diff --git a/analysis/coarse_k_point_implementation.ipynb b/analysis/coarse_k_point_implementation.ipynb
deleted file mode 100644
index f9ad770d582aad69cd625baf2d3cf55e53bf2f30..0000000000000000000000000000000000000000
--- a/analysis/coarse_k_point_implementation.ipynb
+++ /dev/null
@@ -1,805 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "cb509096-42c6-4a45-8dc4-a8eed3116e67",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "import kwant\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "import utils, hf"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8a550e7e-e90b-4443-99a4-315f96539ac4",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "s0 = np.identity(2)\n",
-    "sz = np.diag([1, -1])\n",
-    "\n",
-    "norbs = 2\n",
-    "\n",
-    "graphene = kwant.lattice.general(\n",
-    "    [[1, 0], [1 / 2, np.sqrt(3) / 2]], [[0, 0], [0, 1 / np.sqrt(3)]], norbs=norbs\n",
-    ")\n",
-    "a, b = graphene.sublattices\n",
-    "\n",
-    "# create bulk system\n",
-    "bulk_graphene = kwant.Builder(kwant.TranslationalSymmetry(*graphene.prim_vecs))\n",
-    "# add sublattice potential\n",
-    "m0 = 0\n",
-    "\n",
-    "bulk_graphene[a.shape((lambda pos: True), (0, 0))] = m0 * s0\n",
-    "bulk_graphene[b.shape((lambda pos: True), (0, 0))] = -m0 * s0\n",
-    "# add hoppings between sublattices\n",
-    "bulk_graphene[graphene.neighbors(1)] = s0\n",
-    "bulk_graphene[graphene.neighbors(2)] = 1j * s0\n",
-    "\n",
-    "# use kwant wraparound to sample bulk k-space\n",
-    "wrapped_syst = kwant.wraparound.wraparound(bulk_graphene)\n",
-    "wrapped_fsyst = wrapped_syst.finalized()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9cc3b32d-404f-4bc5-a338-83571c9e4c4b",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "def func_onsite(site, U):\n",
-    "    return U * np.ones((2, 2))\n",
-    "\n",
-    "def func_hop(site1, site2, V):\n",
-    "    return V * np.ones((2, 2))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d1ef154e-70bd-4f28-887f-72362d8533dd",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "Us = np.linspace(1e-6, 5, 10)\n",
-    "Vs = np.linspace(1e-6, 5, 1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "117f5557-0e6a-4b02-b0eb-125e68c839dd",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "from numpy.linalg import qr\n",
-    "from functools import partial\n",
-    "\n",
-    "def scf_loop(mf, H_int, scf_syst, ks, hamiltonians_0, filling=2, max_neighbor=1):\n",
-    "    if np.linalg.norm(mf) < 1e-5:\n",
-    "        return 0\n",
-    "    # mf = mf.reshape(\n",
-    "    #     max_neighbor + len(graphene.sublattices),\n",
-    "    #     2,\n",
-    "    #     norbs,\n",
-    "    #     norbs,\n",
-    "    # )\n",
-    "    params = dict(mat=mf)\n",
-    "    mf_k = utils.syst2hamiltonian(syst=scf_syst, kxs=ks, kys=ks, params=params)\n",
-    "\n",
-    "    H0_int = H_int[0, 0]\n",
-    "\n",
-    "    # Generate the Hamiltonian\n",
-    "    hamiltonians = hamiltonians_0 + mf_k\n",
-    "    vals, vecs = np.linalg.eigh(hamiltonians)\n",
-    "    # Orthogonalize vectors\n",
-    "    vecs = qr(vecs)[0]\n",
-    "    # Compute new Fermi energy\n",
-    "    mf_k_new = hf.compute_mf(vals, vecs, filling, ks, H_int)\n",
-    "\n",
-    "    diff = mf_k_new - mf_k\n",
-    "    shift = np.trace(np.average(diff, axis=(0,1)))\n",
-    "    diff -= shift / norbs / len(graphene.sublattices)\n",
-    "\n",
-    "    if np.linalg.norm(mf_k_new) < 1e-5:\n",
-    "        return 0\n",
-    "    else:\n",
-    "        return np.linalg.norm(diff) / np.linalg.norm(mf_k_new)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "eb19dbaf-8a85-4eb8-9c68-7266ee250fdc",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "def generate_guess(max_neighbor, norbs):\n",
-    "    n_sub = len(graphene.sublattices)\n",
-    "    guess = np.zeros((n_sub + max_neighbor, 2, norbs, norbs))\n",
-    "    for i in range(n_sub):\n",
-    "        # Real part\n",
-    "        guess[i, 0] = np.random.rand(norbs, norbs)\n",
-    "        guess[i, 0] += guess[i, 0].T\n",
-    "        guess[i, 0] *= 0.5\n",
-    "        # Imag part\n",
-    "        guess[i, 1] = np.random.rand(norbs, norbs)\n",
-    "        guess[i, 1] -= guess[i, 1].T\n",
-    "        guess[i, 1] *= 0.5\n",
-    "    for neighbor in range(max_neighbor):\n",
-    "        # Real part\n",
-    "        guess[n_sub + neighbor, 0] = np.random.rand(norbs, norbs)\n",
-    "        # Imag part\n",
-    "        guess[n_sub + neighbor, 1] = np.random.rand(norbs, norbs)\n",
-    "    return guess\n",
-    "\n",
-    "def generate_guess(max_neighbor, norbs):\n",
-    "    n_sub = len(graphene.sublattices)\n",
-    "    guess = np.zeros((n_sub + max_neighbor, 2, norbs, norbs))\n",
-    "    for i in range(n_sub):\n",
-    "        # Real part\n",
-    "        guess[i, 0] = np.diag(np.random.rand(norbs))\n",
-    "        # Imag part\n",
-    "        guess[i, 1] = np.diag(np.random.rand(norbs))\n",
-    "    for neighbor in range(max_neighbor):\n",
-    "        # Real part\n",
-    "        guess[n_sub + neighbor, 0] = np.diag(np.random.rand(norbs))\n",
-    "        # Imag part\n",
-    "        guess[n_sub + neighbor, 1] = np.diag(np.random.rand(norbs))\n",
-    "    return guess"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 108,
-   "id": "32b9e7c5-db12-44f9-930c-21e5494404b8",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "  0%|          | 0/10 [00:00<?, ?it/s]\n"
-     ]
-    },
-    {
-     "ename": "AttributeError",
-     "evalue": "'tuple' object has no attribute 'hamiltonian_submatrix'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[108], line 158\u001b[0m\n\u001b[1;32m    156\u001b[0m gap_U \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m    157\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m V \u001b[38;5;129;01min\u001b[39;00m Vs:\n\u001b[0;32m--> 158\u001b[0m     gap_U\u001b[38;5;241m.\u001b[39mappend(\u001b[43mcompute_gap\u001b[49m\u001b[43m(\u001b[49m\u001b[43mU\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mV\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m    159\u001b[0m gap\u001b[38;5;241m.\u001b[39mappend(gap_U)\n",
-      "Cell \u001b[0;32mIn[108], line 115\u001b[0m, in \u001b[0;36mcompute_gap\u001b[0;34m(U, V, max_neighbor, nk, filling)\u001b[0m\n\u001b[1;32m    113\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcallback\u001b[39m(x, f):\n\u001b[1;32m    114\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m x\n\u001b[0;32m--> 115\u001b[0m mf \u001b[38;5;241m=\u001b[39m \u001b[43manderson\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    116\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfun\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    117\u001b[0m \u001b[43m    \u001b[49m\u001b[43mgenerate_guess\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmax_neighbor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmax_neighbor\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnorbs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnorbs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    118\u001b[0m \u001b[43m    \u001b[49m\u001b[43mf_tol\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1e-3\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    119\u001b[0m \u001b[43m    \u001b[49m\u001b[43mw0\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0.5\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    120\u001b[0m \u001b[43m    \u001b[49m\u001b[43mM\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    121\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcallback\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcallback\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    122\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    124\u001b[0m mf \u001b[38;5;241m=\u001b[39m mf\u001b[38;5;241m.\u001b[39mreshape(\n\u001b[1;32m    125\u001b[0m     max_neighbor \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mlen\u001b[39m(graphene\u001b[38;5;241m.\u001b[39msublattices),\n\u001b[1;32m    126\u001b[0m     \u001b[38;5;241m2\u001b[39m,\n\u001b[1;32m    127\u001b[0m     norbs,\n\u001b[1;32m    128\u001b[0m     norbs,\n\u001b[1;32m    129\u001b[0m )\n\u001b[1;32m    130\u001b[0m ks \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mlinspace(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m2\u001b[39m \u001b[38;5;241m*\u001b[39m np\u001b[38;5;241m.\u001b[39mpi, \u001b[38;5;241m30\u001b[39m, endpoint\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n",
-      "File \u001b[0;32m<string>:6\u001b[0m, in \u001b[0;36manderson\u001b[0;34m(F, xin, iter, alpha, w0, M, verbose, maxiter, f_tol, f_rtol, x_tol, x_rtol, tol_norm, line_search, callback, **kw)\u001b[0m\n",
-      "File \u001b[0;32m/opt/conda/lib/python3.10/site-packages/scipy/optimize/_nonlin.py:170\u001b[0m, in \u001b[0;36mnonlin_solve\u001b[0;34m(F, x0, jacobian, iter, verbose, maxiter, f_tol, f_rtol, x_tol, x_rtol, tol_norm, line_search, callback, full_output, raise_exception)\u001b[0m\n\u001b[1;32m    167\u001b[0m x \u001b[38;5;241m=\u001b[39m x0\u001b[38;5;241m.\u001b[39mflatten()\n\u001b[1;32m    169\u001b[0m dx \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mfull_like(x, np\u001b[38;5;241m.\u001b[39minf)\n\u001b[0;32m--> 170\u001b[0m Fx \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    171\u001b[0m Fx_norm \u001b[38;5;241m=\u001b[39m norm(Fx)\n\u001b[1;32m    173\u001b[0m jacobian \u001b[38;5;241m=\u001b[39m asjacobian(jacobian)\n",
-      "File \u001b[0;32m/opt/conda/lib/python3.10/site-packages/scipy/optimize/_nonlin.py:166\u001b[0m, in \u001b[0;36mnonlin_solve.<locals>.<lambda>\u001b[0;34m(z)\u001b[0m\n\u001b[1;32m    161\u001b[0m condition \u001b[38;5;241m=\u001b[39m TerminationCondition(f_tol\u001b[38;5;241m=\u001b[39mf_tol, f_rtol\u001b[38;5;241m=\u001b[39mf_rtol,\n\u001b[1;32m    162\u001b[0m                                  x_tol\u001b[38;5;241m=\u001b[39mx_tol, x_rtol\u001b[38;5;241m=\u001b[39mx_rtol,\n\u001b[1;32m    163\u001b[0m                                  \u001b[38;5;28miter\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;28miter\u001b[39m, norm\u001b[38;5;241m=\u001b[39mtol_norm)\n\u001b[1;32m    165\u001b[0m x0 \u001b[38;5;241m=\u001b[39m _as_inexact(x0)\n\u001b[0;32m--> 166\u001b[0m func \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mlambda\u001b[39;00m z: _as_inexact(\u001b[43mF\u001b[49m\u001b[43m(\u001b[49m\u001b[43m_array_like\u001b[49m\u001b[43m(\u001b[49m\u001b[43mz\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mx0\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m)\u001b[38;5;241m.\u001b[39mflatten()\n\u001b[1;32m    167\u001b[0m x \u001b[38;5;241m=\u001b[39m x0\u001b[38;5;241m.\u001b[39mflatten()\n\u001b[1;32m    169\u001b[0m dx \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mfull_like(x, np\u001b[38;5;241m.\u001b[39minf)\n",
-      "Cell \u001b[0;32mIn[24], line 14\u001b[0m, in \u001b[0;36mscf_loop\u001b[0;34m(mf, H_int, scf_syst, ks, hamiltonians_0, filling, max_neighbor)\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[38;5;66;03m# mf = mf.reshape(\u001b[39;00m\n\u001b[1;32m      8\u001b[0m \u001b[38;5;66;03m#     max_neighbor + len(graphene.sublattices),\u001b[39;00m\n\u001b[1;32m      9\u001b[0m \u001b[38;5;66;03m#     2,\u001b[39;00m\n\u001b[1;32m     10\u001b[0m \u001b[38;5;66;03m#     norbs,\u001b[39;00m\n\u001b[1;32m     11\u001b[0m \u001b[38;5;66;03m#     norbs,\u001b[39;00m\n\u001b[1;32m     12\u001b[0m \u001b[38;5;66;03m# )\u001b[39;00m\n\u001b[1;32m     13\u001b[0m params \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mdict\u001b[39m(mat\u001b[38;5;241m=\u001b[39mmf)\n\u001b[0;32m---> 14\u001b[0m mf_k \u001b[38;5;241m=\u001b[39m \u001b[43mutils\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msyst2hamiltonian\u001b[49m\u001b[43m(\u001b[49m\u001b[43msyst\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mscf_syst\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkxs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mks\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mks\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mparams\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     16\u001b[0m H0_int \u001b[38;5;241m=\u001b[39m H_int[\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m     18\u001b[0m \u001b[38;5;66;03m# Generate the Hamiltonian\u001b[39;00m\n",
-      "File \u001b[0;32m~/Sync/kwant-scf/codes/utils.py:21\u001b[0m, in \u001b[0;36msyst2hamiltonian\u001b[0;34m(kxs, kys, syst, params)\u001b[0m\n\u001b[1;32m     18\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mh_k\u001b[39m(kx, ky):\n\u001b[1;32m     19\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m syst\u001b[38;5;241m.\u001b[39mhamiltonian_submatrix(params\u001b[38;5;241m=\u001b[39m{\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;28mdict\u001b[39m(k_x\u001b[38;5;241m=\u001b[39mkx, k_y\u001b[38;5;241m=\u001b[39mky)})\n\u001b[1;32m     20\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m np\u001b[38;5;241m.\u001b[39marray(\n\u001b[0;32m---> 21\u001b[0m     [[h_k(kx, ky) \u001b[38;5;28;01mfor\u001b[39;00m kx \u001b[38;5;129;01min\u001b[39;00m kxs] \u001b[38;5;28;01mfor\u001b[39;00m ky \u001b[38;5;129;01min\u001b[39;00m kys]\n\u001b[1;32m     22\u001b[0m )\n",
-      "File \u001b[0;32m~/Sync/kwant-scf/codes/utils.py:21\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m     18\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mh_k\u001b[39m(kx, ky):\n\u001b[1;32m     19\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m syst\u001b[38;5;241m.\u001b[39mhamiltonian_submatrix(params\u001b[38;5;241m=\u001b[39m{\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;28mdict\u001b[39m(k_x\u001b[38;5;241m=\u001b[39mkx, k_y\u001b[38;5;241m=\u001b[39mky)})\n\u001b[1;32m     20\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m np\u001b[38;5;241m.\u001b[39marray(\n\u001b[0;32m---> 21\u001b[0m     [[h_k(kx, ky) \u001b[38;5;28;01mfor\u001b[39;00m kx \u001b[38;5;129;01min\u001b[39;00m kxs] \u001b[38;5;28;01mfor\u001b[39;00m ky \u001b[38;5;129;01min\u001b[39;00m kys]\n\u001b[1;32m     22\u001b[0m )\n",
-      "File \u001b[0;32m~/Sync/kwant-scf/codes/utils.py:21\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m     18\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mh_k\u001b[39m(kx, ky):\n\u001b[1;32m     19\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m syst\u001b[38;5;241m.\u001b[39mhamiltonian_submatrix(params\u001b[38;5;241m=\u001b[39m{\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;28mdict\u001b[39m(k_x\u001b[38;5;241m=\u001b[39mkx, k_y\u001b[38;5;241m=\u001b[39mky)})\n\u001b[1;32m     20\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m np\u001b[38;5;241m.\u001b[39marray(\n\u001b[0;32m---> 21\u001b[0m     [[\u001b[43mh_k\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mky\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m kx \u001b[38;5;129;01min\u001b[39;00m kxs] \u001b[38;5;28;01mfor\u001b[39;00m ky \u001b[38;5;129;01min\u001b[39;00m kys]\n\u001b[1;32m     22\u001b[0m )\n",
-      "File \u001b[0;32m~/Sync/kwant-scf/codes/utils.py:19\u001b[0m, in \u001b[0;36msyst2hamiltonian.<locals>.h_k\u001b[0;34m(kx, ky)\u001b[0m\n\u001b[1;32m     18\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mh_k\u001b[39m(kx, ky):\n\u001b[0;32m---> 19\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43msyst\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhamiltonian_submatrix\u001b[49m(params\u001b[38;5;241m=\u001b[39m{\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;28mdict\u001b[39m(k_x\u001b[38;5;241m=\u001b[39mkx, k_y\u001b[38;5;241m=\u001b[39mky)})\n",
-      "\u001b[0;31mAttributeError\u001b[0m: 'tuple' object has no attribute 'hamiltonian_submatrix'"
-     ]
-    }
-   ],
-   "source": [
-    "import tinyarray as ta\n",
-    "\n",
-    "def extract_hopping_vectors(builder):\n",
-    "    keep=None\n",
-    "    deltas=[]\n",
-    "    for hop, val in builder.hopping_value_pairs():\n",
-    "        a, b=hop\n",
-    "        b_dom = builder.symmetry.which(b)\n",
-    "        # Throw away part that is in the remaining translation direction, so we get\n",
-    "        # an element of 'sym' which is being wrapped\n",
-    "        b_dom = ta.array([t for i, t in enumerate(b_dom) if i != keep])\n",
-    "        deltas.append(b_dom)\n",
-    "    return np.asarray(deltas)\n",
-    "\n",
-    "def generate_scf_syst(max_neighbor, syst):\n",
-    "    def scf_onsite(site, mat):\n",
-    "        if site.family == a:\n",
-    "            return mat[0, 0] + 1j * mat[0, 1]\n",
-    "        elif site.family == b:\n",
-    "            return mat[1, 0] + 1j * mat[1, 1]\n",
-    "\n",
-    "    scf = kwant.Builder(kwant.TranslationalSymmetry(*graphene.prim_vecs))\n",
-    "    scf[syst.sites()] = scf_onsite\n",
-    "    for neighbor in range(max_neighbor):\n",
-    "\n",
-    "        def scf_hopping(site1, site2, mat):\n",
-    "            return (\n",
-    "                mat[len(graphene.sublattices) + neighbor, 0]\n",
-    "                + 1j * mat[len(graphene.sublattices) + neighbor, 1]\n",
-    "            )\n",
-    "\n",
-    "        scf[graphene.neighbors(neighbor + 1)] = scf_hopping\n",
-    "    deltas = extract_hopping_vectors(scf)\n",
-    "    wrapped_scf = kwant.wraparound.wraparound(scf).finalized()\n",
-    "    return wrapped_scf, deltas\n",
-    "\n",
-    "from scipy.optimize import minimize, anderson, fmin, root\n",
-    "\n",
-    "\n",
-    "def generate_hint(syst, U, V, lattice, func_onsite, func_hop, params, ks):\n",
-    "    Uk = utils.potential2hamiltonian(\n",
-    "        syst=syst,\n",
-    "        lattice=graphene,\n",
-    "        func_onsite=func_onsite,\n",
-    "        func_hop=func_hop,\n",
-    "        params=dict(U=1, V=0),\n",
-    "        ks=ks,\n",
-    "    )\n",
-    "\n",
-    "    Vk = utils.potential2hamiltonian(\n",
-    "        syst=syst,\n",
-    "        lattice=graphene,\n",
-    "        func_onsite=func_onsite,\n",
-    "        func_hop=func_hop,\n",
-    "        params=dict(U=0, V=1),\n",
-    "        ks=ks,\n",
-    "    )\n",
-    "    return U * Uk + V * Vk\n",
-    "\n",
-    "\n",
-    "def total_energy(mf, syst0, syst_mf, ks, max_neighbor, filling):\n",
-    "    mf = mf.reshape(\n",
-    "        max_neighbor + len(graphene.sublattices),\n",
-    "        2,\n",
-    "        norbs,\n",
-    "        norbs,\n",
-    "    )\n",
-    "    hamiltonians_0 = utils.syst2hamiltonian(kxs=ks, kys=ks, syst=syst0)\n",
-    "    scf_mf_k = utils.syst2hamiltonian(syst=syst_mf, kxs=ks, kys=ks, params=dict(mat=mf))\n",
-    "    vals, vecs = np.linalg.eigh(hamiltonians_0 + scf_mf_k)\n",
-    "    E_F = utils.get_fermi_energy(vals, filling)\n",
-    "    vals -= E_F\n",
-    "    N_filling = np.sum(vals < 0)\n",
-    "    E_total = np.sum(vals[vals < 0])\n",
-    "    E_p_atom = E_total / N_filling\n",
-    "    return E_p_atom\n",
-    "\n",
-    "\n",
-    "def compute_gap(U, V, max_neighbor=1, nk=12, filling=2):\n",
-    "    n_sub = len(graphene.sublattices)\n",
-    "    ks = np.linspace(0, 2 * np.pi, nk, endpoint=False)\n",
-    "    hamiltonians_0 = utils.syst2hamiltonian(kxs=ks, kys=ks, syst=wrapped_fsyst)\n",
-    "    # Generate interacting matrix\n",
-    "    H_int = generate_hint(\n",
-    "        syst=wrapped_syst,\n",
-    "        lattice=graphene,\n",
-    "        func_onsite=func_onsite,\n",
-    "        func_hop=func_hop,\n",
-    "        U=U,\n",
-    "        V=V,\n",
-    "        ks=ks,\n",
-    "        params={},\n",
-    "    )\n",
-    "    # Create a dummy kwant system for the mean-field\n",
-    "    scf_syst = generate_scf_syst(max_neighbor=max_neighbor, syst=wrapped_syst)\n",
-    "\n",
-    "    # mf = minimize(\n",
-    "    #     scf_loop,\n",
-    "    #     generate_guess(max_neighbor=max_neighbor, norbs=norbs).flatten(),\n",
-    "    #     tol=1e-4,\n",
-    "    #     args=(H_int, scf_syst, ks, hamiltonians_0, filling, max_neighbor),\n",
-    "    # ).x\n",
-    "    fun = partial(\n",
-    "        scf_loop,\n",
-    "        H_int=H_int,\n",
-    "        scf_syst=scf_syst,\n",
-    "        ks=ks,\n",
-    "        hamiltonians_0=hamiltonians_0,\n",
-    "        filling=filling,\n",
-    "        max_neighbor=max_neighbor,\n",
-    "    )\n",
-    "\n",
-    "    def callback(x, f):\n",
-    "        return x\n",
-    "    mf = anderson(\n",
-    "        fun,\n",
-    "        generate_guess(max_neighbor=max_neighbor, norbs=norbs),\n",
-    "        f_tol=1e-3,\n",
-    "        w0=0.5,\n",
-    "        M=1,\n",
-    "        callback=callback,\n",
-    "    )\n",
-    "\n",
-    "    mf = mf.reshape(\n",
-    "        max_neighbor + len(graphene.sublattices),\n",
-    "        2,\n",
-    "        norbs,\n",
-    "        norbs,\n",
-    "    )\n",
-    "    ks = np.linspace(0, 2 * np.pi, 30, endpoint=False)\n",
-    "    hamiltonians_0 = utils.syst2hamiltonian(kxs=ks, kys=ks, syst=wrapped_fsyst)\n",
-    "    scf_mf_k = utils.syst2hamiltonian(\n",
-    "        syst=scf_syst, kxs=ks, kys=ks, params=dict(mat=mf)\n",
-    "    )\n",
-    "    vals, vecs = np.linalg.eigh(hamiltonians_0 + scf_mf_k)\n",
-    "    E_F = utils.get_fermi_energy(vals, 2)\n",
-    "    print(\"U=\" + str(U) + \" , V=\" + str(V))\n",
-    "    extr = np.max(np.abs(scf_mf_k[0, 0]) - E_F * np.eye(n_sub * norbs))\n",
-    "    plt.matshow(\n",
-    "        (scf_mf_k[0, 0] - E_F * np.eye(n_sub * norbs)).real,\n",
-    "        cmap=\"RdBu_r\",\n",
-    "        vmin=-extr,\n",
-    "        vmax=extr,\n",
-    "    )\n",
-    "    plt.colorbar()\n",
-    "    plt.show()\n",
-    "    emax = np.max(vals[vals <= E_F])\n",
-    "    emin = np.min(vals[vals > E_F])\n",
-    "    return np.abs(emin - emax)\n",
-    "\n",
-    "\n",
-    "from tqdm import tqdm\n",
-    "\n",
-    "gap = []\n",
-    "for U in tqdm(Us):\n",
-    "    gap_U = []\n",
-    "    for V in Vs:\n",
-    "        gap_U.append(compute_gap(U, V))\n",
-    "    gap.append(gap_U)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "a04563c8-81a1-4fd2-9bf3-817224fefe48",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x7f1629743ac0>"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "gap = np.asarray(gap, dtype=float)\n",
-    "plt.imshow(np.log10(gap).T, origin='lower', extent=(0, 5, 0, 5), vmin=-1, vmax=0.6)\n",
-    "plt.colorbar()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "id": "1337b3ba-b7df-4b35-b270-22de3df428a3",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7f1629476cb0>]"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.plot(Us, gap)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "67b7cc81-411d-4e65-b55d-e72c3711318d",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "only length-1 arrays can be converted to Python scalars",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[8], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m ks \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mlinspace(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m2\u001b[39m \u001b[38;5;241m*\u001b[39m np\u001b[38;5;241m.\u001b[39mpi, \u001b[38;5;241m2\u001b[39m, endpoint\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[0;32m----> 2\u001b[0m hamiltonians_0 \u001b[38;5;241m=\u001b[39m \u001b[43mutils\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msyst2hamiltonian\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkx\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mks\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mky\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mks\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msyst\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mwrapped_fsyst\u001b[49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[0;32m~/Sync/kwant-scf/codes/utils.py:21\u001b[0m, in \u001b[0;36msyst2hamiltonian\u001b[0;34m(kx, ky, syst, params)\u001b[0m\n\u001b[1;32m     18\u001b[0m \u001b[38;5;129m@np\u001b[39m\u001b[38;5;241m.\u001b[39mvectorize\n\u001b[1;32m     19\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mh_k\u001b[39m(kx, ky):\n\u001b[1;32m     20\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m syst\u001b[38;5;241m.\u001b[39mhamiltonian_submatrix(params\u001b[38;5;241m=\u001b[39m{\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;28mdict\u001b[39m(k_x\u001b[38;5;241m=\u001b[39mkx, k_y\u001b[38;5;241m=\u001b[39mky)})\n\u001b[0;32m---> 21\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mh_k\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mky\u001b[49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[0;32m/opt/conda/lib/python3.10/site-packages/numpy/lib/function_base.py:2328\u001b[0m, in \u001b[0;36mvectorize.__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   2325\u001b[0m     vargs \u001b[38;5;241m=\u001b[39m [args[_i] \u001b[38;5;28;01mfor\u001b[39;00m _i \u001b[38;5;129;01min\u001b[39;00m inds]\n\u001b[1;32m   2326\u001b[0m     vargs\u001b[38;5;241m.\u001b[39mextend([kwargs[_n] \u001b[38;5;28;01mfor\u001b[39;00m _n \u001b[38;5;129;01min\u001b[39;00m names])\n\u001b[0;32m-> 2328\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_vectorize_call\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfunc\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvargs\u001b[49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[0;32m/opt/conda/lib/python3.10/site-packages/numpy/lib/function_base.py:2414\u001b[0m, in \u001b[0;36mvectorize._vectorize_call\u001b[0;34m(self, func, args)\u001b[0m\n\u001b[1;32m   2411\u001b[0m outputs \u001b[38;5;241m=\u001b[39m ufunc(\u001b[38;5;241m*\u001b[39minputs)\n\u001b[1;32m   2413\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ufunc\u001b[38;5;241m.\u001b[39mnout \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[0;32m-> 2414\u001b[0m     res \u001b[38;5;241m=\u001b[39m \u001b[43masanyarray\u001b[49m\u001b[43m(\u001b[49m\u001b[43moutputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43motypes\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   2415\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   2416\u001b[0m     res \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mtuple\u001b[39m([asanyarray(x, dtype\u001b[38;5;241m=\u001b[39mt)\n\u001b[1;32m   2417\u001b[0m                  \u001b[38;5;28;01mfor\u001b[39;00m x, t \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(outputs, otypes)])\n",
-      "\u001b[0;31mTypeError\u001b[0m: only length-1 arrays can be converted to Python scalars"
-     ]
-    }
-   ],
-   "source": [
-    "ks = np.linspace(0, 2 * np.pi, 2, endpoint=False)\n",
-    "hamiltonians_0 = utils.syst2hamiltonian(kx=ks, ky=ks, syst=wrapped_fsyst)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "id": "8087fe0d-29dd-41c4-89fc-cd5cdc758c28",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "params={}\n",
-    "# @np.vectorize\n",
-    "def h_k(kx, ky):\n",
-    "    return wrapped_fsyst.hamiltonian_submatrix(params={**params, **dict(k_x=kx, k_y=ky)})"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "id": "5f79a80f-d9f6-4b22-b8a4-9d188153f0c9",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "ename": "TypeError",
-     "evalue": "only length-1 arrays can be converted to Python scalars",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[19], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m vhk\u001b[38;5;241m=\u001b[39mnp\u001b[38;5;241m.\u001b[39mvectorize(h_k)\n\u001b[0;32m----> 2\u001b[0m \u001b[43mvhk\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkx\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlinspace\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43mky\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[0;32m/opt/conda/lib/python3.10/site-packages/numpy/lib/function_base.py:2328\u001b[0m, in \u001b[0;36mvectorize.__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   2325\u001b[0m     vargs \u001b[38;5;241m=\u001b[39m [args[_i] \u001b[38;5;28;01mfor\u001b[39;00m _i \u001b[38;5;129;01min\u001b[39;00m inds]\n\u001b[1;32m   2326\u001b[0m     vargs\u001b[38;5;241m.\u001b[39mextend([kwargs[_n] \u001b[38;5;28;01mfor\u001b[39;00m _n \u001b[38;5;129;01min\u001b[39;00m names])\n\u001b[0;32m-> 2328\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_vectorize_call\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfunc\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvargs\u001b[49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[0;32m/opt/conda/lib/python3.10/site-packages/numpy/lib/function_base.py:2414\u001b[0m, in \u001b[0;36mvectorize._vectorize_call\u001b[0;34m(self, func, args)\u001b[0m\n\u001b[1;32m   2411\u001b[0m outputs \u001b[38;5;241m=\u001b[39m ufunc(\u001b[38;5;241m*\u001b[39minputs)\n\u001b[1;32m   2413\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ufunc\u001b[38;5;241m.\u001b[39mnout \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[0;32m-> 2414\u001b[0m     res \u001b[38;5;241m=\u001b[39m \u001b[43masanyarray\u001b[49m\u001b[43m(\u001b[49m\u001b[43moutputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43motypes\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   2415\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   2416\u001b[0m     res \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mtuple\u001b[39m([asanyarray(x, dtype\u001b[38;5;241m=\u001b[39mt)\n\u001b[1;32m   2417\u001b[0m                  \u001b[38;5;28;01mfor\u001b[39;00m x, t \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(outputs, otypes)])\n",
-      "\u001b[0;31mTypeError\u001b[0m: only length-1 arrays can be converted to Python scalars"
-     ]
-    }
-   ],
-   "source": [
-    "vhk=np.vectorize(h_k)\n",
-    "vhk(kx=np.linspace(0,1),ky=[0])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 50,
-   "id": "94474a64-be2f-4b37-a2bf-a926080e4026",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "max_neighbor=1\n",
-    "norbs=20\n",
-    "shape = (\n",
-    "    max_neighbor + len(graphene.sublattices),\n",
-    "    2,\n",
-    "    norbs,\n",
-    "    norbs\n",
-    ")\n",
-    "mf = np.random.rand(*shape)\n",
-    "mf2 = mf.flatten()\n",
-    "mf2 = mf2.reshape(*shape)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 51,
-   "id": "61557cad-5bcc-402b-95a4-ec3e36a6d211",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[[[0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         ...,\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
-       "\n",
-       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         ...,\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.]]],\n",
-       "\n",
-       "\n",
-       "       [[[0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         ...,\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
-       "\n",
-       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         ...,\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.]]],\n",
-       "\n",
-       "\n",
-       "       [[[0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         ...,\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.]],\n",
-       "\n",
-       "        [[0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         ...,\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.],\n",
-       "         [0., 0., 0., ..., 0., 0., 0.]]]])"
-      ]
-     },
-     "execution_count": 51,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mf - mf2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 152,
-   "id": "d45e62e4-dace-4472-adbb-3305a41bd333",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "deltas = extract_hopping_vectors(bulk_graphene)\n",
-    "nk=100\n",
-    "ks, dk = np.linspace(0, 2 * np.pi, nk, endpoint=False, retstep=True)\n",
-    "hamiltonians_0 = utils.syst2hamiltonian(kxs=ks, kys=ks, syst=wrapped_fsyst)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 153,
-   "id": "26e4203a-0140-4a66-891a-2912e3bb721e",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[ 0, -1],\n",
-       "       [ 0,  0],\n",
-       "       [ 1, -1],\n",
-       "       [-1,  0],\n",
-       "       [-1,  1],\n",
-       "       [ 0, -1],\n",
-       "       [-1,  0],\n",
-       "       [-1,  1],\n",
-       "       [ 0, -1]])"
-      ]
-     },
-     "execution_count": 153,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "deltas"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 154,
-   "id": "7570fda5-a1e4-43e8-b89e-a6f6e83436be",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "kxx, kyy = np.meshgrid(ks, ks)\n",
-    "deltas = np.asarray(deltas)\n",
-    "kxy = np.array([kxx, kyy])\n",
-    "hopps = np.sum(\n",
-    "    np.einsum(\n",
-    "        \"ijk,jklm->ijklm\",\n",
-    "        np.exp(1j * np.einsum(\"ij,jkl->ikl\", deltas, kxy)),\n",
-    "        hamiltonians_0,\n",
-    "    ),\n",
-    "    axis=(1, 2),\n",
-    ") * (dk)**2 / (2 * np.pi)**2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 155,
-   "id": "89b06c4e-75b1-430b-b026-22f108898e51",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[4.0983883e-17-1.j, 0.0000000e+00+0.j],\n",
-       "       [0.0000000e+00+0.j, 4.0983883e-17-1.j]])"
-      ]
-     },
-     "execution_count": 155,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "hopps[7][:2,:2]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 156,
-   "id": "52dcb47f-8a52-4c11-8b4e-38d5959ac118",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[1.-1.04091735e-16j, 0.+0.00000000e+00j],\n",
-       "       [0.+0.00000000e+00j, 1.-1.04091735e-16j]])"
-      ]
-     },
-     "execution_count": 156,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "hopps[0][2:,:2]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 140,
-   "id": "3dd2139f-713a-496f-8056-19e8d7ef56d2",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(2, 10, 10)"
-      ]
-     },
-     "execution_count": 140,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "kxy.shape"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 90,
-   "id": "10d07c6b-1762-42e9-aeaf-0c1f4d1ce0e3",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(3, 10, 10)"
-      ]
-     },
-     "execution_count": 90,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.einsum(\"ij,jkl->ikl\", deltas, kxy).shape"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b161c9d7-bbf9-403b-882a-df48262315c8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "deltas=[]\n",
-    "for hop, val in builder.hopping_value_pairs():\n",
-    "    a, b=hop\n",
-    "    b_dom = builder.symmetry.which(b)\n",
-    "    # Throw away part that is in the remaining translation direction, so we get\n",
-    "    # an element of 'sym' which is being wrapped\n",
-    "    b_dom = ta.array([t for i, t in enumerate(b_dom) if i != keep])\n",
-    "    deltas.append(b_dom)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.8"
-  },
-  "widgets": {
-   "application/vnd.jupyter.widget-state+json": {
-    "state": {},
-    "version_major": 2,
-    "version_minor": 0
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/analysis/data/graphene_example.nc b/analysis/data/graphene_example.nc
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diff --git a/analysis/graphene_test_extended_hubbard.ipynb b/analysis/graphene_test_extended_hubbard.ipynb
deleted file mode 100644
index e8a8a5307658263d66acff8b77ffa2c2055668b4..0000000000000000000000000000000000000000
--- a/analysis/graphene_test_extended_hubbard.ipynb
+++ /dev/null
@@ -1,332 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We will test the implementation of long-range interactions by trying to reproduce the results of [arXiv:1204.4531](https://arxiv.org/abs/1204.4531)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Create monolayer graphene model in kwant."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "import kwant\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "import utils, hf\n",
-    "\n",
-    "\n",
-    "s0 = np.identity(2)\n",
-    "sz = np.diag([1, -1])\n",
-    "\n",
-    "\n",
-    "graphene = kwant.lattice.general(\n",
-    "    [[1, 0], [1 / 2, np.sqrt(3) / 2]], [[0, 0], [0, 1 / np.sqrt(3)]]\n",
-    ")\n",
-    "a, b = graphene.sublattices\n",
-    "\n",
-    "# create bulk system\n",
-    "bulk_graphene = kwant.Builder(kwant.TranslationalSymmetry(*graphene.prim_vecs))\n",
-    "# add sublattice potential\n",
-    "m0 = 0\n",
-    "bulk_graphene[a.shape((lambda pos: True), (0, 0))] = m0 * sz\n",
-    "bulk_graphene[b.shape((lambda pos: True), (0, 0))] = -m0 * sz\n",
-    "# add hoppings between sublattices\n",
-    "bulk_graphene[graphene.neighbors(1)] = s0\n",
-    "\n",
-    "# use kwant wraparound to sample bulk k-space\n",
-    "wrapped_syst = kwant.wraparound.wraparound(bulk_graphene)\n",
-    "wrapped_fsyst = wrapped_syst.finalized()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now we sample the non-interacting hamiltonian on a k-grid:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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8z+rcLXWl7HntD4SuycMUEYAUryQ6sI1UdX2//dolXw5IGZQQR5sQiiSo8RUMDIn1lAEHRof8lEuUkZGRuWARRZGNDfv5uK6GDdZI7Hhy55SSiyHWQwwt3EPY/hoU4pHXqgqt5E+QyUlsay1OvRHppiuZePNjZy0w1lRay571OylsOoyVo7mN4epAcjKHkTNz7AWhESUbIgOEy+WieFsehVt20Fx2EIe1od/ngkKPX1g6CcNHMWLOJPzDg05wpgGel+hiWdUOPmtsY4cjBndv70INdi7S1XFTdCwzo0aelSXc1VbPjjf+QNCy7fhYJHr89bRm+BIQ42KYUIa3cNQwc0sC+VISh6Rk6oQobPgQ5xXB8JzhDJk6ApVWPWDXLCMjI3O+qDM182H5LpZ06qiXjlY5hrsbGFG3k+SdhWg7PZIICpUfWoU30fUtxDVXoHE7qI8xoL/tZ4y75gGUyjNfvNpMVvLW7Ca38CCNzva+7Xo0ZIanMGraOCLSYn76hQ4gsiEySLTVtZC7aguVefvobikBqX+Gs9YrmoiUbDKnjCdt7NBjEokGgwZTMx9W7OabDg11Uljf9gihlSsCrNyaOIYYnzMPJ5l7Otj2z2fw+nodgUY3AEaDkrq5QwkP9yK6cxfxYk2/Y5olf/ZJGZRLcZgVkWSGZzB62ngi0i+sH4iMjIzMqXC4nSyr3slnDW3scsTgFnoXfJKN4ca9ZB48QFBhEwIqDH7x+IZFoC7fRcb+4r629tUpfgTddScj5/38jBeGoihStf8w+7fvoaS9EqfgeQ4LEsQZIhg+fDhZU4ej0lyYCz7ZEDkHuBxODm3aR/G2nTRX5uOyNff7XFB4ERCRQeLI0QyfMxHfYP9BnY8oimxuzOXj2irW/chlqMDNGHUNN0QEcXn8eDTKM7tpHVYLWz/8C6pPlx2VlldD/Yws4q+7A3NNPtqqdaSa92MQjhpmDknJQSmZAikJiyqN7MzJjLh4wgXhMpSRkZE5EUUdFbxXdoDvTYF0CkdD4AmOMnIqdxG36zBau4HA6EySRo9GqWrA+NE7xBV39u1bOSyEmHseZOjUq854/J5WI/tW7yCvvIBO8WjZra9gYGhcBqNmjScgKvinXeQ5QDZEzgNNFfXkrt5Cdf5+TO2HQfpxQzoBnU8skWk5DJ06kcSR6YOaQGS09/BpxXYWtTooch/1RvhjZL5PB7cmDGVIUPIZndPldLD981dwfvQFkfUeF6RLAdWTEhny4O8ITxzG4d2rMBesIKp1KzFS/zBWvRTEATGdbn0O2ZOvImPi8POWRCUjIyPzY0wOC+/nrmZJt4si5dFno4/UzYi2XaTvzSO0w9/zDJ82kficFPZ++zbd735ATJWn6tItQNWYaFLvf5zUUTPPaHy3y03J1nz2791LRU89Ym/iqVJSkOwXy4ixI0kZ999VFCAbIucZu8VO/sbdlOzYRWtVPm5He7/PBaUPep9YvAMj8I8IQqEQTnCmn06jl5mtoUq261PpFo5+h2nucqab2rgqZAwpwzPRGk6vAZ8oiuxZ+i+M77xPTIXHWhcFqBoVSdL9vyZ9zBwAasvyqd+zDH3lWtLt+WiFo4aZXVKTK6XS4jWKMdf/irDYuOOOJSMjIzOYrNq+lg/aK9jtlYVFOCqTkGE7RHZpLpn1PqQNH0vO7An4Bvt7FmSfvIjr46+IaPR4gJ1KqJmSzNAHfk9cxpjTHrurrYmyPZuoy9uB0dyFC3ffZ1pBjb+vP4FhQSg1g1cQ4XI6MDaUogpOYvZtTw/ouWVD5ALB1NlDxf4iSnbl0lJRicPahuhqgR/dcIIiAAQdkruJ/jXmA4uoUtAwMpaDaaMo1A9FEjz5K5GuWqbvX0F0oQ3fwGiCYxKISk8haUTGKZNvc9d8TuM/3yC+oKNvW9WQICJ/+QDZM67p22YxGSnZ+QOm/UtJMu8hUmjr+8wk6dipnUHWDc8QEZ8ywFctIyMj0x9RFFm3ejX/tFWy3XdM37MwWGxhVPMBJrXpmDRqGqljsvry/OxWE1vf/RPqL74npN3T5sOqgcaZQxn14DOExZ1YQkF0u2msLqa5dA/2ujz0HUWEWw4TTtsJjznXHBCTGf7HfQN6TtkQOceIokhLVSOVB4poKD1MR0M15s563M7O4+ytRFCGIii0iM56OCKprvBGo4tFY1Aw2BELkz8cGhLCxpCxfZ2B02wFTNm6Cv+yo0aFQumD3i+SwMh4wpOTiB+WTnRa3DFJuEU7vqfijZeI39fY17CvJsmHgF/czqjLftEvBCOJIocP7KBs3WekmjaQrPCUBzslJbu0U4i6/EkSMkcP6vXLyMj87+FyuVi3eDmfiaVsDJuMXfDkq2VbDzLP5uSGsZcQEhXW7xiTsY1t/3ga38Ub8O/xqJSa9AKtl4xh/P1/JCC0v9K1zWKitmQ/nRX7kBoP4mssJsZR2a/a8MfUSsHUSZEIagNqnQZh8JzjALhdTtw2E2rRhtC78HWjpMMrmVmP/huFcuAKLGRDZBBx2B3UHCyjOr+YpsoKjE012EyNx+iNHOHIyzwgPJbw5GTih6UTkxGPQqWkq6WTde9/SXXe+r4mRoJCR3TWVGbedi2BkYOrydFq7eDPhzbydU8MLsGTxDrGtJcx63egb2g+/kGCGq1XBH4hMYQmJBKdmUrS8DR03gYq8rdS+PpfiNtWiaq34WNDlA7trTcw/vqHjylbc1rt/PCvl4hpX8IIRWnf9n3q0RhmPkbG2DmDct0yMjL/O9jMVtZ9vJjvlSWsS5qOUeFJQE10VfCQv4FrRl98zDGdLTXs+PtThCzf3dfRvMtHQfdV05j4y6fx9gumvbmOhpI9mKsPoGotINhUQoy7DuVx2mjYJTVVihiq3OE0SEF0CIGgCOGiUdMZMXf8oOd+lO7fhGn9i+T0bOlT0S5RpWEefT85M28YUAPkCLIhMlDjt3VRvq+QuuLDtNVU0dNWi9PWyo9DK0cRUGmD8Q6KJjg6gai0ZBJHZJyWMWEzWdjw8beUbF/xIy+KitCEsUy95XpiBrgr4n9yuLOap4v2sc6eCIAaB1fqa7jKFEh3UT1t1ZV0t9XitPYPKx1FQKUNwisgmqDoeHxCvDHuWUrSply0vc2KW0LUuH+2gEm3/vYYIR9Ll4nv33+L0K7vmSzk9f1QipTp2MbeT/aM6wflhyIjI/P/l+62Lta8/wU7FMWsy5lJo9KjfhoqtnBvgINf5Mw7JmG+ubqIva8/TcSag+h7tcJaAlUYr5hOeGo67uZCDB1FRNrKCOF4Hm/oxJc6bRLmgExUkcOQlFHk5lZS7/R4mzWoGJ88gkkLZ6LWDV77EEkUyd+8BOX218hy5PVtz9OPRT3lYTLGzkEYRPe7bIicIaIo0ni4lsq8YhoPl9HRUI2lqx7RZTz+AYLG4xUIiyE0PpG4IenEZ6eg8/pppakul4ttX64ib823OK2NRwbDL2wYk66/lvTxw37S+U/F9saDPH24koNuT/KoNybuCOriwcwZ6FV6XA4nVfllVOeX0FxRjrGpBmtPwwm9QYLCC6XSB2+Li4AeM8HGVgShHes1M5l01x8wePv327+9tpUVn31EoGktMxR70AoeK6ZaiKJl6F0Mm/eLQWs4KCMj8/+D5ooG1n3wGYVSIZsnzaJU68nf8JZ6uM2/nUeGzUWn6p+cX120m/zXnyVsZxWmMB9coRpUIS7CfEzESw39pAmOIEoC9YoIWrxScQZnoY/NITJ9DMHhsQgKBe01zaxZvILirioQPI3ncsIzmHHNxXgFDd77zOV0kLvyAwJy/0GSuxLwhL5z/WcSPPtXJGSNHbSxf4xsiJyC+tIqDn35W5qsMfS0mLGbmo4RJzuCQuWHwS+SgMg4IpOTic9JJzI1dlBLT0VR5MDK7exeuhhL1+G+7Qa/JEZfdhUj5k0atPFFUeTbqm38rcZMjeQRQguljV9FCdyUPO2YcUVRpK2mmYpcT35Me1015s463I6O450eUKHCB61bhTrUj9kP3kNMWmq/PWoPVrBi2WIC7NuZo9iJb2/vmxYCqUi6iazLHsLHL3DAr11GRua/l4oDJWz69+fUuUvYOf0i9vmOA0AtOVjoU8uTQ6YTrD+qCyKJIju+/4C2TV8RSieRug6ilW3H7VBulTTUqBPo8kuHsKH4JQwnJn0UXj7+x+xr6TSx7quV5DYU9nW/TfWJZdaV8whJGLxeZRaTkYPfvUlcyftE0OrZJmk5GH4F8fMfJTz23BYDyIbIKVj22p+4rPMFACrdYey2JNLQpkNJMD5B0QTHeipHEkdk4H+OOxb+JyU789ny+ZcYm/I4UlWj1kcwbOYCJl0zZ9BU9RxuJ/8qWcebzTo68Qc8PW1+nxjK7JhTJ5Naus1U7C+itrCUlqoKutvqcJibANd/7CmgMUQzZNrFjL1iFgafox6Pwo25rNm4ggD3QeYothMmdAHQjYGCyIWkXPIowZFy6a+MzP8yB9ftZsfiRXQ4ysmbNY6tIdNwCWoESWSGvpJnMseQ5HdUT6mp5jDla/5FZPUyEhRNx5yvlQAadcmYAzPQRGUTkjKKqMQhKE/RV8xld7Jt8Xq2l+7F3luEEKUJZvbcOcQNHzwjoLO1keJlL5Fe+wUBeCQVOvClJP5nZF76MH5BYac4w+AgGyKnYPeKbzFveZVx6gL0wtGmQYXqIZjSriJtxs34BVxYynV1xVVs+OgLWip2cuRlrlD7kzZ+LtNvuQKd9+CELHocJp4vWMvHXeF9aq3j1JU8k55FdnDqKY7uj8vloq6gkorcAg7v2oK1owW39KM4q6AhMHIYw2bOZPjs8ShUStwuN3u/28qm3K34iWXMEnaQqPCErRySityguUTMfYyYlOwBu2YZGZkLG9HlZseSdRxY+S0WRx0l04exIe5iLL1VgDmqap5OTWJc2BAAeowdFK/7N4bir8lyHOw7j01Ss9+RhDk8h/CcOUSkjSY4/MxaUoiiSO7KnWzcs5VuyeO9DVB4M33iVLKmjRg073VDZTG13z/PsNbv+t5j9UIYdRl3kH3JPegM3oMy7ukiGyKniam7k6L1n6IvWkSm7WiSpF1SU+AzHkX29WROuRKNVjfgY58tHY1trHvvC2oLNvXlZggKA3HDpjHjtmvxDxuckEWdqZk/FmxjuSUOESUK3Mw3VPFU5sSz6mUDntK475/4FZZ66NLZESVT32cKpQ8RqWMYdenFJI/MwG62sXnRGnZVHMBXauAiYTfZinLAE6vN9Z6E17RHSBs1fUCuV0ZG5sLDYbOz8d/LKNr8PU5HGzUTk1mfNY82hacRXazQxBPxPlwWOx63y0nh1iW4DnxBVvdWdL2iiqIkcMgeT02TP7rJM5l+6xNnbSyU7Sxg9dq1tLg8Cyo9WiYPGcvYBRehVA9Ogn35we10rnmRnO4NqHpDP2XKJIwj7yVn9i2n9NycK2RD5CxoriunYv2HRFR926+ZWyc+lAbPwn/cTaSOmDqoWcZngqXbzPoPF3N416qjSbWCmvCk8Uy/9Xoikgen0dzBtlL+UFzADmcCAFps3OTfzONZM/DRnJ0FXrRzBTVP/Q5sEVSHhNCjMsKP2lurdeHE50xk/FVz0eq0rPtqJQdbSzFIHYxnH5MU+X37FmiG4hr3AMOmLrxg/lYyMjI/DVNHN+s+WETFvrWI7h5ah0awYcxcqtWeSr9Aurgv3M4vUqZReXAHnTs+JqV1NYF0952j0hVGeVMEXgUm2kfFMuWZf+AbeHaLqKbSWlZ9u4JKi6eVhUpSMjpuKBddPWdQ+mlJokjB9uWIW19lmO2o8NhB3UgUEx8ka+KlF9zzTjZEfgKSKFKev4O27R+T3LySYLr6PqsVIqmLvYy4qbcSmZB+TuZzKlwOJ5s//4FD65fh7Gu8pyAgMocpN1xH8ujMQRl3de0e/lTRQqkYBXj62NwbauGu9Jln3FgPPJneG954gsAPf0DlUlIRmUZtmD9OZwvQK0qCgCEgmbTxU0nMyWLL6g2Um+vRiiZGSAeZptiLprdDZaUijrbsu8mZeztqzenJ18vIyFxYtNY0se79L6gv3gKSne5YP7ZNnc0hgycUq8PKLQEt3OQTR9uWr4ioWUqcWNd3fLvky/6eRLT5DoJrO2mM0hP+zNNkTVpwVvMxNnWwdtFKDrUdRhIkBAmygpOZdfU8/MIH3hvtdrnIXf1vfPe9QYq7zLNNEjjgOx3/mb8iOXvigI85UMiGyADhcjoo3LoMx4HPyTJu7pdPUqTOojv1KtJn3Ixf4OAKj50Ooiiy97vN7F3+Ddbuir7tXgGpjL1iIdmzxg14rFIURf5dtoGX6iVa8OTUxAjNPB5r4Mr4iWc1XkttCXueuIfEPZ6VRmOgD7UT59Dd3orDfPQBg6AmIHIYUSlDKWutp1XsRCXZyBKLma3YgZfgaczXRDBVqT9n6KX3HzfDXUZG5sKjOr+MDR9/TnvNXsCNLUjHvllT2eE3HknoDQ1ry7mquYaYom/Jchz1itokNfneE6lqVZP6fSEat4RVA203zmLaQ8+j1px5qN1msrJ50Rr2VOXh7F3sxBsimHPZPCLSB977bLOYyFv+D6KK3iVa8iTUWiUNB0MuJWb+ry+YhfDJkA2RQeBE+SQOScUh7wkI2deSddHCCyKfpGDLAbZ/9RXdLYc4UmmjMUSRM+dyxi+chWqAY4hWl5XXi9bxTps/JjzhmaHKGp5JiWdCxNlpn+xe+i/sz/2d4A5PYm5VViAhv/gdFXvLqS/aiejq6ttXofTBJzSDbrWSbi8nguQkTapkprCVYMETtjLiRWH0taRe+iuCwqJ/2gXLyMgMCgWb97Ptqy/paS0AwKVTUXjxxF5Jds+zdYxUyM8P/8C8hpX98j6KtMMwZyzEbLKheeNjAo0eg6FieBgj/vIGEQlDzng+bpeb3Us3syV/JxY8Eg8hKn9mT59JyoQzP9+pMLY3U/jdK6RWfUYQnmdXF94UxVxP2qUPExgaNeBjDhayITLINNeVU7n+Q8KqlpIgVvdtP5JP4jfuRtJGTDvvMbuaggo2fPw5bVW7OaKIqtQEkj5xHlNvWvCTBdj+k1ZrB38p2MjXPdE48SgGTtdW8EzGSFICzrzM1mLqYsOf7yN26T5UIthV0HTtZKY++jKl2ws5sGo1bTUH+mnAKNUhuL3CMQdqEDUiyTRzkbCZGDyVNjZJTV7wfKLn/5qoxKyBuXAZGZmzRhRFdi/byL7l32DrqfJsUwjUzB7H6rhJGAU/AFLcZfy6/B0ubdzZd2yVIobGuAUkTL8V0WEh94n7SchrAaDDX4ny0V8ybuG9ZzWnwo25rNu6gU7RUxLrI+iZOmoSwy8eeEn2ptoyqpa/wLCmJX3iaY2EUJ12G8MuvReDt9+AjncukA2Rc4QkilQc2knrto9Jbl5xbD5JzKXETr2VqMQTd2Y8FzRU1bL2gy9oLdl59KWtMOBOzkZ3+TBC/X0I1fkQrvcn0hCCr8b7J4VxDnfV8EzhXtb2SsarcLLQu5Ynh0wlRH/mcdSyvE2UP/EYseWeB0JTuJaA3/+GnBnXYbfY2b1sPYVbNmBqK+bH+SRoInH5BmMJUJCitTBa2kSa6BGIc0sCuT4XEXzJH4hLH3HW1yojI3N2iKLI5s9+IG/1N7jsHuNBQqBr+lh+SB1FA55E0jCxkcfq3+GGinUogHb8OBx6McETbyZp6ARcLgfrX36UkM/WoXeASwE187O56Hdv4u138g7ix6Mmr5xVP6yk3u4RBdOiYlzKSCZdNeMnSbK7XW7MHd2Y2rvpbu/GbOymtbERU30Jwa4GfAUjXpIRs1KJLXMuIy+9Ga1+4BNfzxWyIXIecDkdFG77Dsf+z8g0buknCVykzuzNJ7llQPJJRFGkw26k0dxGk81Ii62HVpuVFoeDdqdIuws63Wo6RS1GyQszXgB4mW3M2bGLxIqdCL1WvqjyZ8eoeWzPOZrUqsaBHyYCFFYClE4CVSJBKoEQjZoQrY5QnRdhOl8iDEGEGYJOmJy6oymfpw9XkOfyeEO8MHFHUCcPZc5ErzqzH5goimx652m83v4aH4vnli2fksjEP/2jrwNmV1M72xevpHzflv75JKhBH43Dz5+4CDWZ0iZy7HsBj/Tx3sifkf2zP/1XrjpkZP4bqThQwoq33sDW7ZEgR1AjTh7Lisx0CokHwEfq5s7WT7i/ZDGSW0GB72TUI64na9ICVGqPQZC/aQmtz/yRiAZPTlhtvBdxz/6FtNGzz3hObdXNrFn8AyXdHi+3QhIYHpHB9Gsuxivw+O8fu9lGT2sXpo5uejq6MRl7MJvMmM0mzFYLFocVi9OGVbRjkxxIZ9BdV5AEdIIGg0KLXq3DS6vHoDfgZfDC28cbb38fvP198Q7yxTfED43h/KcF/BjZEDnPmHu6KFz3KbqiRWTZcv8jn2Q8QvZ1x+ST2Fx2mixtNFo6aLZ102Iz0+qw0+pw0u6U6HQp6RQ1dIp6jPjg5szyPBS48cVEgMJCoMtKzs4KAg/tAdEMgNU3me9mXUx1yJmXs/nQg59gIUBhJ1DlIlAFwWoFoRotwRodDZZWvuj0oVaKACCUdh6OlLg5ZRpKxZnV2nc0VbP9d3eTtLUKgG4vAevd1zDl9qf6eXGq88vZtXQF9cU7EZ1dP/oivMAQQ0R8JJnqleTYdgGepNbG8U+RM+um8x5Sk5H5/4ql28yyl/9FfdEGPN5LFYYJk1mTFcJ2pSefTC05uKb7Wx4v+JgWRRKW9IVkTP9Zv7YOxvZGtvz+LhLWH0YBmHUCxtsvY+o9fzqmy/epMHd0s/6rVeQ2FuFGRIuKeH0kqVlpoABTt8ljXFjMWOxWLA4rVrcdi2jHJRyvCejJ0UoqdJICLyQMkhsEJU6dPw5JxOr2GC32YxSoT41aUqJXaNErdXhp9Bh0erwMBry8vPD288HLzwefQF98gv3xCvTpCy+JogiihEI1sLonsiFyAdFSX0nF+g8Iq1xKgljVt71T8ma51yQ+zLiSKu/oPq/FmaDHir9gwl9hI0DhIlAtEqxWejwXGj1hOm/CDf5EGAIJ0gUc89I3dXSz9OW3aTq8GZBAUBM38mIyb55Bq7uHZmsPLXYLbQ47rQ43HS7ocCvpdGvpkgz0SN5Iwmm+tCU3qZTQRCTdgj8AMdQw3auDBTEjGBOWiUpx+g+QA6s/xfin5wlr8VQy1aT4kvznF0kaNrnffqIocmjD3t58klyQbH2fCcogAiLjmWn4nBiFp/Q5Tzea4Gtek/NHZGQGEFEU2f7VavYs+xjR7dH20ISmkDsrlpXek3D3SrLPtK3nrpJlKIMuImHaLYTHJB9znq0f/Q3Nm5/iZ/KEYcvHxTD2z28REpV8zLgnwtptpmxPEfm7cmm3GXHiwiG4sOM8I68FeDwnBkGLXqnFoNFj0Bow6A14exnw8vXBx88H7wBf7O5uulb/gVHWjYBHSr569JOMnHv7MYsfl91JT5uRnjYjps4eerq6MZt6DSJrr0HktGF127FKdsTj9Mc5GUe8LTrUKF0SARpffvbUXWd24adANkQuIBpMzaxtKGBLZyedlW3MrNnOFeZNhAkeJT6LpOUD70v4e8bNdHv59Hkt/BUOApVugtQQrFERotESqjUQpvclwhBImD4Ib83AyLqX7i5g9dtvYjd5hNxU2hCm/OwXDJ8z4aTHuUQXLZZ2miwdNFq7er04NtocTtqcEh0uoTdEpKcLbxxo0Ug2EimjkiTsgh6F5CaNIuqIYaimg/F+amaEJZETnHbKPBWH1cK6Fx4k8qutaFzgVELd5aOZ9uQb6A3H3i92i52d364lf91q7KZKjuSTCMoAImJCuULzITqlC7ukZn/crQy//ml0+jM3EGVkZI5SW1jB8tffwNJZCoBC5Ys4Pp5PMybSoPBUgWQ7c7mx5QDjh15D0tDxx/VKVhfuouiJh4kr9jw7W4PVGH77MKPm33rKOTgsNir2lVBRXE51cx0tzk6kk7y8tajRK7QYVDqPcaHTHw2J+PaGRYL88A3xR+ujP+mzyumws+/LPzOs7J8YBDsuScHe8GvIuuGvA9K8UxRFbEYL3W29IaLObszdJo/hYrH0hYhO5m0JcRq465lHBrSiUjZEziNt1k7WNRxkc3s7ey16qnvDEUcQJJEUoZ5L6vczv2IpWaJHprxH0pMfdzPDFv4Wb99z32hPdLlZ9+ES8td92Scd7x85nMsevpeQ2IHpGNnjMHnyWqxdHDbWs6jZSK7kyU2JkOqRgCbB82Dyo5scbRsT/HTMjEglwz/xhD/26qLdFD75MPGFno6/rUEq9L95kNGX3nHCubRUNvDty+/R05rX5yVRqoNJCHFzqc8yFAqoE8Jpn/InsqddPSDXLyPzv4TNbOW7V9+n5uBqPFV7CrwiUiiY6s3XvpchCUoCpA7uEUu4a/KtJ5Q+cFgtrHvufiK/3o7GBQ4l1F85lhlPvIFWf3w1Z5fdSVXuYcoLDlPdVEuTvf0Yr4GXpMVH1BPuF0LKyEx8g/zwCfbHO9hnwJqJFmz/Aa+1j/epdRerM9EseJXEIWMH5PxnSsX+Eta9/yG27lpUai+Uai8MAbEkj8xh3MKpAzqWbIicQ4z2HjY0HmRTWzN7zFrK3RHHhCviFY2MNliZHBjM9Mihfa2oJVEkb90X+O14ri9s04kvJcm3k3Plo+elaVFXcwdLX3qLtureEjlBS9rEy7n4l9cPuP4IwMel63m2Xk0PPiglFyOFXA5KGdiE/p6IIDoZoetgor83syIz+3XThF6X7ScvoP77x/j39Lpsx0Yz5s9vEhp94uZ8hzbsZ81nXyF2l0Bvx0yVNozhgQ1M8d8OwH6vyURe9+oxbmIZGZnjs2vpBnYseh+30+O9UOsiCRnewUtDb6FO4fntThHzeGPcfEK9TtxgdN/Kf9Pzlxf7QrDVqX6k/eVlEob099a6nW5q8ysoO1RCdUMNjdY2XILYbx8DWvxFL9ySmx6FDV+NF1dcexVhyQOvzdHWVEvl548w2rga8DzXD2c/xqjL7kWhHJweNCejtqiKNe98QGf9fo5oS/mF5zDrjluJG5o0KGPKhsggYnZa2dx4kI1tDewxqShxRxyTOBoltDBKb2JSoD8zI4cQ4RV60nOKbjf7V75P2N6XiZE8iqItBFKZeQ/DF9x/XkTSCrYcYN17b+G0evQ31PoIpt96N0MuGjngY9WZmnkwbzvbHJ7+NYmKeu4IFamwiezqEShyR+Ci/wolXGhlpK6bSQF+zIwc0td4r7ujic1/+CUJa4r7kti6bp3PtPv+esIkNqfVwbJ/fkXloQMIpjKOaK6oteFMCy5gqG8hFknLwaS7GHHtkxeEaJ2MzIVIY1kd37369z5BMkHhRVKYmy0XJfOp39VIghI/qYs/xsK1yVNPeJ72xkp2PPlLkrZ7Kli6vQSs91zPlFufRKFQILpFGoqqKTtYQlVdNfXmVpxC/5CDDg3R3mHEx8bhMjvYWrkPl8KNUlIwOXUMk6+dhXKAEzTdLhd7v36BjOLX8cWCKAnsCb6M9BtewC8obEDHOh2aKxpY+fYHtFXt4kgo2js4kxm33kryqMGVlZANkQHE7nKwrTmfjS117DJBoSuiT6zrCCG0M0pvZGKADzMjMon3PTsL2+V0sH/ZW8Tm/51w2gBoEMKoz36QEZfcdc67KrpcLla//SVFW77p0x8JjhvHgkd+iX/4mdfnnwxRFPnw8Hr+3KDDjDdKXNwZUM9vh87D4XawsfEgm9ua2GVSc1iMQKT/AyRGaGaU3szkoEBmRg6hdf82mv7wNJH1nrBLXZwXMc/+mfQxc044h/LdxSz9diliUyOCuYIjP1ydNpRZoXmkepdRpYjBPPN5sibMG9Drl5H5b8Zhd/DD3z+mfO/3IDkBgSDvIOKyK3k882FqlPEATNOW81rORYQaju8FEUWRjf/8PT7vLMHb2lumPzWZ8c+8gdOooCy3hKqaKmpNzdh7PZhH0KAiyhBKfEwcycPSiEiPxdjUwbf//ppqm0cmPUwVwBXXXEl46sDLspfsXY9yxaMkuz3h9sPKZKT5L5M64qIBH+tUdDS2sfKtD2ks3Qq9OSEG/2Sm3HgLWZOHn5M5yIbIT8AlutjdXMj6lip29YgcdIZjp/8KOIAuRmg7mBjgxczwNFID4gd0DnabhQNLXiW55O0+kbRqRQzto39Fzuybz7lrr62uhWUvv0lnvafro6DQkzXtambddtWAl3zV9DTyQN5OdvZ2901R1PN6VjLDg9P69um0GdnQcJDN7a3stuiodIf3C4cJkki8spnRegvRpfsY/88VBLfZcAtQPXcoF/3hHycUOnJYbKz8aBl5VQUYmjvBWskRV6aPLog5YfuJM9Sw13cW8Te8THB47IBev4zMfxsHVm1n86f/wmX3LJ7U6kCmRxbxyfhpfOx3LaKgxJduno4RueEkXpCyAxuoePJxYio8Gke1qfG45lyD0Q613U19EutHUElKIvXBxEfFkTQ0leghCX0eDlEU2bNsK+tyN+PAhVJSMDFlFBddN2fAvSBdbU2UfPYYo9u/QyFIdGOgKOMhRl31q3O+eOxuN7LyrY+pLVjfaxCC1juWidfceMrigwGfi2yInD6iKJLbVsK65nJ2GJ3kOUOPKaX1oYccTSsT/XRMD09mSGDygDeQOx4Wk5G8xc+TWfkBfnj0PsqUSZgn/ZZhF111zvUuclfvYNMn/8J1RHHQK5pZd95L2rihAzqOKIq8V7qOvzUaMOOFGgd3BTbxm6Hzjlvi22JpZ11jPpvbO9hr8aJW6u8CVUhuEpwVDK/NZ0RuIXEF5ejv/jkTrn3whHMo21XIspXLsZjN6JvbwHZEyl8gUO/PxeG78dYaKUh/gFELH+0TWJKR+V+htaaJZa+8SVfDAQAEQcfQQAc+GU08lPFbqpSexcRF2gpezZ50whC1uaeDjX+6n9DNdXTGZ9EcHk6zrxqT0N/wUEoKwrVBxEXEkJSVSlxO0nGTSrsaOvj2k0VUWTxh5VCVP1csvGrAm9OJbjd7v/07KfkvEoDHeNrjN4eE618iOHzgPS4nw9JtZuU/P6Vq/2qk3uR7tT6CMZdfz5jLpp6T99V/Ihsip6Cqs5Y17/9AeZQvS0IiMSr6K2rqsZCtbma8n5ppoQmMDEk/Y+GtgcTY2UbR4r8wtPbTvq6yRepMxGm/P+chAofdwYo3PqFsz3d9Ltiw5Elc/qtf4n0C9cGzpaq7nvsP7mGPMx6ANEUdb2SlMTQ45aTH1fY0sa7xEFs6jOyz+dIk9VezVUlOUqylpHUe5vrhE7koa9Zxz2MzWVn50VJyW4tRm0T0La1I9treTxWEevlycdgOjAY/XHNfIH3UjJ96yTIyFzwul4uV//ickm1LQPIkkQYbApgbvZVXhl/Fx/7X4RZU+NDDU9FObkqZftzzuF1u1v7rPVoON9HmpcKocvT7XJAEwjQBxIVFk5iRQuKINNT6Exv8oiiyb/l21u7fiB0XCklgQuJIpt0wF6V6YJ/f5fk7cS59iHRXEQBVilgss54nc/zcAR3nVNgtdta8+yWlO75H6hWnVGmCGT7vGiZde/F5MUCOIBsip+CTzxdRVuJJpvLCh6aQGCrS1QwPVjItNJaxoVknlC0/n3S01FO6+Flymr7u6zqZrx2Bds7T5zwO2VRRz3evvEF3i6f9tqD0YvjFN3DRjZcO6M0viiL/KlnDc00+WDGgxsE9Qc08NmTuaQuglRtrWdtYxNbOHvbbAminf+1+lruE2+PDWJgw8bh/98PbD7Fszff0SFY03RKG1ibcjvreT1VE+Ri4OGwrpWFTSL3hRfyDB6bcWUbmQuPQxr2s/+CfOHtzLtQqP2aEl2OKd/Ng5pNUKeIBmKSp5PXsCUR6H5ug2d3Syc7lm8irKsSs+JHxIUGIyo/YkGiS0pJIHJWBzuf0WkEYmzpY+vFiKiye32WI0o/Lr7qCqMz4n3S9/0mPsYOCTx9ndPMilIKEWdKRn/JLRl7zW9Qa7YCOdTJcDifrPlxC4aZvEV0egTiF2p9h06/kopsvG5QKxzNFNkROQf6+PNas3obJ1obYW+KlQUVWaDJjZ00iPOXCbhPfUl9J5TdPM6LtO9S9EsMHDBPxv+QZEjJHn9O57P5uI9u/fB+306PhofNNYO4995E4PO3kB54hFcZa7j+4j32ueAAylbX8fUgGWYFnVlIriiLFXZV8c2gT24wSuV45SIJntRRIJ1f5G/lF8lhiffrrv9h6rPzw0RIOtpWCKOHbrULZUYPL7nH/ImiI89EwPmw/9cN/yajLHzgvZXoyMoNBV1M73770Fu01npYICBoyAiQmh27l9yMfYpH3HNyCCm9M/C7Kxs3J0/stSERRpHJfKbu37OSwsbpP00MjKYl0qsgaP57MiSNO2NPlRIiiyIEVO1m9ZwN2nCgkgXHxw5n+s7kDpgUCHqmFfT+8S/zeP/fl7e33voio614hLHpwyl+Ph+hys+mz5eStXtz3zBWU3mRMWsCM269Co71wQsSyIXKa9LQZ2bNyG7nlh+iWLH3bo7WhjB4xkiHTRw24S28gqa8oomHpHxjRtRqlICFKAvv9ZhB+2TNEJw85Z/OwW+wsf+19qnJX4cnQVhCVMZ3LHvkFBt+BUyYVRZG3ilfzUrMfVvRosHNfcCu/ypp7VqEzh9XC5y/fx57QaFYnzqC7N0SnxMUkbQ23xUQzK2pUvwdq8dZ8lq/9ARNWECXiHAF0Nxzs6x4qCDqS/AQSIxswXPECScPObYKYjMxAIrrcrHl/MQUbvkISPWHhAH0Al0ZsY2PSFF5NvopyyZMPMV5dyevZ4/tK6cET3jywaif7CnNpcxv7tgc7tMQ1NBI0P5MJV999VnPrbulk2ceLKTN5GlwGK325/IoriB6ScLaXe1yqi/dj+uYhshx5gKezetfUPzP0oisHdJyTIYoiOxavZe93Xxx91ij0JI+ex+w7r0XnPTAq2wOJbIicIaJbpHhzLrv37KHK3Ai9vQa80JIdl8WYOZPwj/zpUryDRXXxftqX/4ERps0AuCQF+4PmE3vF0+dUhKuuuIrlr/0dc0cJ4JFyHr3gFiYsnDWg4ZrDXTXcn3+A3N6uvkOUNfx9yBAyAhPP6nz7Vv6b7j+/yP5pI1g2bjYl+qP19TFCM9cFu7gteRIBOo+hYu028/1HSzjUXgaAj6QnySuMqoPrj65SBD1p/i78MoIZdsvf8PUf2HJnGZnBpmRnPqvffgNHb7hDpfTlorAanJH+fDP+Wv7tTMeFGi/M/DbSwm0pM/p+502ltexcu43CljIcveWjSklBfLdAUkEuXX4tjHntQ4Ijz86bcGDlTlbtXI8NB4IkMC4umxk3zh9QL4jFZCTvs98xsv5TNIIbm6TmQPztjLj+D2h15+bFL4oi+3/Yyo7Fn/b9HRC0xGfPZM7dN+Id4HNO5nE2XDCGyF//+le++eYbiouL0ev1TJgwgeeee460tNNz25+P8t22qiZ2rd5KfkMJtt46dUESSPKJZuzEcSSNzTivCUAnoyxvK+aVz5Bt3Q14uv3uD7uS5CufOqdZ3NsWrWb3tx8hujwrIK+AVOY/+AAxGfEDNoYoirxetIpXWgKwo0OLjQdC2nko8+Kz8o50ttay/eGfk7i3geLhMSy6cjbbgif1lW7rsDLH0MidCRmMDPUYKkWbcvl+w0pM2ECC7JBUdAqB4q3f9TX2Uii8SAl0EzprJqMvu1Pu7CtzwdPdbuSb5/5Oe/UuPKXrapL9VcTEddI84x7+ZtNQInrC12PUVbyRPYZYn0jcTjf56/eyd/9e6nor6wB8JB2JDR0k7N8C9i7a7riE6Q88d1bP0Z5WI8s+/prDPZ6k8UCFD5cvuJzY7IELj0iiSO7az4jY/jTheK4jTz+WkGteJzIhfcDGORUH1+9hy2cfYeup6t2iIipjKhf/8mb8wy7chfERLhhD5OKLL+a6665j9OjRuFwunnzySfLz8yksLMTL69Qu+/MpaOa0OchdvZt9+ftp6l3lAgQofBiRNoxRF09A73dhNkQr3rUa97o/kuXwJJJaJC15UdeRufD3+AWGnOLogcHSY+G7l9+hrnAdR9p9x2XP5pIHb0XndXoJaKdDaWcV9+XncdDt8Y4MU1bz5tAcUgLizvhcoiiy+b0/4vv3L9E7oCVUx4rHbmCtzzDqflQSnKWs5aZwPdclTkY0OVn+0RIKOz0iRn6CF3OnX0zZgQOU7liOJHpCfiqlDzEhaobfeT8JWec2j0dG5nQQRZE17y6iYMPivvvWVxfIkJgWvObez3IfkX+0h+FEgwELvw7v4c60WXQ3dbFr5RYO1hRi7tX6ECSI04fj21RK+sqVCEg0ROmIe/lVkrPPLrE+b/VuVm5fi7XXCzImZiizbroUlXbgvCD1FUW0LXqQbKsnF6aREJomPE3OzBvO2SKiZGc+Gz76sM+zDErCkiYw5+5bBqzv17nggjFE/pPW1lZCQ0PZtGkTU6ZMOeX+F4KyKkDtwQp2bdxOcXtFX/8CtaQkPTiJcTMmDHhm9kAgiSKHti5Fu/kvpLo8XS+7MVAQfwvDrvoNXj7+52QelXmlrHjzDazGCgCU6gDGX30bYxdMG7Ax3KKbVwtX8nprEHZ06LDycGgn92ecXfladdFuSh++h+iqXu2WsVG4fvs4n7X3sM0R16fq6kc3l/u2c2fyKKz7W1mxaZXnQSzByIhMJl8+g3UfLqIqd02fMq1a5UdEfDhzH//deWluKCNzPIp27GfNP97CafdUwygVPqSFO4m67DoUQ7O5v7CYIrfHqzpKVcVrQ0YgFnWza/suynvq+jrZ6tAwLCqdkDAR6/N/JKTNiQhUXTKMWc9+gEZ/5iENc3s3yz5aTEm3R8snQOHN5ZcuIG74ycv4zwSb1cyBz59hePX76AQnDknJvuibyLnhT+i9zk34ozKvlLXvftBXiQgCQTGjmXP3rUQkn1tdkoHggjVEysrKSElJIT8/nyFDjk2mtNvt2O1HRWy6u7uJiYk574bIESxdJvau2Mb+w/l0iaa+7RHqIEbljCB75pgBtc4HgiNuRv+dz5Mgen7IHfhSmvILcq781Tlpcy+KIps/Xc7+FZ8huT3fm2/IEC556D4ikgeuQqmoo4L7DhVQ0PvAHK6q5vWhw0nxP3P1U6fDxpo/3k3c4l0oJOjwV+L17JMEjruIt8t2s6TLnw78AY+S6zhNNTcGBeBYVU1JVyUA/gpvLpt3KcEJ4Sx75W2aD+/gSGM9jTqAuNGjufT+++Rwjcx5o7Olla//+BzdraV4PJdKwv38SblkCiPm3cxLRat4oy0UJxr0WHk4sJ3sYg25JQfp/NEzMFwdyKhhI8iamsPGVx4m+outqETo9FWg+cOjjJp/61nNL3/tXn7YugYrdgQJRkUNYfbNl6HWDVx1yMGNiwnc9CTRkqcC7pA2B58rXyMuLWfAxjgZdcVVrP7XuW1Idy64IA0RSZJYsGABnZ2dbNmy5bj7PP300zzzzDPHbL9QDJEjiKJI6fYC9uzYRYWpvm81oEfDsOh0xsyZTFDMuQmBnApRFGmuLqT20C7q8zYz0rGNWIUn7tkkBpBbHEtocespzjIw2NR6CuKH0a1qx/ODUxHo9iFI34gqLhrvpFRC0rOJyRyLt9+JO3KeDLfo5qWCFbzRFoIDLXqs/CrMyD3ps8/KO5K3/it6nnyWoE4XogDVV4xi5h/eRlKq+LpqGx83dpPnOhoGihBametuwmt3DU67E0GCkZFDmHPzZfR0GvnmuVcwNhVwpLGeVhfGzPvuJX30iLO6XhmZs+W7N96ibNsmxF4hLL02mNQpOUz7+X2UdFdz/6HCPqM+W6jg6rJ2mmqbcPVKBqgkJenBCYydOoGYoYk0lB8k/4E7iC33qIxWjAhnwqsfERB65gsBS6eJ7z5cTJGxv1GfOOrsZAFEUaSt/jC1BbvpOlyAraIcaurxaujC13x+6zVEAdp9BDq8lVh8/AgeMZrkyVOJyRyLb+B/TyjmP7kgDZF7772X77//nq1btxIdffxV8IXuETkenfVt7Fq5lYO1RX29EAQJEryiGD1uNGkTh6FQDv6Kt6erhZqCnbQW52GpKEOqqUPX0EFgiw3dj3pDuRQCTSNDGBpfTbjS06J7Z086ys0OvHtsgz5PgKaAKPJjI3HSqz0iBTOmtBBvW0/fPp2+CrrDfHDFhKKOi8MvJYOIjFFEJeeclpx6QUcZ9x0q6nMnj1RV8cawUST4nbkHprujic2P3kLS9hoA6mINpLzyBvFZ4wHIayvl7YpDrDCHY8XjetZgZ4ytkPjKarxb+ruTqwsPs+LV1zEbq/GsQtVEpI3huqd+PeC9e2Rk/pPm2iq+e/Y5jEZPwqdC4UV0RhaX/+ZxFCpV/zCnZOXS1l0EFnUi9JYTBii8GZ7qyZMz+HsDsPnDv2J49d942SRsaui8dyFT73zmrIz/Qxv288OmVZ7nqQQjI7K4+JYFJ1VVPYLJ2E5t0W5ai3MxVZQiVtehq28noNWKwX7Kwy84jN4KjGFeOKNDUcfH4pucQXjGSKJTR6DWXNhdwC84Q+T+++/n22+/ZfPmzSQknH6N94WSI3I6uBxO8tftZe+B/dQ7jnoY/AQvhicPZfTcCWcs1vOfOB026g8foKloP8bDhTira1DXteDbbMK/RzzhcW4BOgLVmCL8EGPC0CUk4Z2Qir18MxM7l6ESRLokb/Yn/ILE0Refk1CBKIrs/GoLDcVbATcIesKcClIr8/GxnPiWdCqhI0iDJdIfKSYCfWIyQanDiM4cTVBE/3vLJbp44dAK3vpRgt1j4T3clXZ25cTHPGzvuYqpd/2x71xGew8fl23l0zaoEo8KosW7KsluKSa8wsbY8Gxm3XQJap2GbUuWsu/rxThdHoNMpQlhzr0PkT4u+4znJiNzKiRRZPW//k7x5t24ejU9DD5xLHz6CUKioyjtrOLe/IPkuz0ejDRnCRMOFaLtFnorB6MYPX4sKeOz+u757o4mNv/qFpJ2HN9IPxMsXSaWf/gNhV2efDI/wYvL5l5K0pj+lSoup4OG8jwai/ZhPFyIo6oKVV0Lvk0mArrdJzy/KECHv4rOAAUKbwtaHycKbz2ai+4jNuPcJJBbuk1s+WwJxuZCAASlntSx0wgOV9N9uAhXdQ3q+lb8ms34mU78THcpoCNIjTnCDyk6Al1iEoGpQ4jOGktQROIFUdl5wRgikiRx//33s2TJEjZu3EhKypklF/03GSI/pqGomt3rt1PQUo5TOFpDnxYQz7hpE09aaiaKIh1NldQV7Ka9NB9bZTlCTSNejV0EtjtRnfjepNtLwBjmjSMqGFWv9RyWMYKYlJEnTBIry9uKsOx+ktyeH/9B3SiCr3uLyPiBVUY9EaW7C1jxxkt9Ij3B8eOZdedC2mrzaS85iKW8DGobMDR2EdhqR3Pi5wwmvUBXmAF7ZBDK+Fh8ktIISx9OV3gQj5bV9ZUcjlZX8WZvyeGZUl+Wy6EH7zyp+1kURTY2HuC96mo22WNw4ckb8pJ6GNmTR3aVmZumLiQ2OwlTTzff/O4pWpuqOCIGF5o8gWufeuSCUkmU+e+moaqE9c+/SHN7C+BGELQkT5jDZQ/ciVt083rhSl5tCcIu6NBINma1bCa62IwXOrJjMxh78ST8I/uHS08UttRozzwhtWhTLss3rMTcWwo/IjyTsfOG01R+gPbSfKwV5Qg1DRgaOwloc5zyOdAZZsARGYwyPqb3OTgcUVCi/O4BktyecM/uwEvJuvWNc5a4v23RanYv+QDR7Xl2BMeN44pf34dv8PHHN7Y3Ulu4i9biPKyVZUjV9egbOglstaF1nXgci1agM0yPLTIIZWw0XslphKbnEJMxGi+fc1f2e8EYIvfccw+fffYZS5cu7acd4ufnh15/6hLO/1ZD5Ai2Hiv7Vm5nf1Ee7WJ33/YwVQA5GUPwC3fSXnEQU3kJ7uo6tPVtBLRY8bKd+E/iUEF7iBZrRADERuKVlEJQajYxWWPwD446q3k6HXb2fv4MIyr+hVZwYpG0HEx/kNFXP35O2ljbzFYW/+1Nmko3AqDUBDLnrkfImJTTbz+X00FjZT6NhXvp+tFKyKeph0DjSVZCQGuQim9uv4Rv4q/EJagxSGYe9Knl3uELz7gvg8vpYM1f7+2XkKd9+teMnHfLMfs2mJp5t2wXizq9aMUjaiZIIhnOIuaYrDw472fo9Hq2LPqU/GWrsTraPd+BKpCZdz7IkItGntHcZGR+jOh2s+G95ynZUoTV4fG8afSRXPXkk0SmxJFfW8RDJQUUKD3Ch8nOUiYXFJBoC2XU8JEMnT7yGJGwI4ncsYt3ofxRInfOrOvPeH7dbe0seet1mpoO4mUy4t9jJsTkJLDNhrf1FJ7RYA2WCH+kmEj0SckEpQ4lJnMsgeH9S/dFt5vdX/2N4cWvoBWcdOJL1YS/Mnz2jWc837Ohra6Fb59/FWPzQcBTOTjlxl8y4uKzU112u100VxVSX7ibrsOF2KuqUNY24dPUTUCnm5P5Qjr8lPSE++CKDkWTkIB/SibWiDBiU0eQ4D+wlTkXjCEiCMJxt3/wwQf8/Oc/P+Xx/+2GyBFEUaRyTzHbN26h0tLU12dBL6oZVtlC7L51KMSjL1IR6PJX0hPmgysmrO+GicwYRUTiUJTKwTEOakpzMS26l0znIQBKVOnornqLuIxz8zLc+8MWtnzyVu+KQUH88HksePSO0zIUTMZ26or30FJyAFNZKWJNHbr6DgJaLP1iw2VDIvnbHXdTrvV450Ybd/GznetJnDCT7FnXo9V7n/Z8C7Yupf03vz+tEkWX6GJJ1XY+rGtnn/toCClCbOBBP4mbR8zF2N7M6j//gfqmdiTJDggEx4/j6t89jMHnwpNwlrmwqS7J5cBbL1LRbO29n5TEZs/gqt/ch8Ni529rP+FD3yxsggGNZGdW6xbmt0UyfsZkItKP/1L6z9L28rHRTH75Y/yCIo67//ForS8j/7uPMK3ZQPThdvSOE+/b6aukO8wbV0womvh4/FIyCU8fcdq5Yq0NVTR+fBvDbPsAyNONJurn7xMcfuYJtGeKKIqs/3AJB9d83iuPLxCZPo0rHrt70CTZrZZuagt301J8gJ6KUtxVNWjr2wlotpx0gVsWreXStbkDOpcLxhD5qfy3GyJut4vCLUupWbUE3e4CIutt2H2CqMqZxOFwH8xKTxapn1tLAlYCk70IzcghNnMsBm//8zJn0e1mz+KXySp4CW/B6qmnj7udkT97Fo128JOjupo7WPSnF/pq6bXesVz+2K+JTo8/q/MdyZavK9xDZ+khbBXliA3NrJ0xnq+TF+IW1AS62/jtojfI2lFCU2YouimTGHLpzYTGnDo8ZTK2s/HXt5C0ySNodjqiTUUdFbyyfyvrFImYBY/hkylW8GxmEhPChrL533+ndP1+um0e74hC6cfkn93NqPmTz+o7kPnfwumws/2DP1C+o4FOq8cLolQHc+kjjxM/LJWNS9fwqr6ePXrPAiPZVc4DJonLZs4/YbdbURTZ9O4z+L3xFXoHWLTQ88ANTL3996ecjyiKlOxaQeWKr1HvPEhkjaXfqt2qgfYgLfaYYBRx0XgnpRGSNuwnVc8BHFj1EQk7nsAfEzZJTV7mY4y5+rFzkgNXX1LNspdfxdJ1GAC1LpzZdz1A+oRhgz72iWhvrKS2cBfNxblUFRxA09hNVKuJiA4Xe4cEcNMXm0+7o/npIBsi55Hujibyvv8Y44Z1hOTV9isNE4GGOC9cY4cRM+sq2mqU7Di8F3tvL4ZobQiz5108oHLFZ0tzXTmNn95DjnUnAFWKWOzzXiNt1PRBH1sURTZ8+C25qz8ByQGChuxZP2P6rVcMaBLWhoptPFzVQ5MQjiC5ubpsCb94/RtULs/frD5aj2PcMOIuvoL08fNP6ona9vnLaJ5/F2+rhF3FaclYV1ZW8lT+SjZ6j8QpeFZ309VlPDNkDF6dFva+9kfKm12IvSqX/pEjuPrJR04YU5aROXxgM7WfvEhegwGxV+cjNHEiV//+Icp2FbGoZA3fpOTQqghDkNxc4z7EC9OuR6M6sXfhx+0PAGoTvMl47Z/EpJ7YU2oytnNw5Sd0rFtN0IGqY5Lpq0OVVMYEoY4fyXW/+gPegX4DcPUeeowdFH9wD6O7VgBQpkxCffW7xKUPfom8y+VixRufUrrzW5CcgJKEkfO55MGfn/ecL5fo4p2Sdfy9SUMHHjHFZEU9T8T4MdEv6Yy8WqeDbIicYyoPbad0+WdI2/cSVWbsl1Bq0UJTVjiGiyYz5JKbCYnq34TO3NHN+q9WcqCxyBOykSDdP55ZV80lKDaM84kkiuxb8R6Je/5IIN2IksDusGsYdvMLGLwH7sFxIupLqlny/HPYTZ6MfN/QIVz95GP4hw9cAzmjvYcHD6xhpdXTMC/FdZh7Pn2bnJ31/ffzVtA2PI6A6TPJnnfzcVdqTdWF5D5wO3ElXQBUDg0+ZWMvt8vNokVf8W8/C/t6V6hqycFC3zp+kz6F4k9epmpXLW0WT6m1oDAwesGtTL5u7kBcvsz/E6zmHvZ/8Bh1uUbqekyAhKD0Ydot9xMcEc6K71ewJcXO+sApuAUVQVI7ryR6Mzt+7EnPu2/lv7H94TkCjW7cAtReO4FZT/7juGGR2tJ9FC//FNfWnUSWdPZLKLWroTrRn8qQQLpCklFrgpk14iLGLDi1wvaZULxrNb4r7yNSakaUBHZF3czIW54/J97csn1FrHjzNRxmTzdgrXcclzzwEPHZA6cAe7Ysq9rOX6qNfdV8IbTzSKTEzSnTzqo31+kgGyKDjMNq4eD6L2la8z2+e0sJaXP2+7w1WE336FTCZ85n2PRrT0vWuK2qidXfrKC0V8ZYKSkYEZXJtGsu7qvVP190tTVx+N/3M9q4GoAGIZT2ac8zdMoVgz62y+Vi2cvvUbnve0BEUHoz+fp7GH3pwD7APixdyzP1BqwYPGW+vvWk7crFtnkr4YUt/eLYTiU0pASgmDSGtPk3EJcxpu8zt9vF2hcfJuLjtajdHgNGePJ+xl5x8lbnVftLeX/H12xMSaJU7QkJeWPizuAu5jsMtHz6MnlNPrh7M+59gjO54vFH/qt6T8gMDoe2LsP+3Ytsr4vF4eoCwDdsGLN/cQc71m7moLOSbTkZlKg9ZbBT1OW8NXI6wfoTtxhwWC2s+cMdxC87gAJPsnfAX/7I0IuO/uadDhsFm5ZQv3ophj3FhDf1F+poD1DSNTKZwCmzqK3XUmT0vKBDVf4svO4aQpPPvGrtRDgddvZ+/BvG1H6AUpBoJITOi98gc9zFAzbGiXDY7Cx96V1qDq4CRBA0ZE5ZyJw7rz3vukB7Wgr5Q8lh9veKLnph5ragDh7KmImXeuB6fh0P2RAZBFrryzi0/GMsm7YQXtDULwHSpYD6ZD+EiaNJnX89CUPOLhsaoPrAYVatWEWDow0AHWompI1iwlXTB7TF9dlwcMPXhG76TV9Hyj1+F5N68+v4BQ2+56ZoWy6r/vkK7t6qkvDkKVz1xP0D3kDvzoP5FIueRL2L9RW8NnwWOlEgb83ntKxdgd/ewwR39K+daw7VYB6dTsTsSxk6bSFqjY7i3atoeuzXhDV7LJjy2RnM+NuH6A0nvo+tRjNL3vuKHf71bI0dTqPSUwUVLrTyYKiL5FVf0FDgpK6nB5BA0DJk+rXMumPhBaEbIHNuMXa2UfTh/XSVWinoAHCBoGXYzBtwiLC/voCWeIEVcVMxCT5osfF4uJG7T6GjU5G/lYqHHyCqzgpA+eQEpr74Md5+wXS21HBw+cf0bNxIWH5Dv8oWUYD6BB/ECcNJmnsNScOn0VBYzeJvFvfJwY+MGMLcny8Y0FYYtYfzsH55R19PrT1+s0m79Z/4+g+c5/REHNq0j3XvvYGrt9uwd1A6Cx59mPDEs6tgHCiquut5unAXqyzxSIICJS6u9K7h91lTCDWcfd7NmSAbIgOAKIqU7F5F1Q+LUO06SGS1uV+CVbeXQGt2LP7TZzBs3k0DKsUriiIF6/ezbvvGvp42foIX08ZNYdis0ef1pWPu6SL/40cZ0/I1CkGiHT+qxjzDiItvGfQkMEuPha///CqtldsBUGlDmHvfr0gdc2zforPF4Xby+7zlfNwVhyQoiBRaeDM9gvHhQwHP36Yifwtly79A2L6PqIoelD/6BZl1As1DI/CaehEp067gwCtPkbSmGICmcC2RLzxP2ujZJ53D7qWbWXVgIzVpWjaHjcUo+AOQrqjldncDmT98xrbGaJwujyiV3jeRSx95hJiM+AH7HmQubA6s+gifjS+xrj4Hk92TkKr1jidx1DQONhdjVjgoHB7ONm+PsFiCopF/ZSUzNPjEYQJRFNnw5hME/WspWqfnXrY+cgsRQ8dQ9v0XKLYfILLy2Pu9aVgkPlOnMuySm/v0dERRZOuXa9hUvAu3IKJHy4Lp80ifMnBifZIosnvxKww99BwGwU43Xhwe/UdGzr9jwMY4EZZuM0uee5Omss2AJ2Q6Yv5NTLlh/nl9PnfZuvlrwTo+747EgRaAi7QVPJ2eQ0Zg4jmdi2yInCXmng7yVngSrAIPVBLQ3T/BqiFKh33sEGLmXEnmpEsHrYz2CG6nmx1LNrKtcBdWPCvrcHUgs+fMJnFU+imOHlyK96xFv+Ih4kSPTPQBwwSifvYWoVGnr5x7tuxYso4dX73d26pcSfKYBVz64C0D6gZdVbubR8rMtBOAEhf3BTXy6yHzjomndrXVc3D5x3RvXE9YXv2xK8R4bzoSg/AuqCGxScKphOZbZjHjVy+f9P5pKWvg6y++opEOyrMC2eY3DrvgiXNPUJZxc/4iOChR3mXH07dGRcrYBcx74KYz1kWR+e+hramGmn/fi73Wyo4WfyTJBigJSZhCm9ZNt2DBGiixNnM09UqPgN813hU8N3wuetWJvYftjZXseujnJOS14FBAfqYW78BwgvPrCOrsr9HTHKbBPCaDqNkLyLroimOkxrtbOvnmg6+osnqayMXpI7jq1mvwDR24btPtzXXUfnQHOZYdgKdRXchN7xMWPfiJ/ru/28i2L95B7F0IBESN5MpfPzCguWtnit3l4B/Fa/lHqzdGPO/KTGUtf0iO5qLI4edlTrIhcgbUHT5A0Xef4Nq2k8iSDjQ/8rrb1dCQEYx28kQyL7mRiISBW3mfCdZuMxu/WsXe2kO4BY9xlOwdw+wr5xKaOHBx1jPFbrOw/9PfM7LmAzSCmx5JT+GQxxh95UMolIMbG22ra2HxX17A1F4EgM43gSsff3xAu/m2WNr55YHNbHN4jKuRqireHj6eaO/jh6JcTgcFm7+lbtW36PcUEtH4HzFzH2j2B60TpAA/xrz6AWFxGScc32V3suqjpeypP4TDW6Q4M4Yd+pF9rtZZzn3cve1j9pUnYnN6klk1hkjm/PJBUsdkDcyXIHNBIIkie7/9O3EHXmVl3URaLV2ApyxXHZVFq96MhERTujc/hF6EU9DgRzfPJSi5PH7iSc+9e9k7dL3wCiathNINsW3060/lUEJDWgCqSeNIv+RnJ62WKd6Sx7J1P2DBjlJScFH6WCZde3YtFU5E3voviN78a4Iw4pBU7E99kDHXPTnoz5yu5g6+ee41Ous9miQKlS8TrvkFYxdMG9RxT4Yoiiyq3MLztXbqpVDA03jz1zFqrk2Ycl69M7IhcgqKdq+i5KnHMKtFhpW5Uf3oG+jwV9I5MomQmXMZNueGk8b0zzWd9W2sWfQDhZ0VIIBCEhgWlsaMa+biEzz4VSwnorJwD85v7umL0RZohuJ7zT+ISR46qOOKosjqf31FwYYvOBIfH3nJz5l646UDOsbfi1byUksQDrSn/XAHjxx84REjt7i9v5GrgupQsI7N4sqnPj5pQvOPH+62QIHczAxylakA6LFwTfsyJm0qpbQVT7kzCmKGzGLBr+5Ea9D+xG9A5nxTX1FE55d3o2yzsqoxqS9hWeObRXu4DpQCkhb2jUplryoTgFGqKv55EqMZoKZkLxufvpuIGjPR7f0/6/JR0D48nsAZsxl28Y14+518te9yOFn5wVL2NhwCwdMY76orryJ6yMB5SK3mHg6+fx9j278FoFIRh3TlOyQOOXnlz09FFEW2fL6Cfcs/6vXCQljSZC7/9T14+/sM6tgnY2tjHk8fruZQb28gH3q4O6Sb+9JnoT1JOfa5QjZETsHnj11OznclAHR6QUW0Cq+h2Qy54laShk+74BP/6g5Vsnr5SmpszQBoUDEuaQSTF848rQ6Vg4Hb5WLPV39lWMnfMQh2bJKa3KRfMur635+WAuJPoTq/nGUvP4/D4im59Y8cztW/exTfoIEzzg60lXD3oQqqJU/52+m4u3+MuaeDgys/pX39agL2VRD4o7Cf0QCts3IYc89TJ/SQ9LQaWfzBF1RZPO5uRbw/K+NTqJA8SXFBUht31n6Gdp0Ts93jHVFpgpl2670Mm35uGnrJDCxul4s9X/6ZrOI3WdM8jUqjFRARFF44QtOwBShAAl1yCP+OzqCdQJS4uD+oiceGzD1uWaYoiuRv+JrKt18j6VBHn9SACDTEGnCOG0bC3IWkjZ172s/BlooGvv7sK1p6K3aGBCVz6W0L0XoNXMns4QOb0X53N7Gi5ze+M+w6cn7+Mjq914CNcTyaKxr49sVX+jyvKm0w02+9j6HTRg3quCejtLOKPxTtZ4Pdk/OhxsG1vvU8kTWNQJ3/eZvXfyIbIqegomAb2566l5QqB369gmNOJdSMiSXh9nvImrRgwMYaTIo257J24/q+Pjbe6Jk6ciIj5k1AoTw/xlRDZTHtX/ySofb9gEdMSFjwBknDzr6S6HRw2B18+8K/qM1fBUgoVL5Mu+V+cmafeRfQE2F2WnnswAq+MXseAImKBt7OSjlpAuDxEEWRgm3LyH3zTyQdNhPgUcvGpYDqUVHE3nY3Q6ZcecyLQBRFtn61lk1FO3sTADUoLkrgI8Jow9PMKsFdwQ2FP+DcbkSSPFUPoYmTuOLX9+IdcP5WbzJnRsWhXbi+vQ+vHhNL6kdh7w29oY3DFBOCpIYoQwiF44P4wpl63MTqH2O1dLPz3y8iLlpOZG81DEBVKBjHZTD9gb8RGp16xvPcvXQza/Zvwim40aJi7vhZ5MwZOA+F2+VizydPMbLyn6gFNy0E0jz9VYZOGdxntOhys/qdryjYtKjPyxg7dDaXPfKL8+ZlbLV28OdDG/na5GmkKUgiM/WVPJM5hkS/ge0TMxDIhshp4rBa2P7Zizi/XEp0jaVve128F5prLmf89Y+clgbI+cTtcrP3u61sztuOGU9OQojSj5nTZ5I2cXBDIydCEkX2LnuL1Ny/4IcZl6RgT9SNDL/xr+gMg6uJkr9hL2vfexXR2QVAVMZMrvzNL9HoBu7h8XXFFn5bDT30lkSGdXF3+uyz8qTt/u5dKt56GX+TRFzr0e310XqU11zKhJseO6b/Td2hyn4lkUMj08gfpecjYyhWPPfrKPtepm7di3DYo92gUPoy/po7GHf54Cvjypw9dpuF/Z88yYjqj9jaMZHcNhXgBDS4gtOxBqkJUvmRNnkof1bY+zpKz9VX8OrwWfhp+xubjZWH2P/2Xwlec6BP5dmhhPIIsAV5M+vlz48RWTwdrEYz3773FSW9ukeRmiCuuuk6gmJCftL1/5iGymKMn91KhrMQgP3eU0i69d1Blwuozi9n+WuvYOupAkBjiGLuvQ+RPOrE+VyDidVl5bXCdbzT7o8Zz7MgR1XN06lJjAs7P3mLp4NsiJwF+ZuWUP3BW8TtrutzV3b5KOi8eDSj7nrirFYL5xK72cbmRWvYXZmLU/BkucfrI5izYN4JG1gNNm1NNdR8ch8jTJsAqBUi6Zn9MpnjB1cV1NTZw6I/vUxH3R7A0+fhkoceI3H4qXvHnC41PQ3cmbuH3F6hoIu0Fbw5fNpJRaJORFdbPVsfuQVtWT09BkhqpE+VsttLoG32CEbc+Zt+ydJ2s43l7y8mv93TyyJE5c/UK2fypqmUpeZY3KgQJDfTTFsYsmo/2jZPiad/xHCuePxBAiPOjZaAzOlTvGs1+lUP42fvYVHdVLptnr8Z6jAsUTFo9Vouyp5AQYaDZxu9+sT3no6ycXPqUQNTFEUOrvuS+g/fIW5/Y1+5bYc3NAZCeAfYbr6M6ff99ayM54q9JXz7/VK6JQuCJDA+fjgzbpqPcoCq1jwLmX+QceBZvAUrJklP0fDfM+qyXw6qRIDL4eS71z6kYu/3gAtQkTr+cubed+N5qUQTRZF/l23gpXqJFjy/11ihid/GebMgbsIFn0IgGyI/gZbaEvb+668ErNzT1x/BpYDqMdHE3XpPP2XBC5Hu5k7WLlpBfuthJEFCkASygpOYdfU8/MIDz8ucDqz+hKjtvycUz4N1V9ACMm56ZdAFh7Z8sYI9S99HEq2AivTJC5l7zw0D9gN2i27+nP89b3dE4kZFCO28luLH9Oizix9vfO9ZfF7/HLcgURUGUR0CgT2en6dLATUjIom+9S6GTjsqYJa3ahc/7FiDHRdqScnM4RfhNSmCp0sOsbW32kcr2ZjVvIGUlbtR2ZwICj05F9/I1JsuveAfZv8LmLo7Kfj4EUa3LmG/MYfNzaG9SZEKRL90HGHejEnKIWfBeB4t3swqm6dENUNZy7+GDiMlwGMMWy3d7PjoeaSvvyey3tZ3/ooIBS5BJKkBmmIMJL78GolDJ53xPEW3yPpPfmBbxT4kQcIbPVfMW0DSmIGTEjC2N1P+wS/6Fi9F6kz8bviAyITBlSso3nGQ1f98HaetCQCDXxKXPvLwWTfb/KmsqdvLs+XNlIqeHLAAurg/zMad6TMHtDHdYCIbIgOAw2phx+cv4/jq276W1wB1sQbU1y5gwg2PXtBhm6bSWlZ9u4JKi6dRlUpSMiY+mylXz0LnPbjSvsfD2NlG8b8fZmzHMgCaCaQ0/ddkTlyI3kePzscwKHktLdVNLP7Lc31dMA0BqSx84tcDKo2+pTGX+0taaZJCECSR2wNqeTp7/lk9MOrLcjn00F3ElnXjBvZlGwjvFoitPHoPNkTpEK6+hPE3P4be4EtHXStff/xlnxpvqm8cV9x+DTt6inimvKnPfe8vdTLj8FriNx5EIUp4Baax4FcPD2jJs8yZkbf+K8I2/xZ/dzeL62fTZPZoU6D0wx6eTFpCGjOvvpgCqY57S5pp7L3HbvWv4ens+WiUahrKD3Lg7b8Ruia3T8fGoYLD2cGomztIrRMRBai+cjQzn/onGu2ZP7e6GtpY9NGX1PcqiKb4xHDFbddiCBi4UGv+5qWErX+IUDpwSkr2Jt7NmJ/9EeUgeCPsLgeddiPNXW1s/no53SV7UFrtqK0qsmfdMOANNk+XQ+1lPFWUz3Zn7yICGzf5N/N41gx8NOe31ceZIhsiA0zB1qVUvvcWsbtrUPe6zI3eCjrmjGLknb85qRbE+ebwjgLWrFvTl9FuQMvkoeMYs2DKGbtSnTYH1m4ztm4rVpMFq8mK3WzBZrFhs9qw2+3YbDbsDjt2pwO7y47D5cQhOrGLThySC73YwkJhJXGKFgBWimPZJYxBQoUaFVpBhUahRqNUo1Vp0Kg0aDUatBodOq0WnV6HVq9Dp9eh99Kj8zag8zFg8DWg8/VCqT5+pcAPb3xCybZvABeCQs+YK+5g0jVzfurX20eXrZv7D6xhTe9qNUtZy7+yc0g6iyQyt9vFmr/dT9SnG1GJnnut5ebZKA4WE7Ozqq8MuMcg0DprOMPv+g1hsZms+/f37Kg6gCRI+Ah6rpi/gPgRqXxavpEX69w044nfR7nrmLZ/BeH7qhAELSPm3cK0m/87ErT/v2AxGcl//z7Gdiyj1JTMDw3puN0eI0QyJBOUnMbFCy8hNCWSvx36gbfaI3CjIohOXkn2ZmbUSHLXfEbjR+8Rd6DpaPjFT4lx3nisxjbSfyhGAbQFqvD90+/Jnn7NWc01f+1elm9dhR0nKknJzJzJjFkwcBoVNquZ3A8eZlzLlwDUKKKwX/Y2KTmTj9lXFEUsLhtdjh667D10Ocx0OSwYnTaMTgc9LifdLhc9LpEeN/S4wSwqMYsqzJIas6TFgq5PdfQ/ESQRg2DFgA0vhQMvwYWXwo23QsRHCT4qAV+lEl+VCl+1Bl+1Fj+NHn+NAX+NNwFaH/y1Pme8CGk0t/DHQ1tZZjkSVhWZ71XJHzInEuPz39lPSjZEBonW+jL2vvNX/L/f2T9sc5JKhwsB0S1yYOUONu7dSk9vJUWA4E1WRApeQb7YbDZsNjt2uw27w4HdacfhcmB3O3G4nTgkjxFxREztJyO5GCIe4grFRpSCRJUYxlfMw6Lw/8mnVkkKNIIajUKNVqFGo1KjVWnRqjW4THaairYhOo/0hRjGrFtvJjY7acD6+LxXspY/NXhhRY8XZv4Y4+BnyWcneFS0cwXNj//maL+aGankPPJHDn32Jj7LtxNo9FjFbgGqh4cT+fM78PYbzrKV39EjWREkgQkJI5h+4zycuHjl0Ere6wjEJHgSGtPsRUzZvAL/8g4CokZyze8flStrzgFledvQLP0F0a4GvmueRVmXHU+zND3q8BzmXns5KeOzqO1p4q7cXX0NyyZpKnkpLYeyL99B+HoFEY1Hwy81Kb54X38tQSlDqP/N432hmfJJ8Vz04kf4+Iee8TwdFhvL3/+Gg20efaBgpR8Lr7ua8JSB8aB12LpYm7+OluLlSCqRbpU39fo4pOAETJICk1uBWVT0GhBqzJIOC3rcDJyHRCtZUeHGhg63MHDn1dFrzAgOvAQH3go33koRL4XUz5gxKAWKuhrYZgujgUgQlIxVV/J0eibDgwcup+18IBsig4zDbmHnl69h+/wbYipNfdtPVulwPnDaHDSX1dNUWU9LUwut7W04zXZaFEYcgmdZHer2o0thwiG4T3G2o6glJZojnguFBq1KjUalQafRerwXWh06nRatXo/eoEfrpUPvbUDno0fv44Xe14BKq6ZwxwqCVt1LGO04JSXbwm8ndvTtOCx2rBYrdmuvp8Vmw2a3Y7cf8bQ4cLgdvZ4WFw7JefpGklvCu8GEYPLoyKDwwx6RjLe/L0FeAYQEBhMWFU5EYjRB8WFnlYBX1FHBXflFffHd+fpyXh0x56xcqxZTF+ufuI2k1R4dg5YQNSHP/YWUUTPZtegNzJ99RWx5T9/+jZE6XJfNotEeT6XV43WK0oSw8JZrCYgKps3aye92fsv3UhZOQYMguZnasobh329HLfky6xcPM+SiEytnypw9otvN7s+fZcTh1+lyBLKobiK23iaOgjaGURdf7lEhVSr4pmILv6mW6MYXDXbuM5ST+fVSwtbm94Vf7Cqom5hEyh0PkDJyJutefZTQ91egcYFJL+B47A4m3vDIWc21oaiarxd9TYfoubdGhGUy99bLUevOXBPI5DBzsL2cfGMTRSYTZVYFlS4/2jl7yXdBEtEJNrywYRAceCucfZ4Lb6WEj1KBr0qBj0qFn1qDn1qLr1qHssfF/s8W426qRGV24huQxtW/exz/8CAsLisd9u5eT4ulz9PS43RgdDnpcbnpdon0uCVMogKTqOj1tGiw9HpanJy9ZpJachClaCZF6yDNoCbTJ4DsoHgSfKIuyAXuqZANkXNI0Y7vKX/3DY/L/BSVDoOF2+mmtbKBxop6WhqaaO1op93SSZfbjCQc++fVSEqCRF+aFJ1IAugkNQnaSLyCfNDpdGh1WnR6PTqv/uEPvY/eE/4YwJ4uxo5Wyt+/jREmT/OoQ9ocQm/+8Ix71rjsTqzdFqw9Zmw9ntCR3WzrNWisx3h8uhvbsdTvB9HEkaRAc7geFELfOZWSgkCVD0HeAYQGhxIaHU5EcgwBUUGnfDDYXQ5+l/c9nxg9zfOihGb+kRHNmLCzk17fvewd3M++in+PiEsBdddNYtZv30Sl1lC8exVl775O9PYKtL1hG5NeoGJkAoeDknHpA9CiZv6E2Qyb7RE3y609yB8LdrJdOwaAcHcD87Z+TVBRK/HD57Pg0TvknjUDSFtDNY0f/Zyh9v1sbR/HrlZvkOyAiqC4yVz/9L1oDTqsLiuP7V/B171aNXFSLXeu+IBxy4tQ9P6U2wOUmC6ZzNhf/JaA0Fiaq4vY//DtxBd6tEaqMgIY8ep7ZxUyFkWR7V+vZ0PB9j6tmkunziNzas4pj7W57BR0VHCws55iUw+lVqh0edMsBiEJx/+9BElthLjb8NWq8VUJ+CjBWyXgo1Liq1Ljp1Ljp9bir9Hjr/HCT+sJf/hpfI4r2HYy+veoGvjkdfCU2nbauul09GC09xozLhtGh51ul5Nul5sup5NKixmjqMOFCjta2oWQE4aL9FiJVbSTrLWT5qUlyzeIYYEJRHmFXtAGimyInAfaGsrZ8+7f8Fu+g4Buj0VyokqHs0V0i3TUttBYXkdzXROt7a20mTvpcplO6BHQoCJI7UeQbwChIaGExUQQkRKNb2gAVfsPs3T5Mjp7Vz3J3tFcdtNV+IYNXHOq0+FIH42svD9jEOx04U3lhOcYPvvGQR23q6WTRc8+T3dLPgAqbSQBKSPoxkqnq+eE36laUhGo9iXEN5CQkBDCYiKJSI7CJ9T/mL/xD9U7ebTCRgf+qHDyQHAzj2bNO6t7oaOpmh0P30LiAY+ibm2CNxmv/bOv90dnSw273vkLPt9tJbDraNimMMmLw8mpOPySGRaczqW3X4nGoEMSRV5f/Rr/1GTTKQQiSCJT2tYxYvlWvDXRXPmb38qJrANA7roviNvyGFqXky/rZ9Nh8VSPCaoQZtxyN9mzPQJgeW2l3F1QTqXoUe+d07iCh5//DK3NY11Wp/rh+7PrGXPlL/vUird99jKaF97F2yrhUEHzrRcz8+GXzur+6mkzsuT9r6joVSiO04Vz1a3XHvM8cIkuijurONhZR2GPkcNWNxUOLxqkoBOGTXzpJl7ZSZSzjSEtOxneXUxaWy11KfcyZuGvBrUs12a28vVfXqe5bAsAKm0o8x98jOSR5z63b1Xtbh4vN9IkefK15ujKeTFnGgFaX0q7qjnYWUtRj5FSi5tyh4F6KfiE36kPPcQrO0nWukjz0pHlH0p2YAKhhvPXfO/HyIbIecTpsLHzy9exfPF1P5f5f1Y6nAxRFOlu6qDxsMfgaGltoc3USYezG9cJQigqSUGg2pdg70BCgoMJi44kIiUav4jAkz6UnDYHaz9Zzu7afCRBQouaWaOmMmLe+HNubdcezsP2xW2kuMsAT5nvsNveRO81eHkLoiiy/sMl5K3+BCSnp1/N/FuYfP182qqaaKqop7m+idaOVtrMXXS5Tcf1MgHoUBOk8SPYN4iQ0FDC4zxGX4/Wzt0HtrKzNxN+tLqKt3PGE3mSPiAnm++md57G781F6B1g1UD3/dcy5fan+v5eLqeDXV+/Qc9nXxF32Nh3bG2wkvz0GBRRk7jm2p8RlRkPQEHpHv5UtoMN+ikAhLobmbdjMaEFXYy67Dam3DDvjOcpAzaLibz372ds2zcU9aSzsjERsbdPjG/oaG567tfoDHpEUeTNolW80BKIAy0+opFHf/gHU77Pw66GuknJpN3xECkjZ/Sdu6erhU2P/ZykLZWAJyQX+9LLJA8/u3ykkm35LFuzHDN2FJLAlLSxTLp6JpXmBg52VFPQ00mp2UW5U0+dGHTCEIQBC/HKdhK1DtINOrL8gskOjMcfHfkf3M/Y9qUAlCsTUV39HnHpI85qvqdL2b4ivn/9RVy97TDCkiaz8MkH0Hmd28pBo72H3+SuYYnF4+kKopM/xau5IuHkZdQ2l53CzkoOdTZQaOrmsFWiwulN00m8TIF0Ea8ykqxzk+7txVD/MIYFJh0jdjfYyIbIBULxrpWUvfs6MTsqj1vpEJk4lJ42I02ltTTVNtLS0kpbdzsdTiN2XMc9p0ISCFD2hguCQgiLCic8MYqguLCfVP5ak1fO0mVLaXd75OITDJEsuHEh/pHnVnvEYbex78NfMb7xEwCqFdG4Ln9n0CXiawsr+PbF53GYPUqkAZEjPMmbgf3vO5fdSUtFbxissTcMZu3CKJpBON6ZwQstgTo/itIVfOk7AqegwR8jLyRquDTu7CToa4r3UPzwPX05ShUjwpnw6kcEhMb2269071pK332N6G1laHs7qvboIDc9iMipNzHvzl+gUChwOR28texPvO0/hXaFRzxpcts6Ri3fQljICK556lcYfAe3r8f/JyoLdiEsvoNoVx3Lmmb39YlB4cWYy25j8vWeiq0Wcxu/2LmSXQpPCHeoKY/fvfoPFFYzlssuYuwdv8U/OKrfufPWf0X3754luMOFCFRdmsOsP753VnICLoeTVR8tY1tnHuZAFVY/H6yhEdTgTbUYhI3jv7A12IlVtJGksZHmpSHTN5DsgDjifCKPWcCU5W1Fs/TOo31iwn/G8J+/iFY3ePIHoiiy8h+fU7R5EZ5KOQPjr7mL8VfMOOWxA83y6h08UWGhBY+nYr6+nBdyZvykvjAmh4VDnRXkdzZSZDJx2CZQ5fShlRN7Q0JpJ0HdTYoeMrx9GOofQVZgIhpJQHKLAy5HIRsiFxgdTdXsfufPx1Q6HEzx5nDGKCT9sStjQQI/pTdBen9PAmVkGOGJ0YQmRh63RHUgcNmdrPv0B3ZV5yIKEhpUzMiZzOjLJp9z70j+5qWEr3+QEDrPWatvl8PJkuffpqavX40/M25/8LSaxtnNNprL6mmsrKeluYW2rjbarV2YsPXbzxwE6zJG0aD0hDxmmPfwC1ccOWNGnbHR53I6WPPne4j+ahsq0aMErHrqYUZfescx+3a21rL73b9iWLaZ4E7PPSgKUJDsQ9rDT5E9/RIAdu9azputRazymgVAsNjC/F1fE1FkY87dj5AxMeeM5vi/hiSK7PrybwwvfpkOeyCL68Zhd3pCMTqfFK5/9kkCI4I9XpClz/NPn5G0K0NQSi5uPvQ5k9dtJ+DGGxh9+V3HNIt02C2s/ePdxH2zB4XkKdXV//E3jJhzZiFMt+hmT2sR35UVsM0MtapIzMLxV8tKXEQLrSRqrKQZlJ4EysAYkv1iT5mjIbrd7P70aUaUv4mmt09My4xXGTJ5cEvFOxrbWPTsc32N6gwBKSx84vEB1Q46rXnYungsdx3fWz0l/SG089dEA5ec5eLjdOi0GTnYUUF+VzPFJgvldiWVLn+6OH4DUEFyE+5uYoitnH9f+sCAzkU2RC4gzO3dlOwqoPxwGVXt1Yht+0gvrSC1zlOS6VLAvqwAnEMvITI8jdDwMMITIglPjj5vnXTrC6r49psltPbqGsTpw1nws6sIjB64PhKnQ2drI1Uf3MZwy3YADupGEfnzDwgOjz3FkT+Ng+t2s+791xBdRkAgdugcrvj1XWdV4mvpMtF4uI6Wmkaam5tpM7bT7O5kb3YwO7zHARAstjKjaidJ9QbiQ2JIyUolaVQ6GsPpdS8t2LqU9t/8npA2j8uj/OIsZvzl/eOGAF1OB7sWv0XHh5+Q3CvU5xagMCecSX/+O5GJQ+gxdvDpd0/xZsRltCo8ZZ8TOjYyZvlmMobM59IHf45iABOW/7/Q3lxH3Ye3km3dzca2iexr0/U2TFOTNvEq5t3nSYxcu/Jd/mmxsDXAEwoLdzXyi31fMWfOLSQPn3rcc1fkb6XikQeJqvX0xCofF83klz7GLyjitOZW09PIyvp8NnWY2GsPxkj/e0OQ3EQq2klQm0jVK8jw8WVYQDTp/vFn1VK+ua6cto9vJcuRB8B+r8kk3vou/sGDawzsXb6ZzZ+9heQ2AUpSx1/B/PtuOuf367dV23iy0tFXGXSFoYK/Zs/EX3d+3mNN5lbyOio5ZGylxGyn1CxRQxgWwVPJN7J7D0vn3TKgndJlQ+Q84na6qdpfQml+CVVNNbQ4PZUpR1BKCiJ1wfipOtFt+Y6kUs/L3qqBpsvGMuWxF/H2O/99QNxONxs+W8H2in2IgoRaUjF92ETGXnHROfWOSKLI7q9fIrvgOXSCkw58qZ3yAtnTrxvUcbvbjXz9p5fobPB0EdZ6RbPgsd8QkxE/IOfvaTXyReFaXnX70y543KmjrPvIPliN2qZAKSmI0oeQEBNP6vAMItJjT/q9m4ztbPztrSSt9yjINoVriXj+OdLHnFi0beeSz6h75yWyKjwvN7sKKmdkMf2pv+MXFMHm7//Jv8V2vvOeD0Cg2Mb8PV+TUKFl4RO/ITT+9F6C/wsc3LiYyI2PoHM5+KpuFp1WjxdEpQ3n8sd+Q9zQZIp2reKLnUv5bMi19Cj8PN1TTZv4y+hLiYk4fuM5URRZ/8ZvCX5nGVonmHUCloduYsrPf3vS+ZidVjY05LK2tZGdZj1VYv+/lU6ykuwoI8PUyYKMUYxPHY6XemDyJvav/JCknU/ghxmLpKUg+0lGXX7/oCakOmx2Fv/lTRpK1gOg0gQz9/5HSR1zbpvCtVo7eDR3Q58Mf7jQynNJfsyJGXNO53Eiyg5soPSvfyDhYCsiEg1xAeRePpqM6Qu4JG1gw1ayIXKOaa1opGRvIRXVFdSamnEK/fM7AhQ+xIdEk5KRRtLodLReR1e6+374iM5XXu9b6XR7CXT/bC4X3fvsWUkxDzQNRdUsXfwtzS5PaWCMNpQFN1xFcNzgdsD8T6qL9uFedBuJYhUAu0IWkn3b6+j0g5u3sOHjpez/4WNPqaWgIWf2jUz7+eUDZowZ7T387uAavu6JRxIU+EjdzGnYQVCZBeFHSScGtMT5R5GckkTqmCH4hBzf1brz6zcR/vomvmYJpxIab5zGzF+/jlJ5/Mx7t8vNNy88jX71UpIaPR6VHr1A57XTmfrg3+hsbWTV2qd5Oe4mmhWe1ezYri2M/2E7k2ffysSrZw/I9/Dfit1m4cAHDzOu+QsOdWexpjEWUTQBAhGp01j4u/torS1k7TvP8vnES8j1GQ5AtLuGp8M1XDLk4hOeu7W+jD0P3UpCvke6vzrFj2GvvUNk4rFdtUVRJLe9lNWNZWwxujjoiuyXUCpIIvFiLXE91US0dhHapGDOqOnkXDxuwO5lc08XBe/9kjFdPwBQqkpFf937xCQPbhfwqrzDLHvleZzWRgCC48dz9e8exuBzbp+fiyo281S1SCf+CJLIQp8q/pI9+4KQZm+sPMS+v/yahK2VKCRPWLZyciIjf/vcoElMyIbIIGM1mjm8q5Cy0sNUtdfRLVn6fa5FTaxPBEmJiaSNGUJA1Mk9HKIosvWTF+DtTwhp9xgxrUEquOtGJt342HmvFXe73Gz+YhVbD+/FLYioJSUXZY1nwlXTB6U/zIn4TynoSkUcLHyPhMxT53D8FOpLa1jy3HPYTZ6W535h2Vzz1GP4BvsP2BhbGnN5tKSRasmzch0uVHBrq4v/Y++so6M6tz78nPGZuLuHQALBCe7FCkXqeqnfyld3l1t3d3cvUFqc4m4JkEDcXWaScTnn+2NCgAqaTCidZ61ZLCYz592TnDnvPlt+21jURJWl4fBWYgnCFAEkRSbQo3caSYN6olAfTBs1VBWy9bYrSMpxb2DlPfzJfOV9olP6/u36DaU1/PDyPaRt3U50s3utxkA5rmvOZ8Sld7Puu8f4MUDNT74zkQQZgWIz03f+QL/GWM5/8FY0vt3vNHuasn07cH53JQnOMubVTKGs1QRICHI/JlxxCwn9oln3zJ1sjI/hy74XYBM0KCU7F6nyeHzYhWgUf60bAX/lUE7gjLtfPcyhrDU1sLgqm1XNrWyxBNH8B4GwYPRkaZvpY7Ri3VaC0+p2NDMCk5l+2Wx8Qjrvmpq/YxW6X64jVqpBlAQ2x85l8NznUKr+/jOeLKIosuyDH9iz4ivcBakasuZc06mjG46FenMjt+5aw0qbuyMmWqjnhdTgEx5+2ZnoG6tY/+ydxC7a1dEwUdI3jLT7Hv/bNGBn4XVEOhmX00VFTjEFOXkUV5VRa28+rIVTkASi1MEkRSeQ1i+d2MzkExL9stvMrH7rYfy+XESA0b0ZVMXpCLrtZgadObfTPs+JUltQyfzvfqbG4VaDjFGFMvvCcwhL9myIPvv374ldfQchGLBKSrIz7iTrvLu7dkS408n8Fz6gdOevuAtZ/Rk/9yb6T+68wjOb084zexbxQUsUDlSosXJdSAO3pEygfHshBbn5lNZX0CS2HvY+pSQnxiec5Pgkeg7u3fH3+P3N+wl5b/7BkP4tlzLmivv/dn1RFNn2yxo2/vICg3cVE2x0n+PVURr8br0e/5ge7N3xMk+m/JdqmbuTY3DrRsYs3cbsubeTlnViYm3/NCRRZMuPL9F3z7M0W0P5qWowdoc7YugflslZd13Hrs+exFBQymsXX0ORugcAGRTxWt9+9An56zQMtKfY7r2clN/dLeyHptisThtranJYUV/JeqOKIlfUYS2cSuz0VVQzOkDB5KhUEm2h/PbNPAqN7k4wf0HH9DOm0XNk50UoXE4nW754kCEl76IQRGoJpXnKG2QMn9Zpa/wVbg2gZ2mt3wOA1j+Zc+67l4jk6C5d9498Wfg7j1fIMeCPIIlc6F/K//pOxVfVvY65xdzKmlfvI/i73zuUeCsSfQi/6076T+zatPYBvI5IJ9Bc2UD+lr0UlRRR3laLDcdhP/cXdCSGxJLaswc9hmag7cTWRqOhkTUv3Enk/M1o3TWtlGYEkXTPw/Qa+vehXE8gukTWfreMtfs24xREFJKM0b2GMvr8SR6NjjTWVlD1yRX0s24FYJd2GPFXfERweMxR3nly7Fm9neXvv4KrfeOJzZjEnHuvR6XuvCKvPU2F3LY3l90ud1FuqqyKl3oldqiy6qubyd+6h6KiIspaa7BiP+z9foKWhKAYUnv2QBtooeKhO4gpby9yHBrLqBc/+VNL6KGYmlqZ/9FXNO/+luG7atG1H74sLYDwm2/DmLeQn+IT+NZvDpIgx1/UMz37JybIBzH9psu6PYLXlegbayn+8EoGWtazomE0u5pU7oJUQUXfSZcgt+2Abxby49zZzEs6C5egQCeZuC2ilRvSJx+x0+SPRceF0zKIuesRfm+uYK3ezi5H5J/aaROEGob7WpgYFsWE6P74KN26JJt/Xs3vu9djx4kgCQyO6cOkS6cfcwH0sVBTtp+WL64kw+F2Brb7jSf1ivcJCO7aovadSzaw6tPX2zVZZKQMmcnMW6/waEFqtbGOW3PWs6Y9ChIn1PFSzwhGR/X3mA1/hdNhZ+3HT6L68MeODs26cBWqG69k2Hk3efS76XVETgCbyUrRllwK9hVQ2lBBi2g87OdKSUGcbwQpicmkDcrwSBSgvjKfLc/cTcLK/ShEEIGSYXH0u//pDjXN7qKhuIZ53/xEld09QC5SGczs88/utIFYx4K7VfJpBu57CZXgpJFAasa/TObYs7t0XWNLG98/8RLNlW4nSKWLZubt95CQmdJpa4iiyDv7lvJinR8mfJDh4mL/ch7NnHLY3ZboEqncU0J+dh4llWXU2BoRD4vWQbgyiACrhfjtOwgqy0XvB5rH7mHQ1MuOaMO+tdksXPI9AQUrGbqnpWPydPHgaNSTxuI0r+LBHrdSKXc7TAPbNjNpbT6X3XIPobHHP2TtVGfPugWEL78ZjcPBd5UTMVjdBakqXSw9hqSi+eZzyvqk8PKca6hVuK8Po5TFvNRvOPF+f3+9cNitLH/qRmK/24DZX8PaKX3YNXocOfIE6jk8retPK4PVjYwL9mVqTOafjltbUMmC7+dRbXen5cIUgcycNZO4zOTO/FWwbeF7pG17BH/MGCUteQMfZvBZ13VtQarNzs/PvE1l7jIA5Mpgd0v5qP5dtuYfEUWRzwpX8mSVmjb8kOHiMv9yHu03Fa3CsyJpf7Rry7x3ML/+HlE1NsDdzm++fBZjrnkYparzHNBjxeuIHAOVbbVQZiF/Zx7FlaXUWBsPy8MfuIAnRiWQ1ieNxIE9u0y/42iU7t3I3qcfJHlbNQAOOZRP7s2Ie14kODKhW2wC9ya44cffWb13Aw7BhVySMbLHYMZeOKVT59EcjeI9m5H9dBWJYgUAmyIuYsAVL3WpYBLAmq9+Y9uCj5AkKwhK+ky4iElXn7yU/6FUtNVyx+4NHXdeUUIDTyb5cWbCsL98vdVooXBLHoV5+ZQ2VaL/g0OtkuREmWRE1DXgjLIy9bGXjihkZDNZWfbFQnYUryJp32YG7jciw912XjQ6iaAYIwszR/BlwHmIghw/qZXpe+ZzQcJ0hs+a0Gm/h+7EbrOy7cPbGVb3Fbtb+7CyNgZRNAECIfGDiNyziECDk9dvvoQVEe7PHISeR+MFLkgZe8RjF+3dxJJPnqcwOY3tCf0o0PRAFA5+d+Q4yZBXM9ofJkUmkRWe8ZdRFafdwe9fLWZTyU5c7ZHKUWlZjL5gUqd+F1v1TeR/9F8Gt7qdgX2KdPwu/piY5K6VS6/ILWbe889ib5efD44dwnkP3Y5voOfUQivaarkleyMb2hWSE2U1vNwzluGRXVuMezT2rJ1H1bNPE1/oTtma1QL154xkzG3P4uPnWUHKQ/E6Ikdh0bLFXCkPo4ezkF6NJUSUmpHbZfiicYe001JJy+rdqcVcncHedfOpePbpDtlusxrqzxnV7SdcY1kd87/6kQqbe9prhCKIWefMJjrdc07SoXLaAIXyFJTnf0RCz/5dum5tcRU/Pv0M1la31LZfWG/Of/BuAiM7d97Dd0VreLTc1VGQOE1bzLN9xx51rkRjWR0F23LdKUZjLfY/KPYGONXE+vgy/qJzCT1CO255dhG/LFhAk2E3vXfvIKPMfddlUUH+0HBCMmw8kHkf5XL337yfaRtn5zQw95ZbPS6n3ZlUFO7G/OVcklxlzKueTEWbEZCQyf2JkFz025nNsnOH8vb4yzHI3H+bWbpinu434W+VM0VR5Nf8FXxVsJ+tPv0w/kFMLEaoZ6jOyMTQMM6I6X9Uae7SHfksWPhLx6TceE0EMy+cQ2hi52p27Nu8FP/FNxIt1eOSBLbEX82Q/zzVqdoTf0QURX7/ZB67ln7eMYJh8FlXMvaS6V225l/Z8GH+Cp6p0WLCFzlOLg+s5KHMaUcsOO5qSvZsIPepB0jeUQu4b1ArJvdh+D0vdOsN6gG8jshReGHt97zg7NHxf5VkY5i8jAviojgrYRgq+fELV3kKURTZtuB9jK++Q1SNW7VT7yfDPHcmY659pFtCcAfs2vzzalbmrMchOJFJAiOSBzH+4mkejSTtWvYVCevvJog2LJKK3Zn3MeTsW7u8kPWXlz+heNsCQEQm92PMpTcy6Mwjz5E4XlqsBu7LXsF8k7vVN4BWHohxcmnquGOKwricLsp2FVCQs5/C8gIaJeNBjRsJIgQ/+mcOpP8ZWWgD/lzz5HK4WPOtu3tKrs9jwK49JNa5HRuDj0D1AIHNk6fwRejFuAQFPpKRGfsXcdOQS0kd7PkBYyeDJIps+v4V+uY+Q7MlnJ+rBuBob2FXK6MZnrMNQ7SWl667nG0B7q6tGKGO51JDmPg33RJ7mwv5OH8bS0zBHUJxADrJSD95FRNC/ZkanUGPoGPbRKxtFhZ/Pp9ddftAcM86mjhwLINmjOjUqJzTYWfrZ/eTVf4BckGiWginddpb9Mqa1Glr/BWtTQa+e/x5DLW7AND4JXD2vfcSlRrXpeseSomhklt2b2OLIxGAFFk1r6QnMiQ8w2M2/JH6yny2PHUnCasKDqbsh8fT//5niO0xoNvs+iNeR+QouJwuVm9cwyofA7+2aqmSDmpiBNDKJJ9GLo5LZVhEn1O28M7lcrL2k6dQfPAdIS0Hi5KUN1zO8PNv6Ta7mysbmP/lj5RZ3F56qDyA2XNmE9snyWM2NFSXUvvp5WTadgKw02cUSVd82OWqjnnrd7HknZdx2d1dRdE9J3DO/Tei0nTuXdPKqu3cXdBIZft5O1RZwsuZg0kOOL4LdHXBPtZ/8h2NooI69cGCV7kkI9kvhn4DB5A+ut+fHMmG4hoWfPsz5dZafOpzGLqzgHC9O61ZHyhQN0LBi1MeoUzlrpnpY97FFbUuLrriilP2+3QohuYG8t6eS5ZtPSsax5LTJAccIKiIb5GTXrGHH644g08GXYxV0CLHydyASh7qO+VPdQK1pga+LNnC/EaRfOng30cjWRjSvJkxMgtXn3Ur2uMUE9uzcgeL1yztGCHQKyCR6ZfO+Vt9mROlqjiPtq+uoJfTLZe+NWAyva58F7+Aro3A5qzcyooPX+lQN04cMJ1Zd16NQvHXejidzYEarefr/LGgQ4GDa4KquS/zzG67UW3T17P2+TuJWrAVTXvvRGlGMEn3PnxE4cLuwuuIHAeiKLKxbjdfVRSxzBRK6yHSx7FCHWcFWrk0aSApx3mR9xQ2i5FVr91H8Dcruq1N64+IosjWBetYsWsNdtzRkaEJ/Zh4yfTD9C661AaXiy1fP87AgtcPzrmY9Bp9Rp7VpeuaW018/8TLNJZtAkCpieSs2+8mqV9ap65jcVp4YvcSPtHH4kKBBgv/F9rMrb2noJAd38W6paGCdS8/h73Jl/IwPwyKg06JFhU9w5MZMGIwcX2TOxwJd6vvOlbsXIvNZSGwaivDdlUQYHafg5URsGFqb94feg9OQYlOMnFW6e88NOVaQmNO3ULWXSvnE776NnROB99Xjqe1vSBVSTBDCotpSFHz/JXXUqDuCUAvWQUvZfRgYFivjmOYHBZ+Lt3ED3V6ttrjcAnuv4cguehnzGFE3gZGxKUw/oI7/1Zo7u9orWth4Rc/k99WDrg7pM4cN4X0sf074dMfRBJFti14m/Sd/8NXsNCKjvzBjzF4xrWdus4fcdodzHvhfcqyF3Fg3tOka26lzzjPaXIU6Mu5ZfdOdjjdkameskpe6d2DAaE9PWbDodgtZla99QABXy3B3+T+fp1Ksg5/h9cROUFsTjsLyzfzfW0D622xhykTZsrLmROq4sLkYSc1NbGrMDTVsO75O4lZuAN1h3BNaLtwzYmNBj9Z9NXNzP/iB0rM7iLbEJk/s2bNIr5f53WXHI2CXWvRzL+WOKnaLbQU8x8GX/58lwotAaz7bglbfv4ASbQACjLGns+U6y7s9IhAdmM+t+XuJ9fldpR7yip5OT2FgeHHnwrRN1ax/pUH0O00Upfch9IgBVbZwZqSIJkvGfE9GTA+q0NZt7W+hV+/mMf+1jIkp5no0m1kZdd03LEVJgl8cvYFrE91DzrLsOzmDiGQ6dO61iE8XpwOO6tevZHxbd+TbejLqrpIJNEMyAg3B9K7Yicf3DyL+YmzcQkKtFi4OayFmzOmIJfJcYkuVlbv5JvKMn63RGHmYAFwkq2YCXlrGbhpO5GzZjPsgpuP2wFxO/drWblrHTYcCBIMiMxg8mVnofHt3BocQ3MDhR9fw6C23wHIVfYh6NKPiEro2o3YLRz4DDaj28n6uwnYXYVLdPF67hJeaQjCihYldq4LqeOePtOO27nvFHtcTtZ/9hzC+18T2nxA6FKJcN2ljLzkzlM+uuh1RDqBZqueb0o283ODrUPPAdyiQSPUlZwXGcZZ8UNPaCBUV1Jblsu2p+4mcU0R8gNSvqOSGHjfs38pDd3ViKLIzkUbWbp1VfsFVGBIbCaTLpuBUuOZ353ZaGDPhzeQ1bIQcEtP6y78mNjUrp1DUV9Wy49PPo3ZUASAb0gvznvwHoKjO1dnwSW6eD1vKa/WB2LBnSq4LKCShzKnnND8EENTDRtefYCQhVsxJQ6hLCmZCl/xsK6yaFUomT1702/iEHSBvuSu2sVvq5ZgxAI2PanFO+i3u6Ejh70904fXzrmVyog+aCQzZ9dt4qlZ16PRdX8ha/Gu7Zh/vpY0qYyfqidT1ebuPpAJfmRWtFAyUMPbs6+lWuYWyxqmLOHlzCEkBcSyu7GAL8r2sKjVv2PMO0Cwq5FxZeuYumQtPk3NaK75zwmnTOuLq1nw7Twq24vBQ+X+nHXWTBL6/70w2omyd8NvhCy9iUgacUoytiVdz5BLH0fexSmRVZ8vYPuvnx4cpTD1P0y8fHaXrnko+1tKuGl3DjkudxQkQ17Ba73Tjyg+15VsXfgRra+8QXSlBQCDr4y2S6Yx9obHT4nRH8eC1xHpZIoMFXxRsoNf9JqOvDy4e/rP8Gnk4rgURkRknlIeamH2avKffpikXe6Ll10BldP6M/KeF44oZtVVtNa1sODznyg0ultsg2R+TB4/nphMz1V37131PRm7HicAEyZJw67edzNk5g2oNF23GYpOFwtf/4yCTfMAF4Lch1EXXE/WrHGdvlZpaxW35WxhY3t7YYxQzzOpwUw6Qanp1uZa1r/2IKHzN6CSfKnpM4ySuCjq1LaO18glGUl+MfQb0I+k/mms+G4Ru2rzkARQWxrpVbCTXrnu9IZDDsuGRvPezDsxBETR05bH/8LiGTNo5Ml/+BNk8ZuPMar+LRotESyo6ovDqQfA1xlGcvM+Pr7jElb6uIuOAzHwYKzI+Mh0vi7dzvxmKBAPfpc0koXhDZuYsmYtg3/Poy5ai/bayxl27v+d0LXB5XCx+pslrC90j1aQSzJGpAxi7IWTT2gS9JFw2G1s+/RuhlZ+ikyQqBQiMZ/1LmkDx3XqOociiiLN1U3Me/51DLW7Abcmz5TrbiAy1TN6RC7RxQeFq3nDHIFNpkOFjf8LbeD23lO7JQqSt2kRpc/+j8Q8d2G0RQW1s4cx5o7nT4lhqMeD1xHpIkRRZFPdHr6qKGSZ6fBR2jFCPTMCLVyaOIAegV07pv54yF75HXXPP09ciVtPwqQRaLpgHGNueeYvx8T/HZIoYrWYMLXpsRoNWE0G7OZW7GYDTksrLksbkq0NyWZEsLchsxuRO00onCaUTjNq0YRGNFPuHMEaWSoWwYkgQZZoYrLsQ+SCq6t+BYdRKwXQJAXQW+YO/+4QU4mmAZVMwiJoscp8sMl0OBQ6nAofXAofRJUfksoXQe2LoPZDrvVDqfNHqQ1ApfNH4xOAxjcAX/8g1BrdX3bo5G/Zw6I3XsBpcwtNRaaO4Zz7b+r01lZRFPm6eDX/q5Chx124eJauiGf7TTzhlGKbvp51rz1A6M/r8bVImIOjKe6fRWVYAAbB2vE6DSp6hSURGx3HhpzNNEvudtJwSxNJuzeRWNx+Dqrhh/GZfD3l/0Ct4hL9Dh6fea3HChEBaktL2f/JtYwWN7O0YTx7mwGcgJqkFoHcc2L4Mm02LQfapTWFDAvQ8Fuzg22OOFy4bZVJLvrY9zJp4+9M+GU7OrODqjgdvv+9kqyzrz/hm5Py7CIWLFhAo8vdqh+jDmPWeXMIT+18CfOKwt1Yv7mCHk735OYtgWfS+6q38fEL/NNrRacLc6sJk96Iuc2I2WDEYjRhNZqxGU1YzWZsZjMOiwW7zYLTasVht+CyW3E6bYhOG6LL/UCyA6fQ9iMoEWRqZHI1crkamVKNQqlBodagVGlRajSoNFpUWh1qHx0aHx80Pjo0fj7o/HzQBvjiE+CLLtD3uJWWK/K3k/3kvaRsdsvxO2VQNrEXQ+99nrCY7onKnCxeR8QD2F0OFpZt4vvaBtb9oZ6kj7yc2aEqLkwaSqg26AhH8QyiKLLphzewv/EhEfXuQsQmfxlVE1KJ65WBYDchsxuROUzInSaUThMqlwm1aEYjWtBhQSdZUBw6eO0kaJNC+UX8D/ly96kXKSo5l+8JlZV0yvGPhkuCrWI6g2T5KAUXTZIfFWIY/eXFJ31spyTDLGgxo8Uq02KT+WCX63AofLDix+78YIyt7uF5cmUwvUYOJn5AGv6hsQRHxqHz7Zyuh0ZLC/dkr+RXi7seJwg9D8fDRSnjTviYRkMj615/gOCf1uJnlpCAql69qR0wkmrJguUQqflAwYdIZQhV1nraZFbkIvSQtRL6+3Ji6twFJM2+Ap9OG8MvY69moDWbF1KHk96r69siV3/5Nun5zyCzy/mxahRGW7tCKiHoohwsnDOLjaK7HiKSOvopKljjzMBySN1HilBJVuUmzvp0GVEV7lROZbwOv+uuImv2dSfsgNhMVpZ+voAdNXlIgoQaBRP6jWbIrNGdEnEVRRF9XTPNlfU0VddRtHU12oZcXKIMi6jErIlEodTgtFtw2q24OhwHO5Joc2t5eDkG5AgyFcIBp0ahRq7UoFBpUKo0KDValBotMhnoi/YSUlaHn9WMj6WNxnQdfe9/goSMod39IU4KryPiYVqsBr4p2cTPDVZ2O+M6BlEpsTNcXcl5kaHMjB/WJfUkkijSqm9CX1dOW2Ml1pZqnIYaMNahNNejsTXg72giSGxBI1lYUxOIZqeOoHbBzfIYiZRBzaTqbEde6BBMkgaToGvfaHXYZTrs7dEDl9IHUeULKnf0QKb1R6HxQ6H1R6XzR+0biMbHH51vIPvW5rF85zocghOlpGDSwDH0n5rV6b+jv6Mwex26RbeSKLnTRes1Y1H2Ow8FTpzWNkRLK5KtDexGd4THYUTuNKNymlCJZtSiGa1oRidZ8DkkMnA0NrYMYWNdoFuRFQjUBDM5YgdxugqMkpYWWRCtyhCs6jAcunDwjUAREIUmKBq/sDgCI+LxDwg+Jm2UJRVbuK9IT7Xk7lQZqSrh5b5Difc78Ttro6GJdW88SNBPqzuq+BtCVBhmXEyrMpTitqrD6klCRT/kkoxmmZEAuY5oighf+Dsh7bP79sVqeOGSG9DHJ3JDcynXn3NVl6Q5DS1N7HjjSgZYd7CkbjSVbWbcURAZvrIQGq4byUdiBmZ0yCUnGewhj3ScgruwOZRmJqpq6LNqKVlfbUHVHsSrTPQh4LprGDzzmpOye9+abH77fUnHNO8efvHMuGQ2AZFHb5V1Op00VzXSXFVPS209rQ1NtDU3Y9I3Y23TY7e04rS1IbqMuKt2ThYZgqBCkKuQtW+0CqXG/VBpUGg0qNRaVDodKq0WjU6H2teH1kYD+ZtW4bLrQXISGJXBrDtvwD+0c9uO/w6j3cw92ctYZHanL1NkNbzSM5k4WThmgxFzqxFrm6k9ymPCZjJjM1uwW8zYrRYcVreD5rRbcTpsiE4rLpcNyWVHEu3wB8HAE0WQ6ZCr/FBp3BFXXUAQPsHB+IeGEBgRRnB0GKFxEae0WKDXEelGig0VfFGyk1/0aioOqSfxo40zfBq4KDaZUZF9j3rBEl0uWhpr0NdXYmqsxKqvRjTUIhhrUVoa0Nkb8Xc2Eiy2oBGO/S7FLKmploLZVa4iZbsDjcOdu88dGkz0yFGofYORa/2Ra9zpB5UuALVPADq/QLS+Aeh8/JHJO0+grLG0lu+/+I46p/uuND0wmZlXntOpQwSPhNViYtend5FV8xUyQaKWUBonvkSf0bOO6ziiy4XZ1Iq5TY/FaMBmMmA3G3CYW3FaWhGtbYg2I9jaEOxGrK0OcversFhq2o8gI1QXwNSITURo6o9ut6SkWRZMqyIEsyoUhzYMyTcSWUAkmsBofEJjCYqIIzAkEoto5/GcxXzR6k4paDFzS7iBm44yhO1omNqaWffGQwT8uKpjWnRzgBzTBWfhGzeRvQX7qbI1QLtomlySESz5ggSRoaHYC76g55oKtHZ3KPqnMWl8NPN2JrRt56nhFxAV33m1TFt//ZbgjY+RXZ9JSaujPS0AciEI/2n9+SIxlVzRXa8UI1XgREadEIMWC+O0NUxTy9B88DEJq/I7HJCKJF8Cr7+WwTNOznFqazTw6+c/s89QCoAvGqaOmUSfCYOwW200VdbTVFWPvq4RQ30DppYWzIYWrMZ2B8PRhuQyczxpDkFQI5epUcgVoPbDJygSpUaLSq1BrfNBpdOi8XGnILS+Pmj9fdH5u//1DfRFpdMc12e22+zMf+F9ynOWACKCzIdh51zNiHO7VhTtUDbX7eGGvCqqpAgESeRi/zKe7H9mp6qj2m12zHojJoMRS6sJS5sJS6sRq8mM1WTCZjbT2lhHa2E+CpsLl8xdvycqQXJZ2x3F49iSBTUKpR9KjT9qnwC0/oH4BgbjFxpMQHgYwVFhhMZH4hvkOSn8A3gdkVMAURTZXL+XryoKWGoMwcBBjz+aeiYoaplocxDcokdsq0VmqkNlacDX3kCAs4kgyYDyOOomWvGhRRZMW/udtFMXDn6RKAKj0AbF4B8WQ1BEPL7+B1NFFfnb2XPvzSS2FxPWhynxe/BuBk65tPN+EceAy+Fi6acL2FKRjSS4JxuffdYcEgf2OPqbO4m8zUvwX3wTMVIdAJtDzybz8lc6LVXyd+zbkMPvn32CuSW//Rk5gdF96ZEViUpshLY6FOY6NLZG/BxNBInN+GM65uM7JDnNQiAGRQjZ4Wm8knw2RXJ3uqaXVMwdfjAmdQwBQSdeCGdqa2bdW48Q8P3KwxwS84VTyTzrJvas383esn2HDZJUSwpCRH9iI/ywLXmNXgXu6FBNkJxXLriApvSe3N4G55x7/gnbBW7p/7UvX4etwky+Xo4kubsQZEIAvrGhbJ7Vl8WOvjgFJWrJShJF5JPGYFUV54T7MRJ/9r3yP+JXF3QM/atI9iPohusYdOblJ+yAiE4XtSVVbF24loKi/YgOOzKnAzUScpkTh60Nl8PY3v59rAgIch8UKj9U2oN30r7BwThdZlRVy+kn7CJE1YRLENgVcyEZ5zxIQEjE0Q99EhRuz+O311/C0e50+0f05bz77+j0MQh/hyiKPL/3N15vjMCJkiD0vJCsZnrCcI+sfwC7zczK528j8ps1qJ3uG8DKc4Yx8b7XUWt93bY6XTTXNtFcXU9LTQOG+kbampsx61uwtumxmfU4bG2ITiNwHHV1ghK5wheFut1h8QvAJzAY3+Bg7GYHEQmxDJ7ZuUrQXkekm3E67NRXldBcuR9zXRG2pmJyfERWBWewWT0Ye3uoV5BcDLNv4erKn5hWuYU/XtJESaBF8EcvD8akDMWqCcPlE47MLxJlYBS64Bj8w+IIjohFo/M9IVtFUWTdZ8+ieuOLjk2kaHQSI598h6BwzxbdFmzcy/wlv2DEiiAJjEoZzPhLpiGTe6YbydSmZ8+nt3XMq6kUojBOe73LpawBdi3bxLpvPuvQUEBQEZ85kWnXX/YnHQWr2UhzXSWtDRWYm6tw6GsQ22qRm+rRWN3ObKDYTDCtf1rHiYyX08/jjbArsAnusG6EWEuWeQeDm/fRW29Cro1BHpKELiKF4NiehMckHdM8EbNRz7q3H8Hvu+UEtrnPpRZ/OaYLJzPi2odpKmpi5/qt7KsrxiIcUk8i+hBoM5G66mdCDO7nV/aL4P0L/o8zGvby4JybCQw//lqr7DWLKfrmE8paJETRhISEMTGa2vR4cuPSKBJSOsTGkqRCfAQnU0J9uSRpCGJNNbtefJiENYUo2jMZ5Sl+hN54IwOmXnZMDoi51UR1fjl1JRU0V1Wjr6/F2FiH1dTUrhh6rBuJHJmi3cHQBaD1DUQXGIRfSAj+YSEERYYREhNOUHTonwp+S/O20bLwEQaY1gFgl+TsDJtNyrmPEhrZtd9vp9PJr69+SuGWBYALQaZh4PS5jLvUcxoylcY6rt+1ka3tEu3DlCW8M2AUkT6d20J/NHav/pmGRx/rmIxbnupPj6dfJDnzxDZ/URRpbTTQXFlPc209hrpG2pqaMOlbsLTqsZkNOGytuBzGjujfkZCporjt8/dPyJa/w+uIeABDSyMN5ftorS7A3lCMYChDZ6wgyF5NhNjwt9EMvUrHtwkT+CFsKruVB3U9YsQqzrTvZ5oylLCQRALC4wgKi+5y4a0DtDRUsP7B60lZ7da8aPURsNxwEWOueMCjbcmm5lZ+/ug7Co3u6vFYdRjnzr2AwGjPta7tXv0T4b/fSQRN7uFe0Zcw4D/PodF2bbpIFEW2LFjFlp+/wmF1S+QLMi2pQ85k8rUXoPE9Pv0Ah91Gc30lhvpKzE1V2PTViK3u6Fuz3MK7KZPYqhqISzjYCqqQHGQ69zDGsIWpNZvo11yMS5JTJwujRRWN2TcOKSABVVgy/tFphCf0wj/w8Dtbi7mVtW8/gu+3Swlqde/iej8ZbRdMYvQNj6NS+rBnxTa2btpCtdSMKLgvQWpJSaTRTub61fjo62jVCrx/1jga+qVzZas/s644NhVJq8XMjw/eT0NNHVaNhbo+sZQm9mR/QAbNssNtDZXqGa4q5ca0MfQP7+XuXnjhYRLWFR90QFL9CbvxRgZO+89h7xWdLhrK66gpKqexvIrm6mramuqxtDZgt7QgiUeLXAkg80Oh9EUXEILWPxCfwGD8QoIJCAsjKCqM0Nhw/MODjvs7WF2yj6p5DzFIvwyZIOGSBHYETiFmzuNEJ3a9Qmj53mIWvPRCh2PtE9yTs++9i/CErh2zcCjzStdzT4kTAwEosXN7WCO3ZEz16PWstbmWNQ9fR9Ly/cgAo1ag7b/nMO7axzxmh1HfRlNFPS019dTkl1FeUITR2AIuW/vDgloXyQ3vPdupNnkdkU7AYbdRX1lMc2U+5rpCxOZS1G1l+FmqCHfVEHCU8LhNUlIrj0CvjsbqE4cUlIg6LJnAmB6Ex/fExy+Q7MZ83i7awyJzNDbcw+p0mJnhW8v1Kf1JD072xEc9jF3Lvkb/v2c6umtK04PIeOoVEtI9V0R6YIDeipy1OAURNUqmj5xM30lDPGaDoaWR/E9uZIhhMQClsnics94htV/Xa16IThdrv13MzsXfdcytkcn9SB89kwlXnnPcrYFHwmBr49eSTSyrr2ObM4IG4fA7xVCxnmGWbZzRuJkp1VsJsv/5vNfjS4MiilZNDHb/eOTB7miKT2gs+b9+id93SwlqdTvmej8ZbedNZNQNj6PzDaSlqpE1Pyxjf3MJ5vYoiSAJxFgU9Nqzm+DibHYn+vDRRZcwqqKci2f9h5TMvx7sJYoiiz/4nC3lmyjrEU5hRDrFqtSOqAeAUrITSzlhQgtnhARzXe+ZqORKyvK2sPulR0lYX9LhgJT1CCDwqusIjcmitj2qYaivw9RSj9XU5C64PFpUQ1CD3A8UPkhKDS6lCh+dPzEx8fQdPZCkgT07NeLXWF1G0U+PMqBhPqr2m6EdPmMImfEoCemDOm2dv0MURRa//TV5a74HnCCo6DPhQiZdfa7HNl6L08I9OxfxndF9/YwXanknI+GE1IZPhvVfv4Tw8ocdznjRsDiGPfU2odGeU5YGEF0i+9bmsHnzZsrMNR01W/6CjkFp/RgybSS6wBOLqB+JU8YRWbNmDc8//zzbt2+npqaGn3/+mdmzZx/z+7vKEXE6nbjsLqzWVurL99FaXYi9sRiZvhQfUznB9hrCxYajtqs2EkijMhqjNgZHQAKKkCR8IlMJjetJaGT8MRd1Nlv1vF+wjm+a1NRI7o1AkESGqMq5KjaMGfHDTqqo8HixWYysePomYn7chMoFNgXUXjiGCXe97FFVv5r9Ffz43Q8dWgp9Q9OYceXZqHSemzC8c+kXxG+4nxAMOCQ52xKvYfAlj3skUuW0O1j56Tz2rvoZ0elOs8iVQfSddC7jLpmBTNG554QoiuxtLmJRzX5W653kOKMPa0uXS056ikUMNOYxunoXw+t3Eo7+yJ9BklEnC6NODKS1VYmzTYHUCk6LE+ewvky4+Ul8/IJx2h3kLN/Glh1bqW0vXAYIdqhJK6shfPcafhiTSl3/XkzcW0P61MvIHDcShUpJvbmJzzYsZq2xlX1+vTDIDk/jhIs1BAvNOFDQSwP/TelDVkRvAEpyNrD95ZfQFVsxav0wq1UYdQpcSnA52tpl3o+EDLkyALkyAEGhwyFTYFPJcKnkODUCkhJ0qEkMjCE1LZWew/rg0wWS5frGWvJ+/B/9q79D2+7Q5WgGo53yCD0GjOn09f6KmsJK5j33fIeSsMYvkdl33UVMT8+JFuY05vPfvUWUiFEAzPEp5vn+U/FVee66VV28m133/R9J2e6i88ZgBep7byZr5jUeswHA0mpi62/r2b4/G4N08AYiQRPJkKFZZIzp36Vp71PGEVm0aBHr169n4MCBnHPOOaeMI7Lo3XfIXfkrMpkPGoUKP6VIsNpEuLqFWE014ao6ZDJ3Z0KdPNId1fCNQwpKQhOe4o5qxPXo9EJGl+hifukGPqpqYpszseP5aKGeS0IdXJU6mkCN5yJDxbvXUXD/HcQXuDfBmig1YY8+QubYOR6zwWG1s+jjeeyoywXciqznnnMOMb0TPWZDc30VpZ9ex0DTGgAKFD1QnfOuR+4wAWxmG8s++Jb8jQs7NkaFOpwhMy9i2NkTu+xO02g3saxqJ8sa6tlo9utwkg8QjJ4h6gaGyJ30bbWhaqhAaClFY6wg0FZFpKsO9VE6ugySjmpHCM1WX8wmNS4DuKQQGqL7UOGv6GgDVosKUhtt+JRu5pvJGaSKLirjI9jrn06xIhFJOOiUqSUr6dZ8ohv2sTVyBJJcxeT8lQxdlo9kU2NSq7EqwS6zI0pHb2cVZBqUmmC0fqH4hoQTGBGJRueHqc1MjaGeGlvTYe3KgiQQpQ4mOSaJngMziOmd2HV/o9YWdv/4DH1KP8VPcBe27lNm4Br/EL1HnNkla/4RURRZ+cnPZC/9yi3RjoK0EXOYfuOlne4sH8mGt/Yt5fm6QGxo8KONpxIkzkv2jBMG7trAla/eTehnSzo6wcpnDGD8w2+h8w30mB21BZVsWrqWvfWFONqjYkpJQe+IVIZPHk1EqmeUtU8ZR+SwhQThlHFEfnr+DUq2LT7CKxQo1MHoAiIICI8mJDaWyNRE4jKS8Q/xTL/7nqZC3i7K4TdTFBbcRYVaLEzzqeGGlL4em4EgiiKr3nsEv3d/xNciIQIlk3ox5rG38Q/2XL43d9Uufln1GxbsyCUZY9OHMer8MzwW7pVEke2/vk/a9sfwx4RNUrIz7SaGXPBAl8/hOIBR38aSd7+idOfS9gs+qHxiGXHeZQya1vUpo7zmYn6rzmO13kG2I7IjnQggw0UveTWj/UWmRiaTFZ6BIEFjbTmNFfsx1RbibCpBaSjD11xJiKOaMMFwxPVqXMHUSOFUC2GU6ULJj42jMCSBfE0abcLh14NoZwUZLftJbqyn5/oSXp96JppQDYNztxGxrQSZeKSCPRkyhR8a3zB0gWEEhEUQHBNNeGIs0T3i8Q8NxGq0ULB5LwV5+ZQ2VXZofRzABw1JwbGk9uxB2tDeXRLqPhSrxcSun18iLf+9jqLkInkSxpH30nfc+cekMdMZNFbW8+PTL2BsdN8oqHQxnHXrnST281zHW725iRt2rmad3Z2KGaAo493+Q05KK+d42bd5MZUPPUBMufu8qEzwIf6Jp+g5ZLJH1hddIrmrd7JlyxbKrXUdzwfKfBnUsx+Dp43wmCTCAf6xjojNZsNmOyis1draSlxcXKc7IqY2A4Xbd2Brg+aqOpqrKmlrqsXSVt+e9/37OyRB5oNKF4pvUASBkdGEJcQTnZZITM8EVJrOD9frra18WLiWrxqVVEkHx6cPVpRyZUwIsxJHeCRt01hdxKb7rydlk1v8q8VfhnTbVYy86PYuX/sArXUt/PjJt5RZ3IWciboozrniQvzCPOMcAtRXlVD7+TX0tW4F3JNJAy76gJhkz+Wf9fUtLH77U6pyV3FAQEkXkMKYyy6n9+i/rp/obEwOCyurd7G8vob1Jp/DZjABBGAgS9PIhOAApsf1J1z352Lj1pZG9m9bjqmhDElfjsZYSaC1imhXNT6ChXWRfVgaMYy1vkMolKd2CAUCaCQzvUy5JFXtJy2/hd6yampcfdmq01PTtwd9tu/Ev0x/2HoyuT9KXTA6/2B8Q0MIigwlKjWBXiOG/anbRBRFavdXsH9HLkXlJVRbGzqKagFkkkC0JpTkuCR6DepNZM84jzjFToedHQveIn7360TiHhdQIURTP/gOBky9olM1fo7Gmq9/Y9uCj9tbjGUkDZrOzFuv7PQ5OEdiacVWbis00kQQcpxcH1zNfZnTPZbKNrU1s+qx60n4NQe5BGY1NM89kwm3PHvcE5ZPBLPeyJbf1rGjIOegcyxBok8UQ4cNpeeoo2tWdRX/WEfk0Ucf5bHHHvvT854sVrXb7NTkl1OdX0p9aTn6umqMzbXYzI1ILuMR3ikgVwai8Q3DLzSK4OgYwpMSiO2ZRFhi5EmfDC7Rxa/lm/mwso4t9oSOi3KU0MCFITau6THqhGeJHA9bf/kA69OvdoylLukXTv+n3/DYZF9RFFn77TJW79uEKEjoUDNzwpn0GtPPI+uDOzqy9adX6L37WXwEK2ZJze4+d5N1zu0euxMFaCivZfHbn1BfvIEDzrNfaG8mXHk5qYM8W5hXoC/nt6o9rG6xscMRiZWDio+CJJImr2aUv5MpEYmMiOzzlwPFKtpq+a0qh9+bjGy1h2Pi8KhCnLOMHo25xBcWEZxXR4AiiBFh+WzT9URo9GVzhoyE7Hq0FjVyhRpUKlwqJTaNCoUuiJToZNIyepKalYFS++eCX4vBRP7mvRTsy6e0uRIjh6vl+glaEoPjSEtPo8fQ3mj8PKdqKbpc7Fz8MeHbXiROqgagjhDKMm9i4Mwbj6m9urPQ17fww5MvYqjdBYBCE8G0G28jLatrp1kfis1p5+GcX/lM774WRgkNvNEznJFRnrsObJn3LvZn3yCkxX0tLB4QwaBn3iIyoevHFFTnlbFx+XryGotwtqdfVCjoE5HG8CmjCUuO6nIbjsY/1hHxVETkRDE2t1KRV0xNYRlNFRUY6mswt9bjsDYeeQaDoESpDkEXEIF/eBShcXFEpSQQl5H8J42IYyGvuZi3i3ax0BiJuX3+hRorU3XVXJfSmwGhXdueZzbq+f1/NxL/yw4UontCZON/pjDhluc8dkGs2F3MTz//1CGSNSiyN9OumI1C7bm7seqSfei/vpoMu3tyaI5mMJGXfUB4TJLHbACo2l/G0nc/prlqOwdUGYOiBzL5v1cS2yvRo7YAWJ02Vldns6S+ivVGDWXS4RdFP9oYrG5grJ8W31YH69oa2akIpUx+uK6FTjLSy5hLclUlUbvz0TS5/9YaZRBjwotw+VrZ6JiKWapgkK2Ovtr9BCr0/JUvKEoC1YRQJYVRK4VikUeiC0kjJrUfzXV2SqvLqLY1IR0S9ZBLMmK0YaTEJ9NzcAbhqTEev7uURJGcVd/hu/4ZUlzuWUwt+LM/7Vr6z7m9y1vK/8jm+b+z/tt322/KBGJ7T2LO3f/tkmjw35HfUso1OXvYL7on9E7VFvPqgEkEqD2jHlpfmc+W+28gZUsV4BbvE+64lhHn39yl67qcLvau3MGW7VuotDV0PB8k82Nwen8GTRuBxvf4nGNJFGmoKcPpsHd6W/c/1hH5I6eyjsihiKJIY3kdFXnF1JeU01ztTvVY2+pxOfQcSbJXkOlQaUPQBYYTEB5FSGwMkckJxPZKPKqTYrC18XHhOr5skB0mJz9AUcYV0UGcnTSiS0dZ79+6lPKH7ie21F2RXRWvI/Z/T9Jr6NQuW/NQbCYrCz/6kd1N7qmhYfIAzr3ofI8VY4H7TnXLN08yIP811IKDVnzIH/gQg2b816PREYDinftZ8eHHtDbsaX9GRljSMKZef6VH9RsOxWo0s3XvDpY37WeHXMVeZTJm4e83zwRHET0a8ogvKCWkSA2O2o56GKUikOGhVfTxz+F7JiNz9CR2YgoNX62jJTyBao0FjWTCjzbCpFaiqSdUaCBaaMJf+PvuF5ukpFIKo5oQmgnDqY4hICaDtBFjiU3p5dF0x6HkblyEsPJx0h3u+os2ScuexLlknnPvYQrJnsDY0saPT79KY9kmAOSqYM64+hb6jPVMwfYBPtq/nP9V67CgQ4eZh2PMXJ52hkfWFkWR399+kID35+FjlRAFKJmcwdjH3sYvMPzoBzhBTM2tbP5tHTuLdtPWrgwsSJDkG8PQEcPoMbz3ER3kA85GQ1keppr9uBoLUbeWEWSpINJVjVaws8N3DAPv/KVT7fY6IqcQdquNqv1lVOeX0lBWjr62GmNLHXZzw1FbAwWZDpUuFF1AWLuTEktkcvyfnBRRFFlcsYUPKmrYeEjaJpxGLgixcG2PkYRpjz4460RwuZysfO1egj/5FZ0NXAKUTe/LuEfexseva9b8I9lLNvPbxuXYcKCQ5EzqP6bTppUeK2X7dmD74b+kOd1S7Tt8RpPwn3cIiYj1mA0HyFu3i1Wff4pZX9D+jILoXmOYdv3cLpHVtposVO4rpbaonKaKSvR1NZha6rGZGhFdh6u7ijKB5l7hlPdIoSA0nVZ5AD1MRfRsrCfT4EtMUCINZZVU71sD7YJgMnkAQ0IaGRG0if3Es0Q8k6H9sxh+7jkA2B023n72avqvbqI6PYviIBmO9i4WlSQnw2UmUFkEPYejVYKtfC/q1mLCxWpiqO/Q2/grbJKSGnkkLZo4bH4JCKGp+ESlERqfTnhMcpc4KQW71mJZ/Ch9rdsAsEgqdkWfT/o5DxEY6nmHcueSDaz67M12NViISB3N2ffehM7Pcy2xemsrN+1cxjKrW4MjXV7Be5l96RHkmdbgwuzVFN1/F/FFbQBUx2iIfOxReo86vplUx0PV3lI2rlhHXlPxwe4xlPSJ6snwqaMJTTh48ymJIo215dSX5mKqycfVWIS6tYRASwWRrhp0wt8PNXVKMvbosuh/z5JOtf+UcUSMRiOFhYUADBgwgJdeeonx48cTHBxMfPzR5YVPB0fkSLQ2GajeX0ZtcRlNFZUYGmox6+uxW5qO2UnxCQjHPzzS7aSkxGOPUfBx/T4WtB3MsauxMklXxQ1JGV0m6lNblsv2+24keYe7kLQpSIHqnv8ja/Z/u2S9P9Jc2cCPn31Lld1dwNfDL445V16ALqhruxcOxemws/WLhxhc+j5KwUUz/pQOf4qBUy7zmA2HsnPJBtZ/+zk2k7vAGEFFYr9JTLnu0uMegmU1WajeX051Yenhzoa5sUPj5G8RVCg1Iej8w/EPiyQ4JpqIpARieiYQGBmCTCbD6XSy9OMfyFu1AA4cT+ZHzyA7U0NXggDfixMxC1mcf+u1+AUH/mmZldmLKXryf2TlO6gYMIb9scG0ydu7ZSRIkBQkKOqJn3k+qf3d0tpOh526iiKaK/Iw1+YjNRWhbSsj2FpBpFh3xHlPhzkp/kkIIcluJyUhg/DopON2Usr27aDpl0c62sQdkpwdYbNIPvsRwqITj+tYnYHVaObHZ96ktmA1ADJFAGMuvcEjHVqHsrZmFzftb6BWCkOQRK4ILOfRftNRybs+DWuzGFnxxI3EztuC0gU2JdRdPJ4Jd7yEUtX5ekYuh4vdK7exZftWqtuvZQAhcn8G9epHwsBYDPXFGKv3tzsbpQRayo/J2aiVhdOsjsXim4AUkoI2ogfB8elExqd1iS7SKeOIrFq1ivHjx//p+blz5/LJJ58c9f2nuyNyJFqbDFTtK6GupOIEnBQfZIGhlA6LY31MHyrkB+/KM+XlXBHtz7lJI7vki7zhu9eQXnyPYIP7Al6UFUPWU28RHpvW6Wv9EZfTxe9fLmJ98XYkQcIXLXOmnUXK0K4vHjuUopwNyOZdT5JYCsDWgMmkXf72SQ2WO1FEUWTzvJVsnf81jva2PkGmo8fQM5l0zQWHjRE/3NmoQl9XjUnfHtk4AWcjPNEdvTvgbPydffM/+4bi5YvB4RYyk2Q+BAT6MzfsZ1QyB0ViND9LZ5KVPpYxF888ohlGu4kn372PKV+uJFwvUt9rKHnpPahTH2zfDRCVJCsc9Jk5nZT+f6/We8BJaSrPxVJXcFxOilVSUiuPokUT2+6kpOAT1eMvnZTq0v1UzXuEgS2LkQsSoiSwPXAS0bMe92g31qHsXbuTZe+90qHsGxKXxbn333pCNW0nilN08lTOb7zbEo0LBaE082oPfybGDvbI+juWfEHbE88R3uCu/yvtHUyfp18jLq3z01FtDQY2/7aWncW7sdKKVjLiLxmJkpuJUBoIEWuJclYfn7MRnIw2Mo3g+HQi4nqgUntOCBJOIUfkZPk3OyJH4nicFAmJxj5RZPcfSrbPQMR24acQsZFxhn1MNAQSGxpLcHQE4QlR+Ab7n3RKw2hoZNXD/yVpaS4yCUwaAcM1sxl//RMeSZcUb9vPvF/n0yqZESQYltCfMy47C7nSg+q0VjM7PruHrKrPkQsS9QRTN/5FMsee7TEbDkV0uljx6Xz2rPwZ0dkCgCDzRamNw+V0ILkcSNLR5MoFBJkSuVyJXKlCqVahVKtR6zTIVcoDytHHhIREk7UVU0UJMpvbQZIEDdawZC72X0CysgZREvhZHEuNbAQXXjGX0MRjT0t8nrOQ8jfeZtbaYuQSNMUksG/QKOq00iEiT3ISBSUxwSY0umOfaAzgEiXMNjt2mxXBbkLjasXf1UKY1EQ0jUd1UqoJo1EIoVXwQec0oMWOTrBSp00lesb9pGYOOy57Ogu71ca859+jYs9SQEKQ+zL8vGsYPmeiR+0oba3i2l3byHG5Uy9j1MW8OWBcl6WYD6Wlvpz1D1xHylp3cbDBV4b95ksZdek9J9/96HTSXF+Jvq4cY0M5+tJ8zDUF+LhqiKKRWKEenyM4Gy5JoFYWTpM6DotvPFJwitvZiOtJRHxPjzsbR8LriPyL6XBSistpqqw6zEkxh0DeyP5sjhiFsV0QSiVZGdq0nj4btuFb3QYokCv9UWr80fgGuceIB4UQEB5GUFQ4oXERhMRFHNO8k73r5lP7yKNEV7nbIMtT/Eh56nlS+43tyl8B4G7FnP/R9+wzlAIQpQzhnEvPPyyv6gn2bV2Oz283dbRcbg6ZTZ/LX8XHL7DT1nA6nTRXNdJUWUtzdT2G+gbampow65uxGluwWw047W0dRZ+CPBpJNIB0fJtv16HEGNOH/tpdzFK60xIVUhjfiWfSM2YU064654ScyBJDJQ/89AkXfPEjae3nYFGcL/rhF9AgODAcuOBLkCTJGcEmUoR1yI7Ho/oLnJJAnRRMk+SPBTUSoBXsBNNGpNB8RCcF3JtNsxCIXh6CUR2OXRuO6BeFPCAGbUgs/mHxBEUl4ucf1KkF0YVbc/ntjZc6Bi4GRPbn3PtvJzDCM7VeB/i2aDUPlMsx4osaK/dGGvhvz0ldfhMjiiJrPn4S7Vtf429yb4tFY1MY+cTbBIXFHfX9pjY9TTWltNaXY2mqxKmvQtZWg8pSh4+tnkBnI8GS/qijQw46GwciGyloI1MJjks/5ZyNI+F1RLz8JQeclPLiYn5XlrMiNIUKufsLJkgimeadDNy5kdA9NQhHub8VZD4o1P6odQFo/ILwDQzGLzSUwMiww6IrLqedlS/eQcRXK1E7wCGHytlZTHzwTdTarq/f2LpgHUu3/45DcKFCwdSsCQw8c0SXr3soZqOB3Z/eztCGHwCoEiIwTHmNjGFH7y4yt5poKKuhsbIOfW09rY2NGFuasLS2YDPpcdpaEV0mjiZT3oGgRK70R6EOAHyQRAcKpRKFSolCrUKhkINwkjvxX+AQHTTazLS6FLhwbygyRHx8FaSlqMkq+4B4ubsl8RfXSPJkwzl72tmkDut9Uus6RSdP7JxP83e/MHfRZnTt0ttbeocQO+m/lFXXUn3IAMsQSUuy2kawbxkyWedfGl2ihMkhYXc4EJxWNKIJH7mTQKmNAGcjIVLLUR2VA5glNU2yEFqVYVg04Th8ohD8o1AFRaMLjSMwIoHQyPijttQ7nU4WvPQRJdsXAiKCTMugGZcz9pLpnfCJjx2j3cQdO5cw3+xWSE2RVfNunzSPqEiX5W0h9/5bScxzRwvrwlUEPnQv/Sdd1BHFaKktw9RYgb2lEtFQjcJUh8Zah7+jkWBXY4fE/tFwSQINBNIoBdBMAGZZMMqwNIJ7DiQ04Z/lbBwJryPi5Zg40G3zTkUtWxyJHc8nSxVMNdbQOx+sLXrM7Zuew9aK6GzjmDe9Q6IrMrWTyKIt9Cp1f1nrQhSI/72a/pMuQeOrQ6NVd9lciobiGn746jvq2lMSGYHJzLzqPI8KUgHsWbeA0OW3EUkjoiSwLugcAvteQ2ujAUN9A8bm5r+NYhwdAUHug1Llj0oXgNY/CJ+gEAJCQwmMCCM45qBz6Em21ufyRlEeK6zxOHHXJIXTxCWhFi4O782eN25ksmwDckGiVgria3E6of4DOPuq8zt1ONya6l08tG47c7/+kOEHNpsAgcbZMxl59o2sX7qavMaD3Qk+qBmY3JdhM0Z3yZC6v0N0uWhuqGoP3Vdga65EbK1Gbqx1b3r2BoLFJvyPMv2743iSQLMQQIs89C+jK1azio0/zcNhrENyifiF9OLse+8kLN6z3Tlb63O5IbeiQ4bgQr9inuk/HY2ia/RJnA47FrMRo76BjZ88i++OfAQfOZIvyCLUBPsp8LU3HHMU4wBGSUuTPIQ2ZSgWTQROn0hc6lBq6xxUGM2YBCUOVKhQkRmZxogzx3o8SuspvI6Il+MmpzGf14t2s9gc1zFxNZgWLg5u479pozpys6LTRXNtE40VtbRU16Ova6CtqRGTvhmrUY/dosdlb0OSrH9aQ5JEFEIzQwsMBLaXsmzuoaZRF4mAAlAgyJQIghJBrkQmUyJTqJDL2/9VqlEoVchVKpQqNQqVGqVajUKtRqXRoNRoUGs1qLQa1DoNKp0WjY/7oVAp2fjLKrZW7wEBAgQfzpl9NvH9Do7kdtodWI0WLEYzVpMVm8mCzWzBZrZis1hwWGzYrRYcVpv7YbPisNtw2m047XZcjvaH0/0QXXYklwNRdCCJDiTJATIXmXF6JmuzAWiRfNls7UGRPgCL3vXXcaj2KIZKE4DGNxBdQDC+ISEEhoURFB1OaGwkIbFhHpXWPhIu0cWCso28V9nETufB9spesgquCtfQt9FM64ZP6W3aTLDMLVK21DWErcJwJvSbwNA5Y7skDN9iNfB/O1bgXLOZm35cSEibe3PZ1kOLatglDJwwmZJ9Jews24MFd3GrQpLTOyyVkVPHEp7qudklR8NsNNBUW05rXTmWpgqc+ipoq0FlrkNnc2+gIdLR00B/xCHJsaLCJqixCWrsggaHTI1DpsEp1+KSa3DJtYgKDZJCC0odklKLoNIha3/I1T4o1DoUGh+UGh+UGl/UWh/UWl80Ol/UGl1Hsa4oiry0dxGvNobhQEWA2MIzsTA+JB2rxYjdYsRuMeG0mnDY3P+67GZEmxnRbkZyWMBhRnBYEJwWZO0PucuKQrSidFlRilZUkhW1ZEONDY1kO2LL9l/hlGTudJkiFJM6HLs2AtEvCkVgDNrgGPzCEwiJSjhM36Vqbynrl61hX0tJx3gAX7QMTuvH0Omj0QZ4VozO03gdES8nTK2pgbfyN/CtPhAD7hkuaqxM96nmptT+pAcnH9NxrEYzDeW1NFXW0VJbT2tDI8bmJsytLZiNtQQ17GJIodtZqQ0U2J4YhiB1vTKib2AKhogIzDK7e16IUYGhald75OFYIz0nj0+wnNlh2UTKWjqea5T82ckAjAHDiEkdTmhcdLdEMU4Uo93MxwWr+bRB1jF7RpBERquKucSkJ7JgAymNKwhF3/GeeimQb8WpCKpenHvBuUSmHT0Xf7J8sH8ZLxXYmfvj68zYWIYMaPCHLcmhqDS9iMsYSkBEFHvK9tEsunUjkCDZJ4YRY0aQnJXebfM7jgd3dKUafV0ZzeWF1O7dgUtfho+kJ1BhIlhmJExmwBcLcsGz24BFUmEV1FhQISKglWztBbvHGgHsHERJwISGJgIxaiI6ohiygGhUQbH4hMYRFJlAcHjsMQ23FF0iuWt2sXnTJips9R3PRyiCGTZoCH3PyPJo0Xx34nVEvJw0FqeFTwvW8HGd2CHRLUgiw1VlXJ8Yx8TogSd9Md4y/z1cT7xKYJuIS4CCqX3JuPB+RIfkjkRYrNjbHw6rFYfNht1mw2k7EIWwdUQhnE47YnsUQnQ5EF2HRCEkB4eq2yoUPqjiB1CndjtCgS4N6uoSzMaqg8YJ7ZEZmTsyI8iVyOQq5Ir2h9L9UKhU7siMSo1SrUGpUaPUqFFptCi1atRaLWqdBrVOi8ZX605D+WjR+GhAkNi3aRHmnd+T1vw7gRycZVRPMMXhZxA45AJ6DprgcZXW46HSWMdb+Rv53hBCG25nUiOauLxlI+Nr9tKraTURNHW83iD5sFHsSx4pGGQhDIzsw7QrZqPUeG5eSl5zMf/dnYdfTg73fP4FYa0iIrCxlwa9OgoBGUqfWGJTs2jBSoX94KYSpghkaP8h9J+cdcpEof4Kc6uJLfNXsH/TOoyN+4GDUQCFOpzYjCwGT59EfO8k7HYrVrMJm8WIrT0K4bAacVpNOG1mXDZ3JEI68GiPRMjaIxFylxW5y4LCZUHhsqGUrKhEG2rJ2h6FsKMWjjAG4y+wSwqsghorauyC++GQaXDINThlGnd0RqFDao/OSEodwiHRGUGtQ6HyQa72QanRodT40NpSR9mbrxBXqEdpd1GZ5sfAlz886fkwdrOVbb9tYGvujo6xE4IEKX5xDB87kpQhvU7q+P9EvI6Il05DFEV+q9jMuxV1bD2kjiRVVsVVkWouThmDWnHiG0hLQwXr77iiY25DVayWxBdf7tTOGlEUO9IuVqMFq8mCpc1Iyc4CdtTmYRecCJLAgIh0xl8wBZ8gP4/f8TrsNvLW/4It+wd66lfjz8E27FrCKI2cTHDWBfToP/qUcUp21OfxenEeyyxx7voPUWRk/VYuqV3DsNYtREsHN+82SUu2KYViWX+KtSEgyPAXdEw/Yxo9R3pmYOIfsTntPLNnEV9Wqrnpy2c5Y6e7W6QyREZ2fBiCeLCY2j+0L8rwGCrEpkPqSDQMSunLsBljPCqcdySsRjNbflnF/g1raa3P48B0ZgC5KoSYnkMYNH0SyQO6dh7VX+FyOtldk8vjOdlU2IPQOawkuaq5JDqMHuE9UGl8UWl90Oh80Wh9OnVulSiKrPnwcfze+BadzS1M1njVDCbc/OxJfdcNtc1s+HUN2RV7seJ2tJSSnD6RaYycNva4Ws5PN7yOiJcuIbu9jmTJIXUkIbRwUXAb16WNJlR74vMv1nzyNLpXPsfHKmFXQN3cyUy8/cUuH6VtqG3mly9+otBYCUCgzJezps3o1jsYm9VM3voFOLO/J92wDh/hYL1NlRBBedQUwoddRHKfYR53SkRR5Jfyjbxb0cgOZwKIIumNBVxU+StT2zYTT23Ha82Smt0+QykvceDfEs/OtHisMieCBAMiM5jyn5mofbq/OyCnMZ9bcvcTsWEdt373CwFmCYccdg1PRS/G4DBVdrxWqfTDN3og9Vo71vY7fIUkp094D0ZOG9stU09tZhvbfl1N3ro1GOr2HjaAU64MIqrHYAZMO4PUwd2XUnKKTl7Ys5i3msKwo0aFjRtCGrizz9QunYcF0FRTwqbbryB5p1uvpjLBh9QXXyOpz4l3z1XllrJ+6V/Uf/Tox9AZp3/9x7HgdUS8dCk1pnreyt/Ad/pgDLj/LmqszPCp5uYeA+gZdGLTZ2tK9pB927Uk7HPXTZSlBdD35feITunbabb/HbuWbGbJxhXuIkUJ+kf0Yup/Zh33NMvOxmo2krf2R8TdP5HetvGwHHq5LIaqmGlEj7iYhPSuHT5mclj4tGA1H9cLVEgR9GgsYnb5Mma1rSaV6o7XWSQVeX7DoPfZtDbUo/jwN/KzJlPu494cg2S+nHXmWSQP9vwd+ZFwik5e3ruYLwus3Pbpi2Tt1wNQnuxL+B2PUb6rlvI9m7Cb3Z9VkCnwD+tNW6A/Bll726YEKb4xjBgzkqQhvbp007fb7OxYtI7cNatpqd5zWHeVTBFAZMog+k+ZQM/hfbu9nmVn435u3VvQMS23r7yMV/tkHnO92cmw6Yc34Zm3CDCKOGVQef4Izrj/zROSZxdFkX1rcti4aQMV1kPrP4IYOjCLfpP+PfUfx4LXEfHiEUwOC58VruHjOolyyR2CFCSRkeoybkiIY9wJ1JGIosiKV+4i7KPfUDvBrBZou/lCxlzxYJdfUE1NrSz87GfyDG5FRT9By/QJU+k1ul+XrnusmI0G8lZ/j5A7j97GTYfl3EtkCdTGTSN21MXE9eg8e6uNdbxZsJHv9cEEN+vdzodhFemUd7zGLinY65OFK2MO6WPPx2m3sOauy1Ha0tiRGo5dcCFIAllxfTnj0ukerQU5XvJbSrkpZyeJyxbz3wVr0NrBogL9dWcz7rr/UbW/nG0Ll1GxZzMOay0S4B/YA0dIJA2qgzoS4Yoghg4YQv/JQzttc3LaHexaupE9q1bRXJWDJB6MlMnkfoQnDaDfpAlkjDn5+q3OwOa08+TuRXykj8aJEi1mbg83cGP6lC63z2hoZNXdl5Oyughw64KEP/MkGSNmHPexHBY7235bz5a92/9Q/xHL8LGj/pX1H8eC1xHx4lFEUeTXis28W17HNmdix/NpsiquitJwUcqY455rU7x7HcV33EJMubtWonhgJMNf+oTgyK6ftpn7+w5+W70UI+4Lfe+gFKbPnYMu8NSoAwAwtrawb9W3KPbNI8O05bB2xCJ5MvXxZ5Iw5jKik07sIrmjYR9vFu1lb42c6WWrmGVYTV+puOPnDklOrm4Q9p6z6TnuQvwD3VN9dyz6DMPLX1AwYBzVWncLbJg8gJmzZxGX2fV3wJ2BKIq8s28pX2RXc8fHb5BR7nYwivuGkvXyx4TFuAW2ynYXsm3hMirztuC0NaDVRSIPT6FeY8fVEa7XMCi1L0NnjDmh88fpdLJ7xRZ2r1xFY/muw0Y4CDIfwhL6kzlxPH3HD+kyHZ4TYWPtbm7fX0mJ6E5VZSlLeTVzMEkBXT+NOnvFd7Q+9D9Cm931MUVTezPhiQ/Q+QYe13Fa61rY+OtqdpbnYm1v51ZKcvpE9GDEtHGEJf176z+OBa8j4qXbOLCBLbUcrCMJpZmLQ0xclzaaYE3gMR/LYbey7InrifthEwoR9H4yhPtuZNjZN3SR9QextJpY9Nl8chrzAdChZtqoSWSe4ZmBW8eDobmB/au/RrN/PhmWHYeJL+Ur0mhOnE7i2EuJjDuyQqUoiiws38TXe/aRVpTLTP0qBkkFHT93SjLyNP2xpM2i57iLCAg5KMRkMbey/IErkbXEszMhEKcgIpdkjEgZxLiLpv4jQ9alrVXcunMDPeb9xH+W7EIhQqtOwHn3NYy88LbDXlu4PY8dvy2nOn8rMsmBNiKDJl/ZYXUkvcNSGDV9wlE3MNHpYs+aHeQsX0l96U4k18FuKkGmJSSuH33GjaPf5GEojqGl1JOYHBYeyVnMV63xiMjxo437om1c3mNCl0dB7BYzyx65msRfdiKToDlAjuaRuxh05tzjOk51Xpm7/qO5pKMw+WQdyn8jXkfES7dTbazjrYJNfK8P6qgj0WBhhk8NN/cYSFpQ4jEfa++6+TTe91DHFMyi8amMe+YTfANCusL0wyjYuJdflv5Kq+S+E03zi2fGZXPwDz/xwtyupKWhhoLVX6MrmE+6NfswfYh9ygz0yTNIHXspodEHI0smh4VPts6nZfsmJrVsYohrH7L294mSQJ46E2PqTHqMu5jg8Jg/rZm38VcqnnmHwowR1KvdtQqRimBmX3A2kT26/g64KxFFkc8KV/LVut3c9snHJNa7z8GCEfGMe+FT/IMj//T6wm257Fi0nNrCXfgGxdAa4EurvH3OjwSx8lBGTRhLjxG9OzZnURTJW59N9tIV1BXtQHQdMu1YUBMc05feY8bSf+qIY5rz1B2sqNzGXYXNVEvhAIxTF/NS35FE+3a9cmj+tuVU3n0XUdXtM4WGxzP6hU8ICDm24mFRFNm/NoeNGzdS3j6lGtwptmEDh9BvUuel2P4teB0RL6cMJoeFTwvX8Mmf6khKuSEh/pjrSMxGPSvvv5KUpXkANIQoCHzyEfqOO7dL7Qe3RsCSz35hR81eJAE0KJk0ZBwDpg0/JXLxf0djbQVFq7/Cr+gXetn2/MG56END4mTyjc30rt3KMNfew5yWvYpetKXMInXsJYc5LYfisFtZ9uRN2KuD2R2twyVIKCQZYzOGM/Lcicjkp+7v5nipMdVzx5blZHz1FXPWFiEDGgPl+Dx2LwOnXPqX7xFFkf0bctixZDnmpkbsgUGH1ZEEu3xICo7BpK+jpmg7okN/8M2CisCo3mSMGsug6aNRabpG6rwzMNjauDd7GfOMiUiCjCD0PBIPF6aM6/K1XS4ny5+7magvfkfpAqNWwHbHFYy69K5jer/DYmf7og1s3rOdlnbxOkGCZN9YRowdRdLgtFP6O34q43VEvJxyHAj7v1tRz/ZD6kiihXqmBZi5KL7PMQ232rrwIxyPv0RQqwtRgNJZA5n0yPuotLoutN5N6Y4CFixc0KG2maSLZtalZxMYHdrla58s9VUlFK/+ksDiBfRy7v/L1+yRpdCUeCY9x19+1DRO6d6N5P7vZYqSB9Ckct/tx6pCmX3Jeaft7AyA74vX8M1vK7np8x+IMLgQgcKpGUx+6mO0ur+/RolOF3vX7mT38rW0uezUq60ddSRqSUGIRY7UUotM60P6iDEMPmssGp/u7dg6Fn4p28j9xWYacEcnp2mLea7fuI6REF1JRf52cm+7nvgi9/extE8Ig17+kPC4I3dkuRwu8jfuJmdHDoUt5TgEdy2JUpLTO6IHI6d2Txv26YbXEfFySrOjPo83ivNYbonBzsE7vVRZFTOCJC5OGki839/P9dA3VrHuzstJ2eTWd6iO0ZDwwkukDhjf5bY7bQ5WfPkrm8uyEQUJFQrGZ47ssvkonYHVaeOX8s38VNvIelsM4fpGZpYtZ7phLQpECsKHMnjSDSSmHl1YTBRFVrx6H4Z8BXvDVUiChEpSMKHfKLJmjzllfwedSaOlhfs3zKP3R18webu7nbc6QknMc8/Ra+jRJyo7nU62/7KWfdtzqJEZscoOdj/5oqFXVCr9Rw4its+JtcF7ggZLM3dlr2KxxV2AHEYTTyXrOCtheJevLYoiq957hMC3fkBrB6sSmq+dxfgbn/rb808URUp3FJCzeSf7G4o7ZgmBW/9jYGomw6afOsJ0pwNeR8TLPwK9tZUfyjYzv8HEdkccIu4crCCJ9FVWMCtEzXlJWX97d7X28+fQvPQJvhYJuxxqL5vIGXe90uUiaOAWNJr/0zzqnXoAYtXhzLrw7FOmkt4lulhetZ3vqyv43RyBiYMX2CihgWn+Ji6K701maI9jPmZdWR6bH3uW4ug09Ar3hTxBHc6cuRcSGN31d8CnGr+WbeT7b77lum+XEmCWcMqg+PyhTH/gvWNWBXU5XORv2E3OjmwK9eU4Dul+Cpb5kZHQk35jBp8y5xXAN0WreLRcQE8AgiQyx7eUp/tNIkDd9bOiGquL2HLblSRlu3U8KhJ96PnSmyRkDP3L19fsq2DXuq3kVRV21HkBqFGSFpJEv6z+JA/udVqlEU8VvI6Il38cNaZ6vinZxi/NLnJdBwefKXCQpaxkTkQAcxKG4as6PAVTV5bHjtuuJjG3GYDyHv70efldYlL7d7nNLoeL1d8uYX3BNlyCiEKSMbrXUEaddwbybmilFEWRLQ25fFORz9K2IJo5WFAbhJ5Jvs1cEJvC8IjM445crP74eap3GskPEtx1MpKSSVnjGTBt2L8iCvJ3tNmNPLjyc/q/8xnD9ukBKE7Q0Ofld/52c/w77GYre1fvZPeePZQaqzsUOwEilcH0Tk2n37jB+Ed0T6F0tbGO23LWs9rmjoLECPU8nxrMhFjPdJJt+PZV5M+9i7/J7fRVXjiKSfe9+Senr6migexVW8kt3UfjIUW/CklOSkAsmf370WtU5ik9J+h0wOuIePlHU9BSxtdl2fyqV3YM3AN3181oTTXnRkUyLS6rQ5tEFEVWvn4PoR8sRO0AsxpabzyfsVc/4pFNsq6wivnf/US13T3YLVIZzKxz5xDVs+snyQLkNhfxddlufjNoqZIO1mfoMDNOW8u5UdFMjht8QlLa+sYqfn/kKYqDY2iTu6MgyeoI5lxzMX6hAZ32Gf7prKjYyvwP3mLuz5vQtacLKq6czIxbXj6hc9DcYiTn923s2b+XSmsDCO7nBUkgThtOn/TeZI4fhNa/66XERVHk44KVPFOtpg0/ZLi42L+cx/pOxUfZ9XUsbfp6Vt85l5R1pQDURqqJfOZp0odNO/iaRgM5v29jb0Fux/cQ3L+vBF0kmX360HvswG5XSv434XVEvJw2bK/P45uKfSxu9e8oiAPwp5WJPo1cEJPImKj+yGQySvdupOCOm4gtNQFQ0j+CoS9/TEhU1+faRZfIhh9/Z/XeDTgEF3JJxvDkgYy7aEqX3HmVt9XwTel2FjYL5IsHW2qV2BmuruTsiGBmJQxFqzjxC+/GHz+icF0lRQFuLQWdpGLKyIn0m3x8d/r/FkwOC08ufoeBb3xB7zJ3GiA33Y+Rr3xKZEL6CR9XX93IrlXbyC3e15EKBJBLMpL8Ysjsm0nGmP5dolhbYqjklt3b2NI+8DJJVsNLPWMZHumZQYU7l36J6ZFnCGlxIgKlZ2Yy4YkP0Or8sRot7Fm1gz1791BmrkU6JIIUrQqhd48M+o4f7HWYuwmvI+LltEMURVbV7OT7yjKWm8M6xs0DhNPEVP9WLoxPJzMgkeVP/R+x361HIYLBVwb33sCwc2/0iJ1N5XXM/+qnDi2CUHkAs2bNIq7vyauKNlv1fFuymQWNVnY54pAE9522IIkMVJYzK0zHeYlDCdKc3IXXbNSz+NGnKNIGYJK7Cyl7aMI5+/q53mFex8CG6l389uITnL94L0oXtGoFGm86j+lXPnbSx64rrGLXmm3kVuRjkEwdz6tQkBqUQN9B/ekxLOOkU4OiKPJm3hJeqg/Agg4FDq4MrOaBzGknNW37WLFZjCx/6CoSF+YgA5oD5WgevYd+Ey5k37occnblUGyowHmIeF+o3J+MxF70GzeEkLiwLrfRy5HxOiJeTmtsTjuLKrfyY00ta63RWDl4158oq+HMQAej6puR/e9lIurd6YSiMcmMe/5TfAO6vtVWFEW2/bKOFTvXYMOJIAkMic1k0qUzUGqP7yJucliYV7aJn+v0bLbHdKjVAvSUVXJWsMCFSYOJ7STRqJ1Lf2bXsr2U+bhbGv1ENZPHjidz4rBOOf6/BZvTznM/Pc+gN78jqc59Du4YFMq0V74mOOzkRd5EUaRydwm7NmxnX10RZg4OvdOhpmdEMv2HDyKub/Jxp4bymou5Zc9uclxu/Zieskpe6d2DAaGeGVS4b8sSqu+5h6ga92cqHJlI4sWPkJ9bRH5TKTYOdhn5CzrSY1LpN3IQ0eldP/7By7HjdUS8/Gsw2k38VLqZn+sNbHHE4eJgHUSmcz8X/fghQ1dVuAWoghX4/e8B+k+80CO2GWqb+eWLnyg0utuMA2W+nDVtxlGHZNldDpZUbuOH6mrWWKOwcLBAN1aoY3qglYsT+p7wlOO/wmY18+uTz5EvKLDKnAgS9NCEcs7NV6P2Of5JpV7cbK/YxYon72X66jJkEjT4y2i7+0qmn3tHp63hcroo3JzL7u3Z5DeXYsfZ8bMAwYeMuB70Gz34qCq3TtHJC3sW81ZTGHbUqLBxQ0gDd/aZekL1RceL02Fn+TP/R8zXa5GLUJvck7pRE6mymzrmPgFoUdEzLJm+QweQOLDHv7pY+lTG64h4+VdSb27iu9KtLGi0sdt5MHUxZM+v3PXFV4QZRLcI2oz+THr8Q4+IoAHsWrKZJRtXuLULJOgf0Yup/5l1WOGcKIqsq83h28pilptCMHAwvRJKM5P9DFwYl8bgsPROv/DuWbOcjb9toUrjvnMPcKk5Y9xYMieO6NR1/q04RScvf/EIg9+eT2SLuz13/dgYLnzxO3x9O7ft2WG1k7c2m905ORS3VnXMSgEIUwTSO6kX/ccP/pMI387G/dy6t4D9ottZ6Ssv49U+maQHe2ZQYfm+rey77QaC2wKpzBhMSYQ/BvnBKI9SkrtTTwP7kjY80yu3/g/A64h4+ddT2lrFV6U7+LVFTpEYja+pkVu/fIKJO921G5WRSqKeeYY+w870iD2mplYWfvYzeYYSAPwELdMnTMWWruWr8r0sNvhRx8HNwRcjE3T1nBcTz4ToAchlnX/hdTqdLHj6JfY5bdgFF4Ik0FMZyJzb/4ta542CdDbZZTvY8OBtjNvaroERpsB5//9x5rT/dsl6llYTu1ftYG/uXsotdQeLOSWI0YTRJy2DXmP68XLlWj7SR+NEiRYzt4cbuDF9ikciDaIosvy1x7HktFEZGUqD6qDzIZMEknyj6ZOZSe8x/VF5z8l/FF5HxIuXQ8hpzOeb8lwWtfrQa+Mybv1uIf4WCYccvp6WyeJpV4AHRNAARhTriS8vxNKe09eiRTjQm4mEAMgEkCHQ0bPZBUhIuFxOTDJ3FCTYqWbcuOH0PWNcl63pxb3xvvHObQz+cBlB7XoY309O55ezrunSczDE5GB4cTOBzQ20SYaO52WSgEbQAAICEnJBOOR87FokJCSXE6NgR+poT4YYTTh9emXQd9xgr9LpPxivI+LFy18giiIb6nbzQ/Y6Br31GYPz3WJH21P9eerKB2kO8ozuh7/VztzsPTis5R5Z70jIJYE0mY4599x8Sg9WO93Izt9Azr23MTjXfQ7mJPrw5FX3Ux/a9amQZL2R8aXlBBqqMWHs8vWOhRBRR5+emQwYP/RfqdJ7OuJ1RLx4OQp2p50fX7iBjC/Wo3KCwUeg+OZziZg402M2OKraiLD74KfyzF2f02Fj37zPCM2tAaDVX0HstZfQd8K0o7zTS1fgdDr56dVb6PHJSjQOaNMKFN4wk4hpXT9R+gCO8laixUB0Ss+kPZwOB/t++ZyQ3ZUIQJuvgrC55zJ4+myPrO/Fc3gdES9ejpH8bcupuvNOImvdqZKiab2Z9NQnqLWnV0i4MHs15bfdSlS1u/ugaFIvJj776REnxnrxDEU5aym97Waiq9r/NhPTmPDsp+h8A7vXsE6mLHczBbfcQEyFW+ytaGwK4577FN+AkKO808s/kePZv719T17+1aQNPoOhC1dRdIZbIyFl0V7WzRhNUc7abrascxBFkRVv3Ifx0uuIqrbSphPQ/+8GZrz+s9cJOUVI6TuaUQvXUjytj/v/K/LZPGMc+duWd7Nlnceq9x+l6cLLiakwY9IIND14JTPeXeh1QrwA3oiIFy8dbPj2VZTPvIuvRcKmhKbr5jD++if+sToFLQ0VbLjlPyTvqAWgLC2A/q9/RGRCRjdb5uXv2DLvXcQnXiPAKGJXQP2VZzLx1uf/sedga3Mta267jJTNbi2dimQ/er/2nkeGUnrpXrypGS9eTpCakj1k33w1CQXuzoLiQVGMfPVzAkNjjvLOU4tdy77G9OCTBBtcOGVQddFoJt3/FnIPdQd5OXHqK/PZfvPlJOa2AFDSN4xhr31OcOQ/Szl096of0d//KKHNTkQBys4dyuSH3/vTtFwvpydeR8SLl5PA6bCz7Okbif1mHQrRPefC58kHPabIejI47FaWPX4dCT9uRia51WQDn36czLFzuts0L8eBy+Vk+fO3Ev3ZChQi6P1kqB67m0Fnzu1u046Ky+Vk6ZPXH/z+BMjxeeqf8f3x0nl4HREvXjqB3at/Rn/fw/+YO7qqwl3sveka4krcLZlFw+IY+8oX+AWGd7NlXk6UvI2/Un/3fYQ3ONzTZ2cNZNLj76NSe0YV+HipLctl1/9d+Y+PKHo5ebzFql68dAKZY+fQb+EyiobFIpMg6fvNrJw1iqrCXd1t2p9Y+/lz1Jx7MXElRiwqqLvrImZ8stTrhPzDSR8+nUELf6dodBIyIHn+DlafNZqyvC3dbdqf2PDda1TMPpeEAgM2JdTcfDbTPl/udUK8HBVvRMSLl2Ng1fuP4v/6t2jtYNIIWO+8glGX3tXdZmE0NLHqrv+QsqYYgKp4HT1eeYuEjKHdbJmXzmbNZ0/j8+Ln6GwSFhW03nIx4656qLvNwmzUs/KeuaSsyAegJlpDwiuvkdJ3dDdb5qU78aZmvHjpAkr3bqTw1v87qIMwJpnxL36Oj1/3KEHmbVpE/V33HAzbzxzApP99cMqG7b2cPJUFO8m96RriSk0AFA2PZ+zLn3db5Ktg+woq77jjoA7P1N5Mevr00+Hxcvx4UzNevHQBib2HM2bBWorP6o8IpKwpZuv08ezbvNijdoiiyJJnb8Jx1e2ENzjQ+8mwvHg305/7yuuEnObE9hjA+AXrKDknC1GAlI3l7Jw+kb3r5nvUDlEUWfbynZjn/h+RtTZafQRan76FGa/84HVCvBw33oiIFy8nwNaFH+F87EUC20Qccqi9fDJn3PFyl+s9NFQVsu2muSTmNgNQ0jeUoa9+RkhUUpeu6+XUY+fSLzE/9PTBFu1LxjLp3je6vEW7ubaMTbf8h6Rs9xTh0owgBr32CeGxaV26rpd/Ft6IiBcvXcyQGVeStmAhJZmhKF0Q9+FSlpw/hsbqoi5bc8v89yiaNYvE3Gbscqi89kymfrPa64T8Sxkw+RIyFi6ieGAkChESPl/NsrNHU1eW12Vr7lj0GftmnklSdj1OGZRfPpHJ36/xOiFeTgpvRMSLl5NAFEWWv3wHER8tRuUCg68M2cO3kjXzmk5bw24xs+z+uSQv2gNAXYSKqBeep+eQyZ22hpd/LqIo8vtbDxDyzjzUTmjTCYj338iwc2/stDXsNjPLHr6GxPk7kAENoUpCn3uKjBEzOm0NL6cX3mJVL148zL4tS6i9824i6u0AFE/vy6QnPkalPbmajeLd6yi59aaDA9Em9GDCc5+ddgPRvJw8hTtXUX77bUTVtJ8rk9OZ+MwnJz1TqHzfVvbfcj2xZe0FsqMSGffi5/gGhJ60zV5OX7ypGS9ePEyvrCkM+fV3isanApD8aw5rzhpF6d6NJ3Q8URRZ+c5DGC6+hugqK0atQPMj1zDjrQVeJ8TLX5I6YBzDf11N0eR0AFKW5rFx+lgKd6464WOu/ugJGi74D7FlJsxqgYb7/8OMDxZ5nRAvnYo3IuLFSyez/quXUD/3AT5Wt96D4f/OZ+zVjxxzIauhqYZ1t15K8tZqAMpT/cl87QOikzO70mwvpxGbfnwT4ak38TdJ2BTQ9N9ZjL/xqWM+B9v09ay+/TJSNpQDUJHoQ/pr7xKXNqgrzfZyGuFNzXjx0s1UF+9m901XEV/UBkBRVgyjX/6cgJCoI74ve+V3tD3wOCEtLlwCVFwwkkkPvHXKysp7OXWpK8tj581XkrBfD0DxgAhGvPoZQeHxR3zf3nXzabrnQcKa2kcbnD2ESY+8h1Kl8YDVXk4XTrnUzFtvvUVSUhIajYZBgwaxdu1aTyzrxUu3EZ2cycR56yi9cAQuAVK2VLF7xmRyVv3wl693OuwsevhK5Dc+QkiLi6YgBeLb/2Paox94nRAvJ0REQjqTflpL2WXjcMogeWcdeTPOZMeSL/7y9S6Xk8VPXod47b2ENTlpDpBje+UBznzyM68T4qVL6fKIyLfffstll13GW2+9xciRI3n33Xf54IMPyM3NJT7+yJ65NyLi5XTgaFGO6qIcdt989XFHT7x4OVb2rl9A090PEtbkcEc55gxm0qPvdzgYfxk9ee1zgsLiutFqL/9kTqnUzNChQxk4cCBvv/12x3Pp6enMnj2bp59++ojv9ToiXk4XDE01rL3tMlK2VAHuuo++r39I8calJ1VP4sXLsWI0NLLqtktJ2VAGHKz7qMrZhOypN/Ezn1g9iRcvf8Up44jY7XZ0Oh3ff/89c+bM6Xj+lltuYdeuXaxevfqw19tsNmw2W8f/W1tbiYuL8zoiXk4LRFFk9fuPEvjG92gcYFWCxuH+WVWsltRX3ySx9/DuNdLLac+aj5/C55XP0dkOPwdrojTEv/QyqQPGdad5Xk4TTpkakcbGRlwuFxEREYc9HxERQW1t7Z9e//TTTxMQENDxiIvzhgW9nD7IZDLG//dxzE/dQWXEwQ0gZ7AvWd8v9johXjzCmCvux/X8Q5RHHTwHd/fX0u+b+V4nxEu34JHYmyAIh/1fkqQ/PQdw3333YTAYOh4VFRWeMM+LF48giSKbvn6KwdvuZeyYakpGObBNNXBBaj7Nr0+kZO/m7jbRy2mOJIps+eElMtffwvjR1ZSOcmCc3Mr5vYowvzOFwux13W2il38hXeqIhIaGIpfL/xT9qK+v/1OUBECtVuPv73/Yw4uX04Hm+iqyn5/GsP3PohYc5PkOZdhTq5HPeYNGAkkUy4n+bjqbv30GSRS721wvpyGG5gZ2vjiLrD2PoRXs7NcOZMjjK9Bd8B71BBMnVRP/00w2ffkYosvV3eZ6+RfRpY6ISqVi0KBBLFu27LDnly1bxogRI7pyaS9eThn2rJ2P662R9LdswiYp2dTzHvretZjg8Bgyx56NcP16srVZqAUHQ/OeZtcL02lpqOlus72cRuRuWozltWEMNK3BLsnZlHorve9eTmh0Ar1HTkf1fxvZqRuJSnAxrOAl9jw/mcZab0Tai2fwWPvuO++8w/Dhw3nvvfd4//332bt3LwkJCUd8r7drxss/GYfdxraP72Ro9efIBIkyWRyusz8kuc/QP71WEkU2f/MUA/e/jEpwUk8w9We8Sp9RM7vBci+nC06Hna2f3UdW+YfIBYlKIQrLzPfoMWDMn17rTtu8SL+9z6IRHDQRQNXYl+g7/txusNzLP51TpmvmAG+99RbPPfccNTU19OnTh5dffpkxY/78RfgjXkfEyz+VquK9mL66nDRnPgCbg2fS96q30Pr4HfF9RTkbUM67mnixClES2BxzGYMvfwGlSu0Js72cRtSU7Uf/xeWkO3IB2BowlfSr3sHXP+iI7yvN24b0/VUkiaUAbIq4kAFXvIxac3IDHL38uzjlHJETxeuIePknsnX+W2TseAwfwYoBH4qHP82AKXOP+f1mo4E9H95AVstCAPIVafhc/Akxyb27ymQvpxnbf/uQHlsexB8zbZKW/UMeZ/CMa4/5/VazkeyPbmZo448AFMpTUF3wEfFp/bvIYi+nG15HxIuXbqDN0Mz+D69hcOtyAHJVmQRf9gmRcakndLwdiz4mdfMD+GPCKGnZN+hRBs+8rjNN9nKa4XZiryer5VcA9it64XfJp0Qn9Tqh4+1a/jUJ6+4iiDbMkpo9fe9nyJybEbxiZ16OgtcR8eLFw+zfthLfX68jRqrDKcnYmngtWZc9iVyhOKnj1pYX0Pz55WQ49gCwNWAy6Ve9d9Twupd/H4XZ61HNv+ZgWi/2cgbPffak03oN1aXUfTqXPrZdAGz3HUfqVR8SEBTaCVZ7OV3xOiJevHgI0eVi8xcPM7j4bZSCixrCMJz5Nr2yJnXaGk6Hna2fP0hW2XvtBYeRmM96j7SBYzttDS//XESXiy3fPMnA/FcPFjpPeo0+I8/q1DU2f/kog4vePHieT3uLXkMnd9oaXk4vvI6IFy8e4E93in7jSb3ygy67U8zbvISgRTcSSQMOSc62lBsZesmjyOTyLlnPy6lPY20F1Z9cQV/rVgB26kaQdOXHBIZGdsl6+TtW4fPLtcRIdbgkgS0J15L1n6dOOvLn5fTD64h48dLF/Cl33v9Bhsz6vy7PnRuaGyj66CoGGt1zmvao+xMx91PCohO7dF0vpx45q34ketXthKLHKinJ7n0PWefe0eXnoLsW6loGt7r1oXKVfdy1UPE9unRdL/8svI6IFy9dhLub4CaGNv4EuLsJ1Bd+TFyPfh6zQRJFtv78Gn1ynkIn2GjBn7LRz9N/4oUes8FL92Gzmtn58e0Mq/sagBJZIsJ5H5KYPtijdmxb8Dbp2x/FR7DSig+Fw55i4NTLPWqDl1MXryPixUsX4NZXuJIk0T1GfVPERQy44qVu01co278L53dXkOIqBmBz2Ln0u/I1NFqfbrHHS9dTUZCN7ZsrSHUVAbA59Bz331zn2y32/FEvZ0vwWWRe9fZR9XK8nP54HREvXjqRPypONhJI9biX6DvunO42rf3u+DaG1X0DQLEsEfl5H5GQPqibLfPSmUiiyNb5b9Bn1xPtUTA/ykY+R/9JF3e3aW4F4U/uZGjVQQVh55wPSMkc1t2meelGvI6IFy+dhL6xlpKPrmSAeT0AOZohRF/+MaGRcd1s2eFk//49catvJ5hWLJKKnD73kHXO7V69h9MAQ0sjhR9dzaC23wF3XVD4fz4hPCapmy07nD1r5xOx4hbCaMEuKdjR63aGXnCf9xz8l+J1RLx46QT2rv+VsGX/RzjN2CU5O9JuJevCB07ZLpXG2nKqP7mcvtbtAOzwGU3KlR8SEPLnSdde/hns27KMgN+uJ+pAp1Ty9WRd8tgp26XS0lBD2cdX0N+8EYBs7VDirviY4PCYbrbMi6fxOiJevJwEDruNbZ/ezdDKT5EJEuWyGOyz3ie138juNu2ouDUlnmjXlHBRRwiNk9+g94gzu9s0L8eBy+lky+cPMKT0PRSCSJUQgems90gbOK67TTsqkiiy5fvn6J/7Aur2VGbNhFfIHDOnu03z4kG8jogXLydIdck+2r6cS0/nPgC2BE2nz1Vvo/MN6GbLjo/C7HWo511DnFTtVtmMu4Ihc59FoVR1t2lejkJtRaFbTde+G4Bt/pPoedV7+AUEd7Nlx0fJ3s0IP15NolgOwKbISxh4xUuo1JputsyLJ/A6Il68nADbFr5Hz60P4ydYaEVHQdYTDDrzqu4264QxtenZ++H1ZOl/A2CfIh3/Sz8lOrFnN1vm5e/YueRTkjfeRwAmTJKG3IGPMGTWDd1t1gljNRvJ/vBGhjbNA6BA0QPNhR8Tl5rZvYZ56XK8jogXL8eBsbWFvA+vY4hhMQD7lBkEXPoJUQmnx4a9/dcPSNvyIH6CxT2JNet/DJ5+TXeb5eUQLKY2cj68gaHNCwD3xGXdhR8Tm9qnmy3rHHYu/YKkDfcQiBGzpGbvgIcZPPMGbyHraYzXEfHi5Rgp2LkG7YJriZVq3JLV8Vcx5D9Pn3YpjOrS/bR+MZdezjwAtgZOI+Oqd/DxC+xew7xQtHsTip+vJkGscKfRoi9j0OXPn3YpjLrKIho/m0vvAyknv4mkXfU+/oEh3WyZl67A64h48XIUbCYL6z56gNGNn6ASXNQSQm7K/UTGeU6dsq60CkEhoPPzjCCaKLqo3LGEWMN2ZIKEQfDH/4yrGDqj84ajeTl2XE4nq957iFF176MWHDRIQeQk30NUwnCPrC+KInXFlah0StQ+Wo+tWZm9jNjmrcgEkVbBF+WwSxh9/nnIvNGR0wqvI+LFy1/gcroo3JzLto2r6NX6OYNk+wFYJfZntTAKSVB6xA7BIeFb1QyWEo+sd2RkBISlcvGTj6EL8Kpheor8LVvRL7yVLNkeANaLfVgpjMUldH0kTmGUUOtNyExVILZ1+XrHgkwRSFzvEQydcyZx6YndbY6XTsDriHjx0o4oilTkFJO9cQd5tYUESIVcIvyGn2DBLKn5QZqFQZ6OIBM8Yo+rwYizPgcki/sJeQgcsrSAgEwm6/K7QwkJ0WFFdBkAkMkDGDT7AsacP7NL1/2343K6WPjao4w1fEigYMIqKflBmkmLvE+XnoOSxYmrSY/YVonkajrkJ0pQuK+tAgJyuRxB8Mx3ASREpx2XsxVwdTyr8oklqf8Ihp09ldDYcA/Z4qWz8ToiXv711BVWsWvNVnIrCjBIJmSSnbHSOsbKsgHIlaXhc+EHJKR5ZlhdQ3ktPz/3Mm0NewFQqEOZeOX/EZUcx65V28gt20+Tq7Xj9QpJTkpAHJkD+tJrZCYKVedHayRR5Psnn6Fy706kdsfIL7QXlzz5CD6B3uhIZ1OwNZvKX+5gvGwrAHliIvZxL9Jvwhldsl5zTSObflpC8Y712Izlh/xEhm9IT3qOGMug6WPZsWgDa/dvximIyCUZo3oMZsyFU5ArPCPct/67d9CvWkp5mw9mux44sCUJ6AJT6JE1mmFzJuEb7N0D/kl4HREv/0r01Y3s+n0be0v20eDUdzwf7KrnYtlCQgUDDknO9qTrGHzJox4pSBVFkZUf/0zOsq+RJCsgI67PJGbdcS1qnfqw11bnlbFr3XbyqgtoOxAxATQoSQtNot+Q/iQN7oVM3rnRksKdO1j+2luYzLUAyGR+DJp1MWMu9NaOdAZOu4MFbz7PCP17RAotOCUZK7RzGHfLm6i1nVubYdS3sXneCgo2rcHUUgiIHT/T+CeROngUQ2dPIjDicE2ShuIa5n37E1W2BgDCFUHMPmc20ekJnWrf31FfVULt51cTZShlU0t/io0+OB3Nh7xCjn94OukjxzH4rLFoPFTT4uXE8ToiXv41mJpbyfl9O3vyc6myNnSkOQRJIFYdRCqrGWtfDkCpLA7nrHdI7TfKI7bVFFYw7/mXMOsLAFBqo5h6wy2kZR25JVMURUp35JOzeSf7G0qwYO/4mS9a0qNT6D9yMDG9EzvNVtHl4qcnHqNi3z5E0QyAT0gvLv7fQ/iH/LPE3E4lCjbvZv+vDzBDthqAMimCxpEvMGhy56XA7FYb2xauIXfNKgx1ewFnx8+U2igSMoczbM5UIpKjj3gcURTZ/PNqVuasxyE4kUkCQxP6M/GSM1Gou75+yq3I+jx9c19AK9jZZ05ho+tMDPUVuOyHpJMENcExfcmcOIH+k4ejOEXl7v/teB0RL6c1drOVPat2smfPHkpN1YjCwVM4UhlM79R0fENMhK+/mxipDlES2BJ5If0vfxGN1qfL7ROdLha98zX71v0IkgOQkzx4Bmfdcvlxp1hcDhf5G3aTsyObQn05DuFgLj1Y5kdGQk/6jx1MaGJkp9ieu3kdG979GIOpDgBB5sOA6Zcw/lJv7cjx4LDYmf/2awzSv0+SzB1p+l01lSH/9w6+/kEnfXzR6SJ7xWZyVqykqXxXe7TNjVwZRHSvoQw5azJJ/dKO+9gtVY3M//JHSs01AITI/Jl51lkkDOhx0nYfCxUF2Zi/vYaeTncx+TbdGGQD7mH/2i3UFm5FdB0ssBXkPkQkDaL/1Emkj+zn7bw5hfA6Il5OO1wOF/vX7yZn5y6K9BV/uyH7RwWy/dO7yar6DLkgUUsYTZNepffI6R6xs2x3Ib+88jI2YxkAat94Ztx8G4n9Tv4ibjdb2bt6J7v37KHU+NcOWL9xg/GPOLmNzm6zsvCZhynfV45LNAKgC0rjgkfuJzgq9KSO/W9g//pscpY8xRxhKQpBpE4KojzrSYZMv+SkjiuKIvmb97Bj0TLqCrf9YUP2JSJ5EP2nnNEpG7Ioiuz4bSPLt63CigNBgoHRfZhy2QxUuq7XN3E67Gz94iEGl76PUnDRQBDVY58nc/TZ5KzcQvbyFTRV7EISO88B89K5eB0RL6cFoihSst2doshv/KsURSr9Rw7qSFGU5G5F/PFaUlzFAGwNmErPK97yiGCS0+5g4WufUrR1IeAEQUnPkWdz5vUXI+uCoj9zi5Gc37exZ/9eKv+QkorThtMnvTeZ4weh9T/xCFDOmkXs/PRbGo1NgIQgaOk35SLGz53tvfP8C6xtFua99x6Zho/oLSsFYKNiJBnXf3xSE5DL9xazZcESKnM3/SlFERLbj8wJE+g3eViXpCha61v45fOfKWhzF7sGCD6cNeVMUof17vS1/oqCXWtRLbiOBLESgM0hs8m84jV0vgHYrTa2/7qWvWtWYajdw1+lpIbOmUJksnfyb3fgdUS8/KM5atFm1kCSBqd1bIYup5Ot3zzBwILXUQlOWvCjdPiTDJgy1yP2Fm7NZdGbr2C3VAOgC0hh5h23E9PTM4V++upGd+dN8T7qDynSlUsykvxi6Nu3L+lj+qHUHH9xrtloYPlz91FSqMfZ3tWjDUjh3PvvJTwxqrM+wj+e3FU72LbyVc4TfkMr2DFIOnIzH2D4uf93QsdrKK9l009LKM3egN1cdchPFO6izdHjGDJj3J8KnruKnGVbWbx+OWZsAPQNTWPaf2adlKN7rFjNRnZ9chvD6r8DoFKIwnjmG/QacrDbyKhvY8v8/2fvLMPsqLKv/6vr2u7uHU/HjTgJEQIEdx/DdYABhpkBBh10kBncnYRAnLhbJ+lOd6fd3a9r1fuhOp0E4nR3Mu8/63nyIbfvrXNu3ao6++y99lqrKdq6HntbMYeRdM1JpI48h7HzZ/6KpHsWvYezgchZ/M+hpbKRPet2UFBRRKt4sI1VLSlJDYpnSNYQMo7QxlpXUUjH57d0O5Xu1Y8h9oZ3CYtK6PU5e1xuFr74DtW5KwARBC2Dp1/JubdcctoyBnLb8k7yq4volOzdr2tQkR6cyJCRWaSNGXDSrZm7ln9J4Tc/UW+1IH9XDQOnXM7M31/+fzo74mi3seDdD0i3fspohezYvEcxlOibPyAyLvWkjmVp7WTr9yso2bERZ2cZh7exppE+5hzGXnT62lgd7TZ++ngB+e2lAJjQMXfqLPpPzuqT8fdt+IHwVfcSSatsxxB3IyOuf/ZXUvht9S1sW7CC0l2bukukMg60LU9i9IXT+0zR+P8qzgYiZ/E/AWtzJ3vX7CCvuIB678GUs0ISSDRGM3jQIAZOHo7W+OuatCSK7PjhDQbseRpTlzjZvsEPM+rie/rESCtvfTY/v/s6vq52R1PYAOY/eO8ZkyUQRZGa3HL2bN7F/sbS7p0sgAEt/SJTGTpuOPFDUk44kOhoaWDbKw9SVC7i8clCaFpzEvMffLDPsj9nEnJW7GDbxne5XFhEoODAKWnITr+bcVc9gkJ5YoGey+5k+6I17N+0Dmvzfv4XhL32r9/L4jXLurOV/YNSOP/6izD2QYDU2d5C8Qd/ZKRlJQAlylTUl75DYv8RR3x/fUk1Wxcsp3rfFryuxoN/ENQERQ9i4OSpDJ99Dhrt/1/eUmcCzgYiZ3FGo2xnIZvXbqTUWoN0gHApQaw2nEGZAxgyZQTG0KP/3m1NtVR++DuGOTYBUKAeQMBV7xKb0vt1a4fVwcLn36S+aB0gISgMDJ97PZOunnPGZgYOSNvn7tpLUVsFHcE+ahKCKDSnIqFgrNjMjQNGMDru+NbskiiyY+HbVC3fQGWHA3nhVJMx/iLm3n5tr/BhzjRYmtpZ+OGnxFm/Z5oyG4BCIQ39Ve+RkJF13M97nA7WfvIfStYX4PS2wCHcJ5UmjLiBYxl94awzWurcZXWy7OMf2NO0HwTQo2XWuGkMPW9Mn4yfvfQDUrY9RhA23JKa3Rl3MfrKR48ZAJbsKmDX4pXUFW5HPKSEKSgMxA2cxLQbLz+jAr7/dZwNRM7ijIPf5yfn5x1s27WdhkOEisKVgQxI6UfWlFEExx6/I2PPys+J3/QwoXTikZTsSvkTo6/5O8o+0BLYvXwz6z55C7+3HYCg6GHMf+ju/4lOkry2Er6qzGN5p4ZK6chZm1ixjhkmB9ekDmVw2LG7fBqqS9j/9gPsqzTj7jofGkMc8+65v0c6hM5EiKJI9uLNbNn+FVcoFhEhdOCTFGyPu5lRN/wTtebofA2vx8XupR9TsnAD7XYVLqGFA6UXQTAS5NKT0FyLO9qJ8bxzGX7JHwkI6ZmW7N5E6bZ8fly+mA5RLgOmmeKZd+18AqN6n4vRUldJ7ce3MNQlK9XmaYYSeu17RCUc+/oTRZH89dnsXvEzzeXZSF26OaAkJG44E6+6nLSR/Xt59v//42wgchZnDJwWO9t/2sjO4j3dqVyFJJAZnMz46ecQPzjlhI5js7ST//5tjO5YAkC5IhHxordJHTK+1+bePXabhe+ee52Wii0AKJRmxl56C+Mu7h1p7p5CcXslX1TtZVmHijLxoJiVEh8j1DXMDlDTUtnIerWGAk0mvkNM/5KoY3awlysTh5AZnHzE44t+P1u/fIbWDXsoavcDsmZK8oi5XHDPTb0iS3+60F7bwoKPvyTcsYR5SjkTV0kM7gveJmP45CN+xuf1sHflF9T+8C2uKh0NAXq8HAzCVaoI4gZmonMVYlifTVTDwfKZRwm1gyIwzTqP4Rf/AVNg73d+nSq8Tg8rPvmRnbX7kAQJLWqmD5/EyPMn9L5nkiiy/buXGLzveQyCG6ukZ/+wxxl5wZ9OqETr83jZ9M0Kcn5edBgp2BCUxog5FzFy3qQzNtN5puNsIHIWpx2tVY1sXrKOnPoivILcVqdFTVZcf8bNmUJQzInvmPK3LiNo+V3EHBAni76arBte6BNxsq0LV7Pl63cRuzpGwhLHMv+hO89YtdHyzhq+rNzN0nYFReLBtkUFfrJUNZwfpuOypFGE6w+ef7/Xz4aVa1nYuZeckEgK1Zn4hYMZpjRFLbODRa5MzCI1MP5XY1buz6bh4z+TXR2NwyNnR9S6KM77091kjj1+uedMhiiKbP1+LVv3/sTFwk8kKWSewdawSxl60yvojYd78vj9PnLXfkvNwq8I2F5FTVh/Gs0+RMnW9Q4FhuA0pt5wA/3GHe5zVLJ7LUXffoBx/W4imr3dr7tVUDskisA5cxh+0e8wmIJ68yufMqr2lrJo0Q+0dN0rifooLrj6EkLjw3t97JqSfdi+vJV+vgIAso0TSb7xHYLDT5yzlbtmJ1u//xZLUx4HslUqbTj9zpnN5GvmnZWVP0mcDUTO4rShIruITWs2UmKp7uZ/BCmMjOo/nJFzJhyReHo0uF0Osj96kDF1n6EQJOoJp/281xkwbnZvTb8bHQ2tfP/cq7TXyRwA59boKAAA1DxJREFUhTqISdf8iRGzJ/T62CeLamsDX1fuYnGbSL7/YKAgSCKDVdXMDVVzedJIoo3Hr3+X7tjPqi2r2RFmoSgskSJVBpJwsO7eT1HNnBCBK5OGk2A+mGXxetxs/+gR7LtL2demQpLcgIK4gedy0QN/6LM2055Ec1k9C774hkDXOi5RrJbFyQiladrLDJ50Yff7RFEkb8MPVC78jJBN+xH8QRQkpNGusdDN/xB0xPafyLQbryAi8dglF1EUKdq5ktLvPiZgQw5hbQf1MZwaqMuKJWTuPEZccAtavak3vvopw+fxsubzpWwp340oSKglJVMGjWfcxVN73CPpV2N7Pez87G+MKH8bteCnhSBqJz3H0GlXntRxavZXsO6Tr2ko3dKljCzzSOIHTWbqDZed5ZGcIM4GImfRp/D7/OSu2snWndsO43/EasMZN2YsAyYPO+mHUNm+bfD970kRKwDYHjSH/je9gTmw92vP6z9fws4fP+yuHUelT2b+n2/D0AeaCSeKensTX1fsZHGrl1xfPJJw8PwOUFYzN0TB5YkjiDefGs+gubyBzUvXkm0tpCZRR1FIMiWqtO5xBElkoKqGuSEqrkgaQYxJFuwqyl6L+9uH2VKTgdUtXwtKTSjn3nIng6aM/I3fum/g9/nZ8PVKthesYp6wjP4KWcxrp3k66Tf9h8CQcERRZP/WJZQv+JTAjXmEtvuoDUukOCoah/Ig/0OpCSFz3GwmX3fhKbWLiqJIwZafqPj+M4I25RHScbCrxqEVqB8RT9j5FzJ87o1otGdOO2pdQSU/fLeQRp+cIYvVhHHh5RcTkXZsv5ueQMneTah++ANJYjUA20PmMfCmf2M0B53UcSytnaz58DvKdv3cnREFJaHxIzjnqstIG3GWR3IsnA1EzqJP4LTY2b54I7uK9mKR5EVbIQlkBCUyYfok4oecGP/jUPh9PrZ//ndGlL6BRvDTRgCV459h2Mxre3r6v0JzVQMLnn8Za3MeACptGNNvvuOMWUCbHK18W7GDH1vd7PXFIXIwU5GpqGF2MFyRmEVyYFyPjenosLHtp/XsKsmhzeikIcHE/pAUylQHNTIESWSoupq5IRquSB6FWdKS88FduAvr2dlsRuriBkWlTWL+Q7efUQHdL1G/v5oFX3+L3ruTqxXL0QpeOiUjJWOeZMScWyja+TPF336AeUMu4a1eRARK4gZQEWrAdwj/Qx+QwrDZFzDmgqk91kkkiiL71n9P1YIvCN28nyDrQdEum16gcVQykfPmk3Xetag1vS/Dfjz4fX42fv0zGwq34RNElJKCc9JHMunK805ax+Zk4XLa2fPh/Yxu+BKFIFErRGKd9W/6jZl50sfyebxs/HoZuat+OpxHEpzOiLkXMnLuWR7JkXA2EDmLXkVrdTObF68lt6EQDwf5H0Nj+zN+7snxPw5FXfl+Oj+/mf5eORDYbRhPwg3vEBrZcwvrkSCKIqs/WEDOyi+6zMMUxA+awYX3//60lxTaXZ18W7GdH1vs7PLG4ecgdyNVUcfsIB9XJAwlPbh3dTz8Xj97Vmxj2+7tNPk6cJsl6hPMFAanUa5M6n6fEh/DVDWcH6ZncEMbUT8/w7raLNqd8iKtUAUx6Zo/MmJO3zggnygOlBR2lG1mJqsZqZAN13J0I/GNvZ2GVYswrNtNZJNcanGpdeQlDqTJ5EeSDni+KAiOHcaEyy/tdW6M3+8jZ9VX1P7wNeFbiwmwH3yMW4wCzWPSiL7gMoZOvwKV+vRqZDSX1bPwq++p7dLciVAFc9ElFxHTv/e1Z/I2LSZ05d1E0SyLoMVex4gbXviVCNqJQBRF9q3dxbbvv8PSfJZHcjycDUTOoldQubuYTas3UHwI/yNQkPkfo+aeHP/jUEiiyI4FrzEw5xmMggu7pCMv61FGXXhHr4uT1ZdUs/CFl3B0FAOyR8Ws2+4mY/SgXh33WOh0W/m+Yhs/NlvZ4Y3Fy8GFJElRz3mBHq5IGMSAkJNT7uwJiKJI+Y79bF6/iVJbLQjgDpRoSghhX3AqlcLBoFGFl+HKKsbXb2b0rnz2VpsRu8pdoQljuPjhu84I0m/V3lJ+WLgQlT+fa4QlBAgOHJKW5dIkAjaUEFN/sJulxRzCvvT+OMQ2kOSgRFDoiO03kak3XH5aBO18Xg97VnxGw6LviNxehsl58JHeYVbQOi6T+AuvZNCUi1Eqe7/N/UgQRZFtC9axOmcTXsGHQhIYk5jF9GvmoNL2bneVpaOVwg9uY1TnMgBKlckoLnmH5AGjTvmY1QUVrPv0KxpLtx7GI0kYPIVpN15GSEzvE3TPdJwNRM6ix+D3+dm3ehdbd2w7TP00VhPO2DFjGDhl+G8iobU0VFPz8e/IcsitsfnqQQRd/R4xyf1+89xBfgC6HBZctk5c9k6c9k48dgtOSyd560poKtvd9SBREtN/ElNvOh9TUBh6U2CfPrRtHgcLK7fxQ1M72zyxeDiYiYkVGpkV6OTy+AEMDTtzXEWbyurYvHQ9+5qK8XW5IYvBKlrSothhjKNaOshPUUseRrqz6VdWStD2IlQuv9wGfcktjLvk9LRBH2g7za7JZiKbmKLYDUC+N572DQZCmuRMh08BeYMG0GKKwm2vopv/oQ4hY9x5TLnuojOm3ORxO9iz9BOaflxI1K5KjK6Dj/e2QCUd4/uTePE1DJhwQZ+WE9w+D3afg/raelasWEGdrx1RBTq1ngEDBxKXGItBpcWo0mJS6zGo9JjUBjQKdY/NM3v5JyRv+QvBWPBIKrLT72DUlY//Jg0iS0sHaz46wCM5kBlTEZowgklXX07KsMwemfv/Is4GImfxm+GyOtm+eAM7C/d08z8ESSAzKJHx0yaSMPS378Z3LvmA1O2PE4wVj6RifdgVhA2cit/lwOuw4XHY8Dvt+BwORJcDv9OJ5HQhud3gkv8p3N7uf0qPD5XHj8ojovaKaLwSWu+vx7XoA9mRnolbkAMrNSFklVcRbmk87H0eFXjUAl61Ap9GgU+jxKdRImrViFoVklaDpNWAToug0yLo9Cj0OpR6A0q9AZXeiMpgRG0woTGY0JoC0RkD0JkC0RkDEbQGljflsqCxhc3uGNwczChFCc3MNNu4LD6TEWH9zugatKPdxtaf1rOrNAc7si27UlIQnBRJWXoQa33B1EkHOw20kotBthwyi3OI2lNFZPRoLnv8vj71/qgrqOTbb75F8pZwtWIx4UInXknJ+vpBRG5sQZAkKjOCae83mfbmDtz26u7P6sxJDJt1IWMvmnZGK8l6nA52/fQerYsXEZNdg/6ggCstISosEwaRNP864odPxOF3Yfe5sHud2H1uHD43dp8Hh9+Dw+fD4ffh9Ptw+kUcoojLL+IUwSVKOCUBl6jAJQq4JBUuSYlbUuFGjRs1HjSHlRRPBgr8aPGgwYMWLzrBh1bwoxP86BQiOkFEp5DQKwT0CtApBQwKBXqlEr1CiUGlxqBSYVCqMai0iDYrjrVvM8i+F5PPSY2QTNSlbxKfMuC3nWu3h80HeCRd5pcAhuAMRp1/EcPnnHNG38O9gbOByFmcMtpqmtm8eB059fsP4X+oGBLTn/FzJ5+Q+qkoirQ1lNNcVURnTRm2uio8jfWITS0oWzvA6SdggMAEs9zzX+qNpm5rEGG1nb351fAqoTi2P5Uhii4uiIoQj5n02j1ovX40XgmN77iH6REsu2w0b065GaviYGkiTGxidOdexna00F8fQVBMCmEJ6YTHZZz2Ov+JwOfxsmfFdrbt2UHzIRLaCbpIgscmstHkYqU1gCYOXkNGycqc/O9J2dbK3Dv/3OslMVEU2fztatbuW8tItjNLsQ2ACl8k5dtC8WhF/JMm4iSV6pzN3Sq6oCA4Jovxl19Kv3FDenWOPQWbx0GVrZ5qeyuVnc0UVpXQbHdjUZpp04fQpg6hXRGEX+g74TlBEtEKbrR40eBFLbqRJAmvoMYraPAIWlyS9rAusN6GQvITRAdhSifhKi8RaolojYponZ5YvZl4YygJ5igCtebjHksURXJX72Dbgu+xtuR1v67SRjBg0hwmXT3vtPPO+gpnA5GzOGlU7ilh8+oNFHVWdfM/AgQDo/oNY9Tcc9CZZBKW02GhqaKA1upirLUVuBrr8DY2ITS3oW6zYuhwEmDxo/b/egwJiZqRkYxOKSZIYUeUBNY2DyZ0fRt+hYhXLeDVKPCp5cyDX6uSMw8aDaJODVptV/ZBh0KvQ6HTo9TrURmMh2QfzGiNZrQGM9qu7IPeFARo+OH5/9BYugEAlS6SeXf/mZThh6dO/X4fTlsnLnsHLrtc0nE7LHjsVrwOG16HHa/Tht/hwO904Hc5EZ1OJJerK0vjQXB7ULg9KNw+lB4fSo8flceP2iNiCzLw5p9uYnOIrAgbLLYysXoL09dtYdCWUhQIvzpvogAWkwJ7kA5PiAkxLAhlZAS6qBhMMYkEx6cSmdgfc9CZoW8giiJl2wvYvGEzZV08EoAQhZlRg0fgGW7my6r9rPdG0irIQUmWbSeTflzO4AHnM/eu63pl92ht6eT7d7/C4djG5cJyQgU5lb7CkoUvaiiJE64gd+V2avdvBEnmhQiCjpj+5zD1usuJTOn91tMTgV/00+hoocreTI29nVqnlXq3h0aPSJNXQbNfR6tkws7JaYyoJQ8aQc48aAWfnH3A15150CskdArQKZAzEEoBfVf2waBUyf9UagxKNUaVVi61qLUYVXqMaj0mtR6tQnvYbyuKIjt+2MDKPevxCX60qJk1/lz6T8vC5nXg8DmxHZql8bpx+L04fF4cfi9Ovx+H6MfpF+V/ooRLpCtbI+CSFLglBU5JhVtS4pbUXZkazWHcqxOBHgehgpVwpYsIlY9IjYJorZYYvZE4QxDxpghijOGoFHL2pzq/jLWffk1T2bZDeCRGEodMYeqNl/1PWEP8FpwNRM7ihCD6xW7+R52npfv1SMzEanwobXlIzXIWQ9fmwNTpOYwIdzxYjAK2IC3uYBOO6FDSg6sZqigBoFhIxDrxrwwcNwu11tCracuy7EJ+fPV5fF3um5FpE7n0L3f1OcP9m7L1PFYp0UkgCsnPtcYSbtZGYKutwFZXibO+Fn9TM4qWdjRtNgwdLgKsIsoTPOVODVgD1TiDDfhCAxHCQ9FERWGIjiMwLoWwhAzCYtL6NLvSVFLH5uXr2NdU0s0j0aNhWOIgsmaO4p85X/KN9hz8ghqz1Mm83d+QXqTmsscf6VHhqP0bc1m84ksmsorRCjkTV+aLoiTlWhL6Xcimr7+ho34vILfEKtXBpI89j6nXz+9T/sehWYxah4U6l4MGt48mHzT71LT4DbQReMKlDi0uQgQrYQpn1+IpEK1Vdy+e2vY2Gv7xd1Jzm1GJUJkRyOCX3iY2Lat3v+gv0FhSy7dffE2zX86KDgpNY97Nl54yAf5E4Bf9WF1WNi59E13jcloMQdToIigx98cWnECLX02zX0ebFICTE3tWKPATjIUwhb07uxKGhL+8Fn9pEfrWVnQtDlQugbDEkUy65nKSh545vK+exNlA5Cx+BVEUaazMp65wN62FhbQ3aqhRqbAqupj/kkCyVUF67m6CqguOeSy3CiyBKpxBeryhAQhhIagiI9FHxxEYm0xoQjoRcZlo9AZZHfXzvzGi8j00gg+HpCUn/U+MvOLRXl8QRVFk+dtfkr/ua8CHoDAw7vI/MG7+9F4d95doc3Vw357VLHPKuirxQiOvZkYzPvr4KX6f10NrXSkt1UV01JThqKvB09iA1NyCqtWCrt2BudODwX3cQwHgF8BiVtAeoqHVKKH1SghqNQq1BpVai1KtQeiFtLgkijjtTtxeN+IBszdAMAYgXTCXf4emUqVIAGBU52YmLN7AtPP/wOgLp/ymcX0eL0vf/46O2gVcpliFTvDiltQss4+iOX4O7Xv2oThEG0LUx9KaNZCG0bGg+HV26jdD9ILowCd6cUngELV4BAMWzCeVxRAkkQDBKi94SjcRaokojZJonY5YvZk4YwgJpkhCtIHHDfL9fh+rXnmQiA+WofWBQwudf7yEKX/4R5/yGnxuL0s/WMiuBrmkEawwcfH8i0/Yj+q3oKm2nJrP72S4Xc6Y1gmRtE55lsGTLwagw2WhytYgB4hOK/UuJw1uP41egWa/hlbRSLsUcMIlJYNkJ8jfToCvg2CvnUS9lqzEODIDIukXlECw7vR3k/1WnA1E/o9CFEWaqvdTW7CLjpJ8XJXlCNUN6Bo7CGlx4wlOpGzoWEpDlHi7dqcaSUl6s4fU7A3oOxoPy2KIYUEoIsK6SgAJBMWlEp6YSWBo7Ak9oPK3LsO44n4SxRoA9upGEX7lG8Qk9T6TvKOhla+efA5bSz4gm1hd+ujDhCf0raPp4sotPFTmpIUQBEnkioAKnh46G6O6Z7Mxts4WGisLaK8uOWZ2xS9AcSzEt0CAs0encMrwKiF7UBjbL5rBgsi5SIKSYLGVedu/ZpAliSsev++U6upNZXV8//HrTBN/IEMhBxubbYPZ7RqNs60ewX9Q/8MS3J8NIyaQn5bwm7+PRnIRTCsmbKjxIqLAhZ5OgugUgo/7+WNlMWL1gcSbwokzRqJV9WwgX75vMyUP3EVcheykWz44jJEvvUtEfN92fuxfv5dFq5fgwI1CEpjcbywTr5jRJ0HRnpWfE73pMSKRiew7A84l+ZpXT0jLyOP3UmdvotreTI2jgzqn/WDJzKeixa+nVTLjOoHsSiAWYpSdJKg9JOlVpBhMZARE/E8FKWcDkf+PcViwUVqAq6LssGDjl10iEgKN/cdQkpFO7SG0+QBRS7xCQViCQEhi0mFZjN+KzrZmCj+5h9HtPwHQQhCVox5n+Oybe10XBGDX0k2s/+TfXe10CtLHzOf8u67v0w4Hq8fGn/esYIFd3s1F0sKL6UHMiDs9Kq1ej4u1b/8V46eLCbbI5YfGYAXVSQZwe1B4fKg9IopjPA0kAbxqBX6tCkmnQaHTozKY0JoC0BrMKIQTzyBIEjg6rGhyC0irltM5LjVsGRHOJ/P/QHnAQAAmtK5h3LJcLr79z6QMO7GWblEU2fTtMjpz32COYhMKQWK3dTAbmwfgcTcC/q7vo8Md1x/p3AGI0SdXfvGLHlxeB3afB6sfOkQNraKJFoLp4NjBhgkr4bQRIlgwCC5a/DqcGHBgIEFp5cG0dCbHDjup+fQUfF4PPz97BzFfbkDtlxVbnfdex6TrH+nTeVia2vn+w6+pcNQDsoHeJTdeQUDk8QO53wqbpZ19n/6ZUY3foBQkOjFSNOQhRl50Z488vw7NrhTW1VFQW0OTUkWLPoxmdSQWRdAxPx+IhVhlJ/FdQUqqwUx6QDj9gxIJ0p056+TZQOR/HAeCjbr92bSX5OOqKIOaBvQNRw42DoVfgPZgFZbYKKwp51Cr02AVuvL2EiQZohkzdgyZ5wzpcRMqSRTZtfQ9knc8SShyrXd7yDwyr32ZwJDeF/jxuD18/+yb1Ob/DMgeJ7Nuu7/PuxzW1mZzb3Er9ZL8nS80lPF81owTYt33NPx+H5s+eQHe+YLwVvnCaQ9Q4rx+HhN/9/hh/iR+v4+G8n3UF+6moyQfd0UFQm0jhoZOgls9aI5AQD4AnwLaQtXYIwMRYyPQJiYRmJpJVOYwYlKHHrUMJ4oiGz59Fdf7H5LQIAfKNh38PDGBt+c8ilsXQLi/kfM3f8dowwguvO93x9wZ29ssLHzzH5zr/YZgycaW9tHsaYvA5zuogePTRGDvP4CrbryQ/jHpRz2WzWOnoKOSYksTJXYLFU4f1R4Vtf4A2gg6+skATNiIVXQQp/aQpFeQajCRHhBGv6CEw5yPQTYt/GfBZhbZE7q5HxM05Tya0Z/h4T2jp3OyKNyxgtqHHiK6Tm7HLhsVw/h/fUBwxG/PGJ0oRFFk0zerWJu/Bb8gokfDvClzGDAlq0/GL969HsVPd5PqLwMgTzMY86X/JiGj58e3tVlY+9kPlGz/GZeqE3tMANbwYKyRcVjDo2nRBFLrD6STY6+DgXQSq7QcFqRkBEbQLzChz4OUMyYQefrpp1m8eDF79uxBo9HQ0dFxUp///zkQ+XWwUQ419ScUbIgCtAWrsEWa8cdGoElIICA1k8jMYSj94exYv4OCltJucqAGFYMiMxh73jlE9BLzv658Py1f3cEQ1w4AKhXx2Ge+yICxs3plvF+iOr+MhS881+0FERo/msv/en+fEg2dPieP713GZ52JSIKCENp5NlnLBUnj+2wOByCKItu/fwvHG+8SXS8vJlaDQPsV05l059PoDSd3Px0IUur2Z9NZUoC7sgKhtgFDg+XUgpS0fkRlZHUHKXJA8gL+/35KdIvcQ91hFPhmxjC+nnYnfpWGyc0rGbeqkmufeILQ2MhfjZO9YhXOjX+jv6+aNS1jqLRK3caFIGAN7EfbqDRuuXAKQyPkcsMvg41Kp5cqj/qEg40YRSfxajdJekVX+jyMzMB4IgyhJ3V+AYrbK3lq/05WOJORBAWCJHKuvpzH+g0nMzj5pI/3W+FxOvj5yT+QsGAnSgk6TQp4+DbGXnp7n86jNq+Cb7/7jnZRLqUNjxzA7JsuQq3rfdK1z+th51dPM6T4LQyCG4+kYlfizQy/+u9odT2veyP6/OxcuoHsJT9ibyvsfl2pDiZ15LlkXTGNGqGDIksTZQ6bHBx7NScdpCTrVaT0cpByxgQiTzzxBEFBQdTU1PDee+/9nwxELG0NVOdvo7kwB0dZMVJVLbq6NkKaXOhONNiICUeTmEhASiYRmUOJSxt+WAnF7/OTtyab7Tt3UONu6n49WGFmZP8sRswe391+29Pwetzs+upphpa8hV7wyDdq0q0Mv+qJXrlRj4RVHyxgz/JPZMltQcvIeTcz+Zq5fTL2AWxt3MddBTVUdamJztCV8nLWNML0vZ9K/iV2LfuE1ldeJb6r1u/QQuOFY5l433O90uLr83poqMijvnA3nSUFuCrLUdQ2YmiwENLqOayV26fW0po6jIb4ROqCNDgVfiLcSgKdVvTadvQJwXQ0VRO5fDdhnXIJqSlQwUezprJs4o1E0sD56xYxIXECs269AQCPy83Sl+8jsWUP2a0ptDstdJdfFAZqY4bSPCmC0SmhOEU1+a0Wqn0qGpRhtCmOHTAYsRHbFWwk6hSkGn9bsHEi2N1SyNOFeWz0yGU9JT7ON1Tx6IBxJJj7XkI+d90C2h57gohm+YFVOjGZSc+9T0BI3/GtPA4XP73/PTktRQCEKQO59IpLicqI75Px6yoKaf7ydoZ2b7TisM94kQHjZvfamNX5Zaz//DsaSrZ2t5MjqAlPGsU5V1zyK9XWNlcHhR3VhwUpVV4NdScQpAxTVbJ04oU9Ov8zJhA5gA8//JB77rnn/9tAxON2UFOUTUNBNtbS/XjLK1HXNhPYaCfQJh71cweCDXuEGV9sOOqEBAJT+x0x2DgS7G0Wti3ZyO7SXKxdDqeCBMnGWEaPH0vG+IG9SvAqyl6HcvHdpPrLAcjTDCHgsn8Tnz6018Y8FLY2C1/94wU66mVpbq0pkUseeZjotL55OIFMUHsyZzHvd8iGdAFY+HuCyFWpU/psDgeQt2kRVS8+S1KBLMLlUUHNrCGMe+B5QqJ632DsSPC4XRRt3kbJ7gIaOm0048AvHP2eCPRpiOlwE15TQZN7L4mNboK6khrVYSreP38O60deyvTG5UzYWM+AcyfSvPoH6joUWI0ubDGBdEaE0BYaRWNgNG2aYFoIx3cM0S6jZCPc20CYq5kQWzsRHoHMgGimjZ5Eanzvd2wcDZvq9/LPknJ2+ZIA0ODmUnMdDw+YSIShbzUoHLYOVj9+K8lL81AAbUFKdH99kBFzbujTeeSs3MHiTStw40UlKZg+ZCJj5k/uEyKrJIpkL32fxB1PEkYHANuDzyfzuld6tfRs67Cy4fMfKdq6Ap/7oMyCPjCVoTPmMmb+NFTHkak/NEgptduodB0epEzWlvHV+It7dN7/s4GI2+3G7T7Yh2ixWIiPjz8jAhFRFGmuLqSmYCftRftwl8skUVNDJ8FtXlRHf7bSaVJgiTDiiQtHlRhPQFp/IvplkZAx6pTIobV5FWxZtZGC1rLuh7oWFYOi+zHuvHMIS+rdnYrN0k7eJw8wquk7FIJEByaKhj7UJyZ1B7Bv7U5WvvMKoq8DEEjMmsNFD/7uuDdkT2JvSxF35BVTLMYCcI6mnNezJhBt7FthsZLdayl8/m+k7JZ1UnwKqJySzsiHniUq8bdJV58KXFYnxdvyKCoooqKtujtIPgATOpJC4khNT0UULVTkl9Fgs9GCo1tMD2SZ+CiXCqO1lbjCPMJrKwEojtHy3ryLqes/kHnrVxDpUrI6MoiixCE0hqUhHsEjSC15iPA3EO5qItTWQoTLT7ohgmHxA2jLLqc6bzf2tlLgUGldAa0xjuj0IQyYOI7MsYNPi6T78urtPFveSIFfDrD1OLguqJn7+k/t87r/rmWf4Pz784S2y+epdGZ/pj79LkbzqTlunwraa1v49uOvut1800xxzL/5cowhfXMuOtuaKfz0Xka3/QhAK4GUj3yMEXNu7dXnnyiK7F62mZ0//YCtdT8HPI8UqiBShk9j8nXzCYo4+Qxsm6sDm9fZ49m2/9lA5G9/+xt///vff/V6XwYits4WqvK20lKYg620CLGqBn1dG8FNzsO8Gn4JtxrawnU4o4MREmPRJ6cR3m8ocf1HERQW+5vn5ff6yV29kx27dlB7iPhYqCKAkQOHMXzWuF4V/zmA3Ss+JXbz40Qg27rvDJhByrWvEhLx27/jicDn8/HDi+9SsXsxIKFQBTL9lnsYMu3UnTRPFn7Rzwv7lvJGawReNBix85cYJzelT+tT3YXqol3sffZRkrdUopBkKa7ysfEMfugpEvuP7rN5iKJIQ2E1hbvyKK0up87VgnhIQKGQBGJ0YaTGJ5M5YiBRmfFHPE+OdhuF2/ZRXFhERXstDg4XRzH5NcRYPERXVxFWsoeCGAXvX3g5MXo707aXoyaM5OzttKs7aQrV0h6kw6FXI/qV6LxRxKWMod+EsQw4JwuV5tcZEpfdyb41Oyjctp2Wyn2H7T5BdlcNiupHUtYIsmZO6FNlTFEUWVCxiRerbZSL8oIRgIVbwizc0W96j7eDHwvWjibWPXwLqWtlccLmMDVBT/2VIVMu7bM5iH6RNZ8tZWPpTiRBwoSOi2bNI23swD6bgyxP8ACJouxDlKMbSdgVb/SYYeexUFtYyfrPvqO+aHOXXQWAirDEkUy4/BLSRvbv9TkcD70aiBwtWDgUO3bsYOTIg22KZ1pGpMXazObdy9HX1uKvqMJXWYW6tomABhtB1uOXUmxRAfjjo9AmJROcMZCY/iOJTOzfK26t1uZOti3ZwJ7yfdi6DMUESSDVHMuYCeNIHdO/Txa/ptpyaj+/g2H2jQDUCpG0TX2OwZPm9/rYB9BQVst3/3wGl7UCgMDIoVz+xJ/71Eq+qL2C23Jz2OeXuwdGqCp4Y+gokgL6JhADaKouZPtzD5G4urA7E1eeFUHaA4+TMbJvnGydnXaKtu6juLCYiraa7mvzAMyCnuTQeNL7ZZA+ZiA68+ELpSiKVHfUsLMsm3KvnSqfSJWooVY00yCF4ZVUDG3pZER9IyGWRhz+jsOCG6UkEOlSE93cTqe7koXn9GdsZT0hggulO5X0vFyCK/MOG9OqF2gP1+KMDEKMDkcbl0Bo2iAGTZiHKfDXfI/aoipyV22ict9ubK3F3TLdB6AxxBKVOpj+54yl3zlZfZKN84t+Pi1Zyyt1YndXVijt/CnSze8zp6NR9p1vzLYFbyP+83WCrCKiABUXDGfG397pEQmAE0VFdjHf/7gAi+RAkGB0QhYzr5+HUt03mSu3y0H2F39nRMW7aAQfTknD3rQ/MeKKR1Fret9TxmF1sOHzH9m/eUW3cjTIxoxDzp3LuIvPPWLQ3Rfo1UCkpaWFlpaWY74nKSkJne7g7vxM44h8+vrdjHhjxdHHNQi0RejxxYWjTkrEnJpJZL/hxPcbiVZ/cv4Np4rqnDK2rN5IYXtFd/lFh5ohsf0ZM2siofG93w4L4Pf52PntCwwseBWT4MQrKdkZew1Z1/wTvbHv2lE3fLmUHQvfk6N/Qc3QGdcy7ab5fZaBEEWRNwqW82JTMG50aHHxQEQ7t/c/r8/m0N5czeYXHiJ26e7urqrKzCBi7/szgyf3bkAoiiK1eRUUZudTVltBvbv1V2WUWH04qQkpZI4aSERqDG7RTUlHDSXWRsrsnVQ53VS7Bep8OhrEIFzC0XfxKslLlNhAhLuZIGszkU3tJDXr0Pp0WNUidsXh6UmTX02gW8Ji8jOgPYcccyIGMZyYxmoiczcR2nGMdCbQaRKwhBnwRAWjiI1Gn5BEUHImUelDiUjoh9/rZ9/aXRRt3UZj+b7DHvoAgkJHQHgmSVnDyZo5sUfl6Y8Et8/DO0WreatRS2uXbkm00Mw9MQquTZuCUtE3C3F7czWbHriZ1G2yaGF9tJaYZ5+l35i+6ZYDcFrsLHrvWwo6Za5alDqES6+5vNdL1Ieiungvlm/uYKAnB4BSZTL+ua+QMXxKn4wviiJ7V25l54+LsDTncbBsE0BS1lSmXncxQVG9Q64+Gv5nSzO/RG8FIh//8BJDHn2H+lANNWFmaiLCqI6KpyoyhcrYgVhN8kNEkERChE6ilVZi1V4SdSqSDEZSzaGkB8QQZQjv0UXI5/GS8/MOduzeRb33oO5BmDKQUYOHM/y8caj1fecTUrZvG96Fd5Lpk9vIClX90Mx/jeSBY/psDg6rg2+efImWyq0AaPQxXHD/QyQOTu2zOVRYarlj7w52dpEGByqreXPwoD5rqbR1trDh5YeJWLAZg1u+XWsSDATffQcj597Ua+Pa2ywUbs2jpKiYio5fl0oCBSNxIVHoE4JpTFJTITqpcvmp9aqp95tpkwKPKXktSCIhUhux/loS3HUkOWtIttaiq1fQXGrG7mjngPeLQmEgwSwQH1LDXmk8Drcbf2QyGruHNqXrV6WgEFFHsOSiUdDgFnwMkOyEudZhtzXjsinAokDfIRDSwXHl8T1K6AhR44gw448ORx0XhxAUSXubn/baDuyt1Qe7Grqg1kcTmTKYfuPHMHDS8F7bldq9Tv69fxXvtgRiRd4YJCvqeSDexPykCX0WJG/89AU0L32A2SHhU0DN5RM49y//Rq3p/XLxAez8aRPLd6zBK/hQSypmjZ7KiLkT+mx8SRTZ8cO/ydj7HEHYECWBHRGXMPC6FzEF9F33XH1JDes++5a6/ZuQxAP8LBUhccMYf9nFZI4d3CfzOGMCkaqqKtra2li0aBEvvPACGzbIOv5paWmYTMfPLPRWIOL3y0Qrl+ilrPPXO7Zan44GSd75HgtaXEQJ7cSoXMRrJRL1WpINAaQFRJIaGH/CdVtLYztbl2xgb2Ue9q6HvSAJpAXEM3bieJJHZvQp98Bpt7Ln078wsu4z1IIfq6Qnf8C9jLzkfpR9SAYt2r6PJa+/gN8jB2Wx/adz8cO3odH1jY22KIp8ULyaf9bpsWNEjYfbQ5t4cNDsPtlxup021r3xGIFfrCDALt+mDVFatH+6ibGX3dnj14ToF6nOLaNwdz5ldRU0etoPy3qoJAWB6kDsQQHsiAlhZ3DkCd0j0UI74d5mEpzlpDiqSXHUEmyzo4y9kDHn345Gq8Nld7L+858o2LAMn/tgtkGrDmZwcAtZQXtYyDT0jZFsHuDjqlFXMmrMGBQqJS6bk83fLaAqt4RWvQqr8vDsh17SECDpkSSJQHMgY6dM6L6nmusqyP3iMUJq12BxKnA41DhsBrROLQEdHoLbfcc1HbQYBTqCtHSY1FhVCuxKCa9Cg4QWQdQgKPQEhKeTMHg4w2ZOJCKp51twO1wW/lWwmk87InAil0YGKKt5ODmKmfF9w59qri1hx323kLxXlhCoSTCQ8uIrpA6Z2CfjA7RUNPDNp1/T6JM5bP2DUrjg5kvQ96GeUFtTLWWf3s1Iy0oAmgihdvyTDJt5bZ/NAWTO04YvFlOwYRleV0P361pTAoOmzmH8ZTPRaHtvY3vGBCI33ngjH3300a9eX7NmDVOmTDnu509n+64oijQ4mim21FFqbaXCYafK7afWo6Leb6JVCjquwVEI7UQrbcSpPcTrVCQZDKSYQkgPiCXWGEH13lK2rN1EUUdl945Oj4Yh8QMYN/scgmL63iY6d933hK59mBhJXgyyjZOIv+Z1wmOS+mwOoiiy+LVPKNryPeBHUJqYdO3tjJzTdw+0ensTd+7Z2K3lkKao5Y2B6QwN632nTK/HxYb3nkL74UJCOmU9jJYQFf5bLmfijY/0KBeps7Gd3Zt2Ul5aRqO9BReH8yAMGHEbwtkfEcnmmHCc6sPHFiSRUKFDvs41PhJ0SpL0RlLNYcSpzNQv+4ABZR8RjAWQuUV1g28n6/w/otZoKc8t4ed3PsPSlAvdpDslAfoQJoXlkmkqZpM4iJ2+qZgsVUx67DHSo47+Gyxe+CquT39Ga86gITyUer3vsHZhQRIIloyY0JGcmMT4K89Fa9TRUldJycKnyWr8Hp0gn4NCVSb20fcQGp9GU+k+LOVFuKoqoa4RbWMHga2u47pRe5XQYhZoNymw6lU4tCo82mDM0f3oN342o+ae26OLQZOjhWfzN/CNNbbb5n6EqoJH01JOyGTxt0IURda/9w/M//4ag1vCo4LG62cw/f6XeoVDdyT4vX5WfLSI7dV7kQQIEAxccsF8EocdXUW3N5C7fgEhax4itutZutswgZirXycyru+yuSD/JvvW7GT7DwvpbNxHd5ZRaSZhyGQmX3txr5QSz5hA5LfiTNYRcfqclHbWUmJtpNzWSaXTRbVHrn/Xi0FHNTYKtzs5r7yaqLYabJKl+/VAwYw+IQLNyEiiAwOJNQQTZ4ogSBPQJ9mQ1sYayj+7m5EWWR69kVDqJzxF1oyre33sQ9FS08Q3Tz2Lo10WLjKF9uOyxx/u0w6FL0vX8tcqBRYCUOLj5qAaHh8yt9eJgH6/j02f/Qvpnc+6xaM6zArs153PpD88cZgc+/EgiiJt7k5q7c3U2tuod9locDtpcntp8oKuXmRwfi0WX7tsg9sFlaREqw6lPiiCLbFRlAeZ0OMkStEhZ/40Eol6HcmmQNLMkaQGxqJXHX6t2yzt5C54kX7lHxGMrIZZI0RRN+QOhs39PX6vyIbPl5C3/mf8nhoO1LMRTJjNZi6PWEGQuoMmKYivxfMItEYTfk4osy6964S+u8vr5oU37mX4wk0ktAq0pQylNjGJhkAtliNkSxI1UYydNYGEYem0NdVQsuCfDG34Dr0gv7dIlYFz/P0MmXL5r9ozO1pqqS/eQ0tJHvbKUnw1dajqWzA22wjq8B2zrR/AoodOkwpfmBkxNBAhLARNRCT6yBjM0QmExKUSEZ950ty0KmsdT+dv5SfHQdn4czRlPJ45qE+C6bqyXHLu/T2JhR3yfNICGPDSm8RnjOj1sQ+geEsePyz/ERsuBEngnNSRTL1mdo9bWxwLTruVPZ/9hZG1cnbZJunJ6383Iy99sE+yyz6vh7aGclprSuisq6C1uJjm/Dxob8Hg9mF0iwQ4RGqjTVy+cFuPrjVnA5HTDFEUaXK2UmyppdTaQlWHFc0+K9q6Dizeg+luhSSg1UaxOTGVbUfJfmhwE4yVUKWTUKWXcDVEapREanVE603EGIKJM4YRoQ89pXKBJIrsXPg6GTnPEYgdvySwI/IyBl37fJ/WNQG2/7CWjV++hSTaARX9Jl7K7Nuu7rOyVIuznXv3rGalS96xJAgNvNY/jrGRg3p1XFEU2fHDf7H9+z/E1MpZAZteoO3yKUy8858YTEHd7/WLfpqcrdTYW6hztFPvtNHodtHo8dPshVa/mha/ng7MePh1CUvj83N97n40naWIXZkCIya8xmCaowzYktXEmtRdXKgw0gNiidCHntBvYO1sI2/Bi/Sr+IggbABUCzE0DL2DoefdTP6GPexZsZLWmr2HcSoEZQT6EDOXBC8gQtmJKAksFseTxyhSrBbm/P1RTIEnH4huqtjFJ5/9l0uWbCauVS7HNsTF0pA1FIspjmbJiq/rHISIJtQKFWlJqQybOhq0HkoWPsOQ+m8xdHk1FavSsY+9n6HTrjghvQivx0VDRR6NxTl0dmVTxOo6NA3tBHd4MJ+E+7FdJ2ALUOMK0uMLMSOEhqCKiEAfGYMpOp7g2BTC4zN+dZ4K28t5an82Px8iGz9TX85j/UaSHty7IneiKLLq1T8T/v5itF5waqD9D/OZ+qen+uyetrdZWPD+15TYZDJtnDacS2+4os+zzeV52/AsuItM335AzrapL3qdlEGnxrfzOB201JXQWlOKpb4CZ0MdnqYGxJY2lG2daNrtGCwezDbxuKVFgNIYNeevzjmluRwNZwORMwCiX6R0ewF7tmdT3F6J5xChpDBlIInxCSiywmjUew/bqbb4lLSKOtokc3et90SgxEcQVkIUDkKVHiLUEhEaJZEajRyw6AOJM4URZQjv3tlXFe3B+u0dDPTkAlCqTEE8/1XSh03q2ZNxHLgdbr595nUaitYCoNKGM/euP/dpL/yPlVt4uMxFK8EIksjVAZU8lTXrV7v9nsaelV/Q9PLLxJfJmQOnBnJnZNJx2RU0afU0efw0exW0+jW0iQY6MHfvcE8EBhwEC1ZCFS6G1zsI31+DVZKl36PUoQyfM5Yhg4egU50678bS0UregucZUPkJgcjHrhZiaBx2F8Fxk9n508/UFW5D9HUe/JBgRKGKIGbMQBI7PmGsfx8AJWIMC5mJyRPJwEGhTLz2D6c8LwCXz819Kz/Bs2UX1y9bT3iX83BLINRMSEEfdzX7OsvwCX4UkkCEGEijooNobRiDMweSMDSeqlUvM7Tum+6ApESZinXMfWSde/VvErBqb6xh3eefUL59BUqfHY3fhxEtwSoV2k4nhk4XZqv/MIn848GpAZtZjTNIhy/YjBQahCo8DGuAng2CwE7zQFqC47GbgrnAXMNf+o8n3ty73SWV+dsovP8O4svl4LRiYAjDXnqnz8T2RFFk24J1rMrZgE8Q0aLm/HPOY/C5feuE7ff52PndvxiQ/zJmwYlPUrAj5mqyrn22uwPRbm2jpbqY9toyLPVVuBrr8DY1IbW2oWqzou1wYLR4MDtOfNkWAatJgSNAgzvIgD8k4LDMm9UKIQkZjJlzQY9+37OByGlEQ1E12et2UFBXfJiipAkd/WPSGDZxFDH9T2wnYvPYqbY1Uudoo85pocHloNHjpdkj0uxTyYuTZOpmy58IBEkkyt3AH/O/4kbLT2gFHw5Jy2dh8ykZPQOjTkOAUoVJrcas0mBWaQnQ6AlUGwjUGglQmzBrjD1G1izfW8SPLz3fTaaKSJ7AZY/djc7UN1oEnW4rf96zkh8cMhckWmjmX+khTIs98RSyX/Rj9dixeG10uG1YvE4sHidWnxurz4PV68Xq92H3+bH5JewiiHXVzP7wU7KK5IezRwk/jUvh4/NvpzPw+MaEZqyECDZClR7CVT4iNAoiNRqidAZi9GZijaHEGiMwaYw4LXaWf/Ije5r2gyC3gU8fPpkR54//TTvTzvYW8hc8z8CqTwnoCkAqFXFUpt5GZ7OJir2b8DjqDvmEGkEZDpKfyAGDUATmML/1R3SCF7ek5ltxOqVCP9LtEjP/fAuhkT23Y1+8bz1/rWphwrpFXPXzdoK6yL/1YWC7+FJa3DFUdZFkA0Q9CgQ6FA6UkoJkcyyZGal46r4nq/4rjIKctSpVptA5Wg5IFMpTvx9sbRa+f/7fNJdvBmThtOFzrmXSNecD0NlSQ0t1MR115dgbanA11uNrbkFo7UDVbkXf4cJs8R7Tu+qX8Cihw6Sg3azBa1ShNweAQQdGPQqjCaXRiMpkRm0KQGMORBsQhC4gBENACIbAUEzBEWh1phO+fnxeD6tevIeoT9eg8csZHsfd1zLppr+c9Pk6VdQXVvPd19/Q4pdL4kPCMjj/5ovRGHqms8fjdmDvbMHe2YqjsxWnpQ23tQO3pQOvzYLPZsVvt+Fub8NXV4bO40ThFRA8CvROJWab/7gdXIfCpwCrSYkjSIsnyIgYGogiLBRtRBSGqFgCYhIJjUsjNDqlT7uXDuBsINLHsDS1s2fVdvaVFtDk6+h+XS0pSQ9OZOioYaSPHdhrtUmXz02dvYlaRyt1jk7qXQ6a3G45Xe9Tdu+m7V4dN+z/nntaPydUkHfgq5XDeGjQA1QHxZ3weIIkohPc6HGjFzzoBS8GwYdRIWJUSBiVYFQKmJQKzColJlVXUKPWEKjWE6DWY1TpKfhiHaXrFwA+BIWewRdey9ALzumVc3QkbGzI4e+VPhqRNVmmq3OZHhqBG7D5vFh9fmx+Ebtfwu4HmyjgEBU4JBVOSY1T0uBAi1vSHpe4fCimb/mEe75egskFfgFWjIzjw3l/pCU8qSurZSdU6SFMJRKpURKh1RKtMxBjCCTWEEqMMeKEMxj7Vu9i2fqV3YJj/QKTmHvtfMzhpy4C19neQv73zzKw+jMCkI1giqQU9qgvp622BXtbMQcIcSCgUEUjSRKSvwmNKYbkUQGMqf+CcEHOkOwQM1nJFHRSEIOjjcy47e5TntuxYHHZuGPVl6wX0rli+Ztcui4Hk0sWKswfqSJw0sNk11bIhF0JYqUQGoWO7vKNDg3pwfEEiaWMan+bAIW80ShTJNEx+l6yZlz3mwKSnNU7WPPBG/i6lJONIZlceP89J+ydZO1oorm6iPbacuz11Tgb6/A1N3fvpnUdTkwWL0ZXzzzyfQpwawTcWgVenRKvXo1fp8Gv1yDp5aBGMBpQGo0ojWbUZjM2ewfW1asJbfWi8UFzWijDH36WkMiEHpnT8eB1eVn33UryWmRV2ECFkRnnTsUUpsVpacNpacdj7ez+57db8dvsiA472J0IDhcKpwul04vK5UXt8qFx+9G5JTS+4wx+gnCrwBqgwhmowxtsQgoNQhkehjYiClNUHAExSYTFpREcmdhnBOBTwdlApA/gcbjYtzabnNxcKh0N3bwPQRJIMEQxZNBgBk0Z3iey68eD6PeTvfQ9Yna92N0NUylEszr9KloHjcAuyguuzS/h8EvYRIW84IpKHJIah6TBiRanpDupBfdoiGjt5LJlCzFYiwFwGxL5cu5lNIUG/eZjnwgUko8M9lPIACRBQZDURiAdVAq/zeBMkET0ggsDrq7gzItB4e8K0ESMTiuj33+PMTvlhaYiTkvrn/9A+tCJxBrDiTKEolL0zIPF0tjOj58uoNhaBchKp3OmnEf/yVmnfMzO1kYKFjzHwOrPMQtORFFgjW0yxc407O3lsvtxF9T6aNS6aBzt+wEHkqAmOSuDka6FJCJnv6rFcBYxhSYhliSXlpm3XEhsRu9LdH+ycRHPuXW4HXDvp08z9UC7abSENLEfTaY5lHRlcozoSNZHU+qsxcnB7xcoGIlTCYxxf0OCQq77lysSaRt5L8POu/6UAxK3w82il9+lKmc5IIKgJnP8fGbddnWPKbc6HRZaaopprS5hS/5GcpucaJweTG4bqaKDcL8KHC4UTjdKp0decJ3ygqt1iyeVefm/CI8S3FoBj1aJR6fEp1Pj12sQ9Vokgw6MBhRGAwqDEUmrxdKwnwRPPuE6F+FqL2XmkQRd8E+SB/SdbUVv4Gwg0ksQ/SKl2/LZvWM3xW2VeIWDIXC4KohBqf0ZNm00AZF9b/1+NOSuX4B+3ZOk+UsBaCGI0oF3MvzCO09aglgURRw+Jx0eG50eKxaPE4vXidXrxuKVyxA2vx+7z4/VL2L3g10Eh6jALipx+JUM21hCWt66LrKigvLkKXw7YzL0kRJkqNSEDje1grzLzJTyaSEMpaDAoDiQ2fFjUIgYFWBSgkmpwKhSYlIqCVBpMKu1mNVaAtR6AjUGAjQmgjQmDCr9UVPVuWu/o+MvfyOszSfLYV80ghl/++9JdcKcCGTi6wZW792IGy+CBMOiBjDzunnoTKfGd+loaaBgwbMMrvkSk+Ck3JHE+rbhtDpcSH5r9/sUqgBiMsYQGpfIvjXf4/fKWg4BsXFMDNpJP1EOPFslM4vEKVQqUtCgZpDByPkP3tOnWjn1rY3cufkHNppGc96GD7jruxUY3DLHomOsE2/yVexzB2FFznqkm+Lpl9GfwuL9lFpqDmsJjsDIQH8ZoxRLMQjtVCgSaB1xN1nn3XjKnRFluwtZ8u9XcdvkQFJjiGX27ff0Cm+qtLOaP+zd3W1bMEVbxuvDphCuP7KRnc/rwW5pxd7Z0lWCaMdlacVjteCxdeKzWfHZrIg2O5LDAQ4nCocLhdOD0ulB7fKhdvvRufzoPKA4A1YglxpcGkEOHPTqg8GDQQcGHYLBgGA0oDKZu/4FoO0qWem7ylXGgDBMgeGnJHHfUldJ6XePM6LlR1SCiF8S2BU8m4RLniQqPq0XvnHv42wg0sOoL6xm9/od5NcWY+Nw3seA2AyGTRxFdL++s54/EZTs3YhzyeMMdmcDYJP05CbfyNBLH8Fg6jtvlgNoKKtl4fP/wt7VlqvWRzPjT3eROrL3DaLggDjZGp5rDMSFHiM2/hbr5rqM6b06rs/rYeWTfyT+my0oJWgLVGJ48hGGzbymx8dqKqtj0VcLqOlyJQ1TBjBv3gUkZp3ag6y9uZ79C55hSO1XOD0GtrQPp8xqwOdrP/gmQUNoXBZDzj2XpCEZLHrpTVqrtwOgMpuYEF/PSGkPAHZJy1JxMnmKTCRBRYxbw+QLJpM5ru/UL3+Jl5Z9zBuaZAKaanns/ecZUNVVbkn3M3iwj0362ynyWZEE2eF66tBzGDxlhJwN3b+PWldzd/uzUhJIlBRkSfsYoFhNrTKS5uF3MWzWzacUkIg+P8v/+xX567/tyjYpiB80gwvuuxWdsWdJ1D7Rx1M5i3mnPRY/KsJo419pJs6L713zRJuljVUP30jqajlIrY/REP/cC6QO7RvCvCiK7PpxM2vztuLBh0ISGJc8nKlXzzotHi1VRXto+eFxhtvXA+CW1OyOvpz+l/+dwJC+sfXoKZwNRHpi7MZ2dq+WeR/Nh/E+VKSHJDJs1DBSxwzo0570E0FtWQH1Cx/r1gPxSEqyIy8h49K/9ZlD7qEQRZGV73zDvjVfdT1MlSSPmMsF99zUZzd6i7OdO3evYY1bLr0MVlbxn6HDSAns3eCxumgXBXf/sbtboGxUDBNe/rhH3JgPhd/rZ+0Xy9hcugu/IKKUFIxPHcHkK2ee0jlua6qlcMGzZFYvIKdjCPstYdjd7XTrfaDAGJJOvwlTGXvRNDQGHRu/XMbOnz5C8ttRaJUMTXAwRbkDhSDhlZQslyawm0H4FVq0oooM0c/5jz2IVtd3BmlHQ0FNEX/K202RIpkbFr3ANT/vk4PGANCP70QXkMXPiim0dfFhYrXhXHjZfCLSYmitbmb3mm3kVRTSLh7MDmklFZmiiyxhGwpFHS3D72TYnFtPKSBpLKtj4YsvY2stAECpCWXKdX8ka+a4njkBh2BD/R7uKmymXgpHkESuDazkyaFzflNX1Ylgyzevo3zmLcwOCbcKWn5/AdPueKbvfJxqW1j46XdUOusBubPxovkXETeob2wcfon9O1chLv8rA7xyN5kFI/mpt5J16UPo9H2nEvtbcDYQOUV4HC5y12STsy+Xql/wPhINUQwZLPM+eopl3ZNoa6ql6JsnGN70PRpB7vfbGXAuMfOf7hNb6iOhtrCSH/71Es5OuSykMcYx9857SRmW2WdzWFWzk3uKO2kmFAV+fh9cw2ND5vYYF+NoWPvek5hf+7w73d9555VMvuXxHn+wVu0tZdGiRbT4ZeLnoYvkyaK1sYbC755GUVREQWcMbU77YbwPjSGG5GHnMP7S2YTEyLuzwxZJlYK0WA+z9DvRdqmTLleMpcA7ko6ulvE4h5oh41MYfdFVv/Wr9yj8op+HV3/K54qB9C/awKMfvUdUux8RqBjuYVpqO2u4hV0Kc3ewNy51OFOuPA+VRo0oitTklrN78072N5YezicR1QyU2ohT7MU+/GKGzbkVlfrk1FRFUWTjV8vY+aMc7AGEJY5l/p/vICAsqAfPhNxJdu/ulSxxHlQVfntQJoNCe7dE0FhZwO67bu4WQSvPimDsKx8TEtW7eicHIIoiO3/axKrsdbjxIUgCYxKGcu61c1Fp+z47IokiOWu/JmDjP0kWKwFoIIyqofcwYt6f+tRu41RwNhA5CYh+keKteezdsZvi9qrDeB8RXbyPrOmjCYg4c3gfh8Jh62TvN/9kcMVHmAQ5rZyjG4Fh9pOkDT09KW/R52fp21+wf+N3XdbpKtJGX8Dcu6/vE6t0AI/fy9/2LuaDjgQkQUEkLbyeGcakmKxeHbeztZ4N913f7UZanWSk3ytvkdCvZ4lnbruLFZ8sIrs+v7tsMG3oREZdOPGkg52Whmq2v/ci7WWtNDk8iKKj+28KVSAxmWMYfeEskoceVOQUfX6W/edLCjZ8B4KHmGg/c817CBDkz25RDGAL52H1gySATlSR3tHBtMfvJTi87zNzJ4o1ZTu4p7wVq0vDvZ89ybnZMrG2JhLSxrRi1MWzkEupU8h9lkcqf/m9fgo37mXP7r2UdlYfxieJFtWk0oRhYAajL/7dSQcklpYOvn/udVqrtgEgKE2MuuAGJl45+7d+9V/hs5I1/LVajR0TWlw8GNnBbf1m9mqWwu/38fPzdxPzyWpUIrQHKNA88UCvmjv+Ep0NbfzwyXeU2WsBCFUEcMEFp17i/K3w+3zs+vEtEve+TCSy71aFIoGOCY8ydOqv1X7PFJwNRI4Dn8/H+o+WYHO7KGoq625tBDChZ0BsOsMmjSI688zifRwKr8dN9sLXSM3/N2F0ALLQknPyEwyedOFpm1d1fhmLXnoJl7UCkA2W5t1zH4mD++4mLm6v5Pe5ORT45d9vhq6U14adS7Cud7kxe1Z+gf3xpwnp8OMXoOrSMcx4/O0e7+EvWL+HJWuWd+vUpJsTOP+aiwiMOjK58Ggoyt7Nlo8+orOlGe9hYmMy7yNr5gyGTBuNQnU4kbgsu5Alb7yKy1ZFaKTA7KBcohQyb6SQeD4IupbQVgm7Ul6sE20q4lMEzr3t0d/wrfsOnW4rf9q0iNXCwMNarV1qaBzr4dzoFnZxCauFFNyC75iEYKfFTs7qneTk51LrbunmkygkgQRJSVRECJOuuw5D4IlrAQHsXr6ZdZ++jd8jE4JNYQO46P57iEw5+UzYsVDeWcMfc3ax1ydnJSZoynlr2EQiDL2rTFqwZTFNf36EiGavnJWaN5QZ/3j/lIigpwJRFNm9dCsrd6zBhRdBEhgZO4iZ189Dres7B/RD4XLY2PP9C/QveadbODBfMxjFzL/Tb2Tvct1OBWcDkeNgyRvfsL05r/v/aklJoj6a0eeMIW1c7+l99AQkUWT3io8J3/Yc8ZLcYlgrRFI/8kGGz7r5N+kY/BaIPj+L//0pRVtkXRBQkTnhYubcds2vFrLexAeFP/OPOgNODOhx8HiMg5szz+3VMT1uBz///Q8kLtiJQoLWYBXmpx9n6LTLe3Qca3Mniz9dwP7OCkAmS8+aNJNB04af0Odddif71uygaPsOmspy8HtbD/mrAq05gcFTZzHmoulHJEO6HW4WvfQOlbnLMYUqmBG6n1SlnDGoJ4zXwq7AYElGdNciCaAXVfSrqSPrgRtIHHBqUtanE+/lLefpRhPmlnoeff8ZBlfI2Z7CdC1jB9diUAfzk3gNRV0a2mZBz+zJ5zFgStYRj9dW08zOlZvIryikQzhIeldKCqI0waQnpZMxvD9RmfEnlHVw2Z0seuldqvetRG711TBg0qWc9/srevSe84t+nt23hDdbo/GjIoQOnk/Rcn5iz3NUDoWts5W1D15P6voyAGrj9KS+8m+SB43v1XEPhaWpnR8/+Z5iazUAwQoT8+bMI2Vk35WXf4nOtmbyv/kbw+u+6i6BZhsnEnbhUyRkZJ22ef0SZwOR42DdJ4tZV7KTMK8OdWcb1rZCJNHXZdedQeKQYQyZNr7Hdxe/FXmbl6Be/QQZPrnzpI0AivvdxrD596LRnj7eSmVuCT++8lJ3q6EuIJkL7ruf+P5JfTaHDpeFO3ev7PaJ6a+s5j+DB5MR3LtzqMzfRtE9txFXJS9SpeMTmPTiRwSE9JxstiiK7PppM6uy13WLbWVF9OO86+Yd095cFEUq9hSTt34LNfv34mgvBw5XXVKrQwhNGcCs399EaFzkUY+Vs2o7az58E4WunYmRlWSpygHowMSC8AtYrp/NiMp87F2qoykWJSGaSmb+/bUeb1HuS5R2VnPrrp0UivFcs/hfXL98j1wyMCtonBrBhfrd5IvnskwxDFvXopAZkMT51x1dNE4URcp25rN9xc/Ueu3YhcOFOYxoSQyKJTU9lYzRg44rPleyI5+lb76KxyGXErSmBObccXePc7G2Nu7j9oJaaiX5OrnSVMYzw2b3ug3Cxs9eRPfC+xhdEi41tN9+KVN+//c+bffeu3wby7aswokHQYLh0QM47/oLTitfsKG6hKrvHmdE+1KUgoRPUrArbB6plzxJWEzf8GqOhbOByAnA0WGjta6J3DVbqM7fi6215DBiHsieJ2GJA0kfOZIh00f3mez4L1Getw3LT48z1CnXhR2Slr0J1zH4ssf63JjuUPh8Pha/+hEl238EfCCoGTDpsh7fkR0PG+r3cMf+FhoJQ5BEbgqq4m9De9ctVxRF1v73CYLe/Ba9BxxaAfu91zHpxkd6dJyWigYWfbmAKpcsRBeiMHP+nPOPuiPraGhlz8+bKd+dTUf9fsRDdD4ABEFPkE5HgrEDYcBAJv/+H8fkKdjaLHz/3L9pa9rGyOhGztHInRtOScOWyPm8FjuFUftdeB1VIIBBVDOouIzIG6YwYtZ1PXQWTi98oo+/Zf/I+5YEMsu28Nj7bxPTJhNZ909NITnOyQBPIcvEG9ij0IAAWtRMHz6JkedPOOaC2VBdStmHf8ftCaRMiKROEA/jlCBBuDqI5MgE0gdlkjw844jESZ/Px9I3PqNoy8IuXpaSxKHnccF9t6DR9VzHi81j5/7dy7stEZIV9bw5MIVhYb2bIagryyX3rltJKJHl2ctGRDPh1U96vAPtWLC2dPLTxwsotFQAsqjdBbPmkjqmbzxzjoby/B10/vQ4WY4tQNf6EHc1gy7/K+bAkyvX9iTOBiKnAI/bQ8GG3RRu2U5j2b7u3cVBKDEEJhGTOYT+E8eSNrJ/r0fkDVXFVH/3GCM6lne3QWaHX0jqpX8nLKpvJJGPhrLsQha//lL3eTIEpXHRg/efsBx1T+BI2gevpgcwPa53zazam6vZfPf1pHQRGatSzQx69b/EpmX12Bh+n58NX61kY9F2fF1dGmOTs5h61ezDFiKP20P++mwKt2ynqXzfL7xdAJToAxIx6BWco1lPiqGUWmUMznlvkzF88jHnsPHr5exY8iH9I+uZoduDUpBkoaWQuewecT4bS0wMKs/D2ZUFSetQENi6nXNeeovg8DOXX3WqWFe3mzv3t2JxqbnriyeZvUO+9utitHDr1SSUfY3aE8QiptGmkDc18doILrjyYsKTj54hE/1+tn/1DMMKX0FARa44hWLTZJrcDtrEwwNJtaQkzhhJSmIymSMGEpYSddhzqL6kmh9efLlbr0elDWfaTbczeGrP3hPflK3nL5UCVsyo8XBfeAt3D5jVq89En9fDymduJ+7LjajE3tXkORZyV+1k6YaVOHDL2cnIfsy6/sJTFgzsKeRvXYbi57/RzydvFtoJoDDjDwy7+L7T0iZ/NhDpAcg7yy1U7Mmmva7g1ztLpZGgqH4kDR3OkOnjCIuL6LGxO1sbKfjm7wyr//pgDdA0mfCLniY+bXCPjXMq8Hm8/PDy+1RkLwH8IGgZNO0KZtx6aZ+mSsu61CBzD1GD/PewqYTpezdDlL30Y1xPPE+wxY9PATVXnsOMR9446e6HY6E6t4wff1jU7VsUownlgksvIipDXtyr8srIXbOZmvy92NpKj57JGz2SwGglmiV3kCxWALAt9CIG3/TaMUXtmiobWPCvFwnT5DDHuBu9IB9/t2ECylkP8VJLMxnbO/G45Lq50a9meF4RTI/tU4v304F2Vyd3ZP/MKncqk7d9wX1f/UiAU9a+aL5lDsHp/YjY+QqF/plsVQThFyRUkoIJ6SOZdMV5KNVHzxRWFOzE/+2tpPrlstf2kHnEz36KqrxKSsvKqLLUyaW5Q2AW9CSGxJKekU76mIEYgkyIosj6z34ie8mnSF0dUBHJE5j/59sxhfTcc7TKWs8f92wnu4vIOlpdwdtZ44gxHb3E1xPIXbeAjkf+2q1SXHnxKGY88d8+NXZztNv46aPvye+Q+SsBgoG5584mc8LpfT5LosjulZ8Rtu0ZEsSuQFmIpG74/Qyfc2ufcgjPBiI9DFEUqdhbTN66rV219jJ+VWvXRRGRPIj0MaMYPHXkKaVDXQ4be759jgFl73W7meZphqCe9SQZw6f0wDf5bSjanseyN1/B2yX6YwzJZP6D9/c5l+bT4jU8UXOwrfAv0RZ+l3Fury6AHqeDlX+9maQf96IAmkPVhDz7DwZNvKjnxnC4WPnpYnbW7kMSJDSomDJoPAMmD2Pfmu2U7tpJW20BorfjsM8JCj0BEZkkDs5i6LkTiEiKlnfZXz7F8KLX0Ag+WgmkeuLzZE2/8qjji6LIsv98TlvRl5wfkE2QIF+DBaoBCDP/QWV0IN//XE1KRRFOQe6IyWgXCC9cScrzz5A6ZGKPnYszHe8V/sxTtUZMbQ385f1/klUmi9aVDghh5MvvUbn1B0LylrGGc6lTyMFDqGDmoovnEz/46J5GbpeD3R8+wOj6z1EIEjVCNPa5b5I5chqiX6RmXzlFewoor62g3t2KKBx8fAuSQKQmmOToRNKHZBIYHcqil96krWYHAAqlmTEX38z4S2f02Hnwi37+lbeU11oi8aEmEAvPJimYn9y75pXWjibW3XcdqZtlXlpNkpHMXmiTPx7y12SzZN2K7s7LIWEZzL7+wmNyt/oCPq+H7B/+TfK+1whH7mgrVabgmPQ4gydf3CdzOBuI9DLcDje5a7dTvG0HzRX53Rb23RDUGINTiO03hMFTxpMwOPWYi6Tf5yN70Rsk5rxCBHI7XrkiCcvExxgy+ZLT3ifucbn54V8HjbgEQcfQmVcz9caL+nT3a/XYuCd7OYudMiE1XVHLfwb3Y0BIaq+OW5qzgYp77yKmtsv+fVIKU174CFNgz7UwFm7KZfHPS7FI8g42QRVBAAoaynNw26o5qGoKoEBnTiA6YzD9J4whc8zgwzg5jTWlNH9yM4PcewDYYxhH/A3vEhp5dIfl8r2FrPvoH8wwbSZWIV+DFcTSMeEx+k2+mKe2Lca4sQ23W95lmfwaRu/Jx5rpZcaTH/RZW+WZhML2cn6fk0eRN4orl73KTUt3ovZDh1FAeOwuBp97JXu/ehpfpZWNilg8gh9BEhgUnMi83195TKJj3qbFhK68iyha8EkKdiTeyqjrnj4s8+ayOinenkfp/mIqWmvoEO2HHUODigRTFIFqE9V71+O0y4t2QOQQLnrgLsITeo5QvaMpn9vzq6iS5GNebCzj+axZmDS9e12s/+CfGF/5FINbwqEF611XM+WWx3t1zF/C2Wln8ccL2NcqO/qa0HP+tFn0mzS0T+dxJDhsneR8+xwDy9/H3NWplasdhm72k6Rn9e7G4Wwg0sdormogZ9UWKnN209FQiPSLB4JCFUBwTH9Sho1gyLnjCOoSR5NEkb2rvyJo89MkiXKau4Fwqofdx/C5vz8jlPP2b85h+X9exddFljSHDWT+Q/f26EPsRLClIZfb99dTJ0V0S08/NXQuWlXv9fSLosiaN/5C6H9/QOsFm17A/cDNnHPNAz02hr3NwuJPfiC/XVaf1YsaQlqsWFpzD3ufUhNCaNwA0kaOZPC0MZiCj6w7sWvJe6Rvf5wA7DgkLbmDHmL0JfceNZh1O118/8ITDPf+SKZSDjKapGDKBt3FyIvuoNBaxbsLdxJZWY6rKwvSrxXishejffgPjJp3a0+div9JePxe/rp3MR91JJBWsY3H33+T+BY5W7p/ShqzXvoMu6WTgi+eo6I9glKFTEQ1S1omjRzNqHlH13/obG+h+IM/dNs1FKoyMV75PnFpg474/paKBop25lNaXka1vQHPL7K2AaIek8sP1lYcnXX0nzK/R0uqNo+Dh/Ys4zu7nPFJEBp4a0AiIyJ63qjvUPzSSqF0bByTXvqkRzvXTgT7N+ayeNWSbn2fgcGpzL1hPoYgU5/O40hob66n8JsnGN74bbfy9i7zNKLmP0VsSu84Xp8NRE4jRJ+fkuwC8tZtpb44B2dnJeA/5B0CakM0oYmhDBVWM0iSLcQ7MLE//fdkXfzAGeEl4Ha4WfjC29Tk/wxICAo9w+dez6Sr5/ZpFuTXGgbt/CvVwOyE3tWlaK0vZ9s9N5LcZRFfmRHI0FffJTr5yIvAyUD0+akvrWH3si3sayvF1cUDinFocdTswu93gaAlICyd+IFDGTxtPLGZx27Hs3S0UvT+HxhpWQlAkSoD/RXvEp9+9F3Zms8/ICD/DUaoZMMxi2RgV+RVjL3h72j1Rt7ZsYSOVbU4PXIpLsCvYXR2LhZjDWNe/ZjQ6NPjw3EmYmXNTu4ttmBxabjzqyc5f6ucfagNVxH30r/oN2omNSX7yP/yY/Z6A7tbdpMFE9OvuoC4jIyjHnvnj/8hY9ffCMCBQ9Kyb8gjjJp/9zEzpX6vn8q9xRTn7Ke8vopGTxuScPDvCkkg2KfD6FEwaPwYBk7OwthD/JEF5Rt5uMJPJ4Go8XBnWBP3D5yNshcdtr0eFyv/8UcSv9vWreUT8MwTDJlyaa+NeSS4rE6WfbyQPc2FgNyKPXvSeSes9dPbqCvfT92Cxxje+TMSCurFDHIMs4jKms7w2T2bITkbiJxBcFgd5KzaSumOnTRX5WEOamN8YDn9VXIGxCWpWeIYQV1nCoGhiYTFJxKTkULikIzuzElfI299Nj+/+xo+dwsgp3Ivefjebn+RvkKVtZ4/7NnO7i4y3Dmact7sA1XH7Yvewf/kKwRZRXwKqLtuKuf++TWUypPLUImiSEtVI5W5xdSXlNJaU4WtrQ6/x4IufigNOrnUY/ZrMTXU4fV7iUwZRL8JY+k/YegJG9blb1lKyPI7iaIZvySwPeEWRl73T9SaX/OUPG4Xe5a+jzH7HQYqZKKdW1KxTj2DkX94iZDwGJocLbz51TK0FVW4BQ9IMKBFJHXzT7TfMJ1pdz33/zUh9VTR7Gzjjt1rWedO4Zxd33H/598R5JDwKKHi0onMe+JtFAoF+ZtWs2fFZorwgQBGSc1wbRsJsy8kfdiRXWcbqopp/fRmBnpyANhtGE/ije+esJGlo91G0fY8SoqKqWyr7d61HwoDWkJ1gYQFhhIZGUlUUgxR6fHozCffDVJna+RPezazzSsHqyNUFbyVNYYEc/RJH+tksGfVl9gffapb3bj6ivHMePStHiWTnwhKtuaxaPni7lJrv8Ak5t1wcY8FeycDURRpq26mobSGhpp6WlpbaLa00iHau1vFE0Q1N/z1oR7Nwp8NRM4wNNWWU7rkVTJrvyMEuQ/eLalZ4x5Kfp0Jye0/4ucUSjM6cxSBEbGEJSQS2y+N5KEZGHqJCOWyOVjw/NvUFa5BzoIYGHXhTb3iY3E8HNoeqMXFAxHt3N7/vF5dAN1OGyv/ciOpS2XV3aZwNRHPP0P/cXOP+9mOhlbK9xZSV1xGa3UVlpZaPPZGJMl12PuM5gSsMXHYFR7ZTNEXRFK/VIbPPuekzcs8bhe7PnqQMbWfoBAkaoVIrHPepN+oXyvJttRVUrz0ddKrv+m2BPBIStb7RhB/ydNkDpft3n/cu5bCn/KxeeVMUKBPw+idu3G7i0l46WXShk09qTn+X4MoivyncCXPNgRibG/m0Q+eZHix3HFXlGxgzJufEJU8AEkU2fD5F+wsqsSikEWyRot2ktSbsA+/kSEzrv+VSKHo97P9i38wvPh1NIKfFoKonfwiQ6dedtJzbC6rZ++aHZRWlGBVenAoPEd9v1nQE6oLIjw4lIioKKKSY4hKi0OtP/biLooir+Uv41/NYXjRYMbK0wkSl6ceOdjqKXS21rPh3utI3S6XGnujvf5E4La7WP7xIrIb8kEAPVpmjz+XITN7h1AriiLWpg7qi6ppqKmnqbmZVmsbbV4LXuHIa4xSUhAkqQnXGbjyL3f36HzOBiJnACRRpHDHz9g3vMEQ6wbUXRdCI6GUJV9J5uzbCYmIxWF1UJlTRO3+UporK+loqsFlaUD0W456bIU6CENANIGRsUQkJRPXP43EQWloDacuXJSzegerP3i927siKHoYlzx8D0FRoad8zFOBzePggd3LWHiIYNJ/BqYyJOzoqeueQMnuNVTddx/R9V2E1GnpTH3uQ4zmwwWBbO1WKvYWUltYSktVJZ3NtbhsDd2OqL+GgFITgj4wCmNIIqVCM5IgYULP/DkXkjr61JyRK/dn4/3mVtL8Mrdke9AcBtz85q8E7gp3rsa6/g2GdK7prg03iYGssQ/ElHY5c/8km4k5fU7e+vQb3OXVuAUvggQDmv30X7+IiulpTH/mA/SG/6178HQir62EP+QWUuKL5rIVr3PrT1vR+MGih/bfXcWs2/4KyKn8b9/8iBKnTHiPEtVcyjegaKc44QrS59zxK82g0pzNKBf+vptXti3sYobc9Bp648n51YBcJvzh5fep3L0SnTEctTECY3Q8NtFJq7vzMBfhQyFIAoFKA6H6YMJDwoiMiSQqJY6IlJhftSjvbinktrwyykU5G3KBoYyXhp2HSdN7JWhRFFn/3j8IeP0r9B6w6wQc993ApOsf6rUxj4bSHfv5celPdIgyhyXDnMC86y85rmLusWBvtVBfXE1DVT1NTU20WFpp9Vhw/6K9+wAUkkCQ0kSoMZiI0DAiY6KJSoklNCkSQQBR9Pd41uhsIHIa4XLayVn2HiH7PuxeJEA2J3INu4Uh515zQj+4pbWTir1F1BXJC57lwIJ3iDPq4RBQaUIxBEURFBVPZEoyCQPSieufdMwUv8NiZ8Fzb9BQsl4+itLE2Itv6dEWvxPFjqZ8bsuvproPJaRFUWTVKw8S8f4SND6wGgR8D/+R4XNupSK3hNqCEpqrKulorMFpaUA81BzuF1CoAtEHRBEUGU94YqIcIA5Ow9Vp59uPvqLG3QxAujme+TdfgSH45Elskiiy/evnGFrwL3SCl3bMVIx7mmHn3dD9HrfLQc7yDwnM/aDbDgAgx5fEto5EnPZILnrgERIGysHe9v272fjtJiw+uRQX5NMyevtOlK0FSI/ewdiLbzvpeZ4FuHxuHt2zhM8tiSRXZfP4+6+R1CQvFHuGhjPn7e8IDJbLnbsWb2LZ9tV4BT8aScl5UhEjFIvwSEpyAqcSMOXOw1r4XQ4bez68l7FNXwNQqYjDe+F/SBt6am2zeeuzWfHfl7pawwUSs+Zw0YO/w9lup6G4mobqAwteG63ezl8RYQ9AIQkEK82EmoKJCA0nMjaKqNQ4DDFmHs1Zzpc2+ZqLFRp5o38sYyN/O+fqWKjM30bxPbcRe8CC4Zwkpvzrkx7teDsReJ0eVnyyqKs1H/RomDlmKsNmH9uvx2V1yue/oo7GxkZaOlppdXfKYmpHgCBBgMJIqCGI8OCuADE5lojUmBMu9fYUzgYipwEN1SWUL32NfnULCO4qv7gkNTkhMwmddhepg8f2yDhtdc1U5BRTV1xKa3Ul1tY63PZGkI58YYIStS4MY3AMwTHxRKemkDAonejUOPau2sa6T97C75X7zEPiRnHJI3efdIngt0IURf6Vt4TXWiLwoiGITp5PVnNBUu+aWzXXlrDjrhtIzpOzQEWJOmpSxuK12fF72jm8ZfYgBKUJvSmSgIg4uWSWmUrSkIwjdrLk/ryTnzYux40XlaTg3KGTGH3RpFMqMbXUVVL38S0Mccm6EDm6kcRc/363r0RzXQWlS14jveZbQpEDJo+kYp1nCAVNAXhtfmL6TeOSR25Ho9Pi8/n46LOvaSwrxyPIDqODGz1kbFhEdWYAI177gIi43s1E/V/AksqtPFDmwupRcdvXT3PRpgoA6oIVqO+5n0lX3AxAc3kD3372NY0++XpME1VcKryFTpB30kWqDCxDbmHIeTd2l21y131P1Jr7CKcdr6RkZ8ofGX3NP06p1m9rs/DVky/QUbcbAJ05kYsffoTotMPbvkVRxNLQRn2xzDlobm6mxdZOm9eC7yglAJWkJERtRqfTU642UBEQSnGImfMT23lkyNxeJbJ63A5WPvE7khZmd2sAhT7/FAMnXNBrYx4NlbuL+eHHRd2KuWmmOC647hL0AUYaimuor6iluaGR5vZWWl0dR+TyHIAJPaH6IMKDQomIiiAqKZao9NjT6n9zKM4GIn0ESRQp2L4C18Y3GGLdiKqL+NNAOOUpV9F/zu0EhfV+C5koijRXNFCZW0R9SRltddXY2mrxOJr4pfCaDD2CMgTJ3yVjL5gwBKZhCjai0RvQGIzojEb0ZiM6swmD2YQh0IwxyIw5JABDgLHHvGTqbI38Yc8WdniTABijLuftYROINp64Uq3P48XWYcPebsHeacXRYcVhseG02nDZ7bgddjwOB26nA6/Lic/twGPfz+i8cgId4FHChv5GXIoIBOFggCAodGiNkZjDYrtIxHLAERR5fP8Gr9PDT+99x94WmT0fpgzk0isu7VZHPVlkL/+E5C2PEIwVl6Rmb//7GX25nGYu3LkK+4Y3GWJZ110CbCKEbYrJFBd1Inm9CEojk66+nZHny/X5vJxcVi5aQ0fXohfs1TJm2zYM9YU03DiTc+9/+SwhtQfR5Gjhj9kb2OxNZuzuhfz5s68Jtkt4lbBrdBKXvvQl5uBA/F4/Kz76gW3VOSBAAAaG6WqZ4PwUjSDfyy0EURx/Kemz7yIsJpGOlgbKPvgdw+1yVrNAPZDAaz4gJunU/F9WfbCAPcs/BsmLIOgYddEtJ8QTE/0irVVNNJTW0FjbQHNrMy32dtp91sOE1w6FWlKhU+gwqbTo1To0ajU6jRatVotWp0On06Ez6NDpdWhNBvQmPfoAI/oAIxqj9qSu0V3LPsH91+e6VZFrr57EjEfeOGkS+tHg83hxWhy4LA6cVgdOmwO33YXL6cTldOF2uXC53LjcLjo7OnH53fgR8eLHLrgO62o6FHq0hGoDCQ8MISIyksjEaKLT49EHnv7uymPhbCDSy3A5bOQsfZfQ/A+75ZhBVkF1j/g9Q6Zd0ecs7SNB9PmpLa6mal8RjeXltFRXYe+wIHpqoKuWKKhikXxN3f8/YQhaFAotCpUWpVqPSq1DpTWg1unR6PTdwYwc0JgwBJjQB5gwBpkxBQdgCjbzU912Hir300kAasnDLYpi5joScFvsuOx2nDYbbocDj8OOx+nA63bi87jweZ2IXhd+vwtJdHeZfJ0YJHyEOeoZUyzXvmtDBPYkxqDVp2EOiSE0LoHoNLlrKTQu4pQW47qCSr795tvuXc/wyAHMvuki1LqTvyZslnby37+N0R1LAFkdUXXpu0Qm9SN3+QcE5X5Aur+k+/0F6oG0ZVxDzupSHG1yWcYYksnljz9MSEw4lsZ2vvvsW6o665AECYUkMLjeRcbGn2gOUxD1wnP0GzPrpOd5FseHKIq8XrCMfzWFYuho4ZEPn2R0oZy5KopR4p9zExfcczcqlYrizftYuOIn7LhQSAJjEoZgZitp1V93ix56JSV7A6Zgmnw7GVmT2fXT2wzY/SRGwYVN0lMw/K+MnPfHUxJErM4vY+ELz3V7SYUljuWyx+/DYD55gTK/109zeR31ZbU01TXQ3NZCi6ODTr8d6SgByolAkEAtqNCgRqtQo1Gq0ao0aNUaNGotOq0GrVYOYnR6HTqjHtHvpOKr/xKbX4vKZaUuTknWq+8QFpWBo9OG0+rAZXXisjlwOpy4na6DQYTbjdvtxu314PF5cPu9eEQPbtGHR/IeblZ4CtBIKoIUJiJDwomIiCAqIYao9DjMYafOJTmdOBuI9BIaqoopX/oa/eu/Jwg5XeqUNOSGnkf49DtJHti72hanCp/Px6r3viNv3QIkvzxvtS6GhKETCYoIxmWz4bbbcTscuJ12vC4nXpcDn8eJ3+dG9LkQDyz6/LabDcBrULFz7iQ2hk4DINZXxfk/f01ARcdvPLIK4UBwpNKhVOtRa/SotHJw5PZUk7xpDVFtctYgd1wCI+99maRB/Xpk9y+KIpu/XcOavE34BRE9GuZNnsWAqaemIbB/x8+Yl9xGrNSIKAlsi7mOhJm3U/Xz27/qwNobPIOQqXfQUSuy/tM3un5nJZkTLmHOHdfidXpY89VSdlbu606fxzg1DNu6EVNj+VHJuWfR89jbUsQf80op90Uyf/Vb/H7RRnResGth08BoRl/2KGMunIqz3cZ3739FmV0OBhJ0kVx47cVU7P0Rw5736O/N7z5msSqdjkE3EdZvAq7v/tT9t2zTZFJveofA0JP3f/G4PXz/zJvUFsiCaipNGLPvfICM0T3D6/C6POzI3sk3hVW43Hr0Pi9xYiepWjN+rw+3x4Pb58bj8+Lxe3CLXjySD4/k+00BzC+hkISjZmxOBSpJgUZQo1F0BUgqNVqVFo1a053t0enk4Eij1dBQVktBcykWnCBArCaMmXNmkZiV1mNzOh04G4j0ICRRJH/LUtyb32KobSPKrgu2nnAq066h/+zbTukm7wuIosj2RWvZ9v0n+LqIkgp1EMNnX8XEq2af9OIriiIehwtrmwV7uxV7pxWnxYbDKpdB3HY7brucvfC4nHjdDnweF36vE7/PhehzUzcsjMUj5tOukMliE1tWMXLROlReJYJCi1KpQ6HWoVLLAYRaq5fLRXoDWoMBvcmEzmxCbzZhDDRjDOrKsoQEHNXf55eunR1mBcrH72H0Bb/7bSf4ENhbLb9aNC658QoCo05+Yfd63Oz85C+MrnoPpSBRL4VR0O92AmvXMdS6vrsEKHdgXUW/OXdgDAjl+2feoLZgFXBg0XiQ1OH92PHjBtbv3dJNcAvy6xi2O4eIkt3Y9ALeh//A+Ct6tnXvLI4Np8/JQ7uX8rUthYTavTz+/suk1cm/T3aKmrbYscy4+Q4yxgxiy3drWL3v18Ftyd6NtK/5N0Paf+42x2wlkMKY+ThEJZPrP0Qt+GkihMZprzB40oWnNNedSzYcMbjtqdKd2+fhiZwlfNSRgCQoCKeVl9IDmXEUF235OeTGZbHjtDi7SiBOnPYDGQwnLldX9sLjxu3z4PZ1ZTG6gxnvEYMPtaQ8GEQo1WiVGjRqDVqNBq1ai07XVTLS69AZ9OiNenQmAzqzAZ1Zjz7AcEqkUEeHjTVfLyO7Nr87s5IRkMjMi2cTltS3CrE9hbOBSA/AabeSu/QdwvM/6nYuBdinzcI74ncMmXblGSHBfjTs35LD6g/exdkpi1YJgo70secz8/dX/aY231NFvb2J+/duZLVbZs1H0sJfAv2cFzcaU5Cp1xjdv5R/LhsWybiXPyIk6thKpSeDX6bRJ2WMYdKVM1EoTyElXrwX51e3kuErwiWpWK2aSIZUSZpY1v2efM1gXMNvZcj0q1GpNV1p9GfxOOqAg2n0yuwifl63mlZRzpwYJC0ZlTVkbF2DgETZyBhGPfvWWULqacTy6u08XNpJk9fMLQue54o1BSgkaDHDttQwQqKnMvv23yF5xcPKfcMi+zPnpvmodRrammopWvIGyRVfEkkrIJdtsnVj8DstjBP2IQiwNfJKsm586ZSUm9vqW/jmyWextcpK0IeW+3oKq2t3cU9RO02Edds4PDl0DjpV7zyvvE4PlpYWtr77HNE/bUHrsONWi7TeOJtpdz/fY9yRk0FrVSMrv1vK/s4KQNb5yIruz/QrZp9Sl93pxNlA5DegrqKQqmWv0r9hIYFdDrgOSUtu2Gwiz72TpP5HjtLPFNSX1LD0zXdor93V9YqS6MxJzLnj5tOi1CqKIh8Ur+bZOi1WzAiSyBUBFTw1pG91BJwa6Lz9Mib/7m89tpPzebys/PjHbmJhoGDkkosuJmHoyZvwSaLI9u9eZvC+57Cgo0SMY6CikuCujgm5A+s8QqfdeVgH1qr3v2fPik8OIxYmD+rH8p+WUu2SRcnUkooom4cxy39A6fPQYVYgPfD7s1mQMwQ2j4MncpbzhTWBQfvX8JePPiSyw48IbOmno10TR/yA6cz43TWsX/DzUQnQPq+HnJ8/Q5f9LgO8+7qPXyTF0yHqGaIoo14Zi3TxO6QMOvkysiiKLHnjMwo3fgv4EZQmJl19WzcBuifQ7urk3j2rWOaUNyypijreGpjW+zpCe9dR9vAD3RuW6mQTKc++SNrQyb067tFQtbeU5UuWUduVydaiZlzGCM65ZDoqbd+24Z4qzgYiJwlJFMnb/BPezW8zxL65u/xSK0RSfaD8EtK38uYnC0trJ0te/4DagrUc6JQJjMpi9m2/O65PSW+htLOae3J3dXfEJCnqeTEjhnOie9eVsr2pis333kjKLtkjpTrJSObLb5LYf3SPjSG3Wn5Fo09ufR4QlMIFt1x2SnLYrY01VH1wC1pHHS40DBHKDuvAqki5in6/6MCytVn46h8v0FF/sNVy5q23sXvrLvLby0CQa98BBDBszTdENHVZgU9JY+LT/yUwtHelts/i5LGlIZf7C6tpsOm457OnmJEtX79VYQI5cVEohVAyxs0jLjOTpVt+7m4Jnz5kImPmTz4swC7N2Uzr6tcZ0r4SXVfZpk0yUSjGkyA0Up1xA6OvehyF8uS734q257H03y90W0DEZE7jkr/cftTS6Kng0+I1/K1GjQ0TGtzcG97K3QNm9Wonl9/vY/Wrfyb0w6XoPeBVQu0l45j+yL9Pi7u0KIrkr93Dqo1raO/KhAUIBqaMmkjWrDFnfFfb2UDkBOGwdZK79B0iCz4iSazqfj1XOxz/qN8zeMplZ3T5BWRC2Yr/fkXR5kVIotxzrjMnMe3GW+l/TtZpmZNf9PNK/jJebw7BhR4VXm4JruMvg2b3qlsuwI6f3sf7j38RbJF9YmouH8+5f3kDtabneut3/rSJ5TvW4BV8aFAxa/Q0hs85Nc2THcs+xrXpP8QIraQq6rtfz9MMxT3id0fswNq3bhcr33m5W3wqYcgcDOERZNfmddeXTcowQgvXMHanTFpsDlVjfPxBRsy67pTmeRZ9A7fPw3N5y3inLYqJW7/hnq8XY3ZKeFSwob8JlxCOShPGkOmXUtZQ3S2Sl2aK5+Jbfi2S19HSQMGSN0gu+5wo5MDBJynIEVNoV4Uz4MbXiE48+WyDw+rgm6depqViCwAafQwXPvhwt0heT6DCUsuf9u7s9poapa7gzaFjiTf3LmeitmQPOQ/dTlKXvlBDlJbwJ//GoIkX9eq4R4Pf62f7ovWsz92Ks4vnFakKZuaMGaSOGXBa5nQiOBuIHAcleTuo+uZhRkj5BAqy4p5D0pIbPpeoc+8ksd+Z4ZR4LIiiyOavV7Dzp8/xe+UbRqkJZfSF1zL24umnLVre21LEPfmFFPjldPEAZTWvDMjs9dSq02Fh1aM3d/vENIepCXnmHz368HBZnfzw3jcUdMh8jSh1CJdec/lJk8n8Ph95W5bQtPpNRoo5BAlyCdApacgJnUXE9DuO2IHl8/lY9NJ7lO9aDIgoVMGkjz2fvNbSbilusxCIxdvG3J++w+yS8AtQeX4WU594C4Mp6Dd9/7PoO+S1lXDPvnwamvz85YNnyCqVd8QFcSpKwqJQSlo0pgTiB09gb3tJl22AjvmzLzji4uTzeshd/QWaXe92G+cBlIjRlARNZMjFD5yS7sjGL5exfeG7sqeSoGbozGuZduP8Hnv++EU//8pbyutdYodmrDyVIHJFau+WTERRZP0HT2N44wvMDglRgPJZA5nyt/9gCuxb24sDcFmdrPtmOTsqc7s731KNscycP4fItBMzP+xLnA1EjoOlr9/D7NYPAKiRQimUklBGDyJ61EWkD5t8SunKvsS+tTtZ+8n7uG1yFkdQGOg/8SJm3HpZn8v4HoDL5+bp3KV80BGLDzU6nNwd3s5dA87rVdVEgMIdK6h78M9ENci7hdKpaUx59sMefWBU7inh+x8W0CnZZYOyhCxmXj/vV74aR0NnWzPFWxZC4XJSO7d0cz8AaqVQKlKuZtD5dx61A6uxrI5vn3kGl6UcCYhImEyrCTolOYgxoacmKJLRK99kWNeiVRerI+app07ItO8szjz4RT9vFqzg5Xoj81a8x82Lt3f71WzKDEWSggAIix1PS4ASK04ECcYmZnHudUe/Nsv2baN+2YsMt65FLxz0kilXxNMQOZnAofPIGDHthLWQGspq+e6fz+CyVgBySfjKJ/6MqQedZrObCri9oKLbr2auvpSXhs0kUHvy/jong5a6UrY+8kdSt9UA0BqsQvvovYw6/+ZeHfdY6Khr4+dvl5DXWoIkyL4/Q8IzmH75LAJOk2P7kXA2EDkOKgtzqP3yLhySminiDlSKg6eglUDKAseh7DeL9PEXYg48c3QVqvPLWPbWO1iacrteURE/aDpz7rjxiPLifYWN9Xu5v7COSkl+SIxSV/DK4BGkBp6aiuiJwu/38fPzdxP96WrUfrAYBcSH/8S4y+7ssTFEv8jaL5axsXgHoiBhRMdF580jfdzAY35OEkWqivZQv2Mh5urVZLrzunkfABbJQIEYT2fSHKbf8NgxS4CbvlnBtu/fQRKdGAOS8Mem0NylIaJFjTMkDnvVKq5dvgOdFzwqqL9iItMfeq1HS1JncXpQYanlnpztNJW08tgHr5PcKAcP2f0CqNMGo0CFUmnAmDqeWmUHANHqUC697nJCE44uLdDSUM329+8nyVVAhlBz2PXZiZFi81jIOI/08RcdV6LA5/PxwwvvULFnCSChUAUx43f3MGhKz5H7nT4nf9mzlC8tSUiCgmihmVczwpkUk9VjYxwNW797A//zbxHSKWciSs9JYsIz/yU4vHefccdCXUElyxcto9Ipl3TVkooxKVlMuuzcM0Lm/WwgchJoa6qldPNCFCUryLBuwywc1Pb3SkoKdYOxJUwndsx84tMG98ocjoeOhlYWv/4eDSUbOSAoFhI3ijm3/47IlJjTMicAq8fGY3tX8LVVfjCYsfJIjJsb06f1emmoriyXnLt/R2KxrExZPiiMka+816OtqJ0NbXz74Zfd3SepxlguvvkKjKFHvhbdLgdF25bh2LeYuJYNxEqNh/29XIyiQQoiULBjNyaRfsu7x7QAcNkcfPPUqzSVb0KrC0UVO4gGjZwBUUoKIoNjWPD/2jvv8KjK7I9/pmRKeu+9EwKB0HsHsSBi72V1f65dd11ddS3rKvZdFctiXRUVC1iR3ntIgxDSe8+kTTKTqff+/pgwEOmYgsv9PI/PLnfu3Pfcycx7z3vec77H1cr/LV9KUq2ja3BVnAeJL/6bmNT+7dMjMbAIgsBnJZt5sdzCNd++xaKtJY6+KT4KclKGYO1yzFtegSNo9FU7muehZP64WadsrFawZy3yXx5EL2hBhHh5nXO7EMAuyihSpdAeMYuQMZcSlZR+QrXWA5v2sf79f/U0h5QRnX4xl/75Dyj7MNful6o9/KXUSAs+yLFzm3cNTw6/EJWif6PBne1NbHn8DmI2FCEHOtzl2B64hck3PNyv456Kgu0HWL9pPTq7Yy50R8OUERMZc8nks5IQ6CskR+QssVrMFGaspWv/z4Q2byVSqO31erUslNrAqbgPu4jEMXOdjaf6C5Ohm9XvLKN03y/Opnau3gnM+sPtJI49+Yq8v/m5chd/KzPQhEOYbJa6jFfTphDs1v/VRVs/WYzra5/iZhIxK0F3x8XMvPfFPnV+8jZm8dPW1ZiwoBDlzEydxITLZxwzhq6ukrJdK3EpW0dSVwausiPNBy2ikgLtCGrV8cS1bSVRXodRVHMw7XFGL7z3pNLbJZmH+Pn1lxDtXbiFjqDe1eYQYBIh3jOCtTFaotZ/w1WbD6EUwKiGtj8sYMbdzw2K/oHEwNBk1PFw7hZ0+4p45NPPCNAL2GVwcHoSDUYfbKZm1Fp/7OFDaFM6nJNU33guvu1yNO4nrujSt7dQ+NGdjOlYi12EbbIxyHyjiWzP6KWjBA4xxyr/KWiHXkTi+PnH6JLoWzr46pmX6GjMBUDjGcMVf/tbny6amrtbuS97M5t6dImS5DW8OyyFIb59lyx7InI2fEnH088T2OyoRiofEcioF98lKGpIv499IgS7wL6fd7A1awddOBYl/govZk+fSfKU/q1SPBGSI9JHVJccoHbvd7hVbiDJtB/VUZ0lu0QtRR5jsMfPI3bCQvyCwk9ypTNDsNnZvOwnctd+5Ww7r9QEMeGKGxl7yfQ+G+dsaO5u5eHczc46f39aeTZaxWUxZ9d+/EzoaKln259vJm53NQC14VpiXnuduOFT+mwMq8nCqg9XkN3kEG7yk3ty+ZWXEzrEkbkv2O2U7t+BLusH/Os3k2Ar7vX+Znwo95mEy5D5hKdOofyrR519YoqUiWiv+fCkkTVBEFj9zhcUbFuJZ0gqTZ5KLD3NzsLVgWjTw/mi7CD3LfucCJ3jePnwAEa++DYhMf3bUl3i3OGHip08d6CGWz9ZwrQDjsqZ6kgtnXOvoSorG8FuwDNiLLVuNpCBt9ydyy9bRMSwkz+o9/20lMR9T+GJEYOoIX/kk4SlzaZ673doyteR3J3jVHEFR5J/odsorLFziJ5wGYFhMYDje7zhwxXsX7/MoXEj1zD2sjuYfNW8Pv0cPixcz7N1rnTjihoTjwR3cGfSnH6PyHYb9Wx89i4iv8/sWQjIaL/jUmbc9dygltVajCa2frOePaU5WHvmjShNMHMXXEBYSvSA2iI5Iv1AZ0crxbt+wFawhrj2Hc426wCCKKPYJZHWsBkEpC8gbtiEs2o0BZC1eifbv/wIa8++n1zhQerMy5lxy8I+DW+eDctKNvGPajkdeCETBRa6V7B4+Gy8Nf3/t8leuwzjk4vxbbcjyKBi4SjmPL0Ulbrv6vvrC6v59quv0dkd+RcjApK56LZFmK0Ginb9hO3QKmLbd+JPe6/3FSkTaQmdgX/6JcQNm4hcoaBg3wbcf76LcLHB0Scm/BZG3/wiLqoTay20N7Tw5bMvopDJaff1xCB35AL4yj2YOGEib1JAyufLuXhXJXIcOTHm+29m8g0Pn/OaAhJ9T4e5kyf2r6Pzl83c8+063MxgcoHmP1xMpzmWiux1uHtF0B4USLfcilyUMS1pPFOuOfmDur6ykLbPbnOKomW6Tyf+tvfx8g3A2NVB0e5VmPNXEdO63dmA7zAlijh0IdPxTV9AfNoUqvPL+f7VF53zWUDMRK564gE07n33uy1ur+JP+3PIs0cCMElVzlsjJg9IdLZg7xpqHvsbYTWO6FNVgidJL/yb6KEn3w7rbzqbO9jw1Spym4oQZSIyEVJ845hz5UV4hw5M3qPkiPQzgt1OSe42WntWxfH20l6vN+FLue9k1EPmkzjhIlzdT909sSy7kHXvveeUUEamInrkPObfdeNZdbzsS6o663hw/x52WByrnTBZIy/H+zHzBL0g+hJLt5F1T99B9A9ZyEVH1rr7Px9nxKxr+mwMQRDYs3ILG/ZvwyYT0ODC1NR05NYs3CrW90TDbM7zDaKGQvcx2OLnEjthIf7Bkc7XbFYLGZ/9nTEVS1HKBBoIoHXem6RMOHkb9cxfdpD5/Xd0+/vRpnSEVl1RM3X4BPTprnzy7df8cfkqAvSOHKGSCRFMWvxen0rVS/w+2VKXzfPbd3P7B++TWumQIygZ7kfy3/7F7uXraa05gEtkGk0qx8MyQhXIlX+4Fs+gE1dY2G02Mj57klHl7+Iis9OIH7o5bzJ00pEKLFEQKMvbTVPm9/jWbibBWohc9qvEf++JyOLncGh3E03FOwBQqgO46L6/Ej+677YybIKNFw6s4p3WUOwo8aaDF2OUXBo9qc/GOBFWi4mNrz5E0LJNqG1gVkLDtdOZ9fC/Bj1ZvLGklrUrf6HU4Kj6UYpyRkUOZ8ZV885KfPFMkByRAaaptpyKw3kChsxeeQJm0YUC7QhMMXOIHL+QkKjetfq6miZ+fvM9dBW7ARGQERAzgQvvuR3/8MCBvZFfIQgCbxes5bVGT4y4osDGDV7VPDnsAtxc+vdLDA7Z5co/P0hoz2qjdGIUU1/5GE/fvhM0MrTqWfnhV5R0OX6owbgxjZ8YQk6v82pkwdQETMUt9WISx85BrTnWOayrKKRj2S3Ozqf7PGaRcNtSvHz8Tzi+xWzhu+eXorManA8KpahgbHQa4y6byj8zvyZ66WfMzHUkzOq8Faj/dh9jL/1jX9y+xP8IJpuZZ3N+xLrsG25ck+to7ugmg8fuJjRxHqvffQ+FUk29twK7TEQjunDhpDkMn3tyteGirC1of7yTCLHOEdkLu5FRN7983Py4lsYaynZ9h6JkDQmdGb0S/y2ignz5EPLa/WhukyF0Q/KUK5l/13V9Gs3b3ZjHPYdqqREdVT6L3Mp4acQFuKv6fzFXmb+HQ4/c70ygrwvXEvbc8ySPu6Dfxz4VpXsLWLt2LY02RwRLi4rJQ8cxfuH005YgOFMkR2QQMXUbKNr9C90HVxHRso1QsanX6+XyKBqCpqFNnEfxzkqqDqwH0bHn6u43hHn/90ei0xIGw/Re5LeW8kBeHvvtjhV3gryW14bEMCaw/5X8BEFgw+t/JeCDn1HbwKCR0f3nW5hy41/7dJz963exZttmDDIzMlHGZKGVGfL/IpeJ2EQ5hepUOiNnETp2IRHxw0+63bbvh3dJynwaD1k3XaKWglFPM3rBnScdv2hXHlu+/4U6tbEnfCojxSeWuddcRLm8ifeXvsoNK3bgZRQRgJK5Scx69n3cvU7s2Eic32Q1F/DSD99w20fLnTlEB6dFM/+VZRTvLiJjxXd0+nuhVzgWS/GKEK546CY0bideWBg62zn44d2MbfsJgGJFPOqrPyAyccQJ32MxmyjKWEvXgZ8Ja9pKhFjX6/UKeyC5pkiabHEseOBJgqL6Lseuy2Lk4ZzVrDQ48mHCZY0sGRLG+KD+z6ESBIHN7/4dz6UrcTOJ2ORQdUk6M596B63r4D7DBEEgd80eNu3dhl50RM585O5MHjOWyJHRBBwV2e0LJEfkHEEUBCoLs6jP+B6v6o0kWQ7SYA5mmy6dui6LQ40QULr4EhkXQNiIaDzDkgmOHXbSss7+xGK38vLB1bzbEoQVFSrM/MmviYdT56OU93+OSlNNEZn33+qUV65M8ibt3++ddSKmzWqhobKIlqp8uusLkLWWoO2oocw8nly5ClEGnqILi8SNeMkLKfGagDzpAuInXHrSSMZhOtp0FH/0f4zWrwfgkEsKXtd9RGhM8gnfU72/jI3frabarsPWo90QJvPl4qsvIygxjFc3LCXozY8ZU9SzsgpUEviPpxk2/fKz+gwkzi9sgo1XM1cgf/sDLt7lED2s81cSsPhZUictYPMnP1JyqIA6rSNi4W3XEunqz8zbLsM76MT5A9lr/kvMrsfwpgujqCZv2KOMWfTAaeXDVRfnUrv3e9yrNpBkOoDLUYn/VlFBnSyIVtdozJ4xyAMScQ9LJigmFd+A0LPOt1tZvp2/VdhpxwsFNv7kW8ejwy4ckHmssfIQ+x79E7HZjhL+pgAXvJ78GyPmXNvvYx8Pu81GY3UJuoo8DHWH6C7PxcNSTbisiRBZK1uEMUx+cg0KZd9FRyRH5BxDsNnJ+HkrWb/8iLGtGMcWDMjlboz07WKq3w7k8t5/hjY8aFSG0+kejc0nDnVwMr6RQwiJSTnutkBfsLfxIA8VVFAiOOSCRygreT11OEk+Mf0y3q/Zufx1FC/9B0+DiEUBjTfPYdafXztlOaooCLTp6mkqP0hn7SFszUVoOsrwNVUTYq/rVe1UKaTzHXNo60kEjROUxIS04T96Pgkjp59Rb6H83avxXX0PwTRjE+VkRP+RMTc8e1xFSqvJQu66vWTkZNJob3Me97ZrmThqImMXTqGivYYPXv4LC3/MxdUCNjkULxzJxX9/f1Cabkn8viluq+T1/77GdZ+uw8fgWJ3nLRrJlU99jN0q8uNrn1JkbcAisyEXZYR2ylHIBMZfdukJ+1Q11ZbT9MktpJpzAMh2nUj0rR/iE3D6TRT17S2U7PqB7pzvSTbtw0/WeeJzcaNBGUaHW888GJSEd0QKobFD0bi6n/B9h6k3NHF39g52Wh1z2DBFFe+mjex3scXD7Pj8NRSvfYBXl2PBUTozgan/XNqn28tH09HSSH3ZATprC7A1FaHuKMOnu4pQe12vaqdfkysmkfbM3j615ZxwRCoqKnj22WfZuHEjDQ0NhIaGcsMNN/D444+jUp2edPDv3RFpb2hhy7LvKM/ejN165OGj9YojdcY8okdF0l5bgLG+AFlrKW6dZQSYqwmi5YTXtIsyGuSBtKgjMXrGIPNPwC00mYDooQSGxpzV6sFg7eaZ/atZpo/AjhI3DPwluIv/G4AyOICujhY2//Vm4rY4kn7rQ9SEv/wKiaNn9zrP1G2gvjyftqqDWBqKULSV4GmoJNhWjReG413a8T7RhRpZFNlcRr5oR+zZI58xciLjFs44Y3utFjP7/vsIY2s+RiETqZEF03XR2ySPnnXMuS1VjexZs4MDtQXOfjAyUUagRUOgux+XPHwTKpWKj1a/jedr75NS5VillkWoiVv8Msmj55yxfRIShxEEgf/s+hztK28x7lA7AEXRGoa89haJKRNpKKnlh8++oQ7H/ORt06CqLcGOnORJc5lyzYXHVLgIdjt7v3iW9OI3Ucls6PCmfsa/GDZt0RnbZ9R38vVLr2JozsZdY8NXbSHMzUSwWE+QqOuV/NrLBlFGo8wfnToCo0cM+CfgGpKEf/RQgsLje7XpEASBdwvW8mKjN2Y0uGLkiVAjtyXNPu61+5p2XS3bH/sjcVsdParaPBXI//onxl9x91ldz2wy0lB+iNbqQ5gaClG0luBhqCDYWoNPj+Ly8bCISuoUIbRpozB5xqIITMAzbAgqTSj+waF9Lg9/Tjgiq1evZvny5Vx77bXEx8eTl5fHHXfcwY033sgrr7xyWtf4vToiB7dls3fl97TW5gA91RYyNUFxY5l81aJT5oAYuzqoLztIe3U+lqZiXNpK8DJWEmKtwf2oBLBj3ieqqVOG0+EaicU7DpfARLzChxASNwx3z+N/ydbV7OPRklZqRUdi7BRVGa8Nn9jvHS4Pc2DLStoee4qAFisCUD4/lWF3/R19fTnG+kOgK0bbWYG/uYpgofmEExNAAwE090xMol88bqHJ+EcPxdIq54cff6RFcPxI490jWHDTorP64VWXHKD7y9tItBUBsNf7QlJue7vX5yvYBQq27Sdj714qDHWIMsdxreCCr0HArm9l7l13EjsyCZ2+mY+fuo05a0tQ2R3ll8VXj2fRI/857V4fEhKnokZfz9LXHmbhiky0FocA3sFbZ3LDfW8CkPHDdjZkbz0qOgIdtfuQydQEJ4xn8jWLjumsW7p/J8rv/kiU4ND12R14NSNu/dcxAmenQ+76PWz6eIlzweYXOY6LH7idzvYq2qrysTQW9yw8Kgix1eB5koVHt6iiXhFKu2skZq84lIGJeIYl0+XnxUNV9RQKjnyUGeoy3hw5A3/twPRn2ffzR3Q/9xr+rY5nQunYMMa/8B/8Q+OOOVcUBJrrK2mqyMNQW4CoK0bbWY6fqYoQoRHFSebBJnxpUkdicI9G9ItHG5KMf1QqwZEJA9pN/pxwRI7Hyy+/zDvvvENZWdlpnf97ckRMXUa2fvEzhTvWYek+kpjlogkmaeIcplx7Ma6eZ/4DPRpREGhpqqGxLI+u2kOIumI0+sNfzoZevSJ+TTM+NKki6Or5ctpCYvhAIecXwZF74UM792vrmefR/8qEADabhdyPXiV5TSEKEVo9oGuSkilejb2qjn6NHlcalOGOUK13LKqgZHwiUwiJSUHr1rvfjs1iZcNnP7O7MtcRBcGFuWNnkn7hmdf4i4JAxso3SN3/PK4yMx24UTL2OUZdeKvzHEOLnr2/bCe7NM+ZDAbgb9WibmtB31JMzKj5LHjgVpQqF1b8tATty0uJbnSETA8muDHypSXEDRl/xvZJSJwO/92wFK/F75BU48hPyxjmzeTX3ic2YijtdTpWfvoNld0NAPjYtChrizAZHXkOrt4JDJ89n3GXzXRqGnUbOtn/0X2M060AoFweDVe8T0zKmDO2zag3sOKFJTSWbgNArvRkyrV3Mvriqb3OO7wV21ieR2fNIey64p6t2CpC7PW9tmJ/TQteVCmCKVBGUKKNoM49kNlx4aQHnnnn4bPB1N1F3vL/EJRVhQzodpHRPW88ofHJ2JqKcWkvw9tYQYitFjeZ6YTXMYgax6LTLRqrdywuQYl4h6cQEjsUNw/vAbmXU3HOOiJPPPEEq1evZt++fcd93Ww2YzYfeQjp9XoiIiLOaUek6mAZ279cQUPxbmfyKSjwCU1j7KULSJmaPiDbG1aLmfqKQ7RW5mNqLETeUoJ7VwWB1ppeAlwGuYo3ky/nQ/9r0csc+iYXGVbz4v4l+FtOvFfbl+zXu9K8z4vQJkeooCzBzsS0ZnyUDkfKKiqoVwTToonqSV5LwD1syBklr9XklfPdyu+c/Rfi3MK49KYrTqqdcCLadQ2UfXQ76QbHBHlQlYb/TR8RFO5YyVRmF7N7yy6K2iqw9ziDKlFJkEWLqSEfk7ERF20IF97zEPGjh3AgdwNZi59kdE4rcqBTK6PgpunccP8SSZhMot9p1Dew7MnbmbumFIUIbW4ydl09gTvuex13lSsZ329jfc42rDIbClFOeLcrrZVbcOa2KT2JSpvG1Osuc0oM5G78kvCtf8WPDsyiC9nJDzHu6kfPaqs4e81ONn/yNoKtHQD/6Alc/uh9p9XY80hyeh7d9UXIWktw7ywnwFJzjPjauY5NlNMgD6JFE0m3Zywy/3jcQx3zoF9wxFkn8Q4U56QjUlpaSnp6Oq+++iq33377cc95+umneeaZZ445fq45IjabjT0rN7J//S8Y249IfMuVXkSPmMG06y/FN7T/Vf1Ol442HTWlOXzdcpCvXIbRKnNkxocIdTxW/g4zavYPiB3tVhkHD2lIzHc4IAY1VE/SEJKUAn4JaEKS8YsaSkhU0llvS9itdjYu+5ld5dkIMhE1LswdM52R8yec1UM+b9v3BG54gEBasYgKsuLuZsx1T2G32Mhes4fMg9k09UyYAH4KT8LVflTmrsZu6wTkRI+YzyUP/YHm6gI2PXc/aXsa6PG52Dvcm/GLl5AUN+qs7ldC4mz5YsUrBL7yMaGtjgjCgWhXqu+8lrsvvhdDvZ7vl31DlckRDQmUe+NrlVFXsg1ROLzgkuMVPJyxCxaQOmM0rU211H58K2mmDAByNWMIu+XDXoJ/p0tXeycrX1hCU7lDBE2u9GLqDXcxav7ZC5R16duoL8ujo+YQ1sYilG3FuBkq8Bcc20EyQCY7/P8GCFHALspptnrR3u1Om6BFNXwCyVOuICQ6ud/7mfUn/eqInMhZOJqMjAxGjz6iullXV8e0adOYNm0a77///gnfd65HRHQ1TWxZtpKq/VsQbEeSgtx8EkmbeyFjFkwfdBn2X2MTbHxcvIkl9dAgOpwjP9q4M9DEH5NmoVb2fx6C3W5j8zt/x/OD73HvdnzdSidGMu7ZtwgIi++zceoOVbLymxU090RBYlxDWXjTFXgFn7mksdlkJPvjvzC+YRkAVfIwLJcuxdMtlt3rtnOwsQhzT/6PXJSR4BXF0NSh7P7hWzqbHdLYLppgLrj7QXzC1Gxe/ACJm0pR9USNc+Ldsd1+NTcu/Esf3LmExNnR2dXGl0/fytjVhahsjkqtn6bE4HnHbfwh7RKyf9jJxv3bscrsKEQ5k+JHYTd3U7BjHRbjkaagSk0QieNmM+WaCzm49m3SDr2KRmalFU+qprx81krImau2s3XZO86eW4Gxk7n8b/f+5m3uo9lQs4+/leioEh15cUnyGl5KjmbcAOiOgKPUN+OlR4naVORcoJQP8yf2L4+fE2JoZ0u/OiI6nQ6dTnfSc6Kjo9FoHJ5cXV0dM2bMYNy4cXz88cdntCo9F3JEBEEgb9M+9v7wAx0N+wHHN0Um1xKSOIHJ1ywiYkj0oNh2MgRB4Muyrfy7xuT8gXmh5w/+eu5OnjUgyqgAh3b/Qs1Tfye80pFc1hCsxvuxhxk59/o+G8NutbPpi1/YWZqJIBNRoWR2+jRGXzzprKIglQVZ2L7+A3F2Ry7Tbp/LUCXcQc7+/c4VIoA7WkbEDmXsBZPIWb+LfT9+hCh0A3Iih89j+q0Xsev1vxGxKgdNT+XcwUgtBdfM5c83PYVWOTB/AwmJU1Gcv53cxx5iaIFje7bZU86ni2Yw5bKFXKBK4YcvV1JjdjTXC3Hx47JrL6elvok9K3+gpTqLI0n5KgJjxxI/IZWg7MeJ7encu8dvIcNvW3JMHtfp0NXWybeLX0dXuRsAuYs3M26+hxFz+i6Xymyz8Fr+Gv7T4o8JLTJRYJF7Bc8On4mvxrvPxjkZ1UWZ5L74BDE7Kzis5lA2OpTkvz7dp409B4pzZmumtraWGTNmMGrUKD777DMUijMTSxlMR6SrvZNtn/9E0Z712I56+KjcwkmZPJdJV88/qRrhYCEIAj9W7eLlynanHogbBm7y0fHAkJl4qc98IjgbOlrq2fbM3cSsO4RchG4VNF87kxkPvdy3jeoKqln5zQqabI7warQ2hIU3Xo536Jmrj4qCwN6vXyYt/2U0Mis1Yhx7ve6kTN/qbK2NCFGuwYwZM4YhU0fQ0dzGisWv0dHo2N5SqgOZevMtNGz7hIDvduDW87aSEDVrF07j7hvuJ9lvYBKCJSTOlM2fv4zi9Y/x73AsuPYleLL8uhu4ZUwawVlmNh/cjU1mRynKmTpkPJOvnI2+pYOty76jLHMTduuRPAyNRzT+fi5cpv4EldxGpTwc66VLiU87u+2VvT9uZscXSxF6mlIGx0/lskfv6dNeXBX6Wh7N28Nms+M36k0HD4dauTVh5oDlb5Xu30bBS08Tu89R9CDIoHxiNCMefZ7whJEDYkNfcE44Ioe3YyIjI/nkk096OSHBwadXGjoYjkhZViE7vl5JU/leEC09R5X4RaQzftFCkicOHxA7zoZ1Nft4oayeg3aHWI8aE9d41vNwyvQBK1ETBIGtH/0TzTvLnSI+ZaNCSP/nG33apt5us7PlyzXsKN6HXSagQsmsEVMYs2DKWU0YLY011Hx8G8OMeygXJ7CNaVTJLAg9ZXJqXEgNTmTc3EkExoYCsP3L1ez9/kNEwQjICB0yFW9NJb5fb8TT4HhfVYALX104jblXXM7VCdP76vYlJPoNQ2cr6//xJ2J/3o9SAIsCvpqRwp5Lr+JBz0DqNuRTa3FER8JU/iy89goCYoIRbHYyf9lB1uqf6NId4nByq0zuRpCbitn+u/FRt5CVcC9jr32yl9bH6aJv6WDF4tdpqXaIbylcfJl56z0Mn3Xynjlnyk+Vu3iyvJO6HlmDYYoqXkpJYqT/wFTXABTsWU3ZK88Rc8CxA2GTQ+XMJMY+8iKBEQNnx9lyTjgiH3/8MbfeeutxXzvdIQfKEbGYLez+dj0HNq7C1FnhPK5w8SVu9EymXHcp3n0s9tKX7Kzfz3MlZWTaogFwwcJl7jU8OmQSoe5BA2ZHSfZmSv/+CJEljhVLs58LmkfuZeyCO/p0nIbiGlYuX+Fs4BSpCWLhDVfgG352CcK5m74mYPOTlAtTyZRF0Sq3OF8LUvqQnjqSkXPHonJ1bDe2N7by7eJ/0V6fDYBC5UNEtJaQNTvw6emO2+Cj4NMLpuM/fxpPjrgQd1Xf7WlLSAwEJblbKHrir8QUO37P9T4K3rzicsyjR3J7uYX88gJsMgGlqGD60IlMvGKGcxFQX1LDti9WUpO/HVE4rPkhw1PtQ7pvJS4BEHzLxwSGnZ1q8+7vNrLrq/cQ7I6tpJDE6Sx65K5jxNd+C922bl7IW8uHbSFYUaHAxjUe1Tw9fA4eqlOruvYV+zd/Q92rrzib6ZmVUHvBcCb85aVzuvv2OeGI9AX97Yg0ltWx9fMVVOdvR7R39RyV4eGfQvr8i0i/YBLyPtTe72uymgt4vugQ2y2OH7MCGxe6VvJY8jhivPquidSp6OpoYcs/7ybyZ0fXT4sS6q6YyMxHXket7bsfrN1mZ9vydWwr2otdJuAiKpg5fDLjLpt2VlEQk7GL3e88TXu7moNyDdYe/QGFKCfJN4Zx0yYQNaJ3Mu2Or9eyZ+UHiHYDoiji7etK4oECAloce+QtHnKWzZ1Ixay5vDg8jeH+ib/9xiUkBglBENj+yYu4vPUZ3p0OJ3tnii9vXPMg49UCaQfqndui4epAFl53Of5RRxY/FpOZnd+s5eDm1Zg6K53HFQoPojztBM2Zy8TLj19FeSr0una+ff7ftNY65CAUKj9m/+FeUqePPsU7z4yitgr+ejCb3T0y8f608liEnGtipw5ouf2+nz+i7Y23nPl2RjU0LhjH5Adf6DfJ+N+C5IicgqxVO9my/HMEUyVHhw/DUyYz5drLCIkfuIf42XCotYznCnLYYIpGlMmRiQKzNBU8njyCIb4Dl38gCAK7vvw3vP4hvh2Oh3j5MH9Sn32NyOQzFzQ6GU0ldaxc/i31Vof8fYQ6kIXXX45f5JlFfAS7QE1eObnbd1LbWEOD/EiVlpfMlZEJwxlzwUTcfHt/39qb2ljxwr9pq81EFAWUSjPDa5oJaXJkoXa4ylg+cxQb5lzLn2PU3Bg/Q9IEkfifQd/awNZ/3EP0moMoRIcC8LI5I1k+9y7uKynG1FztXBzMGDaJ8YumH/P9L8nIZ+c339FcmeHsOA5KtG7BxIydSvrc6QT1bHueCbu+Xc+ub9/vWUzKCBsyk4UP39nnOXxflW7l2SorzfgBMMalgpdShg/4nLvn27fofvsDQuodc1eXVkbLFdOYev9iXN29B8yWUyE5Iqfg28UfUpHjUALEJRibdzDuAQHEhEYQOySB2PQEZxj+XKK8o4bnC/awyhiFHUeZ8GRVOY8lDiE94MTdXvuDyvw95D/xENH5ju2RVm8FsgfvYOLV9/fpOIJdYPtX69hSsMc50U1PnciEy0/vQS8IAg2F1ZTkFlJRXUmtodFZdgsgEyHcxZeJU6eSNGk4csWx19y1cgO7vn4PwaZHJu9gaH0nUT1qqAY1fDttGMvn/R8XB3bwzLBZ+Gi8+u4DkJA4hyjYu4aqp54gotwRQa4KcOH1q66lO2QCl+Zn0d7TRiFSE8Sl11+BX8Sx26VdrXo2f/YdxXvWIdjaer2mcPHFJyyJ6OEjGDZj7GnrMbU3tvLtC/+ivc6xXapU+zP7jvsZOqVvkzu7LAaePbCWz3r6crlg4SbvOh5LnTdglYjgkETY8enL8P4XBOgcc1G7h5yu6+Yz7c5/nBNNMiVH5BS01ulY8eLbuPgEoJPp6RR7929RiHKC1b5EhUQSlxJP1IgElGqXPhv/TKk3NLE4fzsru8Kx4tD9GKWs4LH4GCaFpA2oLd1GPZuev4+wlXtQ2R0JVFUL0pn++Ju4eZy5XsfJaC6rZ+WX31JncSRrhakDuOzay/GPPnEYUhAEdBUNlGQVUF5ZQU1ng7PZ3GFcRAWhIngrYcTCRcQMH3rca+lbOhyh35oMRHkHiQ1tJNQ7Ij8mF/h+UhLLLrqLcC8zLyXHMSYwpY/uXELi3MVut7HlvWdwX/otHkbH42NTWiBvX/kgl9R249pa3LNoUDJrxGTGXnr8LQxBEFj3wX+p37OVzm4LFpuewxHqwyg1QfiFJxIzYiTDZozF09/7pLZt/2oNe1d+2JOXIiM8ZTYLH74Ttau6j+7ewQFdMX89lE+2zZGjESxr5qkoLZfFTO7TcU6F1WJi2wf/RP3f7/Btd8xNLT4KrLcsYvKtj+GiGrwFteSInCG6igZKsgsoL6+gWl+Pkd69TpSiglCtP1GhkcQPSyR8WCyKAcgd0XW38fKhzXzZEYIZxxdqqKKaR2NDmBPet/ugp8Oele9iefktZ9OmyiRvEp59qc9r3AW7wM5vN7L54C5nqeC0lAlMumLWcSMWrTXNFO87REV5OdUd9UdKbXtQiHICRRVxYiOxsjwU8no6Zz9P6uQFJ7Rh7/eb2bH8P9jFOmKaW0ipcfzIrQpYNS6aTy6+C6uPNw8FG/lj0mwU8nM3l0hCoj9oa6pix5N3E7O5BDmOnIWPLxjPofQbuaAghy7RER2J0gaz8IYr8Ak7fkm9xWwi88t/EFf4OcWdiZQZgtCZOSZaAjJUriH4RyYTl55O6owxxxU2a29o4ZvF/6KjIQcApTqAeXc+2OcVj4Ig8GnJJl6sVdCKN+CIUL+UOppYr4g+HetUmLu72PrOk3h8vsZZrdgU4ILsjuuZdP2fUSgGXmhTckR+A4Ig0FRSS0lOERVVFdR0NWDC2uscFUrCXAOJDo8iPi2JkOTI4z4gz5YOcyf/PrSRT9r8MeD4ocXLa3k4yptLIs9Oqvy3UFe6n5zH7yMmx6Gn0u4hx3r3DUy+6ZE+t0VX2ch3n3/jFE8KVflx2TVXEBAb4jxH39hG8b5DlJeWUd1WT4fYuxOnXJQRpPIlIjAMF0MR41vfwENuwCy6kBV1G+nXPY1ac/zQZVernm8Wv05zzUYiW3UMr3Q4XXYZbBgVwocL7qLJP5aL3cp5bth0Al39+vT+JSR+b+Rt+47GZ/5BaI0jslwe7MK/rrqFMZYQNG1FR0QGR05l9CWTTzhn1JYdQvfVvU6J+IOWJAq9b6CzpZO2ukLsll/3ipGjdg8nMHoI8WNGkTJlZK+8kK1frGLfDx87y+sjhs1j4V/uQKXp2+hIu0nPUwfW83VXFAIK1Ji4w7eJvwydh0bZt2OdCkNnK9veeAy/b7Y6VazrQzW43nU7Yxf9aUCfHZIj0ocIdoG6Q5WU7C+ksqaKGkMTVpmt1zkaVIS7BxEdGU38yCQC40LP6g9usHbzVsEGPtB50oHjfiNlDTwYoeHqmIHN0AawdBvZ+OqDBC3fisbqeBhXXDCUaU+9jYd3YJ+OJQgCu1dsZtOBHU456anJ45hy1Ry6O7oo2VdAeXEpVS11tAq9m/PJRAhw8SEqMIzY5Hhi0pMoO7AZt3UPO1uU56lH4HXlEiLih53Qhn2rtrH585cJaa1gRLkVuejQ0d2Z5st/FvyJmtBU4uW1vJAYzuQB3hKTkDiXsVktbFryGL4fr8LVLCIAm0cHsXbWfUyuqsDQEx2J1oZw2c1XnrDtgigIZK3+L5F7nyEAR0Rkn+dsoq/7NzajnIOb91B18ADtDYW92mw4UKL1iiQoNoXEcaNJmjicrpYOvl38GvqmAwC4aIK44O4HSRzb9/LtmU2HeLighPweHadwWSPPxfowL7JvNU5Oh46Wena89ijBP+5F27MzXR3thv/995E+/6YBsUFyRPoRu9VO9YEySvIKqaqrpq67GVtPx9XDuKEm3DOEmJho4tOH9CpnOx5mm4WlhRt4t0lDCw69kiB03BcKNydMRykf+LBa5upP6Xz+FYKaHN/i6hh3Ip/5J8lj5/X5WC3VzXy37GuqTU0ABCt9GZmcRpOukarmWpptHcf0ofJTeBLpH0ZsYhxxo5Jx9XaUCbc111O87CHGtq9yXBsvykc9zqiL7jhht8qu9k6++MfTqIrWk15mcfZ7yE7x5O1L/kBJ9FhcMXJvQDv3pswdlL+HhMTvgaaaIvb+/V7idlUBjs7SX1w0Djff2ag6ShzREVHJzPQpjL3kxOKDnR2t5H/2MGOavkUuE9HjxqGhf2bMogeQKxQIgkBtYRX5W/dQnX8AfXMxor13ZBSZC27eMYQkpGIX5JRn/gyiowVD1Ij5LHjoD6jUfdtryy7Yea9wPa81aNH3LCZnqct4YdhEIjwGvsS2pb6c3a88Svia/ah61s+VSd6EPfRXhk27rF/HlhyRAcRmtlKRU0zpwWKqGqqpN7c41TgP4ylzJcI7hJjYGOJHpeAd6lgN2AU7/y3exJv1IvU9Del8aeNPA9iQ7tc0VRey9+/3ELe7BgC9mwzDHZcz7Y6n+nyfURAE9n63lQ2524+0HMePKrEZ8Vfzk7fcnUjfUGLiY4kfNQSPgN6VKaIgkPH9EhJyX8IHR8Rkj9+lJF//Kl6+J8683/rVCko+f45RJUbnD7Ug3o33FlxJVoLD6ZqjKWXxsMmED6A4nITE75nstctof/5lghsc+XZlkWp+vvgWYtrsGETH7zNY7c9VN1990sqY4uytyH56gHh7KQAFyiGoFr5ObOq4XucJgkBFbjGHdmRQV5BHZ0vJUV2Ce5BpkCsDEEUB0d6FUq3lonv/TPzoIX145w6au1t5Yv9mfjA4JBa0GLnbv437UuaiUgx84UNDZT77XnyUqM3FRxrrDfcn9i9P9MviEiRHZFCxGE2UZRZSVlBKZWMNTdY2xF87JkpX2pPc+cUvmmqZo27eEz23erdxX+rcAS0DO4zNamHjG4/g98lqXM2OLYnymQlMeuYtfAJ+e+KV3Wqnq6WDrhY9na0d6KqbOFiUT31P+NVHcMOKnS65Y/LwkGmJ8A4lJiaGhNHJJ+0dU3koE8PK+0mxOMKv5fJozPNfJXnM7BO+pzRnD1tffIS0vEa0PSlAZREavl44j9Upjk6hkbIG/hnnx9yIvtVEkZA4H7CYjWx67S8EfLEJrcXRM2Xv5AhqE6/C3lWLKBNRiS5ExMex8KpL8FAfX33YZrWw7+uXGFb4Jm4yEzZRzr6Qaxl+w2Jc3Y9fKi/Y7BTvy6dw5z7qivMwtJUf1bKjB5kWmdwHN58wEsePwjckAO8gf3xC/XH38eiTrfDt9bk8WlTj7PsVK69jcUII00IHp2dMZUEGmS8+i1++HpPaHaNKQ0uIN8HjJ3Dx3X/o07EkR+QcoltvoHRfIaWFxWQqKtkf6skB11QMMsdWgqtoYGLbXmIOtaGwyXERFWjlarQKDa4qDW4aV9xcXXFzc8PN0wN3bw88fD3x8PfGzdejT5Jk92/+huZnnyO01uEE1IVrCXrqSVKnLDzhewRBwGIw09ncTmdrB12tnXTpOzF0dWEwGDGYDBjNJow2E92CGZNoAZmjdNZP8KBJ3oEgE5GLMgIFL/RyIxFeoY7trJHJJy3RPYzJ2EX2sscZVfMpKpkdo6hmf8KfGHXVY7iojk0S6+rQsefz1zF89zNxld0c/uSqAhVsvWI6H6bcgqhQoqGbP/rp+HPKvEGJSklI/C9RV3aA7CfuIzarAYAOdzlZl12MwRqAAYceibvMi66kQCZNTmJm6MjjVqE11ZZT8/l9pBu2AtBAAA2Tn2XE7GtPaYPNYqVg136K9uyjsSQfY0clYDvJOxTIFa4oVO64aDxQu3qgdffC1csbdx9vPPx88Qz0dTgvIX4n3eKxCTaW5K/lzWYvZ/HBRdpSFg+fRqDrmTfn/DUWk5nWOh3tDS10NLfQqWulq60No74DU5ces0GP1dSJ3WpAsBs43EH+aFT486fPlqJ06bv5TnJEziHyW0v5rOIAP3e408iRL52P2Mr4zkKGFXQhdNsxiuZjtnROhUyUoZGpcJWr0bpocFVrcdO64ubqhruHO25e7nj4eOHu54lngNcxIm2tDZXsfPIu4rY62t0bNDKarp7F0AvvpVvfTVd7J12dXRi6DBiMBozmboxWE912E0bBjF127Bf6xLZCkOBNm7wLc0+yr7/oSXJ4PKnTRhIYH3ZGK5D9m7/Fb8vfCBMdlTw5rhMIuvp1QqJ6N4OyWkxkr/ovTSu/JiyrFs1RBVClwQoKZ4/mvQk30y535OZMVZfx4tCxAyqRLyFxPrD3+6WYXlpCQIvjR1ie6EPVpGtoNrY75xJXZSA7kyNJirVyY9QwUv3ij7lO7sYvCdz6BCE4Kuuy3SYTeu0bBIXHnbYtZqOZg9sy2ffjWrpaa0G0IIoWEE3wqyrJ00Em0yB3ccNF7Y5K64HazRNXT2/cvL1x9/XB098Xu5eCt9uK+UmRBHI5HnRyf5CBPyXP6eV4CYKAXtdBe72O9qYW9LpWOltaMba3093pcCzM3Xpsli7sVgOI5pNYdiKD1SiUbsiVGrDYcfXx4fa3Xjnz65wEyREZZJqMOpaV7eW7FoFC4cgDTUM30zR1XBUayryIMb2SHgVBwNzZjb653bGF0d5Jl77L4QgYDRhN3RgtRow2M92CGfNZ/FgOR1tUgKpmByP2FeHRo+WWmexByZBJoD4zVVCFKHc4Qj0RHFe1q8MZcnfD3dMDNw9Xmqub2FeSix4jAD5yd2ZOms7QGelnHP7U1VVS+cX9jOrcBEATvtRM+Acj51zvTEYVBIHCvWsoXf4B/tsOOevqARq8ZRSFumGcMY9f0saw3+4QJAqRNfNMtBsLoieekT0SEhKnj7m7i42L7yN0xS5UNocgYvn8iegCR1FtbEKUORZYStcIvho6BC+PVi71g+tjxhLsdiSXxNjVQe6yxxhd9wUuMjsGUcOBpHsYfeUjZ7yqN+oNrHrrEypz1/ZIzyvQeiUzdPp0VBoXOlvaMLS3Y+xox9Slx2LUYzV3YbN2IdqN/FqE7dQoEOVa7Eo3rCo3UCrxECzILKaTRi1OjhyZwhWlizsuGndUPREcrWdPBMffF68AX8fWU4jfMfL3giD0eVWm5IgMAt22blZU7Oabhnb2WiOcEuwyUWCUSxWLAt25MmZ8n3VttFmsdOk66NTp6WrT09nRiUHfSZfBiLHbiNFsxGjppttuPhJtsXYSUJXJ6LxGPHsckBp/BXtHp2H1TnAcEEEjU6GVq3F10eCq0jq2h9xccffwwM3THXcfDzx8vfAI9EbjfuJ8lpI9+axbt47GHmEiLWqmpI5j3KXTULicmQCY3WZj37evkJL/bzxk3dhFGRnBV5N6/Qu4ezqiGfXleeQuexP1+j3OJDmATg3kR6hpdvPBOO9CtsQmkS9EAo5Oxbd61/O3YXPRKgc+N0dC4nykqiCDvCceIibPoZpsUUDFjMk0hwynpqeflFJUYPKO4/OUBMwqGWNcqrk8yItF0ROceXTlB/dg/u4Bkq35AJQo4hAueo3E9OlnbJOupomf33wPXcVuHM6FDP/o8Vx07x34hx9frkCw2dHr2mmt19He6IhedLW19UQvOjAZ9Fi7Ox3RC5vh2DyVk9ETtVCq3VFpPFC7e6L18HJEWXx88ArwxSvID59gfzz9vM65Bq2SIzJACILAprosvqitZJMx2Ln/B46kpAU+AtfHjB6Usq2jqSrMJPeNZ4nYWoi6J5Ci85JTNT6NuBl34O3ni4evYwvH3d/rN6vGNhRVs/a71ZQZawHHhDImahjTrpyHxuPMH/YluTsQfnyARFsRAEXKROSX/Jv4tEl0tjexb/kSzD+vJaKow5n3YVVAfriSOm8PrAo/muZOYmvUCKpx/C0U2JirreLRpJEk+ZxdK3IJCYnfxu5v3qLzvY+cHWUFoGj6NGpC4mkRHfkjGlFNXVAS3yZFY5fLccXIDG09V4dFMissHZkI+1a+TlLeK3hhQBBlZARcxpAbXsHT+8wFB8tzi1j7n/foajnkOCBzIWr4HC685+bjKrmeCaYuI20NLbTW69A3t1DfUMvB+loqVD60uXvS7u6BwsvGRXFK7hg+Z1AKF/oKyRHpZw62lvBpRR6rOtxpOirvw482LvBo5/qogW9CdzwK9q6h5O1XiN5Tg6Lnr1wfqkFxw+VMvOEvfd6HoKOhlfVfryZPV4woE5GJMNQ/njlXXnhCAaOT0aVvI++zRxjT+BUKmUinqCU/5UHSLrmb3DWf0bzyG8Kza53OFUBZmJoyXw0muRd2Vw3lMyewLXwsrTjG19LNQo96HkwaT6THmXf6lJCQ6FsEQSB3/RfUL33XGSERkVEwfS6lQUEYZI7opqfMjaLIWL6LPpILEkALF3rquSEqlVC7lrLPH2RMx1oAdHhTOebvpM+/7YQaQicjZ+0utn3xMZaeBZVM4c7QaZcx69ZFKFV9W4Jb19XIG0W7+LrDHwOOqLkXHVzr087dSVMI0PZtH6+BQHJE+oEGQzPLyvfyQ4t43LyPq0PDmBsxetDFrgRBIGfNZzS+9x9nZ1yAykQvfP9wG6Mvub3P9wLNBhNbvlpLRkUuVpmjJ0u0awjzFlxISPKZl/6KgkD2umWE7XqKIBxh2n3u0xBSLqdp7Y/4b++d99Hk70JNciT13TJkNhGzj4ZD08exI3AiRpljBeNNB9f5dnBP0lR8Nd6//aYlJCT6nKJ96yl6+2WidlehFMCuVHFo6nyKA9yx9CS5B7n4Up0cwBe+UXRzpFVDgryWS31hbFsXMZueJkKsA2C/ZjR+Vy0hLPbM9UIEQWDr5z+T/ctyBFs74OhdM3bh9YxbOLPP59IOcyf/KdrCJzpXdD2LJw3dXOpezwOJv68keskR6SMO53183dBOxnHyPi4PdOfKmAm4q35buK4vsFkt7F7+OqZPviSsypEUKsigIj2E6D/dz9DJl/b5mHabnb3fb2Xbgd3ORoEBSm/mzpxNwsSzk1Curyykcfn9jDDuAiDHHESxKZmArEqCGo/sr3a6ymiamIiQOJ7yfYXYzM10hXqwf/IE9vqMxypzJKyFypq4LVDgD4nTpBwQCYnfCXWl+8la8g9CNxxEawGzmzf5k+dS4i135LuJkOgVhX1cEF+LFvZZIxBwbCkrsDFKWcUk3QH+mPcuPnYjJtGFnJg/kn7tk6jUZx4JNhvNrF36BcV7fnIKpWk8Y5h5yx8YMmlEX966YzybhU9Lt/BevY1K0dFnS4GN2ZpKHkhIZaR/0imuMPhIjshvQBAENtRlsfwcz/s4TLdRz473n0O1/BdnWZxFCdVTE0i9+29ED53Q52MKgkD+lhw2btvk7PviIdMyffRkRl4w4ay0TawWM5nLn2N4ybvY7Vb2NHphrvIkutLqzPuwKKAmLRifhZfhHTaJLZ98irG9hLYEPzLHTSbHbRSizHF2kryGO8PduSpmitQZV0Lid0pbczW733oG3x934mkQMfiHcWD8dCrdHdERhSgnPSyFlItG801rHt+3ypziYQBajEzs3stNNd8zuy6bGnk4hjkvkzJh/lnZ097Uxi9LPqKucAvgiP56h4zkgj/dTlhS1G++318jCALfV+7k7epWDtgjncfHuZRzX3QEswahC/vpIjkiZ8HvJe/jMO26Wna9/TQ+P+x0blMYNDIa56cz9p6nCQg7tv6+L6jKLWXtqtXO7rhqlIxPGMXky2fhojk7MZyCjPUofn6QlpY2dJWuhJcpUB+lNVQV54Fy/ixGXXMPJj38suQ9WmozaBwZwd60qRRqUpznjnWp4J6oMGaHjRrwJoESEhL9g7GrnZ0fPId6+Wr8W220RQ0lN30UjWpHJFaNCxOTRjNp0UzyO8v5rPIgq/Rezu0NgAChifmdG7mh8hdMYgoJ17+GT0DIiYY8KbVFVax+5z3a67J7jigISZrKhffchnegz2+93eOytS6HN8rL2WGOci64hiiquTPMkytiJp9zCy7JETlNTifvY17EmHPqD1xfnkfWG88QsiHP2VWx1UtB16IZTLrzKdy9frtS3/HQVTay7ttfKNRXACAXZYwMGcLMqy7Azffs/jZtuka2vXEr8oIi/Etc8DIeea0pwAXjrDGkXncXEYmj0Ld0sGrJR1QXbKF6QhS7hkynWhkNOEKWMzWVPBCXwqjAvu8bISEhcW5gs1rY9eW/Mf/3S0JrumkYOpHcIXF0KB2ToafMlRljp5A2bxwiIutrM1leW8Om7uBe+STx9mLmt2xmlCaOeZc8cFbJrAAFO/ez8aP36dY7RCFlMg3x4y5i3v9dh9r1WHXnviCvpYR/FeeypjsSG46k2TBZI38IglsTpp4zW9CSI3IKVu5bwXt1LeS6j8Quc+R9yEU7o1TVLAo4d/I+jqYkexMFb75I1O5KZ9OihmA1susXMvGmv6JSu578AmeJsa2LDct/Iaf+kFP9MNEzirmL5p+WDPvRdBv1lGVtojZzB+0ZOwgobyW45cjrh/M+oq++hZRJC5DL5VjMFtYuXU5+1k+UTIpjR8wMWuQOYSM1Ji51r+P+xDHEef32fjgSEhK/DwRBIHv1pzS99x8iC/VUjp7DgWg/uuU9Ca1KH+bOmUPcOEe0tMtiZEXFbr5t6mCfJaLXvD/MlkeSys64sGjS/aJJ9I46o8WnIAjs/WEze1Z8iq0nUixXejPygquYev3F/RaZreqs542i3azQB2HscbJ8aec6Xz13nQNJ+ZIjcgpeX/kCi70vACDGXMqs/G3M+3EXmI3oo/yQJ8TiPWwkUenTCI5JHdQQf86GL6l79y1iDuicx6riPPC67WbGXvanfrPNZray/dsN7CrKdKq4hqn8mTt/HlEjE075fl1dKWX7NtJ6IBNbUSnuFU34N1mcZcSHsSigfIg3gVddy+hLb3c6VIIgsH35anZt+4aDE2PYGTqNLpnjO+CJnmt92rg7cTKBrmeuEyAhIfG/Q8Ge1ZS89QphB9opHzeP/CA1tp5FU6xrKHMvu5DghCMR73pDE5+W7OZ7nZ1S+bEaQlq6iVHoSFJbGerhykifENL8EnBXnXyxZ7PZ2PDhCg5uXoFod2igqFxDmXLtrYyY2/e5eodpM3XwdtFWlrV40Ip3zz0YWeTRyP1J44n0OLvtp9+K5IicgtqqfJ7PW8+I/AOE7z6EV1UbPvrjS+p2aWW0hHtiiw/HPSWV4LQJxKZN6bcIBIDdbmPPN2/R9dGnRFQcEfqpHBFExJ33Mmz65f02tiAI5KzezeaM7ejFI5LssybPIGX6yGMcH5vVQlXBXmqyt9GZdwB5SSXe1e14dx7/8+zUQmuAgMlHhjkmmZn3vUZAaGyvc/ZvzGDVmk/IHB3NHr/JWGSOEGcwzdwSaOP2hGmnnBQkJCTOL6qLMsl9858EZLZSMnYmJV6iUzJ+qG8sc6+5GM+g3vkbWw5tZk3hZuqVrhRrYqiURzkr7o5Gjp0wmY4ElYEUNyVp3gGM8osl1D3omHOPlYwHd79k5txxB7Ej+6/axWQz81HxZj5ohBrRYZcSK/O0VTwQP5xh/qdeQPYlkiNyFujqSinP3ERrXhbWwmLcKpoJaDQfs4IHh2pnc7CG7uhgVEkJ+A0fQ9zomXj7hx178hlg6Tay/ePnkX/xI0FNFudYVZNiGXLPo8QNn/Kbrn8qSnYfZO369TSdQJK9q6OF8uzNNObuxlRQgLqsnoA6Qy9BscMIgM5PSau/ApVnF35eJqI9THRrAtGl3cWIC+84pkNu5YFSPv/pQ7anRJDtMQZB5giPxslquTNMy7VxUwddp0VCQuLcpqW+nD1vPYNbRgvFaeOpcXVMUC6igpFhycy6/hLUbr1LeHV1lZT88CLJDSsp8w0h2zeRLI8UitwTqZCH0YnHccfyoZ14l3aStSLDPLwY6RvBEN8YlHIlupomVr35Ps0Vu3BKxkeN48J7bicgsv+qLu2CnW/Ld/BubQf5dseWtUwUmKiu5L6YaKaFjuy3sY9GckT6iG6jnvKcrTTk7MJ4KB+Xslr8azpxPUGzwxYfBfpIP4iPxis1jchR0wiLPzaK8Gv0rQ3sfOcZvL7b6owkGNXQMHcEo+95kqCo/k3ArC+sZu33v1BudAgAKUUFaUHx+Pq2oS/KRigqw72yGf/mI6W0R2NWQnOoK+bYUNRJSbiEhCGv2cH4zo2oegTOihXxdI29j7TZNyBX9N5/1dU08s6PH7AxKoJD2mHO4yPlZdwbHcoFEWOlChgJCYkzwtDZyo6lzyLs1VEcl0KLyjFxa0UXRscMYfoNlx7TzqKjtZn8719hSOVneOPYXmnAl31DbsYwYjIF3QbyjXaKLe7UC/7O6pWjUWMiWq4jSWMhxV1LRBfUf7ERc/0RyfjIYbOZf/dNuHsf38HpKzbW7OONimp2W49sQaUqqvhTuA+XRU/q13lVckT6EUEQqCnKpDprGx0Hc6G4HK+qVnzb7cc936iWoQt3xxoXjuuQFEJGTCB2xDTUWneaqgvJeONpgtfm4mp2/BnaPeR0LJzKxD89hadv/2qVdDS0su6rVRxsKe2RZJcRbVQQu3ct/o3Nx3+Pu5y2SC+EuCg8UoYRmj6J6JQJKF1UlB7YTfvaFxih34xC5rifg6phCJMeInXKwmMy0/Udel75+UPW+EdS6eLYnpGLdibLi/nzkFTGBZ2dKJqEhITEYawWEzs+eZn23U2UhATTpXBESLztatKT4pl83eXHPJANne0c+OENYos/IhCHQnUbHhREXU/KpX/ByzeADnMn2bpictobOdhlpMikplwIwMKx1TIyUSCEJoINtQS1VuHX0IRvdRcjUy9kzm1X9Llk/K/J1hXyeslB1nVHOoU5I2UN3B4s5+b46aiVZye9cDIkR2QQaGuupixzMy37M7AUFKGtbCSw3uSscDmMQQVVASAoZSTWiLj0+C8NPlAdpsZH0KI8btyh77C7htIelEqFu8yZ1BVhcGFYxk48GhxlaIIMmgNUdEUHoEyMw3fYKKJHTScwPPGY6xXsWYt588ukde91HsvRjkcz4y8kj53Te2zBztpDO/iuNJ9drtE0KRzOlko0M1Mo4rFRU0j0ie6nO5eQkDhfEQSBPSvfp3JrJWXeGiw90dpAq4YwNxnpl88lIqn3toXZZCT35/8Qmvcu4WIDAAZRw4GQy4lf8Aj+ob1FzGyCjUOt5WS1VnGgU0+BUUapzZu2niTSX+MhdhBqqUOtkOOiViGXy/r+xo/CLtgx2m1YRDkijrHkCEQrO/lk8i19KlUhOSLnCJZuI6W5W8jf+A2GvP341RmIahR75Z1UBjiUUOPq6Vf3w6bSUpc6kbKoMKcIEIC/RU3KwTxsliIsMSFoh6QQNGI8sSOn4+rufcLriYLAga0rUe78FymWAwDYRRnZnjPxnfcIsanjnOc2GVv4uSqLVTVN5MjD6ZR5OV9zF/XMNRXxxOSLCfU8N9RqJSQk/rfJXrOCAxvyqdDaHZLxgFZQEq634qHSET5rAqnTFzmLEmxWCzlr/4tv5hJihQoAzKILOf4XEXHx3wiNObnYZU1XI1m6UvZ36Mg32Ci2uFIjBCDKzg2NqniK2D7jqj69puSIDDJdHTpyf/mUtk0b8M2uwEffe9um0V9JY7wPsuhIAkJiT3CV344ogLnbjeYuFdX2LmdDOpkIwTIPwr1UpMxOJzJlHArF6SWB2m02ctd9iue+N4m3lwJgERXk+F1I6IWPEh6fiiAIZDTn80t9KZvboFAM7/WD04hGhhgLSLeYeGDGlQT4BPT9zUtISEicgrzNG8nZsI8amQWT/Iicc6BZTWRtPQhFuE4eQ+pFNxAYkYQoCOzf/BXqXa+TbM0HwCbKyfGahf/8R4kecvqS610WI7sqctmcnYG+rQHRfmSBKFOocfcNJjg2Co17/wmU2QQbhR31RLt68FCa5Igcl9+LIyIIAuV5OyhZtRxxVyahJe3OLRdwRDzqknxRThpH4vxriBoytl/t6dR1kLV2N7klec5eMODoBzMscgij50zAN/zMHv4Ws4mcVUsJ2f+Os6ulUVSzP3gRsQseQennwy812WzQtbGr2/eYUGSYrYrElgJS2+0sGnkhQ8al/eb7lJCQkOgLbBYr+37azP79B6gX9Yg9OyQuooLoDoHogjy6baVYxg4lbPYlpExaQHHWJmxbXmG4aZ/zOtmuE3Gb/QiJ6dPPaHxBEDiwMYOsVb/QWpsDHHaK5Lj7JzN85lzGXDKt33NJ+hLJERkAjF3t7F/7ObqNa/HKKsW/1dbrdZ2vko70OPxnzmX43OtOus3RFwh2gcId+8nKyKRUX+MMNypEOXFeEaSPHU3ihKFn3JCu29BJ7g9vEl34AcE4RNU6cCMv4hrE6VeyuauZLR2Qbw91JkEBqEQTycZ84moLia2wMmboDCYsmttvsscSEhISfUF7nY69a3ZyoDKfTkzO4942FXF1bUTu34HF3k7jsFDcp03FI3YIssxPGNG5DXnPvJunHgFT/szQiRefsXx8V6ue7V+tonjPJizGWudxmcKdsKQJTLzyEiJS+i+S3ldIjkg/UXloL4WrvsC+Yy+hRa2ojvI9rAqoi/dGNnE08fOvIia1f0ujDtNS1ci+9bs4UFVIF93O4/4KL9ISU0mfM+6sesF0tOk49P1rJFZ8ii96AMqVQXw/7EbyApPZbfLr1VAKIMheR1LrQaJLigksNhAVN4GJVy0gLDHyeENISEhInLMIgkDp7nz27d5HSUeVs8WFXJQRYVASU1JMQGEGiAJ1UW50DovBRatnjiwDjdwREi9SJmIYez9ps649RrbgdCjJPMSelT/RWLoXUTgyv2s8okmeNItJV85D435uijtKjkgfYe7uYv/6L2ncsBqPzCICm3srd7V5KmhNj8F3xmyGX3B9vzWc+zVWk4UDG/eRvT+H6u4mepKfUaEk2T+W0VPGEZkWd1bXbmmsoej7l0it/QoPWTcHvSL4Nmwm2/0mki+PczZZAnARLSSYCoivKyDsYDnudUY8g4aSNmcu6fMno1RK4mMSEhK/f4xtXWSt201u4QGa7R3O426CC7FNRqLy9uCmc0QvOtxk1ERr8AtsZaRfB95KgQp5JLoRdzNi/m0oXc68VNZiMrN7xQYObl2Hsa34yAsyNQFRoxiz4EKSJgw/p/SWJEfkN1BXup/8n5dh2b6LkEPNaI7yPewyqI31QJwwktgLriQ+feaA/uFrD1aQsWU3h5pKnf1fAMJUAYxITSNt9mhUrpqTXOHE1FcWUvXjiyS2/MLW8DTWBkxgh9tYGuS9+xT4izqS2w4SXVpAQF4dSrMdpTqQ2PRpTLnmYryDpd4vEhIS/7tUHygjc+seDjWXYuZIWDzIqiGmrJLwAztR2BzK2HYZ1IaKiOEWYgIMuLl7UZtyB2mX3IVGe3aNVetLatjx9Y9U521HsB1xilw0QcSOmsbkqy/GO8j3JFcYGCRH5AywmI3kbV5B/fqfcM0oILiht2xqh7scXVokXtNnMGz+9b9Zxv1M6e4wOBJPCw/QZGt3HndDzdCwJEbPGk9gbOhZX7+yMIfczf+m2EvJVp+xZLukOXu7ACiwkSxUEF9fQkhuHu5VbciQgUyFf2Q6oy+5iCGT0s4pT1xCQkKiv7F2W9i/MYPs/bnUmJucx1WikjCrkuBDGUQeyu/1njYPaI2woQkRcRmxkFFXP467p8+vL31aCDY7WWt3krNmDR0NB4DDFRIKvIJSGTF3HukXTEKuHJwSYckROQUHinez/ut3CMspJrawDbejfA8BqIt2wzZ2OFEXLCJp3AWnXdraVwiCQNneQ2Tu2kdRe6Vzb1Imyoh1D2XkqFEMmZp2jDzxqa7ZYemkuquR6s5m8isPUdTZQrZrCjXyiF7n+tDOaFk90eXVuG/PRtl1pPJG7R5F8qSZTLxyPq4e5+bepISEhMRAoqtoIGPDbg5WF9B1VIKrv9yDYAS0B9cRfrC6V16hTQ41YSIdsUF4DR9P2NAx+IbFERCegFrrfkbjtze2sn35T5RlbsFqanQelyu9iEidzKQrLyEkPvwkV+h7JEfkFHz82l2MW7rpyDhaGVkJAexLTaUobQJqH0/8lTYCXCBIpSRIrSVE606Ymy/hbgH4qb37JQLQ0dBKxtqdHCg/RIdocB73kbszPDaFUXMmHNM9UhAEdKZWarqaqe1up767kwaziUazjWYb6GwutAoa2kQPzBx/20Ym2kmSVTHFQySysBXThgwshqOztd0ITRzPhMsvIWpYfJ/ft4SEhMT/AnabncJtuWRlZlHWWdu7etEznABXC915v+CdWUJA+/E7lIOj63uXlwqzlxabrycyfx9cAgLRBIfgERyJb3g8/hEJuHn03oIRBIHCXfvJ+GEVzZWZIB5ZZbv6JDB06hzGL5qFStP/1YuSI3IK1uauwvrg3zgwJIx9w8eRFTcTo+L0mw+5YMGHTnzlRofDohQJUisIUmsI0boTqvUm3M2fIFf/U0rm2q12Dm7OIjs7mwpDPWLPF1cpKoj1DidoeBTtUUoaLUYazGaaLHaabTJ0NhdaBFfa8eiVQHoqtKIRH7ENX3sbAfYOJvr4MMIYSsnPWxz16+Lh3BMZ7n7JpM6Yw7hLZ/yu6tclJCQkBht9UxtZ6/aQW3qQtqP0nDxlrgyLSiYoQk3Bz2+jLizF1WDD1SDD08AxbUFOhlENXZ4umLy0WH09wM8bl8BA1IEhqH2DqSttofZQCZbOOmQ9Dfpkci1BcWMZd9nFxI/qv4aqkiNyFnSYO6kxNFJjaKW+W0+DyUSjxUKzBXR2BS12Da2iGwZOP2SmwIbXYYdFYSHARSBQpSBYriK4WcSY30h9awMmLM73eMo8afQP4fvYGNo1p5946k4XPrIuvIVOvC2tBJvriDA3EGzSEdLdQpixGXu3lq6ASXilXYKrNprctVupyNmKzaI7YrOLL1FpU5h01SUERkmS6xISEhK/BUEQqMgqJmtnBoUt5b0UriNdQxg5YgQhSSHUFmzEemgV/s27sVnMdFiUGExKTCYFRpMrcosabbeIW6cVD70Nte0UAx+FWQl6Nzl6rYwujYxulQKTUoFd44V3dArpl1xKyoQ5p77QGSA5Iv1Il8VInaGJGmNLj8NipNFsockqorPKaRHUtAhu6HHYq7TbSdXpSWptI1DfjsrcgUnodOZ9AKhFF2xuYWyOjuZggLfzuEwU8JQddmTM+CsFAl1kBKpVhGrdCNV64dZtxZy7HdfSDSR1ZeAqOxKKM4su5GtG0uQ5E5ssHH1DM231FXR31vYK2YESn7A00ufPZ/issVLiqYSEhEQ/YOrqJnfdXnLy91Nvben1modMS5CbH0H+QahVFmTtuwltWUecvbzXefUEUOk3CWKn4hUQgVFXT2d9FeameqxNTdDSjktrJ5qObtz1Vlx7118cl5IQBRdt2N+nc7/kiAwSNouV+sJqaourqK2tpaG9mVabvpfTcRilqMBV6UVHqA8NyRr8XV0IVqkJ7nEwItwDCHYNQKXovSUiCgKlB3bRnPk9fnWbSLQVOV8TBMgzpZBvH0WXzROzQY+pq/5XTsdhFKjdQokbPZVJV1+Ip5/Xcc6RkJCQkOgPGoqqydi0h+KGMvSi8bjneMi0+Ku9cJdZ8TEXMcK2Dl95vfN1o6im0G001ri5xE647JhuwACGzlZ01cW01Zahr6/C1FCLtbkJW4MOWVMrrl1mmoK9uO7bnX16f5IjMgAcdjpqiiqpq6unsaOZFmvHcZ0OF1FBgNqHYJ9AQsNDCU+KIjAu7LTl1rsNnRTu+glz/ipiWrcTSCuCIKPaFEG5IZIyczBdFhlWS9sJnQ6VaxCegVEEx8YTNXwIsSOTBiRhSUJCQkLi5Bha9VQfLKe2vIb6pgaaDC0ndE7c0eCDnBB7MzGUEC7fj4fMsb1erExAFzqDgFGXEjds4mnJywuCgKXbjMatb5vrSY5IH2OzWKkvqKam+HScDiWBam+CfAIJjQhzOB2xoWfc46WhuoTKXSvRlK8loSuHZnMIZYYI6k3etJnlmGwGEC3HeedRTkdcAtHDhxAzMgmV+szV/CQkJCQkBoczck5EFUGijWCxjTAqiZDvp1tmp8J3EqohF5I44SJc3Qc26i05Ir+B3k5HXY/TcfztlcNOR7DvYacjmoCYkDN2OgAEu52i7M20ZP6AvPwQ3Z0q6k1etJ/S6QjGKzCKoLh4yemQkJCQ+B/G2NZF1cFy6sqrqW+qp7HrZM6JC0GinWCxjWCqMWlsCAkTiRp/GcGRCf1uq+SInCY2s5W6gipqS6pO6XSoUBKg8iHYN+A3Ox2H6WhpJuP7r9Hl5WHp6KLTLGKydgHW45ytROUahFdQFEGx8cSMSCE6LVFyOiQkJCTOY4xtXVTnl1NbXk19YwNNXS29dKiOxl10IVC044UJtacrwemjGDZ1Dop+6At2zjgiCxYsICcnh6amJnx8fJg9ezYvvvgioaGnJ0neX47Ipo9+JrcsD73c5BScORoXUYGXXY3GIiIzmbB2t2EydxzuLXdGiKIIooiI439BxDGkiN1u5PhOhwIX12B8gqIdkY60FKLTEiSnQ0JCQkLilBjbu3q2dRzOSWOnDj3Hj5y4iS6EyF244am/9qkNZ/L87lft8hkzZvDYY48REhJCbW0tf/nLX7jiiivYubNvs3PPFLvNSrvC0VJZJSrwtKlQm21g6sTc1YCpW4cZOI2qpz5AiVLlg6tPMJGpI4gbOYzotARJQExCQkJC4qxw9XYnadIwkiYNcx477JxUFpZQW1dFm9WIXmbGILNiFga3U/qAbs388MMPLFy4ELPZjIvLqR+0/RURaSqrI/OXnXj4eKD21CKTO2IdFlM3xs42TF3t2IwdCKZOMHeisHaitBnQ2A24iUaUMvspRjhCNxqMMi0WhTs2pRuC2hOZ2h2F1ouguARGXzBHcjokJCQkJAYcfXMb2WvWoNJomXDFpX177XMlInI0ra2tLFu2jIkTJ57QCTGbzZjNR+IQer2+X2wxmuvwUWxE2dCItqIJT6sOX6EVN5np2JOVHPdT6sCNNrkfnS7+mDSB2NyCkHuG4OIdgqtfOF6BEfgGRaDWSI3hJCQkJCTOPTwDfJh2wzWDbUb/OyKPPPIIS5YswWg0Mn78eH766acTnrt48WKeeeaZ/jYJfUMF4xuW9T7YkwDSKWppVfQ4GOoArG5ByDyOOBieAZH4BUfg5eqOJAEmISEhISHx2zjjrZmnn376lM5CRkYGo0ePBkCn09Ha2kplZSXPPPMMXl5e/PTTT8hkx6Z+Hi8iEhER0edbM/WVhVSu+hd4hqD0CkHrG45nTwTDzcO7z8aRkJCQkJA4H+nXqhmdTodOpzvpOdHR0WiO07CtpqaGiIgIdu7cyYQJE0451rkiaCYhISEhISFx+vRrjoi/vz/+/v5nZdhhn+foqIeEhISEhITE+Uu/5Yjs3buXvXv3MnnyZHx8fCgrK+PJJ58kLi7utKIhEhISEhISEv/79Fu/d61Wy4oVK5g1axZJSUncdtttpKamsmXLFtRqqdmahISEhISERD9GRIYNG8bGjRv76/ISEhISEhIS/wP0W0REQkJCQkJCQuJUSI6IhISEhISExKAhOSISEhISEhISg4bkiEhISEhISEgMGpIjIiEhISEhITFoSI6IhISEhISExKAhOSISEhISEhISg4bkiEhISEhISEgMGpIjIiEhISEhITFo9Juyal9wuEmeXq8fZEskJCQkJCQkTpfDz+3Dz/GTcU47Ip2dnQBEREQMsiUSEhISEhISZ0pnZydeXl4nPUcmno67MkgIgkBdXR0eHh7IZLI+vbZeryciIoLq6mo8PT379Nq/B873+wfpM5Du//y+f5A+g/P9/qH/PgNRFOns7CQ0NBS5/ORZIOd0REQulxMeHt6vY3h6ep63X0CQ7h+kz0C6//P7/kH6DM73+4f++QxOFQk5jJSsKiEhISEhITFoSI6IhISEhISExKBx3joiarWap556CrVaPdimDArn+/2D9BlI939+3z9In8H5fv9wbnwG53SyqoSEhISEhMT/NudtRERCQkJCQkJi8JEcEQkJCQkJCYlBQ3JEJCQkJCQkJAYNyRGRkJCQkJCQGDTOS0fk7bffJiYmBo1Gw6hRo9i2bdtgmzRgLF68mDFjxuDh4UFgYCALFy6ksLBwsM0aNBYvXoxMJuOBBx4YbFMGlNraWm644Qb8/PxwdXVlxIgRZGZmDrZZA4LNZuOJJ54gJiYGrVZLbGws//jHPxAEYbBN6ze2bt3KJZdcQmhoKDKZjO+++67X66Io8vTTTxMaGopWq2X69OkcPHhwcIztB052/1arlUceeYRhw4bh5uZGaGgoN910E3V1dYNncB9zqr//0fzf//0fMpmMf//73wNm33nniCxfvpwHHniAxx9/nOzsbKZMmcL8+fOpqqoabNMGhC1btnD33Xeze/du1q1bh81mY+7cuRgMhsE2bcDJyMhg6dKlDB8+fLBNGVDa2tqYNGkSLi4u/PLLL+Tn5/Pqq6/i7e092KYNCC+++CLvvvsuS5Ys4dChQ7z00ku8/PLLvPnmm4NtWr9hMBhIS0tjyZIlx339pZde4rXXXmPJkiVkZGQQHBzMnDlznP2+fu+c7P6NRiNZWVn8/e9/JysrixUrVlBUVMSCBQsGwdL+4VR//8N899137Nmzh9DQ0AGyrAfxPGPs2LHinXfe2etYcnKy+Oijjw6SRYNLU1OTCIhbtmwZbFMGlM7OTjEhIUFct26dOG3aNPH+++8fbJMGjEceeUScPHnyYJsxaFx00UXibbfd1uvYokWLxBtuuGGQLBpYAHHlypXOfwuCIAYHB4svvPCC85jJZBK9vLzEd999dxAs7F9+ff/HY+/evSIgVlZWDoxRA8iJ7r+mpkYMCwsT8/LyxKioKPFf//rXgNl0XkVELBYLmZmZzJ07t9fxuXPnsnPnzkGyanDp6OgAwNfXd5AtGVjuvvtuLrroImbPnj3Ypgw4P/zwA6NHj+bKK68kMDCQkSNH8t577w22WQPG5MmT2bBhA0VFRQDk5uayfft2LrzwwkG2bHAoLy+noaGh17yoVquZNm3aeT0vymSy8yZKKAgCN954Iw8//DBDhw4d8PHP6aZ3fY1Op8NutxMUFNTreFBQEA0NDYNk1eAhiiIPPfQQkydPJjU1dbDNGTC+/PJLsrKyyMjIGGxTBoWysjLeeecdHnroIR577DH27t3Lfffdh1qt5qabbhps8/qdRx55hI6ODpKTk1EoFNjtdp577jmuvfbawTZtUDg89x1vXqysrBwMkwYVk8nEo48+ynXXXXfeNMJ78cUXUSqV3HfffYMy/nnliBxGJpP1+rcoisccOx+455572L9/P9u3bx9sUwaM6upq7r//ftauXYtGoxlscwYFQRAYPXo0zz//PAAjR47k4MGDvPPOO+eFI7J8+XI+++wzPv/8c4YOHUpOTg4PPPAAoaGh3HzzzYNt3qAhzYuOxNVrrrkGQRB4++23B9ucASEzM5PXX3+drKysQft7n1dbM/7+/igUimOiH01NTcesBv7Xuffee/nhhx/YtGkT4eHhg23OgJGZmUlTUxOjRo1CqVSiVCrZsmULb7zxBkqlErvdPtgm9jshISGkpKT0OjZkyJDzJmH74Ycf5tFHH+Waa65h2LBh3HjjjTz44IMsXrx4sE0bFIKDgwHO+3nRarVy1VVXUV5ezrp1686baMi2bdtoamoiMjLSOSdWVlby5z//mejo6AGx4bxyRFQqFaNGjWLdunW9jq9bt46JEycOklUDiyiK3HPPPaxYsYKNGzcSExMz2CYNKLNmzeLAgQPk5OQ4/xs9ejTXX389OTk5KBSKwTax35k0adIxJdtFRUVERUUNkkUDi9FoRC7vPfUpFIr/6fLdkxETE0NwcHCvedFisbBly5bzZl487IQUFxezfv16/Pz8BtukAePGG29k//79vebE0NBQHn74YdasWTMgNpx3WzMPPfQQN954I6NHj2bChAksXbqUqqoq7rzzzsE2bUC4++67+fzzz/n+++/x8PBwroK8vLzQarWDbF3/4+HhcUw+jJubG35+fudNnsyDDz7IxIkTef7557nqqqvYu3cvS5cuZenSpYNt2oBwySWX8NxzzxEZGcnQoUPJzs7mtdde47bbbhts0/qNrq4uSkpKnP8uLy8nJycHX19fIiMjeeCBB3j++edJSEggISGB559/HldXV6677rpBtLrvONn9h4aGcsUVV5CVlcVPP/2E3W53zou+vr6oVKrBMrvPONXf/9eOl4uLC8HBwSQlJQ2MgQNWn3MO8dZbb4lRUVGiSqUS09PTz6vSVeC4/3300UeDbdqgcb6V74qiKP74449iamqqqFarxeTkZHHp0qWDbdKAodfrxfvvv1+MjIwUNRqNGBsbKz7++OOi2WwebNP6jU2bNh33d3/zzTeLougo4X3qqafE4OBgUa1Wi1OnThUPHDgwuEb3ISe7//Ly8hPOi5s2bRps0/uEU/39f81Al+/KRFEUB8blkZCQkJCQkJDozXmVIyIhISEhISFxbiE5IhISEhISEhKDhuSISEhISEhISAwakiMiISEhISEhMWhIjoiEhISEhITEoCE5IhISEhISEhKDhuSISEhISEhISAwakiMiISEhISEhMWhIjoiEhISEhITEoCE5IhISEhISEhKDhuSISEhISEhISAwakiMiISEhISEhMWj8P+z2Cd9psrnDAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "nk = 15  # number of k-points in each direction\n",
-    "ks = np.linspace(0, 2 * np.pi, nk, endpoint=False)\n",
-    "hamiltonians_0 = utils.syst2hamiltonian(syst=wrapped_fsyst, kxs=ks, kys=ks)\n",
-    "\n",
-    "vals0, vecs0 = np.linalg.eigh(hamiltonians_0)\n",
-    "for i in range(len(vals0[:, 0, 0])):\n",
-    "    for j in range(4):\n",
-    "        plt.plot(vals0[i, :, j])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "def func_onsite(site, U):\n",
-    "    return U * np.ones((2, 2))\n",
-    "\n",
-    "def func_hop(site1, site2, V):\n",
-    "    rij = np.linalg.norm(site1.pos - site2.pos)\n",
-    "    return V * np.ones((2, 2))\n",
-    "\n",
-    "Uk = utils.potential2hamiltonian(\n",
-    "    syst=wrapped_syst,\n",
-    "    lattice=graphene,\n",
-    "    func_onsite=func_onsite,\n",
-    "    func_hop=func_hop,\n",
-    "    params=dict(U=1, V=0),\n",
-    "    ks=ks,\n",
-    ")\n",
-    "\n",
-    "Vk = utils.potential2hamiltonian(\n",
-    "    syst=wrapped_syst,\n",
-    "    lattice=graphene,\n",
-    "    func_onsite=func_onsite,\n",
-    "    func_hop=func_hop,\n",
-    "    params=dict(U=0, V=1),\n",
-    "    ks=ks,\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "Us = np.linspace(0, 5, 10)\n",
-    "Vs = np.linspace(0, 5, 10)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "def dm(mf0,mf):\n",
-    "    return np.mean(np.abs(mf - mf0))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "def scf_loop(U, V):\n",
-    "    H_int = U * Uk + V * Vk\n",
-    "    mixing = 0.6\n",
-    "    threshold = 1e-5\n",
-    "    for n in range(5000):\n",
-    "        if n == 0:\n",
-    "            # mf = 0.1 * (np.random.rand(4,4) - 0.5)  # starting guess\n",
-    "            mf = 0.1 * np.random.rand(4, 4)# * np.exp(1j * 2 * np.pi * np.random.rand(4, 4))\n",
-    "            mf = 0.5 * (mf + mf.T)#.conj())\n",
-    "            hamiltonians = hamiltonians_0 + mf\n",
-    "            vals, vecs = np.linalg.eigh(hamiltonians)\n",
-    "            vecs = np.linalg.qr(vecs)[0]\n",
-    "            E_F = utils.get_fermi_energy(vals, 2)\n",
-    "        mf_new = hf.compute_mf(vals, vecs, 2, hamiltonians_0.shape[0], H_int)\n",
-    "        hamiltonians = hamiltonians_0 + mixing * mf_new + (1 - mixing) * mf\n",
-    "\n",
-    "        vals, vecs = np.linalg.eigh(hamiltonians)\n",
-    "        vecs = np.linalg.qr(vecs)[0]\n",
-    "        E_F = utils.get_fermi_energy(vals, 2)\n",
-    "        delta_m = dm(mf_new, mf)\n",
-    "        if delta_m < threshold:\n",
-    "            # # Plot\n",
-    "            # for i in range(len(vals[:, 0, 0])):\n",
-    "            #     for j in range(4):\n",
-    "            #         plt.plot(vals[i, :, j] - E_F)\n",
-    "            # plt.show()\n",
-    "            # Compute gap\n",
-    "            emax = np.max(vals[vals<E_F])\n",
-    "            emin = np.min(vals[vals>=E_F])\n",
-    "            return np.abs(emin - emax)\n",
-    "        mf = mf_new"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "100%|██████████| 10/10 [00:27<00:00,  2.78s/it]\n"
-     ]
-    }
-   ],
-   "source": [
-    "from tqdm import tqdm\n",
-    "gap = []\n",
-    "for U in tqdm(Us):\n",
-    "    gap_U = []\n",
-    "    for V in Vs:\n",
-    "        gap_U.append(scf_loop(U, V))\n",
-    "    gap.append(gap_U)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "gap = np.asarray(gap, dtype=float)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x7fd82887aaa0>"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.imshow(np.log10(gap).T, origin=\"lower\", extent=(0, 5, 0, 5))#, vmin=-1, vmax=0)\n",
-    "plt.colorbar()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x7fd82ae690f0>"
-      ]
-     },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.imshow((gap).T, origin=\"lower\", extent=(0, 5, 0, 5))#, vmin=-3, vmax=0)\n",
-    "plt.colorbar()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.8"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "6b7342be4d7622df79515c26158aa777f5c3738125f220c5a98bec2a0cbdfb50"
-   }
-  },
-  "widgets": {
-   "application/vnd.jupyter.widget-state+json": {
-    "state": {},
-    "version_major": 2,
-    "version_minor": 0
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/analysis/mean_field_demo.ipynb b/analysis/mean_field_demo.ipynb
deleted file mode 100644
index 4c81edb7c64d6c2e3c6b9c9fb8be8201bba27005..0000000000000000000000000000000000000000
--- a/analysis/mean_field_demo.ipynb
+++ /dev/null
@@ -1,596 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# mean-field solver \n",
-    "\n",
-    "## Some background\n",
-    "\n",
-    "### What is a mean field solver and why do we need it?\n",
-    "\n",
-    "Solving many-body systems such as a hellium atom in chemistry ([reference I used here](https://adambaskerville.github.io/posts/HartreeFockGuide/)):\n",
-    "\n",
-    "<p style=\"text-align:center;\"><img src=\"https://adambaskerville.github.io/assets/img/HartreeFockInfographic.png\" width=\"400\"></p>\n",
-    "\n",
-    "Why is it useful?\n",
-    "* If we tried to solve $N$ particles with $M$ distinct states exactly, the full Hilbert space is $M^N$. Mean-field maps into a much smaller non-interacting system of size $M N$\n",
-    "* Quantitative accuracy is either hit or miss, but gives a good understanding of the qualitative behaviour of the system.\n",
-    "\n",
-    "### General idea through an example\n",
-    "\n",
-    "#### The Ising model\n",
-    "\n",
-    "Consider an Ising model:\n",
-    "\n",
-    "<p style=\"text-align:center;\"><img src=\"https://pbs.twimg.com/media/DKu31zYXcAECSDL.jpg\" width=\"400\"></p>\n",
-    "\n",
-    "with the Hamiltonian (straight from [wikipedia](https://en.wikipedia.org/wiki/Mean-field_theory#Ising_model)):\n",
-    "\n",
-    "$$\n",
-    "H=-J\\sum _{\\langle i,j\\rangle }s_{i}s_{j}-h\\sum _{i}s_{i}\n",
-    "$$\n",
-    "\n",
-    "where $s_i$ is the spin of the $i$th particle, $J$ is the exchange coupling, and $h$ is the external magnetic field. The sum is over nearest neighbours.\n",
-    "\n",
-    "#### Identifying and applying mean field\n",
-    "\n",
-    "It is an interacting problem and thus a headache to solve. Rather than consider all the particles, lets consider a single particle in an **effective field** of other spins. To do that, lets define the average spin $m_{i}\\equiv \\langle s_{i} \\rangle$ and re-write the $s_i s_j$ product into:\n",
-    "\n",
-    "\n",
-    "$$\n",
-    "s_i s_j = m_i m_j + m_i \\delta s_j + m_j \\delta s_i + \\delta s_i \\delta s_j \n",
-    "$$\n",
-    "\n",
-    "if we assume the fluctuations are small, then at the very least the last term can be neglected:\n",
-    "\n",
-    "\n",
-    "$$\n",
-    "s_i s_j \\approx m_i m_j + m_i \\delta s_j + m_j \\delta s_i = m_i  s_j + m_j s_i - m_i m_j\n",
-    "$$\n",
-    "\n",
-    "and thus the Hamiltonian becomes:\n",
-    "\n",
-    "$$\n",
-    "H\\approx H^{\\text{MF}}\\equiv -J m \\sum _{\\langle i,j\\rangle }(2 s_{i} - m)-h\\sum _{i}s_{i}\n",
-    "$$\n",
-    "\n",
-    "where for simplicity I also assumed that the average spin $m_i$ is constant for all particles.\n",
-    "\n",
-    "#### Self-consistency\n",
-    "\n",
-    "The average mean-field $m$ here acts as a variable, or better yet, **an initial guess**. After solving $H_{\\text{MF}}$, we need to make sure that the $m$ is **self-consistent** with the new $s_i$:\n",
-    "\n",
-    "$$\n",
-    "m = \\frac{1}{N} \\sum_i^N \\langle s_i \\rangle.\n",
-    "$$\n",
-    "\n",
-    "So we re-calculate $m$, plug it back into the equation of $H_{\\text{MF}}$, and repeat until $m$ converges.\n",
-    "\n",
-    "#### Summary\n",
-    "\n",
-    "1. Identify the mean-field variables and construct the mean-field Hamiltonian.\n",
-    "2. Guess the initial mean-field.\n",
-    "3. Self-consistency loop:\n",
-    "    1. Solve the mean-field Hamiltonian $H_{\\text{MF}}$ for the given mean-field.\n",
-    "    2. Calculate the new mean-field.\n",
-    "    3. Check convergence. If not converged, go back to step 3.1. with the new mean-field.\n",
-    "4. ???\n",
-    "5. Profit.\n",
-    "\n",
-    "\n",
-    "## Why waste time with this?\n",
-    "\n",
-    "Interacting systems have become quite hot research field in condensed matter physics (I mean, take a look at graphene). However, numerical packages to solve them on tight-binding systems lack the following:\n",
-    "* Not many well-maintained packages.\n",
-    "* Code is needlessly complex and documentation is lacking.\n",
-    "* Lack generality.\n",
-    "\n",
-    "## Idea behind our implementation\n",
-    "\n",
-    "### Identifying mean-fields\n",
-    "\n",
-    "#### Real Space\n",
-    "\n",
-    "You can find the whole theory [here](https://hackmd.io/@-DUiWUyjQXei-EsdckYO-w/HyEbQhIjo).\n",
-    "\n",
-    "Here the the main points. A general particle number preserving interaction with all mean-fields can be written as a sort of [Wick's contraction](https://en.wikipedia.org/wiki/Wick%27s_theorem):\n",
-    "\n",
-    "$$\n",
-    "V = \\frac{1}{2}\\sum_{ijkl} v_{ijkl} c_i^{\\dagger} c_j^{\\dagger} c_l c_k\n",
-    "\\approx\n",
-    "\\frac12 \\sum_{ijkl} v_{ijkl} \\left[ \\langle c_i^{\\dagger} c_k \\rangle c_j^{\\dagger} c_l - \\langle c_j^{\\dagger} c_k \\rangle c_i^{\\dagger} c_l - \\langle c_i^{\\dagger} c_l \\rangle c_j^{\\dagger} c_k + \\langle c_j^{\\dagger} c_l \\rangle c_i^{\\dagger} c_k \\right]\n",
-    "$$\n",
-    "(we neglect superconductivity)\n",
-    "\n",
-    "here $i,j,k,l$ label any degree of freedom written on a tight-binding grid, so we maintain full generality. \n",
-    "\n",
-    "The mean-fields are in terms of second quantization operators, but how do we translate the problem to a tight-binding grid/matrix problem?\n",
-    "\n",
-    "$$\n",
-    "\\langle c_i^{\\dagger} c_j\\rangle = \\langle \\Psi_F|c_i^{\\dagger} c_j | \\Psi_F \\rangle\n",
-    "$$\n",
-    "\n",
-    "whereas $|\\Psi_F \\rangle = \\Pi_{i=0}^{N_F} b_i^\\dagger |0\\rangle$. To make sense of things, we need to transform between $c_i$ basis (position + internal dof basis) into the $b_i$ basis (eigenfunction of a given mean-field Hamiltonian):\n",
-    "\n",
-    "$$\n",
-    "c_i^\\dagger = \\sum_{k} U_{ik} b_k^\\dagger\n",
-    "$$\n",
-    "\n",
-    "where $U$ is the matrix of eigenvectors of the mean-field Hamiltonian:\n",
-    "\n",
-    "$$\n",
-    "U_{ik} = \\langle{i|\\psi_k} \\rangle.\n",
-    "$$\n",
-    "\n",
-    "That gives us:\n",
-    "\n",
-    "$$\n",
-    "c_i^{\\dagger} c_j = \\sum_{k, l} U_{ik} U_{lj}^* b_k^\\dagger b_{l}\n",
-    "$$\n",
-    "\n",
-    "and its expectation value gives us the mean-field ... field $F_{ij}$:\n",
-    "\n",
-    "$$\n",
-    "F_{ij} = \\langle c_i^{\\dagger} c_j\\rangle =  \\sum_{k, l} U_{ik} U_{lj}^* \\langle \\Psi_F| b_k^\\dagger b_{l}| \\Psi_F \\rangle =  \\sum_{k} U_{ik} U_{kj}^{*}\n",
-    "$$\n",
-    "\n",
-    "Coming back to the interaction, under mean-field and on our chosen tight-binding grid it reads:\n",
-    "\n",
-    "$$\n",
-    "V_{nm} \\approx -\\sum_{ij} F_{ij} \\left(v_{inmj} - v_{injm} \\right)\n",
-    "$$\n",
-    "\n",
-    "In the simple case of a Coulomb interaction, the potential reads:\n",
-    "\n",
-    "$$\n",
-    "V_{nm} = -F_{mn} v_{mn} + \\sum_{i} F_{ii} v_{in} \\delta_{nm}\n",
-    "$$\n",
-    "\n",
-    "where the second term is the Direct Coulomb interaction, and the first term is the exchange interaction.\n",
-    "\n",
-    "#### k-space or translational invariance case\n",
-    "\n",
-    "The above works for a finite sized tight-binding model, but what about a periodic system? In that case, we can use the Fourier transform to write the mean-field Hamiltonian in k-space. I'll spare you the details, the final result reads:\n",
-    "\n",
-    "$$\n",
-    "V_{nm}(k) =-F_{mn}(k) \\circledast v_{mn}(k) + \\sum_{p} \\rho_{p} v_{pn}(0) \\delta_{nm}\n",
-    "$$\n",
-    "\n",
-    "where $\\rho_{p}$ is the particle density at unit cell site $p$, averaged over a k-grid:\n",
-    "\n",
-    "$$\n",
-    "\\rho_{p} = \\int F_{pp}(k) dk \n",
-    "$$\n",
-    "\n",
-    "Once again, the first term (exchange) is purely responsible for the hopping whereas the second term (direct) is a potential term coming from the mean-field. "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## The actual code\n",
-    "\n",
-    "First, lets create a non-interacting system. In this case, we will go with simple graphene:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import kwant\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "\n",
-    "s0 = np.identity(2)\n",
-    "sz = np.diag([1, -1])\n",
-    "\n",
-    "\n",
-    "graphene = kwant.lattice.general(\n",
-    "    [[1, 0], [1 / 2, np.sqrt(3) / 2]], [[0, 0], [0, 1 / np.sqrt(3)]]\n",
-    ")\n",
-    "a, b = graphene.sublattices\n",
-    "\n",
-    "# create bulk system\n",
-    "bulk_graphene = kwant.Builder(kwant.TranslationalSymmetry(*graphene.prim_vecs))\n",
-    "# add sublattice potential\n",
-    "m0 = 0\n",
-    "bulk_graphene[a.shape((lambda pos: True), (0, 0))] = m0 * sz\n",
-    "bulk_graphene[b.shape((lambda pos: True), (0, 0))] = -m0 * sz\n",
-    "# add hoppings between sublattices\n",
-    "bulk_graphene[graphene.neighbors(1)] = s0\n",
-    "\n",
-    "# use kwant wraparound to sample bulk k-space\n",
-    "wrapped_syst_unfinalized = kwant.wraparound.wraparound(bulk_graphene)\n",
-    "wrapped_syst = kwant.wraparound.wraparound(bulk_graphene).finalized()\n",
-    "\n",
-    "\n",
-    "# return a hamiltonian for a given kx, ky\n",
-    "@np.vectorize\n",
-    "def hamiltonian_return(kx, ky, params={}):\n",
-    "    ham = wrapped_syst.hamiltonian_submatrix(params={**params, **dict(k_x=kx, k_y=ky)})\n",
-    "    return ham"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now we sample the non-interacting hamiltonian on a k-grid:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "N_ks = 60  # number of k-points in each direction\n",
-    "N_k_axis = np.linspace(0, 2 * np.pi, N_ks, endpoint=False)\n",
-    "hamiltonians_0 = np.array(\n",
-    "    [[hamiltonian_return(kx, ky) for kx in N_k_axis] for ky in N_k_axis]\n",
-    ")\n",
-    "\n",
-    "vals0, vecs0 = np.linalg.eigh(hamiltonians_0)\n",
-    "for i in range(len(vals0[:, 0, 0])):\n",
-    "    for j in range(4):\n",
-    "        plt.plot(vals0[i, :, j])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now we need several helper functions to compute:\n",
-    "* the mean-field $F$ for each k-point\n",
-    "* the Fermi level based on the filling (we need to know what states will be occupied!)\n",
-    "* the convolution in k-space with periodic boundary conditions.\n",
-    "* convergence of the mean field\n",
-    "* energy per atom"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def mean_field_F(vals, vecs, E_F=0):\n",
-    "    N_ks = vals.shape[0]\n",
-    "\n",
-    "    def mf_generator(i, j):\n",
-    "        vals_i = vals[i, j, :]\n",
-    "        vecs_i = vecs[i, j, :, :]\n",
-    "        n_occ = vals_i < E_F\n",
-    "        occ_vecs = vecs_i[:, n_occ]\n",
-    "        F_ij = occ_vecs @ occ_vecs.conj().T\n",
-    "        return F_ij\n",
-    "\n",
-    "    F = np.array([[mf_generator(i, j) for i in range(N_ks)] for j in range(N_ks)])\n",
-    "    return F\n",
-    "\n",
-    "\n",
-    "def get_fermi_energy(vals_flat, filling):\n",
-    "    ne = len(vals_flat)\n",
-    "    ifermi = int(round(ne * filling))  # index for fermi\n",
-    "    if ifermi >= ne:\n",
-    "        ifermi = ne - 1\n",
-    "    sorte = np.sort(vals_flat)  # sorted eigenvalues\n",
-    "    if ifermi == 0:\n",
-    "        return sorte[0]\n",
-    "    fermi = (sorte[ifermi - 1] + sorte[ifermi]) / 2.0  # fermi energy\n",
-    "    return fermi\n",
-    "\n",
-    "\n",
-    "from scipy.signal import convolve2d\n",
-    "\n",
-    "\n",
-    "def convolution(M1, M2):\n",
-    "    cell_size = V.shape[2]\n",
-    "    V_output = np.array(\n",
-    "        [\n",
-    "            [\n",
-    "                convolve2d(M1[:, :, i, j], M2[:, :, i, j], boundary=\"wrap\", mode=\"same\")\n",
-    "                for i in range(cell_size)\n",
-    "            ]\n",
-    "            for j in range(cell_size)\n",
-    "        ]\n",
-    "    )\n",
-    "    V_output = np.transpose(V_output, axes=(2, 3, 0, 1))\n",
-    "    return V_output\n",
-    "\n",
-    "\n",
-    "def dm(mf_new, mf):\n",
-    "    # relative convergence of the mean field\n",
-    "    mf_max = np.abs(np.max(np.concatenate((mf.flatten(), mf_new.flatten()))))\n",
-    "    delta = np.abs(mf_new - mf) / mf_max\n",
-    "    return np.max(delta)\n",
-    "\n",
-    "\n",
-    "def energy_per_atom(vals, E_F):\n",
-    "    N_filling = np.sum((vals < E_F).flatten())\n",
-    "    E_total = np.sum(vals[vals < E_F].flatten())\n",
-    "    E_p_atom = E_total / N_filling\n",
-    "    return E_p_atom"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Now its time to spice it up - consider a simple onsite Coulomb interaction. We make it the same for all k-point since we are lazy, but in general, you would have to Fourier transform interaction into k-space:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[2.5, 2.5, 0. , 0. ],\n",
-       "       [2.5, 2.5, 0. , 0. ],\n",
-       "       [0. , 0. , 2.5, 2.5],\n",
-       "       [0. , 0. , 2.5, 2.5]])"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "U = 2.5\n",
-    "# we need block diagonal structure here since opposite spins interact on the same sublattice\n",
-    "v_int = U * np.block(\n",
-    "    [[np.ones((2, 2)), np.zeros((2, 2))], [np.zeros((2, 2)), np.ones((2, 2))]]\n",
-    ")\n",
-    "# repeat the matrix on a k-grid\n",
-    "V = np.array([[v_int for i in range(N_ks)] for j in range(N_ks)])\n",
-    "v_int"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Threshold reached in 51 steps\n",
-      "Energy per atom: -0.3494095226149221\n"
-     ]
-    }
-   ],
-   "source": [
-    "mixing = 0.6\n",
-    "threshold = 1e-3\n",
-    "for n in range(5000):\n",
-    "    if n == 0:\n",
-    "        mf = np.diag(np.random.rand(4)) - 0.5  # starting guess\n",
-    "        hamiltonians = hamiltonians_0 + mf\n",
-    "        vals, vecs = np.linalg.eigh(hamiltonians)\n",
-    "        E_F = get_fermi_energy(vals.flatten(), 0.5)\n",
-    "    F = mean_field_F(vals, vecs, E_F=E_F)\n",
-    "    rho = np.diag(np.average(F, axis=(0, 1)))\n",
-    "    exchange_mf = convolution(F, V) * N_ks ** (-2)  # exchange term\n",
-    "    direct_mf = np.diag(np.einsum(\"i,ij->j\", rho, v_int))  # direct term\n",
-    "\n",
-    "    mf_new = direct_mf - exchange_mf\n",
-    "    hamiltonians = hamiltonians_0 + mixing * mf_new + (1 - mixing) * mf\n",
-    "\n",
-    "    vals, vecs = np.linalg.eigh(hamiltonians)\n",
-    "    E_F = get_fermi_energy(vals.flatten(), 0.5)\n",
-    "    delta_m = dm(mf_new, mf)\n",
-    "    if delta_m < threshold:\n",
-    "        print(f\"Threshold reached in {n} steps\")\n",
-    "        E_p_atom = energy_per_atom(vals, E_F)\n",
-    "        print(f\"Energy per atom: {E_p_atom}\")\n",
-    "        break\n",
-    "    print(f\"{delta_m}\", end=\"\\r\")\n",
-    "    mf = mf_new"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x7f2770fc4520>"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 480x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "for i in range(len(vals[:,0,0])):\n",
-    "    for j in range(4):\n",
-    "        plt.plot(vals[i,:,j])\n",
-    "plt.show()\n",
-    "plt.matshow(np.real(mf[40,20,:,:])-E_F, cmap=\"RdBu\", vmin=-0.5, vmax=0.5) # plotting the mean field\n",
-    "plt.colorbar()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "According to [literature](https://theses.hal.science/tel-02930295v2/document), the critical value for phase transition is around $U=2.23t$, which is around what we get!"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Scaling of the algorithm\n",
-    "\n",
-    "Lets say $M$ is the number of degrees of freedom within the unit cell, and $N$ is the number of k-points along a direction (we consider 2D problem here). Then the following steps limit the scaling of the algorithm:\n",
-    "* Eigenvalue problem for each k-point: $O(N^2 M^3)$.\n",
-    "* Convolution in k-space: $O(N^4 M^2)$. In this case, this is the most expensive step."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# experimental implementation of general Coulomb interaction in case we want to play around.\n",
-    "import scipy.constants as spc\n",
-    "\n",
-    "\n",
-    "def func_onsite(site, U):\n",
-    "    return U * np.ones((2, 2))\n",
-    "\n",
-    "\n",
-    "constant = (\n",
-    "    spc.physical_constants[\"fine-structure constant\"][0] * spc.hbar * spc.c\n",
-    ")  # energy * distance\n",
-    "constant /= 2.8 * spc.e * 1.4 * spc.angstrom\n",
-    "\n",
-    "\n",
-    "def func_hop(site1, site2, U, r_TF):\n",
-    "    rij = np.linalg.norm(site1.pos - site2.pos)\n",
-    "    return (\n",
-    "        U\n",
-    "        * np.exp(-rij / r_TF)\n",
-    "        / np.sqrt(1 + (U * rij * constant) ** 2)\n",
-    "        * np.ones((2, 2))\n",
-    "    )\n",
-    "\n",
-    "\n",
-    "lattice = graphene\n",
-    "max_neighbor = 1\n",
-    "syst = wrapped_syst_unfinalized\n",
-    "V = kwant.Builder(kwant.TranslationalSymmetry(*lattice.prim_vecs))\n",
-    "V[syst.sites()] = func_onsite\n",
-    "for n in range(max_neighbor):\n",
-    "    V[lattice.neighbors(n + 1)] = func_hop\n",
-    "wrapped = kwant.wraparound.wraparound(V).finalized()\n",
-    "\n",
-    "\n",
-    "@np.vectorize\n",
-    "def compute_Vk(dummy_syst, kx, ky, params={}):\n",
-    "    V = dummy_syst.hamiltonian_submatrix(params={**params, **dict(k_x=kx, k_y=ky)})\n",
-    "    return V\n",
-    "\n",
-    "\n",
-    "def potential_to_hamiltonian(\n",
-    "    syst, lattice, func_onsite, func_hop, params, max_neighbor=2\n",
-    "):\n",
-    "    V = kwant.Builder(kwant.TranslationalSymmetry(*lattice.prim_vecs))\n",
-    "    V[syst.sites()] = func_onsite\n",
-    "    for n in range(max_neighbor):\n",
-    "        V[lattice.neighbors(n + 1)] = func_hop\n",
-    "    wrapped_V = kwant.wraparound.wraparound(V).finalized()\n",
-    "    return np.array(\n",
-    "        [\n",
-    "            [\n",
-    "                compute_Vk(dummy_syst=wrapped_V, kx=kx, ky=ky, params=params)\n",
-    "                for kx in N_k_axis\n",
-    "            ]\n",
-    "            for ky in N_k_axis\n",
-    "        ]\n",
-    "    )\n",
-    "\n",
-    "\n",
-    "U = 3\n",
-    "\n",
-    "V = potential_to_hamiltonian(\n",
-    "    syst=wrapped_syst_unfinalized,\n",
-    "    lattice=graphene,\n",
-    "    func_onsite=func_onsite,\n",
-    "    func_hop=func_hop,\n",
-    "    params=dict(U=U, r_TF=1e-9),\n",
-    ")\n",
-    "\n",
-    "# Getting the (0,0) component in k-space for direct interactions\n",
-    "V_direct = V[0, 0]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.8"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "6b7342be4d7622df79515c26158aa777f5c3738125f220c5a98bec2a0cbdfb50"
-   }
-  },
-  "widgets": {
-   "application/vnd.jupyter.widget-state+json": {
-    "state": {},
-    "version_major": 2,
-    "version_minor": 0
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/analysis/scipy_optimizer.ipynb b/analysis/scipy_optimizer.ipynb
deleted file mode 100644
index 681efa222d034c0734b00a3cb72bbb1acd704d9e..0000000000000000000000000000000000000000
--- a/analysis/scipy_optimizer.ipynb
+++ /dev/null
@@ -1,330 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "cb509096-42c6-4a45-8dc4-a8eed3116e67",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "import kwant\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "from codes import utils, hf\n",
-    "from scipy.optimize import anderson\n",
-    "from tqdm import tqdm\n",
-    "\n",
-    "s0 = np.identity(2)\n",
-    "sz = np.diag([1, -1])\n",
-    "\n",
-    "norbs=2\n",
-    "\n",
-    "graphene = kwant.lattice.general(\n",
-    "    [[1, 0], [1 / 2, np.sqrt(3) / 2]], [[0, 0], [0, 1 / np.sqrt(3)]],\n",
-    "    norbs=norbs\n",
-    ")\n",
-    "a, b = graphene.sublattices\n",
-    "\n",
-    "# create bulk system\n",
-    "bulk_graphene = kwant.Builder(kwant.TranslationalSymmetry(*graphene.prim_vecs))\n",
-    "# add sublattice potential\n",
-    "m0 = 0\n",
-    "bulk_graphene[a.shape((lambda pos: True), (0, 0))] = m0 * sz\n",
-    "bulk_graphene[b.shape((lambda pos: True), (0, 0))] = -m0 * sz\n",
-    "# add hoppings between sublattices\n",
-    "bulk_graphene[graphene.neighbors(1)] = s0\n",
-    "\n",
-    "# use kwant wraparound to sample bulk k-space\n",
-    "wrapped_syst = kwant.wraparound.wraparound(bulk_graphene)\n",
-    "wrapped_fsyst = kwant.wraparound.wraparound(bulk_graphene).finalized()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "9cc3b32d-404f-4bc5-a338-83571c9e4c4b",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "def func_onsite(site, U):\n",
-    "    return U * np.ones((2, 2))\n",
-    "\n",
-    "def func_hop(site1, site2, V):\n",
-    "    rij = np.linalg.norm(site1.pos - site2.pos)\n",
-    "    return V * np.ones((2, 2))\n",
-    "\n",
-    "def calculate_Hint(U, V, Uk, Vk):\n",
-    "    return U * Uk + V * Vk"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "a341e0e5-330e-48d1-a20f-a0040688a9d7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "nk = 10\n",
-    "# Generate coarse-grid k-points\n",
-    "ks, dk = np.linspace(0, 2 * np.pi, nk, endpoint=False, retstep=True)\n",
-    "# Generate Hamiltonian on a k-point grid\n",
-    "hamiltonians_0 = utils.syst2hamiltonian(ks=ks, syst=wrapped_fsyst)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "d1ef154e-70bd-4f28-887f-72362d8533dd",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "Us = np.linspace(0, 4, 10)\n",
-    "Vs = np.linspace(0, 1.5, 10)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "32b9e7c5-db12-44f9-930c-21e5494404b8",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "_, deltas = utils.generate_scf_syst(\n",
-    "    max_neighbor=1, syst=wrapped_syst, lattice=graphene\n",
-    ")\n",
-    "deltas = np.asarray(deltas) #deltas are the hopping vecs\n",
-    "deltas = np.unique(np.stack([*deltas, *-deltas]), axis=(0))\n",
-    "\n",
-    "def compute_gap(\n",
-    "    U,\n",
-    "    V,\n",
-    "    H_int,\n",
-    "    max_neighbor=1,\n",
-    "    lattice=graphene,\n",
-    "    filling=2,\n",
-    "    nk=12,\n",
-    "    tol=1e-5,\n",
-    "    norbs=norbs,\n",
-    "    nk_dense=30,\n",
-    "    mixing=0.5,\n",
-    "    order=1,\n",
-    "    guess=None\n",
-    "):\n",
-    "    # Generate coarse-grid k-points\n",
-    "    ks, dk = np.linspace(0, 2 * np.pi, nk, endpoint=False, retstep=True)\n",
-    "    # Generate Hamiltonian on a k-point grid\n",
-    "    hamiltonians_0 = utils.syst2hamiltonian(ks=ks, syst=wrapped_fsyst)\n",
-    "    # Generate guess on the same grid\n",
-    "    if guess is None:\n",
-    "        guess = utils.generate_guess(ks, deltas, ndof=hamiltonians_0.shape[-1], scale=1)\n",
-    "    else:\n",
-    "        guess += np.max(guess) * utils.generate_guess(ks, deltas, ndof=hamiltonians_0.shape[-1], scale=0.1)\n",
-    "    \n",
-    "    # Find groundstate Hamiltonian on the same grid\n",
-    "    hk = hf.find_groundstate_ham(\n",
-    "        H_int=H_int,\n",
-    "        filling=filling,\n",
-    "        hamiltonians_0=hamiltonians_0,\n",
-    "        tol=tol,\n",
-    "        guess=guess,\n",
-    "        mixing=mixing,\n",
-    "        order=order,\n",
-    "    )\n",
-    "    # Diagonalize groundstate Hamiltonian\n",
-    "    vals, vecs = np.linalg.eigh(hk)\n",
-    "    # Extract coarse-grid Fermi energy\n",
-    "    E_F = utils.get_fermi_energy(vals, 2)\n",
-    "    # Generate dense-grid k-points\n",
-    "    ks_dense = np.linspace(0, 2 * np.pi, nk_dense, endpoint=False)\n",
-    "    # Compute groundstate Hamiltonian on a dense grid\n",
-    "    scf_ham = utils.hk_densegrid(hk, ks, ks_dense, deltas)\n",
-    "    # Diagonalize groundstate Hamiltonian\n",
-    "    vals, vecs = np.linalg.eigh(scf_ham)\n",
-    "    # Extract dense-grid Fermi energy\n",
-    "    E_F = utils.get_fermi_energy(vals, 2)\n",
-    "\n",
-    "    gap = utils.calc_gap(vals, E_F)\n",
-    "    return gap, hk\n",
-    "\n",
-    "\n",
-    "def compute_phase_diagram(Us, Vs, nk, tol, mixing, order):\n",
-    "    import qsymm\n",
-    "    import adaptive\n",
-    "    from codes import utils, hf\n",
-    "\n",
-    "    ks = np.linspace(0, 2 * np.pi, nk, endpoint=False)\n",
-    "\n",
-    "    Uk = utils.potential2hamiltonian(\n",
-    "        syst=wrapped_syst,\n",
-    "        lattice=graphene,\n",
-    "        func_onsite=func_onsite,\n",
-    "        func_hop=func_hop,\n",
-    "        params=dict(U=1, V=0),\n",
-    "        ks=ks,\n",
-    "    )\n",
-    "\n",
-    "    Vk = utils.potential2hamiltonian(\n",
-    "        syst=wrapped_syst,\n",
-    "        lattice=graphene,\n",
-    "        func_onsite=func_onsite,\n",
-    "        func_hop=func_hop,\n",
-    "        params=dict(U=0, V=1),\n",
-    "        ks=ks,\n",
-    "    )\n",
-    "    gap = []\n",
-    "    for U in tqdm(Us):\n",
-    "        guess = None\n",
-    "        gap_U = []\n",
-    "        for V in Vs:\n",
-    "            H_int = calculate_Hint(U, V, Uk, Vk)\n",
-    "            _gap, guess = compute_gap(\n",
-    "                U=U, V=V, H_int=H_int, nk=nk, tol=tol, mixing=mixing, order=order, guess=guess\n",
-    "            )\n",
-    "            gap_U.append(_gap)\n",
-    "        gap.append(gap_U)\n",
-    "    return np.asarray(gap, dtype=float)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6a8c08a9-7e31-420b-b6b4-709abfb26793",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      " 70%|███████   | 7/10 [06:20<03:32, 70.75s/it]"
-     ]
-    }
-   ],
-   "source": [
-    "gap = compute_phase_diagram(Us, Vs, nk=15, tol=1e-5, mixing=0.01, order=10)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "39edbf19",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x7fee6f0d48d0>"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.imshow(np.log10(gap).T, origin='lower', extent=(Us.min(), Us.max(), Vs.min(), Vs.max()), vmin=-1)\n",
-    "plt.colorbar()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "27f9d0d8",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x7f717551ca90>"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.imshow((gap).T, origin='lower', extent=(Us.min(), Us.max(), Vs.min(), Vs.max()), vmin=0)\n",
-    "plt.colorbar()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "id": "e17fc96c-c463-4e1f-8250-c254d761b92a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import xarray as xr\n",
-    "gap_da = xr.DataArray(data=gap, coords=dict(Us=Us, Vs=Vs))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "id": "0cb395cd-84d1-49b4-89dd-da7a2d09c8d0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "gap_da.to_netcdf('./data/graphene_example.nc')"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.5"
-  },
-  "widgets": {
-   "application/vnd.jupyter.widget-state+json": {
-    "state": {},
-    "version_major": 2,
-    "version_minor": 0
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/data b/data
deleted file mode 160000
index e8340872e43b81f93f5417a23328955b253ff1c4..0000000000000000000000000000000000000000
--- a/data
+++ /dev/null
@@ -1 +0,0 @@
-Subproject commit e8340872e43b81f93f5417a23328955b253ff1c4
diff --git a/analysis/codes b/examples/codes
similarity index 100%
rename from analysis/codes
rename to examples/codes
diff --git a/examples/data/graphene_example.nc b/examples/data/graphene_example.nc
new file mode 100644
index 0000000000000000000000000000000000000000..e1e2d3c99cabc1b52aadeb1cc9278abb321fea2c
Binary files /dev/null and b/examples/data/graphene_example.nc differ
diff --git a/analysis/data/graphene_test.nc b/examples/data/graphene_test.nc
similarity index 100%
rename from analysis/data/graphene_test.nc
rename to examples/data/graphene_test.nc
diff --git a/examples/graphene_extended_hubbard.ipynb b/examples/graphene_extended_hubbard.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..6d1743b04ed0da5bab2c64cc20d7c55fbd9fe593
--- /dev/null
+++ b/examples/graphene_extended_hubbard.ipynb
@@ -0,0 +1,352 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "cb509096-42c6-4a45-8dc4-a8eed3116e67",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import kwant\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "from codes import utils, hf\n",
+    "from scipy.optimize import anderson\n",
+    "from tqdm import tqdm\n",
+    "\n",
+    "s0 = np.identity(2)\n",
+    "sz = np.diag([1, -1])\n",
+    "\n",
+    "norbs=2\n",
+    "\n",
+    "graphene = kwant.lattice.general(\n",
+    "    [[1, 0], [1 / 2, np.sqrt(3) / 2]], [[0, 0], [0, 1 / np.sqrt(3)]],\n",
+    "    norbs=norbs\n",
+    ")\n",
+    "a, b = graphene.sublattices\n",
+    "\n",
+    "# create bulk system\n",
+    "bulk_graphene = kwant.Builder(kwant.TranslationalSymmetry(*graphene.prim_vecs))\n",
+    "# add sublattice potential\n",
+    "m0 = 0\n",
+    "bulk_graphene[a.shape((lambda pos: True), (0, 0))] = m0 * sz\n",
+    "bulk_graphene[b.shape((lambda pos: True), (0, 0))] = -m0 * sz\n",
+    "# add hoppings between sublattices\n",
+    "bulk_graphene[graphene.neighbors(1)] = s0\n",
+    "\n",
+    "# use kwant wraparound to sample bulk k-space\n",
+    "wrapped_syst = kwant.wraparound.wraparound(bulk_graphene)\n",
+    "wrapped_fsyst = kwant.wraparound.wraparound(bulk_graphene).finalized()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "9cc3b32d-404f-4bc5-a338-83571c9e4c4b",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "def func_onsite(site, U):\n",
+    "    return U * np.ones((2, 2))\n",
+    "\n",
+    "def func_hop(site1, site2, V):\n",
+    "    rij = np.linalg.norm(site1.pos - site2.pos)\n",
+    "    return V * np.ones((2, 2))\n",
+    "\n",
+    "def calculate_Hint(U, V, Uk, Vk):\n",
+    "    return U * Uk + V * Vk"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "a341e0e5-330e-48d1-a20f-a0040688a9d7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "nk = 10\n",
+    "# Generate coarse-grid k-points\n",
+    "ks, dk = np.linspace(0, 2 * np.pi, nk, endpoint=False, retstep=True)\n",
+    "# Generate Hamiltonian on a k-point grid\n",
+    "hamiltonians_0 = utils.syst2hamiltonian(ks=ks, syst=wrapped_fsyst)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "d1ef154e-70bd-4f28-887f-72362d8533dd",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "Us = np.linspace(0, 4, 50)\n",
+    "Vs = np.linspace(0, 1.5, 20)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "32b9e7c5-db12-44f9-930c-21e5494404b8",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "_, deltas = utils.generate_scf_syst(\n",
+    "    max_neighbor=1, syst=wrapped_syst, lattice=graphene\n",
+    ")\n",
+    "deltas = np.asarray(deltas) #deltas are the hopping vecs\n",
+    "deltas = np.unique(np.stack([*deltas, *-deltas]), axis=(0))\n",
+    "\n",
+    "def compute_gap(\n",
+    "    U,\n",
+    "    V,\n",
+    "    H_int,\n",
+    "    max_neighbor=1,\n",
+    "    lattice=graphene,\n",
+    "    filling=2,\n",
+    "    nk=12,\n",
+    "    tol=1e-5,\n",
+    "    norbs=norbs,\n",
+    "    nk_dense=30,\n",
+    "    mixing=0.5,\n",
+    "    order=1,\n",
+    "    guess=None\n",
+    "):\n",
+    "    # Generate coarse-grid k-points\n",
+    "    ks, dk = np.linspace(0, 2 * np.pi, nk, endpoint=False, retstep=True)\n",
+    "    # Generate Hamiltonian on a k-point grid\n",
+    "    hamiltonians_0 = utils.syst2hamiltonian(ks=ks, syst=wrapped_fsyst)\n",
+    "    # Generate guess on the same grid\n",
+    "    if guess is None:\n",
+    "        guess = utils.generate_guess(ks, deltas, ndof=hamiltonians_0.shape[-1], scale=1)\n",
+    "    else:\n",
+    "        guess += np.max(guess) * utils.generate_guess(ks, deltas, ndof=hamiltonians_0.shape[-1], scale=0.1)\n",
+    "    \n",
+    "    # Find groundstate Hamiltonian on the same grid\n",
+    "    hk = hf.find_groundstate_ham(\n",
+    "        H_int=H_int,\n",
+    "        filling=filling,\n",
+    "        hamiltonians_0=hamiltonians_0,\n",
+    "        tol=tol,\n",
+    "        guess=guess,\n",
+    "        mixing=mixing,\n",
+    "        order=order,\n",
+    "    )\n",
+    "    # Diagonalize groundstate Hamiltonian\n",
+    "    vals, vecs = np.linalg.eigh(hk)\n",
+    "    # Extract coarse-grid Fermi energy\n",
+    "    E_F = utils.get_fermi_energy(vals, 2)\n",
+    "    # Generate dense-grid k-points\n",
+    "    ks_dense = np.linspace(0, 2 * np.pi, nk_dense, endpoint=False)\n",
+    "    # Compute groundstate Hamiltonian on a dense grid\n",
+    "    scf_ham = utils.hk_densegrid(hk, ks, ks_dense, deltas)\n",
+    "    # Diagonalize groundstate Hamiltonian\n",
+    "    vals, vecs = np.linalg.eigh(scf_ham)\n",
+    "    # Extract dense-grid Fermi energy\n",
+    "    E_F = utils.get_fermi_energy(vals, 2)\n",
+    "\n",
+    "    gap = utils.calc_gap(vals, E_F)\n",
+    "    return gap, hk\n",
+    "\n",
+    "\n",
+    "def compute_phase_diagram(Us, Vs, nk, tol, mixing, order):\n",
+    "    import qsymm\n",
+    "    import adaptive\n",
+    "    from codes import utils, hf\n",
+    "\n",
+    "    ks = np.linspace(0, 2 * np.pi, nk, endpoint=False)\n",
+    "\n",
+    "    Uk = utils.potential2hamiltonian(\n",
+    "        syst=wrapped_syst,\n",
+    "        lattice=graphene,\n",
+    "        func_onsite=func_onsite,\n",
+    "        func_hop=func_hop,\n",
+    "        params=dict(U=1, V=0),\n",
+    "        ks=ks,\n",
+    "    )\n",
+    "\n",
+    "    Vk = utils.potential2hamiltonian(\n",
+    "        syst=wrapped_syst,\n",
+    "        lattice=graphene,\n",
+    "        func_onsite=func_onsite,\n",
+    "        func_hop=func_hop,\n",
+    "        params=dict(U=0, V=1),\n",
+    "        ks=ks,\n",
+    "    )\n",
+    "    gap = []\n",
+    "    for U in tqdm(Us):\n",
+    "        guess = None\n",
+    "        gap_U = []\n",
+    "        for V in Vs:\n",
+    "            H_int = calculate_Hint(U, V, Uk, Vk)\n",
+    "            _gap, guess = compute_gap(\n",
+    "                U=U, V=V, H_int=H_int, nk=nk, tol=tol, mixing=mixing, order=order, guess=guess\n",
+    "            )\n",
+    "            gap_U.append(_gap)\n",
+    "        gap.append(gap_U)\n",
+    "    return np.asarray(gap, dtype=float)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "6a8c08a9-7e31-420b-b6b4-709abfb26793",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "  8%|â–Š         | 4/50 [03:05<34:05, 44.48s/it]/opt/conda/lib/python3.11/site-packages/scipy/optimize/_nonlin.py:1074: LinAlgWarning: Ill-conditioned matrix (rcond=1.67985e-18): result may not be accurate.\n",
+      "  gamma = solve(self.a, df_f)\n",
+      "/opt/conda/lib/python3.11/site-packages/scipy/optimize/_nonlin.py:1074: LinAlgWarning: Ill-conditioned matrix (rcond=1.35418e-18): result may not be accurate.\n",
+      "  gamma = solve(self.a, df_f)\n",
+      "/opt/conda/lib/python3.11/site-packages/scipy/optimize/_nonlin.py:1074: LinAlgWarning: Ill-conditioned matrix (rcond=1.65467e-17): result may not be accurate.\n",
+      "  gamma = solve(self.a, df_f)\n",
+      "/opt/conda/lib/python3.11/site-packages/scipy/optimize/_nonlin.py:1074: LinAlgWarning: Ill-conditioned matrix (rcond=1.41405e-17): result may not be accurate.\n",
+      "  gamma = solve(self.a, df_f)\n",
+      " 10%|â–ˆ         | 5/50 [03:39<30:38, 40.86s/it]/opt/conda/lib/python3.11/site-packages/scipy/optimize/_nonlin.py:1074: LinAlgWarning: Ill-conditioned matrix (rcond=1.08904e-17): result may not be accurate.\n",
+      "  gamma = solve(self.a, df_f)\n",
+      " 46%|████▌     | 23/50 [18:08<21:08, 46.97s/it]/opt/conda/lib/python3.11/site-packages/scipy/optimize/_nonlin.py:1074: LinAlgWarning: Ill-conditioned matrix (rcond=8.96238e-17): result may not be accurate.\n",
+      "  gamma = solve(self.a, df_f)\n",
+      " 58%|█████▊    | 29/50 [34:18<1:09:00, 197.17s/it]/opt/conda/lib/python3.11/site-packages/scipy/optimize/_nonlin.py:1074: LinAlgWarning: Ill-conditioned matrix (rcond=5.74155e-17): result may not be accurate.\n",
+      "  gamma = solve(self.a, df_f)\n",
+      "/opt/conda/lib/python3.11/site-packages/scipy/optimize/_nonlin.py:1074: LinAlgWarning: Ill-conditioned matrix (rcond=4.45034e-17): result may not be accurate.\n",
+      "  gamma = solve(self.a, df_f)\n",
+      "/opt/conda/lib/python3.11/site-packages/scipy/optimize/_nonlin.py:1074: LinAlgWarning: Ill-conditioned matrix (rcond=1.19451e-18): result may not be accurate.\n",
+      "  gamma = solve(self.a, df_f)\n",
+      "/opt/conda/lib/python3.11/site-packages/scipy/optimize/_nonlin.py:1074: LinAlgWarning: Ill-conditioned matrix (rcond=2.7833e-17): result may not be accurate.\n",
+      "  gamma = solve(self.a, df_f)\n",
+      "/opt/conda/lib/python3.11/site-packages/scipy/optimize/_nonlin.py:1074: LinAlgWarning: Ill-conditioned matrix (rcond=1.16944e-17): result may not be accurate.\n",
+      "  gamma = solve(self.a, df_f)\n",
+      "100%|██████████| 50/50 [1:22:22<00:00, 98.86s/it] \n"
+     ]
+    }
+   ],
+   "source": [
+    "gap = compute_phase_diagram(Us, Vs, nk=15, tol=1e-5, mixing=0.01, order=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "39edbf19",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.colorbar.Colorbar at 0x7fee6ee82690>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.imshow(np.log10(gap).T, origin='lower', extent=(Us.min(), Us.max(), Vs.min(), Vs.max()), vmin=-1)\n",
+    "plt.colorbar()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "27f9d0d8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.colorbar.Colorbar at 0x7fee6ed3e910>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.imshow((gap).T, origin='lower', extent=(Us.min(), Us.max(), Vs.min(), Vs.max()), vmin=0)\n",
+    "plt.colorbar()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "e17fc96c-c463-4e1f-8250-c254d761b92a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xarray as xr\n",
+    "gap_da = xr.DataArray(data=gap, coords=dict(Us=Us, Vs=Vs))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "0cb395cd-84d1-49b4-89dd-da7a2d09c8d0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gap_da.to_netcdf('./data/graphene_example.nc')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
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