Efficient data structures for backtrack search SAT solvers

The implementation of efficient Propositional Satisfiability (SAT) solvers entails the utilization of highly efficient data structures, as illustrated by most of the recent state-of-the-art SAT solvers. However, it is in general hard to compare existing data structures, since different solvers are often characterized by fairly different algorithmic organizations and techniques, and by different search strategies and heuristics. This paper aims the evaluation of data structures for backtrack search SAT solvers, under a common unbiased SAT framework. In addition, advantages and drawbacks of each existing data structure are identified. Finally, new data structures are proposed, that are competitive with the most efficient data structures currently available, and that may be preferable for the next generation SAT solvers

Boosting Haplotype Inference with Local Search

Abstract. A very challenging problem in the genetics domain is to infer haplotypes from genotypes. This process is expected to identify genes affecting health, disease and response to drugs. One of the approaches to haplotype inference aims to minimise the number of different haplotypes used, and is known as haplotype inference by pure parsimony (HIPP). The HIPP problem is computationally difficult, being NP-hard. Recently, a SAT-based method (SHIPs) has been proposed to solve the HIPP problem. This method iteratively considers an increasing number of haplotypes, starting from an initial lower bound. Hence, one important aspect of SHIPs is the lower bounding procedure, which reduces the number of iterations of the basic algorithm, and also indirectly simplifies the resulting SAT model. This paper describes the use of local search to improve existing lower bounding procedures. The new lower bounding procedure is guaranteed to be as tight as the existing procedures. In practice the new procedure is in most cases considerably tighter, allowing significant improvement of performance on challenging problem instances.

Efficient Haplotype Inference with Pseudo-Boolean Optimization

Abstract. Haplotype inference from genotype data is a key computational problem in bioinformatics, since retrieving directly haplotype information from DNA samples is not feasible using existing technology. One of the methods for solving this problem uses the pure parsimony criterion, an approach known as Haplotype Inference by Pure Parsimony (HIPP). Initial work in this area was based on a number of different Integer Linear Programming (ILP) models and branch and bound algorithms. Recent work has shown that the utilization of a Boolean Satisfiability (SAT) formulation and state of the art SAT solvers represents the most efficient approach for solving the HIPP problem. Motivated by the promising results obtained using SAT techniques, this paper investigates the utilization of modern Pseudo-Boolean Optimization (PBO) algorithms for solving the HIPP problem. The paper starts by applying PBO to existing ILP models. The results are promising, and motivate the development of a new PBO model (RPoly) for the HIPP problem, which has a compact representation and eliminates key symmetries. Experimental results indicate that RPoly outperforms the SAT-based approach on most problem instances, being, in general, significantly more efficient

Model systems for regeneration: zebrafish

Tissue damage can resolve completely through healing and regeneration, or can produce permanent scarring and loss of function. The response to tissue damage varies across tissues and between species. Determining the natural mechanisms behind regeneration in model organisms that regenerate well can help us develop strategies for tissue recovery in species with poor regenerative capacity (such as humans). The zebrafish (Danio rerio) is one of the most accessible vertebrate models to study regeneration. In this Primer, we highlight the tools available to study regeneration in the zebrafish, provide an overview of the mechanisms underlying regeneration in this system and discuss future perspectives for the field.N.M. is supported by a European Research Council starting grant (2013 zebraHeart-337703), E.L. is supported by the European Commission (H2020-MSCA-ITN-2016 European Industrial Doctorate 4DHeart 722427).S

Optimal Power Allocation in MIMO wire-tap channels

Projecte Finl de Carrera fet en col.laboració amb Università La Sapienza di Roma.English: Study of a methodology that, without the use of cryptography, limits the possible "intelligence" present at the eavesdropper and increases the level of secrecy on a wireless environment using MIMO systems.Castellano: Estudio de una metodologia que, sin hacer uso de la criptografia, permite limitar la posible "inteligencia" del espia, con la finalidad de aumentar la confidencialidad en comunicacines wireless con sistemas MIMOCatalà: Estudi d'una metodologia que, sense fer ús de la criptografia, permet limitar la possible "intel.ligència" de l'espia per tal d'augmentar la confidencialitat en comunicacions wireless amb sistemes MIMO