Divulgação de informação voluntária : análise empírica às empresas do PSI-20

Mestrado em Contabilidade e Análise Financeira

A transparência fiscal

Mestrado em Fiscalidade

Direct electrochemistry of the Desulfovibrio gigas aldehyde oxidoreductase

Eur. J. Biochem. 271, 1329–1338 (2004)

Electrochemical studies on small electron transfer proteins using membrane electrodes

Journal of Electroanalytical Chemistry 541 (2003) 153-162

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.

Design and implementation of a behaviorally typed programming system for web services

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática.

Efficient middleware for database replication

Dissertação de Mestrado em Engenharia Informática

Experimental Study And Evaluation Of Paper-Based Inkjet Electrodes For ECG Signal Acquisition

Applications involving biosignals, such as Electrocardiography (ECG), are becoming more pervasive with the extension towards non-intrusive scenarios helping targeting ambulatory healthcare monitoring, emotion assessment, among many others. In this study we introduce a new type of silver/silver chloride (Ag/AgCl) electrodes based on a paper substrate and produced using an inkjet printing technique. This type of electrodes can increase the potential applications of biosignal acquisition technologies for everyday life use, given that there are several advantages, such as cost reduction and easier recycling, resultant from the approach explored in our work. We performed a comparison study to assess the quality of this new electrode type, in which ECG data was collected with three types of Ag/AgCl electrodes: i) gelled; ii) dry iii) paper-based inkjet printed. We also compared the performance of each electrode when acquired using a professional-grade gold standard device, and a low cost platform. Experimental results showed that data acquired using our proposed inkjet printed electrode is highly correlated with data obtained through conventional electrodes. Moreover, the electrodes are robust to high-end and low-end data acquisition devices. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.

Lightweight amorphous silicon photovoltaic modules on flexible plastic substrate

Solar cells on lightweight and flexible substrates have advantages over glass-or wafer-based photovoltaic devices in both terrestrial and space applications. Here, we report on development of amorphous silicon thin film photovoltaic modules fabricated at maximum deposition temperature of 150 degrees C on 100 mu m thick polyethylene-naphtalate plastic films. Each module of 10 cm x 10 cm area consists of 72 a-Si:H n-i-p rectangular structures with transparent conducting oxide top electrodes with Al fingers and metal back electrodes deposited through the shadow masks. Individual structures are connected in series forming eight rows with connection ports provided for external blocking diodes. The design optimization and device performance analysis are performed using a developed SPICE model.

Carbon surfaces for the oxidative quantification of pravastatin: glassy-carbon vs. screen-printed carbon electrodes

The electrooxidative behavior of pravastatin (PRV) in aqueous media was studied by square-wave voltammetry at a glassycarbon electrode (GCE) and at a screen-printed carbon electrode (SPCE). Maximum peak current intensities in a pH 5.0 buffer were obtained at +1.3 V vs. AgCl/Ag and +1.0 V vs. Ag for the GCE and SPCE surface respectively. Validation of the developed methodologies revealed good performance characteristics and confirmed their applicability to the quantification of PRV in pharmaceutical products, without significant sample pretreatment. A comparative analysis between the two electrode types showed that SPCEs are preferred as an electrode surface because of their higher sensitivity and the elimination of the need to clean the electrode’s surface for its renewal, which frequently is, if not always, the rate-limiting step in voltammetric analysis.

Voltammetric quantification of fluoxetine: application to quality control and quality assurance processes

The oxidative behaviour of fluoxetine was studied at a glassy carbon electrode in various buffer systems and at different pH using cyclic, differential pulse and square wave voltammetry. A new square wave voltammetric method suitable for the quality control of fluoxetine in commercial formulations has been developed using a borate pH 9 buffer solution as supporting electrolyte. Under optimized conditions, a linear response was obtained in the range 10 to 16 μM with a detection limit of 1.0 μM. Validation parameters such as sensitivity, precision and accuracy were evaluated. The proposed method was successfully applied to the determination of fluoxetine in pharmaceutical formulations. The results were statistically compared with those obtained by the reference high-performance liquid chromatographic method. No significant differences were found between the methods.

Electrodeposition and characterization of nikel-copper metallic foams for application as electrodes for supercapacitors

Nickel-copper metallic foams were electrodeposited from an acidic electrolyte, using hydrogen bubble evolution as a dynamic template. Their morphology and chemical composition was studied by scanning electron microscopy and related to the deposition parameters (applied current density and deposition time). For high currents densities (above 1 A cm(-2)) the nickel-copper deposits have a three-dimensional foam-like morphology with randomly distributed nearly-circular pores whose walls present an open dendritic structure. The nickel-copper foams are crystalline and composed of pure nickel and a copper-rich phase containing nickel in solid solution. The electrochemical behaviour of the material was studied by cyclic voltammetry and chronopotentiometry (charge-discharge curves) aiming at its application as a positive electrode for supercapacitors. Cyclic voltammograms showed that the Ni-Cu foams have a pseudocapacitive behaviour. The specific capacitance was calculated from charge-discharge data and the best value (105 F g(-1) at 1 mA cm(-2)) was obtained for nickel-copper foams deposited at 1.8 A cm(-2) for 180 s. Cycling stability of these foams was also assessed and they present a 90 % capacitance retention after 10,000 cycles at 10 mA cm(-2).

Células solares semi-transparentes de silício amorfo micro/nanocristalino

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia dos Materiais

The solvation and electrochemical behaviour of Copper acetylacetonate complexes in ionic liquids

The behavior of copper(II) complexes of pentane-2,4-dione and 1,1,1,5,5,5-hexafluoro-2,4-pentanedione, [Cu(acac)(2) (1) and [Cu(HFacac)(2)(H2O)] (2), in ionic liquids and molecular organic solvents, was studied by spectroscopic and electrochemical techniques. The electron paramagnetic resonance characterization (EPR) showed well-resolved spectra in most solvents. In general the EPR spectra of [Cu(acac)(2)] show higher g(z) values and lower hyperfine coupling constants, A(z), in ionic liquids than in organic solvents, in agreement with longer Cu-O bond lengths and higher electron charge in the copper ion in the ionic liquids, suggesting coordination of the ionic liquid anions. For [Cu(HFacac)(2)(H2O)] the opposite was observed suggesting that in ionic liquids there is no coordination of the anions and that the complex is tetrahedrically distorted. The redox properties of the Cu(II) complexes were investigated by cyclic voltammetry (CV) at a Pt electrode (d = 1 mm), in bmimBF(4) and bmimNTf(2) ionic liquids and, for comparative purposes, in neat organic solvents. The neutral copper(II) complexes undergo irreversible reductions to Cu(I) and Cu(0) species in both ILs and common organic solvents (CH2Cl2 or acetonitrile), but, in ILs, they are usually more easier to reduce (less cathodic reduction potential) than in the organic solvents. Moreover, 1 and 2 are easier to reduce in bmimNTf(2) than in bmimBF(4) ionic liquid. (C) 2013 Elsevier B.V. All rights reserved.

The solvation and redox behaviour of mixed ligand COPPER(II) complexes of acetylacetonate and aromatic dimines in ionic liquids

The behavior of two cationic copper complexes of acetylacetonate and 2,2'-bipyridine or 1,10-phenanthroline, [Cu(acac)(bipy)]Cl (1) and [Cu(acac)(phen)]Cl (2), in organic solvents and ionic liquids, was studied by spectroscopic and electrochemical techniques. Both complexes showed solvatochromism in ionic liquids although no correlation with solvent parameters could be obtained. By EPR spectroscopy rhombic spectra with well-resolved superhyperfine structure were obtained in most ionic liquids. The spin Hamiltonian parameters suggest a square pyramidal geometry with coordination of the ionic liquid anion. The redox properties of the complexes were investigated by cyclic voltammetry at a Pt electrode (d = 1 mm) in bmimBF(4) and bmimNTf(2) ionic liquids. Both complexes 1 and 2 are electrochemically reduced in these ionic media at more negative potentials than when using organic solvents. This is in agreement with the EPR characterization, which shows lower A(z) and higher g(z) values for the complexes dissolved in ionic liquids, than in organic solvents, due to higher electron density at the copper center. The anion basicity order obtained by EPR is NTf2-, N(CN)(2)(-), MeSO4- and Me2PO4-, which agrees with previous determinations. (C) 2013 Elsevier B.V. All rights reserved.