Hydrogen evolution on nanostructured Ni-Cu foams

Three-dimensional (3D) nickel-copper (Ni-Cu) nanostructured foams were prepared by galvanostatic electrodeposition, on stainless steel substrates, using the dynamic hydrogen bubble template. These foams were tested as electrodes for the hydrogen evolution reaction (HER) in 8 M KOH solutions. Polarisation curves were obtained for the Ni-Cu foams and for a solid Ni electrode, in the 25-85 degrees C temperature range, and the main kinetic parameters were determined. It was observed that the 3D foams have higher catalytic activity than pure Ni. HER activation energies for the Ni-Cu foams were lower (34-36 kJ mol(-1)) than those calculated for the Ni electrode (62 kJ mol(-1)). The foams also presented high stability for HER, which makes them potentially attractive cathode materials for application in industrial alkaline electrolysers.

Time-domain optimization of amplifiers based on distributed genetic algorithms

Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering

Step count algorithm adapted to indoor localization

This paper presents a step count algorithm designed to work in real-time using low computational power. This proposal is our first step for the development of an indoor navigation system, based on Pedestrian Dead Reckoning (PDR). We present two approaches to solve this problem and compare them based in their error on step counting, as well as, the capability of their use in a real time system.

Traveled Distance Estimation Algorithm for Indoor Localization

This paper presents an ankle mounted Inertial Navigation System (INS) used to estimate the distance traveled by a pedestrian. This distance is estimated by the number of steps given by the user. The proposed method is based on force sensors to enhance the results obtained from an INS. Experimental results have shown that, depending on the step frequency, the traveled distance error varies between 2.7% and 5.6%.

The insular shelves of the Faial-Pico Ridge (Azores archipelago): a morphological record of its evolution

Shelves surrounding reefless volcanic ocean islands are formed by surf erosion of their slopes during changing sea levels. Posterosional lava flows, if abundant, can cross the coastal cliffs and fill partially or completely the accommodation space left by erosion. In this study, multibeam bathymetry, high-resolution seismic reflection profiles, and sediment samples are used to characterize the morphology of the insular shelves adjacent to Pico Island. The data show offshore fresh lava flow morphologies, as well as an irregular basement beneath shelf sedimentary bodies and reduced shelf width adjacent to older volcanic edifices in Pico. These observations suggest that these shelves have been significantly filled by volcanic progradation and can thus be classified as rejuvenated. Despite the general volcanic infilling of the shelves around Pico, most of their edges are below the depth of the Last Glacial Maximum, revealing that at least parts of the island have subsided after the shelves formed by surf erosion. Prograding lava deltas reached the shelf edge in some areas triggering small slope failures, locally decreasing the shelf width and depth of their edges. These areas can represent a significant risk for the local population; hence, their identification can be useful for hazard assessment and contribute to wiser land use planning. Shelf and subaerial geomorphology, magnetic anomalies and crustal structure data of the two islands were also interpreted to reconstruct the long-term combined onshore and offshore evolution of the Faial-Pico ridge. The subaerial emergence of this ridge is apparently older than previously thought, i.e., before approximate to 850 ka.

Multiple sequence alignment correction using constraints

Trabalho apresentado no âmbito do European Master in Computational Logics, como requisito parcial para obtenção do grau de Mestre em Computational Logics

Evolution and biogenesis of microtubule-derived structures

Dissertação apresentada para obtenção do grau de Doutor em Biologia Celular pelo Instituto de Tecnologia Química e Biológica da Universidade Nova de Lisboa

Hyperspectral unmixing algorithm via dependent component analysis

This paper introduces a new method to blindly unmix hyperspectral data, termed dependent component analysis (DECA). This method decomposes a hyperspectral images into a collection of reflectance (or radiance) spectra of the materials present in the scene (endmember signatures) and the corresponding abundance fractions at each pixel. DECA assumes that each pixel is a linear mixture of the endmembers signatures weighted by the correspondent abundance fractions. These abudances are modeled as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. This method overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical based approaches. The effectiveness of the proposed method is illustrated using simulated data based on U.S.G.S. laboratory spectra and real hyperspectral data collected by the AVIRIS sensor over Cuprite, Nevada.

A lightweight distributed super peer election algorithm for unstructured dynamic P2P systems

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

One-step preparation of optically transparent Ni-Fe oxide film electrocatalyst for oxygen evolution reaction

Optically transparent cocatalyst film materials is very desirable for improved photoelectrochemical (PEC)oxygen evolution reaction (OER) over light harvesting photoelectrodes which require the exciting light to irradiate through the cocatalyst side, i.e., front-side illumination. In view of the reaction overpotential at electrode/electrolyte interface, the OER electrocatalysts have been extensively used as cocatalysts for PEC water oxidation on photoanode. In this work, the feasibility of a one-step fabrication of the transparent thin film catalyst for efficient electrochemical OER is investigated. The Ni-Fe bimetal oxide films, 200 nm in thickness, are used for study. Using a reactive magnetron co-sputtering technique, transparent(> 50% in wavelength range 500-2000 nm) Ni-Fe oxide films with high electrocatalytic activities were successfully prepared at room temperature. Upon optimization, the as-prepared bimetal oxide film with atomic ratio of Fe/Ni = 3:7 demonstrates the lowest overpotential for the OER in aqueous KOH solution, as low as 329 mV at current density of 2 mA cm 2, which is 135 and 108 mV lower than that of as-sputtered FeOx and NiOx thin films, respectively. It appears that this fabrication strategy is very promising to deposit optically transparent cocatalyst films on photoabsorbers for efficient PEC water splitting.

Domestic Consumption Simulation and Management Using a Continuous Consumption Management and Optimization Algorithm

The recent changes concerning the consumers’ active participation in the efficient management of load devices for one’s own interest and for the interest of the network operator, namely in the context of demand response, leads to the need for improved algorithms and tools. A continuous consumption optimization algorithm has been improved in order to better manage the shifted demand. It has been done in a simulation and user-interaction tool capable of being integrated in a multi-agent smart grid simulator already developed, and also capable of integrating several optimization algorithms to manage real and simulated loads. The case study of this paper enhances the advantages of the proposed algorithm and the benefits of using the developed simulation and user interaction tool.

A Learning Algorithm and System Approach to Address Exceptional Events in Domestic Consumption Management

The integration of the Smart Grid concept into the electric grid brings to the need for an active participation of small and medium players. This active participation can be achieved using decentralized decisions, in which the end consumer can manage loads regarding the Smart Grid needs. The management of loads must handle the users’ preferences, wills and needs. However, the users’ preferences, wills and needs can suffer changes when faced with exceptional events. This paper proposes the integration of exceptional events into the SCADA House Intelligent Management (SHIM) system developed by the authors, to handle machine learning issues in the domestic consumption context. An illustrative application and learning case study is provided in this paper.

Análise dinâmica de composições musicais

A composição musical é um tema de muito interesse para a computação evolucionária dentro da área da inteligência artificial. É uma área que tem sofrido vários desenvolvimentos ao longo dos últimos anos pois o interesse em que hajam computadores que façam obras musicais é deveras aliciante. Este trabalho tem por objectivo realizar mais um passo nesse sentido. Assim, foi desenvolvida uma aplicação informática que realiza composições musicais de dois géneros distintos: Músicas Infantis e Músicas Blues. A aplicação foi implementada com recurso aos Algoritmos Genéticos, que são os algoritmos evolucionários mais populares da área da computação evolucionária. O trabalho foi estruturado em duas fases de desenvolvimento. Na primeira fase, realizou-se um levantamento estatístico sobre as características específicas de cada um dos géneros musicais. Analisaram-se quinze músicas de cada género musical, com o intuito de se chegar a uma proporção do uso que cada nota tem em cada um dos casos. Na segunda fase, desenvolveu-se o software que compõe as músicas com implementação de um algoritmo genético. Além disso, foi também desenvolvida uma interface gráfica que permite ao utilizador a escolha do género musical que pretende compor. O algoritmo genético começa por gerar uma população inicial de potenciais soluções de acordo com a escolha do utilizador, realizando, de seguida, o ciclo que caracteriza o algoritmo genético. A população inicial é constituída por soluções que seguem as regras que foram implementadas de acordo com os dados recolhidos ao longo da primeira fase. Foi também implementada uma interface de avaliação, através da qual, o utilizador pode ouvir cada uma das músicas para posterior avaliação em termos de fitness. O estado de evolução do algoritmo é apresentado, numa segunda interface, a qual facilita a clareza e justiça na avaliação ao longo de todo o processo. Esta última apresenta informação sobre a média das fitness da geração anterior e actual, sendo assim possível ter uma noção da evolução do algoritmo, no sentido de se obterem resultados satisfatórios no que diz respeito às composições musicais.

Evolution of IgG antibody response against Toxoplasma gondii tissue cyst in acute and chronic human infections

The recognition profile of the tissue cysts antigens by IgG antibodies was studied during acute and chronic human toxoplasmic infection. Thus the IgG response against Toxoplasma gondii was investigated by immunoblotting in two patients accidentally infected with the RH strain as well as in group of naturally infected patients at acute and chronic phase. There was an overall coincidence of molecular mass among antigens of tachyzoites and tissue cysts recognized by these sera, however, they appear not to be the same molecules. The response against tissue cysts starts early during acute infection, and the reactivity of antibodies is strong against a wide range of antigens. Six bands (between 82 and 151 kDa) were exclusively recognized by chronic phase sera but only the 132 kDa band was positive in more than 50% of the sera analysed. A mixture of these antigens could be used to discriminate between the two infection phases. The most important antigens recognized by the acute and the chronic phase sera were 4 clusters in the ranges 20-24 kDa, 34-39 kDa, 58-80 kDa and 105-130 kDa as well as two additional antigens of 18 and 29 kDa. Both accidentally infected patients and some of the naturally infected patients showed a weak specific response against tissue cyst antigens.

Rapid Evolution of the Sequences and Gene Repertoires

Proteins secreted to the extracellular environment or to the periphery of the cell envelope, the secretome, play essential roles in foraging, antagonistic and mutualistic interactions. We hypothesize that arms races, genetic conflicts and varying selective pressures should lead to the rapid change of sequences and gene repertoires of the secretome. The analysis of 42 bacterial pan-genomes shows that secreted, and especially extracellular proteins, are predominantly encoded in the accessory genome, i.e. among genes not ubiquitous within the clade. Genes encoding outer membrane proteins might engage more frequently in intra-chromosomal gene conversion because they are more often in multi-genic families. The gene sequences encoding the secretome evolve faster than the rest of the genome and in particular at non-synonymous positions. Cell wall proteins in Firmicutes evolve particularly fast when compared with outer membrane proteins of Proteobacteria. Virulence factors are over-represented in the secretome, notably in outer membrane proteins, but cell localization explains more of the variance in substitution rates and gene repertoires than sequence homology to known virulence factors. Accordingly, the repertoires and sequences of the genes encoding the secretome change fast in the clades of obligatory and facultative pathogens and also in the clades of mutualists and free-living bacteria. Our study shows that cell localization shapes genome evolution. In agreement with our hypothesis, the repertoires and the sequences of genes encoding secreted proteins evolve fast. The particularly rapid change of extracellular proteins suggests that these public goods are key players in bacterial adaptation.