We review a recently proposed approach to the computation of the E-entropy of a given signal based on the exit-time statistics, i.e., one codes the signal by looking at the instants when the fluctuations are larger than a given threshold, epsilon. Moreover, we show how the exit-times statistics, when applied to experimental turbulent data, is able to highlight the intermediate-dissipative-range of turbulent fluctuations. (C) 2000 Elsevier Science B.V. All rights reserved.

The exit-time statistics of experimental turbulent data is analyzed. By looking at the exit-time moments (inverse structure functions) it is possible to have a direct measurement of scaling properties of the laminar statistics. It turns out that the inverse structure functions show a much more extended intermediate dissipative range than the structure functions, leading to the first clear evidence of the existence of such a range of scales. [S1063-651X(99)51012-X].

We present a numerical study of two-dimensional turbulent flows in the enstropy cascade regime, with different large-scale energy sinks. In particular, we study the statistics of more-than-differentiable velocity fluctuations by means of two sets of statistical estimators, namely inverse statistics and second-order differences. In this way, we are able to probe statistical fluctuations that are not captured by the usual spectral analysis. We show that a new set of exponents associated to more-than-differentiable fluctuations of the velocity field exists.

The first carved ambers appear in the Adriatic area at the end of the eighth century BC with the beginning of the Orientalizing period. Among the most active centers, the Etruscan Verucchio is one of the main poles for the sorting of amber. At the beginning of the sixth century, a fundamental role is exercised from Piceno and the Etruscan Felsina, whose intercept part of the tra!cs previously directed on the Adriatic road.

The computation of the eigenvalue decomposition of matrices is one of the most investigated problems in numerical linear algebra. In particular, real nonsymmetric tridiagonal eigenvalue problems arise in a variety of applications. In this paper the problem of computing an eigenvector corresponding to a known eigenvalue of a real nonsymmetric tridiagonal matrix is considered, developing an algorithm that combines part of a QR sweep and part of a QL sweep, both with the shift equal to the known eigenvalue. The numerical tests show the reliability of the proposed method.

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 use of a mathematical model is proposed in order to denoise X-ray two-dimensional patterns. The method relies on a generalized diffusion equation whose diffusion constant depends on the image gradients. The numerical solution of the diffusion equation provides an efficient reduction of pattern noise as witnessed by the computed peak of signal-to-noise ratio. The use of experimental data with different inherent levels of noise allows us to show the success of the method even in the case, experimentally relevant, when patterns are blurred by Poissonian noise.

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.

We obtain sharp decay estimates in time in the context of Sobolev spaces for smooth solutions to the one-dimensional Jin Xin model under the diffusion scaling, which are uniform with respect to the singular parameter of the scaling. This provides the convergence to the limit nonlinear parabolic equation both for large time and for the vanishing singular parameter. The analysis is performed by means of two main ingredients.

We revisit a method introduced by Tartar for proving global well-posedness of a semilinear hyperbolic system with null quadratic source in one space dimension. A remarkable point is that, since no dispersion effect is available for 1D hyperbolic systems, Tartar's approach is entirely based on spatial localization and finite speed of propagation.