From f2c1cc3d623f8a8a71eb3c132357b2d376314b73 Mon Sep 17 00:00:00 2001
From: Manuel Morales <64017590+manuel-morales-a@users.noreply.github.com>
Date: Mon, 23 Dec 2024 14:04:10 -0300
Subject: [PATCH] docs: re-run and seed SBC tutorial (#1336)

* Got rid of not used method

* Done until Ranks versus Uniform distribution subsection

* Done until DAP versus prior

* Done until Running SBC

* Done until When things go haywire

* Done until A dispersed posterior

* Done

* Cells properly executed
---
 ...nostics_simulation_based_calibration.ipynb | 278 +++++++++++++++---
 1 file changed, 244 insertions(+), 34 deletions(-)

diff --git a/tutorials/11_diagnostics_simulation_based_calibration.ipynb b/tutorials/11_diagnostics_simulation_based_calibration.ipynb
index 5fa160cfc..0763772b3 100644
--- a/tutorials/11_diagnostics_simulation_based_calibration.ipynb
+++ b/tutorials/11_diagnostics_simulation_based_calibration.ipynb
@@ -78,7 +78,10 @@
     "\n",
     "from sbi.analysis.plot import sbc_rank_plot\n",
     "from sbi.diagnostics import check_sbc, check_tarp, run_sbc, run_tarp\n",
-    "from sbi.inference import NPE, simulate_for_sbi"
+    "from sbi.inference import NPE\n",
+    "\n",
+    "# Set random seed\n",
+    "_ = torch.manual_seed(42)"
    ]
   },
   {
@@ -130,8 +133,6 @@
     "    ).sample()\n",
     "    return value\n",
     "\n",
-    "\n",
-    "_ = torch.manual_seed(3)\n",
     "theta = prior.sample((num_simulations,))\n",
     "x = simulator(theta)"
    ]
@@ -145,14 +146,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "theta: [[1.9352932 1.3774877]]\n",
-      "x    : [[1.941461  1.4396194]]\n"
+      "theta: [[3.8389134 1.6634762]]\n",
+      "x    : [[3.9267206 1.6138272]]\n"
      ]
     }
    ],
    "source": [
-    "_ = torch.manual_seed(1)\n",
-    "\n",
     "# let's sample an observation from the parameters we\n",
     "# just produced\n",
     "theta_o = prior.sample((1,))\n",
@@ -170,13 +169,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      " Neural network successfully converged after 66 epochs."
+      " Neural network successfully converged after 93 epochs."
      ]
     }
    ],
    "source": [
-    "_ = torch.manual_seed(2)\n",
-    "\n",
     "# we use a mdn model to have a fast turnaround with training the NPE\n",
     "inferer = NPE(prior, density_estimator=\"nsf\")\n",
     "# append simulations and run training.\n",
@@ -185,12 +182,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "47b1ba98ab1d4c4e8d75703114a3adee",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Drawing 10000 posterior samples:   0%|          | 0/10000 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/manuelmorales/miniconda3/envs/sbi_dev_e/lib/python3.10/site-packages/nflows/transforms/lu.py:80: UserWarning: torch.triangular_solve is deprecated in favor of torch.linalg.solve_triangularand will be removed in a future PyTorch release.\n",
+      "torch.linalg.solve_triangular has its arguments reversed and does not return a copy of one of the inputs.\n",
+      "X = torch.triangular_solve(B, A).solution\n",
+      "should be replaced with\n",
+      "X = torch.linalg.solve_triangular(A, B). (Triggered internally at /Users/runner/work/pytorch/pytorch/pytorch/aten/src/ATen/native/BatchLinearAlgebra.cpp:2198.)\n",
+      "  outputs, _ = torch.triangular_solve(\n"
+     ]
+    }
+   ],
    "source": [
     "posterior = inferer.build_posterior()\n",
     "posterior_samples = posterior.sample((10_000,), x=x_o)\n",
+    "\n",
     "# Generate predictive samples by simulating from posterior samples.\n",
     "posterior_predictive_samples = simulator(posterior_samples)"
    ]
@@ -202,7 +227,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
        "<Figure size 500x500 with 4 Axes>"
       ]
@@ -250,6 +275,7 @@
    "outputs": [],
    "source": [
     "num_sbc_samples = 200  # choose a number of sbc runs, should be ~100s\n",
+    "\n",
     "# generate ground truth parameters and corresponding simulated observations for SBC.\n",
     "thetas = prior.sample((num_sbc_samples,))\n",
     "xs = simulator(thetas)"
@@ -268,7 +294,36 @@
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f048b19b2292495e9f32092da6160603",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Drawing 1000 posterior samples:   0%|          | 0/1000 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a57d6e8e3ffa4a0abc6f9d35c049e0b2",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Calculating ranks for 200 sbc samples.:   0%|          | 0/200 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# run SBC: for each inference we draw 1000 posterior samples.\n",
     "num_posterior_samples = 1_000\n",
@@ -328,7 +383,7 @@
      "text": [
       "kolmogorov-smirnov p-values \n",
       "\n",
-      "    check_stats['ks_pvals'] = [0.1201229 0.2126625]\n"
+      "    check_stats['ks_pvals'] = [0.1561183 0.9964161]\n"
      ]
     }
    ],
@@ -359,7 +414,7 @@
      "output_type": "stream",
      "text": [
       "c2st accuracies \n",
-      "check_stats['c2st_ranks'] = [0.475 0.53 ]\n"
+      "check_stats['c2st_ranks'] = [0.57  0.485]\n"
      ]
     }
    ],
@@ -392,7 +447,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "- c2st accuracies check_stats['c2st_dap'] = [0.45   0.4875]\n"
+      "- c2st accuracies check_stats['c2st_dap'] = [0.5125 0.4775]\n"
      ]
     }
    ],
@@ -421,7 +476,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
        "<Figure size 800x500 with 2 Axes>"
       ]
@@ -455,7 +510,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 800x500 with 1 Axes>"
       ]
@@ -489,11 +544,39 @@
    "execution_count": 16,
    "metadata": {},
    "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "80616613a5b24018bde222bb7f7aae8c",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Drawing 1000 posterior samples:   0%|          | 0/1000 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "b097376779704be7aa2fb54b532b3cd0",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Calculating ranks for 200 sbc samples.:   0%|          | 0/200 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{'ks_pvals': tensor([0.0468]), 'c2st_ranks': tensor([0.5025], dtype=torch.float64), 'c2st_dap': tensor([0.4500, 0.4850], dtype=torch.float64)}\n"
+      "{'ks_pvals': tensor([0.3516]), 'c2st_ranks': tensor([0.5000], dtype=torch.float64), 'c2st_dap': tensor([0.5100, 0.4750], dtype=torch.float64)}\n"
      ]
     }
    ],
@@ -556,11 +639,39 @@
    "execution_count": 18,
    "metadata": {},
    "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a2b8788b4cfa4de98ff03e54a54f2ede",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Drawing 1000 posterior samples:   0%|          | 0/1000 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0d9ced461cdc41678075a0448b309c39",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Calculating ranks for 200 sbc samples.:   0%|          | 0/200 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{'ks_pvals': tensor([1.7612e-37, 1.3333e-34]), 'c2st_ranks': tensor([0.5900, 0.5725], dtype=torch.float64), 'c2st_dap': tensor([0.4350, 0.4950], dtype=torch.float64)}\n"
+      "{'ks_pvals': tensor([2.3607e-38, 5.3656e-30]), 'c2st_ranks': tensor([0.6100, 0.6250], dtype=torch.float64), 'c2st_dap': tensor([0.4750, 0.5225], dtype=torch.float64)}\n"
      ]
     }
    ],
@@ -584,7 +695,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 800x500 with 2 Axes>"
       ]
@@ -625,16 +736,44 @@
    "execution_count": 21,
    "metadata": {},
    "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "db025cf99159435b80b6dfc0de55eae8",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Drawing 1000 posterior samples:   0%|          | 0/1000 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "c54ed60632d847039d899080413c2339",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Calculating ranks for 200 sbc samples.:   0%|          | 0/200 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{'ks_pvals': tensor([1.6989e-28, 1.6361e-21]), 'c2st_ranks': tensor([0.6200, 0.5475], dtype=torch.float64), 'c2st_dap': tensor([0.4525, 0.4475], dtype=torch.float64)}\n"
+      "{'ks_pvals': tensor([4.8637e-27, 3.7769e-30]), 'c2st_ranks': tensor([0.5400, 0.5950], dtype=torch.float64), 'c2st_dap': tensor([0.4800, 0.5150], dtype=torch.float64)}\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 800x500 with 2 Axes>"
       ]
@@ -692,16 +831,44 @@
    "execution_count": 23,
    "metadata": {},
    "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7ad02300bee7434ca05c813fd80a028e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Drawing 1000 posterior samples:   0%|          | 0/1000 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "c51477576a5941fba48fa2dfa57bffac",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Calculating ranks for 200 sbc samples.:   0%|          | 0/200 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{'ks_pvals': tensor([0.0006, 0.0003]), 'c2st_ranks': tensor([0.4800, 0.4900], dtype=torch.float64), 'c2st_dap': tensor([0.4375, 0.4850], dtype=torch.float64)}\n"
+      "{'ks_pvals': tensor([0.0005, 0.0174]), 'c2st_ranks': tensor([0.5350, 0.5400], dtype=torch.float64), 'c2st_dap': tensor([0.5050, 0.4675], dtype=torch.float64)}\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
        "<Figure size 800x500 with 2 Axes>"
       ]
@@ -721,7 +888,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The rank histograms now look more like a very wide gaussian distribution centered in the middle. The KS p-values again vanish unsurprisingly (we must reject the hypothesis that both distributions are from the same uniform PDF) and the c2st_ranks indicate that the rank histogram is not uniform too. As our posterior samples are distributed too broad now, we obtain more \"medium\" range ranks and hence produce the peak of ranks in the center of the histogram.\n"
+    "The rank histograms now look more like a very wide gaussian distribution centered in the middle. The KS p-values are again small (we must reject the hypothesis that both distributions are from the same uniform PDF) and the c2st_ranks indicate that the rank histogram is not uniform too. As our posterior samples are distributed too broad now, we obtain more \"medium\" range ranks and hence produce the peak of ranks in the center of the histogram.\n"
    ]
   },
   {
@@ -745,16 +912,44 @@
    "execution_count": 25,
    "metadata": {},
    "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8fec496527154b2eaf5718e6c19f3f53",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Drawing 1000 posterior samples:   0%|          | 0/1000 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "aff99a47aea0475bb5a3c7706eec882b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Calculating ranks for 200 sbc samples.:   0%|          | 0/200 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{'ks_pvals': tensor([2.8365e-01, 1.3149e-04]), 'c2st_ranks': tensor([0.4950, 0.5300], dtype=torch.float64), 'c2st_dap': tensor([0.4175, 0.4750], dtype=torch.float64)}\n"
+      "{'ks_pvals': tensor([0.0190, 0.0468]), 'c2st_ranks': tensor([0.5250, 0.5250], dtype=torch.float64), 'c2st_dap': tensor([0.4825, 0.5250], dtype=torch.float64)}\n"
      ]
     },
     {
      "data": {
-      "image/png": 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SqFGj8s1r0KCB9u3bd0nLlIqv/WKdDyjm3+c8Sir0p3UuvLDhwnPkSuJ8/a+//nq+kOrv7+/xvGrVqhWi5otRUM1/vhDE4XAUOO1i62nTpo3i4uL09ttv69Zbb9XOnTu1bNmyiy8aAFCuCIBecs011ygoKEiHDh0qcvRt7Nix8vPz04oVK3TbbbepV69e+stf/uLR5rvvvnOPImVmZmrPnj2KjY2VJLVt21a7du1SkyZNClx+y5Yt5XK5tG7dOiUkJOSbHxgYKOncFdEXU3tsbKzHuWHn6yzKFVdcIenceW/nRxIv5XfoYmNjtWnTJg0cOLDAdUdERCg6Olo//fST7r333oteflnUXJywsDBFR0dr48aNHtt848aNuu6660p9fX9W0OfgvKFDh+qFF17QL7/8ooSEBMXExJR5PQCAy0MA9JLq1atr3LhxevTRR+VyuXTDDTfo+PHj2rhxo8LCwjRo0CAtW7ZMb775pr799lu1bdtW48eP16BBg7R9+3aP34WbPn26ateurYiICE2aNEl16tRR3759JUkTJkxQp06dNHLkSA0dOlRVq1bVrl27tGrVKv3P//yPGjVqpEGDBulvf/ub5s2bp7i4OB08eFAZGRm655571LBhQzkcDn3++ee67bbbFBISUqLahw0bpjlz5mj8+PEaOnSotm7dqqSkpCK3SUhIiDp16qRZs2apcePGysjI0BNPPHHR2/aRRx7R4MGD1b59e3Xu3Fnvvvuudu7cqSuvvNLd5sknn9SoUaNUo0YN9ejRQ2fPntWWLVuUmZmpMWPGlHhdpVVzSYwfP15Tp07VVVddpdatW2vBggVKTk4u8Ork0lbQ5+D8z9b853/+p8aNG6fXX39db7/9dpnXAgC4fFwFXAJOp1M5OTlFPpxO50Uv96mnntLkyZM1c+ZMxcbGqkePHlq2bJkaN26sX3/9VUOGDNG0adPUtm1bSedCS0RERL7z22bNmqVHHnlE7dq105EjR/TZZ5+5R2xatWqldevWac+ePerSpYvatGmjKVOmKDo62v36+fPn669//auGDx+u5s2b64EHHnD/TEy9evX05JNPauLEiYqIiHBfPVxU7dK5w8sfffSRli5dqri4OL366quaMWNGsdvkzTfflNPpVLt27TR69Gg9/fTTF71d+/fvr8mTJ+uxxx5Tu3btdPDgQT388MMebYYOHao33nhDCxYsUMuWLdW1a1clJSW5678YpVFzSYwaNUpjxozR2LFj1bJlS61cuVKffvppgeeFlrbCPgeSVKNGDfXr10/VqlVz/+EBAKjYHObCk5cKceLECdWoUUPHjx9XWFhYmRSyvk+fIuff+MknZbJeScrOzlZaWpoaN26s4OBg9/SKficQ7s6AiuLmm29WixYt3D9ZVJjCvmtS+fQz3uTtfrQs+1AAFcPF9DMcAi5ClSpV1KxZswLPeyqIv78/dwGBVTIzM7V27VqtXbs2328tAgAqLgJgMapUqUKoAwrRpk0bZWZm6plnnlGzZs28XQ4AoIQIgJVYt27dVIIj+ECZKe72fgCAiomLQAAAACxDAAQAALAMAfACHE4FyhbfMQCoGAiA+uM2WWfOnPFyJYBvO/8d48IqAPAuLgLRuZ9vCQ8PV0ZGhiQpNDSUm9kDpcgYozNnzigjI0Ph4eH57rkMAChfBMB/i4yMlCR3CARQ+sLDw93fNQCA9xAA/83hcCgqKkp169ZVbm6ut8sBfE6VKlUY+QOACoIA+Cf+/v78JwUAAHwaF4EAAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYBkCIAAAgGUIgAAAAJYhAAIAAFiGAAgAAGAZAiAAAIBlCIAAAACWIQACAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYBkCIAAAgGUIgAAAAJYhAAIAAFiGAAgAAGAZAiAAAIBlCIAAAACWIQACAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYBkCIAAAgGUIgAAAAJYhAAIAAFiGAAgAAGAZAiAAAIBlCIAAAACWIQACAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYBkCIAAAgGUIgAAAAJYhAAIAAFiGAAgAAGAZAiAAAIBlCIAAAACWIQACAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYBkCIAAAgGUIgAAAAJYhAAIAAFiGAAgAAGCZAG8XIEk5OTly+hWdRbOzs8upGgCF8fPzU2BgoLfLAABcJq8HwJycHO3evVv/qlmzyHY7duwop4oAFCYoKEjNmzcnBAJAJef1AOhyuXT27Fn5GSM/YwptFxwcXI5VAfgzp9Ops2fPyuVyebsUAMBl8noAPM/PGPkX8R8LIw6A9zmdTm+XAAAoBVwEAgAAYBkCIAAAgGUIgAAAAJYhAAIAAFiGAAgAAGAZAiAAAIBlCIAAAACWIQACAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYBkCIAAAgGUIgAAAAJYhAAIAAFgmwNsFAKg4diYmFjovz89PjUaMKMdqAABlhRFAAAAAyxAAAQAALEMABAAAsAwBEAAAwDIEQAAAAMsQAAEAACxDAAQAALAMARAAAMAyBEAAAADLEAABAAAsQwAEAACwDAEQAADAMgRAAAAAyxAAAQAALEMABAAAsAwBEAAAwDIEQAAAAMsQAAEAACxDAAQAALAMARAAAMAyBEAAAADLEAABAAAsQwAEAACwDAEQAADAMgRAAAAAyxAAAQAALEMABAAAsAwBEAAAwDIEQAAAAMsQAAEAACwT4O0CAAAAfMX6Pn2KnH/jJ5+UUyVFYwQQAADAMgRAAAAAyxAAAQAALEMABAAAsAwBEAAAwDIEQAAAAMsQAAEAACxDAAQAALAMARAAAMAyBEAAAADLEAABAAAsQwAEAACwTIC3CwAAlI48Pz+ZQuZlZ2eXay2ArZx+RY+tZWdny8/PT4GBgeVUUcEIgADgA3JycvRrjRrKK+Q/nx07dpRzRYCd/lWzZpHzd+zYoaCgIDVv3tyrIZAACAA+wOVyKc/PT37GyM/kHwcMDg72QlWAfQJcrqLnBwTo7NmzchXTrqwRAAHAh/gZI/8C/mPx9uEmwBYFff8uFBAQIKfTWU7VFI6LQAAAACxDAAQAALAMARAAAMAyBEAAAADLEAABAAAsQwAEAACwDAEQAADAMgRAAAAAyxAAAQAALEMABAAAsAy3gkOltTMxsdB5LSZNKsdKKpaitotk97YBAJzDCCAAAIBlGAEEABSLkWXAtzACCAAAYBkCIAAAgGUIgAAAAJYhAAIAAFiGAAgAAGAZAiAAAIBlCIAAAACWIQACAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYBkCIAAAgGUIgAAAAJYhAAIAAFgmwNsFVAY7ExOLnN9i0qRyqgQlxT4DAKBwjAACAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYBkCIAAAgGUIgAAAAJYhAAIAAFiGAAgAAGAZAiAAAIBlCIAAAACWIQACAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYJkAbxdQWnYmJhY5v8WkSeVUCQAAQMXGCCAAAIBlCIAAAACWIQACAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYBkCIAAAgGUIgAAAAJYhAAIAAFiGAAgAAGAZAiAAAIBlCIAAAACWIQACAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWCbA2wVUBDsTE71dQqHKurYWkyZd8vqLe21ldrnbvSy3TUX+vAIAKgdGAAEAACxDAAQAALAMh4ABwAKcOlAxFbdffPlUm8vBdrt8jAACAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYBkCIAAAgGUIgAAAAJYhAAIAAFiGAAgAAGAZAiAAAIBlCIAAAACWIQACAABYJsDbBQAAgPK3MzGxyPktJk0qp0oqnqK2ja9sF0YAAQAALGPNCGBxf+mU5bJ95a+F8ubNfebLbH7vAIBzGAEEAACwDAEQAADAMgRAAAAAyxAAAQAALEMABAAAsAwBEAAAwDIEQAAAAMsQAAEAACxDAAQAALAMARAAAMAyBEAAAADLEAABAAAsE+DtAgAAld/OxMQi57eYNOmyXn85ils3Cna5+7Qs1325r+czwQggAACAdQiAAAAAliEAAgAAWIYACAAAYBkCIAAAgGW4CrgCKMur38oSV1kBAFA5MQIIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYBkCIAAAgGUIgAAAAJYhAAIAAFiGH4IGAOASVeQfxK/oNxmo6PX5OkYAAQAALEMABAAAsAwBEAAAwDIEQAAAAMsQAAEAACxDAAQAALAMARAAAMAyBEAAAADLEAABAAAsQwAEAACwTKW5FVxlvmVMZa4dl+Zy9rk3bx0FALADI4AAAACWIQACAABYptIcAgYAACgNnJrFCCAAAIB1CIAAAACWIQACAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYBkCIAAAgGUIgAAAAJYhAAIAAFiGAAgAAGAZAiAAAIBlCIAAAACWCfB2AQAAoGA7ExOLnN9i0qRyqgTnFbdPKgsCILzGV75EpY3tAgAoaxwCBgAAsAwBEAAAwDIEQAAAAMsQAAEAACxDAAQAALAMARAAAMAyBEAAAADLEAABAAAsQwAEAACwDAEQAADAMgRAAAAAyxAAAQAALEMABAAAsEyAtwsAAMCbdiYmersEoNwxAggAAGAZAiAAAIBlCIAAAACWIQACAABYhotALFeWJz9zYjUAABUTI4AAAACWIQACAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYBkCIAAAgGX4IWgAAMpIWf8gvjd/cJ8f+6/cGAEEAACwDAEQAADAMgRAAAAAyxAAAQAALEMABAAAsAwBEAAAwDIEQAAAAMsQAAEAACxTYX4I2uVwSH7kUaCicjkc3i4BAFBKvB4A/fz8FBQUJJfDwX8wQAUXFBQkP/5QA4BKz+sBMDAwUM2bN9dvmZneLgVAMZo3b67AwEBvlwEAuExeD4DSuRAY4HJ5uwwAxSD8AYBv4FgOAACAZSrECCAAoHRU1AvqcnJyipyfV4Y1e3PdwJ85nU5vlyCJAAgAPsHPz0/+Lpfy/Pwq5AV1Pz7/fNENyjCEZWdnFznfSQBEOXI6nRXigjoCIAD4gMDAQF1x/LiMtwupgFq2bFnk/JNchIhy1LJlS/n5+Xn9nGoCIAD4CH8upitQcHBwkfO5CBHlqbjPY3lh3BsAAMAyBEAAAADLEAABAAAsQwAEAACwDAEQAADAMgRAAAAAyxAAAQAALEMABAAAsAwBEAAAwDIEQAAAAMsQAAEAACxTonsBG3Pu9uInTpwos0JO5+aW2bIBlI6y7APOL/t8f+Nr6Ee9p7htznZDeaoo/WiJAuDJkyclSTExMZdRFoBKr0aNMl/FyZMnVaMc1lPe6Ee9yAc/T6jEKkg/6jAliIkul0uHDx9W9erV5XA4Sq1A6VxajYmJ0c8//6ywsLBSXTa8h/3qe8p6nxpjdPLkSUVHR8vPz/fOTinLflTiO+eL2Ke+qSz368X0oyUaAfTz81P9+vVLpbjChIWF8QH3QexX31OW+9QXR/7OK49+VOI754vYp76prPZrSftR3/szGwAAAEUiAAIAAFjG6wEwKChIU6dOVVBQkLdLQSliv/oe9mnFxv7xPexT31RR9muJLgIBAACA7/D6CCAAAADKFwEQAADAMgRAAAAAyxAAAQAALOP1APjyyy+rUaNGCg4OVseOHfX99997uyQUYtq0aXI4HB6P5s2bu+dnZ2drxIgRql27tqpVq6Z+/frpX//6l8cyDh06pF69eik0NFR169bV+PHj5XQ6y/utWGv9+vXq3bu3oqOj5XA4tHTpUo/5xhhNmTJFUVFRCgkJUUJCgvbu3evR5vfff9e9996rsLAwhYeHa8iQITp16pRHm+3bt6tLly4KDg5WTEyMnn322bJ+a1ajH6086Ed9gy/0pV4NgIsWLdKYMWM0depU/fOf/1RcXJy6d++ujIwMb5aFIrRo0ULp6enux4YNG9zzHn30UX322Wf64IMPtG7dOh0+fFh33XWXe35eXp569eqlnJwcffPNN3rrrbeUlJSkKVOmeOOtWOn06dOKi4vTyy+/XOD8Z599VvPmzdOrr76qTZs2qWrVqurevbuys7Pdbe69917t3LlTq1at0ueff67169frwQcfdM8/ceKEbr31VjVs2FBbt27Vc889p2nTpunvf/97mb8/G9GPVj70o5WfT/Slxouuu+46M2LECPfzvLw8Ex0dbWbOnOnFqlCYqVOnmri4uALnHTt2zFSpUsV88MEH7mkpKSlGkvn222+NMcYsX77c+Pn5mSNHjrjbzJ8/34SFhZmzZ8+Wae3IT5JZsmSJ+7nL5TKRkZHmueeec087duyYCQoKMgsXLjTGGLNr1y4jyWzevNndZsWKFcbhcJhffvnFGGPMK6+8YmrWrOmxTydMmGCaNWtWxu/ITvSjlQv9qO+prH2p10YAc3JytHXrViUkJLin+fn5KSEhQd9++623ykIx9u7dq+joaF155ZW69957dejQIUnS1q1blZub67E/mzdvrgYNGrj357fffquWLVsqIiLC3aZ79+46ceKEdu7cWb5vBPmkpaXpyJEjHvuwRo0a6tixo8c+DA8PV/v27d1tEhIS5Ofnp02bNrnb3HjjjQoMDHS36d69u1JTU5WZmVlO78YO9KOVE/2ob6ssfanXAuBvv/2mvLw8jw+xJEVEROjIkSNeqgpF6dixo5KSkrRy5UrNnz9faWlp6tKli06ePKkjR44oMDBQ4eHhHq+5cH8eOXKkwP19fh686/w+KOo7eeTIEdWtW9djfkBAgGrVqsV+9gL60cqHftT3VZa+NOCylwBr9OzZ0/3vVq1aqWPHjmrYsKEWL16skJAQL1YGAJUD/SgqCq+NANapU0f+/v75rm7617/+pcjISC9VhYsRHh6uq6++Wvv27VNkZKRycnJ07NgxjzYX7s/IyMgC9/f5efCu8/ugqO9kZGRkvosLnE6nfv/9d/azF9CPVn70o76nsvSlXguAgYGBateunb7++mv3NJfLpa+//lrx8fHeKgsX4dSpU9q/f7+ioqLUrl07ValSxWN/pqam6tChQ+79GR8frx07dnh86FetWqWwsDBdc8015V4/PDVu3FiRkZEe+/DEiRPatGmTxz48duyYtm7d6m6zevVquVwudezY0d1m/fr1ys3NdbdZtWqVmjVrppo1a5bTu7ED/WjlRz/qeypNX1oql5Jcovfff98EBQWZpKQks2vXLvPggw+a8PBwj6ubUHGMHTvWrF271qSlpZmNGzeahIQEU6dOHZORkWGMMWbYsGGmQYMGZvXq1WbLli0mPj7exMfHu1/vdDrNtddea2699VaTnJxsVq5caa644grz+OOPe+stWefkyZPmhx9+MD/88IORZObOnWt++OEHc/DgQWOMMbNmzTLh4eHmk08+Mdu3bzd9+vQxjRs3NllZWe5l9OjRw7Rp08Zs2rTJbNiwwTRt2tQMGDDAPf/YsWMmIiLC3HfffebHH38077//vgkNDTWvvfZaub9fG9CPVi70o77BF/pSrwZAY4x56aWXTIMGDUxgYKC57rrrzHfffeftklCI/v37m6ioKBMYGGjq1atn+vfvb/bt2+een5WVZYYPH25q1qxpQkNDzZ133mnS09M9lnHgwAHTs2dPExISYurUqWPGjh1rcnNzy/utWGvNmjVGUr7HoEGDjDHnfr5g8uTJJiIiwgQFBZmbb77ZpKameizj6NGjZsCAAaZatWomLCzM3H///ebkyZMebbZt22ZuuOEGExQUZOrVq2dmzZpVXm/RSvSjlQf9qG/whb7UYYwxlz+OCAAAgMrC67eCAwAAQPkiAAIAAFiGAAgAAGAZAiAAAIBlCIAAAACWIQACAABYhgAIAABgGQKghaZNm6bWrVt7u4yL1qhRI73wwguXtYykpCSFh4e7n1fWbQHAuypr30E/ivMIgJXA2rVr5XA48t0g/FKNGzfO4x6FNiurbbF+/Xr17t1b0dHRcjgcWrp0aamvA0DJ0Y+WnbLaFjNnzlSHDh1UvXp11a1bV3379lVqamqpr8dWBECLGGPkdDpVrVo11a5d+7KWdeHNqUujnbeUxrYoyOnTpxUXF6eXX3651JcNwHvoR/Mrq3503bp1GjFihL777jutWrVKubm5uvXWW3X69OlSX5eNCICloFu3bho5cqRGjhypGjVqqE6dOpo8ebIuvMteZmamBg4cqJo1ayo0NFQ9e/bU3r173fMPHjyo3r17q2bNmqpatapatGih5cuX68CBA7rpppskSTVr1pTD4dDgwYMlSS6XSzNnzlTjxo0VEhKiuLg4ffjhh+5lnv+Ld8WKFWrXrp2CgoK0YcOGfMP1LpdL06dPV/369RUUFKTWrVtr5cqV7vkHDhyQw+HQokWL1LVrVwUHB+vdd98tcFs4HA7Nnz9fd9xxh6pWrarExETl5eVpyJAh7jqbNWumF1980eN1gwcPVt++fTV79mxFRUWpdu3aGjFiRJEd3xtvvKHw8PAi//JMSkpSgwYNFBoaqjvvvFNHjx71mP/nbXG+jhkzZigiIkLh4eGaPn26nE6nxo8fr1q1aql+/fpasGBBoeuUpJ49e+rpp5/WnXfeWWQ7AOfQj/6BfvSclStXavDgwWrRooXi4uKUlJSkQ4cOaevWrUW+DiVUancVtljXrl1NtWrVzCOPPGJ2795t/vd//9eEhoaav//97+42d9xxh4mNjTXr1683ycnJpnv37qZJkyYmJyfHGGNMr169zC233GK2b99u9u/fbz777DOzbt0643Q6zUcffWQkmdTUVJOenm6OHTtmjDHm6aefNs2bNzcrV640+/fvNwsWLDBBQUFm7dq1xpg/blbdqlUr8+WXX5p9+/aZo0ePmqlTp5q4uDh3bXPnzjVhYWFm4cKFZvfu3eaxxx4zVapUMXv27DHGGJOWlmYkmUaNGpmPPvrI/PTTT+bw4cMFbgtJpm7duubNN980+/fvNwcPHjQ5OTlmypQpZvPmzeann35yb59Fixa5Xzdo0CATFhZmhg0bZlJSUsxnn32Wbxs2bNjQPP/888YYY5555hlTu3Zts2nTpkL3y3fffWf8/PzMM888Y1JTU82LL75owsPDTY0aNdxt/rwtBg0aZKpXr25GjBhhdu/ebf7xj38YSaZ79+4mMTHR7Nmzxzz11FOmSpUq5ueffy7iU+G5TZYsWVKitoCt6Ef/QD9asL179xpJZseOHSV+DQpHACwFXbt2NbGxscblcrmnTZgwwcTGxhpjjNmzZ4+RZDZu3Oie/9tvv5mQkBCzePFiY4wxLVu2NNOmTStw+ec7oMzMTPe07OxsExoaar755huPtkOGDDEDBgzweN3SpUs92vz5yxodHW0SExM92nTo0MEMHz7cGPNHx/XCCy8Uuy0kmdGjRxfbbsSIEaZfv37u54MGDTINGzY0TqfTPe3uu+82/fv3dz8/33E99thjJioqyvz4449FrmPAgAHmtttu85jWv3//Yjuuhg0bmry8PPe0Zs2amS5durifO51OU7VqVbNw4cJi36cxBECgJOhH/0A/ml9eXp7p1auX6dy5c4nao3gB5TjY6NM6deokh8Phfh4fH685c+YoLy9PKSkpCggIUMeOHd3za9eurWbNmiklJUWSNGrUKD388MP68ssvlZCQoH79+qlVq1aFrm/fvn06c+aMbrnlFo/pOTk5atOmjce09u3bF7qcEydO6PDhw+rcubPH9M6dO2vbtm0lXk5x7V5++WW9+eabOnTokLKyspSTk5PvqrEWLVrI39/f/TwqKko7duzwaDNnzhydPn1aW7Zs0ZVXXllkHSkpKfkOwcbHx3sclilIixYt5Of3x9kRERERuvbaa93P/f39Vbt2bWVkZBS5HAAXh3606HY296MjRozQjz/+qA0bNpSoPYrHOYAVxNChQ/XTTz/pvvvu044dO9S+fXu99NJLhbY/deqUJGnZsmVKTk52P3bt2uVx/ookVa1atVRqLOly/tzu/fff17hx4zRkyBB9+eWXSk5O1v3336+cnByPdlWqVPF47nA45HK5PKZ16dJFeXl5Wrx48SW8g5IpqI6S1AbAu+hHfbMfHTlypD7//HOtWbNG9evXL9U6bUYALCWbNm3yeP7dd9+padOm8vf3V2xsrJxOp0ebo0ePKjU1Vddcc417WkxMjIYNG6aPP/5YY8eO1euvvy5JCgwMlCTl5eW5215zzTUKCgrSoUOH1KRJE49HTExMiesOCwtTdHS0Nm7c6DF948aNHrVdjo0bN+r666/X8OHD1aZNGzVp0kT79++/pGVdd911WrFihWbMmKHZs2cX2TY2NrbA/QKgYqIfLZyN/agxRiNHjtSSJUu0evVqNW7cuFzWawsOAZeSQ4cOacyYMXrooYf0z3/+Uy+99JLmzJkjSWratKn69OmjBx54QK+99pqqV6+uiRMnql69eurTp48kafTo0erZs6euvvpqZWZmas2aNYqNjZUkNWzYUA6HQ59//rluu+02hYSEqHr16ho3bpweffRRuVwu3XDDDTp+/Lg2btyosLAwDRo0qMS1jx8/XlOnTtVVV12l1q1ba8GCBUpOTi70CrWL1bRpU7399tv64osv1LhxY73zzjvavHnzJX+Zr7/+ei1fvlw9e/ZUQECARo8eXWC7UaNGqXPnzpo9e7b69OmjL774otjDFqXl1KlT2rdvn/t5WlqakpOTVatWLTVo0KBcagAqG/rRwtnYj44YMULvvfeePvnkE1WvXl1HjhyRJNWoUUMhISHlUoMvYwSwlAwcOFBZWVm67rrrNGLECD3yyCN68MEH3fMXLFigdu3a6fbbb1d8fLyMMVq+fLl7SDwvL08jRoxQbGysevTooauvvlqvvPKKJKlevXp68sknNXHiREVERGjkyJGSpKeeekqTJ0/WzJkz3a9btmzZRXcIo0aN0pgxYzR27Fi1bNlSK1eu1KeffqqmTZuWyrZ56KGHdNddd6l///7q2LGjjh49quHDh1/WMm+44QYtW7ZMTzzxRKGHeDp16qTXX39dL774ouLi4vTll1/qiSeeuKz1ltSWLVvUpk0b93lEY8aMUZs2bTRlypRyWT9QGdGPFs7GfnT+/Pk6fvy4unXrpqioKPdj0aJF5bJ+X+cw5oIfWcIl6datm1q3bn3Zt9cBAFvRjwLlixFAAAAAyxAAAQAALMMhYAAAAMswAggAAGAZAiAAAIBlCIAAAACWIQACAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYJn/D2+uOCaw9obrAAAAAElFTkSuQmCC\n",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 800x500 with 2 Axes>"
       ]
@@ -774,7 +969,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The histogram of ranks now shoots above the allowed (greyed) area for a uniform distributed around the extrema. We made the posterior samples too thin, so we received more extreme counts of ranks. The KS p-values vanish again and the `c2st` metric of the ranks is also larger than `0.5` which underlines that our rank distribution is not uniformly distributed.\n"
+    "The histogram of ranks now shoots above the allowed (greyed) area for a uniform distributed around the extrema. We made the posterior samples too thin, so we received more extreme counts of ranks. The KS p-values are small again and the `c2st` metric of the ranks is also larger than `0.5` which underlines that our rank distribution is not uniformly distributed.\n"
    ]
   },
   {
@@ -835,7 +1030,22 @@
    "cell_type": "code",
    "execution_count": 27,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d1bbef1d247f4006aabb68e919079351",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Drawing 1000 posterior samples:   0%|          | 0/1000 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# the tarp method returns the ECP values for a given set of alpha coverage levels.\n",
     "ecp, alpha = run_tarp(\n",
@@ -856,7 +1066,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0.757999837398529 Should be close to 0\n",
+      "-0.7949994206428528 Should be close to 0\n",
       "0.999115261755522 Should be larger than 0.05\n"
      ]
     }
@@ -876,7 +1086,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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xvD9x4gT3798nffr00Y4NCQnh/N9zEt+/f59Ro0axadMmrl27RkREBCEhIeoZEZFE4+JFM4T88IP5PlcuM4Q0aWLbgakx2bZtG02bNiU0NJRMmTIl+tsy/6UwEktxmfffVvtay/3798maNSu7d+9+4rPHoWXgwIHs2LGDiRMnUqBAATw9PXnjjTcICwuzb7EiIlYWGgoTJ8Jnn5mTl7m6wsCB5m0aRyzxsmXLFpo3b05oaChNmzZl1apVuLm52b8QB1IYSWSKFClCREQER44csdymOXv2LHf/NSVg2bJlCQgIIFmyZOTJkyfG8+zdu5fOnTvTvHlzwAww1u7FERGxt59+gu7dzZlSAWrVglmzzAnJHGHz5s00b96csLAwmjdvzooVK5JcEAENYE10ChcuTP369Xn33Xc5ePAgR44coVu3btEmyfHx8aFy5co0a9aM7du3c+nSJfbt28ewYcM4fPgwAAULFmTdunUcP36cEydO0K5dO6Kiohz1a4mIvLQ//oB69cz/zZIFli2DnTsdF0Qe94iEhYXRokULVq5cmSSDCCiMJEqLFi0iW7Zs1KhRgxYtWvDOO++QKVMmy+dOTk5s3ryZ6tWr06VLFwoVKkSbNm3466+/yJw5MwCTJ08mbdq0vPbaazRu3Jh69epRtmxZR/1KIiIvJSoKunY1b8t4e5uP8LZta/+xIf+WO3du0qRJQ8uWLVmxYkWSnrjSyTCeNrt+4hQcHIyXlxdBQUFPjFR+9OgRFy9eJG/evElu8JCt6JqKSHwwY4Y5WDVlSvjtN3Owanxw8eJFcuTIkWCCyLO+Q1+GekZERCRRu3DBnMYd4IsvHBtENm7ciK+vr+V93rx5E0wQsSUNYBURkUQrKgq6dTMnNatZE955x3G1rF+/njfffBNXV1cOHDhAyZIlHVdMPKOeERERSbTmzQM/P0ieHObPB2cHfeutW7eON998k4iICJo3b07RokUdU0g8pTAiIiKJkr8/DBpkvh47FvLnd0wda9eutQSR9u3bs3TpUpIl042Jf1MYiUESG9NrU7qWIuIIhmHekrl3D157DRy1isXq1atp3bo1kZGRdOjQgSVLljwxa7cojETzeBDRw4cPHVxJ4vH4WmqAlojY0+LF5mq77u6wcCE44vt/z549tG3blsjISDp27MiiRYsURJ5C/UT/4uLiQpo0aSxryyRPnhwnRz6EnoAZhsHDhw+5ceMGadKk0X+AImI3//sf9Otnvh49GgoXdkwdlSpVolmzZqRMmZIFCxbo78FnUBj5jyxZsgDPXuxOYi9NmjSWayoiYmuGAe+9B0FBUKEC9O/vuFpcXV1Zvnw5zs7OCiLPoTDyH05OTmTNmpVMmTIRHh7u6HISNFdXV/0HKCJ2tXw5fP+9ufjdwoVg73Giy5YtY8+ePcycORNnZ2fdoo4lhZGncHFx0RepiEgCcv069O5tvh4xAooXt2/733zzDZ06dSIqKooqVarQvn17+xaQgGkAq4iIJAq9ekFgIJQuDR99ZN+2v/76azp27EhUVBTdu3enbdu29i0ggVMYERGRBG/NGvMnWTJYtMi8TWMvS5YsoVOnThiGwbvvvsucOXNwdtTsagmUrpaIiCRot25Bz57m68GDzZ4Re1m8eDFdunTBMAx69OjB7NmzFURegK6YiIgkaH36wI0bUKwYDB9uv3YvX77Mu+++i2EYvP/++8yaNUtB5AVpAKuIiCRYGzfCsmXmmjOLFpmTnNlLzpw5WbZsGT///DNTpkzRvFQvwclIYvN1BwcH4+XlRVBQEKlTp3Z0OSIi8oLu3DF7Q65dgw8/hM8/t0+7ISEheHp62qexeMZW36HqTxIRkQRpwAAziBQqBKNG2afN+fPnU7x4cfz9/e3TYBKhMCIiIgnO1q3mbRknJ3NyM3t0VMydO5fu3btz4cIFvv76a9s3mIQojIiISIISHGyuyAvwwQdQpYrt25wzZw7vvvsuAP369WPo0KG2bzQJURgREZEE5cMP4fJlyJcPxoyxfXuzZ8+mR48eAAwYMIBJkyZpsKqVKYyIiEiCEBZmPsb71Vfm+/nzIUUK27Y5c+ZMev49icnAgQP54osvFERsQI/2iohIvPfXX/Dmm3DokPn+00/B29u2bYaGhjJnzhwAPvzwQ8aPH68gYiMKIyIiEq9t2gQdOpiP8qZNC0uWQOPGtm/X3d0dX19fli1bRt++fRVEbEi3aUREJF6KiIAhQ6BRIzOIVKgAR4/aPoicPn3a8jpz5sz069dPQcTGFEZERCTe+d//oHZtGD/efN+7N/z8M+TJY9t2p0yZQvHixVm0aJFtG5JodJtGRETiFV9faNfOXG8mVSpzoOqbb9q+3UmTJjFw4EAALl68aPsGxUI9IyIiEi9ERZkDU+vUMYNIyZJw+LB9gsgXX3xhCSIjRozgk08+sX2jYqGeERERcbibN+Gtt2D7dvN9164wY4Z9Zlb9/PPPGTx4MAAjR45klL3mlhcLhREREXGovXuhdWu4etUMH19+CZ062aftcePGWWZTHTVqFCNHjrRPwxKNbtOIiIhDGAZMmgQ1aphBpHBhcx4RewURMFehBRg9erSCiAM5GYZhOLoIe7LV8sciIhJ7d+5Aly7w3Xfm+zZtYO5cc8CqPRmGgZ+fH7Vq1bJvwwmUrb5D1TMiIiJ2df48lCtnBhE3N5g9G5Yts18Q+fbbbwkJCQHAyclJQSQeUBgRERG7CQoyJy27eBHy5oV9+6BHD7DXnGKffPIJb731Fk2bNiUiIsI+jcpzaQCriIjYRWSkOX/ImTOQPbs5cDVrVvu1P2rUKMsjuz4+PiRLpq/A+EL/T4iIiF0MHQqbN4OHB2zYYL8gYhgGo0aNYvTo0QBMmDCBQYMG2adxiRWFERERsbmvv4YJE8zXixZB+fL2adcwDEaMGMFnn30GwMSJExkwYIB9GpdYUxgRERGbOngQunc3Xw8daj45Yy9jx461BJHJkyfTr18/+zUusaYBrCIiYjNXr0KzZhAaCk2bmtO921OdOnXw8vJiypQpCiLxmHpGRETEJkJCzCASEADFi5u3apzt/E/gihUr8scff5ApUyb7Nixxop4RERGxOsOAt982F7pLnx42brTPPCKGYTBy5Eh++eUXyzYFkfhPYURERKxu3DhYsQKSJYO1a805RWzNMAwGDRrE6NGjqVu3Lrdu3bJ9o2IVuk0jIiJW9d13MGyY+XrmTHPtGVszDIOBAwcyefJkAMaMGUOGDBls37BYhcN7RmbNmkWePHnw8PCgUqVKHDp06Jn7T506lcKFC+Pp6UnOnDnp168fjx49slO1IiLyLCdPwltvma979oR337V9m4Zh0L9/f0sQ+fLLL3n//fdt37BYjUPDyMqVK+nfvz8jR47k6NGjlCpVinr16nHjxo0Y91+2bBmDBw9m5MiRnDlzhgULFrBy5UrL8s8iIuI4t25BkyZw/z54e8OUKbZv0zAM+vXrx9SpUwH46quveO+992zfsFiVQ8PI5MmT6d69O126dKFo0aLMmTOH5MmTs3Dhwhj337dvH1WqVKFdu3bkyZOHunXr0rZt2+f2poiIiG2Fh8Mbb8ClS5A/P6xeDa6utm937ty5TJs2DYB58+bxzjvv2L5RsTqHhZGwsDCOHDmCj4/PP8U4O+Pj48P+/ftjPOa1117jyJEjlvBx4cIFNm/eTMOGDZ/aTmhoKMHBwdF+RETEuj74AH780Xxi5rvvzCdo7KFjx47UrVuX+fPn061bN/s0KlbnsAGst27dIjIyksyZM0fbnjlzZn7//fcYj2nXrh23bt2iatWqGIZBREQE77333jNv04wbN86yMJKIiFjf7NkwZ4658u6yZVCsmG3bMwwDACcnJzw9PdmyZQvO9p7ARKwqQf2/t3v3bsaOHcvs2bM5evQo69atY9OmTXz6jCn9hgwZQlBQkOXn8uXLdqxYRCRx27XL7BUB83HeRo1s215UVBTvv/8+Q4cOtYQSBZGEz2E9IxkyZMDFxYXr169H2379+nWyZMkS4zEff/wxHTp0sHTFlShRggcPHvDOO+8wbNiwGP9Auru74+7ubv1fQEQkiTt/Hlq1gshIaN8ePvzQtu09DiJfffUVTk5OtGrVirJly9q2UbELh8VJNzc3ypUrh6+vr2VbVFQUvr6+VK5cOcZjHj58+ETgcHFxAf7pthMREdsLDjafnAkMhAoVYN488zaNrURFRfHee+9ZgsjixYsVRBIRh0561r9/fzp16kT58uWpWLEiU6dO5cGDB3Tp0gUwByZlz56dcePGAdC4cWMmT55MmTJlqFSpEufOnePjjz+mcePGllAiIiK2FRgIjRvD6dOQLRts2ACenrZrLyoqinfffZf58+fj7OzMkiVLeOvxZCaSKDg0jLRu3ZqbN28yYsQIAgICKF26NFu3brUMavX394/WEzJ8+HCcnJwYPnw4V69eJWPGjDRu3JgxY8Y46lcQEUlSrlyB+vXht98gTRrzyZls2WzXXlRUFN27d2fhwoU4OzuzdOlS2rdvb7sGxSGcjCR2fyM4OBgvLy+CgoJInTq1o8sREUkwzp6FunXB398MINu2mavx2tJPP/1EjRo1cHZ25uuvv6Zdu3a2bVCeyVbfoVqbRkREnuuXX6BhQ3OW1UKFYPt2yJ3b9u1Wr16defPmkSJFCtq2bWv7BsUhFEZEROSZtm+HFi3gwQMoXx42b4aMGW3XXmRkJMHBwaRNmxZAk5klAXo4W0REnmr5cnPukAcPwMfHnFfE1kGkS5cuVKtW7anrlEniozAiIiIxmj4d2rUz151p3Ro2bTKne7eVyMhIOnfuzNdff83vv//O4cOHbdeYxCsKIyIiEo1hwPDh0KeP+b5XL3Oadzc327UZERFBx44d+eabb0iWLBkrV6585rpjkrhozIiIiFhERkKPHuYkZgCffgrDhtl2QrPHQWT58uWWINKiRQvbNSjxjsKIiIgA8OiReVtm/XpwdoYvv4R33rFtmxEREXTo0IEVK1aQLFkyVq9eTbNmzWzbqMQ7CiMiIkJQEDRtCj/+CO7u5m0Ze3RO3Lp1iwMHDuDq6srq1atp2rSp7RuVeEdhREQkiQsIMGdVPXECUqc2Z1WtWdM+bWfJkgU/Pz/OnDlDgwYN7NOoxDsawCoikoSdPw9VqphBJHNms2fE1kEkPDycffv2Wd7nyZNHQSSJUxgREUmijh0zg8iFC5AvH+zdC6VL27bN8PBw2rRpQ40aNVi/fr1tG5MEQ2FERCQJ8vODGjXg+nUzgOzdC/nz27bNsLAwWrduzbp163B2dsbd3d22DUqCoTAiIpLErFtnjhG5d88MJLt3Q5Ystm0zLCyMN998k/Xr1+Pu7s53332neUTEQmFERCQJmTsXWrWCsDDzaZmtW8HLy7ZthoWF0apVK7777jtLEKlfv75tG5UERWFERCQJMAxzArN334WoKHP+kFWrwMPDtu2GhYXxxhtvsHHjRjw8PNi4cSP16tWzbaOS4CiMiIgkclFR0Ls3jBhhvv/4Y5gzB1xcbN92smTJyJw5syWI1K1b1/aNSoLjZBiG4egi7Ck4OBgvLy+CgoJInTq1o8sREbGp0FDo1AlWrjSndJ8+3Vxrxp6ioqI4ffo0xYsXt2/DYnW2+g5Vz4iISCJ17x40amQGEVdXc1ZVewSRR48e8fnnnxMeHg6As7Ozgog8k2ZgFRFJhG7ehIYN4fBhSJHCXG+mTh3bt/vo0SOaN2/O1q1bOXPmDIsXL7Z9o5LgKYyIiCQyly5B3brw55+QIQNs3gwVKti+3ZCQEJo1a8b27dtJnjw5nTt3tn2jkigojIiIJCInT0K9enDtGuTODdu2QeHCtm83JCSEpk2bsmPHDpInT87mzZupUaOG7RuWREFjRkREEok9e6B6dTOIFC9uzqpqjyDy8OFDmjRpwo4dO0iRIgVbtmxREJE4URgREUkEvv/eHBNy96653sxPP0H27PZpu02bNuzcuZOUKVOydetWqlevbp+GJdFQGBERSeAWLYLmzeHRI/Ppme3bIW1a+7Xfp08fMmXKxNatW6latar9GpZEQ2NGREQSsEmTYOBA83XnzjBvHiSz89/stWvX5sKFC6RIkcK+DUuioZ4REZEE6tAhGDTIfP3hh7BwoX2CyIMHD2jdujVnzpyxbFMQkZehnhERkQQoMhJ69jTXnOnQAT7/3D7t3r9/n9dff52ffvqJEydOcOrUKZLZuytGEh39CRIRSYAWLDAnNEudGr74wj5t3r9/n4YNG/Lzzz+TOnVqlixZoiAiVqHbNCIiCczt2zBkiPl69GjInNn2bd67d48GDRrw888/4+XlxY4dO6hUqZLtG5YkQZFWRCSBGToUAgOhRAnzVo2tBQcH06BBA/bt22cJIhXsMaWrJBnqGRERSUAOHzafmAGYNcs+A1aHDh3Kvn37SJMmDTt37lQQEatTGBERSSCiov4ZtPrWW1Ctmn3aHTNmDPXr12fnzp2UL1/ePo1KkqLbNCIiCcTChebjvKlSwYQJtm0rLCwMNzc3ALy8vNiyZYttG5QkTT0jIiIJQGAgDB5svv7kE8ia1XZt3b17l2rVqjFp0iTbNSLyLwojIiIJwLBh5lM0xYpBr162a+fu3bvUrVuXQ4cOMW7cOG7dumW7xkT+FucwcuHCBVvUISIiT3HkCHz1lfl61ixwdbVNO3fu3KFOnTr88ssvpE+fHl9fXzJkyGCbxkT+Jc5hpECBAnh7e/PNN9/w6NEjW9QkIiJ/+/eg1XbtoEYN27TzOIgcPnyYDBkysGvXLkqVKmWbxkT+I85h5OjRo5QsWZL+/fuTJUsW3n33XQ4dOmSL2kREkrzFi+HgQUiZ0nYzrQYGBuLj48ORI0fImDEjfn5+lCxZ0jaNicQgzmGkdOnSTJs2jf/9738sXLiQa9euUbVqVYoXL87kyZO5efOmLeoUEUly7tyBjz4yX48aBdmy2aadH374gaNHj5IxY0Z27dpF8eLFbdOQyFM4GYZhvMwJQkNDmT17NkOGDLE8Cvbmm2/y+eefk9WWw71fUHBwMF5eXgQFBZE6dWpHlyMi8lQ9e8Ls2VC0KBw/bruxIgAzZ87E29ubYsWK2a4RSfBs9R36wmHk8OHDLFy4kBUrVpAiRQo6depE165duXLlCp988gnBwcHx8vaNwoiIJATHjkH58uaYkV27wNvbuue/desWrq6ueHl5WffEkqjZ6js0zpOeTZ48mUWLFnH27FkaNmzI0qVLadiwIc7O5h2fvHnzsnjxYvLkyWO1IkVEkpLHg1ajoqBNG+sHkZs3b1K7dm2SJ0/Otm3bFEjE4eIcRr788kvefvttOnfu/NTbMJkyZWLBggUvXZyISFK0dCns328OWp040brnfhxETp48SZYsWbhx44bCiDhcnG/TXLp0iVy5cll6Qh4zDIPLly+TK1cuqxZobbpNIyLx2d27UKgQ3LxpTvk+aJD1zn3jxg1q167NqVOnyJo1K35+fhQuXNh6DUiiZ6vv0Dg/TZM/f/4YZ+QLDAwkb968VilKRCSp+vhjM4gUKQJ9+ljvvNevX8fb25tTp06RLVs2du/erSAi8Uacw8jTOlLu37+Ph4fHSxckIpJUHT9uPj0DMHMm/L1O3Uu7fv06tWrV4vTp02TPnp3du3dTqFAh65xcxApiPWakf//+ADg5OTFixAiSJ09u+SwyMpKDBw9SunRpqxcoIpIUGIa55kxUFLz5JtSubb1z37lzh1u3bpEjRw78/PwoUKCA9U4uYgWxDiPHjh0DzJ6RkydPWpaWBnBzc6NUqVIMHDjQ+hWKiCQBX38Ne/dCihRg7cVyixQpgp+fH25ubgoiEi/FOoz4+fkB0KVLF6ZNm6bBnyIiVnL37j8DVT/+GHLkePlzXrt2jT///JPq1asDULRo0Zc/qYiNxHnMyKJFixRERESsaORIuHEDCheGfv1e/nz/+9//qFmzJvXr12f37t0vf0IRG4tVz0iLFi1YvHgxqVOnpkWLFs/cd926dVYpTEQkKVi1CmbNMl/PmPHyg1avXr2Kt7c3f/75J7ly5SJ37twvX6SIjcUqjHh5eeHk5GR5LSIiL2/WLOjd2xy82qUL1Knzcue7cuUK3t7enDt3jty5c+Pn56cpFyRBeOmF8hIaTXomIo5mGOYqvKNHm+/ffx+mTwcXlxc/5+XLl/H29ub8+fPkyZMHPz8/LcshVhdv1qYREZEXFxlprjvz1Vfm+1GjYMQI+Lvz+YUEBARQs2ZNLly4QN68efHz89PtGUlQYhVGypQpY7lN8zxHjx59qYJERBKrR4/grbdg7VozfMyeDe+99/LnTZ8+PWXLlsUwDHbv3h3vl+UQ+a9YhZFmzZrZuAwRkcQtOBiaNQM/P3OQ6rffwhtvWOfcrq6uLFu2jNu3b5MlSxbrnFTEjjRmRETExq5fhwYN4NgxcyXe776DWrVe7px//fUX8+fP55NPPnli4VIRW9GYERGRBOjCBahbF86fh4wZYcsWKFfu5c556dIlatasyV9//UWyZMkYOXKkdYoVcZBYhZF06dLxxx9/kCFDBtKmTfvM8SOBgYFWK05EJCE7cQLq14eAAMiTB7Zvh4IFX+6cFy9epGbNmvj7+1OwYEG6detmlVpFHClWYWTKlCmkSpUKgKlTp9qyHhGRROHHH6FJE3OsSMmSsHUrZM36cue8cOECNWvW5PLlyxQqVAg/Pz+yZctmnYJFHEhjRkRErGz9emjbFkJDoXp1c4xImjQvd87z58/j7e3N5cuXKVy4MH5+fmR92XQjEkfxasxIZGQk69ev58yZM4C5AFPTpk1JlkxDUEQkaZs/H959F6KizKdnli0DT8+XO2doaCh16tTh8uXLFClShF27dimISKIS5yHYv/32G4UKFaJTp06sX7+e9evX06lTJwoWLMipU6dsUaOISLxnGDB2LHTvbgaRrl1h9eqXDyIA7u7uTJo0iZIlS6pHRBKlON+mqVy5MhkzZmTJkiWkTZsWgDt37tC5c2du3rzJvn37bFKoteg2jYhYW1SUudru9Onm+yFDYMyYl5tVFcAwjGgPDERERKgHWhzKVt+hce4ZOX78OOPGjbMEEYC0adMyZswYjh07ZrXCREQSglu3oGHDf4LI1KlmD8nLBpGzZ89SrVo1/vrrL8s2BRFJrOIcRgoVKsT169ef2H7jxg0KFChglaJERBKCffugTBnYts28HbNsGfTp8/Ln/f333/H29mbv3r307t375U8oEs/FKowEBwdbfsaNG8cHH3zAmjVruHLlCleuXGHNmjX07duXzz//3Nb1iog4nGHA5MlQowZcuQKFCsHBg+YTNC/rcRC5du0aJUqUYMGCBS9/UpF4LlZjRpydnaPdt3x8yONt/34fGRlpizqtRmNGRORl3L0LXbrAhg3m+9atYd48+Hsqppdy5swZvL29uX79OiVLlsTX15cMGTK8/IlFrMShj/b6+flZrUERkYTqyBFo1QouXjQXu5syBXr0ePnxIQCnT5/G29ubGzduUKpUKXx9fUmfPv3Ln1gkAYhVGKlRo4at6xARibcMA776yhwPEhZmTu2+ejWUL2+9Nnr37s2NGzcoXbo0O3fuVBCRJOWFhmbfvXuXBQsWWCY9K1asGG+//TZeXl5WLU5ExNHu3zcnMVu2zHzfpAksXgz/eqDQKpYvX06/fv2YMWMG6dKls+7JReK5OM8zcvjwYerVq4enpycVK1YE4JdffiEkJITt27dTtmxZmxRqLRozIiKxdeqUeVvm99/BxQXGj4cBA6xzWwYgKChI/4iTBCXezDPSr18/mjRpwqVLl1i3bh3r1q3j4sWLNGrUiL59+1qtMBERR1q6FCpWNINI9uzmwncDB1oviJw4cYKCBQuycOFC65xQJAGLc8+Ip6cnx44do0iRItG2nz59mvLly/Pw4UOrFmht6hkRkWcJCYHeveHxE7V168I330DGjNZr48SJE9SuXZvbt29TsWJF9u7dqwnNJEGINz0jqVOnxt/f/4ntly9fJpU1nm0TEXGQP/+EV181g4iTE4weDZs3WzeIHD9+nFq1anH79m0qVKjAtm3bFEQkyYvzfwGtW7ema9euTJw4kddeew2AvXv3MmjQINpaY8YfEREH2LoV3nwT7t2DTJnMAau1a1u3jaNHj+Lj48OdO3eoVKkS27Zt05gREV4gjEycOBEnJyc6duxIREQEAK6urvTo0YPx48dbvUAREVvbvRuaN4dHj6B6dVi+HLJls24b/w4ir776Klu3blUQEflbnMJIZGQkBw4cYNSoUYwbN47z588DkD9/fpInT26TAkVEbOnQIWjc2AwiTZua84e4ulq/nU2bNnHnzh0qV67M1q1bNWZN5F/iPIDVw8ODM2fOkDdvXlvVZFMawCoij506Za4vExho3pL54Qfw8LBNW4Zh8NVXX9GuXTv93SMJVrwZwFq8eHEuXLhgtQJERBzh/HmoU8cMIq++aq41Y+0gcurUKUJCQgBz7a733ntPQUQkBnEOI5999hkDBw7khx9+4Nq1a9FW9A0ODrZFjSIiVnXlCvj4QEAAlChhPjGTMqV12zh48CBVqlShadOmlkAiIjGL8wDWhg0bAtCkSZMnVvJNCKv2ikjSdvOm2SNy6RIUKADbt1t/avcDBw5Qr149goODefTokf5eFHmOOIcRa6/gO2vWLL744gsCAgIoVaoUM2bMsEwzH5O7d+8ybNgw1q1bR2BgILlz52bq1KmWkCQi8jRBQVC/vjmras6csHMnZMli3Tb2799PvXr1uHfvHtWrV2fTpk2ktHa3i0giE6cwYhgG2bJlIywsjMKFC7/0RD0rV66kf//+zJkzh0qVKjF16lTq1avH2bNnyZQp0xP7h4WFUadOHTJlysSaNWvInj07f/31F2nSpHmpOkQk8Xv4EBo1gqNHzUnMduyA3Lmt28a+ffuoX78+9+7do0aNGmzatIkUKVJYtxGRxMiIpQsXLhjFixc3nJ2dDWdnZyNXrlzGL7/8EtvDY1SxYkWjZ8+elveRkZFGtmzZjHHjxsW4/5dffmnky5fPCAsLe+E2g4KCDMAICgp64XOISMISGmoY9esbBhiGl5dhHDtm/Tb27NljpEyZ0gCMmjVrGvfv37d+IyIOZqvv0FgPYB00aBARERF88803rFmzhhw5cvDuu+++cAgKCwvjyJEj+Pj4WLY5Ozvj4+PD/v37Yzxm48aNVK5cmZ49e5I5c2aKFy/O2LFjn3k/NjQ0VINsRZKwiAho396cYTV5cnOwaunS1m/Hzc0NZ2dnatWqpR4RkTiK9X2WPXv2sGbNGqpWrQrAq6++So4cOXjw4MEL/Ud369YtIiMjyZw5c7TtmTNn5vfff4/xmAsXLrBr1y7at2/P5s2bOXfuHO+//z7h4eGMHDkyxmPGjRvHJ598Euf6RCThi4qCd96BNWvAzc18fPfvVSysrkKFCuzZs0eTQIq8gFj3jNy4cYOCBQta3mfNmhVPT09u3Lhhk8JiEhUVRaZMmZg7dy7lypWjdevWDBs2jDlz5jz1mCFDhhAUFGT5uXz5st3qFRHHMQzo3x8WLQIXF1ixwnyKxpp++uknDh06ZHlfokQJBRGRFxDrnhEnJyfu37+Pp6enZZuzszP37t2LdusjthP6ZMiQARcXF65fvx5t+/Xr18nylOHtWbNmxdXVFRcXF8u2V155hYCAAMLCwnBzc3viGHd3d9zd3WNVk4gkHp98AtOmma8XLjTXnrGmH3/8kYYNG+Lq6sqePXsoXry4dRsQSUJi3TNiGAaFChUibdq0lp/79+9TpkwZ0qZNS5o0aUgbh4f13dzcKFeuHL6+vpZtUVFR+Pr6Urly5RiPqVKlCufOnSMqKsqy7Y8//iBr1qwxBhERSZqmTDHDCMCMGdCxo3XPv3v3bho2bMjDhw959dVXyZ8/v3UbEEliYt0zYu35RQD69+9Pp06dKF++PBUrVmTq1Kk8ePCALl26ANCxY0eyZ8/OuHHjAOjRowczZ86kT58+9O7dmz///JOxY8fywQcfWL02EUmYFiwwb88AfPYZ9Opl3fPv2rWLRo0aERISQv369Vm/fj0etlrQRiSJiHUYqVGjhtUbb926NTdv3mTEiBEEBARQunRptm7dahnU6u/vj7PzP503OXPmZNu2bfTr14+SJUuSPXt2+vTpw0cffWT12kQk4VmzBrp3N18PGgRDh1r3/L6+vjRu3JiQkBAaNGjAunXrFERErCDOq/YmdFq1VyRxCgiAwoUhOBjefRe+/BL+tWLFS/vll1+oXr06jx49omHDhqxbt07j0STJsdV36MtNoSoiEk989JEZRMqXh1mzrBtEwFyxvFq1ari5ubF27VoFERErUhgRkQRvzx5YutQMILNmmY/yWpunpyffffcdzs7OCiIiVhbrp2lEROKjiAjo2dN83bUrPGOdzTjbunUrH3/8MY/vZnt6eiqIiNjAC/eMnDt3jvPnz1O9enU8PT0xDAMna/eLiog8x5dfwq+/Qtq08PeDd1axZcsWmjVrRlhYGEWKFKF9+/bWO7mIRBPnnpHbt2/j4+NDoUKFaNiwIdeuXQOga9euDBgwwOoFiog8zfXr8PHH5uuxYyFDBuucd/PmzZYg0qJFC958803rnFhEYhTnMNKvXz+SJUuGv79/tGmPW7duzdatW61anIjIswweDEFBULbsP4/0vqwffviB5s2bExYWRsuWLVmxYgWurq7WObmIxCjOt2m2b9/Otm3byJEjR7TtBQsW5K+//rJaYSIiz7J/PyxebL621qDV77//npYtWxIeHs4bb7zBsmXLFERE7CDOPSMPHjyIcSGowMBADewSEbuIjIT33zdfv/02vPrqy5/z6tWrtGrVivDwcFq1aqUgImJHcQ4j1apVY+nSpZb3Tk5OREVFMWHCBLy9va1anIhITObMgePHIU0aGD/eOufMnj07s2fPpk2bNgoiInYW5xlYT506Re3atSlbtiy7du2iSZMm/PbbbwQGBrJ37954v2CUZmAVSdhu3oRCheDuXfP2zOMekhcVGRkZbSVwPRko8nS2+g6Nc89I8eLF+eOPP6hatSpNmzblwYMHtGjRgmPHjsX7ICIiCd/gwWYQKVPGnPb9Zaxdu5by5ctz48YNyzYFERH709o0IpJgHDgAlSubr/ft++f1i1izZg1t2rQhMjKSYcOG8dlnn1mnSJFELN6sTfPrr7/GuN3JyQkPDw9y5cqlgawiYnWRkf/MtNq588sFkdWrV9O2bVsiIyN56623+OSTT6xSo4i8mDiHkdKlS1u6MR93qvy7W9PV1ZXWrVvz1VdfaWltEbGaefPg6FHw8oLPP3/x86xcuZL27dsTGRlJhw4dWLRoUbQxIyJif3EeM7J+/XoKFizI3LlzOXHiBCdOnGDu3LkULlyYZcuWsWDBAnbt2sXw4cNtUa+IJEG3bsHQoebrzz6DTJle7DwrVqywBJFOnTopiIjEE3HuGRkzZgzTpk2jXr16lm0lSpQgR44cfPzxxxw6dIgUKVIwYMAAJk6caNViRSRpGjIE7tyBUqXgvfde7ByhoaF8/PHHREZG0qVLF+bNm6cgIhJPxLln5OTJk+TOnfuJ7blz5+bkyZOAeSvn8Zo1IiIv49AhWLDAfD1rFiR7weU93d3d2blzJ0OHDmX+/PkKIiLxSJzDSJEiRRg/fjxhYWGWbeHh4YwfP54iRYoA5kyGmTNntl6VIpIkPR60ahjQsSNUqRL3c1y9etXyOnfu3IwZMwZn5zj/1SciNhTnf2PMmjWLJk2akCNHDkqWLAmYvSWRkZH88MMPAFy4cIH3X3YmIhFJ8hYsgMOHIXVqmDAh7sd//fXXdO/eneXLl9O8eXPrFygiVvFC84zcu3ePb7/9lj/++AOAwoUL065dO1KlSmX1Aq1N84yIJAy3b5szrQYGwrRp8MEHcTt+yZIldOnSBcMw6NmzJzNnzrRNoSJJSLyZZwQgVapUvPeio8hERGJh6FAziJQsGfcp3xcvXszbb7+NYRi89957TJ8+3TZFiohVvOBQMDh9+jT+/v7Rxo4ANGnS5KWLEpGk7fBhc14RgJkz4zZodeHChXTr1g3DMOjRowezZs3SFO8i8Vycw8iFCxdo3rw5J0+exMnJ6YmJzyIjI61boYgkKVFR/wxafestqFYt9scuWLCA7t27W27NzJgxQ0FEJAGI85DyPn36kDdvXm7cuEHy5Mn57bff+Omnnyhfvjy7d++2QYkikpQsXGg+zpsqVdwHrR4+fBjDMOjdu7eCiEgCEueekf3797Nr1y4yZMiAs7Mzzs7OVK1alXHjxvHBBx9w7NgxW9QpIknApUvw0Ufm608+gaxZ43b8rFmzqFmzJm+++aaCiEgCEueekcjISMtTMxkyZOB///sfYD6/f/bsWetWJyJJxr170KSJOWi1fHno1St2x23bto3w8HAAnJ2dad26tYKISAIT5zBSvHhxTpw4AUClSpWYMGECe/fuZfTo0eTLl8/qBYpI4hcVZU5qdvIkZMkC69eDq+vzj5szZw7169enXbt2RERE2L5QEbGJON+mGT58OA8ePABg9OjRNGrUiGrVqpE+fXpWrlxp9QJFJPEbORI2bAA3NzOI5Mjx/GNmz55Nz549AbNnVtO7iyRcLzTp2X8FBgaSNm3aBNE1qknPROKXlSuhTRvz9ZIlZg/J88yaNYtef9/HGThwIBMmTEgQf/+IJHS2+g6N022a8PBwkiVLxqlTp6JtT5cunf4iEJE4O3IEunQxXw8cGLsgMmPGDEsQ+fDDDxVERBKBOIURV1dXcuXKpblEROSlBQRAs2YQEgINGsD48c8/ZtasWXzw97zwgwcPZvz48QoiIolAnAewDhs2jKFDhxIYGGiLekQkCXj0CJo3hytXoEgRWL4cYjPko0iRInh4eDBkyBDGjh2rICKSSMR5zEiZMmU4d+4c4eHh5M6dmxQpUkT7/OjRo1Yt0No0ZkTEsQzDvDWzZAmkSWNOcFawYOyPP3fuHPnz51cQEXGAeLNQXrNmzazWuIgkPZMnm0HExQVWrXp+EJk9ezY1a9akaNGiABQoUMAOVYqIPVnlaZqERD0jIo6zZQs0amTOKzJtGvw9/OOpvvjiCz788EMyZ87MyZMnyZgxo30KFZEYxYunaR67e/cu8+fPZ8iQIZaxI0ePHuXq1atWK0xEEpfffzcf4Y2Kgm7doHfvZ+//+eef8+GHHwLw3nvvKYiIJGJxvk3z66+/4uPjg5eXF5cuXaJ79+6kS5eOdevW4e/vz9KlS21Rp4gkYHfumFO9BwdD1aowaxY8a8jH+PHjGTJkCACjRo1i5MiRdqpURBwhzj0j/fv3p3Pnzvz55594eHhYtjds2JCffvrJqsWJSMIXEQFvvgl//gm5csHateZMq08zduxYSxAZPXq0gohIEhDnnpFffvmFr7766ont2bNnJyAgwCpFiUjiMXAg7NwJyZPDxo2QKdPT9128eDHDhg0D4LPPPrO8FpHELc49I+7u7gQHBz+x/Y8//tA9XRGJZsECc6AqwNdfQ6lSz96/efPmVKpUiTFjxiiIiCQhce4ZadKkCaNHj2bVqlUAODk54e/vz0cffUTLli2tXqCIJEx79kCPHubrTz6BFi2ef4yXlxc//fQTbs+6jyMiiU6ce0YmTZrE/fv3yZQpEyEhIdSoUYMCBQqQKlUqxowZY4saRSSB+esvM3yEh0OrVvDxxzHvZxgGo0aN4osvvrBsUxARSXri3DPi5eXFjh072LNnD7/++iv379+nbNmy+Pj42KI+EUlgHj6Epk3h5k0oXRoWLYr5yRnDMBg5ciSffvopAN7e3pQvX96+xYpIvBDnMHL58mVy5sxJ1apVqVq1qi1qEpEErE8fOHHCHKj63XfwnxUjADOIjBgxgs8++wyAiRMnKoiIJGFxvk2TJ08eatSowbx587hz544tahKRBGrlSpg/3+wJWb7cfJT3vwzDYPjw4ZYgMnnyZAYMGGDnSkUkPolzGDl8+DAVK1Zk9OjRZM2alWbNmrFmzRpCQ0NtUZ+IJBAXL8I775ivhw6FWrWe3McwDIYNG8bYsWMBmDJlCv369bNjlSISH73w2jSGYbB7926WLVvG2rVriYqKokWLFixcuNDaNVqV1qYRsb7wcKhWDQ4ehNdegx9/hGQx3AT++eefqV69OgDTpk3jg+ctTiMi8YqtvkOtslDe0aNH6dq1K7/++iuRkZHWqMtmFEZErG/wYPj8c0iTBo4fh9y5n77vF198gYeHB72ftziNiMQ7tvoOjfMA1seuXLnCsmXLWLZsGadOnaJy5crMmjXLaoWJSMKwfbsZRMAcL/LfIGIYBiEhISRPnhyAQYMG2blCEYnv4hxGvvrqK5YtW8bevXspUqQI7du357vvviP3s/4pJCKJ0vXr0LGj+fq99+C/8x4ahsHAgQPZu3cv27Ztw8vLy/5Fiki8F+cw8tlnn9G2bVumT59OqefN7SwiiVZUlBlErl+H4sVh8uTonxuGwYABA5gyZQoAO3fu1CzNIhKjOIcRf39/nJ619reIJAmTJpm3aDw9YcUK838fMwyDfv36Me3vhWm++uorBREReao4hxEnJyfu3r3LggULOHPmDABFixala9eu6oIVSSIOHTIf3wWYOhWKFfvnM8Mw6Nu3L9OnTwdg7ty5dO/e3f5FikiC8ULzjOTPn58pU6YQGBhIYGAgU6ZMIX/+/Bw9etQWNYpIPBIUBG3bQkSEue7Mv3OGYRh88MEHliAyb948BRERea44P9pbrVo1ChQowLx580j290QCERERdOvWjQsXLvDTTz/ZpFBr0aO9Ii/OMKBdO/O2TO7c5mO8adL88/n//vc/ypYty40bN5g3bx5du3Z1VKkiYgPxZp4RT09Pjh07RpEiRaJtP336NOXLl+fhw4dWK84WFEZEXtzChdC1K7i4wM8/Q+XKT+5z+vRpjh07Rvv27e1foIjYlK2+Q+N8myZ16tT4+/s/sf3y5cukSpXKKkWJSPxz5gw8nqfs00//CSJRUVGcPn3asl/RokUVREQkTuIcRlq3bk3Xrl1ZuXIlly9f5vLly6xYsYJu3brRtm1bW9QoIg726BG0aQMPH0Lt2vDRR+b2qKgoevToQbly5fD19XVskSKSYMX5aZqJEyfi5OREx44diYiIAMDV1ZUePXowfvx4qxcoIo43cCD8+itkzAhffw3OzmYQeffdd5k/fz7Ozs4EBAQ4ukwRSaBeeG2ahw8fcv78eQDy589vmeo5vtOYEZG42bABmjc3X2/ZAvXrm0HknXfeYcGCBTg7O7N06VLdmhFJAhw+ZiQyMpJff/2VkJAQAJInT06JEiUoUaIETk5O/Prrr0RFRVmtMBFxvMuX4e23zdcDBvwTRLp162YJIl9//bWCiIi8lFiHka+//pq3334bNze3Jz5zdXXl7bffZtmyZVYtTkQcJyIC2reHO3egfHkYO9b8R0nXrl1ZtGgRzs7OfPvtt7Rr187RpYpIAhfrMLJgwQIGDhyIi4vLE58lS5aMDz/8kLlz51q1OBFxnE8/NR/fTZUKli8HNzdzUrMHDx7g4uLCsmXLaNOmjaPLFJFEINYDWM+ePcurr7761M8rVKhgmR5eRBKu69dh+nR4PB59zhwoUMB8nSxZMr799lsOHjxI1apVHVekiCQqse4ZefDgAcHBwU/9/N69e/F+wjMRebrffzends+d27wlExUF3bpB69aRLFy40DImzNXVVUFERKwq1mGkYMGC7Nu376mf79mzh4IFC1qlKBGxD8Mwb8U0aQKvvALz50NoKLz6KqxdC7NmRdCxY0e6du1K78cznomIWFmsw0i7du0YPnw4v/766xOfnThxghEjRmggm0gCERkJa9aYs6hWrw7ffw9OTtC0KezZA/v3Q5MmEXTu3JFly5aRLFkyateu7eiyRSSRivU8I+Hh4dStW5c9e/bg4+NjWZvm999/Z+fOnVSpUoUdO3bg6upq04JfluYZkaTs4UNYvBgmT4a/pwnC3R06dYL+/aFwYXNbREQEHTp0YMWKFSRLlozVq1fTrFkzR5UtIvFEvFgoLzw8nClTprBs2TL+/PNPDMOgUKFCtGvXjr59+8b42G98ozAiSdHNmzBzJsyaBbdvm9vSpYP334devSBz5n/2jYiIoH379qxatQpXV1dWr15N06ZNHVO4iMQr8SKMJAYKI5KU/PknTJoES5aY68sA5M1r9oJ06QIpUjx5zFtvvcW3336Lq6sra9asoUmTJvYtWkTiLYfPwCoiCcuUKeZtl6++MoNI+fKwciX88YfZGxJTEAFo2bIlKVKkYN26dQoiImIX6hkRSYT27IEaNczHcxs2hA8/NAeqOjnF7vibN2+SMWNG2xYpIgmOekZEJFYCA6FdOzOIdOgAmzaZweRpQSQsLIzevXtz6dIlyzYFERGxJ4URkUTEMMyJyi5fNmdNnTXr2fuHhYXRunVrZs6cSYMGDYiIiLBPoSIi/xLr6eBFJP6bMwfWrwdXV1ixwlxX5mnCwsJo1aoVGzduxN3dnalTp5Ismf5KEBH7i9XfPP3794/1CSdPnvzCxYjIi/v1V+jXz3w9YQKUK/f0fUNDQ2nVqhXff/89Hh4efPfdd9StW9c+hYqI/EeswsixY8eivT969CgREREU/nuGpD/++AMXFxfKPetvPxGxmQcPoE0bcyr311+HPn2evm9oaCgtW7Zk06ZNeHh4sHHjRurUqWO/YkVE/iNWYcTPz8/yevLkyaRKlYolS5aQNm1aAO7cuUOXLl2oVq2abaoUkWfq2xfOnIGsWWHRomc/NfPRRx9Zgsj333+Pj4+P3eoUEYlJnB/tzZ49O9u3b6dYsWLRtp86dYq6devyv//9z6oFWpse7ZXEZuVKs1fEyQl8fcHb+9n737hxg0aNGjFu3DitNyMicWKr79A4j1YLDg7m5s2bT2y/efMm9+7ds0pRIhI7Fy/CO++Yr4cNe3oQMQwDp7+7SzJlysSBAwdwdtbDdCISP8T5b6PmzZvTpUsX1q1bx5UrV7hy5Qpr166la9eutGjRwhY1ikgMwsOhbVsIDoYqVWDkyJj3CwkJoWHDhixcuNCyTUFEROKTOP+NNGfOHBo0aEC7du3InTs3uXPnpl27dtSvX5/Zs2e/UBGzZs0iT548eHh4UKlSJQ4dOhSr41asWIGTk5NWE5Uk6eOP4eBBSJMGvv0WYnoqNyQkhKZNm7J161b69u0bY6+miIijvfB08A8ePOD832uQ58+fnxRPW+jiOVauXEnHjh2ZM2cOlSpVYurUqaxevZqzZ8+SKVOmpx536dIlqlatSr58+UiXLh0bNmyIVXsaMyKJwfbtUK+e+XrtWoipU/Lhw4c0bdqUnTt3kiJFCjZv3kz16tXtW6iIJCrxbjr4a9euce3aNQoWLEiKFCl40SVuJk+eTPfu3enSpQtFixZlzpw5JE+ePFqX8n9FRkbSvn17PvnkE/Lly/eiv4JIgnT9OnTsaL7u0ePpQaRJkybs3LmTlClTsnXrVgUREYm34hxGbt++Te3atSlUqBANGzbk2rVrAHTt2pUBAwbE6VxhYWEcOXIk2qOFzs7O+Pj4sH///qceN3r0aDJlykTXrl2f20ZoaCjBwcHRfkQSqqgoM4hcvw4lSsCkSU/u8+DBAxo1aoSvr68liFStWtX+xYqIxFKcw0i/fv1wdXXF39+f5MmTW7a3bt2arVu3xulct27dIjIyksyZM0fbnjlzZgICAmI8Zs+ePSxYsIB58+bFqo1x48bh5eVl+cmZM2ecahSJTyZNMm/ReHqa0717ej65z/Lly/Hz8yNVqlRs27aNKlWq2L9QEZE4iPOjvdu3b2fbtm3kyJEj2vaCBQvy119/Wa2wmNy7d48OHTowb948MmTIEKtjhgwZEm06++DgYAUSSZAOHoShQ83X06ZB0aIx79e1a1euXr1K3bp1qVy5sv0KFBF5QXEOIw8ePIjWI/JYYGAg7u7ucTpXhgwZcHFx4fr169G2X79+nSxZsjyx//nz57l06RKNGze2bIuKigIgWbJknD17lvz580c7xt3dPc51icQ3QUHmY7wREfDmm+bKvP92//59XFxc8PT0xMnJiZFPe85XRCQeivNtmmrVqrF06VLLeycnJ6KiopgwYQLez5v68T/c3NwoV64cvr6+lm1RUVH4+vrG+C+6IkWKcPLkSY4fP275adKkCd7e3hw/flw9HpIoGQa89545wVmePDB3bvTp3u/du0eDBg1o0qQJISEhDqtTRORFxblnZMKECdSuXZvDhw8TFhbGhx9+yG+//UZgYCB79+6NcwH9+/enU6dOlC9fnooVKzJ16lQePHhAly5dAOjYsSPZs2dn3LhxeHh4ULx48WjHp0mTBuCJ7SKJxaJF5vgQFxdYvhy8vP757HEQ2bt3L15eXpw/f17/LYhIghPnMFK8eHH++OMPZs6cSapUqbh//z4tWrSgZ8+eZM2aNc4FtG7dmps3bzJixAgCAgIoXbo0W7dutQxq9ff312yRkmSdOQO9epmvP/sMXn31n8+Cg4Np0KAB+/btw8vLix07diiIiEiCFOdJz/z9/cmZM6dlnYv/fpYrVy6rFWcLmvRMEopLl6BOHTh3Dnx8YNs2eJzLg4ODqV+/Pvv37ydNmjTs2LGD8uXLO7ReEUn84s2kZ3nz5o1xSunbt2+TN29eqxQlktSdPAmvvWYGkdy54euv/wkiQUFB1KtXj/3795M2bVp8fX0VREQkQYtzGPn36p//dv/+fTw8PKxSlEhStmcPVK8O165B8eKwbx/8++GyS5cucebMGdKmTcvOnTspW7as44oVEbGCWI8ZeTxXh5OTEx9//HG0x3sjIyM5ePAgpUuXtnqBIknJxo3QujU8egRVq5rv06aNvk+pUqXYvn07rq6ulClTxjGFiohYUazDyLFjxwCzZ+TkyZO4ublZPnNzc6NUqVIMHDjQ+hWKJBGLFkH37hAZCY0bw8qV/8ywevfuXS5evGgJHxUrVnRgpSIi1hXrMOLn5wdAly5dmDZtmgZ/iliJYcCECTB4sPm+c2eYNw+S/f1f5507d6hbty5//vknO3bsoEKFCg6rVUTEFuI8ZmTq1KlEREQ8sT0wMFCL0InEUVQUDBjwTxD58ENYuDB6EKlTpw6HDx/G1dVVswmLSKIU5zDSpk0bVqxY8cT2VatW0aZNG6sUJZIUhIdDp04wZYr5ftIk+Pzzf2ZXDQwMxMfHhyNHjpAhQwZ27dpFyZIlHVewiIiNxDmMHDx4MMZp32vWrMnBgwetUpRIYvfgATRpAt98Y/aCLF0K/1rPkdu3b1O7dm2OHj1KxowZ8fPzo0SJEo4rWETEhuI8A2toaGiMt2nCw8O1LoZILNy+Da+/bq7C6+kJa9dCgwb/fP64R+T48eNkypSJXbt2UaxYMccVLCJiY3HuGalYsSJz5859YvucOXMoV66cVYoSSawuX4Zq1cwgkjYt+PpGDyIAnp6eZMyYkcyZM+Pn56cgIiKJXpx7Rj777DN8fHw4ceIEtWvXBsDX15dffvmF7du3W71AkcTizBmoWxeuXIEcOczp3YsWfXI/T09PvvvuO65evUqBAgXsX6iIiJ3FuWekSpUq7N+/nxw5crBq1Sq+//57ChQowK+//kq1atVsUaNIgnfggDmJ2ZUrUKSIOavqv4PIzZs3mTZtGo+XivL09FQQEZEkI849IwClS5dm2bJl1q5FJFHauhVatoSHD6FSJdi0CdKn/+fzGzduULt2bU6dOsXDhw8ZMmSI44oVEXGAOPeMAJw/f57hw4fTrl07bty4AcCWLVv47bffrFqcSEJ3/Dg0a2YGkXr1zDEi/w0itWrV4tSpU2TLlo2WLVs6qlQREYeJcxj58ccfKVGiBAcPHmTt2rXcv38fgBMnTjBy5EirFyiSUN2/D23aQGgoNGxorjOTIsU/n1+/fh1vb29+++03smXLxu7duylUqJDjChYRcZA4h5HBgwfz2WefsWPHjmjr09SqVYsDBw5YtTiRhKx3bzh7FrJnN+cR+dd/LgQEBODt7c3p06fJnj07u3fvpmDBgo4rVkTEgeIcRk6ePEnz5s2f2J4pUyZu3bpllaJEErply2DxYnB2hm+/jX5rJiwsjNq1a3PmzBly5MihICIiSV6cw0iaNGm4du3aE9uPHTtG9uzZrVKUSEJ2/jy89575+uOPoUaN6J+7ubkxcOBAcufOze7du/XUjIgkeS+0Ns1HH31EQEAATk5OREVFsXfvXgYOHEjHjh1tUaNIghEWZo4TuXfPnNxs+PCY9+vSpQunT58mf/789i1QRCQeinMYGTt2LEWKFCFnzpzcv3+fokWLUr16dV577TWGP+1vXpEkYuhQOHzYnF3122//WX336tWrNGvWzPL0GUDy5MkdVKWISPziZDyeZSmO/P39OXXqFPfv36dMmTIJ5p53cHAwXl5eBAUFkTp1akeXI4nIli3mUzMAGzZA06bm6ytXruDt7c25c+d4/fXX+eGHHxxWo4jIy7DVd+gLTXoGkCtXLnLmzAmA0+M1z0WSqGvXoFMn83WvXv8EkcuXL+Pt7c358+fJkycPs2bNclyRIiLx1AtNerZgwQKKFy+Oh4cHHh4eFC9enPnz51u7NpEEISoKOnSAmzehVCn44gtzu7+/PzVr1uT8+fPkzZuX3bt3kzt3bscWKyISD8W5Z2TEiBFMnjyZ3r17U7lyZQD2799Pv3798Pf3Z/To0VYvUiQ++/xzc2bV5MlhxQrw8PgniFy8eJF8+fLh5+dHrly5HF2qiEi8FOcxIxkzZmT69Om0bds22vbly5fTu3fveD/XiMaMiDXt328+NRMZCQsWwNtvm9t9fHzw9fUlX7587N6923JLU0QkIbPVd2icb9OEh4dTvnz5J7aXK1eOiIgIqxQlkhDcvQtt25pBpE0b6NLln88WLFhAnTp1+PHHHxVERESeI85hpEOHDnz55ZdPbJ87dy7t27e3SlEi8Z1hwDvvwF9/Qb58MGcOhIeHWT7PnTs327dvJ0eOHA6sUkQkYXihp2kWLFjA9u3befXVVwE4ePAg/v7+dOzYkf79+1v2mzx5snWqFIln5s2D1avNeUSWL4fbty9Qt25dJkyYQIsWLRxdnohIghLnMSPe3t6xO7GTE7t27XqhomxJY0bkZf32G5QvD48ewYQJ0LLlBWrWrMnly5cpXrw4x44dI1myF35qXkQk3oo384z4+flZrXGRhCYkBFq3NoNIvXrQrNl5atSoyZUrVyhcuDDbt29XEBERiaM4jxm5efPmUz87efLkSxUjEt/172/2jGTODKNGncPbuwZXrlyhSJEi7N69m6xZszq6RBGRBCfOYaREiRJs2rTpie0TJ06kYsWKVilKJD5au9YcqAowfvyfvPFGTa5evcorr7yCn58fWbJkcWyBIiIJVJzDSP/+/WnZsiU9evQgJCSEq1evUrt2bSZMmMCyZctsUaOIw/31F3TrZr7+6CP4449FXL16laJFiyqIiIi8pDjf3P7www+pU6cOHTp0oGTJkgQGBlKpUiV+/fVX/YUsiVJ4OLRrZ84rUqkSfPopuLh8RvLkyXnnnXfIlCmTo0sUEUnQXmhtmgIFClC8eHEuXbpEcHAwrVu3VhCRRCky0lwAb98+SJnyL5YuDcfVFZydnRk+fLiCiIiIFcQ5jOzdu5eSJUvy559/8uuvv/Lll1/Su3dvWrduzZ07d2xRo4hDGAb07GnOI+LicgZX11cZOrQt4eHhji5NRCRRiXMYqVWrFq1bt+bAgQO88sordOvWjWPHjuHv70+JEiVsUaOI3RkGDB4MX30FcJqUKb25cyeAP//8k3v37jm6PBGRRCXOY0a2b99OjRo1om3Lnz8/e/fuZcyYMVYrTMSRxo0zJzSD06RK5U1Q0A1KlSrFzp07SZcunaPLExFJVOI8A2tCpxlY5XlmzoTevQF+I2XKWty/f4PSpUuzc+dO0qdP7+jyREQcxuGr9jZs2JCgoCDL+/Hjx3P37l3L+9u3b1O0aFGrFSbiCEuXPg4ip0ie3Jv7929QpkwZBRERERuKdRjZtm0boaGhlvdjx44lMDDQ8j4iIoKzZ89atzoRO1q/Ht5+23zdvPlNDOM+ZcuWVRAREbGxWI8Z+e/dnCR2d0cSuR07oE0b81Hezp1hwQJv9u/fQdGiRUmbNq2jyxMRSdS0opckefv2QbNmEBb2K3XqJGPevKI4O0OVKlUcXZqISJIQ69s0Tk5OODk5PbFNJCE7cQIaNoSHD4/j6lqLEye8OX9etxtFROwpTrdpOnfujLu7OwCPHj3ivffeI0WKFADRxpOIJAR//AF160JQ0DGSJfMhPDyQPHkqajZhERE7i3UY6dSpU7T3b7311hP7dOzY8eUrErEDf3/w8YEbN47i4uJDRMQdKlWqxLZt2/Dy8nJ0eSIiSUqsw8iiRYtsWYeI3Vy/bgaRy5eP4Oxch8jIO1SuXJmtW7dq7hkREQd4oYXyRBKqO3fMWzN//vkrzs4+REXd4bXXXlMQERFxID1NI0nG/fvmYNVff4VMmXKTNWthUqZMxpYtW0iVKpWjyxMRSbIURiRJePTIfHz3wAFImxZ27vQiV65tODs7K4iIiDiYwogkCSNGgK/vQdzc9rNlS1/MBaY1UFVEJD7QmBFJ9E6fhsmTDwB1CQvrx4ULyx1dkoiI/IvCiCRqhgEdO+4nMrIuEEyNGjVo0qSJo8sSEZF/URiRRO3TT/dy5Ehd4B6VK3uzadMmy0R9IiISP2jMiCRa27fvYdSoBsB98uatxc6d35M8eXJHlyUiIv+hnhFJlK5du0ajRg0wjPt4etbml18URERE4iuFEUmUgoKyEhk5CqjD119/T/r0CiIiIvGVwogkKoZhYBjQuzdERQ3g9de30LKlp6PLEhGRZ1AYkUTDz8+P2rVrs3RpEDt3grs7TJ/u4uiyRETkOTSAVRKFXbt20ahRI0JCQvjllzHABD76CPLlc3RlIiLyPOoZkQTP19fXEkTy5WvA/fujyZMHBg92dGUiIhIbCiOSoO3cudMSRGrUeB1///WAB9OmgaeGioiIJAgKI5Jg7dixg8aNG/Po0SMaNWqEq+taIiLcadgQGjd2dHUiIhJbCiOSIIWFhfHOO+/w6NEjmjRpwltvrWHnTnfc3GDaNHBycnSFIiISWxrAKgmSm5sbmzdvZvLkyUyYMItSpdwA+PBDKFDAwcWJiEicqGdEEpSgoCDL61deeYV58+YxcaIbly9D7twwZIgDixMRkReiMCIJxpYtW8iTJw++vr6WbX/+CRMnmq+nTAHN+C4ikvAojEiCsGnTJpo1a8bdu3dZtGgRgGWm1bAwqF8fmjVzbI0iIvJiFEYk3vv+++9p3rw5YWFhtGzZ0hJGNmyAbdvAzQ2mT9egVRGRhEphROK1jRs30rJlS8LDw2nVqhXLly/H1dWVhw+hb19zn4EDoWBBh5YpIiIvQWFE4q0NGzbwxhtvEB4eTuvWrVm2bBmurq4AjBsH/v6QMycMHergQkVE5KUojEi8tWbNGsLDw2nTpg3ffPMNyZKZT6KfOwcTJpj7TJkCKVI4sEgREXlpmmdE4q1Fixbx6quv8t5771mCiGHABx+Yg1br1IEWLRxcpIiIvDT1jEi88ssvvxAVFQWAq6srvXr1sgQRgI0bYcsWcHWFGTM0aFVEJDFQGJF4Y/Xq1VSuXJl3333XEkj+LSTkn0GrAwZA4cL2rU9ERGxDYUTihVWrVtG2bVsiIyMJDQ3FMIxon0dFmQHk0iXIkQOGD3dMnSIiYn0aMyIOt3LlStq3b09kZCSdOnViwYIFuLi4WD4PD4du3WDpUvP99OkatCoikpgojIhDLV++nLfeeouoqCi6dOnCvHnzogWRhw/hzTdh0yZwcYEFC6B5cwcWLCIiVqcwIg6zbNkyOnToQFRUFG+//Tbz5s3D2fmfO4eBgdCoEezfD56esGqV+V5ERBIXhRFxGE9PT5ydnXn77bf56quvogWRK1egXj04fRrSpDF7Rl57zXG1ioiI7SiMiMM0b96c/fv3U7Zs2WhB5PffzSDi7w/ZspnrzxQv7sBCRUTEpvQ0jdjVqlWruHTpkuV9+fLlowWRQ4egalUziBQqBPv2KYiIiCR28SKMzJo1izx58uDh4UGlSpU4dOjQU/edN28e1apVI23atKRNmxYfH59n7i/xx+LFi2nTpg01a9bk5s2bT3y+fTvUqgW3b0OFCrBnD+TO7YBCRUTErhweRlauXEn//v0ZOXIkR48epVSpUtSrV48bN27EuP/u3btp27Ytfn5+7N+/n5w5c1K3bl2uXr1q58olLhYuXMjbb7+NYRg0bNiQDBkyRPt8+XJ4/XV48MCc5n3XLsiY0UHFioiIXTkZ/51dys4qVapEhQoVmDlzJgBRUVHkzJmT3r17M3jw4OceHxkZSdq0aZk5cyYdO3Z84vPQ0FBCQ0Mt74ODg8mZMydBQUGkTp3aer+IPNWCBQvo3r07hmHQs2dPZsyYgdO/5nGfPh369DFft2kDS5aAm5uDihURkacKDg7Gy8vL6t+hDu0ZCQsL48iRI/j4+Fi2OTs74+Pjw/79+2N1jocPHxIeHk66dOli/HzcuHF4eXlZfnLmzGmV2iV25s+fT7du3TAMg169ekULIoZhzqT6OIj07g3ffqsgIiKS1Dg0jNy6dYvIyEgyZ84cbXvmzJkJCAiI1Tk++ugjsmXLFi3Q/NuQIUMICgqy/Fy+fPml65bYWbVqFd27dwfggw8+YPr06ZYgEhEB774LY8aY+372GUybBs4Ov3EoIiL2lqAf7R0/fjwrVqxg9+7deHh4xLiPu7s77u7udq5MAGrWrEmxYsXw8fFhypQpliDy6BG0bQsbNpjh48sv4Z13HFuriIg4jkPDSIYMGXBxceH69evRtl+/fp0sWbI889iJEycyfvx4du7cScmSJW1ZprygTJkysW/fPlKlSmUJIkFB0LQp/PgjuLvDsmXQooWDCxUREYdyaKe4m5sb5cqVw9fX17ItKioKX19fKleu/NTjJkyYwKeffsrWrVspX768PUqVWJo9ezbz58+3vE+dOrUliJw5Y86i+uOPkDo1bN2qICIiIvHgNk3//v3p1KkT5cuXp2LFikydOpUHDx7QpUsXADp27Ej27NkZN24cAJ9//jkjRoxg2bJl5MmTxzK2JGXKlKRMmdJhv4fAzJkz6d27N05OTpQsWZKKFStaPlu2zLwV8+ABZMkCW7ZA6dKOq1VEROIPh4eR1q1bc/PmTUaMGEFAQAClS5dm69atlkGt/v7+0Wbo/PLLLwkLC+ONN96Idp6RI0cyatQoe5Yu/zJjxgw++OADAAYNGkSFChUAc3xIv34wZ465X61aZjD5z5hlERFJwhw+z4i92eoZ6aRs2rRp9O3bF4DBgwczduxYnJycuHABWrWCo0fBycl8jHfkSHBxcWy9IiLyYmz1HerwnhFJ2KZMmUL//v0B8zHqMWPG4OTkxPr10KWLOWA1fXr45huoX9/BxYqISLykWR3khe3du9cSRIYNG8aYMWOIiHBiwABzYGpQkDlg9dgxBREREXk69YzIC3vttdcYMmQILi4ujB49mitXnGjdGh5PnjtgAIwbB66ujq1TRETiN40ZkTiLiIggWTIzxz7+47NtmxNvvWWuuOvlBYsXQ7NmjqtRRESsL1GuTSMJz+eff06DBg0ICQkBICrKiREjnGjY0AwiZcuaA1YVREREJLZ0m0Zibfz48QwZMgSAdevWUbt2e9q1Az8/8/MePWDyZHjKzPwiIiIxUhiRWBk7dizDhg0D4NNPPyV79vaUKQMBAZAiBcydC+3aObhIERFJkBRG5Lk+++wzPv74YwA+/fQzXFyGUbs2REVBsWKwZg0UKeLgIkVEJMFSGJFn+vTTTxkxYgQAw4ePZd++IWzZYn7WqRPMmmX2jIiIiLwohRF5qmvXrjFp0iQA3n9/PEuWfMTly+aYkJkzoWtXBxcoIiKJgsKIPFXWrFnZvn0H48btZe7cvkREQMGC5m2ZkiUdXZ2IiCQWerRXojEMgytXrgDmDKqff16BDRvMINKqFRw+rCAiIiLWpTAiFoZhMGLECIoVK8bXXx+iXDlYt86cQXXGDFi5EjRPnIiIWJtu0whgBpHhw4czduxYAN5++xARERXJnRtWrYKKFR1coIiIJFrqGREMw2DYsGGWIAJTiYjoRaNG5myqCiIiImJLCiNJnGEYDBkyhHHjxv29ZRouLn34/HP47jtIl86h5YmISBKg2zRJmGEYfPTRR3zxxRd/b5lB1qy9WLECqld3aGkiIpKEqGckCbt3L5zly0/8/W4mtWv34vhxBREREbEvhZEk6tw5qFHDjStXNgAbGDmyJ9u2QaZMjq5MRESSGoWRJMYwDGbM+IGyZQ2OH4cMGTzZtq0po0aBi4ujqxMRkaRIYSQJMQyDXr368cEHjbl3byiVKsHx41C3rqMrExGRpEwDWJMIwzDo06cPs2fPAMDLKy/ffw8ZMzq4MBERSfIURpIAwzD44IMPmDlz5t9b5rF+fTcFERERiRcURhI589ZML2bPng04AfMZPvxtvL0dXZmIiIhJYSSR692797+CyAKqVOnCyJGOrkpEROQfGsCayJUrVw4nJxdgEWnSdGHZMkimCCoiIvGIvpYSuWzZumAYNYB8LFwIuXI5uiIREZHo1DOSyERFRTF69GiuX79OQAB07AiQjx49oHlzR1cnIiLyJPWMJCJRUVG88847LFiwgLVr15Ix42Fu3HClRAmYNMnR1YmIiMRMPSOJRFRUFN26dWPBggU4OztTtOhH+Pq64ukJK1aAp6ejKxQREYmZwkgiEBkZSdeuXVm0aBHOzs6MGvUNa9a0A2D6dCha1MEFioiIPIPCSAL3OIgsXrwYFxcX5s9fxsKFbYmIgDffhK5dHV2hiIjIsymMJHDDhg1jyZIluLi48O23y9i2rTWXLkGePDB3Ljg5ObpCERGRZ1MYSeDef/99ChYsyPLly7l//01WrjRX312+HLy8HF2diIjI8+lpmgQuV65cnDp1inPn3Chf3tw2Zgy8+qpj6xIREYkt9YwkMBEREXTq1Im1a9datkVGutGmDYSEQJ06MGiQAwsUERGJI4WRBCQiIoIOHTqwdOlSOnbsyI0bNwAYOBBOnoRMmWDpUnDW/6siIpKA6DZNAhEREUH79u1ZtWoVrq6uLFu2jEyZMrF+Pcyebe6zdClkyeLYOkVEROJKYSQBCA8Pp3379qxevRpXV1fWrl1L48aN8ff/59HdQYOgXj3H1ikiIvIiFEbiufDwcNq1a8eaNWtwc3Nj7dq1NGrUiIgIaNcO7tyBChXgs88cXamIiMiL0eiCeG7JkiWWILJu3ToaNWrEb79B7dqwdy+kSmVO9+7m5uhKRUREXox6RuK5t99+mxMnTtCgQQOqV2/IoEEwdSpERJjrzSxdCvnyObpKERGRF6cwEg+FhYXh5OSEq6srzs7OTJ8+g3Xr4JVX4MoVc59mzcxQkju3IysVERF5eQoj8UxYWBitWrXC1dWV5cuX89dfrvTqBdu2mZ/nzQszZsDrrzu2ThEREWtRGIlHQkNDadWqFd9//z0eHh706nWSJUvKEhpqjgn56CMYMsS8PSMiIpJYKIzEE6GhobRs2ZJNmzbh5uZBmjTfM3duWQDq1oWZM6FgQQcXKSIiYgN6miYeePToES1atGDTpk24uHgSFvYDAQE+ZM8Oq1bB1q0KIiIikngpjDjYo0ePaNasBZs3bwY8iYz8AReX2gwYAGfOQKtW4OTk6CpFRERsR7dpHGzJkt/Yvn034AlsompVb2bPhhIlHFyYiIiInSiMOND48TBkSDnge7y8XJg+vSYdOqgnREREkhaFEQcICQnhxx+v8PHH5kCQ996rzdixkDatgwsTERFxAIURO3v48CFNmzblp59+JSLCj0aNivLll46uSkRExHEURuzo4cOHNG7cmF27dgEpcHUNZNo0R1clIiLiWHqaxk4ePHhAo0aN2LVrF05OKYGtDBlSVevKiIhIkqcwYgePg4ifnx9ubikxjK3kyVOVwYMdXZmIiIjjKYzY2IMHD3j99dfZvXs3KVKkIjJyG1CFadM0rbuIiAgojNhcZGQkoaGhpE6dmmLFthMZ+RoNG0Ljxo6uTEREJH5QGLGx1KlTs3XrVoYP382hQ6/i5gbTpmkuERERkccURmzg3r17fPvtt5b3yZJ5MWNGGcBcebdAAUdVJiIiEv/o0V4rCw4OpkGDBuzbt49bt27Rp08fxo6Fy5chd240aFVEROQ/FEasKDg4mPr167N//37SpElDlSpV+PNPmDjR/HzqVEie3KElioiIxDsKI1YSFBRE/fr1OXDgAGnTpmXHjh2ULVuOBg0gLAzq14emTR1dpYiISPyjMGIFQUFB1KtXj4MHD5I2bVp27txJ2bJlWb8etm0DNzeYPl2DVkVERGKiMPKSwsLCqFu3LocOHSJdunTs3LmTMmXK8PAh9O1r7jNoEBQs6NAyRURE4i09TfOS3NzcaN26NenTp8fX15cyZcynZsaNA39/yJULhg51cJEiIiLxmJNhGIaji7Cn4OBgvLy8CAoKInXq1FY7761bt8iQIQMA585BsWLmWJG1a6FFC6s1IyIi4jC2+g5Vz8gLuHPnDt27dycoKMiy7XEQMQz44AMziNStC82bO6pKERGRhEFjRuIoMDCQOnXqcPToUQICAvj++++jfb5xI2zZAq6uMGOGBq2KiIg8j8JIHAQGBuLj48OxY8fImDEj48aNi/Z5SMg/g1YHDoRChexfo4iISEKj2zSxdPv2bWrXrs2xY8fIlCkTfn5+FC9ePNo+48fDpUuQMycMG+aYOkVERBIahZFYuHXrFrVr1+b48eNkzpwZPz8/ihUrFm2f8+fh88/N15MnQ4oUDihUREQkAdJtmlh46623OHHihCWIvPLKK0/s06cPhIaCjw+0bOmAIkVERBIo9YzEwtSpUylTpgy7d++OMYh8/z1s2qRBqyIiIi9CPSNPERUVhbOzmdWKFCnCkSNHcIohZYSEmL0iAP37Q5Ei9qxSREQk4VPPSAyuX79OpUqV8PX1tWyLKYgYBowaBRcvQo4cMHy4HYsUERFJJBRG/iMgIABvb28OHz5Mjx49CA8Pj3G/06ehVi2YMMF8P2kSpExpx0JFREQSCYWRf3kcRM6cOUP27NnZvHkzrq6u0fZ58AAGD4ZSpWD3bvD0NANJq1aOqVlERCSh05iRv127do1atWrx+++/kyNHDvz8/ChQoIDlc8OA9evNSc0uXza3NWkC06ZBnjwOKVlERCRRUBjBDCLe3t6cPXuWnDlz4ufnR/78+S2fnz8PvXub07yDGT6mT4fGjR1Tr4iISGKi2zTAlClTOHv2LLly5WL37t2WIPLoEXzyibkC7+P1ZoYNg99+UxARERGxFvWMAGPHjiU0NJS+ffuSN29eALZuhV69zF4RMCczmzkTChd2YKEiIiKJULzoGZk1axZ58uTBw8ODSpUqcejQoWfuv3r1aooUKYKHhwclSpRg8+bNL9V+smTJmDZtGnnz5uXyZXjjDWjQwAwi2bLBihWwfbuCiIiIiC04PIysXLmS/v37M3LkSI4ePUqpUqWoV68eN27ciHH/ffv20bZtW7p27cqxY8do1qwZzZo149SpUy9VR3g4fPEFvPIKrF0LLi7mJGa//w6tW2tWVREREVtxMgzDcGQBlSpVokKFCsycORMwZz7NmTMnvXv3ZvDgwU/s37p1ax48eMAPP/xg2fbqq69SunRp5syZ89z2goOD8fLyIigoiNSpUwPw44/w/vvm3CEAVarA7NlQsqQVfkEREZFEIqbvUGtw6JiRsLAwjhw5wpAhQyzbnJ2d8fHxYf/+/TEes3//fvr37x9tW7169diwYUOM+4eGhhIaGmp5HxQUBJgXFGDnzn8WtkuXDj77DNq2BWdn+HsXERER4Z/vTmv3Yzg0jNy6dYvIyEgyZ84cbXvmzJn5/fffYzwmICAgxv0DAgJi3H/cuHF88sknT2zPmTPnE9sCA80ekvffj+1vICIikvTcvn0bLy8vq50v0T9NM2TIkGg9KXfv3iV37tz4+/tb9ULK0wUHB5MzZ04uX75s1W49eTpdc/vTNbc/XXP7CwoKIleuXKRLl86q53VoGMmQIQMuLi5cv3492vbr16+TJUuWGI/JkiVLnPZ3d3fH3d39ie1eXl76w2tnqVOn1jW3M11z+9M1tz9dc/t7vKq91c5n1bPFkZubG+XKlYu2Om5UVBS+vr5Urlw5xmMqV64cbX+AHTt2PHV/ERERid8cfpumf//+dOrUifLly1OxYkWmTp3KgwcP6NKlCwAdO3Yke/bsjBs3DoA+ffpQo0YNJk2axOuvv86KFSs4fPgwc+fOdeSvISIiIi/I4WGkdevW3Lx5kxEjRhAQEEDp0qXZunWrZZCqv79/tO6g1157jWXLljF8+HCGDh1KwYIF2bBhA8WLF49Ve+7u7owcOTLGWzdiG7rm9qdrbn+65vana25/trrmDp9nRERERJI2h8/AKiIiIkmbwoiIiIg4lMKIiIiIOJTCiIiIiDhUogwjs2bNIk+ePHh4eFCpUiUOHTr0zP1Xr15NkSJF8PDwoESJEmzevNlOlSYecbnm8+bNo1q1aqRNm5a0adPi4+Pz3P+P5Elx/XP+2IoVK3BycqJZs2a2LTARius1v3v3Lj179iRr1qy4u7tTqFAh/f0SR3G95lOnTqVw4cJ4enqSM2dO+vXrx6NHj+xUbcL3008/0bhxY7Jly4aTk9NT1337t927d1O2bFnc3d0pUKAAixcvjnvDRiKzYsUKw83NzVi4cKHx22+/Gd27dzfSpEljXL9+Pcb99+7da7i4uBgTJkwwTp8+bQwfPtxwdXU1Tp48aefKE664XvN27doZs2bNMo4dO2acOXPG6Ny5s+Hl5WVcuXLFzpUnXHG95o9dvHjRyJ49u1GtWjWjadOm9ik2kYjrNQ8NDTXKly9vNGzY0NizZ49x8eJFY/fu3cbx48ftXHnCFddr/u233xru7u7Gt99+a1y8eNHYtm2bkTVrVqNfv352rjzh2rx5szFs2DBj3bp1BmCsX7/+mftfuHDBSJ48udG/f3/j9OnTxowZMwwXFxdj69atcWo30YWRihUrGj179rS8j4yMNLJly2aMGzcuxv3ffPNN4/XXX4+2rVKlSsa7775r0zoTk7he8/+KiIgwUqVKZSxZssRWJSY6L3LNIyIijNdee82YP3++0alTJ4WROIrrNf/yyy+NfPnyGWFhYfYqMdGJ6zXv2bOnUatWrWjb+vfvb1SpUsWmdSZWsQkjH374oVGsWLFo21q3bm3Uq1cvTm0lqts0YWFhHDlyBB8fH8s2Z2dnfHx82L9/f4zH7N+/P9r+APXq1Xvq/hLdi1zz/3r48CHh4eFWX3gpsXrRaz569GgyZcpE165d7VFmovIi13zjxo1UrlyZnj17kjlzZooXL87YsWOJjIy0V9kJ2otc89dee40jR45YbuVcuHCBzZs307BhQ7vUnBRZ6zvU4TOwWtOtW7eIjIy0zN76WObMmfn9999jPCYgICDG/QMCAmxWZ2LyItf8vz766COyZcv2xB9oidmLXPM9e/awYMECjh8/bocKE58XueYXLlxg165dtG/fns2bN3Pu3Dnef/99wsPDGTlypD3KTtBe5Jq3a9eOW7duUbVqVQzDICIigvfee4+hQ4fao+Qk6WnfocHBwYSEhODp6Rmr8ySqnhFJeMaPH8+KFStYv349Hh4eji4nUbp37x4dOnRg3rx5ZMiQwdHlJBlRUVFkypSJuXPnUq5cOVq3bs2wYcOYM2eOo0tLtHbv3s3YsWOZPXs2R48eZd26dWzatIlPP/3U0aXJcySqnpEMGTLg4uLC9evXo22/fv06WbJkifGYLFmyxGl/ie5FrvljEydOZPz48ezcuZOSJUvassxEJa7X/Pz581y6dInGjRtbtkVFRQGQLFkyzp49S/78+W1bdAL3In/Os2bNiqurKy4uLpZtr7zyCgEBAYSFheHm5mbTmhO6F7nmH3/8MR06dKBbt24AlChRggcPHvDOO+8wbNgwqy97L0//Dk2dOnWse0UgkfWMuLm5Ua5cOXx9fS3boqKi8PX1pXLlyjEeU7ly5Wj7A+zYseOp+0t0L3LNASZMmMCnn37K1q1bKV++vD1KTTTies2LFCnCyZMnOX78uOWnSZMmeHt7c/z4cXLmzGnP8hOkF/lzXqVKFc6dO2cJfgB//PEHWbNmVRCJhRe55g8fPnwicDwOg4aWYbMJq32Hxm1sbfy3YsUKw93d3Vi8eLFx+vRp45133jHSpEljBAQEGIZhGB06dDAGDx5s2X/v3r1GsmTJjIkTJxpnzpwxRo4cqUd74yiu13z8+PGGm5ubsWbNGuPatWuWn3v37jnqV0hw4nrN/0tP08RdXK+5v7+/kSpVKqNXr17G2bNnjR9++MHIlCmT8dlnnznqV0hw4nrNR44caaRKlcpYvny5ceHCBWP79u1G/vz5jTfffNNRv0KCc+/ePePYsWPGsWPHDMCYPHmycezYMeOvv/4yDMMwBg8ebHTo0MGy/+NHewcNGmScOXPGmDVrlh7tfWzGjBlGrly5DDc3N6NixYrGgQMHLJ/VqFHD6NSpU7T9V61aZRQqVMhwc3MzihUrZmzatMnOFSd8cbnmuXPnNoAnfkaOHGn/whOwuP45/zeFkRcT12u+b98+o1KlSoa7u7uRL18+Y8yYMUZERISdq07Y4nLNw8PDjVGjRhn58+c3PDw8jJw5cxrvv/++cefOHfsXnkD5+fnF+Pfz4+vcqVMno0aNGk8cU7p0acPNzc3Ily+fsWjRoji362QY6rsSERERx0lUY0ZEREQk4VEYEREREYdSGBERERGHUhgRERERh1IYEREREYdSGBERERGHUhgRERERh1IYEREREYdSGBERERGHUhgRERERh1IYERGLmjVr0rdv31i/t9U5EqrE/LuJ2FIyRxcgIs8WEBDAmDFj2LRpE1evXiVTpkyULl2avn37Urt2bZu2vW7dOlxdXa16zL8/r1mzJqVLl2bq1KkvUyYAnTt35u7du2zYsOGlzyUi9qUwIhKPXbp0iSpVqpAmTRq++OILSpQoQXh4ONu2baNnz578/vvvTxwTFhaGm5ubVdpPly6d1Y95kXOKSOKm2zQi8dj777+Pk5MThw4domXLlhQqVIhixYrRv39/Dhw4AJi9C7169aJv375kyJCBevXqARAVFcW4cePImzcvnp6elCpVijVr1ljO/eDBAzp27EjKlCnJmjUrkyZNeqL9mG47RERE0KtXL7y8vMiQIQMff/wx/178+3m3Kh5/3rlzZ3788UemTZuGk5MTTk5OXLp0iaVLl5I+fXpCQ0OjHdesWTM6dOgQ10sYq2sxd+5csmXLRlRUVLTjmjZtyttvvx2rc8TWoUOHqFmzJp6enhQpUoTDhw8zd+5cmjRp8kK/m0hioDAiEk8FBgaydetWevbsSYoUKZ74PE2aNJbXS5Yswc3Njb179zJnzhwAxo0bx9KlS5kzZw6//fYb/fr146233uLHH38EYNCgQfz444989913bN++nd27d3P06NHn1rVkyRKSJUvGoUOHmDZtGpMnT2b+/Plx/v2mTZtG5cqV6d69O9euXePatWvkzJmTVq1aERkZycaNGy373rhxg02bNlmCQVw971q0atWK27dv4+fnZznm8fVv3759rM4RGwcOHKBGjRq8/vrr/Prrr7zyyiuMHj2azz//nE8++eSFfjeRxEC3aUTiqXPnzmEYBkWKFHnuvgULFmTChAmW96GhoYwdO5adO3dSuXJlAPLly8eePXv46quvKFeuHAsWLOCbb76xjDtZsmQJOXLkeG5bOXPmZMqUKTg5OVG4cGFOnjzJlClT6N69e5x+Py8vL9zc3EiePDlZsmSxbPf09KRdu3YsWrSIVq1aAfDNN9+QK1cuatasGac24PnXokaNGqRNm5YGDRqwbNkyy/VYs2YNGTJkwNvbO1bniI3+/fvTqlUrBg0aBEDbtm1p27YtTZs2pUyZMnH+3UQSC4URkXjq37c+nqdcuXLR3p87d46HDx9Sp06daNvDwsIoU6YM58+fJywsjEqVKlk+S5cuHYULF35uW6+++ipOTk6W95UrV2bSpElERkbi4uIS65qfpXv37lSoUIGrV6+SPXt2Fi9eTOfOnaO1G1vPuxaPtW/fnu7duzN79mzc3d359ttvadOmDc7OzrE+x7NcuXKF/fv3M3HiRMu2ZMmSYRiGekUkyVMYEYmnChYsiJOTU4yDVP/rv7dx7t+/D8CmTZvInj17tM/c3d0JDAy0XqE2UKZMGUqVKsXSpUupW7cuv/32G5s2bXqhcz3vWjzWuHFjDMNg06ZNVKhQgZ9//pkpU6bE6RzPcubMGQDKli1r2Xb27FkqVqxIiRIl4vhbiSQuCiMi8VS6dOmoV68es2bN4oMPPngicNy9ezfauJF/K1q0KO7u7vj7+8d4CyFt2rS4urpy8OBBcuXKBcCdO3f4448/nnvL4eDBg9HeHzhwgIIFC75Qr4ibmxuRkZExftatWzemTp3K1atX8fHxIWfOnHE+Pzz/Wjzm4eFBixYt+Pbbbzl37hyFCxe2BIfYnuNZgoKCcHFxsfTuBAYGMnHiREqVKvVC5xNJTBRGROKxWbNmUaVKFSpWrMjo0aMpWbIkERER7Nixgy+//NLyr+3/SpUqFQMHDqRfv35ERUVRtWpVgoKC2Lt3L6lTp6ZTp0507dqVQYMGkT59ejJlysSwYcNwdn7+mHZ/f3/69+/Pu+++y9GjR5kxY0aMT+LERp48eTh48CCXLl0iZcqUpEuXzlJDu3btGDhwIPPmzWPp0qWxOl9QUBDHjx+Pti19+vTPvRaPtW/fnkaNGvHbb7/x1ltvWbbH5no+T+nSpYmMjGTChAm0atWKPn36kCdPHk6fPs1ff/1F7ty5Y/U7iiRGCiMi8Vi+fPk4evQoY8aMYcCAAVy7do2MGTNSrlw5vvzyy2ce++mnn5IxY0bGjRvHhQsXSJMmDWXLlmXo0KEAfPHFF9y/f5/GjRuTKlUqBgwYQFBQ0HNr6tixIyEhIVSsWBEXFxf69OnDO++880K/38CBA+nUqRNFixYlJCSEixcvkidPHsAc4NqyZUs2bdpEs2bNYnW+3bt3PzGGo2vXrsybN++Z1+KxWrVqkS5dOs6ePUu7du2iffa86/k8BQoUYPTo0UybNo2xY8fSpk0bli1bRt26dalfv/5Tg6VIUuBkxGWUnIiIHdWuXZtixYoxffp0R5ciIjakMCIi8c6dO3fYvXs3b7zxBqdPn47VUz4iknDpNo2IxDtlypThzp07fP755woiIkmAekZERETEoTQdvIiIiDiUwoiIiIg4lMKIiIiIOJTCiIiIiDiUwoiIiIg4lMKIiIiIOJTCiIiIiDiUwoiIiIg4lMKIiIiIOJTCiIiIiDjU/wH87XcQZaj9kQAAAABJRU5ErkJggg==\n",
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",
       "text/plain": [
        "<Figure size 600x600 with 1 Axes>"
       ]
@@ -923,7 +1133,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.14"
+   "version": "3.10.16"
   },
   "toc": {
    "base_numbering": 1,