We describe a solution for fast indexing and searching within large heterogeneous data sets whose main purpose is to support investigators that need to analyze forensic disk images originated by seizures or created from bodies of evidence. Our approach is based on a combination of techniques aimed at improving efficiency and reliability of the indexing process.We do not rely on existing frameworks like Hadoop but borrow concepts from different contexts including High Performance Computing and Database management.

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.

A systems of self-propelled dumbbells interacting by a Weeks-Chandler-Anderson potential is considered. At sufficiently low temperatures the system phase separates into a dense phase and a gas-like phase. The kinetics of the cluster formation and the growth law for the average cluster size are analyzed.

The aim of the paper is to analyze the performance of a portfolio of participating life annuities, focusing on the minimum acceptable income level throughout the quantiles of the return distribution. The model, in addition to the necessary consideration of the volatility of financial markets, gives a central role to the impact of the longevity phenomenon.