# Are the final states not being updated in this $n$-step Q-Learning algorithm?

I am reading this paper and in algorithm 3 they describe an $$n$$-step Q-Learning algorithm. Below is the pseudo-code.

From this pseudo-code, it looks as though the final tuples that they would visit in don't get added to the memory buffer $$M$$. They define a sample size $$T$$, but also say in the paper that an episode terminates when $$|S| = b$$.

This leaves me two questions:

1. Have I understood the episode termination correctly? It seems from the pseudocode they are just running an episode for $$T$$ time steps but also in the paper they have a definition for when an episode terminates, so I'm not sure why they would want to truncate the episode size.
2. As I mentioned, it seems as though the final state $$S_T$$ that you would be in won't get added to the experience buffer as we only append the $$(T-n)$$th tuple. Why would you want to exclude the information you get from the final tuples you visit?