address pr-53 feedback
diff --git a/site/docs/quarks-getting-started.md b/site/docs/quarks-getting-started.md
index a1e2336..9aab9a1 100644
--- a/site/docs/quarks-getting-started.md
+++ b/site/docs/quarks-getting-started.md
@@ -142,7 +142,7 @@
A streaming application can run indefinitely, so the `TStream` might see an arbitrarily large number of readings pass through it. Because a `TStream` represents the flow of your data, it supports a number of operations which allow you to modify your data.
-## Filtering a `TStream`
+### Filtering a `TStream`
In our example, we want to filter the stream of temperature readings, and remove any "uninteresting" or expected readings—specifically readings which are above 50 degrees and below 80 degrees. To do this, we call the `TStream`'s `filter` method and pass in a function that returns *true* if the data is interesting and *false* if the data is uninteresting:
diff --git a/site/recipes/recipe_adaptable_deadtime_filter.md b/site/recipes/recipe_adaptable_deadtime_filter.md
index 76d773e..8441c9f 100644
--- a/site/recipes/recipe_adaptable_deadtime_filter.md
+++ b/site/recipes/recipe_adaptable_deadtime_filter.md
@@ -60,7 +60,7 @@
## The final application
-When the application is run it will initially print out temperature sensor readings every second for 15 seconds—the deadtime period is 0. `Then every 15 seconds the application will toggle the deadtime period between 5 seconds and 0 seconds, resulting in a reduction in tuples being printed during the 5 second deadtime period.
+When the application is run it will initially print out temperature sensor readings every second for 15 seconds—the deadtime period is 0. Then every 15 seconds the application will toggle the deadtime period between 5 seconds and 0 seconds, resulting in a reduction in tuples being printed during the 5 second deadtime period.
```java
import java.util.Date;
