Neste trabalho são apresentadas contribuições para a estimação do desempenho elétrico na distribuição de energia elétrica, com implicações nos mais diversos problemas da operação e do planejamento da distribuição. Entende-se por desempenho elétrico, a avaliação dos parâmetros de congestionamento de redes, as perdas e o nível de tensão. A motivação deste trabalho está na agregação dos esforços advindos da campanha de medição compulsória das concessionárias de distribuição e da necessidade do órgão regulador de estabelecer parâmetros de avaliação do desempenho operacional das empresas, como previsto no documento intitulado “Procedimentos da Distribuição" da Aneel. A estimação do desempenho elétrico é formulada segundo um problema de otimização multiobjetivo onde as funções objetivo compõem uma avaliação de probabilidade de ocorrência e uma avaliação de proximidade dos parâmetros elétricos calculados com os valores obtidos por medição. Os valores das cargas são discretizados segundo probabilidades de ocorrência em cada intervalo, de modo que a formulação resulte em um problema de otimização combinatória multiobjetivo de dimensão exponencial. Propõe-se um procedimento de redução de rede, que diminua consideravelmente o espaço de decisões, e um procedimento de expansão de redes para recompô-la. Também são propostas heurísticas específicas para a obtenção de soluções com cargas diversificadas e desequilibradas. Para uma aplicação adequada destas heurísticas, propôs-se e aplicou-se um método evolucionário metaheurístico para composição das soluções factíveis, ordenadas de acordo com o conceito de dominância de Pareto. Para cada fronteira de dominância, ou conjunto de fronteiras, o aplicativo constrói a distribuição probabilística da corrente e fluxo de potência de cada trecho, o nível de tensão em todas as barras e as perdas técnicas totais do circuito. A formulação matemática de otimização é flexível o bastante para a aplicação prática, considerando os diversos estágios de implementação dos atuais sistemas supervisórios. O modelo evolucionário metaheurístico proposto foi aplicado para um caso ilustrativo evidenciando as suas potencialidades e os pontos a serem aprimorados. / This thesis aims at contributing for the estimation of electrical performance in the distribution of electrical energy. Electrical performance is assumed to be the evaluation of network congestion parameters, losses and voltage level. The development of this work was impelled due to distribution utilities compulsory measurement permanent campaigns, and due to the need of the regulatory agency in establishing operational performance standards, as stated in the Distribution Code of Aneel, the Brazilian Energy Regulatory Agency. The electrical performance estimation is formulated according to an optimization problem where the objective functions correspond to an evaluation of occurrence probability, and correspond to a proximity evaluation of calculated parameters with values obtained by measurement as well. Load values are discretized according to ocurrence probabilities within each interval, so that formulation results in a multiobjective combinatorial optimization of exponential dimension. Network reduction procedures to substantially reduce Decision Domain and network expansion procedures to recompose it are proposed. Specific heuristics are also proposed to get solutions with load diversity and unbalanced loads. In order to adequately apply these heuristics, a metaheuristic evolutionary method to build feasible solutions is proposed and applied, and ranked according to Pareto´s concept. For each dominance frontier or group of frontiers, the application builds the probabilistic: current and load flow distribution of for each branch, voltage level for each bar and circuit technical losses. The mathematical formulation of optimization is flexible enough to be effectively applied taking into account different levels of supervisory systems developed in the utilities. The metaheuristic evolutionary model proposed was applied to a representative case with main potentialities and weak points to be improved.

A capacidade das células para responder corretamente a sinais externos e perceber mudanças no seu microambiente é a base do desenvolvimento, reparação de tecidos e de imunidade, bem como a homeostase do tecido normal. Transdução de sinal é o principal meio pelo qual as células respondem a sinais externos de seu ambiente e coordenam alterações celulares complexas. O estudo das vias de sinalização molecular permite-nos tentar compreender o funcionamento dessas transduções de sinais e, consequentemente, as respostas celulares a estímulos externos. Uma abordagem adequada para tais estudos é o uso de modelos matemáticos para simular a cinética das reações químicas que descrevem uma dada via de sinalização, o que nos permite gerar predições testáveis de processos celulares. Construir modelos cinéticos preditivos de vias de sinalização molecular através de dados de alto rendimento produzidos utilizando técnicas ômicas (i.e., genômica, transcriptômica, (fosfo-)proteômica) constitui um dos atuais desafios enfrentados pelos pesquisadores na área de Biologia Molecular. Recentemente, para lidar com este desafio, o arcabouço de e-Science SigNetSim foi introduzido pelo Grupo de Biologia Computacional e de Bioinformática do Instituto Butantan. Esse arcabouço permite fazer a descrição de vias de sinalização molecular através da descrição da estrutura de um modelo através de um conjunto de reações químicas, que por sua vez é mapeado para um sistema de Equações Diferencias Ordinárias (EDOs), numericamente simuladas e avaliadas. Todavia, modificações na estrutura das vias precisam ser feitas manualmente, o qual restringe severamente o número de estruturas da via que precisam ser testadas, especialmente no caso de modelos grandes. Portanto, diante desse panorama, este trabalho propõe o desenvolvimento de um método para modificar vias de sinalização molecular. Esse método se baseia no uso de bancos de dados de interatomas para fornecer um conjunto de espécies químicas candidatas para serem incluídas na via de sinalização. Um componente integrado ao arcabouço SigNetSim capaz de testar diferentes hipóteses de modificação de vias foi desenvolvido neste projeto utilizando a metodologia de heurística incremental. Para avaliar a eficiência do componente implementado, utilizamos como estudo de caso um modelo de vias sinalização de MAPKs e PI3K/Akt para realizar testes experimentais e analisar os resultados obtidos. / The ability of cells to respond correctly external signals and to perceive changes in their microenvironment is the basis for development, tissue repair and immunity as well as normal tissue homeostasis. Signal transduction is the primary means by which cells respond to external signals from their environment and coordinate complex cellular changes. The study of molecular signaling pathways allows us to understand the operation of each process of cellular signal transduction. The use of mathematical models to simulate the kinetics of chemical reactions that describe a given signaling pathway, allow us to generate testable predictions of the cell processos. To Build Kinetic predictive models to molecular signaling pathways through massive data omics produced using modern techniques, Genomics, transcriptomics, (Phospho) proteomics, is one of the current challenges faced by researchers in the field of molecular biology. Recently, the \\textit SigNetSim e-Science was introduced by the Biological Computacional and Bioinformatical Group from the Butantan Institute to face this challenge. This \\textit makes the description of molecular signaling pathways through a set of chemical reactions, which are mapped into a system of ordinary differential equations, this system will be numerically simulated and evaluated . However, changes in the structure of the pathways need to be updated manually presented in this work, which severely restricts the number of track structures that need to be tested, especially for the large models. Therefore, given this background, we present the method to modify the molecular signaling pathways. This method relies on the use of interactome database to provide a set of chemical species candidates to be included in the signaling pathway. An component integrated to SigNetSim framework able to test different hypotheses of pathways modification was developed in this project using the incremental heuristic methodology. To evaluate the implemented component, we used the MAPKs and PI3K/Akt pathways model as case study, in order to perform experimental tests and to analyze the obtained results.

A method to detect relationships between disease susceptibility and multilocus genetic interactions is the Multifactor-Dimensionality Reduction (MDR) technique pioneered by Ritchie et al. (2001). Since its introduction, many extensions have been pursued to deal with non-binary outcomes and/or account for multiple interactions simultaneously. Studying the effects of multilocus genetic interactions on continuous traits (blood pressure, weight, etc.) is one case that MDR does not handle. Culverhouse et al. (2004) and Gui et al. (2013) proposed two different methods to analyze such a case. In their research, Gui et al. (2013) introduced the Quantitative Multifactor-Dimensionality Reduction (QMDR) that uses the overall average of response variable to classify individuals into risk groups. The classification mechanism may not be efficient under some circumstances, especially when the overall mean is close to some multilocus means. To address such difficulties, we propose a new algorithm, the Ordered Combinatorial Quantitative Multifactor-Dimensionality Reduction (OQMDR), that uses a series of testings, based on ascending order of multilocus means, to identify best interactions of different orders with risk patterns that minimize the prediction error. Ten-fold cross-validation is used to choose from among the resulting models. Regular permutations testings are used to assess the significance of the selected model. The assessment procedure is also modified by utilizing the Generalized Extreme-Value distribution to enhance the efficiency of the evaluation process. We presented results from a simulation study to illustrate the performance of the algorithm. The proposed algorithm is also applied to a genetic data set associated with Alzheimer's Disease.

De nombreux glycoclusters multivalents des calixarènes, des pillararènes ou des fullerènes ont été synthétisés au sein de notre laboratoire et ont montré d'excellentes affinités pour diverses lectines grâce à leur multivalence et au « glycoside cluster effect ». Nous avons cherché à approfondir ces résultats en ajoutant un degré de dynamisme à ces molécules. Pour cela, nous avons appliqué les concepts de la chimie combinatoire dynamique où des briques moléculaires s'auto-assemblent via des liaisons réversibles pour générer à l'équilibre thermodynamique une chimiothèque d'oligomères. Des briques moléculaires dithiophénols glycosylés sont capables de s'auto-assembler via la formation de ponts disulfures. Leurs propriétés ont été investiguées en chimie combinatoire dynamique et la distribution d'espèces résultant de l'équilibration a montré la formation exclusive des cyclotrimères et cyclotétramères, ou dyn[3]- et dyn[4]arènes. La répétition de l'expérience en présence d'une lectine modèle (ConA) a mené à l'amplification des homodyn[3]- et homodyn[4]arènes. Ces derniers ont été isolés par HPLC semi-préparative et leurs affinités pour ConA ont été mesurées en ITC dans le domaine du nanomolaire. Une extension de cette méthodologie aux lectines LecA et LecB de Pseudomonas aeruginosa est en cours / Several glycoclusters based on calixarenes, pillararenes or fullerenes have been synthesized in our laboratory. They exhibited strong affinities for several lectins through their multivalence and the “glycoside cluster effect”. The prupose of this study was to add a dynamic part to these molecules. We therefore applied the concept of dynamic combinatorial chemistry in which building blocks are able to self-assemble through reversible bonds to generate a library of oligomers. Dithiophenols bearing carbohydrate epitopes can self-assemble through the formation and exchange of disulfide bonds. Their properties in dynamic combinatorial chemistry were studied and the species distribution at the thermodynamic equilibrium revealed the selective formation of cyclotrimers and cyclotetramers named dyn[3]- and dyn[4]arenes. The equilibration in the presence of ConA, used as a model lectin, have led to the amplification of homodyn[3]- and homodyn[4]arenes. These glycodyn[n3,4]arenes have been isolated and their affinities toward ConA measured by ITC in the nanomolar range. Extension of this methodology toward the lectins LecA and LecB of Pseudomonas aeruginosa is in progress

Abstract not available

This thesis develops an integrated methodology based on the desirability index and QSAR models to virtually optimise molecules. Statistical and algorithmic tools are proposed to search in huge collections of compounds obtained by combinatorial chemistry the most promising ones. First, once the drugability properties of interest have been precisely defined, QSAR models are developed to mimic the relationship between those optimised properties and chemical descriptors of molecules. The literature on QSAR models is reviewed and the statistical tools to validate the models, analyse their fit and their predictive power are detailed. Even if a QSAR model has been validated and sounds highly predictive, we emphasise the importance of measuring extrapolation by the definition of its applicability domain and quantifying the prediction error for a given molecule. Indeed, QSAR models are often massively applied to predict drugability properties for libraries of new compounds without taking care of the reliability of each individual prediction. Then, a desirability index measures the compromise between the multiple estimated drugability properties and allows to rank the molecules in the combinatorial library in preference order. The propagation of the models prediction error on the desirability index is quantified by a confidence interval that can be constructed under general conditions for linear regression, PLS regression or regression tree models. This fulfills an important lack of the desirability index literature that considers it as exact. Finally, a new efficient algorithm (WEALD) is proposed to virtually screen the combinatorial library and retain the molecule with the highest desirability indexes. For each explored molecule, it is checked if it belongs to the applicability domain of each QSAR models. In addition, the uncertainty of the desirability index of each explored molecule is taken into account by gathering molecules that can not be distinguished from the optimal one due to the propagation of QSAR models prediction error. Those molecules do not have a significantly smaller desirability than the optimal molecule found by WEALD. This constitutes another important improvement in the use of desirability index as a tool to compare solutions in a multicriteria optimisation problem. This integrated methodology has been developed in the context of lead optimisation and is illustrated on a real combinatorial library provided by Eli Lilly and Company. This is the main application of the thesis. Nevertheless, as the results on desirability index uncertainty are applicable under general conditions, they can be applied to any multicriteria optimisation problem, like it often occurs in industry.

The game of Hex is of interest to the mathematics, algorithms, and artificial intelligence communities. It is a classical PSPACE-complete problem, and its invention is intrinsically tied to the Four Colour Theorem and the well-known strategy-stealing argument. Nash, Shannon, Tarjan, and Berge are among the mathematicians who have researched and published about this game. In this thesis we expand on previous research, further developing the mathematical theory and algorithmic techniques relating to Hex. In particular, we identify new classes of moves that can be pruned from consideration, and devise new algorithms to identify connection strategies efficiently. As a result of these theoretical improvements, we produce an automated solver capable of solving all 8 x 8 Hex openings and most 9 x 9 Hex openings; this marks the first time that computers have solved all Hex openings solved by humans. We also produce the two strongest automated Hex players in the world --- Wolve and MoHex --- and obtain both the gold and silver medals in the 2008 and 2009 International Computer Olympiads.

The development and application of a combinatorial sputtering thin film technique to screen potential scintillation material systems was investigated. The technique was first benchmarked by exploring the binary lutetium oxide-silicon oxide material system, which successfully identified the luminescence phases of the system, Lu2SiO5 (LSO) and Lu2Si2O7 (LPS). The second application was to optimize the activator concentration in cerium doped LSO. The successfully optimized cerium concentration in the thin film LSO of 0.34 atomic percent was much greater than the standard cerium concentration in single crystal LSO. This lead to an intensive study based on temperature dependent steady-state and lifetime photoluminescence spectroscopy to understand the different concentration quenching mechanisms involved in the bulk single crystal versus the thin film LSO. The results were used to develop configuration coordinate models which were employed to explain the observed concentration dependent behavior. The nature of single crystal LSO:Ce concentration quenching was determined to be due to radiative energy transfer, and ultimately self-absorption. For the thin films it was found self-absorption was not a dominant factor due to the thin dimension of the film and also its nano-crystalline nature. Instead, the photoluminescence excitation and emission spectra as a function of concentration demonstrated the concentration quenching behavior was due to an increase in defect-mediated non-radiative transitions with increasing cerium. The final application of the thin film screening technique was the exploration of the ternary Lu2O3-SiO2-Al2O3 material system doped with cerium. It was found that the presence of aluminum and silicon hindered LSO and Al5Lu3O12 (LuAG) emission, respectively. However, the presence of aluminum was found to increase LPS emission intensity. The percent of aluminum in the LPS phase was estimated at 2.5 atomic percent.

The family 1 cellulose-binding modules (CBM1) form a groupof small, stable carbohydrate-binding proteins. These modulesare essential for fungal cellulosedegradation. This thesisdescribes both functional studies of the CBM1s as well asprotein engineering of the modules for several objectives. The characteristics and specificity of CBM1s from theTrichoderma reeseiCel7A and Cel6A, along with severalother wild type and mutated CBMs, were studied using bindingexperiments and transmission electron microscopy (TEM). Datafrom the binding studies confirmed that the presence of onetryptophan residue on the CBM1 binding face enhances itsbinding to crystalline cellulose. The twoT. reeseiCBM1s as well as the CBM3 from theClostridium thermocellumCipA were investigated by TEMexperiments. All three CBMs were found to bind in lineararrangements along the sides of the fibrils. Further analysesof the bound CBMs indicated that the CBMs bind to the exposedhydrophobic surfaces, the so called (200) crystalline face ofValoniacellulose crystals. The function and specificity of CBM1s as a part of an intactenzyme were studied by replacing the CBM from the exo-actingCel7A by the CBM1 from the endoglucanase Cel7B. Apart fromslightly improved affinity of the hybrid enzyme, the moduleexchange did not significantly influence the function of theCel7A. This indicates that the two CBM1s are analogous in theirbinding properties and function during cellulosehydrolysis. The CBM1 was also used for immobilization studies. Toimprove heterologous expression of a CBM1-lipase fusionprotein, a linker stability study was carried out inPichia pastoris. A proline/threonine rich linker peptidewas found to be stable for protein production in this host. Forwhole bacterial cell immobilization, theT. reeseiCel6A CBM1 was expressed on the surface of thegram-positive bacteria,Staphylococcus carnosus. The engineeredS. carnosuscells were shown to bind cellulosefibers. To exploit the stable CBM1 fold as a starting point forgenerating novel binders, a phage display library wasconstructed. Binding proteins against an amylase as well asagainst a metal ion were selected from the library. Theamylase-binding proteins were found to bind and inhibit thetarget enzyme. The metal binding proteins selected from thelibrary were cloned on the surface of theS. carnosusand clearly enhanced the metal bindingability of the engineered bacteria. <b>Keywords</b>: cellulose-binding, family 1carbohydrate-binding module, phage display, bacterial surfacedisplay, combinatorial protein library, metal binding, proteinengineering,Trichoderma reesei, Staphyloccus carnosus.

A design of anautomatic network capacity markets, oftenreferred to as a bandwidth market, is presented. Three topicsare investigated. First, a network model is proposed. Theproposed model is based upon a trisection of the participantroles into network users, network owners, and market middlemen.The network capacity is defined in a way that allows it to betraded, and to have a well defined price. The network devicesare modeled as core nodes, access nodes, and border nodes.Requirements on these are given. It is shown how theirfunctionalities can be implemented in a network. Second, asimulated capacity market is presented, and a statisticalmethod for estimating the price dynamics in the market isproposed. A method for pricing network services based on sharedcapacity is proposed, in which the price of a service isequivalent to that of a financial derivative contract on anumber of simple capacity shares.Third, protocols for theinteraction between the participants are proposed. The marketparticipants need to commit to contracts with an auditableprotocol with a small overhead. The proposed protocol is basedon a public key infrastructure and on known protocols for multiparty contract signing. The proposed model allows networkcapacity to be traded in a manner that utilizes the networkeciently. A new feature of this market model, compared to othernetwork capacity markets, is that the prices are not controlledby the network owners. It is the end-users who, by middlemen,trade capacity among each-other. Therefore, financial, ratherthan control theoretic, methods are used for the pricing ofcapacity. <b>Keywords:</b>Computer network architecture, bandwidthtrading, inter-domain Quality-of-Service, pricing,combinatorial allocation, financial derivative pricing,stochastic modeling