Rule Representation in Distributed Environments with Accepting Networks of Splicing Processors.

This paper presents the model named Accepting Networks of Evolutionary Processors as NP-problem solver inspired in the biological DNA operations. A processor has a rules set, splicing rules in this model,an object multiset and a filters set. Rules can be applied in parallel since there exists a large number of copies of objects in the multiset. Processors can form a graph in order to solve a given problem. This paper shows the network configuration in order to solve the SAT problem using linear resources and time. A rule representation arquitecture in distributed environments can be easily implemented using these networks of processors, such as decision support systems, as shown in the paper

A data mining framework based on boundary-points for gene selection from DNA-microarrays: Pancreatic Ductal Adenocarcinoma as a case study

[EN] Gene selection (or feature selection) from DNA-microarray data can be focused on different techniques, which generally involve statistical tests, data mining and machine learning. In recent years there has been an increasing interest in using hybrid-technique sets to face the problem of meaningful gene selection; nevertheless, this issue remains a challenge. In an effort to address the situation, this paper proposes a novel hybrid framework based on data mining techniques and tuned to select gene subsets, which are meaningfully related to the target disease conducted in DNA-microarray experiments. For this purpose, the framework above deals with approaches such as statistical significance tests, cluster analysis, evolutionary computation, visual analytics and boundary points. The latter is the core technique of our proposal, allowing the framework to define two methods of gene selection. Another novelty of this work is the inclusion of the age of patients as an additional factor in our analysis, which can leading to gaining more insight into the disease. In fact, the results reached in this research have been very promising and have shown their biological validity. Hence, our proposal has resulted in a methodology that can be followed in the gene selection process from DNA-microarray data

Simulating Membrane Systems in Digital Computers

* Work partially supported by contribution of EU commission Under The Fifth Framework Programme, project “MolCoNet” IST-2001-32008.Membrane Computing started with the analogy between some processes produced inside the complex structure of living cells and computational processes. In the same way that in other branches of Natural Computing, the model is extracted from nature but it is not clear whether or not the model must come back to nature to be implemented. As in other cases in Natural Computing: Artificial Neural Networks, Genetic Algorithms, etc; the models have been implemented in digital computers. Hence, some papers have been published considering implementation of Membrane Computing in digital computers. This paper introduces an overview in the field of simulation in Membrane Computing

An Ensemble Framework Coping with Instability in the Gene Selection Process

[EN] This paper proposes an ensemble framework for gene selection, which is aimed at addressing instability problems presented in the gene filtering task. The complex process of gene selection from gene expression data faces different instability problems from the informative gene subsets found by different filter methods. This makes the identification of significant genes by the experts difficult. The instability of results can come from filter methods, gene classifier methods, different datasets of the same disease and multiple valid groups of biomarkers. Even though there is a wide number of proposals, the complexity imposed by this problem remains a challenge today. This work proposes a framework involving five stages of gene filtering to discover biomarkers for diagnosis and classification tasks. This framework performs a process of stable feature selection, facing the problems above and, thus, providing a more suitable and reliable solution for clinical and research purposes. Our proposal involves a process of multistage gene filtering, in which several ensemble strategies for gene selection were added in such a way that different classifiers simultaneously assess gene subsets to face instability. Firstly, we apply an ensemble of recent gene selection methods to obtain diversity in the genes found (stability according to filter methods). Next, we apply an ensemble of known classifiers to filter genes relevant to all classifiers at a time (stability according to classification methods). The achieved results were evaluated in two different datasets of the same disease (pancreatic ductal adenocarcinoma), in search of stability according to the disease, for which promising results were achieved

On Logical Correction of Neural Network Algorithms for Pattern Recognition

The paper is devoted to the description of hybrid pattern recognition method developed by research groups from Russia, Armenia and Spain. The method is based upon logical correction over the set of conventional neural networks. Output matrices of neural networks are processed according to the potentiality principle which allows increasing of recognition reliability

Modeling, simulation and application of bacterial transduction in genetic algorithms

At present, all methods in Evolutionary Computation are bioinspired by the fundamental principles of neo-Darwinism, as well as by a vertical gene transfer. Virus transduction is one of the key mechanisms of horizontal gene propagation in microorganisms (e.g. bacteria). In the present paper, we model and simulate a transduction operator, exploring the possible role and usefulness of transduction in a genetic algorithm. The genetic algorithm including transduction has been named PETRI (abbreviation of Promoting Evolution Through Reiterated Infection). Our results showed how PETRI approaches higher fitness values as transduction probability comes close to 100%. The conclusion is that transduction improves the performance of a genetic algorithm, assuming a population divided among several sub-populations or ?bacterial colonies?

Prevalencia de varias entidades patológicas en ganado lechero del noroeste del Quindío.

Mediante la determinación de una muestra probabilística utilizando un modelo matemático de función binomial, se obtuvo la prevalencia de varias entidades patológicas en ganado lechero del noroeste del departamento del Quindío, Colombia. El tamaño n de muestra obtenido fue de 62, presumiendo una prevalencia crítica del 5 por ciento para las entidades patológicas consideradas en el estudio y con un nivel de confianza del 95 por ciento. La prevalencia de brucelosis fue estimada en 3.2 por ciento utilizando la prueba de Bang, mientras que para leptospirosis se encontraron índices de 20 por ciento para L. wolffi, 3.2 por ciento para L. canicola, 8 por ciento para L. hardjo y 1.6 por ciento para L. pomona, no lográndose hallar positivos a L. icterohemorragiae, L. ballum, L. javanica, L. autumnalis, L. bataviae y L. patoc. Para anaplasmosis, la prevalencia obtenida fue del 17.8 por ciento para A. marginale por la técnica del frotis sanguíneo, mientra que para la técnica de fijación del complemento (FC) el índice obtenido fue del 46.55 por ciento. Para babesiosis (B. argentina) se obtuvo el 56.8 por ciento de positividad (FC) y el 16.05 por ciento por la técnica indirecta de anticuerpos fluorescentes (FA) en tanto que para babesiosis (B. bigemina) se obtuvo una prevalencia del 46.55 por ciento (FC) y del 48.3 por ciento (FA). La proporción de positivos a IBR fue del 28.3 por ciento y a parainfluenza (PI3) del 10 por ciento. El estudio reveló, además, una alta proporción de animales afectados por nemátodos gastrointestinales (43.1 por ciento) y por Eimeria sp (29.4 por ciento)Ganado de leche-Ganadería lech

Estados emocionais agudos em residentes mexicanos durante a pandemia de COVID-19

The purpose of the study was to evaluate acute emotional states in Mexicans during the Covid-19 pandemic. Non-experimental-cross-sectional design. 585 Mexicans between 18 and 67 years of age participated. The DASS-21 scale was used to measure the variables of stress, anxiety and depression; and a questionnaire on situations related to confinement by COVID-19. The results show that a small percentage of the sample manifested negative emotional symptoms ranging from severe to very severe, as well as fear and anguish of contagion from a relative. Similarly, significant differences were identified between men and women, and age groups. The findings show the importance of designing and implementing psychological interventions aimed at reducing negative emotions during the coronavirus pandemic.El propósito del estudio fue evaluar los estados emocionales agudos en mexicanos durante la pandemia por Covid-19. Se tuvo un diseño no experimental-transversal. Participaron 585 mexicanos entre 18 y 67 años. Se utilizó la escala DASS-21 para medir las variables de estrés, ansiedad y depresión, y un cuestionario sobre situaciones relacionadas al confinamiento por COVID-19. Los resultados arrojan que un pequeño porcentaje de la muestra manifestó sintomatología emocional negativa de severa a muy severa, así como temor y angustia al contagio de un familiar. De igual manera, se identificaron diferencias significativas entre hombres y mujeres, y grupos de edad. Los hallazgos muestran la importancia de diseñar e implementar intervenciones psicológicas dirigidas a minorar las emociones negativas durante la pandemia por coronavirus.Le but de l'étude était d'évaluer les états émotionnels aigus chez les Mexicains pendant la pandémie de Covid-19. Conception en coupe transversale non expérimentale. 585 mexicains âgés de 18 à 67 ans y ont participé. L'échelle DASS-21 a été utilisée pour mesurer les variables du stress, de l'anxiété et de la dépression; et un questionnaire sur les situations liées au confinement par COVID-19. Les résultats montrent qu'un petit pourcentage de l'échantillon manifestait des symptômes émotionnels négatifs allant de graves à très graves, ainsi que la peur et l'angoisse de contagion d'un proche. De même, des différences significatives ont été identifiées entre les hommes et les femmes et les groupes d'âge. Les résultats montrent l'importance de concevoir et de mettre en œuvre des interventions psychologiques visant à réduire les émotions négatives pendant la pandémie.O objetivo do estudo era avaliar os estados emocionais agudos nos mexicanos durante a pandemia de Covid-19. Desenho transversal não experimental. Participaram 585 mexicanos entre 18 e 67 anos. A escala DASS-21 foi utilizada para medir as variáveis ​​de estresse, ansiedade e depressão; e um questionário sobre situações relacionadas ao confinamento por COVID-19. Os resultados mostram que uma pequena porcentagem da amostra manifestou sintomas emocionais negativos que variam de graves a muito graves, além de medo e angústia de contágio de um familiar. Da mesma forma, foram identificadas diferenças significativas entre homens e mulheres e grupos de idade. Os resultados mostram a importância de projetar e implementar intervenções psicológicas destinadas a reduzir as emoções negativas durante a pandemia