968 resultados para COMBINATORIAL BIOSYNTHESIS
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This paper presents a methodology for applying scheduling algorithms using Monte Carlo simulation. The methodology is based on a decision support system (DSS). The proposed methodology combines a genetic algorithm with a new local search using Monte Carlo Method. The methodology is applied to the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The methodology is tested on a set of standard instances taken from the literature and compared with others. The computation results validate the effectiveness of the proposed methodology. The DSS developed can be utilized in a common industrial or construction environment.
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Wythoff Queens is a classical combinatorial game related to very interesting mathematical results. An amazing one is the fact that the P-positions are given by (⌊├ φn⌋┤┤,├ ├ ⌊φ┤^2 n⌋) and (⌊├ φ^2 n⌋┤┤,├ ├ ⌊φ┤n⌋) where φ=(1+√5)/2. In this paper, we analyze a different version where one player (Left) plays with a chess bishop and the other (Right) plays with a chess knight. The new game (call it Chessfights) lacks a Beatty sequence structure in the P-positions as in Wythoff Queens. However, it is possible to formulate and prove some general results of a general recursive law which is a particular case of a Partizan Subtraction game.
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This paper presents an optimization approach for the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The proposed approach is based on a genetic algorithm technique. The scheduling rules such as SPT and MWKR are integrated into the process of genetic evolution. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities and delay times of the operations are defined by the genetic algorithm. Schedules are constructed using a procedure that generates parameterized active schedules. After a schedule is obtained a local search heuristic is applied to improve the solution. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed approach.
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The container loading problem (CLP) is a combinatorial optimization problem for the spatial arrangement of cargo inside containers so as to maximize the usage of space. The algorithms for this problem are of limited practical applicability if real-world constraints are not considered, one of the most important of which is deemed to be stability. This paper addresses static stability, as opposed to dynamic stability, looking at the stability of the cargo during container loading. This paper proposes two algorithms. The first is a static stability algorithm based on static mechanical equilibrium conditions that can be used as a stability evaluation function embedded in CLP algorithms (e.g. constructive heuristics, metaheuristics). The second proposed algorithm is a physical packing sequence algorithm that, given a container loading arrangement, generates the actual sequence by which each box is placed inside the container, considering static stability and loading operation efficiency constraints.
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Trabalho apresentado no âmbito do European Master in Computational Logics, como requisito parcial para obtenção do grau de Mestre em Computational Logics
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Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Informática, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding the management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.
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Microcystin-leucine and arginine (microcystin- LR) is a cyanotoxin produced by cyanobacteria like Microcystis aeruginosa, and it’s considered a threat to water quality, agriculture, and human health. Rice (Oryzasativa) is a plant of great importance in human food consumption and economy, with extensive use around the world. It is therefore important to assess the possible effects of using water contaminated with microcystin-LR to irrigate rice crops, in order to ensure a safe, high quality product to consumers. In this study, 12 and 20-day-old plants were exposed during 2 or 7 days to a M. aeruginosa extract containing environmentally relevant microcystin-LR concentrations, 0.26–78 lg/L. Fresh and dry weight of roots and leaves, chlorophyll fluorescence, glutathione S-transferase and glutathione peroxidase activities, and protein identification by mass spectrometry through two-dimensional gel electrophoresis from root and leaf tissues, were evaluated in order to gauge the plant’s physiological condition and biochemical response after toxin exposure. Results obtained from plant biomass, chlorophyll fluorescence, and enzyme activity assays showed no significant differences between control and treatment groups. How- ever, proteomics data indicates that plants respond to M. aeruginosa extract containing environmentally relevant microcystin-LR concentrations by changing their metabolism, responding differently to different toxin concentrations. Biological processes most affected were related to protein folding and stress response, protein biosynthesis, cell signalling and gene expression regulation, and energy and carbohydrate metabolism which may denote a toxic effect induced by M. aeruginosa extract and microcystin- LR. Theimplications of the metabolic alterations in plant physiology and growth require further elucidation.
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Dissertação apresentada para a obtenção do Grau de Mestre em Genética Molecular e Biomedicina, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Dissertação para obtenção do Grau de Mestre em Biotecnologia
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Dissertação para obtenção do Grau de Mestre em Genética Molecular e Biomedicina
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RESUMO: Os Staphylococcus aureus resistentes à meticilina (MRSA, do inglês “methicillin-resistant Staphylococcus aureus”) são um dos principais agentes responsáveis por infeções hospitalares. Os MRSA são resistentes a praticamente todos os antibióticos β-lactâmicos devido a dois mecanismos principais: produção de β-lactamase (bla), codificada pelo gene blaZ, e produção de uma proteína de ligação à penicilina (PBP2a, do inglês “penicillin binding protein 2”), codificada pelo gene mecA. Estes dois genes são regulados por sistemas homólogos, constituídos por um sensor-transdutor (BlaR1 e MecR1) e um repressor (BlaI e MecI), de tal modo que ambos os sistemas são capazes de co-regular os genes mecA e blaZ, embora com eficiências de indução muito diferentes. De facto, a indução mediada pelo sistema mecI-mecR1 é tão lenta que se acredita que este sistema não está funcional na maioria das estirpes MRSA. No entanto, dados recentes do nosso laboratório, demonstram a ausência de relação entre a presença do gene mecI e o nível de resistência à meticilina em estirpes MRSA epidémicas, e também que, o fenótipo de resistência da grande maioria das estirpes não é perturbado pela sobre-expressão em trans do repressor mecI. Curiosamente, as duas estirpes em que a expressão da resistência foi afetada pela sobre-expressão do mecI são negativas para o locus da β-lactamase, o que sugere que este locus pode interferir diretamente com a repressão do gene mecA mediada pelo MecI. Nesta tese de mestrado esta hipótese foi explorada usando estratégias de biologia molecular e ensaios fenotípicos da resistência aos -lactâmicos. Os resultados obtidos demonstram que a presença do plasmídeo nativo da β-lactamase não só anula a repressão mediada pelo MecI, como também aumenta o nível de resistência das estirpes parentais. Várias hipóteses foram então formuladas para explicar estas observações. Dados preliminares, em conjunto com evidências experimentais publicadas, sugerem que o BlaI forma hetero-dímeros com o MecI que, após a indução, são inativados eficientemente pelo BlaR1. Em conclusão, estes resultados apresentam novas perspetivas para o mecanismo de regulação do mecA e para uma nova importante função do operão da β-lactamase para o fenótipo das estirpes MRSA.-------------------ABSTRACT: Methicillin-resistant Staphylococcus aureus (MRSA) is an important nosocomial pathogen and is also emerging in the community. MRSA is cross-resistant to virtually all β-lactam antibiotics and has acquired two main resistance mechanisms: production of β-lactamase (bla), coded by blaZ, and production of penicillin binding protein 2a (PBP2a), coded by mecA. Both genes are regulated by homologous sensor-transducers (BlaR1 and MecR1) and repressors (BlaI and MecI), and coregulation of mecA and blaZ by both systems has been demonstrated, although with remarkable different efficiencies. In fact, induction of mecA by mecI-mecR1 is so slow that it is believed it is not functional in most MRSA strains. However, recent data from our laboratory has unexpectedly demonstrated that not only there is no correlation between the presence of mecI gene and the resistance level in epidemic MRSA strains, but also that for most strains there were no significant changes on the resistance phenotype upon the mecI overexpression in trans. Interestingly, the two strains in which mecI overexpression affected the resistance expression were negative for the bla locus, suggesting that this locus may interfere directly with the MecI-mediated repression of mecA and account for those puzzling observations. In this master thesis we have explored this hypothesis using molecular biology strategies and phenotypic analysis of -lactam resistance. The data obtained demonstrate that the presence of a wild-type plasmid containing the bla locus not only disrupts the MecImediated repression, but also significantly enhances the expression of resistance. Several preliminary hypotheses were formulated to explain these observations and preliminary data, together with published evidence, support the working model that BlaI forms functional hetero-dimers with MecI, which upon induction are readily inactivated by BlaR1. These results provide new insights into the regulatory mechanism(s) of mecA and open new perspectives for the role of β-lactamase operon in the MRSA phenotype.
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Microalgae are promising microorganisms for the production of food and fine chemicals. Several species of microalgae are used in aquaculture with the purpose of transfer bioactive compounds up to the aquatic food chain. The main objective of this project was to develop a stress–inducement strategy in order to enhance the biochemical productivity of Nannochloropsis gaditana, Rhodomonas marina and Isochrysis sp. for aquaculture purposes having in account their growth and organizational differences. In this regard, two experiments were design: the first one consisted on the alteration of overall nutrient availabilities in growth medium; and the second one comprised changes in nitrogen and sulfur concentrations maintaining the concentrations of the other nutrients present in a commercial growth medium (Nutribloom plus), which is frequently used in aquaculture. Microalgae dried biomass was characterized biochemically and elemental analysis was also performed for all samples. In first experimental design: linear trends between nutrient availability in growth media and microalgae protein content were obtained; optimum productivities of eicosapentaenoic (EPA) and docosahexaenoic acids (DHA) were attained for both R. marina and N. gaditana in growth media enriched with 1000 L L-1 of nutrient solution whereas for Isochrysis sp. the double of Nutribloom plus was needed; the decrease of glucans and total monosaccharides with nutrient availability for R. marina and Isochrysis sp. showed the occurrence of a possible depletion of carbohydrates towards lipids and proteins biosynthesis. Second experimental desing: N. gaditana exhibited the highest variation in their biochemical composition against the applied perturbation; variations observed for microalgae in their biochemical composition were reflected in their elemental stoichiometry; in N. gaditana the highest nitrogen concentrations lead to overall maximum productivities of the biochemical parameters. The results of the present work show two stress-inducement strategies for microalgae that may constitute a base for further investigations on their biochemical enhancement.
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A Computação Evolutiva enquadra-se na área da Inteligência Artificial e é um ramo das ciências da computação que tem vindo a ser aplicado na resolução de problemas em diversas áreas da Engenharia. Este trabalho apresenta o estado da arte da Computação Evolutiva, assim como algumas das suas aplicações no ramo da eletrónica, denominada Eletrónica Evolutiva (ou Hardware Evolutivo), enfatizando a síntese de circuitos digitais combinatórios. Em primeiro lugar apresenta-se a Inteligência Artificial, passando à Computação Evolutiva, nas suas principais vertentes: os Algoritmos Evolutivos baseados no processo da evolução das espécies de Charles Darwin e a Inteligência dos Enxames baseada no comportamento coletivo de alguns animais. No que diz respeito aos Algoritmos Evolutivos, descrevem-se as estratégias evolutivas, a programação genética, a programação evolutiva e com maior ênfase, os Algoritmos Genéticos. Em relação à Inteligência dos Enxames, descreve-se a otimização por colônia de formigas e a otimização por enxame de partículas. Em simultâneo realizou-se também um estudo da Eletrónica Evolutiva, explicando sucintamente algumas das áreas de aplicação, entre elas: a robótica, as FPGA, o roteamento de placas de circuito impresso, a síntese de circuitos digitais e analógicos, as telecomunicações e os controladores. A título de concretizar o estudo efetuado, apresenta-se um caso de estudo da aplicação dos algoritmos genéticos na síntese de circuitos digitais combinatórios, com base na análise e comparação de três referências de autores distintos. Com este estudo foi possível comparar, não só os resultados obtidos por cada um dos autores, mas também a forma como os algoritmos genéticos foram implementados, nomeadamente no que diz respeito aos parâmetros, operadores genéticos utilizados, função de avaliação, implementação em hardware e tipo de codificação do circuito.
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Dissertation presented to obtain the Ph.D degree in Biology