Economic Instruments and Regulatory Approaches in Implementing Riparian Revegetation Options: Observations of the Queensland System

Riparian vegetation can be an effective measure for preventing degradation of streambanks and riparian areas. However, riparian revegetation imposes large costs on landholders associated with tree establishment and removal of land from cropping, while providing benefits to downstream landholders, fishers, the local community and environmentalists. Appropriate policy instruments are required to promote sustainable and balanced use of riparian zones. This article analyses the capacity of existing legislation and other instruments to promote restoration of degraded riparian zones on private land. The role of legislation. economic instruments, community engagement and extension programs, in persuading landholders to revegetate riparian areas and improve riparian vegetation cover; is examined in the context ofa small degraded catchment in an intensive farming area in tropical north Queensland. It is found that while legislation and regulations can control undesirable modification of riparian areas, in general they are unable to make a useful contribution to restoration of these areas; incentives and assistance measures appear to offer greater potential.

Absorption and dispersion by a multiple driven two-level atom

We investigate the absorption and dispersion properties of a two-level atom driven by a polychromatic field. The driving field is composed of a strong resonant (carrier) frequency component and a large number of symmetrically detuned sideband fields (modulators). A rapid increase in the absorption at the central frequency and the collapse of the response of the system from multiple frequencies to a single frequency are predicted to occur when the Rabi frequency of the modulating fields is equal to the Rabi frequency of the carrier field. These are manifestations of the undressing or a disentanglement of the atomic and driving field states, that leads to a collapse of the atom to its ground state. Our calculation permits consideration of the question of the undressing of the driven atom by a multiple-modulated field and the predicted spectra offer a method of observing undressing. Moreover, we find that the absorption and dispersion spectra split into multiplets whose structures depend on the Rabi frequency of the modulating fields. The spectral features can jump between different resonance frequencies by changing the Rabi frequency of the modulating fields or their initial phases, which can have potential applications as a quantum frequency filter.

On measuring quality of a probabilistic commodity forecast for a system that incorporates seasonal climate forecasts

Regional commodity forecasts are being used increasingly in agricultural industries to enhance their risk management and decision-making processes. These commodity forecasts are probabilistic in nature and are often integrated with a seasonal climate forecast system. The climate forecast system is based on a subset of analogue years drawn from the full climatological distribution. In this study we sought to measure forecast quality for such an integrated system. We investigated the quality of a commodity (i.e. wheat and sugar) forecast based on a subset of analogue years in relation to a standard reference forecast based on the full climatological set. We derived three key dimensions of forecast quality for such probabilistic forecasts: reliability, distribution shift, and change in dispersion. A measure of reliability was required to ensure no bias in the forecast distribution. This was assessed via the slope of the reliability plot, which was derived from examination of probability levels of forecasts and associated frequencies of realizations. The other two dimensions related to changes in features of the forecast distribution relative to the reference distribution. The relationship of 13 published accuracy/skill measures to these dimensions of forecast quality was assessed using principal component analysis in case studies of commodity forecasting using seasonal climate forecasting for the wheat and sugar industries in Australia. There were two orthogonal dimensions of forecast quality: one associated with distribution shift relative to the reference distribution and the other associated with relative distribution dispersion. Although the conventional quality measures aligned with these dimensions, none measured both adequately. We conclude that a multi-dimensional approach to assessment of forecast quality is required and that simple measures of reliability, distribution shift, and change in dispersion provide a means for such assessment. The analysis presented was also relevant to measuring quality of probabilistic seasonal climate forecasting systems. The importance of retaining a focus on the probabilistic nature of the forecast and avoiding simplifying, but erroneous, distortions was discussed in relation to applying this new forecast quality assessment paradigm to seasonal climate forecasts. Copyright (K) 2003 Royal Meteorological Society.

A proposal for media component brokerage

This paper describes how MPEG-4 object based video (obv) can be used to allow selected objects to be inserted into the play-out stream to a specific user based on a profile derived for that user. The application scenario described here is for personalized product placement, and considers the value of this application in the current and evolving commercial media distribution market given the huge emphasis media distributors are currently placing on targeted advertising. This level of application of video content requires a sophisticated content description and metadata system (e.g., MPEG-7). The scenario considers the requirement for global libraries to provide the objects to be inserted into the streams. The paper then considers the commercial trading of objects between the libraries, video service providers, advertising agencies and other parties involved in the service. Consequently a brokerage of video objects is proposed based on negotiation and trading using intelligent agents representing the various parties. The proposed Media Brokerage Platform is a multi-agent system structured in two layers. In the top layer, there is a collection of coarse grain agents representing the real world players – the providers and deliverers of media contents and the market regulator profiler – and, in the bottom layer, there is a set of finer grain agents constituting the marketplace – the delegate agents and the market agent. For knowledge representation (domain, strategic and negotiation protocols) we propose a Semantic Web approach based on ontologies. The media components contents should be represented in MPEG-7 and the metadata describing the objects to be traded should follow a specific ontology. The top layer content providers and deliverers are modelled by intelligent autonomous agents that express their will to transact – buy or sell – media components by registering at a service registry. The market regulator profiler creates, according to the selected profile, a market agent, which, in turn, checks the service registry for potential trading partners for a given component and invites them for the marketplace. The subsequent negotiation and actual transaction is performed by delegate agents in accordance with their profiles and the predefined rules of the market.

Simulation of offshore wind system with two-level converters: HVDC power transmission

A new integrated mathematical model for the simulation of offshore wind energy conversion system performance is presented in this paper. The mathematical model considers an offshore variable-speed turbine in deep water equipped with a permanent magnet synchronous generator using full-power two-level converter, converting the energy of a variable frequency source in injected energy into the electric network with constant frequency, through a high voltage DC transmission submarine cable. The mathematical model for the drive train is a concentrate two mass model which incorporates the dynamic for the structure and tower due to the need to emulate the effects of the moving surface. Controller strategy considered is a proportional integral one. Also, pulse width modulation using space vector modulation supplemented with sliding mode is used for trigger the transistor of the converter. Finally, a case study is presented to access the system performance. © 2014 IEEE.

A preliminary idea for an 8-competitive, log2 DMAX + log2 log2 1/U asymptotic-space, interface generation algorithm for two-level hierarchical scheduling of constrained-deadline sporadic tasks on a uniprocessor

Consider a single processor and a software system. The software system comprises components and interfaces where each component has an associated interface and each component comprises a set of constrained-deadline sporadic tasks. A scheduling algorithm (called global scheduler) determines at each instant which component is active. The active component uses another scheduling algorithm (called local scheduler) to determine which task is selected for execution on the processor. The interface of a component makes certain information about a component visible to other components; the interfaces of all components are used for schedulability analysis. We address the problem of generating an interface for a component based on the tasks inside the component. We desire to (i) incur only a small loss in schedulability analysis due to the interface and (ii) ensure that the amount of space (counted in bits) of the interface is small; this is because such an interface hides as much details of the component as possible. We present an algorithm for generating such an interface.

Simulation of offshore wind system with two levels converters: HVDC power transmission

A new integrated mathematical model for the simulation of offshore wind energy conversion system performance is presented in this paper. The mathematical model considers an offshore variable-speed turbine in deep water equipped with a permanent magnet synchronous generator using full-power two-level converter, converting the energy of a variable frequency source in injected energy into the electric network with constant frequency, through a high voltage DC transmission submarine cable. The mathematical model for the drive train is a concentrate two mass model which incorporates the dynamic for the structure and tower due to the need to emulate the effects of the moving surface. Controller strategy considered is a proportional integral one. Also, pulse width modulation using space vector modulation supplemented with sliding mode is used for trigger the transistor of the converter. Finally, a case study is presented to access the system performance. © 2014 IEEE.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Terapêuticas antigénio-especificas no tratamento das doenças desmielinizantes: estudos sobre a vacinação com ADN e a descoberta de um novo alvo antigénico

RESUMO A Esclerose Múltipla (EM) é uma doença desmielinizante crónica do Sistema Nervoso Central (SNC), provocada, em grande parte, por um ataque imuno-mediado contra diversos elementos da bainha de mielina. Dentro dos alvos antigénicos desta resposta autoimune, vários componentes proteicos e lipídicos da mielina têm vindo a ser identificados ao longo dos anos, entre os quais se destacam a proteína básica de mielina(MBP), glicoproteína ligodendrocitária da mielina (MOG), proteína proteolipídica (PLP) e glicoproteína associada à mielina (MAG). Com o desenvolvimento do modelo animal de Encefalomielite Autoimune Experimental (EAE), diversas terapias antigénio-específicas foram desenhadas, baseadas na modificação benéfica da resposta autoimune contra a mielina, tais como a administração de mielina ou seus componentes, os copolímeros terapêuticos, os ligandos peptídeos alterados e, recentemente, a vacinação com ácido desoxirribonucleico (ADN) codificador de proteínas de mielina, integrado em plasmídeos e purificado para administração parentérica. Neste trabalho, apresentamos os resultados de um extenso conjunto de experiências, subordinadas a dois temas fundamentais: 1) avaliação do potencial terapêutico, e dos mecanismos de acção, da vacinação tolerizadora com ADN codificador de proteínas de mielina (MBP, MOG, PLP, MAG) na EAE, e da associação desta vacinação com a administração de ADN de citocinas Th2, ou de oligonucleótidos imunomoduladores; 2) identificação e caracterização da resposta imune contra um novo componente da mielina com potencial antigénico, a proteína inibidora do recrescimento axonal, Nogo-A. No que respeita à vacinação com ADN, os nossos resultados comprovam a eficácia desta terapêutica antigénio-específica na prevenção e tratamento da EAE. Os seus mecanismos de acção incluem, entre outros, a supressão anérgica da proliferação antigénioespecífica dos linfócitos T anti-mielina (no modo de prevenção da doença), o enviesamento Th2 da resposta imune (quando co-administrada com a vacina de ADN codificadora da citocina IL-4, funcionando como terapia génica local), e a redução da diversificação de epítopos da resposta humoral anti-mielina, avaliada através de myelin spotted arrays. A associação das vacinas de ADN com oligonucleótidos imunomoduladores GpG, desenvolvidos para contrariar as sequências CpG imunoestimuladoras presentes no vector de vacinação, levou à melhoria da sua eficácia terapêutica, devida, provavelmente, ao efeito estimulador preferencial dos oligonucleótidos GpG sobre linfócitos Th2 e sobre células reguladoras NK-T. Com base nestes resultados a vacinação com ADN foi desenvolvida para o tratamento da EM em humanos, com ensaios clínicos a decorrerem neste momento. Em relação à proteína Nogo-A, estudos de estrutura primária e de previsão de antigenicidade identificaram a região Nogo-66 como alvo antigénico potencial para a EAE. Nas estirpes de ratinho SJL/J e C57BL/6, fomos capazes de induzir sinais clínicos e histológicos de EAE após imunização com os epítopos encefalitogénicos Nogo1-22, Nogo23- 44 e Nogo45-66, utilizando protocolos de quebra de tolerância imune. Ao mesmo tempo, identificámos e caracterizámos uma resposta linfocitária T específica contra os antigénios contidos na região Nogo-66, e uma resposta linfocitária B com diversificação intra e intermolecular a vários determinantes presentes noutras proteínas da mielina. A transferência adoptiva de linhas celulares Th2 anti-Nogo45-66, levou à melhoria clínica e histológica da EAE em animais recipientes induzidos com outros antigénios de mielina, após migração destas células para o SNC. Estes dados comprovam a importância da Nogo-66 como antigénio na EAE, e a eficácia de terapias antigénio-específicas nela baseadas. No seu conjunto, os nossos resultados confirmam o potencial terapêutico das vacinas de ADN codificadoras de proteínas de mielina, bem como a importância dos encefalitogénios contidos na proteína Nogo-A para a fisiopatologia da EAE e da EM, com eventual relevância para o desenvolvimento de novas terapias antigénio-específicas. O aperfeiçoamento futuro destas terapias poderá levar, eventualmente, a uma capacidade de manipulação da resposta imune que permita o tratamento eficaz das doenças inflamatórias desmielinizantes, como a Esclerose Múltipla. ABSTRACT Multiple Sclerosis (MS) is a chronic demyelinating disease of the Central Nervous System (CNS), caused, mainly, by an immune-mediated attack against several elements of the myelin sheath. Among the antigenic targets for this autoimmune response, several proteic and lipidic myelin components have been identified throughout the years, of which myelin basic protein (MBP), myelin oligodendrocyte glycoprotein (MOG), proteolipidic protein (PLP), and myelin associated glycoprotein (MAG) are the best characterized. With the development of the animal model for MS, Experimental Autoimmune Encephalomyelitis (EAE), several antigen-specific therapies have been designed, based on beneficial modifications of the autoimmune response against myelin. These have included myelin and myelin component administration, therapeutic copolymers, altered peptide ligands and, more recently, vaccination with myelin-protein encoding deoxyribonucleic acid (DNA), integrated into plasmids and purified for parenteral administration. In this work we present the results of an extensive series of experiments, subordinate to two fundamental areas: 1) evaluating the therapeutic potential, and mechanisms of action, of tolerizing myelin protein (MBP, MOG, PLP, MAG) DNA vaccination in EAE, alone and in association with Th2 cytokine DNA administration, or immunomodulatory oligonucleotides; 2) identifying and characterizing the immuneresponse against a new myelin component with antigenic potential, the axonal regrowth inhibitor Nogo-A. Regarding DNA vaccination, our results prove the efficacy of this antigen-specific therapy for the prevention and treatment of EAE. Its mechanisms of action include, among others, anergic suppression of antigen-specific T-cell proliferation against myelin (in prevention mode), Th2 biasing of the immune response (when co-administered with the IL- 4 codifying DNA vaccine, acting as local gene therapy), and reduction of epitope spreading of the anti-myelin antibody response, assessed by myelin spotted arrays. The combination of myelin DNA vaccination with the administration of GpG immunomodulatory oligonucleotides, designed to counteract immunostimulatory CpG motifs present in the vaccination vector, led to an improvement in therapeutic efficacy, probably due to the preferential stimulatory effect of GpG oligonucleotides on Th2 lymphocytes and on regulatory NK-T cells. Based on these results, tolerizing DNA vaccination is being developed for human use, with ongoing clinical trials. As concerns the Nogo-A protein, based on studies of primary structure and prediction of antigenicity, we identified the Nogo-66 region (responsible for the most of the inhibitory capacity of this protein) as a potential antigenic target for EAE. In the SJL/Jand C57BL/6 mouse strains, we were able to induce clinical and histological signs of EAE,after immunization with the encefalitogenic epitopes Nogo1-22, Nogo23-44 and Nogo45-66,using a tolerance breakdown protocol. Concomitantly, we identified and characterized a specific T cell response against these antigens, together with a B cell response which showed extensive intra and intermolecular epitope spread to several determinants present in other myelin proteins. Adoptive transfer of nti-Nogo45-66 Th2 cell lines resulted in clinical and histological improvement of EAE in recipient animals induced with other myelin antigens, after intraparenchymal CNS migration of anti-Nogo cells. These data confirm the relevance of Nogo-66 as an antigen in EAE, as well as the efficacy of antigenspecific therapies based on the response against this protein.In conclusion, our results substantiate the therapeutic potential of myelin-encoding DNA vaccination, as well as the importance of encefalitogenic epitopes present in the Nogo-A protein for the pathophysiology of EAE and MS, with potential relevance for the creation of new antigen specific-therapies. The future development of these therapies may eventually lead to a degree of manipulation of the immune response that allows the effective treatment of autoimmune, inflammatory, demyelinating diseases, such as Multiple Sclerosis.

Environmental/Regatta Buoy: Sensing System

Um dos principais objetivos da ciência é perceber a natureza, i.e., descobrir e explicar o funcionamento do mundo que nos rodeia. Para tal, os cientistas precisam de coligir dados e monitorar o meio ambiente. Em particular, considerando que cerca de 70% da Terra é coberta por água, a coleta de parâmetros de caracterização da água de grandes superfícies é uma prioridade. A monitorização das condições da água é feita principalmente através de bóias. No entanto, as bóias disponíveis no mercado não satisfazem as necessidades existentes. Esta é uma das principais razões que levaram o Laboratório de Sistemas Autónomos (LSA) do Instituto Superior de Engenharia do Porto a lançarem um projeto para o desenvolvimento de uma bóia reconfigurável e com dois modos de funcionamento: monitorização ambiental e baliza ativa de regata. O segundo modo é destinado a regatas de veleiros autónomos. O projeto começou há um ano com um projeto do European Project Project [1] (EPS), realizado por quatro estudantes internacionais, destinado à construção da estrutura da bóia e à selecção dos componentes mais adequados para o sistema de medição e controlo. A arquitetura que foi definida para este sistema é do tipo mestre-escravo e é composta por uma unidade de controlo mestre para a telemetria e configuração e uma unidade de controlo escrava para a medição e armazenamento de dados. O desenvolvimento do projeto continuou com dois estudantes belgas que trabalharam na comunicação e no armazenamento de dados. Este projeto, que prossegue com o desenvolvimento da medição e do armazenamento de dados do lado da unidade de controlo escrava, tem os seguintes objetivos: (i ) implementar o protocolo de comunicação na unidade de controlo escrava; (ii ) coligir e armazenar os dados dos sensores no cartão SD em tempo real; (iii ) fornecer dados em tempo útil; e (iv) recuperar dados do cartão SD em tempo diferido. As contribuições anteriores foram estudadas e foi feito um levantamento dos projetos congéneres existentes. O desenvolvimento do projeto atual começou com o protocolo de comunicação. Este protocolo, que foi projetado pelos alunos anteriores, foi um bom ponto de partida. No entanto, o protocolo foi atualizado e melhorado com novas funcionalidades. Esta última componente foi um trabalho conjunto com Laurens Allart, que esteve a trabalhar no subsistema de telemetria e de configuração durante este semestre. O protocolo foi implementado do lado da unidade de controlo escrava através de uma estrutura de múltiplas actividades paralelas (multithreaded). Esta estrutura recebe as mensagens da unidade mestre, executa as ações solicitadas e envia de volta o resultado. A bóia é um dispositivo reconfigurável multimodo que pode ser expandido com novos modos de operação no futuro. Infelizmente, sofre de algumas limitações: suporta uma carga máxima de 40 kg e tem uma área de implantação limitada pela distância máxima à estacão base.

On-line system for faults detection in induction motors based on PCA

Dissertation to obtain the degree of Master in Electrical and Computer Engineering

The impact of banks dimension on profitability, sustainability and efficiency: An analysis for the Iberian financial system

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Toxocariasis of the central nervous system: with report of two cases

Clinical involvement of the nervous system in visceral larva migrans due to Toxocara is rare, although in experimental animals the larvae frequently migrate to the brain. A review of the literature from the early 50's to date found 29 cases of brain involvement in toxocariasis. In 20 cases, various clinical and laboratory manifestations of eosinophilic meningitis, encephalitis, myelitis or radiculopathy were reported. We report two children with neurological manifestations, in which there was cerebrospinal fluid pleocytosis with marked eosinophilia and a positive serology for Toxocara both in serum and CSF. Serology for Schistosoma mansoni, Cysticercus cellulosae, Toxoplasma and cytomegalovirus were negative in CSF, that was sterile in both cases. Improvement of signs and symptoms after specific treatment (albendazole or thiabendazole) was observed in the two cases. A summary of data described in the 25 cases previously reported is presented and we conclude that in cases of encephalitis and myelitis with cerebrospinal fluid pleocytosis and eosinophilia, parasitic infection of the central nervous system should be suspected and serology should be performed to establish the correct diagnosis and treatment.

Using an LED as a sensor and visible light communication device in a smart illumination system

The need for more efficient illumination systems has led to the proliferation of Solid-State Lighting (SSL) systems, which offer optimized power consumption. SSL systems are comprised of LED devices which are intrinsically fast devices and permit very fast light modulation. This, along with the congestion of the radio frequency spectrum has paved the path for the emergence of Visible Light Communication (VLC) systems. VLC uses free space to convey information by using light modulation. Notwithstanding, as VLC systems proliferate and cost competitiveness ensues, there are two important aspects to be considered. State-of-the-art VLC implementations use power demanding PAs, and thus it is important to investigate if regular, existent Switched-Mode Power Supply (SMPS) circuits can be adapted for VLC use. A 28 W buck regulator was implemented using a off-the-shelf LED Driver integrated circuit, using both series and parallel dimming techniques. Results show that optical clock frequencies up to 500 kHz are achievable without any major modification besides adequate component sizing. The use of an LED as a sensor was investigated, in a short-range, low-data-rate perspective. Results show successful communication in an LED-to-LED configuration, with enhanced range when using LED strings as sensors. Besides, LEDs present spectral selective sensitivity, which makes them good contenders for a multi-colour LED-to-LED system, such as in the use of RGB displays and lamps. Ultimately, the present work shows evidence that LEDs can be used as a dual-purpose device, enabling not only illumination, but also bi-directional data communication.