  Tight bounds for several symmetric divergence measures are introduced, given
in terms of the total variation distance. Each of these bounds is attained by a
pair of 2 or 3-element probability distributions. An application of these
bounds for lossless source coding is provided, refining and improving a certain
bound by Csisz\'ar. A new inequality relating $f$-divergences is derived, and
its use is exemplified. The last section of this conference paper is not
included in the recent journal paper that was published in the February 2015
issue of the IEEE Trans. on Information Theory (see arXiv:1403.7164), as well
as some new paragraphs throughout the paper which are linked to new references.
