Multi-objective genetic algorithms in the study of the genetic code’s adaptability

Using a robustness measure based on values of the polar requirement of amino acids, Freeland and Hurst (1998) showed that less than one in one million random hypothetical codes are better than the standard genetic code. In this paper, instead of comparing the standard code with randomly generated codes, we use an optimisation algorithm to find the best hypothetical codes. This approach has been used before, but considering only one objective to be optimised. The robustness measure based on the polar requirement is considered the most effective objective to be optimised by the algorithm. We propose here that the polar requirement is not the only property to be considered when computing the robustness of the genetic code. We include the hydropathy index and molecular volume in the evaluation of the amino acids using three multi-objective approaches: the weighted formula, lexicographic and Pareto approaches. To our knowledge, this is the first work proposing multi-objective optimisation approaches with a non-restrictive encoding for studying the evolution of the genetic code. Our results indicate that multi-objective approaches considering the three amino acid properties obtain better results than those obtained by single objective approaches reported in the literature. The codes obtained by the multi-objective approach are more robust and structurally more similar to the standard code

Viral quasispecies diversity and evolution : a Bioinformatics molecular approach

El grup de hepatitis virals del Vall d'Hebron Institut de Recerca (VHIR) de Barcelona, en els darrers 10 anys, ha estat desenvolupant solucions metodològiques experimentals i computacionals per a l'estudi de poblacions complexes de virus (quasispecies) mitjançant l'aplicació de les tècniques de seqüenciació de nova generació (NGS). Aquest llibre consisteix en una selecció de treballs empírics sobre les quasispecies virals. En oferir aquest format obert de publicació, l'objectiu és que, per una banda, pugui ser una eina útil per a tots aquells investigadors interessats en aquest camp i, d'altra banda, divulgar aquesta àrea de coneixement a tota la comunitat científica que, sense ser necessàriament experta, vulgui conèixer amb més detall l'evolució i diversitat dels virus. En els tres primers treballs s'aprofundeix en l'ús, interpretació i utilitat d'índexs de biodiversitat, alguns específics per a poblacions genètiques i d'altres importats del camp de l'ecologia. La segona part posa de manifest algunes limitacions en aquests índexs de diversitat i aborda el desenvolupament d'eines integradores que proporcionen una interpretació més directa en termes biològics i clínics. Les seccions prèvies als sis treballs esmentats, situen al lector en el context en què es realitzen els desenvolupaments i expliquen la necessitat i utilitat. El llibre es tanca amb una secció que recull les observacions i conclusions generals dels treballs, i amb una altra que reflexiona sobre les limitacions que comporta l'estudi de sistemes complexos i dinàmics com les quasispecies virals

Automated Design and Optimization of Metallic Alloys

The design and optimization of metallic alloys poses a significant engineering challenge. The search space of all possible alloys is sufficiently large that it is impossible to fully explore by traditional methods. In order to address this challenge, physics based computational frameworks linked to advanced machine learning algorithms can serve to automate this process with computational efficiency such that the state of the industry may be rapidly advanced. The work herein presents a suite of computational frameworks leveraged to automate the design and optimization process of advanced alloys. An ab initio alloy thermodynamics system, Molecular Dynamics simulations, a Convolutional-Neural Network system, and a coupled Neural Network and Multi-objective Genetic Algorithm. These algorithms are validated over the set of binary nanocrystalline Al-X alloys, and multi-component High Entropy Alloys (HEA)

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 140

This bibliography lists 306 reports, articles, and other documents introduced into the NASA scientific and technical information system in March 1975

State-of-the-art in aerodynamic shape optimisation methods

Aerodynamic optimisation has become an indispensable component for any aerodynamic design over the past 60 years, with applications to aircraft, cars, trains, bridges, wind turbines, internal pipe flows, and cavities, among others, and is thus relevant in many facets of technology. With advancements in computational power, automated design optimisation procedures have become more competent, however, there is an ambiguity and bias throughout the literature with regards to relative performance of optimisation architectures and employed algorithms. This paper provides a well-balanced critical review of the dominant optimisation approaches that have been integrated with aerodynamic theory for the purpose of shape optimisation. A total of 229 papers, published in more than 120 journals and conference proceedings, have been classified into 6 different optimisation algorithm approaches. The material cited includes some of the most well-established authors and publications in the field of aerodynamic optimisation. This paper aims to eliminate bias toward certain algorithms by analysing the limitations, drawbacks, and the benefits of the most utilised optimisation approaches. This review provides comprehensive but straightforward insight for non-specialists and reference detailing the current state for specialist practitioners

Unknown area exploration for robots with energy constraints using a modified Butterfly Optimization Algorithm

Butterfly Optimization Algorithm (BOA) is a recent metaheuristic that has been used in several optimization problems. In this paper, we propose a new version of the algorithm (xBOA) based on the crossover operator and compare its results to the original BOA and 3 other variants recently introduced in the literature. We also proposed a framework for solving the unknown area exploration problem with energy constraints using metaheuristics in both single- and multi-robot scenarios. This framework allowed us to benchmark the performances of different metaheuristics for the robotics exploration problem. We conducted several experiments to validate this framework and used it to compare the effectiveness of xBOA with wellknown metaheuristics used in the literature through 5 evaluation criteria. Although BOA and xBOA are not optimal in all these criteria, we found that BOA can be a good alternative to many metaheuristics in terms of the exploration time, while xBOA is more robust to local optima; has better fitness convergence; and achieves better exploration rates than the original BOA and its other variants

Human Being Emotion in Cognitive Intelligent Robotic Control Pt I: Quantum / Soft Computing Approach

Abstract. The article consists of two parts. Part I shows the possibility of quantum / soft computing optimizers of knowledge bases (QSCOptKB™) as the toolkit of quantum deep machine learning technology implementation in the solution’s search of intelligent cognitive control tasks applied the cognitive helmet as neurointerface. In particular, case, the aim of this part is to demonstrate the possibility of classifying the mental states of a human being operator in on line with knowledge extraction from electroencephalograms based on SCOptKB™ and QCOptKB™ sophisticated toolkit. Application of soft computing technologies to identify objective indicators of the psychophysiological state of an examined person described. The role and necessity of applying intelligent information technologies development based on computational intelligence toolkits in the task of objective estimation of a general psychophysical state of a human being operator shown. Developed information technology examined with special (difficult in diagnostic practice) examples emotion state estimation of autism children (ASD) and dementia and background of the knowledge bases design for intelligent robot of service use is it. Application of cognitive intelligent control in navigation of autonomous robot for avoidance of obstacles demonstrated.