The Smoothed Particle Hydrodynamics (SPH) method, often used for the modelling of the Navier- Stokes equations by a meshless Lagrangian approach, is revisited from the point of view of Large Eddy Simulation (LES). To this aim, the LES filtering procedure is recast in a Lagrangian framework by defining a filter that moves with the positions of the fluid particles at the filtered velocity.

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.

MagnetoEncephaloGraphy (MEG) and ElectroEncephaloGraphy (EEG) are the most common non-invasive brain imaging techniques for monitoring the electrical brain activity with millisecond resolution. Due to their high, millisecond, temporal resolution, these techniques are also the most suitable for studying the dynamic interplay of between brain regions during information processing. In clinical settings, MEG and EEG are valuable methods for the pre-surgical evaluation of patients with pharmaco-resistant epilepsy.

Investigation about the mechanisms involved in the onset of type 2 diabetes in absence of familiarity is the focus of a research project which has led to the development of a computational model that recapitulates the aetiology of the disease. The model simulates the metabolic and immunological alterations related to type-2 diabetes associated to several clinical, physiological and behavioural characteristics of representative virtual patients.

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.

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.

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.

Network embedding, also known as network representation learning, aims at defining low-dimensional, continuous vector representation of nodes to maximally preserve the network structure. Recent efforts attempt to extend network embedding to attributed networks where nodes are enriched with descriptors, to enhance interpretability. However, most of these efforts seldom consider the additional knowledge relevant to the aim of the downstream network analysis, i.e. task-related information. When they do, they are analysis-specific and thus lack adaptability to alternative tasks.

In this study, we computationally corroborate the flow of rock glaciers against borehole measurements, within the context of a model previously developed (2020). The model is, here, tested against the simulation of the sliding motion of the Murtel-Corvatsch alpine glacier, which is characterized in detail in the literature with internal structure description and borehole deformations measurement.