The study of the underlying physics of soft flowing materials depends heavily on numerical simulations, due to the complex structure of the governing equations reflecting the competition of concurrent mechanisms acting at widely disparate scales in space and time. A full-scale computational modelling remains a formidable challenge since it amounts to simultaneously handling six or more spatial decades in space and twice as many in time.

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.

Particular solutions of a class of higher order ordinary differential equations, with non-constant coefficients, are determined by using the properties of the Laguerre exponentials functions introduced by G. Dattoli and P. E. Ricci in [4]. © 2004, Heldermann Verlag. All rights reserved.

Let P and (P) over tilde be the laws of two discrete-time stochastic processes defined on the sequence space S-N,where S is a finite set of points. In this paper we derive a bound on the total variation distance d(TV)(P, (P) over tilde) in terms of the cylindrical projections of P and (P) over tilde. We apply the result to Markov chains with finite state space and random walks on Z with not necessarily independent increments, and we consider several examples.

Coronavirus disease 2019 (COVID-19) death rate differs depending on sex. Some hypotheses can be put forward on the basis of current knowledge on gender differences in respiratory viral diseases.

We present an extension of the multiparticle collision dynamics method for flows with complex interfaces, including supramolecular near-contact interactions mimicking the effect of surfactants. The new method is demonstrated for the case of (i) short range repulsion of droplets in close contact, (ii) arrested phase separation, and (iii) different pattern formation during spinodal decomposition of binary mixtures.

Fluid flows hosting electrical phenomena are the subject of a fascinating and highly interdisciplinary scientific field. In recent years, the extraordinary success of electrospinning and solution-blowing technologies for the generation of polymer nanofibers has motivated vibrant research aiming at rationalizing the behavior of viscoelastic jets under applied electric fields or other stretching fields including gas streams.

In the present paper, we propose a numerical method for the simultaneous approximation of the finite Hilbert and Hadamard transforms of a given function f, supposing to know only the samples of f at equidistant points. As reference interval we consider [-1,1] and as approximation tool we use iterated Boolean sums of Bernstein polynomials, also known as generalized Bernstein polynomials. Pointwise estimates of the errors are proved, and some numerical tests are given to show the performance of the procedures and the theoretical results.

The paper deals with de la Vallee Poussin type interpolation on the square at tensor product Chebyshev zeros of the first kind. The approximation is studied in the space of locally continuous functions with possible algebraic singularities on the boundary, equipped with weighted uniform norms. In particular, simple necessary and sufficient conditions are proved for the uniform boundedness of the related Lebesgue constants. Error estimates in some Sobolev-type spaces are also given.

In this paper we revisit the problem of performing a QZ step with a so-called "perfect shift", which is an "exact" eigenvalue of a given regular pencil lambda B-A in unreduced Hessenberg-Triangular form. In exact arithmetic, the QZ step moves that eigenvalue to the bottom of the pencil, while the rest of the pencil is maintained in Hessenberg-Triangular form, which then yields a deflation of the given eigenvalue. But in finite-precision the QZ step gets "blurred" and precludes the deflation of the given eigenvalue.