Solving MPCC problem with the hyperbolic penalty function

The main goal of this work is to solve mathematical program with complementarity constraints (MPCC) using nonlinear programming techniques (NLP). An hyperbolic penalty function is used to solve MPCC problems by including the complementarity constraints in the penalty term. This penalty function [1] is twice continuously differentiable and combines features of both exterior and interior penalty methods. A set of AMPL problems from MacMPEC [2] are tested and a comparative study is performed.

Solving a signalized traffic intersection problem with an hyperbolic penalty function

Mathematical Program with Complementarity Constraints (MPCC) finds many applications in fields such as engineering design, economic equilibrium and mathematical programming theory itself. A queueing system model resulting from a single signalized intersection regulated by pre-timed control in traffic network is considered. The model is formulated as an MPCC problem. A MATLAB implementation based on an hyperbolic penalty function is used to solve this practical problem, computing the total average waiting time of the vehicles in all queues and the green split allocation. The problem was codified in AMPL.

Efeitos de um programa baseado em tarefas orientadas na competência de marcha em indivíduos com acidente vascular cerebral

Mestrado em Fisioterapia.

Biologia e abundância do camarão Plesionika edwardsii (Brandt, 1851) nos Açores

Dissertação de Mestrado, Estudos Integrados dos Oceanos, 15 de Janeiro de 2009, Universidade dos Açores.

A aprendizagem da Matemática no 1º ciclo através de atividades de investigação numa comunidade de aprendizagem

Dissertação apresentada para obtenção do grau de Mestre em Educação Matemática na Educação Pré-Escolar e nos 1º e 2º Ciclos do Ensino Básico na especialidade de Didática da Matemática

Monitorização do adoçante ciclamato de sódio através de sensor óptico

O presente trabalho pretendeu desenvolver e testar um sensor óptico para detectar ciclamato de sódio, um adoçante artificial utilizado nas bebidas em geral. A primeira abordagem neste sentido baseou-se na preparação de um sensor óptico através da formação de complexos corados entre o ciclamato e várias espécies metálicas, nomeadamente Hg(II), Ba(II), Fe(II), Ag(II), Pb(II), Cd(II), Mn (II), Ni(II), Cu(II), Co(II), Sn(II) e Mg(II). Perante a ausência de resultados satisfatórios optou-se por explorar a acção do ciclamato de sódio na transferência/partilha de um corante entre duas fases líquidas imiscíveis. As fases líquidas utilizadas foram a água e o clorofórmio. Testaram-se várias famílias de corantes mas só uma classe se mostrou com as características apropriadas para o objectivo pretendido. Dentro dessa família de corantes, seleccionou-se aquele que, à partida, garantiu o melhor desempenho. O sensor foi testado em diferentes condições de pH e também na presença de potenciais interferentes de forma a estabelecer as melhores condições de utilização. O método mostrou-se bastante simples de executar, rápido na obtenção de resultados e com boas características para ser avaliado visualmente, mas sempre de acordo com os critérios de objectividade que um trabalho deste tipo requer. Além o disso permitiu ser calibrado de uma forma rápida e simples, características essenciais para a aplicação deste método na despistagem de ciclamato em análises de rotina. O método desenvolvido foi ainda aplicado à análise de vinho dopado com diferentes concentrações de ciclamato de sódio. Destes testes verificou-se a necessidade de optimização do método através da introdução de outras substâncias na fase não aquosa diminuindo a vulnerabilidade do sensor a outros interferentes. Como conclusão, o método correspondeu às expectativas, mostrando-se viável para aplicação à análise de vinhos, ainda com uma margem significativa de desenvolvimento no sentido de o tornar mais fiável e preciso.

Reading performance in children with visual function anomalies

Aims - To compare reading performance in children with and without visual function anomalies and identify the influence of abnormal visual function and other variables in reading ability. Methods - A cross-sectional study was carried in 110 children of school age (6-11 years) with Abnormal Visual Function (AVF) and 562 children with Normal Visual Function (NVF). An orthoptic assessment (visual acuity, ocular alignment, near point of convergence and accommodation, stereopsis and vergences) and autorefraction was carried out. Oral reading was analyzed (list of 34 words). Number of errors, accuracy (percentage of success) and reading speed (words per minute - wpm) were used as reading indicators. Sociodemographic information from parents (n=670) and teachers (n=34) was obtained. Results - Children with AVF had a higher number of errors (AVF=3.00 errors; NVF=1.00 errors; p<0.001), a lower accuracy (AVF=91.18%; NVF=97.06%; p<0.001) and reading speed (AVF=24.71 wpm; NVF=27.39 wpm; p=0.007). Reading speed in the 3rd school grade was not statistically different between the two groups (AVF=31.41 wpm; NVF=32.54 wpm; p=0.113). Children with uncorrected hyperopia (p=0.003) and astigmatism (p=0.019) had worst reading performance. Children in 2nd, 3rd, or 4th grades presented a lower risk of having reading impairment when compared with the 1st grade. Conclusion - Children with AVF had reading impairment in the first school grade. It seems that reading abilities have a wide variation and this disparity lessens in older children. The slow reading characteristics of the children with AVF are similar to dyslexic children, which suggest the need for an eye evaluation before classifying the children as dyslexic.

Phenotypic impact of deregulated expression of class I histone deacetylases in urothelial cell carcinoma of the bladder

Deregulated expression of histone deacetylases (HDACs) has been implicated in tumorigenesis. Herein, we investigated class I HDACs expression in bladder urothelial cell carcinoma (BUCC), its prognostic value and biological significance. Significantly increased transcript levels of all HDACs were found in BUCC compared to 20 normal mucosas, and these were higher in lower grade and stage tumors. Increased HDAC3 levels were associated with improved patient survival. SiRNA experiments showed decrease cell viability and motility, and increased apoptosis. We concluded that class I HDACs play an important role in bladder carcinogenesis through deregulation of proliferation, migration and apoptosis, constituting putative therapeutic targets

Relatório de estágio

I (Prática Pedagógica)- No que se refere à secção da tese dedicada ao estágio, esta pretende desenvolver uma síntese do que se passou ao longo deste ano lectivo. Durante o ano lectivo 2012/2013, tive a oportunidade de assistir a aulas ministradas pela professora Ana Valente. A tese procura focar variados aspectos das aulas a que assisti. De uma forma geral, o relatório do estágio evidencia vários aspectos: metodologias de ensino, questões motivacionais, relação aluno/professor, questões de disciplina, entre outras. No decorrer das aulas, foi possível constatar muitas dessas questões na prática. Tentei registar as actividades desenvolvidas nas aulas relativas a várias questões, nomeadamente questões relacionadas com a prática do instrumento, assim como outras relacionadas com a noção de musicalidade. Como resultado, esta secção apresenta diversos tipos de estratégias de ensino, ilustrando exemplos práticos que efectivamente se passaram nas aulas. É essencialmente, uma secção dedicada à reflexão sobre metodologias de ensino e estudo. A segunda parte desta secção é relativa à análise das gravações das aulas dadas por mim e pretende sobretudo focar-se na crítica pessoal. É uma parte importante do estágio, em que tenho a oportunidade de observar a minha forma pedagógica de lidar com os alunos. Por fim, a terceira parte do relatório refere-se à observação crítica da abordagem da professora tendo por base o meu ponto de vista. Esta parte pretende essencialmente descrever e analisar a forma como a professora dá as aulas. Com base no que disse anteriormente, esta parte do trabalho mostra mais em detalhe as metodologias e estratégias de ensino utilizadas pela professora em questão. De um modo geral, esta secção pretende descrever as três vertentes que mencionei anteriormente (relatório das aulas, análise das gravações, observação crítica ao método pedagógico da professora).

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.

Penalty fuzzy function for derivative-free optimization

Penalty and Barrier methods are normally used to solve Nonlinear Optimization Problems constrained problems. The problems appear in areas such as engineering and are often characterised by the fact that involved functions (objective and constraints) are non-smooth and/or their derivatives are not know. This means that optimization methods based on derivatives cannot net used. A Java based API was implemented, including only derivative-free optimizationmethods, to solve both constrained and unconstrained problems, which includes Penalty and Barriers methods. In this work a new penalty function, based on Fuzzy Logic, is presented. This function imposes a progressive penalization to solutions that violate the constraints. This means that the function imposes a low penalization when the violation of the constraints is low and a heavy penalisation when the violation is high. The value of the penalization is not known in beforehand, it is the outcome of a fuzzy inference engine. Numerical results comparing the proposed function with two of the classic penalty/barrier functions are presented. Regarding the presented results one can conclude that the prosed penalty function besides being very robust also exhibits a very good performance.

A Java expression evaluator for nonlinear programming

Finding the optimal value for a problem is usual in many areas of knowledge where in many cases it is needed to solve Nonlinear Optimization Problems. For some of those problems it is not possible to determine the expression for its objective function and/or its constraints, they are the result of experimental procedures, might be non-smooth, among other reasons. To solve such problems it was implemented an API contained methods to solve both constrained and unconstrained problems. This API was developed to be used either locally on the computer where the application is being executed or remotely on a server. To obtain the maximum flexibility both from the programmers’ and users’ points of view, problems can be defined as a Java class (because this API was developed in Java) or as a simple text input that is sent to the API. For this last one to be possible it was also implemented on the API an expression evaluator. One of the drawbacks of this expression evaluator is that it is slower than the Java native code. In this paper it is presented a solution that combines both options: the problem can be expressed at run-time as a string of chars that are converted to Java code, compiled and loaded dynamically. To wide the target audience of the API, this new expression evaluator is also compatible with the AMPL format.

Logarithmically proportional objective function for planar surfaces recognition in 3D point cloud

3D laser scanning is becoming a standard technology to generate building models of a facility's as-is condition. Since most constructions are constructed upon planar surfaces, recognition of them paves the way for automation of generating building models. This paper introduces a new logarithmically proportional objective function that can be used in both heuristic and metaheuristic (MH) algorithms to discover planar surfaces in a point cloud without exploiting any prior knowledge about those surfaces. It can also adopt itself to the structural density of a scanned construction. In this paper, a metaheuristic method, genetic algorithm (GA), is used to test this introduced objective function on a synthetic point cloud. The results obtained show the proposed method is capable to find all plane configurations of planar surfaces (with a wide variety of sizes) in the point cloud with a minor distance to the actual configurations. © 2014 IEEE.