Aproveitamento da energia das correntes marítimas

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica

Prevalência e vulnerabilidade à infecção pelo HIV de moradores de rua em São Paulo, SP

OBJETIVO: Analisar a prevalência e o perfil de vulnerabilidade ao HIV de moradores de rua. MÉTODOS: Estudo transversal com amostra não probabilística de 1.405 moradores de rua usuários de instituições de acolhimento de São Paulo, SP, de 2006 a 2007. Foi realizado teste anti-HIV e aplicado questionário estruturado. O perfil de vulnerabilidade foi analisado pela frequência do uso do preservativo, considerando mais vulneráveis os que referiram o uso nunca ou às vezes. Foram utilizadas regressões logística e multinomial para estimar as medidas de efeito e intervalos de 95% de confiança. RESULTADOS: Houve predominância do sexo masculino (85,6%), média de 40,9 anos, ter cursado o ensino fundamental (72,0%) e cor não branca (71,5%). A prática homo/bissexual foi referida por 15,7% e a parceria ocasional por 62,0%. O número médio de parcerias em um ano foi de 5,4 e mais da metade (55,7%) referiu uso de drogas na vida, dos quais 25,7% relataram uso frequente. No total, 39,6% mencionaram ter tido uma doença sexualmente transmissível e 38,3% relataram o uso do preservativo em todas as relações sexuais. A prevalência do HIV foi de 4,9% (17,4% dos quais apresentaram também sorologia positiva para sífilis). Pouco mais da metade (55,4%) tinha acesso a ações de prevenção. A maior prevalência do HIV esteve associada a ser mais jovem (OR 18 a 29 anos = 4,0 [IC95% 1,54;10,46]), história de doença sexualmente transmissível (OR = 3,3 [IC95% 1,87;5,73]); prática homossexual (OR = 3,0 [IC95% 1,28;6,92]) e à presença de sífilis (OR = 2,4 [IC95% 1,13;4,93]). O grupo de maior vulnerabilidade foi caracterizado por ser mulher, jovem, ter prática homossexual, número reduzido de parcerias, parceria fixa, uso de drogas e álcool e não ter acesso a ações de prevenção e apoio social. CONCLUSÕES: O impacto da epidemia entre moradores de rua é elevado, refletindo um ciclo que conjuga exclusão, vulnerabilidade social e acesso limitado à prevenção.

Tipificação de fundações de torres eólicas em parques industriais, para diversos tipos de solos

Dissertação para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Edificações

Identificação da combinação ótima das fontes de energia renovável de origem hídrica, eólica e fotovoltaica para a integração no sistema elétrico português

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

A general overview on hybrid and electric vehicles

The economical and environment impacts of fossil energies increased the interest for hybrid, battery and fuel-cell electric vehicles. Several demanding engineering challenges must be faced, motivated by different physical domains integration. This paper aims to present an overview on hybrid (HEV) and electric vehicles (EV) basic structures and features. In addition, it will try to point out some of the most relevant challenges to overcome for HEV and EV may be a solid option for the mobility issue. New developments in energy storage devices and energy management systems (EMS) are crucial to achieve this goal.

Reabilitação energética de um edifício de serviços

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Edificações

Análise e avaliação de riscos na actividade de manutenção de juntas de dilatação em obras de arte rodoviárias

Relatório de Estágio para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Edificações

Experimental study of proton induced nuclear reactions in 6,7 Li

This work presents the results of the experimental study of proton induced nuclear reactions in lithium, namely the 7Li(p,α) 4He, 6Li(p,α) 3He and 7Li(p,p)7Li reactions. The amount of 7Li and 6Li identified as primordial and observed in very old stars of the Milky Way galactic halo strongly deviates from the predictions of primordial nucleosynthesis and stellar evolution models which depend, among other factors, on the cross sections of reactions like 7Li(p,α) 4He and 6Li(p,α) 3He. These discrepancies have triggered a large amount of research in the fields of stellar evolution, cosmology, pre-galactic evolution and low energy nuclear reactions. Focusing on nuclear reactions, this work has measured the 7Li(p,α) 4He and 6Li(p,α) 3He reactions cross sections (expressed in terms of the astrophysical S -factor) with higher accuracy, and the electron screening effects in these reactions for different environments (insulators and metallic targets). The 7Li(p,α) 4He angular distributions were also measured. These measurementstook place in two laboratory facilities, in the framework of the LUNA (Laboratory for Undergroud Nuclear Astrophysics) international collaboration, namely the Laboratorio ´ de Feixe de Ioes ˜ in ITN (Instituto Tecnologico ´ e Nuclear) Sacavem, ´ Portugal, and the Dynamitron-TandemLaboratorium in Ruhr-Universitat¨ Bochum, Germany. The ITN target chamber was modified to measure these nuclear reactions, with the design and construction of new components, the addition of one turbomolecular pump and a cold finger. The 7Li(p,α) 4He and 6Li(p,α) 3He reactions were measured concurrently with seven and four targets, respectively. These targets were produced in order to obtain adequate and stable lithium depth profiles. In metallic environments, the measured electron screening potential energies are much higher than the predictions of atomic-physics models. The Debye screening model applied to the metallic conduction electrons is able to explain these high values. It is a simple model, but also very robust. Concerning primordial nucleosynthesis and stellar evolution models, these results are very important as they show that laboratory measurements are well controlled, and the model inputs from these cross sections are therefore correct. In this work the 7Li(p,p)7Li differential cross section was also measured, which is useful to describe the 7Li(p,α) 4He entrance channel.

Technical and economic assessment of energy from Tidal Currents

The present work aims to study the feasibility of deploying a farm of sea current turbines for electricity generation in Portugal. An approach to the tides, which are they, how they are formed, its prediction, is held. It is also conducted a study about the energy of sea currents and it is presented some technology about ocean currents too. A model of tidal height and velocity of the currents it is also developed. The energy produced by a hypothetical park, built in Sines (Portugal), is calculated and afterwards, an economical assessment is performed for two possible scenarios and a sensitivity analysis of NVP (Net Present Value) and LCOE (Levelized Cost of Energy) is figured. The conclusions about the feasibility of the projects are also presented. Despite being desired due to its predictability, this energy source is not yet economically viable as it is in an initial state of development. To push investment in this technology a feed-in tariff of, at least €200/MWh, should be considered.

Renewable energy in Islands: an integrated proposal for electricity generation and transports

The purpose of this article is to analyse and evaluate the economical, energetic and environmental impacts of the increasing penetration of renewable energies and electrical vehicles in isolated systems, such as Terceira Island in Azores and Madeira Island. Given the fact that the islands are extremely dependent on the importation of fossil fuels - not only for the production of energy, but also for the transportation’s sector – it’s intended to analyse how it is possible to reduce that dependency and determine the resultant reduction of pollutant gas emissions. Different settings have been analysed - with and without the penetration of EVs. The Terceira Island is an interesting case study, where EVs charging during off-peak hours could allow an increase in geothermal power, limited by the valley of power demand. The percentage of renewable energy in the electric power mix could reach the 74% in 2030 while at the same time, it is possible to reduce the emissions of pollutant gases in 45% and the purchase of fossil fuels in 44%. In Madeira, apart from wind, solar and small hydro power, there are not so many endogenous resources and the Island’s emission factor cannot be so reduced as in Terceira. Although, it is possible to reduce fossil fuels imports and emissions in 1.8% in 2030 when compared with a BAU scenario with a 14% of the LD fleet composed by EVs.

Renewable energy in Islands: an integrated proposal for electricity generation and transports

The purpose of this article is to analyse and evaluate the economical, energetic and environmental impacts of the increasing penetration of renewable energies and electrical vehicles in isolated systems, such as Terceira Island in Azores and Madeira Island. Given the fact that the islands are extremely dependent on the importation of fossil fuels - not only for the production of energy, but also for the transportation’s sector – it’s intended to analyse how it is possible to reduce that dependency and determine the resultant reduction of pollutant gas emissions. Different settings have been analysed - with and without the penetration of EVs. The Terceira Island is an interesting case study, where EVs charging during off-peak hours could allow an increase in geothermal power, limited by the valley of power demand. The percentage of renewable energy in the electric power mix could reach the 74% in 2030 while at the same time, it is possible to reduce the emissions of pollutant gases in 45% and the purchase of fossil fuels in 44%. In Madeira, apart from wind, solar and small hydro power, there are not so many endogenous resources and the Island’s emission factor cannot be so reduced as in Terceira. Although, it is possible to reduce fossil fuels imports and emissions in 1.8% in 2030 when compared with a BAU scenario with a 14% of the LD fleet composed by EVs.

Zinc-substituted desulfovibrio gigas desulforedoxins

Protein Science (2002), 11:2464–2470

Adolescência, comportamento sexual e fatores de risco à saúde

OBJETIVO : Analisar a relação entre comportamento sexual e fatores de risco à saúde física ou mental entre adolescentes. MÉTODOS : Estudo realizado com 3.195 escolares de 15 a 19 anos de idade, do segundo ano do ensino médio de escolas públicas e particulares das capitais de 10 estados do Brasil, em 2007-2008. Foi utilizada amostragem por conglomerados com multiestágio de seleção (escolas e alunos) em cada cidade e rede de ensino pública e particular. Foi aplicado questionário a todos os alunos selecionados, com os seguintes itens: dados socioeconômicos e demográficos; comportamento sexual; “transar” com pessoas do mesmo sexo, do sexo oposto ou de ambos os sexos; uso de bebida alcoólica e maconha; usar camisinha ao “transar”; presença de experiências sexuais traumáticas na infância ou adolescência; e ideação suicida. A análise incluiu descrição de frequências, teste de Qui-quadrado, análise de correspondência múltipla e de cluster. Foram analisadas qualitativamente, por análise dos conteúdos manifestos, as respostas a uma questão livre em que o adolescente expressou comentários gerais sobre si e sua vida. RESULTADOS : Cerca de 3,0% dos adolescentes referiu comportamento homossexual ou bissexual, sem diferenciação de sexo, idade, cor da pele, estrato social, estrutura familiar e rede de ensino. Adolescentes com comportamento homo/bissexual comparados aos heterossexuais relataram (p < 0,05): ficar de “porre” (18,7% e 10,5%, respectivamente), uso frequente de maconha (6,1% e 2,1%, respectivamente), ideação suicida (42,5% e 18,7%, respectivamente) e ter sido vítima de violência sexual (11,7% e 1,5%; respectivamente). Adolescentes com comportamento homo/bissexual relataram utilizar menos preservativo de forma frequente (74,2%) do que aqueles com comportamento heterossexual (48,6%, p < 0,001). Três grupos foram encontrados na análise de correspondência: composto por adolescentes com comportamento homo/bissexual e que vivenciava os fatores de risco: sofrer violência sexual, nunca utilizar camisinha ao “transar”, ideação suicida, uso frequente de maconha; composto por usuários ocasionais de maconha e camisinha e com frequentes “porres”; adolescentes com comportamento heterossexual e ausência dos fatores de risco investigados. Entre adolescentes com comportamento homo e bissexual, houve mais fatores de risco quando comparados àqueles com comportamento heterossexual. Os adolescentes com comportamento homo e bissexual expuseram mais suas vivências pessoais positivas e relacionamentos negativos do que seus pares heterossexuais, mas se expressaram menos sobre religiosidade. CONCLUSÕES : O tema não somente deve ser mais estudado como também devem ser ampliadas as ações preventivas voltadas aos adolescentes com relações afetivo-sexuais homo/bissexuais.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Renewable Power Sources

Of all of the sources of renewable energies available one can argue that the most abundant and accessible are solar power, radiation, and the energy of the tides (70 % of the earth surface is covered by water). The tidal wave energy hasn’t seen a widespread distribution yet, mainly due to the lack of interest of the governments, most of the coastal areas of the world are exclusive responsibility of the governments, thus not easily open for private venture. Considering solar power, there exist two main fields of application, land based systems and space based systems. The former systems are still in a very embryonic phase, with Japan being the lead researcher in the field, with an experimental satellite-power station to be launched before 2010. Land based systems, on the other hand, are well studied, with major research and application programs in all known forms of solar power production. Given a minimum value of incident radiation, and applying the appropriate system, (i.e. power plant type), for any given area the solar power becomes an income-producing industry.