diff --git a/examples/jupyter-src/modelica_conference_2021.ipynb b/examples/jupyter-src/modelica_conference_2021.ipynb
index e5add7c3..1144224a 100644
--- a/examples/jupyter-src/modelica_conference_2021.ipynb
+++ b/examples/jupyter-src/modelica_conference_2021.ipynb
@@ -21,7 +21,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 129,
+   "execution_count": 1,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2022-10-14T15:30:08.475000Z",
@@ -88,7 +88,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 130,
+   "execution_count": 2,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2022-10-14T15:30:08.740000Z",
@@ -656,7 +656,7 @@
     "\n",
     "    display(fig)\n",
     "    \n",
-    "    return forces   \n",
+    "    return nothing\n",
     "end"
    ]
   },
@@ -755,7 +755,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 147,
+   "execution_count": 19,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2022-10-14T15:33:56.111000Z",
@@ -808,7 +808,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 149,
+   "execution_count": 21,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2022-10-14T15:34:29.265000Z",
@@ -864,7 +864,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 151,
+   "execution_count": 23,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2022-10-14T15:35:11.153000Z",
@@ -909,6 +909,9 @@
    "outputs": [],
    "source": [
     "for run in 1:numRuns\n",
+    "\n",
+    "    global forces\n",
+    "    \n",
     "    optim = Adam(10.0^(-3+1-run)) # going from 1e-3 to 1e-4\n",
     "\n",
     "    @time for epoch in 1:numEpochs\n",
@@ -929,7 +932,7 @@
     "    netBottom = Chain(layersBottom...)\n",
     "    transferFlatParams!(netBottom, paramsNet, 7)\n",
     "    \n",
-    "    forces = plot_friction_model(realSimData, netBottom, forces) \n",
+    "    plot_friction_model(realSimData, netBottom, forces) \n",
     "    \n",
     "    # displacement model extraction\n",
     "    layersTop = neuralFMU.model.layers[1:1]\n",
@@ -949,7 +952,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 153,
+   "execution_count": 25,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2022-10-14T15:39:38.848000Z",