Bio-inspired computation: where we stand and what's next

In recent years, the research community has witnessed an explosion of literature dealing with the adaptation of behavioral patterns and social phenomena observed in nature towards efficiently solving complex computational tasks. This trend has been especially dramatic in what relates to optimization problems, mainly due to the unprecedented complexity of problem instances, arising from a diverse spectrum of domains such as transportation, logistics, energy, climate, social networks, health and industry 4.0, among many others. Notwithstanding this upsurge of activity, research in this vibrant topic should be steered towards certain areas that, despite their eventual value and impact on the field of bio-inspired computation, still remain insufficiently explored to date. The main purpose of this paper is to outline the state of the art and to identify open challenges concerning the most relevant areas within bio-inspired optimization. An analysis and discussion are also carried out over the general trajectory followed in recent years by the community working in this field, thereby highlighting the need for reaching a consensus and joining forces towards achieving valuable insights into the understanding of this family of optimization techniques

COVID-19 Data Analysis with a Multi-Objective Evolutionary Algorithm for Causal Association Rule Mining

Association rule mining plays a crucial role in the medical area in discovering interesting relationships among the attributes of a data set. Traditional association rule mining algorithms such as Apriori, FP growth, or Eclat require considerable computational resources and generate large volumes of rules. Moreover, these techniques depend on user-defined thresholds which can inadvertently cause the algorithm to omit some interesting rules. In order to solve such challenges, we propose an evolutionary multi-objective algorithm based on NSGA-II to guide the mining process in a data set composed of 15.5 million records with official data describing the COVID-19 pandemic in Mexico. We tested different scenarios optimizing classical and causal estimation measures in four waves, defined as the periods of time where the number of people with COVID-19 increased. The proposed contributions generate, recombine, and evaluate patterns, focusing on recovering promising high-quality rules with actionable cause–effect relationships among the attributes to identify which groups are more susceptible to disease or what combinations of conditions are necessary to receive certain types of medical care

Studying the Effect of Robustness Measures in Offline Parameter Tuning for Estimating the Performance of MOEA/D

International audienceOffline parameter tuning (OPT) of multi-objective evolutionary algorithms (MOEAs) has the goal of finding an appropriate set of parameters for solving a large number of problems. According to the no free lunch theorem (NFL), no algorithm can have the best performance in all classes of optimization problems. However, it is possible to find an appropriate set of parameters of an algorithm for solving a particular class of problems. For that sake, we need to study how to estimate the aggregation quality function for an algorithmic configuration assessed on a set of optimization problems. In this paper, we study robustness measures for dealing with the parameter settings of stochastic algorithms. We focus on decomposition-based MOEAs and we propose to tune scalarizing functions for solving some classes of problems based on the Pareto front shapes using up to 7 objective functions. Based on our experimental results, we were able to derive interesting guidelines to evaluate the quality of algorithmic configurations using a combination of descriptive statistics

Nanofibras de Base Metálica para Aplicaciones Catalíticas

Los materiales nanoestructurados unidimensionales presentan nuevas propiedades que pueden ser aplicables en diferentes áreas de la tecnología. En particular, las nanofibras poliméricas (PVP) de base metálica presentan altos valores de razón área/volumen, esta sobresaliente propiedad hace de las fibras compositas óptimos candidatos para aplicaciones catalíticas

Synthesis and Optical Properties of Au-Ag Alloy Nanoclusters with Controlled Composition

Colloidal solid-solution-like Au-Ag alloy nanoclusters of different compositions were synthesized through citrate reduction of mixed metal ions of low concentrations, without using any other protective or capping agents. Optical absorption of the alloy nanoclusters was studied both theoretically and experimentally. The position of the surface plasmon resonance (SPR) absorption band of the nanoclusters could be tuned from 419 nm to 521 nm through the variation of their composition. Considering effective dielectric constant of the alloy, optical absorption spectra for the nanoclusters were calculated using Mie theory, and compared with the experimentally obtained spectra. Theoretically obtained optical spectra well resembled the experimental spectra when the true size distribution of the nanoparticles was considered. High-resolution transmission electron microscopy (HREM), high-angle annular dark field (HAADF) imaging, and energy dispersive spectroscopy (EDS) revealed the true alloy nature of the nanoparticles with nominal composition being preserved. The synthesis technique can be extended to other bimetallic alloy nanoclusters containing Ag

Effect of ultrasonic irradiation power on sonochemical synthesis of gold nanoparticles

In this work, optimized size distribution and optical properties in the colloidal synthesis of gold nanoparticles (GNPs) were obtained using a proposed ultrasonic irradiation assisted Turkevich-Frens method. The effect of three nominal ultrasound (20 kHz) irradiation powers: 60, 150, and 210 W have been analyzed as size and shape control parameters. The GNPs colloidal solutions were obtained from chloroauric acid (HAuCl4) and trisodium citrate (C6H5Na3O7·2H2O) under continuous irradiation for 1 h without any additional heat or stirring. The surface plasmon resonance (SPR) was monitored in the UV–Vis spectra every 10 min to found the optimal time for localized SPR wavelength (λLSPR), and the 210 sample procedure has reduced the λLSPR localization at 20 min, while 150 and 60 samples have showed λLSPR at 60 min. The nucleation and growth of GNPs showed changes in shape and size distribution associated with physical (cavitation, temperature) and chemical (radical generation, pH) conditions in the aqueous solution. The results showed quasi-spherical GNPs as pentakis dodecahedron (λLSPR = 560 nm), triakis icosahedron (λLSPR = 535 nm), and tetrakis hexahedron (λLSPR = 525 nm) in a size range from 12 to 16 nm. Chemical effects of ultrasound irradiation were suggested in the disproportionation process, electrons of AuCl2− are rapidly exchanged through the gold surface. After AuCl4− and Cl− were desorbed, a tetrachloroaurate complex was recycled for the two-electron reduction by citrate, aurophilic interaction between complexes AuCl2−, electrons exchange, and gold seeds, the deposition of new gold atoms on the surface promoting the growth of GNPs. These mechanisms are enhanced by the effects of ultrasound, such as cavitation and transmitted energy into the solution. These results show that the plasmonic response from the reported GNPs can be tuned using a simple methodology with minimum infrastructure requirements. Moreover, the production method could be easily scalable to meet industrial manufacturing needs.Authors would like to acknowledge Rodrigo Fernandez Pacheco from Laboratorio de Microscopias Avanzadas (LMA) of INA for the facilities in TEM observations, the use of Servicio General de Apoyo a la Investigación-SAI, Universidad de Zaragoza. J.A. Fuentes-García thanks the Mexican council of science and technology (CONACyT) for financial support through a postdoctoral fellowship #711124.Peer reviewe

Preparación controlada y actuación química de fibras de poliacrilonitrilo

Pure polyacrylonitrile (PAN) fibers with diameter size at micrometric scale were obtained and collected radially using an immersion-jet wet spinning .system. This technique is a fast and easy approach to fabricate micrometric PAN fibers. The diameter of the fiber can be easily controlled by adjusting the size of the spinneret. Uniform, smooth and continuous PAN microfibers were suitable modified by thermal stabilization and alkaline saponification to obtain pH-sensitive fibers. The effect of diameter size fiber on the chemical actuation behavior was investigated in terms of length change characteristics under the influence of pH solution. The microfibers showed expanding/contracting behavior and force generation stimulated by changes in the environment pH. The fibers structural and chemical properties were characterized using the FT-IR spectroscopy and SEM microscopy techniques.Se obtuvieron fibras puras de poliacrilonitrilo (PAN) con un diámetro a escala micrométrica y se recogieron radialmente utilizando un sistema de hilatura húmeda por inmersión. Esta técnica es un método rápido y sencillo para fabricar fibras de PAN micrométricas. El diámetro de la fibra puede controlarse fácilmente ajustando el tamaño de la hilera. Las microfibras de PAN uniformes, lisas y continuas se modificaron adecuadamente mediante estabilización térmica y saponificación alcalina para obtener fibras sensibles al pH. Se investigó el efecto del tamaño del diámetro de la fibra en el comportamiento de actuación química en términos de características de cambio de longitud bajo la influencia de la solución de pH. Las microfibras mostraron un comportamiento de expansión/contracción y generación de fuerza estimulado por cambios en el pH ambiental. Las propiedades estructurales y químicas de las fibras se caracterizaron mediante técnicas de espectroscopia FT-IR y microscopía SEM