Repository: Infleqtion/client-superstaq (language: python)

Issue:
Split up notebook check
Interim test for https://github.com/Infleqtion/client-superstaq/issues/889

(Also re-runs some notebooks for updated target outputs and adds the `available=True` flag in `_HPCA_Tutorial.ipynb`)


Discussion / hints:
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Reminder: https://github.com/Infleqtion/client-superstaq/issues/752

Fix patch:
diff --git a/docs/source/optimizations/ibm/ibmq_dd_strategies.ipynb b/docs/source/optimizations/ibm/ibmq_dd_strategies_qss.ipynb
similarity index 100%
rename from docs/source/optimizations/ibm/ibmq_dd_strategies.ipynb
rename to docs/source/optimizations/ibm/ibmq_dd_strategies_qss.ipynb
diff --git a/supermarq-benchmarks/README.md b/supermarq-benchmarks/README.md
index 04d6a1376..bbdf5c903 100644
--- a/supermarq-benchmarks/README.md
+++ b/supermarq-benchmarks/README.md
@@ -18,7 +18,7 @@ The Supermarq package is available via `pip` and can be installed in your curren
 pip install supermarq
 ```
 
-## Install Dev Requirements 
+## Install Dev Requirements
 
 This is required if you intend to run checks locally
 
@@ -36,7 +36,7 @@ after execution on hardware.
 The quantum benchmarks within Supermarq are designed to be scalable, meaning that the benchmarks can be
 instantiated and generated for a wide range of circuit sizes and depths.
 
-The [`examples/ghz_example.py`](examples/ghz_example.py) file contains an end-to-end example of how to execute the GHZ benchmark
+The [Supermarq tutorial](examples/Supermarq_HPCA_Tutorial_css.ipynb) notebook contains an end-to-end example of how to execute the GHZ benchmark
 using [Superstaq](https://superstaq.infleqtion.com/). The general workflow is as follows:
 
 ```python
diff --git a/supermarq-benchmarks/examples/Supermarq_HPCA_Tutorial.ipynb b/supermarq-benchmarks/examples/Supermarq_HPCA_Tutorial_css.ipynb
similarity index 66%
rename from supermarq-benchmarks/examples/Supermarq_HPCA_Tutorial.ipynb
rename to supermarq-benchmarks/examples/Supermarq_HPCA_Tutorial_css.ipynb
index 88595c746..593517e46 100644
--- a/supermarq-benchmarks/examples/Supermarq_HPCA_Tutorial.ipynb
+++ b/supermarq-benchmarks/examples/Supermarq_HPCA_Tutorial_css.ipynb
@@ -5,7 +5,7 @@
    "id": "5588660c",
    "metadata": {},
    "source": [
-    "# HPCA 2023 Supermarq Tutorial"
+    "# HPCA 2023 Supermarq Tutorial using `cirq-superstaq`"
    ]
   },
   {
@@ -24,16 +24,41 @@
    "outputs": [],
    "source": [
     "try:\n",
-    "    import cirq\n",
     "    import cirq_superstaq as css\n",
     "except ImportError:\n",
     "    print(\"Installing cirq-superstaq...\")\n",
-    "    %pip install -q cirq-superstaq[examples]\n",
-    "    print(\"Installed cirq-superstaq. Please restart the kernel to import the packages.\")\n",
-    "\n",
-    "import os\n",
-    "import qiskit_superstaq as qss\n",
-    "import supermarq"
+    "    %pip install --quiet 'cirq-superstaq[examples]'\n",
+    "    print(\"Installed cirq-superstaq.\")\n",
+    "    print(\"You may need to restart the kernel to import newly installed packages.\")\n",
+    "    import cirq_superstaq as css"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "34b47d69",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "try:\n",
+    "    import supermarq\n",
+    "except ImportError:\n",
+    "    print(\"Installing supermarq...\")\n",
+    "    %pip install --quiet supermarq\n",
+    "    print(\"Installed supermarq.\")\n",
+    "    print(\"You may need to restart the kernel to import newly installed packages.\")\n",
+    "    import supermarq"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "84c2bd90",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Optional\n",
+    "import os  # Used to store a token in an environment variable"
    ]
   },
   {
@@ -54,7 +79,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 4,
    "id": "e93f9f7b",
    "metadata": {},
    "outputs": [
@@ -67,40 +92,17 @@
     }
    ],
    "source": [
-    "# Provide your api key to the Service using the \"api_key\" argument if\n",
-    "# SUPERSTAQ_API_KEY environment variable is not set.\n",
+    "# Provide your api key to `css.Service()` using the `api_key=` argument if\n",
+    "# the SUPERSTAQ_API_KEY environment variable is not set.\n",
     "\n",
-    "# Submit cirq circuits via cirq-superstaq\n",
+    "# Submit cirq circuits via `cirq-superstaq`\n",
     "service = css.Service()\n",
     "print(service.get_balance())"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "id": "696ded37",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "20 credits\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Provide your api key to the Provider using the \"api_key\" argument if\n",
-    "# SUPERSTAQ_API_KEY environment variable is not set.\n",
-    "\n",
-    "# Submit qiskit circuits via qiskit-superstaq\n",
-    "provider = qss.SuperstaqProvider()\n",
-    "print(provider.get_balance())"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "id": "4551cfe4",
    "metadata": {},
    "outputs": [
@@ -116,42 +118,30 @@
        " Target(target='cq_hilbert_simulator', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
        " Target(target='ibmq_brisbane_qpu', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
        " Target(target='ibmq_extended-stabilizer_simulator', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
-       " Target(target='ibmq_fake-athens_qpu', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
-       " Target(target='ibmq_fake-lima_qpu', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
        " Target(target='ibmq_kyoto_qpu', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
        " Target(target='ibmq_mps_simulator', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
+       " Target(target='ibmq_osaka_qpu', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
        " Target(target='ibmq_qasm_simulator', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
        " Target(target='ibmq_stabilizer_simulator', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
        " Target(target='ibmq_statevector_simulator', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
-       " Target(target='ionq_aria-1_qpu', supports_submit=False, supports_submit_qubo=False, supports_compile=True, available=False, retired=False),\n",
-       " Target(target='ionq_aria-2_qpu', supports_submit=False, supports_submit_qubo=False, supports_compile=True, available=False, retired=False),\n",
-       " Target(target='ionq_forte-1_qpu', supports_submit=False, supports_submit_qubo=False, supports_compile=True, available=False, retired=False),\n",
-       " Target(target='ionq_harmony_qpu', supports_submit=False, supports_submit_qubo=False, supports_compile=True, available=False, retired=False),\n",
+       " Target(target='ionq_harmony_qpu', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
        " Target(target='ionq_ion_simulator', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
-       " Target(target='oxford_lucy_qpu', supports_submit=False, supports_submit_qubo=False, supports_compile=True, available=False, retired=False),\n",
        " Target(target='qtm_h1-1_qpu', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
        " Target(target='qtm_h1-1e_simulator', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
        " Target(target='qtm_h2-1_qpu', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
-       " Target(target='rigetti_aspen-10_qpu', supports_submit=False, supports_submit_qubo=False, supports_compile=True, available=False, retired=True),\n",
-       " Target(target='rigetti_aspen-11_qpu', supports_submit=False, supports_submit_qubo=False, supports_compile=True, available=False, retired=True),\n",
-       " Target(target='rigetti_aspen-8_qpu', supports_submit=False, supports_submit_qubo=False, supports_compile=True, available=False, retired=True),\n",
-       " Target(target='rigetti_aspen-9_qpu', supports_submit=False, supports_submit_qubo=False, supports_compile=True, available=False, retired=True),\n",
-       " Target(target='rigetti_aspen-m-1_qpu', supports_submit=False, supports_submit_qubo=False, supports_compile=True, available=False, retired=True),\n",
-       " Target(target='rigetti_aspen-m-2_qpu', supports_submit=False, supports_submit_qubo=False, supports_compile=True, available=False, retired=True),\n",
-       " Target(target='rigetti_aspen-m-3_qpu', supports_submit=False, supports_submit_qubo=False, supports_compile=True, available=False, retired=False),\n",
        " Target(target='sandia_qscout_qpu', supports_submit=False, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
        " Target(target='ss_unconstrained_simulator', supports_submit=True, supports_submit_qubo=False, supports_compile=True, available=True, retired=False),\n",
        " Target(target='toshiba_bifurcation_simulator', supports_submit=False, supports_submit_qubo=True, supports_compile=False, available=True, retired=False)]"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "# See which backends are available\n",
-    "service.get_targets()"
+    "# See which targets are available\n",
+    "service.get_targets(available=True)"
    ]
   },
   {
@@ -169,7 +159,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "id": "67da9bdb",
    "metadata": {},
    "outputs": [
@@ -192,57 +182,7 @@
    "source": [
     "# Create your benchmark using cirq circuits\n",
     "ghz = supermarq.ghz.GHZ(5)\n",
-    "print(ghz.circuit())"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "77f5d9cd",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">      ┌───┐          ┌─┐                      \n",
-       " q_0: ┤ H ├──■───────┤M├──────────────────────\n",
-       "      └───┘┌─┴─┐     └╥┘     ┌─┐              \n",
-       " q_1: ─────┤ X ├──■───╫──────┤M├──────────────\n",
-       "           └───┘┌─┴─┐ ║      └╥┘     ┌─┐      \n",
-       " q_2: ──────────┤ X ├─╫───■───╫──────┤M├──────\n",
-       "                └───┘ ║ ┌─┴─┐ ║      └╥┘┌─┐   \n",
-       " q_3: ────────────────╫─┤ X ├─╫───■───╫─┤M├───\n",
-       "                      ║ └───┘ ║ ┌─┴─┐ ║ └╥┘┌─┐\n",
-       " q_4: ────────────────╫───────╫─┤ X ├─╫──╫─┤M├\n",
-       "                      ║       ║ └───┘ ║  ║ └╥┘\n",
-       "m0: 5/════════════════╩═══════╩═══════╩══╩══╩═\n",
-       "                      0       1       2  3  4 </pre>"
-      ],
-      "text/plain": [
-       "      ┌───┐          ┌─┐                      \n",
-       " q_0: ┤ H ├──■───────┤M├──────────────────────\n",
-       "      └───┘┌─┴─┐     └╥┘     ┌─┐              \n",
-       " q_1: ─────┤ X ├──■───╫──────┤M├──────────────\n",
-       "           └───┘┌─┴─┐ ║      └╥┘     ┌─┐      \n",
-       " q_2: ──────────┤ X ├─╫───■───╫──────┤M├──────\n",
-       "                └───┘ ║ ┌─┴─┐ ║      └╥┘┌─┐   \n",
-       " q_3: ────────────────╫─┤ X ├─╫───■───╫─┤M├───\n",
-       "                      ║ └───┘ ║ ┌─┴─┐ ║ └╥┘┌─┐\n",
-       " q_4: ────────────────╫───────╫─┤ X ├─╫──╫─┤M├\n",
-       "                      ║       ║ └───┘ ║  ║ └╥┘\n",
-       "m0: 5/════════════════╩═══════╩═══════╩══╩══╩═\n",
-       "                      0       1       2  3  4 "
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Create your benchmark using qiskit circuits\n",
-    "ghz_qiskit_circuit = supermarq.converters.cirq_to_qiskit(supermarq.ghz.GHZ(5).circuit())\n",
-    "ghz_qiskit_circuit.draw()"
+    "print(ghz.cirq_circuit())"
    ]
   },
   {
@@ -251,7 +191,7 @@
    "metadata": {},
    "source": [
     "### 3. Circuit evaluation\n",
-    "The generated circuits can be evaluated on a backend using any compatible service: AWS Braket, IBM Qiskit, cirq-superstaq, qiskit-superstaq, etc."
+    "The generated circuits can be evaluated on a backend using any compatible service: AWS Braket, IBM Qiskit, `cirq-superstaq`, `qiskit-superstaq`, etc. Here we use `cirq-superstaq`"
    ]
   },
   {
@@ -262,20 +202,7 @@
    "outputs": [],
    "source": [
     "job_css = service.create_job(\n",
-    "    ghz.circuit(), repetitions=1000, target=\"ss_unconstrained_simulator\", method=\"dry-run\"\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "ea1693e7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "backend = provider.get_backend(\"ss_unconstrained_simulator\")\n",
-    "job_qss = backend.run(\n",
-    "    supermarq.converters.cirq_to_qiskit(ghz.circuit()), shots=1000, method=\"dry-run\"\n",
+    "    ghz.cirq_circuit(), repetitions=1000, target=\"ss_unconstrained_simulator\", method=\"dry-run\"\n",
     ")"
    ]
   },
@@ -290,7 +217,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "id": "5508a063",
    "metadata": {},
    "outputs": [
@@ -300,7 +227,7 @@
        "'Done'"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -311,7 +238,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "id": "9723e0e9",
    "metadata": {},
    "outputs": [
@@ -319,8 +246,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{'00000': 518, '11111': 482}\n",
-      "0.9996758949559204\n"
+      "{'00000': 484, '11111': 516}\n",
+      "0.9997439344304242\n"
      ]
     }
    ],
@@ -331,49 +258,6 @@
     "print(score_css)"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "id": "4e1c5b9a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<JobStatus.DONE: 'job has successfully run'>"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "job_qss.status()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "7c371847",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'00000': 501, '11111': 499}\n",
-      "0.999998999999\n"
-     ]
-    }
-   ],
-   "source": [
-    "counts = job_qss.result().get_counts()\n",
-    "print(counts)\n",
-    "score_qss = ghz.score(counts)\n",
-    "print(score_qss)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "2a801645",
@@ -385,13 +269,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 10,
    "id": "8c176996",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 960x720 with 1 Axes>"
       ]
@@ -401,7 +285,7 @@
     }
    ],
    "source": [
-    "supermarq.plotting.plot_results([score_css, score_qss], [\"ghz_css\", \"ghz_qss\"])"
+    "supermarq.plotting.plot_results([score_css], [\"ghz_css\"])"
    ]
   },
   {
@@ -423,7 +307,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 11,
    "id": "776bc0d4",
    "metadata": {},
    "outputs": [
@@ -436,7 +320,7 @@
     }
    ],
    "source": [
-    "ghz_circuit = supermarq.ghz.GHZ(10).circuit()\n",
+    "ghz_circuit = supermarq.ghz.GHZ(10).cirq_circuit()\n",
     "ghz_features = [\n",
     "    supermarq.features.compute_communication(ghz_circuit),\n",
     "    supermarq.features.compute_depth(ghz_circuit),\n",
@@ -458,20 +342,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 12,
    "id": "5f5fd6da",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "findfont: Font family ['Times New Roman'] not found. Falling back to DejaVu Sans.\n",
-      "findfont: Font family ['Times New Roman'] not found. Falling back to DejaVu Sans.\n",
-      "findfont: Font family ['Times New Roman'] not found. Falling back to DejaVu Sans.\n",
-      "findfont: Font family ['Times New Roman'] not found. Falling back to DejaVu Sans.\n"
-     ]
-    },
     {
      "data": {
       "image/png": 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AZGRkIC0tDZMnT77h8QsLC/HYY4/hySefhJ+fH1xcXMDj8ZCVlaURmroOgBgqL730Ep544gn2+oIFCxAZGQmZTIZLly4N+LjvvvsuFi1aBIZh0NnZiXnz5mHSpElwc3ODRCJBTk4O26ftrbfe6vNxX3jhBVy8eBH79u0DcG1i24ceegivvPIKgoKCIBAIUFJSgrS0tAGX/Wbq6+vx0EMPaQRHCwsLfPrpp/j000973e9GqzzcyMqVK7Flyxbw+XzEx8drbOtao7N69Wp89tlnbLP+li1bsG/fPgQGBkIoFKKsrAxXr16FXC7XqLUbjNtvvx3Tp09ng2VZWRlCQkIQFBQEe3t7FBYWIjMzEwcOHLjh4IaRFB4ejmPHjgG41p0hICAA4eHhyM/PR05ODjgczpD8SPjwww9RWVmJnTt3Arj2w+DBBx/E3r17h7T5mhBtohBHdM6BAwc0+mjdaJ3MriEOuFYbd7MQp6ZQKJCRkdFjh2qRSNSvcDNQq1evxvHjx9mAoVAo2C9kDw8PeHp64sSJEwDAjlbsizvuuANff/01XnjhBbamIz09vccamf58YXE4HOzevRseHh745JNP2FULampq8M8///S4j4+PT5+P3xcZGRndZv2vra296UCCgZg9ezby8vI0mm3VFi9erDGowtDQEEeOHMGiRYvYgSS1tbXs69eVtkICh8PBn3/+icWLF7MBU6FQ9Ljagq5au3YtfvzxR3Ykem1tLbuyxerVq3HixIkhqRXncDj46aefUF1dzdZU//HHH3jqqaewbds2rZ+PkKFAzalE51zfLHr33Xf3et9FixZpTJexe/fum/5qnzlzJr7++mvcd9998Pf3h6WlJbhcLoyMjDBhwgSsWbMGV65cQVhY2OAeSB9wOBzs2bMHn3zyCXx9fSEQCODg4ICnn34aiYmJGkt/qaeB6KtnnnkG6enpeO655zBp0iQYGxuDy+XC3NwcoaGhePbZZ3H06NFuTaQ3w+VysXnzZuTm5mL9+vWIjIyEtbU1eDweDAwM4OzsjDlz5mD9+vU4f/78qF7CyMXFBUlJSXj88cdhb28PgUAAb29vbN68Gfv37+/WD8vf3x+pqan48ssvMXv2bFhZWYHH48HQ0BBeXl645557sHXrViQmJmqtjNbW1jh37hx+++033HHHHbCzswOfz4eJiQkCAgLw9NNPIygoSGvn0zZra2tcvHgRDzzwACwsLKCvr48JEybg888/13ofx+vx+Xz8+eefCAwMZG/bvn07Xn/99SE9LyHawmGGuzMLIURDSUlJj81rMTExmDdvHjuA4+GHH8Yvv/wy3MUjhBCioyjEETLC1IMbIiMj4eDgAJlMhqysLBw7doydRkUgECAlJaXHecsIIYSMT9QnjhAdkJOT02uzo4mJCX777TcKcIQQQjRQTRwhI2znzp04fPgwUlJSUFNTg46ODpiamsLPzw+33HILnnjiiQFPZEoIIWTsohBHCCGEEDIK0ehUQgghhJBRiEIcIYQQQsgoRCGOEKJTiouLweFwerzweDxYWFggKCgITz/9dLcVFHojl8uxb98+PP7445g0aRJsbW0hEAhgamoKLy8vLF26FFu2bEFdXd0QPzpCCNEe6hNHCNEpxcXFcHd37/P9V65ciW3btvW6osXOnTuxYcOGPs36z+PxsGrVKrz77ruwsbHpcxkIIWQk0BQjhBCdFRYWhp9++om9rlQqUVVVhaNHj2Lr1q2QyWT45ZdfIBAIus3ur1Kp8Nxzz2HLli3sbdHR0Vi0aBECAwNhZWWF9vZ2lJeX4/Tp0zh06BDq6urw/fffIyoqCo888shwPUxCCBkQqokjhOiUrjVxM2fORExMTI/3i4mJwS233AKFQgEOh4OsrCz4+vqy29944w1s3rwZAGBjY4OdO3di3rx5vZ63o6MD3377Ld5++2189dVXFOIIITqP+sQRQkalWbNmYenSpQAAhmHYRdOBawHvww8/BACYmZkhLi7uhgEOuLaA/csvv4ykpCR4eXkNXcEJIURLKMQRQkatadOmsX8XFRWxf7/99ttQNzJ89tln8PT07PMxfX19MX36dO0VkhBChgiFOELIqMXj/a9br1KpBADk5eUhNjYWAODg4IDly5ePSNkIIWSoUYgjhIxaV65cYf92dHQEAJw+fZq9bcGCBb2OWiWEkNGOQhwhZFTKy8vDjh072OvqPm/JycnsbeHh4cNeLkIIGS4U4ggho4ZSqURFRQW2bduG6OhotLe3AwBuueUWREREAADq6+vZ+9va2o5IOQkhZDjQPHGEEJ0VGxsLDodzw/uEhYVh9+7d7PWWlhb2b5FINGRlI4SQkUY1cYSQUUcoFGLq1KnYunUrLl68CEtLS3abiYkJ+3dbW9tIFI8QQoYF1cQRQnTW9Ss2cLlcGBsbw9bWttcBC1ZWVuzfNTU1Q15GQggZKRTiCCE6y8jICBMnTuzXPsHBwezfly5dwpNPPqntYhFCiE6g5lRCyJgyZ84c9u8jR45ALpePYGkIIWToUIgjhIwpPj4+mDFjBgCgqqpKYxoSQggZSyjEEULGnLfffpv9+6WXXkJBQUGf983JycGFCxeGoFSEEKJdFOIIIWPO7NmzsW7dOgCAWCzGtGnTcOrUqRvu09nZic8//xxhYWHIy8sbjmISQsig0MAGQsiY9N5776G1tRVbtmxBTU0N5s2bh+joaCxevBiBgYGwtLRER0cHKioqEBMTg4MHD6K6unqki00IIX1GIY4QMibp6enh66+/RlRUFDZs2ICSkhKcO3cO586d63UfPp+Pxx9/HAsXLhzGkhJCyMBQiCOEjGnLly/HsmXLcODAARw/fhwJCQmoqalBU1MTDAwMYGNjg6CgIMyZMwfLli3TmGeOEEJ0GYdhGGakC0EIIYQQQvqHBjYQQgghhIxCFOIIIYQQQkYhCnGEEEIIIaMQhThCCCGEkFGIQhwhhBBCyChEIY4QQgghZBSiEEcIIYQQMgpRiCOEEEIIGYUoxBFCCCGEjEIU4gghhBBCRiEKcYQQQgghoxCFOEIIIYSQUYhCHCGEEELIKEQhjhBCCCFkFKIQRwghhBAyClGII4QQQggZhSjEEUIIIYSMQhTiCCGEEEJGId5IF4AQQvpKqVSira0NbW1tUCqVUKlU7EW9raCgAA4ODrC2toaenp7GhcvlwsjICCKRCHw+f6QfDiGEDAqFOELIsJHL5aiurkZVVRV7aW5uRmtrK9ra2tDa2nrDvyUSidbKIhQKYWxsDJFIpPFvT3+bmJjAzs4O9vb27MXAwEBrZSGEkIHgMAzDjHQhCCGjm0wmQ2VlJaqqqth/1Zeu1+vq6vp0PENDwxuGKyMjI/D5fLZ2TV3TVl5ejl9++QVhYWGYP3++Rk2dSqWCQqFAe3s7Gwx7CottbW19KqOZmZlGqHNwcOh23dHREYaGhoN5agkhpFcU4gghfaJSqVBWVobc3Nxul+LiYqhUqh73MzQ0vGHYMTc37xbQuFzugMt5+vRpAMCcOXMG/Dg7Ojo0Qp1YLO5Wg9g1nDY3N/d6PEdHR/j4+HS7uLu7U5MuIWRQKMQRQlgMw6C+vr7HoJafn4/Ozk6N++vr68Pb2xs+Pj5wdXXtMaSZmJiAw+EM22MYbIgbiI6ODo2Apw55ZWVlyMvLQ05ODlpaWjT24XK58PDwYEOd+nn08fGBo6Mj9PRo3Bkh5MYoxBEyTjEMg4qKCly+fFnjUlNTo3E/PT09uLu791ib5OTkpHNhYyRC3M0wDIO6uroew3FeXh5kMpnG/U1MTBAcHIzQ0FD24u3trXPPNSFkZFGII2QcYBgGZWVlGmEtOTkZtbW17H0EAgEmT56MwMBA+Pn5sUHNw8MDAoFgBEvfP7oY4m5EqVRqNFPn5OQgLS0NKSkpaG1tZe9nbGzcLdj5+PhQsCNkHKMQR8gYVFdXh/PnzyMpKYkNbfX19ex2oVCIyZMnawSCCRMmjKqw1pvRFuJ6o1KpkJeX1y14dw12IpFII9hNnz4dbm5uI1doQsiwohBHyBhQX1+P2NhYxMTEICYmBhkZGew2oVCIwMDAboFtrHaqHyshricqlQoFBQXdgl3XgRWurq6YNWsWe6FQR8jYRSGOkFGovr4eZ8+eZUNbeno6u83BwQGzZs3CzJkzERERgYCAgDEb2HoylkNcT1QqFQoLC3Hp0iU2yOfk5LDb3dzcNEKdq6vrCJaWEKJNFOIIGQVuFNrs7e0xe/Zs9kvay8trWEeD6prxFuJ6UlVVpVEzS6GOkLGJQhwhOohhGKSkpOCvv/7C4cOHkZyczG6zt7dnv4Bnz5497kPb9SjEdVdVVcUGupiYGOTm5rLbPD09sWjRIixevBjTp08fV7W2hIx2FOII0RGdnZ04c+YM/vrrL/z1118oLy8HcG1lgPnz52POnDmYNWsWvL29KbTdAIW4m6usrERsbCzOnDmDY8eOoaysDMC199qCBQuwaNEiLFiwAGZmZiNbUELIDVGII2QE1dXV4b///S8OHz6M48ePo729HQDg5eWFxYsXY9GiRZg2bRrVjvQDhbj+YRgGqampbK1vUlISAIDH42HGjBlsLZ2Hh8cIl5QQcj0KcYQMI4ZhkJ2djcOHD+Pw4cO4ePEiGIaBnp4epk6dyn5h+vr6jqvaNvW6pje6KJVKjesqlQrqjy+GYcAwjMbap/b29uBwOOzzqP6bx+NpXLhcLvh8PrhcbrdtPB4Penp64+q1qKysxN9//43Dhw/j1KlT7CodEyZMYN+fU6ZMGdTSaIQQ7aAQR8gwyM/Px86dO7Fr1y62P5JIJML8+fOxaNEi3H777bC2th7hUmoXwzCQyWSQSqXo7Ozsdul6e2/rruoCDocDoVAIfX19jcv1twmFwjEX9trb23Hy5Em2iV89ObSNjQ3uu+8+rFixAuHh4WPucRMyWlCII2SI1NXVYe/evdixYwcSEhIAALa2trj77rtx5513YtasWRAKhSNcyoFjGAZSqRTt7e1oa2tDW1sb2tvbNYLajT5ehEIhG4T4fH6PtWDqmrIb1ZB1rWkDNJtTr6+pU6lU3Wr0eqvp63rpGjxv9pjUoc7IyAhGRkYQiUQQiUQwMDAY1WFHpVLh0qVLOHz4MPbv38/+GPHy8sKKFSuwfPlyeHl5jXApCRlfKMQRMkiXL1/GiRMnkJiYiPj4eFRVVQG4tsC5UqmEkZER7r77bqxYsQJz5swBj8e74fGamprw9ttv4+DBg6iuroadnR2WLFmCt99+e0Q6msvl8m5BTf23QqHodv+eaqmuv00oFA7ZclFD2SdOXbt4o1pF9fXraxf19PQ0Ql3XvwUCwagKeAzD4PLly9i5cyd2797NrrcbERGBFStW4L777htzNcuE6CIKcYQM0uLFi/HXX391u/2OO+7A8uXLsXjxYhgZGfXpWPX19YiKikJ+fj48PDwQFhaGzMxMZGZmwsfHBxcvXoSFhYW2HwIAsH3KxGIxmpub0dzcjLa2Nkil0m731dfX7zGMGBoajvhanrowsIFhGEgkkm6ht62tDR0dHd3uz+fzYWRkBFNTU5iamsLMzAwmJiajot+ZQqHA6dOnsWPHDvz5559ob28Hl8vF/PnzsWLFin69/wkh/UMhjpABYBgGycnJ2LFjB7Zv3852pg8NDUVqaioUCsUNm916s2LFCuzcuRN333039u7dy9baPffcc/jqq6+wcuVK/Pzzz4Muv0qlQltbG8RisUZoUyqV7H14PB4bzrpejIyMblqbOJJ0IcTdiFKpREdHR481m10DM4fDgYmJCRvqRkOwa29vx+HDh7Fz504cO3asW0303Llzdbr8hIw2FOII6Ye2tjbs2rUL3333HTsBr7e3N1asWIEHH3wQXl5e0NfXv2nfqZ5UVVXByckJPB4PpaWlsLW1ZbdJpVI4OzujsbERlZWVsLGx6fNxu9awqS8tLS0agY3P52uEBVNTUxgZGY2qJj41XQ9xNyKRSNDc3MwGa7FYzI4OBa4FO2NjY/Y1Ur9eI1372ZO6ujr8/vvv2LFjB+Lj4wFcW9f18ccfx6pVq2Bvbz/CJSRk9KMQR0gfpKamYuvWrdi5cydaW1shEomwYsUKPProo91G5w00xP30009YtWoV5s6di5MnT3bb/thjj+HHH3/ETz/9hEceeaTX4zAMg5aWFtTX16O+vh4NDQ2Qy+Xsdj6f3y0EGBoajsrA1pPRHOJ60tnZqRHqrg92XC4X5ubmsLKygpWVFczNzXUu1OXn5+OXX37BDz/8gKqqKvB4PNx555146qmnMGfOHJ0rLyGjhe62iRAywjo7O/H777/j22+/ZWsSgoOD8dRTT+GBBx6AsbGxVs+XmpoKAAgJCelxe0hICH788UekpaVp3N41tDU0NKC+vl4jtJmZmbFf7qampmMqsI0H+vr6sLOzg52dHXtbZ2cnmpub0dTUhIaGBjQ2NqK+vh7AtVBnYWEBS0tLnQl1Xl5eePfdd7Fx40b8/fff2Lp1K/744w/88ccf8PT0xFNPPYVVq1YNWX9PQsYqCnGEXKesrAxbt27Ftm3bUFdXBwMDA6xatQpPPvnkkM6JVVpaCgBwcnLqcbv69pKSkm41bTKZjL2fOrRZWVnBwsKCVnsYg9SjfNVN7kqlEmKxWOM9UVdXB0Az1FlbW49o8yufz8eSJUuwZMkSFBQUYNu2bfjxxx/x6quvYuPGjVi+fDnWrFmDwMDAESkfIaMNhThCcK02KzY2Fl9//TUOHjwIpVIJDw8PrFu3Do8++ijMzc2HvAzqwRGGhobdtikUCkgkEgBAUVERzpw5w24zMzODi4sLhbZxjMvlwtLSEpaWlvD19e011GVnZ4PL5cLa2hp2dnawtbWFvr7+iJTZ09MTmzdvxjvvvIN9+/bhq6++wvbt27F9+3ZER0djzZo1WLJkCb2fCbkBCnFkXFMoFPj999/x4Ycfss2U8+fPx9q1a3HbbbeN6Eg6iUSC6upqVFdXo76+np1cVU9PD15eXhTaSK9uFOrq6urY9xUAmJubs821xsbGw97ULhQKsWLFCqxYsQKJiYn4+uuvsXfvXpw7dw6Ojo548cUX8eSTT0IkEg1ruQgZDSjEkXGps7MTP//8Mz766CMUFhbCyMgIa9euxZo1a+Dj4zMiZVJ/SRUVFSEmJgbNzc0Aro1ItLKyYpvOXF1dMWHChBEpIxmdrg91MpkMNTU1qK6uRm1tLZqampCVlQVDQ0M20FlaWg57s+uUKVPw66+/4uOPP8a2bdvw9ddf45VXXsH777+PtWvXYu3atbC0tBzWMhGiy2hIEBlXWltb8dFHH8Hd3R1PP/00xGIx3n77bZSUlODLL78c9gCnVCpRU1OD1NRUdjTr1atX0dHRAScnJ4SFhWHBggWYOnUquzqCq6vrsJaRjD0CgQDOzs4IDw/HggULEBUVBXd3dzAMg8LCQsTFxeHo0aNISkpCWVmZRp/L4WBjY4MNGzagqKgIW7duhZmZGd555x24urripZdeQkVFxbCWhxBdRTVxZFyoq6vDl19+ia+//hpisRgODg749NNP8fjjjw97Mw3DMKivr0d5eTkqKyvZcKZed7KxsRG33XZbt1oQ9bx0kydPHtbykrFNT08PNjY2sLGxwaRJk9Da2oqqqirU1NSgoqICFRUV4HA4sLW1hbOzM2xtbYetm4G+vj6efPJJPPbYY9i3bx82b96Mzz77DF9//TUefvhhvP766/D29h6WshCii2ieODKmlZWVsU0zEokEXl5eeP311/HQQw8N2eLzPc0Tp54GpLy8HOXl5ew8X6ampnB0dISdnR3a2trYyX7Lyso0JvQdzGS/481YmyduJHV2drJhTj3alcfjwcHBAU5OTrCyshrWPnQMw+DIkSP44IMPcOHCBXA4HNx7771Yt24dgoODh60chOgKCnFkTMrJycGHH36I3377DQqFAkFBQXjjjTdwzz33DHktQtcQ19HRwQa31tZWAMCJEydw5MgRLFmyBJ988onGvuplt+655x7s2bOHXd7q+eefx5dffqm1ZbfGMgpxQ6OzsxMVFRUoKytj+2vq6+vDyckJTk5OMDU1HdbynDt3Du+//z6OHTsGALjtttuwfv16REdHD2s5CBlJFOLImFJQUICNGzdi9+7dYBgGM2bMwBtvvIH58+cPWY3Bf//7X7z77rvs9cTERDAMg4CAALap9IEHHsCSJUvg5OSEL7/8Ev/+9797DGT19fWIjIxEQUEBPD09ERYWhszMTGRkZMDb2xvx8fE0IepNUIgbeq2treyPk46ODgCAsbExnJ2d4ejo2OM0OUMlJSUFmzdvxr59+9j/85s3b0ZUVNSwlYGQkUIDG8iYUFNTgzVr1sDPzw+7du3C/Pnzcf78ecTGxuK2224b0iafuro6JCQksJeuAxRyc3ORm5sLFxcXBAYGwtLS8oZlsbKyQmJiItauXQuZTIYDBw6gubkZzz33HBITEynAEZ1gbGwMf39/zJs3D9OnT4ebmxs6Oztx9epVnDhxAufPn0dpaanG+rxDJTg4GHv37kVOTg5WrVqFCxcuYOrUqbjrrrtw9erVIT8/ISOJauLIqNbS0oKPP/4Yn376Kdrb2xEREYEPP/wQM2fOHJbzd3Z2orS0FCUlJWyNhJWVFZycnODg4EBzuI0AqokbGSqVCjU1NSgvL0d1dTVUKhX4fD6cnZ3h5uam9WXqepOdnY1//etf+OOPP6Cnp4eVK1finXfegbOz87Ccn5DhRCGOjEpSqRTffPMN3nvvPTQ0NMDPzw/vv/8+7rrrriHvaK0eXVpcXIyqqiowDAOhUAhXV1e4uroOa1MS6Y5C3MiTyWQoKytDcXExuxKJpaUl3NzcYG9vPyyjWxMTE7Fu3TqcOXMGQqEQa9aswRtvvEHzzJExhUIcGVWUSiV27NiBjRs3orS0FE5OTnjnnXfw8MMPs4MAhopcLkdZWRmKiorYLyZra2u4ubnBzs5uxBcZJ9dQiNMdDMOgoaGB/cGjUqnYHzxubm4wMDAY8vOfOHEC69atQ0pKCkxMTPDaa6/hhRdegJGR0ZCem5DhQCGOjAoMw+Dvv//G+vXrkZGRAXNzc6xfvx7PPvvskH8RtLa2oqioCGVlZVAoFODz+XBxcYGbmxstBaSDKMTpJqlUitLSUhQXF6OjowMcDgf29vbw8PCAhYXFkNagq1Qq/P777/jXv/6FgoIC2NnZYePGjVi9ejV1eSCjGoU4ovMuXryIV199FRcuXICBgQFeeOEFvPbaazAzMxuyczIMg7q6OuTn57PzY5mYmMDDwwOOjo5DXutHBo5CnG5jGAbV1dUoKipi/2+ZmprCw8MDTk5OQ1qjLZPJsH37dvz73/9GTU0NPD098f777+Pee+8d9jVjCdEGCnFEZ9XU1OD111/HL7/8Ai6Xi8cffxwbN26Evb39kJ2TYRhUVlYiLy8Pzc3Nw1pbQLSDQtzooa7lVo9kNTAwgKenJ1xdXYf0h1JbWxu++OIL/Oc//0FLSwtmzZqFr7/+mtYkJqMOhTiicxQKBb799lu8+eabaG5uxq233oovv/wSvr6+Q3ZOlUqFsrIy5OXlob29HVwuFy4uLvDy8qKBCqMMhbjRRy6Xo6ioCIWFhZBKpRAIBPDw8ICHh8eQNnfW19djw4YN2LZtG7hcLp5//nm89dZbwzaSlpDBohBHdMr58+fx7LPPIi0tDS4uLvjss8+wZMmSIasBUygUKCkpQX5+Pjo7O8Hj8dgvj6FalosMLQpxo5dSqWT/P0okEvB4PLi5ucHT0xP6+vpDdt5Lly7hmWeeQVJSEuzt7fHJJ5/g/vvvp5p3ovMoxBGdUFNTg9deew2//vor+Hw+Xn31Vaxfv37IRpDJZDL2l79MJoNQKISnpyfc3Nyoo/MoRyFu9FOpVKioqEBeXh5aW1uhp6fH1owP1WeCUqnEDz/8gDfeeAONjY2YOXMmtmzZQk2sRKdRiCMjSqFQ4JtvvsGbb76JlpYW3Hrrrfjqq6/g4+MzJOeTSCQoKChAcXExlEolDA0N4eXlBRcXl2GZu4oMPQpxY4d6EEReXh6ampoAAE5OTvD29oaJicmQnLOhoQHr16/Htm3boKenxzaxDtX5CBkMCnFkxAxn06lUKkVOTg5KSkqgUqlgYmICb29vODg40PxuYwyFuLFHPcF2Xl4eO6LV3t4e/v7+Q9Z/7dKlS3jhhRdw+fJl2NnZ4YMPPsCyZcuoiZX0CYfDGZb3CoU4Muy6Np0KBAK88sorQ9Z0KpfLUVBQgPz8fCiVSpiZmcHX1xe2trb0YTxGUYgb25qampCbm4vq6moAgIuLC/z8/LQyX6REIkFzczNaW1uhUCjY8FhRUQGFQgFjY2O4uLgM+dyUZGzg8XgwNjaGqanpkL1nKMSRYcMwDHbv3o21a9eisbER8+fPx5dffjkkTadKpRLFxcXIzc2FTCaDSCSCv78/7O3tKbyNcRTixofGxkZkZWWhvr4eenp68PDwgLe3NwQCwYCO19LSgoqKih63MQwDuVwOuVwODocDPp8PHo9HnyWkzxwdHYekSZ5mLCXDoqamBk899RQOHjwIa2tr/P7771i6dKnWPwQZhkF5eTmys7PR0dEBfX19BAUFwdnZmZpNCRlDLCwsMHXqVNTW1iIrKwv5+fkoLi6Gt7c3PDw8+jXPnEQiYQOcSCSCubk59PX1u31mtLe3o6SkBJ2dnew0RDQFEemJSqVCZ2cnmpqa0NbWhoqKCvD5fK3XyFFNHBlSDMNgz549WLNmDRobG7Fs2TJ8/fXXsLa21vp5ampqkJWVhZaWFvD5fPbDnAYsjC9UEzf+MAyDiooKZGVloaOjA0KhEL6+vnB1de3Tj7fq6mo0NTVBJBLBycnphj8uVSoVKisrUV1dDQ6HAwcHB9jZ2VGtHOmRumKhra0N5ubmsLOz0+rxqSaODJmamho888wz+PPPP2FtbY19+/Zh6dKlWj9PY2Mjrl69ioaGBnC5XHh7e8Pb25umCiFknOBwOHBycoKDgwPbjSItLQ0FBQXw9/eHg4PDDUNWa2srAMDc3PymYUxPTw9OTk4wNzdHUVERKioq0NTUBHd3d+orR7rhcDgwNzdHW1sbWltbKcQR3ccwDPbu3Ys1a9agoaEB9957L7Zs2aL12rf29nZkZGSwv4hdXV3h6+tLH6SEjFPqvnEuLi7sgKakpCSYmZlh4sSJsLS07LYPwzBQKBQA0K8JhY2MjBAQEMDWyl29epVq5UiP1O8r9WAZbb4/KMQRraqtrcXTTz+NP//8E1ZWVvj9999x7733avUcCoUCeXl5yM/Ph0qlgoODA/z8/GipHEIIgGujAn19feHm5oa8vDwUFRXh/PnzcHZ2RkBAgEZY69qjqL/9ZqlWjvRF1/cVhTiis37//Xc888wzaGhowNKlS7FlyxbY2Nho7fjqiT8zMjLQ0dEBY2NjTJ48GVZWVlo7ByFk7BAKhZg4cSLc3NyQnp6OsrIyVFVVwc/PD+7u7lob7ES1cmSkUIgjg9bQ0ICnnnoK+/fvh5WVFfbu3Ytly5Zp9RxtbW3IyMhATU0NeDweJk6cqNUPYULI2CUSiRAZGYmqqipkZGQgIyMDpaWlmDx5MszNzbVyDnWtnJmZGYqLi1FRUQGxWAx3d/chXfeVjG8U4sigXLhwAffffz/Ky8txzz334JtvvtFq7dv1TadOTk6YMGECfSgSQvpFPZLUxsaG/Uw5f/48nJycepxOZKBEIlG3WjlXV9ce++MRMlgU4siAqFQqfPjhh3jzzTchEAjw448/4pFHHtFa04G66TQ9PR0SiQQmJiaYNGkSNZ0SQgaFx+PB398fzs7OSE9PR3l5OWxtbWFsbAxtzbilrpUzNTVFYWEhioqK0NLSQms0E62jtijSbzU1NViwYAHWr18PPz8/JCUl4dFHH9VagGtra0N8fDwSExMhl8sxceJEzJw5kwIcIURr1E2s4eHh4HA4YBiGXW5LW4yNjREQEABTU1M0NDSw89iNVz///DM4HA5mzZo10kUZMyjEkX45ffo0goKCcPz4caxevRqJiYkICAjQyrFVKhVycnJw5swZ1NbWwsnJCXPnzoWnpyf1fSOEaB2Hw4GdnR2MjY3B4XCgUqnQ1taGjo4OqFQqrZyDz+fDy8sLTk5OkEqlyMrKQl1dndZq/UjPxGIxfv/9d7z66quYNWsW+xq7ubn1aX+GYbB9+3ZERkbCxMQEJiYmiIyMxPbt23XqtaPmVNInSqUS//73v/Huu+/CyMgIO3fuxIMPPqi147e0tCA5ORnNzc0wNjZGYGAg9SEhhAwLDocDDocDY2NjSKVSyGQyyOVyGBoaamXScHVYFIlEKCwsRElJCVpbW+Hq6krNq0MkJiYG991334D2ValUuP/++7Fv3z4AYCsqEhISkJCQgFOnTmHXrl06MfKYQhy5qYqKCixfvhyxsbEIDg7G3r174e3trZVjq1Qq5OXlIScnBwDg7e0NX19f+mAjhAw7LpcLIyMjyGQySCQStLe3QyAQaG3gg3rQQ3FxMRobG9He3g4PDw8YGRlpofSkKwMDA8yYMQPh4eEICwtDY2Mjnn322T7t+8UXX2Dfvn2wsLDA33//jaioKADAxYsXsXDhQuzZswdTp07F2rVrh/Ih9Am1UZEbOnr0KIKCghAbG4u1a9fi4sWLWgtwLS0tOHv2LLKzsyESiRAdHY2AgAAKcISQEcPhcCAUCmFiYgIejweZTIbW1lbI5XKtHJ/H48HT0xMuLi6QyWTIzs5GTU2NTjXRjQXz589HbGwsPv74Y9x///1wcXHp035yuRzvv/8+AODjjz9mAxwAREVF4aOPPgIAbNq0Sav9JweKQhzpkVwux+uvv47bb78dCoUCf/zxB7788ksIhcJBH1ulUiE3NxexsbFobm6Gt7c3Zs6cqbX5mgghZLD09PRgZGQEAwMDMAyD9vZ2rfWV43A4sLGxgZ+fHwQCAcrKylBQUKAToaA/Kioq8Nhjj8HBwQH6+vrw9vbGm2++ic7OTna2gp9//rnHfRmGwdatWxEcHAxDQ0NYWFjgrrvuQmZmZrf7qo91s0txcfGgH1NMTAzq6+shEol67DK0fPlyiEQi1NbWIjY2dtDnGyxqTiXd1NfX495770VMTAwiIiKwZ8+ePncGvZmWlhakpKRALBZDJBIhJCSEwhshRCepa+V4PB4kEonW+8qpV3ooKSlBY2MjsrKy4OXlNSqW7MrNzUV0dDRqa2vB5/MxceJESCQSbNq0CSdPnoS7u/sN91+5ciV+++03uLm5wdfXF9nZ2Th06BBiYmKQlJQELy8v9r4+Pj6YNm1aj8dpamrC1atXtfa44uPjAQBTpkzpsdJCKBQiPDwcZ86cQXx8PObOnau1cw8EhTiiISMjA4sXL0ZRURGeffZZfPbZZ1r5sFKpVMjPz0dOTg5UKhW8vLzg5+dHTaeEEJ2np6cHpZ4AcgASSSeaJc0QCPjQF+qDo4W+cpZ2TmB4+qioqEBSaiZc3dxgamo6+IJfx0Sfp5XO+AzDYPny5aitrcXUqVOxb98+ODg4AABSUlKwcOFCXL58udf94+LikJWVhdjYWMyYMQMA0NjYiLvuugvnzp3DW2+9hZ07d7L3X79+PdavX9/tOFKpFHPmzAEALFq0qM9NpjeSm5sLAPD09Oz1Pp6enjhz5gzbl3skUYgjrEOHDmHFihXo7OzEd999hyeeeEIrx21tbUVycjJb+xYcHAwLCwutHJsQQoZaS6cCgf8+MYxnrBmSo6a+dStMDQb/o/zMmTNISkqCoaEh9u/fD3t7e3ZbcHAwfv75Z9x666297i+Xy/Hll1+yAQ4ALCws8MUXXyAkJARHjhzpUzmeeOIJxMXFYdKkSdi1a5dWBp80Njay5emNeltTU9OgzzdY1CeOgGEYvPfee7jrrrugr6+PU6dOaS3AlZWVITY2FmKxGF5eXpg1axYFOEIIGcWOHTsGALj99ts1ApzaLbfcAldX1173NzMz63H6j+DgYAiFQojFYjQ0NNywDB9++CF+/fVX2NjY4K+//oJIJOrno+hZZ2cnAEAgEPR6H3Uzq0Qi0co5B4Nq4sa5jo4OrFq1Cnv37sXkyZNx6NAhrfR/UygUSEtLQ1lZGfT19REZGUkrLhBCyBigbnIMDAzs9T6BgYEoKSnpcVvX/m7Xs7GxQVlZGdra2nqdK/Tw4cNYv349hEIhDhw4cMPA2F/qdbllMlmv95FKpQCgE30XKcSNY2VlZbjrrruQnJyMu+++G7/88otWfs20tLTg0qVLaGtrg62tLfvrivSdRCLBBx98gD179qC0tBQWFha47bbb8O6778LR0bFfxzpx4gQ+//xzJCYmQiwWw8TEBKGhoXj66aexZMmSIXoEhIwdJvo8pL7VS/Mgw0DSKYFMJgeHw4GhgQF4WuhHDIZBVXUVaqprwOPz4e7uPuj55Ez0tfOV39bWBuDasmK9udG2Gz0OdZNob1OupKenY/ny5VCpVNi2bRumTp3alyL3mXqgnbpZtSfqbbowKI9C3DgVFxeHu+++GzU1NXjrrbewcePGQfcnYBgGJSUlSE9PB8MwmDBhAjw9PXViVuvRpLOzE3PmzEF8fDzs7e1x5513ori4GD/99BP+/vtvxMfHw8PDo0/H+vzzz/Hiiy+Cw+EgKioKzs7OKCsrw8mTJ3HixAmsX78e77333hA/IkJGNw6Hc8O+ZKaGAnaCYEYlgwAc6OvrD/qzz9TDFTZmxiguLkZVSQFcXV11okVD/WO/tbW11/vcaNtA1dXVYdGiRWhra8O6devw0EMPaf0cPj4+AID8/Pxe71NQUKBx35FEIW4c+umnn/DUU0+Bx+Nh3759WLp06aCPKZfLkZqaioqKChgYGCAsLIz6vg3Qpk2bEB8fj6ioKBw/fpz9wPz000/x8ssvY9WqVYiJibnpcerq6rBu3Trw+XycOHECM2fOZLedPXsWt956Kz744AM89thjfQ6FQ4lhGEilUkilUsjlcigUCigUCiiVSvbv6y9KpZL9xc4wDFpaWthJWc+fP89+iXI4HOjp6YHH4/V64XK54PF44PP5EAqFEAqFtGYv6TOBQAAul4uOjg5IpVIoFAoYGhoOegS+hYUFhEIhCgoKUFxcDIlEAicnpxH9cawOL2lpab3e50bbBkImk2HJkiUoKSnBXXfdxU7Iq22RkZEAgEuXLkEqlXZrRZJKpbh06RIAaEwEPFIoxI0jSqUSr776Kj777DO4uLjg0KFDCAoKGvRxxWIxkpKS0N7eDnt7ewQFBd2wUyjpnUwmw9dffw0A2LJli0bz9ksvvYRffvkFsbGxuHz5MkJDQ294rISEBEilUsyfP18jwAHAjBkzMH/+fBw+fBhJSUlDHuJkMhna29shlUrR2dnJXrpel0ql/Z61nsfjaQS1rrPqq2sCGIYBwzAaga+v1EsuqS9CoVDjuoGBgVZqXMjYwOVyIRKJ2Pdza2srDA0NB/15aGRkBH9/fxQUFKCmpgYSiQQeHh7g8UbmK/y2227DRx99hCNHjqCmpga2trYa20+dOqWViXe7euKJJ3DhwgUEBQVhx44dQ/Z/bvbs2bC0tERDQwN27dqFRx99VGP7zp070dbWBmtr626fqyOBQtw40dnZiRUrVuCPP/7A9OnT8ccff8DGxmZQx2QYBoWFhcjMzASHw8GkSZPg7u5OX2iDcOHCBTQ3N8PT0xPBwcHdti9duhRpaWn466+/bhri+toPsbfOw/2lUCjQ3t6OtrY2tLW1afzd25JF6slU9fX1YWZmxoYjde0Yn89na8iuv+jp6fX4Xjt9+jQAsPNHdaVSqXqt1et6uT5g1tfX9zpTv/qLWyQSwcjISONf+jEz/nA4HBgYGIDH46GjowMdHR1QKBQwMDAY1Gcjn8+Hj48PSktLUV9fj9zcXHh7e2tlHs/+mj17NsLDw3Hp0iUsXboUv//+OztK9cqVK3jkkUfA5/O1tlTZRx99hF9++QV2dnY4fPjwkK41y+fz8cYbb+CVV17BK6+8Aj8/P421U1999VUAwIYNG0YsRHc18iUgQ665uRl33XUXYmJisGzZMvz666+DHmggl8uRnJyM6upqGBkZISwsDGZmZtop8DiWmpoKAAgJCelxu/r2vjRVTJkyBWZmZjh9+jRiY2O7Naf+888/8Pb2RnR0dL/KqFKp0NraCrFYDLFYzAY19dD8roRCIYyNjSESiWBoaKhRi6Wvrw+BQDCsoV9PTw8CgaDf4YphGDbcdb10dHSwYbWioqLbfgKBgA14JiYmMDMzg6mpqU58+JOhxefzYWxsjI6ODshkMigUChgZGQ2qeVVPTw+urq4QCoWoqKhAdnY2vL292RGVw4XD4WDHjh2Ijo7G+fPn4erqiokTJ0IqleLq1auIiIhAdHQ0du/erZUJ3bds2QLg2nP6wAMP9Hq//fv3w87Ojr3etf+gOlCWlZVp3P7AAw/gq6++0jjOiy++iLi4OPz555+YOnUqAgICAIBdGeLee+/F2rVrB/motIM+Sca4qqoqLFiwAKmpqVizZg2++OKLQffzaWtrQ0JCAtra2uDo6IjAwMAR+TU4FpWWlgIAnJycetyuvr23oftdmZqa4ocffsCDDz6I2bNnY+rUqXByckJ5eTni4uIwbdo0/PrrrzcMNCqVCi0tLRCLxWhuboZYLEZLS4tGrRSPx4ORkREsLS01aqFEItGYeV9wOBzw+Xz2i7knCoUCHR0dbKjtWht5/Ug3Y2NjmJqawszMjILdGKZef1Vdq9vW1jboJbs4HA7s7e3B4/FQUlLCBrmhrJ3qiY+PDy5fvoy33noLR44cwdWrV+Ho6Ih169bhzTffxMqVKwEAJiYmWjtnWVkZysrKet1+/Q/JnuaaU6lUGrf3NABDT08P+/fvx7Zt27B9+3ZkZWUBAMLDw/H4449j9erVOtPiRJ8aY1heXh7mz5+PoqIivPfee3jjjTcG/carra1FUlIS5HI5jT4dAuqh+4aGhj1uV39Q93Xk1913342jR49i2bJluHDhAnu7iYkJbr311m7TlUgkEtTX16OhoQFisRitra0agU0oFMLKykojfAy2mWis4PF4MDEx6fFLSyqVsiFYHYjLy8tRXl7O3kckEsHMzAwWFhawtLSEsbExPa9jAIdzbaQql8tFe3s72tvbYWBgMOhaaGtra/D5fBQUFCAnJwdeXl5aDUx94eTkhB9++KHHberg03Xe0UceeQSPPPLIDY/ZU1+6gfav628f2K44HA6eeOIJrU18P1QoxI1RSUlJuP3229HQ0IBt27Zh9erVgzpe1/5vXC4XkZGR3TqzEt3zySef4LXXXsNdd92Ft99+Gx4eHigsLMTGjRuxceNGxMXF4fvvv0d9fT3q6+vR0dHB7isUCmFtba1RY0Sd+AdGKBTCxsZGox+qTCbTqOEUi8UawU4oFMLS0hJWVlawsrKCSCSi534UU9fitre3QyKRQKlUDvoHkJmZGXx8fJCfn4+8vDy4u7vrxKwACQkJyMzMhIWFBSZMmDDSxRnTKMSNQSdOnMDdd98NhUKBAwcOYPHixYM6nlKpRFpaGkpLS2FkZISIiIgbTuRIBk49GrVrmOqqvb0dwI0n0lSLiYnBK6+8gpCQEOzbtw96enqQSCQwMzPDhg0bkJ6ejmPHjmHbtm0IDQ2FkZERXF1d2eBAgW1oCQSCHoNdY2MjG6orKytRWVkJgELdWKAeBKPuJ6dUKmFkZDSoLi7Gxsbw9fVFXl4eCgsLIZfLh+UHdl5eHo4ePYqHH35Yoz/0hQsX8OCDDwK4NqKUugkMLXp2x5g9e/bg4YcfhpGREY4ePYrp06cP6nidnZ24dOkSGhsbYWNjg7CwsDHTz0kXubi4AIBGM1tX6tv7sszMb7/9BgCYP38+srKyUF1dzTbXAsD06dNRUFCAhoYG3HrrrTqxhMx4JxAIYGdnx3bOlslkaGhoQENDQ4+hTn1fa2trrXQgJ0NP3U9OIpFAJpOhtbUVRkZGgwo7hoaG8PPzQ15eHsrKyiCXy+Ho6DikIb+5uRnPP/88XnrpJfj4+MDExAQVFRXsZ9TUqVOxcePGITs/uYZC3BjyxRdf4IUXXoCjoyOOHTuGiRMnDup4YrEYiYmJkEgk8PT0xIQJE+iX/xBTr0WYnJzc43b17ZMnT+71GHK5HHV1dexIqrq6OuTn50MoFMLFxYWtySkpKcEvv/zCNusQ3SMQCGBvb89O36AOdfX19aitrUVJSQlKSkrA5XJhbW0NOzs72NraDvtoRdI/HA6HnQhYIpGwAx4GMyWNUCiEr68v8vPzUV1dDYVCAVdX1yH7zPb09MSGDRtw/PhxlJSUID8/HwYGBoiMjMT999+Pp556ipZbHAYU4sYAhmGwfv16bN68Gb6+vjh+/DhbozNQFRUVSElJAcMwCA4OHvTxSN9MmzYNpqamKCgowJUrV7pNxrx//34AwKJFizRul0gkqK6uRnV1NTunmTqY1dXVYcaMGTAzM9P4QFfPOt614zHRbdeHura2NvZ1r6mpQXV1NYBrazqqa+logITuEgqF7ICHjo4OKJXKQXVjUM8lV1hYiPr6esjlcnh4eAxJLa25uTk2bdqETZs2af3YpO9oTZlRTqVS4ZlnnsHmzZsRERGB8+fPDypwMQyDrKwsJCUlgcfjYdq0aRTghpFAIMCaNWsAAM8++yzbBw64tuxWWloaZs6cidDQUHR2dqKgoADPP/88vL298eqrr6Kurg6WlpaYNGkSO6rq77//xoULFzS+GA4dOoRdu3ZBT08PS5YsGd4HSbRGJBLBy8sL06dPx2233YaQkBA4ODigtbUVWVlZOHPmDE6ePImsrKwhWcuSDB6Px4NIJAKXy4VUKkVHR8egRlVyuVx4enrC0tISzc3NyMvLg1Kp1GKJiS6hmrhRTKVS4cknn8T27dsxd+5cHDp0aFBzBalUKqSkpKC8vBympqaIiIigZrYR8K9//QsnT55EXFwcOxlvSUkJEhISYG1tjU2bNiEuLg51dXUArtW0VVRUQE9PDwsWLGD7LLq7u+PPP//Evn37sGjRIoSFhcHd3R1FRUVISkoCALz33nvw9fUdscdKtEcgEMDZ2RnOzs5QqVSor69HdXU1qqqqkJubi9zcXJiamsLZ2RmOjo7U5KpDug54kMvlaGtrG9SABz09Pbi5uYHL5aK2thZ5eXnw9vamfpNjEIW4UUqpVGL16tX4+eefMX/+fBw4cGBQgUuhUCAxMRF1dXWws7NDaGgojSoaIfr6+jhz5gw++OAD7Nq1CwcPHoSZmRkWLlyIe+65Bw0NDeBwOLCzs4OTkxMuX74MAN0mEeVwONi7dy9uu+02/PLLL0hLS8OVK1dgZmaG22+/HWvXrsVtt902Ug+TDCE9PT125OukSZNQX1+P8vJyVFZWIiMjAxkZGbC2toaTkxPs7e1psJIOUPeTUy/5pg5yAw1eHA4Hzs7O4HA4qKmpYZfpos/1sYXDDKbelowIpVKJRx99FL/99htuv/12/PHHH4P6VS2VShEfHw+xWAxXV1dMnjx50Ks6kMFhGAZisRhlZWWoqKiATCYDAFhYWMDJyQmOjo60LmcvbrR26ninVCpRXV2N8vJy1NTUgGEYcLlc2NnZwdnZGTY2NuOu/xzDMMjOzgYAnQk5UqkUEokEHA5n0CNXGYZBRUUFu0SirjzG8UShUCAvLw8A4Ofnp9X/Y/RKjjIKhQIrV67Erl27sGjRIuzbt29QI4A6OjoQFxeH9vZ2+Pj4aP0NRvpHLpejoqICxcXFaG5uBnCt35OnpyecnJx6XcmBkL7gcrlwdHSEo6MjZDIZOyVERUUFKioqYGBgAFdXV7i6uo6b5lYOhwMej8eujaueq3EkCYVCcDgcdhk3IyOjAdeWcjgcdroRddO6j48PBblhpF4OjMfjaf37lV7FUUSpVOLhhx/G7t27sWTJEuzZs2dQtTHNzc24ePEipFIpJk2aBA8PDy2WlvRHc3MziouLUVZWBqVSCS6XCzc3N7i6usLU1JSCNdE6gUAAd3d3uLu7o729HWVlZexanDk5ObCzs4Obmxusra3H/PvP2NgYTU1NaGpqgpGRkU48XvWyXOqlugYzBQmHw4GDgwM4HA4qKyspyA0jhmHQ1NQEoG+TtPcXNaeOEl2bUJcsWYK9e/cOqh9LfX09EhISoFKpEBIS0m0NTTL0VCoVqqqqUFhYyC6QbmpqCjc3Nzg6OlI/pQGi5tSBU6lUqKmpQXFxMWprawFcqwl2d3eHs7PzmH1PSiQSdn1OkUgEc3Nz6Ovr60S3EoVCgfb2djAMAwMDg0HPvVZVVYWqqioYGhrCy8uLgtwQUalU6OzsRFNTEzvJupubm9YHC1KIGwVUKhUee+wx/Pzzz1i8eDH27ds3qBq4yspKXL58GXp6epgyZQqsra21WFpyM1KpFMXFxSguLkZnZyf09PTg6OgId3d3mJubj3TxRj0KcdrR3t6O4uJilJSUQC6Xg8fjwdnZGR4eHjrR5KhtLS0tqKioGOli9IhhGKhUKgDXatUGGy5lMhnkcjm4XC7bdEuGlqOjI0xMTLR+XApxOq7rNCK33347/vzzz0H9EisuLkZqaiqEQiEiIyM11rwjQ6ujowP5+fkoKSmBSqWCvr4+3N3d4erqSjObaxGFOO1SKBSoqKhAYWEhWlpaAAD29vbw8fEZc58fEokEzc3NaG1thUKhGOniaFCpVGhvb4dSqYRAIBh0/9jy8nJUV1dDJBLR9CNDhMfjwdjYGKampkM2XReFOB3GMAyeeeYZbN26FfPnz8fBgwcH3NmYYRjk5uYiOzsbRkZGiIqKGtSccqTvWlpakJ+fj/LycjAMA1NTU3h7e8Pe3l4nmmvGGgpxQ4NhGDQ2NiIvLw81NTUAAGtra3h7e8PKymrM1eYwDDOoSXeHglwuR1JSEurr6+Hg4ICgoKABhy+GYbBhwwZ8/vnnmDZtGg4ePEjfCVrE4XCG5f8ENYbrsHXr1mHr1q2YN28eDhw4MKgAd/XqVeTn58PU1BSRkZHjZuTZSGpqakJubi67FJKVlRW8vb3HRUdxMvZwOBxYWlpqrARQUVGBuro6mJubw9vbG3Z2dmPmvT1cX8L9oW5BSU5ORmVlJRQKBaZMmTLgIPfBBx9AKpXi888/x9KlS/HXX3/R1EWjDNXE6ahPP/0UL7/8MqKionDy5MkBV50zDIPMzEwUFBTAwsICkZGRY7Zzsi5gGAZ1dXXIy8tDfX09AMDOzg7e3t6wsLAY4dKND1QTN3za29uRn5+P0tJSqFQqGBsbw9vbG46OjlTLPIQYhsGVK1dQWloKa2trREREDKpG7oknnsD27duxfPly/Prrr/TajSIU4nTQzp07sWLFCvj7++P8+fMD/vJnGAbp6ekoKiqCpaUlIiIiKMANEXV4y8rKglgsZudm8vb2HpLOrKR3FOKGn0QiQWFhIYqKiqBUKmFoaAgfHx84OztTIBgiDMMgNTUVJSUlsLKyQkRExIBHmioUCtx77704ePAgXnzxRXzyySc6VwtJekYhTsf8888/WLhwIezs7BAXFwdnZ+cBHYdhGKSlpaG4uHjQ/8HJjTU1NeHq1auor6+Hnp4eXFxc4OXlRf1LRgiFuJEjk8lQVFSEgoICyOVyiEQiBAQEjKlmVl2izc95iUSC+fPn49y5c/jPf/6DV199VculJUOBQpwOSUxMxJw5cyAQCHD+/HkEBAQM6DgU4IZHW1sbsrKyUFlZCQBwdnaGn58fraowwijEjTy5XI78/HwUFBRAqVTC3NwcAQEBsLKyGumijTkMwyAjIwOFhYWwtLREZGTkgD/vxWIxZsyYgfT0dPz8889YuXKllktLtI1CnI7IycnB9OnT0d7ejlOnTiEqKmpAx+ka4AbbV4L0TCKRICcnB6WlpWAYBnZ2dvD396dmUx1BIU53dHZ2IicnByUlJWAYBjY2NggICICpqelIF21M6dr3ebBBrrKyElOnTkV5eTkOHTqEO+64Q8ulJdpEIU4HdP1Pc/DgQSxcuHBAx+naB87KygqRkZEU4LRILpcjLy8PhYWFUCqVsLCwQEBAACwtLUe6aKQLCnG6p62tDdnZ2exkuk5OTvDz86MuB1rUtUZusC0wOTk5mDZtGjo6OnD69GlERkZqubREWyjEjbCu1dc//fQTHnnkkQEdR5v/gYkmlUqFoqIi5OTkQC6Xw8TEBP7+/rC1taV+PjqIQpzuEovFyMrKQm1tLTgcDjw8PODr60sDrrSk6w/5wbbEJCYmYvbs2dDX18f58+fh7++v5dISbaAQN4K6diTdvHkzXn/99QEdp+s8cIOtSiea6uvrkZ6ejpaWFhgYGMDf3x9OTk4U3nQYhTjdV1dXh6tXr0IsFkMoFGLChAn0/0pLunapsbGxGdQ8cseOHcOiRYtgb2+PuLg4ODk5abm0ZLAoxI0QpVKJpUuX4uDBg3jhhRfw6aefDvgDLDs7Gzk5OTQPnBZ1dnYiMzMT5eXl0NPTg5eXF7y9vSkcjwIU4kYHhmFQWlqKq1evQiaTwdLSEpMmTaL+clrQdR45Ozs7hIeHD3iqlx07duChhx5CQEAAzp07R/Nd6hgKcSNkzZo12LJlCx544AHs2LFjwP/BioqKkJaWBjMzM0ydOpUC3CCpm06zs7OhUChga2uLiRMnjskFv8cqCnGji0wmQ1ZWFoqLi8HhcODu7g4/Pz/6LBskhmGQnJyM8vJyuLi4ICgoaMAVBerJ56dPn46TJ0/SWs86hKoVRsDWrVuxZcsWzJ49Gz///POAA1xlZSXS0tJgZGRENXBaUF9fj7S0NLS2tsLQ0BAhISE0vxUhQ0wgECAwMBCurq5IS0tDYWEhKioqqIl1kDgcDoKDgyGTyVBaWgqhUDjgaateeukllJeX47PPPsOzzz6Lbdu20euiI6gmbpjFxsZi3rx5cHFxQWJi4oBHNtbV1SE+Ph58Ph/R0dE0ymsQrm869fb2hre3N43sHaWoJm70ur6J1cLCAoGBgTR9zyAoFApcuHABYrEYEydOhKen54COo1QqsXDhQhw7dgxffvkl1q5dq+WSkoGgEDeMioqKEB4eDqlUivj4eEyYMGFAxxGLxbhw4QIAYPr06dSHZIAYhkF5eTnS09Mhl8tha2uLSZMmUSAe5SjEjX4ymQzZ2dkoKioCh8OBr68vvL29aQmvAZJKpTh//jza2toQGho64AEKYrEYERERKCgowLFjxzBv3jwtl5T0F4W4YdLW1oapU6ciIyMDhw4dwqJFiwZ0nPb2dpw7dw5yuRxRUVE0A/oAdXZ2IjU1FdXV1RAKhZg8eTIcHBxGulhECyjEjR1isRgpKSloaWmBqakpgoOD6UfrAHV0dODcuXOQSqWIjIyEjY3NgI6Tk5ODiIgI6OnpITExEV5eXlouKekP+lkzDFQqFR5++GGkp6fjvffeG3CA6+zsxMWLFyGVShEaGkoBbgAYhkFZWRlOnz6N6upqODo6Ys6cORTgCNFBZmZmmDlzJnx8fNDS0oLY2Fjk5ORApVKNdNFGHUNDQ0RFRYHH4yExMRFisXhAx/H19cXevXvR3NyMxYsXo6WlRbsFJf1CIW4YvPPOOzhw4ADuv/9+rFu3bkDHkMvliI+PR3t7O9UaDVBnZycSExORnJwMPT09hIeHIywsDAKBYKSLRgjphZ6eHvz9/TFjxgyIRCJkZ2fj7NmzFB4GwMTEBBEREWAYBhcvXkRbW9uAjjN//nx89NFHyMrKwoMPPgilUqnlkpK+oubUIbZv3z4sW7YMoaGhOHv27IAWR1epVIiPj0ddXR18fX3h5+c3BCUduxiGQUVFBdLS0iCXy+Ho6IhJkybRMPkxippTxy6lUonc3Fzk5eUBAPWVG6CqqiokJibC0NAQ0dHR0NfX7/cxGIbBo48+il9++QXr1q3DBx98MAQlJTdDIW4IpaSkYNq0aTAxMUFSUtKAOpMyDIPLly+joqICbm5umDx5Mg3t7gepVIrU1FRUVVWxUxlQLebYRiFu7GtqakJKSgpaW1thamqKkJAQGsHaTyUlJbhy5QpMTU0xbdq0AU1R1dnZidmzZyM+Ph47d+7Egw8+OAQlJTdCIW6I1NTUIDw8HDU1NYiJiUFUVNSAjpOZmYn8/HzY29sjPDycAlw/1NfXIykpCVKplGrfxhEKceODUqlETk4O8vLyoKenh8mTJ8PFxYU+I/shJycH2dnZsLa2RmRk5IBqNKuqqhAeHo6GhgacPXsW4eHhQ1BS0huqgx4CMpkM99xzD8rKyvD9998POMCVlZUhPz8f5ubmCA0NpQ+nPmIYBtnZ2bhw4QIUCgVCQkIQFhZGAY6QMYTL5SIgIADR0dEQCoW4cuUKLl++DLlcPtJFGzV8fHzg6urKrmU7EPb29jh48CAA4K677kJVVZUWS0huhkLcEHj55Zdx4cIFvPTSS1i5cuWAjtHU1IQrV65AX19/UAsYjzcSiQRxcXHIycmBqakpZs2aBWdn55EuFiFkiFhYWGDWrFmws7NDRUUFYmNjBzzycrzhcDiYPHkyLC0tUVBQgJKSkgEdJywsDD/++CMqKytx7733QqFQaLmkpDcU4rTszz//xNdff42ZM2fiww8/HNAxJBIJEhMTAQARERED6nQ6HtXW1iImJgb19fVwd3dHdHQ0rXlKyDggEAgwZcoUTJo0CRKJBOfOnUNhYSGot9DNqUfqGxgYIC0tDY2NjQM6zgMPPIAXX3wRFy5cwFtvvaXlUpLeUJ84LSouLkZQUBD4fD6uXLkCR0fHfh9DqVTi/PnzEIvFg5pZezxRqVTIyspCfn4+eDwegoODafDCOEZ94sY3sViMpKQktLe3w97eHkFBQTSNUB80Nzfj3Llz4PF4mDlzJgwMDPp9DJlMhmnTpuHy5cv4559/cMsttwxBSUlXVBOnJXK5HPfffz+am5vx66+/DijAMQyDK1euQCwWw9vbmwJcH3R0dOD8+fPIz8+HmZkZZs2aRQGOkHFMPUGwo6MjqqqqEBMTM+DapfFEPcpXKpUiISFhQE2iAoEAe/fuhbGxMVasWIHq6uohKCnpikKclmzYsAEJCQl47bXXsGDBggEdo6CgAOXl5bCzs4O/v7+WSzj21NXVITY2Fk1NTfDy8kJ0dDSte0oIAZ/PR2hoKIKCgth1Q4uLi0e6WDrPwcEBvr6+aG5uxpUrVwbUHO3h4YHt27ejtrYWy5cvp4mAhxiFOC04cuQIPvroI0RGRmLTpk0DOkZNTQ0yMzNhbGyMkJAQGol6E0VFRbh48SJUKhUiIiIwYcIEmvCTEMLicDhwdXVlmwZTU1ORmppKS3bdhK+vL+zt7VFRUYHc3NwBHePee+/FU089hdOnT9MkwEOMvvUGqby8HA8//DDMzMywe/fuAU2Y2NraiqSkJPD5fERERAzoGOOFSqVCamoq0tLSYGhoiBkzZsDOzm6kizUqSCQSbNy4ET4+PtDX14eDgwNWrVqFioqKAR2vuLgYTz31FNzd3SEUCmFlZYWoqCh89NFHWi45IQNnYmKCmTNnwsrKCsXFxez606RnHA6HnTw5Ozt7wFOGfPrpp5g8eTLeeustnD17VsulJGrDMrAhOTkZBw8eRExMDIqLi1FfXw+GYWBubg4fHx9ERkbi3nvvRWhoaLd9Z82ahdjY2G638/l8mJiYwMTEBC4uLggJCUFERAQWLVo0oKWtBkKhUGDu3Lk4e/Ys/vzzTyxZsqTfx5DJZDh79iw6OjoQFRUFa2vrISjp2CCVSnHp0iU0NDTA2tqa1j3th64zq9vb2yM6OhrFxcVITEyEtbU14uPj4eHh0efjHT16FEuXLoVEIkFISAi8vb3R0NCA9PR0GBkZIT8/fwgfzY3RwAbSE5VKhYyMDBQVFcHQ0BARERG0ysMNdHR0IDY2FkqlEjNmzBjQc5WdnY3Q0FCYmZkhNTUVVlZWWi1jcXEx3N3de9zG5XLZfBAVFYWVK1ciMjJSq+fXCcwQysnJYW6//XYGQJ8uYWFhzJkzZzSOMXPmzD7vD4AxMTFh1q5dy4jF4qF8aAzDMMzGjRsZAMzatWsHtL9KpWLi4uKYgwcPMgUFBVou3dgiFouZ48ePMwcPHmTS0tIYpVI50kUaVTZs2MAAYKKiopjW1lb29k8++YQBwMycObPPx8rKymL09fUZa2tr5sKFCxrblEolc+nSJW0Ve0BOnTrFnDp1akTLQHRXUVERc+jQIeavv/5iKisrR7o4Oq2+vp45dOgQc/z4cUYmkw3oGL/88gsDgLnjjju0/rldVFTUr3ywcuXKAT8OXTVkNXH//PMP7r//fnbSRQcHByxbtgzR0dGws7ODQCBATU0NkpKScPjwYSQnJwMAZs6ciZiYGPY4XWvi/vnnH3bkIcMwaG1tRVNTE9LS0hAbG4sTJ06w/R2cnJzwxx9/YMqUKUPx8HD69GnMmzcPwcHBiIuLG9BqALm5ucjKyoKLiwuCgoKoH1wvKisrkZycDJVKhcDAQLi6uo50kUYVmUwGGxsbNDc3Izk5GcHBwRrbAwMDkZaWhqSkpB5rw693++234+jRo/jvf/+L22+/faiKPWBUE0dupqGhAYmJiZDJZPD394e3tzd9/vaiqKgIaWlpg1r68ZFHHsEvv/yCjz/+GC+//LLWyta1Ji4sLAw//fQTu02pVKKqqgpHjx7F1q1bIZPJAACPP/44vv/+e62VYcQNRTJMSUlhDAwM2PS7fv16RiKR3HCfkydPMsHBwd1qBLrWxBUVFd3wGAUFBcy8efPY+1tZWTF5eXmDfDTdVVdXM3Z2doxIJGJyc3MHdAz1L5xTp04xcrlcyyUcG1QqFZOdnc0cPHiQOXr0KFNfXz/SRRqVTp8+zQBgPD09e9z+73//mwHAvPXWWzc9VmlpKaOnp8d4eHhouZTaQzVxpC/a29uZ06dPMwcPHmQuXbrEKBSKkS6STlKpVExiYiJz8OBBprCwcEDHaG1tZfz8/Bgej8fEx8drrWxda+Ju1Jpw5swZhsfjMQAYDofDZGdna60MI03rAxsUCgWWLVsGiUQCAPj444/x3nvv3XTVgblz5+LixYt47LHHBnxuDw8P/PPPP7j33nsBXFsAffXq1QM+Xk8YhsGjjz6K6upqfP/99/D29u73MWQyGS5fvgw9PT2EhYWBx+NptYxjgUqlwpUrV5CdnQ1TU1PMmDEDlpaWI12sUSk1NRUAEBIS0uN29e1paWk3PVZMTAxUKhWmTp0KhUKB33//Hc8//zzWrFmDrVu3oqmpSXsFJ2QIGRoaIjo6mh2JGRcXx9bWkP/hcDgICgqCoaEhMjIy0Nzc3O9jiEQi7N27F1wuFw888ADa2tqGoKS9mzVrFpYuXQrg2nf4f//732E9/1DSenrYsWMH8vLyAFx74vpTdSoUCvHQQw8N6vx6enr48ccfERsbi9raWsTGxiI2NhYzZ84c1HHVfvrpJxw9ehQPP/wwHnjggX7vzzAMUlJSIJFIEBQURB1re6BQKHD58mVUV1fDxsYG4eHhFHQHobS0FAB6nTxafXtf1k1UL5ItEokQHR2N+Ph4je0bNmzA/v37MXv27AGXV6VSQSqVQiKRQCqVorOzEwqFoteLUqkEwzBsFws1dbMqh8MBl8sFj8fr9SIUCqGvr89eaK3i8YHH4yE8PByZmZkoKCjA+fPnERUVNaDVCsYyPp+PsLAwnDt3DpcuXcLMmTP7PYvC5MmT8dFHH+G5557Da6+9hm+++WaIStuzadOmYc+ePQCuNRED1wZ8HTt2DMePH8elS5dQWFiIlpYWGBgYwNHREdOmTcMTTzxxw25ZXZt033rrLbz99ttISEjA1q1bcfbsWVRVVUEikSAlJQVBQUFaf1xa/2bctm0b+/err76q7cP3iUgkwlNPPYV///vfAID9+/drJcSVlZXhxRdfhIODA7744osBHaOwsBDV1dVwcnKCi4vLoMs01shkMiQkJKCxsRFOTk4IDg6m+d8GSf2rt7dR2+oJkrsGoN6oa9q2b98OkUiEXbt24bbbbkNdXR3effdd7NixA0uWLEFmZmavq5YolUq0t7ejvb0dbW1taGtrQ2dnJ3vpa22IOphxuVxwOJxufXWY/+/uqw6F6sDXFzweTyPUGRkZQSQSQSQSwcjIiKYBGkM4HA4mTpwIfX19ZGZm4ty5c4iKioKxsfFIF02nmJubY8KECcjIyEBaWtqA5jN99tln8eeff+Lbb7/F0qVLh7XfateKAPXnwP33349Dhw51u29rayuys7ORnZ2NH374AS+99BI+/vjjPj3e999/H2+++eawzUeo1RDX3t7OLtxuYGAwouumLViwgA1xXQdKDBTDMHj88cfR0tKC3bt3w8zMrN/HaGpqQmZmJoyMjDB58mTqSHsdiUSCixcvorW1FV5eXggICKDnSMeoP5gUCgW+++47LFu2DMC1D/jffvsNOTk5uHTpEr755hv8+9//RktLC8RiMVpbW9nQ1tHR0e24XC4X+vr6EIlEGuFJX18fQqEQfD6/W+1Zb++NGw1sYBgGSqVSoyZPLpdDKpWytX5dL2KxuMflh4RCIRvqRCIRzMzMYGpqSuFuFPPy8oJQKERKSgrOnz+PiIgIWFhYjHSxdIqHhwfq6+tRXl4OKyurfg8y09PTww8//IDJkydj1apVSE9PH7awfOXKFfZv9Q9MhUIBT09PLFq0COHh4XB3d4e+vj4qKyuRlpaGLVu2oKKiAp9++ikcHBxu2rJ46NAhXLlyBZ6ennjhhRcQGhoKPT09JCcnD9l7SashLi0tjf3ACwwMHNEPNPWvBIZhkJOTM+jj/fjjj/jnn3/wyCOPDGhEnlwuR1JSEjgcDsLDw+nD/jqtra24ePEiJBIJJkyYAC8vr5Eu0pghEokAoMfwBFz78QWgTx+m6mOJRCK27ylw7Zdtc3MzFi1ahEuXLuHw4cOIiIjQWLaHy+XCyMgIDg4O3Wq2BALBsAR2DofDhsC+ksvl3WoO29ra0NzcjIaGBo37GhkZsYHOzMwMZmZm9H99FHF2doZAIMClS5cQFxeH8PBw2NrajnSxdAaHw0FwcDBiYmKQnp4Oc3PzfncJ8vDwwIcffog1a9bgtddew7fffjtEpf2fvLw87Nixg70+b948AMBnn30GLy+vbp89wcHBuOOOO/Diiy9i4cKFOHXqFDZt2oQnn3yS/QzsyZUrVzB16lQcP35cYwnIiIgILT+i/9FqiKuvr2f/Huk3vkAggImJCZqbmyGXy9Ha2jrgxF9WVoaXXnoJjo6O+Oyzz/q9P/P/C9t3dHRg0qRJMDU1HVA5xqrGxkbEx8dDoVAgJCQEzs7OI12kMUXdbF9eXt7jdvXtfflVrb6Ps7Mzampq0NDQgPr6ejQ3N4NhGMjlcgDXap1tbW3ZQGNiYgIDA4NRWbPK5/PZQNYVwzCQyWRobW2FWCxmLxUVFRqrYIhEIlhZWcHS0hJWVlY3HeRFRpatrS2mTp2KhIQEJCQkICgoiLq+dCEQCBAaGooLFy4gKSkJM2bM6Hef5aeffhr79+/H1q1bsXTpUsydO1fr5VQqlaiursaRI0fw5ptvsj9Wb7nlFjZU3Wxgor6+Pj755BMEBQVBLBbj1KlTuPPOO3u9P4fDwU8//TSsa3hrNcS1tLSwf98orQ4XkUjEjqRpaWkZUIjr2oy6Z8+eATWjlpSUoLKyEvb29r3OLj1e1dTU4NKlSwCu/VoZ6fA/FgUGBgIAOxfj9dS3T548uddjyOVyNDQ0sO//6upqJCQkALj2oa4ObOrwYmNjM6S/PnUBh8OBUChklxxTk8vlaG5uhlgsZmvriouL2QXYKdTpPgsLC0yfPh0XL15ESkoKpFLpgGYiGKssLS3h5+eHrKwsZGRk9LvDvnoA4qRJk/DYY49ppVk1Njb2pj8Sw8LCsHv37l63t7S0oLGxEe3t7WwrQtfWhOTk5BuGuKioKPj4+PSz5IOj1RDXtVp1uIcQ96RrR+2B1n798MMP+Oeff/Doo49iwYIF/d6/ubkZ6enpMDQ0RHBw8KisiRgqlZWVGmvGUv+ToTFt2jSYmpqioKAAV65c6faBu3//fgDAokWLNG5va2tDdXU1qqur0djYCIZhYGxsDBMTE4jFYhgZGWHKlCkwNjZm39effPIJAHSbUHg84fP5sLKy0gh2HR0dqK+vZy9dQ52JiQns7OxgZ2cHMzMz+ozQEcbGxoiOjsbFixdx9epVKJVK+Pr60uvz/7y9vVFfX4+SkhJYWVn1Ovq9N+7u7vjPf/6DZ599Fq+++iq2bt06JOUUCoUIDQ3Fww8/jMcee6xbrWFaWhq+/PJLHDt27KbrSHdtbezJUIw+vRmtDvvr+qFVU1OjzUP3m1QqZUOcQCAYUM1gaWkp24z66aef9nt/pVKJy5cvg2EYhIaGUt+YLioqKpCUlASBQIBp06ZRgBtCAoEAa9asAXBtdJi6WQG4tkh1WloaZs6ciZCQEDQ0NCAzMxNr166Fn58f1q1bB7FYDFtbW0ycOBFz587Fa6+9BoZhsHnzZgBgv9ROnjyJn3/+GRwOB08++eTwP1AdZmhoyK7xfOutt+KWW25BcHAwnJyc0NnZidzcXJw9exb//PMPrly5gurq6j6PpCVDx8DAANOnT4eZmRlycnKQnZ2tUTMznnE4HISGhkIoFCI1NbXXPrc38tRTT2H27Nn47rvvcPLkyUGVJywsDOnp6ezl6tWrKCsrQ2trKy5cuIAnn3yyW4D79NNPERwcjB9++OGmAQ7ovV+x2kh8j2m1Jm7SpEng8XhQKBRITU2FXC4fseCiDk8A4Ovr2+/9GYbB6tWr0drait9//31Azag5OTlobW2Fn58fhZQuysvLkZyczAY4Gso/9P71r3/h5MmTiIuLg7e3N6Kjo1FSUoKEhARYWlri5ZdfxrFjx9jpPZqamlBRUQEul4sFCxZozJv22muvISYmBidPnoSPjw8iIyNRX1+P+Ph4KJVKvPfee0O23N1YoQ51Li4uYBgGjY2NbK1nSUkJSkpKwOVyYW1tDScnJ9jZ2dHcdSNEIBBg6tSpiIuLQ25uLlQqFY2c/39CoRDBwcGIj4/HlStXEBUV1a/npadm1YHOnWpkZISJEyf2+f7nzp1jR5taWlripZdewpw5c+Dh4QFTU1N2KU2VSsX+37tZgB+J/6NarYkTiUQIDw8HcG26iOPHj2vz8P1y9OhR9u9Zs2b1e//t27fjxIkTeOyxx3Dbbbf1e/+mpibk5+fD1NSU+lJ0UVZWhsuXL0MoFGL69OkU4IaJvr4+zpw5gzfffBOGhoY4ePAgCgoKcMstt+DDDz+ESqWCvr4+fHx8MGPGDHh6egK4VhNx/QcTn8/HkSNH8OGHH8LKygr//PMP0tPTMXPmTPz1119Yv379SDzEUYvD4cDS0hITJkzA3LlzMXfuXEyYMAHm5uaorq5GUlISjh07huTkZNTW1lJN0Ajg8/mYOnUqzM3NkZ+fj8zMTHod/p+trS1cXFxQV1fXpwnDr+fm5oaPPvoIpaWlwzq3rHpUrJ6eHmJiYrB+/XpERkbCxsZGYy30xsbGYSvTQGh9st/HH38cFy9eBHBtya077rhD26e4qdbWVnz33XfsdfVyG31VWlqKl19+GU5OTmwfn/5QKpVISUkBAJqstgt1DZyBgQGmTZs2rCN4yLVflMuXL8fMmTM1JgB2cnKCk5OTRqB+55138M477/R6LD6fj9deew2vvfbakJd7vBGJRPDy8oKXlxc6OztRUVGB8vJylJWVoaysDEKhkH3NTE1NqUZomPD5fERFRSE+Ph4FBQXgcDhUI/f/Jk6ciNraWmRmZsLGxqbXicV78+STT2L//v34/vvvsXTp0mGZYzY9PR3AtYFfN6rBU899q6u0ni4eeughdo6vmJiYfoUgmUymMZfLQKhUKjz22GOoq6sDcK0WbsaMGf06xvPPP4/W1lZs3759QAMi1M2ovr6+NJ3I/6uoqMDly5ehr69PAW4YqVQqVFZW4sKFCzh58iSys7Mhk8ng7u6O6OhozJs3D/7+/lQjqqP09fXh6emJmTNnYs6cOfDx8QGXy0VBQQFiY2MRExODoqIidmoXMrT4fD4iIyNhYWGB/Px8ZGVlUY0crj0vQUFBUCgUuHLlSr+fEw6Hgx9++AFGRkZ4+umn0dnZOUQl/R/1nLZd+wj35KuvvhrysgyG1kMcj8fD77//zq4998orr+DNN9+86YsSGxuLqKgobN++fcDnLiwsxG233YZ9+/YBuDbQousyYH1x9OhRHDx4EPfddx/mz5/f7zI0NTUhLy+PmlG7qKysZJtQKcAND4lEgqtXr7JrAjY0NMDBwQERERGYP38+Jk+eDAsLC6pFGEWMjY3h7++PefPmITo6Gm5ubujo6EBaWho7IGIgi5OT/lEHOXNzc+Tl5SE7O3uki6QTBtus6urqirfffhsFBQX46KOPhqCEmtR95fPy8nD27Nke7/Pee+/h2LFjQ16WwRiSVcWDg4Nx4MAB3HfffWhubsamTZvw448/4v7770d0dDTs7OzA4/FQW1uL5ORk/PXXX2yV5Y3WOM3NzWWbgRiGQVtbGxobG5Geno7Y2FgcP36cXRbIyckJf/zxR79m/u/s7MTatWthZGSEjz/+uN+PW92MyuFwEBISQs2oANunRz2IQRfmDxyrGIZBQ0MDCgsLUVVVBeBac6m/vz9cXFxoPrIxgsPhwMLCAhYWFpgwYQIqKipQXFzMDoiwsLCAh4cH7O3t6TNoiKibVtWDHfT09AY0gG6sUTerZmRkDKhZ9fnnn8ePP/6I999/Hw899BDc3NyGpqAAVq1ahUOHDoFhGCxatAgvvvgiZsyYAVNTU+Tm5uLHH3/EyZMnMWPGjF5Dni4YkhAHAPPnz0diYiJeeOEFHD16FJWVlfj0009vOFVHZGQkNm3adMNj3oyJiQkefvhhbNq0qd9NmR9//DEKCgrw4Ycf9nvOGwDIzs5mR6MOdITNWNLY2MjOAzd16lRqshsi6ibTvLw8dsJtGxsbeHh4wMbGhmrbxjAejwdXV1e4urqiqakJRUVF7PQ9+vr68PLygqura79n1Cc31zXIZWdnQygUDmnoGA34fD6Cg4Nx8eLFAY1W5fP5+PrrrzF37ly88MILOHjw4JCVdfHixXj++efxxRdfoKWlpcc+wBEREfjjjz9gbW09ZOUYrCH9n+3j44MjR44gOTkZBw4cQExMDIqLi9HQ0ACVSgVzc3P4+voiKioK9957L0JCQvp8bB6Px0486urqiuDgYERGRmLx4sX9Tv8AUFxcjPfffx9+fn544YUX+r1/Y2MjjUbtoqWlBfHx8QCuhXMKtdqnVCpRVlaG/Px8tLe3g8vlwt3dHR4eHlTjOQ6Zm5vD3NwcEyZMQElJCQoLC5GRkYGcnBx4eHjAw8MDAoFgpIs5pggEAkRGRuLcuXNITU2FUCiEvb39SBdrRNnY2MDFxQWlpaUoKSnpd7CdM2cO7rvvPuzduxdHjhwZ0FrlffX5559j7ty5+Oabb3Dp0iW0tLTAwsICAQEBuO+++3qcHFjXcBjqlQkAWLJkCQ4ePIiTJ0/2ex03pVKJmJgYdHR0YObMmeM+sEgkEpw9exZSqZQdsk20Ry6Xo6SkBPn5+ZBKpeDz+fDw8IC7u7vG0Pjx6vTp0wCufRmMZ0qlEqWlpcjPz0dHRwe4XC7c3Nzg6enJ9lkm2tHW1obz589DLpcjKipKY+L78Ugul+P06dOQy+WYM2dOvytWysvL4efnBzs7O2RkZFBXkBugDhP432CGZcuWDWgh3uzsbLS1tcHX13fcBziZTIa4uDh0dnYiJCSEApwWyeVyZGdn48SJE8jMzAQATJgwAbfccgv8/PwowBEN6prZuXPnIjQ0FIaGhigoKMDJkydx5coVSCSSkS7imCESiRAZGQkOh4OEhASNdcTHI3WzqrqfeH/ripycnPDWW28N2yCH0Wzc18RJpVJMnDgRVVVVyM7O7ndfuObmZsTExMDMzAzR0dHjuiOxQqFAXFwcmpqaMHHiRHbCWDI4SqUSxcXFyM3NhUwmg5GREby8vODs7Eyz+PeAauJ6xjAMampqkJeXh8bGRujp6cHd3R0+Pj7UzKoldXV1uHjxIgQCAWbMmDGgrj1jyZUrV1BSUoLg4GC4uLj0a1+ZTIbAwEAUFxcjKytr3Pc37M34TRz/7+OPP0Z+fj42btzY7wDHMAzS0tIAXJswcDwHOJVKhaSkJDQ1NcHLy4sCnBYwDIPS0lKcOnUKGRkZ0NPTQ1BQEObMmQM3NzcKcKRfOBwO7OzsMH36dERFRcHY2BgFBQU4ceIEcnNz2XmzyMBZW1sjNDQUUqkUcXFxkEqlI12kETVhwgQIBAJkZmb2ey5DgUCAr7/+Gp2dnQPqpz5ejOuauJKSEvj7+8PZ2Rnp6en9/jVaWlqKlJQUuLu7Y/LkyUNUSt3HMAxSUlJQVlYGZ2dnBAcH04jIQVDXmFy9ehWtra3g8/nw8fGBu7s7Bbc+oJq4vmEYBhUVFcjKykJHRweEQiF8fX3h6uo6rn+QakNhYSHS09NhZmaGadOm6Xzn+KE02O/JpUuX4o8//sB///vfIR3kMFqN6/+pL774IiQSCZYvX87OZN9XcrkcV69ehUAggJ+f3xCWUvdlZ2ejrKwMtra2CAoKogA3CM3Nzbhw4QISEhLQ0dEBb29v3HLLLfDy8qIAR7SKw+HAyckJc+fOZb9c09LScPr0aVRXV49w6UY3Dw8P+Pj4QCwW49KlS+N6VQdnZ2eYm5ujqKioX5NRq1Qq5OfnY9GiRdDX18dzzz03LCs5jDbjNsT9888/OHDgAO68807MmjULRUVFOHnyJIqKitgJg28kKysLUqkUAQEB47o/SXl5OXJzc2FmZoawsDD6BT9AcrkcaWlpiImJQUNDA1xdXTF37lwEBASAz+ePdPHIGKbuGzdv3jz4+fmhs7MTCQkJSEhIuOmSRKR3fn5+cHZ2Rm1tLa5evTrSxRkxHA5H40fCzQItwzCorq7G6dOnkZmZCQcHB7z88ssoKCgY0CT8Y924bE5VKpUICgpCQUEBcnJy4OTkhPLycly9ehWdnZ0wNjbGpEmTep3gTz2YwdzcHNHR0eO25kksFuPcuXPg8/mYOXMmTVswAAzDoKysDFevXoVUKoW5uTkmT54MMzOzkS7aqEXNqYMjkUiQmZmJiooK6OnpwcfHh2qCB0ipVCIuLg6NjY0D6tw/lqSlpaGoqOiGz0NraysyMjJQW1sLLpcLHx8feHp6QqlUYvLkySgvL0dBQQFsbW2HufS6a1xWm+zcuRMZGRl44YUX4OzsDA6HA2dnZ8ydOxc+Pj5ob29HXFwcEhMTu/0S7TqYYfLkyeM2wKl/rQPAlClTKMANQHNzM86fP88OwQ8ODkZ0dDQFODKiDAwMEBYWhqlTp8LQ0BDZ2dnUxDpAXC4X4eHh0NfXR2pqKhobG0e6SCPGz8+v10EOMpkM6enpOHPmDGprazW+j7lcLgQCAd5//320t7ffcFWn8Wjc1cRJpVL4+vqipaUFhYWFPX5hdnR0IDMzE5WVldDT04Onpye8vb3B5/PZTppubm4IDAwc/gegA5RKJS5cuICmpiaEhITA2dl5pIs0qigUCmRlZaGwsBAA4O7uDn9/f2o21RKqidMelUqFwsJCZGdnQ6lUws7ODpMnT6Yfbf0kFotx/vx58Hi8cd1qUVJSgitXrrCDHFQqFUpKStg+6ebm5pg0aRLMzc277cswDCIjI5GSkoLs7Gx4eHiMwCPQPeNuyMy3336LkpIS/Oc//+m1xsPQ0BDh4eGor69HRkYG8vLyri1jw9gis7gKARZ8zPcdn4MZGIZBamoqO5UIBbj+aWhoQEpKCtrb22Fubo7AwMB+r/FLyHDR09ODl5cXHB0d2SbWhoYGTJw4kW3FIDdnZmaG4OBgJCUlITExEdOnTx+XzdMuLi4oKSlBUVERTExMUFRUhJaWFujr6yMkJAROTk69vqc4HA42b96MOXPmYOPGjdixY8cwl143jauauJaWFnh6ekJfXx+5ubl9+jXEMAxKSkqw7/xVbMn431PlaGaAhYH2WDTZARMcTMbNh1lBQQEyMjJgY2PDzlBObq5r7RuXy4W/vz88PDzo+RsCVBM3dKqqqpCamgqpVApbW1sEBgaO21qlgcjKykJubi6cnJwQEhIyLv//V1VVITExEcC1YObt7Q1vb+8+T8Ny22234fjx40hJSRm3rWFdjas+cR9//DHq6+vx9ttv9/mDh8PhwM3NDWYObhq3V4gl+C62EAu/Oo+5n8bi85O5KKhrG4JS647a2lpkZGRAJBIhLCxsXH4ADURDQwNiYmJQWFgICwsLzJo1C56envT8kVHH3t4ec+bMgZOTE2pqanDmzBmUlZWN6yk0+kO9Hmh5eTny8/NHujjDSj0tV1JSEnubv78//P39+zWP3gcffACGYfDGG28MRTFHnXFTE1dTUwNPT092Yt/+vGkYhsGXf8Tgs6SOm953goMJFgc6YGGgAxzNxs4v1La2NsTGxoLD4WDGjBkQiUQjXSSdp1QqcfXqVRQWFkJPTw/+/v4U3oYB1cQNj661cnZ2dggMDKSFyvtAoVDg3LlzaGlpQWRk5JgfaXn9CHwTExP4+/sjJSUFHA4Hc+fO7Xd/4AcffBC7d+9GTEwMZs6cOUQlHx3GTU3cpk2b0N7ejvfff7/fs2fX1NQAnf9b0FjI08PyEGu4m3T/Ms6sbMEHR7MxbfNpLP02Dr9eLEZd6+heekWpVCIpKQkKhQJhYWEU4PqgtbUVZ8+eRWFhIczNzTFr1ix4eXlRgCNjRtdauerqasTExKC2tnaki6XzeDwepkyZAj6fj8uXL0MikYx0kYZMY2Mjzp49y47ADwwMxKxZs2BnZwd/f39IpVIUFBT0+7jvvvsueDweXn/99XFfCzwuauIKCwvh5+eH0NBQxMXF9euLlGEYxMTEoKS+DW9f/l/m/e2xKeBygLLSMpzPqURyHVDR0fNx9TjANC8rLAp0wPwJdjA1GF2jENPT01FYWAgfHx/4+/uPdHF0XmlpKdLS0qBUKuHn5wcfHx8Kb8OIauKGX0VFBa5cuQKFQgFvb2/4+fnRxN83oe4bZmlpialTp46p50sikeDq1asoLy8Hh8OBh4cHfH19NWrcVCoVTp8+jc7OTtxyyy0QCoX9OseaNWuwZcsW/Pnnn1iyZIm2H8KoMS5C3PLly7Fr164BVb2WlZUhOTkZzm4euHt3KXv7lgdDYGF0baUGlUKOtpoSFFdUI7lBDymNPNR29Lzqg4Crh5m+1lgc6IB5/rYwEOj2CKWx/EGjbQqFAmlpaSgrK4O+vj7CwsJgaWk50sUadyjEjYz29nYkJSVBLBbDwsICYWFhNOjhJsbaD2SlUon8/Hzk5eVBqVTCxsYGEydOhLGxcY/3r6ysxKVLl+Dh4YFJkyb161zqLlIuLi5IS0sbt+vTjvlHfeXKFezatQsLFizod4BTKpXIysoCn8/HRH9fiISVaJMqAADNEjkb4vR4fJg4esHfwg7O1UVY0NaMcgkX6e0muFQlRWP7/9ZklSlVOHG1Bieu1sBQwMU8f1ssDnTADB9rCHi6FZA6OjqQkpICgUCA0NBQCnA30NzcjKSkJLS1tcHW1hbBwcH9/mVJyGhmZGSE6OhoXL16FQUFBThz5gxCQkJgZ2c30kXTWRMmTEBjYyNyc3NhaWkJGxubkS7SgDAMg6qqKmRkZEAikUAkEmHixIk37e9nb28PMzMzFBUVwcPDA0ZGRn0+p62tLV566SW8++67+PXXX7Fq1arBPoxRaczXxC1YsADHjh1DSkoKgoKC+rWvejqNgIAAeHt7Y/bHMSiqv7aCw2vzfRHs0vOEhNKWBrRVF0Ell4LD10cVzw5J1XIkFDagpVPR47lM9HlYMNEei4McEOlhCa7eyDa/qVQqnD9/Hk1NTeOi8+1glJSUsGsCBgQE0OCFEUY1cSOvuroaycnJkMvl8PT0REBAAP0I7EV7eztiYmLA5XIxa9asUTc4pLm5Genp6WhoaACPx4Ofnx/c3d37/HrX1dUhLi4OTk5OCA0N7de5W1pa4OHhAQMDgz5PGzbWjOn/VRcvXsSxY8fw4IMP9jvAyeVy5ObmQl9fH+7u7gAAK9H/Frpvlsh73I/D4UDf1AqW3iEwsnEFlDLYSYpxt2MHvlzqj3W3+WGGtxUM+JrNqC2dCuxNKsPy7QmIeP8U3j6cicslTSPWaTMrK4ud0JcCXM9UKhXS0tJw5coV6OvrIzo6mgYvEALAzs4Os2fPhoWFBQoKChAfHw+ZTHbzHcchIyMjBAUFQSqV4vLly6Omo75UKkVqaipiYmLQ0NAANzc3zJs3D56env0K7NbW1rC2tkZ5eTmam5v7VQYTExNs2LAB5eXl2L59e38fwpgwpmviFi9ejL///huZmZn97m+QnZ2NnJwcBAYGws3NDQDw9I7LOJpxbf3A+8OdcWeQ402Po5RL0V5TjE5xHQAODCztYWTjAgWjh9QyMS4U1CO5tAlyZc8vg6OZARYFOmBxoAP87Y2HJSDU1NQgPj4e5ubmmD59Ov2C7oFMJsOlS5dQX18PKysrhIeHQyAQ3HxHMuSoJk53qFQqpKeno7i4GEZGRoiIiOi1f9R4l5qaiuLiYvj5+cHX13eki9MrlUqFoqIiZGdnQ6FQwNLSEpMmTRrUyjNisRixsbGwtbVFZGRkv/bt6OiAm5sbDAwMkJ+fP+6WLxyzfeIyMjLw119/YcmSJf0OcFKpFPn5+RCJRHBxcWFvtzb+Xx8ncS81cdfj8oUwcfKFgYU9WqsKIWmoRKe4FiJbV4S52SHc3QISmRKXS5sQl1+PtPJmKLvk6gqxBFtjC7A1tgCe1kZYHOiIxUEOcLfqe9+B/pBIJEhOTgaPx0NYWBgFuB60tLQgISEBHR0dcHd3x8SJE+l5IqQHenp6CAwMhImJCdLT03H27FmEhoZSP7keTJw4EY2NjcjOzoaVlZVODoqqqalBRkYG2traYGBggODgYNjb2w+6csHMzAyOjo6oqKhgfxj3laGhIV544QVs2LABu3btwsqVKwdVltFmzNbErVixAjt37kRiYiLCw8P7tW9aWhqKiooQHh4OBwcH9vYvT+Xh0xO5AIAoT0s8N8e7X8dlGAad4jq01xRDpZCBp28IkZ0HBCIz9j5tnQokFDcgLr8BWVUt6O3Fmej4/5MKT3aAg5YmFWYYBhcvXkRdXV23x06uqaqqwuXLl6FSqTB58mS2lpboDqqJ0011dXVISkqCTCZDQEAAdT3oQWtrK2JjYyEQCDB79mydqVVqbW1FZmYmampqwOVy4e3tDS8vL62u/9rW1obTp0/DzMwM0dHR/XpviMViuLq6wtHRERkZGePqR/WYfKRFRUXYs2cP5s2b1+8A197ejuLiYpiZmcHe3l5jm5XofzVxzR19q4nrisPhwMDcBhbeoTC0doJCKoG4OAPNpVlQyjoBACJ9Hub62eLNhQHYsjwED0e5wsum++S6GRUteP9INqZuPo1lWy/it4vFaGgb3KTCJSUlqKurg4uLCwW46zAMg9zcXCQmJoLL5WLq1KkU4AjpB2tra8yYMQPGxsa4evUqkpOToVQqR7pYOsXY2BgTJkyARCJBZmbmSBcHcrkcGRkZOHPmDGpqauDk5IS5c+fC19dXqwEOAEQiEVxdXdHU1ITq6up+7WtmZoZnnnkGWVlZOHTokFbLpevGZE3cM888g2+//RanTp3q96/xy5cvo7y8HFOnToW1tbXGthNXa/D4r9fWfXM0M8DH9w5u8V2lrBNt1UWQtjQAHA4MrZxgaOUEvR7+c9S2dCKusAFxBQ0oa+x5+S+uHufapMKT7TF/oh1M9Pv+K66jowNnzpwBj8fDnDlzdOYXoC5gGAbp6ekoKiqCiYkJIiIiYGhoONLFIr2gmjjdJpfLkZycjOrqalhZWbGrF5BrGIZBXFwc6uvrERUVNSLTjjAMg5KSEmRlZUEmk8HMzAyTJk2ChYXFkJ63s7MTJ0+ehIGBAebMmdOv2riamhq4ublh0qRJSEhIGDe1vGMuxFVXV8PNzQ2BgYGIj4/v1wvZ2tqK06dPw9raGlOnTu22PaW0CUu+iQMAiIQ8bHs4TCtllrWJ0VpVCKW0A3o8AUR2bhCaWvda9rLGDlwsbEBcQT1qWnqufRPw9DDb1xqLAh0w1+/Gkwp3bUYdqQ8NXaVUKpGcnIzKykr6whklKMTpvq4/jExNTREZGTnqptYYSh0dHTh9+vSINKvW19cjPT0dLS0tEAqFCAgIgLOz87CFoqysLOTm5iIkJATOzs792vfZZ5/FN998g5MnT2Lu3LlDVELdMuaaUz/77DNIpVK88cYb/X7T5eXlAQD8/Px63N61ObVNqoBC2fOqDP0lEJnBwisYxg6eYBgVWspz0VSYBnlHa4/3d7YwxLIwZ3y2LAib7pqI2yfZsxMPq8kUKvyTWYM1u1IQtukEXtiTglNZNZApupe5azMqBbj/kcvliI+PR2VlJRwcHBAZGUkBjhAt4HA4mDRpEvz8/NDc3Izz58+jvb19pIulMwwNDTFx4sRhbVbt6OjApUuXcOHCBbS1tcHb2xtz586Fi4vLsNZqeXp6gsvlIi8vr9/Trbz66qvgcrl4//33h6h0umdM1cSJxWK4uLjA2dkZ6enp/erc2NHRgZMnT8LCwgLTp0/v8T6dciX83jzGXv/6gWBYirQ7K79KqUB7bSkkDVUAGOib2cDI1hVc/o3Po2IYZFe34mJBPeILG9mVJa5nZsjHgol2WDTZAREelpB2SnD69Gnw+XxqRu2is7MT8fHxaG5uhru7OyZNmjRuqudHO6qJG12Ki4uRmpoKoVCIyMhImJmZjXSRdMJwtZAoFArk5eUhPz8fKpUK9vb2mDBhQr9WT9C2jIwMFBQUICIiot8jmR966CHs2LEDCQkJmDJlyhCVUHeMqZq4LVu2oLW1Fa+//nq/R6fk5+eDYRj4+Pj0eh99PhfGwv/NytLbhL+DocflwdjeAxZewRCIzNAprkVj3mW015WBUfVe86fH4SDA3gSPTffAtytC8PptvojuYVJhcYccuxPL8OD2BER9cAov/XYBBWIlgoKCKMD9v/b2dpw7dw7Nzc3w8/OjAHcDEokEGzduhI+PD/T19eHg4IBVq1ahoqJiUMfNy8uDgYEBOBwO5s2bp6XSEl3k5uaGKVOmQC6X4/z586irqxvpIukEDoeDoKAg8Hg8pKSkQC7X7vcNwzAoKyvDqVOnkJubCyMjI0ydOhVTpkwZ0QAHgJ0wODc3t9+1cevWrQMAfPDBB0NRNJ0zZmriOjo64OrqCiMjI+Tl5fUrkEilUpw4cQIikQgzZ8684Rd2X5be0haGYSBra0JbVSGUsk7o8YUQ2blDaGLZ51AhU6iQUtaEiwUNN5xU2NnCAIsmO2BRoAP87IZnUmFd1NraigsXLkAqlWpM9Ey66+zsxOzZsxEfHw97e3tER0ejuLgYiYmJsLa2Rnx8PDw8PAZ07NmzZyM2NhYMw2Du3Lk4efJkn/elmrjRqb6+HgkJCVCpVAgPD6e55P6fuqbSxcUFwcHBWjlmU1MT0tPT0dTUBIFAAD8/P7i6uurU1BxXrlxBSUkJpk2b1q954wDgrrvuwqFDh5CZmYmAgIAhKqFu0J1XbJB++OEH1NfX49VXX+13jVJhYSGUSiW8vb1vGl6sRf2f8HegOBwOhMYWsPAKgcjODYxSgZaybIiLM6Do7Fv/EQFPDxHulnhhng+2rgjFM7M8EeRsBu51D7OsUYJvYgqw4ItzuPWzs/jqVB6K68dXH5WWlhZcuHABMpkM4eHhFOBuYtOmTYiPj0dUVBRyc3Oxd+9eJCQk4JNPPkFdXd2AF6T+4YcfEBMTg8cff1zLJSa6zMrKCtOnTwePx0NiYiKqqqpGukg6wdXVFdbW1igtLUVNTc2gjtXZ2Ynk5GScPXsWYrEYHh4emDt3br/WOh0uXl5eAIDc3Nx+7/vGG28AwP+x9+fhbdz3vT/6Guw7QBAkwX0nJVI7ZcmbLEtyktqJkzRN62bpaZsu95wmafI7v9v2tLdN87Rpenq6uFmaX9r0pstJmqRN2zRuc3tsSZZsiZZkUStFUtx3cAMIgNiXmfsHBIqStRAkQQAjvp5HT2KSM/gOgJl5z2d5f/ijP/qjDV1TPiKLSFw8HqepqYlIJMLo6GhGQ3Dj8TivvvoqWq2WY8eOPVTE/cq3u/jR9ZSHzUuPVfPBVYze2ijERIzA7BiRxdSJrLc7MZbWolBlngadHLjO2+N+rgVM3JwL39dUeFeVddlU2GmVb/dYWsDF43Eee+yxd3gEbnEnsViM0tJSfD4fly5dekeEYPfu3Vy7do2LFy9mNNR6dnaW7du3s3//fn7rt36LI0eObEXiHjFWnov79+/f8qzkdreqVqvl6NGjGXu0JZNJhoaG6O/vJ5lMUlJSwo4dO7BYLFla8cZw8eJFpqamOHz4cMa1kkePHuWNN95gaGiI2tra7CwwD8gv6b1G/u3f/o3x8XE+/elPZyTgIBWqTiQSq4rCwV2Gv1mOxN2NQqXBUtlMUeMe1AYLYc8M7v6LhBamkKTVd8pG/W40UR9HWxz87gd289WP7uNnHq+lseSddRDXJn184T96eeJ/nuCn/vItvnVuDE9QXoOs0zeNRCLBgQMHtgTcKjh79iw+n4/GxsZ7png+/OEPA/DKK69ktN/PfOYzhMNhvva1r23IOrcoPCwWC0899RQajYaLFy9uReRIdatu27aNUCi07KKwGiRJYnp6mpMnT9Lb24tOp+PgwYM88cQTeS/gAJqbU1ORMjnmNL/xG79BMpmU/bVEFiLuK1/5ChqNhl/+5V/OaLv004lOp1u1H03JOqc2bARqvQlb/U4s1a0IShWBmRE8g5eJLi0+dFtJTLLkGkZQKDE56wCwGzW8sLOcL3xwJ3/+0h5+an81VUV3imFJggsjHn77B9089gfH+dlvXuCfuyZZiuTmPdgolpaW6OzsXI7AbdXhrI6rV68CsG/fvnv+Pv3za9eurXqfP/rRj/je977Hb/3Wby2nUrZ4NLFYLDz55JNoNBrefvvtjB385UhDQwNms5mBgYFV2bH4/X46Ozt5++23icVitLe3c/ToUZxOZ8HUPFutVsrKypienmZp6d6WW/fjXe96Fy0tLfz1X/814XA4SyvMPQUv4q5du8Ybb7zBSy+9lHEL9vj4ONFolKamplXXAzjMuYvErUQQBHTWEoqb92EsrSEZi+Ibu4F37AaJ6P2/sMH5ScR4FGNp9T1tS8osOn58byV//OHd/K+f2MUH91RQar7z75KixOn+ef7vf7pKxxeO81//dxc/uu4iEi+sETqBQOCOGrgtAbd6xsfHAaiqqrrn79M/HxsbW9X+gsEgv/Irv0Jrayu/8Ru/sTGL3KKgSQs5tVrN22+/ve56sEJHoVCwa9cuRFHk+vXr9/27aDTK1atXef3111lYWKC2tpZjx45ldJ/LJ9LRuMHBwYy2UygUfPKTn8Tj8fCd73wnG0vLCwrvE72Lr371qwB86lOfymg7URQZHBxErVZnlC/PZTr1XggKJcbSGoqbO9BaS4gtLeIZvMSSawQxeadXXDIWIbQwiVJrQF/88DqTaruBlx6r4c9f2sPvf2AHz+9wYjPcWX8XS4j8540ZfuXbl+j4/df4v753hdf75ohvkBFytohEIrz11lvEYjH279+/lULNkEAgAHDf8WNpi4LVPj3/9m//NmNjY3z9619Ho9E8fIMtHgnSQk6pVPL222/j8XhyvaSc4nA4qKqqYnZ29h3RSVEUGRoa4sSJE4yOjmK32zl8+DB79uwp6GkYxcXF2O12JiYmMo6o/ezP/ixGo5GvfOUrGVuVFAoFLeIWFxf51re+xYEDBzI29ZuamiIUCtHY2IhKpXr4BrcoMa/sTs2f2jClRou1upWihl2odEbC7inc/V2EPTPLX94l1xBIEubyBgRh9R+9IAg0lZr4L0/U8Rcf2cfvvHc7x7aVYtLe+b4FY0n+9fIUP/+3b/PYHxznN//lOm8NuUmK+XXyxONx3nrrLUKhELt3794qnM4xFy9e5Mtf/jL/5b/8F5599tlcL2eLPCM9lgvg/PnzGafV5EZbWxsqlYrr16+TTKayH3Nzc7z++ut0d3ejUqnYv38/Tz/9tGyMk1taWpAkKeNonNVq5Wd/9me5cuUKnZ2dWVpdbiloEfc3f/M3hMPhjKNwkiQxNDSEUqmkvr4+o20dpttRgmA0uWGjtzYKtcFCUcNuzJXNCAIsTQ+yOHSF4PwEsaVFtNYSNCbbmvevUAi0VVj5xUMpU+Fff08rTzc50Knv/CqlTIXH+cg3zvHk/zzB773Sw5UJb86fhpLJJOfPn8fv97N9+3ZZdy1lE5PJBKS65u5FumbHbDY/cD+JRIJf+qVfwmaz8Sd/8icbu8gtZIPdbuexxx5bfgCTc43Tw9Dr9bS2thIKhbhx4wbnzp1bfk9aW1s5evQolZWVBVP3thpKS0uxWCyMjY1lbHr8yU9+EridtZMbqw9B5RmiKPK1r32NkpISfvInfzKjbT0eDz6fj7q6uoxTN467xmz5wvENH721XgRBQF9UhtZSTGh+ktDC5C1fOQFD8calDVUKBXtrithbU5QyFR5fpHPIzeWJO02FZ/1Rvnl2hG+eHaG22LBsKtzqfPANfqORJImuri7cbjcNDQ3LtRZbZE5NTQ0Ak5OT9/x9+ucPE8mTk5NcuXIFp9P5jvPY6/UCqUjdU089hSiK/N3f/R3RaJRIJEIkEiEWiyFJEqIoIkkSkUhkefv/83/+D4IgLP9Tq9XodLo7/mm12jv+v5xufHKjrKyMPXv2cPnyZd566y2efvrpRzb1Xl1dzcDAACMjIwBUVlbS3t6esTtDoSAIAo2NjVy+fJnx8XEaGxtXvW1bWxtHjx7l+9//Pi+//LLsap8LVsSdOHGCoaEhfuM3fiPjfH/6i78WN3mdWolZp2Ipkqo38+ahiEujUKpSJsFikrAnNYt1caQbg6MSY0kVgiIzr6EHoVEpONhQzMGGYkKxBBdHF+kcWuD6lI+V2dQxd4ivvj7IV18fpLXMzPv3VPDirgpqiu9dW7VRSJLEtWvXcLlcVFZWsmPHjq0b9jrYvXs3AJcuXbrn79M/37Vr16r2NzMzc98ORJ/Pt5wK6e3tXf65VqtFo9GgVCqXhVoymVx+UjcYDMviThRFIpEIPp/vvtFgQRDQaDTo9XqsVitWqxWbzYbFYsnYl2uL7FBTU0M0GqWnp4fz588v18s9KkiSxPj4OL29vcRiqXKeoqIi9u/fn+OVZZ/Kykpu3LjByMgIDQ0NGV2//9t/+2+cPHmSb37zm/zWb/1WFle5+RSs2e+HP/xh/vmf/5mhoaGMxFg4HOa1117D4XDw5JNPrum1j/7JKYZvTTP4tfe0si+Lo7fWSzIexd3fhVKjxeRsIDAzQjIaQqHSYHLWobWWZFXM+CNxzg976Bxa4ObM0n1NhXdX226ZCpdTZtn4ItybN2/S19dHSUkJBw8efKQu/Nlgpdnv5cuX2bNnzx2/v5/ZryiKBAIBvF4vXq8Xn8+Hz+dbru0BUKlUGI1Genp6+OQnP8njjz/Od77znXdEze7Xafcgs19JkojFYsuRvJX/0hG+UChENBpd3kYQBMxmMzabDZvNtizwtr5DuUGSJG7cuMHQ0BBOp5MDBw48Eg9kbreb69ev4/P50Gq1bN++nfn5eaampnjiiScydmcoRHp6ehgYGODxxx+nrKxs1dvF43FqamrQ6XQMDg7K6twtyEjc9PQ0P/jBD3j3u9+dcTRtbGwMSZIyroVbicOkXRZx+dCh+iCCcxMgiZjK6tGai9CYbIQ9LoJz4/gn+1F7XJjKG1Drs5PatOjUvKutjHe1leEORDl3S9AN3zXS6+qEl6sTXr7wHz0crLfz/t2VPL/DSZFx/emS6elp+vr6sFqtPPbYY7I6gXOFRqPhU5/6FH/wB3/AJz/5SV599dXljtQ/+7M/49q1axw+fJh9+/bh9XqZmZnh61//Ot///vd5/PHH+Zmf+RkA1Go1drt9Oepls9kwGAx33JSNRuOGjUATBAGtVotWq8Vqtd737yKRyLLITAvO8fHxZWuVtLBzOBw4nU6Ki4sL0r6hEBEEgfb2dqLRKJOTk/T29sp6PmYoFKKnp4epqalUk1lTEy0tLajVakpKSnC5XPT09FBSkt0H8nygrq5uOY2ciYhTq9V84hOf4Itf/CKvvvoqzz//fBZXubkUpIj75je/STKZ5L/+1/+a0XaiKC6P5VpPXnxlh2quDH9XQyIaIrI4g9pgQWNORQsFQcBQXIHOWkJwbpywx8Xi0FV0tlKMZXUo1dmrMSk2aXnvrnLeu6scly/MW0NuOofcTHlvFylLEpwb9nBu2MPn/q2bQ80O3r+ngne1Od/RDbsa0mOhtFotBw8ezHiu7hb357d/+7c5fvw4nZ2dNDc3c+jQIcbGxjh//jzFxcX82q/9Gq+++upynVo6apBIJHjsscewWq3vEGz5gk6nw+l03nGdSKdj06LO6/UyPDzM8PAwKpWKsrIynE4npaWlj2yt1mYhCAJ79uwhEAgwMDCAxWK5r2dhoZJIJBgcHGRgYABRFHE6nbS3ty83FUGqZKC+vp6hoSGmp6eprNy8MZC5wGAwUF5ejsvlIhAI3PFePIxf+qVf4g//8A/5y7/8yy0Rl0uSySTf+MY3qKio4H3ve19G205PTxONRmlra1vXjWNlh2o+R+KCsymjVZOz7h3Hq1CpMVc0orc7WXKNEPHOEfW7MZRUYyiuQMhyVKHcqudD+6r48b2VjHtCvDXspnPQzXzgdhorIUq8fnOe12/Oo1Vd59j2Ut6/u4JnW0vRqR8eTYtGo5w/fx5Jkjhw4IBsi35zhU6n4/XXX+cP//AP+fa3v80PfvADzGYzx44d4yMf+QiJRAKdTkdTUxNOp3O5Ts5msxWkrUs6lZuOAEiSxNLSEi6Xi9nZWaamppajJcXFxcuiLpMbzRarR6lUcuDAAd544w0uX76M0WikqCh/S1tWiyRJTE1NcePGDSKRCGazmR07dtw3Xdrc3MzY2Bi9vb2Ul5fLPiJcX1+Py+VidHSUHTt2rHq7uro6nn/+eV555RUmJydlI/oLribuRz/6Ee9973v5nd/5HX7v934vo23PnDnD4uIi7373u9Fq196M8NWTA/zJq/0APNFQzK8ey78ux3hoicXhq2jMdmy1D041SJJEbMmTqpeLRVBqdJic9WjM9k2NkkiSxOBcgM5hN+eG3HjvI5BNWhXvbi/j/bsreKrJgVr5zouWKIqcPXsWj8fDnj17tqxEskAsFmNiYoKpqSkWF2+PfCsuLsbpdFJWVvZQi5Fs8KCauGwSiUSWTVjn5+eX6/xMJhMVFRXU1tbe1xx5i7WzuLjImTNn0Gg0HD58uKCNbb1eL9evX8fj8aBWq9m2bRt1dXUPFWbpmt9du3atq1SoEJAkiZMnTxKNRnnPe96TUXnMD3/4Qz7wgQ/w+c9/nt/93d/N4io3j4ITcT/90z/N9773PUZGRjKqk1laWuLkyZNUVVXdUWi9Fr57YZz/8S+psSfby8187n3t69rfRiNJEt7RbuJBH/amvah07xxsf8/tRJGQe5rQ/ASSmERttGEur1/19huJKEr0uPy8Nezm/IibYPTeI73sRg3P73Dy/t0VPFZnR6EQkCSJq1evMjY2RmNjY0ZPa1s8GEmScLvdjI2NMT09jSiKKJXK5ahTWVlZzlOJuRJxK0kkEiwsLCx33aYbJUpLS6mtrcXpdMo+YrKZTExMcOnSJYqKinjqqacKru41EonQ29vL+Pg4giBQV1fHtm3bVn0uJRIJjh8/DsBzzz2XkYF9ITI0NER3dzf79u1b9dxzSL1P1dXVGI1GBgYG8rKUI1MK6pP2+/3827/9G4cOHcq40Hl0dBRgQwqk82301t3EAl7iQR86W2lGAkxQKDCWVKGzlRKcHSPincUzeBm9vRxjaQ0K1ebVkykUAjsqreyotPLzT9ZxbdJH57Cbi6MeoonbBsueYIxvnx/n2+fHcVp0vG9XOR0lElHXGKWlJbIueN5M4vE44+PjjI6OLo/cstvt1NbWUlFRIfubRqaoVKrlmjpJkpibm2N0dJTZ2Vnm5ubQarXU1NRQX1+/lebfAKqrq/H7/QwODnL16lX27t1bEDfoZDLJ8PAw/f39JBIJHA4HO3fuxGKxZLQflUpFS0sL169fZ3h4mJaWliytOD+orq6mp6eH0dHRjEScSqXiIx/5CC+//DIXLlzg4MGDWVzl5lBQV95//dd/JRKJ8LGPfSyj7ZLJJBMTE5jNZux2+7rXcUdjQ56JOEmSCM6OgiBgLK1Z0z6Uag2Wqmb0xU4CrmHCHhcR3zzG0hr09vJNvziqlAr21Raxr7aIaCLJpTEvbw0vcHncS2KFCd2MP8Jfnxnhr4FSvZoPH7BRMh+kuWzzU3pyIRAIMDIywvj4OIlEAo1GQ2NjI7W1tTlJlRYigiBQVlZGWVkZkUiE8fFxxsbGGBgYYHBwkIqKChoaGigqKioI4ZGvtLW1sbS0xMTEBMXFxXldQiFJEjMzM9y4cYNgMIjBYGDfvn04nc41fwfq6uoYGhpiYGBgTUb2hYRGo6GyspKJiQn8fn9GovdjH/sYL7/8Mt/61rdkIeIKKp367ne/m1OnTjEzM5ORGBsfH+fy5cvs2LEjI6fn+zHlDfPU/zy5/N9//4kD96zLygUR3zz+iZvoiyswl2duZnw3kiQR9S0QmBlBTMRQag2Yy+vRmHJfQByKJXh71EPnkJvuu0yFV7LNaebF3RW8f3cF1fatmqTVsLi4yM2bN5mdnQVSg8gbGhqoqqrK+1RVPqRTH4YkSczOzjI8PMz8/DyQavhobm6mvHzzH5TkQiwW49SpU8RiMZ555pmMI1qbgd/vp7u7m/n5eZRKJa2trTQ0NGzIeTU5OUlXVxdNTU20t+dXmc9G4/F4ePPNN6mvr1+1qTikzr22tjYWFhaYnp4ueMeCgonEuVwuTpw4wYsvvphxNG1sbAylUplR2PVBFN/lXebPk6kNqSjcGIJCibFkY45VEAR0thK0FjvB+UlCC1N4R2+gMdsxOetRaXOXCjJoVBxuKeVwSyneUIzTl3q4MBlmeOnOG2DfzBJ9Mzf54/9zk701Nl7clTIVLs2CqXChs7S0RG9vLy6XCwCn00lDQwMOh2NLWGwggiAsp1v9fj/Dw8NMTk7y9ttvU1RURFtbGw6HI9fLLDg0Gg379+/nzJkzXLx4kWeeeSZvUv2xWIy+vj5GR0eRJImamhq2b9++oY0YlZWVDA4OMjw8TENDg6xT9UVFRVgsFiYmJmhvb1+1CBYEgY997GP8zu/8Dq+99hovvPBClleaXfIjfLQKvvvd7yKKIh//+Mcz2i4YDOLxeCgvL9+w8LJOrcSiu31huF8X5WYT9S+QjEXQF1dseP2aoFBiKquluHkfWquD2JIHz+ClVIQumdjQ11oL2oibJ2wBfv1JG1/56T187GAN9Y531gNeHvfye//ew+N/eIKPfuMc37kwjjcUy8GK84twOMyVK1d4/fXXcblcOJ1Ojhw5wsGDBx8JE9FcYrFY2LNnD8899xz19fV4vV7Onj3LW2+9hc/ny/XyCg673c62bdtYWlri+vXruV4OoigyPDzM8ePHGRkZwWaz8cwzz7B3794N76QVBIHW1tbl15QzgiBQU1NDIpG478i++/HRj34UgG9961vZWNqmkh+PKKvgW9/6FhaLJWNvuPQg7o32hHGYtfhvzU/NB8NfSZIIzU+CoMBQnD0PLqVGh7V6GzG7j4BrmNDCFBHvHMayWnS2spzc7OPhAEuuYRRqLebKZhRKFe/bVcH7dlXg8obpHHbTObTAtPf2cHRRgs5bZsOf+7dunmku4cXdFbyrrQzjGkyFC5VYLMbAwADDw8OIokhxcTFtbW0bUju6RWbodDp27dpFY2Mjvb29TE1NMTc3R1VVFdu2bVueiLHFw2lubmZhYYHx8XEcDseGZWEyZW5uju7ubpaWlpY/38rKyqxeJ51OJ2azmZGREZqbm2VdG1dZWUl3dzeTk5MZGR03NDTw5JNP8oMf/IClpaWCru8tiLtVb28vly5d4hOf+ERGTy6SJDE5OYlGo6GkpGRD1+QwaRmez5/RW7HAIolIMCtRuHuhMVopatxDZHGWwOwYS1ODhN0zmMob0Bg3rw5FTCbxT9wECazV21Ao7/xKl9v0/MS+Kj50y1Q4JdwWWAjcjr7FkxIn+uY40TeHTq3g2PYyXtxVwbOtJasyFS5E0l1xAwMDxONxLBYL27dvp6wsN0J8i9sYjUb2799PU1MTvb29TE5OMjU1RV1dHa2trevyuHxUEASBjo4OXn/9da5evUpRUdGmmi4Hg0G6u7uZmZlBoVDQ2tpKU1PTpqR2BUGgubmZS5cuMTIyQmtra9ZfM1fodDpKSkqYnZ0lFotlJFg//vGP09nZyQ9+8IPlMYCFSEGIuG9/+9sAGXeler1eAoEADQ0NG+7JlG8dqqkonIDBsXljVwRBQG93orU6CM1PEHJP4x25htZagqmsDqUm+zebwMwwyVgYk7MeteH+T1OCIFBbbKS22MhPP1bNwFyAziE354bdd3x+kbjIf1xz8R/XXJi1Kt5zy4PuycZiVHnSvLIe0g82PT09RCIR9Ho9O3fupKqqaku85Rk2m40nnniC+fl5enp6lruEm5ubaW5u3vKZewharZaOjg46Ozvp6uri0KFDWX/P4vE4/f39y5HtiooK2tvbN93kubKykr6+PoaHh2lsbMybusBsUF1dvTzSLxOj45/8yZ/kV3/1V/nWt761JeKyiSRJfPvb36ayspLDhw9ntG22UqkAJSsaGXJdExcL+oiH/OhsZSjVm/+UrlCqMDnr0RU5CcyMEPXNE/W7MZZUYXBUIiiyE82KLi0SWZxFbbShzyCFLAgCLWVmWsrM/MzjtfS6/HQOLXBhxEMwdttUeCma4Ptdk3y/a5Jio4YXdpbz/j0VdNQUoVAUnuCJRCJcvXqVmZkZNBoNO3bsoK6uLu+7TR91SkpKeOaZZ3C5XPT29tLX18f09DT79u3DarXmenl5TUlJCU1NTQwODjI4OJg1/zRJkpiYmKCnp4doNIrVamXHjh05a05RKBQ0NTVx7dq1ZdNzueJ0OlEqlUxOTmYk4hwOB88//zz/8R//wczMzLrmqeeSvH+U6+zsZHR0lI9+9KMZ3WxEUWRqagqj0YjNZtvwdd05PzW3hfGh+ZRYNZTkdvixSqvHVtuGtbYdpUZLcG4c98AlIr55NtrJRkwmWJoaQFAosVQ2rTmKpLxlKvzLzzTy/3y8g//3u1t5srEYrerOU8MdjPG/z43xk19/i6f/6CRf/FEv1yd9G35c2SB9gzl58iQzMzNUVVVx7NgxGhsbtwRcgSAIAhUVFRw5coSWlhaWlpY4ffo0fX19iKL48B08wmzbtg2z2UxfXx9+v3/D9+/xeJbnt0qSxJ49ezh8+HDOu4tramrQarUMDg7K+juiVqtxOp14PB6CwWBG23784x9HFEW++93vZml12SfvRVy6eyTTVOrCwgLRaDRraaJ8SafGwwFigUW0lmJU2vzwQNOai7A37cVU3oCUTOCfuIl35DrxcGDDXiPtW2dy1qPUbEyHl1qpoKO2iE8fbebrH+/gV482sb+2CNVdUbdpX4S/emOYF796hqN/epo/e62fwbmlDVnDRhOJRLhw4QKXLl1CoVBw4MABOjo6ZF3sLGcUCgXbt2/nmWeewWw2c/PmTd54442tLtYHoFQq2bt3L5IkcenSpQ0TNOFwmK6uLt588018Ph+NjY0899xz1NbW5kVpglKppLGxkUgkwsTERK6Xk1XS2bZ09m21vPjii5jN5uWSrUIkr9Op8Xicf/zHf2THjh0ZmfkBy1/abKRS4a7RWznsTg0tpKNwuem+uh/CrS5ZnbWE4Nw4YY+LxaEr6IrKMJXVolCtXUSsTKPqiso2cNW30amVPNHo4IlGB8FoggujHt4actM97WNl8G1kIciXTwzw5RMDbC+38P7dKQ+6XJsKp2vfrl+/Tjwep7Kykl27dm2JN5lgs9k4fPgwN2/eZGBggNOnT9Pa2rpVK3cfioqKaG5uZmBggIGBgXUV+yeTSQYHBxkYGCCZTFJWVkZ7e3tedjjW1dXR39/PwMAANTU1eSEus0FpaSkajYbJyUlaWlpWfZx6vZ6f+Imf4G//9m+5efNmQTaB5PXZ/sYbb+DxeHjppZcy+vIlEglcLldWO5LyYX5qIhom6ltAY7Kh1m9e51UmKFRqzBWN2Jv2ojZaiSzO4u7vIrQwibSGJ+KNSqNmglGr4khrKb/1wna+9tF9/NyTdbTeY5RXr8vPH/1nH4f+1+t86Gtn+duzI8wtRe6xx+xyd/TtscceY//+/VsCTmasjMqZTCb6+vq2onIPoLW1dTl6uZb3SJIkpqamOHHiBH19fej1eh5//HEef/zxvBRwkEo11tfXEwwGlw285YhCoaCyspJAIJDxZ/vSSy8BqbGehUhei7hXXnkFgPe///0ZbTczM0MymcxaFA7uTKcGY0niyc2vOQi7pwEwOLJ3nBuFSmfEVrcDa812BKWKwMwonsFLRP2ejOrKAq6NT6Nmgs2g4T3tTj7//na+/NN7+ciBGuqK3xl1uzTu5fOv9PD4F0/wsb8+x/feHt+UiK3L5VqufausrOTo0aNUVGTPN3CL3JOOyrW0tOD3+zl9+jQDAwMFUa+5maTTqgCXL1/OKK2aNmC+ePEiiUSCHTt2cOTIEcrKspMJ2EgaGxtRKBQMDg7meilZZa0p1SNHjmAymZb1RqGRt+lUSZL44Q9/SG1tLTt37sxo28nJSQRByMj8L1OKTXdGNXzh+B3RuWwjJhNEvHOodAbUxsLoUBMEAa2lGI2piJB7itD8BL7xHjQmGyZnAyrdg1OQsaCPiDe7adRMKDFref+tmaxT3jBvDS3QOeTG5bvTVPjsoJuzg25++wfdHG65bSps0Gzc6SdJEgMDA/T29qLRaHjssce2xNsjhFKpZPv27TidTi5dukRPTw9+v589e/ZsNa+soKioiKamJgYGBhgZGXlo12Y0GqW3t5exsTEglZ7ctm1bQXn1abVaqqqqGB8fZ3FxkaKi3M+9zgZFRUUYjUYmJydpb29fdZZGq9Xynve8h3/5l39hbm6O0tLSLK90Y8nbSNyNGzcYGRnh/e9/f0Yps2g0uvxBZPNE06ruHL212SnViHcOSUyit1cUXJ2DoFBgLKnG3tyBzlZKLODFM3iJJdfQfUd4SZLE0vQQCALmisa8O+ZKm54Pd1Tzpz+5my/++E7et6v8HTN240mJ471zfOa7V+j4/eN86h8u8eqNGaKJ5H32ujoSiQRdXV309vZisVg4fPjwloB7RCkqKuKZZ57B6XQyOTnJmTNnCIfDuV5WXtHS0oJer6evr49I5N7lDqIoMjg4yPHjxxkbG8PhcPDss8+ye/fughJwadLWGyMjIzleSfYQBIGqqiqi0Sjz8/MZbfv+978fSZL40Y9+lKXVZY+8FXHp0OaLL76Y0XYzMzNIkpTVKFyaOzpUN7G5QZIkwh4XgkKJzraxkyg2E6Vai6WqhaKG3aj0ZsJuF+7+i4TcrnekgsIeF8loCIOjEpU2f4c6C4JAvcPIxw7W8uWP7OXzL7bz7rYyLPo7p2iE40n+/ZqLX/7fXez/wnF+7Z+u8ubAPIkM0/LhcJgzZ84wNTVFeXk5hw4d2nRj0S3yC7VazYEDB2hpacHr9XL69Gk8Hk+ul5U3qFQqdu7cSSKR4MaNG3f8TpIkZmZmOHnyJDdu3FiOaj/55JMF7clns9mw2+1MTU0RjUZzvZyskb7vZ1r/98ILL6BQKPjhD3+YjWVllbxNp/7whz/EbDZnbPA7MzODIAibUqvgMGkZujV6azMNf+NBH8loGH1x9ox0NxO1wUxRwy6ivnkCM6MEXEOEPS7M5Q1oTDaS8RjB2TEUai3GPOvCfRAKQaDVaabVaea/PFHHjWkfnUNu3h71EFppKhxJ8E9dk/xT1yQO0y1T4d0V7HuIqbDH4+HChQtEo1FaW1tpbW3NuwjlFrlBEAS2b9+OxWLh8uXLnD17lj179uRshmi+4XQ6KS0tZXJykrq6OoqLi1laWqK7u5u5ubnl9LScvBTr6+vp6upibGwsa6bHucZsNmMymZiZmWHXrl2rvh46HA6efPJJXn31VSKRSEbjPXNNXoq42dlZzp8/z4c//OGMOuoSiQTz8/MUFxdvSieeI0decWFP6inDUFy+aa+ZbQRBQGcrRWMuJrQwSWhhEu9oN1pLMQCSmMRc2VywolWpENhVZWNXlY1feLqeqxNeOofcdI0tElsRfVsIxPj7t8b4+7fGqLTped+ucl7cXUF7heWOC9L4+DhXr15FEISt+rct7ktlZSVGo5Hz589z6dIl/H4/bW1tj7zYFwSBnTt3Ls9WdTgcjI6OIkkS1dXVbN++Hb0+fyP+a6GiooLu7m7GxsZobm6W7XfA6XQyODiIz+fLyOj/xRdf5MyZM7z++us8//zz2VvgBpOX6dT/+I//QJKkjLtSFxYWSCaTmzY+oyQHNiPJeJSo343GVJST7sxso1AqMZXVUtzcgdZSTNTvJup3o1BrC6aB42GolQr219n51WPN/OXPdPCpI03sqylCeVfUbcob5i/fGOZ9XznDsT87zcuv9TM466e7u5vLly+j1Wo5dOjQloDb4oGku1ftdjuDg4OcO3eOeDz3855zjcFgwOFwsLS0xMjICDabjUOHDrFv3z7ZCThI2XDU1tYSCoWYm5vL9XKyRvr+PzMzk9F2ab1RaCnVvBRxP/zhD1EqlbzwwgsZbZf+0DZNxK2IxHlDmzN6K7I4C4DeXphz3laLUqPDUr0NxS2hKsajLA5eIrw4KyvrBJ1ayVNNDn7tPa18/WMd/PKhBnZUWLj7IXl4PsiXTgzw3Mtv8l//dZTORSPNuw8WdJ3OFpuHTqfjySefpKamhrm5Od588837FvU/CszPz3P69OllMZOeZmK323O8suxSW1sLwOjoaG4XkkWKiorQaDQZi7i0WfYrr7xSUPeYvBNx4XCY1157jaeeeiqjEypdkGoymTAajVlc4W3unJ+a/SdbSZIIL86iUGnQmOV9sYFUB64Yi6AvrsRc0ZTqUJ0aYHH4KvHQxs9AzDUmnYoj20r5/7y3ja99dB8/+0QdzaXvNHGeDAp8ry/KkZfP8OH/p5O/6xxlfkm+xcpbbAxKpZI9e/bQ3t7O0tLSI9m5GgwGuXDhAp2dnQQCAVpaWti3bx+iKNLf35/r5WUdg8FAWVkZMzMzsv3sFQoFpaWl+Hy+jI5REARefPFFpqamuHz5chZXuLHknYg7efIkoVAo41Sq1+slGo1uWhQO7ozE+TdBxMWWFhHjUXRFZbKtZ0gjiSLBuXEEpQpjaTV6u5Pilv3oiytIhIMsDl/DN3GTZFye4sVm0PBjO5z83gd28Oc/uYsPNqmpNLzz6fDi2CK/+8MbHPzicX7m/3uef7w4kdNZvlvkN4Ig0NTUxK5duwgGg5w5cybjoeGFSCKRoKenh5MnT+JyuSgvL+fo0aNs376dqqoqioqKGB0dfSTei7q6OoBl7zs5Ul6eqhdfa0q1kIx/807EpfPRa5nSALc/vM1gpbnvZnSnRry3Uql5YHSbbcIeF2I8isFRhUKZ6r9RKFWYyxuwN+9FYyoi6pvH3d9FcG4cSVyf11q+IiYTaDwDHCkJ87tHSvnjn9jFh/ZV4rTcWQ8pSvDmwAK//v1rPPaF4/zS31/klavThGL39t3b4tGmvr6ePXv2EAqFOHPmDIFAINdLygqSJDE+Ps7x48cZGBjAZDLx1FNPceDAgeWMjSAItLW1IUkSfX19OV5x9ikrK0On0zE+Pl5QacNMKCkpQaFQZCzinnrqKYqKigqqLi6vulNFUeTf//3fl3PTmTAzM4NGo9lUN+qVIi4USxJLiGhU2dHFYjJBdMmD2miVZUPDSsRkguD8BAqV5p4duCqtAVtdO9ElDwHXCMG5ccKLs5ic9WgtxbKJUorJBN7RGyTCSxgclRjL6jALAj9pN/DhfVWMLAR5a9hN55AbT/B2TWYsKfJazyyv9cxi0Ch5bnsZ799dwTMtJVn7fm5ReNTW1qJUKrl06RJnz57l6aef3rRSlM3A4/Fw/fp1vF4vGo2G3bt3U1tbe8/rg8PhWLYcaWpqknWtadoUd3BwEI/HQ3Fxca6XtOGo1WqKi4tZWFggHo+jVqsfvhEpD8EXXniBb3/720xOTmZ1dOdGkVdX9O7ubqanp3nf+96X0XahUAi/309Z2eamGe8eveWPZC8aF/UtgCShsxauue9qCS1MISUTGEtrHmgpojXbsTftxeSsR0om8E/04R25Tjxc+FEFSUziG+u5Q8Ct/G4LgkBDiYmPHazlKx/Zy+++r413tZXdMUUEUg8XP7w6zS/+/UX2f+E1fuP71zg7uEBSlOcT+BaZUVVVxb59+4hEIpw9e5ZQKJTrJa2bcDhMV1cXb775Jj6fj4aGBo4dO0ZdXd0D7w/bt28HoKenZ7OWmjPWOme0kHA6nYiimPH0hrT+ePXVV7OxrA0nr0TcqVOnADh69GhG2212V2oarUqJdYUTvzeLUxsivnkQBLRWR9ZeIx8QEzHC7imUWv2q5qMKCgUGRyXFLfvRFTmJh/wsDl3BPzWImCjM2jBJFPGO9RIP+dEXl79DwN2NQhDYVm7hE0/V87WPdfA/fmwbh1tK0KvvFMD+SILvXZzgY399noNfPMHnf3iDrrFF2aZUtlgdVVVV7N27l3A4TGdnZ8EWvCeTSfr7+zlx4gSTk5OUlpZy5MgRdu7cuSrfUJvNRmVlJXNzcywsLGzCinOH1WrFbDYzNTWFKGY2JaZQWKvVyJEjR4DbeiTfyat06qlTp1AoFDz99NMZbTczM7PckbLZOEya5ULybBWUJ+NR4kEfWkvxcn2YXAnOTSCJIqaye6c97odCpcZS2YTe7iTgGiayOEPUN4+xtAa9vRxBkVfPK/dFkkR8E73Eg150RU5MzoaM3gelQmB3tY3d1TY+8dQtU+HhBS6Nee8yFY7yt52j/G3nKJU2PS/uruD9uyvYXm6WTTp6i9VTU1ODKIpcvXqVzs5Onn766YKZESpJEi6Xixs3bhAKhTAajezcuXNNU3u2b9/O9PQ0PT09HDp0SNbnQnV1NT09PczOzm5qLflmYTAYsFgszM6mbKlW+1mWlZWxfft2Tp06ldF2uSJv7myiKHL69Gk6OjqwWCyr3i4ej7OwsIDD4UCl2nyBU7IJUxsi3lQ4WGfbfJG6mYiJGOHFWVR6Exrz2uo01HoTtvqdWKq3IShVBGZG8AxeJrpUGLMjA64RYkuL6GylmCsa13UB0agUPFZv5zPHWvj6xzv45JEm9tXYUArvNBX++ukhXvjymzz3Z6f50vEBRhbk36W3xZ3U1dWxY8cOAoEAFy5cKIgIjc/no7Ozk7fffptYLEZ7eztHjx5d89hFo9FIbW0ti4uLso/GpeeMyj2lGovFMp4d/OyzzzIxMcHIyEiWVrZx5I2I6+7uxuPx8Oyzz2a0ncfjQZKknETh4K4O1SwZ/kZ9cwgKJRrT5jVt5ILQwjRIIsaSqnWJF0EQ0FkdFDfvw1haSzIexTfWk2oSiOZvzU/Y4yLscaE2WjFXNm3oE6Beo+TpJge/9p5tfP3jHfziofrUKK+7/m5oPsjLx/s58ieneN9X3uSv3hhi2luY6bUtMqexsZHGxkY8Hg/Xrl3L21R7NBrl6tWrnDp1ioWFBWpra3nuuedoampCsc6oe1NT6twbGBjYoNXmJwaDgeLiYmZmZmQ7wSMt5jMV5IWUUs2b3Fz6zcpUxKU/HIcjN7VijiyP3kpEgiQiIXRFzoJJCa4FMZkg7HGh1OrXHIW7G0GhxFhaja6olMDMKFHfPJ4Bb6rOrLQmr1LTsaCPpelhFGot1uptCEL2PmuTTsWxbWUc21bGYijGuWE3bw25GZi7syGke8pP95SfL/6ojwN1dl7cXc4LO8spNhVGmm2LtdHW1obf72dsbAyLxUJDQ0Oul7SMKIqMjIzQ19dHIpGguLiYHTt2ZDQj82EYjUYqKyuZnJxkcXFxUx0PNpuqqircbjfT09PL0xzkhM1mQ6lUsrCwQGtr66q3O3z4MJDSJZ/4xCeytbwNIW/uYq+//vqa6uEWFhZQq9UZpWA3kmynU2+nUuXdlRp2u5DEJAbH+qJw90Kp1mKtbiVeXM6Sa5iwe5qIdw5TWV1eGCcnYxF8470ICgW22jYUqtW1w28ERQYNz+8o5/kd5cz5I3TeEnTjnjsjlhdGPVwY9fD5V3p4qsnBi7vKec8OJxbd5q11i81BoVCwf/9+3njjDbq7uzGbzZSU5P76Mzs7S3d3N4FAAL1ez549e6ioqMjK+dvc3Mzk5CQDAwMcOHBgw/efL1RUVHD9+nUmJydlKeIUCgV2ux23200ymUSpvL/bwUpKS0tpa2vj9ddfz/u6uLwI7aynHs7r9eJwOHL2JpdkMRInSRIR33xq+LshNyJ1M5DEJCH3NAq1NqtiVW2wUNSwG3NlM4KgYGl6kMWhK8QC3qy95sMQk0l84z1IyQSWqhZUutz5dJVadHxwTyV/9BO7+OMP7+LH91ZSZrkz6pYUJd7on+fXvn+N/V84zv/rf1/k369NE45tjNlyOBzmc5/7HC0tLeh0OioqKvjEJz7B1NTUqvcRCAQ4ceIEH/nIR6ivr0ej0WA2mzl48CBf+tKXZJs62kg0Gg0HDx5EqVTy9ttv59QMeGlpiXPnznHu3DnC4TDbtm3j2LFjVFZWZu26b7FYcDqduFwulpaWsvIa+YBGo6GsrIyFhYWC7Up+GA6HA1EUWVxczGi7Z599lsnJSYaHh7O0so0hL0Tc9evXWVxcXM5Dr5Z0sWIuzQod5uzNT02EA6kxW9bcidTNILw4i5SMY3BUZjWNCKl6OX1RGfbmfRgcVSSiIbyj3fjGe0nGNncgeGoWbD+JSAhjaS1aS/6YblYVGfip/dW8/FN7+MIHd/DCznLsxjttGmIJkf9zY5ZP/cNl9n/hNT773cuc6J0lllhbQXwkEuHo0aP8/u//PoFAgA984ANUV1fzN3/zN+zdu3fVF9N//Md/5Itf/CLf+973KCoq4kMf+hAHDhzg6tWrfPazn+Xo0aOy8EPLNmazmf379xOPxzl//vymi994PE53dzevv/46s7OzVFVVcezYMVpbW1cdUVkPacN5udfGpRscXC5XjleSHdKlVm63O6Pt0qVd+V4XlxcirlDr4QBKTLenJ2y0iEt3VObTzX2jkSSR0MIUglK9qePEFEoVJmcdxc0daC3FRP1u3ANdBGbHEJObM8IrODdO1O9Ga3VgKMlPZ3BBEGgsMfEzj6dMhT/3vjae216KSXtnJUYwluQHV6b5hb+7yIEvHuc3/+UanRmaCn/hC1/g3LlzPPHEE/T39/O9732P8+fP86d/+qfMz8+vujZFp9Px0ksvMTo6yqVLl/jud7/LiRMnuH79OjU1NZw5c4YvfOELGb0PjyplZWW0t7cTCATo6uralEYHSZIYHR3l+PHjDA0NYbVaOXToEB0dHej1+qy/fhq73U5xcTGTk5OyFv2lpaVrGlFVKKysi8uElXVx+Ywg5UH70Y//+I/zyiuv4PF4Mkqnnj59mlAoxI/92I/lLFLl8oV54g9PLv/33/38gQ0bbeQZvEQyHsOx7aBsI3ER3wL+iT6MpTUYS2tyto5YwMuSa5hkNIRCpcHkrENrLcna+54+bpXOSFHDrgdOpshHEqJI95SfzqEFLo4uEo7fW/iWmrW8d1c5L+6uYG+17b7vZywWo7S0FJ/Px6VLl9i7d+8dv9+9ezfXrl3j4sWLdHR0PHBtJ0+mzsd7mYZ/5zvf4aMf/Sh1dXUFYR+QD0iSxOXLl5mYmKCpqYn29vasvdbCwgLXr1/H7/ej1Wppa2ujuro6Z9e/2dlZzp07l/XjzjWdnZ0sLCzw/PPPr3pEVSHR2dmJ2+3mhRdeyCiK297ejt/vZ3x8PG/vwTmPxK23Hq64OLezMouNd9YMbVQ0LhmLkIiE0Jrtefvl2QjC7mkQBPT2zZ22cTcaky01wqu8EUkS8U/2szh8jXho4+thkrEIS1MDKFRqrDVtBSfgAFQKBXuqbfzKs018/eMd/F/PtXCw3o5aeed3dW4pyt+cHeVDX+vkmT9+nf/1n330uvzviOicPXsWn89HY2PjOwQcwIc//GEAXnnllXWte/fu3QBMT0+vaz+PEoIgsHv3boqKihgcHGRubm7DXyMUCvH2229z9uxZAoEAzc3NHDt2jJqampxe/0pLSzEajYyNjZFIJHK2jmzjdDqRJCnjEVWFwlrr4o4cOZL3dXE5F3Hperi1+MNBblOpkDJUtRluP7lslIi7nUq1b8j+8pF4OEA85EdnLUGhevhYnGwjCAKG4nKKW/ajL64gEV5icfgq/sl+kvHohryGJEn4pwaRxCTmyhaUmsK369CoFByot/PZ51Kmwr/ybCN7qt9pKjzhCfO1U0M8/6U3effLb/CVEwOM3jIVvnr1KgD79u2752ukf37t2rV1rTV9Md7sEX2FjlKpZP/+/ahUKi5fvrxh9XGJRILe3l5OnDjB9PQ0TqeTo0eP0tbWlhcRIUEQaGhoIB6PZ9RcU2isdURVoZDWCZmmVAuhLi7nFiOnT58GbuefV0s+1MOlcZi0y3NTveGNMfyN+j0gCKiN8vUoCntShbR6e36NfFEoVZjLG9AXOQnMDBPxzhH1L2AoqcZQXLkuv77I4sytkVplaM3y+2wNGhWHmks41FyCPxLn7REPnUPuVPRtxd8NzAX409f6+dPX+tlVZUWalFCaipcHc99N+udjY2PrWt+XvvQlAD7wgQ+saz+PIgaDgfb2dq5evUp3d/c9I6arRZIkJicn6enpIRKJYDab2blzZ15YmdxNejzV8PBwziOD2WLliCpRFNdtmJxvpOviMm1uWFkX9wu/8AvZWNq6ybmIe/vttwF4/PHHM9puYWFh2Tog1zhMGgZvZRg2IhInJhPEQz40RhuKTejCygViMkHUN49Kb0JtyP1neC9UOgPW2nZiS4sEZoYJzo4R9sxgLq9HY848jZ+MRQjMjKJQazE567O06vzBolNzbHsZx7aX4QmmTIU7hxYYmr9zpNe1SR+oWqj8lb/hjBDgW+fG3tENazSmrFfWY/fw9a9/nePHj2Oz2fgf/+N/rHk/jzK1tbVMT08zPj5ORUXFmsZbLS4uLmdg1Go1u3btora2Nm+Fg1qtprq6mtHRURYXF7Hb5ZkdcTqd9Pf3s7i4mFPHh2ywVr+4kpISGhsbuXjxYpZXuHZyftZ0dXVRX1+f0YmRL/VwaUrMKzpUQ+sXcbHAIkgSGrM8LxaQMjGWRDHntXAPQxAEtBY79qZ9mJx1SMkEvvE+vKPdJCKrny+aSqMOpNKoFU15NS1iM7AbNbyws5wvfHAnf/7SHl7aX0110Z2dhoKgYA4Lv/2Dbh77g+P87Dcv8M9dkyxF1n9Ovfnmm3zmM59BEAS++c1vUlFRse59PooIgsCePXtQqVRcuXIlo7RqJBLh0qVLvPHGG3i9Xurr63nuueeor6/PWwGXpq6uDoDR0dGcriObPAop1bXUxXV0dHDz5s289QvM6ZkTCATo6+t7aLfZ3eSDP9xKHKaN9YqL+uVdDydJEmGPC0GhRGfNv/TJvRAUCgyOKopbOtAVlREP+vAMXmZpehAx8fDPPJVG9ck2jZoJZRYdH9xbyf/68G7+10/s4oN7KtAm7xTESVHidP88//c/XaXjC8f5nf8cx9D6FCZr5u9dd3c3H/jAB4jFYnzpS1/ix3/8xzfqUB5J0mnVSCRCd3f3Q/8+mUzS39/P8ePHmZiYoKSkhGeffZZdu3ah0eS+FnY1WK1WioqKmJ6elq1ZtM1mQ6vVylrEQeZ+cR0dHUiSxJUrV7KwqvWTUxF35coVJEnKWMR5vV6AvAlrb+T8VEmSiAUWUemMKNWFX/R+LxLhAMloCJ2ttOA6MxUqDZbKZooa96A2WAh7ZnD3XyTknkaS7m1ym0qjjjwyadRMqLYbeOmxGn5MM4Dr7/871vnrdzQKQcpU+K3JMCUf/E28R/4H/9f3rvB63xzx5MNNhUdGRnj3u9/N4uIin//85/n0pz+drUN5pKitraWkpITx8XFmZ2fv+TeSJOFyuTh58iS9vb3odDoOHjzIE088kbMxieuhrq6OZDLJ5ORkrpeSFQRBwOl0EggEcjqhI1tYrVYEQcg4Epduqurq6srGstZNTkVc+k1Zi4gTBCFvLgQbOT81EV5CSiZknkpNFRDqikpzvJK1o9absNXvxFLdiqBUEXAN4xm8THTpzgvE7TSqiKXy0Uujrpbm7e3EXP24j/8Vf/GRffzOe7dzbNs7TYVFhYZ/vTzFz//t2zz2B8f5zX+5zltD7nuaCrtcLt71rnfhcrn4zGc+w+/+7u9u1uHInoelVf1+P52dnVy4cIFYLEZbWxtHjhzB6XTmRQnMWqioqECpVDIxMZHrpWSNdI1jNmxkco1SqcRisSwHgVZLvou4nN5R0m/K/WwF7ofX68VsNm/K6JXVsHJ+qnedNXGxoA8AjdG6rv3kK5IkEvEtoNToUelMuV7OuhAEAZ21BK3ZTmhhiuD8JL6xG2jMRZicDai0esKedBrVicb0aKdRH8SujoOYzBamxkcY7OumrW0nbRVWfu6pOq5P+vjjv/4OydJtKLSG5W28oTjfuTDOdy6MU2bR8t6dFbx/TwWSJBEIBHjPe97D0NAQP//zP8/LL7+cw6OTJwaDgR07dnDlypXlbtVYLEZvb+9y7VhNTQ3bt29Hp9M9eGcFgEqlory8nMnJSYLB4HKzjZxYacXR0NCQ49VsPFarFZ/PRyQSWfV30m63U19fn7ciLueRuNra2oxq2yKRCJFIBJvNlr2FZchGplPjQV/KWkSmA+9jAS9SMo7Olr1pCJuNoFBiLK1JjfCylhBbWsQzeIml6SGCs+lu1LpcLzOvUWs0/MTP/CIAf/r53yAcStXIqRQK+l77DqP/8DmKz32Vzx5r5kDdO02FZ/1Rvnl2hA/+xVl+4bUIn3lLxYBfwU/91E/xjW98QzbftXyjpqZmOa3a3d3N8ePHGR0dxW63c/jwYfbu3SsLAZcmbXUj15SqWq3GarXidrs3ZcTaZpPWDZlG4zo6Oujr68vLNHPOInHBYJC+vj4++MEPZrSdz5eKVOWTiFuZTg3Hk8QS4ppGb0mSSCzoR603r8uLLJ+JeFOO4Dpb4aZS74dSo8Va3UrMXk7ANbzsg6e1FBdc7V8u+LlP/ncunj3N9UsXeOm5A+ze/zgzU5PcuNqFze7gt77wx5SVqtlpNRPcpuIr3/0R1zygr98HwjvPF31DB7OzQzz//POoVCoUCgVKpRKlUolGo+Hv//7vC6awPl8RBIGKigrm5+cZGhpCp9Oxa9cuKisrZSmcS0pK0Gg0TExM0NLSIstjdDgcDA0NsbS0lDclSxtFWjf4fL6MDL87Ojr4/ve/z5UrV3j66aeztLq1kTMRd+XKFURRXHNTg9WaP+nGYtOdNwJfOHaH7chqSYQDIImoZZpKFZNJon43Kr0ZpUY+T+d3ozFasNRsw9PfBUhEvHMkIkFM5Q2yTZNvBFqtjq9++wf8/df/nFd/+C+88dr/D7PFwrt+7AU++tGPoQm4WAy4lv++2NvL3D99j8PveR+Pv/RpuuZEBhZvz3AN9Xdyeqrvvq/3kY98BIPBgNVqxWazUVJSgs12//muW9xJIBDgxo0bzMzMIAgCkiSxe/duWU/DUCgUVFZWMjIygtfrpahIfiUSaRG3sLAgOxFnsVgQBGFNkThIZQ+3RNwt1tvUkE8iTq1Mjd5K18P5wvE1iTi518PFltwgibKMwt1NaH4SkLBUtZKIBAm5p/COXEdrdWAqq5O1iF0rkiQhJGN85Kd/mg+98G6SsfDy7xRqLWq9CZXOhEpvRKnR8+nfe5zP/MFfLP/NB4CPfOPc8n9f67pAS9ltI+lkMkkkEiEcDuPz+fB6vXi9XlwuFy6Xi97eXrRaLU6nE6fTicPhQKXaakS5m3g8Tn9/P0NDQ0iSRGVlJfX19XR2dtLX10dZWZmshXB1dTUjIyNMTk7KUsSly5vkWBenVCoxm82yam4oOBHn8/nyqqkhTckdo7fWVhcn93q4VCpVQGfN/ai0bJKIhogszqA2WNBaHehsJeiKygjMjBD1LRD1ezA4KjGWVG2lWYFEJEjYM0PEN4+UTA0ZV6g06IqcaM1FqA0WFKrVzdHUqhREE/e2HlEqlRiNRoxG4x3j+hKJBF6vl9nZWWZmZhgbG2NsbAylUonT6aS2thaHwyFrYbIaJElifHyc3t5eotEoVquVnTt3Lt/06+rqGB4eZnp6msrKyhyvNnvYbDaMRiNTU1O0t7fnvVFxpqjVamw223JdnNy+9zabjfHx8YyaG4qLi6mtrd0ScSvp6uqipqYmo9mn0WiUcDicl/P1HCYtA3Opose1TG1YroczWGRZDycmE8QCXjQm26pvyIVKcDY139PkrFu+AKq0emy1bcQCiyy5RgjNTxBZnMXkrEdrffQEgiSJRP1uwu5p4qGUE7pSa0BrL0drsaPSmTbtPVGpVDgcDhwOB+3t7QQCAWZmZnC5XExNTTE1NYXRaKS+vp6ampq8GMy+2bjdbq5fv47P50Or1bJnz553zBFtaWlZFnnl5eWyEzdpBEGgsrJStiOqIJVSHRwclG1d3Pj4OD6fL6Omm46ODn7wgx/kXWdyTs6yYDBIb2+vLOrh0jjW6RWXroeTbSo1sAhIsp1CkSYeWiLqd6Mx2+8ZUdWYirA37cVU3oAkifgnb+IduU48nJ8jXTYaSRIJe1y4b17EP3GTeDiAzlZKUcOu1PtSVptq7MmhqDWZTDQ1NXHo0CGOHTtGU1MT8Xic7u5uXn31VXp7e2Xr2n83oVCIixcvcubMGfx+P01NTRw7doza2tp3fEZarZampiaCwSBjY2M5WvHmIPcRVStTqnIjrR/WUhcnimLeTW7ISSSup6cHURTZu3dvRtul3/R86kxNU7JOm5F0PZxcmxrSo8TkbGIMEJgdBcBUVnvfvxEEAUNxBTprCcG5ccIeF4tDV9HZSjGW1aFUy69jUpIkov4FgrNjJGMRBKUaY2kterszryOzJpOJ9vZ2tm3bxuTkJIODg/T39zM6OkpzczP19fV5V9qxESQSCQYHBxkcHCSZTOJ0Omlvb8dkerC3Y2NjIyMjI9y8eZPq6mrZ1hSuHFHV3t6e6+VsOHKui0tPbshUxKX1ytWrV3nqqaeysLK1kZMzrL+/H4Bt27ZltJ3P58u7poY0DvPtG+9aauLiQX+qHk5vfvgfFxiPwigxSEUb40EfOlspKt3Dw+0KlRpzRSN6u5Ml1zAR7xxRvxtDSTWG4grZpNVjAS+BmVESkcCyp56+uBJFAYkfpVJJbW0tNTU1jI+Pc/PmTW7cuMHw8DDbtm2jurpaFilxSZKYmpqip6eHcDiM2Wxmx44dlJaurhlJpVLR0tLC9evXGR4epqWlJcsrzg3pEVVjY2MEAoGHittC426/ODl8t9OkmxvSdmWrJa1XBgYGsrGsNZOTu0RaxGV6gvt8PkwmU14++d5h+JthTZwkScTDAVQ6o2xu3CuJh/xIyQRai/xqR1YSmB0HQcBYWpPRdiqdEVvdDqw121Go1ARnR/EMXiLqL2zDTTGZwD81gHe0m0Q0iL64guKW/RhLawpKwK1EEARqa2s5duwY7e3tJBIJLl++TGdnJ6FQKNfLWxder5czZ87Q1dVFIpFg586dPPvss6sWcGnq6uowGo0MDg6SSCSytNrcI/eUalFREbFYjHA4/PA/LjBsNhvhcJhoNLrqbWpqatBoNMv6JV/IaSSuqalp1dskk0lCoVDedj2tZ36qGI8hJeOo9fIUOVG/G5B3KjUeWiIRXkJXVLYm+xBBENBaitGYigi5pwnNT+Ab70VttGEur19VZC+fiC4tsjQ9iBiPojbasFQ2ycpWRalU0tTURG1tLT09PYyOjnLy5Ena29upq6srqMhFJBKht7eX8fFxICXCtm3bhla7tqi5QqGgqamJq1evMj4+Lrt0XJqSkhKUSiUzMzMZ3csKhZXTDQwGw4P/uMAwm1MZr0AgsOrvefqczzcRl7NIXFVVVUYdHsFgagxPPnWFrGQ9NXGJSKqrtdBnid4LSZKILXlQqDQFJ0QyIeSeBsBQXLGu/QgKBcaSKuzNHehspcSDXjyDl1maHkJM5H8xvZhM4p8awDd2AymZwFzRhK2uXVYCbiVqtZrdu3fzxBNPoNFouHbtGp2dnQURvUgmkwwMDHDixAnGx8dxOBwcOXKE3bt3r1nApamqqkKtVjM8PFzQ0eQHoVQqKSkpwePxEIvFcr2cDWfldAO5kdYRmY7RamlpYWRkJK8+700XcZIk0d/fn3EqNf1m52vtwcp0anr01mqJh2+JOH1+Htt6SMYiJGMRtBZ7QUUnMiEZjxL1LaA2WjdMqCrVGixVLRQ17kZtMKc6Oge6CLmn8/ammIxF8I5cJbI4i9poxd60F73dKdvPfSWlpaUcOXKE2tpaFhYWOHXqFG63O9fLuieSJDEzM8Prr79OT08PGo2GAwcO8OSTT26YnYRKpaK2tpZgMMjc3NyG7DMfcTqdSJIky2M0m80oFIqMGwAKgbSOSAeHVktLSwvJZJKRkZFsLGtNbLqIm5mZIRAIyE7E3Wv01mpJhAMgCKi08gpZwy0DY0BjsuV2IVkk7JkBpHVH4e6FWm/GVr8LS1UrgqAg4BrGM3iZWMC74a+1HmJBH56hKyQiIYyltdjqdsg2+nY/1Go1e/bs4bHHHiOZTHL27Nm8s9rw+/289dZbnD9/nkgkwvbt2zl69Cjl5eUbLrbr6+sRBIHh4eEN3W8+kfYslaMVh0KhwGKx4PV68/bBca2sJxIH5FVKddNr4tba1JB+s/M1napWKigyqFlMT20IrW701nJTg1aeTQ2xoBcAtSH/Ooo3AkkUCXtmUKh1Wav5EwQBna0ErcVOcH6S0MIU3tFuNGY7Jmc9Kq0+K6+7WsKeGZamhxAUCqw122XfwPIwKioqMJlMnD9/nitXruD3+3Pu7B+Lxejr62N0dBRJkqiurqatrS0js9NMMRgMlJeXMz09LcsOTkgdo8FgkKWIg1RK1ev1EolE0Otze53ZSBQKBUajURYibtOvKmsVccFgEI1Gg0aTvx5ajjXUxYmJVFODHFOpkiQRD/pQ6Qx57QW2HqJLHqRkfFPShoJCiamsluLmfWitDmJLHjyDlwjMjCImN78LUJIkAjOjLE0PolBrKWrY9cgLuDQWi4VnnnmG4uJihoeHuXDhAslkctPXIYoiIyMjHD9+nJGREWw2G8888wz79u3LqoBLU1dXB5B3EcmNxOFwEAwGC6IOMlPWaoxbCBiNRoLBYEZRxi0Rx/oicfn+JLeWDtXErXo4tQxFXDIWRkzEZWtgDOlUqoC+KDMbhvWg1OiwVm/DVr8TldZAaGESz0AX4cXZTUt7pATcMKGFSVR6M/bG3bJuXFkLWq2WJ598kurqamZnZzl//vymWm7Mz89z6tQprl27hlKpZN++fRw6dGhTh7Y7HA4MBgMTExOI4urrhAuJ9OhIOUbjVnaoyg2TyYQoihmJ79LSUiwWy5aIU6lUy09oqyEWixGLxfI2lZpmZSRutYa/cm5qWK6Hk6mIS8YixINetBY7CtXmR4g1RitFjXswVzQhSbA0NcDi0FXiIX9WX1eSJAKuYcJuF2qDBVtdu2wjretFoVCwd+9e6urqmJ+f5/z581mPyAWDQc6fP09nZyfBYJCWlhaOHTuWE0PitK9eNBqVrZ9aWsTlayPLerBYLLJtblhLXZwgCLS0tGyJuIaGhoyGSOd7U0OataRTExH5NjUsjxKTaT1ceHEWAF2RM2drEAQBvd1JcUsHBkcliWiQxeFr+CZukoyv3shytUiSRHB2lLBnhYBTynO00kYhCAK7du2irq6OhYWFrKVW4/E4PT09nDx5kpmZGSoqKjh27Bjbt2/P6firmpoaBEGQbUpVr9djNBplGYlTKBRrmm5QCKT1xFrq4tJ1nvnApoq4RCLB0NDQmurhIP9F3JrSqZEwSo1edk0Ncq+HkySJiHcOhVqbF523CqUKk7Mee9M+NOYior553P1dBOfGkcSNEwxhj4vQwhQqvRlrbTuCojAnL2w2aSFXU1PD3NwcV65c2bDUtyRJjI+Pc+LECQYGBjCbzTz11FM89thjeWHSqtPpKCsrY25ujkgkkuvlZIXi4mLZ1sVZLBai0WheeaNtBOuxGYH8Gb+1qcphbGyMeDwuO3uRNI4VNiOrGb0liSJiPJLz7sJskIxFUvVwMo3CJaMhxHgUraU4r3zQVFo9ttp2rLXtKDVagnPjuAcuEfHNr1s0xAJeAq5hlBr9rQjcloDLBEEQ2LNnD2VlZUxOTjI0NLTufXo8Ht544w0uX76MJEns3r2bw4cPL6f48oWKipT9zuzsbI5Xkh3SA+M9Hk+OV7LxrDVile/o9XoUCsWaO1Rv3ryZjWVlzKaLOEj5B2VCvtuLpHFkGIlLxlJPpUqN/ETc8hQKGdb6we1RYto8HSWmNRdhb9qLqbwBKZnAP3ET78j15RrMTElEw/gm+hAUSqy127dSqGtEEAQ6OjowmUzcuHFjzaImHA7T1dXFm2++ic/no7Gxkeeeey5vR36VlZUhCIJs6+Lk3gAAmUes8h1BENZkM5IeI5ceU5drNlXETU+nRhOln8pWSzAYRK/X5+Xg+5VkOnorGUuF3pUyjMTJuesWUtYigkKJ2rgxDvfZQBAUGG4NndfbncRDfhaHruCfGkBMrD41IiYT+MZ7kJIJLNWtsqzf3EzUajUHDx5ErVZz8eJFlpaWVr1tMpnk5s2bnDhxgsnJScrKyjhy5Ag7duzIqM54s9FoNNjtdubn53NitZJtzGYzSqVS1iJObpE4SB1bKBTKqHO6vLwcuK1ncs2mijiXywXcfhNWSzgcLgijwZU1ceF4kmjiwRerRPSWiJNhJC4eDoCgQCnDG34yHiMRDqAxFyEI+V/LqFCpMVc0YW/ai9poJbI4i7u/i9DCJNIqLl5L00Mko2FMzrq8jTwWGiaTaXmyw9tvv/1QYSNJElNTU5w4cYK+vj70ej2PP/44jz/++PIw73zH6XSSTCaZn5/P9VI2HEEQsFqt+Hy+rekGBURaV2RSq+l0phrZ0nom1+S9iBNFkVgstinGlOvFbrxr9NZD6uLSkTi51cRJkkQiEkSlM+Zlame9xJZSdS+FJmhUOiO2uh1YqrchKFUEZkbxDF4i6vfc98YT8S0Q9c2jMdvRF1du8orlTUlJCa2trSwtLT2wvsbn83H27FkuXrxIPB5nx44dHDlyhLKysk1c7fpJ3/zknFKNx+OEQqFcL2VDUSqV6PV62aVTgWVdkYmI02g0FBcX542I29TClrWIuGg0ZZNQCCJOrVRgN2rwBFOpKl84Tqnl/utORsMICiWCzOqLxHgUKZmQcSo1VQ+XrTFb2UQQBHRWB1qznZB7itD8BL7xHjQmGyZnAyrd7cipmIinxmkpVZgrmmQpyHNNc3MzLpeLgYEBysvL7zDijUaj9Pb2LtcS19XVsW3bNrRa7f12l9eYTCZMJhMzMzNIkiS779PK6Qb5Xr+dKSaTCY/HI7vPbS0iDlIlYfki4ja9Js5ut2d0EUq/uYVy4VrZofoww99kLIJSq5fVSQHyNjCWxCSxgA+10VrQxf2CQoGxpBp7cwc6WymxgBfP4CWWXMPLI7yWXENIyTjm8gaU6vwdd1fIKBQK9u3bhyAIXL58mWQyiSiKDA4Ocvz4ccbGxnA4HDz77LPs3r27YK6D98PpdBKNRmVZOybn5gaj0UgymZSdRUz6fEoHi1ZLeiZwPqTONz0Sl2k9XPpLUwiROEgZ/vbPpkTMg5obxGQCMRGT5UgqOTc1xAJekMSCS6XeD6Vai6WqBb29nCXXMGH3NBHvHFqLg6hvAY3ZjtZakutlyhqLxUJrayt9fX1cunQJn89HMBjEYDCwd+9eysvLZfOg53Q6GRwcZGZmZlPHf20G6eYGuRvjFkJ9+mpZaySuvLycUCjE0tISFktum9s2vSZO7iJutYa/aXsRudXDASSiQRAEWTY1RG/VwxViKvVBqA1mihp2YalqAQQii6m6JZ21RDYCIp9xOp2oVCqmp6cJh8Ns27aNo0ePUlFRIav33263o9FoZOkXJwgCZrMZvz+7Y+9ygVxtRtYj4iA/mhs2TcQtLS0RCAQythcpNBF3x/zUBzQ23PaIK4zjyoRkNIJSo5PVzSdNbGkRpVYvS/EtCAI6WymGkqrln/knb+Ib713+vm6xscRiMa5fv87p06dJJFJp7PLyclpbW/PeUmktCIJAaWkpPp9Pdqk5SImdaDRKPL66iT2FQrrGT24iTq1Wo1Ao1lQTB4+YiFurvUghNTbAnSLO/6B06i2fLoW6sGtc7kaSpFStnwxtU5LxWCoFrs9fb7j1IolJwguTKFRq7E170VqKifrduAe6CMyOIsrQ4ysXSJLE6OgoJ06cYHh4GKvVytNPP01xcTFTU1MZeccVGnZ7Kootx9qxrYhVYSEIAjqdbk01cZAfXnF5L+IikQgKhSKvjSxXstp0qhi/JeJU8ioYT0VsJFlGquQ+hQIg5J5GTMQxlFSj0hmx1mzHVrcDlVZPaH4Sz0AX4cXZvCjoLVTm5+c5deoUV69eRRAE9u7dyzPPPENxcTFtbW0A9Pb25niV2UPODQByNcZVqVSoVCrZiThINTcUcjp10xob1iPitFptwaTm7uxOvb8r/nIkTnYiTr4GxnJu2IBUs01ofhKFWoe+yLn8c43JRlHjXiKLswRmR1maGiDscWEub0BtkG9UcqMJBoPcuHEDl8uFQqGgubmZlpYWVKrbl2G73U55eTkulwuv17sseOSExWJBEATZNwDIDZ1OJ0sRp9PpWFxcRBRFFIrVxbUeaRG3lpo4g6FwCuQdqxy9lYzHEBRK2Q0RT0blO0ps2TpFVzjfx0yIeOeQxCQmZz3CXRczQRDQ251orQ6Cc+OE3S4Wh6+htZZgctahlFlZwEaSSCTo7+9naGgIURQpLy+nvb39vl5iLS0tuFwuhoeH2bdv3yavNvsolUosFossI3FyrR2DlNiRo/BOp4qj0eiqO28faRGXSSROkiSi0ehyDUUhULoinRqJi0TiSXTqdwo1MRFDoSqMFHEmyD0Sp9IZEBTyEt6QOtfCbheCUoXOdn9LEYVShbm8Ab3dScA1QtQ3T9TvxlhSjcFRIcv3Zq1IksTk5CQ3btwgGo1isVjYsWMHJSUPtmyx2WzLtXFtbW0FUw+cCVarlfHxcSKRiKyOT6VSodPpZBmJ02q1xONxksmkrJpuVtb7rVbE6fV6bDbbo1UTt7i4CJCRIEsXGxaSwaXdqGFl5vd+0biUiJNXKhVS82AFhVJ2AlVMpJoaVDp5plLjQR/JWBh9UdmqhJhKa8BW1461tg2lWktwbgz3wCUivoWtejnA4/Hw5ptvcunSJSRJYteuXRw+fPihAi5NfX09oigyPj6e5ZXmBrnXxQUCAdmdB3Jtblir4a/dbs+L7++mReLS3VbpmoHVkG7T1mgKR+yolAqKDHeO3iq7a/SWJIpIyQQKGbrgi/EoCnXh1DCuFjlPoQAIe275wq2ohVsNWrMdjdFG2OMiODeOf6IPtcGCqbxBtrWDDyIcDtPT08Pk5CSCINDQ0EBra2vG17Dy8nI0Gg3j4+M0NzfL7nxKizifz7c8U1Uu6PV6FhYWSCQSBdOQtxpWijg5jRVLn5uZ2sKYzea86CLftEhcIBBAq9Vm9KVO+yatLPwtBEoeUhcn16YGSM3blONxybmpQUwmiC65URuta+oqFhQKDI5Kils60BU5iYf8LA5dwT81iJjIvV9WOBzmc5/7HC0tLeh0OioqKvjEJz7B1NRUxvtaXFzkM5/5DLW1tWi1Wmpra/nsZz+L2+2mv7+fEydOMDk5SWlpKUeOHGHnzp1reghVKBTU1NQQDAbxeDwZb5/vpJsb8iGSsdHINWK1snZMTqT1RVpvrBaTyfRoibilpSXMZnNG2xSqiHOYV3So3sPwV64iTkwmkMSkLOds3m5qkM8TaJpYYBEkCZ3Vsa79KFQaLJVNFDXuQW2wEFmcwd1/kdDCFJIobtBqMyMSiXD06FF+//d/n0AgwAc+8AGqq6v5m7/5G/bu3cvw8PCq97WwsMCBAwf48pe/jEql4oMf/CBms5kvfelL7NmzhwsXLqDT6Th48CCPP/54xte7u6msrARgZmZmXfvJR5RKJWazeUvEFRDptKPcjmutIs5sNudF7eOmRuIeGRG3ykic3MROOuoiN3EKkIgEUWrl2dQQ9W/sKDG13oStfieW6m0IShWBmRE8g5eXR5ZtJl/4whc4d+4cTzzxBP39/Xzve9/j/Pnz/Omf/inz8/N84hOfWPW+PvvZzzI4OMiHPvQhbt68yV/91V/xl3/5l7z3ve9lcnKSf/mXf+Ho0aM4nc4NSX9arVZ0Ol1edMBlA5vNRiQSkV1kR64RK7mK0/WIuFAoRDLHBuibGonLpB4OClfEPTSdmkwdl6AsrON6GLenUMhLxEmSiBiPytLAWJJEYkseVDrThtqECIKAzuqguHkfxtIakvEovrEevKM3SERDG/Y6DyIej/PVr34VgL/4i7+44/rz3//7f2fXrl2cPn2arq6uh+7L5XLxne98B41Gw8svv8yNGzc4deoUCwsLfO5zn6OkpIQf/vCHLCwsbNj6BUHA6XQSDAbzIm2z0WxNNygs1lo7lu+sJ50Kuf/+FkQ6tdDamR13TG14p+FvOrUkt6iOXKdQyDnCGA/6kcQkWkt2bHwEhRJjaQ3FLR1orSXEAot4Bi6z5BpefpjJFpcvX8bn89HY2MjevXvf8fsPf/jDALzyyisP3dd//ud/Iooi+/fvp7u7m9HRUYqLizl8+DAHDhzgxRdfJJlM8qMf/WhDj6GsrAxAlgPj5Rqx2ko7FhbricQBOX/A2kqnZoGHpVOlW+FX2Ym45Vo/+XRkwQpxKrMII9yqh2PjUqn3Q6nWYq1upahhFyq9kbB7Gnf/RcKemaxZMdzsuwlwX8Pc9M+vXbv20H299dZbAJSWlqJSqdi/fz9PPfXUcpdlJvvKhJKSEpRKpSxFnFzFjlwjcQqFAkEQZCfi0kGiQhVxm6KORFEkEAhknE5N55oLTcQ9bH6qJMpdxMlL7Mj1uCDVsCEolJvWsKE2WChq2E3EO0dwdpSl6UHCHhem8gY0RuuGvpZrJlVLVlVVdc/fp38+NjZ2330EAgG6u7u5fv06AG1tbRw7duwd2YHV7GstKJVKbDYbXq8XSZJkZTUiV7GjVCpRq9WyizAKgoBSqZSdiFMoFCiVyoxr2/JlxNqmqKNQKFUD8+hE4h7cnZoWcXIbuZVOj8kuEidTESdJ0q0pFMZNFQeCIKAvKkNrKSY0P0nIPYV35DpaiyM1wkuzMQ7+6evO/cb2pb2u7vUkHY/HuXnzJsPDw0iStBwtrK+vv2d5x4P2tV5sNhtut5tgMJjxg3A+I1cRB6BWq2VXOwape7HcRBywJnH6SEXi1mL0C4Ur4lY2NkQT7xy9JddI3O3j2rQs/aaQjMuzmzgZiyCJyZwZGCuUKkzOutQIr5kRov4FokseDI5KjCVVOTk/JElibGyM3t5eYrEYVquVnTt3YrFYNn0taazWVITS6/XKSsSp1WoUCoXsIlYgX7GjUqly3o2ZDdbyeaXPxUdCxKXDjY9KJC49eitd6uMLx+8p4hDkJXYkMQmCgCCz45JrJC4RyQ8DY6VGh7VmO7GAlyXXMKH5CSKLs5icdWitJWuOEqYjcOmI3N2ku8rS16WFhQW6u7vx+XxotVr27NlDTU0NgiAsX7BXu6+NZOV0g/ulhgsRQRDQ6XSyjMSpVCrZilO5HtdaI3GPRDo1rVTXIuIUCgWKAovsqJQK7AYN7vuM3hKTSQSFUlb1LZBq2JBbdBFuiThBkJ0lTGLZwDg/ojsakw17017CnhmCc2P4J/tRuV2YyxtQGzIXR+XOcgAmJyfv+fv0z6uqqnj77beZnp5GoVDQ1NRES0vLHdNlampqVrWv2trajNf5MEwmE0qlUpbGuFqt9r7CuJCRcyQu15Ya2WAt4vSRSqemlepa0qmFFoVL4zBpb4u4u+riJFGeYkeuxyXGYyhUGtmJ7mQsddHaqBq0jUAQBAzF5eisDoLz44TdLhaHr6KzlWIsq8sopd26rRWAS5cu3fP3Fy9eBFIRu+npaZxOJ+3t7fe8Tu3evfuB+0r/fNeuXate32oRBAGj0ShLsaPT6VhcXEQUxYJ7WH8Q6bSj3JpR0uJUrseVCfmSTt2Us2atg+wL+cRe2aHqDW+JuEJGrvNgxUQMQanKyxpGhUqNubwRe9M+NCYbEe8cnoEugvMTqx7htXfvXqxWK0NDQ1y5cmX555IkMTk5yd/93d8BcPjwYZ544gkOHjx43wfNH/uxH0OhUPDmm28yNzd3x++i0SivvPIKSqWSF154YW0H/BB0Oh3RaDRrdiy5Qq5ecXL2VJMkCTFHY/SyxVq6U9N6Jtef8aZcvdMfeKaCrJDV/soO1bsNf1NiJ/9unOtFEkXZddxCSuzIreMW0seV3+JUpTNgrW3HWtOGQqUmODuGe+ASUb/7oYJGrVbzqU99CoBPfvKTBINBFhcXOXPmDJ/73OcYGRnh4MGD/PIv/zKlpaUAfPWrX2Xbtm385m/+5h37Ki8v5yMf+QixWIxf+ZVfuePC/eu//uvMz8/z8Y9/fHk/G41OpyOZTOb8hrHRpL3iYrF3mqIXMnIVcenObDk2N2RKWs/kWtBumk8cPGoi7sFecRTocT0IOUbi0kJBbs0akiSRjMfQGHPXdblaBEFAa7GjMdkIe6YJzk3gG+9FbbRiLm94oMfdb//2b3P8+HE6Ozupq6ujtbWV+fl5+vv7KSkp4R/+4R/uuC4tLCxw8+bNe84r/fM//3POnTvHP//zP7Nt2zb279/PjRs36O7uprm5mT/7sz/LyvHDnXYcK2v1Cp18uRFuNGs1kM130vdjuUWEVx7XajVHvnx3N+XOlFbta0mNFqqIe6DhryQBhXlcD0KSJBmK01sXK5kdlyQmQRLzPhK3EkGhwOCoorilA11RGfGgD8/gZZamh5ZHo92NWq3mG9/4Bi+99BIqlYoLFy7g8/n4uZ/7OS5dukRDQ8OqX9/hcHDhwgU+/elPE4vF+Nd//Vd8Ph+/+qu/yoULF7Dbszf1Qq7TDeQqCtL3Orkdl1w/r7XojHwRcXkfiStUVkbi7mX4KzNNcAsZitPlSFyO17HBLI9+K8COW4VKg6WyGb29nIBrmLDHRcQ3j7G05o6/m5+fZ/z6MMFgkF/8xV/k5Zdfxul0PvCC/fnPf57Pf/7z9/293W7ny1/+Ml/+8pc36nBWhVyHj8tdFGwdV2GwlkhcOtq6JeIeQEGnUx84ekuGYgduG+PJiNsXK7l9XmlxWrjHpdabsNXvJOpfIDAzSsA1jCTevqRdv36daouKtrY2Ghoa7jlpoVCQ680zX6IZW2wBmZ1f+fLd3VQRV8g3jEwpeUBNnMyuw3cg289YZsclF3EqCAI6awlas53g3DgwQ/qYSkpKOPb0vuV6skImfV7l+oax0chVnG4dV2GxluNKi7hcN3lsSk2cbG/sD8Bhvl1rlB69leYRfDu22CJrSJJEeHGW8OLsHT9fWFhgaGhIVilIuV5L5XpcckVun9ftBrbVH1d6m1zboG1KJG6tYUdBEAr2ydNueNDoLXmdALcRZPuEJrfw6e2LVWEfV3pUVzIaSjVpCBLpYzIZTQwODjIxMcH27duXR2gVIvlyw9ho5JqlWYsoKATkdn2/m0w+r7WWiW00m/Lq+ZI73kxUSgXFxpVecXenVGV4MsjrenULeaYP0nN7V2ucm28komG8Yz14R7tJxiIYSqopbum44yK8/7H97NmzB4ArV65w+vRp3G53jla8PtbT4Z/PyFXspJHbccn181rL9T1fzsm8j8QV8s3TYdKyEEiZWN7RoSqzE+A2guwiVsgkYnU3afNiMVFYJqtiMkFofoKQexokCa3Vgams7p6jwwRBoLa2loqKCvr7+xkaGuLMmTNUVlbS1taGwWDIwRGsjbS1SNpqRC5siYLCRG6fV5pCjMRtiojLl1bczSZlM5Kaq3b31Aa5iQJI+XhJkkw/Y5ldlAVBQKFSF4yIkySJiHeO4OwoYiKOSmfEVN6Axmh96LZqtZr29nZqa2u5ceMGU1NTzMzM0NTURFNTU0HMZ06PpZJDk8ZK8uVGuNGkozSF3BF9L+QqTtdyXPny3d2KxGWR+xn+CoKiYNNYD0JQKJf9x+SCIAgICiViUl7O65DyW0vG81/ExYJ+Aq5hEpEAglKNuaIJXVFZxtEAk8nEwYMHmZubo7u7m5s3bzI+Pk5bWxuVlZV5HV2QayQuPdFAbmInfVyF8ICQCfkiXDaatUSE8+W92FQRl2krbiE3NsCd81NXplMFhUKWokBQKFOTAGRGKmIlnw7HNAqVhkQ0nLd+jMlYlMDsKFHfPAgCBkclhpJqFOs0KC4tLeXZZ59ldHSUvr4+urq6GBkZYefOndhsto1Z/AYTiUTQarU5v2FsNGlxKrcIo1xFnFyPay3XwEeqJi5dexIKhTLaTqVS5dyDZT3cb36qoFAixaO5WFJWERRKRBkeV0rsZPbdLQQUag1IIlIygaDKn3mckpgktDBFcH4SJBGN2Y7JWY9Kq9+w11AoFDQ0NFBVVUVfXx8jIyOcPn2ampoatm/fnneiIi3i5EYkEkGpVMpOFCQSiVTJgsxEdyKRQKlU5uVD33pIJBIZfwfTeibXtbWbcuaYTCYAlpaWMtpOpVKRSCTyNlLwMO6bTlUq5ZtOlWMkTq1BCvmRRBFBRhdllTZ18UlEgmhMttwuhtTTcHr6ghiPotTqMTkb0JqLsvaaGo2GXbt2UVdXx/Xr1xkfH2d6epqWlpa8mfIQj8cJhUJUVVXleikbTiQSQafTFeT1/UGkRYFcj0turOW40nomrW9yxaZ8GmazGYBAIJDRduk3NZlMFuQX50GROCSxYMXp/VAoUyJOdsd1a0i8mIjdswuyUFHpUxefeDiQcxEXDwcIuIaJh/wICiWm8gb0dieCsDmi2WKx8OSTTzIzM0N3dzc9PT2MjY2xY8cOysoyr7/bSLxeLwBW68ObOAqNaDS6fH+QE1tip7BYy3Gl9Uyuv795H4mDwv3iPFDEkUobFeIA8vuRPi4kEYTcRzA2CtmKOJ0RgEQks4erjURMxAjMjhG5NW1Bb3diLK1dtkDZTARBoLy8nNLSUoaGhujv7+f8+fOUlJSwY8cOLBbLpq8JwOfzAeRtvd5aEUWRWCwmyzRxod6zHkYikUCtzp/Si40ikUig12dWrpHWM4+EiEsfZKYiLp3KSBdTFhor06np0Vs6tfK2iEsmQYYiTkwmUSrkI+KU6pSIS8ZjyOnypVCqUGr0JMKbL+IkUSTsmSY4N4EkJlEbrZjLG5aFZS5RKpW0tLRQU1NDT08PExMTnDp1irq6OrZt24ZGo3n4TjYQuUbi5NrUAKl7lhyPK5lMZix2CoF0rV8mPFLpVI1Gg0ajWXM6tVBFnN2oQSGAeMslxRuK47Qq74jEyYmVBrJp4SMHVkbi5IZKbyLqm0dMxDcl+iVJErGlRQIzwyRjERRqLZaqZjTm4rxLwet0Ovbt20d9fT3Xr19nZGSEyclJtm3bRl1d3aYVrXu9XoxGo+wiIHIVcZIkEY1GZSe6YW1iJ9+RJKmg06mbVqVtMpnWnE4t1A5VpULAbnxnSlW+Ik6eYkeuxwUsm+XGAt6sv1YiEsI3dgPfeA9iIoaxrJbi5g60FkfeCbiVFBUVcejQITo6OlAqlVy/fp1Tp04xPz+f9dcOBAIEg0EcDkfWX2uzkauIi8ViSJIku+MSRbFg69MfRNrGbK2NDbkWcZv2aZjN5kcuEgcpr7iFQMp2Iy3iFMotEVdIKG5FFcUCMMbNFM2tzs/okgedrSQrryEmEwTnxgm7pwHQ2UoxltWiVBdOLZQgCFRVVeF0OhkYGGBwcJDOzk6cTic7duzAaMxOGnh2NlUr6HQ6s7L/XCLXKRRyFafpYIrcRNxave/SeuaRSKfC+iJxhSziSsxa+mZSx+29NXrrdiSucI/rXtwWO/IyxhUUShAUJGXogadUa1HpTcSWPEiSuKHdoJIkEfbMEJwbQ0omUOnNmMsbUBsKtxtRpVKxffv25RFe09PTzM3N0dDQQEtLy4anPGdmZlAqlbKMxIXDYUB+Ykeu4lSuRr9rPa5HMhI3Pj6e0TayEHH36FC9XTsmL7Ej10icIAiodAYSkaDs7FMAtGY7wfA48aB/w6xGYgEvS65hktEQCpUGc1ULWmuJbN47g8HAY489xsLCAt3d3QwODjIxMUFbWxvV1dUbcpyxWAy3201ZWZnsbpyQ6rpVKBRZi2LmCrmOSJPrca1HxCmVypy/H5taE/dIplNXGv6G0iLudrejnFjZ2CA31HoTUjIhy4kUGrMdgOiSe937SsYi+MZ78Y52k4yFMZRUY2/uQGcrlY2AW4nD4eDw4cPs3r0bSZK4fPkyb7zxBh6PZ937np2dRZIkWaZSJUnC6/VisVhkN9VArunUdIQx16Jlo1lPOtVsNuf8urbpNXGZRDJkIeJWzE+9HYmTb8RKoVLLTpwCqHS3jXHl5BUHKb84pUZHxDuPqax+TVMpxGSC0PwkIfcUSBJaSzEmZ73s3qt7IQgCdXV1VFZWcvPmTYaHh3nzzTepqqqira1tzZYM4+PjCIIgSxEXiUSIxWJUVFTkeikbjlxFXPq45GYxsp5IXK5TqbDJNXGiKBIKhVYdPpeDiLvX6C1BqQJBkJ2Ig5RAleNxpacbJCJBsMqrPkkQBHRFToKzo0SX3Oisq29wkCSJiHeO4OwYYiKGSmfEVN6w3PX6KKFWq9mxY8dyvdzk5CQul4vm5maampoysmYIBoMsLCxQUVEhu8gH3Pa+k5uBMcg37SjX41qPiMt1UwNsYjo17Xbu9/tXvU36y5L+8hQi95rakIpYaWTZ7ajU6BHjUdl13qp0BhCEnBjjbgb6olIQBMKemVVvEw/5WRy+ytLUAJIkYq5ooqhxzyMp4FZiNpt5/PHHefzxx9Hr9fT19XHixAmmpqaQJGlV+xgdHQWgtrY2iyvNHXI1MIaUADcYDFtp4gJhreLU7/fnRSRu075lpaWlwO2W+dWgUqlQKpXLufhCZKWI84biyxfxVMRKXo0NAEptKtSejBWu8L4XgqBApTMSDwdWfSMuJBQqDVqLg3jQl4o2PoBkPIpv4iaLw9dIhIPoiysobtl/a9ap/Ore1kpZWRlHjhxhx44dxONxLl68yNmzZ5cFzP1IJBKMjY1hMpkoKcmO7UuuSTc15GqUWbaQJIlAIJAXEZqNJhqNIgjCpk8syTZrqfUTRZG5uTnKysqytaxVs2kirry8HACXy5XRdjqdrqAjcSvTqbGkSCSeMhZUqlNpR7kJAqUmJeIS0XCOV7LxpJob4rKMoAIYilP1SaGFqXv+XhKTBOfGcfd3EfXNozEVYW/ei7m8AYWMxsdtJAqFgsbGRp577jnq6upwu92cPn2aK1eu3PfhdHx8nHg8TkNDgyxFsdybGkRRlF3HLaQsYXQ6ney+k2uJMLrdbhKJxLKuySWbduVNF7CuRcRlkoLNN4oMd47e8oXj6DXKFc0NcVmNqFItR+LkJ+LSzQ2JSAClRl51IQBqgxm10UrEO4fBUZVKIXNrjJDfTWBmBDEeRanRYyqvR3urq3WLh6PVatm9ezd1dXV0d3czNjbG1NQUra2tNDQ0LIuZRCJBf38/Wq2W6urqHK86O0QiEaLRaF7cADeafDGAzQbRaFR2qVRIfR+VSmVGNXFpHZMPjTmbHombnp7OaDudTkc8HpfN6K204a9cO1TT3YhJGUbi0s0NcZnWxQGYyuoACMyOAqlj9Y5cxz/Rh5RMYHLWY2/auyXg1ojVauXJJ5/kscceQ6PRcOPGDU6ePLlcZjI0NEQ0GqW1tVWW3nAg73o4uYq49DxYuYq4TCOMaR2TDw8im3aVWE86FVJPAQaDYcPXtRmUmLXvHL2llqenmkKlRlCqZFcTB6DSyru5AVLROK2lmKjfjXesh9hSyu9MV+TEVFa77AW4xdoRBIGKigrKysoYHBxkYGCAc+fO4XA4WFxcxGg0yrahAeTdmSpXEReNRmU5DxZSx5Zpg0JaxzxSIq60tBSFQpGxiFvZoVqoIu5eXnHpuZFyFDtKjV6WNXGCQoFabyYW9CGJ4pr81PIdSRSXo6mxJU9qVFZFI2q9vG5K+YBSqaS1tZWamhp6enqYnJwEwGg0kkgkZFdAnmZ+fh6VSiW7pgZIdaYqFArZeamlR6TJ7bhEUSQWi2XcmZpPIm7T7kJKpZKysrI1R+IKurnB9M6pDekGADmKOJVWn2oAkGH3rcZsB0kkFvTmeikbTnTJg2fwcqqx4dYMVb29fEvAZRm9Xk9zczOCIKBUKpmbm+PEiROMjIzIrvEpEomwuLi4/FAvN5aWljAajbIr/pdrhHGttimPZE0cpFTrWmrioMBF3D0MfxVqLQjCVu1YgaG13BpR5V//WKV8IREN4R29gW+sh2Q8irG0luLmfQhKNYGZYVlO4MgnRFHk0qVLSJLEk08+yb59+xAEgWvXrnHq1Cnm5+dzvcQNI137J8cpFLFYjFAoJOtaP7l13a5VxE1PTyMIwrJ1Wi7ZdBE3MzOT0dOlHETc/Qx/lRq97Ls45YZKa0Cp0RNb8hR8lERMJlhyDeMZuEwssIjWWkJxSwfG0mqUGh3mikakZIKl6cGCP9Z8ZmBgAJ/PR3NzM3a7nerqap577jmam5sJBAJ0dnZy4cIFgsEH+/cVAjMzMwiCkBf+WhuNnGv90t+9LRGXwuVyUVpamhfNR5u6gvLycmKxGB6Ph+Li4lVts7KxoVBxmG/XtnjDt1OMKq2eqN8tu/oqtT51osu1AUBjthN2T5GIBAsy1ShJEpHFWQKzo0jJBCq9CXN5A2rDnTVKOquDqN9B1LdA1DePzpb7p0654fP5uHnzJmazmdbW1uWfq1Qq2tralkd4uVwuZmdnaWxspKWlJS9uHpmSTCaZn5/HbrfLst7P5/MB8hRxgUAAvV5fkN+7B7EWo19Iibh8qIeDHETiILMOVZVKhUKhKOhIXInptspP18TBirq4eOEe270QFEqUWoMs06mwMqXqzvFKMicW9LE4dIWl6UEEQcBc2UxRw+53CLg05vJGBKWaJdewLOs3c0kikeDSpUsA7N27956zVY1GIwcOHODJJ5/EZDIxMDDA8ePHmZiYKLjo6Pz8PMlkUpapVJCvdUp6CoXconCwtkicJEmProhLFwFmUhcnCELBT21YGYnzhW+P3lJq5eupptYbEeNRWTY3qA0WBKVq2X6jEEjGIvjGe/GOXCcRDWFwVGFv7kBfVPbAImyFSo2lshkpmcA33oNYoH6N+YYkSVy5cgW/309raytFRUUP/PuSkhIOHz7Mrl27kCSJS5cu8eabb+LxFM53cGYmNZdXziLOZDLJLloViURIJpOya2qAtYm4xcVFotFoXjQ1QAFE4gAMBgPBYLDgnjzTrKyJiyVFwvHUjfB2h6r8RJyc6+IEQUBjKiIRCZKM5XeaXxKTBGbHcA90EfW70VqKKW7uwOSsW/WoLK3FjrG0lkQkxNJUf8Geh/nEwMAAU1NTlJeX09LSsqptFAoF9fX1HDt2jIaGBrxeL2+++SZdXV3LFhD5iiRJzMzMYDKZZCkG0k0Nckylpuvh5Pi5BYNBVCoVavXq/S/zyV4ENlnEVVZWAiz7Ia0Wk8lEMpks2GhckUGDUnE72pFubkiPqJKjp5qcO1QBtJZUTWc0T6NxkiQR8c7h7u8iND+BUqPHVrcDa832ZR+4TDCUVKG1Ooj63QTnxrOw4kcHl8tFb28vFotluRM1EzQaDTt37uTIkSOUlpYyOTnJiRMn6O/vz9vJNl6vl2g0KtsonNzr4UCeIi4QCGAymTI6B9P65ZGMxDU2NgKpp9BMSH95CrU7KzV6652Gv4JSjaBQyjSdekvEvsyMXQAApe9JREFUhZZyvJLsoDHZQBCILeVfXVw8tMTi8DX8k/1IkoipvBF7097UmteIIAhYKptR6YyE5ieIeOc2bsGPEF6vl66uLjQaDQcPHlxX6s1sNvP4449z8OBBdDodvb29nDx5kunp6byLlso9lZpOa8tZxMmtJi4ejxONRjMWp2n90tzcnI1lZcymJu+LioooKSmhv78/o+3Sb3IgEMDhcGRjaVnHYdIyv3Rr9FZohc2IVp42I4JCiUpvJh70IUmS7MwvFUoVGqONWGCRZDyGUp37brtkPEZwdnRZYOmLyzGW1GzYqCxBocRa08bi8FX8k/0gKNBZC/N8zAV+v5/Ozk4kSeKxxx7bkAk0giDgdDopLS1leHiYmzdv8vbbb+NwONixY0deFNlLksTk5CRarRa7XZ4zdxcWFlAqlQ+tbSxEAoEAgiAU7MSk+7HWNHFav6y2DCLbbLqvRUtLS8YiLv0EkH4iKETuZfgLoNIZERNxWRqqaoxWJDFJIlKYEdSHobenvK4ii7M5XYckigTnJ/AMdBHxzqEx2bA37cNc3rjhs06VGi22+p0oVGr8kzcLskM3F6QFXCKR4MCBAxv+MKpQKGhqauK5556jtraWhYUFTp06xdWrV3NuzzQ/P08oFKKmpkZ2D3OQsk5ZXFzEbrfLcgqFz+fDYrHI7tjWGmHs7+9Hp9NRVVWVjWVlTE5EnNvtxu1e/cXfYDAgCELBplPh3vNT4XbaUY6eampjKgoQD/pyvJLsoDHbUajUhBczM7DeKCRJIupfwD3QRXB2DIVKjbWmDWttOypd9p6aVdpUfZ2gUOEb7yPik89EgWzg9Xo5e/YssViMxx57LKtGt1qtlj179nD48GGKi4sZHR3lxIkTDA0NIYpi1l73QYyNjQFQW1ubk9fPNl6vl2QyuWrv00IiEokQiUTyIqK70awnEtfc3Jw3ojYnIg4yq4tTKBQYjcbCjsSt6FC9w/BXxl2cae+xmExFnCAo0NnKEONR4ps8SzURCeId7cY33oeUTGBy1mFv2ofWYt+UaIdKZ6So4VZEbuImoYWpvKvDygdmZ2c5e/YsiUSCgwcPblpHm81m46mnnmL//v2oVCq6u7t5/fXXl8debRaRSASXy4XD4ZBdTVWahYUFgIIt9XkQcp5CsZZIXDQaZXR0NG9SqZBDEbeWurhgMJizp8n18qB0Kgiy7OJUKO+si5MjuqJUVCXsmdmU1xMTcZamB/EMXiYe9KErKqO4pQODo2rTp36otAZs9TtRavUEZkZYmhpAKtDzc6ORJInBwUHOnTuHIAg88cQTmz5qShAEKisrOXbsGNu2bSMcDnPu3DnOnTu3aQ/EaVPiurq6TXm9XCDneji5d91qtdqM7EWGhoaQJCmvRNymuxKuVcQZjUYkSSIcDhfkE9295qcCCAoFKp1BlulUSNXFhcJLBTui6mGotHrURhtRv5tkPIpSndn4ltUiSSJhzwzB2TEkMYnaYMFU3pDz91Sl1VPUsBv/xE0i3jkS0XDKxiQPGj1yRTKZ5OrVq0xMTGA2mzl48GBOr1lKpZLW1lZqamro6elhcnKSubk5GhoaaG1tzegmlgmiKDIyMoJWq5VtV2oymVweI5kv6bWNxOv1pjrTLfee6FKoSJJEMBjM+LjyrakBchCJa2xsRBCEdXWoFiIrRZw3dGcTg0pnQkzEZNnccLsuzpvbhWQRQ3HKLyjszszEerVElxbxDF4m4BpGUKqwVLdiq9+ZcwGXRqFUYa1tw+CoJBFeYnHoimxT6A8jEAhw5swZJiYmKCsr49ChQ3nz0KnX6+no6ODQoUNYrVaGhoY4fvw4o6OjWYmUz8zMEA6Hqauru+dIMTmwuLiIKIqyTKVCSsSZzWbZfX6xWIx4PF7wnamQAxGn1+upqal55ETc3enUlRfNtDGuHOviNEYLCAqiS4u5XkrW0JiLUGp0qQYHcePMVhPRMN6xG/jGbpCMRTGW1lDcvA+dtSTvuvwEQcDkrMdc2YKYTOAduc7S9NCGvh/5jCRJDA0NcerUKbxeL83NzRw8eDBrUa71YLfbeeaZZ9i7dy+CIHD16lVOnz69XNu1UQwPDyMIgqxTqekaw5KSkhyvZONJNzXINZUKhW8vAjlIp0LqDTh79iyiKK46BF3oNiMru1PjSYlwPIlBk3r7V3aoas3y8lESFEo0JiuxJS9iMrHqUU+FhCAI6IsrCLiGiXjn0dvXlzoSkwlC8xOE3NMgSWitJZjK6lBqspOq3Uj0RaWoDWaWpgYIe1zEAouYK5vRGOXX3ZYmEAhw5coV3G43BoOBvXv35n1kRhAEampqKC8vp7+/n+HhYc6ePUtFRQXt7e3r9gTz+Xy43W6qqqoymktZaMzMzKDVamUpdNL1cHLsTF2PvUhRUVFedSLnJInf0tJCKBRienp61dvodDqUSmXBirh3jN4KrWxuSF0w5djcAKA1FwMSMRlH43S2UgSFkpB77W75kiQR9sykRmUtTKHSGrHV78Ja3VoQAi6NSqvHVr8Tk7OeZDyGd+Q6/qlBkvH8njObKYlEgps3b3Lq1Cncbjf19fUcOXIk7wXcStRqNe3t7Rw9ehSn08n09DQnTpygt7eXRCKx5v0ODQ0Bt6f0yJFAIEAgEMDpdOZdZHwjeBQ6U9cSiWtpacmrzztnkThIvSGrNcxLF1f6/f6CnACgUAgUGzXMpac2hOOU21KzUwWFUt7NDeZU11Z0yYPOJr+0A6TqwvR2J6GFKaK+eXS20oy2jwV9BFzDJCJBFCo1psrmlDAssO95GkEQMDgq0ZjtLE0NEFmcIeKdw1BcgaGkqqAjsqIoMjo6Sn9/P9FoFKPRyJ49ewpKvN2N0Wjk4MGDzM3N0d3dTX9/P+Pj47S3t1NZWZnR99Dv9zMxMYHD4ZClAEgj91Fi6aYGOUbi/H7/snXZavH5fMzOzvLud787iyvLnJxF4iDzDlWr1UosFiMcLswxVffrUAVQ6S2p5oZYZLOXlXWUai0qvYnYkgdJkq8FRcrmQ0lgdmzVVhvJWATfRB/ekeskoiEMjkrszR3oi8oKVsCtJB2Vs9a0odToCC1M4u6/SHB+EjFPh7XfD1EUl4fNX79+HYBdu3Zx9OjRghZwKyktLeXZZ59l586dJJNJurq6OHPmDIuLq4+i9/b2AtDW1patZeYFMzMzKJVKWdbDSZKEx+PBYrHIrqlBkiS8Xm/GUyjS3rb5VA8HOYrEbd++HWD5Qrha0k91Xq+3IOe4OcxauNXA6L1LxGmMViKLM8SCPvQa+dWQaM12guFx4kH/ugax5zMKlRpDSRXB2THCizPLXav3QhKTBOcnCS1MgSSiMdsxOetRafWbuOLNQRAEtBY7GnMREe8cwblxgrOjhOYn0BWVYSiuQJnH3/lYLMbY2BgjIyOEw2FUKhXbt2+noaFhXQPs8xWFQkFDQwNVVVX09fUxOjrKG2+8QXV1NW1tbQ+scfN4PMzMzFBeXi5L37Q0sVgMj8dDWVmZ7EQOwNLSErFYjOrq6lwvZcMJh8PEYjEqKu5/fb4X3d3dAGzbti0by1ozObkC1dTUYLfbuXTpUkbbrRRxmX4A+UDJAyJxamPKryYe9KEv2lxT0M1AY7YTnBsnuuSRrYiDlN1I2O0iODeBzlaG4q4LvCRJRH0LBGZGEBMxlFoD5vJ6NCb53vDSCIKAvqgMnbWEiHeWkHua8K1/aqMNvb0MrdmOoMj9TVEURdxuN2NjY7hcLkRRRKvVsm3bNurr69Fo5O+Dp9Fo2LVrF3V1dXR3dzMxMcH09DStra00NDS8Q7xIkkRPTw+CICw/qMuV2dlZJEmSbSp1awrFO+nq6gKgo6Njg1e0PnIi4gRBoKOjgzNnzpBIJFb9NGs2m1EoFMtdM4WGw3zv+amQSjkqNXrZ+mupdEYUai1RvxuTs14WqcJ7ISiUGEtrWJoeJOyewlhas/y7eDhAwDVMPORHUKowlTegt5fL9r24H4JCgd5ejq7ISTzoJeyZIer3pLwEBQGN0XYrcmfPmnnyvYjH48zOzi7/i8dT52hxcTG1tbVUVlbK0tD1YVgsFp544glmZma4ceMGPT09jI2N0d7efkdR/9zcHG63m9raWsxmc45XnV1crlRKZbOncGwW6dnm+dSFuVGsdQpFV1cXRUVFeWeZk7NcQEdHB6+99hq9vb3s3LlzVdsoFAosFgter7cgmxvumJ8air/j9+pbKdVkLJLX6aW1IAgCOquD0MIU8ZBf1pYTuqJSQgupVKneXp5yB58dJeKdA0BvL8dYWoNClX8eYpuJIAhoTEVoTEWIiRgR3wJRv5tYwEsssAgModIZURssqPQmVDojKp0BQVi/kEo7tvt8PrxeL4uLi3g8nuXOYqvVSnl5ORUVFbIXJKtBEATKy8spLS1leHiY/v5+Lly4gMPhYOfOnZjNZnp6elAoFLS2tuZ6uVklLfYdDocs7VMkSWJhYQGr1ZqXPofrxev1olAoMjqvE4kEV65c4amnnso73ZFTEQcpdbtaEQcp9ez1egmHwwVXF3en4e87pzPIvS5OZysltDBFxDsvaxEnCAqMZXX4J/rwjveQjIRSo7KMVszlDbfm5W6xEoVKk+pcLa5ATCaIBRaJ+j3EAoskPCsmYQipMXVKjQ6FSoNCpUGpTv2voFTdYe/i9y/hVsWWTUvT/8LhMD6f7w4LDaVSSWlpKU6nk7KyMvR6+dUmbgRKpZLm5maqq6vp7e1lfHyc119/nZKSEvx+P01NTbJ/76anpxFFcdXOCoWGnOvh1trU0NfXRzgczrtUKuSJiPu5n/u5VW9XyM0ND+pOBfnXxal0RpRaA1H/AlJ5w6YPbN8sloWEIJAILSGoNFirWtCY7Xn3FJePKJQqdNYSdNYSJElCjEeJhwMkwgESkQDxcPD+djySEki9xxcvvs3UPS4RKpUKi8WCzWbDarVis9kwm81bn00G6HQ69u7dS11dHdevX2d+fh5I1dFlYuJeiExOTqJQKAqyLns1yLkeLhKJrKmpIV/r4SCHIq6uro6ioqLlN2e1pEWcz+cruJPobhF3d0pY7nVxkIrGBWdHiQUW0VrkV2+RiARZco3cqu9SABIao1WWx7oZCIKAUqNLlRdYb99UJFFETMSWZw6LiVhqxJcwDaREdENDA40OA1qtFp1Ot/xPjh2luaKoqIjKykoWFxdRqVT09PQwMTHBjh07KC3NzCuxEAiHwywsLFBRUSHLVCPcFnFyrIdLNzVk6n23JeLugSAI7Nu3j87OzjU1N6Q/jEJiZTr17tFbaeRcFwegs5bcqg+bl5WwERNxgnPjhG+l/nS2UoxldSxN9RP1zRMrKpN1V+5mIygUy+Ju5a1UEFykRVxdXR2NZVv1bNkkFArR19eHTqfj2WefZWRkhIGBAd566y2cTift7e0Zu+LnM5OTkwCyTaVKkoTb7ZZ1PRxk3tRw6dIlbDYb9fX1G7+odZLTmHdHRwfhcJi+vr5Vb5NubvD5fGseb5QrbHr1fUdvpUnXisk1GqfUaFEbLESX3IjJtY/1yRckSSLknsY90EXY40KlN1PUsBtLVQtKtQZzRROCQoF/akAWx7vFFmkkSeLKlSskEgn27NmzbMFy7NgxKisrmZmZ4eTJk9y4cWO507fQmZycRK1Wy7YrNV0PJ8dUKqQyeGkNsVqSySSXL19m3759eVlykXMRB6wppRqNRolECmu6QXr0Vpq7DX8hFYkDbnXnyROdrRQkiah/IddLWRexgBfP4GUCrmEEQYGlqoWihl2oDbejP0qNDmNZPWI8SmBmNHeL3WKLDWZsbIz5+XlqamruEDUGg4H9+/fz9NNPY7FYGBwc5MSJE4yNjRXcg/dKfD4ffr9f1lYzc3OpDno5irh0U0M6m7dabt68SSgUystUKhSwiAMKPqV6r+YGpVpza0TVomxHVGmtDhAUhD2zuV7KmkhEw3jHevCOdpOMRTCUVFPc0nHfWad6u3M5TS5ncb7Fo0MoFOLGjRvodDp27Nhxz78pLi7m8OHD7NmzB4ArV65w+vTpZQ+yQmNsbAxAll2baeQ8SiwSiRCNRmVj8psmpyKuoaEBm82WsYhLj3MpxIvBwzpUITWiShKTxIP+zVrWppLqPnSQCC8Rv1+XYR4iJhMEZkbxDF4ituRBa3FQ3LwPU1ntA6cMCIKApbIZQaHEPzW4lVbdoqBZmUbdu3fvA2unBEGgtraWY8eO0dTUhN/v58yZM1y8eLGgZmAnEgkmJiawWCyyHSeWHiVWUlIiy1Fiab1gt9sz2m5LxD2AdHPDlStXSGYwDNtsNqPRaJa7aAoJx0MMfyE1ogoguuTZlDXlAr29HIDI4kyOV/JwJEkivDiLZ6CL0MIkKq3h1lD3batuPlFqdJicdbfSqiNZXvEWW2SPlWnU1XagqtVq2tvbOXr0KE6nk6mpKU6cOEFfX98dfn35ytTUFIlEgtra2rysi9oItkaJ3Zuuri6sViuNjY3ZWNa6yXliv6Ojg1AoRG9v76q3EQQBh8OBz+cruILZh6VT4c4RVYVcQ/Ig0g78Ee98Xkem4iE/i8NXWZoaQJLAXNFEUeOeNZkV64rSadVZoktbadUtCo9QKER3d/cD06gPwmQycfDgQZ544gn0ej03b97k5MmTTE1N5e21TpIkRkdHUSqVsk+lgnxHiS0sLGAwGDLyl00kEnnd1AB5IOKeeuopAN58882Mtkur6UJLqTpM95+fmkYQBLRmO2I8SjIa2qylbSqCIKRGUonJ5XFU+UQyHsU3cZPF4WskIkH0xZUUt3SgtzvXfDKvTKsubXWrblFgpNOoyWTyoWnUh1FaWsqRI0fYsWMHiUSCixcvcubMmbysc15cXMTr9VJVVSVL2w0AURSZm5ujqKhIlqPEwuEwwWAwY++7K1euEAwGl3VKPpJzEXfo0CEEQeDUqVMZbZf+MAotpfqw0VtpHoWUqs5WgqBQEva48uYpXBKTBOfGcfd3EfXNozEXYW/ah7m8HoVy/baKqbRqPWIiRsA1nDfHvcUWD2NkZIT5+Xlqa2s3xMhXoVDQ2NjIsWPHqKurw+PxcPr0aS5fvpxXzgMjI6nyh4aGhhyvJHssLCyQSCRkG4VLB3syTaWmdcmzzz67wSvaOHJuXW6329m9ezenTp3KaKh9odbFlayisQFSfnGCQknU78FYIs8QvqBQoity8v9n77zj2yrv/f+WLO+9ty3vnZ04IYuwOhlt4ZaRW2YptBRaLu29wK+UFlqgtKUto4OWVUIJXRCgrJCEJMRx4sRxvONty7bkeMqytnR+fxiLJGRYtmRL8vN+vfQi2DrP+VrjnM/znYahXiwTowSEzV/CsPRJyxOduhO7xYRfYDBhSdkEhrvepqDoREzaIYyjAyiCwwiJ9a7JI4KFx+DgIHV1dYSEhFBSUuLStQMDA1m8eDFZWVnU1tbS3d1NX18fBQUFZGdnz2s7D6PRSG9vL7GxsU71FvM2pkKpycnJ82yJe5hpPtzOnTvx9/dnzZo17jDLJcy7Jw4mVe7AwIBTTX9PzIszm8/s0fI04sI/O3rrdMjkcgLCorAaxrFbvefvc5aQ2MmLhn6wb95ssBh0jHbUou1pRrJZCUvOJiZ3qVsEHHwSVk0vwC8gCF1/O2bdqFvOIxC4Ar1ez8GDB5HL5ZSXl7stpBgREcF5553HqlWrCAgIoL6+nh07dqBWq+fNY93R0YEkST7thZMkCbVaTUhICOHhvjnhZKb5cHv27KG8vNyj57R7jIgDnA6pemNe3InVqRabhN585qrcgPDJkLEvJ8H7BQQRGBmHWTcy5+1G7FYz2t4WRtqOYNFrCY5JIjZ/BSGxKchk7v1qyP0URGYWI5P7MdbThNXkPe0WBAsHq9VKZWUlZrOZ5cuXu90bJZPJSE5O5oILLqCoqAij0UhlZSUVFRVotXPbcslisdDR0UFoaKjPeqhgckqDwWAgMTHRY5P3Z8NUPpyzXrjq6mrGx8c9OpQKHiLiZpsX500iLirYH8WJo7fOElKd8gSZxrwrZOwsIXGTcwj1x1Vzcj7Jbkc/qGLo2CGMIxr8QyOJyV1KeEoucsXcJS4rAkOISC9AslkZ624QhQ4Cj0KSJA4fPoxWq6WoqGhOhYyfnx/5+flceOGFpKenc/z4cXbt2kVtbe2cRV46OzuxWCzk5eX5pLiZoq9vMgriq61FpvSBs0UN3pAPBx4i4k7Ni5su3pgXJ5fLiJ1GhSqAXOFPQFg0Zt0Idqt3tVJxBv/gMALCojFpB93qkZIkCdP4MMOth9GpO5H5KYhILyRKWYoiKNRt5z0bgeExhCUpsZkMaFXNotBB4DE0NzfT399PamoqeXl582JDcHAwy5YtY8OGDURFRdHe3s727dvp6OjAbnffRBubzUZbWxtBQUE+3VZEkiRUKhWBgYE+OWoLZp4Pt2vXLo/PhwMPEXEAmzZtYmBgYMb94rwqL24aDX+nCIqaHH9iHDvuVpvmm5D4T7xxg+7xxlmNesa6GhjrasBuNROamEls3nKCIuPmfZcdHJtKUFQC5vERJjRd82qLt6I3WznSM4rVLkSwK+jt7aW5uZnIyEiWLFky79+R6Oho1q9fz7Jly/Dz8+Po0aPs2rWL48fdc13s7u7GZDKRm5vrs3NSYbJ9ysTEhE/Pg51NPtzq1as9Oh8OPKA6dYrzzz+fJ554gl27dlFcXDzt4+Li4ujr62NoaMhr8ham0/B3isCIWGRyOcbR4z5dxRgQGol/SATG0QFCEzLw8w8890HTwG6zMjHQjWFoMmQQFJVAaGKmy9Z3BTKZjPCUXKwmw+REiKAQgqJm38LBlxkzWGhSa2lSj9OsHqdzaIJTnZi+GwBzL6Ojo1RXVxMYGEh5eTkKhWfcJmQyGenp6SQnJ9PS0kJrayv79u0jOTmZkpISQkNd40232+20trbi7+9PZmamS9b0VFSqyU1zWlraPFviHqby4TIyMpw6zlvy4cCDRNyJeXHf/va3p33cif3ivEXETWd+6hQyuR8B4bGYxo5jNRlQBAa727x5IyQ+jbGuBvSDvYQnz64aTJIkjCNqdJouJJsVRXA44cnZ+Id4ZvWVTC4nMqOIkbYjaHtb8QsI9lhb5xpJkjg+bqJJPf7JQ0v/2Nn7iEUFgjJufkLk3ozRaOTAgQNIksSqVasIDva8641CoaCoqIjMzEzq6+vp6+tDo9GQk5NDXl7erKtn+/r60Ov1FBQUeIyAdQd2u53e3l7CwsKcHgrvLUyFUp3Nh9u5cyfg+flw4EEiLjo6miVLlsyoX1xwcDBqtZrS0tJ5d/tPh5NF3LnDwEFRCZjGjmMaO44iwbkdhTcREBaNIigEw7CakLg0/PwDzn3QaTDrRhnvb8dm0iNXBBCelk9gZLzHfzb8/AMmhVxHLaOddURlleEfHDbfZs05dkmid8Tg8LQ1qccZnjj39yQiSMFKZQwxtmHWpijw9/PN8JC7MJlM7Nu3D4PBwNKlS50eFD7XhISEsHLlSgYHB6mtraWlpYXu7m6Ki4tJT0+f0ffdbrfT3NyMn5+fT7cVATh+/Dhms5ns7GyPvzbOlKn+d842p961axcBAQGsXr3aHWa5FI8RcfBpSLWxsXHaIVWZTEZSUhIdHR2Mj497RUNGZ8KpAAFhUcj8/DGODhASP7OLkzcgk8kITchkrLsR/fFuwlNynTreZjaiU3dg0g6BTEZIfDohcWnI/fzcZLHr8Q8JJyqziNGuBkY764jOKpu3oou5wmq30zk4QZN6nMb+cY5pxtGZzl2pmxgRyKqsWFYpo1mZFUN+QjhyuYwdO3bMgdW+hdlsZt++fYyPj1NaWup0+Gk+iYuL4/zzz6erq4vGxkaqq6vp6OigrKzMaSHa09ODTqcjPz+fgICZbSK9BV8Ppc50lJi39IebwiNFnLN5cVMiTq1We4WIm8781BORyWQERcVjGOrDatD5dJgtIDwG/5BwDMMagmNTpxU+ttts6Ad70A/2giQRGBFLWFIWfgHeOQMwICyayPQixnoaP/HILfKpMLrJaqNFo3N42loHdJis5640zIoLZZUyhpVZMaxSxpAeE+yzG5q5xGKxOPqwFRUVkZOTM98mOY1MJkOpVJKamkpzczPt7e3s2bOHtLQ0iouLpxUWttlsNDU1ERAQQG6ucxtIb8NqtdLf309MTIzLcgk9jalRYs62Tjl8+DA6nc4rQqngYSJuw4YN+Pn58e677zqdF6dQKFCr1eTn57vRQtcQ70R16hRBkZMizjg24NMiTiaTEZqoZLSjlomBLiLTC8/4XEmSMI4OMKHpwm41owgKISwpm4CwqLkz2E0ERsQQkVaAtqeJ0Y5aorLKvFbI6YxWmjXjDtHWcXwC2zlaqchkUJwcwUplDKuyYlihjCYh3DtFuSczJeBGR0fJz8/3iuvn2fD396e0tNSRL6dSqejv7ycvL4/c3Fz8zuKV7+jowGg0Ulpa6rOD7qfo7+/HZrP5rBcOPg2lOivi3nvvPQAuuOACl9vkDjxKxEVFRbF+/Xq2b9+OwWCYdlKtn58fCQkJ9PX1YTKZCAz0nMrD03FqOHU6OYCK4DD8AoIxjg4SluS7OQwwWakaEB6NaWwQS5zutHlhFr2W8f52rAYdMj8F4Sk5BEUn+dTrEhQZB1IBWlXzpJBTlqII8nz3/pDu0yKEZrWWnpFz9/4L8JOzOD2SlZ942pZnRhMR5Ns30vnGbDY7BFxubi6FhWfeMHkb4eHhrF69Go1GQ11dHU1NTXR1dVFaWkpycvJnrhMWi4Vjx44RHByMUqmcH6PnEJVKhUwmIyXFNzsezGaU2LZt24iMjGTt2rVuss61eJSIA7j00kvZtWsXH374IV/+8penfVxSUhJ9fX2o1WqPLws/sbDBap8cvRUaePa3YiqkOjHQjXl8mMAI56ptvI2wRCXD4yPo1J1EZ5U6fm6zmJjQdGIcPQ7ICI5NITQhA7mfx32UXUJQVDzIZGh7mhnpqCU6a/4aE58OSZLoHzM6qkab1eMMjJvOeVxYoIJlmdGT+WzKGBanRxHk7z25i96OyWSioqKCsbEx8vPzKSws9KkN0BSJiYnEx8fT0dFBU1MTBw8eJDY2lrKyMiIjIx3Pa2lpwWKxUFpaelZvnS9gMBgYGBggMTHR4x0eM2VqlJizRRt9fX1UVVVxzTXXeI031uPufJdeein/8z//w7Zt25wScYmJiQBeIeIiPxm9NdWYdNRgOaeIAwiKTpzseTas9nkRpwgKJTAyHtPYccy6UfxDItAP9qIf7EGy2wkIiyYsOQtFoOd7pmbLVEPisZ4mRj7xyM1X1ardLtE1rD+pclQ7jbzO2NAAh5etPCuGwqRwFKJ6dF4wGo2OIobCwkIKCgrm2yS3IpfLycnJIS0tjaamJjo7O9m1axeZmZkUFRUhSRLt7e2Eh4f79HSGKbq6JhuK+7LHsb+/H3A+lPrWW28BcNlll7ncJnfhcSIuLy+PwsJC3nrrLex2+7S7SAcEBBAbG8vx48ex2WwevZuSy2XEhQWi1k72uhozWEiNOnfo2M8/kIDwGMzjw9jMRq9N3J8uYYmZmLSDaHtbkCQJyWrGLyCYsOQsAsM9u/2BqwmMiCUyo5ix7kZGO2qJSCsgMML9r4HZaqf9uM7haTum0WGw2M55XFp08KdFCFkxZMeF+qSnx9vQarVUVlai1+spKSnx+QT+EwkMDGTx4sUolUpqa2vp6upy9Emz2WwUFRX5/GfUbrfT1dVFcHCww/Hhi6jVahQKhdP94d58800UCgWf//zn3WSZ6/E4EQeTKvgXv/gFhw4dYuXKldM+LikpiaGhIQYHBz3+AxoXHvCpiJtmcQNAcEwS5vFhDCMawhI92+M4W+w2K3JFAHaLCWQywpKyCI5JRuaj42HORWB4NFHKEsa6GxnrbiA0UUlIXKpLbzx6s5VjGh3Nai2N/eO0D+qw2M49yio/MYxVWTGOQoTkSO8swvBl+vv7OXToEHa7nSVLlnh8xMJdTOU79ff3U1NTw+joKHK53OcFHIBGo8FoNPps+BwmPc2jo6NOjxKbmJhg+/btjjm93oJHi7ht27Y5LeLq6+tRq9WeL+KcbPg7RUBYNHL/QIwjakIT0pHJfE/Q2K0WdJoujCOT1UXI5I6cwIUq4KYICI0kJmcJo10NTGg6sRoniEjNRSafmef5xPFVTf1auob1nxlfdSoKuYyS1EjKPxFtKzKjiQ717Z5a3owkSbS0tNDY2OhoYOqrw86ni0wmIzk5mebmZsfc7crKShISEigtLXU6Gd5b6OzsRCaTeVUfQGfRaDSA86HU7du3YzQaufTSS91hltvwSBE3dZF58803eeihh6Z9XFhYGKGhoajVahYtWuTRO414J0ZvnYhMJiM4JokJTRcm7fBkBaOPIEl2DEP9TAx0I9lt+IdEEJacjc1sRNvThE7dSUSad7dAcAV+AUFEZy9CqzqGaew4I2YDkRlF55wHe/L4qknhdq7xVQBB/nKWZUQ7vGxLM6IICfDIS4fgFKxWK0eOHKG3t5eIiAivaWA6F3R2dqLVasnNzSU7O5uGhgZUKhU7d+4kKyuLwsJCr0lunw46nY6BgQGSk5M9cpyaq1Cr1chkMqenNLz55psAQsS5Aj8/P770pS/x4osv0tXV5ZTbPzk5mdbWVsbGxjzaJRrn5NSGEwmeKnAY6vMZEWcaH0an7sBmMiD3DyQ8NY/AiFhkMhmKoFD8Q6Mwjg4QHJOEf4jnN3R2N3I/BZEZRUwMdKM/3sNIWw2RGUUn9RCcGl/VeMKg+OmMr4oM9mflJ1WjK7NiKE2JJECxsD2g3ojBYKCyspKxsTGSk5NZtmyZT88CdQaTyURjYyNBQUGOGanLly8nKyuL2tpa2tvbUalUjhmtnuwQmC6dnZ0AZGVlza8hbsRqtXL8+HFiY2Odmrhht9t58803KS4u9rpm1x77jb7ssst48cUXefPNN7njjjumfVxSUhKtra309vZ6toibQcPfKeSKAIIi4zGODmAxnL6PmrdgNenR9Xdg1o2ATE5oQsZkntcJ4UGZTEZ4SjbDrdWM97URnbPEJy6qs0UmkxGWmIkiKAStqoXBtqMMBafTMaGYFG0aLROmcxchJEUEfTIF4eTxVQLvZXh4mAMHDmAymSgoKKCgoEB8Z06goaEBi8XC4sWLTxK2MTExbNiwgZ6eHhoaGqipqXGM8PLmELTVaqWrq4vw8HCv/jvOxcDAADabzelQ6oEDBxgYGOCmm25yk2Xuw2NF3CWXXEJAQIDTIi4mJobg4GB6e3spLi722AuXs/NTTyU4Jhnj6ACG4X78U/NcadqcYLdZP/Em9gMSgZHxhCUpzxgSVASGEBKbin5QhWG4n5BY32xS6QxGi43WAR1NaiONfeG0Dkxgtved87jsuNCT2n2kRYvxVb6CJEl0d3dz9OhRZDIZK1eu9NmGrjNleHiY7u5u4uLiTvvaTOWMJScn09LSQltbGx9//DEpKSmUlJR4ZThapVJhtVrJysry6e96T08PgNOfeW8NpYIHi7iwsDAuuOACPvzwQ7Ra7bRnospkMtLS0mhpaWFoaMhjdx3Ozk89Ff+QcBTBYRhHjxOWqESu8I7cDUmSMI5o0Gm6kGwWFMFhhCdnTytEGhKf7hizFRge4/MtVk5FZ7TSpJlsqDvd8VVyGRSdML5qpTLmpA2EwHcwGo3U1NSgVqsJDg6mvLz8pIa2gsn5qEeOHEEmk50zb9rf35/i4mLHCK+pZvK5ubnk5eV5TWh6qg+eQqHw6T54ZrOZgYEB4uPjnc7527ZtG/Hx8ZSXl7vJOvfh0Z/Cyy67jHfffZf33nuPq666atrHTYk4lUrlsSLu1MKG6YzeOpWQ2BS0qmMYhvsJTfD8aiPzxBi6/nasxgnkCn/CUvMIikqY9t8t9/MjPDWXsa4GtL2tRClLfHpXObPxVTLyYgNJ8deTEyFxybJclpQUOlVqL/AuJEmit7eXo0ePYrFYSE1NpayszGe78c+G5uZmR5Pj6VaghoaGsmrVKo4fP05dXR3Hjh2ju7ub4uJi0tLSPP4aNDAwwPj4ONnZ2V4jPGdCX18fdrvd6XmwHR0d1NXVceONN3p0f9kz4dHv6Je//GW+/e1v8+9//9spERcREUFERAR9fX2UlZV55BtzojfEapeYMNsIm8bUhhMJjIxDrulCP9T3mTwyT8JmNqJTd2LSDoJMRkhcGiHxaTMalRUYHkNQVCLGUQ3GEQ3BMc7lPngqsx1fNdXuY1FaJEH+foyMjFBdXU1PewvaoQGWLVs2bW+2wHs40fsWEBAgwqdnYWRkhJaWFiIjI8nLcz4FJT4+no0bN9LV1UVTUxOHDx925MtFR0e7wWLX0NLSgkwm87qEfWdRqVTI5XKSk5OdOu7f//434J2hVPBwEZeens7atWt5/fXXGR8fd6p3T3p6OvX19Wg0Go+8qEUG++PvJ3M0Uh0zWJwWcTKZnJC4VHT97RiG1YTEpbrD1Bkj2W1MHFehH+wFyU5gRCyhiUoUgbMrbw9LzsKsG0Gn7iAgLMorw6qzGV91YlPdM42vio6OZuPGjTQ3N9Pa2squXbsoKCggLy9PeOV8AOF9cw6bzcbhw4eRyWQsW7Zsxt8BuVxOVlYWqampNDc309HRwe7du0lPT6eoqMjjWncMDQ0xNDREenq6V+byTRe9Xs/Q0BCpqalOt4XZsmULERERXjWl4UQ8WsQBXHfddXz88ce8/vrr/Pd///e0j0tNTaW+vh6VSuWRIk4mkxEbesLoLb15WqO3TmWy3UgP+sFej5lmIEkSprHj6NSd2K1m/AJDCE/OJiAsyiXry/0UhKfmMdZV7zVh1RPHVzWqtbRMc3xVekzwpGD7pBDBmfFVfn5+FBcXk5ycTHV1NU1NTfT39wuvnJdjNBo5evQo/f39wvs2TZqamtDpdBQWFrrksx8QEEBZWRmZmZnU1dXR09NDX18f+fn55OTkeEz0p6WlBWBGnkdvQqVSATgdSm1sbOTw4cPceOONHifAp4vHi7j/+q//4s4772TLli1Oibjg4GDi4uLQaDRYLBaPbNoYH37y/NSZIJP7ERKXwoSmC+PYcYKj53dShUU/znh/O1bDODI/BWHJOQTHJLlcZAWGRxMUnYhxRINxRE1wjHMudHczNb6qSa2lqX+ctuM6rPZzj68qSAxnZVa0S8dXneiVa2lp4aOPPnLcbHw5R8bXkCSJnp4e6uvrMZvNpKSksGjRIuF9OwfDw8O0trbOOIx6NiIiIlizZg0ajYa6ujoaGxvp6uqipKSE5OTked1cjo2NodFoSE5O9tkJFDD5vVCpVAQEBDjd4HfLli0AbN682R2mzQkefwWPjY3lC1/4Am+//TZqtdqp/i9paWkMDg7S19fnkXMCZ1uhOkVwTDL64yr0x1VOFQq4EpvFzISmE+PowKRNscmExme4tWo2LCkLs24UnboT/9CoWYdpZ8Oo3kyzZpym/smctumOrypNjXSER905vup0XrnOzk4KCgrIyMgQIVYPRpIkNBoNjY2NaLVaAgICWLFiBampnpU+4YlYrVaqq6uRy+WzCqOeDZlMRlJSEgkJCbS3t9Pc3MzBgweJi4ujtLR03iqEp7xw+fm+PeVGq9UyPj6OUql06v2VJIktW7aQmprKxo0b3Wihe/F4EQeTKvnNN99k69at3HXXXdM+LiUlhaNHj6JSqTxUxJ3Q8HcWIk7up5gUcoMqTNqhOZ3iINnt6Id60R9XTY7KCo0iPDkbRZD78y/kfgoiUvMY7axD29NMdPaiOQknT42vavykatSbxldFR0dz/vnn09nZybFjx6ipqaG1tZWioiJSUlI8Piy90BgeHqahoYGhoSHkcrmjvYUz3egXMrW1teh0OoqLi92eQjD1/qSlpdHU1ERXVxe7du1CqVRSWFg4px7TiYkJent7iY+P9+im965gKpTqbPuUffv20dnZyT333OMx4e+Z4BUi7tJLLyU8PJyXX37ZKRHn7+9PUlISfX19GAwGj4t5n9Tw18mpDacSEpeCfqgP/XGVY1yVO5EkCfP4MOP9HdgtRvwCgghLyicgPGZOhUBAWBQh8Wnoj6vQaToJT852+TnskoRqxOAoQpjJ+KpVWTGUpkbif5oihLlGLpeTnZ1Neno67e3ttLS0UFVVRVRUFMXFxcTHx8+3iQserVZLY2OjYw5kZmYmBQUFHncN82R6enro7u4mISGB3NzcOTtvUFAQS5YsQalUUltbS2dnJ729vRQUFJCVlTUnXu/W1lbA93PhpkKpISEhTlcIv/zyy4B3h1LBS0RccHAwX/va13jhhRdobm6moKBg2sempaXR19eHSqXyuA90XNjspjaciFwRQHB0IobhfiwTowSEua/k3WqcYLy/HcvEGDK5H2FJSoJjUuatqCI0IRPLhBbDUB8BoZEERsTOaj2r3U7H8YlPe7Q5O74qa7IQIS8hzKPHV/n7+1NQUIBSqeTYsWN0dHSwb98+4uPjKS4u9vkdvCei1+tpampydJ5PTk6mqKjIp3Oa3IFOp6OmpobAwECWLVs2Lx7mqKgo1q1bR19fH/X19dTV1dHZ2UlZWZnTuVvOYDQa6e7uJjo62mP7pLqKwcFBjEYj+fn5Tr3HZrOZ1157jZKSEhYtWuRGC92PV4g4mKxSfeGFF9iyZQs//elPp31cYmIi/v7+9PT0kJub61Hhorhw14RTpwiJS8Uw3M/EQA/+oVEu/1vtVsvkqKzhfgCCohMJS8xErpjf0I5MJiMirYDhtmq0vS3EBIU61Xbk0/FVk5621gEdJqv9nMdNja9a9Ylw89bxVYGBgZSVlZGTk0NjYyMqlYqPPvqIlJQU8vLyhJibA/R6Pe3t7XR0dGC324mLi6O4uNij+495KjabjYMHD2Kz2Vi9evW8Fn7IZDJSU1NJTEykra2NlpYWKioqSExMpLS0lLAw18+9bm1txW63k5eX55XXI2eY2uw4W5X67rvvMjw8zA9+8AOvf428RsRt2rSJ5ORktmzZwk9+8pPpd/mXy0lLS6Ojo4ORkRFiYmLcbOn0OXVqw2zxCwhyVGyadSMEhrvmb5UkO4ZhNRMD3Ug2K/4hEYQlZ+Mf7PoL0EzxCwgkIjWPse5GtKpmorLKkMlO7xmc6fiq4pQIR7uPFT44viokJITly5eTm5tLY2MjfX199PX1ERsbS3Z2NklJSaIAwoVIksTw8DDt7e309U3OvI2MjHSEtL395jJf1NfXo9VqKSgo8BhPlEKhcBQRNTQ0oFKpGBgYIDs7m4KCApd1T9Dr9XR0dBAZGen0EHhvw2Kx0NfXR3R0tNOe6qlQ6rXXXusO0+YUrxFxfn5+XHPNNfz6179m//79rFmzZtrHKpVKOjo66Ozs9CwRF35ydepMRm+dSmhCBsbR40xouggIi571eqbxyaa6NpMeuX8g4Sk5BEbEeeQNJjAiluDYFAxDfUxouglLUgInj69qUmtRTWd8lULOkrQoR7uP5ZnRhAd5XpsadxAZGcnq1asZHR2lvb2d3t5eDh48SHBwMFlZWWRkZIi2FrPAarXS19dHe3s7Y2NjACQkJJCdnU1CwvxUl/sKfX19dHR0EBcX51TazVwRHBzM8uXLHflybW1t9PT0UFxcTEZGxqzf++bmZux2O8XFxT7/Oerp6cFms6FUKp06bmxsjDfffJMNGzaQkeH54yrPhdeIOJhMQPz1r3/Nyy+/7JSIi4iIICYmht7eXkpLSz2msuvEnDibXWLCZCMsaHZviZ9/ICGxyegHezGNHScoama5F1aTAZ26A/P4MMjkhCZkePRorylCEzJRHR+lor6X7qMTtAyZOa6b3viq5ZnRjnYfU+OrFjJRUVEsW7aM4uJiOjs76ezspKGhgcbGRpKTk8nMzBQeIycYGxujs7MTlUqF1WrFz88PpVJJdna2yHlzAVqtlsOHDxMQEDBveXDTJTY2lo0bN9Ld3U1jYyNHjhxxjPCKjZ1ZTq9Wq6W7u5u4uDifL06SJInOzk78/f2dbrXzr3/9C6PR6PUFDVN4lYhbsmQJRUVFbN26ld/85jdOuaCVSiWHDx+mp6fHY2bInXb01ixFHEBIXBqGYTU6Tdek18yJEJjdZkV/vAf9UB9IEoGRcYQlKj12tNXU+KrG/k/Co5qp8VV+wPgZj4sLC2Cl8tPxVUXJEfh5cBHCfBIUFERhYSF5eXn09/fT1dXlCLWGhISQkZHhaCjqyTfO+cBgMKBWq+nu7mZ0dBSY3FRmZmaSlpbmMRtKb8dkMlFZWYndbmf16tVeUcU7VXWckpLCsWPHaG9vZ+/evaSmplJcXOz0mKzGxkaABeGFGx4eZnx8nOzsbKfbg2zZsoWAgACuvPJKN1k3t3iViJPJZGzevJn777+f//znP1x++eXTPjYlJcVR7p2dne0RH3KZTEZcWKCjx9iYwUxq9OwvPnKFPyHxaUxoujCMqAmJPfdIHkmSMI5o0Gm6kGwWFEGhhCVnExA6P40qz8TU+KrGT0KjMxlftSorhiwnxlcJJvHz8yMtLY20tDR0Oh1dXV309PTQ1NREU1MTISEhJCUlkZSURGxs7ILMn5MkibGxMdRqNWq12hEu9fPzIyMjg8zMTKKjZ5/mIPgUu91OVVUVer2exYsXe0we3HTx9/enpKSEzMxM6uvr6e3tpb+/n7y8PHJzc6c1VWV4eBi1Wk1ycvKCKIbp7OwEcDqU2t3dzY4dO7j88st95nXyKhEHcP311/PAAw/wxz/+0SkRN3URbWtrY3Bw0GPczSeKOFdUqE4REpuCYWiyUjUoKgG535nfavPEGLr+dqzGCWR+/oSn5hIUlegRN5rJ8VWf5LM5Ob6qKM6fSPNxlmVEcumF6xekqHAXYWFhlJSUUFRUxODgoEO0tLe3097ejkKhIDEx0dHJ3pc9Tjab7aTXwGic/D77+/uTlpbmeA08cfSfL1BbW8vg4CBZWVlO39Q9ibCwMMrLyxkYGKCuro7m5mbHCK/U1NQzXo8lSaKhoQGZTEZRUdEcWz33mEwmR8GVs2kIf/7zn5EkiVtuucVN1s09XifiUlNT+fKXv8y2bdvo7Ox06kurVCppa2ujo6PDY0TcSQ1/XSjiZHI/QhPSGe9rwzDUR2jCZxM4bWYjOk0nprFBkMkIiUslJD79rILP3YzqzY6q0ZmMr5qsHI0mKmRSNNTV1dHW1kZNTQ1LlizxCGHqS8jlchISEkhISKCsrAytVusQM729vfT29iKTyYiNjSUxMZHo6GgiIyO9emar3W5Hq9UyOjrKwMAAAwMD2GyT3uDQ0FBycnJISkoiJiZGbBzczFTB2tSIK18gISHBMVWlqamJQ4cO0dHRQWlp6Wm9RwMDAwwNDZGZmbkgciu7urqw2+1OC3aLxcKf//xnMjIy+PznP+8e4+YBr7yS3nbbbbzxxhs8++yz/OxnP5v2cWFhYSQkJKBWqz1mgoOr5qeejqDoRPSDvegHewmOSXbMMZXsNiaOq9AP9oJkJyA8hrCkrDmfPSpJEgPjpk+mIEx/fFWwvx/LMqMc4dElZxlfVVxczPj4ON3d3URERHhMPqQvIpPJiIyMJDIykoKCAoxGI2q1Go1Gw8DAAIODg47nhoeHExkZSVRUFFFRUR4r7E4UbGNjY4yOjqLVarHbP+0jOCVQk5KSFsRN1FMYHByktraWkJAQVq5c6VOCeWqqytQIr87OTnbv3k1GRgZFRUUEBU3mKE954eRyuUdW47oau91OZ2cngYGBpKScO03oRN566y36+/t56KGHvHrM1ql43lVzGlxyySUolUr+8pe/8OCDDzoVpsjKymJgYICOjg6Ki4vdaOX0OGl+6ixHb52KTCYnNFGJtqeJiePdhCVlYxobRKfpxG4x4RcYQlhSFoHhc5MbMNPxVVEh/qzIjGHVJ+0+nBlfJZfLWbFiBR999BF1dXUEBwc7/eUXzIygoCCUSiVKpRKr1crw8PBJYkilUjnmHsLkJmtK1IWGhhIYGEhQUBCBgYFuvUFLkoTZbMZoNGI0GjEYDIyOjjI6Osr4+PhJgi0wMJC4uDiHnTExMaLdyjyg1Wo5cOAAcrmc8vJynw3XBwQEsGjRIkdLku7ubvr6+sjPzyc7O5u+vj60Wi25ubke4ZRwN1MOmIKCAqevCX/84x/x8/PjpptucpN184NXiji5XM6tt97KfffdxxtvvOFUlUliYiIhISF0dXVRUFAw74rcXeHUKQIjYlEEh2EY6scyof0k701BWHI2wTFJZ2yI6wqsNjsdgxOO0GizZnza46tWZcVMjrBywfgqf39/1qxZw549ezh06BABAQFel/zs7SgUCkfYdQqz2XySqDudsJviREEXFBTkeAQEBCCXy5HJZI7/Wq1WYDLMZLfbkSTJIdRMJpNDrE09TCYT0mli9oGBgY4B4lNew6CgIBGSn2f0ej0VFRVYrVZWr17t9sH2nkBERATnnXcearWa+vp6Ghoa6OzsxGKx4O/v73EjJd1FR0cHMpnM6VBqe3s77733Hl/96ld9bhPvlSIO4KabbuKBBx7gD3/4g1MiTiaTkZWV5agCmu9mf66cn3o67FYLcr/JXarVOEFQdNIno7Jcn2R94viqxv7J8VVm2zTGV8WHsuqEdh/uGF8VGhrK6tWr+fjjj6msrGTdunVERnpW5e1CIyAg4LTCbmxsDIPBcJLImvr3qZ6xs1FRUXHG38lkMocgnBJnUyIxODiYiIiIBeHZ8DbMZjMVFRUYjUaWL1/u1hmknoZMJiM5OZmEhATa29tpbGxEkiTCwsIwGo0+642cQqvVMjg4SGpqqiOcPF3+9Kc/AfCtb33LHabNK14r4hITE/na177G1q1baWpqorCwcNrHZmRk0NTURHt7O+np6fO6s3aXiJPsdvRDfeiP9yDZbcgVAditZgJCI1wm4KbGVzX1T3raOgf1Hj2+KioqilWrVrF//34qKirYsGGD072YBO4lICDgrEVHkiRhtVoxGAyYTCbMZvNJ3ja73U5zczMAhYWFDu+cTCbD39//JA+e8Kh5F1arlf3796PT6SgtLXV6Xqav4OfnR2JiIo2NjQQEBKDT6di1axdKpZLCwkKfFXMdHR0AZGdnO3Wc0WjkL3/5Czk5OVx00UXuMG1e8VoRB3DHHXewdetWnn76aZ588slpHxcQEEB6ejqdnZ3z3m7k1HDqbEdvSZKEeXx4clSW2YjcP4iItHwUweEMtx5Gp+4kIDxmRhWon46vmsxpc3Z81aqsWJZlRM3r+Kr4+HiWLVtGVVUV+/btY/369SKnyYuYEmNny4Oduth7c7sJwclM9YIbGRkhLy9vQRcoSZJEbW0tkiSxevVqYLIKv6OjA5VKRWFhIUql0qcKPYxGI93d3URFRTnd323r1q0MDg5y3333+dRrMoVXi7i1a9eyePFiXnjhBX72s585lRuRm5tLZ2cnLS0t8yviXDh6y2qcYLy/A8vE6GSLkUQlIbEpjokNYYlKxvtamRjoJjz57LsZSZLoHzPSqNbS3D/Z8sPZ8VWrsmIoS/W88VWpqamYTCZqa2vZv38/5513nujhJRB4KJIkceTIETQaDenp6QuiF9rZ6O3tZXBw0NE4GmDdunX09vZSX1/vaGpfWlrqM+Hm9vZ27HY7eXl5Tjk5JEniySefJCQkhBtvvNGNFs4fXi3iZDIZ3/3ud7nlllt46aWXuOOOO6Z9bGhoKGlpaahUKkZGRuate3NEsIIAP7kjd2zUYHZaxNmtFiYGujEM9wMQFJVAaKISP/+T3epB0YkYRtQYhvoIjk5EERTq+J3NLtE1NOGoGv10fNXZmRpfNTVz1FvGV2VnZ2MymTh27BiVlZWsXr3aI1tcCAQLGUmSOHr0KD09PSQmJi74Xo8Wi4X6+nr8/f1PErMymczRWLq1tZWWlhYqKipISkqipKSEsLCwebR6dlgsFjo6OggLCyM5OdmpYysrKzl06BDf+ta3iIqKco+B84zX37WuueYafvCDH/DUU0/xne98x6kveF5eHiqVipaWFlatWuVGK8/M5OitAPoco7cspE1TT0qShGFYzcRAF5LNiiI4nPDkbPxDTt+rSiaTEZ6cw0h7DcOqNgZDMmnW6JwaX5URE/KJaJts9+HN46sKCwux2Wy0tbVRWVlJeXm5EHICgYcwFTbs7OwkPj7e53rBzYRjx45hNBpZvHjxadNAFAoFhYWFZGRk0NDQQG9vLwMDA2RnZ5Ofn++VEYeOjg6sViu5ublO32ueeuopAKccPN6G19+xQkJCuPnmm/nlL3/J9u3bufjii6d9bEREBImJifT39zM+Pj5vjTrjwgNPEnHTwawbZby/HZtJj1wRQHhaPoGR8Wf8kJ84vqq+K4iO0QlsUuM5z1OYFD45KP6Tdh9Jkc5VBXkyMpmMkpIS7HY7HR0dQsgJBB6CJEmOPK+4uDhWrVo17+2g5hutVktbWxuRkZFkZmae9bkhISGsWLGCrKwsamtraW1tpaenh6KiIjIyMrxm422z2Whvbyc4OJj09HSnjlWr1bz22mucf/75PjPN43T4xN3q29/+Nr/61a944oknnBJxAPn5+Wg0GlpaWli2bJmbLDw7zjT8tZoM6NQdmMeHQSYnJD6d0Pg0ZPKTL3DnHl/12S+xQi6jLC3S0e7jxPFVvopMJqOsrAxJkujs7BRCTiCYZ6Y8cB0dHcTGxorvIycXMyxevHjaIiw2NpaNGzfS3d1NY2MjR44coaOjg0WLFhETE+Nmq2dPV1cXJpOJ0tJSp72wzzzzDBaLhe9+97tuss4z8IlvRlZWFldeeSV///vfOXLkCEuWLJn2sTExMcTGxjqqeuaj5UT8NNqM2G1W9MdV6Id6QZIIjIgjLEmJX0AQkiSh0Rod46sa+8dRa889vipALlEYH8QFZRnnHF/ly8hkMhYtWoRMJqOjo4P9+/eLHDmBYB6YyoGbmocqBNwkXV1dnylmmC4ymYzMzExSUlI4duwYbW1t7Nmzh9TUVEpKSjy2H6Ldbqe1tZWAgIBzeh5PZXx8nCeffJLc3Fwuv/xyN1noGfjMt+Pee+/l73//O48++iivvvqqU8fm5eWxf/9+WltbWbRokZssPDNx4WeenypJEsbRASY0nditFhRBoYQkZTFgDqCyddTRo21kGiO7Th1fpe2qZ3R4iDWLokhIWNgTDKY8cjKZjPb2dioqKnx6nI9A4GnY7XZqamro7u4mPj6eVatWCQHH5ISKuro6goKCKCkpmfE6/v7+lJSUkJmZSV1dHb29vajVakfLFk97rXt7ezEYDBQWFjpt2x//+EdGR0d5/PHHfT4ML5NON2/GS/nCF77A+++/T3NzM7m5udM+TpIkPvroI3Q6HRdffPGc9w17/uMOfvJmAwBL0qP4389PNi626LWM97djnNChMihQ2aNpHZM4NjC98VXJkUGOfLbyrBhy408eX6XX69mxYwcBAQFs2rTJK5NeXc3UQOnW1lbCw8NZs2aNx+5UBadnx44dAFxwwQXzbIlgulitVg4dOoRarSYhIUHkwH2CJElUVFRw/Phx1qxZ49KWIRqNhrq6OnQ6HcHBwZSUlJCSkuIR+XKSJLFz5070ej2XXHKJU5tpk8lEVlaWY0Pu631APUt6z5J7772Xd999l1/84heOMRvTQSaTkZeXR1VVFe3t7XPeh+jUhr8Tej11x9pp7NfSrpXRqVNgsQOMnHWdqfFVU+0+zjW+KiQkhNLSUmpqaqivr3cqDO2rTBU7BAYGUl9fz549e1izZs28Fb0IBL6O2WymsrKS4eFh0tLSWLp06YKvQp2iq6uL48ePk5GR4fKeb4mJicTHx9PR0UFzczNVVVXExMRQVlY27+041Go14+Pj5ObmOh0NefHFF+nv7+dXv/qVzws48DFPnCRJrFu3jqqqKjo6OpwadCtJEh9++CEmk4lLLrlkTr1S+9uHuPpP+4HJsVQgYZfOvhuaGl+1ShnLqqxoVihjTiqQmC7u3Ol5Oz09PVRXV6NQKFi9erVXJAILhCfOmzAYDFRUVDhu2MXFxR7hCfIEpiIl/v7+XHDBBW69J5lMJpqamujs7AQgMzOToqKieRFBkiSxe/dutFotF198sVNzUq1WK4WFhYyMjNDV1eXV/fGmi09td2QyGffeey9ms5lf//rXTh+bl5eH1Wp1fJDnirjQT3cadonTCrgAhZxVWTHcsSmXF29aRc2PL+Gt767ngUuL+Xxp8owEHEz+3UuWLEGhUFBdXY3F4rr5rd5Oeno65eXl2O129u3bh0ajmW+TBAKfYXx8nD179jA+Pk5JSQklJSVCwH2CJElUV1djs9lYunSp250KgYGBLF68mPPPP5+4uDi6urrYvn07ra2t2O12t577VAYHBxkdHSUjI8PpQff/+Mc/aGtr47vf/e6CEHDgY544wFGC3d7eTldXF7GxsdM+1m63s337dqxWKxdffPGceONGR0c5XFPLd94fw2D79AIWHqhguTLaMQ1hUVokgQr35Yh0dnZSU1NDRkYGS5cuddt5vJHh4WEqKyuxWCwsXrzY6UopwdwiPHGez/DwMPv378dqtbJ06VKne4D5OlPX48zMzDlPc5Ekif7+furr69Hr9YSGhlJaWkpiYqLbRfaUF25sbIwLL7yQ0NDQcx90wrFLliyhra3N6Xu/N+NTOXEw6Vn6v//7P6677jqeeuopfvzjH0/7WLlcTmFhIdXV1bS0tFBcXOw2O00mE42NjXR1dQHwwKZkGsaDyE4In5fxVZmZmfT19dHd3U1KSgqJiYlzdm5PJyYmhnXr1lFRUcGRI0fQ6XQi7CMQzJDu7m5qamqQyWSUl5eLa80pTFWjThUbzDUymcxxD2hra3OMJkxISKC0tNSt+cH9/f2Mjo6SlZXllIAD+M9//sPRo0f5/ve/v2AEHPigJw4m4+IFBQWMjo46HRc/sSrmoosuctqdey7sdjvt7e00NzdjtVqJi4ujtLSUyMhIl55nJuj1enbu3IlCoWDTpk2ivcYpGI1GDh48yPDwMAkJCaxYsUJU9HogwhPnmdjtdhoaGmhrayM4OJjy8nKPuO55EpIksW/fPgYHBz0mR9lgMNDY2EhPTw8ymYysrCwKCgpcfn+w2+3s3LkTg8Ewo3vvunXrOHDgAO3t7aSlpbnUNk/Gp3LiplAoFPzgBz9geHiYZ5991qljZTIZxcXF2Gw2mpubXWqXRqNhx44d1NfXExAQwMqVKznvvPM85kI2Va1qNBqprq7GB/X9rAgKCuK8884jIyODgYEBdu/ejU6nm2+zBAKPx2w2s3//ftra2hxTBDzluudJHDt2jMHBQZRKpUcIOIDg4GCWLVvGhg0biIqKor29nQ8//JCOjg6X5sv19PSg0+nIyclxWsDt2bOHjz/+mG984xsLSsCBj3riYNJrkpWVhZ+fH21tbU5V2UiSxN69exkZGeGCCy6YdYLk+Pg4dXV1DAwM4OfnR35+Pjk5OR7ZB0mSJA4fPoxKpaK0tJScnJz5NsnjkCSJ9vZ26urqUCgUrFy50mMuuALhifM0xsfHqaysZGJigszMTBYtWiRaiJyGoaEh9u7dS0REBBs2bPDY+4NKpaKhoQGj0UhERASlpaXEx8fPal2bzcb27dux2+1cdNFFTkc4vvjFL/Luu+/S1NREfn7+rGzxNnz2mxQUFMTdd99Nb28vf/3rX506dsobJ0kSjY3nHhJ/JsxmM7W1tezcuZOBgQHS0tK48MILyc/P98gvKHw6gio0NJT6+npGRs7em24hIpPJyMnJYc2aNchkMioqKmhtbRWeS4HgFNRqNbt370av11NWVsbixYuFgDsNJpOJqqoq/Pz8WLFihUffH9LT0x33MZ1Ox759+zhw4AATExMzXre9vR2j0Uh+fr7TAq66upp33nmHq666asEJOPBhTxxM7gCVSiWhoaEcO3bMaRft/v370Wg0bNy40anmh5Ik0dXVRWNjI2azmaioKMrKyryqz9jo6Ch79uwhKCiI888/X+R+nQGdTkdlZSU6nY6kpCSWLl0qcgnnGeGJm3/sdjuNjY20trbi7+/PypUrZ+2t8VUkSaKyshKNRsPSpUvJyMiYb5OmzcTEBA0NDfT19SGXy8nJySEvL8+p+4XFYuGDDz5AoVBw4YUXOi1gv/SlL/Gf//yH6urqBdmw3qe3ROHh4dx333309PTwzDPPOH38VHVqQ0PDtI85fvw4u3btclRfTeUSeJOAA4iKiqKkpAS9Xk9NTY3wMp2BsLAwNmzYQFpaGmq1ml27djE8PDzfZgkE84Zer2fv3r20trYSHR3N+eefLwTcWWhra0Oj0ZCenu5VAg4gNDSUlStXsnbtWsLCwmhpaeHDDz+ku7t72veMlpYWLBYLhYWFTgu43bt385///Ierr756QQo48HFPHOBw0U5MTNDe3u50Mu3hw4fp6ek5Z6XQxMQE9fX19Pf3I5fLyc3NJS8vz+OGCjuDJEkcPHiQ/v5+Fi9ejFKpnG+TPBZJkuju7qa2tha73U5hYSF5eXmiDck8IDxx80dfXx9HjhzBYrGQm5tLUVGRCJ+ehZGREfbs2UNoaCgbN270+vuFsxEog8HAhx9+SEhICJs2bXLqeilJEueddx5VVVU0NjY6NS/dl/D5b1dQUBA/+clPGB4e5vHHH3f6+MLCQuRyOQ0NDafdWVitVhoaGtixYwf9/f0kJydzwQUXUFRU5NVfSPh0mkNwcDC1tbVotdr5NsljkclkZGZmsmHDBsLCwmhsbKSiogKTyTTfpgkEbsdms3H06FEOHjyITCZj9erVlJSUCAF3FiwWC1VVVchkMlasWOET9wulUslFF11ETk4OY2Nj7Nmzh0OHDmEwGE57THNzMzabbUZ9N9944w3279/PrbfeumAFHCwATxxMXmAWLVpEZ2cnra2tJCcnO3V8bW0t7e3trFixgtTUVODTKp36+npMJpPLqnQ8keHhYfbu3esTu8W5wGq1UldXR1dXF4GBgSxdulQ0NJ1DhCdubtFqtRw+fJixsTFiY2NZvnw5wcHB822WR7MQohyndmXIy8sjNzfXETIdHx9n586dREdHs27dOqdEnNVqZdGiRXR1ddHW1kZSUpK7/gyPZ0Fsk/z8/Pj5z3+OXq/noYcecvr4/Px8FAoFjY2N2Gw2hoeH2bNnD4cPH0aSJBYtWsTGjRt9UsDB5MSCoqIidDqd6B83DRQKBUuWLGH58uXYbDb2798v5tIKfA673U5zczO7du1ibGyMgoIC1q5dKwTcNGhtbaW/v5+UlBSfHeMXHh7OmjVrWL16NUFBQTQ1NbFjxw76+vqQJMkR3ZqJF+6ll16isbGRu+++e0ELOFggnjiY3PlMdXSeSfy8paWFhoYGIiIi0Gq1bu1c7YlIkkRVVRV9fX0UFhZSUFAw3yZ5BQaDgerqao4fP05QUBBLliwRXjk3Izxx7udE71t4eDhLly4lOjp6vs3yCjQaDfv37yc8PJz169cviMp/u91OR0cHTU1NWK1WwsPDGR8fJzk5mVWrVjm1ltFoJC8vD4PBQFtb24JvGr0gPHEwGa9/9NFHsVqt/OhHP3LqWJvN5uhMrdVqiY2NZdOmTZSVlS0IAQeTr9/SpUuJiIigqamJvr6++TbJKwgODmbNmjUsWbIEq9UqvHICr8Zut3Ps2DE++ugjxsbGyMvLY+PGjULATZPx8XGqqqrw9/envLx8QQg4wNF+5KKLLiIjI4Px8XFgMkrmbN7w008/jUql4r777lvwAg4WkCduii9/+cu8/fbbHDp0iGXLlp31uZIk0d/fT319PXq9nqCgIIxGI0lJSZSXl8+RxZ6FXq/no48+wmazsX79evElcgK9Xs+RI0eEV87NCE+ce9BqtVRXVzM6OkpYWBjLli0T4s0JzGazo/HxmjVrfDb95lw0NzfT1NRESEgIer0ehUJBYWEhWVlZ5yyEGRsbIzs7e8a9X32RBeOJm+KRRx5BJpNx7733nvV5Y2Nj7Nu3j4MHD2I2mykpKeHiiy8mJSUFtVqNRqOZI4s9i5CQEFatWoXdbqeyslJUXzpBSEgIa9asYfHixQ6v3IEDB9Dr9fNtmkBwRiwWC3V1dezatYvR0VFyc3M5//zzhYBzArvdTlVVFRMTE5SVlS1YAafX62lpaSE0NJQLLriAlStX4u/vT11dHTt37jznffUXv/gFw8PD/PSnPxUC7hMWnCcO4Bvf+AZ//etf+fDDDz+zWzeZTDQ1NdHZ2QlAZmYmRUVFjtmrU31tgoKC2LRpk8eOR3E3XV1dHDlyhNjYWM477zzRSsBJDAYDdXV19PX1efw8XW9DeOJcw6kV+FFRUSxevNip6TWCSaY6HCiVShYtWrRg+0ceOHCA/v7+k/qu2mw2WltbaWlpwWazkZiYSElJCeHh4Scd29/fT05ODtnZ2dTU1Ihr5ScsSBHX2dlJfn4+S5YsobKyEplM5ki8bG5uxmKxEBsbS2lp6WkvWMeOHaOxsXHBJ/gfPXqUjo4OlEolixcvnm9zvJKBgQFqa2vR6XSEhoZSVlYmQqyzRIi42aPVajl69ChDQ0MEBARQXFxMRkbGghUfs0FseCcZGBigoqLijMUMBoOBhoYGVCoVMpmM7OxsCgoKHHmDt99+O3/4wx944403uOyyy+bafI9lQYo4gO9973v89re/5aWXXuKSSy6hrq4OnU5HcHAwJSUlpKSknPGCZbfb2blzJwaDgQsuuICQkJA5tt4zsNvtVFRUMDg4yKJFi8jKyppvk7wSu91OW1ubo/FlUlISpaWlhIaGzrdpXokQcTPHYrHQ3NxMe3s7kiShVCopKipaMAVcrmZoaIiPP/6YoKAgNm7c6IjoLDRsNhs7d+7EaDSe8545PDxMbW0to6OjBAQEUFRUxNjYGMuXL6e8vJy9e/eKzcQJLFgRNzIyQkFBATabjSeffJKIiIjPNCM8G+faVSwUTkzWLS8vF16kWXBiiFUul6NUKsnPz1+wF/6ZIkSc89hsNjo6Ojh27BgWi4Xo6GgWLVokQqezQKfTsWfPHlEExqfRq6KiIvLz88/5fEmS6OnpoaGhAaPRyAMPPEBdXR0HDx5k+fLlc2Cx97Aw/bpAdHQ0jz32GMPDw7z11ltceOGFFBQUTDvOnpCQQHJyMv39/Qu2yAEgICCA8vJyFAoFBw8eFMPfZ0FwcDArV67kvPPOIyIigvb2drZv305zczNWq3W+zRP4IHa7na6uLrZv3059fT0KhYKlS5eyfv16IeBmgcFgoKKiAovFwooVKxa0gNPr9Rw7dozQ0FBycnKmdYxMJiMjI4MLL7yQ5uZmamtrue2224SAOw0L1hMHkxewtWvXcuDAAaqrq1m0aJFTx+v1enbs2LHgixxg0gW+b98+5HI569ev/0xSqsA5ptrbNDQ0MDExQWBgIPn5+SiVygWbUzNdhCfu3Ex9vhobG9HpdAQEBDg+Xwv5OuYKLBYLe/fuRavVsmTJEp+dyDBdTlfMMF2mJoHYbDaam5uJiYlxk5Xey4K+G8jlcp5++mkAvvOd7zg9TiokJIT8/HwmJiZobW11h4leQ0xMDCtXrsRqtVJRUXHGgceC6SGTyUhJSeGCCy5wFI3U1tby4Ycf0t3d7Wg+LRA4gyRJDAwMsGfPHg4ePIjBYCA/P98xtFwIuNlhs9morKxEq9VSVFS04AWcRqOhv7+f5ORkpwUcwIMPPohGo+HRRx8VAu4MuEzEdXZ2IpPJnH68/vrrrjJhRixbtozbbruNvXv38vLLLzt9fE5ODmFhYRw7dgytVusGC72HxMRElixZ4gglmM3m+TbJ65nKjbvooosoKirCbDZTXV3N9u3baW9vF2FWwbSQJIm+vj4++ugjKioqGB0dJSsry/G5WiiTA9yJJEkcOnSIoaEhsrOzycvLm2+T5hWLxeJoBVJaWur08bW1tTz55JMA3HLLLU5rhrq6us/oje3btztth6fjs564Bx980PHGTfV8OxMPP/wwcXFx/OAHP2BsbMyp8/j5+bF06VLsdjuHDx9e8B6SjIwMSkpKGB8fp7KyEpvNNt8m+QQKhYL8/HwuueQSioqKsNls1NbW8sEHHzja4ggEpzKV8/bhhx9y8OBBdDqdQ7wtWrRINEx1EZIkUVNTQ39/P6mpqZSWli74Csr6+noMBgMlJSVOd3CQJInvfOc7p72fPv/889Na4y9/+YtT5/RWFO5YdMWKFdN+oT3B3TxV5HDzzTfz4IMP8sQTTzh1fExMDLm5uY6GhQu5dxxAbm4uRqORtrY2qqqqWLlypcjjchH+/v7k5+eTnZ1Nd3c3ra2tNDU10drailKpJCcnR9yYBVitVrq6umhtbcVoNKJQKMjLyyMnJ0dUO7uB5uZmurq6iI+PZ9myZQtewA0MDNDV1UVcXBxKpdLp41955RX27NnD5s2bHRGy4OBgDAYD//nPf9BoNGfthGCxWNiyZctJx/kqbhFxoaGhM3Kfzic33HADzz77LE8++SQ33XQTZWVlTh1fWFiIRqOhubmZ5ORkIiIi3GSpd1BSUoLJZEKlUlFTU8OSJUsW/IXNlSgUCrKzs1EqlahUKlpaWmhtbaWtrY3U1FSysrKIjo4Wr/kCQ6fT0dnZSVdXF1arlcDAQIqLi1EqlSJk6iammsRHRkaKDSuTAqq6utoRpXL2GqTVarnnnnuIjY3lf/7nfxwi7pJLLmH79u1MTEzw17/+lXvuueeMa7z55pscP34cgK985Su88sorM/+DPJyF/Wk7gakiB7vdPqMih6kPrCRJIqzKZGL+0qVLSUhIoLu7m7q6OqdfU8G5kcvlZGRkcMEFF7Bq1SpiY2NRqVTs2bOH3bt3O27mAt9FkiTUajX79+/nww8/pK2tjeDgYBYtWsTFF19MXl6eEHBuoru7m6NHjxIaGsqaNWvE68xkLprRaKS0tHRGjfAffPBB1Go1jz322EltbsLCwrjqqquAc4dUn3vuOQDWr1/v87mJHifipvLYbrjhBmByZMndd99NQUEBISEhREVFsWbNGp555pnT3pxeeOEFZDIZP/nJTxw/y8rK+kyC49T6J7Js2TJuv/129uzZ43DFOkN0dDR5eXmMjY3R0tLi9PG+hlwuZ+XKlcTGxtLe3k59fb0Qcm5CJpORnJzM2rVr2bRpE0qlkvHxcY4cOcJ7773H0aNHF3zhja9hMBhobm7mgw8+oLKyEo1GQ1JSEueddx6bNm0iKytLVJu6kZ6eHqqrqwkODua8884TYWomq1G7u7uJj4+fUapUbW0tv/vd7ygvL+fGG2/8zO+nftbQ0EBlZeVp1+jv7+fdd9896fnTYXh4mJ///OesX7+exMREAgICiIuLY926dTz22GPnvH6qVCqefPJJrrzySgoKCggLC8Pf35/4+HjWr1/Pww8/zNDQ0LTtmS5uCae6iv/85z9ce+21JxUbGAwG9u/fz/79+3njjTd46623XLr7efjhh3nttde45557uPTSS51u0lhQUIBaraa5uZmkpKQF3eQRJsN+q1evpqKigra2NmQyGcXFxSLM50YiIiJYvHgxxcXF9PT00NnZSUdHBx0dHURGRpKenk5qaqrInfNCLBYL/f39qFQqR7goKCiIgoICMjMzCQ4OnmcLFwYqlYrDhw8TFBTE2rVrF+zoxROxWCwcOXIEhUIxo/QZSZK44447sNvtPP3006cNS2/YsMGRf/78889TXl7+mee89NJL2Gw2wsLC+K//+i8ef/zxc55769at3HrrrZ8RalNj0z7++GOeeOIJ/vnPf7J27drPHD88PExGRsZpnRSDg4Ps3buXvXv38sQTT/CPf/yDTZs2ndOm6eJxnrgpamtrueqqqwgJCeHRRx9lz549VFVV8dxzzzlmdL7//vv84he/OOm4K664gtraWm6//XbHz9577z1qa2tPevzsZz877Xmnihw0Gg3/8z//47TdU2FVgOrq6gUfVoVPhVx0dLQjEV945NyPv78/2dnZbNq0iXXr1pGens7ExAR1dXW899577Nu3j+7ublHZ6uHY7XbUajVVVVW89957VFdXMzg4SFJSEitXruTiiy+msLBQCLg5oq+v7yQBJ2YcTzIVRp1JNSrAH//4R3bv3n3OyQxTUbRXX331tAULU6HWq666alrvzUsvvcQ111yDVqslMTGRn/zkJ7z++utUVVXx4Ycfcu+99xIeHo5Go+ELX/gCjY2Nn1nDbrcjk8m44IILePTRR3n77bc5cOAAFRUVbN26leuvvx5/f3+Gh4e54ooraG9vn+arcm5cNrGhs7PTIa6mW5061SX8JINOUO+lpaXs2LGD+Pj4k56jVqspKSlheHiYxMREent7PxM2ePDBBx0h1Y6ODqcqZCRJ4nOf+xwffPAB77zzDp///OenfewUDQ0NtLS0UFhYuOCrVaewWCzs27eP0dFR8vLyKCoqEh65OcZms6FWq1GpVGg0GiRJws/Pj6SkJFJTU4mPj0eh8GgH/TnxhYkNdrudoaEh+vv76e3tdfRcjImJIS0tjdTUVDGUfh7o7e3l0KFDBAQEsG7dOsLCwubbJI9Ao9Gwf/9+4uPjWbNmjdPX9c7OTsrKyoiJiaG2ttZRGHiirrjuuut4+eWXUalUZGZmYrfbefnll7nuuusc6+zbt8/hKdu9ezfr168/SQt88MEHXHTRRY7nd3R0UFJSgsFg4Gtf+xp//etfT7sZam5uZt26dQwODnLRRRfxwQcfnPR7s9lMX1/fWXXGkSNHWLduHRMTE9x88838+c9/duo1OhNuuVpXVVVNq7ozMzPzrD3cXnjhhc8IOICkpCRuvPFGfvWrX6HRaGhsbHRpNaxMJuPPf/4zpaWlfPOb36Surk6EVV2Av78/5513HhUVFbS0tCBJkgitzjF+fn6kpqaSmprquPD09PTQ29tLb28vcrmc+Ph4EhMTSUpKEt6dOcRisaDRaFCr1QwMDDg8pGFhYeTk5JCWlibCdvOISqXi0KFDBAUFcd555wkB9wmzDaPa7XZuvvlmdDod//rXv87Z2SEtLY2LL76Y9957j+eff/4kETdV0JCXl8f69evPee5f/vKXGAwG4uPjeeGFF854vSsoKOCBBx7gzjvvZPv27XR0dDjEJUw6pM7lKFqyZAnf/OY3+c1vfsO//vUvnn32WZfc+zx2y11SUnJWl+qJsfC2tjaXtzTJyMjgV7/6Fbfeeit33323040D/fz8WLZsGbt376a6upr169eLJGMmhdyaNWvYv38/ra2tSJJESUmJEHLzwNSFR6lUotfr6e/vR6PRMDAwgEaj4ejRo0RGRpKUlOTYiIj3yXVIkoRer0etVqNWqxkaGnKkGURFRTle94iICPG6zzPd3d1UV1c7QqhCwH1KbW0tRqORJUuWzDiMumPHDm699VYuvvjiaR1z44038t5777Fjxw66urrIzMxkYmKC1157DeC0hYun41//+hcAl1566Tnf0xPz2D7++OOTRNypTI2302q1mEwmx8+nqm1HRkZO8jLOBreIuI0bN7Jr165ZrVFUVHTW38fGxjr+7a6qu1tuuYV//OMfPPfcc1x55ZV84QtfcOr4qKgo8vPzaW5upqGhwenec76Kv78/q1evprKykra2Nmw2G4sWLRI3qnkkJCSEnJwccnJysFgsDAwMoFarHb0Pm5ub8ff3JzY2lri4OOLi4oS4cJIp0TY4OMjQ0BCDg4OOnB65XE5CQgJJSUkkJiYKD6gH0dnZSU1NDcHBwSIH7hR6enro6ekhISGBjIwMp4/v6OjgBz/4ARkZGdMqQJjiiiuuIDo6mpGREV544QV+/OMf849//IPx8XHkcjnXX3/9Odfo7u5GrVYDkx68KS/edOjv7//Mz+x2O1u2bOGll15i//796HS6s64xODjouSLOFZzri3Ji5Yq7RjvJZDKeffbZk8KqJ/atmQ75+fkMDg7S3t5OXFwcycnJbrHV2zhRyHV2dmI2m1m2bJnwVnoA/v7+jpCr3W5neHgYjUbD4OCgw2s09by4uDhiY2OJjY0lIiJiwTc6PRFJkpiYmGBoaOgzog0mw6RKpZKEhASfyEX0NSRJ4tixYzQ1NRESEiKqUE9Bp9NRU1NDUFDQjKZUTIVRJyYmeP31151qkB8YGMi1117L008/zYsvvsgDDzzgEGGXXHIJqamp51xjYGDAKXtPRK/Xn/T/Wq2Wyy67jI8++mjGa8wUcdU4BxkZGTzxxBPccsst3H333U6pdZgUm8uXL2fXrl1UV1cTGRkpLgSfMFW1evjwYfr6+jCbzaxatUo0zPQg5HK5w/MGk/kvw8PDDA4OMjg4SH9/v2NXKpfLiYiIICoqiqioKCIjIxeMsJMkCZ1Ox9jYGKOjo4yOjjI2NnZSL8sp0TYlfEWLF89FkiRqa2sdbXlWr14t3q8TsNlsHDx4EJvNxurVq2fUI+8Pf/gDO3fu5Lbbbjup2GC63HTTTTz99NN0dHTw5z//mT179jh+Ph1O/G7ecMMNTnWjSEhIOOn/7777boeAW7NmDd/+9rdZsWIFKSkphISEODZozz33HDfffDOAyzo0CBE3DW666Sb+8Y9/8Pzzz/O1r32NL33pS04dHxwczNKlS6msrKSqqop169YtiBvbdPDz82PFihWOC+bHH38sLpgejL+/P4mJiY65hRaLhaGhIUZGRhzCZXR01PF8uVxOeHg4kZGRhIaGEhYWRlhYGKGhoV7pdbXb7ej1eiYmJtDpdOh0OsbHxz8j2BQKBZGRkURFRREdHS1Emxdhs9kcG8u4uDixsTwNdXV1aLVaCgsLHRs8Z2hvb+cHP/gBmZmZn2kTNl2WLVvGokWLOHr0KHfeeSeSJBETE8Nll102reNPLJq02+0zzqsfHx93jAZbs2YNe/bsOeO1bXh4eEbnOBs+K+JcmaszFVYtKSnh1ltvpa6ujujoaKfWSEpKIicnh7a2NhobGykpKXGZfd6OTCajrKyMwMBAmpqa2LNnD2vWrBHJw16Av7+/IwEfJneXRqPxJG/U1H9PJTg42CHqgoODCQoKIjAwkKCgIIKCgvD395/znDur1YrRaHQ8TCYTBoPBIdomJiY+s4NWKBQOz+PUf8PCwkS+oBdisVg4cOAAg4ODpKSkiBSP09DX10dnZydxcXGfaRE2Hex2OzfddBN6vZ7nnnuO8PDwGdty00038b3vfQ+j0QhMtiGZrlcwKyuLmJgYhoeH2bt3L5Ikzeg7e+zYMUfxwtVXX33Wz8uBAwecXv9c+KyIOzEx+MTqkJmSlpbGE088wc0338z3v/99XnjhBafXKC4uZmhoiNbWVuLj4z/jkl3IyGQyCgoKCAwMpKamhr1797J69WqncxAF84tMJiM4OJjg4OCT8j/NZrNDBE15sHQ6HcPDw47JA6cil8tPEnR+fn4oFIrPPPz8/JDL5Y4L8FRrjt7eXiRJQpIkrFYrNpsNq9V62seUYDvTnFmZTEZoaCiJiYkOT+KUAA0MDBSCzQcwGo3s37+fsbExsrKyKCsrE+/rKUxMTFBdXU1AQMCM8uAAnnnmGT766CNuv/32WfdyvO666/jRj37k6KPozJgtuVzOFVdcwXPPPUd7ezv//Oc/ufLKK5224cRrxsTExBmf193dzRtvvOH0+ufCZ0VcSkqK49/Nzc0uabh744038o9//IMXX3yRq666yumwqlwuZ8WKFezatYtDhw5x/vnniyq0U1AqlQQGBlJVVcXevXspLy8/ba9AgXcREBBATEwMMTExJ/18ynNnMBgcQupEL5jRaGRiYsIhwpyhqqrqnM+Ry+UoFAoCAwOJjo4+yRN44iM4OFikQPgwOp2OiooK9Ho9hYWF5OfnCwF3Cna7naqqKqxWK2vWrJnRvautrY3//d//RalUzjiMeiJxcXGz6k5x3333sWXLFkwmE7feeiupqamsWbPmjM8fHBzkb3/7G9/97ncdP8vLy0Mul2O323nllVf43ve+95nXZmRkhKuuusohNl2JW0Tc1Gif6RAXF+cIxbiSdevWIZPJkCSJe++9F7vdTm5uriPBMDIy0ulKUZlMxp/+9CdKS0u55ZZbqKmpcdqbFhoaytKlSzl48CCHDx/mvPPOExeLU0hOTmbNmjVUVlZSUVHB0qVLSU9Pn2+zBG7gRM/dubDb7Wf0pk2FOCVJclx7plr6yGSyM3rxhDATjIyMUFlZiclkYsmSJTMa3L4QaGhocEzbmUkUyWq1csMNNzjCqJ6QLpOTk8Nzzz3H5s2bGRkZYf369Vx11VVcdtll5OTkoFAoGB4epq6ujg8//JD333+f+Pj4k0RcTEwMl19+Of/+97+pq6tjzZo1fP/736ewsBCLxUJFRQW//e1v6e3tZcOGDezevdulf8O8TmwAuOuuu/jNb37jchuUSiU33ngjzz33HA0NDXzlK1856ffXX3/9jEKiaWlpPP3002zevJnrr7+et99+2+kbQUpKCkqlks7OTpqbmyksLHTaDl8nLi6O9evXU1FRweHDhxkfHxdjuhY4crkcuVx+ziTz5uZm4GRvvEBwOnp6ejhy5AgymYxVq1aJFlBnQK1W09bWRkxMzIzvVw8++CB79+7lrrvucukA+Nly7bXXEhUVxY033sjAwACvvvoqr7766hmff7rpS7///e9paGigubmZmpqazzQblsvlPPjgg2RmZrpcxPn0NvTZZ5/lj3/8I5s2bXJpH6brrruOG2+8kXfffZdf/epXM1qjtLSUiIgImpubGRwcdIldvkZERAQbN24kOjqalpYWKisrxbB2gUAwayRJor6+nsOHDzvmoAoBd3oMBgPV1dX4+/uzfPnyGXmvt2/fzs9//nOWL1/OY4895gYrZ8cXv/hFOjs7+f3vf8+ll15KWlqaIxc3Pj6e1atXc8cdd/Dmm29y5MiRzxyfmJhIVVUVP/3pT1m8eLEjupCVlcX111/P3r17+fGPf+wW22WSq5qVLDAmJiZYuXIlLS0t7N69+6xx9DOh0+nYtWsXCoWCjRs3ivy4M2Cz2aipqaGnp4ewsDDKy8s9whUv8Ex27NgBMOukaYFvYrFYOHToEBqNhujoaFatWiXav5wBm83Gxx9/zMjIyIw9lWq1miVLlqDX66muriYnJ8cNli5cfNoT505CQ0N57bXXUCgUXH311YyMjDi9RlhYGEuXLsVkMlFZWem2yRPejp+fH0uXLqWkpASdTsfu3bvPWNEoEAgEZ2Lq+qHRaEhPT2ft2rVCwJ0BSZKoqalhZGSE3NzcGQk4u93Of//3f6PRaPjzn/8sBJwbECJuFpSWlvK73/2O7u5ubrrpphl1YE5NTSU/P5+xsTGqq6td1sXZ15DJZOTm5rJ69WokSaKiooL29nbxegkEgmkxMDDA7t270el0lJaWsnTpUtED7iy0t7fT09NDYmIixcXFM1rj0UcfZfv27dx6663813/9l4stFIAQcbPmlltu4eqrr+b111/nqaeemtEahYWFJCUl0dvbS0tLi4st9C0SExPZsGEDISEh1NbWUlNTg91un2+zBAKBhyJJEm1tbVRUVACTXfVzcnJEkdRZGBgYoK6ujrCwMJYvXz6j12rPnj386Ec/orS01C3Fi4JJRE6cC9BqtSxbtoyenh4qKipYtmyZ02tYrVb27NmDVqulvLzcLW1XfAmz2cyhQ4cYGBggOjqaFStWiJm0AkDkxAk+xWKxcPToUVQqlcinnSbj4+Ps3r0bmUzGhg0bZvR6DQ4OsmTJEkZGRqiqqqKoqMgNlgpAeOJcQkREBK+99hoAX//612fUfFChUFBeXk5AQABVVVWzamC4EAgICKC8vJzc3FxGRkbYtWuXYxC7QCAQjI2N8dFHH6FSqUhKSpqxIFlIWCwWR372ypUrZ/R6SZLEjTfeSG9vL88884wQcG5GiDgXsWzZMn75y1/S2trKt771rRnlaoWEhLBy5UrsdjuVlZVu6e7sS8jlckpKSli9ejUymYwDBw5QW1srCkQEggWMJEl0dHSwe/du9Ho9paWlYoj9NJAkiaqqKiYmJigtLZ3xpJzf/OY3vPXWW3zjG9/g+uuvd7GVglMR4VQXIkkSX/3qV3n99dd59tlnueWWW2a0TmdnJzU1NcTFxbFmzRrRVX4aGAwGDh06xNDQEJGRkaxYsULsuhcoIpy6cLFYLFRXV9Pf309ISAgrVqwgOjp6vs3yCurq6mhrayMzM5PFixfPKA/uwIEDrFu3juzsbKqqqsQ1eA4QIs7FDA8Ps3TpUgYGBqioqGDJkiUzWqempobOzk6ysrJYtGiRa430Uex2O83NzRw7dgyFQsHixYtJS0ubb7MEc4wQcQuT4eFhDh06hF6vJyUlhSVLlgjv2zTp7u6murqamJgY1q5dOyPHwdDQECtXrqSvr4/KykoWL17sBksFpyJcPC4mJiaGrVu3YrfbufzyyxkYGJjROmVlZcTFxdHR0UFnZ6drjfRR5HI5RUVFnHfeefj5+XHo0CGOHDkiwqsCgQ8jSRKtra3s3bsXo9HI4sWLWbFihRBw02R4eJiamhqCg4NZtWrVjAScxWLhqquuoqOjgyeffFIIuDlEiDg3sHr1av7whz/Q3d3N1772tRnltsnlckfF5dGjR0VzWyeIj4/n/PPPJz4+nq6uLj766CPGxsbm2yyBQOBijEYjlZWV1NfXExoayoYNG1AqlaJ9yDSZmJjgwIEDyGQyysvLCQwMnNE6d999Nzt37uQ73/kO3/zmN11speBsCBHnJm688Ua+//3vs3fvXr7zne/MqNAhMDCQ8vJy/Pz8OHDgAKOjo6431EcJCgpizZo1FBUVodPp+Oijj2hqahI95QQCH0CSJHp6etixY4dj+sLGjRtPO5xccHpMJhMVFRWYTCaWLVs249fuT3/6E0899RSbNm3iiSeecLGVgnMhcuLciNVq5Utf+hLvv/8+Tz75JHfccceM1hkaGmLfvn34+/uzfv16QkNDXWypbzM6Osrhw4cZHx8nMjKSpUuXiou9DyNy4nwbo9FITU0NarWawMBAFi9eLIbXO4nFYmHfvn2Mjo6yaNEisrKyZrTO7t27ufDCC0lPT+fgwYPExsa62FLBuRAizs2MjIxQXl5Oe3s77733HhdeeOGM1unv7+fAgQOEhISwfv16Me/PSWw2G8eOHXNMxCgoKCAvL09U/vogQsT5JpIkoVKpqK2txWKxkJqayqJFiwgICJhv07wKu93O/v37OX78OAUFBRQWFs5ona6uLlasWIHRaKSiooLS0lIXWyqYDuIO5maio6PZtm0boaGhXHXVVbS1tc1oneTkZBYvXoxer2f//v1YLBYXW+rb+Pn5UVRUxPr16wkLC6OpqYndu3eLpsoCgRdgNBo5cOAAhw8fRi6Xs3LlSlasWCEEnJNIksThw4c5fvw4mZmZFBQUzGgdnU7HZZddxtDQEFu2bBECbh4RIm4OKCws5NVXX2V0dJTLLrtsxsJBqVRSWFjI2NgYBw4cEFWXMyA6OpqNGzeSn5+PVqtl165dNDc3i1w5gcADmfK+7dixA7VaTWpqKps2bSIlJWW+TfM6JEmirq6O3t5eh1NgJgUgdrudG264gaNHj/Lwww9z2WWXucFawXQRIm6O+MIXvsAvfvELGhoauO6662YswPLz81EqlQwODnL48OEZFUwsdM7klRseHp5v0wQCwSfo9XoOHDjAoUOHkMlkDu/bTCsoFzqtra20t7cTGxs746H2AA899BD//Oc/+frXv869997rYisFziJy4uYQSZK4/vrr+etf/8q9997Lz3/+8xmvU1VVRV9fH1lZWZSVlYmS+hlis9lobm6mtbUVSZLIzMykqKhI3Ci8GJET593YbDZaW1s5duwYdrud1NRUysrKxHdyFnR1dXHkyBEiIiJYt27djHvo/fOf/+TKK69k2bJl7Nmzh5CQEBdbKnAWIeLmGKPRyMaNGzlw4ACvvPIK11xzzYzWsdls7N+/n8HBQQoLC2ec2yCYZHx8nKNHjzI4OIi/vz9FRUWi35SXIkSc96LRaKitrWViYoKwsDAWLVo04xmegknUajUHDhwgKCiI9evXExwcPKN1ampqOO+88wgPD+fgwYOkp6e72FLBTBAibh7o6+tj5cqVDA0N8cEHH7B+/foZrWOxWPj4448ZGxtjyZIlZGZmutjShYUkSfT19VFXV4fRaCQyMpJFixYRExMz36YJnECIOO9Dr9dTW1uLWq3Gz8+PgoICcnJyRPX4LBkeHmbfvn34+fk50kdmQk9PD2vXrkWj0bBr1y7WrFnjYksFM0WIuHni8OHDbNy4EYVCwe7duykrK5vROkajkT179qDX61mxYgWpqakutnThYbVaaW5upq2tDUmSyMjIoLi4WIRzvAQh4ryH04VOS0pKZuwtEnzK6Ogo+/btw263s3btWqKjo2e0zvDwMOvXr6ehoYGXX36Z6667zsWWCmaDEHHzyPbt2/niF79IfHw8+/btm7EnbWJigr1792IymVixYoWo3HIRp4ZYCwsLUSqVwjvg4QgR5/lIkoRGo6Gurk6ETt3A2NgYH3/8MTabjfLychISEma0jl6v5+KLL2bfvn38+te/5vvf/76LLRXMFiHi5pmtW7dyzTXXkJ+fz969e4mLi5vROjqdjr1792I2m1m5cqXoYO4iTg2xhoaGUlRUREpKisiX81CEiPNshoeHaWhoYGhoSIRO3YBWq+Xjjz/GarWyatUqEhMTZ7SO1WrlK1/5Cm+99RY//OEPeeyxx1xsqcAVCBHnATz55JPceeedrFq1ih07dsx4rNb4+Dgff/wxZrOZVatWkZSU5GJLFy5Wq5W2tjZaW1uxWq1ERUVRXFwsPAceiBBxnolWq6WxsRG1Wo1MJiMjI4OCggIROnUhUwLOYrHM6h4gSRI333wzzz//PNdffz3PP/+82LR6KELEeQj3338/P//5z/n85z/Ptm3bZlwC7qpdmOD0mEwmjh07RmdnJ3a7nfj4eIqLi4mKippv0wSfIEScZ6HX62lqaqKnpweAlJQUCgsLCQ8Pn2fLfIsTN/Gzjcbcd999PPLII3zxi1/k9ddfn/H9SOB+hIjzECRJ4pZbbuG5555j8+bNvPjiizMOL5wo5FauXCk8cm7gdDemoqKiGVd/CVyHEHGegdls5tixY3R0dGC324mLi6O4uHjGCfaCM6PVatm3bx9ms3nWedG//e1v+d73vsfq1avZvn37jCNDgrlBiDgPwmq18tWvfpU333yTe+65h8cff3zGa42NjbFv3z4sFovIkXMjWq2WhoYGNBoNMpmMzMxM8vPzRYhoHhEibn6xWCy0t7c7Ug8iIyMdqQciJOd6XCngXn31Va655hoKCwvZu3cvsbGxLrRU4A6EiPMw9Ho9l1xyCR9//DGPP/4499xzz4zXcuWXW3B2hoaGaGhoYHh4GJlMRnp6Orm5uSJkNA8IETc/mEwm2tra6OjowGq1EhoaSmFhIampqUK8uQlXbtY/+OADvvSlL5GQkMC+ffvIyMhwoaUCdyFEnAcyPDzMhg0bqK+v56WXXuK///u/Z7zWiXkSy5cvF33k3IgkSQwMDHDs2DHHHNaUlBTy8vJEztwcIkTc3KLX62ltbaW7uxubzUZoaCh5eXmkp6eLilM3MtUHzmazzTpt5uDBg2zatAl/f3/27t1LSUmJCy0VuBMh4jwUlUrFeeedR39/P//+97/58pe/POO1xsfH2bdvH0ajkWXLlolxKXPA0NAQLS0taDQaAOLj48nPzyc2NlZ4JdyMEHFzw/j4OC0tLahUKiRJIjIykry8PNF+Zw4YHh5m//792Gy2WRewNTY2snHjRsbHx9m+fTtr1651oaUCdyNEnAfT2NjIhg0b0Gq1vP7663zhC1+Y8Vo6nY59+/ZhMBgoKSkhNzfXhZYKzsTY2BgtLS309vYCEB0dTX5+PomJieJG5yaEiHMvIyMjtLS00N/fD0BsbCz5+fki522O0Gg0HDx4EIBVq1bNuJEvQHNzM+effz6Dg4P861//4tJLL3WVmYI5Qog4D+fo0aNs2rSJiYkJtm3bxiWXXDLjtQwGAxUVFYyPj5Obm0txcbG46M4ROp2O1tZWenp6sNvthIeHk52dTVpaGgqFYr7N8ymEiHM9drsdtVpNR0cHg4ODACQlJZGXlydmC88h3d3dHDlyBIVCwerVq2f12re2trJx40Y0Gg1bt27la1/7mgstFcwVQsR5AdXV1Vx44YUYDAbefvvtWd2czGYzlZWVDA8Pk5aWxtKlS0XeyhxiMBhob2+ns7MTq9WKQqEgMzOTrKwsUcrvIoSIcx0mk4muri46OzsxGAzIZDJSU1PJy8sjIiJivs1bULS2tlJfX09wcDBr1qyZVdFUe3s7GzdupK+vj7/97W/813/9lwstFcwlQsR5CYcOHeLCCy/EbDbzzjvvsHHjxhmvZbVaOXToEGq1moSEBFauXCm8QXOM1Wqlp6eHjo4OxsfHAUhISECpVJKYmCiE9SwQIm52SJLEyMgInZ2d9Pb2YrfbCQwMRKlUolQqCQoKmm8TFxSSJFFfX09bWxvh4eGsWbNmVi2MOjs72bhxIyqVir/+9a9ce+21LrRWMNcIEedFHDhwgIsvvhir1co777zDhg0bZryW3W6npqaG7u5uoqKiWL16NYGBgS60VjAdJElicHCQ9vZ21Go1AEFBQWRmZpKZmSn6zc0AIeJmhsViQaVS0dnZiVarBSAmJoasrCxSUlLExmIesNvtVFdXo1KpiImJoby8nICAgBmv19nZyaZNm+jq6uLFF1+cVecDgWcgRJyXsX//fi655BJsNhtvvvnmrG5UkiTR2NhIS0sLYWFhrFmzhpCQEBdaK3AGg8FAV1cXXV1dGI1GABITE0lPTycxMVF4S6eJEHHTR5Ikjh8/jkqloq+vD5vNhkKhID09HaVSKUKm84jVauXgwYMMDAyQlJTEihUr8PPzm/F67e3tbNq0iZ6eHp577jluuOEG1xkrmDeEiPNCKisr+dznPofJZGLbtm1cfPHFs1qvra2Nuro6goKCWLNmjbhwzzN2ux2NRkNXV5ejRYmfnx8pKSmkpaWJKsBzIETc2ZEkibGxMVQqFSqVCpPJBEBUVBRKpZLU1FSxYZhnTCYT+/fvZ3R0lIyMDBYvXjwrT2hrayubNm2ir6+PF154QXjgfAgh4ryUqqoqLr74YgwGA6+//jqf//znZ7WeSqXi8OHD+Pn5sXr1ajFuxUMwGo309vaiUqkYHR0FIDAwkLS0NNLS0oiMjBSC7hSEiDs9er0elUpFT08POp0OgJCQEMdnSUwX8Qz0ej379u1jYmKC/Px8CgsLZ/UdP3bsGJs2bUKtVoscOB9EiDgv5vDhw1x88cXodDr+9a9/8aUvfWlW6w0MDHDgwAEkSWLZsmViuoOHodPpHDdhvV4PQFhYGOnp6aSmporq1k8QIu5TTCYT/f399PT0OKaIBAQEkJqaSlpaGtHR0WIT4EGMjIxQWVmJyWSirKyM7OzsWa3X2NjIBRdcwPHjx9myZQtf//rXXWSpwFMQIs7Lqamp4cILL0Sr1fLyyy/PulR8dHSU/fv3YzKZXLILFLieqepBlUpFb28vZrMZgPDwcJKSkkhKSlrQN+eFLOIkSWJ8fByNRoNarXYINz8/P5KSkkhLSyMhIUEUKXggKpWK6upqAJdsog8fPswXvvAFhoeHefXVV0UfOB9FiDgfoLa2lksuuQSNRsOTTz7Jd77znVmtZzAYOHDgAKOjoyQlJbFs2TL8/f1dZK3AldjtdgYGBujv70ej0TjymwICAkhKSiIxMZGEhIQFleO00ESc3W5naGgItVqNRqNhYmICmBRuCQkJJCcnk5SUJL7DHsqJBWZBQUGsWrWK6OjoWa354YcfcsUVV2CxWNi6dSuXX365i6wVeBpCxPkIHR0dfO5zn6OlpYX/9//+Hz/96U9n5Ymx2WwcOXIElUpFeHg45eXlIlzn4Ux56Ka8MFNtIuRyOXFxcQ5R5+sVyAtBxJnNZgYGBlCr1QwMDGCxWAAIDg52eGNjY2NnVc0ocD8Wi4XDhw+jVquJiopi1apVs24r9Nprr7F582ZCQkLYtm3brFpRCTwfIeJ8iOPHj/PFL36RqqoqbrnlFn7/+9/PygMjSRKtra00NDQQEBDAypUriYuLc6HFAnei1+tRq9Wo1WoGBweZ+qqHhoYSGxtLXFwccXFxPteLzhdFnNlsZmhoiMHBQYaGhhgbG3P8LioqyiHcIiIiFmwY3duYmJigsrKS8fFx0tLSWLJkyaxF91NPPcWdd95JUlIS7777LosWLXKRtQJPRYg4H0On0/G1r32N999/n8svv5y//e1vs75Jq9VqDh06hM1mo6ysjKysLBdZK5grLBYLAwMDHD9+nMHBQUfIDXxP1PmCiDubaAsMDHS8V4mJiV7/fi1Ejh8/zsGDB7FYLJSUlJCTkzMr8S1JEj/60Y/42c9+Rn5+Pu+99x5KpdJ1Bgs8FiHifBCz2cyNN97IK6+8wrp169i2bduscyy0Wi0HDhxgYmICpVJJWVmZSI72YgwGg0MgnEnURUVFERUVRUREhFeF5bxNxE0VI4yOjjI2NnZG0TYltMPCwoS3zUuRJImOjg7q6urw8/NjxYoVJCYmzmpNq9XKbbfdxl/+8hdWrlzJ22+/TXx8vIssFng6QsT5KHa7nXvuuYcnnniC0tJS3n333VlXO5nNZg4ePMjg4CCxsbGsXLlSjOryEaZE3ZSwO1HUyWQywsPDHaIuMjKSyMhIjxV2nizi7HY7Op2O0dFRh2gbGxvDZrM5nhMYGHiSZ1SINt/Abrdz9OhRurq6CA0Npby8fNa9+QwGA1dffTXbtm3jc5/7HP/4xz8ICwtzkcUCb0CIOB9GkiR++ctf8sMf/pCMjAzee+89CgsLZ7Wm3W6nrq6Ojo4OQkJCWLVqFZGRkS6yWOApGI1Gh8iYEhxTo8DgZGEXHh5OWFgYoaGhhIaGzruH1hNEnCRJGAwGdDqd4zE6OopWqz1JsPn7+zuE8ZRIDgkJEaLNxzAajVRVVTE0NER8fDwrVqyY1QxUmOwpd9lll7F37142b97MX/7yl1mvKfA+hIhbALz44ovcfPPNREVF8fbbb1NeXj7rNbu6uqipqUEmk1FaWopSqRQ3Hh/HaDSeJOrGxsYwGAwnPUcmkxESEkJoaChhYWEOcRcWFkZwcPCcfEbmSsRJkoTZbD5JqE1MTDj+a7fbT3r+lGA70aMpBJvvMzAwwOHDhzGZTOTk5FBcXDzrjU5vby+f//znqaur4+677+bxxx+f982TYH4QIm6B8Pbbb3PVVVchk8nYunUrX/7yl2e95sjICFVVVej1elJSUliyZInoRbXAMJlM0xYxMpmMoKAgAgMDCQoK+sxj6ueBgYGzEjazFXGSJGGxWDAajSc9TCbTZ/7/RK/a1N8YEhJyknidaxEr8AzsdjvNzc0cO3YMhULBkiVLXDIFp76+ni9+8Yt0d3fz+OOPc88997jAWoG3IkTcAmL//v18+ctfZnh4mEceeYQf/vCHs76pWCwWqqur6e/vJyQkhBUrVsy6iELg/ZwunKjX6x3ix2QycbZLj7+/PwqFAoVCgZ+fn+Pfpz78/Pwcn2GZTIZMJqO5uRmA/Px8xzkkScJms2Gz2bBarad9TP3OYrGc1baAgACH8AwODj7J4+gJ4WTB/GMwGDh06BBDQ0NERkayYsUKl+Sqbdu2jeuuuw6j0chf/vIXvvGNb7jAWoE3I0TcAqO9vZ3LL7+curo6rr32Wv785z/PukWBJEl0dnZSV1eHJEmUlJSQnZ0tvA6CMyJJksOzdaqHy2g0nlFouZozCcQzeQwDAwOFSBOcFbVaTXV1NWazmezsbIqLi2ddBCRJEo888gj/7//9P2JjY/nnP/8pmvgKACHiFiTj4+Ns3ryZbdu2sWLFCl5//XWXuPnHxsY4ePAgExMTJCUlsXTpUpFoK3AZkiRht9s/4z070dsmSdJJ8yfhUw+dXC4/oxdPIJgtdrudhoYG2tra8Pf3Z+nSpSQnJ896Xb1ez0033cTWrVtZtGgRb7zxhugBJ3AgRNwCxW6388ADD/Czn/2M5ORk/v3vf7uk4MFisXD06FFUKhVBQUGsWLGC2NhYF1gsEEwPT6hOFSwsJiYmqKqqYnR0lOjoaFasWOGS8XY9PT1cccUVHD58mK985Su89NJLooWI4CREXGCBIpfLefjhh3n11VcZHR1l48aN/PWvf531uv7+/ixbtowlS5ZgsVj4+OOPOXbs2FlzjAQCgcBb6evrY9euXYyOjpKXl8e6detcIuAqKipYuXIlhw8f5sc//rHoASc4LULELXC+/vWvs2fPHuLj4/nGN77BD3/4w89U3DmLTCYjMzOTDRs2EBYWRmNjIxUVFZ9pRyEQCATeitVqpaamhoMHDyKXy1m9erVL2ocAvPDCC5x//vmMj4/z97//nQcffFDkYgpOiwinCoDJZNyvfvWrVFRU8IUvfIG//e1vLmnia7Vaqauro6urC4VCQVlZGenp6SIXSeA2RDhV4G4GBweprq5Gr9cTFxfHsmXLXDLD1mq18sMf/pAnnniCjIwM3njjDZYsWTJ7gwU+ixBxAgcmk4nbbruNF154gYKCArZt20Z+fr5L1lar1Rw5cgSTyURiYiKLFy8Wg7sFbkGIOIG7sFqtNDY20t7ejp+fH0VFRS6rxB8ZGeHqq6/m/fffZ+3atfzrX/8iISHBBVYLfBnhnxU4CAwM5LnnnuOJJ56gpaWF8vJytm3b5pK1k5KSuOCCC0hLS0Oj0bBz5066u7tFrpxAIPAKhoaG2LVrF+3t7cTExHD++eeTk5PjEgFXU1NDeXk577//PjfffDM7duwQAk4wLYSIE5yETCbje9/7Hu+88w5yuZzLL7+c73//+5jN5lmvHRAQwPLly1m1ahVyuZzq6moqKytFrpxAIPBYrFYrtbW17N27F4PBQGlpKevWrXNJkYEkSfzhD3+gvLyczs5Ofve73/Hss8+K1kyCaSPCqYIz0tPTw7XXXsvevXtZsWIFr776Kjk5OS5Z22w2U1tbi0qlwt/fn7KyMtLS0kSunGDWiHCqwFUMDQ1RXV3NxMQEMTExLF261GUVomNjY3zzm9/k73//O1lZWbz66qusWrXKJWsLFg7CEyc4I+np6ezcuZP777+fQ4cOsWzZMl577TWXrH2qV+7w4cMcOHAAo9HokvUFAoFgppzqfSspKXGZ9w3g4MGDLF26lL///e9ceeWVHD58WAg4wYwQIk5wVhQKBQ8//DDvvfceQUFBfP3rX+e2225zWQg0OTnZkSunVqvZsWMHPT09IldOIBDMCyfmvkVHR3P++eeTm5vrkiiBJEk88cQTrF27lr6+Pp555hlee+01oqKiZm+4YEEiwqmCaaNWq7nuuuvYsWMHZWVlvPbaaxQWFrps/f7+fmpqajCZTMTFxbFo0SLCw8Ndtr5gYSDCqYKZYDKZaGhooLu7G7lcTlFRkcsKF2BSHN5www289dZb5Ofns3XrVtE+RDBrhCdOMG2SkpJ4//33eeihh6ivr2f58uW89NJLLlt/yiuXmZnJ4OAgO3fupL6+3i2DzwUCgQAmvWMdHR18+OGHdHd3Ex8f71LvG8DevXtZsmQJb731Fps3b6aqqkoIOIFLEJ44wYzYvXs31157Lb29vVx//fU89dRTLh0JMzw8zNGjRxkbGyMoKIjS0lJSUlJE4YPgnAhPnGC6nHqdKSsrIzk52WXXGbvdzmOPPcaPfvQjAgMDefrpp7n++uvFdUzgMoSIE8yYwcFBrr/+ev7zn/9QUFDAK6+8wrJly1y2viRJdHV10dDQgMViESFWwbQQIk5wLk4MncpkMnJzc8nPz0ehULjsHL29vdx444188MEHlJaWsnXrVoqLi122vkAAIpwqmAVxcXG8+eab/PKXv6StrY1Vq1bxwAMPuKSnHEz2rFMqlVx44YWfCbFaLBaXnEMgECwcJEmivb39pNDppk2bKC4udpmAkySJF198kZKSEj744ANuueUWKisrhYATuAXhiRO4hCNHjnDDDTdQU1PDokWLeOGFF1i6dKlLzzEyMsLRo0cZHR0lKCiIkpISUlNTRWhCcBLCEyc4HSeGToODgyktLXVp6BSgr6+PW2+9lbfffpukpCT++Mc/ctlll7lsfYHgVISIE7gMs9nMz3/+c372s58BcN9993H//fe7tPv46UKspaWlREZGuuwcAu9GiDjBiRgMBhobG+np6XFb6FSSJP76179y1113MTo6yubNm/ntb39LTEyMy84hEJwOIeIELqe6upobbriBo0ePsnjxYl544QWXV2KZTCYaGxvp6uoCIC0tjaKiIkJCQlx6HoH3IUScAMBisdDS0kJ7ezs2m434+HjKyspcnlPb19fHt771Ld566y3hfRPMOULECdyC2Wzm4Ycf5uc//zkymYz777+f++67z+UzAUdHR2loaOD48ePIZDKysrLIz88nMDDQpecReA9CxC1sbDYb7e3ttLS0YLFYCA8Pp7i4mMTERJeGTiVJ4uWXX+bOO+9kdHSU6667jt/97nfC+yaYU4SIE7iVw4cPc8MNN1BbW8vixYt58cUXWbx4scvPc/z4cRoaGhgdHcXPz4/c3FxycnLw9/d3+bkEno0QcQsTu91OT08PTU1NGI1GgoODKSoqcstM5v7+fm677Ta2bdtGYmIif/jDH7jiiitceg6BYDoIESdwO2azmYceeohHHnkEmUzG//t//4/77rvP5QJLkiT6+/tpaGhgYmKCgIAACgoKUCqVyOWiEHuhIETcwmLqe9/Y2IhOpyMgIID8/HyUSiV+fn4uP9eWLVu48847GRkZ4ZprruHJJ58kNjbWpecRCKaLEHGCOePQoUPccMMN1NXVsWjRIp555hnWrl3r8vPY7Xa6u7tpbm7GaDQSEhJCYWGhW3bkAs9DiLiFw+DgIA0NDYyMjLjdA9/e3s6dd97J22+/TUJCAn/4wx/4yle+4vLzCATOIEScYE4xmUw8/PDDPPbYY1gsFm644QYee+wxEhISXH4uq9VKR0eHIzcmIiKC4uJiEhIShJjzYYSI833GxsZoaGhgYGDA0U8yPz+foKAgl5/LYDDw2GOP8eijj2Iymbj22mv57W9/S1xcnMvPJRA4ixBxgnmhubmZ7373u3zwwQdERkby8MMPc9ttt7m07H8Ks9nsqFKz2+1ERkaSn5/v8h5RAs9AiDjfZWhoiJaWFjQaDTBZlV5YWEhoaKhbzvfmm29y11130dHRQXFxMU8//TTnn3++W84lEMwEIeIE84YkSfzrX//i+9//Pj09PSxevJinn37aLSFWmNxRt7S00N3djc1mIzQ0lLy8PNLT00XOnA8hRJxvIUkSAwMDtLS0MDQ0BEBKSgr5+flu6w/Z3t7OXXfdxVtvvUVYWBg/+clP+O53vysKpQQehxBxgnlnYmKCn/3sZ/zyl7/EYrFw/fXX89hjj5GYmOiW85lMJtrb22lvb8dqtRIUFERubi6ZmZlu8QQK5hYh4nwDSZLo6+ujpaWFsbExZDIZ6enp5Obmum1+8ulCp48//jgpKSluOZ9AMFuEiBN4DM3Nzdx55528//77REZG8tBDD3H77be7TVhZLBY6Oztpa2vDZDIREBBAdnY2WVlZLu9nJ5g7hIjzbmw2Gz09PbS2tjIxMYGfnx+ZmZnk5uYSHBzstvOeGDotKSnhqaeeEqFTgccjRJzAo5AkiX//+99873vfm5MQK0zeNLq7u2ltbUWv1+Pn54dSqSQnJ8etNw2BexAizjuxWq2OTZXRaMTf39+xqXJn8+62tjbuuusu3n77bcLDw3nwwQdF6FTgNQgRJ/BIJiYm+PnPf87jjz+OxWJh8+bNPPTQQyiVSred026309vbS0tLC+Pj48jlctLT08nOziYiIsJt5xW4FiHivAuDwUBnZycdHR1YLBYCAwMd6Q3uFFJjY2P84he/4Fe/+pUInQq8FiHiBB7NsWPHuOuuu3j33XcJCAjg9ttv5/777yc+Pt5t55QkCY1Gw7FjxxgZGQEgLi6OrKwskpKSRBGEhyNEnOcjSRLDw8N0dHTQ19eHJEmEhoaSm5tLenq6y5v0nojRaOSpp57ikUceYXh4mNLSUp566ik2btzotnMKBO5CiDiBV/Dhhx/yf//3f1RVVREeHs4999zD3XffTVhYmNvOKUkSIyMjdHR00NvbiyRJBAcHo1QqyczMFPNZPRQh4jwXm82GSqWio6ODsbExAOLj4x0bJHe2/LFarbz00kv8+Mc/RqVSkZGRwU9/+lM2b97sVtEoELgTIeIEXoMkSfzjH//g/vvvp6WlhYSEBH70ox9x6623ur0QwWg00tXVRUdHByaTCblcTkpKCkqlkpiYGNFvzoMQIs7zGB8fp6uri+7ubiwWC35+fmRkZJCVleW2StMpJEni9ddf5/7776exsZHY2Fjuv/9+br/9drc0BxYI5hIh4gReh8Vi4bnnnuMnP/kJ/f39ZGdn89BDD3H11Ve7PdRpt9vp7++no6PD0bMqPDwcpVJJenq6SIb2AISI8wxsNhv9/f10dXUxODgIQFhYGEqlkoyMjDn5rnz00Uf83//9H/v37yc0NJS7776be+65R+S4CnwGIeIEXoter+d3v/sdjz76KGNjYyxevJhHHnmEz3/+83PiGdNqtXR1ddHT0+PwLqSmppKenk5sbKzwzs0TQsTNL1qtlp6eHrq7uzGbzcjlcpKTk1EqlXP2vaipqeHee+/lnXfeQaFQ8K1vfYsf/ehHbus9KRDMF0LECbye4eFhHn30UX73u99hMpnYuHEjjz76KKtXr56T81utVvr6+ujs7HQUQgQHB5OWlkZaWprY9c8xQsTNPQaDgd7eXlQqlSPXLTQ0lMzMTDIyMuYsf7S9vZ0HHniAV155BUmSuOaaa3jooYfIycmZk/MLBHONEHECn0GlUvHggw/y/PPPY7fbueiii7j33nvZtGnTnHnFprwQKpUKo9EIQGRkJGlpaaSmpoq+c3OAEHFzg8Vioa+vD5VK5QiXKhQKUlNTSUtLm1NvdH19PY8++ih/+9vfsNlsfO5zn+ORRx5h6dKlc3J+gWC+ECJO4HM0Njbys5/9jFdffRWbzcaqVau49957ueyyy+asPYgkSQwNDaFSqejt7cVqtQKTrUrS0tJISUkR+XNuQog492G329FoNKhUKtRqNXa7HblcTmJiImlpaSQmJs5ppef+/ft55JFH2LZtGzD5nv/oRz8SkxYECwYh4gQ+S3t7O7/85S957rnnMJlMFBcX87//+79cc801cyqgbDab48an0WgcN76kpCTHjU/0nnMdQsS5lqmeblMbEovFAkBsbKxjQzKXY+okSeKDDz7gkUceYdeuXQBcccUV3HvvvaxatWrO7BAIPAEh4gQ+j1qt5oknnuD3v/894+PjZGZmcs8993DzzTfPeXjTbDY7QlBT1a0KhYLExESSkpJISEgQc1tniRBxs8dmszE4OIharUatVjtSA8LDwx25niEhIXNqk91u59///jePPPIIhw4dws/Pj+uuu47//d//pbi4eE5tEQg8BSHiBAuG0dFRnn76aX7zm98wODhIfHw83/ve9/j2t79NVFTUnNuj1+tRqVT09/czOjoKgEwmIzY2lqSkJJKSkggNDZ1zu7wdIeJmhslkQq1Wo9FoGBgYwGazAZMFCsnJyY4inbmuujabzWzZsoXHHnuM5uZmgoKCuPnmm7nnnnvcOoZPIPAGhIgTLDj0ej1//vOf+eUvf0lPTw8RERHcfvvtfO973yMpKWlebDIajSfdQO12OzDp+UhMTCQ5OZno6GjRtmQaCBE3PSRJYnx83OFtm6qshslQ6ZR32N3NeM+ETqfjL3/5C7/61a8c39PvfOc73HXXXaJViEDwCULECRYsZrOZV155hccee4ympib8/f256qqruOOOO1i9evW8CSar1XpSKMtkMgEQEBDguLHGx8eLwogzIETcmbHZbAwPDzs+W3q9HgA/P7+TQvrzOVKupaWFZ555hueff56xsTESEhIcHvPIyMh5s0sg8ESEiBMseOx2O2+88QZPPvkkO3fuBGD58uXccccdXH311fM6mkeSJEZHRx03Xa1W6/hdVFQUcXFxxMbGEhsbK0TdJwgR9yk2m42RkRGGhoYYHBxkeHjY4eUNDg52hO1jY2PndX6o3W7nvffe48knn+Sdd94BoKSkhDvuuIPrr79etOYRCM6AEHECwQnU1dXx9NNP89JLL6HX64mLi+OWW27h1ltvJSsra77NQ6/Xo1arGRwcZGhoCLPZ7PidEHWTLGQRdzbR5ufnR0xMDHFxcSQmJs5LftupDA8P8+KLL/LMM8/Q2tqKXC7n8ssv57vf/S7nn3/+vNsnEHg6QsQJBKdhdHSUF154gaeeeoq2tjZkMhmf+9znuO222/jSl76EQqGYbxMdOU2Dg4NC1J3AQhJx0xVtcXFxREVFeUQrG0mSqKio4I9//CNbt27FZDIRGxvLN7/5TW6//XYyMjLm20SBwGsQIk4gOAt2u53t27fzhz/8gW3btmGz2UhNTeWWW27hlltuIS0tbb5NdHCqqBscHHT09ILJIonIyEiioqKIiooiMjLSI8Soq/FVEWe329FqtYyOjjI2Nsbo6ChardbjRdsUY2NjvPzyy/zxj3+ktrYWgHXr1vGtb32LK6+8cl7TFgQCb0WIOIFgmvT19fGXv/yFZ599lp6eHuRyOZ/73Oe47rrruOKKKzyuHYgkSWi1WoeXbmxszJHIPkVYWNhJoi4yMtLrPXa+IOJsNhvj4+OMjo46HuPj4w7BBpOFLlFRUQ7hFh0d7VGiDSaLdLZv387LL7/Mv//9b/R6PZGRkXzjG9/gW9/6FiUlJfNtokDg1QgRJxA4ic1m45133uFPf/oT77zzDlarldDQUK644go2b97MRRdd5LEeLrPZ7BAFU96cMwm7yMhIwsPDCQ0NJSQkxOMEwpnwJhEnSRJGoxGdTodOpzvJw3bipTkwMNDxnkyJ7qCgII/MGZMkiaqqKl5++WVeffVVBgYGAFizZg3f/OY3+frXvz7njYIFAl9FiDiBYBYMDg7y2muv8fLLL1NRUQFAQkICV199NZs3b2bFihUeeaM9kSlhNyUgTifsZDIZoaGhhIWFERYWdtK/AwMDPepv9EQRZzabHUJtYmLipH9PNdWdYkqwnSjaPFWwnUhbWxtbtmzh5ZdfpqWlBYD8/Hw2b97MtddeS05OzjxbKBD4HkLECQQuoq2tjVdeeYWXX36ZY8eOAZCXl8fmzZu57rrrvOomZjab0Wq1nxEeExMTnHrJ8PPzO0ncBQcHExQURGBgoOO/c+nFm2sRJ0kSZrMZo9F40mNiYsLxup1YcDJFcHDwZ0RxRESEV7XTOH78OFu3bmXLli3s378fgMTERMcmZvny5R4vPgUCb0aIOIHAxUiSxKFDhxzhJI1GA8Dq1au57rrruPLKK+dtMsRssdvt6PX6k7xJU+LOYDCc8bgpQXeiuDvx3/7+/igUCsdjNjf+2Yo4SZKw2WxYrVbHY0qYmUymz4g1k8n0GWE7RUBAwGm9l6GhofPal202jI+P89Zbb7FlyxbeffddbDYboaGhfPWrX+W6667jwgsv9Nh0AoHA1xAiTiBwI1arlQ8//NCR2D0xMQFAeXk5l156KZdddhmlpaU+4a2wWq3o9frPiJxTxc+Jyflnws/P7yRRp1AoPvMzufz/t3d3L009cBzHP5u6QnxWfLzQICcIlSYF0dMSCtM2u+hGK6r/wD+poLLLUiRDQrMriVU+XWQWouWsVmYpPm77XcjOz7lZWunZ2d4vOEy3o3yzC998587sstlsxs8u/PH79+8lSQcOHDDiKhQKGcfGONt4bAy337HZbBExujlO9+/fr/T0dDkcjr/4icaPyclJdXZ2qrOzU729vVpZWVFKSorxwp7m5ua4e2EPkAyIOGCPLCwsqKOjQ48ePdLjx4+Nd1+oqKgwgu7MmTMJ84s/llAopNXV1ai4W11djQqpWJG1+e/H/obdbo8Zh5vDMS0tLSrQHA5HQoT3VoLBoLxerzo7O9XR0aHBwUFJUlpamurr6+XxeHTlyhUVFhaaPCmQ3Ig4wAQrKyvq7+83fklOTExIkrKystTQ0CC3263Gxkbl5eWZO2icCQaDRugFg0FjuybJuB0YGJC0vu3cvKWz2WwRmzz8b3FxUU+fPjU2bj6fT5KUn5+vpqYmeTweXbhwQZmZmSZPCiCMiANMFgqFNDIyYgRdOEJSUlJ08uRJeTweNTU1qaqqKqG3P/9KPL46NV59/PhR3d3d6ujoUE9Pj/F3jVVVVfJ4PPJ4PDpx4oRl/34PSHREHBBnZmZm1NXVFfWLtbi4WC6XyzicTidRFwMRt7Xp6Wn19fUZR/hSIHa7XadPn5bb7Zbb7ZbT6TR5UgDbQcQBcSz8FFdPT4/6+vo0NDRkPBaOunPnzsnlcqmyspKoExG30fT0tJ49e6be3t6IaJPWX/jhcrlUX1+vixcvKj8/38RJAfwJIg6wEL/fr+fPnxublI1RV1JSErGpS9aoS+aI8/l8EZu28PUKpf+jzeVy6ezZsyovLzdxUgD/AhEHWJjf71d/f7/xSzv8xuLSetQdP35cdXV1xlFUVGTitHsjWSLux48fevXqlbxer7xer168eBGxaauoqIiItoqKCvOGBbAriDgggWyMuv7+fo2MjERclqOsrCwi6urq6ix74eGtJGLEzc3N6eXLl/J6vcbtxi2bJB08eFCnTp0i2oAkQsQBCWxxcVFDQ0PGtsbr9Wp0dDTigralpaURUVdTU6OysjLLPhVr9Yj7+vWrBgcHI/7PxsfHI86prKyM+D+rra1VTk6OOQMDMA0RBySZpaUlDQ8PR0TC8PBwRNilp6fL6XTGPHJzc02c/vesEHELCwsaHx/X2NhY1PHt27eIc51OZ1SwZWdnmzQ5gHhCxAHQ8vKyEXZDQ0N6+/atxsbGNDk5GfW+oAUFBTHjrry8XJmZmaZv8OIl4hYXFzU1NWX8LDceHz58iDq/uLhYlZWVcjqdqq6uNoItKyvLhOkBWAERB2BLi4uLevfuXcyN0ZcvX6LOT09PV2lpqUpKSowj1uc5OTm7Fnu7HXHz8/Py+Xyanp6Wz+czjs2ff//+PeprMzMzVVVVFRXAlZWVxBqAHSPiAPyR2dnZiC3T1NRURMz4/f4tv3bfvn1G1OXm5iozM1MZGRm/vN18X/its1JSUmS3242jr69PwWBQLpdLwWAw4lhbW9PCwoLm5+f18+dP43bjx7Fu5+bmjDibn5/f8t+VnZ0dEatlZWURsVZYWGj6phJA4iDiAOyKlZUVffr06bcbq7m5OeNdKeKRw+FQVlaWiouLf7lhLCkpUXp6utnjAkgiRBwA04U3ZJu3YrE2Y+GPA4GAAoFA1LYtEAgYW7nNWzq73a6MjIwtt3ux7nM4HGb/eAAgJiIOAADAguxmDwAAAICdI+IAAAAsiIgDAACwICIOAADAgog4AAAACyLiAAAALIiIAwAAsCAiDgAAwIKIOAAAAAsi4gAAACyIiAMAALAgIg4AAMCCiDgAAAALIuIAAAAsiIgDkDBsNptsNptu3rxp9igAsOuIOABxY2Jiwggxl8tl9jgAENeIOAAAAAtKNXsAAPhXQqGQ2SMAwJ5hEwcAAGBBRBwAAIAFEXEAEsZWr05ta2szHvN6vb/9PgMDA8b5bW1tuzMsAPwlIg5Awrtx44bx8Z07d357/sZzuFwJgHhFxAFIeLW1tTp8+LAkqb29Xaurq1ueu7y8rAcPHkiSjhw5opqamr0YEQB2jIgDkBTC2zi/36+urq4tz+vs7NTs7KwktnAA4hsRByApXLt2Tamp61dV+tVTquHHUlNT1drauiezAcCfIOIAJIXCwkI1NDRIkrq6uuT3+6PO+fz5s7q7uyVJjY2NKiws3NMZAWAniDgASSP89Ojq6qra29ujHr9//77W1tYizgWAeEXEAUgabrdbeXl5kmI/pRq+r6CgQJcuXdrT2QBgp4g4AEnD4XCopaVFkuT1ejU6Omo8Njw8rNevX0uSWlpalJaWZsaIALBtRByApLLVNeO4NhwAqyHiACSVY8eOqbq6WpJ09+5dBQIBBQIB3bt3T5J06NAhHT161MwRAWBbiDgASSe8jfP5fOrp6dGTJ080MzMjiS0cAOsg4gAknevXryslJUXS+tOoG68Nd/XqVTNHA4BtSzV7AACIZWZmRrdv397Wua2trXI4HNv+3iUlJTp//ry6u7v18OFD4/6GhgYVFRXtcFIAMAcRByAuvXnzRrdu3drWuZcvX95RxEnrT5t2d3draWkp4j4AsAqeTgWQlJqbm5WTk2N8npeXJ7fbbd5AALBDtlAoFDJ7CAAAAOwMmzgAAAALIuIAAAAsiIgDAACwICIOAADAgog4AAAACyLiAAAALIiIAwAAsCAiDgAAwIKIOAAAAAsi4gAAACyIiAMAALAgIg4AAMCCiDgAAAALIuIAAAAsiIgDAACwICIOAADAgog4AAAACyLiAAAALIiIAwAAsKD/AF7Zz5VURU4oAAAAAElFTkSuQmCC",
@@ -509,7 +383,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 13,
    "id": "a4348cf7",
    "metadata": {},
    "outputs": [
@@ -531,12 +405,12 @@
     "]\n",
     "for benchmark, label in benchmarks:\n",
     "    benchmark_features[label] = [\n",
-    "        supermarq.features.compute_communication(benchmark.circuit()),\n",
-    "        supermarq.features.compute_depth(benchmark.circuit()),\n",
-    "        supermarq.features.compute_entanglement(benchmark.circuit()),\n",
-    "        supermarq.features.compute_liveness(benchmark.circuit()),\n",
-    "        supermarq.features.compute_measurement(benchmark.circuit()),\n",
-    "        supermarq.features.compute_parallelism(benchmark.circuit()),\n",
+    "        supermarq.features.compute_communication(benchmark.cirq_circuit()),\n",
+    "        supermarq.features.compute_depth(benchmark.cirq_circuit()),\n",
+    "        supermarq.features.compute_entanglement(benchmark.cirq_circuit()),\n",
+    "        supermarq.features.compute_liveness(benchmark.cirq_circuit()),\n",
+    "        supermarq.features.compute_measurement(benchmark.cirq_circuit()),\n",
+    "        supermarq.features.compute_parallelism(benchmark.cirq_circuit()),\n",
     "    ]\n",
     "print(benchmark_features)"
    ]
@@ -551,7 +425,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 14,
    "id": "580b8cfd",
    "metadata": {},
    "outputs": [],
@@ -559,7 +433,7 @@
     "jobs = []\n",
     "for benchmark, label in benchmarks:\n",
     "    job = service.create_job(\n",
-    "        benchmark.circuit(), repetitions=1000, target=\"ss_unconstrained_simulator\"\n",
+    "        benchmark.cirq_circuit(), repetitions=1000, target=\"ss_unconstrained_simulator\"\n",
     "    )\n",
     "    jobs.append((label, job, benchmark))"
    ]
@@ -574,7 +448,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 15,
    "id": "bf692416",
    "metadata": {},
    "outputs": [
@@ -582,10 +456,10 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{'00000': 477, '11111': 523}\n",
-      "0.9994707198625362\n",
-      "{'0000': 2, '0001': 1, '0010': 4, '0011': 16, '0100': 4, '0101': 13, '0110': 17, '0111': 89, '1000': 3, '1001': 15, '1010': 16, '1011': 102, '1100': 17, '1101': 97, '1110': 100, '1111': 504}\n",
-      "0.9914466094067258\n",
+      "{'00000': 481, '11111': 519}\n",
+      "0.9996388695848232\n",
+      "{'0000': 1, '0001': 2, '0010': 3, '0011': 22, '0100': 2, '0101': 13, '0110': 14, '0111': 89, '1000': 4, '1001': 11, '1010': 14, '1011': 93, '1100': 14, '1101': 83, '1110': 99, '1111': 536}\n",
+      "0.9978033905932742\n",
       "{'001': 1000}\n",
       "1.0\n",
       "{'11111110001': 1000}\n",
@@ -616,21 +490,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 16,
    "id": "4af88344",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "findfont: Font family ['Times New Roman'] not found. Falling back to DejaVu Sans.\n",
-      "findfont: Font family ['Times New Roman'] not found. Falling back to DejaVu Sans.\n"
-     ]
-    },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 1920x1440 with 2 Axes>"
       ]
diff --git a/supermarq-benchmarks/examples/Supermarq_HPCA_Tutorial_qss.ipynb b/supermarq-benchmarks/examples/Supermarq_HPCA_Tutorial_qss.ipynb
new file mode 100644
index 000000000..4d9ae4ad9
--- /dev/null
+++ b/supermarq-benchmarks/examples/Supermarq_HPCA_Tutorial_qss.ipynb
@@ -0,0 +1,556 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "5588660c",
+   "metadata": {},
+   "source": [
+    "# HPCA 2023 Supermarq Tutorial using `qiskit-superstaq`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "71b6a205",
+   "metadata": {},
+   "source": [
+    "You can run this notebook on our [JupyterHub](https://hub.super.tech/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2FInfleqtion%2FSupermarQ&urlpath=tree%2FSupermarQ%2Fexamples%2FSupermarQ_HPCA_Tutorial.ipynb&branch=main) or [Binder](https://mybinder.org/v2/gh/Infleqtion/client-superstaq/main?urlpath=git-pull%3Frepo%3Dhttps%253A%252F%252Fgithub.com%252FInfleqtion%252FSupermarQ%252Ftree%252Fmain%252Fexamples%26urlpath%3Dtree%252Fexamples%252FSupermarQ_HPCA_Tutorial.ipynb%26branch%3Dmain). The JupyterHub requires sign up while Binder does not."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "9599fca0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "try:\n",
+    "    import qiskit\n",
+    "    import qiskit_superstaq as qss\n",
+    "except ImportError:\n",
+    "    print(\"Installing qiskit-superstaq...\")\n",
+    "    %pip install --quiet 'qiskit-superstaq[examples]'\n",
+    "    print(\"Installed qiskit-superstaq.\")\n",
+    "    print(\"You may need to restart the kernel to import newly installed packages.\")\n",
+    "    import qiskit\n",
+    "    import qiskit_superstaq as qss"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "9a704403",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "try:\n",
+    "    import supermarq\n",
+    "except ImportError:\n",
+    "    print(\"Installing supermarq...\")\n",
+    "    %pip install --quiet supermarq\n",
+    "    print(\"Installed supermarq.\")\n",
+    "    print(\"You may need to restart the kernel to import newly installed packages.\")\n",
+    "    import supermarq"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "1172c409",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Optional\n",
+    "import os  # Used to store a token in an environment variable"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "79996440",
+   "metadata": {},
+   "source": [
+    "## Basics:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "320767be",
+   "metadata": {},
+   "source": [
+    "### 1. Provider creation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "696ded37",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "20 credits\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Provide your api key to `qss.SuperstaqProvider()` using the `api_key=` argument if\n",
+    "# the SUPERSTAQ_API_KEY environment variable is not set.\n",
+    "\n",
+    "# Submit qiskit circuits via `qiskit-superstaq`\n",
+    "provider = qss.SuperstaqProvider()\n",
+    "print(provider.get_balance())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "4551cfe4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<SuperstaqBackend('aqt_keysight_qpu')>,\n",
+       " <SuperstaqBackend('aqt_zurich_qpu')>,\n",
+       " <SuperstaqBackend('aws_dm1_simulator')>,\n",
+       " <SuperstaqBackend('aws_sv1_simulator')>,\n",
+       " <SuperstaqBackend('aws_tn1_simulator')>,\n",
+       " <SuperstaqBackend('cq_hilbert_qpu')>,\n",
+       " <SuperstaqBackend('cq_hilbert_simulator')>,\n",
+       " <SuperstaqBackend('ibmq_brisbane_qpu')>,\n",
+       " <SuperstaqBackend('ibmq_extended-stabilizer_simulator')>,\n",
+       " <SuperstaqBackend('ibmq_kyoto_qpu')>,\n",
+       " <SuperstaqBackend('ibmq_mps_simulator')>,\n",
+       " <SuperstaqBackend('ibmq_osaka_qpu')>,\n",
+       " <SuperstaqBackend('ibmq_qasm_simulator')>,\n",
+       " <SuperstaqBackend('ibmq_stabilizer_simulator')>,\n",
+       " <SuperstaqBackend('ibmq_statevector_simulator')>,\n",
+       " <SuperstaqBackend('ionq_harmony_qpu')>,\n",
+       " <SuperstaqBackend('ionq.simulator')>,\n",
+       " <SuperstaqBackend('qtm_h1-1_qpu')>,\n",
+       " <SuperstaqBackend('qtm_h1-1e_simulator')>,\n",
+       " <SuperstaqBackend('qtm_h2-1_qpu')>,\n",
+       " <SuperstaqBackend('sandia_qscout_qpu')>,\n",
+       " <SuperstaqBackend('ss_unconstrained_simulator')>]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# See which backends are available\n",
+    "provider.backends(available=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5d96ed7f",
+   "metadata": {},
+   "source": [
+    "### 2. Benchmark instantiation\n",
+    "NOTE: after executing a benchmark circuit, the score should always be evaluated using the same `Benchmark` object that was used to generate the circuit.\n",
+    "\n",
+    "All of the benchmarks can be found in `supermarq/benchmarks/`.\n",
+    "\n",
+    "Think about other circuits/benchmarks you would like to implement and run!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "67da9bdb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"word-wrap: normal;white-space: pre;background: #fff0;line-height: 1.1;font-family: &quot;Courier New&quot;,Courier,monospace\">     ┌───┐          ┌─┐                      \n",
+       "q_0: ┤ H ├──■───────┤M├──────────────────────\n",
+       "     └───┘┌─┴─┐     └╥┘     ┌─┐              \n",
+       "q_1: ─────┤ X ├──■───╫──────┤M├──────────────\n",
+       "          └───┘┌─┴─┐ ║      └╥┘     ┌─┐      \n",
+       "q_2: ──────────┤ X ├─╫───■───╫──────┤M├──────\n",
+       "               └───┘ ║ ┌─┴─┐ ║      └╥┘┌─┐   \n",
+       "q_3: ────────────────╫─┤ X ├─╫───■───╫─┤M├───\n",
+       "                     ║ └───┘ ║ ┌─┴─┐ ║ └╥┘┌─┐\n",
+       "q_4: ────────────────╫───────╫─┤ X ├─╫──╫─┤M├\n",
+       "                     ║       ║ └───┘ ║  ║ └╥┘\n",
+       "c: 5/════════════════╩═══════╩═══════╩══╩══╩═\n",
+       "                     0       1       2  3  4 </pre>"
+      ],
+      "text/plain": [
+       "     ┌───┐          ┌─┐                      \n",
+       "q_0: ┤ H ├──■───────┤M├──────────────────────\n",
+       "     └───┘┌─┴─┐     └╥┘     ┌─┐              \n",
+       "q_1: ─────┤ X ├──■───╫──────┤M├──────────────\n",
+       "          └───┘┌─┴─┐ ║      └╥┘     ┌─┐      \n",
+       "q_2: ──────────┤ X ├─╫───■───╫──────┤M├──────\n",
+       "               └───┘ ║ ┌─┴─┐ ║      └╥┘┌─┐   \n",
+       "q_3: ────────────────╫─┤ X ├─╫───■───╫─┤M├───\n",
+       "                     ║ └───┘ ║ ┌─┴─┐ ║ └╥┘┌─┐\n",
+       "q_4: ────────────────╫───────╫─┤ X ├─╫──╫─┤M├\n",
+       "                     ║       ║ └───┘ ║  ║ └╥┘\n",
+       "c: 5/════════════════╩═══════╩═══════╩══╩══╩═\n",
+       "                     0       1       2  3  4 "
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Create your benchmark using qiskit circuits\n",
+    "ghz = supermarq.ghz.GHZ(5)\n",
+    "ghz_circuit = ghz.qiskit_circuit()\n",
+    "ghz_circuit.draw()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7366ec76",
+   "metadata": {},
+   "source": [
+    "### 3. Circuit evaluation\n",
+    "The generated circuits can be evaluated on a backend using any compatible service: AWS Braket, IBM Qiskit, `cirq-superstaq`, `qiskit-superstaq`, etc. Here we use `qiskit-superstaq`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "ea1693e7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "backend = provider.get_backend(\"ss_unconstrained_simulator\")\n",
+    "job_qss = backend.run(ghz_circuit, shots=1000, method=\"dry-run\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2839ee4f",
+   "metadata": {},
+   "source": [
+    "### 4. Compute the score\n",
+    "NOTE: after executing a benchmark circuit, the score should always be evaluated using the same `Benchmark` object that was used to generate the circuit."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "4e1c5b9a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<JobStatus.DONE: 'job has successfully run'>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "job_qss.status()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "7c371847",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'00000': 508, '11111': 492}\n",
+      "0.9999359959034757\n"
+     ]
+    }
+   ],
+   "source": [
+    "counts = job_qss.result().get_counts()\n",
+    "print(counts)\n",
+    "score_qss = ghz.score(counts)\n",
+    "print(score_qss)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2a801645",
+   "metadata": {},
+   "source": [
+    "### 5. Visualize the results\n",
+    "The function in `supermarq/plotting.plot_results` produces a simple bar plot. Feel free to copy and paste that code here to generate more detailed figures."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "8c176996",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 960x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "supermarq.plotting.plot_results([score_qss], [\"ghz_qss\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5afa11d5",
+   "metadata": {},
+   "source": [
+    "## Quantum Program Profiling\n",
+    "The current hardware-agnostic application features can be found in `supermarq/features.py`. Quantum program profiling is an exciting area of research that is just getting started -- what kinds of features would you find meaningful? Try implementing them!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "34378bd5",
+   "metadata": {},
+   "source": [
+    "### Compute features"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "776bc0d4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0.2, 1.0, 0.9, 0.2636363636363636, 0.0, 0.0]\n"
+     ]
+    }
+   ],
+   "source": [
+    "ghz_circuit = supermarq.ghz.GHZ(10).qiskit_circuit()\n",
+    "ghz_features = [\n",
+    "    supermarq.converters.compute_communication_with_qiskit(ghz_circuit),\n",
+    "    supermarq.converters.compute_depth_with_qiskit(ghz_circuit),\n",
+    "    supermarq.converters.compute_entanglement_with_qiskit(ghz_circuit),\n",
+    "    supermarq.converters.compute_liveness_with_qiskit(ghz_circuit),\n",
+    "    supermarq.converters.compute_measurement_with_qiskit(ghz_circuit),\n",
+    "    supermarq.converters.compute_parallelism_with_qiskit(ghz_circuit),\n",
+    "]\n",
+    "print(ghz_features)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d48e399c",
+   "metadata": {},
+   "source": [
+    "### Visualize the feature vector"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "5f5fd6da",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 960x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "supermarq.plotting.plot_benchmark(\n",
+    "    [\"A single GHZ benchmark\", [\"ghz10\"], [ghz_features]],\n",
+    "    spoke_labels=[\"PC\", \"CD\", \"Ent\", \"Liv\", \"Mea\", \"Par\"],\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a88d51bd",
+   "metadata": {},
+   "source": [
+    "## Correlating performance <> features\n",
+    "To correlate the performance of a particular device with a certain application feature, it is helpful to evaluate several different benchmarks on that same device. This code example creates 4 different benchmarks, computes their feature vectors, evaluates them on a backend, and then measures the correlation between the performance seen and the application features."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d24c527c",
+   "metadata": {},
+   "source": [
+    "### Characterize the benchmarks"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "2ec5036f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'ghz5': [0.4, 1.0, 0.8, 0.4666666666666667, 0.0, 0], 'hsim4': [0.5, 1.0, 0.2857142857142857, 0.5961538461538461, 0.0, 0.38095238095238093]}\n"
+     ]
+    }
+   ],
+   "source": [
+    "benchmark_features = {}\n",
+    "benchmarks = [\n",
+    "    (supermarq.ghz.GHZ(5), \"ghz5\"),\n",
+    "    (supermarq.hamiltonian_simulation.HamiltonianSimulation(4), \"hsim4\"),\n",
+    "]\n",
+    "for benchmark, label in benchmarks:\n",
+    "    benchmark_features[label] = [\n",
+    "        supermarq.converters.compute_communication_with_qiskit(benchmark.qiskit_circuit()),\n",
+    "        supermarq.converters.compute_depth_with_qiskit(benchmark.qiskit_circuit()),\n",
+    "        supermarq.converters.compute_entanglement_with_qiskit(benchmark.qiskit_circuit()),\n",
+    "        supermarq.converters.compute_liveness_with_qiskit(benchmark.qiskit_circuit()),\n",
+    "        supermarq.converters.compute_measurement_with_qiskit(benchmark.qiskit_circuit()),\n",
+    "        supermarq.converters.compute_parallelism_with_qiskit(benchmark.qiskit_circuit()),\n",
+    "    ]\n",
+    "print(benchmark_features)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6d48ae31",
+   "metadata": {},
+   "source": [
+    "### Evaluate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "6fc58905",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "jobs = []\n",
+    "backend = provider.get_backend(\"ss_unconstrained_simulator\")\n",
+    "for benchmark, label in benchmarks:\n",
+    "    job = backend.run(benchmark.qiskit_circuit(), shots=1000)\n",
+    "    jobs.append((label, job, benchmark))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9e206840",
+   "metadata": {},
+   "source": [
+    "### Wait until the benchmarks have successfully executed..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "bf692416",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'00000': 493, '11111': 507}\n",
+      "0.9999509975987646\n",
+      "{'0000': 1, '1000': 2, '0100': 1, '1100': 23, '0010': 7, '1010': 13, '0110': 10, '1110': 91, '0001': 3, '1001': 17, '0101': 14, '1101': 88, '0011': 12, '1011': 101, '0111': 81, '1111': 536}\n",
+      "0.9990533905932741\n"
+     ]
+    }
+   ],
+   "source": [
+    "device_scores = {}\n",
+    "\n",
+    "for label, job, benchmark in jobs:\n",
+    "    if job.status() == qiskit.providers.jobstatus.JobStatus.DONE:\n",
+    "        counts = job.result(0).get_counts()\n",
+    "        print(counts)\n",
+    "        score = benchmark.score(counts)\n",
+    "        print(score)\n",
+    "        device_scores[label] = score\n",
+    "    else:\n",
+    "        print(label, \"not done!\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0b92718b",
+   "metadata": {},
+   "source": [
+    "### Measure the correlation between device performance and application features"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "4af88344",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1920x1440 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "supermarq.plotting.plot_correlations(\n",
+    "    benchmark_features,\n",
+    "    device_scores,\n",
+    "    [\"PC\", \"CD\", \"Ent\", \"Liv\", \"Mea\", \"Par\"],\n",
+    "    device_name=\"ibmq_sim\",\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": "3.9.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/supermarq-benchmarks/supermarq/benchmark.py b/supermarq-benchmarks/supermarq/benchmark.py
index 6289da146..5ae424b3c 100644
--- a/supermarq-benchmarks/supermarq/benchmark.py
+++ b/supermarq-benchmarks/supermarq/benchmark.py
@@ -1,10 +1,12 @@
 from __future__ import annotations
 
 import abc
-from collections.abc import Sequence
 from typing import Any
 
 import cirq
+import qiskit
+
+import supermarq
 
 
 class Benchmark:
@@ -20,13 +22,24 @@ class Benchmark:
     """
 
     @abc.abstractmethod
-    def circuit(self) -> cirq.Circuit | Sequence[cirq.Circuit]:
-        """Returns the quantum circuit corresponding to the current benchmark parameters."""
+    def circuit(self) -> cirq.Circuit | list[cirq.Circuit]:
+        """Returns the quantum circuit(s) corresponding to the current benchmark parameters."""
+
+    def cirq_circuit(self) -> cirq.Circuit | list[cirq.Circuit]:
+        """Returns the cirq circuit(s) corresponding to the current benchmark parameters."""
+        return self.circuit()
+
+    def qiskit_circuit(self) -> qiskit.QuantumCircuit | list[qiskit.QuantumCircuit]:
+        """Returns the qiskit circuit(s) corresponding to the current benchmark parameters."""
+        cirq_circuit = self.cirq_circuit()
+        if isinstance(cirq_circuit, cirq.Circuit):
+            return supermarq.converters.cirq_to_qiskit(cirq_circuit)
+        return [supermarq.converters.cirq_to_qiskit(c) for c in cirq_circuit]
 
     @abc.abstractmethod
     def score(self, counts: Any) -> float:
         """Returns a normalized [0,1] score reflecting device performance.
 
         Args:
-            counts: A dictionary containing the measurement counts from execution.
+            counts: Dictionary(s) containing the measurement counts from execution.
         """
diff --git a/supermarq-benchmarks/supermarq/benchmarks/bit_code.py b/supermarq-benchmarks/supermarq/benchmarks/bit_code.py
index 86c376771..883a4c1e8 100644
--- a/supermarq-benchmarks/supermarq/benchmarks/bit_code.py
+++ b/supermarq-benchmarks/supermarq/benchmarks/bit_code.py
@@ -3,7 +3,7 @@
 from collections.abc import Iterator
 
 import cirq
-from qiskit.quantum_info import hellinger_fidelity
+import qiskit
 
 from supermarq.benchmark import Benchmark
 
@@ -108,4 +108,4 @@ def score(self, counts: dict[str, float]) -> float:
         ideal_dist = self._get_ideal_dist()
         total_shots = sum(counts.values())
         experimental_dist = {bitstr: shots / total_shots for bitstr, shots in counts.items()}
-        return hellinger_fidelity(ideal_dist, experimental_dist)
+        return qiskit.quantum_info.hellinger_fidelity(ideal_dist, experimental_dist)
diff --git a/supermarq-benchmarks/supermarq/benchmarks/ghz.py b/supermarq-benchmarks/supermarq/benchmarks/ghz.py
index 80e45f7a0..28ae3e6f3 100644
--- a/supermarq-benchmarks/supermarq/benchmarks/ghz.py
+++ b/supermarq-benchmarks/supermarq/benchmarks/ghz.py
@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import cirq
+import qiskit
 from qiskit.quantum_info import hellinger_fidelity
 
 from supermarq.benchmark import Benchmark
@@ -22,7 +23,7 @@ def __init__(self, num_qubits: int) -> None:
         self.num_qubits = num_qubits
 
     def circuit(self) -> cirq.Circuit:
-        """Generate an n-qubit GHZ circuit.
+        """Generate an n-qubit GHZ cirq circuit.
 
         Returns:
             A `cirq.Circuit`.
@@ -35,7 +36,21 @@ def circuit(self) -> cirq.Circuit:
         circuit.append(cirq.measure(*qubits))
         return circuit
 
-    def score(self, counts: dict[str, int]) -> float:
+    def qiskit_circuit(self) -> qiskit.QuantumCircuit:
+        """Generate an n-qubit GHZ qiskit circuit.
+
+        Returns:
+            A `qiskit.QuantumCircuit`.
+        """
+        circuit = qiskit.QuantumCircuit(self.num_qubits, self.num_qubits)
+        circuit.h(0)
+        for i in range(self.num_qubits - 1):
+            circuit.cx(i, i + 1)
+        for i in range(self.num_qubits):
+            circuit.measure(i, i)
+        return circuit
+
+    def score(self, counts: dict[str, float]) -> float:
         r"""Compute the Hellinger fidelity between the experimental and ideal results.
 
         The ideal results are 50% probabilty of measuring the all-zero state and 50% probability
diff --git a/supermarq-benchmarks/supermarq/benchmarks/hamiltonian_simulation.py b/supermarq-benchmarks/supermarq/benchmarks/hamiltonian_simulation.py
index 043bcd8fb..a8dcfa5dc 100644
--- a/supermarq-benchmarks/supermarq/benchmarks/hamiltonian_simulation.py
+++ b/supermarq-benchmarks/supermarq/benchmarks/hamiltonian_simulation.py
@@ -4,6 +4,7 @@
 
 import cirq
 import numpy as np
+import qiskit
 
 import supermarq
 from supermarq.benchmark import Benchmark
@@ -21,20 +22,19 @@ class HamiltonianSimulation(Benchmark):
     """
 
     def __init__(self, num_qubits: int, time_step: int = 1, total_time: int = 1) -> None:
-        """Args:
-        num_qubits: int
-            Size of the TFIM chain, equivalent to the number of qubits.
-        time_step: int
-            Size of the timestep in attoseconds.
-        total_time:
-            Total simulation time of the TFIM chain in attoseconds.
+        """Initializes a `HamiltonianSimulation`.
+
+        Args:
+            num_qubits: Size of the TFIM chain, equivalent to the number of qubits.
+            time_step: Size of the timestep in attoseconds. Defaults to 1.
+            total_time: Total simulation time of the TFIM chain in attoseconds. Defaults to 1.
         """
         self.num_qubits = num_qubits
         self.time_step = time_step
         self.total_time = total_time
 
     def circuit(self) -> cirq.Circuit:
-        """Generate a circuit to simulate the evolution of an n-qubit TFIM
+        """Generates a circuit to simulate the evolution of an n-qubit TFIM
         chain under the Hamiltonian:
 
         H(t) = - Jz * sum_{i=1}^{n-1}(sigma_{z}^{i} * sigma_{z}^{i+1})
@@ -83,6 +83,56 @@ def circuit(self) -> cirq.Circuit:
 
         return circuit
 
+    def qiskit_circuit(self) -> qiskit.QuantumCircuit:
+        """Generates a circuit to simulate the evolution of an n-qubit TFIM
+        chain under the Hamiltonian:
+
+        H(t) = - Jz * sum_{i=1}^{n-1}(sigma_{z}^{i} * sigma_{z}^{i+1})
+               - e_ph * cos(w_ph * t) * sum_{i=1}^{n}(sigma_{x}^{i})
+
+        where,
+            w_ph: frequency of E" phonon in MoSe2.
+            e_ph: strength of electron-phonon coupling.
+
+        Returns:
+            The circuit for Hamiltonian simulation.
+        """
+        hbar = 0.658212  # eV*fs
+        jz = (
+            hbar * np.pi / 4
+        )  # eV, coupling coeff; Jz<0 is antiferromagnetic, Jz>0 is ferromagnetic
+        freq = 0.0048  # 1/fs, frequency of MoSe2 phonon
+
+        w_ph = 2 * np.pi * freq
+        e_ph = 3 * np.pi * hbar / (8 * np.cos(np.pi * freq))
+
+        circuit = qiskit.QuantumCircuit(self.num_qubits, self.num_qubits)
+
+        # Build up the circuit over total_time / time_step propagation steps
+        for step in range(int(self.total_time / self.time_step)):
+            # Simulate the Hamiltonian term-by-term
+            t = (step + 0.5) * self.time_step
+
+            # Single qubit terms
+            psi = -2.0 * e_ph * np.cos(w_ph * t) * self.time_step / hbar
+            for i in range(self.num_qubits):
+                circuit.h(i)
+                circuit.rz(psi, i)
+                circuit.h(i)
+
+            # Coupling terms
+            psi2 = -2.0 * jz * self.time_step / hbar
+            for i in range(self.num_qubits - 1):
+                circuit.cnot(i, i + 1)
+                circuit.rz(psi2, i + 1)
+                circuit.cnot(i, i + 1)
+
+        # End the circuit with measurements of every qubit in the Z-basis
+        for i in range(self.num_qubits):
+            circuit.measure(i, i)
+
+        return circuit
+
     def _average_magnetization(self, result: Mapping[str, float], shots: int) -> float:
         mag = 0.0
         for spin_str, count in result.items():
diff --git a/supermarq-benchmarks/supermarq/benchmarks/mermin_bell.py b/supermarq-benchmarks/supermarq/benchmarks/mermin_bell.py
index ff25711f2..b2ab4b1ce 100644
--- a/supermarq-benchmarks/supermarq/benchmarks/mermin_bell.py
+++ b/supermarq-benchmarks/supermarq/benchmarks/mermin_bell.py
@@ -18,6 +18,11 @@ class MerminBell(Benchmark):
     """
 
     def __init__(self, num_qubits: int) -> None:
+        """Initializes a `MerminBell`.
+
+        Args:
+            num_qubits: The number of qubits.
+        """
         self.num_qubits = num_qubits
         self.qubits = cirq.LineQubit.range(self.num_qubits)
 
@@ -32,7 +37,6 @@ def circuit(self) -> cirq.Circuit:
         Returns:
             The Mermin-Bell `cirq.Circuit`.
         """
-
         circuit = cirq.Circuit()
 
         # Create a GHZ state
diff --git a/supermarq-benchmarks/supermarq/converters.py b/supermarq-benchmarks/supermarq/converters.py
index 3f54675ac..28fc53e0c 100644
--- a/supermarq-benchmarks/supermarq/converters.py
+++ b/supermarq-benchmarks/supermarq/converters.py
@@ -4,7 +4,7 @@
 import qiskit
 
 
-def cirq_to_qiskit(circuit: cirq.Circuit) -> qiskit.circuit.QuantumCircuit:
+def cirq_to_qiskit(circuit: cirq.Circuit) -> qiskit.QuantumCircuit:
     """Convert a circuit from cirq to qiskit.
 
     Args:
@@ -17,7 +17,7 @@ def cirq_to_qiskit(circuit: cirq.Circuit) -> qiskit.circuit.QuantumCircuit:
     return qiskit.circuit.QuantumCircuit().from_qasm_str(str(qasm))
 
 
-def compute_communication_with_qiskit(circuit: qiskit.circuit.QuantumCircuit) -> float:
+def compute_communication_with_qiskit(circuit: qiskit.QuantumCircuit) -> float:
     """Compute the program communication of the given quantum circuit.
 
     Program communication = circuit's average qubit degree / degree of a complete graph.
@@ -42,7 +42,7 @@ def compute_communication_with_qiskit(circuit: qiskit.circuit.QuantumCircuit) ->
     return degree_sum / (num_qubits * (num_qubits - 1))
 
 
-def compute_liveness_with_qiskit(circuit: qiskit.circuit.QuantumCircuit) -> float:
+def compute_liveness_with_qiskit(circuit: qiskit.QuantumCircuit) -> float:
     """Compute the liveness of the given quantum circuit.
 
     Liveness feature = sum of all entries in the liveness matrix / (num_qubits * depth).
@@ -68,7 +68,7 @@ def compute_liveness_with_qiskit(circuit: qiskit.circuit.QuantumCircuit) -> floa
     return np.sum(activity_matrix) / (num_qubits * dag.depth())
 
 
-def compute_parallelism_with_qiskit(circuit: qiskit.circuit.QuantumCircuit) -> float:
+def compute_parallelism_with_qiskit(circuit: qiskit.QuantumCircuit) -> float:
     """Compute the parallelism of the given quantum circuit.
 
     Parallelism feature = max(1 - depth / # of gates, 0).
@@ -84,7 +84,7 @@ def compute_parallelism_with_qiskit(circuit: qiskit.circuit.QuantumCircuit) -> f
     return max(1 - (circuit.depth() / len(dag.gate_nodes())), 0)
 
 
-def compute_measurement_with_qiskit(circuit: qiskit.circuit.QuantumCircuit) -> float:
+def compute_measurement_with_qiskit(circuit: qiskit.QuantumCircuit) -> float:
     """Compute the measurement feature of the given quantum circuit.
 
     Measurement feature = # of layers of mid-circuit measurement / circuit depth.
@@ -113,7 +113,7 @@ def compute_measurement_with_qiskit(circuit: qiskit.circuit.QuantumCircuit) -> f
     return reset_moments / gate_depth
 
 
-def compute_entanglement_with_qiskit(circuit: qiskit.circuit.QuantumCircuit) -> float:
+def compute_entanglement_with_qiskit(circuit: qiskit.QuantumCircuit) -> float:
     """Compute the entanglement-ratio of the given quantum circuit.
 
     Entanglement-ratio = ratio between # of 2-qubit gates and total number of gates in the
@@ -131,7 +131,7 @@ def compute_entanglement_with_qiskit(circuit: qiskit.circuit.QuantumCircuit) ->
     return len(dag.two_qubit_ops()) / len(dag.gate_nodes())
 
 
-def compute_depth_with_qiskit(circuit: qiskit.circuit.QuantumCircuit) -> float:
+def compute_depth_with_qiskit(circuit: qiskit.QuantumCircuit) -> float:
     """Compute the critical depth of the given quantum circuit.
 
     Critical depth = # of 2-qubit gates along the critical path / total # of 2-qubit gates.


Test patch:
diff --git a/supermarq-benchmarks/supermarq/benchmarks/ghz_test.py b/supermarq-benchmarks/supermarq/benchmarks/ghz_test.py
index 320a78456..cf956a4e7 100644
--- a/supermarq-benchmarks/supermarq/benchmarks/ghz_test.py
+++ b/supermarq-benchmarks/supermarq/benchmarks/ghz_test.py
@@ -1,10 +1,15 @@
 # pylint: disable=missing-function-docstring,missing-class-docstring
+import cirq
+
 from supermarq.benchmarks.ghz import GHZ
 
 
 def test_ghz_circuit() -> None:
     ghz = GHZ(3)
-    assert len(ghz.circuit().all_qubits()) == 3
+    cirq_circuit = ghz.cirq_circuit()
+    if isinstance(cirq_circuit, cirq.Circuit):
+        assert len(cirq_circuit.all_qubits()) == 3
+    assert ghz.qiskit_circuit().num_qubits == 3
 
 
 def test_ghz_score() -> None:
diff --git a/supermarq-benchmarks/supermarq/benchmarks/hamiltonian_simulation_test.py b/supermarq-benchmarks/supermarq/benchmarks/hamiltonian_simulation_test.py
index eee4932b4..b5e5c0485 100644
--- a/supermarq-benchmarks/supermarq/benchmarks/hamiltonian_simulation_test.py
+++ b/supermarq-benchmarks/supermarq/benchmarks/hamiltonian_simulation_test.py
@@ -6,6 +6,7 @@
 def test_hamiltonian_simulation_circuit() -> None:
     hs = HamiltonianSimulation(4, 1, 1)
     assert len(hs.circuit().all_qubits()) == 4
+    assert hs.qiskit_circuit().num_qubits == 4
 
 
 def test_hamiltonian_simulation_score() -> None:
diff --git a/supermarq-benchmarks/supermarq/benchmarks/mermin_bell_test.py b/supermarq-benchmarks/supermarq/benchmarks/mermin_bell_test.py
index 018476b91..0b0e83c36 100644
--- a/supermarq-benchmarks/supermarq/benchmarks/mermin_bell_test.py
+++ b/supermarq-benchmarks/supermarq/benchmarks/mermin_bell_test.py
@@ -1,4 +1,8 @@
 # pylint: disable=missing-function-docstring,missing-class-docstring
+from unittest.mock import patch
+
+import qiskit
+
 import supermarq
 from supermarq.benchmarks.mermin_bell import MerminBell
 
@@ -12,6 +16,14 @@ def test_mermin_bell_circuit() -> None:
 
     mb = MerminBell(5)
     assert len(mb.circuit().all_qubits()) == 5
+    qiskit_circuit = mb.qiskit_circuit()
+    if isinstance(qiskit_circuit, qiskit.QuantumCircuit):
+        assert qiskit_circuit.num_qubits == 5
+    with patch(
+        "supermarq.benchmarks.mermin_bell.MerminBell.circuit",
+        return_value=[mb.circuit()],
+    ):
+        assert mb.qiskit_circuit()[0].num_qubits == 5
 
 
 def test_mermin_bell_score() -> None: