Recycling workflows and services through discovery and reuse

Scientific workflows are becoming a valuable tool for scientists to capture and automate e-Science procedures. Their success brings the opportunity to publish, share, reuse and repurpose this explicitly captured knowledge. Within the myGrid project, we have identified key resources that can be shared including complete workflows, fragments of workflows and constituent services. We have examined the alternative ways these can be described by their authors (and subsequent users), and developed a unified descriptive model to support their later discovery. By basing this model on existing standards, we have been able to extend existing Web Service and Semantic Web Service infrastructure whilst still supporting the specific needs of the e-Scientist. myGrid components enable a workflow life-cycle that extends beyond execution, to include discovery of previous relevant designs, reuse of those designs, and subsequent publication. Experience with example groups of scientists indicates that this cycle is valuable. The growing number of workflows and services mean more work is needed to support the user in effective ranking of search results, and to support the repurposing process.

December 2006/January 2007: Space Shuttle Discovery Launch

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Cointegração e price discovery do risco soberano brasileiro

A lei do preço único afirma que o mesmo ativo negociado em diferentes mercados deve apresentar preços equivalentes. Este trabalho busca verificar se o risco de crédito soberano brasileiro negociado no mercado internacional é precificado de forma semelhante tanto nos tradicionais mercados de títulos quanto no novo e crescente mercado de derivativos de crédito. Adicionalmente, utiliza-se a análise de Price Discovery para examinar qual dos mercados se move mais rapidamente em resposta às mudanças nas condições de crédito da economia brasileira. A análise empírica é feita por meio de modelos de séries de tempo, mais especificamente análise de cointegração e vetor de correção de erros. Os resultados confirmam a predição teórica da lei do preço único de que o risco de crédito brasileiro, tanto nos mercados de títulos quanto no mercado de derivativos de crédito, movem-se juntos no longo prazo. Por fim, a maior parte do Price Discovery ocorre no mercado de derivativos de crédito.

Price discovery in dual-class shares across multiple markets

We extend the standard price discovery analysis to estimate the information share of dual-class shares across domestic and foreign markets. By examining both common and preferred shares, we aim to extract information not only about the fundamental value of the rm, but also about the dual-class premium. In particular, our interest lies on the price discovery mechanism regulating the prices of common and preferred shares in the BM&FBovespa as well as the prices of their ADR counterparts in the NYSE and in the Arca platform. However, in the presence of contemporaneous correlation between the innovations, the standard information share measure depends heavily on the ordering we attribute to prices in the system. To remain agnostic about which are the leading share class and market, one could for instance compute some weighted average information share across all possible orderings. This is extremely inconvenient given that we are dealing with 2 share prices in Brazil, 4 share prices in the US, plus the exchange rate (and hence over 5,000 permutations!). We thus develop a novel methodology to carry out price discovery analyses that does not impose any ex-ante assumption about which share class or trading platform conveys more information about shocks in the fundamental price. As such, our procedure yields a single measure of information share, which is invariant to the ordering of the variables in the system. Simulations of a simple market microstructure model show that our information share estimator works pretty well in practice. We then employ transactions data to study price discovery in two dual-class Brazilian stocks and their ADRs. We uncover two interesting ndings. First, the foreign market is at least as informative as the home market. Second, shocks in the dual-class premium entail a permanent e ect in normal times, but transitory in periods of nancial distress. We argue that the latter is consistent with the expropriation of preferred shareholders as a class.

KittyCat: a cognitive model of structure-form discovery

Cognition is a core subject to understand how humans think and behave. In that sense, it is clear that Cognition is a great ally to Management, as the later deals with people and is very interested in how they behave, think, and make decisions. However, even though Cognition shows great promise as a field, there are still many topics to be explored and learned in this fairly new area. Kemp & Tenembaum (2008) tried to a model graph-structure problem in which, given a dataset, the best underlying structure and form would emerge from said dataset by using bayesian probabilistic inferences. This work is very interesting because it addresses a key cognition problem: learning. According to the authors, analogous insights and discoveries, understanding the relationships of elements and how they are organized, play a very important part in cognitive development. That is, this are very basic phenomena that allow learning. Human beings minds do not function as computer that uses bayesian probabilistic inferences. People seem to think differently. Thus, we present a cognitively inspired method, KittyCat, based on FARG computer models (like Copycat and Numbo), to solve the proposed problem of discovery the underlying structural-form of a dataset.

Macroeconomic announcements, price discovery, and order flow efects in the stock market: evidence from incomplete data and multiple financial markets

This paper investigates heterogeneity in the market assessment of public macro- economic announcements by exploring (jointly) two main mechanisms through which macroeconomic news might enter stock prices: instantaneous fundamental news im- pacts consistent with the asset pricing view of symmetric information, and permanent order ow e¤ects consistent with a microstructure view of asymmetric information related to heterogeneous interpretation of public news. Theoretical motivation and empirical evidence for the operation of both mechanisms are presented. Signi cant in- stantaneous news impacts are detected for news related to real activity (including em- ployment), investment, in ation, and monetary policy; however, signi cant order ow e¤ects are also observed on employment announcement days. A multi-market analysis suggests that these asymmetric information e¤ects come from uncertainty about long term interest rates due to heterogeneous assessments of future Fed responses to em- ployment shocks.

Price discovery using a regime-sensitive cointegration approach

This work proposes a method to examine variations in the cointegration relation between preferred and common stocks in the Brazilian stock market via Markovian regime switches. It aims on contributing for future works in "pairs trading" and, more specifically, to price discovery, given that, conditional on the state, the system is assumed stationary. This implies there exists a (conditional) moving average representation from which measures of "information share" (IS) could be extracted. For identification purposes, the Markov error correction model is estimated within a Bayesian MCMC framework. Inference and capability of detecting regime changes are shown using a Montecarlo experiment. I also highlight the necessity of modeling financial effects of high frequency data for reliable inference.

SysPRE: systematized process for requirements engineering in knowledge discovery projects

The domain of Knowledge Discovery (KD) and Data Mining (DM) is of growing importance in a time where more and more data is produced and knowledge is one of the most precious assets. Having explored both the existing underlying theory, the results of the ongoing research in academia and the industry practices in the domain of KD and DM, we have found that this is a domain that still lacks some systematization. We also found that this systematization exists to a greater degree in the Software Engineering and Requirements Engineering domains, probably due to being more mature areas. We believe that it is possible to improve and facilitate the participation of enterprise stakeholders in the requirements engineering for KD projects by systematizing requirements engineering process for such projects. This will, in turn, result in more projects that end successfully, that is, with satisfied stakeholders, including in terms of time and budget constraints. With this in mind and based on all information found in the state-of-the art, we propose SysPRE - Systematized Process for Requirements Engineering in KD projects. We begin by proposing an encompassing generic description of the KD process, where the main focus is on the Requirements Engineering activities. This description is then used as a base for the application of the Design and Engineering Methodology for Organizations (DEMO) so that we can specify a formal ontology for this process. The resulting SysPRE ontology can serve as a base that can be used not only to make enterprises become aware of their own KD process and requirements engineering process in the KD projects, but also to improve such processes in reality, namely in terms of success rate.

In vivo CYP2E1 phenotyping as a new potential biomarker of occupational and experimental exposure to benzene

Assessing CYP2E1 phenotype in vivo may be important to predict individual susceptibility to those chemicals, including benzene, which are metabolically activated by this isoenzyme. Chlorzoxazone (CHZ), a specific CYP2E1 substrate, is readily hydroxylated to 6-OH-chlorzoxazone (6-OH-CHZ) by liver CYP2E1 and the metabolic ratio 6-OH-CHZ/CHZ in serum (MR) is a specific and sensitive biomarker of CYP2E1 activity in vivo in humans. We used this MR as a potential biomarker of effect in benzene-treated rats and, also, in humans occupationally exposed to low levels of benzene. Male Sprague-Dawley rats (375-400 g b.w.) were treated i.p. for 3 days with either a 0.5 ml solution of benzene (5 mmol/kg b.w.) in corn oil, or 0.5 ml corn oil alone. Twenty-four hours after the last injection, a polyethylene glycol (PEG) solution of CHZ (20 mg/kg b.w.) was injected i.p. in both treated and control animals. After 2, 5.10,15, 20,30,45, 60, 90, 120, 180, and 240 min from injection, 0.2 ml blood was taken from the tip tail and stored at -20 degrees C until analysis. A modified reverse phase HPLC method using a 5 mu m Ultrasphere C18 column equipped with a direct-connection ODS guard column, was used to measure CHZ and its metabolite 6-OH-CHZ in serum. No statistically significant difference in the MR was observed, at any sampling time, between benzene-treated and control rats. The concentration-versus-time area under the curve (AUC), however, was lower (p < 0.05, Mann-Whitney test), whereas the systemic clearance was higher (p < 0.05) in treated than in control rats. Eleven petrochemical workers occupationally exposed to low levels of airborne benzene (mean +/- SD, 25.0 +/- 24.4 mu g/m(3)) and 13 non-exposed controls from the same factory (mean +/- SD, 6.7 +/- 4.0 mu g/m(3)) signed an informed consent form and were administered 500 mg CHZ p.o. Two hours later a venous blood sample was taken for CHZ and 6-OH-CHZ measurements. Despite exposed subjects showed significantly higher levels of t,t-MA and S-PMA, two biomarkers of exposure to benzene, than non-exposed workers, no difference in the MR mean values +/- SD was found between exposed (0.59 +/- 0.29) and non-exposed (0.57 +/- 0.23) subjects. So, benzene was found to modify CHZ disposition, but not CYP2E1 phenotype in benzene-treated rats, nor in workers exposed to benzene, probably due to the levels of exposure being too low. (C) 2009 Elsevier B.V. All rights reserved.

Chicken skeletal muscle-associated macroarray for gene discovery

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)