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.

Component-based software engineering: a quantitative approach

Dissertação apresentada para a obtenção do Grau de Doutor em Informática pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

The daily and hourly energy consumption and load forecasting using artifitial neural network method: a case study using a set of 93 households in Portugal

It is important to understand and forecast a typical or a particularly household daily consumption in order to design and size suitable renewable energy systems and energy storage. In this research for Short Term Load Forecasting (STLF) it has been used Artificial Neural Networks (ANN) and, despite the consumption unpredictability, it has been shown the possibility to forecast the electricity consumption of a household with certainty. The ANNs are recognized to be a potential methodology for modeling hourly and daily energy consumption and load forecasting. Input variables such as apartment area, numbers of occupants, electrical appliance consumption and Boolean inputs as hourly meter system were considered. Furthermore, the investigation carried out aims to define an ANN architecture and a training algorithm in order to achieve a robust model to be used in forecasting energy consumption in a typical household. It was observed that a feed-forward ANN and the Levenberg-Marquardt algorithm provided a good performance. For this research it was used a database with consumption records, logged in 93 real households, in Lisbon, Portugal, between February 2000 and July 2001, including both weekdays and weekend. The results show that the ANN approach provides a reliable model for forecasting household electric energy consumption and load profile. © 2014 The Author.

Segmentation of striatal brain structures from high resolution pet images

Dissertation presented at the Faculty of Science and Technology of the New University of Lisbon in fulfillment of the requirements for the Masters degree in Electrical Engineering and Computers

Synthesis of Sub-5 NM Co-Doped SnO2 nanoparticles and their structural microstructural, optical and photocatalytic properties

A swift chemical route to synthesize Co-doped SnO2 nanopowders is described. Pure and highly stable Sn1-xCoxO2-delta (0 <= x <= 0.15) crystalline nanoparticles were synthesized, with mean grain sizes <5 nm and the dopant element homogeneously distributed in the SnO2 matrix. The UV-visible diffuse reflectance spectra of the Sn1-xCoxO2-delta samples reveal red shifts, the optical bandgap energies decreasing with increasing Co concentration. The samples' Urbach energies were calculated and correlated with their bandgap energies. The photocatalytic activity of the Sn1-xCoxO2-delta samples was investigated for the 4-hydroxylbenzoic acid (4-HBA) degradation process. A complete photodegradation of a 10 ppm 4-HBA solution was achieved using 0.02% (w/w) of Sn0.95Co0.05O2-delta nanoparticles in 60 min of irradiation. (C) 2014 Elsevier B.V. All rights reserved.

Sub-micron structuring of silicon using femtosecond laser interferometry

We report the fabrication of planar sub-micron gratings in silicon with a period of 720 nm using a modified Michelson interferometer and femtosecond laser radiation. The gratings consist of alternated stripes of laser ablated and unmodified material. Ablated stripes are bordered by parallel ridges which protrude above the unmodified material. In the regions where ridges are formed, the laser radiation intensity is not sufficient to cause ablation. Nevertheless, melting and a significant temperature increase are expected, and ridges may be formed due to expansion of silicon during resolidification or silicon oxidation. These conclusions are consistent with the evolution of the stripes morphology as a function of the distance from the center of the grating.

People counting system using existing surveillance video camera

The Casa da Música Foundation, responsible for the management of Casa da Música do Porto building, has the need to obtain statistical data related to the number of building’s visitors. This information is a valuable tool for the elaboration of periodical reports concerning the success of this cultural institution. For this reason it was necessary to develop a system capable of returning the number of visitors for a requested period of time. This represents a complex task due to the building’s unique architectural design, characterized by very large doors and halls, and the sudden large number of people that pass through them in moments preceding and proceeding the different activities occurring in the building. To achieve the technical solution for this challenge, several image processing methods, for people detection with still cameras, were first studied. The next step was the development of a real time algorithm, using OpenCV libraries and computer vision concepts,to count individuals with the desired accuracy. This algorithm includes the scientific and technical knowledge acquired in the study of the previous methods. The themes developed in this thesis comprise the fields of background maintenance, shadow and highlight detection, and blob detection and tracking. A graphical interface was also built, to help on the development, test and tunning of the proposed system, as a complement to the work. Furthermore, tests to the system were also performed, to certify the proposed techniques against a set of limited circumstances. The results obtained revealed that the algorithm was successfully applied to count the number of people in complex environments with reliable accuracy.

Avaliação de riscos na atividade de manutenção: estudo de caso

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Desenvolvimento de um Code Set para a escrita manual baseado na classificação internacional de funcionalidade versão crianças e jovens

Compreender a funcionalidade de uma criança é um desafio persistente em contextos de saúde e educação. Na tentativa de superar esse desafio, em 2007, a Organização Mundial de Saúde desenvolveu a Classificação Internacional de Funcionalidade, Incapacidade e Saúde para Crianças e Jovens (CIF-CJ) como o primeiro sistema de classificação universal para documentar a saúde e funcionalidade da criança. Apesar de a CIF-CJ não ser um instrumento de avaliação e intervenção, tem, no entanto, a capacidade de servir de enquadramento para o desenvolvimento de ferramentas adaptadas às necessidades dos seus utilizadores. Considerando que no contexto escolar, a escrita manual encontra-se entre as atividades mais requeridas para a participação plena de uma criança, parece ser pertinente a definição de um conjunto de códigos destinados a caracterizar o perfil de funcionalidade de uma criança, no que se refere à escrita manual. O objetivo deste estudo foi, pois, o desenvolvimento de um conjunto preliminar de códigos baseado na CIF-CJ que possa vir a constituir um code set para a escrita manual. Dada a complexidade do tema e atendendo a que se pretende alcançar consenso entre os especialistas sobre quais as categorias da CIF-CJ que devem ser consideradas, optou-se pela utilização da técnica de Delphi. A escolha da metodologia seguiu a orientação dos procedimentos adotados pelo projeto Core Set CIF. De dezoito profissionais contactados, obtiveram-se respostas de sete terapeutas ocupacionais com experiência em pediatria, que participaram em todas as rondas. No total, três rondas de questionários foram realizadas para atingir um consenso, com um nível de concordância, previamente definido, de 70%. Deste estudo resultou um conjunto preliminar de códigos com 54 categorias da CIF-CJ (16 categorias de segundo nível, 14 categorias de terceiro nível e uma categoria de quarto nível), das quais 31 são categorias das funções do corpo, uma categoria das estruturas do corpo, 12 categorias de atividades e participação e 10 categorias de fatores ambientais. Este estudo é um primeiro passo para o desenvolvimento de um code set para a escrita manual baseado na CIF-CJ , sendo claramente necessário a realização de mais pesquisas no contexto do desenvolvimento e da validação deste code set.

Optimal brake specific fuel consumption trajectory for stand-alone variable speed Diesel Gen-Set

Energy efficiency plays an important role to the CO2 emissions reduction, combating climate change and improving the competitiveness of the economy. The problem presented here is related to the use of stand-alone diesel gen-sets and its high specific fuel consumptions when operates at low loads. The variable speed gen-set concept is explained as an energy-saving solution to improve this system efficiency. This paper details how an optimum fuel consumption trajectory based on experimentally Diesel engine power map is obtained.

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).

Notes on the Cretaceous invertebrate faunas of Portugal I: a new species of Anadromus (Mollusca, Gastropoda) from the Campanian-Maastrichtian of Taveiro (Coimbra, West central Portugal)

A new species of terrestrial gastropod - Anadromus penai sp. nov. (Fam. Anadromidae) - is described from a set of composite moulds collected in reddish silts and clays of Campanian-Maastrichtian age, found in the lower pan of the Taveiro Formation (Taveiro, Coimbra, West Central Portugal). The known occurrences of this new species are restricted to the type locality. The main differences from other contemporaneous Anadromidae are the profuse spiral sculpture of the body-whorl, with 20-22 sub-equal, close, and regular ribs.

Unified overhead-aware schedulability analysis for slot-based task-splitting

Hard real- time multiprocessor scheduling has seen, in recent years, the flourishing of semi-partitioned scheduling algorithms. This category of scheduling schemes combines elements of partitioned and global scheduling for the purposes of achieving efficient utilization of the system’s processing resources with strong schedulability guarantees and with low dispatching overheads. The sub-class of slot-based “task-splitting” scheduling algorithms, in particular, offers very good trade-offs between schedulability guarantees (in the form of high utilization bounds) and the number of preemptions/migrations involved. However, so far there did not exist unified scheduling theory for such algorithms; each one was formulated in its own accompanying analysis. This article changes this fragmented landscape by formulating a more unified schedulability theory covering the two state-of-the-art slot-based semi-partitioned algorithms, S-EKG and NPS-F (both fixed job-priority based). This new theory is based on exact schedulability tests, thus also overcoming many sources of pessimism in existing analysis. In turn, since schedulability testing guides the task assignment under the schemes in consideration, we also formulate an improved task assignment procedure. As the other main contribution of this article, and as a response to the fact that many unrealistic assumptions, present in the original theory, tend to undermine the theoretical potential of such scheduling schemes, we identified and modelled into the new analysis all overheads incurred by the algorithms in consideration. The outcome is a new overhead-aware schedulability analysis that permits increased efficiency and reliability. The merits of this new theory are evaluated by an extensive set of experiments.

Evolução da ocupação e da perda de solo numa pequena sub-bacia da Bacia Hidrográfica do Rio Sado

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente,Perfil Gestão de Sistemas Ambientais

An Approach To Publish a Data Warehouse Content as Linked Data

Mestrado em Engenharia Informática - Área de Especialização em Tecnologias do Conhecimento e Decisão