A Model for Urban Social Networks

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.

Why diffusion-based preconditioning of Richards equation works: spectral analysis and computational experiments at very large scale.

We consider here a cell-centered finite difference approximation of the Richards equation in three dimensions, averaging for interface values the hydraulic conductivity, a highly nonlinear function, by arithmetic, upstream and harmonic means. The nonlinearities in the equation can lead to changes in soil conductivity over several orders of magnitude and discretizations with respect to space variables often produce stiff systems of differential equations.

Task-oriented attributed network embedding by multi-view features

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.

The core-radius approach to supercritical fractional perimeters, curvatures and geometric flows

We consider a core-radius approach to nonlocal perimeters governed by isotropic kernels having critical and supercritical exponents, extending the nowadays classical notion of s-fractional perimeter, defined for 0<s<1, to the case s>=1. We show that, as the core-radius vanishes, such core-radius regularized s-fractional perimeters, suitably scaled, ?-converge to the standard Euclidean perimeter.

An Integration by Parts Formula for Functionals of the Dirichlet-Ferguson Measure, and Applications

The Dirichlet-Ferguson measure is a random probability measure that has seen widespread use in Bayesian nonparametrics. Our main results can be seen as a first step towards the development of a stochastic analysis of the Dirichlet-Ferguson measure. We define a gradient that acts on functionals of the measure and derive its adjoint. The corresponding integration by parts formula is used to prove a covariance representation formula for square integrable functionals of the Dirichlet-Ferguson measure and to provide a quantitative central limit theorem for the first chaos.

Minimising movements for the motion of discrete screw dislocations along glide directions

In Alicandro et al. (J Mech Phys Solids 92:87-104, 2016) a simple discrete scheme for the motion of screw dislocations toward low energy configurations has been proposed. There, a formal limit of such a scheme, as the lattice spacing and the time step tend to zero, has been described. The limiting dynamics agrees with the maximal dissipation criterion introduced in Cermelli and Gurtin (Arch Ration Mech Anal 148, 1999) and predicts motion along the glide directions of the crystal.