Abstract
An exchange-traded fund (ETF) is a marketable security that tracks a stock index, a commodity, bonds, or a basket of assets. Therefore, returns of ETFs that track a benchmark index portfolio should mimic the returns of their benchmark indexes. If a benchmark index's performance exhibits a seasonal pattern, then the performance of its associated ETF should replicate that pattern. This type of ETF performance seasonality is induced by trends in the market of securities in the benchmark index portfolio. Any other seasonality can be considered to be idiosyncratic. Based on a sample of 148 ETFs listed in NYSE Arca, this article provides evidence of a half-year effect (higher performance in the first half-year), a quarter effect (outperformance of the second quarter and underperformance of the fourth quarter), and month within the quarter effect (higher and lower performance in the first and third months of each quarter, respectively). Additionally, superior and inferior performance were observed in April and December, respectively. These seasonal patterns are not visible on benchmark indexes, with the exception of the unusually positive performance in April, which can be considered induced seasonality. The other effects, which cannot be attributed to underlying markets, are evidence of idiosyncratic seasonality.

Abstract
Bayesian Monte Carlo (BMC) is a promising integration technique which considerably broadens the theoretical tools that can be used to maximize and exploit the information produced by sampling, while keeping the fundamental property of data dimension independence of classical Monte Carlo (CMC). Moreover, BMC uses information that is ignored in the CMC method, such as the position of the samples and prior stochastic information about the integrand, which often leads to better integral estimates. Nevertheless, the use of BMC in computer graphics is still in an incipient phase and its application to more evolved and widely used rendering algorithms remains cumbersome. In this article we propose to apply BMC to a two-level adaptive sampling scheme for illumination integrals. We propose an efficient solution for the second level quadrature computation and show that the proposed method outperforms adaptive quasi-Monte Carlo in terms of image error and high frequency noise. © 2016 The Eurographics Association.

Abstract
A Loggi, criada em 2013, é uma das empresas unicórnios no Brasil, com soluções inovadoras e relevantes no setor de logística, com forte base em tecnologias digitais. O conhecimento teórico, o conhecimento de aspectos de automatização do processo e de evidências do custo e eficácia de critérios, técnicas e ferramentas de testes são de fundamental importância para a construção de produtos de software de qualidade. Salienta-se que dispor de material de treinamento e capacitação em automatização de teste de software, considerando essa vasta gama de tecnologias e ferramentas, é desafiador e indispensável. Neste artigo relata-se um treinamento bem sucedido em automatização em teste de software instanciado para o contexto da Loggi Tecnologia. O grande diferencial está na combinação de teoria com prática intensiva com base em produtos de software da empresa e ferramentas já adotadas no desenvolvimento das soluções na empresa.

Abstract

Abstract
Software testing can promote software quality. However, this activity is often performed at the end of projects where failures are most difficult to correct. Combining requirements specification activities with test design at an early stage of the software development process can be beneficial. One way to do this is to use a more structured requirements specification language. This allow to reduce typical problems such as ambiguity, inconsistency, and incorrectness in requirements and may allow the automatic generation of (parts of) acceptance test cases reducing the test design effort. In this paper we discuss an approach that promotes the practice of requirements specification combined with testing specification. This is a model-based approach that promotes the alignment between requirements and tests, namely, test cases and also low-level automated test scripts. To show the applicability of this approach, we integrate two complementary languages: (i) the ITLingo RSL (Requirements Specification Language) that is specially designed to support both requirements and tests rigorously and consistently specified; and (ii) the Robot language, which is a low-level keyword-based language for specifying test scripts. This approach includes model-to-model transformation processes, namely a transformation process from requirements (defined in RSL) into test cases (defined in RSL), and a second transformation process from test cases (in RSL) into test scripts (defined according the Robot framework). This approach was applied in a fictitious online store that illustrates the various phases of the proposal.

Abstract
Expression Atlas is EMBL-EBI's resource for gene and protein expression. It sources and compiles data on the abundance and localisation of RNA and proteins in various biological systems and contexts and provides open access to this data for the research community. With the increased availability of single cell RNA-Seq datasets in the public archives, we have now extended Expression Atlas with a new added-value service to display gene expression in single cells. Single Cell Expression Atlas was launched in 2018 and currently includes 123 single cell RNA-Seq studies from 12 species. The website can be searched by genes within or across species to reveal experiments, tissues and cell types where this gene is expressed or under which conditions it is a marker gene. Within each study, cells can be visualized using a pre-calculated t-SNE plot and can be coloured by different features or by cell clusters based on gene expression. Within each experiment, there are links to downloadable files, such as RNA quantification matrices, clustering results, reports on protocols and associated metadata, such as assigned cell types.