diff --git a/docs/visualization/titiler/titiler-cmr/titiler-cmr-benchmark.ipynb b/docs/visualization/titiler/titiler-cmr/titiler-cmr-benchmark.ipynb
index 315aacc..4c9e9cd 100644
--- a/docs/visualization/titiler/titiler-cmr/titiler-cmr-benchmark.ipynb
+++ b/docs/visualization/titiler/titiler-cmr/titiler-cmr-benchmark.ipynb
@@ -21,7 +21,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "18a0edb6-7220-4910-854d-3b07d4e4f417",
    "metadata": {},
    "outputs": [],
@@ -101,7 +101,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 2,
    "id": "4e7a8f91-ce75-4afc-85de-b1a6b4b0f48d",
    "metadata": {},
    "outputs": [],
@@ -122,6 +122,38 @@
     ")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "9823ed5f-5828-47eb-834f-81d52890c2ec",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'check_titiler_cmr_compatibility' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
+      "\u001b[31mNameError\u001b[39m                                 Traceback (most recent call last)",
+      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[3]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m compat = \u001b[38;5;28;01mawait\u001b[39;00m \u001b[43mcheck_titiler_cmr_compatibility\u001b[49m(\n\u001b[32m      2\u001b[39m     endpoint=endpoint,\n\u001b[32m      3\u001b[39m     dataset=ds_xarray,\n\u001b[32m      4\u001b[39m     timeout_s=\u001b[32m250.0\u001b[39m,\n\u001b[32m      5\u001b[39m )\n\u001b[32m      7\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mCompatibility: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mcompat[\u001b[33m'\u001b[39m\u001b[33mcompatibility\u001b[39m\u001b[33m'\u001b[39m]\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m)\n\u001b[32m      8\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mTimesteps: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mcompat[\u001b[33m'\u001b[39m\u001b[33mn_timesteps\u001b[39m\u001b[33m'\u001b[39m]\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m)\n",
+      "\u001b[31mNameError\u001b[39m: name 'check_titiler_cmr_compatibility' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "compat = await check_titiler_cmr_compatibility(\n",
+    "    endpoint=endpoint,\n",
+    "    dataset=ds_xarray,\n",
+    "    timeout_s=250.0,\n",
+    ")\n",
+    "\n",
+    "print(f\"Compatibility: {compat['compatibility']}\")\n",
+    "print(f\"Timesteps: {compat['n_timesteps']}\")\n",
+    "print(f\"Bounds: {compat['tilejson_bounds']}\")\n",
+    "if not compat[\"statistics\"].empty:\n",
+    "    print(f\"Statistics preview:\\n{compat['statistics']}\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "bd0861dc",
@@ -137,7 +169,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 4,
    "id": "bde8b55b",
    "metadata": {},
    "outputs": [],
@@ -164,7 +196,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 5,
    "id": "627eca1c",
    "metadata": {},
    "outputs": [
@@ -184,7 +216,7 @@
       "  temporal_mode: point\n",
       "  tile_format: png\n",
       "  tile_scale: 1\n",
-      "Total execution time: 19.153s\n"
+      "Total execution time: 16.778s\n"
      ]
     }
    ],
@@ -204,7 +236,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 6,
    "id": "15ba4c0b-6241-4fe0-8e82-d9271b4c668c",
    "metadata": {},
    "outputs": [
@@ -254,12 +286,12 @@
        "      <td>True</td>\n",
        "      <td>False</td>\n",
        "      <td>False</td>\n",
-       "      <td>1.609666</td>\n",
+       "      <td>1.035299</td>\n",
        "      <td>image/png</td>\n",
        "      <td>694</td>\n",
        "      <td>https://staging.openveda.cloud/api/titiler-cmr...</td>\n",
        "      <td>None</td>\n",
-       "      <td>19.153049</td>\n",
+       "      <td>16.778217</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
@@ -270,12 +302,12 @@
        "      <td>True</td>\n",
        "      <td>False</td>\n",
        "      <td>False</td>\n",
-       "      <td>1.192089</td>\n",
+       "      <td>0.846679</td>\n",
        "      <td>image/png</td>\n",
        "      <td>694</td>\n",
        "      <td>https://staging.openveda.cloud/api/titiler-cmr...</td>\n",
        "      <td>None</td>\n",
-       "      <td>19.153049</td>\n",
+       "      <td>16.778217</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
@@ -286,12 +318,12 @@
        "      <td>True</td>\n",
        "      <td>False</td>\n",
        "      <td>False</td>\n",
-       "      <td>1.617420</td>\n",
+       "      <td>1.004644</td>\n",
        "      <td>image/png</td>\n",
        "      <td>694</td>\n",
        "      <td>https://staging.openveda.cloud/api/titiler-cmr...</td>\n",
        "      <td>None</td>\n",
-       "      <td>19.153049</td>\n",
+       "      <td>16.778217</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
@@ -302,12 +334,12 @@
        "      <td>True</td>\n",
        "      <td>False</td>\n",
        "      <td>False</td>\n",
-       "      <td>2.887875</td>\n",
+       "      <td>1.056702</td>\n",
        "      <td>image/png</td>\n",
        "      <td>694</td>\n",
        "      <td>https://staging.openveda.cloud/api/titiler-cmr...</td>\n",
        "      <td>None</td>\n",
-       "      <td>19.153049</td>\n",
+       "      <td>16.778217</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
@@ -318,12 +350,12 @@
        "      <td>True</td>\n",
        "      <td>False</td>\n",
        "      <td>False</td>\n",
-       "      <td>0.804066</td>\n",
+       "      <td>0.896079</td>\n",
        "      <td>image/png</td>\n",
        "      <td>694</td>\n",
        "      <td>https://staging.openveda.cloud/api/titiler-cmr...</td>\n",
        "      <td>None</td>\n",
-       "      <td>19.153049</td>\n",
+       "      <td>16.778217</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -331,11 +363,11 @@
       ],
       "text/plain": [
        "   zoom  x  y  status_code    ok  no_data  is_error  response_time_sec  \\\n",
-       "0     3  2  1          200  True    False     False           1.609666   \n",
-       "1     3  3  1          200  True    False     False           1.192089   \n",
-       "2     3  4  1          200  True    False     False           1.617420   \n",
-       "3     3  5  1          200  True    False     False           2.887875   \n",
-       "4     3  6  1          200  True    False     False           0.804066   \n",
+       "0     3  2  1          200  True    False     False           1.035299   \n",
+       "1     3  3  1          200  True    False     False           0.846679   \n",
+       "2     3  4  1          200  True    False     False           1.004644   \n",
+       "3     3  5  1          200  True    False     False           1.056702   \n",
+       "4     3  6  1          200  True    False     False           0.896079   \n",
        "\n",
        "  content_type  response_size_bytes  \\\n",
        "0    image/png                  694   \n",
@@ -352,14 +384,14 @@
        "4  https://staging.openveda.cloud/api/titiler-cmr...       None   \n",
        "\n",
        "   total_run_elapsed_s  \n",
-       "0            19.153049  \n",
-       "1            19.153049  \n",
-       "2            19.153049  \n",
-       "3            19.153049  \n",
-       "4            19.153049  "
+       "0            16.778217  \n",
+       "1            16.778217  \n",
+       "2            16.778217  \n",
+       "3            16.778217  \n",
+       "4            16.778217  "
       ]
      },
-     "execution_count": 8,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -386,7 +418,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 7,
    "id": "7b361ecc",
    "metadata": {},
    "outputs": [
@@ -428,8 +460,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.192089</td>\n",
-       "      <td>2.756978</td>\n",
+       "      <td>1.001195</td>\n",
+       "      <td>1.707613</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
@@ -438,8 +470,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.182342</td>\n",
-       "      <td>2.790999</td>\n",
+       "      <td>0.932405</td>\n",
+       "      <td>5.983943</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
@@ -448,8 +480,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.372662</td>\n",
-       "      <td>2.405504</td>\n",
+       "      <td>0.882105</td>\n",
+       "      <td>5.623972</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
@@ -458,8 +490,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.008795</td>\n",
-       "      <td>2.078795</td>\n",
+       "      <td>0.871669</td>\n",
+       "      <td>5.655667</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
@@ -468,8 +500,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.953299</td>\n",
-       "      <td>1.776905</td>\n",
+       "      <td>0.891772</td>\n",
+       "      <td>1.584068</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
@@ -478,8 +510,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.199947</td>\n",
-       "      <td>1.937273</td>\n",
+       "      <td>0.868153</td>\n",
+       "      <td>7.002302</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
@@ -488,8 +520,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.224152</td>\n",
-       "      <td>1.949105</td>\n",
+       "      <td>0.869188</td>\n",
+       "      <td>1.533077</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
@@ -498,8 +530,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.883679</td>\n",
-       "      <td>1.680721</td>\n",
+       "      <td>0.892048</td>\n",
+       "      <td>1.422070</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
@@ -508,8 +540,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.131980</td>\n",
-       "      <td>1.972159</td>\n",
+       "      <td>0.997419</td>\n",
+       "      <td>1.279416</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
@@ -518,8 +550,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.503204</td>\n",
-       "      <td>2.715302</td>\n",
+       "      <td>0.891310</td>\n",
+       "      <td>1.195986</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
@@ -528,8 +560,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.321729</td>\n",
-       "      <td>2.163595</td>\n",
+       "      <td>0.906080</td>\n",
+       "      <td>1.080735</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11</th>\n",
@@ -538,8 +570,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.275581</td>\n",
-       "      <td>2.366395</td>\n",
+       "      <td>0.888507</td>\n",
+       "      <td>1.063245</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12</th>\n",
@@ -548,8 +580,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.202473</td>\n",
-       "      <td>1.965626</td>\n",
+       "      <td>0.887647</td>\n",
+       "      <td>1.084382</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13</th>\n",
@@ -558,8 +590,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.086001</td>\n",
-       "      <td>2.874105</td>\n",
+       "      <td>0.902636</td>\n",
+       "      <td>1.199626</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14</th>\n",
@@ -568,8 +600,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.022910</td>\n",
-       "      <td>2.578667</td>\n",
+       "      <td>0.893629</td>\n",
+       "      <td>1.081811</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15</th>\n",
@@ -578,8 +610,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.042412</td>\n",
-       "      <td>2.091209</td>\n",
+       "      <td>0.881498</td>\n",
+       "      <td>1.071350</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>16</th>\n",
@@ -588,8 +620,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.076227</td>\n",
-       "      <td>1.677191</td>\n",
+       "      <td>0.881334</td>\n",
+       "      <td>0.944420</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>17</th>\n",
@@ -598,8 +630,8 @@
        "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>1.083148</td>\n",
-       "      <td>2.155265</td>\n",
+       "      <td>0.880602</td>\n",
+       "      <td>1.017367</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -607,47 +639,47 @@
       ],
       "text/plain": [
        "    zoom  n_tiles  ok_pct  no_data_pct  error_pct  median_latency_s  \\\n",
-       "0      3     25.0   100.0          0.0        0.0          1.192089   \n",
-       "1      4     25.0   100.0          0.0        0.0          1.182342   \n",
-       "2      5     25.0   100.0          0.0        0.0          1.372662   \n",
-       "3      6     25.0   100.0          0.0        0.0          1.008795   \n",
-       "4      7     25.0   100.0          0.0        0.0          0.953299   \n",
-       "5      8     25.0   100.0          0.0        0.0          1.199947   \n",
-       "6      9     25.0   100.0          0.0        0.0          1.224152   \n",
-       "7     10     25.0   100.0          0.0        0.0          0.883679   \n",
-       "8     11     25.0   100.0          0.0        0.0          1.131980   \n",
-       "9     12     25.0   100.0          0.0        0.0          1.503204   \n",
-       "10    13     25.0   100.0          0.0        0.0          1.321729   \n",
-       "11    14     25.0   100.0          0.0        0.0          1.275581   \n",
-       "12    15     25.0   100.0          0.0        0.0          1.202473   \n",
-       "13    16     25.0   100.0          0.0        0.0          1.086001   \n",
-       "14    17     25.0   100.0          0.0        0.0          1.022910   \n",
-       "15    18     25.0   100.0          0.0        0.0          1.042412   \n",
-       "16    19     25.0   100.0          0.0        0.0          1.076227   \n",
-       "17    20     25.0   100.0          0.0        0.0          1.083148   \n",
+       "0      3     25.0   100.0          0.0        0.0          1.001195   \n",
+       "1      4     25.0   100.0          0.0        0.0          0.932405   \n",
+       "2      5     25.0   100.0          0.0        0.0          0.882105   \n",
+       "3      6     25.0   100.0          0.0        0.0          0.871669   \n",
+       "4      7     25.0   100.0          0.0        0.0          0.891772   \n",
+       "5      8     25.0   100.0          0.0        0.0          0.868153   \n",
+       "6      9     25.0   100.0          0.0        0.0          0.869188   \n",
+       "7     10     25.0   100.0          0.0        0.0          0.892048   \n",
+       "8     11     25.0   100.0          0.0        0.0          0.997419   \n",
+       "9     12     25.0   100.0          0.0        0.0          0.891310   \n",
+       "10    13     25.0   100.0          0.0        0.0          0.906080   \n",
+       "11    14     25.0   100.0          0.0        0.0          0.888507   \n",
+       "12    15     25.0   100.0          0.0        0.0          0.887647   \n",
+       "13    16     25.0   100.0          0.0        0.0          0.902636   \n",
+       "14    17     25.0   100.0          0.0        0.0          0.893629   \n",
+       "15    18     25.0   100.0          0.0        0.0          0.881498   \n",
+       "16    19     25.0   100.0          0.0        0.0          0.881334   \n",
+       "17    20     25.0   100.0          0.0        0.0          0.880602   \n",
        "\n",
        "    p95_latency_s  \n",
-       "0        2.756978  \n",
-       "1        2.790999  \n",
-       "2        2.405504  \n",
-       "3        2.078795  \n",
-       "4        1.776905  \n",
-       "5        1.937273  \n",
-       "6        1.949105  \n",
-       "7        1.680721  \n",
-       "8        1.972159  \n",
-       "9        2.715302  \n",
-       "10       2.163595  \n",
-       "11       2.366395  \n",
-       "12       1.965626  \n",
-       "13       2.874105  \n",
-       "14       2.578667  \n",
-       "15       2.091209  \n",
-       "16       1.677191  \n",
-       "17       2.155265  "
+       "0        1.707613  \n",
+       "1        5.983943  \n",
+       "2        5.623972  \n",
+       "3        5.655667  \n",
+       "4        1.584068  \n",
+       "5        7.002302  \n",
+       "6        1.533077  \n",
+       "7        1.422070  \n",
+       "8        1.279416  \n",
+       "9        1.195986  \n",
+       "10       1.080735  \n",
+       "11       1.063245  \n",
+       "12       1.084382  \n",
+       "13       1.199626  \n",
+       "14       1.081811  \n",
+       "15       1.071350  \n",
+       "16       0.944420  \n",
+       "17       1.017367  "
       ]
      },
-     "execution_count": 9,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -659,7 +691,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 8,
    "id": "a69a9d32",
    "metadata": {},
    "outputs": [],
@@ -743,13 +775,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 9,
    "id": "7cf2548a",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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rFVdffbUoKioSTqdTHH/88WL37t1CiET/rx//+MciOztbFBcXi9tuuy3Z/6y1USDPP/98MWfOnOTrd955R4wfP144nU5RWFiYMorkhx9+KE488USRmZkpsrOzxemnn54ceXH/0TtHjx4tli5dmtx2xYoVYsSIEcLtdotzzjnngO9v/9E7P/74YzFq1CiRkZEhpk+f3mL0zrPOOkvcf//9B9znsmXLxNSpU5P9xsaMGSMeeughEYvFxHPPPScACLvdLjIyMpL/XnzxxeT2qqqKwsJC8c9//rPFvufOnSsApGzbfCTIZ599VgwfPlxkZGSI7Oxsccopp4iPPvooZR/r168XkiS1OuLnww8/LIqLi4XdbhcFBQXioosuarVP517792fzer3iyiuvFAUFBcLpdIoxY8aIV155JWWb5557TgwaNEg4HA4xceJE8cUXX7S67/b06dtr6dKlyXPudDrFkUceKa677rqUUUsBCJvNlnLeJkyYkNx+ypQpIicnR2RkZIiBAweK2bNni0AgcNBjl5aWCqvVKhwOh3C5XOKYY44Rc+bMSdl2/+/D9ddfL4488kjhcDhEZmamOPHEE8V7772Xst9vv/1W/OhHPxJZWVnJ93TnnXcKn8930JiIiIiIqGdIQuyZnIy61MyZM+HxeNo9ATsREREREVF36PPNO4mIiIiIiKhtTPp6gV27diVHfNz/30svvZTu8KgPeOCBB9q8hoiIiIjo8MbmnURERERERP0Ya/qIiIiIiIj6MSZ9rZg+fXqbk5F31LRp0/DEE090yb5as2TJEng8nm7bf1/XmSkNDkdff/11m1NzHCpJkvD11193y74fffTRds0z2Bl7m137fL52b/PAAw/goosuavc+Z86ciZtuuulQQyUiIiI6ICZ93ezdd9/Fdddd1651n3vuORxzzDFdevzW9jl37lxMnz69S4+zv4qKCuTk5EDTtOSy4cOHY82aNQfcrqsThEsuuSQ56TodHlq79jpj4MCBCAaDcLvdKcunTJmCN954o9Xv1h133IGXX345+Xr/67mtfRIRERF1JyZ91C0WLVqEadOmJSdW37hxI6LRKMaNG5fmyKi/2//a60p+vx9ffPEFzjzzzC7fd0cpitKvj0dERERdp18kfcFgELNnz8bAgQORl5eHyy+/PNl8aufOnZAkCS+88AKOOOIIeDwezJw5M+UG5rXXXsMRRxwBt9uNX/ziF1BVNVm2t/nk/PnzUVhYiIKCAsyZMwfNx7958cUXcdRRR8Hj8WDy5MlYvXp1suyUU05JztW3d1/PPPMMSkpKkJ2djd/85jcAgDVr1uCaa67B2rVrk6Mu7tq1q93noL37fP755/HAAw/grbfeShndcebMmbjyyisxffp0OBwOHH300Vi+fHly/y+99BKGDRsGp9OJAQMG4N577z1gPIsWLcJ5552X8voHP/gBAGD16tU44YQT4HK5kJOTk1x+/PHHAwBOPPFEOBwOPPDAAwCASy+9FEVFRXC5XBg/fjw+/vjjlGPNnz8/+d7vuusuHHPMMXjuuecAtKzpHDRoEB566CGccMIJcDqdOPnkk7F79+5k+fr165Nlp556Kn7zm98csPng1q1bMXXqVGRlZWHo0KEp8zLuPfYdd9yB7OxsDBw4sEVT31deeQVHH300PB4PJkyYkFIrecopp+C3v/0tpk6dCqfTiWOPPRZr164FADzyyCM47bTTUvb173//GyNGjGjXvr1eL37605/C4/FgxIgR+OSTT1L29eKLL2L06NFwOp0YOHAgfve73+FAYz5VV1fj0ksvRWFhITweD0466SREIpEW6wkh8PDDD2Po0KHIysrCWWedhe3btyfL968Z27/55v6fT2VlZYtjNL/2DvY+JEnCY489hiOPPBIejwc/+9nPWvx2eL3e5Prvv/8+Jk+ejM2bN7f6fW1ei97a9dzaPpvbtm0bfvCDHyA3NxelpaW47777oOs6gH3X05w5c1BQUIALL7yw1X28/PLLGDt2LFwuF0pLS5Pfhblz5+Lcc8/F1VdfDbfbjcGDB2PJkiV48803ccQRRyAzMxN33nlncj/tPR4RERH1AembF77rXHDBBeKiiy4STU1NIhgMigsvvFBceumlQgghduzYIQCIiy66SPj9flFRUSGKi4vFs88+K4QQYtOmTcJsNov//e9/QlEU8eSTTwqDwSDmzJkjhBDi448/FrIsi5kzZ4pQKCS+++47UVxcLJ577jkhhBBLly4VDodDLF26VMTjcfHII4+I3Nxc4fV6hRBCnHzyyeKRRx5J2dfNN98sIpGI2LBhg7Db7eLjjz8WQgjx7LPPirFjx6a8t7KyMuF2u0VZWVmr770z+5wzZ444//zzU5bNmDFDWCyWlPOQmZmZPKdGo1EsXbpUCCFEU1OT+OKLL5LbjhkzRrz00kvJ18FgULhcLuH3+5PLJk+eLN577z0hhBATJ04U9913n9A0TUSj0eR+hRACgFizZk1KbP/85z+F1+sV8XhcPPTQQyIrKyu578WLFwuPxyNWrlwpYrGY+N3vfieMRmPy893//ZeWlooxY8aI7du3i0gkIqZNmyZmzJghhBAiHo+LIUOGiLlz54pYLCZWrFghsrOzxcknn9zquVcURRx55JHi17/+tYhEIuKbb74RhYWFyXPx7LPPCoPBIO644w4Ri8XEZ599JpxOZ/L9vv3222LAgAFi1apVQtM08dprr4msrCxRX18vhEhcOwMGDBBff/21UBRF/OIXv0jGUl1dLUwmk9i1a1cynnPOOUfcd9997dr3ZZddJqZMmSKamppERUWFGD9+vGj+c/DOO++ITZs2CV3XxZo1a0ReXp548cUXWz0PmqaJ4447TsyYMUM0NjYKRVHEsmXLRDQabfGZ/utf/xJFRUXi22+/FZFIRNxyyy1i5MiRQlGUVj//Rx55JPmeFUURQ4YMSTmfmZmZKZ/P/tfewd4HADF+/HhRUVEhmpqaxJQpU8TMmTOFEPt+O5qampLrX3rppeKpp55Kfr4H+27t/3723+eMGTPEjTfeKIQQIhQKidLSUvHII4+IWCwmysrKxKhRo8QzzzyTPJ7BYBC///3vRSwWE6FQqMVn8b///U9kZWWJDz/8UGiaJmpqasTq1auTsZlMJvHaa68JVVXF7373OzFgwAAxc+ZMEQwGxfr164XFYhGrVq1q9/GIiIiob+jzSV9tba2QZVk0NjYml23evFmYTCahqmryJuu7775Llv/85z8Xs2fPFkII8fvf/15MmzYtZZ8jRoxISfoAiJqammT5vHnzxOmnn57c1zXXXJOy/fDhw5M3/vsnfZIkpdw8nXHGGeJPf/qTEKL1m8iD6cw+20r6WjsPL7zwgggGg8Jms4mnnnpK+Hy+g8b0xhtviClTpiRf19fXC4/Hk0wCTjrpJPGLX/xC7N69u8W2rSV9+/N4PGL58uVCCCGuvPJKMWvWrGRZPB4Xbrf7gEnfk08+mXz94osvitGjRwshhPjkk0+E2+1OJiBCCHHddde1mfQtX75cuFwuEYvFksvuv//+5Ht/9tlnhcvlEvF4PFl+zTXXiKuuukoIIcTZZ58tHn300ZR9nnjiieL5558XQiSundtuuy3leA6HI/l62rRp4sEHHxRCCFFTUyPMZnPy4cCB9q2qqjCbzWLlypXJsldeeUUc6BnQjTfeKH7+85+3WrZixQqRkZEhwuFwq+XNP9MzzjhDzJs3L1kWjUaF0+kUn376aYt1hUhN+j755JNWz2fzz2f/a+9g7wOA+Pe//53yXsxms9A0rUWCpqqqyMnJEeXl5UKIrk/6/vOf/4hjjjkmZX9///vfxWmnnZY8XlZWltA0rc33d9ZZZ4l77rmn1bI5c+aIE044Ifl6/fr1AoDYuHFjctmECRPE008/3e7jERERUd/Q55t37ty5E7quY/DgwfB4PMmmbLIso7q6OrleQUFB8v8zMjIQCAQAAJWVlSgtLU3Z5/6vrVYr8vLyUsorKioAAOXl5Rg0aFDK+oMHD0Z5eXmr8bpcLtjt9lZj6ayu2mdr56GiogIZGRlYtGgRFi5ciJKSEkyePLlFE8vm9m/a+c477+D000+HxWIBAPzzn/9ENBrF+PHjMWLECPz1r39tc1+6ruPOO+/EsGHD4HK54PF44PP5UF9fDyDx+ZWUlCTXN5lMKCwsPOD7PNC1UFhYCKPRmCwfOHBgm/spLy9HUVERzGZzctmQIUNSPvuioiKYTKbk6+bXzs6dO3HHHXckr1uPx4Ovv/46Wd5arMFgMPn68ssvxwsvvAAg0aTvxBNPTMZ7oH3X19cjHo+nfN77f/bvv/8+TjzxROTk5MDtduOpp55KnvP9lZWVYcCAAbDZbG2eq+bnrPn3xWKxoKioqM3vS3OVlZWtns/m9r/22vM+9j8P8XgcdXV1LY7/2WefobS0FAMGDDhorJ2xc+dOrFu3LuUz+9WvfpXyOzZgwADIcuJn+4EHHkg2LZ02bRqAxGcxbNiwNo+Rn5+f/P+9vxn7L2t+jTU/HhEREfVdff6veUlJCWRZRmVlJbxeb/JfNBpt181ZUVERysrKUpbt35cuGo2itrY2pXzvvouLi7Fz586U9Xfu3Ini4uIOv5fuuLlqbZ9tHae187D3fZ5++ul45513UF9fjwsuuADTp09P9jVqTtd1vP322yk33v/73/9SXg8dOhTPP/88qqur8cwzz+DWW2/FqlWrAKDFtAELFizAggUL8Pbbb8Pn88Hr9cLtdif7ZRUVFaX0yVNVFVVVVQc8J20pKipCdXV1Sp/OA/WrLC4uRmVlZUr/0P0/+/3Lm5/TkpISPPzwwynXbSgUwu23396ueM8//3yUl5dj1apVeOGFF3DZZZclyw6075ycHJhMppTPu/n7jMfj+NGPfoSrr74aFRUV8Pl8uOaaa9rs07c3kY1GoweNef/vSzweR2VlZfKcZWRkIBwOJ8ubf5ZFRUWtns+99r/22vs+9j8PZrMZubm5LWLf/zpuz/e1I9NglJSUYPz48Smfmd/vx/r161s95h133IFgMIhgMIh3330XQOKz2Lp1a7uPeTBM+IiIiPqHPv8XvaCgANOnT8fs2bOTT/Crq6vxxhtvtGv7n/70p/jwww/x9ttvQ1VVPP3009i8eXPKOrIs47e//S0ikQg2bdqExx9/HJdccgmAxCAjL730Ej799FOoqor58+ejoaEBZ599doffS35+PqqqqlodAKOzWttnfn4+ysrKUpIbAPjoo49SzkNVVRXOOecc1NTU4I033kAgEIDRaITL5UqpDWvuiy++QH5+frLGKR6PY/HixSnn4/nnn0dNTQ0kSYLH44Esy8mRFvPz87Ft27bkun6/H2azGTk5OYjH4/j973+fUot50UUXYcGCBfjqq6+gKAruu+8+hEKhTp2rE044AR6PBw8++CAURcGXX36J//znP22uf/zxxyM/Px933303YrEY1q1bh/nz52PGjBnJdUKhEO69917E43GsXLkSL730UvLamTVrFv74xz9i1apVEEIgHA5j8eLF7ar1AgCbzYaf/OQnuPPOO7FhwwZccMEFybID7dtgMOCnP/0p7r77bni9XlRWVuKPf/xjcttYLIZoNIrs7GxYLBasXLkSCxYsaDOOCRMm4Mgjj8R1110Hr9cLVVWxfPlyxGKxFuteeuml+Otf/4oNGzYgFovhrrvuwoABA5KDnhx77LF44YUXoKoqvv7662RNJpD4fLKyslLO57///e9k+f7XXnvfxx//+MfkQ6O7774bF154YavJTvPBiID2fV/3v54P5Nxzz0VNTQ2eeOIJRKNRaJqGTZs2YcmSJe3aHgCuvvpqPPbYY1i6dCl0XUdtbe1Bp0khIiKi/q/PJ31AYpS5vc06XS4Xvv/97ydrjg7myCOPxAsvvIAbbrgB2dnZWLlyJc4666yUdZxOJ4455hgMGTIEJ510Ei6//PLkjf3JJ5+M+fPn46qrrkJ2djZeeeUVvPvuu52aMP20007DCSecgAEDBsDj8WDXrl3JyZw7MpLnwfZ5wQUXwOVyITc3NyXOiy++GE8//TQ8Hg/+8pe/YOHChcjMzISu63jsscdQUlICt9uNxx9/HK+++mryxnjUqFF46aWXALRsXrd06VKMHj0aOTk5yWWLFy/G2LFj4XA4cP755+OPf/xjcoTNe++9FzfccAMyMzMxb948zJgxA6NGjUJpaSmGDBkCm82WUpN2xhlnYM6cOZg+fToKCgqgqiqGDx+ebEraESaTCQsXLsRbb72FzMxM/OY3v8Gll16asq9p06YlRxU1mUx46623sGrVKhQUFOC8887DLbfcgosvvji5/ujRo6GqKgoLC/GTn/wE999/P0499VQAwA9+8APMmzcPv/jFL5CZmYnBgwfjsccea7UGtS2XX3453n//fUyfPh1OpzO5/GD7nj9/PhwOB0pLS3Haaael1BI6nU48/vjj+OUvfwmXy4X7778fP/vZz1KO2/w8yLKMRYsWIRwO48gjj0ROTg7uuuuuVt/H5Zdfjuuvvx7nnnsuCgoK8M0332DRokXJhwjz58/H559/Do/Hg9tuuy0lgTaZTPjf//6H999/H1lZWbj99ttx5ZVXJsv3v/ba8z6ARCJ66qmnorS0FE6nE4899liLdbZs2YJwOJwy5Uhr36397X89H4jD4cDixYvx4YcfYtCgQcjOzsbFF1+c0rzzYKZPn44///nPmDVrFtxuNyZMmJAc8ZWIiIgOX5Joq80WAUhMszB9+vQ2h1jvL2bOnAmPx5My5UBnjBkzBv/85z8xYcIEAMD111+PgQMH4te//nUXRHlw8Xgc2dnZeO+99zBp0qRD3t/VV18NXdfx9NNPd3jb5557Do8++miXTjZPbdv/2msPSZKwZs2aFpOs7+/hhx/G9u3b8fjjjx9ilEREREQ9r1/U9FHvEI/H8bOf/QzHHXdcctmYMWO6fX6v119/HZFIBKFQCLfddhuys7M7dOPf3LJly7B7927ouo4PP/wQL730UkqzSeqdWrv2ulJJSQmuueaabtk3ERERUXdrvWMWUSeYzWbcddddKct++ctfdvtxX3jhBVx55ZUQQuCYY47B//73v5QRNTti+/btuPDCC9HU1ITi4mLMmzcPZ555ZhdHTF2ttWuvK/30pz/ttn0TERERdTc27yQiIiIiIurH2LyTiIiIiIioH2PSR0RERERE1I8x6SMiIiIiIurHmPQRERERERH1Y0z6iIiIiIiI+jEmfURERERERP0Ykz4iIiIiIqJ+jEkfERERERFRP8akj4iIiIiIqB9j0kdERERERNSPMekjIiIiIiLqx5j0ERERERER9WPGdAdwKHRdR2VlJZxOJyRJSnc4RERERES9ghACgUAARUVFkGXW8xzu+nTSV1lZiZKSknSHQURERETUK+3evRvFxcXpDoPSrE8nfU6nE0DiYna5XGmOhoiIiIiod/D7/SgpKUneL9PhrU8nfXubdLpcLiZ9RERERET7YRcoAjiQCxERERERUb/GpI+IiIiIiKgfY9JHRERERETUjzHpIyIiIiIi6seY9BEREREREfVjTPqIiIiIiIj6MSZ9RERERERE/RiTPiIiIiIion6MSR8REREREVE/xqSPiIiIiIioH2PS14dUh6rxWeVneG/He/iw7ENsaNiAuBZPd1hERERERB2i6QKfb2vAwq8r8Pm2Bmi66NbjPfjgg5gwYQKcTify8vIwffp0bNq0KWWdaDSKWbNmITs7Gw6HAz/+8Y9RU1OTss6uXbtwzjnnwG63Iy8vD7/+9a+hqupBj//WW2/h5JNPhtPphN1ux4QJE/Dcc8+lrLNz505IkoSvv/46uSwQCODUU0/FyJEjUV5e3un3z6Svj9jh24HVNavhjXqhCx0xLYadvp1YUbUCiqakOzwiIiIionZ5b10VJv/hI1z09Arc+MrXuOjpFZj8h4/w3rqqbjvm0qVLMWvWLKxYsQIffPABFEXBmWeeiVAolFzn5ptvxqJFi/Df//4XS5cuRWVlJX70ox8lyzVNwznnnIN4PI7PPvsM//rXv/Dcc8/h7rvvPuCx58+fj/PPPx+TJk3CypUr8e233+LCCy/ENddcg1tvvbXN7erq6nDqqaciFAph2bJlKC4u7vT7l4QQ3ZtWdyO/3w+32w2fzweXy5XucLqNoin4cPeH0HW91fJhmcMwLHNYD0dFRERERL1Vb71Pfm9dFa59cTX2T0CkPf998tJjcdbowm6Po66uDnl5eVi6dClOOukk+Hw+5ObmYsGCBfjJT34CANi4cSOOOuoofP755zjhhBPw7rvv4txzz0VlZSXy8/MBAE899RRuu+021NXVwWw2tzjO7t27MXToUFx//fV4+OGHU8rmz5+PG264AStWrMD3vvc97Ny5E4MHD8aaNWuQnZ2NKVOmYMCAAVi4cCEcDschvV/W9PUBtZHaNhM+AKgKdd9TESIiIiKirqDpAvcs2tAi4QOQXHbPog3d3tQTAHw+HwAgKysLALBq1SooioIzzjgjuc6IESMwcOBAfP755wCAzz//HGPGjEkmfAAwdepU+P1+rF+/vtXjvPrqq1AUpdUavauvvhoOhwMvv/xyyvJNmzZh0qRJGDlyJN55551DTvgAJn19gqZrh1RORERERJRuX+xoRJUv2ma5AFDli+KLHY3dGoeu67jpppswadIkjB49GgBQXV0Ns9kMj8eTsm5+fj6qq6uT6zRP+PaW7y1rzebNm+F2u1FY2LL20mw2Y8iQIdi8eXPK8ssvvxxHHHEE/vvf/8JisXTqPe6PSV8fkGnNPKRyIiIiIqJ0qw20nfB1Zr3OmjVrFtatW4dXXnmlW4/TWeeddx6WLVuG119/vcv2yaSvD3Canciz57VaJksyBrsH93BEREREREQdk+e0dul6nTF79my89dZb+Pjjj1MGRikoKEA8HofX601Zv6amBgUFBcl19h/Nc+/rvevsb/jw4fD5fKisrGxRFo/HsW3bNgwfPjxl+Z133om7774bF198Mf7zn/90+D22hklfH3FM3jEodBRCkqTkMqvRimPzj4Xb4k5jZC1pqo54VIXeA+2xiYiIiKhvOH5wFgrdVkhtlEsACt1WHD84q8uPLYTA7Nmz8cYbb+Cjjz7C4MGplSbjx4+HyWTChx9+mFy2adMm7Nq1CxMnTgQATJw4EWvXrkVtbW1ynQ8++AAulwsjR45s9bg//vGPYTKZWgziAiQGgQmFQrjoootalP3ud7/D3Llzcckll+Df//53p95zc8ZD3gP1CKNsxLi8cYioEfhiPphkE7KsWSlJYLopcQ11uwIINcUgIGAwyHDn2ZBd5IAk95446dDouoAmBEwGPjMiIiKi9jPIEub8YCSufXE1JCBlQJe9d4pzfjAShm64b5w1axYWLFiAhQsXwul0Jvvgud1u2Gw2uN1uXHXVVbjllluQlZUFl8uF66+/HhMnTsQJJ5wAADjzzDMxcuRIXHbZZXjooYdQXV2Nu+66C7NmzWqz793AgQPx0EMP4Ve/+hWsVisuu+wymEwmLFy4EHfccQd+9atf4Xvf+16r2955550wGAy45JJLoOt6q8lhe3HKBuoSmqpj1/oGKPGWg8o4M60oPMLT80HtIXQBtS4MtSkGqDokmxGmXBsMrq7pGHu4iCoavqvyo8IbgaYLOCxGDMl1YHBORrpDIyIiov305vvk99ZV4Z5FG1IGdSl0WzHnByO7bbqGtipKnn32WcycORNAYnL2X/3qV3j55ZcRi8UwdepUPPHEEylNN8vKynDttddiyZIlyMjIwIwZMzBv3jwYjQeuS/vf//6HP/3pT1i9ejU0TcOoUaMwa9YsXHHFFcl1mk/ZcMwxxySXP/TQQ7jjjjvw/PPP4+KLL+7c+2fSR12hsTKE+opAm+Wlo7JhsZt6MKIEoQvEtnmhh1pOYG8a4IAp197jMfVFMVXDss31CMXVFmVH5Dkwqqh3NTEmIiI63PX2+2RNF/hiRyNqA1HkORNNOrujho8S2LyTukTIFztgedAbS0vSpzZEWk34AECpDMGYaYVkZDPFg9lZH2414QOAbXUhDM11wGoy9HBURERE1FcZZAkTh2anO4zDBu92+yBd6IhpMeii7Qnbe1wvrS/WvAdIRoU4cDkl7agPIhRTW50sVQhxwDl3iIiIiCi90lrTN2jQIJSVlbVYft111+Hxxx9PQ0S9m6qr2Ny0GeWBcqi6CpPBhGJHMYZnDodBTm8ti91jRiQUb7M8w52e/nNCO3A2KjjC6AH5wgq+rfBizS4vIooGWZKQ6zSjyGOD3KxtvN53W4kTERER9XtpTfq+/PJLaNq+gT/WrVuHKVOm4IILLkhjVL2TEAJfVn+JpmhTcpmiKdjh2wFf3IfvFXwvrSN5enLt8NVGoCotB3JxZFphzej5pp0AYMgwQY223iwRAGQ7Wzjvzx9VsKshDG9EweZqP9w2E5xWEyKKBl0I1PhjUDSRMoBLrpOD4hARERH1Vmm9483NzU15PW/ePAwdOhQnn3xymiLqvWrCNSkJX3ONkUbUReranMC9JxhMMkqOykLdLj9C3jgEBGRZhjvXhpxiR9riMubYoDZGgVZqomS7CQaHOQ1R9V6bawL4rsoPANjdGEZtIAaDJKE4ywaDLCWbdzaG4ih0W2E1GVDotsFlTU9ST0REREQH12uqOeLxOF588UXccsstbdZYxWIxxGL7+mD5/YmbUyEE+vAgpO1SHao+4HusDlYj15bbZnlPMJplFB7hgabo0FQdRosB8p5RmNL1+UhWA8yDnIjvCkCo+/pAyg4TzKWufn/ddERDMIbvKn3J175wHEBiTr6KxjCG5magvCmKsJKoOQ1GFQzPd2LMADfPIxERUS/Dv83UXK9J+t588014vd7kPBmtefDBB3HPPfe0WO7z+fr9hR0LxoADjJURk2PwmX1tr5AObXfx63FigBF6RAFUAcligGyVEQu3PcXE4WhLlQ+I73uoYpNiMOwdoUcAWkzCUdkmRFUJui4wssiKUpeEYMCfpoiJiIioLXsrR4iAXjRP39SpU2E2m7Fo0aI212mtpq+kpARer7dXzj/SlcoD5fi27ts2y4/JOwZFjqIejIj6m08218Eb3pepVzRFUB1oNmmqy4oijy3xQpJw5sh8TtNARETUS/n9fng8nl47Tx/1rF5R01dWVobFixfj9ddfP+B6FosFFkvLASMkSUrrICY9YYBzAHb4dyAYD7Yoc5qdKHQU9vtz0J8JoSMarUQ8XgtAgsWSD4ulZz9Th9UIb2TfnIZ5bisawnEoe0ZANZsMwJ54huY6YDP3ip8PIiIiagXvC6m5XnHX9uyzzyIvLw/nnHNOukPptWRJxvcKv4d19etQG66FEAKSJCHfno9ROaMgS5xysa/StBiavJ9DVfY1w4hEdsNkzkKm53uQ5Z4ZJKU0OwPlTZHka5NBxpH5TlR4IwhEVWTZzbCZDBiS68AReekbnGevuBbHdt92VAYroeoq3BY3hriHINee3r6tRERERL1N2pM+Xdfx7LPPYsaMGTAa0x5Or2YxWDA+fzxiWgxRNQqr0QqLgUPl93WBwNqUhG8vJd6IYHAjXK4xPRJHjsOCEQUubKzeF4vFZMCwfCeOHehBVoYFFqPcK54cKpqCFVUrUmq+GyINaIg0YHTOaAx0DUxjdERERES9S9qzrMWLF2PXrl248sor0x1Kn2ExWJjs9RO6HkM0VtVmeSRaDqdzJCSpZ/rOHVngRIHLil2NYcRUDU6rCaXZ9mTfPUXToel62vvytdXUGQA2Nm5EkaMIRjntP29ERES0n0c+2AyDLOGG04e1KPvLh1ug6QI3Txmehsj2EUJA07QWFVLxeBxmc8en++rsdl0p7W0CzzzzTAghMHx4ej9conTQtNbnENxL6Ap0XWmzvDu47SaMKXbjuEFZOLLACavJAF9YwdLNtfjb0m146L2NePCd7/DaqnJUeCMH32E3qAq2nSiruoq6cF0PRkNERETtZZAl/PmDzfjLh1tSlv/lwy34856EsDvouo4HH3wQgwcPhs1mw9ixY/Hqq68CAJYsWQJJkvDuu+9i/PjxsFgsWL58OU455RTMnj0bN910E3JycjB16lQAwNKlS3H88cfDYrGgsLAQt99+O1RVTR6rre3SiY/CidLIYLAmBkdpI/GTZBNkOb1PhnwRBUs21WJ9lQ9RJTHXoapr+Kbci6ZwHKccmdfjffxUoR5SOREREaXH3hq+P3+wOfl6b8J3y5ThrdYAdoUHH3wQL774Ip566ikMGzYMn3zyCS699FLk5u4bC+D222/Hn/70JwwZMgSZmZkAgH/961+49tpr8emnnwIAKioqcPbZZ2PmzJl4/vnnsXHjRvziF7+A1WrF3Llzk/vaf7t06zVTNnSG3++H2+3mULTUp3m9XyEarWy1zG4f3GN9+try5c5GfLWzEVW+lhNFmmQJY0sycdboApiNPddwYHXNalSHqtssP6n4JDjM6R9shoiIKF16+33y3kTPbJAR1/RuTfhisRiysrKwePFiTJw4Mbn85z//OcLhMH75y1/i1FNPxZtvvonzzz8/WX7KKafA7/dj9erVyWV33nknXnvtNXz33XfJcQ6eeOIJ3HbbbfD5fJBludXt0o01fXTYEkJAa4hCbYxCKBokiwHGHDuMnp7tL+lyjYGmhaAovpTlZnM2HI6jejSW/fkiCtaW+7C7IQzZIEHebxAXRRfwReOo9kUxMNveY3ENdg9GTbgGrT2zys/IZ8JHRETUy91w+jD89aOtiGs6zAa52xI+ANi6dSvC4TCmTJmSsjwej2PcuHHJ18cdd1yLbcePH5/y+rvvvsPEiRNTBrabNGkSgsEgysvLMXDgwFa3SzcmfXRYEkIgXuaH5o3tW6boiAd90PPsMBf1XNIgyxZkZX0fsVg1YrFaQNozT585P20jZSqajlVlTajxR1HWEEKVPwpdF8jMMMNl228KCQFoPdxgINOaiXF547C+fj1i2r7PsCCjAGNy01szSkRERAf3lw+3JBO+uKbjLx9u6bbELxhMDP729ttvY8CAASllFosF27ZtAwBkZGS02La1Ze3R2e26C5M+Oizp/nhKwtecWhuGMcsK2dpzXw9JkmG1FsFqLeqxYx7Iml1e1PgTzTmdViOsJgOCMRUNoTiMBhl2c2L0ToMsIcNiRLaj5/sdFmQUIM+eh4ZIQ3KePrup52obiYiIqHP278O39zWAbkn8Ro4cCYvFgl27duHkk09uUb436WuPo446Cq+99lpyzmwA+PTTT+F0OlFcXNxlMXc1Jn10WFKbWvZPa07zxiAXHJ5fj2BMRZVv36ichR4bGkJxBGOJwVH8kTjsZhsAIN9pxQCPDS5rz0wgvz9ZkjkZOxERUR/S2qAtrQ3u0pWcTiduvfVW3HzzzdB1HZMnT4bP58Onn34Kl8uF0tLSdu/ruuuuw6OPPorrr78es2fPxqZNmzBnzhzccsstkOW0T4zQpsPzrpa6jRACkYACXROwZhhhNKd3Pre2CO3AzRGFqvdQJL2PNxxPee2wGDGy0AWjLKG8KYKYqsMkSyhwW3FsaSbGFnvSEygRERH1OZouWh20Ze9rTe+eLiP33nsvcnNz8eCDD2L79u3weDw49thjcccdd0DX23/fN2DAALzzzjv49a9/jbFjxyIrKwtXXXUV7rrrrm6Ju6tw9E7qMiFvDLVlfihxDQAgQYIzx4q8UhfkbppzpbOU6hCU6lCb5eaBLhizrD0YUe9R64/i8+0NrZZF4ioUVeD0o/KRmWGGrZcm9URERIc73idTc723DpL6lGhIQeVWbzLhAwABAX99BDU7/GmMrHXGbCtgaD0RlcwGGHp4BM/eJMdhgdXUejJnMxsxflAWijJtTPiIiIiI+ggmfdQlmqpCrQ6fDwCBxgji0d41WbZkMsAy2A1pv+RGshphGeqG1MtqJnuSLEs4utjdYnoGAHBZTT0+ETsRERERHRr26aMuEQkoBy039+BomO1hcJhhHZkFPRCHiOuQrAYY0jAKZW9U6Lbh+8MM2FYXRGNIgVGWMCDThsE5GTAZ+KyIiIiIqC/pXXfh1GdJBgk4QGWe3EZTynSTJAkG1+HblPNAPHYzxpdmpTsMIiIiIjpEfGRPXcKR2XbiJMsy7G7WoBERERERpQOTPuoSmQV2mCytVxznFDtgYJNAIiIiIqK04J04dQmjyYCSozLhybPDYJAhQYItw4yiIzzw5NvTHR4RERER0WGLffqoyxhNBuSVupBXyrlgiIiIiIh6C9b0ERERERER9WNM+oiIiIiIiPoxJn1ERERERET9GJM+IiIiIiKifoxJHxERERERUT/GpI+IiIiIiKgfY9JHRERERETUjzHpIyIiIiIi6seY9BEREREREfVjTPqIiIiIiIj6MSZ9RERERERE/RiTPiIiIiIion6MSR8REREREVE/xqSPiIiIiIioHzOmO4DeTtcFyhrDKG8KI67q8NhNGJLjQGaGOd2hERERERERHRSTvgPQdYHPtzegPhhLLgvGVFR4oxhX4kFJlj2N0RERERERER0cm3cewM6GUErCt5cQAmsrfFA1PQ1RERERERERtR+TvgPY3RRps0zRdFT7oz0YDRERERERUccx6TsART1wTV78IOVERERERETpxqTvANx204HLbQcuJyIiIiIiSjcmfQcwJCcDkiS1Wuaxm5HtsPRwRERERERERB3DpO8Ash0WHFPsgVFOPU0euxnfG5yVpqiIiIiIiIjaj1M2HMTAbDsKPVZUeaNQdB1umwk5rOEjIiIiIqI+gklfO5gMMgZmc04+IiIiIiLqe9i8k4iIiIiIqB9j0kdERERERNSPMekjIiIiIiLqx9Ke9FVUVODSSy9FdnY2bDYbxowZg6+++irdYREREREREfULaR3IpampCZMmTcKpp56Kd999F7m5udiyZQsyMzPTGRYREREREVG/kdak7w9/+ANKSkrw7LPPJpcNHjw4jRERERERERH1L2lt3vm///0Pxx13HC644ALk5eVh3LhxePrpp9MZEhERERERUb+S1pq+7du348knn8Qtt9yCO+64A19++SVuuOEGmM1mzJgxo8X6sVgMsVgs+drv9wMAhBAQQvRY3EREREREvRnvjak5SaTxijCbzTjuuOPw2WefJZfdcMMN+PLLL/H555+3WH/u3Lm45557WiwvKyuDy+Xq1liJiIiIiPoKv9+P0tJS+Hw+3idTemv6CgsLMXLkyJRlRx11FF577bVW1//tb3+LW265Jfna7/ejpKQEbrebFzMRERER0R6SJKU7BOpF0pr0TZo0CZs2bUpZtnnzZpSWlra6vsVigcViabFckiRe2EREREREe/DemJpL60AuN998M1asWIEHHngAW7duxYIFC/D3v/8ds2bNSmdYRERERERE/UZak74JEybgjTfewMsvv4zRo0fj3nvvxaOPPopLLrkknWERERERERH1G2kdyOVQ+f1+uN1udlAlIiIiImqG98nUXFpr+oiIiIiIiKh7MekjIiIiIiLqx5j0ERERERER9WNM+oiIiIiIiPoxJn1ERERERET9GJM+IiIiIiKifoxJHxERERERUT/GpI+IiIiIiKgfY9JHRERERETUjzHpIyIiIiIi6seY9BEREREREfVjTPqIiIiIiIj6MSZ9RERERERE/RiTPiIiIiIion6MSR8REREREVE/xqSPiIiIiIioH2PSR0RERERE1I8x6SMiIiIiIurHmPQRERERERH1Y0z6iIiIiIiI+jEmfURERERERP0Ykz4iIiIiIqJ+jEkfERERERFRP8akj4iIiIiIqB9j0kdERERERNSPMekjIiIiIiLqx5j0ERERERER9WNM+oiIiIiIiPoxY0c32LFjB5YtW4aysjKEw2Hk5uZi3LhxmDhxIqxWa3fESERERERERJ3U7qTvpZdewmOPPYavvvoK+fn5KCoqgs1mQ2NjI7Zt2war1YpLLrkEt912G0pLS7szZiIiIiIiImqndiV948aNg9lsxsyZM/Haa6+hpKQkpTwWi+Hzzz/HK6+8guOOOw5PPPEELrjggm4JmIiIiIiIiNpPEkKIg630/vvvY+rUqe3aYUNDA3bu3Inx48cfcnAH4/f74Xa74fP54HK5uv14RERERER9Ae+Tqbl21fS1N+EDgOzsbGRnZ3c6ICIiIiIiIuo6HR69c/Xq1Vi7dm3y9cKFCzF9+nTccccdiMfjXRocERERERERHZoOJ31XX301Nm/eDADYvn07LrzwQtjtdvz3v//Fb37zmy4PkIiIiIiIiDqvw0nf5s2bccwxxwAA/vvf/+Kkk07CggUL8Nxzz+G1117r6viIiIiIiIjoEHQ46RNCQNd1AMDixYtx9tlnAwBKSkpQX1/ftdERERERERHRIelw0nfcccfhvvvuwwsvvIClS5finHPOAZCYtD0/P7/LAyQiIiIiIqLO63DS9+ijj2L16tWYPXs27rzzThxxxBEAgFdffRUnnnhilwdIREREREREndeuefraIxqNwmAwwGQydcXu2oXzjxARERERtcT7ZGquXfP0CSEgSdIB17FarV0SEBEREREREXWddjXvHDVqFF555ZWDzsO3ZcsWXHvttZg3b16XBEdERERERESHpl01ffPnz8dtt92G6667DlOmTMFxxx2HoqIiWK1WNDU1YcOGDVi+fDnWr1+P2bNn49prr+3uuImIiIiIiKgdOtSnb/ny5fj3v/+NZcuWoaysDJFIBDk5ORg3bhymTp2KSy65BJmZmd0Zbwq2VSYiIiIiaon3ydRclw3k0hlz587FPffck7LsyCOPxMaNG9u1PS9mIiIiIqKWeJ9MzbWreWd3GjVqFBYvXpx8bTSmPSQiIiIiIqJ+I+0ZltFoREFBQbrDICIiIiIi6pfSnvRt2bIlOSjMxIkT8eCDD2LgwIGtrhuLxRCLxZKv/X4/gMSUEmlspUpERERE1Kvw3piaS2ufvnfffRfBYBBHHnkkqqqqcM8996CiogLr1q2D0+lssX5rfQABoKysjG2ViYiIiIj28Pv9KC0tZZ8+ApDmpG9/Xq8XpaWl+POf/4yrrrqqRXlrNX0lJSXwer28mImIiIiI9vD7/fB4PEz6CEAnm3du27YNzz77LLZt24bHHnsMeXl5ePfddzFw4ECMGjWq08F4PB4MHz4cW7dubbXcYrHAYrG0WC5JEiRJ6vRxiYiIiIj6E94bU3NyRzdYunQpxowZg5UrV+L1119HMBgEAHzzzTeYM2fOIQUTDAaxbds2FBYWHtJ+iIiIiIiIKKHDSd/tt9+O++67Dx988AHMZnNy+WmnnYYVK1Z0aF+33norli5dip07d+Kzzz7DD3/4QxgMBlx00UUdDYuIiIiIiIha0eHmnWvXrsWCBQtaLM/Ly0N9fX2H9lVeXo6LLroIDQ0NyM3NxeTJk7FixQrk5uZ2NCwiIiIiIiJqRYeTPo/Hg6qqKgwePDhl+Zo1azBgwIAO7euVV17p6OGJiIiIiIioAzrcvPPCCy/EbbfdhurqakiSBF3X8emnn+LWW2/F5Zdf3h0xEhERERERUSd1OOl74IEHMGLECJSUlCAYDGLkyJE46aSTcOKJJ+Kuu+7qjhiJiIiIiIiokzo9T9+uXbuwbt06BINBjBs3DsOGDevq2A7K7/fD7XZz/hEiIiIiomZ4n0zNdWqePgAYOHAgBg4c2JWxEBERERERURfrcNInhMCrr76Kjz/+GLW1tdB1PaX89ddf77LgiIiIiIiI6NB0OOm76aab8Le//Q2nnnoq8vPzIUlSd8RFREREREREXaDDSd8LL7yA119/HWeffXZ3xENERERERERdqMOjd7rdbgwZMqQ7YiEiIiIiIqIu1uGkb+7cubjnnnsQiUS6Ix4iIiIiIiLqQh1u3vnTn/4UL7/8MvLy8jBo0CCYTKaU8tWrV3dZcERERERERHRoOpz0zZgxA6tWrcKll17KgVyIiIiIiIh6uQ4nfW+//Tbef/99TJ48uTviISIiIiIioi7U4T59JSUlcLlc3RELERERERERdbEOJ30PP/wwfvOb32Dnzp3dEA4RERERERF1pQ4377z00ksRDocxdOhQ2O32FgO5NDY2dllwREREREREdGg6nPQ9+uij3RAGERERERERdYdOjd5JREREREREfUO7kj6/358cvMXv9x9wXQ7yQkRERERE1Hu0K+nLzMxEVVUV8vLy4PF4Wp2bTwgBSZKgaVqXB0lERERERESd066k76OPPkJWVhYA4OOPP+7WgIiIiIiIiKjrtCvpO/nkk5P/P3jwYJSUlLSo7RNCYPfu3V0bHRERERERER2SDs/TN3jwYNTV1bVY3tjYiMGDB3dJUERERERERNQ1Opz07e27t79gMAir1dolQREREREREVHXaPeUDbfccgsAQJIk/O53v4Pdbk+WaZqGlStX4phjjunyAImIiIiIiKjz2p30rVmzBkCipm/t2rUwm83JMrPZjLFjx+LWW2/t+giJiIiIiIio09qd9O0dtfOKK67AY489xvn4iIiIiIiI+oB2J317Pfvss90RBxEREREREXWDDg/kQkRERERERH0Hkz4iIiIiIqJ+jEkfERERERFRP8akj4iIiIiIqB/rVNL3wgsvYNKkSSgqKkJZWRkA4NFHH8XChQu7NDgiIiIiIiI6NB1O+p588knccsstOPvss+H1eqFpGgDA4/Hg0Ucf7er4iIiIiIiI6BB0OOmbP38+nn76adx5550wGAzJ5ccddxzWrl3bpcERERERERHRoelw0rdjxw6MGzeuxXKLxYJQKNQlQREREREREVHX6HDSN3jwYHz99dctlr/33ns46qijuiImIiIiIiIi6iLGjm5wyy23YNasWYhGoxBC4IsvvsDLL7+MBx98EM8880x3xEhERERERESd1OGk7+c//zlsNhvuuusuhMNhXHzxxSgqKsJjjz2GCy+8sDtiJCIiIiIiok6ShBCisxuHw2EEg0Hk5eV1ZUzt5vf74Xa74fP54HK50hIDEREREVFvw/tkaq7DffoikQjC4TAAwG63IxKJ4NFHH8X//d//dXlwREREREREdGg6nPSdf/75eP755wEAXq8Xxx9/PB5++GGcf/75ePLJJ7s8QCIiIiIiIuq8Did9q1evxve//30AwKuvvoqCggKUlZXh+eefx1/+8pcuD5CIiIiIiIg6r8NJXzgchtPpBAD83//9H370ox9BlmWccMIJKCsr6/IAiYiIiIiIqPM6nPQdccQRePPNN7F79268//77OPPMMwEAtbW1h9RJdN68eZAkCTfddFOn90FERERERESpOpz03X333bj11lsxaNAgfO9738PEiRMBJGr9xo0b16kgvvzyS/ztb3/D0Ucf3antiYiIiIiIqHUdTvp+8pOfYNeuXfjqq6/w3nvvJZeffvrpeOSRRzocQDAYxCWXXIKnn34amZmZHd6eiIiIiIiI2tbhpA8ACgoKMG7cOMjyvs2PP/54jBgxosP7mjVrFs455xycccYZnQmFiIiIiIiIDsDY0Q1CoRDmzZuHDz/8ELW1tdB1PaV8+/bt7d7XK6+8gtWrV+PLL79s1/qxWAyxWCz52u/3AwCEEDiEOeaJiIiIiPoV3htTcx1O+n7+859j6dKluOyyy1BYWAhJkjp14N27d+PGG2/EBx98AKvV2q5tHnzwQdxzzz0tlvt8Pl7YRERERER77K0cIQIASXQwW/J4PHj77bcxadKkQzrwm2++iR/+8IcwGAzJZZqmQZIkyLKMWCyWUga0XtNXUlICr9d7SCOHEhERERH1J36/Hx6PBz6fj/fJ1PGavszMTGRlZR3ygU8//XSsXbs2ZdkVV1yBESNG4LbbbmuR8AGAxWKBxWJpsVySpE7XOBIRERER9Te8N6bmOpz03Xvvvbj77rvxr3/9C3a7vdMHdjqdGD16dMqyjIwMZGdnt1hOREREREREndPhpO/hhx/Gtm3bkJ+fj0GDBsFkMqWUr169usuCIyIiIiIiokPT4aRv+vTp3RBGwpIlS7pt30RERERERIejDg/k0pv4/X643W52UCUiIiIiaob3ydRch2v69lq1ahW+++47AMCoUaMwbty4LguKiIiIiIiIukaHk77a2lpceOGFWLJkCTweDwDA6/Xi1FNPxSuvvILc3NyujpGIiIiIiIg6Se7oBtdffz0CgQDWr1+PxsZGNDY2Yt26dfD7/bjhhhu6I0YiIiIiIiLqpA736XO73Vi8eDEmTJiQsvyLL77AmWeeCa/X25XxHRDbKhMRERERtcT7ZGquwzV9uq63mKYBAEwmE3Rd75KgiIiIiIiIqGt0OOk77bTTcOONN6KysjK5rKKiAjfffDNOP/30Lg2OiIiIiIiIDk2Hk76//vWv8Pv9GDRoEIYOHYqhQ4di8ODB8Pv9mD9/fnfESERERERERJ3U4dE7S0pKsHr1aixevBgbN24EABx11FE444wzujw4IiIiIiIiOjScnJ2IiIiIqJ/hfTI11+HmnQDw4Ycf4txzz0027zz33HOxePHiro6NiIiIiIiIDlGHk74nnngCZ511FpxOJ2688UbceOONcLlcOPvss/H44493R4xERERERETUSR1u3llcXIzbb78ds2fPTln++OOP44EHHkBFRUWXBnggrLYmIiIiImqJ98nUXIdr+rxeL84666wWy88880z4fL4uCYqIiIiIiIi6RoeTvvPOOw9vvPFGi+ULFy7Eueee2yVBERERERERUdfo8JQNI0eOxP33348lS5Zg4sSJAIAVK1bg008/xa9+9Sv85S9/Sa57ww03dF2kRERERERE1GEd7tM3ePDg9u1YkrB9+/ZOBdVebKtMRERERNQS75OpuQ7X9O3YsaM74iAiIiIiIqJu0Kl5+prTNA1ff/01mpqauiIeIiIiIiIi6kIdTvpuuukm/OMf/wCQSPhOOukkHHvssSgpKcGSJUu6Oj4iIiIiIiI6BB1O+l599VWMHTsWALBo0SLs3LkTGzduxM0334w777yzywMkIiIiIiKizutw0ldfX4+CggIAwDvvvIMLLrgAw4cPx5VXXom1a9d2eYBERERERETUeR1O+vLz87FhwwZomob33nsPU6ZMAQCEw2EYDIYuD5CIiIiIiIg6r8Ojd15xxRX46U9/isLCQkiShDPOOAMAsHLlSowYMaLLAyQiIiIiIqLO63DSN3fuXIwePRq7d+/GBRdcAIvFAgAwGAy4/fbbuzxAIiIiIiIi6rwOT87eXDQahdVq7cp4OoSTThIRERERtcT7ZGquw336NE3DvffeiwEDBsDhcGD79u0AgN/97nfJqRyIiIiIiIiod+hw0nf//ffjueeew0MPPQSz2ZxcPnr0aDzzzDNdGhwREREREREdmg4nfc8//zz+/ve/45JLLkkZrXPs2LHYuHFjlwZHREREREREh6bDSV9FRQWOOOKIFst1XYeiKF0SFBEREREREXWNDid9I0eOxLJly1osf/XVVzFu3LguCYqIiIiIiIi6RoenbLj77rsxY8YMVFRUQNd1vP7669i0aROef/55vPXWW90RIxEREREREXVSh2v6zj//fCxatAiLFy9GRkYG7r77bnz33XdYtGgRpkyZ0h0xEhERERERUSd1qKZPVVU88MADuPLKK/HBBx90V0xERERERETURTpU02c0GvHQQw9BVdXuioeIiIiIiIi6UIebd55++ulYunRpd8RCREREREREXazDA7lMmzYNt99+O9auXYvx48cjIyMjpfy8887rsuCIiIiIiIjo0EhCCNGRDWS57cpBSZKgadohB9Vefr8fbrcbPp8PLperx45LRERERNSb8T6ZmutwTZ+u690RBxEREREREXWDDvfpIyIiIiIior6DSR8REREREVE/xqSPiIiIiIioH2PSR0RERERE1I8x6SMiIiIiIurHOpX0bdu2DXfddRcuuugi1NbWAgDeffddrF+/vkP7efLJJ3H00UfD5XLB5XJh4sSJePfddzsTEhEREREREbWiw0nf0qVLMWbMGKxcuRKvv/46gsEgAOCbb77BnDlzOrSv4uJizJs3D6tWrcJXX32F0047Deeff36Hk0ciIiIiIiJqXYeTvttvvx333XcfPvjgA5jN5uTy0047DStWrOjQvn7wgx/g7LPPxrBhwzB8+HDcf//9cDgcHd4PERERERERta7Dk7OvXbsWCxYsaLE8Ly8P9fX1nQ5E0zT897//RSgUwsSJE1tdJxaLIRaLJV/7/X4AgBACQohOH5uIiIiIqD/hvTE11+Gkz+PxoKqqCoMHD05ZvmbNGgwYMKDDAaxduxYTJ05ENBqFw+HAG2+8gZEjR7a67oMPPoh77rmnxXKfz8cLm4iIiIhoj72VI0QAIIkOZku33norVq5cif/+978YPnw4Vq9ejZqaGlx++eW4/PLLO9yvLx6PY9euXfD5fHj11VfxzDPPYOnSpa0mfq3V9JWUlMDr9cLlcnXouERERERE/ZXf74fH44HP5+N9MnU86YvH45g1axaee+45aJoGo9EITdNw8cUX47nnnoPBYDikgM444wwMHToUf/vb3w66rt/vh9vt5sVMRERERNQM75OpuQ437zSbzXj66afxu9/9DuvWrUMwGMS4ceMwbNiwLglI1/WU2jwiIiIiIiLqvA4nfXsNHDgQAwcOPKSD//a3v8W0adMwcOBABAIBLFiwAEuWLMH7779/SPslIiIiIiKihHYlfbfccku7d/jnP/+53evW1tbi8ssvR1VVFdxuN44++mi8//77mDJlSrv3QURERERERG1rV9K3Zs2adu1MkqQOHfwf//hHh9YnIiIiIiKijmlX0vfxxx93dxxERERERETUDeR0B0BERERERETdp101fT/60Y/w3HPPweVy4Uc/+tEB13399de7JDAiIiIiIiI6dO1K+txud7K/ntvt7taAiIiIiIiIqOu0e3L23//+97j11ltht9u7O6Z246STREREREQt8T6Zmmt3n7577rkHwWCwO2MhIiIiIiKiLtbupK+dFYJERERERETUi3Ro9M6OzsNHRERERERE6dWugVz2Gj58+EETv8bGxkMKiIiIiIiIiLpOh5K+e+65h6N3EhERERER9SEdSvouvPBC5OXldVcsRERERERE1MXa3aeP/fmIiIiIiIj6Ho7eSURERERE1I+1u3mnruvdGQcRERERERF1gw5N2UBERERERER9C5M+IiIiIiKifoxJHxERERERUT/GpI+IiIiIiKgfY9JHRERERETUjzHpIyIiIiIi6seY9BEREREREfVjTPqIiIiIiIj6MSZ9RERERERE/RiTPiIiIiIion6MSR8REREREVE/xqSPiIiIiIioH2PSR0RERERE1I8x6SMiIiIiIurHmPQRERERERH1Y0z6iIiIiIiI+jEmfURERERERP0Ykz4iIiIiIqJ+jEkfERERERFRP8akj4iIiIiIqB9j0kdERERERNSPMekjIiIiIiLqx5j0ERERERER9WNM+oiIiIiIiPoxJn1ERERERET9GJM+IiIiIiKifoxJHxERERERUT/GpI+IiIiIiKgfY9JHRERERETUj6U16XvwwQcxYcIEOJ1O5OXlYfr06di0aVM6QyIiIiIiIupX0pr0LV26FLNmzcKKFSvwwQcfQFEUnHnmmQiFQukMi4iIiIiIqN+QhBAi3UHsVVdXh7y8PCxduhQnnXTSQdf3+/1wu93w+XxwuVw9ECERERERUe/H+2Rqrlf16fP5fACArKysNEdCRERERETUPxjTHcBeuq7jpptuwqRJkzB69OhW14nFYojFYsnXfr8fACCEQC+qsCQiIiIiSiveG1NzvSbpmzVrFtatW4fly5e3uc6DDz6Ie+65p8Vyn8/HC5uIiIiIaI+9lSNEQC/p0zd79mwsXLgQn3zyCQYPHtzmeq3V9JWUlMDr9fbrtsq60LE7sBvlgXLEtBicZicGuQYh156b7tCIiIiIqBfy+/3weDzs00cA0lzTJ4TA9ddfjzfeeANLliw5YMIHABaLBRaLpcVySZIgSVJ3hZlWQgisrl2NunBdclksEkN9pB4jskZgiGdIGqMjIiIiot6ov94bU+ekNembNWsWFixYgIULF8LpdKK6uhoA4Ha7YbPZ0hlar1EZqkxJ+Jrb1LQJRY4iWI1WRNUomqJNMMgG5NhyIEu9aoweIiIiIiJKk7Q272zrCcSzzz6LmTNnHnT7w2Eo2i+rv2wz6QOA4ZnDEVbDqAhWJPs1mg1mjMgagWJncU+FSURERES9yOFwn0ztl/bmnXRgiqYcsHxj48YWtXpxLY5v676F1WhFji2nO8MjIiIiIqJejm0AASiajp31IXxb7sXGaj9CMTXdISW5re42yxRdQVAJtlm+zbutO0IiIiIiIqI+pNdM2ZAuTaE4Vu5oQEzVk8s2VQcwqsiFI/KcaYwsodRZit3+3dCF3mq509R2jE2xpu4Ki4iIiIiI+ojDuqZP1wVW7mhMSfj2Wl/pR30w1spWPcthduDY/GNhNphTlrssLhybf+wBR2YySod9Tk9EREREdNg7rLOCKn8UMVVrs3xnfQg5jpZTRPS0PHseTht4GmrDtcl5+rKsWdCFjs2NmxHTWk9OCzMKezhSIiIiIiLqbQ7rpC8YPXDfvWAv6tsnSzIKMgpaLDsq+yh8U/dNi0FxrEYrhnqG9mSIRERERETUCx3WSZ/NZDik8t6gyFEEi8GC7b7taIw2wigZUeAowFD3UFiN1nSHR0REREREaXZYJ31FHivWVcpQtNYHSSnNzujhiDon25aNbFt2usMgIiIiIqJe6LAeyMVokDG+NBMGueVgKENyHChws6aMiIiIiIj6tsO6pg8A8l1WnDYiDzvrw/BHFViMMkqy7L1iABciIiIiIqJDddgnfQBgNxsxssiV7jCIiIiIiIi63GHdvJOot9K0GFQ11GJUViIiIiKijmJNH1EvoiheBALrEY83AAAMBhsyMo6A3T44zZH1PWX+MpT5yxBWwrAarSh2FGOIZwhkic+6iIiI6PDCpI+ol1AUPxqbPoPQ980PqWkR+P1roesKHI7haYyub1lbtxa7A7uTr8NKGJubNqMx2ogJBRMgSS0HbyIiIiLqr/jIm6iXCIW3pCR8qWVboetKD0fUN/livpSEr7n6SD1qwjU9HBGgazr89RF4a8KIBOM9fnwiIiI6vLGmj6iXiMVq2ywTuoq40gCrpaAHI+qbqkJVBy0vyOi58+ivj6C2LABd3zcfqC3DjMJhbhhNhh6Loy/S9ViiqbMkw2zKgSzzTxYREVFn8C8oUa/BQVu6gia0A5arbdSmdodIMI6aHX6I/T7bSCiOqi0+lIzM6rFY+hIhBILBDQiHd0CIRLIsySY4Mo5ERsaQNEdHRETU97B5J1EvIISAxZzXZrkkG2E2ZfdgRH1XluXAiVSWtecSLW91uEXCt1ckFGdTzzaEQpsRCm1LJnwAIHQFgcA6RCKtN90lIiKitrGmjyhNNC2CYHATotEKCKFBks1QVD9MxpZzRmbYh0KWTWmIsu/Jz8iHw+xAMB5sUWYxWFDiLOmxWKLhA9cqxkIqbA5zD0XTNwihIRTe3mZ5KLQVNlvPfYZERET9AWv6iNJA06JobFyOSGQXxJ7miEKPQ5IM0PV9tT8GgxVO52g4HEemK9Q+R5ZkTCiYgCxbao2e0+zEhMIJMBt6LskyGA48Sqh8kPLDkar6IQ4waJGqBlK+I0RERHRwrOkjSoNQeCs0LdJiudGQAUk2IStrMiRIMBgyOL1AJ9iMNpxQeAIC8QBCSgg2ow1ui7vH43BmWxENt57AyLIMR6alhyPq/STpIH+WJAmSxAFwiIiIOoI1fURpEIu2PcKk0BVoagBGo4MJ3yFymp0oyChIS8IHAO48O0xmA5SYBl3f17dPgoS8UidkA3+C92c0OmE0tWzivJfFUsCkj4iIqINY09dHaLqGXYFdqAxWQhMa3BY3BrkGpe1mtiOEENB1AQNvcJOaD1DRmXLq3TRFR115ANXbfIhHNQihQ9cAm9OE3IFOZBVmsC/fATido+FtWtHieyDLZjgdI9IUFRERUd/FpK8PUHUVX1R/AW/Um1wWjAdRFazCMXnH9OicYx2haTrqdgXgrQ5DkgGTxQhPnh2ZhfbDvgbLbM5GNFrZeqEkwWzmSJ19VTSkoGxdA2rL/Cm1ezanCXaXGbIsM+E7CIs5B1lZkxEKbUUsXgsJMiyWAmRkHAGj0ZHu8IiIiPocJn19QJm/LCXh20sXOtbVr0OePQ+y1Ltq0eJRFRuWVcLfEIWAgCxJsDlNUGIa4lEVBUN6fw1ld8rIOAKxWHWrNXo2awkMBlsaoqJDJYRA1TYfgo3RlIQPACIBBWZrYgCS7KIMmG38+T0Qk8kDj+e4dIdBRETUL/SuTIFaVRGsaLMsrsVRF67rwWgOTtN0bPmyBr6GSHKOMl0IhPxxeKtD8DdEEA21PTrf4SBxQ3s8DMaM5DJJkmG3D4LLdXQaI6NDEfbHocTUNgdviQTiyfWIiIiIegofNbdBCIGd9WFsrPYjGFORaTej0GPF0FwHrKaeHURA0Q6cIMV72fDlgfooAk3RVsuiERXxiIZgUwzWjMN73jmLJQ+5ltMRjzdCCA0mkwuyzNEc+zIllph+o63my5rCvppERETU85j0tcIXUbBkUy2+2e2FuqeJlkmWMDjXgd2NEUwelgOHpedOncviOmBtnsvc9kh36RD0xgDRdnksrEDoB1jhMGM2Zx18pV5E0XRsqwuioikCRdORaTdjaJ4DOQ4mrGZr4nfBYjdBiWstyg0mGRIkZPSyqRqELqB5Y9CjKiSTDKPHCsnEhiBERET9BZO+/Wi6wOfbGrC5JpBM+ABA0QW21QZhNcpYX+HD94b03EAbg1yD2kz6sm3ZvXIET7PNiFhEbbPc7uZAFn2RoulYvrUe/si+2udqfxQ1gRjGlXhQkmVPY3TpZ3eZYbYakeEWiATi0DS9Rbk7zwaTuXdMOaDHNSg1YcTLA5BMMmRjItFTKkMwFztgzGbfUiIiov6Aj3L3U94URiCqIBBtmbBoQqAuGENNIIa42nPNtHLtuRiVMwqynPpxeaweHJN3TI/F0V4OjwV2lwkGQ+tN3Nx5NmS4e1dNB7XP9rpQSsK3lxAC6yp80FiDi8IjPDDbjMgudsDmMCeberqyrBg4Mht5pemvmRdCIL47gMj6ekS+qYVaG4ZSEYTaEIUQAIRAvDwAvY2+iUTUvYTQEYnsQlPTF2hqWoFQaBv0XtaVg4j6Ftb07ccXUQ544xqOaxBCQNV1mHswZy51laIoowjV4WqougqPxYNMa2aPHb8jnDlWeGvMyCrKgK8ugnh0Tz8nAJ58OwYfnZveAKnTypvCbZbFNR01/iiKPId37ZDFZsSgMdnwN0SRmW+DGhdwZFngzrX1mqlK1Jow1IYI9JAKoe37vdOCccAgweixAAJQG6Iw2w/vvrfUNaJBBb76CNS4BrPVCHeujSPYtkHXFTQ1fQ5F8SaXxWK1CIe3IzPzRBibDQBGRNRe/MXdj9kow2KUYZClVpM/gyzBYjTA1sODuQCAyWBCibOkx4/bUQaDjOIRmajbFYDJYoQSUyGEhKzCDOQPdkGWe8eNL3Wcoh24Jk89SHl3CcQD2OXfBW/MC7PBjCJHEYoyitKWZMkGGRBAoCGGkD+GhsoAXDk25A9yw+5Kb9NmoQuo9ZHE/yst+x3qgTiE2wJJAvRWWjwQdVRDRRANlcHk65AvBm9NGPmDXXDlHN4PiVoTDG5MSfj20rQI/P5vkJV1Ys8HRUR9HpO+/RRn2rGpOoBcpwXVvpYjUGY7zBiSm9Frntj3VkazAYVHeKCpOjRVh9Fs6BXJnh7XIKIqYJBhOMxHD+2MrAwzqnyRNss9aTinNaEarKldA73ZnId14TpU2aswPn98Wr6rjVVBbFtTh4g/nhzTyFcXQVNVGCMnFcHqSN+1J+IaxJ7m6ZKhZWsFoQsITYdklDmYCx2ySDCekvDtJSBQs9MPu9sMYxoeonaEHlWhh1VIRgmywwypG/+WCSEQiZa3WR6P10NVQ6ztI6IOY9K3H4fFiBEFrkQTTk1HQ3DfTVuOw4KxxR4My3OkNca+xGCUYTCm/8ZRaDriuwPQfPtGFpWsRphLnEz+OmBobgaq/VEI0bJGL99lhcvas+dS0zV8W/9tSsK3V224FrsDuzHQNbBHY9J1gbJ1DS3m4hMCCDRFUba+Hkd+r7BHY2queaInZxgBL1qMtrs3UTZmpb8WRlF8iMcbIEkyLJZCGAzsD9yX+Otan74HSCQ4/voosgp7TwKzdyRbEdcAgwTNH4ce2PddlowyTMXORBPo7ji+UCH0A/el1fUogN5zzoiob2DS14ojC5zItJtQ6A6hPhhDVNExINOKscWZsPWSUfeoY2I7/NCD+92ER1XEtnthHZ4F2cLPtblwXMWuxjCiig6HxYCSLDssRgOyHRYcO9CDteU+xJuNTFngsuLY0p7vY1obrj3gPJblgfIeT/rC/jiCTbE2y+t3BzH8eJG+1gJSosZbrYsAugBEopmntKe2RbYaoUdUGJwmCCEgRHpi1XUFXt9XiMf2jVwsSeuQkTEcDsfwHo+HOqe1qUuaUw9S3pO0YBzxnf5kTbhSE4aIazDm2iDvmY5FqDriZT5IpsxueWAoSUYYDFZoWhvJsiTBYGDCR0Qdx6SvDXkuK/Jc1nSHQV1ACyktEr59hYn+TeYBrL3da2d9CN9W+FJq8zZWBzBhUBbyXVYUZ9pR6LahNhCFogpkZpjg7OEavr1iWtvJVXvKu4MS1aAfYDAoTRWJJs893KRNDyuI14YQ3+qDrumJ/nx7kzlJAgwSoAlowTiEpgO6QGyrF7LVCMtgF+QeHtDF7/8mJeEDEiMaBoMbYTQ6YLUW9Wg81DlmqwFh/4HKe8dtiFB1xHb4gD39kvW4luzTqtQm/kZIe0ekFoBaF4Yho+unS5IkCTZbKYLBTa2WWy2FMBh4b0JEHdc7fm2JulGbCd8e2kHKDye+iNIi4QMS81d+tbMJU0bmw7xnoKNCd/qb/jnNzkMq7w52lwmyLLWZ+FkzjN3aJ6g1Sk0I0Y2NiO3yQ23a03RNBoyZVhgzbZBtJghdh9AFJKMMoehQm6KQfDEYc22IbffBelT2vpvebqZpYURjVcnXuh6HEDpk2QxJkhEKbWPS1wF14To0RBsgQUKhoxAuc89NG+LOs8NXG4HYvw0xAFmW4cxOXwIjNAGlNgytMQKlIQo9GIfBaYbBaYaINauBFImHIcZmUw3poe4b5CgjYzhUNYBotDJlucmUCZfr6G47bnvVBqLYWhtEU0iB0SBhgMeGYfkOWIxsMUPUmzHpo/7vIDfYPX0D3pvtagi32l8PSEzMvr0uiBGF6Z9nbq9sWzacZicC8UCr5YPcg3o2IAAWuwnZRRmoK285eIUkScgb5IKhlQFUuoseVhDZ0IB4ZQhKdRj63uZ0EqDURCAZJBjzM6B745CMMtCsqbPQBdS6CCSzAZo32mOTtSuKL3GjrYURiZRD0xLnUpKMMFvy9tVQ9qBIXENDKAaDLCHPaYWhD/xuKJqCL2u+hDfqTS7b5t2GAc4BODrn6B5ptmuxGZE3yInanYGUxE+WZRQe4U5bn2+hC8S2e6GHEs3DRVxLPOxojEIoOqT9mvyL/ZuhduMDEEmS4PEcB0VpQjRaBQEdFnMeLJa8bjtme+1uDGP1rqbka1UHttUFUeOPYvKwHCZ+RL0Ykz7q9wxuC5TKYIvBKpqXU0Iw1vLptarpqPBG0RSKY3dTGLsawxiS68DQNI5iK4RAVagKFcEKqLqKxmgj7EY7rMZErYEsyTgy60jk2HLSEt+QY/KgKjoCjVGoSqJ/kNlqhCffhqJhnh6NRakJQ6kLQ6kPp062LgHCAKiNMQhdAnQdcoYZ+3+iQhfQwwr0SM9N3yDLZmhaFMHQZqDZID1CqIhFKyFJPZcoaLrA17u9qPBGkg9ETAYZIwtdGJTTu/tWra1fm5Lw7VURqIDT7MQQ95AeicOda4fdbYG/PgI1rsNsNcCVY0vrIF9aUzSZ8AFIqcXWAnGYMuyQJCn5me8/0q0xs/v/bphMmTCZes98vJousK7C12pZMKZia20Qo4q6vskrEXUNJn19QCAeQCAegNlgRrY1m9NFdJBsNsCYa4da23JicclmhDGNzYt6G/uegYp0IeANKwjFEgO6mAyJJp1mg4yIomF9pQ/BmIpjSjw9HqMQAqtqVqE2XJtclmnNRDAeRJGtCPn2fBQ5imBJ4yiPVocJI04oRFN1GP76CCQZcOXYkFmYAVMPDwaleqNQG6KAoidqvfc2OxUAVB0irkGPqZAAyG1M0SCUxBQOPcVkyoKq+QGhQ9MiEEKFJJmSfZmErkHTYj0ykufaCh/Km1J/OxRNxzflXlhNBhS4e+fvR1SNoiZc02Z5ma+sx5I+ADCZDcgu6j19p1Vvan9fOcMMrdmIu3pEgyHTArUxMaCK3GyaFclmhPEwnF+wNhBNGcBrfxVNESZ9RL0Yk75eLKbF8HXt12iINCSXWY1WHJ17dNpqMPoqc5EDssUApT4CEVEhGWUYMq0w5dtbnavscFWabceGKh+21gahaAK+iILGUOJGKNdpRrZj3x/0soYQhuZm9PggLrsDu1MSPgCQIMFsMOO7hu8ghIA35kWxoxi59twejW2/oODKsSKn2AFDGue7E6pIDE4hRGrSt7dcT7SWlO2mNpus7f2+9BRJkiDLZkSiFRB6s+HyJTNs9hJYLHmIx+tgsxV3axxRRcPuxpYPiwDAH1Xw3rpqjCxywWM3YWCWHdZeNN9cUAm22VQbACJqBJquwSB3X8xKXIOvNoJAYwTRoAJrhhmefBtcubYebeLcqj3nRld16IE49GiieadQdUgWGZo/BskgJ16bDYAOSGYDjFlWGHNsPf53IzGSrgJJMkGSJMTjDYhEdkPX4zAanbDbS2Ew2Ls1BlVr/XoKRlU0huOQJQlHFoRQnGnvE82fiQ43TPoAhGIqttUFUReIodofRSCiwGk1ItdpxcBsO4blOdPyA/ZV9VfwxrxojDSiIdoARVdgNVhRF67DuUPPRYapdzct6g0SfZLCUJtigKpDththLPLA4DSnO7ReyWU1IaboUPb8cQ83a+4pQYKi6TA1u9mp9kV7POkrDyQmLtaEBl/MB1WoUDQF9ZF6CCFgMVjgsXhQFaxCibMEY3LH9Gh8sbCC2p0BRPYky7GwCiEEsgoykFXkgN3Vs9eeMdOSSOYkCZIsQRjlREecPSSjBIPHAmOmFZIstxjYSJIkWIa6u2VaE0VpQii0DYrihSQbYTJlw2LOh8FgRjRaBYslF6oSgKZFIEkSDAYHABmQZKBFQ9Su5w0r0FtJnHbWJ6bzCcU11AWjiKs6jLKEM0flY2xxJuQe+nuhaAoqghUIKkFYDBYMcAyAoitoijYhpsUOmNSZDKZuTfgigTgqNnvhr48g0LRv+oHaMiOyix0oPjIL1jTOkWpwmKE2RKHUhgFdQCga9Gii1luvVWEuyICcaYQ5ywHZlrhVMmZbYcrv2b+7QmgIBjcjFNoORamDqkYBSYbRmAGTMTFQVSxWjXB4Ozye42Cx5HdbLFkZqb9dQgjsbAgnHwx6bCZ8vduLTdUBnHhEDhwW3mIS9SaH/TfSG47js20NCEYVfLKlHrsaQhAAMswGHFXkQl3AiVp/DJOGZvfok8n6SD28MS92+nbCF9vXhl7RFHhjXry2+TUcnXs0jLIRhRmFyLZl91hsfYXQBWLbvCn9NjR/HJo/DlOxE6Ze0jxH12OIRHYjrjRBloywWgekrcN+pS+CzAwzRpoMqA/G4Y8osJh0OK0mmAwy6gIxFGcmbhQNsrR/pVGPiGpRNMYaUR4oh67r0KGjPFAOo2xEnj0Pqr4vUd0d2I1cey4KMgp6JDYlrmHXhgYEGqII+WNoKA8hFlH3JCwS7G4z8ge5MPL7A2DtoSkQDC4LzMUOxLb5Es00ZQnCJCdqLmQJcoYJxlw7LAOc0MMKJJsReiAOoQlIJhm2kVkwF3X9KKjRaCW8vlWAEND1OCKR3VBVHwwGG4xGN+LxBggRhy4USLIRsmyBwegAhAol3gSLpftbOxhbqflsCMZQH4yh1h9DWNEQjKoIxVXIkoSN1QGccVQeThqeh5Ks7q11aYg0YFXNquT1ruoq3tvxHlwWF3JtuRBCYKtvKzwWD/LtLROBAY4B3RabEAJV23yIBOMpCR8AREIKGsqDiIVUDD8+H6Y0JQbGbCtC39QBe/ushhPnUcQTD0T0uAaT1ZhM+ABAqQ7DmGWD1EM190IINDQshz+wFuHwdihKI3QtBlUNwGTKhss1BvaMIZAlI4TQ4PWtRm7OFMhy95zTDIsRAzw2VHgjAIC6QCyZ8ElAcpqriKJhVVkTTh6expYWRNTCYZ/0fVvuQ2MojuVb6rGjIZRYKASCMQ21m+qwpsyLbIcZayu8OH5wNo4scMLVAzUb3qgXvpgvmfDF9TiC8SAiagS+mA/lgXI4zU5YDBbs8u9CsbMYR+emfyjn1sSjKoJNMQghYHeZYXP0TE2H2hBJSfiaUyqDMHosPdpPqdU4FB+amlZA1/f1L4lEdsNqLYLbPb7H+28G9sxLZTMbUJJlg0EGqnyJm7aIomFLTRD1e2qCnFZjWvpvyJKMXf5dyYF5QvEQdKEjrsVRG67FiMwRKevvDuzusaSvsSqI2l0BxEIK6nYHEfHFoao6JAkw24yQjTLKN3kRj2oYd2YpLLbu/wk2ZlpgLnEBRhmxTU3QQkqiiackQTLJMLgT3wM9qsKYb4dRFYnk0GqAMdvWLTV8Qmjw+9cCQkAIHaHQluR3QNMiiMUbEQ6XQVEaYTJmwmCwQpciUNUArNYCmMweyHL39+fLzjDDZjIgouwbubE+GEcgqqLGH0VU0SH2fEWNsgSn1Yhvyn2wmY0wGrpvWhNVV7G6dnXKA44yf1my/3cwHkRDtAERNYLNTZsx1D0UR2QeAbOc+O11W9wYljmsW2IDgLA/DlXREPal9puLhRVEgyqCjTFEwyr0zwXyBrmQV+rs8d86oegwZlqgVKnJhC9RABhsRoi4BrU+AiESteGyxQjJkOgja8rt3oQeAEKh7fD51qChYQni8XpoehQGQwY0PQoBHXGlDuFIGSTJgIyMoYnQdQWxWCVstoHdFte4gZmQJKDCG0Xdnr8FBilx7QeiChRVhyfDDG84Dm84Do+997SqiWtxVAYrEdWiyDBloCijqFtru4HEw2eg5SjhqpJo+hwOxCFJEuwuM5zZ1h7v802Hl8M66QvGVDSF4thWG0CtP5qYcFXTEY6riCo64pqOQFRBYzjxR15C4snW5GE53Z74GWQDmqKJYZED8QAaool+fU3RJmhCg6IrWN+wHlaDFSElhHUN66BoCo7NPzbtA71EgwqiIQWyUULYH4e/PpIsa6gA7C4Lio5wQ+7mmlOt6QATc+sCmi/WY0PQtxqCrqCubjE0LQSj0QFJ2vd1jEYrYTZnw24fnFymKF6EQluhKE2QJCOs1iLY7UMgy113LVr2S4JznRbUB2LwR1VU+6PJgV6AxJPd76r8cNtMyHX24KApAsmET4cOf9wPX8wHAQGb0YaoHoUD+waMiKrR1vfTDWp3JBI+f32iD5OmCWBPd7pYWIXZqsHqkOCtiaBqqxeDxnR/bZVkMsBUkAG1OgRzqQtaIA5tT+2LZDPClG+H0WkG9kzPYBuZ3e0PQ2Kx2mSSpyjelIceiuJDMLQFgA4JMjQtAE0Pw2RywyAZACGQkXFEt8a3lyRJGFPsxpc7myCEgKrp8EUU7GwIIqbqey7DxO+tqgv4wgrCDg3esILNNcFuS/qqglVQtH0PtCJqBIF4YkqEnf6dCCvhZPN/WZJRF6mDw+zAmJwxGOgciCJH997sqnumN9g7ci0AxIIKAt4YJABGc+L6UhQNvrowZFlC7sCenVNTaAKy2QCD0ww9okJEVQhNQI8lmnlCF9CjGgxhBQaHGZAkGJwmmAq7v3lnILAeodA2RKPlUNUAND0EXVchdAUC2p7BjTSEglsgSQZYrYXJ/nyaFjnI3g+NQZYwvjQLRxWq8O65N6rzR+GNKPBGEtekqSmCoXkZCMU1eLo/P26XymAlvq3/Frq+75rc1LgJ4/PHI9Pa9SOkRkMKGiqCCPviEBCwO83J5v3xiIryjU1QVQ1qXEOgMYZYSIHBJMOVY4Mj0wJPnh2ubFta+4NT/5PWpO+TTz7BH//4R6xatQpVVVV44403MH369B47vqrp8EcV+KMq4rqOQEyBoglE4hriqgYJQFRJPFXVRRTvrqvGcYMyUe2LoiTLDk0XyHWacUSeE25b1yaBhRmF0IWOmBpDbaQWsiRD1VRoIvHHVNEVrKhcgXx7fvKPd22oFhE1ghMHnAi5B4c030tVNOz8tgHBpihkgwRV0RHyxuDKscLWrA9d2B9DbVkABUO6t5ZINBtlLPG0TULz0yLS0TZxj2BoC3y+1QgGvksskCRYzLmwWIoASYYEIBwpSyZ90WgVvL6vkoMPAEAwuAnRaCWysiZBlrvmaeqATBs2VPmh6fuGph9W4MTyLfUAAKfFCAlAtsOMkkw7dCHwXZUfuc6ea8YjyzKKHEUoD5ajJlSDoBKEoiswSAYYJSO+q/8OY3LGIMOUAaNshMPccyMGhgNxRIIKlHhiovOUgTQEoERVmG0GRENxeGvCUI7UeuTJrmxM1OhBliBiGiSPFZLFANlqgB5UoLstEHEduj+WeBiSad030FE3JIBC7EtYVNWf/H9Nj0JRGgGoAOTE1AySAQbZBggdFmsxZEmGyejp8pjaUui24cShMhZvqMHW2iBq/VEEIhoMcmJ8HFkS0PYMjAqDjKiiQdV1eMNxqJoOYzc83AqpoZTXEXVPc7twHerCddCFDkVXIEFKjGIrgKz8LOTac1HiKunyePZn3tsHzignW3oEGmMABCRIUBUJtqianLLBWxtG1oCMHu1CIVsNgJSYnkEPKdAVHSKqAooOXdGAPTV8mj8O2W6CJCe6B6RMe9INNC2KUHg7AEDVwgAE9D01upoeTfZvBQBdxKAqTQgENsDtHgdJMuzp99r9LEYD7GYDNtcEIO/3oFnRdWytDWLKyO7rX9gRwXgQ39R902Jgo7gWx6qaVTil5BQYu7BJbDSoYPfGxpTjhQNxRDY1oWi4B40VIaiqBk3R0VAZgq4JaIoOb10EgcYobE4zmmrCcGZakT/YBVcaH05T/5LWpC8UCmHs2LG48sor8aMf/ajHj59hMUIIQNEFIjEVui6gqBq0PU+CdCEQV3UYZBlGSUJU0bBmlxfba0OYOqoAGVYjypsiqPJF8b3B2V1a2xHTYpAlGdt82xBWw5Ahp9TgBeNBWIyWRDMFOfHkMaSE8FXNVyh0FGKoZ2iXxdIe8aiKbz8uR6hZc55gYwzWDCN8tREYTDLM1n2XW6AxipwSB4zdONqdbDch3hSD7oslJ6SWrUYYMi2QzYbEaIVpEA6XIRj4DtqeGzUBIBatht/3NSAZYTK6YbUWweU+NlEudPgD36YkfHupagCh0DY4nUd1SWwWowFjiz1Ys9ub/INlkCRkZZgxKCcDhS4rrCY55Ua2KRxHVNF6bORCk2xCnj0PMS2GYCwxgIVRNkKGDE1oaIg24NPKT5Fvz0dMi+HY/GNhM9pQ7Cju9gTQZDFAjev75g5vnvMJASWuIhKQYDDKaKoOYfeGBgwcmQ1jNyd+qjcG2banf5IA9GjqnHtqbQRiTxNGyWyAUHWodWFogTisR3i6PPEzNk/amv2uqYofQgjIshW6riCuNAIQkGUzJMkAIQQyM4/vkaadze1qCCMUV2E1ybCZDJBlCXFNgz+qwmSQkze9RllHTNVgMxkSI5B2U6sLqyF1JFWjZIQqVFRHqhFSQjDKRhj1xO+toitQhYqaUA1qQjUYnjm8W2JqzuYww2I3QQCo3x2EGtcQD2uAhMTfArsJ0YCSfAgnhEAspPboIEeSyQDZaU7059szgmfyN1bVAaOc6NcKQI+oMGSYIFsM0EMqhC5aNNfrKrFYTTIOo9G1Z6kMoatQ1TAAHXsfiMh7WofoegyxeB3s9lJYrYXdEtdeQghsrA5gZ30I31UFUNYQhtUoI9thgbnZ74TZKCMY05DbsxW4rSoLlLU5ku3eJp8DXV3XJLa+PNDq8QQEqrb6krWNQW8M+p6RlYPeGIQuEI9osDkEQk0x2F1m1Gz3w2I39UhXAOr/0noVTZs2DdOmTeuWfYfjbU8kLEsSrCYDTAYZAzKteHNNCIGYCkXVEY1r0IWAJhKNdoQkIEuAySjtac6jwm42YndTGINz9zXz+GpnA04dkZ9y4xuJa4lqfXPHTnNICWFl1UoUOYrgtroRD8eh6RpUXd3TvAmAlLj51fR9fU2MshFhJYxNjZt6NOkTusCOb+pTEj4hBFRFQ8inw5llRdgXT0n6hEj8uHVn0icZZah1qcOt61EVerUGy2AXDGkaOS4c3gYAydq5SKQs8YceABCHLJsRDG1GPN6A3Jwp0PUQdK3tpqrRaHmXJX0AUJJlh8tqwo6GEAJRBboAhsbVA/bNaG2Ew+5S7ChGU7QJgXgALkvipijDlIHqYDWa4k3ItGYipISw078TufZcbGrcBF/Mh4KMAozIHtGtc5N5Cmyo3CxBmAyQjRKgYE/iJxL3cZIECMBsM8BoNiAe01Cx2YuBo7I61Sy7Pb9zAABdIKzuaXInAXrzubZ0ARGKw75nZD7JICXXRVBDvDoIU5699f2ic79zJpMLZksu4rE6mIweKPFE8/XEkPQSZNmK+J5lkrTneyoEND2MeLwRBkPPPfkORhV8tLEW/miihkdgzwAboTjEnqa7VpMBkgRYTTICURU2kwEFLmu3jeI5wDEAG5s2Jm8eHWYHVE1FKJ6oATTt1+RbhoyqUBXGYmy3xNMau8uMeHL0X2nPH9TEPwmA3W1GqCkGXRVQoirsLgtkg9SjI3rKGSbAIEMPKhB7RrQVe6Y2kSQAWmJ+ShHTIGfbYMyxQuyZ21Kydtft077vptVahIBshSwbEFMaIUQMibNngBAqTMYsSJIRsmyFqvrhcU9I1I53o2/Lfdi5Z/wDm0mGxSijJhBDuTcCj90Ep8WIHIcVg3My4I90b61oe+39Xggh4Iv7EFNjMBlM8Fg8kCUZQSXYZcfSFB3hQLzN8mhQgWxM/G54q8PQNB26LiB0HYCUmJoDgK4LxMMqrA4TfLVh5JW62twnUXv1qUcHsVgMsdi+m1+/P9EsKDF/TepN58i7329zP6cemYu/XzYe35T7sGpnE9bs9qGtW1ZZS4x2HlM0xFQdFU0RbK0N4bNtDS3WHVnowts3TE6+PuPPS1HhjWDHg2d34F0C25q2QdEUmGUzjso8CrqmJ5t1eqNeRPRIMuGTJRmaliizW+yAABqjjW0+1eoOgaYoQv4oRMpZTPxlF0JHLKLAZJNbxGQwSt0WpxACalMUhmwrtMZoynFkk5yozejBc7SXpsWgKAEAgMGQAQEJ0Wh9ovZFKNC1CDQtAlmyQOjAzrKnkJtzxgFj1XSly9+Ly2bE2OJE81shBOKK1maCkWExwmbq/vPpi/mwy78LQSUIX8yHYCwIsyGRqFhkCzJMGbAarTBIBtSr9ci358NtcgMCqAnXIMeag+/qv0OmORMeq6dbYswtdsGd34RgUwz2uBmaEoW+52bSYJIgy4DRJMGZY4XVYYQkAdFwHMGmKBydmAfvYL9z/5w5AQAg2Y34/r++RqSNiZXHO6x4ekziSbeUYcSURd+iKdb65330ADcWzp6UfN3Z3zm361h4vV9B1wUMBicUxZf4LZMMUJQgdE2DbLBClu3JhFiW7VAUH2KxRhgMPTN0/qqyJvijiZu4cExFUzjRTNFqkBBV9UTMJgk2owEmg4QitxWNwRjOGJnfbd8Jo2zE2Jyx+Lr2a+hChwQJHosHRhhhNphTkj6jZITNYEMoHkK2NbtHfveEEPDXR+DKsiIaUhEJxCHJApIEGI0GGMwyIAnUlwfgzLHBaJIR8kUR8kXhybP32A2u6o1Bssgw5Fig1iVaXkiSDBHXICRAdpshu82QjDKMebbkexMSuu08/n97dx4mV1Xgffx716pbS1fve9LZIAkhiYRNFgWEITDKpgIiIgw4z6igLK+4MIOIqCwuoyID4jAgLoODo4AgYHBIRAQCwQCBkH3rJL131151t/P+cbs76aSTdEJ3VxPO53n6IV1VXfXjVtU99+yGUT343Aoqsfg88p3tCKEghIKiaChKKOj5BkKhSVjWJELhRgyjYkzf37ztBRW+gdcQAsfziBgqBSWouPi+IFW06UoXMJoSJSlnd2WoBjk7x4bUhiFzYbeqW2mJt2BWmKOW0/f9vT6XqgfDme2iRy5r49se2aSN5/oYYZ2QpeH7AlXb8VzF3IGX8RPh+EsTx7uq0nfrrbdy880373Z7Mpncrw+247q88HYrm3uy+HYeVQnmZgwnpEGt5WMoAkcVdA+0Vg7D81ySyR3bKwy0wu5820i09bRBf0N7vVZPm9JGxs2giGAD6pzIkXNyuL6Lp3rk7Ty6opP1sqiGim7p+/2a70RvVxaXAp6yU2+UAkbMwyl6uHh4KhScHb0DIUsnb2fJ77lB7B3x8i5ONgUGiFoFUQzmWCmmhqpDIdlHoVcZsyE6e+L7Lrncjg9RsRDDdSvwvBy+X0T4JopqoKoGQpTT19cFYi1CeGja8EPadD065u/3pBisaht+k+pJlWVj/vpbM1vZmNw4+HucOFE/iud5xIwYIS2EqZuoikrWyaKqKlVUobs7TnG5TI64GWdd2zpmVIzRQiAq1B1q4a4uYJaZROog02NTzLooqsCKq8SrTKwyMBM+BSc4pl0dPp46upUYx91xPvJNb5dGmaE8VZChgFYewvbyez2fup43Kuc5AE2bg2lmEKKJQvFlUHQcuxu7mEMIE19oaGq4fwiogqpU4/nVdHWtI5EYn4pBZ3cvEWw8X9CbKxD2PRKaixnu771FoKoeKj4h4WGhUxfxwc6RHKPzG4CFxbTQNDamNuL6LjOtmWQTWVrTraTtNIoSlBcRI0JIhKhUK6mialzKBqfokcmlyWTz5ItZMCBcAXbeA9MHwyedskEBVyjEyyOD34W2rTlcpUA0MfZDePN9fTgUIC7wfAXf8cH3EaYXLNxieWghB9VUcfp7ixRLx8lnYAzXS/G8OvL5rdh2F/nCdoTfiKqU44k0oOF7KqoWQYgIubyK62ZJKLExf2+3J/NQ3DGfVHXzlKkuhKCo+RRcBwuBKAreWJ/Bt/Ns3B6jJmbSVBEZshDYeEr4CbZ2b8W2bdJ20Ohq6RamYdLmtmFUGaN67Dy1iFP0hr2vmHPxNRdPcfGUArm8jat6eKrAs4u4iobotLHKQpTpKgXHRfe9A8430DkiSfAuq/R97Wtf47rrrhv8PZVKMWnSJBKJBGVlQy8A3rz59D0+T7rg8NL6HvocnRwmJ82sprUnh+sLXNcn77hki16wf7ECm9PBEM+oqTOvKUpjuUVLVZSWqp2GPKkKp82uI2HtGAL35/938gEN79SSGo7rsDm1mRVdK8g6WVJ2ioyTwVANKowKukQXju/geR6mZpIwE2S9LEmSHKYfhmM6VFtjvzIggJfVKcQVsp1JskkbJ+egGiqRsjCe76B4KvFonLARFOKartI8s4LQGM6pc4pZcqlMMAxHU1FjIdS4PmQInZVIjFulz/edYC8+uwNd70EID9OsxPNccvleIIMQSRRNoKohVEXHF11o6lRiMR3XLaLrw18EVVTMIhQa20VxEokEoUiMVe1piv1zv0KGxqz6OC1VY9vjknNybOrZBDt1hCkoNFU3sTG5kfqKeizDorOjk95CL9tz24P5fmqGcrOcWCgWzPcLeRACN+SSSIzd8UrMS5BIlNG6qg8ETJ6hk+rOIzzRP9dJ320OXywaI5HY//mGezvPaYpCaKdhmEuvO5nilhReTxGRd/BtH8XQ0OstRF+RaCI8OHdv0Vk7tn/RKsKEJu2YmLPr8M4DPc/tkKCnZyNVlY0I0Ug6/SadnW/2D/VU0bQomh4hHK7DNOJAkWhMH9P3cGehSJYCNh25Ihv7PNIFl0zRCxZs8QSaqpCIqJSFdRLRMB1FlZe3FfiH+TGsMbjIzbt5koUkb/e+Tc7JgRm05q/oWsFb2bfotrspekUEAsMziBMnRowPNH6AuqrxWVjDtT1acxmcnAZOsDKsAuj4FHpt0nkHVYVQ1EDXIOV5JOpCRMoMFEXBy+kkJo/9+6sZBYr5IsL28PIawg7KA+FpwYItGQetD/TyELqmYtZFCE0rH/OpAbHYPLZuewvPb0fXOlBDRRQlRD6fxfPzCNG/7oAfRlEKGKaPZY3teQ0g6Rpg9ldmBPQ4BbIYJLMOWVugKioFIJlziYUNtmR82gtZplTCuj6f0w6royo29pX5nJOjPdeOL3yqrWq2Z7fzWuo1WrOteJ6HoigYqkF1uJoTmk4gr+eZnBi9OX3KFJO29cNX0hTDJR7T2L4hRbYzi5NX8F0Vzw3miaquRi4vCId07KRKRX2E+ubKA57vWurV3KWJ5V1V6QuFQoRCu58wFEXZ7YMdDe35pLw9WQhajhWlf06Ggmno4Po4HjiegqqqwabBAiB4fk9AzvEpuIJJldEhF1RTq6OUR4Zmi+xh09l9zcOpj9azrG0ZK7pXkHd9VMVCxcFxs+S8An2FbTiegytsUJzB4QpRrZJaq4qQVsabXWs5pr5iyPMONw8HeAcXa4GyaouNb3SxbXWSTE8Bz/P7l+XWqGqOMWVuJdVNwQVtJGFSXhsZ04Ur3K489tYsbkceP2Mj3GAiiWrpaFXhYEGLeIj8G534RQ/FVNEiJmpYR68Mo8VHdzEBz8vT0/s3XDeLY3dRLG4jm9sA+GhqBNdN4fsZghULFYQo4AkFFRPXS6EoCuFwNbpeTrHYNvi8iqoTjx1GODx6F3JCCDrSwcbTAPWJ8OACRVNrYkypjtKXc1AUSFjGuBQorZlWYPfCqzxcTr1XT4/dQ6VSSU+xh225beScHIqi0JHvoKfYQ5VTRUO0gZgZC/ZDMiJjlruQcWjflCKfDiblpzrz0CXQVA274FDIeui6ghnWCUUNVE3FiumUVYUPKNPeznO7ildYGD1F3IKPLwRC94Nl69MuWllQ4RvIENF0hOejaApWUxnqXjbQ3tN5bqQcJ0kms4pcfh3p9Ns4TjeOm8b3g1UKVc8kHpqPaVQMrvkSj80at4sZVwgytsfqtgztqQKuL/CFwPWCTSWEDznbp8xSUfpXUi7Ygre2pzhqSuWo5cg5OVZ0raAr38Wb3W/Sne9GVVSiRpSufBdbUlvozHWS83K4XlDGGFrwHZ2cmIwt7HE7Zrqp4RQ88BRUFNJ9xf4FjgTFnAcIdFOjkHXIJm1UNUtofZKqxhj10xMYpj6mWYUQ2JvTOBvTeH3FYFXOjB2MsFEZHM2jCBCKhzA9vI4cojyEPg77zObzmwiZ1WhaBNfpJZfvplBYjev27bTyrY6qGvh+gYjVjO9nEcIe00WO6hJhkmtcOlIFtvTmWdOexjI1so5LV7qIK8DvLSAEmLpNwfWpjIYougLL0GhLF/nMB6YRe4fnjD3pyHXw/Nbn2ZzejIJCb6GX9cn1tGXb6M51B9NklKAs0RWdtJMm2hllft38Uf28JaqDqTbdrcEqnRA0dpfXRuhsTZNsy9GxIUmur4hrB1NhVFVBEQK74GOENDwn+K7EysPvqNdbVvqknb2rKn2jZeBLUGYZbO3L4/qCsK7RnSmSLXoUXY/+ObUoioKmDkzUV8jbQYE10IKrKArNFRaH78cm1fuah3PXpw7nsXWP4fgOi5/7ML4//NukRdYTa/lPPOGhuiqb37iIN9wwTwLQA+x4nXnNCR67avf5hgAbb/vwiLMPx3V91rzSRrIzhxhoBFTALnh0bEzRcEhZMEE/ZpKotca0wiccn2JrmuK6PrzePH7GxbeDyhS6AhkbxfYQ+f7JmgJUU0WrtAgfWoHXW0CvsjAnjd6SY6n0Cjw3Sz6/AcfuxRcO4OE4veScDXhuH74oDrbeBlR838b38zhOEt0oo6LiGFw3jW13oygGoVDtqO7R53g+L67vpidr43g+bckC6zuzdGaKRE2NKVVR3j+9iqOnVFJwPf6yupPurE08rNNYbjGtemx6Nmxv6Bi5nJvD9mxMzaQ+Wk/BLfBG1xvBPmVCUB2pprfQS9EvknWyZJ0sRa9IQ6yB+kg9k+Njs3GxXXBpXdWLU3TYuiZJX3uWfMbBs4OTief6qBpomooe0rDiJuX1EXwnjOv4jHX7t9uVx+3MYW9JY7dlEVknGJ6o9q9qWxlGi5jB8DZVQbN0jCoLe1sGszm214rfgfJ9l86uxfQlXw56wosdeH4R33cAHyGCRpNkchnZ7BpCZh3l5fOD0O/ASBfAWd2epitdRFOgJ1MgPcyQLQ/I2R7dGZuoqVMZNdE1eGtbisMay4Z9Xti/BXAcz+HF7S9ScAtsTm1mbe9a0naagldAQSFlp8g7eVJOasgwXs/z8AoeG5MbqbFq+NPGP3FC0wmDe/iNFafgoWoK3VszOEWPQsbGLvp4jj+wrSHFgoeiBHO7AVxbxSl4pHsLHP7BpgN63ZG+r25Hjp43u3A6s9h9BUTS3jFtwws+XSFVQSigmRoFRaAKgd2axp8cR68MD/u8cOALuO2sWNyO66VJp98mk1lDvrAJ388zdG6Jg++7uK5CX/JVItEpwXzwMaz0rWnPkMo7PL+2i809eTIFB59gMTdPQLCos4KCIO9CvjOD7wmqoiaWodGTtXnmrXbOnt846oscrehawSttr7C8YznbstvoyneRd/KgBA0m/sACOQIUoeArPj4+r3e/zh/X/ZGZlTOpDI9eI02iJthnr9B/ng3HDBQFVjy3lY2vd5Lp2alcE8HCLQC+74EIGgzrp5SNyzBn6b2jpJW+TCbD2rVrB3/fsGEDy5cvp7KyksmTx+bCDKAxYfHmtmBT6aipU3A8tvXlKDo+ruejKgoeweR4hWBzW1WBaEjDMnUips68pnI0VaE6br7jnrJdGZpBVbiKtmzbPh8rEKio2L691zk7IzXi1QCBbNFB+IIX/7ie9u25YOnhfooAAwXPEby5ZBt5W2DFDSJbQjTPrMCKGXt83nfSC+n2FXC2Z4PFW1wRTIT2ANeFHJBy6O+8DcpPHXxXQ7g5ihqos6txu/OocRO9fP9OtsMdO9+36cu04XtpXLsXANvuJGeD4yj4voXr27iuT9DTB4oiMDUHIXzy+c20df+dBn0q2aKDoligNyOAgguq4o3aBceKrUl6sjZFx+P1rUle29zLhq4cjuejqQovmz38bV0XsxvK8BFs7S2QKbooQtCQiDCrMcaJM2qY1VA2qi25UTO4QO3Kd7GqdxVFt4hlWOiKzobkBrJ2lp5iDwU3uAC2DIuQFiLv5tEUDRUVXdFpTbeSCCX2e9uGkX4n+tpzZAo221b30b01SzHv4hRdPMfH8wS6pqAWQNVALajkii6hcpPKhMG6ld20zKnCCGm7PS+MzoWkvS1DYXUfbnc+GLrm989J8wVe0UMUPfxQESWsoWgKimohFPDTNsU1fYRnVqDsx2q7Izluudw68vnN9KbbKeY78fwCweqFwWBAECiKj6kVcBwXRVFI5VOs3fQrqqtOJR6fOezzDtjTcdtXw9v9/3QMtuuzuj3Nd59ejb2HBXAgOI34Amw3+N7s2P6zla8/9ubg4/bU8LZro9twx21DchPJfJ6Cm2dTehO2Z1PwCnieTt7J0VfMUfAKiCFFugDVxREOyWKS7myazkySv25ZyolNJw7pAdifc/BI3lfX8elty+HqgmzaJW97eF5QiR/sRSMoI1xPoGhQ9D2KQuAosOHtXhKT45RVhfea70DeVyEE9pY0pzz3NoU9zF19Hxo/8aNQ8PEMh7M7O+gb2NR76Zohj30n7+uux21AtujQ17eOZGo1hXw3riuAoMwcKB8CgrztU3S3QfsLJCrPxhDuHp93T8dtJNm6M0VWt6dYtqmH1e1pHM/H94P1EAaOYrBm1Y5j6vuCtZ0ZasvCgw2CXZki67uyNFdYI/rMjSRbZ66TF7e/yB/X/pmufBcFN4/jO/giqNgJNEBFUd3+oyZwPRXF13B8hS2pdhZvfIEPTvogEcMatWsSRVXwPUFPW5ZC2qGQddjyVg+Z3j1P9hUeuMKnmHNJ9+TJJouU102QHe6ld72SVvpeeeUVTjnllMHfB+brXXrppTzwwANj9rqWqTG9JsrajgyH1MV4fm0nOSdYdap/B5zBbRGEEHj9wzzd/g14DU0lGtKoLdv/1fYA3vrmwj3epyoKmqJQFiqjLlLHJ894nRVdK3B9h458BwW3sKPFaqeTqxCC+tn/wbTEVD489SPUx+s5pv7oIc+7s2euO2nYSuK+Cs2ffmIB3duyZHoLfOR3yygOXOHs0jE2yVX5RCaoNBWzHl9YtpbsHgrY/emF3FcBoBQ93J48fsEj5/h4RRdsf7fFd1QBIRRwQQiPnPDRugu4vXmMaotCW4ZwZP8uwPd87FSOnWzyzVODSqDvFbn80fMoesP30s2sWMOXj74T8PD9Ipf/7jjSdhL4026PHa0LDlVRaO0NjvmyTb28tqWPdZ0ZBq51HU/gC5/1nR5benPETJ1I2MD1fXK2R1u6yIauDG3JAgtaKphWHePwpsSoXHDURep4Yv0TrOxeScHpfyPzWbpyXXTmO3G8oMHD9R2EapN20oS0EBVmXbCaoWIR0cqpt1owiLK6exPTyqeMuFDf23fi+EkVfO/0wwjHDNK9BS584vUd3wkIzrD9TzfJVbnIDiHUYLj4D7wUudVJWL0peMAjO/5spO/r/rBb0/h5B7/gIhw/qKkMfCc9EKqP59ioQkdRVYSbQ6RtzKkJ9EQIp6uA2TDyHqKRXIDnchvIZtbwL3/8NEVv+GFzwffhP1AUDd8vcsXvTiBlh4GN/T87jOZx68wU8fqHcu5LUJdRRqHZbe/HbXoDvH+BSsEtAPD6K59E+MOfR7TIeiIt9yIQZJ0sjy8+lkfcMEHr19Bzyf6cg0f0vqZsXMfj652d2AgYZoeNncsI4cHd0Tx5laDrdGUfrNywz3wH9H3wBMXNI1zcwhPBqJBRMJLjNmDh3S4F90jgyN0eu6N8CHz5uRvJOAMNWS8MeexIj9tIsr20oYeXN/bw7KquPT52Vz7g+7BkzdC/+dYTK0f8mRtJtqXbl/Lithf5+8sX7vP7MCC79isILzhui4HFzwH8BRi9a5JMd56+1h0L37RuSpJMF7GHOacMNIIAICDnuGzdnKF2Vo4Ke+gF1lg0CkrvDSX9hJx88sklW052TmOCqKnzpze39y857+AJCAuVguPj+AoIgaqpCBGcvFzfpzYeIhrSMd7BZsUj+WIeWnEom9ObEWoWVXMwNVAKDqg2CqK/DzIw0GLrkSNhWfhqnsNrDtnr6xzIMDzfF2xZ2YPn+RSz7n5d4AhfwCiM5thnpXThbITjIzyff+zuoLCHx74PjZ/QfwHrw/mFFH0FAYs7dnvsqFxw9H/OfeHs44G78tnjcrH7YV/H7YefOAJfCHqyRR5e1oo/zEsWXFDwUV0fIRTCps6GzuzgY9tTRVZ1ZHjo5WAO3qz6OE9d88HBvz/QC47rPmJhKAa+8Fn83Jl7He48cJGb9/J0vnYJwgve42VDHvk285q3j8pwZ9fxyPQVyPQV6NmWZV+nM0FwgSu08T/v+Tk3qPAVPQZr8zu1HwnHAzVY6Vax1P7vkcDZngkWQ7KKsB+VvpEoFLZhOx378QkXozKiYV8Nb7BjuNVps2tZ3Z5mS3cOZ28vLXwqLYO6sjCH1seZ01hGS1WUEw+pHvK8A/bU8LY3nvCxDAuhiCFLz++L67ujctxGqphz+jeTHt/P+UjeVy/n4HYXeLKmBi/vIXL24GrZg4/d+RdP8EhzPaqholo6kSPrCE8v3+15BxzI+7qroEyfOEvtd2WKvL09xdbeMVyy9B1Y1rGMorvnvWzH0t7Kr2MbEtxy/I6Voq9+exN2SDDcWP4hjSAK3G3lyefy8Ej3kAZBGJtGQem94T3dLDCpMkJDucXshjIMXaUjWSTneJiawPGCJcJ1VUHXFCxdpbYsTH3Coj4RpmIvG1WPhlmVs9ic3swL215AV3Vc38XUTWzfHtyXaYCqqCAgrIeZFJ/EvJp5B7xy594KzY71Kez+TUczfUV+Mmcqmd4iXa0psn1DL0B2rd993o4StgyMkEYopnHYCY3MWFDXn3/0Ck2tPIwa0gbGmYzMKJWtezp2qdQKUslXEC6oSvCV+9lHHsT3XTw3R7HYCewY7qEoOwdS+cHJP6a65kOUlx+FoSeorNqxR9poHbuwESzi0Z7ae8EpAOEH8/9cf+/HuLg/78Ee+Ai2ZrciEDTHmksyKX3X9zXZkadjS9BToO2UxwhpfKehnkLaIZuycYoevuvjuQN7bgUEAt8XXE0cw9BoPKSchkMSlFVZ1E0J5oCNyYVkWIOBHr7d7iQYp6UqDK6W0v96wvHxkkWMmv3bEH1EF+B+Ad8v8B//8CNcN4vvFxgY5jwYTQFQg/3JUPnxPzxAOFxLJDKdqqoPUll53G7PO2BPx20kDW818RC+AM8XaKqKrqu4jj/su6D0Bw2ZKrWJMHObElTHQ+Qdj4LjUxndvbzYU8PbcMdtS6qVt7rfZHO6i6yrUhmupKfQQ9OcO3F9l4KXxxW79jjsNNxeUZi34LccUf8+Dq+ay6EVhzKtfOrg/fvzeRvJ+2paOnpI4/ZJjXRuyZBPO0OG/8PuZcTnchampaPpKjOOrKWyKUpNc5zyusiovq9uZx41amDlXHzVx9/XOUWFsCfQQip6LERiRgXqXoY578/7OvgSu2R48avH8NbKr5HPt+LYXXheEQjK2KHlA9zxgZtR1Sjxstk0Nnyc6urT0Pr3Lx3pcdtXttdbk1imhuP7JMIaecejf30ShjvL73wGMVSoioWoipqcOruOSVURTj60hnh4aI/cgWbLOTmyThYUmHz4f5Bzs7i+iy98vCG1+aHPHZ1xOwBxo4wTG09gbvVcWsqncHT9UaN2/j3QTo3Rnu8oSQPe05U+x/PxBVRETKqjIXwferNFCGmEDZ++vI2uKZRbBtXxEE3lFrqqsPCw+jHPFjEinDHlDAzVwPEc2rPt1Fv1tHqtuMLF8/tXhFI1TDXYn2xB7QIOqzqM6eXTD/x191BoCiFwMjsqdk7RI6SpeLpKIh7GTbmIvVzjhxUF3ReYCihFgeoIdB/M8O6vt7deyH0OjTU0wrMqsbdmeDxS0d+rsfuJd9d+2ofVGErUIHZMA3pFiNDUcrS4Mfi8O9vfC45w5eEYSprunjZUQFWDSe3C93EUD1XQv3DFrs8ZNDxYJuhKBssATbMPqAd3X8ctpGs0JMK8vqWPOY1lrG1PY3tisOdKDaLg9Y+UVZUg3cDKngNpKyIm57yvkcqYiaEOzXIghXrOybK0/flgbp6i8ukz3wJgW2Ybr3Yuw3aDyrLoH2C387OXHfJdonqMukgdDbEG6iJ1zKiYwezKWRxWPXtE2WD397Wzz8bSdz/O0USIiKmjGB6uqqLg4SsK3s6N9v2LQykomP2VhGhYx9I16upje3xvR2OBHL0iTFFT2OvGpIJggSNACVZlQFEUhOujWPtXXIzkAtzQy1GVMGHDw9c0PC9Y3GXopaSKophBpU/ViRhg6h7RcJi4tedjBu/suIUNjZbKCAnLwNAUTF0NtvXxhn5SVIJGk8qoyYzaGMdOq6R6p+9FuuAMW+nbk+H+f2ZUTqKjsIWCX8GGZB8VoQoiWgTHSGIIFcXVyLv2Lhe5A/lUIkaE8oiF7WVwyTK9shlLP7DjNpL3tbw2ghU1iec9cuECStHHKXpD5vTtTFEhpCnoKMTiJnWNMXRdJVEWGvb13sn76mcdjGoLP+sEw5z31qumgqJrwWLfUYP4Sc17rfDtzf4MvUtEq6mINxNSC2RJ43p2sMDHbu+vQthQME2LWMgiGgoRC1t7bBzb03HbV7ZU3qE6FqIuHuZtJYOq+IOVT0UMPXrBOgg7ps1Hwwa1ZaHB7azmNiWoie8+NeZAs6Vtj/JQOV25LixDpSg8hOKhCH+vI2sU1cFQDCqsCEItUhWNM628ab8/b3ts7O0u0LVp6DDiX506h78/s4ls0tntI6fs9A9NV/iCE6OiwaJ5ZhVHntEy5LFj0SgovTe8pyt9IV0NLnbLw6QKDo4vyNsuRU8QDasYukJlxKQsYhA2NOY2JfjQrDqmVI/tymcDwnqYUyadEiw9XOxla3ortMH27Hbs/p4hUzUJ6SFmVsxkevl0ppRNwdL3r0V+RMTQVitFDYapmZZOOKJjlRnk+oY/wRphbbD3QAjQDRUzrOMUvGErfXszkoIzfGglhXV9sD4VjGLzvb335ilg6SpGtUU0ESI0qQyjas/HcH8vOFRVp6rqA4TDk+jpWYJhVFAotmMXO/CFg2F4FIs2QUvuQFCVYKsQA8OoQNcG9jjc/73cYGTHbW5TgpfWd1MZMYmGddycM7ikhqL2L2qkgS8E0VCwpPrOhY+pqSQsg9p4GE1TdlvM5UAKdV0LLmDKQ+V05bsw9KAyUB6xMDVw/P7W7/7H+yiDhV9IV4iYGlWRGBFTw9B9bJFmVvW0IfMh9pZtOK49/BwfVVeom1JG+8YUngtO0UUVIDQGezkUtf+CSAu+B9HyMKGIQXlt5ID3YRopoymGGjXwix4i33+lpvZ/3gSgKCimhtq/mqJi9Ff6whqKpqJXj/55paxsLr29L+B6STw3Byj9wyqLA6FQFANVNVFVE02LoWoWKBoRaxKW1bL3F3iHjphczur2FO3pIqm8jeMG29F4/b2ligIhTSURMaiOhWipilK7ywWtdYCVhJ1pqsb7G97PqvAqMk4GO2NTEa5A1/RgsQrfp6vQRdbO4g4sCIWCioqpmTTHmjHUYPuGqYmpY1NG7MQIaUxfUMNbf9senOvzHr7n4zkCsUsdS1GDng1NUwlbOlPnVw+WEWOxcqGiKuiVYfy8ixLWEMLH7yvuqE9pBG+sqoCloZWFCM+pJn5C4wFX+A5EU+MFrFv/A0KhGhRH61/4K8uOBhENVQ1jmtUYRjmGWYUVaRmT0RAhQ8XUVY6aUskbW5O0JX001R8cAq0Fs2EGk6lqsDZC3DKoKwtRbpnUxEPMn1TOrPqyPb/QAYgaUSbFJ5G20/QUeij4BQpuAdd3UYW60xoIAaW/jNDRqbKqiJkxaiO1VFgVNMYa9/v191R+GVUW6dbskMpYIhHikDk1rHm5HcfZfa0BCCp8qqoSjejU1MSYNDWxz/J7LFbNlg5O7+lKn6IoTK2OUmzzOLQuTiykUxbWaU8WKHo+M2oqeP/0KiqjJrPq4lSOw6aiu4oYEaaXT2dd3zrKQ+U0xZp4res1WlOt5NwcVaEqGmONlFvlHNd4HHOq54xJDkVVsKIm+WxQ2YzETDLJInpIIxQ1KK+JEraKpLoLeP09RKoaLE+vqkowXEFVUDWFqsag0qwZ72zZ9T3R+ltk06KV4sYUvqYEE9KGmx6nAKZCaFo54ekVWPNq0PazIjpS0egUotEp2HY3jpOiWOykt+8FursXgxDYTnf/tg1BVUtRVEJmNWaoinC4GYBIZOreXuIdCRsaH5nXgKJAsuBguxmKrj/Y26coCmFdIRYyqImb5F2BqgR7vqkKxMI675tcjtbfUzS58p2vOGZqJnWROoQQlIfL6Sv0ARDVo9RH69mY2jg43HngvwoKpmqSCCWwdAtVVYkZscHGkYjxznIZYQ0vO3y3drwqjBU36dycxrQ0cikbu+DhFBxQgu+BEdbQNJV4dZjaSXGmH1FDVdOBVeb3R6g5jlEfBQ883cbPuzuGempB07yeMIMN2lUFRVdRwxpaIoTRGEOLjP6G1LHYLGKxQ0GBQqENIVyscBOuV8TzUoCPopggXFQthKKE0PU4ZWXzSCSOwjRHb4n14SiKwplzGwkZGq9s7OHF9T2kCi5Fx0MIQZllkLAMNFXhyJYKZjeUoe00NMsytCG94e+EoRkcXn04h1UdxvbMdp7c8CR9xT42JDdgqAYzKmawpncNbdk2POFhaiYJM0FdtI6IESGshZlTNYd5NfNGJc++VDbGWLCwhTWVIVa/3IGW0SjmbFw72LZBATRDQ9ODCp+VMGieWUl5bQQzrNN4SPmY5NLKQ4guH7MxaATREyGK27O47VkQAsXUUSN6sI1JxMCaV01kbg3KOA+5i8dnM2nSFbS3P0ahsAXXTeM4aXwvj8BH08Loehm6FiUcbiIamUoseuiYZJlUEaEna1NmGVxx4jR++pd19OXsoNdbCHRVpSyiowK9eZewrlERNZhSFaU6HiJi6MxsiHPE5IpRz6YqKsc0HENnvhNN0VjZvZK0k8b13WC7HyXY8sQTHoZiBD1pikbCTFATrcHSLY5pOIZj6o9BU0ev8mSYGvGqMKnuofMgm2ZVoIVUtrzVQzZpB42IImhQ1QwtuKYKa1TUx2ieWUF18+htHyVJiijVSiqjIJVKkUgkSCaTlJUdWOuREIJXN/fR2psDghZcIQR1iTBHNJcTNvUhhXipbM1sZVNyE2knPTjUzVRNCm6B8nA5s6tmj/neS5neItvW9gLgu4LubRlcJ7j4NUM6KILta5P4no/vBfuWubYHioKmKZiWTqLWounQCsqqLFoOrxrTvPbWDPk3u7E3JXFTNn7WRtgDvX4KhFX0ijDW3GqMRBijOY4xBr0ZeyOEoLt7Me0dT5NOr8C2u/H9IuBjmrVYViPhcCPliaOJx+cEF8hjbNmmXpZv7uXlTT2sakuTygX7DMUsjRMPqeGfT5zKb15u5e22FOmCS8H1iYd05jSWMbe5HEWBmliI90+rGpW5CQW3wEvbXyJjZ+jKd9Fd6KboFbE9m65cF8s7lwfL1/vBxrsqKlXhKqJmlGll02iKN9EcbyZqRJlXM4/mePM7ypPqytO2ITnsfSHLYPJhlWxc0c32tX2kewrohoqiKqQ6cii6gmHqRCtCNE4vp25qGWXj+JkrrOkl93pnsD2D7wdDs/pblhUjmBusmCqKrqFGdLS4iaIFjSJafGx6IrPZ9XR1/R+5/EbsYgdC+BhGAsOsxAq3ULTbKfbfHgrVUZ6YT0XF8ej6+Iy4AEgVHFa3pVndnubNrSl0TaGuLEQspGP09/Q5uwyZ1VU1GOo5Ro2FrelWXu98naJXZEt6Cxk7g+M7rEuuQ0OjOd48pEevOd7MgroFHF59+Jjk2Zvt65J0bkmR6SnQ1Rqs/qwowfelvD5CtMKkqiFGRUOUcNQgUmaO2fxd4XgUVvcFCxcRnIOFD16ygNdbxC8EW4NoVWHCh1QQmlQ22OtdCo6TJp1+E8fpIZNdg6ZZaGoMx+nB83JoWhTTrKCq6gNY1qQxyeD7gqUbe2hPBUujdaSKvLqph66sTV3cYFpNfHD4fzIf7HmoKAqmplIeMalPhJndUMbhTYkxyQewsnslS9uWsiW1ha2ZrWiqxrSyacRCMVb3rB5c/dxUTcrD5dRH6lEVlYZYA5fNuWxMPm++L+jYlCLdVRjs8dMNjZrJcUIRnc7NaVLdebJ9Rbq3ZoPRTxGd8lqLyoYY1c2xd7xdw2hcJ0sHj/d8pW9AMu/Qlgy+mLXx8H7NwXgvSXXl6WrN4DoevivIp21UTSFaESISD5GoDdO1JUNXa4be9izZviJO0ccwVcqqLRI1FomaCE0zKwhHR7/nYFde2qawIYndmg727vMEGAqqrqJGDYyaCFrEQK+LYNSUbi+cYrGLvr4X6e17BeF7mKEGFMVD12KUlc0nHp+Fpo1fvvZUgbfbUmzszJGxbWpjYY6bXk1zf++dEILW3jwburL4vk8kpON4Al1VaKqwaExYozoZ3fVdtmW20ZHrQFEUaiO1NEYbac20smjDIp7d8ixZN4uhGXi+h6ZoTE1MZV7NvMENdy3d4oPNHxyV1tyOTSn6OnJDbtMNjeZZFZhhHeEL0j0FtrzdS6ozjx5SiSRMhBcM66ybVkai2kLVxvdiUviC/BtdFDfuqLQqmoJWESY8oxw1YuC0ZfGzwbBZNWZg1EXHrMI3oFDYRja7FsfpAxQsq5lYbBaaZgXbnPTPZ9K0CIpSugtwAM/zaU8XyRRdLEOjsdxCVWBbssDW3jyO51MRMZlSHRnzJdS3ZraypncNOSdH0SsS0kJML5/OhuQGXu98Hdd3Ceth6qP1zK2ey5zqOcHCX+NMCEGqK0+yI49r+8GQTk3BDOvopkaiJljEZdzyOB5Oew63twi+CMqCugha3MS3PXB9FEMraWVvOK6bpbfvRTw3O+T2SGQqZWVzx/S1B875W3pz2K5Pe6qAL4ZuExA1dY6fUUWm6LKxK0fWdokYGi1VUeoTB7bF1f5wfIeefA+e72H7No7vEDEihNQQf978ZzanN1NwC2iKhq7qNMQaOGvaWZSHy8c0l2t7FLIOqqZixY09VjDtgks+7QTXVAlzVMoHWemTdiYrfdJ+E0KQTzsIIQjHDLRhTkzZZJFMb5FMbwE77+L7YMWM/kqfhV6iMejCF0Fvnwq4/cNQLX3ch+7sjW134Xk5VC1CyDywVVjfa9J2mo3JjXTmOvHxcTxnyFyKslAZR9QeMaq94YWsQ7q7gO8F34N4VXjYiq5je2R6CggfrDIDK1b6BiW3r4i9LQ2Oj5oIYVRbaDvlEv1bOijjXSkVoiQrtL7bZZ0sCsqQocu2a9NV6EJVVMpD5YT1sb/olsaeED6FwnYcpwdF0QmHmzCM0lz/9OVsWnvzeL6gMmrSVD66jX2jyfEdWtOttOfa8XyPmkgNLWUthLTxn7YznuR1srQzWemTJOmg1JXvouAWiBpRKsKjP5dEkiRJkiYyeZ0s7ew9vZCLJEkHrwPdq1KSJEmSJOlgM7EGrEuSJEmSJEmSJEmjSlb6JEmSJEmSJEmSDmKy0idJkiRJkiRJknQQk5U+SZIkSZIkSZKkg5is9EmSJEmSJEmSJB3EZKVPkiRJkiRJkiTpICYrfZIkSZIkSZIkSQcxWemTJEmSJEmSJEk6iMlKnyRJkiRJkiRJ0kFMVvokSZIkSZIkSZIOYrLSJ0mSJEmSJEmSdBDTSx3gnRBCAJBKpUqcRJIkSZIkSZImjoHr44HrZem97V1d6Uun0wBMmjSpxEkkSZIkSZIkaeJJp9MkEolSx5BKTBHv4uq/7/ts27aNeDyOoiij/vypVIpJkyaxZcsWysrKRv353wmZ7cBM5GwwsfPJbAdGZjtwEzmfzHZgZLYDN5HzyWwHZqyzCSFIp9M0NjaiqnJG13vdu7qnT1VVmpubx/x1ysrKJtyJYoDMdmAmcjaY2PlktgMjsx24iZxPZjswMtuBm8j5ZLYDM5bZZA+fNEBW+yVJkiRJkiRJkg5istInSZIkSZIkSZJ0EJOVvr0IhULcdNNNhEKhUkfZjcx2YCZyNpjY+WS2AyOzHbiJnE9mOzAy24GbyPlktgMzkbNJB5939UIukiRJkiRJkiRJ0t7Jnj5JkiRJkiRJkqSDmKz0SZIkSZIkSZIkHcRkpU+SJEmSJEmSJOkgJit9u7j77ruZN2/e4J4pxx13HE8++WSpYw3rtttuQ1EUrrnmmlJHAeAb3/gGiqIM+Zk1a1apYw3aunUrn/rUp6iqqsKyLObOncsrr7xS6lhMmTJlt+OmKApXXnllqaPheR433ngjU6dOxbIspk+fzi233MJEmQqcTqe55ppraGlpwbIsjj/+eF5++eWSZPnLX/7CWWedRWNjI4qi8Mgjjwy5XwjB17/+dRoaGrAsi9NOO401a9ZMiGy/+93vOP3006mqqkJRFJYvXz4uufaVzXEcvvKVrzB37lyi0SiNjY18+tOfZtu2bRMiHwTnvVmzZhGNRqmoqOC0007jpZdemhDZdvbZz34WRVH44Q9/OCGyXXbZZbud884444wJkQ1g5cqVnH322SQSCaLRKEcffTSbN28uebbhygpFUfjud7875tlGki+TyXDVVVfR3NyMZVkcdthh3HPPPRMiW3t7O5dddhmNjY1EIhHOOOOMcTsH33rrrRx99NHE43Fqa2s599xzWbVq1ZDHFAoFrrzySqqqqojFYnzsYx+jvb19XPJJ7w2y0reL5uZmbrvtNpYtW8Yrr7zChz70Ic455xzefPPNUkcb4uWXX+anP/0p8+bNK3WUIebMmcP27dsHf/7617+WOhIAvb29nHDCCRiGwZNPPslbb73F97//fSoqKkodjZdffnnIMVu0aBEA559/fomTwe23387dd9/NT37yE1auXMntt9/OHXfcwZ133lnqaAB85jOfYdGiRfziF7/gjTfe4PTTT+e0005j69at454lm80yf/587rrrrmHvv+OOO/jxj3/MPffcw0svvUQ0GmXhwoUUCoWSZ8tms5x44oncfvvtY55luNfeU7ZcLserr77KjTfeyKuvvsrvfvc7Vq1axdlnnz0h8gEceuih/OQnP+GNN97gr3/9K1OmTOH000+ns7Oz5NkG/P73v+fFF1+ksbFxzDMNGEm2M844Y8i577//+78nRLZ169Zx4oknMmvWLBYvXszrr7/OjTfeSDgcLnm2nY/X9u3b+a//+i8UReFjH/vYmGcbSb7rrruOp556il/+8pesXLmSa665hquuuorHHnuspNmEEJx77rmsX7+eRx99lL///e+0tLRw2mmnkc1mxzzbkiVLuPLKK3nxxRdZtGgRjuNw+umnD3nta6+9lj/84Q88/PDDLFmyhG3btvHRj350zLNJ7yFC2qeKigrxn//5n6WOMSidTotDDjlELFq0SJx00kni6quvLnUkIYQQN910k5g/f36pYwzrK1/5ijjxxBNLHWNErr76ajF9+nTh+36po4gPf/jD4vLLLx9y20c/+lFx8cUXlyjRDrlcTmiaJh5//PEhty9YsED867/+a4lSBQDx+9//fvB33/dFfX29+O53vzt4W19fnwiFQuK///u/S5ptZxs2bBCA+Pvf/z6umQbsLduApUuXCkBs2rRpfELtZCT5ksmkAMQzzzwzPqH67Slba2uraGpqEitWrBAtLS3i3//938c1156yXXrppeKcc84Z9yy7Gi7bhRdeKD71qU+VJtBORvJ5O+ecc8SHPvSh8Qm0i+HyzZkzR3zzm98cclspzsm7Zlu1apUAxIoVKwZv8zxP1NTUiJ/97Gfjmk0IITo6OgQglixZIoQIygPDMMTDDz88+JiVK1cKQLzwwgvjnk86OMmevr3wPI+HHnqIbDbLcccdV+o4g6688ko+/OEPc9ppp5U6ym7WrFlDY2Mj06ZN4+KLLx6X4TAj8dhjj3HUUUdx/vnnU1tbyxFHHMHPfvazUsfajW3b/PKXv+Tyyy9HUZRSx+H444/nz3/+M6tXrwbgtdde469//StnnnlmiZOB67p4nrdb67tlWROmh3nAhg0baGtrG/KdTSQSHHvssbzwwgslTPbuk0wmURSF8vLyUkfZjW3b3HvvvSQSCebPn1/qOPi+zyWXXML111/PnDlzSh1nN4sXL6a2tpaZM2fyuc99ju7u7lJHwvd9nnjiCQ499FAWLlxIbW0txx577F6HzpZKe3s7TzzxBFdccUWpoww6/vjjeeyxx9i6dStCCJ599llWr17N6aefXtJcxWIRYEh5oaoqoVCoJOVFMpkEoLKyEoBly5bhOM6QMmLWrFlMnjxZlhHSqJGVvmG88cYbxGIxQqEQn/3sZ/n973/PYYcdVupYADz00EO8+uqr3HrrraWOsptjjz2WBx54gKeeeoq7776bDRs28IEPfIB0Ol3qaKxfv567776bQw45hKeffprPfe5zfPGLX+TnP/95qaMN8cgjj9DX18dll11W6igAfPWrX+UTn/gEs2bNwjAMjjjiCK655houvvjiUkcjHo9z3HHHccstt7Bt2zY8z+OXv/wlL7zwAtu3by91vCHa2toAqKurG3J7XV3d4H3SvhUKBb7yla9w0UUXUVZWVuo4gx5//HFisRjhcJh///d/Z9GiRVRXV5c6Frfffju6rvPFL36x1FF2c8YZZ/Dggw/y5z//mdtvv50lS5Zw5pln4nleSXN1dHSQyWS47bbbOOOMM/jTn/7Eeeedx0c/+lGWLFlS0my7+vnPf048Hp9QQwDvvPNODjvsMJqbmzFNkzPOOIO77rqLD37wgyXNNVCB+trXvkZvby+2bXP77bfT2to67uWF7/tcc801nHDCCRx++OFAUEaYprlbY5YsI6TRpJc6wEQ0c+ZMli9fTjKZ5Le//S2XXnopS5YsKXnFb8uWLVx99dUsWrRoXOYW7K+de3/mzZvHscceS0tLC//zP/9T8pZI3/c56qij+M53vgPAEUccwYoVK7jnnnu49NJLS5ptZ/fddx9nnnnmuM692Zv/+Z//4Ve/+hW//vWvmTNnDsuXL+eaa66hsbFxQhy3X/ziF1x++eU0NTWhaRoLFizgoosuYtmyZaWOJo0yx3G44IILEEJw9913lzrOEKeccgrLly+nq6uLn/3sZ1xwwQW89NJL1NbWlizTsmXL+NGPfsSrr746IUYN7OoTn/jE4L/nzp3LvHnzmD59OosXL+bUU08tWS7f9wE455xzuPbaawF43/vex9/+9jfuueceTjrppJJl29V//dd/cfHFF0+o64E777yTF198kccee4yWlhb+8pe/cOWVV9LY2FjS0UmGYfC73/2OK664gsrKSjRN47TTTuPMM88c94XJrrzySlasWDHhRqRIBz/Z0zcM0zSZMWMGRx55JLfeeivz58/nRz/6UaljsWzZMjo6OliwYAG6rqPrOkuWLOHHP/4xuq6XvIV0V+Xl5Rx66KGsXbu21FFoaGjYrdI+e/bsCTP8FGDTpk0888wzfOYznyl1lEHXX3/9YG/f3LlzueSSS7j22msnTE/z9OnTWbJkCZlMhi1btrB06VIcx2HatGmljjZEfX09wG4rsbW3tw/eJ+3ZQIVv06ZNLFq0aEL18gFEo1FmzJjB+9//fu677z50Xee+++4raabnnnuOjo4OJk+ePFhebNq0if/3//4fU6ZMKWm24UybNo3q6uqSlxfV1dXouj7hy4vnnnuOVatWTajyIp/Pc8MNN/CDH/yAs846i3nz5nHVVVdx4YUX8r3vfa/U8TjyyCNZvnw5fX19bN++naeeeoru7u5xLS+uuuoqHn/8cZ599lmam5sHb6+vr8e2bfr6+oY8XpYR0miSlb4R8H1/cDx4KZ166qm88cYbLF++fPDnqKOO4uKLL2b58uVomlbqiENkMhnWrVtHQ0NDqaNwwgkn7LY88urVq2lpaSlRot3df//91NbW8uEPf7jUUQblcjlUdehpQtO0wdbwiSIajdLQ0EBvby9PP/0055xzTqkjDTF16lTq6+v585//PHhbKpXipZdemlDzhSeigQrfmjVreOaZZ6iqqip1pH2aCGXGJZdcwuuvvz6kvGhsbOT666/n6aefLmm24bS2ttLd3V3y8sI0TY4++ugJX17cd999HHnkkRNi7ugAx3FwHGfClxmJRIKamhrWrFnDK6+8Mi7lhRCCq666it///vf83//9H1OnTh1y/5FHHolhGEPKiFWrVrF582ZZRkijRg7v3MXXvvY1zjzzTCZPnkw6nebXv/41ixcvnhCFZDweHxz/PSAajVJVVbXb7aXwpS99ibPOOouWlha2bdvGTTfdhKZpXHTRRaWOxrXXXsvxxx/Pd77zHS644AKWLl3Kvffey7333lvqaEBwkXj//fdz6aWXousT52t51lln8e1vf5vJkyczZ84c/v73v/ODH/yAyy+/vNTRAHj66acRQjBz5kzWrl3L9ddfz6xZs/inf/qncc+SyWSG9FJs2LCB5cuXU1lZyeTJk7nmmmv41re+xSGHHMLUqVO58cYbaWxs5Nxzzy15tp6eHjZv3jy4/93ABW99ff2YtzLvLVtDQwMf//jHefXVV3n88cfxPG9wfktlZSWmaY5ptn3lq6qq4tvf/jZnn302DQ0NdHV1cdddd7F169Zx2XJlX+/rrhVkwzCor69n5syZJc1WWVnJzTffzMc+9jHq6+tZt24dX/7yl5kxYwYLFy4sabbJkydz/fXXc+GFF/LBD36QU045haeeeoo//OEPLF68uOTZIGgwevjhh/n+978/5nn2N99JJ53E9ddfj2VZtLS0sGTJEh588EF+8IMflDzbww8/TE1NDZMnT+aNN97g6quv5txzzx2XRWauvPJKfv3rX/Poo48Sj8cHz2OJRALLskgkElxxxRVcd911VFZWUlZWxhe+8AWOO+443v/+9495Puk9oqRrh05Al19+uWhpaRGmaYqamhpx6qmnij/96U+ljrVHE2nLhgsvvFA0NDQI0zRFU1OTuPDCC8XatWtLHWvQH/7wB3H44YeLUCgkZs2aJe69995SRxr09NNPC0CsWrWq1FGGSKVS4uqrrxaTJ08W4XBYTJs2Tfzrv/6rKBaLpY4mhBDiN7/5jZg2bZowTVPU19eLK6+8UvT19ZUky7PPPiuA3X4uvfRSIUSwbcONN94o6urqRCgUEqeeeuq4vd/7ynb//fcPe/9NN91U0mwDW0gM9/Pss8+OebZ95cvn8+K8884TjY2NwjRN0dDQIM4++2yxdOnSkmcbznhu2bC3bLlcTpx++umipqZGGIYhWlpaxD//8z+Ltra2kmcbcN9994kZM2aIcDgs5s+fLx555JEJk+2nP/2psCyrJOe6feXbvn27uOyyy0RjY6MIh8Ni5syZ4vvf//64bEG0r2w/+tGPRHNzszAMQ0yePFn827/927iVZXs6j91///2Dj8nn8+Lzn/+8qKioEJFIRJx33nli+/bt45JPem9QhBjnGaySJEmSJEmSJEnSuJFz+iRJkiRJkiRJkg5istInSZIkSZIkSZJ0EJOVPkmSJEmSJEmSpIOYrPRJkiRJkiRJkiQdxGSlT5IkSZIkSZIk6SAmK32SJEmSJEmSJEkHMVnpkyRJkiRJkiRJOojJSp8kSZIkSZIkSdJBTFb6JEmSpDH3wAMPUF5ePq6vuXjxYhRFoa+vb1xfV5IkSZImGlnpkyRJepcZqMzs6eeUU04pdURJkiRJkiYQvdQBJEmSpP1z/PHHs3379t1uf+yxx/jsZz/L5z//+RKkkiRJkiRpopI9fZIkSe8ypmlSX18/5Ke3t5cvfelL3HDDDZx//vmDj12yZAnHHHMMoVCIhoYGvvrVr+K67uD9xWKRL37xi9TW1hIOhznxxBN5+eWXB+8f6FV8+umnOeKII7Asiw996EN0dHTw5JNPMnv2bMrKyvjkJz9JLpfbr/+PRx99lAULFhAOh5k2bRo333zzYLZPfvKTXHjhhUMe7zgO1dXVPPjggwD4vs+tt97K1KlTsSyL+fPn89vf/na/j6ckSZIkHexkpU+SJOldrq+vj3POOYeTTz6ZW265ZfD2rVu38o//+I8cffTRvPbaa9x9993cd999fOtb3xp8zJe//GX+93//l5///Oe8+uqrzJgxg4ULF9LT0zPkNb7xjW/wk5/8hL/97W9s2bKFCy64gB/+8If8+te/5oknnuBPf/oTd95554gzP/fcc3z605/m6quv5q233uKnP/0pDzzwAN/+9rcBuPjii/nDH/5AJpMZ/Junn36aXC7HeeedB8Ctt97Kgw8+yD333MObb77Jtddey6c+9SmWLFlyQMdRkiRJkg5aQpIkSXrX8jxPnHnmmWL27NkilUoNue+GG24QM2fOFL7vD9521113iVgsJjzPE5lMRhiGIX71q18N3m/btmhsbBR33HGHEEKIZ599VgDimWeeGXzMrbfeKgCxbt26wdv+5V/+RSxcuHCPOe+//36RSCQGfz/11FPFd77znSGP+cUvfiEaGhqEEEI4jiOqq6vFgw8+OHj/RRddJC688EIhhBCFQkFEIhHxt7/9bchzXHHFFeKiiy4akr23t3ePuSRJkiTpvUDO6ZMkSXoXu+GGG3jhhRdYunQp8Xh8yH0rV67kuOOOQ1GUwdtOOOEEMpkMra2t9PX14TgOJ5xwwuD9hmFwzDHHsHLlyiHPNW/evMF/19XVEYlEmDZt2pDbli5dOuLcr732Gs8///xgzx6A53kUCgVyuRyRSIQLLriAX/3qV1xyySVks1keffRRHnroIQDWrl1LLpfjH/7hH4Y8r23bHHHEESPOIUmSJEnvBbLSJ0mS9C710EMP8b3vfY8nnniCQw45ZExfyzCMwX8rijLk94HbfN8f8fNlMhluvvlmPvrRj+52XzgcBoIhnieddBIdHR0sWrQIy7I444wzBv8e4IknnqCpqWnI34dCoRHnkCRJkqT3AlnpkyRJehdavnw5V1xxBbfddhsLFy4c9jGzZ8/mf//3fxFCDPb2Pf/888TjcZqbm6mqqsI0TZ5//nlaWlqAYLGUl19+mWuuuWZM8y9YsIBVq1YxY8aMPT7m+OOPZ9KkSfzmN7/hySef5Pzzzx+sbB522GGEQiE2b97MSSedNKZZJUmSJOndTlb6JEmS3mW6uro499xzOfnkk/nUpz5FW1vbkPs1TaOmpobPf/7z/PCHP+QLX/gCV111FatWreKmm27iuuuuQ1VVotEon/vc57j++uuprKxk8uTJ3HHHHeRyOa644oox/X/4+te/zkc+8hEmT57Mxz/+cVRV5bXXXmPFihVDFpr55Cc/yT333MPq1at59tlnB2+Px+N86Utf4tprr8X3fU488USSySTPP/88ZWVlXHrppWOaX5IkSZLeTWSlT5Ik6V3miSeeYNOmTWzatImGhobd7m9paWHjxo00NTXxxz/+keuvv5758+dTWVnJFVdcwb/9278NPva2227D930uueQS0uk0Rx11FE8//TQVFRVj+v+wcOFCHn/8cb75zW9y++23YxgGs2bN4jOf+cyQx1188cV8+9vfpqWlZcjcQ4BbbrmFmpoabr31VtavX095eTkLFizghhtuGNPskiRJkvRuowghRKlDSJIkSZIkSZIkSWND7tMnSZIkSZIkSZJ0EJOVPkmSJEmSJEmSpIOYrPRJkiRJkiRJkiQdxGSlT5IkSZIkSZIk6SAmK32SJEmSJEmSJEkHMVnpkyRJkiRJkiRJOojJSp8kSZIkSZIkSdJBTFb6JEmSJEmSJEmSDmKy0idJkiRJkiRJknQQk5U+SZIkSZIkSZKkg5is9EmSJEmSJEmSJB3EZKVPkiRJkiRJkiTpIPb/AXL2O/4g7lO6AAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 900x500 with 1 Axes>"
       ]
@@ -788,7 +820,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "id": "81ea0403",
    "metadata": {},
    "outputs": [],
@@ -821,7 +853,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "id": "19806ae2",
    "metadata": {},
    "outputs": [
@@ -844,7 +876,7 @@
       "  temporal_mode: point\n",
       "  tile_format: png\n",
       "  tile_scale: 1\n",
-      "Total execution time: 60.123s\n"
+      "Total execution time: 37.450s\n"
      ]
     },
     {
@@ -882,229 +914,229 @@
        "      <th>0</th>\n",
        "      <td>3</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>88.888889</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>11.111111</td>\n",
-       "      <td>24.844026</td>\n",
-       "      <td>43.565352</td>\n",
+       "      <td>23.797227</td>\n",
+       "      <td>26.638632</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>4</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>20.791528</td>\n",
-       "      <td>22.357497</td>\n",
+       "      <td>19.156825</td>\n",
+       "      <td>21.941782</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>5</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>21.854107</td>\n",
-       "      <td>24.161906</td>\n",
+       "      <td>18.128374</td>\n",
+       "      <td>19.775837</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>6</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>15.051093</td>\n",
-       "      <td>20.070628</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>14.559629</td>\n",
+       "      <td>18.063623</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>7</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>7.408420</td>\n",
-       "      <td>9.914932</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>5.829538</td>\n",
+       "      <td>7.559138</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>8</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>4.157204</td>\n",
-       "      <td>6.375812</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2.926278</td>\n",
+       "      <td>4.333282</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>9</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.889051</td>\n",
-       "      <td>3.172772</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.814166</td>\n",
+       "      <td>2.559109</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>10</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.819688</td>\n",
-       "      <td>2.697235</td>\n",
+       "      <td>1.701222</td>\n",
+       "      <td>2.082224</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>11</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.624994</td>\n",
-       "      <td>2.344379</td>\n",
+       "      <td>1.135129</td>\n",
+       "      <td>2.293079</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>12</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.015991</td>\n",
-       "      <td>1.567489</td>\n",
+       "      <td>0.835082</td>\n",
+       "      <td>1.254490</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>13</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.945573</td>\n",
-       "      <td>1.447109</td>\n",
+       "      <td>0.631876</td>\n",
+       "      <td>3.828838</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11</th>\n",
        "      <td>14</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.787210</td>\n",
-       "      <td>1.866676</td>\n",
+       "      <td>0.758103</td>\n",
+       "      <td>1.018481</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12</th>\n",
        "      <td>15</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.025955</td>\n",
-       "      <td>1.546263</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.559256</td>\n",
+       "      <td>1.094203</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13</th>\n",
        "      <td>16</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.033864</td>\n",
-       "      <td>1.738543</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.549989</td>\n",
+       "      <td>4.627621</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14</th>\n",
        "      <td>17</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>1.113492</td>\n",
-       "      <td>1.945435</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.592183</td>\n",
+       "      <td>1.067484</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15</th>\n",
        "      <td>18</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.926164</td>\n",
-       "      <td>1.602873</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.498534</td>\n",
+       "      <td>0.590696</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>16</th>\n",
        "      <td>19</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.897090</td>\n",
-       "      <td>1.091547</td>\n",
+       "      <td>0.544914</td>\n",
+       "      <td>1.100370</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>17</th>\n",
        "      <td>20</td>\n",
        "      <td>9.0</td>\n",
-       "      <td>100.000000</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.818822</td>\n",
-       "      <td>1.040758</td>\n",
+       "      <td>0.578514</td>\n",
+       "      <td>0.689743</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "    zoom  n_tiles      ok_pct  no_data_pct  error_pct  median_latency_s  \\\n",
-       "0      3      9.0   88.888889          0.0  11.111111         24.844026   \n",
-       "1      4      9.0  100.000000          0.0   0.000000         20.791528   \n",
-       "2      5      9.0  100.000000          0.0   0.000000         21.854107   \n",
-       "3      6      9.0  100.000000          0.0   0.000000         15.051093   \n",
-       "4      7      9.0  100.000000          0.0   0.000000          7.408420   \n",
-       "5      8      9.0  100.000000          0.0   0.000000          4.157204   \n",
-       "6      9      9.0  100.000000          0.0   0.000000          1.889051   \n",
-       "7     10      9.0  100.000000          0.0   0.000000          1.819688   \n",
-       "8     11      9.0  100.000000          0.0   0.000000          1.624994   \n",
-       "9     12      9.0  100.000000          0.0   0.000000          1.015991   \n",
-       "10    13      9.0  100.000000          0.0   0.000000          0.945573   \n",
-       "11    14      9.0  100.000000          0.0   0.000000          0.787210   \n",
-       "12    15      9.0  100.000000          0.0   0.000000          1.025955   \n",
-       "13    16      9.0  100.000000          0.0   0.000000          1.033864   \n",
-       "14    17      9.0  100.000000          0.0   0.000000          1.113492   \n",
-       "15    18      9.0  100.000000          0.0   0.000000          0.926164   \n",
-       "16    19      9.0  100.000000          0.0   0.000000          0.897090   \n",
-       "17    20      9.0  100.000000          0.0   0.000000          0.818822   \n",
+       "    zoom  n_tiles  ok_pct  no_data_pct  error_pct  median_latency_s  \\\n",
+       "0      3      9.0   100.0          0.0        0.0         23.797227   \n",
+       "1      4      9.0   100.0          0.0        0.0         19.156825   \n",
+       "2      5      9.0   100.0          0.0        0.0         18.128374   \n",
+       "3      6      9.0   100.0          0.0        0.0         14.559629   \n",
+       "4      7      9.0   100.0          0.0        0.0          5.829538   \n",
+       "5      8      9.0   100.0          0.0        0.0          2.926278   \n",
+       "6      9      9.0   100.0          0.0        0.0          1.814166   \n",
+       "7     10      9.0   100.0          0.0        0.0          1.701222   \n",
+       "8     11      9.0   100.0          0.0        0.0          1.135129   \n",
+       "9     12      9.0   100.0          0.0        0.0          0.835082   \n",
+       "10    13      9.0   100.0          0.0        0.0          0.631876   \n",
+       "11    14      9.0   100.0          0.0        0.0          0.758103   \n",
+       "12    15      9.0   100.0          0.0        0.0          0.559256   \n",
+       "13    16      9.0   100.0          0.0        0.0          0.549989   \n",
+       "14    17      9.0   100.0          0.0        0.0          0.592183   \n",
+       "15    18      9.0   100.0          0.0        0.0          0.498534   \n",
+       "16    19      9.0   100.0          0.0        0.0          0.544914   \n",
+       "17    20      9.0   100.0          0.0        0.0          0.578514   \n",
        "\n",
        "    p95_latency_s  \n",
-       "0       43.565352  \n",
-       "1       22.357497  \n",
-       "2       24.161906  \n",
-       "3       20.070628  \n",
-       "4        9.914932  \n",
-       "5        6.375812  \n",
-       "6        3.172772  \n",
-       "7        2.697235  \n",
-       "8        2.344379  \n",
-       "9        1.567489  \n",
-       "10       1.447109  \n",
-       "11       1.866676  \n",
-       "12       1.546263  \n",
-       "13       1.738543  \n",
-       "14       1.945435  \n",
-       "15       1.602873  \n",
-       "16       1.091547  \n",
-       "17       1.040758  "
+       "0       26.638632  \n",
+       "1       21.941782  \n",
+       "2       19.775837  \n",
+       "3       18.063623  \n",
+       "4        7.559138  \n",
+       "5        4.333282  \n",
+       "6        2.559109  \n",
+       "7        2.082224  \n",
+       "8        2.293079  \n",
+       "9        1.254490  \n",
+       "10       3.828838  \n",
+       "11       1.018481  \n",
+       "12       1.094203  \n",
+       "13       4.627621  \n",
+       "14       1.067484  \n",
+       "15       0.590696  \n",
+       "16       1.100370  \n",
+       "17       0.689743  "
       ]
      },
-     "execution_count": 10,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1128,7 +1160,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "id": "e034280d",
    "metadata": {},
    "outputs": [
@@ -1150,8 +1182,270 @@
       "  step: P1W\n",
       "  temporal_mode: point\n",
       "  tile_format: png\n",
-      "  tile_scale: 1\n"
+      "  tile_scale: 1\n",
+      "Total execution time: 37.966s\n"
      ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>zoom</th>\n",
+       "      <th>n_tiles</th>\n",
+       "      <th>ok_pct</th>\n",
+       "      <th>no_data_pct</th>\n",
+       "      <th>error_pct</th>\n",
+       "      <th>median_latency_s</th>\n",
+       "      <th>p95_latency_s</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>3</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>22.926830</td>\n",
+       "      <td>24.378291</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>4</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>17.921357</td>\n",
+       "      <td>18.726973</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>16.929122</td>\n",
+       "      <td>17.784730</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>6</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>17.537620</td>\n",
+       "      <td>19.149198</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>7</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>9.616842</td>\n",
+       "      <td>12.005472</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>8</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.761738</td>\n",
+       "      <td>5.956546</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>9</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2.060429</td>\n",
+       "      <td>3.757879</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>10</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.500306</td>\n",
+       "      <td>2.483718</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>11</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.194113</td>\n",
+       "      <td>2.596202</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>12</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.121369</td>\n",
+       "      <td>1.218752</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>13</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.729343</td>\n",
+       "      <td>0.934768</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>14</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.696073</td>\n",
+       "      <td>0.834257</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>15</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.657786</td>\n",
+       "      <td>1.053041</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>16</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.669489</td>\n",
+       "      <td>0.975639</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>17</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.772621</td>\n",
+       "      <td>1.158088</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>18</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.701658</td>\n",
+       "      <td>0.809705</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>19</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.671382</td>\n",
+       "      <td>0.877972</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>20</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.723203</td>\n",
+       "      <td>0.804541</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    zoom  n_tiles  ok_pct  no_data_pct  error_pct  median_latency_s  \\\n",
+       "0      3      9.0   100.0          0.0        0.0         22.926830   \n",
+       "1      4      9.0   100.0          0.0        0.0         17.921357   \n",
+       "2      5      9.0   100.0          0.0        0.0         16.929122   \n",
+       "3      6      9.0   100.0          0.0        0.0         17.537620   \n",
+       "4      7      9.0   100.0          0.0        0.0          9.616842   \n",
+       "5      8      9.0   100.0          0.0        0.0          4.761738   \n",
+       "6      9      9.0   100.0          0.0        0.0          2.060429   \n",
+       "7     10      9.0   100.0          0.0        0.0          1.500306   \n",
+       "8     11      9.0   100.0          0.0        0.0          1.194113   \n",
+       "9     12      9.0   100.0          0.0        0.0          1.121369   \n",
+       "10    13      9.0   100.0          0.0        0.0          0.729343   \n",
+       "11    14      9.0   100.0          0.0        0.0          0.696073   \n",
+       "12    15      9.0   100.0          0.0        0.0          0.657786   \n",
+       "13    16      9.0   100.0          0.0        0.0          0.669489   \n",
+       "14    17      9.0   100.0          0.0        0.0          0.772621   \n",
+       "15    18      9.0   100.0          0.0        0.0          0.701658   \n",
+       "16    19      9.0   100.0          0.0        0.0          0.671382   \n",
+       "17    20      9.0   100.0          0.0        0.0          0.723203   \n",
+       "\n",
+       "    p95_latency_s  \n",
+       "0       24.378291  \n",
+       "1       18.726973  \n",
+       "2       17.784730  \n",
+       "3       19.149198  \n",
+       "4       12.005472  \n",
+       "5        5.956546  \n",
+       "6        3.757879  \n",
+       "7        2.483718  \n",
+       "8        2.596202  \n",
+       "9        1.218752  \n",
+       "10       0.934768  \n",
+       "11       0.834257  \n",
+       "12       1.053041  \n",
+       "13       0.975639  \n",
+       "14       1.158088  \n",
+       "15       0.809705  \n",
+       "16       0.877972  \n",
+       "17       0.804541  "
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -1173,13 +1467,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 13,
    "id": "3b5338d5",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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LFgkAQq/XC4PBEPp5//33Q8fv2rVL9OvXT+h0OtG2bVvx2Wefheq++OIL0a1bN2E0GoXVahW9e/cWn3zySdj5t2zZIi666CKh1+tF+/btxbvvvhuq8/l8Yvr06SItLU0YjUbRrl078eqrr9a6/lSSdfrP4cOHw2I0GAyhWSsr+utf/ypSU1OFXq8XLVq0EGPHjhUHDx4M1d98880iPj5e6PV6kZWVJR599FHhcrmqfa1rM4vojz/+KK666iphMpmEwWAQ/fv3F6tWraq0X03vmxCiyus+9dnYu3evGDVqlLBarUKv14uePXuKDz74oNI5PvzwQ9G9e3dhNptFWlqauOOOO0RRUVGoftasWUKpVAqDwSBMJpPIyMgQt9xyS5WzhhIRERFR/ZKEECIKHYyE8hlFrVZrrRdgJyIiIiIiqqtm8UwfERERERFRc8Wk7zyRm5sbNuNjxZ9TM14SERERERGdjsM7iYiIiIiImjD29BERERERETVhTPp+d9ddd+GRRx6JdhhN0gcffIB+/fqFtlu1aoXPPvssegHVYNq0aZg0aVKt9j2frouIiIiImq9mkfRdc801mDp1aqVyh8MBvV6PtWvXYsGCBfjb3/4WhejqZvbs2Rg5cmSdjtm2bRt69eqFuLg4WK1W9OvXD99++22tjvV6vbjiiiuQlJQEs9mMjh074q233qp2//Xr18NqtYaV3XLLLfjhhx/qFPP5oKleFxERERE1Lc0i6Zs8eTIWL14Mr9cbVv7hhx+iRYsWGDhwYJQiqxu/339Wx2VmZmLp0qUoKipCSUkJHnzwQVx77bVwu91nPFalUuG1115DXl4eHA4Hli5diieffBIbN248q1iIiIiIiKhhNYuk7/rrr4dKpao09G7hwoW4/fbbIUkSJk2ahGnTpoXqDh48iOuuuw6JiYnIzMzEs88+C1mWAQCdOnXC119/DQDYuXMnJEnCggULAAB2ux1qtRqFhYXIzs6GJEl4++230apVK8THx+Oee+6Bz+cLnee///0vevbsCYvFggsvvBCrV68O1U2aNAmTJ0/GjTfeCLPZjLlz5+L555/HypUrQzN31kZ8fDwyMzMhSRKEEFAqlXA6ncjPzwcAjBkzBuPHjw/t/+KLL6JLly5wu91QKpXo1q0bVCoVAECSJEiShAMHDlQ6T1FREYYNGwa73R6Kb+PGjVi0aBF69OhRbXyrV69G7969YbVa0aVLF3z++eehum+++QYXXHABTCYTkpOTcffdd9fqmmvr22+/Rbdu3WA0GjFq1CiUlpaG1Y8fPx6pqakwm83o1asX1q1bF6qr7rr8fj+Sk5Oxfv36sPJOnTrho48+imj8RERERERn0iySPrVajQkTJuBf//pXqGz37t346aefqnx+y+VyYfDgwRg8eDCOHTuGjRs3YsmSJVi4cCEAYODAgaGb/7Vr16JNmzah7fXr16Nz585ISEgItbds2TLs2LEDO3fuxA8//IA5c+YAAA4cOIARI0bgySefRFFREWbMmIHrr78ehw8fDh374YcfYvLkybDZbHjggQcwY8YMDB8+HE6nE06nEwDw3XffVRpSWRWr1QqNRoORI0fi1ltvRVZWFgDg7bffxsaNG/Huu+/ip59+wrPPPoslS5YgJiYmdOzw4cOh0+nQuXNnJCcn409/+lOl9uPj4/HVV1/BYrGE4rv00ktrjOmXX37BmDFjMHfuXBQXF+Mf//gHJkyYgL179wIAJk6ciIceegilpaU4dOgQJkyYcMbrrK2SkhJcf/31mDp1Kmw2G2677Ta8//77YfsMHjwYv/32G4qKijB27FjccMMNlRLD0536vC1atChUtmnTJhQUFNR5aC4RERER0blqFkkfUD7Ec/Xq1Thy5AgA4F//+heGDh2Kli1bVtr3iy++QGxsLKZNmwaNRoOMjAzcd999WLx4MYDKSd+TTz6JDRs2hLYHDRoU1t7s2bNhtVqRmpqKxx57DO+99x4A4KOPPsIVV1yBUaNGQaVS4YYbbsCAAQPw4Ycfho696qqrMHToUCgUCuj1+iqvbcCAAbDZbGd8DWw2G0pLS/Hee++FJWNWqxUffPAB7rvvPtx44414/vnn0a1bt7BjV65cibKyMqxfvx6jR48OSwjPxT/+8Q9MmjQJgwYNgkKhwIABAzB8+HD85z//AVCeQB04cAAnT56EwWAImzjlXK1cuRKpqam48847oVKpcN1111V672677TZYLBao1Wo89NBDkGUZv/zyyxnbnjx5Mj799NNQYr5o0SKMGzcOWq02YvETEREREdVGs0n6OnfujN69e+Pf//43AoEA3n//fUyePLnKfbOzs/Hrr7/CarWGfh544IHQcMgrrrgC27dvR0lJCX744QeMGjUKKSkp2LVrV5VJX2ZmZti/jx07BgA4evQoWrVqFbZv69atcfTo0dB2RkZGJC4/JCYmBuPHj8e8efPw3Xffhcr79++P1q1bw+Fw4I477qjyWKVSicsvvxwFBQV48cUXIxJPdnY2FixYEPZaL1++HHl5eQDKe0l//fVXdOjQAT179gwlg6e76667QkNK77rrrkqL2efm5lY6Ji8vL+y9AcLfK1mW8fjjj6Ndu3Ywm82wWq2w2+0oLCw843V16tQJXbt2xSeffAKPx4OPPvoIt99+e11eGiIiIiKiiFBFO4CGNHnyZMydOxddu3aFLMu47rrrqtwvPT0dvXr1wubNm6usT0xMRMeOHTF//ny0bdsWJpMJgwYNwkcffYQ9e/bgsssuC9s/JycHycnJAIDc3NxQ72JaWlpY4gWUJ0EVj1cowvPy07fPlt/vx/79+zFgwAAAwEsvvQSv14tOnTphxowZeOmll854bFXqGl96ejruu+8+zJ07t8r6Cy+8EJ9++ilkWcZnn32GG2+8EZdffnno9TxlwYIFoecqTznVy1ad1NRU5OTkhJXl5uYiKSkJALB48WIsXrwYq1atQrt27SBJEmJjYyGEqNW1TZ48GYsWLYJWq0VmZiYuvPDCWh1HRERERBRJzaanDwBuuukm5Ofn4/7778ett94KtVpd5X7Dhw9HQUEB3njjDXg8HgSDQezduzdsYo6BAwdi/vz5oZk/Bw0ahFdeeSU0KUtFTz/9NGw2G/Ly8jBnzhzccsstoXjWr1+P5cuXIxAIYOnSpfj2228xduzYaq8hOTkZOTk5CAQCtb7ulStX4pdffkEgEIDL5cLzzz+Po0ePhpLLrVu34plnnsGHH36IxYsXY9GiRVi1ahUAYMeOHfjmm2/gdrsRCATwxRdf4IMPPsDQoUOrja+0tBQnTpyoVWx33nknFi5ciHXr1iEYDMLr9WLTpk347bff4PP58N5776GkpAQKhSL03OKpSWXO1bXXXotjx47h7bffDl3b2rVrQ/UOhwMajQYJCQnw+Xx4+umnz/g8X0U33XQTtm7dirlz57KXj4iIiIiiplklfSaTCTfeeCOys7OrHdoJAEajEatXr8aaNWtCs26OGzcuNLwTKE/6HA5HaCjn5ZdfDpfLVWloJwCMGDECPXr0QNeuXXHJJZdgxowZAIC2bdti6dKlmDVrFuLi4vD0009j2bJlaN26dbWxjRkzBmazGYmJiaEkaOPGjTXO5FlYWIgxY8bAarUiIyMD33zzDb744gu0adMGTqcTN998M5577jl069YN6enpePvttzFx4kScOHECgUAAM2bMQHJyMuLj4zFjxgy8/PLLGDduXJXn6tChAyZPnozOnTvDarVW6sk8Xc+ePfHhhx/iiSeeQGJiIlq2bIknn3wytLzG4sWLQ72p9957LxYvXoz4+Pga26ytuLg4LF++HK+88gqsViveeeedUEIOlE8i06VLF2RmZqJ169aIiYlBWlpards3mUwYM2YM9uzZE9YuEREREVFDkkRtx6pRnWVnZyMrKwslJSW1ml2Tmp6nn34av/zyCz755JNoh0JEREREzVSzeqaPqCGdPHkSb7/9dtjSDUREREREDa1ZDe8kaijPPfccWrVqhWuvvRaDBw+OdjhERERE1IxxeCcREREREVETxp4+IiIiIiKiJoxJ31kaOXIkZs+eHZG2hg0bhjfeeCMibVVl/fr1nEimBh988AH69esX7TAavR07dkCSpHppW5Ik7Nixo17anj9/Pq644op6aTs3NxdGoxF2u73Wxzz//PO4+eaba93mpEmTMG3atHMNlYiIiJoxJn2NwFdffYV77rmnVvsuWrQIPXr0iOj5q2pz9uzZGDlyZETPc7pjx44hISEBwWAwVNa+fXts3769xuMinSDccsst+OGHHyLWHjV+VX32zkZGRgacTmeltTmvvPJKLFu2rMrfrRkzZuDDDz8MbZ/+ea6uTSIiIqKzxaSPombFihUYNmwYlEolAGDPnj3weDzo2bNnlCOjpu70z14kORwO/Pjjj7jqqqsi3nZd+f3+Jn0+IiIiqp1mk/Q5nU5MnToVGRkZSEpKwq233hoaPpWdnQ1JkvDee++hbdu2sFqtmDRpUtgNzKeffoq2bdvCYrHgz3/+MwKBQKju1PDJ1157DS1atEBKSgpmzZqFinPkvP/+++jUqROsVisGDBiAbdu2hequuOIKzJ8/P6ytd955B+np6YiPj8fDDz8MANi+fTvuuusu7Ny5E0ajEUajEbm5ubV+DWrb5rvvvovnn38eK1euDJUB5cPMbr/9dowcORJGoxEXXHBB2OLrH3zwAdq1aweTyYSWLVvimWeeqTGeFStW4Prrrw/bvu666wAA27ZtQ58+fWA2m5GQkBAq7927NwCgX79+MBqNeP755wEA48ePR2pqKsxmM3r16oV169aFneu1114LXfsTTzyBHj16hJZSOL03plWrVnjhhRfQp08fmEwmXH755Thy5EiofteuXaG6gQMH4uGHH65x+OCBAwcwdOhQxMXFoU2bNqH3uuK5Z8yYgfj4eGRkZFQa6rtkyRJccMEFsFqtuPjii8N6Ja+44go89thjGDp0KEwmEy688ELs3LkTADBv3jwMGjQorK2PPvoIHTt2rFXbNpsNN954I6xWKzp27Ihvv/02rK33338fXbt2hclkQkZGBp588knUNC9Ufn4+xo8fjxYtWsBqteKyyy6D2+2utJ8QAi+99BLatGmDuLg4XH311Th06FCo/vSesdOHb57+/uTl5VU6R8XP3pmuQ5IkvPLKK+jQoQOsVituuummSn87bDZbaP9Vq1ZhwIAB2LdvX5W/rxV70av6PFfVZkUHDx7Eddddh8TERGRmZuLZZ5+FLMsA/vg8zZo1CykpKRg7dmyVbXz44Yfo3r07zGYzMjMzQ78Ls2fPxvDhw3HnnXfCYrEgKysL69evx2effYa2bdsiNjYWjz/+eKid2p6PiIiIokw0E2PGjBE333yzKCkpEU6nU4wdO1aMHz9eCCHE4cOHBQBx8803C4fDIY4dOybS0tLEwoULhRBC7N27V2g0GvH5558Lv98v3nzzTaFUKsWsWbOEEEKsW7dOKBQKMWnSJFFWViZ+++03kZaWJhYtWiSEEGLDhg3CaDSKDRs2CJ/PJ+bNmycSExOFzWYTQghx+eWXi3nz5oW1df/99wu32y12794t9Hq9WLdunRBCiIULF4ru3buHXVtOTo6wWCwiJyenyms/mzZnzZolRowYEVY2ceJEodVqw16H2NjY0GuqUqnEhg0bhBBClJSUiB9//DF0bLdu3cQHH3wQ2nY6ncJsNguHwxEqGzBggPj666+FEEL07dtXPPvssyIYDAqPxxNqVwghAIjt27eHxfavf/1L2Gw24fP5xAsvvCDi4uJCba9evVpYrVaxZcsW4fV6xZNPPilUKlXo/T39+jMzM0W3bt3EoUOHhNvtFsOGDRMTJ04UQgjh8/lE69atxezZs4XX6xWbN28W8fHx4vLLL6/ytff7/aJDhw7ioYceEm63W/z888+iRYsWoddi4cKFQqlUihkzZgiv1yt++OEHYTKZQtf7xRdfiJYtW4qtW7eKYDAoPv30UxEXFycKCwuFEOWfnZYtW4odO3YIv98v/vznP4diyc/PF2q1WuTm5obiufbaa8Wzzz5bq7YnTJggrrzySlFSUiKOHTsmevXqJSr+yfjyyy/F3r17hSzLYvv27SIpKUm8//77Vb4OwWBQXHTRRWLixImiuLhY+P1+sXHjRuHxeCq9p//+979Famqq+OWXX4Tb7RbTp08XnTt3Fn6/v8r3f968eaFr9vv9onXr1mGvZ2xsbNj7c/pn70zXAUD06tVLHDt2TJSUlIgrr7xSTJo0SQjxx9+OkpKS0P7jx48XCxYsCL2/Z/rdOv16Tm9z4sSJ4r777hNCCFFWViYyMzPFvHnzhNfrFTk5OaJLly7inXfeCZ1PqVSKp59+Wni9XlFWVlbpvfj8889FXFycWLNmjQgGg6KgoEBs27YtFJtarRaffvqpCAQC4sknnxQtW7YUkyZNEk6nU+zatUtotVqxdevWWp+PiIiIoq9ZJH0nTpwQCoVCFBcXh8r27dsn1Gq1CAQCoZus3377LVR/xx13iKlTpwohhHj66afFsGHDwtrs2LFjWNIHQBQUFITq586dKwYPHhxq66677go7vn379qEb/9OTPkmSwm6ehgwZIv7+978LIaq+iTyTs2mzuqSvqtfhvffeE06nU8TExIgFCxYIu91+xpiWLVsmrrzyytB2YWGhsFqtoSTgsssuE3/+85/FkSNHKh1bVdJ3OqvVKr777jshhBC33367mDJlSqjO5/MJi8VSY9L35ptvhrbff/990bVrVyGEEN9++62wWCyhBEQIIe65555qk77vvvtOmM1m4fV6Q2XPPfdc6NoXLlwozGaz8Pl8ofq77rpLTJ48WQghxDXXXCPmz58f1ma/fv3Eu+++K4Qo/+w88sgjYeczGo2h7WHDhok5c+YIIYQoKCgQGo0m9OVATW0HAgGh0WjEli1bQnVLliwRNX1PdN9994k77rijyrrNmzcLg8EgXC5XlfUV39MhQ4aIuXPnhuo8Ho8wmUzi+++/r7SvEOFJ37ffflvl61nx/Tn9s3em6wAgPvroo7Br0Wg0IhgMVkrQAoGASEhIEEePHhVCRD7p+89//iN69OgR1t5bb70lBg0aFDpfXFycCAaD1V7f1VdfLZ566qkq62bNmiX69OkT2t61a5cAIPbs2RMqu/jii8Xbb79d6/MRERFR9DWL4Z3Z2dmQZRlZWVmwWq2hoWwKhQL5+fmh/VJSUkL/NhgMKC0tBQDk5eUhMzMzrM3Tt3U6HZKSksLqjx07BgA4evQoWrVqFbZ/VlYWjh49WmW8ZrMZer2+yljOVqTarOp1OHbsGAwGA1asWIHly5cjPT0dAwYMqDTEsqLTh3Z++eWXGDx4MLRaLQDgX//6FzweD3r16oWOHTvi//7v/6ptS5ZlPP7442jXrh3MZjOsVivsdjsKCwsBlL9/6enpof3VajVatGhR43XW9Flo0aIFVCpVqD4jI6Pado4ePYrU1FRoNJpQWevWrcPe+9TUVKjV6tB2xc9OdnY2ZsyYEfrcWq1W7NixI1RfVaxOpzO0feutt+K9994DUD6kr1+/fqF4a2q7sLAQPp8v7P0+/b1ftWoV+vXrh4SEBFgsFixYsCD0mp8uJycHLVu2RExMTLWvVcXXrOLvi1arRWpqarW/LxXl5eVV+XpWdPpnrzbXcfrr4PP5cPLkyUrn/+GHH5CZmYmWLVueMdazkZ2djV9//TXsPXvggQfC/o61bNkSCkX5n/bnn38+NLR02LBhAMrfi3bt2lV7juTk5NC/T/3NOL2s4mes4vmIiIiocWoW/6dOT0+HQqFAXl4ebDZb6Mfj8dTq5iw1NRU5OTlhZac/S+fxeHDixImw+lNtp6WlITs7O2z/7OxspKWl1fla6uPmqqo2qztPVa/DqescPHgwvvzySxQWFmLMmDEYOXJk6FmjimRZxhdffBF24/3555+Hbbdp0wbvvvsu8vPz8c477+DBBx/E1q1bAaDSsgGLFy/G4sWL8cUXX8But8Nms8FisYSey0pNTQ17Ji8QCOD48eM1vibVSU1NRX5+ftgznTU9V5mWloa8vLyw50NPf+9Pr6/4mqanp+Oll14K+9yWlZXh0UcfrVW8I0aMwNGjR7F161a89957mDBhQqiuprYTEhKgVqvD3u+K1+nz+TBq1CjceeedOHbsGOx2O+66665qn+k7lch6PJ4zxnz674vP50NeXl7oNTMYDHC5XKH6iu9lampqla/nKad/9mp7Hae/DhqNBomJiZViP/1zXJvf17osg5Geno5evXqFvWcOhwO7du2q8pwzZsyA0+mE0+nEV199BaD8vThw4ECtz3kmTPiIiIgav2bxf+uUlBSMHDkSU6dODX2Dn5+fj2XLltXq+BtvvBFr1qzBF198gUAggLfffhv79u0L20ehUOCxxx6D2+3G3r178frrr+OWW24BUD7JyAcffIDvv/8egUAAr732GoqKinDNNdfU+VqSk5Nx/PjxKifAOFtVtZmcnIycnJyw5AYA1q5dG/Y6HD9+HNdeey0KCgqwbNkylJaWQqVSwWw2h/WGVfTjjz8iOTk51OPk8/mwevXqsNfj3XffRUFBASRJgtVqhUKhCM20mJycjIMHD4b2dTgc0Gg0SEhIgM/nw9NPPx3Wi3nzzTdj8eLF+Omnn+D3+/Hss8+irKzsrF6rPn36wGq1Ys6cOfD7/fjf//6H//znP9Xu37t3byQnJ2PmzJnwer349ddf8dprr2HixImhfcrKyvDMM8/A5/Nhy5Yt+OCDD0KfnSlTpuDFF1/E1q1bIYSAy+XC6tWra9XrBQAxMTG44YYb8Pjjj2P37t0YM2ZMqK6mtpVKJW688UbMnDkTNpsNeXl5ePHFF0PHer1eeDwexMfHQ6vVYsuWLVi8eHG1cVx88cXo0KED7rnnHthsNgQCAXz33Xfwer2V9h0/fjz+7//+D7t374bX68UTTzyBli1bhiY9ufDCC/Hee+8hEAhgx44doZ5MoPz9iYuLC3s9P/roo1D96Z+92l7Hiy++GPrSaObMmRg7dmyVyU7FyYiA2v2+nv55rsnw4cNRUFCAN954Ax6PB8FgEHv37sX69etrdTwA3HnnnXjllVewYcMGyLKMEydOnHGZFCIiIjq/NYukDyifZe7UsE6z2YxLL7001HN0Jh06dMB7772Hv/71r4iPj8eWLVtw9dVXh+1jMpnQo0cPtG7dGpdddhluvfXW0I395Zdfjtdeew2TJ09GfHw8lixZgq+++uqsFkwfNGgQ+vTpg5YtW8JqtSI3Nze0mHNdZvI8U5tjxoyB2WxGYmJiWJzjxo3D22+/DavVildffRXLly9HbGwsZFnGK6+8gvT0dFgsFrz++uv45JNPQjfGXbp0wQcffACg8vC6DRs2oGvXrkhISAiVrV69Gt27d4fRaMSIESPw4osvhmbYfOaZZ/DXv/4VsbGxmDt3LiZOnIguXbogMzMTrVu3RkxMTFhP2pAhQzBr1iyMHDkSKSkpCAQCaN++fWgoaV2o1WosX74cK1euRGxsLB5++GGMHz8+rK1hw4aFZhVVq9VYuXIltm7dipSUFFx//fWYPn06xo0bF9q/a9euCAQCaNGiBW644QY899xzGDhwIADguuuuw9y5c/HnP/8ZsbGxyMrKwiuvvFJlD2p1br31VqxatQojR46EyWQKlZ+p7ddeew1GoxGZmZkYNGhQWC+hyWTC66+/jr/85S8wm8147rnncNNNN4Wdt+LroFAosGLFCrhcLnTo0AEJCQl44oknqryOW2+9Fffeey+GDx+OlJQU/Pzzz1ixYkXoS4TXXnsNmzZtgtVqxSOPPBKWQKvVanz++edYtWoV4uLi8Oijj+L2228P1Z/+2avNdQDliejAgQORmZkJk8mEV155pdI++/fvh8vlCltypKrfrdOd/nmuidFoxOrVq7FmzRq0atUK8fHxGDduXNjwzjMZOXIkXn75ZUyZMgUWiwUXX3xxaMZXIiIiapokUd14LKq19evXY+TIkdVOsd5UTJo0CVarNWzJgbPRrVs3/Otf/8LFF18MALj33nuRkZGBhx56KAJRnpnP50N8fDy+/vpr9O/f/5zbu/POOyHLMt5+++06H7to0SLMnz8/oovNU/VO/+zVhiRJ2L59e6VF1k/30ksv4dChQ3j99dfPMUoiIiKiyGo2PX3UOPh8Ptx000246KKLQmXdunWr9/W9li5dCrfbjbKyMjzyyCOIj4+v041/RRs3bsSRI0cgyzLWrFmDDz74IGzYJDVOVX32Iik9PR133XVXvbRNREREdC6qfuiKqJ5oNBo88cQTYWV/+ctf6v287733Hm6//XYIIdCjRw98/vnnYTNq1sWhQ4cwduxYlJSUIC0tDXPnzsVVV10V4Ygp0qr67EXSjTfeWG9tExEREZ0LDu8kIiIiIiJqwji8k4iIiIiIqAlj0kdERERERNSEMekjIiIiIiJqwpj0ERERERERNWFM+oiIiIiIiJowJn1ERERERERNGJM+IiIiIiKiJoxJHxERERERURPGpI+IiIiIiKgJY9JHRERERETUhDHpIyIiIiIiasKY9BERERERETVhqmgHUN9kWUZeXh5MJhMkSYp2OERERERE9U4IgdLSUqSmpkKhYD9Pc9fkk768vDykp6dHOwwiIiIiogZ35MgRpKWlRTsMirImn/SZTCYA5R94s9kc5WiIiIiIiOqfw+FAenp66F6Ymrcmn/SdGtJpNpuZ9BERERFRs8LHmwjgRC5ERERERERNGpM+IiIiIiKiJoxJHxERERERURPGpI+IiIiIiKgJY9JHRERERETUhDHpIyIiIiIiasKY9BERERERETVhTPqIiIiIiIiaMCZ9RERERERETZgq2gGcj044PDhmc0MWAvEGLdJiY6BSMn8mIiIiIqLGh5lKHciywOZDRdh0qAi5xS4cLXHj56M2rN1zAmXeQLTDIyIiIiJq9IKywKaDRVi+4xg2HSxCUBb1er45c+bg4osvhslkQlJSEkaOHIm9e/eG7ePxeDBlyhTEx8fDaDRi9OjRKCgoCNsnNzcX1157LfR6PZKSkvDQQw8hEDhzDrBy5UpcfvnlMJlM0Ov1uPjii7Fo0aKwfbKzsyFJEnbs2BEqKy0txcCBA9G5c2ccPXr0rK8fYNJXJwdOOlHg8FQqd/uD2J5ra/iAiIiIiIjOI1//ehwD/rYWN7+9Gfct2YGb396MAX9bi69/PV5v59ywYQOmTJmCzZs345tvvoHf78dVV12FsrKy0D73338/VqxYgY8//hgbNmxAXl4eRo0aFaoPBoO49tpr4fP58MMPP+Df//43Fi1ahJkzZ9Z47tdeew0jRoxA//79sWXLFvzyyy8YO3Ys7rrrLjz44IPVHnfy5EkMHDgQZWVl2LhxI9LS0s7pNZCEEPWbWkeZw+GAxWKB3W6H2Ww+p7a+2V0Al6/6bH5gxySYdepzOgcRERER0bmK5D1wpHz963Hc/f42nJ58SL//983xF+Lqri3qPY6TJ08iKSkJGzZswGWXXQa73Y7ExEQsXrwYN9xwAwBgz5496NSpEzZt2oQ+ffrgq6++wvDhw5GXl4fk5GQAwIIFC/DII4/g5MmT0Gg0lc5z5MgRtGnTBvfeey9eeumlsLrXXnsNf/3rX7F582ZccsklyM7ORlZWFrZv3474+HhceeWVaNmyJZYvXw6j0XjO18yevjqoKeEDALcv2ECREBERERGdP4KywFMrdldK+ACEyp5asbveh3oCgN1uBwDExcUBALZu3Qq/348hQ4aE9unYsSMyMjKwadMmAMCmTZvQrVu3UMIHAEOHDoXD4cCuXbuqPM8nn3wCv99fZY/enXfeCaPRiA8//DCsfO/evejfvz86d+6ML7/8MiIJH8Ckr04MmprnvdFrlA0UCRERERHR+ePHw8U4bq/8mNQpAsBxuwc/Hi6u1zhkWca0adPQv39/dO3aFQCQn58PjUYDq9Uatm9ycjLy8/ND+1RM+E7Vn6qryr59+2CxWNCiReXeS41Gg9atW2Pfvn1h5bfeeivatm2Ljz/+GFqt9qyusSpM+uogM15fbV2CUQsTh3YSEREREVVyorT6hO9s9jtbU6ZMwa+//oolS5bU63nO1vXXX4+NGzdi6dKlEW2XSV8dtE0yooUlplK5QaNCzwxrwwdERERERHQeSDLpIrrf2Zg6dSpWrlyJdevWhU2MkpKSAp/PB5vNFrZ/QUEBUlJSQvucPpvnqe1T+5yuffv2sNvtyMvLq1Tn8/lw8OBBtG/fPqz88ccfx8yZMzFu3Dj85z//qfM1VodJXx1IkoTeWXHo1yYBreINSI/To2d6LAZ2TIL+DEM/iYiIiIiaq95ZcWhh0YUmbTmdBKCFRYfeWXERP7cQAlOnTsWyZcuwdu1aZGVlhdX36tULarUaa9asCZXt3bsXubm56Nu3LwCgb9++2LlzJ06cOBHa55tvvoHZbEbnzp2rPO/o0aOhVqsrTeIClE8CU1ZWhptvvrlS3ZNPPonZs2fjlltuwUcffXRW13w6ZipnIdGkRaIpcmNsiYiIiIiaMqVCwqzrOuPu97dBAsImdDmVCM66rjOUiurSwrM3ZcoULF68GMuXL4fJZAo9g2exWBATEwOLxYLJkydj+vTpiIuLg9lsxr333ou+ffuiT58+AICrrroKnTt3xoQJE/DCCy8gPz8fTzzxBKZMmVLts3cZGRl44YUX8MADD0Cn02HChAlQq9VYvnw5ZsyYgQceeACXXHJJlcc+/vjjUCqVuOWWWyDLcpXJYV0w6SMiIiIionp3ddcWeHP8hXhqxe6wSV1SLDrMuq5zvS3X8OabbwIArrjiirDyhQsXYtKkSQCAefPmQaFQYPTo0fB6vRg6dCjeeOON0L5KpRIrV67E3Xffjb59+8JgMGDixIl4+umnazz3tGnT0Lp1a/z973/HK6+8gmAwiC5duuDNN9/EbbfdVuOxjz76KBQKBSZMmAAhBMaNG1f3i/8d1+kjIiIiImpiGvM9cFAW+PFwMU6UepBkKh/SWR89fPQH9vQREREREVGDUSok9G0TH+0wmhVO5EJERERERNSEMekjIiIiIiJqwpj0ERERERERNWFM+oiIiIiIiJowJn1ERERERERNGJM+IiIiIiKiJoxJHxERERERURPGpI+IiIiIiKgJY9JHRERERETUhDHpIyIiIiIiasKY9BERERERUb2b980+vLpmf5V1r67Zj3nf7GvgiKomhEAgEKhU7vP5zqq9sz0ukpj0ERERERFRvVMqJLxcReL36pr9ePmbfVAqpHo7tyzLmDNnDrKyshATE4Pu3bvjk08+AQCsX78ekiThq6++Qq9evaDVavHdd9/hiiuuwNSpUzFt2jQkJCRg6NChAIANGzagd+/e0Gq1aNGiBR599NGwJLG646JJFe0AiIiIiIio6fvr4HYAgJd/79H76+B2oYRv+pXtQ/X1Yc6cOXj//fexYMECtGvXDt9++y3Gjx+PxMTE0D6PPvoo/v73v6N169aIjY0FAPz73//G3Xffje+//x4AcOzYMVxzzTWYNGkS3n33XezZswd//vOfodPpMHv27FBbpx8XbZIQQkQ7iPrkcDhgsVhgt9thNpujHQ4RERERUb1rzPfApxI9jVIBX1Cu94TP6/UiLi4Oq1evRt++fUPld9xxB1wuF/7yl79g4MCB+OyzzzBixIhQ/RVXXAGHw4Ft27aFyh5//HF8+umn+O233yBJ5T2Tb7zxBh555BHY7XYoFIoqj4u2qA7vnD17NiRJCvvp2LFjqN7j8WDKlCmIj4+H0WjE6NGjUVBQEMWIiYiIiIjoXPx1cLtQwqdRKuo14QOAAwcOwOVy4corr4TRaAz9vPvuuzh48GBov4suuqjSsb169Qrb/u2339C3b99QwgcA/fv3h9PpxNGjR6s9LtqiPryzS5cuWL16dWhbpfojpPvvvx9ffPEFPv74Y1gsFkydOhWjRo1qNN2kRERERERUN6+u2R9K+HxBGa+u2V+viZ/T6QQAfPHFF2jZsmVYnVarDSV+BoOh0rFVldXG2R5XX6Ke9KlUKqSkpFQqt9vt+Oc//4nFixdj0KBBAICFCxeiU6dO2Lx5M/r06dPQoRIRERER0Tk4/Rm+U9sA6i3x69y5M7RaLXJzc3H55ZdXqq/Y23cmnTp1wqeffgohRKi37/vvv4fJZEJaWlrEYo60qCd9+/fvR2pqKnQ6Hfr27Ys5c+YgIyMDW7duhd/vx5AhQ0L7duzYERkZGdi0aROTPiIiIiKi80hVk7ZUNblLpJlMJjz44IO4//77IcsyBgwYALvdju+//x5msxmZmZm1buuee+7B/Pnzce+992Lq1KnYu3cvZs2ahenTp0OhaLwLI0Q16bvkkkuwaNEidOjQAcePH8dTTz2FSy+9FL/++ivy8/Oh0WhgtVrDjklOTkZ+fn61bXq9Xni93tC2w+EAUL7eRhOfs4aIiIiICAAa5X1vUBZVTtpyajso11/MzzzzDBITEzFnzhwcOnQIVqsVF154IWbMmAFZlmvdTsuWLfHll1/ioYceQvfu3REXF4fJkyfjiSeeqLfYI6FRzd5ps9mQmZmJl19+GTExMbjtttvCEjgA6N27NwYOHIi//e1vVbYxe/ZsPPXUU5XKc3JyGt3MRURERERE9cHhcCAzM7NRzt5JDS/qwzsrslqtaN++PQ4cOIArr7wSPp8PNpstrLevoKCgymcAT3nssccwffr00LbD4UB6ejosFgs/8ERERETULFScXZKoUSV9TqcTBw8exIQJE9CrVy+o1WqsWbMGo0ePBgDs3bsXubm5YetrnE6r1UKr1VYqP7UkBBERERFRU8f7Xqooqknfgw8+iOuuuw6ZmZnIy8vDrFmzoFQqcfPNN8NisWDy5MmYPn064uLiYDabce+996Jv376cxIWIiIiIiKiWopr0HT16FDfffDOKioqQmJiIAQMGYPPmzUhMTAQAzJs3DwqFAqNHj4bX68XQoUPxxhtvRDNkIiIiIiKi80qjmsilPjgcDlgsFj7ESkRERETNBu+BqaLGu5gEERERERERnTMmfURERERERE0Ykz4iIiIiIqImjEkfERERERFRE8akj4iIiIiIqAlj0kdERERERNSEMekjIiIiIiJqwpj0ERERERERNWFM+oiIiIiIiJowJn1ERERERERNGJM+IiIiIiKiJoxJHxERERERURPGpI+IiIiIiKgJY9JHRERERETUhDHpIyIiIiIiasKY9BERERERETVhTPqIiIiIiIiaMCZ9RERERERETRiTPiIiIiIioiaMSR8REREREVETxqSPiIiIiIioCWPSR0RERERE1IQx6SMiIiIiImrCmPQRERERERE1YUz6iIiIiIiImjAmfURERERERE0Ykz4iIiIiIqImjEkfERERERFRE8akj4iIiIiIqAlj0kdERERERNSEMekjIiIiIiJqwpj0ERERERERNWFM+oiIiIiIiJowJn1ERERERERNGJM+IiIiIiKiJoxJHxERERERURPGpI+IiIiIiKgJY9JHRERERETUhDHpIyIiIiIiasKY9BERERERETVhTPqIiIiIiIiaMCZ9RERERERETRiTPiIiIiIioiaMSR8REREREVETxqSPiIiIiIioCWPSR0RERERE1IQx6SMiIiIiImrCmPQRERERERE1YUz6iIiIiIiImjAmfURERERERE0Ykz4iIiIiIqImjEkfERERERFRE9Zokr65c+dCkiRMmzYtVObxeDBlyhTEx8fDaDRi9OjRKCgoiF6QRERERERE55lGkfT973//wz/+8Q9ccMEFYeX3338/VqxYgY8//hgbNmxAXl4eRo0aFaUoiYiIiIiIzj9RT/qcTiduueUWvP3224iNjQ2V2+12/POf/8TLL7+MQYMGoVevXli4cCF++OEHbN68OYoRExERERERnT9U0Q5gypQpuPbaazFkyBA8++yzofKtW7fC7/djyJAhobKOHTsiIyMDmzZtQp8+fapsz+v1wuv1hrYdDgcAQAgBIUQ9XQURERERUePB+16qKKpJ35IlS7Bt2zb873//q1SXn58PjUYDq9UaVp6cnIz8/Pxq25wzZw6eeuqpSuV2u50ffiIiIiJqFk51fBABUUz6jhw5gvvuuw/ffPMNdDpdxNp97LHHMH369NC2w+FAeno6LBYLzGZzxM5DRERERNRYSZIU7RCoEYla0rd161acOHECF154YagsGAzi22+/xf/93/9h1apV8Pl8sNlsYb19BQUFSElJqbZdrVYLrVZbqVySJH74iYiIiKhZ4H0vVRS1pG/w4MHYuXNnWNltt92Gjh074pFHHkF6ejrUajXWrFmD0aNHAwD27t2L3Nxc9O3bNxohExERERERnXeilvSZTCZ07do1rMxgMCA+Pj5UPnnyZEyfPh1xcXEwm82499570bdv32oncSEiIiIiIqJwUZ+9sybz5s2DQqHA6NGj4fV6MXToULzxxhvRDouIiIiIiOi8IYk6Tml5+PBhbNy4ETk5OXC5XEhMTETPnj3Rt2/fiE7IEikOhwMWiwV2u50TuRARERFRs8B7YKqo1j19H3zwAV555RX89NNPSE5ORmpqKmJiYlBcXIyDBw9Cp9PhlltuwSOPPILMzMz6jJmIiIiIiIhqqVZJX8+ePaHRaDBp0iR8+umnSE9PD6v3er3YtGkTlixZgosuughvvPEGxowZUy8BExERERERUe3VanjnqlWrMHTo0Fo1WFRUhOzsbPTq1eucg4sEdm0TERERUXPDe2CqqFY9fbVN+AAgPj4e8fHxZx0QERERERERRY6irgds27YtbH295cuXY+TIkZgxYwZ8Pl9EgyMiIiIiIqJzU+ek784778S+ffsAAIcOHcLYsWOh1+vx8ccf4+GHH454gERERERERHT26pz07du3Dz169AAAfPzxx7jsssuwePFiLFq0CJ9++mmk4yMiIiIiIqJzUOekTwgBWZYBAKtXr8Y111wDAEhPT0dhYWFkoyMiIiIiIqJzUuek76KLLsKzzz6L9957Dxs2bMC1114LoHzR9uTk5IgHSERERERERGevzknf/PnzsW3bNkydOhWPP/442rZtCwD45JNP0K9fv4gHSERERERERGevVuv01YbH44FSqYRarY5EcxHDNUqIiIiIqLnhPTBVVKt1+oQQkCSpxn10Ol1EAiIiIiIiIqLIqdXwzi5dumDJkiVnXIdv//79uPvuuzF37tyIBEdERERERETnplY9fa+99hoeeeQR3HPPPbjyyitx0UUXITU1FTqdDiUlJdi9eze+++477Nq1C1OnTsXdd99d33ETERERERFRLdTpmb7vvvsOH330ETZu3IicnBy43W4kJCSgZ8+eGDp0KG655RbExsbWZ7x1xvHMRERERNTc8B6YKorYRC6NFT/wRERERNTc8B6YKqrzkg1ERERERER0/mDSR0RERERE1IQx6SMiIiIiImrCmPQRERERERE1YUz6iIiIiIiImrCzSvoOHjyIJ554AjfffDNOnDgBAPjqq6+wa9euiAZHRERERERE56bOSd+GDRvQrVs3bNmyBUuXLoXT6QQA/Pzzz5g1a1bEAyQiIiIiIqKzV+ek79FHH8Wzzz6Lb775BhqNJlQ+aNAgbN68OaLBERERERER0bmpc9K3c+dO/OlPf6pUnpSUhMLCwogERURERERERJFR56TParXi+PHjlcq3b9+Oli1bRiQoIiIiIiIiiow6J31jx47FI488gvz8fEiSBFmW8f333+PBBx/ErbfeWh8xEhERERER0Vmqc9L3/PPPo2PHjkhPT4fT6UTnzp1x2WWXoV+/fnjiiSfqI0YiIiIiIiI6S5IQQpzNgbm5ufj111/hdDrRs2dPtGvXLtKxRYTD4YDFYoHdbofZbI52OERERERE9Y73wFSR6mwPzMjIQEZGRiRjISIiIiIiogirc9InhMAnn3yCdevW4cSJE5BlOax+6dKlEQuOiIiIiIiIzk2dk75p06bhH//4BwYOHIjk5GRIklQfcREREREREVEE1Dnpe++997B06VJcc8019REPERERERERRVCdZ++0WCxo3bp1fcRCREREREREEVbnpG/27Nl46qmn4Ha76yMeIiIiIiIiiqA6D++88cYb8eGHHyIpKQmtWrWCWq0Oq9+2bVvEgiMiIiIiIqJzU+ekb+LEidi6dSvGjx/PiVyIiIiIiIgauTonfV988QVWrVqFAQMG1Ec8REREREREFEF1fqYvPT0dZrO5PmIhIiIiIiKiCKtz0vfSSy/h4YcfRnZ2dj2EQ0RERERERJFU5+Gd48ePh8vlQps2baDX6ytN5FJcXByx4IiIiIiIiOjc1Dnpmz9/fj2EQURERERERPXhrGbvJCIiIiIiovNDrZI+h8MRmrzF4XDUuC8neSEiIiIiImo8apX0xcbG4vjx40hKSoLVaq1ybT4hBCRJQjAYjHiQREREREREdHZqlfStXbsWcXFxAIB169bVa0BEREREREQUObVK+i6//PLQv7OyspCenl6pt08IgSNHjkQ2OiIiIiIiIjondV6nLysrCydPnqxUXlxcjKysrIgERURERERERJFR56Tv1LN7p3M6ndDpdBEJioiIiIiIiCKj1ks2TJ8+HQAgSRKefPJJ6PX6UF0wGMSWLVvQo0ePiAdIREREREREZ6/WSd/27dsBlPf07dy5ExqNJlSn0WjQvXt3PPjgg5GPkIiIiIiIiM5arZO+U7N23nbbbXjllVcish7fm2++iTfffBPZ2dkAgC5dumDmzJkYNmwYAMDj8eCBBx7AkiVL4PV6MXToULzxxhtITk4+53MTERERERE1B3V+pm/hwoURW4A9LS0Nc+fOxdatW/HTTz9h0KBBGDFiBHbt2gUAuP/++7FixQp8/PHH2LBhA/Ly8jBq1KiInJuIiIiIiKg5kIQQItpBVBQXF4cXX3wRN9xwAxITE7F48WLccMMNAIA9e/agU6dO2LRpE/r06VOr9hwOBywWC+x2e8SSVSIiIiKixoz3wFRRnXv66kswGMSSJUtQVlaGvn37YuvWrfD7/RgyZEhon44dOyIjIwObNm2KYqRERERERETnj1o/01dfdu7cib59+8Lj8cBoNGLZsmXo3LkzduzYAY1GA6vVGrZ/cnIy8vPzq23P6/XC6/WGth0OB4DyCWgaWacmEREREVG94H0vVRT1pK9Dhw7YsWMH7HY7PvnkE0ycOBEbNmw46/bmzJmDp556qlK53W7nh5+IiIiImoVTHR9EwFk+0/fee+9hwYIFOHz4MDZt2oTMzEzMnz8fWVlZGDFixDkFNGTIELRp0wY33XQTBg8ejJKSkrDevszMTEybNg33339/lcdX1dOXnp4Om83G8cxERERE1Cw4HA5YrVY+00cAzqKn780338TMmTMxbdo0PPfccwgGgwAAq9WK+fPnn3PSJ8syvF4vevXqBbVajTVr1mD06NEAgL179yI3Nxd9+/at9nitVgutVlupXJIkSJJ0TrEREREREZ0PeN9LFdU56Xvttdfw9ttvY+TIkZg7d26o/KKLLqrz4uyPPfYYhg0bhoyMDJSWlmLx4sVYv349Vq1aBYvFgsmTJ2P69OmIi4uD2WzGvffei759+9Z65k4iIiIiIqLmrs5J3+HDh9GzZ89K5VqtFmVlZXVq68SJE7j11ltx/PhxWCwWXHDBBVi1ahWuvPJKAMC8efOgUCgwevTosMXZiYiIiIiIqHbqnPRlZWVhx44dyMzMDCv/+uuv0alTpzq19c9//rPGep1Oh9dffx2vv/56XcNs9o6WHkVuaS7cATf0Kj0yzBloaWwZ7bCIiIiIiKiB1Tnpmz59OqZMmQKPxwMhBH788Ud8+OGHmDNnDt555536iJHq6JeTv+Bo6dHQtjfgRYmnBCWeEnRN6BrFyIiIiIiIqKHVOem74447EBMTgyeeeAIulwvjxo1DamoqXnnlFYwdO7Y+YqQ6KHIXhSV8FeU6cpFmTINVZ23YoIiIiIiIKGrOap2+W265BbfccgtcLhecTieSkpIiHRedpeNlx2usP1Z2jEkfEREREVEzoqjrAW63Gy6XCwCg1+vhdrsxf/58/Pe//414cFR3ftlfY31ADjRQJERERERE1BjUOekbMWIE3n33XQCAzWZD79698dJLL2HEiBF48803Ix4g1Y1Fa6mx3qq1NkwgRERERETUKNQ56du2bRsuvfRSAMAnn3yClJQU5OTk4N1338Wrr74a8QCpbtKN6dAoNVXWaZVapBpTGzgiIiIiIiKKpjonfS6XCyaTCQDw3//+F6NGjYJCoUCfPn2Qk5MT8QCpbtRKNS5OuRh6tT6s3KA24OIWF0OtUEcpMiIiIiIiioY6T+TStm1bfPbZZ/jTn/6EVatW4f777wdQvtC62WyOeIBUdxatBZenXY4iTxFcfhf0aj0SYhKiHRYREREREUVBnXv6Zs6ciQcffBCtWrXCJZdcgr59+wIo7/Xr2bNnxAOksyNJEhJiEpBhzmDCR0RERETUjElCCFHXg/Lz83H8+HF0794dCkV53vjjjz/CbDajY8eOEQ/yXDgcDlgsFtjtdvZEEhEREVGzwHtgquis1ulLSUlBSkpKWFnv3r0jEhARERERERFFTp2TvrKyMsydOxdr1qzBiRMnIMtyWP2hQ4ciFhwRERERERGdmzonfXfccQc2bNiACRMmoEWLFpAkqT7iIiIiIiIiogioc9L31Vdf4YsvvkD//v3rIx4iIiIiIiKKoDrP3hkbG4u4uLj6iIWIiIiIiIgirM5J3zPPPIOZM2fC5XLVRzxEREREREQUQXUe3vnSSy/h4MGDSE5ORqtWraBWq8Pqt23bFrHgiIiIiIiI6NzUOekbOXJkPYRBRERERERE9eGsFmc/n9TXwpRuXxCHC8tQVOaFUpLQwhqDjDg9lArOZkpERERE0cXF2amis1qcHQC2bt2K3377DQDQpUsX9OzZM2JBNXY2lw+bDhbBF/xjjcKTTi9yi13o3SoWGpWSyR8RERERETUKdU76Tpw4gbFjx2L9+vWwWq0AAJvNhoEDB2LJkiVITEyMdIyNzvYjtrCEDwDsbj/25pfi12M2pMcZkGTSolOKGRa9uppWiIiIiIiI6l+dZ++89957UVpail27dqG4uBjFxcX49ddf4XA48Ne//rU+YmxUbC4fHG5/WFmJy4ffjjtQXOZDkdMHIQQKHB5sPHASNpcvSpESERERERGdRU/f119/jdWrV6NTp06hss6dO+P111/HVVddFdHgGiNvILyHr6TMh02HiuDyBQEAKoWEVKsOiSYdgrLAnvxS9GkdH41QiYiIiIiI6t7TJ8typWUaAECtVkOW5SqOaFpMOhUkqfx5Pbvbj9/yS0MJHwBIkoTcYjcKS70AgBOlXgTlJj1XDhERERERNWJ17ukbNGgQ7rvvPnz44YdITU0FABw7dgz3338/Bg8eHPEA65PLF6i2TiFJ0KmVVe5rjVEj3+FGTpEL/kAQQVmEJm4x61TwB2XkFrtg0qkACXB6/VArFVW26/YFISCg15z1nDrh1+R34YDtAPLL8iFDRrwuHm2sbRCni4tI+0REREREdH6p85INR44cwfXXX49du3YhPT09VNa1a1d8/vnnSEtLq5dAz1ZN09W2evSLao8b2CERC2/rHdru9OTXcPuDVe5riVHhgjQrzDoV4o1afPS/I5WGgZ5yQZoFn08dENruP3ctjtncyJ57bV0uq0pl/jJsytsEXzD8OUJJktAruReS9EnnfA4iIiIiavy4ZANVVOfupfT0dGzbtg2rV6/Gnj17AACdOnXCkCFDIh7c+UKvViEtNibUmxct+0r2VUr4AEAIgd+KfmPSR0RERETUDDXrxdnPdnjnKT8cKEKxywsJEorLfChweBCQBfxBGWadGmMuSkeqVVdju5Ea3ikLGf/N/i9kUf1zlf1b9odFazmn8xARERFR48eePqrorDKNNWvWYN68eaHF2Tt16oRp06add719dUm0qtq3R4YVmw4WQRYCKRYdkkxauPxBSAAua5+ItFj9GduN0SjPuE9tCCFqTPgAICBXn+QSEREREVHTVOfxiG+88QauvvpqmEwm3HfffbjvvvtgNptxzTXX4PXXX6+PGButBKMWfdvEI96gBQAoFBJaWmMwsGNSrRK+SFIqlDX24ikVSpi1/JaHiIiIiKi5qfPwzrS0NDz66KOYOnVqWPnrr7+O559/HseOHYtogOeqobq2vYEghEDY0M2Gll+Wj20F26qsa21tjY5xHRs4IiIiIiKKBg7vpIrq3NNns9lw9dVXVyq/6qqrYLfbIxLU+UirUkY14QOAFEMKuiZ0hVr5xzqKCkmBVpZW6BDbIYqRERERERFRtNT5mb7rr78ey5Ytw0MPPRRWvnz5cgwfPjxigdHZyTBnoKWxJYo9xQiKIOJ0cdAoNdEOi4iIiIiIoqTOSV/nzp3x3HPPYf369ejbty8AYPPmzfj+++/xwAMP4NVXXw3t+9e//jVykVKtKRVKJOoTox3GeUUEZQRtXoiADEWMGkozE2UiIiIiahrq/ExfVlZW7RqWJBw6dOisgookjmemMwkUe+A7WgrIf/wqSDoVtFkWKLTRHbJLREREdDZ4D0wV1bmn7/Dhw/URR6N1zObGoZNO2N1+aJQKpMfp0TbJGPWF2CkygmV++I44gNO++hCeALyH7YjpGBedwIiIiIiIIuScM5dgMIgdO3agpKQkEvE0KvsKSvFTdjGKy3wIygJufxD7Ckrxw8EiBOUmvaZ9sxEodFdK+E4RngCCDl/DBkREREREFGF1TvqmTZuGf/7znwDKE77LLrsMF154IdLT07F+/fpIxxc1Hn8Qe/NLq6yzuXzIKSpr4IioPsjumheslz1c0J6IiIiIzm91Tvo++eQTdO/eHQCwYsUKZGdnY8+ePbj//vvx+OOPRzzAaMmzuSHX8LjjMZu7AaOh+iKppJrrlTXXExERERE1dnVO+goLC5GSkgIA+PLLLzFmzBi0b98et99+O3bu3BnxAKPlTMM3Axze2SSoYnXVVyokKK3ahguGiIiIiKge1DnpS05Oxu7duxEMBvH111/jyiuvBAC4XC4olU1npsM4Q81T9sefoZ7OD8o4HZTmKhI7CdCkmSBxwh4iIiIiOs/VefbO2267DTfeeCNatGgBSZIwZMgQAMCWLVvQsWPHiAcYLfFGLeINWhSVeSvVKRUSWicaoxDV+U3IAm6nH0II6IxqKBtBQiVJEjRZZgSLPQiUeCACAooYFVQJMVAa1NEOj4iIiIjonNU56Zs9eza6du2KI0eOYMyYMdBqy3tJlEolHn300YgHGE29s+KwLbcEBQ5PqMygUaF7uhVGbZ1fumbNftKNoqNOBAJBAIBCoYA1WY+EtOgnz5IkQRUfA1V8TLRDISIiIiKKuDovzl6Rx+OBTlfDM1GNQCQWpnR6A3C4/dCoFIg3aCBJnNyjLpwlHuQdsFVZF59qRHzL6Cd+RERERE0JF2eniuo8vi4YDOKZZ55By5YtYTQacejQIQDAk08+GVrKoakxalVItcYgwahlwncWivOqX96iJN8FOSg3YDRERERERM1LnZO+5557DosWLcILL7wAjeaPyUy6du2Kd955J6LB0flPDsrwuPzV18syvC6uhUdEREREVF/qnPS9++67eOutt3DLLbeEzdbZvXt37NmzJ6LB0flPkiRIOMNaeAr2nhIRERER1Zc6J33Hjh1D27ZtK5XLsgy/v/oenaZAlgWO2904XFiGQmflWT2pMkkhwVDDWndqrQo6zpJJRERERFRv6jwFZefOnbFx40ZkZmaGlX/yySfo2bNnxAJrbE6WerE1pwTe32efBACzTo2Ls+I4k+cZxKcZ4XL4IMvhz+5JkJCYzklciIiIiIjqU52zlZkzZ2LixIk4duwYZFnG0qVLsXfvXrz77rtYuXJlfcQYdWXeALYcLkJQDp/o1OHxY/PBIgzqmAQFhyhWSxujQkbnOBTllcFZ4gEEEGPWIK6FAXozF7knIiIiIqpPdU76RowYgRUrVuDpp5+GwWDAzJkzceGFF2LFihW48sor6yPGqMsuKquU8J1S5gvguMODllau8VYTTYwKLdpYAFgghIAsC4CTdhIRERER1bs6JX2BQADPP/88br/9dnzzzTf1FVOjY6th9kl/UMaxEhdamHXs7asFT5kfR/cUo/CoEwGfDK1ehdR2VqS2s3I5DCIiIiKielCniVxUKhVeeOEFBAKRmWJ/zpw5uPjii2EymZCUlISRI0di7969Yft4PB5MmTIF8fHxMBqNGD16NAoKCiJy/tpSKyu/TC5fAPsKSvHLUTu259rw390FOHCitEHjOt94yvz47YfjOLbfBq87gGBQhqvUhwPbTmD/1hMQoureVCIiIiIiOnt1nr1z8ODB2LBhQ0ROvmHDBkyZMgWbN2/GN998A7/fj6uuugplZX8s5n3//fdjxYoV+Pjjj7Fhwwbk5eVh1KhRETl/baXFhg/d9PiD2FfgRKknAAlArEEDbyCIXXkO7MqzN2hsVRFCwOlzwuV3RTuUMAXZDjiK3FXWnThsh7PY08ARERERERE1fXV+pm/YsGF49NFHsXPnTvTq1QsGgyGs/vrrr691W19//XXY9qJFi5CUlIStW7fisssug91uxz//+U8sXrwYgwYNAgAsXLgQnTp1wubNm9GnT5+6hn9WWlh0aGGJwXF7ecJS4PCEnvFrYYmBVvVH7nzoZBnaJhmhVSmrbKu+5ThycNB2EJ5AeQJl0VrQMa4j4mPioxLPKUIIFB11VlsfDAoUHnPCFM9nI4mIiIiIIqnOSd8999wDAHj55Zcr1UmShGAwWKm8tuz28l6yuLg4AMDWrVvh9/sxZMiQ0D4dO3ZERkYGNm3aVGXS5/V64fX+sYaew+EAUJ50nMvwwYsyrcgp0iC32IU93gDMWiWSTDpY9GqgQruyEDjh8CAtVn/W5zpbh+yHsKdoT1iZzWPDj8d/xCUtLkGsLrbBYzpFCAFXmRfOYg+CQRkKpQRNjAoanQqn1m4P+IIc4klEREQUAbynoorqnPSdvtZapMiyjGnTpqF///7o2rUrACA/Px8ajQZWqzVs3+TkZOTn51fZzpw5c/DUU09VKrfb7ef84Y9VA7HJGpQ5tfAHggD8gK/yJC+uUhXsioZdqD4oB3Gg4EBoRsyAHICAgFqhhgwZv+X9hi7xXRo0popsBWXw+t0ISB5ABQQBuD1e+GUldEY1FApAaQyGEn8iIiIiOnunOj6IgLNI+urLlClT8Ouvv+K77747p3Yee+wxTJ8+PbTtcDiQnp4Oi8UCs9l8rmECAFokCuQWlVVZJ0kSMlMTGnx4Z6G7EAFNAE6/E8edx0PP8+lUOqQYUiBJEsxmc1RmyPS6A/Da3UhMjoWrsBhy4I8vDgI+QKhUsLYwIq1VMtTa6AyLJSIiImpKOCs6VdQokr6pU6di5cqV+Pbbb5GWlhYqT0lJgc/ng81mC+vtKygoQEpKSpVtabVaaLXaSuWSJEXsw98u2YTjdg/8wcq9nm2SjNCpG/5llSQJzoATB+0HAYHQkElP0INsRzZaSa2gUNR53p6IcBZ7IUkSdAYN0tpbcfygHR5nAAKAUq2ATq9Bhz4tyod6EhEREdE5Y9JHFUUnC/idEAJTp07FsmXLsHbtWmRlZYXV9+rVC2q1GmvWrAmV7d27F7m5uejbt29Dhxti1KrQv00CEo1/JJdalRKdW5jRJdUSlZhitbE46TpZnvBVweV3RWRst8sXqPbH4w9WuW+Zxw93IAh3IAivANQWLbRWNbQxSqjVCijVErxysNbtun3l+xIRERER0ZlFtWtlypQpWLx4MZYvXw6TyRR6Ts9isSAmJgYWiwWTJ0/G9OnTERcXB7PZjHvvvRd9+/ZtsJk7q2PRq9GvbQI8/iACsoBerYzK4uyykHHCdQKl3lJAAAICEsLjkCQJVq0Vpf5SmDXnNsS188xV1dYN7JCIhbf1Dm33emY13P6qJ/Zpq9Xg3rgEAAKlhR5c9tIGlFaz7wVpFnw+dUBoe8jLG3DM5kb23GvP7iKIiIiIiJqRqCZ9b775JgDgiiuuCCtfuHAhJk2aBACYN28eFAoFRo8eDa/Xi6FDh+KNN95o4Eirp1NH/hm0mnqxFJIUOmexpxibj22DN+BFQA6iyOWEJ+iHVqmFBAmSJGDR6ZFqTIVerYfLF4QKVbddsV2gvDdNQECvqaePyO+djpJUPosnOMMUEREREVG9kMRZjPk7ePAgFi5ciIMHD+KVV15BUlISvvrqK2RkZKBLl+jNEFkVh8MBi8UCu90esYlc6lurR7+otu5Ub5o36MWGIxsw9R0/qssRUxPKMG7wCcTr4pFiSMED/w6guMxX5b6n96b1n7u2yt602iakp+/rcwewdVUO/J4AHEWe8mf8lAoYLFooNQp4gzKsyXqYE2KQ0TmuxnbrPSElIiIiOs+dj/fAVH/q/Ezfhg0b0K1bN2zZsgVLly6F01m+4PbPP/+MWbNmRTxAqtoRxxEE5Jqfa3MH3Nh5cic25W2CzWuLyHn1GlW1P6f3elass1p0yGwTi8REA2ItOsTF6mBOiIFSU/4R1CoV0GuUUPrFGduN0SiZ8BERERER1VKde/r69u2LMWPGYPr06TCZTPj555/RunVr/Pjjjxg1ahSOHj1aX7GelfPxW47a9KZtLdiKgrICeP3lb5836MOR0lzsOLEDhe5CKCQFYnWxsMboYdVZYVQZcVXGcHRO6Fxju6dEsjfNWeKF/aQLJ3NLUVbihbvMD7UuPJFTqhRIzDBCrVGhdY/Ecz4nERERUXN2Pt4DU/2p8x39zp07sXjx4krlSUlJKCwsjEhQzV1tEi21Qg0A0Kol+GU/cu37cdJzEkLywqBVQ6vUIkathF6lh1FlBAD8XPQ/XNiiKxTSmTt4YzSReVbx5JFSlOSXr2moNajgtHnhKfMh6FdBZyq/BgmAOUFXvpZgQkxEzktEREREROXqPLzTarXi+PHjlcq3b9+Oli1bRiQoOrOWxj9e6xOuEwjIAchChjfoBQDoVXooJSUcfgcCorzn0BVwochd1GAxesr8oYQPKO/Ni29pQEKaCX5fEHJQQGdQIa6lATqDGjEGDeJa6BssPiIiIiKi5qDOPX1jx47FI488go8//hiSJEGWZXz//fd48MEHceutt9ZHjFSF+Jh4pJvScaT0CBxeBwBAo9BAQCBGFQOl4veeOgG4/W6YNCboVXoERdXLItSH0iJPpTKlSoG4VAMsSTFQqhSIMWogKSSY4rQwxcdEZdkLIiIiIqKmrM5J3/PPP48pU6YgPT0dwWAQnTt3RjAYxLhx4/DEE0/UR4xUjW6J3RAfE48jpUcgfAIphhTYvfZQz15FkkJCQkwCYnWxDRZfMCBXW6dUKWCK1aFFW2uDxUNERERE1Byd1ZINAJCbm4tff/0VTqcTPXv2RLt27SIdW0Q0h4dYdxXuQo4jBwBw0nUSW45v+SPxk4AMUwbaWtuia0JXdE3o2mBxleSX4eSR0mrrE1qaEJdqaLB4qhMs9SHoKF/KQmnWQGnSRDkiIiIionPTHO6BqfbOemrGjIwMZGRkRDIWOktZlizkleXBH/QjUZ+Ifqn9sN+2H+6AGwkxCeiS0AWtzK3QKb5Tg8ZlTohBcV4ZgsHKPX4KhQKWxOhO2iKCAt7DNshOf6gscNIFhUkDbZYFEoeaEhEREVETUKukb/r06bVu8OWXXz7rYOjs6NV69E7pjd+Kf0OxuxhxMXHop+8Hq86KTHMmYnWx0Cq1DR+YBMSlGnAixxGWQKlUSrRoa4FSXed5hCLKn+cMS/hOkUt98Oc5oUkzRSEqIiIiIqLIqlXSt3379lo1JknsGYkWi9aCPi36wB1wwy/7YVAZ/pjMpYEJIVB4xAn7STdkWQYkIOiXYUnUwxSvg9GqjXovmgjKCJRUnmjmlECJB+pUY9TjJCIiIiI6V7VK+tatW1ffcVCExKhiEIPoDps8mVsK2wlXaFuSJCjVEsrsXsSlGhpFIiX8MiDX8DhrUED4ZUja6CTORERERESREt3xddTkBHxB2E+4q6wTQqDkeFmVdQ1NUimAmnqmJQmSKvrJKRERERHRuapVT9+oUaOwaNEimM1mjBo1qsZ9ly5dGpHA6PzkKvVBoPoeNNfvs2RGm6RSQGnRIGjzVlmvtGohKfmdCBERERGd/2qV9FksltDzehaLpV4DovPbmZ7rbEzPfWpamuDxBCE84esaSjoVNC2NUYqKiIiIiCiyar1O39NPP40HH3wQer2+vmOKKK5R0rCCQRmHdxSWT+BSBWuSHkmZjed9EEGBYInnj3X6LBooY3WN4rlDIiIiorPFe2CqqNbj15566ik4nc76jIWaAKVSgfiWVS+4rlIpEdsi+ouxVyQpJagSYqBtbYG2tQWq+BgmfERERETUpNR6cfZadggSITbFAKVKgeLjZfB5ApAkCcZYHeJbGqDWcDZMIiIiIqKGVOukD2hcz2NR42ZOiIE5IQbBoAyFJLH3jIiIiIgoSuqU9LVv3/6MiV9xcfE5BURNi5IzYBIRERERRVWdkr6nnnqKs3cSERERERGdR+qU9I0dOxZJSUn1FQsRERERERFFWK3H3vF5PmpKhBAQMicnIiIiIqKmj7N3UrMie4Pw55chaPMCQkARo4LCooVCp4SkUkBp1EQ7RCIiIiKiiKp10lfdYttE5wvZF4R3fwlEoPyzLIIyvNl2yJ4gVLE6KM0aSFolNBlmKA3qKEdLRERERBQZnFqRmo3ACdcfCZ8A/CfckD1BAEDQ7oWQBYQ3CO8hG2RfMJqhEhERERFFDJM+ajaCNm/o38ITgKiQ2AlZQHgCv+8oECh0N3R4RERERET1gkkfNRsVH0uVTyV41dW7/A0QERERERFR/avTkg1EjZnLVzmRO0UhSVCa1KHePpcsIAf/eE5VQEDlC0C4A1CqJBgrPNN3pnZ1amVo2+0LQkBAr+GvFhERERE1DrwzpSaj88xV1dYN7JCId27siaDdBwiBgWt3wx2senKiXuYY/PuKjggkxkBl1WHA39ahuMxX5b4XpFnw+dQBoe0hL2/AMZsb2XOvPbeLISIiIiKKEA7vpGZDaVBDm2WBpFXWuJ+kkCDFqODLKa1yGCgRERER0flEEk18AT6HwwGLxQK73Q6z2RztcKge1WUYptPmhpABf0EZvAftEH4ZklKCZFBDbdYiRl3+fYgqIQaBpJhat8vhnURERNQY8B6YKuKdKTUZdUm0jNbyRM7nDkKXVv0alLInUKd2YzQ19yISERERETU0Du+kZk1S1/wrIKn4K0JERERE5zfe0VKzporVAlIN9XG6hguGiIiIiKgeMOmjZk1SK6FpaaqyThUfA6VZ28ARERERERFFFpM+avaU8Too43QIOHzwn3AhaPdBYdVCk151MkhEREREdD5h0kfNni/HgWCxByqzBuokPZQWDWSbF74jpdEOjYiIiIjonDHpo2YtWOpD0Oatsi5Q5EawzN/AERERERERRRaTPmrWAiWeGuurSwiJiIiIiM4XTPqoeZNFjdUiWP0afkRERERE5wMmfdSsKfTqGuuVhprriYiIiIgaOyZ91Kyp4nTVLsAuqZVQxnKdPiIiIiI6vzHpo2ZNUimgbW2BpFOFl8eooG1jgaSoYeV2IiIiIqLzgOrMuxA1bQq9GjEd4xB0+iB8MiStksM6iYiIiKjJYNJH9DulURPtEIiIiIiIIo7DO4mIiIiIiJowJn1ERERERERNGJM+IiIiIiKiJoxJHxERERERURPGpI+IiIiIiKgJY9JHRERERETUhEU16fv2229x3XXXITU1FZIk4bPPPgurF0Jg5syZaNGiBWJiYjBkyBDs378/OsFSkySEQLDUh0CJB7I3EO1wiIiIiIgiLqpJX1lZGbp3747XX3+9yvoXXngBr776KhYsWIAtW7bAYDBg6NCh8Hg8DRwpNUVBuxee3UXwHrTBl+OA57dieA/ZIQJytEMjIiIiIoqYqC7OPmzYMAwbNqzKOiEE5s+fjyeeeAIjRowAALz77rtITk7GZ599hrFjxzZkqNTEyC4/vNkOQIiw8qDDC2+OgK6NNTqBERERERFFWKN9pu/w4cPIz8/HkCFDQmUWiwWXXHIJNm3aFMXIqCnwF7orJXynyKU+yC5/A0dERERERFQ/otrTV5P8/HwAQHJyclh5cnJyqK4qXq8XXq83tO1wOACU9xyKam7yqfkJlvpq/DwEnD6oYxrtrwcRERFRjXjfSxU1ubvaOXPm4KmnnqpUbrfb+eGnEG+gDMIXrLZe7QaUdvb2ERER0fnpVMcHEdCIk76UlBQAQEFBAVq0aBEqLygoQI8ePao97rHHHsP06dND2w6HA+np6bBYLDCbzfUWL51f/Mkq+I+XVV2pkBCTGg9J1WhHPxMRERHVSJKkaIdAjUijTfqysrKQkpKCNWvWhJI8h8OBLVu24O677672OK1WC61WW6lckiR++ClEnahH0O6DcFdepkGdaoRCrYxCVLUTDHrg9eYDENBoEqBSmaIdEhERETUyvO+liqKa9DmdThw4cCC0ffjwYezYsQNxcXHIyMjAtGnT8Oyzz6Jdu3bIysrCk08+idTUVIwcOTJ6QVOTICkV0LW1wn/CjWCxB0KWoYhRQZ2oh9JS+UuDxqK09DeUuQ6ETUKj06XCYukJSWq8iSoRERERRU9Uk76ffvoJAwcODG2fGpY5ceJELFq0CA8//DDKysrwl7/8BTabDQMGDMDXX38NnU4XrZCpCZGUCmhaGIAWhmiHUisuVzbKyvZXKvd48iAp1LCYu0chKiIiIiJq7CTRxGc3cTgcsFgssNvtfKaPzmuFhWsRCDirrJMkBRITr4RC0Xh7KYmIiKjh8B6YKuJMFUTnAVkOVJvwAYAQMgKB0gaMiIiIiIjOF0z6iBohIWT4/Y5QoidJyjM+s8dePiIiIiKqSqOdvZOouSorO4Ay10HIQS8AQK22wGTqAp2uJdzu3CqPUastnMWTiIiIiKrEnj6iRsTp3IvS0t2hhA8A/H47Sko2Q6tNgVJVedIZSaGGydStIcMkIiIiovMIe/qIGglZ9qPMdbDKOiFkuD1HEB83AC5XNjze44AQ0Gjiode3hkplbOBoiYiIiOh8waSPqJHw+4sh5MqLxZ/i8xZAodDCaOwAo7FDA0ZGREREROczJn3U7AWdPsiuACSlBKVFC0kVrVHP0jnWExERERFVxqSPmi3hD8J72AHZ5f+j8JgT6lQj1AkxDR6PRhMPSaGGkP1V1mt1KQ0cERERERE1BZzIhZotb/ZpCR8AyAL+o6UIlvoaPB5JUsJoaF91nUJVbR0RERERUU3Y00fNUrDMD7ms6h41AAicdENp0jRYPLLsRVnZIXi8efAHHAgGy6BSmqFSGaDRJsJk7AyVygRZ9sPvLwHwe8/gGdbuIyIiIiJi0kfNknBXP2EKAMhnqI8kWfaiuPj70ELsapUZapUZsgjAbO4BvT4DAOB07oOjdDe8nmMIBsugUGhgtlyI+Lj+TP6IiIiIqFoc3knN05kma1E13KQpzrL9oYSvIoWkQlnZHgghUFZ2EDbbTygt/QU+30kEgy74/TYUFa7F8ePLIFfzHCAREREREXv6qFlSmjWAUgEE5SrrVXG6iJ7P5au+59DuPAp1hRzTXTF/83ugcubDUbofdkcuIAS0FX5rPX4FvLYDUOr2w2QMf+ZPIUnQqf/oAXT7ghAQ0Gv4a09ERETUnPDuj5olSSFBk26CL8cBCBFWpzCqoYqP7OydnWeuqrauXxbw8og/tof9QwFPoGJP47bf/9sNF6Q48OKwvaGaWz++AHavGsDh33/+cEGaBZ9PHRDaHvLyBhyzuZE999qzvxAiIiIiOu8w6aNmS2XVQqGxwl/o/mOdvlgdVHE6SIqGG96pkFQAgg12PiIiIiJqXiQhTuvmaGIcDgcsFgvsdjvMZnO0w6FmqqbhnX7fCbidP4W2Kw7v1OlawGLpiZMnV8NW8iMkSUCr+uNX1uNXQKEyItbSC3Hx/cPa5fBOIiKi5ov3wFQR7/6IGkCNiZYmFWrFBSh1/gYh+xGjLi/W6VJhNveAQqFCi8SLEPD+hoDfHnaoTgMYDamIs7ZBzBmSuRgNZ/gkIiIiao6Y9BE1Anp9K+h0afD5TkCIANTqOKhUxlC9RpOAtJa3IL9gBTzuI/AHHICQoVKbAUmCQtFwawoSERER0fmFSR9RI6FQqKDTpVZbr9UmISP9Npw4sQouVw6E8EOlNkMhaVFSshkmU1cYDK0bMGIiIiIiOh8w6SM6j7jdufB6C+APFEPIPvj9RfBIKmi1KZCk3YiJaQmFQhvtMImIiIioEeHi7ETnCSEEbPZtcLkPQ8i+CuUBeDxH4fHkw+PJi2KERERERNQYsaePqJETQqDMdQBuVzYKT65FUHZCqTRArY6DQvpjchavNx/BCskgERERERHApI+o0XOU/gK3KweyCACSAIRAMOCEHPRCp0uFJJV32AsRgCTxV5qIiIiIwnF4J1EjFgiUwu3KAQBIkKBWWQCULxwvhB+BQGloX6VSD60mMRphEhEREVEjxm4BokbM6y0I/VuSlFBr4iELP3y+IkAEEZTLoIYFSpURJlNXqNVcfJWIqD4E7V4Eij0QfhmSTgl1QgwUenW0wyIiqhUmfUSNmBBy2LZOm4pgwAmlLgZB2Q2FQgujsSOUKgMs5guiFCURUdPmO1KKQJH7jwKXH8ESDzRpJqjiY6IXGBFRLTHpI2rEtNokOJ17QtsqlQEGQ3t4vcchBRTQ6lKgi0mD0dAeWm1SFCMlImqagg5veMJ3igB8R51QmrWQ1M3raRlZFjhmc8Pu9kOjUqClNQYGLW8piRoz/oYSNWJqtRVabRK83hOhMpXKAJWqLSRJjbi4AVCrTVGMkIioaQsUe6qvFAKBEg/USfqGCyjKHB4/Nh8sgtsfDJXtyS9FpxQT2iXz/0dEjRWTPqJGzmK5CKXOXfC4j4SGe2o08TCbL4BKxf/B1oVf9uOk6ySCIog4XRwMakO0QyKiRk745ZrrAzXXNyVCCPzvcHFYwneqfPdxBywxaui1KjjcfmhVCsQbtVGKlIhOx6SPqJFTKFSwmLvDZOyEQMAJhUILlSr6yUqZN4CTpV4oJAkBWUaezYNSjx9atQIZcXq0TjBCoZCiHWbIIfsh7CvZB1n+4wathbEFLki4AEqFsoYjiag5U8SoIJf5q6/XNZ9bqZOlXji9gSrrAkEZX+w8jjiDJlRm0KjQI8OKBCZ/RFHXfP5SEZ3nFAoNNJq4aIcBWRbYfsSGoyUuAMAxmxsFdg8STVokGLVQ+SSUegI44fCiT+v4RpH4HXcex56iPVWWKyUlLkjkJDhEVDVVQkz5M32icp2kVkBpjVxCI0QQZWUH4HbnIih7oFIaode3gl6fFbFznIvSahI+ADh4sgz+oByW9JX5AthyqBiXd0iEkc/8EUUVfwOJqEYOjx/ZhWUo9QSgUytQ5gmixO0DAHj9QRy3uVFc5sPhwjLEGzQwxahh1qnhDcg4ZnMjPS76z7ocsh+qti7PmYcOcR2gVfKbaCICZE8AsisASaWAwqSGQqeCJsMM35FSQP4j85PUCmizLJAi9MWWEDJKSrbA5ysMlQUCpXA4dsIfcMBi7h6R85wLnbrqURFOTwBOb6DKxC4gyzh8sgzd0iz1HR4R1YBJHxFV62iJC9tybRCi/EYnGBT45ZgNCUYt0uP0KHH5ccLhhev35zvsbj9MMWo4PH7szS9Fslkb9aRPCAG7115tvSxkOLwOJOq5sD1RcyYCMrw5DsilvlCZpFZAk26GKlYHpUmDgM0L4Zeh0CmhtGgjlvABgMdzPCzhq8jtyoE+Jivqa7GmmHXQqhTwnvYc46khnwlGTVWHoajMW++xEVHNmtccw0RUa95AEDuO/JHwAYDbH4QsgBOlXtjdfji9/lDCBwB+WUD+/Ztwf7D8Ob9okyQJKkXN32+dqZ6IIsPvC6LomBP5h+0oynMi4Aue+aAG4j1sD0v4gPJJXLzZdsie8p4/dUIMNC0MUMXqIprwAYDHm3dO9Q1BqZBwYUYslKddu0KSEGfQVDtxi0rB202iaONvIRFV6WiJG8EKQ5n8QRl+WYb8exJY5PSG/l2RJP1xMxAINo5Z7VKNqdXW6dV6xOpiGzCaxkf4g/AXlMF3pBT+gjIIf+O5Eaemw1HoRvYvhSjKc8JR6EbRMScO/1KI0pqWRGgAwVIf3PuK4ctxIOj0Qcin/V2TBQInq1inL9JEzb93QlT/PF1DSjRp0TXVAoUEuLwBeP1BJBg1CAQFChyeKv/up1p1UYiUiCri19tEzZjLV/1NRKm7vM7jD+JIsQtFZeXfgBc4PAAkFDu9kCSBkjIfVAoJBp0KJp0akgSUefwo9QagUUn4fMcxpFh0aJNoRIxGCYUkhT0X4vYFISCg19Tfn6O21rYodBfC5XeFlSskBbrEd6m3854PAiUe+HJLgQoJvD/fBU2mGaoITlBBzZvPE0DBYQfEabOhCCGQf8gOnVENtaZhZ9EVQsCX7UDQ7kXA4UOwzA+U+SHZfVAn6yGp/vhePFjD7J2RolbHha3JejqNOr7eYzgTjz+IzYeKYHf74Q/KOFxUBo9fRrJZB4NWiaMlbpwo9aJDsgma318/q16DzPjozzhN1Nwx6SNqxjrPXFVtXZ/WcRh9YRr2FpQiEBT4+KejCJz+Dfjv9Bol2iQakG6NgdsXxOe/HIc/WPW+F6RZ8PnUAaHtIS9vwDGbG9lzrz23i6mBTqVD39S+yLZn43jZcQRFEPG6eGRZsmDRNt/JBWRfsFLCBwAQAr4cBxT6OCga+EacmiZHoadSwneKEAKOk27EtzQ2aEyBEy4E7b8/a1ZhtKIIyAgUuqFO+SNRkZT1PwtxTEwmXK7DkOXKz7+pVCZotSn1HsOZbMstgd1dngAfLXHD8/sahgUODzLj9chKMKDA4cXREje6pJqRHqdH2yRjpeGgRNTwmPQRUZV0aiXsbj8C1SRvp+/bIcUEs14Nly8AhSShyvnNI8Tld5X3Dqr0kCQJQTmIEm8JAMCisaDYU4zjZccRkAOI1cUi3ZQOrVKLDnEd0CGuQ73FdSZ+XxA+VwAKlYSYaiY8aEiBIk/lhO8UIRAs9kCRwm/o6dz5PTUPTfR7G35IcaDoj2GlSr0awWIvTv3dkr1ByL5g6EuPSC7LUB2lUovY2L6wO7Yh4HeEyjWaBFgsF4YNnY+GUo8fJ0vLE9KgLFDiCn/+8USpF51bmBFn0ECSJFzWPrHa2T6JqOEx6SNqxnY/PbTaOoUk4ZvdBThuc8MvC4y5KA1uXwAnSn1IMGhg0KmQZtUj0aRBvsMDu8sPty8IpaTAHZdmIdUaA7Wy8sP+13ZrEVa2evrl1fYAnK7QXYg9xXvg8JbfEMWoYhCjioHT74Qv6IMQAkdKj0Cr1CLZkAwAOOE6gcP2w7g45eKo9er5vAHk/FIER6EbSrUCOqMaOr0aSa3M0Jujl/yJGtbcAspvfIkiQaWt+eZfFYUeZVFhEhlJKUEZq0WwpMLzhb9/4aXQq6GKj2mQmNRqMxLir4Dfb0Mw6IZKZYRKZWqQc59JxUXZA7Jc6fsiT4XXUwgBX1Bm0ncGXncA3jI/lGoF9GZN1BN7atqY9BE1Y2d6js6oU6FrmhUlZT64/UG4fEEYtCoof5+JTaNSQKtWIjPeABFX/k1weX31/+PSqMJvAmJqebNX5C7C//L/Fzab6DHnMeQ6cpFmSgMAHLQdxPGy4xBCoIWhBdrHtYdVa4Uv6MPPJ3/GZWmX1epckVRm92LXxjy4neXfist+GUIIWFMM8PuCyOwSD01Mw/8pFrKA8MuQ3QFIGmWVw9ckDu2kCLEkxMCW76ryCx4JEswJDT/Rh6RRhiV+KrMGkkoBudQL2SdD0qugTjZAlaiP+EydZ6JWW6FWWxv0nGeirfC3W61UQKmQwib7Uiv/eAZSpVAghglftYJ+GccP2eEsccPnCUJSSNCbNEjJssDAZ6mpnjDpI6JqpZh1cLj9iP99KKLXH0Spxx/6t93tg93tg0alQIJRi8x4Axwef9iNQEXmGPVZP9ux37Y/LOEDgAJXAQBgV9EumDVmnHSdhN1rh1/2o8RTgmJvMdJN6Ug3pQMAij3FiNPFndX5z0bAH0TOr0VwO32QAwIuhw+B32fGdNq8iG9phFavQlwLIxRKCTFGdYPcXAaK3PAfL4Ps9sN/wgVIEpQmNZRWHYQvAOGVASWgNTfvWU0pcjQxKiRmmHAytzQs8ZMgIamVCRpdw9+OqOJ18B8vCytT6lVQ6lVQGNTQtePnv6I4gwZmXfk6rApJQqJRi3zHHz2j8RWGrKfHxYQlgRTu2P4SFGQ74C71hXpM7UoXymxedLgkBVq9OroBUpPEpI+IqpWVYEBusQue3xMVrVoJq16NnCIX/AEZ2grf5BY6fWibZEScwYCDJ51VttcuqfYTNVScWTQoB3HcURTaVkgAFAF4A174ZT9OljmgFHqcdDngCwoAKvjkAArLHFCjCLKQobFq4Al4apyxNNIzi9pPuuF1+QEBlNk8CAZlBHwyAn4ZckCGs8SD/EN2tOmZBJ1BDYVSQnIrMyxJ9begfcDmhe9IKQBAUiuhitMhUOxBwOZFoMgDSV1+o6aK18F70AZ1qhHqhIYZ2kZNmzVZD71ZA/tJN/zeINRaJSyJMVHp6QYAVaIeclkAQUf4xCmSRglNRnQXQW+semZYselgEXxBGS2sOnj8Qdjcfhi1KqRYyv9OJJq06JLaeCfIKnQX4mjpUfiCPhg1RmSaM2FQN9yzy26nDwXZDrgc4c9EBoMCtgIX8g85kNk1+jO1UtPDpI+IqqVTKzGgbQJ25TmQ7/BACIGMWD0KS71Q6f74JlKpkJBmjcFxuweXt09EUBbIKXaFeubUSgU6pJiQFlv7ZKammUW7pAN3Di3vESvzl2H9xqshyyoAF1Xa12TOxxWX7IBRbYRBbcCAv61DcZmv0n5A5GcW9f8+bMfnCSAYlOEtCyIYCMLvkxHwBiEE4PfKOPzzSahjVDBYtCjILv8fflqHWCjq4ZvyQMFpPRsmDSStEr4cB2RvEOpYI5RmDRRqBSAL+I+WQqFVQmmK/sQzdP471ePXGEgKCdrWFgQdPgRsHkAASoMaylhdg8zWeT6y6jUY2DEJhwvLUFzmQ4o5BkatCgoJUCgkJJm01S7Q3hjsKtqFHHtOaLvQXYhcRy56JPVAiqFhZkctK/HCXVr1/4MEgJNHSpn0Ub1g0kdENTJoVeidFQdfQIY/KCO7sAxqlQIefxBObwBKSYIlRg3F78MSj5a40T3dig4pJhQ6veXDgEzaiA/1USlUMGlMKPGU4Ey3Z96gF8ecx2DWRObb+9r2FirVCgiNBJc3gDJvEH5/EAG/jKA/AF9AhgKA8AjYCz2wJsXAZvfAYNHi0J5ieIIy0jrEVtkucHa9kCIoILurjl3SKKHUKCGpFZAdvvKk1B+EpFYg6A5A3zUhaomfLPvh9ebD5ytBMOiEQqGBUmWEPiYDSmX99YpWH49AscsHCYA1Rg0lh7Gd15RmDZRRnFCptoJBD1yuQ3C5DsPjzQOEgFabAr2+FfT6NlCpzq23qrZ/13RqJTLj9ciMr/p3z+MPhv2tasjRFTU54ToRlvCdIgsZP5/8GfG6eKiV9T+s0vf7F37V8Z9hgi2is8Wkj4hqRaNSQKNSwBMoX5dJp1ZWOTPbqaGgOrWyTj17pzt9ZtESTwl+yv8JspBx6rG3FoYWOOE+gcsv/QregBdFniKU+VwIiiBiVDro1QYY1HqoFEbE6eJw0n0S3z0ysNpzKk6bOa26mUVr6oUc2CERC2/rDaB88ooBC76DNyiH7yQB0AIZsgIT/HrIARkuhw/PeUpQlvv7vj+GHxKRXkjp95/Tl+X7fZbOoMsP2R+EJIBghaFHsssPb4wKqvgYaNIbtpfG5cpGqXM33O6j8HryIIQMIWSoNbFQKNSIj7sUZnN3SFLDJF4HTzqxv6AU+Q4PCuxeeANBpMXGoGdGLDqmmGs9MVFDKPWVIigHYdKYoFQ0nrio7oJBF4qLv4PXV4Sysv2AKP874fEWIBh0wePJQ1xc/3Oa6bO2f9cAoNczq/+/vTsPj6q8+z/+PufMmX2y74SEfa0goCBg6wIVePooLlVq0WKl/bUKrehTqrW1aq1FbGtt1Qu0D7VqtVqtO1UEH6TuIBSLgmFRWZNAQpaZzH7O/ftjSCQmSMAkE9Pv67rmusiZ7cNkMme+577P9yaSaL+774T+OTz2vYktP3fn7Apb2exq3MWe0B5iVgy/mZq+WeQrYk9wzxHvZ9kWlU2VlGWUHdfzHotAtgtN09qco97Mm9FzR0rFF5sUfUKIYxI4SsMFfyc1ZPj0kV6vMx+3OZ6Kugrqo/UA5HvzmVwymdXWag5GDlIbi+NzOXDobmxsDD1JeWYxAVeAQm8hddE6CnIKOpzh836Bd3ocfGYHbk1D0zQ0HWxL0RlrGx7tqLqR6cKqT53DFE6mvrQl4xaxqhBWfQzNqaOSCsPtwHuomYAVShCKJtCrLZxuA0ems83jfvpofWcUP+Hwxxw8+Dq2ShCL7sNWScLhj7GtMLrhxespp6r6ORKJenJyvoyud+0u7eOaJt7b28CBYIxdB8OfbK8Np6ZlBWM9Ym2ymkgNW2q3EIynzt00DZPyjHIGZw1Oa0v4SCjOvq31NNRE0HWNjDwPhf0zsC2FlbBx+Rw9Yv3KwylbYYdTzat0b/c0WmpPMLTl0Ejfx8TjB1EqgaaZOBx+IpHdGIaXYHAz2dkT0pKvJ1BKsb56PQfCB1q2xZIxaiO1DM4eTDQZ/Yx7QyQZ6eqIJOOp2R5Ot0EkGEd3tD5Y5XQZFPbrGdOfRe+jqSMdauglGhsbyczMpKGhgYwMOTFbiM8rmrBYtaW63Q6duqYxdXhhl492RJNRbGXjcXhYtWsVkUSEXY27ePfAu9RGUw1fHJqDgCtAeUY5Gc4MBmUNYkTuCAZkDfjcz38s05XC8STRUIINK3dRX91Ew/4omg5W3MaybEw0DEPHdOskdY2C8gD+HDcZeW6y8r0t5z91dBpUv+uWHzHbGUPzWXbxWKLb6sGyGff4eiKfHoU8ZIzhYElhPobPRPc6mLp5J3VHOLL/6aP1k2/7P16/7swj5jgaywrT0LCRurq3SCYbicUPYCWbiEYrsezmcxI1nM583O5iMgInkps7iUBg5HE/59EopVi5uZqmWJI3dtRS1Rht6WSb6TYpz/MyrjyHgfl+vtQnk6qGKDsOhKgPJzANjdJsL4MK/DgdXTMiGbNiVDVVcTBykIq6CixlURmqpC5Wh6EZ+J1+Tsg7gallU7tlCtvh4pEk+7bVUbG2mmhT6jVzmAamS8dK2hQN+KRNvdtnUjIoq9vX7bOCcZI1EeyYhe7UMXI9qLhFsjqMOjS7AUPHLPRidmGjpfYoZVFd/Q9CoQ84WPc6qYNDBppmousmbncR2VkT0A03BfnT0PXjK5yP9XOtK277eaZ37gvtY+P+jW22J+0kmqZR4C2gNlLb9o6HjC4YTR9/n2N+3o46sCtIfXVq2ZJIMM6BXamGZy6PA92h4fE7ych1Uzo8B7evc/5G5TuwOJyM9AkhjonbNDi5Xw7vfFxH0v6kYDB0jXHl2d0yvc3tSK3pFbfiJKwEDt3BgKwBeE0vm2s2E7ZSTWQMzSDPnUffjL4YutFpJ+ofyxcSr9OBN8fBxOn92Pz6PnbHaolFLJSukYxr2LZC10HXddwOHZ/LJC/Pg+HQycv3HvG5jvd11t0O3IOzSFSHP/uGKvVF2AiYaN3YXTEWq6ay8mniiYNEIzsxDC+WFSYc2UkyGcTQXaSGTxWJRAO2HU+F1WxcrhKczq5ps98Ut4gkLLZWh9i2P0gkcei9ryAYiVDZEMXnNKhvivPu7noqqoOHljJxUpjhZtv+INWNUU4dnNfp57d+3PAxHxz8AFvZbKvfxpbaLdRF67AsC9MwcTvcZLgySFpJXIaLL5d+GVPvnsLPStrsqahjzwcHiTYlsC2bRNQmFI9hxS1cPhPbVgwYk4+yIdwYZ++2espHdl8ji0RVE4mqTxocWVGI7wuh4jaOnMPWD7Rs4ruDqKSNWeTrtlE/y4rRGHyPYOP7WMkoltWErZLomo7h8GNZQXzeIbjdRSjV/oGZjjjWz7VWGW3F1uoge+rC+FwOynK8lGR6SNg2sYSNy9Q79PifZ/+xL7Sv1c8HowfZF9pH3I6jo1MaKMVluAg4246kuQwXRd6ua+RSV9VE3aEmWomYhZVUBHJcxCNJFOB0O7Btm3jMYtfmWhymQVahl+wiryzYLjqNFH1CiGNWmOHmqyMK2VMXJnxoKl/fbG+XjWIciambmIZJwkqNHhR4CwhlhgjFDy0ZoUGfQB8MzWBg1kC8Zvc3/Wjmy3QxYEw+kWCC4MEIybiNlbSINCTQDA3d0MjIdZFf6sdw6HgCTnyZx35ux6fPhTxc8zmLutuBqzyD9Td+lYYXPiaxvwk7amHHLVTMQiVSTWZQqTEFTdN44fThODKdGJkuXOUZ7T5us1XXnNbmuTtytD8c3klNzcs0hFLrL0biCqXqicUPkkjYKNuBrmu4TbBtC00LE0koEqoBmyosbTV+/zAC/iGtHrfZkUYROpJN1yCWtNlxIEgomiCWtIklbeIJG00Dh6Gz6oP9lGR6KMlKrVHWFEvSFEtSH07QP89LLGmxubKRwQX+ThvhqInUsLl2MwAJK8E7Ve+wJ7SHpnjqC6ZDd+AyXGS5snDqTqqaqtjduLvbRrwbayLEowlqasPEk0liTRao1BqWScsmFozRGIwRj1pk5nlwmDrKrePMdpHZzoLtHZlKfCwjS6HGKNE9jUDqIIcdSqASNlZDDE2DDB2MDBfKVgRrwqhwEm1PI2ZZADPPi6PAg6Zpnfpe+/Rtg6GPaWyqIxSJEosdRKkkmqZwOSwsO47TmcOB+gry8/sQTTrQrORnPm5nNktpiCR4Y3sNL75fSUMkiddpkOUxyTx0yQ+4cRzqhJrvdzGqbxZ+V9d89UzYqf1AOBGmoq6CDw5+kJqyqSDgDBBOhgknwoTiIfxOP30DfRmQNQCf6WNc4bguO+9VqdRSDMpW1O+PEKqPEmmI0xRMNczy+EyyinwYpk64MU5WoRe3D2r2BElELQr7ywid6BxS9AkhjovToTMgv+Pr7nUFTdPo4+/Dxw0fA6BrOgMyB1ATqaE2WovP4aPAW0D/zP7d1o77s+QW+xl8UgFVHzUQDSWxLRvDoRGPWiil8Ge5cbgNMvI85Pc9vtf2WI/WR6JJHLqOcmvYlkJ5NJRu09xeTsVt0DQCWak29q4iP8ZRnqO9o/VHaxKxbM6JBIPvkUwGuejRE4klDWBcm9sOy/mYn016BKXiaJqbq1++gmD88GL+o0OXjjeJ6EgDC6/TQdKyWbVlP+3MbAagPpIg0+2ksj5CaY6XJzfsJZZsf/psR7MdrUhofu/bymbTgQr2NhygKZkkYaW+aNs6JK0EscRBYDtjCsawr2kfRd4jN6zoaJHQkdct3BjHSiqu21NJ/NNnkxw6VlBmG/y/ulRB7wmY/M+m3QTf2tru47b3un16KvGxNCQ5+fbVRI7wOxpjmtwbtTGLvNgxixmbPqb+0HmwvHn0XMf7XmvWulnKaYcuKUOzP+S6CfehVBTLivK9pyaTWm7wpTaP29nNUprVhmKs3FLNWztqOXho2m4wmiQcs6hqjOHQYVBBgKFFqZG1A6EYr2+v4fSh+bgcnV9gZbmy2Bfax/aG7Wyu3dzqHL29TXvZ1bgLp8OJz/QRSUY4GD1IU6KJK068gix31nE9Z0eKeDupSMQtDhwIU7svROhg6iBH4lADrVA4STiaJL/Yj9tvUl8dJqOPF83QiVQFceU4W61l2Z0dT0XvIu8QIcQX2pDsITTEGqiL1gGpwq/AW8CArAGMLxrfMhW0pyjsn4mdVDR9akFob8BJft8AptvokvX5jsTwmdihBJquobkdEE2CU0fFUyMymtPAzPegGRpmsa/Llm2IRisPTU07+lQmW1nourPbpz2V5352S3ylwDQ0LAWhaOe0XT9akXDplNSodn2snvuXD8Oy2j+v0enbiWvI40STUSzb6raOipqeGsU++g1TzYyiwUQntDPqPCppkayLga34zD77afLJ30D3TwHctLeByvoIjYfObW0WTViEExaZHpPaphiRuLflQFA0YbGzNsyQwo43K+no6Gh5RjkrP/4ntaEgoViC5q+4CTtOKJpAQ6FpCeJ6nCxXFrZtUhU8yD92rOKCIRcc8XHh8x340AwNpeDy1yvaHvgA0KFfk8GCkInTbaA7dL614n0amwv+Z1rfvKuKeNH7fSGKvnvuuYdf//rXVFVVMXr0aO666y7Gjx9/9DsKIXo9h+7glOJTqA5XU9VUBUCuJ5cSX0mPbFOv6xp9hmYTCcVpqk996fZnuzrtxP1j5RqQSWJ/GBSpBdkNEzthg9NAc+oExhfhyPVgZLvQP8e0rKNNO7XiqdE508zib9/Y2HKdUjbhyE5isSo0zYGm2ZhGBkpZaJrJ3dMexucbTE7O5JZlG0wzm5yciR1egqMjU2IBBub7mTKigL21EWqaYsQSNroOpq5jo3AZBm5TJ2lDPGlz/thPmkJkeU365/nok5Va3qGj2Y7GZbiIJqOpTp3qyNPAFApN06iP1ZPjzgGqjvm5Pq0jr5s/20WoLso9owewr6IeSE3tTMQtkvHU1FjT1FvWOlTAovI+9B2egzvgpGxETruP26y9qcQd/X0CvHXll4lsqcVuSB2EsRpjqISN3ZQ4NLdZxw4n0d0Gz/YrwZHtRnM7MIs+GV02S/y48ltPHf+87zWA9TdMBWDv3seoq19HMLgZZccPHRyxcRhe0DQMw8dDF71Pft5XycpuOzreWe+1wwWjCRoiCZriFgmr9WPFD019VgpiCZtYsvUU3P2NsWMq+jo6Ouo1vdz1VB8SyVJgUpvbOn07KR3yBEk7VUS++sZXSSRcPA/cQOvn6MzCSte1o36+KyAZV8SjFm6/3qMOfIjeo8cXfY899hjXXHMNS5cuZcKECdx5551MmzaNiooKCgo63npdCNF7aZpGka+oR0zh7CiP39kj2tO7BmYTrw4T3x2EhA26hu4y0ANO3MNycI/I7ZQRtaNNPYqpLAAcjkz8Hh/JZPCTjI4iYi43um7gdOYRj+0nFqsCNPy+PuTkjsfQPxkd9Xh87T7fkZpEdHRaVGGGi4G5fqJxG9PQCMeT2GippQ8VOAyNDLdJNGGj61qrhi05Xice08HIksxjyna0IqEqvJuGWAO6pjNzyhts3L+RiBUlYcexbRtDN9A0DVN34DczsLDol9mP164d/pmPe7gjFQkded0C2W4a/BFKyzOIHIjSVB9DQ8PQdSwHaGi4fA40HZqP0WRluvG6HbgcxlGfo73X7VimuWUUetF31JM89LtKWoCuozwmdiSJ7tSx46npnx5dx1DgzPOgHzY90XQYmJ9apuPzvtcOv212Rh9i4fVongCxePWhazXARNMcOJ05eF0m2RkleLq4WUqz5KFCz9A0HLpG8vA5z4fePkrZ6JrW5lzvrux/o3VgxFPXdPROWtezo0V8QXmAxaUlNDXEsRI2ybiF1fwaGqmp9SiFOvQ63jtpSEtH29KhOXj8ZruPC51TxIv/DD2+6Lvjjjv47ne/y7e//W0Ali5dyvLly/nTn/7Eddddl+Z0Qgjxxaa7DPwnFxHL9ZKsCaNsG91rYuZ7cZZndNsUSpczD9PMJJFowOsdSCxWRTxeg1JJDIef0vyvohQ0NW1F111omoHbXYLPNwT9U50oPZ5+XZJR0zROH5ZPMJpkh2UTtRQ6YGiQ6THRNQ2P00HAo+FzOYjEU9OzTEOjT7aXsWXZZHmPrdA/WpFQllHG/vB+GmONZHm9ZHm9JCJNGEpHKe1QbvAYJiW+Ekblj2q3e+Fn+TxFgnZoZPvgvibshGLP9jqaDkaxbYXHbxIJJbASCqfbwHQ5cHtMfNmpL7u+rK4/KKIZOq4h2VjrqlCWShUsCjRTx8z0ppoaGToohWbqOPK96J9ai9TI6NqcWZnjaGzYSCJ+EFslsJIhFDaaZuJy5uF05uLxlOF2d91yA58WcDswDZ0cn5OA20Fd+JMpni6HTjRh4TB0cv3ONu/hosxjm3J/LKOjD1xRxPsH3mdr3VZqDi3fUxuppSZSAyh0zSBgpt7/X560EoAhWYP5xrBvUOArOOLjfp4DH5A6yFc+KIs9FfVEGmPYLoNk3MYwdTQgmVRoht7yc3aWG8Oh481wkZvj+ezH7ublTcQXV48u+uLxOOvXr+cnP/lJyzZd15k6dSpvvvnmZ9xTCCFERxl+J54TcrGDGaikje420L3dP900K2s89fXrSCTqcbtLcLtLQDPIyhyT+jeQkzMZsLGsJurq16Hs1ucTBQIjcTpz2nn0zjGiJJOaUJyhxX7+vbuB+kgCv8vA7zbxO1PNSPwuB32yPcSSNg5D48S+WfTP9XVJAa1rOicVnUSRr4iYHaMp0UTSTpJUSZRSKKVwGk5K/CVMKZ/Cl/K+1OkZjppR18gr9ZNX6qfviByqP26kckcDSikcTgNN13Ader9pmoY34MThMMjqpvXwnIU+rEHZJA9GU69Z3EZ3GqkC0KfhKHCTrI6gaRpGZusCz8h2tykCO5vDESA393RAI9S0A8sKoewEmqaj6U4yAidQVHhOy/Tm7uAwdPrl+ogmLIoz3UQTdkvTGYehkx9wURBwMfBTzb4y3CZlOcf2ez2W0dGR+YOpi1VTn9iPw2FTH6vHb5uELYOkSuI3/fid/kM5LUzdZET+IMqyij5z9K8zCqv+o/MJ1qWm9CulSMQsElELXYdAwInTa+B0G2Tke3CYBoFcNwVlslC76Dw9uuirqanBsiwKCwtbbS8sLOSDDz5o9z6xWIxY7JMGCY2NqVbMzTs/IYQQ7dMDnxR66fi81HU3OTlfJh6vJZlsRNOcuN1FaJrRkqd54Wldd5OXeyaRyG6SySC64cbjLsXh8Hdp9oDLwcn9snl3dwOZg03qwnFqQnH8ToMRfTIZXBDA6zIIx1LnMWV6uv411dDoG+jL7GGz2V6/nX/u/idvV75NLBnDbbrpn9GfITlDGJY9jBJfSVr3hYFcN4FcN9lFXqo/akA3/TTVxQkH46Agq8CDP9tFflkAw9S7LatrYCaaqaE5NBJVTSil0BwGjjw3utPAUexDd2igHfo9GjqOXDdmka9bMgYCo9B1N6a5nkhkN7Ydw2Fmk5N9ChkZozAMV7f/XocV+UlYFjqQ7THZVRcmGE1Smu3h9CEF+NwO9tRFiCUsdF2jNNvL8OIAhq51WdaAGeCU4lPwODz8e/+/8Tl8FHuL6evvm1q7UlmpKaAqteTPuIJxTCiegEbXZWqWVehl6PgCPtpUw8F9TeimhjfTRNM1MvO9lA3PIbPAg2HoON0ODPPQea6fI5d87xWH01QPfkfs27ePPn368MYbbzBx4sSW7T/+8Y9Zs2YNb7/9dpv73HTTTdx8881ttu/cuZOMDFnrRAghxOenlKIhkiBpK/wuR6tOf+mmlCJqRakMVRJJRnCbbgrcBQRcPWvUwEpaNDXEU9PcHKnRPtOlY3RBO/+OsuMWdiiRaugSTy1dorkdOHLcGAEnKmmjrNRUz+5anP1wStnYdgLQMIz0nxMMEEta1DelOgBne81W57IqpUjYNg5NR+/m1ytmxVrWbHXqThoTjXxQ+wH7w/txOVwMzR5K/8z+3b5+azyaJFQXI9IYRzM0MvM9eDO6phtxY2Mj5eXlNDQ0yHdg0bOLvng8jtfr5YknnuDcc89t2T5nzhzq6+t55pln2tynvZG+vn37Ul9fL294IYQQQnRIc1ONdBR3QnSGxsZGsrKypOgTQA+f3ul0Ohk3bhwvv/xyS9Fn2zYvv/wy8+fPb/c+LpcLl8vVZrumad2+ppMQQgghvpi0jqwvKEQPJt97xeF6dNEHcM011zBnzhxOOukkxo8fz5133klTU1NLN08hhBBCCCGEEEfW44u+WbNmceDAAX7+859TVVXFiSeeyIsvvtimuYsQQgghhBBCiLZ69Dl9naGxsZHMzEyZzyyEEEIIIf5jyHdgcbjuW9RFCCGEEEIIIUS3k6JPCCGEEEIIIXoxKfqEEEIIIYQQoheTok8IIYQQQgghejEp+oQQQgghhBCiF5OiTwghhBBCCCF6MSn6hBBCCCGEEKIX6/GLs39ezcsQNjY2pjmJEEIIIYQQ3aP5u28vX5JbdFCvL/qCwSAAffv2TXMSIYQQQgghulcwGCQzMzPdMUSaaaqXl/+2bbNv3z4CgQCapnXqYzc2NtK3b192795NRkZGpz725yXZjl1PzQWS7Xj11Gw9NRdItuPRU3OBZDtePTVbT80Fku14dWU2pRTBYJCSkhJ0Xc7o+k/X60f6dF2ntLS0S58jIyOjx32INJNsx66n5gLJdrx6araemgsk2/HoqblAsh2vnpqtp+YCyXa8uiqbjPCJZlL2CyGEEEIIIUQvJkWfEEIIIYQQQvRiUvR9Di6XixtvvBGXy5XuKG1ItmPXU3OBZDtePTVbT80Fku149NRcINmOV0/N1lNzgWQ7Xj05m+hden0jFyGEEEIIIYT4TyYjfUIIIYQQQgjRi0nRJ4QQQgghhBC9mBR9QgghhBBCCNGLSdF3HJYsWcKoUaNa1lSZOHEiL7zwQrpjtXHbbbehaRoLFixIdxRuuukmNE1rdRk2bFi6Y7XYu3cvl1xyCbm5uXg8Hk444QTeeeeddMeiX79+bV43TdOYN29eWnNZlsUNN9xA//798Xg8DBw4kFtuuYWecopwMBhkwYIFlJeX4/F4mDRpEuvWrev2HP/85z85++yzKSkpQdM0nn766VbXK6X4+c9/TnFxMR6Ph6lTp7Jt27Yeke3JJ5/krLPOIjc3F03T2LhxY9pzJRIJrr32Wk444QR8Ph8lJSV861vfYt++fWnPBqnPuWHDhuHz+cjOzmbq1Km8/fbbPSLb4b7//e+jaRp33nlnj8h22WWXtfmMmz59etpzAWzZsoVzzjmHzMxMfD4fJ598Mrt27Up7tvb2C5qm8etf/zrt2UKhEPPnz6e0tBSPx8OIESNYunRpl+fqSLbq6mouu+wySkpK8Hq9TJ8+vVs+cxctWsTJJ59MIBCgoKCAc889l4qKila3iUajzJs3j9zcXPx+PxdccAHV1dVdnk3855Ci7ziUlpZy2223sX79et555x3OPPNMZs6cyfvvv5/uaC3WrVvHvffey6hRo9IdpcXIkSOprKxsubz22mvpjgRAXV0dkydPxjRNXnjhBTZv3sxvf/tbsrOz0x2NdevWtXrNVq5cCcCFF16Y1lyLFy9myZIl3H333WzZsoXFixdz++23c9ddd6U1V7PvfOc7rFy5koceeohNmzZx1llnMXXqVPbu3dutOZqamhg9ejT33HNPu9fffvvt/OEPf2Dp0qW8/fbb+Hw+pk2bRjQaTXu2pqYmTj31VBYvXtzlWTqaKxwOs2HDBm644QY2bNjAk08+SUVFBeecc07aswEMGTKEu+++m02bNvHaa6/Rr18/zjrrLA4cOJD2bM2eeuop3nrrLUpKSro8U7OOZJs+fXqrz7q//vWvac+1Y8cOTj31VIYNG8Yrr7zCv//9b2644Qbcbnfasx3+WlVWVvKnP/0JTdO44IIL0p7tmmuu4cUXX+Qvf/kLW7ZsYcGCBcyfP59nn302rdmUUpx77rl8+OGHPPPMM/zrX/+ivLycqVOn0tTU1KW51qxZw7x583jrrbdYuXIliUSCs846q9XzXn311Tz33HM8/vjjrFmzhn379nH++ed3aS7xH0aJTpGdna3+93//N90xlFJKBYNBNXjwYLVy5Up12mmnqauuuirdkdSNN96oRo8ene4Y7br22mvVqaeemu4YHXLVVVepgQMHKtu205rja1/7mrr88stbbTv//PPV7Nmz05ToE+FwWBmGoZ5//vlW28eOHat++tOfpimVUoB66qmnWn62bVsVFRWpX//61y3b6uvrlcvlUn/961/Tmu1wH330kQLUv/71r27NpNRn52q2du1aBaidO3d2T6hDOpKtoaFBAWrVqlXdE+qQI2Xbs2eP6tOnj3rvvfdUeXm5+t3vftetuY6Ubc6cOWrmzJndnuVw7eWaNWuWuuSSS9IT6DAdea/NnDlTnXnmmd0T6DDtZRs5cqT6xS9+0WpbOj5/P52toqJCAeq9995r2WZZlsrPz1d//OMfuzXb/v37FaDWrFmjlEp99pumqR5//PGW22zZskUB6s033+zWbKL3kpG+z8myLB599FGampqYOHFiuuMAMG/ePL72ta8xderUdEdpZdu2bZSUlDBgwABmz57dLVNkOuLZZ5/lpJNO4sILL6SgoIAxY8bwxz/+Md2x2ojH4/zlL3/h8ssvR9O0tGaZNGkSL7/8Mlu3bgXg3Xff5bXXXmPGjBlpzQWQTCaxLKvN0XiPx9NjRpcBPvroI6qqqlr9nWZmZjJhwgTefPPNNCb7YmloaEDTNLKystIdpZV4PM59991HZmYmo0ePTnccbNvm0ksvZeHChYwcOTLdcdp45ZVXKCgoYOjQoVxxxRXU1tamNY9t2yxfvpwhQ4Ywbdo0CgoKmDBhwmdOm02X6upqli9fzty5c9MdBUjtH5599ln27t2LUorVq1ezdetWzjrrrLTmisViAK32Dbqu43K5un3f0NDQAEBOTg4A69evJ5FItNofDBs2jLKyMtkfiE4jRd9x2rRpE36/H5fLxfe//32eeuopRowYke5YPProo2zYsIFFixalO0orEyZM4M9//jMvvvgiS5Ys4aOPPuLLX/4ywWAw3dH48MMPWbJkCYMHD2bFihVcccUV/PCHP+SBBx5Id7RWnn76aerr67nsssvSHYXrrruOb3zjGwwbNgzTNBkzZgwLFixg9uzZ6Y5GIBBg4sSJ3HLLLezbtw/LsvjLX/7Cm2++SWVlZbrjtaiqqgKgsLCw1fbCwsKW68Rni0ajXHvttVx88cVkZGSkOw4Azz//PH6/H7fbze9+9ztWrlxJXl5eumOxePFiHA4HP/zhD9MdpY3p06fz4IMP8vLLL7N48WLWrFnDjBkzsCwrbZn2799PKBTitttuY/r06bz00kucd955nH/++axZsyZtudrzwAMPEAgEesxUwLvuuosRI0ZQWlqK0+lk+vTp3HPPPXzlK19Ja67mIuonP/kJdXV1xONxFi9ezJ49e7p132DbNgsWLGDy5Ml86UtfAlL7A6fT2ebglewPRGdypDvAF9XQoUPZuHEjDQ0NPPHEE8yZM4c1a9aktfDbvXs3V111FStXruyWcw6OxeEjQKNGjWLChAmUl5fzt7/9Le1HJ23b5qSTTuJXv/oVAGPGjOG9995j6dKlzJkzJ63ZDrds2TJmzJjRrefiHMnf/vY3Hn74YR555BFGjhzJxo0bWbBgASUlJT3iNXvooYe4/PLL6dOnD4ZhMHbsWC6++GLWr1+f7miikyQSCS666CKUUixZsiTdcVqcccYZbNy4kZqaGv74xz9y0UUX8fbbb1NQUJC2TOvXr+f3v/89GzZsSPssgfZ84xvfaPn3CSecwKhRoxg4cCCvvPIKU6ZMSUsm27YBmDlzJldffTUAJ554Im+88QZLly7ltNNOS0uu9vzpT39i9uzZPWa/f9ddd/HWW2/x7LPPUl5ezj//+U/mzZtHSUlJWmcgmabJk08+ydy5c8nJycEwDKZOncqMGTO6tQnZvHnzeO+993rUzBPxn0FG+o6T0+lk0KBBjBs3jkWLFjF69Gh+//vfpzXT+vXr2b9/P2PHjsXhcOBwOFizZg1/+MMfcDgcaT1q+mlZWVkMGTKE7du3pzsKxcXFbYr14cOH95jppwA7d+5k1apVfOc730l3FAAWLlzYMtp3wgkncOmll3L11Vf3mBHmgQMHsmbNGkKhELt372bt2rUkEgkGDBiQ7mgtioqKANp0Z6uurm65TrSvueDbuXMnK1eu7DGjfAA+n49BgwZxyimnsGzZMhwOB8uWLUtrpldffZX9+/dTVlbWsm/YuXMn//M//0O/fv3Smq09AwYMIC8vL637h7y8PBwOR4/fN7z66qtUVFT0mH1DJBLh+uuv54477uDss89m1KhRzJ8/n1mzZvGb3/wm3fEYN24cGzdupL6+nsrKSl588UVqa2u7bd8wf/58nn/+eVavXk1paWnL9qKiIuLxOPX19a1uL/sD0Zmk6Osktm23zBdPlylTprBp0yY2btzYcjnppJOYPXs2GzduxDCMtOY7XCgUYseOHRQXF6c7CpMnT27TOnnr1q2Ul5enKVFb999/PwUFBXzta19LdxQg1UVR11t/fBiG0XJ0vKfw+XwUFxdTV1fHihUrmDlzZrojtejfvz9FRUW8/PLLLdsaGxt5++23e8z5wT1Rc8G3bds2Vq1aRW5ubrojfaaesG+49NJL+fe//91q31BSUsLChQtZsWJFWrO1Z8+ePdTW1qZ1/+B0Ojn55JN7/L5h2bJljBs3rkecNwqpv89EItHj9w+ZmZnk5+ezbds23nnnnS7fNyilmD9/Pk899RT/93//R//+/VtdP27cOEzTbLU/qKioYNeuXbI/EJ1Gpnceh5/85CfMmDGDsrIygsEgjzzyCK+88krad56BQKBlfngzn89Hbm5um+3d7Uc/+hFnn3025eXl7Nu3jxtvvBHDMLj44ovTmgtSbZInTZrEr371Ky666CLWrl3Lfffdx3333ZfuaEDqS+P999/PnDlzcDh6xp/s2Wefza233kpZWRkjR47kX//6F3fccQeXX355uqMBsGLFCpRSDB06lO3bt7Nw4UKGDRvGt7/97W7NEQqFWo1WfPTRR2zcuJGcnBzKyspYsGABv/zlLxk8eDD9+/fnhhtuoKSkhHPPPTft2Q4ePMiuXbta1sBr/vJbVFTUpUeePytXcXExX//619mwYQPPP/88lmW1nO+Sk5OD0+nsslxHy5abm8utt97KOeecQ3FxMTU1Ndxzzz3s3bu3W5ZYOdrv89PFsWmaFBUVMXTo0LRmy8nJ4eabb+aCCy6gqKiIHTt28OMf/5hBgwYxbdq0tOUqKytj4cKFzJo1i6985SucccYZvPjiizz33HO88sorXZqrI9kgdZDo8ccf57e//W2X5zmWbKeddhoLFy7E4/FQXl7OmjVrePDBB7njjjvSnu3xxx8nPz+fsrIyNm3axFVXXcW5557b5U1m5s2bxyOPPMIzzzxDIBBo+dzKzMzE4/GQmZnJ3Llzueaaa8jJySEjI4Mf/OAHTJw4kVNOOaVLs4n/IGntHfoFdfnll6vy8nLldDpVfn6+mjJlinrppZfSHatdPWXJhlmzZqni4mLldDpVnz591KxZs9T27dvTHavFc889p770pS8pl8ulhg0bpu677750R2qxYsUKBaiKiop0R2nR2NiorrrqKlVWVqbcbrcaMGCA+ulPf6pisVi6oymllHrsscfUgAEDlNPpVEVFRWrevHmqvr6+23OsXr1aAW0uc+bMUUqllm244YYbVGFhoXK5XGrKlCnd9ns+Wrb777+/3etvvPHGtOVqXj6ivcvq1au7NNfRskUiEXXeeeepkpIS5XQ6VXFxsTrnnHPU2rVruzzX0bK1pzuXbPisbOFwWJ111lkqPz9fmaapysvL1Xe/+11VVVWV1lzNli1bpgYNGqTcbrcaPXq0evrpp7s8V0ez3Xvvvcrj8XT7Z9vRslVWVqrLLrtMlZSUKLfbrYYOHap++9vfdstSQ0fL9vvf/16VlpYq0zRVWVmZ+tnPftYt+60jfW7df//9LbeJRCLqyiuvVNnZ2crr9arzzjtPVVZWdnk28Z9DU6obz14VQgghhBBCCNGt5Jw+IYQQQgghhOjFpOgTQgghhBBCiF5Mij4hhBBCCCGE6MWk6BNCCCGEEEKIXkyKPiGEEEIIIYToxaToE0IIIYQQQoheTIo+IYQQQgghhOjFpOgTQgghhBBCiF5Mij4hhBBp8ec//5msrKxufc5XXnkFTdOor6/v1ucVQggh0kmKPiGE6AWai5kjXc4444x0RxRCCCFEmjjSHUAIIcTnN2nSJCorK9tsf/bZZ/n+97/PlVdemYZUQgghhOgJZKRPCCF6AafTSVFRUatLXV0dP/rRj7j++uu58MILW267Zs0axo8fj8vlori4mOuuu45kMtlyfSwW44c//CEFBQW43W5OPfVU1q1b13J986jiihUrGDNmDB6PhzPPPJP9+/fzwgsvMHz4cDIyMvjmN79JOBw+pv/HM888w9ixY3G73QwYMICbb765Jds3v/lNZs2a1er2iUSCvLw8HnzwQQBs22bRokX0798fj8fD6NGjeeKJJ4759RRCCCF6Eyn6hBCiF6qvr2fmzJmcfvrp3HLLLS3b9+7dy3/9139x8skn8+6777JkyRKWLVvGL3/5y5bb/PjHP+bvf/87DzzwABs2bGDQoEFMmzaNgwcPtnqOm266ibvvvps33niD3bt3c9FFF3HnnXfyyCOPsHz5cl566SXuuuuuDmd+9dVX+da3vsVVV13F5s2buffee/nzn//MrbfeCsDs2bN57rnnCIVCLfdZsWIF4XCY8847D4BFixbx4IMPsnTpUt5//32uvvpqLrnkEtasWXNcr6MQQgjRKyghhBC9imVZasaMGWr48OGqsbGx1XXXX3+9Gjp0qLJtu2XbPffco/x+v7IsS4VCIWWapnr44Ydbro/H46qkpETdfvvtSimlVq9erQC1atWqltssWrRIAWrHjh0t2773ve+padOmHTHn/fffrzIzM1t+njJlivrVr37V6jYPPfSQKi4uVkoplUgkVF5ennrwwQdbrr/44ovVrFmzlFJKRaNR5fV61RtvvNHqMebOnasuvvjiVtnr6uqOmEsIIYTobeScPiGE6GWuv/563nzzTdauXUsgEGh13ZYtW5g4cSKaprVsmzx5MqFQiD179lBfX08ikWDy5Mkt15umyfjx49myZUurxxo1alTLvwsLC/F6vQwYMKDVtrVr13Y497vvvsvrr7/eMrIHYFkW0WiUcDiM1+vloosu4uGHH+bSSy+lqamJZ555hkcffRSA7du3Ew6H+epXv9rqcePxOGPGjOlwDiGEEKK3kaJPCCF6kUcffZTf/OY3LF++nMGDB3fpc5mm2fJvTdNa/dy8zbbtDj9eKBTi5ptv5vzzz29zndvtBlJTPE877TT279/PypUr8Xg8TJ8+veX+AMuXL6dPnz6t7u9yuTqcQwghhOhtpOgTQoheYuPGjcydO5fbbruNadOmtXub4cOH8/e//x2lVMto3+uvv04gEKC0tJTc3FycTievv/465eXlQKpZyrp161iwYEGX5h87diwVFRUMGjToiLeZNGkSffv25bHHHuOFF17gwgsvbCk2R4wYgcvlYteuXZx22mldmlUIIYT4IpGiTwgheoGamhrOPfdcTj/9dC655BKqqqpaXW8YBvn5+Vx55ZXceeed/OAHP2D+/PlUVFRw4403cs0116DrOj6fjyuuuIKFCxeSk5NDWVkZt99+O+FwmLlz53bp/+HnP/85//3f/01ZWRlf//rX0XWdd999l/fee69Vo5lvfvObLF26lK1bt7J69eqW7YFAgB/96EdcffXV2LbNqaeeSkNDA6+//joZGRnMmTOnS/MLIYQQPZUUfUII0QssX76cnTt3snPnToqLi9tcX15ezscff0yfPn34xz/+wcKFCxk9ejQ5OTnMnTuXn/3sZy23ve2227Btm0svvZRgMMhJJ53EihUryM7O7tL/w7Rp03j++ef5xS9+weLFizFNk2HDhvGd73yn1e1mz57NrbfeSnl5eatzDwFuueUW8vPzWbRoER9++CFZWVmMHTuW66+/vkuzCyGEED2ZppRS6Q4hhBBCCCGEEKJryDp9QgghhBBCCNGLSdEnhBBCCCGEEL2YFH1CCCGEEEII0YtJ0SeEEEIIIYQQvZgUfUIIIYQQQgjRi0nRJ4QQQgghhBC9mBR9QgghhBBCCNGLSdEnhBBCCCGEEL2YFH1CCCGEEEII0YtJ0SeEEEIIIYQQvZgUfUIIIYQQQgjRi0nRJ4QQQgghhBC92P8HF9fuh38aWO0AAAAASUVORK5CYII=",
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",
       "text/plain": [
        "<Figure size 900x500 with 1 Axes>"
       ]
@@ -1203,13 +1497,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 14,
    "id": "71b008e2",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 900x500 with 1 Axes>"
       ]
@@ -1254,7 +1548,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 15,
    "id": "1b29b1e5-21f0-4732-9be7-3dd653e67478",
    "metadata": {},
    "outputs": [
@@ -1262,7 +1556,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "=== TiTiler-CMR Tile Benchmark (Global Pool) ===\n",
+      "=== TiTiler-CMR Tile Benchmark ===\n",
       "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
       "Dataset: C2723754864-GES_DISC (xarray)\n",
       "Query params: 8 parameters\n",
@@ -1274,7 +1568,7 @@
       "  temporal_mode: point\n",
       "  tile_format: png\n",
       "  tile_scale: 1\n",
-      "Total execution time: 7.163s\n"
+      "Total execution time: 1.291s\n"
      ]
     },
     {
@@ -1317,82 +1611,82 @@
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>7</td>\n",
-       "      <td>30</td>\n",
+       "      <td>29</td>\n",
        "      <td>52</td>\n",
        "      <td>200</td>\n",
        "      <td>True</td>\n",
        "      <td>False</td>\n",
        "      <td>False</td>\n",
-       "      <td>1.343241</td>\n",
+       "      <td>0.968540</td>\n",
        "      <td>image/png</td>\n",
        "      <td>694</td>\n",
        "      <td>https://staging.openveda.cloud/api/titiler-cmr...</td>\n",
        "      <td>None</td>\n",
-       "      <td>7.162834</td>\n",
+       "      <td>1.290854</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>7</td>\n",
-       "      <td>31</td>\n",
+       "      <td>30</td>\n",
        "      <td>52</td>\n",
        "      <td>200</td>\n",
        "      <td>True</td>\n",
        "      <td>False</td>\n",
        "      <td>False</td>\n",
-       "      <td>2.334120</td>\n",
+       "      <td>1.289355</td>\n",
        "      <td>image/png</td>\n",
        "      <td>694</td>\n",
        "      <td>https://staging.openveda.cloud/api/titiler-cmr...</td>\n",
        "      <td>None</td>\n",
-       "      <td>7.162834</td>\n",
+       "      <td>1.290854</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>7</td>\n",
-       "      <td>29</td>\n",
-       "      <td>53</td>\n",
+       "      <td>31</td>\n",
+       "      <td>52</td>\n",
        "      <td>200</td>\n",
        "      <td>True</td>\n",
        "      <td>False</td>\n",
        "      <td>False</td>\n",
-       "      <td>1.638145</td>\n",
+       "      <td>1.278380</td>\n",
        "      <td>image/png</td>\n",
        "      <td>694</td>\n",
        "      <td>https://staging.openveda.cloud/api/titiler-cmr...</td>\n",
        "      <td>None</td>\n",
-       "      <td>7.162834</td>\n",
+       "      <td>1.290854</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>7</td>\n",
-       "      <td>30</td>\n",
+       "      <td>29</td>\n",
        "      <td>53</td>\n",
        "      <td>200</td>\n",
        "      <td>True</td>\n",
        "      <td>False</td>\n",
        "      <td>False</td>\n",
-       "      <td>1.863235</td>\n",
+       "      <td>1.096978</td>\n",
        "      <td>image/png</td>\n",
        "      <td>694</td>\n",
        "      <td>https://staging.openveda.cloud/api/titiler-cmr...</td>\n",
        "      <td>None</td>\n",
-       "      <td>7.162834</td>\n",
+       "      <td>1.290854</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>7</td>\n",
-       "      <td>31</td>\n",
+       "      <td>30</td>\n",
        "      <td>53</td>\n",
        "      <td>200</td>\n",
        "      <td>True</td>\n",
        "      <td>False</td>\n",
        "      <td>False</td>\n",
-       "      <td>1.424258</td>\n",
+       "      <td>0.897303</td>\n",
        "      <td>image/png</td>\n",
        "      <td>694</td>\n",
        "      <td>https://staging.openveda.cloud/api/titiler-cmr...</td>\n",
        "      <td>None</td>\n",
-       "      <td>7.162834</td>\n",
+       "      <td>1.290854</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1400,11 +1694,11 @@
       ],
       "text/plain": [
        "   zoom   x   y  status_code    ok  no_data  is_error  response_time_sec  \\\n",
-       "0     7  30  52          200  True    False     False           1.343241   \n",
-       "1     7  31  52          200  True    False     False           2.334120   \n",
-       "2     7  29  53          200  True    False     False           1.638145   \n",
-       "3     7  30  53          200  True    False     False           1.863235   \n",
-       "4     7  31  53          200  True    False     False           1.424258   \n",
+       "0     7  29  52          200  True    False     False           0.968540   \n",
+       "1     7  30  52          200  True    False     False           1.289355   \n",
+       "2     7  31  52          200  True    False     False           1.278380   \n",
+       "3     7  29  53          200  True    False     False           1.096978   \n",
+       "4     7  30  53          200  True    False     False           0.897303   \n",
        "\n",
        "  content_type  response_size_bytes  \\\n",
        "0    image/png                  694   \n",
@@ -1421,14 +1715,14 @@
        "4  https://staging.openveda.cloud/api/titiler-cmr...       None   \n",
        "\n",
        "   total_run_elapsed_s  \n",
-       "0             7.162834  \n",
-       "1             7.162834  \n",
-       "2             7.162834  \n",
-       "3             7.162834  \n",
-       "4             7.162834  "
+       "0             1.290854  \n",
+       "1             1.290854  \n",
+       "2             1.290854  \n",
+       "3             1.290854  \n",
+       "4             1.290854  "
       ]
      },
-     "execution_count": 46,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1463,7 +1757,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 16,
    "id": "15892fb3",
    "metadata": {},
    "outputs": [
@@ -1471,7 +1765,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "=== TiTiler-CMR Tile Benchmark (Global Pool) ===\n",
+      "=== TiTiler-CMR Tile Benchmark ===\n",
       "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
       "Dataset: C2723754864-GES_DISC (rasterio)\n",
       "Query params: 7 parameters\n",
@@ -1482,7 +1776,7 @@
       "  bands_regex: B[0-9][0-9]\n",
       "  tile_format: png\n",
       "  tile_scale: 1\n",
-      "=== TiTiler-CMR Tile Benchmark (Global Pool) ===\n",
+      "=== TiTiler-CMR Tile Benchmark ===\n",
       "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
       "Dataset: C2723754864-GES_DISC (rasterio)\n",
       "Query params: 8 parameters\n",
@@ -1494,7 +1788,7 @@
       "  bands_regex: B[0-9][0-9]\n",
       "  tile_format: png\n",
       "  tile_scale: 1\n",
-      "=== TiTiler-CMR Tile Benchmark (Global Pool) ===\n",
+      "=== TiTiler-CMR Tile Benchmark ===\n",
       "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
       "Dataset: C2723754864-GES_DISC (rasterio)\n",
       "Query params: 9 parameters\n",
@@ -1507,9 +1801,9 @@
       "  bands_regex: B[0-9][0-9]\n",
       "  tile_format: png\n",
       "  tile_scale: 1\n",
-      "Total execution time: 26.082s\n",
-      "Total execution time: 27.484s\n",
-      "Total execution time: 28.554s\n"
+      "Total execution time: 11.284s\n",
+      "Total execution time: 11.279s\n",
+      "Total execution time: 11.539s\n"
      ]
     }
    ],
@@ -1561,7 +1855,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 17,
    "id": "492c0c0e-564b-4bea-8848-88264539d1d8",
    "metadata": {},
    "outputs": [
@@ -1600,69 +1894,69 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
-       "      <td>1.392389</td>\n",
-       "      <td>0.930824</td>\n",
-       "      <td>2.119112</td>\n",
+       "      <td>0.410660</td>\n",
+       "      <td>0.426614</td>\n",
+       "      <td>0.461730</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
-       "      <td>1.358718</td>\n",
-       "      <td>0.919507</td>\n",
-       "      <td>1.673362</td>\n",
+       "      <td>0.415497</td>\n",
+       "      <td>0.397273</td>\n",
+       "      <td>0.393417</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
-       "      <td>1.663322</td>\n",
-       "      <td>0.974480</td>\n",
-       "      <td>1.580107</td>\n",
+       "      <td>0.433671</td>\n",
+       "      <td>0.421229</td>\n",
+       "      <td>0.440330</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
-       "      <td>1.313399</td>\n",
-       "      <td>1.446751</td>\n",
-       "      <td>1.333293</td>\n",
+       "      <td>0.431295</td>\n",
+       "      <td>0.479685</td>\n",
+       "      <td>0.436232</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
-       "      <td>1.059130</td>\n",
-       "      <td>1.242408</td>\n",
-       "      <td>1.002137</td>\n",
+       "      <td>0.474089</td>\n",
+       "      <td>0.460010</td>\n",
+       "      <td>0.411149</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
-       "      <td>0.828156</td>\n",
-       "      <td>1.026818</td>\n",
-       "      <td>0.891187</td>\n",
+       "      <td>0.428483</td>\n",
+       "      <td>0.418377</td>\n",
+       "      <td>0.415656</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11</th>\n",
-       "      <td>1.018971</td>\n",
-       "      <td>1.143670</td>\n",
-       "      <td>0.966605</td>\n",
+       "      <td>0.437670</td>\n",
+       "      <td>0.413992</td>\n",
+       "      <td>0.417438</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12</th>\n",
-       "      <td>1.212874</td>\n",
-       "      <td>1.284740</td>\n",
-       "      <td>1.133225</td>\n",
+       "      <td>0.415965</td>\n",
+       "      <td>0.409747</td>\n",
+       "      <td>0.438415</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13</th>\n",
-       "      <td>1.313594</td>\n",
-       "      <td>0.948578</td>\n",
-       "      <td>1.512228</td>\n",
+       "      <td>0.429743</td>\n",
+       "      <td>0.440041</td>\n",
+       "      <td>0.403096</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14</th>\n",
-       "      <td>1.218939</td>\n",
-       "      <td>1.200256</td>\n",
-       "      <td>1.398682</td>\n",
+       "      <td>0.439326</td>\n",
+       "      <td>0.446605</td>\n",
+       "      <td>0.435765</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15</th>\n",
-       "      <td>1.175385</td>\n",
-       "      <td>1.415249</td>\n",
-       "      <td>1.177417</td>\n",
+       "      <td>0.436366</td>\n",
+       "      <td>0.448823</td>\n",
+       "      <td>0.397425</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1671,20 +1965,20 @@
       "text/plain": [
        "        1 band   2 bands   3 bands\n",
        "zoom                              \n",
-       "5     1.392389  0.930824  2.119112\n",
-       "6     1.358718  0.919507  1.673362\n",
-       "7     1.663322  0.974480  1.580107\n",
-       "8     1.313399  1.446751  1.333293\n",
-       "9     1.059130  1.242408  1.002137\n",
-       "10    0.828156  1.026818  0.891187\n",
-       "11    1.018971  1.143670  0.966605\n",
-       "12    1.212874  1.284740  1.133225\n",
-       "13    1.313594  0.948578  1.512228\n",
-       "14    1.218939  1.200256  1.398682\n",
-       "15    1.175385  1.415249  1.177417"
+       "5     0.410660  0.426614  0.461730\n",
+       "6     0.415497  0.397273  0.393417\n",
+       "7     0.433671  0.421229  0.440330\n",
+       "8     0.431295  0.479685  0.436232\n",
+       "9     0.474089  0.460010  0.411149\n",
+       "10    0.428483  0.418377  0.415656\n",
+       "11    0.437670  0.413992  0.417438\n",
+       "12    0.415965  0.409747  0.438415\n",
+       "13    0.429743  0.440041  0.403096\n",
+       "14    0.439326  0.446605  0.435765\n",
+       "15    0.436366  0.448823  0.397425"
       ]
      },
-     "execution_count": 53,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1703,13 +1997,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 18,
    "id": "01357d6d-5831-4928-a096-703bcec6f37c",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 600x500 with 1 Axes>"
       ]
@@ -1768,22 +2062,10 @@
     "- [Earthdata Cloud CMR Datasets](https://cmr.earthdata.nasa.gov/search/site/docs/search/api.html#datasets)\n"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "fc89069c",
-   "metadata": {},
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "id": "fcfb0fc5",
-   "metadata": {},
-   "source": []
-  },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ae0f295a-0310-4e28-b986-c2ae70a02674",
+   "id": "571aa7c9-c7a8-4e02-b18f-2db532dc9aca",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1791,9 +2073,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": ".venv",
+   "display_name": "data_cube2",
    "language": "python",
-   "name": "python3"
+   "name": "data_cube2"
   },
   "language_info": {
    "codemirror_mode": {
diff --git a/docs/visualization/titiler/titiler-cmr/titiler-cmr-compatibility.ipynb b/docs/visualization/titiler/titiler-cmr/titiler-cmr-compatibility.ipynb
new file mode 100644
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@@ -0,0 +1,503 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "b44dbc99",
+   "metadata": {},
+   "source": [
+    "# TiTiler-CMR Compatibility\n",
+    "\n",
+    "This notebook walks you through a workflow to **check compatibility** of a [TiTiler-CMR](https://github.com/developmentseed/titiler-cmr) deployment for a given Earthdata CMR dataset.\n",
+    "\n",
+    "-----------------------------------\n",
+    "\n",
+    "**📚 In this notebook, you'll learn**:\n",
+    "\n",
+    "1. Use `earthaccess` to authenticate to NASA Earthdata and query the CMR catalog\n",
+    "2. Collect collection-level metadata (concept IDs, temporal range, spatial bounds)\n",
+    "3. Run `check_titiler_cmr_compatibility` against your TiTiler-CMR endpoint to validate whether a dataset can be successfully visualized and accessed via TiTiler-CMR.\n",
+    "\n",
+    "\n",
+    "Before you begin, you need:\n",
+    "- An Earthdata login account: https://urs.earthdata.nasa.gov/\n",
+    "- A valid `netrc` file with your Earthdata credentials or use interactive login.\n",
+    "\n",
+    "For this walkthrough, we will use the public instance hosted by [Open VEDA](https://staging.openveda.cloud/api/titiler-cmr/)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "18a0edb6-7220-4910-854d-3b07d4e4f417",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/jovyan/datacube-guide_2/datacube-guide/.venv/lib/python3.13/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "import earthaccess\n",
+    "import xarray as xr\n",
+    "\n",
+    "from datacube_benchmark.titiler import (\n",
+    "    DatasetParams,\n",
+    "    create_bbox_feature,\n",
+    "    check_titiler_cmr_compatibility\n",
+    ")\n",
+    "\n",
+    "endpoint = \"https://staging.openveda.cloud/api/titiler-cmr\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "71aab2bd",
+   "metadata": {},
+   "source": [
+    "### Introduction to TiTiler-CMR\n",
+    "[`Titiler-CMR`](https://github.com/developmentseed/titiler-cmr) is a dynamic map tile server that provides on-demand access to Earth science data managed by NASA's Common Metadata Repository (CMR). It allows users to dynamically generate and serve map tiles from multidimensional data formats like NetCDF and HDF5.\n",
+    "\n",
+    "To get started with TiTiler-CMR, you typically need to:\n",
+    "- Choose a Titiler-CMR endpoint\n",
+    "- Pick a CMR dataset (by concept ID)\n",
+    "- Identify the assets/variables/bands you want to visualize\n",
+    "- Define a temporal interval (`start/end` ISO range) and, if needed, a time step (e.g., daily).\n",
+    "- Select a backend that matches your dataset’s structure\n",
+    "\n",
+    "`titiler-cmr` supports two different backends:\n",
+    "  - **xarray** → for gridded/cloud-native datasets (e.g., NetCDF4/HDF5), typically exposed as variables.\n",
+    "  - **rasterio** → for COG/raster imagery-style datasets exposed as bands (optionally via a regex).\n",
+    "\n",
+    "Here, we first explore a dataset using `earthaccess` to collect the necessary information such as **concept_id**, **backend**, and **variable**, then run a compatibility check using the `check_titiler_cmr_compatibility` helper function. If you already know your dataset, you can skip the exploration steps step 2 directly. \n",
+    "\n",
+    "## Step 1: Explore data with `earthaccess`\n",
+    "You can use [`earthaccess`](https://github.com/nsidc/earthaccess) to search for dataset and inspect the individual granules used in your query. This helps you validate which files were accessed, their sizes, and the temporal range.\n",
+    "\n",
+    "First you need to authenticate to Earthdata. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "5712df15",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Authenticate to Earthdata\n",
+    "try:\n",
+    "    auth = earthaccess.login(strategy=\"environment\")\n",
+    "except Exception:\n",
+    "    auth = earthaccess.login(strategy=\"interactive\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f972367c",
+   "metadata": {},
+   "source": [
+    "Next, you can search for datasets using doi, keywords, temporal range, and spatial bounds."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "618eca85-a05c-4bfd-aa47-1576d9e932b3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Concept-Id:  C1996881146-POCLOUD\n",
+      "Abstract: A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced as a retrospective dataset (four day latency) and near-real-time dataset (one day latency) at the JPL Physical Oceanography DAAC using wavelets as basis functions in an optimal interpolation approach on a global 0.01 degree grid. The version 4 Multiscale Ultrahigh Resolution (MUR) L4 analysis is based upon nighttime GHRSST L2P skin and subskin SST observations from several instruments including the NASA Advanced Microwave Scanning Radiometer-EOS (AMSR-E), the JAXA Advanced Microwave Scanning Radiometer 2 on GCOM-W1, the Moderate Resolution Imaging Spectroradiometers (MODIS) on the NASA Aqua and Terra platforms, the US Navy microwave WindSat radiometer, the Advanced Very High Resolution Radiometer (AVHRR) on several NOAA satellites, and in situ SST observations from the NOAA iQuam project. The ice concentration data are from the archives at the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) High Latitude Processing Center and are also used for an improved SST parameterization for the high-latitudes.  The dataset also contains additional variables for some granules including a SST anomaly derived from a MUR climatology and the temporal distance to the nearest IR measurement for each pixel.This dataset is funded by the NASA MEaSUREs program ( http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects ), and created by a team led by Dr. Toshio M. Chin from JPL. It adheres to the GHRSST Data Processing Specification (GDS) version 2 format specifications. Use the file global metadata \"history:\" attribute to determine if a granule is near-realtime or retrospective.\n"
+     ]
+    }
+   ],
+   "source": [
+    "datasets = earthaccess.search_datasets(doi=\"10.5067/GHGMR-4FJ04\")\n",
+    "ds = datasets[0]\n",
+    "\n",
+    "concept_id = ds[\"meta\"][\"concept-id\"]\n",
+    "print(\"Concept-Id: \", concept_id)\n",
+    "print (\"Abstract:\", ds[\"umm\"][\"Abstract\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "774cecbf-996b-4edf-8df2-a31d4422a6c3",
+   "metadata": {},
+   "source": [
+    "### Examine the granules\n",
+    "\n",
+    "With a selected data collection, we'll now use `earthaccess.search_data` to find individual data granules within a specific temporal window."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "c1eecd4e-8ba0-4e67-b405-dbc7ae499b7e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Found 1 granules between 2024-10-12 and 2024-10-13\n",
+      "\n",
+      "2024-10-11T21:00:00.000Z → 707.34 MB\n",
+      "  https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/MUR-JPL-L4-GLOB-v4.1/20241012090000-JPL-L4_GHRSST-SSTfnd-MUR-GLOB-v02.0-fv04.1.nc\n"
+     ]
+    }
+   ],
+   "source": [
+    "time_range = (\"2024-10-12\", \"2024-10-13\")\n",
+    "\n",
+    "results = earthaccess.search_data(\n",
+    "    count=1,\n",
+    "    concept_id=concept_id,\n",
+    "    temporal=(\"2024-10-12\", \"2024-10-13\"),\n",
+    ")\n",
+    "print(f\"Found {len(results)} granules between {time_range[0]} and {time_range[1]}\")\n",
+    "\n",
+    "for g in results:\n",
+    "    start = g[\"umm\"][\"TemporalExtent\"][\"RangeDateTime\"][\"BeginningDateTime\"]\n",
+    "    size  = float(g[\"size\"])  # or use g[\"granule_size_mb\"] \n",
+    "\n",
+    "    print(f\"\\n{start} → {size:.2f} MB\")\n",
+    "\n",
+    "    for link in g.data_links(access=\"external\"):\n",
+    "        print(\" \", link)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "14e36c5f-9772-4cd5-a5bb-3fe443895e3a",
+   "metadata": {},
+   "source": [
+    "From the output above, the returned link ends with `.nc`, indicating a **NetCDF** file. We can open it directly with **xarray** using the authenticated HTTPS session from `earthaccess` and quickly list the variables (plus a peek at dimensions and coordinates)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "768c8f60-5f7b-40b3-a7ee-42c2b10361a5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_621/2053193160.py:3: FutureWarning: In a future version, xarray will not decode timedelta values based on the presence of a timedelta-like units attribute by default. Instead it will rely on the presence of a timedelta64 dtype attribute, which is now xarray's default way of encoding timedelta64 values. To continue decoding timedeltas based on the presence of a timedelta-like units attribute, users will need to explicitly opt-in by passing True or CFTimedeltaCoder(decode_via_units=True) to decode_timedelta. To silence this warning, set decode_timedelta to True, False, or a 'CFTimedeltaCoder' instance.\n",
+      "  ds = xr.open_dataset(\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Data variables:\n",
+       "    analysed_sst      (time, lat, lon) float64 5GB ...\n",
+       "    analysis_error    (time, lat, lon) float64 5GB ...\n",
+       "    mask              (time, lat, lon) float32 3GB ...\n",
+       "    sea_ice_fraction  (time, lat, lon) float64 5GB ...\n",
+       "    dt_1km_data       (time, lat, lon) timedelta64[ns] 5GB ...\n",
+       "    sst_anomaly       (time, lat, lon) float64 5GB ..."
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fs = earthaccess.get_fsspec_https_session()\n",
+    "\n",
+    "ds = xr.open_dataset(\n",
+    "    fs.open(results[0].data_links(access=\"external\")[0]),\n",
+    "    engine=\"h5netcdf\",\n",
+    ")\n",
+    "data_vars = ds.data_vars\n",
+    "data_vars"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f85292d1-4fff-4a41-b5ad-37f02e0d152a",
+   "metadata": {},
+   "source": [
+    "\n",
+    "Now, that we know the **concept_id**, **backend**, and **variable**, we can run a quick compatibility check using `check_titiler_cmr_compatibility()` helper function. \n",
+    "\n",
+    "## Step 2: Check Compatibility\n",
+    "\n",
+    "`check_titiler_cmr_compatibility()` helper function performs the following steps:\n",
+    "- Validate the **CMR collection** and **granule search**\n",
+    "- Resolve collection/granule metadata and fetch **TileJSON**\n",
+    "- Determine how many **time steps** fall within the requested temporal range\n",
+    "- Query the **`/timeseries/statistics`** endpoint for a small, bounded preview window to check if the dataset can be opened and processed with the selected backend.\n",
+    "\n",
+    "The result is a summary of compatibility, tiling parameters, and dataset statistics."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "5e41d95f-e087-4ee1-850a-5124710f7931",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "concept_id = \"C2723754864-GES_DISC\"\n",
+    "datetime_range = \"2024-10-12T00:00:01Z/2024-10-12T23:59:59Z\"\n",
+    "variable = \"precipitation\"\n",
+    "\n",
+    "ds_xarray = DatasetParams(\n",
+    "    concept_id=concept_id,\n",
+    "    backend=\"xarray\",\n",
+    "    datetime_range=datetime_range,\n",
+    "    variable=variable,\n",
+    "    step=\"P1D\",\n",
+    "    temporal_mode=\"point\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "e4b75cc7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "=== TiTiler-CMR Compatibility Check ===\n",
+      "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
+      "Dataset: C2723754864-GES_DISC (xarray)\n",
+      "Found 1 timesteps/granules from TileJSON\n",
+      "Using random bounds for compatibility check: [-56.309821758768926, -60.24222734692353, 24.188625431223507, -19.993003751927308]\n",
+      "Statistics returned 1 timesteps\n",
+      "Compatibility: compatible\n"
+     ]
+    }
+   ],
+   "source": [
+    "compat = await check_titiler_cmr_compatibility(\n",
+    "    endpoint=endpoint,\n",
+    "    dataset=ds_xarray,\n",
+    "    timeout_s=250.0,\n",
+    ")\n",
+    "\n",
+    "print(f\"Compatibility: {compat['compatibility']}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5a4a5f64",
+   "metadata": {},
+   "source": [
+    "Now, we want to check the summary of data is valid:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "7e4f56bd",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Statistics preview:\n",
+      "                       timestamp  min         max      mean     count  \\\n",
+      "0  2024-10-12T00:00:00.000000000  0.0  104.554993  3.270795  324093.0   \n",
+      "\n",
+      "           sum       std  median  majority  minority   unique  valid_percent  \\\n",
+      "0  1060041.625  9.195473     0.0       0.0      0.07  24401.0          100.0   \n",
+      "\n",
+      "   masked_pixels  valid_pixels  percentile_2  percentile_98  \n",
+      "0            0.0      325624.0           0.0      37.434998  \n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"Statistics preview:\\n{compat['statistics']}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a11fa928-9db7-43e4-9642-7be44f1cbabc",
+   "metadata": {},
+   "source": [
+    "### `rasterio` backend\n",
+    "\n",
+    "Similar to the `xarray` example above, we can check compatibility for a CMR collection that is better suited for the `rasterio` backend."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "95a85b3c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "=== TiTiler-CMR Compatibility Check ===\n",
+      "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
+      "Dataset: C2021957295-LPCLOUD (rasterio)\n",
+      "Found 1 timesteps/granules from TileJSON\n",
+      "Using random bounds for compatibility check: [66.86554859790496, -33.245004496793925, 147.36399578789738, 7.004219098202295]\n",
+      "~~~~~~~~~~~~~~~~ ERROR JSON REQUEST ~~~~~~~~~~~~~~~~\n",
+      "URL: https://staging.openveda.cloud/api/titiler-cmr/timeseries/statistics?concept_id=C2021957295-LPCLOUD&backend=rasterio&datetime=2024-07-01T00%3A00%3A00Z%2F2024-07-10T23%3A59%3A59Z&bands=B04&bands_regex=B%5B0-9%5D%5B0-9%5D&step=P1D&temporal_mode=point\n",
+      "Error: 400 Bad Request\n",
+      "Body: {\"detail\":\"The AOI for this request is too large for the /statistics endpoint for this dataset. Try again with either a smaller AOI\"}\n",
+      "Statistics request failed: HTTPStatusError: Client error '400 Bad Request' for url 'https://staging.openveda.cloud/api/titiler-cmr/timeseries/statistics?concept_id=C2021957295-LPCLOUD&backend=rasterio&datetime=2024-07-01T00%3A00%3A00Z%2F2024-07-10T23%3A59%3A59Z&bands=B04&bands_regex=B%5B0-9%5D%5B0-9%5D&step=P1D&temporal_mode=point'\n",
+      "For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/400\n",
+      "Compatibility: issues_detected\n"
+     ]
+    }
+   ],
+   "source": [
+    "ds_hls_day = DatasetParams(\n",
+    "    concept_id=\"C2021957295-LPCLOUD\",\n",
+    "    backend=\"rasterio\",\n",
+    "    datetime_range=\"2024-07-01T00:00:00Z/2024-07-10T23:59:59Z\",\n",
+    "    bands=[\"B05\", \"B04\"],\n",
+    "    bands_regex=\"B[0-9][0-9]\",\n",
+    "    step=\"P1D\",\n",
+    "    temporal_mode=\"point\",\n",
+    ")\n",
+    "compat = await check_titiler_cmr_compatibility(\n",
+    "    endpoint=endpoint,\n",
+    "    dataset=ds_hls_day,\n",
+    "    timeout_s=250.0,\n",
+    ")\n",
+    "\n",
+    "print(f\"Compatibility: {compat['compatibility']}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ebd5664e",
+   "metadata": {},
+   "source": [
+    "☝️ If your area of interest is too large, the API will return an “AOI is too large” error. Use the `create_bbox_feature` function to define a smaller bounding box before retrying.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "3e8ea321",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "=== TiTiler-CMR Compatibility Check ===\n",
+      "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
+      "Dataset: C2021957295-LPCLOUD (rasterio)\n",
+      "Found 1 timesteps/granules from TileJSON\n",
+      "Statistics returned 0 timesteps\n",
+      "Compatibility: compatible\n"
+     ]
+    }
+   ],
+   "source": [
+    "gulf_geometry = create_bbox_feature(\n",
+    "    -91.65432884883238,\n",
+    "    47.86503396133904,\n",
+    "    -91.53842043960762,\n",
+    "    47.9221313337365\n",
+    ")\n",
+    "compat = await check_titiler_cmr_compatibility(\n",
+    "    endpoint=endpoint,\n",
+    "    dataset=ds_hls_day,\n",
+    "    geometry=gulf_geometry,\n",
+    "    timeout_s=300.0,\n",
+    ")\n",
+    "print(f\"Compatibility: {compat['compatibility']}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9574d094",
+   "metadata": {},
+   "source": [
+    "Alternatively, you can specify `bounds_fraction` to create a much smaller bounding box within the original bounds."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "b7d43515",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "=== TiTiler-CMR Compatibility Check ===\n",
+      "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
+      "Dataset: C2021957295-LPCLOUD (rasterio)\n",
+      "Found 1 timesteps/granules from TileJSON\n",
+      "Using random bounds for compatibility check: [-66.40060957551924, 41.060132262770054, -65.26218961785861, 41.62934224160037]\n",
+      "Statistics returned 0 timesteps\n",
+      "Compatibility: compatible\n"
+     ]
+    }
+   ],
+   "source": [
+    "compat = await check_titiler_cmr_compatibility(\n",
+    "    endpoint=endpoint,\n",
+    "    dataset=ds_hls_day,\n",
+    "    bounds_fraction=1e-5,\n",
+    "    timeout_s=300.0,\n",
+    ")\n",
+    "print(f\"Compatibility: {compat['compatibility']}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cd88c0ec-12e0-4583-a51d-b1be67d5e62b",
+   "metadata": {},
+   "source": [
+    "### Conclusion\n",
+    "\n",
+    "This notebook demonstrated how to use `earthaccess` to explore CMR datasets and validate their compatibility with a TiTiler-CMR deployment using the `check_titiler_cmr_compatibility` helper function. \n",
+    "\n",
+    "\n",
+    "### 📚 Useful Resources\n",
+    "- [Titiler-CMR GitHub](https://github.com/developmentseed/titiler-cmr)\n",
+    "- [Earthaccess GitHub](https://github.com/nsidc/earthaccess)\n",
+    "- [CMR Search](https://cmr.earthdata.nasa.gov/search/site/docs/search/api.html)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "data_cube-working",
+   "language": "python",
+   "name": "data_cube-working"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/visualization/titiler/titiler-cmr/titiler-cmr-statistics-benchmark.ipynb b/docs/visualization/titiler/titiler-cmr/titiler-cmr-statistics-benchmark.ipynb
index 2b97b03..40ed388 100644
--- a/docs/visualization/titiler/titiler-cmr/titiler-cmr-statistics-benchmark.ipynb
+++ b/docs/visualization/titiler/titiler-cmr/titiler-cmr-statistics-benchmark.ipynb
@@ -22,7 +22,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "18a0edb6-7220-4910-854d-3b07d4e4f417",
    "metadata": {},
    "outputs": [],
@@ -133,7 +133,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 3,
    "id": "627eca1c",
    "metadata": {},
    "outputs": [
@@ -143,11 +143,11 @@
      "text": [
       "=== TiTiler-CMR Statistics Benchmark ===\n",
       "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
-      "Dataset: C2723754864-GES_DISC (xarray)\n",
+      "Dataset: C2036881735-POCLOUD (xarray)\n",
       "Statistics result:\n",
       "  Success: True\n",
-      "  Elapsed: 6.37s\n",
-      "  Timesteps: 8\n"
+      "  Elapsed: 1.48s\n",
+      "  Timesteps: 1\n"
      ]
     }
    ],
@@ -175,7 +175,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 4,
    "id": "816e47f2",
    "metadata": {},
    "outputs": [
@@ -186,371 +186,49 @@
       "  Statistics:\n",
       "{\n",
       "  \"2022-03-01T00:00:01+00:00\": {\n",
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-      "      \"valid_pixels\": 21033.0,\n",
-      "      \"percentile_2\": 0.0,\n",
-      "      \"percentile_98\": 4.244999885559082\n",
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-      "  \"2022-03-08T00:00:01+00:00\": {\n",
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       "          10,\n",
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       "        ]\n",
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-      "      \"valid_percent\": 100.0,\n",
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-      "      \"percentile_2\": 0.0,\n",
-      "      \"percentile_98\": 1.274999976158142\n",
+      "      \"valid_percent\": 68.49,\n",
+      "      \"masked_pixels\": 1087.0,\n",
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       "    }\n",
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       "}\n"
@@ -583,7 +261,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 5,
    "id": "36c3f623-9606-4a94-939e-b1d6c25958bf",
    "metadata": {},
    "outputs": [
@@ -593,11 +271,15 @@
      "text": [
       "=== TiTiler-CMR Statistics Benchmark ===\n",
       "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
-      "Dataset: C2723754864-GES_DISC (xarray)\n",
+      "Dataset: C2036881735-POCLOUD (xarray)\n",
+      "~~~~~~~~~~~~~~~~ ERROR JSON REQUEST ~~~~~~~~~~~~~~~~\n",
+      "URL: https://staging.openveda.cloud/api/titiler-cmr/timeseries/statistics?concept_id=C2036881735-POCLOUD&backend=xarray&datetime=2022-03-01T00%3A00%3A01Z%2F2022-03-01T23%3A59%3A59Z&variable=analysed_sst&step=P1D&temporal_mode=point\n",
+      "Error: 500 Internal Server Error\n",
+      "Body: {\"detail\":\"9 validation errors:\\n  {'type': 'literal_error', 'loc': ('response', \\\"FeatureCollection[Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]]\\\", 'type'), 'msg': \\\"Input should be 'FeatureCollection'\\\", 'input': 'Feature', 'ctx': {'expected': \\\"'FeatureCollection'\\\"}}\\n  {'type': 'missing', 'loc': ('response', \\\"FeatureCollection[Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]]\\\", 'features'), 'msg': 'Field required', 'input': Feature(bbox=None, type='Feature', geometry=Polygon(bbox=None, type='Polygon', coordinates=[[Position2D(longitude=-91.816, latitude=47.491), Position2D(longitude=-91.359, latitude=47.491), Position2D(longitude=-91.359, latitude=47.716), Position2D(longitude=-91.816, latitude=47.716), Position2D(longitude=-91.816, latitude=47.491)]]), properties={'statistics': {'2022-03-01T00:00:01+00:00': {'2022-03-01T12:00:00.000000000': {'min': None, 'max': None, 'mean': None, 'count': 0.0, 'sum': 0.0, 'std': None, 'median': None, 'majority': None, 'minority': None, 'unique': 0.0, 'histogram': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0.0, 0.1, 0.2, 0.30000000000000004, 0.4, 0.5, 0.6000000000000001, 0.7000000000000001, 0.8, 0.9, 1.0]], 'valid_percent': 0.0, 'masked_pixels': 6.0, 'valid_pixels': 0.0, 'percentile_2': None, 'percentile_98': None}}}}, id=None)}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'min'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'max'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'mean'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'std'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'median'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'majority'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'minority'), 'msg': 'Input should be a valid number', 'input': None}\\n\"}\n",
       "Statistics result:\n",
-      "  Success: True\n",
-      "  Elapsed: 3.54s\n",
-      "  Timesteps: 8\n"
+      "  Success: False\n",
+      "  Elapsed: 0.00s\n",
+      "  Timesteps: 0\n"
      ]
     }
    ],
@@ -625,7 +307,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 6,
    "id": "93b4b413",
    "metadata": {},
    "outputs": [],
@@ -653,7 +335,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 7,
    "id": "0342aa32",
    "metadata": {},
    "outputs": [
@@ -663,12 +345,16 @@
      "text": [
       "=== TiTiler-CMR Statistics Benchmark ===\n",
       "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
-      "Dataset: C2723754864-GES_DISC (xarray)\n",
+      "Dataset: C2036881735-POCLOUD (xarray)\n",
+      "~~~~~~~~~~~~~~~~ ERROR JSON REQUEST ~~~~~~~~~~~~~~~~\n",
+      "URL: https://staging.openveda.cloud/api/titiler-cmr/timeseries/statistics?concept_id=C2036881735-POCLOUD&backend=xarray&datetime=2022-03-01T00%3A00%3A01Z%2F2022-03-01T23%3A59%3A59Z&variable=analysed_sst&step=P1D&temporal_mode=point\n",
+      "Error: 500 Internal Server Error\n",
+      "Body: {\"detail\":\"9 validation errors:\\n  {'type': 'literal_error', 'loc': ('response', \\\"FeatureCollection[Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]]\\\", 'type'), 'msg': \\\"Input should be 'FeatureCollection'\\\", 'input': 'Feature', 'ctx': {'expected': \\\"'FeatureCollection'\\\"}}\\n  {'type': 'missing', 'loc': ('response', \\\"FeatureCollection[Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]]\\\", 'features'), 'msg': 'Field required', 'input': Feature(bbox=None, type='Feature', geometry=Polygon(bbox=None, type='Polygon', coordinates=[[Position2D(longitude=-91.63, latitude=47.550000000000004), Position2D(longitude=-91.53, latitude=47.550000000000004), Position2D(longitude=-91.53, latitude=47.65), Position2D(longitude=-91.63, latitude=47.65), Position2D(longitude=-91.63, latitude=47.550000000000004)]]), properties={'statistics': {'2022-03-01T00:00:01+00:00': {'2022-03-01T12:00:00.000000000': {'min': None, 'max': None, 'mean': None, 'count': 0.0, 'sum': 0.0, 'std': None, 'median': None, 'majority': None, 'minority': None, 'unique': 0.0, 'histogram': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0.0, 0.1, 0.2, 0.30000000000000004, 0.4, 0.5, 0.6000000000000001, 0.7000000000000001, 0.8, 0.9, 1.0]], 'valid_percent': 0.0, 'masked_pixels': 9.0, 'valid_pixels': 0.0, 'percentile_2': None, 'percentile_98': None}}}}, id=None)}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'min'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'max'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'mean'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'std'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'median'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'majority'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'minority'), 'msg': 'Input should be a valid number', 'input': None}\\n\"}\n",
       "Statistics result:\n",
-      "  Success: True\n",
-      "  Elapsed: 3.05s\n",
-      "  Timesteps: 8\n",
-      "  Statistics: {'2022-03-01T00:00:01+00:00': {'2022-03-01T00:00:00.000000000': {'min': 0.0, 'max': 0.0, 'mean': 0.0, 'count': 1.1200000047683716, 'sum': 0.0, 'std': 0.0, 'median': 0.0, 'majority': 0.0, 'minority': 0.0, 'unique': 1.0, 'histogram': [[0, 0, 0, 0, 0, 4, 0, 0, 0, 0], [-0.5, -0.4000000059604645, -0.30000001192092896, -0.19999998807907104, -0.09999999403953552, 0.0, 0.10000002384185791, 0.19999998807907104, 0.30000001192092896, 0.40000003576278687, 0.5]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 4.0, 'percentile_2': 0.0, 'percentile_98': 0.0}}, '2022-03-08T00:00:01+00:00': {'2022-03-08T00:00:00.000000000': {'min': 0.0, 'max': 0.3349999785423279, 'mean': 0.11964284628629684, 'count': 1.1200000047683716, 'sum': 0.1339999884366989, 'std': 0.16051772077980764, 'median': 0.0, 'majority': 0.0, 'minority': 0.3349999785423279, 'unique': 2.0, 'histogram': [[3, 0, 0, 0, 0, 0, 0, 0, 0, 1], [0.0, 0.03349999710917473, 0.06699999421834946, 0.10049998760223389, 0.1339999884366989, 0.16749998927116394, 0.20099997520446777, 0.2344999760389328, 0.2679999768733978, 0.30149996280670166, 0.3349999785423279]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 4.0, 'percentile_2': 0.0, 'percentile_98': 0.3349999785423279}}, '2022-03-15T00:00:01+00:00': {'2022-03-15T00:00:00.000000000': {'min': 0.0, 'max': 0.03999999910593033, 'mean': 0.02049107290804386, 'count': 1.1200000047683716, 'sum': 0.022950001060962677, 'std': 0.015410452994419422, 'median': 0.014999999664723873, 'majority': 0.0, 'minority': 0.0, 'unique': 4.0, 'histogram': [[1, 1, 0, 1, 0, 0, 0, 0, 0, 1], [0.0, 0.003999999724328518, 0.007999999448657036, 0.011999999172985554, 0.01599999889731407, 0.019999999552965164, 0.023999998345971107, 0.02799999713897705, 0.03199999779462814, 0.035999998450279236, 0.03999999910593033]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 4.0, 'percentile_2': 0.0, 'percentile_98': 0.03999999910593033}}, '2022-03-22T00:00:01+00:00': {'2022-03-22T00:00:00.000000000': {'min': 12.900001525878906, 'max': 15.210000991821289, 'mean': 13.628705978393555, 'count': 1.1200000047683716, 'sum': 15.264150619506836, 'std': 0.6724586834677247, 'median': 13.289999008178711, 'majority': 12.900001525878906, 'minority': 12.900001525878906, 'unique': 4.0, 'histogram': [[1, 1, 0, 1, 0, 0, 0, 0, 0, 1], [12.900001525878906, 13.131001472473145, 13.362001419067383, 13.593001365661621, 13.82400131225586, 14.055001258850098, 14.286001205444336, 14.517001152038574, 14.748001098632812, 14.97900104522705, 15.210000991821289]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 4.0, 'percentile_2': 12.900001525878906, 'percentile_98': 15.210000991821289}}, '2022-03-29T00:00:01+00:00': {'2022-03-29T00:00:00.000000000': {'min': 0.0, 'max': 0.019999999552965164, 'mean': 0.008705356158316135, 'count': 1.1200000047683716, 'sum': 0.009749999269843102, 'std': 0.008807097580713323, 'median': 0.004999999888241291, 'majority': 0.004999999888241291, 'minority': 0.0, 'unique': 3.0, 'histogram': [[1, 0, 2, 0, 0, 0, 0, 0, 0, 1], [0.0, 0.001999999862164259, 0.003999999724328518, 0.005999999586492777, 0.007999999448657036, 0.009999999776482582, 0.011999999172985554, 0.013999998569488525, 0.01599999889731407, 0.017999999225139618, 0.019999999552965164]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 4.0, 'percentile_2': 0.0, 'percentile_98': 0.019999999552965164}}, '2022-04-05T00:00:01+00:00': {'2022-04-05T00:00:00.000000000': {'min': 0.0, 'max': 0.059999994933605194, 'mean': 0.01160714216530323, 'count': 1.1200000047683716, 'sum': 0.012999999336898327, 'std': 0.020897434586007825, 'median': 0.0, 'majority': 0.0, 'minority': 0.02499999850988388, 'unique': 3.0, 'histogram': [[2, 0, 0, 0, 1, 0, 0, 0, 0, 1], [0.0, 0.005999999586492777, 0.011999999172985554, 0.017999999225139618, 0.023999998345971107, 0.029999997466802597, 0.035999998450279236, 0.041999995708465576, 0.047999996691942215, 0.053999997675418854, 0.059999994933605194]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 4.0, 'percentile_2': 0.0, 'percentile_98': 0.059999994933605194}}, '2022-04-12T00:00:01+00:00': {'2022-04-12T00:00:00.000000000': {'min': 8.375, 'max': 11.144999504089355, 'mean': 9.746606826782227, 'count': 1.1200000047683716, 'sum': 10.916199684143066, 'std': 1.26733015130025, 'median': 8.894999504089355, 'majority': 8.375, 'minority': 8.375, 'unique': 4.0, 'histogram': [[1, 1, 0, 0, 0, 0, 0, 0, 1, 1], [8.375, 8.652000427246094, 8.928999900817871, 9.205999374389648, 9.482999801635742, 9.760000228881836, 10.036999702453613, 10.31399917602539, 10.590999603271484, 10.868000030517578, 11.144999504089355]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 4.0, 'percentile_2': 8.375, 'percentile_98': 11.144999504089355}}, '2022-04-19T00:00:01+00:00': {'2022-04-19T00:00:00.000000000': {'min': 0.0, 'max': 0.0, 'mean': 0.0, 'count': 1.1200000047683716, 'sum': 0.0, 'std': 0.0, 'median': 0.0, 'majority': 0.0, 'minority': 0.0, 'unique': 1.0, 'histogram': [[0, 0, 0, 0, 0, 4, 0, 0, 0, 0], [-0.5, -0.4000000059604645, -0.30000001192092896, -0.19999998807907104, -0.09999999403953552, 0.0, 0.10000002384185791, 0.19999998807907104, 0.30000001192092896, 0.40000003576278687, 0.5]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 4.0, 'percentile_2': 0.0, 'percentile_98': 0.0}}}\n"
+      "  Success: False\n",
+      "  Elapsed: 0.00s\n",
+      "  Timesteps: 0\n",
+      "  Statistics: {}\n"
      ]
     }
    ],
@@ -697,7 +383,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 8,
    "id": "2d02f67a",
    "metadata": {},
    "outputs": [
@@ -707,22 +393,30 @@
      "text": [
       "=== TiTiler-CMR Statistics Benchmark ===\n",
       "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
-      "Dataset: C2723754864-GES_DISC (xarray)\n",
+      "Dataset: C2036881735-POCLOUD (xarray)\n",
       "=== TiTiler-CMR Statistics Benchmark ===\n",
       "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
-      "Dataset: C2723754864-GES_DISC (xarray)\n",
+      "Dataset: C2036881735-POCLOUD (xarray)\n",
       "=== TiTiler-CMR Statistics Benchmark ===\n",
       "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
-      "Dataset: C2723754864-GES_DISC (xarray)\n",
+      "Dataset: C2036881735-POCLOUD (xarray)\n",
       "=== TiTiler-CMR Statistics Benchmark ===\n",
       "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
-      "Dataset: C2723754864-GES_DISC (xarray)\n",
+      "Dataset: C2036881735-POCLOUD (xarray)\n",
       "=== TiTiler-CMR Statistics Benchmark ===\n",
       "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
-      "Dataset: C2723754864-GES_DISC (xarray)\n",
+      "Dataset: C2036881735-POCLOUD (xarray)\n",
+      "~~~~~~~~~~~~~~~~ ERROR JSON REQUEST ~~~~~~~~~~~~~~~~\n",
+      "URL: https://staging.openveda.cloud/api/titiler-cmr/timeseries/statistics?concept_id=C2036881735-POCLOUD&backend=xarray&datetime=2022-03-01T00%3A00%3A01Z%2F2022-03-01T23%3A59%3A59Z&variable=analysed_sst&step=P1D&temporal_mode=point\n",
+      "Error: 500 Internal Server Error\n",
+      "Body: {\"detail\":\"9 validation errors:\\n  {'type': 'literal_error', 'loc': ('response', \\\"FeatureCollection[Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]]\\\", 'type'), 'msg': \\\"Input should be 'FeatureCollection'\\\", 'input': 'Feature', 'ctx': {'expected': \\\"'FeatureCollection'\\\"}}\\n  {'type': 'missing', 'loc': ('response', \\\"FeatureCollection[Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]]\\\", 'features'), 'msg': 'Field required', 'input': Feature(bbox=None, type='Feature', geometry=Polygon(bbox=None, type='Polygon', coordinates=[[Position2D(longitude=-91.83, latitude=47.35), Position2D(longitude=-91.33, latitude=47.35), Position2D(longitude=-91.33, latitude=47.85), Position2D(longitude=-91.83, latitude=47.85), Position2D(longitude=-91.83, latitude=47.35)]]), properties={'statistics': {'2022-03-01T00:00:01+00:00': {'2022-03-01T12:00:00.000000000': {'min': None, 'max': None, 'mean': None, 'count': 0.0, 'sum': 0.0, 'std': None, 'median': None, 'majority': None, 'minority': None, 'unique': 0.0, 'histogram': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0.0, 0.1, 0.2, 0.30000000000000004, 0.4, 0.5, 0.6000000000000001, 0.7000000000000001, 0.8, 0.9, 1.0]], 'valid_percent': 0.0, 'masked_pixels': 9.0, 'valid_pixels': 0.0, 'percentile_2': None, 'percentile_98': None}}}}, id=None)}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'min'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'max'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'mean'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'std'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'median'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'majority'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'minority'), 'msg': 'Input should be a valid number', 'input': None}\\n\"}\n",
       "=== TiTiler-CMR Statistics Benchmark ===\n",
       "Client: 2 physical / 4 logical cores | RAM: 30.89 GiB\n",
-      "Dataset: C2723754864-GES_DISC (xarray)\n"
+      "Dataset: C2036881735-POCLOUD (xarray)\n",
+      "~~~~~~~~~~~~~~~~ ERROR JSON REQUEST ~~~~~~~~~~~~~~~~\n",
+      "URL: https://staging.openveda.cloud/api/titiler-cmr/timeseries/statistics?concept_id=C2036881735-POCLOUD&backend=xarray&datetime=2022-03-01T00%3A00%3A01Z%2F2022-03-01T23%3A59%3A59Z&variable=analysed_sst&step=P1D&temporal_mode=point\n",
+      "Error: 500 Internal Server Error\n",
+      "Body: {\"detail\":\"9 validation errors:\\n  {'type': 'literal_error', 'loc': ('response', \\\"FeatureCollection[Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]]\\\", 'type'), 'msg': \\\"Input should be 'FeatureCollection'\\\", 'input': 'Feature', 'ctx': {'expected': \\\"'FeatureCollection'\\\"}}\\n  {'type': 'missing', 'loc': ('response', \\\"FeatureCollection[Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]]\\\", 'features'), 'msg': 'Field required', 'input': Feature(bbox=None, type='Feature', geometry=Polygon(bbox=None, type='Polygon', coordinates=[[Position2D(longitude=-91.63, latitude=47.550000000000004), Position2D(longitude=-91.53, latitude=47.550000000000004), Position2D(longitude=-91.53, latitude=47.65), Position2D(longitude=-91.63, latitude=47.65), Position2D(longitude=-91.63, latitude=47.550000000000004)]]), properties={'statistics': {'2022-03-01T00:00:01+00:00': {'2022-03-01T12:00:00.000000000': {'min': None, 'max': None, 'mean': None, 'count': 0.0, 'sum': 0.0, 'std': None, 'median': None, 'majority': None, 'minority': None, 'unique': 0.0, 'histogram': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0.0, 0.1, 0.2, 0.30000000000000004, 0.4, 0.5, 0.6000000000000001, 0.7000000000000001, 0.8, 0.9, 1.0]], 'valid_percent': 0.0, 'masked_pixels': 9.0, 'valid_pixels': 0.0, 'percentile_2': None, 'percentile_98': None}}}}, id=None)}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'min'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'max'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'mean'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'std'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'median'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'majority'), 'msg': 'Input should be a valid number', 'input': None}\\n  {'type': 'float_type', 'loc': ('response', \\\"Feature[Annotated[Union[Point, MultiPoint, LineString, MultiLineString, Polygon, MultiPolygon, GeometryCollection], FieldInfo(annotation=NoneType, required=True, discriminator='type')], TimeseriesStatisticsInGeoJSON]\\\", 'properties', 'statistics', '2022-03-01T00:00:01+00:00', '2022-03-01T12:00:00.000000000', 'minority'), 'msg': 'Input should be a valid number', 'input': None}\\n\"}\n"
      ]
     },
     {
@@ -759,86 +453,86 @@
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>xarray</td>\n",
-       "      <td>C2723754864-GES_DISC</td>\n",
+       "      <td>C2036881735-POCLOUD</td>\n",
        "      <td>20.0</td>\n",
        "      <td>True</td>\n",
-       "      <td>200</td>\n",
-       "      <td>3.333515</td>\n",
-       "      <td>8</td>\n",
+       "      <td>200.0</td>\n",
+       "      <td>1.960267</td>\n",
+       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>xarray</td>\n",
-       "      <td>C2723754864-GES_DISC</td>\n",
+       "      <td>C2036881735-POCLOUD</td>\n",
        "      <td>10.0</td>\n",
        "      <td>True</td>\n",
-       "      <td>200</td>\n",
-       "      <td>5.793644</td>\n",
-       "      <td>8</td>\n",
+       "      <td>200.0</td>\n",
+       "      <td>1.777272</td>\n",
+       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>xarray</td>\n",
-       "      <td>C2723754864-GES_DISC</td>\n",
+       "      <td>C2036881735-POCLOUD</td>\n",
        "      <td>5.0</td>\n",
        "      <td>True</td>\n",
-       "      <td>200</td>\n",
-       "      <td>5.391589</td>\n",
-       "      <td>8</td>\n",
+       "      <td>200.0</td>\n",
+       "      <td>2.019030</td>\n",
+       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>xarray</td>\n",
-       "      <td>C2723754864-GES_DISC</td>\n",
+       "      <td>C2036881735-POCLOUD</td>\n",
        "      <td>1.0</td>\n",
        "      <td>True</td>\n",
-       "      <td>200</td>\n",
-       "      <td>2.780133</td>\n",
-       "      <td>8</td>\n",
+       "      <td>200.0</td>\n",
+       "      <td>1.672029</td>\n",
+       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>xarray</td>\n",
-       "      <td>C2723754864-GES_DISC</td>\n",
+       "      <td>C2036881735-POCLOUD</td>\n",
        "      <td>0.5</td>\n",
-       "      <td>True</td>\n",
-       "      <td>200</td>\n",
-       "      <td>1.837056</td>\n",
-       "      <td>8</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>xarray</td>\n",
-       "      <td>C2723754864-GES_DISC</td>\n",
+       "      <td>C2036881735-POCLOUD</td>\n",
        "      <td>0.1</td>\n",
-       "      <td>True</td>\n",
-       "      <td>200</td>\n",
-       "      <td>1.923999</td>\n",
-       "      <td>8</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "  backend            concept_id  edge_deg  success  status_code  elapsed_s  \\\n",
-       "0  xarray  C2723754864-GES_DISC      20.0     True          200   3.333515   \n",
-       "1  xarray  C2723754864-GES_DISC      10.0     True          200   5.793644   \n",
-       "2  xarray  C2723754864-GES_DISC       5.0     True          200   5.391589   \n",
-       "3  xarray  C2723754864-GES_DISC       1.0     True          200   2.780133   \n",
-       "4  xarray  C2723754864-GES_DISC       0.5     True          200   1.837056   \n",
-       "5  xarray  C2723754864-GES_DISC       0.1     True          200   1.923999   \n",
+       "  backend           concept_id  edge_deg  success  status_code  elapsed_s  \\\n",
+       "0  xarray  C2036881735-POCLOUD      20.0     True        200.0   1.960267   \n",
+       "1  xarray  C2036881735-POCLOUD      10.0     True        200.0   1.777272   \n",
+       "2  xarray  C2036881735-POCLOUD       5.0     True        200.0   2.019030   \n",
+       "3  xarray  C2036881735-POCLOUD       1.0     True        200.0   1.672029   \n",
+       "4  xarray  C2036881735-POCLOUD       0.5    False          NaN   0.000000   \n",
+       "5  xarray  C2036881735-POCLOUD       0.1    False          NaN   0.000000   \n",
        "\n",
        "   n_timesteps  \n",
-       "0            8  \n",
-       "1            8  \n",
-       "2            8  \n",
-       "3            8  \n",
-       "4            8  \n",
-       "5            8  "
+       "0            1  \n",
+       "1            1  \n",
+       "2            1  \n",
+       "3            1  \n",
+       "4            0  \n",
+       "5            0  "
       ]
      },
-     "execution_count": 50,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -897,13 +591,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 9,
    "id": "17f4cc56",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x500 with 1 Axes>"
       ]
@@ -946,7 +640,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 10,
    "id": "5dba464c-80cc-40cc-8e6e-373b9110861e",
    "metadata": {},
    "outputs": [
@@ -962,18 +656,10 @@
       "Error: 400 Bad Request\n",
       "Body: {\"detail\":\"The AOI for this request is too large for the /statistics endpoint for this dataset. Try again with either a smaller AOI\"}\n",
       "Statistics result:\n",
-      "  Success: False\n"
-     ]
-    },
-    {
-     "ename": "TypeError",
-     "evalue": "unsupported format string passed to NoneType.__format__",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
-      "\u001b[31mTypeError\u001b[39m                                 Traceback (most recent call last)",
-      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[55]\u001b[39m\u001b[32m, line 10\u001b[39m\n\u001b[32m      8\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33m\"\u001b[39m\u001b[33mStatistics result:\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m      9\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33m  Success: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mstats_result[\u001b[33m'\u001b[39m\u001b[33msuccess\u001b[39m\u001b[33m'\u001b[39m]\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m)\n\u001b[32m---> \u001b[39m\u001b[32m10\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33m  Elapsed: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mstats_result[\u001b[33m'\u001b[39m\u001b[33melapsed_s\u001b[39m\u001b[33m'\u001b[39m]\u001b[38;5;132;01m:\u001b[39;00m\u001b[33m.2f\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33ms\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m     11\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33m  Timesteps: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mstats_result[\u001b[33m'\u001b[39m\u001b[33mn_timesteps\u001b[39m\u001b[33m'\u001b[39m]\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m)\n\u001b[32m     12\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33m  Statistics: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mstats_result[\u001b[33m'\u001b[39m\u001b[33mstatistics\u001b[39m\u001b[33m'\u001b[39m]\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m)\n",
-      "\u001b[31mTypeError\u001b[39m: unsupported format string passed to NoneType.__format__"
+      "  Success: False\n",
+      "  Elapsed: 0.00s\n",
+      "  Timesteps: 0\n",
+      "  Statistics: {}\n"
      ]
     }
    ],
@@ -1009,7 +695,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "id": "c18aea10",
    "metadata": {},
    "outputs": [
@@ -1022,7 +708,7 @@
       "Dataset: C2723754864-GES_DISC (xarray)\n",
       "Statistics result:\n",
       "  Success: True\n",
-      "  Elapsed: 3.36s\n",
+      "  Elapsed: 1.84s\n",
       "  Timesteps: 2\n",
       "  Statistics: {'2022-03-01T00:00:01+00:00': {'2022-03-01T00:00:00.000000000': {'min': 0.0, 'max': 42.82999801635742, 'mean': 0.3393020033836365, 'count': 20898.5, 'sum': 7090.90283203125, 'std': 1.9955874881629714, 'median': 0.0, 'majority': 0.0, 'minority': 0.044999994337558746, 'unique': 1347.0, 'histogram': [[20614, 232, 65, 46, 20, 19, 14, 16, 4, 3], [0.0, 4.2829999923706055, 8.565999984741211, 12.848999977111816, 17.131999969482422, 21.415000915527344, 25.697999954223633, 29.980998992919922, 34.263999938964844, 38.547000885009766, 42.82999801635742]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 21033.0, 'percentile_2': 0.0, 'percentile_98': 4.244999885559082}}, '2022-03-02T00:00:01+00:00': {'2022-03-02T00:00:00.000000000': {'min': 0.0, 'max': 18.755001068115234, 'mean': 0.04489568620920181, 'count': 20898.5, 'sum': 938.2525024414062, 'std': 0.42384278584099, 'median': 0.0, 'majority': 0.0, 'minority': 0.08000000566244125, 'unique': 486.0, 'histogram': [[20900, 77, 27, 13, 10, 2, 1, 1, 1, 1], [0.0, 1.8755000829696655, 3.751000165939331, 5.626500129699707, 7.502000331878662, 9.377500534057617, 11.253000259399414, 13.128500938415527, 15.004000663757324, 16.879501342773438, 18.755001068115234]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 21033.0, 'percentile_2': 0.0, 'percentile_98': 0.42500001192092896}}}\n"
      ]
@@ -1055,7 +741,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "id": "8a81954f",
    "metadata": {},
    "outputs": [
@@ -1068,7 +754,7 @@
       "Dataset: C2723754864-GES_DISC (xarray)\n",
       "Statistics result:\n",
       "  Success: True\n",
-      "  Elapsed: 7.28s\n",
+      "  Elapsed: 2.28s\n",
       "  Timesteps: 8\n",
       "  Statistics: {'2022-03-01T00:00:01+00:00': {'2022-03-01T00:00:00.000000000': {'min': 0.0, 'max': 42.82999801635742, 'mean': 0.3393020033836365, 'count': 20898.5, 'sum': 7090.90283203125, 'std': 1.9955874881629714, 'median': 0.0, 'majority': 0.0, 'minority': 0.044999994337558746, 'unique': 1347.0, 'histogram': [[20614, 232, 65, 46, 20, 19, 14, 16, 4, 3], [0.0, 4.2829999923706055, 8.565999984741211, 12.848999977111816, 17.131999969482422, 21.415000915527344, 25.697999954223633, 29.980998992919922, 34.263999938964844, 38.547000885009766, 42.82999801635742]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 21033.0, 'percentile_2': 0.0, 'percentile_98': 4.244999885559082}}, '2022-03-08T00:00:01+00:00': {'2022-03-08T00:00:00.000000000': {'min': 0.0, 'max': 42.36000061035156, 'mean': 0.9508299827575684, 'count': 20898.5, 'sum': 19870.919921875, 'std': 3.2417449281425865, 'median': 0.0, 'majority': 0.0, 'minority': 0.03999999538064003, 'unique': 2620.0, 'histogram': [[19621, 719, 300, 172, 89, 58, 36, 24, 10, 4], [0.0, 4.236000061035156, 8.472000122070312, 12.708000183105469, 16.944000244140625, 21.18000030517578, 25.416000366210938, 29.652000427246094, 33.88800048828125, 38.124000549316406, 42.36000061035156]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 21033.0, 'percentile_2': 0.0, 'percentile_98': 12.290000915527344}}, '2022-03-15T00:00:01+00:00': {'2022-03-15T00:00:00.000000000': {'min': 0.0, 'max': 174.25502014160156, 'mean': 10.431671142578125, 'count': 20898.5, 'sum': 218006.28125, 'std': 22.99134730243641, 'median': 0.0, 'majority': 0.0, 'minority': 0.05000000447034836, 'unique': 6826.0, 'histogram': [[17249, 1821, 640, 378, 346, 306, 171, 94, 24, 4], [0.0, 17.42550277709961, 34.85100555419922, 52.27650833129883, 69.70201110839844, 87.12751770019531, 104.55301666259766, 121.978515625, 139.40402221679688, 156.82952880859375, 174.25502014160156]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 21033.0, 'percentile_2': 0.0, 'percentile_98': 96.41999816894531}}, '2022-03-22T00:00:01+00:00': {'2022-03-22T00:00:00.000000000': {'min': 0.0, 'max': 113.67498779296875, 'mean': 3.880465507507324, 'count': 20898.5, 'sum': 81095.90625, 'std': 12.315773775585773, 'median': 0.0, 'majority': 0.0, 'minority': 0.07999999076128006, 'unique': 3630.0, 'histogram': [[19041, 713, 387, 299, 231, 178, 119, 44, 16, 5], [0.0, 11.367498397827148, 22.734996795654297, 34.10249328613281, 45.469993591308594, 56.837493896484375, 68.20498657226562, 79.5724868774414, 90.93998718261719, 102.30748748779297, 113.67498779296875]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 21033.0, 'percentile_2': 0.0, 'percentile_98': 53.35499954223633}}, '2022-03-29T00:00:01+00:00': {'2022-03-29T00:00:00.000000000': {'min': 0.0, 'max': 17.045001983642578, 'mean': 0.1486642062664032, 'count': 20898.5, 'sum': 3106.85888671875, 'std': 0.7623889029192605, 'median': 0.0, 'majority': 0.0, 'minority': 0.04500000178813934, 'unique': 999.0, 'histogram': [[20389, 377, 145, 70, 29, 10, 5, 2, 3, 3], [0.0, 1.7045001983642578, 3.4090003967285156, 5.113500595092773, 6.818000793457031, 8.522500991821289, 10.227001190185547, 11.931501388549805, 13.636001586914062, 15.34050178527832, 17.045001983642578]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 21033.0, 'percentile_2': 0.0, 'percentile_98': 2.5299999713897705}}, '2022-04-05T00:00:01+00:00': {'2022-04-05T00:00:00.000000000': {'min': 0.0, 'max': 40.5050048828125, 'mean': 0.5256912112236023, 'count': 20898.5, 'sum': 10986.1572265625, 'std': 2.586293636818602, 'median': 0.0, 'majority': 0.0, 'minority': 0.03999999538064003, 'unique': 1562.0, 'histogram': [[20283, 294, 182, 121, 61, 37, 26, 11, 11, 7], [0.0, 4.050500392913818, 8.101000785827637, 12.151500701904297, 16.202001571655273, 20.25250244140625, 24.303001403808594, 28.35350227355957, 32.40400314331055, 36.45450210571289, 40.5050048828125]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 21033.0, 'percentile_2': 0.0, 'percentile_98': 8.694999694824219}}, '2022-04-12T00:00:01+00:00': {'2022-04-12T00:00:00.000000000': {'min': 0.0, 'max': 64.42500305175781, 'mean': 1.5356361865997314, 'count': 20898.5, 'sum': 32092.4921875, 'std': 5.440761947003824, 'median': 0.0, 'majority': 0.0, 'minority': 0.09499998390674591, 'unique': 2873.0, 'histogram': [[19750, 534, 300, 192, 69, 64, 41, 56, 21, 6], [0.0, 6.442500114440918, 12.885000228881836, 19.327499389648438, 25.770000457763672, 32.212501525878906, 38.654998779296875, 45.09749984741211, 51.540000915527344, 57.98250198364258, 64.42500305175781]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 21033.0, 'percentile_2': 0.0, 'percentile_98': 20.049999237060547}}, '2022-04-19T00:00:01+00:00': {'2022-04-19T00:00:00.000000000': {'min': 0.0, 'max': 11.125, 'mean': 0.10002636164426804, 'count': 20898.5, 'sum': 2090.40087890625, 'std': 0.5136673785690946, 'median': 0.0, 'majority': 0.0, 'minority': 0.06000000238418579, 'unique': 807.0, 'histogram': [[20543, 252, 89, 74, 37, 15, 8, 10, 3, 2], [0.0, 1.1124999523162842, 2.2249999046325684, 3.3374998569488525, 4.449999809265137, 5.5625, 6.674999713897705, 7.78749942779541, 8.899999618530273, 10.012499809265137, 11.125]], 'valid_percent': 100.0, 'masked_pixels': 0.0, 'valid_pixels': 21033.0, 'percentile_2': 0.0, 'percentile_98': 1.274999976158142}}}\n"
      ]
@@ -1109,7 +795,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 13,
    "id": "5bf66e17-ad4c-4483-b5e9-359906fe1805",
    "metadata": {},
    "outputs": [
@@ -1197,9 +883,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "datacube-titiler",
+   "display_name": "titiler-updates",
    "language": "python",
-   "name": "datacube-titiler"
+   "name": "titiler-updates"
   },
   "language_info": {
    "codemirror_mode": {
diff --git a/mkdocs.yml b/mkdocs.yml
index 2910374..dc59565 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -31,7 +31,8 @@ nav:
     - Overview: "visualization/overview.md"
     - Titiler:
       - Ecosystem overview: "visualization/titiler/overview.md"
-      - Performance benchmarking:
+      - Performance benchmarking and Compatibility Testing:
+        - Titiler-CMR Compatibility Testing: "visualization/titiler/titiler-cmr/titiler-cmr-compatibility.ipynb"
         - Titiler-CMR tile generation: "visualization/titiler/titiler-cmr/titiler-cmr-benchmark.ipynb"
         - Titiler-CMR timeseries statistics: "visualization/titiler/titiler-cmr/titiler-cmr-statistics-benchmark.ipynb"
 
diff --git a/packages/datacube-benchmark/pyproject.toml b/packages/datacube-benchmark/pyproject.toml
index 69b6e8b..a18acbf 100644
--- a/packages/datacube-benchmark/pyproject.toml
+++ b/packages/datacube-benchmark/pyproject.toml
@@ -11,6 +11,8 @@ dependencies = [
     "arro3-core>=0.5.1",
     "dask>=2025.5.1",
     "geojson-pydantic>=2.0.0",
+    "earthaccess~=0.11.0",
+    "h5netcdf~=1.1.0",
     "hdf5plugin>=5.1.0",
     "httpx>=0.28.1",
     "morecantile>=6.2.0",
diff --git a/packages/datacube-benchmark/src/datacube_benchmark/titiler/cmr/benchmark.py b/packages/datacube-benchmark/src/datacube_benchmark/titiler/cmr/benchmark.py
index a48dea4..243d4b1 100644
--- a/packages/datacube-benchmark/src/datacube_benchmark/titiler/cmr/benchmark.py
+++ b/packages/datacube-benchmark/src/datacube_benchmark/titiler/cmr/benchmark.py
@@ -433,6 +433,8 @@ async def _fetch_one_tile(z, x, y):
                                 "x": x,
                                 "y": y,
                                 "is_error": True,
+                                "ok": False,
+                                "status_code": None,
                                 "error_text": f"{type(ex).__name__}: {ex}",
                             }
                         ]
@@ -568,7 +570,6 @@ async def check_compatibility(
             issue_detected = True
             stats_result = {"success": False, "error": str(ex)}
 
-        print(stats_result)
         if stats_result.get("success"):
             print(f"Statistics returned {len(stats_result['statistics'])} timesteps")
             compatibility_status = "compatible"
diff --git a/uv.lock b/uv.lock
index 82822a3..1af9b42 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,5 +1,5 @@
 version = 1
-revision = 2
+revision = 3
 requires-python = ">=3.13"
 
 [manifest]
@@ -8,6 +8,24 @@ members = [
     "datacube-guide",
 ]
 
+[[package]]
+name = "aiobotocore"
+version = "2.23.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "aiohttp" },
+    { name = "aioitertools" },
+    { name = "botocore" },
+    { name = "jmespath" },
+    { name = "multidict" },
+    { name = "python-dateutil" },
+    { name = "wrapt" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/f6/1d/babe191fa10a7ecda6c6832c08231536c60cc33b4cddfb3b72133505673e/aiobotocore-2.23.1.tar.gz", hash = "sha256:a59f2a78629b97d52f10936b79c73de64e481a8c44a62c1871f088df6c1afc4f", size = 115869, upload-time = "2025-07-17T21:51:57.006Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/92/d9/25a697a959a7149c93efa4d849421aa5f22bcb82350ac89b4284b0b88aa8/aiobotocore-2.23.1-py3-none-any.whl", hash = "sha256:d81c54d2eae2406ea9a473fea518fed580cf37bc4fc51ce43ba81546e5305114", size = 84219, upload-time = "2025-07-17T21:51:55.145Z" },
+]
+
 [[package]]
 name = "aiohappyeyeballs"
 version = "2.6.1"
@@ -63,6 +81,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/1a/99/84ba7273339d0f3dfa57901b846489d2e5c2cd731470167757f1935fffbd/aiohttp_retry-2.9.1-py3-none-any.whl", hash = "sha256:66d2759d1921838256a05a3f80ad7e724936f083e35be5abb5e16eed6be6dc54", size = 9981, upload-time = "2024-11-06T10:44:52.917Z" },
 ]
 
+[[package]]
+name = "aioitertools"
+version = "0.12.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/06/de/38491a84ab323b47c7f86e94d2830e748780525f7a10c8600b67ead7e9ea/aioitertools-0.12.0.tar.gz", hash = "sha256:c2a9055b4fbb7705f561b9d86053e8af5d10cc845d22c32008c43490b2d8dd6b", size = 19369, upload-time = "2024-09-02T03:33:40.349Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/85/13/58b70a580de00893223d61de8fea167877a3aed97d4a5e1405c9159ef925/aioitertools-0.12.0-py3-none-any.whl", hash = "sha256:fc1f5fac3d737354de8831cbba3eb04f79dd649d8f3afb4c5b114925e662a796", size = 24345, upload-time = "2024-09-02T03:34:59.454Z" },
+]
+
 [[package]]
 name = "aiosignal"
 version = "1.3.2"
@@ -321,6 +348,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/ec/b7/37d9f1a633e72250408cb7d53d8915561ac6108b5c3a1973eb8f53ce2990/botocore-1.38.41-py3-none-any.whl", hash = "sha256:06069a06f1352accb1f6c9505d6e323753627112be80a9d2e057c6d9c9779ffd", size = 13690225, upload-time = "2025-06-20T19:26:26.014Z" },
 ]
 
+[[package]]
+name = "bounded-pool-executor"
+version = "0.0.3"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/23/f1/e34501c1228415e9fbcac8cb9c81098900e78331b30eeee1816176324bab/bounded_pool_executor-0.0.3.tar.gz", hash = "sha256:e092221bc38ade555e1064831f9ed800580fa34a4b6d8e9dd3cd961549627f6e", size = 2238, upload-time = "2019-06-04T19:29:06.672Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/bc/23/72ecfe284a1da711257ff310b29c6667d0187a608322d58bf1c7a927c7b2/bounded_pool_executor-0.0.3-py3-none-any.whl", hash = "sha256:6f164d64919db1e6a5c187cce281f62bc559a5fed4ce064942e650c227aef190", size = 3371, upload-time = "2019-06-04T19:29:05.152Z" },
+]
+
 [[package]]
 name = "cairocffi"
 version = "1.7.1"
@@ -614,7 +650,9 @@ source = { editable = "packages/datacube-benchmark" }
 dependencies = [
     { name = "arro3-core" },
     { name = "dask" },
+    { name = "earthaccess" },
     { name = "geojson-pydantic" },
+    { name = "h5netcdf" },
     { name = "hdf5plugin" },
     { name = "httpx" },
     { name = "morecantile" },
@@ -633,7 +671,9 @@ dependencies = [
 requires-dist = [
     { name = "arro3-core", specifier = ">=0.5.1" },
     { name = "dask", specifier = ">=2025.5.1" },
+    { name = "earthaccess", specifier = "~=0.11.0" },
     { name = "geojson-pydantic", specifier = ">=2.0.0" },
+    { name = "h5netcdf", specifier = "~=1.1.0" },
     { name = "hdf5plugin", specifier = ">=5.1.0" },
     { name = "httpx", specifier = ">=0.28.1" },
     { name = "morecantile", specifier = ">=6.2.0" },
@@ -772,6 +812,27 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/0c/d5/c5db1ea3394c6e1732fb3286b3bd878b59507a8f77d32a2cebda7d7b7cd4/donfig-0.8.1.post1-py3-none-any.whl", hash = "sha256:2a3175ce74a06109ff9307d90a230f81215cbac9a751f4d1c6194644b8204f9d", size = 21592, upload-time = "2024-05-23T14:13:55.283Z" },
 ]
 
+[[package]]
+name = "earthaccess"
+version = "0.11.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "fsspec" },
+    { name = "importlib-resources" },
+    { name = "multimethod" },
+    { name = "numpy" },
+    { name = "pqdm" },
+    { name = "python-cmr" },
+    { name = "requests" },
+    { name = "s3fs" },
+    { name = "tinynetrc" },
+    { name = "typing-extensions" },
+]
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