diff --git a/advanced/apply_ufunc/complex-output-numpy.ipynb b/advanced/apply_ufunc/complex-output-numpy.ipynb
index fc26045b..24f90470 100644
--- a/advanced/apply_ufunc/complex-output-numpy.ipynb
+++ b/advanced/apply_ufunc/complex-output-numpy.ipynb
@@ -33,10 +33,10 @@
     "This function expects a 1D array as input, and returns a 1D array as output.\n",
     "\n",
     "\n",
-    "```{tip}Exercise\n",
+    "```{tip} Exercise\n",
     "How many core dimensions does `numpy.interp` handle?\n",
     "```\n",
-    "```{tip}Solution\n",
+    "```{tip} Solution\n",
     ":class:dropdown\n",
     "\n",
     "One.\n",
@@ -125,8 +125,7 @@
     "user_expressions": []
    },
    "source": [
-    "```{tip}Exercise\n",
-    "\n",
+    "```{tip} Exercise\n",
     "\n",
     "Apply the following function using `apply_ufunc`. It adds a new dimension to the input array, let's call it `newdim`. Specify the new dimension using `output_core_dims`\n",
     "\n",
@@ -134,7 +133,7 @@
     "def add_new_dim(array):\n",
     "    return np.expand_dims(array, axis=0)\n",
     "```\n",
-    "```{tip}Solution\n",
+    "```{tip} Solution\n",
     ":class: dropdown\n",
     "\n",
     "```{code-cell} python\n",
@@ -320,7 +319,7 @@
     "user_expressions": []
    },
    "source": [
-    "```{tip}Exercise\n",
+    "```{tip} Exercise\n",
     "\n",
     "We presented the concept of \"core dimensions\" as the \"smallest unit of data the function could handle.\" Do you understand how the following use of `apply_ufunc` generalizes to an array with more than one dimension? Try it with `air3d = xr.tutorial.load_dataset(\"air_temperature\").air.isel(time=0)`\n",
     "\n",
@@ -333,7 +332,7 @@
     ")\n",
     "```\n",
     "\n",
-    "```{tip}Solution\n",
+    "```{tip} Solution\n",
     ":class:dropdown\n",
     "\n",
     "We want to use `minmax` to compute the minimum and maximum along the \"lat\" dimension always, regardless of how many dimensions are on the input. So we specify `input_core_dims=[[\"lat\"]]`. The output does not contain the \"lat\" dimension, but we expect two returned variables. So we pass an empty list `[]` for each returned array, so `output_core_dims=[[], []]`\n",