diff --git a/README.md b/README.md
index 1c2c395..8ad486e 100644
--- a/README.md
+++ b/README.md
@@ -15,13 +15,27 @@ In the limit of arbitrarily many subsets, each new addition or point moved by a
 all nearest neighbors, to keep the in-degree of each point low, and
 2. When we insert a point, we don't bother updating other points' neighbors.
 
-**Total space:** $20n$ bytes (could be reduced to $4n$ at some cost in update time).
-
-**Time per insertion or single distance update:** $O(n)$.
-
-**Time per deletion or point update:** $O(n)$ expected, $O(n^2)$ worst case.
-
-**Time per closest pair:** $O(n)$.
+<table>
+  <tr>
+    <td align="center" colspan="2"><b>Complexity</b></td>
+  </tr>
+  <tr>
+    <td><i>Total space</i></td>
+    <td>$20n$ bytes (could be reduced to $4n$ at some cost in update time)</td>
+  </tr>
+ <tr>
+    <td><i>Time per insertion or single distance update</i></td>
+    <td>$O(n)$ </td>
+  </tr>
+ <tr>
+    <td><i>Time per deletion or point update</i></td>
+    <td>$O(n)$ expected, $O(n^2)$ worst case</td>
+  </tr>
+ <tr>
+    <td><i>TTime per closest pair</i></td>
+    <td>$O(n)$</td>
+  </tr>
+</table>
 
 This `Python` version of the algorithm combines ideas and code from the [closest-pair data structure testbed (C++)](https://www.ics.uci.edu/~eppstein/projects/pairs/Source/testbed/) developed around a [series of papers](https://www.ics.uci.edu/~eppstein/projects/pairs/Papers/) by Eppstein *et al.*
 
@@ -62,88 +76,16 @@ pytest -v fastpair --cov fastpair
 
 Currently `fastpair` is tested against Python 3.{10,11,12}.
 
-## Features
-
-In the following examples we use the `random` module to generate data.
-
-```python
-from fastpair import FastPair, interact
-import random
-
-def rand_tuple(dim=2):
-    return tuple([random.random() for _ in range(dim)])
-```
-
-### Basics
-
-The simplest way to use a `FastPair` data-structure is to initialize one and then update it with data points (via the `+=` operator).
-In this first example, we create a sequence of $50 \times 10$ uniform random points and add them to a `FastPair` object:
-
-```python
-points = [rand_tuple(10) for _ in range(50)]
-# Create empty data-structure with `min_points=10` and
-# using a Euclidean distance metric
-fp = FastPair()
-fp.build(points)  # Add points all at once and build conga line to start
-```
-
-You can then add additional points, and start to query the data-structure for
-the closest pair of points. As points are added, the data-structure responds
-and updates accordingly
-(see [this paper](http://dl.acm.org/citation.cfm?id=351829) for details):
-
-```python
-fp += rand_tuple(10)
-fp += rand_tuple(10)
-
-# This is the 'FastPair' algorithm, should be fast for large n
-fp.closest_pair()
-# There is also a brute-force version, can be fast for smaller n
-fp.closest_pair_brute_force()
-```
-
-`FastPair` has several useful properties and methods, including checking the size of the data-structure (i.e., how many points are currently stored), testing for containment of a given point, various methods for computing the closest pair, finding the neighbor of a given point, computing multiple distances at once, and even merging points (clusters):
+## Utilizing `FastPair`
 
-```python
-len(fp)
-rando = rand_tuple(10)
-points[0] in fp  # True
-rando in fp  # False
-fp()  # Compute closest pair
-neigh = fp.find_neighbor(rando)  # Neighbor of 'outside' point
-fp.sdist(rando)  # Compute distances from rando to all points in fp
-```
+This notebooks linked below are designed as interactive, minimum tutorials in working with `fastpair` and require additional dependencies, which can be installed with:
 
-To illustrate the `merge`ing methods, here is a simple example of hierarchical clustering, treating `points` as the 'centroids' of various clusters:
-
-```python
-for i in range(len(fp)-1):
-    # First method... do it manually:
-    dist, (a, b) = fp.closest_pair()
-    c = interact(a, b)  # Compute mean centroid
-    fp -= b
-    fp -= a
-    fp += c
-    # Alternatively... do it all in one step:
-    # fp.merge_closest()
-len(fp)  # 1
+```bash
+pip install -e .[tests,notebooks]
 ```
 
-Finally, plotting should be pretty obvious to those familiar with `matplotlib` (or other `Python` plotting facilities).
-
-```python
-import matplotlib.pyplot as plt
-
-points = [rand_tuple(2) for _ in range(50)]  # 2D points
-fp = FastPair().build(points)
-dist, (a, b) = fp.closest_pair()
-
-plt.figure()
-plt.scatter(*zip(*fp.points))
-plt.scatter(*zip(a, b), color="red")
-plt.title("Closest pair is {:.2} units apart.".format(dist))
-plt.show()
-```
+* [`basics_usage.iypnb`](https://github.com/carsonfarmer/fastpair/notebooks/basics_usage.iypnb): Understanding the `fastpair` functionality and data structure
+* [`n-dimensional_pointsets`](https://github.com/carsonfarmer/fastpair/notebooks/n-dimensional_pointsets.iypnb): Querying point clouds
 
 ## License
 
diff --git a/notebooks/basic_usage.ipynb b/notebooks/basic_usage.ipynb
index afb0f8f..5ae2c52 100644
--- a/notebooks/basic_usage.ipynb
+++ b/notebooks/basic_usage.ipynb
@@ -18,11 +18,11 @@
    "id": "2da42c3d-a668-456c-9d05-5b826d2ca963",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:47.717373Z",
-     "iopub.status.busy": "2024-06-12T02:00:47.717160Z",
-     "iopub.status.idle": "2024-06-12T02:00:47.752407Z",
-     "shell.execute_reply": "2024-06-12T02:00:47.751967Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:47.717349Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.402265Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.401881Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.431762Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.430862Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.402240Z"
     }
    },
    "outputs": [
@@ -30,7 +30,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Last updated: 2024-06-11T22:00:47.741779-04:00\n",
+      "Last updated: 2024-06-15T14:59:33.420817-04:00\n",
       "\n",
       "Python implementation: CPython\n",
       "Python version       : 3.12.3\n",
@@ -59,11 +59,11 @@
    "id": "5f2c2691-2f11-4649-aafd-eaf734d5c368",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:47.753362Z",
-     "iopub.status.busy": "2024-06-12T02:00:47.753168Z",
-     "iopub.status.idle": "2024-06-12T02:00:47.977527Z",
-     "shell.execute_reply": "2024-06-12T02:00:47.977286Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:47.753345Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.432574Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.432449Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.660652Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.660447Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.432556Z"
     }
    },
    "outputs": [
@@ -75,14 +75,12 @@
       "\n",
       "matplotlib: 3.9.0\n",
       "fastpair  : 0.1.1.dev8+g5f8e7a5.d20240611\n",
-      "numpy     : 1.26.4\n",
       "\n"
      ]
     }
    ],
    "source": [
     "import matplotlib.pyplot as plt\n",
-    "import numpy\n",
     "\n",
     "import fastpair\n",
     "\n",
@@ -90,127 +88,6 @@
     "%watermark -iv"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "8f7e9080-ff0d-4a6d-8cdc-e7a7b4e71946",
-   "metadata": {},
-   "source": [
-    "---------------------------------\n",
-    "\n",
-    "## 1. Setup\n",
-    "\n",
-    "The following helper function will be used the generate random tuples of points in the example.\n",
-    "\n",
-    "* A reproducibile state can be set with the `seed` argument.\n",
-    "* Use the `size` argument to indicate the tuple dimensions.\n",
-    "* Set the `n` argument for the number of desired points\n",
-    "* `low` and `high` control for minimum and maximum values, respectively.\n",
-    "* The [desired distribution](https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.default_rng) is set in `sample`. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "26917e2e-d996-469e-9028-3edd638ffe10",
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:47.978599Z",
-     "iopub.status.busy": "2024-06-12T02:00:47.978494Z",
-     "iopub.status.idle": "2024-06-12T02:00:47.980383Z",
-     "shell.execute_reply": "2024-06-12T02:00:47.980190Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:47.978592Z"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "def random_points(\n",
-    "    seed: int = 0,\n",
-    "    size: int | tuple = (2),\n",
-    "    n: int = 1,\n",
-    "    low: int = 0,\n",
-    "    high: int = 20,\n",
-    "    sample: str = \"integers\",\n",
-    ") -> list[tuple[float]]:\n",
-    "    rng = numpy.random.default_rng(seed)\n",
-    "    return [\n",
-    "        tuple(getattr(rng, sample)(low=low, high=high, size=size)) for i in range(n)\n",
-    "    ]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "ea1a2cd7-7822-4fbc-af59-d1587dc72e9c",
-   "metadata": {},
-   "source": [
-    "Generate a single 1D point from seed `0`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "e7078d76-f6db-43c9-aff8-8c541ea385f9",
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:47.980711Z",
-     "iopub.status.busy": "2024-06-12T02:00:47.980639Z",
-     "iopub.status.idle": "2024-06-12T02:00:47.983242Z",
-     "shell.execute_reply": "2024-06-12T02:00:47.983070Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:47.980703Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[(9,)]"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "random_points(1, 1, 1)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "cc8f9d0e-fff0-4231-b650-c9f107c9e535",
-   "metadata": {},
-   "source": [
-    "Generate 3 2D points from seed `1`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "c9a81f46-a864-4d96-a9a3-9e801a8a6e42",
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:47.983606Z",
-     "iopub.status.busy": "2024-06-12T02:00:47.983545Z",
-     "iopub.status.idle": "2024-06-12T02:00:47.985417Z",
-     "shell.execute_reply": "2024-06-12T02:00:47.985231Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:47.983599Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[(9, 10), (15, 19), (0, 2)]"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "random_points(1, (2), 3)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "7a01e92a-78cd-4ced-ac36-868e3ae74969",
@@ -218,38 +95,38 @@
    "source": [
     "---------------------\n",
     "\n",
-    "## 2. Properties\n",
+    "## 1. Properties\n",
     "\n",
-    "The simplest way to use a `FastPair` data-structure is to initialize one and then update it with data points (via the `+=` operator), which we will explore later. In this first example, we create a sequence of 3 2D random integers and add them to a `FastPair` object."
+    "The simplest way to use a `FastPair` data-structure is to initialize one and then update it with data points (via the `+=` operator), which we will explore later. In this first example, we declare 3 2D points and add them to a `FastPair` object."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
-   "id": "119645fe-c0ca-4b9f-a074-9a3c80a24204",
+   "execution_count": 3,
+   "id": "c4845e9d-f5d5-4f92-94f8-72f809f0fac9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:47.985856Z",
-     "iopub.status.busy": "2024-06-12T02:00:47.985753Z",
-     "iopub.status.idle": "2024-06-12T02:00:47.987630Z",
-     "shell.execute_reply": "2024-06-12T02:00:47.987468Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:47.985849Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.661746Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.661641Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.664384Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.664183Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.661739Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[(9, 10), (15, 19), (0, 2)]"
+       "[(1, 1), (2, 2), (4, 4)]"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "points = random_points(1, (2), 3)\n",
+    "points = [(1, 1), (2, 2), (4, 4)]\n",
     "points"
    ]
   },
@@ -266,25 +143,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 4,
    "id": "7e37b5d2-e626-486d-a02f-c982eea73907",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:47.987966Z",
-     "iopub.status.busy": "2024-06-12T02:00:47.987901Z",
-     "iopub.status.idle": "2024-06-12T02:00:47.989627Z",
-     "shell.execute_reply": "2024-06-12T02:00:47.989454Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:47.987959Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.664794Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.664731Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.666585Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.666413Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.664787Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<fastpair.base.FastPair at 0x14966b050>"
+       "<fastpair.base.FastPair at 0x118a22840>"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -304,25 +181,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 5,
    "id": "895e21eb-9449-4aa5-999b-5ac13f9e4219",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:47.989916Z",
-     "iopub.status.busy": "2024-06-12T02:00:47.989858Z",
-     "iopub.status.idle": "2024-06-12T02:00:47.991625Z",
-     "shell.execute_reply": "2024-06-12T02:00:47.991426Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:47.989910Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.666934Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.666875Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.668678Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.668503Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.666927Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<fastpair.base.FastPair at 0x14966b050>"
+       "<fastpair.base.FastPair at 0x118a22840>"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -356,15 +233,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 6,
    "id": "01160597-4c0f-4cd1-9cd4-b7dc8bce6b2a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:47.992043Z",
-     "iopub.status.busy": "2024-06-12T02:00:47.991982Z",
-     "iopub.status.idle": "2024-06-12T02:00:47.994019Z",
-     "shell.execute_reply": "2024-06-12T02:00:47.993813Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:47.992036Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.669075Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.668999Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.670639Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.670479Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.669069Z"
     }
    },
    "outputs": [
@@ -374,7 +251,7 @@
        "3"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -395,15 +272,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 7,
    "id": "9d7adeb7-36a4-41e7-93e9-9a1fee6edbed",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:47.994442Z",
-     "iopub.status.busy": "2024-06-12T02:00:47.994356Z",
-     "iopub.status.idle": "2024-06-12T02:00:47.996536Z",
-     "shell.execute_reply": "2024-06-12T02:00:47.996174Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:47.994436Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.671017Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.670952Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.672651Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.672478Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.671011Z"
     }
    },
    "outputs": [
@@ -413,7 +290,7 @@
        "True"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -432,15 +309,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 8,
    "id": "30355b1a-3757-43c0-ab95-0733f4f50e81",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:47.997338Z",
-     "iopub.status.busy": "2024-06-12T02:00:47.997263Z",
-     "iopub.status.idle": "2024-06-12T02:00:47.999418Z",
-     "shell.execute_reply": "2024-06-12T02:00:47.999172Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:47.997331Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.672954Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.672898Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.674490Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.674320Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.672948Z"
     }
    },
    "outputs": [
@@ -450,7 +327,7 @@
        "False"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -471,25 +348,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 9,
    "id": "78034246-f548-4a1c-9872-ea071462c058",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:48.001699Z",
-     "iopub.status.busy": "2024-06-12T02:00:48.001534Z",
-     "iopub.status.idle": "2024-06-12T02:00:48.003536Z",
-     "shell.execute_reply": "2024-06-12T02:00:48.003330Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:48.001690Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.674824Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.674719Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.676467Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.676278Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.674818Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(10.816653826391969, ((9, 10), (15, 19)))"
+       "(1.4142135623730951, ((1, 1), (2, 2)))"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -508,25 +385,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 10,
    "id": "9f7315f7-72d0-4693-9808-d1e325f93c8d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:48.004333Z",
-     "iopub.status.busy": "2024-06-12T02:00:48.004247Z",
-     "iopub.status.idle": "2024-06-12T02:00:48.006416Z",
-     "shell.execute_reply": "2024-06-12T02:00:48.006222Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:48.004324Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.676827Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.676771Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.678580Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.678391Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.676821Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(10.816653826391969, ((9, 10), (15, 19)))"
+       "(1.4142135623730951, ((1, 1), (2, 2)))"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -545,25 +422,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 11,
    "id": "37366768-415c-42ab-9c18-110750160483",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:48.006952Z",
-     "iopub.status.busy": "2024-06-12T02:00:48.006878Z",
-     "iopub.status.idle": "2024-06-12T02:00:48.008937Z",
-     "shell.execute_reply": "2024-06-12T02:00:48.008735Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:48.006944Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.678945Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.678887Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.681266Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.681076Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.678939Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(10.816653826391969, ((9, 10), (15, 19)))"
+       "(1.4142135623730951, ((1, 1), (2, 2)))"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -584,25 +461,52 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 12,
+   "id": "65890425-a4c6-45f2-8c57-90c7afd9a204",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:33.683179Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.683091Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.684782Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.684599Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.683171Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "points=[(1, 1), (2, 2), (4, 4)]\n",
+      "points[1]=(2, 2)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"{points=}\\n{points[1]=}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
    "id": "ac10107e-1f1b-437c-a0c5-0323460a9bff",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:48.009444Z",
-     "iopub.status.busy": "2024-06-12T02:00:48.009343Z",
-     "iopub.status.idle": "2024-06-12T02:00:48.011279Z",
-     "shell.execute_reply": "2024-06-12T02:00:48.011088Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:48.009437Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.685173Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.685115Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.687289Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.687107Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.685167Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(9, 10)"
+       "(1, 1)"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -622,25 +526,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 14,
    "id": "9284e7a7-0765-4d9e-9f51-0c64217fe778",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:48.011695Z",
-     "iopub.status.busy": "2024-06-12T02:00:48.011622Z",
-     "iopub.status.idle": "2024-06-12T02:00:48.014009Z",
-     "shell.execute_reply": "2024-06-12T02:00:48.013783Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:48.011682Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.687723Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.687661Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.689574Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.689367Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.687716Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "10.816653826391969"
+       "1.4142135623730951"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -659,25 +563,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 15,
    "id": "2e255c57-90c4-4596-8f31-9f352cc89357",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:48.014826Z",
-     "iopub.status.busy": "2024-06-12T02:00:48.014632Z",
-     "iopub.status.idle": "2024-06-12T02:00:48.016780Z",
-     "shell.execute_reply": "2024-06-12T02:00:48.016591Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:48.014816Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.690071Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.689975Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.691883Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.691718Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.690064Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(15, 19)"
+       "(4, 4)"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -689,25 +593,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 16,
    "id": "dcc5c91e-1ab4-4ee9-acad-a9a349de8793",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:48.017226Z",
-     "iopub.status.busy": "2024-06-12T02:00:48.017160Z",
-     "iopub.status.idle": "2024-06-12T02:00:48.019127Z",
-     "shell.execute_reply": "2024-06-12T02:00:48.018937Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:48.017219Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.692191Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.692136Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.694180Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.693986Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.692185Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "11.661903789690601"
+       "29.698484809834994"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -728,27 +632,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 17,
    "id": "05d78d6f-1f73-4718-b070-cc81e27154ec",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:48.019873Z",
-     "iopub.status.busy": "2024-06-12T02:00:48.019765Z",
-     "iopub.status.idle": "2024-06-12T02:00:48.021810Z",
-     "shell.execute_reply": "2024-06-12T02:00:48.021605Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:48.019866Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.694597Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.694529Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.696568Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.696373Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.694591Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "((14.866068747318506, (9, 10)),\n",
-       " (25.612496949731394, (15, 19)),\n",
-       " (3.1622776601683795, (0, 2)))"
+       "((2.8284271247461903, (1, 1)),\n",
+       " (4.242640687119285, (2, 2)),\n",
+       " (7.0710678118654755, (4, 4)))"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -770,201 +674,190 @@
     "\n",
     "* ***David Eppstein*** (2001). *Fast hierarchical clustering and other applications of dynamic closest pairs*. ACM J. Exp. Algorithmics 5 (2000), 1–es. doi: [10.1145/351827.351829](https://doi.org/10.1145/351827.351829)\n",
     "\n",
-    "### Create a fresh `FastPair` instance\n",
+    "### Explore the current state of the `fp` instance\n",
     "\n",
-    "4 2D points from a random seed of `101`."
+    "#### Query the closest pair"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
-   "id": "4da8f641-5732-4932-8d6e-c181bd7af500",
+   "execution_count": 18,
+   "id": "aa6bab3b-18d0-489e-9d56-2b1e215b8f36",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:48.022233Z",
-     "iopub.status.busy": "2024-06-12T02:00:48.022170Z",
-     "iopub.status.idle": "2024-06-12T02:00:48.025391Z",
-     "shell.execute_reply": "2024-06-12T02:00:48.025178Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:48.022225Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.696931Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.696865Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.699292Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.699068Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.696924Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<fastpair.base.FastPair at 0x1073c3b30>"
+       "(1.4142135623730951, ((1, 1), (2, 2)))"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "points = random_points(101, (2), 4)\n",
-    "fp = fastpair.FastPair()\n",
-    "fp.build(points)"
+    "dist, (a, b) = fp.closest_pair()\n",
+    "dist, (a, b)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "7ffc8ae9-59a2-44bb-81ad-72e0beb524be",
+   "id": "fae6b80b-34e5-4ce2-807f-144035befaf4",
    "metadata": {},
    "source": [
-    "Query the closest pair."
+    "Here we can verify the closest pair is `((1, 1), (2, 2))` at `≈1.414` units distance.\n",
+    "\n",
+    "#### Visualize\n",
+    "* 3 initial points in `\"cadetblue\"`\n",
+    "* Current closest pair in `\"red\"`"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
-   "id": "9382b0a5-e16f-4bf2-a537-cc442fd7c719",
+   "execution_count": 19,
+   "id": "62b69b65-7070-4667-a447-cc8f7b2a6396",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:48.025916Z",
-     "iopub.status.busy": "2024-06-12T02:00:48.025812Z",
-     "iopub.status.idle": "2024-06-12T02:00:48.027816Z",
-     "shell.execute_reply": "2024-06-12T02:00:48.027601Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:48.025909Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.699861Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.699640Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.786552Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.786306Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.699853Z"
     }
    },
    "outputs": [
     {
      "data": {
+      "image/png": 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Z27/+9a+jVatWm21/wQUXxD777BMREbW1tRtMuY6I7JKRiIiysrLtXmLw7rvvxp/+9KeIiOjYsWP86le/2mL7wsLC+PnPf569/ec//3mzde22227bVVMSvvSlL8WgQYM2e/+RRx4ZJ5xwQvb2jTfe+KnGa9WqVYwePToiIhYtWpRd7rIjXHLJJdGuXbsd1l99pPXr/mk9+eSTccstt0RExJgxY2LEiBEJV7Tj7LbbbnHJJZds9v4OHTrE5z//+eztfG4I29C/30466aRo2bJlREQ8/vjj9fqYnj17xoUXXrjZ+zt27LjB1+Pmm2+OTCbzqeqsu5lrfetM4vkFYEeyxwaQWh988MEGt9f/wplPzzzzTPZUjXbt2sVxxx23xfZNmjSJr3zlK9lfdMePH7/B/e3atYvmzZvHqlWr4pVXXolJkyZt174hjz/+eHb/jRNOOGGTe3l80mc+85lo0aJFrFy5MiZOnLjBfXX3nhg/fnzMnj07evXqtc115Vt91vSPHTs27rvvvojY+OuxKe+8804899xzMWPGjFi2bFmsXLlygxcidY8efvHFF2O//fbbjso3tj17HXxadb/u119/fVx33XV5ryHfqqur45xzzomIdeHiVVddlXBFO9Zxxx231eeD/v37xz333BMRUa+TWXaUut9v9913X3z/+9/P+9G6L730UkybNi3mzp0bK1as2OjUpPVh88svvxy1tbXRpMmW/0Z4+umnR1HRln/d/vKXvxzf+c53Yu3atVFRURGzZs3a5N5D61VVVcVzzz0XL7/8crz77rvxwQcfbLCv0cKFC7PX9T3GPInnF4AdSbABpNYuu+yywe31G6vl07Rp07LXAwcO3OovsBGxQVAxbdq0yGQy2V+Wi4uLY9SoUXHXXXfFmjVrYsSIEXHqqafGSSedFIcffni9Z6U8++yz2euXXnopzjvvvHp+Ruusf8HeokWLiFj3guOQQw6J5557Lt5///046KCD4owzzojRo0fH4MGDo7S0dJv6z4eCgoL4zGc+s9V2hx56aPZ6yZIlsWjRoujUqdNG7V577bW4+OKL45///OcmN0fdlB21oWbPnj2jbdu2O6SvbXHKKadkZy5cf/318fzzz8fYsWNj5MiR9dqUMI0uueSSePPNNyMi4sorr2x0f8WuT9BWVlaWva47iyLXDjnkkOjatWvMnz8/5s2bF/vss0+cddZZcdxxx8VnPvOZKC4uztnYt912W1x++eUxe/bserVfvXp1vP/++9GmTZsttqv7/LI5bdq0id69e2dneE2bNm2TwcZ7770Xl1xySdx+++0bBfubU5/noKSeXwB2JMEGkFq77rprFBUVZZejLF++PO81vPvuu9nr7t271+tjevTokb2uqamJDz74IHbdddfs+66++up4/vnn4/XXX4+ampq444474o477ogmTZrEPvvsE4cddlgcddRRccwxx2z21I31J7BEREycOHGjGRj1sWzZsmywEbFuivSIESNiyZIl8eGHH8Z1110X1113XRQVFUW/fv3i8MMPj5EjR8YRRxwRhYWF2zzejtamTZuNwq9NWX+6yapVqyJi3df0k8HGI488Escff/xGf73dmvq++KhPjUkYOXJknH/++XHttddGRMSUKVNiypQpEbFuycKQIUNi2LBhMWrUqOjSpUsiNe5Izz//fFx99dURETF8+PANpvQ3FltaKrde06ZNs9erV6/OZTkbjXvHHXfEscceGx9++GEsXbo0rrjiirjiiiuiefPmcfDBB8fhhx8en/vc52LQoEE75DSgTCYTZ599dtx6663b/LEffPDBVoONbt261auvbt26ZYONuv+vrPf222/H4Ycfnj3BZVtq3JqGuOwHYFvZYwNItbphwo7cz6C+6s4SqRsCbMkn233yF8+OHTvG1KlT40c/+lF06NAh+/7a2tp4+eWX4w9/+EOMHj06OnXqFL/85S83OXtg/ZGNn0bd/UsiIvr27RvTp0+P888/f4MXR2vWrImpU6fGb37zmxg5cmR07949brrppk89/qe1LbNI6n5NPvn1ePfdd+PUU0/Nhhrdu3ePX/ziFzFx4sSoqKiIqqqqqK2tjcy6Dbnjxz/+cfZja2trP+VnsU5JSckO6Wd7/O53v4v77rtvoyN4lyxZEn/729/i/PPPj27dusVJJ520zS+6GpqvfvWrsXbt2mjWrFlcf/31SZeTE7k6GnhHGTp0aEyfPj3GjBmzwff9qlWrYuLEiXH55ZfHkCFDory8PHsU76dx4403bhBqfPazn43bbrstXn755Vi2bFl89NFH2Z/tTCazwf859fn5ru/z0JaegyLWLWlZ//O1yy67xHe+853417/+FW+99VZ8+OGHsXbt2myNdZfU1afGJJ9fAHYUMzaAVBsyZEh22vh//vOfvI9fd1+PlStX1utjPtluU7MKdt111/jpT38al156aUydOjWefvrpmDRpUkycODE7tXjZsmXx/e9/P5577rn4+9//vsELlrq/JP/mN7+J73znO9v0eW1Ohw4d4ne/+11cccUV8dxzz8XTTz8dzzzzTEyaNCk7ZX3hwoXxta99LV566aX43e9+t0PG3R5VVVX1blv3a/LJr8eNN96YDYoOOOCA+Pe//73BDJtP2lGzNBqS0aNHx+jRo2PevHnx1FNPxTPPPBNPP/10NkzMZDLxt7/9LXtfGvZf2ZT1+xE0a9asXvuzrPfNb34z+z1x4IEHxh/+8IdclLdJOyo8a0j22GOPuO222+IPf/hDdsbZpEmT4rnnnovq6uqIiJg9e3aMHj06rrrqqviv//qv7R7ryiuvzF5fdtllW9xYNWLbf77r+zy0peegZ555Jp555pmIWPd/znPPPRd9+/bdYTUCNAZmbACpVve0grfffjv7y1++1J3CW9+/VtfdjK+4uHiLyyUKCwvjM5/5TPz3f/93/P3vf48lS5bE008/HV/4wheybR544IH429/+tsHH1Z3psXjx4nrVtS2aNWsWQ4cOjR/96Efxj3/8I5YuXRr//Oc/Y8iQIdk21157bXbZQhKWLVtWr31Xli5dml2GEhEb7anwxBNPZK9/9KMfbTHUiFj3fdhYdevWLcaMGRPXX399vPrqqzFv3ry47LLLsn+Vrqys/FQvMhuKFStWxH/+858tvtU1Y8aM7Ps/7cyxustAPjlralN2xOyshqpFixYxcuTI+OlPfxpPPvlkVFZWxr333rvBPiHf//73N9gsc1vMnz8/Xn/99YhYd6rW97///S22X7FiRSxbtmybxqjv/wvz58/PXm/pOWjs2LFbDDUiGvdzEMDmCDaAVDv55JM3+CXwN7/5TV7H79+/f/Z68uTJ9dpUsm740r9//22aGt6kSZMYMmRI3H///XHUUUdl3/9///d/G7Sru2nmpEmT6t3/9mratGl89rOfjccffzz23Xff7PsffPDBjdrmayp8JpOp1yyeuhutdujQITp37rzB/XX3K9naxotr167Ny+PdUHTt2jUuueSSDY4tfvTRR7d5LxL+n7rBWWVl5Vbbv/zyy7ks51PZ0T/rJSUlcdJJJ8VTTz2VDW9ramrikUce2a7+6v5sl5eXbxAqbcrEiRO3+SjW5557bqttli9fHjNnzszePvDAAzdbZ302f/33v/+9DRVum4a+lAnYeQk2gFQrKSmJb33rW9nbf/vb3zaavVAfK1eu3K7ZHoMGDcpu4Pnuu+/Gww8/vMX2tbW1G6znrjvjZFsUFBRscLTskiVLNrh/5MiR2RNannnmmZg+ffp2jbOtmjVrFkcfffRm64qIDY6azPXGhHfcccdW29x+++3Z6+HDh290f93jHLc2rfz+++/PyQyZhq7uDKLVq1fHe++9l2A126/uXgpbe6tr/Pjx2fc/9dRTn6qGupsLb+2ozqlTp8acOXM+1Xi5lKuf9bZt225wutSmnmfqY1t+tiNiu447vvPOO7caeP/5z3/OtunUqVP07t17u+usqKiIBx54YJvrrK98Pn8DbAvBBpB6F1100QZ/4TrjjDM2OVNgc1555ZU45JBD4tFHH93msVu3bh2nnnpq9vZ3v/vdLa5v/v3vf5/9C2uTJk3inHPO2eD+Dz74IGpqauo1dt2py+3bt9/gvt133z2+/OUvR8S6F2tjxoyp97GNtbW1G+3Kv2zZsnqv5d9SXREbHiW5vVPI6+tPf/rTFmdtjB8/foMg7Ktf/epGbfbYY4/s9SdnxtT17rvv7rC9TBqK+h5XW/dr3qRJkw2+xmyburOtbrvtts22W7NmTVxwwQX5KGm7tW7dOvui/N13393qC+H6zFBZb2vPM/XRs2fP7AyEV155Jd56663Ntr377rvjoYce2uYx3nzzzexJO5uyZMmS+MlPfpK9ffbZZ280K6K+z0Fr166Nc845p97/h2yPfD5/A2wLwQaQes2aNYt77703+8ttdXV1jBo1KsaMGRMzZszY5MdkMpmYMmVKjB07Ng444IB45ZVXtnv8Sy65JLuJ6OzZs2PkyJEb/YJcW1sb11xzzQb7D5x77rkb/HU2Yt1xkz169IhLL710s2v1165dG3fffXf2CM6IiGOOOWajdj//+c+zx5a+9NJLMXDgwC2GNwsWLIirr746evfuHXffffcG9z3wwAPRq1evuPLKKzfYI6Sujz76KH7/+9/HX//61y3WVXepygMPPJCzX8KbNm0aa9eujWOPPTYef/zxje5/+OGHY/To0dm/vh911FFxxBFHbNSu7syYX/ziF/GnP/1pozYvvPBCDB06NObPn1/v03HS4NBDD43TTz89/vnPf2726zR79uwYO3Zs9vYRRxwRxcXF+Sqx3oYNGxYFBQVRUFAQw4YNS7qczTr11FOzYcCzzz4b3/ve9zb6i/+CBQvi2GOPjWeeeWazRz43BM2aNYu99947Itb9dX9rp5hce+210a9fv7juuus2O/Ppww8/jB/+8IfZ/XsKCws3mCW2Ldq1axeHHHJIRKx7jj7ppJNi1qxZG7Spra2N//3f/40zzjgjCgsLN5ixUB/FxcVx8cUXxzXXXLNRODxjxow46qij4p133omIdUvhNhWOfv7zn8+GHU899VT893//d3YT1fUWL14cJ554Yjz88MM5fQ6q+/z9n//8p957iPTo0SP789cYj1EGkudUFKBR2GOPPeI///lPHHfccfHKK69EbW1t3HHHHXHHHXdEjx49Yv/994927drF2rVrY/HixfHiiy9uNH15S5t4bsmee+4ZN910U3zpS1+KtWvXxrPPPhu9e/eOww47LPbcc8/48MMP4+mnn97gr1uHHHJI/PrXv95kf4sWLYrLLrssLrvssujYsWP069cvOnbsGEVFRbFkyZJ4/vnnN1hzfdhhh8UXv/jFjfrp3LlzPPDAA/G5z30uli5dGrNmzYqRI0fG7rvvHgMHDozddtstVq9eHUuXLo1XXnllq1Pa33zzzfjud78b3/3ud6Nbt26x//77Z8OkxYsXx3PPPbfBEoQvfelLMWjQoI36OeaYY6KkpCSqq6vjxRdfjD59+sSwYcOidevW2V/ejz766O1+sVL38x89enT89re/jaOOOioOOOCA6NevX2QymXj++efj1Vdfzbbt1KlT3HjjjZvsZ+zYsXHVVVfF7Nmz46OPPoozzjgjLr/88jjggAOiefPm8corr8TUqVMjYt2pKSNHjtzs1zZtVq9eHXfeeWfceeedUVJSEvvvv3/sscceseuuu8ayZcvirbfeyn7uEeuWhtU9ZWJ7XX/99Rsdt/rJYOVzn/vcRgHK17/+9fj617/+qcdPUvfu3ePrX/969mSVX/3qV3HnnXfG4YcfHs2bN48333wzJk2aFDU1NXHkkUdGx44dNxm2NRQnnnhiXH755RGx7jlh3Lhxsddee22wn0Xd75np06fHN7/5zTj33HNjzz33jH333TfatWsXq1evjkWLFsUzzzyzwabA3/ve96Jr167bXd9Pf/rTOProo6O2tjamTZsW++23XwwePDj22GOP7HP3okWLImJdWHzDDTds0+acv/71r+Pb3/52fPvb344rr7wyhgwZEi1btozZs2fHxIkTs2FHUVFR3HLLLdG2bduN+igvL48zzjgju2zuqquuir/85S8xYMCAaN++fcydOzf+/e9/R01NTeyyyy5xxRVX5OznoGPHjjFo0KB45plnYtWqVXHAAQfEZz/72ejUqVM2kNtzzz3jG9/4Rk7GB9isDEAj8sEHH2R+8pOfZFq3bp2JiHq9HXDAAZm///3vm+xv7Nix2Xa33nrrFsd+8MEHMx06dNjqeKeddlpm5cqVm+zjueeeyxQVFdW79pNOOimzYsWKLdY1d+7czBFHHFHvPjt06JD517/+tUEf9957b6agoKBeH9+kSZPMN7/5zUxNTc1ma7ruuuu22N+Pf/zjLX5OmzNnzpxsH927d8/U1NRkzj777C3W27t378yMGTO22O+sWbMye+yxxxb7GTx4cGbBggWZH//4x1v9PG699dZsm7Fjx26yzfjx47Nthg4dul2Px9YMHTo0O8b48eM3un/fffet9/dNz549M5MmTdohddV9DLflbUvfN3U/1x3xeNYdd1OP3adRXV2d+dznPrfFz/XYY4/NLFu2rF7PUdvyPJbJ1O/7sz5tMplMZvny5Zny8vItfi7rXXnllfX+WhcXF2cuu+yyrX4u9XHddddt8Xm3SZMmmUsuuSRTW1ub6d69e/b9c+bM2WR/n2xz3XXXZYqLizfbf+vWrTP33XffFmtcuXJl5uijj97iY9KlS5fMxIkT6/Xc8WmeX6ZMmZLZZZddNlvHpvqr+5hs6fsFYHuZsQE0Ki1btoz/+Z//iW9961vxj3/8Ix577LF4/vnn45133on33nsviouLo23btlFeXh6f+cxnYtSoURvtQL+9jj322HjjjTfilltuiYceeiheffXVWLp0aZSUlETnzp1j+PDhMWbMmA3W0H/SZz7zmXjnnXfi8ccfj4kTJ8a0adPizTffjMrKyli7dm3suuuuseeee8YhhxwSX/7yl2PgwIFbrat79+7x+OOPx7PPPhv33ntv/Pvf/4758+fHsmXLoqioKMrKymLvvfeOgw8+OI4++ugYNmxYduPR9U466aRYtGhRPProozFp0qSYPn16vPXWW7F8+fKIiGjVqlX06tUrhgwZEmPGjNnqcYRf//rXY7/99os//vGP8Z///CcWLlwYVVVV23ziwNY0bdo0brrppjj55JPj5ptvjilTpsSiRYuiRYsW0adPnzj11FPjnHPO2ep0/l69esW0adPif//3f+O+++6LWbNmRU1NTXTs2DH222+/OP300+OUU06JwsLCHVp/0l588cV47rnnYvz48TF58uSYNWtWVFRURFVVVZSWlmZnFH3hC1+IU045pUEvi0iT5s2bx0MPPRR33nln3HbbbfHCCy/E+++/H+3bt48DDjggzjzzzDjppJNScUJFq1atYsqUKfGHP/whHn744ZgxY0YsX758k/ttXHjhhXHiiSfGY489Fs8880y8/PLLMXfu3FixYkU0adIkWrduHX369IkRI0bEmDFjonv37jukxq9//esxePDguPrqq2P8+PFRUVERJSUlsfvuu8eIESPiK1/5ygYnYG1P/4cddlhcf/318fjjj8eCBQsiYt3yjOOOOy7OP//87LLBzSktLY1//vOf8Ze//CVuu+22mDZtWqxYsSLatWsXe+yxR5x44olx5plnRps2bT71BrZbc/DBB8dLL70U1157bYwfPz7eeuut+PDDD+t1KhhArhRkdvRvkQCQkLlz50bPnj0jYl2gs7n9QABypUePHtnlKnPmzNloLyUAdjybhwIAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1cnrca33PVx86dGjOz9wGAAAAGh8zNgAAAIDUKsrHIN/4xjfim9/85mbvb9GiRT7KAAAAABqZvAQb7du3j3333TcfQwEAAAA7EUtRAAAAgNQSbAAAAACpJdgAAAAAUisvx7327ds3MplMzJ07NwoLC6Njx44xaNCgOPPMM2P48OHb3f+CBQu2eP+qVati5syZ0aFDh9htt92iqCgvW4oAAADATmXNmjXx7rvvRkTEfvvtF82bN8/b2HkJNrZk1KhRMW7cuGjVqlVO+gcAAADyZ/LkyTFgwIC8jZfTKQylpaXxhS98IY444ogoLy+Pli1bxrvvvhsTJkyI66+/PiorK+P++++P448/Ph577LFo2rRpLssBAAAAGpmczthYvnx5tG7depP3LVmyJI455piYNm1aRERcc8018a1vfWub+t/aUpT58+fHoEGDImJdYtSpU6dt6h8AAADYukWLFsXAgQMjImLOnDnRo0ePvI2d02Bja956660oLy+P1atXx1577RWvv/76Du1/wYIF0bVr14hYF3J06dJlh/YPAAAAJPv6O9FTUfbYY4846qijIiLijTfeiIqKiiTLAQAAAFIm8eNe+/btm71euHBhgpUAAAAAaZN4sOFkEwAAAGB7JR5svPbaa9nrzp07J1gJAAAAkDaJBhtz5syJxx57LCIi9txzz9h9992TLAcAAABImZwFGw8++GCsWbNms/cvWbIkTjzxxKipqYmIiG9+85u5KgUAAABopIpy1fH5558fq1evjhNPPDEOPfTQ6NGjR5SUlMTSpUvjqaeeij/+8Y+xdOnSiIgYMmRInHvuubkqBQAAAGikchZsRERUVFTEtddeG9dee+1m25x44olx0003RbNmzXJZCgAAANAI5SzYuO2222LChAnx7LPPxltvvRVLly6NFStWRMuWLaNr164xaNCgGDt2bBx66KG5KgEAAABo5HIWbAwdOjSGDh2aq+4BAAAAkj/uFQAAAGB7CTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSqyjpAgAAABqiTCYTy6uqYm5lZcytfC/mVlbGeytXxuo1a2P12rWxprY2ipo0iaaFhdG0qDDatmgRPcrKokdZ2+jRrl20KS1N+lOAnYJgAwAA4GMVy9+PyXPmxJyllTGncmmsqF5V74+d/96ymD5/QfZ2q5KS6FFWFj3blcXAnj2jc+tWuSgZdnqCDQAAYKe2prY2ps2bF0/OmBUzFi/eYf2+X10d0xcsiOkLFsT9L06PPp06xojy8ujfrWsUNbErAOwogg0AAGCntGzlynhq9usxYdbsWF5dnfPxZixaHDMWLY7WpSUxrFevGNq7l+UqsAMINgAAgJ1KdU1N3DP1+Zgw+/WozWTyPv7yquq4/8Xp8X/TX4qhvfaOUwYcHCVNm+a9DmgsBBsAAMBO49WKirhl4jNRuXJl0qVEbSYT42fNjpcWLIyvDBkU+3TunHRJkEqCDQAAoNGrrqmJu6c8H0/Nnp10KRupXLkyrnjksRjWu1ecavYGbDPBBgAA0Kg1pFkaW/LUrNnxstkbsM1sxQsAADRa/3zl1bjikccafKix3vrZG/985dWkS4HUMGMDAABodDKZTNz3wrR48KWXky5lu9w9ZWpU1dTECf37RUFBQdLlQINmxgYAANCoZDKZ+MvkKakNNdZ7cPpL8ZfJUyKTwMktkCaCDQAAoFG574Vp8dhrM5IuY4d47LUZcd+0F5MuAxo0wQYAANBo/POVV1M/U+OTHpz+kj03YAsEGwAAQKPwakVF3D1latJl5MTdU6bGaxWLki4DGiTBBgAAkHrVNTVxy8Rnki4jp26eNCmqV69OugxocAQbAABA6t099fnUHOm6vSo/XBn3NNIZKfBpCDYAAIBUe7WiIp6aNTvpMvJi/KzZlqTAJwg2AACA1NoZlqB8kiUpsCHBBgAAkFr37ARLUD6p8sOVce/U55MuAxoMwQYAAJBKy6qqYsLs15MuIxETZs2OZVVVSZcBDYJgAwAASKUJs2ZHbSaTdBmJWJvJxL930lAHPkmwAQAApM6a2tp4avbOsWHo5oyfNSvW1NYmXQYkTrABAACkzrR582N5VXXSZSRqeVV1vDhvftJlQOIEGwAAQOo8OXNm0iU0CE/OnJV0CZA4wQYAAJAqFcuXx4xFi5Muo0F4bdGiqFj+ftJlQKIEGwAAQKpMnjM36RIalMlz5iRdAiQqsWDj4osvjoKCguzbU089lVQpAABAisxZWpl0CQ3KnEqPBzu3RIKNF198MX7zm98kMTQAAJBimUwm5nohv4G3BT3s5PIebNTW1sY555wTa9asifbt2+d7eAAAIMWWV1XF+9U792kon7S8ujqWVVUlXQYkJu/Bxu9+97uYMmVKlJeXx9lnn53v4QEAgBQzW2PT5pq1wU4sr8HGvHnz4n/+538iIuL666+P4uLifA4PAACk3NzK95IuoUES+LAzy2uwce6558aHH34YY8eOjaFDh+ZzaAAAoBHwAn7TPC7szPIWbNxzzz3x0EMPRdu2bePKK6/M17AAAEAj8t7KlUmX0CB5XNiZFeVjkOXLl8cFF1wQERG/+tWvol27djuk3wULFmzx/kWLFu2QcQAAgIZh9Zq1SZfQIK1e63Fh55WXYOOiiy6KxYsXx+DBg3fohqFdu3bdYX0BAAANnxfwm+ZxYWeW86UoTz/9dNx0001RVFQU119/fRQUFOR6SAAAoJFaU1ubdAkN0pq1Hhd2XjmdsVFTUxPnnHNOZDKZ+M53vhP77rvvDu1//vz5W7x/0aJFMXDgwB06JgAAkJyiJnk9/yA1igo9Luy8chpsXH755TFz5szo1q1b/PjHP97h/Xfp0mWH9wkAADRcTQsLky6hQfK4sDPLWaw3c+bM+MUvfhEREddee220aNEiV0MBAAA7iaZFXsBvimCDnVnOZmxcffXVUVNTE3vssUdUVVXFXXfdtVGbV155JXv95JNPxuLFiyMi4rjjjhOEAAAAG2nbokXMf29Z0mU0OG29fmInlrNg46OPPoqIiLfeeitOO+20rbb/6U9/mr2eM2eOYAMAANhIj7KymD5/QdJlNDg9ysqSLgESY4cZAAAgNXqUtU26hAZJsMHOLGfBxrhx4yKTyWzxre6GouPHj8++v0ePHrkqCwAASDEv4DetRzuPCzsvMzYAAIDUaF1aGq1KSpIuo0FpXVISbUpLky4DEiPYAAAAUqOgoMCsjU/obrYGOznBBgAAkCo9vZDfQE9BDzs5wQYAAJAqA3v2TLqEBuUze3g82LklGmxceuml2Q1Dhw0blmQpAABASnRu3Sr6dOqYdBkNQt9OnaJTq1ZJlwGJMmMDAABInRHl5UmX0CCMKO+ddAmQOMEGAACQOv27dY3WpTv36SitS0uif7euSZcBiRNsAAAAqVPUpEkM69Ur6TISNbx37yhs4iUd+CkAAABSaWjvXtGkoCDpMhJRWFAQh/faO+kyoEEQbAAAAKnUprQ0hu6kL+6H9u4VbUpLky4DGgTBBgAAkFqnHHxQlLVokXQZeVXWskWcfPBBSZcBDYZgAwAASK2S4uL4ypBBSZeRV2cPHhwlTZsmXQY0GIINAAAg1fbp3DmG9d45NhId3rtX9O3cKekyoEERbAAAAKl36k6wJKWsZYs4ZcDBSZcBDY5gAwAASL2dYUmKJSiwaYINAACgUdinc+c4tZHOaPjigIMtQYHNEGwAAACNxjH77hPH7b9f0mXsUMcdsH98dt99ki4DGizBBgAA0KiccGD/OKpvn6TL2CGO6tsnTujfL+kyoEErSroAAACAHamgoCBOHzggmjdtGg9OfynpcrbbFw7YP0b37xcFBQVJlwINmmADAABodAoKCuLEA/tHaXFx3D1latLlbLNTBxwcx1h+AvUi2AAAABqtY/bdJ7q3bRs3T5wUlStXJl3OVpW1bBFnDx5so1DYBvbYAAAAGrW+nTvFz0YfH8N690q6lC0a3rtX/GzU8UIN2EZmbAAAAI1eSdOmceagQ2NAj+5xy8RnGtTsDbM04NMxYwMAANhp7NO5c/xs9PExorx3NEl4U87CgoIYUd7bLA34lMzYAAAAdiolTZvGmEMPieMO2D8mzJodT82eHcurqvM2fuvSkhjeu3cc3mvvaFNamrdxobESbAAAADulNqWlMap/vzj2gP1j2rz58eTMmTFj0eKcjde3U6cYUd47+nXrGkVNTJ6HHUWwAQAA7NSKmjSJAT26x4Ae3aNi+fsxec6cmFNZGXOXVsb71ds/k6N1SUl0b1cWPcvKYmDPntG5dasdWDWwnmADAADgY51bt4pR/ftlby+rqoq5SytjbuW6t/dWrozVa9fG6rVrY83a2igqbBJNCwujaWFhtG3RInqUla17a1dmmQnkiWADAABgM9qUlkabbqXRv1vXpEsBNsPCLgAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUqsoVx2vWLEi/vGPf8SUKVNi6tSpsXDhwnj33Xejuro6WrduHX379o3Pfe5zcfbZZ0dZWVmuygAAAAAasYJMJpPJRcePP/54HHXUUVtt165du/jTn/4UI0eO3OE1LFiwILp27RoREfPnz48uXbrs8DEAAABgZ5fk6++czdiIiOjatWsMHz48DjrooOjatWt06tQpamtrY8GCBfHXv/417rvvvli6dGl84QtfiMmTJ8cBBxyQy3IAAACARiZnwcbw4cNj3rx5m73/lFNOifvvvz9Gjx4dNTU1cdlll8V9992Xq3IAAACARihnm4cWFhZutc2oUaOid+/eERHx9NNP56oUAAAAoJFK/FSUXXbZJSIiVq1alXAlAAAAQNokGmzMmjUrXnzxxYiIKC8vT7IUAAAAIIXyHmxUVVXF66+/Hr/5zW9i6NChsWbNmoiI+Pa3v53vUgAAAICUy+mpKOuNGzcuzjrrrM3e/73vfS9OP/30be53wYIFW7x/0aJF29wnAAAAkB55CTY2p1+/fnHDDTfEgAEDtuvj15+RCwAAAOyc8rIUZdSoUfHyyy/Hyy+/HJMnT44777wzRo8eHS+++GKcdtpp8dBDD+WjDAAAAKCRKchkMpmkBr/jjjti7NixUVBQEDfffHOceeaZ2/Tx9VmKMnDgwIiImD9/fnTp0mV7SwUAAAA2Y8GCBdlVFfl+/Z1osBERceqpp8Y999wTLVq0iHnz5kXbtm13WN9JPrAAAACws0jy9Xeix71GRBx//PEREbFy5cr417/+lXA1AAAAQJokHmzstttu2eu33347wUoAAACAtEk82Fi4cGH2umXLlglWAgAAAKRN4sHGvffem73eb7/9EqwEAAAASJucBRvjxo2LVatWbbHN1VdfHf/4xz8iIqJnz55x2GGH5aocAAAAoBEqylXHl156aVx44YVx4oknxpAhQ2LPPfeMli1bxgcffBAvv/xy/PnPf45JkyZFRERxcXHccMMNUVhYmKtyAAAAgEYoZ8FGRMR7770XN954Y9x4442bbdOlS5e45ZZb4sgjj8xlKQAAAEAjlLNg45FHHomHH344Jk2aFG+88UYsWbIkKisro6SkJNq3bx/9+vWLY489Nk455ZQoLS3NVRkAAABAI5azYKN3797Ru3fv+K//+q9cDQEAAADs5BI/FQUAAABgewk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKRWUdIFAEA+ZTKZWF5VFXMrK2Nu5Xsxt7Iy3lu5MlavWRur166NNbW1UdSkSTQtLIymRYXRtkWL6FFWFj3K2kaPdu2iTWlp0p8CAAB1CDYAaPQqlr8fk+fMiTlLK2NO5dJYUb2q3h87/71lMX3+guztViUl0aOsLHq2K4uBPXtG59atclEyAAD1JNgAoFFaU1sb0+bNiydnzIoZixfvsH7fr66O6QsWxPQFC+L+F6dHn04dY0R5efTv1jWKmljhCQCQb4INABqVZStXxlOzX48Js2bH8urqnI83Y9HimLFocbQuLYlhvXrF0N69LFcBAMgjwQYAjUJ1TU3cM/X5mDD79ajNZPI+/vKq6rj/xenxf9NfiqG99o5TBhwcJU2b5r0OAICdjWADgNR7taIibpn4TFSuXJl0KVGbycT4WbPjpQUL4ytDBsU+nTsnXRIAQKMm2AAgtaprauLuKc/HU7NnJ13KRipXrowrHnkshvXuFaeavQEAkDOCDQBSqSHN0tiSp2bNjpfN3gAAyBnbtwOQOv985dW44pHHGnyosd762Rv/fOXVpEsBAGh0zNgAIDUymUzc98K0ePCll5MuZbvcPWVqVNXUxAn9+0VBQUHS5QAANApmbACQCplMJv4yeUpqQ431Hpz+Uvxl8pTIJHByCwBAYyTYACAV7nthWjz22oyky9ghHnttRtw37cWkywAAaBQEGwA0eP985dXUz9T4pAenv2TPDQCAHUCwAUCD9mpFRdw9ZWrSZeTE3VOmxmsVi5IuAwAg1QQbADRY1TU1ccvEZ5IuI6dunjQpqlevTroMAIDUEmwA0GDdPfX51Bzpur0qP1wZ9zTSGSkAAPkg2ACgQXq1oiKemjU76TLyYvys2ZakAABsJ8EGAA3OzrAE5ZMsSQEA2D6CDQAanHt2giUon1T54cq4d+rzSZcBAJA6gg0AGpRlVVUxYfbrSZeRiAmzZseyqqqkywAASBXBBgANyoRZs6M2k0m6jESszWTi3ztpqAMAsL0EGwA0GGtqa+Op2TvHhqGbM37WrFhTW5t0GQAAqSHYAKDBmDZvfiyvqk66jEQtr6qOF+fNT7oMAIDUEGwA0GA8OXNm0iU0CE/OnJV0CQAAqSHYAKBBqFi+PGYsWpx0GQ3Ca4sWRcXy95MuAwAgFXIabEydOjV+8pOfxNFHHx1dunSJZs2aRcuWLaNXr15x1llnxcSJE3M5PAApMnnO3ETHr6mujuULF8a7b70VyxcujJrqZJfETJ4zJ9HxAQDSoihXHR9++OHx9NNPb/T+mpqaeP311+P111+PcePGxZgxY+LGG2+M4uLiXJUCQArMWVqZ9zEzmUwsnjkzZj35RMyb9kJk6mzaWdCkSXQ78MDoPfyI6FheHgUFBXmtbU5l/h8PAIA0ylmwUVFRERERnTt3jpNPPjkOO+yw6NatW6xduzaeffbZuOqqq2LhwoVx++23x+rVq+Mvf/lLrkoBoIHLZDIxN88v5CvfnhsTb7oxli9cuOmaamvj7alT4+2pU6P17rvHkK9+Lcq698hbfW8nEPQAAKRRzoKN8vLyuPzyy+PEE0+MwsLCDe475JBD4owzzojBgwfH7Nmz484774yvf/3rcfjhh+eqHAAasOVVVfF+Hpd+VLz6Soz//bWx5qOPsu/rEBFHR0SriHg/Ih6NiCXr61u4MP71y1/E8PPOj8777JuXGpdXV8eyqqpoU1qal/EAANIqZ3tsPPTQQ3HKKadsFGqs165du7jqqquyt//617/mqhQAGrh8ztaofHvuBqFG/4i4OyLmRcTtEXHtx//Oi4i7Pr4/ImLNRx/F+N9fG5Vvz81brXPN2gAA2KpET0UZPnx49vrNN99MsBIAkjS38r28jJPJZGLiTTdmQ41REfFMRJwSEZ/c6ak4Ik79+P7jP37fmo8+iok33RSZTCYv9eZ7eQ4AQBolGmx8VGcK8OZmdgDQ+OXrBfzimTOze2r0j4g7I6L5Vj6meWw4c2P5wgWxZNbMnNVYl2ADAGDrEg02JkyYkL3u06dPgpUAkKT3Vq7Myzizxj+Rvb44th5qrNc8Ii6qc3vmk0/uwKo2L1+PCwBAmuVs89Ctqa2tjV/+8pfZ26eccso297FgwYIt3r9o0aJt7hOA/Fu9Zm3Ox6ipro55L7wQEes2Ch29jR9/QkS0j4h3ImLeC89HTXV1FJeU7NgiP2H12tw/LgAAaZdYsHH11VfH5MmTIyLihBNOiIMOOmib++jateuOLguABOTjBXzVe+9FprY2ItadfvLJPTW2pjgiRkbEHbHuKNiqZcsEGwAADUAiS1EmTJgQ3/ve9yIion379nHdddclUQYADcSajwOHXFpdZ1+nVtvZx651+1u16lPVUx9r1ub+cQEASLu8z9h49dVXY/To0bFmzZpo3rx53HvvvdG+ffvt6mv+/PlbvH/RokUxcODA7eobgPwpapL7nL1ps2bZ6/e3s48VdftrXt8dOrZfUWGiW2EBAKRCXoONOXPmxNFHHx3Lli2LwsLCuOuuu+Lwww/f7v66dOmyA6sDIClN83AyVmnbtlHQpElkamvj0YioiW1bjlITEY98fF1QWBilbdrs8Bo/KR+PCwBA2uXtT0EVFRVx5JFHRkVFRRQUFMQtt9wSxx9/fL6GB6ABa1qU+xfwxSUl0e3AAyMiYklE/H0bP/6+WLdxaEREt/4H5nx/jQjBBgBAfeQl2Fi6dGkcddRR8dZbb0VExLXXXhtjxozJx9AApEDbFi3yMk7v4Udkr38VEfXdJaM6In5d53b5iBE7sKrNy9fjAgCQZjkPNt5///0YOXJkvPbaaxER8ctf/jLOPffcXA8LQIr0KCvLyzgdy8uj9e67R0TEtIj4Ymw93FgVEad93D4iovXuXaJD7/Kc1VhXvh4XAIA0y2mwUVVVFZ///OfjhRdeiIiIH/7wh3HxxRfnckgAUqhHWdu8jFNQUBBDvvq1KPp4I9EHImJQRNwd6/bQqKsmIu76+P4HPn5fUbNmMeSrX42CgoK81CvYAADYupwFGzU1NTF69OiYNGlSRERccMEF8bOf/SxXwwGQYvl8AV/WvUcMP+/8bLixfuZGt4gYExHnffxv19hwpkZRs2Yx/Lzzo6x7j7zV2qOdYAMAYGtydirKaaedFo8++mhERIwYMSLOPvvseOWVVzbbvri4OHr16pWrcgBowFqXlkarkpJ4v7o6L+N13mff+Oz3vh8Tb7oxli9cGBHrNhS9Y3P17d4lhnz1q3kNNVqXlESb0tK8jQcAkFY5Czbuu+++7PWTTz4Z+++//xbbd+/ePebOnZurcgBowAoKCqJHWVlMX7Agb2OWde8RX/jJz2LJrJkx88knYt4LL0Smtvb/1VRYGN36HxjlI0ZEh97leVt+sl53szUAAOolZ8EGAGyLnu3yG2xErAtUOpb3iY7lfaKmujqqli2L1atWRdPmzaO0TZu8HOm6OT3trwEAUC85CzYymUyuugagERrYs2fc/+L0xMYvLilJNMj4pM/s0TPpEgAAUiHnx70CQH10bt0q+nTqmHQZDULfTp2iU6tWSZcBAJAKgg0AGowR5eVJl9AgjCjvnXQJAACpIdgAoMHo361rtC5tOMtBktC6tCT6d+uadBkAAKkh2ACgwShq0iSG7eRHfw/v3TsKm/jvGQCgvvzmBECDMrR3r2iS56NVG4rCgoI4vNfeSZcBAJAqgg0AGpQ2paUxdCd9cT+0d69oU1qadBkAAKki2ACgwTnl4IOirEWLpMvIq7KWLeLkgw9KugwAgNQRbADQ4JQUF8dXhgxKuoy8Onvw4Chp2jTpMgAAUkewAUCDtE/nzjGs986xkejw3r2ib+dOSZcBAJBKgg0AGqxTd4IlKWUtW8QpAw5OugwAgNQSbADQYO0MS1IsQQEA+HQEGwA0aPt07hynNtIZDV8ccLAlKAAAn5JgA4AG75h994nj9t8v6TJ2qOMO2D8+u+8+SZcBAJB6gg0AUuGEA/vHUX37JF3GDnFU3z5xQv9+SZcBANAoFCVdAADUR0FBQZw+cEA0b9o0Hpz+UtLlbLcvHLB/jO7fLwoKCpIuBQCgURBsAJAaBQUFceKB/aO0uDjunjI16XK22akDDo5jLD8BANihBBsApM4x++4T3du2jZsnTorKlSuTLmerylq2iLMHD7ZRKABADthjA4BU6tu5U/xs9PExrHevpEvZouG9e8XPRh0v1AAAyBEzNgBIrZKmTePMQYfGgB7d45aJzzSo2RtmaQAA5IcZGwCk3j6dO8fPRh8fI8p7R5OEN+UsLCiIEeW9zdIAAMgTMzYAaBRKmjaNMYceEscdsH9MmDU7npo9O5ZXVedt/NalJTG8d+84vNfe0aa0NG/jAgDs7AQbADQqbUpLY1T/fnHsAfvHtHnz48mZM2PGosU5G69vp04xorx39OvWNYqamAgJAJBvgg0AGqWiJk1iQI/uMaBH96hY/n5MnjMn5lRWxtyllfF+9fbP5GhdUhLd25VFz7KyGNizZ3Ru3WoHVg0AwLYSbADQ6HVu3SpG9e+Xvb2sqirmLq2MuZXr3t5buTJWr10bq9eujTVra6OosEk0LSyMpoWF0bZFi+hRVrburV2ZZSYAAA2MYAOAnU6b0tJo0600+nfrmnQpAAB8ShYDAwAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEgtwQYAAACQWoINAAAAILUEGwAAAEBqCTYAAACA1BJsAAAAAKkl2AAAAABSS7ABAAAApJZgAwAAAEitoqQLAHInk8nE8qqqmFtZGXMr34u5lZXx3sqVsXrN2li9dm2sqa2NoiZNomlhYTQtKoy2LVpEj7Ky6FHWNnq0axdtSkuT/hQAAAC2SLABjUzF8vdj8pw5MWdpZcypXBorqlfV+2Pnv7csps9fkL3dqqQkepSVRc92ZTGwZ8/o3LpVLkoGAADYboINaATW1NbGtHnz4skZs2LG4sU7rN/3q6tj+oIFMX3Bgrj/xenRp1PHGFFeHv27dY2iJlayAQAAyRNsQIotW7kynpr9ekyYNTuWV1fnfLwZixbHjEWLo3VpSQzr1SuG9u5luQoAAJAowQakUHVNTdwz9fmYMPv1qM1k8j7+8qrquP/F6fF/01+Kob32jlMGHBwlTZvmvQ4AAADBBqTMqxUVccvEZ6Jy5cqkS4naTCbGz5odLy1YGF8ZMij26dw56ZIAAICdjGADUqK6pibunvJ8PDV7dtKlbKRy5cq44pHHYljvXnGq2RsAAEAeCTYgBRrSLI0teWrW7HjZ7A0AACCPHGsADdw/X3k1rnjksQYfaqy3fvbGP195NelSAACAnYAZG9BAZTKZuO+FafHgSy8nXcp2uXvK1KiqqYkT+veLgoKCpMsBAAAaKTM2oAHKZDLxl8lTUhtqrPfg9JfiL5OnRCaBk1sAAICdg2ADGqD7XpgWj702I+kydojHXpsR9017MekyAACARkqwAQ3MP195NfUzNT7pwekv2XMDAADICcEGNCCvVlTE3VOmJl1GTtw9ZWq8VrEo6TIAAIBGRrABDUR1TU3cMvGZpMvIqZsnTYrq1auTLgMAAGhEBBvQQNw99fnUHOm6vSo/XBn3NNIZKQAAQDIEG9AAvFpREU/Nmp10GXkxftZsS1IAAIAdRrABCdsZlqB8kiUpAADAjiLYgITdsxMsQfmkyg9Xxr1Tn0+6DAAAoBEQbECCllVVxYTZryddRiImzJody6qqki4DAABIOcEGJGjCrNlRm8kkXUYi1mYy8e+dNNQBAAB2HMEGJGRNbW08NXvn2DB0c8bPmhVramuTLgMAAEgxwQYkZNq8+bG8qjrpMhK1vKo6Xpw3P+kyAACAFBNsQEKenDkz6RIahCdnzkq6BAAAIMUEG5CAiuXLY8aixUmX0SC8tmhRVCx/P+kyAACAlMppsPHOO+/EQw89FJdcckkcc8wx0a5duygoKIiCgoI488wzczk0NGiT58xNdPya6upYvnBhvPvWW7F84cKoqU52SczkOXMSHR8AAEivolx23qFDh1x2D6k1Z2ll3sfMZDKxeObMmPXkEzFv2guRqbNpZ0GTJtHtwAOj9/AjomN5eRQUFOS1tjmV+X88AACAxiGnwUZd3bp1i/Ly8nj00UfzNSQ0SJlMJubm+YV85dtzY+JNN8byhQs3XVNtbbw9dWq8PXVqtN599xjy1a9FWfceeavv7QSCHgAAoHHIabBxySWXxIABA2LAgAHRoUOHmDt3bvTs2TOXQ0KDt7yqKt7P49KPildfifG/vzbWfPRR9n0dIuLoiGgVEe9HxKMRsWR9fQsXxr9++YsYft750XmfffNS4/Lq6lhWVRVtSkvzMh4AANB45DTYuOyyy3LZPaRSPmdrVL49d4NQo39EfC8iRkVEcZ12NRHx94j4VURMi4g1H30U439/bXz2e9/P28yNuUsro003wQYAALBtnIoCeTa38r28jJPJZGLiTTdmQ41REfFMRJwSG4Ya8fHtUz++//iP37fmo49i4k03RSaTyUu9+V6eAwAANA6CDcizfL2AXzxzZnZPjf4RcWdENN/KxzSPiLs+bh8RsXzhglgya2bOaqxLsAEAAGwPwQbk2XsrV+ZlnFnjn8heXxxbDzXWax4RF9W5PfPJJ3dgVZuXr8cFAABoXPJ2KkouLFiwYIv3L1q0KE+VQP2tXrM252PUVFfHvBdeiIh1G4WO3saPPyEi2kfEOxEx74Xno6a6OopLSnZskZ+wem3uHxcAAKDxSXWw0bVr16RLgG2WjxfwVe+9F5na2ohYd/rJJ/fU2JriiBgZEXfEuqNgq5YtE2wAAAANkqUokGdrPg4ccml1naNdW21nH7vW7W/Vqk9VT32sWZv7xwUAAGh8Uj1jY/78+Vu8f9GiRTFw4MA8VQP1U9Qk93li02bNstfvb2cfK+r217y+O3Rsv6JCOSsAALDtUh1sdOnSJekSYJs1LSzM+RilbdtGQZMmkamtjUcjoia2bTlKTUQ88vF1QWFhlLZps8Nr/KR8PC4AAEDj40+kkGdNi3L/Ar64pCS6HXhgREQsiYi/b+PH3xfrNg6NiOjW/8Cc768RIdgAAAC2j2AD8qxtixZ5Gaf38COy17+KiPruklEdEb+uc7t8xIgdWNXm5etxAQAAGhfBBuRZj7KyvIzTsbw8Wu++e0RETIuIL8bWw41VEXHax+0jIlrv3iU69C7PWY115etxAQAAGhfBBuRZj7K2eRmnoKAghnz1a1H08UaiD0TEoIi4O9btoVFXTUTc9fH9D3z8vqJmzWLIV78aBQUFealXsAEAAGwPwQbkWT5fwJd17xHDzzs/G26sn7nRLSLGRMR5H//bNTacqVHUrFkMP+/8KOveI2+19mgn2AAAALZdTk9FmThxYrzxxhvZ20uXLs1ev/HGGzFu3LgN2p955pm5LAcahNalpdGqpCTer67Oy3id99k3Pvu978fEm26M5QsXRsS6DUXv2Fx9u3eJIV/9al5DjdYlJdGmtDRv4wEAAI1HToONm266KW677bZN3jdp0qSYNGnSBu8TbLAzKCgoiB5lZTF9wYK8jVnWvUd84Sc/iyWzZsbMJ5+IeS+8EJna2v9XU2FhdOt/YJSPGBEdepfnbfnJet3N1gAAALZTToMNYNN6tstvsBGxLlDpWN4nOpb3iZrq6qhatixWr1oVTZs3j9I2bfJypOvm9LS/BgAAsJ1yusfGuHHjIpPJ1PsNdhYDe/ZMdPzikpJo3blz7LbHHtG6c+dEQ42IiM/skezjAQAApJfNQyEBnVu3ij6dOiZdRoPQt1On6NSqVdJlAAAAKSXYgISMKC9PuoQGYUR576RLAAAAUkywAQnp361rtC5NdglI0lqXlkT/bl2TLgMAAEgxwQYkpKhJkxjWq1fSZSRqeO/eUdjE0xAAALD9vKKABA3t3Sua5Plo1YaisKAgDu+1d9JlAAAAKSfYgAS1KS2NoTvpi/uhvXtFm9LSpMsAAABSTrABCTvl4IOirEWLpMvIq7KWLeLkgw9KugwAAKAREGxAwkqKi+MrQwYlXUZenT14cJQ0bZp0GQAAQCMg2IAGYJ/OnWNY751jI9HhvXtF386dki4DAABoJAQb0ECcuhMsSSlr2SJOGXBw0mUAAACNiGADGoidYUmKJSgAAMCOJtiABmSfzp3j1EY6o+GLAw62BAUAANjhBBvQwByz7z5x3P77JV3GDnXcAfvHZ/fdJ+kyAACARkiwAQ3QCQf2j6P69km6jB3iqL594oT+/ZIuAwAAaKSKki4A2FhBQUGcPnBANG/aNB6c/lLS5Wy3Lxywf4zu3y8KCgqSLgUAAGikBBvQQBUUFMSJB/aP0uLiuHvK1KTL2WanDjg4jrH8BAAAyDHBBjRwx+y7T3Rv2zZunjgpKleuTLqcrSpr2SLOHjzYRqEAAEBe2GMDUqBv507xs9HHx7DevZIuZYuG9+4VPxt1vFADAADIGzM2ICVKmjaNMwcdGgN6dI9bJj7ToGZvmKUBAAAkxYwNSJl9OneOn40+PkaU944mCW/KWVhQECPKe5ulAQAAJMaMDUihkqZNY8yhh8RxB+wfE2bNjqdmz47lVdV5G791aUkM7907Du+1d7QpLc3buAAAAJ8k2IAUa1NaGqP694tjD9g/ps2bH0/OnBkzFi3O2Xh9O3WKEeW9o1+3rlHUxIQvAAAgeYINaASKmjSJAT26x4Ae3aNi+fsxec6cmFNZGXOXVsb71ds/k6N1SUl0b1cWPcvKYmDPntG5dasdWDUAAMCnJ9iARqZz61Yxqn+/7O1lVVUxd2llzK1c9/beypWxeu3aWL12baxZWxtFhU2iaWFhNC0sjLYtWkSPsrJ1b+3KLDMBAAAaPMEGNHJtSkujTbfS6N+ta9KlAAAA7HAWyQMAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFp5CzbefvvtuPDCC6O8vDxatGgRbdu2jQEDBsQVV1wRVVVV+SoDAAAAaESK8jHIgw8+GF/+8pdjxYoV2fdVVVXF1KlTY+rUqXHTTTfFww8/HHvttVc+ygEAAAAaiZzP2Jg2bVqceuqpsWLFimjZsmX8/Oc/j2eeeSaeeOKJ+NrXvhYREbNnz47Pf/7z8cEHH+S6HAAAAKARyfmMjQsuuCCqq6ujqKgoHn300Tj00EOz940YMSL23nvvuOiii2L27Nlx1VVXxaWXXprrkgAAAIBGIqczNiZPnhxPP/10REScffbZG4Qa61144YXRp0+fiIi45pprYvXq1bksCQAAAGhEchps3H///dnrs846a9MFNGkSY8aMiYiI5cuXx/jx43NZEgAAANCI5DTYmDhxYkREtGjRIg466KDNths6dGj2etKkSbksCQAAAGhEchpszJgxIyIi9tprrygq2vx2HuXl5Rt9DAAAAMDW5Gzz0FWrVsXSpUsjIqJLly5bbNumTZto0aJFrFy5MubPn1/vMRYsWLDF++v2tWjRonr3CwAAANRf3dfca9asyevYOQs26h7d2rJly622Xx9sfPjhh/Ueo2vXrvVuO3DgwHq3BQAAALbPu+++Gz169MjbeDlbirJq1arsdXFx8VbbN2vWLCIiqqurc1USAAAAkGNLlizJ63g5m7HRvHnz7HVNTc1W23/00UcREVFSUlLvMba2bGXOnDlx+OGHR0TEM888s00zPKAxW7RoUXYW0+TJk6NTp04JVwTJ83MBG/NzAZvmZwM2Nn/+/Bg0aFBEbLiPZj7kLNjYZZddstf1WV6ycuXKiKjfspX1trZ3R11du3bdpvaws+jUqZOfDfgEPxewMT8XsGl+NmBjdSc65EPOlqI0b948ysrKImLrm3wuW7YsG2yYVQEAAADUV06Pe+3bt29ERLzxxhtb3BV15syZ2es+ffrksiQAAACgEclpsDFkyJCIWLfM5Pnnn99suwkTJmSvBw8enMuSAAAAgEYkp8HGqFGjste33nrrJtvU1tbG7bffHhERrVu3juHDh+eyJAAAAKARyWmwMXDgwDjssMMiIuLmm2+OZ599dqM2V111VcyYMSMiIi644IJo2rRpLksCAAAAGpGcnYqy3jXXXBODBw+O6urqOProo+MHP/hBDB8+PKqrq+Ouu+6KG264ISIievXqFRdeeGGuywEAAAAakZwHG/3794+77747vvzlL8eKFSviBz/4wUZtevXqFQ8//PAGR8QCAAAAbE1BJpPJ5GOgt99+O6655pp4+OGHY8GCBVFcXBx77bVXnHzyyXHeeedFaWlpPsoAAAAAGpG8BRsAAAAAO1pONw8FAAAAyCXBBgAAAJBagg0AAAAgtQQbAAAAQGoJNgAAAIDUEmwAAAAAqSXYAAAAAFJLsAEAAACkVqMNNt5+++248MILo7y8PFq0aBFt27aNAQMGxBVXXBFVVVVJlwd59c4778RDDz0Ul1xySRxzzDHRrl27KCgoiIKCgjjzzDOTLg8SMXXq1PjJT34SRx99dHTp0iWaNWsWLVu2jF69esVZZ50VEydOTLpEyLsVK1bEXXfdFRdeeGEMHTo09tprr2jVqlUUFxdH+/btY9iwYfHrX/86Kisrky4VGoSLL744+ztVQUFBPPXUU0mXBHlV9/t/S2/Dhg3LbR2ZTCaT0xES8OCDD8aXv/zlWLFixSbv79WrVzz88MOx11575bkySEZBQcFm7xs7dmyMGzcuf8VAA3D44YfH008/vdV2Y8aMiRtvvDGKi4vzUBUk7/HHH4+jjjpqq+3atWsXf/rTn2LkyJF5qAoaphdffDEGDBgQa9asyb5v/PjxOX8BBw3Jll5n1DV06NCcBn9FOes5IdOmTYtTTz01qquro2XLlvH9738/hg8fHtXV1XHXXXfFjTfeGLNnz47Pf/7zMXXq1Nhll12SLhnyqlu3blFeXh6PPvpo0qVAYioqKiIionPnznHyySfHYYcdFt26dYu1a9fGs88+G1dddVUsXLgwbr/99li9enX85S9/SbhiyJ+uXbvG8OHD46CDDoquXbtGp06dora2NhYsWBB//etf47777oulS5fGF77whZg8eXIccMABSZcMeVdbWxvnnHNOrFmzJtq3bx/vvPNO0iVBor7xjW/EN7/5zc3e36JFi5yO3+iCjQsuuCCqq6ujqKgoHn300Tj00EOz940YMSL23nvvuOiii2L27Nlx1VVXxaWXXppcsZAnl1xySQwYMCAGDBgQHTp0iLlz50bPnj2TLgsSU15eHpdffnmceOKJUVhYuMF9hxxySJxxxhkxePDgmD17dtx5553x9a9/PQ4//PCEqoX8GT58eMybN2+z959yyilx//33x+jRo6OmpiYuu+yyuO+++/JYITQMv/vd72LKlClRXl4eo0ePjl/84hdJlwSJat++fey7776Jjd+o9tiYPHlydmrx2WefvUGosd6FF14Yffr0iYiIa665JlavXp3XGiEJl112WRx77LHRoUOHpEuBBuGhhx6KU045ZaNQY7127drFVVddlb3917/+NV+lQaI29zNR16hRo6J3794REfVa0gWNzbx58+J//ud/IiLi+uuvt1wRGoBGFWzcf//92euzzjprk22aNGkSY8aMiYiI5cuXx/jx4/NRGgApM3z48Oz1m2++mWAl0PCsX8q7atWqhCuB/Dv33HPjww8/jLFjx8bQoUOTLgeIRhZsrN/BvkWLFnHQQQdttl3dJ6BJkyblvC4A0uejjz7KXtfnr9iws5g1a1a8+OKLEbFuWRfsTO6555546KGHom3btnHllVcmXQ7wsUYVbMyYMSMiIvbaa68oKtr89iF1/xNe/zEAUNeECROy1+uXMMLOqqqqKl5//fX4zW9+E0OHDs2eAvHtb3872cIgj5YvXx4XXHBBRET86le/inbt2iVcETQc9957b/Tt2zdKS0tjl112ib333jvGjh2btxUSjWbz0FWrVsXSpUsjIqJLly5bbNumTZto0aJFrFy5MubPn5+P8gBIkdra2vjlL3+ZvX3KKackWA0kY9y4cZtd2hsR8b3vfS9OP/30PFYEybroooti8eLFMXjw4Dj77LOTLgcalNdee22D22+88Ua88cYbcfvtt8eoUaNi3Lhx0apVq5yN32iCjQ8++CB73bJly622Xx9sfPjhh7ksC4AUuvrqq2Py5MkREXHCCSdscXkj7Gz69esXN9xwQwwYMCDpUiBvnn766bjpppuiqKgorr/++igoKEi6JGgQSktL4wtf+EIcccQRUV5eHi1btox33303JkyYENdff31UVlbG/fffH8cff3w89thj0bRp05zU0WiCjbqbV9VnZ+JmzZpFRER1dXXOagIgfSZMmBDf+973ImLd0WXXXXddwhVBMkaNGhUHH3xwRKz7fenNN9+Me+65J/7+97/HaaedFr/97W/j2GOPTbhKyL2ampo455xzIpPJxHe+851Ej7SEhmbhwoXRunXrjd5/1FFHxfnnnx/HHHNMTJs2LSZMmBDXXXddfOtb38pJHY1mj43mzZtnr2tqarbafv2mcCUlJTmrCYB0efXVV2P06NGxZs2aaN68edx7773Rvn37pMuCRLRu3Tr23Xff2HfffWPAgAHxxS9+Me677764/fbb46233orjjz8+xo0bl3SZkHOXX355zJw5M7p16xY//vGPky4HGpRNhRrrdejQIf76179mZ2lce+21Oauj0QQb648di4h6LS9ZuXJlRNRv2QoAjd+cOXPi6KOPjmXLlkVhYWHcddddcfjhhyddFjQ4Z5xxRpx88slRW1sb5513Xrz33ntJlwQ5M3PmzPjFL34REetelLVo0SLhiiBd9thjjzjqqKMiYt2+GxUVFTkZp9EsRWnevHmUlZVFZWVlLFiwYIttly1blg02unbtmo/yAGjAKioq4sgjj4yKioooKCiIW265JY4//viky4IG6/jjj4977rknVq5cGf/6179sIkqjdfXVV0dNTU3sscceUVVVFXfddddGbV555ZXs9ZNPPhmLFy+OiIjjjjtOEAIR0bdv3/jHP/4REeuWrnTu3HmHj9Fogo2IdQ/Y008/HW+88UasWbNms0e+zpw5M3vtCD+AndvSpUvjqKOOirfeeisi1v1FbsyYMQlXBQ3bbrvtlr1+++23E6wEcmv98vW33norTjvttK22/+lPf5q9njNnjmADIvKy2W6jWYoSETFkyJCIWLfM5Pnnn99suwkTJmSvBw8enPO6AGiY3n///Rg5cmT2iLJf/vKXce655yZcFTR8CxcuzF5b1gvAltQ9CjYXszUiGlmwMWrUqOz1rbfeusk2tbW1cfvtt0fEuo1Ohg8fno/SAGhgqqqq4vOf/3y88MILERHxwx/+MC6++OKEq4J0uPfee7PX++23X4KVQG6NGzcuMpnMFt/qbig6fvz47Pt79OiRXOHQQMyZMycee+yxiIjYc889Y/fdd8/JOI0q2Bg4cGAcdthhERFx8803x7PPPrtRm6uuuipmzJgREREXXHBBzs7RBaDhqqmpidGjR8ekSZMiYt3/Bz/72c8SrgqSN27cuFi1atUW21x99dXZtdI9e/bM/u4FwM7lwQcfjDVr1mz2/iVLlsSJJ56YPbX0m9/8Zs5qaVR7bEREXHPNNTF48OCorq6Oo48+On7wgx/E8OHDo7q6Ou6666644YYbIiKiV69eceGFFyZcLeTHxIkT44033sjeXrp0afb6jTfe2Oi4vjPPPDNPlUEyTjvttHj00UcjImLEiBFx9tlnb7D52ycVFxdHr1698lUeJObSSy+NCy+8ME488cQYMmRI7LnnntGyZcv44IMP4uWXX44///nP2UCwuLg4brjhhigsLEy4agCScP7558fq1avjxBNPjEMPPTR69OgRJSUlsXTp0njqqafij3/8Y/Z1x5AhQ3K63Lcgk8lkctZ7Qh588MH48pe/HCtWrNjk/b169YqHH3449tprrzxXBsk488wz47bbbqt3+0b4tAAb2NZNrLp37x5z587NTTHQgPTo0aNem4F26dIlbrnlluwRfrAzu/TSS+Oyyy6LiHVLUYYNG5ZsQZAn9f0/48QTT4ybbropWrdunbNaGt2MjYh1Ryu99NJLcc0118TDDz8cCxYsiOLi4thrr73i5JNPjvPOOy9KS0uTLhMAoEF55JFH4uGHH45JkybFG2+8EUuWLInKysooKSmJ9u3bR79+/eLYY4+NU045xe9SADu52267LSZMmBDPPvtsvPXWW7F06dJYsWJFtGzZMrp27RqDBg2KsWPHxqGHHprzWhrljA0AAABg59CoNg8FAAAAdi6CDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFqCDQAAACC1BBsAAABAagk2AAAAgNQSbAAAAACpJdgAAAAAUkuwAQAAAKSWYAMAAABILcEGAAAAkFr/P/+MV1hKJlIZAAAAAElFTkSuQmCC",
       "text/plain": [
-       "(5.0, ((6, 18), (2, 15)))"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
+     "metadata": {
+      "image/png": {
+       "height": 434,
+       "width": 539
+      }
+     },
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "dist, (a, b) = fp.closest_pair()\n",
-    "dist, (a, b)"
+    "plt.scatter(*zip(*fp.points, strict=True), s=600, color=\"cadetblue\", zorder=1)\n",
+    "plt.scatter(*zip(a, b, strict=True), color=\"red\", ec=\"k\", zorder=2)\n",
+    "plt.xlim(0, 5)\n",
+    "plt.ylim(0, 5)\n",
+    "plt.title(f\"Closest pair is {dist:.2} units apart.\");"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "b630b4ed-2c34-4dc1-a7c2-63293e3aab2a",
+   "id": "27db7630-2c71-458e-b95f-4af0e1ba6c3b",
    "metadata": {},
    "source": [
-    "Vizualize the current set.\n",
+    "### Append several points\n",
     "\n",
-    "* 4 initial points in `\"cadetblue\"`\n",
-    "* Current closest pair in `\"red\"`"
+    "Add 3 more 2D points with the `+=` operator and query again."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
-   "id": "e544b5d1-6489-43a1-86f0-60b7999870ec",
+   "execution_count": 20,
+   "id": "55c1f26a-62e1-4c9b-a407-23f476967f65",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:48.028241Z",
-     "iopub.status.busy": "2024-06-12T02:00:48.028170Z",
-     "iopub.status.idle": "2024-06-12T02:00:48.124236Z",
-     "shell.execute_reply": "2024-06-12T02:00:48.123985Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:48.028235Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.787074Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.786995Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.789125Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.788914Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.787066Z"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "image/png": {
-       "height": 434,
-       "width": 572
-      }
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "plt.scatter(*zip(*fp.points, strict=True), s=600, color=\"cadetblue\", zorder=1)\n",
-    "plt.scatter(*zip(a, b, strict=True), color=\"red\", ec=\"k\", zorder=2)\n",
-    "plt.xlim(0, 20)\n",
-    "plt.ylim(0, 20)\n",
-    "plt.title(f\"Closest pair is {dist:.2} units apart.\");"
+    "fp += (1, 2)\n",
+    "fp += (3, 3)\n",
+    "fp += (2, 4)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "cfcae4e4-0093-4776-8174-d0e6396afc2b",
+   "id": "4f198e80-d1d4-4bd2-8a03-242c58441d24",
    "metadata": {},
    "source": [
-    "Add 4 more 2D points with the `+=` operator and query again."
+    "#### Query the closest pair"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
-   "id": "95725979-b1e1-4561-a0cb-817bc012a6b6",
+   "execution_count": 21,
+   "id": "58e711ce-4774-4e26-958e-13dabb91c7f2",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:48.124743Z",
-     "iopub.status.busy": "2024-06-12T02:00:48.124670Z",
-     "iopub.status.idle": "2024-06-12T02:00:48.127973Z",
-     "shell.execute_reply": "2024-06-12T02:00:48.127776Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:48.124736Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.789448Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.789378Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.791875Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.791673Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.789440Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(2.23606797749979, ((9, 10), (7, 11)))"
+       "(1.0, ((1, 2), (1, 1)))"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "for p in range(4):\n",
-    "    fp += tuple(*random_points(p, (2), 1))\n",
-    "\n",
     "dist, (a, b) = fp.closest_pair()\n",
     "dist, (a, b)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "eb398691-723d-41d0-a59d-b7ea92cb3218",
+   "id": "22d37722-c759-499f-a0c3-37973d2bde93",
    "metadata": {},
    "source": [
-    "The closest pair has been updated!\n",
+    "The closest pair has been updated to `(1, 2), (1, 1))` at exactly `1` units distance.\n",
     "\n",
-    "Vizualize the current set.\n",
+    "#### Visualize\n",
     "\n",
-    "* 4 initial points in `\"cadetblue\"`\n",
-    "* 4 additional points in `\"goldenrod\"`\n",
+    "* 3 initial points in `\"cadetblue\"`\n",
+    "* 3 additional points in `\"goldenrod\"`\n",
     "* Current closest pair in `\"red\"`"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
-   "id": "b29156fa-5ec2-4e93-ab3a-317b4a298ceb",
+   "execution_count": 22,
+   "id": "f44c118b-cca2-4c40-b0a1-f66436f0ab22",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:48.128421Z",
-     "iopub.status.busy": "2024-06-12T02:00:48.128356Z",
-     "iopub.status.idle": "2024-06-12T02:00:48.222337Z",
-     "shell.execute_reply": "2024-06-12T02:00:48.222104Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:48.128414Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.792296Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.792234Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.873693Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.873470Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.792289Z"
     }
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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9929x/YwZM3LX7ezQl51prGJj02M8adKk7W7/1FNPbbH9P/7xjz0av7y8PHc4Urdu3bYqiDbZ1WJj04ueZcuW7VG+D9tZsXH22Wfnrn/qqafqdexd1RjFxl/+8pfc/vfee+86326vvfbK3e6vf/3rHmVo6GIjIrLf/OY3t7u/pUuX5l7AR0T2hRde2OZ2DVFsPProo7ntP3woW1Nw//335/JdccUV293uw4fd/eQnP9nutkuWLNmiNP7ud7+7xzlPO+203P5ee+21bW6zu88vig2gqbJ4KJBaq1at2mLBy9LS0kbPUF5eHg888EDu85/97GfRrl277W7/la98JQYNGhQREbW1tVtMuY6I3CEjEREdO3bc7UMMli1bFr/97W8jIqJr1665U1JuT35+fvzoRz/Kff673/1uu7k6d+68W5mS8OlPfzqOOeaY7V5/0kknxSc+8Ync57fddtsejdeuXbsYM2ZMREQsWbIkd7hLfbjqqquiU6dO9ba/ukjr9313bZrqHxFRXFxc59ttvu3m+2iKOnfuHFddddV2r99nn33i4x//eO7zxlwQtqn/vJ1zzjnRtm3biIj4+9//Xqfb9O3bNy6//PLtXt+1a9ctvh933HFHZLPZPcq5+WKudc2ZxPMLQH2yxgaQWqtXr97i801/cDam5557LndWjU6dOsUZZ5yxw+3z8vLiM5/5TO4P3fHjx29xfadOnaKoqCjWrVsXM2fOjEmTJu3WuiF///vfc+tvfOITn9jmWh4fduSRR0abNm1i7dq1MXHixC2u23ztifHjx8fcuXOjX79+u5yrsdXlmP5x48bFQw89FBFbfz+25b333osXXnghZs2aFStXroy1a9du8UJk81MPv/zyy3HwwQfvRvKt7c5aB3tq8+/7rbfeGrfcckujZ2hM69aty10uLCys8+02X0ulsrKyXjPVtzPOOGOnzwdDhgyJBx98MCKiTmdmqS+b/7w99NBD8c1vfjO6dOnSaONHRLzyyivx0ksvxfz582PVqlVbnTVpU9k8Y8aMqK2tjby8Hb9HeMEFF+z01MUXXnhhfO1rX4uamppYvHhxzJkzZ5trD21SUVERL7zwQsyYMSOWLVsWq1ev3mJdo3feeSd3+eWXX97h2Jsk8fwCUJ8UG0Bq7bXXXlt8nsQ7pS+99FLu8vDhw3f6B2xEbFFUvPTSS5HNZnN/LBcWFsbo0aPj/vvvj+rq6hg1alScd955cc4558QJJ5xQ51kpzz//fO7yK6+8Epdddlkd79FGm16wt2nTJiI2vuA46qij4oUXXoj3338/jjjiiLjoootizJgxceyxx+7wlJhJyWQyceSRR+50u6OPPjp3+d13340lS5ZEt27dttrutddeiyuvvDKeeOKJbS6Oui31taBm3759o0OHDvWyr11x7rnnxp133hkRG4uNadOmxbhx4+LUU0+t06KEabP5C/66nDJzk81f/O7KTI8k1KVo69ixY+7y5rMoGtpRRx0VPXv2jIULF8aCBQti0KBBcckll8QZZ5wRRx555C6VTbvqnnvuiWuvvTbmzp1bp+03bNgQ77//frRv336H223+/LI97du3j/79++dmeL300kvbLDZWrFgRV111VfzmN7/Zqtjfnro8ByX1/AJQnxQbQGrtvffeUVBQkDscpby8vNEzLFu2LHe5d+/edbpNnz59cperqqpi9erVW5xF4YYbbohp06bF66+/HlVVVXHvvffGvffeG3l5eTFo0KA4/vjj4+STT47TTjttu2fd2HQGloiIiRMnbjUDoy5WrlyZKzYiNk6RHjVqVLz77ruxZs2auOWWW+KWW26JgoKCOOyww+KEE06IU089NT7ykY9Efn7+Lo9X39q3b79V+bUtm85usund+mXLlm1VbPztb3+Ls846a6t3b3emri8+6pIxCaeeemp86UtfiptvvjkiIqZMmRJTpkyJiI2HLBx33HFx4oknxujRo6NHjx6JZKxPm8/62pWZF5tvm8TMsV2xo0PlNmnVqlXu8oYNGxoyzlbj3nvvvXH66afHmjVrYvny5XHdddfFddddF0VFRTF06NA44YQT4mMf+1gcc8wx9XI2oGw2G5deemncddddu3zb1atX77TY6NWrV5321atXr1yxsfn/K5u8/fbbccIJJ+TO4LIrGXemKR72A7CrrLEBpNrmZUJ9rmdQV5vPEtm8BNiRD2/34T88u3btGlOnTo3vfOc7sc8+++S+XltbGzNmzIhf/vKXMWbMmOjWrVv85Cc/2ebsgU2nbNwTm69fEhFx0EEHxfTp0+NLX/rSFi+OqqurY+rUqfGLX/wiTj311Ojdu3fcfvvtezz+ntqVWSSbf08+/P1YtmxZnHfeeblSo3fv3vHjH/84Jk6cGIsXL46Kioqora2N7MYFuePqq6/O3ba2tnYP78VGSc4CuOmmm+Khhx7a6hS87777bvzv//5vfOlLX4pevXrFOeecs8svupqaD89U2PzQlO2pqKjY4memqb/z3VCnBq4vI0aMiOnTp8fYsWO3+Llft25dTJw4Ma699to47rjjYsCAAfHwww/v8Xi33XbbFqXGRz/60bjnnntixowZsXLlyli/fn3udzubzW7xf05dfr/r+jy0o+egiI2HtGz6/dprr73ia1/7Wvz1r3+Nt956K9asWRM1NTW5jJsfUleXjE19lhFAXSg2gFQ77rjjcpf/9a9/Nfr4m787u3bt2jrd5sPbbWtWwd577x0/+MEP4p133okXXnghrrvuuhg9evQWi7utXLkyvvnNb8bZZ5+91WJzm/+R/Itf/GKLP8zr+rH5zJJN9tlnn7jpppvi3XffjQkTJsQPfvCDOO2007aYcfLOO+/Ev//7v8eXv/zlOj0eDaWioqLO227+Pfnw9+O2227LFUWHHnpovPLKK/GNb3wjjj322OjWrVsUFxdv8WKxvmZpNCVjxoyJf/3rX/H222/HPffcE//xH/8RBx10UO76bDYb//u//xuHH354nafyN0X9+/ff4vO33357p7f5cJnz4X00tPoqz5qS/fbbL+65555YtmxZ/PWvf43vfOc7MXLkyC1egM+dOzfGjBkTv/jFL/ZorJ///Oe5y9dcc0088cQTMXbs2Bg8eHCUlpZudfjLrv5+1/V5aEfPQc8991w899xzEbHx/5wXXnghVyT37ds32rRps8VaH83xOQhgZxQbQKqNGjUqd/ntt9/O/fHXWDafwlvXd6s3X4yvsLBwh4dL5Ofnx5FHHhn/7//9v/jTn/4U7777bjz77LNx5pln5rZ55JFH4n//93+3uN3mMz2WLl1ap1y7onXr1jFixIj4zne+E3/5y19i+fLl8cQTT2xRNN188825wxaSsHLlyjqtu7J8+fIt3pn/8JkB/vGPf+Quf+c739mixNmWurwYTqtevXrF2LFj49Zbb41XX301FixYENdcc03uXemysrL4z//8z4RT7r527dptcRjS5mvobM+LL76Yu7zvvvvu9OdjZzY/DOTDs6a2pT5mZzVVbdq0iVNPPTV+8IMfxNNPPx1lZWXxhz/8YYt1Qr75zW9usVjmrli4cGG8/vrrEbHxrFrf/OY3d7j9qlWrYuXKlbs0Rl3/X1i4cGHu8o6eg8aNG7dFqbgtzfk5CGB7FBtAqn3yk5/c4o/APX33blcNGTIkd3ny5Ml1WlRy8/JlyJAhuzQ1PC8vL4477rh4+OGH4+STT859/c9//vMW222+aOakSZPqvP/d1apVq/joRz8af//732Pw4MG5rz/66KNbbdtYU+Gz2WydZvFsvtDqPvvsE927d9/i+s3XK9nZwos1NTWN8ng3FT179oyrrrpqi9MWP/nkk7u8FklTMnLkyNzlCRMm7HT7Z555Jnd586J1d21ejJSVle10+xkzZuzxmA2lvn/Xi4uL45xzzokJEybkytuqqqr429/+tlv72/x3e8CAAVuUStsyceLEXT4V6wsvvLDTbcrLy2P27Nm5zw8//PDt5qzL4q///Oc/dyHhrmnqhzIBLZdiA0i14uLiLQ55+N///d+tZi/Uxdq1a3drtscxxxyTW8Bz2bJl8fjjj+9w+9ra2i2O597dF0KZTGaLU8u+++67W1x/6qmn5s7Q8txzz8X06dN3a5xd1bp16zjllFO2mytiyzNPNPTChPfee+9Ot/nNb36Tu7z5i9pNNp/ivbNp5Q8//HCDzJBp6jafQbRhw4ZYsWJFgmn2zOjRo3OXH3jggR0uIlpZWZk7LeqHb7u7Nj8EbGen6pw6dWrMmzdvj8dsKA31u96hQ4ctzi61reeZutiV3+2I2K3THd933307Lbx/97vf5bbp1q3bVocz7UrOxYsXxyOPPLLLOeuqMZ+/AXaFYgNIvSuuuGKLd7guuuiibc4U2J6ZM2fGUUcdFU8++eQuj11aWhrnnXde7vOvf/3rOzy++b//+79z77Dm5eXFZz/72S2uX716dZ1PM7n51OUuXbpscd2+++4bF154YURsnLkwduzYOp+2sba2dqtV+VeuXFnnY/l3lCtiywUad3cKeV399re/3eGsjfHjx29RhP3bv/3bVtvst99+ucsfnhmzuWXLlsXXvva13UzaNNX1dLWbf8/z8vK2+B6nzZlnnpk7w0t5eXn86Ec/2u62P/jBD3JnY+rdu3ecfvrpezz+5rOt7rnnnu1uV11dHV/5ylf2eLyGVFpamntRvmzZsp2+EK7LDJVNdvY8Uxd9+/bNzUCYOXNmvPXWW9vd9oEHHojHHntsl8d4880344Ybbtju9e+++258//vfz31+6aWXbjUroq7PQTU1NfHZz352l05VvKsa8/kbYFcoNoDUa926dfzhD3/I/XFbWVkZo0ePjrFjx8asWbO2eZtsNhtTpkyJcePGxaGHHhozZ87c7fGvuuqq3CKic+fOjVNPPXWrP5Bra2vjxhtv3GL9gS9+8YtbLdA5bdq06NOnT3zve9/b7lleampq4oEHHsidgjMi4rTTTttqux/96Ee59QJeeeWVGD58+A7Lm0WLFsUNN9wQ/fv3jwceeGCL6x555JHo169f/PznP99ijZDNrV+/Pv77v/87/vjHP+4w1+aHqjzyyCMN9kd4q1atoqamJk4//fT4+9//vtX1jz/+eIwZMyY3tfzkk0+Oj3zkI1ttt/nMmB//+Mfx29/+dqttXnzxxRgxYkQsXLiwzmfHSYOjjz46LrjggnjiiSe2+32aO3dujBs3Lvf5Rz7yka0WXGwKTjzxxMhkMpHJZOLEE0/c7natW7eOa665Jvf5j3/847jpppu2KPZqa2vjpptuip/+9Ke5r33/+9+vl/t93nnn5cqA559/Pr7xjW9s9Y7/okWL4vTTT4/nnntuu6d8bgpat24dBx54YERsfHd/Z2cxufnmm+Owww6LW265Zbszn9asWRPf/va3c+v35OfnbzFLbFd06tQpjjrqqIjY+D0955xzYs6cOVtsU1tbG//zP/8TF110UeTn528xY6EuCgsL48orr4wbb7xxq3J41qxZcfLJJ8d7770XERsPhdtWOfrxj388V3ZMmDAh/t//+39bzSRaunRpnH322fH444836HPQ5s/f//rXv+q8hkifPn1yv38XX3xxA6UDWrKCpAMA1If99tsv/vWvf8UZZ5wRM2fOjNra2rj33nvj3nvvjT59+sQhhxwSnTp1ipqamli6dGm8/PLLW01f3tEinjuy//77x+233x6f/vSno6amJp5//vno379/HH/88bH//vvHmjVr4tlnn93i3a2jjjoqfvazn21zf0uWLIlrrrkmrrnmmujatWscdthh0bVr1ygoKIh33303pk2btsUx18cff3x86lOf2mo/3bt3j0ceeSQ+9rGPxfLly2POnDlx6qmnxr777hvDhw+Pzp07x4YNG2L58uUxc+bMnU5pf/PNN+PrX/96fP3rX49evXrFIYcckiuTli5dGi+88MIWhyB8+tOfjmOOOWar/Zx22mlRXFwclZWV8fLLL8fAgQPjxBNPjNLS0twf76eccspuv1jZ/P6PGTMm/uu//itOPvnkOPTQQ+Owww6LbDYb06ZNi1dffTW3bbdu3eK2227b5n7GjRsX119/fcydOzfWr18fF110UVx77bVx6KGHRlFRUcycOTOmTp0aERvPmnLqqadu93ubNhs2bIj77rsv7rvvviguLo5DDjkk9ttvv9h7771j5cqV8dZbb+Xue8TGQ8M2P8vE7rr11lvj1ltv3eJrHy5WPvaxj21VJHzuc5+Lz33uc3s8/mc+85mYMGFC3HvvvVFbWxtf+cpX4qabbsq9CH7hhRfizTffzG1/ySWXxNixY/d43IiNMz8+97nPxS9/+cuIiPjpT38a9913X5xwwglRVFQUb775ZkyaNCmqqqripJNOiq5du26zbGsqzj777Lj22msjYuNzwt133x0HHHDAFutZbP4zM3369PjCF74QX/ziF2P//fePwYMHR6dOnWLDhg2xZMmSeO6557ZYFPgb3/hG9OzZc7fz/eAHP4hTTjklamtr46WXXoqDDz44jj322Nhvv/1yz91LliyJiI1l8a9//etdWpzzZz/7WXz1q1+Nr371q/Hzn/88jjvuuGjbtm3MnTs3Jk6cmCs7CgoK4s4779zm6YIHDBgQF110Ue6wueuvvz5+//vfx7Bhw6JLly4xf/78+Oc//xlVVVWx1157xXXXXVcvvwfb0rVr1zjmmGPiueeei3Xr1sWhhx4aH/3oR6Nbt265Qm7//fePz3/+8w0yPsB2ZQGakdWrV2e///3vZ0tLS7MRUaePQw89NPunP/1pm/sbN25cbru77rprh2M/+uij2X322Wen451//vnZtWvXbnMfL7zwQragoKDO2c8555zsqlWrdphr/vz52Y985CN13uc+++yT/etf/7rFPv7whz9kM5lMnW6fl5eX/cIXvpCtqqrabqZbbrllh/u7+uqrd3iftmfevHm5ffTu3TtbVVWVvfTSS3eYt3///tlZs2btcL9z5szJ7rfffjvcz7HHHptdtGhR9uqrr97p/bjrrrty24wbN26b24wfPz63zYgRI3br8diZESNG5MYYP378VtcPHjy4zj83ffv2zU6aNKlecm3+GO7Kx45+bja/r3V5PNevX5+97LLLdvhzmslksl/+8pd3+LO+OyorK7Mf+9jHdnhfTz/99OzKlSvr9By1K89j2Wzdfj7rsk02m82Wl5dnBwwYsMP7ssnPf/7zOn+vCwsLs9dcc81O70td3HLLLTt83s3Ly8teddVV2dra2mzv3r1zX583b9429/fhbW655ZZsYWHhdvdfWlqafeihh3aYce3atdlTTjllh49Jjx49shMnTqzTc8eePL9MmTIlu9dee203x7b2t/ljsqOfF4DdZcYG0Ky0bds2vvvd78aXv/zl+Mtf/hJPPfVUTJs2Ld57771YsWJFFBYWRocOHWLAgAFx5JFHxujRo7dagX53nX766fHGG2/EnXfeGY899li8+uqrsXz58iguLo7u3bvHyJEjY+zYsVscQ/9hRx55ZLz33nvx97//PSZOnBgvvfRSvPnmm1FWVhY1NTWx9957x/777x9HHXVUXHjhhTF8+PCd5urdu3f8/e9/j+effz7+8Ic/xD//+c9YuHBhrFy5MgoKCqJjx45x4IEHxtChQ+OUU06JE088Mbfw6CbnnHNOLFmyJJ588smYNGlSTJ8+Pd56663c+gLt2rWLfv36xXHHHRdjx47d6ekIP/e5z8XBBx8cv/rVr+Jf//pXvPPOO1FRUbHLZxzYmVatWsXtt98en/zkJ+OOO+6IKVOmxJIlS6JNmzYxcODAOO+88+Kzn/3sTqfz9+vXL1566aX4n//5n3jooYdizpw5UVVVFV27do2DDz44Lrjggjj33HMjPz+/XvMn7eWXX44XXnghxo8fH5MnT445c+bE4sWLo6KiIkpKSnIzis4888w499xzm/RhEbuqsLAwbr755rjooovizjvvjAkTJuRmXe27775x4oknxqWXXhrDhg2r97GLiorisccei/vuuy/uueeeePHFF+P999+PLl26xKGHHhoXX3xxnHPOOak4Q0W7du1iypQp8ctf/jIef/zxmDVrVpSXl29zvY3LL788zj777HjqqafiueeeixkzZsT8+fNj1apVkZeXF6WlpTFw4MAYNWpUjB07Nnr37l0vGT/3uc/FscceGzfccEOMHz8+Fi9eHMXFxbHvvvvGqFGj4jOf+cwWZ8Danf0ff/zxceutt8bf//73WLRoUURsPDzjjDPOiC996UtbnGZ4W0pKSuKJJ56I3//+93HPPffESy+9FKtWrYpOnTrFfvvtF2effXZcfPHF0b59+zqdzWdPDB06NF555ZW4+eabY/z48fHWW2/FmjVr6nRWMICGksnW91+RAJCQ+fPnR9++fSNiY6GzvfVAABpKnz59coerzJs3b6u1lACofxYPBQAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGo16Ole63p+9REjRjT4ObcBAACA5seMDQAAACC1ChpjkM9//vPxhS98YbvXt2nTpjFiAAAAAM1MoxQbXbp0icGDBzfGUAAAAEAL4lAUAAAAILUUGwAAAEBqKTYAAACA1GqU070edNBBkc1mY/78+ZGfnx9du3aNY445Ji6++OIYOXLkbu9/0aJFO7x+3bp1MXv27Nhnn32ic+fOUVDQKEuKAAAAQItSXV0dy5Yti4iIgw8+OIqKihpt7EYpNnZk9OjRcffdd0e7du0aZP8AAABA45k8eXIMGzas0cZr0CkMJSUlceaZZ8ZHPvKRGDBgQLRt2zaWLVsWzzzzTNx6661RVlYWDz/8cJx11lnx1FNPRatWrRoyDgAAANDMNOiMjfLy8igtLd3mde+++26cdtpp8dJLL0VExI033hhf/vKXd2n/OzsUZeHChXHMMcdExMbGqFu3bru0fwAAAGDnlixZEsOHD4+IiHnz5kWfPn0abewGLTZ25q233ooBAwbEhg0b4oADDojXX3+9Xve/aNGi6NmzZ0RsLDl69OhRr/sHAAAAkn39nehZUfbbb784+eSTIyLijTfeiMWLFycZBwAAAEiZxE/3etBBB+Uuv/POOwkmAQAAANIm8WLDmU0AAACA3ZV4sfHaa6/lLnfv3j3BJAAAAEDaJFpszJs3L5566qmIiNh///1j3333TTIOAAAAkDINVmw8+uijUV1dvd3r33333Tj77LOjqqoqIiK+8IUvNFQUAAAAoJkqaKgdf+lLX4oNGzbE2WefHUcffXT06dMniouLY/ny5TFhwoT41a9+FcuXL4+IiOOOOy6++MUvNlQUAAAAoJlqsGIjImLx4sVx8803x80337zdbc4+++y4/fbbo3Xr1g0ZBQAAAGiGGqzYuOeee+KZZ56J559/Pt56661Yvnx5rFq1Ktq2bRs9e/aMY445JsaNGxdHH310Q0UAAAAAmrkGKzZGjBgRI0aMaKjdAwAAACR/ulcAAACA3aXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASK2CpAMAAAA0RdlsNsorKmJ+WVnML1sR88vKYsXatbGhuiY21NREdW1tFOTlRav8/GhVkB8d2rSJPh07Rp+OHaJPp07RvqQk6bsALYJiAwAA4AOLy9+PyfPmxbzlZTGvbHmsqlxX59suXLEypi9clPu8XXFx9OnYMfp26hjD+/aN7qXtGiIytHiKDQAAoEWrrq2NlxYsiKdnzYlZS5fW237fr6yM6YsWxfRFi+Lhl6fHwG5dY9SAATGkV88oyLMqANQXxQYAANAirVy7NibMfT2emTM3yisrG3y8WUuWxqwlS6O0pDhO7NcvRvTv53AVqAeKDQAAoEWprKqKB6dOi2fmvh612Wyjj19eURkPvzw9/jz9lRjR78A4d9jQKG7VqtFzQHOh2AAAAFqMVxcvjjsnPhdla9cmHSVqs9kYP2duvLLonfjMccfEoO7dk44EqaTYAAAAmr3Kqqp4YMq0mDB3btJRtlK2dm1c97en4sT+/eI8szdglyk2AACAZq0pzdLYkQlz5sYMszdgl1mKFwAAaLaemPlqXPe3p5p8qbHJptkbT8x8NekokBpmbAAAAM1ONpuNh158KR59ZUbSUXbLA1OmRkVVVXxiyGGRyWSSjgNNmmIDgBYnW1sdVaveiPUrZsa6FTNi/YqZUV2xNLI16yNbWxWZvMLI5LeOgpKu0brD4CjqcHC07jA4Cvc+IDJ5/usEaOqy2Wz8fvKUeOq1WUlH2SOPTn8l1m3YEBcMH6bcgB3w1xkALUI2m411y6ZG+eu/jbWLnopsTeVOb1NdsTjWLX8x3v/g80x+cbTpcXKU9rsoijod4Y9MgCbqoRdfSn2psclTr82Kolat4uzDhyQdBZosxQYAzVrthrWxav7D8f7r90ZV+Zw92le2pjLWvP3nWPP2n6OwdECUHnhR7NXnrMhr1aae0gKwp56Y+WpqDz/ZnkenvxIlhYVx2uBBSUeBJsnioQA0W6sXPBHzHx0Ry6Z8Z49LjQ+rKp8d7035dsx/dESsXvBEve4bgN3z6uLF8cCUqUnHaBAPTJkary1eknQMaJIUGwA0O9XrymLJxMti6cQvRM26sgYdq2ZdWSyd+IVYMvFLUbNuRYOOBcD2VVZVxZ0Tn0s6RoO6Y9KkqNywIekY0OQoNgBoVtYsfDIWPH5qrFnweOOOu+CxePvxU2LNwicbdVwANnpg6rTUnNJ1d5WtWRsPNtMZKbAnFBsANBvlc+6KJc/+R9Ssb9hZGttTs74sljz7H1E+5+5ExgdoqV5dvDgmzJmbdIxGMX7OXIekwIcoNgBoFla8+stYNu37SceIiIhl066JFa/+MukYAC1CSzgE5cMckgJbUmwAkHrlc+6KsunXJR1jC2XTrzNzA6ARPNgCDkH5sLI1a+MPU6clHQOaDMUGAKm2ZuGTTWamxoctm3aNNTcAGtDKiop4Zu7rScdIxDNz5sbKioqkY0CToNgAILWq15XFe5O/lXSMHXpvyrecLQWggTwzZ27UZrNJx0hETTYb/2yhpQ58mGIDgNRaNvXqxBYKrauadWXx3tSrk44B0OxU19bGhLktY8HQ7Rk/Z05U19YmHQMSp9gAIJVWL/hLo5/SdXetWfBYrF7wRNIxAJqVlxYsjPKKyqRjJKq8ojJeXrAw6RiQOMUGAKlTu2FtLJt6VdIxdsmyqd+N2g0ta3E7gIb09OzZSUdoEp6ePSfpCJA4xQYAqbN6/iNRs65pH4LyYTXrymL1248kHQOgWVhcXh6zlixNOkaT8NqSJbG4/P2kY0CiFBsApEo2m43y1+9NOsZuKZ97b2Rb6CJ3APVp8rz5SUdoUibPm5d0BEhUYsXGlVdeGZlMJvcxYcKEpKIAkCLrlk2NqvJ0Tj+uKp8d65ZPSzoGQOrNW56uWXsNbV6Zx4OWLZFi4+WXX45f/OIXSQwNQMqVv/7bpCPskfK56ZxtAtBUZLPZmO+F/BbeVvTQwjV6sVFbWxuf/exno7q6Orp06dLYwwOQYtna6li76KmkY+yRtYueimxtddIxAFKrvKIi3q9s2WdD+bDyyspYWVGRdAxITKMXGzfddFNMmTIlBgwYEJdeemljDw9AilWteiOyNen+YzZbUxlVq95MOgZAapmtsW3zzdqgBWvUYmPBggXx3e9+NyIibr311igsLGzM4QFIufUrZiYdoV40l/sBkIT5ZSuSjtAkKXxoyRq12PjiF78Ya9asiXHjxsWIESMac2gAmoF1K2YkHaFeNJf7AZAEL+C3zeNCS9ZoxcaDDz4Yjz32WHTo0CF+/vOfN9awADQjzWWmQ3O5HwBJWLF2bdIRmiSPCy1ZQWMMUl5eHl/5ylciIuKnP/1pdOrUqV72u2jRoh1ev2TJknoZB4CmobpiadIR6kV1hf+fAHbXhuqapCM0SRtqPC60XI1SbFxxxRWxdOnSOPbYY+t1wdCePXvW274AaPqyNeuTjlAvsrXN434AJMEL+G3zuNCSNfihKM8++2zcfvvtUVBQELfeemtkMpmGHhKAZipbW5V0hHqRrWke9wMgCdW1tUlHaJKqazwutFwNOmOjqqoqPvvZz0Y2m42vfe1rMXjw4Hrd/8KFC3d4/ZIlS2L48OH1OiYAycnkNY+zaWXym8f9AEhCQV6jnv8gNQryPS60XA1abFx77bUxe/bs6NWrV1x99dX1vv8ePXrU+z4BaLoy+a2TjlAvMnnN434AJKFVfn7SEZokjwstWYPVerNnz44f//jHERFx8803R5s2bRpqKABaiIKSrklHqBcFJd2SjgCQWq0KvIDfFsUGLVmDzdi44YYboqqqKvbbb7+oqKiI+++/f6ttZs78v9PdPf3007F06cbV7s844wxFCABbad1hcKxb/mLSMfZY6w71e2gmQEvSoU2bWLhiZdIxmpwOXj/RgjVYsbF+/cYV39966604//zzd7r9D37wg9zlefPmKTYA2EpRh4Pj/aRD1IOiDgcnHQEgtfp07BjTFy5KOkaT06djx6QjQGKsMANAajSXmQ7N5X4AJKFPxw5JR2iSFBu0ZA1WbNx9992RzWZ3+LH5gqLjx4/Pfb1Pnz4NFQuAFCvc+4DI5BcnHWOPZPKLo3Dv/ZOOAZBaXsBvW59OHhdaLjM2AEiNTF5BtOlxctIx9kibHidHJq9BT0oG0KyVlpREu+J0l9z1rbS4ONqXlCQdAxKj2AAgVUoPvDDpCHuktN9FSUcASLVMJmPWxof0NluDFk6xAUCqFHUeGoWlA5KOsVsKSwdGUacjko4BkHp9vZDfQl9FDy2cYgOAVMlkMlF6YDpnPZT2uzAymUzSMQBSb3jfvklHaFKO3M/jQcuWaLHxve99L7dg6IknnphkFABSZK8+Z0V+Ubrencov6hh79T4r6RgAzUL30nYxsFvXpGM0CQd16xbd2rVLOgYkyowNAFInr1Wb6Dz0B0nH2CVdhv0w8lq1SToGQLMxakA6D0usb6MG9E86AiROsQFAKu3V67Ro2+vjSceok7a9To+2PT+adAyAZmVIr55RWtKyz45SWlIcQ3r1TDoGJE6xAUBqdR56TeS3btqHpOQXdYwuQ69JOgZAs1OQlxcn9uuXdIxEjezfP/LzvKQDvwUApFZBUcfoMvzapGPsUJdh10Z+UYekYwA0SyP694u8Frooc34mEyf0OzDpGNAkKDYASLW2PU+JzkdclXSMbep8xNXRtucpSccAaLbal5TEiBb64n5E/37RvqQk6RjQJCg2AEi90v6XRMdDv550jC10PPSKKO1/cdIxAJq9c4ceER3btKzFmTu2bROfHHpE0jGgyVBsANAsdBj0heh8xNVJx4iIiM5HfC86DPp80jEAWoTiwsL4zHHHJB2jUV167LFR3KpV0jGgyVBsANBslPa/OLod/6vEFhTNL+oY3Y7/VZT2H5fI+AAt1aDu3ePE/i1jIdGR/fvFQd27JR0DmhTFBgDNStuep0Tvjz8ZbXud3rjj9j4jen/sSWtqACTkvBZwSErHtm3i3GFDk44BTY5iA4BmJ7+oQ3Q77uboetwvI7+oYWdvbJylcUt0O/YmZz8BSFBLOCTFISiwbQVJBwCAhrJXr9OiTbcTYvX8R6L89Xujqnx2ve27sHRAlPa7KPbqfVbktWre7xACpMWg7t3jvGFD44EpU5OOUu8+NWyoQ1BgOxQbADRrea3aRLsDL4i9Dzg/1i2fFuVz7421i56KbE3lLu8rk18cbXucEu36XRRFnQ6PTCbTAIkB2BOnDR4UFevXx6OvzEg6Sr0549BD4qODByUdA5osxQYALUImk4nizkOjuPPQyNZWR9WqN2P9ipmxbsWMWL9iZlRXLIls7frI1lRFJr8wMnmto6CkW7TuMDiKOhwcrTsMjsK9949Mnv86AZq6Txw+JNZVV8dTr81KOsoeO/mggfGJIYclHQOaNH+dAdDiZPIKonVp/2hd2j/23u/spOMAUM8ymUxcMHxYFLVqFY9OfyXpOLvtzEMPiTFDDjNDEHZCsQEAADQ7mUwmzj58SJQUFqZyzY3zhg2N0xx+AnWi2AAAAJqt0wYPit4dOsQdEydF2dq1ScfZqY5t28Slxx5roVDYBU73CgAANGsHde8WPxxzVpzYv1/SUXZoZP9+8cPRZyk1YBeZsQEAADR7xa1axcXHHB3D+vSOOyc+16Rmb5ilAXvGjA0AAKDFGNS9e/xwzFkxakD/yEt4Uc78TCZGDehvlgbsITM2AACAFqW4VasYe/RRccahh8Qzc+bGhLlzo7yistHGLy0pjpH9+8cJ/Q6M9iUljTYuNFeKDQAAoEVqX1ISo4ccFqcfeki8tGBhPD17dsxasrTBxjuoW7cYNaB/HNarZxTkmTwP9UWxAQAAtGgFeXkxrE/vGNandywufz8mz5sX88rKYv7ysni/cvdncpQWF0fvTh2jb8eOMbxv3+he2q4eUwObKDYAAAA+0L20XYweclju85UVFTF/eVnML9v4sWLt2thQUxMbamqiuqY2CvLzolV+frTKz48ObdpEn44dN3506ugwE2gkig0AAIDtaF9SEu17lcSQXj2TjgJshwO7AAAAgNRSbAAAAACppdgAAAAAUkuxAQAAAKSWYgMAAABILcUGAAAAkFqKDQAAACC1FBsAAABAaik2AAAAgNRSbAAAAACppdgAAAAAUkuxAQAAAKSWYgMAAABILcUGAAAAkFqKDQAAACC1FBsAAABAaik2AAAAgNRSbAAAAACppdgAAAAAUkuxAQAAAKSWYgMAAABILcUGAAAAkFqKDQAAACC1FBsAAABAaik2AAAAgNRSbAAAAACppdgAAAAAUkuxAQAAAKSWYgMAAABILcUGAAAAkFqKDQAAACC1FBsAAABAaik2AAAAgNRSbAAAAACppdgAAAAAUkuxAQAAAKSWYgMAAABILcUGAAAAkFqKDQAAACC1FBsAAABAaik2AAAAgNRSbAAAAACppdgAAAAAUkuxAQAAAKSWYgMAAABILcUGAAAAkFqKDQAAACC1FBsAAABAaik2AAAAgNRSbAAAAACppdgAAAAAUkuxAQAAAKSWYgMAAABILcUGAAAAkFqKDQAAACC1FBsAAABAaik2AAAAgNRSbAAAAACppdgAAAAAUkuxAQAAAKSWYgMAAABILcUGAAAAkFqKDQAAACC1FBsAAABAaik2AAAAgNRSbAAAAACppdgAAAAAUkuxAQAAAKSWYgMAAABILcUGAAAAkFqKDQAAACC1FBsAAABAaik2AAAAgNRSbAAAAACppdgAAAAAUkuxAQAAAKSWYgMAAABILcUGAAAAkFqKDQAAACC1FBsAAABAaik2AAAAgNRSbAAAAACppdgAAAAAUkuxAQAAAKSWYgMAAABILcUGAAAAkFoFSQcAACB52drqqFr1RqxfMTPWrZgR61fMjOqKpZGtWR/Z2qrI5BVGJr91FJR0jdYdBkdRh4OjdYfBUbj3AZHJ8yclAMnxvxAAQAuVzWZj3bKpUf76b2PtoqciW1O509tUVyyOdctfjPc/+DyTXxxtepwcpf0uiqJOR0Qmk2nY0ADwIYoNAIAWpnbD2lg1/+F4//V7o6p8zh7tK1tTGWve/nOsefvPUVg6IEoPvCj26nNW5LVqU09pAWDHrLEBANCCrF7wRMx/dEQsm/KdPS41PqyqfHa8N+XbMf/REbF6wRP1um8A2B7FBgBAC1C9riyWTLwslk78QtSsK2vQsWrWlcXSiV+IJRO/FDXrVjToWACg2AAAaObWLHwyFjx+aqxZ8HjjjrvgsXj78VNizcInG3VcAFoWxQYAQDNWPueuWPLsf0TN+oadpbE9NevLYsmz/xHlc+5OZHwAmj/FBgBAM7Xi1V/GsmnfTzpGREQsm3ZNrHj1l0nHAKAZUmwAADRD5XPuirLp1yUdYwtl068zcwOAeqfYAABoZtYsfLLJzNT4sGXTrrHmBgD1SrEBANCMVK8ri/cmfyvpGDv03pRvOVsKAPVGsQEA0Iwsm3p1YguF1lXNurJ4b+rVSccAoJlQbAAANBOrF/yl0U/purvWLHgsVi94IukYADQDig0AgGagdsPaWDb1qqRj7JJlU78btRvWJh0DgJRTbAAANAOr5z8SNeua9iEoH1azrixWv/1I0jEASLmChtrxqlWr4i9/+UtMmTIlpk6dGu+8804sW7YsKisro7S0NA466KD42Mc+Fpdeeml07NixoWIAADR72Ww2yl+/N+kYu6V87r2x9/7nRyaTSToKACnVYMXG5MmT4/zzz9/mdcuWLYtnnnkmnnnmmbjuuuvit7/9bZx66qkNFQUAoFlbt2xqVJXPTjrGbqkqnx3rlk+L4s5Dk44CQEo1WLEREdGzZ88YOXJkHHHEEdGzZ8/o1q1b1NbWxqJFi+KPf/xjPPTQQ7F8+fI488wzY/LkyXHooYc2ZBwAgGap/PXfJh1hj5TPvVexAcBua7BiY+TIkbFgwYLtXn/uuefGww8/HGPGjImqqqq45ppr4qGHHmqoOAAAzVK2tjrWLnoq6Rh7ZO2ipyJbWx2ZvAZ9zw2AZqrBFg/Nz8/f6TajR4+O/v37R0TEs88+21BRAACarapVb0S2pjLpGHskW1MZVaveTDoGACmV+FlR9tprr4iIWLduXcJJAADSZ/2KmUlHqBfN5X4A0PgSLTbmzJkTL7/8ckREDBgwIMkoAACptG7FjKQj1Ivmcj8AaHyNXmxUVFTE66+/Hr/4xS9ixIgRUV1dHRERX/3qVxs7CgBA6jWXmQ7N5X4A0PgaZYWmu+++Oy655JLtXv+Nb3wjLrjggl3e76JFi3Z4/ZIlS3Z5nwAAaVJdsTTpCPWiusLfbQDsnkSXnj7ssMPi17/+dQwbNmy3bt+zZ896TgQAkC7ZmvVJR6gX2drmcT8AaHyNcijK6NGjY8aMGTFjxoyYPHly3HfffTFmzJh4+eWX4/zzz4/HHnusMWIAADQ72dqqpCPUi2xN87gfADS+RpmxUVpaGqWlpbnPhw0bFp/61Kfi3nvvjXHjxsVZZ50Vd9xxR1x88cW7tN+FCxfu8PolS5bE8OHDdyMxAEA6ZPIKk45QLzL5zeN+AND4Ej0U5aKLLorHHnssHnzwwbjsssvizDPPjA4dOtT59j169GjAdAAATV8mv3XSEepFJq953A8AGl+ip3uNiDjrrLMiImLt2rXx17/+NeE0AADpUlDSNekI9aKgpFvSEQBIqcSLjc6dO+cuv/322wkmAQBIn9YdBicdoV40l/sBQONLvNh45513cpfbtm2bYBIAgPQp6nBw0hHqRXO5HwA0vsSLjT/84Q+5ywcf7D80AIBd0VxmOjSX+wFA42uwYuPuu++OdevW7XCbG264If7yl79ERETfvn3j+OOPb6g4AADNUuHeB0QmvzjpGHskk18chXvvn3QMAFKqwc6K8r3vfS8uv/zyOPvss+O4446L/fffP9q2bRurV6+OGTNmxO9+97uYNGlSREQUFhbGr3/968jPz2+oOAAAzVImryDa9Dg51rz956Sj7LY2PU6OTF6iJ+sDIMUa9H+QFStWxG233Ra33Xbbdrfp0aNH3HnnnXHSSSc1ZBQAgGar9MALU11slPa7KOkIAKRYgxUbf/vb3+Lxxx+PSZMmxRtvvBHvvvtulJWVRXFxcXTp0iUOO+ywOP300+Pcc8+NkpKShooBANDsFXUeGoWlA6KqfHbSUXZZYenAKOp0RNIxAEixBis2+vfvH/3794///M//bKghAACIiEwmE6UHXhTvTfl20lF2WWm/CyOTySQdA4AUS/ysKAAA7Lm9+pwV+UUdk46xS/KLOsZevc9KOgYAKafYAABoBvJatYnOQ3+QdIxd0mXYDyOvVZukYwCQcooNAIBmYq9ep0XbXh9POkadtO11erTt+dGkYwDQDCg2AACakc5Dr4n81k37kJT8oo7RZeg1SccAoJlQbAAANCMFRR2jy/Brk46xQ12GXRv5RR2SjgFAM6HYAABoZtr2PCU6H3FV0jG2qfMRV0fbnqckHQOAZkSxAQDQDJX2vyQ6Hvr1pGNsoeOhV0Rp/4uTjgFAM6PYAABopjoM+kJ0PuLqpGNERETnI74XHQZ9PukYADRDig0AgGastP/F0e34XyW2oGh+UcfodvyvorT/uETGB6D5U2wAADRzbXueEr0//mS07XV6447b+4zo/bEnrakBQINSbAAAtAD5RR2i23E3R9fjfhn5RQ07e2PjLI1botuxNzn7CQANriDpAAAANJ69ep0WbbqdEKvnPxLlr98bVeWz623fhaUDorTfRbFX77Mir1WbetsvAOyIYgMAoIXJa9Um2h14Qex9wPmxbvm0KJ97b6xd9FRkayp3eV+Z/OJo2+OUaNfvoijqdHhkMpkGSAwA26fYAABooTKZTBR3HhrFnYdGtrY6qla9GetXzIx1K2bE+hUzo7piSWRr10e2pioy+YWRyWsdBSXdonWHwVHU4eBo3WFwFO69f2Ty/EkJQHL8LwQAQGTyCqJ1af9oXdo/9t7v7KTjAECdWTwUAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqVWQdAAAaEzZbDbKKypifllZzC9bEfPLymLF2rWxobomNtTURHVtbRTk5UWr/PxoVZAfHdq0iT4dO0afjh2iT6dO0b6kJOm7AADAZhQbADR7i8vfj8nz5sW85WUxr2x5rKpcV+fbLlyxMqYvXJT7vF1xcfTp2DH6duoYw/v2je6l7RoiMgAAdaTYAKBZqq6tjZcWLIinZ82JWUuX1tt+36+sjOmLFsX0RYvi4Zenx8BuXWPUgAExpFfPKMhzhCcAQGNTbADQrKxcuzYmzH09npkzN8orKxt8vFlLlsasJUujtKQ4TuzXL0b07+dwFQCARqTYAKBZqKyqigenTotn5r4etdlso49fXlEZD788Pf48/ZUY0e/AOHfY0Chu1arRcwAAtDSKDQBS79XFi+POic9F2dq1SUeJ2mw2xs+ZG68seic+c9wxMah796QjAQA0a4oNAFKrsqoqHpgyLSbMnZt0lK2UrV0b1/3tqTixf784z+wNAIAGo9gAIJWa0iyNHZkwZ27MMHsDAKDBWL4dgNR5Yuarcd3fnmrypcYmm2ZvPDHz1aSjAAA0O2ZsAJAa2Ww2HnrxpXj0lRlJR9ktD0yZGhVVVfGJIYdFJpNJOg4AQLOg2IBmLltbHVWr3oj1K2bGuhUzYv2KmVFdsTSyNesjW1sVmbzCyOS3joKSrtG6w+Ao6nBwtO4wOAr3PiAyeZ4iaDqy2Wz8fvKUeOq1WUlH2SOPTn8l1m3YEBcMH6bcAACoB161QDOUzWZj3bKpUf76b2PtoqciW1O509tUVyyOdctfjPc/+DyTXxxtepwcpf0uiqJOR3gBRuIeevGl1Jcamzz12qwoatUqzj58SNJRAABST7EBzUjthrWxav7D8f7r90ZV+Zw92le2pjLWvP3nWPP2n6OwdECUHnhR7NXnrMhr1aae0kLdPTHz1dQefrI9j05/JUoKC+O0wYOSjgIAkGoWD4VmYvWCJ2L+oyNi2ZTv7HGp8WFV5bPjvSnfjvmPjojVC56o133Dzry6eHE8MGVq0jEaxANTpsZri5ckHQMAINUUG5By1evKYsnEy2LpxC9EzbqyBh2rZl1ZLJ34hVgy8UtRs25Fg44FERGVVVVx58Tnko7RoO6YNCkqN2xIOgYAQGopNiDF1ix8MhY8fmqsWfB444674LF4+/FTYs3CJxt1XFqeB6ZOS80pXXdX2Zq18WAznZECANAYFBuQUuVz7oolz/5H1Kxv2Fka21OzviyWPPsfUT7n7kTGp/l7dfHimDBnbtIxGsX4OXMdkgIAsJsUG5BCK179ZSyb9v2kY0RExLJp18SKV3+ZdAyamZZwCMqHOSQFAGD3KDYgZcrn3BVl069LOsYWyqZfZ+YG9erBFnAIyoeVrVkbf5g6LekYAACpo9iAFFmz8MkmM1Pjw5ZNu8aaG9SLlRUV8czc15OOkYhn5syNlRUVSccAAEgVxQakRPW6snhv8reSjrFD7035lrOlsMeemTM3arPZpGMkoiabjX+20FIHAGB3KTYgJZZNvTqxhULrqmZdWbw39eqkY5Bi1bW1MWFuy1gwdHvGz5kT1bW1SccAAEgNxQakwOoFf2n0U7rurjULHovVC55IOgYp9dKChVFeUZl0jESVV1TGywsWJh0DACA1FBvQxNVuWBvLpl6VdIxdsmzqd6N2Q8ta+JH68fTs2UlHaBKenj0n6QgAAKmh2IAmbvX8R6JmXdM+BOXDataVxeq3H0k6BimzuLw8Zi1ZmnSMJuG1JUticfn7SccAAEiFBi02pk6dGt///vfjlFNOiR49ekTr1q2jbdu20a9fv7jkkkti4sSJDTk8pF42m43y1++t9/2uqaiNNxZVxfQ318cbi6piTUX9H89fPvfeyLbQBSDZPZPnzU86QpMyed68pCMAAKRCQUPt+IQTTohnn312q69XVVXF66+/Hq+//nrcfffdMXbs2LjtttuisLCwoaJAaq1bNjWqyutnan42m41/vbYufvfU6vj7tIqo2azLyM+LOHloSVxw0l5x5EFFkclk9ni8qvLZsW75tCjuPHSP90XLMG95umYmNbR5ZR4PAIC6aLBiY/HixRER0b179/jkJz8Zxx9/fPTq1Stqamri+eefj+uvvz7eeeed+M1vfhMbNmyI3//+9w0VBVKr/PXf1st+Xp23Pq64dXm8vmjDNq+vqY346+SK+OvkijiwR6v42ec6xaC+rfd43PK59yo2qJNsNhvzvZDfwtuKHgCAOmmwYmPAgAFx7bXXxtlnnx35+flbXHfUUUfFRRddFMcee2zMnTs37rvvvvjc5z4XJ5xwQkPFgdTJ1lbH2kVP7fF+Js2ojC/e8F5UrP+/w0L2iYhTIqJdRLwfEU9GxLsfXPf6og3x6R8sjf/5Wpc49uDiPRp77aKnIltbHZm8BnuqoZkor6iI9ytb9tlQPqy8sjJWVlRE+5KSpKMAADRpDbbGxmOPPRbnnnvuVqXGJp06dYrrr78+9/kf//jHhooCqVS16o3I1uzZC71X563fotQYEhEPRMSCiPhNRNz8wb8LIuL+D66PiKhYn40v3vBevDpv/R6Nn62pjKpVb+7RPmgZzNbYtvlmbQAA7FSiZ0UZOXJk7vKbb3rxA5tbv2LmHt0+m83GFbcuz5UaoyPiuYg4NyI+vKJNYUSc98H1Z33wtYr12bjy1uV7vADont4PWob5ZSuSjtAkKXwAAHYu0WJj/fr/ezd4ezM7oKVat2LGHt3+X6+ty62pMSQi7ouIop3cpii2nLkxd9GGmDxr3R7l2NP7QcvgBfy2eVwAAHYu0WLjmWeeyV0eOHBggkmg6dnTmQ6///vq3OUrY+elxiZFEXHFdvazO8zYoC5WrF2bdIQmyeMCALBzia3oV1tbGz/5yU9yn5977rm7vI9Fixbt8PolS5bs8j6hqaiuWLrbt11TURtPTa2IiI0LhY7Zxdt/IiK6RMR7EfHklIpYU1EbbUt2rwetrvB7yM5tqK5JOkKTtKHG4wIAsDOJFRs33HBDTJ48OSIiPvGJT8QRRxyxy/vo2bNnfceCJiNbs/sLdy5dUR01tRsvnxJbr6mxM4URcWpE3BsbTwW7dGV1HFCyq3vZKFu7ZwuQ0jJ4Ab9tHhcAgJ1L5FCUZ555Jr7xjW9ERESXLl3illtuSSIGNGnZ2qrdvu3azU7t2m4397H35vtbt/sLiGZrdv9+0HJU19YmHaFJqq7xuAAA7Eyjz9h49dVXY8yYMVFdXR1FRUXxhz/8Ibp06bJb+1q4cOEOr1+yZEkMHz58t/YNScvk7d4MiYiINq0zucvv7+Y+Vm2+v6LMdrfbmUz+7t8PWo6CvESXfGqyCvI9LgAAO9Ooxca8efPilFNOiZUrV0Z+fn7cf//9ccIJJ+z2/nr06FGP6aBpyeS33u3bdu1QEPl5Gw8jeTIiqmLXDkepioi/fXC5ID+ia/vdf6rI5O3+/aDlaOXMWNvkcQEA2LlGeyto8eLFcdJJJ8XixYsjk8nEnXfeGWeddVZjDQ+pU1DSdbdv27YkL04eWhIREe9GxJ928fYPxcaFQyMiTh5astsLh0ZEFJR02+3b0nK0KvACflsUGwAAO9coxcby5cvj5JNPjrfeeisiIm6++eYYO3ZsYwwNqdW6w+A9uv0FJ+2Vu/zTiFhXx9tVRsTPtrOf3bGn94OWoUObNklHaJI8LgAAO9fgxcb7778fp556arz22msREfGTn/wkvvjFLzb0sJB6RR0O3qPbH3lQURzYo1VERLwUEZ+KnZcb6yLi/A+2j4jo16NVDB9YtEc59vR+0DL06dgx6QhNkscFAGDnGrTYqKioiI9//OPx4osvRkTEt7/97bjyyisbckhoNvZ0pkMmk4mffa5TlHywkOgjEXFMRDwQG9fQ2FxVRNz/wfWPfPC1ktaZ+OnnOkUms/sLh0aYsUHd9OnYIekITZJiAwBg5xps8dCqqqoYM2ZMTJo0KSIivvKVr8QPf/jDhhoOmp3CvQ+ITH5xZGsqd3sfg/q2jv/5Wpf44g3vRcX6bG7mxj4RcUpsPKXrqti4UOh7m92upHUm/udrXWJQ3z1b+DOTXxyFe++/R/ugZfACftv6dPK4AADsTIMVG+eff348+eSTERExatSouPTSS2PmzJnb3b6wsDD69evXUHEgdTJ5BdGmx8mx5u0/79F+jj24OH733a5xxa3L4/VFGyJi44Ki925n+349WsVPP9dpj0uNiIg2PU6OTF6jn1WaFCotKYl2xcXxfuXuF3nNTWlxcbQvKUk6BgBAk9dgrzgeeuih3OWnn346DjnkkB1u37t375g/f35DxYFUKj3wwj0uNiI2ztx47CfdY/KsdfG7p1bHU1Mroqb2/64vyN949pMLTtorhg8s2uPDTzYp7XdRveyH5i+TyUSfjh1j+qJFSUdpMnqbrQEAUCfeSoUmrKjz0CgsHRBV5bP3eF+ZTCaOPKg4jjyoONZU1MbSldWxdl022hRlomv7gj06peu2FJYOjKJOR9TrPmne+nZSbGyur8NzAADqpMEWD81ms7v0YbYGbC2TyUTpgfU/66FtSV4csG9hHLp/6zhg38J6LzUiIkr7XVhvMz9oGYb37Zt0hCblyP08HgAAddHgp3sF9sxefc6K/KJ0vXObX9Qx9up9VtIxSJnupe1iYLeuScdoEg7q1i26tWuXdAwAgFRQbEATl9eqTXQe+oOkY+ySLsN+GHmt2iQdgxQaNWBA0hGahFED+icdAQAgNRQbkAJ79Tot2vb6eNIx6qRtr9Ojbc+PJh2DlBrSq2eUlhQnHSNRpSXFMaRXz6RjAACkhmIDUqLz0Gsiv3XTPiQlv6hjdBl6TdIxSLGCvLw4sYWf+ntk//6Rn+e/ZwCAuvKXE6REQVHH6DL82qRj7FCXYddGflGHpGOQciP694u8FrrwbH4mEyf0OzDpGAAAqaLYgBRp2/OU6HzEVUnH2KbOR1wdbXueknQMmoH2JSUxooW+uB/Rv1+0LylJOgYAQKooNiBlSvtfEh0P/XrSMbbQ8dArorT/xUnHoBk5d+gR0bFNy1qAtmPbNvHJoUckHQMAIHUUG5BCHQZ9ITofcXXSMSIiovMR34sOgz6fdAyameLCwvjMccckHaNRXXrssVHcqlXSMQAAUkexASlV2v/i6Hb8rxJbUDS/qGN0O/5XUdp/XCLj0/wN6t49TuzfMhYSHdm/XxzUvVvSMQAAUkmxASnWtucp0fvjT0bbXqc37ri9z4jeH3vSmho0uPNawCEpHdu2iXOHDU06BgBAaik2IOXyizpEt+Nujq7H/TLyixp29sbGWRq3RLdjb3L2ExpFSzgkxSEoAAB7piDpAED92KvXadGm2wmxev4jUf76vVFVPrve9l1YOiBK+10Ue/U+K/JaNe93z2l6BnXvHucNGxoPTJmadJR696lhQx2CAgCwhxQb0IzktWoT7Q68IPY+4PxYt3xalM+9N9YueiqyNZW7vK9MfnG07XFKtOt3URR1OjwymUwDJIa6OW3woKhYvz4efWVG0lHqzRmHHhIfHTwo6RgAAKmn2IBmKJPJRHHnoVHceWhka6ujatWbsX7FzFi3YkasXzEzqiuWRLZ2fWRrqiKTXxiZvNZRUNItWncYHEUdDo7WHQZH4d77RybPUwRNxycOHxLrqqvjqddmJR1lj5180MD4xJDDko4BANAseNUCzVwmryBal/aP1qX9Y+/9zk46Duy2TCYTFwwfFkWtWsWj019JOs5uO/PQQ2LMkMPMggIAqCeKDQBSI5PJxNmHD4mSwsJUrrlx3rChcZrDTwAA6pViA4DUOW3woOjdoUPcMXFSlK1dm3ScnerYtk1ceuyxFgoFAGgATvcKQCod1L1b/HDMWXFi/35JR9mhkf37xQ9Hn6XUAABoIGZsAJBaxa1axcXHHB3D+vSOOyc+16Rmb5ilAQDQOMzYACD1BnXvHj8cc1aMGtA/8hJelDM/k4lRA/qbpQEA0EjM2ACgWShu1SrGHn1UnHHoIfHMnLkxYe7cKK+obLTxS0uKY2T//nFCvwOjfUlJo40LANDSKTYAaFbal5TE6CGHxemHHhIvLVgYT8+eHbOWLG2w8Q7q1i1GDegfh/XqGQV5JkICADQ2xQYAzVJBXl4M69M7hvXpHYvL34/J8+bFvLKymL+8LN6v3P2ZHKXFxdG7U8fo27FjDO/bN7qXtqvH1AAA7CrFBgDNXvfSdjF6yGG5z1dWVMT85WUxv2zjx4q1a2NDTU1sqKmJ6praKMjPi1b5+dEqPz86tGkTfTp23PjRqaPDTAAAmhjFBgAtTvuSkmjfqySG9OqZdBQAAPaQg4EBAACA1FJsAAAAAKml2AAAAABSS7EBAAAApJZiAwAAAEgtxQYAAACQWooNAAAAILUUGwAAAEBqKTYAAACA1FJsAAAAAKml2AAAAABSS7EBAAAApJZiAwAAAEgtxQYAAACQWooNAAAAILUUGwAAAEBqKTYAAACA1FJsAAAAAKml2AAAAABSS7EBAAAApJZiAwAAAEgtxQYAAACQWooNAAAAILUUGwAAAEBqKTYAAACA1FJsAAAAAKml2AAAAABSS7EBAAAApJZiAwAAAEgtxQYAAACQWooNAAAAILUUGwAAAEBqKTYAAACA1FJsAAAAAKml2AAAAABSS7EBAAAApJZiAwAAAEgtxQYAAACQWooNAAAAILUUGwAAAEBqKTYAAACA1FJsAAAAAKml2AAAAABSS7EBAAAApJZiAwAAAEgtxQYAAACQWooNAAAAILUUGwAAAEBqKTYAAACA1FJsAAAAAKml2AAAAABSS7EBAAAApJZiAwAAAEgtxQYAAACQWooNAAAAILUUGwAAAEBqKTYAAACA1FJsAAAAAKml2AAAAABSS7EBAAAApJZiAwAAAEgtxQYAAACQWooNAAAAILUUGwAAAEBqKTYAAACA1FJsAAAAAKml2AAAAABSS7EBAAAApJZiAwAAAEgtxQYAAACQWooNAAAAILUUGwAAAEBqKTYAAACA1FJsAAAAAKml2AAAAABSS7EBAAAApFZB0gGAhpPNZqO8oiLml5XF/LIVMb+sLFasXRsbqmtiQ01NVNfWRkFeXrTKz49WBfnRoU2b6NOxY/Tp2CH6dOoU7UtKkr4LAAAAO6TYgGZmcfn7MXnevJi3vCzmlS2PVZXr6nzbhStWxvSFi3Kftysujj4dO0bfTh1jeN++0b20XUNEBgAA2G2KDWgGqmtr46UFC+LpWXNi1tKl9bbf9ysrY/qiRTF90aJ4+OXpMbBb1xg1YEAM6dUzCvIcyQYAACRPsQEptnLt2pgw9/V4Zs7cKK+sbPDxZi1ZGrOWLI3SkuI4sV+/GNG/n8NVAACARCk2IIUqq6riwanT4pm5r0dtNtvo45dXVMbDL0+PP09/JUb0OzDOHTY0ilu1avQcAAAAig1ImVcXL447Jz4XZWvXJh0larPZGD9nbryy6J34zHHHxKDu3ZOOBAAAtDCKDUiJyqqqeGDKtJgwd27SUbZStnZtXPe3p+LE/v3iPLM3AACARqTYgBRoSrM0dmTCnLkxw+wNAACgETmtATRxT8x8Na7721NNvtTYZNPsjSdmvpp0FAAAoAUwYwOaqGw2Gw+9+FI8+sqMpKPslgemTI2Kqqr4xJDDIpPJJB0HAABopszYgCYom83G7ydPSW2pscmj01+J30+eEtkEztwCAAC0DIoNaIIeevGleOq1WUnHqBdPvTYrHnrp5aRjAAAAzZRiA5qYJ2a+mvqZGh/26PRXrLkBAAA0CMUGNCGvLl4cD0yZmnSMBvHAlKnx2uIlSccAAACaGcUGNBGVVVVx58Tnko7RoO6YNCkqN2xIOgYAANCMKDagiXhg6rTUnNJ1d5WtWRsPNtMZKQAAQDIUG9AEvLp4cUyYMzfpGI1i/Jy5DkkBAADqjWIDEtYSDkH5MIekAAAA9UWxAQl7sAUcgvJhZWvWxh+mTks6BgAA0AwoNiBBKysq4pm5rycdIxHPzJkbKysqko4BAACknGIDEvTMnLlRm80mHSMRNdls/LOFljoAAED9UWxAQqpra2PC3JaxYOj2jJ8zJ6pra5OOAQAApJhiAxLy0oKFUV5RmXSMRJVXVMbLCxYmHQMAAEgxxQYk5OnZs5OO0CQ8PXtO0hEAAIAUU2xAAhaXl8esJUuTjtEkvLZkSSwufz/pGAAAQEo1aLHx3nvvxWOPPRZXXXVVnHbaadGpU6fIZDKRyWTi4osvbsihoUmbPG9+ouNXVVZG+TvvxLK33oryd96JqspkD4mZPG9eouMDAADpVdCQO99nn30acveQWvOWlzX6mNlsNpbOnh1znv5HLHjpxchutmhnJi8veh1+ePQf+ZHoOmBAZDKZRs02r6zxHw8AAKB5aNBiY3O9evWKAQMGxJNPPtlYQ0KTlM1mY34jv5Ave3t+TLz9tih/551tZ6qtjbenTo23p06N0n33jeP+7d+jY+8+jZbv7QSKHgAAoHlo0GLjqquuimHDhsWwYcNin332ifnz50ffvn0bckho8sorKuL9Rjz0Y/GrM2P8f98c1evX5762T0ScEhHtIuL9iHgyIt7dlO+dd+KvP/lxjLzsS9F90OBGyVheWRkrKyqifUlJo4wHAAA0Hw1abFxzzTUNuXtIpcacrVH29vwtSo0hEfGNiBgdEYWbbVcVEX+KiJ9GxEsRUb1+fYz/75vjo9/4ZqPN3Ji/vCza91JsAAAAu8ZZUaCRzS9b0SjjZLPZmHj7bblSY3REPBcR58aWpUZ88Pl5H1x/1gdfq16/Pibefntks9lGydvYh+cAAADNg2IDGlljvYBfOnt2bk2NIRFxX0QU7eQ2RRFx/wfbR0SUv7Mo3p0zu8Eybk6xAQAA7A7FBjSyFWvXNso4c8b/I3f5yth5qbFJUURcsdnns59+uh5TbV9jPS4AAEDz0mhnRWkIixYt2uH1S5YsaaQkUHcbqmsafIyqyspY8OKLEbFxodAxu3j7T0REl4h4LyIWvDgtqioro7C4uH5DfsiGmoZ/XAAAgOYn1cVGz549k44Au6wxXsBXrFgR2draiNh49pMPr6mxM4URcWpE3BsbTwVbsXKlYgMAAGiSHIoCjaz6g8KhIW3Y7NSu7XZzH3tvvr916/YoT11U1zT84wIAADQ/qZ6xsXDhwh1ev2TJkhg+fHgjpYG6Kchr+D6xVevWucvv7+Y+Vm2+v6K6rtCx+wry9awAAMCuS3Wx0aNHj6QjwC5rlZ/f4GOUdOgQmby8yNbWxpMRURW7djhKVUT87YPLmfz8KGnfvt4zflhjPC4AAEDz4y1SaGStChr+BXxhcXH0OvzwiIh4NyL+tIu3fyg2LhwaEdFryOENvr5GhGIDAADYPYoNaGQd2rRplHH6j/xI7vJPI6Kuq2RURsTPNvt8wKhR9Zhq+xrrcQEAAJoXxQY0sj4dOzbKOF0HDIjSffeNiIiXIuJTsfNyY11EnP/B9hERpfv2iH36D2iwjJtrrMcFAABoXhQb0Mj6dOzQKONkMpk47t/+PQo+WEj0kYg4JiIeiI1raGyuKiLu/+D6Rz74WkHr1nHcv/1bZDKZRsmr2AAAAHaHYgMaWWO+gO/Yu0+MvOxLuXJj08yNXhExNiIu++DfnrHlTI2C1q1j5GVfio69+zRa1j6dFBsAAMCua9CzokycODHeeOON3OfLly/PXX7jjTfi7rvv3mL7iy++uCHjQJNQWlIS7YqL4/3KykYZr/ugwfHRb3wzJt5+W5S/805EbFxQ9N7t5du3Rxz3b//WqKVGaXFxtC8pabTxAACA5qNBi43bb7897rnnnm1eN2nSpJg0adIWX1Ns0BJkMpno07FjTF+0qNHG7Ni7T5z5/R/Gu3Nmx+yn/xELXnwxsrW1/5cpPz96DTk8BowaFfv0H9Boh59s0ttsDQAAYDc1aLEBbFvfTo1bbERsLFS6DhgYXQcMjKrKyqhYuTI2rFsXrYqKoqR9+0Y5pev29LW+BgAAsJsadI2Nu+++O7LZbJ0/oKUY3rdvouMXFhdHaffu0Xm//aK0e/dES42IiCP3S/bxAAAA0svioZCA7qXtYmC3rknHaBIO6tYturVrl3QMAAAgpRQbkJBRAwYkHaFJGDWgf9IRAACAFFNsQEKG9OoZpSXJHgKStNKS4hjSq2fSMQAAgBRTbEBCCvLy4sR+/ZKOkaiR/ftHfp6nIQAAYPd5RQEJGtG/X+Q18qlVm4r8TCZO6Hdg0jEAAICUU2xAgtqXlMSIFvrifkT/ftG+pCTpGAAAQMopNiBh5w49Ijq2aZN0jEbVsW2b+OTQI5KOAQAANAOKDUhYcWFhfOa4Y5KO0aguPfbYKG7VKukYAABAM6DYgCZgUPfucWL/lrGQ6Mj+/eKg7t2SjgEAADQTig1oIs5rAYekdGzbJs4dNjTpGAAAQDOi2IAmoiUckuIQFAAAoL4pNqAJGdS9e5zXTGc0fGrYUIegAAAA9U6xAU3MaYMHxRmHHJx0jHp1xqGHxEcHD0o6BgAA0AwpNqAJ+sThQ+LkgwYmHaNenHzQwPjEkMOSjgEAADRTBUkHALaWyWTiguHDoqhVq3h0+itJx9ltZx56SIwZclhkMpmkowAAAM2UYgOaqEwmE2cfPiRKCgvjgSlTk46zy84bNjROc/gJAADQwBQb0MSdNnhQ9O7QIe6YOCnK1q5NOs5OdWzbJi499lgLhQIAAI3CGhuQAgd17xY/HHNWnNi/X9JRdmhk/37xw9FnKTUAAIBGY8YGpERxq1Zx8TFHx7A+vePOic81qdkbZmkAAABJMWMDUmZQ9+7xwzFnxagB/SMv4UU58zOZGDWgv1kaAABAYszYgBQqbtUqxh59VJxx6CHxzJy5MWHu3CivqGy08UtLimNk//5xQr8Do31JSaONCwAA8GGKDUix9iUlMXrIYXH6oYfESwsWxtOzZ8esJUsbbLyDunWLUQP6x2G9ekZBnglfAABA8hQb0AwU5OXFsD69Y1if3rG4/P2YPG9ezCsri/nLy+L9yt2fyVFaXBy9O3WMvh07xvC+faN7abt6TA0AALDnFBvQzHQvbRejhxyW+3xlRUXMX14W88s2fqxYuzY21NTEhpqaqK6pjYL8vGiVnx+t8vOjQ5s20adjx40fnTo6zAQAAGjyFBvQzLUvKYn2vUpiSK+eSUcBAACodw6SBwAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRQbAAAAQGopNgAAAIDUUmwAAAAAqaXYAAAAAFJLsQEAAACklmIDAAAASC3FBgAAAJBaig0AAAAgtRqt2Hj77bfj8ssvjwEDBkSbNm2iQ4cOMWzYsLjuuuuioqKisWIAAAAAzUhBYwzy6KOPxoUXXhirVq3Kfa2ioiKmTp0aU6dOjdtvvz0ef/zxOOCAAxojDgAAANBMNPiMjZdeeinOO++8WLVqVbRt2zZ+9KMfxXPPPRf/+Mc/4t///d8jImLu3Lnx8Y9/PFavXt3QcQAAAIBmpMFnbHzlK1+JysrKKCgoiCeffDKOPvro3HWjRo2KAw88MK644oqYO3duXH/99fG9732voSMBAAAAzUSDztiYPHlyPPvssxERcemll25Ramxy+eWXx8CBAyMi4sYbb4wNGzY0ZCQAAACgGWnQYuPhhx/OXb7kkku2HSAvL8aOHRsREeXl5TF+/PiGjAQAAAA0Iw1abEycODEiItq0aRNHHHHEdrcbMWJE7vKkSZMaMhIAAADQjDRosTFr1qyIiDjggAOioGD7y3kMGDBgq9sAAAAA7EyDLR66bt26WL58eURE9OjRY4fbtm/fPtq0aRNr166NhQsX1nmMRYsW7fD6zfe1ZMmSOu8XAAAAqLvNX3NXV1c36tgNVmxsfurWtm3b7nT7TcXGmjVr6jxGz54967zt8OHD67wtAAAAsHuWLVsWffr0abTxGuxQlHXr1uUuFxYW7nT71q1bR0REZWVlQ0UCAAAAGti7777bqOM12IyNoqKi3OWqqqqdbr9+/fqIiCguLq7zGDs7bGXevHlxwgknRETEc889t0szPKA5W7JkSW4W0+TJk6Nbt24JJ4Lk+b2Arfm9gG3zuwFbW7hwYRxzzDERseU6mo2hwYqNvfbaK3e5LoeXrF27NiLqdtjKJjtbu2NzPXv23KXtoaXo1q2b3w34EL8XsDW/F7Btfjdga5tPdGgMDXYoSlFRUXTs2DEidr7I58qVK3PFhlkVAAAAQF016OleDzrooIiIeOONN3a4Kurs2bNzlwcOHNiQkQAAAIBmpEGLjeOOOy4iNh5mMm3atO1u98wzz+QuH3vssQ0ZCQAAAGhGGrTYGD16dO7yXXfdtc1tamtr4ze/+U1ERJSWlsbIkSMbMhIAAADQjDRosTF8+PA4/vjjIyLijjvuiOeff36rba6//vqYNWtWRER85StfiVatWjVkJAAAAKAZabCzomxy4403xrHHHhuVlZVxyimnxLe+9a0YOXJkVFZWxv333x+//vWvIyKiX79+cfnllzd0HAAAAKAZafBiY8iQIfHAAw/EhRdeGKtWrYpvfetbW23Tr1+/ePzxx7c4RSwAAADAzmSy2Wy2MQZ6++2348Ybb4zHH388Fi1aFIWFhXHAAQfEJz/5ybjsssuipKSkMWIAAAAAzUijFRsAAAAA9a1BFw8FAAAAaEiKDQAAACC1FBsAAABAaik2AAAAgNRSbAAAAACppdgAAAAAUkuxAQAAAKSWYgMAAABIrWZbbLz99ttx+eWXx4ABA6JNmzbRoUOHGDZsWFx33XVRUVGRdDxoVO+991489thjcdVVV8Vpp50WnTp1ikwmE5lMJi6++OKk40Eipk6dGt///vfjlFNOiR49ekTr1q2jbdu20a9fv7jkkkti4sSJSUeERrdq1aq4//774/LLL48RI0bEAQccEO3atYvCwsLo0qVLnHjiifGzn/0sysrKko4KTcKVV16Z+5sqk8nEhAkTko4EjWrzn/8dfZx44okNmyObzWYbdIQEPProo3HhhRfGqlWrtnl9v3794vHHH48DDjigkZNBMjKZzHavGzduXNx9992NFwaagBNOOCGeffbZnW43duzYuO2226KwsLARUkHy/v73v8fJJ5+80+06deoUv/3tb+PUU09thFTQNL388ssxbNiwqK6uzn1t/PjxDf4CDpqSHb3O2NyIESMatPgraLA9J+Sll16K8847LyorK6Nt27bxzW9+M0aOHBmVlZVx//33x2233RZz586Nj3/84zF16tTYa6+9ko4MjapXr14xYMCAePLJJ5OOAolZvHhxRER07949PvnJT8bxxx8fvXr1ipqamnj++efj+uuvj3feeSd+85vfxIYNG+L3v/99womh8fTs2TNGjhwZRxxxRPTs2TO6desWtbW1sWjRovjjH/8YDz30UCxfvjzOPPPMmDx5chx66KFJR4ZGV1tbG5/97Gejuro6unTpEu+9917SkSBRn//85+MLX/jCdq9v06ZNg47f7IqNr3zlK1FZWRkFBQXx5JNPxtFHH527btSoUXHggQfGFVdcEXPnzo3rr78+vve97yUXFhrJVVddFcOGDYthw4bFPvvsE/Pnz4++ffsmHQsSM2DAgLj22mvj7LPPjvz8/C2uO+qoo+Kiiy6KY489NubOnRv33XdffO5zn4sTTjghobTQeEaOHBkLFizY7vXnnntuPPzwwzFmzJioqqqKa665Jh566KFGTAhNw0033RRTpkyJAQMGxJgxY+LHP/5x0pEgUV26dInBgwcnNn6zWmNj8uTJuanFl1566RalxiaXX355DBw4MCIibrzxxtiwYUOjZoQkXHPNNXH66afHPvvsk3QUaBIee+yxOPfcc7cqNTbp1KlTXH/99bnP//jHPzZWNEjU9n4nNjd69Ojo379/RESdDumC5mbBggXx3e9+NyIibr31VocrQhPQrIqNhx9+OHf5kksu2eY2eXl5MXbs2IiIKC8vj/HjxzdGNABSZuTIkbnLb775ZoJJoOnZdCjvunXrEk4Cje+LX/xirFmzJsaNGxcjRoxIOg4QzazY2LSCfZs2beKII47Y7nabPwFNmjSpwXMBkD7r16/PXa7Lu9jQUsyZMydefvnliNh4WBe0JA8++GA89thj0aFDh/j5z3+edBzgA82q2Jg1a1ZERBxwwAFRULD95UM2/094020AYHPPPPNM7vKmQxihpaqoqIjXX389fvGLX8SIESNyZ4H46le/mmwwaETl5f+/vXsLibJbwDj+iOXnKTIqg9IyNQkx8CID0yIri8hSEyWjUhC6KE1CKKmLjKLsIky60KTDKASiUYEYlVANJkJQQUcvJi1SURrzS/OAie4LaahdWRv2+M47/n8grJlZ+D544YyP71rrX+Xn50uSzp49q3nz5hmcCHAdtbW1ioyMlK+vr2bNmqVly5YpKytrylZIuM3mocPDw7Lb7ZKkoKCgSefOmTNHfn5+GhgY0IcPH6YiHgDARMbGxlRcXOx4nJGRYWAawBgWi+W3S3slqbCwULt27ZrCRICxDh8+rK6uLsXFxSknJ8foOIBLef369Q+PbTabbDabqqqqlJKSIovFotmzZzvt+m5TbPT39zvG/v7+f5z/rdj48uWLM2MBAEyopKREjx8/liTt2LFj0uWNwHQTHR2tiooKxcTEGB0FmDKNjY26dOmSZsyYofLycnl4eBgdCXAJvr6+2r59uzZs2KDly5fL399fHz9+lNVqVXl5uXp6enTr1i0lJyeroaFBM2fOdEoOtyk2vt+86m92Jv7nn38kSUNDQ07LBAAwH6vVqsLCQkkTR5eVlZUZnAgwRkpKilauXClp4vPS27dvVVNTo5s3byozM1Pnz59XUlKSwSkB5xsZGdG+ffs0Pj6uQ4cOGXqkJeBqOjo6FBAQ8NPziYmJysvL05YtW/Ts2TNZrVaVlZXp4MGDTsnhNntseHt7O8YjIyN/nP9tUzgfHx+nZQIAmMurV6+Umpqq0dFReXt7q7a2VoGBgUbHAgwREBCgqKgoRUVFKSYmRjt37tSNGzdUVVWl1tZWJScny2KxGB0TcLrTp0+rpaVFixcv1vHjx42OA7iUX5Ua3yxYsEDXr1933KVx4cIFp+Vwm2Lj27Fjkv5qecnAwICkv1u2AgBwf21tbdq0aZN6e3vl6emp6upqrV271uhYgMvZs2eP0tPTNTY2ptzcXH369MnoSIDTtLS06MyZM5Im/ijz8/MzOBFgLqGhoUpMTJQ0se9GZ2enU67jNktRvL29NXfuXPX09Ki9vX3Sub29vY5iIzg4eCriAQBcWGdnpzZu3KjOzk55eHjoypUrSk5ONjoW4LKSk5NVU1OjgYEB3blzh01E4bZKSko0MjKi0NBQDQ4Oqrq6+qc5L1++dIzv37+vrq4uSdK2bdsoQgBJkZGRun37tqSJpSsLFy78v1/DbYoNaeIH1tjYKJvNptHR0d8e+drS0uIYc4QfAExvdrtdiYmJam1tlTTxH7m9e/canApwbfPnz3eM379/b2ASwLm+LV9vbW1VZmbmH+efPHnSMW5ra6PYAKQp2WzXbZaiSFJ8fLykiWUmT548+e08q9XqGMfFxTk9FwDANX3+/FmbN292HFFWXFysAwcOGJwKcH0dHR2OMct6AQCT+f4oWGfcrSG5WbGRkpLiGF+9evWXc8bGxlRVVSVpYqOThISEqYgGAHAxg4OD2rp1q54+fSpJOnbsmI4cOWJwKsAcamtrHeMVK1YYmARwLovFovHx8Um/vt9Q9MGDB47nQ0JCjAsOuIi2tjY1NDRIksLCwrRo0SKnXMetio1Vq1ZpzZo1kqTLly+rubn5pznnzp3TmzdvJEn5+flOO0cXAOC6RkZGlJqaqqamJkkT7wenTp0yOBVgPIvFouHh4UnnlJSUONZKL1261PHZCwAwvdTV1Wl0dPS3r3d3dystLc1xaun+/fudlsWt9tiQpNLSUsXFxWloaEibNm3S0aNHlZCQoKGhIVVXV6uiokKSFBERoYKCAoPTAlPj0aNHstlsjsd2u90xttlsPx3Xl52dPUXJAGNkZmbq3r17kqT169crJyfnh83f/puXl5ciIiKmKh5gmKKiIhUUFCgtLU3x8fEKCwuTv7+/+vv79eLFC127ds1RCHp5eamiokKenp4GpwYAGCEvL09fv35VWlqaYmNjFRISIh8fH9ntdj18+FAXL150/N0RHx/v1OW+HuPj4+NO++4Gqaur0+7du9XX1/fL1yMiIlRfX6/w8PApTgYYIzs7W5WVlX893w1/LQA/+F83sVqyZInevXvnnDCACwkJCfmrzUCDgoJ05coVxxF+wHRWVFSkEydOSJpYirJu3TpjAwFT5G/fM9LS0nTp0iUFBAQ4LYvb3bEhTRyt9Pz5c5WWlqq+vl7t7e3y8vJSeHi40tPTlZubK19fX6NjAgAAuJS7d++qvr5eTU1Nstls6u7uVk9Pj3x8fBQYGKjo6GglJSUpIyODz1IAMM1VVlbKarWqublZra2tstvt6uvrk7+/v4KDg7V69WplZWUpNjbW6Vnc8o4NAAAAAAAwPbjV5qEAAAAAAGB6odgAAAAAAACmRbEBAAAAAABMi2IDAAAAAACYFsUGAAAAAAAwLYoNAAAAAABgWhQbAAAAAADAtCg2AAAAAACAaVFsAAAAAAAA06LYAAAAAAAApkWxAQAAAAAATItiAwAAAAAAmBbFBgAAAAAAMC2KDQAAAAAAYFoUGwAAAAAAwLQoNgAAAAAAgGlRbAAAAAAAANOi2AAAAAAAAKZFsQEAAAAAAEyLYgMAAAAAAJgWxQYAAAAAADAtig0AAAAAAGBaFBsAAAAAAMC0KDYAAAAAAIBpUWwAAAAAAADT+g+M5UYtp0J6KAAAAABJRU5ErkJggg==",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -972,94 +865,121 @@
      "metadata": {
       "image/png": {
        "height": 434,
-       "width": 572
+       "width": 539
       }
      },
      "output_type": "display_data"
     }
    ],
    "source": [
-    "plt.scatter(*zip(*fp.points[:4], strict=True), s=600, color=\"cadetblue\", zorder=1)\n",
-    "plt.scatter(*zip(*fp.points[4:], strict=True), s=300, color=\"goldenrod\", zorder=2)\n",
+    "plt.scatter(*zip(*fp.points[:3], strict=True), s=600, color=\"cadetblue\", zorder=1)\n",
+    "plt.scatter(*zip(*fp.points[3:], strict=True), s=300, color=\"goldenrod\", zorder=2)\n",
     "plt.scatter(*zip(a, b, strict=True), color=\"red\", ec=\"k\", zorder=3)\n",
-    "plt.xlim(0, 20)\n",
-    "plt.ylim(0, 20)\n",
+    "plt.xlim(0, 5)\n",
+    "plt.ylim(0, 5)\n",
     "plt.title(f\"Closest pair is {dist:.2} units apart.\");"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "aa581029-388f-4b6b-ac0e-0cd4e39aedcd",
+   "id": "bbc0a040-967c-4d3d-8ee2-e72bee6973c9",
    "metadata": {},
    "source": [
-    "Add another 4 2D points and query again."
+    "### Append several more points\n",
+    "\n",
+    "Add 3 more 2D points with the `+=` operator and query again."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
-   "id": "9cf2120b-3f9c-47a7-9398-72d5c41605b3",
+   "execution_count": 23,
+   "id": "100f2b17-9c34-4d43-9e21-f293744fcb68",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:48.222902Z",
-     "iopub.status.busy": "2024-06-12T02:00:48.222831Z",
-     "iopub.status.idle": "2024-06-12T02:00:48.225882Z",
-     "shell.execute_reply": "2024-06-12T02:00:48.225687Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:48.222895Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.874275Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.874202Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.876386Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.876170Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.874268Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "fp += (4, 1)\n",
+    "fp += (1, 4)\n",
+    "fp += (4, 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "28a6a37e-c8fa-423d-80b2-3fd85c25a2e6",
+   "metadata": {},
+   "source": [
+    "#### Query the closest pair"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "3c729bbd-6e6d-4e1d-bc04-e8bbdb81c9a7",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:33.876768Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.876686Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.878895Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.878683Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.876760Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(1.0, ((8, 10), (9, 10)))"
+       "(1.0, ((1, 2), (1, 1)))"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "for p in range(4):\n",
-    "    fp += tuple(*random_points(p + 2**p, (2), 1))\n",
-    "\n",
     "dist, (a, b) = fp.closest_pair()\n",
     "dist, (a, b)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "dab306cd-c44a-4212-8117-f395d20b9977",
+   "id": "b7febaf1-3b5a-4c7f-98ff-a17b52b0c035",
    "metadata": {},
    "source": [
-    "The closest pair has once again been updated!\n",
+    "The closest pair remains `(1, 2), (1, 1))` since no closer points were added.\n",
     "\n",
-    "Vizualize the current set.\n",
+    "#### Visualize\n",
     "\n",
-    "* 4 initial points in `\"cadetblue\"`\n",
-    "* First set of 4 additional points in `\"goldenrod\"`\n",
-    "* Second set of 4 additional points in `\"darkolivegreen\"`\n",
+    "* 3 initial points in `\"cadetblue\"`\n",
+    "* First set of 3 additional points in `\"goldenrod\"`\n",
+    "* Second set of 3 additional points in `\"darkolivegreen\"`\n",
     "* Current closest pair in `\"red\"`"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
-   "id": "0255e23a-180c-4a17-a386-e8e3206dd9f5",
+   "execution_count": 25,
+   "id": "1a071985-2d07-4473-a5a4-5c2ab151139d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-12T02:00:48.226275Z",
-     "iopub.status.busy": "2024-06-12T02:00:48.226215Z",
-     "iopub.status.idle": "2024-06-12T02:00:48.319771Z",
-     "shell.execute_reply": "2024-06-12T02:00:48.319561Z",
-     "shell.execute_reply.started": "2024-06-12T02:00:48.226269Z"
+     "iopub.execute_input": "2024-06-15T18:59:33.879285Z",
+     "iopub.status.busy": "2024-06-15T18:59:33.879227Z",
+     "iopub.status.idle": "2024-06-15T18:59:33.963223Z",
+     "shell.execute_reply": "2024-06-15T18:59:33.962995Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:33.879279Z"
     }
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1067,19 +987,19 @@
      "metadata": {
       "image/png": {
        "height": 434,
-       "width": 572
+       "width": 539
       }
      },
      "output_type": "display_data"
     }
    ],
    "source": [
-    "plt.scatter(*zip(*fp.points[:4], strict=True), s=600, color=\"cadetblue\", zorder=1)\n",
-    "plt.scatter(*zip(*fp.points[4:-4], strict=True), s=300, color=\"goldenrod\", zorder=2)\n",
-    "plt.scatter(*zip(*fp.points[-4:], strict=True), s=100, color=\"darkolivegreen\", zorder=3)\n",
-    "plt.scatter(*zip(a, b, strict=True), color=\"red\", ec=\"k\", zorder=4)\n",
-    "plt.xlim(0, 20)\n",
-    "plt.ylim(0, 20)\n",
+    "plt.scatter(*zip(*fp.points[:3], strict=True), s=600, color=\"cadetblue\", zorder=1)\n",
+    "plt.scatter(*zip(*fp.points[3:-3], strict=True), s=300, color=\"goldenrod\", zorder=2)\n",
+    "plt.scatter(*zip(*fp.points[-3:], strict=True), s=100, color=\"darkolivegreen\", zorder=3)\n",
+    "plt.scatter(*zip(a, b, strict=True), color=\"red\", ec=\"k\", zorder=3)\n",
+    "plt.xlim(0, 5)\n",
+    "plt.ylim(0, 5)\n",
     "plt.title(f\"Closest pair is {dist:.2} units apart.\");"
    ]
   },
diff --git a/notebooks/n-dimensional_pointsets.ipynb b/notebooks/n-dimensional_pointsets.ipynb
new file mode 100644
index 0000000..cb470f5
--- /dev/null
+++ b/notebooks/n-dimensional_pointsets.ipynb
@@ -0,0 +1,853 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "fc0bc877-aa93-40af-9b4a-4d9d89ded2b9",
+   "metadata": {},
+   "source": [
+    "# Querying Point Clouds\n",
+    "\n",
+    "1. Setup\n",
+    "2. 3-dimensional Points\n",
+    "3. Higher Dimensions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "2da42c3d-a668-456c-9d05-5b826d2ca963",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:19.800738Z",
+     "iopub.status.busy": "2024-06-15T18:59:19.800507Z",
+     "iopub.status.idle": "2024-06-15T18:59:19.832881Z",
+     "shell.execute_reply": "2024-06-15T18:59:19.832503Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:19.800703Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Last updated: 2024-06-15T14:59:19.824932-04:00\n",
+      "\n",
+      "Python implementation: CPython\n",
+      "Python version       : 3.12.3\n",
+      "IPython version      : 8.25.0\n",
+      "\n",
+      "Compiler    : Clang 16.0.6 \n",
+      "OS          : Darwin\n",
+      "Release     : 23.5.0\n",
+      "Machine     : arm64\n",
+      "Processor   : arm\n",
+      "CPU cores   : 8\n",
+      "Architecture: 64bit\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "%config InlineBackend.figure_format = \"retina\"\n",
+    "%load_ext watermark\n",
+    "%watermark"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "5f2c2691-2f11-4649-aafd-eaf734d5c368",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:19.833802Z",
+     "iopub.status.busy": "2024-06-15T18:59:19.833671Z",
+     "iopub.status.idle": "2024-06-15T18:59:20.062575Z",
+     "shell.execute_reply": "2024-06-15T18:59:20.062380Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:19.833784Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Watermark: 2.4.3\n",
+      "\n",
+      "fastpair  : 0.1.1.dev8+g5f8e7a5.d20240611\n",
+      "matplotlib: 3.9.0\n",
+      "numpy     : 1.26.4\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy\n",
+    "\n",
+    "import fastpair\n",
+    "\n",
+    "%watermark -w\n",
+    "%watermark -iv"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8f7e9080-ff0d-4a6d-8cdc-e7a7b4e71946",
+   "metadata": {},
+   "source": [
+    "---------------------------------\n",
+    "\n",
+    "## 1. Setup\n",
+    "\n",
+    "The following helper function will be used the generate random tuples of points in the example.\n",
+    "\n",
+    "* A reproducibile state can be set with the `seed` argument.\n",
+    "* Use the `size` argument to indicate the tuple dimensions.\n",
+    "* Set the `n` argument for the number of desired points\n",
+    "* `low` and `high` control for minimum and maximum values, respectively.\n",
+    "* The [desired distribution](https://numpy.org/doc/stable/reference/random/generator.html#numpy.random.default_rng) is set in `sample`. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "26917e2e-d996-469e-9028-3edd638ffe10",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:20.063748Z",
+     "iopub.status.busy": "2024-06-15T18:59:20.063563Z",
+     "iopub.status.idle": "2024-06-15T18:59:20.065445Z",
+     "shell.execute_reply": "2024-06-15T18:59:20.065238Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:20.063740Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "def random_points(\n",
+    "    seed: int = 0,\n",
+    "    size: int | tuple = (2),\n",
+    "    n: int = 1,\n",
+    "    low: int = 0,\n",
+    "    high: int = 20,\n",
+    "    sample: str = \"uniform\",\n",
+    ") -> list[tuple[float]]:\n",
+    "    rng = numpy.random.default_rng(seed)\n",
+    "    return [\n",
+    "        tuple(getattr(rng, sample)(low=low, high=high, size=size)) for i in range(n)\n",
+    "    ]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ea1a2cd7-7822-4fbc-af59-d1587dc72e9c",
+   "metadata": {},
+   "source": [
+    "Generate a single 1D point from seed `0`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "e7078d76-f6db-43c9-aff8-8c541ea385f9",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:20.065764Z",
+     "iopub.status.busy": "2024-06-15T18:59:20.065702Z",
+     "iopub.status.idle": "2024-06-15T18:59:20.068272Z",
+     "shell.execute_reply": "2024-06-15T18:59:20.068088Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:20.065758Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[(10.236432494005134,)]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "random_points(1, 1, 1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cc8f9d0e-fff0-4231-b650-c9f107c9e535",
+   "metadata": {},
+   "source": [
+    "Generate 3 2D points from seed `1`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "c9a81f46-a864-4d96-a9a3-9e801a8a6e42",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:20.068756Z",
+     "iopub.status.busy": "2024-06-15T18:59:20.068653Z",
+     "iopub.status.idle": "2024-06-15T18:59:20.070411Z",
+     "shell.execute_reply": "2024-06-15T18:59:20.070230Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:20.068750Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[(10.236432494005134, 19.009273926518706),\n",
+       " (2.8831922543926747, 18.972988942744877),\n",
+       " (6.236629040209709, 8.466528979451514)]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "random_points(1, (2), 3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9e864cfb-278f-46ac-b8e1-492c35ec2d15",
+   "metadata": {},
+   "source": [
+    "---------------------\n",
+    "\n",
+    "## 2. 3-dimensional Points\n",
+    "\n",
+    "Generate a random set of 4 3D points and build a `fastpair.FastPair` object."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "8a43ef42-621d-42b1-9ca6-cc1e5ec1d0b1",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:20.070857Z",
+     "iopub.status.busy": "2024-06-15T18:59:20.070765Z",
+     "iopub.status.idle": "2024-06-15T18:59:20.072578Z",
+     "shell.execute_reply": "2024-06-15T18:59:20.072408Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:20.070851Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<fastpair.base.FastPair at 0x11ef8ab10>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "points = random_points(101, (3), 4)\n",
+    "fp = fastpair.FastPair()\n",
+    "fp.build(points)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9e588a47-d9fa-46da-b95f-32985d168378",
+   "metadata": {},
+   "source": [
+    "### Explore the current state of the `fp` instance\n",
+    "\n",
+    "#### Query the closest pair"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "cccf5da4-94ad-46d6-89a6-17a1444ca15a",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:20.072982Z",
+     "iopub.status.busy": "2024-06-15T18:59:20.072923Z",
+     "iopub.status.idle": "2024-06-15T18:59:20.074833Z",
+     "shell.execute_reply": "2024-06-15T18:59:20.074665Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:20.072976Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(4.0502751383410684,\n",
+       " ((18.870650112211077, 7.188420666831464, 15.696108239399543),\n",
+       "  (17.38663089357139, 7.282768525810457, 19.463536292657878)))"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dist, (a, b) = fp.closest_pair()\n",
+    "dist, (a, b)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "83a56f4b-eab0-47a6-b957-762dcec14b6f",
+   "metadata": {},
+   "source": [
+    "The closest pair is `≈4.05` units apart.\n",
+    "\n",
+    "#### Visualize\n",
+    "* 3 initial points in `\"cadetblue\"`\n",
+    "* Current closest pair in `\"red\"`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "c8c7dd0d-20ca-43cd-b22a-c0308f203497",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:20.075343Z",
+     "iopub.status.busy": "2024-06-15T18:59:20.075222Z",
+     "iopub.status.idle": "2024-06-15T18:59:20.167579Z",
+     "shell.execute_reply": "2024-06-15T18:59:20.167365Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:20.075337Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "image/png": {
+       "height": 434,
+       "width": 572
+      }
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "_first_4 = numpy.array(list(zip(*fp.points, strict=True))).T[:, :2][:4].T\n",
+    "_closest = numpy.array(list(zip(a, b, strict=True))).T[:, :2].T\n",
+    "\n",
+    "plt.scatter(*_first_4, s=200, color=\"cadetblue\")\n",
+    "plt.scatter(*_closest, s=30, color=\"red\", ec=\"k\", alpha=0.9)\n",
+    "plt.xlim(0, 20)\n",
+    "plt.ylim(0, 20)\n",
+    "plt.title(f\"Closest pair is {dist:.3} units apart.\");"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "01f17f6c-8007-4641-982c-e2e0b7a2f2c5",
+   "metadata": {},
+   "source": [
+    "#### Append 3 points\n",
+    "\n",
+    "Add 3 3D points with the `+=` operator and query again."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "626ff3e1-727a-49ab-ad1b-91fd4eae5541",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:20.168108Z",
+     "iopub.status.busy": "2024-06-15T18:59:20.168036Z",
+     "iopub.status.idle": "2024-06-15T18:59:20.169974Z",
+     "shell.execute_reply": "2024-06-15T18:59:20.169784Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:20.168100Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "for p in range(4):\n",
+    "    fp += tuple(*random_points(p, (3), 1))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "81f3ea5b-b048-4c4d-ac43-33ef15cb0995",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:21:48.230037Z",
+     "iopub.status.busy": "2024-06-15T18:21:48.229330Z",
+     "iopub.status.idle": "2024-06-15T18:21:48.237899Z",
+     "shell.execute_reply": "2024-06-15T18:21:48.237244Z",
+     "shell.execute_reply.started": "2024-06-15T18:21:48.229982Z"
+    }
+   },
+   "source": [
+    "#### Query the closest pair"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "144bebae-d91b-432a-b048-6b4f6d7e68d5",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:20.170357Z",
+     "iopub.status.busy": "2024-06-15T18:59:20.170288Z",
+     "iopub.status.idle": "2024-06-15T18:59:20.172189Z",
+     "shell.execute_reply": "2024-06-15T18:59:20.171978Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:20.170350Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(3.738192198648357,\n",
+       " ((1.7129833428724872, 4.736210131921994, 16.025489304127937),\n",
+       "  (5.232242684986328, 5.969822868282466, 16.284514811885607)))"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dist, (a, b) = fp.closest_pair()\n",
+    "dist, (a, b)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c907b173-4992-4471-a881-1aac7532536f",
+   "metadata": {},
+   "source": [
+    "The closest pair is `≈3.78` units apart.\n",
+    "\n",
+    "#### Visualize\n",
+    "\n",
+    "* 3 initial points in `\"cadetblue\"`\n",
+    "* 3 additional points in `\"goldenrod\"`\n",
+    "* Current closest pair in `\"red\"`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "d26a20cc-5710-43d4-911f-733f85b5d882",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:20.172555Z",
+     "iopub.status.busy": "2024-06-15T18:59:20.172491Z",
+     "iopub.status.idle": "2024-06-15T18:59:20.265862Z",
+     "shell.execute_reply": "2024-06-15T18:59:20.265608Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:20.172549Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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5/w2JFfu7OkVFRUZUVJQhyWjcuHG513xXML7dY9W5VkM9fvOu0iJfffWVuVOnTp1a4TbFxcVGly5dzBO0goICl+s8++yzZp3U1NQKt0lNTTW3ee6551yuAc9t3LjR3AfTp093ux1OAOsGbwQ8gwYNMg8wmZmZFW6zatWqKg8e8I7i4mKjVatWhiQjJCTEuHbtmlvtML69z52TAW8ddwsKCoywsDBDktGlS5dKp4tPnTrVrLV//363ajUkNXECaBiGMWrUKLPdgwcPut0OJ4DWqssBT3Z2tuHj42NIMgYOHFjpdgMHDjSkm1//zc7OrrH+1Ac1Mb7/+te/mm1OmjTJo7YY3zXHmXOthnr85iLLFlm/fr25PGnSpAq38fHx0fjx4yVJFy9e1I4dO1yqYRiGPvvsM0lSTEyMevXqVeF2vXr10p133ilJ+uyzz2QYhkt14Ln4+Hhz+dSpU7XYE9jBlStXtH37dknSI488UumU7JEjRyo0NFSS9H//939e6x9utX37dp09e1aS9Mtf/lJBQUG13CPUFG8ed3fs2KFLly5JuvmVAB+fit+ilb2QKK8DtYfjPFy1YcMGlZSUSKr8XEH69xgvKSnRhg0bvNE1lLFixQpz2YqvZ6FmVPca3JCP3wQ8Fim9kndwcLDuv//+SreLi4szl/fs2eNSjYyMDPM7iWXbqarO2bNndebMGZfqwHM3btwwl319fWuxJ7CDAwcOqKCgQFLVY9vf3988QB04cECFhYVe6R9uVfbNX2loj/rJm8fdsncEqapWbGysGSq6+j4C1uE4D1c5O8Y9OVeAZ65cuWJ+aN++fXv169evdjuESlX3GtyQj98EPBY5cuSIJKlTp07y86v82tUxMTHlfsZZhw8frrAdq+vAcykpKeZyly5dLGkzISFBERER8vf3V0REhPr376+FCxfqwoULlrSP6q1du1Z33XWXgoKC1LhxY3Xu3FkTJkxweTbez7kztouKiswLucF7rl69an7q0q5dO/Xv39+SdhnfdZM3j7vO1vLz81OnTp3crgNrWH2c37Vrl37xi1+ocePGCgoKUocOHTRmzBitX7+emdheNGnSJEVFRcnf31/NmzdXr1699Pvf/96ctemJ0jEeFhamyMjISrdr2bKlOVuXMe5d69atU15eniTpqaeeksPhsKRdxrf1qnsNbsjHbwIeC1y/fl25ubmSqr+6fpMmTcw77WRmZrpUJysry1yurk6bNm3MZVfrwDMlJSVauHCh+e/Ro0db0u62bduUk5OjwsJC5eTkKCUlRb/73e90xx13mFMQUbMOHz6sI0eOKD8/X1evXtXJkye1YsUKPfTQQ0pMTDSnZ7qKsW0fn3zyiXmHrSeffNKyN3+M77rJm2OztFZwcLDCw8OdqpWTk3PLp5jwjm+++UabN2+WJHXt2tWSgCcjI0PffPONrl69qvz8fJ05c0Yff/yxEhMT1bdvX0sCBlRv586dys7OVmFhoc6fP6+vvvpKCxYsUKdOnZSUlORR26Vj3Jk7Y5WOcY7z3lVTM3QZ39Zy5lyrIR+/uU26Ba5cuWIuh4SEVLt9cHCwrl27Zt6GsybqlL1ds6t14Jk333xT+/fvl3TzmilVfWXPGV27dtVjjz2mHj16KCoqSoWFhTp27JhWrlyprVu36uLFixo1apQ2btxoya1aUV5QUJCGDx+uhx9+WDExMQoJCTFPwt955x2dP39e69ev14gRI7Rt2zbddtttLrXP2LYPq9/8Mb7rNm+OzdJazr6PKFurUaNGLteDe27cuKEpU6aouLhYkrRgwQKP2vP399fw4cOVkJCge+65R2FhYbp48aJSU1P19ttvKzMzU3v27NGAAQOUmpqqsLAwK54GfuaOO+7QyJEj1bt3b/ME7PTp0/rkk0+0bt06Xb9+Xc8884wcDoeefvppt2q4M8Y5znvP999/b84KeeCBB8yZFp5gfNcMZ861GvLxm4DHAtevXzeX/f39q92+dEfm5+fXWJ2yfyyu1oH7UlJS9D//8z+SpIiICL399tsetTdz5kzNmzev3P/37NlT48ePV1JSkp555hkVFxdrypQpOnXqlAICAjyqifLOnj1bYSI/YMAATZ8+XYMGDVJ6erpSUlL09ttv6z//8z9dap+xbQ9ZWVnauXOnpJsX5YuOjvaoPcZ33efNsVlay5X3Ee7WgvumTZumtLQ0STcvpjls2DCP2tu/f3+Fx5f+/ftr2rRp+uUvf6mtW7fqyJEj+t///V/98Y9/9KgeyktMTNSECRPKzcjs3r27xowZo02bNmnkyJEqLCzUf/3Xf2n48OFVfsWqMu6Mcca393z44Yfm16Wsmr3D+Laes+daDfn4zVe0LFD2DXfphVKrUjodKzAwsMbqlJ3y5WoduOfbb79VYmKiioqKFBAQoLVr1yoiIsKjNqub5jd16lRNnjxZknTu3Dl98sknHtVDxaraD7fffrvWrVtnztp56623XG6fsW0PH374oXkHFCvurMH4rvu8OTZLa7nyPsLdWnDPa6+9pvfee0/SzZP/P//5zx63WdXrQOPGjfXxxx+radOmkqSlS5c69fcB14SFhVX5dduhQ4dq7ty5kqS8vDwlJye7VcedMc749p4PPvhA0s0T8DFjxljSJuPbWq6cazXk4zcBjwUaN25sLjszrav0+g3OTONyt05pDXfqwHUZGRlKSEjQhQsX5Ovrq9WrV3vtyvtTp041l8tecAzec8cdd2jAgAGSpJMnT5pX7XcWY9seauLNX3UY37XLm2OztJYr7yPcrQXXJSUl6YUXXpB08yKan3/++S1T7WtKWFiYxo4dK+nmfi+dPQTvevrpp80QyN3XYnfGOOPbO/bv36+jR49KkoYPH17tBzBWYXw7z9VzrYZ8/CbgsUBAQICaNWsm6dYLOlXkwoUL5o4te0EnZ5S9QFR1dcpeIMrVOnDNuXPn9Mgjj+jcuXNyOBx6//33NWLECK/Vv+uuu8xlLtJWezzZD4ztui8tLc28S8LQoUPVpEkTr9RlfNcub47N0lrXrl3TxYsXnarVokULrr/jBatWrdJzzz0n6ebd87Zt26bmzZt7rT6vA7UvIiLCfK/v7j4oHePVvZZI/x7jHOe9o6YuruwMxnf13DnXasjHbwIei5QOzpMnT6qoqKjS7UrTYcn122qWfQEo247VdeC83NxcDRgwQKdPn5Z08+s53j4wWHUXH3jGk/3gztj28/NT586d3a4J15R982fF17OcxfiuXd487jpbq6ioSKdOnXK7DlyzYcMGjR8/XiUlJWrZsqW2b9/u1F2QrMTrQN3g6X4oHeOXLl3SDz/8UOl22dnZunz5siTGuDcUFhZq9erVkm4GeY8++qhX6zO+q+buuVZDPn4T8FjkwQcflHQzuTt48GCl25Wd1tmnTx+XanTo0EFRUVHl2qnIrl27JEmtWrVS+/btXaoD51y6dEkDBw40P9VfuHChfvvb33q9H6X1JZl/H/A+T/ZD9+7dzQuzVTW2CwoKtG/fPvNnXL1bF9xT9s1fixYtvHo3K8Z37fLmcbf0fUR1tdLS0syZwK6+j4Brtm/frtGjR6uoqEjNmjXTtm3b1LFjR6/3g9eB2peTk6Pc3FxJ7u8DZ8e4J+cKcN3mzZt1/vx5SdKvfvUr+fl59x5EjO/KeXKu1ZCP3wQ8FnnsscfM5WXLllW4TUlJifkpcHh4uOLj412q4XA4zOloR48eNU/0fm7fvn1mejhixAiS4RqQl5enIUOG6Ouvv5Ykvfjii3r++edrpS9JSUnmclxcXK30oaHLyMjQtm3bJEkdO3ZUq1atXPr5xo0b6+GHH5YkffHFF5VOJf3000/NT/USExM96DFcsWXLFuXk5Ejy/ps/xnft8uZxt3///uYtcv/yl7+Yd3P5ueXLl5vLvA7UnL1792rEiBG6ceOGwsLC9Le//U1333231/tx6dIlM2AOCgpSbGys1/uAmxfALR2T7r4WDx8+XD4+N0+9KjtXkP49xn18fDR8+HC3asF5tTVDV2J8V8XTc60Gffw2YJm+ffsakgw/Pz9j79695dYvWrTIkGRIMl5++eVy63fs2GGunzBhQoU1jh07Zvj6+hqSjNjYWCMvL++W9Xl5eUZsbKzZj+PHj1vx1FDGjRs3jISEBHNfzZgxw612li1bVuXfwz/+8Q/jxIkTVbaRlJRkthEZGWlcvXrVrb6gchs2bDAKCwsrXf/DDz8Y3bp1M/fD4sWLy21T3b42DMPYvn27uc3w4cONoqKiW9bn5OQYbdu2NSQZ4eHhxk8//eTR84LzRo0aZe6bgwcPOvUzjO+6KSMjo9rj7M9ZddydMGGCWXvHjh0VbvPSSy+Z2yxatKjc+r179xp+fn6GJCMuLs6p/jd07uzz9PR0Izw83JBkBAcHG7t373ardlxcnFk7IyOj3PotW7aU+3sq68qVK7e835g+fbpb/WhIXN3fGRkZxtdff13lNhs3bjT8/f0NSUZgYKCRlZVV4XbV7W/DMIynnnrK3Gbt2rXl1n/88ccu/702ZO6M77LOnz9v7tuuXbu69LOM75pj1blWQz1+e3cOWj23ZMkS9enTR/n5+UpISNALL7yg+Ph45efna/Xq1Vq6dKkkKTo6WrNmzXKrRnR0tGbPnq2FCxcqLS1Nffr00fPPP6+OHTvq1KlTev3115Weni5Jmj17NtfoqAHjxo3T1q1bJUkPPfSQJk+erH/+85+Vbu/v76/o6GiX6xw8eFBTpkxRfHy8Bg0apK5du6pZs2YqKirS0aNHtXLlSrMfvr6+Wrp0qVfu6NHQTJ8+XYWFhRo1apR69+6t9u3bKzAwULm5udq5c6eSkpLMadsPPvig21/Te+ihhzR27FitXr1aGzZs0IABAzRz5kxFRUXp0KFDWrBggb7//ntJ0uuvv+61i/w2dBcuXNCmTZskSffcc4/+4z/+w5J2Gd/esXv3bp08edL8d+lYlW5eM6/sp2mSNHHixHJtePO4O3v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+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "image/png": {
+       "height": 434,
+       "width": 572
+      }
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "_first_4 = numpy.array(list(zip(*fp.points, strict=True))).T[:, :2][:4].T\n",
+    "_second_4 = numpy.array(list(zip(*fp.points, strict=True))).T[:, :2][4:].T\n",
+    "_closest = numpy.array(list(zip(a, b, strict=True))).T[:, :2].T\n",
+    "\n",
+    "plt.scatter(*_first_4, s=200, color=\"cadetblue\")\n",
+    "plt.scatter(*_second_4, s=125, color=\"goldenrod\")\n",
+    "plt.scatter(*_closest, s=30, color=\"red\", ec=\"k\", alpha=0.9)\n",
+    "plt.xlim(0, 20)\n",
+    "plt.ylim(0, 20)\n",
+    "plt.title(f\"Closest pair is {dist:.3} units apart.\");"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6c8490c8-17f1-4081-bf57-2716a9b1fb40",
+   "metadata": {},
+   "source": [
+    "But is something going wrong here? It appears the new closest pair are farther apart than the original...\n",
+    "\n",
+    "This is because we are still considering only 2 dimensions. Let's plot again while incorporating the 3rd dimension.\n",
+    "\n",
+    "#### Visualize 3D\n",
+    "\n",
+    "* 3 initial points in `\"cadetblue\"`\n",
+    "* 3 additional points in `\"goldenrod\"`\n",
+    "* Current closest pair in `\"red\"`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "5c7921d4-9fd5-4fa0-9d9e-e39a4b12e2b4",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:20.267699Z",
+     "iopub.status.busy": "2024-06-15T18:59:20.267595Z",
+     "iopub.status.idle": "2024-06-15T18:59:20.395680Z",
+     "shell.execute_reply": "2024-06-15T18:59:20.395397Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:20.267689Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Closest pair is 3.7 units apart.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x700 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "image/png": {
+       "height": 562,
+       "width": 576
+      }
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(7, 7))\n",
+    "ax = fig.add_subplot(projection=\"3d\")\n",
+    "\n",
+    "ax.scatter(*zip(*fp.points[:4], strict=True), s=200, alpha=0.9, color=\"cadetblue\")\n",
+    "ax.scatter(*zip(*fp.points[4:], strict=True), s=200, alpha=0.9, color=\"goldenrod\")\n",
+    "ax.scatter(\n",
+    "    *numpy.array(list(zip(a, b, strict=True))), s=50, color=\"red\", ec=\"k\", alpha=0.9\n",
+    ")\n",
+    "\n",
+    "ax.axes.set_xlim3d(left=0, right=20)\n",
+    "ax.axes.set_ylim3d(bottom=0, top=20)\n",
+    "ax.axes.set_zlim3d(bottom=0, top=20)\n",
+    "\n",
+    "print(f\"Closest pair is {dist:.2} units apart.\");"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "32973029-641a-4881-b8bf-ad27eabd2f96",
+   "metadata": {},
+   "source": [
+    "By plotting with the 3rd dimension the updated closest pair makes more sense.\n",
+    "\n",
+    "## 3. Higher Dimensions\n",
+    "\n",
+    "It may be tough for humans to think about dimensions higher than 3, but not for `fastpair`. Next, let's generate 100 4D points and build the data structure."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "a25c1e2b-7b5e-4cf4-ab8a-e267dca0b502",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:20.396449Z",
+     "iopub.status.busy": "2024-06-15T18:59:20.396296Z",
+     "iopub.status.idle": "2024-06-15T18:59:20.411426Z",
+     "shell.execute_reply": "2024-06-15T18:59:20.411189Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:20.396438Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<fastpair.base.FastPair at 0x11f8eef60>"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "points = random_points(101, (4), 100)\n",
+    "fp = fastpair.FastPair()\n",
+    "fp.build(points)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bfaebbb1-b13a-400d-b437-3389e93d394c",
+   "metadata": {},
+   "source": [
+    "#### Verify the number of points generated"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "e56fcf7d-739d-4e44-967e-b157fdc408b5",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:20.411981Z",
+     "iopub.status.busy": "2024-06-15T18:59:20.411911Z",
+     "iopub.status.idle": "2024-06-15T18:59:20.414050Z",
+     "shell.execute_reply": "2024-06-15T18:59:20.413832Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:20.411974Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "100"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(fp)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0f288bab-78cf-42d0-9db5-d8835828539d",
+   "metadata": {},
+   "source": [
+    "#### Explore the first and last two points"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "3a2dda4b-e65a-44c9-881b-1267bffe0425",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:20.414516Z",
+     "iopub.status.busy": "2024-06-15T18:59:20.414451Z",
+     "iopub.status.idle": "2024-06-15T18:59:20.416562Z",
+     "shell.execute_reply": "2024-06-15T18:59:20.416371Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:20.414509Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "([(18.870650112211077,\n",
+       "   7.188420666831464,\n",
+       "   15.696108239399543,\n",
+       "   11.825563704588236),\n",
+       "  (19.463536292657878,\n",
+       "   4.490486614702625,\n",
+       "   16.10991735856244,\n",
+       "   13.617924625616881)],\n",
+       " [(6.281485191595186,\n",
+       "   15.617152919852579,\n",
+       "   18.501034362350563,\n",
+       "   0.8032379106434839),\n",
+       "  (19.60606658563202,\n",
+       "   0.9476558986387795,\n",
+       "   18.152996427027382,\n",
+       "   3.1155672960451475)])"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fp.points[:2], fp.points[-2:]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8791c05c-f005-4d46-81c9-06a64d913e72",
+   "metadata": {},
+   "source": [
+    "#### Query the closest pair"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "cfedf7c1-83f2-4c4e-a83c-4741a681ba3d",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:20.416957Z",
+     "iopub.status.busy": "2024-06-15T18:59:20.416891Z",
+     "iopub.status.idle": "2024-06-15T18:59:20.419429Z",
+     "shell.execute_reply": "2024-06-15T18:59:20.419202Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:20.416950Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1.471913992306667,\n",
+       " ((12.143319051427731,\n",
+       "   8.096696612806012,\n",
+       "   8.069117114956994,\n",
+       "   1.7566196855998584),\n",
+       "  (12.855616484647092,\n",
+       "   8.883192737858987,\n",
+       "   7.978835783535024,\n",
+       "   0.7405309621851197)))"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dist, (a, b) = fp.closest_pair()\n",
+    "dist, (a, b)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b6594762-0a8c-4f3d-9168-0a6ad5ec702b",
+   "metadata": {},
+   "source": [
+    "The closest pair is `≈1.472` units apart.\n",
+    "\n",
+    "Since visualizing data in more than 3 dimensions is difficult at best, next we'll look at `fastpair`'s performance.\n",
+    "\n",
+    "### Performance\n",
+    "\n",
+    "This next section demonstrates an example workflow of creating a `fastpair.FastPair` object and appending points while profiling run time. We will generate an initial set of 100 7D points (integers between 10-99) and then a second set with the same parameters. We query the data structure after the initial object is built and again after the addition of the second set. The profile is run twice for 3 loops each."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "38fb8d6c-7a2b-48b3-b473-c2793451880c",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-06-15T18:59:20.419997Z",
+     "iopub.status.busy": "2024-06-15T18:59:20.419923Z",
+     "iopub.status.idle": "2024-06-15T18:59:20.796052Z",
+     "shell.execute_reply": "2024-06-15T18:59:20.795820Z",
+     "shell.execute_reply.started": "2024-06-15T18:59:20.419990Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "points=100, dimensions=7\n",
+      "  fp.closest_pair()=(22.22611077089287, ((75, 82, 62, 53, 97, 30, 37), (77, 89, 72, 61, 97, 44, 46)))\n",
+      "points=200, dimensions=7\n",
+      "  fp.closest_pair()=(15.491933384829668, ((62, 28, 18, 58, 90, 59, 24), (60, 33, 17, 52, 92, 58, 37)))\n",
+      "\n",
+      "points=100, dimensions=7\n",
+      "  fp.closest_pair()=(22.22611077089287, ((75, 82, 62, 53, 97, 30, 37), (77, 89, 72, 61, 97, 44, 46)))\n",
+      "points=200, dimensions=7\n",
+      "  fp.closest_pair()=(15.491933384829668, ((62, 28, 18, 58, 90, 59, 24), (60, 33, 17, 52, 92, 58, 37)))\n",
+      "\n",
+      "points=100, dimensions=7\n",
+      "  fp.closest_pair()=(22.22611077089287, ((75, 82, 62, 53, 97, 30, 37), (77, 89, 72, 61, 97, 44, 46)))\n",
+      "points=200, dimensions=7\n",
+      "  fp.closest_pair()=(15.491933384829668, ((62, 28, 18, 58, 90, 59, 24), (60, 33, 17, 52, 92, 58, 37)))\n",
+      "\n",
+      "points=100, dimensions=7\n",
+      "  fp.closest_pair()=(22.22611077089287, ((75, 82, 62, 53, 97, 30, 37), (77, 89, 72, 61, 97, 44, 46)))\n",
+      "points=200, dimensions=7\n",
+      "  fp.closest_pair()=(15.491933384829668, ((62, 28, 18, 58, 90, 59, 24), (60, 33, 17, 52, 92, 58, 37)))\n",
+      "\n",
+      "points=100, dimensions=7\n",
+      "  fp.closest_pair()=(22.22611077089287, ((75, 82, 62, 53, 97, 30, 37), (77, 89, 72, 61, 97, 44, 46)))\n",
+      "points=200, dimensions=7\n",
+      "  fp.closest_pair()=(15.491933384829668, ((62, 28, 18, 58, 90, 59, 24), (60, 33, 17, 52, 92, 58, 37)))\n",
+      "\n",
+      "points=100, dimensions=7\n",
+      "  fp.closest_pair()=(22.22611077089287, ((75, 82, 62, 53, 97, 30, 37), (77, 89, 72, 61, 97, 44, 46)))\n",
+      "points=200, dimensions=7\n",
+      "  fp.closest_pair()=(15.491933384829668, ((62, 28, 18, 58, 90, 59, 24), (60, 33, 17, 52, 92, 58, 37)))\n",
+      "\n",
+      "62.2 ms ± 5.66 ms per loop (mean ± std. dev. of 3 runs, 2 loops each)\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%timeit -n 2 -r 3\n",
+    "\n",
+    "dimensions = 7\n",
+    "n_points = 100\n",
+    "kwargs = {\"low\": 10, \"high\": 99, \"sample\": \"integers\"}\n",
+    "\n",
+    "fp = fastpair.FastPair()\n",
+    "fp.build(random_points(101, (dimensions), n_points, **kwargs))\n",
+    "print(f\"points={len(fp)}, {dimensions=}\\n  {fp.closest_pair()=}\")\n",
+    "\n",
+    "for p in range(n_points):\n",
+    "    fp += tuple(*random_points(p * p, (dimensions), 1, **kwargs))\n",
+    "\n",
+    "print(f\"points={len(fp)}, {dimensions=}\\n  {fp.closest_pair()=}\\n\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "19b17ef2-3f4a-4490-b302-558c850e33c0",
+   "metadata": {},
+   "source": [
+    "#### This workflow runs in ≈60 milliseconds\n",
+    "\n",
+    "* *Timing will vary across machines, sofware versions, and runs themselves*. \n",
+    "\n",
+    "---------------------------"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}