The recent COVID-19 pandemic came alongside with an "infodemic", with online social media flooded by often unreliable information associating the medical emergency with popular subjects of disinformation. In Italy, one of the first European countries suffering a rise in new cases and dealing with a total lockdown, controversial topics such as migrant flows and the 5G technology were often associated online with the origin and diffusion of the virus.

Here some issues are studied, related to the numerical solution of Richards' equation in a one dimensional spatial domain by a technique based on the Transversal Method of Lines (TMoL). The core idea of TMoL approach is to semi-discretize the time derivative of Richards' equation: afterward a system of second order differential equations in the space variable is derived as an initial value problem. The computational framework of this method requires both Dirichlet and Neumann boundary conditions at the top of the column. The practical motivation for choosing such a condition is argued.

The main focus of this paper is the characterization and exploitation of the asymptotic spectrum of the saddle--point matrix sequences arising from the discretization of optimization problems constrained by elliptic partial differential equations. They uncover the existence of an hidden structure in these matrix sequences, namely, they show that these are indeed an example of Generalized Locally Toeplitz (GLT) sequences.

A (2+2)-dimensional kinetic equation, directly inspired by the run-and-tumble modeling of chemotaxis dynamics is studied so as to derive a both ''2D well-balanced'' and ''asymptotic-preserving'' numerical approximation. To this end, exact stationary regimes are expressed by means of Laplace transforms of Fourier-Bessel solutions of associated elliptic equations. This yields a scattering S-matrix which permits to formulate a timemarching scheme in the form of a convex combination in kinetic scaling.

Background: The aim of a recent research project was the investigation of the mechanisms involved in the onset of type 2 diabetes in the absence of familiarity. This has led to the development of a computational model that recapitulates the aetiology of the disease and simulates the immunological and metabolic alterations linked to type-2 diabetes subjected to clinical, physiological, and behavioural features of prototypical human individuals. Results: We analysed the time course of 46,170 virtual subjects, experiencing different lifestyle conditions.

Conformational variability and heterogeneity are crucial determinants of the function of biological macromolecules. The possibility of accessing this information experimentally suffers from severe under-determination of the problem, since there are a few experimental observables to be accounted for by a (potentially) infinite number of available conformational states. Several computational methods have been proposed over the years in order to circumvent this theoretically insurmountable obstacle.

A composite specimen, made of two slabs and an interface A is heated through one of its sides S, in order to evaluate the thermal conductance H of A. The direct model consists of a system of Initial Boundary Value Problems completed by suitable transmission conditions. Thanks to the properties of multilayer diffusion, we reduce the problem to the slab between A and S only. In this case evaluating the thermal resistance of A means to identify a coefficient in a Robin boundary condition. We evaluate H numerically by means of Thin Plate Approximation.