Fractional-step methods and finite elements with symmetric stabilization for the transient Oseen problem

International audienceThis paper deals with the spatial and time discretization of the transient Oseen equations. Finite elements with symmetric stabilization in space are combined with several time-stepping schemes (monolithic and fractional-step). Quasi-optimal (in space) and optimal (in time) error estimates are established for smooth solutions in all flow regimes. We first analyze monolithic time discretizations using the Backward Differentation Formulas of order 1 and 2 (BDF1 and BDF2). We derive a new estimate on the time-average of the pressure error featuring the same robustness with respect to the Reynolds number as the velocity estimate. Then, we analyze fractional-step pressure-projection methods using BDF1. The stabilization of velocities and pressures can be treated either implicitly or explicitly. Numerical results illustrate the main theoretical findings

Standard Operating Procedure for the PIC Content Management

The Rotterdam Convention that was signed in Rotterdam on 10 September 1998 and entered into force on 24 February 2004 regroups currently 154 Parties. It introduced the Prior Informed Consent (PIC) procedure for certain hazardous chemicals and pesticides in International trade. The convention aims to promote shared responsibility and cooperative effort among Parties in order to protect human health and the environment from potential harm and to contribute to their environmentally sound use, by facilitating information exchange about their characteristics, by providing for a national decision-making process on their import and export and by disseminating these decisions to Parties. The European Union adopted the Rotterdam Convention by Council Decision 2006/730/EC of 25 September 2006. Furthermore, Regulation (EC) No 689/2008 of the European Parliament and the Council of 17 June 2008 concerning the export and import of dangerous chemicals is the latest in a series of measures over the years that seek to address international trade with dangerous chemicals. This Regulation reaffirms the EU commitment towards ensuring proper control in the trade and use of dangerous chemicals at the global level, based on the principle that it should help to protect human health and the environment beyond its borders as well as within. Two linked processes were identified as characterising the PIC content management activities. They are analysed separately: the export notifications process and the explicit consents process. The export notifications process aims to identify uniquely the single administrative document clearing customs. The explicit consents process aims to explicitly exchange risk management information, between an exporting designated national authority and an importing one, prior to export of chemicals. Each process is first described. The functionalities supporting the process are listed and explained. The specific implication of the administrator in the process is then identified. Finally the liaison between both processes is analysed. Several working documents are annexed in order to transparently manage the hand over of the PIC content management activities to the European Chemicals Agency - ECHA.JRC.I.1-Chemical Assessment and Testin

The Central role of KNG1 gene as a genetic determinant of coagulation pathway-related traits: Exploring metaphenotypes

Traditional genetic studies of single traits may be unable to detect the pleiotropic effects involved in complex diseases. To detect the correlation that exists between several phenotypes involved in the same biological process, we introduce an original methodology to analyze sets of correlated phenotypes involved in the coagulation cascade in genome-wide association studies. The methodology consists of a two-stage process. First, we define new phenotypic meta-variables (linear combinations of the original phenotypes), named metaphenotypes, by applying Independent Component Analysis for the multivariate analysis of correlated phenotypes (i.e. the levels of coagulation pathway–related proteins). The resulting metaphenotypes integrate the information regarding the underlying biological process (i.e. thrombus/clot formation). Secondly, we take advantage of a family based Genome Wide Association Study to identify genetic elements influencing these metaphenotypes and consequently thrombosis risk. Our study utilized data from the GAIT Project (Genetic Analysis of Idiopathic Thrombophilia). We obtained 15 metaphenotypes, which showed significant heritabilities, ranging from 0.2 to 0.7. These results indicate the importance of genetic factors in the variability of these traits. We found 4 metaphenotypes that showed significant associations with SNPs. The most relevant were those mapped in a region near the HRG, FETUB and KNG1 genes. Our results are provocative since they show that the KNG1 locus plays a central role as a genetic determinant of the entire coagulation pathway and thrombus/clot formation. Integrating data from multiple correlated measurements through metaphenotypes is a promising approach to elucidate the hidden genetic mechanisms underlying complex diseases.Postprint (published version

A new gene-based association test for genome-wide association studies

Genome-wide association studies are widely used today to discover genetic factors that modify the risk of complex diseases. Usually, these methods work in a SNP-by-SNP fashion. We present a gene-based test that can be applied in the context of genome-wide association studies. We compare both strategies, SNP-based and gene-based, in a sample of cases and controls for rheumatoid arthritis

Molecular determinants of caste differentiation in the highly eusocial honeybee Apis mellifera

<p>Abstract</p> <p>Background</p> <p>In honeybees, differential feeding of female larvae promotes the occurrence of two different phenotypes, a queen and a worker, from identical genotypes, through incremental alterations, which affect general growth, and character state alterations that result in the presence or absence of specific structures. Although previous studies revealed a link between incremental alterations and differential expression of physiometabolic genes, the molecular changes accompanying character state alterations remain unknown.</p> <p>Results</p> <p>By using cDNA microarray analyses of >6,000 <it>Apis mellifera </it>ESTs, we found 240 differentially expressed genes (DEGs) between developing queens and workers. Many genes recorded as up-regulated in prospective workers appear to be unique to <it>A. mellifera</it>, suggesting that the workers' developmental pathway involves the participation of novel genes. Workers up-regulate more developmental genes than queens, whereas queens up-regulate a greater proportion of physiometabolic genes, including genes coding for metabolic enzymes and genes whose products are known to regulate the rate of mass-transforming processes and the general growth of the organism (e.g., <it>tor</it>). Many DEGs are likely to be involved in processes favoring the development of caste-biased structures, like brain, legs and ovaries, as well as genes that code for cytoskeleton constituents. Treatment of developing worker larvae with juvenile hormone (JH) revealed 52 JH responsive genes, specifically during the critical period of caste development. Using Gibbs sampling and Expectation Maximization algorithms, we discovered eight overrepresented <it>cis</it>-elements from four gene groups. Graph theory and complex networks concepts were adopted to attain powerful graphical representations of the interrelation between <it>cis</it>-elements and genes and objectively quantify the degree of relationship between these entities.</p> <p>Conclusion</p> <p>We suggest that clusters of functionally related DEGs are co-regulated during caste development in honeybees. This network of interactions is activated by nutrition-driven stimuli in early larval stages. Our data are consistent with the hypothesis that JH is a key component of the developmental determination of queen-like characters. Finally, we propose a conceptual model of caste differentiation in <it>A. mellifera </it>based on gene-regulatory networks.</p

Identificação de outliers em dados de precificação de ativos com um novo estimador de forward search ponderado

O objetivo deste trabalho é apresentar o método Forward Search Ponderado (FSW) para a detecção de valores discrepantes (outliers) nos dados de precificação de ativos. Esse novo estimador, baseado em um algoritmo que reduz o peso das observações mais anômalas do conjunto de dados, é testado utilizando dados simulados e empíricos de precificação de ativos. O impacto dos outliers na estimativa de modelos de precificação de ativos é avaliado em diferentes cenários, e os resultados são avaliados com testes estatísticos associados, com base nessa nova abordagem. Nossa proposta gera um procedimento alternativo para uma estimativa robusta dos betas da carteira, permitindo a comparação entre modelos concorrentes de precificação de ativos. O algoritmo, eficiente e robusto para outliers, é utilizado para fornecer estimativas robustas dos parâmetros dos modelos em uma comparação com os métodos tradicionais de estimativa econométrica geralmente utilizados na literatura. Em particular, a precisão dos alfas é significantemente aumentada quando o método Forward Search (FS) é utilizado. Utilizamos simulações de Monte Carlo e também o conhecido conjunto de dados de fatores de retornos acionários, fornecido pelo Prof. Kenneth French, que consiste em 25 carteiras Fama-French no mercado acionário dos Estados Unidos, utilizando modelos de um e três fatores, em base mensal e anual. Nossos resultados indicam que a rejeição marginal do modelo de três fatores de Fama-French é influenciada pela presença de outliers nas carteiras, ao utilizar retornos mensais. Em dados anuais, o uso de métodos robustos aumenta o nível de rejeição de alfas nulos no Modelo de Precificação de Ativos de Capital (Capital Asset Pricing Model –CAPM) e no modelo de três fatores de Fama-French, com estimativas mais eficientes na ausência de outliers, e alfas consistentes quando os outliers estão presentes.O objetivo deste trabalho é apresentar o método Forward Search Ponderado (FSW) para a detecção de valores discrepantes (outliers) nos dados de precificação de ativos. Esse novo estimador, baseado em um algoritmo que reduz o peso das observações mais anômalas do conjunto de dados, é testado utilizando dados simulados e empíricos de precificação de ativos. O impacto dos outliers na estimativa de modelos de precificação de ativos é avaliado em diferentes cenários, e os resultados são avaliados com testes estatísticos associados, com base nessa nova abordagem. Nossa proposta gera um procedimento alternativo para uma estimativa robusta dos betas da carteira, permitindo a comparação entre modelos concorrentes de precificação de ativos. O algoritmo, eficiente e robusto para outliers, é utilizado para fornecer estimativas robustas dos parâmetros dos modelos em uma comparação com os métodos tradicionais de estimativa econométrica geralmente utilizados na literatura. Em particular, a precisão dos alfas é significantemente aumentada quando o método Forward Search (FS) é utilizado. Utilizamos simulações de Monte Carlo e também o conhecido conjunto de dados de fatores de retornos acionários, fornecido pelo Prof. Kenneth French, que consiste em 25 carteiras Fama-French no mercado acionário dos Estados Unidos, utilizando modelos de um e três fatores, em base mensal e anual. Nossos resultados indicam que a rejeição marginal do modelo de três fatores de Fama-French é influenciada pela presença de outliers nas carteiras, ao utilizar retornos mensais. Em dados anuais, o uso de métodos robustos aumenta o nível de rejeição de alfas nulos no Modelo de Precificação de Ativos de Capital (Capital Asset Pricing Model –CAPM) e no modelo de três fatores de Fama-French, com estimativas mais eficientes na ausência de outliers, e alfas consistentes quando os outliers estão presentes.The purpose of this work is to present the Weighted Forward Search (FSW) method for the detection of outliers in asset pricing data. This new estimator, which is based on an algorithm that downweights the most anomalous observations of the dataset, is tested using both simulated and empirical asset pricing data. The impact of outliers on the estimation of asset pricing models is assessed under different scenarios, and the results are evaluated with associated statistical tests based on this new approach. Our proposal generates an alternative procedure for robust estimation of portfolio betas, allowing for the comparison between concurrent asset pricing models. The algorithm, which is both efficient and robust to outliers, is used to provide robust estimates of the models’ parameters in a comparison with traditional econometric estimation methods usually used in the literature. In particular, the precision of the alphas is highly increased when the Forward Search (FS) method is used. We use Monte Carlo simulations, and also the well-known dataset of equity factor returns provided by Prof. Kenneth French, consisting of the 25 Fama-French portfolios on the United States of America equity market using single and three-factor models, on monthly and annual basis. Our results indicate that the marginal rejection of the Fama-French three-factor model is influenced by the presence of outliers in the portfolios, when using monthly returns. In annual data, the use of robust methods increases the rejection level of null alphas in the Capital Asset Pricing Model (CAPM) and the Fama-French three-factor model, with more efficient estimates in the absence of outliers and consistent alphas when outliers are present

Business Intelligence e a Ciência da Informação na Era dos Dados Abertos e Big Data

The combination and analysis of data from different bases, contextualized as an organization's activities and used for decision making, is the object of Information Systems (IS) called Business Intelligence (BI). Among the various aspects related to Open Data and Big Data is the use of the same data for decision making, whether they are in research groups, expert panels, entities and research institutions. The Information Science (IS) and the scientific research on BI can support in this attempt, however IS has researched very little this theme. Considering the terminological, conceptual and understanding problem of BI in IS, a proposal for a term, concept and taxonomy of BI is presented to support the research by IS and leverage the contribution in this important technological trend associated with Data Science and Digital Transformation. The research used was of the bibliographic and exploratory type. He analyzed documents retrieved from the Web of Science, BRAPCI, CAPES Thesis and dissertations databases. As results a) it is proposed to adopt the term in English without translation; b) a BI concept is presented; and, c) a BI taxonomy is presented containing seven main categories. Keywords: Business Intelligence; BI; Information Science; Terminological Analysis; Taxonomy

Business Intelligence e a Ciência da Informação na Era dos Dados Abertos e Big Data

The combination and analysis of data from different bases, contextualized as an organization's activities and used for decision making, is the object of Information Systems (IS) called Business Intelligence (BI). Among the various aspects related to Open Data and Big Data is the use of the same data for decision making, whether they are in research groups, expert panels, entities and research institutions. The Information Science (IS) and the scientific research on BI can support in this attempt, however IS has researched very little this theme. Considering the terminological, conceptual and understanding problem of BI in IS, a proposal for a term, concept and taxonomy of BI is presented to support the research by IS and leverage the contribution in this important technological trend associated with Data Science and Digital Transformation. The research used was of the bibliographic and exploratory type. He analyzed documents retrieved from the Web of Science, BRAPCI, CAPES Thesis and dissertations databases. As results a) it is proposed to adopt the term in English without translation; b) a BI concept is presented; and, c) a BI taxonomy is presented containing seven main categories. Keywords: Business Intelligence; BI; Information Science; Terminological Analysis; Taxonomy