In this article, we study in detail the fluid dynamics system proposed in Clarelli et al. (2013, J. Math. Biol., 66, 1387-1408) to model the formation of cyanobacteria biofilms. After analysing the linear stability of the unique non-trivial equilibrium of the system, we introduce in the model the influence of light and temperature, which are two important factors for the development of a cyanobacteria biofilm.

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 RapidCell (RC) model was originally developed to simulate flagellar bacterial chemotaxis in environments with spatiotemporally varying chemoattractant gradients. RC is best suited for motility simulations in unbounded nonfluid environments; this limits its use in biomedical applications hinging on bacteria-fluid dynamics in microchannels. In this study, we eliminated this constraint by coupling the RC model with the colloidal lattice Boltzmann (LB) model.

We investigate Poiseuille channel flow through intrinsically curved media, equipped with localized metric perturbations. To this end, we study the flux of a fluid driven through the curved channel in dependence of the spatial deformation, characterized by the parameters of the metric perturbations (amplitude, range, and density). We find that the flux depends only on a specific combination of parameters, which we identify as the average metric perturbation, and derive a universal flux law for the Poiseuille flow.

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.

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 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.

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 propose a mathematical model for the transport of DNA plasmids from the extracellular matrix up to the cell nucleus. The model couples two phenomena: the electroporation process, describing the cell membrane permeabilization to plasmids and the intracellular transport enhanced by the presence of microtubules. Numerical simulations of cells with arbitrary geometry, in 2D and 3D, and a network of microtubules show numerically the importance of the microtubules and the electroporation on the effectiveness of the DNA transfection, as observed by previous biological data.

The large amount of work on community detection and its applications leaves unaddressed one important question: the statistical validation of the results. We present a methodology able to clearly detect the truly significance of the communities identified by some technique, permitting us to discard those that could be merely the consequence of edge positions in the network. Given a community detection method and a network of interest, our procedure examines the stability of the partition recovered against random perturbations of the original graph structure.