A semi-implicit semi-Lagragian mixed finite-difference finite-volume model for the shallow water equations on a rotating sphere is considered The main features of the model are the finite-volume approach for the continuity equation and the vectorial treatment of the momentum equation. Pressure and Coriolis terms in the momentum equation and velocity in the continuity equation are treated semi-implicitly. Discretization of this model led to the introducion, in a previous paper, of a splitting technique which highly reduces the computational effort for the numerical solution. In this paper we solve the full set of equations, without splitting, introducing an ad hoc algorithm A von Neumann stability analysis of this scheme is performed to establish the unconditional stability of the new proposed method Finally, we compare the efficiency of the two approaches by numerical experiments on a standard test problem Results show that due to the devised algorithm, the solution of the full system of equations is much more accurate while slightly increasing the computational cost. A semi-implicit semi-Lagrangian mixed finite-difference finite-volume model for the shallow water equations on a rotating sphere is considered. The main features of the model are the finite-volume approach for the continuity equation and the vectorial treatment of the momentum equation. Pressure and Coriolis terms in the momentum equation and velocity in the continuity equation are treated semi-implicitly. Discretization of this model led us to introduce, in a previous paper, a splitting technique which highly reduces the computational effort for the numerical solution. In this paper we solve the full set of equations, without splitting, introducing an 'ad hoc' algorithm. A von Neumann stability analysis of this scheme is performed to establish the unconditional stability of the new proposed method. Finally, we compare the efficiency of the two approaches by numerical experiments on a standard test problem. Our results show that, due to the devised algorithm, the solution of the full system of equations is much more accurate while slightly increases the computational cost.

Conditions are proven which assure the summability of the first difference of the fundamental matrix of nonconvolution Volterra discrete equations. These conditions are applied to the \st analysis of some linear methods for solving Volterra integral equations of nonconvolution type.

We study general over-relaxation Markov Chain Monte Carlo samplers for multivariate Gaussian densities. We provide conditions for convergence based on the spectral radius of the transition matrix and on detailed balance. We illustrate these algorithms using an image analysis example.

An algorithm for the approximate evaluation of the Hilbert transform has been proposed. The convergence of the procedure is proved. The stability of the algorthim is considered and some numerical examples are given.

We propose a semilinear relaxation approximation to the unique entropy solutions of an initial boundary value problem for a scalar conservation law. Without any restriction on the initial--boundary data or on the flux function, we prove uniform a priori estimates and convergence of that approximation as the relaxation parameter tends to zero.

It iswell-knownthat multivariate curve estimation suffers from the “curse of dimensionality.”However, reasonable estimators are possible, even in several dimensions, under appropriate restrictions on the complexity of the curve. In the present paper we explore how much appropriate wavelet estimators can exploit a typical restriction on the curve such as additivity. We first propose an adaptive and simultaneous estimation procedure for all additive components in additive regression models and discuss rate of convergence results and data-dependent truncation rules for wavelet series estimators. To speed up computation we then introduce a wavelet version of functional ANOVA algorithm for additive regression models and propose a regularization algorithm which guarantees an adaptive solution to the multivariate estimation problem. Some simulations indicate that wavelets methods complement nicely the existing methodology for nonparametric multivariate curve estimation.

In this paper we study several different methods both deterministic and stochastic to solve the Nuclear Magnetic Resonance (NMR) relaxometry problem. This problem is strongly related to finding a non-negative function given a finite number of values of its Laplace transform embedded in noise. Some of the methods considered here are new. We also propose a procedure which exploits and combines the main features of these methods. To show the performances of this procedure, some results of applying it to synthetic data are finally reported.

By improving a one-dimensional model proposed by De Fabritiis, Mancini, Mansutti and Succi in 1998, we develop a simple reaction model for liquid-solid phase transitions in the context of the lattice Boltzmann method with enhanced collisions.Calculations for a two-dimensional test problem of gallium melting and for a two-dimensional anisotropic growth of dendrites are presented and commented on.

We introduce a geometry of interaction model given by an algebra of clauses equipped with resolution (following \cite{Girard95d}) which proofs of Elementary Linear Logic can be interpreted into. In order to extend geometry of interaction computation (the so called {\em execution formula}) to a wider class of programs in the algebra than just those coming from proofs, we define a variant of execution (called {\em weak execution}). Its application to any program of clauses is shown to terminate with a bound on the number of steps which is elementary in the size of the program. We establish that weak execution coincides with standard execution on programs coming from proofs.

The Italian Ministry of Education in collaboration of the Italian National Research Council are engaged in joint activities concerning the modeling, design and prototype implementation of an adaptive e-framework supporting the interactions of various actors of the national teacher training system. The framework includes patterns of static and adaptive versions for resources-services allocation and management.

The Infrared Atmospheric Sounding Interferometer (IASI) has 8461 potential channels to be exploited for inversions of geophysical parameters. In this paper we analyse two different strategies for their reduction. The first one looks for suitable spectral ranges where the inverse problem is as linear as possible; the second one is based on the cluster analysis theory. Our aim is to minimise the potential information loss evaluated by directly comparing the retrieved temperature and water vapour profiles on a complete set of test atmospheres.