  In this paper we study the separation between two complexity measures: the
degree of a Boolean function as a polynomial over the reals and its block
sensitivity. We show that separation between these two measures can be improved
from $ d^2(f) \geq bs(f) $, established by Tal, to $ d^2(f) \geq (\sqrt{10} -
2)bs(f) $. As a corollary, we show that separations between some other
complexity measures are not tight as well, for instance, we can improve recent
sensitivity conjecture result by Huang to $s^4(f) \geq (\sqrt{10} - 2)bs(f)$.
Our techniques are based on paper by Nisan and Szegedy and include more
detailed analysis of a symmetrization polynomial.
  In our next result we show the same type of improvement in the separation
between the approximate degree of a Boolean function and its block sensitivity:
we show that $deg_{1/3}^2(f) \geq \sqrt{6/101} bs(f)$ and improve the previous
result by Nisan and Szegedy $ deg_{1/3}(f) \geq \sqrt{bs(f)/6} $. In addition,
we construct an example which shows that gap between constants in the lower
bound and in the known upper bound is less than $0.2$.
  In our last result we study the properties of conjectured fully sensitive
function on 10 variables of degree 4, existence of which would lead to
improvement of the biggest known gap between these two measures. We prove that
there is the only univariate polynomial that can be achieved by symmetrization
of this function by using the combination of interpolation and linear
programming techniques.
