In this paper, we numerically investigate the breakup dynamics of droplets in an emulsion flowing in a tapered microchannel with a narrow constriction. The mesoscale approach for multicomponent fluids with near contact interactions is shown to capture the deformation and breakup dynamics of droplets interacting within the constriction, in agreement with experimental evidence. In addition, it permits us to investigate in detail the hydrodynamic phenomena occurring during breakup stages.

Primary biliary cholangitis (PBC) is a chronic, cholestatic, immune-mediated, and progressive liver disorder. Treatment to preventing the disease from advancing into later and irreversible stages is still an unmet clinical need. Accordingly, we set up a drug repurposing framework to find potential therapeutic agents targeting relevant pathways derived from an expanded pool of genes involved in different stages of PBC.

Drug repurposing is a highly active research area, aiming at finding novel uses for drugs that have been previously developed for other therapeutic purposes. Despite the flourishing of methodologies, success is still partial, and different approaches offer, each, peculiar advantages. In this composite landscape, we present a novel methodology focusing on an efficient mathematical procedure based on gene similarity scores and biased random walks which rely on robust drug-gene-disease association data sets.

We study some numerical properties of a nonconvex variational problem which arises as the continuous limit of a discrete optimization method designed for the smoothing of images with preservation of discontinuities. The functional that has to be minimized fails to attain a minimum value. Instead, minimizing sequences develop gradient oscillations which allow them to reduce the value of the functional. The oscillations of the gradient exhibit analogies with microstructures in ordered materials. The pattern of the oscillations is analysed numerically by using discrete parametrized measures.

Started as a hyped technology a few years ago, IoT is now a reality providing sensing and computing capabilities from SCADA systems to households. At their core, IoT devices connect to the outside world to share sensed or computed data. However, the sensitivity and privacy of shared data has made access management a stringent need also for the IoT. In particular, continuous authentication could solve a few security issues, like session hijacking, via checking device legitimacy for each exchanged message and preventing attackers from pretending their actions came from authenticated devices.

Some known models in phase separation theory (Hele-Shaw, nonlocal mean curvature motion) and their approximations by means of Cahn-Hilliard and nonlocal Allen-Cahn equations are proposed as a tool to generate planar curve-shortening flows without shrinking. This procedure can be seen as a level set approach to area-preserving geometric flows in the spirit of Sapiro and Tannenbaum [38], with application to shape recovery. We discuss the theoretical validation of this method and its implementation to problems of shape recovery in Computer Vision.

The dynamics and rheology of a vesicle confined in a channel under shear flow are studied at finite temperature. The effect of finite temperature on vesicle motion and system viscosity is investigated. A two-dimensional numerical model, which includes thermal fluctuations and is based on a combination of molecular dynamics and mesoscopic hydrodynamics, is used to perform a detailed analysis in a wide range of the Peclet numbers (the ratio of the shear rate to the rotational diffusion coefficient).

In this paper, the modal analysis model, made up by a linear combination of complex exponential functions, is considered. Padè approximants to the Z-transform of a noisy sample are then considered, and the asymptotic locus of their poles is studied. It turns out that this locus is strongly related to the complex exponentials of the model. By exploiting these properties, powerful methods for estimating the model parameters can be devised, which have both denoising and super-resolution capabilities.

This paper presents a sparse factorization for the delay Vandermonde matrix (DVM) and a faster, exact, radix-2, and completely recursive DVM algorithm to realize millimeter wave beamformers in wireless communication networks. The proposed algorithm will reduce the complexity of $N$-beam wideband beamformers from $\mathcal{O}(N^2)$ to $\mathcal{O}(N {\rm\: log\:} N)$. The scaled DVM algorithm is at least 97$\%$ faster than the brute-force scale DVM by a vector product. The signal flow graphs of the scaled DVM algorithm are shown to elaborate the simplicity of the proposed algorithm.