diff --git a/doc/chart_manual_matching.ipynb b/doc/chart_manual_matching.ipynb
index 366ee61..5a6348d 100644
--- a/doc/chart_manual_matching.ipynb
+++ b/doc/chart_manual_matching.ipynb
@@ -18,7 +18,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "id": "14c9acaa-9f2e-4f89-bb51-6b9497c88ef6",
    "metadata": {},
    "outputs": [],
@@ -53,19 +53,583 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "id": "566888d7-4c62-47ae-a22d-20c98d06e509",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "c1226b7018b64e25bdf9290d6508296b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/3 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [62.29569364 59.63865631]\n",
+      "Rounded result: [62.3, 59.64, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [43.79471605 12.        ]\n",
+      "True solution #1: [62.04750653 59.82089341]\n",
+      "Rounded result: [150.0, 150.0, 62.05, 59.82]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [62.79555202 60.33256126 62.56014141 60.56659681]\n",
+      "Rounded result: [62.8, 60.33, 62.56, 60.57]\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d7d30cecd0814df6a19433ddb744558d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/10 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [52.19340257 46.72252791]\n",
+      "Rounded result: [52.19, 46.72, 150.0, 150.0]\n",
+      "True solution #1: [51.83607386 46.88542139]\n",
+      "Rounded result: [150.0, 150.0, 51.84, 46.89]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [52.7300015  47.19412529 52.4588477  47.38074514]\n",
+      "Rounded result: [52.73, 47.19, 52.46, 47.38]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [40.30033916 12.        ]\n",
+      "True solution #1: [52.80412456 46.59857656]\n",
+      "Rounded result: [52.8, 46.6, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [52.44015711 46.75884496]\n",
+      "Rounded result: [150.0, 150.0, 52.44, 46.76]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [53.3689562  47.02105264 53.09340511 47.18743058]\n",
+      "Rounded result: [53.37, 47.02, 53.09, 47.19]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [41.27417811 12.        ]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [41.27380196 12.        ]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [53.35770047 46.52383542]\n",
+      "Rounded result: [53.36, 46.52, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [52.98691072 46.68177155]\n",
+      "Rounded result: [150.0, 150.0, 52.99, 46.68]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [53.95049606 46.88534191 53.64962539 47.05895731]\n",
+      "Rounded result: [53.95, 46.89, 53.65, 47.06]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [53.86765876 46.48346616]\n",
+      "Rounded result: [53.87, 46.48, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [53.48963678 46.63905621]\n",
+      "Rounded result: [150.0, 150.0, 53.49, 46.64]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [54.47436353 46.79615985 54.19211866 46.9669927 ]\n",
+      "Rounded result: [54.47, 46.8, 54.19, 46.97]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [54.34156816 46.46819071]\n",
+      "Rounded result: [54.34, 46.47, 150.0, 150.0]\n",
+      "True solution #1: [53.9556413  46.62131823]\n",
+      "Rounded result: [150.0, 150.0, 53.96, 46.62]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [54.94734959 46.71916227 54.65440099 46.88871912]\n",
+      "Rounded result: [54.95, 46.72, 54.65, 46.89]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [54.7840589  46.47153814]\n",
+      "Rounded result: [54.78, 46.47, 150.0, 150.0]\n",
+      "True solution #1: [54.38938691 46.6218051 ]\n",
+      "Rounded result: [150.0, 150.0, 54.39, 46.62]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [55.39436812 46.67126232 55.09340892 46.82138317]\n",
+      "Rounded result: [55.39, 46.67, 55.09, 46.82]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [55.19790008 46.48860348]\n",
+      "Rounded result: [55.2, 46.49, 150.0, 150.0]\n",
+      "True solution #1: [54.79345336 46.63544013]\n",
+      "Rounded result: [150.0, 150.0, 54.79, 46.64]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [55.80916977 46.62300128 55.50172846 46.77697315]\n",
+      "Rounded result: [55.81, 46.62, 55.5, 46.78]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [46.23583269 12.        ]\n",
+      "True solution #1: [55.58465995 46.51519962]\n",
+      "Rounded result: [55.58, 46.52, 150.0, 150.0]\n",
+      "True solution #1: [55.16929785 46.65801736]\n",
+      "Rounded result: [150.0, 150.0, 55.17, 46.66]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [56.17368606 46.57419567 55.86007472 46.72277313]\n",
+      "Rounded result: [56.17, 46.57, 55.86, 46.72]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [55.94506206 46.54799573]\n",
+      "Rounded result: [55.95, 46.55, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [55.51770384 46.6858566 ]\n",
+      "Rounded result: [150.0, 150.0, 55.52, 46.69]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [56.50626384 46.53926777 56.19680216 46.68549166]\n",
+      "Rounded result: [56.51, 46.54, 56.2, 46.69]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [56.27954574 46.58379748]\n",
+      "Rounded result: [56.28, 46.58, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [48.003754 12.      ]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [55.83854714 46.71552448]\n",
+      "Rounded result: [150.0, 150.0, 55.84, 46.72]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [56.79962969 46.48615672 56.47423822 46.61429603]\n",
+      "Rounded result: [56.8, 46.49, 56.47, 46.61]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [50.69944511 48.61618258]\n",
+      "Rounded result: [50.7, 48.62, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [50.46747251 48.77906093]\n",
+      "Rounded result: [150.0, 150.0, 50.47, 48.78]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [51.38513228 49.38111347 50.85931216 49.54091416]\n",
+      "Rounded result: [51.39, 49.38, 50.86, 49.54]\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9619055165154c5cbf720d8971393b02",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/10 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [52.19341368 46.72251379]\n",
+      "Rounded result: [52.19, 46.72, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [51.83605904 46.88543157]\n",
+      "Rounded result: [150.0, 150.0, 51.84, 46.89]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [52.7300015  47.19412529 52.4588477  47.38074514]\n",
+      "Rounded result: [52.73, 47.19, 52.46, 47.38]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [52.80409655 46.59857608]\n",
+      "Rounded result: [52.8, 46.6, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [52.44012024 46.75886128]\n",
+      "Rounded result: [150.0, 150.0, 52.44, 46.76]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [53.3689562  47.02105264 53.09340511 47.18743058]\n",
+      "Rounded result: [53.37, 47.02, 53.09, 47.19]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [53.35770619 46.5238223 ]\n",
+      "Rounded result: [53.36, 46.52, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [41.12766984 12.        ]\n",
+      "True solution #1: [52.98691742 46.6817721 ]\n",
+      "Rounded result: [150.0, 150.0, 52.99, 46.68]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [53.95049606 46.88534191 53.64962539 47.05895731]\n",
+      "Rounded result: [53.95, 46.89, 53.65, 47.06]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [53.8676564  46.48347005]\n",
+      "Rounded result: [53.87, 46.48, 150.0, 150.0]\n",
+      "True solution #1: [53.48962351 46.63910189]\n",
+      "Rounded result: [150.0, 150.0, 53.49, 46.64]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [54.47436353 46.79615985 54.19211866 46.9669927 ]\n",
+      "Rounded result: [54.47, 46.8, 54.19, 46.97]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [54.34159024 46.46820413]\n",
+      "Rounded result: [54.34, 46.47, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [53.95565342 46.62133033]\n",
+      "Rounded result: [150.0, 150.0, 53.96, 46.62]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [54.94734959 46.71916227 54.65440099 46.88871912]\n",
+      "Rounded result: [54.95, 46.72, 54.65, 46.89]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [54.78406274 46.47154006]\n",
+      "Rounded result: [54.78, 46.47, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [44.13405362 12.        ]\n",
+      "True solution #1: [54.38939341 46.62180359]\n",
+      "Rounded result: [150.0, 150.0, 54.39, 46.62]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [55.39436812 46.67126232 55.09340892 46.82138317]\n",
+      "Rounded result: [55.39, 46.67, 55.09, 46.82]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [55.19795629 46.48854724]\n",
+      "Rounded result: [55.2, 46.49, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [45.13931861 12.        ]\n",
+      "True solution #1: [54.79354291 46.63544218]\n",
+      "Rounded result: [150.0, 150.0, 54.79, 46.64]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [55.80916977 46.62300128 55.50172846 46.77697315]\n",
+      "Rounded result: [55.81, 46.62, 55.5, 46.78]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [55.5846004 46.515185 ]\n",
+      "Rounded result: [55.58, 46.52, 150.0, 150.0]\n",
+      "True solution #1: [55.16923637 46.65798273]\n",
+      "Rounded result: [150.0, 150.0, 55.17, 46.66]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [56.17368606 46.57419567 55.86007472 46.72277313]\n",
+      "Rounded result: [56.17, 46.57, 55.86, 46.72]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [47.19130189 12.        ]\n",
+      "True solution #1: [55.94511254 46.54800065]\n",
+      "Rounded result: [55.95, 46.55, 150.0, 150.0]\n",
+      "True solution #1: [55.51771291 46.68585937]\n",
+      "Rounded result: [150.0, 150.0, 55.52, 46.69]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [56.50626384 46.53926777 56.19680216 46.68549166]\n",
+      "Rounded result: [56.51, 46.54, 56.2, 46.69]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [56.27954816 46.58379059]\n",
+      "Rounded result: [56.28, 46.58, 150.0, 150.0]\n",
+      "True solution #1: [55.83847967 46.71550159]\n",
+      "Rounded result: [150.0, 150.0, 55.84, 46.72]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [56.79962969 46.48615672 56.47423822 46.61429603]\n",
+      "Rounded result: [56.8, 46.49, 56.47, 46.61]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [48.49098707 46.50766218]\n",
+      "Rounded result: [48.49, 46.51, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [48.26285477 46.6659165 ]\n",
+      "Rounded result: [150.0, 150.0, 48.26, 46.67]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [49.05218949 47.25635994 48.7644896  47.47005479]\n",
+      "Rounded result: [49.05, 47.26, 48.76, 47.47]\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2d9550ebcc124d4d87cb1692725ff8a2",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/10 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [52.19339645 46.72253102]\n",
+      "Rounded result: [52.19, 46.72, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [51.8360612  46.88543791]\n",
+      "Rounded result: [150.0, 150.0, 51.84, 46.89]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [52.7300015  47.19412529 52.4588477  47.38074514]\n",
+      "Rounded result: [52.73, 47.19, 52.46, 47.38]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [52.80411215 46.59857577]\n",
+      "Rounded result: [52.8, 46.6, 150.0, 150.0]\n",
+      "True solution #1: [52.44013015 46.75887725]\n",
+      "Rounded result: [150.0, 150.0, 52.44, 46.76]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [53.3689562  47.02105264 53.09340511 47.18743058]\n",
+      "Rounded result: [53.37, 47.02, 53.09, 47.19]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [53.35769622 46.52381896]\n",
+      "Rounded result: [53.36, 46.52, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [52.98690307 46.68174374]\n",
+      "Rounded result: [150.0, 150.0, 52.99, 46.68]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [53.95049606 46.88534191 53.64962539 47.05895731]\n",
+      "Rounded result: [53.95, 46.89, 53.65, 47.06]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [53.86765497 46.48346765]\n",
+      "Rounded result: [53.87, 46.48, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [53.48962761 46.63908187]\n",
+      "Rounded result: [150.0, 150.0, 53.49, 46.64]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [54.47436353 46.79615985 54.19211866 46.9669927 ]\n",
+      "Rounded result: [54.47, 46.8, 54.19, 46.97]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [54.34153864 46.46822753]\n",
+      "Rounded result: [54.34, 46.47, 150.0, 150.0]\n",
+      "True solution #1: [53.95567146 46.62131738]\n",
+      "Rounded result: [150.0, 150.0, 53.96, 46.62]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [54.94734959 46.71916227 54.65440099 46.88871912]\n",
+      "Rounded result: [54.95, 46.72, 54.65, 46.89]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [54.78406254 46.47154682]\n",
+      "Rounded result: [54.78, 46.47, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [44.13441262 12.        ]\n",
+      "True solution #1: [54.38945493 46.6217935 ]\n",
+      "Rounded result: [150.0, 150.0, 54.39, 46.62]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [55.39436812 46.67126232 55.09340892 46.82138317]\n",
+      "Rounded result: [55.39, 46.67, 55.09, 46.82]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [45.25354377 12.        ]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [55.19787771 46.48854074]\n",
+      "Rounded result: [55.2, 46.49, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [54.79342102 46.63547607]\n",
+      "Rounded result: [150.0, 150.0, 54.79, 46.64]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [55.80916977 46.62300128 55.50172846 46.77697315]\n",
+      "Rounded result: [55.81, 46.62, 55.5, 46.78]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [55.58461276 46.515189  ]\n",
+      "Rounded result: [55.58, 46.52, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [55.16936212 46.65796432]\n",
+      "Rounded result: [150.0, 150.0, 55.17, 46.66]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [56.17368606 46.57419567 55.86007472 46.72277313]\n",
+      "Rounded result: [56.17, 46.57, 55.86, 46.72]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [55.94510134 46.54800045]\n",
+      "Rounded result: [55.95, 46.55, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [55.51762522 46.68584202]\n",
+      "Rounded result: [150.0, 150.0, 55.52, 46.69]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [56.50626384 46.53926777 56.19680216 46.68549166]\n",
+      "Rounded result: [56.51, 46.54, 56.2, 46.69]\n",
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [56.27958094 46.58378724]\n",
+      "Rounded result: [56.28, 46.58, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [48.00388852 12.        ]\n",
+      "True solution #1: [55.83849281 46.71549824]\n",
+      "Rounded result: [150.0, 150.0, 55.84, 46.72]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [56.79962969 46.48615672 56.47423822 46.61429603]\n",
+      "Rounded result: [56.8, 46.49, 56.47, 46.61]\n"
+     ]
+    }
+   ],
    "source": [
     "# WEST Antenna matched on vacuum condition in dipole (default) for a given frequency\n",
-    "f0_MHzs = [55.5, 57] # [48, 53, 55.5, 57, 63]\n",
+    "f0_MHzs = [48, 55.5, 57] # [48, 53, 55.5, 57, 63]\n",
     "delta_Cs = {}\n",
     "\n",
     "for f0_MHz in tqdm(f0_MHzs):\n",
     "    freq = rf.Frequency(f0_MHz, f0_MHz, npoints=1, unit='MHz')\n",
     "    ant_vacuum = WestIcrhAntenna(frequency=freq)  # default is vacuum coupling\n",
-    "    Cs_vac = ant_vacuum.match_both_sides()\n",
+    "    Cs_vac = ant_vacuum.match_both_sides(decimals=2)\n",
     "    \n",
     "    Rcs = np.linspace(0.4, 1.7, num=10)\n",
     "    Cs_plasmas = []\n",
@@ -73,7 +637,7 @@
     "    for Rc in tqdm(Rcs):\n",
     "        plasma = WestIcrhAntenna.interpolate_front_face(Rc, source='TOPICA-H-mode')\n",
     "        ant_plasma = WestIcrhAntenna(frequency=freq, front_face=plasma)\n",
-    "        Cs_plasma = ant_plasma.match_both_sides()\n",
+    "        Cs_plasma = ant_plasma.match_both_sides(decimals=2)\n",
     "        Cs_plasmas.append(Cs_plasma)\n",
     "        \n",
     "    delta_Cs[f0_MHz] = np.array(Cs_plasmas) - np.array(Cs_vac)"
@@ -81,21 +645,74 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "id": "adeffd01-319d-4240-afdd-0ffdad081ef2",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "ba5f90860dbd466599b25cdbe3caee5f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/3 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "fig, ax = plt.subplots()\n",
     "for f0_MHz in tqdm(f0_MHzs):\n",
+    "    fig, ax = plt.subplots()\n",
     "    ax.plot(Rcs, abs(delta_Cs[f0_MHz][:,0] + delta_Cs[f0_MHz][:,2])/2, marker='^', label=f'{f0_MHz} MHz - Top')\n",
     "    ax.plot(Rcs, abs(delta_Cs[f0_MHz][:,1] + delta_Cs[f0_MHz][:,3])/2, marker='v', label=f'{f0_MHz} MHz - Bot')\n",
-    "ax.set_xlabel('Coupling Resistance $R_c$ [Ohm]')\n",
-    "ax.set_ylabel('Capacitance Shift $\\Delta C$ [pF]')\n",
-    "ax.set_title('Capacitance Shift to add from Vacuum Match Points (55 MHz)')\n",
-    "ax.legend()\n",
-    "ax.grid(True)"
+    "    ax.set_xlabel('Coupling Resistance $R_c$ [Ohm]')\n",
+    "    ax.set_ylabel('Capacitance Shift $\\Delta C$ [pF]')\n",
+    "    ax.set_title(f'Capacitance Shift to add from Vacuum Match Points ({f0_MHz})MHz')\n",
+    "    ax.legend()\n",
+    "    ax.grid(True)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3fc64f2d-cde8-44df-90d1-11ff305f65a3",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/doc/chart_manual_matching_vacuum.ipynb b/doc/chart_manual_matching_vacuum.ipynb
new file mode 100644
index 0000000..9204ea1
--- /dev/null
+++ b/doc/chart_manual_matching_vacuum.ipynb
@@ -0,0 +1,297 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f2df5433-1df0-4ea1-b055-dffbc8993123",
+   "metadata": {},
+   "source": [
+    "# Manual Matching of a WEST ICRH Antenna on Vacuum"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "808b14fd-dc7e-412c-abfa-b3ca0254598b",
+   "metadata": {},
+   "source": [
+    "This notebook calculates the charts used in the internal documentation for the IC Operators for the manual matching on vacuum. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "14c9acaa-9f2e-4f89-bb51-6b9497c88ef6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "from tqdm.notebook import tqdm\n",
+    "import skrf as rf\n",
+    "\n",
+    "# WEST ICRH Antenna package\n",
+    "import sys; sys.path.append('..')\n",
+    "from west_ic_antenna import WestIcrhAntenna\n",
+    "#rf.stylely()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6c69f03f-a506-4d68-bdd7-f9e5fe758d4d",
+   "metadata": {},
+   "source": [
+    "# Matching each side separately\n",
+    "For a given RF frequency $f_0$, an antenna can be matched on the left side only, then on the right side only, before using both sides together and shifting the frequency depending on the phase excitation (see [Tutorial on Manual Matching](tutorial_matching_manual.ipynb). A further step can consist of slightly adjusting the four capacitors, to decrease the reflected powers seen by the generators.  \n",
+    "\n",
+    "This section calculates the frequency shift to apply depending on the phase excitation and the theoretical capacitance shifts to further apply for additional improvement."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "0f2d4877-46c6-44db-8501-c0363046fa8b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "f0_MHzs = np.arange(46, 66, 5)  # decrease the step size to get more precise plots"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "4d290673-ea1c-4f85-8a66-f54ee92a6121",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a0e3b6db34614336aad72328cece9d13",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/19 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# frequency scan for dipole and monopole\n",
+    "freq_shift_MHzs_dipo, freq_shift_MHzs_mono = [], []\n",
+    "C_vacuums, C_opt_dipoles, C_opt_monopoles = [], [], []\n",
+    "for f0_MHz in tqdm(f0_MHzs):\n",
+    "    freq = rf.Frequency(f0_MHz, f0_MHz, npoints=1, unit='MHz')\n",
+    "    ant_vacuum = WestIcrhAntenna(frequency=freq)  # default is vacuum coupling\n",
+    "    Cs_left = ant_vacuum.match_one_side(f_match=f0_MHz*1e6, side='left', decimals=2, verbose=False)\n",
+    "    Cs_right = ant_vacuum.match_one_side(f_match=f0_MHz*1e6, side='right', decimals=2, verbose=False)\n",
+    "    Cs = [Cs_left[0], Cs_left[1], Cs_right[2], Cs_right[3]]\n",
+    "    del ant_vacuum  # cleanup mem\n",
+    "\n",
+    "    # searching for the frequency shift to apply\n",
+    "    freqs = rf.Frequency(f0_MHz - 1, f0_MHz + 1, npoints=201, unit='MHz')\n",
+    "    ant = WestIcrhAntenna(frequency=freqs)\n",
+    "\n",
+    "    # dipole\n",
+    "    s_act = np.abs(ant.s_act(Cs=Cs, power=[1,1], phase=[0,np.pi]))\n",
+    "    f_opt_dipole = freqs.f_scaled[np.argmin(s_act[:,0])] # assume same at right\n",
+    "    freq_shift_MHzs_dipo.append(f_opt_dipole - f0_MHz)\n",
+    "    \n",
+    "    # monopole\n",
+    "    s_act = np.abs(ant.s_act(Cs=Cs, power=[1,1], phase=[0,0]))\n",
+    "    f_opt_monopole = freqs.f_scaled[np.argmin(s_act[:,0])]\n",
+    "    freq_shift_MHzs_mono.append(f_opt_monopole - f0_MHz)\n",
+    "\n",
+    "    # Finally determining the optimum set of capacitance\n",
+    "    # for the dipole or monopole case\n",
+    "    C_opt_dipole = ant.match_both_sides(f_match=f_opt_dipole*1e6, decimals=2, power=[1,1], phase=[0,np.pi], verbose=False)\n",
+    "    C_opt_monopole = ant.match_both_sides(f_match=f_opt_monopole*1e6, decimals=2, power=[1,1], phase=[0,0], verbose=False)\n",
+    "    del ant  # memory cleanup\n",
+    "    \n",
+    "    C_vacuums.append(Cs)\n",
+    "    C_opt_dipoles.append(C_opt_dipole)\n",
+    "    C_opt_monopoles.append(C_opt_monopole)\n",
+    "\n",
+    "freq_shift_MHzs_dipo = np.array(freq_shift_MHzs_dipo)\n",
+    "freq_shift_MHzs_mono = np.array(freq_shift_MHzs_mono)\n",
+    "C_vacuums = np.array(C_vacuums)\n",
+    "C_opt_dipoles = np.array(C_opt_dipoles)\n",
+    "C_opt_monopoles = np.array(C_opt_monopoles)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d12d6bb7-2f22-4d3d-b4af-fa56d2373fdb",
+   "metadata": {},
+   "source": [
+    "The frequency shift to apply for dipole and monopole configurations are:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "01247c63-ad55-4ddd-8aa3-08bbf368cace",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots()\n",
+    "ax.plot(f0_MHzs[freq_shift_MHzs_dipo>0.1], freq_shift_MHzs_dipo[freq_shift_MHzs_dipo>0.1], marker='^', ls='')\n",
+    "ax.set_xlabel('Initial match frequency (side by side) [MHz]')\n",
+    "ax.set_ylabel('Frequency shift to apply [MHz]')\n",
+    "ax.set_title('Dipole')\n",
+    "ax.set_xlim(46, 65)\n",
+    "ax.grid(True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "99d3385b-3f70-439d-9dd7-856544de6139",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots()\n",
+    "ax.plot(f0_MHzs[freq_shift_MHzs_mono<-0.1], freq_shift_MHzs_mono[freq_shift_MHzs_mono<-0.1], marker='o', ls='', color='C1')\n",
+    "ax.set_xlabel('Initial match frequency (side by side) [MHz]')\n",
+    "ax.set_ylabel('Frequency shift to apply [MHz]')\n",
+    "ax.set_title('Monopole')\n",
+    "ax.set_xlim(46, 65)\n",
+    "ax.grid(True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c474551a-ef4c-43a2-a72b-bfb4e65c116a",
+   "metadata": {},
+   "source": [
+    "The capacitor shift"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "8d6793fd-f53b-4f47-901f-3a9c6010ccbf",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "diff_dipole = C_opt_dipoles - C_vacuums\n",
+    "\n",
+    "fig, ax = plt.subplots()\n",
+    "ax.plot(f0_MHzs, diff_dipole[:,0], marker='o', ls='', color='C0', label='C1')\n",
+    "ax.plot(f0_MHzs, diff_dipole[:,1], marker='o', ls='', color='C1', label='C2')\n",
+    "ax.plot(f0_MHzs, diff_dipole[:,2], marker='o', ls='', color='C2', label='C3')\n",
+    "ax.plot(f0_MHzs, diff_dipole[:,3], marker='o', ls='', color='C3', label='C4')\n",
+    "\n",
+    "ax.set_xlabel('Initial match frequency (side by side) [MHz]')\n",
+    "ax.set_ylabel('Capacitance shift to apply [pF]')\n",
+    "ax.set_title('Dipole')\n",
+    "ax.set_xlim(46, 65)\n",
+    "ax.set_ylim(-0.2, +0.2)\n",
+    "ax.legend()\n",
+    "ax.grid(True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "41cfe253-886f-44c4-8132-5a6704ef47cc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "diff_dipole = C_opt_monopoles - C_vacuums\n",
+    "\n",
+    "fig, ax = plt.subplots()\n",
+    "ax.plot(f0_MHzs, diff_dipole[:,0], marker='o', ls='', color='C0', label='C1')\n",
+    "ax.plot(f0_MHzs, diff_dipole[:,1], marker='o', ls='', color='C1', label='C2')\n",
+    "ax.plot(f0_MHzs, diff_dipole[:,2], marker='o', ls='', color='C2', label='C3')\n",
+    "ax.plot(f0_MHzs, diff_dipole[:,3], marker='o', ls='', color='C3', label='C4')\n",
+    "\n",
+    "ax.set_xlabel('Initial match frequency (side by side) [MHz]')\n",
+    "ax.set_ylabel('Capacitance shift to apply [pF]')\n",
+    "ax.set_title('Monopole')\n",
+    "ax.set_xlim(46, 65)\n",
+    "ax.set_ylim(-0.2, +0.2)\n",
+    "ax.legend()\n",
+    "ax.grid(True)"
+   ]
+  }
+ ],
+ "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": "3.11.9"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": true,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": false
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/doc/tutorial_matching_manual.ipynb b/doc/tutorial_matching_manual.ipynb
index f114be2..013212d 100644
--- a/doc/tutorial_matching_manual.ipynb
+++ b/doc/tutorial_matching_manual.ipynb
@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -26,7 +26,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -42,7 +42,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -70,20 +70,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
-    "f0 = 55e6\n",
-    "freq = rf.Frequency(54, 56, npoints=1001, unit='MHz')\n",
+    "f0 = 55.5e6\n",
+    "freq = rf.Frequency(54.5, 56.5, npoints=1001, unit='MHz')\n",
     "ant = WestIcrhAntenna(frequency=freq)  # default is vacuum coupling"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "True solution #1: [49.96759955 47.93907206]\n",
+      "True solution #1: [49.73848215 48.10011089]\n",
+      "Left side matching point:  [49.967599548873835, 47.93907205854311, 150, 150]\n",
+      "Right side matching point:  [150, 150, 49.738482149208544, 48.10011089414825]\n"
+     ]
+    }
+   ],
    "source": [
     "C_match_left = ant.match_one_side(f_match=f0, side='left', solution_number=1)\n",
     "C_match_right = ant.match_one_side(f_match=f0, side='right', solution_number=1)\n",
@@ -100,9 +111,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x21136f19750>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 720x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "fig, ax = plt.subplots()\n",
     "ant.circuit(Cs=C_match_left).network.plot_s_db(m=0, n=0, lw=2, ax=ax)\n",
@@ -120,9 +152,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "True solution #1: [49.96759964 47.93907245]\n",
+      "Rounded result: [49.97, 47.94, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [49.73848167 48.10011115]\n",
+      "Rounded result: [150.0, 150.0, 49.74, 48.1]\n",
+      "Left side matching point:  [49.97, 47.94, 150.0, 150.0]\n",
+      "Right side matching point:  [150.0, 150.0, 49.74, 48.1]\n"
+     ]
+    }
+   ],
    "source": [
     "C_match_left = ant.match_one_side(f_match=f0, side='left', solution_number=1, decimals=2)\n",
     "C_match_right = ant.match_one_side(f_match=f0, side='right', solution_number=1, decimals=2)\n",
@@ -139,9 +188,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x211367af8d0>"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 720x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "fig, ax = plt.subplots()\n",
     "ant.circuit(Cs=C_match_left).network.plot_s_db(m=0, n=0, lw=2, ax=ax)\n",
@@ -165,9 +235,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Optimum frequency is f_opt=55.728 MHz --> 0.228 MHz shift\n"
+     ]
+    }
+   ],
    "source": [
     "# dipole excitation\n",
     "power = [1, 1]\n",
@@ -185,9 +263,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Dipole excitation')"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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N+diPPvqoz7k/+ugj+WEAPXr0kJ5++mnpxx9/lMrLy6WTJ09Ka9eule68807plltu8dqvtcnqn3zySfn6eP/996XKykrJ4XBIDodDcrlccjrPBxYsWLBA2rt3r1RSUiJ9++238rahQ4e2+DdqfKJUv379pB07dkhWq1U+l9vtltO154lJs2fPlnbu3CmVlpZKe/fulRYuXCiX06hRo1p8YpK/a91T4zlam1yfiJowCCWKcp5BaFt+Lr30Umn37t0tHrOtz45//vnnJZVK5fc8rT07fs2aNSF9dvzatWullJSUVstDrVZLZWVlLZZHIC+//LJkMBhaPUdKSoq8j9PplB+PmZycLJ04ccLvsWfNmiUB9Y/u3L59u8/21atXS3FxcS2et63Pjm9UVFQkpaen+z2W51OUzp07J/Xt2zfgeceNGyetW7euxb/Rxo0b5QCx+U97nh1fUVERtGfHt4RBKFH7sTmeKEZptVqkpaVhwIABuO6667B06VLs27cPX375JYYPHx6Uc/z617/G5s2bcd1116F79+7QarXIysrC/PnzsW/fvhZH3t9444348ccfsXDhQgwZMgRGoxEGgwH9+/fHnXfeib179+Kee+7pcN6mTp2Ko0eP4oknnsCECROQnp4OURQRFxeHfv364frrr8crr7yCwsJCeYBLe82bNw/Hjh3D4sWLcckllyA1NRVqtRpGoxGDBg3CLbfcgrfeekueGxUAli5diq+++gpA/QCkQANlnn32WfTv3x9OpxO33HKLz2j4m2++GUeOHMHDDz+MUaNGITExEVqtFpmZmbjsssvw+OOPyxPht1V6ejq+/vprzJ07F3379oVOp/Obrlu3btixYwfuu+8+9O3bFxqNBikpKbjkkkuwbNkybNq0KeDk8Y0mTpyIzz//HNOmTUP37t07/HSnxMREfP7553jjjTcwZcoUmM1maDQapKamYsKECXj++efx7bffokePHh06PhF1nCBJnNSMiIJnzpw5WLlyJcaPH48tW7YonR0iIopQrAklIiIiorBjEEpEREREYccglIiIiIjCjkEoEREREYUdg1AiIiIiCjuOjiciIiKisGNNKBERERGFHYNQIiIiIgq7jj2CggAATqcT7M3QRBAEiKLIcvGDZeMfy8W/qqoqCIKAhISEmCyX48ePAwD69OnjtZ7Xi38sl8BYNv6JoghBEJTOBoPQzigrK4PT6VQ6GxFDFEWYzWaWix8sG/9YLv698847EEUR06dPj8lymTZtGgBg8+bNXut5vfjHcgmMZeOf2Wzu8KNwg4nN8UREREQUdgxCiYiIiCjslK+LJSIiLzNmzIDZbEZRUZHSWVFE82Z4IopOrAklIiIiorBjTSgRUYQ5efIkqqqqkJCQoHRWFLFlyxYAQG5urqL5IKLQYhBKRBRh8vLy5NHxsWjJkiUAGIQSRTs2xxMRERFR2DEIJSIiIqKwYxBKRERERGHHIJSIiIiIwo4Dk4iIIkxCQgJ0Op3S2VBMVlaW0lkgojBgEEpEFGGuuuqqmJ6sfsWKFUpngYjCgM3xRERERBR2rAklIoow+fn5MJlM6NOnj9JZUURjTeicOXMUzQcRhRaDUCKiCJOfnw9RFGM2CF25ciUABqFE0Y7N8UREREQUdgxCiYiIiCjsGIQSERERUdgxCCUiIiKisOPAJCKiCNO7d28YDAals6GYcePGKZ0FIgoDBqFERBFm7NixMT1Z/ZIlS5TOAhGFAZvjiYiIiCjsWBNKRBRhtm3bBoPBgFGjRimdFUUsWrQIAGtEiaIdg1Aioghz6tQpiKIYs0Ho1q1blc4CEYUBm+OJiIiIKOwYhBIRERFR2DEIJSIiIqKwYxBKRERERGHHgUlERBEmOzsbJpNJ6WwoZvbs2UpngYjCgEEoEVGEyc7OjunJ6ufMmaN0FogoDNgcT0RERERhx5pQIqIIs27dOuh0OkyaNEnprCiisSZ0xYoViuaDiEKLQSgRUYSpqqqCKMbu7fnEiRNKZ4GIwoDN8UREREQUdgxCiYiIiCjsGIQSERERUdgxCCUiIiKisIvdnu9ERBEqJycHSUlJSmdDMYsWLVI6C0QUBgxCiYgiTGZmZkxPVp+bm6t0FogoDNgcT0RERERhx5pQIqIIs3r1aoiiiOnTpyudFUVMmDABALB582aFc0JEocSaUCIiIiIKOwahRERERBR2DEKJiIiIKOwYhBIRERFR2DEIJSIiIqKw4+h4IqIIM2XKFKSmpsLpdCqdFUUsX75c6SwQURgwCAVw+vRpLF++HIcOHYLRaMTEiRNx4403QqViRTERhV9iYiJSUlJidrL6vn37Kp0FIgqDmA9Ca2pq8Le//Q29evXCAw88gHPnzmHVqlWQJAkzZsxQOntEFIMqKyshirF7ez527BgABqNE0S5273INPvvsM9jtdvzud79DXFwcLrjgAtTW1uLtt9/GNddcg7i4OKWzSBQT3A4HJLsNUKkAQYAgCBA0GggqtdJZC7v169fH9GT18+bNA8DJ6omiXcwHobt378bw4cO9gs2xY8fi9ddfx/79+3HhhRcqmDuirkeSJLjrauGqqYazphqu6sr63zXVcNZUef121VRjf60F9soKuOtq/R5PZYiD2hgPtdEEMSERmpQ0aJJToUlJgzYlDZqUVGiS06CKM0IQhDC/WyIi6qiYD0LPnDmDYcOGea1LS0uDTqdDQUFBwP0kSYIguaGC1OLxBbThn2Jb/3G2KVnwztfef+hqtdrrNzVRsmwktxuS2wW4XJBcrvpllwtwN72uX9+QxumE225r+LHLryW7DW6bDW5H/TqXxQKXpQZOSzVclhq4rA3L1hrA5Qpa/t21VrhrrXCUFLaYTqXTQZOU2hCUNv1oU9KgSUqBJjkVYmISVDp9xAerjfmL1c9S4/tv3iWB9xj/WC6BsWwiW8wHoRaLBUaj0We90WhETU1NwP1qThzFd7+6MZRZixpS26LnNsXPbTpWMAOMNh3LN43gd3Vb8u674HsYoVkKP4kkqT7IdLnqX8cAt80GW2EBbIWBvzwCgEqjhSYhEdrEpPrfCcnQJCZBm5AITWISNPEJ0MQnNvxufB0PlagJ0ztp+oeZmpoatnNGksb3bzab/W6P1XJpTSyUiyRJDV+Y679c13/Jrv9Bwxdut8sNt9sNSXJDcjlRcfoUVJIEwS3BLbkhuaX67Y2/IcHtluqPI0lwu12Q3IAkueX1bskNSWr8Ui/VH9vjeJLUtK4+ff3+aEgLSPW34oZzQHLXV2E1pJMAwC3J7xGS1LC98bdbvpX7bJc3NJzTcz/U51neDjfgBsbeeAPiU5JD+8dqg5gPQgH/NX6SJEV8bUlXIbRSWyxrQ7I2HSs2Yi4AXeitCgLUxniI8fEQ4xMhmuKhNiVAm5iEBHN32NUiVEYTVDp9003V7YbbbpNrWp011XBWlMNeVgJHWQnsZSX1fUjbye2ww1ZaDFtpcbv2U+kN9fk2murfS8Pr+t/xEI0mqE3xPmlUekO77yUulwtqtRqlpaVwBbFWuatofM/NZwdQq9VITU2N2XIJpC3lIkkS4HLVt2w4HPWfLZsdtrpa2OvssNtssNfZ4LDZ4Gz4cTkc9X21nQ64nA2tJC5n/W+nE5LL2dCS4mxoaXECzvrXcLsAlxOC21X/43IBkhuCVB8soqE1UZDXeS8L8vam9SpJavv/E2rZlbkAg1DlGY1GWCwWn/VWq9VvDSlRrHFDgFMtwqHSwqHWwKHWwKnSoE7Uo05jQJ0mDpI+DkKcCeo4I0RTPPQmIwyJiYhPSUJSSjKSkxOQYtRCJ3pPeyaKIsxmM4qKito9J6YkSXBZauAoK4GjvASOslI4K8rgKC+FvbwUtoZlqboyOOVQVwt7XS1Q0r5pkySVGjAY64PsOBPURhM08QnQmeoDWM+gtf63Ce6GINTlcsXkXKGNNTuB3nuslYvkdsNltcBZXYXaqkpUl1XCWlkJW001HBYr3LZaqJxO1FVXwV1rhWCrA+y1UNnroLbXQXTYILpsULWzVUSFpifahK8dgGJJzAehGRkZOHPmjNe6kpIS2Gw29OzZM/COyemomvm7+qr5Zpsaq8g9fjWu9UorSd4rJD9p5OP4HN/3XP63S8021P+S/CSWfA/lfe6GJgC/+QEgCCpotRrYbTa4PQ7kk1/vhQDnlZqt88hj4/masuOv5LzO6/lS8nwPUv15JM9ljzxJcpNH0zkai0FqdkzJ42/ueYzGc6kEAa6GphhJaravV9qmc7glqb5Zx/edtcotqOEWVA0/argaX6ua1jVt90inUsGp0jQEnFq4BHX7uzjUNfwUSgDKGn4Ao1aFFIOIZIOIFIOIVKMWmek26Nx1SNAKSGlYr1ELchk5XBIsDhcsdjcsdhdq7C5U21yokn/0qLL1QJXdjCq1C9XxTtTo3JC612dF7XbCZKtGgq0ScXYL4hzWZr8bfuxWxDksMDisUDc2aQWB4HYBlipIliq4ALgA2AH4fvVtMgiApDPgu6/WQ0xJgyEtHXFpZmjT0qHr1gPa7hkQE5KitrUmVkbFux0OOMqKUVtagvLCYtQUl6C2tASOijJIlWVQW6og1tVAY7f6DSAFAFqPZa1PCuqK3B79q6SGz7jkZ528XvB4jcb0AATPeuOG1w19xSQhMuZBj/kgdMSIEfjoo49QW1sLg8EAAMjLy4NWq8XQoUMD7hefmIDcqyfH1Lfx1nSmVivadbZsGoNRl1uCS5LgcqPhd7PXzdM0vpYAh8sNh0uCzSXB4ZJgd7kbXrthd0kNP02vax1uWBuCP2vD6zpn55rC6gNJO05V2j3WlnTqmK1xqURUGpJRaWhj05MkQeuyw+CwNvzUNr121vqsj3NYoW94rXe1v3tAIIKtFig6A1fRGdQAaN5D3aWLg5DWA7oeGUjq3RvGvv1h6NMPmqSUoOWBOk+SJDhKClF+9ChKTp2GpeAMnMVnoS4rhK6mzCe41Df8KMkNoaHFQ4RLJcItqOp/q+q/uEoqNdwqNSSVGpJarP+tUkNSqwGVWP9bLQIqNaCu3wa1GhDUgEoFQaWCoBLqXwsqQKWGoBLqp2OTtzeu81xWQVDXL6vUanmbSqWCJNT/hkoFlUqApFJBBQFqUUR8vAkWq7WhokCoP27DNHAqldCwrj5PKgiASoBKEOqnilMJEAQVVILHfipV/b4C6s/XcEyVqn6f+gfdNKWH0Hg8FeoXVYCqfuByfUzYcEw0jSdoDDMb400BQv2+Hn+npmXBI533tkBfVOMC9LcOt5gPQidPnoz169fjySefxLXXXouioiK8/fbbmDZtGucIpYiharjhiSpla75cbkkOSGvsblTUOlFR50RlnQsVdU5UNP6udaGs1oFqe/BqFDtLL6pgEAVoRRW0aqHhRwWNWoBOLchlDDT+rr+Rqzz+I7jcEqrcEsrdEpyNAb9bgqPht9vpAuosUFlroKqzQG2zQG9vWzDrWftakZQOAEiqCNxvVW2zAmeOwHHmCIp3Ao0pncZEiL3PQ8rgIUgedgEM5w2CStO1GlO3bNkCAMjNzVU0H+0lSRLsRedQtG8vig8chP30cWiKTkLjqJPTBCvAdAkq1GriYBP1sIs6uDR6ODV6uLU6SFoDoDNA0Ovr+yTrDVDp9VBrdVBrtRC1Oog6LTQ6HUSdDlqdDlq9Djp9w2+dBhqVAI1agKgSoBYEqBW+93QUK0cimyBJfur4Y8zp06fx8ssvez2286abbmr1sZ28qL3xwx5YrJaNw+VGea0LZbVOlNc6Udbw0/i6os6FCpsL5VZHu46rUQlI0KmRoFfX/5Z/RMQ3vtarkahTy8sadfibnySpPkCtc7hR55RQ53LD5nTDYnej2tbQtcDuQk2dE1ZLLWzV1XBUVyGx+hDgcsF5rhqJdRUNP5VIqKuAKLVvQI5brYGUOQDmUaORemEOdD17RXwz/oQJEwD4NstH4ufIXlKEszu+QdEPu4DjP0Jn7VgfZDcEWLQmVOkTUReXCKcpGTAlQhWfAI0pHpqEBBgSEmBMTIQxOREJCfGI16kRp1HBoNNGXLlEiki8ZiKB2WyOiKeyKZ+DCNCrVy8sWrRI6WwQRR2NWgWzSQWzyX9NXOM/iDNnz6GkxlYfmNY64XRLDc1J9TUxRq0KJq0aRq0KRq0aOrUQ8YEUUN8U1ljjmtCO/d555xxEUcSVd96Bour6cim1OnCoxo7ys2dhKzgNqeQsTJWFSLMUo1vNWZjs/nuZqlwO4Nh+lB7bj9J3V8GZ0h3JF+WgR+5k6DN6B+eNxpjaU8dxYssmVO36FvqS0wAAXRv2s2iMKDWmwZpghiulG7TmHjD16IEEczqSzenoFa9Dsl7ssrWORO3FIJSIFKdRq5Bu1CDd2LWajUMtXifCoAaykjxCnOFmAMMBADU2F87W2HGivA6HTp1D9bEjEM4cQ7fyE8iqOA69s87nmGLZOVRveA/VG96Dq3d/9Lp8ClIvndjlmuzDzVVrRcGm/+Hcls+gKzwBIHDTuhsCik3dUJLcG+7umTBmnQfzgH7o3TMdF5o0itTKE0UiBqFERF2USafGAJ0BA1INQP9kYMIQuCUJBVV27C+04MT+H1F3KB89zh3EeaWHfZry1acO4+wry3Dq7VUwX3ktelwxFWoD+8J7spcU4djH78Hy1ecQHXV+azzdEHA6KRNlPQZB138IMs7PxqjMNKTGMbAnagmDUCKiKKISBPRK1KFXog4YeAkk6WKcqbJjx5FinNn5LZIPf4/BRfnQuJv6x4k1FSh7dyWK1r2Lnr+4Dd0mTYEQ4485dFZV4ug7b8C69VOo3C6ff5YOlYifzENRN2g0el00BpcO6IEkA/+lErUHPzFERBEmISEBOl1behm2TmgMSkf1Akb1Qon1anyxvwBntm7BkMNfolvNOTmtWFuDoteeR8GGjzHorvtg7D84KHlor6ysLEXOC9RPDH/2s3U49/ZKiPZaNG84P5HUB0VDLsV548fj2gHdYNCwaZ2oozg6vhM42s4bRyEGxrLxj+XiXzjKRZIk7CqoQd5nW5G561P0KT/mvV0QkHDlDci66TaoxMhoVg51udgKz+Lgs/+CcPyg13o3BOzvMRyOsVdhUu5o9EoIzheEYOHnKDCWjX8cHU9ERIoRBAGjMuIxas5UHLhqAj77ZAuGfvsOzJb6x5IKkoTqT9/F3oP5GPq7P0OTqPxzpkOp/LtvcOw/T0K013qtP2geBtvkmzFt3AVIZnM7UVDxE0VEFGHy8/NhMpnQp0+fsJxviDkOg+dMwbbxl+DLt1bjkoOfyoOYhOM/Yu/D92Lw7x9BXJ/+YcnPihUrAABz5swJ+bkkScLJd15H5cervf4hlhuSsXfsrbjuugkRV/NJFC3YmYWIKMLk5+dj586dYT2nIAi49Lxk3H7/ndh+/UMoMjY91k+sKsPBpQ/C8tOBsORl5cqVWLlyZcjPI7ldOPzfZ1D58Wqv9bt6Xwzbgidwz+1XMgAlCiEGoUREJEvQqXHXtWPguHspDqYPldeL9locevzPYQtEQ02SJPz0wv9D7Zcb5HUOlYhNF96CCQ/8AVcM694lHohA1JUxCCUiIi+CIGDK+T0x8P6/YGefS+X1aocNPz6xBLZzZxTMXXAcf/1l1H29UV6uFQ348sqF+NX8m5GZyNpPonBgEEpERH6NyIjHpQsW4Jt+ufI6sa4G+/7+FzhrqpXLWCed+3wdqv/3gbxs0cTh26t/j3tuGgeTNrbnRyUKJwahREQU0MC0OIy/527s7nWRvE4sL8KB5/4PXXGGP8vhH3HutRflZZtah2+vXIC7rh3Dx2kShRk/cUREEaZ3794477zzlM6GbGBaHAb9egGOpAyQ10n5O1Cw/sOQnG/cuHEYN25c0I/rslpw6N+PQdXwtCg3BGy99Je48/ociCr2/yQKN07RREQUYcaOHStPsB0pfpaVjPdnLkD1Sw8h3l7fFF/09kqkjf4ZdN16BPVcS5YsCerxGh1Z9V+oq0rl5W2Df45ZMybzqUdECuEnj4iI2uTaMX3wXe48uFFfa6h2OXDwxWVdolm+On8X6rZ9Ji8fSRmAi2+/HenGyHgaFFEsYhBKRBRhtm3bhk8//VTpbPhQCQJuvSEXu7Jy5HXCT3tQ+vUXQT3PokWLsGjRoqAdT3I6cfi/z8rLNrUWFdN+idG9E4J2DiJqPwahREQR5tSpUzh69KjS2fArNU6DbtNnoVobL687/uYKuJ2OoJ1j69at2Lp1a9COV7hxPdRl5+TlbcOuxs3jhwTt+ETUMQxCiYioXa48vye+H32DvKytLMHZjZFXcwsArlorCt5/Q14uNHXDmF9chzgNp2IiUhqDUCIiahe1SsCE66fgnKlpQNK5D96C21anYK78K1j3IURr05ym+y+8AZf0SVIuQ0QkYxBKRETtlt3dhCMXXSMvaywVOLv5fwrmyJfbbkfxZx/Ly8eSz8PEq3L5OE6iCMEglIiIOmT8VRNxJqGXvHz2048hud0K5shbyZefQ7RWycunL5qG87sbFcwREXniPKFERBEmOzsbJpNJ6Wy0amg3I7664HJkfLUCAKAtO4uq/F1IvGB0p447e/bsTudNcrtxeu178j+5s/E9MXZiTov7EFF4sSaUiCjCZGdnY8yYMUpno03Ov3yS10j5Y2s7/xSlOXPmYM6cOZ06Rs3+HyCWNo2IPzh0Eob3YC0oUSRhEEpERB02pk8S9vX1mDf04C7YS4sVzFG9Exub+qdWa+Mx5PJJ7AtKFGEYhBIRRZh169bhzTffVDobbaJWCUidOEV+ipIACWe+2NipY3a2JtRVa4Xjh2/k5QO9RmF8v5RO5YmIgo9BKBFRhKmqqkJ5ebnS2Wiz3OFZOJI2UF4u/WpTpx7leeLECZw4caLD+5dt/xJqp11eVl2YC53If3dEkYafSiIi6pTUOA3KhlwiL2tLClB38phi+Tmz5fOm1wkZuOiioYrlhYgCYxBKRESd1mfspbCrNPLy6byvFMmHs6oSwvGD8vJPWWMwzBynSF6IqGUMQomIqNMu6Z+OI+mD5OWK775WJB/lu3ZA8OgKkDYmByoOSCKKSAxCiYio00xaNaoHNM0Pqis6BVvh2bDno+CbPPn12fieuHBYn7DngYjahpPVExFFmJycHCQlJSmdjXbrMeZiuLatglqqf2pS8XffoNdV17X7OIsWLerQ+d12O9w//gB1w/LxHtmYnKrv0LGIKPRYE0pEFGEyMzPRv39/pbPRbhf1745TSVny8rnvv+vQcXJzc5Gbm9vu/SwH90LtsMnL6uwL2RRPFMEYhBIRUVCYTRoUZzSNRFcf3Q+30xG285/b0TQ3aJUuAYMu4Kh4okjGIJSIKMKsXr0azz33nNLZ6BD90BHya7XTBstPB9p9jAkTJmDChAnt3q9y/x759eG0QRiZEd9CaiJSGoNQIiIKmv7nD4VV0zQl0rldu8JyXmdVJbTFp+XluqwhMOnULexBREpjEEpEREGT3cOEE8l95eWKg/lhOW/NgT1ey8nZw8NyXiLqOAahREQUNEatGpaMpkd4iqcPh6Vf6LkfdsuvS+PSMKhfr5Cfk4g6h0EoEREFlWGgx+AkpwO1x4+E/Jw1Hn1Pj6ech0FphpCfk4g6h0EoEREFVeaQQbCrmx7hWZq/N6Tnc9vqoCk6JS/bMgbAoOG/N6JIx8nqiYgizJQpU5Camgqn06l0VjpkUPd4fJmYhX5lhwEAJYcOIrMd+y9fvrxd57Me+8nrUZ3xAwa3a38iUga/KhIRRZjExESkpKQonY0OS4vToDytadJ618n2Ncf37dsXffv2bT1hg4qDTU3xdaIevfu3fV8iUg6DUCKiCFNZWYmysjKls9Ep6symJz7pqkrgrK5s877Hjh3DsWPH2py+9MemIPR0YiYGpMe1kJqIIgWDUCKiCLN+/XqsXr1a6Wx0SmL/gV7L1mOH27zvvHnzMG/evDand3rUtBalZKK7SdNCaiKKFAxCiYgo6LL6ZMCiMcrLJT/+GJLzOKuroKluqjUWep0Hgc+LJ+oSGIQSEVHQnZeix5nEprk6Kw4fCsl56k55N9sn9e0XkvMQUfAxCCUioqBL1IuoTGkKQl1nT4bkPJVHm5ri60Q9MrIyQnIeIgo+BqFERBQS6p5NI+S1FcVw2+qCfo6yI019Tc+ZeiArhZPUE3UVDEKJiCgkTL37yK8FSKg7E/zaULtHc3xRYk/0jNcG/RxEFBqcrJ6IKMLMmDEDZrMZRUVFSmelU8x9+8AlqKCW3ACAmhPHEXfewFb2AjZv3tym40suF9QlBfKy3ZwJtYqDkoi6CtaEEhFRSPROjUNpXLq8XHL0aFCPbys6C5XbJS/rM9rzXCYiUhqDUCKiCHPy5EkcPtz2eTUjVc94LYriu8vLtaeOt2m/LVu2YMuWLa2msxWc8lpOzWIQStSVsDmeiCjC5OXlQRRFTJ8+XemsdIpOVMGSkgGc+wEAIBWdadN+S5YsAQDk5ua2mK7yZFMf0xqtCRndUzuWUSJSBGtCiYgoZMRuPeXX2pryoI6Qrzx5Qn5dbDQjI4GDkoi6EgahREQUMvEZvbyWbYUFAVK2n/3safl1qakbzEY+rpOoK2EQSkREIZPc2zsIrT0bnCBUkiSoPEbG21J7cmQ8URfDIJSIiEKme2oCqnQJ8nLFqeDMFeqsLIfa3tS0r+7GJyURdTUcmEREFGESEhKg0+mUzkZQdDdp8FNcOhJsVQCA6jOtD07KyspqNY296JzXsqlnzwApiShSMQglIoowV111VVRMVg8AKQYR5aZ0oLz+Ge+OwtaD0BUrVrSapq7wrPzaJaiQ1rN7C6mJKBKxOZ6IiEJGEAQ4U5oCRFXJuRZSt12lR41qpT4ZPZPignJcIgofBqFERBEmPz8f3377rdLZCBpVWlMQKtbVwFVrbTH9ihUrWq0NrTnXVBNaFpeKbiaOjCfqahiEEhFFmPz8fOzcuVPpbASNsZt3U7mjtOVuBitXrsTKlStbTOPw6BNaEZeCFAN7lxF1NTH/qV28eDH279/vs/61116DVsuJj4mIOiupWX9NW3Eh9L36dOqYQlmh/NqeaOb0TERdUMwHoQAwbNgwzJw502udRsOmHSKiYDCnJaFW1MPgrJ9SqfpcIRI7cTxXXS1Ea1XTitRuncsgESmCQSgAk8mEgQMHKp0NIqKolGbU4IAhBYbq+snlqz36c3ZE8+mZdGaOjCfqitgnlIiIQiotTkSFIVlerisqbCF16+zN+pTGd2cQStQVsSYUwJ49e3DbbbcBAIYMGYLbbrutTZMlq9XqUGetS2ksD5aLL5aNfywX/zIzM6HX66OmXBJEETXGVHnZVVYMUQz87yc3NxcAfNI0loe9tFReZ1NrYU5PafF40Y6fo8BYNpEtdj+1DYYOHYrx48eje/fuKC4uxvvvv49HHnkETzzxBMxmc4v7pqamtrg9VrFcAmPZ+Mdy8XbdddcpnYWgk1K7AcfqX6sqSlq8v77wwgstHstWUSG/rtIn4YLMbjCbk4KQy66Nn6PAWDaRKeqCUKvVivLy8lbTZWTUP2f4pptuktcNGTIEF1xwARYuXIh169Zhzpw5LR6jtLQULperU/mNJmq1GqmpqSwXP1g2/rFc/IvKcklKk1+KtdU4e+I41Ib2TTAvl4vH8+cr9EkQHTUoKrIHLatdTVReL0HCsvEvJSUyWg+Uz0GQff31161+iwaANWvW+F2flJSEQYMG4dixY60ew+Vywel0tjuP0Y7lEhjLxj+Wi7dt27bBYDBg1KhRUVMu+tQ0r+Xa4kLoe/b2m3bRokUAgCVLlvjdbispkv95VemTEK8RoqacOoOfo8BYNpEp6oLQSZMmYdKkSUpng4iow06dOgVRFDFq1CilsxI0pvR0r2VHeWnAIHTr1q0tHksqL5Ff20zJEDlHKFGXxNHxzVRUVODHH3/Eeeedp3RWiIiiRkpaCpxC0+CQOo/BRe0hud1QV5fJy+6ktBZSE1Eki7qa0PY4ceIE3njjDVxyySVIS0tDSUkJPvjgAwiCgKlTpyqdPSKiqJFm0qJEF4+kugoAQE1xMdJb3sUve2U5VK6mZlV1MoNQoq4qpoPQ+Ph4AMAbb7yB6upqGAwGDB06FH/4wx+QlsYbGxFRsCQbRBzVJ8pBqKWkuEPHaT7HqC61I6EsEUWCmA5CU1JS8OCDDyqdDSKiqJdiEFGla3pYp72sY83xdSXeQagxnUEoUVcV00EoEVEkys7OhslkUjobQaUTVaiNawpC3RWBg9DZs2cH3FZX2lSDWivqkZJoDE4GiSjsGIQSEUWY7OxsmM1mFBUVtZ64C3HGp8ivharA8zm3NEdzZWFTEFqji0dqnCYoeSOi8OPoeCIiCo+EpiBUtFZC6sDk4VUefUKrtQlIiWNdClFXxU8vEVGEWbduHXQ6XdTNeaxJ8qgJlSQ4KsuhTfEdBNpYE7pixQqfbbUlzWpCDfw3RtRV8dNLRBRhqqqqIuKResGmS/F+frezvNRvEHrixImAx3BUlMlNeFZ9AuI0bNAj6qr46SUiorAwpqZ4LTurKtp9DKmyaUCT05gIQeDTkoi6KgahREQUFkmJJjhUTTW89oqKdu0vud1Q1VQ2rUhIDlLOiEgJDEKJiCgsUuI0qNHGy8uWsrIWUvty1lRBcDcNZlIlJAUra0SkAAahREQUFskGETW6pvlPreWBp2nyx1HhHbR6DnQioq4n+nq+ExF1cTk5OUhKSlI6G0GXqFPDom0KQu0V/oPQRYsW+V3vbJZen8wglKgr61AQ+s4773TqpOPGjYPZbO7UMYiIolVmZmZUTlZv0qlh0TU1xzurK/2my83N9bvesybUKagRn5zoNx0RdQ0dCkLffvvtTp108ODBDEKJiGKMShDgMCTIy1KAIDQQz4FMFq0JiXo25hF1ZR3+BM+ePRsXXXRRu/apqanBn/70p46ekogoJqxevRqiKGL69OlKZyXoXMam2kuvke4eJkyYAADYvHmz13qrR3O8VWtEd05UT9SldfgTnJCQgPT09Hbto9frO3o6IiKKBvFNQahYVwPJ5YKgVrdp19rmNaG6tu1HRJGpQ0Hon//8Z/Tu3bvd+8XFxeHPf/4z+vbt25HTEhFRF6eOT/JadlZXtnmUu72yQn5t0RqRxJpQoi6tQ5/g888/v0MnU6vVHd6XiIi6Pk1ikteys7KizUGos7pK/qdl1ZgQr2VNKFFXFpJ5Qt1uNwoKCnDkyBHYbLZQnIKIiLogQ7L3U46cle2YK7Smqmm/uHioVXxkJ1FX1qm2jJ07d2LLli0QRRGTJ0/GsGHDcPDgQTz33HMoLCwEAGi1Wtx8882YNm1aUDJMRERdlzExHm4IUEECUP8UpLYSrE1ppbj4FlISUVfQ4SA0Pz8fTzzxhLy8Y8cOPPzww/jnP/8JURQxevRouN1u/Pjjj1i1ahW6d++OCy+8MCiZJiKKZlOmTEFqaiqcTqfSWQm6BL0GtZo4GB0WAICj2jcIXb58uc86t8MBtb2uaYUpwScNEXUtHQ5C161bB5PJhLvvvhtJSUl45ZVXsGzZMqSlpWHJkiUwGo0AgIqKCjz44INYv349g1AiojZITExESkpK1E1WDwCJehGl2qYgtLbSNwj1N3jV1WxOURWDUKIur8N9Qo8fP45JkyZh9OjR6NevH2bOnImysjJceeWVcgAKAElJSZgwYQKOHTsWlAwTEUW7yspKlJWVtZ6wC0rQqWHVNP2PqKv0nSv02LFjPv8znM1qTDUJDEKJuroO14SWl5ejR48e8nLja39PQjKbzbBarR09FRFRTFm/fn3UTlafoPcOQu1+muPnzZsHwHuy+uZBqC6Bj+wk6uo6XBPqdruh0Wjk5cbXaj+TDqvVakiS1NFTERFRlEjUqWHVxsnLzYPLQDyfM++GAH0ia0KJurqQTNFERETkj0atgk3bVBPqtlS3aT/PPqFWbRzidZoWUhNRV9CpKZp27Nghd5y32+0AgC+//BKHDh3ySnf8+PHOnIaIiKKI22BqWrDWtGkfR5VHEKoxIZ6P7CTq8joVhG7fvh3bt2/3Wrdly5bOHJKIiKKcZxCqqm1bEFpb1dRsb9XGIZ1BKFGX1+EgdNGiRcHMBxERxQjB2DTRvNphg9vhgErTcvO6vbqp2b5WE8dHdhJFgQ4HoUOHDg1mPoiIqMGMGTNgNpujcp5QAFAZvZ925Kqpgio5VV72HBXfyFHjEYSKBjbHE0UBDkwiIqKwEuO9g1BnTeuDk1yWpmb7Wk0cTKwJJeryOtUnlIiIgu/kyZOoqqpCQpROyK6N935frmbTNDWOLcjNzZXXSR4DmGzaOOhFIWT5I6Lw6FAQevPNN7d7H0EQsHr16o6cjogopuTl5UXtZPWA70TzzhrvIHTJkiUAvINQ1Frkl5LBCEFgEErU1XUoCB03bpzPDeDYsWM4efIkunfvjl69ekGSJJw5cwbnzp1DZmam32cBExFR7DEatKhT66B32QAArlaa4yW3G6q6piBUFWdqITURdRUdCkLvuecer+V9+/bh66+/xr333oucnByvbdu2bcMLL7yAuXPndjyXREQUNUxaNWo1cXIQ6mxlwnp3XS0Ej6fuCQxCiaJCUAYmvfXWW5gwYYJPAAoAY8eOxfjx49kUT0REAACjVoU6jUFettdYWkjtPSgJYE0oUbQIShB67Ngx9O7dO+D2zMxMHDt2LBinIiKiLs6kVaNO1MvLtlaa45vXlKpN8QFSElFXEpQgVKvV4siRIwG3Hz58GFqtNhinIiKKegkJCUhOTlY6GyFj0qqb1YR613RmZWUhKytLXm5eE6plEEoUFYIyRdPIkSOxZcsWZGVl4YorroBaXT9/m8vlwoYNG/DFF1/g0ksvDcapiIii3lVXXRXVk9UbtSrUik1BqNPi3Ry/YsUKr2WfIDSezfFE0SAoQejtt9+On376CStWrMDbb7+N7t27AwDOnTsHi8WCbt264bbbbgvGqYiIqItrXhPqrm17n9A6UQ+jni1rRNEgKEFoYmIi/vGPf+DDDz/Et99+ixMnTgAAunfvjiuvvBJXX3014uLignEqIqKol5+fD5PJhD59+iidlZDQiSrYPYNQq/+a0Dlz5gBo9rQk0YA4DR/2RxQNgvbEJL1ej5tvvrlDE9kTEVGT/Px8iKIYtUEoAEj6pooJoVlN6MqVKwE0BaGej/Ws1cTByEd2EkUFfp0kIqKwk/RG+bVgs0LymAe0ObtXEGqAkTWhRFGhQ5/kzz//HOfOnWv3fg6HA59//jnKy8s7cloiIooWhqYgVOVyQnLYAyb1DELrNAbEsSaUKCp0KAh96aWXcPjw4XbvV1dXh5deeglnzpzpyGmJiChKCAbvcQIua+DBSU6LVX5dJxpgYhBKFBU63Cf0zJkz2L9/f7v2sVqtrSciIqKopzJ6T7PksligSUrxm9bl0We0TtRzYBJRlOhwEPree+/hvffeC2ZeiIgIQO/evWEwGFpP2IWp44xeyy5r0wj4cePGeW1z11ohNLy2ifqGgUmB+5ASUdfQoSD0rrvu6tRJe/Xq1an9iYii2dixY6N6snoA0Jqa1YR6NMcvWbLEa5tU5x2EGjQquF2uUGeRiEKsQ0Fobm5ukLNBRESxRGswwA0BqoYazZb6hKKuqSuXpI+DShDgDnUGiSjkgjZPKBERBce2bdtgMBgwatQopbMSMnFaTX3/TmctAO8J6RctWgSgvkZUcjqh8hg5Lxi8m/GJqOtiEEpEFGFOnToFURSjOgg1aFT10y01BKGeT03aunWr/NpV6z2gVRXHIJQoWnCIIRERhV2cRoVaj0d3Oi3VftM1D0LFZqPqiajrYhBKRERhZ9CoYFPr5WVnba3fdO5mQaiWQShR1GAQSkREYRenUcEmNgWh9gADk1zNnisvmhiEEkULBqFERBR2Bo0KNlEnLzsDPMzE1Wy91hQf0nwRUfhwYBIRUYTJzs6GKcpr/AzNakI9g9DZs2fLr90eNaEuQYW4KJ/EnyiWMAglIoow2dnZUT9ZfZxG7RWEuuua+oTOmTNHfu05MKlO1MOg478tomjRoU/zPffcA0EQWk/YAkEQsGzZsk4dg4iIuqa4Zs3xUp3/5ni3Rw2pTTQgTqMOed6IKDw6FIQOHTq000EoERH5t27dOuh0OkyaNEnprISMTi3A7hWE+taErlixwmtgUp2oR7yWQShRtOhwTSgREYVGVVUVRDG6m50FQYCka+rfKdiagtATJ07Irz0f52kTdejGmlCiqMHR8UREpAivINTlhNvh8EnjOWCpTjTAwJpQoqgR0iB0x44doTw8ERF1YSp9nNey20+/UIdnTahGzz6hRFEkpEHoM88843f9sWPHQnlaIiLqAlTNplty+XlqktPq3Sc0Thvd3RSIYklIgtCNGzfi6NGjAbcvXrw4FKclIqKupHlNaK1vTajnOptahzg2xxNFjZB8pdy6dStWrVqFuro63H///TjvvPPkH0mSoFKFvitqXl4e8vLycOjQIVRUVODuu+9Gbm6uT7qysjK8/PLL2LNnD7RaLXJycnDbbbdBp9P5HpSIKAxycnKQlJSkdDZCTm3wDkIb5wRdtGiRvM5dVye/tos6GDRqwB6e/BFRaIUkCF2yZAkkScKsWbMwc+ZMHD16FD/88AM++OADWCwWXHvttaE4rZft27ejuLgYo0aNwqZNm/ymcblcePTRRyGKIu677z5YLBa8+uqrsFgsWLBgQcjzSETkT2ZmZtRPVg8Aap8+ofXN8Z4VBpLHqPnGmlAHg1CiqBCyzjWCIOC5555DfHw8LrroolCdJqCFCxdCpVKhrq4uYBD69ddf4/Tp01i2bBnMZjMAQK1W4+mnn8aNN96IHj16hDPLREQxRaPXwQ0BKkgAvJ+O1Eiy1aFxVmpbQ02o7xh6IuqKQtou/tZbbyE/Pz+UpwioLU3+u3fvRv/+/eUAFADGjBkDURSxe/fuEOaOiCiw1atX47nnnlM6GyGn16i9nprU2P9zwoQJmDBhAiSnE4KzKeR0iDroRM4sSBQtQjrM8Ouvv8Ytt9zitS4/Px8nTpzA1KlTQ3nqNjlz5gx69erltU4URXTr1g1nzpxpdX+1mh3kPTWWB8vFF8vGP5aLf41PpIv2cjFoRdhEPQzOhn6ftjqIoii/f88AFACgM0AQhKgvl/bi5ygwlk1kC2kQqlKpfAb49OnTB88++2xEBKEWiwVGo9FnvdFohMVi8bOHt9TU1FBkq8tjuQTGsvGP5eKt8R9mtJdLWpLVqyZUr1bBbDbL7z/Z6N1nVG2ov19He7l0FMslMJZNZAppEJqZmYkffvgBo0aNkteZTKY2BXjNWa1WlJeXt5ouIyOj3cf2p/GbeEtKS0vhcrmCcr5ooFarkZqaynLxg2XjH8vFP5fLBbVaHfXl4qyzQhL18nJVSTGKiork91x05pT3Dtr6gDXay6W9+DkKjGXjX0pKSkQ8GjikObjhhhvw73//G3fccQfGjBkDANizZw+Sk5Pbfayvv/4aL7zwQqvp1qxZ0+ZjGo1GWK2+HeEtFguysrJa3d/lcsHpdLb5fLGC5RIYy8Y/los3SWoYqBPl5aJRAdXqpppQp6UGTqdTfv+OZhUWgr4+YI32cukolktgLJvIFNIgdNiwYZg7dy5eeOEFvPLKKzCZTCgoKMAdd9zR7mNNmjQJkyZNCmr+MjIyfPp+Op1OFBYWYvLkyUE9FxERedOLKpR41IQ2Hx3f/AlKot77CUtE1LWFvC42JycHo0ePxr59+1BTU4O+ffuid+/eoT5tm4wYMQJfffUViouLkZ6eDgDYuXMnnE4nRowYoWzmiChmTZkyBampqVFfc6MXBa8+oc6GoHP58uUAAHfpWa/0Ypx3H1Ei6trC0iFAp9N59QsNh9OnT+P06dOw2+tnNT5y5Aj0ej0SEhIwdOhQAMDFF1+M999/H08++SRuvvlmWK1WrFy5EmPHjuUcoUSkmMTERKSkpET9ZPV6UQW7R3N8Y01o3759AQDlBcfkbU5BzSfZEUWZkAahu3fvxn/+8x9YrVZkZmaib9++8uM7+/TpE8pTIy8vD++88468vGHDBmzYsAFDhw6Vn10viiIeeughvPzyy3jqqaeg0WiQk5OD22+/PaR5IyJqSWVlZUQMGgg1naiC3aMm1NXwiM5jx+qDz3iP5vj6R3ZyjlCiaBLSu9yqVatw5ZVXIicnBw888AAGDhyIl19+GaIoYuXKlaE8NW666SbcdNNNraZLTU3FAw88ENK8EBG1x/r16yGKIqZPn650VkJKL6pg86gJbXxs57x58wAAb/3uHnmbTa2DnhPVE0WVkAahxcXFuP766+XJhWfPno3u3bvHxDd8IiJqWfM+oW6b90CkxqAUAOyilk9LIooyIf1EG41GuU+mTqeD0+nExIkT8dFHH4XytERE1AXomvUJha3Oa7tnEGpT66ETW5+/mYi6jpAGoUOGDMGuXbsAAL1798aBAwfgdDpRVlYWytMSEVEXoG/WJxROBySPGQFcdd59QnVq1oQSRZOQtovfc8898tORpk6diqeffhrx8fEYNGhQKE9LRERdgFYtePUJBbwDT6/meLUWJjbHE0WVkAaharUaCQkJAOrn5PzTn/6EY8eOIScnJ5SnJSKiLkAlCJC0eq917gBBqE3UsTmeKMp0+GvlmjVr8Nvf/jZg03pJSYnPM+L79++PyZMnw2g0dvS0RERRb8aMGbj77ruVzkZYCDrfIHTz5s3YvHmzV62oTc3meKJo0+Ga0H379kGv1yMlJcVr/alTp/DEE0+gsLAQgiBg1KhRmD9/vlwjSkREJGv2KE7PwNPVbJ5Qjo4nii4d/kQXFhb6fbTlCy+8gMLCQsTHxyM1NRXfffcdHnvsMbjd7s7kk4goZpw8eRKHDx9WOhthofJTE7plyxZs2bLF61nydrUOWjWb44miSYdrQqurq9GtWzevdQUFBfjpp5/Qv39/LFmyBKIoYuPGjXjxxRexadMmXH755Z3OMBFRtMvLy4uJyeoBQNWsJtRdW4slS5YAAJYN7Smvt7EmlCjqdPgTLYqiPAdooz179gAAJk+eLE9IP2nSJAwePBh5eXmdyCYREUUjrU4Lp6CWlz0nrPceHc8nJhFFmw5/onv27IkjR454rcvPzwcADB8+3Gv9iBEjcPLkyY6eioiIolTzpybJfUIlCXA0VXTYRDbHE0WbDgehF110EbZv3y73W7Jardi7dy969uyJ5ORkr7RJSUmwWq3+DkNERDFM12zCenfDYCRJkrzS2dRsjieKNh3uE3rVVVdh48aNWLx4MQYPHoySkhLU1dXhkksu8UlrtVoRFxfXqYwSEVH00aq9H90pN8FL3oNZOTqeKPp0+BOt1+vxl7/8Bb169cLevXtx9uxZZGRkYOrUqT5pjxw54lM7SkRE/iUkJMTMPVOnbtYcb6tFVlYWMnv29EpnV+ugY3M8UVTp1BOTunfvjscffxwFBQWw2Wzo3bu3PCCpkdVqxc6dO3HppZd2KqNERLHiqquugtlsRlFRkdJZCbnmj+5019ZixYoVsB75EYeX/E5e79DoIKoYhBJFk6A8trNns2+snk6ePIn+/fvjwgsvDMapiIgoimjVzfqENjTHu211XukkrQGCwCCUKJqE9NnxADB48GA88sgjoT4NEVHUyM/Ph8lkQp8+fZTOSshpRQFWz5pQWx1WrFiB2pPHMNYjnaDX+e5MRF1ayINQIiJqn/z8fIiiGBNBqE6tQoVnn9DaWqxcuRIuqwVjB5nr1wkqqDUMQomiTYeC0HvuuafTzSKCIGDZsmWdOgYREXVtPn1C6xqm8/MYHW9X66DlyHiiqNOhIHTo0KHsm0NERJ2mVQt++4RK7qZ5Qu2iltMzEUWhDteEEhERdZZWrfKqCXXVNQxI8qgJtXF6JqKoxK+WRESkmIA1oR5PTLKJbI4nikYcmEREFGF69+4Ng8GgdDbCQit614RKDjvGXXYZavb/AMAFALCr9awJJYpC/GpJRBRhxo4di5///OdKZyMsmteEAsBf/vgAFuQ2PQLaxkd2EkUlfqqJiEgxzUfHA/VN8vIz5NEQhLImlCjqsDmeiCjCbNu2DQaDAaNGjVI6KyGna/bEJAD462N/R82+HzDPXN8lwcYpmoiiEj/VREQR5tSpUzh69KjS2QgLrVqArVkQ+uX27fj21Bl52S6yTyhRNGIQSkREitGKKtibNcdDkgC39+h49gklij78VBMRkWL81YRKbrfPPKFa1oQSRR0GoUREpBidWoBLJcIpqJtWSpLPPKE6Nf9dEUUbfqqJiEgxokqAAMCu1srr6mtCPR/bqWdNKFEU4uh4IqIIk52dDZPJpHQ2wkIQBGga5gqNc9ZPyzT94tGoyd8tp7GpddAwCCWKOgxCiYgiTHZ2NsxmM4qKipTOSljomvULvT57ICoqm0bH20T2CSWKRmyOJyIiRWnVKtjUennZWV7mtd0u6qBln1CiqMOaUCKiCLNu3TrodDpMmjRJ6ayEhVYUYBeb+oQ+8P56uOtqsXh4PwAcHU8UrRiEEhFFmKqqKohi7NyetWrvuULPVFR7T9Ek6tknlCgKsX2DiIgU5TNXqEcACtSPnGdzPFH04aeaiIgUpVMLsDV/alIDu0oDt0rNmlCiKMQglIiIFKVVq2AXAwShDeu1KgahRNGGQSgRESlKoxZ8nx/foLGGlDWhRNEndnq+ExF1ETk5OUhKSlI6G2GjU6u8+oTeOSBDfi3XhLJPKFHUYRBKRBRhMjMzY2qyeq0ooEpsmid0dGqC/NomB6GsCSWKNvxqSUREitKqBdRp4vxuqxXr14vsE0oUdVgTSkQUYVavXg1RFDF9+nSlsxIWWrUKtRqDvPzr7QcAAC9cPAS1GgNEFaBmEEoUdVgTSkREitKqBdQGqgnVxEGj4r8qomjETzYRESlKqxZQKxr8bqvVxLE/KFGUYhBKRESKqm+O918TatXEcXomoijFIJSIiBSlUQtwqjVwqHyHKdRpDKwJJYpSDEKJiEhRjUGmv9pQqyaOc4QSRSmOjiciijBTpkxBamoqnE6n0lkJi8bpl6waIxJsVVh0wXnytlpNHIysCSWKSvx6SUQUYRITE5GSkqJ0NsKmsSa0Up8IAOgZp0PPuPpJ6qt1CWyOJ4pSrAklIoowlZWVEMXYuT03NrdXGJIBAAVWGwAg3WREjS4eGjbHE0UlfrKJiCLM+vXrsXr1aqWzETYauSa0Pghdsucoluw5ikp9MiRBxZpQoijFIJSIiBSlVTUGoUle68sbakY1fFoSUVRiEEpERIpqbG4/lZTptf5sQgYAsCaUKEoxCCUiIkU1BpnlcWl4feQcCFodHBo98rLGNWznvyqiaBQ7Pd+JiCgieT4R6aA5G0KKGdZaJyy6eJ/tRBQ9+PWSiIgU1by5XZIkSJACbiei6MCaUCKiCDNjxgyYzWYUFRUpnZWwaD4F03/eXoeXdhbiVKW9YTuDUKJoxJpQIiJSVPOaTodLgsPlUROq4r8qomjETzYRUYQ5efIkDh8+rHQ2wqb5FEzfbtuKgvxvmrazJpQoKkVtc3xeXh7y8vJw6NAhVFRU4O6770Zubq5Xmn379mHJkiU++1577bW49dZbw5RTIiJveXl5EEUR06dPVzorYaFWCVALQGPl54qnH0d5nRND718OgH1CiaJV1Aah27dvR3FxMUaNGoVNmza1mHbBggUwm83yciw9s5mIKBJo1Cq4nG4AgARAamqNZxBKFKWiNghduHAhVCoV6urqWg1CMzMzkZmZ2WIaIiIKHa1aQJ2z/rUkwWNsvO/AJSKKDlH7yVaxIzsRUZfh2e9TaraNNaFE0Slqa0Lb469//Suqq6uRlpaGiRMn4vrrr2cQS0QURp6BplvyDkP57Hii6BTTQWhcXByuu+46DB48GKIo4vvvv8eaNWtQVVWFuXPntrq/Wq0OQy67jsbyYLn4Ytn4x3LxLzExEVqtNqbKxfPRnIndesFW45CXDToRoijyegmA5RIYyyaydZkg1Gq1ory8vNV0GRkZbT5m37590bdvX3n5ggsugCiK+OSTT/CLX/wCCQkJLe6fmpra5nPFEpZLYCwb/1gu3mbPnq10FsIuTn8CgA0AMP0vz+Kzg00T9XdLS4XZnCgv83rxj+USGMsmMnWZIPTrr7/GCy+80Gq6NWvWdOo8F198MT766COcPHkS2dnZLaYtLS2Fy+Xq1PmiiVqtRmpqKsvFD5aNfywX/2KxXFTupvdZWmX12lZTVYEi0RaT5dIWLJfAWDb+paSkQBSVDwGVz0EbTZo0CZMmTVI6G15cLhecTqfS2Yg4LJfAWDb+sVy85efnw2QyoU+fPjFTLqJHN/zv17+FIosD5pzrAABqye1VDrxe/GO5BMayiUxdJggNl2+++QZqtRpZWVlKZ4WIYlR+fj5EUUSfPn2UzkrYeA5M+nHTe3C4JTkI1XKKJqKoFLVB6OnTp3H69GnY7XYAwJEjR6DX65GQkIChQ4cCAF566SUkJCSgX79+EEURu3btwqeffoqpU6ciPj5eyewTEcUUz7lA3c3maOIUTUTRKWqD0Ly8PLzzzjvy8oYNG7BhwwYMHToUixcvBlA/iGnTpk345JNP4HQ60b17d8yaNQtTpkxRKNdERLFJq2phiiYGoURRKWqD0Jtuugk33XRTi2muuuoqXHXVVWHKERERBcLJ6oliDzvaEBGR4lqq7RQ5WT1RVIramlAioq6qd+/eMBgMSmcjrDwHHyUMuNBjvQBBYBBKFI0YhBIRRZixY8fCbDajqKio9cRRwvPRnJnX3N20nk3xRFGLzfFERKS4QP0+OT0TUfRiTSgRUYTZtm0bDAYDRo0apXRWwsazxvPkR88BqK8R5aAkoujFIJSIKMKcOnUKoijGVBDqWeNZ9dNO+bWGg5KIohbbOYiISHGB+n6yJpQoejEIJSIixQUKNjXsE0oUtfjpJiIixbEmlCj2MAglIiLFaVX+/x0xCCWKXhyYREQUYbKzs2EymZTORlh51oSaL7lGfs0glCh6MQglIoow2dnZMTdZvWewac65Tn7NPqFE0YufbiIiUhz7hBLFHtaEEhFFmHXr1kGn02HSpElKZyVsPOcJ/emVPwMABsxdynlCiaIYg1AioghTVVUFUYyt27NnjaetrMDveiKKLmyOJyIixQVqjmefUKLoxU83EREpThug2Z01oUTRi0EoEREpLlCNJ4NQoujFIJSIiBQXKNjUsjmeKGrFVs93IqIuICcnB0lJSUpnI6zUKgEqAXBLQO9pd8nrA/UVJaKuj0EoEVGEyczMjLnJ6oH62tA6p4TEQRd5rSOi6MR2DiIiigj++oWyJpQoerEmlIgowqxevRqiKGL69OlKZyWsGkfI5/9rHgAg+3fLoVWxroQoWvHTTUREEcFfradWZE0oUbRiTWiIVFRUQJIkpbMRdhUVFXA4HIqcWxCEmBvMQRRNdH6a4wPNH0pEXR+D0BCRJAnJyclKZyPsNBqNYkFoeXm5IuclouDQa/z1CWWDHVG04qebiIgigsFPEMrmeKLoxSCUiIgigkH0/Zdk9BOYElF0YHM8EVGEmTJlClJTU+F0OpXOSlg11oT2n/03n3VEFH346SYiijCJiYlISUlROhth1xhw6tMyoE/LgErwXztKRNGBNaFERBGmsrISohh7t+fGgLOu5AwAILVnbwgC+4QSRavYu8sREUW49evXx+Rk9Y01oYdX/gUAkPnIq0pmh4hCjO0c1Cq3241XXnkFV1xxBfr164dBgwZhwoQJ+Mtf/hKTc6ESUWg0b3qP06gVygkRhQNrQqlVd911F7Zu3Yo777wTo0ePhsViwc6dO5GXl8emMiIKmuaDkOI4KIkoqjEIpRZt2rQJa9euxapVqzBx4kR5/ZQpU1gLSkRB1bwm1OnmPYYomvFrJrVo+/btAICxY8f6bGMtKBEFUzeTxms5ycB6EqJoxk94mNhdbpyrVuZxlp66x2ugbcdj8AwGAwBg6dKl+PWvf41evXqFKmtEFOP6JuswoocR+Q3LQ9INiuaHiEKLQWiYnKt24LefHFM6G1g2tS8yk3RtTn/rrbfik08+wfLly7F8+XIMGjQI1113HX75y1/CaDSGMKdEsWvGjBkwm80oKipSOithJQgC/nhZT5z38gfQqVWYOjBZ6SwRUQixOZ5aZDabsWHDBrzxxhuYNWsWKisr8Y9//APXXnst7HZ7h45ZWVmJVatWtZruT3/6E0aPHo2MjIwOnYeIup44jRqzR5ox44I06DhRPVFU4yecWqVWqzF+/Hj8/e9/x44dO3DzzTfjwIED+O677zp0vO+++07ua9qS6667Dp9++mmHzkHUlZ08eRKHDx9WOhuK2bJlC7Zs2aJ0NogoxNgcHybd4zVYNrWv0tlA93hN64laoFKpMH78eLz11luw2WwAgC+++AJPPvkkbDYbXC4XHn/8cVx00UUoKyvD0qVLsX//ftTU1OCXv/wlRo0ahYULF0Kr1WLy5Mn44x//iMsvv9zvuS6++OJO5ZWoq8rLy4vJyeobLVmyBACQm5urbEaIKKQYhIaJVq1qV1/MSFBcXIz09HSf9f/73/9gMBgwcuRIAMD555+Pjz76CIIgYNu2bXjhhRcwevRozJ49G9OnT8f//d//QZIklJSUID09HZdccgluvvlmrymfiIiIKLYwCKWA5s+fD6PRiKuvvhq9e/dGSUkJ3n//fWzYsAFPPPEEEhMTAQCffPIJ1qxZg9raWlgsFowcORIbN26EXq/H7NmzAdQPOGgMaPft24fs7GzF3hcREREpj0EoBXTjjTfi448/xuOPP47S0lIYjUaMGjUKa9asQU5ODgBg7dq12LBhA1atWoWkpCQsXboUCQkJ2LdvHy688EKfY1osFtTW1sJsNof77RAREVEEYRBKAc2YMQMzZsxoMc3+/fsxYsQIJCUlYe/evXj11Vfx/PPPo7CwEJ999hkkSYIgCCgqKoLZbMapU6d8mvgXLFiAKVOmYMqUKaF8O0RERBRBODqeOmX69On46KOPMHXqVHz88cdITk5GdnY2brjhBuj1eowfPx6TJ0/Gm2++CQDIysqCXq9Hbm4u3n77bQBAfn4+evTo4XPs3//+9xg9ejQAYPTo0fj9738fvjdGpKCEhAQkJ8fuHJlZWVnIyspSOhtEFGKCxAeAd1hRURGcTqffbeXl5TH5T0Sj0cDhaPuToSorKzF//nw5SO2MSC5zURTlyccDXTOxiOXiH8vFP5aLfyyXwFg2/pnNZoii8o3hrAklRSUmJgYlACUiIqKuRfkwmIiIvOTn58NkMqFPnz5KZ0URK1asAADMmTNH0XwQUWgxCCUiijD5+fkQRTFmg9CVK1cCYBBKFO3YHE9EREREYccglIiIiIjCjkEoEREREYUdg1AiIiIiCjsOTCIiijC9e/eGwWBQOhuKGTdunNJZIKIwYBBKRBRhxo4dK0+wHYuWLFmidBaIKAzYHE9EREREYceaUCKiCLNt2zYYDAaMGjVK6awoYtGiRQBYI0oU7RiEEhFFmFOnTkEUxZgNQrdu3ap0FogoDNgcT61yu9145ZVXcMUVV6Bfv34YNGgQJkyYgL/85S+QJEnp7BEREVEXxJpQatVdd92FrVu34s4778To0aNhsViwc+dO5OXlQRAEpbNHREREXRCDUGrRpk2bsHbtWqxatQoTJ06U10+ZMoW1oERERNRhURmEWq1WrF27Frt27UJBQQG0Wi0GDhyIW2+9FT179vRKW1ZWhpdffhl79uyBVqtFTk4ObrvtNuh0OoVyH1m2b98OoH7KmOZYC0pEREQdFZVBaElJCTZu3IgJEyZg5syZsNls+OCDD/Dwww/jiSeeQFpaGgDA5XLh0UcfhSiKuO+++2CxWPDqq6/CYrFgwYIFQc2T226HvehsUI/ZEVpzD6i02janb5wwe+nSpfj1r3+NXr16hSprRNQgOzsbJpNJ6WwoZvbs2UpngYjCICqDULPZjGXLlkHrEWwNGTIEd911FzZv3owbb7wRAPD111/j9OnTWLZsGcxmMwBArVbj6aefxo033ogePXoELU/2orM49NA9QTteRw187Fnoe2W1Of2tt96KTz75BMuXL8fy5csxaNAgXHfddfjlL38Jo9EYwpwSxa7s7OyYnqx+zpw5SmeBiMIgKkfH6/V6rwAUAEwmE9LT01FZWSmv2717N/r37y8HoAAwZswYiKKI3bt3hyu7Ec1sNmPDhg144403MGvWLFRWVuIf//gHrr32Wtjt9g4ds7KyEqtWrWoxzZkzZ3DTTTdh/PjxmDBhApYuXco+qERERFEkKmtC/amqqsK5c+dwxRVXyOvOnDnj07wsiiK6deuGM2fOtHpMtVod9HxGIrVajfHjx2P8+PF49NFH8fvf/x5vvfUWvvvuO1xyySVyusY+ooIgtBgwfvfdd9i+fTtuv/32gGlEUcTDDz+M4cOHw263Y+bMmVi3bh2mTp3aYl5FMTIv6cZrJVaumbZiufi3fv16aLVar/tVLGm8NzT/ssrrxT+WS2Asm8gWmf+xQ+DVV1+FXq/3GmBjsVj8NikbjUZYLJZWj5mamhpwW0VFBTQajbyszsjE0H++0M5cB5+uW0+oPPLVERMnTsRbb70Fp9MJjUaDzZs345///CdsNhucTieeeOIJ/OxnP0NZWRmWLFmCffv2oaamBnfccQdGjx6N++67T/4H+9BDD2Hy5Mk+5+jVq5f8BUGj0WDYsGEoLCz0KtPmNBqNV612JGrpmollLBdvFosFFoslZsvl9OnTABDw8xyr5dIalktgLJvI1GWCUKvVivLy8lbTZWRk+Kz73//+hy+//BK/+93vEB8f36bztWXkd2lpKVwul99tDocDDofD84AQu/vmLdxcAFye+WpBcXEx0tPTfdavX78eBoMBF1xwARwOB4YOHYoPP/wQKpUKX331FZ577jmMGDECt9xyC6ZPn44nn3wSkiShpKQE6enpuPjii3HzzTfLUz45WslPWVkZ1q1bhzfffLPFtA6HI2L70KnVaqSmprZ4zcQilot/LpcLarU6Zsul8T03/zzzevGP5RIYy8a/lJSUiGg5VD4HbfT111/jhRdar0lcs2aN1/LOnTuxfPly3HrrrRgzZozXNqPRCKvV6nMMi8WCrKzWB++4XC44nc5W03VV8+fPh9FoxNVXX43evXujpKQE77//PjZs2IAnnngCiYmJAIBPPvkEa9asQW1tLSwWC0aOHImNGzdCr9fLo1wFQZAD2n379iE7O7tNebDZbLjzzjvxq1/9CgMGDGg1faT/PaL9mukolou3xu4ssVouje8/0HuP1XJpDcslMJZNZOoyQeikSZMwadKkdu3z448/4t///jcmT56Ma665xmd7RkaGT99Pp9OJwsJCv03EsebGG2/Exx9/jMcffxylpaUwGo0YNWoU1qxZg5ycHADA2rVrsWHDBqxatQpJSUlYunQpEhISsG/fPlx44YU+x7RYLKitrW1Ts7nL5cJvfvMbZGdnY/78+UF/f0RERKScLhOEttepU6fw+OOPY8SIEZg7d67fNCNGjMBXX33l1ey8c+dOOJ1OjBgxIoy5jUwzZszAjBkzWkyzf/9+jBgxAklJSdi7dy9effVVPP/88ygsLMRnn30GSZIgCAKKiopgNptx6tQpnyb+BQsWYMqUKZgyZYrX+gceeAAmkwmLFi0K+nsjIiIiZUXlFE2VlZV47LHHoNfrMWXKFBw+fBiHDh3CoUOH5A7vAHDxxRcjIyMDTz75JL7//nt89dVXePnllzF27NigzhEazaZPn46PPvoIU6dOxccff4zk5GRkZ2fjhhtugF6vx/jx4zF58mS8+eabAICsrCzo9Xrk5ubi7bffBgDk5+f7lPeOHTuwevVq7NmzB1dccQUmT56Ml19+Oezvj0gJOTk5MTsyHgAWLVrEL59EMUCQonDyxX379mHJkiV+tw0dOhSLFy+Wl0tLS/Hyyy9j79690Gg0yMnJwe23396mx3YWFRUF7GNSXl6O5OTkDuW/K9NoNK0ONPJUWVmJ+fPny0FqZ0RymYuiKE8+zn5JTVgu/rFc/GO5+MdyCYxl45/ZbObApFAZNmyYzwClQFJTU/HAAw+EOEcUSGJiYlACUCIiIupaojIIJSLqylavXg1RFDF9+nSls6KICRMmAAA2b96scE6IKJSisk8oEREREUU2BqFEREREFHYMQomIiIgo7BiEEhEREVHYMQglIiIiorDj6HgioggzZcoUpKamxuy8hsuXL1c6C0QUBgxCQ0QQBJSXlyudjbBr72T1wSQIgiLnJQq2xMREpKSkoKioSOmsKKJv375KZ4GIwoBBaIgkJSUpnYWw45MpiIKjsrIyIp5mopRjx44BYDBKFO1i9y5HRBSh1q9fH9OT1c+bNw8AJ6sninYcmEREREREYccglIiIiIjCjkEoEREREYUdg1AiIiIiCjtBkiRJ6Ux0VU6nEyy+JoIgQBRFlosfLBv/WC7+VVVVQRAEJCQkxGS5HD9+HADQp08fr/W8XvxjuQTGsvFPFMWImNaQQSgRERERhR2b44mIiIgo7BiEEhEREVHYMQglIiIiorBjEEpEREREYccglIiIiIjCLmaeHb9lyxY899xzPut/9atf4YorrvBZv2LFCqxbtw7Tpk3DrFmzWjz2s88+iy+++MJn/VNPPYWMjAx52Wq1YsWKFdixYwfcbjdGjx6NuXPnIj4+vgPvKDhCWS433XST3/WiKOKNN94AABQVFeE3v/mNT5qcnBwsXLiwDe8gNNpSLvfccw+Ki4u9ticmJuKll15q9fg7duzA6tWrce7cOZjNZtx4443IycnxShOJ1wsQurJxu9346KOP8P333+P06dMAgPPOOw8zZsxA//795XSxeM1E+z2mo+US7fcYADh58iTeeOMNHDhwAJIkISMjA3fccQfOO++8Fo/fVe8xoSqXrn5/AUJ7zSh1j4mZILTRI488Aq1WKy9369bNJ83p06exefNmGAyGNh83IyMDd911l9e69PR0r+WnnnoKBQUF+PWvfw2VSoXXX38dTzzxBP7617+2810EXyjKZenSpT7r/vGPf2DQoEE+62+//Xav9QkJCW06R6i1Vi6XXnopfv7zn8vLotj6R+rgwYP417/+hSuuuAJz587Frl278PTTT8NoNGL48OFyuki+XoDgl43dbseHH36I3NxcXHfddRAEAZ9++ikeeeQRLF261OcGGkvXDBD995iOlEu032OOHz+ORx55BBdeeCHuu+8+AMDhw4dht9tbPGY03GOCXS7Rcn8BQnPNAMrcY2IuCO3fvz/0en2LaV555RVMmTIFX375ZZuPq9PpMHDgwIDbDx06hB9++AGLFy/G0KFDAQApKSl46KGHsGfPHlxwwQVtPlcohKJcmpfH4cOHUV1djUsvvdQnbc+ePVssP6W0Vi5JSUntzve7776LIUOGYN68eQCA7OxsnD59Gu+88478DyLSrxcg+GWj1WqxbNkymEwmed3555+Pe++9F59++inuvvtur/SxdM0A0X+P6Ui5RPs95qWXXsLo0aOxYMECed2IESNaPWY03GOCXS7Rcn8BQnPNAMrcY9gntJnt27fj9OnTuO6664J63F27diExMVH+wwH1F5LZbMbu3buDeq5QCEa5bNu2DTqdDqNHjw5exroYh8OB/Px8XHLJJV7rc3JycOjQIVitVgBd/3rpCJVK5fUPAqivDevVqxcqKysVylXXEYvXTHPRdI85ffo0fvrpJ0yZMqVd+0X7Paaj5RIL95eOlk1bheKaibma0N/+9reorq5Gt27dMG3aNEyePFneZrfb8eqrr+LWW29ttVawudOnT2P27NlwOBzo168fZs6c6fWHOnPmjFe/ikYZGRk4c+ZMx99QkISqXBpJkoTt27fjoosugk6n89n+3HPPoaamBomJiRg7dixmzpzp1dyglJbKBQA2b96M9evXQ6vV4oILLsCsWbN8mi88FRYWwuVy+VwLGRkZkCQJBQUF6N+/f8RfL0Dwy8Yfh8OBo0ePYty4cT7bYuWaaRTN9xig89dLtN1jfvrpJwBATU0N/vCHP+DUqVNIT0/H9ddfj4kTJwY8XrTcY4JdLv50xfsLELqyUeIeEzNBaFJSEm6++Wb0798fbrcb27Ztw0svvQSbzYZp06YBAN5//30kJyfjsssua9ex+/btiwEDBqBXr16oqqrCxx9/jL/97W/429/+Jnd4tlgsiIuL89nXaDSiqKio82+wg0JZLp4OHDiA0tJSn47xGo0GV155JYYPHw6DwYB9+/bhww8/RGFhIR544IFOvbfOaEu5XHjhhRgwYABSU1Nx5swZvP3223jkkUfwr3/9y+/fGqi/OQD1f3dPjd/QLRaL/DsSrxcgdGXjz3vvvQeLxYJJkybJ62LtmgGi/x4TjOsl2u4xFRUVAOoHjFxzzTXo168ftm/fjueffx5JSUkYNWqU3+N29XtMqMrFn650fwFCWzZK3WNiJggdMWKEV7+IkSNHwuFw4L333sNVV12FkpISfPzxx3jkkUcgCEK7jn3VVVd5LY8aNQr33Xcf3nvvPa+LNtBx23u+YApluXjatm0bjEajT9+U5ORk/PKXv5SXhw0bhqSkJPz3v//F8ePH0adPnw6fszNaKxeVSoW5c+fK24cMGYKBAwfigQcewObNmzF16tR2nU+SJADe10IkXi9A+Mrm+++/x3vvvYdZs2ahZ8+e8vpYvGai+R4TrOsl2u4xjfeEiRMn4tprrwVQ37fzzJkz+OCDD9oVbAFd5x4TrnLpavcXILRlo9Q9Jqb7hF588cWoqalBcXExXn/9dYwYMQIZGRmwWCywWCxwu91wOp2wWCzyH7cttFotRo4ciWPHjsnrjEaj3BfHU6BvFkoKdrm4XC588803+NnPftamEa8XX3wxAODo0aOdfi/B5Fku/mRmZqJnz55ef/fmGmsjml8LjbUTjddCV7pegOCUjafDhw/jqaeewuTJk9sUhETzNeNPNN1j/GlvuUTjPabxXjFs2DCvNI2DjAKJxntMMMrFU7TcX4Dgl02jcN1jYjoIbSQIAgoKCvDtt99i7ty58k9paSk+/fRTzJ07F2VlZR06bqNAfSYKCgr89rGIBMEql71796KqqsrviNXWzh+JOpOvbt26Qa1W+1wLBQUFEARB/kbeFa8XIDh/s4KCAjz++OM4//zz5dG94Tx/KIQqX9FwjwmGaLzHBPqbSZLUYr6j+R7TmXJpFI33FyA4ZRPouI1Ccc3ETHO8P9988w3i4+ORlpaG+fPno66uzmv7v//9bwwdOhRXXHFFu+YIs9vt2L17t9e8YyNHjsS7776LgwcPYvDgwQCAI0eOoLCwsM3TJ4RLsMtl27ZtSEpK8urg3JLt27cDQKuTMYebZ7n4c/LkSRQUFODyyy8PeAyNRoPs7Gxs377da2BGXl4eBg4cKH+b7ErXCxCcsgGA8vJyPProo+jWrRvuvfdeqFRt+54czdeMP9F0j/GnveUSjfeYlJQUGI1G5Ofne/398vPzW2wSjsZ7TDDKBYi++wsQvLJpLlz3mJgJQp988kn0798fWVlZcLvdyMvLQ15eHubOnQuVSoV+/fr57KPVapGamupVtf3FF1/gP//5D5YtW4b09HRYrVY8/vjjuOyyy9C9e3dUV1fjk08+QVlZmTxRLFA/n93w4cPxzDPP4Pbbb4cgCHj99dcxePBgRedjC1W5NHI4HNixYwdyc3P9fuDXrFmDuro6DBo0CAaDAQcOHMBHH32EMWPGICsrKzRvug1aK5fvv/8eW7duxejRo5GcnIyCggK8++67SEtLQ25urnwcf+Xyi1/8AosXL8aKFStw0UUXYdeuXdi1axceeugheb9IvV6A0JWN3W7HY489BovFgl/+8pc4ceKEnFaj0aBv374AYu+aifZ7TGc+S0D03mNUKhWmT5+O1157DXFxcejfvz+2b9+OAwcOYPHixfJxou0eE6py6er3FyB0ZaPkPSZmgtCePXti8+bNKC0thSRJ6NWrF37zm9/4nZqhJZIkwe12y30hRVFEQkIC3nvvPVRWVkKj0WDgwIFYvHixTwC3cOFCrFy5Ev/5z38gSRJGjRrl1SFfCaEql0a7du2C1Wr1GbHaKCMjAx9//DE2btwIu92OtLQ0XHPNNbjhhhs6/J6CobVySU1NRVVVFVasWAGr1QqTyYQRI0Zg5syZXn1j/JXL4MGDcf/99+Ott97C//73P5jNZixYsMDrSSZAZF4vQOjKpqKiQv7H8Pjjj3udMz09Hc8++yyA2Ltmov0e05nPEhC99xgAmDp1KiRJwvr16/H222+jZ8+euP/++zFkyBA5TbTdY0JVLl39/gKErmyUvMcIUntG3BARERERBQEHJhERERFR2DEIJSIiIqKwYxBKRERERGHHIJSIiIiIwo5BKBERERGFHYNQIiIiIgo7BqFEREREFHYMQomIiIgo7BiEEhEREVHYxcxjO4mI2quqqgqvvvoq9u7di/LycgwdOtTrGcyeioqK8Jvf/EZezsnJwcKFC8OT0U6aP38+ysrKAHg/wpCIKJQYhBIRBfDqq68iLy8PN9xwA8xmM5KSklrdZ8yYMRgzZgzMZrPX+nvuuQfFxcXQ6XR48cUXYTAYfPZ966238O677wKA1zOhGwPciRMnYv78+X7Pu3jxYhw8eBCrV69u57sE5s2bh7q6Orz//vuw2+3t3p+IqCMYhBIRBbB3714MHz4c06dPb/M+mZmZcvDYnEajgc1mQ15eHiZNmuS1ze12Y8uWLdBoNHA4HJ3Kd3uNGTMGALBp0yYUFxeH9dxEFLvYJ5SIKICKigqYTKagHS8lJQX9+/fHpk2bfLbt3r0bpaWl+NnPfha08xERRTLWhBIRNfPss8/iiy++AAB88cUX8uu7774bubm5nTr2xIkT8eKLL+L06dPo1auXvH7Tpk0wm804//zz8dVXX3XqHACwb98+LFmyJOD28ePH45577un0eYiIOopBKBFRM5MnT8b555+PZ555BkOGDJGbzgcNGtTpY48dOxYrV67Epk2bMGvWLABAZWUlvvvuO0yfPh2CIATc1+FwoKqqyu82l8vltZyRkeE1UKrR9u3bsXPnzjb1byUiCiUGoUREzQwcOBADBw7EM888A7PZHLCPZ0cYDAZccskl2Lp1K2655RaIoogtW7ZAkiTk5uZi7969Aff98ssv8eWXXwbcrlI19bBKSkryyffevXuxa9cuDBkyBDfddFPn3wwRUScwCCUiCrNJkyZhy5Yt2LlzJy6++GJs3rwZw4cPR2pqaov7jRw5ElOnTvW7bdWqVTh16lTAfU+cOIEnn3wS3bt3xx/+8AdoNJpOvQcios5iEEpEFGaDBg1CRkYGNm/ejISEBBQUFGDmzJmt7pecnIwLLrjA7zaj0Rhwv5KSEvz973+HTqfDgw8+GNTBVkREHcUglIhIARMnTsRrr70Gp9OJxMREjB49OiTnsVgs+Pvf/w6r1YrFixf7zF9KRKQUTtFERKSA8ePHQ6VSYe/evRg3bhxEMfh1Ak6nE08++SQKCgpw33334bzzzgv6OYiIOoo1oURECkhISMAdd9yBkpKSTk/75I8kSXj22Wexb98+3HnnnRg5cmTQz0FE1BkMQomIFDJx4sSQHfuzzz7Dtm3b0K9fP2i1WmzdutVre/fu3TFw4MCQnZ+IqDUMQomIolBFRQUA4MiRI3jmmWd8to8fP55BKBEpSpAkSVI6E0REXV1RURF+85vf4JprrsE111wDjUYDg8GgdLbapKamBm63G0888QTKysrw7LPPKp0lIooBrAklIgqijz76CB999BFycnKwcOFCpbPTJr///e9RVlYGAEhPT1c4N0QUK1gTSkQUBHa7HQcPHpSXk5KSkJmZqWCO2u7gwYOw2+0AAK1Wi8GDByucIyKKBQxCiYiIiCjsOE8oEREREYUdg1AiIiIiCjsGoUREREQUdgxCiYiIiCjsGIQSERERUdgxCCUiIiKisGMQSkRERERhxyCUiIiIiMKOQSgRERERhR2DUCIiIiIKOwahRERERBR2/x9aAQvKIGP/7gAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 720x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "fig, ax = plt.subplots()\n",
     "ax.plot(freq.f_scaled, 20*np.log10(np.abs(s_act)), lw=2)\n",
@@ -203,14 +302,146 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Monopole excitation (phase $(0,0)$) at the contrary requires shifting the operating frequency toward lower frequencies:"
+    "However, the reflection coefficient is not that low (-15 to -20 dB at best). That means that there is certainly a sweeter spot of the capacitor set."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Looking for individual solutions separately for 1st guess...\n",
+      "True solution #1: [49.30690682 47.31824748]\n",
+      "Rounded result: [49.31, 47.32, 150.0, 150.0]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [49.07962386 47.47779344]\n",
+      "Rounded result: [150.0, 150.0, 49.08, 47.48]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [49.87563114 48.04904444 49.55481102 48.25487323]\n",
+      "Rounded result: [49.88, 48.05, 49.55, 48.25]\n",
+      "[49.88, 48.05, 49.55, 48.25]\n"
+     ]
+    }
+   ],
+   "source": [
+    "C_opt = ant.match_both_sides(f_match=55.728e6, decimals=2)\n",
+    "print(C_opt)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The difference is:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([-0.09,  0.11, -0.19,  0.15])"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.array(C_opt) - np.array(C_match)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "That is, one should:\n",
+    "- decrease slightly the top capacitors\n",
+    "- increase slightly the bottom capacitors"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As a rule of thumb, at 55.5 MHz, we can remember to do -0.1pF for top and +0.1pF for bottom capacitors. Doing, so, we get a better match point (between -20 and -30 dB)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Dipole excitation')"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 720x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "C_match_improved = [C_match[0] - 0.1,\n",
+    "                    C_match[1] + 0.1,\n",
+    "                    C_match[2] - 0.1,\n",
+    "                    C_match[3] + 0.1]\n",
+    "fig, ax = plt.subplots()\n",
+    "ax.plot(freq.f_scaled, ant.s_act_db(Cs=C_match_improved, power=[1,1], phase=[0,np.pi]), lw=2)\n",
+    "ax.axvline(f0/1e6, ls='--', color='gray')\n",
+    "ax.axvline(f_opt/1e6, ls='--', color='k')\n",
+    "ax.set_ylabel('$|S_{act}|$ [dB]')\n",
+    "ax.set_xlabel('f [MHz]')\n",
+    "ax.legend(('$S_{act,1}$', '$S_{act,2}$'))\n",
+    "ax.set_title('Dipole excitation')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
+   "source": [
+    "Monopole excitation (phase $(0,0)$) at the contrary requires shifting the operating frequency toward lower frequencies:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Optimum frequency is f_opt=55.27 MHz --> -0.23 MHz shift\n"
+     ]
+    }
+   ],
    "source": [
     "# monopole excitation\n",
     "power = [1, 1]\n",
@@ -228,9 +459,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Monopole excitation')"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 720x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "fig, ax = plt.subplots()\n",
     "ax.plot(freq.f_scaled, 20*np.log10(np.abs(s_act)), lw=2)\n",
@@ -242,6 +494,86 @@
     "ax.set_title('Monopole excitation')"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The matching can also be improved:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Looking for individual solutions separately for 1st guess...\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [29.95534337 29.95534337]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "Wrong solution (out of range capacitor) ! Re-doing...\n",
+      "False solution #1: [150. 150.]\n",
+      "True solution #1: [50.6416654  48.57244674]\n",
+      "Rounded result: [50.64, 48.57, 150.0, 150.0]\n",
+      "True solution #1: [50.41067506 48.73500811]\n",
+      "Rounded result: [150.0, 150.0, 50.41, 48.74]\n",
+      "Searching for the active match point solution...\n",
+      "Reducing search range to +/- 5pF around individual solutions\n",
+      "True solution #1: [50.06507201 47.82371932 49.8891473  47.9801226 ]\n",
+      "Rounded result: [50.07, 47.82, 49.89, 47.98]\n",
+      "[50.07, 47.82, 49.89, 47.98]\n"
+     ]
+    }
+   ],
+   "source": [
+    "C_opt_mono = ant.match_both_sides(f_match=55.27e6, decimals=2, power=[1,1], phase=[0,0])\n",
+    "print(C_opt_mono)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "So a difference of:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 0.1 , -0.12,  0.15, -0.12])"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.array(C_opt_mono) - np.array(C_match)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "That is the opposite trend than for dipole:\n",
+    "- increase slightly top capacitors (~ +0.1 pF as a rule of thumb)\n",
+    "- decrease slightly bot capacitors (~ -0.1 pF as a rule of thumb)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -570,7 +902,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.7"
+   "version": "3.11.9"
   },
   "toc": {
    "base_numbering": 1,
diff --git a/west_ic_antenna/antenna.py b/west_ic_antenna/antenna.py
index 13ca845..334a313 100644
--- a/west_ic_antenna/antenna.py
+++ b/west_ic_antenna/antenna.py
@@ -550,11 +550,12 @@ def match_one_side(
         side: str = "left",
         z_match: complex = 29.89 + 0j,
         decimals: Union[int, None] = None,
+        verbose: bool = True
     ) -> NumberLike:
         """
-        Search the best capacitance to match the specified side of the antenna.
+        Search for the best capacitance to match the specified side of the antenna.
 
-        Capacitance of the non-matched side are set to 120 [pF].
+        The capacitances of the non-matched side are set to 120 [pF].
 
         Parameters
         ----------
@@ -571,6 +572,8 @@ def match_one_side(
         decimals : int or None, optional
             Round the capacitances to the given number of decimals.
             Default is None (no rounding)
+        verbose : bool
+            Display search information. Default is True.
 
         Returns
         -------
@@ -612,14 +615,21 @@ def match_one_side(
             # test if the solution found is the capacitor range
             success = sol.success
             if (
+                # out of range capacitor
                 np.isclose(sol.x, 150).any()
                 or np.isclose(sol.x, 12).any()
-                or np.isclose(sol.x[0], sol.x[1])
+                # can't be found equal
+                or np.isclose(sol.x[0], sol.x[1], atol=1e-3)
+                # too large relative differences 
+                or sol.x[0]/sol.x[1] > 1.2
+                or sol.x[0]/sol.x[1] < 1/1.2
             ):
                 success = False
-                print("Wrong solution (out of range capacitor) ! Re-doing...")
+                if verbose:
+                    print("Wrong solution found ! Re-doing...")
 
-            print(success, f"solution #{solution_number}:", sol.x)
+            if verbose:
+                print(success, f"solution #{solution_number}:", sol.x)
 
         if side == "left":
             Cs = [sol.x[0], sol.x[1], 150, 150]
@@ -629,7 +639,8 @@ def match_one_side(
         # round result to realistic values if requested
         if decimals:
             Cs = list(np.round(Cs, decimals=decimals))
-            print("Rounded result:", Cs)
+            if verbose:
+                print("Rounded result:", Cs)
 
         return Cs
 
@@ -639,6 +650,7 @@ def match_both_sides_separately(
         solution_number: int = 1,
         z_match: NumberLike = [29.89 + 0j, 29.87 + 0j],
         decimals: Union[int, None] = None,
+        verbose: bool = True
     ) -> NumberLike:
         """
         Match both sides separately and returns capacitance values for each sides.
@@ -656,7 +668,8 @@ def match_both_sides_separately(
             antenna feeder characteristic impedance to match on. Default is 30 ohm
         decimals : int, optional
             Round the capacitances to the given number of decimals. Default is None (no rounding)
-
+        verbose : bool
+            Display search information. Default is True.
 
         Returns
         -------
@@ -670,6 +683,7 @@ def match_both_sides_separately(
             solution_number=solution_number,
             z_match=z_match[0],
             decimals=decimals,
+            verbose=verbose
         )
         C_right = self.match_one_side(
             side="right",
@@ -677,6 +691,7 @@ def match_both_sides_separately(
             solution_number=solution_number,
             z_match=z_match[1],
             decimals=decimals,
+            verbose=verbose
         )
 
         C_match = [C_left[0], C_left[1], C_right[2], C_right[3]]
@@ -690,6 +705,7 @@ def match_both_sides(
         solution_number: int = 1,
         z_match: NumberLike = [29.89 + 0j, 29.89 + 0j],
         decimals: Union[int, None] = None,
+        verbose: bool = True,
         method: str = "SLSQP",
         C0: Union[None, list] = None,
         delta_C: float = 5,
@@ -705,16 +721,18 @@ def match_both_sides(
         ----------
         f_match: float, optional
             match frequency in [Hz]. Default is 55 MHz.
+        power : list or array
+            Input power at external ports in Watts [W]. Default is [1, 1] W.
+        phase : list or array
+            Input phase at external ports in radian [rad]. Default is dipole [0, pi] rad.
         solution_number: int, optional
             1 or 2: 1 for C_top > C_lower or 2 for C_top < C_lower
         z_match: array of complex, optional
             antenna feeder characteristic impedance to match on. Default is 30 ohm
         decimals : int, optional
             Round the capacitances to the given number of decimals. Default is None (no rounding)
-        power : list or array
-            Input power at external ports in Watts [W]. Default is [1, 1] W.
-        phase : list or array
-            Input phase at external ports in radian [rad]. Default is dipole [0, pi] rad.
+        verbose : bool
+            Display search information. Default is True.
         method : str, optional
             Scipy Optimization method. 'SLSQP' (default) or 'COBYLA'
         C0 : list or None, optional
@@ -755,20 +773,24 @@ def match_both_sides(
 
         if not C0:
             # initial guess from both side separately
-            print("Looking for individual solutions separately for 1st guess...")
+            if verbose:
+                print("Looking for individual solutions separately for 1st guess...")
             C0 = self.match_both_sides_separately(
                 f_match=f_match,
                 solution_number=solution_number,
                 z_match=z_match,
                 decimals=decimals,
+                verbose=verbose
             )
 
-        print("Searching for the active match point solution...")
+        if verbose:
+            print("Searching for the active match point solution...")
         success = False
         while not success:
-            print(
-                f"Reducing search range to +/- {delta_C}pF around individual solutions"
-            )
+            if verbose:
+                print(
+                    f"Reducing search range to +/- {delta_C}pF around individual solutions"
+                )
             lb = np.array(
                 [
                     C0[0] - delta_C,
@@ -822,16 +844,19 @@ def match_both_sides(
                 or np.isclose(sol.x[2], sol.x[3])
             ):
                 success = False
-                print("Wrong solution (out of range capacitor) ! Re-doing...")
+                if verbose:
+                    print("Wrong solution (out of range capacitor) ! Re-doing...")
 
-            print(success, f"solution #{solution_number}:", sol.x)
+            if verbose:
+                print(success, f"solution #{solution_number}:", sol.x)
 
         Cs = [sol.x[0], sol.x[1], sol.x[2], sol.x[3]]
 
         # round result to realistic values if requested
         if decimals:
             Cs = list(np.round(Cs, decimals=decimals))
-            print("Rounded result:", Cs)
+            if verbose:
+                print("Rounded result:", Cs)
 
         return Cs
 
diff --git a/west_ic_antenna/test/test_antenna.py b/west_ic_antenna/test/test_antenna.py
index cdb370c..f6ee806 100644
--- a/west_ic_antenna/test/test_antenna.py
+++ b/west_ic_antenna/test/test_antenna.py
@@ -211,6 +211,15 @@ def test_match_both_sides_separately(antenna_default_arg):
     # reference values 25/03/2024
     np.testing.assert_allclose(Cs, [51.44282792582701, 49.32527088864287, 51.20987339854108, 49.48946981138618], rtol=1e-1)
 
+def test_match_both_sides_separately_plasma():
+    # Test the matching set for a plasma
+    plasma = WestIcrhAntenna.interpolate_front_face(Rc=1, source='TOPICA-H-mode')
+    freq = rf.Frequency(55, 55, npoints=1, unit='MHz')
+    ant_plasma = WestIcrhAntenna(frequency=freq, front_face=plasma)
+    Cs = ant_plasma.match_both_sides_separately(f_match=55e6)
+    # reference values version 0.14.0
+    np.testing.assert_allclose(Cs, [54.41165709, 46.46759841, 54.02665722, 46.62026873], rtol=1e-1)
+
 def test_match_both_sides(antenna_default_arg):
     # Test the return values of both sides matching
     Cs = antenna_default_arg.match_both_sides(
@@ -221,6 +230,15 @@ def test_match_both_sides(antenna_default_arg):
     # reference values 25/03/2024
     np.testing.assert_allclose(Cs, [52.09695694, 50.08075395, 51.62129529, 50.25710599], rtol=1e-1)
 
+def test_match_both_sides_plasma():
+    # Test the matching set for a plasma
+    plasma = WestIcrhAntenna.interpolate_front_face(Rc=1, source='TOPICA-H-mode')
+    freq = rf.Frequency(55, 55, npoints=1, unit='MHz')
+    ant_plasma = WestIcrhAntenna(frequency=freq, front_face=plasma)
+    Cs = ant_plasma.match_both_sides(f_match=55e6)
+    # reference values version 0.14.0
+    np.testing.assert_allclose(Cs, [55.01900067, 46.71040951, 54.72355795, 46.88053526], rtol=1e-1)
+
 def test_currents(antenna_default_arg):
     ant_1freq = WestIcrhAntenna(frequency=rf.Frequency(55,55,1,unit='MHz'))
     Cs = [50] * 4