diff --git a/docs/examples/basic/xopt_parallel.ipynb b/docs/examples/basic/xopt_parallel.ipynb
index a487d4491..afdcfa0c7 100644
--- a/docs/examples/basic/xopt_parallel.ipynb
+++ b/docs/examples/basic/xopt_parallel.ipynb
@@ -15,7 +15,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:51:12.734939Z",
@@ -72,7 +72,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:51:13.120880Z",
@@ -84,7 +84,91 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\n",
+       "            Xopt\n",
+       "________________________________\n",
+       "Version: 3.1.2\n",
+       "Data size: 0\n",
+       "Config as YAML:\n",
+       "dump_file: null\n",
+       "evaluator:\n",
+       "  function: xopt.resources.test_functions.tnk.evaluate_TNK\n",
+       "  function_kwargs:\n",
+       "    raise_probability: 0\n",
+       "    random_sleep: 0.1\n",
+       "    sleep: 0\n",
+       "  max_workers: 1\n",
+       "  vectorized: false\n",
+       "generator:\n",
+       "  crossover_probability: 0.9\n",
+       "  mutation_probability: 1.0\n",
+       "  name: cnsga\n",
+       "  output_path: temp\n",
+       "  population: null\n",
+       "  population_file: null\n",
+       "  population_size: 64\n",
+       "  returns_id: false\n",
+       "  supports_constraints: true\n",
+       "  supports_multi_objective: true\n",
+       "  supports_single_objective: true\n",
+       "  vocs:\n",
+       "    constants:\n",
+       "      a:\n",
+       "        dtype: null\n",
+       "        type: Constant\n",
+       "        value: dummy_constant\n",
+       "    constraints:\n",
+       "      c1:\n",
+       "        dtype: null\n",
+       "        type: GreaterThanConstraint\n",
+       "        value: 0.0\n",
+       "      c2:\n",
+       "        dtype: null\n",
+       "        type: LessThanConstraint\n",
+       "        value: 0.5\n",
+       "    objectives:\n",
+       "      y1:\n",
+       "        dtype: null\n",
+       "        type: MinimizeObjective\n",
+       "      y2:\n",
+       "        dtype: null\n",
+       "        type: MinimizeObjective\n",
+       "    observables: {}\n",
+       "    variables:\n",
+       "      x1:\n",
+       "        default_value: null\n",
+       "        domain:\n",
+       "        - 0.0\n",
+       "        - 3.14159\n",
+       "        dtype: null\n",
+       "        type: ContinuousVariable\n",
+       "      x2:\n",
+       "        default_value: null\n",
+       "        domain:\n",
+       "        - 0.0\n",
+       "        - 3.14159\n",
+       "        dtype: null\n",
+       "        type: ContinuousVariable\n",
+       "is_done: false\n",
+       "serialize_inline: false\n",
+       "serialize_torch: false\n",
+       "stopping_condition:\n",
+       "  count_valid_only: false\n",
+       "  max_evaluations: 1000\n",
+       "  name: MaxEvaluationsCondition\n",
+       "  use_dataframe_index: false\n",
+       "strict: true\n"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Make a proper input file.\n",
     "MAX_EVALUATIONS = 32 if SMOKE_TEST else 1000\n",
@@ -124,7 +208,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:51:13.160584Z",
@@ -136,7 +220,15 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "108 ms ± 17.2 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
+     ]
+    }
+   ],
    "source": [
     "%%timeit\n",
     "# Check that the average time is close to random_sleep\n",
@@ -145,7 +237,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:51:21.140796Z",
@@ -157,7 +249,16 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 6.26 s, sys: 137 ms, total: 6.4 s\n",
+      "Wall time: 1min 54s\n"
+     ]
+    }
+   ],
    "source": [
     "%%time\n",
     "X.run()"
@@ -176,7 +277,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:53:14.805616Z",
@@ -188,7 +289,26 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 3.22 s, sys: 240 ms, total: 3.46 s\n",
+      "Wall time: 13.4 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "1000"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "%%time\n",
     "X = Xopt(YAML)\n",
@@ -215,7 +335,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:53:28.076716Z",
@@ -227,7 +347,26 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 3.13 s, sys: 77.5 ms, total: 3.21 s\n",
+      "Wall time: 11.1 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "1000"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "%%time\n",
     "X = Xopt(YAML)\n",
@@ -256,7 +395,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:53:38.989702Z",
@@ -268,7 +407,83 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "data: null\n",
+      "dump_file: null\n",
+      "evaluator:\n",
+      "  function: xopt.resources.test_functions.tnk.evaluate_TNK\n",
+      "  function_kwargs:\n",
+      "    raise_probability: 0\n",
+      "    random_sleep: 0.1\n",
+      "    sleep: 0\n",
+      "  max_workers: 1\n",
+      "  vectorized: false\n",
+      "generator:\n",
+      "  crossover_probability: 0.9\n",
+      "  mutation_probability: 1.0\n",
+      "  name: cnsga\n",
+      "  output_path: temp\n",
+      "  population: null\n",
+      "  population_file: null\n",
+      "  population_size: 64\n",
+      "  returns_id: false\n",
+      "  supports_constraints: true\n",
+      "  supports_multi_objective: true\n",
+      "  supports_single_objective: true\n",
+      "  vocs:\n",
+      "    constants:\n",
+      "      a:\n",
+      "        dtype: null\n",
+      "        type: Constant\n",
+      "        value: dummy_constant\n",
+      "    constraints:\n",
+      "      c1:\n",
+      "        dtype: null\n",
+      "        type: GreaterThanConstraint\n",
+      "        value: 0.0\n",
+      "      c2:\n",
+      "        dtype: null\n",
+      "        type: LessThanConstraint\n",
+      "        value: 0.5\n",
+      "    objectives:\n",
+      "      y1:\n",
+      "        dtype: null\n",
+      "        type: MinimizeObjective\n",
+      "      y2:\n",
+      "        dtype: null\n",
+      "        type: MinimizeObjective\n",
+      "    observables: {}\n",
+      "    variables:\n",
+      "      x1:\n",
+      "        default_value: null\n",
+      "        domain:\n",
+      "        - 0.0\n",
+      "        - 3.14159\n",
+      "        dtype: null\n",
+      "        type: ContinuousVariable\n",
+      "      x2:\n",
+      "        default_value: null\n",
+      "        domain:\n",
+      "        - 0.0\n",
+      "        - 3.14159\n",
+      "        dtype: null\n",
+      "        type: ContinuousVariable\n",
+      "is_done: false\n",
+      "serialize_inline: false\n",
+      "serialize_torch: false\n",
+      "stopping_condition:\n",
+      "  count_valid_only: false\n",
+      "  max_evaluations: 1000\n",
+      "  name: MaxEvaluationsCondition\n",
+      "  use_dataframe_index: false\n",
+      "strict: true\n"
+     ]
+    }
+   ],
    "source": [
     "X = Xopt(YAML)\n",
     "X.dump(\"test.yaml\")  # Write this input to file\n",
@@ -277,7 +492,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:53:39.162178Z",
@@ -286,7 +501,100 @@
      "shell.execute_reply": "2024-09-13T15:53:57.496156Z"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Namespace(input_file='test.yaml', logfile='xopt.log', verbose=2, asynchronous=True)\n",
+      "Parallel execution with 8 workers\n",
+      "Enabling async mode\n",
+      "Initialized generator cnsga\n",
+      "Created toolbox with 2 variables, 2 constraints, and 2 objectives.\n",
+      "    Using selection algorithm: nsga2\n",
+      "\n",
+      "            Xopt\n",
+      "________________________________\n",
+      "Version: 3.1.2\n",
+      "Data size: 0\n",
+      "Config as YAML:\n",
+      "dump_file: null\n",
+      "evaluator:\n",
+      "  function: xopt.resources.test_functions.tnk.evaluate_TNK\n",
+      "  function_kwargs:\n",
+      "    raise_probability: 0\n",
+      "    random_sleep: 0.1\n",
+      "    sleep: 0\n",
+      "  max_workers: 1\n",
+      "  vectorized: false\n",
+      "generator:\n",
+      "  crossover_probability: 0.9\n",
+      "  mutation_probability: 1.0\n",
+      "  name: cnsga\n",
+      "  output_path: temp\n",
+      "  population: null\n",
+      "  population_file: null\n",
+      "  population_size: 64\n",
+      "  returns_id: false\n",
+      "  supports_constraints: true\n",
+      "  supports_multi_objective: true\n",
+      "  supports_single_objective: true\n",
+      "  vocs:\n",
+      "    constants:\n",
+      "      a:\n",
+      "        dtype: null\n",
+      "        type: Constant\n",
+      "        value: dummy_constant\n",
+      "    constraints:\n",
+      "      c1:\n",
+      "        dtype: null\n",
+      "        type: GreaterThanConstraint\n",
+      "        value: 0.0\n",
+      "      c2:\n",
+      "        dtype: null\n",
+      "        type: LessThanConstraint\n",
+      "        value: 0.5\n",
+      "    objectives:\n",
+      "      y1:\n",
+      "        dtype: null\n",
+      "        type: MinimizeObjective\n",
+      "      y2:\n",
+      "        dtype: null\n",
+      "        type: MinimizeObjective\n",
+      "    observables: {}\n",
+      "    variables:\n",
+      "      x1:\n",
+      "        default_value: null\n",
+      "        domain:\n",
+      "        - 0.0\n",
+      "        - 3.14159\n",
+      "        dtype: null\n",
+      "        type: ContinuousVariable\n",
+      "      x2:\n",
+      "        default_value: null\n",
+      "        domain:\n",
+      "        - 0.0\n",
+      "        - 3.14159\n",
+      "        dtype: null\n",
+      "        type: ContinuousVariable\n",
+      "is_done: false\n",
+      "serialize_inline: false\n",
+      "serialize_torch: false\n",
+      "stopping_condition:\n",
+      "  count_valid_only: false\n",
+      "  max_evaluations: 1000\n",
+      "  name: MaxEvaluationsCondition\n",
+      "  use_dataframe_index: false\n",
+      "strict: true\n",
+      "\n",
+      "\n",
+      "Running Xopt\n",
+      "Xopt is done. Stopping condition met.\n",
+      "CPU times: user 138 ms, sys: 49.6 ms, total: 188 ms\n",
+      "Wall time: 20.3 s\n"
+     ]
+    }
+   ],
    "source": [
     "%%time\n",
     "!mpirun -n 8 python -m mpi4py.futures -m xopt.mpi.run -vv --logfile xopt.log test.yaml"
@@ -294,7 +602,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:53:57.499178Z",
@@ -306,7 +614,21 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2026-07-06T15:29:00-0700 - xopt - INFO - Parallel execution with 8 workers\n",
+      "2026-07-06T15:29:00-0700 - xopt - INFO - Enabling async mode\n",
+      "2026-07-06T15:29:01-0700 - xopt.generator - INFO - Initialized generator cnsga\n",
+      "2026-07-06T15:29:01-0700 - xopt.generators.ga.cnsga - INFO - Created toolbox with 2 variables, 2 constraints, and 2 objectives.\n",
+      "2026-07-06T15:29:01-0700 - xopt.generators.ga.cnsga - INFO -     Using selection algorithm: nsga2\n",
+      "2026-07-06T15:29:01-0700 - xopt.base - INFO - Running Xopt\n",
+      "2026-07-06T15:29:17-0700 - xopt.base - INFO - Xopt is done. Stopping condition met.\n"
+     ]
+    }
+   ],
    "source": [
     "!tail xopt.log"
    ]
@@ -325,7 +647,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:53:57.627616Z",
@@ -337,7 +659,365 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
+       "    <div style=\"margin-left: 48px;\">\n",
+       "        <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
+       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-20e621f4-798a-11f1-a971-060412c509ea</p>\n",
+       "        <table style=\"width: 100%; text-align: left;\">\n",
+       "\n",
+       "        <tr>\n",
+       "        \n",
+       "            <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
+       "            <td style=\"text-align: left;\"><strong>Cluster type:</strong> distributed.LocalCluster</td>\n",
+       "        \n",
+       "        </tr>\n",
+       "\n",
+       "        \n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\"></td>\n",
+       "            </tr>\n",
+       "        \n",
+       "\n",
+       "        </table>\n",
+       "\n",
+       "        \n",
+       "\n",
+       "        \n",
+       "            <details>\n",
+       "            <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
+       "            <div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n",
+       "    <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\">\n",
+       "    </div>\n",
+       "    <div style=\"margin-left: 48px;\">\n",
+       "        <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">LocalCluster</h3>\n",
+       "        <p style=\"color: #9D9D9D; margin-bottom: 0px;\">099ec1fe</p>\n",
+       "        <table style=\"width: 100%; text-align: left;\">\n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Workers:</strong> 5\n",
+       "                </td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Total threads:</strong> 10\n",
+       "                </td>\n",
+       "                <td style=\"text-align: left;\">\n",
+       "                    <strong>Total memory:</strong> 64.00 GiB\n",
+       "                </td>\n",
+       "            </tr>\n",
+       "            \n",
+       "            <tr>\n",
+       "    <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n",
+       "    <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n",
+       "</tr>\n",
+       "\n",
+       "            \n",
+       "        </table>\n",
+       "\n",
+       "        <details>\n",
+       "            <summary style=\"margin-bottom: 20px;\">\n",
+       "                <h3 style=\"display: inline;\">Scheduler Info</h3>\n",
+       "            </summary>\n",
+       "\n",
+       "            <div style=\"\">\n",
+       "    <div>\n",
+       "        <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
+       "        <div style=\"margin-left: 48px;\">\n",
+       "            <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
+       "            <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-41b090e0-950a-458a-b4fd-50ee9be82904</p>\n",
+       "            <table style=\"width: 100%; text-align: left;\">\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Comm:</strong> tcp://127.0.0.1:58797\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Workers:</strong> 0 \n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Dashboard:</strong> <a href=\"http://127.0.0.1:8787/status\" target=\"_blank\">http://127.0.0.1:8787/status</a>\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Total threads:</strong> 0\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "                <tr>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Started:</strong> Just now\n",
+       "                    </td>\n",
+       "                    <td style=\"text-align: left;\">\n",
+       "                        <strong>Total memory:</strong> 0 B\n",
+       "                    </td>\n",
+       "                </tr>\n",
+       "            </table>\n",
+       "        </div>\n",
+       "    </div>\n",
+       "\n",
+       "    <details style=\"margin-left: 48px;\">\n",
+       "        <summary style=\"margin-bottom: 20px;\">\n",
+       "            <h3 style=\"display: inline;\">Workers</h3>\n",
+       "        </summary>\n",
+       "\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:58810\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 2\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:58812/status\" target=\"_blank\">http://127.0.0.1:58812/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 12.80 GiB\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:58800\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-scratch-space/worker-b2o0h1x7\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 1</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:58811\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 2\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:58814/status\" target=\"_blank\">http://127.0.0.1:58814/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 12.80 GiB\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:58802\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-scratch-space/worker-1tqay888\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 2</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:58816\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 2\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:58817/status\" target=\"_blank\">http://127.0.0.1:58817/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 12.80 GiB\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:58804\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-scratch-space/worker-97_eog5t\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 3</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:58818\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 2\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:58821/status\" target=\"_blank\">http://127.0.0.1:58821/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 12.80 GiB\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:58806\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-scratch-space/worker-6_w4lxy9\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "        <div style=\"margin-bottom: 20px;\">\n",
+       "            <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
+       "            <div style=\"margin-left: 48px;\">\n",
+       "            <details>\n",
+       "                <summary>\n",
+       "                    <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 4</h4>\n",
+       "                </summary>\n",
+       "                <table style=\"width: 100%; text-align: left;\">\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Comm: </strong> tcp://127.0.0.1:58820\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Total threads: </strong> 2\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Dashboard: </strong> <a href=\"http://127.0.0.1:58823/status\" target=\"_blank\">http://127.0.0.1:58823/status</a>\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Memory: </strong> 12.80 GiB\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td style=\"text-align: left;\">\n",
+       "                            <strong>Nanny: </strong> tcp://127.0.0.1:58808\n",
+       "                        </td>\n",
+       "                        <td style=\"text-align: left;\"></td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <td colspan=\"2\" style=\"text-align: left;\">\n",
+       "                            <strong>Local directory: </strong> /var/folders/2f/l5_mybzs30j4qqvyj98w1_nw0000gn/T/dask-scratch-space/worker-n5_sogtu\n",
+       "                        </td>\n",
+       "                    </tr>\n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                    \n",
+       "\n",
+       "                </table>\n",
+       "            </details>\n",
+       "            </div>\n",
+       "        </div>\n",
+       "        \n",
+       "\n",
+       "    </details>\n",
+       "</div>\n",
+       "\n",
+       "        </details>\n",
+       "    </div>\n",
+       "</div>\n",
+       "            </details>\n",
+       "        \n",
+       "\n",
+       "    </div>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "<Client: 'tcp://127.0.0.1:58797' processes=5 threads=10, memory=64.00 GiB>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "client = Client()\n",
     "executor = client.get_executor()\n",
@@ -346,7 +1026,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:53:58.572623Z",
@@ -358,7 +1038,26 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 5.04 s, sys: 545 ms, total: 5.58 s\n",
+      "Wall time: 12.9 s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "1000"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "%%time\n",
     "X = Xopt(YAML)\n",
@@ -383,7 +1082,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:54:10.655270Z",
@@ -395,14 +1094,219 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "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>x1</th>\n",
+       "      <th>x2</th>\n",
+       "      <th>a</th>\n",
+       "      <th>y1</th>\n",
+       "      <th>y2</th>\n",
+       "      <th>c1</th>\n",
+       "      <th>c2</th>\n",
+       "      <th>xopt_runtime</th>\n",
+       "      <th>xopt_error</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1.656101</td>\n",
+       "      <td>2.293345</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>1.656101</td>\n",
+       "      <td>2.293345</td>\n",
+       "      <td>7.085638</td>\n",
+       "      <td>4.552658</td>\n",
+       "      <td>0.013142</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2.566841</td>\n",
+       "      <td>1.020208</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>2.566841</td>\n",
+       "      <td>1.020208</td>\n",
+       "      <td>6.532137</td>\n",
+       "      <td>4.542450</td>\n",
+       "      <td>0.009709</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1.406810</td>\n",
+       "      <td>2.955525</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>1.406810</td>\n",
+       "      <td>2.955525</td>\n",
+       "      <td>9.646381</td>\n",
+       "      <td>6.851906</td>\n",
+       "      <td>0.030881</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2.674928</td>\n",
+       "      <td>1.880077</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>2.674928</td>\n",
+       "      <td>1.880077</td>\n",
+       "      <td>9.782890</td>\n",
+       "      <td>6.634924</td>\n",
+       "      <td>0.035817</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.393400</td>\n",
+       "      <td>2.287370</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>0.393400</td>\n",
+       "      <td>2.287370</td>\n",
+       "      <td>4.478278</td>\n",
+       "      <td>3.206055</td>\n",
+       "      <td>0.011276</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>995</th>\n",
+       "      <td>0.954590</td>\n",
+       "      <td>0.313168</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>0.954590</td>\n",
+       "      <td>0.313168</td>\n",
+       "      <td>-0.025878</td>\n",
+       "      <td>0.241558</td>\n",
+       "      <td>0.065372</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>996</th>\n",
+       "      <td>0.959897</td>\n",
+       "      <td>0.648406</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>0.959897</td>\n",
+       "      <td>0.648406</td>\n",
+       "      <td>0.441508</td>\n",
+       "      <td>0.233530</td>\n",
+       "      <td>0.074797</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>997</th>\n",
+       "      <td>0.541181</td>\n",
+       "      <td>0.957632</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>0.541181</td>\n",
+       "      <td>0.957632</td>\n",
+       "      <td>0.246667</td>\n",
+       "      <td>0.211123</td>\n",
+       "      <td>0.127204</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>998</th>\n",
+       "      <td>0.867102</td>\n",
+       "      <td>0.845820</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>0.867102</td>\n",
+       "      <td>0.845820</td>\n",
+       "      <td>0.369247</td>\n",
+       "      <td>0.254356</td>\n",
+       "      <td>0.074385</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>999</th>\n",
+       "      <td>0.094810</td>\n",
+       "      <td>1.051405</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>0.094810</td>\n",
+       "      <td>1.051405</td>\n",
+       "      <td>0.101290</td>\n",
+       "      <td>0.468226</td>\n",
+       "      <td>0.000649</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1000 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           x1        x2               a        y1        y2        c1  \\\n",
+       "0    1.656101  2.293345  dummy_constant  1.656101  2.293345  7.085638   \n",
+       "1    2.566841  1.020208  dummy_constant  2.566841  1.020208  6.532137   \n",
+       "2    1.406810  2.955525  dummy_constant  1.406810  2.955525  9.646381   \n",
+       "3    2.674928  1.880077  dummy_constant  2.674928  1.880077  9.782890   \n",
+       "4    0.393400  2.287370  dummy_constant  0.393400  2.287370  4.478278   \n",
+       "..        ...       ...             ...       ...       ...       ...   \n",
+       "995  0.954590  0.313168  dummy_constant  0.954590  0.313168 -0.025878   \n",
+       "996  0.959897  0.648406  dummy_constant  0.959897  0.648406  0.441508   \n",
+       "997  0.541181  0.957632  dummy_constant  0.541181  0.957632  0.246667   \n",
+       "998  0.867102  0.845820  dummy_constant  0.867102  0.845820  0.369247   \n",
+       "999  0.094810  1.051405  dummy_constant  0.094810  1.051405  0.101290   \n",
+       "\n",
+       "           c2  xopt_runtime  xopt_error  \n",
+       "0    4.552658      0.013142       False  \n",
+       "1    4.542450      0.009709       False  \n",
+       "2    6.851906      0.030881       False  \n",
+       "3    6.634924      0.035817       False  \n",
+       "4    3.206055      0.011276       False  \n",
+       "..        ...           ...         ...  \n",
+       "995  0.241558      0.065372       False  \n",
+       "996  0.233530      0.074797       False  \n",
+       "997  0.211123      0.127204       False  \n",
+       "998  0.254356      0.074385       False  \n",
+       "999  0.468226      0.000649       False  \n",
+       "\n",
+       "[1000 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "X.data"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:54:10.662656Z",
@@ -414,7 +1318,248 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "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>x1</th>\n",
+       "      <th>x2</th>\n",
+       "      <th>a</th>\n",
+       "      <th>y1</th>\n",
+       "      <th>y2</th>\n",
+       "      <th>c1</th>\n",
+       "      <th>c2</th>\n",
+       "      <th>xopt_runtime</th>\n",
+       "      <th>xopt_error</th>\n",
+       "      <th>feasible_c1</th>\n",
+       "      <th>feasible_c2</th>\n",
+       "      <th>feasible</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>0.559672</td>\n",
+       "      <td>1.195656</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>0.559672</td>\n",
+       "      <td>1.195656</td>\n",
+       "      <td>0.667745</td>\n",
+       "      <td>0.487498</td>\n",
+       "      <td>0.085315</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>0.556263</td>\n",
+       "      <td>0.931855</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>0.556263</td>\n",
+       "      <td>0.931855</td>\n",
+       "      <td>0.246435</td>\n",
+       "      <td>0.189664</td>\n",
+       "      <td>0.002391</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>0.663205</td>\n",
+       "      <td>0.871685</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>0.663205</td>\n",
+       "      <td>0.871685</td>\n",
+       "      <td>0.255247</td>\n",
+       "      <td>0.164786</td>\n",
+       "      <td>0.155068</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>1.044052</td>\n",
+       "      <td>0.629606</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>1.044052</td>\n",
+       "      <td>0.629606</td>\n",
+       "      <td>0.560136</td>\n",
+       "      <td>0.312790</td>\n",
+       "      <td>0.024014</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>54</th>\n",
+       "      <td>0.825409</td>\n",
+       "      <td>0.984049</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>0.825409</td>\n",
+       "      <td>0.984049</td>\n",
+       "      <td>0.632576</td>\n",
+       "      <td>0.340195</td>\n",
+       "      <td>0.025046</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>992</th>\n",
+       "      <td>0.463256</td>\n",
+       "      <td>0.911677</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>0.463256</td>\n",
+       "      <td>0.911677</td>\n",
+       "      <td>0.013185</td>\n",
+       "      <td>0.170828</td>\n",
+       "      <td>0.137994</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>996</th>\n",
+       "      <td>0.959897</td>\n",
+       "      <td>0.648406</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>0.959897</td>\n",
+       "      <td>0.648406</td>\n",
+       "      <td>0.441508</td>\n",
+       "      <td>0.233530</td>\n",
+       "      <td>0.074797</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>997</th>\n",
+       "      <td>0.541181</td>\n",
+       "      <td>0.957632</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>0.541181</td>\n",
+       "      <td>0.957632</td>\n",
+       "      <td>0.246667</td>\n",
+       "      <td>0.211123</td>\n",
+       "      <td>0.127204</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>998</th>\n",
+       "      <td>0.867102</td>\n",
+       "      <td>0.845820</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>0.867102</td>\n",
+       "      <td>0.845820</td>\n",
+       "      <td>0.369247</td>\n",
+       "      <td>0.254356</td>\n",
+       "      <td>0.074385</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>999</th>\n",
+       "      <td>0.094810</td>\n",
+       "      <td>1.051405</td>\n",
+       "      <td>dummy_constant</td>\n",
+       "      <td>0.094810</td>\n",
+       "      <td>1.051405</td>\n",
+       "      <td>0.101290</td>\n",
+       "      <td>0.468226</td>\n",
+       "      <td>0.000649</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>477 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           x1        x2               a        y1        y2        c1  \\\n",
+       "5    0.559672  1.195656  dummy_constant  0.559672  1.195656  0.667745   \n",
+       "12   0.556263  0.931855  dummy_constant  0.556263  0.931855  0.246435   \n",
+       "45   0.663205  0.871685  dummy_constant  0.663205  0.871685  0.255247   \n",
+       "49   1.044052  0.629606  dummy_constant  1.044052  0.629606  0.560136   \n",
+       "54   0.825409  0.984049  dummy_constant  0.825409  0.984049  0.632576   \n",
+       "..        ...       ...             ...       ...       ...       ...   \n",
+       "992  0.463256  0.911677  dummy_constant  0.463256  0.911677  0.013185   \n",
+       "996  0.959897  0.648406  dummy_constant  0.959897  0.648406  0.441508   \n",
+       "997  0.541181  0.957632  dummy_constant  0.541181  0.957632  0.246667   \n",
+       "998  0.867102  0.845820  dummy_constant  0.867102  0.845820  0.369247   \n",
+       "999  0.094810  1.051405  dummy_constant  0.094810  1.051405  0.101290   \n",
+       "\n",
+       "           c2  xopt_runtime  xopt_error  feasible_c1  feasible_c2  feasible  \n",
+       "5    0.487498      0.085315       False         True         True      True  \n",
+       "12   0.189664      0.002391       False         True         True      True  \n",
+       "45   0.164786      0.155068       False         True         True      True  \n",
+       "49   0.312790      0.024014       False         True         True      True  \n",
+       "54   0.340195      0.025046       False         True         True      True  \n",
+       "..        ...           ...         ...          ...          ...       ...  \n",
+       "992  0.170828      0.137994       False         True         True      True  \n",
+       "996  0.233530      0.074797       False         True         True      True  \n",
+       "997  0.211123      0.127204       False         True         True      True  \n",
+       "998  0.254356      0.074385       False         True         True      True  \n",
+       "999  0.468226      0.000649       False         True         True      True  \n",
+       "\n",
+       "[477 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "df = pd.concat([X.data, get_feasibility_data(X.vocs, X.data)], axis=1)\n",
     "df[df[\"feasible\"]]"
@@ -422,7 +1567,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:54:10.671305Z",
@@ -434,7 +1579,23 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "image/png": {
+       "height": 432,
+       "width": 458
+      }
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Plot the feasible ones\n",
     "feasible_df = df[df[\"feasible\"]]\n",
@@ -443,7 +1604,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:54:10.759331Z",
@@ -455,7 +1616,23 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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AEdOKjEkenxdzc7wqSmAHAAAAREzL7Cd5fB58lPNVUQI7AAAAIGLaO03L7Js4qmfnxHuvpcGmnK+KEtgBAADAob0oV6zZ6HxE+LR3mtlxvUM/lyzqlPNV0XSfPQAAAAJZu3GrzJq/XB58+V3ZVlBJsLamWsYc3UOmjesn3TvXcS+HQBtiX7tgpa/iHgd2bC/jBx7M/e9jVXS5QTpmFlZFWbEDAABW0v0u65q3pX7fi81ue3KVDJv9sFMRsDCoU/q1fl8v1+shuI61NfLziYOkfY23Ibhe74ZJg5zj4M3EHK+K8igBAADW0F5SWq5cK9sVzrrrLLwO2HTFg0FuODRYu/LeZRWv1yqy+3rnH9snpFvPr6GHdZG5Fw1zeqeVW7nTlToN6ob06RLr+aXdWTleFa1qbW3V5ysyrKmpSXr16uV83tjYKA0NDUmfEgAAe1n65gZPg11d8dDBMYKlX+pKnJ9BYJWIPH3FSaRlhjiJoSuiWmZfKzIWpgTq6pEGGkximL+WTLz5aU9NynVVdN6UYbEG0FGNzQnscoDADgCQtYGYrngQ3JmbeuefjRoy62rIdecMDHDLKEbTjbUioxbvSPs+r7RNFN2QwKpoVGNz9tgBAIDEVy50AOYlqFN6Pb2+HgczWijF7Lg13OUR0GCuW30tQV2Ihh7WRR67fLTMnjDAWQUtpF/r9/XyLKW6sscOAAAkSvfU+dkPo/T6uuJ07jCzQgl5pq0M2hZK8Wpryy7n+C6d2od+XkDYOtbWOK8R+j8Pq6Ks2AEAgERpoRSz41Yb32aeK26ubd6a6PFAEvbNwaooK3YAACAxGliZ9JxSWnBCj/c6UKPi5se619clejyAaBDYAQCAxGhqVNDjvQR25QopaGA57e6XnRLpeai4qWmU2nzcJB2zrqaaNEzAUqRiAgCAxOh+l6iPdytuVtrHp5fr9fT6WTfm6B6Gx/UM/VwAhIPADgAAJEZX27T5uAmtbFdptc6k4uaU257JfMXNaeP6OX3p/NDrXzGub0RnBCAoAjsAAJCoicPNKltqE+coKm5u3Noi1y98TbKse+c6mXFmf1/HzBzfn+bkgMUI7AAAQKK06bU2CvZDrz9+4MGRVdy8+Yk3M79qd/6xfWTmmf0rrtzp5VeN7y+TR/SJ6cwAmCCwAwAAifea0qIl7Wu8DUv0ejdMGuQcF1XFzZ27WuV/nm2SrNPg7ukrTnKCay2MUki/1u/r5QR1gP2oigkAABKnlSjnXjSsZOXKwpU6DeqG9OkSeb+1Xz29Wi44LvurVJqWed05A0VkoNN8XO83bWlAE3IgXQjsAACANcHdY5ePlt8//47TfFz71BUWStE9dZp+WWmlzvXHFWsDnc/KtZt89cnLAg3mCOiAdCKwAwAA1tCg7dxhhzr/NajSPnXa0sAkuPptCKmUXvvkAUDSCOwAAICVNKAyDaqC7K8Ls88eAMSF4ikAACBzdKUtKC998gDAFgR2AAAgc8JYafPSJw8AbEFgBwAAMkdX2vr17Gx8vNc+eQBgCwI7AACQSROHH2p0XE11lac+eQBgEwI7AACQSdpcW1fe/KgSkVsuGOKpTx4A2ITADgAAZJKuuP184iBpX+NtuNOuukpuu2iojDqyW+TnBgBhI7ADAACZbno+96JhFVfu9PI7Lx4uoz5NUAcgnUgeBwAAmQ/uHrt8tPz++Xdk7pLV8kpBfzttaaDVL7VQCnvqYEr7JmqLDa3GSosMJIXADgAAZJ4GbecOO9T5zyAcYdi8rUXuef5tmbvkLVleMFmg1Vi1cI/u8WSyAHEisAMAALmiKyqsqiCIpW9ukH+Y+5y8v3n7XpdpkDft7pfl2gUrnT2eumIMxIE9dgAAAICPoG7izU8XDeoK6eV6Pb0+EAcCOwAAAMBj+qWu1G1v2eXp/tLr6fX1OCBqBHYAAACAB7qnrtJKXVt6fS3cA0SNwA4AAADwQAulmNBqrEDUCOwAAEAuaXXMdc3bnI95x33h7T4qrH7ph7bY4HGGqFEVEwAA5AYl6rkvTGmfuqDHU40VUSKwAwAAuUCJeu6LILT5eJLHA5WQigkAADKPEvXcF0Hpaps2HzdxVM/OrNYhcgR2AAAg0yhRz30RlonDDzU8rndo5wCUQmAHAAAyjRL13BdhOWvgIXJgx/a+jtHrjx94cGjnAJRCYAcAADKNEvXcF2HpWFsjP584SNrXeBtC6/VumDTIOQ6IGoEdAADILErUc1+EbehhXWTuRcMqrtzp5fOmDJMhfbqEfg5AMUwfAACAzKJEPfdFVMHdY5ePlt8//47TfFz71BUWStE9dZp+yUod4kRgBwAAMosS9dwXUdGg7dxhhzr/dWVYJxH08UavOiSFVEwAQOx0ELSueZvzEYgSJeq5L+J6nHWrr90d1PEahySwYgdkADOFSEvJea1OqIUslhekLWlfKC0hrtXmSFtCFPTxNe3ulw2Oy16Jeu6L6PAah6RVtba2tiZ9EohWU1OT9OrVy/m8sbFRGhoauMszgDcQpK059D/MfU7e37y9bKEBrTane1eAsF8vR12zqOzjr9jjUfdQZW2ygfsiGrzGwYaxOamYQErfQHSQojPQhSsfSr/W7+vlej0gafo4nHjz0xUH1Xq5Xo/HLcJGiXruiyjxGgdbENgBKcMbCNK2OqArddtbdnm6vl5Pr6/HAWGiRD33RRR4jYNNCOyAFOENBGmje+r8pL8pvb6WEAeiKlE/e8IApyR9If1av6+X56HvGPdFOHiNg02ylTgOZFyQNxAtxwzETQulmB23mscsIkGJeu6LMPEaB5uwYgerUB44ujcQIInnc9s9oF5ps19aISDuEvV5xn3hH69xsA0rdkgc1R3jewNh8II4abPeoMfzmAVgK17jYBsCO1hbHtit7njtgpWUQOcNBCnUKWCZ+KDHA0CUeI2DbUjFRGKo7ugPbyBIG11t0+bjJrSQBat1AGzGaxxsk9vA7k9/+pPMnj1bxo4d6zQIrK2tlU6dOsmRRx4pF1xwgSxevDiU25kxY4ZUVVV5+v/II49IXlDd0T/eQJBGE4ebFe2ZOLx36OcCAGHjNQ42yWVgd/zxx8ugQYNk2rRp8uCDDzrd37dv3y6bN2+W1157TW677TYZNWqUTJ482fk+wkd5YDO8gSBtzhp4iBzYsb2vY/T64wceHNk5AX5R2Aul8BoHm+RyA8Pbb7/tfDz44IPly1/+sowcOVIOPfRQ2blzpzz11FPyox/9yLnOHXfcIS0tLfKrX/0qlNt96aWXyl5+2GGHSV5QHtj8DUT3HPppecAgGUmXlv/5xEEy8eanPTUpb19TLTdMGuQcBySJwl7wgtc42KSqtbW1VXLmC1/4grMa96UvfUnatdu7xPH69evluOOOk5UrVzpfP/bYY07wZ5qKOXPmTOfzpO5qXZHUdFPV2NgoDQ0NkvTMZ7/pDxofv/yqMbnee+PuTfQ6SJ43ZVgumu0ivYWSCichNKjj8Yq0PF510kIbfQO8xsGGsXkuUzHvv/9+Ofvss4sGdapr167Oqp3rd7/7XYxnl31hlAfOMx1EzL1oWMX0Nr2coA42PW4fu3y0zJ4wwCmMUki/1u/r5QR1SBqFvWCC1zjYgFyXEk444YTdn//lL3+J6++RC1R3DO8N5PfPv+M0H9c+dYWDZC08oXuUSGeDTfTxeO6wQ53/unKvkzT6epDnFXhko7CXvh7zegte45A0ArsSCoumVFfncmEz8uqOJs22KYH+Cd5AkPbXAQI6ZKmwl05YAC5e45AEArsSHn300d2f9+3bN5Q7+5RTTnHaLDQ3N8v+++8vRx11lIwZM0YuueQSOeCAAwLl6ZazZs0asbG6ozYf938cJdCL4Q0EAIK7/cnVhsetIrBDqMhqgAkCuyJ27dolP/zhD3d/rfvxwrBw4cLdn69bt84JHvX/1VdfLbfeequMHz/e6Oe6my/ThOqOAADbBtKvvtdsdOyK95qd41mFhq2VWAkU84HArogf//jHsnTpUufzCRMmyODBgwPdyQMGDJCzzjpLhg4d6rRY2LFjh7z66qsyb948WbBggfz1r391KnTed999TsP0PKA8MAAga4W9COwQRVVNDfI0y0nbHfmpxErLjvzJZbuDcnQF7eSTT3b613Xv3l1efPFFOeigg4x/ngZtmnZZyo033iiXXnqp87kGfa+//rrsu+++oadialBpS7uDQpQHBgDYYMOm7fJ333/I+Pg//fsp0qVT+WrFQBhtjLQydqXgjpYddqPdQQyWLVvmrNBpUFdbWyu//e1vAwV1qlxQp3R/3ZQpU5zP33nnHbnrrrt834YGauX+9+zZU2xFeWAAgA12BpznDno88sm0EqseVwotO/KLVMy/efPNN+XUU0+VDz74wOlv9+tf/1qOP/74WP4IGtzNmTNn94rheeedJ3lCdUcAQNJoxYMsVGKlZUe+Ucf/bytlmn6pH6uqquSWW25xVu7iotUxXW+//bbkme5P6FZfyz4FAEDs7z+f6VFvdGzfHvW8b8GIFkoxO2516IEi0i/3gd369eudNgRvvPGGc4f89Kc/lcmTJ8f6R2CbIwAAyZs8wqylzuQRfUI/F2SfVqo06emrXlmz0Tk+6kAR6ZLrwO7DDz+U0047TV555RXna21x8I1vfCP283Bv3y2gAgAA4qfl5A/s6K8Ail5//EDeu5FMJdaoA0WkS24Duy1btsjpp5/uNAxX06ZNk+985zuJnItWxnTFta8P2aIvxuuat/GiDAAhtOLRyoNe6PVumDTIuLcY8i3sfZ1hB4pIn1wGdtu3b3f20D3xxBPO11OnTpXvf//7vn+ONhXXPXn6f8aMGXtd/tJLLzntCyoFdTfffLPzeY8ePWLd24d00w3S855eLWOvXyz9pj8oQ2YtdD7q1/r9chWzAAClqzVrOflKK3d6+bwpw2RIH289xYBi+zq1+biJo3p23mtfJwWAkMsppq9+9atOY3B14oknykUXXSQvv/xyyeu3b99ejjzySN+389xzzzmtDEaPHu00HtdG5QceeKDTTmHFihUyd+5ceeihj3vmaCVODfI6duwY4DdDXkTRyBQAsGcrHi0ooXuPNE2tcEA9cXhvJ/2SlToENXH4oc57tv/jepcMFE3SMYsFikifXAZ2hb3i/vjHP8oxxxxT9vq9e/eWVatWGd3Wzp07ZeHChc7/UjTY01W7M8880+g2kC9eG5lq0KfX89LIFACwJ1rxIK59nToR66eSZbl9nWEGilnevrJpW4uzwpm1YDaXgV1cxo0b5wRsTz31lPz5z3+W9957T95//32nCmaXLl3ks5/9rIwZM0YuuOAC6dzZbCke+UJ/GgCInw7+0jAAzPKANev7Or1M2HrZ1xl2oJil8dM9z7/tVA0tXNHUFU4NhvV+y8IKfFUrtfYzr6mpSXr16uV83tjYKA0NDUmfEgzp3jmTmbjZEwYUbWQKAEi3vAxY87zFojAA06Cu0r5Or5k9bqCY9b2iSz3et3FuX4lqbE5glwMEdtmhhVFMc+fnTx0ZyTkBAJJh44AVwYL0sPZ1hhkoptlSn0FuXNtXCOxg3YMH8afYaNVLU8uvGkNqDgBkhK0DVtiTVhtmoJhGm7e1yKhrFvlOS9XCSVHfL1GNzbP71wQyJoz+NOy5AID0Y7919oWxrzPvBYDuef5tX0Gd0utrMJzW7Su57GMHpBH9aQAAQQesyCcN5rrV1+YmqFO679SErnCmFYEdkNNGpgCAdMrjgBV70hW4dc3bnI/Y20fbdxrVJFCatprW+5VUTCBF6E8DAPkWxoCVib50ogKqd5tyun2FFTsgRbRstW7s9SMP/WkAIC/CGLAincVytBCItjxqG9jr1/p9vVyvB8nt9hUCOyCFjUy1wpkXlRqZAgDSJa8D1jxzK6BW2lepl+v1CO4kt9tXCOyAlNFy1Vq2utLKnV6e9aajAJA3eR2w5pVpBVQ9Lu8mDjerbKmtINKKwA5IaXCnfVZmTxjgvFEX0q/1+3o5QR0AZE8eB6x5RQVUc2flcPsK6/FASuW9Pw0A5HnAeu2Clb4bL6d5wJpXQSqgprUXW9jbVybe/LSnFc8sbF9hxQ7IgDz2pwGAvGK/dT7ktWR/mIbmbPsKgR0AAEDK5G3AmkdJVEDNYn+8oTnavpLetUYAAIAccwesv3/+HSf1TldpCgesuqdO0y/TnFqWZ3FVQM1Df7yOOdm+ku6/EgAAQI7lZcCa5wqoJumYXiugamsEraJZbL+m2x9P93PqXjWdSMiCfdu3y+zzg1RMAACADGC/dfZEWQGV/njZQ2AHAAAA5KhkP/3xsonADgAAAMhRBVT642UTgR0AAACQowqoQfrjwV4UTwEAAAByUgE1jP54WS0+knYEdgAAAEBOKqCG0R+PwM5OBHYAAABATkr2x9UfD/Fjjx0AAACQs/54Jrz2x0MyCOwAAACAHImyPx6SQ2AHAACcPTvrmrc5HwFkW1T98ZAskmSBlAuygTqM44E0y/vjX5sUaz8rLX1eWCVP07R0Rl8Hf16q7AFIZ3+8iTc/LdtbdoXWHw/JqmptbW1N+BwQsaamJunVq5fzeWNjozQ0NHCf53wwxmAOecbj/2NL39wg/zD3OXl/8/ayM/Q6+NNS6wDy+zqgQZ2X/nhIdmxOYJcDBHbZEnQwxmAOecbj/5P7wc9MvTZHJrgDsjvZFUZ/PHhHYAdjBHbZEXQwxmAOecbj/5NB3KhrFpWdHCo2WaTNkRncAdmW9/T0tI/NKZ4CpGgwpit1XoI6pdfT6+txYRwPpFlUj/80FhzRNG4/QZ3S6+uMPpKVxscb0kWDuW71tQR1KcW6KpCDwdi5ww4NfDyQZmE+/tO+R0/P2+y41bwWJCDtj7csYTULtuOVAEiJoIMxBnPIs7Ae/+X26Omge9rdL8u1C1ZaW3BEB6aFwYEfuvdGjyc9Kz5pf7xlIeDKemBNsJot6X0kAjkSdDC2YdN2BnPIrbCCGa979HQQrtezseCIDn6DHk9gF48sPN6iFEfAldXAOuvBap6xxw5IgaCDsbXNWxO9fSDtwUxW9qjqikaSx8ObrDzeoqIBlxYA0sCq7aSNG3Dp5Xq9ILehAXOlFG43sA5yW1m775AcAjsgBYIOprrX1yV6+0Dag5msFBzR1TadlTehpc9ZrYtHVh5vUYgj4MpqYJ3VYBWfILADUiDoYKxLp/YM5pBbYQQzQfbo2VYBUVOtzI7rHep5oLQkHm9pEFfAlcXAOqvBKvZEYAekRNDBGIM55FmQx38Ye/S8Bm46iJr39GoZe/1i6Tf9QRkya6HzUb/W74cxyNL9M9qXzg+9vjYpRvSierxlQVwBVxYD6ywGq9gbgR2QEkEHY1EN5uirhDQI8vgPY4+el8Bt1gPLZeTVf4x874sWRdBiD+1rvA0B9Ho3TBpEMYWYhPl4y5o4Aq6sBtZZDFaxNwI7ICWCDsbCHMzFsaoAhCnI4z+sgiOVihbctPgN2bBlRyx7X7SCn1ZRrBTs6uXzpgyTIX3SU/Ev7Shwk2zAlcXAOqvBKvZGYAekSNDBWBiDOSpqIa1MH/9h7NHzWrQgzr0ven88dvlomT1hgHOehfRr/b5eTlAXLwrcJBtwZTGwzmKwiuLse/QB8DQY07x3TZHQ2bTCwZjuCdL0sVI9aIIcT18lpJ3p41/36OlKm1/68/wWLfCz96WweboJ/T31Z+h/GhWXFvd9E+TxllVxBVxuYG2ywmVr5dgsBqsojr8UkEJBB2Mmx5tW1NJBNI1OYROTx7/u0dNGxH5W3Nw9eiZFC7zQwDRoYFdIf38bB6V5bOIc5PGWVXEGXKaB9VeG9HIKIsU1AeBVFoNVFEcqJpBy+oLbrb7W+IXX6/G2VtSieAuC8Pr4D7JHz7RoQSXsfYlO0innFLgpLq7qzibFltpVV8mV9y6zds85lbHzgcAOQOoqalG8BWnZoxekaIEX7H3JbhNnCtwk16rDb2Ctdu5qjX0CwA/anOQDgR2AVFXUSnomHfnmt+BI1IEXe1+y3cSZAjfJrWR6DawriXoCwCtWgfOhqrW1dc8pBmROU1OT9OrVy/m8sbFRGhoakj4lpIzuGdD0ElPPTDvZSXcLymvxFvcNXd+U9c0ZiEqlPXp6uaZlRUEDyflTR0bys/NKU+dM9lZpQB/mfsdSKHDzyXuBBtTlVlU1INOgLmhVVw3aixVb0tTLtqt05ej52LDnPM77DvGPzSmeAiAVFbUo3gIbVSo4EqRoQZ4rIKYx5TyOwI4CN+FUhw5abOn+F9+Rmfe9kkgl2zTdd4gffzUAqaioFaR4S9JvpMg30wp7ea6AmNaUc6oHxieJVh1uYP3bZ5usngCohDYn2cUeOwCpqKhlU/EWIOqiBVHtG0JpNHHOb3XotO45T9t9h+gR2AGwvqJW1t5IkS8mFfa8VNxE9lLOYT8mAGAzAjsA1lfU4o0Uaee1wl6Xju3l4pGf8lRxE9GknJugiXN+MAEAmzG9BMD34DTuilq8kSIL/BYtoAJievZDUsgmP2zYcw6UQmAHwPqKWryRIiv8FC2gAmIyKefXLljpq1AThWzyhwkA2IrADkAqKmrxRoqsIXCzN+XcT79MCtnkDxMAsBV77ACkoqJWksVbAOSH1/2QFLLJryT3nAPlENgBSAXeSAHEnXKuBWsoZINSjxEmAGCbqtbW1takTwLRampqkl69ejmfNzY2SkNDA3c5UmvpmxtiL94CIN8oZMN9VMrmbS2x7jlHNjRFNDYnsMsBAjtkDW+kAGDHa/E9z78tc5e8tUeVSK0aqfuiNYU+T0ENEwDwisAOxgjskGW8kQKAvdkTuhdN0xYBRD82Z48dgFSLq3gLAOCToE4rh1ZqC6GX6/X0+gCiR2AHAAAAz+mXulLnpR2E0uvp9fU4ANEisAMAAIAnuqfOTwN3pdfXAiMAokVgBwAAAE+0UIoJrRoJIFoEdgAAAPBUrKqw+qUf2gpAjwcQHQI7AAAq0AHpuuZtDEyRa5sC7pMLejyA8vLTXAQAAB/o0QXsqVPAnnRBj48DLXSQZvY/wwAAsKhHl6aiTbv7Zbl2wUp6dCFXtK2MNh83Scc8qmdna9vSMImDrCAVEwCAAvToAkqbOPxQo7tn4vDe1j7fR12zyJmsaRuwupM4ejm9+JAGBHYAAPwNPbqA8s4aeIgc2LG9r7tJrz9+4MHW3bVM4iBrCOwAAPgbenQB5XWsrXFSkNvXeBtC6vVumDTIOc4mTOIgiwjsAADISY+utz/4SJ56fb3zETA19LAuMveiYRVX7vTyeVOGyZA+Xay7s/M4ibNh03ZZsWaj8xHZZNf0CQAAKe7RZWNxiFXrN8nUO5+XF5s+lNaC71eJyDEN+8n15wyUPl07JXiGSGtw99jlo51ARyc29DlQWChF99Rp+qVtK3VhTOKcO8xsn2ES1m7cKrPmL5cHX35XtrXs2v392ppqGXN0D5k2rp9071yX6DkiPHY+2wAASGGPLtsCu6vuWya3PLGq6GUa5L3Q9KGc8F+PyteO6yPTz+gf+/kh3TRo0yBH/6epTUBWJ3Hauu3JVTLj3mV7TOi4NMjToPze59+RGWf2l/OP7ZPAGSJsBHYAAGSwR1e5oK4t93oEdzClgU4agp2sTuIUC+quvHdZxetp0Odej+Au/dhjBwBAQY8uE7b16NL0S69BnUuvr8cBWZe1SZxi6Ze6UueHXl+PQ7oR2AEAkLEeXbqnzsS37nwh9HMBbJOlSZxidE9dsfTLcvT6s+eviOiMEBcCOwAAMtajSwulmHih6a+hnwtgo6xM4hSjhVLMjlsT+rkgXgR2AABkqEeXtjLwO1vv0uNohYA8yMokTlvayqCw+qUfW1t20Qoh5QjsAADIUI+ut97fnOjxQBpkYRKnmLXNWxM9HskisAMAoESPrtkTBjh7agrp1/p9vdy2oE4demDHRI8H0iLtkzjFdK+vS/R4JMvuaQcAABKS1h5dhxywr9N83CQds+pvxwN5kfZG62116dTeaT5uko5ZV1PtHI/0SsejFACABKWpR5c6pmE/p/m4X59t2D+S8wFsltZJnFLGHN3DCVT9H9czkvNBfEjFBAAgY64/Z6DRcded89nQzwVIEw3mutXXpjaoU9PG9XNW3/3Q618xrm9EZ4S4ENgBAJAxfbp2kq8d18fXMRd9vo9zHIB06965Tmac2d/XMTPH93eOQ7oR2AEAkEHTz+jvObjToO57X/A3EARMabrjuuZtzkdE4/xj+8jMM/tXXLnTy68a318mj/A3EQQ7sccOAIAMB3eTR/SWb935gtN8vLXNgE731Gn6JSt1iNrmbS1yz/Nvy9wlb8nyggIl/ZwCJYc6feXSUqAkTcHd2KN7yOz5K5zm49qnrrBQiu6p0/RLVuqyo6q1tdW0jylSoqmpSXr16uV83tjYKA0NDUmfEgAgAdp8XPvUaUsDql8iLkvf3CD/MPc5eX/z9rItBbSvnFapRHTNy7VPnbY0oPplNsfmuU3F/NOf/iSzZ8+WsWPHOndsbW2tdOrUSY488ki54IILZPHixaHf5p133imnnXaa9OzZU+rq6qRPnz4yadIkWbJkSei3BQBAWxrMjTiiK0EdYg3qJt78dNmgTunlej29PqKhwVzfnp0J6jIslyt2xx9/vDz22GMVr6dB15w5c6R9+2A9PbZu3Spf/vKX5f777y96eXV1tcyYMUO+973vSRRYsQMAAEmkX466ZlHFoK7typ32lSMtE1nWxIpdeN5++23n48EHHyxTp06V3/3ud7J06VJ56qmn5Nprr5VDDjnEufyOO+5wVu+Cuuiii3YHdaNHj5Z77rnHub2bb75ZDj/8cNm1a5dMnz7dCSIBAACyQPfU+QnqlF7fpAcbgJyu2H3hC1+QyZMny5e+9CVp127vPiXr16+X4447TlauXOl8rat7I0eONLqtRx99VE444QTn8zPOOEPuvvvuPW5Tb2vQoEHy1ltvyQEHHCBvvPGG7L9/uA1iWbEDAABxG3v94j0KpXh1VM/OMn+q2bgLSANW7EKkq2dnn3120aBOde3aVX70ox/t/lpX9Exdc801zke9rZ/97Gd73abe1tVXX+18/sEHHzireAAAAGmmrQxMgjr1ypqNtEIADOS2eEol7iqb+stf/mL0MzZt2iQPP/yw8/kpp5xSsuLNF7/4RencubPz+V133WV0WwAAALbYtK0l0eOBPCKwK2H79u17FDcxofvotm3btrtgSylanGX48OG7j9mxY4fR7QEAEBeaTKOcTgF70gU9HsgjnjVl9sa5+vbta3TnLl++3PPP0MsXLFggLS0t8tprr8lRRx3lK0+3nDVr1nj+WQAARN1kWoNCXZHRwfu+7Ytvi0C66d9VHxeme+x4XAD+EdgVoVUqf/jDH+7+WvfjmdCGg65KjQfdJoXucX4Cu8JjAQCIu8m0Dt6n3f2yXLtgZckm02EFhUgP/bvq48L/cb0jOR8g60jFLOLHP/6xkxKpJkyYIIMHDza6c5ubm3d/rs3Py+nYseMee/MAAMhKk2n9WvuZ6SC/7QqOGxTq5TSnzhYN1rUvnR96/fEDD47snIAsI7ArkoL5b//2b87n3bt3l5///OeBGpO7KjU5r62t3f35Rx995Ot2dIWv3H83SAUAwC9dadOVuu0tuzxdX6+n19fjwggKkV66AqsruO1rvA039Xo3TBrEyi1giJyHAsuWLXNW6HSfmwZav/3tb+Wggw4yvW+lrq6uaDGWYtwiK2rffff1dTuV0jwBAEiiybSuvJgEhY9dPprBfUZoWu7ci4aVTOMtXKnToG5In73TeAF4Q2D3N2+++aaceuqpTi857TX361//umwlSy/q6+s9p1du3rzZc9omAABx0T1xZsetllZpNQ4Kzx12qNHtws7gToN1/bvq40L71BUWStE9dToJwB5LIBgCOxF555135OSTT3Y+VlVVyS233OKs3AVVuJKmlSvL7dUrLLRCMRQAQBaaTN/x1GqjY3XwT2CXLRq06d9U/1MVFYhG7gO79evXO83D33jjDecO+elPfyqTJ08O5c4trGy5YsWKstd1L6+pqZEjjjgilNsHACDJJtEr3v2kiJjfoFAH/5S8zyb9u/K3BcKX6+IpH374oZx22mnyyiuvOF9ri4NvfOMbof38IUOG7C6aUtgXry3df7dkyZK9jgEAIElJNokOGlQCQN7kNrDbsmWLnH766fKnP/3J+XratGnyne98J9Tb0D12J510kvP5woULSzYSv+uuu2Tjxo9TXcJIAQXSQmfk1zVvcz4CsLfJtIm+PT7ZZ562oBIA0iiXgZ2ukGkA9cQTTzhfT506Vb7//e/7/jm33nqrsydP/8+YMaPodb797W87H7XSpq4G7ty5c69UUDeg3H///WXKlCkGvxGQHloCfd7Tq2Xs9Yul3/QHZcishc5H/Vq/75ZIB2BPk2kTk0f0MQ4KtaAGqXoA4E8up8O++tWvyoIFC5zPTzzxRLnooovk5ZdfLnl9TY088sgjjW5Lf/4555wjd955p9x7773Ofr5vfetbcvDBB8tLL70ks2bNkrfeemt3KugBBxxg+FsB9tP+VKVKXrtNiq9dsNLpe6RV1ADY0WRan5d+qlu6Taa1KqY+r/3SKokAAH9yGdhp6qPrj3/8oxxzzDFlr9+7d29ZtWqV8e1plU1NtZw/f74sWrTI+V+ourpavve978kll1xifBuA7dwmxZX6WblNirXvEcEdYE+TaS/P37ZNpoMEhQAAf3KZihk3bTj+wAMPyLx585wVu+7duzurgNrW4Nxzz5XHH3+8ZConkAWaXmnSpJi0TMCuJtMadJWjl8+bMmx3k2k3KNRgz4vCoBAA4E9Va2trq89jkDJatMXtjaf98gr76wFx0L1zJulYsycMoJcVYBGdbDFpMl0uDbswKNSgzg0KASCrmiIamzMlBiByc5e8ZXgcTYqBLDSZ1hW/xy4fbRQUAgC84RUUQKR08KeFUWxsUuxnYAogWJNp06AQAOANgR0Aq5sM6/FhDvw0leye5992VhELA04ty65l3bXYA6sGgF1BIQCgMgI7AJEK2mQ4zCbFtFsAAABZRVVMAJHSWXkbmhS77RYqlV132y3o9bNK0+DWNW9zPqZJWs8bAIA4sGIHIHKa4phkk2LTdgta7CEraZlpTUFN63kDgBdZ2G+ahd8hK2h3kAO0O4ANg/NR1yzy3aQ4rMAq7+0WvJaa135jNjWFT+t5A0DWJ6yy8DtkcWxOYJcDBHawgZsK6WXVTJsUFzY5Dmrs9YuNKnNqKuj8qSMlT/e7NqG2IUhK63kDQNYnrLLwO2R1bM4eOwCx0Bd3HXzri305enmYQV0Y7RbSyjQFVY9LUlrPGwCyvtc7C79DlhHYAYiN26RYUxx1NayQfq3f18vDCurCareQVpom4yf9Ven1tYl0ktJ63gCQ5QmrLPwOWUfyK6zERtzsirtJsU3tFuKmex/Mjlud6N7CtJ43AEQxYWXL61oWfoesS++IBZnDRtz8iaNJsdtuwXSPXVorfIWRgprE757W8waArE9YZeF3yDpSMWEFzcHWqolaubDtoE6/1u/r5WnP1aYPVzK0QpfZceG0W0hCWlNQ03reAJDlvd5Z+B3ygBU7pKb6nbsRN23V71iJTJ6WXb52wUrf7RbGDzxY0iqtKahpPW8AiHLCKulMhCz8DnnAih0SlfWNuHlZiUzDvj4tu6xl8b3Q690waVCqe/C4KagmkkxBTet5A0CWJ6yy8DvkAYEdEpXl6neUBLZLUu0WkpTWFNS0njcAZHXCKgu/Qx4Q2CG1G3FtlvWVyLRKot1C0imolQJZG1NQ03reAJDlCass/A5Zx7ooEpPl6neUBLZX3O0WbEhB9bKH1aYU1LSeNwBkea93Fn6HrGPFDonJcvW7rK5EZo0Gc93qazMZ1KU9BTWt5512VO4FopGFvd5Z+B2yjnsaicnqRtwsr0Qi3SmoujdVJw/0cVaYgqppMjqjatubb1rPO21MK/dmfcUbiGrCSrdelFv10gkrDYhsnLDKwu+QZVWtra2tSZ8EotXU1CS9evVyPm9sbJSGhgZr7vKx1y82bhw9f+pIsdG65m0yZNZC4+OfmXays4rkxdsffCRvvb9ZDj2woxxywL7Gt4l8SeuAPK3nbXuRJy8DNJ2l1wEd7VuA4PR5lPYJqyz8DlkcmxPY5YDNgd28p1c7Jf/90iIXukfK1sFnv+kPGh+//KoxZQetq9Zvkql3Pi8vNn0ohbMyVSJyTMN+cv05A6VP104SNQbZQD56iLopVdPG9ZOfPPya5yAQQD7eS7PwO2RlbE4ojURlcSOuWxLYdCWy3IviVfctk1ueWFX0Mg3yXmj6UE74r0fla8f1keln9JewMVsPZINJ5d4r711W8Xr6Wq7BoqZqEdwBlel7ftqDoSz8DllB8RSkciNudVWVk/Kos0Q2iqIkcLmgri29nl4/TDRbB7LDpHKvV7RvAYBkENghNdXvunTYRy44to9M//0yJ9VR97HpR92npymdNvWAC7sPl6Zfeg3qXHp9PS4MNFsHssW0cq9XGjTq/hsAQHwI7JCKxtFfH/kpkaoq+cVjb+yV4qhf6z69UdcscgKQLJYE1j11Jr515wsSFM3WgWwJUrnXD9q3AEC82GMH6xtHv/T2h542+Nu2tyPMksBaKMXEC01/laBotg5kS1w9QGnfAgDxYsUOVjeO3tXa6nuDv17flrTMSiuR+n29vFxQpy0NTHuStP7t+CBotg5kS5w9QOMKIgEArNjBcllYLSq1Eum1gpT2qQtCjzftcUezdTtQShph0tee2ppq2eZxwiwtQSQA5B2vuLBakNUiWwK7oCWBtfl4EEGODzrbrsdTAtkMrSUQ5URBHEFdpfYtAIBwEdjBWqwWfUxX27T5uGk6Zhef1TnDnG1ntt6MFgEqtTfTLRak/R9pBA2b0yPLtW8BAISPPXawVhirRVlxTMN+xscGaQnhNls3wWy9GVpLIGpxTLiUa98CAIgGgR2sxWrRJ64/Z2Cg+zJIS4gomq2jOFpLIA5BJmy8mnryp0u2bwEARIPADtZitegTfbp2kq8d1yfwfeq2hPAT3IXdbB3RFAsC4piw8er7Dyy3pq8oAOQFgR2sxmrRJ6af0T+U4M5vS4iwm62jNFpLIC4mEza619cr21rPAEAeENjBaqwW7R3cPfLt42Vgw/6+BllBV3ncZuuVBoJ6+bwpw8r25UN0xYIAr/xO2LSrrvJdwInV5GzT15x1zdt47QEswpQ6UjH40PRBL03K87BapGmZ93zzOOdzbT5+7k1LZPWGLZG3hHCbrWtAqMdqMFFYKEX31Gn6ZZbv+yjRWgJxcydsSlVgLZyw6VRXI6vfj/51BnajDQtgN0ZgyNTgQ4O6PK0WaSsDk6CucJXHT5+poM3WURrFgpAELxM2px51kAyetTC21xnYiTYsgP0I7JAKrBbZt8pj0mwdlSsVmqRj0loCQVSasNF0u6ReZ2BXG5ZKmTNugS6djNX3bQDxIrBDarBatDdWebJXLEjbUvg/jtYSCEexCRteZ/LNtA2LrgSTmg/Ei+IpSCUdeHSrr839LDAtIbKFYkGwEa8z+UYbFiA9COyAlKMlRHbQWgK24nUmv2jDAqQHgR2QcqzyZAutJWAjXmfyiTYsQLoQ2AEpxypPdosFzZ4wwCmMUki/1u/r5XmqAItk8TqTT2EU6AIQH4qnIHeyWKaflhDZQ7Eg2IbXmfyhcA6QLgR2yIU8NFXtf3Bn+caJh8svHntT3v1w6x6X9dyvTi4e9Sk5e3Cv1P+eeURrCdiC1jP5QhsWIF2qWltbW5M+CUSrqalJevXq5Xze2NgoDQ0NuVpVK9dUtbC5+c8nDkpt3508/I4A7JPFDAjsad7Tq43asGjKuPZGBBDf2Jype2R6VS0PTVXz8DsCsBOrydmn773XLlhZduKw2ETi+IEHR3peAPZG8RRYQYOTUdcscmYFC4M6pV/r9/VyvV7UTVX1uLTIw+8I5Hk1bF3zNudjGs7P9vOFGQrnAOnBih0yu+IUpKlqWtJH8vA7Anli+37gUudXW1Mt2wpew205X4SDwjlAOrDHLgds3mOngwRdifOb4qGl3isNFsZev3iv1T8vtJz8/KkjJQ3y8DsCeWH7Xlkv59cWe3uzRd+zdWJw7pLV8krBe4++p0wc3ttJvySQBypjjx0yKaoVpzCaqtpeCCAPvyOQF7bvlfV6fm2xtzdbaMMC2I09dkiUpvOYuOOpVWX3cuShqWoefkcgD2zfK+v3/Npib2826cRgt/paJggBixDYIZUrTsvfbZYhsxZKv+kPOumIWo65cJCTZFPVv6zdJH94cY3zMUo0jgWyIUjmgq3nl+T5AkBesaMZiQlrxcitmqnlmN29J3E3VX3lnQ/l4tuflaa/7tkYXDXsXye/mDxYjjp4PwkTjWOBfGcu6D6nOIogmZ5fUucLAHnFih0SE3TFqdReDrclglZkM6EbwP34x7nPybifPF40qFP6fb1crxe2uH5HAPbulbX1/JI4XwDIMwI7JMZdcQpT4V4OLbOtFdn88NtUVYO1+S+/6+m6er2wg7s4fkcA+d0rG/bPZ28vAESHwA6JMl1x8rKXI+qmqpp+6TWoc+n19biw0DgWSDfb98qG/fOjPl8AyDMCOyTKZMXJ616OwqaqlW5DL583ZZgcffB+ZattFtI9dSYuvj3cVTu/v+OQPvH3vwIQfuaCyX7gJDMr4jhfAMgzps6QKHfFyaQ/ktc+bRr4aEPzUk1Vvzy4QVqlVab/ftkee0l0MKMrihp8FlvFK7WnrpKmv34kYav0O9I4FrCXvs5oAShb98qant/eP4e9vQAQparW1tbWSG8Bme1uHyYteKJ744KW1C70zLSTnR47bWnAp/s8NCXopbc/rHi7utLlVtt0aSuDk6591PjcHv6X4+Xw7p0kKoW/IzPkgN10T/Coaxb5ev3T1yWdzPGaOh73+SV5vgCQ17E5qZiwgrviNHvCAGeFKcq9HG5TVQ3qdKWw0mClbbVNtfLd5kDnFvT4SmgcC6SH7Xtl/Z5f0ucLAHlFYAdr6Ju+9jiaP3WkLL9qjLPi9pke9ZHs5dAZaF2p85r+WVhtUx1peF6uoMcDyBbb98p6Pb+22NsLAPEhsIOV3BWnySN6R7KX457n3/adVuRW21RB0yijTMMEkL3MBf1av6+XJ1UAqdz51bVZzbPhfAEgb8iLgNW0cMm1C1b63ntSqU/b3CVvGZ2PFibRVUXVsH+dUQGVhv33NbptAPnJXND/Nu6VLXd+pc7Xxt8DALKIwA6ZqprpZS+HDjIKq1+aVtv8xeTBMu4nj/v+Gb+YPMjotgHki77O2BwItT2/wq81bV0zI3QSzU+1YQCAOVIxkbu9JzpzHIR7/FEH7yfjju7h69jTB/RwjgOArNJCU1pFU1sktJ1E06/1+3p5YUEqAEBwBHbI3d6TUtUyvSo8/mcTB3kO7jSo+3/nsVoHILs0WDOtNgwACIY8CORu74leX9OBTNIxi1Xb1ODulXc+lItvf65o83HdU6fpl6zUAcgy02rD9LcDgHAQ2CGXe090j4emA4VVbVODtsf/7cTdzcu1T522NKD6JYC8CFJt2C1KBQAwRyomckk37pv0Y6pUbVNpMDf2mJ4EdQByJUi1YQBAcAR2yHW1Ta2i6YWXapsAkFdhVBsGAARDYIfcCrvaJgDkVVjVhgEA5lh+QK651TZ1j4emA+nMcWGhFN1Tp+mXrNTlF82VAYm12jAAwEwsr6QffPCBvPnmm1JdXS1HHHGEdOrUydNxH374ofz+9793Pp88eXLEZ4m8CqvaJrKD5sqAJFptGABgWSrmiy++KKeccop0795dhgwZIoMGDZIDDzxQxo8f71xWSVNTk1xwwQXyta99LcrTBHbTwUW3+loGGTlGc2XAvNqw2XHFqw0DACwJ7B555BE57rjj5I9//KPs3LlTWltbnf87duyQ+++/XwYPHiz/8R//4XyvEi/XAYCgaK4M2FltGACQUGCnKZRf/epXZfPmzU5QpkHct7/9bfmnf/onOeaYY5zvtbS0yIwZM+Sss86Sbdu2RXEaABB5c2U9DgDVhgEgk4HdnDlz5L333pOqqir56U9/KkuXLpVrrrlGrr/+enn++eflvvvuk969ezsBnq7enXbaadLc3BzFqQCx031665q3Ub47R82VAXyMasMAkLHiKRqsaVD3la98Rb7xjW/sdfnpp58uxx57rJx77rnyf//3f7J48WI56aST5MEHH5QuXSgpj/Sh2Ea+mytr4R0AH6PaMABkKLBbtmyZ8/G8884reZ0DDjhAHnjgAfmHf/gHuemmm+S5556T448/Xh566CHp0aNHFKcFRLYvS1Pyiq32aIW4aXe/LNcuWOk0RNcBD7LZXJmqfsAnqDYMABnaY6caGhrK33h1tdx4443yne98x0nLfOWVV2TUqFHS2NgYxWkBoaPYRjbQXBmIDtWGASDFgV2HDh2cj3/96189Xf8HP/iB81+Du7/85S8ycuRIef3116M4NSA0FNvIDporAwgL+6wBZCqw+9SnPuV8fOGFFzwfo6t2//3f/+18rit2unL30ksvRXF6QCgotpG95somaK4MQCf65j29WsZev1j6TX9Qhsxa6HzUr/X7VM8FkNrAThuR6+qbFkPx4x//8R/l1ltvdVI0taqmNicHslhsA/ahuTIA05T8UdcscvZTt92r6+6z1sv1egCQusBOK1wqLYTy9ttv+zp20qRJ8pvf/Eb22Wcfp5k5kNViG7ALzZUB+MU+awCZD+zGjRsn7du3l507d8qsWbN8H//FL35R7r33Xtl3330lKmvXrnXaMkyfPl3Gjh0rXbt2dVo06P8wVwq1Cbv7cyv9f+SRR0K7XUSLYhvZrOKnlUvb13h7WdTr3TBpkHMcgPxhnzUA20QyIqmvr5d77rlH3n//fWflzcSpp54qDz/8sO90Tq8OOuigSH4u8oFiG9lurlyqfYXrwI7tnaBuSB/aVwB5FWSfNb0vAUQhsqnmMWPGBP4Zw4YNc/5HrVevXtKvXz9ZsGBBpLdTqRjMYYcdFuntI/xiGybpmBTbsBvNlQFEvc+awA5AFGLLIfrhD38o559/vvTs2VNsoCmYQ4YMcf7r6t2qVasiD6yOPvroSH8+4i+2oZvi/R/XO5LzQXhorgwg6n3WOkEIANbvsSvmiiuukN69e8sZZ5zhpGm2tLRIkmbOnClf+MIXSMmEMYpt5APNlQG0xT5rALkO7JQGc/Pnz5cvfelLcsghh8i3v/1tWbZsWZynAISGYhsAkE/sswaQ68BO95d961vfcqpPao+7devWyY9//GM55phjZPjw4XLTTTdJc3NzXKcDhFpsQ4tplKOXz5syjGIbAJChfdYm2GcNIPWBXf/+/eXaa691+trdddddTkpmu3btnCDvmWeekUsvvdTZf6f78B599FHJolNOOUUOPPBApxVE9+7d5YQTTnD2Hn7wwQdJnxpCKLYxe8IA5w27kH6t39fLqaAIANnaZ212XL73Wev+wnXN2+jnCkSgqlUjq4RoL7nbb79dbr31VnnllVc+PqGqKuejFjL52te+5gR6mrYZtcLiKXqbek5h9bHT/Xzl7L///s7tjR8/3ug2mpqayl6+Zs0aGTp0qPN5Y2OjNDQ0GN0OvL9p6f4LTdVJy+b4DZu2y9rmrdK9vk66dCq/+ggA+LiP3ahrFvlqeaDZGzrRl7f+l3pfaXsIrSRaWHRGVz01QNY963m7T5BvTU1NTlX+sMfmiQZ2hZYuXSq33HKL/OY3v5EPP/xwd5BXXV3trHRddNFFcuaZZxr3xUsysNMVyrPOOssJrg4++GDZsWOHvPrqqzJv3rzdLRZ09fK+++5zmqX75QbDXhDYwbV241aZNX+5PPjyu7KtZdfu79fWVMuYo3vItHH9pHvnOu6wBBFwA3Zb+uYGmXjz07K94DW0lPY11blMydf7yEtv0J9PHORkwAB50JT1wM61detW+d3vfieXX365vPvuu3sELprGqKt4U6dODb1tQlSB3V//+ldnRa6UG2+80UlDVRr0vf7667Lvvvv6ug0CO/h125OrZMa9y6Tck1+fdTPO7C/nH9uHOzhGBNxANgOXGyYNymVQ5yfw1T3rBHfIg6Y8BHYaXN12223O/9WrVzvfa3t6GsTU1dXJf/zHf8i//Mu/WB/YefH1r39d5syZ43w+d+5cOe+883wdTyom/AZ1V97rvRrtTIK72BBwA+lNNfz98+84zce1T13hPmvdUzd+4MFWpBrGuVWAVFUg/sAu8VeZjz76SP73f/9XfvnLXzpFUzSQc4O5fv36OSmYkyZNcqpq3nzzzc5qnh7zr//6r04BkokTJ0raXXLJJbsDO70P/AZ27JmDn9UgXanzQ68/9ugepGVaEnDrq6N7PVZTATto0HbusEOd/7bts05qf5vepp/9h0qvrwGy3o8ALO9jV+ipp56Siy++eHclzEceeUR27drlpCFecMEF8vjjjzs97nRVrlu3bnLiiSc6e9J0b9rnPvc5J/jTdglZcNRRR+3+XKuGAlHRPXV+l+j1+rPnr4jojBAk4NbjANhFg7lu9bVWBHWaCqkFXqbd/fIeQZ3Sr/X7erleL2waSJod93HGFgDLAzutznj11VdL37595fOf/7yzArdx40YnSPu7v/s7+fnPf+5cR4uoHHvssUV/Rp8+fZwWAWrlypWSBRZlwyLjtFCK2XFrQj8XfIKAG0BU+9sqrZrp5Xq9MIM7XbVsG0h6pamsejwAi1MxTz/9dKcCpK7KuYGMFhU599xznT1mn/3sZz3/LHcv3JYtWyQL3FYPbgEVIKoKi4XVL/3Y2rLLOZ5WCDYG3ANDPx8A6abpl1rQxUvREqXX0+uH1YpBU1GDHm/DiieQNrEFdn/4wx92fz5q1CiZMmWK/P3f/71TCMWvDh06OD/DTzVIm2llTNfxxx+f6LkgG4rt8dA+dUHo8QR24SPgBpC1/W363pPk8UBexfbM0UInupdOA7pPf/rTgX6WrmrpnrykaeXMCy+80Pn8yiuvdHrWFdKCL7pn8Igjjigb1GlKqurRo4dMmDAh4rNGVlXaIH/8p7sF+vnavBzhI+AGYNP+tjACO51Q1Pcek3RMrSTKah1geWCnZT1rauyZgdHiLNozzrV+/frdn+v327Y70IIufj333HNOIDt69Gin8fiAAQOcXnwtLS2yYsUKp7XBQw89tLtBuQZ5HTt2lDywrWpYlvsouRvktY/SPu2qZMdO/3s662qqWa2LSNCAmYAbQNj728J4X9YJRX3v8X9c78C3DeRVbJGWTUGd0vYC2i+vmCeeeML5HzSwUzt37pSFCxc6/0vRYE9X7c4880zJsqRKLmed1wawGvRVG2Yvjzm6p9mBqEjTW2trqo32PxJwA7B1f5u+p1+7YKWvlFCdgNSefwDMMIqO0Lhx45yATVs7/PnPf5b33ntP3n//fad4TJcuXZyCMWPGjHGCxs6dO0veV5T0DeDnEwfJ0MO6JHKOedggv8ugAKvGgleM6+v/QHg25ugezt4Wvwi4Adi6v00navU93cvEo2pfUy03TBrEBC8QQFUrtfYzL6ru9mGvKLkv7HMvGkZw59G8p1cbpbr4cdX4/jJ5RJ9IbyPvtB/dsNkP++oxqAH301ecRON4AHsZe/1i4/1t86eOjG1it3ClToO6IX2Y2EU+NEU0Nk+sQTnywbTksh6H6DbI9+hc5wQG5ejlBHXx6N65Tmac2d/XMTPH9yeoA1CUbm8wEcX+Ns3C0TYKsycMcALHQvq1fl8vJ6gDgiMVE5kuuZxlQTbIv7txqzz2ryfItQ+95vRC0z51hfu2NMVP0y814EA8hYHOP/bjVdEZ9y4ru3JX9begjlVUAGnZ36Zpmfqerv8pngZEh8AOmS65nGVBN8jv275GrjtHm1sPdHqpadl9rbBIr7rkCgNpcDf26B4ye/4KAm4AmdzfphNeVMMGokFgh8yXXI5SkjOPYW6Q12Au7oAuK8Fk2IWBdJWUgBtAUPp6o3vW2d8G5AeBHTJfcjmrbRteevtDaVddJTsNSl0m1QBWi4TMmr9cHnz53T3K+2u5f60MOW1cv1Slf/ppNaHX81sYKImAG0B2uPvbdHuDZsLopGnh+4DuqdP0S1oNAdlAVcwcSKoqpq5m9Zv+oPHxy68aY1Vgp7/P4tfWyb/d9ZJsqFDdK+q2DX4qjRajm9ULU13jWD277clVnvaPaRERd7+ZzTTAH3XNIt97WHSQxSAKQBLY3wZke2zOih0io0GZrmKZlly2IagrtToXxepMVJVGS22Qj3P1TIO6K+9dVvF6GvS517M9uKMwEIC0YX8bkG20O0CmSy7r7OS65m3OR5NVMV2R0T1SfoPTKNs2mAQUbTfI/+65JqdvmqbnFAZ1Sr/W7+vlGpAFpQGkrtT5odfX47JaGAgAACBsrNghcyWXw9gDFzTVMcq2DaYBhe7HmzdlmLzyzsZYV890VdDvLkC9vlaG/LiIiH3yUBgIAACkCyt2iKXksq4UeRG05HK5VTa3QqFerteLKtUxytWZIAGFFlk5qL429tUzTfU0O26NZLkwEAAAQJgI7BBbyWVdiStHL9cVpSF9zPaluatslVYH3T1wpYK7IKmOpVZnwhI0IAiyemZCi7K0TfX0Spum6/E2CrPVBAAAQBgI7BBryWWtxqiFUQrp1/p9vdw0qPO7ylZuD5xpqmPUqzMaIG7dESxIXLRibayrZ40fbJEgtFKnzYWBTNhSGAgAAGQL08aIjaZX6n4z/R92yeWwKhQGSXWMYnXGpCpnKZ85qF5efa850OqZl1YIYZ6ztl+wle7X1NTepAoDAQAAFCKwQyZKLgepUFgY2IW99ynI6oymiuqqYlhpoaf1P8g4sHNXzyoFdmGec11NtdXNuU/pd5D8+90v+0pt1T59J/frLragpxUAANlBYIfUC7NCYdh7n0xXZ8Koytl2/+LZg3vJT/74emSrZ2Gf85ije4rNHlr+ntF+xYXL14ZeKTXuqrEAAMA+7LFD6oVZoTDI3qmw2jaEWZWzsNJoQ5cOTvPxKFbPwj5nXdm6YlxfsVka+9iFUTUWAADYicAOqRd2hULTpuphtW0Isypn20qjY47uEcnqWZjnrGaO7y/dO9dlepU4bmFVjY2a7uVcsWajtRVRAQCwFfk2SD13lc1koF1sD5ymov3o/16VDVt2GAdTGtSZVvgMoyqn/l6aBqorhoXB5bRx/eTe59/xvS+s0upZWJVEq/4W1E0eYd4QPS2rxHFWxjStGquVauNIy9Q+idqKQ3seFrbH0BVmnYzQx63NgT4AADYgsEMmhFmhcNk7G6VlV2towZQfQatyLr58tHTtVFsyaNDB8Ywz+8uVPpqUV1o9C7OS6KP/eoIcemBHsV3a+tiFVTU2Crc9uUpm3Lus6GSDBnl6DjoZoY/b84+1O+AHACBJBHbIBF1lu3bBSl+D12J74PwWAKmvbSfXfmWgfP6IbqGswARdCarbp3K1UXdwXGow7Xf1LMxKovu2r8nlKnHUwqoaG0VQ52WSQR+n7vUI7sJDVVQAyJZ0jKKACnSF7OcTB3kOyortgTMpALJPTTs59vCuoQ3U41oJ0sHx2KN7yOz5K5zm49qnrrBQiu6p0/RLL+lvYa4+xb2SlYc+dmFWjQ07/VInF/zQ6+vjlrRMc1RFBYDsSs8oCqhg6GFdZO5Fwyr2USu1B84kXW1DyOlqca4E6eD4unMGishAp1CF9qnTlgZ+e8cFOeekV7JsWCXO635A3VNn0i5CJyM+ftzCr3J9Jt2qqPqY1kkyfT0FYD9W3lGIqpjIFB2MaMGH2RMGOIFCIf1av6+XFytsYkv5etOqnEFWgjSY69uzs3FD8DAqica9khXWKrGu/kZdKTWL+wG1UIrZcWtCP5c8SEtVVADeVt7nPb1axl6/WPpNf1CGzFrofNSv9ft6OfKJFTtkjg6cdQVN/3udybIpXS0tK0FBz9mm8zcVdJU4r/sBdYW4sPqlH5o2rMebTkLkke1VUQF4x8o7ymHFDpmmg9Ju9aWrREbR5DwvK0FBztm2809qlTguSawCl6Npv0kenzdBqqICsAcr76iEwA6x0VWtdc3bQmnO7PVneW12bFu6mrsSpCs9fhqQJ8nrOdt6/mGsEs+fOlKWXzVGnpl2svNRv9bvJx206oqqn79L1KuoupczyePzxpY0cwDxr7yTlpkv6ZwiRy4rsHn9WSbNjm1MV3NXgnTWXAdYmvIZZs88P8qltBZeVu6cC8V9/nHS+8e2IjBhVI0Nk6ZR6vPRJB1Tq7aShuld0DTz9c3bpGt9rdHxAPLRjxT2qGptbfXfiRmp0tTUJL169XI+b2xslIaGhsTzwAtXBbxUYPP6szRQ+OUTqyr2ZyvW7Fg3HJuUr9dUuzheNOOufFUukD57UIO0VrXK/zz7dtkgu/CcVZznD/PnURz7Aafe+WejVD99bFEV0zvNbNDCCqYO6LCP3DhpMFUygYRpYRTTyWfNHkE+xuYEdjmQRGDnp9G3rg5oCl+p4M5v03CvZrYJ7jSQGXXNIt9FS7JUYMANxDR99Vu/eT5QMRRKpttJH+dhrgKbTjjoyvqw2Q/7anmgkzJPX3ESfex80L+PVssLotJrNAC7n8e6NYAJ1XyMzbMxGkXq88AvnfucLC4SIJk0DTdtdmxbulpcSq3MBeGWTGcwmI2qsVGkWOvzTlfOr/TRpHzm+P4EdT6F0WcyzCqZ9NwCstOPFPaheApCZ9ro+/qFr4Xys/w2O0570ZIgdDVUVyk1BTWsoM7Fxu3sVI31+phxm1zr5V76oJ09uJf866mf8bRSd9X4/jJ5xJ7p03EVa0q7MPpMBqmSSc8tINhrlm0F3mAv/tKwpgLbTYvfkJOPOmiPdB/Tn+Wv2fFAa4uWRCmqFNdCbNzOFn3MnDdniezY2Wq8Yltqta9z3T6yZXuLtOxq3aNQypije8oV4/p6WqkLs1hTlgTtM+nS10O/+4npuQUEf82yscAb7MQeuxyIc49d0DzwLh32kcXfOVH+umWHvL62Wc7/5TMStT/9+yllq+xlMXXIZD+hKX1T+d9/ODZz92Ge6OPlt880yvfnL5edBYGX3z2oXoq3aLEOrVx7Yt+DfFW/DLNYUxaFNZHjZ69OmHutgazx+5ple4E32DE2JxUTVuWBb9iyQ/pf+X9y3NV/jCWo89Ls2CRdzXZRpri2pSueGuxrZT79qJW99A2K3jrp4KZezrz/FV9BXdv0Pa+NdT/YskOuuOdleX3dJl/n6OVnuyuJXtJEs8ZNM9fAOY7XeHpuAeG+ZtnWjxR2IrBDqNKYx53HZsdRp7iW43cfFuwffFRK34tykE8A4S+4e+ifj5c4XuOD9NwCssz0NUvp6p2ubnuRlQJv8IfADqFy88DTIo/NjoM0LA5TnldP0iCsirS6YvvbZxsjG+QTQPijzcZNX6P97NUxnTzSiQAgy4K8ZuWtwBv8I7CDlRXY4qKFGfImaLpsmKicmY903Z8t+ktkg3wCiPheo7VwVNSTRzoRQCVTZFnQ1yy3wJvundPJlkL6tX5fLyeoyyfWZxE6zQP/r/971dkrYzMtoa7V9rxKQxEVL+doW7oslTOzn667btO2QIP8Uo/lMAIIL8/lNDz3o66S6WevDj23AIn0NSuMfqTIJrtGeMgEfcG5+kvHyMV3fJwTbisvzY7TUD7d7zmG0bA4bCZl1JH9dN1KjXWjDCDS8Nw3peete3X8VKz0s1eHnluAxPaapV8T0MFFKiYiMfLT3WK/Z3VG+WvH9XFW4sJodhxmI+aomJ6jbemyXtOvaDqdv3TdckFCVAFEGp77QUW5VyfIXus+B3ZgkIrMYtLjE7yfRyOd042wnr6xf+agenn1vebIb6tt0/BLjz9cZs9f4TQf31owG+2n2bHX/kvlGjGHpVSahek56krE9h27pF11le/y9VEqtXqS5ZUTW9mSrlupWEcUTXtteu5Hzd2ro0UZdNVcJ1hKva76pc9Nk55b65q3Oc95ntPIorw3Guf9PHo0KM+BOBuUFzJtpunVfd88To7oXl/2hW7Dpu1OnzptaeC1+qVJ8+62jZijfvE7pd9BTj84v+f4468MlH/+zfOx9bAL2viYptPJ0cdXkHTM9u2qZfvOYBU1vTTWDbNprw3P/SSFuVdH78uhsxbKZg8r8W3RUBlZltdG47yf74kG5Ugdk2aaXmk65YCG/SsOPjSY69uzs6+WBkmXT/eSBjb6vx4xOsev3fpM4KCuUqqriWIzkTSdTlaQdF193s+ecHSg299v3308FesIs2lv0s/9pOlzsFt9bSirAhromraSuf2pVYFvH7BVHhuN834eH/bYIfIN+l6bafpxyP77SlSSLJ/u9cXPZBZctQRIvdTga+aZ/eU///4YCVvbMuo0nU7n4EPTe6884yhnBevEvgcFuv1rv/xZT6tgfl9nyhUCoXVCuKt/jRs+Mjp2xbvNtDxAZoX5mpUGvJ/Hi8AOVmzQ96tun2geukn2XwqrIXSYNJB79F9PcAbrGhJeee8y+fbvXgz1NorNROZ95SStg487Lx4uFx532O7VmlrDSZ327arkpKMOirUQiI2919JcXCCM6n9AVuWp0XhU7+dpfn2MUjrDf2Rmg76p19dt9tyDyo8k+y+F2RA6LL984k35ycOvRXZepWYig6ycpHkPgsuWvkTu4EMnHMo9Bjq2b+cEgW0HH2OO7mEUbI8bcHDshUBs6b2WleIC7aqqEj0eyHPxIpuE+X6eldfHKOX7t0dsijXT3Lpjp4y8ZlHiAylbShGH2RA6LKve3xLZz9aZSA3q2gYDcTWdNmFSjMerMN6woggIdfChRXc0uCuVAqzf16I8GtwVVoicNq6f3Pv8O85qr1c6nNfKtSaCNO21oQx5ueIC7v5abSze9n620c7W1kSPB9Ig643Gw3w/z9LrY5QI7BA7t5lm0OXzKEqyJ1WK2KaG0FHr26Pe6SFYaibSlpUT19qNW2XW/OXy4MvvyraCNFlNM9QVKQ1eKrXPqETfsC6941nZsGWH7zesqGcw9dym3P6sUfl/vV9mnNnfSeH1aub4/oHvT5OmvUmXIc9amwUbAmUgTbLYaDys9/OsvT5GiT12SEyQJrZR9nMxrQbYtgCIH3nZT3Lz+YPlwW+NcmYnSwUbNg0Ib3tylQyb/bCTKlMY1Cn9Wr+vl+v1TGhQNuuB5fKVG58qGtQVe8MqbIoddSPtMDa9n39sH2evZqXEOr38qvH9naA/KUk897NaXMDtZWqi70Hl29gASIcw3s+z+PoYJQI7JCqpgZRtpYjzMDvd58AOclK/g1IT8GuwpitNlRLC3KIyfoM7DbY0FfmmxW94TlXUN6wLf7nUWUWMo3x0WJveNbh7+oqTnOdWbbviId4R3Ts5VTWTfDNOqgx5VosFTT7W7HV68rHJBfcAwhPG+3lWXx+jQmCHRNnYzyWJUsRBXvy80AFz0i4edXhqAn4NnGb4SB9Uen09zgs3KNtgUJRG97Od8F+PyJTbnol8BjPM8v+aXqkrtZ3q9il6zGtrNwVeYUxrGfKstlmw8fUdQLyCvp9n9fUxKgR2SJTfgdQ+7aqcgVR1VZW89l6zvND4V6egRdjlcJMoRRykIXSlc/zlhUMiaxYfxWAt6QGh7qnzW7pBrz97/oqK19PgT1fdgrS12LJ9p2zc2hLpDGbY5f/T0qA27ue+jW0WwpK3fl0Awn0/z/LrY1R49UTivJZUVzt2tjr7kdr22a6prpLT+vdw+q3poCCMYhJxlyLW89ICGWG1FmhbpEQHWF42H4fNZLDm93zDHhBqoRQTv3/+bRly2AElH2MarGhQZ9pgPig/7SDCLGJjukdCn39JDPLjfO7bViwoqdf3UlVyAaRbkPdznZjP8utjFKpaW6kpnHVNTU3Sq1cv5/PGxkZpaGgQG+ngL4xedx3at3NWNMoNIEzK4cZRithr5Scvnpl2snSrr93r53sZYHWqq5HVIbQ6CDpY83q+YQ4IdQX4777/UKCfUewxFubfNojlV43x9PjVx3u/6Q+Gcjvznl7tpFn6NXvCACv6Ekb53A/zfrZZqdf3LPXrAhDu+3mWXx+bIhqb8yoK6/q5aBGFIAPgckFdkHK4cZQi9rN6aVKQxetKhK54mgzEwx6sxbly4rYNuHnxm4F/VtvHmN8Vqyh5ncEMs/x/2hvOR/ncT7rNQlyy3q8LQPjv53l5fQwTgR2sEtcAOOlUL68vfjPvW7ZXmf2gL2heBlgmaaFdOraXu//xWKd5d5gvpnEMCL3MJAZ5jJlU9YqKnwqsmrpsEuAXFrGxueG8LcK4n9Mki/26AETzfp6318egKJ4Cq8Q5ALa5HK774jf9jKOMjvf6gqYvppqu2fZF1aTowY2TBknvAztGOmArdb5BeC3qEeQxZrpiFTa/M5gmm967dNhnjyI2Yewhy7qkiwUBQNy8vp/z+ugPgR2sEvcA2PZyuEm+oCVRGTSLK8S3P7XKeMUqbG0D/kpVY/0G+KplV6s88fr63T/TpobztqJ6JADw+hiG7L9jIjWCpGyZsj3VK+nqkHFXBs3iCvGKd5vFBm7A7+4l9Fo11g3wtW+elxYLep2L73huj5/5mR718qrB/RDXHgkb9nxRPRIAeH0MiqqYOZCWqpi6cjBk1sLYb7dY9UjbJFEd0tYBcJjGXr/YmtW0KGnAr6uqWgP50juelQ1bdpRNpbxh0uA9CgtpMDjymkVGDdVVx/btjFo8RFkV02+AGxeqRwJA9l8fmyIamxPY5UBaArugZW2zWA43qy9oNkjq8RamznU1Tg/HSoHa1X9/jNTVtJMLb3tGWnZWbr1e065KfjVl+O7gzrRdQRA6URFVcSOvEyUmbVHCnBTJ2kQKAIQl7a+PTbQ7QNYFKWtrKk3lcCkXHq60F+XQVbibLxjiPIaLBfw9O9eJVIms+XCrfP32j1MjvdLgT1Mvn/ruSc7jLu69r2GnFBfy2k/QtC1KmKuCVI8EAF4f/aB4Cqyig514by+d5XCjqA6ZN2kuylFYsMYN+OdPHemsPv9i0iCn9cSajVudoM6U7pX77bONoe991bTMpIrx+C2W47as0ONMAshR1yxyVjrb3n/6tX5fL9frAQAQBgI7pL4KpCnKheebu0KcJro6p/vONEWxWODz0tsfyjd//WfjvXBt/eKxN0Jf2ex1QAfnd9Dfxc/vllSxHJO2KF5baLirggR3AIAwpHfKGpnktwqkjaleSA/Txqdx6tejXm6/aFjFfQRRtG7QFb92VVUSphXvNcuEzx0SacP5UkxTSjXN1WsRF9NVwaj2EwIA8oMVO1jHLfut6WRRSHPfNSS/QqwFS7QgSVwmjejjKe02qtYNm7e3hL6y6a4CxplSHCSl1G2LYtOqIAAAbRHYwdrgbvHlo6XHfnVGx/fcry6RVC9kvzG0FixZ/J0Ti6YTJpkurGmTadn7msT+xqAppV6PD7IqCABAEOR9wOpB9z+deIRRqtw/nfjpRFK9kD6mjaH18dX2MfbFnz8ZWqERP+nCi1euk9Xvb5EodO1U66xsXrtgZSgrgklVog0aTFbFtCrI6xQAwBQrdshcqlzhKgfVI+E1uNOVXJOiHoWPsbBWtvykC+uerv/vzj9LVDRY/e0zjfKFz/b0FNzYWok2aLGc0657rGKRk7hWBQEAKIYVO2SqmApFURDksVZsFc7PCkrQlS2TZvO6p+uDMg3Kg9IVqJn3v5KJSrRBiuV46WsXdFUwzS04AADJY8UOqUmVq7RyR1EUhMV0pdediNinnf+1LS0W9D+XjnACSz/VEeNuHm7KhkmXoO1UKvW1C7IqmFSKKgAgOwjskPlUOSDux+oFxx7m+7gNPisjanBx6xNvhto8PCq2TLr4LZZjUsHSNB03qRRVAEB2kPeBXKXKAXF4/PX1kfZL071elYq92MAktdSWYjmmfyeTdNykU1QBANlgxzst4JMGcwR0sFHUlRE1qPO65zQJfXvUyx0eGqonHdz937dGyeBZC0P/O7EvGLAbE8PIMgI7AAhR0MqG6zdtk7p92hUNjDT9UleabA3q1Ip3m60O6lytIfydS/2Opi00AERDXzu10JTuSS6ceNM9sZo+rSvttmQVAEHwKAaAEAWtbDjymkUlBx06MLE9/bJS0GPLbHvUFSzdfcG6H09TN3WVz+YUVSCryqWua5CnlXI1fVr335aqeAukBe8oABAitzJiGEVN2g460lIBM+yy/VHMtgf5O3mtYMm+YCBZXlPXvbQzAdKAqpgAELKwGpW3HXSkoQJm2GX7dWA26ppFToDb9vd3A1+9vFLz8KQrWJq20ABgxm/qeqV2JkAaENgBgGX90oqxeV9dVGX73dn2SumnbuDrN7gz+TtRwRJIB5PU9UrtTADbEdgBgIX90sL2tWP7GDVOTyroiWO23e/fyYYm6wC8MU1d1z2xQFrZM+oAgAxxKyOGvXJnQs9h+pn9Zd6U4ZGdT9hBT1yz7V7/TrY0WQcQT9sZII0I7AAgIm5lxNkTBjh7z5LywZbtzkpWVOcTRdAT52x7uftFv9bv6+UEdUA+2s4EPR5ICvkkABChYpURt+7YuUdbg6jtahX53XNNcv6xfZyvW51/wR3UuVamnnRk6GX7o27yXgwVLIHsiLqdCWArHrkAEBMNNvR/Emk+855e7ZT3r9Q024/1m7bLEd07eQ7qvPagC2O2PUj1SffvBCCd4mhnAtiIwA4AUtzrzquV722S8+YskR07w1ir+9jOXa0Vez+Z9KBjth1AUJ8/oqvRa2zbyr5eJ6QAGxDYAUACNKjRHmxxCjOoa1uNUvegtQ3QtP1AqRXCts3XCwNDZtvBYBpB6GvPrU++aVzZ12RCCrABxVMAICO97pJSrBpl0B50cTYPhx10MK0pw2OvXyz9pj8oQ2YtdD7q1/p9GkfD6+NIJ5T8TmS5lX2XvbNRRl2zyJl4arvi505I6eV++2YCcchtYLd27Vq5//77Zfr06TJ27Fjp2rWrVFVVOf8vuOCCSG7zzjvvlNNOO0169uwpdXV10qdPH5k0aZIsWbIkktsDYC8be90FUViNMowedDQPzxcdJDOYRlKtUtQFI/pIa6sEmpACkpaNEYWBgw46SM444wz5j//4D3nwwQfl/fffj+y2tm7d6tzWV7/6VVmwYIG8++67sm3bNlm9erXMnTtXjjvuOOc8AOSLTb3ugnKrUWpwdsXdLwXuQZfm5uF6P6xr3kYvLI+Cru4CYbRKeey1dYEnpICk5TawK9SrVy859dRTI/v5F110kbM6qEaPHi333HOPLF26VG6++WY5/PDDZdeuXc7K4Zw5cyI7BwB2KtdDrV11laTJ4tfWOasufpuEl+pBl6bm4aQRmt9vDKZhQ6uUFe82B56QApJW1dqqC8/5c+WVV8qQIUOc/7p6t2rVKjnssMOcy84//3y59dZbQ7mdRx99VE444QTnc121u/vuu6Vdu0+qKq1fv14GDRokb731lhxwwAHyxhtvyP777y9hampqcoJX1djYKA0NDaH+fADRFI146e0PnRUKrzPIxWhwqNUr47BPu6rABVqWXzVmr8pzOvjXwZMGfroy6NJAWPfUhd1Hz69yRWIKg8+2RWLwcRsOkyJCOhGivSGBQrpSrnsz46SvQ/OnjuQPASvG5snnrCRk5syZsdzONddc43zUYO5nP/vZHkGd0r19V199tZOm+cEHHzireJdddlks5wbAPoU91NwVK9Pec7reF1dQpwFkGFU3i/Wgi6p5eBg/y00jrBR8u2mE5VpD5JFp2pwG+QR2sKGxuJuGTisE2IBUzAht2rRJHn74YefzU045pWQ0/sUvflE6d/44Beuuu+6K8pQAZChVs2+PeqfISN+D6vf4fp8DOziBVpzpGGEFkJUGZjp46lZfazyICjNlkjTC5NLm3ME0UMhtlRI3nSACbJDbFbs46D46LZKijj/++JLXa9++vQwfPtwprKLH7NixQ/bZZ58YzxSAzbysWLnf11W60657LLaVujDTPTVwjXLW27SvXpjV99w9Oaw2BR8MF1vdBZLoEZrESiFQDCt2EVq+fPnuz/v27Vv2uu7lLS0t8tprr/nO0y33f82aNYa/AQDblFqxcr//f6+8a5S2WaimXZWzX85rNcqwgsgoe9BFUXkxSBohlTODD4YZTKMY01Ypn2mT+RDHhBSvAwgbUwwR0s2QrkqbIt0NlO5xRx11lOfbKTwWQL6ZBhuFAxxtG6BltbwUBPnhl46Rr9/+rASlYeTJ/bpLFExTJjUFtlRRlqBphJr+6dLUMV1l0AGpDe0a4k6bM7kfo17dRXq5rVK8Fp5yW6WsfK/ZaKXP74SUvh7par++Vhc+9vP6OoBwsWIXoebm5t2fd+rUqex1O3bsuMfePOQPM3cI4zFkGmyoGWf0d4IZbRtQbm+ffq3f18s/f0TXUP5wuuY3a/7ySHpCBUmZjGNPjZsGqq0ikuzRlsRrkA5kbVvdRfqZtEoxXenTqrxe6fNbn+f6fG/7Wm3L6wDSjSmBCGlj8sJ9dOXU1tbu/vyjjz4yXhksRlMxhw4dKmkVZhU82zBzhzAFDTZOP6bnHjPFXqtRmq66tKWB1OOvrQ+9LUAUlRejSANMonJm0q9B+vN1X6OfwNvvYBr55E5OeW2VYrrS5/X5QQVdxIHALkJ1dXW7P9++vfyblltkRe27776+bieLfenCHGzYGhiaFHKw9XdB9vcsFbZhiLJYQdjBTRiVF4v93kHSCIOmgdpaTMZE1INp5JvfVileW8y4Keu60pdUOjhQDI+WCNXX13tOr9y8ebPntM2sC2OwkfQsdNgzd+eP6C2Pv/6+lb8L7JHUniWTVZe4BjVRVl6MqvpeHJUzbVo9iGowDXidnAqy0ucFFXQRF/bYRahwJU2rU3pNp8xzMZQwKtfZnsNuMnN30+I3rfxdYJ8k9iy5qy66mhKWSnvcvO4Ni3IV02RPjlc6oIyKjf33vO7pJKhDnCt986eOlOVXjZFnpp3sfNSv9ft+J5yCpIMDfjDNH6HCypYrVqwoe1338pqaGjniiCMkj8JIVbBpFjrMmTtbfxfYJ6k9S15XXcLa4+Z1VT7KVUy/aYRhpYEGZevqgd+0OcCmlb6408GBYlixi9CQIUN2F0159NFHS15P998tWbJkr2PyJmjlOhtnoaMoR2/T7wL7+F09C3PPkrvqElZhC3dQ03ZVzu+qfNBVzHIrgl6r75kIs/Jm2lYPSvVrBNImjHRwwCsCu4j32J100knO5wsXLiyZjnnXXXfJxo0fD04mTJggeRV0sBFFSXPbytHb9LsgW6W+w6IB4vdOP0oO6LBPKD/v9qdWydjrFzt934bMWuh8/MqNT/lK1zZJmezSYR/ZtmPnXretX897evUekyjl0giDiKLyZhirB3lHaxr4EWU6ONAWgV0At956q1RVVTn/Z8yYUfQ63/72t52PLS0t8o1vfEN27tzzTXH9+vXyne98x/l8//33lylTpkgehTHYMA0M73hqlcQl6pk38vGR1J4lDXQ04NHAZ/CshfLBlh2h/Nwf/GHFXq8N2vPOz0q2+vFXBkq7am2DXllNuypp2dUqM+9/xfPe1lJ7cjQN1ERUDbhZPQj++K4U6AOF3HRwm14HkF25nQZ4/PHH5fXXX98jwHLp9zVoK3TBBRcY3c6JJ54o55xzjtx5551y7733yimnnCLf+ta35OCDD5aXXnpJZs2aJW+99XFA8sMf/lAOOOAAyaOgg431m7YZB4bL322W0657TCaP6B15hcmoZ97Ix0cSe5bKVbJNmp7TdQtfk7v+1CQ7d1UOCTvX1chHO3bKxq0txntbC/fkmFbOjKoBN6sH6WwLgXSz7XUA2ZXbwG7OnDly2223Fb3siSeecP6HEdipW265xUm1nD9/vixatMj5X6i6ulq+973vySWXXCJ5lXSqwavvNsfy5hxV7yuv5dmRX0ELAJTitWBRkuYsfsPTKp+u6On1duxsDa0tg20NuJNqiZFWaSjIBfvZ9jqA7CIVMwbacPyBBx6QefPmOSt23bt3dwqkaFuDc88911k9LJXKmRdBUxW6dqoN5TzKtVEIa3+FaSGHtATJyA+/BYuS4jV1U1f0mius1Pnd25pkMRubWmKkUVoKcsF+Nr4OIJtyG9hpqmVra6vn/8XoKp57uZfATIO4BQsWyHvvvSfbtm1zUjA12BsxYkQEv2H6BBlsBAkMvbw5h7W/QoPBzx/R1SnMEIXCGXU2+CNtrTvSqtLe1iSL2RRjUkwmj6sHaSjIZSvef+x/HUA2VbWWilqQGVqN0216ro3QCxun20SDIy1I4DdVwU2D0gDLJIe9FC0uoXuTvOwf0vMolcJZqt+WlnEI+8l35RlHOTN9lXp7AWHQiY0o04rTRAulVEpT1NcCHfRrIKj7YQsnZHSCSgOnuJ6fflNo92lXJeMG9JRp4/pJ9851kgemj2/9e2oRnbzx2lsy72x6HUD2xuYEdjmQlsDO72BDA5jCWS2TwLAcfZGdcWZ/X+fTdn9FnEUltOhDTbtq2WAYgAJ+Z+R11Rof0yqY2nfNz/2XdANuk9cnnZDS18Xzj+0jWRb08e0l0M+SoBOgeWXD6wCyNTbPbSomspeq4DeHvRKdSbs0wP4KN0j1MmiqKhJUXjzyU84sudfy7FrJr1xQ53UPIeBlMLL6/c3cUQH2ttrQgLuwJcZBnb0FpZplcOW9y+S2J+NrE5ME2kJ45/W9jvcfO18HkC0EdshU/y2vgaFXlQKlUvsr/G6618FSl47t5dF/PcGZ6dU0nitO7yfzpgyv+Lvofr0O+7TzXcmPDf7wo+0+0zHXL+YOzEC1SJ0QO7lfd1m7cZuv42bcu0zWbtwqWUVbCG8oMAPYhSReZK7/lhsYaoClzce1T12cNG++VVp9p19qEPnE6+87v3Ox36VUPv62HTudRsomAWjhbQFp7FNng0rVIjds2i5rm7dK9/o66dIpnEmnMM2av9z3fl+9/uz5K+S6cwZKFtEWIvoCM7z/AOEjsEMm+28VBobafFz71MVFg69bDdOUbn9q1V5vdpWCXF1BMaGBIm+syEKfuiSVqhapq1kaMD348ruyreC+q62pljFH97CqCImeo9lxa0Qkm4Gdoql0ZVooxQTvP0A0SMVE5k0eEX/vpdfe22R03Ip3m8v2x2ubj6/XNa1KqAGoaS8+5ENa+tSFqb62nee9raV6Ten+s2GzH3ZWJQqDOqVf6/f1chv2qelqYttz9Gpryy7n+KyiLUR5vP8A9iGwQ+aZvDlH1Wcu7E37bPBHlPLWp07DuVsuHOppb2upXlMarGlxkdaUFCHRFNEkj7cZTaXL4/0HsA+BHTLP5M35xsmDjRuef+agegmiXZW31QLFBn/YmGaVVl8f9SknUDMt4KTpl1pUJE1FSHTfX5LH246m0qXx/gPYhz12yAX3zblSAYgDOuwjP/3q55wBm+n+ii/+3SHygz+sMD7Xna1hty0vbcLPnpBJI3rTOBahplkV6tejPvYCRia0Ku3Ukz4dqIBTGouQaDEX3fdnko5ZV1NtZTGYsHkpYpXHptIUmAHsk69XIeRauTdnd2DzwZYdMvHmpc5q3dmDGpyUzA1bdni+jY7t28nYo3sECuz8zIIGTYXRPX0avF67YCWNYxHqY+vBqSOl94EdncHfMTP+TzZuDfbzouSs0hfZK+e3gFNai5BoMRd9XfR/XE/JiyCVmrOMAjOAXUjFRK64b87aJ+6Orw11VuhU29lqXanQFgItu1qd5t9ebd6+Uyb87EnpdcC+RufX96B6XwOFoKkwLhrHIuzHlhvUqX8cfbi1d3CpvXJ5KkKiFTq9v8p9TK9/xbi+kkc0lf4EBWYAuxDYIbcl3C+6/Vlnha4cXWXQAUznuhpfQdKaD832zEw+to9RKkwYaFyOsB5bbRt2TxreRzpEuLKhz0+vlSy97JXLWxESbbsw48z+vo6ZOb6/Ne0akBwKzAB2IbBD7vgt4b5jZ6u0q67yNTDVlb6qkPpheUmFCYvbOBYI8thq27BbB3+3XjhU2nl8x6muEl8tB26+YIinSpaaWn3T5EGy/Koxzqq9rt6HtS8q7UVIzj+2j8w8s3/F1y29/Krx/WXyCH+TUMguCswA9iCwQ+6YlHDXlb0tPnu+aVEEDQiD9MOKKhWmHN1/CJg+tkpNUOjg79dfHyEH7Fv+Ma6X/+aSEb5bDnipZLn4OyfKKUf1iGRflFuExIQtRUg0uHv6ipOcv7ueUyH9Wr+vlxPUoS3TSrIAwlXV2hpjCT4koqmpSXr16uV83tjYKA0NDbn+S4y9fnEo1f686HNgB2ne2lI2kNTBqQZ17htepY35xS7X1NKJNz8dWiNpXdHIe1EAiO/Hlk5QVNqvpivmXqsL+rluW0kUuJh655+NVrw1YEqqKmY5uu9PU0R1NdGGwBPpQYEZIJmxOYFdDhDY7flm02/6g7He/89OO1kWvPJe2cGpu5KofcMKg07d46TpcKf0O0geWv5eyct1YLjsnY0V2zl49cy0k6VbfW3gn4PsBHeVHlttJyjCHvylYaCo/eiGzX7YV8sDXdPXVTD2qwFAfjQR2MG2B08arWveJkNmLYz1Nn8xaZCc2r9H2dW2SoNmHfyVGyzqoFqbsPc/uLOzYnDDo6/LWxs+Mj5nVuzQVpDVszy57clVcqWPJuXsV0MU0jARAuRZU0Rjc96FkSthtQfw4xu/+pOzX0j3ILTth+U1za3VY7sCbcJ+RPdO8u7GbYEaSjMQQFv08fK+T03NuHdZ2edt1d8qS7JfLT1sD5Z08qVc5odmdjD5AmQbqZg5wIpdcnvsClfUdON44ZuqvgmPumZRKKmThVX/pKpKNgT8mT32q5NLRn5Kzh7Si4EAYJiWOXv+Cqf5uPapKyxCoo29tQcc6Zf2S0uw5DVdWjM7dJIRQLJIxYR1D560zrbe/+I7MvO+V2K/fa0KpuXVXfOeXi3T7n5ZbKb9weacP4SBABAARUjSKS3Bkt8CR5rZQXAHZHNsTrsDZH62VQMoXaXToim6v06DOq9tCApXwroEbCnw04dfc87HpTPAttMG7efNWeIMHACY0YqSfXt2prJkirjBUqWMCjcNPqnXSL99WfV6ev3C9yIA2UFgh8zSN1pNddRVsbaplzt3ea9bpzOcN04eLDdMHOR8bmrNxq0y8ppFznmtb94WezqoKW3QfikDAQA5kaZgyaQvq17fpC0HAPsR2CHXs62VtG2A/N9f/Vygn6d733QF7IT/WiRpoufNQAC2p1pr1Vv9COQlWDLN/NDqtgCyJ/kdv0DCs61KUzMLV/FKlXAf+eluoayA7diZvsGnDgQK9wgCSUtLYQukS5BgKc7XSJ3EMM380JYleryN1T0BmOMdD5ljMtuqQd3MM/vLuAE9y5ay1u/3PrCDrH5/i+QNAwGkpbCFDnY1BfvaBSsTL2yBdElTsKTFwIIeT2AHZAupmMgc09nW3zzTKN3qa8u+0elg8u0PzBt/p13QgQSQp8IWSJ8wgqW09GVNoq8rgGgR2CFTwphtrZTi2eKj8ErW+KslCuS7sAXSJ03Bkk5CatqxCd1uwGodkD0EdsiUKGdbTVI8s+bUHz8qC5a9WzQApngF4pCmwhZIn7QFS7qX1Oy43qGfC4DksQ6PVDcbb7sfLuhsabuq0mtSNved67BPtWzZ4b1YjKkNW3bIxXc853yug58vDz5Eqlqr5LfPNVG8ArFIS2ELpJcGS7pHMw3BkhYI0r2kfiY7tNqzFgYDkD0EdshcBTz92jQd8+++/1DRinpBUjzj0NClg6x8b1Ost6n3x1X3Fb9PKF6BvBe2QHqlKVjS9ygtEKR7Sb2kJ2sv1hsmDaJaLJBRpGIi9c3G3SBCL3eKKhimppT6eWkoGqJBXd8e9WIbv8UrNmzaLivWbHQ+AkkUtrA9pZjnSHzBkgZBXiQdLGnV17kXDXOCS699WQFkEyt2SE0FvEqzkW4QMWfyYOcNLOh+OPfn6RvmgEP2E9tN+Nwh8oM/rBDbuMUrHrt89B4DHzed9qPtLfKjh1bKgy+/K9sK/sY6WDq130Ey/YyjpHvnuoTOHnkobGF7P7y1G7fKrPnL93qO1NZUy5ije8i0cf14jkQULJVqqeHS9xoN6pIOlvR89TVW95Jq2rGuUFfqywoge6paW1vzW+IvJ5qamqRXr17O542NjdLQ0CBpoQMuXTnzmxLz468MlCm3P+urSXm5n6dvmH9/w1NWp2M+O+1kOe26x6wt8DJ7wgBnYFFsAF3JF47pKVd/6RgGJZCx1y82eh7q4Hb+1JG++uEVvgYk1Q/vtidXyYx7l0m5N2rdGTzjzP5y/rF9YjyzfND3oDQGS6X2oQPI9ticwC4H0hzYzXt6tdEmdg0ijujeqeKAzc/Pa5VWo3Mp1LmuRrbs2CktO8OdT3EHrV5XN5PQu0sHZ6Bh+vfo0L6d3HrhUJpN51yQ14S2xVP8PF90BVlXcOIM7jSou/LeZZ6vP5PgLlIESwBsH5uzxw6ZrYDnpqbogE4Dn2DnsdpJx6q0h6Gcju3bycJ/OV5+NWV4oJ9Trhqb170WSVi9YUugIHvL9p1y7k1P0Ww650yeh8UKW9jeD0/TL3Wlzg+9vh6HaOjKV7f6WlbAAFiLwA6ZroCnKTI6S6+rWX/691OMz0V/XnVVla8N9W1t3r5TFi5fG2rAWWzQGvbPt4mOwQsH17YXuoC9hS1s74ene+r8ruvr9WfPt2+fLQAgHvYlhgMhVsAr3FuwM+B2Uv157orYV29aIjt3tRr30nIDTv2vQcni19bJv931kmzwOdAsNWht+/PP/O/H5bW18bZDiIoOrq+4+yWnEqiNhS6QjsIWtvfD00IpZsetEZGBoZ8PAMB+rNghNxXwwvp5WiHTJKgrXEkspMHnqf17yGKfq2xeS1frz7/guGwVVdBVk0ptL5Aufldfy61M69f6fb282PMjjGyAqFsaFFa/9GNryy7ahQBATjGtDWtpQGLabFwHdm0rgYX188JeSSy1yra2eas88uo6+c0zjYGrsZk03E2rwjYVSVQxhHdB2wy0fc54rQIY1XM4LPrcD3p8l0727bMFAESLwA5W08GdSQU8t5hIFD8vql5ahXTQ2PvAjnL+sfq/T+BqbO6+JFsrZsbVOw/2KNdmwF191ckIr20G9Hnh9bkRx3M4iO71dYkeDwBIJ1IxkYsKeEF+nvaIajhg371W/kwUW0mMqxqbuy+pS4d9JA/iLHQBf9w2A5VWkN3V17BTa5N4Dvuhq23afNxEXU11LKt1FC4CAPsQ2CEXFfBMf57S3XTa7LxwcKkrfyZKrSTGRYO7xd85Ub4+8lNOwJp1WugCdrGlzYDtz+ExR/cwPK6nREX/BtpHUJvE95v+oAyZtdD5qF/r9+NqBQEAKI7ADtbz2pvNazER/XlzJg/2Fdi0HVyGvZIYJw1up53eT35zyQjpYmG/uzDFUegC/tjSZsD25/C0cf18T77o9a8Y1zeS89GJLS1MpCmyfgoXsbIHAPEhsEMqBKmAV0zjB1t894gqHFyGvZKY2Ord5aPlu2OjGQjaImihDIQrSJuBMNn+HO7euU5mnNnf1zEzx/d3jks6dfaxletY2QOABFS1tgZs7gXrNTU1Sa9evZzPGxsbpaGhQdIuaDERTR0yrY6pzc69FIDw0kvLlvtS06myavlVYyLfE4V4HmtR/C1tfw7f9uQqmXHvsrITUVV/C+omj+gT+uuqZinoSpyfVVY9n3Lnq/en16I4AJBFTRGNze1ZPgB88FMBL4oeVu5tuyuJupKnKwpB2xIkIUgbCNv161FPUGcRG9sM2P4c1qq4Y4/uIbPnr3Caj2ufusJCKbqnTtMvTVfqKrWc2L5jl+/U2UqzxbQkAYBosGKXA1lcsQtCmyDrpn9Tz0w72alQGcVKYlK08IFJG4g46OD60wd1Mt5j5bUnGvK5Ype257A2L9c+ddrSIGj1Sy+rle2qq2TnrmgSe3TljpYkAPKoKaKxOXvskDtBe1C1q6qKtC1BEkwKScThT/9+ipP6qnsoTc+vXGEHxEufF5/pUW9tm4E0PIc1mOvbs3MoQZ2XfXNRBXWKliQAEC4CO+ROkB5W6u++/1DmynubtIGIw7OrN4R2flH1RIN3et83bdiSylYheW45ESVakgBAeOwaxQExMe1hleVVIK9tJeL0zV//eff9G8b5RdUTDd5XiDYbtJ+wpVVInltORCWLLUlo8QAgKQR2yKWwUg+ztgpUqa3ElWccJQd1Lr6/MAqFgZgOlg7r2lH+71ujip6fV6R/pWuFyMZWIXltORGVLLQkoXk7ABtQPCUHKJ5SfgUhjHSkrBYBaFtIIqnWCD32q5N3P9y6V0GUW59YJa+t3RS4bQXsLM7TsX07ufVrQ61tFZJGNrY3SXtLEq8tM2jxAMBF8RTA4tTDrK4CtS0kkdTMemFQV5gKaxLUZTX9K4srRL0O6EBQl/HVsbiK4kTFb/P2rGR3ALATqZjItXKph37loQhA0IqiNrFtgJtVQfpGrnivOTMBuC37rmx7Dqe5KI7fFGP2+AKIml2v8EACNH3y3GGHOv+1R5RWvQyjeXkWZamZuW0D3KyysSl5XCo1/06it2KQ53ClnnbaCKY1R0VxTIrQuNkd+n4DAGFjxQ4osLO11cpVIFtm+8OoKGqDtKd/5SmALnW8TsKsWLPR+WgjTbnTqrmaMtw2iEq6qq7pc/jfT+9XsrCSfv+2rw313JIkC0VxTFOM85DdASAZ6X1FBVI0CI1jtr9toZMwFPuZervXLlhpTbn0vKV/pU2QFaK2AfjajVtl1vzl8uDL78q2gvS32ppqGXN0D5k2rp9071wnaSnM5O670r2+mhYeF5PnsK6unT241+4Mh1KvN/q7eCkkokFdmoviBEkxzkN2B4BkENgBBXa1tkqPznXy7sY9i3XEvQpUrsqaO9uvA7Mff2WgNH6wJdRULy8BpVZ3C6uiaNzSnv6VRvq4MamKWRiA3/bkKplx77KiqX4a5Gl6273PvyMzzuwv5x/bR9K27yrOqrp6O/ocPm/OEtmxs9VodU1f64q93rn7lvXvoStTGsQUvkbq31Sff2leqct7ijEAe6X7lRWIuWR1HKtAfmb7J9+ytOhlhcFf2xLb5Vb2vAaU+jN1Zv6rNy0pu+fGNllI/0oj0xUiNwDXoO7Ke5dVPEYfie71/AR3Ya52p2nf1b77tJMdO8sHKJ3rauTmC4b4Wl0r3LccRSaBDWzK7rCBn79zVh8TgA2y9coCJNTTLoxVIH2zW9u8VS41bORcLtVrzuTBFVf2lr2z0Xf62NSTjpBrH3pN0qAw/YuBRbzcFSKvz7HCAFzTL3Wlzg+9/tije5RNy4yqsEmQfVdxBXZ+Xu+2tuySIFuPS63spZ3+Tm37a3rVc7+6TNwnfp5DNhYSArKIBuU5QIPy8vQNR4sYmK7U6SB03pRhRvtFSr3Zha1StboO7dvJ1h07xc/im87k79i5Sz7aYXc6ppv+dXK/7vLQ8vcYWKSgkXPh/qupd/7ZqEekDhSvO2dgrA2lgzb/jqNRt8nrnd4XcaaKpsXw2Q8bpe1rYPfUd0+SNPPzHFI0cAfiGZvzKo3cM0mdCqMIQNDUTz8qxWtbDKptbtwaTQVQHfSsMZgFL+XGSYNk1frNMub6xbLBQ4ppnEUs8sZk/5UWSjHx4MtrRGRgrIVN0rDvKk2pojbTIN4kqFP6+pbm4il+nkO6j1Pff1oq7OVMqpAQkDUEdsg909QpDUAW/svxRrPYQVM/s6Zfj3q5/aJhzp4LLWATZAW1rZHXLPJ0PQYW8fCz/0pbGRRWv/RDUwj1+C6d2sdW2CQN+67SkCqaBmkI4qPg9znkpThPkoWEgKyhjx1yLUjJap11ra7SJMdo3xjzYPm7zbsH93qf/uCLA2Sfdv7v26DcgYX+jRA9/Xt3q68tOcDVPadBtD0+yGqVn9YOtvZWDKNEP9ITxNuW4RL28w3A3gjskGthzLra9saYVrc/tUrGXr/Y2aN08R3POTO9BnFzYAws7NG9vi7U4+NoKG3a/DuO3opJvN5lle1BfFRMn0P+boMG7oApAjvkWhKzrnG8MabRD/6wYq/VhCDV+IJgYGEHTaPU5uMm6mqq90jDjGu1Sou26N5bG3sr5nWVKSo2B/FRCPIc8oPVYcAcgR1yLe5Z17jeGBEMAwt7jDm6h+FxPUNdbVr82jpfrR20Wq5tvRXzusoUFZuD+CjEuWLL6jBghsAOuRfnrCtvVunB38oO08b1c9p1+KHXv2Jc31BXm/7trpc8773Uqn5a3a/SoF8vN22VYipvq0xRsjmIj0KcK7asDgNmCOyQSrryta55Wyib+eOcdeXNKrjqmPbd8beygzYZn3Fmf1/HzBzff6/m5EFWq5S2yvjts42er6/B3R+mjnReJ9qmk+rX+n29PM6gLo+rTFGzOYgPW9DnkFesDgPmCOyQGjpbPu/p1bsLbAyZtdD5qF/r900rGcY56xrXG2OWHXlQvcw4o78c2b1TZLfBwMIu5x/bR2ae2b/iyp1eftX4/jJ5RJ9QV6tc339gudOqxAu9nvZO1Ap/bVs26Nf6fb3c688LS95WmeLszzh7wgDntaOQfq3f18vTHNSF9RzydhusDgOmqlpbkypPgLR3t4+Tl2beOiMapMG019swbUju0iBUG2Kbchs5Nxywr/zzb54ve7460M3iE3z5VWOcIFlXbNdv2ua5V51XOhCjZ1f8KvW1W7txq8yev8JpPq596goLpeieOk2/bLtSV0gnf0Ze/UfZsGWH8TlqG455U4aXfZ3R1xJtzOylh5eXnxeFuF7v8qjS4zjN9DkUZp/RYo85+tghD5oiGpsT2OVA2gM7P828dXZZ02JMB0n6pqUz6VoVUQtotA2mNB0p6Mx10DdGXfHTWVNNqVLlzleDvym3P5u5nnmP/usJ0vvAjru/1lXbsIrSMLCIlz4ftAWIVost/BsWPs6LPee0+bj2qdOWBoXVLytZsOxdp51GEF067COLv3Ni0fPS32fEDx6WjVu9ZxB0rquRp757UuyrYnG83iF7/Lwn68SFTm+0eJjk0PfvtKerAl4R2CGXgZ1JEBTWwDzKWVc/b4xeVyhLna+Xmfm06aIrCQW/e9BVUBcDi+ytxLelzxNN4Q6q53518s0Tj9gr8Pzl42/KzPtf8f3zrjzjKLnwuMMkKVleZUKyK76aF8bqMLAnAjvkMrAzHbCnIZUujIDL6wplqZn5Pgd2cIrQbA6hCE3cCn/3MNKDNFi8kbSzTK7El1sZDKpt4Dn8Bw/Lux9uNQoUddUOSAs/K76sDgN7IrBDLgM70xQ7fWOZP3Wk2K7Um50fflco287MV3rDve3JVfLqe81io8Lf3XQVVPchfn3Up2TqSZ8m7SyjK/FRr1q7geeAQ/YLtBro7h0F0sbPii+rw4BENjYneR7WCtLM220wbfsgSQepurKo//V8b39qlfzgDyt8/QwdrGpg5nWFUu+Twvul7Tm0fXNuldZQ0hyjoL/7/zzbJKcf09MZVOvg2s8AXvdK3Th5sBx98H7O711dVWX9YyYLdOXMb5Dl93EeZtpzJfqz9XH3q68PC/RztBBQry4dQjsvIC5t31fCui4AfwjskNkG0Xp8mt489Fzvef4do2N1tS2M1NNib7i6h+jqP6zwVQwiTjPuW+b8dwtufHP0Ec4ynAZ8pVZBdTXyy4MbnJKh37vnZVnxbrPnoh0ITtMh43ic68qgBlxxFA/SwHPhK2sjvx0AAEph1AJrBW0QnbYG07auUC57Z6N8tCMde/D0/tPCFe6+J13Fc1cglfv5M6s+Ts0rtrdQf4auUF67YGWoRTsQ/+PcZGUwiPtfNJuYcXXtVBvauQAA8ocG5bCWDt4+06Pe6Ni+PepTtVoX1gplMToQ1gIp+tEvd8XDSz8um+hgXtPvXnr7Q+lWX7tHUPfbZxtl8i1LKxaMcX9G3A2ksy6qx3mYK4Omlr/bLAf97fFmUjwlba9ZAAC7pGtJA7mjAdqrBWly3o/rLHleoTTtDZb0ikeYNP3uwl8ulYYuHYweQ+7P0MCWhrnpW4kPsjIYxHkjDpVrF7zm+7iLR30qkvMBAOQHK3aw2oo1ZgPyFQkM6ILS2XoNvEzonjF3tl9XmLTioKYTth3YummGermXlai4VzzCpqtypkFd26IdsOtxXo5ObGghoiScO6S303DcD73+2YM/ro4GAIApAjtYS2fcTcvsr3iv2Sj1MGm6mmZ2XO89KgBWWmXzkmaY1IqHjX7x2F+SPoVMCfo4L8ed2PBbXTYMGnh2ra+VOecPkZp22kijMr3ezRcMoVAPACAwAjtYK869OLbQFEkt/OGHXl8bwfqtAOimGepxWbn/orLq/S2yvnlb0qeRGUEe5+V4ndiIiht4asGdX00Z7rTTKEcv//XXh8uQPhToAQAER2AHa+WtKqbSfW9aiVEbHnuh17th0iCn/5qWgjftDZaV+y9K//unpqRPITNMH+fl9oXG2drAS+Cpwd3i75wosycMcFbyCunX+n29nKAOABAWRm6wfi+OSTpgu+oqpyJiGkvV6zl7abTdpWN7+dLfHSLTf78sUMpkqd5gQe7/LLr7z2/LJccfnvRpZIbXx7kGTBrUVQqAkiz0Uyrw1K/1uaX/NbXZrcya5+qX3A8AEB0CO1i/F0eLffi1c1erk5KlA8e0BndaiVFX0zTwKmy0rbP9nz+iq/zuuUa5afGbgW+rXG8w0/s/i7SJeVS9AvOq0uNcUxt1FcxLBdekCv14DTz1cZPXx05YVXqjQKAJIEuqWltb09WgKgJvvfWW/OQnP5EHHnjA+by2tlaOOOIIOfvss+Uf//EfpUOHDsY/e8aMGTJz5kxP1120aJGccMIJErampibp1evjimuNjY3S0NAgaRoQaCEE05l4HXSZlqq36Q2/8Fx0JVKD1jBTzp6ZdvLufm9h3v9hqq4S2ZXwq1Wp+wnhMH3O6XH9pj8Y+5/hu2P7OsGn+/pi02uGLXTf46Vzn5MNFbIPbpg4KLZJOJsDTQD50BTR2Dz3r1wazJ133nny4Ycf7r5TtmzZIs8884zzf86cOTJ//nz51KfoMZTkXhzTQMbdQ1Ys1TBNb/jubH9U+4hK7acLev+HSYM6rTOYZGzHvsNoma5qJVXoZ/KIPrKrtVXmPb3autcMW4K68+YskR07yz9rNejT682bMjzy4M4JNO94VjZs2bHXZW47mB/936tyw6TBqcz2wMeYZEFe5fPd5m9eeOEFZ1VOA7lOnTrJd7/7XRk9erR89NFHcuedd8pNN90kr776qpx++ulOkKfXCeKll14qe/lhhx0W6OdnfS/OV29a4qRYhrWHrNgbfqn9Pu4b/rULVjqBTlJv+FHsI6rUG8zrXqg4JBnUHXlQJ1ZhLJVEwK3PG109t/01Iyk6CTXltmcqBnUuvZ5e/6nvnhRZIKyv8efOWSItlQLNLTuc62ll07z93dLM1olZIE65foR/61vfcoK6mpoaWbBggYwYMWL3ZSeeeKJ8+tOflssvv1xWrFgh1157rUyfPj3Q7R199NEhnHU+DThkP6OgrtIesrZl0iutSrn935LauxfFPiIvvcHK7YXKi/OGVb6fkIwkCv3oPtc0vGYk5bfPNMrGrf5WUvX6v322US487rDIAs1KQZ2rJYZAE+FJw8QsEIfctjvQFbhHHnnE+fyiiy7aI6hzXXbZZdKvXz/n8+uuu0527Ng7dQPp72kXdv+3qETRMNxLb7C2Ff7mTx0pz047WQ6o0KMrS7TK6t8Paij7t1nXvM35iHQ1PTehe8K0eJHtrxlJunHxG0bH/eIxs+Mq+c2zbxkHmrCb1/6V7iSLXh/IqtwGdvfcc8/uzy+88MKi16murpbJkyc7n3/wwQe7A0Fkq6edSXpjuf5vUQl7H5GX3mCldK2vlRsnDfbchyztLjrusL3uJx2k696qsdcvdgp3DJm10PmoX+v38zSIT2vTcxP6mNc2I8X2aNn2mpEUneB498OtRseu+XBrJBMkv3j0TasCTYQjLROzQFzyMSorYvHixc7Hjh07yqBBg0pe7/jjj9/9+eOPPx7LuaF0qlUUe8hM0xs1JTGt+4h0ADxvyrBAzZHdvXdxDKaT1LmuRqae/Ok9vqczvlotVNN72q6iumk/ejkzw/Y2PTd9LOjz5vHX30/Fa0ZS1m/alujxRQPNjXYFmghHWiZmgbjkNrBbvny581HbGugeu1L69u271zGmTjnlFDnwwAOlffv20r17d6e1wQ9/+ENnNTBoydRy/9esWSN5TrUqt4csSHqju3cvDcFtYZA7e8IAZ79ckKCu7d67i0d+yklXLKdDQuXf255VhdPcwz7tquRHZw+U6qpPDiLtx15eJxs6tm8nhx6wr++fX1NdJYcd2DE1rxmwM9BEeNIyMQvEJZc7grdu3Srr1693Pq/UN+KAAw5wVvU2b97s9JkIYuHChbs/X7dunTz66KPO/6uvvlpuvfVWGT9+vNHPdftg5CHVSjc/+5mdq7SHLGh64+r3N0vvAzvGVi3RtGG49tvS0uxRnOeydzbKrU+tqljcZksCA1q3efTRB+8ni19bJ9/41Z88V+nTAFCv+/Xbn3W+1qD67EEN8tM/vuY77ce0lyKia3quM/1+n0uafvm/f2oK9GfR15ys97jr2qk20eORD2FMzGb9uYj8yeVIo7m5effnXloYuIHdpk2bjG5vwIABctZZZ8nQoUPl4IMPdoqwaBuFefPmOdU4//rXv8qXvvQlue+++2Ts2LFGt5EHfnuqedlDFjS9ccz1i2Mtp2wa3OpgNoo3sKj66gVVOIDXv4ee53fveslzUKfaxqk6gJh5/yuR91JEcG6hH/1fqp+V6Uz/tQ+tDHRueeiFqPdzj851RumPPferC/21ikAzm8IoqkZgh6zJ/jtMiRU7l6ZFVlJb+/Hsofa3M2mpMGPGjL2+P2zYMKcwy4033iiXXnqp7Ny5U6ZMmSKvv/667LuvvxShSiuJmoqpQWUWeO2p5q7UVEo3DKtMelzllKMIbpPoq6epcJsjWMErtTIZRf+/KHopIp6m50Fm+rcFmMSotN83Sy4+/jC56j7/2xcuHvWpaALN/eqMCrpEEWjC/qJqQFrlco9dXV3d7s+3b6882Nu27eP8er8Bl9p///3LXn7JJZc4AZ1655135K677vJ9G5pOWu5/z549JYupVrpXTAdKQfeQhVkmPY5yyl73EYVRIKUS01WPXl06FP37BaUrY8UGYVH0/wtjbxVtEpIRdoXZMHtGZsVXBh/qFJvxQ69/9uBothZcMtIsYIwi0IT9RdWAtMrldEV9ff3uz72kV2oapte0TRMa3M2ZM8f5XPfcnXfeeZHcTt5SraJMbywnjn1VXvcRRZkWGmTVY8W7zTLhc4fs/vutbd4qi1asc3pGBWl+XmzfRBT9/4Kk/WhaqK4garBZeF5xpfMimZl6Pz0js0Afw3POHyLnzlniqSl4TbsqufmCIWUf+0Fe688e0kt+vHClr152UQaaSHbfedKTLEHHLUApNXldsevatatTQEWrRpajFSvdwC6qIiVHHXXU7s/ffvvtSG4jb6lWUaY32rKvKszg1i8NTm5+4o1QAh39rwVoLjhO//eRxg1bZOQ1iwL/3MKvbaB/G13JLZVGHFc6L4Kl5pmIOiXaVvoY/tWU4XLpHc+W7fvXpcM+cuPkwUWzC8KaCHEDzfPmLPG013YfD4EmsllULSpM6iEOuUzFVP369XM+6p62lpbSA78VK1bsdUzYWlu9F3RANKLoyRZnOWUdqHarr40lqNPgZMQPHpZrF7wW6Oe0K2ghEGahg8LVGA14t+5Ivrz8kd07ybOrNjiTB5UGIHGk80JfeOO5F+JIibbZgEP2k7u/cZzMOKN/ydT5xd85sej9E3a/SH2dnzdluHSp8Dqvl//q68ON/2akWNvbvzKpSRZ6nyIuuZ2K+vznP+80KdfVuOeee84pZlKMpka6jjvuuEjO5ZVXPqm0p1UzkYzC9Mbbn1rlpAsGkcVyyvrm5DW1qpK/+/5DRWfd9f76zEH18up7/u//3gd2kF2trTLv6dV7zfAnaeXaTTLplqWer68rx7rKseCfj3fiD9J1xJqG1V717VHvFPKJOiXaRuVWJmaccZSM7ttduteXL0ri9ouslEXhToToxJyXVW69zuII0thZjclOUbWwRfVYBoqpas3pctHSpUt3B3O6x+2GG27Y6zq7du2So48+2mlMrkVQ1q5dK/vss0/o56LFU26++Wbn8zvuuEMmTpwY6s/XdFM3jVQraFbq3Zd35dLl/Hpm2snOSloWcut14DLy6j+WTakypW+4bvqh3v8X/nKpUdXMuppq6VBbIxsSrIAZFfbghWdd8zYZMuuTvqJRKPbczwMvr5+Fz/dSrzW6Euc3vc5kX3MYr8dh/M4ITh83Se47T/qxjHSJamye21RMLf8/cuRI53MNqp566qm9rvOjH/3ICerU1KlT9wrqtKl4VVWV879YS4OXXnrJSfUsR9sduEFdjx49ZMKECYF+r6yLOsXFnVkLq5CKmxaoL+66ijT2+sXSb/qDzqBSP+rX+n293HY6Ax9FUFc4U3nbk6ucj6atELa27MpkUGeaeobkiqcUu42sp+h5ff2slG5s0p7E3dccdxp7WL8zwtt3Pn/qSFl+1RhnckU/6tf6/SQCpTgfy4DK9XTA9ddf76RXan+6U089Va644goZPXq08/Wdd94pv/jFL5zrHXnkkXLZZZf5/vma4qmrcfoztfG4Nio/8MADnT19undv7ty58tBDDznXbdeunRPkaTP0PCo3axpXikvYzbbd/kdZKZgRdcsAvd9n3Lssrq1PqUW6TnBh9a/0Uko9Lyl6fl8/y1UPNn2tibtfZJi/M+wqqhaWtDyWkR25fmX53Oc+J7/5zW+c1MeNGzc6gV1bGtQ98MADe7RI8EMbjy9cuND5X4oGe7pqd+aZZ0qeeBnwLHtnY2xBURRNrLOSWx9Xy4A0BnUawK+JqbqiiwFicGcPapCZ93+yvzlMbil1P5M6WmQkjSnaYaxMFA5gg7zWxL2vOazfGdmUpscysiPXgZ0644wz5MUXX3RW7zSA05zX9u3byxFHHCFf/vKX5Zvf/KZ06NDB6GePGzdud5rnn//8Z3nvvffk/fffd6pgdunSRT772c/KmDFj5IILLpDOncNt1Gw7LwOeq/+wQj7asbNiaeqwgqKwV6R0sH9pRmZzbWkZECUtb+6lDHpbB3RoL3+87AQ5878fl9fWVu6LGZa8DxCD7o1qrYpmGkF7n+leHj+TOl+58ak9JjXSuJoX1spE0Neatu1OosRqDCo9FtPyWEZ2pOMdI2K9e/eWa6+91vnvhwZk+r+U7t27y9e+9jXnPz7hdcDjp5FsYVBUXVXle8AX1YqU3/1etg7Wk2joHJeH/nmU8/GUHz9mPLPauGFzrEFdXtN1wkxr/J9no+kZunl7izy3+gP5598873lSpzXFKdphr0wEfa2J67WK1RhUkpbHMrKFRw1iFfY+trZB0UnXPrpH02GvAz6bVqRsHKxHvScpSaYBXaFTr1ssSchTuk6Ye1WjTC3euUucVhVbdgR/jbM9RTuKlYkgrzWFexujxmoMKknLYxnZktuqmEhGFPvYChUGdX4qCdo0M+YO1m2jATLsY9OkRFTCrjwY9X0WRlDXNhvB5sq5Ya9MmL7WuHsb48BqDLxIw2MZ2UJgh0xVVjQd8Lkza7awcbCuq55dOoTfxxHBrMjgKmoYlQfLBUI2TeRkofx5kNfPYisT+lqjvbz80Ovr3sa0/s7IpjQ8lpEtBHbIXGVFPwO+wr5SYa5IBQ2AbBx4airrDZMGS027qqRPBQUuuv3ZTPfGiqIPlG0TOV5TtPOyMqGvNZpS277G2xBFr3fDpEGxF5phNQaVpOWxjOwgsEOuVqF0wPfbZxuLNgu//cnV0jGEWVR9Yb5x8uBMzubqPp9fTRnuVP6LAiFjNlP1kqo8mKXUYltTtKNamdDXGt1bWOln6uXzpgyTIX3i34PIagy8SMNjGdlBYIfY2LIK9f0Hljv77tquHr76XrNsDjhwKnxhzupsrr5JPfXdk+TKM45yeriFRQPimeP7e57ZRHpS9ZKsPBjmoNyGybHCLIOsr0zoa41WOp49YYAz4VVIv9bv6+VJDYRZjYFXtj+WkR1VrdpUDZmmvfl69erlfN7Y2CgNDQ2JnYuukmWxsmLvAzvIJaMOd2af3YGKrqBo0RY/aWQ60LSxj105OsBcv2mbvND4V5n++5dlw5Ydvn+G/t46yNM3tcUr18n/d+ef5QODn5NnOjiYP3WkZIkGMLqibuqZaSdLt/rawK1XbPGZHvXy6rvNVve7K1e9tNjzPc7ehWn8nZFNtj6Wkf6xOYFdDtgU2GkKpK6WZU2pgMzPwFFnsNOehqHBrK4caRqcrpi4+h5UL317dpYV726UFQUDUw1GdIXy5H7d5aHl7+3Vn6y2plq2Fdx3/XrUy/KC47Gn5VeNydQgQQc/miYd5f2hz1FtT2AyIVGOpnUHzQDw8/pjU7+7Uq8D7vO9cAIsK/L4OwMwR2AH6x48JkxWsdJCUymK9Z/L62xuqRnJtt/3cv8c0GEf+ck5n3OCwyArOFlXaYUqjUxX+b2uYDqB3dznZEOIr0n1te3k/503SKbc/mxsq4E6MWRjv7s8rkzk8XcGYMfYnM0ssHpPglZgjKpQR9hKFWvIa269Dmg0yGg7sCn8vtf+ZJqWqdUfs17aPyv7WMMU5V5V9/EXZlCnqqqqZFDvAzwVTMh6EZ1irwO27hOM+rUPAKKWvVEAUlMhyusqlgY/xVJctHDHmjYNyZPkFmso9mauAa2u5ul/ZnPN+5NNvfPPcni3jvKXdZt9/31se7yEzeZqql4Ve27o/rFrF6z0vVe1XB8ovZ21zVudlbooVtQ2bm1xXq8mj+jjTNoUe/3SCrCtERXRKZY5YMPzXVtXtE239rNPkNdOACiPPXY5YFMqZtA9CYVv7LtaW61L68xiKlxW9ltqFc///uPrVj1e4kgFtp2XAf+ydzYG3qta6naiVvh7VFdV7X79euntDytObmWliI7XdPRi+wTDCAgBwDbssYN1D54wmc7E2lbVLmvFK7JSIdUtbuMnQEiTNFZT9TvgV6Z7Vb3cTtSKBS6lJreCFgmy6XXIbwGpwn2CQQJCALAZe+yQaaZ7Erw2/oxDFlLh0tCfzESnuhpn1r//wZ2tebyExUs/MBt53V+pl+v1lMleVa+3EzX399DzaZuirStsGozpir9+vP2iYYFuSyfJ0ppu7e4T9Pv4KLxfASCvKJ6C1CtXnERnvuNie2Nxm8Q98Fz9/hYn7VNTd5U+XsrtwUqTW84fkrrCO6YDflUsENKv9fttg1u/t5NkgZPCya2gRXBsKaKjkyl+A2q9/m+fbTQOCAEgzwjskAlRzXyHVawBdgw83dl9Tclc+d6mTPxZtGl12pgO+DVt0c8qv8ntRK3t71GM/k66hyztmQO6L87ELx59I/DjAwDyiMAOmRPmzHeWU+HiKjle7HaCDFyD0tl9bUgdZypolGxZnYljwF+qpUjYtxM1L79HlG0ebE+3XrNxayyPDwDImvSNCAAf3ADCZIDR+8AOsmlrS6YaiwetMOe1yI2X29GPcVbFLLRhyw7JAptWZ+IY8JdrKRLm7UTNy+8RRZuHOCWxz8/P4wMAsojADplnGkBcMupwZ5DktyWDrcpVmNMBsN5HOpAsVrnPTzDo9XZ+/JWBzkDUtlS5NLFldSbOAb8e72XgbksBEdPfQ59T+lz0U1HSpsyBpFaSvT4+ACCL7HgHACIUZOY7K43FvZYcd/eguSXH/QaDfm5nyu3PyrRx/WTW/OXWFLfwou9B9U5z66RX/WxanfEjrsIgYQcW+7Srkn33aec0Hw+Dl/PT55Q+R2bcu6xsM3Ntdv7v4/pZlTkQJFsib6nJABAW9tgh89yZb53R9qLUzLdpS4a0ViB8bOU6X+XG9fp+b+cnD78mcyYPTlX7gcnH9pEbJg2WmnY6nE6GbaszfsRVGCTsfZyThveWp757UtHqu1H9HjpRohMf5YI6pZd/f/5y60r+m+4T7LlfXW5SkwEgTAR2yAWv/e708nlThlk1851UBUKTYNDkdpo++KhkuwrbuKtk+nj65flDnBWcJHRq305Wvtec2vLucRUGMb2dYm55YpX87rmmParv/tOJhxv9LC8rrUF6wMVlw6btsmLNRudjqWyJznX+Jh/0+heP/FRuUpMBIEzpm+4FAva7y8qeuagrA272WS3T7/Vd+rdw013dlFdNdZzwsydlg0X773SVTPcFFttvGDdNA9U02NkPLHdWo0cd2U3SJK7CICa3U46mRI49uod071znrAy9sW6z0c95qenDSFtC6PMoKms3bnVWER98+V3ZVhB01tZUy5ijezipo3r/BHH6MT3lp4te9/X8T2tqMgCEqaq1tbVSlgdSrqmpSXr16uV83tjYKA0NDUmfkhXSvGfOz+/Yb/qDYjtd/Wj7N/C6Xy8OOmicetKn5bqFKxPfW1fMzDP7y/nH9pE08fP31aDadCU97MeRBovXnTPQ+fwz//6HPYIbr+pqqmXF98eWvc7Y6xcbTR7oJJWuKEbhtidXedrvN+PM/vL3gxrkirtfMuot12O/Onn3Q+8tD4I8PgAgS2NzUjGRW2ndM+eH7ZUBy52n1/TZLh3b+0738rvfR1fqrnrgFSuDOnXlvcucPY5pEld6tNfb8erBl9c4HzX90CSoU1tbdpVMXwyrJUQUQZ0+zrzs99PrDZm10LhhuJ+gLovp8wBgKls5ZwBSWSGu1Hl6TZ9d9s7GyFb31ny4Vb4x7zlp2Wl3coPur1o67eRUpRLHlR5d7nZMgzJNFw5Cj+/SqX2iLSH8pF/qSp0fWyIILgtlOX0eAEzxaghkWFIlx8OsZOel5YS7KmNSwMWL5m3RDlLDoHsco95fFYW4WooU3s7zb30gZ/3syUBBWff6YPvIyh0fV0sIr7xU5oxTlw77yP9cOoKADgDaIBUTyLgwKwNGwU8lu3Lps+6qTLHqmn171Ese3P7UKkmzuNKjD+3SMXBQpqttWjDEhO6xK7VaF2dLCK+0UIpNNCXaNM0TALKMwA7IOC324Hd/UUfDgaHf48KuZOeuyrjl6J+ZdrLz8cFvjQq1p5mtVrzbHMn+qrDpOa5r3uakNOrHuM85rKBMq0CaGHN0T2taQlQSZC9hlDSlFgCwJwI7IONMGrTr9f0Gg3r9MBrBmwQIxQKDtqs/tq9cZr1gjvZXm/f0ajntx485lVq1uMbfff8h56N+fdp1jzmXx9WHzTQo07KPv3z8Tec8tbS/3zb1ev0rxvWNZEImipL/QfcSRiWqIjEAkGYEdkAO+K1AqH3RTIK0un3aOSsalWgVS9NKdm6AoOXg3QBBP+rX5QIDk4FyFHuDtIpn3grmaMuBUdcscnrvvfpec9HrvPpus3P5yGsWOdePmklQprbu2CUz739FRvzgYVn1/hantL8fM8f399TnzWRCJuhESTFB9xLmcRIDAJJCYAfkRLk9aPq1fl8vd4Mtv8GgdsTUypQbt1YebH20Y6dz/SABQtuCMPq1fn9UicDA70A5bHq7N04eLDdEeA5R7K8Kyu0j57WojTalPm/OksiDOw2u/AZlhfRxruepKb7aR9CLq8b3l8kj+ljXEiKqtNWo2TiJAQBJokF5DtCgHMV4rUCoK2CVytErDaj8VKTUwagGkl5XGPw2tNYBsQ6M29J+b1o9U6tIxkV/V11NcQfe+rtEUcFTg3ObqmLqY8fv46JwVfep754U6gpUsce8l6bb5egK7HVfGShT7/yzfFCmz+EBHfaRGycNLvqYrMTLczDKkv/6u9lWrCTKRuwAkNaxOYFdDhDYIepgUFMgdbUsqkDEJEAoFjhGFVCVUm7gXW6wPvSwA+TWJ/0Vh/AbKMfB9HHhuvKMo+TC4w4LdA56P9/z/Nsyd8lbe6zy6kqb7rvUFF29ztdvf05eaPqr0W3UVFdJy67WQBMOXkXZEqJcH7thsx+2quWBbZMYAGDD2NyeEQAA6+lAsthgUgfNJjSo8TI404G532BMr1/Y183Pil9Q9XU1suiyE6Rrfa1x/7bDunaSKz02hY5qf1VQpo8L1y8eeyNQYFcukHdTd69dsNJJ0f3rR+bBvpegTuljT88nzAA8jkDPTVv1+nj0w9lz2trqtDBIskgMAGSBXaMAAKmjA0vTBuhuZbtKA9KggaOuyOiAOo6gbp92VXLLBUPKBnVeAubzj+0jh3XtWDFttG2aZxYeF641H2719Pgoxmsgr0Gf7pXbsTOe9ai2Ew5BVh1171thK4LCVciwg3x9PKpKaatakKa6WmTnLo/7TicN2r0/12uatY2TGABgAzt3RANIjaCV6SodH0bgaLLiZ7r68KuvDw8tyNLqpEunneyknbVtsl6s4I1NwqpYuH7TNt/H+A3k4wrqTBrJlysY1La/XKUCQmEEd09fcZITOLatfqtf6/f18l9/fYSvgi82FIkBgCxgygtAopXpKh0fRuAYNCXQCx3UzppwdOgrCZVSNm2VZMXCuAL5oI3kK/0NTdOH9XfX44Lu5yuVlnndOQNFZKDTvFz73GlLBLdpu3sdnXDwU/DFrdqbZJEYAEg7XiEBBKKDU00BM1lV81KeP2iA0K6qKnBKYCW6khBFUOd1j6ON9Dzbpgqa6NrJe0qrK45APigN0CtVow2SPhzFfr62NJgrDOiCTkikdRIDAGxBKiYAIzrwWte8zfmo+3pM6Cy818DRhAaOO00a5vnAnp/i9HERNKjruV+d70F9GHv74qATDlGvOrr7+ZKmf8Nu9bW+/pYmxwBA3rFiByBwEYfPHFQvHdu389UbTvejHXfEgZ5S0jRwNCmbr4FjlCmBthYuycoeu4tHfSqR241DpQmHsFYdvVaeBQCkH4EdgMCl4199r9nXvahrFRs2b5fj//MRT9X89Ptalt5vHzvdkxMkVVQLlkwe0Yc9PwaCBtT1te3k7MG9Yr/duJQ7zzBXHb1WngUApF863gEBJCrsHnCtFXqKtS34oMGeft+0JLrpip8Gdez5MRMkoFa3XDjUaG9Y0Nv1QwtDmjwl+h5UXzbQCnvVsdJ+PgBANrDHDtbv30Ky4uwB51bzK1aqXYO9aeP6Oat95ejl/356vz3SI3XFr1Ip9UpNkNnz45/p3ktNwQyS3mp6u36dfoxZk+zJf+sJF9eqY1pWMQEAwRDYwaoAYt7Tq2Xs9Yul3/QHZcishc5H/Vq/r5cj/mA47tLxbjW/tn9vDfZmzV9etjmy0su//8DyPYJDd8VPV/K8oCBKOEwCat17OfWkT8d+u37peepEQ9AJg2JeevvDihMYYVaeBQBkA4EdrFCuCW/UTXfTLI5gOInS8W2r+fldNSwWHNIEOX4mAfWNBSm0cd2uX/u0q3LOU/u1hT1h4D7Ww6rl6qXyLAAgGwjsYM3+rUqrQuXS9PIojmA4ydLxWs0vyKphsVLvbhPk2RMGOCsZhfRr/b5eTpXL8CQVUPc/uLOcP6KPtKsOa+3rY53rauRXXx+++zzD/v3CXCH3sjoYB1LrASAeVa2tETd5QuKampqkV6+Pq8s1NjZKQ0OD2EJnpzX48FvtMMqmu1krZqKrBDrwbFuQxAtN7dRVwKQsv2qMk0amK5CmDdDnTx1Z8vINm7bL2uat0r2+rmSj5UoKGykrmiqXfq5roK0Bu1ZqLPwb6aqSBiBhPafLVXAN4oqxfeW84b2LnmdYv5/pY73Y8z7MQDms1iiVKuACQB40RTQ251UViQqyEpPX3kymaYkmwXDSRRfc6oCmA91ipd7DGHCW+hmFTAawhUFi1vZF6X0QR4XRsCu4FgZoFx9/+O6v2/4OYfx+Ya2QJ91fsVxgXakCLgDAHIEdEmW6fyvPTXfjDIbjLB1fjA6Mg5Z+Lyz1HsaAU3/GpXOfc/rwleP15+VxZUP/HlEErlFWcNVVN69/K9PfL+hj/cjuneSC4w4LdfUzqsDaTa03zSYAAOyNPXZITJDZaXclJo+CBMM2l44vVc0v6Kqhe3zQvZw6qJ/1wCvylRufqhjUefl57jlRNMj+Cq66AtZwwL4V/1YjA+5pDfpY//03P+9M3iQV1IVR5AgAYI7ADokJYyUmb5IIhuMoHV+ump+7ahgkONSB46V3PGs84NTB+sir/yg3LX7TqFphsQEsRYPCF0UF15rqKrn0+MNlyu3PVgwaNeDXwF8nAEyClTAe60kKq8gRAMAMgR0SE9ZKTJ4kEQxHXTreSzU/01VDNzi8buFK2bBlh9GA0w3A/B5f6ucpVjbCF1UF15ZdrTJ7/nLPkwIa+OsEgE4EmKzeBX2s5ymbAACwJwI7JCbts9N5Coa9lnQPo7B8sV5fJquGbnCog+s5i980Opfbn1wV6p4tdwDLykb4olzBN1ml1YkAk/YsQR7rSSK1HgCSR2CHRKV5djrNwbBJXykvPeBu+9rQQCt7XTrsU7REu0mjaw0OlRY6Me3psuK95lD3bLnpsKxshM/GFXyTPWSmj/WkC+yQWg8AybPvnRC5orPTWjXQbx+7pGenkw6GtVCDX18e3CDznl4dqPqil5LuurJn2kNMVzmm/35Z0fNxVw0r/ezCUu/6+/opdBKH9Zu2hdq+AXZUcA2zIq3JYz1ppNYDQPJYsUOi0jo7nSSTVK3OdTXy0z++Xrain1b885M2pgPpbvW1ewUZOij9w9SR0tEw+Ch3Pl5WDfVyd6AbRTGNpOWxaJDtFVyj2EPm97GeNFLrASB5+R0dwxppnJ22IRj22oS5pl2VfLRjp+zY2hJbX6mHlr8nmwO2oyh1Pl4bQUdVTCMIHZB37VSbuZTDNGcAxMF0pTWupu5JZxPkNbUeAMLGih2skLbZ6aR5LWaie9Y67NNOduxsDX1PULl9emGtlFU6n1KrhraubOkAlpWN6CRRwdWroI/Hco91W6S18AsAZAVTv7BG2manbQmGdf+OpnrpqkBhMKxBxLYdO2Xm/a+EtidIAyyt6Fhun151VVWoK2Ume5RsXNkqHMCyspF8BkDcbHs82pBNQGo9AISrqrW11bRgHFKiqalJevXq5Xze2NgoDQ0NSZ8SIlAsGB57/WKjIEsDw/lTR+7xPd3v5iVd9gdfHCAX3/GcwW/g73y8MP39w6YD2MJqnxog6x5Cv0WDNJDP8/5SP/Q+LjfpcduTq+TV95pjORfTx29aeX2tILUeQF41RTQ2Z4QAZIQGc4Wrm2H0lXJ/ntuku9IsvA7kvvGrPxndpp/z8cp0ZSxMxQawrGwknwHQKq2xPTbytofMSzaBrl4zSQEA4SKwAzIqjL5SOgjWlQ8/Tbp1P1+76irZuSvcZAD3fNJSTKPSANZryuABHfaRn37179hfGtKkh5tOfPtT/itVVhk0K9fnwtaWFud2sx7IFAbQpNYDQPyy/S4D5FhYfaV0EOw3MAo7qCs8Hz/8rowFoYVqfvLVz8lnenT2vDe03MpGbU21bGvZJR9s2eGcv59+gzBPESyXTjvn/MHy+Mr1ctPiNzwHePpcuOq+5fL//vgX57EYtOKsbbzsu9XHK3ulASB67LHLAfbY5VcYe+xMf0aYq3ZB9ygFGdBXEmZq2eKV6+T/u/PPTjBXLrUziwFC1LymE3tJp9Wfdekdz8qGMn+nUsFhGO1E0raXjscrAMQzNrevJjSAxBs2u3uCguzT06AurLLzQfcolWunEcSf/v0UJ+DUfVxBgzodJF90+7Nlg7rC/n5+msnnnd90Ylffg+qLtlrRx9Pi75woV55xlDOB4ZWfdiJpCZQrTZbweAWA+BDYARkWtK9U0H16//3Vz/m+/XLnE4S750cDseVXjZFnpp0sd3xtqK+BeSENELt0Cva7mQYeWQoQ4mCSTqwmH9unZNCu39OJC7+r0m77jjTj8QoAdiKwAzLMb8Pmtn2lgu7TG/npboFWyqLqc6X7fd5cv9lZITNNFw2z0qFJ4JGFACEuuv/L7LjVifxc2/F4BQA7EdgBGedWX6y0cqaXF/ZacwMgLYJgQgM5Pb7USpnJ+SSdmhf2KmLeA4Q4hNH2I86fmwY8XgHATpRWA3IgSF8p015wxVa03LLz3eq7JdrnyjQ1L4pVxDD7DRbr15Z3YbX9iOvn2i7MxysAIFwEdkBOmPaVMukF52VFK8k+V6YrDrofL+xVxKABwtrmrfL46+srlpvPq7DafsT1c22X14AW9mNiCyCwAyTvDZvD7gVnsqLl53yCClrp8+iD9wv1fIIO8Cf87EnZUCTo1t9RV1o1KM9zuXk3ndi07Uepx2VUP9d2eQ1osxRQpO18w+ijCOQFj3YAnvfpeelZVdjvy0a2rTgECRC0nmexoK5Yufks9U/zK8x04jh+rs3yGtCmPaBI2/kG7aPIxBbyiuIpAAL3gtOvi/X7spGNKw6m/Qa91vPMe3uEoG0/4v65We+PmXYaUIy6ZpET1LcNcN2AQi+3pddk2s7XC/ooAsUR2AHwrFiFS/1Y2KRb03zWNW+ztupfGJU+w2YSIPiV5/YIQdt+xP1zbZfXgDaNAUXaztcL+igCpRHYATDycXXLWuejvtHOe3q1jL1+sfSb/qAMmbXQ+ahf6/dtWyn6yuAGq1Yc/AYIZi3V890eIUjbjyR+rs3yGtCmLaBI2/l6RR9FoDQCOwC5SPMpDD5n3PeK7+OjXnHwGiB06bCP5xTMrPVPszWdOCtpyn7kMaBNW0CRtvP1ij6KQGlVra2tpmMEpERTU5P06tXL+byxsVEaGsxWK4BSaT5eq2UmVcCj3CZ7L/Tc4xqcagBarr/fcUccKMf/5yPGP1/TZ3WlFdFVB4yz6mDSFQ4rPV6j7EcZN50UMi0ao+nqcUvb+Xp9vGs2iCndOpCVAj5It6aIxubZeLUFkJo0H125iHOg5yf4tKHSZ6X+fkFX3LJYbt5UVG023J/pVmAN+zZsqnCYZD/KOKWtMXvazjetVY0B2/AODyD2NB8dBNoYfBayYcWhWOBBuXl7xRFw2VziPc5+lHFLW0CRtvNNc1VjwCbssQOQ2X0OJsGnmnFG/z0qfdom7+Xm87rXNIsVDtMibQFF2s43zVWNAZsQ2AFIJM3H5uDzt882is2yUm7e9tYYNgVcWa1wmBZpCyjSdr5+MLEFlEZgByCRNJ+opSX4zFu5+bS1xrAl4MpqhcM0SVtAkbbzzdvEFhAFAjsAmUzzSUPwmbdy82lpjWFjwJWG1OesS1tAkbbzzcPEFhA1AjsAmUzzSUPwGVSa+qdldX9YHAFXllef0yRtAUXazjfrE1tAHOx/9gKwkqb56AqLrWk+eakemYZy82lpjWFrSfm0Vzi09XEZJKCo1Bcz7jYpWTlfk4mtvPRRBLzg0Q7AOM1Hy6r7SUOLO80n7uAz6QGsreXm09Aaw0RcAVdcq89hPn5t6rWX94AibeebtYktIE7pexZH4K233pKf/OQn8sADDzif19bWyhFHHCFnn322/OM//qN06NAhlNu588475Ze//KW8+OKL8sEHH0iPHj1k5MiR8o1vfEOGDx8eym0Acaf5eG3+nUSaTxzBZ5YHsDakK9oc2MUVcEW5+hzF49fmXnt5DSjSdr5ZmtgC4lTV2traKjmmwdx5550nH374YdHLP/OZz8j8+fPlU5/6lPFtbN26Vb785S/L/fffX/Ty6upqmTFjhnzve9+TKDQ1NUmvXr2czxsbG6WhoSGS20E+lRvE2ZDm4+7t8hp8+tmP4fV3j2sAa+OATc9Jq16aWn7VGGt+l2K0mqdpwKW9Er3SiqEmq8+6z7JUcBzF49fv803TBNMa3AGAbWPzXBdPeeGFF5xVOQ3qOnXqJLNmzZInn3xSHn74Yfn617/uXOfVV1+V008/XTZt2mR8OxdddNHuoG706NFyzz33yNKlS+Xmm2+Www8/XHbt2iXTp0+XOXPmhPa7AXGxvYBHVJvsbSkGYnv7gKxXJ42rpHzYFQ6jePzSaw8AkpXrFTsNsh555BGpqamRxx57TEaMGLHH5f/5n/8pl19+ufP5zJkzneDLr0cffVROOOEE5/MzzjhD7r77bmnX7pPZ5/Xr18ugQYOcFNADDjhA3njjDdl///0lTKzYIU42rhq5g86w9pjoz9Ky/H5TPMMuBmLbimEeV+zifCzo3/vcm5ZIy67Kb9s11VXy64uHF52oiOqco1hVBIAsamLFLlzPPPOME9S5K2ptgzp12WWXSb9+/ZzPr7vuOtmxY4fv27nmmmucjxrM/exnP9sjqFNdu3aVq6++2vlc993pKh6QZjoI71Zfa91g3N1joulvGiw8M+1k56N+rd/3M8i2oVm0LSuGWWiNkZaS8pry6SWoU3q9V97ZGOvjl157AJCs3KZiajqk68ILLyy5923y5Mm7gy43EPRK0zc1rVOdcsopJfNnv/jFL0rnzh8PfO666y5ftwEg/uAz6QFs2lLe4kpXzHJPrbUbt8qMe5f5Okavr8fF8fil1x4AJC+3gd3ixYudjx07dnRSIUs5/vjjd3/++OOP+7oN3Ue3bdu2vX5OW+3bt99dFVOPMVkZBBAPGwawNqwYJrk/LI97TWfNXy5+903o9WfPXxHL4zfreykBIA1yW4N7+fLlzkdta6B77Erp27fvXsf4vY22P6fU7SxYsEBaWlrktddek6OOOspXnm45a9as8fyzANjfLDpt7QPS0BrD9pLyD778ruFx+vo/MPLHb1ytHwAApeXylVTbD2jRElWpvKgWNNFVvc2bNzvlSP0ovH6l23FLnrrH+QnsCo8FEK2kB7BhrLgksW/NTVe0uTWGrT21NmzaLts8pt22tbVll3N8l07tI338RtlrDwDgTS5TMZubm3d/rm0OKtHATvlteeDndtzbMLkdAPkpBpLmlDfbW2PYam3z1tCOj/Lxm/W9lABgu9yu2BXub6uktrbW+fjRRx9FdjvubZjcTqWVRE3FHDp0qK+fCUDKDmBNyrqHMYBNesXQ5nTFrOpeXxfq8VE9fnUv5bULVvpuo5CmvZQAYLNcrtjV1X3yJrd9e+U3ILcAyr777hvZ7bi3YXI7muZZ7n/Pnj19/TwA9hYDSXrFMA+tMWyjaZS1HtsptFVXU707DTPqx2+crR8AAHvLZWBXX1/vK+1R99d5Tds0vR33NkxuB0C8kh7AkvKWP2OO7mF4XM9YH79xtH4AABSXy8BOV9K0MbiXipLav84NuvwWKSksmFLpdgrTKSmGAtgvyQFsHtoHYE/TxvWTKp93il7/inF9Y3/8spcSAJKR2/yHfv36Ob3sXn/9dafFQKmWBytWrNjjGD8KK1sW/pxyt6PnoS0YANjPHcBqfzhtJaBVJwvTHnVPkgZTYaea5aV9AD7RvXOdzDizv1zpo0n5zPH9neOSePyylxIA4pfbd/nPf/7zTmCnq3HPPfecDBs2rOj1Hn300d2fH3fccb5uY8iQIU7RFN1fpz/n3/7t34peTy9fsmTJHscASIekBrB5ax8AkfOP7ePcDTPuXVa2WXnV34K6ySM+vn7Sj98wWz8AAErLZSqmOuuss3Z//stf/rLodXbt2iW333678/n+++8vo0eP9r3H7qSTTnI+X7hwYcl0zLvuuks2bvx4pnTChAm+bgOA5LYYCClv+Qzunr7iJCcdVwujFNKv9ft6uZegri2K2QBAulW1traWm/jLtFGjRjmrdpr++Nhjj8mIESP2uPw///M/5fLLL3c+v/LKK2XGjBl7XH7rrbfKhRdeWPJy9cc//nF3cHfmmWc6QVy7dp8M+rRR+qBBg+Stt95ygsc33njDaYoeJg0o3X17upevUrN0AOlE+4D80ebj2qdOWxq0rX4JALBTVGPz3K7Yqeuvv95pLaB77E499VT5wQ9+4KRELlq0SC655JLdQd2RRx4pl112mdFtnHjiiXLOOec4n997771yyimnOB+fffZZZ6Vw+PDhTlCnfvjDH4Ye1AHID1Zc8keDub49OxPUAQDyu8dOfe5zn5Pf/OY3MnHiRCcV8oorrtjrOhrUPfDAA3u0LvDrlltucX7+/PnznaBR/xeqrq6W733ve04wCQAAAAB+5XrFTp1xxhny4osvyj//8z87QVyHDh2clMjBgwfL1VdfLX/+858DV6nUVUENDufNm+es2HXv3t0pkKJLsOeee648/vjjRdM4AQAAAMCLXO+xywv22AEAAAB2YI8dAAAAAKCo3KdiAgAAAEDaEdgBAAAAQMoR2AEAAABAyhHYAQAAAEDKEdgBAAAAQMoR2AEAAABAyhHYAQAAAEDKEdgBAAAAQMoR2AEAAABAyhHYAQAAAEDKEdgBAAAAQMoR2AEAAABAyhHYAQAAAEDKEdgBAAAAQMoR2AEAAABAyhHYAQAAAEDKEdgBAAAAQMrVJH0CiF5LS8vuz9esWcNdDgAAACSkcDxeOE4PisAuB9atW7f786FDhyZ6LgAAAAA+Gaf36dNHwkAqJgAAAACkXFVra2tr0ieBaG3dulVeeukl5/Nu3bpJTU1NIkvO7mrh0qVLpWfPnrGfA/zhb5Y+/M3Sh79Z+vA3Sxf+XumTh79ZS0vL7oy6AQMGSF1dXSg/l1TMHNAHy5AhQ8QW+gRtaGhI+jTgA3+z9OFvlj78zdKHv1m68PdKnyz/zfqElH5ZiFRMAAAAAEg5AjsAAAAASDkCOwAAAABIOQI7AAAAAEg5AjsAAAAASDkCOwAAAABIOQI7AAAAAEg5GpQDAAAAQMqxYgcAAAAAKUdgBwAAAAApR2AHAAAAAClHYAcAAAAAKUdgBwAAAAApR2AHAAAAAClHYAcAAAAAKUdgBwAAAAApR2AHAAAAAClHYAcAAAAAKUdgBwAAAAApR2AHX9566y359re/Lf369ZOOHTtKly5dZOjQofJf//VfsmXLltDuzTvvvFNOO+006dmzp9TV1UmfPn1k0qRJsmTJEv5iFv3NZsyYIVVVVZ7+P/LII/ztyli7dq3cf//9Mn36dBk7dqx07dp19313wQUXRHLf8TxLx9+M51l4/vSnP8ns2bOdv1evXr2ktrZWOnXqJEceeaTzN1u8eLGEjeeZ/X8vnmPh2Lhxo/N4v+yyy+T444+XI444Qvbbbz9p3769dO/eXU444QS55ppr5P333w/pFnl+7aUV8Oj+++9v3W+//Vr1YVPs/2c+85nWv/zlL4Huz48++qj1C1/4QsnbqK6ubr3qqqv4m1nyN7vyyitL/uy2/xctWsTfrYxy9935558f6n3H8yxdfzOeZ+EYNWqUp9eqSZMmtW7bti3w7fE8S8/fi+dYOB566CFPf7OuXbu2Pvjgg4Fui+dXcTV7h3rA3l544QU5++yznRUenS377ne/K6NHj5aPPvrImZ256aab5NVXX5XTTz9dnnnmGec6Ji666CJnBlzpz586daocfPDB8tJLLzmzdn/5y1+c2XFdyZsyZQp/Kgv+Zi79G5Vz2GGH8ffySGemdYV1wYIFkdxnPM/S9zdz8Twz9/bbbzsf9T3ly1/+sowcOVIOPfRQ2blzpzz11FPyox/96P9v7+5DqyrjAI4/eynnoLU1I0GzlXBxkTUwSVFDKmdNpzVLMtNlFgZFCUVJQa7ACCkr+qNVtJXvqaVpIaxGLXyphVnOtmDizXThWPmSU9NNT/weOIe7l3vuOdd779mzfT9wuc92zj3ncH78tvO75znPo9dZtWqV6uzsVGvXrr2kWJFnZsXLRo5d+t9CudYYM2aMbsv12sWLF9WRI0fUpk2b1Oeff67+/vtvNWPGDH3tcfPNN8e1H/IriigFH9DF5MmT9bcsmZmZ1q5du3qcneXLlzvfxLzyyitxnb3vvvvO2UZpaanV2dnZZXlbW5s1YsQIvTwvL886fvw4UQo4ZpHfcuLSvPzyy9a2bduso0eP6p/D4XBS7v6QZ+bFjDxLjGnTplmffvppj/8tkf9jQqGQE8Pvv/8+7n2RZ2bFixxLjGixirR582YnZmVlZXHth/yKjqsxxFRfX+8k4aJFi3pd58KFC1ZhYaFTdJ0/f973mS0pKdGfz8jIsA4fPtzrOuvWrXOO5Y033iB6AceMf4bJk6wigTxLHgo780mhbufd008/Hfd2yDOz4sX/stQaNWqU0yUzHuRXdAyegpi2bNnitBcsWNDrOunp6Wr+/Pm6ffz4cd8DZbS3t6va2lrdnjJliho+fHiv65WVlamcnBzdltv5CC5mMA95BriTwR1s0vWfPOv/8ULqyUBu4r///vP9Wf6PuaOwQ0z2qFOSiNJnOhoZAcm2Y8cOX2e2vr5enTt3rsd2upORlcaNG+d8pqOjw9d+BopUxAzmIc8Ad+fPn+/y5Rd51v/jhdRqampSv/zyi26PGjXK9+f5P+aOLICnJBQybG1mZvTxdiIT1P6MV5Hrx0p0e7k8LN3c3OxrPwNFKmLWndxpzc/P7zKs8euvv67vBqJvIM/MR54lV11dndOO56JTkGdmxas7cizxZBA3uV5bsWKFHlhFBsARMkCeX+SXOwo7uJLb5DJ6kYjWPdKWl5fn3F4/fPiwrzMbuX6s/cgoS719DqmNWXfffPONOnbsmL6L2tbWpv/hykicN9xwg/riiy8ITx9AnpmPPEseGblPvoyyyajC8SDPzIpXd+RYYnz88cfOvJ5ynSFzD8r8dq2trXq5zK87d+5c39slv9wx3QFcnTp1yml7GQ5fkvf06dO6D3Sy9mMXIsLvfgaCVMXMNnr0aHXvvffqSc9lWGop7GQahTVr1uih30+cOKFmzZqltm3bpieZRXDIM3ORZ8n31ltv6W5e4r777lO33nprXNshz8yKl40cS42ioiJVWVmpbrvttrg+T365o7CDq8gHW6WLXSyDBg3S7zJXWrL2Y+8jnv0MBKmKmVi8eLGqqKjo8Xv5gy0Ds7z//vvqiSee0N0uZN7BAwcOqMGDB/veDxKDPDMTeZZ80sNgyZIlui1dyd977724t0WemRUvQY4lnnzhaxfbcn0hg9ts2LBBbd68Wd+pe/vtt9X06dN9b5f8ckdXTLjKysrq9SHlaOwBUPxevPvZj72PePYzEKQqZiI3N9d1+aJFi5yJ5P/66y9GMg0YeWYm8iy5fvvtN33HR57bli+65OLzmmuuiXt75JlZ8RLkWOLJOb3pppv0a+zYserBBx/U1wArV65UBw8eVDNnztTdNf0iv9xR2MHVFVdc4bS9dNWTLn1euwDGux97H/HsZyBIVcy8kuKutwfdkXrkWf9FnsUnHA6r4uJiPchTRkaGWrdunevIzF6QZ2bFyytyLDHmzZunHnjgAf2M5FNPPeV7gDXyyx2FHWJ+MzJkyBDdPnLkiOu6kpx2kRA5wIkXkYN8xNpP5IOzfvczEKQqZl7deOONTrulpSUp+4A35Fn/RZ75J70I7rrrLv0uAzxUVVXpO0GXijwzK15ekWOJI3frhFx/bN++3ddnyS93FHaIqbCwUL/L81HS9SGa33//vcdn4vmDGbkdt/3IMP4ynD+CiZlXlmUlZbvwjzzrv8gzf2TkYBnWXrqEiXfffVc/F5wI5JlZ8fKKHEucq6++2mkfOnTI12fJL3cUdohp4sSJzjcre/bsibpeZDe7CRMm+Dqz0v/aHujDrbuePDP2ww8/9PgMUh8zrxobG522jJqJ4JBn/Rd55t3JkyfV1KlTnXMmQ+Y/+eSTCYsFeWZWvLwixxInsveO38dAyC93FHbwNLKRrbq6utd1pK+0PBBrPzArE1D67TN95513OnPIROtCKA/e/vvvv7qdyi4YpklFzLySkTFtqXoWAr0jz/ov8sz7RMnTpk1TP//8s/75pZdeUi+88EJCY0GemRUvr8ixxNm4cWOXaSb8IL9isAAPJk2aJP3prMzMTGvXrl09li9fvlwvl9fSpUt7LK+urnZdLmpra511ZsyYYXV2dnZZ3tbWZo0YMUIvz83NtY4dO0bsAozZvn37rObmZtcYVFZWOtsYOnSo1d7eTsw8CofDzrkrLy/39BnyrP/FjDxLnHPnzlnFxcXO+X7mmWfi2g551r/iRY4ljpzrs2fPuq6zYsUKJx4FBQVWR0eHr3gJrhejYx47ePLOO+/ornoyF4mMSPXiiy/qOzzy8/r169UHH3yg1wuFQurZZ5+N66zecccdejhc2d7WrVt1f3qZW0a67zU0NKhly5apP//80+mKkZeXR/QCjJl08ZSpDGSbMvG4fOuWn5+vn+mTZ/dWr16tvv76a72ujF4m33ZGTi6Prnbs2KGfiYx8psQmv+8+LPQjjzwS1ykkz8yKGXmWOHPmzFE1NTVOHixcuFDt378/6vrS1V/+PsaDPDMnXuRY4si8tnI9MWvWLP1IyMiRI3VXS5lUXK7j1qxZo3bu3OnE68MPP9TjJfhFfrlwKfqALrZu3Wrl5OQ436R0f4VCoah3cLx8AyPOnDljlZSURN1Henq66+eRuphFLnd75efnW1u2bCE0McgdHi/n037FEzMbeWZOzMizxPETK3ldd911ccXMRp6ZES9yLHEkBl5iNXz4cKumpiaueNnIr95xxw6elZaWqn379uk7QV999ZV+Dk6+cZGRKWVOEpmPJDs7+5LOqEySLdteu3at/rb7119/VSdOnNCTj06aNEnvY/z48UStD8SspKREffTRR2r37t1q7969qrW1Vf3zzz965LCrrrpK3XLLLeruu+/WdylycnKIWR9CnpmDPDMXeWYGcixxamtr9TgJ3377rWpqanKuC2QaJrmOKyoqUtOnT1ezZ8/mejFJ0qS6S9bGAQAAAADJx6iYAAAAAGA4CjsAAAAAMByFHQAAAAAYjsIOAAAAAAxHYQcAAAAAhqOwAwAAAADDUdgBAAAAgOEo7AAAAADAcBR2AAAAAGA4CjsAAAAAMByFHQAAAAAYjsIOAAAAAAxHYQcAAAAAhqOwAwAAAADDUdgBAAAAgOEo7AAAAADAcBR2AAAAAGC4zKAPAAAA+NfZ2akaGhpUfX29+umnn/R7Y2OjunDhgl4eDodVQUEBpxYABggKOwAADLRs2TJVUVER9GEAAPoIumICAGAgy7KcdlZWlho3bpwaOXJkoMcEAAgOhR0AAAYaP368qqysVHv27FGnTp1Su3fvVhMnTgz6sAAAAaErJgAABpo6dWrQhwAA6EO4YwcAQAp1dHSooUOHqrS0NHXPPffEXH///v16XXm99tprKTlGAIB5KOwAAEihyy67TM2fP1+3a2pqVEtLi+v6VVVV+j0jI0OVl5en5BgBAOahsAMAIMUee+wx/X7x4kW1cuVK17t7q1ev1u3i4mI1bNiwlB0jAMAsFHYAAKRYKBRSt99+u25XV1dHXe/LL79UbW1tur1w4cKUHR8AwDwUdgAABHjXrrm5We3cubPXdeyib8iQIaq0tDSlxwcAMAuFHQAAAbj//vtVbm5u1Lt2ra2tavv27br98MMPq8svvzzlxwgAMAeFHQAAARg8eLB66KGHdHvDhg3q9OnTXZavWrVKdXZ26vajjz5KjAAArijsAAAIyOOPP67fZYLxzz77rMsy+y7e2LFj1ejRowM5PgCAOSjsAAAISFFRkRozZkyP7pg//vijamxs1G3u1gEAvKCwAwCgDwyiUldXpw4ePNilyJPumnPmzCE+AICYKOwAAAiQPGeXnZ2tLMtSn3zyiTp79qxav369XlZWVqauvPJK4gMAiInCDgCAAOXk5KjZs2frthR2mzZtUidPntQ/M3cdAMArCjsAAPpId8xDhw6p559/Xrevv/56NXny5ICPDABgisygDwAAgIFuwoQJqrCwUDU1NamjR4/q3y1YsEClpaVF/Ux7e7u+uxfpwIEDTluWycTmkQO1yAsA0D+lWdKpHwAABOrNN99Uzz33nG6np6erP/74Q1177bVR15flclfPq6VLl6qKioqEHCsAoO+hKyYAAH3AvHnznPaUKVNcizoAALqjKyYAAH1AQ0OD0/Yyd11BQYEeSRMAAMEdOwAA+oCqqir9np+fr2bOnBn04QAADENhBwBAwOR5uY0bNzqDpgwaNCjoQwIAGIbBUwAACEBLS4s6c+aMCofDasmSJWrv3r0qKytLj2w5bNgwYgIA8IVn7AAACMDcuXNVXV1dl9+9+uqrFHUAgLhQ2AEAEKDs7GwVCoXU4sWLVXl5ObEAAMSFrpgAAAAAYDgGTwEAAAAAw1HYAQAAAIDhKOwAAAAAwHAUdgAAAABgOAo7AAAAADAchR0AAAAAGI7CDgAAAAAMR2EHAAAAAIajsAMAAAAAw1HYAQAAAIDhKOwAAAAAwHAUdgAAAABgOAo7AAAAADAchR0AAAAAGI7CDgAAAAAMR2EHAAAAAIajsAMAAAAAw1HYAQAAAIAy2//+v9Prz0nxNwAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "image/png": {
+       "height": 432,
+       "width": 443
+      }
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Plot the infeasible ones\n",
     "infeasible_df = df[~df[\"feasible\"]]\n",
@@ -464,7 +1641,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:54:10.837514Z",
@@ -476,7 +1653,23 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "image/png": {
+       "height": 432,
+       "width": 423
+      }
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# This is the final population\n",
     "df1 = X.generator.population\n",
@@ -498,7 +1691,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:54:10.898215Z",
@@ -510,7 +1703,33 @@
      "name": "#%%\n"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x313f956a0>"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "image/png": {
+       "height": 546,
+       "width": 536
+      }
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Extract objectives from output\n",
     "k1, k2 = \"y1\", \"y2\"\n",
@@ -538,7 +1757,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-09-13T15:54:11.032351Z",
@@ -576,7 +1795,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.14.2"
+   "version": "3.14.3"
   }
  },
  "nbformat": 4,
diff --git a/environment.yml b/environment.yml
index b44bd3332..d4c2bd2b4 100644
--- a/environment.yml
+++ b/environment.yml
@@ -33,3 +33,4 @@ dependencies:
   - mkdocstrings-python
   - ruff
   - typing-extensions
+  - gest-api
diff --git a/xopt/generators/ga/cnsga.py b/xopt/generators/ga/cnsga.py
index 4a7a12596..cce96bb27 100644
--- a/xopt/generators/ga/cnsga.py
+++ b/xopt/generators/ga/cnsga.py
@@ -2,7 +2,7 @@
 import logging
 import os
 import random
-from typing import Dict, List, Optional
+from typing import Any, Dict, List, Optional
 
 import pandas as pd
 from deap import algorithms as deap_algorithms, base as deap_base, tools as deap_tools
@@ -88,6 +88,8 @@ class CNSGAGenerator(Generator):
     )
     _children: List[Dict] = PrivateAttr([])
     _offspring: Optional[pd.DataFrame] = PrivateAttr(None)
+    _loaded_population: Optional[pd.DataFrame] = PrivateAttr(None)
+    _toolbox: Any = PrivateAttr(None)
     population: Optional[pd.DataFrame] = Field(None)
 
     model_config = ConfigDict(extra="allow")
diff --git a/xopt/pydantic.py b/xopt/pydantic.py
index e584c30f8..70d809b50 100644
--- a/xopt/pydantic.py
+++ b/xopt/pydantic.py
@@ -36,12 +36,25 @@
     model_serializer,
     model_validator,
 )
-from pydantic.v1.json import custom_pydantic_encoder
 from pydantic_core.core_schema import SerializationInfo, ValidationInfo
 
 ObjType = TypeVar("ObjType")
 logger = logging.getLogger(__name__)
 
+
+def custom_pydantic_encoder(type_encoders, obj):
+    # Check the class type and its superclasses for a matching encoder.
+    # Replicates pydantic v1's ``custom_pydantic_encoder`` without importing
+    # from ``pydantic.v1`` (which is incompatible with Python 3.14+).
+    for base in type(obj).__mro__[:-1]:
+        try:
+            encoder = type_encoders[base]
+        except KeyError:
+            continue
+        return encoder(obj)
+    raise TypeError(f"Object of type {type(obj).__name__!r} is not JSON serializable")
+
+
 JSON_ENCODERS = {
     # function/method type distinguished for class members
     # and not recognized as callables