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.

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.

The main steps taking the Lattice Boltzmann (LB) method beyond the realm of continuum hydrodynamics are discussed along with an appraisal of future prospects for coupling LB with other computational kinetic methods, such as Bird's Direct Simulation Monte Carlo and/or Discrete Velocity Models.

The effects of compressibility on Rayleigh-Taylor instability (RTI) are investigated by inspecting the interplay between thermodynamic and hydrodynamic nonequilibrium phenomena (TNE, HNE, respectively) via a discrete Boltzmann model. Two effective approaches are presented, one tracking the evolution of the local TNE effects and the other focusing on the evolution of the mean temperature of the fluid, to track the complex interfaces separating the bubble and the spike regions of the flow.

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.

The vortex-body interaction problem, that characterizes the flow field of a rudder placed downstream of a single-blade marine rotor, is investigated by numerical simulations.

Marine propellers in behind-hull conditions develop, in addition to thrust and torque, in-plane loads that are strictly related to fatigue stress of the propulsive shaft bearings, hull-induced vibrations and the dynamic response of the ship while maneuvering or experiencing wave induced motions. An in-depth understanding of their nature as well as their quantification in typical design and off-design operative scenario is fundamental for improving ship design criteria.

We investigate the non-equilibrium hydrodynamic effects on the reactivity of a nanoporous catalytic sample. Numerical simulations using the Lattice Boltzmann Method (LBM) show that non-equilibrium effects enhance the reactivity of the porous sample, in agreement with theoretical predictions [1]. In addition, we provide a quantitative assessment of the reactivity in terms of the thickness of the reactive layer inside the nanoporous catalytic sample.

Planktonic copepods are small crustaceans that have the ability to swim by quick powerful jumps. Such an aptness is used to escape from high shear regions, which may be caused either by flow perturbations, produced by a large predator (i.e., fish larvae), or by the inherent highly turbulent dynamics of the ocean. Through a combined experimental and numerical study, we investigate the impact of jumping behavior on the small-scale patchiness of copepods in a turbulent environment.

Background: Electrocorticography (ECoG) measures the distribution of the electrical potentials on the cortex produced by the neural currents. A full interpretation of ECoG data requires solving the ill-posed inverse problem of reconstructing the spatio-temporal distribution of the neural currents. This study addresses the ECoG source modeling developing a beamformer method.