This work investigates the capability of supervised classification methods in detecting both major tissues and subcortical structures using multispectral brain magnetic resonance images. First, by means of a realistic digital brain phantom, we investigated the classification performance of various Discriminant Analysis methods, K-Nearest Neighbor and Support Vector Machine.

The problem of asymptotic features of front propagation in stirred media is addressed for laminar and turbulent velocity fields. In particular we consider the problem in two dimensional steady and unsteady cellular flows in the limit of very fast reaction and sharp front, i.e., in the geometrical optics limit. In the steady case we provide an analytical approximation for the front speed, vf, as a function of the stirring intensity, U, in good agreement with the numerical results.

We examine spatially explicit models described by reaction-diffusion partial differential equations for the study of predator-prey population dynamics. The numerical methods we propose are based on the coupling of a finite difference/element spatial discretization and a suitable partitioned Runge-Kutta scheme for the approximation in time. The RK scheme here implemented uses an implicit scheme for the stiff diffusive term and a partitioned RK symplectic scheme for the reaction term (IMSP scheme).

In a recent paper, we investigated the uniform convergence of Lagrange interpolation at the zeros of the orthogonal polynomials with respect to a Freud-type weight in the presence of constraints. We show that by a simple procedure it is always possible to transform the matrices of these zeros into matrices such that the corresponding Lagrange interpolating polynomial with respect to the given constraints well approximates a given function.

In order to take into account the territory in which the outputs are in the market and the time-depending firms' strategies, the discrete Cournot duopoly game (with adaptive expectations, modeled by Kopel) is generalized through a non autonomous reaction-diffusion binary system of PDEs, with self and cross diffusion terms. Linear and nonlinear asymptotic $L^2$-stability, via the Lapunov Direct Method and a nonautonomous energy functional, are investigated.

The starting transient of highly under-expanded supersonic jets is studied by means of very high resolution weighted essentially non oscillatory finite volume schemes, coupled with a positivity-preserving scheme in order to ensure positivity of pressure and density for high compression/expansion ratio. Numerical behaviour of the schemes is investigated in terms of grid resolution, formal accuracy and different approximated Riemann solvers. The transient flow field is also discussed.

We use a framework that takes into account the effects of deformation of both the solid and fluid in the solidification process, to study the solidification of a semi-infinite layer of fluid. It is shown that the time required for solidification, and the final location of the interface are significantly different form the predictions of the classical Stefan problem. A detailed numerical solution of the initial-boundary value problem is provided for a variety of values for non-dimensional parameters relevant for freezing water.