About Designing an Observer Pattern-Based Architecture for a Multi-objective Metaheuristic Optimization Framework

Multi-objective optimization with metaheuristics is an active and popular research field which is supported by the availability of software frameworks providing algorithms, benchmark problems, quality indicators and other related components. Most of these tools follow a monolithic architecture that frequently leads to a lack of flexibility when a user intends to add new features to the included algorithms. In this paper, we explore a different approach by designing a component-based architecture for a multi-objective optimization framework based on the observer pattern. In this architecture, most of the algorithmic components are observable entities that naturally allows to register a number of observers. This way, a metaheuristic is composed of a set of observable and observer elements, which can be easily extended without requiring to modify the algorithm. We have developed a prototype of this architecture and implemented the NSGA-II evolutionary algorithm on top of it as a case study. Our analysis confirms the improvement of flexibility using this architecture, pointing out the requirements it imposes and how performance is affected when adopting it.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A Study of Archiving Strategies in Multi-Objective PSO for Molecular Docking

Molecular docking is a complex optimization problem aimed at predicting the position of a ligand molecule in the active site of a receptor with the lowest binding energy. This problem can be formulated as a bi-objective optimization problem by minimizing the binding energy and the Root Mean Square Deviation (RMSD) difference in the coordinates of ligands. In this context, the SMPSO multi-objective swarm-intelligence algorithm has shown a remarkable performance. SMPSO is characterized by having an external archive used to store the non-dominated solutions and also as the basis of the leader selection strategy. In this paper, we analyze several SMPSO variants based on different archiving strategies in the scope of a benchmark of molecular docking instances. Our study reveals that the SMPSOhv, which uses an hypervolume contribution based archive, shows the overall best performance.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Applications of Direct Injection Soft Chemical Ionisation-Mass Spectrometry for the Detection of Pre-blast Smokeless Powder Organic Additives

Analysis of smokeless powders is of interest from forensics and security perspectives. This article reports the detection of smokeless powder organic additives (in their pre-detonation condition), namely the stabiliser diphenylamine and its derivatives 2-nitrodiphenylamine and 4-nitrodiphenylamine, and the additives (used both as stabilisers and plasticisers) methyl centralite and ethyl centralite, by means of swab sampling followed by thermal desorption and direct injection soft chemical ionisation-mass spectrometry. Investigations on the product ions resulting from the reactions of the reagent ions H3O+ and O2+ with additives as a function of reduced electric field are reported. The method was comprehensively evaluated in terms of linearity, sensitivity and precision. For H3O+, the limits of detection (LoD) are in the range of 41-88 pg of additive, for which the accuracy varied between 1.5 and 3.2%, precision varied between 3.7 and 7.3% and linearity showed R20.9991. For O2+, LoD are in the range of 72 to 1.4 ng, with an accuracy of between 2.8 and 4.9% and a precision between 4.5 and 8.6% and R20.9914. The validated methodology was applied to the analysis of commercial pre-blast gun powders from different manufacturers.(VLID)4826148Accepted versio

Comparison and Uniqueness Results for the Periodic Boundary Value Problem for Linear First-Order Differential Equations Subject to a Functional Perturbation

This is a post-peer-review, pre-copyedit version of a chapter published in Area I. et al. (eds) Nonlinear Analysis and Boundary Value Problems. NABVP 2018. Springer Proceedings in Mathematics & Statistics, vol 292. Springer, Cham. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-26987-6_14We improve some comparison results for the periodic boundary value problem related to a first-order differential equation perturbed by a functional term. The comparison results presented cover many cases as differential equations with delay, differential equations with maxima and integro-differential equations. The interesting case of functional perturbation with piecewise constant arguments is also analyzed

A Novel Stochastic Multi-Scale Model of Francisella tularensis Infection to Predict Risk of Infection in a Laboratory

We present a multi-scale model of the within-phagocyte, within-host and population-level infection dynamics of Francisella tularensis, which extends the mechanistic one proposed by Wood et al. (2014). Our multi-scale model incorporates key aspects of the interaction between host phagocytes and extracellular bacteria, accounts for inter-phagocyte variability in the number of bacteria released upon phagocyte rupture, and allows one to compute the probability of response, and mean time until response, of an infected individual as a function of the initial infection dose. A Bayesian approach is applied to parameterize both the within-phagocyte and within-host models using infection data. Finally, we show how dose response probabilities at the individual level can be used to estimate the airborne propagation of Francisella tularensis in indoor settings (such as a microbiology laboratory) at the population level, by means of a deterministic zonal ventilation model

Unveiling the nature of the "Green Pea" galaxies

We review recent results on the oxygen and nitrogen chemical abundances in extremely compact, low-mass starburst galaxies at redshifts between 0.1-0.3 recently named to as "Green Pea" galaxies. These galaxies are genuine metal-poor galaxies ($\sim$ one fifth solar) with N/O ratios unusually high for galaxies of the same metallicity. In combination with their known general properties, i.e., size, stellar mass and star-formation rate, these findings suggest that these objects could be experiencing a short and extreme phase in their evolution. The possible action of both recent and massive inflow of gas, as well as stellar feedback mechanisms are discussed here as main drivers of the starburst activity and their oxygen and nitrogen abundances.Comment: To appear in JENAM Symposium "Dwarf Galaxies: Keys to Galaxy Formation and Evolution", P. Papaderos, G. Hensler, S. Recchi (eds.). Lisbon, September 2010, Springer Verlag, in pres

Updating known distribution models for forecasting climate change impact on endangered species

To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli’s Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species’ distribution, instead of building new models that are based on climate change variables only.Ministerio de Ciencia e Innovación and FEDER (project CGL2009-11316/BOS

Predicting prostate cancer treatment choices: The role of numeracy, time discounting, and risk attitudes

Prostate cancer is the most common cancer among males in the United States and there is lack of consensus as to whether active surveillance (AS) or radical prostatectomy (RP) is the best course of treatment. In this study we examined the role of three overlooked determinants of decision making about prostate cancer treatment in a hypothetical experiment—numeracy, time discounting, and risk taking in 279 men over age 50 without a prior prostate cancer diagnosis. Results showed that AS was the most frequently chosen option. Furthermore, numeracy and time discounting significantly predicted participants’ preference for AS, whereas a propensity to take risks was associated with a preference for RP. Such insights into the factors that affects cancer treatment preferences may improve tailored decision aids and help physicians be better poised to engage in shared decision-making to improve both patient-reported and clinical outcomes

Perfil psicopatológico de pacientes con Dependencia Emocional

Diversos autores defienden la Dependencia Emocional como una categoría diagnóstica propia. El perfil psicopatológico de las personas afectadas por este trastorno ha sido expuesto a nivel teórico o basado en observaciones clínicas. Con este estudio se pretende determinar el perfil psicopatológico de una muestra de pacientes que presentaban problemas de Dependencia Emocional, desadaptativa, así como estudiar la relación entre autoestima y síntomas psicopatológicos. Se analiza el perfil sintomático a través de los resultados del Symptom CheckList-90 items-Revised (SCL-90-R) y el nivel de autoestima medido a través del Rosenberg Self-Esteem Scale (RSES) de una muestra de 33 pacientes de género femenino admitidos consecutivamente, que consultaron por problemas de dependencia emocional. Las pacientes presentaban elevada puntuación en las escalas obsesión-compulsión, sensibilidad interpersonal, depresión, ansiedad, hostilidad, ideación paranoide, psicoticismo (medidas a través del SCL-90-R) comparados con baremos normativos de población psiquiátrica española y una autoestima baja (medida a través del RSES). En la muestra la autoestima correlaciona de manera negativa con somatización, obsesión-compulsión, depresión y hostilidad. Se discuten las características y perfiles de esta muestra clínica. English abstract: Several authors defend that Affective Dependence is a diagnostic category. The psychopathological profile of these patients has been explained from a theoretical point of view or based on clinical observations. In that study we want to determinate the pathological profile of a sample of patients with problems of affective dependence, and to study the relationship between their self-esteem and their psychopathological symptoms. We analyzed the symptomatic profile of a sample of 33 female consecutive patients consulting for affective dependence, measured trough the Symptom CheckList-90 items-Revised (SCL-90-R) and the Rosenberg Self-Esteem Scale (RSES). Patients present high obsessive-compulsive, interpersonal sensitivity, depression, anxiety, hostility, paranoid ideation, psychoticism (measured by the SCL- 90-R) compared with compared with normative scores of Spanish psychiatric population, and low self-esteem (measured by the RSES). In these subjects the self- esteem showed negative correlation with somatization, obsessive-compulsive, depression and hostility. These characteristics and profiles are discussed

Microbial catabolic activities are naturally selected by metabolic energy harvest rate

The fundamental trade-off between yield and rate of energy harvest per unit of substrate has been largely discussed as a main characteristic for microbial established cooperation or competition. In this study, this point is addressed by developing a generalized model that simulates competition between existing and not experimentally reported microbial catabolic activities defined only based on well-known biochemical pathways. No specific microbial physiological adaptations are considered, growth yield is calculated coupled to catabolism energetics and a common maximum biomass-specific catabolism rate (expressed as electron transfer rate) is assumed for all microbial groups. Under this approach, successful microbial metabolisms are predicted in line with experimental observations under the hypothesis of maximum energy harvest rate. Two microbial ecosystems, typically found in wastewater treatment plants, are simulated, namely: (i) the anaerobic fermentation of glucose and (ii) the oxidation and reduction of nitrogen under aerobic autotrophic (nitrification) and anoxic heterotrophic and autotrophic (denitrification) conditions. The experimentally observed cross feeding in glucose fermentation, through multiple intermediate fermentation pathways, towards ultimately methane and carbon dioxide is predicted. Analogously, two-stage nitrification (by ammonium and nitrite oxidizers) is predicted as prevailing over nitrification in one stage. Conversely, denitrification is predicted in one stage (by denitrifiers) as well as anammox (anaerobic ammonium oxidation). The model results suggest that these observations are a direct consequence of the different energy yields per electron transferred at the different steps of the pathways. Overall, our results theoretically support the hypothesis that successful microbial catabolic activities are selected by an overall maximum energy harvest rate