The role of optimization in some recent advances in data-driven decision-making

Mathematical Programming - In this paper, we present a new framework of bi-level unconstrained minimization for development of accelerated methods in Convex Programming. These methods use...     

Stability and integrability aspects for the Maxwell–Bloch equations with the rotating wave approximation

Infinitely many Hamilton–Poisson realizations of the five-dimensional real valued Maxwell–Bloch equations with the rotating wave approximation are constructed and the energy-Casimir mapping is considered. Also, the image of this mapping is presented and connections with the equilibrium states of the considered system are studied. Using some fibers of the image of the energy-Casimir mapping, some special orbits are obtained. Finally, a Lax formulation of the system is given.     

Strategies for protein folding and design

Fundamental challenges in molecular biology can be addressed by using simple models on a lattice, where statistical mechanics and combinatoric techniques can be employed. The basic premise is that it is sensible to test any proposed method on the simplest of models in order to assess their validity before launching a full-scale attack on realistic problems. In this paper we follow this strategy and we present different efficient schemes to perform protein design and to extract effective amino acid interaction potentials.This work was supported in part by INFM, INFN sez. di Trieste, NASA and NATO.     

Functional data clustering: a survey

Clustering techniques for functional data are reviewed. Four groups of clustering algorithms for functional data are proposed. The first group consists of methods working directly on the evaluation points of the curves. The second groups is defined by filtering methods which first approximate the curves into a finite basis of functions and second perform clustering using the basis expansion coefficients. The third groups is composed of methods which perform simultaneously dimensionality reduction of the curves and clustering, leading to functional representation of data depending on clusters. The last group consists of distance-based methods using clustering algorithms based on specific distances for functional data. A software review as well as an illustration of the application of these algorithms on real data are presented.     

Damage detection through nonparametric models using Kautz filters

Meccanica - The goal of this paper is to present an approach to detect structural changes by using nonparametric models. The impulse response functions (IRFs) of mechanical systems in healthy...     

Negative sulfur-based electrodes and their application in battery cells: Dual-ion batteries as an example

Journal of Solid State Electrochemistry - In this work, a cell concept comprising of an anion intercalating graphite-based positive electrode (cathode) and an elemental sulfur-based negative...     

Boolean Percolation on Doubling Graphs

Journal of Statistical Physics - We consider the discrete Boolean model of percolation on weighted graphs satisfying a doubling metric condition. We study sufficient conditions on the distribution...