Aprendizagem autónoma (self-directed learning): relatório de um atelier pedagógico

Educação Médica. 1994, 5(3):178-181.

Application of NMR RDC’s, relaxation and self-diffusion for the study of dynamic processes of small molecules in solution

Spin-lattice Relaxation, self-Diffusion coefficients and Residual Dipolar Couplings (RDC’s) are the basis of well established Nuclear Magnetic Resonance techniques for the physicochemical study of small molecules (typically organic compounds and natural products with MW < 1000 Da), as they proved to be a powerful and complementary source of information about structural dynamic processes in solution. The work developed in this thesis consists in the application of the earlier-mentioned NMR techniques to explore, analyze and systematize patterns of the molecular dynamic behavior of selected small molecules in particular experimental conditions. Two systems were chosen to investigate molecular dynamic behavior by these techniques: the dynamics of ion-pair formation and ion interaction in ionic liquids (IL) and the dynamics of molecular reorientation when molecules are placed in oriented phases (alignment media). The application of NMR spin-lattice relaxation and self-diffusion measurements was applied to study the rotational and translational molecular dynamics of the IL: 1-butyl-3-methylimidazolium tetrafluoroborate [BMIM][BF4]. The study of the cation-anion dynamics in neat and IL-water mixtures was systematically investigated by a combination of multinuclear NMR relaxation techniques with diffusion data (using by H1, C13 and F19 NMR spectroscopy). Spin-lattice relaxation time (T1), self-diffusion coefficients and nuclear Overhauser effect experiments were combined to determine the conditions that favor the formation of long lived [BMIM][BF4] ion-pairs in water. For this purpose and using the self-diffusion coefficients of cation and anion as a probe, different IL-water compositions were screened (from neat IL to infinite dilution) to find the conditions where both cation and anion present equal diffusion coefficients (8% water fraction at 25 ºC). This condition as well as the neat IL and the infinite dilution were then further studied by 13C NMR relaxation in order to determine correlation times (c) for the molecular reorientational motion using a mathematical iterative procedure and experimental data obtained in a temperature range between 273 and 353 K. The behavior of self-diffusion and relaxation data obtained in our experiments point at the combining parameters of molar fraction 8 % and temperature 298 K as the most favorable condition for the formation of long lived ion-pairs. When molecules are subjected to soft anisotropic motion by being placed in some special media, Residual Dipolar Couplings (RDCs), can be measured, because of the partial alignment induced by this media. RDCs are emerging as a powerful routine tool employed in conformational analysis, as it complements and even outperforms the approaches based on the classical NMR NOE or J3 couplings. In this work, three different alignment media have been characterized and evaluated in terms of integrity using 2H and 1H 1D-NMR spectroscopy, namely the stretched and compressed gel PMMA, and the lyotropic liquid crystals CpCl/n-hexanol/brine and cromolyn/water. The influence that different media and degrees of alignment have on the dynamic properties of several molecules was explored. Different sized sugars were used and their self-diffusion was determined as well as conformation features using RDCs. The results obtained indicate that no influence is felt by the small molecules diffusion and conformational features studied within the alignment degree range studied, which was the 3, 5 and 6 % CpCl/n-hexanol/brine for diffusion, and 5 and 7.5 % CpCl/n-hexanol/brine for conformation. It was also possible to determine that the small molecules diffusion verified in the alignment media presented close values to the ones observed in water, reinforcing the idea of no conditioning of molecular properties in such media.

Self-initiation expatriation: A focus on Italian and Portuguese students

The purpose of this work project is to analyze the phenomenon of self-initiated expatriation (SIE) through its link to the Protean Career and Career Capital theories, focusing in particular on Italian and Portuguese students attending a Master in the business area. The main research questions are to understand the reasons driving the intention to expatriate, after the conclusion of the academic path, using three main categories (Adventure Motivation, Work Characteristic Motivation and instrumental Motivation) and the intention to repatriate. A sample of Italian and Portuguese students was obtained. Italians show a higher intention to expatriate relative to Portuguese; nevertheless, no other significant differences were found among the two populations, because of the similar cultural background and economic situation. Additionally, several heterogeneities were observed considering other clusters defined by Gender, Teaching Language of the Master and Past International Experiences, across the two nationalities. Furthermore, possible future researches and practical implications were discussed.

Democratic dialogue and collective learning in the context of self-managed teams

This paper provides a longitudinal, empirical view of the multifaceted and reciprocal processes of organizational learning in a context of self-managed teams. Organizational learning is seen as a social construction between people and actions in a work setting. The notion of learning as situated (Brown & Duguid 1989, Lave& Wenger 1991, Gherardi & al. 1998, Easterby-Smith & Araujo 1999, Abma 2003) opens up the possibility for placing the focus of research on learning in the community rather than in individual learning processes. Further, in studying processes in their social context, we cannot avoid taking power relations into consideration (Contu & Willmott 2003). The study is based on an action research with a methodology close to the ‘democratic dialogue’ presented by Gustavsen (2001). This gives a ground for research into how the learning discourse developed in the case study organization over a period of 5 years, during which time the company abandoned a middle management level of hierarchy and the teams had to figure out how to work as self-managed units. This paper discusses the (re)construction of power relations and its role in organizational learning. Power relations are discussed both in vertical and horizontal work relations. A special emphasis is placed on the dialectic between managerial aims and the space for reflection on the side of employees. I argue that learning is crucial in the search for the limits for empowerment and that these limits are negotiated both in actions and speech. This study unfolds a purpose-oriented learning process, constructing an open dialogue, and describes a favourable context for creative, knowledge building communities.

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.

Self-organization and complexity theory to support evolvable production 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

Digital-domain self-calibration technique for video-rate pipeline A/D converters using Gaussian white noise

Electronics Letters Vol.38, nº 19

Visualization of clusters in geo-referenced data using three-dimensional self-organizing maps

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Wetland Habitat Studies using various Classification Techniques on Multi-Spectral Landsat Imagery: Case study: Tram chim National Park, Dong Thap Vietnam

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

CARTO-SOM - Cartogram creation using self-organizing maps

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica

Exploratory geospatial data analysis using self-organizing maps

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica

New simple digital self-calibration technique for pipeline ADCs using the internal thermal noise

IEEE International Symposium on Circuits and Systems, pp. 232 – 235, Seattle, EUA

Efficient digital self-calibration of video-rate pipeline ADCs using white gaussian noise

Proceedings of IEEE, ISCAS 2003, Vol.I, pp. 877-880

Sub-notificação de reacções adversas medicamentosas : um problema com solução? : contribuição para o conhecimento da sub-notificação de RAMs em Portugal e implementação de medidas minimizadoras do impacte

RESUMO - Introdução: As Reacções Adversas Medicamentosas (RAMs) constituem um grave problema de Saúde Pública em termos da mortalidade e morbilidade provocadas, tendo também um impacto económico considerável nos Sistemas de Saúde. Os Sistemas de Notificacão Espontânea de RAMs são considerados como o método de vigilância de medicamentos mais eficaz, sendo a sub-notificação de RAMs uma das suas maiores limitações. Em termos globais, foi estimado que apenas 6% de todas as reacções adversas são notificadas. Portugal apresenta uma taxa de notificação de RAMs relativamente baixa quando comparada com os países mais notificadores da Europa. São objectivos deste estudo: 1) caracterizar as atitudes e os comportamentos dos médicos, dos farmacêuticos e dos enfermeiros em Portugal Continental relativamente à notificação de RAMs; e 2) caracterizar a efectividade de intervenções educacionais destinadas a reduzir a sub-notificação de RAMs. Métodos: Numa primeira fase será efectuado um estudo de caso-controlo em médicos, farmacêuticos e enfermeiros de Portugal Continental, a exercer actividade no Servico Nacional de Saúde (SNS), de modo a caracterizar as suas atitudes e comportamentos relativamente à notificação de RAMs. Como casos serão considerados os Profissionais de Saúde que notificaram pelo menos uma RAM num determinado período e os controlos os Profissionais de Saúde que não notificaram qualquer RAM nesse mesmo período, sendo estes útimos seleccionados aleatoriamente. O estudo será conduzido através de um questionário de auto-resposta, em que as questões relativas às atitudes e comportamentos são baseadas nos “sete pecados mortais” de Inman. Será utilizada uma Escala Visual Analógica para registar as respostas, podendo estas ir de zero (totalmente em desacordo) até 10 (totalmente de acordo). Será utilizada uma análise de regressão logística para determinar o odds ratio ajustado (ORadj) da notificação de RAMs para uma mudança de exposição correspondente ao range interquartil para cada atitude. Numa segunda fase, será efectuado ensaio aleatorizado controlado de cluster, para caracterizar a efectividade das intervenções educacionais realizadas sobre as causas identificadas na primeira parte do trabalho, com o intuito de reduzir a sub-notificação de RAMs. Com base em informacão de 2007 foram identificados 43 clusters dispersos pelas várias Regiões de Saúde. As intervenções educacionais são compostas por uma apresentação com uma hora de duração complementada por um folheto recordatório. Serão ainda realizados dois sub-estudos, em que o V1.0, Final 28Set09 viii Sub-notificação de RAMs em Portugal – Um problema com solução ? primeiro tentará caracterizar o efeito de contaminação entre Profissionais de Saúde e o segundo pretende caracterizar a duração do efeito das intervenções educacionais. Resultados a atingir: Pretende-se, com a implementação deste projecto, aumentar o número de notificações de RAMs pelos médicos, farmacêuticos e enfermeiros em cerca de 110%, de modo a atingir-se uma taxa de notificação de aproximadamente 300 notificações por milhão de habitantes por ano (i.e., multiplicar por 2,1 o número notificações existentes). -------------------ABSTRACT - Introduction: The Adverse Drug Reactions (ADRs) are a serious Public Health problem in terms of mortality and morbidity caused, being also an economic burden for the health systems. The Spontaneous Adverse Event Reporting Systems are considered as the most effective drug surveillance methods, in which the ADR under-reporting represents one of its biggest limitations. It was estimated that only 6% of all adverse reactions are notified globally. When comparing with high ADR reporting rate countries Portugal shows a low ADR reporting rate. This study aims to: 1) characterize the physicians, pharmacists and nurses attitudes and behaviours related to ADR under-reporting; 2) characterize the educational interventions effectiveness to decrease the ADRs under-reporting. Methods: During a first phase a case-control study will be conducted in physicians, pharmacists and nurses in Continental Portugal working in the National Health System (NHS) in order to characterize their attitudes and behaviours related to ADR reporting. The Healthcare Professionals that have reported at least one ADR during a determined period will be considered as the cases and those that have not reported any ADR during the same period will be considered as the controls. The controls will be randomly selected. The study will be conducted through a self-administered questionnaire in which the questions related to the attitudes and behaviours are based in the Inmans’s “seven mortal sins”. A Visual Analogue Scale will be used to record the responses. The responses can range from 0 (totally disagree) to 10 (totally agree). Logistic regression will be used to determine the ADR reporting adjusted odds ratio (ORadj) for a change in the exposure corresponding to the interquartile range for each attitude. In the second phase of the study a cluster-randomized controlled trial will be conducted to characterize the educational interventions effectiveness focused on the first phase identified causes with the aim to decrease the ADRs under-reporting. Based in 2007’s information 43 clusters have been identified throughout the several Health Regions. The educational interventions are composed of one hour presentation complemented by an informational leaflet. Two sub-studies will be also conducted in which the first one will try to characterize the contamination effect between the Healthcare Professionals and the second to characterize the educational interventions effect duration. V1.0, Final 28Set09 x Sub-notificação de RAMs em Portugal – Um problema com solução ? Outcome: With the project implementation an increase of the ADR notifications performed by the physicians, pharmacists and nurses by 110% is aimed in order to obtain approximately 300 notifications per million habitants per year (i.e., multiply by 2,1 the existent notifications).

Utilização do algoritmo Self-Organizing Map na caracterização de organizações públicas portuguesas.

Dissertação apresentada como requisito parcial para a obtenção do grau de mestre em Estatística e Gestão de Informação.