diff --git a/examples/Example_EarthObservation_-_Attitude_Sequence.ipynb b/examples/Example_EarthObservation_-_Attitude_Sequence.ipynb
index e1ed9c78dbe8ccf1afe63eb8d454321890baf2cc..f3d7e3fe7a027ee3934d0f7f81961b7039ae3bb5 100644
--- a/examples/Example_EarthObservation_-_Attitude_Sequence.ipynb
+++ b/examples/Example_EarthObservation_-_Attitude_Sequence.ipynb
@@ -6,7 +6,7 @@
    "source": [
     "# Attitude Sequence\n",
     "\n",
-    "THIS EXAMPLE IS CURRENTLY NOT WORKING - NEEDS UPDATE FOR OREKIT 9.2"
+    "THIS EXAMPLE IS CURRENTLY NOT WORKING FULLY, Needs some more updates for 10.1"
    ]
   },
   {
@@ -86,7 +86,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -109,7 +109,7 @@
     "from org.orekit.propagation.sampling import OrekitFixedStepHandler, PythonOrekitFixedStepHandler\n",
     "from org.orekit.time import AbsoluteDate;\n",
     "from org.orekit.time import TimeScalesFactory;\n",
-    "from org.orekit.utils import Constants, IERSConventions\n",
+    "from org.orekit.utils import Constants, IERSConventions, AngularDerivativesFilter\n",
     "from org.orekit.utils import PVCoordinates;\n",
     "from org.orekit.utils import PVCoordinatesProvider;\n",
     "from org.hipparchus.ode.events import Action\n"
@@ -316,7 +316,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -324,8 +324,12 @@
     "\n",
     "# Should add something more on Switching\n",
     "\n",
-    "attitudesSequence.addSwitchingCondition(dayObservationLaw, nightRestingLaw, dayNightEvent, False, True, 10.0, None, None)\n",
-    "attitudesSequence.addSwitchingCondition(nightRestingLaw, dayObservationLaw, nightDayEvent, True, False, 10.0, None, None)"
+    "attitudesSequence.addSwitchingCondition(dayObservationLaw, nightRestingLaw,\n",
+    "                                        dayNightEvent, False, True, 10.0, \n",
+    "                                        AngularDerivativesFilter.USE_R, None)\n",
+    "\n",
+    "\n",
+    "attitudesSequence.addSwitchingCondition(nightRestingLaw, dayObservationLaw, nightDayEvent, True, False, 10.0, AngularDerivativesFilter.USE_R,  None)"
    ]
   },
   {
@@ -341,7 +345,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -362,7 +366,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -382,7 +386,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -399,7 +403,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -430,7 +434,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -449,7 +453,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
@@ -489,18 +493,48 @@
       "2004-01-02T00:57:00.000     0.325      44.0\n",
       "2004-01-02T01:00:00.000     0.178      44.0\n",
       "2004-01-02T01:03:45.919  : event occurred, entering eclipse => switching to night law\n",
-      "2004-01-02T01:03:00.000     0.035      44.0\n"
-     ]
-    },
-    {
-     "ename": "JavaError",
-     "evalue": "<super: <class 'JavaError'>, <JavaError object>>\n    Java stacktrace:\njava.lang.NullPointerException\r\n\tat org.orekit.utils.TimeStampedAngularCoordinates.interpolate(TimeStampedAngularCoordinates.java:315)\r\n\tat org.orekit.attitudes.AttitudesSequence$Switch$TransitionProvider.getAttitude(AttitudesSequence.java:497)\r\n\tat org.orekit.attitudes.AttitudesSequence.getAttitude(AttitudesSequence.java:292)\r\n\tat org.orekit.propagation.analytical.AbstractAnalyticalPropagator.basicPropagate(AbstractAnalyticalPropagator.java:383)\r\n\tat org.orekit.propagation.analytical.AbstractAnalyticalPropagator$BasicStepInterpolator.getInterpolatedState(AbstractAnalyticalPropagator.java:542)\r\n\tat org.orekit.propagation.analytical.AbstractAnalyticalPropagator.acceptStep(AbstractAnalyticalPropagator.java:246)\r\n\tat org.orekit.propagation.analytical.AbstractAnalyticalPropagator.propagate(AbstractAnalyticalPropagator.java:166)\r\n\tat org.orekit.propagation.AbstractPropagator.propagate(AbstractPropagator.java:261)\r\n",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mJavaError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m<ipython-input-22-0e3c9d2b0ffd>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# Propagate from the initial date for the fixed duration\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mfinalState\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpropagator\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpropagate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minitialDate\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshiftedBy\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m12600.\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[1;31mJavaError\u001b[0m: <super: <class 'JavaError'>, <JavaError object>>\n    Java stacktrace:\njava.lang.NullPointerException\r\n\tat org.orekit.utils.TimeStampedAngularCoordinates.interpolate(TimeStampedAngularCoordinates.java:315)\r\n\tat org.orekit.attitudes.AttitudesSequence$Switch$TransitionProvider.getAttitude(AttitudesSequence.java:497)\r\n\tat org.orekit.attitudes.AttitudesSequence.getAttitude(AttitudesSequence.java:292)\r\n\tat org.orekit.propagation.analytical.AbstractAnalyticalPropagator.basicPropagate(AbstractAnalyticalPropagator.java:383)\r\n\tat org.orekit.propagation.analytical.AbstractAnalyticalPropagator$BasicStepInterpolator.getInterpolatedState(AbstractAnalyticalPropagator.java:542)\r\n\tat org.orekit.propagation.analytical.AbstractAnalyticalPropagator.acceptStep(AbstractAnalyticalPropagator.java:246)\r\n\tat org.orekit.propagation.analytical.AbstractAnalyticalPropagator.propagate(AbstractAnalyticalPropagator.java:166)\r\n\tat org.orekit.propagation.AbstractPropagator.propagate(AbstractPropagator.java:261)\r\n"
+      "2004-01-02T01:03:00.000     0.035      44.0\n",
+      "2004-01-02T01:06:00.000    -0.100       0.0\n",
+      "2004-01-02T01:09:00.000    -0.222       0.0\n",
+      "2004-01-02T01:12:00.000    -0.326       0.0\n",
+      "2004-01-02T01:15:00.000    -0.402       0.0\n",
+      "2004-01-02T01:18:00.000    -0.441       0.0\n",
+      "2004-01-02T01:21:00.000    -0.435       0.0\n",
+      "2004-01-02T01:24:00.000    -0.386       0.0\n",
+      "2004-01-02T01:27:00.000    -0.302       0.0\n",
+      "2004-01-02T01:30:00.000    -0.193       0.0\n",
+      "2004-01-02T01:33:00.000    -0.067       0.0\n",
+      "2004-01-02T01:34:28.690  : event occurred, exiting eclipse => switching to day law\n",
+      "2004-01-02T01:36:00.000     0.071       0.0\n",
+      "2004-01-02T01:39:00.000     0.215      44.0\n",
+      "2004-01-02T01:42:00.000     0.363      44.0\n",
+      "2004-01-02T01:45:00.000     0.512      44.0\n",
+      "2004-01-02T01:48:00.000     0.660      44.0\n",
+      "2004-01-02T01:51:00.000     0.805      44.0\n",
+      "2004-01-02T01:54:00.000     0.944      44.0\n",
+      "2004-01-02T01:57:00.000     1.072      44.0\n",
+      "2004-01-02T02:00:00.000     1.185      44.0\n",
+      "2004-01-02T02:03:00.000     1.273      44.0\n",
+      "2004-01-02T02:06:00.000     1.328      44.0\n",
+      "2004-01-02T02:09:00.000     1.341      44.0\n",
+      "2004-01-02T02:12:00.000     1.309      44.0\n",
+      "2004-01-02T02:15:00.000     1.239      44.0\n",
+      "2004-01-02T02:18:00.000     1.139      44.0\n",
+      "2004-01-02T02:21:00.000     1.018      44.0\n",
+      "2004-01-02T02:24:00.000     0.885      44.0\n",
+      "2004-01-02T02:27:00.000     0.744      44.0\n",
+      "2004-01-02T02:30:00.000     0.597      44.0\n",
+      "2004-01-02T02:33:00.000     0.449      44.0\n",
+      "2004-01-02T02:36:00.000     0.300      44.0\n",
+      "2004-01-02T02:39:00.000     0.154      44.0\n",
+      "2004-01-02T02:42:16.591  : event occurred, entering eclipse => switching to night law\n",
+      "2004-01-02T02:42:00.000     0.013      44.0\n",
+      "2004-01-02T02:45:00.000    -0.121       0.0\n",
+      "2004-01-02T02:48:00.000    -0.241       0.0\n",
+      "2004-01-02T02:51:00.000    -0.341       0.0\n",
+      "2004-01-02T02:54:00.000    -0.411       0.0\n",
+      "2004-01-02T02:57:00.000    -0.443       0.0\n",
+      "2004-01-02T03:00:00.000    -0.430       0.0\n"
      ]
     }
    ],
@@ -511,9 +545,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 33,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Propagation ended at 2004-01-02T03:00:00.000\n"
+     ]
+    }
+   ],
    "source": [
     "print(\"Propagation ended at \" + finalState.getDate().toString())"
    ]
@@ -527,7 +569,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -550,7 +592,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -559,9 +601,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 36,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 864x864 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plt.xticks(rotation=90)\n",
     "ax = plt.gca()\n",