Desenho e desenvolvimento de um Sistema de Informação em Oracle ADF

Um Sistema de Informação consiste num sistema capaz de armazenar, organizar e estruturar dados para ajudar a responder às necessidades das empresas, passando também pela capacidade de resposta às questões diárias das empresas. Assim, um Sistema de Informação pode ser definido como o software que ajuda a organizar e analisar dados, tendo como objetivo fornecer informação útil na altura certa para que possa ser utilizada para a tomada de decisões ou para uma gestão mais eficiente dos diversos fluxos que uma empresa pode conter. Neste sentido, o projeto apresentado centra-se no desenho e construção de um Sistema de Informação capaz de gerir o negócio de uma empresa do setor alimentar, mais propriamente do setor da transformação de carnes. Foi desenvolvido em Oracle ADF, de forma a aproveitar as vantagens inerentes à tecnologia e ao desenvolvimento web. Sendo uma tecnologia relativamente nova no mercado e dominada por poucos, a sua utilização neste momento pode tornar-se uma grande vantagem. Para o desenvolvimento da aplicação foi realizado o levantamento e análise de requisitos, foi criada a base de dados capaz de suportar o funcionamento do software e desenvolvido um sistema de login, capaz de gerir as sessões de cada utilizador. Foi implementado um processo de introdução e edição de informação, nomeadamente o registo de entradas, transformações e saídas. Contemplou-se também uma secção com dados mestre da empresa com a possibilidade de inserção, atualização e/ou remoção. Além disso, foram incorporadas validações em todos os processos que são usados pelos utilizadores, de modo a evitar a existência de dados incoerentes ou duplicados. Relativamente à lógica de negócio, foi embutida na aplicação de forma a permitir consultar a informação de forma clara, rápida e em diversos lugares, reduzindo tempo e tarefas ao colaborador/utilizador, visto que os processos foram automatizados. Com a implementação deste Sistema de Informação, a empresa pode usufruir de um sistema integrado capaz de gerir e controlar todo o seu processo produtivo, reduzindo custos e desperdícios, aumentando a produtividade e eficiência.

Molecular characterization of Trypanosoma cruzi Mexican strains and their behavior in the mouse experimental model

INTRODUCTION: For a long time, the importance of Chagas disease in Mexico, where many regarded it as an exotic malady, was questioned. Considering the great genetic diversity among isolates of Trypanosoma cruzi, the importance of this biological characterization, and the paucity of information on the clinical and biological aspects of Chagas disease in Mexico, this study aimed to identify the molecular and biological characterization of Trypanosoma cruzi isolates from different endemic areas of this country, especially of the State of Jalisco. METHODS: Eight Mexican Trypanosoma cruzi strains were biologically and genetically characterized (PCR specific for Trypanosoma cruzi, multiplex-PCR, amplification of space no transcript of the genes of the mini-exon, amplification of polymorphic regions of the mini-exon, classification by amplification of intergenic regions of the spliced leader genes, RAPD - (random amplified polymorphic DNA). RESULTS: Two profiles of parasitaemia were observed, patent (peak parasitaemia of 4.6×10(6) to 10(7) parasites/mL) and subpatent. In addition, all isolates were able to infect 100% of the animals. The isolates mainly displayed tropism for striated (cardiac and skeletal) muscle. PCR amplification of the mini-exon gene classified the eight strains as TcI. The RAPD technique revealed intraspecies variation among isolates, distinguishing strains isolated from humans and triatomines and according to geographic origin. CONCLUSIONS: The Mexican T. cruzi strains are myotrophic and belong to group TcI.

Optimal monitoring to implement clean technologies when pollution is random

We analyze a model where firms chose a production technology which, together with some random event, determines the final emission level. We consider the coexistence of two alternative technologies: a "clean" technology, and a "dirty" technology. The environmental regulation is based on taxes over reported emissions, and on penalties over unreported emissions. We show that the optimal inspection policy is a cut-off strategy, for several scenarios concerning the observability of the adoption of the clean technology and the cost of adopting it. We also show that the optimal inspection policy induces the firm to adopt the clean technology if the adoption cost is not too high, but the cost levels for which the firm adopts it depend on the scenario.

Bayesian Inference in the Time Varying Cointegration Model

There are both theoretical and empirical reasons for believing that the parameters of macroeconomic models may vary over time. However, work with time-varying parameter models has largely involved Vector autoregressions (VARs), ignoring cointegration. This is despite the fact that cointegration plays an important role in informing macroeconomists on a range of issues. In this paper we develop time varying parameter models which permit cointegration. Time-varying parameter VARs (TVP-VARs) typically use state space representations to model the evolution of parameters. In this paper, we show that it is not sensible to use straightforward extensions of TVP-VARs when allowing for cointegration. Instead we develop a specification which allows for the cointegrating space to evolve over time in a manner comparable to the random walk variation used with TVP-VARs. The properties of our approach are investigated before developing a method of posterior simulation. We use our methods in an empirical investigation involving a permanent/transitory variance decomposition for inflation.

A New Model Of Trend Inflation

This paper introduces a new model of trend (or underlying) inflation. In contrast to many earlier approaches, which allow for trend inflation to evolve according to a random walk, ours is a bounded model which ensures that trend inflation is constrained to lie in an interval. The bounds of this interval can either be fixed or estimated from the data. Our model also allows for a time-varying degree of persistence in the transitory component of inflation. The bounds placed on trend inflation mean that standard econometric methods for estimating linear Gaussian state space models cannot be used and we develop a posterior simulation algorithm for estimating the bounded trend inflation model. In an empirical exercise with CPI inflation we find the model to work well, yielding more sensible measures of trend inflation and forecasting better than popular alternatives such as the unobserved components stochastic volatility model.

Fiscal Sustainability in a New Keynesian Model

Recent work on optimal monetary and fiscal policy in New Keynesian models suggests that it is optimal to allow steady-state debt to follow a random walk. Leith and Wren-Lewis (2012) consider the nature of the timeinconsistency involved in such a policy and its implication for discretionary policy-making. We show that governments are tempted, given inflationary expectations, to utilize their monetary and fiscal instruments in the initial period to change the ultimate debt burden they need to service. We demonstrate that this temptation is only eliminated if following shocks, the new steady-state debt is equal to the original (efficient) debt level even though there is no explicit debt target in the government’s objective function. Analytically and in a series of numerical simulations we show which instrument is used to stabilize the debt depends crucially on the degree of nominal inertia and the size of the debt-stock. We also show that the welfare consequences of introducing debt are negligible for precommitment policies, but can be significant for discretionary policy. Finally, we assess the credibility of commitment policy by considering a quasi-commitment policy which allows for different probabilities of reneging on past promises. This on-line Appendix extends the results of this paper.

Fiscal Sustainability in a New Keynesian Model

Recent work on optimal monetary and fiscal policy in New Keynesian models suggests that it is optimal to allow steady-state debt to follow a random walk. Leith and Wren-Lewis (2012) consider the nature of the timeinconsistency involved in such a policy and its implication for discretionary policy-making. We show that governments are tempted, given inflationary expectations, to utilize their monetary and fiscal instruments in the initial period to change the ultimate debt burden they need to service. We demonstrate that this temptation is only eliminated if following shocks, the new steady-state debt is equal to the original (efficient) debt level even though there is no explicit debt target in the government’s objective function. Analytically and in a series of numerical simulations we show which instrument is used to stabilize the debt depends crucially on the degree of nominal inertia and the size of the debt-stock. We also show that the welfare consequences of introducing debt are negligible for precommitment policies, but can be significant for discretionary policy. Finally, we assess the credibility of commitment policy by considering a quasi-commitment policy which allows for different probabilities of reneging on past promises. This on-line Appendix extends the results of this paper.

Measuring the Euro-Dollar Permanent Equilibrium Exchange Rate using the Unobserved Components Model

This paper employs an unobserved component model that incorporates a set of economic fundamentals to obtain the Euro-Dollar permanent equilibrium exchange rates (PEER) for the period 1975Q1 to 2008Q4. The results show that for most of the sample period, the Euro-Dollar exchange rate closely followed the values implied by the PEER. The only significant deviations from the PEER occurred in the years immediately before and after the introduction of the single European currency. The forecasting exercise shows that incorporating economic fundamentals provides a better long-run exchange rate forecasting performance than a random walk process.

Knowledge of Catalan, public/private sector choice and earnings: Evidence from a double sample selection model

This paper explores the earnings return to Catalan knowledge for public and private workers in Catalonia. In doing so, we allow for a double simultaneous selection process. We consider, on the one hand, the non-random allocation of workers into one sector or another, and on the other, the potential self-selection into Catalan proficiency. In addition, when correcting the earnings equations, we take into account the correlation between the two selectivity rules. Our findings suggest that the apparent higher language return for public sector workers is entirely accounted for by selection effects, whereas knowledge of Catalan has a significant positive return in the private sector, which is somewhat higher when the selection processes are taken into account.

Random mating with a finite number of matings.

Random mating is the null model central to population genetics. One assumption behind random mating is that individuals mate an infinite number of times. This is obviously unrealistic. Here we show that when each female mates a finite number of times, the effective size of the population is substantially decreased.

Hierarchical conditional random fields for parts based models matching

A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.

Mòdul de gestió de magatzems segons el model d'organització física de "magatzem caòtic"

Creació d'una 'aplicació de gestió comercial i comptable partint de la ja existent en l’empresa Ph Systems S.L., seguint per tant la tecnologia utilitzada en aquesta aplicació, desenvolupada en Visual Basic 6 i utilitzant uns objectes i llibreries propis per facilitat l’enllaç dels formularis amb les taules de la base de dades utilitzant tant connexions ODBC com connexions OLE DB. El gestor de base de dades seleccionat per realitzar el projecte serà Oracle, que és el que actualment s’utilitza per les dades de l’aplicació de gestió d’estocs. Tasques a realitzar:Anàlisi dels requeriments del sistema.Disseny dels diferents mòduls de la futura aplicació.Obtenir una base de dades ben definida partint de la ja existent.Implementació dels mòduls de la futura aplicació.Els objectius d’aprenentatge d’aquest projecte són els següents:Millora del coneixement de la gestió d’una base de dades OracleMillora en l’aprenentatge del llenguatge de programació Visual Basic 6

A continuous strain-space model of viral evolution within a host

Viruses rapidly evolve, and HIV in particular is known to be one of the fastest evolving human viruses. It is now commonly accepted that viral evolution is the cause of the intriguing dynamics exhibited during HIV infections and the ultimate success of the virus in its struggle with the immune system. To study viral evolution, we use a simple mathematical model of the within-host dynamics of HIV which incorporates random mutations. In this model, we assume a continuous distribution of viral strains in a one-dimensional phenotype space where random mutations are modelled by di ffusion. Numerical simulations show that random mutations combined with competition result in evolution towards higher Darwinian fitness: a stable traveling wave of evolution, moving towards higher levels of fi tness, is formed in the phenoty space.

A general continuous auction model with insiders

We analyse in a unified way how the presence of a trader with privilege information makes the market to be efficient when the release time is known. We establish a general relation between the problem of finding an equilibrium and the problem of enlargement of filtrations. We also consider the case where the time of announcement is random. In such a case the market is not fully efficient and there exists equilibrium if the sensitivity of prices with respect to the global demand is time decreasing according with the distribution of the random time.

The average inter-crossing number of equilateral random walks and polygons

In this paper, we study the average inter-crossing number between two random walks and two random polygons in the three-dimensional space. The random walks and polygons in this paper are the so-called equilateral random walks and polygons in which each segment of the walk or polygon is of unit length. We show that the mean average inter-crossing number ICN between two equilateral random walks of the same length n is approximately linear in terms of n and we were able to determine the prefactor of the linear term, which is a = (3 In 2)/(8) approximate to 0.2599. In the case of two random polygons of length n, the mean average inter-crossing number ICN is also linear, but the prefactor of the linear term is different from that of the random walks. These approximations apply when the starting points of the random walks and polygons are of a distance p apart and p is small compared to n. We propose a fitting model that would capture the theoretical asymptotic behaviour of the mean average ICN for large values of p. Our simulation result shows that the model in fact works very well for the entire range of p. We also study the mean ICN between two equilateral random walks and polygons of different lengths. An interesting result is that even if one random walk (polygon) has a fixed length, the mean average ICN between the two random walks (polygons) would still approach infinity if the length of the other random walk (polygon) approached infinity. The data provided by our simulations match our theoretical predictions very well.