Rotational kinetics of absorbing dust grains in neutral gas

We study the rotational and translational kinetics of massive particulates (dust grains) absorbing the ambient gas. Equations for microscopic phase densities are deduced resulting in the Fokker-Planck equation for the dust component. It is shown that although there is no stationary distribution, the translational and rotational temperatures of dust tend to certain values, which differ from the temperature of the ambient gas. The influence of the inner structure of grains on rotational kinetics is also discussed.Comment: REVTEX4, 20 pages, 2 figure

Knowledge-based energy functions for computational studies of proteins

This chapter discusses theoretical framework and methods for developing knowledge-based potential functions essential for protein structure prediction, protein-protein interaction, and protein sequence design. We discuss in some details about the Miyazawa-Jernigan contact statistical potential, distance-dependent statistical potentials, as well as geometric statistical potentials. We also describe a geometric model for developing both linear and non-linear potential functions by optimization. Applications of knowledge-based potential functions in protein-decoy discrimination, in protein-protein interactions, and in protein design are then described. Several issues of knowledge-based potential functions are finally discussed.Comment: 57 pages, 6 figures. To be published in a book by Springe

Approximation of Sobolev classes by polynomials and ridge functions

AbstractLet Wpr(Bd) be the usual Sobolev class of functions on the unit ball Bd in Rd, and Wp∘,r(Bd) be the subclass of all radial functions in Wpr(Bd). We show that for the classes Wp∘,r(Bd) and Wpr(Bd), the orders of best approximation by polynomials in Lq(Bd) coincide. We also obtain exact orders of best approximation in L2(Bd) of the classes Wp∘,r(Bd) by ridge functions and, as an immediate consequence, we obtain the same orders in L2(Bd) for the usual Sobolev classes Wpr(Bd)