rx72iAF9WKv7MFNJG3LwlJ4/P3nclOn3sUo/xwGg0YjQaKSoqoqmpCY1Gg9FoxGq1cuLECTQajRLjZJm2aAnurq4u7r//fg4cOMDQ0BBFRUVce+213HvvvUoO0NXVFbKuO3z4MDt3/nuC+KmnnuJzn/scXV1dLF++nG984xu8/e1vV34vSRJf+MIX+OlPf8r4+Di7d+/mRz/6EcuXL1deE890XbwIvo68Xi9NTU1xSUPKZHkiYpAsUSl36yfK/y2apkdZLcDlcrFz586wn3u4SdqFgEqlUrilpUuXKtyS1WpVNr0zMjIiNvFFg0TFH0mSOGr7NS9PPk/bX8rx+VT4fRpUHglO/R9TG9NJbbJjbOzDvbwAV2UOKo+fghYPN990Afv2bZjzeUSDwM+3vLycf/zjH1RWVjI1NaXIbcr1aUpKCiMjIxiNxqji/NkafxaU4JZvzmhMlJJNcIcq+nw+Hw0NDUxMTMTdSZWoDu7+/n6am5uprKxEr9crUiMyJEmKq3iSd6ltNhtqtZrCwkKlC+DkyZNoNJoZZpXzobOY7AD9v795mR80vUmhagovWSD5QZTQa3wIDgPuHD9aqwq1XYU30wh+EXOLC1O6ntvefzFvuWh1Qs8ncKduyZIlp+3UtbW1Kaah8utnw/nRuNhhsVior69XJjT6+/uxWq0JWXu22BUNURSIRJBGExMTTE1NsWzZMiorK+O6384EDe65Hmc2ORN56iIwYYt2Q6RzcIxPPvIXMktrSd3iwzcFgl9AUEvY0w20OvJYmzpE1cY+3nvzIQ7+eQ3eP6SzodTCqs3LueaKK8jOzJhhjjqfiDTlI4/GZWZmht1oO3z4MBkZGQq5DbBnzx5UKhWvv/4673nPe077m6NHj+L1etmzZ4/ys6qqKkpLS5Uk6/Dhw6fpNO7du5dbbrmFpqYmNm3axOHDh2esIb/mzjvvDPueJiYmAJRrIdFQq9V0d3czPDzMihUrKC0tTdpzcK4a3HLh5/F4ZjWcm2+C2+/343Q6Fz2xuViIMY/o4wcnX2Da58KsPSXF5PF4mBRdPNp1gG+tuTruZ4Ns5ibrd8v5zMjIiGKCHmjmFkte6ff7w06AyjjfPRk7AuuwjRs3KmPosSARdZpspjY5Ocn27dsTaqQWqR7z+Xw0NjZis9nYtm0bGRkZMa21WDawAsmQYO3ctra2GRMW2dnZMZNNcyWYeq3DfOm5n7J9WwMqncB4ax6SBFrBh8OQgm7MiydPi8opMr47A3eujrQGG/p2G9s2L2f1W8t5/7Vvj3ygJEEURYxGI6WlpZSWliKKomLG3d/fz5VXXonL5eI3v/kNKSkpXHrppbNeS8ePH0cURX784x+zbNkyGhsbufHGG5menubBBx+c8doXXniBNWvWKP8OJIAPHTrEBz7wAR544AHe8Y538MQTT3DllVdy7Ngx1q5dC8A3v/lNvve97/HrX/+aiooKPve5z7F3716am5uVLv94pusSgYmJCWpra0lJSYlLGlIQhIR4jMiNBpmZmSxfvpxjx47Nab1ARGp6lBsZzWYz1dXVs27sLdaNfJg5ASFvesv1k9zEFzhhEst3nQiC+4lDf+fPQ6+wZUM3Rr+PyZNpqAQJlUZEPyAy6ZeQ9AJ+1Ax9sJC02ilS2vrJMqazcVsp77pmJ1WrV8zpHOKFfH3n5OQo0mHyFJ3VauWJJ57gq1/9KoIg8LWvfY23vvWtbNmyJey1dLbGnwXv4I7WRGk+OrgDk5WpqSlqamoU/c14id25dnDLrr0DAwMK+T80NJSUoBZqJELWjQ42ZMvOzsZkMiWcXEmmRMmvX63hd8+8gadrCu9eNarX/3UcAQQEjGNe0jwepjQ67Mu96GxqtDYVSLB6Qwnfu/qd6LXJv2VCJadyJ+nw8DAej4cjR47MMHYLJJxk/cnziIxA09iVK1dSUlKCIAhoNJqExRs5BgTrm7pcLurq6vB6vbMSRcFrxUsaybGkr68Po9HIsmXL4loHFndilSyEkjORE4qTJ08CpyQ7hoaGQsqZ+CWRP7Qe4sf/U0dKn4uUt/kQXYAfJCTwC2Q4nfx+dCOp6iOUGmxs2nqS9Zs7sU2XsibvhxgNZcp68nWw2AjuaEbjhoaGTtOXlzdTh4aGwv6NTqc7rVDMz89X/mZoaOi0UU7535FeMzk5idPpPE3nURRF7rzzTnbv3q0kaYmCIAi4XC48Hg8WiyVmqaB4MJcObrnwy8rKYvPmzRGLr/kguOHU+PixY8eYmppCr9eTkpKCx+PB6/XGZeZ8LqBxsg+Lx06axqB8noIgoEdD5/QofS4rJcb4jJUDEawdLJug22y20zqPQuUzwZAnSM4T3HOH/BkG1mGBOvqxQqVSKaaV8UAmuNLS0pS6K5GmuLPVY9PT09TU1KDVaqMi186kHChYO1fWdpVru3jIpnjrtJ/+40VePfg8tt0G7CodRsGFoJFAgPRBB+Ol+WT9c5TRfWn409UggX1TOq5lKTyw5a1sKMk5rcFrvhGcAwVO3C5dupT6+nq2bduG0Wjkvvvu49prr+Uzn/lM2PX27dvHvn37lH8vXbqU1tZWfvSjH51GMGVnZ4fVw3/44YfZt28fn/zkJwG4//772b9/P4888giPPvookiTx3e9+l/vuu493v/vdADz22GPk5+fz9NNPc/XVV8c1XTdXBE5NVFZWUlFREff1NZf8JnByRG40mJ6eTmgeM1uHeV9fHy0tLVF/BmdKDArc9Jab+CYnJ7FYLMp7lg1do5Uziff68Pn83Po/38TqdrBhZy8u1KSqJQSVhOgTyNDaGS/IJOOVccZ3pyMaVYhGFbZLsxCqMvn9HR+nrbmFdPPCcSyhmpsCp+hWrlxJfn4+9913H3V1dXz3u9+loaEhbAPd2Rp/FozglgNJe3t7VDezWq2eU+IUCYFJlNwtXV5ezrJly+ZEuM6FkHK73dTW1uLz+U7T5E1GUAteMzDpkc9HTooaGhoQRfE0Q7ZEn0Mi4HD3cM1P/kq3X0tu4whCego+rQpVoRfaAUkAQULTqiVzlQNdlx+HVovP5Eet83HXBbt4344tCT+vaKHRaBTTUI1Gg91uJzc3F5vNRktLC16vF7PZTGZmJhMTEzEXd+Xl5XR3d8/42QMPPMCnP/1p5d/19fXceuutHDlyhNzcXG6//XbuueeeGX+zmEZTooHL5eLNN9/E4/GcZl6UyA01+UEdSHCPjY1RX19Pbm4uq1evjnpcNN7kTSbTfT4fVVVVp33fseJMkShJ1mZZoJyJvBnY2NiIx+OZYbomx8YRj49vtv4fg81TaIZTUWt8oAYCpJAlJAxeL4Io8cfud5GfNUqx3sWytE3sXPIBNKqZhLl8Hcx3R+hsPgBf+MIXeOihhwDCbgq3tLQk7dySgVtvvZXGxkZeeeWVhK89MjJCbW0tKpWKZcuWJZ3chvg6uAML0MCNwEjHSaYGt3xeFouF2tpaCgoK2LBhA1NTU/T19eF2u3nllVcwmUzKpnwyjdeiwWIqRr2iH4nTGwoEBCQkPGJyGkqCTdDlyZhQ+Uwo/e7zRtuJgyzB2NbWlhAzW7VaHZdXkiRJ9Pb20traelo9mEhT3HCbbrJE3JIlS1ixYkVUm8bJ3MBLNkKRTVarVZGniUQ2xdOI1N1v4SePH8Rq+ieTuemgOSUBICKQu9HG0Ks50KMhP9PK8Jpssv9px5fqxJ8uoJU0fPOG97Jl7VIGBwfnfVM/GJFiUFZWFoIgcM8997Bz5864rpOJiYmQE2Pvete7cLlcrFixgnvuuWeGv8nhw4e5++67o/BWGgABAABJREFUZ7x+7969PP3008Ap/5GhoaEZE2xms5kdO3Zw+PBhrr766rim6+YCj8dDTU0NU1NTEacmokG8tVvw5IjZbAYSP4kWKi8SRZGWlhaGhobCqhiEwplCcAdDpVKRkZFBRkYGlZWVeL1ehVs6fvw4Xq93xnRssFRuvPKhzx9s5ocvvkzh9Aiey02kq7zYJD1qvUT2hnGGX8smrd6Fe6MG51AWec9O4M6VkLQqysxmfvaZG9DrtGHNuOcL8hTbbFKm2dnZFBYW8tRTT8V1vmdD/FnQDm6XyxW19Md8SJTI42nDw8Nxj+gFI94kaHx8nJqaGrKyslizZs2MTqlkFo6zIdjh1W63zxg7NRgMMzTe4tXMS1QBKop+Xuh/iGdftdDrWoqkB53NiztdAJuAe7ca4WU3kqAHRJBA26LDLEhcdnEuH//YXurfqOHS7ZsTcj6JgCiKp3WSyqM/Y2NjvOc978Fms/HDH/6Q6elp3va2t4XUwA3Gl7/8ZW688Ubl34Fk7+TkJJdffjl79uzh0UcfpaGhgY9+9KNkZGRw0003AYtvNCUayJ1ly5cvP+1aTQbBLSfFJ06coLOzk1WrVrFkyZKY1oon2ZINcrOzs1mzZg02my0hCVu8BPd8YT5jpEqlQqfTkZqaSmVl5YxxscO19fy4pw31yiHctkz0XnCLKfhtApocCb83YCE9GLw+bsq/glVLq2Y9ppzkLRYNboDbb7+djRs3cscdd3Do0KGQ3/fSpUspKChgZGRkxs99Ph9WqzVsd0BBQQEej4fx8fEZRdDw8LDyNwUFBbzxxhsz/m54eFj5nfxf+WeBrzGZTKd1b99222389a9/5eWXX475Xo0GLpeLqqoqBgcHE752OMQa27xeL42NjUxMTMRUgM6HREl3dzcnT55k1apVFBUV4fF4yM7ORhRFPB4P69atU0xje3t7EQQh7rHYRJ/7QqMqvZAUtQ6H30O65tTzVxIl3Pgo1GVSmoDu7WgQLp+Ru0vl70wmvKM12pYJivMID7/fz+joaMLMbOMhowOlUUJp7iYyjsjPLZmglSRJyceikYgLxJlKLgUjkGwK1s6VyaZgX6ZYCG5Jkvjfx1/ll4cbcWm8bJ/yMLRGAFEiXzVNny+NrNWTFF40yuDLuWjeFChIteFdriE1M5OPv+tiLlq5Sllvockl+RyiiUFyY06s59vR0cH3v//9Gd2TaWlpfPvb32b37t2oVCr+8Ic/cOWVV/L0008rJFO46bTA6TX5Z7O9JtbpurlgcnISlUrF7t27EzJtFU/tFmpyJHC9UBO48SI4nrlcLmpraxFFkV27dp2Wg86GsyUGabXaGR4egRMmgVK5gQ2XseRRkxNOPv+VP9A4bSfrwkEm/54CGmi05FFmnMArqai8sp+p7lScQwbML7swLXHiXq5nfWUxn77q7eSk/rv5ZKFjULTxR97kP1fjz4IR3IIgsHr16qgTl2QT3H6/n+HhYUX7KZYgMxviIaPlkY1ly5ZRXl4e8kZOdFCLtegSBIH09HTS09MpKyvD5/MpciYnTpzA6XQqGm+hunDCIVESJV2WPr7Z+jM+XfkcX227DtF8yhHXa9Yi+HyY6yV683JYftMQrl+mI3qNIAiAyMpVZu655/14PO6Io7DzjWByKXj05/jx46xdu5aqqiqefPJJXC4Xd9xxR8R109PTwxJLjz/+OB6Ph1/84hfodDrWrFlDbW0t3/nOdxSCe7GNpkQDg8HAqlWrQv4ukRMj8vXjdDqpr6/H6XSe1jEeLWIp9gINcgN1fRORFAWvMT4+rmxUyIVQvGPOZyokSVLuTY1Gg7V7mu7jFo74HPjSXWhVoBHBlwLaSTWWgyby3jWB2gSiBwQtCCrI7StiVfXs5DYsXJI1W/dSTk4O2dnZmM1mqqqqwsbO6upqxsfHOXr0KFu2nJqOOXDgAKIosmPHjpB/s2XLFrRaLS+++CLve9/7AGhtbaWnp4fq6mpl3a9+9auMjIwoSdL+/fsxmUysXr1aec2zzz47Y+39+/cra8Cp7/L222/nj3/8Iy+99FLSTHvlZ+fIyEhS85tAxEJCyVJtcl4Ui1RbMjsc5XW7u7sV0j2UHq7BYKCoqIiioiLF28JisSidirOZxiYDi6kYNWtTuKp4O7/pPcSEx4FapcIjedEIaq4t2Y1WFb8JXbwINcoc7Eei1Z7qoBoZGSEzMzMkKeJwOBJmCnY2Q6PRsG3btoRdl7HWaXa7nZqaGnQ6XVhplGQQ3KIoIooi9fX1TE9Px5WPnS3kUjCCtXMDyabOzk6F8BsbGyM/P3/WZ8L333iKF37XjatbwF2UhqQBtUZCNQRioUD7cCaabHCodCy/uofcjeNY6jLw+wS2bFjPf771WrTamXFoocklmH2TX/69w+HgBz/4AY8++uisa7W0tFBV9e98r7+/n3379nHVVVfNaDrKycmZ0R25bds2BgYG+Na3vjWji/JMQ25u7py7tgMRSwyabXJERmDMSMR1F5gXWa1WamtrY57kDVzrbItBoaRyZYlWeTpWbkywWq2z5m0Wh417n3mc/icmmS7IQOWREHR+1OMSeGBEk84e4SRNnlzyMyfZ8qkWRt7IYqonBXWKxMeuuJWqFZWnrbvQMSjaKbbh4eGI/NXZHH8WXIM7WiST4B4ZGWFgYACj0ciOHTsSeuHGkpwFjqnM5h68GIOaRqMhJydHGa0J7MLp6emJunNqru/L6XKxv+H7/G1kFHPhJF6vAb/3X9+nAFOrzOS+OMz06izS/inStrmIjNvspPRNIgyrueuq93BR1ToA3G7XgidSwfD7/bN2nel0Ovx+PzfddNMMZ9tI+PrXv879999PaWkpH/zgB7nrrruUrubDhw9z0UUXzUhk9+7dyze+8Q1sNhuZmZmLbjRlrkikBrfcZXvs2DGysrLYtGnTnKYbookncleU1Wo9rTsrERMggTFI3pCTJwUGBwdpbW0lJSVFkQaQdVXPFomSUJA352r7evjxZ3/PZLMFtSQwuDMXaacfI5BS6GZM0qC1C0x0FyH9n4qsHeNoCyREq0D59DI+fsXHozpevGN6c0U0JpPBI4XBWLVqFfv27ePGG2/k0Ucfxev1ctttt3H11VcrG1n9/f1cdtllPPbYY8rI6A033MDdd99NVlYWJpOJ22+/nerqaiXWXX755axevZoPfehDfPOb32RoaIj77ruPW2+9VYmbN998M4888gj33HMPH/3oRzlw4AC/+93veOaZZ5Tzu/XWW3niiSf405/+RHp6utI5YDabE7b5HYhkS7AFIlqJElmqraKiIi4z2mRNmjmdTmpqagDYunVrSFmXUOca6G2xdOlSZcrCYrHQ3NyM3+8nIyND2aBLllnlYtowf0/hVvL1Zv42XM+we4JMlY6LUiq5OCfyBtt8IJQfSVdXF0NDQ3R2dtLY2Kj4wmRmZirPmfM+JAuDWOq0gYEBmpqaKCsrY9myZbOOWydSogRObdzV19eTmppKdXV1XJ2ji7EOSzTC+TLV1tYyMDBAe3t7SP38g+1tPNrzK4YPLMHY4MZbkQGihH5ExLtZQP83P741ampZwrbJHlKz/Ix40tEu81G+Yoy92R9hefqlIc8psJFgoRCtD8mdd94ZscFo6dKlyv8/MDDApZdeyq5du/jJT34S8Tx27NjB/v37lX+Hm04LnF6TfxY4rSBPrcuviXW6bi5I9PMw2hgUaXJERiDBnQjI8UyWhopW8i0UzoUYFKhvL0/HnjhxQsnbfD7faVK5giDwyRceo2O4h6k3sjBOioglalQeL2M9mWyq6mT6aDa+3QJP9qzlyiUtjHlTcWnUpO22s+JSFe/P/xYGbegccKFjUKQNNjgVg1auXMnf//73WV93NsefBSW4Y7mhk0Fwi6JIe3s7PT09Sst8oi/aaANQLGMqyQpqiVzTaDRSXFxMcXFxWI03uZAMNBWKt4NbEkVeOfgYr3e+jlTuRJORgUHlI9cwjdbgR+NU4U0BZ5ER285sTEdteItSyRgH0lNZsXIlX/n0e9AFdAssFIE0G6LZuXM4HDFpVv/3f/83mzdvJisri0OHDvGZz3yGwcFBvvOd7wCnRkaCOxgDjdsyMzMX3WhKNIik+Z+IeCNr14qiSFFREStXrpyzxmWkRCuSWVIiCkaZaG9ubmZwcJBNmzZhMpmQJImKigplzNVisSi6qpmZmaSkpCBJUlLNZBcKg+NTfOcf/8TXMkRqrQMxRQCdCsnvwzliIL0C1FVO0oe0TFXqSOlXMTFUxMSfCtDmqvjv92zFaPLyxuuvz5h+SUtLC/lZLVQXQaTxOIfDERW59Pjjj3Pbbbdx2WWXKXr73/ve95Tfe71eWltbcTgcys8eeugh5bVut5u9e/fywx/+UPm9Wq3mr3/9K7fccgvV1dWkpqZy3XXX8eUvf1l5TUVFBc888wx33XUXDz/8MEuWLOFnP/sZe/fuVV7zox/9CIBLLrlkxjn/8pe/5Prrr4/43mJFIjfUIiFSDPH7/bS0tMxZqi0ZEiVyx1NeXh6Tk5NhuwejyZECTXlk01iLxcLo6Cjt7e3o9XolR5mL5FogFlsxKggCu7NXsDt7BQDHjx9f1KacGo2GlJQUUlNT2bRpE263W5FTkIvdxx9/nPr6etasWRNVjOzq6uL+++/nwIEDDA0NUVRUxLXXXsu999474/o6G31IILH1RDR5U2Ajz4YNG07L+YKRjA7uI0eOzNljKdTndrblNMGQ5UwANm3aBKDcfy0tLUzZHTz8Rgu6C8fwdGYguVSoPT4QAQHUooomzxLWLe2j9/dZuPaoOOIrhXEwTHm4b/f1rMtdOes5LIa6LFIdJucs5eXlUctg9ff3c+mll7JlyxZ++ctfRpXb1dbWziCKqqurefHFF7nzzjuVnwVOp1VUVFBQUMCLL76oEEqTk5O8/vrr3HLLLcoasU7XLSZEE4OimRyRkWiCW5IkJiYmmJiYmLM01LlAcAdDp9NhMplwu91s2LCB6elpRYbuxIkT1A9Yebr/JEsuHGTyn0tReXwI/lOfkV8noD+iYfI/dWQ96cQmGfBu1vB/fesQfBKFHg0P7ruHVM3s08cLHYOi7eDOysqa0Z09G87G+HPGdXAnihiRTde8Xi/V1dWMjY1hs9kScKYzEU1yFqyRG417bKITq2TerOE03gLJL7lzyuPxRF4wCMeONNPY/E1eemkFV9zRzRvdy9AX+Wiczken8bBtdTeHjlUi6gREDUxWpWOvTEU/4mZf5VI++5G3odGe/pkv9BhKKEQil+IZjQvsvF6/fj06nY6Pf/zjPPDAAwuiUTqfCJcgJCLeBJqWyGTKXO+zSPEkGrOkRCRFoigyMDCARqOhuroao9GI1+tVPq/gMVc5CRkeHsbr9XL48OGEk0fBmM/E7/MvP8vBP7fhvshH3hMuJDVIGhWIErr+SaaLU5k6mYZp+TQpl02g79HizDSilvRctWEbH7p4OyqVcNpIcFdXF2q1ekaHgnxPLkR8krUII3VwR0PGZGVlzaqtX15eftp3aDAY+MEPfsAPfvCDsH9XVlZ2mgRJMC655BKlCzgU5uvaCTRSmy+Ce7YObofDQW1tLYIgzFmqLZHElCRJ9PT0zOh46uvrm/V7iuU7DDSNLSsrw+/3K8RNR0cHLpdL2XTKzs4Ou+l0pmOhO5OiQWD80ev1M/S7HQ4HR44c4W9/+xvf/e53+fnPf8699947axfl8ePHEUWRH//4xyxbtozGxkZuvPFGpqenFQ3Ks9WHJNGIFMcC40t1dXVUUxKJio2iKNLW1gYQl/9JMBaaXFqoYwceN3CT8KEX9/OnQ82oTR5yUx0MjJ/qiPWbNOhHpnGWmXGbVOj/nkLDpSUsXzqAplbCqdci5qbxwAc+SXbG6aZmwVgMdVmkHGh6ehqdThf1ZmF/fz+XXHIJZWVlPPjgg4yOjiq/k7sWf/3rX6PT6ZSNhf/7v//jF7/4BT/72c+U195xxx1cfPHFfPvb3+aKK67gySef5M0331S6MQVB4M477+QrX/kKy5cvV2JQUVERV155JRDddN1iRqS8I9rJERmyrGMichmHw0F3dzd+v58LL7xwzvX1QseghYJcZwbmbXkFBVz70E8YETwYV7nBrQa3GilNQuPwoHL7EA0avClw8ukyct87QvmgFfdBNS6zlqLK5Xzp/dFPzy50B3csHgCRcLbGnzOG4JYJkGjE1SPBYrFQV1dHTk4OW7ZsOaWXarUmpcCcLdgG6j8FauRGwpke1MJpvFksFmw2mxK4ZEInXJLg9Yv8+Kcvok//Ba1vVKJO8aNP8WDUeBixpCOaVDxvXcKXLt7PJ9066lqK8alViBoBrRpuvvJirq3eEPY8F2OxF2k0RR6Nu+OOO2IajQvEjh07lFHglStXhh07gcjGbYt5NG42BBpDxkO+BpuWvP766wmJL+HiiSRJdHR00NXVFdEsaa7J2uTkJCMjI+j1enbu3IlGo5k1HgUmIZmZmdTU1LBixYrT9PplwvtMIo9eeqWFb7z2LJNONUKJCgEJwS0hqeXzF9COuzAftzLly0RypWHMd6JNh0uXLeO29XtI0/ybRJxNf06WgklNTSUrKwuNRjPvn5N8DUeKQcmSdzhbodFocLvd83KscB3cIyMjNDQ0UFhYSFVV1ZyffYkqCv1+P83NzaeZ4c2WB831vlCr1adJrlksFsX4UK1Wz5Bci1WbfLFioTuTokG44k6OnZ/85Cd5+umnuffeeykuLo7oBbFv3z727dun/Hvp0qW0trbyox/9SCG4z1YfkkRjtnpH3nwvKiqKKb4kYqPM7XZTV1enNNCEkyOIBWd6HRYv5Pcsx4mRaTsfeeZJPC+PIK4wos0QEQQJjKe+M3dZKqmvW/FmGvCZ9LjyNahqdLS501mxMo8v3nA5BbnRG8IuNLkU7SZ/JJm2QOzfv5+Ojg46OjpO23gJvMbuv/9+uru70Wg0VFVV8b//+7+8//3vV36/a9cunnjiCe677z4++9nPsnz5cp5++mllgw3gnnvuYXp6mptuuonx8XEuuOACnnvuuRlxMtJ03WJGuA2xWCdHAhGtrNtsGB0dpb6+HpPJhCiKCWkeO5djUOC99eeTLXzn+WdQj+jQmHyoU0XUeh+oJfCr8ZSnktZmZWp1Dv5UDUhqxp4rZlyzhP+4YhMfevs2NJroecWFjkHRHD8WgvtsjT9nlEQJRLdzEQ6SJNHZ2cmJEyeoqqpiyZIlMzqokmGIFK7Ik8eAR0ZG2LJli+IMG+2ai12iJFoEEzodHR1MT0+j1Wrp6uqiqakJk8mkFJImkwmVSsU3f/sYz7VNkltj52OfsPDG39YiGsHnUbOqpJfGNy5g2eZeftK/Dau3kS++9VnGd6dyZGAJGemr2bvy06jUs1/+i7HYi3Y0rqysLO7uu9raWlQqlZIAVFdXc++99+L1epXNhv3797Ny5UqFbFhsoylzhUxqx0pwhzMtSUSCBKETLY/HQ319PQ6HIyqzpLkUjIODgzQ2NpKWlkZGRkbcndfhyCO5Yzle8igYybp/fX6RX/7fYf78w/1MfNSErl7Em61C0gp4CzTour349dK/jGsh5eQEhb1+LvnUWymqzGPjknxy0yLLeATrz8nTL1arlaGhIbxeLzU1NRHlTBIF+dqLFIOSNU5/tmIhOrjlIkGSJNrb2+nu7mbNmjUJI9ESocHtcrmUTvvgUeJIBHeiJdeWLFmiGB/Km049PT00NzcrOtDZ2dlKjhIKi70YXYyb+sGItMkvN01kZmZywQUXxHWMiYmJGTn52exDksjnRag4FigFGWnzPRTmmjvJmtEZGRls3ryZF198MSG13rkoUQL/jmFen8htf3iaN6Q+zFNOtL4U0PrxT6uY8KaQVj7BVLcBUdDj3JhBWrMVb6oer1lPqlHDBZsKuOzi5Xhdk0xPaxTt3EhYaHIp2k3+WDwArr/++ojSZ9dddx3XXXddxLWuuuoqrrrqqrC/FwSBL3/5yzNk24IRaboukZgPDe54JkeC14w3ZkiSxMmTJzl58iRr1qwBoLe3N661ghEuBi32PGOu+LffUT//79n9TGgnyR6YwpWah8YLkkcAEwilTqSOFFwV6RjESUx1w3iyUxFT1BRlGXnX3mWsWpGB1WoJa1gdCoshBkXTwS3X2JFwtsafM6aDW76Y4k10vF4v9fX12O12xbAqeP1kENxykRe44zRb0RYNQj0QzpbEShAEDAYDy5YtY9myZbjdbmVcv6Ghgf7REY4OvsKrzpUYB3ykmj0YjF5UKgm80FpbyoZdHVyysoGDdaspK7Hx+mQJ/7BUUqDO5+71HybfGN1Nv9BBLBSiMTfR6XRR7w4fPnyY119/nUsvvZT09HQOHz7MXXfdxbXXXquQ1x/84Af50pe+xA033MCnPvUpGhsbefjhh3nooYeUdRbbaMpcIU8RxBJvAo0dgzetErWBplKp8Hq9yr8nJyepqakhPT09arOkeBIgSZJoa2ujt7eXDRs2YLFYYj53+djBiEQeyRtc2dnZpKenR31PJivJe+gf/+TZVztQ1VvQpvuRUCFq/KisKvwVAtOXpKH97TjqSRFRD4IIGr+KDReX86G3bZ9TTAmcfsnMzKSrq4vc3Fxlc0ClUkVl5hsv/H6/smETDrF0DpzrkO8HjUYzbyaTgX4XXq+Xuro6XC5XVJtjsWCuOZXNZqOmpobc3FxWr1592nMvUhxL1v0fyvRInkBraGhAFMUZ92DwRvNiztUWY84TjGiKu7mYTHZ0dPD9739f6d6Gs9eHJNEIJpeCpSDjeS4E5zyxQJ56WrZsGeXl5cqzKxGx4VwgkkJBkiR+NdbKvd86gSddRJMjosaDIGrwparR1frwrdaQlz+Ba4MBb6MZb1oK3m1GVG4vu7Zk8/nrrsbpdGK1WhkbG+PEiRPodDolZs5GNkmSNOcp7rkgmk1+meBezLF+MSGZPgDxTo4EIt5cxufzUV9fz9TUFDt27MBkMjE0NJRQ09xzMQY5PG7+67WX8HfrmV7hJ9UpoXKIqCQBfxn4uwyMmdIp2dhHr6MUadiAsywToVhEq3bxxevezva1yxkfH8dqtSqG1aGaKUNhoRsBoiW4z3Wj7TOG4BYEIe4up0C5gOrq6pAdgcnqoJIfcDLBLZskhSvaol0z0WT8YgmUwaMner2ewsJCcvNzOdRxlONNL3Byaileg4p0t8iUxYhPI1JWMUbb8QJOvFyGwehh6dp+SvNH6BrOxzmWx7s2XM+qolUxn8tiK/YSPRqn1+t58skn+eIXv4jb7aaiooK77rprRieS2Wzm+eef59Zbb2XLli3k5OTw+c9/XhnNhcU3mhItwl33scabqakpamtr0ev1IY0dExVfAhOt/v5+mpubWbp0KUuXLo36O5ev6Wj1xWUSzOl0snPnTtLS0rBarXPqaJjt3ALJo8ANrvr6eiRJIjMzU5EziXVzcC4YmLDywaf+F8+gCo1NIsXpRXABRhFXqRbzYQ/T5Wrca/WMX5tB6j/saAd9SEaBi969jRv+6x0JjSeiKKLVamdsDoQy85UTtoyMjDkXhtFIhEWrwX0e/8Z8d3DDKam2xsZGMjMz2bRpU8J18OeSp/T09ESUbpvPDu7ZoNPpZuhAT01NKX4DbW1tGI1G5R5cbPlEMM4E819RFCNeq9PT0/z85z+P2MEt+5DI6O/vZ9++fVx11VXceOONCTnfcwmBcSyUFGQ8iIdckg2wh4eH2bx58wxJkkQ1MwXHGL/fz/Hjx3G5XOTk5CRlg3mhUddxgnvf/C0jvbnopiV8xRI6FfhNWrSOKTQ92fiLPNiPpiJthewVVjTlYziG0hAkeM+6HXxg5dsAFNm60tJS/H5/1GTTQk/WRrvJf66TSwsFtVqN2+2e8+RIIOKJGbKRpdFonME7JTI3CV5ramqK1tZWjEYjOTk5mM3mBd0MSga+9vSj/HXagTiYjqCVkHQiwqSAmK9GfcLLdLqe1BoHzkwjY0skllzUi2dch2fcgE4HD7/1VnJTTjU5ZmdnK88Gl8ul1Jr9/f1hGxVkiaKFjkGRvleHw5HQhpUzEWeMRAnEXgSGkwsIhWR2cMOph3Jvb+8Mk6S5uHfH8vMzCaEC/xsNr/BE5zNMWLysLXBiHzKAEXwZGvw9fl57eRUXvbOOcVsqoyPpHH1qNU0HKslZMsGubeu4fM816KIcPQnEQgexUIgU2Ox2e0zjV5s3b+a1116L+Lr169dz8ODBWV+zmEZTEgG1Wh1VV6VMNJeXl7Ns2bKQ10yiJUqampoYGhpi06ZNUY8hBa4B0ZGVU1NT1NTUkJqays6dO5WumkTHrnCQN7gKCwsV8shisTA4OEhrayspKSlKd3eoZC4R96/PL/JCQwffeuFZJjN1pLgEJI2EpFOh6RFR+zxIKh3OpWD8h4Rrsw53qQr3DXo0owKfv+ht7FkR2+ZaNAjegAtn5mu1WmltbcXtds/ZKC+SPACcKu4SoXF6LiHaWJMIyN+frIVfVlaWlOdcPJ2SMjEVjXTbbBIBC/XcFgQBk8mEyWSivLwcn8+n3INtbW243W4EQaCnp4esrKxF1+V3pnRwz0YcyqbGN998M/fcc8+sawX6kAwMDHDppZeya9cuZfJMxtnsQ5JoiRLZD6Szs/M0Kch4EGvuFDwhG2qCItEd3PIx5Q14eYM5LS1N2Yw3m82L/t4KB0mS+NKPf46lqAUbS1C5VQiShCAJeFNAHDKgKplC1+/FtSIVjdqB628GhkqMqEwiuZKZX3/gRrRhNjnUavUMsil4clcURcVo2+PxzMn8eK44v8m/uKFSqfB4PBw5cmROkyPBa8bCDw0NDdHQ0EBZWRnLly+fEf8SzTXJMWh4eJj6+noKCwsVCVyv1zujIehM9saZdI1z41d+iG+bB489D4MTfEaQvAI+E7hyU0g9NoJ4rIjpTUaMbW6mj6fhLE1F0Eh8aPkFfHhn+A1vg8FAUVERRUVFIRsVDAaD0igEs0sUJRvRxKDzm2xnUAc3xFYE+nw+mpubGRsbO20HPxSSTXA3NjZis9lmmCTFi7NJgzsU5IdBy8lefvvsI4xqPUhrQX1cjbHUhdYvIkjgKNaS2uHmyF+XIwjw9utexdKdg200DUnSUFG5h8LCdVjGxsjOzo5Zy3cxFnuRCCZZ/3YxFc1nKiJtqMlJhFyg5ubmzrpWogzXLBYLKSkpIYu3aBA4VTIb5IQpVJI2l+7MeONMIHlUUVGhELgWi2VGMicTuImIZ489/QxPvXQce66KyWwtgg8ESUA0CHjNBtBMY358GusNKvxqI9MZEvoeL8IJgeIl2fz81g9i0MevIT4bIsWnYDNfeSRYNsqTu+XlDoVouuGj7Rw4X9zFBo1GMy8d3D6fj8bGRgDWrVs3p66mSIg1p3K5XNTW1iKKItXV1RFjW6g8KPDfiyGf0Wg05ObmkpubiyRJDA0N0d7ejs1m4+TJk2i12hldQtFqQCYLi3FTPxiRYpDT6USSJMrKyk6TAwmH/v5+Lr30UrZs2cIvf/nL0+LquehDEg/kGNbf3x9SCjIexJI7yV3jeXl5rFq1KuR1kugO7vHxcWpqasjJyWHFihWIoqj4ZcjeIo2NjTM6ArOzs+d1+mwueLaplqcOPcXkQBqGSj2i49S9ISCgnpTwpKtxp/hgTQapx62oGgz4U9Px54DKAl+77J1sW1ke0zGDGxvsdjsWi4WRkRHGx8eZmJjA7XYrciaJnj6aDdFs8jscjjOaTJxvJJLTcLlcjI2NUVBQMKfJkUBEu8kWKOW4fv36kM+fRE7gy7FM3lBct24dWVlZymc5PT2N1WpldHSU9vZ2DAaDQnZnZmaeEd3dHp+Pzz7zR/pePkrxTi+vWcrAKyAAaieo3Wpc2X40vQYc7/RjeHkIzWsZeDJSENMh15bC/9x2HTpd9NdBqEYFecLk5MmTADQ0NCifpclkmte8ye/3R8wVz2+ynYEEdzRBxm63U1tbi1arjVrjOlkjwm63Gzj1wKuurk5IUpMMgnuxFDWSJOEXfXzip19hoF5k7bphxPIsBK+Ex6TGadNTlG1h3FGEO1XN2K40TE1OXnu6kqPPL6Wg1MdbLt7Bu99/KZOTk1gsFkWHLy0tbca4fqQkZbER3JIkRaXBfa7v2sWC2a772Uin6elpamtrUavVURHNiejgtlgsdHZ2otFo2LFjR9zJifyewyVZcgdWV1cX69atC9k5Fvy5RRs/EhlngglcOZkbGxujo6NDSWxHR0djLoJGxu3c9cAPcdRamVxdgk41jaTSIhkkJEECScCXZcC+0kxq2yR5X5/AcZELX7GGtNJUvv/hayhPj62zPlbEEp8EQSAlJYWUlJTT5EwGBgaUscbA+Bjq84pW++1cH42LFoEm18kmuGUZJYPBgEqlSvp3FAuRJJNE2dnZrFmzJqrYtlgkSqKF7C+i0WjYsGEDfr9f8Rvo6uoKaVY533nZYpRlC0Ykgml6ehog6uKuv7+fSy65hLKyMh588EFGR0eV38nPvnPRhyRWyGaOcGoyMFHxJZo4IkkS3d3dtLe3U1VVRUlJSdjXJopgEgQBl8vFkSNHWL58OWVlZfj9fmVtrVY7Q7pIJmmHhoZoa2ubMX0WTT0y3xifHuX6J35OnyaNlU1uctfClFpCJYh4tCAJoLcJ+FM1ODMl/H4B35Ic1Mt8qN0erl6/jZurL5rzeQiCQHp6Ounp6ZSXlyvPMEEQOHHiBE6nc4acSSw+LfEg2hzoXCeX5huymWNfXx+pqamsW7cuYc/PaDbZPB7PDD+TcN9/ojwA4N9xz+v1KseU/QoEQZghAySTtBaLhba2NjweDxkZGUoMitbkdT7x9/o/8sVjnRRpJpkeyKVM14ckAEYfXqMGnV1APwpOjQb7Eh8G2ymtf0Hyk6aC773zP1memxfxOJGg0WjIyckhJycHj8fDK6+8QkFBATabTTEMDWwWSvaEid/vn5VLlOvhc50LOuskSgYHB2lsbKS0tJTly5dH/aBLRge3xWJREr6NGzcmbMd+MRZvicLx/mO81PkyzU0VrC/qw+3QgBrwg6HYy3CTmU0727AfNNI/lYEzRY1laxpaj593r67i/11xMep/fefyuL5sBCV3ezY3N+Pz+WYEpFDBfbEVe/J3Ho0G93nMHeHizdDQEI2NjSxZsoQVK1ZEdY3MhcCSJImuri46OjooKCjA4XDMaec9UKIkGIGmKLOZzoUqEqON58mIXcHJnN/vp7Ozk6GhITo6OnC5XJjNZmXHPdyUg9/n57EXX+c3/6wht2EIj9GMpBEQAe24iLNchc8kop1QIxrUuIrT8afr0Y67MQ1qePv69dxw7WUJf3+hMJcNuHByJjabTZFSkOVM5KJRNl2Nprg7370UPWS9/2RKlAwMDNDU1KTIKB04cCDphHq0RJK8AS2TRLFsls1GcC9GBGpcq9Vq5f6SDbXljs++vj6AGR2f86HnezZ0cNvtdtRqddT59v79++no6KCjo4MlS5bM+J18fZ3tPiRzgSRJ9PT00NbWxrJly2htbU1oZ2Ck2izQ3Hvbtm3KCPls6801BxFFkcHBQRwOh3I9zIZgkjZ4+iywHsnOzl5QCQ6n08nVP/wmZUVWurMrybZ6cI9rUdm1ZArjtI9rkdJ8+FwatA6BtG5wj2vxmSUcaokPrtrM3dt2oUlS7SRJEiaTSdnwCdTOnQ+yKVqT2/ME9/zB4/HQ0NCA3W6nsrISi8WS0OdYpBg0MTFBTU0NZrOZ6urqWZtpErXB5nA4mJqawmAwKBrfs8W1QJJWnui0WCxYLBZOnjypmLxmZ2fP+1REMB75659pHTlAq6sIZ2YKuUwyLZkR/ZBXaGVswozbKKFxC+htAiq3Go9ZhSdVRNKqeWjvPnYXlSbl3OTvrri4mCVLliBJktIsJG9eRtMsNBec1+CODmdNB7coirS2ttLf3x92NGQ2JJLgDiSkVq1aRVNTU0LWlXE2SpSMjPfyP098lf4UgWlfKh6/HrXaT0qqB2lUQFUioXJLDBfqUR3JZfvGZiZdaVjH03FNa3nvhZdx+a5Lw66v0+nIz88nPz9/RrenxWIJ6+C92Iq9WNy7z2PuCCadAmPMunXrYoox8UqUyJIC4+PjbNu2DafTSVdXV8zrBCKcRMn09DQ1NTXo9fqwZrzBa8R77GRDrVaTlpaG0Whky5YtSjInd0vK5JJMeGu1Wg42neQHP/gr3YVqMhzTSBY/QokEAoijOtLzHXjs6TjKfBgGQWdTIelVeAoNfOADu1hn9LOssnJe3h8kdsIksBseTiVHsnZwoJxJNMez2+3nfGIVKzQaDaIoJtzkTxRFjh8/zuDgIBs2bFC+30RJJs2GSFMrgecWjYxcKMyWs5xpTQB6vX6GBmTwhEUkv4FEYLFt6odCJP1JOQeK9n1cf/31XH/99RFfdy76kESCnJ8Eyi+eOHEioZtns9Vmcs4iT+tGswk0V4LJ6/VSW1urkJixeqBA6Okzi8WiSAnIBInc3T1fUgIf/84DtKWpubion0NjyxGXCHjcGtJz7Ay2FFJUYSOzaAL7eCpuAfzjGtQeAe20gMYv8fA1b2N7Wfju+UQgOO+JpJ2baLIp2k3+83XY/ECeHDGZTOzatQur1Xqaj8FcMVsMkj2YIvm8Ba4119xEbp7UarWUlZXFLL8aONFZUlKimLzKfIjT6VQagrKzs+fNK8ThcHDVg19DMhi4+KIx3jhRjiAKoFOjck4x3Gtm2Vorw9NZaEqncalT0DhUqDwC+nGBFLWW5z56HRpN8uKlzAsF+r2YzWbMZjMVFRUzfFfa29uV5qrgZqG54HwMig5nBcHtdDqpra1FkiR27doVV/eYXPDNtcD0+/00NjbO6CZobm5OaDEpE9xnguN9NHizsYeGjk9zcrCElGILflGNqFNh6TKz7IJ+Ov+Ui5gnoDJLGI0+rGUahjvyyJrQs2vVVv7j7e+N6Xihuj0DHbybmpqUMTf5YbQYPmf52o9Gg/s8osNs32tgvJlrjJGNT2KB7MKt1+vZtWsXOp1OcQefC+SHc2CSNTo6Sl1dXdRd6WfaFInRaGTJkiWKPMfExAQWi4Xu7m7ebHyVX3YPYjs4jdsMgjcdRAEE0FunUZWJiIIW1bSPLHGaiVQj7mwfniwwOVU8cPledi+t5LXXXpvXOJFMCSU5+S0uLkYURaVoHBwcxOVy8dprr4UtGh0OxzmfWMUKOVn1+/0J6/YIjFnV1dUzYlaiTG9ng0qlUsZlg+F2u6mtrcXn8512btHiTJMokRFNjAgummbzGwg3gRYPFtumfihEI1FyPv4kH4GSR4HkcqLllsLFqpGREerr6ykuLmblypUxTevGGxvsdjvHjh0jLS2NFStW0NPTE9c6gQisR8rKymYQJK2trYqUQKBRXKLv0bEJK3c9+g3Gpk0YHJC21ol39NTn6VBpyd3qZvB/HfQ057Jh7TA9Bel0e/IQlroQJChPMfL4u29O6DmFw2ybcLOZ/CaKbIom73I4HDE32Z3LiOd6Dp4cKS8vV6bhEp3bhCK4AzfoN23aFPVG11yaKQPfc1VVVcKI/GCT11ANQfLv5QbARON/Dv2N3/7hGI6qDFZ3DoIKJDX41SJto0tYtraVrmOryCh0sKPkJG32PMYz1agKRAREPrn5Yt5dtSXh5xWMSE0Agb4rEL5ZKBbvo2BEikHypum5zgWd8QT36Ogo9fX15OfnhzUViQaBY/vxruFwOKipqUGj0cxI+BKpuQTJ6YJciKJmf0s9P/rN6xTndLJMo0M0CPj9YMzzoO700WfJpqI9kw0X99L0UjHeFSqEAgmVGzaXVvHxy65Hp557oA0O7vLIW09PD06nk4MHD85wIl4ocxi5sJvtuzo/Gpc4yBrccowpKCigqqoqrvgQa8ekLINSUlIyQ2opUZMm8jqSJNHZ2cmJEydYs2ZN1Dqf8RJIi4F4khMMs9nM0cnHedYi0TlRRFGHHfueTNSihEujJ6NEg7rNQ1rfGPYluXidKeCSSMfDEoOJj128m4tXVinrzvdG2HyRUSqVSiHbBEFgamqKgoKCkEXj0NBQVB3cVquV22+/nb/85S/KGP7DDz88a+xyuVx84hOf4Mknn8TtdrN3715++MMfzigke3p6uOWWW/jHP/5BWloa1113HQ888MAM0vill17i7rvvpqmpiZKSEu67776wHZxf//rX+cxnPsMdd9zBd7/73Zg+t2ghF2VwqiMyEQR3pJg1Xx3coY4hj/NmZmaydu3aOXkJBMaSYBPcxYh4Y184v4HgCbS5jhcvNt+RUDjvQ5JYxHOvyF2LsuRR4BqJJpiCY5UkSZw4cYLOzs6YchYZ8XZwy4R6WVkZy5YtY2RkJCm5TLAxrcPhOO1ez87OxuVyJYRouun7d9OSmod+sAB/sR/DoBe/pCbT68SGFn+Gn2O21Wzc10jT38uZ7F3Kki0j7EzvxefQcu+7/h8FWbFP38SLWPKeYLIp0Gi7p6cHQRCSYrR9nlxKLkJNjshIFsEduGawIXYsG/Tx1kCiKNLc3MzIyIjynpMVg4IbgoIbAE0mE9nZ2Uqj5Vxw4M0j/OKlv6DSODGW63DlatG2+ElJdaOzSbgLYEKrxb06g3x7B21/LCOl0sOK1TaEFCtp3iV85dq7E/TOIyPWuiu4WShwMu/48eOkpqbOaBaKJh+OFIM8Hg8+n++cn6Q9ozS4A03fAo3QVq9eTXFx8ZzOZa4E99jYGHV1dRQWFlJVVTWjSEi0vnegxID8/09NTTE2NjanHf75Ip7sXjdfrvk9dU+M43epuWDbCGK3gDilgtUaDJNOSvJGOCkU8epzq6ha1c+KrcO4xzVM1mRxw3/eREXp6qSdnzzy5nA48Pv9FBYWYrFYGBwcnGHGNt/jg9Fcm+f1bxMHlUrF6Oho3IVUIKJNukRRpL29nZ6enpAGj4mKJYIgKHrbNpuN7du3YzabY/r74HgRS8yZLzI43DGs9gF+/c8HMZWMcXJwB5IAKp+IZsqHq0iH1q7BnpVLWv4wqW02tINO3HnpSEYVO1cs554PX4lRN7O4XAiCOxmdFLNBdu8OVTT29vby3ve+F7vdzv33389//Md/8M53vjOkSek111zD4OAg+/fvx+v18pGPfISbbrpp1tH8u+66i2eeeYannnoKs9nMbbfdxnvf+15effVV5dyuuOIKCgoKOHToEIODg3z4wx9Gq9Xyta99DYDOzk6uuOIKbr75Zh5//HFefPFFPvaxj1FYWMjevXtnHO/IkSP8+Mc/Zv369Yn6+MJCnhaaa2EWSP7MlhfNVwd3cKySibHAjqt4EalQXOiNtHCYa4yYbQIt0HRN3pCPpUvxTJAoiZbgXqybHGcy/H4/LS0tDA8Ps3HjRuUZEIhkdHDLccTr9VJfX4/dbp/VIyTSerHEBtm87uTJkzNysrnmQNFAEARSU1NJTU09TUpgcnISm83G1NSUcq/Hct0/8NjP6XUdw+YsYolgoV8oQyWJkAXeTi3bd7Qy1LaZ6UyBMbOGVyY3sfKqflSjY/jGDfzX225hedH8SbLJmMsmnNFopLi4OORkmlzbyZ9luNruPMG9sJiamqKmpgaj0RhSligZfmqBm2w2m43a2tqYDLHnen5ut5uamhqFUJd15cPFskTWIiqVaoZXiNwAaLFYADh69Khyz2RlZcUkl/Lu/3cv5lwVg7km8ntEpEJAkOgbyyB/YoJSv5VWfw6+bGiYWELmWheVxj48I5DhXsK9H/ovdJr5bThMhveR1Wrl+PHjM4w/Z/WKiiIHguiNts9WLHgHdyy7WXLiJLvVOp3OuJOcYMgXrFzAR4vADshwBWWiTAUC15OPDae6PRsaGkhNTZ2xwy9388wXARsJkiTx6QN/5hVXO5ndfvyeDBBEbFNGluYN4zushYs0+CwuskomUekkhqUM6kbLaH52CSuXpvLgJ26aV0JZpVIpI2/B+kqtra243e4ZTsTJLKyiNRY4PxoXPcJ9Vy6Xi9HRUfx+P9XV1XN+UEST1AS6cIc7ZiKTt/r6ekVvO1YDs7l0cM8XQp2fX3Rjn3qYR/5uQb/MiuhTIfpUoBVw5xpIb57GWWrEnSEwqTLhXqUlo8SG3u1Fn+qieudKLtm8grHhIcUMKtSG43xgIbotQ22yBRaNXV1d5Ofns3r1ah577DHy8vJ497vfPeP1LS0tPPfccxw5coStW7cC8P3vf5+3v/3tPPjggyE3kiYmJvj5z3/OE088wVve8hYAfvnLX7Jq1Spee+01du7cyfPPP09zczMvvPAC+fn5bNy4kfvvv59PfepTfPGLX0Sn0/Hoo49SUVHBt7/9bQBWrVrFK6+8wkMPPTSD4Lbb7VxzzTX89Kc/5Stf+UpCP8NwmKvRpMfjob6+HofDETEvSkaXUzACY4TsXzAwMBDTOG+06wf+LPC/iw3JIN0DJ9CWL18+o0tRHomVC6asrKxZY/2ZIFESjQb3uV7YJQPyhKparWbXrl1hzfsSTTDJ68nEVkpKCrt27Yp7czeW8wv0QNmxYwcmk0n53UJMowXe6/JEZ2pqqmIUp9VqZ3iLhJrkcHm8/PejX6S3TUVmQT6uPDUZbgGVXyLV5sS7S0XH77NY8bFRLslp4VBPFfZ8Ne48gRZHHtsKTXygcMWCkNuQuLwncDJNloGSNw+Ca7tAsuk8wZ14RPvMmW1yREYyO7i7u7tpa2tj5cqVlJSUxPWsjFViNtLE23zHoEDN+wMHDrBixQrsdjs9PT00NzdjMpmUGGQymUK+x8aeFu7/8ROYl0wz2FnBRJlAkUpEGlPhc2qZXi/ieNnA9re3I72sojslA1eGiE1U0zS5hP/atJ6dpRXzTm5D8ryPZONPOXeTpWECJ0zk3C0ao21ZZ/1cxoIT3LFArVZjt9s5dOgQZrOZXbt2JUyvUpZ+iCUxC0x+ZuuATJZEiSiKnDx5kq6uLtatW0dGRgaSJClajW1tbTP024IJmVBrJgtvdPZy9z//iiZrClIlsJ363gQV1L68jM3X9VBUZmXwj5mk7p1A5fSQpR7BvHKCVFMaN150M2UFS5N6jsEI1SEZPD4YKiAFFpOxmj/MhvOJ1fzAYrFQV1eHXq8nIyMjIZ9npKQrWhfuRBSPFosFn89HVlYWGzdujOthHaq4i7Uraj6JFJ/Px09//zDr1/yFNIPA2PBOcleqSRNcaPR+BL+GqXUmcg6MkH3Qhm2bGW++Cs+0ESkvnY9ctoP/3LYOp/PUuPDY2BgdHR3o9XqlmJxvcmghCO5IG8CSJOH3+/nUpz4VduLh8OHDZGRkKOQ2wJ49e1CpVLz++uu85z3vOe1vjh49itfrZc+ePcrPqqqqKC0t5fDhw+zcuZPDhw+fZv66d+9ebrnlFpqamti0aROHDx+esYb8mjvvvHPGz2699VauuOIK9uzZM28Ed+CEWqyQjZbk+BGJ/JlPiRKPx0NtbS0ejyduve1QmO1eWwxSSOGQ7BgR3KUoj8T29fXR0tJCWlqaErPMZvOMGLLYO7glSYraZPI8Eofh4WEaGhqi0rue60ZdMFQqFT6fj9dee21WYitaRFvnOZ1Ojh07pkhOBufyiyHGaLXa06QELBbLaVIC2dnZpKWl8Zump3mz/iCTQxkYCt04pvWoJD8nc3PIbJ9GXziN/WQuQ5eB7zE1Ky4e4x1bjjE9rWN63MCn3/MFVF49TU1NC/aek5X3BE6mhart5I1Cr9cbsSHkfB2WWEQzOSJDrrUSXWOMjo7i8/lOk0SJFfK1G835DQwM0NTUFNbAcjHEIJPJRH5+PpWVlbjdbqW7u6+vD2DGhpsgCHzq5e8wNjSC15FJsWmaXjSoRC8akwtb51JSs2w4Nuh5s6aUVb/Vse6iXjZnnmB8NIUMbTH/732f5/jx4wu2EZ+s+BNo/BnoFRWcu2VlZeHz+WZ9//Ik/2LO5eYDZwzBLbvKWywWVq5cSVlZWcIv8FjII9m9W6fThUx+ApGsDu7AUb3U1FQ8Hg9qtZqcnBxycnJm1W8L1d2djEA5aB3n5p8/TVeOgwyPB78ekECV8i+pGQE8Kh3/PFbFBXtbyW6couvvefhMRtLKpnnLpsu4dMvphMd8IFKxN1tA6u3tpbm5mfT0dIXsDi4mY0UkcyU4n1jNBYGjqFVVVfh8PsbHxxOy9mwEd29vL8ePH49qbD9RBiUajYby8vK4r8czoYNbPt7kpJNPffvbXH75IUpzJmgfWsKkx0COX6Qwc4rc/EncXdm48o2MXpZPesMEBX8Zw1OgY/dFq/l/H307qamnOgWCpQHkaY6Ojg68Xi9tbW3k5eXNOl6WKCwUwT2bTqXdbgdmH40bGhoiLy9vxs80Go2i4R3ub3Q6HRkZGTN+np+fr/zN0NDQadMr8r8jvWZychKn04nRaOTJJ5/k2LFjHDlyJOx7SCTkaySeziNJkujt7aW1tTUm2Y/5kijxeDwcOnSIjIwMNm/enLCGBIicVy104bcYEDwS6/F4FNKmqakJv98/o0NosXdwR2O0bbfbzxPcMWC271sURdra2ujr62Pt2rUh5aaCkcjNM1EU6erqQhRFNm/efNpzIx5E03BktVqpra1VvJ1CXW/zIVESCwInNeDUFKJsFNd6oo4/jtUwqFORk6XGO63Hq/WRZvDAmAp7Vgoryjvpbi0js2qY6ZMm+t6awdCkGV4HvUfgmXvuAU5JNCzk+5yPTbhQtZ28USj/b3JyMqx27vlNtsRBnhxRqVSzTo7IkL+HufipBR9fzh937do1Zw+uwAbFcNexJEm0tbXR29vLhg0bwsa9xUBwB0Kv11NYWEhhYeEMzq6/v5+/Hvkbb5ia0XWDr18HWgm3Q4UGkXy7k6a8YiqtwwxNmkmpc+LITaE2vwjNSQnJLfCxrdu5+qJLgflvkArEfDUByF5RmZmZVFZW4vF4lHpTFEWOHj06I3cLVA84L9N2CgtO70fzBfh8PmpraxkfHycjI2PO2o3hEG2BOTo6yuHDh8nJyWHr1q0Ru3QT3cHtcrmAU3p01dXVYUeRZf22kpISNm7cyIUXXsiKFSsAaGtr4+DBg9TW1tLb24vX603oOUqSxNde2s9VP3mcYacbKVVEgwQCeH1qqHKiFvwgqvBroam5nMf+cCnuYiNrrxpmz3+m8fmbv71g5DbEPq4rB6TKykq2bdvGBRdcQElJCW63m6amJg4ePEh9fT19fX04HI6YP+9oOrjPF3exQf5+PR4PR48epb+/nx07dlBSUjKnjspghCKm/X4/jY2NtLe3s3nz5pA79MGIt3iUj3Xy5EklZs3lfp9rYjUfSdn4hIPf/LGGD3/sp+QXDpGVNQWiipxUOw6DniXWKV6ZKuS6tTUUlVgx+Lz4MvVYL8nDcXUxn/nqB/nC7e9VyO1gyJuJK1asoLq6WpnemJiY4NixY7z66qs0NzczPDyM1+tN+PtbiG7L2WLQF77wBSoqKgAUQ8rg/x0/fnw+Tzdm9Pb2cscdd/D444/Pu5mwRqOJqfNR1tA/ceIEW7ZsiSp+yJiPDu6JiQkmJiYoLS1lw4YNCSW3IXIHNyw+knuhz0en01FQUMDq1avZvXs3mzdvxmw2MzIywuuvv44kSXR1dTE2NpbQLtxEQX4en5coSSxC3Usul4s33ngDi8VCdXV1VOQ2JE4iwOPx8Oabb2Kz2QBm7dqMBZE2xnp6ejh69CjLli1jzZo1YZ+xi41cCobBYKCwsJBftb3KP4YO4C2dIsvqwW1Uo9L58Q2oKCgYYGTIxNKxCY4tKad8eTfqHj0+iwZzo530nkmeuu4mhdyGhSWXYGFklOSNwqVLl5KVlUVZWZkiWXn8+HGllu7p6aGuri4qo20ZMp8R+L+vf/3rM15TX1/PhRdeiMFgoKSkhG9+85unrfPUU09RVVWFwWBg3bp1PPvsszN+L0kSn//85yksLMRoNLJnzx7a29tnvMZqtXLNNddgMpnIyMjghhtuUJoWkolw3+fQ0BCHDh0iKyuLHTt2RCS34d/PhkTEIJnrMRqN5OTkJCQnDOzgDgWv18uxY8cYHh5m586ds27qLeYYJAgCZrMZbbqeXw39npd7exhSp5Gi8oIG3BY9Q9NZ5OZbkbp0aEQVvVUplBeMIFn1aLs8mJunKHW6eeHuTynkNixsDFqoJgCdTkd+fj4rV64EYOPGjWRnZ2Oz2XjzzTeVevP48eN0d3fHxAOdrTFo0XdwBxoKVFZWKsL2yUCk7sjADs9YTOcSqUlns9moqakBYMOGDTFJYITq7rZYLIyNjWGz2VCr1bS1tZGVlTUn7e76gQ7uOfYnpto1qKeMiBmniG3RrUKLiBsNEwYdGdtsuN7MxC+qkVTgRE990xa+dM1lLKusiOvYicRcOyTlYrKgoABJkrDb7VitVkZHR2lvb58hb5CZmRmRAIhmR9rhcJzzzrmxItx4fyK13ILXcjqd1NTUIAhCTF0B8mZZLA94l8ulxIzq6moMBsOcY1JwYuX1epWOwJycHLKzs0PGpvlKDH6y/xH+/OgUmnEBoVwLfhUajZ8pl5aKLAtV+cMcrF9DdXUTNSlZfGBzDZMrUxicTiXPUMzHNn86rnu/oKCA1NRUZZrDYrHQ3d2tjAvL43rp6elzJqejmehINGYjuG+//XZ27tzJ9ddfz5tvvhny3JYuXUpBQQEjIyMzfu7z+bBarWFJlIKCAjwej7LJLWN4eFj5m4KCAt54440Zfzc8PKz8Tv6v/LPA15hMJoxGI0ePHmVkZITNmzfPeM8vv/wyjzzyCG63O2keELHEG7vdTm1tLVqtNqTRUiQks4Nb7vocGBggNTWVpUuTIy02G1G1mDtXFsu5CYJAeno66enplJWV4fF4eOWVVxAEgfb2dlwuF2azWclRkj2REg38fj+CIMwa9xwOx3mCe44YGxujrq5O6WCOJeYlIm+SJdsyMjJYu3YtL7/8csI6MsM1HImiSEtLC0NDQ2zZskXphA6HcOTSQt8jMn773J94rqOWyu1dNP19BcKKCdSCBr3DjZRuR+9JYWDSxPLlPXQ0l7KqdIK+7HwcWRqMHi9ffeu1rC1bcdq6i4HgXsjRe1EU0el0M7Rz5Unp/v5+3v3ud+NyuXjwwQcZGBhg3759ZGdnz7rml7/8ZW688Ubl34E13OTkJJdffjl79uzh0UcfpaGhgY9+9KNkZGRw0003AXDo0CE+8IEP8MADD/COd7yDJ554giuvvJJjx46xdu1aAL75zW/yve99j1//+tdUVFTwuc99jr1799Lc3KzUH/GYfycD8UyOyAj0U4sXgVzP6tWr8Xg8TExMxL1eqPMLlbtMT09z7NgxjEZjVFJzi5ngdrk9/PC3X+NZdzpXrTnJYfdyPH4DKhe4N6pItflx9mrIWz2A21lORr0eY6lIZ24eYq5AntfLb6//QsjPYKEJ7oWOP3AqRmRmZlJSUqLIU1mtVp588km+9a1vodfr+exnP8vll1/ORRddFPHZeTbGoEVNcAcbCgwODiZ1rHY20kfulpqamjrNbCQSEiVRIuvwrFixgpaWljnr0Mnu3KWlpZw8eZLx8XFlNCZYuzsa3Uyfz8vnnv8mtS6BMbsZvd6P5AfBA5JfwCmoSLerMKT5cLr1+Eu8pBVbMHRr0Xj1vG/7VjZozeh1i+OyTGSHZHAxGeiGfuLECZxO52kEWPD3G60G9/kO7ugxPT3NkSNHWL58+WmyR4nu4JbXkovHgoKCsOOvs60D0Y/fyY7fOTk5rF69WvmbuSZGgX8vJ2UGg4G0tDQlTqWnpyvxI5zZSKIxbOnn1zVf55XHstGMGxB1gF+DfdqA261lXOMnz6/m49Wv8mvNdl49up4K4xAn8k0YDQXcsPlGCrPK4jp2YNIVOF4GhNWmk+/3WAlK+XgLYTIZ7pjy5ml6ejqrVq0K+31XV1czPj7O0aNH2bJlCwAHDhxAFEV27NgR8m+2bNmCVqvlxRdf5H3vex8Ara2t9PT0UF1draz71a9+lZGREaXrZf/+/ZhMJlavXq28JrirYP/+/coal112GQ0NDTN+/5GPfISqqio+9alPJYXclj+naDu4BwcHaWxspLS0lOXLl8d1DSSrg1s2ynW73axYsYL+/v6EH0NGNPFkocmYYCzWYhT+/WxZtmwZWq1WIW3mw18kWkTz3LPb7REJpfMIDUmSOHHiBJ2dnaxatYolS5bEvMZcCW45f5All+S1EkVwh6rHPB4PNTU1+Hy+qGQQ5HUW4/3c39fDXQ//ho/vOUyb6nLem3OQI871ZAg2etNSqR4do3WZGoPHj6c/lYE0L6vXNOH2mDDaNGj1Dm7ccQ1Gn5rx8XFMJtNpz5iFlAdYaJ+A4MaCwFq6pKSEzs5OSkpKKC4u5qGHHkKn03HVVVfNumZ6enpYEvfxxx/H4/Hwi1/8Ap1Ox5o1a6itreU73/mOQi49/PDD7Nu3j09+8pMA3H///ezfv59HHnmERx99FEmS+O53v8t9992nmH4/9thj5Ofn8/TTT3P11VfHZf6dDLhcLmpra/H7/VRXV8dcz8oboPHGIJ/PR0NDA5OTkwrXI8skJQLhpstGR0epq6ujpKSEFStWRHWPLdYY9KOfPEGX9U0yit0UlzvxOzT4PCp0Oi8D2gyyJAeO9EkEWya9LWBeOsqSNBdTk5lk+iZZkprHe3e8k+HhYcU7LhjnKsEdSqYtUJ7qvvvuIzs7mx//+McMDAxwyy230NDQEPHZeTbGoMXBJAYhnKFAMtxxAxFufbvdTk1NDQaDgerq6pgT+7lKlIiiSGtrKwMDA2zevJns7GxaWloSGthUKhV6vZ6VK1ee1t3d0dGBwWCY0W0cfLM8/o9DvDb9R0Z7TfhXqBBtKlD7QQW6KQGXU4UjX0TTnYKh0InG5MXrVWH3GVm3fAnfu/AqtCo19fX1i6YgTeYoSqAbOpx6qMsEWG9vL8CMYtJgMETs2JQk6fx4boxITU1l9+7dITdwEmmWJMeWEydOcPLkybiLx1gIbrlQDEXez3XTTU6sLBYLtbW1FBcXs3TpUkRRVPTCLBaLQugKgqBoFULiiZ5Rq5XvPfUAky4n2iIvPrseHYAKxHEBt6Ch7XgJ6zacpGtKT0GKh9sufJnhqXSmvBsoL/gEWemr5nQOs5Fpwdp0U1NTWCwWBgYGaG1tJSUlRYmvGRkZUSVQC6XBHUkeINJm6KpVq9i3bx833ngjjz76KF6vl9tuu42rr75aSWD6+/u57LLLeOyxxxQD5xtuuIG7776brKwsTCYTt99+O9XV1ezcuROAyy+/nNWrV/OhD32Ib37zmwwNDXHfffdx6623KhsIN998M4888gj33HMPH/3oRzlw4AC/+93veOaZZ4BTSZ7cbSAjNTWV7Ozs036eaETKb+Q8oL+/f1ZdxmggG7clElNTUxw7dgyTycSmTZsUrcBkIZoO7sVY/C2W/CYY8mclx5RQ/iIWi4Wenh7FX0SOWaFIsGQgWh+SsrL4NinPVQiCgNvtpq6uDqfTyc6dO+OeBIyXXBJFUZH0kusceT3594lAcD02OTnJsWPHyMjIYMuWLVFLKS02ckmSJL7w+5/S8JcRdmzqZ0qtQ9SBSpDINE1jsIsYipx0NedRmm6jbwMYG1V47Kn0Hy9GY/Ty0B23k5tlVmqRhoYGJEkiMzNTqVcWunsSZtfgTzYi5UBarRav18t9991HaWlpVGt+/etf5/7776e0tJQPfvCD3HXXXcp1ePjwYS666KIZvMPevXv5xje+gc1mIzMzk8OHD3P33XfPWHPv3r08/fTTAHR2djI0NDTDYNtsNrNjxw4OHz7M1VdfHZf5d6IgX09y809eXt6MhpxYEe8GfjiuJ5ENAbIEhLyeLAvW0dERkzKAvFZgDFro3GJgzMrXHvkGHeM5fOat7fysbTua4ikKs8cYeWkHecsG6CvMYlv/ONJ2Hf40G+oJHc7OHPoNPrIy1fz4059lenoai8XCyMgI7e3tGI1GpRkoIyNjwWPQQsefSFNser2e8vJyfv3rX0e97tkYgxac4A6+SB0OB7W1tcrofuDOTaLduYMRqoNbdg+PZVctmnWjhdfrnZF0yruZyUyugru7ZTM1i8VyWne3RqXhoWd+x1GPl2XFaqbdRgSVC0EtgtOPmCKinlCT0qXCUaZhosiP02lANymh06r58lv2cnHZMuXYiylhnM9AZjAYKCoqoqioCFEUmZqawmq1ziDAVCoVOp1u1gTrPMEdG2QzmVBI5IaaKIr4fD76+voUwi4eRFPsiaLI8ePHGRwcnFEoBq8z1w5ul8vFsWPHFLLe5/Mp56XT6RRCV76ex8bGlI7OmpoaRcok1LRCLPjJi5+j5uUpCkyTGCu1TE8JIL81AQS3m+72XFSShNOpZ2VVD5NOD163lhTthVyw/vNzTpZikY0RBAGTyYTJZKKiogKv16vE15aWFrxer1JQZmVlhb0+FyPBLXsARPocHn/8cW677TYuu+wyVCoV73vf+/je976n/N7r9dLa2orD4VB+9tBDDymvdbvd7N27lx/+8IfK79VqNX/961+55ZZblM6f6667ji9/+cvKayoqKnjmmWe46667ePjhh1myZAk/+9nP2Lt3bzwfR0IxW34T2NW0a9euqCaqIh3L4/HMaY1AyF3lS5cuZenS/8/em8e3VV/p/2/ti2XJ++54j+M4++LEgbJDKDBT2n5p6TBToC0MFNICnQLtQBcoZSilQCEtQ6HQzkChtFOmNIUSwlIWEyC2492xEzveF0leZe26vz/yu7eSLFmL5dh08rxefZVYV/deSfeeez7nPOd5SqUEfCmf59FocK80rKT8Jhhi7A713YWbSLFarQFFMHERulT69aem2JYGExMT1NfXk5qayubNmxellx/POk2UURMEYd66z9+ULRHwX4+NjIzQ3NwcELeixUoqcH/Q38IDz/wvuUOj2LOLKTJNole7wKGgbSqX07c18eJbO8n/5CBDa4xMDmRTYTEjr/SCysUNp19PRW6ZtD9/aUWxGT88PExnZycajQafz8fExAQmk+mk5iDBTbjlQDQ5EBB1g+hrX/saW7ZsIS0tjffee49vfetbDA8P85Of/AQ4cY2K3iYi/M2zU1NTw5pn+5tr+78v3Daxmn8nCoIg0NXVRW9vb9zkH3/Es3YTY0FRUREVFRUBsSCRMrPwt+a81+ultbUVi8US17pwpRjd+nw+/uPAL/noyBjK97Xo1rjJzZpFf8xFlzkDVamH0qxxZjq1ZK2e5JAqm8whN/kpk3jznKQbdHxr9+2oVCcKqAaDAYPBQFFRER6PR1ofdXR04Ha7pftPZHefzM+8EiZIosmBYqkD/b3GoGUvcPtjbGyMpqYm8vLyWLNmzbyLaKkZ3P5BTBAEuru76e3tZf369TFpQAUjXrakOPqv1+vZuXNngBZRopOrhQJEKO1us9nM611NNBzeT8tQGRlnT+O0KZE5QSn4UKS6cE6p0GQ68fk0qGxykjsUeJPleDVw+ZZ1fO3cXfOOu5JGiperUyeXyzGZTJhMpoACWE9PD5OTk7z99tukpKSEdM89pT8ZO8LdS4mKNzMzMxw+fBiAnTt3xiVHISLSYs/pdNLY2IjH46G2tjZsIWwxDG6fz8fAwABOp5Oamhqp6BEO/tdzUVERf/3rX8nJyWFycpK+vj7kcrnEDkpLS4uoOyfiN4c+onvmMfoPG9FNevHpZQhqGUk5XmRyJ8i04AWZ3IvQD0encpkq19N1PA+9SsalZ3+a0zdujus7CIZ4/cQTu1QqVYCeo81mi0qrfyUWuKONP2lpaQtqqhUXF8+7J7VaLXv37mXv3r1h31dUVDRPgiQYZ511lqRJHw3efPPNqLeNB/4SJaHijcVi4fDhw2RmZi6K1eSPRGlwi5Jm/f3981jliV4UBiOaGLZSClD+WCn5TTBiiWGhJlKsVisjIyMcOXIEnU4XMJGSKGmfaBZ3c3NzpwrcMeLYsWOUlJTMm/SKB7HmTVarlcbGxrDxTSaTJXTtJ5PJ8Hq9UkEt3mmYlVDgtjucfPX5n6D0DDCpz0PbqUe2CebsanalT5A67eSvfWu4uvptzrcf5q0/VZOzaQpF4Qx2n4zTTWdw5abwrLhQzfje3l6Gh4clzxX/Znw00i6LwUpgcEeanhSb8pE03Nvb21mzZk0A63HDhg2o1Wr+9V//lXvvvXdRa4WPE+bm5hgbG1vU5Ig/YokX/jnMhg0b5hXgIPG5jFwux+FwSHJ4ojdSrFgJMejdtlZ+0f1nTIMuyotm6NJm4nYpcToVnF/ZweH2s3ltaC2fuuRtXvlLLf1vpVKyyYKszIfbm8SedVezOqMs7P6VSiWZmZlkZmZK9afm5mZsNhsHDx6U1kciuzvRZubBWA7vI39EM71ts9no6uqK+Cz/e49BK6LA7fP56Orqoq+vj3Xr1pGbmxtyu0Rq4oaCGBTdbjdNTU3YbLaEBNx4mExms5nGxsawzPGlCGzR7E8mk/HXtj6eaHwPT183yXkGBI8Mm0eFSTWHQefEOqIlOcfOVI4C54gCjcmBL1UBThkmmYonr/oc+enhi2IrZQG43J06EWIBzGKxkJmZSXZ2tsSeOnbsGEqlkuTkZA4ePIjD4QhbYLrnnnvYt28fjY2NqNVqJicn523T19fH9ddfzxtvvIHBYODKK6/k3nvvDXhovPnmm9xyyy20trZSWFjIHXfcwVVXXRWwn71793L//fczMjLCxo0beeSRR6ipqZFedzgcfOMb3+C5554LYGP6JxfRnMtSQowHi2m6iMzGwsJCent7F33uIjMyVLLlb8wUadQ2XnalqLErSlFEKm6HOn84wRASzTHE0ffe3l7a2towGo1SwhLK2Gxkysqnnvtv0gUHnyyZY1SWBF4BpcaLdcxEeYmFpMopZts0qG0im9sL5jkcCiP3PXgV2dnxMejDYTEFbn/IZDKJveA/PWO1Wunu7g4wfvN4PCc9VkZKrkQG9ynEjmBWtb/RUSJYTcHHWuyCLXi6LPi5czIK3P6Ynp6ms7MTg8EgxaXlXvwFY6Wdjz/EhlmsMcW/CFZcXBzAuOrs7JQm/kR2t16vjztuLQV76RRgy5YtCbs2oy0uCYLA8ePH6erqorKyksLCwrDXRaJjyfj4ODKZbFHru+UuLjU2dPD7kRacOXJWz8pR6r0o5V4UKh8fHs/jTMdxrt3+Lg8dOosnnGexvego//D59xgZSsU9Vc53L74dmSy2xpNKpcJoNDI1NcXWrVuZnZ3FarUyOjq6pI0tEQtNmZwsRCPTptFoqK+vX3D9GM58eceOHXg8Hnp7e6msrAxrjA2RzbP9Xxf/5l9fEWVgxW1iNf9OFAwGA7t2zSe8xYtoY5C4nnE4HCFzGBGJjj+CIEhSLNXV1XHXGRLl7xYPfD4ff3nnQ46XOjBqbYyPZZNZMQmTAu4KFe835nHhOd3UHuulrr4K8+pktp7eS5Wni96hHM7M+Uc+uT62yUlRXUCr1ZKZmUlOTo60PhKNsUV1gWDyX6Kw3CTMaHOgrVu38j//8z8Lbvf3HoOWvcDtdDo5dOgQbreb2traBRPTk8Hgttvt1NXVkZSUFJWLbbT7jTYI+Sd9a9euJT8/P+R2y5Fc2ez9fOO5/6ajzYRQY6fkoylsebnIPWA2G9lePsSAG+w9qSBXkJE1w2yKEs+UGq0g8O87z+f8ojULHmMlLQCXUoM7HoiBzd/QRHTPbWlpkZiNn/rUp7j44ou57rrrAooiLpeLyy67jNraWp588smQ+7/44ovJycnhvffeY3h4mC9+8YuoVCp++MMfAid0lMR9P/PMMxw4cICvfOUr5ObmSmP+zz//PLfccguPPfYYO3bs4KGHHmL37t10dnZKTJmbb76Zffv28cILL2Aymbjxxhv5zGc+w7vvvhv1uSw1lEolgiDEZW4UrJebnp5Ob29vVA+nSAgVT4aGhmhtbaWsrIySkpKI1208Cdvs7Cz19fUYDAbWrFlDd3d3wOux3Cv+o6bi6Ht5eTkOh0PS7j5+/HiAVn1aWhrfe+kxXu1WkKRzk6RyYpvQIlMKzAzrKDtvHPl7MqbytWz45CRtephuMiF4NCCDnDIlD9x5DSnGxck7LPR5Eh0v/KdngADjN7fbTXNzc1zs93gRib1wSh4gfviP9rtcLpqbm5mdnY3Z1DoaLJbBPTMzQ0NDA0lJSfOmy0Qs9eLLf/+jo6M0NTWRm5uLy+Wira0NOMFQyczMJD09fVlMET9OSFS+E4px5d+QV6lUUrE7NTU1ppgVzdTKqQJ37EjURAdEt07zeDy0trZitVrZvn275M2x0PklIpbMzc0xNDSEXC7ntNNOW3RMWI71StvoWzz1xP8ybVOjXKfDLQOZwsf0eBI7PtHN+EdpHCvO4nevVnHpOZ08fO4f+EPretrqyuhQlvPvF32GTSWr4z6+WOCRyWQkJyeTnJwcVkrAX7ZosbJa8LcYtdwFpoVi0OzsLAaDYUGj7YXQ2NiIXC6X1kq1tbX8+7//O263W4qV+/fvp7KyUmrk1tbWcuDAAW666SZpP/7m2SUlJeTk5HDgwAGpmDQ9Pc3Bgwe5/vrrpX3Eav6dSCTyN40mBomEIJPJRG1tbURCUKLi48DAAF6vl4KCAtasWbOoz70c94HX6+WFgw/y1xfGGNSlolMLJCmcWH0CvUIKKapZ3HItL7VXkZNpY8/OOs62dvNS6zr+2rGRwpRk/uNzX0KvjX/aQ4xB4dZHFotlXq6RlpaWEHLcStDgjiYHyszMZM2ahett4fD3EoOWvcA9PDyMVquNytxDoVBIBaeluMBcLhe9vb2UlJRQXl6esOAR7UJPNFkZGxuLmPSFKnD7s01j/X4W+qw+n4/7H38AobqFjubt+FIEZBofs9MqUlQ2JtJMaHoUHEzPZ3PqKG5BQapNzky7FkOym4o0DZekbsXdM8LhSeeCCc9yd8f8sdyBLBihiqOie+4ZZ5zBn//8Z6qqqvja177GgQMHsNvtAdt+//vfB+Dpp58Ouf9XX32VtrY2XnvtNbKzs9m0aRN33303t912G9/73vdQq9U89thjlJSU8MADDwAnDOPeeecdHnzwQanA/ZOf/IRrrrmGq6++GoDHHnuMffv28ctf/pLbb7+dqakpnnzySZ599lnOOeccAJ566imqqqp4//332blzZ1TnkigsJFEC0XVM/SHKhIhNu6SkJGn/iVik+S/2fD4fR44cYWBgIMCQNxJiLT6JDt+rVq2ioqICi8US8J2Jcdnj8aBQKMLGoEj3tlarJT8/n/z8fKl5Y7FYONjcwHP1f6U/PQ2vRo9K7sVrV5G2eoYeayqCSsZIi5GSyjF638xkbrOK9bWTOHbNgE3DpZsuZ/OqT0T9eWPFUhW4g+Fv/Pbmm29SVlbG3Nwcx48fp7W1FaPRKMVXo9GY0PPx+XwIgpAQiZJT+BuCJUqmpqZobGwkOTmZXbt2LUnTYjEMblGrsri4eME86WRocIss96NHj7Ju3TpSUlLw+XyUl5fzzjvvoNfrGRwcpKOjA4PBQHp6OhkZGYvW/V/sea9ELMXEmr+fS2FhoXR9WywWenp6aG1tnWdWudD3E+lZLBbUEzHmfgrxIVJxaW5ujvr6elQqFbt27YpqBDoRBW7RwE6v15OUlLToHDJcfIuUA8WLWaedhxruZPxdJ7ZjSUwnG1Ap3cy5tKRmzKBv9TF0vpHs98yMjmfypqqCxufzWJc3ilblZr0qie9+9WuLPo9wa7RQjS2LxYLZbKa7uxutVhvQ2IqH6LES1mTRMLijbfLX1dVx8OBBzj77bJKTk6mrq+Pmm2/mn//5n6XC0T/90z/x/e9/ny9/+cvcdttttLS08PDDD/Pggw9K+/n617/OmWeeyQMPPMDFF1/Mc889x0cffcTjjz8OnIjDN910Ez/4wQ+oqKigpKSEO++8k7y8PC699FIgOvPvpUQiSXuR4sXg4CBtbW1RE4ISMfEmkp6GhoZQqVRkZ2cnZOLT/7xEL6ClikF/HWjn/f576Xo6C50J5rRqNIKbGa+WnEILTU35XPyVBmYeVuPYlcyjdbuoaB6jIGOaHN80l3/iHzl3+7bIB4qAcDHIf33kn2scO3aM1tZWTCaTFINCTQdHg+WOQdEyuMMpYQTj7zkGLXuBu7i4mIKCgqguNP+CUyIvMNHgYGpqiuzsbCoqKhK2b4huoedyuWhoaJBMpCLpMfk/DHw+nxTk/BNLuVwufU/xfl+d/Uf53r2/5AuXfcjTA6eBTw4ekAkwU2iixDzMeGYKtuNJzH2Qwl/L9KwtHEad7MPoknPnuTeQbgif8PhrJ4m/70pZAC53IAtGNImVVqvlyiuvlIrLsaCuro7169cHyITs3r2b66+/ntbWVjZv3kxdXV2AC664jdi1c7lcHDp0iG9961vS63K5nPPOO4+6ujoAaWLDfz9r1qxh1apV1NXVsXPnzqjOZakh/vaxdO4nJiZobGwkLS0toGknJhqJYAGIyZv/eJ1YSI8W0SaT/hMl/g7f/u8XBAGv1yu5O4eKQcH3UTTHlsvlJCUb+NEb99FxSE5utQ/XmB404HUpcCjl6PNcuPapMZ41y9CBFJyTNoorx3AeVzF1TEP16s3886euXfKYshzmR4IgkJKSIv0movGbxWJhYGAAQNLpT09PX7SWmvi7RpIoOVXgjg9yuZy5uTk++OCDqBdeizlWrLHI35cknFZl8DGWenx2eHhY8gJISkrC7XYDSFIvubm584xcRRPzkzn5IGIlTagF42RMrCkUCikmwQmpMpHd3d/fDywcs06ZTK58LFQMEhvl+fn5VFZWRv28XEws8c9hqqqqcDqdkhHgYuGfA4mFpWhzoFhw9+uP88aMmfOyxpg9nI3aJCD3CrjdcpReORZ0lBWP0vHXYoq/MsCGph6O16Xh0qk5Zkvnvu/vITMnY9GfF6IjIfk3tvyl1iwWC0eOHMHpdEpSArHIFi33miyaJr8Yf6L1Mnjuuef43ve+h9PppKSkhJtvvjlAE9dkMvHqq69yww03sHXrVjIyMvjOd77DtddeK22za9cunn32We644w6+/e1vU1FRwYsvvsi6deukbW699VZsNhvXXnstk5OTnH766bzyyisBtYZI5t8fF4Rrsvl8Pjo6OhgeHmbz5s0S8zcSFpvLiGs1p9NJbW0tH330UUJyAf9rLNw6TFx7LqbYPWWb4Jr9j1Ga3oP7WDLOESWGTDc4QadycdyWzvmlHYy9m8LLA+s57RtdzL08xdiACXOKhhxDNXfffuOiP6//Z42mKSHmEhUVFdjtdml9JE4H+7O7o80B45noTiSizYGinZj5e45By17gjkXzz7/AnagFicvloqmpCbvdTnZ2dkLGqIIRiS05MzPDoUOHSElJYf369VHdPOI+RSdeOHGhikFOfBCLI8/RBDn/gGu1zXLnL55gZvwI02MZFJdNMNOvQyYI4JTDpBznDj1HfpdM+dZjjJTlMjGTjK9bgaUvn+v+8WzO27Ix4Hz9Ex5xnM1qtQaMszkcDmmRutxYKRrcIqLRv12MvmU4F1zxtYW2mZ6exm63MzExgdfrDblNR0eHtA+1Wj1vQiHYTTfSuSw1YjE3EgSB/v5+Ojs7qaioCGnWlCiJJblczuzsLE1NTSQnJ0ccrwu3j0gJ1kITJWKB2z/eKJVKacpG/Jt/8y3We+nLe+/BZBxk0JWKUTuDWqVGkIN8ToYjRYZO6eYvr2/ik1c28PpvK9F8wovToaJvOAOfSs4/n/d5jJqT47B9shjc/scLXmgFG79NT09jtVoZGhqis7MTvV4foI8Z6+8h/o6RFnenCtyxw+v1Mjg4iN1uZ9u2baSnpy/p8WJlJPn7kkSSkhOxlBIlYjNHLpdLEik+nw+VSsXs7CzNzc1kZGSgUqkkQkR6ero04TI7OystdKLR/U8kVkoDPxjLke9otVry8vLIy8uTYpbFYmFoaIiOjg6SkpICYtYpDe6lQSKvSblcLq07RAiCwNGjR+np6QlolMeyz3hiic/no7W1FbPZLOUwPT09CSkuifeKuNYSG0RqtVr6dzzrMH/UH+/iyQ8fo1udzhbTAJNTSfjsclxqGenJM7QN5ZJXMkHT9Co2FPaxK2OaYw051MuzUJ7r5cbzd3PBxo0RjxML4pmyDSUlYLFYAmSLxPjrb6Qd6tjLXeCGyDlQtA22LVu28P7770fcbsOGDbz99tsLbnPZZZdx2WWXhX1dJpNx1113cdddd4XdJpL598cFodZaDoeDxsZGfD4ftbW1MdV6FlPgFuXcDAYDO3fuRKlUJqz5L+ZY/msulUo1b222mIbbfa//mkPjR7HodZyRPMXR2RM5lFeQkTplZ3pWi0Hh4Z3pcrbuOEruoImOhiIcJQpSN6l58svXkKSL3UBzIcQTg3Q6XcB0sMjuFnNAcZIsPT19wQk/8TteLkRTYI9lkvbvOQYte4E7FiSSBQknAk99fb1UJOrq6loSje+FikmidmRpaSmlpaVR37Rih86/Syf+zz/x8v/fQkFOPK7H4+HWlx+l68NZTGVT+A4KIChQyAUyU2cYVujAp0A4qkVWJTB5WRZN7cmkj05Tmefi3PNr+eQZF0e8Af3H2VavXi0lPJOTk3R3dzMwMBCS3X0ysRI1uIMfSt/97ncDxkRgfiFRdMo9hdihVCrnLdaC4fV6aW1txWKxsHXr1rDu6YlKanw+H+3t7YuSUopUfPKfKKmtrUWnC9RLEwvcYgIlLtrEcxHvVzHuiEmYw+EAThTMlEplyIXeh50d/MefnkEY9pD+CZga15EtTONxK1ClOvAc02NPVaOy+SBJx+/+uoPTPnkEk3IO+6wKrbCaat0FaORKXC5XQnTPI+FkMzMjmS3JZDJMJhMmk2keg7WtrQ2Px0NqaqpUPIom2Rfjz0LXm81mi8jsPYVAuFwu3n//fQRBkBzhlxqx5FGi9r5er4/Jl0S8rxMtOyYSAhQKBXl5eZJXglwux2q10tTUREFBAeXl5fMWeuJ9o9frMRgMFBcX43Q6pXvj+PHjKJXKqIot8eD/OoN7IfjHrNLSUtxut8TuFmOWWq1Gq9UyNzeHTje/eenz+U4VuJcZwc0zsTm2GD+BeNZ9DoeDhoYG4IS2p8gSS3TjLbh4LcI/B4p2HSbC63Vx65O/xJbVxYg3FZ9ShlbhwZ0kR67z4Z5UkFLoIbd3mnGNgdzcaXocOThlAinVDs7JLebfPnFFwj6jPxIRz0UpAVG2aHJyEqvVytGjR7Hb7WGlBJY7Rom/XTQa3KcQGxIpURJc4BYna9PT06muro55PRDv2k2s7wTLuSXqs8a7Doum4dY9eJRvvPA/rK3oZU6dh08hQyHzoUzxIQNmR5XkZ03Q2ZyNdp2TpCQ378+Uok9zkpxl49u1l7Mtv2rRnzEUFhuD/L2f4ARhQmy49ff3I5PJAibJ/OWslltGN1oN7lMx6GNW4IbEsSCHh4dpaWmhpKSEsrIyia25FOzhUMFR1I48duwY69evj8khVAyMo6OjqFSqsONQ/omTP8sgVJDz+XyMztn42e++y1FVEsYJN0qDgNMu4FEp6T2aygVFLfxi9Rmo22T4BCW+w0mQ7sGVrKOoejPf/YeL0Cti17XzZ3ePjY2Rn5+PUqmcZ1YSSzEmEVjucbhghCrU7dmzhyuuOJHIvv322zzyyCPs27cvYJtwTrnByMnJ4YMPPgj4W7ROuUajEZ1Oh0KhQKFQRHTTdblcTE5OBrCCg7eJdC6JwkIPq2j0JBsaGlAoFAGLqHj2FQmiRIDD4aC4uHhRUkoLNd3Exp/RaGT9+vUhCzyCIOB2uxkcHCQjIyPs5/aPQVNTUzQ1NZGdnY1arZ630AO45of30JmURpnGgdsnw+NVINOBvUeBVZdKSdk4naZC1AMqprLB6XGj93n5S+M6FGoVv//n69CoVExMTHD8+HFmZ2d5++23543DJhon2/woVla8SqUiKyuLrKwsBEHAZrNhtVoZHx+nq6tLKqyKDcVQv3k0idUpDe7YoVarWbVqFUlJSRw+fPikHDNaBvfY2BhNTU2S9n4s17d/7pGoBtPY2BiHDx+muLiYubk5JicnmZiYICUlRZpUqKqqCpBSgvALPXHyJCsri5ycnAAWsVhsiWeU/uOI5WZHBkPUKc3OzpZiVkdHBw6Hg4MHD0oxKy0tTWpEzM3NAZzS4F5G+Oc5IntRbI7Fq3sd68TJ1NQU9fX1IQtaifIGEOPA6OgomZmZYRt/odZhol9SqGLTkO097vrPAxzT6vmEdpZhIRV8Mg6ZV3F2cQfOrUqsBwyY29VklU1jGphjtNcIqQIlKRruumoP6cmJNSUO99kTAX8j8UhSAnByZeCCIco/LHQOc3NzpySSlhliDBIEgb6+Po4cOUJlZSWFhYVxXbuxFrgj1XcSQXYSY5jNZpNyoIX8UKIlPsoQ+EvvIzz5czeOGi9jNiOCTkCh8GJ3q1GUeNHkubH3q5mWq1iTM4KlwcCkVocxxUNt6Rpu+uznljxPSuT+NRqNNEnm8/mk6deBgQHa29sDfEISLZEcK05NsUWPZS9wxzPqtJgikb8p28aNGyWXUFg6zchgTTav10tzczOTk5MxMxrE5KisrIyRkREp0RfHv8KZd4g3ZChWgcPh5L7336XbNkyWToZsSoYcAa9KjkonoFTZ+fNz1Vxz63tcvvUgf9JvwtGjQ2GXo5318MUdp/GFM2oW+S397fMFm5UEF2N0Op2U8Cwlu3ulLfhCBTb/sb/m5mbS0tLiZmvX1tZyzz33MDY2Jt0X+/fvx2g0snbtWmmbP//5zwHv83fKVavVbN26lQMHDkjGAT6fjwMHDnDjjSc0uLZu3YpKpeLAgQN89rOfBaCzs5O+vj5pP9Gcy8nAQvEmVj3JxUyfeDweDh8+jM1mIzk5OS4WVPC5hIp1YkGrqKgoJDtcXJTp9XqKiooYHBykvb0do9EoXYuhjMLGx8clYzpRW9i/2PTcX99iX/0BrEImyAQ8LjlelwJ1sgf9jJtJUyrZ6mGEoRTKCwbpncxAPaHD61Uyq/Px9V1b+KetO6XjZWRkYLfbUalUlJWVYbVaI2r/LwYnu6u/GM1vmUyGwWDAYDAE6GNarVa6urpwOByYTCbpOxIbqKcSq6WBTCZj1apVzMzMRJwWSRQi5VH+kgKxNuBFJLLALQgCvb29dHd3s27dOjIzM5mammJgYICWlhaJmFBUVLSgrma4YpP/Qs9gMGA0GikrK5Nkt0SjIrVaTUZGRtyxY7nZPwthpTX0/SHGLJ1OR0ZGBoWFhZIBsdiIEASBl156CWDexFEkOJ1OduzYweHDh2loaGDTpk3Sa01NTdxwww18+OGHZGZmsmfPHm699daA97/wwgvceeed9Pb2UlFRwX333cdFF10kvS4IAt/97nf5xS9+weTkJKeddho///nPA5rUVquVPXv28NJLL0nakw8//PBJiaeJLlh6vV6JRBTJjDYaxLI2GxoaorW1lfLycoqLi+cdN1HFJblcTlFREb29vbS1tZGSkkJGRgaZmZlhG2Gh1mFiIW54xsJb4/9O77iHsZ5qXLtAKfPic8gBGXa1miTBhb7GieCRMVOvY6JNhUwLhSVTfOOLN7OqKDpjscV+9qWMYeGkBHp7e7HZbMjlcnp6eiJKCSwFTnkAfDwgl8txuVw0NzdjsVjYtm2bxNaNB6L0YjTPSI/HQ0tLy4L1ncVOkYjnkp6eztTUFIcPH0Ymk0lrsPT09JgabmIt6NWBvzLne5jX9q/BZUhDp3Yj9wioFD6cHiV/6t3AF9YchM/A5F/0OPvUmMfVKFMdnFlpYs9Xvo5KtfRlxaWMQXK5nJSUFFJSUigtLcXlckkNt+bmZjwej7S2TIS3UayI1mj7VAxaAQXuWKFQKOJeBAYL/QdfAImUPwner1iQcDgc1NfXS4zPWG4O/6J0bm4ueXl5eL1eqXjT3t6Oy+UiLS2NzMzMqJiVP973PC99OIy5UMV61SRuFAgaAe+EEsEhR12jxvC6haPebPbeewYXXNrOd2r+RF9VKh57CZfvuheVMnE3UjCzIrgYI2p3h2J3p6enx7ywWeg8VtpiNBoN7oWCWl9fH1arlb6+PrxeL42NjQCUl5djMBi44IILWLt2Lf/yL//Cj370I0ZGRrjjjju44YYbpOv0uuuu49FHH+XWW2/lS1/6Eq+//jq//e1vA1jjt9xyC1deeSXbtm2jpqaGhx56CJvNJhlfmkwmvvzlL3PLLbeQlpaG0Whkz5491NbWsnPniSJlNOdyMhCqEBSvnmS8Ttw2m436+nq0Wi21tbU0NDQseoEWyn3bv4AUyoHZPxFSKBSUlpZSVlYmjXeZzWb6+vqQy+UBidbQ0BDd3d2sXbs2oFAml8t5+6OP+I/HXmaiNon8o0pms7UIuFHoBBwOH6oZHyVaK201WYy+bSI7awKHK5Uq0xjqPA9lpjL+7R++GvIzivevOB1SWFiIx+ORCiOJjB8nO1b4S1MtFqH0MUVpgN7eXolBpdFoohqNO5VYxQd/1tFSX0sL5Toej4empiZmZmbYuXNn3GxY/0XUYhCso2swGPD5fJhMJgwGg6QNnpmZKRVCTCaTdE2HK4KEKzb5T7iJLOLc3NyAYktnZyculyuu2LGScgp/rLR8JxTExZ0/6xPAbrfT0NBAU1MTACUlJVxwwQX8x3/8BwUFBRH3e+utt5KXlzdvgmJ6epoLLriA8847j8cee4zm5ma+9KUvkZKSIhksvffee3zhC1/g3nvv5ZJLLuHZZ5/l0ksvpb6+XjJY+tGPfsRPf/pTfvWrX1FSUsKdd97J7t27aWtrk3L0K664guHhYfbv34/b7ebqq6/m2muv/dhp4oq5RWtr6zwSUbyIpigtCAKdnZ0MDAywadMmSW8/3PnFA3FdIMaIiooKVq9ejd1uZ3x8HLPZzNGjR6MiHYmfC+C7f3maWVMd5+b20dBficwrw+uV4fIpYE6GLsWJ4FPxXN82LslpJve8Gazb9Xgn5eSkpvCvu+47aTKOJzNO+EsJlJeXMzAwQF9fH7OzswFSAiK7Mt4JgWgRTbP2VJM/PiTymvL5fIyOjmIwGCJO1kYD/1xmoRzYbrdTX1+PUqlk165dYa/HxUyR+E+AJCUlsXHjRik3MZvN9PT00NLSgslkkupAC035AwxaLNz+4ePsLn+XGZ+ByV4Tci1MyrRsN/UxNF6OQi8gM3r5Q/cWLik+TNo/zzEzokHhFjhv3fmcXnp5XJ8n3u/gZMUgtVpNTk6ONOF36NAhVCqVNDGYlJQkxSCTybTkJAGv1xuxBjI7O3tqio2PaYE7niL01NQUDQ0NmEwmNm/eHHIEO94CVCSIydnk5CQNDQ1kZmaydu3aqG8Efx1JcX/+o7f+bOfZ2VnMZjPDw8OSSY/IKjCZTNL7BsZ7+Ppvf4utT8V0pgZBAQoBVB4P4zla3MkqVIcVsFWH4Tw7qg+GsMwZ+K9nN2Awarn1xsvZtL0y4d8VLPygC8fuHhsbSyi7O15jvKWC+PsvdD6Rikvf+c53+NWvfiX9e/PmzQC88cYbnHXWWSgUCv70pz9x/fXXSw2gK6+8MsAQoKSkhH379nHzzTfz8MMPU1BQwBNPPMHu3bulbT7/+c8zPj7Od77zHUZGRti0aROvvPJKgDbvgw8+KLGUnE4nu3fv5mc/+5n0ejTnkihEkijxb6j5m63FWvyJp4EmssQLCwtZvXq1NB6ZyAK3fwGppqYGk8k0b3t/pmPwiGbweNfk5KTElm5qakImk1FQUEBycnJAYvJPP/gaM81p6E8XmHQpwCsHAWQaSJU7sJtUHH0jheKLJ6mcGWNsZzIT9gwUZg8qrY5HrvpWzPq4SqVSWniuXr06ZPzwZ3fHEqNPNoM7FoPmWCDqYxYUFAQU9UZHR3E4HHz00UdSjA1m659a3MUPfxPtROo+hztWqCZucDNtMQUDcb+LkQPw9wLwN5OUy+WSaZRGo5FegxNsXLPZjNlslho0Yg6UlpYW9ruNZozXaDSSkpJCeXk5DocDi8Wy6NixUrCSGdwiwrGXdDodu3bt4ic/+QmXXHIJv/vd73j11VejmnR6+eWXefXVV/n973/Pyy+/HPDaM888g8vl4pe//CVqtZrq6moaGxv5yU9+IhW4H374YS688EK++c1vAnD33Xezf/9+Hn30UR577DEEQeChhx7ijjvu4FOf+hQAv/71r8nOzubFF1/k8ssvp729nVdeeYUPP/yQbdu2AfDII49w0UUX8eMf/zhmU8blgsiaBNi+fXvIXCIeRMp53G43hw8fxm63hyQvBe8rnpjk3+AX9yPGOJ1Ox6pVq6SJKHHitK2tDbfbTXp6upR3+BfbDnYd5N59+5BVe/hU5iAOnxq53IvTpURvddNgymNr/jEODpejy3Yhl8OrlrV43EpUPhnfqTiHM9ZvifmzLAbL2QhTKBRotVrWr18vSQlYLBb6+/tDGsUlOp5Fw+CORDQ6haWF2Wymv78frVZLTU1NQq6BaJr1VquVhoYGcnJyqKqqWvC48TbZQulti+cnNoJEmR8xBzp69Kg0eZaRkUFaWpp0DQs+Hz966Rd84O5Bk+qlMtnCK+YsFCovSrMS57QSiyKJLOUUZncyXie4FEp+N7ANr1tBjqDhqQu/fNJkY/2/h+WIQeLaNysri9zcXMknxGKx0NraitfrDZDTTRTh0h/R5Gmn1mEnsOwF7pMhUTI4OEhbWxtlZWXSeHwoLKVEic1m48MPP6SiooKioqKoP3dwUrWQzqtMJiM5OZnk5GTJWEwMciJbN8lk4Lk/7KM3CTTJXqz2LIT/fw1rdhiozu1lxKXHfrYc2f4kNG/YESqUcL4Og0XG52t2c/6OXcAJplewseViEUvgWkp292IkAJYC4u+/UHIVSf/26aef5umnn17wOEVFRfMkSIJx1llnSeY94XDjjTdKkiShoNVq2bt3L3v37l3UuSw1lEplgJ5kfX29xAqI1Uk5ltglCAI9PT0cPXp0Hks8EXFKLLY7nU4aGhoQBCEs0yFcUhVuvyIrf3Z2FkEQyM3NZWpqivfffx+NRkP/lJU/j/8F44iSQYWWNOMc3mkZbpmMZJmDaaeGxski1q7pw3xETuf/plGwepqCggnykgXO3/k5zqo+HZ/Ph8fjCWnSJGKhcw0XP8xmM21tbQHJSnp6+oIskJOdcJ2sYpR/4mwwGOjv7yc/Px+LxcLAwACAZMYik8mi0uCOZxTf4XDwjW98g+eeey6gIebfNOvr6+P666/njTfewGAwcOWVV3LvvfcGFDTffPNNbrnlFlpbWyksLOSOO+7gqquuCjjW4OAgt912Gy+//DJzc3OUl5fz1FNPSYWnpYBMJpPO82QUuMVrx/9YojxRYWEhFRUVi76+xNwg3ljl7wWwbt06aV9yuZypqSkaGxvJyclh9erV8xpu/iPuk5OTkryZ3W4nNTVVWuyFK0QEF7uBedrdKpWK3Nxc8vPzJaM00cTV6/VKTSD/MdZTJpOLQ6S4Jzb5P/GJT3DGGWdE3N/o6CjXXHMNL774YshFel1dHWeccUZAo2f37t3cd999TExMkJqaSl1dHbfcckvA+3bv3s2LL74IQE9PDyMjI5x33nnS6yaTiR07dlBXV8fll19OXV0dKSkpATHmvPPOQy6Xc/DgQT796U9H/CyLQSJ+d38SEcQuE7MQFsp5RBPcpKSkgEZXOMQTk/xZk+L5hEM0pCN1soH/af8LjePTGEoduAQlarmbJIWAutCFxuBG2+9l1GSkJTWHXXld9E2lMuExoFZ5qckp4kzDFpJ1yRFzoERjOWOYv2ykv5RAWVkZLpdLMoprampCEIQAo7hETH5G60OyGDmMU4gP/rrXOTk5uN3uhN0TkQrcfX19dHZ2UllZyapVq6LaX6z3kX8MirQO0+l0FBYWSiau4pR/R0eHNOXf45zjjWO/o/NYCtlneNDIXMhkAga5m7y1Y7S+VkFG3xwHtYVsTxqgUDlB93gObrUcvdLNzVsux9ozJhEAElkHiua7WC74x6Bgn5DZ2VmJDHTkyJEA0oPJZErIlE00EiWnJmlPYNkL3LEiliKRz+ejs7OToaGhBUfWRCyFRIkgCJjNZqanp9m6deuC+pCh3huONRkNxAVYbm4ugiDw+3f/yKP3/YnKcyYZsG5gtW8ckKFy+nAhZ0huoNBuYLVg5qg2ndnPyHEM6FHMCJjmlDz99W+gVinnLfRgYTfeWLCYwBWK3R2KYZWWlhaR3e3/uVYCxOtyoXM+FdQSDzHeiLqO/qa08ewrmoVVJA23RDG4nU6ntLBev359yGsrluK2CLvdLjErd+zYIS04J2cmueOp/2AMFd5JDeoZJYJKjsrjw6lQkrPegu24hxly8Zi0NFuLqSwcQlB6MDuSkA9q+O+bfxCQ6IViVIkxKNZYEip+mM1mRkZGOHLkCHq9PiBZ8Y9zf68Fbn94vd55zxTRjKW3t5dPfepTeDwe/uu//gu1Ws3pp58eclEZzyj+zTffzL59+3jhhRcwmUzceOONfOYzn+Hdd9+Vzu3iiy8mJyeH9957j+HhYb74xS+iUqn44Q9/CJwoNF188cVcd911PPPMMxw4cICvfOUr5ObmShMoExMTnHbaaZx99tm8/PLLZGZm0tXVdVIWrOL16/F4llyGyV+Ww39hGE6eKF7EG6vEyZVVq1ZRWloqsc3lcjkjIyO0tbVRUVERcTEpNtzS0tKorKxkbm5Oavp3dXWh1WqlMd7U1NSQ95R/QQXCs7tTUlJIS0tj9erVzM3NYbFYGB4elsZY09PTl4RAkSisNM+RUIi0uBOZS9HEYkEQuOqqq7juuuvYtm0bvb2987YZGRmhpKQk4G9iU21kZITU1FRGRkYCGm3iNiMjI9J2/u8Lt02wlIdSqSQtLU3aZiVDNOMqLy+nqKiIV199NaFrqXDrPv84Ea0Jbqy5QTw5kIhg0pHD4eDaF/6Lo2M2NhccwzGYS8baWWbtWqY8OtbohlAaCimvPU7H22VkN7qYLTRyIC0ZldJDocrAzy69jqNHupiamqK8vDykUeVSFpuWk8G9UN6jVqtD5iZDQ0N0dHRgMBik9V+8UgKnfEhWJjweD83NzUxPT7Njxw5mZmYYHBxM2P7DNet9Ph/t7e2Mjo6ydetW0tLSotpfrHmRf74RawwKbri19w1wwyu/I1+wMpeiRan1Ilf6cDhUjLr1bDCMML5GR3a3mdGj6WTYHTRlFSCYfOjx8Kn87Vyx+TQaGxvJzs5GrVbPM6oMzpkSjZUYg/xjfXFxMR6PR5J6bG9vDyBcpqWlxc16jxSDHA4HPp/vlEQJK6TALZPJok44oi1wO51OGhsbcbvd1NbWRnUxJVqiRDSGm52dlQxIosVikqpgjE3N8ODvHmEyaQivQ0eyxotXJket8QACOouAIwW8WgUHZ4uokFmo0I/inNTgSdLxDzvO5dObz5X2F8mkSdwm3iCXiMDlz84sKiqKmd290iRK/OVpwuHUaFx8iMRIHh0dxW63R9UkWwjRNNDm5uZoaGhYUMMtEQXuubk5xsfHKS8vp7S0NKyZZKxJlciszMrKCjDe/Ma9P6RXM0O228WcwYDaaUch84LXi/OIDm21g8PTpVQlD1A8NYIVEzMyHV1CEXrBxdPXXkmhXwEglElT8KTLYr4j//hRXFyM2+2W2N3iKJo/Q/P/SoHbP7GSyWSYTCZMJhMlJSW0tLSwfv165ubm+OIXv8g999wzjx0dzyj+1NQUTz75JM8++yznnHMOAE899RRVVVW8//777Ny5k1dffZW2tjZee+01srOz2bRpE3fffTe33XYb3/ve91Cr1Tz22GOUlJTwwAMPAFBVVcU777zDgw8+KBW477vvPgoLC3nqqaek4wcXuJYS/hMjSwnx2nG5XLS2tjI1NRWz4XW0x4m1mHT8+HG6urqorq4mKytLer9MJuPo0aP09/ezcePGmPIpEXq9XpISEBcg4j3t8XhIS0sLKSUQ/JlC5UD+MVNkkYu6/2LuMT4+jiAItLa2njTd2GjxcWBwR1PgnpycjPg52tvbefXVV5mZmeFb3/pWok/z/wzEAs/IyAibN2+W7sl4pSTDITjn8Z9wi7UpF0tu4F88Xuw67P2uD7jtxTdxGZQU62eZVqgQXHI8djkqtYfOiWyKdVYuSu/ktQ1lbMhqx9yahs2qJ1Wj4ObLrqAku5DDhw/j9XqpqalBo9GEbbiJ55xodvdyF5eiOXZwbuIvJdDS0oLP5wtgd0er0RxtgftUcSl2xHtNzc7O0tDQECCrNjc3l/A8Knj9JtaYPB4PtbW1MU2sRFvzWkgWKVb4fD6+/9zjvDVtwT5ppCDHTLMiC+8cKPEybk/h6GwGtaY+tqUO0/iPPjK6rYwdycA4qWBdTib/9v+uZXZ2hkOHDknkAzGeBvuXiJ9zKRpuH4cYpFQqycrKknJYUQ5TnCbUarVSDriQT0MwosmBgFNNNlZIgTsWRJM4iaNyKSkpbN26Nepx30RKlMzNzVFfX49Go6G0tJTx8fGo35uo4rbP5+Oh/f/FG4cHKc8dYfaoAplGjlzlRe31YHElkWSaY3YyCWOvwEyeDK9WSacsmwFLFjes28Jl6zeFbQ5EY9IEsQW5pQpcsbK7xSC2UhZ8ornJQudjs9miMlQ6hejgcDgYHx/H5/NF3SRbCJEaaBaLhcbGRnJzc1mzZk3Ye2UxcUpka46MjGAymSgrKwu5TTxJ1ejoKK2trZSXl1NYWIhMJuOD3g94dO9zqFd5yTKAc1iD1yeHJB/qZBe6YR/WcR3FExMcTzHSLCshP2uUjJExjHMqTt+0kRv+4bMxOYJ7vV7JTFKtVuNyueaxu2OFSqUKSFb8x447OzvRarXSMY1G45IXn5ejwB3JYCkzMxOXy8X9999PeXl5yOd0PKP4hw4dwu12B4z4r1mzhlWrVlFXV8fOnTupq6tj/fr1ASzJ3bt3c/3119Pa2srmzZupq6sL2Ie4zU033ST9+49//CO7d+/msssu46233iI/P5+vfvWrXHPNNVF9R/HC31PjZBS4xXtB1NteyBBpsceJNlb5fD7a2toYGxtj27ZtJCcnS9e5z+ejpaWF6elpyWhysQhegMzOzjI+Ph7A+BOL3f7+Jf4IlwOJMVQc3RUL5waDAYvFgk6no7+/n/b29nm6scuVc/w9MLhnZ2cpKSnhrbfeWnA/paWlvP7669TV1c2blti2bRtXXHEFv/rVr8jJyWF0dDTgdfHfomFyuG38Xxf/5l+IHR0dZdOmTdI2Y2NjAfsQGzD+xsxLhXiuOYfDIcmb7dq1K6DAsxQFbnF/Xq+XlpYWJiYmwnqGRNpXpOJSsJnkYtZhNpud+179HgcPGFFu9OG06lCk+VD7vMiL5Uwd05K1dYZOaz4ahYfN6QOcl9mJ1ZSEtWSMKs3n2FzwBVwuFx9++CF6vZ7NmzdL90GoHEjM35ai2LTcxaV487dQUgL+03n+3k3hjhEpB4JTk7QnE6OjozQ3N8+b4FiKPMp//TY9PU19fX3MNSYR0azhYpFFioSDHx3m1+1PUH+0GHWRAplTjkbpRaFz45jQY59Uk2Ka46/9a/AJMtYmj3JR9gRjqQZmN85yQeadZKVVSNNza9asIT8/P+DzRJpw899usXnGxy0GhZLDFCXtjhw5gsvlwmQySXmgXq8P+/kixaDZ2VnkcvmS6H9/3PCxK3BHYjj5j8oVFxfHdBMkSqJELFTl5eVRWVnJ8PBw1N26RCVVdXWdPPnOc/RmqihTTuKRK5AlCfiGfczoFJS7LLTM5VBdNIRS5WXGmoS6U45P76MgX8F3L7yQmekp3nvvPfR6vbTQW+jhn4ggdzK0laJhd4tMNrvdviICRbTab6e6domB1WqVZDYMBkNCTDTCJV3+rMWqqqqITYp4C9z+C8OioiLsdnvIc4k1qRIEgd7eXnp6eli/fj2ZmZk4XS7uavh3+n/tw50hx5OvINs+h8OlQyV4ySixMTWhp8Rg4ehMBsMNJkwmD8mrzXjkKgzZWXzj/N1MTEzy1ltvYTKZpBgUbgTdP/aIOrhlZWXSgjZRckqhvA76+voYGBigublZ0n4Uk5WlKByuBAZ3MPxH4/w1pf0Rzyj+yMgIarWalJSUgL8Hj/iHkgAQX1tom+npaSnOHzt2jJ///OfccsstfPvb3+bDDz/ka1/7Gmq1miuvvDLsZ08UlEplgKntUkFkEptMJtavX79k11K0scrlckkTd6KOrpgDia/J5XJqamqWrBAv3tOlpaWSnqvZbKahoQGZTCbFn/T09JgbbmIe5HQ6USgUrFq1iqKiIlwul5R79PX1oVAopGL4QoaYS4GPA4M70uJubm6OlJQU1qxZE3FfP/3pT/nBD34g/XtoaIjdu3fz/PPPs2PHDgBqa2v593//d9xut/Sb79+/n8rKSkm2qLa2lgMHDgQ0yvbv309tbS1wYgIkJyeHAwcOSAXt6elpDh48yPXXXy/tY3JykkOHDrF161YAXn/9dXw+n3QuKwlifpSZmcnatWvn/SZLUeB2u93Y7XYaGhqQy+XU1tbGJeUUKSYlkjX5i317eevVdnSbFczoc0hWT4Mgo3/CxPnGHobz7djf0TKR4iWneJKumRy6J3PQKFxkyNL4ctY/MjM2xRtdbwAntNsrKirC3gPRNNz8t42n2PRxKy4FI1hKQJzOs1gsEaUETq3DVgYEQaCrq4u+vr55xAZYGj81cZ/Dw8O0tLRQWloacvo1GkRq/MczPRsKUzYz/3b3gxi2DDFxKAdZkYBPJgMBRkgjc24G+3o95r/qyTrbhiHJzltDazgoL0Ur87DLuJNaVSWthwdoZQCfz0dJScm879sfwTkQkHB298c9BimVSimfFAQBu92OxWLBYrFw7Ngx1Gq1tIZMTU0NyAMjxSCxwbbSc7mTgRVR4E6ERInP56Ojo4Ph4WG2bNlCenp6zOeRCIkS0WzAv1AVDYspFjPJhTA0MsF3/uN39IxMsu4SKzNzRSgFHz63jIyNc0z+Wk5nXSY1O4/haZXTZc5Gk+QlJ8uMQpBz6bbz+Nz206X9eTweaaHX3NwsjXaJN2e4BDNeVsFyBK5Q7O6hoSHJGM/fKGChAv9S4pT229LB/3rzLzZXVlbi8XiYnp5OyHHkcvm84pXX66W1tRWLxcL27dvnFfFCIZ7Fo8i2ghOL6ZGREWmUSYR/cTva+CMWk61WK9u3byc5OZn/fP9JXre1US0zIyML75wCpdKL2WJgTdYgMnkux82ryKoYxoaSCsMwM5NJzI6qkU14uP1rn2Pntk0B5y7q5vb09KBSqUhPTyczMzPAEdz/c2q12gCWUzRySvHe1yqVipSUFMxmMzU1NczMzGCxWBgcHJzH0DQajQmJb8tV4A53zO9+97s8+OCDAGHHxdvb25fs3BIFn8/Htm3bJN3uzZs309LSwmOPPXZSCtxLzeD2H+1XKpUUFRUt6XUUzUJTNIkzGAxs2rRJeo9cLpfGj9PS0li7du1Ju+b99Vx9Ph9TU1NS/GlpaZEabpmZmWEXE/7FJrEJODw8THV1tZQPifqYIrNQjB09PT20trYGsHqWetGyHDElVkRa3M3OzkadAwXrt4vvKysrk3L3f/qnf+L73/8+X/7yl7nttttoaWnh4YcflmIdwNe//nXOPPNMHnjgAS6++GKee+45PvroIx5//HHgRH5x00038YMf/ICKigpKSkq48847ycvL49JLLwVOyCVdeOGFXHPNNTz22GO43W5uvPFGLr/88pCyTUuBaNZhwfmROKkVjKUocNvtdurq6sjKylpULFjocyaKNXl0sI//bbuT/f9ZwIYrpjD3ZuJDhswDQrIH55iaUU8Gpd4xenZlMX3EgK1biybTg1oBN5/9JbavrgBOmP82NzeTnp6Ox+Ohrq4ubtJROP+SlTBlGw2WIkYFT+eJ073BUgLp6em43e6I67BTUpHxIdpryuVycfjwYRwOBzt37gwZ75cij5LJZPT19TE+Ps7GjRvnETViwUJTJIma4P/dm8/ybtcbDLSmU/1pOc6XlHgKFSRp5nCrk2jpz+XSinpsaSomq1MYftOEOt2DyuAhPSmXBy67Dr1WJ63xzGYzmZmZjIyM0NPTQ2pqquRfEmnKP9Hs7r+nGCSTydDr9ej1eskUVGR3Hz16FLvdHpAHejyeqLzYThW4V0iBOxYoFApcLlfA3xwOB42NjYuWElhM10/UohsdHWXbtm0BplSRRuISkVR5vV6+9uyTHH1+HJ/NjXNjCjqtC69LhmXKSFnWEILXS/KVArNPeTlozWPV6SOUeYaYmtFRblzDjZdfN+/YSqUyYLRrZmaG8fFxBgYGaGtrw2g0SolWuOJNLKwCkcW+XBDZ3dnZ2YyNjbFz505Jeze4ux9Ku3upEG2B+1RiFT9Ec8eJiQnpHu7r60tYohQcu4KLztHqAIpspmghSjalpaVRXV2NQqGYF5PiKW67XC6amprweDzU1NRQ39bL4wefZrxISaHJzdBQKgKgTndhtDhpncln49Z+1O/5yMmZxuLKJmnzBNNWNx7HHKU5eh7457vmHUer1VJQUEBBQQE+n4+JiQnGx8fp7OzE6XSSmpoqJVltbW1kZGTMk3jxj0FLwSrwlzQyGo0YjUZKSkokJqjVauXw4cOSXMFi9XeXg23p9XrDNjT37NnDmWeeyaWXXkpLS0vIWFVaWhrXKH5OTg4ul4vJycmABlCwDMAHH3wQ8L5opQSMRqMUx3Nzc1m7dm3ANlVVVfz+978PeW6JhkKhWDIGt795bU1NDY2NjUsuhxKpuW82m2lsbAxpJjk+Pk5LSwslJSUxT+MlEnK5nNTUVFJTU6moqMBut0sNN5FtI+ZAwQ03OBFbOzs7pdzQaDSGbbglJSVJLHKHwyExC8XGnsggj0WzMVqsdIkS8TuLxmQyUTCZTLz66qvccMMNkkn8d77zHa699lppm127dvHss89yxx138O1vf5uKigpefPFF1q1bJ21z6623YrPZuPbaa5mcnOT000/nlVdeCXjmP/PMM9x4442ce+65yOVyPvvZz/LTn/40YZ9lsfB4PLS2tmK1WuetcYKRqGlYEdPT01gsFqqqqli1atWiYkG4dV4iWJM2p4PvPPALDKsOYXXocDuVqIwCCpMPbbcbm12LNtWGc8bEh10lrM4fZbNvhMliJXavmgvLT+Mz2z8r3Yf9/f10dXWxbt06iTUZjnSUmZlJenr6gqQjiLwO85dyCzdl+/cqoxRuutdqtdLZ2YnD4UCr1dLf3y+xu4MJMqc0uJcOoseP0WiktrY27IRTogvcHo8Hl8uF1WoNW1SPBeHyIv/ib7wxqOX4Ue7+8a85+zOtHH2nHLXeg08OWp0b2aQCpdEHWU48Q1r+eGQL2wp6KVb0M7lBjUaWwg1n/DOr86qkz93U1ITT6WTnzp3S88pms2E2mxkfH+fIkSPodDopBwpn1g2R/UuiXYf9PccghUIh1ZcAid1ttVrp7e3F6/Vy/PhxcnJySE1NnTdNeKoO9Dd8LAvc/oFrYmKCxsZG0tPTpeJNvIg3KfMfrw1lNrBQ4TyewlIw9nW8xxN1rzC7X4NMJkPhEZDJwOB1oVZ7GVQlU2qTY+szUFhpY+YuJWOvaOj5XwNJ2Rq+d/sNlBXnRzyOf/GmrKwMl8slLfT6+vqQy+UBC71Yx3jHx8dxu93SWPJSGRREA/EBE61291Kzu6PRfpubmzuVWMUJm81GQ0MDKpWKXbt2SYuERBac/GPXxMQEDQ0NcbGRYmnEjYyM0NzcTFlZGSUlJVJ8EROseM0kbTYbjY2NJCUlsX79ev7lhz9iYMLEJy41Y/ZkAwKZSTP0zZpIyvdie19H5nnT/OWjKravO07SjIO+sRzm5rSkG/K4/+tfDxsvgj+7v7Hj3NwcZrOZoaEhZmZmUKlUKBQKqRga6ntdClZBuIQrmAkqMjQXq7+70jS4MzIyyM7OJjk5maqqqrDnFs8o/tatW1GpVBw4cIDPfvazAHR2dtLX1yfJANTW1nLPPfcwNjYmMWv279+P0WiUCta1tbX8+c9/Dti3v5QAwGmnnUZnZ2fANkeOHKGoqGjB72axEH/3pTKZ9DevFUf7E22qHQrhmvuCINDX18eRI0dYu3at1ECHE9/F8ePHOXbsGNXV1QuOwy4HdDodhYWFEttGbICLDTf/CTe1Wk1LSwuzs7PU1NRIuWG4YpN/w03UCM/JycHn80lFvq6uLhwOR0CjPRESWitdokS8LyJJlMS7uCsuLg55rW7YsIG33357wfdedtllXHbZZWFfl8lk3HXXXdx11/wGroi0tDSeffbZ6E/4JCLY/DqSNEiiYos4mWs2mzGZTAmJw6GKS4lgTf6u8UWe+k0jijEXl9ROc+wDE4JShnsYFGvcpB+Ypn80A6NyBkXBJLaZJDons+icziDdqOWFL15NkkYtnU93dzeDg4Ns2bIloLEbTDqanp7GbDbT399Pa2trVKQjiCynFCzR4r8OW072ZKIbewsheP0nmhGL7Eq1Wj3PKG4xMegUwmNwcJC2traopEESWeAW14YAFRUVCWmghiIYifef+Hqs95jT7eSOVx6g9Rk7qzZP4NXJcE+Bz6Miye3AsM2B6S0bFmMK6emTzK7y4prS8N5oKTKlj09vXMtt55wv7U8kYGk0GrZv3x7QTEhKSiIpKUlqAgWbdaenp0c15Q/xyymtdJPJREGn0wUQvN58801UKpU05Wc0GiXSVHJy8ikGtx9WRIE7lh/CP3D19/fT0dFBRUUFRUVFi/5B40nKZmZmqK+vx2g0smXLlpAdxXDdusUWt0fGzfzgjZ/SNGQkK8eFeliFM0WN3ONDZYE+axqr08doKcjl7b4KqvXD6HxONEoF+dtVXLLxk5y35eyYjukPtVpNXl4eeXl5+Hw+JicnMZvNHD16lObmZlJSUqQx3nCi+WLAGhoaoquri/Xr15OcnJxQzbh4EKpLF6q7Lzpzt7e34/F4SE1NlYJNItnd0Wi/nRqNiw9Op5O6ujoKCgpYvXp1wPecyIKT2EAT49ZCI76R9hON5NHRo0fp6ekJOU4n7iMerUmr1UpTUxP5+fkcGuvgx/f9N2OD6WgzfHhVMtwuJTNuNeeXdNKZm4VQ70O50UHS6z7SNs/Rbs/EM6XEoPDwvS9cQ2VhSUyfX4RMJiMpKYmZmRlsNhuVlZVoNJq4mE3xyCn5IxpGgVwux2QyYTKZKC0txel0SvGjv78fmUwmFawWahCK57kcEiWRzE0iJVbRjOIPDg5y7rnn8utf/1oyEfvyl7/MLbfcQlpaGkajkT179lBbW8vOnTsBuOCCC1i7di3/8i//wo9+9CNGRka44447uOGGG6Tf/brrruPRRx/l1ltv5Utf+hKvv/46v/3tb9m3b590fjfffDO7du3ihz/8IZ/73Of44IMPePzxxyW5gaXGUozWhjOvTTTLMhRCxargaTej0Sg93wRBoK2tDYvFIr22kqFQKAK0FEVm0+joKJ2dnZIWfVVV1YJFweAYFKrhlpycjMlkory8HIfDIWk2dnd3B4zRp6SkxFUE+jgwuGHhArfNZiMzM/NkndLfFcJJd4yPj3P48GHy8/OprKyM6hpJRBwTiUMul4uysjIsFsui9iciuLi0WNbkkb4R/v3VXyDXOfC1K1DngkImYMhxI/d6OfqXNFbfMonwWTm+F2FsOhV3ASRpHaCWcXXNmXzRr8kqytaJhroL5fQymUzKKcrKynA6nZK8RjDpKD09PSzjNVLDzV/KJJq1yFLB5/NFRYRYCohr9JSUFIqLiwOkBLq7u5mcnOT+++9namqKoaGhiDnhm2++ydlnh15/f/DBB2zfvp3e3l5KSubnx6K5togXXniBO++8k97eXioqKrjvvvu46KKLpNcFQeC73/0uv/jFL5icnOS0007j5z//ORUVFdI2VquVPXv28NJLL0kTJA8//PBJk71cyFRPlJ/dvHkzGRkZEfclyoItNk82m80cPnyYvLw8pqamEnbd+0/hBk/wx1ML+skfX+OY8w90dBeQ5PGhN7qQA5pMD9MjRmY+UKCptVMwYkbWlIZ1lQllpgedcg69XsPTV3yJLL8m2szMDA0NDaSnpy9IWIH5Zt0zMzOYzWapIZGcnCzVgRLVcBNfP9lIxDWVCJSVlaFWq3E4HNIasq+vj3feeYeXX35ZykMXulf+L8SfFVHgjgUKhQK3201LSwtjY2Ns3bqVtLS0hOxbTHyiHX8YGxujqamJoqIiysvLF7xxQ3XrFpNU/f6553nmnWaU57owyHU4vWpkAijdPjwGGeoxJ63deexSdbMz5Tjt5dm02LPQOdL5xKoi/v3iyxLaCZfL5aSlpZGWlsbq1aulMd7x8XGOHj2KRqMJGGERjy0IAseOHaOvr28eUyFWVkEiEU2XLjiwLyW7O1JxSTz+KQ3u2KHVaqmpqQlZTElkwUkmkzE9Pc3U1NSi4lakArfX66W5uZmpqSl27twZktUvNt3876doMDQ0RHt7Oxmr0vnmfz9LVpqFaU8a+JR4BTkGtQPXlBK9ykGTLZ+aC45Tvy8f4SM1ynIfjjE1GrOX8owM7r/9G3F9fhGiHuixY8fYuHGj9DAPllPq7+8PSLQSJafk33CLZ2ROo9HM0/m1Wq0cP35ckn8S40ewseZK0+CGE8WlaJikkUbx3W43nZ2dzM3NSX978MEHpW2dTie7d+/mZz/7mfS6QqHgT3/6E9dffz21tbUkJSVx5ZVXBjAmS0pK2LdvHzfffDMPP/wwBQUFPPHEE+zevVvaZvv27fzhD3/gW9/6FnfddRclJSU89NBDXHHFFVF/T4tBIidG/PVyQ5nXngwGd3BzX9TPdLlc7Ny5E7VaLV1Xbrc7QPIoWsmmlQL/BnhOTg6HDh1CoVCQlJREe3s7Pp8vgNkUTp4omoabUqkkJyeHvLw8vF4vU1NTASbZ/ia30X6PJ5sdGSvE62ShODs7O0tpaelJPKu/X/g3yaurq2PSAl9s3hRMHBobG0tYrAqeXouXNen1erntwcd5zz7H2Vt6ONhTicY5jccuw+2DqrVm+pKSsM5lMPCUm4LPW1Hf4Ca9fRbftIzq4lXcdNGegHtOjI+CIMRlqKvRaBYkHYlybqKkW6zFJpfLxfT0NBkZGbhcrpNKOhLPZTmLS/7rsGApgfHxcc4//3w++ugjLr/8clJTU3nhhRfYtWtXyH3t2rWL4eHhgL/deeedHDhwgG3btgX8/bXXXqO6ulr6t7/H2HvvvccXvvAF7r33Xi655BKeffZZLr30Uurr6yWZpB/96Ef89Kc/5Ve/+pXkAbB7927a2tqk58MVV1zB8PAw+/fvx+12c/XVV3Pttdcu61RJvPKz4m8UbzPGP3dau3Yt+fn5fPjhhwmNQYmoAx0b7edr3/8NrHdQlC/DNyJDJgPzcBLVa8cpPNfGkSfVtL5axDpVH+nnOdFuc+A8okHhg6su/H/sKg+8Pi0Wi1TX8p/6jfZziVP+olm3OOVfX1+PTBa9WTeEbrhNTExI9TRx4v9kTfkv1pthsfB/VsGJ2oV/vNdqtbz99tv09PSQnZ3NGWecweuvvx7yN/y/EH8+dgVur9fLzMwMgiCElANZDMSLxuv1Luhe72/UtH79+rDaof77FQNjsLlHrEHt+NhBfvv0g9T3FKLbIsdmV+PxKMgw2RhOS0c34sFRpEc+MIuxJYkPJ8vR5zkoSZnEqDFxyxe+REH6wuebCASP8YojLO3t7bhcLmmMd3JykomJCbZv3z6vOBsLqyDRQS7WRGohdndbWxterzfAmTvW6/aUBvfSwmQyhewIJ6rA7XQ66e3txePxcPrppy8qbi1U4HY4HNTX16NQKKitrQ25QBIEAbVazczMDHV1ddIIpslkCnvNi4vd3t5ehr0f8vhLU2iTwTqUhFcrB5+Ay61EYxdIkTnom81AEKyk6VXsvqqTjzoKGO8zkGyS84tb7kITp/a0//kE69r6IxY5pUjMpmhYBWJRMt4FmFz+N53fsrKygM788ePHAxZTaWlpK5LBHe1oXKRR/FBSAVqtlr1797J3796w7ysqKponQRKMs846Sxo3DYdLLrmESy65ZMFtEo1ES5R4vV5aWlok89dQ5rUni8Et/pY2m41Dhw5hMBjYvn27FMfkcrkkgZCcnBxgDvtxhGia6e8F4C8l0NfXJxlIijEonDxRtA03k8kUoBFusVgYHR3lyJEj6PV6KXYsFOOXu3gUCdEUK07JAyQGbreb5uZmZmZm2LFjR8yTFIvJm0ZHR2lqaqKkpISysjIpr09UcUm8hvwbibFe9+9/VM9Tf32BI00pJG9zo1F78PnkCIIcpcJDa2c2ayvNbL1unMZfwXBvBsP/kYExe5b0bAX3/tu3yMxOD9inGAMNBgPr1q1bdAwMJh2Jcm5ms5nu7u6wpKNQ+4ET31dzczNarVbSQU+Ef0ksWO4YtVAOlJmZyb/+679y77330tvbS3NzM2vWrAm7L7VaHVA7cLvd/O///i979uyZ9yxIT08PW2d4+OGHufDCC/nmN78JwN13383+/ft59NFHeeyxxxAEgYceeog77riDT33qUwD8+te/Jjs7mxdffJHLL7+c9vZ2XnnlFT788EOpuPXII49w0UUX8eMf//ikGd36YzHys/61nFgZ/+IEhcViCcidEh2D/OsZsdaBPB4Pj/7Xf3Pwo2OY01NZnWrGhxyfVo5vVmCyR4fdCeuLxpj7jJKhPxto+WMRyldcmHLsbNpQyW1fv3beMUUCU1VVVUJ+8+Ap/2CzbnHKPyMjY8G1g7gOGxsbo62tjTVr1qDT6cKSjsT/TjRiJYQlGgvJtMnlcnbs2MEnP/lJsrKy+PnPf05LS0vY7/T/Qvz5WBW4rVYrR44cQSaTUVNTk/BFkP8iIhzE4Ge1WqXx6Ujw79bFayY57Zzjpy0/Inf4XY4eyMJRnoRebUendTDqyWC1zMnxHTLUr0Byv4e5DD1ejxvlcSfyMTWf2/MFLrhgU9THSyQUCkWAjtns7CxjY2McPXoUt9uNXq9neHhYKrLFM8KSaCmTxY7rhmN3i4vOWNnd0RS4T2lwJx6JKHCLJo86nQ6FQrHoply4RGtycpKGhgYyMjKorq4OeU2J90xycjJnnnmm1HgSWUPiKJl/d10slrX2dXJk+HXGC31M9JVQvGEU87AejduDTe1CJgi89041nzj/MAetJfRMZTCtm6FvzoiQJuf2T3yJzTnhE/5oIZ5PsK7tQkiknFJwscnj8TA+Po5KpcLj8SRkoRfcmRcZmqLumlqtRq1WRyULkihEYniemiBZPBQKBU6nc1H7sNvtNDQ0IJfLF9TLXQo5lGCIsUqUScnPz6eiokJ6fsvlcknyqKCgYMFJuI8DRDPZYPZTKCkBsdjU29srSZ1kZmaSlpYWc8PNnw0mxrqCggI8Ho+0qGxtbZVkm8RGmf+1sZzGTdHgVJN/aSH+9uJ4ul6vD9skj4R4mmf+jPENGzYEaO8nshknfk6r1RqzWWvvxDC3//inzByfIdWYhiNNhc7rBgT0Jjv2Ij2qkVn63ktFrXZTWTxJzldnGTYn455VcsHGczmn+vJ5+xVzxNzcXFavXr0k96Fer2fVqlWsWrVKIh2Nj4/T1taG2+0OmC4JnvqYm5ujvr6elJSUAM+YcHJKsDSSksstoxRNDgQnmvjnnntuTPv+4x//iMVi4eqrr5732j/+4z/icDhYvXo1t956K//4j/8ovVZXV8ctt9wSsP3u3bt58cUXAejp6WFkZITzzjtPet1kMrFjxw7q6uq4/PLLqaurIyUlJYC5ed555yGXyzl48CCf/vSnY/os8UC85v39OVavXh2XqayYf8dakBZ1p+GEZ4v/fZDIAjecuFbi0Uv+xbt/5pUn/4ypUsHkQAbkyUGAdO00siwFLhTo8PL6H1az6+JeatcOMrVOg3lIj0au46sX3EaWqTBgn/6T9Js3b06YKoI//Ek8wWbdop79Qmbdg4ODdHZ2sm7dugDJzWDi41I23JabwR1NM0S8pnJyciKSb/3x9xh/VkSBO9LN7R/wCgoKGBkZWRKGj/9DOxSCg18koxX//S6mW/fblj/y9NiHXOJqBC84JmSgEHB0akn5jAXVqIPOI4Ws3dBPlyYHPpCjNnsRVDJW7czh4TuuQqeN7lyXGjKZDK1Wi9VqRa/XU11dLTGbGhsbAQISrXhGWBIR5BJpJJAIdnekxMrlcuFyuU4VmBIMpVK5KMkAUYesvLwcg8FAR0fHos8p1GJvaGiI1tbWBf0IgrUmFQpFgFnR1NQU4+PjAd311NRUegaO8UbPPppajZz1mWmODmbgccuZnNRjzLcjcymYUqnRdE9jxchf/nc727Z2oUhxM2vXUKBYw60Xfm3RnxtOdJkbGxsRBIHt27fHvfiOR04p1H58Pp9UOFq3bl1ArPffbjGsAv/EsLy8HLvdLkl4fPTRR6hUKqlZlpqauuD00WIQjQZ3Iszu/i9DqVRKi+R4IBaSc3JyImonJnrBFu4YonRGVVWVZJgovtbf38+RI0cSxhhaToyOjtLS0sKaNWvIz1/YtFuj0ZCfn09+fr7UcBsfH6erqwu73R4gJRCuYBsNu1vUjE1LS0Mmk0mN9sHBwXkmt8uprRsNopFQsdlsp5r8i4BoSl1UVERFRUXcOXCszTORHTw9PR1SVi1RckpigTQvL4+WlhaAqEbmvV4vd+z/BR98MITpyATJ5Tqcgwrkepi065iUaVmT1U991WpsNh16i52jr2fTnZyFId3JtspqvnbFVSGv37GxMVpaWigvL2fVqlWL/ozRIBTpyGw2Mzw8TEdHB0lJSWRmZpKRkYFcLqehoYGcnJx5xfdo5JQgccWmlcDgjkamLZ5zfPLJJ9m9e3eAlJjBYOCBBx7gtNNOQy6X8/vf/55LL72UF198USoyjYyMzDNizs7OZmRkRHpd/NtC2wT79CiVStLS0qRtTgb82dPbtm0jNTU17n3FGoNEglA4xngimmxiIzo1NRWz2cz7779PUlKS1NxeiOA3YLHw9Tf34nllAtmIG8NONTgEfDKYGjegyhgms9DK6PZUZB9Mo56T8fZvS1FmeDGavHz5H77A6Vu2zduv6IkiTvudrBpCuCn/jo6OgCn/jIwMRkZG6O3tZdOmTfOK78ExaCkbbv6qAcuBaJv88fyGf4/xZ0UUuBdCcMCTy+UMDQ0tybFETedQQWxqaor6+vq4xmVkMhkej4ehoSEyMzOjfm/34FGe+fARDukN5BmnUU66URt9eOwK9Po5Jo6mox9TU1oxzNEjubS2lpKbbkX+Dx4cXjVf3fppzq/aHPV5ngyITQKtVsuGDRskjcrc3FypyGY2mzl+/Pi8Md5gHVp/JDrILWUiFczunp2djcjujkYeADhV4I4T4QyW4jUr8fl8dHZ2MjQ0xKZNm8jMzMRqtSaEheQ/9i8IAt3d3Rw/flw6TjCikUUSCyEpKSlSd31gYIAn//QnfKY2Rr3JFDLLpFqNAh8ao4eZPh2lZ41x5EAmeemzjJXrEUYmcE9reO+11SiVXv7n7n8lNSUxRnEiMzUpKSkhI7wiIskphWM2uVwu6uvrUavV82QVlpJVoNPpJBfz0tJSid199OhR7HY7KSkpUvxYSGczVkSzuDsVf+KD+BvFy6r2JwGsWbOGwsLCiO9Zaga3z+djZmYGl8vF1q1bMZlMAddQZ2cnw8PDbNmyZVEL2ZWAvr4+uru72bBhQ8wmh/4Nt8rKygApga6uLrRarVRsSk1NDXsPRpJTghOTIYWFhaxatQq32y1NsgwMDOD1enE6najV6gWLfcuFUwzupUV3dzdHjx6dx56OB6JXUjQQ2cFqtTosYzwRzTj/wuvatWsB5jX1U1NTpXtNbNb+8a2P2NuwH1+Bi+SeWXxucLplmNI9aI86mC7XcbSzgHWre9m0posjqQXMjhhRjblJS/Xyw+tupiho8S5CjBvBrMSTCZlMRnJyMsnJyZSUlOByubBYLJJurtfrxWAwYDQa8Xg8MZOOIvmXxIJEEo/iQTRNfkEQIsap9vb2APmSgYEB/vKXv/Db3/42YLuMjIwAduT27dsZGhri/vvvD2BR/j3A4/Fw8OBB5HL5PPZ0PIglv/EnIhUXF4e8xhbbZPOftkpOTmbr1q14PB7pXhMJfmL8EaUTPR4PN/38N4yntTFoSaFg2o7HDnKVF6VSQN3vY7TQwPGpTNal9KHf5GAoJ4PZIRnqOSdr12Xyw6uvD/mZRN8Tt9vN9u3bl833JLjhJpokjoyM0NHRgUwmIzc3V2Llx5IDJbLhJsaf5ZQoiXTsN998k+bmZv7zP/8z7Db/V+LPii5w+4/aigFvdnZ2SRdloYLY8PCw1GEPF/zCwefzodFoKCoqoq+vj/b2dlJSUqSbORTjzWZ3csMDT1C2+hDjej1OpQKlzIcgyNCmuElb7WG2y4omX4vlvzNIu3iS0o3DOMxq5qY1nJZbye1nzR8zWG7YbDbq6+tJS0sLyS7zL7KVl5fjcDikhV5PTw9KpTKAbbEQs3KxQe5kjcL5J5fFxcW43W4mJibmsbtdLteCOoizs7MApxZ3CUY8ZiWiUZDT6WTnzp3Sb5IoFpK42AtmPYUqLsYri9TR28Ndv/4jpuIJMm0yHGoNSocLlSCQmTuLd5WF4405tLXkUXXOMP2HTWTLp/BkqfBh4/PnncGnz/zkoj+riOnpaRoaGsjOzqaysnLJFjnRMpuSk5Pp6urCaDRKzG1/LDWrwOfzoVQqUSgUUnGsoqKCubk5aTrk2LFjUrFKZHcvpikQTZPtVIF7cYjHZNLr9dLW1obZbI6J9bSUJpPipIXb7aawsBCj0SjFUNEE1263U1NT87Fm/QuCQFdXF0NDQ1IRf7HwlxIQp71EiRGPxxPAbAq3II004SYuEtPT06VY19DQgEqlkvLUhUxulwORnsHiwvgUgzs+iCzCRMRwhUKBw+GIuJ04cZKbmyvp1YfCYgrcC5lJBjf1x8fHGR8f58iRI/hkcn799kf0uJQUb5iky56O0W3FqxBwtLmo/KyXsRYF2jYNQ2uM2FsqyM61Up4yhNug4qwLd3PZ5tBeDoIgcOTIEanBF8ojYbmgVqvJzc1FoVAwNjZGUVERcrmc3t7eRZGOwvmXiL9HNIWjlcDgjpQDZWRk8Je//GXBeBlshPvUU0+Rnp4eVdFox44d7N+/X/p3Tk4Oo6OjAduMjo5K8gTi/4+OjpKbmxuwzaZNm6RtxsbGAvYhPntikTlYDJRKJaWlpWRlZSXkN46mwO3z+Thy5AgDAwNhCUIiFhuDQk3wq1QqSUpClCIUJ0mbm5vpn57l+dc7mCtWkm/wIjsOMpcPFHL6jynJ2uDC9dE0U6km2rrzmUhJJiNjguqcXnxZKdx+3k3kpuSGPCeRbKjRaNi2bduSTX7GCnHiXa/XMzs7i8PhYNWqVczMzEhSmmLekp6evqBZNyS24bbSG2wAZWVlnHHGGdx4441ht/m/En9WxBUd6oIJN2qrVCqlh+VSXGj+QUxcvPT19UUMfsHwL6rKZDLKy8sDdIfEcVS9Xh8wnrL3N3/i+be7qawaJSXZxnH3iQXTuNOAokjJxHEtW740yrv35ZHiGcJZko7tbT28ric3Tc/e268hI33lsaFEjbn8/PyodTa1Wi0FBQUUFBTg851wzxWTT6fTOc8RPBTiDXLLFchUKlVIdnd/fz/T09NMTExIGpr+2t1zc3Po9fqPtTnXSoR/gTsaRtvMzAz19fUYjUY2b94ckDQkijEpl8sltoNKpVrQTNJfkiSa69nhdPKV5x5nuG6KgkIvxlQ7rn4lar2XHlcqW6Z7sRpT0OXMUrjGwlB3GvXjxZhy5lCb7BQkp/IfV3wzoYsQi8XC4cOHKS0tDSu/shQIZja53W6JVdDT0yN9p6OjoxHllBLNKgi30NPr9ej1egoKCvB6vUxOTmKxWDhy5Agul2seuztaiOd8qsC9tIjVZHIhzchISMTIbSiIjWwxt/F4PHg8HpRKJQ6Hg8bGRjQaDdu3b19xLOFYIMoTTU1NsX379iVpLoea9jKbzQwNDdHR0YHBYJByoMX6l8hkMjIyMsjLy8PtdmOxWOaZ3Ios8uVYDEfrQ3KqyR8fUlNTFyXH5o9IuY7/xElVVVXAWHQoxFtcCm7wi4XUUNDpdKxatYqCggIe/8PP2Ndkxd6nwbdGjlbtQRDArdWgmrOjtrs5ckxD1cWzHHlDhv0dJbZCDceGc7EbdfzXN7+MLoyEZbCHyEps8A0ODtLR0cH69eslZnkw6ci/gS56B0Qyqlyo4QaRc6DlLnBHkwMlJydTVVUV9T4FQeCpp57ii1/8YlTPQ7EhJKK2tpYDBw5w0003SX/bv38/tbW1AJSUlJCTk8OBAwekgtL09DQHDx7k+uuvl/YxOTnJoUOH2Lp1KwCvv/46Pp+PHTt2RP1ZFgtxkjsRiBSDxCa8w+GgtrY24nNjsTEo0jrMX4owJz+Vrz34n0y53MxiIinNjoAMj0YOGiUofDjfnkP9T16yHQrk9dM4TBpGC42M9yTz+Z1b2PP/zgl7TqLPgr8R9kqC1+ulqakJh8NBTU2NJAccasrfaDQGNGdjzYHEBmg067CVHn/gxHe3atWqBQ1u/fH3HH9WRIHbH4IgcPz4cbq6ukKO2voXnJYiyRYXfR6Ph6amJmZnZ8OyI8NhIdak/zi8OJ4yPj7OXxve5X8a/0pvUx46vR2dwYNa5UXhBJXXx6xSzTF5BqVJw7idcOZdAwy8a2R6YBp1kop/vuYOytesTfj3kQiYzWaampoWpTEnso3S09MRBEEa4xUL3uJiOiMjY0HTxmhZBaJZ3HIGNP8C29TUFKmpqWi12nnsbrVaTXt7e1g5gnvuuYd9+/bR2NiIWq1mcnIy5LGC8Zvf/IbLL/+bIc6bb77JLbfcQmtrK4WFhdxxxx1cddVVAe/Zu3cv999/PyMjI2zcuJFHHnmEmpoa6XWHw8E3vvENnnvuOZxOJ7t37+ZnP/tZwEhsX18f119/PW+88QYGg4Err7ySe++9d0kX1eEeijKZLGpWpahfWVJSQllZ2bx9irFlsc05m82Gw+EgMzMzrM5utEmVP/7rlbd5suMgyd4pXPIU1LIpbC41GcoZkgxzyPJTafvfXEovH2OwMAldihlV3iyyKSVquZLzcmrJS82ju7s74n0YLURX77Vr1wY8VJcDKpUKvV7P1NQUxcXFZGRkSAWgaJlNoRZ68bC7o4lLYlEqPT1daq6KRavu7m60Wm2AFNJCiZOYBEZa3K0kJtrHCf4SJdEWmSYmJmhoaCArKyvA+CtaxMMWj4RgM8mhoSG6uroYGRnBaDQyNTVFTk7OilxUxQKPx8Phw4el0d5o/VgWg4WkBBoaGqQCdSQ94VAxqLe3VyrOiLlPZmam5M8wPT19UmSQFkK0GtynmmzLj4WKSz6fj7a2NsbGxqKeOImnGRdPDvRBawNvt/+Ylz7YSKbRhY0kQMBuV5NqmMOcn0bexBSydPDWzdKZpyX/bCs+lxalkMRXv3A561etDrt/l8slSRHE6yGy1Ojt7aWnpyek2Zw/6cjr9TIxMYHZbKazszOAdJSZmbmg+Xc0Dbfg7cQC43IzuBMt0/b666/T09PDV77ylXmv/epXv5Ik8AD+53/+h1/+8pc88cQT0jZf//rXOfPMM3nggQe4+OKLee655/joo494/PHHgRPPjZtuuokf/OAHVFRUUFJSwp133kleXh6XXnopAFVVVVx44YVcc801PPbYY7jdbm688UYuv/zyk+qNEU4qMh4sVJCenZ2lvr6epKQkamtro1pbyuXyqGWXRPjn9tHGoJ+/9FOOtHTSayvFaBfwqWW4vHKSvB58eTJsqSaShs1gVND/vBPNphlKLgbntJZV+YXc+oWr0WnC33tiPaakpCRmRYKTAbfbLeUz27ZtC8hjQk35izlQb29vwJR/JLNuiI/4uNzxJ9E50N9z/FlRBW6xsy2K3YdaLC91gVuhUGC322lra0Oj0bBz586YkpBYWJNKpZLMzEx+a32Ozpk2xpoL8WkVKAUvDo8SFV5SFDamXSosCi2HZgqYTdOwWjGMe9iDcbOH9Rdt45Mbv71iF4tigaq6ujpho04ymUzSoBVNG8Ug19zcjM/nIy0tTRphCbf4DBfknE4nZrOZlJQUabEXj15TIiEyiEOxu1966SXuvPNO5HI53/zmN7nooos444wzpPvD5XJx2WWXUVtby5NPPhn2GE899RQXXnih9G//+6+np4eLL76Y6667jmeeeYYDBw7wla98hdzcXHbv3g3A888/zy233MJjjz3Gjh07eOihh9i9ezednZ0SC+Tmm29m3759vPDCC5hMJm688UY+85nP8O6770qf8+KLLyYnJ4f33nuP4eFhqbP4wx/+MNFfa1SIho0kTnps3LgxrJaieJ0tpsAtMmvkcjlr166Nykwy0rGOjQyz59YnmDhdgQ4lnkkQZDK8ghzcCky5duZGVRSWjNPhy2X0V0Y2bRxEne0mBzin5p/ZselsaaRofHxcug/FZGMhhnMoCIJAT08Px48fXzJX71ghMsnLysooKioCkIwfw8kpRcNsiodVEGuiJZPJJHa3qDUuSiF1dnbicrkko9v09PR5i1P/8e5wmJubi8jEO4WFEQ2DWxAE+vv76ezspLKyksLCwrjiSaIZ3P39/XR0dLBmzRpyc3Px+XzS+G1PTw/Hjh1Do9EwNDTE3NxcgEyb0+dgzjuLRq5Fr1jZBUqn00l9ff2yj/aKUgLidy0ym0Q9YbHhlpmZSVJSUshrRIyz/f39bNu2DYPBELLhJmrwlpWV4XQ6pUZZomWQFkKkxZ3X68Vut58qcK8AhMuZnE4nDQ0N+Hw+amtrFyyCBu9PfCZGE+tiLW7POZ3c8cSjJJs6mOhJxanWolBMInMJ4JYz7dORL0zRUqVj1FVI5sAo8nQXCqeT8XoF5521ln/6zKcWlCgStcaTk5MT6iGSKIh57PDwMFu3bl1QEhFO/CZibieSjsbHxxkbG4uZdCTuDxb2L1kqSa1oIJ5PJA3uWCdInnzySXbt2hWWcXn33Xdz/PhxlEola9as4fnnn+f//b//J72+a9cunn32We644w6+/e1vU1FRwYsvvsi6deukbW699VZsNhvXXnstk5OTnH766bzyyisBE1/PPPMMN954I+eeey5yuZzPfvaz/PSnP43ps6wkhItBY2NjNDU1sWrVqpiMdGNhcC8kixQOh4908+BvfsmO045wZGQjGqMXHzKULnBMapjTqSkymendlEWWXIZhYgKFxofQ78A8p+XfvvL/2FBdjVYTfopPXD+uBMJQKIgTiTqdjvXr10eMkVqtNsCsW2y4+Zt1B3sqhEK0xEe3272sxMdopFJjLXD/PccfmZCodtkiIAiC5GCrVCrZtGnTgoyYv/zlL3ziE59YktGut956C7fbTV5eXswso1iTqjePvM7vx37PtFJBSpeT9j8VY081IPPMkV89RW1JLz6tQI8zDbNSz6Rai1suQ0BOqlzLT7ZfQ4EhfbEfeUkgMvF7enrYsGED6ekn5zwFQWBmZobx8XHMZjPT09PSCEtGRgZGo3HB38XlcnHo0CG0Wi3r1q2TGhb+t0kwq+Bk4MMPP6SoqChs8fS5557jrrvu4vzzz+ftt9+mpaVl3j309NNPc9NNN4VlcP/hD3+QOmrBuO2229i3b5/kPA9w+eWXMzk5ySuvvAKc0Gbavn07jz76KHDiQVFYWMiePXu4/fbbmZqaIjMzk2effVYKkB0dHVRVVVFXV8fOnTt5+eWXueSSSxgaGpJY3Y899hi33XYb4+PjS8Z48Xg8YYs9b731FuvXrw9ZZBVNOmw2G1u2bFnwweLxeHjttdc499xzYx7NFzUb+/v7qayspKOjg/PPP3/eNv5J1ULjuHDi9/nB73/MB89PY92YjKrAh3pGgXJ6FscRHRkbfRhcdoQCF6vlo4yMGfFlgc2hxe1SUlNSzo0XXB2WQS4WXMbHxyV2r5hsLLQI8Pl8dHR0YDab2bx584rQVB0dHaWlpYWqqqqIHWV/OSWz2Ry1nFKo/fizCvxjUFtbG+np6VGZCUaCuDgVi1aTk5PzjG5dLhfvvfceZ599dthr6oorruD000/n1ltvXfQ5/V+Ey+WSRvfOO++8kNv4sx9DOcrHgt7eXiYmJiR2Rrzw+QINdU0mU8AC4OjRo/T397N+/XoyMjICZNrMVjOzJgs24wRyrYwkjYFCXRnrk7eili89KzpWiPIrqampcbHmTxbEhtv4+DhWqxW1Wh3AbBILhv4FreBnVyg5JX+pB3HBL5rcWiyWiI2yxeDo0aO43e6wC7GpqSkKCwuxWCwroiH6cYPP54uZoRgOIyMjHDt2jF27dkl/E2UKU1NTYy7wulwuXn/9dc4///yI74u1wf/Yi3t57aMhkmVeas48xvuvFHNEV0B58hCjjanM5KshWyAnewKjYY4RmYHpKT2qSQ+ZRjn3nvM5XDMnYhr8TctcNIkDmJycpLGxkby8vJiKaicL4nNlcnKSLVu2LHpt7U86MpvNUZOOQp2X+L/JyUmam5vZuHEjSUlJcfuXxAu3283bb78dQB4Kxt69e3nvvff44x//eFLO6e8Nbrc7YU2MQ4cOkZmZKU2NC4LAsWPHOHbsGOvWrYu5wNvT08PU1JQksxAO/s9MiLwOm56d5c5H76XP7SNb6WbnGUd45rlanAYtuQYzltZUbJUq1NkOCk0TeHQ+hjxG3GYFWpebM1YXc/WaMzCbzUxOTkqyZZmZmVK9QxAEKQ/buHHjinw+RvJoi2d/YvyZmJhAp9NJOdBCZt3BENdhXq+XY8eOSdfAchAf+/r6mJqaYv369WG32bVrF9///vf5zGc+c1LOaSVjRTC4Z2dnqauri2g0IiJRWrbB6O/vx263U1BQILlsR4tYkiqbzckv9t3PAaWLLWWTTM5loFIIoAaF24fTpMXZa+MjdTHbC3qo1I6R5jIw61Dj9apYr9lCzaodqOe8eLSeFWMOIEIsxo2MjETFBEgkZDIZRqNRYhu5XC4pyPX19SGXywPGeP2/O4fDwaFDhzAajVRXVwdchwuxCk5GkIvEXlIoFOTm5vLLX/4y7mPccMMNfOUrX6G0tJTrrruOq6++WrqO6+rq5hVddu/eLekuiY2Bb33rW9Lrcrmc8847j7q6OuBEwuF2uwP2s2bNGlatWiUVuOvq6li/fn2AZMnu3bu5/vrraW1tXXQxJh6Eizezs7NSt7m2tjZi0Vq8PqLV8xYhjsPbbDZ27twZkskSi9YkgMVWz2OvPMlHY5kwCp5MGSoE7DYNGQUzuA/PMDCQxeo8D4oBGUcyc8gomEJl92GUy/naF24hJ4x5iXh8/1GyYO8BnU4nFbv92T2i9prdbmf79u0JLZDEi8HBQTo7OwP0KBfCUsspzc3NMTs7S1ZWFi6XS4o/8cYg/4kY0dhOZHe3t7fj8XhITk5GJpPhdDrD6jzbbLZT+reLhCgbEoqpKLJbBEGIif0YDolgcLvdbg4fPozdbmfnzp1oNBopBxI1qqenp9m+fbtUQPWXaWudauADSxs+B3jHfUzJZxjSDWJNsnB23idXVG4jFqkKCgpCSlCtJEQjJeDxeKQ4G6qgFe0Yr9FonDcy7B/n/Rtli8mRojF4A04xuFcAgg1sh4aGaG1tpaysjJKSkpjvHf/nYLhrIFbWZKe5nQf/+J9MN+pxZciR2ZTI5T7SdDbkgpexqTRMa2YQ2ozYBCXDrnSsyQYMGidZXhffvOhznF5RKe1PbPb4m8SlpaWh0WgYGRmhoqIibonGpYS/3m2i5JaUSiXZ2dkBEkdms5n+/v4A3dxIpCMxB5qYmKClpYXy8nKpgXqy12Hi9RwpBp3KgeJHIp+p/us20dh6cnKSmpqauMygo5kg8Cc5RnMt/uqjvbS8/REDE8XoU2aRKWXINV50bhezCj1KhYDS4EJ7TIbDq6F7KgtTih0jXjI0RvZedQ1J2hN5YHFxseQTND4+Tn19vVTvsNvtzM3NBeRhKwnxeLRFQvCUvzhd3NLSgtfrlTxFMjIyFox5Ylw5evQoZrOZTZs2Sc+3eIwqF4NIOZC43lyJv/FyYEWsHpKSktiwYUPUJo6J1o4UGYPDw8MkJydHpQknItak6sCfGnj+Ly+TursPuTwDhdyHTCFDlexGkeZENajEq9ExrEwhq32ad2dKSU11oJF5yDWWcdOnr2NuziYtIBwOhzSGkZmZGZPJ1FIg2HhpuQ1U1Go1eXl55OXlSSwAs9ksJaApKSlkZGSQnJxMW1sbaWlpIaUfgotN8ejmLgaR9CdnZ2cXFdTuuusuzjnnHPR6Pa+++ipf/epXmZ2d5Wtf+xpwgpHjX3QGyM7OZnp6GrvdzsTEBF6vN+Q2HR0d0j7UavU86aHs7GxGRkYWPI742lJhoXs2VIFbHHMrLCxk9erVUT2QxdgQC0NBHGvVaDRSEd1utweM68Yii3TcMsQrx37AyIwNx6Qer0uBzOMBDziS5CjkAm6vBvUOF7IPxzlmT0WXKZA+5GB4wMDFO07nnz55dtTnLyLYeyCUlElqaioDAwMolcoVY0An6lHGy5ZNtJySw+GgqakpYPEYi0lTNBClszIzMxEEAZvNxtDQEFNTU9TV1aHX66Wilclkko5zSv928RALusHxfmJigsbGRtLT06murk7IeHtwESpWiLFJq9VSU1Mj7U8ul0tas3K5nJqampCTN26fm17nEUz6FFJMJ5pBDocTq81Ml7UN51EfeabCFZHbjI2N0dLSQkVFRUKmJk4mgqUEZmdnaW1txWazIQgCjY2Ni2q4+ccflUpFXl4e+fn5eL1eaYrH3zNEJBfEWkjzer0Lvsdms6HRaFZUU+T/KsScyX/ybNOmTVGv8YLhf92FQiysSZ/Px74Pn+Gvw++RPTXNkLoan28OhczH9LSOitNHaHsxj+l0AxqPh/T1Eyj7DHgsSnw62LRhNfdcf/m8/crlfzOJW716NXNzcxw5coShoSHgRKPc5XJFNIQ9mRCN9oB5ereJgkwmw2QyYTKZAiSOxsfHI5KO4G/ScKtXrw6QQDvZ6zBRHmBh8tqpHGilQIxBdrudhoYGFAoFtbW1cTdwIuVLsUzwT02N8LOPHuFwj0BGvwa51odMLmduWonHoaIyf4SJWQO90zkUlozinnEy06fDo1CgMGm4+YpPcu7W6nn7ValUAbJlZrOZjo4OXC4XMpmMrq4uid293LUiEeL9XVpaSnFx8ZIcI9ise2ZmBrPZzODgIG1tbSQnJ89jvYsQBIH29nYsFgvbtm0LqGmdbOLjKR+S2LAiMkG5XB5T4pNIBrf4gHc6ndTW1tLW1haTzlK0rMnDrcf46c3/xZBMy6az+5lGi8urRCt34/LImZPLyV9voW9OiXYc3EYNFn06Qp+HseMyfvqNy1hXng+ARqOWkiib7USxe3R0lM7OTgwGg8SMjCTHkWiIxpwul+ukGS/FArlcTlpaGmlpaaxevRq73S59d11dXSgUChQKBRaLZUEtyeCFHrDkQS64c/fd736XBx98cN52/r93e3t71E66d955p/Tfmzdvxmazcf/990sF7v/LUCqV0m+62DG3WFiTVquVhoaGeZMt/teeuL9okqpvP3U33uJezitu5VD3aaRjR1CAwutF3Q/OdAW6DBvW0WSMqXPodjvQjE4hOKG4ooR7Pn9VQh7WwcnG9PQ0Q0NDdHR0IAgCKSkpDA4OStqxywFBEOju7mZwcDChUyjBzCZRTikaZtPs7CyHDh0iLy8vgOUQjUlTvL+bTCbDYDCQlZXF+Pg4NTU1Eru7tbUVr9dLWloahw8fxmq1RkysrFYre/bs4aWXXpJ01h5++OEF35coY9pIJrler5fvfe97/Pd//zcjIyPk5eVx1VVXcccdd5yU56hoaCuei/jforZ1RUUFRUVFCTuXxTC4xdgkjtyLjRa5XC5NtojN4nDXnsM3h8NrR6c4sWCQyWTodFrytPmMuWRUFa1BMaVZ9txmYGCAI0eOsG7duqgmOFYyxFFlQRA4/fTTkcvlWK3WgIabP7MpnCRYJN1cMS9KSUmRGoOiDNLw8DCdnZ0kJSVJjTKj0RgxRkXT5A+nNX4KkZFo9qTH46G+vl6aPFvMotv/WReMWFiTf3j7Zbo7X2C0ALrNhezyjuHxKNAq3ch0Xjo7cjntjE7OrOng3Q9XYzEmMe7SY8xwUGiU89CNX8WYFJm0IwiCNE5eU1ODXq+XiroNDQ1SUVf06FiOpow4EaTVatmwYcNJ0wTXaDQLko785dxsNpskDReca8frXxIvotG/XSzR6BQSB4VCgc1mo66uLm4jbn8spMEdbXHb5Xbx41/fj8bYgTdZicKXiXNOic+gYNKpItcl0N+XwboL+7H9Xk2nLZc+WSYKwYexYI5LNqzma5+LTnrC6XTS3d1NcnIy69evx+l0Mj4+zsjIyLLXikTEIv2YKPhP+ZeWlgZM+dfX1weYdaemptLV1SURNoObAieb+LgUGtx/z1gRBe5YkagCt7+T7s6dO1EqlVHvO1rW5OjUEDf86Al4fQaX1Yt3rRGt2oVDIeCc1eL0qkhVzmHNMJLJDFVn9dN3NB3XqAa5V2D3Geu58fLPhj0PkR0YPJ4idsZF9tNCRmeJgMvlkjTUl9N4KRbodDpSU1Pp6elh1apVpKamSmP5LpcrYKEXrtsZqui4FEEuOLDt2bOHK664Qvr3E088QV9fHw888ID0t9LS0piPI2LHjh3cfffdOJ1ONBoNOTk5jI6OBmwzOjqK0WhEp9NJzYFQ24jmojk5ObhcLiYnJwNY3MHbfPDBB/P2Ib62HBBjgsfjobm5menpaXbs2BFX0TNa1uTAwADt7e1UVlbOG2sV72OPxxPAmgwXg15uPsS+v/ya2Sw16zNm0Mg8OD0KctWzNNrkeDerMNXNYUlLwlagRrnKhsOmYG7aSGqahvs+9WmqcvJj/qzRQDzn0dFRieEtLgS7u7sl3bTMzMxFj7hHC/+O/fbt25esyB6LnJJarebw4cMUFhZSWloa8FtHKjYlYqEnFlxDGd2Oj4/zn//5n3R1dXHrrbdy6NAhvvjFL4Zsrl1xxRUMDw+zf/9+3G43V199Nddeey3PPvts2GMnwpg2GpPc++67j5///Of86le/orq6mo8++oirr74ak8l00hp94u/j8ZyQHmtvb2dkZIQtW7Yk3MciXga3f2wSmbpic18cAS0pKaG4uHjBRZNGrkWj0OL0OdAq/ia34vDZUck0pBnSSU3NCJnbiKzkpcxt/HUrt2zZEtL0/OMEr9dLY2MjXq83gK0ZTkqgra0toOEmyhSFQrhik38OpNFoKCgoYNWqVbjdbiYnJ7FYLDQ3NyMIAmlpaVLBO1RhPdLi7pQ8wMqBy+XC7XZLckqLZQaLzb/gtVm0haWhiRFu/+NPSRmcZfPmCaaEFNyCErkelNNuNOkKRtRKcqe9fFRXwZp1A1z2Tx8yfCQZ26yeS865lJ3rLo7qXEU5BJvNRk1NjSQlJRru+hd1l2sKN9F6t/EimHQkyrmJ340gCFI8WMjYLVo5JXHbeNZhkeQB4EQT7+PeBF1OJLLIarPZsFqtVFVVxW3E7Y9QBW7/CcpIMei591/iz4deoxQH7lwVGpmXOa+aEu0Ag9OrMKTN4DJBd30uHq+czbv72ejqY6QrBaU2iRs//31MydHlgNPT0zQ0NJCVlUVlZSVyuRylUinVilwu17wpipNVKxLR399PV1dXTOoNS4HgKX9x6uzYsWPYbDbkcrk0fbuQyXGoHMjfvyRR67CFiKPixO2pAvcJrJgqpDhqHw0SUeAeHx/n8OHD85x0F+rSiYg2qfruhz/g4H5I6bTjsnoRlEpQwNRQMhkbLRi9Dg4OlPOJVR0M242MpyeD0Ut2moUiUwnf3PFvKBXR/0TB4ynBuoviKHxmZmZC2dV2u13Srl63bt2yJUuxYmpqivr6eoqLiykpKQEIKNyYzWaGh4fp6OggKSlJWlAvNF64FKwCMVD6P3TERacInU4nMX0TgcbGRlJTU6XrpLa2lj//+c8B2+zfv5/a2lrgxENi69atHDhwQDKq9Pl8HDhwgBtvvBGArVu3olKpOHDgAJ/97ImmTWdnJ319fdJ+amtrueeeexgbG5MSxf3792M0GmPWxY8FkSRK7HY777//Pmq1mtra2rjNLiOxJgVBoKOjg6GhobBFLfFc3W63dL2FOn/rzDRf/PXPcAx42V7uRmbyIlMIaOVeDAYnPpRkTE1jWZeMbNZBxouT2Et1uPMU4PHwz7Vb+NfPnT9vv4mEKFNSVlZGUVERAHq9PqyUSXp6usQ6WIpxWp/PJy1OQ3XslxLh5JRER3CxkTQ3N4der486BiWi4RZqcSeTyUhOTiY5OZm//vWvlJWV8cUvfpGjR49y7NixebGovb2dV155hQ8//JBt27YB8Mgjj3DRRRfx4x//OCSDY2pqiieffJJnn32Wc845B4CnnnqKqqoq3n//fXbu3Mmrr75KW1sbr732GtnZ2WzatIm7776b2267je9973uo1Woee+wxSkpKpAZgVVUV77zzDg8++KBU4H7vvff41Kc+xcUXnyhkFBcX85vf/GZew20pIRZy7HY7TU1N+Hw+du3atSRa9LEyuAVBoLOzk8HBQTZv3kxKSkpAcfv48eMcO3aM6urqeTJToaCWayjRrebw9AfIZXL0iiScPidTbisl+kpSlH+LfaFym/HxcWn81j8uJCK38fl8tLe3Y7VaV6xuZSwQJxVlMhlbtmwJSUAIJSUgFpt6e3sDpE5CSQmIiKbhJpPJSEtLk3KY2dlZLBaL1DwxGo1SsVssrEejwX2Kwb38ENdWAFu2bEnYeiB4bRbNOkwQBH7wP//B4ZFptEo7SVofGq0Lm0NNTtoUfZZsSjXH6BxfQ0qmlZEkOWl2OQ1/LUKm91FaWMTde26I+poSpZlkMhk1NTUhc5Tgom7wFG5SUpK0TlsKZuX09DT19fUr0vBSr9ezatUqlEolExMTUjGutbUVj8cjxYyFSEewcMPNX8pGvG6iWYdFU+A+1WRbfoiSsxMTE6SnpydM9z5U/Al1LQWja6CXn7/1CP1OBUkWJXlrJun3GtApfMyiw7TaSdJHU7iSUvAJ05DqYrg7lcGuNOQ6GZeffxHnbftE1OcprpdKS0vDTvyp1eqoakWR7rN4IAgCPT09HD9+fMURB0SZKaPRyOzsLAC5ublMTk5y/Phx1Gq19L1EmvKHxDfcIsWgubk5BEH42OericKKKXDHgsUUuAVBoLe3l+7ubqqrq+ctqiMVuP0fkOECWn1nJ3uP/AKdag71cC7YQEBAPudA5vVxbCCLouFRqrKG6ZjIZX/XeorTx8jQ2BBkaq7ZdjPVmYsrVMrlfzM680+iRCmA5ORkKYkyGAxxJzkzMzPU19eTnZ1NZWXlikqWFoKoaSo+BPzhX7gpKSmR2GNms1nSq/Nnd4crtCUqyEVjbrLQaFxfXx9Wq5W+vj6JxQVQXl6OwWDgpZdeYnR0lJ07d6LVatm/fz8//OEP+bd/+zdpH9dddx2PPvoot956K1/60pd4/fXX+e1vf8u+ffukbW655RauvPJKtm3bRk1NDQ899BA2m42rr74aAJPJxJe//GVuueUW0tLSMBqN7Nmzh9raWnbu3AnABRdcwNq1a/mXf/kXfvSjHzEyMsIdd9zBDTfcsGySN263W2IYi93weLFQ7Ao2bAuVKIvXjlar5f333ycjI4OsrKx5BYc/tP03j77TgzDnRGFNwutT4PXKsPtUWF0Gakq7ef3wOk7LHaJhNJOBXSaE7TJ0FhflaSZ+9vWbUMiXtosvjv6HK4iFkjIZHx+nt7eX1tZWST8/UVImopmnx+Nh27ZtcTcxEgFxESyTyRgcHKSkpASNRiMZWGk0moAxumjllOJlFUSzuHM4HFx66aVs3Lgx5Ot1dXWkpKRIxW2A8847D7lczsGDB/n0pz897z2JMqaNZJILJ9zHH3/8cY4cOcLq1as5fPgw77zzDj/5yU8W/NyJgvjslMlkki7yunXrloxNEwuDW7w35ubm2LFjB1qtVsqBBEGgra1N0iiMZbKl0rABj+Cmd+4IVpcZlVxNmb6KTcYdCzZwxNymsrJSakYPDg5KxVExt4mn4ClKrTmdzpPe5FoKuFwuycchFikCjUZDfn4++fn5UsNNnKwJlhJYKP5Gw+7W6XSsWrWK4uJiyafAYrHQ39+PTCYjPT0dh8Ox4PmeKi4tDovN3f3XVpWVlbS1tSXozE5AXJv5syZFWaRQ5/6nhn385vXXyMrxgVaDbBZ8ggKD3MW43UC11swb3nJO29ZOVUMHR/uLkKXKmcZNikHGvdffRFZa9H5MNpuNhoYGyaQ+2vss1BSuOC7vL2WSnp6+6GeB1Wrl8OHD0oTNSoSYF27atEkieIQjHYnFpkikI4gspxQpB4pW/zY5OTnuz34Ki4PYYHK73RQVFUV8ZsQCf0JAsDxtqOvF4/Fw929+yKjTjFUwIk+zI+uR4xPk5GsmafdlUJUzwrsDVZy+rpXW9mLG1Zmok91M4WJrVRm3X/mlmM5RvHfWrl0b9cRzuFqReJ+JUiaZmZkLTnFFA5EkMTo6yrZt21bkveI/6ebvBeX1eiU5N3HK37/hthAJZSHiYywNt0gx6JTRdiA+lgVupVIZV4Hb5zthgGg2m8M66YYrQEVjJul0u9lzzy+xGkdQ17iYO56M0uMDOch0KuQ2FwrzDHPZJt77y1rWbe9lZ9lRJrw6nGM61qdu5epz/jXhRWJRR9VgMFBSUiKNwovFIpVKFTDuG20BT0yWiouLI44jrySEMy0JB3/2mCAI0gjL8ePHaW1txWQySUFuoWZBvKwC8ZqLFNjCjfl85zvf4Ve/+pX0782bNwPwxhtvcNZZZ6FSqdi7dy8333wzgiBQXl7OT37yE6655hrpPSUlJezbt4+bb76Zhx9+mIKCAp544gmJ/Qjw+c9/nvHxcb7zne8wMjLCpk2beOWVVwIKTw8++KCkveuvpytCoVDwpz/9ieuvv57a2lqSkpK48sorueuuu8J+9qWCuGCzWCzSKOdiEa6oJI6M6nQ6du7cGbJp4v9Q3LVrl6TfLGoXpqWlMeR28tro75izOHDP5aJKkiG4ZSRr7XQMFpBTPEGnLIOtpn7YAAePlmPM8LDTN4hareezl19HeU5ipgDCwX/0f/PmzVGZ+vqzC8vLy7Hb7VIMO3r0KFqtdlFSJv4SS1u3bl0REktWq5XGxsaAOFVYWBg20YrEuFhMwy1SYhXNaNzIyMi88V2lUklaWlpYA9lEGdNGMsnV6XTcfvvtTE9Ps2bNGikPuOeeewKkoJYaAwMDuN1uCgoKqK6uXtJnarQMbn+j2x07dkiFJrlcjtvtpqmpCY/HQ01NTczFYKVMyUbjDiqSqpn1zKBVaDEqoy8qBTejRdbx+Pg4x44dkxg3mZmZpKamRowLYhxQKBRLZrp2MuFwOKivr8dgMCxqus6fdVpZWTlPSkCr1QYwm6KREljIv0Rs3Io+BRaLBafTSUdHByMjI9KC3L+BcUr/dvng9XppbW3FYrFQU1NDUlKSZCyaSAa3f74MoX2PhgbMfHPfQ+hHJ0nOkzPt1SGT+XDq5FiPa5ib07JZO0wXaZxZeIxD42Vo1rmo8PYj9wqsW386Xzz76pjObWJigsOHD5Ofnx/gjxErgidVxKZSV1eXlOPFaxK3HHq3sUKcAgrOC4PjvCixECvpCKJruPlvJ15j0erfnmqyxY/F5Dsi2c5oNLJlyxYGBwelgl8iID6zopkceeq5fXwgfxlrr5rSCi+DFiUGuQyZxkvfcAa1OW00mPPJTZ5CVSjwxvAmCrZZqHJ2I1MrueHTd1KUHb2Ztb9nULRrqlBYqFZ0/PhxlEpl3NJwPp+PlpYWZmZmAqSbVhI8Hg8NDQ0hJ90UCoWUS4rrHbPZLGmai1P+YsMtVjmlaBpu0ci0KZXKFed/t1xY/lX8/4+llihxOp00NDRImnALFQFC6SxFMpP85Z9f5XevfYhe7UVV4EFQyFCrPEypVGi1c8hSVAizSlTHxpE5PUxmJvP262sx1nlZvdrE167eTclJ6qgHj8L7F0vcbnfAuG84FqOYLK1Zs4b8/KXR510KjI2N0dzczNq1a2M2CIQTv31KSgopKSmUl5fjcDikhV5PT0/UD4BYgpzL5ZL+Oxzm5ubCJlZPP/00Tz/9dNj3XnjhhVx44YURP/tZZ51FQ0PDgtvceOONkiRJKGi1Wvbu3cvevXvDblNUVDRPDmWpEfzd+i/Y8vLyltTYzWKx0NjYSH5+ftgpiFBJlXgdVlRUMGQe4rsvP86M00X52lEGegqQCcCcgMwoIPN6ULtkDHSlQ4XABxRTkDzBP275kAmbkV35N1OUunvecRONRI3+63Q6SbN7sVImYhEoKSmJ9evXrwiJJbPZTFNTE2vWrJm3GA1OtJZCTim4iCDK4YSCv+FteXl5yG3a29vj+h5OJn7729/yzDPP8Oyzz1JdXU1jYyM33XQTeXl5XHnllUt+/K6uLnp6etDr9WRmZi55wzgaBvfExAQNDQ3k5OSwevXqADPJubk5GhoaSE5OZvPmzYtiF+oVBvSKxRcn/VnHYiNI1AWPFBfEQr7JZKK6unpFxIHFQJSOS01NZe3atQm9nkQpgVWrVuH1eqViUyxSAuL3G0lOKSkpieTkZMbGxigtLZWO19PTg0qlIj09HUEQsFgs6PWRDQBF7Nu3j7vuuoumpia0Wi1nnnkmL774ovR6IoxrAfbu3cv999/PyMgIGzdu5JFHHqGmpkZ6PRoT3ZOFWNZhIkSzQplMJq2txH14vd6ENYnkcjkejyeACBKMb9zxM474himtNTM6oCdD5kGQefDMqfEVKhH6XTR1FLO5+hjJCgfN9hwq8wZJkvnITa3kys3/FnNze3R0lNbWVioqKigsjL4oFQnBTSWRWRmPSZzI7FxuvduF0NPTQ29vL1u2bAlJPvOHv8SCP+lInO6LhXQE0fmXuN3uqBjcp5psJx8jIyM0NzdTUlJCWVlZWM3+xUCsDYk5cqji9vjEBP961UN4dgsUubx49aBUCig0MpgRmMxRwFEtPQN5XJjbSbsrC6fWy/aSXrQKFdtLL+Pcsk/GdF5i4Xh6ejrhnkHBtaJQ0nDiWmOhoqo4Fedyudi+ffuyTseGg9vtpr6+HpVKxcaNGxe81/0bAeLkjZgDHT58WPIOECdvFvq8sTTcPB5PxAK3Xq//2OeuicKKKXDHglgDl6g5lpqaGnHkV2QliYjk0P3hsXf46TMvY5FrcY0pSFkLyEAQZGRlTtKdmUvynBKVy4s7NwmZ1Yl8bBrl+DT567I57x/WccYFpwXoKZ9MiCNwGRkZ0rjv+Ph4gMlQ8LjvSjEHiBUjIyO0trayfv36hBmBaLVaCgoKKCgoCHgAiFpW/mO8Cy2+Fgpy09PTKJXKAM1l8T0iTo3GJQ52u11yut+1axeDg4PMzMwkZN/BRaW+vj46OzupqqoKO00QiTHw/Rd/y7DzLY4NrmLdujEEQY5MEPAmqZB32lCuc/L2u2Wce04XzcOrOGxNJjdvkn5lJmq3kW/vvgOTbumvnaUa/Y8kZWIymaQYFqxdLTLn09PTqaqqWhFTKGITrrq6OuKYYSg5pXiYTQuxu71eLzMzM9KzUXwOiu/Zs2cPu3fv5sILL+TQoUMh41xpaSk5OTmMjY0F/F1sToT7nIkypo1kkgvwzW9+k9tvv53LL78cgPXr13P8+HHuvffek1Lgzs7OJicnh+bmZmlhvZQQm23hjHMGBwdpa2uTJgj8Gx5Wq5WmpiYKCgoWxVhcSgQ3gkQDRXHyyl/iSGTurERd2nhgs9k4dOiQZDK1lJ9HoVDMM541m82SHJ7BYAhgNsXTcHM4HLjdbtRqNcnJyZJZn8ju/vGPf8zzzz9PRkYGDz30EBdddBGrV68Oe86///3vueaaa/jhD3/IOeecg8fjoaWlRXo9Uca1zz//PLfccguPPfYYO3bs4KGHHmL37t10dnZKOWgkE92VjMnJSRoaGsjIyAhoCgVPHy4WYkGpv78fr9c7b73UbWnj208/w+xBOfJLleiUbvDImHUpyNG76JOZSLVNYFmrRuiAv36whuz0GVZpbGgUaVz1mW9jTI5tLSMIgsQ4Xr9+/ZKvhUJJmUQyifPXu10Ms3MpIU70DQwMxCVbsBDpSJziEYtNkVinwTHIv9k2NTWFXC7H5XKFlJQUWZ2nGNwnDyJzube3lw0bNgQ0BRNZ4BZzJJfLRXd3N1lZWfOk2H7T+t88d08bvnwFSSYP9ANKGQ6XggyVjZFJLboiFw6nnaa2XAaG0khLnWEVdqqLT+Oic78S83Na9Nbw+XzU1NQsaeE4WBouWtlb/+nYbdu2rYjp2GC4XC4OHTqETqdjw4b/j73vDo+qzL8/d/qk955AEhJSSE8oimKXTlh00VWxszZs2NDFsq6FZXXtZV3rd0VXiiBFECGICiqkd0gnZVqSmWT6zL339we/9+5MmCQzySSZYM7z8OyaTCbvTOa+9/Oez+eck+kyQSwUCrkQYUcqfxLWPZwl8FANN5PJBKPRaDdwNJCTnFKx2cPzPmlOwJWNi3T2EhMTER8fP+wGwufzOd+moYgli8WKJ3b/FT01Omh0QeAHWQErHwwD6DReiKR70OclwszkTpw2RyFM0A+RrwkIFYEWS5CcMx1Xz0tBdna2xxCTtmRJQkLCOXJfsVgMoVAIrVaLnJwcBAUFTfSSnUZHRwfq6+uRlZU1Zs0E2xsAy7KcjFepVOLUqVPw8vLiDnpD2SjYbnLd3d04ffo0kpOTOb9TR765U4WVe0BsIcLCwpCWlgYej+fWQok8FwlC6erqQl5ensNraThbpAO//oSPj++FMVQAX703QFHgCxhYhRRCRGp0WYNBRQhh6rRAlEvh4A8pSIhRIlpshPkMH5dnrsKSi6845/eOBYiCRigUoqCgYMyKnIFWJkajEUql0s67mhRhPB6Pm5z3FJJutE244QotV+2UiE2PRqNBdnY2gP8d/MjjAgMDER4eDj6fP+Tkw7x586BWq1FcXIy8vDwAwOHDh8EwDObMmePwZ9wVTDtcSC5wdoJ34J7sik/1aOHv7w+r1TpiCzZXYUuC2H4OWJbFqVOnOAuhgIAAu7/3mTNncOrUKY+Wug/EwABFW4ujhoYGsCyLwMDASdWwHwxEqh0dHc1Ns40XhrISIFO+tkGVzjTcjEYjKisrudA923uij48P/Pz88O6770IoFKKurg779+/H3r17cfDgQYfPbbVa8cADD2Dz5s24/fbbua/bhli7K7iWWL2RHJL33nsPe/fuxUcffYQnnnjCqRBdTwUJBE1KSnIYZuauuon8vVNTUyGTyXD69GlUVVUhODgYUn8vHOj9ElUqFczFvkAowPIARsyDsJtFX4QAMTwzpvtq0NLjD1+pFtosCro+K/r7pVgw4yrceuU1I1qTrZesK7kD7sBgVia2IXEhISFcU89T/W7JvYa8j+4gZ2yHjmiaPidAjwwdhYaGOuWbS2ogtVqN7OzsYc9hnvg+n4+wWq2orKxEX18f5s6de8777q7ajSgapVIp0tLSoFQqUVxcDKFQiNDQUMh4Svzc8wV+q/AF3SEGYvmgaQaiaAsE9RTkEgGmh2qhswZD2yYCL5CFOpyGScVCbQjGk39ch+nhrgdhkkEsLy8vZGRkjFlWiyM4a3vr5+eHlpYWziJtPNfoLEwmE4qLi0dt40bgqOFGaqCWlhZO5R8SEoKgoKAhz8JkDzKbzaiqqkJQUBDHLzmyU5rigezhMQS3K0U4n8+HyWQa8jG2nb2srCynyQLbIJPByO0jvx3Dpl8OoSC2CTL1dLASHiBgAAEPfW0UBIl8GJul4M8wQTjdgILgU2g9E45etQ+kEjNuTZ2HMEkgcnJyPNorx1bua7FYUFlZid7eXvD5fJSXlzstwZhotLW1oaGhAdnZ2eNGylMUxU1cTJs2jQtOUqlUnI0C8c0NDg52+DkgHuepqamcncpgMt62tjY75cEUXANFUdw09cyZM+2St/l8vtsmKsnNqri4GCaTCfPmzXM48erIJoLsQTTD4OHX3oNRVAuFfhoSfNuh03uBtVLoM0gxjdFAFG9BRIMKXX4h4AtMsHQaQCVacFrih/TANFwfl85J8gnhO1ZhamRKmkjlx1M+JZFIOCsTIm1XKpVcmCQp0qxW64T77ZJJCHc14Zy1UyJk08Dik0xWdXV1IT8/nyucHNkpdXV1QSgUDnkfT01NxcKFC3HnnXfivffeg8ViwX333YfrrruOI0o7Ojpw+eWX47PPPuNyMtwRTOtMSO6yZcvwwgsvIC4uDunp6SgtLcWrr76K225zLehntHDnfjPc7wHsff2IykKr1XKhw6QGAs42F7q6upCbm+uR04DOglgc8Xg89PT0IC4ujgv5BWAX7OaJE0eDgUzUTp8+HfHx8RO9HDsrAaJGUyqVaG5uRlVVFddwGywQlBw+bW1WBssv6e3tRWxsLLZt2zakzUZJSQk6OjrA4/GQk5PD5YVs3rwZs2bNAgC3BNeS+/yGDRu47/N4PFxxxRU4fvw4AOdCdMcTzliUMAyD+vp6dHZ2Ijc3lwsCHIjREty2YZIMw8DPzw/+/v5cENrGH/8Dg7oc8ZJ+KJXRoEw8WPl8iIyAXOOP0PQ+WJW+OMVIMD3chJwQE5QmL+h7KET6BOGFP62HWOT6+YumaVRUVMBgMHiEl6ytlYltSFxjYyMsFgt8fHygUCjAsuyoQ+LcCZZlUVdXxxHwrtgLOQs+n8/VOGToSKlUQqFQODV0RHiEwWog2/wSsgdN2QOMHM5+NsnZRSQSYd68eQ75B2LpMBrYqogoiuLsOmiaRktXB54o/Rg5kafQbfSGRc0Dj2YBmobBKAJvBgXpL1b0BQlwpleMGUHd0EmE6LZIYe0BFmfPx/Vzzw1WdwYajQZlZWUIDw8fc4WWM3BkZdLZ2YmamhqOC5HJZAgJCfEozmssbdwIJBKJXVg3abidPn0aBoOBG6wYTOVP6ghbAn6w/JKWlhaYTKYJ/zx4CiZP5W6D4Q6Aw3X2hgIJkyDPb0tuN7Z24r1vXkdduw8kGQYYDWKABSgBDVrAg8CXhlEBhIQZ0YsQSHR6+E3rRY+PENJp/fhDXjam90dwXq+e2M1yBOJHbDQaceGFF0IsFnMBd7aTgbZWJp4CW1+3gUFl4wmBQIDw8HCEh4dzwUm2VjC+vr5coeXn54fe3l6UlZUhJSXFzivckYz3zTffhFKpHNa3bgqDw2w2o62tDfn5+ecQN+6cqGQYBm1tbQgICMDcuXMdkidDJXQfPLIP/3foFwj8NRBSPJisQkAA+Aj06KSDIZcHICKgFwikkZzUieAzfZBTQTBEixHsJ8Qbi+9ByP+/Dkixb+vpGBYWNqyMyhWo1WqPmZImUnrg7KQ0IYAc7WEDrUzGGsQjcyybcI7slFQqFU6dOuXQTqmxsREdHR12Bzvg3D1Io9Hg8ccfR0hICKxW65DNzs8//xz33XcfLr/8ci5s9o033uC+b7FYUF9fD71ez33NHcG0zoTkvvnmm9i4cSPuueceKBQKREVF4c9//jOefvrp0b3xToJ83sZrgts2uEYoFMJgMHAehHPmzOEmoIjVQGVlJUfqjAUZMZ6wle7n5uZy1xxRPQwM7yUHkIkms4YCUR+52wvYXeDxeHa5EaThZhsIajvZZLVaUVxcDH9/f7vDpyMZ7w8//IDvvvuO878eau9uamoCADz77LN49dVXMX36dLzyyiu45JJLcOrUKS70drTBtb29vaBp2uFj6urquOcYLkTXk2A2m1FeXj5kc55gNBYlAxv8tuewMz1y3Pf9R6B9dVgYLIdSHQCa4oPvz4DXRIHXy6LXxxv+aXpEVGuhaPNCs14MvpSFRGTF/VfciDkpuSNal8lkQllZGfh8PgoKCia8KT4QFEVBKpWit7cXEokE+fn5dtZMowmJcydYlkV1dTXUajXy8/PHZV+1HToiNi8kf8o2u8XWzq2xsRGdnZ3D1kAMw2D9+vXg8/ljNigyhbMgmUVRUVGYOXPmoA2F0U5w2+5BA4ccPys5jK1tPyE8sBd+lBky+MEKHrwkgK6DD2EYi5bOUMQvl0N8WAINX4JatRQSLwbh3iK8eNtTEAtGRvSSrKHExETExcV5HJnJ4/EgEAjQ3d2N6dOnIyIiAiqVCh0dHaitrXXarmOsodfrUVxcjJCQEKSkpIzLOhzZvNiq/KVSKbf/BAYGcjWQt7e33XS5o/yS9vZ2bN68mVPvetrnYiIwaQnuwQonckgTCASDdvYGA8uy4PP5UKvVaGlp4S5AhmHw1Kbn0CPqh0XLhyCAhVDAQiSmARYQs1Zou6UQJerB0BJ01zMQ+lggjRZAIw9HekwsHly1HOXl5QiJDEFycvKk+fARjycAdgWdn58f/Pz8kJiYyNkAqFQqNDY2QiKRcBvYUFYcY4nR+rqNJSiKsnv/iLxHpVKhra0NwFnSITo6ekjlAUVReP/997F582b88MMPg8r8pzA8RCIR5s+f7/B77pLakhsZSfl2NkwSADq1Sjz/f29C2NoDZX804qJ6QFn4EFAMOtWBSBJ3wS9Yjz6VDyowHXHRSgQH9CEgxQhfSx/uyLwTKSFZdr/Ly8sL06ZNw7Rp0xxKzAjZGxgYOKJrWKFQoKqqyqMIFzIlbWsBYmtlQvYwWyuTsd7D2tra0NjYOK4emcMVWoRkTUlJGfLwqdfrsXr1aoSGhuLXX38d9n4bFBSELVu2DPr96dOnnzNB6K5g2uFCcn19ffHaa6/htddeG/J5xhrjNcFN9hfS7CgtLeUmggBwe5DRaERZWRnEYrFHkjqugkwOKpXKc2qDgeG9pAkol8tRX18Pb29vbl8YLthtPEEOvY5CaT0Vw1kJEEIqISFhyPf5l19+wfXXX48FCxbg/fffx/vvvz/oY2traznS46mnnuJsjz7++GPExMRg69at+POf/+zeF3qeoL+/H6WlpfDx8Rm0OW+LkRJMgzX4dQY9Xv9xE36SC0B5meAvMkHEo8GjAf8gE7ojBRCd5sFQw4dEyKDRGoaAcAMCZ2iBfiAhNBUPXzF4APpw0Gq1KC0tRUBAgMeG0JrNZpSVlYHH43F+tz4+PueExNlamZD9bLwmK0konlarRUFBwYRNdAqFQruhI9IIIENHIpEIVqsVaWlpwzZ0n3zySRw4cADl5eVITEwcp1fw+wLLsmhra+Ps0QbLLCIYzbltsHPYL83HsaVkByrNfmCkAsR4q882lXgW8CMBKtEKYRXABlDQ88SoM8YgZE4/wvg60Fohbp9/O3KmZY9oTQC4/LP09PQJCSF2BiqVChUVFZgxYwanhCaWZcT2lth1kHMmaWqP156q1WpRXFzMhadPVB03UOVvG4pO0zTXsExKShryvVEoFFi+fDmuvPJKfPTRRx5Tl040PIbgdtWixNHGZXtIS01NdeliIRtaSEgIGIbhZNxFlT+ju7sXWtoLcSlanJaFAwGAUuOL2Qn1EPhYwPbzIA0wwdAvhXCmCSIDBUsfBZbyxZv33gKKNqGkpATJyckeQ/Q4A6PRiJKSEs54f7Bu/2A2AKQrbiv3HY/DMfF1k8lkbvN1G0vYynt6enpQWlqKwMBA9Pb24siRI3ZhWGSylGVZfPjhh/jrX/+KvXv3TpHbbsBg8lx3SG1JYRYcHDzodLCjooplWWw4/AqqG3uQ2atCF88PNMuDgAUo1gpfqR5drcGIzVEhnulCJz8YvWof1PZOg1BoRc60aGy6dviAPNvPIE3Tdjda22s4JCTEKck+KcRmzZrltkDX0aK1tRWNjY0Op6Qd7WEDJ3vGwo6ppaUFzc3NyM3NnVAFhm2h1dDQgLa2NgQHB6OhoQH19fV2k03kQKrX63HttdeCz+dj165dHj3dOpkgEAiGtWBzF3g8Hrq6utDU1ISkpCTExMTYEUtECksOAp5I6rgCMomu1+tRUFAw7GfWtgloG+xWUlIyaLDbeEMul6O6utqjD73DwdZKwGQy4cSJExAIBODz+Th27NigVgInTpzANddcgxdeeAGrV69GT0/PkL8nISEBXV1dAOw9t8ViMRISErgBA3cE1/L5fPD5fIePsX2O4UJ0xxODncPkcjkqKiowffp0p5VYI6mbBiOWPvnhR8gsH6G5JxgmkT8kFAWGpWCk+QiRGtHL00I1MxgwWCAtoWA+BPCjLdD4CmBkgnH7ygsh4QlRXl7OXbOunEWIojI2Nnbcfe2dBTmvkWm/gfvRwIwgRyFxpM4bKysThmE4e5f8/HyPsbYcmNFw6tQptLe3w9/fH7W1taivr7ezcyM1MMMwePrpp/H111+jqKhoitweJQb7zDEMg5qaGigUCocqW0cY6bnN1vaK7EF6owkbt78N3+AaNGviwPNjYKGEoBkeeCILpCyDqAgdzszwho+ZgbmSB0szDV40DQVPAu+gWKy8KhO6M1rUG+tdHpxhWRanT5/mbKEmUo0+FLq6ulBTU4O0tDQ75TmBre0taWorlUrU1tbCYrFw54zQ0NAx2xv6+/tRXFyMmJgYj9rLBQIBF9ZtNptx4sQJzpr0559/ho+PD3cGtx2uUCgUWLp0KfLz8/Hhhx9OGmeI8YDHENyuwNHGRQJPkpOTXZZt2BZVQqEQMTExUPSbsPXoh9BBimm+ZnRr/CDgM5AIrOhX+EAcY0CrNgSJs9vR8EsMpBoaYjENo4oPigJuWbgAqy69iLPIGMtww7EAmVYICgpyqVlAbADCwsK4rrit52JAQICdDYC7wbIsamtr0d3djYKCgkklpVar1SgvL8fMmTO57rTBYLCbLBWJRPjiiy8gEomwZcsW7NmzZ9DJ4ym4B6OZqGQYBrW1tVyIjkqlOoe8Gug1SYqqV7/ajWpDERThUlg6BfARmQAWELCAulsCnwgzInTdMFlEKC5NQmyiEuERPQgP7QELKR695D7EB08f0esl16jtNdzU1MQFXQzm2008Czs6OjymELNVc+Tl5Q1LJA+2h7nTyoRlWTQ1NeHMmTPIy8sb95CqwdDc3Iz29nYUFBTA19fXzk6pvb0dNTU16OzsRElJCRcaeuDAAY9vIk4muDPUdiiQfaepqQnZ2dkIDAy0I7fJYWWyNeYHA5lupChqRJPowwW72R7OxmsqkYRnZ2ZmTqr6cjCYzWaUlJTAz8+Pk+Q6shI4fPgwaJrGxx9/jKeffhr33XcfKIpyqpmal5cHsViM+vp6rnayWCxoaWnBtGnTALgnuFYkEiEvLw+HDh1CYWEhgLP1wKFDh3DfffdxaxkuRHciQfaHpqYmZGRkuES6u7qPOSK3n/3Ph/ipXYaUaBXCIvjQmkXgeQN8hoXS5AOtWYwgqRFhRhGo6T3o8PWDNpaGSMFAxAhw1zXLcEXBbLAsC61WC4VCgba2NtTU1CAgIICzZBuq0UX2Qdu63NNAck6Cg4ORmpo6bE0yVEgcsTKxnax0B2lC0zTKy8thsViQn5/vsUqg5uZmdHZ2Yvbs2ZyCW61Wc2ewyspKAMBPP/2E7u5u7NmzB0VFRUhOTp7glZ+fIAH1DMPgggsucNoChihInLVrIPUQ2bPIHvSHl55Ft8kLKy+pQIsqGBbwQAmskMCEVl0Qwr01CPftg0VLgZfDQB7mBTaJhqSbh9BgH7z24APw8fK2G/6rqKgAALvBocGuMWIR29fXh4KCAo+ygLUFyTpzlusa6I+v1Wq5cwaxMiHvjbusTDQaDUpKSjwmo8QRLBYL16jMzMzkcrtsVf48Hg91dXUwm8349NNPkZaWhk8//XRS5cWMByblu2FbOJE0a0KoDBZ4MhgcFVV/eOtv8Nb2w9tHAG89A6GQAW3lgRGxCAjQQ97tD+8uoMYahwRfGVLnN0Kt9oNeI4aXtxjPXfsyREIRampqOKLVkywyhgPxzR1th8u2Kz5jxgw7svb06dPw8vLiiCJ/f/9Rb2Cky6vRaFBQUDCpvNA0Gg1KS0sxY8YMuyJaKpUiLi4OcXFxoGmaK85PnjwJsViMV199FQEBAcjOzp64xZ8nGGyCe6SeuIRQsVgsmDdvHqRSKXp6euyey5HXZL+2B3e+9jaMRgv4eRJQAFgLC54fA14bC99gA2RdwUjxbQclZZHIPwO11Rd9LV5oQySWZ6fjrqtGFl4yEAOv4YGSfdJVDgsLg5eXl9315wmFmK0dwUjWNPD1u8PKhDQBiLejp5DDLS0taG1tRV5eHne/cmSntH//fnz99dfo7e1FSEgIHnzwQbz//vsee2CdLCD3v/GwKCE5JSzLIj09HYGBgXZhkg0NDThz5syka8wPBmJdR4J6RkvYDBbsZjsNSfaFsfKZJNZG4xmePZYgBzsvLy87v0lHVgJbt27Ff/7zH7Asi61btyI6OhrXXXedU7/Hz88Pd911F5555hnExsZi2rRp2Lx5MwDg2muvBeC+4NqHH34YN998M/Lz8zF79my89tpr0Ol0uPXWWwHAqRDdiYLVakVVVRXUajXmzJnjchPWFYJ74NRkU3MTHtryAVipFGaLDxKiu6E0+IDHY8EaKBhEfFgYPqp6ozErsB3BwWoEGEWIFGqhDxVhfsxCXDn9j9zzUxQFX19f+Pr6IjExkTuLEEsuYj0UFhbGTS+zLMsprDx5HyRnh9Gc1xyFxCmVSo5EIQq2kYbEWa1WlJWVgWVZ5OXleSwRQ3IZ8vLyuLps4F6v1+vx66+/4osvvkB7eztiY2Px/vvv4+mnn3aZf5jCubA9h5HPdmBgoMv3bduMkeE+b45ska7/+wOw0r7oE/qAR1MI8jOiSUGBDxosDxAbrWhBEMI0Wkzz60ZMQC/C9DpMTxaCnxqM1TPuQXzQ/5oeAwdnNBoNFAoFGhoazhkcItcYyTxgWRazZ8/2GMWDLVwdIHIE2/05ISGBszKxzecYrWUmUeEQ73JPBKmBxGIxR24D5+7PGo0GRUVFeP3112GxWBAWFoZPP/0Ud9xxxwS/As+CZ95lhgEpnEjqvcFgwNy5c10iLxxNTW47/jW+rPgR6qZIBEcbYaLEkFJWWFkK3qwF8h5fRIf1IVYvwpnmYEh7GSijQ9AqD4eAFeCBeZfg4lnZ4PP4KCkpgdVqxezZsycV0UqsRWz9k9wFW7LWarVy3Uzi8W1rZeJqAcQwDCc9zs/P96ik3uFAuoqJiYlDTsrx+XwUFxejpqYGu3fvRlxcHPbu3esRROL5DFcnAYD/eXwRv23yebb1pXRUVL21ZwOaylRQdSdiZnI3mqgAiFgLRP5WKIS+CKL1oPkU/LyEOFUfg6AQNfzDDfCT9CNYBPzzjqchGsPP/lC+3eT1DefbPF4gXo/9/f1O2RE4g9FamRD7JDLR7ynXbmtrK5qbm+3I7cHw+eefIzY2FtXV1airq8OJEyemyG03YqxDJomUnc/nQyqVQiAQgGVZLp3ddlrIU5ovo0F/fz9KSko4f3F3k82OpiEJedbc3OyWw9lA2IZnnw/h0haLBcXFxZBKpcjIyBj0PaIoCh0dHdi7dy82btyItWvXYv/+/S4rhTZv3gyBQICbbroJBoMBc+bMweHDhznpu7uCa1evXg2lUomnn34aMpkM2dnZ2L9/v52VzHAhuuMJcm3YZhldcMEFIyJWnCG4HTX4F//9boSwAviJfSGDBAzNBw8sJBIzvGEF3wzAj4Kv0QQZ44ceczLCJVrwKSsElD9eveAx+IqHvofZnkVsrYdOnjzJTS8bDAZuH/TUAaXu7m6Ul5e79bw2MJ9Dq9XahcS52ryzWCwoLS0Fn89HTk6Ox0roHTX4HUEqlaKsrAw6nQ4//fQTenp68O2333pMLXe+oLOzE9XV1ZgxYwamT5/u8n3b1kZmKAzkgcpPVeGpr/8NsFKIvQHaSoFiAKnAAorPIkhkRGevD6wBFILNBpzsjkOrPgj+QgNYAOn+2Xg079Yhf6dt1gdpkCsUCq5B7ufnh4CAAM7yyh1N+bEAUcyrVCq3DusMtDIhCq7q6mpYrVa7hpsz9yayTyYnJ3usCsdqtaK0tBQikQhZWVmD1kAk4PbIkSO47LLL8Nprr+HQoUMwGAzjvGLPB8U6GlmcADAMA4vF4tRjNRoNTp48CZFIBC8vL2RmZrp0wB5YVCm7u/Ds1y/AIBJCZgyC6IwQEUFyUHw+rP08iIwspkXrcKIxEhFpKoSIdTCqxdCopTCzAiy7cD7yZmRDqVSit7cXFEVBIpEgLS0NAQEBHuPxMxw6OztRW1uL9PT0cfX/I91McijU6/UICgriCO/hiCkifTObzcjNzfXILudg6OvrQ3FxsVNdxW+++Qa33347vvjiCyxfvnycVvj7gcVicVgMWSwWHDp0CFdccYVTjRelUony8nJMmzbtHL/KM2fOQC6XIy8vz045UnOmAx/vfxHTAnpwsGwadLogzJghgyzMB2wADXSzMFVKsCC2CX1VEvSIvWD0FsHCihDoJcGGtXciNnRivK5tCTMfHx+oVKoJ8d63xXjvCbYhRUqlElqtlrMyCQkJ4Q4/dXV1UKlUyMvL8xj7pNbWVjQ1NQ1rlWKxWHDbbbfh1KlTKCoq8tiJtskKlmVhNpshk8nQ3Nw8JhYFarUapaWlCA0NRUpKCkpKSqDVajnytbW1FXw+H1lZWZPqPjoYuru7Oe/gkRySRwvbw5lSqYTVarXbF119j23VH7m5uR5LvLkCQm5LJBK7qSVHqK+vx6JFi3DbbbfhhRdemDS19WQBTdNQKBQoLS1FZGQkUlJSRtyQqaqqglgsRlJSksPvD2zwHyj7FZ//+hn6DBKwPDH8eSy6zEEwGcTIjm9FXloHypsi0Gv0QpfJF6wPA1ZAQ0pbAR4ff0y6BDdlXTri1w6cPYeSqW6TyQQej4eQkBCEhYVNSB0zFGQyGaqrqwf1ux0LkOadSqVCd3c3hEIht585CokjlkNkItETSTrA+RqIZVm8/fbbeOmll3DgwAHMnj17HFf5+4DJZEJ9fT2nIAsNDR3R87AsiwMHDmDBggWDcggDFfyFr74IK+SIERgh748A4yeAnhHDqJDgxsW/oNvihTNd/lBavdDHeIHyswK0FUKKhQ/fB29ethZh/qMLijeZTGhra0NraytYloWXlxdnpeQOpbu7QIYKdTodcnJyxmWoydYyUaVSob+/n7MyCQ0Nhbe39znvz2QI4LZarVxDOSsra8h9sr+/HytXroSXlxd2797tEcNknopJOcHd19cHi8WC6OholydyBhZVaz++GzMZ3xgAANrPSURBVGF+Jkj5AnRrfECLeaCtFHgiwEdtQgs/AOHQo0suQc70LjQ2BKGeFwih2AJfkRSv3bcefj5nyQs/Pz+UlpbC398ffD6f8yglm5MroQLjCSLFa2lpQU5OzrjLXW27mUlJSZwNwkD5YGhoqJ25PnCu9M2TCtDhQMjthISEYcntffv24fbbb8dnn302RW6PEQbbR8jNxmq1Dklwk+uooaEB6enpDm+mPB4PNE1zFgQatRaP/OszdNDdKJzVCUbtBVrAA8sCspZAREeo0MAEQBpIQ5xixI+NsYicbkQwq4Of1YyLZl+JFVcWjv7FjxBardbO+5HH4zn03g8MDOSu4bG+IZOJIR6Ph/z8/HGRww4MKXJkZUL8ZD0pG6CtrQ1NTU3Izc0d8mBntVpx1113oba2dorcHiOMtUVJV1cXqqqqMGPGDMTGxoJlWWRlZUGj0aCjowNVVVWcj3Fvb++IlFSeBOKdm5qaOmEHG9s8g5SUFO5w5sjPf7gJQGLHp1QqPUr9MRoMJsl1hIaGBixduhQ33ngj/va3v3nMQf98QmdnJ8rLy5GSkjJq332iCHGEgUNG173xDHr7zPANECPSW48zBi/w2bN7IM/XjMraWKTFdiEpToXmriD4CE3otwphNvMxLy4DDyz406jWSmCxWNDc3AwvLy/MmTOHszKxrWPIeW4ilbkkxHu8rVNEIpHTIXEsy6K4uBje3t5DqjImGqQGcobc/uCDD/DCCy/g22+/nSK3xwAsy3JN97lz545qIpiiqCFVJLa2SL+cKsdzu3Yghq+EnAkAj8eABg8CIQNWxwK+DA6XJmHVRWUAS0Hcw0BvNUCnE4HP4+GhBTcjN8Y9HuwajQZnzpxBcnIyoqKi7JTuFEVxDbeJDLa2Wq0oLy+H1Wod17DYgZaJRqPRzspELBZz+09gYCCUSiWqqqowa9Ysjw3gJpPbZLBkqL+pTqfDtddeC5FIhF27dk2R28NgUk1wsyyL1tZWnDp1CgzD4Oqrrx5xmOQtb/8NErEM4ZEGyNp8Ee6nwyl1KPRSETQlAZiZIQOrMMI/gEKHzgcBtBGUFpB6MQCfxeL5y3HVpZdzzy2TyVBTU2MnFSPTO4SsZVnWqVCB8QSRzMtkMuTk5HhM2BmBxWLhNniVSsVNVBCyu6KiAnw+H9nZ2R7xfjoLkuRLJsuGwsGDB3HDDTfggw8+wPXXXz8+C/wdwmq1DloMfffdd7jwwgsHJRWItF+lUiEnJ2dQyXRXVxfq6uqQlJSEt4p24PRvcqh8fRHm342rZlXAoArCT5VBUJkiQQNIniGHPlgAuY8XhCIaPJYFpaMR6xOC1654CAL+xBFQPT09KC8vR1xcHBISEgbdi20bVmq1mvPtDg0N5fwu3QWj0YjS0lJO6u4Je4LFYkFZWRm0Wi136CcHQWcldmOBM2fOoKGhYVibA5qmce+99+KXX37BkSNHPHYK4nyAyWRCb28vysvLcckll7jlOcnUb2trKzIzMxEUFGRni6RQKFBVVYXp06cjODgYSqUSCoUCBoPBoS+kp4PUiU1NTcjKyvJYX1TSBCPKP4lEYpdJYksIkXwRtVqNvLy88+JgQ6aWhELhkJJc4Kx9wMKFC7FixQq8/vrrHkuWTXZotVr09/e7Zcilvr4eNE1zoZwEtuewj4s+wPfVdVBpAxDByKGVSOHvY4TF5A3KJECftxQGkwhmRgCqD5g9qwXxMSoYLCL06QKxZva9SAx1D7Gk1Wo5v9+0tLRzPmOO6hhCdo+Vz/5AkNDPtra2IevM8YZtSJxKpYJGowGPx4O3tzfS0tLcXue5CyTHYLgaiGVZfPrpp3jiiSewZ88eXHzxxeO4yt8X2tvbERAQ4JZhtcOHD5/jC20bJknTNB745EnIeikoEYC00HZ0qHwRI1WjUReFSC89OsyBYPkUjBoRQn37MS+tBb6+BvTpJRDzk/HwpU8Abvpsk6DGWbNmnROYbBtsrVQquWDrsLCwcT1HEFUGuW97yhCELd+mUqlgsVjAsixiY2MRHx/vkYpEmqZRUlICHo83LIdlMBhw7bXXwmw249tvvz0v1HtjDY8huIk8dzCQAl+hUCAjIwPFxcW48sornSYwWJaF1WrFwV+O4s0DuxGVqoVOI0VaQi8aqv0R6dWPNlEALH1AuzoavhoasYkKsP1meOtpmHzFsDB8+PBEeP2RF+2elwSRZGRkDCqnsbXhUCgUMBqNCAoK4gqkibj4CCmn0WiQm5vrMVOFg2HgBm8wGCAUCpGQkICwsLBJ43VOyO1p06YNm+T7ww8/4Nprr8U777yDm266ySOLxPMFQxHchw4dQkFBgcMGkNlsRmlpKWiaRm5ursPPIZlYslgseOE/f0ML1Y++o74whkthFvAR6NeLJWnFMBsD0PSbN054TwOUEoDHIiygD6GJfdDxRbAyfDx0yY3Ijs1y++t3BUQem5KSgujoaKd/ztbvUqVSQSgUus2fVq/Xo7i4GEFBQdw0+UTDNhuAKEyGszIZj2u8vb0dp0+fHvaQzDAMHnzwQRQVFaGoqMhjw1nOF5jNZmg0Gpw4cQKXX3758D8wDGiaRmVlpd09nqZp7togRHB6evo5Ey4kOFGhUKCvr4/7nJJAWU+EpzfsB4PVarUbhgBgN4lUW1sLvV6P3NzcSdNoGAquSHLb29tx9dVXc97UnrCvn69wxSpyODQ0NMBgMCAjI8Pu+RmGQWnLabx7+A3090lhZSn06H0QxcihCxHAZBYj0mRAszUEMT56dPN8YDSJwPIAxswHTCzuvPQi3HCx+0I4nW3WE9jmj6hUKohEojFX6toGZufm5npsPoJer8fJkychlUohFArR3d09JjkEo4WzDX6WZbFlyxY8/PDD2LVrFy677LJxXOXvD4NZRY4EP/zwAzIyMriGna2Cf8Out2HRVqKj3xtGkwRKawAy/FvRpfJGSKAW5n4v6MxeEAcz6DZ4g2F4YCgKjIEPAcvgs/vuRHTg6OxICEjd0tXVhZycnGFzNWwbSkqlEv39/fD39+f2oLGqz0g2g6+vr10QtKfhzJkzOHXqFMLCwqDT6SbsnDUUaJpGaWkpAAybTWAymXD99ddDrVbjwIED50XuynjAM1ovw8CWQJo3bx5HBtM0PSzBbRsmufjFuyASBIANECCAoWGiABYUwgP6oTOKECTVo1MXgMhIBRSCENTXRCIw0IQ+qRm0no/Nt92JhJj/eZ0xDIPa2lp0d3cjPz9/yMOUrQ3HjBkzuMMjCe4Y78MjkZhYLBaPTecdCJJm7eXlhe7ubgQHByMwMBByuRynTp0a08lQd4GED8bFxQ1Lbv/000/44x//iNdee22K3B4HDPX+DiZ1I82KgICAQSeGSVHVLuvCM9uegconDNGMFSazBVq+D1gK6DNJIJcFICzOgMh0IbIrW1ETGAmzyRsKjR+UZT5IjQ/Hm+tud+trHglaW1vR2NiIzMxMl/3xhEIhIiMjERkZCYZhOFKnuroaNE3bhYe4MsFBguQiIyORlJTkEdcKTdOoqKiA2WxGfn4+93oGWpmQgzKxMiGvf6wOgu3t7Th16hRyc3OHJbcfe+wxfP/991Pk9jhCIBC4xaLE1ht/7ty53B5GbISGq128vb3h7e2N6dOnw2QycWR3Q0MDZxsWFhbmMfdamqZRXV3Nhcp6KgnvCAKBAGFhYQgLC7MbhmhsbIROpwOfz0d8fLzbDv4TCVckuV1dXViyZAkuvfRSvP322x57oJ7CubCtmWynJpe+/izC/PoQ5aOHERKYNXxQNKCHEEFBZnS2iGH2tSBO3YsOQwBCYECgWA8zw4eFpfD2XfcjKnxkvryOQKyMXGnWi0QiREVFISoqym5ysLKy0k6p6y6bp7EIzB4L6HQ6FBcXIzw8HMnJyaAoys7KZKQhce4GafA7E9K7bds2PPTQQ9i2bdsUuT0OcGctMXAPomkax2sr8LdftiLS0gexVQSeGWAZgE+xMKso8EPM6FBLkeSlhkVAoU/ljQhpP2gBBYuVB5rPw44Nfx3mNzsPmqZRVVUFrVaL2bNnO1W3UBQFX19f+Pr6IiEhwU4Ndvr0aTvf7oG2riMF4S7GKqzbXbBVZZDQ6MHOWRNlHUzTNMrKygAMT26bzWasWbMGSqUS33///RS57QI8foLblkCaNWsWBAIBFx5w8cUXD7kZEGL7++IDeH/vbvRbpfD1AqxhFJIlPajRBCArVoUAsRUl5aGI8VFDHyCFUuMDSmeGxV8EmhHgkvgUPHjFGrvntlgsqKiogMViQXZ29qimh8nFp1Ao0NPTMyabky08VWLiDAwGA4qLizkZIXlvzGaznZWJQCCwCz/xBKsCcoOIiYlBYmLikI/99ddfUVhYiBdffBH33HOPx95MzifYemMPxI8//oiUlBQ7QlehUKC8vBzx8fFITEx0+Dcie9CqN5+FkNeLSGjR5h2GEJMJPYe9oZ/hDQOEEIjNCPLSYH5MLbyDaRj7fWHp5qFPTUHg54cHbtoMqdfEeq7aTkdmZ2e79UZr69utVCqh0+mc9u3u7e1FWVnZhAXJOQIpYGiaRk5OjlNk/UBLq7GwMuno6EB9fT1ycnK44s8RGIbBU089he3bt+PIkSOYMWPGqH/3FIaH2WyG0WhEUVERrrrqqhEX3hqNBiUlJQgJCUFqaioAcEFKFosF5eXloGl6RLWL1Wrl6hVbFUZYWNiE5YyQ18QwDLKzsydFw344ECKYpmmEh4ejp6cHvb29Q2aSeDpckeTK5XIsWrQIBQUF+OSTTzyihjvf4c4J7ra2Nm7amKZp/O3zz3CsrR6C6TxEa/sQHtSHxt4QsFqg2+qFHsobaeZmmGL46OuUQCKmESHUQa+VguVTMDFWfPH4225ZG3C25mhubuasm9xhZWTbnCIq09HaPNn63ebk5Hjs3kaGDKKios4JVydwNHk6XEicu0Ea/MPVQACwc+dOrF27Fl9++SWWLl06puuawlkMpaR1FceOHUNCQgLCw8NB0zSWbHoaBkqA8CgtvM0MBH1WaKUUtHovaDVSCIQ6xIVoINdJYLBSCPc2QmpmQZvEYIUW3LfibuQlzXLL2oCz9R7x1nZXsPdAW1fbHBBHQbDOgISTE9W5p9Yczc3NaGlpGbJxNdg5aySDVSMBORsyDIOcnJwh+TeLxYJbbrkFTU1NOHTo0FT2kYvwGIIbODuGbwu5XI6KigqHBNLBgwcxd+7cQX1oyI30ng+fhA9fjYa+EEhpHkQUoPOnEB/Si16ZGBEhZviEmiCxWFBzKhjeYiukIhNYqQBeggC8sHrTOc9tMBjsfF7dSRCTw+PAzSksLMwtE316vR4lJSXw9/dHenr6pJqI0el03KE9JSVl0E2WYRhuYkClUnFeVYTwngiJr06nw8mTJ50it4uLi7F8+XI888wzeOCBBzz2ZnK+YSiC+/jx44iPj0dERAR3MGpsbERGRgYiIiIc/gzLsvjX7rexu64RQpoFz9+KcJEJnQhCtKAP9XujEBGjRZswBJSQBl9ghVSsR7yXCsF+faBZAQIleciPyeWm+yYqRdt2yiAnJ2fMpyNJuBPxp/X29uaafrYTo2RqKjk5GTExMWO6JmdBiCmKopCdnT2i+4NtWritlQnZw0ZyEOzs7ERdXR2ys7OH9FhlWRbPPfcc/u///g9FRUVISUlxef1TGBksFgvMZjO+//57XHbZZSM68MhkMlRWViIxMRHTpk3jpn4pioJer0dpaSknMR0taUhUGAqFwi5nJCwsDMHBweNCSpJJdalUiszMzPOCCCXhi2QIgbwmR5kk5GA2Xu/3SOGKJFelUmHx4sVIT0/H559/PqmGMCYzhrOKdAXt7e3o7OxEZFwU7vjX2+AFsND2ieCXaEaUuh+Rob04URWPAGk/NPCCViuBXsggme6CcBoPvQYBGDUflNiEnQ+945Y1Ediqb3NycsbMz3SgzZOrZC5RLxMrH0+9Dvr6+lBSUsJZvDgLogxSqVTo7u4+JyTO3edTZxv8ALBnzx7ceuut+M9//oOVK1e6dR1TGBzuJLh//fVXREdH4+vi/dhxpAWi6RbwJAIEUXrwWQrhwm600/5ANw+9rBg6sxckbD+ipf2wRFPQKASAiUKAUIBPH/qHW9ZEoNPpUFpaCj8/P6Snp4/JvduWC1EqlbBYLHY5cM6QueSMlZSUNOrg4bECySY4c+YM8vLynN7PyWCVI8tIZ4K/XQVN09xwyXDkttVqxZ133omqqioUFRWd48k+heHhkQQ3+bA2NTUNSiA5Cg8gYFkW1733NwjVKvBF/WAtAsh5/uBpGAj9edBrhAjOUCPWqMOpHj9MDzLAK8ACb6kVjJGCyUjhlgseQ2JU2jnPrdFoUFZWxkmwxpIgJpsTOTzSNG23Obla7PT19aG0tBQRERGcfGyygEw/u2pBwLIsV2QqlUr09fXB19eX28DGIxyGkNvR0dGDTvoSlJeXY8mSJXjiiSfw6KOPTqq/0WTHUNNLv/32G6KjoxEREYHq6mp0d3cP2SXu6ujAy988ji5rIOTwR6haCyqYRjSlQzkvFpn+HWgtDwdqAdEMQCn0B8MAELDgU1YsTJ+B9X+8BjRNc4SGUqkERVFcw2uk3XhXQUISWZadkOnIgb7dAoEAoaGh4PP5aGtrQ0ZGhsckZFssFrsDqbuKVluJXU9Pj8tWJq6Q2y+99BL+9a9/oaioCOnp6W5Z/xScg8ViAU3TOHDgABYsWOCSFJ1lWTQ2NqK5uZmbSCTlHUVR6OnpQUVFBWJiYgadsBsNyPSiQqGAQqEYlxAkrVZr1/SeTA37wWAymVBSUgIvLy9kZGQM+pochU55aigomVpiWXZYcrunpwdLly5FfHw8vvrqqzGfqJrC/+BOgrurqwsvfrYZCj4DVbs/BBkW6HrE8I8xIrpXA5GUhUnNos9LAlbJwiAUw2AVwkILYRbywWNofLLmViREubdxbbVaUVFRAZPJhJycnHHL7jGZTHZKXdtQ2YCAgHP248nid0umOxMSEjBt2rQRP8/AkDh3W5k4WwMBwIEDB3DjjTfio48+wurVq0f1e6fgGoYaNHIFLMvi20P78N/ib9DJCwFPw0LgQ4MK4kMiMMHPZEJMaC9OlsUiOK4Pxl4RdKwIRpMIFqEIFpZCmESErx98xA2vyh5qtRplZWWIiooaN0tF26EZhULhlEq2s7MTtbW1mDVrlsecsQaCZVmcPn0aXV1dyMvLG1U2AbF6UalU3B5NOLfRqhMZhkFZWRmsVityc3OH5O9omsbdd9+NEydO4MiRI4iMjBz0sVMYHB5FcJvNZlitVlRWVkKtViM3N3dQX+sffvgBs2bNOkdWtuPX7/HvYwfAC2Tgr2YhMvWCofhQmf1gpkXggYUXzNBIhQiL0SGK1qO/RwA5JYKYz8CPz8O/7nzD4e+Uy+Worq7GjBkzxt2P1FbCr1AooNfr7Q4zwxVpJEQlPj4e06ZNm1TEKZkOiI2NdSoAZijYhsN0d3dz8uqQkJAxIQyJJ11kZOSwpEJ1dTUWLVqEBx98EE899dSk+hudDxiK4Ca2OHK5HAAGPRixLIuFT90JL4sQKfkGNKuCcIbvi4gODdgYGtN6NGiMjYTIYEW0Vz866oLRd0qMILERVh8ehGI+nrr9T0hNTXa4PrVazTW8SDeeEEhjMd1D1CqEbJnoCUEyMdrc3Ay1Ws1NMI6XvGwoEOsnsVg8ppOkAw+CxLt8MCuTrq4u1NbWIisra0gZNsuyeOWVV/DGG2/g0KFDyMqa2CDT3yNIwNJwCrWBIGGSpG7y9vbm/LYpiuJCd1JTUxEVFTXGr+J/jWVCdmu1WgQEBHAqDHd4yBJrImeD4SYDCKnl7++PtLQ0p+sRT2jkDwZXJLlqtRrLli1DZGQktm/f7lEk/e8B7iK4X/7gbdTKqmGWUlDwA0E3iiHO18PQJkBAvBn+egP4LIuIoD4o272gYn0hFhvBMwIMKFyduQC3XL7CDa/IHkajEaWlpRCJRBM6ET1wcAEAd60GBwdz+0BoaOiQatWJRk9PD8rKytw+3eluBRupgZwht4uKirB69Wq8++67uPHGGz32vT9f4Q6Cm2VZ3PTM/ZBSNKw+PLRp/SBiWcCbhUEkgTTShNhuNYyUGPEhcpTXRkMcZgVrACiWBSgB/rnmUYQHus/rn4DwSBM9ET1QJTsww4x4WQ93bphIsCyL+vp6zgrLnRPXtnu0SqUCwzDcGcvVsybDMCgvL4fZbEZubu6QP8swDNatW4cff/wRRUVFHjs1PxngUQR3X18fiouLwePxkJOTM2Rx+9NPPyE5OdlubP/ylx6GKJSCpUuKkHAd+EYKInUPpL4sVDp/8IP0ULf5AX4CSCw0tGYBhOFmSHytoHXAx396btCJ8NbWVjQ1NWHWrFkeIRXQ6/Uc0aXRaIaUvslkMlRXV4/b4dadINMB8fHxmD59uluf2zb8RKVSwWKxuHVigKSJR0REDNulraurw6JFi7B27Vr89a9/nSqqJgBDEdwnTpyARqNBaGjooNL+ncU/4c3vPoeo3Q8JqZ3gB3lBqZaii/FBJKsFX2oCzAzCzUbUBUWCNfIQJuyHmG+B0STCdK84PLz0Tqc60OQAQAgk0vAiBJI7iAHiqRgWFuYxhyxbKRqZkHZlImGs4OzUpbsx3EGwv7/faXL7jTfewObNm/Hdd98hPz9/XNY/BXsQeW5RURFycnKGDAElIKSNrSUO8du29c3PysoaVpY9VjAajVy9Qg5TxHZpJHY75JDoSdZEo4WzFmzOYLBG/lhJ/weDK5Lcvr4+FBYWwt/fH7t27Rq3ydop2GOgVaQr0Op1uOPlxyAJZSBW8tDvLUSX2A+CRgFEs/TgtbPQRwohCrYirEcLPljwhUCwtxZWEx98QSBevP7vbnw1/0N/fz9KS0sRHByM1NRUj5mIZhiGU74QJQaxekpNTfXYJo9KpUJFRQVSUlLG/Fw5GgWbsw1+4GzWzjXXXIPXX38dt956q0fUvL83jJbg3vfbHnz06UGIZtLwlVpg7ZOgud8HPD0PVLoV1iY+vKaZwRMAkTotzBDC30cPKd8Cg0GAS9IXYXlBofte0P8Hy7IcaZyRkWGX5zTRICpZhUKB7u5uAGfXm5SUhJiYGI/ZK23BsixqamrQ29uLvLy8MT3vOcqICggIsGu4DQZXye3169fju+++Q1FRkds5r98bPIbgZhgGhw8fRkBAgFPe0MePH8f06dMRGRmJxY/cBZUwCCFRZvBZBtpeX4RF9cFHY4FZSEPkq4e+QwSd1QdeoVoo5IGQCixg+XxQfAaMWYw9f/nboOuqq6uDUqlETk7OoBPlEwmz2cyRPLbSt7CwMGg0Go/cUJ1Bd3c3ysvLx6XT6e7wE71ej+LiYoSFhQ1rB3P69GksWrQIN910E1566SWPvJn8HjAYwS2TyVBeXo7AwEAUFBSc87c0mUxY8sazEAYawSrN4KsEmDGjG4IgKWQ9EvR3C6D180JArwHe0/WwaimE9uvA+omg5YvBM1txQ8Y1mDv7whEfZgZ6PRIfsbCwsBH5ZXd3d6OiosKjghtJt16hUCA3N/ecRoAj3+7xCGMzGo0oLi7mvPQm8vq1PQh2d3eDZVmEhoYiNjZ20IMgy7J477338Pzzz2P//v2YO3fuBKx8CsD/CO6jR48iPT192AM5UTcFBQUhLe2spRoht2maRkVFBYxGI7Kzs8fcN99ZWCwW7jpVqVQQi8UuZQy0tbWhoaFhUtY0g4E0E121YHMGto18pVLpdun/YHBFkqvVavGHP/wBIpEIe/bs8ZjP6u8RZrMZIzkWPvn2m9CYKqA67Q3xBYCk1QoNxYfOyxvWTj4YqRVIAHgNFEzhPHgFWCGgGEiNJlhZ4Lmr7kNKjPP+za6A1DOeHpKmVCpRUVGBoKAgmM1m9Pf3j6kn7EihUChQWVmJ9PT0QTNoxgpDhcQFBwfb7WcymQw1NTVOkdvHjx/HypUrsWnTJtx1110e+xk53zHSoNv+/n7c+sbfIEE3RP0C0DwRxCkWQC5APT8QomYBhMl6MCYWWp0YflEWwJsHL7MBApoGC29sueX5MXhF/zu7yOVyZGdnD2ptOdFgGAY1NTVQqVQICgpCb28vN7k8UmvcsVpndXU1+vv7kZubO+7NcIPBYNdwk0ql3Ptja2XCMAxXg+fl5Q1Lbm/YsAE7d+7EkSNHhs1qm8Lw8BiCGzjrby0Wi526sZw4cQKdvW344Nj3YIRiUP588HkCwGSBvscb4jQzwptM0EYAotY+SOOsMCr5oK1iaFgxzDwBJFYtdm4cPLzEYrGgoqICZrN5XL3aRgMiq1AoFJDL5dzmFBMTg6CgoAm3GHAWJNhgPKYDHIGEn4xkYsBgMODkyZNOkdvNzc1YuHAhVq1ahVdffXWK3J5ADJTn2nraBgUFwdvb+5zAveueuRe6EC9oaQnC6E6wtBgamRSxIX2ISjegThYKlgZ0Oj6MYhGCjIazU0s+FtA0D5nSRCzOW+DWkBHy2SUNLxLQGBYW5pRUnfiueZLigxQ0Go3GqW69rW93d3e3W5LEHcFgMHD2NWlpaR5zKJLL5aisrMT06dO5aU5HxBbLsvjoo4/w1FNPYd++fZg/f/5EL/13DUJwHzt2DImJiUP6HpIQ7oSEcMTEhQGsBDzqbCOWTHVLJBJkZGR4rI/xYBkD5Dq13RNZlkVDQwM6OjqQk5PjsYdEV6HRaFBaWoq4uLgxJ98GU3y4m0BzZWpJr9fjmmuuAcMw2Ldv36g8NKcwerhKcP9QeQCvfvoteJEUYtAPzSkvMBfz4FdjgjaSD6GRjwYmAOIzFKgQIxADQMWA1Qlg4QNx/n5Yk1HAXfvh4eFuVRl4Yj3jCF1dXaipqbEjjYknLDmHeHl5cYMLY9m0HwpEEZyRkTHhauahQuIoisLp06eRnZ2NkJCQIZ/nxIkTWLFiBf76179i3bp1HlPH/R4xEoL7sY8fReVJFtPTNVCc8UKQtxEm2gteQSZ09whh8hVD3yuApUcM7yQDLF6AWMbCAAFYlsVduTnwF/nB19fXTlnmDhD7OL1ej5ycnHFVlroC23US0phcX0Rd4qo17liAYRhunXl5eeOeCTUQVqvVzjKScG7BwcGQy+UwmUxOkdvPPPMMvvjiCxw5cgTJyedalE7BdXgUwU38J53BOzvewNHTVehTiaAX+CMgzgCGEcIoZCDuE0LjxUcoq0VArxW6MApCkwWs3gjKnwKfpfHGTe/AWzr4xUm8ZyUSCTIzMz2ia+UsbBPCExMTodVqoVAoOAsO4tnrqYdeuVyOqqoqjwk2GGpiYOD7SMjt0NBQzJw5c8hCqa2tDVdffTWWLFmCt956a4rcnmDYEtwDPW1lMhksFotd6N6yF+6GPyNAU1ggpDwGwX0K9OokQKcPvPyMSM3oAiP2QpPKF0IW0BoEMPP5MPOEiBRIcNvMuYiNjR02eHQ0GBjQKBQKORuTwMBAu9/LsixaWlrQ0tLChdR5AojMnTQaXZ1yd0eSuCMQlYY7LAXcCTJdlZmZyU24OiK23n33XbAsi6NHj2Lv3r249NJLJ3jlUyDy3F9//RWxsbEOCRkuhLu5HqmzKHj79IBhjeBBAqEgCUbdNJSXV3Fh0pPlvmIbmkjqFXKdBgcHo76+HhqNBjk5OR4zyThaEB/x0Qa0jRQDpf9E/TdwEskVuEJuG41GrF69GjqdDvv37/dIheTvDa4Q3G8feA4/FXdD3S5C3Jx+SHppKCukEF3KQlhMgUmloekSwMuXhzPwhVDFwqzjQSChIRACe//6VwD2+SIKhQI0Tdvli4yk+U/2yba2No+qZxyhtbV1WL9bq9XKDS+pVCq7/JHxGl7q6OhAfX09MjMzhyWNJwKkIdDR0YH+/n6IRCJEREQMGRJXVlaGJUuW4KmnnsL69es9po77vcIVgttkMmHDV39Gc3kQ9KwEM2K6IVdJ4WOwwJAlRFCtCcYUgJYLoBb5QKPnQdwrgNVCgy9mkJEYi813rAXwP1svYtMhlUo5stvX13dEnwuz2YzS0lLweDxkZ2d7LOdisVjsQqAHW+dAa1yS8zFSqzlXQc6CFotl2NpiIkCC1pVKJdrb22G1Wu2yZxwp01iWxQsvvIAPP/wQRUVFnBJzCqPHpCS49RYj7nj8flCxYvR2esMopCAKtULIsGAjKfBlVpj6vaCPoBAoNsKvlwHfYAUjAAoy8nHPVTcM+fwajQZlZWUICwvDzJkzJ80BEYCdLNl26pxYcJDNSavVTphf7VAgSdeeKj8eamLAz88PNTU1CA4OHpbw6uzsxNVXX43LLrsM77///qT6jJ2vIAS30WhESUmJXRZAY2MjdDodMjMzAQB/futJ9Hf2QRjCQ500CBKGQaBYA4MOkLYKoGfNkPKAmbNUkPrz0KPzgt4ohJBnxiMLHkVTU+u4TxSRRg3ZAwBwxUlgYCBOnz7N2X84G2431iCFFwC3FIiOiN6RhN/pdDqcPHlyTCwFRgMicR5uuspgMODuu+/G9u3bIRQKERUVhRdffBHXXXfdOK52CgNBCG6iABoYZk3TNKqqqtDb24v0TAY84SnwEAgezwcstFBr2tDa6ItpsQsndTiNbb0il8uh0+nA5/MRHx+PyMjISaGmGw7Ew3bmzJmIjo6e6OUMGqpEGgzO7L2uSHJNJhNuuOEGKJVKHDx40Cm/+SmMPZwluE+1l+KfB16Hoj4Eer0AkbP74NVpRnunH4KDddDGiRFYToNOZtBv4EFCA+AJQIPCuoU3IC811+Hz2k4NKhQKGI1GbjAnNDTU6c9hbW0tenp6kJOT47GqgJGqUhwFjo/18NKZM2e4iejhghonErb2KTwez24/GziYVFVVhUWLFmH9+vXYsGGDx9Rxv2e4EnT72oEHUNtkgLzKB0aJF1KSZDCbGGiqfCCeZ4ZFJoaf2QRjDNCvEMJHyMJCiSARUHhv3eBe/wObSQKBwO6s5MznRKfTobS0FP7+/hNuXTgUSH4QGeZ0tlE2sCFAVO5DNZNGA6vVypHwntwsYBgGVVVV0Ol0SE9Ph1qthkql4hQ4pKYidnybN2/GW2+9hcOHD3P8whTcA48iuIk8dzjsrfkvvtlyGPpQEbq7KEjDGDR1hSEmvhesRQgmmAFPwYBixTAbKFiEAngJLdj1gGOfbVsoFApUVVUhMTERcXFxk+qGZ7FY7MKmhtoAiF+tQqGAWq3mEnSdtTEYC0yWAsoWZGJALpejt7cXAoEAUVFRnJ+oo01eJpNh0aJFmDt3Lj766KNJYxvze4BCoUBJSQmCg4Mxa9Ys7u/X0tKC3t5e5OTkgGVZLP/7o/Dqs8IrwIqagHB4qc3wn64H3a6BRidFYLcYeisfwQE6mE188CkLBJQXnr75dnR2diIzM3NCP+Msy9pNTBmNRvD5fCQmJiIqKsojioeRFl6uYCS+3cQvNzo6ekyn710FIbedUb7s2LEDf/7zn/HVV1/hsssuw+HDhxEVFYWcnJxxWu0UHIEQ3GVlZfD390d8fDz3PZPJhNLSUrAsi6zsJJjoAwArAJ9/NjhSJutCd08zYmJjEBF8PXjU5CeByWvm8/kIDg5Gd3e3Xai2O6XE4wmiUpsID1tnYDuJpFKpnArwJdJhg8EwLLltsViwZs0atLW14fvvv/fo6drfG5wZNGJZFm8eug8tSi1aikNgMgjAm0Eh2toLE0XDcMob3tNMMMSJwG+gILVYwIp4iAiPxrNrH3N6LSzLQqfTcXUKGcwhZLejRhexlrRYLMjOzvbYZhjJd+ru7kZubu6I9zFHw0sjadoPhZaWFjQ3NzsdfDxRGKzBPzAkbtu2bThy5Aja2tpw22234Y033vCYOu73DmcJbpqm8djnt6NX4wNNvRg6vhjT5irBa+Ghq1cCX40VwnwaeloEr2YWAhEDVkjhrlV3IjtlltPrYRjGbjCI5NqEhYUhODjY4Rm/t7cX5eXliI6OxowZMzz2s6XX61FSUoKAgACkpaWNmJQeaDUHgFPgBAcHj/rsRrgtPp+P7Oxsj+VMWJZFVVUV+vv7kZ+fb2efQpompKbauHEj9Ho9zpw5g71792LBggUTuPLzE5OK4GZZFizL4ovf3sGB7TXoD+DD3M8DTyCCxiKERcxHSIQWrJEPSHlgJSxAs/jHZXcheVr8oM9Lnru1tRVNTU2YNWvWhHuLuQoyderl5YWMjAyXNoCBoU8ikYgrjsaiE+cIk6WAcgQSMkcmuVUq1aATUAqFAosXL0ZWVhb+7//+b1JZ35zvMJvN+P7775GQkHBOsGJ7ezu6urqQn58PmqZR+OoG+Kp0kPrx0BobCFrFgpEKEBjcB7ajD0ZGCLOOQqCAhz6rEd9ueAeVlZXQ6XTIzs72GFKGSOhYlkVQUBC6u7uh0+km3GeNeFuPtvByBRaLhZvaGMy3m4T6xcXFISFhbAKxRgKVSoXy8nKnyO3du3fjtttuw+eff47CwsLxWeAUnAKR51ZWVkIqlWLGjBkA/hcmSbzeaVYJnXEfBPwoADy0trbBYDBg+vQoiMR6eIsXg8+bHE3iwaDT6exeM9kDBoZqk4CfifSldQWerlJzhMEagSEhIfD39+cOdjqdblhfTKvVittuuw319fU4fPjwpHkPfi8YjuBmWRYMw+Cfh/6Mpk4aXfUhsHazMPuIMC1PCbQIYKbMUMt84WViIPSmQYPFq088g+Dg0dlaGAwGjuwmjS5iI+Dl5cVlD4jFYo+2liRKHJ1O5/aQNEfXKjnPuWq1wLIsmpub0dbWhtzcXI+2EHKlwX/48GFcf/31CA0NRUdHB1JTUznV5hQmFs4Q3GebOjo8vWMdrBYeOir9YDBJwETykBbbBbOMB5VZAkYugIiyQiBlIPUOwNvPjC5EcuBgELFRI8oJgUDABZsmJycjJiZmVL9vLEEGdYiVnbvqJtIcJw0Bo9Fod5501WLSbDajpKSE29M9mdyurq5GX18f8vLyhnydDMPg4YcfxqeffoqYmBicOXMGzz//PB5//PFxXPH5j0lDcLMsC5qmwbIsfmk/htff3ArfRCv0eiE0ciNEPr4wUUC3OgBCXzPEUhoCvQXb1v9l2Ilk0klXKpUenXA7GLRaLUpKSjgv2NHcpB3ZGLizEzcQxCfvzJkzHl9AOYLJZMLJkyc5Io58zsgmT6xMjh07hu3bt0MmkyE7Oxu7d+/2iCnZKdijr6/P4Y2pq6sLra2tyM/PB8MwuOGfj8GX1aPb6ItAPyMag0LB9lohsFIQ+jEQiqxgzXy8ueweRPoHoqysDAKBAFlZWR7zd9fr9SgtLYWvr69dyKVer+cIJNtDpDtDyIbCWBVersCRb7efnx80Gg3i4+M9jtyuqKhAWlrasNOg3377LdasWYNPPvkE11577TitcArOghDcNTU14PF4SElJgUKhQHl5OeLj4xEfHw+GYcCwWujN+0DTFFqae8DjUWcDCnkaAHx4i5eCR7l2kPAkqNVqlJWVISYmZkiVxEApMWlKESmxpxEWRKU2lNeup4M0AslABI/H497n/Pz8ISdGaZrGn//8Z5SVleHw4cMeOb3+e8dQBDc5hzEMgy+O/w1FpTLwIUBvgxAGsxiMjwA+M0yIEKjB9AlAUcCfrr4J81LnuX2dZrOZI5qIf7zZbEZQUJDLQz7jCYvFgvLycjAMM6Tfrbt+18AMFkI0Dbc/EvuUzs5O5OXleazNC+Bag7+pqQkLFy7E6tWrsXnzZuj1elRUVOCCCy4Yp9VOYSgMR3CTPYimabz47W1QqsXobAwG1U3DCBGoYB5C49Xw0VlAmSkIJN74+x0vg+/mZhexOyR7kMFggEQigcFgwKxZszz63tbT04Py8nJMnz79nGEud4IocMg5qq+vzyX1HVHxksFNT6vnCFwht1mWxYcffoiNGzdi3759uPDCC9Hc3Ayr1YqkpKRxXPX5D48iuIk8dyBsiyoejwcLS+Ppzx9GVykDNoEH2kyhv1sA0FZYGS/wWRM+WP8Yd+ghE8nENsL2YrZaraioqIDJZEJ2drbHeFE7C7VajdLSUm6i0J0blW0nTqFQwGQycR5moaGho06vZVkWp0+fRldXl8cXUI5gMplQXFwMPz8/pKenD/neV1RUYOXKlbBYLOjr60NSUhKOHj06YYfct99+G5s3b4ZMJkNWVhbefPNNzJ49e0LW4kkYzH9SLpejuroaaWlpCAoKwj93foTDpxsQqVWjV+iHIC8z+gPE0PLEoGgKl4VNx8OFt6G/vx+lpaUIDg5Gamqqx9ygSc7AcCQyOUQqlUp0d3fDy8uLI7vHYlqS7GfTpk07S9h5wDQmy7Lo7OxEbW0tRCIRzGYzAgICuH3QUXDIeKG7uxvl5eVITU1FZGTkkI89dOgQrr/+evzrX//Cn/70J5d/l6t7xtatW7Fx40a0tLQgKSkJmzZtwuLFi7nvsyyLZ555Bh988AHUajUuvPBCvPvuu3ZFXk9PD9atW4fdu3eDx+Nh1apVeP311+3uFRUVFbj33ntx4sQJhIaGYt26dXjsMedl8J4EQnCfOnUKZrMZXl5eaGxs5FRlhHiiKAo9mqNo6zgAiTgcMdEzAEoPhtFALJwNiXDyevkRm7ikpCSXfMRJU4rsV7ZBdcHBwRM+zTmZVWqDgaZplJWVoa+vD0KhECaTiZvWCgkJsZtMpWka69atw7Fjx3DkyJFxzZ9whKkayDEGGzQaeA6T9bTjnR+egrJHAkO/F3RdQjA6FlZKCJbPInVGJP6+7oFxWbNcLkdlZSW8vb1hMBggEok4EiUgIMAj6gjgf5ZLIpEIWVlZ40rCE6sFQjbRNG3n2227P7Isi/r6eigUCuTl5XmM4tARXGnwt7a2YuHChVi2bBneeOMNj6nHp2APk8l0zteIgp9hGG4P2v7r6/ihphoSLyvaToeC7mFgtfBAU3xQQhYbb70JBRnpY75e4rusUqkgkUig1+vdbhPkLpD6aiImzE0mE7f/kKYkeY8GcnNEGU/4FU+9VlmWRU1NDdRqNfLz84cltz/77DM8/vjj2L1795QtyRjD4wnugUUVuQDk/Uq8tfclnP7NiIAQGlYfPmCh8Kf51+CyOZfaPSeZ8FEqleDz+RzZLZFIUF5eDrFYjIyMDI+ZrHQWSqUSlZWVLh8ERwLbTpxCoUB/fz/8/f2HTIcd7vnq6uqgUqlG5T83UTCbzTh58qRT5HZfXx+WL1+O4OBg7Ny5EyaTCUeOHMGyZcsmpPD+73//izVr1uC9997DnDlz8Nprr2Hr1q2or6+fdNY87sZAgpsUVWazGQ0NDdzBIDQ0FB/+vA2ne/Xw4+sgUFOwCMRgWAv++9c3APzv+oyPjx/TLrmrIOtKTEzEtGnTnP45q9XKhYrYTgORQ+RoCxByUBmP/cwVEBKZhMER331SpI016T8Yenp6UFZW5hS5ffToUVx77bV46623sGbNGpfX6OqecezYMVx88cV46aWXsHTpUmzZsgWbNm1CSUkJZs0663+4adMmvPTSS/j0008RHx+PjRs3orKyEjU1NRwxtmjRInR1deH999+HxWLBrbfeioKCAmzZsgXA2b01OTkZV1xxBTZs2IDKykrcdttteO2117B27VqXXqMngBDcp0+fRmdnJxiG4e6PDMOAoijweLyzh5TqMsQnWBAcpgdgAkVJIOQnQyxIA0V5pjR/OLS3t+PUqVOjtomzDapTKpUwGAwICgrirtPRNuddXUtjYyPa29uRl5fnMQG+o8XAqSWRSMSpf5RKJTQaDXx9fdHX1wcvLy98+eWXOHLkCIqKis4JTx1vTNVAg8MRwT3YOaz41CHsrvkMXXIRfPysMOgkEFIMnv/jP+A3Tp/zjo4O1NXVIS0tDZGRkeeoUCmK4uoUYjU2ESB+t54QOjfQk9rWli4kJATNzc3o7u4eVpEx0XClwd/R0YGrrroKV111Fd59990JJ8ymGmyDw9E5jBDbwNkGP0VRYFkW//fzX1HR0op+gwDeYho6owiRgb549trBQyTdCZqmUVFRAYPBgJycHEilUu6MoFAo0NvbC19fX672mMhBvo6ODtTX13uEDe9AT2qKoriBBKlUirKyMs6ezlPOzgPBsiwXZpyfnz+k1RTLsvjiiy/w0EMPYefOnbj88svHcaWOcb7vQR5NcJMNbWBRZYuOvi50GxSY5hcPf+nQ9ha2Ez5yuRwWiwVeXl5ISkpCSEjIhN/wXAEp6pyRZI0FBpI8xJMxLCxsWJ83hmG4jldeXp5HF1COQMhtX19fzJo1a8jXqtVqUVhYCC8vL+zevdsjXuucOXNQUFCAt956C8DZv0dsbCzWrVuHJ554YoJXN7Gwlec6KqoAcKoGuVwOjV6LSnkTxFIh1hXeCqFQCJZl0dbWhsbGRqSnp0/I9TkYyL4x2nAzR8Ero7Eykslk3IT8cAeV8QRpBgx2gHIk17f17R6rCS1CbqekpAw7Cfnzzz9j1apVeOWVV3DHHXeMqFh0dc9YvXo1dDod9uzZw31t7ty5yM7OxnvvvQeWZREVFYX169fjkUceAXD2ugoPD8cnn3yC6667DrW1tUhLS8OJEyeQn58PANi/fz8WL16M9vZ2REVF4d1338VTTz0FmUzGkZZPPPEEdu7cibq6Opdf50SDBIYdP34cFosF8+fPh0Ag4GogAFxWCNlbGFYPljWAorwnbbAkIYHPnDmD7OxsBAYGuvX5SVAdkcmOpjnvCibTJKQrcGZqyWw2Q6VS4b333sNrr70GALj++utxww034Oqrr57QQ+tUDTQ4bAluR1OTA/9uLMuiuu0E+k0KzIq6GL4+42MzaLtnZGVlOQztZhjGzjPXVtUREhIybhPUnmC7NhRsbenUajV4PB5iY2MRGRk5rMXnRMGVBr9MJsPVV1+Niy66CB988MGE29dMNdiGhi3BbWtPC8AhT6PWqlHf+SskIl9kTR8/qxmiyBjKfpLcB0m2z0RkhpCMuebm5kH3yokE2aeVSiXkcjlMJhOkUini4+PHfSDBWbhCbgPAtm3bcM8992Dbtm1YuHDhOK1ycPwe9iCPIrjJ9BIpqkiRRbp17oJCoUBlZSWioqK4aSiLxWKXjDvRctbBwLIsWlpa0NLS4jEblW04m0qlgkAg4A6PA33eiJRHq9UO61XkiTCbzSguLoa3tzdmzZo1ZFNEp9Nh1apVoCgK+/bt84jDLZG9b9u2zS5g7uabb4ZarcauXbsmbnEeAEJw204skanJgXDkwRYcHAyr1QqtVoucnByP8fMnXvdtbW1u3zccWRmRcNXQ0NBhlTHElzYzMxMhIaMLoXIniJTP2SaFI99uYukUEhLitiKtt7cXpaWl3ET5UPj1119RWFiIF154Affee++I7qMj2TPi4uLw8MMP48EHH+S+9swzz2Dnzp0oLy9HU1MTEhMTUVpaiuzsbO4xCxYsQHZ2Nl5//XV89NFHWL9+PXp7e7nvW61WSCQSbN26FStXrsSaNWvQ19eHnTt3co8pKirCZZddhp6eHrcTpWMNnU6Hn3/+GSKRCHw+H7m5uRyxRArq7u5uZGdnT7q8isHAMAx3UMjJyRnzCSdHzXmi6nMnmUNI4N7e3knZyB8MtuR2Xl7ekAc7hmHwl7/8BVu3bsVf//pXlJSUoLGxEfv37x/HFdtjqgYaGmTQaLCpSU8AGZLp7e11es+wVXUoFAoYjUbOosOZOmWk6O3tRVlZ2Zj73Y4WDMNwQegxMTHo7e2FSqWCWCzmajl3KPXcAVca/AqFAosWLUJubi4+++yzCSe3gakG23AgBPdgyhFPgFarRWlp6Tkh2EOBpmk7FaxAIHCrCtYRbK1gc3JyPLpu1Gq1OHnyJEJDQyGRSKBSqUbtFjAWIA4EROUyHLm9a9cu3HHHHfjiiy+wfPnycVrl0Pg97EEex+KOZVFlO1lpO/mcnJzMEVUNDQ2oqqoal8LHVZBpILlcjvz8fI+RugqFQkRERCAiIsLO5626utpuYiIgIAA1NTUwmUzIz8/3yK7cUCDktpeX17DktsFgwHXXXQeGYfDtt996BLkNnLWBoGn6HMIuPDx8Uk48jgWcLaooioKfnx/8/PwwY8YMqNVqVFVVwWQycdNFhDiZyM+6LYFUUFDgdgKJoigEBAQgICAASUlJ3LRkW1sbampqEBgYyO2ltoUAy7Jobm5Ga2srcnNzPcqXtqurC7W1tcjIyEBoaKhTP8Pj8RAcHIzg4GDMnDkTWq0WSqWSex/cUaS5Qm6XlJTgD3/4A5599tkRk9vAyPYMmUzm8PEymYz7PvnaUI8ZOEkgEAgQFBRk95j4+PhznoN8b7IR3BKJBAkJCeDxeDh16hS6uroQGhoKmqZRXl4OmqYxe/bsYQvqyQIi7zUajSgoKBiX1yWRSBAbG4vY2Fi7ELYTJ05AKBRy1+hoDpy2jXxnDkCTBaTJ0tvb65Qk9/nnn8d///tfFBUVISUlBbfffvs4rtYxpmqg4eHM1OREgYQ0Wq1WzJ492+khGYqi4O/vD39/fyQlJUGr1TpVp4wGE+l36wrIPmx7NouLi+PsXoiSjSj1QkNDJ2wQjDQMZs6cOSy5rVKpsGzZMmRkZODTTz/1CHKbnCM3bNjAfY3H4+GKK67A8ePHJ3BlngOKosAwDLcHeRq5TUIaY2NjhwzBHgg+n4/w8PCzyjsbFSy5tmytlNzxWbVVyxcUFHgEOTwY+vr6UFJSgtjYWC5PLjEx0W4g4fTp0xNmCUlAeDiVSuVUbbd3717ccccd+OyzzzyG3P697EEeRXBbrVZucmCwqcmRgmEYO6mo7WTlQKJqYOFj6904URPH5MDU39+P2bNne+w0EI/HQ0hICEJCQpCSksL5vDU0NECv10MgECAhIcFhkJ8nw2KxOJ3mazKZcMMNN0Cr1eK7777zmEbEFIYHUZC4OjFgMBhQU1MDLy8vzJ07lwtn7OzsRF1dHQICAhAeHu7Ww5MzsA3RHQ8CiaIo+Pj4wMfHBwkJCTAYDJzsrL6+3s6LrqOjAzKZzKOadQC4v1lWVtaIQ2ApioKvry98fX2RkJDgsEgjU1EDw1UGAwngTE5OHpbcrqiowPLly/HEE0/gwQcf9KjDwRQGB8uyiIyMhNVqRVRUFFpaWlBTUwOKouDt7Y3s7Ozzhiw1m80oLS0Fn89Hfn7+hAwSCIVCREZG2nn32pI55Bp1xXbJEVl0PoBMLTnrN/nyyy/j448/xuHDh5GSkjKOK53CaGCxWLhzmKcRSwaDAaWlpZBKpcjOzh4VwTpUneLn58eRTSMdTploG0lnQYJiaZpGXl6e3T7M5/O5PZAo9ZRKJRobG1FVVcX5do/X2diVBn9vby9WrFiBxMRE/Oc///EYVfZUg21osCw74nPYeKCrqws1NTVISUkZ9jM4FGy5EpZlOSul+vp6mM1mOyulkXx2Bw4PeLJanpxtSF6VLQYOJBBLyJKSErv9aTzyFViWxalTp6BUKp3KJzh48CBuvfVWfPjhh1i1atWYrs0V/F72IM/Y8f8//vjHP0KlUqGwsBDLly9HdHS0WzY2QvIYjUanyOGBhY9cLudID39/f46oGi+S2Wq1chMLBQUFk+bARCYmvLy80NPTwxWNCoUCp0+fdksROR6wWCwoLi6GRCIZltw2m81Ys2YNFAoFvv/+e4+xqCAgvoNyudzu63K5fFSezOcDlEolUlNTcdVVV6GwsBCXX365U9e4Wq1GeXk5wsPDkZycDB6PB4FAwElSjUYj59lNDk9hYWEIDw8f0z2E+MMJhcIJI5CkUini4uIQFxcHs9nM+Tw2NDSAoihERUVxljCeUMQSu5Ts7Gy32rjYFmkkXEWhUKC0tNQp325SACYlJQ07CVZTU4OlS5fiwQcfxGOPPTbq93Uke0ZERMSQjyf/K5fL7fwz5XI5Z1kSEREBhUJh9xxWqxU9PT12z+Po99j+jsmE1157DR999BGWL1+OlStXQi6Xo729HXPnzgVN0/jpp5+4hvtEK0NGAxK45ufnN6waarzgiMxRKBQ4deqU07ZLVqsVZWVlYBjmHLJoMsNWkjucLQnLsvjnP/+Jd955B4cOHeJCZT0FUzXQ0LjgggsQGhqKFStWYNmyZQgKCvKIe3NfXx9KS0sRFhaGmTNnunXPGKxOaWxs5CYGnckXImhpaUFzczNycnI8wkZyMFitVpSWloKiKOTm5g5JpDlS6imVSu5sTM5zoaGh8Pb2dvtnxpUGv0ajwYoVKxAVFYX//ve/k/Y++XvEiRMnsHz5cixbtgyFhYWYP3++R9xHB9rDutNOkaIoBAYGIjAwEMnJydyQZXNzM+coQLgSZz7LFouFu64n6uznLIjd0IwZM4YNnx7oFkAsIWtqamC1WrkaLSQkxO2vmZDbZEh2uLP7kSNHcMMNN+Cdd97B6tWr3bqWKTgHjyK433rrLWzfvh07duzAhg0bkJeXhxUrVmDFihWYNm3aiG6YRqMRpaWlEIlEKCgocPlDL5VK7YgqUvicOnWKm0YcS4KWkFQikQh5eXke04V2FmazGSUlJRCLxcjMzASfz0dCQgJMJhM30djU1ASJRMJNdjo70TgeIJPbZP1DFdUWiwW33XYbWltbcfjwYY8sbMnn6NChQ5z/JMMwOHToEO67776JXdwEIzg4GLt27cK2bdvw+OOPo7u7GwsXLsSKFStw1VVXObzGZTIZampqhrw5SyQSu8MT8YBsaGiAj48PwsPD3b6H6HQ6lJaWwt/fH+np6R5BIIlEIo609Pb2RlxcHNRqtV0nPiws7Bzf/vECCe8ba7sUgUBgJ1Mk4Sp1dXXc5Iatb7dGo0FpaSlmzJiB2NjYIZ+7rq4OS5YswV133YWNGze6ZR8dyZ4xb948HDp0yM6D++DBg5g3bx4AID4+HhERETh06BBHaPf19eHXX3/F3XffzT2HWq1GcXEx8vLyAACHDx8GwzCYM2cO95innnoKFouFu7cfPHgQM2fOnHT2JACwdu1aREZGYseOHbjoootgtVpx2WWX4cILL0ReXh7XLBuoDAkLC/PoCR1bkM9zZGSkRwauAc7ZLpH9ipC95FDJ5/ORl5fnEXJ4d2CgJHeogx3Lsnjrrbfw6quv4sCBA3b++p6CqRpoaHz55ZfYunUrPvroIzzwwAO46KKLUFhYiGXLliEsLGxCrleiqkhISBjxWdBZiEQiREdHIzo6GlarlfPMPXnyJGdhRCwXHQVuEr/bvLw8j/a7JWcboVCIrKwsl/crb29veHt7Y/r06TCZTNz7RM5zZH90x3nOlQZ/f38//vCHPyAoKAjbt2/3uPviVINtaOTm5uLTTz/Fjh07cNttt4GmaSxduhQrV67EggULJqRZwTAM6urquHvgWCpObdWfiYmJ0Ov1djXfcEOWhPOSSqXIyMjw6Dqku7sb5eXlTikyBmKgJWR/fz+USiVaWlpQXV3N1WjuGEYl+zqxBx7O6uXHH3/E6tWr8frrr+Omm27yuBr397IHeVTIJAHLspDJZPj666+xfft2HD16FJmZmRzZPWPGDKc+MH19fSgrK+PsMtxJmpBkXLlcju7ubq7LHx4e7ragIjLlFBAQ4HSIgSfBZDJxgYxDTT6TiUZCeDsz0TgesFqtdgXgUO+/1WrFnXfeicrKShw5csSjU2j/+9//4uabb8b777+P2bNn47XXXsNXX32Furo6j5ZSjicYhsHJkyexbds2fP311+js7MRVV12FFStWYNGiRfD29sbBgwchFApd8mm2hcVi4RpmJF3bHXuIWq1GWVkZoqOjnd4rxwMWiwVlZWUAgOzsbI6QJJ14hUIBpVIJmqa565/ciMcaxAt8IoNBWZblfLuVSiX6+/vh4+MDnU6HadOmYcaMGUP+fENDAxYuXIgbbrgBmzZtcuv9Yrg9Y82aNYiOjsZLL70EADh27BgWLFiAl19+GUuWLMGXX36JF198ESUlJdxE56ZNm/Dyyy/j008/RXx8PDZu3IiKigrU1NRwpOGiRYsgl8vx3nvvwWKx4NZbb0V+fj62bNkC4CxZOnPmTFx11VV4/PHHUVVVhdtuuw3//Oc/sXbtWre9/vHGU089hffffx/3338/ampqsG/fPgQHB2PZsmVYuXIlCgoKuGaZXC6HRqPhPN7DwsI81sJMpVKhoqICiYmJmDZt2kQvZ0QgdgYKhQJqtRo+Pj4IDg6GXC6Ht7c318g/H2A7teQMuf2vf/0Lzz33HL799luumeWJmKqBhgfJyCBDRydPnsS8efOwYsUKLF++HFFRUeNSW7S3t6O+vh7p6ekTevgmFkakTqEoys4zFwAXfJmbm+vRqlTiwSqVSocd3HEVNE1zCjWVSgUAI7J6ItBoNCgpKXGqwa/T6bBq1Srw+Xzs2bPHY/8Gc+bMwezZs/Hmm28COFsDx8XF4b777jtvAt7cAavVip9++glbt27Fzp07odfrsWTJEqxYsQKXX375uNi12do85uTkTKhFnO2QZW9vL3x8fOyGLAlnFBQUhNTUVI/mjEg+QWpqqp2K0x1wVKORPchZFQ4By7JoaGjgmpbD7Sm//PILVq5ciZdeegl33323x5y/B+L3sAd5JMFtC5ZloVKpsGvXLmzfvh2HDx/GzJkzsWLFChQWFiIlJcXhB2g8O/62XX6VSgWRSMRtOiPtXhM5XmRkJJKSkjz2IhkMBoMBxcXFLpPzZKKRFJEWi2VMZSeDgZDbAoFg2OkGmqZxzz334LfffsORI0fcvlmPBd566y1s3rwZMpkM2dnZeOONN7ipyCnYg2EYlJeXcwe9pqYmBAYGwmQy4ejRo4iPjx/19TnYHhIeHu5SkAYpGpKSkoY9DIwniJJDJBINeT2xLIu+vj5uyt1oNHLyvNDQULdPb7Asi6amJpw5cwZ5eXke5QWuUqlQXl4OiUQCg8EwpG93c3MzFi1ahJUrV+Kf//znmBS2Q+0Zl1xyCaZPn45PPvmEe/zWrVvxl7/8BS0tLUhKSsLf//53LF68mPs+y7J45pln8K9//QtqtRrz58/HO++8g+TkZO4xPT09uO+++7B7927weDysWrUKb7zxhl1QakVFBe69916cOHECISEhWLduHR5//HG3v/7xxJEjRxAXF4eEhAQAZ5vd3333HbZv384d3JcvX47CwkLMmzcPVquVu2Z6e3vh6+vLTXZ7SrBQZ2cnamtrJ5yocifMZjO6urrQ2NgImqa5JqW7JhcnEmRqieQkDPU5YlkWn3zyCTZs2IC9e/fioosuGseVjgxTNZDzYFkWZ86cwY4dO7Bjxw4cO3YMBQUF3NBRXFyc2z/rhFjo6OhAVlaWRylyHJ1TBAIBZ/XhqcQqcJYkKykpgY+Pz5jbQzEMw1k9KZVKmEwmBAcHc97Cw9VzhNxOTEwc1r7AYDDgmmuugdVqxbfffuv2MHV3YqrB5jpomsbx48e5oSO1Wm2nsB2LOsdoNKKsrAxCoRCZmZkeZfUxcEBKJBLBbDYjPDzc4wciZTIZqqurkZGRMebDgCRInLxPQqGQO0cNpxZmWRaNjY3o6OhAfn7+sPv6yZMnsXz5cjz33HO4//77Pbr++z3sQR5PcNuCZVn09vbim2++wY4dO3Dw4EFMnz4dK1aswMqVKzkpfllZGXp6epCenj7ufyjb7rVSqQSfz7eTtDmz6RDZRkJCwjmG+5MBer0excXFCA4ORmpq6ogvcpZlOdmJQqGATqcbk6TzgSC+dDweD9nZ2UOS2wzD4P7778fRo0dRVFTkUaTiFNwPpVKJRYsWoaurC35+fmhsbMSll16KwsJCLFmyBMHBwaO+qQ22h4SHhzuUxRIQ/+hZs2Z5lILAYDBwfruu2qWQiWaFQoH+/n4EBARw17+7ZGekM+9JB6L+/n4UFxdz9liDqVxaWloQHx+PVatWYdGiRXj77bc9urCdwuhhNBrx/fffY8eOHdi1axeEQqGdXyXLslxgWk9PD7y9vTmyeyI+42QStLW1FVlZWR5p3TVS2NY6ycnJ3ISnSqU6Z8JzMl2XtlNLzpDb//nPf/DII4/gm2++waWXXjqOK53CeINlWXR1dXEK2x9//BFZWVkc2Z2YmDjqGohhGFRVVaGvrw85OTkeTRiTaWiLxQI+nw+j0YigoCCEh4c7ReKOJ8jgUWBgINLS0saVgGFZlvPtJvWcv78/t0cO3GP6+vpQXFzMDakNBaPRiOuuuw79/f3Yv3+/x2UfOcJUg23kYBgGJ06c4MhumUyGK6+8EoWFhVi4cKFbBlW0Wi1KS0snxTS0UqlERUUFvL29YTAYRsQ7jReI1UpmZqZbfcydAU3TdmphhmHsBigHWgA3Njaivb3dKXK7rKwMS5YswZNPPolHHnnEo8ltgvN9D5pUBPdAaDQa7NmzBzt27MD+/fsREREBiUQCjUaDX375ZcIPUrbSe4VCAZZluZt5cHCww02HdLZSU1MRFRU1AaseHbRaLYqLixEREeF2f01HshNCdrnLFoamaZSUlDhNbj/yyCM4cOAAioqKJmUzYgquoaqqCv/4xz/wzjvvQCqV4vTp09i2bRt27NiB8vJyXHTRRZyE1x1+lQzDcKSJQqHgSJPw8HCu+2w76ZSdnT2m/tGuQqvVoqSkhAuGGs37MZw8z1XZWX19PZRKJfLy8jxmyhX4H7k9bdo0xMfHn/N9Mj3W2dmJFStWQC6XIzY2Fk8//TSWL18+IrucKUxOWCwWHDlyBNu2bcPOnTtB0zSWLVuGFStW4JJLLgFFUWNig+QsSDihUqlETk6ORykkRouhap3BlGik9vOkSbCBIPeTzs7OYQ92LMviq6++wrp167Bjxw5cddVV47jSKUw0iMKWkN1FRUVITU3lFLYjuecTKzOGYZCdne1xHsq2IH63EomEsyYa2JR35Nc/ESDNOGLZOdEEDKnnlEolenp6OIUaqZtLSkq4Bv9QMJlMuPHGGyGXy3Hw4EGPmvSfwtiDYRiUlZVxZHdLSwuuuOIKrFixAosXLx6Rkqqnpwfl5eWcim6ir5WhIJfLOauPqKgouzOjUqm0450m0vIVOGs3derUKWRnZ084P2erFlYqldDr9QgKCuKmuzs6OtDe3u7U8FNVVRUWL16Mhx56CE8++aRHf15+T5jUBLctZDIZlixZgtOnT3MerkTCW1BQMOGeiCzLcgcehUIBi8ViR3YLBAK0tbWhoaFhQjpb7kBfXx9KSkoQExPjlimOoUA80JVKJVQqFcRiMfd+DjXlOhRomkZpaSkAICcnZ1hye8OGDdi5cyeOHDmCxMTEEb+WKUx+DOZXuXz5ci7N3R1kt+0eQvY5g8EAg8HglD/YeIKEycXGxrq9SCTyPNvr31lrAJZlUVtbi56eHqfSsMcTWq0WJ0+etLOnGAwymQwLFy5EcnIy5s6di927d+Pmm2/GPffcM06rnYInwZFf5eLFi7FixQpcccUVEAgEnFRTqVRCLBZzk92u2CA5C5qmUVlZCb1ej5ycHI+6zkYLUus4s7cRJRp533U6HYKCgrjmvCcReK5Kcnfs2IG77roL//3vf7FkyZJxWuUUPBFEYbtr1y5OYZuQkMApbJ2RzRsMBpSWlsLLy8vjA9J0Ot2wfrcDh3J8fX3tmvLjBdKM81TLS6JQs81h8fPzQ2Ji4pDqF4vFgjVr1qC1tRWHDh1CcHDwOK98Cp4ElmVRXV3NDR3V19fbKWyDgoKG/ewTK7XJMGRICOPBcqBYluUsghQKhV2IfWho6DkTy2OJ1tZWNDU1IScnx6OGsAhImKdSqYRarQZFUYiJiUFMTMyQA1S1tbVYtGgR7r77bjz77LMet7f+nnHeENz79+/HK6+8gq+++gpisfgcv0oi4Z03b964XtSOYHvgkcvlMBqNkEgkMJlMyMrKmpQ3aZJyPX36dIdTh2OJgeEvgOuhJjRNo6ysDCzLOkVuP/vss9iyZQuKioowc+ZMt72WKUx+2PpVfv311zh27Bjy8vK4qSZ3+FWyLIvu7m7U1tbCZDKBx+MhJCQE4eHhXMNsIkFslmbMmDGsd+JoMTDUaChrAIZhUFNTA41Gg7y8vAmdqBoIQm7HxsYO2zBTKpVYvHgxMjIy8J///If7e7MsO1VgTYHzq9y+fTu+/vpr9PT0YOHChSgsLMSVV14JiUSC7u5uyOVyqFQqCAQCbrLbHd7RZrMZZWVloCjKLlD2fACpdeLj40ek2rI9SGk0Gvj5+XFk90Q3KIkk15mppT179uDWW2/F559/jsLCwvFZ4BQmDTQaDXbv3o0dO3bgwIEDiIqK4mqg7Ozsc0hLjUaDsrIyhIeHj1rtNdYYSUaS2Wy2U9N4eXlxZLerwWeugCjCxmPwaLTQarU4ceIEwsLCwOfzOfWLrW83uZdYrVbcfvvtqK2tRVFR0ZRybQp2IAHJ27dvx/bt21FRUYGLL74YK1aswLJly85R2NpaqWVmZno0D2O71uzsbKdUCyTEnpDdto32sLCwMbVSampqQltbG3JycjzePqi5uRktLS2Ii4tDf38/uru7uQHK0NBQO8uX06dPY+HChbj55pvx0ksvefTe+nvEeUNwA44P90ajEYcOHeL8KgUCAZYuXYqVK1di/vz5E37wYhgGFRUV6O3thVgs5mQSnjjdMxh6enpQVlY2LmTWcCCT8qSQdCbUhJDbDMMgJydnSHKQZVm8+OKL+Pe//42ioiKkpaWN5cuZwiSHrV/ljh07cPToUWRmZqKwsHBUfpVEGisWi5GRkQGDwcAVLgaDgfvMh4aGjvseRyRzaWlp4x64OtAawGq1chMLQUFBqKurg1arRV5enkftrTqdDidPnuQOoUOhu7sbS5YsQVJSEr788ssJv4dNwbNB/CoJ2d3Z2YmrrrqK86v09va2m56jKIqb7B6JfyOZwvT29sasWbM8egrTVZDGXXJyMmJiYkb9fCaTiVOi2JJeoaGhYzJVPxTIITQ/P39Ycnv//v1Ys2YNPv74Y1x77bXjtMIpTFZotVrs27cP27dvx759+xASEmKnsN23bx+EQiFSUlLGJLDSnSD2BSNtcAHnhooLhUI7z1x3vX4S0jgRg0euwpF6zZaUUyqVnP3L6dOnUV1djYaGBhQVFZ03ocVTGBuQMHmisC0uLsa8efO43ICgoCBs3boV06ZN83grNWKvKJfLkZubO+K1kka7QqFAX18f/P39uT3IXWo7W0XYaNY6XmhpaUFLSwvy8vK4tZIBKlKnAcCxY8cgkUjw7rvv4o9//CNeeeUVj/I5n8JZnFcE93AgfpXbt2/Hzp07YbVasXTpUhQWFuKSSy4Z9zAQmqZRUVEBo9GInJwcSCQSh5tOeHi4W0LVxgIqlQoVFRWYOXMmoqOjJ3o5diChJqQ4IiF1pBPn5eUFmqZRXl4OmqadIrf/8Y9/4M0338Thw4eRmZk5jq9mCpMdxK9y586d2L59Ow4fPoyUlBSO7HbWF3G48BPbLr1Wqx23Lj0wvGRuPEE81mxDavl8PhITExEZGekx4U+E3I6Ojh624aFWq7F06VJER0dj+/btHvMapjA5wDAMysvLOQnvQL9KX19fqNVqyOVyzr+R7B3OBCX29/ejpKRkUkxhugqFQoHKysoxa9zZyvRVKhUXFBUaGsrlLYwVyDSYM+T24cOHcd111+H999/Hn/70p/PqbzyFsYder8eBAwc4hS1wtmZ59tln8cADD3h0Q4w071NSUtx23nGkQCXX/WBZTc6gt7cXZWVlSExMnPDBo+FALFSGa/AbDAbs27cPDz/8MFQqFdLS0nDNNdfg0Ucf9aiQ8Cl4LojClpDdx48fh5eXFyQSCb799luP8KcfDAzDoLq6mlOguosTcme+EQGZoJfL5R5nn+kIxEIlLy8Pfn5+Dh9DLF82bNiAzz//HACwaNEi3HLLLVi1atV4LncKTuB3RXDbgvhVknAmrVaLJUuWcH6VYy1dd0bCO3DTmSj/tsFAir309PRJ0UEf+H56e3uDpmnw+Xzk5+cPOQnJsizeeOMNbN68GQcPHkReXt44rnwK5xuIX+U333yD7du32/lVFhYWIj093eHBhhxanA0/GdgwCwgI4PYQd+5xLMty3W9nJXPjBdLEMhqNCA8PR3d395hNLLgKQm5HRUVhxowZQ/49+/r6sGLFCgQGBmLnzp1u+fv19PRg3bp12L17N3g8HlatWoXXX399yMOi0WjE+vXr8eWXX8JkMuHqq6/GO++8g/DwcO4xbW1tuPvuu1FUVAQfHx9OwmfbQDxy5AgefvhhVFdXIzY2Fn/5y19wyy23cN9/6aWXsGPHDtTV1UEqleKCCy7Apk2bpiyh3ITB/CpXrFiBpUuXIjAw0KHnf3h4uMOwou7ublRUVHDBYJ56SBwJurq6UFNTg4yMDISFhY357xsYUM4wDNeYDwkJcSsJSMht26mlwXD06FFce+21ePPNN3HzzTefV3/jKYwvGIbB+vXr8eGHH+LCCy/Eb7/9BpFIxClsL7zwQo9SJ5Hm/axZs8ZsDyAKNHJOIeG0rlrPuVtpMpZwpcHPMAwefvhhfP/999i5cyeqqqpw4MABfPjhhxNuyzeFyYczZ87g6quvBsuyCAkJwS+//IKsrCxu6MiTAibJOcZsNiM3N3fMhltIvhGxUpJIJNw5yVlVGQkXV6lUyMvLg5eX15is1V1whtwm6OjowNVXX43LL78cDz74IHbv3g0vLy/cf//947TaKTiL3y3BbYvB/CpXrFiBq666yu1k8kgkvIP5t4WHh8PHx2fcN+HxPvC5GyaTCaWlpTAYDGBZFkKhkDtADpyWYlkW7777Lv72t7/hwIEDmDNnzgSufArnIzQaDfbs2YPt27dzfpXLly/HypUrOb/Kuro6dHZ2jvjQYjQaOcJErVZz3q/h4eGjInhZlsXp06fR1dXlcTI0q9Vq561PDkGk2aVUKtHT0wNvb2+uiBuv/VSv1+PkyZOIiIgY1sdTq9Vi5cqVkEgk2LNnj9sI+UWLFqGrqwvvv/8+LBYLbr31VhQUFGDLli2D/szdd9+NvXv34pNPPoG/vz/uu+8+8Hg8/PzzzwDO3k+zs7MRERGBzZs3o6urC2vWrMGdd96JF198EcBZUm3WrFm46667cMcdd+DQoUN48MEHsXfvXlx99dUAgIULF+K6665DQUEBrFYrnnzySVRVVaGmpsYjGrznE2z9Knfs2IHy8nJcdNFFKCwsxLJlyxAaGsolzsvlcruQ7JCQECgUCtTU1EyKYCZXQYiticpHIUoUsncbjUY7G7vRHHQdSXIHw7Fjx/CHP/wBmzdvxtq1az3m4D+FyQmaprF+/Xrce++9SEpKgsViQVFREbZt24Zdu3aBYRgsWbIEK1euxIIFCyZMrTRRzXvbrCZiPefMda9UKlFZWYnU1NRxt4hzFa40+BmGwRNPPIFvvvkGR44cGTaEewpTGA6nTp3Ce++9h02bNkEgEECpVHJ2kkVFRUhNTeXI7olUpJGBSB6Ph+zs7HFr5tA0DZVKxZ2ViKpsKPs6knOkVqvdOmU+Vmhra0NjYyNyc3OH9QeXyWRYuHAhLrjgAnz44YcerTaawhTBfQ4YhsHJkyexbds2O7/KFStWYNGiRaMmb7RaLUpKShAaGjpiKcxA/zaRSMRtOu4IiBoOE33gGy2ITJt0Qvl8vp1EkGEYhISEgMfjISoqCtu3b8fGjRuxb98+XHjhhRO9/Cmc57D1q/z2228RHByM8PBw1NXV4ddff0VsbOyof4fZbOYOTj09PZwkLTw83CXykGEY1NbWoqenB7m5uR5FPFosFruicLBixGKxcPtpd3c3RCIRR9650w/TFoTcDg8PR3Jy8pC/Q6/Xc/K3vXv3uk2KW1tbi7S0NJw4cQL5+fkAznrrLl68GO3t7Q6JSo1Gg9DQUGzZsgXXXHMNAKCurg6pqak4fvw45s6di2+//RZLly5FZ2cnN9X93nvv4fHHH4dSqYRIJMLjjz+OvXv3oqqqinvu6667Dmq1Gvv373e4XqVSibCwMPzwww+4+OKL3fIeTOFc2PpVfv311zh58iTnV7l8+XJERkZCq9VCLpdzxAvLspzP6/k0SdfS0oLm5maPUqUQ2zWFQoH+/v4RK1FcmVr67bffUFhYiL/97W+49957p8jtKYwprFYrfvzxR05hq9frOYXt5ZdfPm7h0KTxJ5PJJrx5P/C6d6TGI6raWbNm2SmqPBGkBoqMjHSK3N64cSO++uorHDlyBElJSW5bR0tLC55//nkcPnwYMpkMUVFRuPHGG/HUU09xTYSWlhaHHuak5iHYunUrNm7ciJaWFiQlJWHTpk1YvHgx932WZfHMM8/ggw8+gFqtxoUXXoh3333X7vWMRFU3BfeCKGx37dqF7du34/vvv0diYiKnsE1LSxs3z2Wj0YiSkpIJzzQZqCpjWZYbCgwODgafzwfDMKiqqvLInCNHOHPmDBoaGpwitxUKBRYvXoycnBx8+umnbq1zp/agscEUwT0EbP0qv/76azQ3N+Pyyy/HihUrsGTJEpfJZFftBZwBMcAn5KwzHbbRgByKPOnA5wpIqKfRaEReXt45EkjbaalXX32V81l66KGH8Mgjj3h80TiF8wtarRZ/+tOf8N1330EgECAgIIALZ5o3b55bip2BkjSpVOqUOoSmaVRVVUGn0yE3N3fcDp3OwGKxoKSkBEKhEFlZWU6/TwP9MCmK4oo4R7YMI4HBYMDJkycRFhY2LLltMBiwevVq6PV67N+/f1giyhV89NFHWL9+PXp7e7mvWa1WSCQSbN26FStXrjznZw4fPozLL78cvb29CAgI4L4+bdo0PPjgg3jooYfw9NNP45tvvkFZWRn3/ebmZiQkJKCkpAQ5OTm4+OKLkZubi9dee417zMcff4wHH3wQGo3G4XobGhqQlJSEyspKzJo1a9SvfwrDg/hV7tixAzt27MCxY8dQUFDA2Zi8++67uPDCC5GcnAy1Ws1NGZLcEE+yGHAFhOQ/c+YMcnNz3XrduROObNecUaKQqSVnyO2SkhIsW7YMGzduxEMPPTRFbk9hXEHTNI4dO8Y13NRqtZ3Cdqzk77Z+t7m5uR4lsx+oxvP19YVUKoVSqURmZuaE558MB1fUayzL4vnnn8cnn3zCTdW6E/v378d///tfXH/99ZgxYwaqqqpw55134qabbsI//vEPAP8jl77//nukp6dzPxscHMzd444dO4aLL74YL730EpYuXYotW7Zg06ZNKCkp4eqVTZs24aWXXsKnn36K+Ph4bNy4EZWVlaipqeHq55Go6qYwttBoNNi9ezensI2JieHI7qysrDEju8lAZEhICFJTUz3m3ku8qMkeZDabERQUBIPBAADIy8vz+Hyg9vZ2nD59Gjk5OXZnGUfo7u7GkiVLMHPmTGzZssXtde3UHjQ2mCK4nQTLsqipqeH8Kuvq6nDJJZegsLAQS5cuRVBQ0JCbj0KhQFVV1Zh6opEOm21AFJlEHE1YCXD29ROvRme6XZ4IhmFQWVkJg8HgkNy2Bcuy+OKLL7Bu3TrceOONqKmpQUNDA7q6utxyM5s+fTpaW1vtvvbSSy/hiSee4P67oqIC9957L06cOIHQ0FCsW7cOjz32mN3PTHXrzm9UVVXh+uuvx86dOxEdHY3vv/8eO3bswK5duyAUCrFs2TK3+lU6qw6xWq124ayeRGSZzWaUlJRAIpEgMzNzxNcrwzB2RRzxwyQ+uCN5zYTcDg0NHVbyaDKZ8Kc//Qnd3d347rvvhi3CXMWLL76ITz/9FPX19XZfDwsLw3PPPYe77777nJ/ZsmULbr31VphMJruvz549G5deeik2bdqEtWvXorW1FQcOHOC+r9fr4e3tjX379mHRokVITk7Grbfeig0bNnCP2bdvH5YsWQK9Xn/OJCrDMFi+fDnUajV++uknd7z8KbgIlmXR1dWFr7/+Gl999RV+/PFHCAQC3HXXXbjzzjuRkJDAef7L5fJxD7h1F2ynNvPy8ibNfdBZJYorU0sVFRVYsmQJHn30UTz++OMec8Cewu8TDMPgxIkT3NCRTCbjFLYLFy5024S1rd9tTk6OR08ims1mnDp1Cl1dXaAoirOvDAsLg6+vr8dds640+FmWxaZNm/Duu+/i8OHDyMjIGJc1bt68Ge+++y6ampoA/I9cKi0tRXZ2tsOfWb16NXQ6HRecCgBz585FdnY23nvvPbAsi6ioKKxfvx6PPPIIgLPEaXh4OD755BNcd911I1LVTWF80d/fb6ewDQkJ4ewk8/Pz3UZ2azQalJaWcsGrnnYdE5ChwMrKSphMJrAsa2el5Il7J3EhyM3NHfZc1dvbi2XLliE2NhZbt24dtzp2ag8aPcZHY3EegKIopKen45lnnkFZWRkqKyuxYMECfPjhh0hISMCyZcvw73//G3K5HAN7Bu3t7ZxsbCwDP3g8HoKDg5GWloaLL74YWVlZEAgEqKurw5EjR1BZWQm5XA6apl16XpZl0dDQgDNnziA/P3/SkttVVVXQ6/XIzc0dlpzavn07HnzwQezYsQMffPABfv75ZzQ2Nrq1U/vXv/4VXV1d3L9169Zx3+vr68NVV12FadOmobi4GJs3b8azzz6Lf/3rX9xjjh07huuvvx633347SktLUVhYiMLCQjvZ/9///ne88cYbeO+99/Drr7/C29sbV199NYxGI/eYG264AdXV1Th48CD27NmDo0ePYu3atW57nVMYOWbNmoWysjIkJiZCIpFg6dKl+OijjyCTyfB///d/4PF4uPXWW5GYmIh77rkH3333Hcxm84h/n0AgQEREBDIzM7FgwQIkJyfDbDajtLQUP/74I+rq6qBQKHDy5EkAcOpaGk+YTCacPHkSXl5eoyK3gbP7aWBgIGbOnIn58+ejoKAA3t7eaGlpwQ8//ICSkhK0t7efQ/YOBoPBgOLiYoSEhAxLbpvNZqxZswZyuRz79+93idx+4oknQFHUkP/q6uqcfj5PwL333ouqqip8+eWXE72U3y0oikJUVBTWrl0LHo+HnJwcvPjii6ivr0deXh4uuOACvPXWWzCZTJgzZw4uuOACBAUFobOzE0ePHsXJkydx5swZp6+XiQDLsqitrYVCoUBBQcGkIbcBQCgUIjIyEllZWViwYAFmzpzJNSJ/+OEHVFdXo6amhptaGq6Oq6mpwbJly/DAAw9MkdtT8AjweDzMmTMHmzdvxqlTp3D06FGkpKTg5ZdfxvTp07F69Wps2bIFarX6nHOYs7BYLCguLgbDMJNCZi+TyaBUKpGfn49LLrkEiYmJ3IT0Tz/9hPr6evT09Iz4/XAnXCW3X3vtNbz99ts4ePDguJHbwFnSJygo6JyvL1++HGFhYZg/fz6++eYbu+8dP34cV1xxhd3Xrr76ahw/fhzAWRWbTCaze4y/vz/mzJnDPeb48eMICAjgiCUAuOKKK8Dj8fDrr7+67fVNYeTw9fXF6tWr8dVXX0Eul+OVV15Bd3c3Z13y6KOP4ueff3aZZ7FFd3c3iouLkZCQMKx9z0SDpmmcOnUKYrEYCxYssKv7fvzxR5w4cQKtra3cdPdEo6OjA6dOnXJqcluj0aCwsBARERH46quvxnVIY2oPGj2mCO4RgKIoJCcn48knn8SJEydQX1+PRYsW4YsvvkBycjIWLVqEd999F2fOnMHzzz+P3377DTk5OeMaxkhRlB05k5+fD6lUioaGBhw5cgRlZWXo7OyExWIZ8nlYlkV9fT26urqQn5/vUQFyzoKQ2zqdzinpzDfffIO7774bW7ZswaJFi7ivu/uw6+vri4iICO6frX/x559/DrPZjI8++gjp6em47rrrcP/99+PVV1/lHvP6669j4cKFePTRR5Gamornn38eubm5eOuttwD8r0D8y1/+ghUrViAzMxOfffYZOjs7sXPnTgBnfXj379+Pf//735gzZw7mz5+PN998E19++SU6Ozvd+nqnMDI4ssUQCoW48sor8f7776OjowPbtm2Dt7c37r33XsTHx2Pt2rXYs2ePXSNjJL83LCwMs2bNwoIFC5CWlgaLxYLy8nJotVpIJBKo1WowDDOal+c2GI1GnDx5En5+fsjIyHBrM4qiKPj6+iIxMRHz5s3jiriuri78+OOP+O2339DS0gK9Xj/o2oqLixEUFDRs9oLFYsHtt9+O1tZWfPfddw6LnKGwfv161NbWDvkvISEBERERUCgUdj9rtVrR09ODiIgIh88dEREBs9kMtVpt93W5XM79TEREBORy+TnfJ98b6jF+fn7nTG/fd9992LNnD4qKisa0QTwF5yAUCrF27VocPXoUjzzyCPbv3w+ZTIYHH3wQxcXFuOCCCzB79my88sor0Gq1yM/Px/z58xEWFgaZTOaRhx7gf3VCb28vCgoKPMqSwFXw+XyEhoYiPT0dCxYsQFZWFoxGIzo6OsCyLFpbW9HV1TVo/VdfX4+lS5di7dq12Lhxo9sO2C0tLbj99tsRHx8PqVSKxMREPPPMM+c0ZSsqKnDRRRdBIpEgNjYWf//73895rq1btyIlJQUSiQQZGRnYt2+f3fdZlsXTTz+NyMhISKVSXHHFFTh9+rTdY3p6enDDDTfAz88PAQEBuP3226HVat3yWqcwtuDxeMjNzcWLL76Impoa/Pbbb8jNzcUbb7yB+Ph4rFq1Cp999hm6u7udJneNRiNOnDgBsVjscco0R2hubuYC0gIDAyEQCBAeHo7MzExccsklSElJAU3TqKio4JpcJGdovGGrXnOG3H777bfxj3/8A/v37x90YnEs0NDQgDfffBN//vOfua/5+PjglVdewdatW7F3717Mnz8fhYWFdgSTTCY7x8IyPDwcMpmM+z752lCPGcgTCAQCBAUFcY+ZgufAy8sLf/jDH/Cf//wHMpkMb7/9NvR6PVavXo3k5GQ8+OCD+OGHH2C1Wp1+TplMhrKyMqSmpiIuLm4MVz96ECtIshcLBAJ4eXlh+vTpmD17Ni666CJERERApVLh559/xi+//IKmpiZotdoJabh1dnaivr4eOTk5w1rs9vf3Y9WqVQgICMCOHTvGtdE5tQe5B1ME9yhBURQSEhLw6KOP4tixY2hsbMQf/vAH7Ny5E6mpqfjHP/6B48ePo6+vb8I66BRFwc/PDzNmzMCFF16IOXPmwM/PD21tbUNOIhJbFpVKxU0vTjawLIvq6mou9GA4cnvfvn24/fbb8dlnn2H58uVjuraXX34ZwcHByMnJwebNm+1ugsePH8fFF19st96rr74a9fX1nGfuVLduCsDZm88ll1yCt99+G21tbdi9ezdCQkLw2GOPIT4+HrfccgsX1DRS8Hg8SKVSqNVqREVFceGsNTU1+OGHH1BVVQWFQjGqqYXRgByeAgMDkZ6ePuYTD6SIKygowEUXXYSoqCj09PTg2LFjOH78OBoaGrg9nxDvQUFBw/roWa1W3HXXXaitrcXBgwcREhLi8tpIgPFQ/0QiEebNmwe1Wo3i4mLuZw8fPgyGYTBnzhyHz02snQ4dOsR9rb6+Hm1tbZg3bx4AYN68eaisrLQjzw8ePAg/Pz+kpaVxj7F9DvIY8hzA2b37vvvuw9dff43Dhw87DFiZwsTg+uuv5+oBiqIQFBSEW2+9FXv27IFcLseGDRtQX1+PSy65BDk5OXjppZfQ3d2NvLy8cw49v/7665DNofEAIYEIIe9JeQKjBUVR0Ov10Gg0yMvLw+zZs+Hj44PW1lb88MMPKC4uxpkzZ7hmQ0NDA5YuXYqbbroJzz//vFv30rq6OjAMg/fffx/V1dX45z//iffeew9PPvkk95gp9doUXAVFUcjIyMBzzz2H8vJylJeX46KLLsIHH3yAxMRELF++HB9++CEXjuYIOp0OJ06cQEBAADIzMycszM0ZsCyLxsZGtLa2Dqqq5fF4CA0NRVpaGtfkslX0VlRUQCaTuUS+jRSkwe+Meo1lWXzwwQd48cUXsW/fPhQUFIzod45EydbR0YGFCxfi2muvxZ133sl9PSQkBA8//DDmzJmDgoICvPzyy7jxxhuxefPmEa1tCucfJBIJli1bho8//hgymQyffPIJAODmm29GYmIi7r33Xhw8eHBIhW1bWxtqamqQlZWFyMjIcVr5yGA2m1FcXAyhUIjs7GyH+6VYLEZsbCzy8vKwYMECTJs2Df39/fj1119x7NgxnD59GhqNZly4sc7OTtTV1TmVH6fT6XDttddCJBJh586dI64Hp/agicX5E3fvAaAoCnFxcbj//vtx7NgxxMfHY82aNTh69CgyMzORmZmJwsJCrFixYkI9lXx8fODj42PnmUkufn9/f4SHhyMkJAQNDQ2T+sBHyO3+/n6nyO2DBw/illtuwb///W+sWrVqTNd2//33Izc3F0FBQTh27Bg2bNiArq4ubkJbJpOdQ+iQrptMJkNgYOBUt24K54DP52P+/PmYP38+Xn31Vc6v8umnn8batWtx5ZVXorCw0GW/Skd+cEFBQZg5cybnU33q1CmYzWaEhIQgLCwMISEhbk2aHgw6nQ7FxcUICwsb9vA0FhCLxYiJiUFMTIydh/nJkychEAhA0zT8/f2HXRtN07jvvvtQXFyMI0eOjHmgbWpqKhYuXIg777wT7733HiwWC+677z5cd911nM9aR0cHLr/8cnz22WeYPXs2/P39cfvtt+Phhx9GUFAQ/Pz8sG7dOsybN49L8r7qqquQlpaGm266CX//+98hk8nwl7/8Bffeey83BXHXXXfhrbfewmOPPYbbbrsNhw8fxldffYW9e/dy67v33nuxZcsW7Nq1C76+vtx+5O/vf86U9xQ8B/7+/rjxxhtx4403cn6VO3bswMKFCzm/ysLCQhQUFMBqtUKpVEIul6OhoQHe3t4IDw/nQhLHAzRNo6ysDDRNIz8/3+OnNl2Fo6klokYxGAzc+//2229j7969UKlUWLZsGV5++WW3h2ctXLgQCxcu5P47ISEB9fX1ePfdd7kwJVv1mkgkQnp6OsrKyvDqq69y5LOteg0Ann/+eRw8eBBvvfUW5zVpq14DgM8++wzh4eHYuXMn5zW5f/9+O6/JN998E4sXL8Y//vGPSeU1OYX/gaIopKSk4KmnnsKTTz6JpqYmbN++HZ9//jkefvhhzJs3D4WFhVi+fDkiIyNBURSUSiWqq6s93u8WOHuuOX36NKeqdWafJIrewMBAJCcno7+/HwqFAk1NTaiurrbzzHW3DN+2wT+ceo1lWXz66ad4+umnsWfPHruGt6tYv349brnlliEfk5CQwP3/zs5O/L/27jssiuvrA/iXXqUpRVSKFRQFBEEMdiIKKhi7WGOPHWOLijU27D3Ggvkpogg2UBQBNQqiNJVqAxtVEBALbc/7h8/Oy4SOdO/nefZJdufM7My63J05c++5ffv2RY8ePXg300pjbm4OX19f7nlpo9KKjloTvlY0eZmSksL1UK/KqDqm/pGUlIS1tTWsra1x8OBB/Pvvv3B3d8fs2bPx5csXDB48GHZ2dujXrx+kpaUhEAi4eT8qUhe6ruXm5iI0NBTy8vIwMDCo0HmCsIRa8+bNUVhYiPT0dKSmpiIsLIwbcaampgZlZeVqP+9ISkpCbGwsDA0Nyx0R++XLF4wePRoCgQDe3t7f1bGTtUF1iyW4a4CoqChsbW1x8OBBNGvWDESE9+/f48KFC/D09MSGDRugp6fHJbvL+9GvScKeiDo6Ovj69St3sRMXFwdRUVFoa2vXWa/M7yFMbmdnZ1eojt6tW7fg4OCAgwcPYsyYMVV6z+XLl2Pr1q1lxsTExEBPTw+Ojo7ca126dIGkpCRmzpyJzZs31/uaf0zDIKxXaW5ujq1btyIiIgIeHh7YsmULZs2aBSsrK9jZ2cHGxoY3geR/ZWRk4NGjR2jdujW0tbV5y0RERKCkpAQlJSW0a9cOOTk5SElJ4S6cmjZtyl041UTiKCcnB6GhodDU1KwXteqENcw1NDTw5csXPHz4EBISEvj48SP+/fdfqKqqQlVVFU2bNuX1eBAIBFi4cCHu3buHgICAWkuunD59GnPnzkX//v25CWb37t3LLc/Pz0dcXByvd+2uXbu42NzcXO4kXkhMTAxeXl6YPXs2LCwsICcnh0mTJmH9+vVcjK6uLry9vbFo0SLs2bMHLVu2xNGjR2Ftbc3FHDp0CADQp08f3j6fOHGi3JNGpn4Q1qscPXo0Pn/+jOvXr8PDwwPDhg1DkyZNMHToUNjZ2cHCwgICgQBpaWlITU1FfHw8ZGRkoKamBnV1dcjLy9fI33Z+fj7Cw8N5Q2wbk/J6LcnIyEBLSwtaWloQFRXF6dOnoaysDA8PDzx8+BD3798vt7fT9/pvrcnSRq9t3boVHz58gLKyMoKCgnjnUMIYYem18kavjRkzptzRa8OGDauhI2Zqi4iICNq0aYOlS5diyZIleP36NTw9PeHp6Ylly5ahW7duaN26Na5fvw4vLy+0bdu2rne5TESE2NhYblRtVcooCUf0Ckf1fvr0CampqXj79i1iYmKgpKTETVL5vR2bipZmK2/0GhHB1dUVy5Ytw+XLl9GrV6/vem/huVZFvHv3Dn379oWJiQlOnDhRoQRbREQEL0kkHJW2cOFC7rWio9J0dXWhoaEBPz8/LpmUnZ2N4OBgbkLvoqPqTExMAJQ/qo6p38TFxdG3b1/07dsX+/btQ2BgIM6fP4/FixcjMzMTAwYMwLt379CkSRP873//q/fzfgj/phUVFdGxY8cqJaOF5S/V1NQgEAjw4cMHpKamIjIyEgKBgEt2//c6qSqSk5MRExMDQ0NDNG3atMzYr1+/Yty4cdy56veW5GVtUN1qXGfz9cikSZO4/xcREYGqqipmzJiB6dOn48OHD7h8+TI8PDywbds2tG7dGnZ2drC3t0enTp2q/e5VRUlLS0NTUxOpqalo0qQJNDU1kZ6ejoSEBMjKyvJ6VtV1IqkswtIqWVlZMDU1LTdhfPfuXYwePRq7d+/GhAkTqnxslb1bV5S5uTkKCgqQkJCADh06fFcd2x/1bh1TOmECp2vXrti4cSOioqJw/vx57N27F3PmzEHfvn1hZ2eHwYMHQ0VFhfsbEJ506OnplZt0FdapbtKkCdq2bYucnBykpqZyw+6EvYTU1NSqpZfQx48fERoailatWqF169b1qk0STsypoqKCTp06AUCxnu5NmzbF58+f0bp1a2zbtg1+fn4ICAio1bp7KioqcHV1LXW5jo5OseGD0tLSOHDgAA4cOFDqetra2sVq4v5Xnz59EB4eXury+jApFlN9ZGVlMWzYMAwbNgxfv37FzZs34eHhgbFjx0JSUhKDBw/GsGHD8NNPP0FERIQbCfHgwQNISUlx5x8KCgrV8reel5eHsLAwSElJ1fuSBFVRmV5LSUlJmDx5Muzt7XHkyBF8/foVd+7cqfHktrDWpLD3NsBGrzE1Q0REBNra2li0aBEWLlyIxMRErF69GidPngTwbcSQsNNRfTufAP7/uubDhw/cnErVQU5ODrq6utDV1cXXr1+RmpqKtLQ0PH36FE2aNOHO2Srbk1HYy1NJSalCyW13d3csWrQIHh4e6Nu37/ceVoW9e/cOffr0gba2NrZv3460tDRumfAa6OTJk5CUlISxsTEAwNPTE8ePH8fRo0e52AULFqB3797YsWMHbG1t4ebmhpCQEK4npoiICBYuXIiNGzeiXbt20NXVxerVq6GpqQl7e3sAFRtVxzRcYmJi6NmzJ3r27Ildu3bh7t27mD59Ol6+fAlxcXHMmjUL9vb2sLa2rpfznX3+/BmhoaFo2rRpuX/TFSUqKoqmTZuiadOm0NPT410n5ebm8kYEV7aTVEpKCqKjo9GlS5dyk9t5eXmYOHEi0tPT4evrW+4k3NWJtUE1gyW4a5lwaP/kyZMxefJkZGVlwcvLCx4eHujXrx80NTW5ZLeRkVGtJrsLCgq4hIOpqSnExcWhpaXFG3b/8OFDSEpKcic9ZfX8rAtEhJiYGO4ksLzk9v379zFy5Ehs2bIFU6dO/a5jqczduv+KiIiAqKgod8FlYWGBlStXIj8/n2vUfX190aFDB+6ik92tY6pCREQEBgYGMDAwwJo1a/D06VN4eHjg2LFjmD9/Pnr16gU7OzuudJGTk1OVJsgtqxTS9/YSysrKQlhYGHR0dOpdbea8vDyEhISgSZMmvHrg/+3pnpqais2bN8PLywsSEhL4448/anWWboapK9LS0hg8eDAGDx6M/Px8BAQE4Pz585gyZQoEAgFsbW0xbNgw9O7dG506dUJ6ejpSUlK4mo/Cnt1VPf/4+vUrwsLCKjXEtiFJSkqqcK+llJQU2NrawsLCAkeOHIGYmBjk5OR4E2yXpzKj14RKqzXJMDVNREQERISLFy/iypUrMDExwcWLF+Hp6Yn169dDX1+fq+te3oSItUE4AW5Nl4yUlpbmRnTk5eXh/fv33Ig84YgaVVXVcm8yCpPbwl6e5X1+ly5dwty5c+Hm5sYbxVUbfH198fz5czx//rzYJNZFb7Jv2LABr169gri4OPT09HD27FmMGDGCW96jRw+4urpi1apV+OOPP9CuXTtcvHgRBgYGXMzSpUvx6dMnzJgxA5mZmbC0tISPjw/v37O8UXVM4yAcKaSoqIh3797hzZs38PDwwKZNmzBz5kxYWVnB3t4eNjY21XZT/3sIS0Gqq6vXWJtY0ojg1NRUJCQkFCulVF5uJyUlBVFRUejSpUu5cxnl5+djypQpePPmDfz9/Wv8xv5/sTaoZogQ6yZVb+Tk5ODq1avw8PDAtWvX0LRpU169ypq8CBPOhishIQFDQ8NSezMVrZ2UlpbGG2qipKRUpxeKwuR2RkZGhU4CQ0NDMWTIEKxbtw7z58+vtR+QoKAgBAcHo2/fvmjSpAmCgoKwaNEiDBo0iOtNkpWVhQ4dOmDAgAFYtmwZIiMj8euvv2LXrl1cHcrAwED07t0bW7Zs4e7Wbdq0CWFhYVyDtnXrVmzZsgUnT57k7tY9fvwY0dHR3OczaNAgpKSkcHfrpkyZAlNT0zJ7djKNDxFx9SqFE1Z27NgRv/76K4YOHQpNTc1q+RsR9hJKTU1FZmYmFBQUuDakIkNuMzMzER4ejjZt2tS7WcaFE6/IycmVmzgjIqxduxYuLi6YNm0a7t27h+zsbERERNTeDjNMPVJQUIB///0X58+f5ybGtbW1hZ2dHfr37w9JSUnu/CM1NRWioqJcz+6Knn98+fIFoaGhUFZWrlDypaFJTk7mei2Vd2H3/v172NjYwMDAAKdOnapyiZa0tDSkp6eXGdO6dWvuBl5iYiL69OmD7t27w8XFhffvNnHiRGRnZ3PlRgAgICAA/fr1Q0ZGBpSVlaGlpQVHR0fezf01a9bg4sWLePToEV6+fIk2bdogPDycu7kPAL1794aRkRH27NmD48ePY/Hixdyk3cC375+0tDTc3d1ZiZIfQGZmJq/eLRHhw4cPuHTpEjw8PHDz5k20adMGdnZ2GDZsGPT19Wv9GkcgEODx48f48uVLheYSqgkFBQVcu/v+/XuIi4tzZQT+2+4Kb/ArKChUaMJvLy8vTJkyBadOnWJ/c8wPJT8/H7m5ubyyJESEyMhInD9/Hp6ennj69Cn69evHjbBVVlau9XOWjx8/IiwsDC1atKizOQqEnaRSU1ORnZ0NRUVF7rrxv6NZUlNT8eTJE3Tp0qXcTocFBQWYNm0aoqKiEBAQUKXOXEz9xBLc9VTRepXe3t6Ql5fHkCFDYG9vDwsLi2odTpubm4uwsDDIyMigS5cuFT6BE9ZOSklJQVpaGoiIVzupNk8EhbXp0tPTYWJiUu7wvUePHsHW1hYrVqzA77//XqsNdlhYGH777TfExsYiNzcXurq6mDBhAhwdHXl3JR8/fow5c+bg4cOHaNasGebNm4dly5bxtuXu7o5Vq1YhISEB7dq1w7Zt22BjY8MtJyKsWbMGR44c4e7WHTx4EO3bt+diMjIyMHfuXFy5coV3t66+1wJjasaBAwe4xOvTp09x4cIFBAUFwdTUFHZ2drCzs4OWlla1lQkQnrRkZGRAXl6eO2kp6fuXkZGBiIgItG/fvtid7romTG7Lysqic+fO5Sa3N2/ejCNHjiAgIIArY5KXl8d6cTMMvt1MDwwMhIeHBy5cuIDMzEwMHDgQ9vb2+PnnnyEtLV3s/EPYdqioqJT491fXE9LWtJSUFERGRsLQ0LDc5HZGRgZsbW3Rpk0bnD17ttYm1yxaa/LUqVPFzmUPHTqElStXIiUlhdunP/74A56enoiNjQUArqb7lStXuPV69OiBLl26cJNMampq4vfff8fixYsBfBu9pqamBhcXF26SyY4dOyIkJIQbvXbjxg0MHDgQb9++bXDDcZnql5WVhStXrsDDwwPXr19Hy5YtuRG2hoaGNX6NU1hYiEePHiE/Px9du3atFxPgCgQCZGRkcJ2cil73NWnSBOHh4dzImPLa1+vXr2PChAk4fvw4Ro0aVUtHwDANAxEhLi4OHh4e8PDwQGRkJDfCdsiQIVBVVa3xc5isrCyEh4dDS0ur1BKrtS03N5ebryUjIwNycnLcud/nz58RGRmJzp07l5usLiwsxOzZs/Hw4UPcvn2blWVtZFiCuwEQ1qv09PTEpUuXICEhgSFDhnD1Kr/npEc4YYDwbntVT9iICJmZmVyyKj8/nzvpadasWY3WtxT+CKSlpVWoNl1kZCRsbGywcOFCrFy5stFd5DLM90hOTuZGEADf/r4SExO5SXL//fdfGBoaVnu9yvz8fO6kJT09nRsSK7xwSk9Px+PHjytUD7y25efnIzQ0FDIyMhVKbu/YsQN79uyBv78/DA0Na3FPGabhEQgEePDgAZfsTk5OxoABA2BnZ4eBAwdCXl6em6goNTUVhYWFUFVVhbq6OlRUVCAmJsbV7G/ZsmWd9UKqSZXptZSZmYkhQ4ZAU1MTHh4etXZTrWityZMnT/LOC4UXl2z0GlMfffz4kTfCtlmzZhg6dCiGDRsGU1PTak92FxQUICIiAkQEY2PjejkBbtHrvpSUFOTm5kJKSgrt2rWDqqpqmfvs7++PMWPG4PDhw3BwcGh07THDVCciwosXL+Dh4QFPT0+EhYWhR48esLOzw9ChQ9G8efNq/xsSjpZt3bo1tLW1q3Xb1SU/P58roVv0hpuOjk6ZJewEAgHmzZuHu3fvIiAgoN51mGK+H0twNzDCepUeHh64ePEiCgsLMXjwYNjb26NPnz6VulCpiQkDgG8N8cePH7mTnq9fv6Jp06Zc7aTq7IVARHj69ClSU1MrlNyOjY3FoEGDMHPmTKxbt46dVDFMJRAR0tLScPHiRXh4eCAgIICrV2lnZ1dtvSKL1v1///49xMTEkJ+fj9atW0NXV7de/d0Kk9vS0tLljoAhIuzduxfOzs64ceMGTE1Nv/v9MzIyMG/ePN4IjD179pQ5AuPr169YvHgx3NzckJubC2traxw8eJA3Kdvr168xe/ZsBAQEQF5eHpMmTcLmzZt5F623bt2Co6MjoqKi0KpVK6xatarUiXa3bNmCFStWYMGCBdi9e/d3H3d94O3tjfXr1+Px48eQlpZG7969eaUVquszPHDgAJydnZGcnAxDQ0Ps27cPZmZm3PKK/Hs2FgKBABEREdwQ3levXsHKygp2dnZcvcrs7GykpKRwN9sVFRWRmZkJHR0dtGnTpq4PodoJk9sV6bWUnZ0Ne3t7KCkp4eLFizVWz7ckLi4umDJlSonLil6KsNFrTH32+fNn+Pj4cCNsFRQUuBG23bt3/+4OPfn5+QgPD4eYmBiMjIzq/QS4wtFrEhISUFRURFpaGj5//sy77it6bfrvv/9ixIgR2Lt3LyZPnlyvzucYpr4jIrx+/Zq74X///n1069aNG2HbqlWr7/6bEo6WbdeuHVq1alVNe15z0tLS8PjxY7Rq1Qp5eXlIS0vj5jVTU1ODsrIyd20mEAiwePFi3LhxA7du3aq3yXvm+7AEdwNWUFCAu3fvwt3dnVevcujQobCysirzwqU2JgwAvjXEnz594npW5eTkVGqigPK2/ezZMyQnJ8PU1LTc+r3Pnj3DoEGDMGHCBGzevLnRTSzFMLWptHqVwl5NHTt2rJa/saSkJERHR0NRUREfP37k1f2vi3p0RQnnLpCUlCx3yDIR4fDhw9iwYQN8fHzQvXv3atmHQYMGISkpCX/99RfXC7Fbt25l9kKcPXs2vL294eLiAkVFRcydOxeioqK4d+8egG9D94yMjKChoQFnZ2ckJSVh4sSJmD59OjZt2gQAiI+Ph4GBAWbNmoVp06ZxE956e3sXmyjq4cOHGDVqFBQUFNC3b99GkeD28PDgPo9+/fqhoKAAkZGR3FDr6voMz549i4kTJ+Lw4cMwNzfH7t274e7ujri4OC6ZWd6/Z2NVtF7lhQsXEBcXh759+8Le3h62trZQVlbGvXv38PXrV0hISKCwsBDNmjWDuro6mjVrVi97RVaW8MKuIsntnJwc/PLLL5CSkoKXl1e5HQIYhinb169f4evry42wlZKS4o2wrWwbk5eXh7CwMEhJSaFLly71Prld2ug14XVfWloaVzP31q1b0NHRwbx587Bt2zbMnDmTJbcZ5jsIR9h6enrC09MTd+/ehZGREdfpqCodgt6/f19vR8uW5P3793j06BEMDAy4Th3CErrC3JNAIEB2djaysrIQFhYGHx8fBAQENMoOD8w3LMHdSBQWFiIoKIibnOnDhw+wtraGvb09BgwYwEv+1uVQ3ZImClBXV4eqqmqlLraICM+fP0dSUlKFktvx8fEYOHAghg8fjp07d7LkNsNUM2G9Sk9PT/j4+KBFixawt7f/rnqVSUlJiImJQefOnaGqqlpi3f/y6u7WlIKCAt7EvOUlt48fP46VK1fi6tWrsLS0rJZ9ENaRffjwIdcb3MfHBzY2NqXWkc3KyoKqqipcXV25GbhjY2Ohr6+PoKAgdO/eHdeuXcPgwYORmJjInTAePnwYy5YtQ1paGiQlJbFs2TJ4e3sjMjKS2/aYMWOQmZkJHx8f7rWcnBx07doVBw8exMaNG2FkZNTgE9wFBQXQ0dHBunXrMHXq1BJjquszNDc3R7du3bB//34A307cW7VqhXnz5mH58uUV+vf8ERStV+np6YknT56gQ4cOiIuLw7FjxzBs2DAu6ZKSkoIvX75ARUWFO/+oD/VtK0uY3C56YVeaz58/Y8SIESAibl4XhmGqT15eHm+ELRFxI2x79+5d7ghb4XxIFZnHoz6o6Oi1r1+/4vnz55g0aRJiY2PRqlUrzJgxAw4ODtDV1a3lvWaYxomIkJqayo2wvXXrFjp27MjNG1CRzozC0WCdOnVqEDWp09PT8ejRI3Ts2LHU/SUiZGVl4ezZs3ByckJOTg4GDBiACRMmYMSIEbU6io2pPfX715OpMDExMVhaWmL37t14+fIlbty4AW1tbTg5OUFHRwcODg5wd3fH1atXsWzZMmhra6Nt27a1fvdcVlYWOjo6MDMzg6WlJTQ0NJCWloZ79+4hODgY8fHx+PTpU5nbECa3ExMTYWJiUm5y+/Xr17CxscGQIUNYcrsRy8jIgIODAxQUFKCkpISpU6ciJyenzHW+fv2KOXPmoGnTppCXl8fw4cORkpLCi3n9+jVsbW0hKysLNTU1LFmyBAUFBbyYW7duoWvXrpCSkkLbtm3h4uLCW15YWIjVq1dDV1cXMjIyaNOmDTZs2IDGdH9RUVER48ePh6enJ1JSUrBx40a8fv0aAwcOROfOnbFixQo8ePAAAoGgQtt7+/YtYmJiYGhoyNWUFRUVRdOmTdGxY0f06tWLu6iKjo7G7du3ERkZydXgrUnC5La4uHiFypL873//wx9//IHLly9XW3IbAIKCgqCkpMQrdWJlZQVRUVEEBweXuE5oaCjy8/NhZWXFvaanpwctLS0EBQVx2+3cuTMvaWZtbY3s7GxERUVxMUW3IYwRbkNozpw5sLW1LRbbkIWFheHdu3cQFRWFsbExmjdvjkGDBvES1dXxGQqHfheNERUVhZWVFRdTkX/PH4GIiAj09PSwcuVKhISEYPv27YiLi0OrVq3w66+/wsbGBqdPn4aMjAwsLCzQvXt3KCoq4vXr17h9+zbCwsLw9u1b5OXl1fWhVIiwl1VFkttfv37F2LFjkZeXhytXrrDkNsPUAElJSVhbW+PIkSNITEzEuXPnICMjg9mzZ0NXVxczZ87E1atX8fXr12Lrfv36FSEhIZCXl28wye2iPc3L2l9paWnk5+cjOTkZ69atw/r16xESElLqOQrDMJUnIiICdXV1zJw5E9evX0dSUhLmz5+PkJAQWFhYwNzcHBs3bkRUVFSJ12FJSUncBI0NKbmtr69f5v6KiIhwpZNkZWVx4cIFrmRZY7oGZ/jq9y8oUyWioqIwNzeHs7Mznj59ijt37qBjx45wcnLCyJEjERgYiKCgIGRmZtbpH7e0tDRatWoFExMT9OrVCy1btkRmZiaCgoIQFBSEFy9e4OPHj7x9FE60kJiYCFNTU8jJyZX5HomJibCxscGAAQOwf//+en/SyFSdg4MDoqKi4OvrCy8vL9y5c4eblKo0ixYtwpUrV+Du7o7bt28jMTERv/zyC7e8sLAQtra2yMvLQ2BgIE6ePAkXFxc4OTlxMfHx8bC1tUXfvn0RERGBhQsXYtq0abh+/ToXs3XrVhw6dAj79+9HTEwMtm7dim3btmHfvn3V/0HUA02aNMHo0aNx9uxZpKSkYOfOnUhPT4e9vT309fWxZMkS3Lt3r9RE9Js3b/Ds2TMYGxujadOmJcaIiIhARUUFenp66NmzJ7p27QpJSUk8ffoUt2/fxuPHj5GcnFzsZsT3KigoQHh4OMTFxWFoaFjmEGIiwtmzZ/H777/D09MTffr0qdZ9SU5OLlaWQFxcHCoqKkhOTi51HUlJSSgpKfFeV1dX59ZJTk4uljQTPi8vJjs7G1++fAEAuLm5ISwsDJs3b67aAdZTL1++BACsXbsWq1atgpeXF5SVldGnTx9kZGQAqJ7P8P379ygsLCwxpug2yvv3/NEIBAKuZMDz58/x/PlzDBs2DBcuXIC+vj5+/vlnHD9+HOLi4jA3N0ePHj2goqKCxMRE3LlzByEhIXjz5g1yc3Pr+lBKJJxwt1OnTuUmt3NzczF+/HhkZWXh6tWrUFBQqKW9ZJgfl7i4OPr27YuDBw/izZs3uHz5MlRUVLB48WLo6uri119/xaVLl/D582fExsbiwoULUFZWhoGBQb2/ThGeA1WkNBsAPHnyBEOHDsXSpUuxevVqTJ48GRcvXsSYMWO+e190dHQgIiLCe2zZsoUX8/jxY/Ts2ZO75ty2bVux7bi7u0NPTw/S0tLo3Lkzrl69yltORHByckLz5s0hIyMDKysrPHv2jBdTlU42DFMTRERE0LRpU/z666/w8vJCcnIyli1bhpiYGPTu3RsmJiZYs2YNIiIiIBAI4O7ujsjISBgaGpZb6qw+yMjI4JLbzZs3LzOWiODs7Iy///4bN2/ehL29PVavXo3AwMBqKdPG2qD6qcZ+Rf/880/06NEDsrKyxS68hP77hRAREYGbmxsvpryekcC3CZh0dHQgLS0Nc3NzPHjwgLe8unppNkSioqLo2rUrBg4ciIyMDKxduxbjxo3D3r17oauri+HDh+Off/5Benp6nSa7JSUl0aJFCxgbG6NPnz7Q1dXFp0+f8PDhQ9y7dw9Pnz5FZmYmXrx4gXfv3sHExKTc5HZycjJsbGzQs2dPHD58uN6fNDJVFxMTAx8fHxw9ehTm5uawtLTEvn374ObmhsTExBLXycrKwrFjx7Bz507069cPJiYmOHHiBAIDA3H//n0AwI0bNxAdHY1Tp07ByMgIgwYNwoYNG3DgwAGup9/hw4ehq6uLHTt2QF9fH3PnzsWIESOwa9cu7r0CAwNhZ2cHW1tb6OjoYMSIERgwYECxtqoxkpWVxbBhw3Dq1CkkJyfj0KFD+Pz5M8aMGYP27dtj4cKFuHXrFvLz8wF8+6yeP38OY2NjKCsrV+g9hHfo27dvj59++gndunWDrKwsXr58idu3byMiIgKJiYnce1SV8MJOVFS03OQ2AHh6emL+/Pk4d+4cfv755wq/z/Lly0v8fSz6iI2N/a5jqWlv3rzBggULcPr06QYzBLCin7uw98vKlSsxfPhwru0QERGBu7t7HR8FIyYmhoCAAAwaNAgiIiLQ1tbGokWLcOfOHSQkJGDcuHHw8fFB586d0adPHxw+fBiFhYXo1q0bLC0toaamhuTkZPz77794+PAhXr16xd20qWsV7bUEfBsBMGnSJCQlJcHHx6fUc3GGYWqOmJgYevbsiT179iA+Ph7Xr19Hy5YtsWrVKmhpaaFHjx5wc3OrlsnhalplRq8BQHR0NIYMGYL58+dzv6/Vbf369UhKSuIe8+bN45ZlZ2djwIAB0NbWRmhoKJydnbF27VocOXKEiwkMDMTYsWMxdepUhIeHc6X1io7I2rZtG/bu3YvDhw8jODgYcnJysLa25vXGr0onG4apaSIiIlBSUsKECRNw4cIFpKSkYN26dXj16hWsra2hra2NadOm4e3btxW+5qpLwgkw9fT0KpTc3rNnD/bu3Yvr16+jc+fONbJPrA2qf2os45eXl4eRI0di9uzZZcadOHGC96Wwt7fnllWkZ+TZs2fh6OiINWvWICwsDIaGhrC2tkZqaioXUx29NBs6fX19nDp1CmvWrMHatWvx6NEjPH78GL169cLff/+N1q1bY+jQoTh69ChSUlLqNNktLi4ODQ0NdOnSBb1790b79u25odrx8fFQUVFBXl5emaUOUlNTMXjwYJiamuLYsWP1fqIW5vvU91INPXr0gJ+fH54+fQoAePToEe7evYtBgwZ955E3LNLS0hg8eDBOnDiB5ORknDx5EgAwZcoUtG3bFmZmZhg+fDjatWtX5WSMiIgImjRpgrZt26JHjx7o3r07FBQUvrsUQWFhISIiIiAqKgojI6Ny25TLly9j1qxZOH36NGxsbCr1XosXL0ZMTEyZj9atW0NDQ4P3Wwd8uwDNyMgoNfmloaGBvLw8ZGZm8l5PSUnh1tHQ0Ch2E1j4vLwYBQUFyMjIIDQ0FKmpqejatSvExcUhLi6O27dvY+/evRAXF6/xMjJVUdHPXXhS3bFjR25dKSkptG7dGq9fvwZQPZ9hs2bNICYmVmJM0W2U9+/5IyopkSIiIoIWLVpg7ty58Pf3x9u3bzFt2jTcuXMHJiYm+Omnn7Bnzx58+fIFpqam6NmzJzQ0NPD+/XuujFpCQgI+f/5cB0dUuV5LBQUFmDZtGuLj4+Hr6wsVFZVa2kuGYUojKiqK7t27Y/v27bhw4QJkZWVhaGiIV69eQVdXF6NHj8aZM2eQlZVV74bPV2b0GgA8ffoUQ4YMwbRp0+Dk5FRjyfsmTZpAQ0ODexTt/HT69Gnk5eXh+PHj6NSpE8aMGYP58+dj586dXMyePXswcOBALFmyBPr6+tiwYQO6du3KzXtBRNi9ezdWrVoFOzs7dOnSBf/88w8SExNx8eJFAFXrZMMwdaFJkyYYM2YMzp07hxUrViA3Nxe9e/fGypUr0bFjRyxduhSBgYH18hz9w4cPiIiIQIcOHcqdAJOIcPDgQTg7O8PHxwddu3atsf1ibVD9U2MJ7nXr1mHRokXl3i1RUlLifSmK9vSqSM/InTt3Yvr06ZgyZQo6duyIw4cPQ1ZWFsePHwdQfb00G7pmzZrBzs6Oey4iIoIOHTrgjz/+QEhICGJjY2FtbQ1XV1e0b98egwYNwqFDh/Du3bs6PckSExODmpoa5OTkICoqCn19fYiJieHJkye4c+cOoqKikJaWxkt2p6enY+jQoejYsSNOnjxZ6VnMmYanvpdqWL58OcaMGQM9PT1ISEjA2NgYCxcuhIODQ9UOuBGQkJDAgAEDcOTIEbx9+xbW1tZ4+fIlJCUlYW5ujhkzZpRar7Iy5OTk0Lp1a3Tv3h0//fQTrxTBw4cP8fr163Lfo7CwEOHh4QBQoeT21atXMXXqVJw8eZLX7laUqqoq9PT0ynxISkrCwsICmZmZCA0N5db19/eHQCCAubl5ids2MTGBhIQE/Pz8uNfi4uLw+vVrWFhYAAAsLCzw5MkTXvLc19cXCgoKXFLXwsKCtw1hjHAb/fv3x5MnTxAREcE9TE1N4eDggIiIiHp507Gin7uJiQmkpKQQFxfHrZufn4+EhARoa2sDqJ7PUPheRWMEAgH8/Py4mIr8ezLFlVavMjQ0FBYWFjAzM4OzszOys7NhbGzMlVHLyMjgyry9fPmy1oZ/VqbXUkFBAWbOnIno6GjcvHkTzZo1q5V9ZBim4qKiorBgwQLcv38fcXFxCA4ORteuXbF7925upN8///yDjIyMOk92V3b02osXLzB48GCMGzcOGzdurNGe6Vu2bEHTpk1hbGwMZ2dn3ujroKAg9OrVizfBp7W1NeLi4vDhwwcupqxOKvHx8UhOTubFKCoqwtzcnNcZprKdbBimLhUWFiI2NhZ37tzBzZs3kZSUhP379yMnJwejRo1Chw4dsGjRIty+fbteVDTIzMxEeHg42rdvjxYtWpQZS0Q4evQoNm7cCG9vb5iZmdXovrE2qP6p88zfnDlzMG3aNLRu3RqzZs3ClClTuB/C0v7BFy5cCOD/J2BasWIFt7yyEzB179691F6as2fPRlRUFIyNjWvq8OsFERERtGnTBkuXLsWSJUvw5s0beHh44MKFC1i+fDlMTU1hZ2cHOzs7aGlp1foQuvj4eLx69QqmpqZo0qQJgG+NV2ZmJlJTUxEbG4v8/Hw8fvwYEhIS+N///gddXV24urpCQkKiVveVqV7Lly/H1q1by4yJiYmppb2punPnzuH06dNwdXVFp06duBEpmpqamDRpUl3vXp1LTExEaGgowsLC0K5dOwQGBsLDwwOLFy9GZmYmBg4cCHt7e/z888/lTipbFhkZGejo6EBHRwdfv35FamoqUlNT8fTpUygoKEBNTQ1qamq89xD23CYidO3atdwLu5s3b2Ly5Mk4evQoRowYUeV9rQh9fX0MHDgQ06dPx+HDh5Gfn4+5c+dizJgxXO+Gd+/eoX///vjnn39gZmYGRUVFTJ06FY6OjlBRUYGCggLmzZvHTbwHAAMGDEDHjh0xYcIEbNu2DcnJyVi1ahXmzJkDKSkpAMCsWbOwf/9+LF26FL/++iv8/f1x7tw5eHt7A/jWo8HAwIC3v3JycmjatGmx1xsaBQUFzJo1C2vWrEGrVq2gra0NZ2dnAMDIkSMBVM9nCACOjo6YNGkSTE1NYWZmht27d+PTp0+YMmUKAFTo35MpW9F6lb/++isyMzNx5coVeHp6Yvfu3WjZsiXs7Oxgb28PIyMjFBYWIi0tDampqYiPj4eMjAzU1NSgrq4OeXn5aj9HqkyvpcLCQsybNw+hoaG4detWuTW6GYapG2PHjuU979y5Mzp37oy1a9ciLi4O58+fx5EjRzB//nz06tULdnZ2GDJkCFRVVWv1Oqyyo9cSEhIwePBgDBs2DM7OzjVaHnL+/Pno2rUrVFRUEBgYiBUrViApKYnrHZmcnAxdXV3eOkU7qSgrK5faSaVoJ5ai65UWU9lONgxTl8TExPDPP/9wz2VkZDB06FAMHToUeXl5CAgIwPnz57lrVFtbWwwbNqxYsrY2FE1ut2zZssxYIsI///yD1atX48qVK+jRo0eN7htrg+qnOi1KvH79epw7dw6+vr4YPnw4fvvtN96ka7U1AVNFemn+KERERKClpcXdtUtISICDgwNu3LjBlQzZuXMnXrx4USs9ChISEvDq1SuYmJhwyW3hfiorK6NDhw6wtLSEqakp0tPTsWrVKq50hIeHx3e9d0XqyFekdjurI191jaFUAwAsWbKE68XduXNnTJgwAYsWLWp0k+9Vlba2NiIjI6Gnp8fVq9y9ezdXr1JLSwurV6+Gjo4Oxo8fD3d3d3z8+PG73lNaWhpaWlowNTVFr169oKmpWax3ZnZ2Nh49egSBQABjY+NyL+zu3LkDBwcHHDhwoFomUKqI06dPQ09PD/3794eNjQ0sLS15td3y8/MRFxfHK6uwa9cuDB48GMOHD0evXr2goaEBT09PbrmYmBi8vLwgJiYGCwsLjB8/HhMnTsT69eu5GF1dXXh7e8PX1xeGhobYsWMHjh49Cmtr61o57rrm7OyMMWPGYMKECejWrRtevXoFf39/roZhdX2Go0ePxvbt2+Hk5AQjIyNERETAx8eHd85S3r8nUzn/rVe5YcMGvHr1CgMHDkTnzp3h5OSEt2/fcudErVu3xufPn/HgwQPcu3cPz549q7YSA5XptSQQCLBo0SLcvXsXN2/eLDcZzjCluXXrVqnzEDx8+BDAt/PzkpYLR8cKscmzKkdERAR6enpYtWoVQkNDER0djZ9//hmnTp1Cu3btYGNjg8OHDyMxMbHGr8MqO3rt3bt3sLW1xaBBg7Bnz54qJbcrMweJo6Mj+vTpgy5dumDWrFnYsWMH9u3bV28nCGYqjrVBdUdSUhLW1tb4+++/kZiYCDc3N0hLS2PWrFlo3bo1Zs6ciWvXrn33CNuKyMrKQnh4ONq2bVuh5PaZM2ewdOlSXLx4Eb17967Se7I2qBGgSli2bBkBKPMRExPDW+fEiROkqKhYoe2vXr2aWrZsyT1v164dbdq0iRfj7e1NAOjz58/07t07AkCBgYG8mCVLlpCZmRkREZ0+fZokJSWLvVe3bt1o6dKlREQ0ffp0GjBgAG/5p0+fCABdvXq1Qvve2AkEAkpJSaG//vqLBgwYQBISEtSlSxdycnKi0NBQysnJoU+fPlXrIzo6mry8vCgpKanc2JSUFLKwsKD+/ftTaGgobdiwgWbMmPFdx+zk5EQ7d+4kR0fHEr/DBQUFZGBgQFZWVhQeHk5Xr16lZs2a0YoVK7iYly9fkqysLDk6OlJ0dDTt27ePxMTEyMfHh4txc3MjSUlJOn78OEVFRdH06dNJSUmJUlJSuJhZs2ZRq1atyM/Pj0JCQqh79+7Uo0ePSu1LYxYdHU0AKCQkhHvt+vXrJCIiQu/evStxnczMTJKQkKDz589zr8XGxhIACgoKIiKiq1evkqioKO/f4q+//iIFBQX6+vUrEREtXbqUDAwMeNseO3YsWVtbc89VVFTo4MGDvJhNmzZRu3btqnjEP57CwkIKDQ2lFStWUIcOHUhaWpoGDx5Mf//9N717967a2qDMzEx6/vw53bt3jy5evEiXL1+m8PBwSkpKKvM9bty4QU2aNKEjR46QQCCo64+LYZhq9unTJ/Lw8KBx48aRoqIitWrVin777Te6ceMGZWdnU3Z2NsXHx9P9+/fpypUr5OPjQ2FhYVVun969e0deXl4UFxdXbuzHjx9p9uzZpK2tTS9fvqzrj4pp4HJzcykpKYn3mDZtGunq6nK/b/Hx8QSAbt68yYvLy8vjtnPv3j0SExOjbdu2UXR0NK1atYokJCToyZMnXMyWLVtIUVGRLl68SI8ePaKhQ4eSrq4uffnyhYsZOHAgGRoa0v379+nff/+ltm3b0tixY2vvA6kHBAIBJSQk0I4dO8jS0pLExcXJwsKCtmzZQjExMdV+HZadnU137tyhW7duUXZ2drnxL168oLZt29KUKVOooKCgyseZmppKMTExZT5yc3NLXDcyMpIAUGxsLBERTZgwgezs7Hgx/v7+BIAyMjKIiKhVq1a0a9cuXoyTkxN16dKFiIhevHhBACg8PJwX06tXL5o/fz4RER07doyUlJR4y/Pz80lMTIw8PT2r8jH88FgbVP8UFBTQ7du3af78+dSqVStSUFCg0aNH05kzZygtLa3a80CJiYnk5eVFMTExFYo/efIkycnJ0bVr177rOFkb1PBVKsFdlX/wyiS4vby8CACXOOrZsyctWLCAF3P8+HFSUFAgom+Nn5iYGF24cIEXM3HiRBo6dCgREfn5+REA+vDhAy9GS0uLdu7cSUTfEuuGhoa85S9fviQAFBYWVqF9/5EIBAJKT0+n48ePk62tLUlJSVHHjh1pxYoVFBwcTB8/fvzuRi0mJqbCye3U1FTq2bMn9erVi3Jycqr9eEv7DguTn8nJydxrhw4dIgUFBe7vYOnSpdSpUyfeeqNHj+YlP83MzGjOnDnc88LCQtLU1KTNmzcT0f8nYt3d3bmYmJiYEhOxZe1LYzdw4EAyNjam4OBgunv3LrVr14538vH27Vvq0KEDBQcHc6/NmjWLtLS0yN/fn0JCQsjCwoIsLCy45cIbBwMGDKCIiAjy8fEhVVXVEm9iLFmyhGJiYujAgQPFbmJMmjSJWrRoQV5eXhQfH0+enp7UrFkz7iYbUzkCgYAeP35MTk5O1LlzZ5KUlKSBAwfSoUOH6PXr1999offx40e6e/cu+fv707NnzygoKIiuXLlC169fp/Dw8GIJK39/f1JQUKB9+/ax5DbD/AC+fPlCly9fpsmTJ5OysjJpaGjQ9OnT6erVq5SVlUUfP36khIQEevDgAXl5edHVq1cpNDSU3rx5U6FzJOGFXWxsbIXaqwULFlCLFi3o2bNndf3RMI1QXl4eqaqq0vr167nXhMml/150FzVq1CiytbXlvWZubk4zZ84kom+/5RoaGuTs7Mwtz8zMJCkpKTpz5gwR/X8HhocPH3Ix165dK7MDQ2MnEAjo7du3tHfvXurTpw+Ji4uTqakpbdy4kZ48efLd50DZ2dn077//0q1btygrK6vc+Pj4eNLT0yMHB4fvSm5/r1OnTpGoqCiXODp48CApKyvzEp7CThJCo0aNosGDB/O2Y2FhUew7un37dm55VlZWid/RynSyYSqHtUH1S2FhIQUGBtLixYupdevWJC8vT7/88gv9888/lJKS8t15oKSkpEolt11dXUlOTo4uX75cp58La4Pqh0oluKuiMgnujRs3krKyMve8Ij0jzczMaO7cudzzwsJCatGiRbHk4Pf20mRKl5mZSf/73//I3t6eZGRkqF27dvT777/T3bt3q5TsFia3ExMTy419//499evXj3766SfKzs6ukeMr7TtckRsj7CZN7UlPT6exY8eSvLw8KSgo0JQpU+jjx4/ccuGJUEBAAPfaly9f6LfffiNlZWWSlZWlYcOGUVJSEm+7CQkJNGjQIJKRkaFmzZrR4sWLKT8/n9LT02ncuHHUpEkTkpOTIxUVFZKQkKDWrVvTiRMneNvIzs6mBQsWUKtWrUhMTIxERUVJQkKC7O3teTcliIhevXpFNjY2JCMjQ6qqqvT7779Tfn4+LyYgIICMjY1JUlKS2rRpU+z9iL4l9B0cHEhFRYWkpaXJwMCAd3LWWAgEAoqJiaGNGzdS165dSUJCgvr160d79+6l+Pj4Sl/oFU1uZ2Zm8i74EhISKDg4mLy8vOjatWs0b9482rRpEykqKtLOnTtZcpthfkC5ubnk4+ND06dPJ1VVVVJVVaXJkyfTpUuX6MOHD/Tx40d6/fo1PXz4kLy9vcnb25sePnxIr169KvEcqTK9lnJycmjp0qWkoaFRbAQlw1SX8+fPk6ioKL1584Z7TXhO1apVK1JVVaWffvqJLl26xFuP9UyreQKBgJKTk+nw4cP0888/k4SEBBkaGtKaNWsoLCys0udAwuR2QEBAhZLbr169IgMDAxo1alSxc9WaFBgYSLt27aKIiAh68eIFnTp1ilRVVWnixIlcTGZmJqmrq9OECRMoMjKS3NzcSFZWlv766y8u5t69eyQuLk7bt2+nmJgYWrNmTYk9fJWUlOjSpUv0+PFjsrOzK7GHb1mdbJjvw9qg+quwsJBCQkJo+fLl1L59e5KRkaEhQ4bQ0aNHKTExsdJtkDC5HR0dXaH4c+fOkZycHHl4eNTqcbM2qP6qsQT3q1evKDw8nNatW0fy8vIUHh5O4eHhXMLp8uXL9Pfff9OTJ0/o2bNndPDgQZKVlSUnJyduGxXpGenm5kZSUlLk4uJC0dHRNGPGDFJSUuIljaqjlyZTMdnZ2eTm5kYjR44keXl50tHRofnz51NAQECFkt2xsbHk5eVF7969Kzc2IyODrK2tyczMjDIzM2vsmEpLcFektA0rs9N4VWW4WnWUmqlI2ZuMjAzS1tamyZMnU3BwML18+ZKuX79Oz58/r/4Poh4RCAT0/Plz2rJlC5mbm5O4uDj17NmTduzYQc+ePSv3JOvjx49079498vPz4yW3S4qLj4+n/v37k4iICMnJydHUqVPp7t27df0RMAxTh/Lz88nPz49mz55NzZs3J2VlZRo/fjydP3+e0tPTKScnh968eUOhoaF07do18vLyouDgYEpISKDs7OxKXdjl5OTQqlWrSFVVlSIjI+v60JlGbNCgQTRo0CDea2lpabRjxw66f/8+PXjwgJYtW0YiIiK8BJOEhAS5urry1jtw4ACpqakR0bcLewCUmJjIixk5ciSNGjWKiIj+/PNPat++fbF9UlVVLVb67UcnEAjo/fv3dOzYMbKxsSFJSUnq1KkT/fHHH/TgwYNyr8OEN/grmtx++/YtGRkZkb29Pa+HYm0IDQ0lc3NzUlRUJGlpadLX16dNmzYV65j26NEjsrS0JCkpKWrRogVt2bKl2LbOnTtH7du35z4vb29v3nKBQECrV68mdXV1kpKSov79+1NcXBwvprxONsz3YW1QwyAcYbt69Wrq1KkTSUlJ0aBBg+jQoUP05s2bcq/DkpOTydvbm6KioiqU3L5w4QLJycmRm5tbrR8ra4PqrxpLcE+aNKnEGt3C3pPXrl0jIyMjkpeXJzk5OTI0NKTDhw9TYWEhbzsBAQFkZGREkpKSJfaMJCLat28faWlpkaSkJJmZmdH9+/d5y7+nlyZTdZ8+fatX6eDgQIqKitSyZUtevcr/NlJxcXF05cqVCiW3P3z4QIMHD6auXbtSenp6hfepOuvIswT3j6sqw9Wqq9RMRcreLFu2jCwtLb//QBswYb3KnTt3kqWlJYmJiZVZr/Ljx48UGBhYbnJb+Hjw4AE1bdqU1q5dS7dv36YFCxbQ/v376/qwGYbz9etXMjQ0LLF3UtET7pYtW9LWrVuLrX/u3Dnq0KEDSUlJkYGBQakn3BoaGiQtLU39+/enp0+f8mKKjnRRVFSkX3/99Yc54S6tXqWrqyulpaVRTk4OvXv3jsLCwsjHx4cuX75Mly5dovv375db8zYnJ4fWr19PTZs2pYiIiBo9DvY9ajyqcg785s0bEhUV5Y2ELc2ECRN45x4suVR3BAIBffjwgf755x+ys7MjGRkZat++Pf3+++907969Ysnu0kavlfZITEwkExMTsrW1ZaOdmQpjbdCPQyAQUHR0NK1fv56MjY1JQkKC+vfvT/v27aOEhIRi12HC5HZkZGSFktteXl4kJydH//zzDxtBy/DUeIkShiHi16tUUVHh6lV6e3tTZmYmHT58mNzd3ent27flNmiZmZlkb29PXbp0obS0tErtR3XWkWclSn5cVRmuVl3/juV9p4iI9PX1aeHChTRixAhSVVUlIyMjOnLkSBWOtHEQ1qvct28fr17lhg0b6PHjx5SRkUHbtm2jmzdv0ocPH8ptg0JDQ0lNTY1WrlzJTqqYemv+/Pk0aNCgYonJrKwsUldXJwcHB4qMjKQzZ86QjIxMsSGTbGKm6lNYWEhBQUFcvUo5OTkaNmwYnTx5klJSUsjPz4/++usvun37Nt24cYMuX75MgYGB9OLFi2I9KXNycmjz5s2krKxcK2Wn2Peo8ajKOfD69etJVVW1Qj109+/fTxoaGtxzVh6g/sjOzqYzZ87QiBEjSF5ennR1dWnBggV069YtSktLo5UrV9LNmzcrlNxOTk4mc3NzGjBgAO/vlGHKw9qgH5NAIKBnz57R5s2byczMjMTFxalXr160c+dOev78OQUEBND27dvpyZMnFUpu+/j4kLy8PB07doxdhzHFsAQ3U+vy8vLo+vXrNH36dFJTUyN5eXkSExOjDRs2lJtcysrKolGjRlHHjh15NdNrUnmTTJZVu53VkW+cqnI3v7p64pc3KoCISEpKiqSkpGjFihUUFhZGf/31F0lLS5OLi0vlD7aR+W+9SnFxcVJQUCBlZWW6c+dOucPnIiIiqHnz5rRkyZJiI44Ypr64evUq6enpUVRUVLGLN+GkN0UvIpctW1Zs0hs2MVPN+G+9SikpKRIXF6fBgwdTYmIiffz4kZKTk+nx48fk6+tLly9fprt379KdO3coPj6eduzYQYqKitzvf01i36Mfm0AgIF1dXVq8eHGF4qdNm0bGxsbcczZ5Vv2Uk5ND58+fp3HjxpGCggJJS0uTkpISXbhwodzRI6mpqWRpaUl9+/alT58+1fWhMI0ca4MaH4FAwJ3L/PTTTyQqKkpiYmLUq1cvio2NLfc67ObNm6SgoEAHDx5kyW2mRD9Mgnvjxo1kYWFBMjIypU56WV2Tu+3fv5+0tbVJSkqKzMzMKDg4mLdcWDJFRUWF5OTk6JdffqnSRHONwbFjx7jJCDQ1NUlJSYkcHBzI3d2d0tPTeQ1adnY2OTg4UPv27YsNJaoJ5dWRr0jtdlZHvmGp6NC5+p7glpCQ4H0/iIjmzZtH3bt3r+An8WPIz8+n4cOHk6amJvXr14+kpKSoY8eOtGLFihLrVUZGRlLLli1p/vz51Zrcrsrw++r6HWETljY+ycnJ1KJFC3r48CE3CVPRxOSECRPIzs6Ot46/vz8B4GZ+Z72easeTJ09IWVmZevfuTQYGBiQpKUkDBw7k1atMTU2lJ0+e0IQJE7gLwaVLl1JqamqN7hv7HjE3b94ssWQAEZGLiwu5urpyvS7//PNPEhUVpePHj3MxbPKs+i0vL4/s7e1JR0eHRo0aRcrKytS8eXOaMWMGXbt2rdjokffv31OfPn2oZ8+erEQQUytYG9S4RUVFkaqqKllbW1Pv3r1JXFycunXrRn/++SdFRkYWS3bfvn2bFBUVac+ePSy5zZTqh0lwOzk50c6dO8nR0bHEBHd1Te7m5uZGkpKSdPz4cYqKiqLp06eTkpISr2dtdUw011gsWLCA/Pz8iOjbcd+5c4cWLFhAWlpapKCgQKNGjSJXV1dKTU2lKVOmUJs2bej169e1sm/l1ZEnqljtdlZHvuGo6NC5+l6iREtLi6ZOncqLOXjwIGlqalb0o/ghpKWlkb29PZcYFtartLe3JxkZGWrXrh1XrzI6Opq0tbVp1qxZ1d5zm01YylQXgUBAAwcOpA0bNhARlZiY/Pnnn2nGjBm89YQ9dKOjo4mI1a2sLWfOnKF169YR0bd/u5iYGNqwYUOxepXx8fF0+PBhkpGRoZkzZ1L37t2pSZMmNTZCi32PGKJvIw6L/q4U5eLiQvr6+iQrK0sKCgpkZmbGm2NEiE2eVX9lZWXRlClTuHKPubm55OPjQ9OmTSNVVVVSVVWlKVOm0KVLlyg5OZl+/vlnsrCwoKysrDrec+ZHwdqgxs3f35/WrVtHAoGABAIBJSUl0aFDh8jKyookJCTIyMiI1qxZQ+Hh4XTv3j1SUlIiZ2dnltxmyvTDJLiFyis38b2Tu5mZmdGcOXO454WFhaSpqVms3MT3TjTX2AnrVf7+++/Upk0bkpCQIBUVFYqPj6/rXWOYKg1Xq65SMxUpezN27Nhik0wuXLiwWK9upnTZ2dnk5uZGI0eOJDk5ORIXF6dRo0ZVe3KbTVjKVERFR5fs2bOHfvrpJyooKCAilphsqIT1Krds2UJmZmYkKipK4uLidP36dS5G2Eu6Mtj3iGGYisjPzyc/Pz+aNWsWNW/enCQkJKht27bFOmkwDMNUN4FAQO/fv6ejR4+SjY0NSUhIkJiYGK1du5Ylt5lyiYIBAAQFBaFz585QV1fnXrO2tkZ2djaioqK4GCsrK9561tbWCAoKAgDk5eUhNDSUFyMqKgorKysuJjQ0FPn5+bwYPT09aGlpcTEV2ZfGTlRUFN27d4ezszOePn2K06dPw9XVFTo6OnW9awwDfX19DBw4ENOnT8eDBw9w7949zJ07F2PGjIGmpiYA4N27d9DT08ODBw8AAIqKipg6dSocHR0REBCA0NBQTJkyBRYWFujevTsAYMCAAejYsSMmTJiAR48e4fr161i1ahXmzJkDKSkpAMCsWbPw8uVLLF26FLGxsTh48CDOnTuHRYsWcfu3aNEi3L9/H5s2bcLz58/h6uqKI0eOYM6cObX8STVcTZo0wejRo3Hu3DmkpqZi+fLl+N///gdR0er92QwKCoKSkhJMTU2516ysrCAqKorg4OAS16mu35HyftMA4PLlyzA1NcXIkSOhpqYGY2Nj/P33399/4EylLF68GDExMWU+WrduDX9/fwQFBUFKSgri4uJo27YtAMDU1BSTJk0CAGhoaCAlJYW3feFzDQ2NMmOKLi+6XmkxqampvOUFBQXIyMjgYpiSiYiIoG3btli2bBnu37+PiIgI7Ny5EwMGDOBilJWVK71d9j1iGgodHR2IiIjwHlu2bOHFPH78GD179oS0tDRatWqFbdu2FduOu7s79PT0IC0tjc6dO+Pq1au85UQEJycnNG/eHDIyMrCyssKzZ894MRkZGXBwcICCggKUlJQwdepU5OTkVP9B1yPi4uLo168fDh06hDdv3mD37t3w9PSEkpJSXe8aw9QK1gbVHRERETRt2hRTp06Fl5cXkpOTsWrVKjg5OUFERKSud4+p7+o6w17bSuvBXR21b9+9e0cAKDAwkBezZMkSMjMzI6Lqq8PLMEzdKm+4mrDHW9GSNtVVaqYiZW+uXLlCBgYGJCUlRXp6enTkyJFqPX6metT3eu5swtKG5dWrV/TkyRPucf36dQJA58+fpzdv3hDR/08OmJeXx623YsWKYpMDsomZflzse8TUNW1tbVq/fj0lJSVxj5ycHG55VlYWqaurk4ODA0VGRtKZM2dIRkaG/vrrLy7m3r17JCYmRtu2baPo6GhatWpVifV3FRUV6eLFi/To0SMaOnRoifV3K1tGjGGYho21QQzTMDXoBHdFh1oWxRLcDMM0VPV9MkKhzZs3E4BitcJ/JGzCUqY+KKm0RGZmJqmrq9OECRMoMjKS3NzcSFZWtthFGZuYiRFi3yOmtmlraxeboLQo4Q2WoqUbly1bVuwGi62tLW89c3PzYjdYnJ2dueWZmZkl3mCpTBkxhmEaPtYGMUzD1KBLlFR0qGVFfM9QSwUFBcjIyKBZs2YQExMrd6hlXl4eMjMzy4wpb18YhvnxODg4ICoqCr6+vvDy8sKdO3cwY8aMMtdZtGgRrly5And3d9y+fRuJiYn45ZdfuOWFhYWwtbVFXl4eAgMDcfLkSbi4uMDJyYmLiY+Ph62tLfr27YuIiAgsXLgQ06ZNw/Xr14u938OHD/HXX3+hS5cu1XfgDVBFf5+qMvy+un5HyvtNA4DmzZujY8eOvBh9fX28fv26Ep8GU58oKirixo0biI+Ph4mJCRYvXgwnJydeW9KjRw+utJGhoSHOnz+PixcvwsDAgItZunQp5s2bhxkzZqBbt27IycmBj48PpKWluZjTp09DT08P/fv3h42NDSwtLXHkyJFaPV6mZrDvEVPTtmzZgqZNm8LY2BjOzs4oKCjglgUFBaFXr16QlJTkXrO2tkZcXBw+fPjAxZRVhis+Ph7Jycm8GEVFRZibm/PKfVW2jBhTtlu3bhUr/SB8PHz4EACQkJBQ4vL79+/ztsXKPzA1ibVBjRNrgxq5us6w17byJpn83sndzMzMaO7cudzzwsJCatGiRbFJJr93ojmGYX4s9X0yQiKijx8/Urt27cjX15d69+79Q/fgrig2YSnDMAzD8O3YsYMCAgLo0aNHdOjQIVJSUqJFixZxy9kkpw1Xbm4ur+xDUlISTZs2jXR1dbkJ5ISjRm7evMmLK1oSiZV/YGoSa4MaL9YGNW4/TIL71atXFB4eTuvWrSN5eXkKDw+n8PBwbnh/QUEBGRgY0IABAygiIoJ8fHxIVVWVVqxYwW3j5cuXJCsrS0uWLKGYmBg6cOAAiYmJkY+PDxfj5uZGUlJS5OLiQtHR0TRjxgxSUlLiJY9mzZpFWlpa5O/vTyEhIWRhYcFLFlRkXxiG+bEcO3aMlJSUeK/l5+eTmJgYeXp6lriOn58fASg2672Wlhbt3LmTiIhWr15NhoaGvOUvX74kABQWFkZERD179iyWrD5+/DgpKCjwXps4cSItXLiQiIgluCuhvOH3b9++pQ4dOlBwcDD3WnX8jlTkN+3BgwckLi5Of/75Jz179oxOnz5NsrKydOrUqRr+VBiGYZjGpCqlJYWOHTtG4uLi3A1allxqPPLy8khVVZXWr1/PvVZSWaT/YuUfmMpibRBTEtYGNS4NukRJZTg5OcHY2Bhr1qxBTk4OjI2NYWxsjJCQEACAmJgYvLy8ICYmBgsLC4wfPx4TJ07E+vXruW3o6urC29sbvr6+MDQ0xI4dO3D06FFYW1tzMaNHj8b27dvh5OQEIyMjREREwMfHB+rq6lzMrl27MHjwYAwfPhy9evWChoYGPD09ueUV2ReGYX4sycnJUFNT470mLi4OFRUVJCcnl7qOpKRksVnv1dXVuXWSk5N57ZNwuXBZWTHZ2dn48uULAMDNzQ1hYWHYvHlz1Q7wB1be8Pv8/HzExcXh8+fP3GvV8TtSkd+0bt264cKFCzhz5gwMDAywYcMG7N69Gw4ODjX8qTAMwzCNyfeUljQ3N0dBQQESEhIAfF8ZrqLLi65XWkxly4gxlXP58mWkp6djypQpxZYNHToUampqsLS0xOXLl3nLWPkHprJYG8SUhLVBjYt4Xe9AbXFxcYGLi0uZMdra2sXq5vxXnz59EB4eXmbM3LlzMXfu3FKXS0tL48CBAzhw4MB37QvDMA3f8uXLsXXr1jJjYmJiamlvqubNmzdYsGABfH19eXVTmYpRUVGBq6trqct1dHRARLzXqut3pCK/aYMHD8bgwYPLjGEYhmGYsqiqqkJVVbVK60ZEREBUVJS70W9hYYGVK1ciPz8fEhISAABfX1906NABysrKXIyfnx8WLlzIbcfX1xcWFhYAvt3k1dDQgJ+fH4yMjAAA2dnZCA4OxuzZs7ltZGZmIjQ0FCYmJgAAf39/CAQCmJubV+lYGL5jx47B2toaLVu25F6Tl5fHjh078NNPP0FUVBQeHh6wt7fHxYsXMXToUACld74o2jlD+FpZMZXtPMI0XKwNYkrC2qDG5Yfpwc0wDFMfNYbJCENDQ5GamoquXbtCXFwc4uLiuH37Nvbu3QtxcXEUFhZW+fNhGKZxSUhIwNSpU6GrqwsZGRm0adMGa9asQV5eHi/u8ePH6NmzJ6SlpdGqVSts27at2LbY5D4M0/gEBQVh9+7dePToEV6+fInTp09j0aJFGD9+PJc4GjduHCQlJTF16lRERUXh7Nmz2LNnDxwdHbntLFiwAD4+PtixYwdiY2Oxdu1ahISEcJ2QREREsHDhQmzcuBGXL1/GkydPMHHiRGhqasLe3h7At0mVBw4ciOnTp+PBgwe4d+8e5s6dizFjxkBTU7PWP5v6bPny5aVO3CZ8xMbG8tZ5+/Ytrl+/jqlTp/Jeb9asGRwdHWFubo5u3bphy5YtGD9+PJydnWvzkJgfFGuDGibWBjEAfrxJJuszbW3tYnWghJNTCj169IgsLS1JSkqKWrZsSVu3bi22nXPnzlGHDh1ISkqKDAwMyNvbm7dcIBDQ6tWrSUNDg6Slpal///709OlTXkx6ejqNGzeOmjRpQoqKivTrr79y9coZhql99XkywuzsbHry5AnvYWpqSuPHj+dNtMEwDHPt2jWaPHkyXb9+nV68eEGXLl0iNTU1Wrx4MReTlZVF6urq5ODgQJGRkXTmzBmSkZGhv/76i4thk/swTOMUGhpK5ubmpKioSNLS0qSvr0+bNm3izkmEil4TtWjRgrZs2VJsW+fOnaP27duTpKQkderUqdRrInV1dZKSkqL+/ftTXFwcLyY9PZ3Gjh1L8vLypKCgQFOmTGHXRCVITU2lmJiYMh/CycuF1q9fT6qqqryJ20qzf/9+0tDQ4J63atWKdu3axYtxcnKiLl26EBHRixcvSqyh26tXL5o/fz4RVW1+G6bxY21Qw8TaIIboB5pksiHQ1tam9evX82ZqzcnJ4ZazC76ybdy4kSwsLEhGRoYUFRVLjPnvDQQAXJF/oYCAADI2NiZJSUlq06YNnThxoth29u/fT9ra2iQlJUVmZma8yd+IiL58+UK//fYbqaiokJycHP3yyy+8iUaJvk18amNjQzIyMqSqqkq///475efnf9dnwDRu9Xkywv9ik0wyDFNR27ZtI11dXe75wYMHSVlZmXchsmzZMurQoQP3nE3uwzAM03AJBALS1dXl3dwsy7Rp08jY2Jh7PmrUKBo8eDAvxsLCothvwPbt27nlWVlZJf4GVKbzCMMwjQNrgxonluCuR7S1tYvdBSqKXfCVzcnJiXbu3EmOjo5lJrhPnDjBu4lQNLEvTOQ5OjpSdHQ07du3r1giz83NjSQlJen48eMUFRVF06dPJyUlJV4P2FmzZlGrVq3Iz8+PQkJCqHv37tSjRw9uuTCpaGVlReHh4XT16lVq1qwZL6nIMP9V3h184YzPAQEB3GvCmy3KysokKytLw4YNo6SkJN52ExISaNCgQSQjI0PNmjWjxYsXF7vZEhAQQEZGRiQpKUmtW7cu8cZPUSzBzTBMRa1cuZJMTEy45xMmTCA7OztejL+/PwGgjIwMImI9ZxiGqTnx8fH066+/ko6ODklLS1Pr1q3JycmJdw0mPOf670M4Qk6Ijawt2c2bNwkAxcTEFFvm4uJCrq6uXK/LP//8k0RFRen48eNczL1790hcXJy2b99OMTExtGbNmhI7dSkpKdGlS5fo8ePHZGdnV2KnrrI6jzBMbWPtT+1gbVDjxBLc9Yi2tjapq6uTiooKGRkZ0bZt23hJJnbBVzEnTpwoM8F94cKFUtddunQpderUiffa6NGjuVIMRERmZmY0Z84c7nlhYSFpampy5WSEZSHc3d25mJiYmBLLQhTt1X3o0CFSUFAoNnSGYepSVU5qqmsEQ3mjKTZt2kSmpqYkLy9PqqqqZGdnR7GxsdVy3AzD1I5nz56RgoICHTlyhHvt559/phkzZvDioqKiCABFR0cTEZGEhAS5urryYg4cOEBqampE9O3CAwAlJibyYkaOHEmjRo0iIqI///yT2rdvX2yfVFVV6eDBg99/cAzDNEgVKaUkTDDdvHmT13Gm6FD3H3lkbXnGjh3L6/xTlIuLC+nr65OsrCwpKCiQmZkZ77pKiJV/YBoj1v7UDtYGNU4swV2P7NixgwICAujRo0d06NAhUlJSokWLFnHL2QVfxZSX4NbU1KSmTZtSt27d6NixYyQQCLjlPXv2LNbr9Pjx46SgoEBERLm5uSQmJlYsST5x4kQaOnQoERH5+fkRAPrw4QMvRktLi3bu3ElERKtXryZDQ0Pe8pcvXxIACgsLq9wBM0wNqspJTXWMYKjIaApra2s6ceIERUZGUkREBNnY2JCWlhavtBPDMLVj2bJlJfYmKvr4by+Zt2/fUps2bWjq1Km819n5DsMw9c1/SykJE0z/7TRU1I88spZhmOrD2h+GqRjR6pmqkilNZWZzdXR0RJ8+fdClSxfMmjULO3bswL59+5Cbm1vHR9F4rF+/HufOnYOvry+GDx+O3377Dfv27eOWJycnQ11dnbeOuro6srOz8eXLF7x//x6FhYUlxiQnJ3PbkJSUhJKSUpkxJW1DuIxh6oOYmBj4+Pjg6NGjMDc3h6WlJfbt2wc3NzckJiaWuE5WVhaOHTuGnTt3ol+/fjAxMcGJEycQGBiI+/fvAwBu3LiB6OhonDp1CkZGRhg0aBA2bNiAAwcOIC8vDwBw+PBh6OrqYseOHdDX18fcuXMxYsQI7Nq1i3svHx8fTJ48GZ06dYKhoSFcXFzw+vVrhIaG1vyHU0RGRgYcHBygoKAAJSUlTJ06FTk5OWWu8/XrV8yZMwdNmzaFvLw8hg8fjpSUFF7M69evYWtrC1lZWaipqWHJkiUoKCjgxdy6dQtdu3aFlJQU2rZtCxcXF97ywsJCrF69Grq6upCRkUGbNm2wYcMGEFG1HDvDCC1evBgxMTFlPlq3bs3FJyYmom/fvujRoweOHDnC25aGhkaxvwfhcw0NjTJjii4vul5pMampqbzlBQUFyMjI4GIYhmGAb+c3KioqxV4fOnQo1NTUYGlpicuXL/OWBQUFwcrKiveatbU1goKCAADx8fFITk7mxSgqKsLc3JyLCQoKgpKSEkxNTbkYKysriIqKIjg4uNqOj2GY+ou1PwxTMSzBXcMqe8FXlLm5OQoKCpCQkADgx7zgq8wNgopYvXo1fvrpJxgbG2PZsmVYunQpnJ2da/AIGKbhqspJTWhoKPLz83knS3p6etDS0uKdLHXu3Jl3k8fa2hrZ2dmIioriYso6KStJVlYWAJR4AliTHBwcEBUVBV9fX3h5eeHOnTuYMWNGmessWrQIV65cgbu7O27fvo3ExET88ssv3PLCwkLY2toiLy8PgYGBOHnyJFxcXODk5MTFxMfHw9bWFn379kVERAQWLlyIadOm4fr161zM1q1bcejQIezfvx8xMTHYunUrtm3bxruxxzDVQVVVFXp6emU+JCUlAQDv3r1Dnz59uBtgoqL801ELCwvcuXMH+fn53Gu+vr7o0KEDlJWVuRg/Pz/eer6+vrCwsAAA6OrqQkNDgxeTnZ2N4OBgLsbCwgKZmZm8m2L+/v4QCAQwNzevxk+HYZiG7Pnz59i3bx9mzpzJvSYvL48dO3bA3d0d3t7esLS0hL29PS/JVFqHlqIdXoSvlRWjpqbGWy4uLg4VFRXWKYZhfgCs/WGYihOv6x1o7FRVVaGqqlqldSMiIiAqKso1KhYWFli5ciXy8/MhISEBoPQLvoULF3LbKe2Cz8jICMD/X/DNnj2b24bwgs/ExARA3V3wLV68GJMnTy4zprQbBBVhbm6ODRs2IDc3F1JSUqXeIFBQUICMjAzExMQgJiZW7g2CvLw8ZGZm8npx/zfmwYMHxbYhXMYw9UFVTmqqawRDeaMpZGRkeMsEAgEWLlyIn376CQYGBpU70O8g7OX+8OFD7kbAvn37YGNjg+3bt0NTU7PYOsJe7q6urujXrx8A4MSJE9DX18f9+/fRvXt3rpf7zZs3oa6uDiMjI2zYsAHLli3D2rVrISkpyevlDgD6+vq4e/cudu3aBWtrawBAYGAg7OzsYGtrCwDQ0dHBmTNnirU/DFNbhMltbW1tbN++HWlpadwy4e/fuHHjsG7dOkydOhXLli1DZGQk9uzZwxvBsWDBAvTu3Rs7duyAra0t3NzcEBISwvUGFxERwcKFC7Fx40a0a9cOurq6WL16NTQ1NWFvbw/g29/MwIEDMX36dBw+fBj5+fmYO3cuxowZU+LfLsMwDdvy5cuxdevWMmNiYmKgp6fHPX/37h0GDhyIkSNHYvr06dzrzZo1g6OjI/e8W7duSExMhLOzM4YOHVr9O88wTIPG2h+GqXmsB3c9ERQUhN27d+PRo0d4+fIlTp8+jUWLFmH8+PFc8nrcuHGQlJTE1KlTERUVhbNnz2LPnj28xm3BggXw8fHBjh07EBsbi7Vr1yIkJARz584FwL/gu3z5Mp48eYKJEyeWesH34MED3Lt3r84u+CrTI6wqIiIioKysDCkpKQDl9wiTlJSEiYkJL0YgEMDPz4+LMTExgYSEBC8mLi4Or1+/5vUae/LkCa+nvK+vLxQUFNCxY8cqHw/DVER1j4yoD+bMmYPIyEi4ubnV6vvW917uPXr0gJ+fH54+fQoAePToEe7evYtBgwZ955EzTNX4+vri+fPn8PPzQ8uWLdG8eXPuIaSoqIgbN24gPj4eJiYmWLx4MZycnHgjI3r06AFXV1ccOXIEhoaGOH/+PC5evMi7wbV06VLMmzcPM2bMQLdu3ZCTkwMfHx9IS0tzMadPn4aenh769+8PGxsbWFpaFiuZwjBM41CdpZRKYm5ujufPn3PPG9vIWoZhqo61PwxTC+q6CDjzTWhoKJmbm5OioiJJS0uTvr4+bdq0ib5+/cqLe/ToEVlaWpKUlBS1aNGCtmzZUmxbP+psrq9evaLw8HBat24dycvLU3h4OIWHh3P7ffnyZfr777/pyZMn9OzZMzp48CDJysqSk5MTtw3hxHZLliyhmJgYOnDgQLGJ7dzc3EhKSopcXFwoOjqaZsyYQUpKSpScnMzFzJo1i7S0tMjf359CQkLIwsKCLCwsuOXCSfYGDBhAERER5OPjQ6qqqrxJ9himpqSmplJMTEyZj9zcXDp27BgpKSnx1s3PzycxMTHy9PQscdvVNclqeRO+FjVnzhxq2bIlvXz5shKfQvWoyiR1p0+fJklJyWKvd+vWjZYuXUpERNOnT6cBAwbwln/69IkA0NWrV4mIqF27drRp0yZejLe3NwGgz58/ExFRYWEhLVu2jEREREhcXJxERESKrcMwTMPl5eVFZmZmJC0tTUpKSmRnZ8db/urVK7KxsSEZGRlSVVWl33//nfLz83kxAQEBZGxsTJKSktSmTRs6ceJEsffZv38/aWtrk5SUFJmZmVFwcDBv+ZcvX+i3334jFRUVkpOTo19++YV3XsQwDc3bt2+pXbt2NGbMGCooKKjQOtOmTSNjY2Pu+ahRo2jw4MG8GAsLi2KTvG3fvp1bnpWVVeIkbyEhIVzM9evX2SRvDNOIsfaHYaqGJbiZRmPSpEkEoNgjICCAiL7N+GtkZETy8vIkJydHhoaGdPjwYSosLORtJyAggIyMjEhSUpJat25d4oXevn37SEtLiyQlJcnMzIzu37/PWy680FNWViZZWVkaNmwYJSUl8WISEhJo0KBBJCMjQ82aNaPFixcXu+hkmLpUlZOazMxMkpCQoPPnz3OvxcbGEgAKCgoiIqKrV6+SqKgopaSkcDF//fUXKSgocDf1li5dSgYGBrxtjx07lqytrbnnAoGA5syZQ5qamvT06dPvP+Aili1bVmJ7UvQRExNT7xPcZ86coZYtW9KZM2fo8ePH9M8//5CKigq5uLhU/kNhGKZeOX/+PCkrK9OhQ4coLi6OoqKi6OzZs9xy4c10KysrCg8Pp6tXr1KzZs14N9OFN/YdHR0pOjqa9u3bV+KNfUlJSTp+/DhFRUXR9OnTSUlJideGz5o1i1q1akV+fn4UEhJC3bt3px49etTOB8Ew1ezt27fUtm1b6t+/P719+5aSkpK4h5CLiwu5urpyHQP+/PNPEhUVpePHj3Mx9+7dI3Fxcdq+fTvFxMTQmjVrSEJCgp48ecLFbNmyhZSUlOjSpUv0+PFjsrOzI11dXfry5QsXM3DgQDI2Nqbg4GC6e/cutWvXjsaOHVs7HwbDMLWKtT8MU3Uswc0wDMOUqryTmrdv31KHDh14vfmqYwRDRUZTzJ49mxQVFenWrVu8kz9hcvd7NJZe7i1btqT9+/fzYjZs2EAdOnSo6EfBMEw9lJ+fTy1atKCjR4+WGiO8mVi0J/WhQ4dIQUGBcnNziejbzcROnTrx1hs9ejTvZqKZmRnNmTOHe15YWEiampq0efNmIvr/G5vu7u5cTExMDO/GJsM0JCdOnCj15raQi4sL6evrk6ysLCkoKJCZmRnvb0DoRx1ZyzBM1bD2h2GqjiW4GYZhmFKVd1ITHx/PGylBVH0jGMobTVHayV9Joy5qSn3v5a6iolKsJ/mmTZuoXbt2VTxihmHqg+DgYAJAx48fJyMjI9LQ0KCBAwfyemZVx42y3NxcEhMTowsXLvBiJk6cSEOHDiWiit20YxiGYRiGYZiaxCaZZGrEgQMHoKOjA2lpaZibm+PBgwd1vUsMw1SBiooKXF1d8fHjR2RlZeH48eOQl5fnluvo6ICI0KdPH+41aWlpHDhwABkZGfj06RM8PT2LTUSira2Nq1ev4vPnz0hLS4Ouri7atm3LazP69OmD8PBw5Obm4sWLF5g8eTK3vru7Ozp06AApKSkYGBjA29sb9O2mLSZPngwigpOTE5o3bw4ZGRlYWVnh2bNnvH3IyMiAg4MDFBQUoKSkhKlTpyInJ4cX8/jxY/Ts2RPS0tJo1aoVtm3bxltekUl53717Bz09Pa4dVFRUxNSpU+Ho6IiAgACEhoZiypQpsLCwQPfu3QEAAwYMQMeOHTFhwgQ8evQI169fx6pVqzBnzhxuUtxZs2bh5cuXWLp0KWJjY3Hw4EGcO3cOixYt4vZvyJAh+PPPP+Ht7Y2EhARcuHABO3fuxLBhwyrzNWAYppJq+jzo5cuXAIC1a9di1apV8PLygrKyMvr06YOMjAwAQHJyMm+iWgDc8+Tk5DJjsrOz8eXLF7x//x6FhYUlxhTdhqSkJJSUlEqNYRim9rDrMIZh6hJrg5i6whLcTLU7e/YsHB0dsWbNGoSFhcHQ0BDW1tbFZuBlGIYBKt9mBAYGYuzYsZg6dSrCw8Nhb28Pe3t7REZGcjHbtm3D3r17cfjwYQQHB0NOTg7W1tb4+vUrF+Pg4ICoqCj4+vrCy8sLd+7cwYwZM7jl2dnZGDBgALS1tREaGgpnZ2esXbu22Ezmp0+fhp6eHvr37w8bGxtYWlryYvLz8xEXF4fPnz9zr+3atQuDBw/G8OHD0atXL2hoaMDT05NbLiYmBi8vL4iJicHCwgLjx4/HxIkTsX79ei5GV1cX3t7e8PX1haGhIXbs2IGjR4/C2tqai9m3bx9GjBiB3377Dfr6+vj9998xc+ZMbNiwoTL/RAzDVML3nActX74cIiIiZT5iY2MhEAgAACtXrsTw4cNhYmKCEydOQEREBO7u7jV9iAzD1FPsOoxhmLrE2iCmTtVtB3KmMSqvViPDMExRlW0zRo0aRba2trzXzM3Ni80K7uzszC3PzMwscVbwhw8fcjHXrl3jlRY5ePAgKSsrc7Vqib5NPsnqVzMMU5bvOQ+qaP1/f39/AkD//vtvsff+448/iIiVKGGYHxG7DmMYpi6xNoipS6wHN1Ot8vLyEBoaCisrK+41UVFRWFlZISgoqA73jGGY+qgqbUZQUBAvHgCsra25+Pj4eCQnJ/NiFBUVYW5uzsUEBQVBSUkJpqamXIyVlRVERUURHBzMxfTq1QuSkpK894mLi8OHDx++88gZhmmMvvc8SFVVFXp6emU+JCUlYWJiAikpKcTFxXHr5ufnIyEhAdra2gAACwsLPHnyhNdrytfXFwoKCujYsSMX4+fnx9sHX19fWFhYAAD3XkVjBAIB/Pz8uBgTExNISEjwYuLi4vD69WsuhmGYmseuwxiGqUusDWLqGktwM9WqIrUaGYZhhKrSZpRWM7ZoPVjha2XFqKmp8ZaLi4tDRUWl3Nq0Rd+DYRimqNo6D1JQUMCsWbOwZs0a3LhxA3FxcZg9ezYAYOTIkQCqr5a/o6Mj/v77b5w8eRIxMTGYPXs2Pn36hClTpgCo2LwCDMPUPHYdxjBMXWJtEFPXxOt6BxiGYRiGYRiGqRxnZ2eIi4tjwoQJ+PLlC8zNzeHv7w9lZWUA/1/Lf/bs2bCwsICcnBwmTZpUYi3/RYsWYc+ePWjZsmWxWv6jR49GWloanJyckJycDCMjI/j4+PAuYHft2gVRUVEMHz4cubm5sLa2xsGDB2vvw2AYhmEYhmF+aCzBzVSrZs2aQUxMDCkpKbzXU1JSoKGhUUd7xTBMfVWVNkNDQ6PMeOF/U1JS0Lx5c16MkZERF/PfyU4KCgqQkZHB205J71P0PRiGYYqqzfMgCQkJbN++Hdu3by81RltbG1evXi1zO3369EF4eHiZMXPnzsXcuXNLXS4tLY0DBw7gwIEDZe80wzA1hl2HMQxTl1gbxNQ1VqKEqVYVqdXIMAwjVJU2o7yasbq6utDQ0ODFZGdnIzg4mIuxsLBAZmYmQkNDuRh/f38IBAKYm5tzMXfu3EF+fj7vfTp06MD1kGQYhimKnQcxDFNXWPvDMExdYm0QU9dYD26m2jk6OmLSpEkwNTWFmZkZdu/ezavVyDAMU1R5bcbEiRPRokULbN68GQCwYMEC9O7dGzt27ICtrS3c3NwQEhKCI0eOAABERESwcOFCbNy4Ee3atYOuri5Wr14NTU1N2NvbAwD09fUxcOBATJ8+HYcPH0Z+fj7mzp2LMWPGQFNTEwAwbtw4rFu3DlOnTsWyZcsQGRmJPXv2YNeuXbX/ITEM02Cw8yCGYeoKa38YhqlLrA1i6hJLcDPVriK1GhmGYYTKazNev34NUdH/H3DUo0cPuLq6YtWqVfjjjz/Qrl07XLx4EQYGBlzM0qVL8enTJ8yYMQOZmZmwtLSEj48PpKWluZjTp09j7ty56N+/P1c7du/evdxyRUVF3LhxA3PmzIGJiQmaNWsGJycnzJgxoxY+FYZhGip2HsQwTF1h7Q/DMHWJtUFMXRIhIqrrnWAYhmEYhmEYhmEYhmEYhmGYymI1uBmGYRiGYRiGYRiGYRiGYZgGiSW4GYZhGIZhGIZhGIZhGIZhmAaJJbgZhmEYhmEYhmEYhmEYhmGYBokluBmGYRiGYRiGYRiGYRiGYZgGiSW4GYZhGIZhGIZhGIZhGIZhmAaJJbgZhmEYhmEYhmEYhmEYhmGYBokluBmGYRiGYRiGYRiGYRiGYZgGiSW4GYZhGIZhGIZhGIZhGIZhmAaJJbgZhmEYhmEYhmEYhmEYhmGYBokluBmGYRiGYRiGYRiGYRiGYZgGiSW4GYZhGIZhGIZhGIZhGIZhmAbp/wBNH0hEc9EtUQAAAABJRU5ErkJggg==",
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i0tJSxcTEuK1i86ZNm3XsNbVpqxpwsw8J4Fve7JtWWVmpzZs36+DBgxo6dKi9+tXizUW1qvePiopSVFSUunXrJmNMtTZt1jjJGgNFREQ0ynmYFXBL7EOCxkGg7UPeBkk7duzQjh071K9fP/Xo0aPafeoTZNckODi42sCqOfrfMnMA8B1vVoaUlJQoJSVFZWVlGjVqlGJiYqo9z9HWIIfDocjISEVGRqpr165uA6ucnJx69b+tqV7UNbBi5gDQvLwNkg4dOqT169crMTFRAwcO9Dj2qG+YVFVgYKDatWundu3aSTqyiq0x+99ax+ZNwM0qNqB5eBskbdmyRfv379eQIUOUlJRU7XmsulO19Vp9hIaG2v3/JbmtYtu8ebPKy8vr7H9b2+vWdB7mug8JATfQvLzZN62goEBr165VUFCQxo4dW+Pqsaqt1+rDU5u2/Px8ZWdnKyMjQ9u2bVNQUFC1VWyNEXBbYyCJgBsNQ6DtI94GSevXr1dxcbFGjhyp2NhYj8/lcDjkdDobJdi2eNP/1nVgVdOx1YSAG/Cd+gZJCQkJGjFiRI2rNFxnBDVGDfI0sPKm/219X4OAG/ANb4Ikp9OpLVu2aN++fRo8eLA6derk8bmq1p3GqEG19b/dtWuXCgoKqrVpqy/XgJs2bUDz8jZISklJUUBAgJKTkxUREeHxuepa7t8QDel/Wx+1BdylpaXsQwI0IW/3Tdu3b582b96sHj16qG/fvjWeg9R3hnZdAgICFBsbq9jYWPXs2VNOp9O+yF+1TZv1KywszD6n9Ian87Da2rRxHoaaEGj7QGVlpdLS0hQcHKwOHTp4/OK77p49fPjwWtt9NKTlSH156n9rndxZ/W8DAwPldDoVExPToP63LI0Dmp4VJG3cuFE9e/a0N+5w5bp79uDBg9W5c+dan7Opa1Bd/W9TU1MVFBSkiooKHT58WCEhIY0ecFvHwcAKODpOp1NZWVnav3+/+vXr5/E7VFhYqJSUFEnSmDFjFBkZWePzNfaJnCfe9L+1jjEzM1Px8fFH3aZNIuAGGpsVJO3cuVNBQUHq1KmTx+/Qvn37tGnTJnXv3r3GOlX1eaWmqUGe2rR56n8bERGhsrIy5efnN7hNm+v7qWkfEs7DgIazJjWuWbNG/fr189jKo6KiQhs2bFBWVpaGDx9ut4itiacwvDEFBATYwbUku01bdna29u3bp19//VVhYWH2JKDS0tI627RVVdsqNus8rGrAzUbbkAi0m5XrjKTMzEyFhYXZJ0cWT7tne/NFPZplbvXlOrCyZg4UFRVpw4YNKi0t1bp16+R0Ot127o6Ojm7wwKqmpXHMHADqxxoYOJ1O7du3z95UzVVRUZHWrl0rY4ySk5NrDZIsTXkxzZOa+t+uW7dOhw8fVlpaWr3731ZV19I4Zg4A9eM6I6m4uFjp6enq379/tfvt379fGzduVNeuXdW/f/86v1MN6V97tDz1v83IyNDWrVuVmpqq0tLSo27TJnm3DwkBN+Ad19WxeXl5CgkJ8Rgkbdq0SYcPH9awYcOqnad50hSrROp6PU/9b/fs2aOioiL98ssvcjgcbmOgxup/yz4kQMO57pt2+PBh9e7du9r3JTc3VykpKQoPD9fYsWO9On9p7nGQpzZtOTk59gq25cuXKzIy0m0VSXBwcL1ew9s2bZ5qENoWAu1m4hokSUdOQqoWm5p2z65Lc8zQruv1IyMjFR4ernbt2qlLly4qKCiwZy/Vp/9tba/hKeC2Zg5YS+OcTqeCgoLsq4QE3ID7IMBa2mZ9X1y57p49YMAAr8PZxm45Ul/WwCooKEgDBgxQZGRkk/S/rWlpnDVzQDoyayEyMtIeXFF/gOpt1qx/x11VVFRo8+bNOnTokI477jg7LK5LU89M8kZoaKg6dOigrVu3asyYMSopKbHHQFabttjY2Fr739amtlVspaWl9uzJiooKBQcHKzw8XEFBQYyBgP/PNUiyxkBVa0VeXp7Wrl2rsLAwJScnKywszKvntlo/Wv/f3DXIatPWsWNHFRYWasSIER7737qehzVW/1vXNm3SkRaVsbGxdqs2Am7A875pVWuQMUa7d+9Wamqq+vTpo169etWrfUdzX9h3FRQUpA4dOig3N1dRUVHq06ePWw60YcMGRUVFuZ2H1WcVm+RdwF1WVqbAwEBFR0dzkb8NIdBuYp6CJGtA4Bom1bZ7dl1cA+2WwLX/bbdu3ersfxsXF9doMwe2b9+ugIAA+4qn1YPbdVlKS/mcgOZQU79+1wGPtXt2enq6x92z6+Lri2pV1dT/1nX2QNX+t40xc6C0tFQrVqxQcnKyXW+sYJuZA2irqgZJnsZA+fn5Wrt2rUJCXzkYEQABAABJREFUQjR27FivgyTJvf60lBpk9b91bdNWtf+tFXC3a9dOUVFRjRJw7969W5KqjYFYxYa2ylOQZH1/rBpkjFFaWpq2bt2qXr16qU+fPvU+J/H0/75SU//bnJycWvvf1oen87Dy8nL99NNPGjNmjIKDg+1xEvuQoC2r7TzMqkFlZWVav3698vPzdcIJJ9itPbzVEi7sWxwOh8c2bdYYKDU1VSUlJYqOjnZbzV+f7Mt6napt2vbu3Sun02nXcFaxtQ0E2k2oto0frZMub3bProuvZ0fWxdv+t42xwZsku2CxNA5tneumR1WDDGsglZ+fr5SUFAUFBSk5Obne3z1LS7mo5ukYvOl/W7U9QENmDlgnatYy5pqWxrme3LWEzwxoCjUFSdJvq9SMMdqzZ4+2bNminj17qk+fPvUOPKrOTGppXNu0Ve1/m5OTo7S0NBljqm3wdjSr2IKCgtiHBG1ebedhAQEBqqysVFlZmTZs2KC8vDyNGDHCXkJfH76eHWmp6XVd+9+6tmmr2v/WtQY1tE2bdGQMZNV49iFBW+Y6BqqaOVi1IisrSykpKYqLi1NycnK9V5BarH/zW2IeFBISosTERHvCVElJiT0G2rJli0pLSxUTE+O2iq0hbdpcxzkS+5C0FQTaTaS2IEk68oUrKSnRjz/+WOfu2XVxLVwtrYB54qn/rRVwHzhwQFu2bGlw/1vXfzDqWhrHzAG0VrUFSRaHw6FDhw5pz549de6eXZeWUoO8fW1P/W+tmQPWwKoh/W9dT2i97f3GwAqtUW1BkvTbBbW1a9cqJydHxx9/vL2ioqGv5+n/faGu77DD4bn/rVWDrDZtDel/W3UMJNW8DwkBN1ozawzkujLElcPhUHFxsVasWKHo6OijCpKqBki+rkF1qan/bU1t2rztf1t1DOTpPMwaA0kE3Gi9XPdNk6pvumrdtnfvXqWnp+uYY45R9+7dG/zvb0u/qFZVWFiYOnXqpE6dOkmS2yq2/fv3q6KiQrGxsYqLi1O7du0UHR3tVW2oes7raaNt9iFpfQi0G5nrrOCaBlHWycvhw4fVs2dPr3bPrk1LaTnS0OLp2n5EOjKw8tT/1nXmQE2Dzpo+BwJutBV1BUnSke9YWVmZ9u7d69Xu2XVp6atE6hIaGqqkpCR7hUxxcXGD+t+69tCsytPSOGYOoDWqK0iSpIKCAlVUVKiyslJjx45tcJAktZwTuYZyOH5r09a9e3d75UxD+t/WNQaSqgfcpaWl9j4kbLQNf1c1SKrpPMz6N75///7q0aPHUf2ct7SWI/Vl9b+1xoJWm7b69r+tbaWMp/Owqhf5HQ422ob/87RvWlUlJSUqKytTZmamRo0apZiYmKN6TX8c+7iy2rR17txZxhgVFRXZM7itNiKu52HR0dH1HgNJ7qv4XfchcQ24XVvVMgbyDwTajcjbIGnTpk3KyspSfHy8+vfvf9Sv6+9hUlWe+t9aAffu3bu1cePGGvvfehvs1xVwS8wcgP/xJkjKzc3V2rVrJUkDBw486jBbank9tI9WffrfWgMra3mtt/VH8jxzgIAb/srbIGnnzp3atm2bHA6HRowYcdQ/0y0lTGqs2uep/61rm7ba+t/WdwzkeuzWhIzKysoaaxAnd2jJvAmSSktLtW7dOuXn56t9+/bq2bPnUb9u1YtqVTfcbk6N8f2srf/ttm3bqrVps/rf1nZR39Nx1rSKzToPqxpws9E2WrKa9k2rKiMjQ+vWrZPD4dCAAQOOOsyW/P/CviuHw6HIyEhFRkaqa9eubm3arCxIkttF/sjISLv21ncMVDXgdl3Fxj4k/oFAu5F4EyS57p7do0cPFRcXN9rrt4Tl/lLTnEwGBwe7zRyorf9tSUmJIiMj6/0adS2NY+YAWjJvg6Rdu3YpNTVVffv21YEDB+rdJ7omLWWVSFNwOKr3v7VmDmRnZ7v1v7VqT30/C08Bd00zBwi40RJVDZI8La8tLS3V+vXrVVhYqGOPPVZr165tlJ/f1nQi54mnNm1V+99abdqKiorq3ftWqnkMxD4k8AfeBkmHDx/WunXr1L59e/Xo0UMFBQWN8vr+1nKkvqr2v/XUpi0mJkZRUVGSjpwTH80Gb1LNbdrYhwQtkTeTGp1Op7Zu3ao9e/Zo0KBB2r17d6P9/Fa9sO/rTSEb+/mqtmmzVrFlZmZqx44d9jiptLS0XhOMXF+DgNt/EWgfJW+DJGv37N69e6t3797atWuXioqKGuUYWtvsyLrU1v82Pz9fubm5Onz4cL3737qqbWkcMwfQkngTJLnunn3iiScqPj5e6enpjTaLyLX2+LoGNfV30NPMAav/bUZGhowx+u9//+s2c8maOVCf16hpYFVaWuo2e5KlcfAlb4OkzMxMrVu3TvHx8UpOTrZP+hrjQlhrD5Oq8tT/1gq4i4qKlJeXp4yMDLcaVN+WLnWtYqsp4OYiP5qbt0FSamqq0tLSNHDgQHXp0kW7d+9u1FpRW7uN5tJctc9TmzZrDCRJ//3vf6tt8NaQzX4JuOEP6to3TZKKioqUkpIip9OpMWPGKCoqSnv27GmSGtTaORwOxcTEKCYmRj169HBr05abm6v8/Hy3MZC1iq0pAm72IWkZCLSPgrdBkrV79gknnGD3iW7MJWmteXakN1wHVuXl5YqOjlZYWJjH/rdxcXGKjY1tkoGVa8DtOnsJaAreBkmuu2ePHTvWbs9jXcFuTG3loporh+O3/rfx8fFas2aNjjvuOLf+t677BNTW/7a212DmAFoab4Ok7du3a9euXRowYIC6du3qNv5xOp31vuBclfWaLWEc5IvXd23TVlxcrOjoaEVGRtr9bwsLC+3+t9ZMb282eHNVn4CbfUjQXLwJkoqLi5WSkqKKigo7SJIa/zzM9f/b2jjIatMWExOj7OxsnXjiifZK2vr0v62N63mYa5s2NtqGr3izb5okHTx4UBs2bFDnzp3Vv39/++e4KbKgqv/f3Hzxuq5t2goKChQZGam4uDhlZ2frwIED2rJli0JDQ91alFht2rxV03mY60bb7EPiOwTaDeAaJFknUJ5+WLOzs5WSkqKYmJhqu2c3Zpjk+tptbRBVldPpVEhIiL1zbn3639ZHXQF3VlaWQkJC1K5dO2YOoNF5EyQZY7R9+3bt3LlT/fv3V7du3dzuExAQ0CQX1XxZg3xd/4wx9e5/GxcXp/Dw8Hq9Tl0Bd05OjoqLi9WtWzcGVmgS3gZJ69atU3l5uUaPHq3o6Gj7z1yD0cbSEmqQrzmdTgUFBXnsf5uTk1OtTZtr/9v6qC3gzs3N1d69ezVgwADatKFJ1DdI6tSpkwYMGOD2c97Y52FtaZVITawxkLWKzWrTVlv/27i4OEVFRR11mzZJ9ia3P/74o4YMGaKwsDACbjQJb87DKisrtXnzZqWnp2vo0KF2yx5LU2VBbXkcZIxxm0QkHfl7yMnJUU5Ojt2mLSwszG2iUUNXsUnu52GVlZVKSUlRUlKSOnbsSMDdTAi066lqAfMUZhtjtGPHDu3YsUP9+vXzuHt2U4RJTTHjsj5aQvGsOkPL4fC+/61V1Oo7sLJex3WgnJGRocjISEVHRzNzAI3KmyCppKREKSkpKisrq3H37MYc8PBzfISnGaL16X9r/apvD9yqA6vi4mLl5uaqS5cuLI1Do/I2SDp06JDWr1+vxMREDRw4sFpgaj2mMcZBnsZgvtASx0CS9/1vXdsDHE3AbYxRbm6uHA6HfZFfYqNtNA5vg6QtW7Zo//79GjJkiN0aw1VrnB3pa9a5qCuHo+b+t1lZWW79b60aFBER0eCA2+FwqKCgwA6Z2IcEjc2bfdMKCgq0du1aBQUFKTk52ePElaasQW2VpxoUGBhor2KTjrRps1aQ7N69Wxs3blRkZKTbRf6jWcVWVlZm15aqG21b52GurWrb8t9XYyHQrgdvgiRr9+zi4mKNHDlSsbGxHp+rsQc8VmgREhLSIpbd+kpd793hqLn/rbU81+FweNw5t77HYQ2aXGcOlJWVufW/ZWAFb3kbJFm7Z3fs2FEjRoyocePHxhxIGWOUkZGhioqKNh1QeFN7a+t/u2fPHm3atEkRERFH1f/W+vmw6orr0rjS0lKVlJSwNA715m2LkS1btmjfvn0aNGiQOnfu7PG5GnOGtnUMu3btUmlpaaNtduuPvKlBNfW/zc7O1v79+1VRUXFU/W+t+mP9so6rtjZt7EMCb3gbJKWkpCggIEDJycmKiIjw+FyNPQmoqKhIe/futVfv+oKvz/+8eX2Ho+b+t1abtqCgoGqr2Lx9X9a41hr/eNqHxDXgZh8SeMvbfdP27dunzZs3q0ePHurbt2+N/342ZhZkjFF6erqkI3WyLV9Uq+s7HBQUpA4dOqhDhw6SpPLycnsV244dO9zatFk1qD7jyprGQN7sQ0LA3TBtd9RfD9Y/gCUlJQoJCfFq9+zhw4fX+sPfWGFSRUWF9u7dq6KiIgUHB2v//v1KT09XfHy82rVr16B+rUfD11/C+g7mHI7f+t92795dTqdTBQUFysrKUmZmprZv396g/rdWMbNeQ/K8NI6AG96wZrxJR8IIb3bP7tKlS63P2Vgnc7m5ucrNzVVoaKh91TsnJ8ftO9NWAian01nv76xr/1vpyMDKmjng2v/WdXluXTMHXOuPVH0lkevSONeZA1VP7hhYwVJZWalDhw4pKipKwcHBHn8uCgsLlZKSIkkaM2aMIiMja3w+6/FHW4OMObLptvX6OTk5qqysVHFxsT0Oaki/Vn/VkEDL6n/buXPnGtu0VV3FVlvAXbX+SLW3aWOjbdTFaluRl5en+Pj4Gs/D9u3bp02bNql79+7q169frT+njXUeVlpaqj179qi4uFiZmZnKycmRw+HQpk2b7BpU31VX/qoh9adqm7bKykq7TZvV/9a1TVtd/W+tv9OaxkDsQ4KGcDqdOnz4sL3iwNP4uKKiQhs3blRmZqaGDx9uB6Y1aazzsIyMDBUUFMjpdGrXrl0qLCxUYGCgtm3bpnbt2ik2Nvao9yqpD19+ZxpyHhYcHKyEhAQlJCRIOlLTrfOw1NRUlZSUuLVpq+vzrGkMVFObNvYhOXptI2U4CtaMpP3792vPnj0aNWqUxyCp6u7ZdX2ZGqOIFRQUaM2aNZKk6Oho+6Skffv2ysrKsvu1ui5nb9euXb1n+/kTT0tN6iMgIMCeOSCp1v631gmep2VE1ix+TzwF3DXNHCDghjUjafPmzYqPj1evXr2q3cd19+zk5ORagyTL0c4MMMZoz5492rJlix2GFBUVSZLi4+OVnZ2t7du325uUWRfYGrIpa3209NlJdQkODq7W/9YaWHnqfxsbG1vtgkFdG+3VNLCyVgAwcwAW1xlJP//8s8aNG+dxDLF//35t3LhRXbt2Vf/+/ev8jjdGy5Hy8nKtX79eeXl5kqQBAwbYwVJ8fLyysrLssNt1DNScF/mb29HWIE9t2qr2vzXGuI2BqrZp83Qy5+l16tpo21plwj4kbZv1c5GVlaXU1FSNHTvWY5C0adMmZWRkaNiwYfa/n7VpjNmR1qbb1oZjxx57rHbv3q3s7GyFhobaMzUjIiLsMVBrvsjfGGMgT/1vq7Zpq63/rfVvSl2rdQm44Q3Xf5vS0tIUGhqqY445ptr9cnNzlZKSovDwcI0dO9ari1hHe1HNGKNt27Zp165dCg8PV/fu3ZWUlKS0tDSlp6errKxMmzdvVnl5ub13WFNf5PeHVSJ1CQ0NdWvTVlJSYo+BNm/erLKyMrdVbFXPa73Z7NzbgJs2bd5pnf+iNpKqS9s8fUlq2j27Lkc7kLJOHnv06KHIyEilpaXZx2Zd6bb6tVphSFpamjZt2nRUyyhq0xKWtzR2Ia2t/+3+/fvtnXOr9r/15oTOUtvAqrS0tMbZkwysWjfXIMna5MLTwOfAgQPauHFjtd2z63I0ffytWQhZWVkaMWKE3arH+uV6pdsaCGRlZdnL2ePi4uyTu4b0rG+pmmIgFxISUm3mgKf+t1a4FBsbW6/6I9Vv5kDVFiVovZxOpyoqKtxajFT9d76iokKbN2/WoUOHdNxxx9k/p944mgv7ubm5Wrt2raKiojR69Gh999139nMGBQWpa9eu6tq1q9uqq0OHDik1NdXesLmhPetr4+tadrQX9auyZqNV7X/ruoqkav/b2i7o1/Y63gTcXORvO1x/BlzHQFX/zvPy8rR27VqFhYVp7Nixtc7edXU09ccYo507d2r79u3q37+/pCMbUEpHxvEhISHq06ePpN9WXWVlZbld5LfCpaa+yN+cmmIM5KlNW039b+Pi4mpcxVgbbwNu9iFpW6q2WbN+NqreZ/fu3UpNTVWfPn3Uq1cvr38mjqYGlZaWKiUlRaWlpRo9erQ2bdpkP1dQUJBCQkI0aNAge9VVVlaWnQVJcsst6tuzviVrihoUFhamTp06qVOnTvbnadUg67zWumBwNGMgT+dh7EPiHQJtD6oGSdYskarhT227Z9eloWGS64651iyEAwcOSPJ8IlW1Eb612312dra2bt1qhyHWyV19eyW2NE19ZdDb/rdlZWXKz89v1J1zmTnQdngKkqrWoLp2z65LQy+q5efna+3atQoNDVVycrJCQ0O1a9cu+7tX9TmrDgSs2X5ZWVl2GFJ19mRD+fqiWnPMTKit/+2mTZtUUVGhoKAgRUREKCcnp0E1naVxbVvVIMn158G1Blm1ICQkpF5BkqUhs5NcV4ZYJ4/W995TDXJddWUtZ8/NzVVWVpb9b3ZkZKQ9BmrMi/y+0NQ1yOH4rf+t1aatav9bqzbs27evwW3vXANu2rS1PVWDJOvnwbVeWO2Gtm7dql69eqlPnz71DjEbch5WVlam9evXq6CgwN4rae/evfbPadUaVHXVletsv40bN9oX+a0xkD9f5G+OMVBt/W+tNm2SlJqa2uCaXtN5mNPptM/D2IekdfO0b1pAQIBdk6TfakF+fr5OOOEEe1WBtxpag6yVIe3atdPxxx9frT2Xaw1yXXVl7R2Wn5+vrKws+9/s4OBgt1a1/twiqTnGQNbnabVpKyoqsmv6nj17VFlZqa1bt6pDhw6Ki4tr0Iz4ugJuZnC7899RexPxFCRVLWLe7J5dl4aESUVFRVq7dq0cDofbjrmuz1XXc1bd7d4KQ7KysrR37145nU63gVVDNkT0peZe6lJT/1trxlpaWlqj7ZwrMXOgtaspSJLcL4Ll5+crJSWl1t2z69KQgZTVn7Jnz57q27evfWze1rOqs/2sMKRqiyTX2ZP+1CLJF0vtPPW/3bRpk92Oob79bz2pK+CWmDnQWngKkqrWINdQuWfPnurTp0+D/q7rOzupoqJCGzZsUHZ2tkaMGGFfWPZ2/CNVvyhthSGuvRKtpaTt2rWr1wUhX19Qs46hOWtQ1f63TqdT27ZtU2Zmpg4ePOjWps2b/reeuI5/JALu1s5TkCS5j4HKysq0YcMG5ebmutWC+mjI7Mjc3FytWbNGMTExSk5OtsfzVcdAtT1v1Yv8RUVF9uzJXbt22SseGroPki9/5hvSv/ZoVe1/m5mZqQ0bNqiysrJa/1trxW19+wnXdB7maR8SzsP8m2v7vaqbzwYEBNgbQlqhcmxsrJKTkxt0rlLfGlR1ZUi3bt08nofVdk7melHa9SK/68Q8K7do166d313kb+4xkMPhUGRkpCIjI+1Vgd99953i4uLsi2wOh8PtPKwh2Zqn8zD2IfmN//yENrHagiTpt4GUt7tn16W+M7TT09O1fv16denSpVp/SqtwNSQkrxqGFBQU2Cd3O3bscNtpul27dvU+EWluvu7dZM3ESE1N1cCBAxUZGVnv/rd18WbmgMPh0HXXXaerrrpKo0aNavT3icZXW5Bk/b6yslJ79uzRr7/+Wufu2XWpz0DK08oQV641qD51zTUM6dWrl73iISsry15KarVIsgZWzbmxSX019nL/+rJmDoSFhSkmJkbdunXz2P+2asDd2DMHJGnbtm167LHH9O6777aZAZW/qylIsgQEBKi0tFRr165VTk6Ojj/+ePtibkPUp154Whni+jyS5xnadakahriueFi/fr3fXeT39RgoICBAYWFhio6O1pAhQ+rsf2u1CKiP2gJu131IFixYoA4dOujPf/5zI75DNJXagiTpt/Om7OxspaSkKDo6WmPHjm3wRe/61B/X2eB9+/ZVz549q43PPP2/N8dghSG1XeR3nT1Z2/v19UU1X9cfSfbKsQEDBkhynxH/66+/Vut/GxMT0+CA29M+JFbAbYzR73//e73yyivq3r17o79PNL6q52GealBlZaW2bdumnTt36phjjlH37t0b/DNfnxrkaWVI1edqyPff9SJ/nz593C7yb9u2rUH7IPmyBrSEGiRJXbt2VUhIiJ0dZmdnKzMzU9u3b3fbJyAuLq5BLV9cV7FJ1du0VVRU6PPPP9fq1av19NNPN/bba3EItOXeYkSqHiRJv12V++GHH7zaPbsu3hYep9OprVu3au/evTXOBj+aQLvq80RHRys6OtpeSmqdiFg7TYeFhbnNnqw629jXRcQXswNqOg6rj15d/W/rs3OuJzUF3N9//73mzJnT2G8NTaCuIEk68veckZGhgwcPerV7dl28HUgVFhZq7dq19kU8T7PB67NKpDZVVzxYLZKysrLs70vVjU1a0izgljKQcg0Dqva/db1oac0cONpeep5O7tLT07Vq1aqmeHtoZHUFSa7327hxo2JiYo4qSLJ4e1GtppUhlpqW2jZE1Yv8hYWF9uxJ1xZJrrMnW5KWUINc+0d62//W9SJbQ1axWa/lOgZKSUmxQy20bHUFSdJvF/VXrVqlfv36qUePHkf1s+5t/alpZUjVY/NmdqQ3x1TTPkhVL/K3xBZJLaH+VN1DpOqMeNeA21P/24aMKz2NgfLz8/Xtt98e1aZ/aD5V902raQyUmZmp3NxcjRo1SjExMUf1mt7WipycHK1du7baypCanutoalDVi/wlJSX2GMgf9kHydQ2yvu9WLXBte9ejRw85nU7l5eUpOztb6enpSk1NdZs82tBxZdWAu7CwUGvWrNGGDRsa5421cC3nX0EfcQ2SXP8xclVRUaHt27eroqJCI0aM8Gr37Lp4M0Pb2nCysrJSY8aMUWRkpMf7NdUX17W3rfTbiYjV+3bDhg1uG5v4emaA5PtCZqlpU7ba+t9aO+e6Dqwa2v9WOlLMvN2kFL7hbZCUm5urvXv3KjAw0Ovds+tStRecJ9Y+AZ5Whriqb+sRb3lqkWQNrKwWSa6DAF9//339+paaNiTxdNGyav/boKAgt3Cpof1vCwsLW/xsVngXJBljtGvXLpWUlKhLly4aMmRIo/y91nVRra6VIVWfq7G/f64XhKzvS15enrKystwu8ltjoJCQEJ//vLeEi/q1bUrrqf+t6waTGzZsOOrAzgqXrBqEls1qHVPbGKi0tFQbNmyQMUYnnnii4uLijvp1vbmon5+frzVr1ig8PLzaypCqz+Vty5H6qO8+SL4+D2sJY6Da6o/D4ah20bJq/1trVY41Dmpo/9uCggJJOurQE03LdVKjtcrS0993RkaGdu3apeDgYCUnJzfKhaS6zsPqWhniqjEv7LsKCwtT586d3S7y17YPUluvQVUD7aqsllJxcXH2RUsr4LbGldaqnKPZuNxasdZWcqA2G2h7GyRZu2cHBwfL4XA0Spgt1V1sMjIytG7dOiUmJmrgwIF1ztptjBnadal6IuI623jz5s32Us/S0lJ79mRzFxVfFzJLbQMqV57631qf6d69e+3+t9bV0Pr0vyXQbtm8DZKs3bPj4+MVFBTUaJt11HYy53Q6tWXLFu3bt8/rfQKa47sXHh6uLl26qEuXLm6zja1lXFb/1oSEhAb1aj1a/lZ/PPW/tVblWMudG9r/lvrT8nkbJK1fv94OBzt06NBoP+O1jVmslSGBgYFe7RPQWKtEauN6IiK5zzZ23Yxs27Ztdhjb3C2SWkIN8rb+SNU3zHMN7Fz731rhUn0+U2pQy2adh1mtHmuqQYcPH9a6devs711jBYR1zdCua2VIVY0xO7Iude2DZF3M3rNnT4N7tR4Nf6s/ri1frA3zCgoK7Lq+a9cuORwN63+bl5cnSdSgFqymfdOq3mfr1q3as2ePEhMTVVZW1mirImo7D3NdGeLNhpNVZ2g3haqrPl1bJFl7Zri2HfPFPki+rkGubUO94dp+RJLdetO1p3lERIQ9/vH2M7VaH7WV+tMmA21vgyTrqljv3r2VlJSk//73v432RampiBljtG3bNu3atUuDBg1Sly5dvHquhvSvPVqus42NMVq1apUiIyOVn5+vtLQ0SXJbltKQpez15etCZh1DfQZUFofjt51zrcDOtf9tWlqa1/1vKysrVVJS0mYKmb/xJkiqunu29Q9cY6npZM7blSGumiNM8vSaVWcbf//99woNDbV7tYaHh7v1367vUvb6agmzI63jaOgmfa4Dq5r637rWoJousDA7suXyNkjKzMzUunXrFB8fr+TkZP3yyy+NOsaoqQZ5uzKkqua4sO+q6kX+7OxsrV27VuXl5Xav1tjYWHsM1BwtklrCGMhqudYQVQO7o+l/W1RUxBiohfI2SEpNTVVaWpoGDhyohIQEu4VDY3yPaqoVritDvG3vVnV2ZHOpOilm165dOnjwoLKysrR9+/Zm3wfJ1/uISDWvUPOG67jSatNmrWLLzMzUjh077HGSNQ6q6dy2oKBAISEhLaolDI5w7Tds/Zvp6e+wqKhIKSkpcjqdGjNmjHJycrR///5GO46axkDergxx5SnHamqe9kHauHGjysrKfLYPkq9rUG1jam9Ubb1ZXl5un4e5tmlzXcXm6dyWQLuV8zZI2rBhg/Ly8ux+adZme411suCpiJWWlmrdunUqKSnR6NGjFR0d7dVzNcVS2/qyevfEx8fbfcqsq3bWUvbg4GC33pONNdPUla8LmXUMUs3LTbx1NP1vraVubaWQ+QtvgyRr9+y4uDiNHTtWwcHBys/Pb9QwydPJXH1XhlR9rvru2N2YrM+yW7duioyMVEVFhdsGt4WFhdU2NmnsgZWv67ClsU74a+t/m5aW5jZzoGr/WwLtlsnbIGn79u3atWuXBgwYoK5du9ot2Rq7Brk+n+vKkKFDh9qhprfP5fpfXwgODlZAQIAGDhzotuIqKyvLviDtGi41xUX+llCDnE5no1089Lb/rTV5wvWiATWo5fE2SLIurFdUVGjMmDGKioqya1Zj1SBPk4BcV4aMHTvW6wDYGgM194X9qscQGhqqsLAwHXfccQ3aB+lotZT601jngQ6Ho8b+t4cOHbLbtHnqf5uXl6ewsDCffx5w59piRPK8b5r024X1zp07q3///goMDGyS87Cqz7d3715t3rxZvXr1Up8+fer189Mcq0RqExQUpLCwMEVFRalPnz4+2QfJ1zWoMeuPdGRc6TpxoqyszD4P2759u4qKiuzZ8NYKwqCgIHtio9ULvbVrObtpNTGrgJWWltYaZmdnZ2vFihWS9P/Y++8gSRL7vhP9lPemq9p7O97P7JheDEEYAksjCRIFUSQl8qgL6v5BHI+40JFgSAzxeHFgxIl85ImKQ+DuUUfFCUc+vqfgSQQEcQlwidnZmdnZmfbe++ry3mfm+6Mnc6qqq7uruqunG7v9jUAstrc6Kys781s/+/0yODioJPLyzVnLQKqQbILBIB988AE6nY4HDx5UXMwuPdZJaxfJkIOA7u5ubt68ycOHD7l48SIGg4G1tTUeP37Ms2fPmJ2dxefzKV8sR8VJExkcrJ90WMiTA52dnVy/fp2HDx9y/fp1bDYbPp+P58+f8/jxY/7mb/5GcbStJJn7N//m39Dd3Y3RaOTevXt8+OGH+77+z/7sz7hw4QJGo5GrV6/yne98p+i//1f/1X+lBAjy/955552i1wSDQX7+538eu92O0+nkv/6v/2ulCP9xhbwZksvlgL03Q+bn53nx4gV9fX3cuHFDSThqXUwqPJ4kSczNzTE8PMyFCxe4cuVKVcXewmLSaeEgrVZLQ0MD586d4969e7z99tu0t7eTyWSYmpri0aNHDA0Nsby8TDQarcl5nwb+gdoHVDLkidSBgQHu3r3Lw4cPlYB7aWmJR48e8eGHH/Lv/t2/49mzZxUny2ccdPyQm2nZbLbIM6T0fk2n0zx//hyPx8P9+/fp6OhQXqPRaI5tQjuVSvHs2TNCoRCDg4NVFbOhuJB9GjhI3rhqa2vj6tWrPHz4kJs3b+JwOPD7/cr39eTkJFtbW2QymZq872lo6h8X/8j6t62trVy+fJm3336bt956i4aGBuLxOKOjozx69Ijh4WF+53d+B7/fj9lsPvC4Z/zzZiDnYdlsdt9i9vb2No8fP8ZmsynFbKh9Hibzj8wXHo+HJ0+e4Ha7uXv3blXTzKXr/qeBg+RJ4t7eXm7fvs3Dhw8ZGBgo+r5+/vw58/PzBIPBAz1VKsFpiIGOi3/gtexUT08Pt27d4uHDh1y+fBmTycTW1hZPnz7lgw8+4Nvf/jb/z//z/1Qst3DGQW8G8lDjfnmYIAhMTEwwPj7O1atXuXTpkpIPHUceJnOFIAiMjY0xMzPDzZs3K5I5KsSbkBypFvLG1cWLFxkcHOT+/fs0NTWRSCSU7+vR0VHW1taIx+M14c2T3pQ9Tv6BnWva2NjI+fPnuX//Pm+//TYdHR3kcjlmZ2d59OgRH330EX/6p3/K2tpaRRz0ceCfT8SEdqUSI4uLiywuLpZ1zz6uQEoURZaXl1lYWOD8+fNFyWOlOE3FpL3OvXDSr6+vj1wup0zZLCwskEqldk1PHoYQTkswBbUvaJdiL/3bZ8+e8Rd/8RcADAwM8JnPfIZ/+S//JT09PbuO8ad/+qd89atf5Rvf+Ab37t3j93//9/niF7/IzMxM2a7eBx98wM/+7M/y9a9/nZ/6qZ/iW9/6Fl/60pd4+fIlV65cUV73zjvv8G//7b9V/r10Gv/nf/7n2dra4t133yWXy/FLv/RL/NN/+k/51re+VavLc2pQ6URSOp1WNjTKuWcfx3SkJElkMhlGRkbIZDJVbYaUO9ZJP3vyuZSDwWAomvSTjYDk6UmgaHryMGaIp+UaHHdAJWMv/dtvf/vbfP/73ycej3P37l3+1t/6W/yLf/Evyh7jjIOOH5VOJHm9XsbGxmhqauL27du7VqWPa0L7sJsh5Y51GuKgciid9JONgILBIBsbG0xNTWE2m4umJw+zqn4aOOgokiPVQKXarX+bSCTY3Nzk0aNHbG9v8+Uvf5nPfvaz/Mqv/Aqf/exndx3jjH/eDOQYqLCZVgpBEJiZmWFzc7Osd4fMW7UcLJLfd25u7lCbIYXHOm3FpFLs5YMUDAaZmpoil8vtmp78YYyB3lT8A3vr337nO9/hL//yL/H7/Vy4cIHPfOYz/M7v/E5ZM9MzDjp+VOqbFo/HGR4eRqvV8vbbb+/y7jiuPCyRSDA0NKS872GkgUpjn5OKg/Z733I+SMFgUPFBkrcd5DjoMNfhpDnoKJJHh0Gh/C/sDIeEw2EmJycZHR3l5cuXPHv2jJ/7uZ/jn/7Tf7rr9z8u/POxL2gXrvfvlcTJUh+pVIq7d+/icDh2veY4JrQBhoaGlKS/3PtWeqw3rR15VOh0OhobG5WHRV4jDQaDyhppof72XlrRpThpIoPqDQFqBXka45133qGpqYkvfelL/NEf/RF//dd/veeU0u/93u/xy7/8y/zSL/0SAN/4xjf49re/zR/90R/x67/+67te/wd/8Ae88847/LN/9s8A+O3f/m3effdd/vAP/5BvfOMbyutkgi2Hqakpvvvd7/L8+XPu3LkDwL/+1/+an/iJn+Bf/at/RWtr65Guw2lCpYUkuaDT0NDArVu3yhYyDnLDrhYqlYp0Os0HH3yAy+Xa830rPVbhtPdpR2khRBRFJbDyer3Mzc2h1+uLikuVSCSdBv6BN5vQFUKexvit3/otZdri05/+ND6fb8/fOeOg40UlhSRZ6mN9fZ3Lly/v+fmPI5nb2toiGAzu+76VHus0bKpV+vyXFkJyuRzhcFjRvpWb/HJyV2mT/zRw0Enxj0q1I9N27tw5/uIv/oLW1lb+9//9f2dtbW3PbZEz/jleVFNIGhkZQa1WMzg4uGfMWksOku/R58+fI0nSvu97EE7jhPZBKPVBSqVSBINBRVIMKJLSqEQi6ZPMP/Ba//Yf/+N/TDqd5pvf/Cb/6l/9K37wgx/sKQF5xkHHi0qHGuXGcldXF/39/WXvoeOY0E6lUjx58oT29nbOnTt3JP33095UK4S8dW6z2RQ5n1LPnsP4IJ00B50k/8BrX4Vf//VfZ319nc9//vO0t7d/7GOgj21Bu9JCkuye7Xa7uXnz5p4FHZkAa0Vk8li9HEQdRcfstExHHiWAK9VJlM0Qg8EgS0tLRWZl8vRkufc/Dddhv6D9TSEej2O1Wvnc5z7H5z//+bKvyWazvHjxgq997WvKz9RqNZ///Od58uRJ2d958uQJX/3qV4t+9sUvfpE///M/L/rZe++9R2NjI3V1dXz2s5/lf/qf/ifF4ODJkyc4nU6FxAA+//nPo1arefbsGX/37/7dw3zkUwe5kLTfxH6he/ZBJrC1DKQkSSIQCBCJRLh06dKhNkMKcVqaaod9b7VarUxPdnd3K2aIwWBQcZm2WCxKgVvWKCv3/ifNP/DmJiT3QyKRoKenh3/0j/7Rnq8546DjQ6WFpEQiwcjICLAjs7afTFUtOSiTyRCLxdBoNEWyAofFaYmDDovSbYdCreiJiQmlyS/HQHs1+U/DNTjphE4+h2Qyyd27d/mH//Afln3NGf8cLyopJAFsbGwwOTlJR0fHgQWdWjb2A4EAsOM1UygrcBiUK5D9MEGWSDKbzcq2w2F8kE563V8+h5OOf2AnD7PZbPzUT/0UP/VTP1X2NWccdLyoxDdNNjIMBAIHmsDWMgYSRRGPx0MsFuPGjRuH2gwpROFnO+lc7DAorPP09vYW+SAVakUf5IN00jHQaYh/AEVDu7u7WylWl+LjxD8fy4K2PG2n0WhQq9V7FpIK3bPb2toOfABqQWSSJLG6usrMzAwA165dq4kpx2mYTKoV5Ckb2QxRFEUlsNre3mZ2dhaDwVAUWOn1+lPTmTwNZJZIJA6cavf7/QiCsOtLtKmpienp6bK/4/F4yr7e4/Eo//7OO+/w9/7e36Onp4eFhQV+4zd+gx//8R/nyZMnaDQaPB7PrjUWrVaLy+UqOs4PK+QkLh6PYzQa9wyiSt2zDyro1CqQymazjI2NEQ6HsdvtdHZ2HvmYhbJHHweUmiEWSiTNzc2RTqex2+0KB9ntdkVG6qSffThdHLQfzjjoeCBJEtFoFEEQMJlMe3LQ5uYmExMTtLe3c/78+QPvmVpxkGx6q9Fo6OnpqYl58WmQXqvl+5Y2+ZPJpDI9uby8rGi5yjGQ3OQ/6WQOTkdRK5lMIknSvhJaZ/xzfBBFke3tbUwm057GePl8nsnJSXw+Hzdu3FCaOfuhFhwkiiLz8/OsrKwAKIZvR8Fpmo6sxfsXSiQVNvlDoVBRk79wglur1Z4a/jnp+Ad2CtoHTfyfcdDxQJZT3Nraoqmpac8YKBKJMDIygslk4u233z5wE7NWMVAqlWJ4eJhMJoPdbj9yMRtOj+SIfC5HheyDJH8vZDIZJQbaTyLppDnotPCPIAikUql94+uPE/98rArahVq1f/M3f8Pg4GDZP2Q59+xKcFQiy+fzjI+PEwqFuH37trLmdlSclunI40KhVnRPTw+CICiruSsrK0xMTGC1WhVtslquAx0Gp4HMkslkRYaQx4HCaairV69y7do1+vr6eO+99/jc5z53Iuf0piAXs71eL1NTUzx8+LDsF+vW1hYTExNF7tkHoRaBVDgcZnh4GLvdzsDAAFtbW0c6XiE+Tk21UpRKJKVSKaXAPTY2hiiKOJ1ORFFEp9OdaEAlb6qcBg6qRaHyMPgkc5A8kbS4uIhKpeLixYu7XpPP55mamsLr9XL9+vWKXdCPykGFXiXnz5/fV4rmsMcv/OfHBYUSSfs1+eUYKJfLHUp7slY4DROSyWQS4EQ46JPMP/JmSC6XY2JiggsXLpTdqIxGowwPD2M0GqvSjD0qB8leJdlslnv37vHBBx/UdPMNPj5NtUJU6oOkUqkU8+CTikFOA//AWR52UpDzsEQiwdjYGM3NzWU3KFZWVpibm6O3t5fe3t6KYvZa5GGyV0lzczMOh4ONjY0jHa8QH2cOqtQHSZIk0un0oXyQaoHTUAOCygrax4WT4J+PTUG73GpbuYfK4/EwPj5OS0sLFy5cqOpL7yhEFovFGBoawmQyMTg4qLiOnhW0q4dGo8HtdiurC7IRmbw++PTp011duzdJLqeBzOLx+IGBVH19PRqNhu3t7aKfb29v76l71NzcXNXrAXp7e6mvr2d+fp7Pfe5zNDc34/V6i16Tz+cJBoP7Hue0o1CrVqPRKJq1hRAEgampKba3t6s2HzoK/8ibIbOzs/T399Pd3Y3H46m5J8AnhYNkjbLW1lZFIikYDLK+vk44HOb9998v2iApl9AfF96UKe1BSCQSZxz0BlFYSJIkCa1WSy6X2/W6WCzG8PAwer2+avMhtVpd9piVQN4MKfQMCQQCNeOL0zCZ86awV5NfjoGeP3+O1WpVJif3kkg6LpyGGCiRSKDVaveduDvjn9qiXB5WGmMUxiI9PT309fVV9czKxdLDIBAIMDIyQn19Pbdu3VLyv1rmYTI+7nHQXj5Iq6urxGIxfvCDHxzKB6kWkAcLThqJROLACe0zDqotSmOgcs+hHIvEYjHu3Lmj+FhUgqPkYYXKALJnyNbWVk3zsNMivXrc2MsHKRAI4PP5GBkZOZQPUi1wGuIf2HmeDypof5z45+SveA0gTyTl83nF9EguKMkQBIHJyUnGx8e5cuUKly9frrqDe1gi29jY4OnTp7S0tHDnzh0MBoNCNrUgstNURDoJEpWNyAYGBgC4c+cOTU1NJBIJRkdHefToEaOjo6ytrSlGZceJ0zAdUEkxSa/Xc/v2bb73ve8pPxNFke9973s8ePCg7O88ePCg6PUA77777p6vB1hfXycQCNDS0qIcIxwO8+LFC+U13//+9xFFkXv37h342U4bZL3+TCajuBtrtdpdz3Y8HufJkyfE43EGBwerXjE7bCKXz+cZGRlhcXGRO3fu0NPTo/DkcRSTTpqL3jQHyRJJnZ2dNDQ00NbWxtWrV7FYLGxtbfH06VOePHnC9PQ0Xq+XbDZ7rOdzmgraB00GnHFQbSAXkuRic7kYSC4kPX36lObmZt56662qp3gPGwOFw2E++OADVCoVg4ODigF2rTlI/ucP+6pttZCb/L29vQDcv39fkQmYnZ3l0aNHvHjxgqWlJcLh8LFvsZ2GhE5u6u/39zjjn9pBEAQymcy+eVgul2N4eJjFxUVu375Nf39/1c/LYThIkiQWFhZ4+fIlAwMDXL16Fa1Wq3gr1bqg/XEvJpWDLJHkdruVXNftdhMKhXj58iXvv/8+4+PjbGxskEqljvVcTgP/wFkM9CYhx0DZbFbJReQmbiEHBYNBHj9+rMQi1RSz4TX/VMsZ6XSa58+f4/P5ePDggWJ6dxwxkIyTzsXeJGQfpK6uLmAnBrp48SI6nY61tTUeP37Ms2fPmJubw+/3K/56x4HTwj+CIBy4JfJx4p8f6gnt/UyPCgOpSt2zD0K1gVThNGY5o4FaEdlpSeROGvJnN5vN2Gw22trakCSJeDyuTHAvLCyg1WqLpidrvZp7GsiskkAK4Ktf/Sq/+Iu/yJ07d7h79y6///u/TyKRUAwEfuEXfoG2tja+/vWvA/Arv/IrfPrTn+Z3f/d3+cmf/En+5E/+hI8++ohvfvObwM6z9lu/9Vv89E//NM3NzSwsLPA//A//A/39/Xzxi18E4OLFi7zzzjv88i//Mt/4xjfI5XJ85Stf4R/+w3/4Q+esvZfpUaFxUaXu2QfhMKa0pZshhR3qWvLFJ517ZMjNLKfTidPppKenh3w+TzgcJhQKsbS0pDybhQaTtWyAnYaCtjy1fsZBxw95Imm/GEhe/w+FQty6dUvZbqoW1cZA5TZDSo2Laj2dJL/vJxHy59br9WUlkuQtElkiSeaggwq/1eI0xECVbKnBGf8cFXJDXy4QlHKQ/HyHQiFGRkaw2Wy8/fbbypZqtaiWM7LZLKOjoyQSCWUz5CjH2++8Cv//J62pJkOWO6vEB6lwevKw90M5nIahItiRHKlEzuuMg44GeTu2NPaV/ykIAlqtloWFBZaWljh37hydnZ2Hek7kY1YzBV24GXL79u2ibanjioFOmoNOCvJnlvWYq/VBqgVOQ/wDrwva+/mIwMeHf35oC9oHuWfLBSXZPbuzs5OBgYEj3WTVJHOJRILh4WE0Gs2ea721nAyQA4bj7DodhJMmT/n9C//GKpUKm82GzWajs7MTURQVY5ONjQ2mp6cxmUxFxiZHXVU7DWRWyYQ2wM/8zM/g8/n4zd/8TTweDzdu3OC73/2uMj28urpa9FkGBwf51re+xT//5/+c3/iN32BgYIA///M/58qVK8BOAjM6Osof//EfEw6HaW1t5Qtf+AK//du/XVRM/ff//t/zla98hc997nOo1Wp++qd/mv/1f/1fa3wVjhd7FZLgdSKXy+WYnJysyD37IBROBlQSSK2vrzM1NbXnWm+tA6l0On2kdeBa4DRwUOl11mq11NfXK3/7bDarGJtMT0+TzWZxOBxKcndUiSTZkO2kp8QqLWifcdDhsF8hSf53URQJh8OMjIxgsVh2NbWqRTUxUKFnyF5rvbWcToKd6SuDwfCx046s9v1Ln/1SiSS5yR8MBoua/HJyd9Qm/2mIgSrVrz3jn8Njr0KSDI1GQz6fZ2FhgcXFRQYGBujq6jrSd1M1MYbsGeJwOBgcHCwb29dysEgURbxeb8157YcJ5fw7SiWS8vk8kUhklw+SzD9HbfKfBv6BnUbiGQcdHwp908rlYfK/p1IpRkdHSafT3Lt3D7vdfuj3lP8OldxjhZ4hFy5coL29vWweVkuuSCQShEKhE2/onKSHULn3r9QHSeagozT5TxP/CIJwYB72ceGfH8qC9n6FJBlqtZqlpSXi8XjF7tkHodJkTtbpbm9v59y5c3ve2LVyy5V1E8PhMJlMhqdPnyqdqTetnXiSqORLQa1WK4lbb28v+XxeIbWlpSXGx8ex2WxKccnhcFT9xXAayKzSgjbAV77yFb7yla+U/W/vvfferp99+ctf5stf/nLZ15tMJv7Lf/kvB76ny+XiW9/6VkXnd9pwUCEJUO6ZDz74ALPZXJF79kEo1Hvc74tWllfyer37FtFrlXTJSVw0GiUej5PL5Xj58qXCQbJR0CcBlTQb9Ho9zc3NNDc3I0lS0fTk6uoqkiQVFZfMZnNV1+808A+ccdBxorSQVK6BoVaricfjPH/+vOx09GFQacxSuBmy3zRmrZpq8XicVCpFPp9X9DMnJiYUDnpT2oknjXJN/VLs1+Tf2tpiZmYGo9FYND1ZbZP/NHCQzD+V3PNn/FMdDiokFb5ONusqNx19GFTCQYWGbwdxXy04SJIkPB4PgiCwurpKIpFApVIxPz+Py+U6VB5xlHM5SVQSA2m12rI+SMFgkJmZGTKZzJF8kE4D/0B1xthnHFQdDhpqlKFSqXj58iUNDQ3cunXryPWQwoL2fpA3Q5LJ5L5F9FrlYblcDq/XSzqdZnJyEkEQkCSJtbW1Q+URR8FJclClsk97+SDJtSC5VnQYH6TTwj+JRAKozBj748A/P1SVzkoKSYBSWJGTqVpJShwUSImiyMzMDBsbGxUZvh21MydJEvPz8ywvLwPQ2dmJz+ejo6ODYDBYtFbhcrlwu93HXlw6ycLVYSYTtVotDQ0NSsMjk8kogdXU1BS5XG5XYHXQ8U8DmSUSCdra2k70HD6OqKSQJEkS6+vrALS0tDAwMFCT56KSyYBEIsHQ0BBarfZA7qtFIpdOpxkaGiKdTuNyuWhsbGRtbY3GxkZl+qYwMKjF9N9pRrVmLCqVCrPZjNlsLpJICgaD+P1+ZXpSDqoqKc6dBv6RA8SDVt3OUB0qLSRls1lWVlaUiSSn01mT96+kmHTQZkjp8Y6a/Hg8HsbGxtBqtYom7/z8PEajUTkXi8VS1OQ/6eml48JhrmVhkx9QJJKCwWBRk1/mn0qKc6eBg+LxeMXFpDNUjkoLSX6/n0AggNls5v79+zUbrDmIg/L5PGNjY4TD4YoM347KQYUDBCqVirfeeotAIMD09DS5XE7JI2SJn6NO/512yHlYNZB9kOScOZVKKcUlWSKpcIv2oOt3GvgHdj7HWQxUe8gxkOxZVO5ekA0YRVGkp6dH8dg6KiopaBduhjx48GDfhnAtBhvlAQJJkmhoaODChQv4/X6mpqYUqVWdTqfwT60lfk4TCnPzSiH7IMleSKIoEo1GCQaDRU3+wg2S/a7faeGfZDKp5JifBPzQFLQrLSTJeo1Go5HOzs6aFk8KdXFLkUqlGB4eRpKkinW6j0Jkhd2/W7du8fz5c+WaFBZo5cAgGAyytrYGUFRcqqbrdNpRC2dfg8FQND2ZTCaLpieBoulJk8m06z1PA5lVuu5/hspQTSFJds8G6OjoqFniclAgVelmSOHxjpLIybpwjY2NNDU1EQqFFP3w9vZ2xXlaDgw2NzeZmZnBZDIVBVYfp+LSUTmocHqyq6sLQRCU6yfrsJvN5qLpydJCwWngn3Q6jSAIZ8lcDVFpISkQCDA6OorJZMJsNtesmC2/5178Ixd2fD5fxfJKR2nqywnr2toa165dY2FhQTlHjUZDX18ffX19inZiYZFJlvhxuVxYrdaPTXFJ5p+jfJ5SiSS5yR8KhSpq8suyWCfNQdVsiJyhMlRaSJqfn2dlZQWn04ndbq/pluh+HBSNRhkeHla24iop2hylsZ9MJhkeHkalUnHz5k2eP38O7BRo1Wo1Fy9eVPIIOQ9bXFws0nd1uVwfq+JSLfIwk8lEW1vboX2QTkMMBDv591HkLc5QjP180wqRTCYZGRlBFEUMBsOhPUPKQf5+LVcLKtwMqVRe6aiDjVtbW4yPj9Pd3a1sfKpUKiwWC2q1mhs3biAIwi6JH3kTXW5Sn4bnpRaohTGvWq1WfJCAqn2QToOGvzxU9HFunpbi1Be0CwtJ+wXr2WyW8fFxIpEIt2/fZmVlpeZarnsFUj6fj9HRUZqbm7lw4ULFN/JhiSwajTI0NITNZuPBgwdF51R6vMLAoNCYw+PxMDs7q+hHyw/mD7M8SS0CqULIXwoWi0UpzsnTkz6fj7m5OfR6fVFxyWAwKMH+SaJS/cgzHIxKC0nBYJCRkRFFr/G9997bswF2GOxV0BZFkenpaTY3NyvaDJFx2EROkiSWl5eZn5/nwoULdHR0KFsipZxWGBj09vYqxaVgMMjs7KyyWlpLeZLTYIhUK2g0mqLpyVwupwRWCwsLygRQ4fTkaeEf4IyDaoRKC0kLCwssLy9z4cIFTCYTk5OTNT2PvZr68Xic4eFhdDodg4ODFQ8S7JUYHoRsNsvw8DCZTIb79+9jtVpZXFxUjlnIQYXaiaVN6uXlZdRqdVFx6ajyJKdhS62WKG3yF05Pyk3+QoNJuTh30hx0VtCuHSotJKVSKUZGRsjn8zx48ICNjY2axkBQPg8rNN6uZDOk9HiHycP8fj8jIyM0Nzdz8eJF0un0rnOC4jxCNkiUi0tra2tMTk4qxZFayZOcdAxU6zysUh8keXryNBW0zwaLaoNK8zB5sKe1tZXz58/z5MmTN8JBuVxOqUFVshki47B5WKEiwPXr12lsbGR+fr6Iy+T/r9FoigwSZR+fYDDIxMQE+Xy+aNDxTcqT1Bq1KGiXolofJEEQjuzFdlSIokg6nf6h/ltWi1NdvSwlsL2K2eXcs+U1pVqilMQKJxEuX75ctTPnYYhMNrns7e2lt7cXlUpFNput+PxLjTnkxG5+fr5InkR2fa3mQfhh0G47CtRqNXa7HbvdTnd3d1HXUw5M5a6oVqsln8+fWIPgbN22NqikkCRJUln37FobJMr8V3jMw2yGyDhMIicbvYXDYd566y2lgy0XkQ5q0pUac8iTS6FQ6GMhT3LcHKTT6XZJJMnXTw5MzWYz+XyeWCx2YtOn8Xj8E7XqdlyotJCUTqcZGRkhm81y//59bDYb4XD4jSRy8oTQYYy3D8NBkUiEoaEhHA5HkSZmJRxUrkldugHxwyxPctz8UyiR1N7ejiRJypCEz+djfn5e+Xv4fD7cbveJ6ZefbanVBpUWkra3txkfH6epqYmLFy+i0WhQq9Xkcrmank8pBwmCwMTEBH6/n1u3blU9jVltHlZo9Hbp0iVF2q+Qdw6SWZKb1H19fUX60R8HeZI3kYft5YO0uLio6Jd7PB5UKtUb1S8vhFxQqoVu/CcdlfimCYLA9PQ0W1tbXLlyhebmZmCnmHvccVDhZsjg4GBVGxeHiYEymQzDw8PkcjkePHigNG4Lr8t+cVCpj4+sH/1xkCc5bv6Bg32QBEHAZDIp1/EkisqCIJBOpz9RMdCpLWhXWkiSA4vS9Y7jJrF0Os3o6CiZTIYHDx4c6qaphsjkKcytra1dJpeF16YaYizVj/5hlyd5E0RWiNKupzx9ury8TDQa5dGjR9jtduUa2u32NzY1kEwmz9b9j4BqCkl7uWcfNwd5vV7Gxsaq3gyRUe2GSDweZ2hoCIPBsCtoO+y2SWFxRN4gCQQCZeVJDjK4PemGmnwOb5KDDAYDLS0ttLS0KNOnq6urpNNpXr58iUql2mVs8ibOTy4m/TAl4qcNlRaSZB5oamri9u3byjNy3PxTuBkiTwhVi2qLSWtra0xPT5c1eivkoEq5YL8NEnnyprC4dNA9fdIc9Kb5R6VS7Wry+/1+JiYmlOlJi8VSpH/7ppr8ZxPaR0elhaSZmRk2Nze5fPkyLS0tyn87bg467GZIIaqJXXK5nCIpVxrvydemksZ+IQr1ow+SJ5G3QPfDaeCgNzkdXc4H6dmzZ+Tz+UP7INUCckH7THLk8KjUN03mAa1Wu2uwpxYa1aWQjyn7JU1PTxcNGVaDamOgUCjE8PAwLperKN6Tj1XthHKpfnSt5ElOKvY/iRio1AdpaGgIjUZzaB+kWkAuaP+wNUSPglNX0K60kJTJZBgdHSWVSpV1z95P7/qwkElM1o51u91Hcs2tNOhJp9MMDw8jiiIPHjzYNfUmX5+jajGV6pbJk0uyPInRaCwKrE6bPMmbJrJSyNOn4XCYuro62tvblcmBsbExRFHE6XQqid1xFnzOkrnDo9JCkiw1tJd79nFxkJxArq6uHmozpPBYlQZS29vbjI2N0dHRUXYKsxYcVLhBIheXZHOy45InqTVOkoPk6dO6ujqSySQ3b95Upie3t7eZnZ3FYDAUeQAc1+TFJ027rdaopJAkr5yur6+X5YHj4B9560TWqDzMZkjpOVbCF4IgMDU1hdfr3XMKs3BC+7AolScpbPIfhzxJrXHSMZBGo1F4+a233lIaBKUSSXIMeZzanYlEomjw4wyVo9JCUiKRYHh4GLVaXZYHjrOgfZTNkNLjVcJBsvGa2WzmwYMHu747Cwvahf+sBichT1JrnDQHGQwGVCoVvb29WK3WQ/kg1QJyQelsQvtwqNQ3Td6s2osHjoODNBqN0tw67GaIjEr5p9Ajbi997tL86zAcVAt5kpNsqp20f4e8ne12u2lvbz+UD1ItIAgC2Wz2bEL7pFCNe/bo6Chut5ubN2+WvRk0Gk3FUhyVQq1WK4nNhQsXaG9vP7Lw/EEFpWAwyPDwMA0NDVy6dOnA4KVWRCKvapXKkxQmJoXyJPI08MdJu+2wEEURnU6HyWTCZDLR2tqqrPXIgdXS0lKRvII8PVkLyO/1SSKyWqHSQtLs7Cxra2tFK6elqLXkCOw8X+Pj40iSdOjNkMJjSZK073MjSRJzc3OsrKxw9epVZY1vr2MdtalWiFJ5jdLEpHD6uLC49HHTsD3MOajV6l0SU4IgKPrbq6urSnIsB1UHTcBXg0QicSY3cggUFpLkwHyvQtLIyAgAg4ODZZuXGo3mwOe7WqjVavL5PE+ePKGlpYULFy4cKXmoZDoplUoxNDSESqXiwYMHe35P1qqxX3i80g2Sg+RJThqnIQYq1K8tlZhKp9MKh29ubpLP54v0t2vZ5E8kEvT09NTkWJ8kVFJIgtfyhx0dHXuaUB9HU02lUuH3+4+0GVJ6vIM4qNB4rb+/v+z1KJ3QrgUqkSdxOBy43W5FnuSkcZo4qJzEVCU+SLVAOp0ml8ud5WFVolLftHw+z8TEBIFAYF8T6uMoaANMTk5iMpkOvRkio5I8TJZVCgQC++pzl05o1yIOOkie5LQZ3J4m/oG9fZCCweCePki1KMjLBe1PUh52agralRaS5ubmWF1d5eLFi7S1te1549a6mJTNZvH5fOTz+bIT4YfBfoQjSa/dcs+fP09HR8een/VNPLzl5EnkwEqWJ4GdArzVaj0ReZKT7szJKGdIUrjWI09eRKNRQqEQW1tbzMzMYDAYipLjo3wxnE1oV4dKC0mF7tkHFZRrHUgFAgGy2Sw2m23PRl41OCgBy2azjIyMkE6nD/ystSxk74XCta5Cg1v5+ZE5JxgM0tDQcCIbJKclmCrX+JSnBuRJkmw2qwRWc3NzRR4KdXV1R5JIisfjZxPaVUIURfL5/IEN/c3NTSYnJ2lra+P8+fN7/o3ke0AQhJo8C6Iosrq6Sj6f59q1a4feDCnEQbxRarx20P14lOnIg7CfPMnMzAyZTAar1YogCCemX39a+Gevv5PRaCySSJKb/KFQqKjJXzg9eVicGWNXh2oKSZOTk/h8vl3yh6WodR6WTCbZ3Nzcc1v1MNhvQrKc8VolOK54aD95kqWlJTQaDQaDAUmSyGQyJ7JBcpo5qFIfJDkGOkqTPxqNApxJjlSBSn3TIpEIIyMjmEwm3n777X3v81o31TY3N0kmkzQ1NXH9+vUj1xwOysOSyaQiYfHgwYN9i+elEmz7Hfew57qXPEnhkIz8/J2EOetp5h/YPaglN/kLfZAKN5EPG0cKgqDEpJ8UnHhBu9JCUql79kF/pFoWk8LhsLJW19TUVLMVor0mtGXjtVAoVGS8thcKr9ebWvUonT6OxWKMjo4SDofZ3Nw8EXmS00BksD+ZyShMjuUJeHl6cnl5WTF1LAysqlktTCQSZxraFaLSQlKpe/ZBf49acVChV4Ber6erq6smz5N8j5bjjELjtQcPHhz4fscxob0fyhncBgIBJiYmWFpaYnp6+kTkSU4DB1UaROr1+qLpycImpWyqXDg9WU2B+mxDpHJUU0iSZTeuXbt2YHGllgVt2XQyk8mgUqlqUsyGvYtJkiSxtLTEwsICFy9epL29/cBjFU5ovwmUkyfZ2NggkUjw8uXLE5En+WHin3JN/nISSYXTk9U0+c+MsStHpYWkaDTKyMgIBoOBt99++8DJxFrmYV6vl9HRUSwWC0ajsWaTZ3tNaO9lvLbfceB4m2ql71dOnmR5eZlYLMbjx4+VDaw3aXB70hwkaxtXwkF7+SCFQqGiJv9hfJBisRjAWVOtQlTqmyYP+lWqWV2rppooikxNTeHxeLBYLDQ3N9ekWLtfHubz+RgZGTlweEFG6YT2cWMveZLFxUW8Xi/b29tv3OD2pPkH9h4qKofSJr/cpJRrQXKtqFofpLOC9huGKIoEg0HF1fmgQpK84lrJjVKLrlwhefb395PP50mn00c6ZiHKFX8SiQRDQ0Po9XoGBwcrSoJqvWpbLVSqHWMgvV5PT08PdXV1u1YqSuVJjqNrdxrW/eXzqDZw1Gq11NfXK2tT8hdDKBRSzKlKjU32uoa5XO4Tp510GMiFpJWVFex2+56d0EL37KtXr9LU1FTR8WvBQdlsltHRUZLJJPfu3WNsbOxIxyuE/FlL79f19XWmpqbo6+ujp6enqmfqpDhI3iABuH37tvLdUqibWFhcOsqK4H44DVsih52KKG1SxuNxpcAtrxYWTk/udw3PJEcqgyRJpNNp5ubm6OvrQ6PRlH3eYrEYw8PD6PX6igpJ8Pr5PioHyZ4h9fX1XL58mffff79mSUO5pn4+n2dsbIxIJFLVNtybbqqVvrfZbKahoQGv18uDBw8OlCc5juLSaeGfw3y2vSSSCs2pqinQJZPJsxioAoiiiN/vx+fz0dfXt2chSdZv7enp2fN1pahFDFS4mXvlyhUymQyhUOhIxyxEOb4Ih8MMDQ1RV1e3y3htv+PAyRVU5O2GeDyOVqvlwoULSgw0PT1dJE9ynB4+J11Qkr9PDsODpRJJcpP/MD5I8Xgcg8Fw6jTOTxtk3zR5Q2evzftsNqsYsu4nu1GKWjTVkskkw8PDiuzZ+Ph4zTZPyuVhkiSxsLDA0tJS1T5JpVz2Jp9HWZ4kEAhgsVior69X6hilBrfHJU9yGupAh83ByjUpD+uDJGv4f5I2RE6soC1PBHg8HtLptNLhKUShe/aVK1f21G8th6N25XK5HOPj44TDYYU8FxcXa7o+V5rMyRMI7e3te2rSlcNJTGjvh9LibDl5kkLt21pqR580kcHhyawQpbpVpddQkqQiUis0ZojH4wBnydwBkCSJbDbL6uoqXV1dZSfaC92z33777aru1aNyUCgUYmRkRJmS1ul0NV2fK50MEEWRyclJtre3qzY5KUwKTwMHFRrc7iVPUlhcqtUGyWngoFrwj0qlwmazYbPZ6OzsLNIPlq+hvIUj85BOp1N+/2xCuzLI22lLS0v09PTsug8lSWJtbY2ZmRm6u7vp6+urKi44CgcVJlWyxJvsS1Kr+7y0mBSPxxkaGsJoNDI4OFhVwnOSBe1SVCJPIm+QuN3umhWXPi78A+UlkuTiUuE13KvJfya7djDkGCiZTLK9vU1/f/+u1xTmQrdv3y6bq+2Fo8ZA8maIPCVttVpZXV2teR5WGLvIfLuX8dpeKC1onxQHye+r0+kOlCcp50FyVJx0QekoBe1SHMUHKRaLHZvh5McJ8mR2PB7fc6gxGAwyOjqK3W6vOi6QfT8OC7ku09raqniGVOJ/Vs35wevnNpfLMTo6SiKR4P79+1VtWpeb0D4JHpI5sFCeRBRFpUF9nAa3H6cY6Cg+SJ/ECe0TG+VQqVSo1Wq0Wm3ZAk08Hufp06dEIhEGBwerKmbD0bpy0WiUJ0+ekM/nefvtt5VOYC1JDIrNAGZnZxkZGeHKlSuHMlo6DUncXpADgitXrvDw4UNu3LiBzWZje3ubp0+f8uTJE2ZmZhSN8sPiNBAZ1I7MZMjTX21tbVy9epWHDx9y69YtHA4Hfr+f58+f8/jxYyYnJ1lcXGRmZgaobNXt3/ybf0N3dzdGo5F79+7x4Ycf7vv6P/uzP+PChQsYjUauXr3Kd77zHeW/5XI5fu3Xfo2rV69isVhobW3lF37hF9jc3Cw6Rnd3t7LSKv/vd37ndw5xZY4GOXjSarW7nmtJklhfX+fJkyc0NjZy9+7dqhsvh+UgSZJYXl7mo48+oru7mxs3bijFwlpyUOFkQCqV4tmzZ8RiMQYHB6t27D7N/CMHBT09Pdy+fZuHDx/S19enGF4+evSIly9fsry8TDQaPdLnOA0cdBy6dXKBrre3V7mGAwMDqFQqlpaWePToEc+fP2d+fp6JiQlCoVBFgdQnmX8AhX9g9yR1LpdjZGSEhYUFbt26xcDAQNV/18NyUDab5cWLF2xubnLv3j3FAFt+/1pykHwsj8fDkydPaGpq4s6dO1VP75y2ploh5Mm/Cxcu8ODBA+7du0djYyPRaJSXL1/y/vvvMz4+zubm5pG2AD+u/AOv9YMvXLjA4OAg9+/fp6mpiUQiwejoKI8ePWJ0dJS1tTXGxsaIx+MVFQM+yRwkP9M6na4sT4RCIR4/fowoirz99ttVFbPhaHmY3+/ngw8+wGw2F8lM1loTV46pBEFgbGyM+fl5bt++rfyNKkXpa08TB8mTfx0dHVy/fp2HDx9y+fJljEYj6+vrPH78mGfPnjE3N0cgEDjS9T1pDqplQbsQcoGu8BrKz/nW1paSy05PTzM3N8fa2lrFOcMnnYPkOKj0vpOb6i9evKCnp4ebN29WHRccloNEUWR6epqRkREuX77MpUuXlHvquPKwWCzGkydPAHjw4EHVsqFvWnKkGsgSbP39/bz11lt86lOforOzk2w2y9TUFI8ePWJ4eJjV1VXi8fih+fOk+QeOLwaSm/z9/f3cvXuXT33qU4oXwOzsLI8ePeLFixcsLS0xNzdX8WDRx4V/TlRyRJ4gKi1iVuKefRAOQ2KSJCnroeXW6o6joJ3L5Xjx4gXJZLIibfCDjncQCeSFHX0xnfZ41qAOIhJZnkQ25ZC1o2shT3IaiAyOj8xkFE5PdnV1IQiCMj35/e9/n//+v//vUalU/Oqv/iqf//zn+cIXvlB2/f9P//RP+epXv8o3vvEN7t27x+///u/zxS9+kZmZmbL6rB988AE/+7M/y9e//nV+6qd+im9961t86Utf4uXLl1y5coVkMsnLly/5F//iX3D9+nVCoRC/8iu/wt/+23+bjz76qOhY/+P/+D/yy7/8y8q/n5Tet9xUK+SgSt2zKzl2tRwkT0NFIpGya3XHEUjJK6mNjY1cvHjxUF3y0zQdeRAHlDO43UuepHTq5iCcBg56E0YspVs48hp4KBTiN3/zN/ne975Hc3Mz//P//D/zhS98gTt37uw6xhn/oEz7lMYr4XCYkZERLBZLxdJjex2/Wr4otxlSeDyoXUFbPr/p6WnW19e5du1axZJOpSiUXjvNkBvUZrOZ9vb2ou2Hzc1NZmZmMJvNRZN/lXLyJ4V/oHgLp1AiaW1tjS996UtkMhn+l//lf2FtbY0f//EfL3tfnXEQZYtJhRr21U4qF+KweVjhZkipfv5x5GGZTIZnz56hVqsZHBw8lCRZOcmR0/A8lkOh+Wp3Tw/JZJp4LEo4HCqSJzmMMdlJf2Z5Qvy4z2E/H6T/+//+v/nd3/1ddDodv/Zrv8bnPvc5PvvZzxZ9l8r4pHNQYUE7lUopP0+n04yOjpJOp7l3796hpRMOsyVSuBkyODi4azjsOPIwj8fD3NxcVZJO5Y5VTnLkNEKv1+N01SNpzTgb2jBoIJmIKhrch5UnOWn+gTcXA+3ng/S1r32NqakpVldXcTqdvPPOO1y8eHHXMT5O/HPippCFgVQ17tkHoVrCEQSBiYkJ/H7/nuv2tQ6kBEFgeXkZt9vN4ODgkdbeC6e9yyGVzTHvCbIWjCCKEs0OK33NLuostZH7OCwKCyPZnEAimSQRjxJ+lZhA5fIkp4HI4M2RmQx5dbCuro6+vj56e3v5x//4HwPwta99jevXr9PT07Pr937v936PX/7lX+aXfumXAPjGN77Bt7/9bf7oj/6IX//1X9/1+j/4gz/gnXfe4Z/9s38GwG//9m/z7rvv8od/+Id84xvfwOFw8O677xb9zh/+4R9y9+5dVldX6ezsVH5us9mq3ro4LhQmXdW4Z1dz3EoQjUYZHh7GbDbvuVZXaw4CGB8f59KlSxUZr+2FgwragViSZX8YXzSBxaCns95Bh8uBWl275/WwgZvRaMRscyFqLLibO9GrBWLRyKHkSU4DB4mi+EZMeAthMBgUiaQ/+7M/45d+6ZeIRqO8ePGCjz76iP/wH/7Drt8545/XkJtq8nbG/Pw8/f39VU8JlqIaDir0DNmriFXrgnY+nyeRSCCKYkXGawehHAeJosRWOMZGKEYml6PRbqHd7cBiqL1+Y7XPvyhKbAfibIeSCHk9DW19XHKYiMd3ErvZ2dkieZKDDG5Pet1fPoc3reNdKpG0vLxMZ2cnXV1dfPOb30Sn0/HzP//zu37vjIN2UNjUz2QyjI6OkkqlqtKwLwc5Xqn0uchms4yMjJBKpfYsYtU6Bspms3i9Xtrb2w+1HVuKUh37bF5gMxQjlEih02hocliot5mP9Tmt5NiSJLHqCbO0ESSZymLQa+lqbeDeuXNk0mmlMCIbk1VqcHvSMdBJ8A8U57K/+Zu/icFg4I//+I8JBoP8d//df8fQ0FDZgvYZB+2gMFbx+XyMjY1RX1/PrVu3jhTPVpuH+f1+RkdHaWho4NKlS2WbybXkIDlWmZ+fP3Ldq9yEdiKdJZCMkcnlsRr1NDms6I9poLH0XPbD+naYicVtovEMADazgYu9jVy//trg9jDyJCfNP3ByHFQokfR//p//J//kn/wT+vv7effdd1leXuYP/uAPdv3Ox4l/TsWEtjxhOjw8jNForNj0aD9UQ2KyTq5Op9u3O19LEltfXycQCOByubhx48aRH8D99JJyeYGPFjdZ8YdxmA2oVSpmPAH88SSD5zqxm2qjnXZYZHN55lcDrG6HyeUFHFYj/R2dXL58eZcgvqzbKk8uFX7RnQYig5MjMxlyZ/Nf/+t/vef1kFfKv/a1ryk/U6vVfP7zn1dWnkrx5MkTvvrVrxb97Itf/CJ//ud/vue5RCIRVCoVTqez6Oe/8zu/w2//9m/T2dnJz/3cz/Grv/qrb7wIJ0Oj0ZDL5VheXq7KPbuS41YioSPLm0xPTx/43rXiINl4DeDq1au0tLQc6Xj7FbR90QRP5teIpbLYjHpi6RgboSiJjiyX2nd3gN8kcnmBiYVtVrZCZLJ51GoVboeFG+dblakbObErdL2XtW9Li0uf1IJSIdRqtbKK9lu/9VtlX3PGP8XQaDSk02nm5+dJJBK89dZbu875sMetJA4q3AzZ773laapacFA4HGZmZgaVSsX9+/ePfP33khyZ2vAxvu4FQKtRsRqIsB6Mcq+/A6ux9kXtSiGKEhOLHuZW/EjscOfiRpD2Jge3L7Yp0zGF2rcrKytFuq2l5qynIQY6af6BncmlbDbL1772Nbq7u8u+5oyDdlCYh8nFHJfLxc2bN498PhqNRhm0Oei+DIVCDA8P43Q69x3wqVUMJEkSi4uLhEIhpXh1FJSbyk5lc7xY2mItEEGtViGKEgadhisdTZxvOdzmX62wshXi5dQGWq0Gs1FHKptnaGaTfF7kQk8jFotF2SCJRCKEQqGKDG5PmoNOA//ATh7W2trK//F//B97vuaMg14/N3K+NDMzw+rqKpcuXaKtre3Ix6+ULw7aDDnMMQ+CPAkOcP369SMVs6G4iKxSqYhk8vzN9ArRdPbVD6HNaeduXxuWE4x9QtEUI7NbiKJEa8NO0zIUSzE6u4XVbMDtMBcN6cn+GcFgkKmpKXK5HE6nU+Egi8VyqrZiTgsHaTQa/s7f+Tv84i/+Ytn//nHjnxOf0NZoNIp+61FWLcodt5JEbmtri/HxcTo7Ow/UqKwFiYmiyNTUFB6PB7fbjcPhqMnn3W/FajsSZz0Ypc1lQ/cq8LCZDKz5I6z5I1zueF1USmVziKKESa+renryMBOSkiQxMuthft2Pw2LAqNfiDyUIRlPcu9JBS/3B8iR1dXW43e5TUUyCncn7kySzeDxeRPDl4Pf7EQRh1xpuU1MT09PTZX/H4/GUfb3H4yn7+nQ6za/92q/xsz/7s0WTNv/tf/vfcuvWLVwuFx988AFf+9rX2Nra4vd+7/cq/Yg1hUqlUj5DNe7ZB6ESyRF5K2W/zZBCHNVkCYqN1zQazbGaRkiSxNxWgGQ6R1f960mvcDLNnCdIZ71TKSrlBZF0Lo9eq3kjEwQAy5tBZlZ8uB1mGuqs5AWR7WCUkdlNPnWzZ195knIbJGfB1A5kDtoLZ/yzg8J7ZXx8nPr6egYHB8tOch0GlcRB0WiUoaEhRd7koNXOo8ZBhcZrLS0tBAKBmiTRhU01GaFEihmPH7tJj+1V414UJVYDEZa8Ia52vr6fUtkckrQT+7yJZzgYTbKwFsBuNWIx7VzzXF5gzROm2W2jp21Hr7hUniQWixEIBBR5ksINEkEQzviHHUNI2H+F9YyDXkO+Z4aGhhQD2FrlYbB/TFy4lVKJvEktYiDZeC0ej9PQ0FCzGKi0ob/kDbHiD9PusqPV7Hz+UCLF1IaPFocVu3mnGZUXRDK5PAadVnndYVFJHpYXRBbWAuh1GtzOne9pi0lPJJ5maTNIV0sdJuNr3xa5uFRqcFtOnuSkn/+Tfn8ZiUSirNRjIc44aAcqlQpBEIhEIkUGsLVAJTFQ4WZIJUaMtagFyQ08t9tNNBo98hAnFPNPXhBZjqRosGZor3eiVqnICyLrwQg2k4E7va3K76WzO4NXRn1tSoIHcZA3GCORztLR5FR+5naYWd+OsOWP4nYUPzeyf0Y5g9tSeZKTjoHkjaST5iBBEEilUvs+Rx83/jnRgnY2m2VhYYFcLsfdu3erNhzZDwcVk2Tdxs3NTa5fv15WK6baYx6EdDrN0NAQkiQxODjI4uJizXWYyhFJLJ1FlCSlmA2gVqkwGXT440lgZy1lYs3LWmBHksRtM3OxvYGWuuPV1ApGU6xvh2mss2Ay7ARQFpOeTV+UpY0gze7XE5Cluq3pdFohtY2NDQRBQKvVsrGxQV1d3YHBxHHhpAOqZDJ55NXtoyKXy/EP/sE/QJIk/rf/7X8r+m+F3b1r166h1+v5b/6b/4avf/3rNXNarxTy1Im8nVGt4ch+OCjxqnQzpBBHDaQ8Hg9jY2N0dnZy7tw5vv/979eEg/aa0M7mBfzxJA5z8d/VYTKwFogSSaaxGHQsboeY2fITT2Yw6HT0NdVxvq3+2LT+AQRRZGUrjNmox/yqqK7VqGly2fEGYwTCCZrcxfxXqtsqa996PB5mZ2eVYl0ul9u1QfKmcNL8AyfPQT8s/COKInNzcySTSdra2rhy5UpNg/H9+KKazZBKj3kQBEFQZOVu3boFQCAQONSxSlFuQjucSJPK5mm0v74X1WoVNpOejVCUKx2NxFIZJtZ8bAajSECjw8KljkbqbccbP4SiKbJ5QSlmA+i0Ggx6LVv+qFLQLkSh671cXJKb/LOzs6TTabRaLcvLywfKkxwXTgv/AMfarD0IPywclEqlGB4eBuD27ds1z8Ng57kv16SrdDOk9JhHiVlisRhDQ0OK2eT8/HzNdGZLdfzXg1EsRl1RkdppNrIaiOKPp7AaDSxsB5nbDJDIZDHpdfQ3uxhodaM5xmcomc4ST2WxW4tjTqtJz3YwTiKdVQrapZANbhsbG5EkqajJv7y8rEhpptPpA+VJjgOiKB7KB6bWqKSgfdz4YeGgra0tZmdnUavV3L9/v6Z/v4MK2nJhua6uruKtlKNwkCRJrK6uMjs7y7lz5+js7MTn89VcwiSUTBPPCFy0mVDLNRSNGqfFxEYwypX2RjL5PJNrPjZCUZCgpc7KpY7GY5eiTWeFsvwmShLbvhidTc5d3CRDpdoxuJVNbkvlSWKxGGq1mvn5+QPlSY4D8vU/6RiokoL2ceNN88+JFrTlREbW56ol5FW3csF1MplUArjBwcGKv3SOQmKBQICRkZEi4zW1Wl3zQKrc8fRaDUi7VzFyeRGTXkcuL/B0do0VfwSX1YRBq2Y9GCUUT/Hpy93U24+vMJFMZcnmBaWYLcNq1hOOpckL4p5FLaPRSGtrK62trcq6kN/vV+RJDAYDbrdbmS6o1dTbQTjphC4ejx9IYvX19Wg0Gra3t4t+vr29vaemUXNzc0Wvl0lsZWWF73//+weaedy7d498Ps/y8jLnz5/f97W1xtLSkjIVXctiNuwfSG1ubjIxMVHRZkghDstBcuFsbW2tyHitVhy0V0Fbo1ajUavJl5yzIO50sDVqNYvbIT6YXUWn0WAzGkhnc3y0uEE6n+dOX/Urh5UWcARBIpsTdk2DazVqBEEklckd+D5ycUmWJ3n8+DFAWYNbu93+RopLJ70hAhzorn3GPztIpVL4fD6cTmfNtrUKsRcHVbsZUojDcpAcd6lUKqWBFwqFah4DydjPnE2UJDRqFelcng9m1tgKxXDZzKiApe0g4USaH73crUxQvilIkkQ8kUElwcZ2hEa3dd+mnk6nK9ogWVpawuv1EovFDpQnOS6cdPwDO/yj1+v3jfnOOGgHm5ubWK1WwuFwze8PtVq9p0RRJBJheHgYq9Va1TDBUfIwOe7q7u6mv7+/phJKsHtLpBy3qVQqePXj2S0/z+c30Gs1WIx6kpkcz+bWyQkiV7sOZ45bCfQ6LQadlmw2r0xlCqLImifCljfKU/UyvR1uuttcmE17/13KGdw+fvwYg8FQkTzJceA08A/scNBBTf0zDtr5e62srNDb28va2lrN74+9YqDCzRC5sFxp/KVWq8lms1WfSz6fZ2JigmAwWLQNXOs8DHY+n4i0q3CsUavJCzkSmSzP5tbxhOPUWY2oUDG76ScUT/GjV3qPVY7NYTUgCCKCKKJRqxFEkdWNMNOL2zS6rIQiKdqbHFy/0LpnY01G4QZJX18fa2trbG5uksvlDpQnOQ7I3yUnzUH5fP7AgvbHjX9O9Iq3trZy9epVZUS/lpBJsTRQ8Xq9fPDBBzidTu7fv19VB/UwgZTsFv7y5UsGBga4cuWKcm57GagdBvs9oI12Cw6zge1oAuHVtQ4lUqjV0O6ysxXekSRpd9txmI1YjHo63A5i6SxL3jAAmVwefzRJPLU/iVdLFHqdBrVaRS5f7LDuC8QJhhLMr/gJR1P7HOH1++r1eiwWC7du3eLhw4ecO3duR5dycZH333+fjz76iMXFRSKRSM2N9Qpx0gFVJYGUXq/n9u3bfO9731N+Jooi3/ve93jw4EHZ33nw4EHR6wHefffdotfLJDY3N8df/dVfVVQoGR4eRq1WV7QlUWvcunWLhoaGY7kfygVSoigyMTHB1NQU169f5/z581XdK4fhoGw2y0cffYTX6+X+/ftF60K1Sub24jKtRk1XvZNoMkP21TMuiCLbkQT1VhNOs5GZLf8rsyQrZoMOl81MndXM0naIaDJNLi/gCcXwhGJFPHFU6LRqnHYTsWRG+ZkgiMwt+1hYDfBkaIX3XyzhDcQrOp5Wq0WlUtHd3c39+/e5f/8+zc3NJBIJRkZGePToEWNjY2xsbBS5udcaJ80/cHBB+4x/dmCxWHjw4AFGo/FI2197odxWWTwe5+nTp6RSKQYHB6sqZu91zIPg9/t58uQJDoeDe/fuKYWzWvqSlCsm1dvM2Ex6AvHXz1s2L5DM5Oh0O9gIRvGEY3TUO7CbDNhMBjrqnQTiSVb9EfKCyFYwxvJ2CH80WdM41eUwY9BpFf7JCyJTC9tMzW+zvB7gr5/N8/2n8wTCyYqPqdPpMJlMXL16lYcPH3Lt2jUsFgtbW1s8efKEp0+fMjs7i9/vr8jf4TA4DfxTiezaGQftoK+vjytXrqDT6Y7lniiNg+QJxQ8//JD29nZu3bpV1TDBYThDlnqcnJzk+vXrDAwMFE1T1zIPKzxWW52NRDpHXnh9vpFkGrNBh9WgZ3YzgFGno9FhxWLQ02C3YDMZmPMESKSzeMMJZjb8LHqCJA9osJeex34w6rW0NzsIx1IkX23wTi94GZ5cR8gLJFI5no+t8fjlEskDcr5CyA2M9vZ27ty5w8OHD+np6UEQBGZmZvjBD37A0NAQKysrxGKxmuf9cDr4B3YauAcNFp1xEMpUdkNDw7HFQKV8kcvllPvwrbfeOlDmqJJjHoREIsHTp09Jp9MMDg4WSVvWMg+T4TAbMWk1hApiH0mSCCdS1NvM+KMJtsNxOup36j52s4GOBifeaJL1QIRwPMXkmpexZQ/rr2Khw55LKZrr7TS5bGx4o0TiaeaXfYzObGC3GOnvcGMyaJld8jE0uV41R2g0GgwGAxcvXmRwcJC33noLt9tNKBTixYsXPH78mMnJSTweD5lM5uADVonTUtAWRfFADvq48c+Ja2jL6x2yXEStUKjdptVqlQnF1dVVrly5cigTtGpJLJ/PMz4+TjgcLrtOJ+tG1QKSJLG5uYkgCCSTyaJCvc1k4FZPKyMrHjZDcSRJwmrUc62jiRanlekNP5JEkSQJgNmgwxuNM7GyzdSaj3g6i16roafZxY3eZkz6o088u50WGuuseAJRmlw21CoYm/WwthWmyW3lyfAKVrOem5faGeja30SlMJk9SJ5EFMWiyaVarYbJBjgnLTlSyZrJV7/6VX7xF3+RO3fucPfuXX7/93+fRCKhuN3+wi/8Am1tbXz9618H4Fd+5Vf49Kc/ze/+7u/ykz/5k/zJn/wJH330Ed/85jeBHRL7+3//7/Py5Uv+4i/+AkEQFF0ll8uFXq/nyZMnPHv2jM985jPYbDaePHnCr/7qr/KP/tE/qpl2dTVQq9UVmzce5tiFz3fhhOKDBw8Odc+p1WpyucoTm0gkwtDQEA6Ho6xbeC23RPL5PCsrK4iiSD6fV95roNlFNJVmLRBBECVUgMtm5npXM3lRJJ7MYDMWrxjZjHrWEilmN4Ns+MMEYjtBmctm4nZfGx0NjtK3r/pzqFQq+tvdBMMJNn0RLCY9c0s+1j0R2prsmAxaFtf8bAdiPLzTS6Pr4Geq8NkvlSeRtW8rMbg9Ck46oZM17g7SITzjn9feF9WYWFeD0uPKE4pdXV309/cf6j6pJg6SjdcWFxfLmjzVspgkCAKhUEg5t8I4Z3hlmxV/GBUq1CoVPfV1dDfUMbnmQ6VSF00xqVQqDFot6/4I674oW8EYeUHAoNPS2+zirXNtGHTln9VqNPRddhPnuhqYWfYSiaXw+mOsbUXoaHZyvqcBRIktf4yPxtf43P0BtNqD/1aF718oT7KXwW2h9m2t5ElOmn+gsqY+nHEQFJuyHTcHyROKgUCg6s0QGdXmYZlMhuHhYUWbt/S+OKqUZCFEUSza+uuqdxBIplkPRNFrNeRFEZ1Gw9WORnRaNYlMdtd6v81kYCsU5QcTy3jDCbK5ndi0zmbi/vkO2ut3xz6FqJRPz3XWk80JrG9HWNkIsbIRpLOljoHOevQ6DYIosu6JsLQR5HJ/+Wm9vd5fvqcOkieRt7Pl/9VC6uI08A/sbF/tNeVYiDMOem1M+yYaaofdDClEtRzk9XoZHR2lra2t7BBTLfOwTCbD/Pw8brebdruRnCCwHohg0GlJZrM4TEYutDaw7A2j1qiKYh+1SoVeq2Z8xcvL7CaxV80srUZNf4uLBxc7a+JvZNRruXO5nYW1AGvbYbyBBG1NTvo73RgNO38PlUrF+naEUDSFy1F5rlzopXaQPMnk5CRWq1Xhn1rIk8ga3iftZZLP5yuqBX2c+OdEC9oqlerYCtryzSQIguIke1SzgWpITDZeMxgMe5JmrUjM4/GQzWYxmUyIosizZ88UuQ23243T6aS1zobbasIf25kyclpMykqJQacFaccsqdAIMpPLgyjxxLeG2aDFbTORzuUZXdoim8vzI1e6j/zQajVqbp5vZWRWhTcUZ9sfY9Mbpa/DTU+bC7VahT+UYGhynYY6C0773tpO+yWTpfIksViMYDCI1+tlbm4Og8FQVFw6rDzJaejOVZrM/czP/Aw+n4/f/M3fxOPxcOPGDb773e8qE7yrq6tFn2NwcJBvfetb/PN//s/5jd/4DQYGBvjzP/9zrly5AsDGxgb/8T/+RwBu3LhR9F5//dd/zY/+6I9iMBj4kz/5E/7lv/yXZDIZenp6+NVf/dVdrrlvElqt9tgSOfl+kAOa1tZWLly4cOj7oxoOWltbY3p6mv7+frq7yz+rtZgMEASBxcVF8vm88h6PHj3CbrcrHHS3r43eRheJTPbVNLZlZ+U1L2DQ6Uhnc5gLZIfSuTx5QWRkaRO1Sk2Tc4ezvZEEj6dW+IKxH1cNNG4bXVbuXulkcSPI6laIaDzDpf4m2pucaNQqHDYTq1th5ld8FRe097rOdvuOwa1cXCpncFtYXDrsPXIaErqDTCHhjH9kyHHQcSVzoigiCALT09N4PJ6KPUP2QqVxSy6XY2xsjFgsxr1798quHNZqMikWi+H1etFqtYp+8uPHj3G73bhcLgb7Wgin8+RFEbvJQLPDilajxmTQKhuChc9tJpdnxRtGJaloddvQ67Q7PiOrXixGHTf7Wvc6lYqhUqm40N1AvdOMJxAjFE4y0NVAd2sdGrUK1NBcb2M7EMcXitPSsP/KJuwfA+1ncLu6ugpQVFw6rPxErWP5w0COgQ6KT884qLigfZyN/cKc6O233z508VKOgSppHsn6uC6Xi9u3b5e9L2vBQZIkKc18tVqtJPCTY6M0OutwNDnIqjQYdDqaHVaaHBZS2Rx6jYb0KzNIGelcjkgiQzSeps3twGK0IYoSW6EYT2fW+AmbGaNOi0pV/UZsIfQ6LTfPt9LX7mZ0ZpNcNs+57kbkI6pVKvQ6DZvbkUMXtAtRTp5E9iCppTzJaYh/oPLBojMO2oFWq91TJvYokAvahWbUfX199PT0HPr5qTQPkySJ+fl5lpeXuXz5Mq2t5eOGWnBQNptlfn6efD6vxHtNZh0CKbJqE2qNjt72Rrrq63BZTXhCMQShjOdaMosnFaPZYaO7cUcGL5XNMb3up8FpocPtQBAl7GZDUb2o9HMfBItJz7VzLXS2OInHMtgsBkyvitnxRIZoLIU3sFMTqqagvd/3Qqk8STabVZr8sjyJw+FQ4sbDyJOcFv5JJBI7Qx0HcNDHiX9OfEJbXlGqdUFJ7vjJZjn19fXcuXPnSN2XSklse3ubsbExOjo69tXHPSqJFZKlXq+npaWFeDzOpz71qbKTOHJxqfQhbamzUu8wsxGK0uSwolGrCCfSqIBkJodBq1F0tA06LVq1mmVvmM7tECpU6LQamuqshy7O261GBm90EYqm+MHzBYw6Ld2tr7s09XUWljdCePyxQxe0C1FYXOru7kYQBKW4tLS0xMTEBDabrUj7tlKCOg0F7Uo0tGV85Stf4Stf+UrZ//bee+/t+tmXv/xlvvzlL5d9fXd394H3wK1bt3j69GlF5/amcJyTAfl8nunpadbW1g69GVKISjhIEASmpqbwer0HTkEdtakmG93Kpk89PT1sb29z//59pVgia7nKQYLL7kL/KoHTazX0NtXx0cIGOq0Gq1FPOpfHE46jValI5wV6mp3K+7W57Sx5QowtbeO2mREliUanhaa6wxtfNLqsNNRZqLMaScazdLUUd4itJj2+QAJBENFo9n+uK+Wg0g2SVCqlcPba2hpA0QaJyVS5SctpCKgOkhyRccY/O9BoNFVtXlRz3Ewmw7NnzxTt6mrupXKoZKKx1HhtrymoWjT1ZaNbq9WKzWajq6uLx48fc/nyZSKRCBsbG0SjUaxW6078Y3Yh52GtdTYcFiNboRiNDisqFQRiSQRRJJ+X6GiwK1xlMepxWPIML2yRSGZJ5/K4bWZ6Wlw49zAwOggqlYqGOit2i5H5JT9ajXqnmA0kkhmi8Qz+QIxgKFFRQbtwOukgFG6QiKKoNPm3traYmZnBZDIVFZcqLVKfFv6p1JT2jIN2cJyNfZ/Px9ra2pE2Q2TIv7vfd20547X9ihxH4SDZ6Nbv96PVauns7MRms/Hee+/R0dFBNBol6d0gl8thrKsjr8mT0qsxm810NToZXdlGq1YrGtr+aBJRkKiz7sg/7pyjipY6G1NrXv7TkylEUcKo13KuvYHzHfVFppPVQKVS4bAaaXRZWdTrULFz7bb9MTzbUbyBOM0Ndvo76unucFXELZVykFqtxul04nQ6FYNbOQaamZkhk8kUad9ardaK3/+k+QeoaEtNxhkHFW/V1/LvJ+dMo6OjBIPBmhjfVpKHZbNZRkdHSSaT3L9/f9974agcJMdber0eg8HAuXPnUKvVvPfee3S3NhGLxQiHt0llQnjTUQS3myaHBZtRjyccp8G+UzDeiX0ktGo1DQ6z8ryZ9DqQRL79dIZGuwVRkqh3WLjZ30J7mW3ZamA1GbBbDSRSO0a0a5sh1jbCJBIZcoLIk4+WEPMil841V/T8V7Mlp9fraWpqoqmpSdkslfPWpaUlNBpNUR5WSRP2tPCPLGv5ScrDTrygDRzLdJJ8QScnJ5VV16NOEx80GSBJEnNzc6ysrHD16lVl3UiUJDyxOJFMBqteR5vdjlqlKktioiSRyu107kslQAqRz+cZGRkhkUhw//59hoaGlHPQaDRFxZLCh3R5eRmNRvO6uORyYdLruDfQzsvFLXyvdLbtJiPXupoYXfJiNhTfJia9jtFFD+FICq1ajVarpqnOiqkKjbdSaNRq6p0WLCYD2ezroDqdyRGNpQmHk0Ri++vOVkNkRe/96nrIhb90Oq0EVmNjY7vkSUwm057vcxoK2olEQvnbn2F/yNORx5HI5fN5MpkMfr//SJshhTgokEqlUgwNDRUZr+2Ho6z8h0IhhoaGaGhooL29nZcvXyrPhdFoLCqWlK552Ww2hYPOtbjI5PMsbYcIxpMYdFr6m13ksgIrvnDRe0qSRCCS4D1fFLfSZNNwtbeJm32VTxGVuw4mox61WoUgiDubIcEEW9tRvIEYdXYzywNBejvd+ybRh+Ugk8mEyWTatUFyGHkSURTfqKt3KSRJqrigfYYdaDSaY9FVT6VSbG9v09HRcaTNkEIcxEFbW1uMj48XGa/thaPwT2FD/9q1a4RCoaItEbmJ39vbSzabVWKgiYkJBEGgrq4Ot9vNjY56prZCeMIxREnCaTbR4XYwsbyNQVf8HEUTGWZWfESiaSwmPdOrPmY3/HzmRh+NzsObZ+t1GlxOM2tbYaxmvZLUxRJp8oLEs6EVVCoVlwb257jD8k8t5UlOQ0JXTVP/DDs4DskRQRDIZrOsra1x48YNZTvgKJDvrb3uM0EQFFmTQuO1vXCUwSK5oQ872qJPnjwp4rP6+npFciyRSBAMBvH5fMzNzWE0GrHaHbTZ9ARSafyxJMZXsc+6L0rp4xVLZVjZDJGIZ+ludhKKpXhvZJFQPMXblys3tCuHRpcVs0lPMJIkkciwsBxQcl1BEPmbZ/Pk8r2c6z3473dYDpINbo8qT3Ia+Acqn9A+w+sBRNjJmw67IV0O6XRa+efg4GBNZG0OioGi0ShDQ0NYrVYePHhw4Oc5Shy0vb3N6Ogo3d3d1NXVMTExoRxTpVLR3NxMX1+fMrgXCASUrVCr2sBWUmQpnkRn0FNnMXGhzcLCZrDoGc7mBVY8YVKZPJ31DtRqFRv+HZ3tL7517kixj1arpr+rgQ9HV1laDbCyFkSlVqEzaOmst2Ex63k5vo7bZaH5iFtq5ZDLCayvhwiHEmh1Gtpa63bJk6yvrzM1NYXValVqQXttkJy05KyMeDyORqN5I0bgpwWnoqBd60Aqm80yMjKCKIpcvnyZ9vb2mhx3v8kA+T3T6XRR8SqRzfK9hUXmAyHSQh69WkNPnZPP9/fuIrEZn5+h9S38iSQmnY4rzY3cbGvZpVm0vO3jo5ERXBYzD1+R5X6u2qVrXvI08srKChMTE4o0wFtdbnKq5p2kzmJEp9GwsBUikcoUOd6ubIfxhpI0O220ue3k8iIb/ijpSJRrl4/2d2xttLPhCSOIIv5AgsUVP9F4hkwmh1G/48x9/WLrng2FWhCJ0WikpaWFlpYWJEkiHo8XBaL7yZPI0wknraFd6XTSGY4nkfP7/YyNjQE7iU6tCoz7BVJ+v5+RkRGam5u5ePGicg8uh8KMb3vxJhK4zSYuNzbS796ZUChM5iLpNAv+EPFMBrvRQF+9C1uZ4E98tbo3OzOjTD/JBj+FPFSo5Vq65hUIBJSGkSRJ1NXVcb3Zhs5kxW4147KamFz1Mb8VLDpWOJ5m3Relr9lFT/NOohpLZhie38JlNR46mQJocltxO814fFGQYH7JTyaXRxBFQOIHT+fJ5QQu9DeV/X2Ze4/aOC3dIKlWnuSkE7pUKlXRqtsZdnAcTTVRFJmdncXr9eJwOLh06VLNjr0XB4miyMzMDBsbG0WyJqIksRmNEctksOj1tNltim6j3NSXn9tgMkUmn8dpMmLaJwnM5/OMjo4Si8WU6adwOLyLg2To9Xqam5tpbm5WvtNlPftIJILDYKDOZsXpdNLd2kROkFj2hIgmMzgsOwlBLi8wu+5Hr9XQ3+5G/Sp+W/KEeH9sifsXO5FyuUM9/yqVinPdDfgCcaYWvGxshlEBeoOW7gYHJqOOj0bWcDstNDXsPel1FP6LRlOkkjksVgNWq+HQ8iQnzT/ALh+ZM+yNQt+ZWg4WyZ4hgiDQ399fk2I2FBe0y73n0NAQWq1WMdut5HiHKSbJcib19fVcunQJjUajxFOlHKRSqbBarVitVjo7O4u+0205P9lkAoPZRrPbQk+7G61KzdjKNnXW18Mzi5tBcoJIX6tL4aRIPM2ziVVyWYFml5WOJmfVnwOgzmHmxoVWno+vMTHrQRRErFYjrc0OulpdBIJxJma36OlwodPtH8tWy0HpdI6ZGQ9LCz4EUaKj08WFC83Y7XvLk0xPT2M2m8vKk5wG/oGdAmqlE9pneF3UrmUcJHuGwI78QS2K2bB/HraxscHk5CS9vb309vZWvDVebVOtsKEvD1AGg8EiLit879LBPfk7vWHbx9q2H3VWRadbh85oZEUN8XRWqfv4wwkC0RRXuhuxmXeuoV6rYXhui/8rOERvcx29bS4GOuoxvZKOrIYD+jrciKLIXz2aJZnO4nZZaXBaqHdZkESJcCTFpidS84J2KpXl/UfzrK4EEMWdONRqM3D3bg/9A01FeWsul1NioOnpaUWepHSDpNYbBoeB3EA1m80nfi5vEieuoQ21DaTkIMPpdGIymWpGYMCeX5iFxmsPHjwomp57vLrGqMdLu92OWa8jlcsx5fOj12i4ajIoJDbj8/OdqTnyoojTZCSZy/G9uUWimQw/dq4PgHgmy396OcqzmTkMZgttBivS4ioP+7qV4nheEPFE46hQUW81FQn+A0VdbtgxEJCLS/Kqu8vlglfTkxfaG3h/YoVALIndZCCVzTG74afOaqSt3o6KHZ21JqeV9xdX+f7QChd7cnQ2O6l3VF9U7W13s+6JMLvoY209RF4UMRq0dLQ04LAaeTGyisthprNt99TFUZK5vaBSqbDZbMoq80HyJBqN5sQJJJFInAVSVaBQY+2o948kSSwsLLC0tERfXx9zc3M1nZYtF0hJksTS0hILCwtcvHixqIE37fPz3dl5Uvk8Vr0ObzzBfCDIj/X3ca25SUnmNiJR/vPUHJ54AjUgItFqs/ETFwdotu/cS4lMlpdrm7w/MUUkGuPBpfPYGhqLDDAkSSIv7q+DJ8sjyQ0j2SwxGAwQXVlSEhWbxYbbZmLVG8H9SmpoZs2HTqOhuyBx02k1bHqj/OlfjaJKRzA1rHGtvxWruTruN+i1vHWtk6dDyzx9sUwmJ+C0m2hwWelscRIIJRib2aKn041Bv/ur8ygFbUEQ8XgiBAMJNFo1bW11OBw7n3k/g9ty8iQnndAlEgmgslW3M+yglolcOp1WCknd3d3E4/GaHFdGoTeAjL2M1+KZLO8uLDDvD5ER8ug1Ow39Lwz04TAalWclkkrzaGmVhUCIrCDgMBq43d7CrfZW1K9ek8nnWfSHWA8EWVlcpKvOzqcL5ExKn7u9ilSF3+lyw0ieRg541vlwdXFnFV4nshxMkMnmMRl1rPsipNN5Lg20KOeUzuYJhpPMrvhY24pg0IjYNGnulviRVIKWBjufut3Dt78/ST4v0FBvo6HOQoPLilqtYnUjxPpWuOYF7XQ6x4uPVlha8pPJ5DCb9PQPNHLjZqdSvKpGnuQ0JHRnGyLVo5YcJMsutrW1odPpaqqpvldB2+fzMTIysst4bTEYYtSzzXY8QYPFzNWmRgbqX8uwqVQqsvk8Ex4vc/4gOUGgx1XHxaZ6LAVSSZIk4Y0lSOZyJENBNpcWGRgYoKura0/N6L04qPA7/dy5c8oWbSAQ4OXLlyRzEtmEwORSgsY6J3lRYssfpdVtw27eKWZnsnmWN4MsboZIJLI4rUbcDjP9jXpshupjkIHuBiRJYmszjMNuxmbWI4oSm5thBEEkmcoSS6Rx7TONKX/eSp//XE7g/R/Msbjow2zZ2ZB7+WIFz1aEz37uAtZXUk6VyJPIxaVUKnXihmzyhHk534gz7I1aNfZl2cXt7W2uX7/Oy5cva+LVIaNcHiaKItPT02xtbRVtowiiyPqrhr5Nr6fdYS9bl4lmMkS9flBBh8OBWb+7oS++av5LryRUChv6sJtz9uOgwu/0WwXTyH6/l1zYy/imhNVsxmqzsBlMYjHqaHXv3M+5vMD0khePP0rCbMRq0LHiCbG6HebH3ho4xPVUcb6nkc2tMBq1ipYGO1ueCCOj6+TzAulMHofNyI3L7QfGVdXEQLMzHpYWfbS2OdC9kpbz+WK8eLFCU7MDm+11Q1Sn05WVJwmFQoryQV1d3aFMRmsNURTJZDKfuMHGE5/QrlVXTpIklpeXmZub49y5c3R1dfHkyZOakxgUB1LyKkI5k4FoJsOsL0CDxayQk0mno8VmZTEYorPBvWOCIEkMrW+RF0W66pwAOIxg1GmZ9Pi43tpMg8XM/+fxMz5cXOF8RzstbjfRdJqny+votVpUwGo4xvvbEcY/HEOtUtHssPKwv4tWp025RoIoFemtGQyGIrPEaDRKIBBQTDrMFgutFg3eZJpkJodOq8VlNdPisqLidVI3vezFG0ozsejFG05jtxh5eKOHcx3VSV9YzHp+5E4vmXSO9fUQbU0OXA4zbqcFjUbF6maI5fVAzQvagiCytOhjcdFPJpOntc3BwEAT9hLN7tIuZyaTUYpLY2NjSmF0fX39QHmS40I1+pGfdNTSmFbe0kilUty7dw+DwcDs7GxNC4ylgVQ+n2dsbIxIJMLdu3dxOF7rmeUEgWdrG+RFkT7X6+dlMxrj2do65+p35DNyeYEniyv4Ekn63XWoVSpEUWIxFObR0io/fe0SOUHgP45O8cHUDCa1ipaWVsb8YcJjM/zd6xd2+DeaZHloisnNEOHhaW50tnCucW/9bthtlignKoFAAO/SAvp4Ck1WjcebwGQ20+i0YNbpML7i02xOYGppG48/Rr3ThCYv8nR8je1Qknfun1OmBSpFo8vKW1c7WF4NYLUYcdiMqCUIhnaKtJFIikg0RWP97qLSYQvauZzA48dzzM96yeUFkMBmN3L/fi/9A7unwfcyuJXlSeTvwsbGxgPlSY4Dn8RVt6OiVk19eUujsbGRS5cusbW1RSQSqcEZvkYpB4XDYYaGhsoar72/ssqYx0tHQUN/+lVD/+9curAzmSRJfHd6nrlAkGabFZfWSCiV5q/mFjFotVxtaSKeyfLtiVnG1zbw+/2YLRaSNjWtgTCXWxrJ5PPMB6Ms+0PMZyGYyJAXRSpJLQrNEgsTFUH0ExCibG8G0BlMmI0m2uttip+IKErMrvjwheIY9Toa66wEwxGmtmJMr3i51FN+k2M/NDfY6eusRxQlWhvsbPtijIytk8sJCKJIZ6tz398/TAz00fNlxsc3cLutOJ0m4vEML1+uoNFquHWrc9frD5InSaVSZLNZstnsgfIkx4UzyZHqUQsvEXkzZH19nStXrtDc3Kx4bNQKcgNd5qDCIYJS47Upr49vz8yRyeex6g1M+/zMB4J8caCP6y2yJCS88AUJRVKoVSq0ajXTXj+zPj9/+/IFrAY90XSa780sMe8P4PH5ENNpPn3lEm0dHahUKtK5PEv+EPORJHp/mGuvCpmVTn6X26JtWN9ibHGT1dUlLCYTjVYdDtNrRlv1hNkOxrGadbQ3OnDbTSxsBNnYTHJnwM15UdxVODsIDS4rjfU2TAYdmxthtn1RBEEimxPQ6dSsboQrKmhX+ryvrQVZXvHT0upA/2pIwOk0s7YWYmnRz9Vr5berdTodjY2NyhZQoaxmIBBQJiWPanB7WJwVtKtDLY1p5S0NtVqteIZU6n9WKUqb+oVDBA8ePFC2g2KZDP95dp75QJCcKKBVa+itc/Lj5wdwFtyT89E4y4Eogk6HChVui4kf7evhUtNOUTyWzvByfYspj49MJos6FuJyg4tPvWroZ/MC29E4sViCvLB74OkglG7RXr2aYmR+lZlVD6GQH6sokVdBKhFHq7ISiKTxhhIYDVqaXVaaXFa2AzEevVgkFEriNKSx2avX1m5tcjK/7GdlLcDmZgSTWY9BryUaz7CyHGB6zsOl8/v7UFUaA4mixMKiH4vVoBSzAerrraythdjejhYVtAuhUqmwWCxYLJZd8iRer5dUKsWzZ8+ObHB7WAiCQDqd/sTFQCde0Iajk1gul2N8fFwp6jidTuW4tQykCgvaoigyOTnJ9vb2nsZr6VyerCBgL5kSN2q1BJIpcpKIJIqkcjn8iSROU/HD4zAa8ceT+GNxJsYnGF/b5GpvDw3OHaJwmk3kRJHxLS8NyTTTvjjRbJ5+qxkRWAlGSEzO87evnWPFH2Fs3Us6l6e1zsaNzmY6XcWEo1KplERF7oIHg0HsgQBGwU8inaXeVodBMLMdy9D0qlC+vh1mOxjDbNDS2eSgpcHFhi/Key8WqLebq3KohZ2idluTg662Ojrb6giFkywu+cgLInlBJBIprzV6WMkRSZL48NkSIyNrqFSg1WlYWfGztOjn8z92Cadz7/M3GAxF06Yej4fZ2dmK5EmOC2cT2tWhULvtsMU/eTOkrq6OmzdvFhWoajmxVmjIFo/HGRoawmg0Mjg4uKszHE6nCSR3ppIKUW8xsxmNEUgmUavVBFMpNiIxWmxWZfJQrVbRbLWwHo4STKZY3Nrm/fFJOuocdLW3o1GrEUSRBX+IKY+fRCLJS1+Udv3OfbccCLMRiZG/1E+9xczkpo/NcAy7ycCFlnr6GurKBh2FiYq8NhUIBFj3eIlEIqRUKvzJLIGQnjqHDX84ji+cwGzS0V7vIBFKU2c3MTS9jkalYvBaF/VV6ruZTXpcDgt6nYZtT5QtT4RMNo8oShiMWmLxdE0L2nNz20xNbtHYaMNk0iNJEj5vjGdPl2hotCuT2uVQKk+SzWZ5//33UavVFcmTHAdkyaOTntL8YcJRY5XC9dPCLY1KDByrRaGXyNraGjMzM2UnFSPpNLP+AE0Wy+6GfiiEL5GkzqAnmM2zFgzR6XRgfJVYNNusrIUjDG96uNzcyMu1TZ7PL2LMpLnZ04XD6WQzEuVv5pdptFp4NLfC08VNRCFPQNKw6Yvhnl3m85f6WQ1GWQmEQYJ2l52+BteeJmqlicqN6wKBYBCvP0AgEOADb4jhqRhdTXUIaAlEdji0sc6K2aDFmxPxBlL8u//0gs+91c+VgWZa6qsrajTVW5me32Zu0ceWJ4xOq0GlVhEMJpiZ3ebWlQ4a95jSrjYGCoeTLC35qK+3KtOQTqcZUZSYn/Vw6VILRuP+MUthQwDg2bNnOJ1OYrHYLnmSurq6I5uSVoIz2bXqcdTpyNKijnz9j0PSTeagXC7H6Oio4iVUGPdmBYEnq+uIkkSvYgJnYTMa4+naOucb6jFqtWwnU8xHYlzqacBq2ImhcoLAvD/E1LaPOx2tvDu9yOj6FlIihlOtwtbZyZg/ROPKBv31Lr49Nst6KMqWL8JidpG5SAJ7XiSZzbEY9JLIZnGYjHTXOxWO2++zyc/LnWuXlY2s55PLPJ3ZJB7yY7dZWN1Kkhck6m0WbCY9SxtBtrYjbAciBMNJolkjn77TS5298vzLaTfR1uzg2UfLBAMJnM6dYmAkmsJs1DM2vk5PhwuHvfwzXG0MFA4lEUVJKWYDaDRqjEYtW1vhPQvapShsCMzMzJDP5zGZTGxubu7aIKmrqzv24pI8IXlW0K4OR+UKj8fD+Pj4ri2N46gFyQXtYDCoSA9dvny56N56b3GZiW0v7U4HZt3rhr5Bq+XvXb4IwFIwxMtAGLvVSp/LtbMlEYvzlzMLuM0m7EYD/3FshjlfAJ0k4PP6wGDEojZyR5RY8vj5wdwyvniSXCZDNhKiPRCmr9FNLCcw4wlgT2TpcNl3zB0rgNls4sG18zy4dn6nruEL8OePxplf82LSbBGIC4RieeocFupsRuZX/Wx4I0QTGcbmt9CrckRSKlpb28pus+6FrvY6XDNmHk1sYjLrEQWRcDxLg8uC02FiYmqLgb5GdNq9n99qYiBREMll8yQTGYymnQ0RmbtEsXIZqsKGgMViUQyQA4HAvvIkxwW5oG2xWE58W+VN4lQUtI8SSEUiEYaHh7FYLLuKOrVO5uTJALkDCCgdwHJwGA3YjQZC6RQtuteBVjidxmYw4DAYCEkSeo0G4yuycxTUtDP5PJIoMD0xgVajwdXUiLvkC9Ki1xNKpViOpIgJUG/UYdBqUKnVdLmdLHiD/IcXU/hjSUx6HQatlvENL6uBCF+40kcmmyecSGM26OhtrKPO8vqzFK5YXLz4Wks6ltxg0uvB5/PS4LAxvxkjL4LDrMNm1rPtj+0EVsEYkWiaB9c6uXOpA2MVxFbnMIFKxeKyn42NMHlBRK1SEYmlMRt1xOMZrNbiRsFhJ7R9vhiTk5s4nCalIyeKEmsrQaantrj/oK+i46hUKgwGA3q9nps3b+6SJxkfHy8qLtnt9mMp+sjaSWeoDGq1+tBcIU/Dzs/PK3rShdrRsPPlUqtGhhxIeTwexsbG6OrqYmBgoOx9r1Wr0ag15ESRQobKCcKOmatajUqlIi+KSLBrlUutUiEhsbW1xZOhUaxWKz2dHcpmhkatxqTTMu8L4A3FMGjUtDltpANeOuvsbMUS/PXMMmoRgokUFoOO1WCE6S0fD8910Wy3shWKoVGr6XA7aHYWd5MLdSdluR+vP0Di+QzTyxtoEAknJaLJPD2tblw2E8tLGTwxD+FoikQiw+Z2hDuX27l9sb1ibnDYTLS3OHj8bJFQKIHFYsBhNxKKpBByIkOj63S2u3YFVYctaM/PeTEYtJhMr6UTGhptrK4Ed9Z/9ylol0IOpvv7+9HpdAfKkxxHcSkej58Vk6qAvKV22KZ+JpNhdHSUVCq1q6hTTh7kqFCr1cpmiN/v5/bt24qEWSHS+Z2GvqNcQz+1o5WtNhlJiyI5QdhV6JEnI+PpNH89PIaUTtHf16vcs812G4v+IB8srjK55aXZZkLM52lyOYj5thlZ3yaUyLIRipJ/lZw8X9rkSnsj93raWA9GyQsijQ4L7a7da8Cwc/0aGxpofFWsbenc5q+ez7DkCROKxPGGM7TW23Ca1Cys+llcD5DNiSQzWYZnNljxhHhn8ALtTZVPK3V3uBkeX2dichOrxYBGqyadydPZXockSUxMb9LYcL7s71Zb0E4ms2QyeVyuYu41m/VEIknSqdyBBe1yqK+vx+12K1t/e8mTOJ3OY9kgSSQSNDVVPyH/SUThdGQmkznUMeTNkJ1c4WJRUafW05HyMaPRKPPz81gslrLGa6FUCn8ySX1JLFxvNrMV32not9nt+JIpsoKoFLMBdBoNZr2OOX+Adoedqc0tcpEgdVYrrS0tqDUaiMUZ3vAwvx1kPRSly+1EFQtht5pY8IUQI1HWXkwTSO5cU5UKOl0OPn+5j0gyrWjUdtc7MexT5JY3sn68sQl7/TKTS1v4wjH84Rh6tYTBrmJuaYNNfxKr2YTZqMWkVzM+7yEYTvCzP3ELU4XPsEql4q1rnTz/aJmcIBCNp8llBMxGPa2Nth0t261IzQraKhVEwym29RHMFj1W244MVT4nYDQebnVfFEVMJpOiYZzL5ZQ8bHZ2tkie5Lg2SOSC0llBuzocdlOt0L9D3gwpxHEUtAVBUFQBzp8/T8erbQ0Z4VSauUCQRqsVs66goW+3sRAM4kskabCYmfUFyIoSbpNxZ6BIpaLdYWfW52chEMKq17PgD+JQiYRDIc53tmO12Vjwh3i8sML0lp9MLker3UoqrWXM6+U743P01Qd4bzWIOSxiMOipt5n57IVuLAY925EEOo2arnpnkT9aOahUKloa6/nSZ27z4fQ6nkCEQNqPWhXHpsmzurzCZiCH1WLEbNRhsxiJhzJ8MLSOWmXkcw8GaCozAFQORoOOq+damJjcIp8XCAUSIEpE8hK5VJ50Kkcymd2Tf6DyOlA4lCCwHWV60oPVpsdqN9HV7Uaj1WA26amvP9x0syiKaLXaosGswxrcHhaCIJxJjpwEDis5UjgdtJf4/nEkcyqVipcvXyrGa/t1eg1aLXfaWvnLuQXWI1FsBj3xbJZMXuAzvd1YNGoCoohOo+FqcyPfm1vEqNPiMBrJ5PPMbW2jjkcZuHKB1u4eVl6MEU2ncZpfP8yRV8Vxryhi1OqgIB5Vq1RkcgKzngAXWuqxGXceGrfVxNSmj3/73kusej0SIAH1VjNfuNaH3WhAlCTcNrMyyVSqJT0w4OfDiWVWtwOkkilMehUNDiPrm342AxnUajVa7U4g+2RkhXgiyxcHz1UcOHS01uFymPnB4zlMRh0mk45UOk9Lk41UMsvkzBZ3b3cX/U6hGUs18PniZDI5mppfBx9qtQqrzcDKSqDigrZ8DoVd4f3kSURR3FVcqoWG89mEduU4yqpbLpdjbGyMaDTKW2+9pWyGyFC/KhjXkoNUKhXpdJrx8XGuXbu2b9JeZzLRXedgzOPFpNWi02jIiyKb0RgD9W4aLBY21WrsBj31FhPeWILOuteFl+14Am06xebSIucHBoh5AkoxW7kGgoggisTSGSxatfJfJaDObOLF0iYuk4mLrfXKtd6OxvmzpxM7GykSoAKLQc/gQDtdDXVkc3lcNvOuQEuj0dDS1MjPfMHF3EaA6dVtJuc3UEtxjGKCmfk4/kgWu12PxWygud5GJpPnr57M4bAYGeiq3JTq5uV23n8yTzYnoM3kSSZzOKxGejrdbHujbGyF6e4o3so5bEE7m82jLSmOq1QqULFrffAgyPeazEEHyZMYjcaiyaVaFJfOJI+qx2Gb+uU2QwpxHNORoiiysbGB2WxmcHBwz3Vup9GIo0xDP5RKY9MbqDPtFC+MajVatYpULldkBBnPZHEbjbx8/hG5fJ6ujvaiBoz8lK0FI+g0GvQqkXQ+DyoVRo2aUCKNN7LJlbZGhUtS2Rw/mF7mo/mNnYYeOxr8F1vrudHVQjqbx2rS0+wsP0FzrrOJ+jobK9th1rbDvJhcxWXREg6FmVkJodVq0GpVGLVq1BKMz2wRjab4B1+8QXuzs6LrazLqONfbyMzsNqIE8UgajVqFlBNR6VRsbO2YZpcrwFfb1JckiWg4RTiQwOk0426wYTLrSSQymM16TObqi0qFMVDh1l85eRK56ONyuXC73TUrLp1paFcHWXpN9j+oFIWbIZcuXaKtrW3Xa46DgyRJYnx8nN7eXvr6+spve6k16DRqcoKIqaCeu7P6vyMtsnN+asrN4omvcrPljQ3WNre43N5CQ33DThWWnWEiTyRGQEzS4rTt5EoqFTqNBrdVz6PFBBldlEttTWjUanKCwLTHz+S6D6tejyhJqFUqOuod3OttI5sX0WvVdDWUL3DrtRo+fa2Xi52NBKNJPpxcIxBO0GDT83Jqg0w6TTaTIi/AtldErcmzvBokmczxxYcXGOiqTP7RZjXS1e5ChQq/L46QzpPKS8zMeEENsXh6378LVBYDebejjA2tsbEaZGMlgMVqoKnZQUOzHZVaTWfX7iZpJSiV+NPpdEUbJMlkUuGglZUVZbqylvIkqVSKfD5fJAF4hr1RmIdVyxWpVIqRkZFdmyGFqHVTTZIkcrkcS0tL3Llzh7q63RKoSkO/5H4yvNrQz7zKN2OZDHq1GkqkQTRqNclslngyTTAYAI2Krq4u5f40ajUMrW2Ry4kMNO48K6JOoN6oY9kfZtEbxqhW0eWyoTMaWAtE+eb3X+AwGRGlnWvhtpp5q6cN3SsObHPZadzD+6zFZeMn750nEE2yvh3hyfgKDosRbyCCKuQjk80SjaaJ+WOAhCipeDq8TDSW4os/cpGe9sqe5zqnhUa3lfW1IHqNBqvDgEoFgWCCRCJLLJY+ckE7lczy/b+cJB5NY3caSSayxGNhvJ4ovecaefD2AC7X4XKYUv5RqVS7JKUKDW6npqawWCw1lScRBIFsNvuJi4FOvKAN1ReT8vk8ExMTBAKBPeU+5OPWKpCSjddEUaSnp4eBgcqE7681N6FVqxne2iKSzuA2m7ne3MSVpkZ8Xq8SANxsayGayTDp8eGLJUgmEmiScf7u7RtcPbfzXpeaG3i6vE5OFLHo9UTTGZLZHJ/q7eS5z8dSMkchdYqSRDKbQwKlmC0jnsyyFYrzY1d6Mei0SJLE1LqPP/zOU5qdNtQqFQ0OCw8vdtHXvJuIelvr6W52k8zkeDy6xOjcFmTCrPtiRBMZ9DoNKrWWXCpNMi3y/SdzOC1G3rrWUZGum0Gvpa/TzdjYOhqNmlQqh8Woo6nejlqlYmHZv6ugfdgJbY1aRTaTJ5XMYjTplGMIorir0HQQ9tNLLpUnkSfefT4f8/Pz6PX6msiTnBWUqke1XCFvhlit1rJyH4c97n7IZDLMzs4iCAKf+tSnKvobP+zqIp7JshqJIEoSKlS0Oxz8aE836lcbJ1qVisHuTr47M8e8P4hRpyWRyZIKh7nhtPCpwUHigsRMOM5WNEazbedLMpTcKbQMNLjZ9EdIlKxoJV7x07kmd9FzKeRF1oIR6jvNdNU7AVgPRPjjvxmmyW5Fp1FjMxm43dvK3f4dE5DC6XGDXsuVniau9DSxfrGLv3g8hUGnYX0riCDGSGfSpFM5FuMJJDSkMgL/PpnjS5+/wvULrRVxhMmoo63ZidmgIxBIkkllieVElgU/Gp2GTHr399VhCtrBQJx4OMXY6DruegtNLQ4amx1kMnn0Oi3uKoOq0oJ2IUrlSfL5vDK5VChPUldXpxSXDrNBIvPPJ2nV7aiolif22ww5ynEPgs/nw+PxYLFYuHv37r73h9zQ/y9zC6xFItgMBuKZLBlR4LM9PYrhmkuvReV0sBCO0myzYNRqCSXTxJNJ3NEQDX09fKq+iY9WN2l4VQQCCCZTWA0G6kwm4pnsTqGp4BlMZLNoVJqixpgkwVYwTp3ZyP3+na2NcCLFX7yY5f2pVawGPSa9lr5mF/cG2jHotDgtxqKYxWUz47KZud7bgl6jYXrFh95swGDKgpQnlU7h3Q6zvRVCo9YwHkmiEiW++PASl/ormxp22EzYLAYioRRSXkSl0+D3J0hnwohig3INSlFNDOT1RPmbd6cIeKOEwyl0Og12u5G2DhcqrZorV3sxGKpPEfaLgUrlSQonl2q5QXJW0K4e1XKFvBmSTqd3bYaUHjeXy9XkHGXjtXw+z8DAAH19ew+buMwmuuucjG5tY9K9augLIpuxGOdfNfQBWm1WjGoVgUQS9yt5tmQuR1YQMCQTbIWCdDQ3o7falWI2QDSd3vEFSOfQyYM/r/5bJieQzIvUW00Kd2jVahLJLNvhBJ++0IXNZCCdzfNkepWnU6s0Oaw78kV2Mzd7WqizmHBYjDQUFJjUahXNLhvNLhtOi4l3P5zDF00gqLQYTBaQRLLhJGkph8EgkM0ITM2uEwhE+IW/e4+ezsqK2p3tdTx/vgwSNDTsxAHJZJZAMM7mRhhul/+9SmOgXDbPD74/TSSc5PyFJjyeKPFYmpnpLdKZHJ/9wmU6O/f3X9kLB3nWyMWlSgxuD7tBIvtWnHFQdai2FuTz+RgdHS27GVJ63FrFQYlEgvHxcURRZHBwcM/p2jqTEYfRSChV2tBP4XgVtwC02mxkRRGhIH/KiyKiJGHTaRmZmSSXz9PdN1B0L+ZFCUkQMZQOwwDRVAaDRkeDQbuT46nV6NRqlnwhLrc3cq7JjSCKjCx7eD67QbvLhk6jxaTX0t3gpKvegcmgo7fZhaUgftJq1DTVWWlwWMgLIiPzmwSiabICWC1mEHRIgoiaLKFIhqA/zJNgjPkFDz/3pdvcvFLeQLcQ9W4LJr0Ovy+O220hlciQyeZBlDDoNSwvB2gv46Emo5ItteUlP1ubYXr7G8nnRQKBOLFYmkgoSWuzgxs3Ovb9/f1wEP8cZHCbzWaPLE9yNqF9gqhmOknWjTUYDLz99tv7jurXisQKjdfkbm+lUKtUXGlq5GJDPem8gFGrUQKcQgdavVbDj53r41pzIx+NTxDPJvnsFz5LQ0Gx/mFfN3qtlvEtL6FUCpvBwGBvBzfaW/AuLuIXE2xGc7Rls6BS440maLRbSKWz5EVRmUjI5PIE4knsJr2yNp/J5QnFUviiSVrrbDgtRpa3Q0yv+ehvrKOpzsr5tgYG2l4Xp9RqFVaTnjsXOghEUgxN+Ejn1RjNFlRI5FM55pf8IIlk8hL/v//8glA4yhd/5HJFhRKDXovDZiIRy5BL5cgmc0RDKXR6NRcv7DYGOExB2++LMTm6wdpSgJUFH43Ndjq76zGa9SQTWW6XFM0PQqUGgKUT77WUJ0kmk2eBVJWolIMKN0PKGcGWolayR+FwWJFW0mq1FX9Rucwm/v6VSyyFwsQyGax6Pd11TmUSUp5cONfgxqrXM+3zsxEIog8HudfWyGfv3d15P+Az53p4NL/MvD8IgNVg4O3eTt7qbmdxO8DS6hrZ/M5nTWVz+JNp3BYTGlXxfeuNJFFLKqXQJIgi3nACXyRBvdVCd4MdTyjGv39vhL98MUez08qFjkZu97diMxfzfVuDnXuXOng5u0k4niGdF6k329BKWXLZHHotJMQs6+vb/Ml/jBOPXuCtG/0HrnjpdBocNiOjI+sgSZjNBlQqFV5fDNhJyEoh80+lHBTwx/nP/2kEz1YErUbNxnoYz1YEd72VxlYnl6+00dRc3YSPIAgVn4NWq6W+vp76+p0kt1CeZGNjA1EUleaay+WqWMborKFWHeTpSNmb4yCeL9wMKTWCLUWtJpMKjdfcbjdGo7Gi76MbLc2vGvoewukM9RYLN1qauNr8urCr1Wj4XF839i0vi4EQ4VQaMmmaM0k+e/smXZ2dNMWTbETizPsCmPV6svk8GrWaT/V2YjMYWA6EyYiCMmmZzgto1DoshuJGYyiRIpvPY3/1PANsh+JEEml0GjXXu5rxRxP8549meW94kY56Jw0OM/cvdNDX4i7S3larVTy83oNBp2VoZpNcXsRm0pNX59AbTdgsOvyBGMlklrHxFVZWPPyDH7/I+f6OA6dwWlscpFM5vL4oLS0OkCCfl8hk86QSWYKhZNlmV6VbapIk8eyDBfy+GNdvdLLtieD3xwmHkqhUIb70929z5cruadtKUI0Jsslkoq2tjba2NmWDJBAIKF4kh90gOeOg6lFNMSkYDDIyMrLnZkghahUDFWp0m0ymiuQcfqR7p6G/Eo7scIMEHQ4Hn+3rUZpCLTYrFxxWIvkcc34/SDt1a3smjVUPd3/kU5hXt/hwZYOcIGDW64ikMjubtgM9vFzeJBBP0eywgkqFxA7P6NQqLAVDKclMjmgqg1GvRfOKRwKxJPFUFo1aRZPTChJ8NLvBk4lVOuud2C0GOuud3Ohtxm034yrQw25tsPPjg+eZWvYSDqdIZbI4jEaysSwWs4ZMRkU2lSAhZJkOePh/ffO7vPMj3Vy50Inb7cZsNu/JFS6nBUmCdDpHai1ENptHo9XQ0GglEEiQTGYxl9neqLSgvbkRZtsTpaWtDp1OQ53LSiyWJhRM4KqzcP16+y4JvEpRDf+UGtwWypPIGySHkSeJx+MAZ9KPVaKaPOygzZBC1KoW5PV6lQJ6KpXaN48waLXcbW/lu3PzrIYj2A0G4tksWUFgsK8dyys964tNDTSYjKxGY2jMFiRJIpBM0mQ0EJib5VxzIzGzHX8yTZNt5zstkEyh1ajpqXcxteV7nXuwY7KdyYnUWyyQzyO9ioq8kThqlQrjK66Op7JEkxnSuTw2k4F6q5mhhS1ezm7Q4XZgMeoxaDVcbG+gxW2jt8VF/avmmlqt4u6ldrqanYzMbfLB8DI2k4GNdASz1cjWZop0SqTObkarho2tCP/v/+sHPLjZyK1rO/zjcrnKDu2pVCq6O128fLHM1lqIXEZApVFhMurI6Xa09feDKIoHTjj7tqPEIimitiR2p5nWV2bb3u0oKpXq0Nwjv381g0ClvlG1kCc5K2ifICrVbtvc3GRiYoKuri76+/sPvGlqkcyVGq89efLkUMfUqNVY9MXnW3p+6XSaxYlxXCr43Gd/dNfqk16r4WFfF7c7WknlclgNegyvyMll0vMjDgf/JRImmEyj1WjobajjTmcL359cYi0QocPtQKtWE09nyeYEOl0OJajzRZMk0lksRh0GvQ4kiVA0yWYgRjKVpSEY5/nMBuda63nrfBtdTXWKJrbbYeYnBy+QiXiY3syhVmsw63RsZaPUt9jJZHL4A3GSyQzf/qsREiEPF8+1Kmume023tjQ5CAUTBINJGuotaLUaslkBz3aUZDK76/XVFrQT8Qx/+Z0xPJsR2tqcbHkirC4F8WxG6Blo5NLlVi5caD74QAWolsxk1EqeJJvNksvlziRHqkQlyZy8GRIMBvfUjS133KNwUGEBvb+/H7fbzYcffljVMQxaLRcayk/mFEqitDpsaNJJhKV57l86T39/f9E9dq21ic46B+vhCKIo0eKw0WDd+cL8zPkepmZm2IzG2U5l0cWTXGttRKfSMLzm2WmeaTRIkkQwkcRk0OF4ZYIbTqQJxVKYDToMup0pKk8gTiCSJJ8TsBj0/KcnU7w3tMCdc230t9Uz0OZGo9mRdLl5vo2uljrqrAb+8lGUFpeNlUSQeredZDyLkM4g6bVseRL8f78zSsC7TktTncI/Dodj1zOrUqmwW02k0zmMBi3ZdA5RlFCrVWg1GoLBZNm/VTX8MzG6jnc7Sv+5JrKZHH5fHJ83RiqZ4+qVNu496Ks6sDos/8De8iRer1cxuHW73Yr5yV4bJGfTkdVDDsAPMpCtdDOk8LhHTeRk47V4PM69e/cUF/dKoFKpuNrcxOWmRtL5PAaNZteGlkqlwqrX8bcun8cfTzA+OUVaSHPvR39EWeWtt5r5e9cvMuXxsR6OYtHrOdfkpr/eRU4QudrWxJPpeVKpFElNiHhe5FZfE55oikQmqxS2U9k8koQyiZnO5vFGEpgNOjRqNXlBZMUTJpXKkdeJqFQwPL/F+yPLdDfVcamrkTvn2+hodAJgMen5zO0+rvY18x++N8aWN0gsGMds0hOLZ4iEs5iNOixmPf5gku+8t0goGMJiUinf5263e9f3uV6nwWYxoFWrWZ73IeRFNBo1Tc12dFo1295o2YJ2pRwUCibZ2gzjbrCh12vp6HTT1OIgEc+QiGVobXMqRbdqcVgOKtwgkeVJym2QFDb59/qsZ7Jr1UFuqh3EFfKm6sLCQlnd2HKohfSjLK3kdru5fPkyz549q+iYbrOZf3D1MkuhMNFMBltJQx928rDzNgu9166yGo6QSCYJrK7Q0+Tm1o0b6HQ6PnOuB6NOy8SWl3Aqjd1g4EcHerjR3oxereHdyXmW/SEimRzxUAyrxUyz2UAolcb+KkYSRJFUJk+Dw6L4BXhCcXQaNWrNTi644gmTzeYRAbNBx5YvyoupdX4wvEhXk5M2t523LrTT3ujEqNfSWGelsc5Kq9vOXz6ZYX0zjIhELJ4jGs1hs+hx2S34/XFiMZEPPvJhMuhYXFxEp9Mp/FP6fW4y6rAYdKQiKVKpHFqtGpUokYxmCIUS5HLl7xP5b7LfPSFJEuurQXxbEdSAo86MxWbEaNRh0GsR8gL5fPXbsYXncNgYaD95ktXVVVQqVUXyJLFYrOKm7xmqkxzJZDKMjIyQyWT23QwpxFGbaoUF9CtXruB0OtnY2Djw+/ZWaws6jYahzS3C6TQNFjO3Wlu4VtDQrzOb+HR7M3OxJElJRAX0WYxYYxGuXrlMR0cHjvUtfjC/zII/hISE3WjgR/q66K934Y8lWfSHabJbyGSzbKeytDpdOwOMsp4skMrk0arVijFkIJYklxcw6rUIksSaP0I8mUWv1aDTqUkmM0xth5la2qbNbQcRzrXXc7G7kYGOelx2M81uG4115zDqdDwdXSGeyJBKZ4nFsphNeixGPaFAAimnIpFQ8XwkSlNDgng8zsTEBHa7XSluF36fm016hKyA1WxA59Cg1WjQGTRsb0eJhPePPff7m0iSxNCHyzx9b5a1BR/B7RhWu5Hec004XRYy6VxVnkXlcBT+qZU8iazhX0mN4uOEEy9oV6LdJggCU1NTbG9vc+PGjYonpGvhmDs2NkZnZyfnzp171bmpndFkYTEpHA4zNDSkBGz7dZjMeh3mErdalUpFh9PGYJODSzcvYdDrcVlMqFUqPn9FzV+NL7AaiCBJoNeqGWhxo0GlPPypbI5MXqDOasJm1LO8FSKayOC0GHeKTDmBVU+I+VU/U8vbtLjt/OiNXi52NaBRq3FYjZxvs9PX7eLDSQ8eTxS9Vk0ykWXLE0WjUiFo9STTAlOrefp71ayvrzM1NYXNZlMCq8JJZJUKDDotGtXOeiyAVqehocFKPicQCiWpq3vdAa/WEGlxwYtnK0J7pwuNRk1jo51wJLlT0O6q5zOfvYhOVzvJkWpwkDzJXsGoPBlwVlCqDPIX30HJXOFmyH5rZqU4CgcJgsDk5CQ+n0+RVorH4zXX5JYkqShgu3r16i5TFRlOk3FH+7oE9VYz9xsddF0+z5NsjLevn6O3qYF4JkssnWE5EH71PtDosJLJvG4eZHMCOUFEp9uRB/CG44TjKVx2E0gQiiQJRpKsbYcJx1M8Glmis7GOz9zspb+9Hr1Og8tu5rO3+5iZnsMfipPK7BSg/b4YOq0Gp91ELJ4hHMnji1q5cb2NRDzCxMQEgiDsKi4BWMx6LAYd4VCSTDqHWqXC7jTR3GbDF4jtugbVavgvL/mx2Y2o1SqMJj3tnS7aO12sLPmxWY1Vc498DrXgn1J5EkEQCIVChEIhlpaWmJiYUHi7dIPkzBSyesjf9/l8vmyjoNrNEBlyvHJYOa5YLMbQ0BBms5kHDx6g1+vx+/1Vc5BapVKMkcqdoyiKpNNp5sZGMQD3P/WpXcWCOrOJwd7OXb+v12r48SsD2MQss+seurva8JHix64N8HTVy8jaNkQTO4be2Rz1NjOmV834bF5QfABcVhPBaJJwPI3LbiKezrHhjRCJpkjl8mwFYmz5ovyXp7Nc72/m3qVOrvQ2o9dpqHda+IlPXeA/vDvEXEZAiiSJR1KYjDocFhPxWBohLbK5mWS1sZ6f/+mbhMMh/H4/CwsL6PV6JbGrq6tDpVIjZEXETB6TQYfOunN/JGMZJJE9Zdsq+TvnsnnmprZYXfBhMulobHHsFLZ1WrDs6EuKJfJR1aBWHFS6QZJKpZTi0kHyJGcT2tXjoKZ+YWProM2Q0uMeNgaSJImVlRXm5uaKpJWq8SbZr6EPr+W52p12dJkUo3PT3OrtLjLbNmi1/OhAD3e72knlctgMBvSvCq63Oluw6HWMbngYCfrpcTv41MV+3s8mWBdFlv0hzHo94VQKs1GH3ajfMdyWJDK5PDlBxGnUIwgSoVgKu8VIPJ1lwxchlshgNOhIZfIsrQd5MbnB+8PL9Le6udjTyN1LHbgcZgY66xFFke/8zRSbWyGEnIDFtLOh4t2KkErnMBl1rKxGeWm38U9+/gGSlCEQCCjf54XFJavFQDKeRo2KBrcVJAm9UYffHyMWSWIylefyg/hHEER+8O4Uz58s4NsME/RGMVsNdPU10trpIhpJ0dXtPpTUkYxa8Q8cXp4kFovVxBPpk4aDOEjeDHG5XNy6davijZ2jNNWy2Syjo6Mkk0mlgC4PYB50v6tUKq69kpjN5PP8/9n77yi5zuvMF/6dWLm6OmcAjZwDARAExCSREhUtyrIVrZHltGb8eWY88oyv7WV71p079/p+nmVffR4H2deyLWskW7ailcUgkSAJkATQyGh0NxqdU3XlcPL7fn+c7gZAZBAiZZvPWlzEqj59qrrq1D57P3vv5zGv0dAHaI5F6WxI071yJecHBijmcuy6b99yQ39XTyermjJMFMtIKeluSNOSDLmPd2/fwPPDY0yXKvieT1fc5J17t/LChUkGLuaJWDbVQOBLQcTQaVzccvUDgRASw1CJ6TqTsyWiEQ0/UMmVLBzLoyUdp1xzyOZqVOsOYzMFjp2bwlBVtq3p4J5NPWzsa+X+XavoaWvgS/4JJmcKxEyNhrhJIVfHtn2ihoYmIDtT4akfTvILP/smduxoIJfLXXE/X6rBpAgI3IBa3YWlj00BI2ZgWy5BIK7bcL/RZ3Lh/BzPPT1ALGHS0paiXncpF+qcPz1N16omIlGDdRtub4jxlbiVCfFbxc3kSRzHIZPJXCVPsjSh/a+NB/qxaB/eKOGp1+u8+OKLVCoVDhw4cFtyH3eaSC055i4Zr23YsOEymQ11ea3q1WLpXJOTk7z88sv09fWxbdu2q74MS4TT5fCFYKJUYqJUwltcMxdCUPUD6p5H1NCXp6/bUgl+cs9m3nfPJt69Yz0f3reNTzy4i6ZkjAtzBaYLFYo1GyEkK1sa0DWVhXKdqKnjS4nrBEzMF4lHDXRdpVy1OXxyjD/8wrN85p9eZmB0fvl1bepr5d6tKxBSUqrYzGcrGJpKa1MSHRBuwNRUmZEph71793L//ffT29uLbducOnWKgwcPcurUKaampiiVqgSuD16wLDniWx4RRUEEItRVesX7dDsJxPxMGd8NlqcgY3GTzs4MnV0ZFOTrSihdjiV5kpUrV7Jr1y4eeOABNm7ciK7rXLx4kYMHD/Lyyy9z/Phxvv3tbwM3X3X7kz/5E1atWkU0GmXfvn03nfr9x3/8RzZu3Eg0GmXbtm3Lz7MEKSW/+7u/S2dnJ7FYjEcffZShoaErjsnn83z0ox8lnU6TyWT4+Z//+WUC/vXEkjHt9RKpqakpDh06RHt7O3v27LktR+I7bYAtxb1qtcqBAweWJ/eXErO7GYOCIKC/v5/p6Wnuu+++65LZN0Ko06bQ15xhZSpGTyYdNrpiUd63exPv3bWRhzas4u3b1vJLD+9m24p2RrMFZgoVipaN7Xk0xWM0JWKUqja6puL5AhlI5vJVkrEIsYhBqWQzm63ybP8If/H1l/jjf3ieM8OzCCGJRw129KXZs6UXQ9ewLZd4xKApFSOXrVLM1fBtn5eOjnF2qMjmzZt505vexO7du2loaGB+fp7Dhw9z6NAhBgcHmZyYp1yok05F6O1pors7g4rCxFgO8xqx4Vbjj1V3efHgEOdPTHK2f4KLg3PYVrhxIoREIWzc3Ql+FPEHwuuupaWFdevWsW/fPvbv309XVxeWZS3H7ZMnT/Lkk08yOjp6S2TSGzEoxBJBc718xfd9Tp48yYULF9i9e/c1DbCvh6Vc4k7ixfT0NIcPH6azs5Pdu3cvT4PfbYMlRVEol8scOnRoWZv7do25DE1jTXOGezoaeWj9KjoSUQxN462b1/D4ro3sWNHB1u42PnjfVt6xfR25qsVUvkzFdrBcD0PT6GpMhRPcSPxAokgoVWwSMZNk1CSbr1KrORQrFi+dmuDPv3SI3/urp3jp1Dh126WnPcPjD29k44o0MVMnETXJJKLkFqqUyxYqIH3JS0dGefHoBCtWrFi+ny/lmBcuXODgwYP09/dTzBexag46CtIPMPXQOMqquUTNa8eHm8Ugz/X5/jdOcvDJc9QqNpNjOQZOTjJ8bhYRCHILVZqak7S03FkhtHRv+lHEoFgsRldXF1u3buWBBx5g586dpFIp5ubmluP2+fPn+cpXvkKlUrmlyb03YtAl3KipXyqVeOGFFwA4cODAbZnd3WkOtBT3lozXVq5ceUUddrdi0BIBMDw8zMmTJ9m2bdvyANMrETcNmhPxZTJ76fc3drbygT3beM/abt62fgV9LY2saUzwji2r2djVSjJqsntVFx/Yt5VUNMLYQolc1SJYJLVXNDcgpMRbNIGWMpQEiEXC4aViqU615pCMGRSKNfrPTvK5bxzlf/zND/js115idDLP+pWt/Ozje9myphlDU4maekgoOT4aCjgCr+Zy8sQk3/jOKRobG6+4n3d0dCw3MA8ePIRVrVPKVZkeyzM7WWR8OIv0JRFDp1q5tjHkzb77g2dnOP7yKC2tKVauaUU3dGzLY+jsDEPnZohEdbbu6HlVRPCPKgdakifp6+tj9+7dPPDAA6xZswYpJUNDQxw8eJBjx45x+PBhjh49ekv3sDfiz5W4XgySUjIyMsLRo0dZs2YN27dvvy1t8zvlgpbyElVV2b9///I9Zen6utUYpCoKMcO4biNaVdVQSq6/H7tW48CBA1cZTTbGY2zvamdHd8cymQ2wsjnDh+7dzs8euIeP7dvOvtY023vbee+uDazKxJFSYmo6b9++jh0r2hnNllio1HEDQc3xaErGSEUj4XcXBV8IPMfD0DVMQ6NWd6nbLh3NSTzbJ5evMTVX4skXhviT/3WQ3/3Ud3ny+fOkExE+9hO72bCqHSEl+UKdet1Bk+BbPlbVQXoBExcX+OxnX6BSca+4n+/YsYN4PM7U1BSnT57CqtbxbA/f98O8IhAovsBz/Bs23G+UA508OoZdd2nvaGD12jbSmTiaqZHPVfEdnwce3kDPilc31fyjij9wSZ5k48aN7N+/n3379tHa2kqpVOLYsWM899xznDlzhoMHD1IoFG6J0P6XFINe9wltCIPYtcikubk5Tp06RXd3Nxs2bLjti+ROEinXdTl+/Diu63LfffdddUHczURKSonrupwbGKB13TqcdJKa55FcLBwLlsXBsTFOzc+jADs6OnjTihXMVap8Z3CYqVI4JdiZTtJq11nIlTkxm+eFl4/TGI+xqbUFzwsYzOZRFNjQ1kx3Os34RBEJbF3ZTqlmM5ErsWNVO22pBK4fYLseQkoqlkMqHsVzQ73KiKEzl63i1gNScZNK1eaF/oscOTXBQ7tX02x46JrKg7tXIwPB1584Q1nUiUcMCgtVHCcsFi0cnn5mkN3belnZ20xHRwcdHR3Lk8hLGoqjF+eZmsgiUWhqSmBGTHxfMDNVIp6M0JiJXfV+3koiVClbHHp2iMPPDjEzVaBWsujpa6FpsYhzHI/UDVx0b4QfZTBbwvXkSZ599ll+4zd+A4DHH3+cxx57jI997GNkMpkrfv+LX/win/zkJ/n0pz/Nvn37+NSnPsVjjz3G+fPnaWtru+r5XnjhBT784Q/ze7/3e7z73e/mC1/4Ao8//jjHjh1j69atAPz+7/8+f/RHf8RnP/tZ+vr6+J3f+R0ee+wxzp49u5zYffSjH2VmZoYnnngCz/P4xCc+wS/90i/xhS984Uf4bt0arpVI3elmyOW4k8mAhYUFTpw4QWdnJxs3brzielr6951OXL4Svu+TzWZJp9PLE5hLkFIyV6sxWS5jqCprm5pImCbZWp1jU9OMl0o0RKPs6GinwTDoL1Y4eegoc3N51IlpOjMZzs0tULYdutJJ1rY2katajBVKbO5tpbcpxbmpHKl4hIaISanmULbCyYeq7ZGMmZiahi29MLGqOqgotDcmsW2XubkyszMlzg3PsXdzL2/dv4aoqfGWA5sQvuSpg+eRGuQXqrhegIqCqWpUSzY/fGaQe7b10t6WJplMkkwmWblyJb7vX1oxvThFvVKjXrYwDY1YMoJu6nhesLwyfDlu5TNxHI/vfLWfoYFZTFOnkK9xcXCOUr7Gxh09lIoW6UyMnt7rm57cCHdzOuBGeKU8yVLc/tM//VP+7u/+jmQyyb/9t/+W97znPbzrXe+66vffiEFX41pFV6VS4fjx47e9GXL5OeHmUiaXY6mhPzU1xY4dO676PO42oS2E4OzZs6xfv/4K0up6CIRgvFii7nm0JZO0JuJUHZfT8zlmckUi2RyeEIzkilRFgYiu86a1vViez0K1zqaeFjozSU6Mz2J7AW/a0Mt0vkql7hAIgb3YKG+IRig5Fqahk83X8L2AhsYkbq5KsVQnFYtwZnCW8Yk83W0NvOfhLXS3RrhvaytnxwOOnpggW6ngOgFqIMEX2JaDRPLtb59m0/oOerqbrrqfW5bF2Ng0pXwNp+pQL9koatj0SKSidHQ14LrXzmtvFoOGzs0ycHqKts4GGhrjjAxnqdVsRkfmcT2fjt5G9t7Xh2HeWWmw1Dj5UedA1zO4nZqa4rd/+7eZmpriV3/1V3n/+9/PRz7yEdauXXvVOd6IQVfiWvFHSsn4+DiDg4OsXbuWVatW3XbecSdkUq1Wo7+/H8Mwrhn37oaMyRKEEHiex9TU1C1LGLwSgRDk6xY1P9yGEVKSs10yhsY7t61DVRWylRqqorKiKU3/2CzzpSo7VnUwW6hguT4Y4WvJVyxa0nFqZQdD1yiU6wRBqEdbLlvUai4tmQRexWFkZIHRizlePDLK9g1dvPWBjTy8p5dSyWJisobjeBgoSE8QKBLpC/y6xw+fOsfmdR3s2bsKCO/nS1r2QgheenEQtzaKKgWBDJBCRTd1pB+g3IC0vlH88f2Aoy9coFax6ehqYMWqZiJRg1y2Qn6hSixm8OhjW1i1+vbz7MvxWtRgcH2D2y9/+cv8wR/8AZ7n8aEPfYi3ve1t/MzP/MxV1/Ab8ecSbiQ54roup06duu3NkMtxJ1zQ1NQUZ8+eZfXq1VcNEdwuoX0zuK5LNpulvb39phv614KqKLQk49i6ujzc2NGQZH9XIyv6VtPY1AiEBthHR6YZmS/S1ZwiaRpYjkexboEC2VKd7uY0Tt1FCKjWXYQvSaWi2LaP4/gkGkwUT6VQrKP6JqV8nf81WeBr3zrJgXv6eGB3H3Ozc4yNVYlHNaQdxkTb8tAUBV9KRgbn+NxnX+BX/sMjGEZoXLmkZb969WpK+SjCnkYJAkQgEApEYya2JfBd/4bDhteKQZWSxQtPneP5J87h2C6VQo2eVS1s2tJFveowNZ5nz77VbNh8tTfb7UIIcUdGsreLG8mTfP7zn+fZZ5/l/PnzFItF3v/+93P//fdfdY5/aTFIkXdr1O8OEQQBU1NTXLhwgQMHDgDhBTE4OMjk5CRbt269o4lBgLGxMXK5HPfcc88tHb9kvJbJZNi6des1L8oXX3yRnp6em5oQvBJuEFBwLBK6SdI0cV2XI0eOMJrPM93UwGS9hi8EjdEob17Rx+6OTj7T389QLkdDJIIEyo5DTzpN3faouh6dqZCAnalUGZ6eJROJkvA9VvX2kKs7DMxmaYhGWdvciJCSczMLeF5Ad0MaTVUoVC1UqdCajGNoGqqESt3B9QJsy6NWd9m+sp3JuVAz13Y88oU6Xc0pXCcgm6sSN3VkEHb2MnGFD7xjNw/t24jr+XzuK0c4eHgY1/LDSWgp0VDRNZUAwdvftoWPfXDfdROgg8+e53999nkqJRsZCDRDxYwboKhs29bNr/6nx6743f7+ftrb2+nq6rru5+B5AV/9wotcOD9PLG4wPpajXnNJJCNs3NaDFwSoisK7f3IXPb2336kbGRnBcRw2bdp02797N3D48GE++MEP8hu/8Rs88cQTfOELX7iKiN23bx979+7lj//4j4Hw+9bb28u///f/fpkQvxwf/OAHqdVqfPOb31x+7L777mPnzp18+tOfRkpJV1cXv/Zrv8Z//s//GQgnetrb2/mbv/kbPvShD3Hu3Dk2b97Myy+/zJ49ewD47ne/yzvf+U4mJydv+Jn9qOG6LqdPn8YwDNavXw+EE9L9/f2oqsrOnTuvWGe+HRw5coT29nZ6e2/umrw0hTAyMnJdoxPP83jqqad49NFHX/VNM5vNcuzYMcqGjt7dhR34rEg3sKOtg5iu863BQZ6fmKDquiiKQnsiwf29K3hhbJLpcpmIrofbIShIIZmbnae3vY3ZbBZhRkEqNMfjRHSNQs2mXLdpjMWIGTo120MEguZ4DF1TMRSVSt2hZnsEnqBUtuhqThNFZSZfQVMVsgs1WtJxFAlz8xXiUYOIolKpOJi6RiYZZUO3zi///HuwbJ9Pf+45Tp6ewrN91AAUESY6vhcQieq8/bGt/MyH913zvRFC8n/97//EhcF5PN8n8ENZAjOi09iS4J3v3sKjb91+hTxEqVTi1KlT10wcljBweopvfukY7Z0NqJrK6EiWXLZKtWLT3p1h1bo27n9oPRs23VlitbCwwMjICPfee+8d/f7dwC//8i9Tr9dZsWIFUko+9alPXXXMGzHoEpYIlWeffZYtW7YsE5tLBdWqVauu0rO/VUgp+d73vsfDD1/tyXEtOI7D8ePH8X2fXbt2XXPTZ3JykpmZGfbu3Xvbr+dyCCEYGBhgfHycFWvW0NHTQ0MksjzFNFoscmhigovFIo3RKHu7u+lJpfnymXOM5PI4QUA6EmFVJsN8qcpodgHbtsk0pFnI5mnOZFDUULe/ZrskDBNtcdXf9wVJw8TQVHRVxbY9ClUbEQhKZZuortHdmGZ8pkjE1Mjl6yQjBsmoydRMCdNQSeom+UKdqKEReIJkzGRVdwM7NyTZf99u/uyzzzE0OIcSSHw7nJJ0HG/ZWPJN96/j//PLb77m5zo2usDv/7dv4tg+qgKBDEAD3w1obI3zwY/sYvOWVVfpSJ84cYLm5mZ6enquOmcxX+Mr/+swYyMLrNnYQTRmUqs55BeqTE8WWLe5k8c/sIeORYOkO4HneRw8eJCHHnroNWmsXQtSStra2vit3/otTp8+zc/93M/x9re//arj3ohBl+D7PpVKhWeffZbHHgvzat/3OX36NIVCgR07dtyxHueSB8Ob3vSmWz7+5MmTNxxkOnbsGM3NzaxcufKOXtMSarUaR44cwbZt3vzmN1/R0BdSMlYsUnIcMtEoKxsaqLouh8YnOT07j6LA9o520qbJ8xcnmKlUKeRz9DQ2YkaiDIxOkEqliEUiqEIhWNy0lYFEV1Q0BTRFxfMC8hUL1/WpWx7Cl7SmE+TyVQIRktBKAO1NSSanikgkjbEo+VwdTYOoqmPVXHRNJRmPsHFVhi0bG3npVIHB83PgCoQf4Fk+ipRoqoIQkr7VrfzW77ybhoarY/wPnzzL3/zpM/iej6YqoIBuqrgCWjtj/Owv7l5uwl1+X1lqwD7wwANXnG98JMsPv32a/hcvYlkumaYEvatbaOvKIIRk9EKWBx7ZyIGHN7yqzxPg0KFDbNiw4XXVj/2f//N/8pnPfIaPf/zjHDp0iG9+85tXxcM34s+VcBznqtyiVCrR399POp1m27Zt1/VtuRnOnDmDruts2HDz60sIwblz55idnWXHjh3LkleX43bzqhthcnKSM2fO0NDQwL591+dDIIxJFwsFstU6yYjJuqYmLuaLHJ+epWTZdCZiDJ47h9bSQd6yqRfytGSasAV4QYChaiAW5UYWt9Dy1Tqlmk3gSVwnlEWRvqBSC/W0cQMyqRh2zaFccehoSlHKW3i+TypiUik7RHQN4QUoAlKJCJ1tEZxAZXKyjGd5SDdAEQJDUfEcH1VVMAydD/zMPt7z+K6r/s6/++vn+faXj4XNKUVF0RQ8z0czVNZsbuTt7117hUTb5d+tU6dOkclklmtuzwv46t8e4sLALPW6Sz5XwzBUdE1jw44ekg0xZqYKvPv997B+86u//s+ePUssFqOvr+9Vn+tOMTw8zC/+4i9yzz33oCgKfX1914wp/9Ji0I/FhPbl6/6XO1nv37//Veng3c5kwMTEBAMDAzedQrjd6SQpJc9PT/D0+AgF2yai62xJN9KaK5KIJzhYKyF16EmlMVSVrFXn60MDXCwUuJDPs7ZpUdwfaI3HeXFyCgONfT3dy6+xMRKh6Hm0xOLENQ1TDacXbC8gFZU0xmPkaxb+olZtMmoi/IBS1cYXgkw8ylSuQr5SJx0z0aRKzXJRJRwdmcF3AoIgIGmaxCOhuVu2VA1X41Gx7FDTyCoJ/uYfjzA7V+en3r2T979jOyOjWS5eWMBAQfgCRRHYtoemqRx5aZS3P7KZttar3cqllJw4Oo5bD0in4jiuj+v4ePWAhmaDeq3IoUOHrtCRvpUJybELWcZGFujqacSM6ERiBuOjOXLZKoPnptm6awV796++IzIbXrsJyevBtm0ymQz/5b/8F37913/9qp+7rsvRo0f5zd/8zeXHVFXl0Ucf5dChQ9c856FDh/jkJz95xWOPPfYYX/va1wC4ePEis7OzPProo8s/X7o5Hzp0iA996EMcOnSITCazHMAAHn30UVRV5cUXX+R973vfq/mzXxVeKTkyOzvL6dOn73gz5HLcagzyPI9Tp05RqVTYt28f6fTV3wm4s8kAKSXjlRKjpSK6qrIu00RtPtRiH9dVDhdy6E4dVQkdsjc0T7GjpZ0nR0bChlhTE4GUjJdK/MXRoyQ1k83tbcuSRi9PTDJTqrLe0OhMJXFKBcYdD9sPWN/aTDoaYaZQoVC3ScciNMVjTGZLVGwHTVFwnYCZQoWYqRPXdMo1BwUYmS3guX5IPpkGhq5haCr5Qh1FAV0q1KoOMpAoSOZmy8zPCuruU/zch/bzgXfvYnqqSHamhAwkCIHnBqgK+JbkpUMjvPsd28hkri7opicLLMyUEa5PKm6i6ipG1MCqOchAUK3mee6555ZNypqbm2+ooR0EgvGRLAefOMfCbIlMYzw0I1nbRktbiqmxPB2dDbz/g3vINN75Pe+1mk66EVzXZfv27fzX//pfr/vzN2LQJbxyOulubIZcfu6llfqbYcl4rampia1bt173PnY3JrSXNuGKlsURu873LwyijI/QkUjyyKrVJHWDz544Qc6ySJkmM5UKZ7JZVKng+4LedJqoobNQq/Pl0+doikTZ2JCirimUA8F4zSaW8NjR08KFuTyT+TKpWITdPZ2cHp8jW6nTmoyT0A0mc2V0VaEhGqVQtlCAuuMxk6viewE6ClFNw/HCHMT3A9KxCLVKGKekJ/Adn7ITcCpf58KQhuOmeOdbNvGZySK52TL4AtcNQtkRTSJ8yYkjYwwNzrH+GpqNp4+NUy/WcW0fTVdRVRUzqiNVg4huEk8onDhxAmBZP7G5ufmaK/9SSo4+f4FDPzzPxcE5KmWbWsmid00rHT2NJFY2I4Rkw8bOV0Vmw6X70usZg5b0I3/2Z3+WFSuu1lyHN2LQtbDUIBdCUK/XOX78ONFo9I42Qy7HreZAl/t4bNmy5YaF7d2IQUubcNFMA4OlAsb0FB3JJOubmqm6Ll88fZpz2SyW7xMzDNY1NVG3PS7kC4t+AJL+6VmqlkNXMkl7OkleKvxwdIqoYbDS0DA1lZMTc0gJO7rbyJZqTOTKpKImbYkE4wtFAFrjCRZKNaSQGIrKwGRoBKsskt8Ekrrl4To+qahBpeIgpUAJNBzHCzcjPEF+vsKL81UGBubZt3cNc8kSCzNl8ASalChCEjgBmqYyMZzlO984yYd+5r6r3puTL48R2B6qIgkCBUVXsGs+kbjJ2jVdpNNpZmdnGRwcJBaLLZNLmqZdlQMV8zW+86VjlAp12roamBrPY1suIwOzRKIG0biJYWi0tl87571dvN41GIR1WGtrK7/7u797zZ+/EX+uxuWya3djM+Ry3OpGh23b9Pf3I6Vk//7915XuvF0d/2thaRNuenqa9vZ2dF1f/huFlByfneXo9DRF22ZNYyM7Ojr4wcgop2fnsX0fbbEp5nki3D7VNJ4slpgvFFkXaLQm4pzKlXEXKqxtacKQCkOzeUxNoyeTZmqhjOsHtCbjVGounh8Q0w3y5TquF6AEEssChKRUdVCERJWQzddwLY+IrlGvuYBEeAHCE+Gx+TrF+QrJRISEqVESElUBRYDjhLwSgGP7fOtLR9m5awW9K5sve18kQ6enELaHqioEgQ+KQixhgqayccNq1q5dSz6fZ3BwENd1aWhoWI5Bl9dhvhfwwhNnOfnSKO3dGZrbUziOj+f62LbL6NAcjW1pVq5pYeWaV7cZcvnn+nrHnyAI8H2fBx54gI997GPXPOZfYgz6sSC0l9b9lxKM9vZ2Nm3a9KoviltZM1kqHufn55eN1252zlcGMV8Ihks5qp5LRzxFdyK1/IU6NDPB3w2cQlMUGiMx8tUyX54Y40DXCu5tbiI7dI57M43LpHVXMsVIscCh6QkSqrn8OIQ6kZ4QCK4kTpwgQJHgy0uPl20XU9PwAoEvBMWahZBg6Cply6ZSdYgYOroUTOfK+L6gORmnVLXQUVEVJVxrDSS266MEEte2UCTYtovreCRME6fuIYVA8SXCF5RyFl//1kmmpov88ice4P49qxm/kMOx3XBSyQ9dfBUDFmbLnDs3c01Ce2Isz+jgPEHdxfMC4skIzU0JrLoLvsL9D+xkw4ZWcrkcFy5cwLKssOgzzWUJgcvfI9tyOX9qiuefPs/MWJ54zKSxJUkmkyC1Lcb0RB7dDDuGsZh51eu5VbzehNKSGdL1bv4LCwsEQUB7e/sVj7e3tzMwMHDN35mdnb3m8bOzs8s/X3rsRse8coVF13WampqWj3k9oes69Xqdc+fOMTU19ao2Qy7HrcSgaxmv3eh8cOuEdiAEXx0e4LmpMaqei5SgWja7InHetmsPX3npBVRg/WLc84KAc7ksF/MFNFWleTGh0xWF7lSK03PzNDRGl8lsINS6BiwpQ0khXxIEAkNVqTguUoQTko2xGGXbYSooEQhJQzzKfKmGIqA1naBQsag4LlFDDxtqItRzE56g7CxOT1ZslEASMzRsywsnmLwA1w8LusAPOPLyGLNTJT7x0f3s39PHV79yDGH7SF+gQpgkeT75uTIvHh7hsbdvvep9e+b7ZygvVAjcgLLloWoKZsQAUycdifCudz+Iqkry+Ty5XG7Z1EQIwczMDM3Nzcufo+8HPPH1E5w6Mkp2tkx+oYpTc+nua6anr4VMJk61ZLFydeurIrOXnv/1JrTr9foNG9FvxKBrQ9M0arUaQ0NDaJrGgQMH7ngz5JXnvVG8uLx4vNx47Xq43fVdx/c5PDvJ8flZnMBndTxJdHaBzsYmhpNR+icrdEcMMobJaKnI354+QYMeoWDbrGtqWn4tw7k85xayPNCzYtkUW1EUvCDAI/TCkFKQr3uYqkLJcbG9gPlKnYZoBFcIxnMl6q5HWzpOxXap1z0ak1HKdYdCxSIZM6nUHJQgNM+WvkD4korjUPEJ1+2lQqlsITyBKiS+VFBkSGxLIajUfb7ylWNs2dzFrs1d/HC+ShAEaAC+wHdCz5PyQpVnnh64itB2HZ+XnhnEq7vouooIBAGSWiUgljJZt76LHTu2I6VcXjGdnp7m/Pnzy9/9aDRKJpNBVVXGRxY4+P0zqJrKijWtjAzO4Xs+Y4NzJBZllDRVpXfVjXPfW0Gw6OfyepqhLWkx3kg64o0YdDWW6q3JyUkGBwdf1WbI5biVeHEt47WbnfN2yaRsvUbN82iOxViYmmZ4eBi9u4t/mp5ksJTn5LlTGKrK9tZ2EArHZmboTqXoMQyqrssPRkdxXJ/7e1dgLr5XuZrFglVndXMjqUiEQAhUBVDAReJZTkhIq5L5Sp1y3aUlFadqu8wUKiQjEVzfZ65YIR2NYrsejuXTlIhRqdoIIQgCQeAIPOGjSCiXxWIuo+BLgYZEOoskSiARQUB+zuOHTwzQ3BzH0FQ820e4QTjtLWXYhEPyzPfP8vZ3bSfTeIm4m50sMHhiAt92l7dJCFQSqXBTuK+vnVWrVi1L/eTzefL5PAMDA7hu6AUyMTFBY2MjlYLLD75xkgtnp+lb104kaVIt21TKNnbd5sLALE3taTZu7WbV2qtX3O8EPy450I18jN6IP9eGrut4nseJEycoFArs2bPnKi3pO4GmactGjtdDPp/n+PHjtLa2snnz5pvyT3fqDQCXGvqW4yBW9vLFoUFKjs29wufBFSs5N5/lO8PD+EIQ0TTO53J89dwACFjb2EwyYlJ2bJ4dGSNlmjy0ahVCSMZyBXwh8ReH+4SEqKFRsh1UD1LRCG4QDhAZmkrU0Jgv1kiaJtGoRqFk0ZCI4rs+9ZpH1NSoVh2kkCBA+JK640AAwg0JbFWCLyQ6KrgCXVEQbkDVsVBRQk8Sf3FDP5DIQBAEIcldnCnzj589xH/6nXct32cWZktMj2QRixK1mqmjaQpe3cNMmHR2ZZalfqSUWJa1bC45MjIChBtH1aLL4e8Pc/7kFPMzJcq5KpmWJCv6msnOVSgsVKlVHB5+xwrufWAdkcidTf+/Ej8O8ScIAur1+g01tP8lxqDXndBWFAVVVXFdl/7+/uuu2t8JblbIWZZFf38/iqJw4MCBW1odeWUiNV0r87mBE4yUC7giIGmY7G3r5oPrtqIpKs9MjKEAvakG8vk8slJjXVsHU9JnrBZqYOuvuPiThknRsonoV792U1MJfHnFNHJE05BKSDohJSCJaBpuENCkx9BVFQmgXNIXcv0AU9eouwFV26MhGkXXFOq2R2M8iqFqlMs2jfEoih8al6hC4jmCivRRBdQDDyUIiSRdKuBJpBDYjuDQ88PYVYdf/oWH+O63TzOdq0EAKhKVcOVF1VROn5jkoQevXAMKAsF3vnqMhekiChLbcrHrLtWShZEwSSSjbNjYSXNzwxW6k/39/ViWxbFjx9A0bXlyKRpJ8J0v9TMyMEu14lDKVRk4PkHniiZWrW9H01RUTaW7t/FVkdnw2uknXQ9LhPYbuD0IIchms0Sj0Ve9GXI5bhaDZmZmOH369C0Xj9eaDKh5LseyM4xVikQ1ne0t7axraEZRFI7Oz/Dk+AiZSJTWSJT5uXlygcdgWqOrUqTq+XSZl6avDE2jIRJlcGGBTY1XdqxVRUEhlE+64m9UVUASBhjCqcXLficQEilBUSQShZrthav+mkrZdYhpOoam4jg+EV0jZhrkixaJiEFKN6k4NlHToFZ1kUGA9KFuh008VYIuQRUS4QaoQoIImBpZ4H/+z6f46ffvJpOIkq+UUHyJFBJfCFBVXF/Qf2T0KkJ7eiLH0eeGcKsOhqkjNQWpqdiWSzKis3pNG/FFp/AlHWkhBJOTk4yOjjI5Ocm5c+dIJpM0NzczP2Fx/PAIja1JUg1xPH8a1/OZHFkgnYmjaqHu3doNVyYBd4Ifh2TqjRh0ZwiCgKGhIXp7e1/1ZsjluNGEZBAEnDlzhlwud8vF4/XIpEAIAikwtUv3P18I/te5kxyamcBQNVzH4bnSeTa1tPH+9jbOnjlJq2nSHI2SiERIRyIM5Ba4mC+wrbntiniYMAzcIMAO/CvOrykQCIkvJHLxMV1RCITA9QP8IMDQNVxXYLkuCmDqWritIRUiepTAt/D8gDYzQaFogZS0JOLM1yoko2Hj3pU+SqAgfYEtBAgWCW1CAhyQrkAJBK4TcOKlUTo6GkhGDQolC1wBgUSREkVVED70Hx7B+bk3XVFMHXziLBPD8wgnXNMFBU1qJNJRhGSZAL9cd7Kvrw/P8zh69OiyJrlVd6lkAwaOZsnOVlm7pYdkQ5SWtjS5bIVKyWLo7AztPY1s3dVL37pXTyj9uMQf4JYMkd5ACGVRigfCdeVdu3Zdc9X+TnCzHKhcLtPf308ymWT//v23JCtwO4R20bH58uBZTi7MYfsesm6zXjX5wH37+X/PnSFvW7TrBqsbm6l5Ls9PTuD5gnWZpmU/o1QkgioVqp6LL8QyoV13PXRVpWQ79KTBE3K52e8IgXB8dF1FQaFsOfhBQCJqIAKB6wky8RieF+C4AbEGnXrdxfEDGjSVwA99D5K6ScVzMDQFzwqlz7QApBAEgpAckmD7Pqon0CTgBjiOzUzZRtc1gsWfKYFEEYtyA6pKYabEwSfO8p4PXJqWe/a7pynNlVA8gS8DtIgGikK9bJNqTrLissaXruu0tbXR1taGlJLZ2VmGhoZYWFjge199kYunChRzDvWKi1Wxae9uZPX6dnLZClNjOTRN5S3v2MqWHb031MW9Hfy4xKA3cqDbh+M41Ov1u7IZcjluFC+klIyOjjI8PMzGjRvp6bk1U9LbiUFVz+VkdpYFy8IMBHJyhvZMhql4lB8MDuDaFqqUPDsxytHZaVzHpyESpXXxGnKCgCeHR2iKxUgsNvMt10dXVDwhKNo2KgqOHxDTVIqWRVI3QEJc16l5HqorSUVMJJJS1aa9IQEilOTQYwpSgOv7CBn6iLgiwFQ1pAqKpqB6IXGtCUAAUqL4gJAIIfFEgEJIequeAAkikItkuEQqksCXKIFAEQIpQSoKJw9dYOT8HGs2hnnNiz84TzVbBT8ARcH1XFRNQYsamIbGqssmqS/Xke7t7SUIAo4ePYprB3z7b58hN1clkY5hRDV0QyU3W8KM6GzY0sX4SJauFU289T07bukzvFX8OMSfIAiwLOtfXQ70uhPajuNw9uxZpJQ3XLW/E9yokFuaBu/o6GDTpk23fAFenpy5QcDfDhznfGGBFakGIppO0bX5weRFmiIx7u9ayYJdJ22YzM7O4vs+XV2d6LrBUCmPXIyZbhAsJ0gAZddhY3ML+ZrFQr1O8+KU1kK9TlsigY7GSKFIRzKJAhRsmybTxPV8alJiewGKFk4ixhfNy0xDo+qFmkiKCjXh4VgWQSARgOPUkXWBhY/qOwSuwFcEFcfB9wUSgYaKqoaBTXgCL/BDXdpF9kq6AkMCQRis+l8c5bOmwcquDNND8+ALpIBAStAUhCYYvZAlCASadun9f+nZIY4/fwGvFhJK0YiG1DQ82yOiqqxd10ZLy5Vf1FgshmEYrFy5kpaWFkqlUmjsNj7OyZcmON+fp7O3kabWJnxfUClbzIznaWpJLsVmtuy8uc7xzfB6B7NqtXrDRKqlpQVN05ibm7vi8bm5uetOJHd0dNzw+KX/z83N0dnZecUxO3fuXD5mfn7+inMsTXfcjUnoV4NsNsvY2Bi6rnPffffd1XWh68Wgmxmv3QiXJ1JFx+bPT7/MuUI2TCak5OmpEd67aiOPrVzH0blpkJI4IXkej8fZ2tTFUDHHxVJxucl1xfkVSJoRSrYdxpjF5C6QkoZI2OH3hQgbZVKiayqaqmIoCo7rENNUQCCkJBOLoKKgawoly6G3OY1l+5QtF+lKfEXgCQe7FlDDwxMCq+xh4SNcgfRBIhCuD6pEEYtNu4CwmSbDgi4QoAtJ4AXoASAk5dkKX/zci3T3NpKfKMDixokCoEqkojA+PI/nBcvFlOf6fPH/fY6FySJSCNzF77MZNYino4hAsPOeq9fYVVUlkUgQiUTYu3cvruty9sQIz37zLMcPjWFbAYFopqmtgc6eBuamy5TyNS4MzNK9qoV77lvN2o2v/nvwescfCIu5GyVSb8SgKyGl5Ny5c1SrVTo7O++6/8L1YtCST4Cu6+zfv/+WtSBfWcjVPJcnJi5weHYSJ/BZ29DE21asZV2mmbO5LC/PTtGRSOJVa1Qsm20d3Ux7Ngenx/BEQFzTFxvxIRojUSaKpasaZ6auoSoKzmUG4inTRBI22gxNBQlJQ2cuELQbBgnTIGrolC0HXdeImyb5qk3FdvEUiZQBWatOxXeRhLJKdemhSqiXSkgFXMcOizctjI1IBSWQqIFE8cMYRCBxCQluzROoQfi5zl7MEU2YSE+iegEEIREukaAqlOYqDJyZZsc9oRZwMVflO3/3EnapjqKo+J5EjeoIRyBKkqaONOs3XrvxZRgGhmHQ3d1NPJLiH/7yGUbOzbAwV6Fec6mWa3SuaKSrr5WGxjgTIwu0d2V490/vZs1iY//V4scl/kSj0Rvex9+IQVeiWq1y9OhRgOvqxt4pblSH3ch47Ua4Fpk0W68yV6+SNEz60o3LEmqfO3uCI3PTtESiUKlREwFnkwbfnZ5krlajJ5VmtlIFJAnDJKrrTJULbGu5MieLGjrBInEDIakUNwzmFnWpAQxNCU3MNImhaCi6Rtn2UFTIRKNUPIEfBHgIhCLJOxZV18FWA8bLZSzfQ6owVSkTKCH5XHM9UMAXoJgKih9uoij+Yg4UhNOTUoJQFKQQaEKGdVgg8aUHgAgEqh8gl2u2AOGrHHp6gHf91G5UVSE/X+aZfzqOX3NQNC3cZrM8VFOiRjRaW5LXNW1UFIVIJIIiVdx8lKkzFolkEt0wmHIKuJ7D+IVZVEPQubKFwAu498F17L5v9S195reKH5cY9EYddntYigWKorBnz567uuVzvRi05BNQLBbZu3cvmUzmls95q4T2dLXCX546ykipgOM4VKs1VjU28aG2tRw+d4amWAxN1XBch5bGZo7OTlOxXN6y4tJwgZASQ1OwfA9fijC2wHKM84UgrhuhPj7hcMHSoGQgJZqioC0OF/mBQKpQdV1c38fSAmbtGoEv8HXJnFUnEBJ0cF0HtFAuRNEW5fFUBU2TKLXF5vxiHQaEJDYhv6PUAzQhUIRE+sHirGVIaBOI8GBFwSoGfO8rx/jl33onruPzzD/149ftZfk0TddQFB28gHQqSu+q69+bpIDzL81w4cQCUxfymFEDYUp0Q6FcqqFqMD2eRY8oqJrB7v1rbvnzvlUEfvC6bqhBeF3fjND+lxiDXt+oTzhZu1RI3e2O5vVcu0dGRujv72fDhg1s2bLlujc/ISUvzk/wR6cP8X8c/QF/N3ySBd9ZDmLDpRwjpQIrUhmiuoGyKCuSMk1emB1HV1RMFMZnZ1CUcJrPMEzswMdUNba1tNJhGIwUCxRtm5rnMlYqEtN1Hl+/gbetWYMbBAzl8wzl8/hS8vjGjfy7e/fQ15ghX7fI1S1WNWZ4vKuNlYZGIfA4NjlG1arSkokwbpf5yvAAh+enqake877Fy/MzZH2LnOdQli41PIqeQ8X1CCRUbA/LC/ADSc3xcQKBJyR1EeAj8TSAMJCpXvifcMKIJrwAnAAcH1n3OPSDQepVO+zYOQE4HooXoLgBuIJqoY7rXipQx4bm+dJnDlLJV1EVBc/1casuuhAkUhGEH7D73j50/epiZWn6XFVVUqk0hamA088WOH1wAbvsY9UcCqU8sZTAjCpUKxYXBmeRwJvevJ7N2682UrpdBEHwukuO3CiImabJ7t27eeqpp5YfE0Lw1FNPsX///mv+zv79+684HuCJJ55YPr6vr4+Ojo4rjimXy7z44ovLx+zfv59isbhcNAE8/fTTCCHYt+/axnyvFQqFAp2dncTj8buufXWttTTHcXj55ZfJ5XLs37//pmS2lJKsVSNv15dv8ksx6OnJEc7k51mVyrAu08yGxhYMReVbY4NM18pUXQffcZibnaMx00hLSyuqGk4EZ6JRkrpB0XOXnysQgqLl8OCKlbQmEgzn8+Qti/lajdFikQMretnW1sZILs9wLs/gQo6udIo39fRQ8wNOTU4z7zgkNIgYCsfnZnl5doa5oE4em7OFHKO1EvN+naxvUcGjGLjMOXVcVVKTPpXAR0hwfIHnh+tprh/gS/BVCCIKwgBFgrIYf1RfIgVIFKQnUJwA7IDqfJXR83NINwDbR3F9cH1wfPACavk6uWx5+X3+xudf5OTzw/iWi+ILpCuQQmJVHayqQ0MmzvZrENpLv7+UyIwOzPP0l88yfr6M9DU8SzA1XGB2IocvazS26aQaTFata+InP7qXh9666V8UofRGDLp1BEGAbdu0tbXdcE35TnGtGJTNZnnhhRdoampi7969t2VsdHlT3xeCvz7Xz5cvnKXsOkgJL85N8qenXmK4lOdiuYAd+NTyBeq1Op2dnaSTSRK6wXStioJCgLycz8YVAZ2pFEXbXiavhZSUlkyxXZ9srU7VccnbFs2JGAnDYDxfYqFWp1yrYKgKtm0zsbCATUDOtci7FhdrReb8OiP1EhVcisJlxq5hqQJbkZQCD18FTwEPkEE4cSQDEBICBQJdQUTCPRRFXEZqL/0vkOAGKI4PlouTq4HjIZzFuON4KJ6P4gZ4dZeBE5Ph3ygEf/0/vsfsyDzS81EWp8+xfXRNRQW27uilrTNz3c/G93wmhxf46l89x/DJaVasaWf1xi5SDXEipkl2qsz87AKVWg7NDNi8s4Wu3hSqencKsB+H+LPU1L9RUflGDLoS1Wp1WSbrbudAS/Hi8sb50hbBwMAAO3fuZM2aNbdFAlyeA7mBz+cGTvDfXvoBf9D/PP/30YP8Yf/zzNdrjJQKnM1laTUjWLkCyWiULb0riBoGx+anlxvzcKmnljRMNFWhYFlXPKe56OHhepdiaSIaGs0iQ2kxQwrcwKdet9CFxJQB9cCl4rkEiiQvbM6XC5SESwmHaatKWXq4qqQaePgKCBU8RSJUkGqY1yiLvJlUQGggI2pIMMlFcloB1OUwFJJKTpjvKI6HYrlhzeUtxiXHA9cDx2N6JMv8TBEhBF/8kx+Qn8oj/YDAdggcD01TwA9QJazf3EUidf17xYUz0zz992f5hz/9AaPnplkYy5OIxmlqbkDXTEBhfqrEuVNjWG4FM+UyOzu7LFXyauF7AfWKi+/emRTE3cLNCO034s+VkDKU79u8eTPAXScEr8UF1Wo1Dh8+jOu67N+//7bIbLgyBgkpOZ2b4x+HT/P3Q6foz87gL8a8Lw2eZbiYJyMg7fps6eykosLfDZyi4jpkIlFQlMUtVoV0JEo98HDFpdcb0TRMTccNgsX2PTTEo2hqSFLHdZ1ExCRhGNQDge55eJUSGpJ83SZm6CgmjFfLzLl1aprHlFMj6zt4SsjtOITDja4iCRbffqkuDjxpoCBDxlABoSlgqOhq+GqURZmlJUhAEWG8YVGyVvEDFF+A54f/LcYfabucev4CtuXy1JeOMDs0h3Q8FN9H+D6B6yMcF6Rk865eNP3a+UW1ZPH1vzrIkScu4NQ9NF1D01UKsxVSsSgt7Y1oqoFj+VRrdRo7BTVvlgsXLlAsFl+1J8PMWI6v/80LfP3Pj/GFTz3Ls986iV2/O3HtdiGEuCmh/S8xBr3uE9qNjY1s3759eYL5biZTryzkfN/n1KlTlEol7r33XhoaGm74+18bPcs3x84jpMTUNAZKWeKe4MPaetYBFdfFW9Q4uhwx3aDue8xm52gsVhgzDPR0GhSFmucyWS2zpbmNjU2tPJjKUO7sZLCQp+oJOpJJ3rpqDVta29jS2haSR4UCAGuamuhcnJhc09zEYC7Hmewc89NTTDs1inGVehDgqhozToUECqpQqPkehqrRmIxSqYcdvgBBXAkDZKCEK2vLqgEiTJwULXxMFRIlCJMqCaCCH1HRhUB3wukACAkmKYHlVVkI3IDTR8eR9ZAgWurKoaqgS3zLw/cCiMHkSJZP/x/fZG40RyAkurG4mmuo1Eo2ZjLCynVt7Nl3bffYJbJPSsn3v3SMl58ZRDc1Al9Qq9jMj6qs29FNa6tBc0udkfNztPXobNodp61Ho1gsLOtO3ile74LuZvq1AJ/85Cf5+Mc/zp49e7j33nv51Kc+Ra1W4xOf+AQA/+bf/Bu6u7v5vd/7PQD+43/8jzz00EP8wR/8Ae9617v4+7//e44cOcJf/MVfAOFN+Fd/9Vf57//9v7Nu3Tr6+vr4nd/5Hbq6unj88ccB2LRpE29/+9v5xV/8RT796U/jeR6/8iu/woc+9KHX1VkbYMOGDUxPT1Mqle76uV+p3VYsFunv76epqYndu3ffVJ7mfHGBr42e5WKlgILCxkwLndJbLhCPZqdJm5ErNjzaYgkGS3nO5bPEazYLlTI7u3uJx0KyzFk0FNnS3IpWtXhifJThfB5dVXGCgNWNjbx/4ybKtsPTFy8yWixiahpvX7uWt/T1gYSTs3PMVCqkIhF6Y1GGz52llo5QjsWYLxQQWmh0OV2r4klJUjfQpYqzmKRpqoKCEkoPEcYbNAjcMDQoGgSE/1YDlo1ElqST0ENS27CXglL4Q2WJTPLCaWwgbJgJERJJS8dqKlJo+LZPYaFGe2eGJ/7xCN/+3CGcig1aOImgAmogMGMGmq7y6Du3kUhcew1SCEFxvs5z3z7FD795AsfxWbWxAzOiM3Yhi6Io1As+q9atolqpY9cCWrpUhi+eZqGQWTY1icfjd5zQv97xR0p5U+02eCMGXQ7DMLjnnns4c+bMHWsy3giXE9BSSi5cuMDFixdvary2BCElQ6UcWbtGgxmlSzGXzzdQyNKfnaEnkSZhhOv5zdEYQ6UcP5gcoVk1KRWLNMZTdHZ1LcoThVNDnYkkjhlwolAg7vskpCRvW9i+z09v2syFhTznczmEDKVE2hMJfm7nTkbzJfpnZig5Dm2JJO/bvJHpyWl+MHSBugZbenoYnZ1lzvd4LjcT6jzqKnURoLoKKBJVDfVn5aJZkdTCGCNl+G8ARQVVk0h/sVZb+kqqIKVCEFHRXQGKXD6PEkgUT4SEtRfmO8qiDBN+gOL74ZMoajjuLSQz43mklHz5z5+h/+lz+K6Homv4noNq6KimjnB9Ek0J7r1/3XXJ53KhxjNfHqC64DE7XkQISeD6rNjQQTIdo1Ky8D0QtgGGSu+qRjLtBkeOHMEwjCsMtm9F9uF6r6GUtamWLZLpV6//fieo1Wq31Bh6IwZdQmdnJy0tLWSz2bsegy73/dA0Ddu2OX78OEEQ3NB47Wbn9Lxw8vjbY0N8f2KIpmic1fEm6r7H8YVZgoFjPNiximK1ivR8mhqbSKVDbe60GSFnWUR0jfJyQz9srFU9ly0traH/R6VC0jSpOA66ovDgypWU6g6DCzkgnNB+bN0aSlWL/pFRkIIt7c24qsZ4PkfNEXhKgCMkxZKDIpSQpGYxDBCSRhogfEBbJK3l4jaIy6X8aDHGoIaNtsBUMF0VuZgcSbFYxAUC1Q1CAkmEP1MlyCAAx4Wlz3exDnPKFmPD8wy8NMLhbx1H2h4gUXUdqQh820U1DdLpGA89tvman0c5X6X/4BDf+/vDWK5NOt1AtWLjWC4TQ7Os3NhFMWKQnSmiKBrb71nHtr3dJBtVxsfHOXv27BUG26lU6rbyGCklJ164wOEnz3JhcJzzz5XZeWAt9799K2b07mjj3g4sy6Kn58YDUm/En0tQFIXt27dTr9cRQtz1PPaVhPbc3BynTp2it7eXdevW3dFzLRHaQkq+MHiSpydHsHx/cVtM400dvbxz5XoGcvPotosrJR0dHRiGSZcR4UIpjyaUcGOdS5uycd0gbhjMVmusbGhAUUIvobhpENN0JkolMtEodc+jIRYFAdPlKp6bx7ZqZEyNVCpNTvjYuqQeBAyX8mFoUMKYoyzSMAJQdZBeGIdUM+R/Ql3YsPZa2j6RqhJunqmE8o2GguIoaLqKpql4XrDcFVS80FctXCsJJUtQFKTthzHIX4pBgKZSXihx7ugY3/zMM7jV+tIbjFQFmgEIiJo6u/Zdvc0hpeTQd07x3LdOMHRiAtf1EE0yNKhVVaJxk1qxzuZ7VzMXM0lnYnz8Pz1KsiGyrP9/6tQphBDLMrVNTU235V8zO5HnH/7sh+TnK/gioFq0eeorx5gZy/FTv/TQdUn4HxU8z/tXyQW97oQ2XNKFvduJ1OWFXLVapb+/f1mb6UbGaxBqYz85eYGkYdISDS8KISUnZyd4rjDNW7iHjkSSuGFQ9hwazEtd66JtkxFw4cw5Prx3P6sqeV6cneJCqUBE09jW0s6HNm7F1HXSms77tmyn5IUduZZY/ApyqjudpntRhqXueRzLzuCJANv1+fL5M1zMzhMAC65LTNVYqZvMAWgqQtfBhxQKgfCZr9doUAwimkYpEDQkohRqFoEagKbgB0uJ0VJxtkgmGWBYoLphEJRiMRdaPF5RF+NYINBqHqrtowaLBbSiIGwPxfZAiLCTp6ohoSQ1ZCAxDJ2zR0f5zO99m5nRBVRNRdW0cOIxkMSTEbxAkE5HefdP7sI0r33Z1qsOx5+7wMLkCY4+P0xzZ4aWjvCGMHZhHrvuMjuWZ/2OXlwroLu3nfd/5D6SGY1cLse5c+fwPI/GxsYryKXbwetNKFWr1ZuSSR/84AfJZrP87u/+LrOzs+zcuZPvfve7y0L+4+PjV/wNBw4c4Atf+AK//du/zW/91m+xbt06vva1r7F16yXt4V//9V+nVqvxS7/0SxSLRe6//36++93vXjH59/nPf55f+ZVf4ZFHHkFVVd7//vfzR3/0R3f5HbgzLBnT3m1cPp00MTHB+fPnWbduHStXrrwpaTlRLfFnZ19kwarTGksgpeTF+UkiNZvdVo2GhgYCIbnWWaQQDJw/T5+ZYGv3CsatKo1SEAhJxXXY0drO9tYO2j1B1HHxW5qpui6rGxvZ3dFJYzRGazzB6sZG6p6HoWlXxKV9K7o5ODnOk4PnGM3OY+sGFbtGk6Ew4VloQg/j42KsqLthh71R08j7AVFTI64aLFh1dEPD9QUBIZkkJQgDCEDzJaoL1Am127g0SaX4oQmusjRF4EtUO0B1/EvNMxRYJJjw/OWH0HUUXYCnoSgK3/7cC3zlz5+hXnPC+CTCaR8tZhJ44Qpd54om7r1/7TU/KyklLz4xwPPfOQOBztxUkUhUR1MVOla1UMjVKOVrlPJ1Ji8soBsau+/bwHt+ei+u5yybS164cAHDMGhubl4ml25Vk18Iyex4gUq5TldbaIDyeuBmE9rwRgy6FjRNw79MTuNunjcIAjzP4+TJk9RqtVsyXgMouzZ/OXCU0/k57MBHV1VWxFLsWJxSnKqV8WSwTGbDorazGeXE7BT7HI1MPIGaTi5ry9Y8F08E7O3spi/dyML8PPNWnbwISEcivG31Gt62eg1i1WrOZrPM1WokDIMtbW00xWLc09XF29atoew45K0a5wYHOb0wj5uJkC9XGJ2bAN8nZcbQA7FoAhvQIFXqfkCgSZq0CAXHRTNVCCSOEPiLl5siCCWNdPA00DQw6ovk0xI5LSVSJZxcUtRQx1uG+tmKtziZJJdWdEFxPLCdkEySLOdAAJWFKt/4q4N88y+fwam7KKqCDARaxET4AVJTUVWVHXtWsm331dshxWyF8/1jHPzWSUbPz9G3sZtK2sGxPUoLVaa0efo2dTE3VWR6PIeiKux7eAP33r+OxpZk2IgrFsnn81y8eJEzZ85cRS7d7F7lWB5Pf+0YR587TzFf4ezBHDv2r+Hhn9iBcZ187UeFpfhzs9f8Rgy6Gj+KGLQ0pBQEAaVSiePHj9PS0sKWLVtuaYBJSsnZQpb+3DSW77Em3UyLDHVYbd/nuZkxkkaE5miYqycNk55kA4OFHE01D8+2SLe1k0peincV16UzkWRduplnxkcp+R6xWo2y69IUi/GJbTuZKpV5fmKCquuSiUZ5z4YNvGnFCsaLJS7kCyjA2uYmmlSFLz//PEpbijm7zoxno0qdPD5Cg3jERHMFQkhs3yeladieQGgKUV2j7vv4Ggh9kWharL/EYqhQAjBcLjXuWazBVAUhBbquomsanhcgvGDZ14ggZMVVLRzykXUHbAe5WJuhKSiqhlDg5MFBXv7WcaxCFUVVQNMQIpxyxNRRpWTTzl56+q5e9z/6gwF+8OUjTFyYp5CtYMY0InoMVVWIxE3qFYdaqcbqDZ2oChx42ybe+r57ljfS1qxZg+M4y+TSyZMnkVIuE0vNzc031VI+/vww3/r8i6GHkaniWB4/+PpxKkWLn/j4/tdcAuBWmvpvxJ8roSjKcq57tzedl8hnKSVDQ0OMjY2xbdu225Y48ESApqioirJc253KzfHUxAgNkQgrUuGQZNV1OTgzTlrVyebzNJpROjraUdUw3umqSkzXSagmE5USTUr4uOV51HyXt69ey2y5ylA+H9Y4wH09Pezu6OL49Cyz1SqNsSjv2rCOVZkGnjl5hvMz02xYv5JzExPMqzZZy0LRQr1/IcH1BTEUFF9gIYlrGrYfIJa2PpYGEoPF4UTCxzVBKG8UKkmGBLWyFI5CORNVVck0mFh1D88KG2IsxhlFVVAUFVVT8J0a0nYXg9siq65r+MAX/+DbZC/OhfJJqoKiqSiaiiD0aerpa2HLojQbhFzLUP8Yz3z1KCefHyaSiKLpKhFNx67aqJpGIMywvrQ8pkZzpBrjPPLenTS1hveCjo4OOjo6kFJSrVbJ5XLMzs4yODhILBZb5oEymcwN71VHnxkkN1+md00b8/PzZDJppFAYPDnJxYEZ1m69O76At4p6PWwK3CzH/5cWgxT5SgHV1xhSSlzX5cknn2Tfvn23VGTdKizL4plnnmHHjh2cPn2alStXsm7dulu6uR2cGeUvzh1hbbrpiuNHs3MIKfizt/40UU3nr84d4+D0GJlIlJhukLNqVMtVHopl+PD+B5c1wefqVeZqoZvsqnQGVVHwfZ8nn3ySRx555KYTMcezM3zu3Alm61VcETBdLqN5AVsbWqiqKuey86iqQiMqNhoxwwgNTDxJgxFBUWC2UiOjGfhBQN53w0KPxeQo3FMLJ7GlsjyRrXghca15YNRCgjs8ThAtChQRmlFKIaHmYeat5akAIJyMtBzw/XBVRgHUMElC12jva+Ftb9vENz/7HOVCHUXXwmIPBXQVuaihpCdM7n1wPT//ybde0412bjLPn/63f8StSuy6T36+QqoxTt+WbpKZOCPn58jNl1EUhRXr2zBMgz33r+Ut796+PPEkpaRWqy2TS8VikWg0upxUZTKZG5JLdt3lu1//IQ3pJrbuWktrV+am19ndxic/+UlSqRR/+Id/+Jo/9z9XBEHAwsIC/f39vPnNb76r5x4fH2d+fh7TNFlYWGDnzp00NTXd0u9+cfgkXx8bYF26+TIda0H/xEV+dsM9/NSW3Xxx6BTfHB1kXUPT8ursdLnIfD7Pz6/cxKP37GXOqvPDyYucXphHV1X2tnfzcO8qUmaEyclJpqenuffee2/4WqSUnC/mODI3RcmxuVgsMjg3i3B9fENn3rKISehJZRgrFElEItQCH91XaYrFmK1WkQLaI3GmyxWEEk4TLS9kLTXRlmKPBNUDhERzQfXBqC5OF4jwcbMUYPphsqoqCr7loeVtNNu7bA1OQdZtqFlhLFqcSlJ0HQwdPRVl965uTjw7iGN7KFpooKuZBmgqmqGDrpNqSfLxX32EfQ9daWBbzlc5fXiEgWNjHD80hJnU6V3VxcDJydDfO5Cs2dFLqjHBzHiBhbkSW/f1sef+dWzbs5LIK6aHgiBYJpdyuRyWZdHQ0LAcg65H1CzMlvjm5w5x/tQYvhvQ3JZh1/3reOR996DfJbOlW4GUkq6uLg4dOsS2bdtes+f95w7XdRkeHqZWq7F9+/a7eu6jR4+SSqWYmZkhmUyyffv2W57A/auBo3x/cpiuRJqkYWL7HqPlPE11nz9978d4bmaMz5w9xpp00zJhLZGcn5sm6vj8t/2PcsKp8Z2LQ1Q9FwUljEEdXXxs0w4ius7hl1/CjsdoaGmhK5miPXF9IsATAbbvM12t8LnTxzk9NUnBc3EUhc5InEq1Tg2FIAhHjtJ6FIEkb1l0RBOhfr/rkNR0yp4bkthLuY9ULsWhxSJODUD1JYYFunvZsb5EFZJIWWCqIeGMlHhFG71gowYBiqouVn4SmS8hbWe5iFO0Rabc1GltS1GZKWA7XiiZZmhIRUVRVdSIiaKpNPc08Wu//1OsXHtJnspzfAaOjvLdLxwmN1tibrJAEPg0tTeQbE6TnSkRieoEvmDLvjWh+Zzt8eFffpje6+jgAti2vUwu5RcL6ssnl65FLn3jc4d46ekBzJhGIF1ikSS1ssWD79rOo+/ffUvX2t3Cl7/8Zf7kT/6El19++TV93n/OEELgeR4vvfQS3d3ddHffvQJcSsn3vvc91qxZw+joKBs2bKC3t/eW6jApJV8fPcfXxwaw/PD7gZR0axHem+5m85Yt/Pbhp0gYJunLzK193+fE1Dg/kekin0pwurBAZyJJTDcoOBYV1+XDG7byUO8qnhkd5R8Pv0Cmo531zS08vGIVaxrDHM3xfWqeR9I0r2joCyk5lZ3jhZFhXr44Qk5VMHST8UKBQEoSRgTHcklHIixYDlFFJ6WbZOt1UrqBbbvYilj271FQLtVfhPkOAjQvjEPx+mJuJMPGteqFDfxoWaCrCrqhEY+a2JaLnbfQC/VQ49/Qlhtw/sxCOB25RCRpKoqhg6IS08GqWIuxSQVFRTX1sP4yTZq6G/mNP/4IPX1h3PAcn2M/PMehb59g4Mgo0WQUIx6hsFABBLpuEG+IY9k+nuuTbIjR3NVEz+oW3v/z95POXH9QSEpJpVIhl8uRy+WoVCrE4/EryKXLSRbfC/jL/+tbLMyWaelMMzs7S3d3N5WShWO5/Nz/9g7aexqv+3w/CjzyyCO8733v4zd/8zdf0+f95wzf9/F9n+9973s8/PDDtyWDdjNks1kGBgaIRqPYts2uXbtuyzDvQjnPt8bPc66QJaLp3N++gqbZAptWr+Xp8jzfGhtkfab5it85l52j05UQiVPVFValL12DU9UyKdPkp9Zu5quDA4zncziOQ3Omka2tbXxi+y4qjsPp+XnqnkdHMsn29nZihoGQEsvziegaddflyaMv89TUJDlNZaJSxXdcIrqJH0hsz0NKhc5ogrlaDRWVlGpQsCykCv5SLJAs111Lw4yKCPMf3YNooBHXwlwipmrYdQ/TlygVQeCEptuxmE4sGkFXYfbCAkqujiIlmqGjaiFH5I7PhY19udhUU1XQtUVt7SBstqnqYlNNB01FNQ0iqRg//7vv5aH37EBKyfSFeb77twcZPDZGPlvBtX0MU8fzBUbCIJ6K49Q8mnsaqdVcHMtj5wPreeCd29h8z4qb3nt836dQKCzHIM/zyGQyNDU1US8ETJ5fwHU8eta0sfGelfzF//ktahWb5vYw/jQ1NmJGIkxcmOet79/D/e/YesPnu9v4xje+wUc/+lHq9fptTZr/c8frPqG9dGHpun7XJwOWzn3mzBm2b9++3HW4FeiqtriSIdEum4EUSFRAW5wq//D67TRFYhyem6Rs2+gVi7dm2vnI/gevSPzb40na41cG0MtX8V6JC+U8T04MM1BcIKJqXCwV0aVGbzrNZD5PzXWIGQZBLIJr2eiqgqoolIMAU9GQMuwCBmqAGwQYmorQJAuqQ6BKAp2QeJaLnX4/NAEIvU5C91rNU9ACQC6uyUUUlPoiWR0IsMPVWEXX0A2NwHUW3WwX33shkIUyOM5lMiMairbY2wt86mNzfPEPR/E9EU4sSYlEwYhHkVJixExEIFizoYOP/NJDV5DZ9arN8WcHGTw+zuCJCRayRTbuXoVjCWpVG9fxGD8/w5b9a1m9ITQ9CvyAew6sYd3mbtZs6rhifVdRFJLJJMlkkhUrVhAEAYVCgXw+z9DQELZtLwe15ubmK3Qah09P8c3PHWL0wjSmYfLCt8+z+8H1vPX9u1/TdZN6vX6FGP8buDX8KOIPXLoxplIpDhw4cFtJ2mi1SFTTr7j5Lk0HzNo1AN7Ss5qBwgLD5TxRVadq1bFqNd6+Yh1v3X0vqqrSlUzxkY3bCUQ40axedr4liZ5rQUjJVK1MIAUD+QX+YfAMVc/F9T1GS0Viisq97b2cLxZImSY1xybrhLqThqoifYknBZLQsK0e+JRxsaMi1HiUiyRSQKjLpoYmIxigeqGmnOYqoY6bRmjk4YcxWPoSxXbABiUVRdNUtLiByIZJFGoYb4TjQK64uGarhFNJuh7GXN/Dr1Q4Mp0N1/4UBQIVLWoSuB5q1CTwA8yIwe4Dq7nnwKXp7MJ8mfHBWZ7+0hEWZkrh9HWuSiSh09LSRDIVoVK0kEJQmC/T2OtydQkAAQAASURBVJZG0xR237+Oj//qI6jX0cvWNG15OnvdunVYlrVMLI2NjaGq6nJh19TUhGma+F7AVz/zHKPnZ4klTcyIDkLhue+cJpmO8aa3v3bJlBDilqaT3sCVUBYnfn4UWyKO47CwsMCaNWtuS6u26NgcyU7RHI2TXJzAjuoGXfEUI5UZRsp5tja10xpLMFYtsiLRAEjG52ep2BYf2H4vXV1ddErJ+sZmzucX8KSgL51hc3PbcgPO1HQ6k2lWtl//vuWJgO+NDfP0xEXytsVYsUDgeKyKpykB+B7zroUvA5JmFFcGVBanj8zFqSgnEKBJHD3AVQXiMjIbdVEuRAtrLTUANVAWXWYUMCAiNSK6hucHoUlj0UYtWMiIgdIQJxY18YTEy1sglbAoQ0HUashSNWyoAagKUteQqgbVGtlcEamEsVjR9dAk2zRCckkIzJjJOz907zKZXa/YHPz6Ufp/OMCF05NomkbXmnYiMRM/UKjk68STMVINMSrFOp4bMDm6QDoTZ9+bN15zyvJyRKNRurq66OrqQgixTC5NTU1x7tw5ksnkcgxqaGiguFDj7JExGpoSGFGFWk3Q2JICCcdfuMB9b938msqP3MqGyBu4Eksx4UcRg5bONzExwZ49e2hsvHVycbxa4lvj54moGj0N4XCQGwQMLMzyEib7jAhN0RjzVm2Z0HYdh9G5WeKGycN79tIYjfP3509zLpclb1mkIxHeu2YDD/f2oasqb1nVhz84xMMHHrwqP4voOpHFIRYhJUPFHPP1Gi9MTfDS2ChFq05p0TujcbE2TBom5cAjQKArKpqq4AifBjWCgqQsXfyouOSLJkEsxh5FCwlsqYImleUJSaFBUjMwdY1U1ET4krgPxdwsbtWFhjhEDdpaktRNlXLJWjbAVlUFUa5D3QrrNgV0Q+A7KsJ1kZ5PVcpwIlLVQhFvQ0d4AaqpoGkKD75rOz19rZRzVU6/MMSzX3mZmUVpSKtm47kearGOUBUiCYPAlUSiBs1dGSaG58m0pnjwndvYuX/1DclsCK/FdDpNOp2mr68Pz/OWyaWjLx7n4qk5KgsejU0N7Lp/AyvXd1PM1Ug2xEKz3cXbWzIdpbhQJTdbes0Jbdu2l4fZ3sCtY8kD627XYrZtL+el+/fvv+WtR4CRcp4/PPk881aVjBnDDmy+OHKaHl9hjb8KT4grtmSlDHWD69UqTV0rece6LXz2zHGGizkShknd8zA1jXf0rePerh7WNTXzzMA5JufmeGjXPWxsacFQNZKmSec1BjxVRSFr1fjywGkOjgwz7djEDJOEMBBC4CsSx3dpNmNIP6AmA5xFI0lbeFSROOYiTyMJ9Y1EuJG2NImtLWmTsDi97UkCBImoSWsyzrrtzTyyaw39z57n2AtDFMs2kVQDmXSUzo4Gdm/P8NyXh6gWrMXemQqeg2vboSSSASs31IjFPWZGTXJTOqAsm04qhg74qJqBIgUr17ez/22bmRic4Xt//SxDx8eYHsmi6RpBIIhlkkQTEYrZMnZVYsYi4WCSqpJpSrBp90p++t+9+ZZ9inRdp7W1ldbW1mUZxVwux7P/1M+xp4bxHIGu65gRk433rMQ0NIqLXnBLXkpikV975dDSa4FarYZhGDfdbPmXhted0F7C3U6kHMfhxIkTAOzZs+e2Bf83ZVppjsSZqpXpTYSyFW4QUAk87k00Y2rhWxfXDd63ZjN7k00cOXGCteu2s3njpltal1lKIpcIpUAumU3m+X9OPs+CVSdlRJitV5irV1mTaqZaKlOp1YgZJqqqMluv0GTEwy1WBYQCSdOg5LpIBRqjUebsKrXARUaWVkoWn1cLpyEFAmIsirUREky6QqBJkArqkjeKAnFDQx2ah5EFlJqPousoXU0ovS1oyiIhhRLqtc0tLHbjCCclVRVpLGZsQQBBQFlTQ1Jc0yAQ6IkoQSAIPA+pqii2S0tPEx/8hQfINCcQQjA5NEd2usAL3z7F9OgCiqIwM5bD930mB+fp29xDJGbi2C52zaFaqBFJRDAMlbf95E4efveOW7oGNE2jpaVl2fG9Xq8vk0ujo6PL5JOhxvjqZw5TLlo0tMRoyKRx64Lnv3ua1s4Gdj+4/pae727gVvUj38CVWIo/lxv7vVpks1kuXLiApmnce++9t71C1xpNcDKYveIxKUPjjpQW3iRbYwn+/fb7ODw7waEL52nyFR7b9SYeWrvxCuIaWNavvRzhjffqhtpQKcfnB48zUi7gBgEztQqtkQRrU02cm5lGlwrS0JhyqoubFwo6CrbwkchQA19VUTSFkmNTVzycSEBdeKFg5OJEEoFEaotFyOLamyIVAkMivJBYkiIkvaWUxCImkZJNcHISMV8JNdriUZQ1XcTaG6gbCrhhYiR9H2YWwPNpaHZp63Golg2mx6OhcVsgEApIQwc1nEgSgURxfVRTRwMUTWXTrl4+8stvRlUVcrMlnvy7QwweG2NqJIttuazc2EmqMU69ZiN8ydTQHKu2duO5AaVclUK2wuTFBZrbUjzy+I7rktnXQiwWW56YE0JQKpVYyC4wenGUs2fPkkqlqOclo4OztPdkqNt1NE0jlUriOT5HDw6x75FNr9mUdr0eGpe+QSjdPu52U00IwcDAAJVKhc7OTtauvbZczvVQ9R1cEVwhpwahR4gvQ+mitQ3NfGzDDj5//gRDxQUqlQoxTee9m3bw9rWXDJ7WZJpYk7n2Zsr1YlDNc+lfmKHoWJxamOfY3Awx3aBUr5Gza8R0Ay+qIxyblGlSdV08QlklHRVFFdi+RywSRVEhJ+p4qkREACGXN0IkEqlIiFyalAyCULdWtwgJaCXUqFUVhZZkjPjMPIzmKGWruIFAaUxh7uijqStNrmDhFOylDwGZLUHgs3prlfW7KmgKjA9FOfNiAt9WEIvrtVIzkHiouokIAlRNRVFg5/1rect7d3D28DCnnh3gyNNnqZYsEpkEnhsgVMHU8CyKoSOFwIiYlHNVNu5dzdToAo7tsftNa9l2bx9rt3bftvleQ0MDDQ0N9PX1cfz5QQ5/+xTZ6RMkGg1Wbmsh3ZCmVKjQubKZIPCXzx9PRSktVCnna685of1GDnRnuNuSI7Vajf7+/mWN3NshswHOFuepeC5r05dih6lpJHWDM/UCpqbxaM9qPnf+BJPVMhE/YK5QIIiaPNq3ntUN4Ybtv9u+h+lahZrn0R5P0BC5FNNeWYddC0XH5i9OvczJ3Dx5q85MpUwclZWZFuxymYiuUXBsAiRJRcFUNSqKjy8kEU2nGjjU8MJmvrw0SIQITWeJhCQ2sKhdq6BVl0zuQddUNBSiuk5XS5rVhkHh2fPM5UsUCzW8OYX0xm427FhBd3eEwdZJTjw/hpQhoe0VyhAIdjxQ4MHH52jpcCjN6xx5spHnv92E7+vg+7SvqtPWG1CrRpgYawQJfZs72blvFV//4+/z4rePUylZFLIVdF1D0cIJ7kRDnGqhjlQVnLqCpmo4dYdoIsKmXSv48H94lLbuOyOVDcOgra0NnShPffYME8M5pCKZOJflxPNDrN/The3aeJ6HEUktm+aFU5sa8RuYWP6o8EZT/85xt+UfJycnOXfuHKqqsnPnztuu756cHGbeqrH2sk3Zuu9xITvLuXKODc0tPDU5guV7RFSdXC5H3bGJp1Lct3I1ezu6SRgmByfHmKiW2NTUypu6e9nZGsqdNEZj7GvvpMN22dZ2/aHL+XqN52fGOZOb58XJcSo1C1PTEYqCLQKqnktCM9H8gDKCeuBhqCqIAFf4qKaC4wscVYQeQSLU4kcFqctl/kcLFFRVojkKhgpxTac3kSBmmHQ0prlnfRe7VnfwzF8/w+Cz5zDqLs1CEvMdHn7rZvY/to2Bc6fZvK6Xz//R85TyNQxTwy3YIASrt1f4yK+N0NJlI32V4qzBkR808r0vdKMosO+t8+y8v0wsJRk+08CJI3289ad28/n/9hWOfv8Uhfkymq4iVY14OkFxvkw1VyGWihJNRHAcj8AXeI6HVCTb96/hsQ/uvWUyewlSSmolC93USSQSlLMWo8cLNDU3EW+I4LoOtYrF0WfP0rupjWrFoZgzFnXVIT9dJN2YYM2W11abfklp4NV4Mf1zxY8Fob2knXS3Eqkl47Wl5OlOVlcykSgfWLONLwyfYKgcGoCoisK6ZCP3JS6ta0opGR0dZXh4mL1btt7Wqt7SxTZbL/PU2Glezk4C4TpJyXbYmGlFURRs32ehXmeikieiJehuaaWQD6cKbeHTmohzMadRcB0aVZ32eIyC51BTXErSwjODMLEJwuJN0RWUIOwgCUOAseROEjLiikJI+OgKIko4BUk4ra2encEYzmLGTfSmBFa+hrg4G5q8ZVKIkhN2yfMFenoWeORDs6zaVCWwNc6+mOH5bzUyczEKS+aQphGSiEikquHVbbQl53BNpbWjgY/9h0doSEc4f/QiB79+jPGBGfJzZcqFGi1djXSt7SA/XwFHUspWqRbr9K5uZXxonkqpzuxkgVRjgk07V7DvzRtv+1pYQjweJxqJkoplWLtax3ZDgvvFp04xfnGGlq50+J4GgoamBFbVof+5odec0H4jkbo9LE1HQjhNdDvd+2vhcuO1np4e8vn8HenB3dfey+H5CaZqZdpjSSThxHSDZrI1dWm9LalqtMwXeSzSyD37H7mtYv7yCe2sXWPeqiIl/PmZl5mpV2iPJ8jZFmXPwRcCrWZjGgam8DE1jZxt0R1LUy46SEAXkqiqUnYdNE3FjKnMejWEXDJvXCKyAVUJm2kml5ppguWfKyiIGJgB6CrENY2o7aEfHSPhBKzc3ks+Xyc7mYML02S6M6TXpMmfLxEISZCv0LumwE/9+1FWb6miANWFCOePpvjKn3VSmDdRVIVEvE5zt6RUjFCtJ5FBqIUrhWDVujZ+8hP7+eE/HObEMwOMnZ3G8wPaV7US+AGqqjA1PEdTZ2N4HZkqtuUifMHqjR1cHJhl/a4V3PPgejZs7yHTfOffzXKuxvPfOsOZly4ihWTtjh7a9zcwlZugUqlgFMMJfMMwCIKAWCJCvWLh2N5rRmjXauHmwBsx6PZxN5v6lxuvtbe331EO1BpN0BSJkXOsKzSyi65DTNHoiIXeIjtaOkh7gu/0v0yqZy37N25hTUPTLSfT19oSuVDK88enDzNZLeGJgMlqhYRusp4UrmUT0yMYusqcVUVTFDwRTkP6gOOFa/UxTceUKpNOBSfih6S1IGzoL5HUvkBGF4s5WG7oK2qYK5lSJ66ptMY0WjIR4rEoseE8uYs5WtozrFvfycJ8mYXJAl2WxYMfuYfy3la+9/nzVEoWwqqRbqnwb35rmC335VE18CydWtbg1AsZvvCHvUQSKtv2zbN+Zx3NUBk6neHY4Xa8wKBnVRNdLVH+75/5E2YvLqDoGuV8DVVTcS0XRdWIp2PUyxYRQ0cIcB0fKSSFbJlo3OQdH76XB9+z87Y//1fiuW+e4IkvvozvB0RiBgsjFpX5WXY/mkQqAVPjM8RTERRFwXFsrKpHJGaQuslE5t3GGznQneNukknz8/OcPHmSnp4ePM+7Jb3sV+J6JLOihPrRAA919+ELwVfO9DNdrdDa1MgDvat57+pNyzFIURS6k9eemF3ycHrlc83Vqzw9NcL54gLDxRzZWp2+ZIYFywYJvqEx41SRUmCoYc3iKeGav6qqqIQGk0KFICKYp3Zp40MSNvNVeWmYCBb19QljUEqjxTdpi0R5sC2N53g0NaTpSKV55o9/SHmhSueqVnrWdlCYK2EvlNi/toV0X4x1axpJJZOceukiTtUmUD1++jeHeOgnZzHMAM9Tae7R6OqzaF/lMHA8zds+NEP3KgtFqtiWwdhwiqe/eQ+9XSn+9nf+gYnBWTzHQzd1VE0nkYlRXqgiHJ9EJoYR0ZFIjJRJveSgGTp9mzp58D07b5vMllKSnSzguT6tPY2YEYPD3zvD5Mg8PavbQm1voJirMjtcoXtjCwP9U9TtKmZMI5crUF6wWbO5i941bTd5trsLKSW2bd9V+dR/DbjbWyJCCM6ePcvc3BybNm3i/Pnzd0TwnS0ukDYiV/xuXDcIpGTSqvDm1q3sbu3ixdlx6tUamqISScTZ0dLBgY5eADY3t7K5+foyX9dr6kspKbkOo5UCf3nqKFO1Cvl6jZxtkdRNdEPFFBoJw2S+XsOSHnFVQQ0klu9joqEpChXhYqsB0iSkXsRizqMQxiAtfBwJgQaqrpA0o/TGkvzE5hWsjusUCoVwiK9B8OLXDvHyd47T2N5AS08TgS+YG81y9CuHue/Nm5BSsnJtC//b//gpvvePR5gczTFdLNF3X5F/+/tnSDR4+J5K4EOT6fHQ+zx6N9dYvb1CS4eDU9OpLkToWmXz4E/oPPmlZzj9fJV61SYSN3EtF7fm4qdjJBriVAo1KoUqmqahmyrpxjidO1r4wH94lO6+1tv+3AePhdrcM2ML6LrGlv1riDfEqVdtuleH54tGo6TTDagiB55C35YWhk5M47kBlQWXprYGHvnJnTS1vbZxQAiBbds3NYT8l4gfC0Ib7k4Qu5bx2vz8/B2fd397LyuSDRzPzVD3PLoTaZotn2q+AITk15kzZ8jlcuzdu/e2p8AB6gj+fwOHGa2VaDCjBFJytjhPQjfxZICp6ERUFRn4eIqC0ZiiKZ6g1apzsVwgoZuUHYeYrhEEGindZKy6gBXx8BWBFBBBC9diNAXVV1Ckgo9EMQOkLi4jsyXoEjQZGgD4QN0gJeKsjaboteH8U4MYmSitXY00NSTwAxgbnEXULFY8sJKsYbAwtsAD7x3mJ37hIulGL9xo8VU6V1dZv6PE3/yfK7DqKis32PSuddCjKiPnUgwNtBH4YWIZeB4N6Sh77lvBoa8cZuZCltmxBTw3oHdTN3pER9VUCvNlzJhJLBHBsmwUVVIu1Fi1qYvWjhSZlgRv+ak99K5upW9jB7p+Z8SOlJITzw9z8BvHyc2WMCMG29+0lre8fzc9XTVSqTmSyQSlcolKpUKlUsH1BfMzeRzHec1WP94o5u4Ml5uRvBpCe8l4rVqtsm/fPjzPI5vN3tG5NmVa+cjaHXx99Cxj1SKKAh2xJNv1DG1mOPFWqVQ4duwY6XSae+6557Zfu6Io2IHPX55/medmR6kHHjXPpey47GnuJqLp1DwPXSpYro0Vj7C2sYWFuRmswCOmh+aPuXqdGc/BDARRzcAWDnXDoyAD0MNJSBUFfIlccryWEhkTl8jsRUJ7caFj0ZJbZW2qjXdu7GNtwuSHX3iBAdumc00rZlRlZV8zfWvaGD0zye6eNO33pBg56nDkmUG6t07z8d88Q2uPTeApSKnQEPXZmXZJNdscO9jIvW8t0tljIwMNu25w6qUmvvMPfbiBTkNMg0KR//HRP8X3A1ItDdTKFiCZH80iNY1IzMRzfOqlOvFUhEqxDkKhmKuiFFU23RNOJ71aUqdesfn8//N9xs/PEk9HURSFl548x+TwPI/89F5OtEwRj5pYbg3f85ifm6dacGjracSyq0Tjxh0RCreLf62rbq8WS021u9HULxQKHD9+nObmZrZs2cLg4OAd5UARTedtvev43OBxxqtF0kaUuu9S9zw26olwpVVKxsbGGB4a4ie276anp+e2n2eJTJqslTiem8EJfJ6YuMB8vcrKVCMV12G6WqXiWFz0fDobmymVChhKmNe0x5PMVCp4QtAUi+FaHqUgQFcCakY4kSQlKCKUAZGqRBMqnghQ4mG+A4TSaoJlRyShqGiKylt61vBz9+8Ex2J6fIbPf+0YqD7SCPB8j7bODOlUjHqxSnNEJb06w7/77Xfx9b89RHbgDB/+lfNsvreI7yk4topu+kRaAna/a56Vewu0tHskUwFeXaOWj7L13hJb95X59j/ci2ZZPP+Vl1mYLiClRNM1FF0n2ZigWqghCfDjEfSIjhQBTR1xSnM2kXiElq4Mex7eyD0PrLutz0NKydxYjvxciVRjgp517VSKdZ771kk0Q6Wtt3H5uNmxHJMDBfbcv4X+5wYJXFB0wfTEPLWyw7b9KyiUF1CN5tdsYuiNHOj2cTmZ9GpjkJSS4eFhRkdH2bp1K52dnXdch23ItJLQTQquTVMkzHl8IagFPnvMkCjwPY/MXIEPJNpZufchWtMNpMzbu/+8klCaqJb4//Y/y2S1jKoojJYLqCgoOQdVM4ggiRkGTuCjaiq276GpCkkzQuAG2J5HUtWwpUfNCMIhHxQUjVCWMVBAXySTLk/ZgvC1BFLia4L2dJp/d/9edq/sXN4QPfiVw0wMT9HU20jdrhOJRmjsbGBmeI7+J0/x4C/sxTA0fuE/v42zx8Y5+sMB/MLL3P/4LJouqBRMFE1gJF0iMY83/2KZt0iFqAGBq+JUdcplg027KqzaOM1f/u8RNCOCoqmkmpLUSnW8ep1EJk4sFaNWqlMrhiZkelTHNDVW37uax3/pIfo2d932MMfceI5v/fVBxgZmCAJBpjXFm9+/h3NHLpJIRZfJbICGpgTVosXGratpa2/j5IvDFObKWNGAZJNB52aDwaHzyxJtt+od8WogpVz2PnkDt4+7EYMsy+L48eNIKTlw4EDIKdwhD5QyTBYWJR6XIBbdoSNKaEL4012rEVOzzDdEaWhsZFdrJ2/qXEHyFuPQtZr6o5UCfz90irOFecYqRVw/YHUkTc71iWsGiqZS8hxUoaIQyjoGvkTqBiYgvYBy4OGaAn9pC1YsDhRpCoqUCHUxBiksS0DKQOID0pQ8unk17967FV1Tl82js/NZDn/zCJZbJy4iUINIJELHqlZmL84z+PIILPavulc284lfexvlQp3v/fU32Xzvd4infaoFM1RgM330Notkh8WujSUUCZ6jo0U9Uh2C4mwHvT0WXT39zPbcRylXRTM0dEPHtUvUC1UyXU04dRdd03Bsj0RLjO0HVvOujz1IU/vNZX+CQFDKVjCjRui3dnqSL37qe9TKFummJL4X8Pw/HSfZGEeKqze4NV0nEonyi7/+k4wPzfLUdw/S1t5KskUnb0/w8svFZRnJVCp1V81Or/33BG8Q2q83Xi2hHQQBZ8+eJZvNsnv37mXjtVd73u5Emu7EpS/F5OQkZSGwLIv+/n5UVWX//v23NQE1XitwqjCLkIIX/TwjlYA1DS3oqoqQkrFKkZrvMm9XadVjBOUqKSNCUXjUfI+Sa2NoKqsaGmk3Y1TLZTZH4rxt9718bX6Q0/l5AkeiSQVHDVCkRJEqKDJcawtARnwU4zLtJwFSk+hGwKLhLtIATEFHcwu/feAR7Is5/vJrZ2nsSOMLn2q1iu/7tLTHcKs+29enWPGu7bz49F9x/zsmUdMB+ZoWauiaAWqjzYp9Nr/+dwU0RSGZFAhHxy5GcCydky8W+eJfrEM4Al2RaDX47p89AYpCx5qOcL02CJi9MEu0IYGma2iaQmGuxIrN3ZSKFTzLp1a2mLwwTyRm8s6P3cveVzGVvYRThy7w5U//AN8LSGXiuI7PM1/vpzBf5p6HN4bGlaqBqqg0NTUhpGAiP09ilc7zzz9PMplc1t5uaGj4kQW1er3+rzKQvVqoqoqyaNR6p2RcpVKhv7+fRCLBgQMHMAyDQqFwzc77rUBRFB7u6uOelk5GygVURWFtQzPnTpxECMHs7CynTp2ir6/vtrRxX/kcz9TmODluk4nE6IylOO9kqfg2w5Ucm9JtqI6HKiRS0/FUiOk6qxoynMrNIwVMVEpEgI1mnF09KxiXVY7kp/D9IDR1lAp+IJCL+miaVPEUD6JiUX6EMMmSCkpEoGqhS60iFWRCY3dPBz+9eweqojD87SHmmmZIJBM4jkOtVgsnrDRJaXaBHrOBn/3VR1m9NUIi/k9E2nwKjo4fgKIFmEkfNeWwqafK5sfmMVUFPBWrbODNJHnTY/NohsYTX9yAIX3q5Tr1ioUCFGfyoIVkUr1soUXAtT0MU8NzfVasbyPwA6RUaO5sYNu+1ex9y6bbJrMXpouMnJlEQWHNth6aOho4+cIwE0NzdKxsXp62bmhKMD26QHaqyNotXZw9OgZaQCIVQ3qSaFRl4+4uzg+ex/M8Ghsbl2NQLBb7kZBL/1pX3e4GXu105BK5PDQ0xPr161mxYsUyUe553h2d85Gu1RiqyhOTw+Rsi8ZIjMdXbUI5exHP8xgYGHhVDX0IY+8PcxM8M3mUsutgBz5Zq0pHNB16BgAyCNBQsHWFTCxGol6j6NiYmkZrLE7Zdig5FtL16G1oYEVC43xtAc/zUUUoZSRVGRJGQkEoAkyBNC4Vc0gZNtI0EfpSS4WYHuXx+zbS1pACUmCrxMw4jc0R0EJtxVKphKaFk9PZ6RwNKxNs37uKNRs7ePnpc3RsrlMSGo5QUKIBihFgJAU6ks42C22xiFOikkjGYWYww4YddY485ZHP6qSakhSyFWLJCNV8Dd+2+f+z999xkp1XnT/+fp7nhsrVOUyenpw0kkaaJNlWsuW4xjYOhAW8XhsvGFjgt4FlYRdYFtgFjPFvvV4wYcEGszYYY2xLsoLlII0saXLOqadzqq54732e5/vHrarp1qTu0YAM1vHLL0ndXbeqbt37qXM+55zPx7Zl6rJqIWEQEdZCEmmfoBLRt6GXd3zoAVbfvngW+TOXqBSrfPEPvs7h75ymWgrwEg7LNy5i872rmZ4o07P0svSDEIJ8e4aRixO89cfuQUrBnmePUZmMaO9s4a7XLOD21y1hfHyc06dP47ruLP3/l7sJda14VXLk5sNxHGq12k0/PggC9u/fT7lcZvv27c0pVaXUTeVBfdlWHlzYx1cvnmCiVsERkprRLE/nuVPmZjX0X7Nz501fU0IIzhcn2XXpKCcLY5wrTDBcLrOhpZuKjugvTBHpiElH0JdtZWJykrpyCJ2pNMPFIuUoottPUQk1Cd/DT3tMh4VY3ohYskhogZHgIAjR4NnZDX0JSIsUoHDYvKqbO5b2IIQgnU6TTqfpbDlDNpejpSVPrVajMFWITT1NSP+ZAaIoQimF6zls3t7H6o1tnNr/ewSupKAVOmsQnsZRFkdorIiXdAMjiCKJmzR0LC3hqfV43gAL+jqZmsjV9bglqVySyeECJiqweKVgckQQqTSFsRLZ1jR9W3r5/g+8ke7FNzY/r1UCLp4YRErJotU9hLWIv/ydR+g/NUxrdw7HVYwPTfHFP/g60nOvgWcWz3N4xwfuZf22Rex78TB3b7uTxSs6mS4WmhKRDYm2meTSP0Se0iCUXtXQvrl4uXnQ2NgY+/bto6uri3Xr1qGUolqtxnKNxsy79r63ZyknpsaYCqrkXB+L5WKpQIvjsTqZ5+zZs5w4cYL3bL77phr6MLuhNh3WGChN83v7n+FisUDe86mEIbUo4mQ0TmsqQ1CrkVQu06aGVFAMakgELQmf6WqINoZW32PSizBGxz16E09iSymwkUVLG+NP4xawdf8QFSuSdLekeOdd63DqUh1SxtxGNp0l6aXxuhIkEh61Wo1icRopJZVKlaH+ITpa8rPeW74tzbY3gnRDprRDKQ34GikNrhQ4da86D8DVmMDB92DJOkt1wmfp6jGO7PNxPZcwCGjrAde13Pnai2y57yhSGs6fWcLw6FY6Ni3mta/fQUvLje+/A986zlOf3cXwxTGUo1i/fSXF6RrFqQoL+i5PdiezCQbPjiA9j2Kh0pRQ09pQKVbZ+tA6pBQsXtnF8k0d3HvvPXhefG4aMrX79+/HWktra2szD7qVxqeN0FpTq9Vmebx9r8R3BaH9ciVHyuUye/fuRQhxhfGalPKmCaWrhZSSIAh49tln6erqYv369XMGSGstf3v+IH9z/iDFqAoIBvUkCZmIJTaIZU26kmlOFmoMFQvIqEw+l6OqA1JRQN7zqWnNpo5u3tC7lNq5i5DpZLArxR+ce5HTxXh63ChDSvroIBb/R9lYLwmBcUNUUl+eRKqT3coxOI5GyjgBM1agMEwkL/L7l75AWjiUN0ryQ5ZcPodOB4QqYPJkESsNcsEJhtu/SN+/PMcllWIIn2QmICkDfGFICHB9QyJdi0mumkK5GhIhhQGf23eOs39XgVP78nQsaAFgcmQagWX47DBGOaRySSrTVby0risYCEykSSQ98h1JgqJhyeoe+tYv4LYdK1ixcX5u7YXxEod2nWJ6okTHghbWb1uBl3D41pf3EwWanqWx1EMa8JMux/acZ/vDG1m+tocTB/sJdQ3fqVIs1OjobuX7fvgBFixvY3x8nLGxMQ4dOoTW+gpy6VZEQzvp1emk+cVMY9qbTaQuXbrEoUOHWLZsGStXrryl63M5L8HtHZcN06SUDA0NMTU1NW+zW4CJWpmvD57i4OQgQbXGd2qj9OTbafdjEqDFTzJaLTMWlLg0NoxjYHlrG8cLE5TDiLOFSUKjuburl7s6FjA5NEzey7Bj80Y+cWY3L472U7ERvnKoEGGI5UOkEbEhbRhCIgKvvmlrwUqBwKJcjVQGIRqmkfB08QS3jeZREoIlKtbSTiZJpVJYawmCgMJACZGwWFXiuf7fxt22lzKWIyKHLyJ8GZLE4kpIYtHC4mMJLURViZ/WJFuqFEaydPVAJivpWtzN+OAUylEkMwmKEyVMZLA2hXIVSoBKuBQny3hJl/HhArm2JN//4ddz1wPr5v05W2v5+l+/wNf/+gXKhSoWSyaf4sH3bmWofxJglnSIVBLHdTh3bJB3/+QDpHNJvvP0AcrTNbp629j+0Hruvn8NEJM84+PjjI6OcvLkSXzfbyZVra2tt4xcKhaLrzbUbjJezmRSFEUcOnSI8fHxK4zXGgXdzYQQgtf1Luee7qWUooCU4+JKxSNHzrJnzx4cx5l3Q78R2hpKUcC52jRfGTtLIplgebaV8WqF0UqJ0aBEf3EcpxSQdVwKNkLbWMd6Wb6Fw2MjpJRLKQzoS8ZbZFvXrePxiQt89dIJyjbESotQItaltSI2njVglEb4M6az6wZt0rGIOqEtgAkxze+d/DYfzb8FTynSbWlS+TgH6VjYRjabxRjDxMgkTkJRDKeR04YXj36JsOV59PbvcJIMCo3nhfgiIikgQpBAYwAfwNHogkcipelcIonKPUyNTtDe20uxPv0ohCCZTWDtJOtvP0smB4MXshQqPYxcKtC1pJ3W5Une8gP3sea2ZTc8/9PjJU7sOYuONEvXL6RrcTuPfuZZXnjyCC0dGVo7c1TKNY585zSFsSJCgo7MLA8ArQ1SCXItKd7xgXtZuinP1FiRzVs2zlq11VozOTnZJLcPHTpELpdrYtCtJJdKpdK8pP9ejTherjFtoVBgz549ZLNZduzYMWsa9maPK4TgfStvY1W+nRdGLlGKAta2dLDGSdN/4hS7du16WQ39RvSbGp8+8m3Gwyq+UvEAAYLB6jTpSIDRuHW9WiEFHckUA6VpBAJHQEsiQZeFrshy26rVnFMVHr90mkhpZH0D1jS0+iOIiOKGfn3tvyHHJqRBOgYhIBKavxs5iDpm+Yk125vvr3NRLOekpEM+n8BaSxiGnB/uJ9udYmBgIP4+FwZajzMhvsZ0X8igyOAKjSsikiLEQ+ChsdZgEPjWIpMRYSFBrl2RTCYZPROQb9OEYYK23ohl64ZJpCQtLZNs3jFNKhsRhYr+C0voH3wzt73+DgJTnROZveepwzzyp99kcqiAkNCxqJ3VW5YxcHaUnmUdzVyne3E7l06PkPIcStNVcm1pXC/OVyZHi6QyCfrWL0AIQeeCHMvKHfSti/PlRvNs5cqV1Go1xsbGGB8f58KFC7GR5wxy6VZtlUVR9CqhfRPxcrdEZsq/rl27lsWLFzd/19hOvBlC+/4FfZybnuDbQxcYrZawQIef4t5UF+H4JGeGRl5WQx/imm4iqvGxg9/mhdF+hitFJmpV1uU6SUoXqw0eAqMk0pHIQFKLQqQQ9KazDE5PY6wlrVzaXFjT08M+PcVAcQIrbKwrb+ueaaae97j1f84gtIW0CBVPbp9hmH/7wpf5mXX3sC5/WS7F8RwWrurh6HMnae3Ok0rHddjUeAHHq1IVZQoFwblz5wjDkFybxyTP0d/9t1R0CiUiHBHiCkWC2DzXFxqwBIBjLSplSLh5pFvBSaSwbsSi9cdZeccQHV0Xaeup0t5dxZWS4lgGx/XYsHUQJ3WCZw8uuupnfO5wP4e+fZxaucai1b0kMj7/73ceoVqukWuPJ7Gf+8o+ysUq3St7Zn2f+AkXx3XoXtLGxFiJ6fESypHUKiEL+zrZ+lDsF9OYsm88v+/79Pb20tvbi7W2abA9MDDAsWPHSKVSTfxpaWm5JYOODUL7e5EH+q4gtOHmE57R0VH27dtHb28va9euveKCuNVmk+Pj40xPT7N+/XoWL148ryTq8NQQnzu3HyUEy9LxF/5YYYqpqMJYUKLDjy/ARekc5wsTTAdVMqkWyjqgPZnk3629l3X5TmpRCJUqBw4cIN2aZ0+iwv87tYuqjpCAL10KukrVBjhSERiNoxTWCiIRoFIRUpr6UJJAWI0VAtfVOE5ErAhgsVbgKg1uibPVAkJo7PssEwfKrHCGsSuLkKzhmIgO12Uqf5IWv4ArI8ASojDWo+4TGXf4raWGIGnBKkNUckhmQ7ykwfUd2js9Jrqy9C7v4sKxAaSUJDI+5akyKmFJJCGqxcdq7cwycnEcqSTD/RMYbXjg3Vt4xwfvn5fxWiNOH7zIZ3/3UcYGp2h8rItWdvOun3yQ0UuTpPOziedk2mdieJqJ4Wne/eOv4xt/v5+nH30BrQ2rNi7k3jdvZOnqmGzs7u6mu7sbay3FYpHx8XGGh4c5ceIEyWSymXi1tra+LGmAYrH4qnbbTcbNYIUxhmPHjtHf38/mzZvp6pqt13er8ScMQyYnJzHGsGPHjnl/aY1Ui/zmgSc5OT2GIySlsMqQLeOGPh2JuKPb7qe4KKcoBFWKjs/S9i6CapkV+VZub1uALx1W5Fq5vaWdS8dPonJtqKU9/Mbxb3N4chhjLTp2XKvr9hMbj1iQCKxnUEnTvMewYIxAyHhDRMk6oY1AUGNCXeD/nB9GCYNdbRA/LrD/b4CO9SmCtRPUWgq0SuhcphlzvkI2M4ZkEiEsGkllJgbZGjXhkLCxhJOwJi7iih6ZNk2+ZRGXzggEGi/p4XjQs7SEl4pwfbht6xBr7z5NrSo5fWQh/YNrkQIWremld3U7i9a2zYnMHhuY5OC3j1OertK7vJP121dy9vAlvvaXu1COomdZBxaYHC7w6KefZdWWZVxNTlRHmkwuQSaf5Pvefw/tyyVtLe2sWrscb4a7diaTIZPJsGTJErTWTExMMD4+zsmTJ6lWq+Tz+WZilclkbpoceLWhdvNxsw21hvGa67rs3LnzisJcSvmyMciRsmkOOTERN83T6TSbN2+edxJureWJgRN8uf8II9USo9NTFCPNlpbYdCnjeSSUSyms0V8YZ1NLL3nfY/fwANZa+ovTJJTiLctW8ubFK+g/ex4/CFi+fi2/f+p5vjF0ltBqHCkJG2oi0iLrkiNIW5+UbuQ5xNsjCKSjUY5BinhKEjT7C2f4reN/R8kWiWxA6keSlP7PBHJggnRbilL7JJXuSZZt6KF3Z47SWD9T2acJTD9CBiAEGqeOcXUOS4SExN4hEeAIi0wYlOvRvcxn8IRm0boJcp3nkUJw10Mn6VhQQiBZuLBCMi2wxmKMw4VzBQZHf4A3/uhDPPPst1l0Fc3YWl3XP5GJtUD3PHmYL/2fJ5kancZaSyqb5K43bGTfs6fJ5lNk8nFzM5VJQHe8NZJpzzLSP0nPsjaklEShZmqkyG33rCRf9wbItSXJtPhX6EY2DLTb29tZtWoVlUqlObl07ty55vRXA4M8z7viPcw1XsWgm4+bJZP6+/s5fPgwfX199PX1XbmW/TLyICkEd3ct4u6uePrRWsv+/fupVqvccccd827oN0Jbw/GpEQphlSeqw4wbwcqW+Ht3sFSiokNOF0bpE2kW59u4UCwQGk2gI/J+gpqO6ElmWJVrp9cKustVNm/axMfP7eVr/ScJjYl1+iVgbH24qv5PJ0K4FiEbX+rx/SwdjVQgpYm1bynyVxf2srVjIa6rGQkKJDe4LNjUy8U9F8l35XFcxeTIJK1r09z/wR0k/AS1ao1x9QST5W9gnUmksoBCW1WvxQSKGiENEsASxQt0+G2KyNGUojOIfIXb3vg8qdweUokipmpIZTTZXEh5KsVYfxttPQnuWTeBSp3mzMh2wqnZE/5hLeQ7X93H3icPUSsHrL67j0Vrevmbjz1GrRrS2p3DGsvgmWEuHh9AJrwrPD+SaR/XUfSs7+Lc0YGmTJWf9Hjd2++ge0lcT1+PsPR9nwULFrBgwQKMMU1yqb+/nyNHjpDJZJr483K2aEulEsaYVyVHbjJuJg+KooiDBw8yOTnJ1q1brzj3L8cjyVOKD667m/sW9HFmegJfOaxOt3D0xT2Ewtx0Q39mVE3E56YvMBEKWrwkodHUTMTxwgi92iPtuJSsRggwwrA0n+fkxHjcJMOyvrOTDek82clpNm9eye9fOsSp0bF4CrveMLPagpLxHKOy4JpYWrYuh4QFoSzCiesvrSx7py7wC7u/wp/e8x5a6hJzBss979zK+cP9XDoxSLY9NqAvF8rccd8m3vZDb+HFF18gk8kwMt7P4fJfYdNnEW4REITWwbESZA2Eh7IValbGPJQElERLQZEiJrKIVIHMCsnWxV8jnQswgUN5xCedC7FI8gmHbG4TSlmkPUtn7iBCvGbW+f3G557jq596inKhClikkmhjUb7LolWXyetk2ufYi2cpjEzT3tPSfLzRsTTvzjdvwk8lOPz8GSqlGn0bFnDna9fQ0hnnO43h2athhxCCXC5HLpdj+fLlhGHIxMQEY2NjHDlypLlF28Cgm90y01oTBMH35GDRdxWhPZ9EylrL6dOnOX36NOvXr7/mRMatNBg4cuQIg4ODJJNJlixZMqfHTQRlDk0OALB/fJByFNA3w9CtXfkUTYXzpQnavTTGGC6MjdCpXN699k6yiRQpx+XOjgV0JdNorZkaGeHIkSO0L1nIXxVP8sy5c5SiAIEglAZPKhyhCK0m5TjoMJYyUVKQSBusvHyeLQJrYl1J14nwVFzMCREDocTgSY2rApSwCEfD3TCgQ3pUES8RkfAipJxmWkZUjUPCpkmIAE+GuEBgFdK4SGFQQuFhCLC40oJjsErQvjhBR2eeXNc0C9dkSCTLbHmwHx2OUprOkPQqbH/9FOl8wPSEw77n+zh2eBO6O0/fpsWsvGMpk7VB3vSDO29IZg+eHWH3E4cZvTRBx4JW7nxwPe29rXzhfz/J+OAUPUvakUoSBRHnjw3y+F99h0TaozhVmXWcKIxN4dK5BNmWFG/6wa04HdPcvWUrrR25q5JCQgiy2SzZbJalS5cSRVGTXDp+/DhBEDTJpfb2+etOvuquffMx3y2RWq3G3r17iaKInTt3XvULqLEhYu2V2lvzjWKxyJ49ewBYuHDhTX3OX+0/yonCKEvSrThSUqlVGa2UGKpN05vMk3eTKGPJGAilg0omGK6W6UqmefeKjdzTs6Q5bXfgwAHa2tqY6krxGwcfYyQoYYQhqXxMGGKwSAeiCBACKWKjNZWKEI5uDgYYE2tqK2lxnAhH2joGxb93lSawRXxpwImwayzD/wGi6hi5TJlEWuN5Ef3qW7hETGqDZ9KkpMITIY4woJ1YSgAXQ6yp6wmDQSGVxc1ZpCdw1TDL7gp4e/clEolj5PPTKFlASksmq3GFQ1jxsNZw+85JTh4JmQ5/jAfes53zF85TqczGCB1p+k8OYSLNgpU9eAmX/d84xl9/7BEKY7Eun5SC5bctorW3jaAasqAvnq4VQFtPnkunhzFBRDLlMT5UoLVOFk2NlXA9hw3b+prPl0g7dC1snUVmvzSUUnR0dNDR0QHQ1OZsrOYqpWaRS/PRnWxIHn2vrbq93GhMRxpj5jVF1DBeW7hwIWvWrLnq42523f9qceHCBY4ePYqUkr6+vpsq+h+5dIw/OvEcFsg6PmWjmbY1zpXH6ct04EuHFulQMGVqjqKqJIVykeX5Fh5auJIl6TydfpKlyQwHDxygXSmW3nE7v3rwSZ4bu9D0ntUixhirZVy4Ndb6HYvy46JNiLociRJYC45jcByDEAYVc9wIDLunj5FxQRNCp0b9gsA8W6WaGUKuqpBp10wnJvlGtB+3JSShIxLSxbcpErKGIyIMAmnjJpvVEEiFZw2u0DgSnBRoUaNkLuKvsLzxJ32UOkw6G2LKHuVRh67FFaQQjJ7voFbO070kwbYVU5AqYVwHY8yse29icIrH/u83OPDNoxhtWb5pMXc8tIG/+99PUq0EdC/tQEhBYbTI0597HusoepbPJsQTKY/J0WnufmAdu795nEunR+PnEIJFK7t4w3u3Nv92rtduMplk4cKFLFy4EGMMhUKBsbExLly40JQGaGBQLpeb13VWLpdfberfZMyXTJpZF91xxx3N75SXxq3alG14lBQKBTzPu2ky+0Jpko8f+Rani2NUopABW6DNpmPVDyFo8RIUixWMELj5NL1+hpIOmQpqeELR6vt83/LVvHHxCo4fPcr09DSrttzJb5/YxZODpwmFRtSHpIWRGBmbxQshQRiEr+NtkDqhbS0YIZDKopRBSYuq/y4k5DdOfoGOpEPVVIhsiP8jDku2dqH/pkTQPk36h6r4fYbHE3+GMVXSOUXCncIX4ODXjbUjBBajPbQIiGQCn4iqsKj6lKQUFkUNT2uk6EekJfmFSXK5MkJAcTSF6xgsklRrRKa1hUx2EdgSgsN48ixCXK5vtTZ89je/xO6vHUAIgXQUZw9ejCk012HJ2gVNvOpZ1smpfech0OjIoJzL93y1HLBkbQ/v+7k3cnDX6aak5No7l9K34fIxtNZzwgopJfl8nnw+T19fH0EQNMmlmVu0jRxoPlu0xWIReNUY+2ZjvpxNoy5KJBLs3Lnzqs3QhvHrzXJBQghWt3SwuqWDiYkJ9ry4B8/zXpZshLWWQ5ND7Ju4xP7hfs7qIhtSi/CUw3RQY7JaoRwFFD2PVdkujk2OMlmrUJURVSL6WlrZ3rWQOzp7SU2XKAwOse6uu/j1U99h70R/XbYxbtYb4s0qa2zctVIW6cQrsEIQa/xb4g0RZVHSQF2OaCAa47cOfo2t3Z08XzhFWVfpac2z6T9tYfzz/QycGiaZS7Dm/QtI3F3jL4c+QTlboDvdhZccpxSOIJAI7SKFxUETCYk1EKAJhMQVmrKwKGPwhEZZgyQigY0HLNM+yrEYLbFKk+muoRwP6SYRlBGqDCKLtS651LlZOdDQuVEe+eOnscayYGUXQgiCWsjhZ0/S0tMy62+9hFuXbgsojBfJtqbRkWGkf5y2rhzrt64g15bmjteuvupn2ri+5lL/uK5LV1cXXV1dze368fFxRkZGOHHiRHOLtr29nZaWljk3Yl6d0H6FoyE5MlfttjAMOXDgANPT02zbtu26qz23IpFqEFdaa9atW8epU6fm9LhHLh3hs2d3MxnEJEdFhzF5MyPS0qFFJYis5uTUKKVymazj8mMbtvP9K25r3hgNU4PTp09z7tw5Vq9fyx+P7ueFiXOAxpMOrpAUTJWKrZJ2UxRCE5uWCEWHn2ZZLsvB2slYP7IeWgsM8RSlpzSuY+IJSWxzEy7WOdIoEU9POkIjPcsUCbpUCUcaEjJECkNKBDhSo4h1sEVdcMAg4klJIgJhcIjXet2sIZKgksOM2UFe+8MpapXDZHMGEbjUSoZUJiKZNFQnckxP+LR1B7zpPcfpfSGNk/uX7Hzr7UgpeOqpp1AzyOyp0WmOv3Aaoy0rb19K+8JWjj1/ms/8xpeYGp1GKonRhl1f3strv38rwxfHaV/Q0iTEHc8h357h9MGL3P3wJr719/spTpVJ55JEgWa4f4Lepe2sum1x8zNyPUW2Ze4ktOM4dHZ20tnZ2TQTaazFNXQnG4Vda2vrdcmlBih+L3bmXk7cjDxIw3itra2NjRs3XnOqfuaq28uZvG8QV4sXLyaKojlfX6HRfGfsXL2pJvjG4BmSysWpJ/2OVLTiMmoi+stTWBUxWphE+S7vXbyRNy9ag7GWvlwbXn3Sc3BwkCNHjtDX18dxv8b/Pvo0w0ERJSRGGMpUcZVDLbIYYXClQ2QsvnJY2prmTFhPtrCxrFFdL1tJg6sMSlgcaZDNYk9grUGKCFdGSKGRrqWWgaL06fSqJJRBCo0vQpTQJGSAEDEx7ojYK0DWpwO0NdSEg7KGpAiR0uKiSdiIkj5HernLglSCfHs/UgimLrbhqRq59ipB1WVytJVEKk9bl8u9S6cwqQxGqSuaFqf2nuMLH3uEgdMjWGto723lvh/YweN/uYtSoUL38k6kFATVkJN7zpM5N35VjUgpJa7v8NB77uapL+zm0plRsJDM+LzmX9zOuruWNf/2ZlYqU6kUqVSKRYsWYYxhamqKsbExzp0715QGmEkuXe/ae1Vy5OZjpjHtjT7DmcZrGzZsYMGCBdf821vR1J9JXG3ZsoV9+/ZdYWI0l6jpiL87fwiJoDcV520dboJpHTBULdDr56hOl8gZQXsyTYefQQrBpvZu3rBoFVvae4BY3mD3iy/GhMPyRfzSgcfYM9mPFrH5tTISrS1CCoQFrQEBSeWQSlumRaXZMLPETTVrG2SSwVFxDtTAoNBqjLW4KkSgkU5E6X6oCUuX6+I4EQkZgAhwRYiSGis0UmgiBC4ghSGyCoMgROGbiLBevCVFiMTiWEgSooXAa5OoagAY8GuohINEgpB0Lq+S8Dbguh7CDGL1Nwicd87CoMp0lT/+xb/i7MGLZPIppJLsf/oI+54+AkqxdP3C5t/mO7OUChWqpSrlQoVE6jIpUCpUSKZ9Nt+7irseXM+RF84yPVmmozfPuruWkUxf3ggwxsx7Ak5KSUtLCy0tLaxYsYIgCJoSbQcOHJi37mSxWHxVQ/smYr7GtNVqlT179mCtZceOHdc957cCgxrEVTKZ5LbbbmPfvn03dZzAaD56+BscL4zQncjS5iUZKE0xEZW5VJmk20mTrIWkpEsJzVClxHQQ0p5I8RMbtnF3xwLSjoM0ln179yKlZOvWrfzPo9/km6On6/d9nLcgY2FagYyJJA1JzyH0avHWSH1DJJYbscg69ihpUBKEiCcDJ8IQ3wErI6QIqaI5tX6Clk0JWpwI3zcgCmgCHFUhQCNtiMXgY5FSYKyDxBIJRWQVCRMQCgefEFcYQitJEmIEaKtIAQgPvy1CGkVQkaTaqviOh++lgQApCvWzmgI7gpKjCHG5qXHihdPse+owuY4sqexl3dkju06SzM328RBCkEj7WCEYPDdKe28e5SimRos4ruTuhzaQyiTY+tD65or/S+Nm8h+g2RyZuUU7NjbG0NAQx48fb27RNsil6+XyhUIhloe6RVKS3ysxU/pxrhg0NDTEgQMHWLx4MatWrbrmZy+EuCVcUKOhv3r1aqrV6k1LxBlr+aMTz/FI/zGqOmQyqFAUNS5UJliebidpQBiLkJKK0KRch85UCl8pNrf2sDrfwY6eRazOt3H48GEKhQJ33rWF3z/1PM+Mno05HhVLiEij0MZiMIDEEYBvwdGzciBrQYg63+PUhxqJ8eeZ6cOcDV2UExES0l+7wD4PFr6/nTfmdhK5Qxyt7CUIC2iKCD+gZA+jynEtpoRB4COFi8SQkjUiFC4RmogQhwQBjhBoK0kRIISiai1pkUBKg0gGODaJsBLpVJHIemZVxtqY0AZNpL1ZuHLsO6coTZVZsKKr+XPPd/F8l8JIYVbOpLUhlU2w4valjAwWuHR6BCkF7QtaePsH7yPXdv3apoE/8x3oEUJcc4v2xIkTVKtVWlpamhh0vaGhmRra32vxXUFoQwxipVLphn/XMF5LpVLs2LHjhquJLzeRmpqaYs+ePbS2trJx40ampqbmBIqHJgf4v6e/g7GWRal4/eVUcYzxsMR4rUSbH19s1kLadXigo49ocJL23sW8fsMdLM60NI/V0Ik9fPgwk5OT9G1ezyf6d/Gt0dMYG6+cRMLiiTRJ6VIxIRUToIQg5yfZ3NLLT6zfzsdOPgphFPuwCYsxgub3sgBHWZTUuNLgyBmkt5Vg4595MkKK+lSRMExbBx1alBuRkiGO1GAtvoqnAVwRd9zA4godywYQTyOApSYkwhoQAZEViFSKjDuOmwoI8Cn2t9PSNhZrbfsBiHZyHW1kWyq8/p1TRKkVIOQVnbFn/243X/rE15ieKMXnOJ/kvvdu58CzJ5meKNFbF/y31jJ0boxvfP47RKHGeQmhpBxJUAu583WrCaohB549xdRYCaUkC5d38q5/c19zGrLxGm52VU0I0SSXFi9eHE/j18mlM2fOXEEuvVR3slqtorV+dTrpJmMuxZy1lvPnz3P8+PFZxmvXOybE18bNENozN1E2btxIb28vR48enRMGhUbz0aNfZ9fIGUITJyaj1RIJ6dGdzCLrUwtt0iNwFVEQ0B8GtGVz3LOgjx9ZdQcZ18dai7WWKIo4e/Ys586dY+PGjYz6mv+17zEmwzJSaVzhY61LzYQYqUkqj6qJQMDKXDs/s2EHf37x2zjTdcFaQGExFmwk46kkYfEcjRTxpogSsQdAYAQ5IpTQOHWMkhikNExGkqrx6HCDuvN4PGkk65hjsCRFhMTUJ7BAEE9KVq1DipBQCBTgojBCkW6XCCuJtMXLFUkrhTUuibRg8VqPRGoBAhDmLNYcArV5VmI0dmmC//vLn2diaIrWnjxSCkYujvGX//3vsFKyaO0CpKwnVwmXVC7J9HgRlfQx+rJOrY4MRhsWrerm3rduZu2dSzl1qB9rLMvW9dK9uG3W9XezBV0jpJS0trY2NZgbpiZjY2NcvHgRuKxL2d7efoW8xasNtZuPmVhxvcbltYzXrnfcl5MDzWzo79y5k2QyOS8Zk0vlKb548QAvjJ0nsob+UoFFycsa3znHJyddCjrk+NgAGelhEy4bMu38p83305XMxL5p9ab+6Ogohw4doq+vj55FC/nF/V/lUGEAgcURktBqhLJIGxdyQliUVCzwc3xgzR18/OwTSGORdbLI2ngU21qBUjGh5DRJ7RhnLRCaCFdFeCqWVPNkhCstU9ZQjSRZFCkhcZx4AyQpGzlQnCtZBFLo+vgABNbBIQIhCaxDUkRESEIUHmlwKrgZEEEK5dTIdhm8hA8iAdRQTgXwsMIDW8ba+Lurcf/vf/oI549contJB05dczbTmub4i2cQ6sqiy0u6eAmXWjVgbHCKdC5BtRRQKlTY9vAmOhfGn9mON2685mf9cvEHYnKpp6eHnp6ea+pOzjTYfun36qsT2jcfc53QHh8fZ+/evXR2drJ+/fob5jYvF4NGRkbYt28fixcvZvXq1RSLxXmTU1UdcrY4zvHCCKenR1mQzOGr+L7ICo8pGzJQnkTpGvl0hsj6WOC+7j46Emnu6ljAylwbxhiKxSL79u2jra2NdevW8Yenn+NLA4cI0LFOv4xzGmklVllsFOcGfblWti3s4fOXXqwTRvWmPSCsiPMWaXCVjbdE5GWcmgwteTdAqEaNpqmKKmPGUKhZkhLyLjjY+PfCIOq1mLUCIyzxjlqERhKhkEQE1sWjihEylgPAwYiACIVPEiMLoARpL4ulhBQKIUwdN4P62Y2xKNL5Wbhy5sAFwiBqktnxtSBJpH3Kk+VZOZMx8b/f8y/uZOjSJANnRtFak2vL8Lp33MnGHStv+BnfCvyZuUW7bNmyWVu0x44dIwiCWeTSS7doi8XiP5jp9vdCzAUrrLUcP36cCxcusHHjRnp6em7Jca8VL23ot7W1cfLkyZs20H1h7AJf6T9CUnl0JTK4SIpBjeHaNE6gSWvFipYOThbHCbXhXHGKVi/Jv1pzJ29YuAKI88AXX3yx2VD76uAJHhk8ipYRUoDRcX1npUbY+J5wpeTeBUvYNX2K0MZYI+pykPH9DE5d8jFuqtWNjIDxqEpGRrhC4ymNFYbR6CKfnbyIIwwtjsRXNRJK4ssIrMFVEULYehYV63gjBFXjkZZVQuHgorFYAuviUsMIQWiTOMLBUCSyFk94GMogDUr4WAKMAEWNWEDJBVsAIRkrrCS/4PK9F4WXt4FnRqY1zeRwganRafLtWaJIM3JxnI4FLfzIf3475ekqF08N4Sc8VmxaRCJ9Y439W4E/MLct2pkG2zPrhYYp7bW2pf45x3cNoT0XsBkYGODgwYNXGK+93ONeKxpGbytXrmTZsmWz1oJvFN8eOUM5CliavmyOsTzTzlRQ4XRplKi+GjpsqywSOZaM1Ni2adsVLrnGGCqVSnMaYdu2bXzi7Dc5WhhEInGkQCIo6iplU8KXKRwUrlT0+Hl+cs127u1ZxnRY4VR5AE+ZJkAhITL12UUrUdLgqZh0bkxJNqa0q1qR8WqAxZcRSlgk8WS2IyxF42OsQABZVUVi0VAHq3g60m0Uddj6/+M58ACBaxXWOuBO4jqWsOqi3JB0WwUvoRDSI9du6ejuxnFSYJMIO4o2/ViVb06LCSE4f6SfL3zsEcIgomtJrMs5NTrNl//gSZCKrqUdzWtHCEFrV47J0Wm8TJKpsSKtXfHkWGx0UGLB8g56lnTwrn9zPzvffBtD58dJZnxWbFzYNCdpfFZw84T2S6Ox+t/WFl9D1Wq1SS6dP3/+Ct3JRkNovqsm4+Pj/NRP/RRf+tKXkFLyrne9i4997GPXPU61WuXnf/7n+exnP0utVuPhhx/mE5/4RHMFdN++ffzmb/4m3/rWtxgdHWXZsmV8+MMf5md+5meax/j617/O/ffff8WxBwYG5pSg3MpobIlcDyu01hw6dIixsbErjNeuFY1r4WYwaKYu3MxNFCklYRje8PHfGD7FsyNnaPVSpJy48WeMZag6zUhtmu5EfLyy1eSN4vtSi7hz/SYW5NvoSsaffYNEiqKIo0ePMjk5yd13383JaJL/cfgxRoMCSkgQmpqt4DsJbKgIrMbYiLTj8S8Wrucn1m3DU4pfOT6IkhpVxyBjQRsJysQGS8qghMFVdVK6TkwjIbASX4R40gCGhArrK7LxY4rap2qdmDCyloyKz5FAoERsfOTUN0+AOkZJwEdgCKxGGg9sBKpEQrigFU7ekFIJXKWxxJPis795ZPNcNXBlzxOHmBicpLuvs3kNdC5p58z+C2htm2R2I5SrSGZ8WnpbGTgzQqY1DdZSnCyzoK+TO1+3FoCOBS1Nw9yrxa1KqBrxUlOThjTApUuXOHr0KJlMZha5VCwWb2rV7XsdgxorsVLK6zbVGsZrmUzmCuO1a8XL0dB+aUO/QVzNddppuDrNrx14lAvlCdKOR2g0U2GZ0Gg2ugtxhEQJQYeTIAoMrV6StmyeLR0LecvitSxI55oYpLXm/PnznD17lo0bN9LW0cHvH3+K70zUt86UxcVFRyKWWFMWrMARis1tC/mVLQ9QNQHh2aA5gQ1gRXw/6kgisShhcOr448r4nwDaxtmQEDGZHW9+WBIyRAlLYARIB61T8QSSECghcOuNtDptXs+B4rV9g4tCE+KQtCmgTIhGRhFCGbQ0pBIKi48UDhKBIaofLa5EhS2g1XZsPKrQxKBLp4awxjbJ7MbvkhmfwniZKIxw3LqCrrXUygH3vP1O2ha28Z1HD1KaquAlPF73zi28/ge2z+l6udX4M1fdyZkG2zezJfK9jj+NuFG9NNN4bc2aNXP2EbrZOmxmQ3/mJsp8py0fHzjGZ8/tZqxWohyFFIIabX4Kv14CdyiPSqQpRgFTXpKyqdHiJfnQ2q3c2720iUHW2lkNtaVLl/LtkTN84eI+DBG+UFRtfH9Kx2CjWMrIlZItbYv4ja2v53+d+CZSmvr/G+8TtJYgLI6MyWzXifMkUW/sIyxVK8kQN/Vj7ImQ0qJsLBFQ1IKySJK2NTSQlkE8kICIjeEAayVCGCLrkBAhBokWCRQhERJjXJABoY1w0CAF8WJx3XeJLNgSsbVtBmwRYUcw6jYq4VKEuPz9pVwV6/e+ZHstlfGJgoihs6O01DW0J4amaOvNc/97t9HalePiqWHCWkjvsk5S2bnJOtxq/IG5bdHOJJemp6dvitB+FYPiUEpdlygOgoB9+/ZRrVbZvn37nPPNm8Wgl0pLNibv54tB2hr2T1zi5PQo3x4+QyUK6U3Gw44tXgIPRRBFTIoaC9sXMRVWWZTO86ZFq7mttZfVuTbybkyqNnxT2traWL9+PSeKo3z8xDep2KApIyKFwWgZ3/cSHKt417INvHvlWnY9cxxVz4FE/XYxJvZNs4KYzFbxhr1bl6EFqBrw3Phx3gweyBERFWupRZaasVSkjy9CHBE37JWIPZMaNZhG1jHJElmFKwwGiSWDoEJowQ0twoll3oxwiOlKjaVKbKXdAQwg8VB2EkQSox5gZHIZK2bce323LcZLeZQmy3FdRayJLaVgzbYVhKHh0pkRlJJ0L+ngXf/2YTItKTItKbrmYG47M/4h8Aeu3KJtGGzP3KJtYFAURTclOfLPAX/+SRDaNzJeu17cTDFnjOH48eNcvHiR22+/nc7Oyw6v1wIxay1nS2McmIqn2M4UR2OiZ0Y4QtKZyJB3U6Skj7aGO2UrW0wr99+1vUlcNo5nrWVqaop9+/aRz+dZv349T44d5dHh/UQ2QioItSCpEqSsT5WQ0IQ4QvFg90o+tGobi9IxYO6ZPEdENQaW+vS1NgJHxqTytvwKjlQPowT1SWwLwqCor8UhiIwkqeLiDWtIObHMiLCWpIzJpbL1ibQisA4JGZBRtWYBJ4gBTQqHuLOfrGvaFrHCrXfkqighUcrH2ArJtnjNBREbKonm5HgNK1wQl4k3iAugPU8colSoNKewAVq6ckyPl6jVqiBe0rkS8dTAHfetZffXjzF4bhQ/6VEp1UhmfB58z9amScmCZR0sWHb1zldDv/IfqjOfSCRmmZrM1J388pe/zMc+9jEAnn/+ee699945a9/+0A/9EAMDA3zta18jDEPe//7386EPfYi/+Iu/uOZjfvZnf5Yvf/nLfO5znyOfz/ORj3yEd77znXz7298G4MUXX6Srq4tPf/rTLF68mGeeeYYPfehDKKX4yEc+MutYx44dmyUbNJ/7+1bG9Sa0y+Uye/bswXGceZmANEiq+WLQzOd7qS7cXBOp58fOY6xtktkAi9MtTARl+iuTVKKISEdEGF6b6uWHd75+1vNYazHGUK3GBrQAW7duRbkuf7bvEQpRGSXAlQppJBUbULNVpPRwjKQ7lePHV23jbUtik8RDU5filfzGPWwtUgiU1ISRYmGijUk7gCNjgtqRBlfWV9+sxQKNs+hJ3Zy0Tqkwlhex8TZIYF0iG2NQWtVIyBBtRfz39VtT4NVbayEIH0GApYKjGl+JMZFu6oVkGKVQcjzGIVHv1NspEAmM3NQ8XzMntKl/9o0QQpDKJpgaL1GcLJNtTTcfNz1eZMOOVbztww/w9b95gWMvnkMg2PbwJu5/993k2ueWnPxDJVSN1z9TdzIMw2aD7dChQ/zJn/wJu3btoqenh9OnT9PX13fjg9bjVQyK43pNtRsZr10rblZD+2oN/UZIKeckOfLYpaNcKE+wKNXSzIfKUchItchgZYpFqVYqYcB4UOGO1l5+7953ocTl6eGGpnijoTYxMcHdd99NNpvlL889z2NDhzHW4AqFtiERAb5yCbUksgZfebxz8SZ+cv120o7H14ePI6TGFRopL8uqxU212PxSyVj+w1O6vgUSb5oJEVM4jrE4Kp46Squo3nQzTRwSNp6EnDJplNBEVpFUQTypjY6/E3DRGAQpBFUsEUI4gIqLSNdF2xBrJNqW67IoOSJXIcUIkhTCBgjOYUUL2nnLrBwIIJWLC++XkkmO65DvyDJ4dpRsSxrpSApjRVq6cux46x0sXNnNzrfcztToNNnW1KzpyhvFPyT+wLV1J0dHRzl27Bj/7t/9OwYGBti7dy+ve93r5jyp/Sr+XG7qXysHajTYG/dgS0vLnI99M+v+12rozzzeXLxJXhy7wCdPfJvIaFq9FEoIRmsljheH2JiLm2quFeSEIp9p4f7eNbT7KbZ3LWFZpqVJZDe2886cOcPGjRvp6upisFrgd48/zrQuIqTFEOFJSRDF/kRCWhyruL97Bb9+10MkHJeyruI4MTXc8AqJ1/0t2iiktPUcKJ6g9OoTk8LGEkiRFbgWEvWmm7AGv45DShiSMkQIQc24CIinrkWELyNcESGQSAwIicADNIJEfRtFo2S8peYIDTbCWomJJFoVAAdkDiNCpJA4QgAltNpC5P5rrC3Muv/XblvJk595hqmRafKd8UZprRIb5d7/gzsZuTTJaP8EQsCyDYt464fuo723BYAlq+dPpv5D48/Vtmgb5NKZM2f4oz/6I/7yL/+SIAh44YUX2LJly5xfz/c6Bs2UHLlWDtRosOfzeXbs2DEveaubqcMaz9fS0sJdd901axNlrjkQQDkK+N0jT/HC2HlCa5gMKtS0piVI0ualURY6hccgNWoKLpSnyLk+7+nbxA/0bcbO8FYZGRnh4MGDLF++nGXLlgHwv058i6Iu4yqDMYLQ1GtPZTFRzPO8c/EG/tPtr+F8eRLlxJKPSs3AZBVzQraOMwKD1/QTaQw4WqpGkFJ1jf/6Boisy8smZDyR3fAxKZkEjojzLVdqJBpVb61pqxBoEF59cjtCCBeoxfWf62BwEGiMKYJxMNJBqiquSCCFD/JOpNqKlu0YuRYj1mJ5etY9t3TDIu5+02ae/eJupifLOK4iqIR0L+vgX//WD6AcRf+pIdKZCivWDeO4BzAmwIq+ywXjHOMfGn+A5iBjgy+s1WrNBtuFCxf4nd/5HQ4dOoQQgoGBAXp7e+d03H8O+PNdQWhfL5FqdMfCMGTHjh3znryYbzHX6P7VarWrPp8Q4orjWWv5zLnn+PKl/ZR1PBUY6IhaZOk1OVT9Ajd18HvLwnW8Y8FG9uzdy5QzyZo1a64gs7XWTeBaunQpfX19fGP0GH9y7pvUbICDjIkeGVHRBmU9BNDiJ3lLz0Z+YvXO2atf5SFUXX+2sebmypiklsLhJ1bdx2+dHGAkHMCTl8GpMRkQv6565oWNCSVi/be0ioltWwc3V8QTR9pKdKRIypCktDh2Gk/Ei/0QIoSqfyFIJLresXPjrqGKkDikcj2gxxCMosMEE4UKvlcl5U9ina1YcVm/uvH5FCdjA5OXJrqJtIc2hsnhabqWtDUlR+L/buedP/EgKzcv4fnHDzM+OMXKzYvZ+ebNrL5z6ZyunX8MMGvES3Unly9fTn9/P7/3e7/H+973vqa+4Y1IpSNHjvDII4/w/PPPc9dddwHw8Y9/nDe/+c389m//9lW1WaempvijP/oj/uIv/oIHHngAgD/5kz9h3bp17Nq1i+3bt/Ov/tW/mvWYvr4+nn32Wf7mb/7mCiDr6uqaV3H0DxXXaqo11l2vZ7x2o+POB4PGxsbYu3cvvb29rF279ornu1ZxGBnN08PHeWb0FFUTMlCers/UXA5HKtr9FMszHSxSOcYGh1jmtPHBe982KzlsYFChUGD//v3k83k2bNgAUvCHp7/OvukzQGzqGpgQXyVJC5+qCUFYlqZb+bXb3sS6lstfSufKIwipcTAoWXfstjEGCUfyEytey++c+TyyPvEYE9/xyr6rLjfEIgspUV/rr6+0Nf5ditj3261PgdesR2gUYX0ayReChCiTEE5d3R+wGiMsLg5Qi/0EZBuCaZSsImnFRu1oM4kkIgqmQZ1AKh+8N2Pl+uY5a3xWrT35eDLJxDq+jd9bC0vWLqA8VaYyXcH1XSrFKrm2DA/8wHZ6lnbwvp99I0E1/h65nrnj1eIfE4Nc152lO5lOpzl16hSXLl1i7dq1vOlNb+KLX/ziDY/zKgZdjqs11YwxHD16lIGBgSsa7HM95nyN3q7V0G/EjYrDYlSjEgXsm+jHk86s5v6SdCuFsMpYrUSpUkOHIUsTOf79ltfjyLhgbBBIDcf2/fv3Y61l27Zt+L7PWLXI317aExMr0uAIBw+HwGi0iEA4ZJTHj6/YyQ/13X650VSbxlG62SSTsmGGZJFCcntuMUcqJ2MNf+JNEacuDXC5qJNEVuDXp7ethYSqb21YW8ekGIccYTBCUq4XdiEKT2oUEkcEWAxhnVaytgpC4ggPQxEpFL7TjbSDYA3KGqo1wLbh0IbxNNLdAv7bQa3H1q+bxnvd9Nq1PP1Xuxi9OE77gtbY/HGsiHIV7/i3r2f44gSHnz2J0YYNO1fx0A/uZOHKeLImkfJILLls7jbXmKsp262Il+pO1mo1fvEXf5EPf/jD/OEf/iG/+qu/yqc//Wne8573XPc4r+LP5WhgxUuJ4mKxyN69e/E8j507d14hNTWX485nPf+lAwQvfb7GNTYXQvuRS4ep6pBFqRYAPJVhslZlIihzvjRGMhBMmxrJRIIPrdvBwwvWNI+ttW4S50ePHmV8fJy77rqLXC6HsZaPH3+K0aCIRCGEJbIahMF3HAINSgke6lzFr9z5erw6tom6jIirZq/CGwTSuFgksi5X1NhGc6XGETRlSrSVda5F4M7Q4k6qsI5D8Qabqq/7N4aSQutiRUPyzVA0Dq6wRKaGFhIfixElsA5SuCDKuMLHE3mwNYgSlAJLqbwFzWtpzbeRzS9CuStACKydmvV5LF7TywM/tJMnPv1tBk4NYbEopVi/YyXv/rk34yZcBs8OkU4corPzBEJ8ARNtRKuddWml+cU/Zv4DNFf/29tjrOzt7eXYsWM8+uijPPTQQ6RSKU6fPn1DPe1XMehyXCtfaehXX63BPtfjzqcOazT0G/X1S59vPk26v71wgGdHztDmx9uyvnA4Wx7nXHkUV0O1WCYhJN3JLA/0rGJrxxJW5zvpSWaaGCSE4Ny5c035yQbh97kLu9k9eQYhTew1pASuFISRjKVkpeC+7j7+w+Z7UVKSdxOx0WK9UTZzE18KidYSAU0C25Uap05eq3qzzQKBkbGsmog3bVN1KTasiXGo0WyTUROfXBkPBkggqjfvwzqe+UiqpgrCISU0oS2BcDDCRxDhO20EUYaJ6V5K44txnQX4qbtobRdkMilcuYjL/YURomgQKdoQcjnv/Jk3snxDDyPn/57WjpO09bTQ3beDXHcLQjh0dx/ADf8QYSchAEsCre4j9H4cxNxp0n9s/IF4i7Yx6GitZWRkhF/+5V9m7969LFq0iJ/+6Z/mox/96HWP8c8Ff74rCG24OojNNF7bsmXLvM1mrnXca8X09DS7d+8mm82yffv2qz5fAxRnJlIvjJ/ji/17cYViQSKeiB4LSkxHU5wsDdHjt8TvJyzTm8yzNbuQ5557jlQqRTabnTVJ20iizp49y5kzZ1i/fj09PT1ERvPFgd1Ya0kqj0BrEspFEMVGSAYywudDK3bwtoUbrwDf8WACR8bGRo01Nm0FjrLkHZ+V2U7et+g1fPLc5xEiiosuEetze8LgyqgOerHWZMOA2qnLAhgr8IWJZUXq0wYJQpQwhFahjSYwmaZEiUeatAxj3VqRw9opEFVc2Y0UEmMvofBiiQDlIkiTcvKkvSJRJJgoLuTAqY14iReaetIQFzmNokxHummyZo0lDDR3PriRi6eGGTg9gus5hEFEpiXFWz7wOlzfZcsD69nywNUNR24UrwSYNaKjo4OHH36YT3/601y8eJF9+/Y1u7fXi2effbbZfW7EQw89hJSS5557jne84x1XPObFF18kDEMeeuih5s/Wrl3LkiVLePbZZ9m+/erryVNTU7MaN424/fbbqdVqbNy4kf/6X/8r99xzzxze8a2Nq0mOWGs5deoUZ86cuaHx2vVirhhkreXcuXOcOHGCdevWXSE/1IirJVLaGj5+4kmeHj7elPiZjqpUI01HmCLtxsVBVYcoIbkn2UvbQIkVa3dy/PjxWddtYypyeHiYQ4cONRtqQgi+NnSQx0cOg7U4QqGEpCpCarYCJm6qrcx28Msb38SK7GxCpKSrMY5IDTZe+Ff1SSQrHe5qX8bri7fz5Piuuoa/Jani9VprQQmD39gusfEamyPiNTlPxLrbpk40OUI31SkTdcO1wCoMGo1HQLxG5+LhUMW1IGWKwE7jInCExJJC4uCLDMqvgbgTKTYT1qYplDSXRhYyOrWE1tYDtLe3E4Zhc3J/y0Ob+NZfP8/Q2VFae3IIKZkcLpDMJvjhX/o+xgameOFrB5meKLL19b1sfeNtLFy9uHmu5ktkz/zsXgkMEkJwxx13cNttt9HZ2ckv//Ivc+HChTk99lUMuvZ0UrVabepX38h47VoxnxzoRg39RlyrmCuEFT599jmeGT1JYDTFMCAyAmsv+z04QtLqJ1ltcyw1SZb0dLPQeCxJxxJOM9f7G1q1jYaaUoqaDvmdE48wFIzH5I00BEQo6ZIUDjUTkXY93t+3nR9advvsXEjGU4xKRnGRJmJC21iBMZKfXPkQv3D4EqGYQgpwBFhiktoRlpm6t8YKsMSTlHXiKCFjstxYQUJGTRwSGHwR1ldsJaIuW1RBx2a1eFgb4GIJcfBRZEUSYx20WIvnLCPhL0Wobiq12xmdmmZ8sMj4eIjnTdHefoyWljxS1qCuWLlgRTfv/Nk38cWPP0ZYO0u2tUo638rOt7+W171nG1JKaqURXP33JN0ngccxwVYi519g5fyaJo14JXMg3/d517vexYc//GEeffRRPM+7rmF8I17Fn8uh6ubGM+ubhvHaokWLWL169U19vvPBoBs19OEyoX2t6y0ymn2TFxkPShwpDODLGbI7wLJsG5XJgGKljHJTtLoJ3ta7njf0rgZmk9lRFLF//36MMWzdurX5Hf+d8TPsnjqDVCFGGBwchFGERmNFhCNc7ulYzi/d/mCTzAZo9RJxg74+Ud1Y5zdW4kjNhuxSDpROomQ8RdnYVLO23tyvE1HGCnRDvsgKHKGb5FKy3mwzNsYkp+5dJDH4IkDUvUtE3W+kSmOsqC7XJKBqFAm5nBZnOWU7jcHF9zaSyT0IJcF06VEGpp7j1KUWhNlJW+sSrN1PJn2IWjWDVBtxnNfy+h95DRt3VIjKf0W25QLSaSPVthonKRFIli/9O5zoUTBBfV3mcbR8isD/BRDz+757uebrLzeWLFnC3XffzalTp3j++ec5ePDgnMwhX8WgOK5mTKu15siRIwwNDXHnnXc2mwfzjfnUYceOHbtuQx/mPvFtreXJoeN4ymluy7b5KSaCMpNhhbPFUVr8DIVKlTvyC/jgmm3k3UTTt6gRR44cacpdNr7XRmtF/vrCbiwaR0giKzE2zkc8ZYmMZF1LF7925+vxGn4Brk/KlVSsiYeGBLF0WV1qJOVmKBtdl0OKsSAeVoyJ7RiHTF3GEUzsP9k0wvVn4FOykQ9BPR9q4JDGq+dD2tqmN1uAQGGpWoERHsp6BDi4IktapDDuNKLlDLmWSVTgYcL/SaF6mkLVgl2EJ36QhQu+RhicIKQKwkOpzXjeR9hy399D9Azxnu954AjU9oP7PtzwkwhbwtJNTLdP4+jHMHo52nnzDT/jRryS+Q/E98/mzZvp6enhAx/4AN///d/P5OTkDR/3zwV/vqsI7cbNa63lwoULHDt2jFWrVrF06dKblnGYK+gMDg5y4MABli9fzooVK675fFebDHhm9CSB1nSmLq83dvgZSlGNvJOsq0hbtncs440tfZzee7A57fn88883p4uttYRh2ASuLVu2kM/HBPmLk2c4VbpIZCOsiHWPqtoQqz4a8p7HexZt5fsW3XbV113SZZS0+CKqF2UAAm0EC/x4nf2Bjtt5bOTbXKyewxUNQimKySUba03GP4fIShxR13hDIITEkyFYkMLBF7W6Tq7AIEgQ4koTa9Za0EJgrMETBmkrlKxPVjokrKKMRrCCtOxGyAjkJlCvRwsX7Dgi2UUuv5G7O8wVhmWHDx9m0eYuepZ3MnBqmExrGiEF02NF2he08o6feZigGvLCYweZHL7E2s1lVt+1nI5li688afOMVxrMGoZsUkruvPPOOT1mcHDwitUOx3Foa2tjcHDwmo/xPO+Kblp3d/c1H/PMM8/wV3/1V3z5y19u/qy3t5dPfvKT3HXXXdRqNT71qU9x33338dxzz8359d/KUEpRrVYBCMOQ/fv3UyqV5mS8dr2YCwbNR5/7amTS/smLfGvkJDknQdqJp5ladYoTxWHOlUdpcbNYLMZalosMucEiW7bcRSaT4fjx480itpFEXbhwgdOnTzcbahDj06NDB7A2IuFIajrCkx5pIamaECUF3V4r//P2t9OVvPJ8WaJ4TQ2Lo+oNMxtjicLgS4cPLn8Dh0onKESDKBGT2Ka+XtvQjQSa09XGEv+dZAYOGbACIRS+qNYVruNH+s1ETKBQWCICK9FCEhiNFK2kZSdYl8BOIkUHWec28u59GFqo6hewyTSpzEbW9d5OuVxhdLSfQuFrBLUxisVYb7O9vZ0f/i/v4Ouf+RwtHQdwvIjC+CI23fd9rLk7NnW59y0ZnPBPUeZJ4G/QtVVE7o9i1NobX1RXiUaj9ZXEoGKxSF9fH5lMhnXr1s3pMa9i0OWYWXQ1jNc6OjqaZO7NxFwniebS0L/eMbU1/PbRx9g9cZ608vCkQlvNdFTlUtVlQSLGtNFqEVsN2ZHv5h13v5aBgQFGRkaA2UTS+Pg4Bw8eZMmSJbMkVp4YOczR4qW6h4jEsZaajdCEWAOuULxnye380LI7r8jjso6Pp0x9msmisFDf5nKkJu26/MzKt/CxM59DUo31suvyR9ZyeXW2nkNFSDxr60u0Aqc+6iSFxBMzcahSrxtj5xBfmvrUpMQhiSNKaASCBBaPyCo0FteEWEYRpkBBlWgRvdT4H3jZ8/RkHZasuIew8k5K0y8SBH/HurUDjI//L7APks78CFvesIRN2ybRtX0IEaLcNG6yHcRrwGpy6reQ4jBYDxDI8K+R+kVqif8GYn76kfDK50BhGBIEAdlsloULF87pMa/iz+Vo3PNRFOG6LidOnODcuXNs2rTpZenpzgWD5trQbxwPuOoxL5TH+Z9HHuVceQxtLNNRDWOg1Us2N0DCWoCv4fsXbuTNq7Zw8fAxlrctaW5tNjCoXC6zb98+crncLAyeCst86szXKZsySqg6aRMglMSzHhGGtS09/MrmN5ByZjenuxOZeNtDNTZgG78xCAsfXP5a/sfJCUbCIRAWV8ZeAAkV4Ugd4wumLrsWN8ik0KiGLxASV1DHnrp3ka3nRiJo4pAUFl/GNZpF4Yk8jhiJG3CiDSVyBAwxEX4bR+SQwqeqT1EKv0JSGRLZGskstHRYjN5NWFpKS/45pAwplyVS/S2OcwdJ7x30LvxErLstUmALYP4YahcQzoM40aNYEiA66+RaDWX24kSPErlXEinXi1cafyDOgVKpFK7rcscdd8zpMa9i0OWY2dSvVCrs2bMHIcQs/eqbibnUYTP1uW+kCHAjTLtQHuepoWNcrExwsTJKUl7eMpECuoRPjYCOdI7eZAstQZKf3fgAeTfRHCqCy7Wo1npWQw3gS5f2MRyOo1SEARwlsFrVJUcMXX6O/37nG0nPkJ10pWJJuo1T5VK9YaabzTOLQFFjS245B4onmlshCppk9uVaLEaO+qIItl6UqQb2EBPkti732MAhiCUj439TKAyeEMR0pCIpcwgGMQhc0YEvslgOUzURnlyKFEmMGcZ1/xTXS6FEF9pYtD6Htr9KW7ulUskiVRbX1WCfJdBn8e0YQrZebpLZIkRPIIkQtoBlwQyJkRzYMk705D8pQhsum0Jms9lZ2yPXi38u+PNdQWjPnI5sEDujo6NNN9mXE0opgiC45u+ttZw8eZKzZ89y2223NcXMrxVXmwwoRjXkVQhwTzpsbO3lJ1bej8VSGBjh+JHjs5K1RgLV0Krdv38/URSxbdu2JnBdrIzxx+cep2Zqsf6ZECihkSrCaA9XOryt9zbeu2TLNV930nHwZPQSAQKLI8FzdPO1/Nu+9/Ffj38cQ4CsTwfYuvt2qq6V1JhQ0qgmGe/Uk7q4qEvgiEp9fTaFtRU8JRE4seyKTuGJAtIJ0NpHijxWGkq2TGSqSCGBEkU7QFa+jbRYQKX2KbQZRMpuUt73kZS34TgF2tqeIJ8/yJIlCY4d7SCVWsLY2Dh3vLuTbeVDdHV9B2MUE6ObWHn3O+hZFndbl688iBt8DcFkfCaqf0nofgDtvO66n//14pWeDiiVSk3H7f/4H/8jv/Vbv3Xdvz9y5Mg/yus6ePAgb3/72/kv/+W/8IY3vKH58zVr1rBmzZrmf+/cuZNTp07x0Y9+lD//8z//R3ltM6OBQQ1iZz7Ga9eLG626NeRhgDnpc18tkTo42U9oNOkZq7m+cuj0MyihWJPpBgtdRct6cuzceTepVKppLtmYiNRac+zYsSb+NhpqAIemL3K0eJaoYXokYyNFrIPFkncT/NyaB69KZgOkHBdHxGR23CGLMSfeBokoRlXa/Cz/v7538xunPoVhGiHAqa+9NewcEzJC1Se4QxxU0yRN4AinnmAJXOnjUgahcEQKbCnWfLRJLBodpEh4E3EyZtN4cilWTBCa0xStjyPbMHaE8dqjVKM9KDuOtWXiw7v4zmvIJN5MV+fvYswAYVjD2gTlyg4OHXoDbbkX+Jf/6QkEFaSUOO4wwk1g7RqkncAL/hvCjGBFPG2h9F6kvUjN/02snBsZMzNutSntzUSlUmlOEb+KQfMPpRRhGHL27FlOnDgxL+O16x3zRnqzQ0ND7N+/f86G21fDtIOT/Ryc7KfNS5NUMWam0j4npocYD6eJDFhjsLWIN7at4F1334dSqinjNtP8sb+/n5MnT7J+/forNACfGjlMZGt4jiY0IUp4pIRH1YQ4juDe9tX8+MqdV30PPYkcjopzmIbxbCOMsVwsD/O6jg0M1Ub5m8GvQcOAzQpcafBVnCtZaE5LQtyUc+sEtRAGR7ggKjG5JBM4lBHCwZEJpC0ihcQaF0uEsRLl6rpqv48nl4I9j7HDaNrx1EIsNYJoD1PRt1EihxQ5IKQafRnf30OHP4m1FcplgeuWsOZzDAwcJutCa/4YbiKPUm0IUYHoS/XJpeVIcxRLZ6xjGb8TpD1bJ5N+4LrXwNXilS7oisUiAOl0+lX8mWc0/D4gzklmEjs3Y/Q7M240Ham15vDhw4yOjs7JcPtahLa2ht89+jVOFUdo9zJ4UuHWigxUC5wqDbE83UWpVGakVmJhto33bthJu59mRDpNEqnxOicmJjhw4ACLFy++Ysjp6ZGjjAQFHBQSgaM8aibCWAMyot3J8isbHybnXpnLrcl14ypinVoLjmg0t+JG/bHSRf77hh/il4/8X0bD4Vg+0Zr61prAlRq/ud4fywBIYdFQ355VQIPM9kBUEagZOOSi8FCiWFcI8EAaMBWkNBgcNCEJmQRbwVoNwseRXVijUXY/kRV4ch1CKKTVaHEeL3cKqVswug1QBEEZ5ewiLB8l7VYRaiFKOPEApJ2G6BuxljdBTGY3QvhgJUo/c1OE9s1sct/KKJfLr+ZALyMaWNHY1Ojp6WHdunUv+3vlRnXY9PT0LMPtG11H1yO0d4+f57ePPspkGDeyS7rKZFgioRwyKkGhME2AoSOV5Zc2P8ymbDdPPPEELW6iWYvBZUI/m83OMuUGGKpO8eWhPWgiHOEQ2giLQSiLikXN+Miae1iavhJL72hdyNnKeVwVm8o2ni+WKKpwT+dyUq5kT+EIEPscAbiSZi0m0SScqDlkpJE4GIyVIDSu9BHUQAh8WdfGlg5KuCiqCFywDo4s1qVCPBAR1k7G094oIjtNQgLWxFr+NsCRLfU6LsRakDKLVODIFJE5QBj5JFVsjlisgZI+ycQxlEjjiN7LnLXIgJ3E6mPUNWpfcpa8WIJkHvFK5z8Qf5c26rDvNfz5riC04fKE9q5du1BKsXPnzjkbr93ouNcCnSiK2Ldv37ymMKWUWCwvjp/hucnTTEcVqkYTmQhtTVMrUluDwbI220PO8Tl69CiDg4NXJGtCiKZW7b59+8hkMtx5552zgOux4b0Uogo5J00hqiCFRCEJiUi6kpXphfzIsp1XmFDOjLRykUI0O3KNQk5bQWBLzb/rTXTw4SXv5VMX/gREpf4iaRoeWUDWp7M9IZHSp74nhrVOLGtCDHISBXUdyRj0XIQI8T03tkSyLlZAWEshqOAmp4iswhOrkFJh7TSl4E+JhEXgI0SSSJ+mUPkoWp9Hme9gzNmY6LKGZcs02axi2bL3Ytf9IVYfJYrAGI2U36YSFhka+gU6W0ZJ6k8CIZZ2wCLsGF7wcapyAVauuuF1cLV4pcGsVCo1C4+f//mf58d+7Meu+/d9fX309PQwPDw86+dRFDE+Pn7NiZyenh6CIGBycnJWd25oaOiKxxw+fJgHH3yQD33oQ/zn//yfb/getm7dyre+9a0b/t2tjsaqW7FYZNeuXTfc1JhPXK+Ya8gqdXR0sH79+jk1RGYmUtoaSlGtqZX9UtJKCEFvMscvrLqf3bt3k0wmuf3225vJWuN6jaIIay0HDx4kDMNZDTWIpQQ+eeZRTH022hUOUmi0NThIwOX9y3ZyV9u19eZ7Eq34Tjwlbok7/kKYen8sYjgYp83Psjq7mA8ueQd/1v//0LaEKy+fu5QKm3psUtQnIoWsJ1GxqZG1EkdatI1AgERhralLBghi8zVDKmmRNsahyNYolqdJJSbB0RhrkLTWG46TGL0XIdpwxMKYgLMlquETKP103dikA60DlKrQkn+GrXctQgZPYYymVmsjCgxuFOLrpwhrS8kmFMKMYkUPDZtxSwphBnGixwi999/wOnhpfDcQ2sVi8VUMuolo3LNKKS5cuEAQBPM2XrtWNK4HrfUVRdp8G/ozj/nSvOp8eZzImiaZDXGN0JvMU9EhD2X6mBga5YFVm9i5auMVx9JaE0URJ06cYGRkhC1btlzx/g8WznOseI6qDZHEpJCxFSITP2dPIs9HVt13TdzuTbTgS4Wl1mzA14XUcKRm//Rxtrev490LXouUmr8bfBxJSKxjW98gRJBSEUrEM9UWMEJiMGjjxMZMRFirUBKMrZtaI2ONSxFjl1AO2hpcEWOvsRJLhUpQJOlPEs9hxrrDkgSSEEsVwSJk3QxbkARzBCtSwBK0nsb3WrC2SE/XSVxr0VGWIJRYU8FxHDzPRdnHkO7dxEB6eXoL4cT6uXof/BMktEulOJdNp9Ov4s9NRIPUfvHFF2lpaZm38dq14no50Hwb+o3XeTU/oyNTA5wpjdLmpfHrK/btiQw1qykEVS5OjSKsYEP7An5i3eto99PN4zWaaQAXL17kxIkTV22oAXxr7BiBLaOcWMbRWoUnXUJjcRzFv16xkyWZqw9jbcgtIqUkgbX4TkPPn/qktuH5yYN834Id/Mb69/ObJz7DpeBcnCsRyx95DRyyoinJ1ogQBVYTCUVCWDQR1IegLuOQAGFjHJIy1qm1AcLW0PUpS21DIjuFo+LHG1upb56UkNZgUSA0oBBCIaxEUwWTRCqHZCIBJNG6hrCDhGEPtXIxJtldF9f1cdQU1g5z9RDA1c1JrxevNP7A5cEieDUHmm806rBarcbu3btvuKkxn7geBs23oQ/X9zL6w1PfZCqs0JPIIYQg6yQ4WxrjbHmEfJRAKgdcxfb2JWxuXRCvmhJPYzuOg5SS8fFx9u/ff9WGGsA3Ro9R00F9ilqTwCE0BmMNjoJtLct568INV33tr+1YzZeHdsV6/lg85zInZK3gm2O7+e2N/4Y/OvsoXxvd1ZRIc+o5D1iSTtSYS8JXdSkk4touwkHYEGMdXGkIrcGpY4+xGoSIBxdFvM3WwEBjLdYEGBErAlgMxlZp7J7YBibYanwsZgyrisZna/A8D9/360MSETBIqENKpSmUcuoY5MRyKiINjIMNLjf2rQUqaHl12YxrxSs91Ahxnl8ul8lms99z+PNdQ2hPTU0B0NLScku6cY24FoiVSiV2795NIpGY1xSmlJJdcoCDJ44S1XcsrDUEaC6WLVk3XokpRwFL0+3c27aCF198kVqtxvbt22dpYDbIp0uXLnH8+HEWLVrEqlWrrgCuo4V+BJqkIwmAmo7XzjSWpOPy4b77ceX1b6KFyTacSYGSQXO1BOLpgLKZoBxVSDnxa7+jZT3vCN/KV0f+DkOEK2PtSGtjbd6ECup6bYI4WcqRVRmUKKHtEGAQIgOU0DbAkz5xchKfr7i7ZhBCgpBkszmsKYAVGAvl8jRCuDiOIuMVMLi4cjHxVGgOY8YJw88AEiF7kcLBaI0xQ4TR36AoozgBqgfluFgsWpdJq0OMXPoydvo4izqm0HThOKKuG9iFYAAnepLQ+6dJaM8kkzo7O+dkHrZjxw4mJyd58cUX2bIlnvB/8sknMcawbdu2qz5my5YtuK7LE088wbve9S4gdqg9f/48O3bsaP7doUOHeOCBB/jRH/1Rfv3Xf31O76GhnfiPHcYYhoaGKJVK3HnnnfM2Xrte3MjkZPXq1SxZsmTO5LmUkjCK+MrAXv7+0m7GgiKOUEQ2YCqs0OLFGBOYiNBoNid72LVrV1Pm6GrPc+bMGUZGRshms7MI70a8MHmS8WCaLj/HcG2aCIMSCmMtmoDNuZW8oWfjFcedGavSvThCEAG+nCl9BGDZXzjK2mxMiO9sux1HwGcufRZLPEXui8vmR0ooPFnDretGKhRC5EhIB1dUsUwgMEiRBsoYLErEOGTrRZ4jXCBOrAQOqUwWYS9gbVz8lSpFHNcl4ZRAGqxVIGMCS4o00g5h7SRCrkEIhSXEkgWmCMO/JSlClLsA1xMYE0u5GFOlWvkytckOOvJRrLXpxs3GmNhWCHN6TtfBS+O7gdAulUrNxvCrGDS/KJVKjI+P47ruTRmvXSsaCfZLi6+GNmyxWJy3rNLMYm6oOsWRQj8DlXGsNURGN1f7AWomIqklq8Zgy91vmLUC2ZgMKpfLnD9/nuHhYaIoYuvWrVesF2tr+PPzT9d3McCVLo61hES4yuCJND/e91o6/GtPk7a6GTr9NKNBvGnhNrS0iWuYo8UTQFxYf3/vA+SdBF8Y/BKactNYzRMGJXR9GtJFiSq+jKeqlHCADK6wKOkDBUAjRBoo1Q3aUsA0hhApFK7y4/VXBNImUcZgbXw8g6YW1XCcWMbN1ou6Bv8lcJBExCqWjTMDkAYxghCQSCwkkZBoownDiCBUiHCCqYkBuvMhRsZFtGg81moQN7fa/UoXdA0ySSn1Kv7cRFy8eBFjDF1dXaxfv/6WNPTh2uv+N9PQn3nMl2LaVFghMvolmtmCVieJCSK+L72Ce9ffwdrWXpyXyEcODg7iOA7j4+PNDbWrNRQPFS5wvHS+Phmp0NQbWBgEDhtyvbxtwdWlHwHyboqFyTb6axeaOZCSti7RCBdrFxipTdLpt/Ara/8Vf3zhb3lxag8Q4dYHCa0FT16e2naEixQ1PNGYmFSERpKQMUZAEYtGiCxQrONQGpjGihApXFyZAoJYW9skCIIAmTBYBMJKjDBIGt4kLw1RF9a0zLxihIhxJZl0SSTzRFFEGIZUKiVcJ2C6lGZRq0WoEkKm48faCAjR6u5rnsNrxStdg8HswaJXMWh+EYYhJ06caHqGzNwQfblxtTpsZkN/vrJK1yK0TxVHGKhO0uKlmviZdn16vAwjtSKO59CdbuWBntW8Y/FtKCHRxK/r1KlTdHd3UyqVOHnyJGvXrr2md9OLkyepUUKpxpCQQEmFNYKEdPjginuv+do35hfRncgyEtTw1cymWqyZfanWz7Hps3xo+ZtYl1vIn138MmUzGWMPdRkk4ockVcNAkljIUUS4ItbE1jhIq1HxGACWMiARIoulGE96iyxCFLAidg9xZAprx2L5y9ClKjQJz8ZSu9bHmng4sp6NNd9TjHOiKYECjQZJiDUZfNcl4aYII4iikKA2jecGjJduY2GLJOGcBtKAQlDAiha089Y5Xw/w3YE/DcmRTCbzPYc/3xWE9uTkJAcPHgRg1apVt/SCuFoiNTIywr59+1i8eDGrV6+eV9J2vjzGbjVMkiRtibgA1NYwXJ2ix88Qmfi1v7Z3NW9sW8PRF+Op65dqUjbWa33fZ2RkBCklAwMDRFFER0cH7e3tKKWYDIsMBIMUTRFp6iv3SpKUGWpG85aezazM3HiqakV6EQlFfS1N1gtCS0MJct/0EXa0XtarebDjtbhS8NWRvwbiSW1pFb4K48kk4SCQgMEREWUzSK/fR4uzESgyFZ5Bm34cIVAihaUIBLi0okQaY8Fi8EQeISQCjRWghEMm14rWBh1NAZowcgijMo4Tk9xCpJH2Eoh2BJcTYG3SYEvo6GkUDoi4SSEQOCoNcopVfUVcrZDapRYYqrUiAoHrOvguWHF17Z+5xCsNZuVy+bqaX1eLdevW8cY3vpEPfvCDfPKTnyQMQz7ykY/wvve9r/lF2t/fz4MPPsif/dmfsXXrVvL5PB/4wAf4uZ/7Odra2sjlcvzUT/0UO3bsaBoBHDx4kAceeICHH36Yn/u5n2tqKjUKTYDf+73fY/ny5WzYsIFqtcqnPvUpnnzySR577LFbeFbmFocPH26ev1tJZsOViY8xhqNHjzIwMHBTJidSSnZFF/j26QGwloTyqOqQkBrjoaakg5h0BZa7LXRerLJm/aYrJh0aa/6LFy/m4sWLTf3l06dP09HRQUtLS/N6HqlNEdgKodZ4SqOtQJv43ksoh3+78g2zisirRVolaXOzTEbD9W2POAWSAMKyp7Cfdy14CCXi425tvZ2Mk+AvLv05ZTOOFPGarRQOntQ4IkKImMixSJSIiGyNLn8FabkJKFKM+tFmAEeAFAkMJQQhvugk1qsdwhLhy464saXjrRJFGieRIIwiorCK8iDSBquDmPwRAoWIi9j666Uhhyn8WCcSv7nGJqXA81wwKTzfwZpVSHuacq1GuVxBOQrXcfDdCKs65nU9zPw8pZS3jIS4mXgVg24uoijiueeeI5lM0t7efsvIbJg9od2ImQ397du343netR5+zWNGWvPps9/iSwO7KUfxpEzZhvRXQhYk23GEpBjVKFbL3KkWcs+OnbOujYbUWltbG11dXZw8eRJjDLlcjoGBATo7O8lkMs3r+Xx5lIHqOC1ekvFAE5qgnjsINIY12S62ta+47ut2pGJNZgHjEyN1DVpDY/ZRCpiIhjlePM3qTB8Ar+/cSW+ijU9f/Cw1O4LA4NQngaRQOCLEESFxkSaRwkGKuNnX4a3GFy7WFqiYMawdRNaLMEMRWceduDiLj51w2nHdTCxHYmtIm0OHcYHipOLXaFCxEZwQcHk3B7Aztmbr05M4QBlEBqVUTBjaMta2ocVDGHuaoDpKSSdwHQ/PDXAdgVY3Zwj2SudADR+R+WDgq/gTx8DAAMeOHcP3fbq7u2/p98jVNmUvXrzIkSNHbtonqVHbGWt5fvwUz46dYKxWxBJRCCvk6439KIoYK03R4qb4ke2vJ+VextZGHdbX10d/fz+HDx/GGENLSwuFQgHf969orH1laPeMzEXgSTc2j0ST8Xx+YPG2627LAjzUdRufuXi+Od0o695E8Rko83eDj/OBpd9P2knwkWXv5emxPr4w9EVCMx2/d0TsFQJInDoOBSgRI4wrfJTQJFSSNqcLVwqMKRDaImCRGAQ+hjKSEE/ksfV6TgpF0utEeQ7WDCFshA58CtE0jrLkkrHggDUOCEv8v1hwQHD5M7ZWAwFKbgR7CSHSuK6P6yiwU2jbS1h9D+PTJbKJA/F2gHJwpMU4q4icN83reoBXHn8gzoE6OuaXw72KQXHs3bu3iRNzMfSdT7y0Dms09Kenp2/KJ+lqmBaZ2DPENH01AAuVagWCiFY/za9vfju3tSycJTdrrWXz5s0MDw83z0FbWxtCCIIguCI/O1kc5ESpH7C4OGhh0BgEGl+63NOxktXZ2ZrIs167kDzYuZG/GXiKhtG1p0y9uR+3yz838Ai/lP0wr2m/jY3ZZfzB+c9zunwCKCOsbh7HEfUtMuGgRIgngrpsrMQRDlIo8k6ehEzUPUam4yElG+tqC5HAUEES4EqfCFGX1RUkUjm0DuMcx0KlHBKqKVzXkFT1zRMTghBYO44gG2+ymYlYUoQq1k6hnG1IGyHsEXzXwXfj6e9Q30k1vJfdJ1bQnfsavW0ncF2NVbdhEz+IVWuucvauHd8N+NOY0J6PTNg/F/z5riC0W1pa2LlzJ9/61reIomjexdX1YmZXzlrLmTNnOHXqFBs2bLhm5+t6sWfyLBGGjLqcFCkhSTk+NVvjj7f+OEpIxsfG2Ltn71VJ84b54/HjxxkaGuKuu+4in88zMTHB6Ogox48fp1ar0dbWxhPO0bp2dmzqIS1EaMpmmjang3va52a8tSHbhy8VZSNwpcWRYTP5EEiendjF9pY7mq9TCMHr2l9L1knw9wN/RWgnEBKUjBAIlFBoG5GQIZYKFsNw7QQT4QXavaU82PFrQMTFypOMBQfjAspeQgBVU8RBIjG4Mh+b0dXpIUUOKRTSUTgyibASz0lhhUsYhtSqVZQK8JPUXbpjHTlrZ04GxInZlRFPLgh3JUocIO2kQMRfbGEUonXI6Yuascruppj+fIqjVxrMGsXcfOMzn/kMH/nIR3jwwQeRUvKud72L3//932/+PgxDjh07Rrlcbv7sox/9aPNva7UaDz/8MJ/4xCeav//85z/PyMgIn/70p/n0pz/d/PnSpUs5e/YsEBtw/PzP/zz9/f2kUiluu+02Hn/8ce6///6bePcvL1auXElbWxvHjh275ceeiUG1Wo29e/cSRRE7duyYtbEx1wjQPKf7kY6itT6NmMbHEZKaibi3fSVKKPJFS88kbL/rrlleBA3zx4ZWbX9/P+vXr6erq4uxsTFGR0c5cOAAxhg6OjrIt7fw3MRBAluJcQiBFAbXAWWTbMovozd5fc1LiMmk2/Mr+ebEMAKFBJQMkUIDgmk9ypHiCTZmL5sirs+u5aeX/jT/5/THKTOCRNbX1WICTeGgifBljRgZNYO1o7jCp9tbxUOd/w2BZbC2i4ngGNaWqOnjGFuNV4bxUWiEkERmGouDg8CVWVzHw3VdjHERVgI+QRBQqVRQSpL0IxzlYnQVMcPwBVtGyKUIOwK2CiLROPFABdRrcBIP49SeIefU0LYlNkS241SrgoPHW5H+oSYGzXV76JXGH2vtrOmk+cT3OgY5jsOOHTs4f/78nEys5xONNd7GcRsN/UWLFrF69eqbumaklLxQPs9fj+xHCUW7XzedrU5T0TWGawUwYMOI271ufmbb20knLhNDM43XpqenGRwcZPHixSxZsqSJQWfPnsV1XTo6Oujs7KTkVCjpaSJCpLR4Mm7OY30coXjv4u14N2iqAdzTtom9hYP1jYr4u92VxBsdWB4f+WaT0AbYmF3Lzyz9MH9+8k8Zcs7HxIuQSCRSxNejwkUT4YoKUoQEVjNYq+AKj4WJTTzU9rMo4TAa7KYQncHagFp0nKoZJLIRDu04IsDYIjVbRJLAFQZXSZSrMDZE6wSKKkGtRFlrHEfiepMo2YISoqnvb4wGhhFiAUr2gfkOce6TAMpgKwj3zeTS/wIZjpCJvooxZYyZJtKCcwPrOD+epq39FO3t7eRyuTlfI680Bs1c959PfK/jD8QrxNlslt27d99yDJqJPy+3od+IBqH9B6ef4JGB/WgbTw9XbUgpqBBajWMEU7USruvx3lU7rkpmN7YKJiYmaGtrY8WKFUxMTDAyMsLx48dJp9NNDMrn85yYvoQvBVYYQhMSWVkng2FFpoOtbddvqgHc27aBzw88hrEVlGg0perWssKwZ/oAQ7X76PY7EEJwX8dWVni9/NGpP6MgL8Wa1/HsNEpIVINUwkUT4sgqgioVU2A0msYRHsuTW9mceysKl2l9mkJ4FokkMgMUwn0YIpLyDqwdRttJNODIbjyqiFSEtVEsoRZ14NoaFc4iRAJHhUiZw1frMeYoUpQxxgcCpFyCm/hFCP4A9MF6DmRBtKISP8ei7Cawv4EIH8dUnqYaFBkaW8KF0Y1ksudpby/R3t4+ZzPAVxp/4Oaa+vAqBgFs2rQJiKdDryaR9nJiJga9dEP/ZjinmQR5aDSfv/gcjwzspxhVKZsK1VqVBX4b1Uo15hg8SU8qz9pczywyu3GM1tZWLl68SCKRYNWqVRQKBc6dO8ehQ4fI5/N0dnbS0dFBOp3m2fGjCEAhieqbIgqHkAhPSt6x4Np+ao14W882Hh/dRUVP40kTGzg23htwrnKWb4x/h/vat9Pq5fh3K36MZwZf5AuDXyRwinFTTAAixiGJwBVBjEl1HIrlkcpM62lCm8YRPmtS97M8dQeezBDaMaajCzgkEEwzGe7H2IC0ehBtzlHV53GUT9p5A8IOE8pBtCkRhGlK468hnz2H611CSomSbbjiRxkaPsDSJUexdgKEh+Pcj+f/dDx4FD4C0bMgFELtxHPfyIp8GthApXIPA2ODjF8aYmy8gusWaG8/Snt7O62trXO6Fr8b8CcIAqrV6rwx6J8D/gjb2Pl8BcNaSxAEPP7442zbtm3enbLrxeDgIGfOnGHr1q0cOHCAyclJ7rjjjpteZfnCxef5g2NfoyfdNusCL4RlPOnwx3f9OJcuXuT48eOsX7/+Cqd1YwxBELB//35qtRq33377FQm4tZZyuczZoQv8j5EvxNqS0lIlworLa11v676Hf73s4Tm/9t859SmOFU8iZZk4GYqniiyahPT50UU/zO25zbNex/Hjxzk5fIwTC3ZRtJN4sshlN1xNUtUQKAyGlMzhyzSBGaLVaSel8nR661mZeQMZp5tidIbR2rNEZhpPpJgOv0GgL9W7+y6+iEFSigwCibYFEpRisJa9COFiTECkh3CMi0OZWq0Vp+ngWyCR9PDVW3HMF4FWRJNMKgJlSPwKUvbiV38BYaewIr4OhJ3Eijam+G+MjHuMjY0xMTHRLKjb2tpuCGoXL15kfHyc22679rrhP2T84i/+IkEQ8MlPfvIVef5/yqG1ZnR0lD179tzyRO7AgQMkk0k6OzvZs2cPLS0tbNy48aaTtT2XTvCfj/41ben8rKloYw1jQZF/v/qteOcK1Go17rzzzitkjhp6tSdOnGBwcJDNmzdfYcJkraVQKDAyMsI3R/bzCAcIhSXC1LvvoNEkRJJ/v+o93N26ck6v/WDhOL935o/RNsJTl+WPYlNdy5LEYn6u76fx6wSx1poDBw4wXhljaskw+8tPY9GkVLVR/iEJSaoAgcJiSMo8vkwQmGFyKosvU3T5G1mTeQs5dxGRKTER7CWyJVKym0L4DBPBN7A2JKEW4YkyoT6Dra8BShKkpQd2FPBicxJdJAxzqNAlmRgC0kQafC9AOSk89z/gmq8izG5is5N4MhLRAYnfQKiVqOiruMGfIYjltix5AueHGC/fy9jYGGNjY5RKJXK5XJPcnjmx+tIoFArs37+fe++99qrhP2RYa1mxYgV///d/f801tVfj2hEEASdOnKBcLt/y75AnnniCLVu2MD4+/rIa+o04evQo/2vsW5y3U7T7l/M1ay2jtWm2ZvvIjkZs7FrK/RvumiUlMJNIakyFrl279qq5UmP9f2RkhMc4yH73EobYhBrAYJAoFvi9/M6m95NQN27+1EzIfzzyO4yHo/VJxyDW8od6s07xkWU/zrpM3Fir1Wrs2bMHx3UoLB7nucITVOwoIEjLClKoejkXzMKhlGrBxSGyI6RkAkd69PibWZf9PlrcpXGepy9gbJWkXMB0tJep4DksAWlnI9JOUgi+gjZTCOGTcV+DR4la+A20KWOMJQxyDF98I71du0mlTsbbJp6HEJ14/n/AUSsR4f8foueIzdeSoB4A/8fj3MhapDmENLsR1qDVZmp6PeMTk00MstbS1tbWxKDrFf9PPfUU27dvnzMBdavjK1/5Cr/6q7/KoUOHXpHn/6ccxhjCMOS5555j8eLFLwsfXhpTU1O8+OKL3HvvvezZs4coirjjjjtuqvnQiKeffhpneTu/c+FrOEKRduKcITARQ9UpHOsiQ0l3uoV3LLuLty64DVknkmaSSVNTU+zfv5/e3t4rho/CMGw22EZHR4kw/GHyWcq2Gh+rrhmrcJEkeP+SB3hb711zev0fP/VZni+8WBfrEHgqRNb9hgSSzbnNfGjJjyGFpFgssmfPHlpbW5nqneSpiUcIzBiIAAEkZRXVxKEaSRUi4j0OsqotNm5knKT0cYRHp7+Bjdl30+otB2Kdf4tGCZ/AjFEM9wOQcW/DmDEKtSeJ7Ai+WkbWfYhIH2ay+LcEwUXKpS7Gh7fgqrUk/G/S1X2CVAqUvAvHfTtK9SBEBPp5MKdB5EDdg5BXn2Ju1L+N8z41NdXcXGpvb5+1OfjS2L17NwsWLJiXdMStjre85S287nWv49d+7ddesdfwTzUakjSPPfYY99133y3xUWvEyZMnqVQq9PT0vOyGPsQmks899xwPPfQQnzj5Nb46sA8pJJ50mI4qlKMAaRS+9VGuQ9r1+alVD/DartXNHKhBvzVyjEQiwaZNm2YNsVSr1WYOND4+ju/7PJE4y+7oNIjY78cCxiiMVSxJdfIHd3x4Tu/hU+e+xOMjz+Cqy1rUnrR1HIIWp5VfWvXzZN0MY2Nj7N+/n54lPQzmh3lq/KtU9DQJFfuRSCwJWY231JBIUSMh4+01iyErO4AqMEVC+ijh0e6tYnPuh5s4NDOstUR2AoGDI3NYG1HVxzG2QkKtxOgUY+MXmJh6lkJhkkppCa7TVq97V+K6I0jZhuMsmvdnrLVmcvJyDlStVmlpaWliUCqVumoddurUKaIommVy+I8djz/+OO985zsZHR296WbxP9X4rpjQnmmIFEXzN4K4XiilCMOQXbt2NaegXs467+aWpThCUYqq5J14Ek1bQ0UH7GhbxfGjR5tT1zNJokYSVSwW2bdvH4lEgrvvvvuq03dCiFj6YGE3bsHDt2BMiKch1HV/WWnotRmiKJozMbaz7U7OVk6hEfX1MIFG4whQQvPMxLNNQltrzcGDBykWi9y/5SHude/hqfEvcqr0HJoiEo+UEkAN6lObjnCxdgxJkUJUIjBZJsLTXKg+y+va/xM5dzkZ5zJwGfs+iuE+QjNJ0lmGQ5Lx6mcohs8Alqx7P3nv/2PvvcMkuatz/8+3qvP05LhxNucwcYOySEIggUBgorExGBvLxgZjw733Z3zBvte+2MYG22CCSRYYE4xNFEGBlbSrDZPz7uQ809OTOnel3x89Vds9Ybdnpnd3EPs+j55HO91VXV1ddep8z3nP+76EUPRzqPoA5tyJ076LXM/7iEc+hd3ej6IEFlhJMpOTd2AY97O1qBeH3IJhLDC1hR1hewXIJzGETNz5IezxLyEZg4BAlw+h2N+FU97FVg9s3bo1Jah1d3dbQc2UhHG73SlB7VZ350Kh0HXd4W9jZdyI+GPud25ujr6+Pnbv3s3OnTvXNc6bY3cjI1B1NaWgregaEoKBjm72e8tWlDmKx+O0tbURjUY5ceLEsotKIQS5ubnk5ubynKMH26SdPOFiRgkR0xWMBWOzfJub6txdS7ZfCfu8O9nsKsEXH12Yr5WxLSy8BAZ+xU/TfAsn8mqIx+M0NDQgSRJ319yD3W7nQHA/T/v/i6A2hEEckHFZxTLTF8CGYfiQCBHWIuhGDn3hJxmL1nNv0f9Htm0T+Y4qbFKi6JLrPM4W47fQjRiyyAZUQspFImo7knDitd+BXSomGPsGkfjPMIwoHsc9ePPfgiCXmZlPoCrPIwmNYKiQUOjVOBy7yM9/P1mOHyHpTyOMKMinEI43IeRE8V+zPYgmn0LWWhL/lo+CyCfPkZha2r17N7FYzEqqBgYGkGXZSqoKClKbqrc6/gBrZmjfRuKes9lsGWdHQoJNdOXKFUKhkDUuuN79zWgRbIs0bxNGbRrBqWl+c/8DbNu2LeV1MwZpmkZPTw9jY2NUVlamTJAkf0ZRURFFRUWU7drKl1vP41GdhPU4qp7w8DAwMITGS4oPp1XMBnBKdu4rrOH7Ez9HiOhCMTtRyDZIMB+/Pfaf/MmuD6BFNerr68nPz+fQoUNIkkR1wQm+P/EVRmO9QBxjQVfWY916C/ksEobhQxAmpitIIofB8PP4Ym3cU/j/IYSKYShk23ciCwf58l3kO1ObUQXuN6Lqk8giF1lK/GaK2o2idSKEB6f9BNuKHXR0tDI+fgGPZwJV8yDLp8nNLSM/347D8SEkxziS8CPkrQgpSVJLCHT5CLp81f/ALkNpaSmlpaUYhkEgEMDv9zMyMkJHRwfZ2dlWDMrJybGeZWaOe6tzoNvxZ20wf0ebzZbxPMhkU589e5a8vDyqq6vXzb6UJImmwBCKrpHjuNpAsQsZpyHhNWT+X83b2JJXZHkMLWZFjo+P09nZyf79+5c1n7Pb7ZSVlVFWVoau6/x46AW08QVTRj1haGYI0FDIkj2cKtiX9vE/svklNAYbUQ0Fh6RYTO2EhJlOR7CdZ6bPUCGO0dTUxPbt29m1axdCCA7nHOb87Bka5p9CNeJIIo6BjoGBW7rKsxRoCwVzP4IYiq4jS3ZGIxeZjndzR8EfENUmEEKiyFGBLDtxSIUUOJNIHVIhLlvq93LYNuFxvtT6tz/fv0DSupsp/ynsdvsCCUgiNze2YHR3CmE7fd34YK5/s7Ky2L59u2VO5vf7aW9vR9M08vPzrRiUXPTcCDlQJBLJKCnvVw2SJK2oub/e/c7PzzM+Pr7uhj6YuY7OeGSWpybbcMg2vLbEtehEZlKZQ8iCw7lb2ZFVxMs3HeJgzqaUhr4kSczNzdHY2EhZWdmyBXaXy8XWrVutmsT09DT/3l+HThyhJ8hAhjCQ5ITsz4k0yUUAj2y6m4a5ZoLaNAgJpzUxm/h+Ad3PZwc/z+udr6Wvq4+DBw+yefNmDnKQE/k1PDv9FPVzZ4gZM8hCXiA7Jbw/nOZ+FohHQmhgzGCgoOoSsuRkItbCmam/4ljuI0S0EWThosx1mlx7wpjTLq7mhULYcNsOWf+WJSgr3UVZ6S50Xae9vZ2JiQncbjcXL3bh9XrJz49RUDCD15uQXDPNhK8XI5LXWYDVYPP7/fT29uJwOKzX8/PzU3xqbnX8MRnUv4p50IYoaJu4EYu5YDBIOBxm+/btHDhwYN0X286sYqpEGc3GFJPRuQX3aIMyZx77Z9zMarOcPn06haFiJlF+v5+WlpYVA9diFNhzcEgwrUwl/iCDJAtsuLHrDvTREL/o/QX5+fnWOMq1mDEn8yr4hf8XDET7FphNGi5ZQRIAMfojzTzj/ymnvffS1NQEQG1t7QIjx8Mjpb/FYOROfjb1BSJaAIgs8BM07MKNXQgUfR5IjL655DwMQyes+aif/SfcsoOYNkO+Yz/lnofIse8gx5HKZijz/im6ESeh5ZZ4OLgdtcSU51C1MWSpDJfjTiSRhU3azejIV1DUBgryy3E6X4JuHMTn83Op5WHyc3ZSUjiC0+XF7roTWdyJpBkIoaGL4+iuf0AYw4DAEFsWTNmu4lpBraenB4fDYRW38/Ly0DTtlgazSCSSMUfoX0WY8cc0CcoEDMNgdnaWQCCQMbPJElcu240cBrQQNsmGU7Kh6Boz8SCFipPKLbs5sMj80UyiQqEQzc3N12yoLYZDsoHQiIkgdoeCEwmb4SSiaTijCaZUYWEhxcXF12XwOSQ7ryy+l6+Nfi1hTETC5MwhKQn9NiPK0/4fUEohQ60j5OTkcOTIEeu+Ouitoty9j/q5n9M4/5MEq4g4+kISZRdO7EJH0UMkkig7TjkHw9CJ6H4uTP8lBgF0QyHXvoc93jdR7KxAEk4kYTY67Xgdd+B13JFy7Dnu95Djfk/K9REMBunoeBWlpY+yZ88WolEvQswuSCZM43QeJj//LgoK8snJyUXWZCRDtZJ2RD6a7Z4Vz5fT6WTz5s1s3rzZYpP5/X76+vqsUUQzRt3q+KNpGpFIZE3jtreRwI1oqkUikYRcVyy27oa+CUmS2GLLoV3zXb0fDINQJIKqatSUH0wpZiezIuPxuOVZsFJDbTFm1SAaOrmOLDyGnbAWQ9X1hFmZoTPfN077XDvFxcUUFBRc11zuroJqzk5fZF6LIISMtMAisonEyO6cOsYPh79Hfm8R27dtZ/fu3dY9n2vL482bH6M71EL9/M+YiHVgEw5sIoZOjIQVkh0ZFY0oCeNsGw7Ji114iOmTnJ3+YwQaBgYuqYD92e9gi/vepedZuHDI21P+ZrftwW7bY53X3t4u5uaCVFW9naysLGuyZnx8nCtXrpCdnU1+fj75+dvxer1IkmJp7adTXMrJySEnJ4edO3cSj8etHGh4eBghhMXeNg30bnVB+3b8WR9WMrFeD/x+v6VVbRZl1wtJktAWCtPm/nRdJxwJAwKvN4sdBVf9hZJZkYn7ppfh4eEVG2rLfV6XOopDtuPAQUhLaOUaC0SbXEVidnACW5FGbm7ude+Dbe4SanOPUj/fjCQSjGp5oSAkMLAJlScnf0JsNMKxA8dSJljy7Pk8UPxaKnKquDD7NFdC59AI4JQS6zAdNSkOxdFQSORDNuySB9lwoeijvDD94YSMGwKb5GG/99fZkfXqVf0OgUCA1tZWtmzZwt69e9F13ZJs6e3tJR6Pk5ubS35+PgUFBbhcLiv/SSdW2Gw2SkpKKCkpsUhhfr+f8fFxLl++jMfj2TA5EHA7B1oHksmNmYxBmqYxPj5OKBTi5MmTGTGbNDW0e0OTRDWFfEeigKgqCtFolFyHG0UYPLbvPnYv+JwZhmHld6ZvWkdHB/v27VvS/F/pM6NeCMhRZF1GN80cDYFh6Bgizu5YLsFgMC251CJHHg+V3sM3x76PEBqSSDTnTR8jMBiJDPOE76e8qeKNKYzfLDmLVxY/zEsLH+C5mR/TMv8CUUMh4ZXmxi70RD5k6MjChmSE0VFJxCEZu+RGNmxoxgAtc59CFol1Y2/ov9jnfQu7vW/AMDTi+jQ24UWWlq9tGYZBZ2cnMzMznDp1iqysLOLxuMVqb21tRZKkhRwo8Z/dbk87BwLweDx4PB62bduGpmnMzMzg9/u5fPky8XjcYm/H4/GMThWsBaFQCIfDkbZU5YsJG6agvVjncb0wDIPBwUGuXLmCzWbj0KFD198oDQgheIm8k9NbDtMSH2deibDHVUzhqEJpdg7Hjh1blhU5MjJCV1fXikyA5dAfGSWqBzCtG03zI40QNXlHeXjvKwiFQkxNTTExMUFXV5dlaldUVERubm5KQJOExF0FJ5iaGMeGjCpmFvYrYRg6khA87X+CiV4fB5xHOHLkyJKF4Xb3fl5f9sc0zT9FX/giUT2CQ/LglfPRjBkS2tUC+0LwEULCLmLMKBcJqVkIIREI9zMWPUtt/p+R71iqAS4Jx6J/u3E7Xp7yt0QQm2R6+iRVVe+1Egi3BzZt2oJhHGVu7iRTU1P0jfoIBoPk5LRZAS0rK2shodpiaWJeDysFta6uLuLxOE6nE4fDQSQSuSUjt+ZD7DZWDzP+AJam4nqhKApNTU1EIhFKSkoyZjYpSRL3a9s4nz3PleAE84aOrmnkqDYe2/lSDu46kPJ+MwZNT0+vqqFmIs/uRiOMumB0ogEKMYTs5FXld1Ll2s/U1NSKem+Lk6o7Cqo5M/00w9GEqYlTjiPEgtEQOtPKJF8e+jSvKX4zR/cdXbK9R/ZyV8EjbHPv4dLcj5mKdQNBnMKF11aIbkwvvFNgF+6k/w8S0mZwSrkIZKbjrdTN9FCb/2cUOo8S0/wo+hxuedOKyRNcTbrn5uZoaGhg27Zt1iI9KwuysnLYvn27dc59Ph/d3T0oikJeXp4Vg8yFXbqsgeSkbM+ePUQiEYu51NfXlzC1NAx8Pl/amm+ZRCgUArjNTloHMt3Un56epqGhAVmW2b17d8bMJiVJ4rRjO/3KPFOxAFk2J9FolIihUJ5dzAM7rhpMJ7MiI5EIzc3NOBwOTpw4kXbSXezIwyYZzGo+EhqsBjZZYMOFLDzUlB9FmtPp6uqy/EfMGLTcAqPQkc9ry17O10YfR8dIyCdJMWSRcHY1DLgQeobj22u5f9f9S2KQTdg44K1kf9ZxGud/TmPgSSKaDwA7DrJthRiGP3GsSNhN6TM0bASI6wZuuQiBRESbomXuH3FJBWTZSvDHzqEbcXIdx8i27V9xUarrOm1tbczNzVFbW2vlHOZkzZ49e6wJj5UWdgnmZPrFJYfDwaZNm9i0aZOlfz41NcXg4CDt7e0ADA0NUVRURHZ29k03qL1d0F4/MtlUM2ULh4aGANY9nZYMSZI46C7jybkuIlocBxLhcATJJiMkiVOFe1OOw2RFmveNOa2ymuvFMAwQOk5hwELxxyZcqDqUOQuJxWIWGSi5yb9SnHt16UvoDl8hpEdImFvrOBbikACiRGjY9hzHC48su32pcxsPl76DqPYoT/sfZzDahmpEF/yI7Ik4pC/EzAWzSABBBJkImiHhkhPFNsUI0hH4Ih65mKjWzXTsIpKwU+S8hzL3K5asywBmZmZobGxkx44d7NyZmL6VZdmarDHlQyYnJ608xe12W/EnJycHWZZX1WDLzs4mOzubHTt2oCiKlQO1traiKAoDAwPE4/GMmyuni0gkknFDw181ZDIGRSIRS+bIfDZmAua16pVdyEJC1TUMRUNR4rjdbmJoyBhk2xLPZTP2mASAnp4ehoaGqKioWJU0xFjUj2qoFNtzmNeDKLqCbkjIkj3RvgqFOX/+PA6Hg+LiYoqLi8nPz1/x3np58Wnq5hoZifWDEMjYAB1ZxLAvaPUP5LXSKnZzt/HSJbUSu+Tg/sLXciLvJfSFW7k09z1C2iwaMUBHCDvZtgIMfYKrU7SJWCKYR6Bg4MIp5y3IjIS4Evx3MIJMxZ4krk8hcFDiegm7vO/CJl1lHuu6TktLC6FQiNraWivXczgcS4hAPp+P4QU54OzsbEtG1uPxWDEo+XddCcvFN1MeyZSp1XX9uvJINwKmj9FqjbFfLNgwBW3I3KibmbD4fD4OHz5MR0dHBo7uKmyyTJV3O68sqbEMlrZvL2fv3r1LWJGqqnLlyhVGR0dXHbien24EIN+WTUiLohpaYqwD8NoTAcEczSovL7f03nw+Hw0NDQghLDOTwsJCbDYbFTkVPDt9Fr8yAgscyUSAlciSvITVEKPZ/fza/reueEPk28u4r/Ct3FPwJp6b/gK9kfOEtRkEYRL2KA6cC0HHMOIIQggETilvYbFoENNn6Qo8zv7sNzAS/i4htQ+3vIXN7ocpct15zfOyUhBLhhCCvLw88vLy2LNnj6VDNTU1xfDwMLIsWwEtLy/PCmjpLuyWC2qdnZ1Eo1FeeOGFtDXfMonb47brg1kAVFV13QXtQCBAQ0ODNTaZbKSwXkiSRJZu4/8ceRPNswPU9XWgz0d4XcW9lBZeLZonsyLNhlq6TAATuqFzYbYZm5BQjKumIQA2oVGRu4tcVyJJ3L17d4reW09PD06n0yosJSdV9xTexX9NfA9ZxFENAHmhcSdhU+3E7TGmCyeu+VAudx9hu+swIW2OczNfYiTaTESbQyK6YPDmxCmZi9UgwoiDsGFfiE2y4SKuz3Il+O+MR/6L6fg5DEPDJnnZ4nk92z1vXhj/XQq/309TUxN79uxh+/bty77HdHIuLi62Eg3z3PT29uJ2u60YlJ2dvaqFHYDb7WbLli1s2bIFTdPo7+9nbGyMnp4eIpFIWppvmYRZ0L4dg9aGTDb1zYb+5cuXOXDgACMjI5ZeYyYgSRLlch4f3PVq/q33DH3zE0hC4o6S/bx71/3k2N3WcZisSFOrtqSkhP3796/qmaijYRBd0LVPSJzpGMSJsMtVwtFN+2ATKffZ2NgYnZ2deL1eKwYlS2Scyq/i+ZlnGY2NYhMKhkg4gxhGwmjaKTu5rLcyEOllh2d5ozchJCpzX8Gh7LvxxQeon/sG/ng/MT2AIOERIGHDsRCHDOZJ5F0O5IXikkPKIa7P0RX4NJqe0NQGENgocb2EfTkfQBKpqbqmaTQ3NxONRqmtrV2xcLPchEfywi4nJ8cqLnk8Hiv/SbfBZhYIdu/ezfz8PJcuXSIUCjE0NIQkSSnySDeDMXQ7B1o7kiVHMhGDkhv6tbW1nDt3LqMj2ZIksd9Vyt3FB3h6vBVFVbDZ7AjJYJunkEe2JqY/k1mR8XicpqYmbDbbqhpqJso9xVyYqyecZEKvGEEQdk6WHOJI6REr1vl8Pvr6+mhtbSUvLy+lyW9im3sTryt7kP8Y+yaaoSekRyRjgXFpICRBmCD/MfYV/mDHh7GJ5ZfsLjmLVxa/B198kIlYL+3BHxDSplD0MAIVMJCwL4pDBhJOxEKByk42cX2ajrmPkdC6TWAm3oA//gKHc/83krBhGCph9TIzM1Ncbouyb++hFUlapnzIzp072blzJ6qqWmvUy5cvo2ma1eQvKCjA4XCsah1mt9tT5JGef/55PB4Po6OjVuwvLCxcEvtvFAzDuF3QzgAyFYPMhn5ZWRl5eXlWYy0TMK/P/d4ytroL6J4fw2PY8Hq8qEInrMQ4XbiXYme21UyDxDXS2tpKIBBYdUMNIM/uRQJCxjRCaNjlBe8PwCk8nDxaTbbktvxH2traUFXVug+Ki4tTpmhtko13bn8jf9/7z4T0uYRciBRHFpolF6Kj8fOpH6IbGvcXvnLZ48qSszmSfZq9WcfpCTfgi/UzEDmDYkRQjdiC9JGOjAuHlJjKMwgAIC/ENSEENrJQ9XEGQ19GEnYk4UQ34oxGvk9UG+No3l+hGfP4wj9iePIchtvD4b1vX5EZndzE37dvH5FIxKoFDQ4OYrfbrdfz8vKsJn+6DbZkeaSWlhYrh+/o6EBRFGuCraCg4IYTHU3SyK9qU39DFbQzsZiLRqM0NDQAcMcdd1gGaJmEJEmoqkp/fz9XrlxZVo/JMAxisRitra3WaO1qL7IZJSHf4bY5ccvOhR47BLQQs0pgyfsX672ZSVVPTw8tLS2WNMlbit/I13xfYkaNAInxErdwomrzOGxR5kQP3xn/F+7MfxWbXOUrnwchc2fBu9gSPsZApI6oNs280oJNOBbCK+hGEAwDWWSZzblE0BIu5pRGWmbq0FEQyES0UWbjDezSf5utnjeknEtzO1VVaWpqQlVVampq0nYnTtahMkfiTFZpZ2cnubm5VnHJ1MZebVDzer3k5uayY8cOa//X03zLJMLh8O3F3DpgMmXXGy8mJiZobm5mx44d7Nmzh4GBASuZyQTM61FXVfReP4diuVSdun9F88eenh5GRkZW3VADmFbmGItOkW3LQiAS+tkYOISNmBGnNzzMJtdVc5/l9N58Pl9KUlVcXExF4TH6svtpDDy3cH8vTHboNlwOUAlzae4JvDY7x7PvwiUvnwgIIfDa8nhJ0e9zJfQcg5F6oto0YfUysrAnxaFEQ8EuslK2lYSdgHKWqCojL8iOKHqA/uCXkbCxLetNAETUXkJKG7KURXR2N+2t3Rw6dIhNmzaldR6FEHi9XrxebwqzyOfz0dnZia7rKczJ5IUdpMcayMrKwuPxUFVVlbbmWyYRDodxOp2/kqNumUImmEmmnuDk5KTl5TE+Pp7xGKTrOruMXB6e24qn9CgH9u5bYhBpLuQmJydpb29n7969bNu2bdWFhUuz7QmjRclNVI+bVrLICAwU632L7zNTIsPn8zE4OIgkSVZhqbCwkFcWv5x/H/smcT2RT+kLnhsu2YlTlonpAX7u/xYPSr/GZufK7FKn5Gar6wAljg/RFXqa/vAlVH2eqNZv5UOGYVjFaoe0OA7pRNQWbMKDTWSTWERGmYj+jGz7PrZ4HmEudpap6H8TVUcIz+aDdC81Na9N+35Ld2FXUFBAbm4uNpvNyn/SLS4JITh69GiKPFJ/fz/t7e1pm9uuB7dzoPVDlmXi8fj133gNBINB6uvrycrK4tSpU9bzRtO0jE0OSZKEoes8oO9AVueZzDfQbFCRV84DZcfIt2elsCIDgQBNTU0UFxevWX5yIjaBBAtK++b1ayCjsdmdB6SSafbu3WvdZz6fjytXrlgG4UVFReTl5XEqv4bzsy8wGhsBEVmQEEjsxyW5cAkbM8oIZ/w/5K6CV+KQlm9eCSEocZZT4ixnT1YVbcGfMhiuRzM8qPpoghVpLPgOGDEAa5LW3F4mgmrEcUnFVjNfN+JMx84zFXsOl5TFUPDviCjD6LpG/qEiPLnvA9KbOrbZbEv0+X0+H5OTk3R3dy/o3uZbTf7VNNjMeLJlyxZycnKIx+MWezuZNW8WmNJdO64Guq4TjUZvF7TXiExJjixu6G/bto2JiYkbsg6LhiO8NLyZWTHHvE1hVg0jhGB/9mZ+Z9dLU8wf4/E4jY2NyLLMiRMn1nQN7nCXIIkYiq6CkBCAgYFGjBJXKXn2xPPPJNMcOHCAYDCIz+ezfDBycnKs4rbX62WLq4y3bH49j49+HRlAJKTSxIKJrltyAxrPz/yco9kVFDlWNl11Sh4Oee8E753MKy+jJfAjBqMNYEgYxlRiSsRIKG0bhgpCYBdX164CsBFJtOAWfEMQoBkxZuMN+KNPMxb6ZyLqCMJjIEs2ekMvsFX8IcXu11n7UfUZwsrzGIaKx16LXU5INrndbrZt25Yyae/z+ejv77d80swY5Ha7V9Vgg8SE6rZt2yxyhd/vZ2JiYok8UjqyVKuFpmnEYrHbDO1bjUywk2ZnZ2loaKCwsJDDhw8n9IaiUau4k6mLRwjB0NCQxRA2tQPhKisyFArR1NSE3W5fExMAYJu7lOb5K2i6gkI0IQuCDc3Q2e6+tovz4sVLOBzG5/Ph8/mYuTzDjvwdhLKmcUluJENCMaYQsrrAkZS4HGpkMHqZt25+P2XO5RmIkOis7c46ze6s0wC0zn+TzsD3iGozGMJAJopNSDikxYsMHZk5dMOJTbraOVf1AP3Bf6PU9QpAZSz0JWZiP8dAIUuuYbrvBDbK12Uqk8wc2r9/P+Fw2Eo4+/v7cTqd1rkzg046QU3Xdex2OzabLYWZeS3Nt0wGtdvjtmuHWcxeT0HJMAx6enro6+vj6NGjltN6pvXgzOvl/PnzeL3eFc0fVVWlra2NYDBIbW3tmhb6spARC1MVDsmGTTa9WQVxQ2BbgcEMSxnK5uJlaGiI9vZ29uTsxJ87yCgDyIYdSQObM5IYVTMMYnqQJ6e+TVvgAm/Z/Ee45ZWvbVnYOeC9nwPehJlRR+C7tAf+k6iekFWSULEJOaWgnUAUCQWbyLZGaiVhR9EDDIf/k83uhxkKfoLp2E8xUDB00OIe9h79MJtK0itmL4fFzKL5+XlLOipV9zZ/Qff2+gu75GdcuppvJns7EwgGgzeFCf5ixnqZSdFolMbGRgzD4I477rCapzciBoXDYerr6zl48OAShl5yMbuvr4+hoSGOHz9OUVHRCnu8NqaVeQQSOXYP2YYbzdCRhERcV5hTA+gL/16MxRIZs7OzFjswFouRn5/Pg/mv4Eexb6IYMSRDwmNzIYsIijGHwGAseoV/G/lbanNfwksKH73m9e2Q3BzNfhVHs18FQGfge7QFvr0QhwQyCbkSG6kNOmFEQIBNXC30yrjRjTjjkZ9gJ8Zw6J8xDBVNMxBZBracNsL6JnK5OtGmG2HCygV0I4bHXolNKlnxWFda2PX29hKLxVKYk+nIIyXHn8XySNFoNMXc1mazUVBQYE3uZKrIeVt2bX3IxDrMbOiXl6dOrWaCLJAMIQQDAwMA/Paph1N+98Xmjz6fj/b2dnbv3s327dvX9IwyDIO2QA9ZshsExLREI80h2dDR6Q4NcTRn75Ltku8z0+DQ5/PR0tKCrusUFRXxQP7L+L72A3zqXOK7SQKHsOEQcVRmERg8P/t9WoLP8drSd7HDfWDJ56R8ppxLTe4bqcl9IwBdge/TGvgWMWMWAJuwY8PAxlVyjWHoyMQRyCmTaZJwoBoh/NGniannULUAmmrDbvegM81A4P9il4rIdlQCEFYuMRP5GjGtE5tURp7rDWQ7XrXknCfr8+/evTul+dje3o4QIoU5aereXmsdlhyDHA6HRfAycyxT+98s6pk5UKbkkW4XtDOD9UzrL9fQhxu3Drt06RL7y7byhX33UTfXz1QswBZ3ARW55Uhg6boHAgEaGxspLCzk4MGDa173twZ7kESi9qJxVcJEQiKkBYjrCg7par0pWaZn165dxGIxq5Hd39+P3W6nqKiIrUWbOeQ+SHuwCcmWaNcZBtiEvOAPEkYxDD4/9FEOZFXyyuK3XXNNBpBjL+XOgndyJ+/EMAy6gt9LrMsW4pBDuJFRkMTV49WMCLLQkEXqukTCgUqE0dAXiarDCD0Lh8OZiPUEGQn+E7mOO3HIJcxF/4vJ0N9aRCYhHBS4f51C9++l3OeyLJObP4/Le5FtOwS6VsP0lDshVdvXh8vlsoiO6cgjJcefZHKFqaBgrsPa2trQNM1qrmVKHknTNKLR6K9sDrRhCtqwviBmPqT27t1LeXl5SqcPMuc+Go/HCQaD2Gy2Fc0fZ2ZmaG5uXhcTAODugiqemjpHQJsCsTAubIAkbBzLSd/JFhIFjvLycuvGGvYN0Td7maA+jx0dyaYmWE9Cwi17kLET1UKcm3mC15W9J+3POZz9RoqdhxgKv4BihMixbWIo/G00wkhG9kLHT0M3QkhCIEupBRBZeNCMELPxOnzhLxFRuxNdSEMwoz6NVHaRg0WfW1TAU4mozRhGBJftCLK0Oo0sj8fD9u3bl9G97bZ0b82g5nQ6V2RvL3eNXUvzLZNBzWyi3NavXR/WWlBSVZXm5mYCgQCnTp1K+R0ynUjNzCSKtGZ8Wc780dSqXQ8TACDfnsOerO20BS6j6PMLph6AIXBJORzOXn4UfzEWL15MaZLd/v2M24YSiynbAnNIAELCJXuQkZmIDdIwf4Y78h9M+7gPZr+OEudRRiIXUI0oObZSeoJfRTECOAyTARlDGApCyAhSG46ScKDoc4yGv4g/9mMk7OiaB01VkJ1hZqS/Y5NejV1KmElF1S5mI/9OVGvDJpWS63wdXsdL0lokCSFSRveTDU3a2tpSFnbX0r1d6Rl3Lc237u5uXC5XijzSWtnbt4tJ68N6i0nLNfRNSJKUsRik6zpjY2OEw2Fqa2tTDNWSZY4URaGzs9PSeF4Pc3aTswgDI6EXSQzVUBCGQDFgh2t7Wh4YkiRRUFBAQUEB+/fvJxQK4fP5UCdVNrOdEW8fbsmDJOJoJKbXEBIOyY2BzsW5J9npOcQuT/p+LAeyX8MmVyWj0UtohkK2XERX8PMo+jx2IwuQUI0QNgEStqVFH2QUbYrR8BcwDB1NcSJJEjbZhmYEGA79IzmOUwghE4w/w3jwL9D0GcBAEi7y3b9Boft3lo1Dmj6Opk8iS9uQ5fwlMcKMQeku7K6VY7tcLkseyWwsmObakUiE3NxcizW/nqZYKBRac9PkNhJYaw60UkPfRCZjUDgcZnZ2FofDwenTp1MIQ4vNHwcGBujv7+fo0aPr9jGRhQQC3JITpyRjoCMMmYgeTzJSWxmLDQ5NA9fJwUkqQsd4ftM4ik0hS85CiAjqQkEGIXAIJ0F1jv8c/yy/s/1jZMnp5/r7sx9mi/sEY9EGDDSy5SJa5j9FTJ/FprsBA82I4hT2BZPIpYhrfShaAF1x4nC4kCSBYdjRCOCL/hfZjkoCsacYC/7PhNSkkFC0CaJqM3H3AEWe30vZn6JeJhj7NxS1EUkU4nG+jrKyh63m4/z8PJOTk5ZcnimPVFBQYOneLm6wrRSDknMss6hnrsOGhoYQQmREHklV1dsF7QxgrcQis6Gv63pKQ9/cZybXYaOjowCUl5ezZ0+iHnNX0X7gagzSFq5H08Ni165dKfWptcAfn0tcr45s4oa2YLooLUi5xglr0ZSC9mI4nc4UqUJzmryzvZPt8S1o+VF67S1ISDhkFzai6CTkBAWAAR3BS0T1MG/e9IdpfxchBAeyX8t2951MxFoTk+1yPo2zf0Ncn0US9gXWtoZdOK3p2qtIFO+jSg9C2HE4nNZ+JSMLjSBz8bNk2/czEfprDENBEl4S3gQRpiNfwiHvJseZkEwxDIP5yKcIxb4CxsK1JuwUlr6b8vLfTakFLZZHMmtBi9dh18qB7Hb7EnPbqakpRkdHLf87Mwbl5OSsqW5oMrR/VafUNlRBey1BTNd1Ojs7GRsbo6qqaslIfSZH3YLBIHV1dciyTHl5+ZJitumk29HRsS4mgAmvzY1NUhC6sLRrJSEhCzgzfZajOfvWtF+73U552Q7u8T/AC/ozhNxjJAboZGyaDV03EJKGJAT94VZ6ww0U2DeRZ782KxwSwaXUeYRS51UTE6/NS8f8F4nrs9aosFsqRkYDUnU9jQVhlZDSTETtRhJuQEZR4gjJg2SLMBn9Bjsc/wuAsFLPePAjKNooiUWchwL3uyhwv3NN53453Vufz2cVf7KyslIMTZJHctMxE1zMzAwEAvj9/iWab2sJarf1I9ePtcSgUChEQ0MDTqeT06dPLykeZ2ohlzxGB0sNlswYZGrVrpcJYOKVxafoCLagG0nfQRggIkzFp/HaVs/wdblclJaWUjy2ib36Yfo9V9CYRSKhH2nHjqQnzJ0MoCN4np3ufRQ4NuGU0vu8QsceCh1XG38eOZuW+U8T1+eBhBFsvuMwMbUVAw1BcpNMQRIuZmI/AwM0PZEMO5wuBC5UY56Z2FOUuN9AWKljZP59C2wAQYxuwso5Cty/TZHnd5ccV1xtJ6r8HMOI4bSdxGm/M4URdT1Dk5V0b1VVXbXmm6qqFmugs7NzXZpvZvy5zdBeO8xiksm6SRcrNfRNZGoxpygKjY2N1jTQ4mK2yYqMxWI0NzcjSRInT55c93h3Ve5BCh1PMhUfSWnuI6DYubYmijmWOTIyQmXWSSK2ALPaNDY9hBCJnduEDbuwY2AQ0yO0zp+lwF5Ijq04rSI6QK59G7n2q74FblsurXOfIapPgWFgl7Ipc55gOvYUhqFZsSDBPFLx2IpR1BFUxY4sydjtNhJW3m5i2ihRrR9ZOBgL/C90I4wkPCQWcVGmI5/HIW8lx/mQ9fm6Psts+KNElWfA0BDCicfxKDmeDyCEIyVGlJeXp7BKr7WwSyf+QGpjwZRkyJQ80u0caP1YSw6kqiotLS3Mz88vaegn7zcTI/+mLq7T6WTTpk1LitnJMiMdHR3Mzs5SW1u7brKHEIKavEM8M3WRMKGF5r4ph+jgoHfHqvdnGtQNDw+zbfN2Trvv5bnYk4SUAE5bBMvMUbJjlxzYDBtRLUxr4AUqc+7GIaUvX+i1lbLXe1X/1iX/f3QGvsyc0gNAkbOCXFshE5EfoBuqpduvGbFEYy2iYsg6TqcrhXUvDEFU7cUwNKbCn8QwYkhigfEsElMjM5F/I9f5euxyYg0ZVxvxB34HwwiTsBrvJ67WE1fbyMv6n0iSZMm2ACneLENDQ9aER7LurRAibeKaee0kF8/N6ZH1yCMFAgEMw8iY8eCvKtbSVLtWQx8yuw67fPkyw8PDSJK0pHFnxh9d1xFC0N/fT19fH0eOHKGkZOWJqXRR6ixEIFB0BUQcnRi6YaAbMjly/qrWYybZxfRZ2rVjF3vkPXwzPMacNI2hKej2RFPNIGEA6ZCdqLrCQKSL8dggZc7V1bk8tiJ22u6z/n2y4C/oDf0X/ngjsnCzxX0fujbCePRHaEYMCQego+hzaDEPkjOOLC+u5SU+3zDizMd+gGHEr8YgQOBB0+eZi/63VdCOKk8Rin5pYduFnMGIEIh+DrvtKC77XUsK0KbKgVkLSvZAMq+vdElMJtFx586dlv+d3++npaUFwzBSiI7p5s+aphGPx39liUUbpqAthMBmsxGLxdLextQjisfjnD59etnRafPiWm8gM80fy8vLCQaDKa+ZpiO9vb0MDg5mhAkA0BroIqbHybGZRh4JhkBcV+gIdjOvBsmxrT55VxSF5uZmHIqL91V8mKfn/5P6+WdwL+g66pqOpscRcgDN0Pmvsb9bkBap5hXFv72qJAqg3PMqcm27GY2eIabPkWvfzWbnfbTOfYig2oPAhljoMGpGCKdUjGHMJb6xIRFX4siynHjIGQoBpQ4AVfcxGng/mj6HwA0IdCOKP/zP2OVScpyvTv3eaheB6GeJKecQwoPH8TBe97sXunhLkTwykhx0TN1bwzBSxnIVRbGKiulqvpms1Z07d6Zovq0lqN2WHFk71mqINDU1RVNTE5s3b17R6CwTCzld1+no6GBiYoKamhouXLiQYjJiLuTMhlommAAmesJ92ISMJGzoJAptdmwohsLT/ud5p+dNq96n6Tzudrt5x7Hfxq9O8t2JzzMZG8AlZYGeWCQbhopsDzITv8x/jH4Uh+SiKvdBTua9FpFmQcnEZvc9FDiOMBE7j6qHyXccINe2l7rp9xDWhrCRhcCGvmA+V+p8OcH4d9B1gaHpOB3Oq+fTkFB0P4Zh4Av93cLEydWFj24kGAG5ztdglxP+CoZhEIh+mmDk87Bgbhfiqzjtd1Lg/SRCLJ3OWI2hSSSSYJWahaV0FnaL5ZHWo/kWDoczJl/yq4rVNuB1Xaerq4vR0dFlG/rJ+11vDAqFQtTX1+PxeNi/fz89PT3Wa8msSFOrtqCggEOHDmVkMs4lO9jmzsOvjFpN74QXh0xboIPR6ASbXaWr2ufc3ByNjY2UlZWxb98+jmlHuTh3jhdm/hvViGE3nAhNIqZGkSQD2RbkSvhp+iLPkWMr4s6CX2Nf1olVf5cSZzX3Fn+amXgnBgp59gMIoGGmm5A6gGTYEUJCM2LYRBZevYYprQ5ZdmK3JYrZCSycB2zMx36AbkRSYlBiERdgNvotq6BtGAbToT8mrlwgkf47MIw4odjXAEFu1oeWHO9iVunihZ2pe2uyJRVFWbW5bbLvgsneXos80m0N7fXBXIetJgcypYdWauibyERTbWhoiM7OTg4cOMDc3FyK0W2yzJG5xgE4ceJERsa5AR4quZezM+eI64rlaYQACY0XZi+x17uy59BymJycpLW11TKXPmQconCukDP+Jwlq/QmzN8OGpNhQtDiSbGATIZ6f/grnZ77OVvdB7s5/E8XO1X0uQL7jIKcK/pqYPo1Awinno+gBQsplguplVMOwTOFs4aMoMRuOgoGUfZi5p0vejqIPouijSMKVkncKXOhGkIhah11OrMnmw3+PboQQeJGEWYyKEo5/iyzXG7HLqdIty3kgJeve5ubmWmsfU24vXf+R5OK5OT2YLI8ky3IKe/taz2WzNnB7HbY2rFVD+3oNfXOf682BTA+vUCjEqVOneOGFF6zjNO+F5ONub29nenqampqajLH2j2TvZqurlMFoD4KF72MAaCDChNUwOfb0m3eDg4N0d3dz9OhRq+D+7vjv8/WRf8UXG8VY+AzJkLHpCXklWRhozPMfYx/BKbk54L2DU3mvxy2v/tmbY99BRd4fpfxN1UPE9Elm4w2oRBLnNepls3gfkvM/CSqNCK6ux3SiSNjJdlQzE6kDlhJChJBQ9XHr35H49zDQkUTyufJgGAEise/jst+VtG2qbIspj2T6pAHk5uYSCoWsovJqzW2vJY+UnZ2dQnRcaV2frKH9q4gNU9CG1QWx+fl56uvrycvLo6qqasWHjDnGu9ZAZhgG/f39dHd3c+TIETZt2kRzc3NKMSkej9PW1sb8/DwnTpzIWEId0+MYRmLJkpogCHT0RIdulTBNM10uFzU1NdhsNqrFPbQEzhI3ojiEG0mWMeQgGBqSsCEbdjRdpSvwAsHZMPfl/gaFhYWrGsvKc+wnz7E/5W97s/+QtrmPENdnE2JNCGzCw76cPyKsnMMA4kocm2xDNn9fQ0deCEDzsR+i6fMIsqzilsCDbgSZifx7SkFbUbuYCrwD3QgikNCNAMHoF4iplyjK/iJCXL8DtlzQmZqaYnx8nCtXrgCJxdns7GzaurfJuJ7mmxnUioqKlmi+mcWo24u59SHdGJQcFw4dOsSWLVvWvc+VYDbuFEWxZI7MiYBk88f+/n4GBgYyxgQwMRIdBwxccmojS9EUhiKjq97f/Pw8DQ0NlJSUWJIpJfIm7sh/BT+Y+BIIA5vNnjhvxhygIZAxNIjqYc5N/yfxsMqdZa9ftTyGSy6g3JMqXXI4789pn/tLwuoQBhqScFDsupfyrHfSPH8Gwz6A3X51DN4wVEDHLe9G1SeJaVcsZqOJxCIuREh5gTz59QDE1QaCkc+RyD7dC/JLCjHleYLRx8l2v+u6x7+S7q0pj+T1ehkeHrZ0b1eSR1oO69V8CwaDt+PPOmFez6qqXregnU5DP3m/64lBfr+fxsZGtm7dyr59+/D7/Sk5kMlImpqaoq2tjZ07d7Jjx46MsfVVQ+NKqA+X5MAm2cAwEgxpA6JGjOb5jlUVtE0N2927d1NenigG5djyeGnhg2j6HJfmnsYpJ+4f3dAwjClAx9BlNHRm9HF+PPHPOMpc7PAcW/X3kYWDImfqdkfz/pq+4Bfxx57HQCPfUUme+lp6WgPkHczFECEMw4npaaATxSPvwylvZ1afYPlFnIyijVn/VrQ24solwJ6U89gwjAjh+HfIdv8ekrTyYnilhd3IyAgzMzNIkkRnZ6fVZEtH9zblvCQVj5LZ2+nKI91u6q8fq4kV6TT017LfxViucRcIBKwYlMyKDIfDNDY2kpeXx6FDhzJqgDyjziCEgUOyL9hYg12yoRs6F2YbeF3ZK/Ha0rv+hoaGuHLlCocPH6a0NBG7hBCczLubmtzTfGHoL5iKj+GWTXNLBcQMAiMRhySdgXALk7E+3rL5o+TaV5/zCSFwyVeboHYpm+P5f8NE9GdMxy8hDBvBsa0Y8wc5fLyY3lADmh5AJvGs0YwwkrBT5H4dAieJyZCrdpkJmI23RL6g6/PEtRYEjkXxyglGiJhybklBOxnJHkiQuOdHRkYYHBwEsJqppgfS9XRvF2MleaTe3l7a2trIzc21Pn+x+VogEECSpBSpi9tYPdKdEkmOC5WVldeUmzLjz2qn30wsbtyZzzZzHZZs/mgWvnVd5+TJkxlrqEFiSv9E/j6Gx7stPyME2LER1aM85T/LI2UPXHc/hmFw5coVRkdHqa6uTpkqKHaU8vs7PkR7oJHvT34OADtOdF1H1aLYbAEkDAxDENPDNM3/nNHoFd60+SPYxPpN4W1SFkfz/op5pY2xmUZGBmfZt+VVbNuyi4BSRM/cn6AZAYQhJWSfEBS6HsFt201Y3keAn2MYulUXSjQbdFy2q8oBmu5f/rxgrPiaiWRvFsMwLNNzIYR1PZoxKCsra1l5pJWwWB7JzLHMWpAQImUdllyH+1WXHMmsxeY6ka6G9tjYGOfPn2fbtm0cP378ugu/tSZSuq7T2tpKf38/tbW1bNqUMAEzRwvM5Kmuro5YLMbJkyczeiHtzdqBXZKJG4nCtWEY6IaKoscodhSSb1/dWFMgEODChQvk5uamnLcS51buK3wdEjIxI0zcmAdDQRIyTsmNTbbjtLmRJRsTtg4u97fzi1/8gkuXLjEwMEAoFFrT98t1HKaq4DPszPpNSl2voDzrbVQVfJpC5ykIV6GrINvURIHdMNCNOAgodCVGRhRthARTa/FlLKPoQ6nfPfovC4wAN0K4FqRM7MTVRqLK06s+djPo7N69m7KyMmRZZufOnWiaRmtrKxcuXODy5ctMTEwQjUaJx+OoqppiVJPO/nft2kVtbS133nknW7dutZL15557jvb2dsbHx1EUhXA4jGEYqx6rnJ6e5m1vexs5OTnk5eXxrne9a8kEwmJEo1Eee+wxaxzv0UcfZWJiYsnxL/7vG9/4Rsp7nnnmGaqqqnA6nezZs4cvf/nLqzr2TCNdU0hN02hubqa/v58TJ05cs5gN61vIBYNBXnjhBWw2GydPnrQkIMwYpGkaiqLQ3t7O6OgotbW1GS1mA+Tb8xaKr8aS1wrseava19TUFJcuXWL79u1L9L8PemvY5TmCaihEtCAxfQ5QEULGJXtw2F04ZBcGBk2hn/H0M0/R2NjIyMjIqiZ7FiPLtpOags9xLP//cSj3f1Fd8Bn2Zf0Pmhs70Odeik12ohNEN+JoRgTNCOOWd5LnvHtBHmC55NggIeN09dkUif8Y0IHkkd2EnEEk/v1VH7c5Lpibm4umaRw8eJDNmzczOztLXV0ddXV19Pb24vf7icfjKTEoHZiabwcPHuTOO++kqqqK7OxsxsbGOHv2LBcuXKCnp4fZ2Vl0XV9TMel2/LmKZPmq68WL+fl5zp07h91u59SpU9dlrq5n3HZwcJD6+nr279/P/v37U0gCyQa0g4ODtLW1cfjw4SVySOuGYSwws0FGSpjVJt13JosoHQwPD9Pc3MyhQ4esYnYyavNeSpYth5geIa5HUY0AkFgcuWxu7JIdCTuqrvLTvn+jtbWViYmJNfu/mHDJJRzM/TCni7/N6aJvUxr7IN3NcQ7ur2RH7geRhAONeVR9Do0ANpHLtuwPIITAIe8CBIZx9TwkFnEaTtvV4pCqDWCgAosXnXYMI4amr65B6XA4sNvtzM/Pc+jQIaqrq8nKymJ0dJTz58/T3NzMwMAAs7OzxGIxFEWxcufrQQhhGdtWVlZy9913s3fvXgzDoLOzk2effZampiaGh4et6ZRgMHg7B1on0lmHGYZBX18fDQ0NHDhwIC1ps7XGIEVRqK+vZ2pqitOnT1uFzOR1mFlMmp6e5uLFi2zZsoUjR45ktJgNMBWfRjcMnJITj+zCLbuwCRuykFENjRll7rr7MAtJPT09VFVVWcXsZMjCxl35DyELmagWQhcaSAkJEiEk7JILSZdAkwgrAZ7q/2ZKk3E9sElZbPE8woGsPyfS/Wrk0HFqqk+Q497Hjuw/xyGXoBNFJ4JNymOb94PkOGqwy5tx2Q5jGDErDiXWbWFkKReP/VTiA6z12tJ8EljiZ3I9qKrKyMgIu3fv5v7777eeUd3d3bzwwgu0t7czMjJCKBRadQ5kyiPt3buXU6dOcerUKUpKSpidneXSpUucPXuWzs7OhBeDqhIIBCzCyWpwOwalIp0pkXg8zqVLl/D7/Zw+ffq63glmLFhuHXM9zMzMcO7cOQoKCqiurraKiGZBO1liJBwOc+HCBZxOJzU1NRktZpsYiAxhEzJZsgePzYVX9uCyOTGAlkDHdbfXNI2WlhYmJyc5ceLEshI5spA5mlPN0exTgIEuVGSbjGyLwoJQkNBtGKrA0GAi2keT75k1nd/lIIQgNFXAaNtmju74NbZt2QVAtr2Cfbn/RKHzARzSJry2o2z3fpht3vcDkOt6DTapEN0IohtRdCOGbswjCTf57rdY+3fYji8YXyZP+SSK4w57+iSFSCTC5cuXKSsr47777uPuu+9m27ZthMNhWlpauHjxIl1dXVYtaDU5EFwtnh85coS77rqLo0eP4nK5GBwc5Nlnn+XSpUv09fURCAQsDf9f1XXYhmFop2OIZGoXDQ0Ncfz48bQLN2tJpOLxOA0NDWiaxunTp1M6rqZW1+zsLE1NTeTn52ecCQBQ5izhjvwanp2+QFgLIIsYBjqyBLIIMxobZatra1r78vv9lvP4covNE3kvZZfnEJ3BeiZi3QxELuIQCRkPE7KwoQuVPRXbCEenmJ4fZcwf4sqVK7jdboqKiiguLiYvLy/tB7pLLqHc++spfxsdHeVyh8r2I28lIH07yZBAkOe4h2L3GwCwy9sAI6UTl4CGQ9qRss+Y8sJSpruwYRgqMeUibsf1O5rLwZSZSdboM6+NqakphoaGLEMTs2NnJjyrYQ2spPk2ODjIM888wyc+8QkAuru7KS4uTruY8La3vY2xsTF+9rOfoSgK73znO3nPe97D17/+9RW3ef/7388Pf/hDvvWtb5Gbm8vv//7v8/rXv57nn38+5X1f+tKXeOUrr2r2mXp4AH19fbz61a/md3/3d/na177Gk08+ybvf/W42bdrEAw+s7bfIBK6XSJlSGZIkcccdd6SVrKx1IWfKHG3fvp29e/em/KamZmk0GqWlpQXI7GhtMu7Ir+b5mQtE9RgOScYghkYcSRJs85SkzXgYGRmhs7OTQ4cOWc3BZNiEjUfLfpfW4HkuhxqZU4YIqCM4patxSAgJm2THkBT2V5UzNNtCi78BLheS7ym1YtBqXeuFkMl3VAILiXL9Jex2O1UH3sWcuo2x0BeJ65MIJHKd97LN+0dIwokknLhsx4golzCwW9JJifF/D1mOO6zPMAhjYFgjttZnI9CNaycPK8E0TKqoqLAW+qvRvV0Na2CxuW2y5tt3vvMdzpw5Q15eHhMTE8su0pfD7fizFNdrqo2NjVkGQ7t27UrrOl/LlJrpTzI+Pk5NTQ35+fnWa+ZCzixmd3V1ZXy0Nhk2ycZB7x6aAwmpLwQYxFENBQnBQe/KjD4Tpmnd0NAQVVVVKd8nGfn2Yt6++YOcnfkR3eEWDEPBINHcFwiEJJCQEIaO4plDVee4MHYGtd9gs72CTUXbKCoqWrP8jiycDA0n2JvHjh1bkK/bhEsuxx/7EXFtHJdtF0Wuh3DKiWZqjvPVzES+iqr7E8xHJHQjihB28l1X8ytZKkMgw5KitgrCjiStTirP5/PR3NzM4cOHLS3RvLw89u7da+neTk1NMTw8jCzLKczJlcxtV4LNZrOMK/ft22fJI01OTnL58mU++tGP0tfXx5UrV4jH42nrTt6OQVeRzjrMJG1MT0+vWAxZDmuJQabMkdvt5tSpUylsNCGE1dQ3DIPh4WF6eno4dOjQEl3bTKHEWYgsJDRDw7agMW2goxkKNmGn0LF8TDGh6zptbW2WUe61Cg+Hs2tRjTjPTn+foDaHjJJoqkmeRDNv4Z6J61GmtQEu9PyYsDxOrruEfbl3UVa8dc3eBbFYzDrvR48etda2ec67yHGcIKQkfEey7EeQxVWfjdKs/8Hw/GOout+aupWEi9Ks/4UsJchekvDitN25oOGvWzkThEE4cNrvTfs4Td1kU2IPuK7ubbIH0mrXYSvJI3V3d3Px4kX+7d/+DYCuri6rsJ4ObsegBNKVHDGnPHNycq45oZ8M8/fVNG1VDQdzQnr//v1s3759yT7NAqUkSVY+vG3bNnbv3p3Zpn4S7GLBR2MZ2UXHdRjSpg+KYRicOHHiujHi5UVvJqqH6Qm3EtMjOISCEAKn5EFK8LQxdAPFiNEyepbhoSs4cjRKs3ZyuOQlONfgsQQwMDBAT08PFRUVKV4tAB77fnbYP7LsdjapmK05/8xk6O+IqI2Ajst2gCLPH+KyXTX0znK+mUj8++j6DIbhINFgU5CkQjyON6R1jKFQiLq6OkpLS9m3b19i4mWZCQ+fz8fg4CBdXV3k5uZaMcjtdlsTJOn6jyTLI8ViMWsdNjg4yOc//3nq6uqoqalhbm4u7WfziyX+CCNT7ZR1QtM0hoeH6evr4/Tp00teVxSFpqYmIpEIlZWVq2JCP/vssxw4cCBtXetAIEB9fT25ubkpD3PAYoeMj48Tj8eXLTZlEpqh8b3xH/Pk9BMLo1wCCRmEgUfy8KHdHyLffu0kanR0lI6ODovBdz2Mx3r5j9GPJT5JXH1QqEYcm9DJlmVi+vyCpreNg1mvZLf6IFNTidFQXdcpLCykuLiYoqKiVUmTmEHs+PHjFBYWEla7mY39AsOIk+2oIdtebRWvVd1P/+wb0PTZpHG3GEIINnn/imznK65+p9mXoOmTC8zsBBKXfhSv67fI8Xwg7WM0t+3p6WFkZITq6uprXo+m7q3P52NmZga73b7sSFy6QW0xJiYm+PSnP83f//3fk52djdfr5dlnn2X37t3X3K6jo4NDhw5x8eJFampqAHjiiSd41atexfDw8LLXytzcHMXFxXz961/nDW9IBP3Ozk4OHjzIuXPnOHUqwcIQQvDd736XRx55ZNnP/tCHPsQPf/hDWltbrb+9+c1vZnZ2lieeeGLV5yATiMfjtLS04HA42LdvqeHq9PQ0jY2NlJSUrEobNhwO8+yzz6YdoA3DYGBgwBpHXfw7GIbBs88+i81mIxwOk5+fvyROZRrnZur4xuh3UYxZWBgpFUJCEoKXF76ch0sfvub3MRs/x48fX5KcrISu4Av82PdpZBwpiZtixHBJ4BBxVCMOgCzs7BcPkT19FL/fbxU/iouLKSgoSPvcRKNR6urqyM7O5siRI9ZvbBgqMX0cWWRhl1LjbVTtZHj+99D0GazxWmGjJOtPyHP9mvW+UOw7zIb+HIGLZOM3CON2vJZ87/9J6xhNmCPLlZWVKxbnzM8wF3ZTU1PMzc0ta2iymoXd4v1fuHCBD33oQwwMDDAzM8Ojjz7KN7/5zWtudzv+pMLUfv3FL37B0aNHl9wnJrNvcHCQY8eOrWoSo7+/n+npaaqqqtJ6v7noicViVFVVpRRnzevp7NmzFBcXEwwGkSSJysrKGzpqPRwZ4+/7Pk9ICyKJMCbDTxKCzc7NvLf8vSvmQrqu097ezszMzKrzxxdmvssLs9/FtmhEXjGieCUZg+ACe9xAxsH2+VchJjbj8XisHOh6+vMmTObrwMAAFRUV17yvFyOqdjEZ/D9EtQ7AwCaVUOR5n2WClNi/jm/+zahaB+AAZEABVNyO16wqBk1MTNDa2sqRI0eu28AydW/NAnckEll2YZdug20xYrEY3/zmN/ngBz+Ix+MhFovxpS99yYoRK+F2DEqFqqrMz8/z3HPPLZuvJDf0KysrV9VAv3TpEqWlpWzbtu36b+aqzNGWLVuWFAfNnKKvr4+SkhJisRjz8/NUVlbeUEM+wzD4297P0h3qRxYgRBSDxARtlpzF27e8jeM5x5fd1lzDappGRUVF2udOMzRmlSmenX6c/kgT9kVeG4oRJUcWaEYIc0pD1l2UjL6SUscBKwala25oSiuYki2rvRdVfZr52PeJaz3Iophc10M45J2p79H6mQq8C12fXJAMkEDYyHG/H6/rHWl9zszMDI2NjezZsyetayrZA8nvT/ifmPFnLfJIi9HX18dHP/pRfvjDHwKwdetWmpqarsuWvB2DUhGLxRgcHGRyctI6H8lYS0MfEvfuT37yE+6777608hTDMOjq6mJkZCSFMGJC13UuXLhANBq1GijDw8McPnx4WcJOJnFxtokvDH4dWcjIkoRBDMOIo2NQk1vNb2x5W0KabRHM+O3xeFa9ZpyMjeBXxjnj/xJhbS7FS80wDDQieGUNzYjDghSITfVyMPjrbCtMxKF0z3tPTw/Dw8PrjueqPoVhqNik0mWvE0XtYD7ySWLqRUDgtJ0kx/NH15Q8MhEMBqmrq2Pz5s3s2bMn7dhq5kDT09M4nc51ySMlQ9d1vv3tb/PRj36UWCzG9PQ073//+/n4xz9+ze1eTPHnl0JyJBgMcu7cOYQQnDp1atWyHqthBkxOTnL+/Hm2bNnC8ePHlxSzVVVFCEE8Hsfj8TA4OMj58+fp6emxHI4zCVnIBPUZZCHjFE6ckhO7ZMOGjYge4ezM2RW3NZM+k8GXTjEboNSxk82uveioaIaCbuioRhwDFYeIENMDCGQkbOiGRlvwB/g9TRw+fJh77rnHWgAPDAzwi1/8gosXL9Lf308wGFzx/BiGQXd3N319fVRXV1sPD49tD5uz3sUW73vJcdSmMLFtUiFbsj+VGLcVCgYxZCmbYs8fpxSzATyO1yyMl6jW50EMkHE5Ut97PZjHmk4xG67q3lZVVXHfffdZbP7e3l7Onz9PW1sbIyMjBINB4vH4qkdSSktLecMb3kBOTg4+n4/HH3982VHqxTh37hx5eXkpScPLXvYyJEni/Pnzy25TV1eHoii87GUvs/524MABtm/fzrlz51Le+9hjj1FUVMSJEyf44he/mPLbnzt3LmUfAA888MCSfdxMrMROMgyDwcFB6urq2LNnT0qhMx3IpmROGr+nyeDp6+ujtrZ2yT1rsiK3bdtGIBBAlmWmpqaor6+nv79/zfI/18Pp/Gp2ZZUgC4FN2HBIDhxSolH1c//PGY+NL7udWUgy5VDSLWYD7PJU4ZUL0Igv6NgaqEYcCQWJwML/25BImMV26P9FwT6d++67j8OHDyNJEl1dXTzzzDM0NDQwPDxMNBpd8fNCoRAXL160GgTJv7EQNlzy1iXFbACX7QDluV+n0PMeshz3kut6lG05X0gpZgO4HQ9il/cBMQwjjGFEMQgjRA5e92+lfV4g0fjr7u6+JtP06rELS/P2xIkT3HvvvZbJbXt7O+fPn6ezs5OxsTEikciqx3KFEJw8eZKTJ0/y5je/mbGxMf7kT/7kutvdjj+puBY7yRy7Hx8ft8aeV4PVyB6Z+ZYsy0vkTEyJEZfLxaFDh5ieniYWixEKhWhvb2doaOia99h6sNW9iT/d9Xvk2CWEWDCnlWzIyIzHx/nqyFeX3U5RFBoaGggGg2vyODngvRObsKOQGKVPxCEFGQWdeQCkhXxIQ2Eg9wdU3rXfYtA0NTVx5swZWlpaLImw5ZA8gbiYEZ8OXLb9bMv9CjvyvkN57r+zM+97KcVsSDQhC7z/gN12mARLOwzCwGW/n9ys/5H2Z42Pj9Pa2sqxY8fSmsYwdW/379/PnXfeyR133EFpaSlzc3M0NDRQV1dHd3c3U1NTa8qBnE4nb3/723E4HDzxxBM8++yz3HHHHdfd7nYMWgqbzbZsvjI9Pc25c+fIyclZ0zTYamJQsszRYmkyMwZt2bKFQ4cO4ff7mZ6eRtd1+vv7GR0dXfEeWy+EEPzO9rdxyLsHRAgDBUGiqRbVI/zr8L/SFmhbsl0kEuHixYvIsrxqGQJZyBQ6SjmW8xIEIrEWWzCgU404dhFFNUIIJARSwrxbjjFd/iSlm4uYm5vjwoULPPfcc3R2djI1NbXi7xAIBLh48SLFxcVWDrVa2KQCCty/QZn3YxRn/cGSYjaATd5Bcc43yXb/IW7HK/A4f42i7C+mXcyenp6moaGBvXv3pt0gMT2Qjh49yr333ktVVRVer9eSMG1qalqzPBLAzp07uffeeykvL8fv9/P5z38+rdH/2zEoFSsZ05rPx7a2No4fP75qBrRZJEwnBqmqSn19PT6fj1OnTqUUs5N9iyoqKti7dy9+v5+hoSFkWbZM1dcrQXYtVOUeoTr3GJqhohmz6EYYAxVJaDTOX+JzQ59DM1K/5/z8PBcuXCA/P39JbSsdlDi3cNBbnYhDQqAl1VJUYjhEBM1QkLAhSzKykNHtYYbyfsjExATPPfcc586do7u7e4mhrwmTMGquF9fbnLRJRdjlshWvE7vtIIXZ/0JZ3i8oy3uGwux/TquYHQgEuHTpElu3bk27mA3g8XjYvn07VVVV3H///dazzZRHamtrY3h42KoFrVYeqba2lvLycj784Q/T3d3Nr//6r193uxdT/NkwkiOwfMIzOTlJc3PzupjQ6SRSy5k/Ln5dURQ6OjqsUbucnBzi8bjFvh0YGMBut1NcXExxcTH5+flrSggWoz/Snxjrl5LlMhKyJ0ORoWW3MceFp6amqKmpWZWuoBCCV5f8AT/1fY7BSCsacWRho8yxjVnlCgL5qgbsQjGpNfADDmU/kCJov2fPHqLRqMUM7Onpwel0WowB8/yYQczn81FTU7OqBafbfpQded8ipnWiGxFctgNIYmkS4XW/i5h6kbjaBIZCQsJAItv9XhxJRgHXg/lQnZiYoKamZtVaRabubVFREYZhEA6HrfPT29uL2+1ediTueqwB05DN4XDwkpe8JK1jGR8fX1IYsdlsFBQUMD6+fIFyfHwch8ORMjYCiaJ68jYf+9jHeMlLXoLH4+GnP/0pv/d7v0cwGOR973uftZ/FC+HS0lLm5+eJRCKWVvTNhs1mS9FjNguyk5OTVFdXr6oga8JMHHRdv+ZvmCxzdOrUqZRzkJxEDQ0N0dvby5EjRygrK7PuMXOs0mQGFhcXk5ubm5HpkagWpS/ciyQS+rXWd0NGQ6Mt0EaZM3XMV1VVmpubicVi1NbWrpq9aZccvLbsj/nR5D8yq0wkHKmxUWgvIKyNp8QhybBhoNER/Cnb3JWWYYZplurz+RgbG6OzsxOv12vFINMx2iysbN26dU2jgna5jCLPe6/5Hkl4KMz+AsHo54jEf4RhRHHZ7yTb9V7s8rWnKZLR19dHf38/VVVVa0r4FhuazM3NMTU1xdjYGJcvXyYnJ8eKQVlZWWmzt0OhEJs2bbJGfq+H2/FneSyWHAkGg9TX15OVlWWZEa1ln+kkxlNTUzQ2NrJt2zZrhNJEsvnjzMwMXV1d1mit+RwbHx+nq6uL7OxsKwalywxMB2E9QFQLY8N2dWpDgG7o9IR7mIxNUuK8ek2ZJtimnmU6o8mLkWcv4ZXF7+WnU58npoeBRAHbK9tRFrxGTEiGjGHo9EbPUFv6NkpLS617zOfz0dfXR2trK3l5eVYMysrKsp4zs7Oz1NbWrlmuJKGnvf2a77HJmynK/ncUrRlNn8Am715V/BkdHaWzs5Pjx49fV7d0JZgLu+3bt6NpmiWPZJrbJssjuVyulPznejEoJydn2Qmr5XA7BqXCbOpD4vltjqOb49LLjd2nC1Om6Fow1y1jY2PL5lvJerWxWIzu7m5ycnI4fPgw0WiUyclJBgcHaW9vt+6x4uLiNd9PyyHHns3JgiN0R5oSxJ4U4zGDn0z9hMPZh633BwIBGhoaKCoq4sCBA2teE+50V1CT+xB1cz9EJTGZJhDYhb4gp5i0X0MmpgdQikap2HpXioF0R0cHiqJQUFBgxSCn02nJd6wkS5lpyFIh2e53r3q7qakpmpubOXDgQNokrcVYvE6NxWJL5JHM+JOXl5e2PFIwGMTj8ZCVlcX999+f1rHcjkFLsbhmoygKzc3NhEKhNZEaTaQTg8wJBZfLtUTmaLH5IySeh0II7rzzTuLxuPUca21tte6x4uLijMpBykLm3dvfghiK0RSox1igGEpCQjd0OoIdNMw3UJObKFKa94wpzbOee7sm99WMRi8zFG1HXyiaSxjIgoQUm+UPJGEYGvNimD3HN5HFceseq6+vR5KklClaSZJobW0lEAhQW1t7U689SaR/PZlrRTNOrhWyLFvXRvI6NbkWlDxFmw57W9M0IpEIXq83LVIjvLjiz4YpaJtdOXMhZ7KLe3t7OXr06Lo00a7XlTNZkVNTU8tqwum6TjQatVxrT5w4YRVnHA4HmzdvZvPmzVbSMDk5SWtrK7quWzfsYjfS1SDPlsdUbCrlb4ZhIAmJ3GWMIVVVpaWlhWg0mnKsq4FHzuGRsg8yq0wQVKfJs5fRMPdN5pTuJcFQIAiqV11hNUMhqI7ikLy4XYVs27aNbdu2oWma5Vhvnp+CggJLKH+tQSxh1nTomu+RRDZF2V8iqjxJTKlDCDduxwOrLmabTYJMBFwhBFlZWWRlZbFjxw5UVbVG4kzd2+SROIfDYQWzxUEtHA5bSfuHP/xh/t//+3/X/OyOjusbR6wHf/Znf2b9f2VlJaFQiL/5m7+xAtlGhc1ms1jOsViMhoYGdF3n9OnTa/69k7XbViqomONLOTk5HD16NOV9ZhKlaRpdXV1MTU2luFK7XC7rHku+hszRYPOhuRrpjfUiGo3S2NiI3W6ntrZ2TYUkgGLHNn59y18zGrtMVAtS7NjOL/yfJKSNpWhRCyHQDYOg6rP+NhPvJaCOkO3YzM6du9m5c6flGG1qmkmSRE5ODtPT0+zatWtdCUo6kKUCcj0fJtfz4TVtb0q3rLZJuRKEEJYmm9mANM9Psu6t+Z5rLezC4TBZWVm34886kcxOykRDH67f1DenUC5fvsyhQ4eWGN2aMUjXdUZGRrhy5UqKFn7yc8xs8k9OTtLX12c1sVfrr7Ec5tX5hA79ouHChA69zrw6bxW0zUJSYWFhWqZ118KerBq2uQ/RF25CMWJsde3nv8f/FLGIZJQwz4WwNgNAVJtjKHKGmBSgaNsB9uw5STQas0gQpv+IWQyrrq7OaPFtJQghcNiWl0a4FkzNflMSLhNYbmFnnp+enh48Ho+1sLuW7q3JaPJ6vbdj0Dpg5gjm/b7ehn7yfq8Vg5Jljk6fPr1kMsSMQZDQTm5ubk5hyNntdrKzs9m9e3dKk//KlSt4PB5KSkooLi62mtjrwVBkCElIKca0iRxEZzAyaP3N9C7asWMHO3bsWNfnCiG4s+CNHPTeSV+kEYBi+1Z+4vsYyxlTCwQRbRbd0BiNn2dYOgulBuXlp8hTq5iammZkZISOjg7cbjeRSOSmFbPXiuU0+zMBp9O5rO5tsgdSfn4+BQUF15RHCoVCt9dhGUByLchs6Hs8njU39E1cLwaZzP/Nmzezf//+lN82OQeSJIlIJEJjYyNut9ta43g8HstDYjGRJjs724pBWVlZ677HJCExFhtGILAlN9UXNP6b55upya25rnfRamGXnLyu7E8ZiDQzHO3ELpx4ZAcvzPwri+OQQGCgE9XmkW0w5PoOk8XNOEpyKBN3Y5st5cqVK0QiEWttUVFRcUsJJdfCcpr9mYAQAq/Xi9frtaZnzSZ/Z2cnuq4vqQUttw7TNI1oNPormwNtmII2XA02iqLQ2trK/Pw8J0+eXLfJ0LWCmFm0MgxjifmjyUian5+nubnZ0lVdqSi0mH07Pz+fwsrJz8+npKSEoqKiVd2wd+bfSXe4G9VQkVlgTxgqkpA4lXdq2e9jt9upqalZV/AHyLOXkmdPdFDy7VsSWpHLmMDl2xML4K7gf9My91XiCyZnpc5KTuV/gCxbCbIspxh2zM7O0tbWRiwWQ9d1WltbrQZAJgL+YgjhwO14ELfjwVVvaxiGpcFZU1NzQwKuzWajtLTUYnUFAgGmpqaYmJjgypUreL1eK6CZpndmQAuFQtY5++M//mN+8zd/85qftWvXLsrKypicnEz5u2kmt1KyWFZWRjweZ3Z2NqU7NzExcc0E8+TJk/zFX/wFsVgMp9NJWVnZEkfciYkJcnJybtnDLFlyZG5ujvr6egoKCq55z6cDc/G9UgwyzR/Ly8uXjC+ZMSgWi9Ha2oqiKJw8eXLFJlXyNZScmHd1dRGLxSxt++Li4lUZBrlkF3s8e7gcvpxiAqmhIRApjKRgMEhDQ4NllrveKRVJSGx1HbD+XejYyUSsK+U4DCPhL1Bo30lUm+M5/18yGW+2tilyHOLuwo/gduSnmKv29fXR19eH3W6nt7eX2dlZKwbdSD3g1SJZs3+1UyyrwWJDE1P3NtnQxCxwLza3DYVCeL1efvd3f/d2/FkDkiVHFEWhp6fHmsRY70LkWk19Xdfp6Oiwpo4WS12YjEhVVenu7mZiYoLq6uol7AwTi5v8ZmLe0tJiNflLSkooLCxcdaNri2uLxUIycyEAHR2bsFlTItPT01ZMzVSBxil5OOC96u9S5NjJWLRtSRwCg0L7DoYjZ3nO/3/RURFIGGgUOQ5xf9FfWg3IaDRKfX29JZFw/vz5NfuP3Gikq9m/HiQv7JLNZ6empq67sAsGEzmn1+u9nQOtA2YeFIlELBLPehr6Jq61DjPNHz0eD6dOnVq2oW+yIkdHR+nq6uLAgQNLGm8mkpv8ydrJJjNwvU3+bFv2wlqIJbHFK3ut41yNd1G6KHBspsCR2J9mqLjl3IUGWlLxbcHLo9C+g2f9H2Mk+kJCpxroC/+cTc4a7tn5v9m1a5dVtM3OzmZoaIixsTEr/txMEsT1sBrN/vVAkiQKCgqs5k2yB9Lg4OASDySzEGfmQGZB+3YMWhuS12FmQ3+5ibG14FoxaGhoiM7OTg4cOLBExmZxMXt2dpampiY2bdq04nEtbvKbDbbe3t6MNvlXgkFizTA4OEhlZeW6mpGLIQmJnZ4KdnoqAAiqPi7MfhnD0BdMpxPQ0bELJ5LQ+fHE76EZCgYaIJiijZ1Fr+DEzvdx6dIlNE3D6XRy4cIFsrKyrHVYpqaM14vVavavB3a7PaUWZNYSx8fHU2pBBQUFeL1eq8GmqiqRSISsrKxfyfizoQrapnbb+fPncTgcnD59es0uzclYadw2EAhQV1dHXl7esuaPmqZZbOLVutYuHmkyR3InJibo6uqyxt6Li4ut4uRKqMypZCQ6wpP+J1FRwQCbZOOR0kfY6bnKKDSTwkwVkhZjb9Z9NMx/h6gWwDBEghW1UNA6nvM6ekI/oW720ynbTMaa+LnvT3io7PPI4upvqaoqV65cscZ6VFW1kgYz4JsBLVPSLWuFYRiWM3lNTc1NKXQJIcjJySEnJ4ddu3alMEvb29sRQliLOiEEg4ODxOOJMUTzuroeTp8+zezsLHV1dVRXVwPw1FNPoes6J0+eXHab6upq7HY7Tz75JI8++iiQcPQeHBxc1szVRGNjI/n5+dbY1enTp/nRj36U8p6f/exn19zHzYAsy4RCIS5cuMCePXvWzapJ3u9ymnCm+eNKMkeaphEMBmlubiYrK4uKioq0i0DJifm+ffsIhUJMTk5art25ubnWtZKOdM4jZY/wqf5PEdMTDSjzvLy08KVLCknbt29flWHLanA4+0G6gk+hGTEMw4wLOrKwcyTnVZyd/n/44q0p2/jjXTzn/0teXvJ31t/GxsYYGBjg2LFjFBcXL5FNyMrKss5PJlhda4VpBmiOYd+oYvZimLq3pvZtsqGJybwtKCiwDDgHBgbQNO12/FknJEliZGQETdMy0tCHlRdy8XicxsZGFEVZUrRKZkWaJIN4PM7JkyfTTjYXs29N6Y2enh5aWlpSRnLTea4WOYqozqnm0twlNENbyEESI/d35d+F15bQRG1vb894IWkxKnIeZTzakciBDAnTpNIt57PNXcmPJ96DzsLEIYlz74930jD3r5zIf5917l0uFydPnkSSJGvh0t/fT1tbW0qM9ng8tywGDQwM0NvbS1VV1YqNjBsBU/e2rKwsZWFnNvmzs7PJz8+3ZMKEELjdbnJycm7HoDXAkvCSJBobGyksLFx3Q9/ESk2165k/moUkIYT1HEzHO8JE8jVkNmlN5puiKCkNpHTXmzW5NTzhewINDWkhBzFINNXvyL+D3t5ey9g1U5MMy0EWNipzH+Xs9L+iGcpC0TpRzN7kOkREG2Ek+sLC8V1dA4/FLtEbegLXTAVXrlyhoqKCoqKiJecnHo9TWFhoEbVuVZN/fHyc9vZ2K1e7mTA9kMwp4+npaUsWIB6PW+v8SCTC4OCgFYtu50FrhyRJxONxmpqaMtLQT97v4hik6zpdXV2Mjo5SVVW1rPmj+Z8kSYyNjdHR0cH+/fvZunVrWp/rcDgsoog5qW42+Q3DSJnkX02T/1jOMZ6aeiqlqa4bifs8fz6f0emEFvWNXjN4bcXsz3opncGfoRmqxcwGwbGc19I6/29oRjwpBiVypb7wT4n1lZPn3mPV4JKb2I2NjQBrPj+ZwvT0NI2Njezbty/t3zxTWE4eybx+WltbkSSJ/Px8VFVldnYWv9+PzWb7lYw/wsi0i+EaYTrE1tfXs3Xr1owWZFtbW3E6nezde1XsfXJykqamJnbu3LmkUG2yIk3jrUyNaphQFMUayfX7/WnrbvvjfjqCHchC5pD3UIrcyMzMDE1NTWvWgE0X/ng/v/D/E/54PwBOKYuavLdw0PsA3xv/DULaxLLb3VHwIXZ4EtrOsViM+vp63G73sk67yayuqakpVFVdU9KZCZjM8WAwSHV1dUZ1sNZzTObCrr29nbe//e3WdMCPf/xjjh07lvbv/+CDDzIxMcG//Mu/oCgK73znO6mpqeHrX/86kBgxfulLX8pXv/pVTpw4AcB73/tefvSjH/HlL3+ZnJwc/uAP/gCAs2cTBqXf//73mZiY4NSpU7hcLn72s5/xwQ9+kA9+8IN89KMfBRI6wEeOHOGxxx7jt37rt3jqqad43/vexw9/+EMeeOCBTJ+ytBCPx7l06ZKl5b5WfdDl8NRTT6XIhJijvD6fj8rKyiVFAjOBMhtqqzWfuB6i0agVg6anp9PW3fbH/ZyZPkNvuJdsWzan8k5xNPsoQgjGx8dpa2u7JnMqUxiNtvHc9GeZU0YByLGVcWfBu8m1F/P98ZUNFl9V+lny7Dvo7++nr6+P48ePL8tcMGO0+d9ivbeblVSZTuvmyPdqNftvFJJj9Gc/+1m+8pWvoKoqjz76KH/3d3+Xts7q7fiTitnZWc6ePYssy9xxxx0Ze9bNzc1RV1eX4q9gjvJ6vV6OHTu2IisyHA7T1NSEx+NZIoe0HpgjuT6fj7m5ubR1txVd4XuT3+PczDniRhyn5OTegnt5ZdErGRoYor+/n2PHjt3QQpKJ3vA5Lsx8lcCC1NEm12HuLvgdxqMXqJv7F8yFWzIk7Dxc8O80Nlyd+lsu50v2H5menr4prK7lsF7N/huF5IXdO97xDvr7+xFC8IUvfIHXvOY1aRfeb8egqzCNFVtaWti2bRuHDh3KWM7R3d1NJBLh6NGj1t/MyZ+DBw8uKRQkF7PNPDwSiVBRUZERWR7DMAgGg0xOTuLz+QgGg+Tm5lqyANf7jLq5Or42+jUUXbGkR45kH+F04DQz/hkqKyszIguWzvfoCP6EhrlvE9ZmkYWdvVn3cjL/N3jO/1HGY40sjUOCbH0X3p43Lpt/mvtNjtHz8/OrImJlCqZm/7FjxzKak68XyfJIdXV1vPOd70TXdcrLy/niF7/IXXfdlfaEze0YdBWRSIT6+nqmpqY4ffp0Rp85586dY+fOnRaLVFEUmpqaiEQiS+S+FsscAfT09DA8PJyx/CK5ye/z+QiHwxQUFFiT/NdrIAXUAJ/o+wT+uN9q7AOU6qXcF7yPmsqbQ8AD0A2Nxvn/pHX+h8T0IB45n2M5r+Wg9+V8c/Q1y29kSJTGXsr9uz6wbD5jTvKbZMdwOEx+fr5VC7oZ8myZ0Oy/UdB13bp+PvGJT/D4448D8Ju/+Zt84AMf4MiR9CR1XyzxZ8MwtAOBAE1NTQDs3r07o8l6clfOMAz6+vro6elZVpvbNH/s6urC5/Ndc7R2rbDb7Slj72ZhoK2tDU3TKCwstEZykx+IhY5C7iq4a8n+JiYmaGtruyndo0LHDl5X9jfMqaMoeoR8+zZskhNVj65YzBbIzMR72eF5iWW4kJeXt2LTYjGry5TeGBoaor293WLfFBUVZdRwajF0XaelpYVwOExNTc1NLaRfC5IkWZq2OTk5lJeXU1RUxObNm7nzzjt58sknV+ysLcbXvvY1fv/3f5+XvvSlSJLEo48+yqc+9SnrdfNeCIfD1t/+/u//3npvLBbjgQce4NOfvsrMt9vt/PM//zPvf//7MQyDPXv28IlPfILf/u3ftt6zc+dOfvjDH/L+97+fT37yk2zdupUvfOELt7SYdOXKFQKBAC6XK+OJczJDMtn8cTmZIzOJGhkZ4fLlyzeEaehyudi6dStbt25N0d1ubGxECJHSEU9uOBU6Cnld2etS9mUa6vb29q7LKGw12Ow6zBs3fZJ5dQwDg1zbJoSQGIvWXXO7gDKKr19hZGSE6urqFdmvi2O0mVSZem/Jhko3ajQz05r9mURyjL7nnnt4/PHHeetb30pfXx8vf/nL6ezsTCsu344/V6FpGufPn8ftdpObm5vR581ihrYpc7ScNndyIWlubo7m5uZrjtauFcvpbpvsZLPJX1JSsqR4a5fsPFr2KA+VPERADZBjy8GGzWr8ZEpfPh3s8pxmp/skAdWHTXLikfMAGAjPWTIji6GjcLHuBUqLtlou98shWTYh2X/ElG5JZk7eqNwk05r9mYTT6WTz5s0UFxdz8OBBNE3joYce4uMf/zjd3d187GMfS2s/t2PQVUxMTNDZ2Ynb7aa4uDij93tyDDLNH8fHx68pc2TKrTU1NeFwOKitrc2YDI8Qguzs7Gvqbl+ryV+dW83+rP00BZqIaBF2Oncye2WWYCy4Zu+itX6PQ9mv5ID35US0ORxSFnYpQbxRjRjLNdXAIKoEue8a9/ViXVczRk9NTTEwMGBNZt1If5bh4WEuX75MRUVFRiUTMoHk8zM5OYnX6+WOO+6grKyMt771rZw5cyaFRHct3I5BV9HS0mLpZ2eawJEcg8LhMHV1dbjd7mXNH834A1d91gKBACdOnMjYcSV72Kyku32tJn+2LZs/3vnHPDv9LK3BViRDonC2kIMcpLq2+qaymSUhU5X7RipyXo9qxLALF0JIaIZCQlt7ee5scXHJivW+5En0vXv3WlOips+YGaOLiorIzc3NeJPfZNEfOnQoo5r9mYLJzp6bm8PpdOL1ennsscdobW3lD//wD3nyySfT2s+LJf5sKIb23Nwczz//PCdPnsxo8tzV1YWmaezfv5+2tjamp6epqqpaUswwk6fm5mYURbnp4vTJI5U+n49QKGR1o4qLi5c9loGBAas4f7NHsZJhGDrfHn0UxQgv86qgOu+9bDZeQn19PWVlZWteHJtu1D6fD7/fj8PhSJEmyVRSpes6TU1NxGIxqqqqNkwxOxk+n49Xv/rVHDlyhMcffxybzUYsFsNut99SiZZfVkQiEaanp2lpaUnboTxdPPfcc+zfvx+Xy0V9fT25ubkryhzpus6VK1cYHx/n+PHjN0yvdDkk6277fL7r6m6bDOKJiQkqKyszIo+wHoTUCf57/B0rvn4g+D8I+WSqqqrWnJQmm5bNzs7eEL23ZM3+6urqDVXMTsYPfvADfuu3fovHH3+cRx55BEgkPxtJ+/eXCXNzcwwPDy9hMq4X4XCYM2fO8IpXvILBwUGuXLnC4cOHlzTKkmPQ+Pg4nZ2dqxqtzQSS2f8+ny/FXLuoqGjJIk3TNJqbm4lEIlRWVm6Ie2U48gJn/H++7GtyPI8q/S/Zs3ttEzdmnmjGIJNZmkn/kWTN/pspc7RaqKrKu9/9btrb23nqqacoKUkYgmqatmG0f3+ZoGkagUDA0q3NZCN9YGCAqakpjh07Zpk/VlVVXZMVaTbUSkpKlpi03UgkSyCaE1rX0t02vYtsNhvHjx/fMM+/lvnHaZ3/WorcCACGYJ/79dQUvWdN+0321zDzxOQmfyaK+TdDsz8TqK+v57WvfS1vetOb+Kd/+ickSbLkKW5j9QgGgwgh+PnPf87999+f0anouro66xmZrsyRKQ1ms9k4duzYTasFJJtr+/3+605oZdq7KJN4ZuojjEUvLo1DwIMlnybfsXvV+0wmYk1NTQFYDf7FZNC14GZp9q8XAwMDfOpTn+Lf//3f+clPfmKRGZNlaH5VsGEK2pBICp5++ukVR6DWiu7uboLBINFoFMMwqKysXJYVabLEMz1au1aY3ajJyUlmZ2dTxr28Xq9V9KqoqNgQo6CNc1+kPfBNUjtxAlk4uN/zz7Q1dmfUpEnTNEvvbWpqCkVRUpKqtT4INU2jqakJRVGoqqraMMlpMqanp3nVq17Fnj17+I//+I8NeYy/bDCvp/Pnz/Oyl70so/s+e/YshYWFDA0NsWPHjhVljmKxGG1tbUSj0YyN1q4VySOnk5OTBAKBFE1Xl8tlTTBslEISwLP+jzEcOZeSPAkksuL7KBp/E1VVVRljTyXrvSUnVevRezPlaObm5qiurt5Q5pTJeOKJJ3jHO97Bl770Jd74xjfe6sN5UcA0g5ydnaWysjJj+zVzqy1btjA1NXVNmSNN0+jt7WVkZGRFSZ6bBbN4a8oCmCO5ZgwSQtDY2IgsyxuqkKQbGj+Z/ANmlb4li7h9+ruo2f5rGfssUz7K5/NZ0iTr8R9J1uyvqanZMDJHi6FpGu9973upq6vj6aef3pAMql82GIZhSa+VlpZm1PxqeHiY4eFh4vH4ijJHyazIiYkJOjo62LNnT9oSVjcCZpPfjEHxeDylwaYoijV1evjw4Q1VSIpp8/x48jEi2tTVOGQIXHI+ryr9DK6FiZL1IFl6w5SP8nq91jlai/+Iqdmf6VpAptHS0sLDDz/Mww8/zOc///kN9dv/skJVVTRN4yc/+Ql33313RtdADQ0NCCHw+XzXlTkyPS0aGxspKiri4MGDt+z3Xa7Jb+ZAhYWFBAIBGhsbV+31drMwrwzzU98fEddDgE7CwFbngPdRqvLW1lRLhkmINWNQKBQiLy/PitGrzWFMnfRbTRS9HoaGhvinf/onvvKVr/CjH/2Iu+5aquDwq4QNV9A+c+YMhw4dyujYent7O8PDw5SWli4xODED2PT0NM3NzWzevDnjo7WZgKnpahZvDcNAkiT2799PWVnZhniQakacs9MfZyjyrPU3u8jimO19jLTp7N2794a5w5p6eOb5mZ+fT1uTM+U7aBqNjY1omkZVVdUtb2osh9nZWR5++GE2b97Md77znQ3JHv9lhDlif+bMGR544IGMxQDDMDhz5gyxWIxjx44tK3OkaRqhUIjm5mZcLhdHjx7dMMUZE8mFE7/fjxACu93OoUOHKCws3DAxU9HDnJ/5ewYjz2I217KihyiefoSaiswYDS8H8/pZTu9tpQmb5fax0TT7l8NTTz3Fm9/8Zj772c/y1re+dcP89r/sUBSFgYEBJiYmqKmpydh+TYZ2dnY2VVVVK5o/qqpKe3s7oVCIioqKDVfMNI1bzSa/EIKsrCwOHTp0S41bl0NMn6d+9rP0h5/GQEOK57Df+WYqtzx6wz5zvf4j5sSNKbd3Kxuq14Kmabzvfe/jueee4+mnn77pRk0vVpgF7YaGBvLy8ti5c+f1N0oTly9fpq+vjx07dixZYyUXkiChrTk0NMTRo0c3nG6yuc4wdaVN2YCDBw9uuHgJENGmaZ59nP7gMwDs8N7L0by34ZFvzHlNXqv6/f4U/5HFEnbLoa+vj4GBgWWnqDcS2tvbeeihh3jFK17Bl7/85Q2xBn8xwMxDnnzySWprazN2Dei6zvPPP080GqW6unpJo35xMXtycpK2tjZ27dpFeXn5hsktltPdNgyDsrIy9u7du2EJMP2j7TT5vom9aBqvs4hdWa9gi+vkDTmvkUgkpclvSmgVFRVd13/E1Ow/fvz4TfFhWSuGh4f59Kc/zRe+8AV+8IMfcN99993qQ7rl2FAF7Xg8zvPPP8/u3bszRvGfmJigqakJl8vF3XffvSwrcmhoiMuXL98UM7P1wkw2VVUlLy8Pv99v6W6bN+ytLoTNKv1MxdpxSNlIs9vp6ujm8OHDN5VBY0qTTE1Npbi+FhUVraj3pqqq1cGtqKjYkMXs+fl5Xvva15Kfn89//dd/bdiH1y8jdF0nFArx1FNP8fKXvzwjI8um9trY2Ji1kFv8uqmj39LSYsnxbOTk2NSeczqduN1u/H4/QApjYCOMe4dVHzPRQfq7/Lgo5Pjx4zf1nk7We5uZmUnRe8vLy1uSyCVr9ldXV2/YRtWZM2d44xvfyD/+4z/yG7/xGxsm0X8xQFEUhoeHGRoaStsH4XoIBoPU1dURiUS4++67U4ouZg6kaZqlVWu32zcU23k5zM7OWkU3IQTT09Npm2vfbAwM93Klu52jB2tv6uiqOXVoFrcDgcA1/UcMw6CjowO/309NTc2GmbhZDF3X+cAHPsDPf/5znn76acqHuxrVAACaMUlEQVTLy2/1Ib1oYBa0W1pacLvd7NmzJyP7NM0fHQ7HkoV3ciHJlNqan5+noqJiw0rdQGJt2dLSQklJCaqqrspc+2bClENxOp0cO3bspuZmyRJ2U1NTRKPRFFO3xY3V3t5ehoaGqK6u3nCa/cm4cuUKDz74IPfccw9f//rXN8yz5sUAs6D9zDPPZExyUVEUGhsbmZubY9OmTRw+fNh6zWzom2sxIQT9/f309/dz5MgRS8Zqo8EwDEtytqysjHA4vCpz7ZuJwcFBuru7b0mR2IzNZgwyJezM/5Lz3I2s2Z+MkZERPvvZz/KZz3yG//7v/874RPkvKzZcxW6xedFaYT4ce3t72bp1K6FQaEnyrqoqly9fZnx8nMrKyg19AUOiQNLQ0IDX67WY5sm62/39/bS1ta2aFZhp5Nl3kGffkWgUXLly04zikuF0OtmyZQtbtmyx9N58Ph+dnZ3E4/Elem+KotDQ0IAsy1RUVGyIgtxiBINB3vCGN+D1evnud797u5h9A2D+7pnQ4DQXEoZhUFBQkFKgTGZFmgYg+/btu2ETDJnC3NwcDQ0NKSZxyYuWy5cvX1d3+2ZBUrMZaI7hzVo6mXMz4PF42L59O9u3b0/RezPNj5P13iRJorm5mVgsRk1NzYYtJp49e5Zf+7Vf42//9m9vF7NvAIQQ2Gw2yxRpvTCvt/Lycnp6elJeSy4kzc/P09zcTHFxMQcOHNjQC/TJyUlaW1tTJr6Smcmtra0putuZ0FNcK/r7++nrG6Dq+B03Pb8UQpCTk0NOTg67d+9O8R/p7e1N8R/Jy8ujq6uLmZkZamtrN2xuoes6H/7wh3niiSd45plnbhezMwwznsuynJEYpOs6HR0dTExMsG/fPoaGhlJeT45BiqLQ1NSEJEmcOHFiwzZ04ap30fHjx62R9ORnfENDw3V1t28GIpEIdXV15Obm3hI5FEmSKCgooKCggP3791vSJBMTE3R1dZGVlWWtwyYnJy2Zo43cyOjt7eWhhx7i1KlTfO1rX9vQz8pfZmQqBoVCIerr6/F4PGzatCnl91oscwRY3jW1tbUbtqmS7F2UzGJPNtfu6+vD4XCsaK59s44zuUl1K6RxbTYbJSUllJSUpNTLBgYGaGtrs2Q0VVVlcHBww2v2j4+P88UvfpHPfOYzfOtb37pdzE7ChitoZ2Ixp2kara2tzMzMcPLkSYLBIPPz89bruq4Tj8dpbW0lHA5z4sSJDTtaaWJubo7GxsYlhopCCHJzc8nNzWXPnj1EIhFrFOXy5ctkZWVRUlJCcXEx2dnZN6UAYRhGytjYrdZAkySJwsJCCgsLraTK5/NZoyVZWVnE43HcbjfHjx/fkMXscDjMG9/4RmRZ5r//+783LHvqlx2SJCGEQFXVdS2oAoEAdXV15OXlcfToUVpbW61GXfIizjTeqqio2NDjTXC1kLRY0zJ50bJv3z7r/hoZGaGjo4OcnBwrBt2skVwziS0oKLil2ncmbDYbpaWllJaWpowM9vX10draiizLlunMRi1mX7x4kTe84Q383//7f3nPe95zu5h9g5CJpr7J3rly5QpHjhxh06ZNDAwMWAu35Bg0OTlJR0cHu3fvZvv27Rv6dzWZPouZU7IsW8Wj5EWLeX/l5+dbMehmFGsNw6C7u9syVdwIo/PJTf5k/5H29nbi8TiSJLFr164N+/vrus5HPvIRvvvd7/LMM8+wa9euW31IL1pkophkmqkpisLp06eJRqP09/cDS80fg8EgTU1NFBQUbDhDs2QYhsHly5cZGxtbUqBJfsYnN/m7urqsJn9JSUla0j+ZQDAYpL6+3jLU3Aj3dVZWFllZWZSXl1v+Iz6fj7q6OksXOBQK4XK5NuSEbH9/Pw899BAVFRV885vf3JBrxV92mNepzWZbdx7k9/tTzB+vXLmCoijA1RzIFClQVZXGxkYMw+DEiRMbVu7PrG8Fg0FOnDiRUgtwOBxs3ryZzZs3pzT5W1parmuunWmYRffJyckN06RaXC+LRqP4fD6GhoYIhUI4nU4mJycxDOOWNACuh4mJCb74xS/yyU9+km984xu86lWvutWHtKGwoZ4YQoh1L+ZisRj19fUIITh9+jROp5NIJGIFLlMDrbm5GYfDwYkTJzZsAcGEGZB27959XUaK2+22WIHJWmYDAwOW7EZJSckNG8k1E77x8XFqamo2XIdTCIHX68Xr9bJz507LGRgSCeDZs2etoH+rWBWLEY1Gectb3oKiKDzxxBMb4sHwYoQQIiMxaHJykqamJnbu3GkZdMiybI3UapqGoii0t7cTDAapra3d8L+p6Th/+PDha47NL76/YrGY1WDr6enB5XKlOHXfiEVWIBCgvr6eTZs2sXfv3g2xkEuGqbmZl5fHrl27uHTpEoqi4HK5uHjxoqX3Zo4tb4SkqqGhgUceeYSPfOQjPPbYYxvunL6YsN5ikmkq6vP5qK2ttRrKZlwzY5CmaQwMDDAwMLDhzW9Mo8LR0dHrMn0WL1pM3W2TFWiaa5eUlNyQkdxk6Y7a2toNqasry7IlvxaPxwkEApSWljI5OUl3d/eGG1s2DIP/83/+D1//+td5+umn2bt37y09nhczzCmRWCy25n2YxVSv12t50SiKYsWfZFakz+ejra2NnTt3smPHjlt+ra2ExYWka5GgFjf5Td3toaEh2tvbU8y1b0R8MCfptm3btmGbVHa7ndLSUmZnZ7Hb7ezdu5dAIEBPTw8tLS23fNJ4MYaHh3n44YfZv38/3/nOdzZkwf3FhPWuw0yZo2TzR1mWiUajKcVsIQShUIiGhgZrkmEjrPuXg9kkFEJQW1t7zcbYck3+yclJent7aW1tTTHXznST35TanJ+fp7a2dkPcv8vB5XKhqirxeJyamhqrZmY2AAoLC61J2ls9MTQ5OcmXv/xlPvGJT/DVr36V17zmNbf0eDYiNlxEXg9De35+3mLlJQcls5ikaRqzs7M0NTVRWlrK/v37N0Sx4FowNX2uV0haDna7nU2bNrFp0yZLp9dMHlVVTenWZaKoby6kZ2dnqa2t3fCsd1MrMCcnh6NHjwIwMzPD1NSUxaooKCiwztOtGMONxWK8/e1vZ25ujp/+9Kcbgun1YsdaC0rmZEJPTw9Hjx5N0Yw3kzNN04hEIjQ3NyPL8oYfrU1mGq5l2sLpdLJ161a2bt1qaZmZBX/IvO72zMwMjY2N7NixI6OGVjcCpma/LMtUV1dbzz6/38/U1BTNzc3X1Hu7WWhpaeE1r3kNH/rQh3j/+9+/IRfHLxaYxaS1LuRMjw1N0zh9+nTKM0uSJFRVRVVVNE2jo6ODubm5DT1aC4lCkrk4Wss0ncfjoby8nPLy8pSR3IGBgYzrbps6+KFQaENLd0DiWJubm4lGoynPoWT/kf7+/rT8R24kDMPg4x//OF/4whd46qmnOHjw4E39/F9FrKepZsocbd++PaWhLEmStQ4zyUVDQ0P09vZuaK1aSMTVpqYmDMO4biFpMYQQZGdnk52dza5duyxzbbN5lGndbb/fT1NT05JJuo0Gs/E3PT1tFb1MKTuzCWlOGt9qbfKxsTEeeughysvL+d73vrehc/YXC9Yag3Rdp7Oz0yLVJctHJK/DzGK23++npaWF7du3b9jmDywvOZsukpv8e/fute6v8fHxjDf5NU1LkU/cqEz3lTT7TWkS039kcHDQakKataCsrKybep1MTU3x1a9+lb/927/lX//1X3nDG95w0z77lwkbyhRSURTa2toQQnDgwIFVbTs+Pm6xmHfu3JlysU1PT9PY2MjOnTvp7u7e8A96SNxsPT09DA8PZ8wYIXnfgUCAyclJfD4foVBo3d1wM4hFo1Gqqqo2bBAzEYvFqKurIzs7e1ltOcMwLL03n8/H3NwcXq/XCmg5OTk3PKDF43He8Y53MDQ0xJNPPrnhNd5/2WEaIj377LMcPHhwVbrvZtFlenp6WXf2rq4ugsEgW7dupb29ncLCwg0hhXEt6LpOa2sr8/PzVFZWZpRJpOu6JbsxOTlpNY/Mkdy1xA9zkmXfvn0WI2OjIh3N/mTpBDNO5+XlpSRVNxrt7e286lWv4rHHHuMjH/nIhk32XyzQNI1AIMAvfvELHnjggVWdb3MyITc3l6NHj6ZcU4Zh8Pzzz1NWVkZJSQmtra0IITh+/PiGflabZk6GYVBRUZHRQkKy7IbP57PMtUtKStaku62qKk1NTaiqSmVl5YYuepj5Wjwep6qqasXvmuw/4vP5lvUfuZEwDINPfvKT/O3f/i0///nPqaqquqGfdxuJvHNoaIixsTFqa2vT3i5Z5ujw4cNs3rw55fVwOMyZM2eoqKggLy+Py5cv4/f7qaio2NBEjUgkYrHNM+3Fkay7PTU1hRAiRft/tZ81MTFBa2srhw4dYtOmTRk7zkzDMAza2tqYm5ujurr6mnFEUZQUUzcgZYr2Rjf5JycnefDBBykuLuanP/3phm5SvhiQrKdvNoHShZkvxGIxqqqqUprfpjnt4OAg+/btIy8vj9HRUbq7uzl48OCGvl9WkpzNBJKb/H6/f11NfvP8A1RUVGxY9QOTqGVO/F1vQtpsQvp8Pqanp3E6nVYMutEG5H6/n8cff5y//Mu/5DOf+Qy//uu/fnsdtgI2VEFbVVU6OjqIx+McOXIkrW3Mwm9fXx/Hjh1bwmI2DINIJMILL7xAPB4nOzubrVu3UlxcvGEXcibTeWZmhqqqqhteuEjW3Z6ZmbGMOkpKStLS3f5lCWImotFoilFKOsEhHo9biaff70eSpHUlnteDoii8613voquri6eeempDj4O/mBCLxTh79iy7du1KYVhfbxvT/LGysjIl4TWZSCYLIB6PWxqCJSUlG/ZeMRNKTdOoqKi4obHSbB6ZMWh+fp6cnJyUkdzr3aNjY2O0t7dz5MiRVU+y3GwoikJdXR1Op5Njx46lHTsikYiVVM3MzOByuVJM3TKdVHV1dfHggw/yrne9i7/8y7+8nUTdBJgTHE8++SQve9nL0h5rnpycpLm5mR07dlgyRybM8drh4WF6e3uJx+O4XC52795NSUnJhh2djkQiNDQ04PF4lhToM43lmkerafKbzHibzcbx48c37DmFxDXW2NiIpmlUVlam/QxaLk6bzK4b4dFiGAaf/vSn+au/+iueeOIJTpw4kbF938bKUBSFkZER+vv7OX36dFrbJMscVVZWLpnkMgwDVVW5cuUK4+PjKIqCLMvs3buXTZs2bdgRf7OQZE703shnYLLuts/nW7W5tjnNu9Hlo0w5gkAgQHV19apyy2T/EZ/PRzgcJj8/38qDMj0V7Pf7efDBB8nOzubJJ5/c8FPHLwaYxKLW1lYcDgf79u1La7tkmaNjx46lPINNmaNoNEpPT4/VwAbYvXs327Zt27AxaDWSs+tFsu62z+dble62KffrcrlWta652TBlcScmJqiurl51fc08R+ZaTFVVK05nWppkenqar33ta/zFX/wF//AP/8C73vWu2+uwa2DDFbSvXLlCIBDg+PHj132/pmm0tLQwOzubMjJgwuz0mQ9P0xBwcnKS+fl5S8espKRkwzyoFEWhubkZRVGorKy86UX3ZN3tqakpa9zU7IYvLpqYxTyHw7FhDRWTYbp+m2ZxawkOyyWe5uK3qKho3XpRqqryO7/zOzQ1NfH0009v+ALdiwnxeJwXXniBrVu3smXLluu+35Q5ys/PX8LeMZMoTdPo7++nv7+fvXv3oqoqk5OTBINB67opKSnZMMwPs5DkdrtvSWKSrLs9PT19Xd1t0yju+PHjG95YMx6PU1dXZ53btRahNU1LYXaZem9mg229SVVPTw+vfOUrectb3sLHP/7xDT1J8GKCruvEYjF++tOfcv/991/3+W8YBv39/XR3dy+ROTJfN80fzaba5s2bsdvtVuHWnIzYSE3++fl5GhoabkohaTkkj7zPzs5es3AbjUapr68nKyuLo0ePbuh7Jdn4qrKycl2Fd5PZZf5nanYWFRWtu8lvGAZf+MIX+MhHPsKPf/xj7rjjjjXv6zZWB0VRLL35u+6667rvN5s5qqpSVVWVkv+aDX1TMzs5t8jOzmZqaopoNHrTDRPTgVlI2rVrF+Xl5Tc1BiU3jyYnJwkEAivqbpvPgP7+fioqKjI6zZtpmJJM4XCY6urqdf/Wi8lYHo/HKsCt139kZmaGV7/61djtdp5++ukN73PzYoFZ0O7o6ABIS2JqamqKxsZGtm3btoTBvNj8UdM0mpqaiEaj5OfnMzMzQzweT4lBG4VotB7J2fUiuck/OTlpNY+WM9c26yp5eXkb3tS3s7OTqakpqqur1133Mz35zBgUCAQsMlZRUdG65FtmZmb4xje+wf/+3/+bv/7rv+b3fu/3bhezr4MNV9Du7e3F7/dfd7QwGo3S0NCAEGJJ4ddMosLhME1NTciyzPHjx1MenmbRZHJykunpabKysigpKblhRkHpwPxOLpeLo0eP3nKWjzluakqTLNbdVlWV+vp6cnJylpXt2GgIh8PU1dVRVFTEgQMHMvYbm4nn1NQUs7OzFsO9qKho1Xpvmqbx+7//+5w7d45nnnlmydjmbdxYxONxLl26RHFx8XVliSYmJmhubmbXrl1LtNfMJEpVVTo7O5mdnaWioiKl6WYm45OTk8zOzpKdnW3FoFtlJGbKFpSUlGwIj4Hkwq3P5wNIabANDAwwNDREZWXlNY3iNgJMmSNzdDlT59ZMPM1GZDAYtBa/RUVFq9Z76+/v58EHH+S1r30t//AP/3DLr4FfJZhN+J/85Cfcdddd14wDJtNtamqKqqqqJdd/svmjyc5evDAKh8NMTk5uqCa/qR9/KwpJy2Fxkz95JNfhcNDY2GhJSN3qY70WTM1+SZJWlDlaK8xc0TxP6/EfMQyDr3zlK3z4wx/mBz/4Affcc0/GjvM2ro9kY6x77733mu8NBoPU1dVZPjTLsSJN88fp6WlaWlrYtm2bNUViFm7NGBQMBsnLy7PyoFvV5B8eHqarq4vDhw+nPal3I7F45N3lclnFt8nJScbHx6mqqtrQXgi6rtPU1GTJQWS6cZHsP+Lz+TAMI2WKdjVFyrm5OR5++GE0TeMXv/jFhpbEebHBLGhfuXKFWCx2zWl9U0bk8uXLHDp0aAkJKZlUJEkSkUiExsZG3G63Fa/MoqQZgzZCkz/ZuyjTkrNrxUpN/qysLDo7Oy39+42aAxmGYSkfVFdX3xCjStN/xJzkdzgc1josPz8/7ZxrdnaWb37zm/z5n/85H/3oR/nDP/zDDXteNxI2VEFb0zQGBgYYGRm55njh3Nwc9fX1FBYWLikMmAFsdnaW5uZmCgoKrtsxMhO4yclJpqamcDqd1qJuOUbgjUAgEKChocEqtm60IkKySL5ZNAEs2Y6NwnBfCaFQiLq6OkpLS29o0DWvJfM/IUQKa+laTQpd1/mjP/ojnn76aZ5++ukNr/P+YoTJNsrJyVlRu800k+jt7V1R5kjTNKLRKC0tLQDX1aqNx+MpDTa3223FoJuh1w6J8UpTtmDHjh0b7gFqGEbKZEQkEkEIwY4dO9i6deuGYZcuh2SZoxvNYFhO7y05qbrWZw8PD/PAAw/wwAMP8OlPf3rDPYde7DAL2k8++SS1tbUrLqTTkTnSdR1VVbl8+TJTU1NUVFRcs+kTi8Ws5vWtavKPjIzQ2dm5YQpJi5Fsrj0xMYGiKHg8Hnbt2rWhmF2LoSgK9fX12O32Gz5Jtx7/EcMw+PrXv84HPvABvve973H//fffsOO8jeVhmjdfunSJl770pSu+zzR/LC8vZ8+ePddkRY6MjFhFp2tp1a7U5C8uLr4pDFlTwnJoaGjDsp3Nwu3k5CQTExMYhkFJSQmbNm26IfKHmYDJilUU5Zqa/ZmCKU1ixiDTfyS5yb8SgsEgr3nNawiFQpw5c2ZDXgMvdsRiMfr6+pibm6OiomLZ9+i6TkdHBxMTE1RWVi75nZKn0yRJYmZmhubm5usWXs0mv/nsysnJsfKgm1HnuNmSs2uBOZ01OjrKzMwMNpvN8me50ZrSa4F5TtPR7M8UTI8WMwYpipLiP7LSenV+fp5vfetb/Nmf/Rn/83/+T/7kT/5kw63FNyo2XEF7eHiYvr6+FbXbTPPHPXv2LCm6mAFsfHycjo6ONTF8TH0cM6CZBcmSkpJlJTcyAbOQVF5evsTQciPCbCjk5uZiGEaK7vbNMkxcDUwWyebNm5ck3jcSycZ3U1NThMPhFNZScodQ13X+9E//lB/96Ec8/fTT7Ny586Yc422kIh6P09LSgtPpZO/evUte1zSN1tZWK9lYXHAyY9D8/DzNzc1Ww2c1i4zkBYs5ym0mVDdCKxlgdHSUjo6ODW8mBFfNKufm5igrK2NmZmZNuts3C+Y4Xn5+PocOHbqpx5WsiTc1NXVNvbexsTFe+cpXcs899/C5z31uQy6MX+wwC9rPPPPMisycQCBgjXcuZ/5osiJN+TJTB381SfzNbvKbTcLBwUGOHz++4Q2QTaPxzZs3Y7PZMmaufSMQj8epr6/H6XRy/Pjxm77YTGa4L/YfKSgosJr8hmHw7W9/m8cee4zvfOc7PPDAAzf1OG8jAVVVmZ+f5/nnn+cVr3jFkteTzR+PHDmyJF9ILiQBlm62aQaZLhY3+U1W8o1q8icXkiorKze0xIQptxkKhdizZ8//3957h0dVre/f96T33iCEFkpoqYQAioIgSUiZgCKg0lX0AL8DeEQUkKOiHEU92LEczVdARUjoEEpI6CKkkUYPCSWZmfSeaev9g3dvJ5CEJEzZE57PdXFdMsxk1ozZ917rKffDJ/o76rutr7VmZmZCrVY/tM1RZ2nv/JH6+nrExcWhrKwMJ0+eFLyFXVdFLpejsLAQMpkMISEhLf57ZmYmnyC5917L7YG4YPadO3dw8eJFDBw4sEMD4/XdyW9oy9mOwHXS+fr6wtbWlo+ZcfaHnR2urW2482JtbW2HPfu1BdcFwGlQdXU17O3teZ3mfpdqamqQkJCAVatWYdmyZVi5cqVgzrHGgOAC2sXFxS16t3GZ8xs3bsDf3x8eHh73/btSqURBQQEKCwsxdOjQ+57TUbhKb03LDU2fJW3cmLlA0qBBg4zCXqKsrAxZWVno168fX0F874GF81JszXdbn3CHfx8fn/tsIfQN17JTWlrK+701NDRAqVTi6NGj2LFjB1JTU9GvXz+DrfFRh/PcB+73buOGXrRlc6RWqyGVSpGbm4tevXo99O8cVxHIaRDXRsltFh426GhsgSSu0kculzf7f3Cv77alpSVf2aWvLpuWaGhowPnz57Vuc9QZNLtsSktLeb+3S5cuwcPDAytWrMCIESMQHx9PwWwDwbXbnjx5EgMHDrxvuJdUKkVWVhb69OnT6vBHrkI2KysLdnZ2Dz1Q8V7bH20n+blKq/LycsEHkoC7/w9ycnIwcODAZi3OLQ3X5jRI2wMT2wvn2c8N1jR05ZTm/BHOP9ne3h7Hjh2DnZ0d1qxZg99//x3R0dEGXeejjFKpRF1dHVJTUzFx4sRmvzPtGf7IBbM5v+TGxkYEBQU9VIKntSS/u7u7VioCjSmQxPngcwFiLmDU1nBtQ9nYcTZHIpEIgYGBBrfR5NakmeRXq9V80HLXrl2QyWQ4efLkQ8cPiM4jl8tx69Yt3Lp1C2FhYc3+rT3DH7lkGoBm1h0Pc75pyXpMs9DoYe/vQrOcbYuSkhLk5ube10n3sMO1tY22Pfu1BVfhzsXMzMzMcOLECVRWVuL333/HP/7xD7z33nsUzO4gggpoc8GgrKwsjB07ln+cy0ZXVVW16BPGGINCoWiWXde2lxgXDOB8lhoaGpr5LHX0QtEc5OHv728UmWCJRIKcnJw2qzg5L0VO0BQKRTPfbX1m67iBfT179mzVPsJQKBQKlJWVYcuWLVi7di0UCgViYmLw4osvYsqUKRRQMhAKhQKXLl26z7uN+11ycXG5r+Ja06ft5s2buH79OgYPHqz1lnmujZLToKamJj643ZlriwsklZWV6UQztY1CoUBmZiYAIDAwsNXP25LvtjaTAO2F8+x3d3c3yGC7B8ElAZYsWYKkpCRYW1tjzpw5eOGFF2gIm4HgAtpnzpxBnz59eA1hjKGgoADXrl174PDHiooKZGdno0ePHlrvSNJ2kl+pVOLChQuQy+UdriI3BFyl14MKJlobrq3PllzOs9/e3l6wM07q6uqQl5eHuXPnoqCgAL169cKLL76IBQsWwMfHx9DLeyTh7NKOHDmC8ePH8/dZzo5NpVIhODj4vmtVsyqysbERWVlZsLKyui/o9LBozvaRSqVQq9X8tdWZ+zsXSLK0tNT6WrUN121hYWHxQOugjg7X1jYKhQIZGRkwNTXVume/tuACcL///jveeecd1NbWIiwsDM888wxef/11QWrmo4BcLkdJSQmuXbvWbC/K2Rz17NkT/fv3b9PmiKvMraurQ2BgoFYTOvd28gNopkEd/b0RuuWsJjdv3sSVK1fg7+8PNze3Np/bkeHa2kalUvF7S33YHHUWtVqN4uJi/POf/8TBgwdhYmKCiIgILFiwgBL7HURwd25TU1OoVCr+79wEeVNTU4waNapZ4JiriuQ2T4wxhIWF6SS7LhKJ4ODgAAcHB/Tr148fZHL79m3k5+fD0dGRz9Y9KAulVqv5SavDhw8XfCAJ+Hvarr+//31VY5qYmJjA1dUVrq6uGDhwIF8RWFhYiNzcXN7HrD3f08PA2aL06dMHvXv31tn7dBZzc3N4enqiqakJDg4O+PTTT5GXl4f//e9/ePbZZw29vEcaU1NTKJVK/u+czZGvr+99lkCag9cuXbrET0/WxYBCkUgEJycnODk5oX///vwgkxs3biA3N7fVCdQtwQWSmpqaMGLECMEHkrjqeO6A3NbhSNOiRdN3+8qVK8jOzuZ9zHQ58KWurg7nz59Ht27d7tt4CwVLS0vY2Njg9u3biI6Oxssvv4wDBw7gzz//pIC2gdHUIJVKhdzcXJSVlWHEiBGtDn9kjOHOnTu4fPmyzjq+TExM4OLiAhcXF/7+LpVKcf36deTm5nYoya8ZSBo+fLigA0kAUFhYiGvXriEwMPCBlV7m5ubo1q0bunXr1sx3Ozc3977h2ro4aGl69g8ZMkSQ+gMAtra2fGDgf//7H2xsbLBnzx7U1NQYemmPNNz9VaVSwdzcnB8W7ejo2KbNEXB378151fbv31/rwRnNM4afnx+f5L98+TKf5Ofu7w+6trhqT26oq5ADSQ0NDUhPT4e9vX27hkpbWlqiR48e6NGjB1+VzBWMAX8P19ZFkl+hUCAtLY1PEggxmA3c3VNbW1vj0KFDcHFxwZEjR5CRkYHs7GxB/y50dUQiUbNYkKbN0ZAhQ+7b22hqkImJCT9jxNzcHCNGjND6PVazC12z6+jixYt8EV97k/zGYjnLFVUUFhYiODi4XfZRNjY26NWrF3r16tUsyV9YWNhsuLa2k/yczRGXfBVqMBu4q+unTp1CRkYGFi1ahPnz52P//v2orq429NKMDsFVaFdVVeHEiRMIDw/ng5Jubm73VZhwAlZdXY2srKxOedVqi8bGRr5lqaKiAnZ2dnxA5V4vV6VS2awNT+iBJAAoKCjAjRs3HnpISkstubrw3a6srERGRgZ8fX0FO1iRMYZPP/0UX3zxBZKTkxEQEGDoJRG4e31ev34dpaWlCA4OxrVr11BQUNDm8Mempibk5OTw7aqGuKYbGhr4iiXNQSacn7Qmmps9f39/Qd/sgb89qJ2cnB56oCLXkiuVSnXmu8159nt7e99nCyEkKisrERMTg27duiExMVEw7XiPOlzyxtXVFV5eXq0OfwT+ropUKpW4du0aSkpKWvXe1jVckp9rd28ryV9bW4uMjAy4uLgIPpDE2d3dunULQUFBD5Ws1Oz001VLLqeX3HcrVP0BgJSUFEybNg0bN27ECy+8IOi1PiqoVCoolUocPnwYo0aNQn19PR9wedDwR25+UUe9arUBZ7nB7YNqa2vbTPKXl5fz1Z6GtiN8ENxQezc3t4e+pjVn+3CdftpM8nM2R9bW1vD39xe0tiuVSrz44otIT0/HiRMnaHaRQOA6mDMzM/Hkk08iLy8PUqm0xUDqvcMfq6urkZmZCXd3d71XO7d0f9dM8t97bRUXFyMvL0/wlrOMMVy+fBklJSUtuiR0FM0kv0wmg0qlajbb52HOpJwlE7dnFnKhRENDA/bv348VK1ZALBbjq6++ErReCh3BBbRra2uRkpKCYcOGIS8vr83hjzKZDDk5OVrxqtUWCoWCv0i5YUrcoc7KygqZmZlGE0hijOHKlSsoLi5GUFDQfQPwHgbuhiWVSrXqu11RUYGMjAz0799fsC2rjDF88cUXWL9+PQ4dOoThw4fr/D2PHz+O9evXIy0tDcXFxdixYwfi4uLafE1qaiqWLVuG3Nxc+Pj4YNWqVZgzZ47O12pIlEolioqKcOvWLVhaWqKyshIhISEt2hwplUrU19cjKysLtra2GDp0qCBunpqtpmVlZbCxseE1SCQSITMzkx9QKPSbJ1cZ5uXl1eZk8s7Q1NTUzMdMc/Cdo6Njp74bzrNfiDZHmlRXVyMuLg6Ojo7YtWuXzpMwpD/thxt4ZG5uDqlUCmdnZwwdOrTVqkilUomcnBw0NjYiMDAQNjY2Blz9XdpK8jc1NeHChQtGEUhijOHixYv8cCpt+9BqO8kvdJsjTU6cOIFnn30Wn3/+OebOnavztZIGtQ9uoGxycjK6d++OW7dutTr8kbNaE4lEfNJHKBaKLSX5uft7dXU18vLy4Ofn18wHX4hUVVUhIyMDPXr00HqCvC3f7c4k+TmbIzs7u3ZVkRsSpVKJuXPn4syZMzh27FiLQ+C1DWlQ+1AoFKiqqsKff/4JBwcHKJXKdg1/lEgkyMvL44vZDH3/u7eAhkvyu7u7QyKRGIXlLDc3obKyEsHBwVrfX2rTd5vz7DcxMRGszRFHQ0MDDh48iBUrVmDixIn4/vvvda6XXV1/DB990YBrMwGAvLw8BAYG3mdvwQWSioqKdOZV+zCYm5uje/fu6N69O+/lKpVKkZGRAaVSCWtra/j6+gr6QgOaD2oaPny41g9y5ubm8PLygpeXVzPf7fz8fCgUimaTutsb+OcGVt47rElIMMbw3Xff4aOPPkJSUpJegtnA3RtrQEAA5s2bhylTpjzw+QUFBYiKisKrr76KLVu2IDk5GS+99BK6deuG8PBwPazYcHAVLA4ODhg1alSrwx/LysqQk5OjE6/ah+HeVtPS0lJIpVKcO3cOarUaDg4O6N69u2DW2xpcp4WuWvEsLS3h7e0Nb2/vZr7bXEsu17rs6urarkQF11HUu3dvQVf61NXVYerUqbCxscHOnTv10lFA+tMxOA/Jfv363Rf01ayKbGho4L1qQ0NDBZMkt7Kygo+PD3x8fJol+a9fvw7GGG8ZIGQ4D86amhqEhobqxCLN2toaPXv2RM+ePZu15HI2ex1J8nNVnJ6enlpP/mmbM2fOYOrUqVi/fr1egtkAaVBH4IJEd+7cadPmSK1WgzHGXycjRowwyPDBlrC2tubb3eVyOR9YunbtGhhj8PT0hJ2dHRhjgr1WysvLkZmZCV9fX/Tq1UvrP18kEsHOzg52dnbo06dPs2KI69evd8h3W9PmSOjFEkqlEq+++ipOnjypt2A2QBrUERobG3nLo5CQkPuGP3IaBNz9PeY6yYcNG9amLao+sbW1ha2tLXr37o2mpiY+wXb58mWIRCJ4e3vDwsJCsBrE+VA3NjYiNDRUZ3a+jo6OcHR0RL9+/Zol+S9fvtzu4doKhQLp6ekwNzd/4HwBQ8PNqFi5ciXGjh2L7777Ti962dX1R1AV2pzvlkQiwfDhw+8znOcGJnFetYGBgTrxqtU2XGDG1dUV5ubmfIuFps+SkC4+lUrFD1NoafiLLmGM8d7AMpkMtbW1vO+2u7t7q9nB0tJSXLhwAX5+foJt3WGM4eeff8bKlSuxb98+PP744wZZh0gkemBm7s0338S+ffuQk5PDPzZ9+nRUVlYiKSlJD6s0DGVlZTh79iwYY3jqqadatDlSq9W4ffu2Tr1qtU1JSQkffOeG7wJ/DzJxcXERlAZx17MhOi00h2/KZDI0NjY+sCWX0/i+ffvq5OCpLerr6zF16lSo1Wrs27cPdnZ2el8D6U/rcBXBV65cgZubG0JCQu77d64qkrNb47oXhBxA4Dwwr127hl69evEV3CYmJnzltr6GJbYHlUqFrKwsfqCQvu14NJP8Uqn0gb7bnM1R9+7dBZVcbYnz588jNjYW77//PhYtWmSQtZIGtU5DQwPOnTuHqqoqDB48+D7rEM2qSLlcjqysLJiZmcHf31/QtlVqtRqXLl2CRCJBr169UFNTg9LSUt7L1cPDA05OToLRIKlUiuzsbIPtMTsyXJuzOeI6/4SsPyqVCosWLcK+fftw7NgxDBkyxCDrIA1qnTt37vBFgBMmTLgvmH3v8Mf8/HxUVlYiMDBQ0DPJuABxfX09fHx8UFFRcV8nv6OjoyCuH4VCgczMTABAYGCgQYolWhuufW+SnxuWa2lpiYCAAMFoeEs0NTXhyJEjWLFiBUJDQ7F582aDdHZ3Rf0RVIW2UqmEiYkJTExMmgVRuWwc16qqUCgQFhZmFP7TEokEubm5GDBgAL8x9PPzQ3V1NaRSKa5evYqcnBy4urrywW1DbgqVSiWysrKgUqkwfPhwva9FJBLB3t4e9vb28PX1bda6fOXKlRZbcmUyGS5cuIAhQ4YIqlpfE8YYNm3ahLfeegt79uwxWDC7vZw5cwYTJkxo9lh4eDiWLFlimAXpidraWnh5eUEqld4XzOYqkq5cucJ7iRnCq7YjcIGk69evIyAggK9cGDRoECorKyGVSpsNMtHloLL2UlJSgtzcXAwePPi+Nmd9oDl8c8CAAXzbYHFxMS5evAh7e/tm/uRcMFvINkfA3aqAGTNmoKmpCUlJSQYJZreXR1V/uBZwb29v3FtroKlBEokE+fn5GDBggKB/54C76+YCSaGhobx1mWbQNjc3VzBJfoVCwbetGmpYZXuGa3MapFQqkZaWBh8fH8FbuGRmZkIsFmP16tUGC2a3l0dVg+RyOWxsbKBWq++zOdKsiqytrTWYV21H4QJJDQ0NCAsL47stOC9XLnjMGNPpsMT2cvv2bVy6dAnDhg2Dh4eHQdbQ3uHadnZ2yM7OhpubG/z8/AR9TavVaixbtgx79uzB0aNHDRbMbi+PqgZVV1fDz88POTk5/LBZ4P7hj1xCDQBGjBihsyHv2qCpqQmZmZkwNTXlB1X27NmzWeIoMzMTIpGoWaGRIXSVCxBbWFgYtNq5teHaeXl5fJLf2dkZN2/ehK2tLYYNGybo+5BcLkdKSgpWrlyJwMBAbNq0SRA2pa1hbPojqG/S2toaAQEBSElJgVKpBPC3gHGbJzs7OwQGBgr6l4CDq0i6twVGs8Wif//+qK2thUwmw82bN5GXl8cfVjjfbX0hl8uRkZEBMzMzBAcHC+I7vrd1mRP+9PR0mJiYwM7ODhUVFYIPZm/duhX/+te/kJiYiLFjxxp6SQ+kpKTkviGInp6eqK6uRkNDg07ar4VAjx49YGtri+LiYv4xToPkcjlyc3PR2NiIESNGCMKrti00A0khISHNullEIhGcnZ3h7OyMAQMG8F0RN27cQG5ubpuDTHTJzZs3ceXKFQQEBNzXoWMoNNsGudZlriXX3NwccrkcPj4+grU5Au5upl988UVUVVXh0KFDWp2HoAseVf0xMTFBQEAArl27hqqqKv5x7hCnUqlQUFCAW7duITAwUPC2HSqVCtnZ2aivr8eIESOa/X+7N2grhCR/Y2MjMjIyYG1tjWHDhgmia0UkEsHBwQEODg7w9fW9ryWXMQZnZ2fB6GVr5OTkICYmBsuXL8eyZcsEHfgCHl0NcnBwwLBhw3Du3Llm5zDNqkipVCoor9q24M41JiYm99kymZiYwM3NDW5ubs06sy5fvgy5XN5Mg/SV5L9x4wYKCgoQGBgIFxcXvbzng7h3v8gN37x16xZqampgYWEBS0tL1NXVaW24trZRq9VYvnw5tm3bhiNHjiAwMNDQS3ogj6oG9evXj58NolQqeVsOzeGPXEyIGxYvhHt1a9TV1SEjIwOOjo4YMmRIs6CrZuJIrVbzhUb5+flQKpXNNEgfMZmGhgakp6fDwcHhvrUaEk2t9vPzQ01NDYqLi3H58mWo1WpYWFjg1q1bWhuurW3kcjmOHTuGVatWwc/PD7/99ptgLAJbw9j0x/ARy3vgfLS5zROXvcrOzhacV21raE6EvTeQ1BKaHmaNjY3NfJY0qwF1WVHX2NiI9PR0QWe57vXdvn79OgoKCmBubo78/HxIpVK+wlRIrY87duzA4sWL8ccff2DixImGXg7RBvfqD3A3KFNXV4cLFy4Izqu2NTjboNra2vsCSfdyb1dEfX09pFIp7ty5g4sXL8LR0ZGvGNBVEJ8xhoKCAhQWFrY4yVwoWFhY8L7bXFWXo6MjiouLUVxc3GHfbX2gUCgwZ84cFBcXIzk5WbDfLfE3pqamUCqVzaoiVSoVcnNz+WtaKF61rcENtxSJRA/UTCEk+bmBii4uLhg0aJAg90DA377bDg4OSE9Ph7u7OxhjnfLd1hf5+fmIjo7G4sWLsWLFCsHv4QnAzMyM3wdxCTWRSIQbN24Izqu2NbhAkoODwwOHFGp2ZnEadG+Sn9sH6SLJzxjD1atXcfv2bYSEhAg66cx1yhYVFcHHxwd2dnYoLS1FQUGBVoZraxu1Wo3Vq1dj8+bNOHTokN5mFxGdQyQSQSQS8Rp07/DH0tJS5OTkGMVg6crKSmRmZsLb2/uB8SsTExO4uLjAxcWFT/JzxTP3FhrpIsZRW1uL9PR0eHh4CHqotEgkgoWFBWQyGby8vNCnTx/emoTz3X6Y4draRqFQ4OTJk1i5ciV69eqFbdu2CSpG1VUQxon7HszMzKBUKqFWq/mKPWPxqtUMJIWGhnY4AGRlZcUPCZLL5fxAN25AB3eo0+ZFWldXh/T0dLi6umLQoEEGv/jbQ0lJCYqKihAUFARXV1d+81lUVMQfgB/ku60P9uzZgwULFmDLli2Iiooy2Do6ipeXFyQSSbPHJBIJHBwcBJeV0zampqb88FmRSITy8nJkZ2cbhVctcH8gqaM3ThsbG/Tu3ZsfZMJZ/ly9epUf0OHh4QE7OzutaIVmAnD48OGC9sDjkMlkyMnJ4TtDuOoumUyGa9eu8S25XGWFoeyxlEol5s+fj+vXr+Po0aOCqfh6EI+y/gB/B5O4gFJjYyMuXLjAt6sKfTNcX1/frMqno9VTbSX57ezsmmmQNqipqUF6ejqv8ULfA1VUVCAzMxP9+vVDz549ATS3cNEcrq3vCtN7uXz5MqKjozF//nysWbNG8N8tx6OuQVxSTXP4Y15eHiorKxEaGir4+zQXSOrevTv69+/fod+7lpL8MpkMJSUluHTpEhwcHHgN0sb5gjGG/Px8lJWVITQ0VPDJypqaGqSlpaFHjx7w9fWFSCRCjx49tDJcW9uo1Wq89957+PHHH7F//36MHDlS72voLKRBplAoFM2GPxYVFeHatWsYPHiwYLuyOaRSKXJycjplR3jvsESuK+L27dvIz8+Ho6Mjr0Ha+F2oqqpCRkaGUViXcZ79XPGBSCTS2nBtbaNQKHDq1CmsXLkSXl5eSExMFLQ1jibGpj+CDGibmpqiqakJ+fn5kEgkRuFVC4D3c2KMdSqQdC8WFhbo3r07unfvDpVKxQe3uYuUy9Q9zDCl6upqpKentyt7KBQ4f7mAgAC+5bol323O783Gxob/rvSZrTtw4ADmzZuH+Pj4No33hcioUaOwf//+Zo8dPnwYo0aNMtCK9AcXfGlqakJ5eTkuXrxoFF61wN1AUkZGBuzs7DB06NCHbsOztLREjx490KNHD36jIJVKUVhYCAsLi2bDlDpzXanV6maHZKHbuAB/D2saOnQo3451b3VXS77b3Helr5ZclUqFV199FXl5eTh69Kjgq+k0eZT1RyQS8f6QSqUS9fX1yMzMhJubm6Arhzm4g1FnAkkt0VqSv6CgQCtJfi44zCXxhL4HKi8vR2ZmZrO5LED7fLf1neS/fv06oqOj8fzzz+ODDz4Q/HeryaOqQdz/I1NTU9TW1kKhUIAxZjRetcDfgSTNhM/DYGNjg169eqFXr14tJvm5e7u9vX2Hf8fVajWys7NRV1eH0NBQwc+G4s6MXHWsJvf6bnMWLpyN1IOGa2sbtVqN//znP/j666+xZ88ejBkzRufvqU0eVQ0C7iZ5TE1NUV5eDhsbG5iYmODSpUuQyWTt6nw3NEVFRbh69SqGDh2qFR98W1tb9OnTh0/ya84W00zyd+Z8UVZWhqysLK3ppS7hOunc3d1brCK/13ebS/Jr+m7ra1aUUqnEmTNnsGrVKjg5OWHnzp2CDAS3hrHpj4jdO3nIgDDGIJfLcebMGdy6dQtOTk7w9fWFt7e3YNq3W4PzHdJWIKktuIuUq1pSq9X8hqojg0zKy8uRlZWFPn36oHfv3jpbrzbhKvaDgoLaleTQ9N0uLS2FiYlJs2ydrv4/JScnY8aMGfj+++8xY8YMgx/kamtrcfXqVQBAUFAQPvvsM4wbNw4uLi7o2bMn3nrrLdy+fRu//PILAKCgoABDhw7FwoULMW/ePBw9ehT/7//9P+zbtw/h4eGG/Cg6RaVSoaGhAX/++ScqKipgaWmJ3r17o0+fPoL2aAP+DiR169ZN51WGKpWKH6Ykk8n4QSZcJU57gm6cv25DQwOCg4MFf0gG7naG5OXldajdWtN3u6ysjG/JdXd3h5OTk04ClCqVCosXL8bp06eRmppq8O4m0p/209TUxFfANTU1AbhbKeHn5yf4fZC2A0ltoZnkLy0t5StxPDw82p3kl8lkyM7Ovi84LFS4g6efn1+HrumGhgb+u6qoqNBLS25hYSEiIiIQExODL774wuCJGNKg9sHNC5FIJPzAaMYYHBwcEBAQIPjuEG0HktpCqVQ20yBzc3M+sNSeJL9SqURWVhaUSiWCgoIE/91WVVUhPT29U2dGLskvk8lQVVV133BtbWsQYwyffPIJPvroI+zYsUMQ1yxpUPtQKpVoamrCzZs3UVRUBLlcDlNTU5iYmCAoKEjQA80ZY7hy5Qru3LmDoKAgnQfeFQoFf12VlpbC0tKS1yBHR8cHXlcSiQQ5OTkYPHgwunXrptO1Pix1dXU4f/48unXr1uFiCcYYn+SXyWSora1tNlxb24FmlUrFB7PNzMxw8OBBg3c1dXX9EVRA+8SJE5g9ezbKy8vx2GOPYe3atSgrK0NDQwNcXV3h6elp0NbJ1qiqqkJmZqZB2lU1s+BSqRRNTU18Bsrd3b3V74o7eA4cOFDQw8w04VqNgoKCOuUDqzlwQSaT8S252vbdPn78OKZOnYqvvvoKs2bNMngwGwBSU1Mxbty4+x6fPXs24uPjMWfOHNy4cQOpqanNXrN06VLk5eWhR48eWL16NebMmaO/RRuABQsW8D6GPj4+WLduHSoqKtDY2Ag3Nzf+5ie0wBIXmPH19UWvXr30+t4tXVfcd9XaIBOFQoGsrCyo1WoEBQUJTtNbgvMU9/f37/QANs1EQGlpKZ+M1GZLrlqtxpIlS5CSkoKUlBRBVFyQ/rSP+vp6DB06FOPGjUN5eTlqamrw/vvvo7a2ltcgbh8kNA3iks36CCTdS2eS/MXFxcjLy2vWaSFkOI0fNGjQQx089ZHkv337NiZOnIiJEyfi22+/NXgwGyANai/x8fH48ssvIRaLYWFhgTNnzmDZsmWQy+WC1iDNQFJgYKDeZ0Xcm+QHwGtQS9cVN6zSzMwMAQEBgvouW6KyshIZGRn8INCHQddJfsYYvvjiC7z//vvYunUrYmJiHurnaQvSoPYRGRkJKysriMVi9OzZE7/99huee+45ABD0WYybc1JdXY3g4GC9d5xylj+cBpmYmPDB7ZaS/Ldu3cLly5eNYh5CbW0t0tLS4O3tzdscPQyaw7W1neRXqVT466+/sGrVKqhUKhw+fFgQHQVdXX8EFdA+fPgwnnnmGbi5uaGkpATdunWDWCxGREQEvLy8UFpaitraWri4uMDT01NnxvgdwZCBpHthjPE+S1KpFLW1tXB2duaFn2tlu3PnDvLz8zFs2DC9Hzw7Czf5Ozg4WCvCwBjjB09x3xXnSfUwLbmnTp3CM888g08//RQvvfSSIILZRPs5deoUnnvuOVRVVaGxsRFjxoyBWCzG+PHjAdxNBNXX1zfTIEMHY2/evInLly8LIjDDZcE5Daqvr+eTRh4eHrCwsIBcLkd6ejosLCwQEBAg+Mp3oGWbo4dF03dbJpPxv1fcpqozrcdqtRrLly/Hvn37kJqaij59+mhlrYR+UKlUSEpKwpIlS3D9+nXY2dlh8uTJiI2NRWhoKCorKyGRSPgkP3e/MqQGaQ4zM0QgqaX1cNeVVCpFY2Pjfd8VV8WpzetZl7Rkc6QNNFtytZXkLykpQXh4OMaMGYMffvjBKPSd+JuysjIkJCTgs88+w6VLl+Dt7Y158+ZBLBajR48ekEqlgtMgtVqNnJwcVFdXIygoyOAe1IwxPskvlUrvS/IrlUqkp6fD1tYWw4YNE0TCpy1asznSBpq+21wi4GF9t7/99lusWrUKW7ZswZQpU7S6XkL3ZGVl4Y8//sCmTZtw8+ZN+Pj4YNWqVYiKioKZmRl/XdXV1fHFjobWIIVCgczMTDDGEBgYaPDYlOa9XSqVQqVS8Rrk4uKCW7du4caNGwgMDBS8pW9bNkfagEvyS6VSlJWVPZTvtkqlwvnz5/HOO++gtrYWycnJRjO7yNgRVEB71apV6N69O/7xj3+gtrYWBw4cQGJiIvbt2wcXFxfExMQgIiICPXv2RGlpKWpqaviAra4mT7cFl90aMmSIwQNJLdHQ0MALf1VVFRwcHGBubo7y8nIEBQUZzUV2/fp1FBUVITg4WGeTvzV9tznPLk7Q2tO2AwBnz55FXFwcPvjgAyxcuJCC2UbIihUrIJPJ8M033+DOnTtISEhAYmIi/vrrL4waNQpisRhPP/00TE1N+UQIN/yPC9jqC81AUkBAgCA3JVyCTSaTobq6Gvb29mhoaICjoyMCAgIEf5AD/q48DQwM1KlmttSSy2lQewZwqtVqrFq1Ctu3b0dKSgr69++vs7USumPt2rXYs2cPEhIScPXqVWzfvh07d+5EbW0toqKiIBaLMXLkSFRXVzfTIEMk+dVqNXJzc1FVVSWIQNK9tJTkt7KyQlNTk9Ek9EtKSpCbm6vz9XJJfk6vuZbcjvhuS6VSREZGIiQkBP/3f/9HwWwj5bvvvsOaNWvwyy+/8Pugw4cPo2/fvhCLxYiLi0Pv3r2bFYQYah/EBZK4bi9DB5LuRTPJL5PJUFdXxw+d9Pf3F7xnNmdzpI9u3taS/B0Zrv3jjz/izTffRHx8PKZNm6bT9RK6Y9++fXjuuefw5ptvQq1WIzExEZcuXcK4ceMgFosRHR0NS0tLyGQySCQSg2pQQ0MDMjIyYGNjg2HDhgnuvscY4/eLUqkUDQ0NAIA+ffrAx8dHcJqpycPYHHWGtpL8D0qaqNVqpKWl4d///jfKyspw9OjRTnfzEh1HUAHt1mhoaMDBgweRmJiIPXv2wMbGBrGxsYiMjETfvn1RVlaGqqoqODo6wtPTEx4eHjrdJDDGcO3aNdy8edMoslvAXV/OvLw8lJWVAQA/KLGzg0z0Afc937p1CyEhIXrzH1IqlXy2rr0tuenp6YiJicE777yDJUuWCPL7JB6MSqWCiYlJs/9/jDHcunULiYmJSExMxKlTpzB8+HCIxWKEh4fDysoKUqkU1dXVcHJy4jVIlwk2LpBUWVmJ4OBgwQWSWqKsrAwXLlyAqakp5HI57Ozs+Mrt9gRsDcHD2hx1Fs3hd+1pyWWM4b333sMvv/yClJQU+Pn56W2thHZpbGwEY6yZpx/nx5eQkIAdO3agvLwcEREREIvFePzxx/mgbXV1td6S/JxtkEqlEmQg6V4YY8jNzYVUKoWtrS1qamp4H1dumJLQKC4uRn5+/kPZHHWW1pL8rQ3gLC0tRVRUFAYNGoRff/1VUK3gRMeoqalBZWVls0HYVVVV2Lt3LxISEnDw4EF0794dsbGxmDx5MgYMGMDfr/SpQVwgydraGv7+/oILJN1LdXU10tLSYG9vD7Vajerqajg6OvLXldCGYmvL5qiztJbkb2343S+//IIlS5bghx9+wMyZM/W+XkJ7lJeXIy8vD48//jiAu/fvy5cv80VGWVlZGDNmDOLi4hATEwN7e3s+YKt5Futst2N7qa6uRkZGBjw8PODn5yfIcwyHWq1Gfn4+SktL4eXlhcrKStTU1OjUS/ph0KbNUWfoSJJfrVYjIyMD7777Lu7cuYPU1FSjKJjoShhFQFuTxsZGJCcnIzExEbt27YKpqSmio6MRHR2N/v37o7y8HJWVlXBwcICHhwc8PT21eoGq1Wrk5eWhoqLCaAJJjDFcvHiRnw5saWl53yATbpOgqyFlnVnz1atXcefOHYSEhBhsCATnD8xVosjl8mZTci0sLJCVlYWoqCi8+eabWL58uaBvaMTDwRhDSUkJduzYgYSEBBw/fhz+/v68NRK3qeISbNyhTpsaxAWSuEFCxjBMkRtY2aNHD/j6+kKpVD7UIBN9oG2bo87CeXNy35dareZbB52dnWFubo7//Oc/+O6773D06FEMHTrUYGsldI9arcb58+exfft27NixA3fu3MHEiRMhFosxbtw4NDQ0QCKR6DTJb2yBJM1K8pCQEFhbW/M+rlKpFOXl5bC2tuYPdboalNgRdGFz1Fna8t22tbVFU1MToqOj0bt3b2zdulXwyQ3i4aitrcX+/fuRkJCAAwcOwNXVFTExMZg8eTKGDRuG0tLSZhrEncW0qUE1NTVIT0+Hh4cHBg4cKIhzS1tUVFQgMzOzWaVhU1NTMw2ytbXl90GGTvLryuaos7Tmu819ZwkJCVi0aBG+/vprzJs3z9DLJXQIYwzXr1/nE/znz5/nO2hjY2Ph4uLCX1dcPIjbB2nzLFZaWooLFy6gb9++6NWrl8H3DG2hUqmQnZ2N+vp6BAcH81rc2NjIJwIqKythZ2fXLMlvqM/E2Rz179+/WWLVkHBJ/nuHayuVStTW1uLDDz9EQUEBUlNTBT9gsytidAFtTRQKBY4dO8a35CoUCj64PWjQIFRWVqK8vBx2dna8mD1MAFqhUODChQtQKBRGE0jivOVqamoQHBx8n5ir1epmg0wYY20OMtEHXCZWIpEgJCREMEkDTd9tmUyGX3/9FSdOnEBRURFefvllbNiwQdA3NEK7MMZQWlqKnTt3IiEhASkpKRg4cCDEYjGioqLg7OzM3/js7e15DXqYKpzGxkakp6fD2toaw4YNM4oqOK5ltV+/fi1m2VsaZKKpQYY4qOrD5qgz3NuS+89//hM1NTUoKyvDjh07MHHiREMvkdAjarUaWVlZfHC7oKAA48eP562RmpqaeA3ikvwPq0E1NTXIyMiAu7u7UQSSVCoVLly4gMbGRgQHB7e4b7u3K8vMzMygSX592Rx1Bs2W3OzsbCxYsACWlpbo3bs3Dhw4gO7duxt6iYQeqa+v5zto9+7dC1tbW8TGxiIuLg7BwcH8daXNfRAXSOKCw0Lfd3PXSlu2HQqFolmhERew5TRIn59RIpEgJydHsLZMmkn+7777Dlu2bEFTUxPmzZuHTz/9VFB7NkK3MMZw8+ZNvoP29OnTCA0NhVgshlgshqenJ59g4zSIS7A9jAbdvn0bFy9exODBgwUfvFQqlc1smVqzzbi3M9TKyorfM+ozya9Pm6POoum7PX/+fFy7dg0WFhb48ssvMW3aNMFbSXVFjDqgrYlSqcTJkyeb+U1OmjQJ0dHR8Pf3R1VVFcrKyvhsrqenZ4eyT42NjcjIyICVlZXRBJJUKhWysrIgl8sRHBz8wKoZzUEmMpkMcrmcH/ri5uaml4ELXDV5aWkpQkJCBNeCp8nRo0cxffp0eHp64tatWxg0aBDOnz9vFL8bhHZhjKGiogK7d+9GYmIiDh8+jN69e/Neb+7u7nzrNpcB5zSovXCBJDc3N/j5+Qk+kAT8fTAaNGhQuwIdbQ0y6eyAoI7A2Rzdvn0bwcHBerM56gyMMaxatQobN26En58fsrOz8c9//hOffvqpoZdGGADGGPLy8rB9+3YkJiYiPz8f48aNQ1xcHCZOnAiVSsVXAnZWgzjboN69extFIInz1wWAwMDAdu1hWkvyc0PKdJ3kN5TNUWeoqqrC008/jfr6ejg7OyMrKwv79++nxNojSmNjI44cOcJ30JqbmyMmJgZxcXEYMWIEP9T2YTTImAJJAHDnzh3k5+d3qNKZC9hyGiQSifSW5OdsjoYNGwZ3d3edvY+2SExMxEsvvYTHHnsMxcXFuH37NqRSqVEUnBHahTGG4uJivoP2xIkTCAgI4IPbPj4+zQK2tra2fIKtvV3gXHV4UVERAgICBJdwvhe5XI709HRYWFggICCg3fsXlUqF0tJSvniGG5TIdYbqSoMMbXPUERhjyMnJwQcffIA///wTUVFRSElJwahRo/Dbb78ZenmPHF0moK2JSqXCn3/+yQe3S0tLERERgejoaISEhKCmpgalpaWwsrLixawtH2ljDCQpFApkZGTAxMQEgYGBHQ4EaXoHcdOEXVxceEHTxWaBMYb8/HyUl5fzbcFC5erVq4iIiMALL7yAjz76CLW1tUhPT8fYsWMNvTRCAHB+k4mJiUhKSkK3bt344HaPHj34tklra+tmG6rWNIgLJPXq1Qt9+vQRfCAJ+LtlvrMHo3sHmTQ2NvJDX3Qx/E4oNkftgTGG77//Hu+++y4OHDiAUaNGobS0FBUVFTQMkgBjDFeuXOGD25zfpFgsRmRkJEQiUYc1iAvMGEsgqampCenp6bCysuq0LQrXEcFpkK6T/EKxOWoPdXV1eOaZZ2BqaspX5t66dQvOzs6C6aojDIdCoUBqaip/DlOpVIiOjkZcXBwee+wx/rpqrwYZWyAJAAoLC3Ht2rWHsg3ibA+54LZCoeCT/G5ublpN8gvJ5qg97N+/H7Nnz8aaNWvwxhtvQCQSobi42CjuT4Ru4TpoueB2SkoKBg0axA+19fX15Su3OQ3iEmytaRDnQV1eXo6goCBBnxGAuwlGzrN/6NChnY5dcYVG3D5IrVbzsSBtJvk5m6MhQ4bAy8tLKz9TV3AFJB999BH+/PNPpKamol+/fnzsTMjFUF2VLhnQ1qQlv8mnn34aMTExCA0NRX19PUpLS2FhYcGLmWZrhTEGkrhqcs6WQBtiU19fz2+oqqqqtNa+zMENbOI8LoXcrlFQUIDIyEhMnjwZ//3vf/WW4Pj666+xfv16lJSUICAgAF9++SVGjBjR4nPj4+Mxd+7cZo9ZWlqisbFRH0slNOD8JhMTE7F//364uLggNjYWMTEx6N27N+9NamlpyR/qNDWICyS1t8pZCHCBGW0OzeXsfqRSqdYHmQjV5qglGGOIj4/HW2+9hX379mHMmDF6e2/SIOODMYaCggJ+mNK5c+cwevRoxMbGIioqChYWFnybO9di6unpySf5udcXFhYaTSCpoaEBaWlpcHJywuDBg7Vyj9Z1kl+oNkct0dDQgGeffRZKpRIHDhzQ28Ge9Mc44Tpot23bhp07d6K+vh6TJk2CWCzG2LFjUVtbC4lE0qoGcYGksrIyBAcHCz6QpDnQPigoSGvJKcYYampqeA1qaGjQWpJfyDZHLXH48GG88MILWLFiBVauXKm3szlpkPHBddDu2rULCQkJOHLkCPr27QuxWMwPta2oqOA1yMLC4r6zmFKpxIULF9DU1ISgoCBBxyiAuwnn9PR0uLq6YtCgQVq7PjRtD7lCIy7J7+7u3ukkv9BtjjThii8//fRTpKamIjU1FQMHDtTb+5MGtUyXD2hrwvlNcge769evY8KECYiOjsbo0aN5w3czMzN4eHjAxMQEhYWFGDx4sNEEkurr65Geng5nZ2cMGjRIJ8FWbQ8y4Xy+a2tr+aGVQqWoqAgRERGIjIzE119/rbdg9tatWzFr1ixs3LgRYWFh2LBhA7Zt24ZLly61KP7x8fH45z//iUuXLvGPiUQiQQx3eZSpr6/HoUOHkJCQwFe1xcTEIDY2Fv379+eD2+bm5vDw8IBKpeJvWsZQMaNZ5RwUFKSzwIw2B5lo2hwNHz5c0J0hjDFs3rwZ//rXv7B7926MGzdOb+9NGmT83Os3eebMGYSEhEAsFiMmJga2trZ84prToPr6elRXVwvegoejtrYWaWlp8PT0xMCBA3UW6Kivr+f3QQ+T5DcmmyPgrvZOnz4dNTU1SEpK0lslOelP10ClUuHMmTN85XZFRQXCw8MRFxeH8ePHNyue4QbWV1VVQaVSNRtmJlS4/YRMJtN58L2uro7/rqqrqzs9iNyYbI4AIDU1FdOmTcPSpUvx7rvv6i2YTRrUNaiqqsKePXv4Dlpvb28+uD106FC+GpmLB7m6uqK8vBxWVlad6njXN1VVVcjIyECPHj3g6+urs+uDMcZrkFQqRW1tLZydnfngdnu12phsjrjip88++wwHDx5ESkoKhgwZorf3Jw1qnUcqoK1JS36TY8eORWxsLB577DH88ssvGD58OJycnODl5QVPT0+DDAfqCNzUby8vLwwYMEAvN3lukIlMJkNpaSl/CG7vIBO1Ws1P3g0JCdG6jYA2uXPnDiIiIjB27Fh89913eh2YGRYWhtDQUHz11VcA7n5vPj4+WLx4MVasWHHf8+Pj47FkyRJUVlbqbY1Ex2hsbERycjISEhKwe/dumJmZITo6GmKxGP369cP//vc/PP7447CwsICXlxfvXSbULhEua81VUemryvlhBplw94GKigrB2xwxxvDHH39g8eLFSExM1LtPLWlQ10LTbzIxMRHHjx+Hv78/4uLiEBMTAxMTE+zatQv+/v58xRK3DxKqBlVWViIjI0PvHXUtJfm5yu227OyMyeYIuPs5X3zxRUgkEhw+fFhr3TftgfSn66FWq3Hu3Dm+g7akpARPP/007/t/48YNpKenw8fHB+bm5nzVpFD3QVxxTk1NDYKDg/W6n+AKsrgBnFyS393dvc1CI2OyOQKAkydPYurUqXjttdewbt06vf4ekAZ1PWpqapp10Lq5ufFDbUNCQnDq1ClUV1fD2tqaj28IOR5UXl6OrKws9O3bF7169dLrezc0NPAaVFlZyQ/g5AqNWsKYbI44K78vvvgCu3fvxtGjR+Hv76/XNZAGtc4jG9DWRNNvMiEhARkZGTAzM8PixYvx/PPPA7jr7cMY4y9OXQ/m6CjcQc6Qw5ruHWQCoJnP0r3fF1cx39TU1K6hlYakpKQEkZGRCAsLw88//6zXYLZcLoeNjQ22b9+OuLg4/vHZs2ejsrISu3btuu818fHxeOmll+Dt7Q21Wo3g4GB8+OGHes0kEu1H029yx44dqKyshKWlJTZs2ICxY8fyFQPccCBPT0+dDuboKFxiqq6uzqBVVNwgE85Coa1BJsZkcwTcHX706quvYuvWrYiKitLre5MGdW00/SYTExORnJzMXzt//PEHvL29+SocoWpQaWkpLly4gP79+8PHx8dg61Aqlc00qLUkvzHZHAF371GzZs1CYWEhkpOT9Xr4JP3p+qjVamRmZjbroBWJRAgODsbvv/8OAILWIJVKhaysLMjlcoOfZxQKBT/MrbS0FJaWlrwGOTo68hpkTDZHAHD27FlMmTIFc+bMwWeffabXcy5pUNenvr4eBw8e5Dtozc3NUVVVhdmzZ2P9+vXN7H6EGA+SSqXIycmBn5+fwV0F5HJ5syS/tbU1fxbjCo1u3bqFy5cvG43N0dWrV/Hll18iISEBhw8fRkhIiF7fnzSobSigrYFCocDkyZNx+fJlPPvss0hNTcVff/2FUaNGQSwW48knn4SpqSmkUilUKpVOTPE7AzcVdsCAAejRo4fB1qEJN8iEE7R7B5mIRCJkZWVBoVAgODhY68OVtIlMJsOkSZMwbNgwbN68We/tRnfu3IG3tzdOnz6NUaNG8Y8vX74cx44dw9mzZ+97zZkzZ3DlyhX4+/ujqqoKn3zyCY4fP47c3FzB/I4Q9yOTyRAREQHGGIKDg3HgwAHU1dUhKioKYrEYwcHBqK6uhkQiAWOszYSRvlAqlcjKyoJSqURQUJBgElNtDTJxdnZGfn6+UdgcAcDevXsxd+5cbNmypdlGRl+QBj065OfnIzw8HD169ICTkxOOHj3K+03GxsbC29ubH6YkFA0qKSlBbm6u4AZWtpXk54ZyCt3mCLir8fPnz0d+fj5SUlL03hZM+vNocfz4ccTExMDf3x+VlZW4fPkyxo0bB7FYjKioKH6orVA0SKFQICMjAyYmJoKzJFCpVCgrK+M1yMTEBO7u7lAqlbz+CN3mCADS0tIQFxeH6dOn46uvvtJ70RZp0KPF5s2b8dJLLyEwMBBXrlyBhYUFoqOjMXnyZIwePRp1dXWQSCTN4kGenp5wcXExSDyIq3QeOnSo4DyoOa3RLDSytrbmrez02enVWa5du4ZvvvkGv/76Kw4dOoSwsDC9r4E0qG2Ec9cVAObm5oiNjcVzzz0HJyenZn6TO3bswIoVKzB8+HDExsZi/PjxsLCwwOXLlyGXy+Hm5gZPT0+4ubnpVcyKi4uRl5cnuKmwJiYmcHFxgYuLCwYMGMBnNq9fv46cnByYmZnBzMwMQUFBgg5ml5WVISYmBn5+fti0aZOgNqptMWrUqGaCN3r0aAwaNAjfffcd3n//fQOujGgLOzs7TJ48GcuXL4eFhQXvN5mQkIDly5ejvLwcERERiI2NxciRI1FTU4OLFy9CqVTyGqTPBJtcLuc7WkJCQgR1fZiYmMDV1RWurq7w8/PjB5lcvnwZDQ0NMDU1Rb9+/QRRWdEWSUlJmDdvHuLj4w0SzO4spEHGiZmZGRYsWIC3334bIpGomd/khAkT0L17d74lt0+fPpDJZLwGGSLJzw0z8/f3F5z/Ilfl7u7uDsYYKisrIZVKkZ2dDZVKBTc3N1RVVcHc3FxQ2qmJSqXCa6+9hpycHIMEszsL6Y/xIpPJ8Mknn+Dll1/mOxkSEhLw448/4v/9v/+HMWPG8NZI3FBbQ+2DGhsbkZGRAWtrawwbNsygxU0tYWpqyleSckn+K1euoKamBqamprhx4wav2ULVoKysLEyZMgVTpkzBl19+KUi7mZYgDTJecnJykJiYiEmTJkGhUCAlJQXbt2/H3LlzoVarERUVhcmTJ+OJJ55AQ0MDr0EKhYLfB+krHsTZBgm10tnMzIy3rOMG/BYXF8PMzAxZWVl8saOhi0Nbo6CgAN9//z22bNmCAwcOGCSY3VkeJQ2iCu120prfZGxsLJ5++ml+mFJjYyN/cbq7u+t0g6B5kHNzc9PZ+2gTpVKJtLQ0yOVyWFhYoKamptODTHRNZWUloqOj4e3tjYSEBINVnnamzaQlpk6dCjMzM/z22286WimhSzi/yYSEBOzYsQN37tzBxIkTERsbizFjxvAVA1yCjdtQ6UqDGhsbkZ6eDltbWwwbNkzwgWHg77bmhoYGeHh4oKysjB9kwm1ChWQ9kpycjBkzZuD777/HjBkzDHaQIw0igLsDF/fv34+EhATebzImJgZxcXEYOHAgX7mtDw1ijKGgoACFhYUIDAw0iioftVqNvLw8VFZW8kk2qVSKuro6uLi48PtGoXSMqFQqLF68GKdOnUJqaiq8vb0Nsg7SHwK4e81fv36dtyVJS0vjO2hjYmJgZ2fHV27rQ4Pq6+uRnp4OZ2dnDBo0SPB7IMYYLl26BKlUiuDgYKhUKr5yu6GhoZkGCaXTLjc3FzExMQgPD8fPP/9ssO+YNIgA7sYwTpw4gW3btmHXrl2or6/nO2ifeuopKBQKvnJb1/EgbgYHN1DaGGyDNG2O7O3t+T2QVCpFU1NTM80WQrFjYWEhvv/+e/zwww/Yu3cvxo4da7C1kAa1DQW0OwHnN7lz504kJCTg6NGj8PPzg1gsxsSJE+Hk5ASpVIr6+nq4uLjA09MT7u7uWrs4uU1dUVGR0UylBv5uyzM1NUVgYCBMTU35QSYymYwfpsQFt9saZKJrqqurERsbCxcXF+zcudPgQa6wsDCMGDECX375JYC7B+OePXti0aJFLQ4CuBeVSoUhQ4Zg0qRJ+Oyzz3S9XELHcP7z3FDbGzduYPz48bw1UmNjI6RSKRoaGuDq6sp3j2hLg+rq6pCeng5XV1cMGjTIKCpmOI9LzhqF+y46M8hEHxw/fhxTp07Fl19+idmzZxv8OyYNIjTR9Jvct28fbG1t+crtoUOH8j7SutAgrmqzpKSEPxgJHW5gXEs2R/X19fyhrrq6Go6OjnyCzcbGxmDrXbp0KZKTk5GSkqL3AVP3QvpDaMJ10HIJ/tOnTyM0NJS3RnJxceGvKV1oUE1NDdLT0+Hl5YUBAwYY/P78IDSHdrdkc1RXV8d/XzU1NXBycuIDcYYqNLp06RKioqLwxBNP4NdffzV4woA0iNBEpVLh9OnTvAZVVlYiIiICcXFxmDBhAhhjfHBb2/Egzes5ODhY8DM4GGO4du0aH3y/d8/GGENtbS2fYOMKjTgNMkQMpqioCP/73//wzTffYNeuXZgwYYLe13AvpEGtQwHth4QxhoqKCuzevZs3iu/Tpw/EYjEiIiLg6urKX5xc9tvDw6PT2W8uw84NErKzs9PyJ9INCoUC6enpMDc3R0BAQIttJQqFotkwpdYGmeia2tpaTJ48GVZWVti7d68gqsa3bt2K2bNn47vvvsOIESOwYcMG/PHHH7h48SI8PT0xa9YseHt7Y926dQCA9957DyNHjkS/fv1QWVmJ9evXY+fOnUhLS8PgwYMN/GkIbcINN+SC2xcvXsS4ceMQFxeHcePGQaFQ8FWArq6uD12BU11djfT0dHh7e6Nfv36CP8gBd2/imZmZUKvVCAoKarVSoj2DTPTB6dOnMWXKFL7tWgjfMWkQ0RqNjY04cuQIEhISsHv3bpibm/OV24GBgaioqIBEItGKBmlWOQcHBxss4NsRuKG59fX1CAkJafNzNzU1NdMgQyT51Wo1VqxYgd27dyM1NRV9+/bV+Xs+CNIfojUYY7hz5w7fQXvixAkEBAQgLi4OYrEYnp6ekEqlWtOgiooKZGZmonfv3ujdu7cg7s9twRhDXl4eKioqEBIS8sAzDVcQIZPJUFFRATs7u2ZJfn183mvXrmHSpEkYMWIE/vjjD0FYEZAGEa2hVqvx119/8cHtkpISTJw4kY8FmZiY8Br0sPEgbj9RV1eH4OBggxfcPQjGGK5cuYLi4uJ2x604GxepVIqqqio4ODjwZzF9BO9v3bqFn376CV9++SW2bduGSZMm6fw92wNpUOtQQFvLVFVVYe/evUhISMDBgwfRrVs3iMViREZGolu3bpDJZKiuroaTkxM8PT3h4eHR7vZSzYNcezYlQkEulyM9PR2WlpYICAhoV5adG2TCVW9zU811PVG4vr4ezzzzDABg3759gkoYfPXVV1i/fj1KSkoQGBiIL774gvdyGjt2LHr37o34+HgAwNKlS5GYmIiSkhI4OzsjJCQEa9euRVBQkAE/AaFrNP0mExMTkZWVhTFjxkAsFuPpp58GY4yvwOGy3x3RoPLycmRlZaFPnz7o3bu3bj+MllAqlcjIyIBIJOrQwKaWBplw35eTk5PONOivv/5CXFwc1q5di4ULFwrqsEwaRDwITb/JXbt2QaVSITo6GnFxcRgxYgQ/qJXTIK5iqT0apFKpkJ2djYaGBgQFBQn+IAfcXfOFCxfQ1NSEkJCQDlVmaSb5y8rKYGFhwe+DnJycdKINarUaq1evxh9//IHU1FT0799f6+/RWUh/iAfBGINMJuOD2ykpKRg0aBAf3Pbx8eFtSTqzD5LJZMjOzsaAAQOMYqiWWq1Gbm4uqqurERIS0mHNlMvlzTTIysqK/750leS/ceMGJk2ahGHDhmHHjh2C8vYmDSIehFqtRkZGBn8OKywsxIQJEyAWizFp0iSYm5vzSeuOxoOUSmWzTlOhWAO1hqbNUUhISKeC0XK5nE+wlZWVwcbGhtcge3t7rWvQnTt3EB8fj88++wy///47YmNjtfrzHxbSoJahgLYO0fSbPHDgAFxcXBAbG4tJkybBx8cHpaWlqKqqapeHNHcoamxsRHBwsGA8Fh+EXC5HWloabGxsOu2zq1ar+WFK3ERhzSEC2trsNDQ0YNq0aaivr0dSUpJR+FERRGto+k3u2LED586dw+jRoxEbG4vw8HCYmppCJpPxGsRtqFo78EilUuTk5GDgwIEG81LtKC3ZHHUGtVqN8vJyflPFGNPJIJP09HTExMRg9erVWLp0qaCC2QTRUTi/ye3bt2Pnzp2or6/HpEmTIBaL8dhjj6G6uhoSiYQ/1HH7oJY0SKlUNuuyEIK/4oNozeaosz9LU4N0keRnjOH9999HfHw8HwgkCGOF66DdtWsXEhIScOTIEfj6+iI2NhaTJ09Gnz59+GBte/ZBxcXFyMvLw9ChQ+Hp6WmAT9Qx2rI56gwqlQqlpaV8oRE39NbDwwPOzs5a0aBbt24hMjIS/fv3x+7duwUfsCOItmCMIScnh++gvXz5Mt9BGxUVBRsbGz7B9qB4kFwuR0ZGBszMzBAQECCoRE9LPMjmqDMolcpmnfzm5ubNkvwPq0HFxcXYtGkTPv74Y2zatIkvcCSEDwW09QTnN5mYmIi9e/fC1tYWMTExiIqKQt++fVFWVoaKigrY29vzGyqulVahUCAzMxMAEBgYaBQHOeBu62xaWhrs7OwwdOhQrR24qqurtT7IpKmpCc8//zzKyspw6NAho/ElJ4j2wPlNJiYmIjExkfeb5BJslpaWvIe0g4MDPDw84OnpyW9A7ty5g4sXL2Lo0KHw8PAw8KdpH5zNkYWFBfz9/bUWdGaM6WSQyYULFxAVFYU33ngDb775JgWziS5FS36T4eHhiIuLw5NPPona2lpIJJIWNYjr8rKwsGjVskxoqFQqZGRkgDHWps1RZ9BM8stkMiiVSt5GobMD8Bhj+Oijj/Dtt9/i6NGjGDZsmNbWSxBCoKqqCnv27OE7aL29vREXF4e4uDj4+fnxQ21b0qCioiJcvXoVAQEBcHV1NfRHeSBqtRoXLlxAQ0PDA22OOvvzuW4bqVQKtVrNB5Y6m+QvLi5GZGQkfHx8sH//fqMp3CKI9sBVK3OV29nZ2RgzZgzi4uIQExMDBwcHvnL73niQiYkJ0tPTYWtr2+niQH3SUZujztBSoZFmkr+jGiSRSLBp0yZ89NFH+PHHHzFjxgytr5nQHRTQNgCc32RiYiJ27doFMzMzxMTEIDo6GgMGDEB5eTnKy8thZ2cHV1dXSKVS2NjYaDUoo2saGxuRlpYGR0dHDBkyRGfBGW0MMpHL5Zg5cyZu376NI0eOwMXFRSdrJQghwBhDcXExduzYgYSEBJw4cQL+/v6Ii4vDpEmTYG9vz/u32tnZwdLSEuXl5QgKCjKaa4MLgFlZWcHf319nmz/NQSacT3lnBpnk5eUhMjISixcvxurVqymYTXRp1Go1zp07h+3bt/N+k08//TTi4uLw1FNP8f6JnId0U1MTHBwcEBgYKPiDHNDc5igoKEin+zbGGGpqapoNwOtokp8xhg0bNuCzzz5DcnIyAgMDdbZeghACNTU1zTpo3dzc+KG2AQEBfBVgeXk5zM3NoVQqMWTIEHh5eRl66Q+E6+iVy+UIDg7WeREUl+TngnGNjY3NfMrb8/5SqRSRkZFwd3fHoUOHjMJOiiA6C9dBy+2B0tLSMGrUKMTFxSE2Nhaurq58gq28vBwA+OJAIVmhtgRnc1RTU6M3j2/GWLMkv1wub5bkf5AGSaVSbNmyBR9++CG+/fZbzJw5k85hRgYFtA2MQqFAamoq35LL+U1GRUXB1tYWu3btwqRJk2Bra8tn6vQ1GKizNDQ0IC0tDc7Ozhg8eLDe1trY2Ngsu9meQSYKhQLz5s3DlStXcPToUbi5uellrQQhBBhjKC0t5YPbKSkp8PPzQ1xcHCIjI/HLL78gMDAQ3bp144eTeXp66m0wUGdoamriKxm01RnSXurr63kN4gaZcIe61rzjLl26hMjISMyfPx9r164V7PdKELpArVYjMzOTP9jduHGD95v08vLCr7/+ilmzZkEulxuFBnE2R1xbsL6LELgkPzev5UGWdowxfP3111i3bh0OHTqE0NBQva6XIAwNZzPIddDa29sjNjYWMTEx+O233zB8+HAEBASgsrJS8BrEDcBWqVQGsWZijDUrNKqtrYWzszNfOdlScKu0tJQvpjh69KjRzIciCG3AGENRURHfvXbmzBmMGDECsbGx8PHxwW+//YY333wTpqamKCsrg7W1Na9BQosHcTZH3MBKQ3RZtFRopJnkv3dNMpkMv//+O95//31s2LAB8+fPF9R3SrQPCmgLCKVSiZMnT2Lbtm3Ytm0bSktL0atXL97Avbq6GjKZjB/K4enpqRND/Iehvr4eaWlpcHNzg5+fn8HWplAo+MCS5iATd3d3ODo6QiQSQalU4pVXXsGFCxeQkpJiFJ54BKErNP0mt2/fjqSkJIhEIsycORMvvfQSPD09IZPJUFpaCisrKz7BJiQNamxsRHp6Ouzt7TFkyBCDVnM2NTXxGlReXt7iIJOrV68iMjISzz//PD766COjqD4lCF2h6Te5ZcsWXLt2DT4+PnjzzTcRFRUFlUrFeydyhzohaZBCoUBaWhosLS0F0VH3oCQ/APzwww/497//jQMHDmDUqFEGXS9BGJrGxkYcPnwY27dvx++//w6lUokpU6Zg7ty5CAsL46sAhbgP4uYM6MLmqLM0NDTwGlRZWQl7e/tmGlReXo7o6GiYm5sjJSVF8NWnBKFLGGO4c+cOEhMT8dNPPyEzMxNeXl5YuHAhxGIxevbsyQ+rl8lksLS05DVIV0Na2wtnc8TNehOK/319fT3/fWkWGrm6ukIul2Pr1q1499138Z///Af/+Mc/DK7jROeggLYASU9P59tv7ezssGvXLpSXlyMiIgIxMTEICQlBTU0NZDIZzM3N+eA2F6g1FHV1dUhLS4OnpycGDBggGFFQqVTNbgC3b9/G4cOHUVpailu3buHYsWPo3r27oZdJEIKAMYaZM2fi7NmzWLhwIY4fP46kpCR4e3sjNjYWsbGx6NGjBx/ctrCw4DXIkBuqxsZGnD9/Xu+dIe3h3kEmBw4cwO3bt3H69Gk899xz+OKLLyiYTRD/P2fPnsXTTz+NRYsWwdbWFomJibhw4QLvNxkVFQWRSMRfT0LQIG0MwNYlXJKf0+21a9fCzMwMmZmZ2LdvH8aOHWvoJRKEYHj22Wdx5coVvPXWWzh69Ch27twJxhiioqIwefJkPP744/xQWyFokLYGYOsSuVzOB7ezsrKwbt06KBQKODo64q+//oKjo6Ohl0gQguDPP//EhAkT8P7778PGxgYJCQlITU3F4MGDIRaLERcXB19fX5SXl0MikRg8HsQNwFYoFHqxOeosmoVGGzduRHJyMsrLy/H//t//o6IiI4cC2gJEKpXiwIEDmD17NoD7/SaLi4sxceJExMbGIiwsjG/vMjU15TPfzs7OehWz2tpapKWloXv37ujXr5+ggkmaqNVqpKWlYd68eSgsLISdnR1iY2Px/vvvo1evXoZeHkEIgoSEBIwZM4YfAMn5TSYmJmL//v1wc3NDTEwMxGIx+vbtywdKzMzMeA1ycnLSmw5wNkcuLi4YNGiQYPUHuLvx27x5M/71r39BrVbDzs4OzzzzDL799ltBr5sg9EV1dTVSUlIgFosB/O03yQ1T4vwmxWIxoqKiYGVlxSesDaFBuhiArUsUCgWWLFmCTZs2wcbGBra2tli1ahUWLlxo6KURhCA4evQogoOD+QHxSqUSJ06cwLZt27Bz5040NDQgKioKYrEYY8eObWb1Y2pqyldN6kODuAHY5ubmRjM0986dO4iIiEBpaSnUajUcHR3xxx9/UJcIQeBugc6ZM2cwbtw4AHf3QOXl5di1axcSEhKQnJwMX19fiMViTJ48GQMHDmw2pFWf8SBD2xx1hoqKCmzZsgX//ve/0a9fPxQUFMDLyws5OTk0jNZI0VlA+4MPPsC+ffuQmZkJCwsLVFZWPvA1jDGsWbMGP/zwAyorK/HYY4/h22+/Rf/+/XWxRKOE85vkDnY3btzA+PHjERsbi9GjR6OxsRFSqRQikQju7u7w9PSEs7OzTg9YNTU1SEtLQ48ePeDr6yvooIxarcYbb7yBAwcOIDk5GTKZDDt27MAbb7xB/tldENIh7VNfX4+DBw8iISEBe/fu5ZNCYrEYAwYM4LshRCIRXy3g5OSkMw3ibI7c3d0xcOBAQesPABQXFyM8PBxPPvkkvv32W5w9exbZ2dn4xz/+YeilETqANEi7cH6TiYmJSExMxJkzZxAaGgqxWIyYmBjY2dnxgSV9aJC+BmBrC8YYtm3bhkWLFiEhIQFPPfUUjh8/DktLSzz++OOGXh6hA0iDtItKpcLp06f52UeVlZWIiIhAXFwcxo8fz5/DNPdBXGBJ2xrEDcC2tLREQECA4JNpwN1u3ri4OJSXl+PkyZO8d3ZoaChcXV0NvTxCB5AGaQ9uCOuePXuQmJiIgwcPokePHnzl9rBhw1BVVQWJRAKpVAoA/D5I2xqkOQA7MDBQEDZHD6KyshI7duzA6tWrsWzZMqxcuZKfvTR69GhDL4/oJDq788nlckydOhWvvfZau1/z8ccf44svvsDGjRtx9uxZ2NraIjw8HI2NjbpaptFhYmKC4OBgfPDBB8jLy8O5c+cwfPhwfPXVVwgODsbKlStx48YNeHt7QyQSIScnB8ePH0dubi5kMhnUarVW11NdXY20tDT07NlT0JXZwN1g9ttvv429e/fiyJEj8PX1xciRI/HRRx/pPJj99ddfo3fv3rCyskJYWBj++uuvNp+/bds2+Pn5wcrKCsOGDcP+/ft1ur6uCumQ9rGxscHkyZOxefNmlJSUYOPGjWhoaMDzzz+PUaNG4bvvvoNarYafnx8AIDs7m9cgrhpHW9TV1eH8+fPw9PQ0imC2RCJBVFQURo0ahe+//x4WFhYYM2aMXoLZpEGGgTRIu4hEIvTq1QtLly7F8ePHUVhYiBdeeAEHDx5EYGAgnnnmGRw8eBDe3t4YOnQogL81KC8vT6sa1NDQgPPnz8PJyckogtkAsHPnTixcuBC///47wsPDYW5ujvHjx+slmE0aZBhIg7SLqakpxowZg88//xwFBQU4ePAgfHx8sGrVKvTt2xdLlixBbm4ugoKCMGzYMABodhbTlgZxNkfW1tZGE8xuaGjAs88+C5lMhmPHjsHV1RUWFhaIiIjQeTCb9MdwkAZpD5FIBCcnJ8ycORM7duyARCLBe++9h8LCQkRERCAgIACffPIJamtrMWbMGPj7+8PExAS5ubk4duyY1uJBXGeIiYmJYDz7HwSXCFizZg0WLlyIlStXQiQSwcrKSi/BbNIg3aFzy5H4+HgsWbLkgdk4xhi6d++O119/Hf/6178A3P3F8/T0RHx8PKZPn67LZRo9jDFcvnwZCQkJSEhI4P0mY2NjMW7cOKjVakilUiiVSn7atKur60O1plVVVSE9PR19+vRB7969tfdhdIBarca///1vbNmyBampqRg4cKDe3nvr1q2YNWsWNm7ciLCwMGzYsAHbtm3DpUuXeEsHTU6fPo0nnngC69atQ3R0NH799Vd89NFHSE9P5w/oRMcgHdI9CoUCKSkp2L59O3bt2gWVSoXo6GiIxWIEBgaisrISEokEKpVKKxrE2Rx5e3sLvjMEuDtJOyoqCkOHDsXmzZv1uvkjDTI8pEG6hTEGqVSKnTt38n6TgwYNQlxcHMRiMTw8PCCTybSmQUIZgN0R9u7di7lz52Lz5s2YPHmyXt+bNMjwkAbpFrVajYyMDGzfvh2JiYkoKirChAkTIBaLERkZCQB85fbDnsWENAC7vTQ1NWHq1KkoKCjAyZMn0a1bN729N+mPMCAN0i11dXVISkpCYmIi9u3bBwcHB8TExCAuLg5hYWGora3lK7eVSiXc3Nzg4eEBNze3DmkQF8y2sLAQxADs9lBdXY09e/Zg1apVmDNnDtatW6dX3SQN0i2CCWhfv34dvr6+yMjIQGBgIP/4k08+icDAQHz++ee6XGaX4l6/yfPnz2P06NGIjY3FU089BRMTE0ilUsjl8mZi1pEAS2VlJTIyMtC3b1/Be08zxvDhhx/ixx9/xNGjRzFkyBC9vn9YWBhCQ0Px1VdfAbi76fXx8cHixYuxYsWK+54/bdo01NXVYe/evfxjI0eORGBgIDZu3Ki3dXclSIf0i6bf5K5du1BfX4+oqCjExsYiNDQUVVVVzTTI09OzQxsqzuaoZ8+e6Nu3r44/zcNTXl6OSZMmoV+/fti6davePeZIgwwPaZD+0PSbTExM5DuyYmNjERcXxw+17awGCXUAdlskJSVh5syZ+Pnnn/Hcc8/p/f1JgwwPaZD+YIwhJyeHD25fvnwZ48aNQ1xcHCZNmgQzMzM+uN1RDeIGYBtTZ4hcLseMGTOQl5eHU6dOoUePHnp9f9IfYUAapD8aGhpw+PBhJCYmYvfu3bC0tERMTAwmT56M0aNHo76+HlKpFBKJBE1NTc00qK14EGdzZGVlxVd/Cx1uDtTbb7+NadOm4bPPPtP7ukmDdItgfgtLSkoAAJ6ens0e9/T05P+NaB8ikQi+vr5Yvnw5zpw5g+vXr2Py5MnYvXs3RowYgddee40/jNnY2OD69es4duwYMjMzUVxcDIVC0ebPr6ioQHp6Ovr162cUwexPP/0UGzduxKFDh/QezOZaAidMmMA/ZmJiggkTJuDMmTMtvubMmTPNng8A4eHhrT6f0B6kQ9rBzMwM48aNwzfffIOioiLs3r0bbm5ueOONNxAYGIgPP/wQMpkMgwcPho2NDa5evYrU1FRkZWWhuLgYSqWy1Z/N2Rz16tXLKILZlZWVEIvF6NWrF37//Xe9B7NJg4wL0qCHRyQSwdXVFfPmzcPevXtRUlKCFStW4OLFixg3bhzGjh2LLVu2wMbGBsHBwR3SoNraWpw/fx7dunUzmmD20aNHMWvWLHz33XeYOnWq3t+fNMi4IA16eEQiEYYNG4Z3330XFy5cQFZWFsaMGYPvv/8e/fr1w8yZM3HixAn0798fw4cPh42NDa5du/ZADeJsjlxcXIwmmK1QKDBr1izk5OTg2LFjeg9mk/4YH6RBD4+1tTViY2MRHx+PkpISxMfHgzGG2bNno1+/fnj77bdRWFiI0NBQjBgxAnZ2ds3iQXfu3LkvHtTU1ITz58/DxsbGaILZtbW1SEpKwqpVqzB58mSDBLNJg3RPh/6PrlixAiKRqM0/Fy9e1NVaiU4gEonQs2dPLF26FMeOHeP9Jg8fPozRo0dj7ty5OHPmDNzd3WFvb48bN27g2LFjyMjIwO3btyGXy5v9vLKyMmRkZGDgwIHw8fEx0KdqH4wxfPHFF9iwYQMOHjyIgIAAva+htLQUKpWqQzflkpISuom3AemQccH5TW7YsIH3m+zVqxfWrFkDf39/rFmzBrdv38aQIUNgZ2eHGzduIDU1FRkZGfdtqCorK5GWloY+ffqgT58+BvxU7aO6uhpTpkyBu7s7tm3bBgsLC72vgTRI+5AGGRf3+k2uXbsWhYWFiIyMxGOPPYb//e9/MDU1RWhoKK9B3D5IU4Nqampw/vx59OjRQ/AzQziOHz+OGTNm4Msvv8QLL7xgkDWTBmkf0iDjQSQSwc/PDytXrkRaWhry8vIwceJEbN68GQMGDMBzzz2HI0eOoHfv3nxgqaV9UH19Pc6fPw83NzcMGjTIKPRHqVRi3rx5OH/+PFJTUw1iT0n6oxtIg4wHCwsLhIeH44cffsCdO3ewdetWWFlZ4dVXX4Wvry/+9a9/4fLlywgODsbIkSPh4OCAoqIiHDt2DOnp6bh9+za//3FwcMDQoUONIphdV1eHQ4cOYfXq1Zg0aRK++uorg6ybNEj3dMjE8/XXX8ecOXPafE5nK+a8vLwA3B2apemrJZFImrWbEJ1HJBLB29sbixYtwsKFCyGTybBjxw4kJibi/fffh5+fH+Li4hAeHg4nJyfcunUL+fn5cHZ2hqenJ0xNTZGfnw8/Pz90797d0B+nTRhj2LhxIz766CMkJSVh+PDhhl4SoSVIh4wXExMTjBw5kh/GmpGRgYSEBPznP//Ba6+9xvtNjh07Fo2NjSgqKkJeXh5cXFxgZ2eHW7duoX///oJPpgF3qwKeffZZ2NraYseOHbCysjL0kggtQRpkvNjb22PatGmYNm0a6uvrkZSUhISEBEyZMgX29vaIjY2FWCxGaGgoysrKeA1ycHBAbW0tfHx84Ovra+iP0S7OnDmD5557DuvXr8ecOXOMIgBGtA/SIONEJBKhX79+ePPNN7F8+XIUFRXx9pDLly/HiBEjIBaLIRaL4erqCqlUips3byIvLw8A4OzsjD59+hjFtaxUKvHKK6/g5MmTOH78uNHoJtE+SIOMEzMzMzz11FN46qmn8NVXX+HUqVPYvn07li5diqqqKkRGRkIsFuPpp58GcNf3v7CwEHV1dbCwsICjoyMUCgUsLS0N/Enapr6+HkeOHMHq1asxduxYbNy40SiC8ETn6FBA293dHe7u7jpZSJ8+feDl5YXk5GRerKqrq3H27NkOTcUl2odIJIKHhwcWLFiAV155BRUVFdi1axcSEhLw8ccfo2/fvhCLxYiIiICLiwuSkpLQvXt3ODk5QalUorGxUbABGsYYfvrpJ7z33nvYt28fRo4cabC1cH54Eomk2eMSiYS/Yd+Ll5dXh57/qEE61DUwMTFBSEgIQkJC8MEHH/B+k59//jkWLlyIcePGQSwWY8KECTh69ChUKhW8vb35a8Pd3V2wGlRfX4/nnnsOpqam2LVrF6ytrQ22FtIg7UMa1DWwsbHBlClTMGXKFDQ2NuLw4cNISEjA9OnTYWlpiejoaEyePBlyuRw7d+5EZGQkCgsL+eFUQtagc+fO4ZlnnsEHH3yABQsWGDQARhqkfUiDjB+RSIRevXph2bJlWLp0Ke7cuYPExEQkJiZi1apVCAwMhFgshq+vL37++We89dZbUKlUOHHiBJycnODh4QEPDw9BapBSqcTChQuRnJyM1NRUDBw40GBrIf3RDaRBxo+pqSmeeOIJPPHEE9iwYQPOnj2L7du3Y9WqVXj55ZcxceJEhIaGIj4+Hp9++il69+6NkpISXLp0CY6OjvD09BSkBjU0NCA5ORmrVq3CyJEj8dNPPxl0cCVpkO7RWaqiqKgImZmZKCoqgkqlQmZmJjIzM1FbW8s/x8/PDzt27ABw98a+ZMkSrF27Frt370Z2djZmzZqF7t27Iy4uTlfLJHD3u3dxccHcuXOxd+9eSCQSvP3227h48SIiIyMxfvx4LFu2DJcvX4a3tzekUilOnjyJv/76C4WFhWhoaDD0R+BhjGHTpk14++23sWvXLjz++OMGXY+FhQVCQkKQnJzMP6ZWq5GcnIxRo0a1+JpRo0Y1ez4AHD58uNXnE61DOmQctOY3+eOPP8LPzw//+Mc/+EORu7s7SkpKcPLkSZw7d05wGtTY2IgZM2ZALpdjz549sLOzM+h6SIMMC2mQcWBlZYWYmJhmfpMA8MILL2Dq1KlITU1FY2MjRowYAQ8PD0FrUEZGBuLi4rB69WosWrTI4NWcpEGGhTRI+HAdtIsXL8bRo0dx8+ZNzJ8/H/v27cPzzz+PjIwMHD16FI6Ojnjsscfg4eEh2LOYWq3GsmXLsG/fPhw5ckTvs4vuhfTH8JAGCR8TExOMGjUKn376Ka5cuYLU1FS4u7vjnXfewbVr17Bx40acPn0aAwYMwOOPPw4vLy/IZDJeg27cuIH6+npDfww0NjYiJSUFq1evRmBgIH755Zc2h1zqA9IgPcB0xOzZsxmA+/6kpKTwzwHAfv75Z/7varWarV69mnl6ejJLS0s2fvx4dunSJV0tkWgHP//8M7O0tGSjRo1idnZ2rHfv3mzx4sXs4MGDLD8/n504cYLt2rWLHT16lOXk5DCpVMrq6uoM8qe2tpb9+OOPzNbWlh0+fNjQXx3P77//ziwtLVl8fDzLy8tjr7zyCnNycmIlJSWMMcZmzpzJVqxYwT//1KlTzMzMjH3yyScsPz+frVmzhpmbm7Ps7GxDfQSjhXTIuNmzZw+zsbFh06ZNY2FhYczU1JSNGTOGffLJJyw7O5tdvHiRHT9+nNeg3NxcJpPJDKZB5eXlLDIykoWGhrKKigpDf308pEGGgzTIeDl+/Dizt7dnS5YsYa+99hrr1q0bc3JyYi+88ALbtm0bu3PnjuA06M8//2QuLi7sww8/ZGq12tBfIQ9pkOEgDTJOLl26xJydndnq1avZ//73PzZp0iRmYWHBBg8ezN566y32119/sdLSUnbp0qVmGpSTk2MwDaqpqWGvvvoqc3R0ZOfPnzf0V8hD+mNYSIOMj/r6eubj48PeeOMNlpWVxVavXs2GDBnCLCwsWEREBPv222/ZzZs3WXl5Obt06RIfD0pOTmbZ2dkGiQeVl5ezxMRE5ufnx2JiYlhTU5Ohv0Ye0iDdImKMMX0EzgnjgzGGOXPmYMaMGYiIiOD9JhMTE7F3717Y2dkhNjYWMTEx6Nu3L0pLS1FWVgZbW1t4eHjA09NTr9WJCQkJeO211/DHH39g0qRJenvf9vDVV19h/fr1KCkpQWBgIL744guEhYUBAMaOHYvevXvzFWEAsG3bNqxatQo3btxA//798fHHHwvuMxGErtm0aROsrKwwdepUMMZ4v8kdO3bgzJkzCA0NhVgsRlRUFCwtLSGTyVBWVgY7Ozu+HVdfGiSXyzFr1izcvHkTycnJcHFx0cv7thfSIILoGNevX8eff/6J559/HgCgUqlw6tQpXoOqqqoQERGBuLg4PPnkk6irq4NUKjWYBuXl5SEyMhILFy7EmjVrDF6ZfS+kQQTRfpRKJQ4cOICYmBgAd89kVVVV2LNnDxISEnDo0CH06NEDYrEYkydPhp+fH8rKyngNsrW15S0B9KFBarUaq1atwk8//YRDhw4Z1O6xJUh/CKJjZGVlwd/fn99LMMZw8eJFbN++HYmJicjNzcUTTzyBuLg4REdHw8nJCaWlpbwGWVtbN9MgXe5JmpqacPz4caxatQo9evTAzp07BefzTRqkO7p0QLu8vByLFy/Gnj17YGJigmeeeQaff/55mzf2sWPH4tixY80eW7BgATZu3Kjr5RoVnN9kYmIidu3aBQsLC8TExCA2NhYDBgxAeXk5SktLYW1t3Sy4rSsx2717N+bPn49ff/0VYrFYJ+9BEB2FNEg3MMaa+U2ePHkSAQEBiIuLQ1RUFOzt7ZttqHStQQqFAvPnz8elS5dw9OhRnfkKEkRHIQ3SDWq1GmfPnuWD2xKJBBMnToRYLMb48ePR1NQEiUSiNw26dOkSIiMjMW/ePHzwwQeCC2YTjy6kQbqhpqYG+/btQ0JCAg4cOAB3d3eIxWLExcUhMDCQD27r4yymVqvx7rvvYuPGjdi/fz/GjBmj1Z9PEJ2F9Ec3MMZw7do1PridkZGB0aNHQywWIzY2Fu7u7igrK4NEIkFpaSmsrKx4DbK3t9eqBsnlcpw4cQKrV6+Gm5sb9uzZY9DZRYT+6dIB7cjISBQXF+O7776DQqHA3LlzERoail9//bXV14wdOxYDBgzAe++9xz9mY2MDBwcHfSzZKJHL5UhJSUFCQgJ27twJtVqN6OhoxMbGYsiQIaioqEBpaSksLCz4TJ2Dg4PWxGz//v2YPXs2/u///g/PPvusVn4mQWgD0iDdwxiDVCrFzp07kZCQgNTUVAwaNIivGHB1deUPdbrQIKVSiQULFiArKwspKSnw9PTUwqciCO1AGqR71Go1MjIy+INdUVERJkyYALFYjIkTJ0KpVOpUg65du4aIiAhMnz4d69evh4mJzsbjEESHIQ3SPXV1dUhKSkJCQgL27dsHR0dHxMbGQiwWY/jw4aisrOQDS9rWILVajXXr1mHDhg3Yu3cvxo0bp6VPRRAPD+mP7mGMobCwkE/w//nnnwgLC+M1qHv37nyCTSaTwdzcnNcgR0fHh9IghUKBkydP4p133oGdnR32798PW1tbLX46whjosgHt/Px8DB48GOfOncPw4cMBAElJSZg0aRJu3bqF7t27t/i6sWPHIjAwEBs2bNDjarsOSqUSJ06cwLZt27Bz5040NDQgKioK0dHRCAwMRHV1NWQyGczMzPhM3cOI2ZEjR/D888/jhx9+wIwZM7T8aQii85AG6R/GGMrLy7Fr1y4kJCQgOTkZvr6+iI2NRWxsLDw9PSGTyVBaWqoVDVKpVFi0aBHOnDmD1NTUVv+fEoQhIA3SP4wx5OTkYNu2bdixYwcuX76McePGIS4uDhEREXwCTlsadOPGDURGRiI2Nhaff/45BbMJQUEapH8aGhr4Dtrdu3fD0tISMTExmDx5MkaOHImqqio+sPSwGqRWq/HJJ5/g448/xo4dOxAeHq6jT0UQHYf0R/8wxnD79m2+g/bUqVMIDAxEXFwcxGIxevbsiYqKCkgkEshkMpiamvL2bM7Ozh3SIIVCgT///BPvvPMOzMzMkJSUBHt7ex1+OkKodNmA9k8//YTXX38dFRUV/GNKpRJWVlbYtm0bJk+e3OLrxo4di9zcXDDG4OXlhZiYGKxevRo2Njb6WnqXQaVS4fTp09i+fTvvNxkeHo7Y2FiEhobywW2RSMRvqJycnNp9IDt27BimTp2Kb775BjNnzqQWW0JQkAYZlpb8Jr29vREXF4fY2Fj4+PhAJpNBJpPBxMSkwxsqtVqNJUuWICUlBSkpKejZs6cePhVBtB/SIMPC+U0mJCQgMTER2dnZzfwmTUxM+MBSZzTo1q1bCA8PR3h4OL755hsKZhOCgzTIsMjlchw9epTvoBWJRIiKisLkyZPx+OOPo7a2lg8siUQivmqyPWcxxhg+//xzrF27Ftu2bUNUVJSePhVBtA/SH8PCGINEImnWQTtkyBA+uN2vXz9UVFRAKpVCKpVCJBLB3d0dnp6ecHZ2blODlEolzp49izVr1kCpVOLw4cNwdHTU46cjhISZoRegK0pKSuDh4dHsMTMzM7i4uKCkpKTV1z3//PPo1asXunfvjgsXLuDNN9/EpUuXkJiYqOsldzlMTU0xZswYjBkzBv/973/x119/Yfv27VizZg0kEgmefvppiMVijBw5EnV1dcjOzgZjjD/Uubi4tCpmp06dwrRp07BhwwYKZhOChDTIsIhEIjg5OWHmzJmYOXNmM7/JSZMmwc3NjW+H8/X1hUwmQ3Z2NgA8cEOlVquxfPlyHDlyhILZhGAhDTIsIpEIgwYNwqpVq7By5Ureb3Lz5s1YunQpRo8ezQe3raysIJVK261BxcXFiIqKwrhx4/D1119TMJsQJKRBhsXCwgIRERGIiIjAt99+i2PHjmH79u1YsGABmpqaEBUVxQ+1bWho4DWoPWexb7/9Fu+//z62bNlCwWxCkJD+GBaRSAQvLy+8+uqrWLBgAcrKyvgO2nXr1qF///687//jjz+O6upqSKVS5OTkgDEGd3d3eHh4wNXVtZkGqVQqnDt3Du+99x4aGxtx5MgRCmY/4hhdQHvFihX46KOP2nxOfn5+p3/+K6+8wv/3sGHD0K1bN4wfPx7Xrl2Dr69vp3/uo46JiQlGjhyJkSNH4uOPP+b9JtetW9fMb3L06NFobGxEXl4eVCoVf6hzcXGBqakpAODs2bN49tlnsW7dOsyfP5+C2YReIQ0yTuzt7TF9+nRMnz6d95tMTEzElClTYG9vzwe3/fz8UFpaitzcXKhUKv5Qx22o1Go1Vq5cid27dyM1NRV9+vQx9EcjHjFIg4wPkUiEfv36YcWKFXjzzTdRWFjIt+QuX74cI0aM4DWIG2rbmgZJJBJER0cjLCwMP/zwA783Igh9QRpkfJiZmWH8+PEYP348vvrqK5w6dQrbt2/HkiVLUF1djcjISIjFYkyYMAFyuRwSiaTVs9gPP/yA1atXIz4+HlOmTDH0RyMeMUh/jA+RSAQ3NzfMnz8f8+bNQ1VVFXbv3o2EhAR89tln6NmzJ2JjY/nukZqaGkgkEly8eBFKpRJubm78UNsLFy5g7dq1qK6uRnJyMlxcXAz98QgDY3SWIzKZDGVlZW0+p2/fvti8eXOn2kzupa6uDnZ2dkhKSiJvMB3A+U1yw5Q4v0mxWIwnnngCCoUCEokECoUCu3btgqurKzZu3Ih///vf+Oc//0nBbELvkAZ1LVrzmxSLxRg6dCjKy8t5W4BNmzbBzMwMaWlpSE1NhZ+fn6GXTzyCkAZ1HRhjuHPnDhITE5GQkMD7TYrFYsTGxvJDbaVSKQ4fPoyMjAxcunQJYWFh2Lp1K8zMjK4uhegCkAZ1HdRqNc6ePcvbQ0qlUoSHh0MsFiM8PBwqlQpSqRQSiQQffPABqqqqkJeXh40bN2L+/PmGXj7xCEL607Worq7mO2iTkpLg4eHBB7eDg4NRW1sLqVSK69evY9asWbC2toaFhQVOnDhBRUXEXVgXJS8vjwFg58+f5x87ePAgE4lE7Pbt2+3+OSdPnmQAWFZWli6WSWigVqtZfn4+W7t2LQsKCmJmZmbsqaeeYhs2bGBZWVls8uTJzMTEhJmbm7NnnnmG7du3z9BLJohWIQ0yPpqamlhSUhJ76aWXmLu7O3Nzc2OzZ89mO3bsYOfOnWNBQUHMxMSEWVtbs2effZalp6cbeskE0SqkQcaFWq1mxcXF7Ntvv2UTJkxg5ubmLCAggL3zzjssLS2N7dmzh7m4uDBbW1tmY2PDpk6dysrLyw29bIJoFdIg40KlUrFz586xN998k/Xv359ZW1uzmJgY9uOPP7Lbt28zsVjMTE1NmaenJ7OxsWH/+Mc/DL1kgmgV0h/jo7a2lm3bto3NmDGDOTg4MB8fH7Zw4UK2d+9eNnHiRBYYGMicnZ1Z//79mZWVFfvmm28MvWRCAHTZgDZjjEVERLCgoCB29uxZdvLkSda/f382Y8YM/t9v3brFBg4cyM6ePcsYY+zq1avsvffeY+fPn2cFBQVs165drG/fvuyJJ54w1Ed4ZFGr1ezKlSvsP//5DxsxYgQfyH7nnXdYVlYWe+edd9jnn39ukLWVlZWx559/ntnb2zNHR0c2b948VlNT0+ZrnnzySQag2Z8FCxboacWEoSANMl4UCgVLTk5mr776KuvWrRuztrZmNjY2LCMjg2VlZbHVq1ezjIwMva+L9IfoCKRBxolarWalpaXsxx9/ZJMmTWLm5ubMysqKPfHEE6yhoYFlZWWxDz/8kKlUKr2vjTSI6AikQcaJSqViWVlZbNWqVWzIkCHMxMSEAWBvvPEGU6lULDs7m+3du9cgayMNItoL6Y/xUl9fz3bu3MlefPFFZmZmxkQiEXN3d2dFRUWMMcZyc3PZlStX9L4u0h/h0aUD2mVlZWzGjBnMzs6OOTg4sLlz5zb7hSsoKGAAWEpKCmOMsaKiIvbEE08wFxcXZmlpyfr168feeOMNVlVVZaBPQDB292B3+fJltnjxYqZWqw29HBYREcECAgLYn3/+yU6cOMH69evX7ObYEk8++SR7+eWXWXFxMf+Hfq+6PqRBXQOlUsni4+NZfHy8oZdC+kN0CNIg40etVrOKigq2aNEiVlZWZujlkAYRHYI0yPjZtGkTs7KyYs8//zydwwijgvTHuFGr1Wz69OksICCArVmzhh0+fNjQSyL9ESBG56FNEIYkPz8fgwcPxrlz5zB8+HAAQFJSEiZNmoRbt26he/fuLb5u7NixCAwMxIYNG/S4WoIguhKkPwRBGBLSIIJ49Pj000/h7++Pp59+2tBLIQ0iiEeMvXv3YuTIkXBzczP0Ukh/BIqJoRfQFfn666/Ru3dvWFlZISwsDH/99Vebz9+2bRv8/PxgZWWFYcOGYf/+/XpaKdFRzpw5AycnJ17EAGDChAkwMTHB2bNn23ztli1b4ObmhqFDh+Ktt95CfX29rpdLPKKQBnVNSH8IY4D0p+tCGkQYA6RB2uX1118XRDAbIA0ihA/pj3aJjo4WRDAbIP0RKhTQ1jJbt27FsmXLsGbNGqSnpyMgIADh4eGQSqUtPv/06dOYMWMG5s+fj4yMDMTFxSEuLg45OTl6XjnRHkpKSuDh4dHsMTMzM7i4uKCkpKTV1z3//PPYvHkzUlJS8NZbb2HTpk148cUXdb1c4hGENKjrQvpDCB3Sn64NaRAhdEiDujakQYSQIf3p2pD+CBRDe550NUaMGMEWLlzI/12lUrHu3buzdevWtfj85557jkVFRTV7LCwsjIzi9cybb755n1n/vX/y8/PZBx98wAYMGHDf693d3Ts0aTc5OZkBYFevXtXmxyAI0iAjhPSH6CqQ/hgnpEFEV4E0yDghDSK6AqQ/xgnpj3FjppMo+SOKXC5HWloa3nrrLf4xExMTTJgwAWfOnGnxNWfOnMGyZcuaPRYeHo6dO3fqcqnEPbz++uuYM2dOm8/p27cvvLy87suyKpVKlJeXw8vLq93vFxYWBgC4evUqfH19O7xegmgJ0iDjhPSH6AqQ/hgvpEFEV4A0yHghDSKMHdIf44X0x7ihgLYWKS0thUqlgqenZ7PHPT09cfHixRZfU1JS0uLz22pbILSPu7s73N3dH/i8UaNGobKyEmlpaQgJCQEAHD16FGq1mhen9pCZmQkA6NatW6fWSxAtQRpknJD+EF0B0h/jhTSI6AqQBhkvpEGEsUP6Y7yQ/hg35KFNEB1g0KBBiIiIwMsvv4y//voLp06dwqJFizB9+nR+su3t27fh5+fHD4G4du0a3n//faSlpeHGjRvYvXs3Zs2ahSeeeAL+/v6G/DgEQRgRpD8EQRgS0iCCIAwJaRBBEIaC9EeYUEBbi7i5ucHU1BQSiaTZ4xKJpNU2BC8vrw49nzA8W7ZsgZ+fH8aPH49Jkybh8ccfx/fff8//u0KhwKVLl/jptRYWFjhy5AgmTpwIPz8/vP7663jmmWewZ88eQ30EootCGtT1If0hhArpz6MBaRAhVEiDHg1IgwghQvrzaED6IzxEjDFm6EV0JcLCwjBixAh8+eWXAAC1Wo2ePXti0aJFWLFixX3PnzZtGurr65v9Uo8ePRr+/v7YuHGj3tZNEETXgDSIIAhDQfpDEIQhIQ0iCMJQkP4QhAEw9FTKrsbvv//OLC0tWXx8PMvLy2OvvPIKc3JyYiUlJYwxxmbOnMlWrFjBP//UqVPMzMyMffLJJyw/P5+tWbOGmZubs+zsbEN9BIIgjBjSIIIgDAXpD0EQhoQ0iCAIQ0H6QxD6h4ZCaplp06ZBJpPhnXfeQUlJCQIDA5GUlMQb/hcVFcHE5G+nl9GjR+PXX3/FqlWr8Pbbb6N///7YuXMnhg4daqiPQBCEEUMaRBCEoSD9IQjCkJAGEQRhKEh/CEL/kOUIQRAEQRAEQRAEQRAEQRAEYRTQUEiCIAiCIAiiS/H111+jd+/esLKyQlhYGD9xviXi4+MhEoma/bGystLjagmC6EqQ/hAEYUhIg4hHBQpod3FIzAiCMBSkPwRBGIKtW7di2bJlWLNmDdLT0xEQEIDw8HBIpdJWX+Pg4IDi4mL+T2FhoR5XTBBEV4H0hyAIQ0IaRDxKUEC7C0NiRhCEoSD9IQjCUHz22Wd4+eWXMXfuXAwePBgbN26EjY0Nfvrpp1ZfIxKJ4OXlxf/hPC8JgiA6AukPQRCGhDSIeJSggHYXhsSMIAhDQfpDEIQhkMvlSEtLw4QJE/jHTExMMGHCBJw5c6bV19XW1qJXr17w8fGBWCxGbm6uPpZLEEQXgvSHIAhDQhpEPGpQQLuLQmJGEIShIP0hCMJQlJaWQqVS3ZcQ8/T0RElJSYuvGThwIH766Sfs2rULmzdvhlqtxujRo3Hr1i19LJkgiC4C6Q9BEIaENIh41KCAdheFxIwgCENB+kMQhDExatQozJo1C4GBgXjyySeRmJgId3d3fPfdd4ZeGkEQXRzSH4IgDAlpEGHMUECb4OnKYvbBBx9g9OjRsLGxgZOTU7tewxjDO++8g27dusHa2hoTJkzAlStXdLtQgnhE6cr6A5AGEYS+cHNzg6mpKSQSSbPHJRIJvLy82vUzzM3NERQUhKtXr+piiQaBNIggdA/pT+uQBhGE7iENahnSn64LBbS7KCRmzZHL5Zg6dSpee+21dr/m448/xhdffIGNGzfi7NmzsLW1RXh4OBobG3W4UoIwfkh/7oc0iCD0g4WFBUJCQpCcnMw/plarkZycjFGjRrXrZ6hUKmRnZ6Nbt266WqbeIQ0iCN1D+tM6pEEEoXtIg1qG9KcLw4guy4gRI9iiRYv4v6tUKubt7c3WrVvXrtcrlUo2cOBAtnTpUl0tUe/8/PPPzNHR8YHPU6vVzMvLi61fv55/rLKykllaWrLffvtNhyskiK4B6U/LkAYRhO75/fffmaWlJYuPj2d5eXnslVdeYU5OTqykpIQxxtjMmTPZihUr+Oe/++677ODBg+zatWssLS2NTZ8+nVlZWbHc3FxDfQSdQRpEELqF9KdtSIMIQreQBrUO6U/Xw8zQAXVCdyxbtgyzZ8/G8OHDMWLECGzYsAF1dXWYO3cuAGDWrFnw9vbGunXrAADvvfceRo4ciX79+qGyshLr169HYWEhXnrpJUN+DINQUFCAkpKSZkPtHB0dERYWhjNnzmD69OkGXB1BCB/Sn4eDNIggOs+0adMgk8nwzjvvoKSkBIGBgUhKSuJ9/YuKimBi8neTYkVFBV5++WWUlJTA2dkZISEhOH36NAYPHmyoj2BwSIMIonOQ/mgH0iCC6BykQQ8P6Y/xQAHtLgyJWefhBtd1ZKgdQRB/Q/rzcJAGEcTDsWjRIixatKjFf0tNTW329//+97/473//q4dVGQ+kQQTReUh/Hh7SIILoPKRBDwfpj/FAHtpdnEWLFqGwsBBNTU04e/YswsLC+H9LTU1FfHw8//f//ve//HNLSkqwb98+BAUFGWDV7WPFihUQiURt/rl48aKhl0kQjyxdWX8A0iCCIAwLaRBBEIaENIggCENB+kMAVKFNGDGvv/465syZ0+Zz+vbt26mfzQ2uk0gkzQYiSCQSBAYGdupnEgTRtSANIgjCkJAGEQTRGsePH8f69euRlpaG4uJi7NixA3FxcW2+JjU1FcuWLUNubi58fHywatWqNjWGNIggiJYg/SH0BQW0CaPF3d0d7u7uOvnZffr0gZeXF5KTk3nRqq6uxtmzZzs0HZcgiK4LaRBBEIaENIggiNaoq6tDQEAA5s2bhylTpjzw+QUFBYiKisKrr76KLVu2IDk5GS+99BK6deuG8PDwFl9DGkQQREuQ/hD6ggLaxCNBUVERysvLUVRUBJVKhczMTABAv379YGdnBwDw8/PDunXrMHnyZIhEIixZsgRr165F//790adPH6xevRrdu3d/YHaRIAjiXkiDCIIwJKRBBPFoERkZicjIyHY/f+PGjejTpw8+/fRTAMCgQYNw8uRJ/Pe//201oNQRSIMI4tGB9IfQFxTQJh4J3nnnHfzf//0f/3fOmzclJQVjx44FAFy6dAlVVVX8c5YvX466ujq88sorqKysxOOPP46kpCRYWVnpde0EQRg/pEEEQRgS0iCCINrizJkzmDBhQrPHwsPDsWTJEq38fNIggiBag/SH6Cwixhgz9CIIgiAIgiAIgiAIgtAuIpHogR62AwYMwNy5c/HWW2/xj+3fvx9RUVGor6+HtbW1HlZKEERXg/SH0CUmhl4AQRAEQRAEQRAEQRAEQRAEQbQHCmgTBEEQBEEQBEEQxCOKl5cXJBJJs8ckEgkcHByoOpIgCJ1C+kN0FgpoEwRBEARBEARBEMQjyqhRo5CcnNzsscOHD2PUqFEGWhFBEI8KpD9EZ6GANkEQBEEQBEEQBEF0EWpra5GZmYnMzEwAQEFBATIzM1FUVAQAeOuttzBr1iz++a+++iquX7+O5cuX4+LFi/jmm2/wxx9/YOnSpYZYPkEQRgzpD6EvaCgkQRAEQRAEQRAEQXQRUlNTMW7cuPsenz17NuLj4zFnzhzcuHEDqampzV6zdOlS5OXloUePHli9ejXmzJmjv0UTBNElIP0h9AUFtAmCIAiCIAiCIAiCIAiCIAijgCxHCIIgCIIgCIIgCIIgCIIgCKOAAtoEQRAEQRAEQRAEQRAEQRCEUUABbYIgCIIgCIIgCIIgCIIgCMIooIA2QRAEQRAEQRAEQRAEQRAEYRRQQJsgCIIgCIIgCIIgCIIgCIIwCiigTRAEQRAEQRAEQRAEQRAEQRgFFNAmCIIgCIIgCIIgCIIgCIIgjAIKaBMEQRAEQRAEQRAEQRAEQRBGAQW0CYIgCIIgCIIgCIIgCIIgCKOAAtoEQRAEQRAEQRAEQRAEQRCEUUABbYIgCIIgCIIgCIIgCIIgCMIo+P8AqeRtvNccuR0AAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 1800x1200 with 10 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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       "text/plain": [
        "<Figure size 1800x1200 with 10 Axes>"
       ]
@@ -383,40 +539,66 @@
    ],
    "source": [
     "### Plot a fixed number of states\n",
-    "N_STATES = 10 # should be even\n",
+    "SHOW_N_STATES = 10 # should be even\n",
     "# skip some particles to make the plot more readable\n",
-    "SKIP_NTH_PARTICLE = 10\n",
+    "SHOW_NTH_PARTICLE = 1\n",
     "\n",
+    "particles_in_time = utils.to_particles_3d(sol)\n",
     "\n",
-    "fig, axs = plt.subplots(2, N_STATES//2, subplot_kw={'projection': '3d'})\n",
+    "## Show the particles in 3D\n",
+    "fig, axs = plt.subplots(2, SHOW_N_STATES//2, subplot_kw={'projection': '3d'})\n",
     "\n",
     "for i, ax in enumerate(axs.flat):\n",
-    "    nth = int(sol.shape[0] / N_STATES) * i\n",
-    "    p = utils.to_particles(sol[nth])[::SKIP_NTH_PARTICLE]\n",
+    "    nth = int(particles_in_time.shape[0] / SHOW_N_STATES) * i\n",
+    "    p = particles_in_time[nth][::SHOW_NTH_PARTICLE]\n",
     "    ax.scatter(p[:,0], p[:,1], p[:,2], cmap='viridis', c=range(p.shape[0]))\n",
     "    ax.set_title(f\"t={t_range[nth]:.2g} (step {nth})\")\n",
-    "# set size\n",
-    "fig.set_size_inches(18, 12)\n",
     "\n",
+    "fig.set_size_inches(18, 12)\n",
     "plt.show()\n",
     "\n",
-    "# # Also show the velocities\n",
-    "# scale = 1e-2\n",
-    "# fig = plt.figure()\n",
-    "# ax = fig.add_subplot(111, projection='3d')\n",
-    "# p_reduced = plast[::10]\n",
-    "# ax.quiver(p_reduced[:,0], p_reduced[:,1], p_reduced[:,2], p_reduced[:,3], p_reduced[:,4], p_reduced[:,5], length=0.1, normalize=True)\n",
-    "# plt.show()"
+    "# show some phase space diagrams\n",
+    "# fig, axs = plt.subplots(2, SHOW_N_STATES//2, sharex=True, sharey=True)\n",
+    "# for i, ax in enumerate(axs.flat):\n",
+    "#     r = []\n",
+    "#     v = []\n",
+    "#     for j in range(t_range.size):\n",
+    "#         p = utils.to_particles(sol[j])\n",
+    "#         print(p.shape)\n",
+    "#         r.append(np.linalg.norm(p[i,:3]))\n",
+    "#         v.append(np.linalg.norm(p[i,3:6]))\n",
+    "#     ax.plot(r, v)\n",
+    "#     ax.set_title(f\"particle {i}\")\n",
+    "\n",
+    "## Show the 2D orbits of selected particles\n",
+    "fig, axs = plt.subplots(2, SHOW_N_STATES//2, sharex=True, sharey=True)\n",
+    "\n",
+    "for i, ax in enumerate(axs.flat):\n",
+    "    nth = int(particles_in_time.shape[0] / SHOW_N_STATES) * i\n",
+    "    x = particles_in_time[:,i,0]\n",
+    "    y = particles_in_time[:,i,1]\n",
+    "    ax.scatter(x, y, c=range(t_range.size))\n",
+    "    ax.set_title(f\"particle {nth}\")\n",
+    "\n",
+    "    ax.set_xlabel('x')\n",
+    "    ax.set_ylabel('y')\n",
+    "\n",
+    "# Share x and y axis\n",
+    "for ax in axs.flat:\n",
+    "    ax.label_outer()\n",
+    "\n",
+    "fig.set_size_inches(18, 12)\n",
+    "plt.show()\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -426,7 +608,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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HBz/88APOnDmDGTNmYNKkSUhISKi27U2bNsHS0hJHjx7F0qVL8dZbb2Hv3r0AAK1Wi+HDh+PQoUPYvHkzUlJSsHjxYt0YPpcvX8YTTzyBMWPG4NSpU9i2bRsOHjyIl156qV7fNyIiAo5euYmo784AADyc5TAyEu+JWdEHQly1ahWWLVuGnJwceHl5YeXKlfD396+17dmzZxEVFYXExERcvXoVH3zwQY1OuhqNBgsXLsTmzZuRk5MDJycnhIaG4o033mi2R5PvVGjQO2pPs2z7flLeCoaFacNP4cSJExEZGYmrV68CAA4dOoStW7fiwIED/7juk08+idmzZwMAXn/9dXzwwQfYv38/evToUaNtcXEx1q9fj82bN2Po0KEAqkJIp06d6tx+RkYGHB0dERQUBBMTE7i6uup+Huzs7CCVSmFtbQ1HR0fdOs7Oznj11Vd17+fMmYM9e/bgyy+/rPaz5OnpiQULFgAAunXrhtjYWMTHx+Pxxx/Hvn37kJCQgHPnzqF79+4AADc3N9260dHRmDBhgu7nrVu3bvjoo48QGBiI1atXw8zM7B+/d0REhuza7VLM2pKESq2AEZ4dET7EXdR6RL0CtG3bNkRERGDBggVISkqCl5cXgoODddMI/F1paSnc3NywePHian8A77VkyRKsXr0asbGxOHfuHJYsWYKlS5di5cqVzXkobUqHDh0wYsQIxMXFYePGjRgxYgTs7e3rta6np6fua4lEAkdHxzrP1+XLl1FeXo6AgADdMjs7u1rD0l1jx47FnTt34ObmhunTp+Obb75BZWXlfWvSaDR4++234eHhATs7O1hZWWHPnj3IyMios3agapqKu7UnJyejU6dOuvDzdydPnkRcXBysrKx0r+DgYGi1WqSlpd23PiIiQ1daXonpnybiVkk5+jjZYNmznqKPlybqFaAVK1Zg+vTputsva9aswQ8//IANGzZg/vz5Ndr7+fnBz88PAGr9HAD++OMPjBo1CiNGjABQ1b/kiy++qHE7pCmZm0iR8lZws23/fvttrClTpuhu36xatare65mYmFR7L5FIoNVqG13H37m4uCA1NRX79u3D3r17MXv2bCxbtgy//vprjX3ftWzZMnz44YeIiYmBh4cHLC0tMXfuXJSXl9e79rvTV9SluLgYM2fO1PVHutffO48TEdFftFoB//7yJM5dL4S9lSnWTvZt1N2LpiZaBeXl5UhMTERkZKRumZGREYKCgnD48OFGb/fhhx/G2rVrceHCBXTv3h0nT57EwYMHsWLFijrXUavVUKvVuveFhYUN2qdEImkVJ7MhnnjiCZSXl0MikSA4uHnCW9euXWFiYoKjR4/qQsLt27dx4cIFBAYG1rmeubk5Ro4ciZEjRyI8PBw9e/bE6dOn0b9/f5iamkKj0VRrf+jQIYwaNQoTJ04EUNWf58KFC+jdu3e9a/X09MS1a9d0Pzd/179/f6SkpMDdXdxLtkREbc3KXy7hpzM5MJFKsGaiD5xt7/8/nC1FtL/a+fn50Gg0UCgU1ZYrFAqcP3++0dudP38+CgsL0bNnT0ilUmg0Grz77ruYMGFCnetER0dj0aJFjd5nWySVSnHu3Dnd183BysoKU6dOxbx589C+fXs4ODjgv//9L4yM6r7zGhcXB41Gg4CAAFhYWGDz5s0wNzdH586dAVRd0fvtt9/w/PPPQyaTwd7eHt26dcP27dvxxx9/oF27dlixYgVyc3MbFIACAwPx6KOPYsyYMVixYgXc3d1x/vx5SCQSPPHEE3j99dfx0EMP4aWXXsK0adNgaWmJlJQU7N27F7GxsQ/8vSIi0ke7z+Tgg30XAADvjO4LX6WdyBX9Re+eAvvyyy+xZcsWfP7550hKSsKmTZuwfPlybNq0qc51IiMjoVKpdK/MzMwWrFg8NjY2sLGxadZ9LFu2DIMGDcLIkSMRFBSERx55BD4+PnW2t7W1xbp16zBw4EB4enpi3759+P7779G+fXsAwFtvvYX09HR07doVHTp0AAC88cYb6N+/P4KDgzF48GA4Ojpi9OjRDa7166+/hp+fH8aPH4/evXvjtdde011t8vT0xK+//ooLFy5g0KBB8Pb2RlRUFJycnBr+TSEiMgDnrhci4stkAEDow0o859e6ugtIhMY+S/2AysvLYWFhge3bt1f7YxUSEoKCggJ89913911fqVRi7ty5NZ4Cc3Fxwfz58xEeHq5b9s4772Dz5s31vrJUWFgIuVwOlUpVIyCUlZUhLS0NXbp04ZM/VCf+nBCRIbtVUo6nYg/i2u07GOjeHpvC/GEsbf5rLvf7+/13ol0BMjU1hY+PD+Lj43XLtFot4uPjMWDAgEZvt7S0tMYtFqlU2qQddYmIiKh2FRotZm1OxLXbd9C5vQVix/dvkfDTUKL23I2IiEBISAh8fX3h7++PmJgYlJSU6J4Kmzx5MpydnREdHQ2g6qpRSkqK7uusrCwkJyfDyspK1zl15MiRePfdd+Hq6oo+ffrgxIkTWLFiBaZMmSLOQRIRERmQRd+fxdG0W7CSGWPdZF+0szQVu6RaiRqAnnvuOdy4cQNRUVHIyclBv379sHv3bl3H6IyMjGpXc7Kzs6tN17B8+XIsX74cgYGBukH8Vq5ciTfffBOzZ89GXl4enJycMHPmTERFRbXosRERERmazUeuYvORDEgkQMxz/dBd0fzzSTaWaH2AWjP2AaIHxZ8TIjI0R67cxMRPjqJSK2BecA9RRnpuE32A2jrmRrof/nwQkSHJvFWK2X9OczHSywmzB3cVu6R/xADUQHdHEy4tLRW5EmrN7v581DV6NRGRvihRV2L6p8dxq6QcfZ1tsHSM+NNc1EfbGr64FZBKpbC1tdXNIWVhYdEmTjS1DEEQUFpairy8PNja2jbbIJNERK2BVisg4stknM8pgr2VDGsn+cLctG383mMAaoS7E7HWNQkoka2tbZ0T9hIR6YsP4y9iz9lcmEqN8PEkHzi1kmku6oMBqBEkEgk6duwIBwcHVFRUiF0OtTImJia88kNEeu+n09fxYfxFAMA7T/eFT+d2IlfUMAxAD0AqlfIPHRERGZyU7EJEfHkSADBlYBeM83URuaKGYydoIiIiqrebxWpM//Q47lRoMKibPf7zZE+xS2oUBiAiIiKql/JKLWZtSUJWwR0oW/E0F/XRNqsmIiKiFiUIAhbsPIuEP6e5+CTEF3KLtjvUBwMQERER/aPNR67ii4SqaS4+Gt8P7g6td5qL+mAAIiIiovv643I+Fn1fNRn5a8E98VhPhcgVPTgGICIiIqpTxs1ShP85zcWofk54MdBN7JKaBAMQERER1ar4z2kubpdWwLOTHEvayDQX9cEARERERDVotQIitiUjNbcIHayrprkwM9Gfse8YgIiIiKiGmH0X8HPKX9NcOMrNxC6pSTEAERERUTU/nLqOj365BAB47xkP9HdtW9Nc1AcDEBEREemcyVLh318lAwCmPdIFz/p0EregZsIARERERACAG0VqzPj0OMoqtHi0ewfMH942p7moDwYgIiIiqprmYnMislVlcLO3xMrx3m12mov60N8jIyIionoRBAFR353B8au3YS0zxroQX8jN2+40F/XBAERERGTgPj18FVuPZVZNc/GCN7p2sBK7pGbHAERERGTADl3Kx1u7qqa5iBzeE0N6OIhcUctgACIiIjJQV2+WIPzzJGi0Ap72dsb0QfoxzUV9MAAREREZoKKyCkzbdBwFpRXwcrFF9DMeejPNRX0wABERERkYrVbAK9uScTGvGA7WMqyd5KNX01zUBwMQERGRgVmx9wL2ncuDqbER1k72hcJGv6a5qA8GICIiIgPy/clsxO6vmuZi8TMe6OdiK25BImEAIiIiMhBnslSYt/0kAGDmo254pr9+TnNRHwxAREREBuBGkRrT/5zmYnCPDnjtCf2d5qI+GICIiIj0nLpSgxc3J+K6qgxuHSzx4fPekBoZzhNftWkVAWjVqlVQKpUwMzNDQEAAEhIS6mx79uxZjBkzBkqlEhKJBDExMTXa3P3s76/w8PBmPAoiIqLWRxAEvPntGSRevQ1rM2N8Mln/p7moD9ED0LZt2xAREYEFCxYgKSkJXl5eCA4ORl5eXq3tS0tL4ebmhsWLF8PR0bHWNseOHcP169d1r7179wIAxo4d22zHQURE1BrF/ZGOL49fg5EEiH2hP9wMYJqL+hA9AK1YsQLTp09HWFgYevfujTVr1sDCwgIbNmyotb2fnx+WLVuG559/HjKZrNY2HTp0gKOjo+61a9cudO3aFYGBgc15KERERK3KwYv5eOeHcwCA/zzZC4HdO4hcUeshagAqLy9HYmIigoKCdMuMjIwQFBSEw4cPN9k+Nm/ejClTphjUCJdERGTY0vP/mubimf7OmPpIF7FLalWMxdx5fn4+NBoNFApFteUKhQLnz59vkn18++23KCgoQGhoaJ1t1Go11Gq17n1hYWGT7JuIiEgMRWUVmPbpcajuVKCfiy3ee9qwprmoD9FvgTW39evXY/jw4XBycqqzTXR0NORyue7l4uLSghUSERE1HY1WwNytybiUVwyFjWFOc1EfogYge3t7SKVS5ObmVluem5tbZwfnhrh69Sr27duHadOm3bddZGQkVCqV7pWZmfnA+yYiIhLD+z+nIv78n9NcTPKFgwFOc1EfogYgU1NT+Pj4ID4+XrdMq9UiPj4eAwYMeODtb9y4EQ4ODhgxYsR928lkMtjY2FR7ERERtTXfJWfhfwcuAwCWjvGEl4FOc1EfovYBAoCIiAiEhITA19cX/v7+iImJQUlJCcLCwgAAkydPhrOzM6KjowFUdWpOSUnRfZ2VlYXk5GRYWVnB3d1dt12tVouNGzciJCQExsaiHyYREVGzOnWtAK9tPwUAeDGwK0Z7O4tcUesmejJ47rnncOPGDURFRSEnJwf9+vXD7t27dR2jMzIyYGT014Wq7OxseHt7694vX74cy5cvR2BgIA4cOKBbvm/fPmRkZGDKlCktdixERERiyCsqw4xPE6Gu1OKxng6YF9xD7JJaPYkgCILYRbQ2hYWFkMvlUKlUvB1GREStmrpSg+fXHsGJjAJ07WCJb8IHwsbMMEd6bsjfb71/CoyIiEhfCYKA/35zBicyCmBjZoxPQvwMNvw0FAMQERFRG7XhUDq2J/41zUUXe0uxS2ozGICIiIjaoN8u3MC7P1Q9FPTfEb3xKKe5aBAGICIiojYmLb8EL32eBK0AjPXphCkDlWKX1OYwABEREbUhhWUVmLbpGArLKtHf1RbvPN2X01w0AgMQERFRG6HRCvi/L07g8o0SdJSbYc0kH8iMOc1FYzAAERERtRFL95zH/tQbkN2d5sKa01w0FgMQERFRG7Aj6Ro+/vUKAGDps57w6CQXuaK2jQGIiIiolfvjUj5e/7pqmovZg7tiVD9Oc/GgGICIiIhasdScIsz8LBEVGgH/8uyIV4dxmoumwABERETUSuWoyhC6MQFF6kr4K+2wfKwXjIz4xFdTYAAiIiJqhYrVlQiLO4brqjK4dbDE2sk+MDPhE19NhQGIiIiolanQaDF7SxLOXS+EvZUpNoX5w9bCVOyy9AoDEBERUStSNcHpafx24QbMTaTYEOoHFzsLscvSOwxARERErcjKXy7hy+N3Jzj1hmcnW7FL0ksMQERERK3E9sRrWLH3AgDgrVF9MbSXQuSK9BcDEBERUStw6FI+5v851s+LgV0x8aHOIlek3xiAiIiIRHY+pxAvfpaISq2AkV5OeC2YY/00NwYgIiIiEV1X3UHohmNVY/10scPysZ4c66cFMAARERGJpKisAmEbjyGnsAzuDlZYN8mXs7u3EAYgIiIiEdwd6+d8ThHsrWTYGOoHuYWJ2GUZDAYgIiKiFiYIAiJ3nMbvF/NhbiLFRo710+IYgIiIiFrYh/EXsT2xaqyfVRO84dFJLnZJBocBiIiIqAV9dTwTMfsuAgDeGe2Bx3pyrB8xMAARERG1kN8v3kDkjtMAgNmDu+KFAFeRKzJcDEBEREQt4Nz1QszanIRKrYBR/Zzw6jCO9SMmBiAiIqJmdl11B2Ebj6FYXYmALnZY+izH+hEbAxAREVEzKrxnrJ9uDlZYy7F+WgUGICIiomZSXqnF7M1VY/10sJZhYxjH+mktGICIiIiawd2xfg5eyoeFadVYP53acayf1oIBiIiIqBl8sO8ivk66BqmRBKsm9EdfZ47105qIHoBWrVoFpVIJMzMzBAQEICEhoc62Z8+exZgxY6BUKiGRSBATE1Nru6ysLEycOBHt27eHubk5PDw8cPz48WY6AiIiouq+PJaJj+LvjvXTF0N6OIhcEf2dqAFo27ZtiIiIwIIFC5CUlAQvLy8EBwcjLy+v1valpaVwc3PD4sWL4ejoWGub27dvY+DAgTAxMcFPP/2ElJQUvP/++2jXrl1zHgoREREA4NcLNxD5TdVYPy8Nccd4f4710xpJBEEQxNp5QEAA/Pz8EBsbCwDQarVwcXHBnDlzMH/+/Puuq1QqMXfuXMydO7fa8vnz5+PQoUP4/fffG11XYWEh5HI5VCoVbGxsGr0dIiIyLGezVRi35jBKyjV42tsZK8Z5QSLh4+4tpSF/v0W7AlReXo7ExEQEBQX9VYyREYKCgnD48OFGb3fnzp3w9fXF2LFj4eDgAG9vb6xbt+6+66jVahQWFlZ7ERERNUR2wR1MiTuGknINBri1x5Ixngw/rZhoASg/Px8ajQYKRfU5UBQKBXJychq93StXrmD16tXo1q0b9uzZg1mzZuHll1/Gpk2b6lwnOjoacrlc93JxcWn0/omIyPCo7lQgdGMCcgvV6K6wwppJPjA1Fr2bLd2H3p0drVaL/v3747333oO3tzdmzJiB6dOnY82aNXWuExkZCZVKpXtlZma2YMVERNSWlVdqMWtzIi7kFsPBWoaNYf6Qm3Osn9ZOtABkb28PqVSK3Nzcastzc3Pr7OBcHx07dkTv3r2rLevVqxcyMjLqXEcmk8HGxqbai4iI6J8IgoD5X5/CH5dvwtJUig2hfnC2NRe7LKoH0QKQqakpfHx8EB8fr1um1WoRHx+PAQMGNHq7AwcORGpqarVlFy5cQOfOnRu9TSIiotqs2HsBO05kcayfNshYzJ1HREQgJCQEvr6+8Pf3R0xMDEpKShAWFgYAmDx5MpydnREdHQ2gquN0SkqK7uusrCwkJyfDysoK7u7uAIBXXnkFDz/8MN577z2MGzcOCQkJWLt2LdauXSvOQRIRkV7ampCBlb9cAgC8O7ovBnOsnzZF1MfgASA2NhbLli1DTk4O+vXrh48++ggBAQEAgMGDB0OpVCIuLg4AkJ6eji5dutTYRmBgIA4cOKB7v2vXLkRGRuLixYvo0qULIiIiMH369HrXxMfgiYjofg6k5mHqpuPQaAXMecwd/x7WQ+ySCA37+y16AGqNGICIiKguZ7JUeO7jqrF+nvF2xvsc66fVaBPjABEREbU1WfeM9fNw1/ZYzLF+2iwGICIionpQ3alA2MYE5BWp0UNhzbF+2jieOSIion+grtRg5mfHcSG3GAobGTaG+cHGjGP9tGUMQERERPchCAJe334KR67cgpXMGBtD/eHEsX7aPAYgIiKi+3j/5wv4NjkbUiMJ/jehP3o78eEYfcAAREREVIfPj2Ygdn/VWD/RT3vg0e4dRK6ImgoDEBERUS32n8/Dm9+dAQC8PLQbxvlxomx9wgBERET0N2eyVAj/PAkarYAx/TvhlaBuYpdETYwBiIiI6B7XbpciLO4YSss1eMTdHtHPeHCsHz3EAERERPQnVWkFQjcew40iNXo6WuN/E/tzrB89xbNKRESEqrF+Znx2HJfyiuFoY8axfvQcAxARERk8rVbAvK9O4Wjan2P9hPmho5xj/egzBiAiIjJ4y39Oxc6T2TA2kmD1xP7o1ZFj/eg7BiAiIjJoW45exf8OXAYARD/jgUHdONaPIWAAIiIig/XL+Vy8+W3VWD9zg7phrC/H+jEUDEBERGSQTl0rQPiWE9AKwFifTvi/oRzrx5AwABERkcHJvFWKKXHHcadCg0Hd7PEex/oxOAxARERkUKrG+klAfvGfY/1M6A8TKf8cGhqecSIiMhjqSg2mf3Ycl2+UoKPcDHFh/rDmWD8GiQGIiIgMglYr4NWvTiEh7Ras/xzrx1FuJnZZJBIGICIiMghL96Ti+z/H+lkzyQc9HTnWjyFjACIiIr332ZGrWPNr1Vg/S8Z4YqC7vcgVkdgYgIiISK/tTcnFgu+qxvqJeLw7xvh0Erkiag0YgIiISG8dvJiP8M+ToBWAcb6dMOcxd7FLolaCAYiIiPTS8fRbmP7pcZRXajGstwLvPs2xfugvDEBERKR3Tl0rQNjGY7hTocGj3Ttg5QveHOuHquFPAxER6ZXUnCJM3pCAInUl/LvY4eOJPpAZS8Uui1oZBiAiItIbafklmPDJURSUVsDLxRYbQv1gbsrwQzUxABERkV64drsUE9YdQX6xGr062uDTMH9YyYzFLotaKQYgIiJq83ILyzDhk6PIVpXBrYMlPpvqD7kFp7igurWKALRq1SoolUqYmZkhICAACQkJdbY9e/YsxowZA6VSCYlEgpiYmBptFi5cCIlEUu3Vs2fPZjwCIiISy81iNSZ+chRXb5bCxc4cn097CPZWMrHLolZO9AC0bds2REREYMGCBUhKSoKXlxeCg4ORl5dXa/vS0lK4ublh8eLFcHR0rHO7ffr0wfXr13WvgwcPNtchEBGRSFR3KjB5QwIu5hXD0cYMn097iPN7Ub2IHoBWrFiB6dOnIywsDL1798aaNWtgYWGBDRs21Nrez88Py5Ytw/PPPw+ZrO6Eb2xsDEdHR93L3p7DnhMR6ZMSdSVCNybgbHYh7K1MsWV6AFzsLMQui9oIUQNQeXk5EhMTERQUpFtmZGSEoKAgHD58+IG2ffHiRTg5OcHNzQ0TJkxARkZGnW3VajUKCwurvYiIqPUqq9Bg2qbjOJFRALm5CT6bGoCuHazELovaEFEDUH5+PjQaDRQKRbXlCoUCOTk5jd5uQEAA4uLisHv3bqxevRppaWkYNGgQioqKam0fHR0NuVyue7m4uDR630RE1LzKK7WYtTkRh6/chJXMGJ9O8UevjpzZnRpG9FtgzWH48OEYO3YsPD09ERwcjB9//BEFBQX48ssva20fGRkJlUqle2VmZrZwxUREVB+VGi3+b+sJ7E+9ATMTI6wP8YWXi63YZVEbJOoACfb29pBKpcjNza22PDc3974dnBvK1tYW3bt3x6VLl2r9XCaT3bc/ERERiU+rFfDa9lP46UwOTKVGWDvJFwFu7cUui9ooUa8AmZqawsfHB/Hx8bplWq0W8fHxGDBgQJPtp7i4GJcvX0bHjh2bbJtERNRyBEHAm9+dwY4TWZAaSRD7gjce7d5B7LKoDRN9iMyIiAiEhITA19cX/v7+iImJQUlJCcLCwgAAkydPhrOzM6KjowFUdZxOSUnRfZ2VlYXk5GRYWVnB3d0dAPDqq69i5MiR6Ny5M7Kzs7FgwQJIpVKMHz9enIMkIqJGEwQB7/14DluOZkAiAVaM88KwPk13l4AMk+gB6LnnnsONGzcQFRWFnJwc9OvXD7t379Z1jM7IyICR0V8XqrKzs+Ht7a17v3z5cixfvhyBgYE4cOAAAODatWsYP348bt68iQ4dOuCRRx7BkSNH0KED/2+BiKitidl3Eet+TwMALH7GA6P6OYtcEekDiSAIgthFtDaFhYWQy+VQqVSwseGTBUREYvn418uI/uk8AGDByN4IG9hF5IqoNWvI32+9fAqMiIjavs8Op+vCz7zgHgw/1KQYgIiIqNXZnngNb353FgAQPqQrwoe4i1wR6RsGICIialV+OHUdr20/CQAIfViJV4f1ELki0kcMQERE1GrEn8vF/209Aa0APO/nggUje0MikYhdFukhBiAiImoVDl3Kx6wtSajUCnjKywnvPu3B8EPN5oEDUFlZWVPUQUREBux4+i1M23Qc5ZVaPN5bgffHeUFqxPBDzadRAUir1eLtt9+Gs7MzrKyscOXKFQDAm2++ifXr1zdpgUREpN9OX1MhbOMx3KnQYFA3e8S+4A0TKW9QUPNq1E/YO++8g7i4OCxduhSmpqa65X379sUnn3zSZMUREZF+S80pwqQNR1GkroS/0g5rJ/lCZiwVuywyAI0KQJ9++inWrl2LCRMmQCr96wfVy8sL58+fb7LiiIhIf6Xll2Di+qMoKK2Al4st1of6wtyU4YdaRqMCUFZWlm7erXtptVpUVFQ8cFFERKTfrt0uxYR1R3CjSI2ejtbYFOYHazMTscsiA9KoANS7d2/8/vvvNZZv37692jxdREREf5dXWIYJnxxFtqoMbh0s8dnUANhamP7zikRNqFGToUZFRSEkJARZWVnQarXYsWMHUlNT8emnn2LXrl1NXSMREemJWyXlmPDJUVy9WQoXO3NsmRaADtYyscsiA9SoK0CjRo3C999/j3379sHS0hJRUVE4d+4cvv/+ezz++ONNXSMREekB1Z0KTFp/FBfziuFoY4bPpz2EjnJzscsiA8XZ4GvB2eCJiJpWiboSk9YfRVJGAdpbmmLbzAFwd7ASuyzSM80+G/yxY8dw9OjRGsuPHj2K48ePN2aTRESkp8oqNJi26TiSMgogNzfBZ1MDGH5IdI0KQOHh4cjMzKyxPCsrC+Hh4Q9cFBER6YfySi1mb0nC4Ss3YWkqxaYp/ujtxCvrJL5GBaCUlBT079+/xnJvb2+kpKQ8cFFERNT2VWq0mLvtBH45nwczEyNsCPVDPxdbscsiAtDIACSTyZCbm1tj+fXr12Fs3KgHy4iISI9otQJe+/oUfjydAxOpBB9P8kWAW3uxyyLSaVQAGjZsGCIjI6FSqXTLCgoK8J///IdPgRERGThBEBC18wx2JGVBaiRB7Av9Edi9g9hlEVXTqMs1y5cvx6OPPorOnTvrBj5MTk6GQqHAZ5991qQFEhFR2yEIAqJ/Oo/NRzIgkQArxnkhuI+j2GUR1dCoAOTs7IxTp05hy5YtOHnyJMzNzREWFobx48fDxIRDmRMRGaoP4y9i7W9XAADRT3tgVD9nkSsiql2jO+xYWlpixowZTVkLERG1YWt/u4yYfRcBAFH/6o3n/V1Froiobo0OQBcvXsT+/fuRl5cHrVZb7bOoqKgHLoyIiNqOz45cxXs/ngcAzAvugSmPdBG5IqL7a1QAWrduHWbNmgV7e3s4OjpCIpHoPpNIJAxAREQGZHviNbz57RkAwOzBXRE+xF3kioj+WaMC0DvvvIN3330Xr7/+elPXQ0REbciPp6/jte0nAQChDysxL7iHyBUR1U+jHoO/ffs2xo4d29S1EBFRG/LL+Vy8/MUJaAXgOV8XRP2rd7U7AkStWaMC0NixY/Hzzz83dS1ERNRG/HEpHy9uTkKlVsBILye894wHjIwYfqjtaNQtMHd3d7z55ps4cuQIPDw8ajz6/vLLLzdJcURE1PokXr2FaZ8eR3mlFo/3VmDFOC9IGX6ojZEIgiA0dKUuXeru3S+RSHDlypUHKkpshYWFkMvlUKlUsLHhpH1ERHedyVJh/NojKFJXYlA3e3wS4guZsVTssogANOzvd6OuAKWlpTWqMCIiarsu5BZh0vqjKFJXwl9ph7WTGH6o7WpUH6CmtmrVKiiVSpiZmSEgIAAJCQl1tj179izGjBkDpVIJiUSCmJiY+2578eLFkEgkmDt3btMWTURkQNLzSzDhk6O4XVoBr05yrA/1hbkpww+1XY0eCPHatWvYuXMnMjIyUF5eXu2zFStW1Hs727ZtQ0REBNasWYOAgADExMQgODgYqampcHBwqNG+tLQUbm5uGDt2LF555ZX7bvvYsWP4+OOP4enpWe96iIioumu3SzHhk6O4UaRGT0drbJriD2szTntEbVujAlB8fDyeeuopuLm54fz58+jbty/S09MhCAL69+/foG2tWLEC06dPR1hYGABgzZo1+OGHH7BhwwbMnz+/Rns/Pz/4+fkBQK2f31VcXIwJEyZg3bp1eOeddxpUExERVckrLMPET44iq+AO3Owt8dnUANhamIpdFtEDa9QtsMjISLz66qs4ffo0zMzM8PXXXyMzMxOBgYENGh+ovLwciYmJCAoK+qsgIyMEBQXh8OHDjSlNJzw8HCNGjKi2bSIiqr9bJeWYuP4o0m+WolM7c2yZHoAO1jKxyyJqEo26AnTu3Dl88cUXVRswNsadO3dgZWWFt956C6NGjcKsWbPqtZ38/HxoNBooFIpqyxUKBc6fP9+Y0gAAW7duRVJSEo4dO1av9mq1Gmq1Wve+sLCw0fsmItIHeUVlmLw+ARdyi6GwkeHzaQ+ho9xc7LKImkyjrgBZWlrq+v107NgRly9f1n2Wn5/fNJU1UmZmJv7v//4PW7ZsgZmZWb3WiY6Ohlwu171cXFyauUoiotbr2u1SjFtzGOdzitDBWoYt0wLg2t5C7LKImlSjAtBDDz2EgwcPAgCefPJJ/Pvf/8a7776LKVOm4KGHHqr3duzt7SGVSpGbm1tteW5uLhwdHRtTGhITE5GXl4f+/fvD2NgYxsbG+PXXX/HRRx/B2NgYGo2mxjqRkZFQqVS6V2ZmZqP2TUTU1l3KK8bYNYd1t72+mjkA7g7WYpdF1OQadQtsxYoVKC4uBgAsWrQIxcXF2LZtG7p169agJ8BMTU3h4+OD+Ph4jB49GgCg1WoRHx+Pl156qTGlYejQoTh9+nS1ZWFhYejZsydef/11SKU1H9uUyWSQyXhfm4gM25ksFSZvSMCtknK4O1hh89QAOMrrdyWdqK1pVAByc3PTfW1paYk1a9Y0uoCIiAiEhITA19cX/v7+iImJQUlJie6psMmTJ8PZ2RnR0dEAqjpOp6Sk6L7OyspCcnIyrKys4O7uDmtra/Tt27faPiwtLdG+ffsay4mIqEpC2i1MjTuGInUlPJzl2DTFH3aWfNqL9FejA9CxY8fQvn37assLCgrQv3//Bk2F8dxzz+HGjRuIiopCTk4O+vXrh927d+s6RmdkZMDI6K87ddnZ2fD29ta9X758OZYvX47AwEAcOHCgMYdDRGTQDqTm4cXNiSir0MK/ix3Wh/hynB/Se42aC8zIyAg5OTk1BirMzc2Fq6trtSeq2iLOBUZEhuKHU9cxd9sJVGgEDOnRAasn+sDMhCM8U9vUbHOB7dy5U/f1nj17IJfLde81Gg3i4+OhVCobVi0REYli27EMRO44Da0A/MuzI1aM6wdT41YxQxJRs2tQALrbUVkikSAkJKTaZyYmJlAqlXj//febrDgiImoen/x+Be/8cA4AMN7fFe+M7gupkUTkqohaToMCkFarBQB06dIFx44dg729fbMURUREzUMQBKzYewErf7kEAJj5qBvmD+8JiYThhwxLozpBp6Wl1VhWUFAAW1vbB62HiIiaiVYrYNH3Z7Hp8FUAwLzgHpg9uCvDDxmkRt3sXbJkCbZt26Z7P3bsWNjZ2cHZ2RknT55ssuKIiKhpVGq0ePWrk7rw8/aoPggf4s7wQwarUQFozZo1uuki9u7di3379mH37t0YPnw45s2b16QFEhHRgymr0GD2liTsOJEFqZEEHzznhUkDlGKXRSSqRt0Cy8nJ0QWgXbt2Ydy4cRg2bBiUSiUCAgKatEAiImq8EnUlZnx2HIcu3YSpsRFWvdAfj/dW/POKRHquUVeA2rVrp5sva/fu3QgKCgJQ1bmutrm2iIio5RWUlmPi+qM4dOkmLEyliAv1Y/gh+lOjrgA988wzeOGFF9CtWzfcvHkTw4cPBwCcOHEC7u7uTVogERE1XF5RGSavT8D5nCLIzU0QF+YHb9d2YpdF1Go0KgB98MEHUCqVyMzMxNKlS2FlZQUAuH79OmbPnt2kBRIRUcNcu12KiZ8cRfrNUnSwlmHz1AD0cOSM7kT3atRUGPqOU2EQUVt1Ka8Yk9YfxXVVGTq1M8eWaQHo3N5S7LKIWkSzTIWxc+dODB8+HCYmJtWmxKjNU089Vd/NEhFREzmTpcLkDQm4VVIOdwcrbJ4aAEe5mdhlEbVK9b4CdO8EqPfOzl5jgxJJm+8IzStARNTWJKTdwtS4YyhSV8KzkxxxYf6wszQVuyyiFtUsV4DuToPx96+JiEhc+1PzMGtzIsoqtAjoYodPQnxhbWYidllErVqDO0FrtVrExcVhx44dSE9Ph0QigZubG8aMGYNJkyZxVFEioha061Q25m5NRqVWwGM9HfC/Cf1hZiIVuyyiVq9B4wAJgoCnnnoK06ZNQ1ZWFjw8PNCnTx+kp6cjNDQUTz/9dHPVSUREf7M1IQNzvjiBSq2AkV5O+HiSD8MPUT016ApQXFwcfvvtN8THx2PIkCHVPvvll18wevRofPrpp5g8eXKTFklERNWt++0K3v3xHADghQBXvD2qL6RGvAJPVF8NugL0xRdf4D//+U+N8AMAjz32GObPn48tW7Y0WXFERFSdIAh4/+dUXfiZGeiGd0cz/BA1VIMC0KlTp/DEE0/U+fnw4cM5GzwRUTPRagUs3HkWK3+5BAB47YkeiBzei30viRqhQbfAbt26BYWi7nlkFAoFbt++/cBFERFRdZUaLV7bfgo7TmRBIgHeGtUXkx7qLHZZRG1WgwKQRqOBsXHdq0ilUlRWVj5wUURE9JeyCg1e/uIEfk7JhdRIgvfHemG0t7PYZRG1aQ0KQIIgIDQ0FDKZrNbP1Wp1kxRFRERVStSVmPHZcRy6dBOmxkb43wv9EcQZ3YkeWIMCUEhIyD+24RNgRERNo6C0HGFxx3AiowCWplKsC/HFw13txS6LSC80KABt3LixueogIqJ75BWVYfL6BJzPKYKthQniwvzRz8VW7LKI9EaDR4ImIqLmlXmrFJPWH0X6zVI4WMvw2dQA9HC0FrssIr3CAERE1IpcyivCxE8SkFNYBhc7c2yeGoDO7S3FLotI7zAAERG1EmeyVJi8IQG3SsrRzcEKn00NgKPcTOyyiPQSAxARUSuQkHYLU+OOoUhdCc9OcsSF+cPO0lTssoj0FgMQEZHI9qfm4cXPEqGu1CKgix0+CfGFtZmJ2GUR6TUGICIiEe06lY25W5NRqRUwtKcDVk3ozxndiVoAAxARkUi2JmQg8pvTEATgKS8nvD/OCybSBk3RSESN1Cr+pa1atQpKpRJmZmYICAhAQkJCnW3Pnj2LMWPGQKlUQiKRICYmpkab1atXw9PTEzY2NrCxscGAAQPw008/NeMREBE1zLrfrmD+jqrwMyHAFR8814/hh6gFif6vbdu2bYiIiMCCBQuQlJQELy8vBAcHIy8vr9b2paWlcHNzw+LFi+Ho6Fhrm06dOmHx4sVITEzE8ePH8dhjj2HUqFE4e/Zscx4KEdE/EgQB7/+cind/PAcAeDGwK94Z3RdSI87oTtSSJIIgCGIWEBAQAD8/P8TGxgIAtFotXFxcMGfOHMyfP/++6yqVSsydOxdz5879x/3Y2dlh2bJlmDp16j+2LSwshFwuh0qlgo2NTb2Og4jon2i1AhZ9fxabDl8FALz2RA/MHuwuclVE+qMhf79F7QNUXl6OxMREREZG6pYZGRkhKCgIhw8fbpJ9aDQafPXVVygpKcGAAQNqbaNWq6tN5FpYWNgk+yYiuqtSo8Vr209hx4ksSCTAW6P6YtJDncUui8hgiXoLLD8/HxqNBgpF9ZmNFQoFcnJyHmjbp0+fhpWVFWQyGV588UV888036N27d61to6OjIZfLdS8XF5cH2jcR0b3KKjSYvSUJO05kQWokQcxz/Rh+iEQmeh+g5tKjRw8kJyfj6NGjmDVrFkJCQpCSklJr28jISKhUKt0rMzOzhaslIn1Voq7ElLhj+DklF6bGRvh4og9G9XMWuywigyfqLTB7e3tIpVLk5uZWW56bm1tnB+f6MjU1hbt71b11Hx8fHDt2DB9++CE+/vjjGm1lMhlkMtkD7Y+I6O8KSssRuvEYkjMLYGkqxSchfhjQtb3YZRERRL4CZGpqCh8fH8THx+uWabVaxMfH19lfp7G0Wm21fj5ERM0pr6gMz689guTMAthamODz6Q8x/BC1IqIPhBgREYGQkBD4+vrC398fMTExKCkpQVhYGABg8uTJcHZ2RnR0NICqjtN3b2WVl5cjKysLycnJsLKy0l3xiYyMxPDhw+Hq6oqioiJ8/vnnOHDgAPbs2SPOQRKRQcm8VYqJ64/i6s1SOFjLsHlaALorrMUui4juIXoAeu6553Djxg1ERUUhJycH/fr1w+7du3UdozMyMmBk9NeFquzsbHh7e+veL1++HMuXL0dgYCAOHDgAAMjLy8PkyZNx/fp1yOVyeHp6Ys+ePXj88cdb9NiIyPAcT7+FFzcnIb9YDRc7c2yZ+hBc21uIXRYR/Y3o4wC1RhwHiIgaY8vRq1i48ywqNAJ6Olpj0xR/KGzMxC6LyGC0mXGAiIj0QXmlFgu/P4vPj2YAAEZ4dsSyZz1hYcpfsUStFf91EhE9gBtFaszekohj6bchkQDzgntgVmBXSCSc2oKoNWMAIiJqpFPXCjDzs0RcV5XB2swYHz3vjSE9HcQui4jqgQGIiKgRvjlxDfO/Pg11pRZdO1hi3WRfuHWwErssIqonBiAiogao1Gix+Kfz+ORgGgAgqJcDPniuH6zNTESujIgaggGIiKiebpeUY84XJ3DwUj4AYM5j7nglqDuMjNjfh6itYQAiIqqH8zmFmP7pcWTeugMLUyneH+uF4R4dxS6LiBqJAYiI6B/8dPo6/v3VSZSWa+BqZ4G1k33Q05FjhBG1ZQxARER10GoFfLDvAlb+cgkA8Ii7PWJf8IathanIlRHRg2IAIiKqRVFZBV7Zlox95/IAANMe6YL5w3vCWCrqHNJE1EQYgIiI/ubyjWLM+PQ4Lt8ogamxERY/44Fn+ncSuywiakIMQERE99h/Pg8vf3ECRepKdJSb4eNJPvDsZCt2WUTUxBiAiIgACIKA/x24jOU/p0IQAD9lO/xvgg86WMvELo2ImgEDEBEZvNLySszbfgo/nLoOAJgQ4IoFI/vA1Jj9fYj0FQMQERm0zFulmPFZIs5dL4SJVIJFT/XFCwGuYpdFRM2MAYiIDNYfl/IR/nkSbpdWwN5KhtUT+8NPaSd2WUTUAhiAiMjgCIKAjYfS8e6P56DRCvDsJMfHk3zQUW4udmlE1EIYgIjIoJRVaPDfb87g66RrAIBnvJ3x3jMeMDORilwZEbUkBiAiMhg5qjLM3JyIk5kFkBpJ8J8ne2HKQCUkEk5mSmRoGICIyCAkXr2FFzcn4UaRGrYWJlj1Qn8MdLcXuywiEgkDEBHpva0JGXjzuzOo0Ajo6WiNtZN84dreQuyyiEhEDEBEpLfKK7V4e1cKPjtyFQDwpIcjlj3rBUsZf/URGTr+FiAivZRfrMbszUlISL8FiQT49+PdET7Enf19iAgAAxAR6aHT11SY+dlxZKvKYC0zRszz/TC0l0LssoioFWEAIiK98u2JLLz+9SmoK7Vws7fE2sm+cHewErssImplGICISC9otAKW7D6Ptb9dAQAM6dEBMc97Q25uInJlRNQaMQARUZtXUFqOOV+cwO8X8wEA4UO6IuLxHpAasb8PEdWOAYiI2rTUnCLM+Ow4rt4shbmJFMvHemGEZ0exyyKiVo4BiIjarN1nchDxZTJKyzXo1M4cayf5oreTjdhlEVEbwABERG2OVisgJv4iPoq/CAB4uGt7xL7QH3aWpiJXRkRthZHYBQDAqlWroFQqYWZmhoCAACQkJNTZ9uzZsxgzZgyUyqr5e2JiYmq0iY6Ohp+fH6ytreHg4IDRo0cjNTW1GY+AiFpKUVkFZnyWqAs/YQOV+HSKP8MPETWI6AFo27ZtiIiIwIIFC5CUlAQvLy8EBwcjLy+v1valpaVwc3PD4sWL4ejoWGubX3/9FeHh4Thy5Aj27t2LiooKDBs2DCUlJc15KETUzNLyS/D0//7AvnO5MDU2wvKxXlgwsg+MpaL/KiOiNkYiCIIgZgEBAQHw8/NDbGwsAECr1cLFxQVz5szB/Pnz77uuUqnE3LlzMXfu3Pu2u3HjBhwcHPDrr7/i0Ucf/ceaCgsLIZfLoVKpYGPD/gRErcGB1DzM+eIEisoq4WhjhjWTfNDPxVbssoioFWnI329R+wCVl5cjMTERkZGRumVGRkYICgrC4cOHm2w/KpUKAGBnZ1fr52q1Gmq1Wve+sLCwyfZNRA9GEASs+fUKlu45D0EAfDq3w+qJ/eFgbSZ2aUTUhol63Tg/Px8ajQYKRfUh6hUKBXJycppkH1qtFnPnzsXAgQPRt2/fWttER0dDLpfrXi4uLk2ybyJ6MHfKNXh5azKW7K4KP+P9XfD59ACGHyJ6YHp/4zw8PBxnzpzB1q1b62wTGRkJlUqle2VmZrZghURUm8xbpRiz+g98fzIbxkYSvD26L9572gMyY6nYpRGRHhD1Fpi9vT2kUilyc3OrLc/Nza2zg3NDvPTSS9i1axd+++03dOrUqc52MpkMMpnsgfdHRE3j8OWbCP88CbdKytHe0hT/m9AfAW7txS6LiPSIqFeATE1N4ePjg/j4eN0yrVaL+Ph4DBgwoNHbFQQBL730Er755hv88ssv6NKlS1OUS0TNTBAEbPojHRPXH8WtknL0dbbB93MeYfghoiYn+kCIERERCAkJga+vL/z9/RETE4OSkhKEhYUBACZPngxnZ2dER0cDqOo4nZKSovs6KysLycnJsLKygru7O4Cq216ff/45vvvuO1hbW+v6E8nlcpibm4twlET0T1R3KrBo51nsOJEFABjdzwmLx3jCzIS3vIio6Yn+GDwAxMbGYtmyZcjJyUG/fv3w0UcfISAgAAAwePBgKJVKxMXFAQDS09NrvaITGBiIAwcOAAAkktonQNy4cSNCQ0P/sR4+Bk/UsuLP5eI/35xGbqEaRhIgcngvTBvUpc5/y0REtWnI3+9WEYBaGwYgopZxu6Qcb+1KwTd/XvXpYm+Jpc96wk9Z+5AVRET302bGASIiw7X7zHW88e1Z5BdXXfWZNsgNrwR1h7kpb3kRUfNjACKiFpVfrMaC787ih9PXAQDuDlZY9qwnvF3biVwZERkSBiAiahGCIGDnyWws3HkWt0srIDWS4MVAN7w8tBvH9iGiFscARETNLq+wDP/99gz2plSN+dXT0RrLx3qhr7Nc5MqIyFAxABFRsxEEAV8nZeGt78+isKwSxkYSvPSYO2YPdoepsd4PRE9ErRgDEBE1i+yCO/jPN6dxIPUGAMDDWY6lz3qiV0c+WUlE4mMAIqImJQgCth7LxLs/nEOxuhKmUiPMfbwbZgxyg7GUV32IqHVgACKiJpN5qxTzd5zCoUs3AQDerrZY9qwn3B2sRa6MiKg6BiAiemBarYDNR69i8U/nUVqugczYCPOCeyBsYBdIjTiaMxG1PgxARPRA0vNL8NrXp5CQdgsA4K+0w5JnPdHF3lLkyoiI6sYARESNotEK2HgoDct/TkVZhRYWplK8/kRPTHqoM4x41YeIWjkGICJqsEt5RZi3/RROZBQAAAa6t8fiZzzhYmchbmFERPXEAERE9Vap0WLt71cQs+8iyiu1sJIZ478jeuF5PxfO3E5EbQoDEBHVy/mcQsz76hROZ6kAAIN7dMB7T3vAydZc5MqIiBqOAYiI7qu8UovVBy4jdv9FVGgE2JgZI2pkH4zp78yrPkTUZjEAEVGdzmSp8OpXJ3E+pwgAENRLgXef7guFjZnIlRERPRgGICKqQV2pwcr4S1j962VotALaWZhg4VN98JSXE6/6EJFeYAAiompOZNzGa9tP4WJeMQBghEdHLBrVB/ZWMpErIyJqOgxARAQAKKvQYMXeC/jk9yvQCoC9lSneHtUXwz06il0aEVGTYwAiIhxLv4XXtp9CWn4JAGB0PycsGNkH7SxNRa6MiKh5MAARGbDS8kos3Z2KTYfTIQiAwkaGd0d7IKi3QuzSiIiaFQMQkYH643I+Xv/6FDJv3QEAjPPthP+O6A25uYnIlRERNT8GICIDU1RWgcU/nceWoxkAAGdbc0Q/44FHu3cQuTIiopbDAERkQH69cAORX59CtqoMADDxIVe8/kRPWJvxqg8RGRYGICIDoCqtwDs/pOCrxGsAABc7cywZ44mHu9qLXBkRkTgYgIj03L6UXPznm9PIK1JDIgFCBijx2hM9YGHKf/5EZLj4G5BIT90uKcei78/i2+RsAICbvSWWPOsJP6WdyJUREYmPAYhID/10+jre/O4M8ovLYSQBpg9ywyuPd4eZiVTs0oiIWgUGICI9kl+sRtR3Z/Dj6RwAQDcHKywb64V+LrbiFkZE1MowABHpAUEQsPNkNhbuPIvbpRWQGkkwK7Ar5gx1h8yYV32IiP7OSOwCVq1aBaVSCTMzMwQEBCAhIaHOtmfPnsWYMWOgVCohkUgQExNTo81vv/2GkSNHwsmpatbqb7/9tvmKJ2oFTl9TYUrcMfzf1mTcLq1Ar442+C58IF4N7sHwQ0RUB1ED0LZt2xAREYEFCxYgKSkJXl5eCA4ORl5eXq3tS0tL4ebmhsWLF8PR0bHWNiUlJfDy8sKqVauas3Qi0SVevY3QjQkYGXsQ+1NvwEQqQcTj3fFd+ED0dZaLXR4RUasmEQRBEGvnAQEB8PPzQ2xsLABAq9XCxcUFc+bMwfz58++7rlKpxNy5czF37tw620gkEnzzzTcYPXp0g+oqLCyEXC6HSqWCjY1Ng9Ylam5HrtzEyl8u4tClmwAAIwkwqp8zXnrMHV07WIlcHRGReBry91u0PkDl5eVITExEZGSkbpmRkRGCgoJw+PBhscoiapUEQcChSzfx0S8XkZB2CwBgbCTBM/2dMXuwO5T2liJXSETUtogWgPLz86HRaKBQVJ91WqFQ4Pz58y1ai1qthlqt1r0vLCxs0f0T1UUQBBxIvYGPfrmIExkFAABTqRHG+nbCi4Fd4WJnIW6BRERtFJ8CAxAdHY1FixaJXQaRjlYrYO+5XMT+cgmns1QAAJmxEcb7u2JmoBs6ys1FrpCIqG0TLQDZ29tDKpUiNze32vLc3Nw6Ozg3l8jISEREROjeFxYWwsXFpUVrIAKqgs9PZ3Kw8peLOJ9TBAAwN5Fi4kOumP6oGxyszUSukIhIP4gWgExNTeHj44P4+HhdJ2WtVov4+Hi89NJLLVqLTCaDTCZr0X0S3atSo8WuU9cRu/8SLuUVAwCsZMaYPKAzpj7SBe2t+PNJRNSURL0FFhERgZCQEPj6+sLf3x8xMTEoKSlBWFgYAGDy5MlwdnZGdHQ0gKqO0ykpKbqvs7KykJycDCsrK7i7uwMAiouLcenSJd0+0tLSkJycDDs7O7i6urbwERLdX4VGi29OZOF/+y8h/WYpAMDGzBhhA7sgbKASthamIldIRKSfRH0MHgBiY2OxbNky5OTkoF+/fvjoo48QEBAAABg8eDCUSiXi4uIAAOnp6ejSpUuNbQQGBuLAgQMAgAMHDmDIkCE12oSEhOi280/4GDw1N3WlBtsTr2H1gcu4dvsOAKCdhQmmDXLDpAGdYWNmInKFRERtT0P+fosegFojBiBqLmUVGmw7lok1v17GdVUZAMDeyhTTB7lh4kOdYSnjcwlERI3VJsYBIjIkpeWV+PxoBj7+7QpuFFUNuaCwkWHmo10x3t8V5qacsoKIqCUxABE1o2J1JT49nI5Pfk/DrZJyAICzrTleHNwVY306wcyEwYeISAwMQETNQHWnAnGH0rHhUBpUdyoAAK52Fpg9uCue6d8Jpsaiz0NMRGTQGICImtDtknJsOJSGuEPpKFJXAgDc7C0RPsQdo/o5wVjK4ENE1BowABE1gfxiNdb9fgWbD19FSbkGANBdYYWXHuuGER4dITWSiFwhERHdiwGI6AHkFpbh41+v4POEqyir0AIAene0wctD3TGstyOMGHyIiFolBiCiRsgquIM1By5j2/FMlFdWBR+vTnLMeawbhvZygETC4ENE1JoxABE1QMbNUqz+9RK2J15DhaZqCC3fzu0wZ2g3PNrNnsGHiKiNYAAiqocrN4qxav9lfJucBY22KvgMcGuPOUPdMcCtPYMPEVEbwwBEdB8XcosQ+8sl7DqVjT9zDwZ1s8fLQ7vBT2knbnFERNRoDEBEtUjJLkTs/ov46UwO7k4WM7SnA+YM7YZ+Lrai1kZERA+OAYjoHqeuFeCj+EvYdy5Xt+yJPo546TF39HWWi1gZERE1JQYgIgCJV2/ho/hL+PXCDQCARAL8y9MJLw1xRw9Ha5GrIyKipsYARAarQqPF4cs3sebXy/jj8k0AgNRIglFeTpg9xB3uDlYiV0hERM2FAYgMiqq0Agcu5CH+XB4OpOahsKxqugpjIwnG9O+E2UO6onN7S5GrJCKi5sYARHovLb8E8edyse9cLo6l39Y9xg4Adpam+JdnR8x41A2d2lmIWCUREbUkBiDSO5UaLZIyCnSh5/KNkmqfd1dYYWgvBYJ6OaCfSzvO00VEZIAYgEgvFJZV4LcLNxB/Lg/7U/NQUFqh+8zYSIIANzsM7alAUC8FXNvzSg8RkaFjAKI2K/NWKfady0X8uTwcTbupm5oCAOTmJnispwOG9nLAo907wMbMRMRKiYiotWEAojZDoxWQnHkb+87lIf5cLi7kFlf73K2DJYJ6KTC0pwN8OreDsdRIpEqJiKi1YwCiVq1EXYnfL97AvnN52H8+DzdLynWfSY0k8FO2qwo9vRToYs+nt4iIqH4YgKjVySq4g1/O5WLvuTwcuXwT5Rqt7jNrM2MM7uGAoF4OGNzdAXIL3toiIqKGYwAi0Wm1Ak5lqf58aisP564XVvu8c3uLqg7MvR3gp7SDCW9tERHRA2IAIlHcKdfg4KV87EvJxS+pebhRpNZ9ZiQBfDq30z2q3rWDFSQSPqpORERNhwGIWkyOqgzx56ue2jp0KR/qyr9ubVnJjPFod3sE9VJgcA8H2FmailgpERHpOwYgajaCIOBsdiH2puQi/nwuzmRVv7XVqZ35nx2YHRDQpT1MjXlri4iIWgYDEDWpsgoN/ricj33n8vDLuTzkFJbpPpNIgH4utrrQ00NhzVtbREQkCgYgemB5RWX45Vwe9v15a+tOhUb3mYWpFIO62WNoLwWG9HBAB2uZiJUSERFVYQCiBtFoBdwsVuNawR0cupiPfefzcDKzoFqbjnIzDO3lgKG9FBjg1h5mJlJxiiUiIqoDAxABqOqvc7u0ArmFZfe81Lr/5hVVLbtRpMY9k6nreHaS625t9e5ow1tbRETUqjEA6TlBEFBYVom8ewNNURnydOGmavmNInW1AQfvx0gC2FvJ4NlJjqG9FHispwMUNmbNfCRERERNp1UEoFWrVmHZsmXIycmBl5cXVq5cCX9//1rbnj17FlFRUUhMTMTVq1fxwQcfYO7cuQ+0zbaqtLzynqs094SaIvWf76vCzb19cv5Je0tTONiYQWEjg8LaDAr5PV//uby9lQxSI17hISKitkv0ALRt2zZERERgzZo1CAgIQExMDIKDg5GamgoHB4ca7UtLS+Hm5oaxY8filVdeaZJttjbqSg3ydLed7rkN9efVmxxVVdgpUlfWe5tyc5OqIGNjBgdrM93XChvZn4HHDB2sZHwUnYiIDIJEEIRaenS0nICAAPj5+SE2NhYAoNVq4eLigjlz5mD+/Pn3XVepVGLu3Lk1rgA9yDYBoLCwEHK5HCqVCjY2No07sFpUarTILy7/69ZTkRq5qr++zvtz+e3Sinpv08JUCkcbMzjoAo0ZHKz/+vpu0GFHZCIi0ncN+fst6hWg8vJyJCYmIjIyUrfMyMgIQUFBOHz4cIttU61WQ63+ayqGwsLCWts9qK8SryFyx+l6tTU1Nqp+G+qeqzb3hh0rmegX8YiIiNocUf965ufnQ6PRQKFQVFuuUChw/vz5FttmdHQ0Fi1a1Kj9NYTCRgZjIwkcrGV/9bOp46qN3NyET1IRERE1E14+ABAZGYmIiAjd+8LCQri4uDT5fgK7O+DCO8NhxA7EREREohI1ANnb20MqlSI3N7fa8tzcXDg6OrbYNmUyGWSy5h+hmE9OERERtQ6iPvJjamoKHx8fxMfH65ZptVrEx8djwIABrWabREREpF9EvwUWERGBkJAQ+Pr6wt/fHzExMSgpKUFYWBgAYPLkyXB2dkZ0dDSAqk7OKSkpuq+zsrKQnJwMKysruLu712ubREREZNhED0DPPfccbty4gaioKOTk5KBfv37YvXu3rhNzRkYGjIz+ulCVnZ0Nb29v3fvly5dj+fLlCAwMxIEDB+q1TSIiIjJsoo8D1Bo11zhARERE1Hwa8vebw/4SERGRwWEAIiIiIoPDAEREREQGhwGIiIiIDA4DEBERERkcBiAiIiIyOAxAREREZHAYgIiIiMjgMAARERGRwRF9KozW6O7g2IWFhSJXQkRERPV19+92fSa5YACqRVFREQDAxcVF5EqIiIiooYqKiiCXy+/bhnOB1UKr1SI7OxvW1taQSCRNuu3CwkK4uLggMzOT84yJjOei9eC5aD14LloPnouGEwQBRUVFcHJyqjaRem14BagWRkZG6NSpU7Puw8bGhj/QrQTPRevBc9F68Fy0HjwXDfNPV37uYidoIiIiMjgMQERERGRwGIBamEwmw4IFCyCTycQuxeDxXLQePBetB89F68Fz0bzYCZqIiIgMDq8AERERkcFhACIiIiKDwwBEREREBocBiIiIiAwOA9ADWrVqFZRKJczMzBAQEICEhIT7tv/qq6/Qs2dPmJmZwcPDAz/++GO1zwVBQFRUFDp27Ahzc3MEBQXh4sWLzXkIeqOpz8WOHTswbNgwtG/fHhKJBMnJyc1YvX5pynNRUVGB119/HR4eHrC0tISTkxMmT56M7Ozs5j4MvdHU/zYWLlyInj17wtLSEu3atUNQUBCOHj3anIegN5r6XNzrxRdfhEQiQUxMTBNXracEarStW7cKpqamwoYNG4SzZ88K06dPF2xtbYXc3Nxa2x86dEiQSqXC0qVLhZSUFOGNN94QTExMhNOnT+vaLF68WJDL5cK3334rnDx5UnjqqaeELl26CHfu3Gmpw2qTmuNcfPrpp8KiRYuEdevWCQCEEydOtNDRtG1NfS4KCgqEoKAgYdu2bcL58+eFw4cPC/7+/oKPj09LHlab1Rz/NrZs2SLs3btXuHz5snDmzBlh6tSpgo2NjZCXl9dSh9UmNce5uGvHjh2Cl5eX4OTkJHzwwQfNfCT6gQHoAfj7+wvh4eG69xqNRnBychKio6NrbT9u3DhhxIgR1ZYFBAQIM2fOFARBELRareDo6CgsW7ZM93lBQYEgk8mEL774ohmOQH809bm4V1paGgNQAzTnubgrISFBACBcvXq1aYrWYy1xPlQqlQBA2LdvX9MUraea61xcu3ZNcHZ2Fs6cOSN07tyZAaieeAuskcrLy5GYmIigoCDdMiMjIwQFBeHw4cO1rnP48OFq7QEgODhY1z4tLQ05OTnV2sjlcgQEBNS5TWqec0GN01LnQqVSQSKRwNbWtknq1lctcT7Ky8uxdu1ayOVyeHl5NV3xeqa5zoVWq8WkSZMwb9489OnTp3mK11MMQI2Un58PjUYDhUJRbblCoUBOTk6t6+Tk5Ny3/d3/NmSb1DznghqnJc5FWVkZXn/9dYwfP54TRP6D5jwfu3btgpWVFczMzPDBBx9g7969sLe3b9oD0CPNdS6WLFkCY2NjvPzyy01ftJ5jACKiNqOiogLjxo2DIAhYvXq12OUYtCFDhiA5ORl//PEHnnjiCYwbNw55eXlil2VQEhMT8eGHHyIuLg4SiUTsctocBqBGsre3h1QqRW5ubrXlubm5cHR0rHUdR0fH+7a/+9+GbJOa51xQ4zTnubgbfq5evYq9e/fy6k89NOf5sLS0hLu7Ox566CGsX78exsbGWL9+fdMegB5pjnPx+++/Iy8vD66urjA2NoaxsTGuXr2Kf//731Aqlc1yHPqEAaiRTE1N4ePjg/j4eN0yrVaL+Ph4DBgwoNZ1BgwYUK09AOzdu1fXvkuXLnB0dKzWprCwEEePHq1zm9Q854Iap7nOxd3wc/HiRezbtw/t27dvngPQMy35b0Or1UKtVj940XqqOc7FpEmTcOrUKSQnJ+teTk5OmDdvHvbs2dN8B6MvxO6F3ZZt3bpVkMlkQlxcnJCSkiLMmDFDsLW1FXJycgRBEIRJkyYJ8+fP17U/dOiQYGxsLCxfvlw4d+6csGDBglofg7e1tRW+++474dSpU8KoUaP4GHw9NMe5uHnzpnDixAnhhx9+EAAIW7duFU6cOCFcv369xY+vLWnqc1FeXi489dRTQqdOnYTk5GTh+vXrupdarRblGNuSpj4fxcXFQmRkpHD48GEhPT1dOH78uBAWFibIZDLhzJkzohxjW9Ecv6f+jk+B1R8D0ANauXKl4OrqKpiamgr+/v7CkSNHdJ8FBgYKISEh1dp/+eWXQvfu3QVTU1OhT58+wg8//FDtc61WK7z55puCQqEQZDKZMHToUCE1NbUlDqXNa+pzsXHjRgFAjdeCBQta4GjatqY8F3eHIajttX///hY6oratKc/HnTt3hKefflpwcnISTE1NhY4dOwpPPfWUkJCQ0FKH06Y19e+pv2MAqj+JIAiCONeeiIiIiMTBPkBERERkcBiAiIiIyOAwABEREZHBYQAiIiIig8MARERERAaHAYiIiIgMDgMQERERGRwGICLSO6GhoRg9erTYZRBRK2YsdgFERA3xT7NeL1iwAB9++CE4xisR3Q8DEBG1KdevX9d9vW3bNkRFRSE1NVW3zMrKClZWVmKURkRtCG+BEVGb4ujoqHvJ5XJIJJJqy6ysrGrcAhs8eDDmzJmDuXPnol27dlAoFFi3bh1KSkoQFhYGa2truLu746effqq2rzNnzmD48OGwsrKCQqHApEmTkJ+f38JHTETNgQGIiAzCpk2bYG9vj4SEBMyZMwezZs3C2LFj8fDDDyMpKQnDhg3DpEmTUFpaCgAoKCjAY489Bm9vbxw/fhy7d+9Gbm4uxo0bJ/KREFFTYAAiIoPg5eWFN954A926dUNkZCTMzMxgb2+P6dOno1u3boiKisLNmzdx6tQpAEBsbCy8vb3x3nvvoWfPnvD29saGDRuwf/9+XLhwQeSjIaIHxT5ARGQQPD09dV9LpVK0b98eHh4eumUKhQIAkJeXBwA4efIk9u/fX2t/osuXL6N79+7NXDERNScGICIyCCYmJtXeSySSasvuPl2m1WoBAMXFxRg5ciSWLFlSY1sdO3ZsxkqJqCUwABER1aJ///74+uuvoVQqYWzMX5VE+oZ9gIiIahEeHo5bt25h/PjxOHbsGC5fvow9e/YgLCwMGo1G7PKI6AExABER1cLJyQmHDh2CRqPBsGHD4OHhgblz58LW1hZGRvzVSdTWSQQOl0pEREQGhv8bQ0RERAaHAYiIiIgMDgMQERERGRwGICIiIjI4DEBERERkcBiAiIiIyOAwABEREZHBYQAiIiIig8MARERERAaHAYiIiIgMDgMQERERGRwGICIiIjI4/w/rTB22oPKBHgAAAABJRU5ErkJggg==",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -436,7 +618,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -492,6 +674,4082 @@
     "plt.ylabel('Number of particles')\n",
     "plt.show()\n"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Full PM solver\n",
+    "We now have all the tools to implement the full PM solver:\n",
+    "- force computation using mesh\n",
+    "- integrator with RK4\n",
+    "- estimate for good timesteps"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "09:38:52 - task2 (mesh) - Integration range: 0.0 -> 952.8627203476617, n_steps: 188495\n",
+      "09:38:52 - utils.integrate - Reshaped 7 columns into particles.shape=(1414,)\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.036589586055252865\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 560.2040843578968 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:52 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023263587300085347\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.03655587384174008\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 561.2378130598636 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:52 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023276852959839096\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.03655588099934548\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 561.2375932802661 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:52 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023277010406627646\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.036522181836341594\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 562.2737834446085 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:52 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002328243321003685\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.036522179872084615\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 562.2738439256772 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:52 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023282430456915432\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.036488485599897924\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 563.312755512869 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:52 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023296764679076416\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.03648849184990921\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 563.3125625363663 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:52 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002329692111844953\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.03645480193246109\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 564.3542208099584 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:52 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023307495043927325\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.03645480256424183\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 564.3542012488526 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:52 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023307495602778597\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.036421119249247735\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 565.398546447918 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:52 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00232950987824078\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.036421124661245585\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 565.3983784171105 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:52 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002329525415335444\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.03638744654358328\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 566.4454628819223 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:52 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002330265642381862\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.03638744661516169\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 566.445460653392 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:52 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00233026562665376\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.03635377396190931\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 567.4952859129335 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:52 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002330678372584404\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.036353779316408485\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 567.4951187417134 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:52 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002330693911383059\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.036320111877452654\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 568.5477015459736 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:52 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023314672626540624\n",
+      "09:38:52 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:52 - utils.forces_mesh - Using mesh spacing: 0.03632011192420981\n",
+      "09:38:52 - utils.forces_mesh - Got k_square with: (50, 50, 50), 568.5477000821195 0.0\n",
+      "09:38:52 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023314672437481994\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03628644983158558\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 569.6030462293836 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023305149129133743\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.036286455021310116\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 569.6028832990178 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023305304307303684\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03625279806602266\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 570.6610084084925 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002329306090022995\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.036252798083507676\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 570.6610078580239 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023293060673842164\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.036219146331349705\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 571.721919888895 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002330314231154491\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03621915150883381\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 571.7217564349863 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023303297472987896\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.0361855049014812\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 572.7854663876836 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023286778658505106\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03618550491239647\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 572.7854660421249 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002328677842376436\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03615186347213306\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 573.8519833284242 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023282876323810985\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.0361518685856862\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 573.8518209897948 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023283031280356297\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.036118232268987915\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 574.9211562432217 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023250593688728337\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03611823226567279\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 574.9211563487603 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023250593436057294\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03608460106875433\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 575.993319896967 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002325299089755698\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03608460621093301\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 575.9931557349782 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023253145704358004\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03605098011062813\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 577.0681576566012 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00232432177073339\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03605098012583874\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 577.0681571696487 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023243217478623296\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.036017359125161685\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 578.1460076701314 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002322310557269271\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03601736409405576\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 578.1458481500695 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023223259969428257\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03598374837169627\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 579.2265509175885 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023193497814591093\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03598374826857731\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 579.2265542373782 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023193497433866535\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03597508648482639\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 579.5055105728891 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023221749878453253\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.035975085994245704\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 579.5055263779498 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002322189722552836\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03614845177080328\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 573.9603090723007 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002349319974408932\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.036148448003124334\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 573.96042871773 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023493194595798775\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03632181141684232\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 568.494496787204 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023769454230430334\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03632181661252154\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 568.4943341458436 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0023769612501366743\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03649518522504969\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 563.1059535538614 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002403616032016721\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.036495185224028615\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 563.1059535853707 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002403616006202652\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03666855901018096\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 557.7936634261977 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0024292907566586274\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03666856414275821\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 557.7935072750676 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0024293069173649323\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03684194314367417\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 552.5558833157955 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002458433818915873\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.03684194311630118\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 552.5558841368764 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0024584337889974875\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.0370153272434377\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 547.3915348133311 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002485512411242158\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.037015332439064075\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 547.391381145026 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0024855289479083567\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.037188721824631066\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 542.2989449869965 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:53 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00251404884942444\n",
+      "09:38:53 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:53 - utils.forces_mesh - Using mesh spacing: 0.037188721803719016\n",
+      "09:38:53 - utils.forces_mesh - Got k_square with: (50, 50, 50), 542.29894559689 0.0\n",
+      "09:38:53 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002514048819737626\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03736211637386111\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 537.27709432545 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002541297860376326\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.037362121599069376\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 537.2769440457338 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002541314765597897\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.037535521450803966\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 532.3243792061463 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002566495030868746\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03753552143203198\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 532.3243797385903 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0025664950008819523\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.037708926451965774\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 527.4398343970948 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0025949977194238026\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.037708931562462356\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 527.4396914347155 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0025950149594037666\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03788234174998739\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 522.6219283217466 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002622309968076876\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03788234173097815\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 522.6219288462466 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002622309937429105\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03805575707520292\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 517.8697351009453 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002651320141805881\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03805576238133679\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 517.8695906872861 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002651337776676783\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.038229182771086\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 513.1817874143567 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0026796937934874705\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03822918285797827\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 513.1817850815038 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0026796937770398738\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03840260865287315\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 508.5572034233362 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0027071743020342293\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.038402613995365154\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 508.55706192449946 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002707192306718585\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.038576045165948813\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 503.9945734129858 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0027346543447897454\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.038576045154906424\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 503.99457370152254 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0027346543140078644\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03874948176768067\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 499.49306872564046 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002763975934293297\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03874948744239526\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 499.4929224279429 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002763994357260491\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.038922929441184806\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 495.051322986956 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002791175691604436\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03892292953744192\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 495.0513205384142 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0027911756755895412\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03909637727660897\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 490.66855820920625 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002822084248331423\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03909638285954076\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 490.6684180750714 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002822103038028579\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03926983873061052\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 486.34340144125224 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002848861190940198\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03926983788098337\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 486.3434224859311 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0028488610372300214\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03944330060255552\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 482.07517166032494 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002875557896251669\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03944331253708033\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 482.07487993344614 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0028755779608717873\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03961678737998908\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 477.86228351470885 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00290370929661196\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03961678731777196\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 477.862285015649 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0029037092564691345\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03979027282627634\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 473.7044117987012 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0029312118266197657\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.039790281140665074\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 473.7042138326601 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0029312317307360176\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.03996377249214289\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 469.60023711490715 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002962228859471317\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.039963773315979\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 469.60021775369074 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002962228949953849\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.04013727342266793\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 465.54914079828126 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00299175904367956\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.04013728058801547\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 465.5489745776979 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.002991779176830723\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:54 - utils.forces_mesh - Using mesh spacing: 0.0403107871390449\n",
+      "09:38:54 - utils.forces_mesh - Got k_square with: (50, 50, 50), 461.5499478069713 0.0\n",
+      "09:38:54 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:54 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0030195643581421815\n",
+      "09:38:54 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.040310787379410296\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 461.5499423027059 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0030195643618921414\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.040484301227356245\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 457.6020571659818 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0030488099811527823\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.04048430806631442\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 457.6019025618294 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0030488304397391806\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.040657828140058916\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 453.7043172449052 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0030778320153044087\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.040657828344473956\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 453.7043126827342 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0030778320133704852\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.04083135532027171\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 449.85616012390295 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0031088687747177126\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.040831361735270244\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 449.8560187704795 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0031088895628316165\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.0410048951110189\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 446.0564798574642 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003136822164054653\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.041004895116062756\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 446.0564797477288 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003136822131313409\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.041178435053046636\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 442.30473443885774 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0031651195009779337\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.04117844189162401\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 442.3045875301957 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003165140721957535\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.0413519887152477\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 438.59983312642464 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003193905262875137\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.041351988699256825\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 438.599833465639 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0031939052262821596\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.0415255422556815\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 434.9412905005172 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0032258587997979126\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.041525548824902114\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 434.94115288764306 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0032258803772067892\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.041700561704319794\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 431.2980091994795 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0032560844359274667\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.04170056124835164\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 431.29801863139846 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00325608432993409\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.04188382930665557\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 427.5318768999715 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003287801763964494\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.04188383587240785\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 427.5317428593273 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0032878237462598114\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.042067110100922456\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 423.81459357484516 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003318272932373397\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.0420671102327973\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 423.8145909176394 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0033182729177265824\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.04225039110110518\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 420.1455775058073 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0033523311522681764\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.04225039749335546\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 420.14545037443594 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003352353529356292\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.042433684882457134\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 416.5237498004125 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003381717573826409\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.04243368483963739\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 416.5237506410391 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003381717530872104\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.042616978637428415\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 412.94855401043344 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0034150966309792804\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.04261698520745494\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 412.9484266864225 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0034151194466354095\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.04280028570408301\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 409.4189378475717 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0034496210226444696\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.04280028566117511\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 409.4189386684685 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003449620978873082\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.04298359248819539\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 405.93438767983446 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0034818198148757955\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.04298359846804267\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 405.93427473324266 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003481842971527453\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.04316691109745263\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 402.4939137487163 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0035122572569996615\n",
+      "09:38:55 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:55 - utils.forces_mesh - Using mesh spacing: 0.04316691115663063\n",
+      "09:38:55 - utils.forces_mesh - Got k_square with: (50, 50, 50), 402.4939126451495 0.0\n",
+      "09:38:55 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:55 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003512257229105658\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.04335022980424852\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 399.096992697314 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003544250745924779\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.04335023572164354\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 399.0968837422249 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0035442742992353128\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.04353356028718269\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 395.74268018077544 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00357613058656368\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.04353356028703281\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 395.7426801835004 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003576130548332662\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.043716891526303536\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 392.43046532244324 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003610362367128101\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.043716899713157176\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 392.43031834173314 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0036103867263656666\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.0439002393407637\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 389.15936620111734 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0036469289715811105\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.043900239273639174\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 389.15936739118564 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0036469289214658427\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.044083587288017645\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 385.92899425318603 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003679657635020478\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.04408359627599934\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 385.92883688297695 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003679682584072768\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.0442669536598046\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 382.73835987332967 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0037122813059081473\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.044266953532696496\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 382.73836207131905 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003712281244928272\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.044450321310543384\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 379.58710814572163 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0037442059186650308\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.04445033489802852\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 379.586876082975 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003744232067644773\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.04463370769670316\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 376.4742991902858 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0037793018298847526\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.044633710552296924\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 376.47425101783443 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0037793022730952105\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.044817098385446785\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 373.39955207400425 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003810946702098358\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.04481710774712022\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 373.3993960780251 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0038109725794442163\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.04500050506534947\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 370.36205667742274 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0038470732616083273\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.045000505024255455\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 370.36205735384476 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003847073213481041\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.045183910780897785\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 367.36149046685455 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0038819453064260594\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.045183917496071535\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 367.36138127330986 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003881971197957995\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.04536732943061428\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 364.3970338906209 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003916749776949878\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.04536732960973344\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 364.39703101319816 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003916749766032604\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.045550748362097826\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 361.46831151924454 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003948798778199218\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.04555075484785753\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 361.4682085836751 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003948825066397169\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.04573418282631714\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 358.5745121916558 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003985209079550122\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.045734181912906235\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 358.57452651467895 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.003985208877786701\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.04591761596959354\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 355.71534498279306 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004018945123586203\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.04591762397298971\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 355.7152209811426 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004018972135287221\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.046101066236042376\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 352.8899770172652 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004054161708219571\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.046101066168421356\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 352.88997805250295 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00405416165301274\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.046284516017417454\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 350.098145095725 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004092552139568612\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.0462845229713178\n",
+      "09:38:56 - utils.forces_mesh - Got k_square with: (50, 50, 50), 350.09803989652346 0.0\n",
+      "09:38:56 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:56 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004092579449082457\n",
+      "09:38:56 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:56 - utils.forces_mesh - Using mesh spacing: 0.04646797921334489\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 347.33911274077457 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004126962796183382\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.04646797940033043\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 347.33910994541344 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004126962785305562\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.046651442630536666\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 344.6125638888823 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0041634915406915055\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.04665144912631636\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 344.6124679207107 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004163519231970291\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.046834918792468594\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 341.91780776518425 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004200536009861196\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.046834918812441284\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 341.91780747356347 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004200535968566456\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.0470183953844423\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 339.2545304452408 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004234710598706227\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.04701840305051075\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 339.25441981841936 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004234738965262875\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.04720188749817544\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 336.62202830800646 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004271052530462094\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.04720188742834397\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 336.6220293040179 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0042710524721939775\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.047385379532351335\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 334.0200498412195 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0043088234827445004\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.04738538737873599\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 334.0199392227473 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004308852367663674\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.0475688850158702\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 331.44793643302756 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004345896069859544\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.04756888578698537\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 331.4479256871577 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0043458961643274415\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.047752391686007645\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 328.9054024381975 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0043815346769568685\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.047752398465557455\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 328.9053090468508 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004381563842378505\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.04793591069138259\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 326.3918442788715 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0044162450088847845\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.047935910842326734\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 326.3918422233378 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004416244989515239\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.048119430313795286\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 323.9069817375696 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0044526771618258396\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.04811943803879326\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 323.9068777388249 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004452706966132375\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.048302965244471086\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 321.45018416725884 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004490088231086842\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.048302965241434404\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 321.4501842076763 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00449008818255142\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.0484865001966901\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 319.0212324699361 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004528603343068513\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.0484865080045378\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 319.0211297251067 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004528633660060709\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.048670051028486316\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 316.61950108952396 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00456729350952105\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.04867005094157273\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 316.6195022203442 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0045672934444130646\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.048853601359860166\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 314.24479633180465 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0046075740602561175\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.04885360818792295\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 314.244708490471 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004607604709955599\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.04903716551334414\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 311.8965319876235 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0046458732996450475\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.049037165487016976\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 311.8965323225267 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004645873245021246\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.049220729454371615\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 309.57449419740783 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004683200317038647\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.04922073580302766\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 309.57441433749403 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004683231368812763\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.04940431026514713\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 307.2780813612818 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004721682613079793\n",
+      "09:38:57 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:57 - utils.forces_mesh - Using mesh spacing: 0.049404308883147285\n",
+      "09:38:57 - utils.forces_mesh - Got k_square with: (50, 50, 50), 307.27809855242475 0.0\n",
+      "09:38:57 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:57 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004721682298472891\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.04958788898349953\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 305.00715188042665 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004758079446932899\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.04958789734688551\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 305.00704899676106 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004758111372740997\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.049771485861969555\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 302.7610836045174 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004799108476378508\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.04977148584489077\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 302.7610838122987 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0047991084218125864\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.049977997650030526\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 300.264202579169 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004845133954806579\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.04997799521900648\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 300.2642317900052 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004845164359027811\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.050310297853312536\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 296.3108036628225 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004922395317244512\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05031029133316833\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 296.3108804657684 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0049223939887840075\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05064258828001145\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 292.4350847912469 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004994604386625169\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.050642595640101984\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 292.43499978973705 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.004994637666482572\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.050974899050386435\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 288.63468228158604 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0050682085012926795\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05097489934929955\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 288.6346788965203 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005068208506584557\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05130721027972318\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 284.9078795554035 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0051464140288577445\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05130721722322007\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 284.90780244122936 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005146448217295593\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05163953127454546\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 281.25268699098905 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0052206221823183595\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05163953254876574\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 281.25267311100765 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005220622384183379\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05197185493200429\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 277.6673582032621 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005295545438992081\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05197186221808958\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 277.6672803492916 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005295580669618131\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.052304192070665056\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 274.15001077832073 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005372723060553249\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.052304192009613226\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 274.15001141832147 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0053727229906099915\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05263652914644301\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 270.6990770611762 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005452517502932287\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.052636536610191076\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 270.69900029208384 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0054525537953769646\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05296888154377233\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 267.31274022245987 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005533779290414563\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05296888143280443\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 267.3127413424811 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005533779208107055\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05330123380354168\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 263.9895521401686 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005615876048208252\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.053301241520417486\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 263.9894757001315 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005615913461460528\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05363360151051344\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 260.727800847546 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005694816872719718\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05363360154305252\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 260.727800531183 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00569481681878787\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05396596927406683\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 257.5261290405456 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00577621561410706\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05396597696545258\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 257.5260556338265 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005776254069491029\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05429835236677216\n",
+      "09:38:58 - utils.forces_mesh - Got k_square with: (50, 50, 50), 254.38292712599508 0.0\n",
+      "09:38:58 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:58 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005862551287474172\n",
+      "09:38:58 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:58 - utils.forces_mesh - Using mesh spacing: 0.05429835237383229\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 254.3829270598429 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005862551226364846\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.054630735447992684\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 251.29692200492758 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005944130715747177\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.054630743062562326\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 251.29685195214512 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.005944170251698846\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05496313388214813\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 248.26659550107564 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006033189039123624\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.054963133838562994\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 248.2665958948208 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006033188965098196\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.0552955322531814\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 245.29075380722793 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006117046701101856\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.055295539939895555\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 245.29068561077733 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006117087382623201\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.0556279463125513\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 242.3679612774731 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006196851214177028\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05562794622214429\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 242.3679620652701 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006196851127829226\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05596036022882944\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 239.49710077352574 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006280908861791813\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05596036802871063\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 239.49703401024786 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0062809506377387424\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05629279006690968\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 236.67681414855275 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006372140618148097\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.056292789989733194\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 236.67681479751278 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006372140532597709\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.056625219792783454\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 233.90605369815466 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006458820184847846\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05662522771910394\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 233.9059882144722 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006458863151832698\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.056957666454543254\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 231.18352815840785 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006550840706041014\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.056957666119223704\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 231.18353088044196 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006550840558921798\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.057290112676134486\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 228.5082638074344 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00664210312632277\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05729012129386635\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 228.50819506180244 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006642147451330177\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05762257979183505\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 225.8790057656731 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006727278504998073\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05762257868410425\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 225.87901445022484 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006727278174476611\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05795504474346114\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 223.29488378882542 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0068168782299057335\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05795505351535413\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 223.2948161944205 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006816923733983116\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05828752775823198\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 220.75471732351036 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006911932841641988\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05828752795439285\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 220.7547158376544 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.006911932814319644\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05862001106054615\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 218.25764823887346 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.007004873781195903\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05862001951810347\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 218.25758525948675 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00700492044100415\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05895251126114798\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 215.80258548005176 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.007102077804204426\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.0589525112014071\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 215.8025859174288 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.007102077713933678\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05928501134643405\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 213.38871529002273 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.007192628790264821\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.059285019816488926\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 213.38865431630603 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0071926766804701805\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05961752804220888\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 211.0150028512461 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.007288587267753154\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05961752817203214\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 211.01500193223265 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.007288587221627186\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05995004496587275\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 208.68067702147584 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00738322607517377\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.05995005334065495\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 208.68061871777132 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0073832751875502756\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.06028257896794842\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 206.38475584450737 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:38:59 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0074787136960718596\n",
+      "09:38:59 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:38:59 - utils.forces_mesh - Using mesh spacing: 0.06028257881509558\n",
+      "09:38:59 - utils.forces_mesh - Got k_square with: (50, 50, 50), 206.38475689112806 0.0\n",
+      "09:38:59 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.007478713578245218\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.060615112597860676\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 204.1265196441863 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.007580591895998461\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.060615120773269915\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 204.12646458143297 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.007580642248123612\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06094766922413486\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 201.90499332578707 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.007682047207112373\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06094766705995425\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 201.90500766460923 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.007682046579478452\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06128022262319255\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 199.7195572729021 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00778396951549932\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06128023410203576\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 199.71948245108382 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.007784022034944901\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.061612796267050074\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 197.56928330402687 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.007882128183596838\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06161279789277874\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 197.56927287781497 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.007882128515345463\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06194537243276277\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 195.45353367943903 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.007983923534216552\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06194538172279995\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 195.4534750545534 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0079839768064416\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06227796551117981\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 193.3714839661576 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.008080758675123666\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.062277965525100676\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 193.37148387970967 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.008080758592403623\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.0626105585057013\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 191.32252668098656 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.008180987311071848\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.0626105674605264\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 191.32247195349518 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.008181041784521077\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06294316958656831\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 189.3058549205543 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.008280733810789647\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06294316952306889\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 189.30585530251201 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.008280733705612754\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06327578144351298\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 187.32089699779354 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.008389438931372629\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06327579310756759\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 187.32082793754589 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00838949548598923\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06360841687666996\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 185.36685854929217 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.008497328162012152\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.0636084168151867\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 185.3668589076397 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.008497328054802186\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06394105222751012\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 183.44323719509993 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.008603036317727821\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06394106401351385\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 183.44316956837176 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.008603094312056001\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06427371161356366\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 181.5492686391455 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.008710571842355595\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.0642737114797085\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 181.5492693953272 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.008710571713013326\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06460637543106862\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 179.68445628414614 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.008819508126614507\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06460640131455775\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 179.6843123089473 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.008819571395689285\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06493909506042184\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 177.8479234326243 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00892932193973739\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.0649390937568759\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 177.84793057263593 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.008929321485855967\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06527181279659944\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 176.03941403882325 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.009038115137953827\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06527184082183646\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 176.03926286964577 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.009038180494567574\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06560458839143823\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 174.25804337064477 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.009150113507499887\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06560458822335269\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 174.25804426357803 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.009150113362855577\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06593736024713492\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 172.50359505032165 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00926360644804626\n",
+      "09:39:00 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:00 - utils.forces_mesh - Using mesh spacing: 0.06593737806345823\n",
+      "09:39:00 - utils.forces_mesh - Got k_square with: (50, 50, 50), 172.50350182916253 0.0\n",
+      "09:39:00 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:00 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.009263670486402942\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.0662701682797997\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 170.77532346335983 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.009375650870731951\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06627016815446751\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 170.77532410931093 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.009375650735102041\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06660297617371924\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 169.07289576812323 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.009489673364579568\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.0666029943257993\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 169.07280360937415 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00948973901014144\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.0669358217232594\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 167.39561020342165 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.009603262822360938\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06693582131463316\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 167.3956122472373 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.009603262602511353\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06726866573189816\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 165.7431682246723 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00971825119146626\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06726868171303058\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 165.7430894729222 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.009718317738536986\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06760154165267318\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 164.11491914253588 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.009840675764078672\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.0676015418056608\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 164.1149183997259 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.009840675703484063\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06793441769823971\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 162.51054584022592 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.00995678574921616\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.0679344331358207\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 162.510471981674 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.009956853723990602\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06826732460444851\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 160.92943887983552 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.010070257811145416\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06826732455836093\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 160.92943909712392 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.010070257689960602\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06860023146318373\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 159.371294885057 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.010194582204980415\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06860024703487011\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 159.37122253314436 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.010194651798075518\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06893318007914706\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 157.83547989286313 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.010310976017362618\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06893317655664966\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 157.8354960237049 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.010310974853417726\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06926612416784339\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 156.32177914298265 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.010427979825140293\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06926614729271274\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 156.32167476529582 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.010428053240278012\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06959910879110676\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 154.82956951404063 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.010552755591857067\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06959911187041268\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 154.82955581364743 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.010552756412895353\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06993209808015721\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 153.35860429097576 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.010679088344447179\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.06993211672655364\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 153.3585225092399 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.010679162091741908\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.0702651229212623\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 151.90834865611768 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01080049826175362\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.07026512247515848\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 151.90835058500903 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01080049800922226\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.07059814611177373\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 150.47857500492762 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.010926726035880966\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.07059816248301098\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 150.47850521500447 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.010926800734056738\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.07093119641318935\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 149.0687785323998 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.011057410196110565\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.0709311984391392\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 149.06877001694062 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.011057410709623797\n",
+      "09:39:01 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:01 - utils.forces_mesh - Using mesh spacing: 0.07126424975905832\n",
+      "09:39:01 - utils.forces_mesh - Got k_square with: (50, 50, 50), 147.67868908250819 0.0\n",
+      "09:39:01 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:01 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0111811190443734\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07126426310795586\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 147.678633757513 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.011181194484785089\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07159732795808904\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 146.30785198367056 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.011311105532765108\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07159732789770912\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 146.30785223044114 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.011311105392842472\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07193040592380129\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 144.9560149386702 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.011446131659435452\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07193041893502317\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 144.95596249758248 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.011446208740739917\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07226351022982902\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 143.62272280341057 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.011574600827182278\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07226351014405585\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 143.62272314435648 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.011574600676045502\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07259661548621166\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 142.3077379469106 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.011706907200237725\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.0725966318631368\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 142.30767374109692 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.011706987084319402\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07292975380199485\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 141.01060258037165 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.011840534031941978\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07292975372880828\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 141.01060286338597 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.011840533881676524\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07326289213703685\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 139.73112173698732 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.011977001755130482\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07326290901085697\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 139.7310573716059 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.011977083595570485\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07359606409523156\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 138.46885003496814 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.012116199706707128\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.0735960641611968\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 138.46884978674478 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.012116199598980854\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07392923669987139\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 137.2236032365678 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.012247407351156824\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07392925511723525\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 137.22353486588796 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01224749149988673\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07426244631542556\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 135.99494337178987 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.012385442160808793\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07426244623479006\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 135.99494366712136 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.012385442001589482\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07459565587892825\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 134.78271171165554 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.012524026602465523\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07459567462394912\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 134.7826439730249 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.012524112706049643\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07492890299746313\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 133.58648258184314 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.012661357764192027\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.0749289030027609\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 133.586482562953 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01266135763071199\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.0752621502008115\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 132.40610800369893 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01279880831024921\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07526216916848516\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 132.40604126537457 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01279889632174166\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07559543554318737\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 131.2411769025763 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01294398060008426\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07559543547361236\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 131.24117714415456 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.012943980437968102\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.07592872101174164\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 130.09155189803488 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:02 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01308784180190965\n",
+      "09:39:02 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:02 - utils.forces_mesh - Using mesh spacing: 0.0759287407754008\n",
+      "09:39:02 - utils.forces_mesh - Got k_square with: (50, 50, 50), 130.0914841744106 0.0\n",
+      "09:39:02 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.013087932017448605\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07626204635450184\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 128.9568315925193 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.013232115340121685\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07626204626215238\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 128.95683190483967 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.013232115166706578\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.0765953704027238\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 127.83689747179872 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.013371506907244531\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07659538683686451\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 127.83684261498756 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.013371597855026361\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07692872675446338\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 126.73138303175426 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.013523230500748367\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07692872697357189\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 126.73138230984131 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.013523230433303673\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07726208483683839\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 125.64014168707047 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.013667229935083404\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07726210514823406\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 125.64007562813282 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.013667324215387093\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.0775954841057942\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 124.5628021359015 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01381317952468223\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07759548384491977\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 124.56280297345671 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01381317928422678\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07792888301621792\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 123.49926150616552 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.013961520300098302\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07792890381726325\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 123.4991955764971 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.013961616723136516\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.0782623239406457\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 122.4491525482047 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.014112378601117592\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.0782623238903919\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 122.4491527054588 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.014112378432221157\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07859576484831399\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 121.41238046836924 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.014265660214093291\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07859578590060412\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 121.41231542650252 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.014265758764212572\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07892924837711934\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 120.38859030378293 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.014415654372163873\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07892924822177916\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 120.38859077765511 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.014415654161408286\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07926273088479219\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 119.37769824465492 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.014564404393784073\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07926274980572479\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 119.37764125099478 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.014564504158763284\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07959623057013987\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 118.37943439174288 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.014719093476412867\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07959623751002076\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 118.37941374908024 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01471909588583141\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.07992974528052188\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 117.39359581879172 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.014875024099340384\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.079929767637273\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 117.39353014766282 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.014875127211603792\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.0802632981171385\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 116.41991033980145 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.015036641384449198\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.08026329799970067\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 116.4199106804827 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.015036641179799947\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.08059685082931245\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 115.45828907725792 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.015195972977454838\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.08059687351736233\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 115.45822407416442 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.015196078369072566\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.08093044937645244\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 114.50840348875371 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.015357943333708175\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.08093044926274451\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 114.50840381052413 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.015357943126472082\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.08126404770822715\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 113.5701926532087 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.015515264412552578\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.081264070432429\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 113.57012913702974 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01551537196070183\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.0815976933895386\n",
+      "09:39:03 - utils.forces_mesh - Got k_square with: (50, 50, 50), 112.64333470382572 0.0\n",
+      "09:39:03 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:03 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01567773017309061\n",
+      "09:39:03 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:03 - utils.forces_mesh - Using mesh spacing: 0.08159769279383489\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 112.64333634853034 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01567772977668362\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08193133819810772\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 111.7277792819518 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.015842979306640814\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08193136187830397\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 111.72771469776089 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01584308942398942\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08226503131759055\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 110.82321083582562 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.016008920776235877\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08226503119942397\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 110.82321115420152 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.016008920559210146\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08260024112240161\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 109.92554644792821 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.016176274935064783\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.0826002479965875\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 109.92552815140667 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.016176380710718998\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08293771194451804\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 109.03279956332153 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.016344104631669805\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08293770607421269\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 109.03281499793812 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.016344102143392773\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08327517399346318\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 108.1509069702569 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.016504669347588874\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08327518976996595\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 108.15086599183522 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01650478077712948\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08361267411028583\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 107.27957312935462 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.016677109251195924\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08361267389550076\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 107.27957368051631 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.016677108987341635\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.0839501739338242\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 106.41872781539885 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0168524987445463\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08395019011918459\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 106.41868678094039 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01685261263523085\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08428769576224804\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 105.56814750423557 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.017025012526426395\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08428769928916902\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 105.56813866948248 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01702501376931973\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.0846252229422757\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 104.72771108001808 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.017204499976267173\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08462523402092081\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 104.7276836593301 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.017204614116461226\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.0849627688272423\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 103.89722527670088 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.017380357156555955\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08496276880243392\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 103.89722533737498 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01738035696071919\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08530031473034061\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 103.07657897296986 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01756079393257056\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08530032601223114\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 103.0765517069872 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.017560910483828872\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08563788295477082\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 102.26556407699134 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.017747336718217873\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08563788304390485\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 102.26556386411028 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01774733656555396\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08597545130364104\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 101.46408306382796 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.017931163668428972\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08597546242404608\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 101.46405681630114 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01793128257323031\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.086313040582362\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 100.67193855090113 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.018097778175473186\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08631304098968284\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 100.67193760073694 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.018097778152932398\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08665063073561452\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 99.88903251622165 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.018283143384837514\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08665064203569095\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 99.88900646324382 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.018283264662648097\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08698824327629495\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 99.115172840323 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.018462178364943908\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08698824321147924\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 99.11517298802619 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.018462178140186455\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:04 - utils.forces_mesh - Using mesh spacing: 0.08732585560540684\n",
+      "09:39:04 - utils.forces_mesh - Got k_square with: (50, 50, 50), 98.35027179068373 0.0\n",
+      "09:39:04 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:04 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.018644420680302594\n",
+      "09:39:04 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.08732586665967235\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 98.35024689107517 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.018644544212013815\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.08766349049454059\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 97.59414091480082 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.018829739981935815\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.08766349036569787\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 97.59414120167725 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.018829739725414373\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.08800112520340564\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 96.84669689622234 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01901346595842207\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.08800113648992225\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 96.84667205422991 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01901359199872716\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.08833878281265228\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 96.10775695423598 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01920410867266939\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.08833878274653317\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 96.1077570981039 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.019204108438750537\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.0886764403338205\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 95.3772422137025 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.019393714627745293\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.08867645175281602\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 95.37721764997198 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.019393843208782083\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.08901412088729055\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 94.65497590531712 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.019588300879039698\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.08901412084460958\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 94.6549759960885 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.019588300650979086\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.08935179987749242\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 93.94088622101297 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0197821229947793\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.089351806862767\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 93.94087153294156 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.019782252149241134\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.08968948391463272\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 93.23483644850045 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01997511046073689\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.08968948690340728\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 93.23483023466397 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.01997511157861267\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.09002717257259052\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 92.53670725981326 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.020177424643232987\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.09002717548767025\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 92.53670126713665 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02017755453040746\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.09036489804101411\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 91.84631522467328 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.020377628583255737\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.09036488671807241\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 91.84633824181135 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.020377623258814218\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.09070260644713013\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 91.1636550141884 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.020577466323118077\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.09070262611293511\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 91.1636154826656 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.020577606375975305\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.09104036564121643\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 90.48847660187674 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.020783536575370895\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.09104036559683015\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 90.48847669011113 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02078353633305953\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.09137812480998964\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 89.82077134051802 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02097844655445471\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.09137814466617167\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 89.82073230498281 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.020978589356597882\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.09171590227760973\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 89.16039372041722 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.021176841666963972\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.09171590943028418\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 89.16037981366429 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02117684474376543\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.09205369074732195\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 88.50725107478794 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.021379272722486468\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.0920537006937332\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 88.50723194835493 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02137941358182499\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.0923914920993183\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 87.86123460357017 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02158119845765946\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.09239149205198283\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 87.86123469359906 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.021581198204978273\n",
+      "09:39:05 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:05 - utils.forces_mesh - Using mesh spacing: 0.0927292934035826\n",
+      "09:39:05 - utils.forces_mesh - Got k_square with: (50, 50, 50), 87.22226542922189 0.0\n",
+      "09:39:05 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:05 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.021783805671106535\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09272930349080966\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 87.22224645289585 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.021783949227611253\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.0930671146067148\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 86.59020430215335 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.021992464801957698\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09306711471439799\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 86.59020410177519 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.021992464617888983\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09340493599426258\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 85.96498842526664 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.022203407142443503\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09340494598863547\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 85.96497002867972 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02220355338505775\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09374277753087279\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 85.3464829566756 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.022416863809131486\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09374277744158332\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 85.34648311925967 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02241686352693203\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09412832205739052\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 84.64876562018593 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.022645169716571243\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09412834758382216\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 84.64871970881723 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.022645326304990367\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.0945241024218193\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 83.94138665682891 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.022902986143369223\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09452411259783933\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 83.94136858336255 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02290299082993567\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09491989975935766\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 83.24280797903232 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.023149952441754072\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09491991514899878\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 83.24278098623877 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.023150107471427196\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09531571789274684\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 82.55287771734979 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.023398612559998828\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09531571782861814\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 82.55287782843342 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.023398612278529192\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09571153596340487\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 81.87148953759728 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.023654333860186956\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09571155154962385\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 81.87146287275193 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02365449230130536\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09610738533664254\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 81.198450006126 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.023909824434322158\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.0961073853147063\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 81.19845004319261 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02390982416796151\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09650323473659617\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 80.53367571191934 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.024169695519911022\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09650325053457998\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 80.5336493445256 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02416985745451311\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09689911552251607\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 79.87698017163446 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.024440027026339614\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09689911559989683\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 79.87698004405965 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.024440026804263288\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09729499821927368\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 79.22828122836012 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.024700474287718203\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09729501928548467\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 79.22824691952246 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02470064238760273\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09769092325206774\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 78.58738454663833 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0249632768274515\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09769092315849592\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 78.58738469718591 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.024963276512929337\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09808684818692592\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 77.9542332354383 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.025228881508143425\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09808686952076062\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 77.95419932544496 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.025229053253594185\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09848281496437794\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 77.32863712576537 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02550267099785087\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09848281527068536\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 77.32863664474061 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.025502670884027405\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09887878224981117\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 76.71054089514121 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.025773137956801057\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.09887880326974452\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 76.71050828046076 0.0\n",
+      "09:39:06 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:06 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.025773313153840502\n",
+      "09:39:06 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:06 - utils.forces_mesh - Using mesh spacing: 0.0992747915445178\n",
+      "09:39:06 - utils.forces_mesh - Got k_square with: (50, 50, 50), 76.09976151599136 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.026046149316148903\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.09927479145270546\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 76.09976165675008 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0260461489897025\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.09967080074317813\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 75.49624800564945 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.026319706971757784\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.09967082202584487\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 75.49621576429168 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.026319885934024706\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10006684151989242\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 74.8998381558936 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.026593306556653956\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10006684521299203\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 74.89983262733803 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.026593308235460977\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10046288784578294\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 74.31045961436398 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02687083184637241\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.1004629036173812\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 74.31043628247568 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02687101151745258\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10085896205258704\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 73.72796967062303 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.027150515000916517\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10085896204238365\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 73.72796968554042 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.027150514705354567\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.1012550362761413\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 73.15230181429581 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0274308412572991\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10125505215921127\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 73.15227886466491 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.027431024665884346\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10165114250434648\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 72.58330424521665 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.027704879489568207\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10165114242831352\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 72.58330435379825 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.027704879152131552\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10204724880689753\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 72.02091956004014 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.027998829899088404\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10204726536920194\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 72.0208961820046 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.027999017409905153\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10244343140609402\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 71.46493933551884 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.028284956153554343\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10244341704092541\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 71.46495937791892 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.028284947918829163\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10283959253871\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 70.9154019590854 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.028572094787210785\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10283963089227832\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 70.91534906394796 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.028572298174465806\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10323584526164664\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 70.3720540205999 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02886968541289004\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10323584508914863\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 70.37205425577093 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.028869685007976913\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10363209782012062\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 69.83492709497453 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.029163894123411135\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10363213671528815\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 69.83487467415671 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.029164101861803144\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10402846934827092\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 69.30376783871961 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.029466237374673125\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10402845567959051\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 69.30378605087338 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.029466229316511546\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10442482050116508\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 68.77867239350772 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0297615665115541\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10442488028263908\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 68.77859364428193 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.02976179024312832\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10482130573787618\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 68.25934754222018 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.030067740335920502\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10482130545409207\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 68.25934791181905 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.030067739851879483\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.1052177906778784\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 67.74588281710868 0.0\n",
+      "09:39:07 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:07 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03038410158874646\n",
+      "09:39:07 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:07 - utils.forces_mesh - Using mesh spacing: 0.10521785127192906\n",
+      "09:39:07 - utils.forces_mesh - Got k_square with: (50, 50, 50), 67.745804788595 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.030384330207325227\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10561439786264204\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 67.2380343495748 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.030700289313894496\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.105614397605299\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 67.23803467724301 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.030700288836290696\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10601100479623637\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 66.73587540043637 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03100312272416508\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.106011066180836\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 66.73579811503677 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.031003356195643345\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10640772318111935\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 66.2391822266407 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.031321211446767055\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10640772703979495\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 66.23917742256266 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03132121338374932\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10680444746983975\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 65.7480063051059 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03163001638105235\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10680450341390024\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 65.74793742768293 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.031630251078837546\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10720128048841726\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 65.2621410530486 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03195357765295971\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10720128025520559\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 65.26214133699841 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03195357717254929\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10759811328029922\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 64.78164191919407 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03226866246902424\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10759816994354221\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 64.78157368872226 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.032268902087642444\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10799506033595963\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 64.30629382305698 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0325867985628366\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10799506010152848\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 64.30629410224378 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03258679807321212\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10839200715466202\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 63.83615881604054 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.032905354414891674\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10839206451361783\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 63.8360912543706 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03290559892998451\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10878906966885582\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 63.37102588189143 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.033231941296740335\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10878906942140532\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 63.371026170177615 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.033231940790521414\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10918613193108584\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 62.91095846472352 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03355074408698709\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10918619001885288\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 62.910891526658766 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03355099358752019\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10958331132970134\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 62.45574946662849 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03388681958941518\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10958331109217001\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 62.45574973738499 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03388681908047253\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10998049084830441\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 62.00546319648983 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.034219179962688084\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.10998055072121993\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 62.005395685519495 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03421943528193913\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.11037779108804546\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 61.559894405679856 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.034551341905036725\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.11037779084239796\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 61.559894679684874 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.034551341382110655\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.110775091083533\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 61.119111444244695 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03488684335002639\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.11077515169757213\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 61.1190445578511 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03488710384525309\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.11117251329799371\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 60.682912324719055 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.035225296758380736\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.11117251304985931\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 60.682912595604705 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.035225296224799314\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:08 - utils.forces_mesh - Using mesh spacing: 0.11156993522360237\n",
+      "09:39:08 - utils.forces_mesh - Got k_square with: (50, 50, 50), 60.25136655245775 0.0\n",
+      "09:39:08 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:08 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0355712410575247\n",
+      "09:39:08 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11156999645989085\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 60.25130041336718 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03557150678250319\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11196748061585415\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 59.82427592664804 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03591068122536842\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.1119674803674946\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 59.824276192045296 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03591068068239878\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.1123650257611124\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 59.401710654490856 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03625933607298609\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11236508774657716\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 59.40164511737963 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03625960714005199\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11276269589179666\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 58.98347601494248 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03661344541794877\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.1127626956367056\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 58.98347628180655 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.036613444861127435\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11316036576573962\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 58.569643191358 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03697078011158456\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11316042851152464\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 58.569578239373115 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.036971056707380885\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11355816214604753\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 58.16002078176163 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03732000929263368\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11355816189310408\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 58.16002104085699 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.037320008727661225\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.1139559582704961\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 57.75468085795867 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03768106125913655\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.1139560217663611\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 57.754616496596434 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.037681343373188944\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11435388201007335\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 57.353435664278024 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03804571357445415\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11435388188688211\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 57.35343578784952 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.038045713086012456\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11475179726654705\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 56.9563658324453 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.038412064955922004\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11475183605224615\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 56.95632733036689 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.038412335702949156\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11514979068788023\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 56.563328476502925 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.038777792861561924\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11514979053129837\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 56.56332863033371 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03877779234180987\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11554777789742587\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 56.174351501953424 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03915493392973796\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11554779898725354\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 56.17433099602785 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0391551977374808\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11594580769658647\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 55.78933218774886 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.039517572302712814\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11594580761222018\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 55.789332268937464 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03951757182300921\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11634383735124443\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 55.40825787502132 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03990037336695873\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.1163438585137615\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 55.40823771790927 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.03990064214732368\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11674196171037465\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 55.03098542973174 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04027164515291459\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11674194427889084\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 55.03100186378735 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.040271632696234225\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11714006000995125\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 54.65757747353272 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04063792443240766\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11714010758270232\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 54.65753307864776 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.040638216405100805\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.1175382715146771\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 54.28785268061196 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.041016365523573586\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.11753827130550576\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 54.28785287383349 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.041016364939380434\n",
+      "09:39:09 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:09 - utils.forces_mesh - Using mesh spacing: 0.1179364827666145\n",
+      "09:39:09 - utils.forces_mesh - Got k_square with: (50, 50, 50), 53.92186691019306 0.0\n",
+      "09:39:09 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:09 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04140427876944476\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.11793653083602873\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 53.92182295448214 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.041404576369817495\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.11833479094135635\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 53.55948194865849 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.041792220790560594\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.11833479074997344\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 53.55948212190202 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04179222020888288\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.11873309892527883\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 53.20073806325337 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04217943191461227\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.11873314757053244\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 53.200694470323896 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04217973526497171\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.11913148972595966\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 52.845512995109566 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04258261763686655\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.11913149461452388\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 52.845508658075445 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0425826206766836\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.11952988961272792\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 52.49382589886794 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04296972568048653\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.11952993618485941\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 52.493784992816046 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04297003298931071\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.11992837829820413\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 52.145560654264955 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04335602552016281\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.1199283781174123\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 52.14556081148365 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04335602492624075\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.1203268667588202\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 51.80074993983637 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04375022160125047\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12032691374112314\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 51.80070948807085 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04375053456445084\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12072544750842829\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 51.45926934886521 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04415214294896324\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12072544812743802\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 51.45926882115893 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04415214293002685\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12112402927653454\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 51.121153461342224 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.044556500887125136\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.1211240756002736\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 51.121114358917545 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04455681890445229\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12152270361393569\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 50.78628169917879 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.044984756271065435\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.1215227034338704\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 50.78628184968313 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04498475565714913\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12192137794795821\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 50.45468958735928 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04539254205264095\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12192142534195316\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 50.454650361294924 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0453928666069933\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12232014755860598\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 50.12625634776016 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04579312112758914\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12232014745596365\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 50.12625643188492 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.045793120561495454\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12271891710593463\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 49.80101964204354 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04621684258330667\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12271896492582579\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 49.80098083013088 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.046217173118642776\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.1231177830236172\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 49.47886061305101 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04663563719997084\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12311778281452446\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 49.478860781112374 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04663563654332463\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12351664872070645\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 49.159817712097876 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.047047743581507255\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12351669713337454\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 49.159779175486584 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.047048080274085\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12391561202517387\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 48.843773757845085 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.047469376222074595\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12391561183441047\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 48.843773908231384 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04746937556877025\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12431457533588208\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 48.53076775707903 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:10 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.047897284472197765\n",
+      "09:39:10 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:10 - utils.forces_mesh - Using mesh spacing: 0.12431462491185208\n",
+      "09:39:10 - utils.forces_mesh - Got k_square with: (50, 50, 50), 48.530729049494795 0.0\n",
+      "09:39:10 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.047897627899856667\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12471363857440476\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 48.220683628319 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04832715873442027\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12471363837959304\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 48.220683778967384 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04832715806712522\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12511270161155164\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 47.913562080201224 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04875440480818881\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12511275175226322\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 47.913523676128385 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04875475457355346\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12551186574612982\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 47.6092886426539 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04919145345182216\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12551186553929217\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 47.60928879956964 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04919145276414389\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12591102966523993\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 47.30790460767865 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04963637370032588\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12591108040057186\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 47.30786648265023 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.04963673000952637\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12631029583594122\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 47.009297235200314 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05007169303419738\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12631029564480833\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 47.00929737746936 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0500716923477082\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12670956182040527\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 46.71350831655862 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.050509243312482244\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12670961314382057\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 46.71347047418435 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0505096060998024\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.1271089312224718\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 46.420426819954095 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.050961249312224\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12710893102949194\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 46.420426960907314 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05096124861302688\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12750830060059837\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 46.13009491185321 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05142214869797762\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12750835301007202\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 46.130056990361155 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05142251865736375\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.1279077758935725\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 45.842402367770354 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05187229242007525\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12790777559283795\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 45.84240258333808 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05187229162196352\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12830725082951888\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 45.55739302137589 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05233563001177133\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.1283073039723166\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 45.557355283121765 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05233600687358844\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12870683294881902\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 45.27495794980793 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05279935929407173\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12870683275005268\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 45.274958089647235 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.052799358566898234\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12910641486184105\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 44.99514135675355 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.053261992213707504\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12910646857840025\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 44.995103915040545 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05326237594643383\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12950610501267112\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 44.7178360828093 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.053723743975307506\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12950610481094138\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 44.71783622212192 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05372374323396848\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.12990579209144526\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 44.44308858416383 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05419594446314248\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.1299058378022151\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 44.44305730724094 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05419632796714928\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.1303055713034067\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 44.17080294956087 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.054669584014668274\n",
+      "09:39:11 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:11 - utils.forces_mesh - Using mesh spacing: 0.13030557113364027\n",
+      "09:39:11 - utils.forces_mesh - Got k_square with: (50, 50, 50), 44.170803064655246 0.0\n",
+      "09:39:11 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:11 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05466958328814281\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13070535074690692\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 43.90101179897097 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05514458248187913\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13070539817089122\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 43.900979941671345 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.055144973906903705\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13110522573960726\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 43.63362130932017 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.055623104268054585\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13110522556266613\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 43.63362142709706 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05562310352365349\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13150510055604148\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 43.36866643364866 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.056095910824084716\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13150514851287198\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 43.36863480259195 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05609630920882312\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13190507196068157\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 43.10605443582506 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.056580671491988324\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13190507179503008\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 43.10605454409355 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.056580670745383706\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13230504320666636\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 42.84582064602667 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05705958957514097\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13230509168143811\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 42.845789249789846 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05705999499890843\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13270511210214941\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 42.58787365692084 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05754980402004306\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13270511192426726\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 42.587873771093136 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.057549803250913634\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13310518083699074\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 42.33224917550873 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05805876264854421\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13310522989712803\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 42.33221796973904 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.058059175426620445\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13350534854797136\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 42.07885691013871 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05853604343634332\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13350534832219907\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 42.078857052458694 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.058536042612978595\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.1339055160668039\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 41.8277331063356 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05903632144447093\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13390556590513114\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 41.827701970604245 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0590367415987287\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13430578403952786\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 41.5787884501684 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05953331548537681\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13430578385593162\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 41.57878856384495 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.05953331468657505\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13470604051861734\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 41.33206670437474 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.060049244865040347\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13470605697761906\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 41.3320566040937 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.060049642202648516\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13510633027897212\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 41.08751422824431 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.060540789855786065\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13510633021915508\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 41.087514264626506 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.060540789155377236\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13550661997860036\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 40.84512582749334 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06104821151971555\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13550663661432472\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 40.84511579863823 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06104861553844497\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13590695548727894\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 40.60484863457221 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0615738952817413\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13590695132811614\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 40.60485111983401 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.061573890855209035\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.1363072847964255\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 40.36668909069807 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06210310215323374\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13630730778852973\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 40.36667547271882 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.062103518855800156\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13670766449984306\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 40.1305891470473 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06262676618117399\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13670766441631077\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 40.130589196089176 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06262676543555346\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13710804412023103\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 39.896554590849675 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0631601592475891\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13710806736444026\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 39.89654106336292 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06316058315067775\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.13750847071759376\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 39.66453425244085 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06370356970705725\n",
+      "09:39:12 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:12 - utils.forces_mesh - Using mesh spacing: 0.1375084705826879\n",
+      "09:39:12 - utils.forces_mesh - Got k_square with: (50, 50, 50), 39.66453433026847 0.0\n",
+      "09:39:12 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:12 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06370356890147022\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.13790889715850563\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 39.43453212206537 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06423707466070053\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.1379089207427957\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 39.434518634390166 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0642375059819041\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.13830937115982778\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 39.206497807648056 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06477302909059697\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.13830937107428998\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 39.20649785614278 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06477302831846168\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.13870984509003303\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 38.98043577795446 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06531456014221336\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.1387098689741988\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 38.980422354034204 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06531499885162967\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.1391103671467846\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 38.75629649784425 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06585470521524675\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.13911036705599722\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 38.75629654843118 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06585470442571587\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.13951088938482092\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 38.53408479075623 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0663910377154251\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.13951091435756524\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 38.53407099539455 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06639148456020463\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.13991144691737567\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 38.31375938658872 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06694202356625702\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.13991145183137155\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 38.313756695262896 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06694202755336737\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.14031201185271902\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 38.09531419848661 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06748643652019498\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.140312029549853\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 38.09530458879257 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06748688360080249\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.14071260745719627\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 37.878715378538274 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0680510397497367\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.14071260739431946\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 37.87871541239016 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06805103896188151\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.141113203010244\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 37.66395862451675 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0686129984796708\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.1411132209303494\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 37.66394905855177 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06861345314202878\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.14151383431282794\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 37.451004158452136 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06917514081137678\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.14151383436408915\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 37.451004131320026 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06917514012244394\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.14191446572516497\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 37.239850629674194 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06972387966983422\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.1419144836669628\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 37.23984121344251 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.06972434161474961\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.1423151338850004\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 37.030458721962304 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.070299820607336\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.14231513358002523\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 37.03045888067163 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07029981955497322\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.142715805061298\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 36.82282635585646 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07087490797029417\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.14271583388233156\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 36.82281148333982 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.070875388246215\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.1431165344930263\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 36.61690561043883 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07145376279208054\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.14311653439035688\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 36.61690566297554 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07145376192616876\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.14351726384968577\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 36.41270741181326 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0720359507113374\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.14351729306152938\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 36.41269258876047 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07203643908477925\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.1439180520664678\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 36.21018294441459 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07262741865722025\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.14391805195534157\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 36.21018300033391 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07262741776913052\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.14431884016729724\n",
+      "09:39:13 - utils.forces_mesh - Got k_square with: (50, 50, 50), 36.00934348453015 0.0\n",
+      "09:39:13 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:13 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07322543316175799\n",
+      "09:39:13 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:13 - utils.forces_mesh - Using mesh spacing: 0.14431886969804264\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 36.009328747958996 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0732259297574394\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.1447196877744803\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 35.81014088483224 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07384273222811426\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14471968766336474\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 35.81014093982218 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07384273132580627\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14512053526613222\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 35.612586755442166 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07444003798107604\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14512056511697713\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 35.61257210464897 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07444054297398807\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14552144288727042\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 35.41663363279698 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07504157241867124\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14552144278184187\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 35.41663368411482 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07504157150821442\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.1459223504033833\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 35.22229342824959 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07565841525167519\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14592238057172358\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 35.22227886436954 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0756589286681282\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14632331867963178\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 35.029519346540795 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07626754923869788\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14632331857375602\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 35.029519397233685 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07626754831350605\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.1467242868505978\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 34.83832359393001 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07687093733494477\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.1467243173383448\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 34.838309115867965 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07687145914050833\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14712531642933335\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 34.64866001398206 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07748757687577608\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14712531632066783\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 34.64866006516449 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07748757593345687\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.1475263458990237\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 34.4605411028803 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07810656628816226\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14752637671162727\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 34.46052670791033 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07810709664877925\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14792743741841052\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 34.273921328686264 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07874141493831693\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14792743731327196\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 34.27392137740625 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07874141398513543\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14832852884839998\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 34.08881344960014 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07938215793207504\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.1483285600236437\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 34.08879912023626 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.07938269716305975\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.1487296830629381\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 33.90517251192327 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0800109136762972\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14872968295343458\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 33.90517256184923 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08001091270366525\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14913083715888398\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 33.72301158757652 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0806259708990918\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14913086863537073\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 33.722997352001755 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08062651872250576\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.1495320546575032\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 33.54228631768453 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08127455739395273\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14953205454424356\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 33.54228636849619 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08127455640251871\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14993327211413243\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 33.36300997262215 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08193089636504322\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.14993330414420836\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 33.362995718022304 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08193145347485777\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.15033455415415276\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 33.1851385739718 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08258675521351597\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.1503345540176344\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 33.18513863424245 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0825867541811884\n",
+      "09:39:14 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:14 - utils.forces_mesh - Using mesh spacing: 0.15073583665164003\n",
+      "09:39:14 - utils.forces_mesh - Got k_square with: (50, 50, 50), 33.008685646519375 0.0\n",
+      "09:39:14 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:14 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08322992149883786\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15073587087322737\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 33.00867065858737 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08323048967249952\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15113718807484577\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 32.833606399662884 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08388575687812592\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15113718795965525\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 32.83360644971172 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08388575585404513\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15153853938499662\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 32.65991645625941 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08455131302112386\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.1515385739585624\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 32.65990155352392 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08455189040475365\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15193996030937607\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 32.487571337628 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0852022103126783\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15193996019222666\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 32.487571387725396 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0852022092710155\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15234138114150708\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 32.31658685524697 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0858695012752933\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15234141614122265\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 32.31657200608451 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08587008793448284\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15274287245255058\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 32.146919018512015 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08654705946924982\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15274287233192796\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 32.14691906928552 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0865470584079108\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15314436364680928\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 31.978583910923877 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08719677689767133\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15314439901990617\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 31.978569138180966 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08719737283990042\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15354592615137008\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 31.811538014371372 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0878889979619032\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15354592600369799\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 31.811538075560577 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08788899685386777\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15394748849812023\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 31.645797663771617 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0885854409353678\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15394752428381597\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 31.645782951397912 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08858604662970875\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15434912290741698\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 31.48131982926401 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08927807109600666\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15434912279308088\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 31.481319875904386 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08927807000991662\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.1547507572079776\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 31.318121015304804 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0899658314837363\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15475079335348108\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 31.318106385213472 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.08996644681761376\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15515246419030015\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 31.156158760630817 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09065285355488353\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.1551524640983204\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 31.156158797571717 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09065285247888923\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.1555541710950754\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 30.995449682123244 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09137064927428684\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15555420755981642\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 30.99543515032844 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0913712743711926\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.1559559516828939\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 30.835951716206726 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09209030575650337\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.15595595146252883\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 30.83595180334884 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09209030451238961\n",
+      "09:39:15 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:15 - utils.forces_mesh - Using mesh spacing: 0.1563577320030931\n",
+      "09:39:15 - utils.forces_mesh - Got k_square with: (50, 50, 50), 30.677681824309026 0.0\n",
+      "09:39:15 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:15 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09280830863962372\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.1563577689871667\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 30.677667311624237 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09280894396493206\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.1567595868929721\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 30.52059828964225 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.0935077672660433\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.15675958676608026\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 30.520598339053127 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09350776611564912\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.15716144165297719\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 30.36471823103217 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09422535746544095\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.1571614790087814\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 30.364703796218475 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09422600270903554\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.15756337163232947\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 30.21000049217094 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09494200189131274\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.157563371505546\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 30.21000054078793 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09494200072418849\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.15796530148511545\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 30.056462298807038 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.095653564553148\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.15796533922192157\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 30.05644793825477 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09565421980695063\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.15836730729745252\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 29.904062956689184 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09640640034931408\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.15836730717790104\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 29.904063001838338 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09640639917378035\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.15876931299558228\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 29.752819822094185 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09715647881580178\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.15876935110707358\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 29.75280553817618 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09715714458848476\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.15917139547239278\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 29.602692627600042 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09791056710178465\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.15917139532717917\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 29.602692681613696 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09791056587708571\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.15957347779467845\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 29.453698900907327 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09865184123673382\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.15957351631387562\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 29.453684681346022 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09865251752194085\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.15997563768438372\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 29.30579878455281 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09940095869168045\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.15997563755661703\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 29.30579883136375 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.09940095747093222\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.1603777974478242\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 29.159009931924068 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.10016023082213835\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.16037783635482716\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 29.158995784214195 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.10016091768965002\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.16078006161942016\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 29.01328351073581 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.100913837290688\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.16078005279752272\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 29.01328669461607 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.1009138251383996\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.16118231257092397\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 28.86865153526061 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.10167231190775355\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.1611823647490338\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 28.86863284448846 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.10167302564111118\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.1615846771123981\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 28.725057975527783 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.1024394838885194\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.16158467697534729\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 28.725058024255084 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.10243948262031256\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.16198704153635912\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 28.58253315701015 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.10322258422620487\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.16198709418423363\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 28.582514577636502 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.10322330910906889\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.16238951191496254\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 28.441029344763734 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:16 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.10399199068968129\n",
+      "09:39:16 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:16 - utils.forces_mesh - Using mesh spacing: 0.16238951174125127\n",
+      "09:39:16 - utils.forces_mesh - Got k_square with: (50, 50, 50), 28.44102940561161 0.0\n",
+      "09:39:16 - utils.forces_mesh - Count of zeros: 1\n",
+      "09:39:17 - utils.forces_mesh - Got phi with: (50, 50, 50), 0.10399198935617504\n",
+      "09:39:17 - utils.forces_mesh - Computing forces for 202 particles using mesh [mapping=particle_to_cells_nn, n_grid=50]\n",
+      "09:39:17 - utils.forces_mesh - Using mesh spacing: 0.16279198212356993\n"
+     ]
+    },
+    {
+     "ename": "KeyboardInterrupt",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[15], line 11\u001b[0m\n\u001b[1;32m      8\u001b[0m mesh_size \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m50\u001b[39m \u001b[38;5;66;03m# as per the previous discussion\u001b[39;00m\n\u001b[1;32m      9\u001b[0m force_function \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mlambda\u001b[39;00m x: utils\u001b[38;5;241m.\u001b[39mmesh_forces_v2(x, G, mesh_size, utils\u001b[38;5;241m.\u001b[39mparticle_to_cells_nn)\n\u001b[0;32m---> 11\u001b[0m sol \u001b[38;5;241m=\u001b[39m \u001b[43mintegrate\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrk4\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mforce_function\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mp0\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mt_range\u001b[49m\u001b[43m)\u001b[49m\n",
+      "Cell \u001b[0;32mIn[10], line 20\u001b[0m, in \u001b[0;36mintegrate\u001b[0;34m(method, force_function, p0, t_range)\u001b[0m\n\u001b[1;32m     18\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m1\u001b[39m, t_range\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m]):\n\u001b[1;32m     19\u001b[0m         t \u001b[38;5;241m=\u001b[39m t_range[i]\n\u001b[0;32m---> 20\u001b[0m         sol[i,\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[43mutils\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrunge_kutta_4\u001b[49m\u001b[43m(\u001b[49m\u001b[43msol\u001b[49m\u001b[43m[\u001b[49m\u001b[43mi\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my_prime\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdt\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     23\u001b[0m logger\u001b[38;5;241m.\u001b[39minfo(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIntegration done, shape: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00msol\u001b[38;5;241m.\u001b[39mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m     24\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m sol\n",
+      "File \u001b[0;32m~/Documents/Uni/HS24/Computational Astrophysics/projects/nbody/utils/integrate.py:86\u001b[0m, in \u001b[0;36mrunge_kutta_4\u001b[0;34m(y0, t, f, dt)\u001b[0m\n\u001b[1;32m     84\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mrunge_kutta_4\u001b[39m(y0 : np\u001b[38;5;241m.\u001b[39mndarray, t : \u001b[38;5;28mfloat\u001b[39m, f, dt : \u001b[38;5;28mfloat\u001b[39m):\n\u001b[1;32m     85\u001b[0m     k1 \u001b[38;5;241m=\u001b[39m f(y0, t)\n\u001b[0;32m---> 86\u001b[0m     k2 \u001b[38;5;241m=\u001b[39m \u001b[43mf\u001b[49m\u001b[43m(\u001b[49m\u001b[43my0\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mk1\u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mdt\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mdt\u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m     87\u001b[0m     k3 \u001b[38;5;241m=\u001b[39m f(y0 \u001b[38;5;241m+\u001b[39m k2\u001b[38;5;241m/\u001b[39m\u001b[38;5;241m2\u001b[39m \u001b[38;5;241m*\u001b[39m dt, t \u001b[38;5;241m+\u001b[39m dt\u001b[38;5;241m/\u001b[39m\u001b[38;5;241m2\u001b[39m)\n\u001b[1;32m     88\u001b[0m     k4 \u001b[38;5;241m=\u001b[39m f(y0 \u001b[38;5;241m+\u001b[39m k3 \u001b[38;5;241m*\u001b[39m dt, t \u001b[38;5;241m+\u001b[39m dt)\n",
+      "File \u001b[0;32m~/Documents/Uni/HS24/Computational Astrophysics/projects/nbody/utils/integrate.py:32\u001b[0m, in \u001b[0;36mode_setup.<locals>.f\u001b[0;34m(y, t)\u001b[0m\n\u001b[1;32m     29\u001b[0m y \u001b[38;5;241m=\u001b[39m to_particles(y)\n\u001b[1;32m     30\u001b[0m \u001b[38;5;66;03m# now y has shape (n, 7), with columns x, y, z, vx, vy, vz, m\u001b[39;00m\n\u001b[0;32m---> 32\u001b[0m forces \u001b[38;5;241m=\u001b[39m \u001b[43mforce_function\u001b[49m\u001b[43m(\u001b[49m\u001b[43my\u001b[49m\u001b[43m[\u001b[49m\u001b[43m:\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     34\u001b[0m \u001b[38;5;66;03m# compute the accelerations\u001b[39;00m\n\u001b[1;32m     35\u001b[0m masses \u001b[38;5;241m=\u001b[39m y[:, \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m]\n",
+      "Cell \u001b[0;32mIn[15], line 9\u001b[0m, in \u001b[0;36m<lambda>\u001b[0;34m(x)\u001b[0m\n\u001b[1;32m      5\u001b[0m logger\u001b[38;5;241m.\u001b[39minfo(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIntegration range: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mt_range[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m -> \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mt_range[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m]\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, n_steps: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mn_steps\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m      8\u001b[0m mesh_size \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m50\u001b[39m \u001b[38;5;66;03m# as per the previous discussion\u001b[39;00m\n\u001b[0;32m----> 9\u001b[0m force_function \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mlambda\u001b[39;00m x: \u001b[43mutils\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmesh_forces_v2\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mG\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmesh_size\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mutils\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparticle_to_cells_nn\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     11\u001b[0m sol \u001b[38;5;241m=\u001b[39m integrate(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrk4\u001b[39m\u001b[38;5;124m\"\u001b[39m, force_function, p0, t_range)\n",
+      "File \u001b[0;32m~/Documents/Uni/HS24/Computational Astrophysics/projects/nbody/utils/forces_mesh.py:72\u001b[0m, in \u001b[0;36mmesh_forces_v2\u001b[0;34m(particles, G, n_grid, mapping)\u001b[0m\n\u001b[1;32m     70\u001b[0m spacing \u001b[38;5;241m=\u001b[39m axis[\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m-\u001b[39m axis[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m     71\u001b[0m logger\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUsing mesh spacing: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mspacing\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m---> 72\u001b[0m phi \u001b[38;5;241m=\u001b[39m \u001b[43mmesh_poisson_v2\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmesh\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mG\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mspacing\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     73\u001b[0m logger\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mGot phi with: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mphi\u001b[38;5;241m.\u001b[39mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mmax(phi)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m     74\u001b[0m phi_grad \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mstack(np\u001b[38;5;241m.\u001b[39mgradient(phi, spacing), axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m)\n",
+      "File \u001b[0;32m~/Documents/Uni/HS24/Computational Astrophysics/projects/nbody/utils/forces_mesh.py:96\u001b[0m, in \u001b[0;36mmesh_poisson_v2\u001b[0;34m(mesh, G, spacing)\u001b[0m\n\u001b[1;32m     91\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mmesh_poisson_v2\u001b[39m(mesh: np\u001b[38;5;241m.\u001b[39mndarray, G: \u001b[38;5;28mfloat\u001b[39m, spacing: \u001b[38;5;28mfloat\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m np\u001b[38;5;241m.\u001b[39mndarray:\n\u001b[1;32m     92\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m     93\u001b[0m \u001b[38;5;124;03m    Solves the poisson equation for the mesh using the FFT.\u001b[39;00m\n\u001b[1;32m     94\u001b[0m \u001b[38;5;124;03m    Returns the scalar potential.\u001b[39;00m\n\u001b[1;32m     95\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m---> 96\u001b[0m     rho_hat \u001b[38;5;241m=\u001b[39m \u001b[43mfft\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfftn\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmesh\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     97\u001b[0m     k \u001b[38;5;241m=\u001b[39m fft\u001b[38;5;241m.\u001b[39mfftfreq(mesh\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m], spacing)\n\u001b[1;32m     98\u001b[0m     kx, ky, kz \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mmeshgrid(k, k, k)\n",
+      "File \u001b[0;32m~/.local/share/virtualenvs/projects-X-9bmgL6/lib/python3.13/site-packages/scipy/fft/_backend.py:28\u001b[0m, in \u001b[0;36m_ScipyBackend.__ua_function__\u001b[0;34m(method, args, kwargs)\u001b[0m\n\u001b[1;32m     26\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m fn \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m     27\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mNotImplemented\u001b[39m\n\u001b[0;32m---> 28\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/.local/share/virtualenvs/projects-X-9bmgL6/lib/python3.13/site-packages/scipy/fft/_basic_backend.py:115\u001b[0m, in \u001b[0;36mfftn\u001b[0;34m(x, s, axes, norm, overwrite_x, workers, plan)\u001b[0m\n\u001b[1;32m    113\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mfftn\u001b[39m(x, s\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, axes\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, norm\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m    114\u001b[0m          overwrite_x\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m, workers\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m, plan\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[0;32m--> 115\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_execute_nD\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfftn\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m_pocketfft\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfftn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43ms\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxes\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnorm\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnorm\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    116\u001b[0m \u001b[43m                       \u001b[49m\u001b[43moverwrite_x\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moverwrite_x\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mworkers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mworkers\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mplan\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mplan\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/.local/share/virtualenvs/projects-X-9bmgL6/lib/python3.13/site-packages/scipy/fft/_basic_backend.py:57\u001b[0m, in \u001b[0;36m_execute_nD\u001b[0;34m(func_str, pocketfft_func, x, s, axes, norm, overwrite_x, workers, plan)\u001b[0m\n\u001b[1;32m     55\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_numpy(xp):\n\u001b[1;32m     56\u001b[0m     x \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39masarray(x)\n\u001b[0;32m---> 57\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mpocketfft_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43ms\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxes\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnorm\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnorm\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     58\u001b[0m \u001b[43m                          \u001b[49m\u001b[43moverwrite_x\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moverwrite_x\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mworkers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mworkers\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mplan\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mplan\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     60\u001b[0m norm \u001b[38;5;241m=\u001b[39m _validate_fft_args(workers, plan, norm)\n\u001b[1;32m     61\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(xp, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfft\u001b[39m\u001b[38;5;124m'\u001b[39m):\n",
+      "File \u001b[0;32m~/.local/share/virtualenvs/projects-X-9bmgL6/lib/python3.13/site-packages/scipy/fft/_pocketfft/basic.py:149\u001b[0m, in \u001b[0;36mc2cn\u001b[0;34m(forward, x, s, axes, norm, overwrite_x, workers, plan)\u001b[0m\n\u001b[1;32m    146\u001b[0m norm \u001b[38;5;241m=\u001b[39m _normalization(norm, forward)\n\u001b[1;32m    147\u001b[0m out \u001b[38;5;241m=\u001b[39m (tmp \u001b[38;5;28;01mif\u001b[39;00m overwrite_x \u001b[38;5;129;01mand\u001b[39;00m tmp\u001b[38;5;241m.\u001b[39mdtype\u001b[38;5;241m.\u001b[39mkind \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mc\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[0;32m--> 149\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mpfft\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mc2c\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtmp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mforward\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnorm\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mout\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mworkers\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
+     ]
+    }
+   ],
+   "source": [
+    "## Integration setup - use the n_squared forces for a few timesteps only, to see if the orbits are stable\n",
+    "t_orbit = 2 * np.pi * r_inter / v_mean\n",
+    "n_steps = int(t_orbit / dt * 30)\n",
+    "t_range = np.arange(0, n_steps*dt, dt)\n",
+    "logger.info(f\"Integration range: {t_range[0]} -> {t_range[-1]}, n_steps: {n_steps}\")\n",
+    "\n",
+    "\n",
+    "mesh_size = 50 # as per the previous discussion\n",
+    "force_function = lambda x: utils.mesh_forces_v2(x, G, mesh_size, utils.particle_to_cells_nn)\n",
+    "\n",
+    "sol = integrate(\"rk4\", force_function, p0, t_range)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## Show some results"
+   ]
   }
  ],
  "metadata": {
diff --git a/nbody/utils/forces_basic.py b/nbody/utils/forces_basic.py
index f96ba44..03f92b8 100644
--- a/nbody/utils/forces_basic.py
+++ b/nbody/utils/forces_basic.py
@@ -33,13 +33,13 @@ def n_body_forces(particles: np.ndarray, G: float, softening: float = 0):
         # m is a list of scalars and displacements is a list of vectors (2D array)
         # we only want row_wise multiplication
         num = G * (masses * displacements.T).T
-        
+
         # a zero value is expected where we have the same particle
         r_adjusted[i] = 1
         num[i] = 0
-        
+
         f = np.sum((num.T / r_adjusted**1.5).T, axis=0) * m_current
-        forces[i] = -f
+        forces[i] = - f
 
         if i % 5000 == 0:
             logger.debug(f"Particle {i} done")
@@ -47,6 +47,24 @@ def n_body_forces(particles: np.ndarray, G: float, softening: float = 0):
     return forces
 
 
+def n_body_forces_basic(particles: np.ndarray, G: float, softening: float = 0):
+    if particles.shape[1] != 4:
+        raise ValueError("Particles array must have 4 columns: x, y, z, m")
+
+    x_vec = particles[:, 0:3]
+    masses = particles[:, 3]
+    n = particles.shape[0]
+    forces = np.zeros((n, 3))
+    for i in range(n):
+        for j in range(n):
+            if i == j:
+                continue # keep the value at zero
+            r_vec = x_vec[j] - x_vec[i]
+            r = np.linalg.norm(r_vec)
+            f = - G * masses[i] * masses[j] * r_vec / (r**3 + softening**3)
+            forces[i] += f
+
+    return forces
 
 def analytical_forces(particles: np.ndarray):
     """
diff --git a/nbody/utils/forces_mesh.py b/nbody/utils/forces_mesh.py
index 5c8f779..d0a0ae7 100644
--- a/nbody/utils/forces_mesh.py
+++ b/nbody/utils/forces_mesh.py
@@ -75,7 +75,7 @@ def mesh_forces_v2(particles: np.ndarray, G: float, n_grid: int, mapping: callab
     if logger.level >= logging.DEBUG:
         show_mesh_information(phi, "Potential mesh")
         show_mesh_information(phi_grad[0], "Potential gradient")
-    logger.debug(f"Got phi_grad with: {phi_grad.shape}, {np.max(phi_grad)}")
+        logger.debug(f"Got phi_grad with: {phi_grad.shape}, {np.max(phi_grad)}")
     
     # compute the particle forces from the mesh potential
     forces = np.zeros_like(particles[:, :3])
diff --git a/nbody/utils/integrate.py b/nbody/utils/integrate.py
index de90173..c4c1744 100644
--- a/nbody/utils/integrate.py
+++ b/nbody/utils/integrate.py
@@ -16,10 +16,9 @@ def ode_setup(particles: np.ndarray, force_function: callable) -> tuple[np.ndarr
     if particles.shape[1] != 7:
         raise ValueError("Particles array must have 7 columns: x, y, z, vx, vy, vz, m")
     
-    # for scipy integrators we need to flatten array which contains 7 columns for now
-    # we don't really care how we reshape as long as we unflatten consistently afterwards
+    # for the integrators we need to flatten array which contains 7 columns for now
+    # we don't really care how we reshape as long as we unflatten consistently
     particles = particles.reshape(-1, copy=False, order='A')
-    # this is consistent with the unflattening in to_particles()!
     logger.debug(f"Reshaped 7 columns into {particles.shape=}")
 
     def f(y, t):
@@ -29,33 +28,35 @@ def ode_setup(particles: np.ndarray, force_function: callable) -> tuple[np.ndarr
         """
         y = to_particles(y)
         # now y has shape (n, 7), with columns x, y, z, vx, vy, vz, m
-        
 
         forces = force_function(y[:, [0, 1, 2, -1]])
-        
+
         # compute the accelerations
         masses = y[:, -1]
         a = forces / masses[:, None]
         # the [:, None] is to force broadcasting in order to divide each row of forces by the corresponding mass
-        # a.flatten()
-        
-        # replace some values in y:
+
+        dydt = np.zeros_like(y)
         # the position columns become the velocities
         # the velocity columns become the accelerations
-        y[:, 0:3] = y[:, 3:6]
-        y[:, 3:6] = a
+        dydt[:, 0:3] = y[:, 3:6]
+        dydt[:, 3:6] = a
         # the masses remain unchanged
+        dydt[:, -1] = masses
 
         # flatten the array again
-        y = y.reshape(-1, copy=False, order='A')
-        return y
+        # logger.debug(f"As particles: {y}")
+        dydt = dydt.reshape(-1, copy=False, order='A')
+        
+        # logger.debug(f"As column: {y}")
+        return dydt
 
     return particles, f
 
 
 def to_particles(y: np.ndarray) -> np.ndarray:
     """
-    Converts the 1D array y into a 2D array IN PLACE
+    Converts the 1D array y into a 2D array
     The new shape is (n, 7) where n is the number of particles.
     The columns are x, y, z, vx, vy, vz, m
     """
@@ -64,10 +65,21 @@ def to_particles(y: np.ndarray) -> np.ndarray:
     
     n = y.size // 7
     y = y.reshape((n, 7), copy=False, order='F')
-    logger.debug(f"Unflattened array into {y.shape=}")
+    # logger.debug(f"Unflattened array into {y.shape=}")
     return y
 
 
+def to_particles_3d(y: np.ndarray) -> np.ndarray:
+    """
+    Converts the 2D sol array with one vector per timestep into a 3D array:
+    2d particles (nx7) x nsteps
+    """
+    n_steps = y.shape[0]
+    n_particles = y.shape[1] // 7
+    y = y.reshape((n_steps, n_particles, 7), copy=False, order='F')
+    # logger.debug(f"Unflattened array into {y.shape=}")
+    return y
+
 
 def runge_kutta_4(y0 : np.ndarray, t : float, f, dt : float):
     k1 = f(y0, t)
diff --git a/nbody/utils/logging_config.py b/nbody/utils/logging_config.py
index a885624..b0cef2c 100644
--- a/nbody/utils/logging_config.py
+++ b/nbody/utils/logging_config.py
@@ -2,10 +2,10 @@ import logging
 
 logging.basicConfig(
     ## set logging level
-    # level=logging.INFO,
-    level=logging.INFO,
-    format='%(asctime)s - %(name)s - %(message)s',
-    datefmt='%H:%M:%S'
+    level = logging.DEBUG,
+    # level = logging.INFO,
+    format = '%(asctime)s - %(name)s - %(message)s',
+    datefmt = '%H:%M:%S'
 )
 
 
@@ -13,4 +13,4 @@ logging.basicConfig(
 logging.getLogger('matplotlib.font_manager').setLevel(logging.WARNING)
 logging.getLogger('matplotlib.ticker').setLevel(logging.WARNING)
 logging.getLogger('matplotlib.pyplot').setLevel(logging.WARNING)
-logging.getLogger('matplotlib.colorbar').setLevel(logging.WARNING)
\ No newline at end of file
+logging.getLogger('matplotlib.colorbar').setLevel(logging.WARNING)
diff --git a/nbody/utils/model.py b/nbody/utils/model.py
index a1ab69a..12281e9 100644
--- a/nbody/utils/model.py
+++ b/nbody/utils/model.py
@@ -11,4 +11,4 @@ def model_density_distribution(r_bins: np.ndarray, M: float = 5, a: float = 5) -
     See https://doi.org/10.1086%2F168845 for more information.
     """
     rho = M / (2 * np.pi) * a / (r_bins * (r_bins + a)**3)
-    return rho
\ No newline at end of file
+    return rho