diff --git a/Lesson3_BP.ipynb b/Lesson3_BP.ipynb
index 6bf9b53..79ea8de 100644
--- a/Lesson3_BP.ipynb
+++ b/Lesson3_BP.ipynb
@@ -35,7 +35,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 1,
+      "execution_count": null,
       "metadata": {
         "id": "TycsC-y6gmpz"
       },
@@ -136,7 +136,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 2,
+      "execution_count": null,
       "metadata": {
         "id": "_GAtzybPgmp1"
       },
@@ -217,7 +217,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 3,
+      "execution_count": null,
       "metadata": {
         "id": "ScMtPuRbgmp2"
       },
@@ -294,7 +294,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 4,
+      "execution_count": null,
       "metadata": {
         "id": "t9qFVtzXgmp4"
       },
@@ -344,7 +344,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 5,
+      "execution_count": null,
       "metadata": {
         "id": "6HzNe9zngmp5"
       },
@@ -396,7 +396,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 6,
+      "execution_count": null,
       "metadata": {
         "id": "S6PolFOFgmp6"
       },
@@ -429,7 +429,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 7,
+      "execution_count": null,
       "metadata": {
         "id": "R6UFiQZwgmp6"
       },
@@ -522,7 +522,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 8,
+      "execution_count": null,
       "metadata": {
         "id": "EquY5VXYgmp7",
         "colab": {
@@ -578,13 +578,13 @@
       "source": [
         "## Using ANI for Feature Extraction\n",
         "\n",
-        "Here is an example where we use the ANI model for feature extraction. We will use values for the symmetry function parameters from the ASE_ANI model references (https://github.com/isayev/ASE_ANI), which serves as an interface for the TorchANI (https://doi.org/10.1021/acs.jcim.0c00451) software package.\n",
+        "Here is an example where we use the ANI model for feature extraction. We will use values for the symmetry function parameters from the ASE_ANI model references (https://github.com/isayev/ASE_ANI), which serves as an interface for the TorchANI (https://doi.org/10.1021/acs.jcim.0c00451) software package. The BP parameters in this tutorial are not optimized for this system. The parameters can be optimized following the procedures outlined in https://doi.org/10.1002/qua.24890.\n",
         "\n"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 9,
+      "execution_count": null,
       "metadata": {
         "id": "f0Vf6S6egmp8",
         "colab": {
@@ -701,7 +701,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 10,
+      "execution_count": null,
       "metadata": {
         "id": "Y9pQYh2Bgmp9"
       },
@@ -713,7 +713,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 11,
+      "execution_count": null,
       "metadata": {
         "id": "SHvZFE4Fgmp9"
       },
@@ -734,7 +734,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 12,
+      "execution_count": null,
       "metadata": {
         "id": "Qg2tueuMgmp9",
         "colab": {
@@ -794,7 +794,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 13,
+      "execution_count": null,
       "metadata": {
         "id": "peKDL7Ufgmp-",
         "colab": {
@@ -836,7 +836,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 14,
+      "execution_count": null,
       "metadata": {
         "id": "fsotMUSxgmp-",
         "colab": {
@@ -890,7 +890,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 15,
+      "execution_count": null,
       "metadata": {
         "id": "Jcd1TkxZgmp-",
         "colab": {