We present an axisymmetric lattice Boltzmann model based on the Kupershtokh et al. multiphase model that is capable of solving liquid-gas density ratios up to 10(3). Appropriate source terms are added to the lattice Boltzmann evolution equation to fully recover the axisymrnetric multiphase conservation equations. We validate the model by showing that a stationary droplet obeys the Young-Laplace law, comparing the second oscillation mode of a droplet with respect to an analytical solution and showing correct mass conservation of a propagating density wave.

This paper proposes a crowd dynamic macroscopic model grounded on microscopic phenomenological observations which are upscaled by means of a formal mathematical procedure. The actual applicability of the model to real-world problems is tested by considering the pedestrian traffic along footbridges, of interest for Structural and Transportation Engineering. The genuinely macroscopic quantitative description of the crowd flow directly matches the engineering need of bulk results.

We consider the problem of determining quantitative information about corrosion occurring on an inaccesible part of a specimen. The data for the problem consist of prescribed current flux and voltage measurements on an accessible part of the specimen boundary. The problem is modelled by Laplace's equation with an unknown term in the boundary conditions. Our goal is recovering from the data. We prove uniqueness under certain regularity assumptions and construct a regularized numerical method for obtaining approximate solutions to the problem.

A critical issue in image restoration is noise removal, whose state-of-art algorithm, NonLocal Means, is highly demanding in terms of computational time. Aim of the present paper is to boost its performance by an efficient algorithm tailored to GPU hardware architectures. This algorithm adapts itself to several variants of the methodologies in terms of different strategies for estimating the involved filtering parameter, type of noise affecting data, multicomponent signals, spatial dimension of the images. Numerical experiments on brain Magnetic Resonance images are provided.

We apply the Z-control approach to a generalized predator prey system and consider the specific case of indirect control of the prey population. We derive the associated Z-controlled model and investigate its properties from the point of view of the dynamical systems theory. The key role of the design parameter A. for the successful application of the method is stressed and related to specific dynamical properties of the Z-controlled model. Critical values of the design parameter are also found, delimiting the lambda-range for the effectiveness of the Z-method.

We study the conformational freedom of a protein made by two rigid domains connected by a flexible linker. The conformational freedom is represented as an unknown probability distribution on the space of allowed states. A new algorithm for the calculation of the maximum allowable probability is proposed, which can be extended to any type of measurements. In this paper we use pseudo contact shifts and residual dipolar coupling. We reconstruct a single central tendency in the distribution and discuss in depth the results.

Nature routinely presents us with spectacular demonstrations of organization and orchestrated motion in living species. Efficient information transfer among the individuals is known to be instrumental to the emergence of spatial patterns (e.g. V-shaped formations for birds or diamond-like shapes for fishes), responding to a specific functional goal such as predatory avoidance or energy savings. Such functional patterns materialize whenever individuals appoint one of them as a leader with the task of guiding the group towards a prescribed target destination.

We discuss the intriguing ability of minimal kinetic theory to describe a broad variety of complex non-equilibrium flows across scales of motion. It is argued that, besides major computational progress, minimal kinetic theory also provides a new conceptual framework to investigate the complexities of flowing matter far from equilibrium.

We present a Lattice Boltzmann method for the simulation of a wide range of Knudsen regimes. The method is assessed in terms of normalised discharge for flow across parallel plates and three-dimensional flows in porous media. Available analytical solutions are well reproduced, supporting the the method as an appealing candidate to bridge the gap between the hydrodynamic regime and free molecular motion.

Here we describe NeuroPype, which is a free open-source Python package, we developed for efficient multi-thread processing of MEG and EEG studies. The proposed package is based on the Nipype framework , a tool developed in fMRI field, which facilitates data analyses by wrapping many commonly-used neuro-imaging software into a common python framework.