The likelihood of a subglacial lake beneath Amundsenisen Plateau at Southern Spitzbergen, Svalbard, pointed out by the flat signal within the Ground Penetrating Radar (GPR) remote survey of the area, is justified, here, via numerical simulation.This investigation has been developed under the assumption that the icefield thickness does not change on average, as it is confirmed by recently published physical measurements taken over the past 40 years.

The melting of glaciers coming with climate change threatens the heritage of the last glaciation of Europe likely contained in subglacial lakes in Greenland and Svalbard. This aspect urges specialists to focus their studies (theoretical, numerical, and on-field) on such fascinating objects. Along this line, we have approached the validation of the conjecture of the existence of a subglacial lake beneath the Amundsenisen Plateau at South-Spitzbergen, Svalbard, where ground penetrating radar measurements have revealed several flat signal spots, the sign of the presence of a body of water.

The segmentation of speckled images, as the synthetic aperture radar (SAR) images, is usually recognized as a very complex problem, because of the speckle, multiplicative noise, which produces granular images. In segmentation problems, based on level set method, the evolution of the curve is determined by a speed function, which is fundamental to achieve a good segmentation. In this paper we propose a study of the new speed function obtained by the linear combination of image average intensity and image gradient speed functions.

Neglecting the horizontal variability of the atmosphere in the forward model for the simulation of limb emission radiances causes a systematic error in MIPAS retrieved profiles. The horizontal gradient model will be introduced into the Optimized Retrieval Model (ORM) v8, which will be used for the final ESA reprocessing of the whole mission. Several optimizations exploiting the spherical symmetry of the atmosphere can no longer be used. Therefore, both the ray tracing and the radiative transfer integration algorithms have been completely rewritten.

The development of high-efficiency porous catalyst membranes critically depends on our understanding of where the majority of the chemical conversions occur within the porous structure. This requires mapping of chemical reactions and mass transport inside the complex nanoscale architecture of porous catalyst membranes which is a multiscale problem in both the temporal and spatial domains.

A deep understanding of the dynamics and rheology of suspensions of vesicles, cells, and capsules is relevant for different applications, ranging from soft glasses to blood flow [1]. I will present the study of suspensions of fluid vesicles by a combination of molecular dynamics and mesoscale hydrodynamics simulations (multi-particle collision dynamics) in two dimensions [2], pointing out the big potential of the numerical method to address problems in soft matter.

We investigate front propagation in systems with diffusive and subdiffusive behavior. The scaling behavior of moments of the diffusive problem, both in the standard and in the anomalous cases, is not enough to determine the features of the reactive front. In fact, the shape of the bulk of the probability distribution of the transport process, which determines the diffusive properties, is important just for preasymptotic behavior of front propagation, while the precise shape of the tails of the probability distribution determines asymptotic behavior of front propagation.

A deep understanding of the dynamics and rheology of suspensions of vesicles, cells, and capsules is relevant for different applications, ranging from soft glasses to blood flow [1]. I will present the study of suspensions of fluid vesicles by a combination of molecular dynamics and mesoscale hydrodynamics simulations (multi-particle collision dynamics) in two dimensions [2], pointing out the big potential of the numerical method to address problems in soft matter.

The parallel implementation of MUPHY, a concurrent multiscale code for large-scale hemodynamic simulations in anatomically realistic geometries, for multi-GPU platforms is presented. Performance tests show excellent results, with a nearly linear parallel speed-up on up to 32GPUs and a more than tenfold GPU/CPU acceleration, all across the range of GPUs. The basic MUPHY scheme combines a hydrokinetic (Lattice Boltzmann) representation of the blood plasma, with a Particle Dynamics treatment of suspended biological bodies, such as red blood cells.