In the past two decades, 7 coronaviruses have infected the human population, with two major outbreaks caused by SARS-CoV and MERS-CoV in the year 2002 and 2012, respectively. Currently, the entire world is facing a pandemic of another coronavirus, SARS-CoV-2, with a high fatality rate. The spike glycoprotein of SARS-CoV-2 mediates entry of virus into the host cell and is one of the most important antigenic determinants, making it a potential candidate for a vaccine. In this study, we have computationally designed a multi-epitope vaccine using spike glycoprotein of SARS-CoV-2.

The study takes up some issues relating to the location of the workshops that produced the valuable figured ambers that marked the aristocratic burials of southern Italy from the eighth to fifth century BC. The contribution of findings and recent studies enabled us to assign some groups of artifacts to the activity of different workshops and even to identify outstanding artistic personalities, highlighting the undeniable stylistic connections between them.

The problem of inverse statistics (statistics of distances for which the signal fluctuations are larger than a certain threshold) in differentiable signals with power law spectrum, E(k) approximately k(-alpha), 3< or =alpha<5, is discussed. We show that for these signals, with random phases, exit-distance moments follow a bifractal distribution. We also investigate two dimensional turbulent flows in the direct cascade regime, which display a more complex behavior.

We provide a framework to extend the relative entropy method to a class of diffusive relaxation systems with discrete velocities. The methodology is detailed in the toy case of the 1D Jin-Xin model under the diffusive scaling, and provides a direct proof of convergence to the limit parabolic equation in any interval of time, in the regime where the solutions are smooth. Recently, the same approach has been successfully used to show the strong convergence of a vector-BGK model to the 2D incompressible Navier-Stokes equations.

The aim of this paper is to prove the strong convergence of the solutions to a vector-BGK model under the diffusive scaling to the incompressible Navier-Stokes equations on the two-dimensional torus. This result holds in any interval of time [0,T], with T>0. We also provide the global in time uniform boundedness of the solutions to the approximating system. Our argument is based on the use of local in time H-estimates for the model, established in a previous work, combined with the L-relative entropy estimate and the interpolation properties of the Sobolev spaces.

WeinvestigatethelinearstabilityofshearsneartheCouetteflowforaclassof2Dincompressible stably stratified fluids. Our main result consists of nearly optimal decay rates for perturbations of stationary states whose velocities are monotone shear flows (U (y), 0) and have an exponential density profile. In the case of the Couette flow U(y) = y, we recover the rates predicted by Hartman in 1975, by adopting an explicit point-wise approach in frequency space. As a by-product, this implies optimal decay rates as well as Lyapunov instability in L2 for the vorticity.

Casual mutations and natural selection have driven the evolution of protein amino acid sequences that we observe at present in nature. The question about which is the dominant force of proteins evolution is still lacking of an unambiguous answer. Casual mutations tend to randomize protein sequences while, in order to have the correct functionality, one expects that selection mechanisms impose rigid constraints on amino acid sequences.

A notion of "2D well-balanced" for drift-diffusion is proposed. Exactness at steady-state, typical in 1D, is weakened by aliasing errors when deriving "truly 2D" numerical fluxes from local Green's function. A main ingredient for proving that such a property holds is the optimality of the trapezoidal rule for periodic functions. In accordance with practical evidence, a "Bessel scheme" previously introduced in [SIAM J. Numer. Anal. 56 (2018), pp. 2845-2870] is shown to be "2D well-balanced" (along with former algorithms known as "discrete weighted means" or "tailored schemes".