From 3be0e4cec669748d1c228d5b664c2992a7a7afa5 Mon Sep 17 00:00:00 2001
From: Simon <31246246+SimonMolinsky@users.noreply.github.com>
Date: Fri, 20 Feb 2026 15:12:00 +0200
Subject: [PATCH] [enhancement] Users can set negative predictions to zero in
 Area-to-Area, Area-to-Point, and Centroid-based Poisson Kriging

---
 CHANGELOG.rst                                 |   4 +-
 .../core/pipelines/block_filter.py            |  42 +-
 .../block/area_to_area_poisson_kriging.py     |   8 +-
 .../block/area_to_point_poisson_kriging.py    |  58 +-
 .../block/centroid_based_poisson_kriging.py   |   9 +-
 tests/test_core/test_smooth_blocks.py         |   4 +
 .../1-1-semivariogram-exploration.ipynb       | 736 +++++++++---------
 .../functional/1-2-semivariogram-models.ipynb |  88 +--
 .../1-3-spatial-dependency-index.ipynb        |  16 +-
 .../2-1-directional-semivariogram.ipynb       |  60 +-
 .../4-2-poisson-kriging-centroid-based.ipynb  | 284 +++----
 .../4-3-poisson-kriging-area-to-area.ipynb    | 264 +++----
 ...sson-kriging-area-to-point-smoothing.ipynb |  71 +-
 tutorials/functional/fitted.json              |   2 +-
 14 files changed, 856 insertions(+), 790 deletions(-)

diff --git a/CHANGELOG.rst b/CHANGELOG.rst
index f56e9f0c..352d6e3b 100644
--- a/CHANGELOG.rst
+++ b/CHANGELOG.rst
@@ -1,12 +1,14 @@
 Changes - from version >= 1.x
 =============================
 
-2026-02-21
+2026-02-2
 ----------
 
 **version 1.2.2**
 
 * [experimental] LSA-method Ordinary Kriging tests and experiments
+* [enhancement] Users can set negative predictions to zero in Area-to-Area, Area-to-Point, and Centroid-based Poisson Kriging
+
 
 2025-12-26
 ----------
diff --git a/src/pyinterpolate/core/pipelines/block_filter.py b/src/pyinterpolate/core/pipelines/block_filter.py
index af7ba3fa..75d08570 100644
--- a/src/pyinterpolate/core/pipelines/block_filter.py
+++ b/src/pyinterpolate/core/pipelines/block_filter.py
@@ -33,6 +33,7 @@ def filter_blocks(semivariogram_model: TheoreticalVariogram,
                   data_crs=None,
                   raise_when_negative_prediction=True,
                   raise_when_negative_error=False,
+                  negative_prediction_to_zero=False,
                   verbose=True) -> gpd.GeoDataFrame:
     """
     Function filters block data using Poisson Kriging. By filtering we
@@ -66,6 +67,9 @@ def filter_blocks(semivariogram_model: TheoreticalVariogram,
     raise_when_negative_error : bool, default=True
         Raise error when prediction error is negative.
 
+    negative_prediction_to_zero : bool, default=False
+        When predicted value is below zero then set it to zero.
+
     verbose : bool, default=True
         Show progress bar
 
@@ -154,7 +158,8 @@ def filter_blocks(semivariogram_model: TheoreticalVariogram,
         number_of_neighbors=number_of_neighbors,
         data_crs=data_crs,
         raise_when_negative_prediction=raise_when_negative_prediction,
-        raise_when_negative_error=raise_when_negative_error
+        raise_when_negative_error=raise_when_negative_error,
+        negative_prediction_to_zero=negative_prediction_to_zero
     )
     return parsed
 
@@ -165,6 +170,7 @@ def smooth_blocks(semivariogram_model: TheoreticalVariogram,
                   data_crs=None,
                   raise_when_negative_prediction=True,
                   raise_when_negative_error=True,
+                  negative_prediction_to_zero=False,
                   verbose=True) -> gpd.GeoDataFrame:
     """
     Function smooths aggregated block values, and transform those into
@@ -191,6 +197,9 @@ def smooth_blocks(semivariogram_model: TheoreticalVariogram,
     raise_when_negative_error : bool, default=True
         Raise error when prediction error is negative.
 
+    negative_prediction_to_zero : bool, default=False
+        When predicted value is below zero then set it to zero.
+
     verbose : bool, default=True
         Show progress bar
 
@@ -276,7 +285,8 @@ def smooth_blocks(semivariogram_model: TheoreticalVariogram,
         number_of_neighbors=number_of_neighbors,
         data_crs=data_crs,
         raise_when_negative_prediction=raise_when_negative_prediction,
-        raise_when_negative_error=raise_when_negative_error
+        raise_when_negative_error=raise_when_negative_error,
+        negative_prediction_to_zero=negative_prediction_to_zero
     )
     return parsed
 
@@ -423,7 +433,8 @@ def regularize(self,
                    number_of_neighbors,
                    data_crs=None,
                    raise_when_negative_prediction=True,
-                   raise_when_negative_error=True) -> gpd.GeoDataFrame:
+                   raise_when_negative_error=True,
+                   negative_prediction_to_zero: bool = False) -> gpd.GeoDataFrame:
         """
         Function regularizes whole dataset and creates new values and error
         maps based on the kriging type. Function does not predict unknown
@@ -444,6 +455,9 @@ def regularize(self,
         raise_when_negative_error : bool, default=True
             Raise error when prediction error is negative.
 
+        negative_prediction_to_zero : bool, default=False
+            When predicted value is below zero then set it to zero.
+
         Returns
         -------
         regularized : gpd.GeoDataFrame
@@ -460,7 +474,8 @@ def regularize(self,
                 uid=block_id,
                 n_neighbours=number_of_neighbors,
                 pred_raise=raise_when_negative_prediction,
-                err_raise=raise_when_negative_error
+                err_raise=raise_when_negative_error,
+                negative_prediction_to_zero=negative_prediction_to_zero
             )
 
             interpolation_results.extend(
@@ -502,7 +517,12 @@ def _check_given_kriging_type(self, k_type):
 
         return k_type
 
-    def _interpolate(self, uid, n_neighbours, pred_raise, err_raise) -> Dict:
+    def _interpolate(self,
+                     uid,
+                     n_neighbours,
+                     pred_raise,
+                     err_raise,
+                     negative_prediction_to_zero) -> Dict:
         """
         Function interpolates block values using one of Poisson Kriging types.
 
@@ -520,6 +540,9 @@ def _interpolate(self, uid, n_neighbours, pred_raise, err_raise) -> Dict:
         err_raise : bool
             Raise error when prediction error is negative.
 
+        negative_prediction_to_zero : bool
+            When predicted value is below zero then set it to zero.
+
         Returns
         -------
         : dict
@@ -539,7 +562,8 @@ def _interpolate(self, uid, n_neighbours, pred_raise, err_raise) -> Dict:
                                            unknown_block_index=uid,
                                            number_of_neighbors=n_neighbours,
                                            raise_when_negative_error=err_raise,
-                                           raise_when_negative_prediction=pred_raise)
+                                           raise_when_negative_prediction=pred_raise,
+                                           negative_prediction_to_zero=negative_prediction_to_zero)
 
         elif self.kriging_type == 'atp':
             model_output = area_to_point_pk(semivariogram_model=self.semivariogram_model,
@@ -547,14 +571,16 @@ def _interpolate(self, uid, n_neighbours, pred_raise, err_raise) -> Dict:
                                             unknown_block_index=uid,
                                             number_of_neighbors=n_neighbours,
                                             raise_when_negative_prediction=pred_raise,
-                                            raise_when_negative_error=err_raise)
+                                            raise_when_negative_error=err_raise,
+                                            negative_prediction_to_zero=negative_prediction_to_zero)
         elif self.kriging_type == 'cb':
             model_output = centroid_poisson_kriging(semivariogram_model=self.semivariogram_model,
                                                     point_support=self.point_support,
                                                     unknown_block_index=uid,
                                                     number_of_neighbors=n_neighbours,
                                                     raise_when_negative_prediction=pred_raise,
-                                                    raise_when_negative_error=err_raise)
+                                                    raise_when_negative_error=err_raise,
+                                                    negative_prediction_to_zero=negative_prediction_to_zero)
         else:
             self._raise_wrong_kriging_type_error()
 
diff --git a/src/pyinterpolate/kriging/block/area_to_area_poisson_kriging.py b/src/pyinterpolate/kriging/block/area_to_area_poisson_kriging.py
index fbdfef4b..19441824 100644
--- a/src/pyinterpolate/kriging/block/area_to_area_poisson_kriging.py
+++ b/src/pyinterpolate/kriging/block/area_to_area_poisson_kriging.py
@@ -24,7 +24,8 @@ def area_to_area_pk(semivariogram_model: TheoreticalVariogram,
                     number_of_neighbors: int,
                     neighbors_range: float = None,
                     raise_when_negative_prediction=True,
-                    raise_when_negative_error=True) -> dict:
+                    raise_when_negative_error=True,
+                    negative_prediction_to_zero=False) -> dict:
     """
     Function predicts areal value in an unknown location based on
     the area-to-area Poisson Kriging
@@ -54,6 +55,9 @@ def area_to_area_pk(semivariogram_model: TheoreticalVariogram,
     raise_when_negative_error : bool, default=True
         Raise error when prediction error is negative.
 
+    negative_prediction_to_zero : bool, default=False
+        While prediction is negative, then set it to 0.
+
     Returns
     -------
     results : Dict
@@ -213,6 +217,8 @@ def area_to_area_pk(semivariogram_model: TheoreticalVariogram,
                              f'not be lower than 0. Check your sampling '
                              f'grid, samples, number of neighbors or '
                              f'semivariogram model type.')
+        if negative_prediction_to_zero:
+            zhat = 0
 
     sigmasq = np.matmul(w.T, covars)
 
diff --git a/src/pyinterpolate/kriging/block/area_to_point_poisson_kriging.py b/src/pyinterpolate/kriging/block/area_to_point_poisson_kriging.py
index cecdf2a2..f6ccb300 100644
--- a/src/pyinterpolate/kriging/block/area_to_point_poisson_kriging.py
+++ b/src/pyinterpolate/kriging/block/area_to_point_poisson_kriging.py
@@ -13,8 +13,10 @@
 from pyinterpolate.kriging.block.weights import pk_weights_array
 from pyinterpolate.semivariogram.deconvolution.block_to_block_semivariance import \
     weighted_avg_point_support_semivariances
-from pyinterpolate.semivariogram.theoretical.classes.theoretical_variogram import TheoreticalVariogram
-from pyinterpolate.transform.select_poisson_kriging_data import select_poisson_kriging_data
+from pyinterpolate.semivariogram.theoretical.classes.theoretical_variogram import \
+    TheoreticalVariogram
+from pyinterpolate.transform.select_poisson_kriging_data import \
+    select_poisson_kriging_data
 from pyinterpolate.transform.statistical import sem_to_cov
 from pyinterpolate.transform.transform import add_ones
 
@@ -26,7 +28,8 @@ def area_to_point_pk(semivariogram_model: TheoreticalVariogram,
                      neighbors_range: float = None,
                      raise_when_negative_prediction=True,
                      raise_when_negative_error=True,
-                     err_to_nan=True):
+                     err_to_nan=True,
+                     negative_prediction_to_zero=False):
     """
     Function predicts point-support value in the unknown location based on
     the area-to-point Poisson Kriging
@@ -60,6 +63,9 @@ def area_to_point_pk(semivariogram_model: TheoreticalVariogram,
         When point interpolation returns ``ValueError`` then set prediction
         or variance error to ``NaN``.
 
+    negative_prediction_to_zero : bool, default=False
+        While prediction is negative, then set it to 0.
+
     Returns
     -------
     results : Dict[numpy array]
@@ -261,16 +267,21 @@ def area_to_point_pk(semivariogram_model: TheoreticalVariogram,
 
         if zhat < 0:
             if raise_when_negative_prediction:
-                if err_to_nan:
-                    predicted_points.append(
-                        [upoint[0], upoint[1], np.nan, np.nan]
-                    )
-                    continue
-                else:
-                    raise ValueError(f'Predicted value is {zhat} and it '
-                                     f'should not be lower than 0. Check your '
-                                     f'sampling grid, samples, number of '
-                                     f'neighbors or semivariogram model type.')
+                raise ValueError(f'Predicted value is {zhat} and it '
+                                 f'should not be lower than 0. Check your '
+                                 f'sampling grid, samples, number of '
+                                 f'neighbors or semivariogram model type.')
+            if err_to_nan:
+                predicted_points.append(
+                    [upoint[0], upoint[1], np.nan, np.nan]
+                )
+                continue
+
+            if negative_prediction_to_zero:
+                predicted_points.append(
+                    [upoint[0], upoint[1], 0, np.nan]
+                )
+                continue
 
         point_pop = upoint[2]
         zhat = (zhat * point_pop) / tot_unknown_value
@@ -282,17 +293,16 @@ def area_to_point_pk(semivariogram_model: TheoreticalVariogram,
 
         if sigmasq < 0:
             if raise_when_negative_error:
-                if err_to_nan:
-                    predicted_points.append(
-                        [upoint[0], upoint[1], zhat, np.nan]
-                    )
-                    continue
-                else:
-                    raise ValueError(f'Predicted error value is {sigmasq} and '
-                                     f'it should not be lower than 0. '
-                                     f'Check your sampling grid, samples, '
-                                     f'number of neighbors or semivariogram '
-                                     f'model type.')
+                raise ValueError(f'Predicted error value is {sigmasq} and '
+                                 f'it should not be lower than 0. '
+                                 f'Check your sampling grid, samples, '
+                                 f'number of neighbors or semivariogram '
+                                 f'model type.')
+            if err_to_nan:
+                predicted_points.append(
+                    [upoint[0], upoint[1], zhat, np.nan]
+                )
+                continue
             else:
                 sigma = 0
         else:
diff --git a/src/pyinterpolate/kriging/block/centroid_based_poisson_kriging.py b/src/pyinterpolate/kriging/block/centroid_based_poisson_kriging.py
index 6c4ddec5..1d403ac9 100644
--- a/src/pyinterpolate/kriging/block/centroid_based_poisson_kriging.py
+++ b/src/pyinterpolate/kriging/block/centroid_based_poisson_kriging.py
@@ -25,7 +25,8 @@ def centroid_poisson_kriging(semivariogram_model: TheoreticalVariogram,
                              is_weighted_by_point_support=True,
                              raise_when_negative_prediction=True,
                              raise_when_negative_error=True,
-                             allow_lsa=False) -> Dict:
+                             allow_lsa=False,
+                             negative_prediction_to_zero=False) -> Dict:
     """
     Function performs centroid-based Poisson Kriging of blocks (areal) data.
 
@@ -64,6 +65,9 @@ def centroid_poisson_kriging(semivariogram_model: TheoreticalVariogram,
         when you have clusters in your dataset,
         that can lead to singular or near-singular matrix creation.
 
+    negative_prediction_to_zero : bool, default=False
+        While prediction is negative, then set it to 0.
+
     Returns
     -------
     results : Dict
@@ -207,6 +211,9 @@ def centroid_poisson_kriging(semivariogram_model: TheoreticalVariogram,
                              f'grid, samples, number of neighbors or '
                              f'semivariogram model type.')
 
+        if negative_prediction_to_zero:
+            zhat = 0
+
     sigmasq = np.matmul(output_weights.T, covars)
 
     if sigmasq < 0:
diff --git a/tests/test_core/test_smooth_blocks.py b/tests/test_core/test_smooth_blocks.py
index 81413da4..29f10d7f 100644
--- a/tests/test_core/test_smooth_blocks.py
+++ b/tests/test_core/test_smooth_blocks.py
@@ -36,8 +36,12 @@ def test_smooth_blocks():
         semivariogram_model=THEO,
         point_support=PS,
         number_of_neighbors=8,
+        raise_when_negative_prediction=True,
+        raise_when_negative_error=False,
+        negative_prediction_to_zero=False,
         verbose=True
     )
+    smoothed: gpd.GeoDataFrame
     print(smoothed.columns)
     assert isinstance(smoothed, gpd.GeoDataFrame)
 
diff --git a/tutorials/functional/1-1-semivariogram-exploration.ipynb b/tutorials/functional/1-1-semivariogram-exploration.ipynb
index cd2c8a9c..8e88de51 100644
--- a/tutorials/functional/1-1-semivariogram-exploration.ipynb
+++ b/tutorials/functional/1-1-semivariogram-exploration.ipynb
@@ -79,8 +79,8 @@
    "id": "initial_id",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:30.426177Z",
-     "start_time": "2025-12-21T14:55:30.422208Z"
+     "end_time": "2026-02-20T11:30:53.029114Z",
+     "start_time": "2026-02-20T11:30:49.649175Z"
     }
    },
    "source": [
@@ -93,7 +93,7 @@
     "from pyinterpolate import reproject_flat, ExperimentalVariogram, build_theoretical_variogram, TheoreticalVariogram"
    ],
    "outputs": [],
-   "execution_count": 42
+   "execution_count": 1
   },
   {
    "cell_type": "markdown",
@@ -117,15 +117,15 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:30.544635Z",
-     "start_time": "2025-12-21T14:55:30.541497Z"
+     "end_time": "2026-02-20T11:30:53.265233Z",
+     "start_time": "2026-02-20T11:30:53.262569Z"
     }
    },
    "source": [
     "DEM_FILE = '../data/dem.csv'"
    ],
    "outputs": [],
-   "execution_count": 43
+   "execution_count": 2
   },
   {
    "cell_type": "code",
@@ -136,8 +136,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:30.670373Z",
-     "start_time": "2025-12-21T14:55:30.651236Z"
+     "end_time": "2026-02-20T11:30:53.306219Z",
+     "start_time": "2026-02-20T11:30:53.282888Z"
     }
    },
    "source": [
@@ -215,12 +215,12 @@
        "</div>"
       ]
      },
-     "execution_count": 44,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
-   "execution_count": 44
+   "execution_count": 3
   },
   {
    "cell_type": "markdown",
@@ -246,8 +246,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:30.974252Z",
-     "start_time": "2025-12-21T14:55:30.826064Z"
+     "end_time": "2026-02-20T11:30:53.648247Z",
+     "start_time": "2026-02-20T11:30:53.510065Z"
     }
    },
    "source": [
@@ -260,7 +260,7 @@
     ")"
    ],
    "outputs": [],
-   "execution_count": 45
+   "execution_count": 4
   },
   {
    "cell_type": "code",
@@ -271,8 +271,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:31.172320Z",
-     "start_time": "2025-12-21T14:55:31.163548Z"
+     "end_time": "2026-02-20T11:30:53.695208Z",
+     "start_time": "2026-02-20T11:30:53.686564Z"
     }
    },
    "source": [
@@ -349,12 +349,12 @@
        "</div>"
       ]
      },
-     "execution_count": 46,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
-   "execution_count": 46
+   "execution_count": 5
   },
   {
    "cell_type": "markdown",
@@ -378,8 +378,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:32.147209Z",
-     "start_time": "2025-12-21T14:55:31.396151Z"
+     "end_time": "2026-02-20T11:30:54.548812Z",
+     "start_time": "2026-02-20T11:30:53.766025Z"
     }
    },
    "source": [
@@ -400,7 +400,7 @@
      "output_type": "display_data"
     }
    ],
-   "execution_count": 47
+   "execution_count": 6
   },
   {
    "cell_type": "markdown",
@@ -424,8 +424,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:32.404771Z",
-     "start_time": "2025-12-21T14:55:32.233775Z"
+     "end_time": "2026-02-20T11:30:54.766874Z",
+     "start_time": "2026-02-20T11:30:54.595106Z"
     }
    },
    "source": [
@@ -438,13 +438,13 @@
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ],
-      "image/png": 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"
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"
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
-   "execution_count": 48
+   "execution_count": 7
   },
   {
    "cell_type": "markdown",
@@ -489,8 +489,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:32.510625Z",
-     "start_time": "2025-12-21T14:55:32.504509Z"
+     "end_time": "2026-02-20T11:30:54.802636Z",
+     "start_time": "2026-02-20T11:30:54.798065Z"
     }
    },
    "source": [
@@ -503,7 +503,7 @@
     "ds = sample[['longitude', 'latitude', 'dem']]"
    ],
    "outputs": [],
-   "execution_count": 49
+   "execution_count": 8
   },
   {
    "cell_type": "code",
@@ -514,8 +514,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:32.626141Z",
-     "start_time": "2025-12-21T14:55:32.605552Z"
+     "end_time": "2026-02-20T11:30:54.853674Z",
+     "start_time": "2026-02-20T11:30:54.831150Z"
     }
    },
    "source": [
@@ -529,7 +529,7 @@
     ") "
    ],
    "outputs": [],
-   "execution_count": 50
+   "execution_count": 9
   },
   {
    "cell_type": "markdown",
@@ -564,8 +564,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:32.733098Z",
-     "start_time": "2025-12-21T14:55:32.726737Z"
+     "end_time": "2026-02-20T11:30:54.882434Z",
+     "start_time": "2026-02-20T11:30:54.876604Z"
     }
    },
    "source": [
@@ -579,30 +579,30 @@
       "+---------+--------------------+---------------------+\n",
       "|   lag   |    semivariance    |      covariance     |\n",
       "+---------+--------------------+---------------------+\n",
-      "|  1000.0 | 66.71388540855338  |  378.36063443979623 |\n",
-      "|  2000.0 | 130.66628344322854 |  321.7000533191133  |\n",
-      "|  3000.0 | 377.5405401178886  |  150.76532645491605 |\n",
-      "|  4000.0 | 250.66718626708865 |  252.71512355654235 |\n",
-      "|  5000.0 | 325.5561456427749  |  133.18403989988315 |\n",
-      "|  6000.0 | 387.4814906048632  |  30.731695978081564 |\n",
-      "|  7000.0 | 302.07493544556206 |  49.092832725093004 |\n",
-      "|  8000.0 | 469.53885776562294 |  -62.21223171644848 |\n",
-      "|  9000.0 | 486.79931370125183 |  -83.13560908274104 |\n",
-      "| 10000.0 | 512.0646265352149  | -119.11920214846046 |\n",
-      "| 11000.0 |  529.991767276145  |  -76.66066356407669 |\n",
-      "| 12000.0 | 582.4717932210419  |  -80.88872027056644 |\n",
-      "| 13000.0 |  692.506923505966  | -185.99762744031003 |\n",
-      "| 14000.0 | 649.5775483966735  |  -129.2268505373204 |\n",
-      "| 15000.0 | 624.8696046337229  | -151.08544277438932 |\n",
-      "| 16000.0 |  643.74627487684   | -135.27647734328391 |\n",
-      "| 17000.0 | 571.3688648923311  | -127.91473349841077 |\n",
-      "| 18000.0 | 540.0470107890337  | -123.14348266241309 |\n",
-      "| 19000.0 | 600.2575887426275  | -153.57635203377805 |\n",
+      "|  1000.0 | 57.836141811479614 |  281.26015594147054 |\n",
+      "|  2000.0 | 86.03437765640514  |  333.94029160019153 |\n",
+      "|  3000.0 | 236.60954497912823 |  168.78259767256887 |\n",
+      "|  4000.0 | 268.7197011214077  |  171.01160804311107 |\n",
+      "|  5000.0 | 216.77470366578342 |  158.33681920551547 |\n",
+      "|  6000.0 | 294.4056440278582  |  57.97311676110505  |\n",
+      "|  7000.0 | 383.72288068192313 |  -28.74193163710372 |\n",
+      "|  8000.0 | 378.7119931185135  |  -47.48412568639648 |\n",
+      "|  9000.0 |  483.465464109033  | -63.574331830829244 |\n",
+      "| 10000.0 | 452.9072205931408  | -43.483690056838746 |\n",
+      "| 11000.0 | 412.07362484342366 | -16.707909354888148 |\n",
+      "| 12000.0 | 491.23925913297296 | -36.920866153150655 |\n",
+      "| 13000.0 | 577.2518572511536  | -130.35128920146093 |\n",
+      "| 14000.0 | 575.1348087672814  |  -99.41651006818448 |\n",
+      "| 15000.0 | 633.2991501319548  |  -140.3010201075645 |\n",
+      "| 16000.0 | 659.1799840204877  | -186.55066903588772 |\n",
+      "| 17000.0 |  641.201731691203  |  -199.5009323022728 |\n",
+      "| 18000.0 | 500.6074586569037  | -122.15320890737334 |\n",
+      "| 19000.0 | 448.75860119019325 |  -86.4378021576186  |\n",
       "+---------+--------------------+---------------------+\n"
      ]
     }
    ],
-   "execution_count": 51
+   "execution_count": 10
   },
   {
    "cell_type": "markdown",
@@ -630,8 +630,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:33.058115Z",
-     "start_time": "2025-12-21T14:55:32.897852Z"
+     "end_time": "2026-02-20T11:30:55.114998Z",
+     "start_time": "2026-02-20T11:30:54.953641Z"
     }
    },
    "source": [
@@ -647,13 +647,13 @@
       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ],
-      "image/png": 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"
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"
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
-   "execution_count": 52
+   "execution_count": 11
   },
   {
    "cell_type": "markdown",
@@ -736,8 +736,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:33.216238Z",
-     "start_time": "2025-12-21T14:55:33.211992Z"
+     "end_time": "2026-02-20T11:30:55.141150Z",
+     "start_time": "2026-02-20T11:30:55.138381Z"
     }
    },
    "source": [
@@ -746,7 +746,7 @@
     "variogram_range = 8000"
    ],
    "outputs": [],
-   "execution_count": 53
+   "execution_count": 12
   },
   {
    "cell_type": "code",
@@ -757,8 +757,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:33.312653Z",
-     "start_time": "2025-12-21T14:55:33.308305Z"
+     "end_time": "2026-02-20T11:30:55.170467Z",
+     "start_time": "2026-02-20T11:30:55.166906Z"
     }
    },
    "source": [
@@ -771,7 +771,7 @@
     "                                             nugget=nugget)"
    ],
    "outputs": [],
-   "execution_count": 54
+   "execution_count": 13
   },
   {
    "cell_type": "code",
@@ -782,8 +782,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:33.392081Z",
-     "start_time": "2025-12-21T14:55:33.385051Z"
+     "end_time": "2026-02-20T11:30:55.212049Z",
+     "start_time": "2026-02-20T11:30:55.206211Z"
     }
    },
    "source": [
@@ -796,41 +796,41 @@
      "text": [
       "* Selected model: Circular model\n",
       "* Nugget: 0\n",
-      "* Sill: 478.90567078851103\n",
+      "* Sill: 415.1536596743022\n",
       "* Range: 8000\n",
       "* Spatial Dependency Strength is Undefined: nugget equal to 0, cannot estimate\n",
       "* Mean Bias: None\n",
-      "* Mean RMSE: 106.4369154595279\n",
+      "* Mean RMSE: 114.23438788269483\n",
       "* Error-lag weighting method: equal\n",
       "\n",
       "\n",
-      "+---------+--------------------+--------------------+---------------------+\n",
-      "|   lag   |    theoretical     |    experimental    |   bias (real-yhat)  |\n",
-      "+---------+--------------------+--------------------+---------------------+\n",
-      "|  1000.0 | 76.02124683696297  | 66.71388540855338  |  -9.307361428409592 |\n",
-      "|  2000.0 | 150.8372591039797  | 130.66628344322854 | -20.170975660751168 |\n",
-      "|  3000.0 | 223.18223486037513 | 377.5405401178886  |  154.35830525751348 |\n",
-      "|  4000.0 | 291.65249083970144 | 250.66718626708865 |  -40.98530457261279 |\n",
-      "|  5000.0 | 354.58310049417867 | 325.5561456427749  | -29.026954851403787 |\n",
-      "|  6000.0 | 409.8026413531391  | 387.4814906048632  | -22.321150748275898 |\n",
-      "|  7000.0 | 453.9807623558251  | 302.07493544556206 | -151.90582691026304 |\n",
-      "|  8000.0 | 478.90567078851103 | 469.53885776562294 |  -9.366813022888095 |\n",
-      "|  9000.0 | 478.90567078851103 | 486.79931370125183 |  7.893642912740802  |\n",
-      "| 10000.0 | 478.90567078851103 | 512.0646265352149  |  33.15895574670384  |\n",
-      "| 11000.0 | 478.90567078851103 |  529.991767276145  |  51.08609648763394  |\n",
-      "| 12000.0 | 478.90567078851103 | 582.4717932210419  |  103.5661224325309  |\n",
-      "| 13000.0 | 478.90567078851103 |  692.506923505966  |   213.601252717455  |\n",
-      "| 14000.0 | 478.90567078851103 | 649.5775483966735  |  170.67187760816245 |\n",
-      "| 15000.0 | 478.90567078851103 | 624.8696046337229  |  145.9639338452119  |\n",
-      "| 16000.0 | 478.90567078851103 |  643.74627487684   |  164.84060408832892 |\n",
-      "| 17000.0 | 478.90567078851103 | 571.3688648923311  |  92.46319410382006  |\n",
-      "| 18000.0 | 478.90567078851103 | 540.0470107890337  |  61.14134000052269  |\n",
-      "| 19000.0 | 478.90567078851103 | 600.2575887426275  |  121.35191795411646 |\n",
-      "+---------+--------------------+--------------------+---------------------+\n"
+      "+---------+--------------------+--------------------+--------------------+\n",
+      "|   lag   |    theoretical     |    experimental    |  bias (real-yhat)  |\n",
+      "+---------+--------------------+--------------------+--------------------+\n",
+      "|  1000.0 | 65.90128445421153  | 57.836141811479614 | -8.06514264273192  |\n",
+      "|  2000.0 | 130.7577753864434  | 86.03437765640514  | -44.72339773003826 |\n",
+      "|  3000.0 | 193.4721746435356  | 236.60954497912823 | 43.137370335592635 |\n",
+      "|  4000.0 | 252.82765753404124 | 268.7197011214077  | 15.892043587366459 |\n",
+      "|  5000.0 | 307.3809328389156  | 216.77470366578342 | -90.60622917313219 |\n",
+      "|  6000.0 | 355.24963824678247 | 294.4056440278582  | -60.84399421892425 |\n",
+      "|  7000.0 | 393.54675964357347 | 383.72288068192313 | -9.823878961650337 |\n",
+      "|  8000.0 | 415.1536596743022  | 378.7119931185135  | -36.44166655578874 |\n",
+      "|  9000.0 | 415.1536596743022  |  483.465464109033  | 68.31180443473079  |\n",
+      "| 10000.0 | 415.1536596743022  | 452.9072205931408  | 37.75356091883856  |\n",
+      "| 11000.0 | 415.1536596743022  | 412.07362484342366 | -3.08003483087856  |\n",
+      "| 12000.0 | 415.1536596743022  | 491.23925913297296 | 76.08559945867074  |\n",
+      "| 13000.0 | 415.1536596743022  | 577.2518572511536  | 162.09819757685142 |\n",
+      "| 14000.0 | 415.1536596743022  | 575.1348087672814  | 159.98114909297914 |\n",
+      "| 15000.0 | 415.1536596743022  | 633.2991501319548  | 218.14549045765256 |\n",
+      "| 16000.0 | 415.1536596743022  | 659.1799840204877  | 244.0263243461855  |\n",
+      "| 17000.0 | 415.1536596743022  |  641.201731691203  | 226.0480720169008  |\n",
+      "| 18000.0 | 415.1536596743022  | 500.6074586569037  | 85.45379898260148  |\n",
+      "| 19000.0 | 415.1536596743022  | 448.75860119019325 | 33.60494151589103  |\n",
+      "+---------+--------------------+--------------------+--------------------+\n"
      ]
     }
    ],
-   "execution_count": 55
+   "execution_count": 14
   },
   {
    "cell_type": "code",
@@ -841,8 +841,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:33.633059Z",
-     "start_time": "2025-12-21T14:55:33.472823Z"
+     "end_time": "2026-02-20T11:30:55.383750Z",
+     "start_time": "2026-02-20T11:30:55.249342Z"
     }
    },
    "source": [
@@ -854,13 +854,13 @@
       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ],
-      "image/png": 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"
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"
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
-   "execution_count": 56
+   "execution_count": 15
   },
   {
    "cell_type": "code",
@@ -871,8 +871,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:33.743775Z",
-     "start_time": "2025-12-21T14:55:33.738473Z"
+     "end_time": "2026-02-20T11:30:55.415024Z",
+     "start_time": "2026-02-20T11:30:55.410071Z"
     }
    },
    "source": [
@@ -885,7 +885,7 @@
     "                                          nugget=nugget)"
    ],
    "outputs": [],
-   "execution_count": 57
+   "execution_count": 16
   },
   {
    "cell_type": "code",
@@ -896,8 +896,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:33.879918Z",
-     "start_time": "2025-12-21T14:55:33.872679Z"
+     "end_time": "2026-02-20T11:30:55.470933Z",
+     "start_time": "2026-02-20T11:30:55.464766Z"
     }
    },
    "source": [
@@ -910,41 +910,41 @@
      "text": [
       "* Selected model: Cubic model\n",
       "* Nugget: 0\n",
-      "* Sill: 478.90567078851103\n",
+      "* Sill: 415.1536596743022\n",
       "* Range: 8000\n",
       "* Spatial Dependency Strength is Undefined: nugget equal to 0, cannot estimate\n",
       "* Mean Bias: None\n",
-      "* Mean RMSE: 112.51542324377124\n",
+      "* Mean RMSE: 120.17733788327587\n",
       "* Error-lag weighting method: equal\n",
       "\n",
       "\n",
       "+---------+--------------------+--------------------+---------------------+\n",
       "|   lag   |    theoretical     |    experimental    |   bias (real-yhat)  |\n",
       "+---------+--------------------+--------------------+---------------------+\n",
-      "|  1000.0 | 44.24686603199425  | 66.71388540855338  |  22.46701937655913  |\n",
-      "|  2000.0 | 145.66080834697556 | 130.66628344322854 |  -14.99452490374702 |\n",
-      "|  3000.0 | 262.4988714324439  | 377.5405401178886  |  115.04166868544473 |\n",
-      "|  4000.0 | 363.8560662826773  | 250.66718626708865 | -113.18888001558867 |\n",
-      "|  5000.0 | 432.92635147156795 | 325.5561456427749  | -107.37020582879308 |\n",
-      "|  6000.0 | 467.67401160879393 | 387.4814906048632  |  -80.19252100393072 |\n",
-      "|  7000.0 | 478.0522323071066  | 302.07493544556206 | -175.97729686154452 |\n",
-      "|  8000.0 | 478.90567078851103 | 469.53885776562294 |  -9.366813022888095 |\n",
-      "|  9000.0 | 478.90567078851103 | 486.79931370125183 |  7.893642912740802  |\n",
-      "| 10000.0 | 478.90567078851103 | 512.0646265352149  |  33.15895574670384  |\n",
-      "| 11000.0 | 478.90567078851103 |  529.991767276145  |  51.08609648763394  |\n",
-      "| 12000.0 | 478.90567078851103 | 582.4717932210419  |  103.5661224325309  |\n",
-      "| 13000.0 | 478.90567078851103 |  692.506923505966  |   213.601252717455  |\n",
-      "| 14000.0 | 478.90567078851103 | 649.5775483966735  |  170.67187760816245 |\n",
-      "| 15000.0 | 478.90567078851103 | 624.8696046337229  |  145.9639338452119  |\n",
-      "| 16000.0 | 478.90567078851103 |  643.74627487684   |  164.84060408832892 |\n",
-      "| 17000.0 | 478.90567078851103 | 571.3688648923311  |  92.46319410382006  |\n",
-      "| 18000.0 | 478.90567078851103 | 540.0470107890337  |  61.14134000052269  |\n",
-      "| 19000.0 | 478.90567078851103 | 600.2575887426275  |  121.35191795411646 |\n",
+      "|  1000.0 |  38.3567150751343  | 57.836141811479614 |  19.479426736345317 |\n",
+      "|  2000.0 | 126.27041470776163 | 86.03437765640514  |  -40.23603705135649 |\n",
+      "|  3000.0 | 227.55497331264343 | 236.60954497912823 |  9.054571666484804  |\n",
+      "|  4000.0 | 315.4194797134835  | 268.7197011214077  |  -46.6997785920758  |\n",
+      "|  5000.0 | 375.2951158146453  | 216.77470366578342 |  -158.5204121488619 |\n",
+      "|  6000.0 | 405.41716103356424 | 294.4056440278582  | -111.01151700570603 |\n",
+      "|  7000.0 | 414.41383108075354 | 383.72288068192313 |  -30.69095039883041 |\n",
+      "|  8000.0 | 415.1536596743022  | 378.7119931185135  |  -36.44166655578874 |\n",
+      "|  9000.0 | 415.1536596743022  |  483.465464109033  |  68.31180443473079  |\n",
+      "| 10000.0 | 415.1536596743022  | 452.9072205931408  |  37.75356091883856  |\n",
+      "| 11000.0 | 415.1536596743022  | 412.07362484342366 |  -3.08003483087856  |\n",
+      "| 12000.0 | 415.1536596743022  | 491.23925913297296 |  76.08559945867074  |\n",
+      "| 13000.0 | 415.1536596743022  | 577.2518572511536  |  162.09819757685142 |\n",
+      "| 14000.0 | 415.1536596743022  | 575.1348087672814  |  159.98114909297914 |\n",
+      "| 15000.0 | 415.1536596743022  | 633.2991501319548  |  218.14549045765256 |\n",
+      "| 16000.0 | 415.1536596743022  | 659.1799840204877  |  244.0263243461855  |\n",
+      "| 17000.0 | 415.1536596743022  |  641.201731691203  |  226.0480720169008  |\n",
+      "| 18000.0 | 415.1536596743022  | 500.6074586569037  |  85.45379898260148  |\n",
+      "| 19000.0 | 415.1536596743022  | 448.75860119019325 |  33.60494151589103  |\n",
       "+---------+--------------------+--------------------+---------------------+\n"
      ]
     }
    ],
-   "execution_count": 58
+   "execution_count": 17
   },
   {
    "cell_type": "code",
@@ -955,8 +955,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:34.162619Z",
-     "start_time": "2025-12-21T14:55:34.000302Z"
+     "end_time": "2026-02-20T11:30:55.665186Z",
+     "start_time": "2026-02-20T11:30:55.541714Z"
     }
    },
    "source": [
@@ -968,13 +968,13 @@
       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ],
-      "image/png": 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"
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"
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
-   "execution_count": 59
+   "execution_count": 18
   },
   {
    "cell_type": "code",
@@ -985,8 +985,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:34.237973Z",
-     "start_time": "2025-12-21T14:55:34.230449Z"
+     "end_time": "2026-02-20T11:30:55.705271Z",
+     "start_time": "2026-02-20T11:30:55.699368Z"
     }
    },
    "source": [
@@ -1006,41 +1006,41 @@
      "text": [
       "* Selected model: Exponential model\n",
       "* Nugget: 0\n",
-      "* Sill: 478.90567078851103\n",
+      "* Sill: 415.1536596743022\n",
       "* Range: 8000\n",
       "* Spatial Dependency Strength is Undefined: nugget equal to 0, cannot estimate\n",
       "* Mean Bias: None\n",
-      "* Mean RMSE: 172.56017194999464\n",
+      "* Mean RMSE: 169.80926717230193\n",
       "* Error-lag weighting method: equal\n",
       "\n",
       "\n",
       "+---------+--------------------+--------------------+--------------------+\n",
       "|   lag   |    theoretical     |    experimental    |  bias (real-yhat)  |\n",
       "+---------+--------------------+--------------------+--------------------+\n",
-      "|  1000.0 | 56.27289968745207  | 66.71388540855338  | 10.440985721101313 |\n",
-      "|  2000.0 | 105.93355936108222 | 130.66628344322854 | 24.73272408214632  |\n",
-      "|  3000.0 | 149.7589377033685  | 377.5405401178886  | 227.7816024145201  |\n",
-      "|  4000.0 | 188.4346983450342  | 250.66718626708865 | 62.232487922054446 |\n",
-      "|  5000.0 | 222.56593731640734 | 325.5561456427749  | 102.99020832636754 |\n",
-      "|  6000.0 | 252.68664999001882 | 387.4814906048632  | 134.7948406148444  |\n",
-      "|  7000.0 | 279.26808562812147 | 302.07493544556206 | 22.806849817440593 |\n",
-      "|  8000.0 | 302.72612024499887 | 469.53885776562294 | 166.81273752062407 |\n",
-      "|  9000.0 | 323.42776313511536 | 486.79931370125183 | 163.37155056613648 |\n",
-      "| 10000.0 | 341.6968988640556  | 512.0646265352149  | 170.3677276711593  |\n",
-      "| 11000.0 | 357.81935455774294 |  529.991767276145  | 172.17241271840203 |\n",
-      "| 12000.0 | 372.04737176947935 | 582.4717932210419  | 210.42442145156258 |\n",
-      "| 13000.0 | 384.60355288875706 |  692.506923505966  | 307.90337061720896 |\n",
-      "| 14000.0 | 395.6843438348108  | 649.5775483966735  | 253.89320456186266 |\n",
-      "| 15000.0 | 405.4631075228907  | 624.8696046337229  | 219.40649711083222 |\n",
-      "| 16000.0 | 414.0928361887279  |  643.74627487684   | 229.65343868811203 |\n",
-      "| 17000.0 | 421.7085450064747  | 571.3688648923311  | 149.66031988585638 |\n",
-      "| 18000.0 | 428.4293844491225  | 540.0470107890337  | 111.61762633991123 |\n",
-      "| 19000.0 | 434.3605044400275  | 600.2575887426275  | 165.89708430259998 |\n",
+      "|  1000.0 | 48.781840915071236 | 57.836141811479614 | 9.054300896408378  |\n",
+      "|  2000.0 | 91.83166442499613  | 86.03437765640514  | -5.797286768590993 |\n",
+      "|  3000.0 | 129.82300032931832 | 236.60954497912823 | 106.78654464980991 |\n",
+      "|  4000.0 | 163.3502365899336  | 268.7197011214077  | 105.36946453147411 |\n",
+      "|  5000.0 | 192.9379187421485  | 216.77470366578342 | 23.836784923634923 |\n",
+      "|  6000.0 | 219.04895659613567 | 294.4056440278582  | 75.35668743172255  |\n",
+      "|  7000.0 | 242.09186662554845 | 383.72288068192313 | 141.63101405637468 |\n",
+      "|  8000.0 | 262.4271633530408  | 378.7119931185135  | 116.2848297654727  |\n",
+      "|  9000.0 | 280.37299972819136 |  483.465464109033  | 203.09246438084165 |\n",
+      "| 10000.0 | 296.2101447435517  | 452.9072205931408  | 156.69707584958905 |\n",
+      "| 11000.0 | 310.18637616539036 | 412.07362484342366 | 101.8872486780333  |\n",
+      "| 12000.0 | 322.52035710496847 | 491.23925913297296 | 168.7189020280045  |\n",
+      "| 13000.0 | 333.4050570806835  | 577.2518572511536  | 243.84680017047015 |\n",
+      "| 14000.0 | 343.0107710948147  | 575.1348087672814  | 232.12403767246667 |\n",
+      "| 15000.0 | 351.4877839593989  | 633.2991501319548  | 281.8113661725559  |\n",
+      "| 16000.0 | 358.96872155556423 | 659.1799840204877  | 300.2112624649235  |\n",
+      "| 17000.0 | 365.57062581260874 |  641.201731691203  | 275.63110587859427 |\n",
+      "| 18000.0 | 371.39678587061064 | 500.6074586569037  | 129.21067278629306 |\n",
+      "| 19000.0 | 376.5383540757594  | 448.75860119019325 | 72.22024711443385  |\n",
       "+---------+--------------------+--------------------+--------------------+\n"
      ]
     }
    ],
-   "execution_count": 60
+   "execution_count": 19
   },
   {
    "cell_type": "code",
@@ -1051,8 +1051,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:34.493978Z",
-     "start_time": "2025-12-21T14:55:34.333238Z"
+     "end_time": "2026-02-20T11:30:55.886604Z",
+     "start_time": "2026-02-20T11:30:55.757122Z"
     }
    },
    "source": [
@@ -1064,13 +1064,13 @@
       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ],
-      "image/png": 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tW7duleHDh1drO/Q9GzZs2EH7/va3v9l9GqABAADcSodjHyguClwYng1EFqrHRyENtn7//e9/5d5775WVK1cGtqWkpMj3338flrYVFBRIfHz8Md+/UaNGUt0aN24sX375pWzatEmaNm0a2P7iiy9K8+bNq709AAAAFUUl8+qjy7rpe6tF58obIu8RRzISU+1xwNGgpz0KabD1X9LT021vcPA2De1+CxYskD59+khSUpKceOKJIeFeffDBB9KrVy+pVauWtG7dWiZNmiRFRUWB/Rs2bJBzzz3XPmZaWppcdNFFsm3btoN6zJ9//nlp1aqVfRylw/J/97vfSYMGDez9zjjjDFm0aJHd9/LLL9vn0dv+0QG6rbzh8RqkL730Uqlbt64kJyfb1zJv3jy7b82aNbZtDRs2tO3r27evTJ8+/ajfz4yMDBkyZIi88sorgW1z5syRHTt2yIgRI0KO9Xq9cv/999twn5CQYF/7p59+GnLMd999Jz179rTvhbb3xx9/POg5ly5dakcUaLu1/VdeeaV9PgAAgIqiknn10nXY9cuQ+rVSbEAP2SeO3a77Wa8dR4vQfoxM4YFDX4oKK35sYUGFjq0qf/7zn+Xxxx+3Pe+xsbFyzTXXBPbNmjVLrrrqKrnllltk+fLl8txzz9nw/OCDDwYCqobiXbt2ycyZM2XatGnyyy+/yMUXXxzyHKtXr5b//e9/8u677wbmbV944YWSlZUln3zyif3iQL8YGDRokH0svf9tt90mnTt3tqMG9FL2MVVubq6ceuqpsnnzZvnwww9tyL/jjjtsu/z7zzrrLJkxY4YNxjrE/ZxzzrFfNBwtfV/8Xxz4e9kvv/zyg0YN/OMf/7Dv52OPPSaLFy+WoUOHym9+8xtZtWpVoE1nn322dOrUyb5u/VJj/PjxIY+hX2jolxga7PW8aOjXL0L0CxEAAICKoJJ5eOjohfHdB9se9WB6W7czugHHguHxx8j7zz8cemerrhJzXmmRMO8zY0WKQsN5QNP2EnPRHaXHPn+HSF7uQYfFjHtBqoIGcA2+6k9/+pPtOc7Pz7e9wNrbrdtGjx5t92tP+wMPPGCD8cSJE20YXrJkiaxdu1aaNWtmj/n3v/9tw/b8+fNtz7Z/SLxu11519c0339jeZg3t2hutNORqD/o777wj119/ve1h1i8RDjcc/vXXX5ft27fb59KedtWmTZvA/u7du9uLn7b9vffeswH/pptuOqr3SYP2DTfcIF9//bX07t1b3nrrLfs6NLwH09dx5513yiWXXGJv//Wvf7VD67XY3VNPPWXbrF8qvPDCC/Y91vdKRwuMGTMm8Bj/7//9PxvYH3roocA2fR59j3/++Wdp167dUbUdAADU3ErmhxJcyTwhhkhQmTSYT+w9IqRKvA6Jp4cdx4pPaA3XrVu3kLnbSsO0ztXWnuvZs2cHetZVcXGxDfX79++XFStW2CDpD+xKe5Br165t9/lDe4sWLQKBXenjao9zvXr1QtqSl5dnh7RXlPbaa7j1B/ay9Dm0J3vq1Km2t16H9etzHEtPe1xcnFxxxRXy0ksv2dEEGpyD3zuVk5MjW7ZskZNOOilku972D/3X90Xv558moAYMGBByvB6rQT94GoOfvj+EdgAAAHfTgM6XIags/J90jDw3P33onU7orAPPmMMtKVZmvsvvHpXqpGE00JKSb/+Ch5drb/v5559/0P2CQ+eR6FzzYPq4+gWBLjtXlgb+ikpMPPzwIh12rkP2tfdbe+D1+AsuuMD2/B8LHSLfr18/O988eBpBZdP3R4fxay99Wf4vVgAAAADUDIT2Y+TEJYT92Kqm88y1MF3wkPNgHTt2lI0bN9qLv7dd577rnGztcT/c42ZmZtrh77pOenl0rrj26h+O9lhrgTudB19eb7uOErj66qvlvPPOC4RhXRP9WOlQdr3oXPXLLrvsoP1aUK9Jkyb2ef1TDvztOOGEEwLv2X/+85/AFAT17bffHvT+aA0AfW/0PQIAADhaVDIHogeF6HBIulSczkXX3vZly5bZod1vvvmm3H333Xb/4MGDpWvXrrYg2w8//GDnqWvhOg2sWhX9UPR+OiR85MiR8vnnn9sgrdXYtSiefyk6Daw6V16HwGvV9AMHDi7Gp1Xjdc67Po4GYx22rmF37ty5dn/btm0Dxe90yLkGbf8ogmP1xRdf2KH2hxoRcPvtt9secl1qT7/w0JoA+vxazE9pG3REw3XXXWe/4Pj444/tSIBgN954o/0iQl+fztfXIfGfffaZ/Pa3vz3iFxkAAACKSuZA9CC045C08vmUKVNssNb56f3795cnnnjCzlFXGj51Sbg6derIKaecYsO4FqvTwHo4ej8Nq3ofDaI6R1sLt61fv94ub6ZGjRplq72ffvrpdj78G2+8UW5vvLZNl2TTKvH6BcIjjzwiMTG+b4wnT55s26ZL2elwc3092ov9a+hQ/8MN4f/jH/8o48aNs9XvtT1a+V0L3+kXCErnqX/00Ue2gJ/Ox9cvKsoOg/f31mtA16Xm9HHGjh1rn9fj4SMLAAAqhkrmQHRwjGGdBy0gpuuZZ2dn2yHOwXQYs/b4Bq8xDiA68PkGANQEuqwblcyByMqhwZgwCwAAAEQxKpkDkY2xtgAAAAAAuBShHQAAAAAAlyK0AwAAAADgUoR2AAAAAABcitBeQRTZB6IPn2sAAAC4HaH9CPxrfhcUFIS7KQAqmf9z7f+cAwAAAG7D2g9HEBsbK0lJSbJ9+3aJi4sTj4fvOYBo4PV67edaP9/6OQcAAADciL9Uj8BxHGncuLGsXbtW1q9fH+7mAKhE+iVc8+bN7eccAAAAcCNCewXEx8dL27ZtGSIPROFnm9EzAAAAcDNCewXpH/a1atUKdzMAAAAAADUIXUwAAAAAALhU2EP75s2b5YorrpB69epJYmKidO3aVb7//vuQJZnuvfdeO69c9w8ePFhWrVoV8hi7du2Syy+/XNLS0qR27dpy7bXXSm5ubhheDQAAAAAAURLad+/eLSeddJKtyv7JJ5/I8uXL5fHHH5c6deoEjnn00UflySeflGeffVbmzZsnycnJMnToUMnPzw8co4F92bJlMm3aNJkyZYp8/fXXcv3114fpVQEAAAAAUDkco13ZYfKnP/1JZs+eLbNmzSp3vzatSZMmctttt8n48ePttuzsbGnYsKG8/PLLcskll8iKFSukU6dOMn/+fOnTp4895tNPP5WzzjpLNm3aZO9/JDk5OZKenm4fW3vrAQAAAACoShXNoWHtaf/www9t0L7wwgslIyNDevbsKf/6178C+3WZtczMTDsk3k9fVL9+/WTu3Ln2tl7rkHh/YFd6vBaO05758hw4cMC+QcEXAAAAAADcJqyh/ZdffpFnnnnGLqf22WefyZgxY+SPf/yjvPLKK3a/BnalPevB9LZ/n15r4A8WGxsrdevWDRxT1sMPP2zDv//SrFmzKnqFAAAAAABEaGj3er3Sq1cveeihh2wvu85Dv+666+z89ao0YcIEOwTBf9m4cWOVPh8AAAAAABEX2rUivM5HD9axY0fZsGGD/blRo0b2etu2bSHH6G3/Pr3OysoK2V9UVGQryvuPKSshIcHOGQi+AAAAAADgNmEN7Vo5fuXKlSHbfv75Z2nRooX9uVWrVjZ4z5gxI7Bf55/rXPUBAwbY23q9Z88eWbBgQeCYL774wvbi69x3AAAAAAAiVWw4n/zWW2+VE0880Q6Pv+iii+S7776T//u//7MX5TiOjB07Vv7yl7/Yee8a4u+55x5bEX7kyJGBnvlhw4YFhtUXFhbKTTfdZCvLV6RyPAAAAAAAbhXWJd+Urquuc8xXrVplQ/m4ceNsAPfT5k2cONEGee1RHzhwoDz99NPSrl27wDE6FF6D+kcffWSrxo8aNcqu7Z6SklKhNrDkGwAAAACgOlU0h4Y9tLsBoR0AAAAAUJ0iYp12AAAAAABwaIR2AAAAAABcitAOAAAAAIBLEdoBAAAAAHCpsC75BgAAgJrDa4wUeosDt+M8MeJxnLC2CQDcjtAOAACAKpddkCeTF8+QzLycwLZGiWkyrtsgSY9PDGvbAMDNGB4PAACAKg/sjy2aLll5e0O2623drvsjYZTAgeKiwEVvA0B1oKcdAAAAVUbDrfaw78jPFa+EBl29rdt1/8TeI1w7VJ5RAgDCiZ52AAAAVBmdw65ht2xg99Ptuj94rrubRMMoAQCRjdAOAAAA/IpRAgyVB1CVCO0AAABAFI4SABAdCO0AAACoMrqsm87/9kj589V1u+7X4wAAByO0AwAAoMpocTkt2Fa/VspBwV1v63bd79YidAAQboR2AAAAVCmtsD6++2DJSEwN2a63dbtbK7AzSgCAGzjGUDkjJydH0tPTJTs7W9LS0sLdHAAAgKikBduC539r2HV7D7u/enzZYnT+UQJu/tIBQHTkUHraAQAAUC00oCfExAYubg/skTxKAED0iA13AwAAAAA302A+sfeIiBslACA6ENoBAACACo4SAIDqxvB4AAAAAABcitAOAAAAAIBLEdoBAAAAAHApQjsAAAAAAC5FaAcAAAAAwKUI7QAAAAAAuBShHQAAAAAAlyK0AwAAAADgUoR2AAAAAABcitAOAAAAAIBLEdoBAAAAAHApQjsAAAAAAC5FaAcAAAAAwKUI7QAAAAAAuBShHQAAAAAAlyK0AwAAAADgUoR2AAAAAABcitAOAAAAAIBLEdoBAAAAAHApQjsAAAAAAC5FaAcAAAAAwKUI7QAAAAAAuBShHQAAAAAAlyK0AwAAAADgUoR2AAAAAABcitAOAAAAAIBLEdoBAAAAAHApQjsAAAAAAC5FaAcAAAAAwKUI7QAAAAAAuBShHQAAAAAAlyK0AwAAAADgUoR2AAAAAABcitAOAAAAAIBLEdoBAAAAAHApQjsAAAAAAC5FaAcAAAAAwKUI7QAAAAAAuBShHQAAAAAAl4oNdwMAAAAAAO7gNUYKvcWB23GeGPE4TljbVNOFtaf9vvvuE8dxQi4dOnQI7M/Pz5cbb7xR6tWrJykpKTJq1CjZtm1byGNs2LBBRowYIUlJSZKRkSG33367FBUVheHVAAAAAEDkyi7Ik0kLpsof57wVuOht3Y4aPDy+c+fOsnXr1sDlm2++Cey79dZb5aOPPpK3335bZs6cKVu2bJHzzz8/sL+4uNgG9oKCApkzZ4688sor8vLLL8u9994bplcDAAAAAJFHg/lji6ZLVt7ekO16W7cT3GtwaI+NjZVGjRoFLvXr17fbs7Oz5YUXXpDJkyfLGWecIb1795aXXnrJhvNvv/3WHvP555/L8uXL5dVXX5UePXrI8OHD5YEHHpCnnnrKBnkAAAAAwJGHxE9ePEN25OeKV0zoPjF2u+7X41ADQ/uqVaukSZMm0rp1a7n88svtcHe1YMECKSwslMGDBweO1aHzzZs3l7lz59rbet21a1dp2LBh4JihQ4dKTk6OLFu27JDPeeDAAXtM8AUAAAAAaiKdw56Zl3NQYPfT7bo/eK47akho79evnx3O/umnn8ozzzwja9eulZNPPln27t0rmZmZEh8fL7Vr1w65jwZ03af0Ojiw+/f79x3Kww8/LOnp6YFLs2bNquT1AQAAAAAQsdXjdTi7X7du3WyIb9Gihbz11luSmJhYZc87YcIEGTduXOC29rQT3AEAQCSgsjMA1CyuWvJNe9XbtWsnq1evljPPPNPOS9+zZ09Ib7tWj9e570qvv/vuu5DH8FeX9x9TnoSEBHsBAACIJFoISueV6jBVv0aJaTKu2yBJj6+6Dg8A0U2//NPfJVp0rrwh8h5xJCMx1R6HGjinPVhubq6sWbNGGjdubAvPxcXFyYwZMwL7V65caee8DxgwwN7W6yVLlkhWVlbgmGnTpklaWpp06tQpLK8BAACgKlDZGUBV0dE6+uVf/VopNqCH7BPHbtf9jOqpgaF9/Pjxdim3devW2arw5513nsTExMill15q55pfe+21dhj7l19+aQvT/fa3v7VBvX///vb+Q4YMseH8yiuvlEWLFslnn30md999t13bnZ50AAAQLajsDKCq6Wid8d0H2x71YHpbtzOap4YOj9+0aZMN6Dt37pQGDRrIwIED7XJu+rN64oknxOPxyKhRo2zFd60M//TTTwfurwF/ypQpMmbMGBvmk5OTZfTo0XL//feH8VUBAABUTWXnQwmu7JwQ46rZjwAiiAbzib1HUDfDZRxj+EpWC9Fpz76uDa9D6wEAANzkQHGR/HHOW0c87skTLyK0A0CU5VB+qwMAEEZUAgcAAIdDaAcAIEyoBI6KorIzANRcrqoeDwBATUElcBwNKjsDQM1FaAcAoJpRCRzHgsrOAFAzMTweAIBqRiVwHCsqOwNAzcNfAgAAABFEAzpf5gBAzcHweAAAAAAAXIrQDgBAmCqBly0o5qfbdT+VwAEAAKEdAIBqRiVwAABQUYR2AADCgErgAACgIqhiAgBAmFAJHAAAHAmhHQCAMKISOAAAOByGxwMAAAAA4FKEdgAAAAAAXIrQDgAAAACASxHaAQAAAABwKUI7AAAAAAAuRWgHAAAAAMClCO0AAAAAALgUoR0AAAAAAJcitAMAAAAA4FKx4W4AAACITF5jpNBbHLgd54kRj+OEtU0AAEQbQjsAADhq2QV5MnnxDMnMywlsa5SYJuO6DZL0+MSwtg0AgGjC8HgAAHDUgf2xRdMlK29vyHa9rdt1PwAAqByEdgAAcFRD4rWHfUd+rnjFhO4TY7frfj0OAIDq5DVGDhQXBS7R8m8Rw+MBAECF6Rz24CHxZWlw1/16XEIMf2YAAKpHdhRP26KnHQAAAAAQsbKjfNoWoR0AAAAAEJG8NWDaFqEdAABUmC7rpsMNPVL+0m66XffrcQAAVNe0LW+ZwF7etK1IRWgHAAAVpuuw6/zA+rVSDgruelu3637WawcAoHIQ2gEAwFHRgj7juw+WjMTUkO16W7dHesEfAADchLKuAADgqGkwn9h7RMhwQx0STw87ACAc07ay8vaWO0ReR4Hpl8qRPG2LnnYAAHBMNKDrsm7+C4EdAFDdPDVg2hahHQAAAAAQsdKjfNoWw+MBAAAAABEtPYqnbRHaAQAAAABRM20r2jA8HgAAAAAAlyK0AwAAAADgUoR2AAAAAABcitAOAAAAAIBLEdoBAAAAAHApQjsAAAAAAC5FaAcAAAAAwKUI7QAAAAAAuBShHQAAAAAAlyK0AwAAAADgUoR2AAAAAABcitAOAAAAAIBLEdoBAAAAAHCp2HA3AAAAoLp5jZFCb3HgdpwnRjyOE9Y2AQBQHkI7AACoUbIL8mTy4hmSmZcT2NYoMU3GdRsk6fGJYW0bAABlMTweAADUqMD+2KLpkpW3N2S73tbtuh8AADchtAMAgBozJF572Hfk54pXTOg+MXa77tfjAABwC0I7AACoEXQOuw6JLxvY/XS77g+e6w4AQLgR2gEAAAAAcClCOwAAAAAALkVoBwAANYIu66ZV4j1S/tJuul3363EAALgFoR0AANQIug67LutWv1bKQcFdb+t23c967QAAN3FNaH/kkUfEcRwZO3ZsYFt+fr7ceOONUq9ePUlJSZFRo0bJtm3bQu63YcMGGTFihCQlJUlGRobcfvvtUlRUFIZXAAAA3E7XYR/ffbBkJKaGbNfbup112gEAbhMrLjB//nx57rnnpFu3biHbb731Vpk6daq8/fbbkp6eLjfddJOcf/75Mnv2bLu/uLjYBvZGjRrJnDlzZOvWrXLVVVdJXFycPPTQQ2F6NQAAwM00mE/sPSKkSrwOiaeHHQDgRmHvac/NzZXLL79c/vWvf0mdOnUC27Ozs+WFF16QyZMnyxlnnCG9e/eWl156yYbzb7/91h7z+eefy/Lly+XVV1+VHj16yPDhw+WBBx6Qp556SgoKCsL4qgAAgJtpQE+IiQ1cCOwAALcKe2jX4e/aWz548OCQ7QsWLJDCwsKQ7R06dJDmzZvL3Llz7W297tq1qzRs2DBwzNChQyUnJ0eWLVt2yOc8cOCAPSb4AgAAAACA24R1ePybb74pP/zwgx0eX1ZmZqbEx8dL7dq1Q7ZrQNd9/mOCA7t/v3/foTz88MMyadKkSnoVAAAAAABEWU/7xo0b5ZZbbpHXXntNatWqVa3PPWHCBDv83n/RtgAAAAAA4DZhC+06/D0rK0t69eolsbGx9jJz5kx58skn7c/aY67z0vfs2RNyP60er4XnlF6XrSbvv+0/pjwJCQmSlpYWcgEAAAAAwG3CFtoHDRokS5YskYULFwYuffr0sUXp/D9rFfgZM2YE7rNy5Uq7xNuAAQPsbb3Wx9Dw7zdt2jQbwjt16hSW1wUAAAAAQFjntOs66F999ZWsWbNGLrvsMklNTZUtW7bYsKzrqVeE3qdLly4h25KTk+2a7P7t1157rYwbN07q1q1rH/vmm2+2Qb1///52/5AhQ2w4v/LKK+XRRx+189jvvvtuW9xOe9MBAAAAAKhRoX39+vUybNgw2+OtVdjPPPNMG8D/+te/2tvPPvtspTXuiSeeEI/HI6NGjbKPrZXhn3766cD+mJgYmTJliowZM8aGeQ39o0ePlvvvv7/S2gAAAAAAQLg4xhhzNHcYOXKkDem6hrr2ii9atEhat25te96vu+46WbVqlUQaXfItPT3dFqVjfjuAmsprjBR6iwO34zwxrF0NAAAQ5hx61D3ts2bNkjlz5tjl2IK1bNlSNm/efGytBQCEVXZBnkxePEMy83IC2xolpsm4boMkPT4xrG0DAACoyY66EJ3X65Xi4tKeGL9NmzbZHngAQOQF9scWTZesvL0h2/W2btf9AAAAiJDQrsXf/v73vwduO44jubm5MnHiRDnrrLMqu30AgCoeEq897Dvyc8UrobOl9LZu1/16HAAAAKrfUQ+Pf/zxx21BOK3anp+fb6vH6zz2+vXryxtvvFE1rQQAVAmdwx48JL4sDe66X49LiDmmBUeqBfPxAQBAtDrqv8CaNm1qi8/997//tdfay65Ls+n66omJzHsEAFQv5uMDAIBodkzdJrGxsTak6wUAgHDPx9dh/OXNxx/ffTDBHQAA1Kw57Q8//LC8+OKLB23XbbpWOwAgcugwcu2V9kj5Q8l1u+7X49yG+fgAAKAmOOrQ/txzz0mHDh0O2t65c2d59tlnK6tdAIBqoPO+dRh5/VopBwV3va3bdb8b54f75+OXDezlzccHAACoMaE9MzNTGjdufND2Bg0ayNatWyurXQCAaqLDx3UYeUZi6LKdepvh5QAAwA1MUaGY3N1itm8Us+EnMT9/L95FX4nZX1rTxvvTPCl+/UEx65ZKjZ7T3qxZM5k9e7a0atUqZLtua9KkSWW2DQBQTTSYT+w9ggrsAACgypnCAhEN21qTJi9XTP4+e20v+bni9BkmTlo9e6z3h+liZr8rUnig3Mdy6jUWSUrz3dDHyfxFTM6OQ0z8qyGh/brrrpOxY8dKYWGhnHHGGXbbjBkz5I477pDbbrutKtoIAKgGGtDdvKzboebja9G58obI6/B+HS3gxvn4AABEG5O9Q2TnZjElwdsXwveJKfnZc+Zoceo09B274DMxc94/5GM5bfuIlIR2iYkpDeyOR6RWskhiiu+iP8fVKr1fy67i/OYmkYzmEk2O+q+z22+/XXbu3Cl/+MMfpKCgwG6rVauW3HnnnTJhwoSqaCMAAIecj++vHh8c3N0+Hx8AALcxWrj1QJ5IfII4JV94m62/iNn4k68HO2/vQT3ingtvF6d+U9+xK+YeNohL7m6RktBuA7d2FNRKCQngjr1OEUmpHbib066vOC06+7Yn1BJHg/shOLUbiOglyjjGnp2jp+uzr1ixwq7N3rZtW0lISJBIlZOTI+np6ZKdnS1paSVDKwAAEYF12gEAOMwwdP33Mbm2OCWj6cyG5WLWLrHD081+DeA5Ivv3+oare4vFc9WkQBD3zpsiZvZ7h3x8G9qb+YqUe1d8K+aHz224DoTvxORAMNfjnOR0XxuMV6OoODX8i/WcCubQYx4HmZKSIn379j3WuwMAUCmYjw8AqClMcVFJT/dekTqNxImN823/ZZGY1T/6irLpPn8ILxlW7rlykkiDkh7xrWvFLPj80E+iQb6Ek9FCpNOJQb3hKeLY4empvkCeXtqr7enYX0QvFXC43nJUQmjft2+fPPLII3Yee1ZWlni9+i1JqV9++eVoHxIAgBo1Hx8AgECPc/7+kqCdI9KwpThxvhHMtjr6yu982zWE6zE6PL2E58r7RBo08x27fZOYpbPKfxL99/HA/sBNp0kbkd5DfcXbkrRXXK/1okE8VZy4+NJjW3W1F4TXUf+F87vf/U5mzpwpV155pV36raYPaQAAAACAkN5wDdq5e3zXOiw83lcszbt8rpjls0tDuF7boeLlBPE920RWLTj4CTR/aU93UDV1p1l7kZPO84XuoABuw3h8rZDMpsfa4xG9of2TTz6RqVOnykknnVQ1LQIAAAAAlzEFeSL7skVys0UalfaI27ncGsR1u+7XaulBPFdMLK1mrsXYNqw4+METknxBWwN/CadFFxGtzWKDeEkA1+uEZHE8ocPLtffc9qAjKh11aK9Tp47UrVu3aloDAAAAANU5PF3niGvYDp4jvuoHMSvnifGH9P3ZIT3bIUF87y6R9ctDH1irr2vRtaR0fZLAZqd1N5GUOqEhXEN5OVO8nIYt7AU46tD+wAMPyL333iuvvPKKJCUlVU2rAAAAAODXDFHXwJ2UVhrE1y0Vs2qBL4j7LyUV05XnintFtPBaydB0nVN+EO1dT64tUlRYJojX9g1L130p6b7ly8optqZV2f2V2YEqC+2PP/64rFmzRho2bCgtW7aUuDjfh8Dvhx9+ONqHBAAAAICKDVGPjS9dR3zTSjG/LLYB3BfG95QMUfcVbPNcfq9ISW+1Lda25OvyH1jnfxfkB246zTuJnHaJb6k07TEvufjnpgcjiMN1oX3kyJFV0xIAAAAANZ7ZvlHMxp9E9u62c8CNzgMPGqLuufweW2XdHpu5Vsz3n5b/QBrsg6qtO03biQz4zUFB3PbGlxmeztB0RHRonzhxYtW0BAAAAEBUMlopfVemL4D7w7jOBS+57Rl5s29NcD12/TIxX7996AfblxP40Wl8vEivM0t7wgNhvHbJEPWgqumNW9sLEGlY1BYAAADAMTE6t1uXNtu7qySQ+4K40SA+8Hxx6jXxHbdsjpiv3zr0A2mQLwntToPmIu362IJtklrHV7hNQ7iGcZ07XlK13R57XFt7AaLZUYf24uJieeKJJ+Stt96SDRs2SEFBQcj+Xbt2VWb7AAAAAISB0WrpJT3h/h5yp0M/cdLr2/3eH2eI+fL1Qz9A55NESkK7k1ZPjN5PA3hK3dIwXnIt9RoH7ua06GQvAI4xtE+aNEmef/55ue222+Tuu++WP//5z7Ju3Tp5//33bVV5AAAAABFQ0K1kmLo0aO5bgswudbZAvHM/9PWYH9h/0P1sz3lJaLfLlamYuDIhvCSUBxVnc9r1kRjtPQdw1BxjghYOrIDjjz9ennzySRkxYoSkpqbKwoULA9u+/fZbef31w3zb5lI5OTmSnp4u2dnZkpaWFu7mAAAAAMfM6BJmxgSKq5ktq8UsmVVS0K1kTrmG9hKe39wkTpue9mfvyvlipj5b+mA6FD21biCQO91OC8wLtz3xOjy+zNxxAJWbQ4+6pz0zM1O6du1qf05JSbFPoM4++2y55557jvbhAAAAABwlo1XRtcp6zk6RnB0iOTvFZPuuNZh7zvmDyPE9fMfq8PZl3xz8IAlJvqHpwcXamrYT5/xbS+eTxyceMpDbueVB88sBVI2jDu1NmzaVrVu3SvPmzW0P++effy69evWS+fPnS0ICH1oAAADg1zDFRb7e8JwdIaHc6XpKoOiaWb88tEe87GNk7xB/1LZLl5040obwkPnk5a057q++DiByQ/t5550nM2bMkH79+snNN98sV1xxhbzwwgu2KN2tt95aNa0EAAAAoiqU7/KF8doNbZE2u33DcvF+9pJvCHt5M1gzWgRCu1O7gZjaDUXS64mTVl/EXvTner6fU0qDt1M7Q5z+51TfCwQQ3jntZc2dO9de2rZtK+ecE5m/DJjTDgAAgKpg9mwXs2yWSPZOMSU95naJNPH9Ce6cfpl4eg7yHbv1F/G+8aDvjjofvSSA21Cu4bxFF1+vOYCoUGVz2ssaMGCAvQAAAAA1pqfczh8PGr6uoXzvTrvd6TdCPD3O8B2ct1fMvKkHP4hWXNcq7CXF4qz6x4nnkrt825NSxXE81feiALhWhUL7hx9+KMOHD5e4uDj78+H85je/qay2AQAAANXODkTVQm97ssTsyRLZs80OS3eal6wdvm29eN986NAPkL299Gcdmt799KBe83q+UJ6YelCBN1vYrcnxVfWyAERzaB85cqStGp+RkWF/PhT9xVNcXFyZ7QMAAACqJpgXF4kTG+e7rdXXZ71TEtKzDl6jvPeQ0tCuoVsDth22Xl+c1Hqhc8trNwjczUlMEWfQFdX62gDUwNDu9XrL/RkAAABwdTDX+eOBHnO93uYL5XuybA+4c8qFvoM9MWJWfhf6ALrsmfaU66VJm9LtSWniuekp1iYHUC2Oak57YWGhDBs2TJ599llbeA4AAAAIJ6MdSrm7AsFclzRzWnfz7czdI95/jT/0fTW8+yWni3PqReKkZ9igLukNxImLL/d+hHUArg3tOqd98eLFVdcaAAAAoJwec39QNoUHxMx+r3QYu84f18Jw/mPb9pYYf2jXZc90LfKktECPeel1Q9888xL6+E7vodX/4gDgCI66erx/XfZHHnnkaO8KAAAAHLoiu1Zh3x08lL1kGHujVuKcdZ3vwNg4MYu+DAnqOrRde8ZtIG9cWshNq697/vBPcTxUYQdQg0J7UVGRvPjiizJ9+nTp3bu3JCcnh+yfPHlyZbYPAAAA0RTM/T3k2rPdurtvu/GK96mbRYoKyr+f9pYHBXFnwLkiCUmBnnNJrXvIYE5gB1DjQvvSpUulV69e9ueff/45ZB/zewAAAODnXT5XZOcWMbu2iOzaKrJnu05C9+1s2EpiSkK7XY88ta5I7m5fCC9vKHsQzwlnhePlAEBkhPYvv/yyaloCAACAyKrMvj9HZOfW0lCuw9FPv7T0mLkfimQHFXtT2mtep6E4Gc1CNnsu/bNIQiKdQADwa0M7AAAAamYROOXVtcw3rRTZlXnwWuYJSWJOuyRwvNOhr0j+fpG6jcWp19heS3LtcoO5Uyup6l8MANSU0P7999/LW2+9JRs2bJCCgtC5R++++25ltQ0AAADVxBQWiOzZJkZ7zHdutT3n9ueCPIn53aOlx2VtENn6i++Ghu+0BiL1GoujgVwv2gNfEso9J50frpcDADU3tL/55pty1VVXydChQ+Xzzz+XIUOG2Lnt27Ztk/POO69qWgkAAIBKYfL3BSqy+3k//peYn+bp3kPex6nlKz7s6T1ETJeTfSFdh7nHxlVb2wGgJjrq0P7QQw/JE088ITfeeKOkpqbKP/7xD2nVqpX8/ve/l8aNG1dNKwEAAHBUzL5skR2bxGiv+e6tvmvtOdd56Bq+b3pKHH9V9oREX2BPSBKp16Sk17xRyXWTkv0+TssuwqxzAHBxaF+zZo2MGDHC/hwfHy/79u2z85JuvfVWOeOMM2TSpElV0U4AAACUYbzFvorsu7RC+1Zxep4pTly8b9/s98QsnVX+HVPqiOzbIxLfyN50+o0Qp/85IklpFIIDgEgP7XXq1JG9e/fan4877ji7BFzXrl1lz549sn9/mWIkAAAAqDQmc62YtUvE7Njk6zXfvU1Eg3sJp1U3kQYlVdnrNxWp0yikCFygBz2+tOfc3k9DPAAgskO7hvMuXbrIKaecItOmTbNB/cILL5RbbrlFvvjiC7tt0KBBVdtaAACAKGcO5PmGtWsw375JnBOGi5NW37dvw3Ixcz8IvUNsfGkg98QENnt6DRbRCwCgZoT2bt26Sd++fWXkyJE2rKs///nPEhcXJ3PmzJFRo0bJ3XffXZVtBQAAiDoazs3K78Xs2GjDumTvCNnvNO8oUhLanePaiXQ+SaT+ceLUO85XrT21jjiOJ0ytBwBUNcfo4psVMGvWLHnppZfknXfeEa/Xa0P67373Ozn55JMl0uXk5Eh6erpkZ2dLWlpauJsDAACisWK7hvPtm+y10/kkcZq08e37+XvxTnkm9A46XL1BU3HqNxOnwwni+Ie8AwCiRkVzaIVDu58WntM12l9++WUb5Nu0aSPXXnutjB49Who18hUziTSEdgAAUJlM9g4xS74uGeK+UWTvrpD9zsBR4jnhrNJjv/3IzkV3GjS1c9GdxJQwtRwAEPGhPdjq1att7/t//vMfyczMlGHDhsmHH34okYbQDgAAjpbJy7Vzzu2wdg3mLbuKp31f376s9eJ99f7QO6TWDQRzp1V3cZocH56GAwAiKocedfX4YNrLftddd0mLFi1kwoQJMnXq1F/zcAAAAK4O6eb7T8VoQNdh7rpkWhA7r7wktOva5k7XU3whvX5J73mtpPA0HAAQ0Y45tH/99dfy4osvyv/+9z/xeDxy0UUX2WHyAAAAkcrsz/H1nmsw16Ht9ZuKp89Q305PjJj5n4TeIb2BL5BrOG/WPrDZiY0T58zR1dx6AIDU9NC+ZcsWO5ddLzo0/sQTT5Qnn3zSBvbk5OSqayUAAEAVMMVFYr55t2SI+yYRDe3BmrYXKQntTkKiOCeMsMPcfXPPjztovXMAAMIW2ocPHy7Tp0+X+vXry1VXXSXXXHONtG9f+o0yAACAGxmvV2R3ppht60Qy14rEJYjn5AvsPicmVrwr5gaFdUekdkZJ5fam4jRuHfJYnoHnh+EVAABqsgqHdl2PXZd7O/vssyUmJqZqWwUAAPArmFU/iNmySkzmOpGs9SKFB0p3JtcWKQntyul3tkhMrG9ZNe09j0sIT6MBAPg1oT0Sq8IDAIDoZRfA0aXUtq0Tk7NDPL1L5p6LiHfBZyJbVpceHBsv0rCFOA1bijRsKcZ4fYXjtPe856BwNB8AgAr5VdXjAQAAqrVIXOZa23tutq0V2ba+dFi744jpeqo48bV8N9v1sZXbNaA7jVqK1G0sjoeRggCAyOP7ijlMnnnmGenWrZtdk04vAwYMkE8+Ka3Kmp+fLzfeeKPUq1dPUlJSZNSoUbJt27aQx9iwYYOMGDFCkpKSJCMjQ26//XYpKioKw6sBAACVurzauqVivMWl275+W7zvPynm2w9F1i7xBXbtLdfK7Z0HhgyB9/Q6UzyDrhBPl4G+uekEdgBAhAprT3vTpk3lkUcekbZt29ohbq+88oqce+658uOPP0rnzp3l1ltvtWu/v/3223bR+ZtuuknOP/98mT17tr1/cXGxDeyNGjWSOXPmyNatW22RPJ1//9BDD4XzpQEAgAoyBXm219wWitOh7joPPXu73ee5apJdUs1q1Mr2tDt6rT3oOtRdA3tcfHhfAAAAVcgxdkKYe9StW1f+9re/yQUXXCANGjSQ119/3f6sfvrpJ+nYsaPMnTtX+vfvb3vltTCeLkXXsGFDe8yzzz4rd955p2zfvl3i4yv2j3hOTo79UiA7O9v2+AMAgKphtDfc8dh1zJX3xxlivnxD9xx8cO0M8Zw5WpxmHXz3NUYcx6nuJgMAUCUqmkNdM6dde821R33fvn12mPyCBQuksLBQBg8eHDimQ4cO0rx580Bo1+uuXbsGArsaOnSojBkzRpYtWyY9e/Ys97kOHDhgL8FvFgBUBq8xUhg0nDfOEyMeQgZq8BrouvZ5aQ/6WpGdW8RzzhiRNr3sMU7tDDEa2FPrBuafOw21J72FOLWSQx6PwA4AqInCHtqXLFliQ7rOX9d56++995506tRJFi5caHvKa9euHXK8BvTMzEz7s14HB3b/fv++Q3n44Ydl0qRJVfJ6ANRc2QV5MnnxDMnMK/0isFFimozrNkjS4xPD2jagOmk49854VWTHJhEN7mX379gsTklol6btxfP7yeIkp1d/QwEAiABhD+3t27e3AV2HBOg68KNHj5aZM2dW6XNOmDBBxo0bF9LT3qxZsyp9TgDRH9gfWzRdduTnhmzPyttrt4/vPpjgjqhicnfbJdXMljU2pDsd+omnxxm+nfr/uvauq4QkOxfd8c9B10ruKXUCj2PnozMnHQAA94Z27U1v06aN/bl3794yf/58+cc//iEXX3yxFBQUyJ49e0J627V6vBaeU3r93XffhTyev7q8/5jyJCQk2AsAVNaQeO1h18DuLTMvV2/rdt0/sfcIhsojoueimxVzRTavEqPrn2fvCD1Ah7f7Q3udDHFG3OAL6en1GdYOAECkLvlWHq/Xa+eba4DXKvAzZswI7Fu5cqVd4k2H0yu91uH1WVlZgWOmTZtmJ/HrEHsAqA46h12HxJcN7H66XfcHz3UH3MwUFojZuFLM+mWh2794XcyKb32BXYO4Vm7vfoY4w64V58SRgeMcxyOe9n3Fqd2AwA4AQCT3tOsw9eHDh9vicnv37rWV4r/66iv57LPPbBW9a6+91g5j14ryGsRvvvlmG9S1CJ0aMmSIDedXXnmlPProo3Ye+913323XdqcnHQCAijG63vlmHeq+Sszm1SJZ60X0S6aGLSSmRWd7jBOXIE7XU0VqJYtzXBuRxseLk8CUDwAAojq0aw+5rquu66trSO/WrZsN7Geeeabd/8QTT4jH45FRo0bZ3netDP/0008H7h8TEyNTpkyx1eI1zCcnJ9s58ffff38YXxUAAJGj+O2/iWz86eAdybXFqd0oZJk1z6DLq7+BAADUcK5bpz0cWKcdwK+d0z5pwVRbdK68IfIecSQjMZU57QgLU1Roe86Nfy767m3iGf1AIIh7pz4nZuV8kXpNxDmurUiTNr6e9DTmogMAUJUibp12AIhUGsR1WTd/9fjg4K6BvX6tFLufwI7qouHcrFnoC+m6NnrZZdd2Z4rUbWx/dE6+QJxBVxy0JjoAAHAHQjsAVAJdzk2XdSu7Trv2sLNOO6qKHSy3J8uGc6dNT3F0eTXdvmaRmPmflB6YlObrQbe96G1F0hsEdjlp9cLRdAAAUEGEdgCoJBrMdQh8cJX4OE8MPeyoNEZ7zLM2+HrSN6+y66SLFpHT8J00VqRVV9/PrbqI5O0VOU6DeluR2hkMdQcAIEIR2gGgEmlAT4jhVysqR3AROB3urvPPpagg9CD9/03XQw/iNG1vLwAAIPLxlyUAAG4Z6p6z0zcPvaRonNP9NHG6n+47QIe0a2DXuefBQ90bthQnNi7czQcAAFWE0A4AQJiYgjwxP30nsnGFb3303N2hB2xaJeIP7fUa26rvUreROI4nLO0FAADVj9AOAEA1MfuyRfbvFadBU98GrxEz4z/aze677YkRyWhe2ovepE3gvjao12sSppYDAIBwIbQDAFCFPemy6WcxG1bYi+zYJNL4eIm59C6736mVJE7XU0WS03xz0Bu1EicuIdzNBgAALkJoBwCgknm//0zM6h9Etv4iYrxldnrFeIvF0V517VwffGV4GgkAACICoR2IUl5jWHoMqGJGA3nWRl/RuB5nlFZ637rGtxybSs8Qp3lHcVp0FGnWQZzE1PA2GgAARBRCOxCFsgvyZPLiGZKZ51u/WTVKTJNx3QbZtcQB/IoK73uySoa7LxfZuFIkP9fuc1p2EanT0P7s6XaamJZdfWE9vX6YWw0AACIZoR2IwsD+2KLpsqMkSPhl5e2128d3H0xwB46B96d5Yma9I7J3V+gOnYPerEPI+ulOi07CuBYAAFAZCO1AlA2J1x52DexeMaH7xNjtun9i7xEMlQcOwRzQ4nErbW+606GfOI1b2+1aIM5oYNe56I2P9wXz5h1966TH8M8pAACoGvyVAUQRncMePCS+LA3uul+PSyBkAJYpKhTZuqa0wnvm2tLicXEJgdAuzdqL5/xbRY5rS4V3AABQbfirHQBQY5k9WeL998SQoe1W7ZLicdqTXsLRaSU6bx0AAKAaEdoBADWgeNy2QE+6k1JHPKdf6tupReJi40Xia/kCeklQd9IoHgcAANyB0A5EEV3WTavEa9G5snPalUccyUhMtccB0czk7vENdd9YMuQ9qHicSakj5rRL7PJsjuMRz5X3iaTUDizXBgAA4CaEdiCKaHE5XdbNXz0+OLhrYK9fK8Xupwgdoo0pLgopBud99wmRHZtKD9B9WjzO9qR3Crmvk1qnOpsKAABwVAjtQJTR5dx0Wbey67RrDzvrtCOamJwdYn5ZbC9aPM5z/WPixMbZfVrZ3cTEiNOsZF46xeMAAECEIrQDUUiDuS7rplXi/XRIPD3siGTG6xXJ/KUkqC8K7UlXm1eJtPD1ojunXMT/7wAAICoQ2oEopYGFZd0QTcwP08R8/VbpBg3lTdqI07q7vUjdxkG7COwAACA68Bc9AMB1y7BpT7r2qDtdTxZP+xPsdqdlFzHzPhKnZVcRDeotu4iTmBLu5gIAAFQpQjsAIKyMTuPYvNoX1NcuFtm1tXRnYrJISWiXek3Ec8PfQwrOAQAARDv+8gEAhI0pyBPv83eK5O8r3ahLEmrhOP+w9+Ah7wR2AABQw/DXDwCgyhljRHZn+grI7csRz6kX2e2OrmaQ3kB/EqeVf9h7Z3ESksLdZAAAAFcgtAMAqmztdNn0c2B+umRn+XZ4YsT0P0ecBN/yg57f3CSSnC6OxxPeBgMAALgQoR0AUOm886aKmf+xSEF+6UYd2t60gzitu2nHeoCTWicsbQQAAIgEhHYAwK8b9r5jk6/Se+cTxUkpCeDxtXyBPSmtZG56N5HmncTR7QAAAKgwQjsA4KiYokKRjT+VDHtfJLJ3l29HYoo43U61PzrtTxCncWuRhi3EcRj2DgAAcKwI7QCACq+f7p35X5H1y0WKCkp3xMSJtOgkTlq9wCYnKVVELwAAAPhVCO0AgIMY4xXJ2iBSWCBO03a+jbWSRbSgnO5LqVM67L1ZB3HiEsLdZAAAgKhEaAcOw2uMFHqLA7fjPDHi0bWigWgd9r5+Wemw933ZIo2Pl5hL77L7nVrJ4gwZLU6D5iINmvnWTQcAAECVIrQDh5BdkCeTF8+QzLycwLZGiWkyrtsgSde1pYEoYdYuEfPTPDFrFooU5JXu0N7zlNpivN7AcmyezgPD11AAAIAaiNAOHCKwP7ZouuzIzw3ZnpW3124f330wwR0Ry3iLxfHEBG57F38looFd6bD3Nj3t0Hdp2l6c2LjwNRQAAACEdqC8IfHaw66B3SsmdJ8Yu133T+w9gqHyiKigLhtWiPn5ezGrfxDPZXeLUzvD7vN0OVlMWj1b8V0at6baOwAAgIsQ2oEydA578JD4sjS46349LiGGjxDcS4e1y6aVYlbOF7N6gUhe6cgRs/pHcfoMtT87x/ewFwAAALgPiQMAopDJWi/ed/8usj/oC6jEVHHa9hanXV8Rf0V4AAAAuBqhHQCiYXm2LWtECvLFadXVt7FOI5HCA3aZtkBQb9Y+ZC47AAAA3I/QDpShy7pplXgtOld2TrvyiCMZian2OCBcjDEiW38R8/N8O09dcneL1GsiMSWhXddN91wyQaRuY3GYxgEAABCx+EsOKEOLy+mybv7q8cHBXQN7/Vopdj9F6BAOZtt6MT996wvqe3eV7ohPFKdhSzGFBeLExdtNToNm4WsoAAAAKgWhHSiHLuemy7qVXadde9hZpx3V3qOuAbzkSyLz43Qxy+f4dsYliHN8T3Ha9xVp0Znl2QAAAKIQoR04BA3muqybVon30yHx9LCjWoL6jk2+qu8/zxfP2TeIZLSw+5wO/USKi3xz1Ft2CfSqAwAAIDoR2oHD0IDOsm6oLsYG9e9tUJfdmaXbV34vjj+0a1Bv2SWMrQQAAEB1Io0AQJiZ7O3iff9JkZ1bSjfql0Wtutmh706rbuFsHgAAAMKI0A4A1czs3iaSs1OcFp18G1LqiOzL8QV17Ulv11ec47uLQ+0EAACAGo/QDsB1vMZEXS0BsyfLVnw3K78T2b5RJLWueH73qC0wp0uyeUb+UaReY3ESksLdVAAAALgIoR2Aq2QX5B1Utb9RYlpEVu03OTtK5qh/J7JtfekOT4xdU13y94kkpthNTpPjw9dQAAAAuBahHYCrAvtji6bLjvzckO1ZeXvtdl2GL5KCu5n/mZhFX/hu6EiBZh19c9Tb9BKnJKwDAAAAh0NoB+CaIfHaw66B3SsmdJ8Yu1336zJ8bhsqb3Qo/9ol4l36jXj6Dg/0mjsdThCza4tvjnrb3uIkpYa7qQAAAIgwhHYArqBz2IOHxJelwV3363FuWYbP7NoqZuk3YlbMFdmX7duWlFoa2o9rKzEX3h7mVgIAACCSueMvXwCIEKa4SMzyuWKWfSOyZXXpjsRUcToNEKfLyeFsHgAAAKIMoR0AjobHI+bbD0X27hJxPCKtuoqny0DfmuouGQEAAACA6MFfmABcQZd10yrxWnSu7Jx25RFHMhJT7XHVxezdLWb5HDFrF4vnwtttKHccjzgnjBApyBOn04niJKdXW3sAAABQ8xDaAbiCFpfTZd381eODg7sG9vq1Uuz+qi5CZ4oKRX5ZZIvKyfqlIqakHWsXi7Tp5WtP99OqtA0AAACAH6EdgGvocm66rFvZddq1h72q12m3a6ovmCZmxbciwUvOHddOHB3+3qJzlT03AAAAcCiEdgCuosFcl3XTKvF+OiS+KnrYjTHi+B/3QJ6YH6f7fk6uLU7nk3yXOg0r/XkBAACAiiK0A3AdDehVtaybMV6RDSvsUm0SX0ucM0fb7U6DZuL0GSZOsw62V93xeKrk+QEAAICjEda/Sh9++GHp27evpKamSkZGhowcOVJWrlwZckx+fr7ceOONUq9ePUlJSZFRo0bJtm3bQo7ZsGGDjBgxQpKSkuzj3H777VJUVFTNrwaAm5ns7eKd8754n79TvP+bLGbld3YovDmQFzjGc8qF4rTqSmAHAACAa4S1p33mzJk2kGtw15B91113yZAhQ2T58uWSnJxsj7n11ltl6tSp8vbbb0t6errcdNNNcv7558vs2bPt/uLiYhvYGzVqJHPmzJGtW7fKVVddJXFxcfLQQw+F8+UBcAGjReUWfC6y8afSjQlJ4nTo55urHl8rnM0DAAAADssxOqnTJbZv3257yjXMn3LKKZKdnS0NGjSQ119/XS644AJ7zE8//SQdO3aUuXPnSv/+/eWTTz6Rs88+W7Zs2SING/rmnj777LNy55132seLj48/4vPm5OTYLwT0+dLS0qr8dQKoOr5faTpX3ddb7v1uqphv3tVfdyItOorTeaA4bXqJExsX7qYCAACgBsupYA511RhQbayqW7euvV6wYIEUFhbK4MGDA8d06NBBmjdvbkO70uuuXbsGArsaOnSofQOWLVtW7a8BQHiY/Xttj7r33xPFrJwf2G7XUh9wrnh+94jEjLpNPNrDTmAHAABAhHBNITqv1ytjx46Vk046Sbp06WK3ZWZm2p7y2rVrhxyrAV33+Y8JDuz+/f595Tlw4IC9+GnABxB5jFaYX7fUt6b6L4tESirOmxVzRTr0sz87KXXEGfCbMLcUAAAAiPDQrnPbly5dKt988021FMCbNGlSlT8PAKmyCvDmm/fELJ8tss83Qsdq2MrOU3fanxDO5gEAAADRFdq1uNyUKVPk66+/lqZNmwa2a3G5goIC2bNnT0hvu1aP133+Y7777ruQx/NXl/cfU9aECRNk3LhxIT3tzZo1q/TXBaDymOIicUqWgdP56t4tq3yBPTFFnI4DfHPVG5T+/gAAAACiQWy4C0bdfPPN8t5778lXX30lrVq1Ctnfu3dvWwV+xowZdqk3pUvC6RJvAwYMsLf1+sEHH5SsrCxbxE5NmzbNTuTv1KlTuc+bkJBgLwAioKjcltVils4Ss2aheH77oDiJqXafp/9vRAryRFp3D4R5AAAAINrEhntIvFaG/+CDD+xa7f456FpBLzEx0V5fe+21tldci9NpENeQr0FdK8crXSJOw/mVV14pjz76qH2Mu+++2z42wRyITCZvr5gls8ToXPU920q3r/pBnG6n2p+dFuV/KQcAAABEk7Au+eY4TrnbX3rpJbn66qvtz/n5+XLbbbfJG2+8YYvHaWX4p59+OmTo+/r162XMmDG2t17Xdx89erQ88sgjEhtbse8kWPINcAezd7eYuR+IWfGtSHGhb2Ncgjjt+vrWVG/S5pC/NwAAAIBIUtEc6qp12sOF0A64g9mXLd5/3e6rAp/RQpwep/sCe3ytcDcNAAAACEsOZSIogLAwB/b7hr/v2CSeodfYbU5yujinXSJOg2b0qgMAAACEdgDVzezOFPPjDDHLZosUHvBt6zUkUPnd0+OMMLcQAAAAcA9CO4AqZ2fhrF8m3h+mi6xbUrqjXhNxeg4Wqd0gnM0DAAAAXIvQDqDqrVog3inPlNxwRFp3E4+G9eYdGQIPAAAAHAahHUClMzk7RHJ2idO0nW9D6+4itRuK06qLOD0GiVOnYbibCAAAAEQEQjuAyhsCv3mVeH+cLrL6B5G0euL57cPieDzixMaJ5+q/2J8BAAAAVByhHcCvYooKxaz8ToyG9awNpTvSG4jk7RVJTrc3CewAAADA0SO0Azhm5ufvxfvFayL7c3wbYuLE6TRAnJ6DxKnvqwYPAAAA4NgR2gEcFVNcJE5Mya8O7UXXwJ5SR5weZ4jT9RRxElPC3UQAAAAgahDaAVQoqJvVP4j5Ybo4DVuKc8Zlvh1N2ojnvLG+KvD+IA8AAACg0vBXNoBDMnm5YpbMFLPwS5Hc3b5tu7eJOeVCW1zOLtfWqmu4mwkAAABELUI7gIOYHZvF/DBNzIpvRYoLfRuT0sTpdpo43U+zgR0AAABA1SO0AziIWTFXzNJZvhsZLcTpNVicdn0J6wAAAEA1I7QDNZw5sF/Mstm+uerHtbXbtKicZG8Xp+dgO2/dDoMHAAAAUO0I7UANZeem/zhDzLJvRAoPiGnVVWK0qJyG9tS64pw9JtxNBAAAAGo8QjtQgxhjRNYvE++P00XWLindUa+JOMf3tPvpVQcAAADcg9AO1CDeKc+IrFpQuqFVN/H0GizSvBNhHQAAAHAhQjsQxUzOTpHEFHHiEuxtp0VnMeuWitNloDg9BolTp2G4mwgAAADgMAjtQLTOV/9uqpjlc8UZdLldqk05nU4Up31fcRKSwt1EAAAAABVAaAeiiNm1Vcy8KWJ+mqcT2H0bt20I7LdLtrFsGwAAABAxCO1AFDA7NvvC+sr5eqt0vnr/c8Rp3DrczQMAAABwjAjtQBTwfv2WyLqlvhvH9/CF9YYtw90sAAAAAL8SoR2IQGbbOpGUOuIkp9vbGtK9cQni6Xe2OBnNw908AAAAAJWE0A5EELNljXjnfWTXWHd6DxHn1IvtdqdJG4lp0ibczQMAAABQyQjtQAQwm1eJ99uPRNYv823QNdULD4S7WQAAAACqGKEdcDGzaaV4534osvEn3wbHI06nAeKcMII11gEAAIAagNAOuJhZ9YMvsHtixOk8UJwThouT3iDczQIAAABQTQjtgEsYXVddK8AnpweKyTl9h4l4vfbaSasX7iYCAAAAqGaEdsANYf2XRb4561oVvlVXiTlvrN3naIX4QZeHu4kAAAAAwoTQDoSJMV6RVT+Id94Uke0bfRtj48Wp20SM9q57POFuIgAAAIAwI7QDYWC0Z33WOyI7t/g2xCWI02OQbxm3pNRwNw8AAACASxDagTAwe3f5Ant8ojg9B4nT60xxElPC3SwAAAAALkNoB6qYKS4S89O34iQki9Omp92mleClIF+crqeKUysp3E0EAAAA4FKEdqAqw/qy2WK++1gkZ4eY2g3F07q7navuxMaJ03d4uJsIAAAAwOUI7UAlM0WFYpbOEjP/ExEdBq+S0sTpeoqIt1iEAnMAAAAAKojQDlQis/oH8c54TWTfHt8GXXO973Ab2J24hHA3DwAAAECEIbQDlSk+0RfYdX11DetdThYnLj7crQIAAAAQoQjtwDEyBfliFn2pZeXE03eYb2OzDuI5e4yIzl2PjQt3EwEAAABEOEI7cJTMgf1iFn4hZsE0kfxckfhaYroMtEu2OY4j0q5PuJsIAAAAIEoQ2oEKMvn7xPw4XcwP00UO7PdtrNNQnH5niyQkhrt5AAAAAKIQoR2oALNmoXg/eV6kIM+3oW5jcfqfI067vnYJNwAAAACoCoR2oCLqNxUpKrDXnv5ni7TtLY5DWAcAAABQtQjtQBnGeMWs+FZk+0bxnHqx3eak1xfPZX8WadCMsA4AAACg2hDagSBm40/infmWSNZ63+32J4jTqJX92cloEebWAQAAAKhpCO2AhvNdW8X79dsivyzybYivJc4JI0TqHRfupgEAAACowQjtqNFM/n4xs98Vs3imiPGKOB5xup0mzoDfiJOUGu7mAQAAAKjhCO2o2TyOmFULfIH9+B7iOfkCceo2DnerAAAAAMAitKPGFZmTXxaLtO5mC8o58YniGXyVSHyiOM07hLt5AAAAABCC0I4aw2xa6Ssyt22dOMOvE6djf7vdadMz3E0DAAAAgHIR2hH1zO5M8X79jsiaH30b4hJECvPD3SwAAAAAOCJCO6KWydsrZu6HviJz3mJfkbmup/iKzCWnh7t5AAAAAHBEhHZELe+UZ0U2/uS70bq7r8hcvSbhbhYAAAAAVBihHVHDGGN71J0Y3//Wnv7niDd/n3hOvUic5p3C3TwAAAAAOGqEdkQFs3mVeGf+V5xWXcUZcK7d5jTrIJ4r7rVV4gEAAAAgEhHaEdHM7m3infWOyOoffLdzdorpe5Y4sXH2NoEdAAAAQCQjtCMimbxcMd9+JGbRlyVF5hxxupwizonnBgI7AAAAAEQ6QjsijvllkXg/eV7kwH7fhpZdxXPKBeLUbxrupgEAAABApSK0I/LUbSJSVCBSv6mvyFyLzuFuEQAAAABUibBO+P3666/lnHPOkSZNmojjOPL+++8fVA383nvvlcaNG0tiYqIMHjxYVq1aFXLMrl275PLLL5e0tDSpXbu2XHvttZKbm1vNrwRVyWxZLd55UwO3ndoNxHPxn8RzxUQCOwAAAICoFtbQvm/fPunevbs89dRT5e5/9NFH5cknn5Rnn31W5s2bJ8nJyTJ06FDJz88PHKOBfdmyZTJt2jSZMmWK/SLg+uuvr8ZXgapi9mSJd8oz4n3zYTGz3xWTuS6wz2nUShwPReYAAAAARDfH2MWtw0972t977z0ZOXKkva3N0h742267TcaPH2+3ZWdnS8OGDeXll1+WSy65RFasWCGdOnWS+fPnS58+fewxn376qZx11lmyadMme/+KyMnJkfT0dPv42mMPFxSZmzdFzMIvfEXmRIvMDRTnxJHipNQOd/MAAAAA4FeraA517Zz2tWvXSmZmph0S76cvqF+/fjJ37lwb2vVah8T7A7vS4z0ej+2ZP++888p97AMHDthL8JuF8DPFRTaoa1X4QJG5Fl18ReYaNAt38wAAAACg2rk2tGtgV9qzHkxv+/fpdUZGRsj+2NhYqVu3buCY8jz88MMyadKkKmk3foXiQjHzP/EFdi0yd8qF4rTsEu5WAQAAAEDYuDa0V6UJEybIuHHjQnramzWjJzccTNYGkQZNxXE84sQninPaJSKFB8TpPJA56wAAAABqPNeG9kaNGtnrbdu22erxfnq7R48egWOysrJC7ldUVGQryvvvX56EhAR7QfiY7O1iZv1PzM/zxTnrenE69LPbPSXXAAAAAIAwV48/nFatWtngPWPGjJAecZ2rPmDAAHtbr/fs2SMLFiwIHPPFF1+I1+u1c9/hPiZ/n3hn/le8L99tA7sWmZOdW8LdLAAAAABwpbD2tOt66qtXrw4pPrdw4UI7J7158+YyduxY+ctf/iJt27a1If6ee+6xFeH9FeY7duwow4YNk+uuu84uC1dYWCg33XSTLVJX0crxqMYic4u+9BWZy9/n29i8k3hOvYgicwAAAADgxtD+/fffy+mnnx647Z9nPnr0aLus2x133GHXctd117VHfeDAgXZJt1q1agXu89prr9mgPmjQIFs1ftSoUXZtd7iH1xgp/vAp8axd7NtQt4kN69Kyi13qDwAAAADg8nXaw4l12qtOdkGeTF48Q1Ky1su1a5bKlCat5Zfm7eXW7mdKenxiuJsHAAAAAK7OoYR2Qnul0/+lzIq5kpefK48UH5Ad+bniFSOxXq8UeTziEUfq10qR8d0HE9wBAAAA1Eg5Fcyhri1Eh8hkdm8T7/8eF/PpCxLz9Tvizd5uA7vSwK70tgZ57YHXofMAAAAAgAhb8g0RWGhuwWdi5n4kUlwoJiZOpjZuLrvi4ss9XoN7Zl6OFHqLJSGG/w0BAAAAoDykJfxqZssa8U57RWTnZt+G5p2k+PTL5PPlX4a7aQAAAAAQ0Qjt+FXM/hzxvv2oSHGRSGKKOKdeLE7HASLe4nA3DQAAAAAiHqEdv4qTlCZO3+EiOTvF0TXXE1Pt9jhPjDRKTJOsvL2BOe3BtBhdRmKqPQ4AAAAAUD4K0eGomL277JrrJnNdYJsz4FzxDLs2ENiVx3FkXLdBtkq8BvRg/urxul+PAwAAAACUj9COCjFer3h/nCHel+8WWf2DeL94zS7tppxDBG9dzk2XddMe9WB6m+XeAAAAAODIGB6PIzLbN/oKzWWu9W1ofLx4zrzqkGE9mAbzib1H2Crxfjoknh52AAAAADgyQjsOyRQeEDP3QzELPteudpH4RHFOvkCcbqeI41R8kIYGdJZ1AwAAAICjR5LCIZmf54v5/lPfjba9xXP6peKk1Al3swAAAACgxiC0I4TOU/cPe3c6nSiydqk4HfuLc3yPcDcNAAAAAGocCtEhENa9S78R72sP2GHxSofAe86+gcAOAAAAAGFCTzvE7M4U77R/i2xa6bu98Etx+g4Ld7MAAAAAoMYjtNdgprhIzPxPxMybIlJcJBIbL86J54rT68xwNw0AAAAAQGivuczmVeKd/m+RnVt8G1p2Ec+gK8RJbxDupgEAAAAAShDaayjvD9N8gT0pTZzTLhGn/QkVWncdAAAAAFB9CO0RwmuMFHqLA7fjPDF2/fOjKTSnQ+Cd2Dh723PapWI0sJ84UpzElCppMwAAAADg1yG0R4DsgjyZvHiGZOblBLY1SkyTcd0GSXp84hHvb3J2iHfGa+IkJIpz1vV2m5NaR5xBV1RpuwEAAAAAvw5LvkVAYH9s0XTJytsbsl1v63bdfyjGWyzeBZ+J9+V7RNYuFrNqgZjs7dXQagAAAABAZSC0u3xIvPaw78jPFa+Y0H1i7Hbdr8eVZbatF+/rD4qZ+ZZIUYHIcW3Fc8VECs0BAAAAQARheLyL6Rz24CHxZWlw1/16XEKM71SawgNi5rwvRgvNaZhPSBLnlAvF6TJQHIfvaAAAAAAgkhDao43XK2blfBvYbUV4rQyfnB7uVgEAAAAAjgGhPRrk5YpJTrdLtmmxOc+Zo+1mp1XXcLcMAAAAAPArMF7axXRZN60S75Hyl3aLMSJn7dkpsa/cI2b57MB2DesEdgAAAACIfIR2F9N12HVZt/q1Ug4K7o3z9sv4nxfK2asWihzYL+an+WFrJwAAAACgajA83uV0Hfbx3QcH1mmP9RbL0K3rZdjWdRKjhebiEsQ56TxxegwKd1MBAAAAAJWM0B4hwX1i7xFSuHmVxHz+sjh7tvl2tO4unjMuFyetXribCAAAAACoAoT2CBoqH+/xiHdPlkhyunhOv0ykbW9bfA4AAAAAEJ0I7RHEadJGnLOuE6dlV3FqJYW7OQAAAACAKkZojzCeDv3C3QQAAAAAQDWhejwAAAAAAC5FaAcAAAAAwKUI7QAAAAAAuBShHQAAAAAAlyK0AwAAAADgUoR2AAAAAABcitAOAAAAAIBLEdoBAAAAAHApQjsAAAAAAC5FaAcAAAAAwKUI7QAAAAAAuBShHQAAAAAAlyK0AwAAAADgUoR2AAAAAABcitAOAAAAAIBLEdoBAAAAAHApQjsAAAAAAC5FaAcAAAAAwKViw90ANzDG2OucnJxwNwUAAAAAUAPklORPfx49FEK7iOzdu9deN2vWLNxNAQAAAADUsDyanp5+yP2OOVKsrwG8Xq9s2bJFUlNTxXGccDcHx/ANlX7hsnHjRklLSwt3c1BJOK/Rh3ManTiv0YdzGp04r9GHcxr5NIprYG/SpIl4PIeeuU5Pu07s93ikadOm4W4GfiX9ZcUvrOjDeY0+nNPoxHmNPpzT6MR5jT6c08h2uB52PwrRAQAAAADgUoR2AAAAAABcitCOiJeQkCATJ06014genNfowzmNTpzX6MM5jU6c1+jDOa05KEQHAAAAAIBL0dMOAAAAAIBLEdoBAAAAAHApQjsAAAAAAC5FaAcAAAAAwKUI7XCFhx9+WPr27SupqamSkZEhI0eOlJUrV4Ycc9ppp4njOCGXG264IeSYDRs2yIgRIyQpKck+zu233y5FRUUhx3z11VfSq1cvW2mzTZs28vLLL1fLa6xp7rvvvoPOV4cOHQL78/Pz5cYbb5R69epJSkqKjBo1SrZt2xbyGJxP92nZsuVB51Uvei4Vn1P3+/rrr+Wcc86RJk2a2PPz/vvvh+zX+rT33nuvNG7cWBITE2Xw4MGyatWqkGN27doll19+uaSlpUnt2rXl2muvldzc3JBjFi9eLCeffLLUqlVLmjVrJo8++uhBbXn77bft7wU9pmvXrvLxxx9X0auu2ee1sLBQ7rzzTvseJycn22Ouuuoq2bJlyxE/34888kjIMZxX93xWr7766oPO17Bhw0KO4bMaeee1vH9j9fK3v/0tcAyf1RpIq8cD4TZ06FDz0ksvmaVLl5qFCxeas846yzRv3tzk5uYGjjn11FPNddddZ7Zu3Rq4ZGdnB/YXFRWZLl26mMGDB5sff/zRfPzxx6Z+/fpmwoQJgWN++eUXk5SUZMaNG2eWL19u/vnPf5qYmBjz6aefVvtrjnYTJ040nTt3Djlf27dvD+y/4YYbTLNmzcyMGTPM999/b/r3729OPPHEwH7OpztlZWWFnNNp06bpCiTmyy+/tPv5nLqfvud//vOfzbvvvmvP3XvvvRey/5FHHjHp6enm/fffN4sWLTK/+c1vTKtWrUxeXl7gmGHDhpnu3bubb7/91syaNcu0adPGXHrppYH9es4bNmxoLr/8cvt7/Y033jCJiYnmueeeCxwze/Zse14fffRRe57vvvtuExcXZ5YsWVJN70TNOa979uyxn7n//ve/5qeffjJz5841J5xwgundu3fIY7Ro0cLcf//9IZ/f4H+HOa/u+qyOHj3afhaDz9euXbtCjuGzGnnnNfh86uXFF180juOYNWvWBI7hs1rzENrh2mCgv8hmzpwZ2KZh4JZbbjnsL0GPx2MyMzMD25555hmTlpZmDhw4YG/fcccdNkgGu/jii+2XBqj80K5/KJRH/4DUfxjefvvtwLYVK1bYc65/TCrOZ2TQz+Txxx9vvF6vvc3nNLKU/YNRz2OjRo3M3/72t5DPa0JCgv2jT+kfd3q/+fPnB4755JNP7B+VmzdvtreffvppU6dOncA5VXfeeadp37594PZFF11kRowYEdKefv36md///vdV9GprjvKCQFnfffedPW79+vUhQeCJJ5445H04r+FzqNB+7rnnHvI+fFaj47Oq5/iMM84I2cZnteZheDxcKTs7217XrVs3ZPtrr70m9evXly5dusiECRNk//79gX1z5861Q3saNmwY2DZ06FDJycmRZcuWBY7RoZ7B9BjdjsqnQ2p1+Ffr1q3t8DwdFq0WLFhgh2sGnwsdntW8efPAueB8ul9BQYG8+uqrcs0119iheX58TiPX2rVrJTMzM+T9T09Pl379+oV8NnWYbZ8+fQLH6PEej0fmzZsXOOaUU06R+Pj4kHOo0552794dOIbzHN5/Z/Vzq+cymA6x1WlLPXv2tMNxg6eucF7dR6cS6TSj9u3by5gxY2Tnzp2BfXxWI59OG5w6daqd1lAWn9WaJTbcDQDK8nq9MnbsWDnppJPsH/1+l112mbRo0cKGQJ2no/Pz9JfPu+++a/frH5rBQUD5b+u+wx2jgSEvL8/O30Tl0D/ydR6y/iGxdetWmTRpkp1btXTpUnse9B+Ssn8s6rk40rny7zvcMZzP6qHz8Pbs2WPnVfrxOY1s/nNQ3vsffH40JASLjY21X7IGH9OqVauDHsO/r06dOoc8z/7HQNXRmiL62bz00kvtXGe/P/7xj7aWhJ7LOXPm2C/d9Pf35MmT7X7Oq7vo/PXzzz/fnpM1a9bIXXfdJcOHD7ehKyYmhs9qFHjllVdsvSc9z8H4rNY8hHa4jha00mD3zTffhGy//vrrAz9rT50WSRo0aJD9h+r4448PQ0txOPqHg1+3bt1siNcw99ZbbxG6osQLL7xgz7MGdD8+p4C76Siniy66yBYcfOaZZ0L2jRs3LuT3tn65+vvf/94Wi9WikHCXSy65JOT3rZ4z/T2rve/6exeR78UXX7QjFbVQXDA+qzUPw+PhKjfddJNMmTJFvvzyS2natOlhj9UQqFavXm2vGzVqdFD1cf9t3Xe4Y7SngSBZtbRXvV27dvZ86XnQodXaS1v2XBzpXPn3He4YzmfVW79+vUyfPl1+97vfHfY4PqeRxX8Oynv/g89PVlZWyH4dlqlVqivj8+vfj6oL7Pr5nTZtWkgv+6E+v3pu161bZ29zXt1Np6Lp1KTg37d8ViPXrFmz7Ei1I/07q/isRj9CO1xBv/HXwP7ee+/JF198cdCQnvIsXLjQXmtPnhowYIAsWbIk5B8o/x8lnTp1ChwzY8aMkMfRY3Q7qpYuMaO9rXq+evfuLXFxcSHnQv9h0jnv/nPB+XS3l156yQ671KXbDofPaWTR3736B1vw+6/TEnT+a/BnU79w09oUfvp7W6c2+b+k0WN0WSMNicHnUKfL6LBM/zGc5+oP7FprRL9w07mwR6KfX53/7B9izXl1t02bNtk57cG/b/msRvZoNv17qXv37kc8ls9qDRDuSniAGjNmjF1i6KuvvgpZvmL//v12/+rVq+3SFro02Nq1a80HH3xgWrdubU455ZSDlpIaMmSIXTZOl4dq0KBBuUtJ3X777bZa+VNPPcVSUlXktttus+dTz5cuK6LLDenSXroygH/JN13W74svvrDndcCAAfbix/l0r+LiYnvutBJtMD6nkWHv3r12uT296J8BkydPtj/7q4jrkm+1a9e252/x4sW2cnF5S7717NnTzJs3z3zzzTembdu2IctIacV5XW7oyiuvtMsNvfnmm/acll1uKDY21jz22GP2POuKEyw3VDXntaCgwC7d17RpU/u5C/531l9des6cObYate7XpaVeffVV+9m86qqrAs/BeXXPOdV948ePtyuu6O/b6dOnm169etnPYn5+fuAx+KxG3u9g/5Jteh50dZWy+KzWTIR2uIL+0irvomu3qw0bNtg//OvWrWuXHtJ1RvUP+uD1n9W6devM8OHD7VqUGhA1OBYWFoYco+tJ9+jRw8THx9tA4X8OVC5doqtx48b2fT7uuOPsbQ11fhoA/vCHP9glSfQfkvPOO8/+ARmM8+lOn332mf18rly5MmQ7n9PIoO9teb9vdfko/7Jv99xzj/2DT8/joEGDDjrXO3futH/4p6Sk2OX6fvvb39o/RIPpGu8DBw60j6G/A/TLgLLeeust065dO3uedZm/qVOnVvGrr5nnVUPdof6d1fupBQsW2OWe9Av0WrVqmY4dO5qHHnooJAAqzqs7zql2auiXnxrWNGjpEmDXXXddyHKais9q5P0OVhqu9d9IDd9l8VmtmRz9T7h7+wEAAAAAwMGY0w4AAAAAgEsR2gEAAAAAcClCOwAAAAAALkVoBwAAAADApQjtAAAAAAC4FKEdAAAAAACXIrQDAAAAAOBShHYAAGogx3Hk/fffD3czAADAERDaAQCIIldffbUN5HqJi4uThg0byplnnikvvviieL3ewHFbt26V4cOHV+gxCfgAAIQPoR0AgCgzbNgwG8rXrVsnn3zyiZx++ulyyy23yNlnny1FRUX2mEaNGklCQkK4mwoAAI6A0A4AQJTRMK6h/LjjjpNevXrJXXfdJR988IEN8C+//PJBvecFBQVy0003SePGjaVWrVrSokULefjhh+2+li1b2uvzzjvP3sd/e82aNXLuuefanvyUlBTp27evTJ8+PaQdeuxDDz0k11xzjaSmpkrz5s3l//7v/0KO2bRpk1x66aVSt25dSU5Olj59+si8efMC+7Xd+hq0Xa1bt5ZJkyYFvngAAKAmILQDAFADnHHGGdK9e3d59913D9r35JNPyocffihvvfWWrFy5Ul577bVAOJ8/f769fumll2zvvf92bm6unHXWWTJjxgz58ccfbe/+OeecIxs2bAh57Mcff9wGcT3mD3/4g4wZM8Y+h/8xTj31VNm8ebN9/kWLFskdd9wRGMY/a9Ysueqqq+wogeXLl8tzzz1nv3R48MEHq/z9AgDALWLD3QAAAFA9OnToIIsXLz5ouwbttm3bysCBA21vuva0+zVo0MBe165d2/be++kXAHrxe+CBB+S9996z4Vt77f002GtYV3feeac88cQT8uWXX0r79u3l9ddfl+3bt9svArSnXbVp0yZwX+1V/9Of/iSjR4+2t7WnXZ9Hg/3EiRMr+d0BAMCdCO0AANQQxhgbyssrXqfF6jRIa4+5zn0fMmTIYR9Le8nvu+8+mTp1qu2B1yHreXl5B/W0d+vWLfCzPrcG/6ysLHt74cKF0rNnz0BgL0t73mfPnh3Ss15cXCz5+fmyf/9+SUpKOur3AACASENoBwCghlixYoW0atXqoO06Z3zt2rV2zrvOS7/oootk8ODB8s477xzyscaPHy/Tpk2Txx57zPaOJyYmygUXXGDnxwfTCvbBNLj7h7/rfY70xYD2tp9//vkH7dM57gAA1ASEdgAAaoAvvvhClixZIrfeemu5+9PS0uTiiy+2Fw3f2uO+a9cu2wuuwVt7uINpD7j20GuBOn/A1mr1R0N74Z9//vnA85T3ZYLOfw8eMg8AQE1DaAcAIMocOHBAMjMzbdDetm2bfPrpp7YavA5718JuZU2ePNlWjteh6h6PR95++207jF3nsSstSqcF50466SRbmb5OnTp2DrwWtdPic9p7fs8994SsA18RWjVeq8uPHDnStk/boAXrmjRpIgMGDJB7773XtlmrzusXCdo2HTK/dOlS+ctf/lJp7xcAAG5G9XgAAKKMhnQNwBq2tcdcC79phXhdPi0mJuag43U5tkcffdRWedel27TH/OOPP7Yh2V8BXofCN2vWzAZ7f9DX8H7iiSfa4D506FDbM3404uPj5fPPP5eMjAxbsK5r167yyCOPBNqojzllyhR7jLarf//+tpBdcKE8AACinWO0Kg0AAAAAAHAdetoBAAAAAHApQjsAAAAAAC5FaAcAAAAAwKUI7QAAAAAAuBShHQAAAAAAlyK0AwAAAADgUoR2AAAAAABcitAOAAAAAIBLEdoBAAAAAHApQjsAAAAAAC5FaAcAAAAAwKUI7QAAAAAAiDv9f/8bmnwvYWOiAAAAAElFTkSuQmCC"
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
-   "execution_count": 61
+   "execution_count": 20
   },
   {
    "cell_type": "code",
@@ -1081,8 +1081,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:34.559847Z",
-     "start_time": "2025-12-21T14:55:34.553788Z"
+     "end_time": "2026-02-20T11:30:55.921913Z",
+     "start_time": "2026-02-20T11:30:55.915750Z"
     }
    },
    "source": [
@@ -1102,41 +1102,41 @@
      "text": [
       "* Selected model: Gaussian model\n",
       "* Nugget: 0\n",
-      "* Sill: 478.90567078851103\n",
+      "* Sill: 415.1536596743022\n",
       "* Range: 8000\n",
       "* Spatial Dependency Strength is Undefined: nugget equal to 0, cannot estimate\n",
       "* Mean Bias: None\n",
-      "* Mean RMSE: 159.98897643128805\n",
+      "* Mean RMSE: 153.225123668266\n",
       "* Error-lag weighting method: equal\n",
       "\n",
       "\n",
       "+---------+--------------------+--------------------+--------------------+\n",
       "|   lag   |    theoretical     |    experimental    |  bias (real-yhat)  |\n",
       "+---------+--------------------+--------------------+--------------------+\n",
-      "|  1000.0 | 7.424744235536801  | 66.71388540855338  | 59.28914117301658  |\n",
-      "|  2000.0 | 29.015427794333753 | 130.66628344322854 | 101.65085564889478 |\n",
-      "|  3000.0 | 62.825213477796176 | 377.5405401178886  | 314.7153266400924  |\n",
-      "|  4000.0 | 105.93355936108222 | 250.66718626708865 | 144.73362690600644 |\n",
-      "|  5000.0 | 154.86188481421806 | 325.5561456427749  | 170.69426082855682 |\n",
-      "|  6000.0 | 206.03344490697575 | 387.4814906048632  | 181.44804569788747 |\n",
-      "|  7000.0 | 256.19385082954307 | 302.07493544556206 | 45.881084616018995 |\n",
-      "|  8000.0 | 302.72612024499887 | 469.53885776562294 | 166.81273752062407 |\n",
-      "|  9000.0 | 343.8241237029969  | 486.79931370125183 | 142.9751899982549  |\n",
-      "| 10000.0 | 378.52158882000424 | 512.0646265352149  | 133.54303771521063 |\n",
-      "| 11000.0 | 406.6017289289635  |  529.991767276145  | 123.39003834718147 |\n",
-      "| 12000.0 | 428.4293844491225  | 582.4717932210419  | 154.04240877191944 |\n",
-      "| 13000.0 | 444.7517070227298  |  692.506923505966  | 247.7552164832362  |\n",
-      "| 14000.0 |  456.506954502525  | 649.5775483966735  | 193.0705938941485  |\n",
-      "| 15000.0 | 464.6681804730809  | 624.8696046337229  | 160.20142416064203 |\n",
-      "| 16000.0 | 470.13420746058165 |  643.74627487684   | 173.6120674162583  |\n",
-      "| 17000.0 | 473.66799080758676 | 571.3688648923311  | 97.70087408474433  |\n",
-      "| 18000.0 | 475.8743341758106  | 540.0470107890337  | 64.17267661322313  |\n",
-      "| 19000.0 | 477.20524505947054 | 600.2575887426275  | 123.05234368315695 |\n",
+      "|  1000.0 | 6.436360915195765  | 57.836141811479614 | 51.39978089628385  |\n",
+      "|  2000.0 | 25.15288870144259  | 86.03437765640514  | 60.88148895496255  |\n",
+      "|  3000.0 | 54.46190948664809  | 236.60954497912823 | 182.14763549248013 |\n",
+      "|  4000.0 | 91.83166442499613  | 268.7197011214077  | 176.88803669641158 |\n",
+      "|  5000.0 | 134.24664218076163 | 216.77470366578342 |  82.5280614850218  |\n",
+      "|  6000.0 | 178.60623476769803 | 294.4056440278582  | 115.79940926016019 |\n",
+      "|  7000.0 | 222.0892782138437  | 383.72288068192313 | 161.63360246807943 |\n",
+      "|  8000.0 | 262.4271633530408  | 378.7119931185135  | 116.2848297654727  |\n",
+      "|  9000.0 | 298.0541930200788  |  483.465464109033  | 185.4112710889542  |\n",
+      "| 10000.0 | 328.13272518911697 | 452.9072205931408  | 124.77449540402381 |\n",
+      "| 11000.0 | 352.4748318741507  | 412.07362484342366 | 59.59879296927295  |\n",
+      "| 12000.0 | 371.39678587061064 | 491.23925913297296 | 119.84247326236232 |\n",
+      "| 13000.0 |  385.546277856497  | 577.2518572511536  | 191.70557939465664 |\n",
+      "| 14000.0 | 395.7366646263568  | 575.1348087672814  | 179.39814414092456 |\n",
+      "| 15000.0 | 402.8114666923392  | 633.2991501319548  | 230.48768343961558 |\n",
+      "| 16000.0 | 407.54985516037124 | 659.1799840204877  | 251.63012886011649 |\n",
+      "| 17000.0 | 410.61322061726753 |  641.201731691203  | 230.58851107393548 |\n",
+      "| 18000.0 | 412.52585514988465 | 500.6074586569037  | 88.08160350701905  |\n",
+      "| 19000.0 | 413.6795949315457  | 448.75860119019325 | 35.07900625864755  |\n",
       "+---------+--------------------+--------------------+--------------------+\n"
      ]
     }
    ],
-   "execution_count": 62
+   "execution_count": 21
   },
   {
    "cell_type": "code",
@@ -1147,8 +1147,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:34.827178Z",
-     "start_time": "2025-12-21T14:55:34.642752Z"
+     "end_time": "2026-02-20T11:30:56.110422Z",
+     "start_time": "2026-02-20T11:30:55.987472Z"
     }
    },
    "source": [
@@ -1160,13 +1160,13 @@
       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ],
-      "image/png": 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129gs+RZmrYXaWmvt4sauttLafWzmequbjfG2niJW9uSTTybk/bOgbrOt2/Jy+++/f6zc3isLvXZxwbrEW+8L607+Q9TE+2ZzILz22mt+yIvNRG/n9ZZbbokNIbDHtIt1dowtKWc9b+wCXzSU2/m3XgP2Gq3V3i4M2uz5dmECAAAASDWBzUanDGfrtFt3fFv6rOqkdNaN2VpAO3fu7C8i/NCJV6qO47LA3rx+vi7vP0yFOTsew5so1lI8YMCA2HrfQLr5sZ9vAED1xrTbUrc26VzVMe3R70Qt8xoxph1Axlm7gxyaVC3t6c4CuQVz+8eoMttO5sAOAABQEyyIj+k31DdWVO19GG3EsP0EdgDYtuToR57mLJjb1WObYCXKusTzjxMAAMikRgybJb7ypHTWiGGBnUYMANg+QnsdsYCeajOivvnmm4muAgAASBM0YgDAD5NaKRIAAAApKxUbMQAg0RjTDgAAAABAkiK0AwAAAACQpAjtAAAAAAAkKUI7AAAAAABJitAOAAAAAECSIrRnKFvOLQgCrVmzRqnE6vzcc8/V2ON16tRJd999txJp3rx5/nVNnTq12vc55JBDdMkll9RqvQAAAAAkHqE9DVkA3NHtuuuuU7KzOg4YMGCr8iVLlujII4+s03rYe3bEEUdste+2227z+yxAAwAAAEBtYKHMNGTBNuqJJ57Qtddeq9mzZ8fK8vPz9cknnySkbqWlpcrJyfnB92/durXqWps2bfTGG29o0aJFateuXaz8gQceUIcOHeq8PgAAAAAyBy3taciCbfRWWFjoW4Mrl1loj5oyZYoGDx6sBg0aaL/99osL9+b555/XwIEDVb9+fXXp0kXXX3+9ysvLY/sXLFigY4891j9mQUGBTjzxRC1btmyrFvN//vOf6ty5s38cY93yf/7zn6tFixb+focddpimTZvm9z300EP+eWw72jvAyrbVPd6C9CmnnKKmTZuqYcOG/rV8+OGHft8333zj69aqVStfv7322ksTJ07c5fezZcuWGj58uB5++OFY2fvvv6+VK1dq5MiRcceGw2HdcMMNPtzn5ub61/7KK6/EHfPRRx9pzz339O+F1fezzz7b6jlnzpzpexRYva3+p59+un8+AAAAAJmF0P4DubJN27+Vl1X/2LLSah1bW37/+9/rjjvu8C3v9erV0znnnBPb98477+iMM87Qb37zG33++ee6//77fXi+8cYbYwHVQvGqVav01ltvacKECfr222910kknxT3H119/rf/973965plnYuO2f/rTn2r58uV6+eWX/YUDuzAwdOhQ/1h2/8suu0x77LGH7zVgt6qPadavX6+DDz5Y3333nV544QUf8q+88kpfr+j+o446SpMmTfLB2Lq4H3PMMf5Cw66y9yV64SDayn7qqadu1WvgL3/5i38/b7/9dk2fPl0jRozQT37yE82ZMydWp6OPPlq9e/f2r9sualx++eVxj2EXNOwihgV7Oy8W+u1CiF0QAQAAAJBZ6B7/A4X/9qvt7+zcV1nHb5kkLHzvJVJ5fDiPaddDWSdeueXYf14pFa/f6rCsMf9SbbAAbsHX/Pa3v/UtxyUlJb4V2Fq7rezMM8/0+62l/Y9//KMPxmPHjvVheMaMGZo7d67at2/vj/n3v//tw/bHH3/sW7ajXeKt3FrVzbvvvutbmy20W2u0sZBrLehPP/20zj//fN/CbBcRdtQd/rHHHtOKFSv8c1lLu+natWtsf//+/f0tyur+7LPP+oB/0UUX7dL7ZEH7l7/8pd5++20NGjRITz75pH8dFt4rs9dx1VVX6eSTT/bbf/7zn33Xepvs7u9//7uvs11U+Ne//uXfY3uvrLfABRdcEHuM//u///OB/aabboqV2fPYe/zVV1+pe/fuu1R3AAAAAKmL0J7h+vXrFzd221iYtrHa1nL93nvvxVrWTUVFhQ/1Gzdu1BdffOGDZDSwG2tBbty4sd8XDe0dO3aMBXZjj2stzs2aNYurS3Fxse/SXl3Wam/hNhrYq7LnsJbs8ePH+9Z669Zvz/FDWtqzs7N12mmn6cEHH/S9CSw4V37vzNq1a7V48WLtv//+ceW2He36b++L3S86TMAMGTIk7ng71oJ+5WEMUfb+ENoBAACAzEFo/4FCF9+z/Z1B/KiD0AU7WlIsiD/257eqLlkYjdUkiNSlcvdya20fNWrUVverHDp3xsaaV2aPaxcIbNm5qizwV1deXt4O91u3c+uyb63f1gJvx59wwgm+5f+HsC7y++yzjx9vXnkYQU2z98e68VsrfVXRCysAAAAAMgOh/QcKsnMTfmxts3HmNjFd5S7nlfXq1UsLFy70t2hru419tzHZ1uK+o8ddunSp7/5u66Rvi40Vt1b9HbEWa5vgzsbBb6u13XoJnHXWWTr++ONjYdjWRP+hrCu73Wys+s9+9rOt9tuEem3btvXPGx1yEK3H3nvvHXvPHnnkkdgQBPPBBx9s9f7YHAD23th7BAAAACBzMREdtsuWirOx6NbaPmvWLN+1+7///a+uueYav3/YsGHq27evn5Dt008/9ePUbeI6C6w2K/r22P2sS/hxxx2n1157zQdpm43dJsWLLkVngdXGylsXeJs1fdOmrSfjs1njbcy7PY4FY+u2bmF38uTJfn+3bt1ik99Zl3ML2tFeBD/U66+/7rvab69HwBVXXOFbyG2pPbvgYXMC2PPbZH7G6mA9Gs477zx/geOll17yPQEqu/DCC/2FCHt9Nl7fusS/+uqrOvvss3d6IQMAANSOsHPaVFEeu9k2ANQFQju2y2Y+HzdunA/WNj5933331V133eXHqBsLn7YkXJMmTXTQQQf5MG6T1Vlg3RG7n4VVu48FURujbRO3zZ8/3y9vZkaPHu1nez/00EP9ePjHH398m63xVjdbks1mibcLCLfccouysrL8/jvvvNPXzZays+7m9nqsFfvHsK7+O+rC/+tf/1pjxozxs99bfWzmd5v4zi4gGBun/uKLL/oJ/Gw8vl2oqNoNPtpabwHdlpqzx7nkkkv884ZCfGQBAKhrRaXFun7KeP36/SdjN9u2cgCobYFzXCa0CcRsPfOioiLfxbky68ZsLb6V1xgHkB74fAMAdsaC+e3TJmplyXqFteVrc0iBmtfP1+X9h6kwZ8fz7ADArubQymi2AwAAALbBusDfOX3SVoHd75Pz5bafrvIAahOzXAEAAADbUBau0NLitdvdb8Hd9ttxuVl8ra5pdjHE3tuo7FCWQptXOwIyCX9dAAAAACTdsATrxVD5oknrvAKN6TeU4QjIOHSPBwAAAJB08wgsL14XV27bVs4EgMg0hHYAAABgG6w7trXu2qRz22Lltt+OQ81gHgFga4T2amKSfSD98LkGAOyIjZ+27tg2S3zV4B6dPd72M8665ucRqBrYtzWPAJApCO07EV3zu7S0NNFVAVDDop/r6OccAICqbPy0LevWMq9RXLlts9wbgLrARHQ7Ua9ePTVo0EArVqxQdna2QiGucwDpIBwO+8+1fb7tcw4AwPZYMB87aCQzmQNICL6p7kQQBGrTpo3mzp2r+fPnJ7o6AGqQXYTr0KGD/5wDALAjFtBZ1q3u5hGwSee21UXehiVYLwfmEUAm4S9PNeTk5Khbt250kQfS8LNN7xkAAJJvHgGbJb7qZHTMI4BMRWivJvtiX79+/URXAwAAAMiIeQSqrtNuLeys045MRGgHAAAAkFSYRwDYgtAOAAAApDFb0zwVwy/zCAARfAoAAACANFVUWrxVN3Ob6I1u5kDqYAYmAAAAIE0Du03oZjOxV2bbVm77ASQ/QjsAAACQhl3irYW96gzsfp+cL7f9dhyA5EZoBwAAANKMjWG3LvHbWuvcWLntrzzWHUByIrQDAAAAAJCkCO0AAAAAACQpQjsAAACQZmxZN5slPqRtL+1m5bbfjgOQ3AjtAAAAQJqxNc5tWbfm9fO3Cu62beW2PxXWawcyHaEdAAAASEO2Dvvl/YepZV6juHLbtnLWaQdSQ71EVwAAAABA7bBgPnbQyLhZ4q1LPC3sQOogtAMAAABpzAJ6bhZf+4FURfd4AAAAAACSFKEdAAAAAIAkRWgHAAAAACBJMbgFAAAAAJDyws6l5aSLCW9p/+6773TaaaepWbNmysvLU9++ffXJJ5/E9jvndO2116pNmzZ+/7BhwzRnzpy4x1i1apVOPfVUFRQUqHHjxjr33HO1fv36BLwaAAAAAEBdKyot1vVTxuvX7z8Zu9m2lae6hIb21atXa//991d2drZefvllff7557rjjjvUpEmT2DG33nqr/vrXv+q+++7Thx9+qIYNG2rEiBEqKSmJHWOBfdasWZowYYLGjRunt99+W+eff36CXhUAAAAAoK4UlRbr9mkTtbx4XVy5bVt5qgf3wFlTdoL89re/1Xvvvad33nlnm/utam3bttVll12myy+/3JcVFRWpVatWeuihh3TyySfriy++UO/evfXxxx9r8ODB/phXXnlFRx11lBYtWuTvvzNr165VYWGhf2xrrQcAAAAApEaX+OunjPcBPayto21IgVrmNdLYQSOTrqt8dXNoQlvaX3jhBR+0f/rTn6ply5bac8899f/+3/+L7Z87d66WLl3qu8RH2YvaZ599NHnyZL9tP61LfDSwGzs+FAr5lvlt2bRpk3+DKt8AAAAAAKmlLFyhpcVrtxnYjZXb/spj3VNNQkP7t99+q3vvvVfdunXTq6++qgsuuEC//vWv9fDDD/v9FtiNtaxXZtvRffbTAn9l9erVU9OmTWPHVHXzzTf78B+9tW/fvpZeIQAAAAAAKRraw+GwBg4cqJtuusm3sts49PPOO8+PX69NV199te+CEL0tXLiwVp8PAAAAAICUC+02I7yNR6+sV69eWrBggf+9devW/ueyZcvijrHt6D77uXz58rj95eXlfkb56DFV5ebm+jEDlW8AAAAAgNSSHcpS67wCP3Z9W6zc9ttxqSqhod1mjp89e3Zc2VdffaWOHTv63zt37uyD96RJk2L7bfy5jVUfMmSI37afa9as0ZQpU2LHvP76674V38a+AwAAAADSUygINKbfUDWvn79VcLdtK7f9yTYJXcqE9ksvvVQffPCB7x7/9ddf67HHHtM//vEPXXjhhX5/EAS65JJL9Kc//clPWjdjxgydccYZfkb44447LtYyf8QRR/hu9R999JGfjf6iiy7yM8tXZ+Z4AAAAAEDqKszJ0+X9h/lZ4iuzbSu3/aksoUu+GVtX3caYz5kzx7esjxkzxgfwKKve2LFjfZi3FvUDDjhA99xzj7p37x47xrrCW1B/8cUX/azxo0eP9mu75+fnV6sOLPkGAAAAAKm//FtZpVnirUt8MrewVzeHJjy0JwNCOwAASBWp9qUUAPDjcmi97e4BAABAUikqLdad0yf5NYejbIIlG6+Z6t0/AQBJOKYdAAAA1Q/st0+bqOXF6+LKbdvKbT8AIP0Q2gEAAFKgS7y1sK8sWa+w4kc22raV2347DgCQXgjtAAAASc7GsFuX+KqBPcrKbX/lse4AgPRAaAcAAAAAIEkR2gEAAAAASFKEdgAAgCRny7rZLPEhbXtpNyu3/XYcgMSz+SU2VZTHbsw3gR+DJd8AAACSnK3Dbsu62SzxVSejs8DevH6+38967UDisTQjahot7QAAACnAvuxf3n+YWuY1iiu3bSsnDACJx9KMqA2Bc/TVWLt2rQoLC1VUVKSCgoJEVwcAAGC7rJtt5VnirUs8LexAcnw2r58y3gf0ba30YL1i7CLb2EEj+cxil3Io3eMBAABSiH3Zz83iKxyQrEszbk/lpRn5DGNX0D0eAAAAAIAkRWgHAAAAACBJEdoBAAAA4EdiaUbUFkI7AAAAANTQ0oy2BGPV4M7SjPgxCO0AAAAAUANYmhG1gWkLAQAAAKCGWDC3Zd1YmhE1hdAOAAAAADWIpRlRk+geDwAAAABAkiK0AwAAAACQpAjtAAAAAAAkKUI7AAAAAABJitAOAAAAAECSIrQDAAAAAJCkCO0AAAAAACQpFg8EAAAAAHhh51QWrohtZ4ey/LrzSBxCOwAAAABARaXFunP6JC0tXhsra51XoDH9hqowJy+hdctkdI8HAAAAgAxngf32aRO1vHhdXLltW7ntR2IQ2gEAAAAgw7vEWwv7ypL1CsvF75Pz5bbfjkPdI7QDAAAAQAazMezWJb5qYI+ycttfeaw76g6hHQAAAACAJMVEdAAAIOMwOzIAIFUQ2gEAQEZhdmQAiGcXLu3voE06t60u8iEFapnXyB+Hukf3eAAAkDGYHRkAtmY9jezCZfP6+T6gx+1T4MttPz2SEoPQDgAAMgKzIwPA9llPo8v7D/Mt6pXZtpXTEylx6B4PAAAyanbk7ak8O3JuFl+RAGQeC+ZjB41kzo8kw79IAAAAAADPAjoXLpML3eMBAAAAAEhShHYAAJBRsyNXnWQpysptP7MjAwCSCaEdAABkBGZHBgCkIkI7AADIGMyODABINcwwAAAAMgqzIwMAUgmhHQAA/CC2nnmqBl9mRwYApAr+tQIAALusqLRYd06fFLfuuU3iZmPC6WIOAEDNYUw7AADY5cB++7SJWl68Lq7ctq3c9gMAgJpBaAcAALvUJd5a2FeWrFdYLn6fnC+3/XYcAAD48QjtAACg2mwMu3WJrxrYo6zc9lce6w4AAH44QjsAAAAAAEmK0A4AAAAAQJIitAMAgGqzZd1slviQtr20m5XbfjsOAAD8eIR2AACwS+ub27JuzevnbxXcbdvKbX+qrNcOAECyS2hov+666xQEQdytZ8+esf0lJSW68MIL1axZM+Xn52v06NFatmxZ3GMsWLBAI0eOVIMGDdSyZUtdccUVKi8vT8CrAQAgM9g67Jf3H6aWeY3iym3bylmnHQCAmlNPCbbHHnto4sSJse169bZU6dJLL9X48eP11FNPqbCwUBdddJFGjRql9957z++vqKjwgb1169Z6//33tWTJEp1xxhnKzs7WTTfdlJDXAwBAJrBgPnbQyLhZ4q1LPC3sAACkWWi3kG6hu6qioiL961//0mOPPabDDjvMlz344IPq1auXPvjgA+2777567bXX9Pnnn/vQ36pVKw0YMEB//OMfddVVV/lW/JycnAS8IgAAMoMF9NyshH+VAAAgrSV8TPucOXPUtm1bdenSRaeeeqrv7m6mTJmisrIyDRs2LHasdZ3v0KGDJk+e7LftZ9++fX1gjxoxYoTWrl2rWbNmbfc5N23a5I+pfAMAAAAAINkkNLTvs88+euihh/TKK6/o3nvv1dy5c3XggQdq3bp1Wrp0qW8pb9y4cdx9LKDbPmM/Kwf26P7ovu25+eabfXf76K19+/a18voAAAAAAPgxEtqn7cgjj4z93q9fPx/iO3bsqCeffFJ5ebU3ic3VV1+tMWPGxLatpZ3gDgAAAABINgnvHl+Ztap3795dX3/9tR/nXlpaqjVr1sQdY7PHR8fA28+qs8lHt7c1Tj4qNzdXBQUFcTcAAAAAAJJNUoX29evX65tvvlGbNm00aNAgPwv8pEmTYvtnz57tx7wPGTLEb9vPGTNmaPny5bFjJkyY4EN47969E/IaAADYFWHntKmiPHazbQAAgKToHn/55ZfrmGOO8V3iFy9erLFjxyorK0unnHKKH2t+7rnn+m7sTZs29UH84osv9kHdZo43w4cP9+H89NNP16233urHsV9zzTV+bXdrTQcAIJkVlRbrzumTtLR4y4SorfMKNKbfUNY6BwAAiQ/tixYt8gH9+++/V4sWLXTAAQf45dzsd3PXXXcpFApp9OjRfsZ3mxn+nnvuid3fAv64ceN0wQUX+DDfsGFDnXnmmbrhhhsS+KoAAKheYL992kStLFkfV768eJ0vv7z/MII7AABQ4Bz98GwiOmvZt7XhGd8OAKht1gX++injfUAPa+t/hkMK1DKvkcYOGunXQgcAAJmbQ5NqTDsAAJmgLFzhu8RvK7AbK7f9dhwAAMhshHYAAAAAAJIUoR0AAAAAgCRFaAcAoI5lh7L8LPE2dn1brNz223EAACCzEdoBAKhjNrmcLevWvH7+VsHdtq3c9jMJHQAASOiSbwAAZCpbzs2Wdau6TrvNGs867QCATORcWCovl1yFVFEh2XZFhRTefMttoKBBo8ix5WXS8vlb9oXDW35v2UFBQXOlC0I7ACAtllCrPNO6dStPhVZqC+a2rFsq1h0AkPxcWalUsl6ygFtht/LNv5dHbs13U9CoaeTYohVy30zbvG/zMbFAXKGg22AF7bpHjl35ndyH4+S2FZjt2P6HKtRzn8ixKxYqPO6+zceUxx/rwgr2PkqhvUdGKrxyscKPjN3u6wkGH6HgoJ9GNtavUfi/N2/7uBFnK9jjAKULQjsAIKUVlRZv1Vpt48FTpbXaAnpuFv8cA0C6cSUbpQ1rIgHYWo8rh2H7uVt3BQ0LI8cumy83b8bm47YO2D6stuoYOfbbaQpPfqFS+K70s7xMoSPPU9B9cOxYN/6+7dYxGH62gj6bw+33S+TefHz7L6hxq1hoV/F6udkfbf/Yzv22/G4t5auXbv/YsrItv4e2MXo7lCUFISkrK/J7VL16UmHLyH2s3P+s538GeZHW+HTBtwQAQEoH9tunTdRKa0WoZHnxOl9u3c9TIbgDABIcru3Cb+kmqaxEstbpshI5v71JQc+9YyHQff2Z3OwPIy3YpXZs5Jjo76HRYxS07hw5dubbcm8/td3nDY2+TIqF9nly7z273WODHntJ0dC+qVhaNm/7r6e8LDZbSlAvW84uDMdu2ZGbBd6segpyG2y5Y6Mmkefxx2w+3ofhyC160cBr3FLBISfH7Y+G58B+b95uy7FNWyl04pXbPNbf6jfccmyT1gpd9H+x8G1hPdhO77Mgv4myzt12S3u6IbQDAFK2S7y1sFtgD8vF75Pz5bbfup/T3RwAUp/bZOF6/VZB2W3eDnrtq2DzhdqwtQJ/M03Oh3A7dvN9/K1EoZN/p6BJq8jjTnnVd/XenqDN7lI0tK9eKjf74+1X0uoUZYHYbvVyNofkaBje/DM7d8tzNGsr9TmwUqDefEy9zT+b7bbl2HY9FBz36837sisdu/l+eflbjt19gLJ+c3+13t+gRXsFI39ZvWMt4A88vHrH2jlp16N6x1pQ52L7VgjtAICUZOPAK3eJr8qCu+234+h+DgCJ52wsswXv+g1jrafuuzlyyxdEwnjJBn9zm3/aWOzQKb9XsDmEWku0m/r6dh8/6NB7S+BbsUjuyw+qGa7zIrd6uVJOrpRdPxKoc3IVbP655Tl6SYecEjvO78+udL/N48NNqO9Bkt2qIditm79V69hGTXyrODIH32IAAAAA7Hr4joXrDVLHPSKtpHbRdNZ70vxZlcL3hkgot27dcgpd8JdYa7D78kO5aW9s/8nsvtGW45zNYdrf6m8OypVulS7QBp37SnkNYwE8Fr6jgbywRezY0OAjJLtVQ9Cqk78BdYnQDgAAAGSgbYVvV6nFO9j3mC1B3Fq5rcu537fRh+/KQhfcHetCrqVzfRivVhBv3UlB8WCpfn5kbPPmm29dt9/zG295jgNGS3ar4ZZrINkR2gEAKcmWRrNZ4m3Suapj2k1IgV/z3I4DgEzhbBbxDUXS+tX+5tavkdat9mXOupsf9+vIRGF27Mv/9JOqbU+w52FbgrgF9TXL4w+wlu9o0LaZzKP36zpQatwiEr6rhHFfVqlFPGTLcqXR0lxAbSC0AwBSkk0uZ8u6RWePrxzcLbA3r5/v9zMJHYB04UqL/drUPoxbEPe/r1Fw2CkKbEksH8T/n9xXn2z/QSx8N9gcxKOzdlcO3/XzFUR/j81BbgF+qJ9FfXvhu7KgY29/A1AzCO0AgJRly7nZsm5V12m3FvZUWacdAJwLSxvXbW4dXyO3frWCfgfHgnj4zf/KzXxXstC+DcG+R8eWDlN+k8gyWtatPL+Jgs0/1bCx1CBfys7Zcr+DTlBwyEnbDd9xz9G0tfVlr6mXDGAXENoBACnNgrkt62azxEdZl3ha2AEkA1szO9Iivkpq223LGPFPJ0SWDrOgbt3ZK/0Ni3UxjwZxEw3sdjHSZg7Pb+zXqfbhfPNj+vvtP0rBwSfGAv+O+MnZACQ9QjsAIOVZQGdZNwB1yTkXmcQtN29L1/Q5U+TmzZKzgB4dS16yPnaf0Pl3bJlYbe330pJvKj1iIDUsiLSK261SiLf1sIN+h0SCunVl34GgUks6gPTANxwAAABgO9zqZXLL50urlkirl/uu69Fu7CovjQvifs3xGW9t/SBZ2ZEgXmlt8KD3EAVtu0bKreW8YWFsgriqgoJmtfcCASQ9QjsAAAAyu8XcQviqpXKrl/pwHux3vIL6DSL7p74u99nE7T+AdW3fHNr92uC5eZvHkm/uum4/bdK2KkN2gpYdJbsBwE4Q2gEAAJBR3LfT5b6YvDmkL/Ut5pUFPfeV2u4e2WjVUWrbVUGTVlKT1lJBs7jJ3Sp3Rw867uFvAFCTCO0AAABIn1nYbRz56qVyFsajreerlyr0kwsVtOoUOa5ohdzsj7bc0bqlF7aQmrZWYME8L3/Lrt77SXYDgAQhtAMAACClOBsbbmG8oLmCzQE7/Pn7chMf2arVPHafVUtjoT1o30M68KeRZcwspBc2r9ayZwCQCPx1AgAAQFJyJRukpXMjrebWeh7tzm5j0C18j/ylgh57RX6vny9ngd1azRu3lJq0UtC0jQ/lPpw33y32uEHzdv4GAKmA0A4AAICEcbb++KplsUAedOmnoE2XyM5FXyn8wv9t+44NCqSyTVu223VX6OybIq3m25mFHQBSEaEdAAAAdbuE2pTXtrSab1gTf0B29pbQ3qyNZK3lTdtExpo3baWgiW23VlC/Ydzd/PrlO1nDHABSEaEdAAAANT8hnE0Ct/RbaclcBR16Keg+OLKzokxu+ptbt5pv7sYetOgQK7agnnXWn+q49gCQXAjtAAAA+FFceZk0b4acjT9f8q20bJ5kk8VFlZduCe2NWynYe+SWmdotrG9eEx0AsDVCOwAAAHZt5vZl8605XUGHnpHCinKFX7jH9m45sF6O1KqT7+oedOwdKw7qZSs4YFQCag4AqYnQDgAAgG1y4Qrp+8WR1nNrRV86V/r+Ox/Y1barsjpc7Y8LcvOkrntGxpm37hwZk96sLRPCAUANILQDAABAzoJ4yYbYuucm/NA10prlWx/cqKmCwuZxRVk/ubAuqgkAGYfQDgAAkIHcpo3S0nmRceg2YZy1ojun0C/uVBAEkYOatZU2rpNad1JgLeitu0Ra0vMbJ7r6AJAxCO0AAAAZJPzReLnPJ0urlmy907qzb1wrNSyMbI44R8rNUxCE6r6iAACP0A4AAJBu3dyLVsZaz60lPTTqEgU5eZEDrOU8GtgLm29pPbdx6C06KMjOiT1W1bXQAQB1j9AOAACQ4tyKhXJffxqZKM5uxevjD1g6X9o803uwxwF+3XS17qKgQaPEVBgAUG2EdgAAgFRqRV+9VG7+5wq69I9NBue+myM3+YUtB2bVk1q0j7Wiq/lusV1Bi3aS3QAAKYHQDgAAkOzroi/8Um7eDLm5M6W1KyM7bL3zvgf5X4N23aVe+0Zazy2kW2Cvl53YigMAagShHQAAIAm51UsVnvQf6bs5UkV5fCv6bt0VbJ4szgTN2yk48rzEVBQAUKsI7QAAAMnQmr7gCx/Ig859I4X1830Luy3D5ieM69Q3sq99TwXZuYmuMgCgjhDaAQAAEjE2/fvFm7u8z4i0pocrpLZdlbU5tAd5+b71PGjZUWrSasva6QCAjEJoBwAAqEPht56U++pjad2q+B2FLRS06uQDfTSgh3ruk5hKAgCSBqEdAACgtlrTV34n991XCg04bEt50YpIYLex6e16KujcJ9LtvTGt6QCArRHaAQAAaojbVCwt+Nx3eXfzZkrrV0fKO+6hoEkr/3to8Aipz4FS+x6MTQcA7BShHQAA4EeygB7+6CVp8deRselRWdl+4jiVl8aKgrZdE1NJAEBKIrQDAADsArdpozT/c8mWWWvaOlJoS7Itmh353bq5W5f3Tn2ldtaanpPQ+gIAUhuhHQAAYKdj0xdFurzbTO9LvvGt6cE+IxXsPypykC3DdujP/Nj0oHHLRFcZAJBGCO0AAADbaVF3bz4RGZu+YU38ziatpbxGsc0gp76CPYfWfSUBAGmP0A4AADKeb01fsUBaX6SgS79IYXZ9uW+mSiXrpXo5UodeCjpFur0HjVskusoAgAxBaAcAABnJlWyQmz9Lmjdzc2t6kZTfRKHzbvNLrwWhkIJDTlbQsEDarbuCetmJrjIAIAMR2gEAQEZx305TeNqbPqzLhbfssOXXWnWUSoul3Aa+KNR7SOIqCgCA/VukJHHLLbf4q9qXXHJJrKykpEQXXnihmjVrpvz8fI0ePVrLli2Lu9+CBQs0cuRINWjQQC1bttQVV1yh8vLyBLwCAACQrF3ffff36LaF9bnTI4G9WVsFg4YrdMJlCl3wF2Ude7GCzYEdAIBkkBQt7R9//LHuv/9+9eu3eQzZZpdeeqnGjx+vp556SoWFhbrooos0atQovffee35/RUWFD+ytW7fW+++/ryVLluiMM85Qdna2brrppgS9GgAAkAzcmuVyn0+W+2KyQiPO9suvmaDPgVJOnoLeQxQ0bZPoagIAsEOBq3zpOQHWr1+vgQMH6p577tGf/vQnDRgwQHfffbeKiorUokULPfbYYzrhhBP8sV9++aV69eqlyZMna99999XLL7+so48+WosXL1arVq38Mffdd5+uuuoqrVixQjk51VsXde3atf6igD1nQUFBrb5eAABQy+PUv/rYh3Ut/jpWHvQ9WKHDz0ho3QAA+CE5NOHd4637u7WWDxs2LK58ypQpKisriyvv2bOnOnTo4EO7sZ99+/aNBXYzYsQI/+JnzZq13efctGmTP6byDQAApC5XslEVL96j8P1j5CY+EgnsQSB17KPgyPMUHHJSoqsIAEDqdY//73//q08//dR3j69q6dKlvqW8cePGceUW0G1f9JjKgT26P7pve26++WZdf/31NfQqAABAXfMdBdevVtCoaaQgN09aPl+qKJea7aZgj/0U9NxHQX6TRFcVAIDUDO0LFy7Ub37zG02YMEH169ev0+e++uqrNWbMmNi2tbS3b9++TusAAAB2nVu3Su6LD+Q+f1/auFah8+/wS7HZZLahoadLDQqkFu39NgAA6SBhod26vy9fvtyPZ4+yieXefvtt/d///Z9effVVlZaWas2aNXGt7TZ7vE08Z+znRx99FPe40dnlo8dsS25urr8BAIDk50qL5eZ8GgnqC2dbSWRHVra0YqHUpovfDDr1SWxFAQBIltBuS6q9+eab+uabb/Szn/1MjRo18pPB2eB5W5qtOoYOHaoZM2bElZ199tl+3LpNJGct3zYL/KRJk/xSb2b27Nl+ibchQyJrptrPG2+80Yd/W+7NWMu91aN3794/5KUBwI8Sdk5l4YrYdnYoSyFa/IAfLDz7I7lXH5TKS7cUtusRmfm922AF1i0eAIA0tsuhff78+TriiCN8eLYJ3Q4//HAf2v/85z/7bZu9vTrsPn36xF8Rb9iwoV+TPVp+7rnn+m7sTZs29UH84osv9kHdZo43w4cP9+H89NNP16233urHsV9zzTV+cjta0gHUtaLSYt05fZKWFm+Z3LJ1XoHG9BuqwhyCBVAdbuUiKQgpaNbWbwfN28lZYG/cKhLUew1RUNg80dUEACB5Q7uNQx88eLCmTZvmA3bU8ccfr/POO69GK3fXXXcpFAr5lna7IGAzw9vScFFZWVkaN26cLrjgAh/mLfSfeeaZuuGGG2q0HgBQncB++7SJWlmyPq58efE6X355/2EEd2A73IYiuS8/9Oupa/kCBT32UjDyl36fhffQaWMZpw4AyFi7vE67BfX3339fPXr08K3lFt67dOmiefPm+VbvjRs3KtWwTjuAH9sl/vop431AD0fH2lYSUqCWeY00dtBIusoDm7myUrlvp0bGqc+bJblwZEcoK9Lt/ajzCOkAgLRW3Ry6yy3t4XDYTxhX1aJFi3yIB4BMY2PYK3eJr8qCvO2343KzErrSJpA0wv+7I7KWelTrLpHu7z32VpBXvflxAADIBLv87dHGkd999936xz/+4bftKvj69es1duxYHXXUUbVRRwAAkMLc6mV+mbZg8AgFOZFlXoOue8rZOus2Rt1uTbe/6gsAAJlsl0P7HXfc4ceWW1f4kpISP3v8nDlz1Lx5cz3++OO1U0sgQZgJHAB+GFe8Xu6rTyLd35d8Eyls3EJB7/38r8GAoQoGDVcQhBJbUQAAktwuh/Z27dr5cexPPPGE/2mt7DbL+6mnnqq8PCZZQvpgJnBUl13Msf83djam3Y4D0pmrKJfmzlDYgvrc6ZJtG7vY2XEPBflNYscG9bITV1EAANJ5Irp0xER02NFM4JVDmIWv5vXzmQkcW+H/GUBya1cq/M+rthTYjO/W9b3nPgryGyeyagAApGwO3eU+aTfffLMeeOCBrcqtzNZqB9KhS7y1sFcNX36fnC+3/XYcEGWB3IK5tahXZtsEdqQjV7ZJ4WlvKPz6Y7GyoKB5ZCK5QcMVOv06ZZ1+nUI2jp3ADgBA3XWPv//++/XYY1v+gY7aY489dPLJJ+uqqypdYQdSEDOB44eyYG7LujEPAtKZ27hWburrclPfkErWS0FIbp+RChoW+v2hkb9IdBUBAEgru5w4li5dqjZt2mxV3qJFCy1ZsqSm6gUAKckCOhdzkI7cqqVyU16T+/y9LWPVC5srGDhc2jwjPAAAqHm7/M2yffv2eu+999S5c+e4citr27ZtTdYNAAAkAZsFPjzu3i0FrTortNcIqetABUywCABAcoX28847T5dcconKysp02GGH+bJJkybpyiuv1GWXXVYbdQTqFDOBA8h0zoZ4bChS0KhppKBjbyk3T2rXQ6FBI6Tduilg2AcAAMk5e7wd/tvf/lZ//etfVVpa6svq16/vx7Jfe+21SkXMHo+qmAkcQCZypSVyM9+V+3SClNdQoZ/9IRbOXckGBfUbJrqKAACkjerm0B+85Jutz/7FF1/4tdm7deum3NxcpSpCO7aFddoBZAq3fo3c1Ely096UNm2MFNbPV+j0sVta2wEAQGqF9nRCaMf22LJuzAQOIF251UvlPnpJ7osPpOjfusYtFQwaoaD3EAXZqXtBHgCAdMmhuzymfcOGDbrlllv8OPbly5crHA7H7f/2229/WI2BJMRM4ADS2veL5Wa9F/m9bVe/prq6DFAQCiW6ZgAAYLNdTiM///nP9dZbb+n000/3S78xEQ0AAMnPVZT7WeAVLldojwMihRbQ+x+moNc+Ctp2TXQVAQBATYT2l19+WePHj9f++++/q3cFAAB1zG0qlpv5ttynE6V1q6QGBXI99lFQL9u3qAdDT010FQEAQE2G9iZNmqhpUyalAQAgmbl1q+Q+myQ3/S2ptDhS2KBAwYDDbE23RFcPAADUVmj/4x//6Jd2e/jhh9WgQYNdvTsAAKhl4Rlvy036z5bJ5Zq2iUwu12tf38IOAADSOLTfcccd+uabb9SqVSt16tRJ2dnx//h/+umnNVk/AACwE34hmLJNCnLq++2gTRc5C+ztekQml+vcV0HA5HIAAGREaD/uuONqpyYAAGDXJ5eb/ZHcJ68qaNlBwRHn+vKgeTuFzr5RQZPWia4iAACo69A+duzYH/ucAADgR3AlG+VmvBWZXG7DmkjZ+tVy1tq+eW11AjsAAOmBBagBAEgRbu1KH9TdjLd9d3ivYaGCPYcp6HdwLLADAIAMDu0VFRW666679OSTT2rBggUqLS2N279q1aqarB8AANjMffGh3KcTIhvNdlMweISCnvsoyOIaPAAA6WqXZ6W5/vrrdeedd+qkk05SUVGRxowZo1GjRikUCum6666rnVoCAJBhnAvLfTtNbtHsWJm1pqtzP4VGXarQGdcrtMf+BHYAANJc4PyUs9W3++67669//atGjhypRo0aaerUqbGyDz74QI899phSzdq1a1VYWOgvQhQUFCS6OgCADObKy+S++EBuyqvSqiVS267KOvnqRFcLAAAkKIfu8uX5pUuXqm/fvv73/Px8/wTm6KOP1h/+8IcfU2cAADKWK14vN/1Nuc8mSRvXRgpz6itos7ufJZ4WdQAAMtMufwNo166dlixZog4dOvgW9tdee00DBw7Uxx9/rNxcJsABAGBXhT9+WW7yC1L55nli8psoGHi4gr4HKshtkOjqAQCAVArtxx9/vCZNmqR99tlHF198sU477TT961//8pPSXXrppbVTSwAA0lhQ2FzOAnuL9goGH6Gg+2Ba1gEAwA8b017V5MmT/a1bt2465phjlIoY0w4AqCuurFRu6utSXkOF+hwYKbN/ihd/7cevB0GQ6CoCAIBUHtNe1ZAhQ/wNAABsnwtXyH3+vtz7z0vrV0t5jeSsRT0nLxLUd+uW6CoCAIAkVK3Q/sILL+jII49Udna2/31HfvKTn9RU3QAASHm+Ff2bqQq/+7/IbPCmUVMF+x0r1WMuGAAAUAPd420Ndps1vmXLlv737T5YEKiiokKphu7xAIDa4JYvUPj1RyNd3039hgr2HqlgwGEK6mUnunoAACBduseHw+Ft/g4AAHbCAnu9nMhs8DbJXH1mgwcAANW3/WbzbSgrK9PQoUM1Z86cXbkbAAAZwa1dqfAXH8S2g5YdFAw/S6FzblLogFEEdgAAsMt2aSI6G9M+ffr0XX8WANgFYedUFt4y1CY7lKUQM2ojibnidXIfjpeb9oYNYpdr00VB45Z+X3SGeAAAgB9il2ePj67Lfsstt/ygJwSAHSkqLdad0ydpafHaWFnrvAKN6TdUhTl5Ca0bUJUr2yT36QS5j1+RSosjhe17ShXlia4aAADI1NBeXl6uBx54QBMnTtSgQYPUsGHDuP133nlnTdYPQIYF9tunTdTKkvVx5cuL1/nyy/sPI7gjKbiKcrmZ78h98KK0oShS2KK9QgeeIHXcg7XWAQBA4kL7zJkzNXDgQP/7V199FbePLykAfkyXeGtht8AeVvyiFrZt5bZ/7KCRdJVH4m0qlnvnaam0RCpsoWD/4xX02EtBsEtTxQAAANR8aH/jjTd29S4AsFM2hr1yl/iqLLjbfjsuN2uX/3QBP5pbNk9Bq07+96BBIwX7HW9XqxX0O1gB/08CAIBawrcMAAB2wC2fr/A7/5Pmz1Jo9GUKOvb25aGBwxJdNQAAkAF+UGj/5JNP9OSTT2rBggUqLS2N2/fMM8/UVN0AAEgYt2a53HvPys3+KFIQypL7/rtYaAcAAKgLuzz47r///a/2228/ffHFF3r22Wf92u2zZs3S66+/rsLCwtqpJYC0Z8u62SzxIW17vLqV2347DqhNbkORwpMeVfihazYH9kBBz30VOutGhQYenujqAQCADLPLof2mm27SXXfdpRdffFE5OTn6y1/+oi+//FInnniiOnToUDu1BJD2bHI5W9atef38rYK7bVu57WcSOtQm55zCz9wlN+11KVwhdeqj0GnXKnTUeQoat0h09QAAQAba5dD+zTffaOTIkf53C+0bNmzws8Zfeuml+sc//lEbdQSQIWw5N1vWrWVeo7hy22a5N9QWV17ml3Az9u9ZsNeRUuvOCp1whbJGXaqgJRekAQBACo1pb9KkidatW+d/32233fwScH379tWaNWu0cePG2qgjgAxiwdyWdbNZ4qOsSzwt7KhpLhyW+/IDufefVzB4hIIBh/nyoMfekRv/zwEAgFQK7RbO+/Tpo4MOOkgTJkzwQf2nP/2pfvOb3/jx7FY2dOjQ2q0tgIxgAZ1l3VCbXeA1d4bC7/5PWrkoUjbzXbn+h0Za2gnrAAAgiVT7W3G/fv2011576bjjjvNh3fz+979Xdna23n//fY0ePVrXXHNNbdYVAIAfxS3+JhLWF82OFOTmKdjrKAV7DiWsAwCApBQ43+Swc++8844efPBBPf300wqHwz6k//znP9eBBx6oVLd27Vo/831RUZEKCgoSXR0AQC0IfzjOL+HmZdVTMGCogr2PUpCXn+iqAQCADLS2mjm02hPRWTh/4IEHtGTJEv3tb3/TvHnzdPDBB6t79+7685//rKVLl9ZU3QEACRB2TpsqymM3204nQae+UhBSsMcBCp1zs0IHn0hgBwAA6dPSvi1ff/21b31/5JFHfGg/4ogj9MILLyjV0NIOINMVlRbrzumTtLR4baysdV6BX2YvFWftdyUb5D56yaaDV+jAE7aUr1utoFGThNYNAACgVlrat6Vr16763e9+58eyN2rUSOPHj9+l+997771+rLxV0G5DhgzRyy+/HNtfUlKiCy+8UM2aNVN+fr7vkr9s2bK4x1iwYIFfgq5BgwZq2bKlrrjiCpWXR5buAQBUL7DfPm2ilhdHVgaJsm0rt/2pwpWVKvzxywr/67dyn7wiN+U1uXWrYvsJ7AAAINX84ND+9ttv66yzzlLr1q19UB41apTee++9XXqMdu3a6ZZbbtGUKVP0ySef6LDDDtOxxx6rWbNm+f229vuLL76op556Sm+99ZYWL17snyeqoqLCB/bS0lI/Gd7DDz+shx56SNdee+0PfVkAkFGsC7y1sK8sWa+w4jte2baV2/5k7ypvy7eFZ7yj8IO/k3vnaWnTRqnZbgr95EIpn6AOAAAypHu8hWYLxXazrvH77befzj33XJ144olq2LBhjVSoadOmuu2223TCCSeoRYsWeuyxx/zv5ssvv1SvXr00efJk7bvvvr5V/uijj/b1atWqlT/mvvvu01VXXaUVK1YoJyenWs9J93gAmcrGrv/6/Sd3etxf9zsxaZfhc6uWKPzyP6Vl8yIFjZoq2P94BT33VRD6UR3KAAAAak11c2i1v4EdeeSRmjhxopo3b64zzjhD55xzjnr06FFT9fWt5taivmHDBt9N3lrfy8rKNGzYsNgxPXv2VIcOHWKh3X7aevHRwG5GjBihCy64wLfW77nnntt8rk2bNvlb5TcLAJCicupLq5dKOXkK9j1GwYDDFNTLTnStAAAAakS1Q7utx27LvVnLdlZWVs08u6QZM2b4kG7j123c+rPPPqvevXtr6tSpvqW8cePGccdbQI/OVG8/Kwf26P7ovu25+eabdf3119fYawAA1B3fQWzhbAUdevrtIL+JQiN/KbXsoKBhYaKrBwAAkJjQXluzwltrvQV06xJgFwXOPPNMP369Nl199dUaM2ZMXEt7+/bta/U5ASAZZYey/CzxNulc1THtJqRALfMa+eOSgVuxSOHX/yN9N0ehUZcq6NTHlwed+ya6agAAALUi4QMUrTXdZqE3gwYN0scff6y//OUvOumkk/wEc2vWrIlrbbfZ423yO2M/P/roo7jHi84uHz1mW3Jzc/0NADJdKAj8sm42S3zVyegssDevn+/323GJ5EqL5Sa/IPfpRJt1TqqXI7d+jRJbKwAAgNqXdDP0hMNhP97cArx1yZ80aVJs3+zZs/0Sb9ad3thP616/fPny2DETJkzwg/itiz0AYOdsHfbL+w/zLeqV2baVJ3KddusKH579scIPXuOXb/OBvdsghc6+UaE+BySsXgAAABnR0m7d1G2CO5tcbt26dX6m+DfffFOvvvqqn0XPZqa3buw2o7wF8YsvvtgHdZuEzgwfPtyH89NPP1233nqrH8dua8bb2u60pANA9VkwHztopMrCFbEy6xKf8Bb21x6Um7V5OdHClgod9jO6wgMAgIyS0NBuLeQ2E/2SJUt8SO/Xr58P7Icffrjff9dddykUCmn06NG+9d1mhr/nnnti97cJ8caNG+dni7cwb8vO2Zj4G264IYGvCgBSkwX0ZFvWLejSX+7LDxXsfZSCvY5iVngAAJBxdmmd9nTFOu0AkBzcN1OlijIF3feKbNs/UTZ2vVGTRFcNAAAguddpBwCgtriilQq/+bhkob1+vkLteynIy1dg3fMJ7AAAIIMR2gEACePKy/wEc+7DcVJ5qRTKUtD3QIlu8AAAAB6hHQCQEG7+55E111dHlupUux4KDT1NQbO2ia4aAABA0iC0AwDqnFu9TOH/3Wm/SQ0KFBx8koKe+0S6wwMAACCG0A4AqBM2qVw0lAdNWinof4gUCinY7zgFuQ0SXT0AAICkRGgHANQ6990chd96QqEjz/OB3QSHnUrLOgAAwE4Q2gEAtcZtXCf3zlNys96LbL/3rIKjf+l/J7ADAADsHKEdAFDjXDgsN/NtuXf+J23a6MuCPgcqOHB0oqsGAACQUgjtAIAa5ZbNU3jif6RlcyMFLdpHZoVv2zXRVQMAAEg5hHYAQI1y82ZFAntOXmSSuQGHKghlJbpaAAAAKYnQDgD40bPCa+NaBQ0L/XYwaLhUsl7BoBEK8hsnunoAAAApjdAOAPjB3MpFCk96VCrZoNBp1yrIqqegXrZfdx0AAAA/HqEdALDLXGmx3OQX5D6daLPOSfVypBULpdadE101AACAtEJoBwDsWlf4OZ8o/OYT0vrVkcKuAxU65GQFBc0SXT0AAIC0Q2gHAFSL21Ss8Lh7pfmzIgWFLRQ69GcKuvRLdNUAAADSFqEdAFA9OfWlinLJxq3vdZSCvY5UkJ2T6FoBAACkNUI7AGC73LfTpd26KshtoCAIFDr8TF8eNGmV6KoBAABkBEI7AGArbu1Khd94XPpmqoI9hyo49Ge+nLAOAABQtwjtAIAYV1EuN+VVuQ/GSeWlUihLys71E9BZSzsAAADqFqEdSFNh51QWrohtZ4eyFCJ0YQfcd3MUnvCwtGpJpKBdD4UOO1VB890SXTUAAICMRWgH0lBRabHunD5JS4vXxspa5xVoTL+hKszJS2jdkJzCs96Ve/Uhi+5SgwIFB52ooNe+tK4DAAAkWCjRFQBQ84H99mkTtbx4XVy5bVu57QeqCjr1leo3ULDHAQqd9SeFeg8hsAMAACQBQjuQZl3irYV9Zcl6ha3FtPI+OV9u++04ZDa3aaPCM96ObQcNCyNhfcTZCuo3TGjdAAAAsAXd44E0YmPYK3eJr8qCu+2343Kz+PhnKvftNIUn/FvasEYur5GCrnv68qBBQaKrBgAAgCr41g4AGcIVr5d743G5Lz+IFDRuKeXlJ7paAAAA2AFCOwBkAPfVJwq//qi0ca0UBAoGjVAw5FgF2TmJrhoAAAB2gNAOpBFb1s1mibdJ56qOaTchBWqZ18gfh8xhYd1NfT2y0aytQsPPVtCmS6KrBQAAgGpgIjogjdg67LasW/P6+T6gx+1T4MttP+u1Z+DM8KEsBfseo9Cp1xLYAQAAUgihHUgztg775f2H+Rb1ymzbylmnPf25davk5s2MbQdd+il0zs0K7XecgnrZCa0bAAAAdg3d44E0ZMF87KCRfpb4KOsSTwt7enMuLDfjbbm3n/Lj1kNn/FFBoyZ+X1DQLNHVAwAAwA9AaAfSlAV0lnXLHG7NcoVfe0haNDtS0GZ3qaI80dUCAADAj8Q3egBIYS4clvtsotx7z0rlpVK9HAUHjFIwYKiCECOgAAAAUh2hHQBSlKsoV/ip26TFX0cK2vdU6PCzFDRukeiqAQAAoIYQ2gEgRQVZ9RS07iy3cpGCg05U0PcgBcxbAAAAkFYI7QCQQtyKhZEu8E1a+e1g/+MVDBquoFHTRFcNAAAAtYDQDgApwJWXyX04Xu7jl6Q2XRQ68UoFQUhBdq5kNwAAAKQlQjsAJDm35FuFX3tQ+n5xpKBBgVS2ScrJS3TVAAAAUMsI7QCQpFzZJrn3n5P7dIItwu7DeuiwUxV0H5zoqgEAAKCOENoBIAm5ohUK/+9Oac1yvx302lfBIacoyMtPdNUAAABQhwjtAJCM8ptExqrnN1Fo2OkKuvRPdI0AAACQAIR2AEgSbuFsqe3ukaXcsuopdMyvpLx8BbkNEl01AAAAJEgoUU8MAIhwJRsUfvUBhZ+61c8QHxU0bklgBwAAyHC0tANAArmvP1N40iPShiKL6ZFZ4QEAAIDNCO0AkABu4zq5Nx6Tm/1RpKBJa4WGn6Vgt26JrhoAAACSCKEdAOqYW/C5wuPvl4rXS0FIweAjFAz5iYJ62YmuGgAAAJIMoR0A6lqjZlJZqdS8nUIjzlbQqlOiawQAAIAkRWgHgFrmnJOWfKOgbVe/HTRppdAJl0utOvpZ4gEAAIDtYfZ4AKhFbu1KhZ+5U+H/3iy36KtYebB5aTcAAABgR/jGCAC1wLmw3LQ35d55OjIjfFa2XNFyBe26J7pqAAAASCGEdgCoYW71MoVfe1D6bk6kYLdukZnhm7ROdNUAAACQYhLaPf7mm2/WXnvtpUaNGqlly5Y67rjjNHv27LhjSkpKdOGFF6pZs2bKz8/X6NGjtWzZsrhjFixYoJEjR6pBgwb+ca644gqVl5fX8asBACk8/U2F/z02EtizcxUcdqpCJ15JYAcAAEDqhfa33nrLB/IPPvhAEyZMUFlZmYYPH64NGzbEjrn00kv14osv6qmnnvLHL168WKNGjYrtr6io8IG9tLRU77//vh5++GE99NBDuvbaaxP0qgBktHo5UkWZ1KG3QmfcoNCAwxQETB8CAACAHyZwflrj5LBixQrfUm7h/KCDDlJRUZFatGihxx57TCeccII/5ssvv1SvXr00efJk7bvvvnr55Zd19NFH+zDfqlUrf8x9992nq666yj9eTk7OTp937dq1Kiws9M9XUFBQ668TQHqNXVfR9woat9i87aS5M6TOfRUEQaKrBwAAgCRV3RyaVM0/VlnTtGlT/3PKlCm+9X3YsGGxY3r27KkOHTr40G7sZ9++fWOB3YwYMcK/AbNmzarz1wAgw8auP3mrwk/cLFcS6SFkQT3o0o/ADgAAgPSaiC4cDuuSSy7R/vvvrz59+viypUuX+pbyxo0bxx1rAd32RY+pHNij+6P7tmXTpk3+FmUBHwB2aWb4zybJvfuMVF7qx65r+UKpQ89EVw0AAABpJmlCu41tnzlzpt599906mQDv+uuvr/XnAZABM8Pb2PXhZyooaJ7oqgEAACANJUX3+Isuukjjxo3TG2+8oXbt2sXKW7du7SeYW7NmTdzxNnu87YseU3U2+eh29Jiqrr76at8VP3pbuHBhLbwqAOnExqqHP52g8CPXbZkZftjpCo0eQ2AHAABAeoZ2+xJsgf3ZZ5/V66+/rs6dO8ftHzRokLKzszVp0qRYmS0JZ0u8DRkyxG/bzxkzZmj58uWxY2wmehvI37t3720+b25urt9f+QYAO+LHqC+dF+kO36FXZGb4focwdh0AAADp2z3eusTbzPDPP/+8X6s9OgbdZtDLy8vzP88991yNGTPGT05n4friiy/2Qd1mjje2RJyF89NPP1233nqrf4xrrrnGP7aFcwD4UTPDl21SkJPnt4NDT5Ha91DQ50DCOgAAANJ/ybftfel98MEHddZZZ/nfS0pKdNlll+nxxx/3k8fZzPD33HNPXNf3+fPn64ILLtCbb76phg0b6swzz9Qtt9yievWqd02CJd8AVOXWLFf41Qel+g0U+slFhHQAAADUqOrm0KRapz1RCO0A4maGn/qG3DtPx2aGD502VkGT+FUqAAAAgLrIoUkzezwAJJpbsyIyM/yi2ZGC9j0VGn6WgsIWia4aAAAAMhShHUDG21brenDgCQr620RzSbHIBgAAADIUoR0AysvkPn0tEtjb9VBo+NkKGtO6DgAAgMQjtAPI3Jnh/YSYIQU2bn34OXLff0frOgAAAJIK30wBZBxXtELhp+/wXeKjgvY9FBpwGIEdAAAASYWWdgCZNXZ92puRsetlm+S+Xyxna65n5yS6agAAAMA2EdoBZARXtDIyM/zCLyMFu3VXaMTZBHYAAAAkNUI7gPRvXZ/+ltzbT/nWddXLicwMP+BQusIDAAAg6RHaAaS3VUvlXn9Msonnoq3rjVsmulYAAABAtRDaAaS1oFlbBfsdK2XXV7AnE80BAAAgtRDaAaQVt3alwhP/o5B1gW/RzpeF9jk60dUCAAAAfhBCO4C04JyTm/GW3FtP+rHr4bISZZ3020RXCwAAAPhRCO0A0qN1/bWHpQWfRwp266bQ8LMTXS0AAADgRyO0A0jx1vW35d5+UioticwMf8AoBXsOZew6AAAA0gKhHUDKcrM/kpv478hG264KjThHQZNWia4WAAAAUGMI7QBSVtB9L7mZ7yjo0l/BgKEKQrSuAwAAIL0Q2gGkDLf2e7kPxys45GQF2Tk+pIdGX6YgCBJdNQAAAKBWENoBpMbY9ZnvyL31RGTsem6egoN+6vcR2AEAAJDOCO0AkppbtyoyM/z8mZGCNrsr6HNgoqsFAAAA1AlCO4Akbl1/d3PrerGUla1g/+MVDDycsesAAADIGIR2AEnJTX5B7oMXIhttdo/MDN+0daKrBQAAANQpQjuApBT0PVBu+psKBo9QMHA4resAAADISIR2AEnBrVgoN3e6QnuP9NtBo6YKnXuLguzcRFcNAAAASBhCO4CEcuVlch+8KPfJK1K4Qq5VJwUd9/D7COwAAADIdIR2AAnjFs5WeMLD0pplkYKuA6VmbRNdLQAAACBpENoB1DlXskHu7af82utew0KFDjtVQbdBia4aAAAAkFQI7QDqfCm38NO3S8sX+O2g38EKDjhBQf0Gia4aAAAAkHQI7QDqVBAEfrK58HvPKnT4GQra9Uh0lQAAAICkRWgHUKucC8tNf1uq31ChHntFCrsNUmj3AQqy+BMEAAAA7AjfmAHUGvf9YoUn/lv6bo5UP1+uQy8Fefm+tV0EdgAAAGCn+NYMoMa5inK5j16S+2i8VFEuZecqGPITKZdx6wAAAMCuILSj1oWdU1m4IradHcpSyFpakZbc4q8jy7h9vzhS0LmfQkNPU1DQLNFVAwAAAFIOoR21qqi0WHdOn6SlxWtjZa3zCjSm31AV5uQltG6oeW7NCoWfuMUGsksNChQceoqC7ntFusMDAAAA2GWEdtRqYL992kStLFkfV768eJ0vv7z/MIJ7mgkat1DQ5yApXK7goBP9+HUAAAAAP1zoR9wX2GGXeGtht8AelovfJ+fLbb8dh9TlNhQp/PL/8y3sUcGw0xQacQ6BHQAAAKgBtLSjVtgY9spd4quy4G777bhcZhFPOc45uZnvyr39pLRpo1zxBmWNusTvCwKuBQIAAAA1hbQEYJe41csiE80tmh0paNlRoQOOT3S1AAAAgLREaAdQ/WXcprwmN/n5yDJu9XIU7HecgoHDFISyEl09AAAAIC0R2lErbFk3myXeJp2rOqbdhBSoZV4jfxxSg5v+lty7/4tsdOyt0NAz/MRzAAAAAGoPg09RK2wddlvWrXn9fB/Q4/Yp8OW2n/XaU0fQ9yCpbVcFR5yr0KgxBHYAAACgDhDaUWtsOTdb1s1a1CuzbZZ7S35u3kxVvPB3uXCF3w7qZSt00m8V6r0f664DAAAAdYTu8ahVFszHDhrpZ4mPsi7xtLAnL1e8Tu7N/8p98UFke9qbCvYc6n8nrAMAAAB1i9COWmcBnWXdUmQZty8+8IFdJestokcmmdtj/0RXDQAAAMhYJCkAckUrFZ74iDR/ZqSgeTuFDj9TQZsuia4aAAAAkNEI7QAUnviwNP9zKauegn1/omDwCAX0jgAAAAASjm/lABQ65BSF33xcocNOVdCkdaKrAwAAAGAzQjuQYVxZqdwHL9pvCh14gi8LmrVV1ujLEl01AAAAAFUQ2oEM4hZ8GekKv2a5TQUv1+dABU1aJbpaAAAAALaD0A5kAFeyQe6tJ+VmvRspyG+yuSs8gR0AAABIZoR2IN2XcfvqE7k3HpM2rvVlQf9DFRwwWkFuXqKrBwAAAGAnCO1AOitZLzfhYam0WGraJrKM227dEl0rAAAAANUUUgK9/fbbOuaYY9S2bVsFQaDnnntuq1bCa6+9Vm3atFFeXp6GDRumOXPmxB2zatUqnXrqqSooKFDjxo117rnnav369XX8SoDk4TYV+8+OCfIaKTj4JL+MW+i0sQR2AAAAIMUkNLRv2LBB/fv319///vdt7r/11lv117/+Vffdd58+/PBDNWzYUCNGjFBJSUnsGAvss2bN0oQJEzRu3Dh/IeD888+vw1cBJAdXUa7wpxMV/tdV0tzpsfJQ3wMV2u9YBfWyE1o/AAAAALsucNEmuQSzlvZnn31Wxx13nN+2alkL/GWXXabLL7/clxUVFalVq1Z66KGHdPLJJ+uLL75Q79699fHHH2vw4MH+mFdeeUVHHXWUFi1a5O9fHWvXrlVhYaF/fGuxB1KJ/wh/O03ht5+UVi+LFHYdqKyfXJjoqgEAAAD4kTk0oS3tOzJ37lwtXbrUd4mPshe0zz77aPLkyX7bflqX+GhgN3Z8KBTyLfPbs2nTJv8GVb4Bqcgtn6/w07cr/PzfIoG9QYGCYWcodPQvE101AAAAAOk8EZ0FdmMt65XZdnSf/WzZsmXc/nr16qlp06axY7bl5ptv1vXXX18r9QbqSnjy83KTX7ToLmXVUzBouIK9jmJWeAAAACCNJG1Le226+uqrfReE6G3hwoWJrhKwy4JWnXxgD3rsrdDZNyrEMm4AAABA2knalvbWrVv7n8uWLfOzx0fZ9oABA2LHLF++PO5+5eXlfkb56P23JTc319+AVOFcWO6LD6RwWKE+B0QKO/dT6IzrFTRvl+jqAQAAAMi0lvbOnTv74D1p0qRYmY09t7HqQ4YM8dv2c82aNZoyZUrsmNdff13hcNiPfQfSgVs0W+HH/iT3yr/k3npCrnh9bPJGAjsAAACQ3hLa0m7rqX/99ddxk89NnTrVj0nv0KGDLrnkEv3pT39St27dfIj/wx/+4GeEj84w36tXLx1xxBE677zz/LJwZWVluuiii/zM8tWdOR5IVm71MoXfeVr6+tNIQU59BXsfJWXTSwQAAADIFAkN7Z988okOPfTQ2PaYMWP8zzPPPNMv63bllVf6tdxt3XVrUT/ggAP8km7169eP3efRRx/1QX3o0KF+1vjRo0f7td2BVOVKNsh9OE7us0lSuMKa1BX0O1jBkGMVNGBJQgAAACCTJM067YnEOu1IJm7ldwo/MtYGskud+ip00E8VNN8t0dUCAAAAkIAcmrQT0QGZwl83W/mdghaR8ekW0IP9Rylo2UFBpz6Jrh4AAACABCK0Awnkli9Q+K0npEWzFTrjBgXNInMxhGzsOgAAAICMR2gHEsCtXy333nNys97za60rq57csnmx0A4AAAAAhtAO1CFXtkluymtyH78slW3yZUGPvRUcMFpBYfNEVw8AAABAkiG0A3XEubDCj90off9dpKBNF4UOPklB266JrhoAAACAJEVoB+pIEIQU9NnfL+UWHHiCgu57KQiCRFcLAAAAQBIjtAO1xK1epvA7TyvU5wAFXfr7smDAUAX9D1NQLzvR1QMAAACQAgjtQA1zJRvkPhznW9QVrlB49TKFOvfzrepBFh85AAAAANVHgkgRYedUFq6IbWeHshSia3VScRXlctPfkpv8vFSyIVLYsY9CB/+UbvAAAAAAfhBCewooKi3WndMnaWnx2lhZ67wCjek3VIU5eQmtGyLcgi8UnvSItHpZpKBZW4UOOlFB576JrhoAAACAFBZKdAWw88B++7SJWl68Lq7ctq3c9iMJ2PJtFtjzGikYdrpCp19HYAcAAADwoxHak7xLvLWwryxZr7Bc/D45X2777TjULbd+jdz8WVsKuvSPhPVzblao3yEKQlmJrB4AAACANEH3+CRmY9grd4mvyoK77bfjcpngrE64sk1yU16T+/hlyeYVOOdmBXn5kUnm+h2S6OoBAAAASDMkPaAanAvLffGh3Lv/k9avjhS27hKZcC4vP9HVAwAAAJCmCO3ATriFsxV++0lp2bxIQaOmCg48QUGPvZkVHgAAAECtIrQnMVvWzWaJt0nnqo5pNyEFapnXyB+H2uE2FCn8vzv8euvKqa9g75EK9hymIDsn0VUDAAAAkAGYiC6J2Trstqxb8/r5PqDH7VPgy20/67XXHFeyUeHZH8e2g4aFCnrt68er+0nm9j6KwA4AAACgztDSnuRsHfbL+w/bap12a2Fnnfaa41Yvk/tsotys9/zyba75bgqatfX7guFn0w0eAAAAQEIQ2lOABfOxg0b6WeKjrEs8Lew/jrOl8my8+qevSd9Ot5LIjubtIhPMbUZgBwAAAJAohPYUYQGdZd1qtmU9PO5eacXCLYWd+yo0cLjUoRdBHQAAAEBSIAUiY7hwWEFo8zQO+U0iS7fVy1Gwx34K9jxcQdPWia4iAAAAAMQhtCPtuZXfyX06QW7ZPIVOu1ZBEPKTyYWOuVBq1lYB66wDAAAASFKEdqTvePV5MxX+dII0f9aWHYu+ktr39L8G7bonroIAAAAAUA2EdqQVV1Yq98VkPxO8vl8cKbTx6bvvqdCg4VLbromuIgAAAABUG6Ed6WXpt3IT/x35Pae+gj4HKthzqILCFomuGQAAAADsMkI7UppbPl9u1VKFeu4TKWjXQ9p9gIJ2PSKBPZd17AEAAACkLkI7UnIWeH07LTJefdFsKSdPrks/BTl5fqm2rGMvTnQVAQAAAKBGENqRMlxpidys9+Q+nSgVLY8UhrIUdO4nlZb48A4AAAAA6YTQjpTgvpmq8Cv/lDYVRwpyGyjod7CCAYcpaNQ00dUDAAAAgFpBaEfScmWbFGTnRjaa7xZpTW/cSsHAYQr22H/LPgAAAABIU4R2JBUXrpCbM0VuygSpYaGyjr3Il9vs76FTfi+16qggCCW6mgAAAABQJwjtSAquZKPczLflPpskrVsVKayXI1e8XkFevt8MWndObCUBAAAAoI4R2pFQbs0KuU8nyM16VyrbFCnMa6Sg/6EK+h8SC+wAAAAAkIkI7UgoN2+G3NRJkY1muykYdLiCnvsqqJed6KoBAAAAQMIR2lFnXEW53OyPFNjM77sP8GVB7/3kFn6pUL9DpA69/DrrAAAAAIAIQjtqlXNhadl8uW+nyc14W9pQJNe8nUJd+vuAHuTUV9Yxv0p0NQEAAAAgKRHaUSvcnE/l5nwiN3+WVLx+y46GjRX03FsKV0hZ/O8HAAAAADtCakKNLNOmpXOlNrvHure7r6fIfflh5ICc+lKH3gq6DVLQfbACwjoAAAAAVAvpCT+IW7dKbt4sP5GcFnwubSpW6LSxUssOfn/Qa4jUqKmCTn0iYZ6gDgAAAAC7jCSFanOrl8pNf1tu3kzp++/id9ZvKK39fkto79QnEtgBAAAAAD8YoR07XENdoUBBQfNIgbWuT3k18rt1g2/deXM47yu16qQgFEpofQEAAAAg3RDaEePKNkmLvpKbOyPSmr5mmYKBhys45OTIAW27KehzoNSxtwIbo56Xn+gqAwAAAEBaI7RnOL92+tTXIyF90WyponzLzlCWtGljbDOol61g+FmJqSgAAAAAZCBCe4Zxm4ql1UsVtO4cKQhlyU15TVq/OrJtk8d17hsZj96+l4LcvITWFwAAAAAyGaE9zTnnpBULfUu6dXvXkm/8EmyhX97tx6DbEm3B4BF2YCSoN20TW7YNAAAAAJBYhPY05eZ/LvfFZLn5s6QNRfE76+dHWtYLmvnN0MDDE1NJAAAAAMAOEdrTgAuHpWXzpOa7KcjOjZQt+lLu8/cjB1hZ+56xZdiCxi0TW2EAAAAAQLUQ2lOU21AUmTzOur1ba3rJBoV+cpHUdU+/P+g6SCov9+PT1barn0QOAAAAAJBaCO0pxNk66dPeiIT15Qvid+bmyW1cq+ho9KBVR38DAAAAAKQuQnsqKS+T++ilLdsWzDttnum9TRcFtkQbAAAAACBtpE1o//vf/67bbrtNS5cuVf/+/fW3v/1Ne++9t9JJ0KSVgj2HSa06Kei0h4IGBYmuEgAAAACgFoWUBp544gmNGTNGY8eO1aeffupD+4gRI7R8+XKlm9ChpyjUewiBHQAAAAAyQFqE9jvvvFPnnXeezj77bPXu3Vv33XefGjRooAceeCDRVQMAAAAAIHNDe2lpqaZMmaJhw4bFykKhkN+ePHnyNu+zadMmrV27Nu4GAAAAAECySfnQvnLlSlVUVKhVq1Zx5bZt49u35eabb1ZhYWHs1r59+zqqLQAAAAAAGRTaf4irr75aRUVFsdvChQsTXSUAAAAAANJv9vjmzZsrKytLy5Ytiyu37datW2/zPrm5uf4GAAAAAEAyS/mW9pycHA0aNEiTJk2KlYXDYb89ZMiQhNYNAAAAAICMbmk3ttzbmWeeqcGDB/u12e+++25t2LDBzyYPAAAAAECqSovQftJJJ2nFihW69tpr/eRzAwYM0CuvvLLV5HQAAAAAAKSSwDnnlOFsyTebRd4mpSsoKEh0dQAAAAAAaW5tNXNoyo9pBwAAAAAgXRHaAQAAAABIUoR2AAAAAACSFKEdAAAAAIAkRWgHAAAAACBJEdoBAAAAAEhShHYAAAAAAJIUoR0AAAAAgCRFaAcAAAAAIEnVS3QFkoFzzv9cu3ZtoqsCAAAAAMgAazfnz2ge3R5Cu6R169b5n+3bt090VQAAAAAAGZZHCwsLt7s/cDuL9RkgHA5r8eLFatSokYIgSHR18AOuUNkFl4ULF6qgoCDR1UEN4bymH85peuK8ph/OaXrivKYfzmnqsyhugb1t27YKhbY/cp2WdhvYHwqpXbt2ia4GfiT7Y8UfrPTDeU0/nNP0xHlNP5zT9MR5TT+c09S2oxb2KCaiAwAAAAAgSRHaAQAAAABIUoR2pLzc3FyNHTvW/0T64LymH85peuK8ph/OaXrivKYfzmnmYCI6AAAAAACSFC3tAAAAAAAkKUI7AAAAAABJitAOAAAAAECSIrQDAAAAAJCkCO1ICjfffLP22msvNWrUSC1bttRxxx2n2bNnxx1zyCGHKAiCuNsvf/nLuGMWLFigkSNHqkGDBv5xrrjiCpWXl8cd8+abb2rgwIF+ps2uXbvqoYceqpPXmGmuu+66rc5Xz549Y/tLSkp04YUXqlmzZsrPz9fo0aO1bNmyuMfgfCafTp06bXVe7Wbn0vA5TX5vv/22jjnmGLVt29afn+eeey5uv81Pe+2116pNmzbKy8vTsGHDNGfOnLhjVq1apVNPPVUFBQVq3Lixzj33XK1fvz7umOnTp+vAAw9U/fr11b59e916661b1eWpp57yfxfsmL59++qll16qpVed2ee1rKxMV111lX+PGzZs6I8544wztHjx4p1+vm+55Za4YzivyfNZPeuss7Y6X0cccUTcMXxWU++8buvfWLvddtttsWP4rGYgmz0eSLQRI0a4Bx980M2cOdNNnTrVHXXUUa5Dhw5u/fr1sWMOPvhgd95557klS5bEbkVFRbH95eXlrk+fPm7YsGHus88+cy+99JJr3ry5u/rqq2PHfPvtt65BgwZuzJgx7vPPP3d/+9vfXFZWlnvllVfq/DWnu7Fjx7o99tgj7nytWLEitv+Xv/yla9++vZs0aZL75JNP3L777uv222+/2H7OZ3Javnx53DmdMGGCrUDi3njjDb+fz2nys/f897//vXvmmWf8uXv22Wfj9t9yyy2usLDQPffcc27atGnuJz/5ievcubMrLi6OHXPEEUe4/v37uw8++MC98847rmvXru6UU06J7bdz3qpVK3fqqaf6v+uPP/64y8vLc/fff3/smPfee8+f11tvvdWf52uuucZlZ2e7GTNm1NE7kTnndc2aNf4z98QTT7gvv/zSTZ482e29995u0KBBcY/RsWNHd8MNN8R9fiv/O8x5Ta7P6plnnuk/i5XP16pVq+KO4bOaeue18vm02wMPPOCCIHDffPNN7Bg+q5mH0I6kDQb2h+ytt96KlVkY+M1vfrPDP4KhUMgtXbo0Vnbvvfe6goICt2nTJr995ZVX+iBZ2UknneQvGqDmQ7t9UdgW+wJp/zA89dRTsbIvvvjCn3P7Mmk4n6nBPpO77767C4fDfpvPaWqp+oXRzmPr1q3dbbfdFvd5zc3N9V/6jH25s/t9/PHHsWNefvll/6Xyu+++89v33HOPa9KkSeycmquuusr16NEjtn3iiSe6kSNHxtVnn332cb/4xS9q6dVmjm0Fgao++ugjf9z8+fPjgsBdd9213ftwXhNne6H92GOP3e59+Kymx2fVzvFhhx0WV8ZnNfPQPR5JqaioyP9s2rRpXPmjjz6q5s2bq0+fPrr66qu1cePG2L7Jkyf7rj2tWrWKlY0YMUJr167VrFmzYsdYV8/K7BgrR82zLrXW/atLly6+e551izZTpkzx3TUrnwvrntWhQ4fYueB8Jr/S0lL95z//0TnnnOO75kXxOU1dc+fO1dKlS+Pe/8LCQu2zzz5xn03rZjt48ODYMXZ8KBTShx9+GDvmoIMOUk5OTtw5tGFPq1evjh3DeU7sv7P2ubVzWZl1sbVhS3vuuafvjlt56ArnNfnYUCIbZtSjRw9dcMEF+v7772P7+KymPhs2OH78eD+soSo+q5mlXqIrAFQVDod1ySWXaP/99/df+qN+9rOfqWPHjj4E2jgdG59nf3yeeeYZv9++aFYOAia6bft2dIwFhuLiYj9+EzXDvuTbOGT7IrFkyRJdf/31fmzVzJkz/Xmwf0iqflm0c7GzcxXdt6NjOJ91w8bhrVmzxo+rjOJzmtqi52Bb73/l82MhobJ69er5i6yVj+ncufNWjxHd16RJk+2e5+hjoPbYnCL22TzllFP8WOeoX//6134uCTuX77//vr/oZn+/77zzTr+f85pcbPz6qFGj/Dn55ptv9Lvf/U5HHnmkD11ZWVl8VtPAww8/7Od7svNcGZ/VzENoR9KxCa0s2L377rtx5eeff37sd2ups0mShg4d6v+h2n333RNQU+yIfXGI6tevnw/xFuaefPJJQlea+Ne//uXPswX0KD6nQHKzXk4nnniin3Dw3nvvjds3ZsyYuL/bdnH1F7/4hZ8s1iaFRHI5+eST4/7e2jmzv7PW+m5/d5H6HnjgAd9T0SaKq4zPauahezySykUXXaRx48bpjTfeULt27XZ4rIVA8/XXX/ufrVu33mr28ei27dvRMdbSQJCsXdaq3r17d3++7DxY12prpa16LnZ2rqL7dnQM57P2zZ8/XxMnTtTPf/7zHR7H5zS1RM/Btt7/yudn+fLlcfutW6bNUl0Tn9/oftReYLfP74QJE+Ja2bf3+bVzO2/ePL/NeU1uNhTNhiZV/nvLZzV1vfPOO76n2s7+nTV8VtMfoR1Jwa74W2B/9tln9frrr2/VpWdbpk6d6n9aS54ZMmSIZsyYEfcPVPRLSe/evWPHTJo0Ke5x7BgrR+2yJWastdXO16BBg5SdnR13LuwfJhvzHj0XnM/k9uCDD/pul7Z0247wOU0t9rfXvrBVfv9tWIKNf6382bQLbjY3RZT93bahTdGLNHaMLWtkIbHyObThMtYtM3oM57nuA7vNNWIX3Gws7M7Y59fGP0e7WHNek9uiRYv8mPbKf2/5rKZ2bzb7vtS/f/+dHstnNQMkeiY8wFxwwQV+iaE333wzbvmKjRs3+v1ff/21X9rClgabO3eue/75512XLl3cQQcdtNVSUsOHD/fLxtnyUC1atNjmUlJXXHGFn63873//O0tJ1ZLLLrvMn087X7asiC03ZEt72coA0SXfbFm/119/3Z/XIUOG+FsU5zN5VVRU+HNnM9FWxuc0Naxbt84vt2c3+xpw5513+t+js4jbkm+NGzf252/69Ol+5uJtLfm25557ug8//NC9++67rlu3bnHLSNmM87bc0Omnn+6XG/rvf//rz2nV5Ybq1avnbr/9dn+ebcUJlhuqnfNaWlrql+5r166d/9xV/nc2Orv0+++/72ejtv22tNR//vMf/9k844wzYs/BeU2ec2r7Lr/8cr/iiv29nThxohs4cKD/LJaUlMQeg89q6v0Nji7ZZufBVlepis9qZiK0IynYH61t3WztdrNgwQL/xb9p06Z+6SFbZ9S+0Fde/9nMmzfPHXnkkX4tSguIFhzLysrijrH1pAcMGOBycnJ8oIg+B2qWLdHVpk0b/z7vtttufttCXZQFgF/96ld+SRL7h+T444/3XyAr43wmp1dffdV/PmfPnh1Xzuc0Ndh7u62/t7Z8VHTZtz/84Q/+C5+dx6FDh251rr///nv/xT8/P98v13f22Wf7L6KV2RrvBxxwgH8M+xtgFwOqevLJJ1337t39ebZl/saPH1/Lrz4zz6uFuu39O2v3M1OmTPHLPdkF9Pr167tevXq5m266KS4AGs5rcpxTa9Swi58W1ixo2RJg5513XtxymobPaur9DTYWru3fSAvfVfFZzUyB/SfRrf0AAAAAAGBrjGkHAAAAACBJEdoBAAAAAEhShHYAAAAAAJIUoR0AAAAAgCRFaAcAAAAAIEkR2gEAAAAASFKEdgAAAAAAkhShHQCADBQEgZ577rlEVwMAAOwEoR0AgDRy1lln+UBut+zsbLVq1UqHH364HnjgAYXD4dhxS5Ys0ZFHHlmtxyTgAwCQOIR2AADSzBFHHOFD+bx58/Tyyy/r0EMP1W9+8xsdffTRKi8v98e0bt1aubm5ia4qAADYCUI7AABpxsK4hfLddttNAwcO1O9+9zs9//zzPsA/9NBDW7Wel5aW6qKLLlKbNm1Uv359dezYUTfffLPf16lTJ//z+OOP9/eJbn/zzTc69thjfUt+fn6+9tprL02cODGuHnbsTTfdpHPOOUeNGjVShw4d9I9//CPumEWLFumUU05R06ZN1bBhQw0ePFgffvhhbL/V216D1atLly66/vrrYxceAADIBIR2AAAywGGHHab+/fvrmWee2WrfX//6V73wwgt68sknNXv2bD366KOxcP7xxx/7nw8++KBvvY9ur1+/XkcddZQmTZqkzz77zLfuH3PMMVqwYEHcY99xxx0+iNsxv/rVr3TBBRf454g+xsEHH6zvvvvOP/+0adN05ZVXxrrxv/POOzrjjDN8L4HPP/9c999/v7/ocOONN9b6+wUAQLKol+gKAACAutGzZ09Nnz59q3IL2t26ddMBBxzgW9OtpT2qRYsW/mfjxo19632UXQCwW9Qf//hHPfvssz58W6t9lAV7C+vmqquu0l133aU33nhDPXr00GOPPaYVK1b4CwHW0m66du0au6+1qv/2t7/VmWee6betpd2ex4L92LFja/jdAQAgORHaAQDIEM45H8q3NXmdTVZnQdpazG3s+/Dhw3f4WNZKft1112n8+PG+Bd66rBcXF2/V0t6vX7/Y7/bcFvyXL1/ut6dOnao999wzFtirspb39957L65lvaKiQiUlJdq4caMaNGiwy+8BAACphtAOAECG+OKLL9S5c+etym3M+Ny5c/2YdxuXfuKJJ2rYsGF6+umnt/tYl19+uSZMmKDbb7/dt47n5eXphBNO8OPjK7MZ7Cuz4B7t/m732dmFAWttHzVq1Fb7bIw7AACZgNAOAEAGeP311zVjxgxdeuml29xfUFCgk046yd8sfFuL+6pVq3wruAVva+GuzFrArYXeJqiLBmybrX5XWCv8P//5z9jzbOtigo1/r9xlHgCATENoBwAgzWzatElLly71QXvZsmV65ZVX/Gzw1u3dJnar6s477/Qzx1tX9VAopKeeesp3Y7dx7MYmpbMJ5/bff38/M32TJk38GHib1M4mn7PW8z/84Q9x68BXh80ab7PLH3fccb5+VgebsK5t27YaMmSIrr32Wl9nm3XeLiRY3azL/MyZM/WnP/2pxt4vAACSGbPHAwCQZiykWwC2sG0t5jbxm80Qb8unZWVlbXW8Lcd26623+lnebek2azF/6aWXfEiOzgBvXeHbt2/vg3006Ft432+//XxwHzFihG8Z3xU5OTl67bXX1LJlSz9hXd++fXXLLbfE6miPOW7cOH+M1Wvffff1E9lVnigPAIB0FziblQYAAAAAACQdWtoBAAAAAEhShHYAAAAAAJIUoR0AAAAAgCRFaAcAAAAAIEkR2gEAAAAASFKEdgAAAAAAkhShHQAAAACAJEVoBwAAAAAgSRHaAQAAAABIUoR2AAAAAACSFKEdAAAAAIAkRWgHAAAAAEDJ6f8DAv0fbLOTGn0AAAAASUVORK5CYII="
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"
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
-   "execution_count": 63
+   "execution_count": 22
   },
   {
    "cell_type": "code",
@@ -1177,8 +1177,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:34.895896Z",
-     "start_time": "2025-12-21T14:55:34.889607Z"
+     "end_time": "2026-02-20T11:30:56.147108Z",
+     "start_time": "2026-02-20T11:30:56.140472Z"
     }
    },
    "source": [
@@ -1198,41 +1198,41 @@
      "text": [
       "* Selected model: Linear model\n",
       "* Nugget: 0\n",
-      "* Sill: 478.90567078851103\n",
+      "* Sill: 415.1536596743022\n",
       "* Range: 8000\n",
       "* Spatial Dependency Strength is Undefined: nugget equal to 0, cannot estimate\n",
       "* Mean Bias: None\n",
-      "* Mean RMSE: 107.47814162764915\n",
+      "* Mean RMSE: 113.53675299439662\n",
       "* Error-lag weighting method: equal\n",
       "\n",
       "\n",
       "+---------+--------------------+--------------------+---------------------+\n",
       "|   lag   |    theoretical     |    experimental    |   bias (real-yhat)  |\n",
       "+---------+--------------------+--------------------+---------------------+\n",
-      "|  1000.0 | 59.86320884856388  | 66.71388540855338  |  6.850676559989502  |\n",
-      "|  2000.0 | 119.72641769712776 | 130.66628344322854 |  10.939865746100779 |\n",
-      "|  3000.0 | 179.58962654569163 | 377.5405401178886  |  197.95091357219698 |\n",
-      "|  4000.0 | 239.45283539425552 | 250.66718626708865 |  11.214350872833137 |\n",
-      "|  5000.0 | 299.3160442428194  | 325.5561456427749  |  26.240101399955506 |\n",
-      "|  6000.0 | 359.17925309138326 | 387.4814906048632  |  28.30223751347995  |\n",
-      "|  7000.0 | 419.04246193994715 | 302.07493544556206 | -116.96752649438508 |\n",
-      "|  8000.0 | 478.90567078851103 | 469.53885776562294 |  -9.366813022888095 |\n",
-      "|  9000.0 | 478.90567078851103 | 486.79931370125183 |  7.893642912740802  |\n",
-      "| 10000.0 | 478.90567078851103 | 512.0646265352149  |  33.15895574670384  |\n",
-      "| 11000.0 | 478.90567078851103 |  529.991767276145  |  51.08609648763394  |\n",
-      "| 12000.0 | 478.90567078851103 | 582.4717932210419  |  103.5661224325309  |\n",
-      "| 13000.0 | 478.90567078851103 |  692.506923505966  |   213.601252717455  |\n",
-      "| 14000.0 | 478.90567078851103 | 649.5775483966735  |  170.67187760816245 |\n",
-      "| 15000.0 | 478.90567078851103 | 624.8696046337229  |  145.9639338452119  |\n",
-      "| 16000.0 | 478.90567078851103 |  643.74627487684   |  164.84060408832892 |\n",
-      "| 17000.0 | 478.90567078851103 | 571.3688648923311  |  92.46319410382006  |\n",
-      "| 18000.0 | 478.90567078851103 | 540.0470107890337  |  61.14134000052269  |\n",
-      "| 19000.0 | 478.90567078851103 | 600.2575887426275  |  121.35191795411646 |\n",
+      "|  1000.0 | 51.89420745928778  | 57.836141811479614 |  5.941934352191836  |\n",
+      "|  2000.0 | 103.78841491857555 | 86.03437765640514  | -17.754037262170414 |\n",
+      "|  3000.0 | 155.68262237786334 | 236.60954497912823 |  80.92692260126489  |\n",
+      "|  4000.0 | 207.5768298371511  | 268.7197011214077  |  61.142871284256586 |\n",
+      "|  5000.0 | 259.4710372964389  | 216.77470366578342 |  -42.69633363065549 |\n",
+      "|  6000.0 | 311.3652447557267  | 294.4056440278582  | -16.959600727868462 |\n",
+      "|  7000.0 | 363.25945221501445 | 383.72288068192313 |  20.46342846690868  |\n",
+      "|  8000.0 | 415.1536596743022  | 378.7119931185135  |  -36.44166655578874 |\n",
+      "|  9000.0 | 415.1536596743022  |  483.465464109033  |  68.31180443473079  |\n",
+      "| 10000.0 | 415.1536596743022  | 452.9072205931408  |  37.75356091883856  |\n",
+      "| 11000.0 | 415.1536596743022  | 412.07362484342366 |  -3.08003483087856  |\n",
+      "| 12000.0 | 415.1536596743022  | 491.23925913297296 |  76.08559945867074  |\n",
+      "| 13000.0 | 415.1536596743022  | 577.2518572511536  |  162.09819757685142 |\n",
+      "| 14000.0 | 415.1536596743022  | 575.1348087672814  |  159.98114909297914 |\n",
+      "| 15000.0 | 415.1536596743022  | 633.2991501319548  |  218.14549045765256 |\n",
+      "| 16000.0 | 415.1536596743022  | 659.1799840204877  |  244.0263243461855  |\n",
+      "| 17000.0 | 415.1536596743022  |  641.201731691203  |  226.0480720169008  |\n",
+      "| 18000.0 | 415.1536596743022  | 500.6074586569037  |  85.45379898260148  |\n",
+      "| 19000.0 | 415.1536596743022  | 448.75860119019325 |  33.60494151589103  |\n",
       "+---------+--------------------+--------------------+---------------------+\n"
      ]
     }
    ],
-   "execution_count": 64
+   "execution_count": 23
   },
   {
    "cell_type": "code",
@@ -1243,8 +1243,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:35.135733Z",
-     "start_time": "2025-12-21T14:55:34.981617Z"
+     "end_time": "2026-02-20T11:30:56.335654Z",
+     "start_time": "2026-02-20T11:30:56.206227Z"
     }
    },
    "source": [
@@ -1256,13 +1256,13 @@
       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ],
-      "image/png": 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LFRZkrSXaWr+NzZJvYdZaqK211i5ubG8rrf2NzVxvdbMx3tYr2fY988wzCXn9LKjbbOu2vNxhhx0W3W+vlYVeu7hgXeKt94V1J98Ro6vhdbM5EF577TU/vNpmorfzeuutt0aHENh9WsOwlbEl5ayXtzUmR0K5nX/rNWDP0VrtrRHaZs+3CxM1JbDZ6FTH2Trt1h3flqNgUjoAAIDqHdNuy4/ZpHObjmmPBMvm2Y3r7Jh268ZsLaB77LGHb7Da0Un+Np0zwF7XZg1yNLJbX+XV3/IY3kSxluL9998/ut43UNfe40XbmEMT3tIOAACA9GVBfETXPj5AbtoiHAmWdrwuBvbqYIHcgrld+Ihl28kc2AFsO/qRAwAAoFaCpc0SHzspnQVLC+wEy51jr5/1VLDJ/CKsSzwXQoD0QGgHAABAjSNY1ix7HVNt9v0pU6YkugpASkitdzYAAABSVioGSwBINMa0AwAAAACQpAjtAAAAAAAkKUI7AAAAAABJitAOAAAAAECSIrQDAAAAAJCkCO0AAAAAqn05tyAItHr1aqUSq/O4ceOq7f523313/eUvf1EiffPNN/55ffzxx9v8Nz/72c90+eWX12i9sO0I7QAAAAC2mQXALd1uvPFGJTur4/7777/Z/qVLl2rAgAG1Wg97zY455pjNjt1+++3+mAVo1G0slAkAAABgm1mwjXj66ac1atQozZs3L7ovJydHH3zwQULqVlpaqvr16+/w37do0UK1rWXLlnrjjTf03XffqXXr1tH9Dz/8sNq2bVvr9UHyoaUdAAAAwHYF28gtLy/PtwbH7rPQHjFz5kwdeOCBatiwoQ499NC4cG+ef/55de/eXQ0aNNCee+6pm266SeXl5dHjCxcu1AknnODvMzc3V6eeeqqWL1++WYv5P//5T+2xxx7+fox1yz/vvPO06667+r876qijNGvWLH9szJgx/nFsO9I7wPZV1j3egvTpp5+upk2bqlGjRv65zJgxwx/76quvfN0KCgp8/Xr27KlJkyZt9+vZvHlz9evXT48++mh037Rp0/T9999r0KBBcWXD4bB+//vf+3CflZXln/srr7wSV+a9997TAQcc4F8Lq+9HH3202WN+8sknvkeB1dvqf/bZZ/vHQ3IitAMAAABJxpVtqPpWXrbtZctKt6lsTfntb3+rO++807e816tXT+ecc0702FtvvaWhQ4fqsssu09y5c/Xggw/68PynP/0pGlAtFK9atUpTp07VxIkT9fXXX+u0006Le4wvv/xS//3vf/Xcc89Fx22fcsopWrFihV5++WV/4cAuDPTp08ffl/39lVdeqf3228/3GrDbpvdp1q5dqyOPPFKLFy/WCy+84EP+1Vdf7esVOT5w4EBNnjzZB2Pr4n7cccf5Cw3by16XyIWDSCv7mWeeuVmvgbvvvtu/nnfccYdmz56t/v376/jjj9f8+fOjdTr22GPVqVMn/7ztosbIkSPj7sMuaNhFDAv2dl4s9NuFELsgguRE93gAAAAgyYTvvbDqg3t0UcaJP00SFr7/cqk8PpxHte6gjFOv/qnsP6+WitduVixjxEOqCRbALfiaa6+91rccl5SU+FZga+22fcOGDfPHraX9D3/4gw/GN9xwgw/Dc+bM0YIFC9SmTRtf5l//+pcP2++//75v2Y50ibf91qpu3n77bd/abKHdWqONhVxrQf/Pf/6jCy64wLcw20WELXWHf+KJJ7Ry5Ur/WNbSbtq3bx893q1bN3+LsLqPHTvWB/yLL754u14nC9q//vWv9eabb6pHjx565pln/POw8B7Lnsc111yjX/ziF377z3/+s+9ab5Pd/e1vf/N1tosKDz30kH+N7bWy3gLDhw+P3sdf//pXH9hvvvnm6D57HHuNv/jiC+2zzz7bVXfUPEI7AAAAgBrRtWvXuLHbxsK0jdW2lut33nkn2rJuKioqfKhfv369PvvsMx8kI4HdWAtykyZN/LFIaG/Xrl00sBu7X2tx3mWXXeLqUlxc7Lu0bytrtbdwGwnsm7LHsJbsCRMm+NZ669Zvj7EjLe2ZmZk666yz9Mgjj/jeBBacY187U1RUpCVLluiwww6L22/bka7/9rrY30WGCZhevXrFlbeyFvRjhzFE2OtDaE8+hHYAAAAgyYQuua/qg0H8CNfQ8C0tKRbElz3vNtUmC6PRmgQb6xLbvdxa20866aTN/i42dG6NjTWPZfdrFwhs2blNWeDfVtnZ2Vs8bt3Orcu+tX5bC7yVP/nkk33L/46wLvIHH3ywH28eO4ygutnrY934rZV+U5ELK0guhHYAAAAgyQSZWQkvW9NsnLlNTBfb5TzWvvvuq0WLFvlbpLXdxr7bmGxrcd/S/S5btsx3f7d10itjY8WtVX9LrMXaJrizcfCVtbZbL4Ff/vKXOvHEE6Nh2NZE31HWld1uNlb9jDPO2Oy4TajXqlUr/7iRIQeRehx00EHR1+zf//53dAiCeffddzd7fWwOAHtt7DVC8mMiOgAAAAC1zpaKs7Ho1tr+6aef+q7dTz31lK6//np/vG/fvurSpYufkO3DDz/049Rt4joLrDYrelXs76xL+ODBg/Xaa6/5IG2zsdukeJGl6Cyw2lh56wJvs6Zv2LD5ZHw2a7yNebf7sWBs3dYt7E6fPt0f33vvvaOT31mXcwvakV4EO+r111/3Xe2r6hFw1VVX+RZyW2rPLnjYnAD2+DaZn7E6WI+G888/31/geOmll3xPgFgXXXSRvxBhz8/G61uX+FdffVW/+tWvtnohA4lBaAcAAABQ62zm8/Hjx/tgbePTDznkEN11111+jLqx8GlLwuXn5+uII47wYdwmq7PAuiX2dxZW7W8siNoYbZu47dtvv/XLm5khQ4b42d5//vOf+/HwTz75ZKWt8VY3W5LNZom3Cwi33nqrMjIy/PHRo0f7utlSdtbd3J6PtWLvDOvqv6Uu/JdeeqlGjBjhZ7+3+tjM7zbxnV1AMDZO/cUXX/QT+Nl4fLtQsWk3+EhrvQV0W2rO7ufyyy/3jxsKEQ+TUeCcc6rjbFIHW2OysLDQdzsBAAAAYoWdU1n4p1bIzFCGQv8bo70zrBuztfjGrjEOIH2UbOE9vq05lEEMAAAAwBYUlhZr9OzJWlZcFN3XIjtXI7r2UV79LU9WBgA7i/4PAAAAwBYC+x2zJmlF8Zq4/bZt++04ANQkQjsAAABQRZd4a2H/vmStwoofUWrbtt+OWzkAqCmEdgAAAKASNobdusRvGtgjbL8djx3rjupjU2+FY25MxYW6ijHtAAAAAJJKeTis5cVFKo+5IFIvlKGC7FzVY4Zz1DH8iwcAAAASjFbkLQf2jfsr/rd/59ZCB1LtvU1oBwAAACphy7rZLPEhVb60m+2341Zuhx8jM9P/XL9+/Q7fR7oFnMoC+6bBnYscSBWR93bkvb4j6B4PAAAAVMLWYbdl3WyW+E0no7PA3qxBjj++M+u1Z2RkqEmTJlqxYoXfbtiwoYJqWP89VdnY9ZKSLc/IXy6pOJS1U687UNPswpIFdntv23vc3us7itAOAAAAVMHWYR/Zre9m67Q3z25cbeu0t2jRwv+MBPe6HnRWbdh6r4MNWT/W6YsbSB0W2CPv8R0VOPqWqKioSHl5eSosLFRubm6iqwMAAIAkbAGOnSXeusRXd0tvRUWFysrKVJeVVpTrjx+9stVy1x9wjOpn0P6I5GZd4rfUwr6tOZR/6QAAAMBWWEDPquGQaF/ud6YLbTqo75yyGzTQiuI1lS61Z8MSrJdDTsNGdI9HncFEdAAAAACSah4Bmy9g0wkAq2seASDVENoBAAAAJN08AtaiHsu2bX91zCMApBK6xwMAAABIKhbMb+gxqMbnEQBSAaEdAAAAQJ2cRwBIBXSPBwAAAAAgSXHpCgAAAEhjtbFcHYCaQ2gHAAAA0lRhabFGz56sZcVF0X0tsnP9DOxM6AakBrrHAwAAAGka2O+YNcmveR7Ltm2/HQeQ/AjtAAAAQBp2ibcW9u9L1iosF39Mzu+341YOQHIjtAMAAABpxsawW5f4TQN7hO2347Fj3QEkJ0I7AAAAAABJitAOAAAAAECSIrQDAAAAacaWdbNZ4kOqfGk322/HrRyA5EZoBwAAANKMrcNuy7o1a5CzWXC3bdtvx1mvHUh+hHYAAAAgDdk67CO79VXz7MZx+23b9rNOO5Aa6iW6AgAAAABqhgXzG3oMipsl3rrE08IOpA5COwAAAJDGLKBnZfC1H0hVdI8HAAAAACBJEdoBAAAAAEhShHYAAAAAAJIUoR0AAAAAgCTFjBQAAAAAgJQXdi4tV0pIeEv74sWLddZZZ2mXXXZRdna2unTpog8++CB63DmnUaNGqWXLlv543759NX/+/Lj7WLVqlc4880zl5uaqSZMmOvfcc7V27doEPBsAAAAAQG0rLC3WTTMn6NJpz0Rvtm37U11CQ/uPP/6oww47TJmZmXr55Zc1d+5c3XnnncrPz4+Wue2223TPPffogQce0IwZM9SoUSP1799fJSUl0TIW2D/99FNNnDhR48eP15tvvqkLLrggQc8KAAAAAFBbCkuLdcesSVpRvCZuv23b/lQP7oGzpuwEufbaa/XOO+/orbfeqvS4Va1Vq1a68sorNXLkSL+vsLBQBQUFGjNmjH7xi1/os88+U6dOnfT+++/rwAMP9GVeeeUVDRw4UN99953/+60pKipSXl6ev29rrQcAAAAApEaX+JtmTvABPazNo21IgZpnN9YNPQYlXVf5bc2hCW1pf+GFF3zQPuWUU9S8eXMdcMAB+sc//hE9vmDBAi1btsx3iY+wJ3XwwQdr+vTpftt+Wpf4SGA3Vj4UCvmW+cps2LDBv0CxNwAAAABAaikLV2hZcVGlgd3YfjseO9Y91SQ0tH/99de6//77tffee+vVV1/V8OHDdemll+rRRx/1xy2wG2tZj2XbkWP20wJ/rHr16qlp06bRMpu65ZZbfPiP3Nq0aVNDzxAAAAAAgBQN7eFwWN27d9fNN9/sW9ltHPr555/vx6/XpOuuu853QYjcFi1aVKOPBwAAAABAyoV2mxHexqPH2nfffbVw4UL/e4sWLfzP5cuXx5Wx7cgx+7lixYq44+Xl5X5G+UiZTWVlZfkxA7E3AAAAAEBqyQxlqEV2rh+7Xhnbb8etXKpKaGi3mePnzZsXt++LL75Qu3bt/O977LGHD96TJ0+OHrfx5zZWvVevXn7bfq5evVozZ86Mlnn99dd9K76NfQcAAAAApKdQEGhE1z5q1iBns+Bu27bfjifbJHQpE9qvuOIKvfvuu757/JdffqknnnhCf//733XRRRf540EQ6PLLL9cf//hHP2ndnDlzNHToUD8j/ODBg6Mt88ccc4zvVv/ee+/52egvvvhiP7P8tswcDwAAAABIXXn1szWyW18/S3ws27b9djyVJXTJN2PrqtsY8/nz5/uW9REjRvgAHmHVu+GGG3yYtxb13r1767777tM+++wTLWNd4S2ov/jii37W+CFDhvi13XNycrapDiz5BgAAAACpv/xbWcws8dYlPplb2Lc1hyY8tCcDQjsAAAAAIBlzaL1arRUAAADqVEsSAGDnENoBAABSRGFpsUbPnqxlxUXRfTYrsk2ylOpjNgEASTgRHQAAALY9sN8xa5JWFK+J22/btt+OAwDSD6EdAAAgBbrEWwv79yVrFVb8dES2bfvtuJUDAKQXQjsAAECSszHs1iV+08AeYfvteOxYdwBAeiC0AwAAAACQpAjtAAAAAAAkKUI7AABAkrNl3WyW+JAqX9rN9ttxKwcg8Wx+iQ0V5dEb801gZ7DkGwAAQJKzddhtWTebJX7TyegssDdrkOOPs147kHgszYjqRks7AABACrAv+yO79VXz7MZx+23b9hMGgMRjaUbUhMA5+moUFRUpLy9PhYWFys3NTXR1AAAAqmTdbGNnibcu8bSwA8nx3rxp5gQf0Ctb6cF6xdhFtht6DOI9i+3KoXSPBwAASCH2ZT8rg69wQLIuzViV2KUZeQ9je9A9HgAAAACAJEVoBwAAAAAgSRHaAQAAAGAnsTQjagqhHQAAAACqaWlGW4Jx0+DO0ozYGYR2AAAAAKgGLM2ImsC0hQAAAABQTSyY27JuLM2I6kJoBwAAAIBqxNKMqE50jwcAAAAAIEkR2gEAAAAASFKEdgAAAAAAkhShHQAAAACAJEVoBwAAAAAgSRHaAQAAAABIUoR2AAAAAACSFKEdAAAAAIAkRWgHAAAAACBJ1Ut0BQAAAAAAySHsnMrCFdHtzFCGQkGQ0DrVdYR2AAAAAIAKS4s1evZkLSsuiu5rkZ2rEV37KK9+dkLrVpfRPR4AAAAA6jgL7HfMmqQVxWvi9tu27bfjSAxCOwAAAADU8S7x1sL+fclaheXij8n5/XbcyqH2EdoBAAAAoA6zMezWJX7TwB5h++147Fh31B5COwAAAAAASYrQDgAAAABAkiK0AwCAOsfGZW6oKI/eGKcJoC6zZd1slviQKl/azfbbcSuH2seSbwAAoE5hSSMAiGfrsNtnoM0Sv+lkdBbYmzXI8cdZrz0xaGkHAAB1BksaAUDl7KLlyG591Ty7cdx+27b9XNRMnMA5+oMVFRUpLy9PhYWFys3NTXR1AABADbAu8DfNnOADemUzJFtrkn05vaHHIFqTANTpz8rYWeKtSzyfiYnNoXSPBwAAdWpJo6rELmmUlcFXJAB1kwV0PgOTC93jAQAAAABIUoR2AAAAAACSFKEdAADUCSxpBABIRYR2AABQp5Y0sqWLNg3uLGkEAEhWhHYAAFBnsKQRACDVMC0gAACoUyyY27JuLGkEAEgFhHYAAFDnsKQRACBV8H8rAACwQ8LO0VoNAEANI7QDAIDtVlharNGzJ2tZcVF0n828bhO5MS4cAIDqw0R0AABguwP7HbMmaUXxmrj9tm377TgAAKgehHYAALBdXeKthf37krUKy8Ufk/P77biVAwAAO4/QDgAAtpmNYbcu8ZsG9gjbb8djx7oDAIAdR2gHAAAAACBJEdoBAAAAAEhShHYAALDNbFk3myU+pMqXdrP9dtzKAQCAFA/tN954o4IgiLt17NgxerykpEQXXXSRdtllF+Xk5GjIkCFavnx53H0sXLhQgwYNUsOGDdW8eXNdddVVKi8vT8CzAQAg/dk67LasW7MGOZsFd9u2/Xac9doBAEiTlvb99ttPS5cujd7efvvt6LErrrhCL774op599llNnTpVS5Ys0UknnRQ9XlFR4QN7aWmppk2bpkcffVRjxozRqFGjEvRsAABIf7YO+8hufdU8u3Hcftu2/azTDgBA9QmcS9yaLNbSPm7cOH388cebHSssLNSuu+6qJ554QieffLLf9/nnn2vffffV9OnTdcghh+jll1/Wscce68N8QUGBL/PAAw/ommuu0cqVK1W/fv1tqkdRUZHy8vL8Y+bm5lbzswQAID3Zsm6xs8Rbl3ha2AEAULXm0IS3tM+fP1+tWrXSnnvuqTPPPNN3dzczZ85UWVmZ+vbtGy1rXefbtm3rQ7uxn126dIkGdtO/f3//5D/99NMEPBsAAOoOC+hZGfWiNwI7AADVr54S6OCDD/bd2Tt06OC7xt900006/PDD9cknn2jZsmW+pbxJkyZxf2MB3Y4Z+xkb2CPHI8eqsmHDBn+LsJAPAAAAAECySWhoHzBgQPT3rl27+hDfrl07PfPMM8rOrrnxcLfccou/QAAAAAAAQDJLePf4WNaqvs8+++jLL79UixYt/ARzq1evjitjs8fbMWM/N51NPrIdKVOZ6667zo8biNwWLVpUI88HAAAAAIC0Ce1r167VV199pZYtW6pHjx7KzMzU5MmTo8fnzZvnx7z36tXLb9vPOXPmaMWKFdEyEydO9IP4O3XqVOXjZGVl+TKxNwAAAAAAkk1Cu8ePHDlSxx13nO8SbzPA33DDDcrIyNDpp5/uZ9E799xzNWLECDVt2tQH60suucQHdZs53vTr18+H87PPPlu33XabH8d+/fXX+7XdLZgDAJDsmIEdAAAkbWj/7rvvfED/4Ycf/PJuvXv31rvvvut/N3fddZdCoZCGDBniJ46zmeHvu+++6N9bwB8/fryGDx/uw3yjRo00bNgw/f73v0/gswIAYNsUlhZr9OzJWlb804SoLbJzNaJrH9Y6BwAAiV+nPVmwTjsAIBGB/Y5Zk/R9yVqF9dP/ikMK1KxBjkZ260twBwAgjaXMOu0AANTFLvHWwr5pYPfH5Px+O27lAABA3UZoBwCgltkYdusSv2lgj7D9djx2rDsAAKibCO0AAAAAACQpQjsAAAAAAEmK0A4AQC2zZd1slnibdK4ytt+OWzkAAFC3EdoBAKhltg67Letms8RvGtwjs8fbcdZrBwAACV2nHQCA6mCrl7o5U6U1q6osE+zTU8GubTaW/2GJ3OfvVl12rwMUtNhjY9kfl8vNfafqsrt3UbDb3hvLFv2wsR5VlW3bSUGbjv733NIN+k1xsWYsX6S15RuiZXLqZenggt3VYMlX0u6dN95v8Rq5DydWfb8t91KwZ7eNZTcUy33wctVlC3ZX0L77xrLlZXIzXqyyrJq1UahDz41lw2G56eOqLpvfUqFOvaKb4Wnj7I8qL5vXXKHOvX8q++6LUkVZ5WUbN1Wo689+KvveS1JZSeVlG+YpdECfn8rOfE0qWVt5Wbtg0qPfT2U/fl1at7ryspkNFDpo4E9lZ9u/tR8qL5uRqdAhx/1U9tO3pdUrKi+rkEKHDf6p7GfvSquWVFFWCnqdoOB/vS/C896Xvl9UddmDjlWQWd//7r78UG75N1WXPXCAgqyNywu6r2fLLf2y6rLdj1aQ3Xhj2W8/lftuXtVlu/1cQU7+xrKL5skt/LTqsl2OUJDbbGPZJV/KLZhdddlOhynIL9hYdtkCua8+qrpsx0MU7NJqY9mVi+S+eD9lPiPc2tVys16vuuxu+yjgM4LPiBh8Rmz+GZEuCO0AgJQXBIGcArkZE6ou1LRV9Au57Ev2lso23iX6hVxF32+5bIOc6Bdyrf1xy2Xr1Y9+IVfxGtX/4FUdXlk5+/ISyoh+IVfJ+i3f7wF9ol/I7cvqFst2Pjz6hdy+BG+pbNDhYOl/X8jty/UW73ev/aWYL+TOvjhXNft9205SzBdyZ1+cN6yvvGzLvaSYL+Tuo8lVf3Fu1tq/FtGys6ZIq5dXXrZJcynmC7mb86a0soovuI3ypJgv5G7uNGlJFV9a62dLMV/I3eczpG/nVl7WvlzHfCF3X3wgbSmAHnL8TxtffbTxvqsq26O/FPlCvmDOxudXVdmuP5ciX8gXzt1y+Ot0qBT5Qm7/Tt/bwr+fvXtIkS/k9iV7S//Wdu8iRb6QWxDfUtnd9pEioX3Fwi2Xbb67FAnt3y9Ouc+ILZY9yPEZYfiMiOIzYvPPiHRBaAcApCznwgqCjSO9AvuCt65QKq681STIb/HTRl4zBfv/9MVts7L/+5LvNW665bK7tv1po2HelssW7B7/RX5LZe2LaERW9pbL2heUiMysLZZVq5j7DdXbctmCdjEPEtpy2Wa7xddp/6OkcBWtaE1bbNaCovIqWtHymsWXtfO8objysjlN4staQFi/pvKyDRvHl+1wkBT7OsbKarD5F83mMa9NrHqZ8WX3OsC3MFZqk+EPwZ5d/b+3KsWWb7efggY5VZfNiPmK16ajgoz4esXJzPrpISxcVnXeTFbDn8rav6Ut/Zv43xd3X9b+LW2pbKOfzp0Pzlsqm7vLT2Xt392WyjbZNf4zYEvvIz4jNuIzYiM+I9LiMyJdBM76FNZxRUVFysvLU2FhoXJzcxNdHQDANrAueuFpYxUacqVcg0Zxa5rbBG6MBwcAAOmQQ2lpBwCk3vj1jybLTX3KNlTy7gu6tXGulhUXRcvYzOs2kVuedUMEAABIYcweDwBIGS5cIff6Y3JTnvSBvWzfXvpzw0ZaURzfvdG275g1SYWlVXSRBAAASBGEdgBASnAb1is89u6NEwfZMmmHn6JbmhVoeel6hRU/0su2vy9Zq9GzJyvMKDAAAJDCCO0AgKTnir5X+KlbpG8/9bMrh46/UOXd+2pZyZrNAnuE7bcu87Fj3QEAAFINY9oBAMnPZq61mYMbNVFo8KUbZ5mtKE90rQAAAGocoR0AkPSC7MYKnXS5VC9LQeONa7oCAADUBXSPBwAk5frr4XfGKTznzbg1lGMDuy3rZrPEh2x8eyVsvx23cgAAAKmK0A4ASCqurFRuwt/lZrwoN/kxudUrKi1n67Dbsm7NGuRsFtxt2/bbcdZrBwAAqYzQDgBIGm5docLP3ib3xftSKENB36EKmjSvsrytwz6yW181z24ct9+2bT/rtAMAgFTHmHYAQFJwK79TeNzd0ppVUoNGCh13oYI2Hbf6dxbMb+gxKG6WeOsSTws7AABIB4R2AEDCua9nKzzhAalsg9SkQKETL1OQX7DNf28BPSuD/6UBAID0wzccAEDCuZWLNgb21h02trBn5yS6SgAAAEmB0A4ASLjgoIFSozwF+x6igBZzAACAKCaiAwDUOrdhvcJvPCFXWuK3gyBQqHNvAjsAAMAm+HYEAKhVbvVKhZ+/R/phibR+rYJBFyS6SgAAAEmL0A4AqDVu8XyFX/irVLxWyslX0LN/oqsEAACQ1AjtAIBaEf7sXbnXHpEqyqXm7RQ64RIFjfMTXS0AAICkRmgHANQo55zctOflZry4cUf77goNOE9BZlaiqwYAAJD0CO0AgJpVvEZuzlT/a9BzgILeJykImAcVAABgWxDaAQA1KmiY67vCux8WK9T58ERXBwAAIKUQ2gEA1c6t/E5a84OCPbv57aDlnv4GAACA7UNoBwBUK/f1bIUnPGCD2RX6xbUKmrdLdJUAAABSFqEdAFB9E859NFlu6lM+sKtNR6nxLomuFgAAQEojtAMAdpoLV8i98aTcrDf8dtD5cAV9zlKQwf9mAAAAdgbfpgAAO8VtWK/w+Aekbz+1uK7giJMV9OivIAgSXTUAAICUR2gHAOwUN2vKxsBer75CA89X0L57oqsEAACQNgjtAICdEhx4jLR6hYJuP1dQwKRzAAAA1SlUrfcGAKgT3II5chXl/vcgFFKo3y8J7AAAADWA0A4A2GbOhRV+Z5zCY/8iN+nffsZ4AAAA1By6xwMAtokrK5V79WG5L97fuKNhY9vrJ58DAABAzSC0AwC2yq0rVPj5e6VlC6RQhoK+QxXq3DvR1QIAAEh7hHYAwBa5lYsUHnePtGaVlNVQoeMvUtCmY6KrBQAAUCcQ2gEAVXLlZQqPvVta+6PUpEChEy9TkF+Q6GoBAADUGUxEBwCoUlAv088Mr7adFDr9NwR2AACAWkZLOwAgjgtXSD8uV7BLK78d7N5ZoXb7KQiYcA4AAKC20dIOAIhyG9b77vDhp2+V+3F5dD+BHQAAIDFoaQcAeK5w5cYJ535YItWrLxWulOgODwAAkFCEdgCA3OL5Cr/wV6l4rdSoiUKDL1VQ0C7R1QIAAKjzdii0l5eXa8qUKfrqq690xhlnqHHjxlqyZIlyc3OVk5NT/bUEANSY8Gfvyr32iFRRLjVvp9AJlyhonJ/oagEAAGBHQvu3336rY445RgsXLtSGDRt09NFH+9D+5z//2W8/8MADNVNTAEC1c/Nnyr38j40b7bsrNOA8BZlZia4WAAAAdnQiussuu0wHHnigfvzxR2VnZ0f3n3jiiZo8efL23h0AIJH26Cq1aq+g5wCFjhtOYAcAAEj1lva33npL06ZNU/369eP277777lq8eHF11g0AUAOcjVtv0FBBENq4DvvJI/1PAAAApEFLezgcVkVFxWb7v/vuO99NHgCQvNzKRQo/dpPc289F9xHYAQAA0ii09+vXT3/5y1/i1u5du3atbrjhBg0cOLC66wcAqCbu69kKP3WLtGaV3PwP5UqLE10lAAAAbEXgnHPaDtai3r9/f9mfzZ8/349vt5/NmjXTm2++qebNmyvVFBUVKS8vT4WFhX4GfABIJ/Z57T6aLDf1KduQ2nRU6NjhCrJZ7QMAACBRtjWHbndojyz59vTTT2vWrFm+lb179+4688wz4yamSyWEdgDpyoUr5N54Qm7WFL8ddD5cQZ+zFGTs0IqfAAAAqOUcut3d4029evV8SL/tttt033336bzzztvpwH7rrbf6rvaXX355dF9JSYkuuugi7bLLLn799yFDhmj58uVxf2dLzw0aNEgNGzb0rfxXXXWVv6gAAHWdXZMNv3jf/wJ7oOCIUxQcPYzADgAAkEK2O7Tfcsstevjhhzfbb/tsrfYd8f777+vBBx9U165d4/ZfccUVevHFF/Xss89q6tSpWrJkiU466aTocZsQzwJ7aWmpn9H+0Ucf1ZgxYzRq1KgdqgcApBO7EBp0PFjKzFLo+AsVOvAYvw8AAABpHNotXHfs2HGz/fvtt58eeOCB7a6Ada+3Vvt//OMfys/Pj+63LgIPPfSQRo8eraOOOko9evTQI4884sP5u+++68u89tprmjt3rh577DHtv//+GjBggP7whz/ob3/7mw/yAFAXuYqfehuFOhyk0Lm3KmjfPaF1AgAAQC2F9mXLlqlly5ab7d911121dOnS7a6AdX+31vK+ffvG7Z85c6bKysri9tvFgrZt22r69Ol+23526dJFBQUF0TI2SZ6NDfj000+rfMwNGzb4MrE3AEgH4bnTFR5zvdyaH6P7gobM1QEAAFBnQnubNm30zjvvbLbf9rVq1Wq77uupp57Shx9+6LvcV3ZxoH79+mrSpEncfgvodixSJjawR45HjlXFHs8G/Edu9pwAIJU5F1b4nbFyr/xTKlwpN+v1RFcJAAAA1WC7ZyM6//zz/WRx1gpu3dbN5MmTdfXVV+vKK6/c5vtZtGiRLrvsMk2cOFENGjRQbbruuus0YsSI6La1tBPcAaQqV1Yq9+rDcl+877eDngMUHHZioqsFAACARIR2m539hx9+0IUXXhgdN26h+5prrvFheFtZ9/cVK1b45eJiJ5aztd7/+te/6tVXX/X3v3r16rjWdps9vkWLFv53+/nee+/F3W9kdvlImcpkZWX5GwCkOreuUOHn75WWLZBCGQr6DlWoc+9EVwsAAACJCu0287DNEv+73/1On332mV/qbe+9997uENynTx/NmTMnbt+vfvUrP27dLgBYy3dmZqZvxbel3sy8efP8Em+9evXy2/bzT3/6kw//ttybsZZ7W+OuU6dO2/vUAGCnhZ1TWbgiup0ZylCohmZsdz8uU/g/d0prVkkNGil03EUK2nSokccCAABAYuzwYr22bnrPnj13+IEbN26szp07x+1r1KiRX5M9sv/cc8/13dibNm3qg/gll1zig/ohhxzij/fr18+H87PPPtuvGW/j2K+//no/uR0t6QBqW2FpsUbPnqxlxT9NbtkiO1cjuvZRXv3s6n/AhnlS/QZSfoFCgy9TkB8/xwcAAADqYGhft26dbr31Vt8Cbi3c4XA47vjXX39dbZW76667FAqFfEu7zfhuM8Pfd9990eMZGRkaP368hg8f7sO8hf5hw4bp97//fbXVAQC2NbDfMWuSvi9ZG7d/RfEav39kt77VEtydcz+twZ6VrdBJV0j16ivIztnp+wYAAEDyCVzkG+A2Ov300zV16lTfum1Lv9kXx1g2uVyqsYnobBZ5WxveWvQBYHu7xN80c4IP6GFt/pEaUqDm2Y11Q49BO9VV3tZfd1OelPKaK3Rg/52sNQAAAFIhh253S/vLL7+sCRMm6LDDDtvZOgJAWrAx7LFd4jdlQd6OW7msjB0bleRK1is84X7p27lSEJJr311Bk113otYAAABIBdv97TE/P9+PMQcA1A63eqXC4+6WVi31XeFDA88nsAMAANQRoe39gz/84Q8aNWqU1q9fXzM1AgBEucXzFX7yjxsDe06+Qr+4VkH7n5bKBAAAQHrb7pb2O++8U1999ZUKCgq0++67+2XZYn344YfVWT+gzizfhdRl/y5slvitjWm3ctsj/Nm7cq89IlWUS83bKXTCJQoa51djzQEAAJB2oX3w4ME1UxOgri/fhZRlF3Ls30Vk9vjY4G6BvVmDHH98uy/4lKzbGNjbd1dowHkKMlnKEgAAoK7Z7tnj0xGzx2NLy3dVFsCqa/kupJeauNDjvvxI2qubgmC7RzMBAAAgDXIooZ3QjgQt34X0tDNDKty6Qrmpzyg46gwFDRrVYC0BAACQtku+VVRU6K677tIzzzyjhQsXqrS0NO74qlWrdqzGQB1avgvpywL6jvy7cCsXKTzuHmnNKrmKMmUcd2GN1A8AAACpZbv7W950000aPXq0TjvtNH9FYMSIETrppJMUCoV044031kwtASCNua9nKfzULT6wq0mBQr2HJLpKAAAASNXQ/vjjj+sf//iHrrzyStWrV0+nn366/vnPf/pl4N59992aqSUApCEbnRT+cKLCz98rlW2Q2nRU6PTfKMgvSHTVAAAAkKqhfdmyZerSpYv/PScnx7e2m2OPPVYTJkyo/hoCCVq+y8auV8b22/HtXb4LiOUqyuUmPyY35SlL7wo6H67QSVcoyM5JdNUAAACQyqG9devWWrp0qf99r7320muvveZ/f//995WVxXJESJ/lu2yW+E2D+04t3wXEKi2W+2aOzQeq4IhTFBw9TAFzJAAAAGBnQ/uJJ56oyZMn+98vueQS/e53v9Pee++toUOH6pxzztneuwOSki3PZcu62SzxsWyb5d5QHYLsxgoNvlSh4y9U6MBjFHARCAAAADWx5Nv06dP9zYL7cccdp1TEkm+oieW7gE25xfPl1qxSqOPBia4KAAAA0nXJt0316tXL34B0tKPLdwGbCn/2rtxrj/jx6y5vVwUt90x0lQAAAJACtimNvPDCCxowYIAyMzP971ty/PHHV1fdACDlOReWm/aC3IwXN+5o311qtluiqwUAAIB06h5va7DbrPHNmzf3v1d5Z0GgioqfuhKnCrrHA6gJrqxU7tWH5b54328HPQco6H2SgmC7pxMBAABAmqnW7vHhcLjS3wEAlXPrCjeuv75sgRTKUNB3qEKdeye6WgAAAEgx29XcU1ZWpj59+mj+/Pk1VyMASAPus3c3BvYGjRQaciWBHQAAADtku2bYsjHts2fP3rFHAoA6JOjRTypeo6Dz4QryCxJdHQAAAKSo7R5YedZZZ+mhhx6qmdoAQIqy6UH8DPFlG6JzfIQOP5nADgAAgJ2y3WtZlZeX6+GHH9akSZPUo0cPNWrUKO746NGjd65GAJBiXEW53JQn5WZNkdu7h0LH/prJ5gAAAJCY0P7JJ5+oe/fu/vcvvvgi7pi1LAFAXeJK1is84X7p27n2Kfi/9df5LAQAAECCQvsbb7xRTQ8NAKnNrV6p8Li7pVVLpXr1FRp4vgJbhx0AAABIVGgHAEhu8XyFX/irVLxWyslXaPAlCpq3S3S1AAAAkGZ2KLR/8MEHeuaZZ7Rw4UKVlpbGHXvuueeqq24AkJRceZnCEx7cGNgL2il0wiUKcvITXS0AAACkoe2eKempp57SoYceqs8++0xjx471a7d/+umnev3115WXl1cztQSAJBLUy9w42VyHgxU69RoCOwAAAJIntN98882666679OKLL6p+/fq6++679fnnn+vUU09V27Zta6aWAJBgrqxUbunX0e2gVXuFBl2gIDMrofUCAABAetvu0P7VV19p0KBB/ncL7evWrfOzxl9xxRX6+9//XhN1BICEcusKFX72NoX/c4fcykWJrg4AAADqkO0O7fn5+VqzZo3/fbfddvNLwJnVq1dr/fr11V9DAEggC+nhJ/4oLVsgZdSTSksSXSUAAADUIdsc2iPh/IgjjtDEiRP976eccoouu+wynX/++Tr99NPVp0+fmqspANQy9/UshZ+6RVqzSsovUOj03yrYbe9EVwsAAAB1yDbPHt+1a1f17NlTgwcP9mHd/Pa3v1VmZqamTZumIUOG6Prrr6/JugJArXDOyX00SW7q07Yhtemo0HEXKmjQKNFVAwAAQB0TOPt2ug3eeustPfLII/rPf/6jcDjsQ/p5552nww8/XKmuqKjIz3xfWFio3NzcRFcHQIKF570nZ0u62Ydk58MV9DlLgXWNBwAAAGo5h25z93gL5w8//LCWLl2qe++9V998842OPPJI7bPPPvrzn/+sZcuWVVfdASChgr17SLt3VnDEqQqOHkZgBwAAQPK3tFfmyy+/9K3v//73v31oP+aYY/TCCy8o1dDSDsDZuPWGudGA7lxYQbDdc3UCAAAAiWlpr0z79u31m9/8xo9lb9y4sSZMmLAzdwcACeEWz1f4sZvk3njSj2c3BHYAAAAkgx3u8/nmm2/67vL//e9/FQqFdOqpp+rcc8+t3toBQA0Lz50uN3GMVFEut3yBgrINUv0Gia4WAAAAsP2hfcmSJRozZoy/Wdf4Qw89VPfcc48P7I0aMasygOoRdk5l4YrodmYoQ6EgqNbHsO7vbtrzcjPGb9zRvrtCA85TkJlVrY8DAAAA1EpoHzBggCZNmqRmzZpp6NChOuecc9ShQ4edenAA2FRhabFGz56sZcVF0X0tsnM1omsf5dXPrpbHcGWlcq8+LPfF+3476DlQQe8T6RIPAACA1A3tth67Lfd27LHHKiMjo2ZrBaDOBvY7Zk3S9yVr4/avKF7j94/s1neng7uNWQ8/f6+0cK4UylDQd6hCnXvvZM0BAACABIf2VJwVHkBqdYm3FnYL7GHFL2ph27bfjt/QY9BOdZUPgkCh7n0VXrlIoWOHK2hDjyEAAAAkLxYfBpAUbAx7bJf4TVlwt+NWLmsH1k13pcUK/tdKH+zZTaFzb1XAhHMAAABIcgzgBJDWfHf4Dycq/PBv5FavjO4nsAMAACAVENoBpC1ny7i9/pjclKek9UVyn01PdJUAAACA7UL3eABJwZZ1s1nibdK5Tce0m5ACNc9u7MttC1eyXuEJ90vfzrV2dQVHnKKgR78aqDkAAABQc2hpB5AUbHI5W9atWYMcH9Djjinw++34tkxCZ93gw0/dvDGw16uv0PEXKXRgfz8JHQAAAJBKCO0AkoYt52bLulmLeizb3tbl3tz3ixV+8o/SqqVSTr5Cv7hWQfsDarDWAAAAQM2hezyApGLB3JZ1s1niI6xL/DYv85a368Zb7i4KnXCJgpz8mqssAAAAUMMI7QCSjgX07VnWzbmw/xkEIQWZ9RUafKmUmaUgM6sGawkAAADUPLrHA0hprqxUbsLf5aa9EN0XNMwlsAMAACAt0NIOIGW5dYUKP3+vtGyBFMqQ63yYAusaDwAAAKQJQjuAlORWLlJ43D3SmlVSg0YKHXcRgR0AAABph9AOIOW4r2cpPOFBqWyDlF+g0ODLFOQXJLpaAAAAQLUjtANIKeGPJstNedJmn5PadFTo2OEKsnMSXa20EHZux2ftBwAAQI0gtANILVnZPrAHnQ9X0OcsBdsxyzyqVlharNGzJ2tZcVF0X4vsXI3o2scvwwcAAIA6OHv8/fffr65duyo3N9ffevXqpZdffjl6vKSkRBdddJF22WUX5eTkaMiQIVq+fHncfSxcuFCDBg1Sw4YN1bx5c1111VUqLy9PwLMBUBtCnQ5V6LRrFRw9jMBejYH9jlmTtKJ4Tdx+27b9dhwAAAB1MLS3bt1at956q2bOnKkPPvhARx11lE444QR9+umn/vgVV1yhF198Uc8++6ymTp2qJUuW6KSTTor+fUVFhQ/spaWlmjZtmh599FGNGTNGo0aNSuCzAlCd3OqVqnjuLj9TfESw294K6LZdbV3irYX9+5K1CsvFH5Pz++24lQMAAEDtC5xLrm9iTZs21e23366TTz5Zu+66q5544gn/u/n888+17777avr06TrkkEN8q/yxxx7rw3xBwcZJqB544AFdc801WrlyperXr79Nj1lUVKS8vDwVFhb6Fn8AycEtnq/wC3+VitdK7bsr4/iLEl2ltLOholyXTntmq+XuOfRUZdGzAQAAoNpsaw5NaEt7LGs1f+qpp7Ru3TrfTd5a38vKytS3b99omY4dO6pt27Y+tBv72aVLl2hgN/379/dPPtJaX5kNGzb4MrE3AMklPHe6wv+5Y2NgL2in0FFnJLpKAAAAQK1LeLPJnDlzfEi38es2bn3s2LHq1KmTPv74Y99S3qRJk7jyFtCXLVvmf7efsYE9cjxyrCq33HKLbrrpphp5PgB2jnNhuWnPy80Yv3FH++4KDThPQWZWoqsGAAAA1LqEt7R36NDBB/QZM2Zo+PDhGjZsmObOnVujj3ndddf5LgiR26JFi2r08QBsG1dWKjfh79HAHvQcoNBxwwnsNciWdbNZ4kOqfI4A22/HrRwAAADqYGi31vT27durR48evgW8W7duuvvuu9WiRQs/wdzq1avjytvs8XbM2M9NZ5OPbEfKVCYrKys6Y33kBiAJVJTLff+dFMpQ0P9XCh1+soIg4R9Tac3WYbdl3Zo1yNksuNu27bfjrNcOAACQGEn3bTgcDvsx5xbiMzMzNXny5OixefPm+SXerDu9sZ/WvX7FihXRMhMnTvQh3LrYA0gtQYOGCg2+VKGTr1Rov96Jrk6dYeuwj+zWV82zG8ftt23bzzrtAAAAdXRMu3VTHzBggJ9cbs2aNX6m+ClTpujVV1/1s+ide+65GjFihJ9R3oL4JZdc4oO6zRxv+vXr58P52Wefrdtuu82PY7/++uv92u7Wmg4g+bmvZ8mt+VGhbj/z20GT5pLdUKssmN/QY5DKwhXRfdYlnhZ2AACAOhzarYV86NChWrp0qQ/pXbt29YH96KOP9sfvuusuhUIhDRkyxLe+28zw9913X/TvMzIyNH78eD8W3sJ8o0aN/Jj43//+9wl8VgC2ha026T6aJDf16Y3bzXbz668jcSygs6wbAABAckm6ddoTgXXagdrlbOz6G0/KzZ7it4POhyvoc5YCAiMAAADqiKJtzKF8QwZQq1zJeoUn3C99a6tEBAqOOEVBj34K6IYNAAAAbIbQDqDWuNUrFR53t7RqqVSvvkIDL1DQ/oBEVwsAAABIWoR2ALXGfTNnY2DPyVdo8CUKmrdLdJUAAACApEZoB1Brgm4/l8o2KNj3EAU5+YmuDgAAAJD0km6ddgDpw7mwwh9Oktuw3m/buPVQzwEEdgAAAGAbEdoB1AhXVio34e9yU55UePyDPsADAAAA2D50jwdQ7dy6QoWfv1datkAKZSjo2FNBwDVCAAAAYHsR2gFUK7dykcLj7pHWrJIaNFLouIsUtOmQ6GoBAAAAKYnQDqDauK9nKTzhQT/ZnPILFBp8mYL8gkRXCwAAAEhZhHYA1cKVlyn8+uMbA3ubjgodd6GCBo0SXS0AAAAgpRHaAVSLoF6mQidcIjfnTQVHnqYgg48XAAAAYGcxMxSAHeZK1sstnBvdDnZto9BRZxLYAQAAgGpCaAewQ9zqlQo/dbPCY++WW/JloqsDAAAApCWawwBsN7d4vsIv/FUqXivl5Ev16ie6SgAAAEBaIrQD2C7hudPlJo6RKsqlgnZ+HHtgwR0AAABAtSO0A9gmzoXlpj0vN2P8xh3tuys04DwFmVmJrhoAAACQtgjtALaJm/d+NLAHPQcq6H2igoBpMQAAAICaRGgHsE2CDj2lr2ZJ7Top1Ll3oqsDAAAA1AmEdgBVcj8skfJ29Wuw+1b1gecrCIJEVwsAAACoM+jbCqBS7utZCj/xR7lXH5Fzzu8jsAMAAAC1i5Z2AHEsoLuPJslNfdo25NYXKigvlZhwDgAAAKh1hHYgTYWdU1m4IrqdGcpQaCst5a6iXO6NJ+VmT/HbQefDFfQ5S0EGHxUAAABAIvBNHEhDhaXFGj17spYVF0X3tcjO1YiufZRXP7vSv3El6xWecL/07VyL6wqOOEVBj350iQcAAAASiDHtQBoG9jtmTdKK4jVx+23b9tvxyrrEh5+/Z2Ngr1dfoeMvUujA/gR2AAAAIMEI7UCadYm3FvbvS9YqLBd/TM7vt+NWLpaF89ChJ0p5zRT6xbUK2h9QyzUHAAAAUBm6xwNpxMawx3aJ35QFdztu5bIy6smtK1TQKM8fC9p0UOiXf2L8OgAAAJBEaGkH6iIXVvidsQo/8lu57xdHdxPYAQAAgOTCN3SgjskMVyj08j/l5s/02+6bTxQ02y3R1QIAAABQCUI7kEZsWTebJd4mndt0TLvJKyvVxV99otCaH6VQhoKjhyq0X++E1BUAAADA1tE9Hkgjtg67LevWrEGOQoqf+b31+rW69rMPtJsF9gaNFDr5SgI7AAAAkOQI7UCasXXYR3brq+bZjaP7Wq9foys/n6m8DcVSfoFCp/9WQesOCa0nAAAAgK2jezyQpsH9hh6D/CzxXkWF6hVtnFU+dNyFCho0SmwFAQAAAGwTQjuQpoJwheoHgYJQhmTLux1/kVSvPjPEAwAAACmE7vFAGnIl6xUed7fc1Kej+4KshgR2AAAAIMUQ2oE041avVPipm6Vv58rNeUuu8PtEVwkAAADADqLZDUgjbvF8hV/4q1S8VsrJV2jwJQrymiW6WgAAAAB2EKEdSBPhudPkJj4qVZRLBe0UOuESBTn5ia4WAAAAgJ1AaAfSQHjGeLl3xm7caN9doQHnKcjMSnS1AAAAAOwkQjuQBoJdWskpUHDQAAWHnaggYLoKAAAAIB0Q2oEU5ZxTEAT+98Ba14fepKDZbomuFgAAAIBqRHMckILcykUKP/EnuaKfZoYnsAMAAADph9AOpBj39SyFn7pFWr5A4Sk/rcMOAAAAIP3QPR5Ioe7w7qNJclOftg2pTUeFjh6W6GoBAAAAqEGEdiAFuIpyuTeelJs9xW8HnQ9X0OcsBRm8hQEAAIB0xjd+IMm5DesVHn+/9O1ci+sKjjhFQY9+0UnoAAAAAKQvQjuQ7EIZUvE6KTNLoYEXKNhr/0TXCAAAAEAtIbQDSS6wsH7CJVLxGgXN2ya6OgAAAABqEbPHA0koPHeawu+9FN0OGucT2AEAAIA6iJZ2IIk4F5abNk5uxoSN263aK2i9T6KrBQAAACBBCO1AknBlpXKvPiT3xQd+OzhooLRb+0RXCwAAAEACEdqBJODWFSr8/L3SsgV+4rng6KEK7dc70dUCAAAAkGCEdiDB3MpFCo+7R1qzSmrQSKHjL1LQukOiqwUAAAAgCRDagQRzy7/dGNjzCxQafJmC/IJEVwkAAABAkiC0AwkW6txbYecU7N1dQYNGia4OAAAAgCTCkm9ALXMV5Qq/M05u/ZrovlCXwwnsAAAAAJIrtN9yyy3q2bOnGjdurObNm2vw4MGaN29eXJmSkhJddNFF2mWXXZSTk6MhQ4Zo+fLlcWUWLlyoQYMGqWHDhv5+rrrqKpWXl9fyswG2zpWsV3jc3XIzXlT4xfvknEt0lQAAAAAksYSG9qlTp/pA/u6772rixIkqKytTv379tG7dumiZK664Qi+++KKeffZZX37JkiU66aSToscrKip8YC8tLdW0adP06KOPasyYMRo1alSCnhVQObd6hcJP3Sx9O1fKzFLowP4KgiDR1QIAAACQxAKXRE19K1eu9C3lFs6POOIIFRYWatddd9UTTzyhk08+2Zf5/PPPte+++2r69Ok65JBD9PLLL+vYY4/1Yb6gYOMEXg888ICuueYaf3/169ff6uMWFRUpLy/PP15ubm6NP0/UPW7xfIWf/6tUslbKyVdo8CUKmrdLdLUAAAAAJMi25tCkGtNulTVNmzb1P2fOnOlb3/v27Rst07FjR7Vt29aHdmM/u3TpEg3spn///v4F+PTTT2v9OQCbCs+dpvB/7tgY2AvaKXTGbwnsAAAAAFJr9vhwOKzLL79chx12mDp37uz3LVu2zLeUN2nSJK6sBXQ7FikTG9gjxyPHKrNhwwZ/i7CAD9QEV14m9+54qaJcat9doQHnKcjMSnS1AAAAAKSIpAntNrb9k08+0dtvv10rE+DddNNNNf44QFAvU6ETL5X7bIaCXscpCJKqcwsAAACAJJcUCeLiiy/W+PHj9cYbb6h169bR/S1atPATzK1evTquvM0eb8ciZTadTT6yHSmzqeuuu853xY/cFi1aVAPPCnWVW1coN39mdDvIb6HQoScQ2AEAAABst4SmCJsDzwL72LFj9frrr2uPPfaIO96jRw9lZmZq8uTJ0X22JJwt8darVy+/bT/nzJmjFStWRMvYTPQ2kL9Tp06VPm5WVpY/HnsDqoNbuUjhJ/6o8PgH5GyWeAAAAABI1e7x1iXeZoZ//vnn/VrtkTHoNoNedna2/3nuuedqxIgRfnI6C9eXXHKJD+o2c7yxJeIsnJ999tm67bbb/H1cf/31/r4tnAO1xX09S+EJD0plG6T8Ail3l0RXCQAAAECKS+iSb1WtUf3II4/ol7/8pf+9pKREV155pZ588kk/eZzNDH/ffffFdX3/9ttvNXz4cE2ZMkWNGjXSsGHDdOutt6pevW27JsGSb9gZ9hZyH02Sm/q0bUhtOip03IUKGjRKdNUAAAAAJKltzaFJtU57ohDasaNcRbncG0/IzZ7qt4POhyvoc5aCjKSZ4xEAAABACudQkgWwE2zCuY2BPVBwxCkKevSrsgcJAAAAAGwvQjuwE4IOB0lLvlTQtpOC9gckujoAAAAA0gyhHdhObunX0i4tFdTP9q3qwVFnJrpKAAAAANIUC0cD2yE8d5rCz/xZ4Zf+IRcOJ7o6AAAAANIcLe3ANnAuLDdtnNyMCRt3hDKkinIpVD/RVQMAAACQxgjtwFa4sg1yrz4s98UHfjvoOVBB7xMVBHRUAQAAAFCzCO3AFrh1hQqPu1davsC3rgdHD1Vov96JrhYAAACAOoLQDlTBOafwC3/dGNgbNFLouIsUtOmQ6GoBAAAAqEPo3wtUwWaGD9nM8M3bKnT6bwnsAAAAAGodoR3YpHXd/bg8uh0U7K7QmaMU5BcktF4AAAAA6iZCO/A/rqJcbvK/Ff73jXLLFsS1uAMAAABAIhDaAQvsJesVHnu33OypUnmZ3IpvE10lAAAAAGAiOsCtXqHwuHukVUulzCyFBl6gYK/9E10tAAAAACC0o25z332h8At/k0rWSjn5Cg2+VEHztomuFgAAAAB4hHbUWTZuPfzfO6WKcskmnDvhYgU5+YmuFgAAAABEEdpRdzVvJ+3eWQpCCg04T0FmVqJrBAAAAABxCO2oU1xZqU0Hr6BepoJQSKGB/yfVq6cgYE5GAAAAAMmHpII6w60rVPiZ2+Qm/cuvx26CzPoEdgAAAABJi5Z21Alu5aKNM8SvWSVXuELBmh+k3GaJrhYAAAAAbBGhHWnPfT1L4QkPSmUbpPwWG2eIJ7ADAAAASAGEdqQt6wLvPpokN/Vp25Da7qvQscMVNGiU6KoBAAAAwDYhtCNtubf+I/fBK/73oMuRCo46Q0EG/+QBAAAApA5m4ELaCnbfT8qop+DIUxX0PZvADgAAACDlkGKQVly4QkEow/8etO2k0Dm3KGjcNNHVAgAAAIAdQks70ob77guFx1wvt2ppdB+BHQAAAEAqI7QjLYTnTlP4v3dKq1fITXs+0dUBAAAAgGpB93ikNOfCctPGyc2YsHFH++4K+v8q0dUCAAAAgGpBaEfKcmWlcq8+JPfFB347OGiggsNOVBDQgQQAAABAeiC0IyW54jUKj71bWrZACmUoOHqoQvv1TnS1AAAAAKBaEdqRmjIb+OXc1KCRQsdfpKB1h0TXCAAAAACqHaEdKSmol+nDukrWK8gvSHR1AAAAAKBGMPgXKcE5p/CHExV+89noviC7MYEdAAAAQFqjpR1Jz1WUy73xhNzsqRu39+xKd3gAAAAAdQKhHUnNlaxXeML90rdzrW1dwZGnSLvtk+hqAQAAAECtILQjabnVKxQed4+0aqmUmaXQwAsU7LV/oqsFAAAAALWG0I4aF3ZOZeGK6HZmKEOhINji37jF8xV+/q9SyVopJ1+hwZcqaN62FmoLAAAAAMmD0I4aVVharNGzJ2tZcVF0X4vsXI3o2kd59bOr/sN1qzcG9oLdFTrhYgU5+bVTYQAAAABIIoR21Ghgv2PWJH1v4TvGiuI1fv/Ibn2rDO7BPj0VOi4k7d5ZQWZWLdUYAAAAAJILS76hxrrEWwu7BfawXPwxOb/fjls548o2KDz533JrVkXLBXv3ILADAAAAqNMI7agRNobdusRvGtgjbL8dt3JuXaHCz9wuN2uKwi/e79dkBwAAAADQPR6JtnKRwi/eJ1kLe4NGCh1xsoKtTFIHAAAAAHUFoR0J03n198p49napbIOUX6DQ4MsU5BckuloAAAAAkDQI7agRtqybzRJvk85t1kXeOfVZvkgnLZov36bepqNCx12ooEGjBNUWAAAAAJITY9pRI2wddlvWrVmDHIU2RvOo+s7psFXL/d6gyxEKnXQFgR0AAAAAKkFoR42x5dxsWbfm2Y3j9jdt1ESNTx6p4KgzFfQdqiCDDh8AAAAAUBnSEmo8uN/QY5DKVi1TsPgLuf0O813nrSVeu+yW6OoBAAAAQFIjtKPGBUu+VL3n/yqVrFOoUZ6CvfZPdJUAAAAAICUQ2lGjwnOnyU18VKoolwrabbwBAAAAALYJoR01wrmw3LRxcjMmbNzRvrtCA85TkJmV6KoBAAAAQMogtKPaubINCr/ykDR/pt8ODhqo4LATFQTMewgAAAAA24PQjmrnvp69MbCHMhQcPUyh/Q5LdJUAAAAAICUR2lHtQh16KvzDYgVt91XQukOiqwMAAAAAKYvQjmrhvvlEKthdQXaO3w4dOjjRVQIAAACAlMcgY+wU55zCM19T+Lm/KPzifXI2SzwAAAAAoFrQ0o4dZgHdvfGE3OypfjvIL0h0lQAAAAAgrRDasUNcyXqFx98vLZxrcV3Bkaco6N5PQRAkumoAAAAAkDYS2j3+zTff1HHHHadWrVr5sDdu3LjNul6PGjVKLVu2VHZ2tvr27av58+fHlVm1apXOPPNM5ebmqkmTJjr33HO1du3aWn4mdYtbvULhp27eGNgzsxQ64WKFevQnsAMAAABAOoX2devWqVu3bvrb3/5W6fHbbrtN99xzjx544AHNmDFDjRo1Uv/+/VVSUhItY4H9008/1cSJEzV+/Hh/IeCCCy6oxWdRB8ewv/R3adVSKSdfodOuVbDX/omuFgAAAACkpcBZCksC1ko7duxYDR68cdZxq5a1wF955ZUaOXKk31dYWKiCggKNGTNGv/jFL/TZZ5+pU6dOev/993XggQf6Mq+88ooGDhyo7777zv/9tigqKlJeXp6/f2uxx5a5H5Yo/MaTCh1zjoKc/ERXBwAAAABSzrbm0KSdPX7BggVatmyZ7xIfYU/o4IMP1vTp0/22/bQu8ZHAbqx8KBTyLfNV2bBhg3+BYm+omnNhuWXfRLeDXVop4+QrCewAAAAAUMOSNrRbYDfWsh7LtiPH7Gfz5s3jjterV09NmzaNlqnMLbfc4i8ARG5t2rSpkeeQDlzZBrkJD/ox7G7R54muDgAAAADUKUkb2mvSdddd57sgRG6LFi1KdJWSklu7WuFnbpf74oPoNgAAAACg9iTtkm8tWrTwP5cvX+5nj4+w7f333z9aZsWKFXF/V15e7meUj/x9ZbKysvwNVXMrFyk87h5pzSqpQSOFjr9IQesOia4WAAAAANQpSdvSvscee/jgPXny5Og+G3tuY9V79erlt+3n6tWrNXPmzGiZ119/XeFw2I99x45xX89S+KlbNgb2/BYKnf5bAjsAAAAA1LWWdltP/csvv4ybfO7jjz/2Y9Lbtm2ryy+/XH/84x+19957+xD/u9/9zs8IH5lhft9999Uxxxyj888/3y8LV1ZWposvvtjPLL+tM8cjnlv6tcLj7rXfpLb7KnTscAUNGiW6WgAAAABQJyU0tH/wwQf6+c9/Ht0eMWKE/zls2DC/rNvVV1/t13K3ddetRb13795+SbcGDRpE/+bxxx/3Qb1Pnz5+1vghQ4b4td2xg1rsoaDjwVJmloKjzlCQkbQjKAAAAAAg7SXNOu2JVNfXaXcl66WMDAWZG8f5u3CFFIQUBEGiqwYAAAAAaSnl12lH7XCrV/jl3MIv/9Ovx26CUAaBHQAAAACSAH2f6zD33RcKv/A3qWStVFoi2ZJujZsmuloAAAAAgP8htNdR4bnT5CY+KlWUSwW7K3TCJQpymiS6WgAAAACAGIT2Osa6wLtp4+RmTNi4Y+8eCh1zbnQ8OwAAAAAgeRDa6xj3+uNys6b434ODBio47EQFAVMbAAAAAEAyIq3VMcG+vaT62Qr6n6NQ7yEEdgAAAABIYrS01wGurFRBZn3/e9CqvULn/VlBg0aJrhYAAAAAYCtoZk1z7utZCj90jdyKb6P7COwAAAAAkBoI7WnKOafwzNcUHnevtL5IbubERFcJAAAAALCd6B6fhlxFudwbT8jNnuq3gy5HKjjqjERXCwAAAACwnQjtKSLsnMrCFdHtzFCGQkGwWTlXsl7h8fdLC+daXFdw5CkKuvdTUElZAAAAAEByI7SngMLSYo2ePVnLioui+1pk52pE1z7Kq58d3efWFSr87O3SqqVSZpZCAy9QsNf+Cao1AAAAAGBnMaY9BQL7HbMmaUXxmrj9tm377XhUdo6U20zKyVfotGsJ7AAAAACQ4gjtSd4l3lrYvy9Zq7Bc/DE5v9+OV4TDfl9gXeYH/Z9CZ/xWQfO2Cao1AAAAAKC6ENqTmI1hty7xmwb2COfC6jn/I4UnPupnizdBVraCnPxarikAAAAAoCYQ2lNUZkWFzvnqEw1Y+o1Cn74tLZ6f6CoBAAAAAKoZE9GloNzSDfr1l7O1+7oilQeBgr7DlNF6n0RXCwAAAABQzWhpT2K2rJvNEh/ST8u17bZ+ja7+7H0f2NdlZOqxLr1Vr3PvhNYTAAAAAFAzCO1JzNZht2XdmjXI8cG98+rvdeVnM9W0dIOWNWiohw44UicfcVql67UDAAAAAFIfoT3J2TrsI7v1VfPsxqoIAtUPV+jz3Hz964Cf65xDBset0w4AAAAASC+Bi0w7XocVFRUpLy9PhYWFys3NVbIu/2azyQeL5sm1aq/MzPq0sAMAAABAmudQJqJLERbQszLqSbvvl+iqAAAAAABqCd3jAQAAAABIUoR2AAAAAACSFKEdAAAAAIAkRWgHAAAAACBJEdoBAAAAAEhShHYAAAAAAJIUoR0AAAAAgCRFaAcAAAAAIEkR2gEAAAAASFKEdgAAAAAAkhShHQAAAACAJEVoBwAAAAAgSRHaAQAAAABIUoR2AAAAAACSFKEdAAAAAIAkRWgHAAAAACBJEdoBAAAAAEhShHYAAAAAAJJUvURXIBk45/zPoqKiRFcFAAAAAFAHFP0vf0byaFUI7ZLWrFnjf7Zp0ybRVQEAAAAA1LE8mpeXV+XxwG0t1tcB4XBYS5YsUePGjRUEQaKrgx24QmUXXBYtWqTc3NxEVwfVhPOafjin6Ynzmn44p+mJ85p+OKepz6K4BfZWrVopFKp65Dot7TawPxRS69atE10N7CT7sOIDK/1wXtMP5zQ9cV7TD+c0PXFe0w/nNLVtqYU9gonoAAAAAABIUoR2AAAAAACSFKEdKS8rK0s33HCD/4n0wXlNP5zT9MR5TT+c0/TEeU0/nNO6g4noAAAAAABIUrS0AwAAAACQpAjtAAAAAAAkKUI7AAAAAABJitAOAAAAAECSIrQjKdxyyy3q2bOnGjdurObNm2vw4MGaN29eXJmf/exnCoIg7vbrX/86rszChQs1aNAgNWzY0N/PVVddpfLy8rgyU6ZMUffu3f1Mm+3bt9eYMWNq5TnWNTfeeONm56tjx47R4yUlJbrooou0yy67KCcnR0OGDNHy5cvj7oPzmXx23333zc6r3excGt6nye/NN9/Ucccdp1atWvnzM27cuLjjNj/tqFGj1LJlS2VnZ6tv376aP39+XJlVq1bpzDPPVG5urpo0aaJzzz1Xa9eujSsze/ZsHX744WrQoIHatGmj2267bbO6PPvss/5zwcp06dJFL730Ug0967p9XsvKynTNNdf417hRo0a+zNChQ7VkyZKtvr9vvfXWuDKc1+R5r/7yl7/c7Hwdc8wxcWV4r6beea3s/7F2u/3226NleK/WQTZ7PJBo/fv3d4888oj75JNP3Mcff+wGDhzo2rZt69auXRstc+SRR7rzzz/fLV26NHorLCyMHi8vL3edO3d2ffv2dR999JF76aWXXLNmzdx1110XLfP111+7hg0buhEjRri5c+e6e++912VkZLhXXnml1p9zurvhhhvcfvvtF3e+Vq5cGT3+61//2rVp08ZNnjzZffDBB+6QQw5xhx56aPQ45zM5rVixIu6cTpw40VYgcW+88YY/zvs0+dlr/tvf/tY999xz/tyNHTs27vitt97q8vLy3Lhx49ysWbPc8ccf7/bYYw9XXFwcLXPMMce4bt26uXfffde99dZbrn379u7000+PHrdzXlBQ4M4880z/uf7kk0+67Oxs9+CDD0bLvPPOO/683nbbbf48X3/99S4zM9PNmTOnll6JunNeV69e7d9zTz/9tPv888/d9OnT3UEHHeR69OgRdx/t2rVzv//97+Pev7H/H+a8Jtd7ddiwYf69GHu+Vq1aFVeG92rqndfY82m3hx9+2AVB4L766qtoGd6rdQ+hHUkbDOyDbOrUqdF9FgYuu+yyLX4IhkIht2zZsui++++/3+Xm5roNGzb47auvvtoHyVinnXaav2iA6g/t9kWhMvYF0v7H8Oyzz0b3ffbZZ/6c25dJw/lMDfae3GuvvVw4HPbbvE9Ty6ZfGO08tmjRwt1+++1x79esrCz/pc/Ylzv7u/fffz9a5uWXX/ZfKhcvXuy377vvPpefnx89p+aaa65xHTp0iG6feuqpbtCgQXH1Ofjgg93//d//1dCzrTsqCwKbeu+993y5b7/9Ni4I3HXXXVX+Dec1caoK7SeccEKVf8N7NT3eq3aOjzrqqLh9vFfrHrrHIykVFhb6n02bNo3b//jjj6tZs2bq3LmzrrvuOq1fvz56bPr06b5rT0FBQXRf//79VVRUpE8//TRaxrp6xrIyth/Vz7rUWvevPffc03fPs27RZubMmb67Zuy5sO5Zbdu2jZ4LzmfyKy0t1WOPPaZzzjnHd82L4H2auhYsWKBly5bFvf55eXk6+OCD496b1s32wAMPjJax8qFQSDNmzIiWOeKII1S/fv24c2jDnn788cdoGc5zYv8/a+9bO5exrIutDVs64IADfHfc2KErnNfkY0OJbJhRhw4dNHz4cP3www/RY7xXU58NG5wwYYIf1rAp3qt1S71EVwDYVDgc1uWXX67DDjvMf+mPOOOMM9SuXTsfAm2cjo3Psw+f5557zh+3L5qxQcBEtu3YlspYYCguLvbjN1E97Eu+jUO2LxJLly7VTTfd5MdWffLJJ/482P9INv2yaOdia+cqcmxLZTiftcPG4a1evdqPq4zgfZraIuegstc/9vxYSIhVr149f5E1tswee+yx2X1EjuXn51d5niP3gZpjc4rYe/P000/3Y50jLr30Uj+XhJ3LadOm+Ytu9vk9evRof5zzmlxs/PpJJ53kz8lXX32l3/zmNxowYIAPXRkZGbxX08Cjjz7q53uy8xyL92rdQ2hH0rEJrSzYvf3223H7L7jggujv1lJnkyT16dPH/49qr732SkBNsSX2xSGia9euPsRbmHvmmWcIXWnioYce8ufZAnoE71MguVkvp1NPPdVPOHj//ffHHRsxYkTc57ZdXP2///s/P1msTQqJ5PKLX/wi7vPWzpl9zlrru33uIvU9/PDDvqeiTRQXi/dq3UP3eCSViy++WOPHj9cbb7yh1q1bb7GshUDz5Zdf+p8tWrTYbPbxyLYd21IZa2kgSNYsa1XfZ599/Pmy82Bdq62VdtNzsbVzFTm2pTKcz5r37bffatKkSTrvvPO2WI73aWqJnIPKXv/Y87NixYq449Yt02apro73b+Q4ai6w2/t34sSJca3sVb1/7dx+8803fpvzmtxsKJoNTYr9vOW9mrreeust31Nta/+fNbxX0x+hHUnBrvhbYB87dqxef/31zbr0VObjjz/2P60lz/Tq1Utz5syJ+x9U5EtJp06domUmT54cdz9WxvajZtkSM9baauerR48eyszMjDsX9j8mG/MeORecz+T2yCOP+G6XtnTblvA+TS322Wtf2GJffxuWYONfY9+bdsHN5qaIsM9tG9oUuUhjZWxZIwuJsefQhstYt8xIGc5z7Qd2m2vELrjZWNitsfevjX+OdLHmvCa37777zo9pj/285b2a2r3Z7PtSt27dtlqW92odkOiZ8AAzfPhwv8TQlClT4pavWL9+vT/+5Zdf+qUtbGmwBQsWuOeff97tueee7ogjjthsKal+/fr5ZeNseahdd9210qWkrrrqKj9b+d/+9jeWkqohV155pT+fdr5sWRFbbsiW9rKVASJLvtmyfq+//ro/r7169fK3CM5n8qqoqPDnzmaijcX7NDWsWbPGL7dnN/saMHr0aP97ZBZxW/KtSZMm/vzNnj3bz1xc2ZJvBxxwgJsxY4Z7++233d577x23jJTNOG/LDZ199tl+uaGnnnrKn9NNlxuqV6+eu+OOO/x5thUnWG6oZs5raWmpX7qvdevW/n0X+//ZyOzS06ZN87NR23FbWuqxxx7z782hQ4dGH4Pzmjzn1I6NHDnSr7hin7eTJk1y3bt39+/FkpKS6H3wXk29z+DIkm12Hmx1lU3xXq2bCO1ICvahVdnN1m43Cxcu9F/8mzZt6pcesnVG7Qt97PrP5ptvvnEDBgzwa1FaQLTgWFZWFlfG1pPef//9Xf369X2giDwGqpct0dWyZUv/Ou+2225+20JdhAWACy+80C9JYv8jOfHEE/0XyFicz+T06quv+vfnvHnz4vbzPk0N9tpW9nlry0dFln373e9+57/w2Xns06fPZuf6hx9+8F/8c3Jy/HJ9v/rVr/wX0Vi2xnvv3r39fdhngF0M2NQzzzzj9tlnH3+ebZm/CRMm1PCzr5vn1UJdVf+ftb8zM2fO9Ms92QX0Bg0auH333dfdfPPNcQHQcF6T45xao4Zd/LSwZkHLlgA7//zz45bTNLxXU+8z2Fi4tv9HWvjeFO/Vuimw/yS6tR8AAAAAAGyOMe0AAAAAACQpQjsAAAAAAEmK0A4AAAAAQJIitAMAAAAAkKQI7QAAAAAAJClCOwAAAAAASYrQDgAAAABAkiK0AwBQBwVBoHHjxiW6GgAAYCsI7QAApJFf/vKXPpDbLTMzUwUFBTr66KP18MMPKxwOR8stXbpUAwYM2Kb7JOADAJA4hHYAANLMMccc40P5N998o5dfflk///nPddlll+nYY49VeXm5L9OiRQtlZWUluqoAAGArCO0AAKQZC+MWynfbbTd1795dv/nNb/T888/7AD9mzJjNWs9LS0t18cUXq2XLlmrQoIHatWunW265xR/bfffd/c8TTzzR/01k+6uvvtIJJ5zgW/JzcnLUs2dPTZo0Ka4eVvbmm2/WOeeco8aNG6tt27b6+9//Hlfmu+++0+mnn66mTZuqUaNGOvDAAzVjxozocau3PQer15577qmbbropeuEBAIC6gNAOAEAdcNRRR6lbt2567rnnNjt2zz336IUXXtAzzzyjefPm6fHHH4+G8/fff9//fOSRR3zrfWR77dq1GjhwoCZPnqyPPvrIt+4fd9xxWrhwYdx933nnnT6IW5kLL7xQw4cP948RuY8jjzxSixcv9o8/a9YsXX311dFu/G+99ZaGDh3qewnMnTtXDz74oL/o8Kc//anGXy8AAJJFvURXAAAA1I6OHTtq9uzZm+23oL333nurd+/evjXdWtojdt11V/+zSZMmvvU+wi4A2C3iD3/4g8aOHevDt7XaR1iwt7BurrnmGt11111644031KFDBz3xxBNauXKlvxBgLe2mffv20b+1VvVrr71Ww4YN89vW0m6PY8H+hhtuqOZXBwCA5ERoBwCgjnDO+VBe2eR1NlmdBWlrMbex7/369dvifVkr+Y033qgJEyb4Fnjrsl5cXLxZS3vXrl2jv9tjW/BfsWKF3/744491wAEHRAP7pqzl/Z133olrWa+oqFBJSYnWr1+vhg0bbvdrAABAqiG0AwBQR3z22WfaY489NttvY8YXLFjgx7zbuPRTTz1Vffv21X/+858q72vkyJGaOHGi7rjjDt86np2drZNPPtmPj49lM9jHsuAe6f5uf7O1CwPW2n7SSSdtdszGuAMAUBcQ2gEAqANef/11zZkzR1dccUWlx3Nzc3Xaaaf5m4Vva3FftWqVbwW34G0t3LGsBdxa6G2CukjAttnqt4e1wv/zn/+MPk5lFxNs/Htsl3kAAOoaQjsAAGlmw4YNWrZsmQ/ay5cv1yuvvOJng7du7zax26ZGjx7tZ463ruqhUEjPPvus78Zu49iNTUpnE84ddthhfmb6/Px8PwbeJrWzyees9fx3v/td3Drw28JmjbfZ5QcPHuzrZ3WwCetatWqlXr16adSoUb7ONuu8XUiwulmX+U8++UR//OMfq+31AgAgmTF7PAAAacZCugVgC9vWYm4Tv9kM8bZ8WkZGxmblbTm22267zc/ybku3WYv5Sy+95ENyZAZ46wrfpk0bH+wjQd/C+6GHHuqDe//+/X3L+PaoX7++XnvtNTVv3txPWNelSxfdeuut0TrafY4fP96XsXodcsghfiK72InyAABId4GzWWkAAAAAAEDSoaUdAAAAAIAkRWgHAAAAACBJEdoBAAAAAEhShHYAAAAAAJIUoR0AAAAAgCRFaAcAAAAAIEkR2gEAAAAASFKEdgAAAAAAkhShHQAAAACAJEVoBwAAAAAgSRHaAQAAAABIUoR2AAAAAACUnP4f+/AsImgOnbkAAAAASUVORK5CYII="
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"
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
-   "execution_count": 65
+   "execution_count": 24
   },
   {
    "cell_type": "code",
@@ -1273,8 +1273,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:35.201511Z",
-     "start_time": "2025-12-21T14:55:35.194494Z"
+     "end_time": "2026-02-20T11:30:56.378793Z",
+     "start_time": "2026-02-20T11:30:56.372705Z"
     }
    },
    "source": [
@@ -1294,41 +1294,41 @@
      "text": [
       "* Selected model: Power model\n",
       "* Nugget: 0\n",
-      "* Sill: 478.90567078851103\n",
+      "* Sill: 415.1536596743022\n",
       "* Range: 8000\n",
       "* Spatial Dependency Strength is Undefined: nugget equal to 0, cannot estimate\n",
       "* Mean Bias: None\n",
-      "* Mean RMSE: 131.6193788004333\n",
+      "* Mean RMSE: 127.3197557675198\n",
       "* Error-lag weighting method: equal\n",
       "\n",
       "\n",
       "+---------+--------------------+--------------------+--------------------+\n",
       "|   lag   |    theoretical     |    experimental    |  bias (real-yhat)  |\n",
       "+---------+--------------------+--------------------+--------------------+\n",
-      "|  1000.0 | 7.482901106070485  | 66.71388540855338  | 59.230984302482895 |\n",
-      "|  2000.0 | 29.93160442428194  | 130.66628344322854 | 100.7346790189466  |\n",
-      "|  3000.0 | 67.34610995463436  | 377.5405401178886  | 310.19443016325425 |\n",
-      "|  4000.0 | 119.72641769712776 | 250.66718626708865 | 130.94076856996088 |\n",
-      "|  5000.0 | 187.07252765176213 | 325.5561456427749  | 138.48361799101275 |\n",
-      "|  6000.0 | 269.38443981853743 | 387.4814906048632  | 118.09705078632578 |\n",
-      "|  7000.0 | 366.66215419745373 | 302.07493544556206 | -64.58721875189167 |\n",
-      "|  8000.0 | 478.90567078851103 | 469.53885776562294 | -9.366813022888095 |\n",
-      "|  9000.0 | 478.90567078851103 | 486.79931370125183 | 7.893642912740802  |\n",
-      "| 10000.0 | 478.90567078851103 | 512.0646265352149  | 33.15895574670384  |\n",
-      "| 11000.0 | 478.90567078851103 |  529.991767276145  | 51.08609648763394  |\n",
-      "| 12000.0 | 478.90567078851103 | 582.4717932210419  | 103.5661224325309  |\n",
-      "| 13000.0 | 478.90567078851103 |  692.506923505966  |  213.601252717455  |\n",
-      "| 14000.0 | 478.90567078851103 | 649.5775483966735  | 170.67187760816245 |\n",
-      "| 15000.0 | 478.90567078851103 | 624.8696046337229  | 145.9639338452119  |\n",
-      "| 16000.0 | 478.90567078851103 |  643.74627487684   | 164.84060408832892 |\n",
-      "| 17000.0 | 478.90567078851103 | 571.3688648923311  | 92.46319410382006  |\n",
-      "| 18000.0 | 478.90567078851103 | 540.0470107890337  | 61.14134000052269  |\n",
-      "| 19000.0 | 478.90567078851103 | 600.2575887426275  | 121.35191795411646 |\n",
+      "|  1000.0 | 6.486775932410972  | 57.836141811479614 | 51.34936587906864  |\n",
+      "|  2000.0 | 25.94710372964389  | 86.03437765640514  | 60.087273926761256 |\n",
+      "|  3000.0 | 58.38098339169875  | 236.60954497912823 | 178.22856158742948 |\n",
+      "|  4000.0 | 103.78841491857555 | 268.7197011214077  | 164.93128620283215 |\n",
+      "|  5000.0 | 162.16939831027432 | 216.77470366578342 |  54.6053053555091  |\n",
+      "|  6000.0 |  233.523933566795  | 294.4056440278582  | 60.88171046106322  |\n",
+      "|  7000.0 | 317.85202068813766 | 383.72288068192313 | 65.87085999378547  |\n",
+      "|  8000.0 | 415.1536596743022  | 378.7119931185135  | -36.44166655578874 |\n",
+      "|  9000.0 | 415.1536596743022  |  483.465464109033  | 68.31180443473079  |\n",
+      "| 10000.0 | 415.1536596743022  | 452.9072205931408  | 37.75356091883856  |\n",
+      "| 11000.0 | 415.1536596743022  | 412.07362484342366 | -3.08003483087856  |\n",
+      "| 12000.0 | 415.1536596743022  | 491.23925913297296 | 76.08559945867074  |\n",
+      "| 13000.0 | 415.1536596743022  | 577.2518572511536  | 162.09819757685142 |\n",
+      "| 14000.0 | 415.1536596743022  | 575.1348087672814  | 159.98114909297914 |\n",
+      "| 15000.0 | 415.1536596743022  | 633.2991501319548  | 218.14549045765256 |\n",
+      "| 16000.0 | 415.1536596743022  | 659.1799840204877  | 244.0263243461855  |\n",
+      "| 17000.0 | 415.1536596743022  |  641.201731691203  | 226.0480720169008  |\n",
+      "| 18000.0 | 415.1536596743022  | 500.6074586569037  | 85.45379898260148  |\n",
+      "| 19000.0 | 415.1536596743022  | 448.75860119019325 | 33.60494151589103  |\n",
       "+---------+--------------------+--------------------+--------------------+\n"
      ]
     }
    ],
-   "execution_count": 66
+   "execution_count": 25
   },
   {
    "cell_type": "code",
@@ -1339,8 +1339,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:35.506762Z",
-     "start_time": "2025-12-21T14:55:35.291434Z"
+     "end_time": "2026-02-20T11:30:56.570735Z",
+     "start_time": "2026-02-20T11:30:56.453012Z"
     }
    },
    "source": [
@@ -1352,13 +1352,13 @@
       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ],
-      "image/png": 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"
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"
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
-   "execution_count": 67
+   "execution_count": 26
   },
   {
    "cell_type": "code",
@@ -1369,8 +1369,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:35.579391Z",
-     "start_time": "2025-12-21T14:55:35.572937Z"
+     "end_time": "2026-02-20T11:30:56.609397Z",
+     "start_time": "2026-02-20T11:30:56.602756Z"
     }
    },
    "source": [
@@ -1391,41 +1391,41 @@
      "text": [
       "* Selected model: Spherical model\n",
       "* Nugget: 0\n",
-      "* Sill: 478.90567078851103\n",
+      "* Sill: 415.1536596743022\n",
       "* Range: 8000\n",
       "* Spatial Dependency Strength is Undefined: nugget equal to 0, cannot estimate\n",
       "* Mean Bias: None\n",
-      "* Mean RMSE: 108.209074255922\n",
+      "* Mean RMSE: 116.88343738778293\n",
       "* Error-lag weighting method: equal\n",
       "\n",
       "\n",
       "+---------+--------------------+--------------------+---------------------+\n",
       "|   lag   |    theoretical     |    experimental    |   bias (real-yhat)  |\n",
       "+---------+--------------------+--------------------+---------------------+\n",
-      "|  1000.0 | 89.32713195371642  | 66.71388540855338  | -22.613246545163037 |\n",
-      "|  2000.0 | 175.8481759926564  | 130.66628344322854 |  -45.18189254942786 |\n",
-      "|  3000.0 | 256.7570442020435  | 377.5405401178886  |  120.7834959158451  |\n",
-      "|  4000.0 | 329.2476486671013  | 250.66718626708865 |  -78.58046240001266 |\n",
-      "|  5000.0 | 390.5139014730534  | 325.5561456427749  |  -64.95775583027853 |\n",
-      "|  6000.0 | 437.7497147051234  | 387.4814906048632  |  -50.26822410026017 |\n",
-      "|  7000.0 | 468.1490004485347  | 302.07493544556206 | -166.07406500297265 |\n",
-      "|  8000.0 | 478.90567078851103 | 469.53885776562294 |  -9.366813022888095 |\n",
-      "|  9000.0 | 478.90567078851103 | 486.79931370125183 |  7.893642912740802  |\n",
-      "| 10000.0 | 478.90567078851103 | 512.0646265352149  |  33.15895574670384  |\n",
-      "| 11000.0 | 478.90567078851103 |  529.991767276145  |  51.08609648763394  |\n",
-      "| 12000.0 | 478.90567078851103 | 582.4717932210419  |  103.5661224325309  |\n",
-      "| 13000.0 | 478.90567078851103 |  692.506923505966  |   213.601252717455  |\n",
-      "| 14000.0 | 478.90567078851103 | 649.5775483966735  |  170.67187760816245 |\n",
-      "| 15000.0 | 478.90567078851103 | 624.8696046337229  |  145.9639338452119  |\n",
-      "| 16000.0 | 478.90567078851103 |  643.74627487684   |  164.84060408832892 |\n",
-      "| 17000.0 | 478.90567078851103 | 571.3688648923311  |  92.46319410382006  |\n",
-      "| 18000.0 | 478.90567078851103 | 540.0470107890337  |  61.14134000052269  |\n",
-      "| 19000.0 | 478.90567078851103 | 600.2575887426275  |  121.35191795411646 |\n",
+      "|  1000.0 | 77.43588769315598  | 57.836141811479614 | -19.599745881676363 |\n",
+      "|  2000.0 | 152.43923441165785 | 86.03437765640514  |  -66.40485675525271 |\n",
+      "|  3000.0 | 222.57749918085148 | 236.60954497912823 |  14.032045798276755 |\n",
+      "|  4000.0 | 285.41814102608276 | 268.7197011214077  |  -16.69843990467507 |\n",
+      "|  5000.0 | 338.5286189726976  | 216.77470366578342 | -121.75391530691417 |\n",
+      "|  6000.0 | 379.4763920460419  | 294.4056440278582  |  -85.07074801818368 |\n",
+      "|  7000.0 | 405.8289192714615  | 383.72288068192313 | -22.106038589538343 |\n",
+      "|  8000.0 | 415.1536596743022  | 378.7119931185135  |  -36.44166655578874 |\n",
+      "|  9000.0 | 415.1536596743022  |  483.465464109033  |  68.31180443473079  |\n",
+      "| 10000.0 | 415.1536596743022  | 452.9072205931408  |  37.75356091883856  |\n",
+      "| 11000.0 | 415.1536596743022  | 412.07362484342366 |  -3.08003483087856  |\n",
+      "| 12000.0 | 415.1536596743022  | 491.23925913297296 |  76.08559945867074  |\n",
+      "| 13000.0 | 415.1536596743022  | 577.2518572511536  |  162.09819757685142 |\n",
+      "| 14000.0 | 415.1536596743022  | 575.1348087672814  |  159.98114909297914 |\n",
+      "| 15000.0 | 415.1536596743022  | 633.2991501319548  |  218.14549045765256 |\n",
+      "| 16000.0 | 415.1536596743022  | 659.1799840204877  |  244.0263243461855  |\n",
+      "| 17000.0 | 415.1536596743022  |  641.201731691203  |  226.0480720169008  |\n",
+      "| 18000.0 | 415.1536596743022  | 500.6074586569037  |  85.45379898260148  |\n",
+      "| 19000.0 | 415.1536596743022  | 448.75860119019325 |  33.60494151589103  |\n",
       "+---------+--------------------+--------------------+---------------------+\n"
      ]
     }
    ],
-   "execution_count": 68
+   "execution_count": 27
   },
   {
    "cell_type": "code",
@@ -1436,8 +1436,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:35.845172Z",
-     "start_time": "2025-12-21T14:55:35.665600Z"
+     "end_time": "2026-02-20T11:30:56.803443Z",
+     "start_time": "2026-02-20T11:30:56.684939Z"
     }
    },
    "source": [
@@ -1449,13 +1449,13 @@
       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ],
-      "image/png": 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"
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"
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
-   "execution_count": 69
+   "execution_count": 28
   },
   {
    "cell_type": "markdown",
@@ -1479,8 +1479,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:35.920991Z",
-     "start_time": "2025-12-21T14:55:35.915911Z"
+     "end_time": "2026-02-20T11:30:56.842655Z",
+     "start_time": "2026-02-20T11:30:56.837866Z"
     }
    },
    "source": [
@@ -1514,19 +1514,19 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Model: circular, RMSE: 106.4369154595279\n",
-      "Model: cubic, RMSE: 112.51542324377124\n",
-      "Model: exponential, RMSE: 172.56017194999464\n",
-      "Model: gaussian, RMSE: 159.98897643128805\n",
-      "Model: linear, RMSE: 107.47814162764915\n",
-      "Model: power, RMSE: 131.6193788004333\n",
-      "Model: spherical, RMSE: 108.209074255922\n",
+      "Model: circular, RMSE: 114.23438788269483\n",
+      "Model: cubic, RMSE: 120.17733788327587\n",
+      "Model: exponential, RMSE: 169.80926717230193\n",
+      "Model: gaussian, RMSE: 153.225123668266\n",
+      "Model: linear, RMSE: 113.53675299439662\n",
+      "Model: power, RMSE: 127.3197557675198\n",
+      "Model: spherical, RMSE: 116.88343738778293\n",
       "\n",
-      "The best model is circular with RMSE 106.4369154595279\n"
+      "The best model is linear with RMSE 113.53675299439662\n"
      ]
     }
    ],
-   "execution_count": 70
+   "execution_count": 29
   },
   {
    "cell_type": "markdown",
@@ -1588,8 +1588,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:36.030968Z",
-     "start_time": "2025-12-21T14:55:36.021Z"
+     "end_time": "2026-02-20T11:30:56.913393Z",
+     "start_time": "2026-02-20T11:30:56.908745Z"
     }
    },
    "source": [
@@ -1602,7 +1602,7 @@
     ")"
    ],
    "outputs": [],
-   "execution_count": 71
+   "execution_count": 30
   },
   {
    "cell_type": "code",
@@ -1613,8 +1613,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:36.148593Z",
-     "start_time": "2025-12-21T14:55:36.141816Z"
+     "end_time": "2026-02-20T11:30:56.988102Z",
+     "start_time": "2026-02-20T11:30:56.983132Z"
     }
    },
    "source": [
@@ -1625,43 +1625,43 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "* Selected model: Circular model\n",
+      "* Selected model: Linear model\n",
       "* Nugget: 0\n",
-      "* Sill: 478.90567078851103\n",
+      "* Sill: 415.1536596743022\n",
       "* Range: 8000\n",
       "* Spatial Dependency Strength is Undefined: nugget equal to 0, cannot estimate\n",
       "* Mean Bias: None\n",
-      "* Mean RMSE: 106.4369154595279\n",
+      "* Mean RMSE: 113.53675299439662\n",
       "* Error-lag weighting method: equal\n",
       "\n",
       "\n",
       "+---------+--------------------+--------------------+---------------------+\n",
       "|   lag   |    theoretical     |    experimental    |   bias (real-yhat)  |\n",
       "+---------+--------------------+--------------------+---------------------+\n",
-      "|  1000.0 | 76.02124683696297  | 66.71388540855338  |  -9.307361428409592 |\n",
-      "|  2000.0 | 150.8372591039797  | 130.66628344322854 | -20.170975660751168 |\n",
-      "|  3000.0 | 223.18223486037513 | 377.5405401178886  |  154.35830525751348 |\n",
-      "|  4000.0 | 291.65249083970144 | 250.66718626708865 |  -40.98530457261279 |\n",
-      "|  5000.0 | 354.58310049417867 | 325.5561456427749  | -29.026954851403787 |\n",
-      "|  6000.0 | 409.8026413531391  | 387.4814906048632  | -22.321150748275898 |\n",
-      "|  7000.0 | 453.9807623558251  | 302.07493544556206 | -151.90582691026304 |\n",
-      "|  8000.0 | 478.90567078851103 | 469.53885776562294 |  -9.366813022888095 |\n",
-      "|  9000.0 | 478.90567078851103 | 486.79931370125183 |  7.893642912740802  |\n",
-      "| 10000.0 | 478.90567078851103 | 512.0646265352149  |  33.15895574670384  |\n",
-      "| 11000.0 | 478.90567078851103 |  529.991767276145  |  51.08609648763394  |\n",
-      "| 12000.0 | 478.90567078851103 | 582.4717932210419  |  103.5661224325309  |\n",
-      "| 13000.0 | 478.90567078851103 |  692.506923505966  |   213.601252717455  |\n",
-      "| 14000.0 | 478.90567078851103 | 649.5775483966735  |  170.67187760816245 |\n",
-      "| 15000.0 | 478.90567078851103 | 624.8696046337229  |  145.9639338452119  |\n",
-      "| 16000.0 | 478.90567078851103 |  643.74627487684   |  164.84060408832892 |\n",
-      "| 17000.0 | 478.90567078851103 | 571.3688648923311  |  92.46319410382006  |\n",
-      "| 18000.0 | 478.90567078851103 | 540.0470107890337  |  61.14134000052269  |\n",
-      "| 19000.0 | 478.90567078851103 | 600.2575887426275  |  121.35191795411646 |\n",
+      "|  1000.0 | 51.89420745928778  | 57.836141811479614 |  5.941934352191836  |\n",
+      "|  2000.0 | 103.78841491857555 | 86.03437765640514  | -17.754037262170414 |\n",
+      "|  3000.0 | 155.68262237786334 | 236.60954497912823 |  80.92692260126489  |\n",
+      "|  4000.0 | 207.5768298371511  | 268.7197011214077  |  61.142871284256586 |\n",
+      "|  5000.0 | 259.4710372964389  | 216.77470366578342 |  -42.69633363065549 |\n",
+      "|  6000.0 | 311.3652447557267  | 294.4056440278582  | -16.959600727868462 |\n",
+      "|  7000.0 | 363.25945221501445 | 383.72288068192313 |  20.46342846690868  |\n",
+      "|  8000.0 | 415.1536596743022  | 378.7119931185135  |  -36.44166655578874 |\n",
+      "|  9000.0 | 415.1536596743022  |  483.465464109033  |  68.31180443473079  |\n",
+      "| 10000.0 | 415.1536596743022  | 452.9072205931408  |  37.75356091883856  |\n",
+      "| 11000.0 | 415.1536596743022  | 412.07362484342366 |  -3.08003483087856  |\n",
+      "| 12000.0 | 415.1536596743022  | 491.23925913297296 |  76.08559945867074  |\n",
+      "| 13000.0 | 415.1536596743022  | 577.2518572511536  |  162.09819757685142 |\n",
+      "| 14000.0 | 415.1536596743022  | 575.1348087672814  |  159.98114909297914 |\n",
+      "| 15000.0 | 415.1536596743022  | 633.2991501319548  |  218.14549045765256 |\n",
+      "| 16000.0 | 415.1536596743022  | 659.1799840204877  |  244.0263243461855  |\n",
+      "| 17000.0 | 415.1536596743022  |  641.201731691203  |  226.0480720169008  |\n",
+      "| 18000.0 | 415.1536596743022  | 500.6074586569037  |  85.45379898260148  |\n",
+      "| 19000.0 | 415.1536596743022  | 448.75860119019325 |  33.60494151589103  |\n",
       "+---------+--------------------+--------------------+---------------------+\n"
      ]
     }
    ],
-   "execution_count": 72
+   "execution_count": 31
   },
   {
    "cell_type": "markdown",
@@ -1688,15 +1688,15 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:36.799206Z",
-     "start_time": "2025-12-21T14:55:36.306402Z"
+     "end_time": "2026-02-20T11:30:57.478129Z",
+     "start_time": "2026-02-20T11:30:57.056293Z"
     }
    },
    "source": [
     "fitted = build_theoretical_variogram(experimental_variogram=experimental_variogram)"
    ],
    "outputs": [],
-   "execution_count": 73
+   "execution_count": 32
   },
   {
    "cell_type": "code",
@@ -1707,8 +1707,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:36.862187Z",
-     "start_time": "2025-12-21T14:55:36.856149Z"
+     "end_time": "2026-02-20T11:30:57.529376Z",
+     "start_time": "2026-02-20T11:30:57.522928Z"
     }
    },
    "source": [
@@ -1720,42 +1720,42 @@
      "output_type": "stream",
      "text": [
       "* Selected model: Spherical model\n",
-      "* Nugget: 24.46175798313624\n",
-      "* Sill: 596.0578687869111\n",
-      "* Range: 14980.760125261822\n",
+      "* Nugget: 15.422971149727896\n",
+      "* Sill: 538.168759462272\n",
+      "* Range: 14791.939719657023\n",
       "* Spatial Dependency Strength is strong\n",
       "* Mean Bias: None\n",
-      "* Mean RMSE: 58.37586447036475\n",
+      "* Mean RMSE: 58.62877697928692\n",
       "* Error-lag weighting method: equal\n",
       "\n",
       "\n",
       "+---------+--------------------+--------------------+---------------------+\n",
       "|   lag   |    theoretical     |    experimental    |   bias (real-yhat)  |\n",
       "+---------+--------------------+--------------------+---------------------+\n",
-      "|  1000.0 | 84.05545137223926  | 66.71388540855338  |  -17.34156596368588 |\n",
-      "|  2000.0 | 143.11727153379871 | 130.66628344322854 | -12.450988090570178 |\n",
-      "|  3000.0 | 201.1153452402711  | 377.5405401178886  |  176.4251948776175  |\n",
-      "|  4000.0 | 257.5177992641128  | 250.66718626708865 |  -6.850612997024143 |\n",
-      "|  5000.0 | 311.7927603777803  | 325.5561456427749  |  13.763385264994554 |\n",
-      "|  6000.0 | 363.40835535373014 | 387.4814906048632  |  24.073135251133067 |\n",
-      "|  7000.0 | 411.83271096441854 | 302.07493544556206 | -109.75777551885648 |\n",
-      "|  8000.0 | 456.53395398230225 | 469.53885776562294 |  13.004903783320685 |\n",
-      "|  9000.0 | 496.98021117983745 | 486.79931370125183 |  -10.18089747858562 |\n",
-      "| 10000.0 | 532.6396093294809  | 512.0646265352149  |  -20.57498279426602 |\n",
-      "| 11000.0 | 562.9802752036886  |  529.991767276145  |  -32.98850792754365 |\n",
-      "| 12000.0 | 587.4703355749175  | 582.4717932210419  |  -4.998542353875564 |\n",
-      "| 13000.0 | 605.5779172156238  |  692.506923505966  |  86.92900629034227  |\n",
-      "| 14000.0 | 616.7711468982636  | 649.5775483966735  |  32.806401498409855 |\n",
-      "| 15000.0 | 620.5196267700474  | 624.8696046337229  |  4.349977863675576  |\n",
-      "| 16000.0 | 620.5196267700474  |  643.74627487684   |  23.226648106792595 |\n",
-      "| 17000.0 | 620.5196267700474  | 571.3688648923311  |  -49.15076187771626 |\n",
-      "| 18000.0 | 620.5196267700474  | 540.0470107890337  |  -80.47261598101363 |\n",
-      "| 19000.0 | 620.5196267700474  | 600.2575887426275  | -20.262038027419862 |\n",
+      "|  1000.0 | 69.91368324508167  | 57.836141811479614 | -12.077541433602057 |\n",
+      "|  2000.0 | 123.90555179953802 | 86.03437765640514  | -37.871174143132876 |\n",
+      "|  3000.0 | 176.89973327219948 | 236.60954497912823 |  59.70981170692875  |\n",
+      "|  4000.0 | 228.3973841221687  | 268.7197011214077  |  40.32231699923901  |\n",
+      "|  5000.0 | 277.89966080854816 | 216.77470366578342 |  -61.12495714276474 |\n",
+      "|  6000.0 | 324.9077197904405  | 294.4056440278582  | -30.502075762582308 |\n",
+      "|  7000.0 | 368.9227175269483  | 383.72288068192313 |  14.800163154974825 |\n",
+      "|  8000.0 | 409.44581047717406 | 378.7119931185135  | -30.733817358660588 |\n",
+      "|  9000.0 | 445.97815510022036 |  483.465464109033  |  37.487309008812645 |\n",
+      "| 10000.0 | 478.0209078551899  | 452.9072205931408  | -25.113687262049098 |\n",
+      "| 11000.0 | 505.0752252011851  | 412.07362484342366 |  -93.00160035776145 |\n",
+      "| 12000.0 | 526.6422635973086  | 491.23925913297296 | -35.403004464335595 |\n",
+      "| 13000.0 | 542.2231795026629  | 577.2518572511536  |  35.028677748490736 |\n",
+      "| 14000.0 | 551.3191293763507  | 575.1348087672814  |  23.815679390930654 |\n",
+      "| 15000.0 | 553.5917306119999  | 633.2991501319548  |   79.7074195199549  |\n",
+      "| 16000.0 | 553.5917306119999  | 659.1799840204877  |  105.58825340848784 |\n",
+      "| 17000.0 | 553.5917306119999  |  641.201731691203  |  87.61000107920313  |\n",
+      "| 18000.0 | 553.5917306119999  | 500.6074586569037  | -52.984271955096176 |\n",
+      "| 19000.0 | 553.5917306119999  | 448.75860119019325 | -104.83312942180663 |\n",
       "+---------+--------------------+--------------------+---------------------+\n"
      ]
     }
    ],
-   "execution_count": 74
+   "execution_count": 33
   },
   {
    "cell_type": "markdown",
@@ -1779,8 +1779,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:37.217584Z",
-     "start_time": "2025-12-21T14:55:36.978151Z"
+     "end_time": "2026-02-20T11:30:57.789171Z",
+     "start_time": "2026-02-20T11:30:57.594111Z"
     }
    },
    "source": [
@@ -1808,13 +1808,13 @@
       "text/plain": [
        "<Figure size 2000x800 with 1 Axes>"
       ],
-      "image/png": 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      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
-   "execution_count": 75
+   "execution_count": 34
   },
   {
    "cell_type": "markdown",
@@ -1842,15 +1842,15 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:37.273212Z",
-     "start_time": "2025-12-21T14:55:37.270601Z"
+     "end_time": "2026-02-20T11:30:57.841581Z",
+     "start_time": "2026-02-20T11:30:57.838693Z"
     }
    },
    "source": [
     "dict_representation = fitted.to_dict()"
    ],
    "outputs": [],
-   "execution_count": 76
+   "execution_count": 35
   },
   {
    "cell_type": "code",
@@ -1861,8 +1861,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:37.364416Z",
-     "start_time": "2025-12-21T14:55:37.357111Z"
+     "end_time": "2026-02-20T11:30:57.911312Z",
+     "start_time": "2026-02-20T11:30:57.904868Z"
     }
    },
    "source": [
@@ -1873,9 +1873,9 @@
      "data": {
       "text/plain": [
        "{'experimental_variogram': None,\n",
-       " 'nugget': 24.46175798313624,\n",
-       " 'sill': 596.0578687869111,\n",
-       " 'rang': 14980.760125261822,\n",
+       " 'nugget': 15.422971149727896,\n",
+       " 'sill': 538.168759462272,\n",
+       " 'rang': 14791.939719657023,\n",
        " 'variogram_model_type': 'spherical',\n",
        " 'direction': None,\n",
        " 'spatial_dependence': None,\n",
@@ -1884,12 +1884,12 @@
        " 'errors': None}"
       ]
      },
-     "execution_count": 77,
+     "execution_count": 36,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
-   "execution_count": 77
+   "execution_count": 36
   },
   {
    "cell_type": "code",
@@ -1900,8 +1900,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:37.475448Z",
-     "start_time": "2025-12-21T14:55:37.471249Z"
+     "end_time": "2026-02-20T11:30:57.979838Z",
+     "start_time": "2026-02-20T11:30:57.975063Z"
     }
    },
    "source": [
@@ -1910,7 +1910,7 @@
     "fitted.to_json('fitted.json')"
    ],
    "outputs": [],
-   "execution_count": 78
+   "execution_count": 37
   },
   {
    "cell_type": "markdown",
@@ -1938,8 +1938,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:37.574490Z",
-     "start_time": "2025-12-21T14:55:37.570833Z"
+     "end_time": "2026-02-20T11:30:58.043135Z",
+     "start_time": "2026-02-20T11:30:58.039732Z"
     }
    },
    "source": [
@@ -1947,7 +1947,7 @@
     "model_from_dict.from_dict(dict_representation)"
    ],
    "outputs": [],
-   "execution_count": 79
+   "execution_count": 38
   },
   {
    "cell_type": "code",
@@ -1958,8 +1958,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:37.710668Z",
-     "start_time": "2025-12-21T14:55:37.706947Z"
+     "end_time": "2026-02-20T11:30:58.109723Z",
+     "start_time": "2026-02-20T11:30:58.106324Z"
     }
    },
    "source": [
@@ -1971,9 +1971,9 @@
      "output_type": "stream",
      "text": [
       "* Selected model: Spherical model\n",
-      "* Nugget: 24.46175798313624\n",
-      "* Sill: 596.0578687869111\n",
-      "* Range: 14980.760125261822\n",
+      "* Nugget: 15.422971149727896\n",
+      "* Sill: 538.168759462272\n",
+      "* Range: 14791.939719657023\n",
       "* Spatial Dependency Strength is strong\n",
       "* Mean Bias: 0.0\n",
       "* Mean RMSE: 0.0\n",
@@ -1983,7 +1983,7 @@
      ]
     }
    ],
-   "execution_count": 80
+   "execution_count": 39
   },
   {
    "cell_type": "code",
@@ -1994,8 +1994,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:37.833154Z",
-     "start_time": "2025-12-21T14:55:37.827834Z"
+     "end_time": "2026-02-20T11:30:58.176768Z",
+     "start_time": "2026-02-20T11:30:58.173226Z"
     }
    },
    "source": [
@@ -2003,7 +2003,7 @@
     "model_from_json.from_json('fitted.json')"
    ],
    "outputs": [],
-   "execution_count": 81
+   "execution_count": 40
   },
   {
    "cell_type": "code",
@@ -2014,8 +2014,8 @@
      "outputs_hidden": false
     },
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:55:37.950580Z",
-     "start_time": "2025-12-21T14:55:37.944810Z"
+     "end_time": "2026-02-20T11:30:58.252979Z",
+     "start_time": "2026-02-20T11:30:58.249879Z"
     }
    },
    "source": [
@@ -2027,9 +2027,9 @@
      "output_type": "stream",
      "text": [
       "* Selected model: Spherical model\n",
-      "* Nugget: 24.46175798313624\n",
-      "* Sill: 596.0578687869111\n",
-      "* Range: 14980.760125261822\n",
+      "* Nugget: 15.422971149727896\n",
+      "* Sill: 538.168759462272\n",
+      "* Range: 14791.939719657023\n",
       "* Spatial Dependency Strength is strong\n",
       "* Mean Bias: 0.0\n",
       "* Mean RMSE: 0.0\n",
@@ -2039,7 +2039,7 @@
      ]
     }
    ],
-   "execution_count": 82
+   "execution_count": 41
   },
   {
    "cell_type": "markdown",
diff --git a/tutorials/functional/1-2-semivariogram-models.ipynb b/tutorials/functional/1-2-semivariogram-models.ipynb
index 863f63cf..39b9c9bd 100644
--- a/tutorials/functional/1-2-semivariogram-models.ipynb
+++ b/tutorials/functional/1-2-semivariogram-models.ipynb
@@ -49,8 +49,8 @@
    "id": "6dfcd9fe-518d-41f0-aadc-8f7533aedc9d",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:56:35.329277Z",
-     "start_time": "2025-12-21T14:56:31.764877Z"
+     "end_time": "2026-02-20T11:34:25.303516Z",
+     "start_time": "2026-02-20T11:34:22.896274Z"
     }
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    "source": [
@@ -100,8 +100,8 @@
    "id": "61b3c30e-f1b2-4f2d-aaae-a6806185adda",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:56:35.505954Z",
-     "start_time": "2025-12-21T14:56:35.501036Z"
+     "end_time": "2026-02-20T11:34:25.405335Z",
+     "start_time": "2026-02-20T11:34:25.401727Z"
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    "source": [
@@ -123,8 +123,8 @@
    "id": "2303386c-2a55-41c7-9fb5-144e743f45e6",
    "metadata": {
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-     "end_time": "2025-12-21T14:56:35.542936Z",
-     "start_time": "2025-12-21T14:56:35.536667Z"
+     "end_time": "2026-02-20T11:34:25.421118Z",
+     "start_time": "2026-02-20T11:34:25.416248Z"
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@@ -138,8 +138,8 @@
    "id": "b42b9099-8ee9-4fdd-8d18-2003f492411c",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:56:35.788222Z",
-     "start_time": "2025-12-21T14:56:35.580504Z"
+     "end_time": "2026-02-20T11:34:25.603458Z",
+     "start_time": "2026-02-20T11:34:25.436387Z"
     }
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@@ -176,8 +176,8 @@
    "id": "3e86b2ca-ffd7-49e7-8a83-16842993e88a",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:56:35.858920Z",
-     "start_time": "2025-12-21T14:56:35.855291Z"
+     "end_time": "2026-02-20T11:34:25.621293Z",
+     "start_time": "2026-02-20T11:34:25.618805Z"
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@@ -191,8 +191,8 @@
    "id": "db00574b-f3b1-475f-aad3-394d563421a3",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:56:36.142212Z",
-     "start_time": "2025-12-21T14:56:35.901562Z"
+     "end_time": "2026-02-20T11:34:25.836799Z",
+     "start_time": "2026-02-20T11:34:25.632844Z"
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    "source": [
@@ -227,8 +227,8 @@
    "id": "a6919e42-7c39-49ce-a0a3-2f6e60070c95",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:56:36.234100Z",
-     "start_time": "2025-12-21T14:56:36.228778Z"
+     "end_time": "2026-02-20T11:34:25.855841Z",
+     "start_time": "2026-02-20T11:34:25.851057Z"
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@@ -246,8 +246,8 @@
    "id": "36e911d6-1b9a-42e8-9805-b505f2eba475",
    "metadata": {
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-     "end_time": "2025-12-21T14:56:36.490978Z",
-     "start_time": "2025-12-21T14:56:36.288972Z"
+     "end_time": "2026-02-20T11:34:25.993268Z",
+     "start_time": "2026-02-20T11:34:25.869995Z"
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@@ -296,8 +296,8 @@
    "id": "bff02585-3196-4b19-977f-597f024b08bc",
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     "ExecuteTime": {
-     "end_time": "2025-12-21T14:56:36.660034Z",
-     "start_time": "2025-12-21T14:56:36.655450Z"
+     "end_time": "2026-02-20T11:34:26.010634Z",
+     "start_time": "2026-02-20T11:34:26.007844Z"
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@@ -313,8 +313,8 @@
    "id": "e78b927f-c18d-475a-a4ef-4ba51829adfa",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:56:36.708613Z",
-     "start_time": "2025-12-21T14:56:36.705249Z"
+     "end_time": "2026-02-20T11:34:26.025391Z",
+     "start_time": "2026-02-20T11:34:26.022514Z"
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@@ -340,8 +340,8 @@
    "id": "a7f7fb90-7ed8-4c37-9e8d-29ac86ad1d61",
    "metadata": {
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-     "end_time": "2025-12-21T14:56:45.469981Z",
-     "start_time": "2025-12-21T14:56:36.743423Z"
+     "end_time": "2026-02-20T11:34:31.322777Z",
+     "start_time": "2026-02-20T11:34:26.042106Z"
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@@ -360,8 +360,8 @@
    "id": "b1cffc47-a5db-4b7d-99db-2a6c88786ab0",
    "metadata": {
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-     "end_time": "2025-12-21T14:56:45.659152Z",
-     "start_time": "2025-12-21T14:56:45.524665Z"
+     "end_time": "2026-02-20T11:34:31.508511Z",
+     "start_time": "2026-02-20T11:34:31.369786Z"
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@@ -400,8 +400,8 @@
    "id": "d425b5d3-cfe6-4796-9c3b-40e39c43ddb0",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:56:45.721156Z",
-     "start_time": "2025-12-21T14:56:45.717308Z"
+     "end_time": "2026-02-20T11:34:31.546941Z",
+     "start_time": "2026-02-20T11:34:31.544010Z"
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    "source": [
@@ -437,8 +437,8 @@
    "id": "c7638281-61b1-421a-bed7-899c2510dfd7",
    "metadata": {
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-     "end_time": "2025-12-21T14:56:45.769090Z",
-     "start_time": "2025-12-21T14:56:45.762741Z"
+     "end_time": "2026-02-20T11:34:31.588802Z",
+     "start_time": "2026-02-20T11:34:31.581970Z"
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    "source": [
@@ -509,8 +509,8 @@
    "id": "d52f4e78-2c2e-4110-95ea-c0c77450fa86",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:56:45.953523Z",
-     "start_time": "2025-12-21T14:56:45.830009Z"
+     "end_time": "2026-02-20T11:34:31.743569Z",
+     "start_time": "2026-02-20T11:34:31.632598Z"
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    "source": [
@@ -537,8 +537,8 @@
    "id": "3bfe9935-6101-4586-8648-1ce217b91362",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:56:46.118915Z",
-     "start_time": "2025-12-21T14:56:46.003567Z"
+     "end_time": "2026-02-20T11:34:31.902368Z",
+     "start_time": "2026-02-20T11:34:31.785109Z"
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    "source": [
@@ -565,8 +565,8 @@
    "id": "128dad7a-2499-471f-9100-550c869ed7b5",
    "metadata": {
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-     "end_time": "2025-12-21T14:56:46.296041Z",
-     "start_time": "2025-12-21T14:56:46.163889Z"
+     "end_time": "2026-02-20T11:34:32.125506Z",
+     "start_time": "2026-02-20T11:34:31.940691Z"
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@@ -593,8 +593,8 @@
    "id": "f8743b52-08a1-48d1-b771-f3562e6e124f",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:56:46.477670Z",
-     "start_time": "2025-12-21T14:56:46.362256Z"
+     "end_time": "2026-02-20T11:34:32.297409Z",
+     "start_time": "2026-02-20T11:34:32.171260Z"
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    "source": [
@@ -621,8 +621,8 @@
    "id": "ed2986f1-dcb2-4efd-9d3a-350690a670d0",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:56:46.632519Z",
-     "start_time": "2025-12-21T14:56:46.518054Z"
+     "end_time": "2026-02-20T11:34:32.481777Z",
+     "start_time": "2026-02-20T11:34:32.350764Z"
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    "source": [
@@ -649,8 +649,8 @@
    "id": "a7fbbc6d-03ff-4c58-a943-0f266b85aae3",
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-     "end_time": "2025-12-21T14:56:46.805666Z",
-     "start_time": "2025-12-21T14:56:46.688432Z"
+     "end_time": "2026-02-20T11:34:32.642779Z",
+     "start_time": "2026-02-20T11:34:32.520331Z"
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@@ -677,8 +677,8 @@
    "id": "3ee590a9-35aa-4eb2-8fd0-3a76222ce445",
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-     "end_time": "2025-12-21T14:56:46.980976Z",
-     "start_time": "2025-12-21T14:56:46.849062Z"
+     "end_time": "2026-02-20T11:34:32.799367Z",
+     "start_time": "2026-02-20T11:34:32.680757Z"
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    "source": [
@@ -729,8 +729,8 @@
    "id": "58a7316a-60bf-450e-bd16-37c0d51f96c3",
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-     "end_time": "2025-12-21T14:56:47.261404Z",
-     "start_time": "2025-12-21T14:56:47.036838Z"
+     "end_time": "2026-02-20T11:34:33.058873Z",
+     "start_time": "2026-02-20T11:34:32.838255Z"
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diff --git a/tutorials/functional/1-3-spatial-dependency-index.ipynb b/tutorials/functional/1-3-spatial-dependency-index.ipynb
index 015687e9..8711dd09 100644
--- a/tutorials/functional/1-3-spatial-dependency-index.ipynb
+++ b/tutorials/functional/1-3-spatial-dependency-index.ipynb
@@ -90,8 +90,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:56:55.949429Z",
-     "start_time": "2025-12-21T14:56:52.665312Z"
+     "end_time": "2026-02-20T11:47:53.971428Z",
+     "start_time": "2026-02-20T11:47:50.994104Z"
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    "cell_type": "code",
@@ -107,8 +107,8 @@
   {
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     "ExecuteTime": {
-     "end_time": "2025-12-21T14:56:56.119320Z",
-     "start_time": "2025-12-21T14:56:56.115842Z"
+     "end_time": "2026-02-20T11:47:54.160258Z",
+     "start_time": "2026-02-20T11:47:54.157207Z"
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@@ -133,8 +133,8 @@
   {
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-     "end_time": "2025-12-21T14:56:56.164797Z",
-     "start_time": "2025-12-21T14:56:56.141165Z"
+     "end_time": "2026-02-20T11:47:54.193236Z",
+     "start_time": "2026-02-20T11:47:54.175921Z"
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@@ -248,8 +248,8 @@
   {
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-     "end_time": "2025-12-21T14:57:00.021339Z",
-     "start_time": "2025-12-21T14:56:56.368717Z"
+     "end_time": "2026-02-20T11:47:56.496337Z",
+     "start_time": "2026-02-20T11:47:54.306564Z"
     }
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diff --git a/tutorials/functional/2-1-directional-semivariogram.ipynb b/tutorials/functional/2-1-directional-semivariogram.ipynb
index 899d985d..1bf5336b 100644
--- a/tutorials/functional/2-1-directional-semivariogram.ipynb
+++ b/tutorials/functional/2-1-directional-semivariogram.ipynb
@@ -41,8 +41,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T14:57:02.611148Z",
-     "start_time": "2025-12-21T14:56:58.979900Z"
+     "end_time": "2026-02-20T12:03:24.526694Z",
+     "start_time": "2026-02-20T12:03:21.159921Z"
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@@ -59,8 +59,8 @@
   {
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     "ExecuteTime": {
-     "end_time": "2025-12-21T14:57:02.990045Z",
-     "start_time": "2025-12-21T14:57:02.760193Z"
+     "end_time": "2026-02-20T12:03:24.950697Z",
+     "start_time": "2026-02-20T12:03:24.718009Z"
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@@ -76,8 +76,8 @@
   {
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     "ExecuteTime": {
-     "end_time": "2025-12-21T14:57:03.087823Z",
-     "start_time": "2025-12-21T14:57:03.050427Z"
+     "end_time": "2026-02-20T12:03:24.977155Z",
+     "start_time": "2026-02-20T12:03:24.966972Z"
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@@ -164,8 +164,8 @@
   {
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-     "end_time": "2025-12-21T14:57:03.683525Z",
-     "start_time": "2025-12-21T14:57:03.290699Z"
+     "end_time": "2026-02-20T12:03:25.347942Z",
+     "start_time": "2026-02-20T12:03:25.090096Z"
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@@ -243,8 +243,8 @@
   {
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-     "end_time": "2025-12-21T14:57:04.517133Z",
-     "start_time": "2025-12-21T14:57:04.511722Z"
+     "end_time": "2026-02-20T12:03:25.389864Z",
+     "start_time": "2026-02-20T12:03:25.387258Z"
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@@ -261,8 +261,8 @@
   {
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-     "end_time": "2025-12-21T14:57:05.082937Z",
-     "start_time": "2025-12-21T14:57:04.795763Z"
+     "end_time": "2026-02-20T12:03:25.578703Z",
+     "start_time": "2026-02-20T12:03:25.407623Z"
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@@ -301,8 +301,8 @@
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-     "end_time": "2025-12-21T14:57:05.108813Z",
-     "start_time": "2025-12-21T14:57:05.105483Z"
+     "end_time": "2026-02-20T12:03:25.601375Z",
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@@ -314,8 +314,8 @@
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@@ -354,8 +354,8 @@
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@@ -367,8 +367,8 @@
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@@ -407,8 +407,8 @@
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@@ -420,8 +420,8 @@
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@@ -460,8 +460,8 @@
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@@ -509,8 +509,8 @@
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@@ -530,8 +530,8 @@
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diff --git a/tutorials/functional/4-2-poisson-kriging-centroid-based.ipynb b/tutorials/functional/4-2-poisson-kriging-centroid-based.ipynb
index 8a1f35f6..ae4517da 100644
--- a/tutorials/functional/4-2-poisson-kriging-centroid-based.ipynb
+++ b/tutorials/functional/4-2-poisson-kriging-centroid-based.ipynb
@@ -49,8 +49,8 @@
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@@ -70,8 +70,8 @@
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@@ -190,8 +190,8 @@
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"
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"
      },
      "metadata": {},
      "output_type": "display_data"
@@ -567,8 +567,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:11:53.632698Z",
-     "start_time": "2025-12-21T15:11:53.302141Z"
+     "end_time": "2026-02-20T12:03:45.750889Z",
+     "start_time": "2026-02-20T12:03:45.441233Z"
     }
    },
    "cell_type": "code",
@@ -590,7 +590,7 @@
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ],
-      "image/png": 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"
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"
      },
      "metadata": {},
      "output_type": "display_data"
@@ -601,8 +601,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:11:53.677115Z",
-     "start_time": "2025-12-21T15:11:53.652504Z"
+     "end_time": "2026-02-20T12:03:45.817652Z",
+     "start_time": "2026-02-20T12:03:45.788550Z"
     }
    },
    "cell_type": "code",
@@ -614,13 +614,13 @@
       "text/plain": [
        "             zhat        rate  forecast_bias  squared_error\n",
        "count   20.000000   20.000000      20.000000      20.000000\n",
-       "mean   131.574586  132.880000      -1.305414     185.804660\n",
-       "std      6.574559   13.410271      13.920850     356.853735\n",
-       "min    120.601986  103.400000     -23.659756       4.407567\n",
-       "25%    127.733954  121.550000      -8.677488      12.200951\n",
-       "50%    131.640182  134.200000      -2.666852      56.582626\n",
-       "75%    135.717496  141.675000       6.067428     153.072548\n",
-       "max    142.869604  153.200000      39.469604    1557.849657"
+       "mean   129.430303  129.990000      -0.559697     144.563971\n",
+       "std      4.768052   11.653231      12.322453     204.664462\n",
+       "min    121.257306  107.600000     -22.514097       2.310367\n",
+       "25%    125.110624  121.100000      -6.814534      18.116912\n",
+       "50%    130.242219  129.850000      -2.011978      91.429304\n",
+       "75%    133.371224  140.950000       9.678415     143.497682\n",
+       "max    136.694439  146.500000      28.238612     797.419208"
       ],
       "text/html": [
        "<div>\n",
@@ -657,52 +657,52 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>mean</th>\n",
-       "      <td>131.574586</td>\n",
-       "      <td>132.880000</td>\n",
-       "      <td>-1.305414</td>\n",
-       "      <td>185.804660</td>\n",
+       "      <td>129.430303</td>\n",
+       "      <td>129.990000</td>\n",
+       "      <td>-0.559697</td>\n",
+       "      <td>144.563971</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>std</th>\n",
-       "      <td>6.574559</td>\n",
-       "      <td>13.410271</td>\n",
-       "      <td>13.920850</td>\n",
-       "      <td>356.853735</td>\n",
+       "      <td>4.768052</td>\n",
+       "      <td>11.653231</td>\n",
+       "      <td>12.322453</td>\n",
+       "      <td>204.664462</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>min</th>\n",
-       "      <td>120.601986</td>\n",
-       "      <td>103.400000</td>\n",
-       "      <td>-23.659756</td>\n",
-       "      <td>4.407567</td>\n",
+       "      <td>121.257306</td>\n",
+       "      <td>107.600000</td>\n",
+       "      <td>-22.514097</td>\n",
+       "      <td>2.310367</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25%</th>\n",
-       "      <td>127.733954</td>\n",
-       "      <td>121.550000</td>\n",
-       "      <td>-8.677488</td>\n",
-       "      <td>12.200951</td>\n",
+       "      <td>125.110624</td>\n",
+       "      <td>121.100000</td>\n",
+       "      <td>-6.814534</td>\n",
+       "      <td>18.116912</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>50%</th>\n",
-       "      <td>131.640182</td>\n",
-       "      <td>134.200000</td>\n",
-       "      <td>-2.666852</td>\n",
-       "      <td>56.582626</td>\n",
+       "      <td>130.242219</td>\n",
+       "      <td>129.850000</td>\n",
+       "      <td>-2.011978</td>\n",
+       "      <td>91.429304</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>75%</th>\n",
-       "      <td>135.717496</td>\n",
-       "      <td>141.675000</td>\n",
-       "      <td>6.067428</td>\n",
-       "      <td>153.072548</td>\n",
+       "      <td>133.371224</td>\n",
+       "      <td>140.950000</td>\n",
+       "      <td>9.678415</td>\n",
+       "      <td>143.497682</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>max</th>\n",
-       "      <td>142.869604</td>\n",
-       "      <td>153.200000</td>\n",
-       "      <td>39.469604</td>\n",
-       "      <td>1557.849657</td>\n",
+       "      <td>136.694439</td>\n",
+       "      <td>146.500000</td>\n",
+       "      <td>28.238612</td>\n",
+       "      <td>797.419208</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -719,8 +719,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:11:53.741660Z",
-     "start_time": "2025-12-21T15:11:53.737072Z"
+     "end_time": "2026-02-20T12:03:45.905919Z",
+     "start_time": "2026-02-20T12:03:45.901280Z"
     }
    },
    "cell_type": "code",
@@ -734,7 +734,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "13.631018290285816\n"
+      "12.023475848470005\n"
      ]
     }
    ],
@@ -777,8 +777,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:11:53.811629Z",
-     "start_time": "2025-12-21T15:11:53.808631Z"
+     "end_time": "2026-02-20T12:03:45.985404Z",
+     "start_time": "2026-02-20T12:03:45.982983Z"
     }
    },
    "cell_type": "code",
diff --git a/tutorials/functional/4-3-poisson-kriging-area-to-area.ipynb b/tutorials/functional/4-3-poisson-kriging-area-to-area.ipynb
index 6b17969a..ac88d391 100644
--- a/tutorials/functional/4-3-poisson-kriging-area-to-area.ipynb
+++ b/tutorials/functional/4-3-poisson-kriging-area-to-area.ipynb
@@ -47,8 +47,8 @@
    "metadata": {
     "collapsed": true,
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:11:51.088926Z",
-     "start_time": "2025-12-21T15:11:48.286540Z"
+     "end_time": "2026-02-20T12:11:53.503598Z",
+     "start_time": "2026-02-20T12:11:50.121717Z"
     }
    },
    "cell_type": "code",
@@ -68,8 +68,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:11:51.245010Z",
-     "start_time": "2025-12-21T15:11:51.207493Z"
+     "end_time": "2026-02-20T12:11:53.701289Z",
+     "start_time": "2026-02-20T12:11:53.697808Z"
     }
    },
    "cell_type": "code",
@@ -90,8 +90,8 @@
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"
+      "image/png": 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"
      },
      "metadata": {},
      "output_type": "display_data"
@@ -532,8 +532,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:11:58.383831Z",
-     "start_time": "2025-12-21T15:11:58.186397Z"
+     "end_time": "2026-02-20T12:12:00.780335Z",
+     "start_time": "2026-02-20T12:12:00.609483Z"
     }
    },
    "cell_type": "code",
@@ -555,7 +555,7 @@
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ],
-      "image/png": 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"
+      "image/png": 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"
      },
      "metadata": {},
      "output_type": "display_data"
@@ -566,8 +566,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:11:58.427009Z",
-     "start_time": "2025-12-21T15:11:58.404488Z"
+     "end_time": "2026-02-20T12:12:00.831603Z",
+     "start_time": "2026-02-20T12:12:00.804682Z"
     }
    },
    "cell_type": "code",
@@ -579,13 +579,13 @@
       "text/plain": [
        "             zhat        rate  forecast_bias  squared_error\n",
        "count   20.000000   20.000000      20.000000      20.000000\n",
-       "mean   129.228669  127.830000       1.398669     179.574443\n",
-       "std      7.810987   14.454142      13.673569     215.335912\n",
-       "min    117.906817  101.100000     -23.332442       0.008683\n",
-       "25%    125.756270  115.575000      -8.189205       3.405850\n",
-       "50%    127.729558  130.700000       0.657993      99.978315\n",
-       "75%    131.912100  138.475000       9.628163     262.877367\n",
-       "max    146.846616  152.900000      24.044155     578.121379"
+       "mean   131.154842  129.290000       1.864842     123.598408\n",
+       "std      5.364100   12.805381      11.244684     133.042729\n",
+       "min    118.099700  107.600000     -14.287299      17.917040\n",
+       "25%    127.487312  119.700000      -7.753780      40.969163\n",
+       "50%    131.526426  129.950000       4.920876      66.352961\n",
+       "75%    134.555554  137.650000       8.447125     172.813286\n",
+       "max    143.779517  148.100000      24.044155     578.121379"
       ],
       "text/html": [
        "<div>\n",
@@ -622,50 +622,50 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>mean</th>\n",
-       "      <td>129.228669</td>\n",
-       "      <td>127.830000</td>\n",
-       "      <td>1.398669</td>\n",
-       "      <td>179.574443</td>\n",
+       "      <td>131.154842</td>\n",
+       "      <td>129.290000</td>\n",
+       "      <td>1.864842</td>\n",
+       "      <td>123.598408</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>std</th>\n",
-       "      <td>7.810987</td>\n",
-       "      <td>14.454142</td>\n",
-       "      <td>13.673569</td>\n",
-       "      <td>215.335912</td>\n",
+       "      <td>5.364100</td>\n",
+       "      <td>12.805381</td>\n",
+       "      <td>11.244684</td>\n",
+       "      <td>133.042729</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>min</th>\n",
-       "      <td>117.906817</td>\n",
-       "      <td>101.100000</td>\n",
-       "      <td>-23.332442</td>\n",
-       "      <td>0.008683</td>\n",
+       "      <td>118.099700</td>\n",
+       "      <td>107.600000</td>\n",
+       "      <td>-14.287299</td>\n",
+       "      <td>17.917040</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25%</th>\n",
-       "      <td>125.756270</td>\n",
-       "      <td>115.575000</td>\n",
-       "      <td>-8.189205</td>\n",
-       "      <td>3.405850</td>\n",
+       "      <td>127.487312</td>\n",
+       "      <td>119.700000</td>\n",
+       "      <td>-7.753780</td>\n",
+       "      <td>40.969163</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>50%</th>\n",
-       "      <td>127.729558</td>\n",
-       "      <td>130.700000</td>\n",
-       "      <td>0.657993</td>\n",
-       "      <td>99.978315</td>\n",
+       "      <td>131.526426</td>\n",
+       "      <td>129.950000</td>\n",
+       "      <td>4.920876</td>\n",
+       "      <td>66.352961</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>75%</th>\n",
-       "      <td>131.912100</td>\n",
-       "      <td>138.475000</td>\n",
-       "      <td>9.628163</td>\n",
-       "      <td>262.877367</td>\n",
+       "      <td>134.555554</td>\n",
+       "      <td>137.650000</td>\n",
+       "      <td>8.447125</td>\n",
+       "      <td>172.813286</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>max</th>\n",
-       "      <td>146.846616</td>\n",
-       "      <td>152.900000</td>\n",
+       "      <td>143.779517</td>\n",
+       "      <td>148.100000</td>\n",
        "      <td>24.044155</td>\n",
        "      <td>578.121379</td>\n",
        "    </tr>\n",
@@ -684,8 +684,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:11:58.493477Z",
-     "start_time": "2025-12-21T15:11:58.489121Z"
+     "end_time": "2026-02-20T12:12:00.978199Z",
+     "start_time": "2026-02-20T12:12:00.973169Z"
     }
    },
    "cell_type": "code",
@@ -699,7 +699,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "13.400538906042224\n"
+      "11.117482069636571\n"
      ]
     }
    ],
diff --git a/tutorials/functional/4-4-poisson-kriging-area-to-point-smoothing.ipynb b/tutorials/functional/4-4-poisson-kriging-area-to-point-smoothing.ipynb
index 237ae992..3227e450 100644
--- a/tutorials/functional/4-4-poisson-kriging-area-to-point-smoothing.ipynb
+++ b/tutorials/functional/4-4-poisson-kriging-area-to-point-smoothing.ipynb
@@ -43,8 +43,8 @@
    "metadata": {
     "collapsed": true,
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:11:53.921286Z",
-     "start_time": "2025-12-21T15:11:51.004285Z"
+     "end_time": "2026-02-20T13:07:23.970144Z",
+     "start_time": "2026-02-20T13:07:20.663882Z"
     }
    },
    "cell_type": "code",
@@ -61,8 +61,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:11:54.020324Z",
-     "start_time": "2025-12-21T15:11:54.017306Z"
+     "end_time": "2026-02-20T13:07:24.196825Z",
+     "start_time": "2026-02-20T13:07:24.192441Z"
     }
    },
    "cell_type": "code",
@@ -83,8 +83,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:11:54.259727Z",
-     "start_time": "2025-12-21T15:11:54.039446Z"
+     "end_time": "2026-02-20T13:07:24.493827Z",
+     "start_time": "2026-02-20T13:07:24.227993Z"
     }
    },
    "cell_type": "code",
@@ -103,8 +103,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:11:54.604431Z",
-     "start_time": "2025-12-21T15:11:54.269439Z"
+     "end_time": "2026-02-20T13:07:24.807056Z",
+     "start_time": "2026-02-20T13:07:24.503962Z"
     }
    },
    "cell_type": "code",
@@ -124,8 +124,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:11:55.556050Z",
-     "start_time": "2025-12-21T15:11:54.614784Z"
+     "end_time": "2026-02-20T13:07:25.690849Z",
+     "start_time": "2026-02-20T13:07:24.818537Z"
     }
    },
    "cell_type": "code",
@@ -175,8 +175,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:11:55.692305Z",
-     "start_time": "2025-12-21T15:11:55.571103Z"
+     "end_time": "2026-02-20T13:07:25.815009Z",
+     "start_time": "2026-02-20T13:07:25.703834Z"
     }
    },
    "cell_type": "code",
@@ -215,8 +215,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:13:59.054834Z",
-     "start_time": "2025-12-21T15:11:55.704576Z"
+     "end_time": "2026-02-20T13:09:45.730679Z",
+     "start_time": "2026-02-20T13:07:44.305175Z"
     }
    },
    "cell_type": "code",
@@ -226,6 +226,8 @@
     "    point_support=point_support,\n",
     "    number_of_neighbors=16,\n",
     "    data_crs=point_support.point_support.crs,\n",
+    "    raise_when_negative_prediction=False,\n",
+    "    raise_when_negative_error=False,\n",
     "    verbose=False\n",
     ")"
    ],
@@ -236,8 +238,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:13:59.094800Z",
-     "start_time": "2025-12-21T15:13:59.083046Z"
+     "end_time": "2026-02-20T13:09:51.685988Z",
+     "start_time": "2026-02-20T13:09:51.677884Z"
     }
    },
    "cell_type": "code",
@@ -326,12 +328,12 @@
        "</div>"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
-   "execution_count": 8
+   "execution_count": 9
   },
   {
    "metadata": {},
@@ -346,8 +348,8 @@
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:14:01.081422Z",
-     "start_time": "2025-12-21T15:13:59.181224Z"
+     "end_time": "2026-02-20T13:09:58.278730Z",
+     "start_time": "2026-02-20T13:09:56.341097Z"
     }
    },
    "cell_type": "code",
@@ -365,7 +367,7 @@
        "<Axes: >"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -380,13 +382,13 @@
      "output_type": "display_data"
     }
    ],
-   "execution_count": 9
+   "execution_count": 10
   },
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:14:03.066161Z",
-     "start_time": "2025-12-21T15:14:01.202022Z"
+     "end_time": "2026-02-20T13:10:05.383573Z",
+     "start_time": "2026-02-20T13:10:03.519936Z"
     }
    },
    "cell_type": "code",
@@ -402,7 +404,7 @@
        "<Axes: >"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -417,12 +419,12 @@
      "output_type": "display_data"
     }
    ],
-   "execution_count": 10
+   "execution_count": 11
   },
   {
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-12-21T15:14:03.099536Z",
+     "end_time": "2026-02-20T12:12:13.025146Z",
      "start_time": "2025-12-21T15:14:03.096462Z"
     }
    },
@@ -438,11 +440,20 @@
    "source": [
     "## Changelog\n",
     "\n",
-    "| Date       | Changes                                      | Author                           |\n",
-    "|------------|----------------------------------------------|----------------------------------|\n",
-    "| 2025-05-31 | Tutorial has been adapted to the 1.0 release | @SimonMolinsky (Szymon Moliński) |"
+    "| Date       | Changes                                                                                                                                | Author                           |\n",
+    "|------------|----------------------------------------------------------------------------------------------------------------------------------------|----------------------------------|\n",
+    "| 2026-02-20 | Changed behavior of `smooth_blocks` - right now setting up negative prediction and negative error checks is more important than before | @SimonMolinsky                   |\n",
+    "| 2025-05-31 | Tutorial has been adapted to the 1.0 release                                                                                           | @SimonMolinsky (Szymon Moliński) |"
    ],
    "id": "45fabf06c69418"
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": "",
+   "id": "508f927add1892c4"
   }
  ],
  "metadata": {
diff --git a/tutorials/functional/fitted.json b/tutorials/functional/fitted.json
index 14b4bb51..5a7496b0 100644
--- a/tutorials/functional/fitted.json
+++ b/tutorials/functional/fitted.json
@@ -1 +1 @@
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\ No newline at end of file
+{"experimental_variogram": null, "nugget": 15.422971149727896, "sill": 538.168759462272, "rang": 14791.939719657023, "variogram_model_type": "spherical", "direction": null, "spatial_dependence": null, "spatial_index": null, "yhat": null, "errors": null}
\ No newline at end of file