Influência da variabilidade dos materiais compósitos na resposta dinâmica de estruturas laminadas

Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Mecânica

Desenvolvimento de um Controlador de Boundary Scan (Ieee 1149.1)

Mestrado em Engenharia Electrotécnica e de Computadores - Área de Especialização em Automação e Sistemas

Avaliação e Otimização Energética das Fornalhas da Fábrica de Aromáticos

O consumo energético verificado nas refinarias petrolíferas é muito elevado, sendo as fornalhas os equipamentos que mais contribuem para esse consumo. Neste estudo foi efetuada uma avaliação e otimização energética às fornalhas da Fábrica de Aromáticos da Refinaria de Matosinhos. Numa primeira fase foi efetuado um levantamento exaustivo de dados de todas as correntes de entrada e saída dos equipamentos para posteriormente efetuar os balanços de massa e energia a cada uma das fornalhas. Os dados relativos ao levantamento compreenderam dois períodos de funcionamento distintos da unidade fabril, o período de funcionamento normal e o período relativo ao arranque. O período de funcionamento normal foi relativo ao ano de 2012 entre os meses de janeiro a setembro, por sua vez o período de arranque foi de dezembro de 2012 a março de 2013. Na segunda fase foram realizados os balanços de massa e energia quantificando todas as correntes de entrada e saída das fornalhas em termos mássicos e energéticos permitindo o cálculo do rendimento térmico das fornalhas para avaliar a sua performance. A avaliação energética permitiu concluir que existe um consumo maior de energia proveniente da combustão do Fuel Gás do que do Fuel Óleo, tanto no período de funcionamento normal como no arranque. As fornalhas H0101, H0301 e a H0471 possuem os consumos mais elevados, sendo responsáveis por mais de 70% do consumo da Fábrica de Aromáticos. Na terceira fase foram enunciadas duas medidas para a otimização energética das três fornalhas mais consumidoras de energia, a limpeza mensal e o uso exclusivo de Fuel Gás como combustível. As poupanças energéticas obtidas para uma limpeza mensal foram de 0,3% na fornalha H0101, 0,7% na fornalha H0301 e uma poupança de 0,9 % na fornalha H0471. Para o uso exclusivo de Fuel Gás obteve-se uma poupança de 0,9% na fornalha H0101 e uma poupança de 1,3% nas fornalhas H0301 e H0471. A análise económica efetuada à sugestão de alteração do combustível mostra que os custos de operação sofrerão um aumento anual de 621 679 €. Apesar do aumento dos custos, a redução na emissão de 24% de dióxido de carbono, poderá justificar este aumento na despesa.

Metalearner based on Dynamic Neural Network for Strategic Bidding in electricity Markets

The restructuring of electricity markets, conducted to increase the competition in this sector, and decrease the electricity prices, brought with it an enormous increase in the complexity of the considered mechanisms. The electricity market became a complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. Software tools became, therefore, essential to provide simulation and decision support capabilities, in order to potentiate the involved players’ actions. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotiation entities. The proposed metalearner executes a dynamic artificial neural network to create its own output, taking advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that provides decision support to electricity markets’ players. The proposed metalearner considers different weights for each strategy, depending on its individual quality of performance. The results of the proposed method are studied and analyzed in scenarios based on real electricity markets’ data, using MASCEM - a multi-agent electricity market simulator that simulates market players’ operation in the market.

DYNAMOD – A dynamic agent based modelling framework for digital businesses

Digital Businesses have become a major driver for economic growth and have seen an explosion of new startups. At the same time, it also includes mature enterprises that have become global giants in a relatively short period of time. Digital Businesses have unique characteristics that make the running and management of a Digital Business much different from traditional offline businesses. Digital businesses respond to online users who are highly interconnected and networked. This enables a rapid flow of word of mouth, at a pace far greater than ever envisioned when dealing with traditional products and services. The relatively low cost of incremental user addition has led to a variety of innovation in pricing of digital products, including various forms of free and freemium pricing models. This thesis explores the unique characteristics and complexities of Digital Businesses and its implications on the design of Digital Business Models and Revenue Models. The thesis proposes an Agent Based Modeling Framework that can be used to develop Simulation Models that simulate the complex dynamics of Digital Businesses and the user interactions between users of a digital product. Such Simulation models can be used for a variety of purposes such as simple forecasting, analysing the impact of market disturbances, analysing the impact of changes in pricing models and optimising the pricing for maximum revenue generation or a balance between growth in usage and revenue generation. These models can be developed for a mature enterprise with a large historical record of user growth rate as well as for early stage enterprises without much historical data. Through three case studies, the thesis demonstrates the applicability of the Framework and its potential applications.

Ontology-based representation and generation of workflows for micro-task human-machine computation

Doctoral Program in Computer Science

Flow updating: fault-tolerant aggregation for dynamic networks

Documento submetido para revisão pelos pares. A publicar em Journal of Parallel and Distributed Computing. ISSN 0743-7315

Cell-matrix interactions in Schistosomal portal fibrosis: a dynamic event

In recent years, one of the most significant progress in the understanding of liver diseases was the demonstration that liver fibrosis is a dynamic process resulting from a balance between synthesis and degradation of several matrix components, collagen in particular. Thus, fibrosis has been found to be a very early event during liver diseases, be it of toxic, viral or parasitic origin, and to be spontaneously reversible, either partially or totally. In liver fibrosis cell matrix interactions are dependent on the existence of the many factors (sometimes acting in combination) which produce the same events at the cellular and molecular levels. These events are: (i) the recruitment of fiber-producing cells, (ii) their proliferation, (iii) the secretion of matrix constituents of the extracellular matrix, and (iv) the remodeling and degradation of the newly formed matrix. All these events represent, at least in principle, a target for a therapeutic intervention aimed at influencing the experimentally induced hepatic fibrosis. In this context, hepatosplenic schistosomiasis is of particular interest, being an immune cell-mediated granulomatous disease and a model of liver fibrosis allowing extensive studies in human and animals as well as providing original in vitro models.

Straightening out the concept of direct and indirect input requirements

Gim & Kim (1998) proposed a generalization of Jeong (1982, 1984) reinterpretation of the Hawkins-Simon condition for macroeconomic stability to off-diagonal matrix elements. This generalization is conceptually relevant for it offers a complementary view of interindustry linkages beyond final or net output influence. The extension is completely similar to the 'total flow' idea introduced by Szyrmer (1992) or the 'output-to-output' multiplier of Miller & Blair (2009). However the practical implementation of Gim & Kim is actually faulty since it confuses the appropriate order of output normalization. We provide a new and elementary solution for the correct formalization using standard interindustry accounting concepts.

Dynamic arterial elastance to predict arterial pressure response to volume loading in preload-dependent patients

INTRODUCTION Hemodynamic resuscitation should be aimed at achieving not only adequate cardiac output but also sufficient mean arterial pressure (MAP) to guarantee adequate tissue perfusion pressure. Since the arterial pressure response to volume expansion (VE) depends on arterial tone, knowing whether a patient is preload-dependent provides only a partial solution to the problem. The objective of this study was to assess the ability of a functional evaluation of arterial tone by dynamic arterial elastance (Ea(dyn)), defined as the pulse pressure variation (PPV) to stroke volume variation (SVV) ratio, to predict the hemodynamic response in MAP to fluid administration in hypotensive, preload-dependent patients with acute circulatory failure. METHODS We performed a prospective clinical study in an adult medical/surgical intensive care unit in a tertiary care teaching hospital, including 25 patients with controlled mechanical ventilation who were monitored with the Vigileo(®) monitor, for whom the decision to give fluids was made because of the presence of acute circulatory failure, including arterial hypotension (MAP ≤65 mmHg or systolic arterial pressure <90 mmHg) and preserved preload responsiveness condition, defined as a SVV value ≥10%. RESULTS Before fluid infusion, Ea(dyn) was significantly different between MAP responders (MAP increase ≥15% after VE) and MAP nonresponders. VE-induced increases in MAP were strongly correlated with baseline Ea(dyn) (r(2) = 0.83; P < 0.0001). The only predictor of MAP increase was Ea(dyn) (area under the curve, 0.986 ± 0.02; 95% confidence interval (CI), 0.84-1). A baseline Ea(dyn) value >0.89 predicted a MAP increase after fluid administration with a sensitivity of 93.75% (95% CI, 69.8%-99.8%) and a specificity of 100% (95% CI, 66.4%-100%). CONCLUSIONS Functional assessment of arterial tone by Ea(dyn), measured as the PVV to SVV ratio, predicted arterial pressure response after volume loading in hypotensive, preload-dependent patients under controlled mechanical ventilation.

Uncertainty Quantification Of A Semi-Supervised Support Vector Regression Reservoir Model

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.

On the timing of balance of payments crises: Disaggregated information and interest rate policy

This paper proposes a dynamic framework to study the timing of balance of paymentscrises. The model incorporates two main ingredients: (i) investors have private information; (ii)investors interact in a dynamic setting, weighing the high returns on domestic assets against the incentives to pull out before the devaluation. The model shows that the presence of disaggregated information delays the onset of BOP crises, giving rise to discrete devaluations. It also shows that high interest rates can be eective in delaying and possibly avoiding the abandonment of the peg. The optimal policy is to raise interest rates sharply as fundamentals become very weak. However, this policy is time inconsistent, suggesting a role for commitment devices such as currency boards or IMF pressure.

Inflation and output dynamics with firm-owned capital

We model firm-owned capital in a stochastic dynamic New-Keynesian generalequilibrium model à la Calvo. We find that this structure impliesequilibrium dynamics which are quantitatively di¤erent from the onesassociated with a benchmark case where households accumulate capital andrent it to firms. Our findings therefore stress the importance ofmodeling an investment decision at the firm level in addition to ameaningful price setting decision. Along the way we argue that the problemof modeling firm-owned capital with Calvo price-setting has not been solvedin a correct way in the previous literature.

Mice carrying ubiquitin-specific protease 2 (Usp2) gene inactivation maintain normal sodium balance and blood pressure.

Ubiquitylation plays an important role in the control of Na⁺ homeostasis by the kidney. It is well established that the epithelial Na⁺ channel ENaC is regulated by the ubiquitin-protein ligase NEDD4-2, limiting ENaC cell surface expression and activity. Ubiquitylation can be reversed by the action of deubiquitylating enzymes (DUBs). One such DUB, USP2-45, was identified previously as an aldosterone-induced protein in the kidney and is also a circadian output gene. In heterologous expression systems, USP2-45 binds to ENaC, deubiquitylates it, and enhances channel density and activity at the cell surface. Because the role of USP2-45 in renal Na⁺ transport had not been studied in vivo, we investigated here the effect of Usp2 gene inactivation in this process. We demonstrate first that USP2-45 protein has a rhythmic expression with a peak at ZT12. Usp2-KO mice did not show any differences from wild-type littermates with respect to the diurnal control of Na⁺ or K⁺ urinary excretion and plasma levels either on a standard diet or after acute and chronic changes to low- and high-Na⁺ diets, respectively. Moreover, they had similar aldosterone levels on either a low- or high-Na⁺ diet. Blood pressure measurements using telemetry did not reveal variations compared with control mice. Usp2-KO mice did not display alterations in expression of genes involved in sodium homeostasis or the ubiquitin system, as evidenced by transcriptome analysis in the kidney. Our data suggest that USP2 does not play a primary role in the control of Na⁺ balance or blood pressure.

Towards a theory of the credit-risk balance sheet

This article designs what it calls a Credit-Risk Balance Sheet (the risk being that of default by customers), a tool which, in principle, can contribute to revealing, controlling and managing the bad debt risk arising from a company¿s commercial credit, whose amount can represent a significant proportion of both its current and total assets.To construct it, we start from the duality observed in any credit transaction of this nature, whose basic identity can be summed up as Credit = Risk. ¿Credit¿ is granted by a company to its customer, and can be ranked by quality (we suggest the credit scoring system) and ¿risk¿ can either be assumed (interiorised) by the company itself or transferred to third parties (exteriorised).What provides the approach that leads to us being able to talk with confidence of a real Credit-Risk Balance Sheet with its methodological robustness is that the dual vision of the credit transaction is not, as we demonstrate, merely a classificatory duality (a double risk-credit classification of reality) but rather a true causal relationship, that is, a risk-credit causal duality.Once said Credit-Risk Balance Sheet (which bears a certain structural similarity with the classic net asset balance sheet) has been built, and its methodological coherence demonstrated, its properties ¿static and dynamic¿ are studied.Analysis of the temporal evolution of the Credit-Risk Balance Sheet and of its applications will be the object of subsequent works.