Discriminant ECOC: a heuristic method for application dependent design of error correcting output codes

We present a heuristic method for learning error correcting output codes matrices based on a hierarchical partition of the class space that maximizes a discriminative criterion. To achieve this goal, the optimal codeword separation is sacrificed in favor of a maximum class discrimination in the partitions. The creation of the hierarchical partition set is performed using a binary tree. As a result, a compact matrix with high discrimination power is obtained. Our method is validated using the UCI database and applied to a real problem, the classification of traffic sign images.

A new aggregation method for strategic decision making and its application in assignment theory

A new aggregation method for decision making is presented by using induced aggregation operators and the index of maximum and minimum level. Its main advantage is that it can assess complex reordering processes in the aggregation that represent complex attitudinal characters of the decision maker such as psychological or personal factors. A wide range of properties and particular cases of this new approach are studied. A further generalization by using hybrid averages and immediate weights is also presented. The key issue in this approach against the previous model is that we can use the weighted average and the ordered weighted average in the same formulation. Thus, we are able to consider the subjective attitude and the degree of optimism of the decision maker in the decision process. The paper ends with an application in a decision making problem based on the use of the assignment theory.

GSVA: gene set variation analysis for microarray and RNA-seq data

Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org.

Combined intermittent hypoxia and surface muscle electrostimulation as a method to increase peripheral blood progenitor cell concentration.

Background: Our goal was to determine whether short-term intermittent hypoxia exposure, at a level well tolerated by healthy humans and previously shown by our group to increase EPO and erythropoiesis, could mobilizehematopoietic stem cells (HSC) and increase their presence in peripheral circulation. Methods: Four healthy male subjects were subjected to three different protocols: one with only a hypoxic stimulus (OH), another with a hypoxic stimulus plus muscle electrostimulation (HME) and the third with only muscle electrostimulation (OME). Intermittent hypobaric hypoxia exposureconsisted of only three sessions of three hours at barometric pressure 540 hPa (equivalent to an altitude of 5000 m) for three consecutive days, whereas muscular electrostimulation was performed in two separate periods of 25 min in each session. Blood samples were obtained from an antecubital vein on three consecutive days immediately before the experiment and 24 h, 48 h, 4 days and 7 days after the last day of hypoxic exposure. Results: There was a clear increase in the number of circulating CD34+ cells after combined hypobaric hypoxia and muscular electrostimulation. This response was not observed after the isolated application of the same stimuli. Conclusion: Our results open a new application field for hypobaric systems as a way to increase efficiency in peripheral HSC collection.

Combined intermittent hypoxia and surface muscle electrostimulation as a method to increase peripheral blood progenitor cell concentration.

Background: Our goal was to determine whether short-term intermittent hypoxia exposure, at a level well tolerated by healthy humans and previously shown by our group to increase EPO and erythropoiesis, could mobilizehematopoietic stem cells (HSC) and increase their presence in peripheral circulation. Methods: Four healthy male subjects were subjected to three different protocols: one with only a hypoxic stimulus (OH), another with a hypoxic stimulus plus muscle electrostimulation (HME) and the third with only muscle electrostimulation (OME). Intermittent hypobaric hypoxia exposureconsisted of only three sessions of three hours at barometric pressure 540 hPa (equivalent to an altitude of 5000 m) for three consecutive days, whereas muscular electrostimulation was performed in two separate periods of 25 min in each session. Blood samples were obtained from an antecubital vein on three consecutive days immediately before the experiment and 24 h, 48 h, 4 days and 7 days after the last day of hypoxic exposure. Results: There was a clear increase in the number of circulating CD34+ cells after combined hypobaric hypoxia and muscular electrostimulation. This response was not observed after the isolated application of the same stimuli. Conclusion: Our results open a new application field for hypobaric systems as a way to increase efficiency in peripheral HSC collection.

A method for decision making with the OWA operator

A new method for decision making that uses the ordered weighted averaging (OWA) operator in the aggregation of the information is presented. It is used a concept that it is known in the literature as the index of maximum and minimum level (IMAM). This index is based on distance measures and other techniques that are useful for decision making. By using the OWA operator in the IMAM, we form a new aggregation operator that we call the ordered weighted averaging index of maximum and minimum level (OWAIMAM) operator. The main advantage is that it provides a parameterized family of aggregation operators between the minimum and the maximum and a wide range of special cases. Then, the decision maker may take decisions according to his degree of optimism and considering ideals in the decision process. A further extension of this approach is presented by using hybrid averages and Choquet integrals. We also develop an application of the new approach in a multi-person decision-making problem regarding the selection of strategies.

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Use of physiological constraints to identify quantitative design principles for gene expression in yeast adaptation to heat shock

Background: Understanding the relationship between gene expression changes, enzyme activity shifts, and the corresponding physiological adaptive response of organisms to environmental cues is crucial in explaining how cells cope with stress. For example, adaptation of yeast to heat shock involves a characteristic profile of changes to the expression levels of genes coding for enzymes of the glycolytic pathway and some of its branches. The experimental determination of changes in gene expression profiles provides a descriptive picture of the adaptive response to stress. However, it does not explain why a particular profile is selected for any given response. Results: We used mathematical models and analysis of in silico gene expression profiles (GEPs) to understand how changes in gene expression correlate to an efficient response of yeast cells to heat shock. An exhaustive set of GEPs, matched with the corresponding set of enzyme activities, was simulated and analyzed. The effectiveness of each profile in the response to heat shock was evaluated according to relevant physiological and functional criteria. The small subset of GEPs that lead to effective physiological responses after heat shock was identified as the result of the tuning of several evolutionary criteria. The experimentally observed transcriptional changes in response to heat shock belong to this set and can be explained by quantitative design principles at the physiological level that ultimately constrain changes in gene expression. Conclusion: Our theoretical approach suggests a method for understanding the combined effect of changes in the expression of multiple genes on the activity of metabolic pathways, and consequently on the adaptation of cellular metabolism to heat shock. This method identifies quantitative design principles that facilitate understating the response of the cell to stress.

Optimal capital structure: a trade-off model and its empirical testing

In the present research we have set forth a new, simple, Trade-Off model that would allow us to calculate how much debt and, by default, how much equity a company should have, using easily available information and calculating the cost of debt dynamically on the basis of the effect that the capital structure of the company has on the risk of bankruptcy; in an attempt to answer this question. The proposed model has been applied to the companies that make up the Dow Jones Industrial Average (DJIA) in 2007. We have used consolidated financial data from 1996 to 2006, published by Bloomberg. We have used simplex optimization method to find the debt level that maximizes firm value. Then, we compare the estimated debt with real debt of companies using statistical nonparametric Mann-Whitney. The results indicate that 63% of companies do not show a statistically significant difference between the real and the estimated debt.

Microscopic-macroscopic approach for binding energies with the Wigner-Kirkwood method. II. Deformed nuclei

The binding energies of deformed even-even nuclei have been analyzed within the framework of a recently proposed microscopic-macroscopic model. We have used the semiclassical Wigner-Kirkwood ̄h expansion up to fourth order, instead of the usual Strutinsky averaging scheme, to compute the shell corrections in a deformed Woods-Saxon potential including the spin-orbit contribution. For a large set of 561 even-even nuclei with Z 8 and N 8, we find an rms deviation from the experiment of 610 keV in binding energies, comparable to the one found for the same set of nuclei using the finite range droplet model of Moller and Nix (656 keV). As applications of our model, we explore its predictive power near the proton and neutron drip lines as well as in the superheavy mass region. Next, we systematically explore the fourth-order Wigner-Kirkwood corrections to the smooth part of the energy. It is found that the ratio of the fourth-order to the second-order corrections behaves in a very regular manner as a function of the asymmetry parameter I=(N−Z)/A. This allows us to absorb the fourth-order corrections into the second-order contributions to the binding energy, which enables us us to simplify and speed up the calculation of deformed nuclei.

A method for decision making with the OWA operator

A new method for decision making that uses the ordered weighted averaging (OWA) operator in the aggregation of the information is presented. It is used a concept that it is known in the literature as the index of maximum and minimum level (IMAM). This index is based on distance measures and other techniques that are useful for decision making. By using the OWA operator in the IMAM, we form a new aggregation operator that we call the ordered weighted averaging index of maximum and minimum level (OWAIMAM) operator. The main advantage is that it provides a parameterized family of aggregation operators between the minimum and the maximum and a wide range of special cases. Then, the decision maker may take decisions according to his degree of optimism and considering ideals in the decision process. A further extension of this approach is presented by using hybrid averages and Choquet integrals. We also develop an application of the new approach in a multi-person decision-making problem regarding the selection of strategies.

Gene Set Analysis for improving genetic association studies

Introduction. Genetic epidemiology is focused on the study of the genetic causes that determine health and diseases in populations. To achieve this goal a common strategy is to explore differences in genetic variability between diseased and nondiseased individuals. Usual markers of genetic variability are single nucleotide polymorphisms (SNPs) which are changes in just one base in the genome. The usual statistical approach in genetic epidemiology study is a marginal analysis, where each SNP is analyzed separately for association with the phenotype. Motivation. It has been observed, that for common diseases the single-SNP analysis is not very powerful for detecting genetic causing variants. In this work, we consider Gene Set Analysis (GSA) as an alternative to standard marginal association approaches. GSA aims to assess the overall association of a set of genetic variants with a phenotype and has the potential to detect subtle effects of variants in a gene or a pathway that might be missed when assessed individually. Objective. We present a new optimized implementation of a pair of gene set analysis methodologies for analyze the individual evidence of SNPs in biological pathways. We perform a simulation study for exploring the power of the proposed methodologies in a set of scenarios with different number of causal SNPs under different effect sizes. In addition, we compare the results with the usual single-SNP analysis method. Moreover, we show the advantage of using the proposed gene set approaches in the context of an Alzheimer disease case-control study where we explore the Reelin signal pathway.

Microscopic-macroscopic approach for binding energies with the Wigner-Kirkwood method

The semiclassical Wigner-Kirkwood ̄h expansion method is used to calculate shell corrections for spherical and deformed nuclei. The expansion is carried out up to fourth order in ̄h. A systematic study of Wigner-Kirkwood averaged energies is presented as a function of the deformation degrees of freedom. The shell corrections, along with the pairing energies obtained by using the Lipkin-Nogami scheme, are used in the microscopic-macroscopic approach to calculate binding energies. The macroscopic part is obtained from a liquid drop formula with six adjustable parameters. Considering a set of 367 spherical nuclei, the liquid drop parameters are adjusted to reproduce the experimental binding energies, which yields a root mean square (rms) deviation of 630 keV. It is shown that the proposed approach is indeed promising for the prediction of nuclear masses.

Method development for the simultaneous determination of methylmercury and inorganic mercury in seafood

This paper reports the method development for the simultaneous determination of methylmercury MeHgþ) and inorganic mercury (iHg) species in seafood samples. The study focused on the extraction and quantification of MeHgþ (the most toxic species) by liquid chromatography coupled to on-line UV irradiation and cold vapour atomic fluorescence spectroscopy (LC-UV-CV-AFS), using HCl 4 mol/L as the extractant agent. Accuracy of the method has been verified by analysing three certified reference materials and different spiked samples. The values found for total Hg and MeHgþ for the CRMs did not differ significantly from certified values at a 95% confidence level, and recoveries between 85% and 97% for MeHgþ, based on spikes, were achieved. The detection limits (LODs) obtained were 0.001 mg Hg/kg for total mercury, 0.0003 mg Hg/kg for MeHgþ and 0.0004 mg Hg/kg for iHg. The quantification limits (LOQs) established were 0.003 mg Hg/kg for total mercury, 0.0010 mg Hg/kg for MeHgþ and 0.0012 mg Hg/kg for iHg. Precision for each mercury species was established, being 12% in terms of RSD in all cases. Finally, the developed method was applied to 24 seafood samples from different origins and total mercury contents. The concentrations for Total Hg, MeHg and iHg ranged from 0.07 to 2.33, 0.003-2.23 and 0.006-0.085 mg Hg/kg, respectively. The established analytical method allows to obtain results for mercury speciation in less than 1 one hour including both, sample pretreatment and measuring step.

Acción educativa para la prevención y el tratamiento de la neglicencia parental en el barrio de Can Rull del municipio de Sabadell

Este trabajo se inscribe en el ámbito de la prevención de la negligencia parental. Basado en un proceso teórico-práctico, el programa de intervención está sujeto a la línea de los programas de formación de padres, por lo que sigue una dinámica psico-educativa y comunitaria. Para la realización del trabajo se ha partido de la idea que la familia es la base del desarrollo personal de los humanos y que el buen desarrollo de los menores dependerá en gran parte de las relaciones intrafamiliares. Se establece como objetivo principal ofrecer un servicio específico, estable y continuo, vinculado a los servicios de atención a la infancia y a la familia, que trabaje con el fin de conseguir un cambio conductual en aquellas familias en las que se presente una dinámica parental negligente. La metodología utilizada ha combinado diferentes técnicas de investigación. Para el trabajo de documentación se ha realizado una búsqueda bibliográfica alrededor del concepto de negligencia parental, se han analizado las acciones que se llevan a cabo a nivel institucional y se ha establecido el marco conceptual en el que se incluye tanto los aspectos legal de las diferentes áreas de la administración como aquellos conceptos que forman la estructura de una intervención en el ámbito de la infancia y la familia. También se ha tenido en cuenta la comunicación directa con algunos profesionales del ámbito social, sanitario y educativo como parte importante y determinante del proceso de ejecución del programa. El diseño del programa sigue la metodología del planeamiento estratégico e incluye un diagnóstico preliminar, un plan de acción detallado de las diferentes fases de implementación de la propuesta de intervención, la previsión de mecanismos de evaluación y un presupuesto detallado. En la primera parte del trabajo se refleja la gravedad y el impacto que tiene la negligencia parental en nuestra sociedad, observando la evolución histórica del concepto y la visualización de la problemática a la que va asociado. También se expone la necesidad de crear programas destinados a trabajar esta problemática y una revisión del marco legal que regula la atención a la infancia por parte de las administraciones públicas. En una segunda parte, se propone un programa específico destinado a trabajar la negligencia parental desde una perspectiva de reeducación y cambio conductual. Este proyecto de intervención se ubica en el barrio de Can Rull en Sabadell, del cual se detallan sus especificidades socioeconómicas y su realidad institucional.