Deterioration of stones is a complex problem and one of the main concern for people working in the field of conservation and restoration of cultural heritage. One important point in cultural heritage is to obtain information about the damage in a non-invasive way. By this paper, we propose a new non-invasive tool that permits evaluation of the thickness of (Formula presented.) (gypsum) grown (sulfation) on marble stones, using a mathematical model on data detected by pulsed infrared thermography.

This paper investigates the problem of quantifying longevity risk in a quantile perspective. In this field, the idea of deepening the expected changes of future mortality rates over a single year is gaining. In the following the authors propose an approach which combines a stochastic model for the evolution of mortality rates and a quantile analysis of the mortality distribution in order to capture the trend component of longevity. An ex post analysis is proposed, relying on the past mortality experience of the Italian male population measured in the period of 1954-2008.

We analyze a peer-assisted Video-on-Demand (VoD) system in which users contribute their upload bandwidth to the redistribution of a video that they are downloading or that they have cached locally. Our target is to characterize the additional bandwidth that servers must supply to immediately satisfy all requests to watch a given video. We develop an approximate fluid model to compute the required server bandwidth in the sequential delivery case, as well as in controlled nonsequential swarms.

We present and compare the performances of two many-core architectures: the Nvidia Kepler and the Intel MIC both in a single system and in cluster configuration for the simulation of spin systems. As a benchmark we consider the time required to update a single spin of the 3D Heisenberg spin glass model by using the Over-relaxation algorithm. We present data also for a traditional high-end multi-core architecture: the Intel Sandy Bridge.

In this paper we propose a new modeling tech- nique for vehicular traffic flow, designed for capturing at a macroscopic level some effects, due to the microscopic granularity of the flow of cars, which would be lost with a purely continuous approach. The starting point is a multiscale method for pedestrian modeling, recently introduced in [1], in which measure-theoretic tools are used to manage the microscopic and the macroscopic scales under a unique framework.

. A guideline for an effective and efficient use of a deterministic variant of the Particle Swarm Optimization (PSO) algorithm is presented and discussed, assuming limited computational resources. PSO was introduced in Kennedy and Eberhart (1995) and successfully applied in many fields of engineering optimization for its ease of use. Its performance depends on three main characteristics: the number of swarm particles used, their initialization in terms of initial location and speed, and the set of coefficients defining the behavior of the swarm.