In this paper, we propose a new mathematical model describing the effect of phosphocitrate (PC) on sodium sulphate crystallization inside bricks. This model describes salt and water transport, and crystal formation in a one dimensional symmetry. This is a preliminary study that takes into account mathematically the effects of inhibitors inside a porous stone. To this aim, we introduce two model parameters: the crystallization rate coefficient, which depends on the nucleation rate, and the specific volume of precipitated salt.

We present a method for applying a class of velocity-dependent forces within a multicomponent lattice Boltzmann equation simulation that is designed to recover continuum regime incompressible hydrodynamics. This method is applied to the problem, in two dimensions, of constraining to uniformity the tangential velocity of a vesicle membrane implemented within a recent multicomponent lattice Boltzmann simulation method, which avoids the use of Lagrangian boundary tracers.

In this paper we consider drug binding in the arterialwall following delivery by a drug-eluting stent. Whilst it is now generally accepted that a non-linear saturable reversible binding model is required to properly describe the binding process, the precise form of the binding model varies between authors. Our particular interest in this manuscript is in assessing to what extent modelling specific and non-specific binding in the arterial wall as separate phases is important.

A methodology to generate calibrated maps of soil moisture from C-band synthetic aperture radar (SAR) images processed by SAR interferometry (InSAR) technique is presented. The proposed methodology uses atmospheric phase delay (APD) maps obtained from a time series of Sentinel-1 interferograms, to disentangle the APD and soil moisture contributions to Sentinel-1 interferograms. We show how the high spatial resolution and short temporal baseline of Sentinel-1 image can help to estimate soil moisture using a daisy chain InSAR processing.

A new technique for nonparametric regression of multichannel signals is presented. The technique is based on the use of the Rational-Dilation Wavelet Transform (RADWT), equipped with a tunable Q-factor able to provide sparse representations of functions with different oscillations persistence. In particular, two different frames are obtained by two RADWT with different Q-factors that give sparse representations of functions with low and high resonance.

Thanks to innovative sample-preparation and sequencing technologies, gene expression in individual cells can now be measured for thousands of cells in a single experiment. Since its introduction, single-cell RNA sequencing (scRNA-seq) approaches have revolutionized the genomics field as they created unprecedented opportunities for resolving cell heterogeneity by exploring gene expression profiles at a single-cell resolution. However, the rapidly evolving field of scRNA-seq invoked the emergence of various analytics approaches aimed to maximize the full potential of this novel strategy.

Mortality models play a basic role in the evaluation of longevity risk by demographers and actuaries. Their performance strongly depends on the different patterns shown by mortality data in different countries. A comprehensive quantitative comparison of the most used methods for forecasting mortality is presented, aimed at evaluating both the goodness of fit and the forecasting performance of these mortality models on Italian demographic data.

If I? R is a bounded interval, we prove the boundedness of Calderón singular operator and of Hardy-Littlewood Maximal operator in the generalized weighted Grand Lebesgue spaces Lpp),?(I), 1 < p< ?.

Defining accurate and flexible models for real-world networks of human beings is instrumental to understand the observed properties of phenomena taking place across those networks and to support computer simulations of dynamic processes of interest for several areas of research - including computational epidemiology, which is recently high on the agenda. In this paper we present a flexible model to generate age-stratified and geo-referenced synthetic social networks on the basis of widely available aggregated demographic data and, possibly, of estimated age-based social mixing patterns.