Stellarator Optimization Using a Distributed Swarm Intelligence-Based Algorithm

The design of enhanced fusion devices constitutes a key element for the development of fusion as a commercial source of energy. Stellarator optimization presents high computational requirements because of the complexity of the numerical methods needed as well as the size of the solution space regarding all the possible configurations satisfying the characteristics of a feasible reactor. The size of the solution space does not allow to explore every single feasible configuration. Hence, a metaheuristic approach is used to achieve optimized configurations without evaluating the whole solution space. In this paper we present a distributed algorithm that mimics the foraging behaviour of bees. This behaviour has manifested its efficiency in dealing with complex problems

Swarm intelligence for optimizing the parameters of multiple sequence aligners

Rubio-Largo, Á., Vanneschi, L., Castelli, M., & Vega-Rodríguez, M. A. (2018). Swarm intelligence for optimizing the parameters of multiple sequence aligners. Swarm and Evolutionary Computation. DOI: 10.1016/j.swevo.2018.04.003Different aligner heuristics can be found in the literature to solve the Multiple Sequence Alignment problem. These aligners rely on the parameter configuration proposed by their authors (also known as default parameter configuration), that tried to obtain good results (alignments with high accuracy and conservation) for any input set of unaligned sequences. However, the default parameter configuration is not always the best parameter configuration for every input set; namely, depending on the biological characteristics of the input set, one may be able to find a better parameter configuration that outputs a more accurate and conservative alignment. This work's main contributions include: to study the input set's biological characteristics and to then apply the best parameter configuration found depending on those characteristics. The framework uses a pre-computed file to take the best parameter configuration found for a dataset with similar biological characteristics. In order to create this file, we use a Particle Swarm Optimization (PSO) algorithm, that is, an algorithm based on swarm intelligence. To test the effectiveness of the characteristic-based framework, we employ five well-known aligners: Clustal W, DIALIGN-TX, Kalign2, MAFFT, and MUSCLE. The results of these aligners see clear improvements when using the proposed characteristic-based framework.authorsversionpublishe

Multiobjective characteristic-based framework for very-large multiple sequence alignment

Rubio-Largo, Á., Vanneschi, L., Castelli, M., & Vega-Rodríguez, M. A. (2018). Multiobjective characteristic-based framework for very-large multiple sequence alignment. Applied Soft Computing Journal, 69, 719-736. [Advanced online publication on 27 June 2017]DOI: 10.1016/j.asoc.2017.06.022In the literature, we can find several heuristics for solving the multiple sequence alignment problem. The vast majority of them makes use of flags in order to modify certain alignment parameters; however, if no flags are used, the aligner will run with the default parameter configuration, which, often, is not the optimal one. In this work, we propose a framework that, depending on the biological characteristics of the input dataset, runs the aligner with the best parameter configuration found for another dataset that has similar biological characteristics, improving the accuracy and conservation of the obtained alignment. To train the framework, we use three well-known multiobjective evolutionary algorithms: NSGA-II, IBEA, and MOEA/D. Then, we perform a comparative study between several aligners proposed in the literature and the characteristic-based version of Kalign, MAFFT, and MUSCLE, when solving widely-used benchmarks (PREFAB v4.0 and SABmark v1.65) and very-large benchmarks with thousands of unaligned sequences (HomFam).authorsversionpublishe

The software project scheduling problem: A scalability analysis of multi-objective metaheuristics

Applied Soft Computing 15, 136-148Computer aided techniques for scheduling software projects are a crucial step in the software development process within the highly competitive software industry. The Software Project Scheduling (SPS) problem relates to the decision of who does what during a software project lifetime, thus involving mainly both people-intensive activities and human resources. Two major conflicting goals arise when scheduling a software project: reducing both its cost and duration. A multi-objective approach is therefore the natural way of facing the SPS problem. As companies are getting involved in larger and larger software projects, there is an actual need of algorithms that are able to deal with the tremendous search spaces imposed. In this paper, we analyze the scalability of eight multi-objective algorithms when they are applied to the SPS problem using instances of increasing size. The algorithms are classical algorithms from the literature (NSGA-II, PAES, and SPEA2) and recent proposals (DEPT, MOCell, MOABC, MO-FA, and GDE3). From the experimentation conducted, the results suggest that PAES is the algorithm with the best scalability features.Spanish Ministry of Science and Innovation and ERDF (European Regional Development Fund) under contract TIN2008-06491-C04 (M* project). Spanish Ministry of Economy and Competitiveness and the ERDF under contracts TIN2012-30685 (BIO project) and TIN2011-28194 (roadME project). Fundación Valhondo, for the economic support offered to David L. González-Álvarez

Solving the Location Area Problem by Using Differential Evolution

In mobile networks, one of the hard tasks is to determine the best partitioning in the Location Area problem, but it is also an important strategy to try to reduce all the involved management costs. In this paper we present a new approach to solve the location management problem based on the Location Area partitioning, as a cost optimization problem. We use a Differential Evolution based algorithm to find the best configuration to the Location Areas in a mobile network. We try to find the best values for the Differential Evolution parameters as well as define the scheme that enables us to obtain better results, when compared to classical strategies and to other authors’ results. To obtain the best solution we develop four distinct experiments, each one applied to one Differential Evolution parameter. This is a new approach to this problem that has given us good results

The enterohemorrhagic Escherichia coli insertion sequence-excision enhancer protein is a DNA polymerase with microhomology-mediated end-joining activity

Bacterial genomes contain an abundance of transposable insertion sequence (IS) elements that are essential for genome evolution and fitness. Among them, IS629 is present in most strains of enterohemorrhagic Escherichia coli O157 and accounts for many polymorphisms associated with gene inactivation and/or genomic deletions. The excision of IS629 from the genome is promoted by IS-excision enhancer (IEE) protein. Despite IEE has been identified in the most pathogenic serotypes of E. coli, its biochemical features that could explain its role in IS excision are not yet understood. We show that IEE is present in >30% of all available E. coli genome assemblies, and is highly conserved and very abundant within enterohemorrhagic, enteropathogenic and enterotoxigenic genomes. In vitro analysis of the recombinant protein from E. coli O157:H7 revealed the presence of a Mn2+-dependent error-prone DNA polymerase activity in its N-terminal archaeo-eukaryotic primase (AEP) domain able to promote dislocations of the primer and template strands. Importantly, IEE could efficiently perform in vitro an end-joining reaction of 3’-single-strand DNA overhangs with ≥4 bp of homology requiring both the N-terminal AEP and C-terminal helicase domains. The proposed role for IEE in the novel IS excision mechanism is discusse

Artrodesis de rodilla por fracaso de la artroplatsia total

Veintiuna artrodesis de rodilla fueron realizadas en nuestro Servicio en los últimos 20 años. Se realiza un estudio retrospectivo con un seguimiento medio de 10 años. Las razones para la artrodesis fueron en 12 ocasiones (57%) infección de la artroplastia total, y en los 9 casos restantes (43%) aflojamiento aséptico. La artrodesis se realizó mediante fijación externa en un solo plano en 11 casos (52%), en biplano se colocó en 7 (33%), 2 casos con placas a compresión (9,5%) y el caso restante mediante un clavo intramedular (5%). La fusión después del procedimiento inicial se obtuvo solamente en 12 pacientes (57%) y añadiendo procedimientos adicionales totalizamos 19 rodillas fusionadas (90%). Las complicaciones encontradas fueron: 9 pseudoartrosis, 2 infecciones en el trayecto de las fichas, 2 roturas del material de fijación, una infección persistente que llevó a la amputación, y una parálisis del nervio ciático poplíteo externo.A total of 21 knee arthrodesis performed in the last 20 years was reviewed with an average follow-up of 10 years. Arthrodesis was performed following deep infection in 12 cases (57%) and aseptic loosening of the prostheses in the remaining 9 cases. TH artrodesis were performed using one-plane external fixation in 11 cases, two-planes external fixation in 7, compression plates in 2, intramedular nailing in only 12 patients. Using additional procedures we obtained 19 fused knees (90 %). The complications in this series were: Psuedarthrosis (9 cases), infection of the fixator pins (2 cases), infection of the fixator pins (2 cases), and broken osteosybrtesis components (2 cases), severe deep infection with final amputation of the limb (1 case), and CPE injury (1 case)

Enseñanza de Arquitecturas de Memorias Caché mediante Simuladores

En este trabajo se presentan dos experiencias docentes en la enseñanza de arquitecturas de memoria caché para la titulación de Ingeniería Informática de la Universidad de Extremadura. Estas experiencias se desarrollan desde dos puntos de vista: Sistemas caché multinivel para una asignatura de carácter fundamental ("Estructura de Computadores"), y sistemas de memoria caché en multiprocesadores, para una asignatura de carácter avanzado ("Arquitectura de Computadores")

A study of methods for reducing the Pareto front to a single solution applied to the extractive multi-document summarization problem

Los métodos de resumen automático son actualmente necesarios en muchos contextos diferentes. El problema de resumen extractivo multi-documento intenta cubrir el contenido principal de una colección de documentos y reducir la información redundante. La mejor manera de abordar esta tarea es mediante un enfoque de optimización multi-objetivo. El resultado de este enfoque es un conjunto de soluciones no dominadas o conjunto de Pareto. Sin embargo, dado que solo se necesita un resumen, se debe reducir el frente de Pareto a una única solución. Para ello, se han considerado varios métodos, como el mayor hipervolumen, la solución consenso, la distancia más corta al punto ideal y la distancia más corta a todos los puntos. Los métodos han sido probados utilizando conjuntos de datos de DUC, y han sido evaluados con las métricas ROUGE. Los resultados revelan que la solución consenso obtiene los mejores valores promedio.Automatic summarization methods are currently needed in many different contexts. The extractive multi-document summarization problem tries to cover the main content of a document collection and to reduce the redundant information. The best way to address this task is through a multi-objective optimization approach. The result of this approach is a set of non-dominated solutions or Pareto set. However, since only one summary is needed, the Pareto front must be reduced to a single solution. For this, several methods have been considered, such as the largest hypervolume, the consensus solution, the shortest distance to the ideal point, and the shortest distance to all points. The methods have been tested using datasets from DUC, and they have been evaluated with ROUGE metrics. The results show that consensus solution achieves the best average values.Esta investigación ha sido apoyada por la Agencia Estatal de Investigación (proyectos PID2019-107299GB-I00 y MTM2017-86875-C3-2-R), por la Junta de Extremadura (proyectos GR18090 y GR18108) y por la Unión Europea (Fondo Europeo de Desarrollo Regional). Jesus M. Sanchez-Gomez está apoyado por un Contrato Predoctoral financiado por la Junta de Extremadura (contrato PD18057) y la Unión Europea (Fondo Social Europeo)