936 resultados para Two Degrees Of Freedom
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Cloninger's psychobiological model of personality as applied to substance misuse has received mixed support. Contrary to the model, recent data suggest that a combination of high novelty seeking (NS) and high harm avoidance (HA) represents a significant risk for the development of severe substance misuse. A genetic polymorphism previously implicated in severe substance dependence, the A1 allele of the D2 dopamine receptor (DRD2) gene, was examined in relation to NS and HA amongst 203 adolescent boys. Specifically, we hypothesized that subjects with the A1 + allele (A1/A1 and A1/A2 genotypes) would report stronger NS and would exhibit a more positive relationship between NS and HA than those with the A1-allele (A2/A2 genotypes). These predictions were supported. The correlation between NS and HA in 81 A1 + allelic boys (r = 0.27, P = 0.02), and that in the 122 A1- allelic boys (r = -0.15, P = 0.09), indicated that this relationship differed according to allelic status (F = 8.52, P < 0:004). Among those with the A1-allele, the present results are consistent with the traditional view that novelty seeking provides positive reinforcement, or the fulfillment of appetitive drives. In contrast, novelty seeking in those with the A1 + allele appears to include a negative reinforcement or self-medicating function. (C) 2002 Elsevier Science Ltd. All rights reserved.
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Lipid, protein, ash, carbohydrate and water content and energy density of eggs were measured from different clutches over a range of egg size in two species of freshwater turtle. Dry egg contents consisted of protein (54-60%), lipid (25-31%) and ash (5-6%) while carbohydrate was found to be negligible (
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The ABA-deficient wilty pea (Pisum sativum L.) and its wild-type (WT) were grown at two levels of nitrogen supply (0.5 and 5.0 mM) for 5-6 weeks from sowing, to determine whether leaf ABA status altered the leaf growth response to N deprivation. Plants were grown at high relative humidity to prevent wilting of the wilty peas. Irrespective of N supply, expanding wilty leaflets had ca 50% less ABA than WT leaflets but similar ethylene evolution rates. Fully expanded wilty leaflets had lower relative water contents (RWC) and were 10-60% smaller in area (according to the node of measurement) than WT leaflets. However, there were no genotypic differences in plant relative leaf expansion rate (RLER). Growth of both genotypes at 0.5 mM N increased the RWC of fully expanded leaflets, but did not alter ethylene evolution or ABA concentration of expanding leaflets. Plants grown at 0.5 mM N showed a 20-30% reduction in RLER, which was similar in magnitude in both wilty and WT peas. Thus, leaf ABA status did not alter the leaf growth response to N deprivation.
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Mutations in the E1alpha subunit of the pyruvate dehydrogenase multienzyme complex may result in congenital lactic acidosis, but little is known about the consequences of these mutations at the enzymatic level. Here we characterize two mutants (F205L and T231A) of human pyruvate dehydrogenase in vitro, using the enzyme expressed in Escherichia coli. Wild-type and mutant proteins were purified successfully and their kinetic parameters were measured. F205L shows impaired binding of the thiamin diphosphate cofactor, which may explain why patients carrying this mutation respond to high-dose vitamin B-1 therapy. T231A has very low activity and a greatly elevated K-m for pyruvate, and this combination of effects would be expected to result in severe lactic acidosis. The results lead to a better understanding of the consequences of these mutations on the functional and structural properties of the enzyme, which may lead to improved therapies for patients carrying these mutations.
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Based on the refined non-conforming element method for geometric nonlinear analysis, a refined nonlinear non-conforming triangular plate element is constructed using the Total Lagrangian (T.L.) and the Updated Lagrangian (U.L.) approach. The refined nonlinear non-conforming triangular plate element is based on the Allman's triangular plane element with drilling degrees of freedom [1] and the refined non-conforming triangular plate element RT9 [2]. The element is used to analyze the geometric nonlinear behavior of plates and the numerical examples show that the refined non-conforming triangular plate element by the T.L. and U.L. approach can give satisfactory results. The computed results obtained from the T.L. and U.L. approach for the same numerical examples are somewhat different and the reasons for the difference of the computed results are given in detail in this paper. © 2003 Elsevier Science Ltd. All rights reserved.
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The aim of the present study was to evaluate water consumption, use efficiency and yield components of sunflower variety Embrapa 122 V/2000 cultivated in two types of soil (Fluvissol and Haplic Luvisol) subjected to increasing doses of cattle manure. The experiment was carried out in a greenhouse at Universidade Estadual da Paraíba. The experimental design was completely randomized in a factorial scheme. The irrigation was performed every other day, replacing the water absorbed by the plants. The water consumption and the use efficiency were evaluated, being the use efficiency determined by the ratio of the total dry mass of sunflower and the amount of water used to produce it in each treatment. Plants were harvested at 95 days after sowing when the following parameters were evaluated: number of seeds per plant, weight of seeds per plant, weight of 1000 seeds and the outer diameter of the capitulum (head). The results showed that the sunflower was positively affected by cattle manure application, increasing the production components and the water use efficiency, regardless of the type of soil. Excepting for the 1000 seeds weight and the water use efficiency, the type of soil affected significantly the water use, the number and weight of seeds per plant. The plants cultivated in Haplic Luvisol had a better performance.
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O presente trabalho teve como objectivos avaliar a influência de diversas grandezas e parâmetros de ensaio no índice de fluidez de termoplásticos e calcular a incerteza associada às determinações. Numa primeira fase, procedeu-se à identificação dos principais parâmetros que influenciam a determinação do índice de fluidez, tendo sido seleccionados a temperatura do plastómetro, o peso de carga, o diâmetro da fieira, o comprimento da medição, o tipo de corte e o número de provetes. Para avaliar a influência destes parâmetros na medição do índice de fluidez, optou-se pela realização de um planeamento de experiências, o qual foi dividido em três etapas. Para o tratamento dos resultados obtidos utilizou-se como ferramenta a análise de variância. Após a completa análise dos desenhos factoriais, verificou-se que os efeitos dos factores temperatura do plastómetro, peso de carga e diâmetro da fieira apresentam um importante significado estatístico na medição do índice de fluidez. Na segunda fase, procedeu-se ao cálculo da incerteza associada às medições. Para tal seleccionou-se um dos métodos mais usuais, referido no Guia para a Expressão da Incerteza da Medição, conhecido como método GUM, e pela utilização da abordagem “passo a passo”. Inicialmente, foi necessária a construção de um modelo matemático para a medição do índice de fluidez que relacionasse os diferentes parâmetros utilizados. Foi estudado o comportamento de cada um dos parâmetros através da utilização de duas funções, recorrendo-se novamente à análise de variância. Através da lei de propagação das incertezas foi possível determinar a incerteza padrão combinada,e após estimativa do número de graus de liberdade, foi possível determinar o valor do coeficiente de expansão. Finalmente determinou-se a incerteza expandida da medição, relativa à determinação do índice de fluidez em volume.
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A presente dissertação apresenta uma solução para o problema de modelização tridimensional de galerias subterrâneas. O trabalho desenvolvido emprega técnicas provenientes da área da robótica móvel para obtenção um sistema autónomo móvel de modelização, capaz de operar em ambientes não estruturados sem acesso a sistemas de posicionamento global, designadamente GPS. Um sistema de modelização móvel e autónomo pode ser bastante vantajoso, pois constitui um método rápido e simples de monitorização das estruturas e criação de representações virtuais das galerias com um elevado nível de detalhe. O sistema de modelização desloca-se no interior dos túneis para recolher informações sensoriais sobre a geometria da estrutura. A tarefa de organização destes dados com vista _a construção de um modelo coerente, exige um conhecimento exacto do percurso praticado pelo sistema, logo o problema de localização da plataforma sensorial tem que ser resolvido. A formulação de um sistema de localização autónoma tem que superar obstáculos que se manifestam vincadamente nos ambientes underground, tais como a monotonia estrutural e a já referida ausência de sistemas de posicionamento global. Neste contexto, foi abordado o conceito de SLAM (Simultaneous Loacalization and Mapping) para determinação da localização da plataforma sensorial em seis graus de liberdade. Seguindo a abordagem tradicional, o núcleo do algoritmo de SLAM consiste no filtro de Kalman estendido (EKF { Extended Kalman Filter ). O sistema proposto incorpora métodos avançados do estado da arte, designadamente a parametrização em profundidade inversa (Inverse Depth Parametrization) e o método de rejeição de outliers 1-Point RANSAC. A contribuição mais importante do método por nós proposto para o avanço do estado da arte foi a fusão da informação visual com a informação inercial. O algoritmo de localização foi testado com base em dados reais, adquiridos no interior de um túnel rodoviário. Os resultados obtidos permitem concluir que, ao fundir medidas inerciais com informações visuais, conseguimos evitar o fenómeno de degeneração do factor de escala, comum nas aplicações de localização através de sistemas puramente monoculares. Provámos simultaneamente que a correcção de um sistema de localização inercial através da consideração de informações visuais é eficaz, pois permite suprimir os desvios de trajectória que caracterizam os sistemas de dead reckoning. O algoritmo de modelização, com base na localização estimada, organiza no espaço tridimensional os dados geométricos adquiridos, resultando deste processo um modelo em nuvem de pontos, que posteriormente _e convertido numa malha triangular, atingindo-se assim uma representação mais realista do cenário original.
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Consider the problem of scheduling a set of implicitdeadline sporadic tasks on a heterogeneous multiprocessor so as to meet all deadlines. Tasks cannot migrate and the platform is restricted in that each processor is either of type-1 or type-2 (with each task characterized by a different speed of execution upon each type of processor). We present an algorithm for this problem with a timecomplexity of O(n·m), where n is the number of tasks and m is the number of processors. It offers the guarantee that if a task set can be scheduled by any non-migrative algorithm to meet deadlines then our algorithm meets deadlines as well if given processors twice as fast. Although this result is proven for only a restricted heterogeneous multiprocessor, we consider it significant for being the first realtime scheduling algorithm to use a low-complexity binpacking approach to schedule tasks on a heterogeneous multiprocessor with provably good performance.
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Adhesive-bonding for the unions in multi-component structures is gaining momentum over welding, riveting and fastening. It is vital for the design of bonded structures the availability of accurate damage models, to minimize design costs and time to market. Cohesive Zone Models (CZM’s) have been used for fracture prediction in structures. The eXtended Finite Element Method (XFEM) is a recent improvement of the Finite Element Method (FEM) that relies on traction-separation laws similar to those of CZM’s but it allows the growth of discontinuities within bulk solids along an arbitrary path, by enriching degrees of freedom. This work proposes and validates a damage law to model crack propagation in a thin layer of a structural epoxy adhesive using the XFEM. The fracture toughness in pure mode I (GIc) and tensile cohesive strength (sn0) were defined by Double-Cantilever Beam (DCB) and bulk tensile tests, respectively, which permitted to build the damage law. The XFEM simulations of the DCB tests accurately matched the experimental load-displacement (P-d) curves, which validated the analysis procedure.
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A thesis submitted for the degree of Doctor of Philosophy
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In the last twenty years genetic algorithms (GAs) were applied in a plethora of fields such as: control, system identification, robotics, planning and scheduling, image processing, and pattern and speech recognition (Bäck et al., 1997). In robotics the problems of trajectory planning, collision avoidance and manipulator structure design considering a single criteria has been solved using several techniques (Alander, 2003). Most engineering applications require the optimization of several criteria simultaneously. Often the problems are complex, include discrete and continuous variables and there is no prior knowledge about the search space. These kind of problems are very more complex, since they consider multiple design criteria simultaneously within the optimization procedure. This is known as a multi-criteria (or multiobjective) optimization, that has been addressed successfully through GAs (Deb, 2001). The overall aim of multi-criteria evolutionary algorithms is to achieve a set of non-dominated optimal solutions known as Pareto front. At the end of the optimization procedure, instead of a single optimal (or near optimal) solution, the decision maker can select a solution from the Pareto front. Some of the key issues in multi-criteria GAs are: i) the number of objectives, ii) to obtain a Pareto front as wide as possible and iii) to achieve a Pareto front uniformly spread. Indeed, multi-objective techniques using GAs have been increasing in relevance as a research area. In 1989, Goldberg suggested the use of a GA to solve multi-objective problems and since then other researchers have been developing new methods, such as the multi-objective genetic algorithm (MOGA) (Fonseca & Fleming, 1995), the non-dominated sorted genetic algorithm (NSGA) (Deb, 2001), and the niched Pareto genetic algorithm (NPGA) (Horn et al., 1994), among several other variants (Coello, 1998). In this work the trajectory planning problem considers: i) robots with 2 and 3 degrees of freedom (dof ), ii) the inclusion of obstacles in the workspace and iii) up to five criteria that are used to qualify the evolving trajectory, namely the: joint traveling distance, joint velocity, end effector / Cartesian distance, end effector / Cartesian velocity and energy involved. These criteria are used to minimize the joint and end effector traveled distance, trajectory ripple and energy required by the manipulator to reach at destination point. Bearing this ideas in mind, the paper addresses the planning of robot trajectories, meaning the development of an algorithm to find a continuous motion that takes the manipulator from a given starting configuration up to a desired end position without colliding with any obstacle in the workspace. The chapter is organized as follows. Section 2 describes the trajectory planning and several approaches proposed in the literature. Section 3 formulates the problem, namely the representation adopted to solve the trajectory planning and the objectives considered in the optimization. Section 4 studies the algorithm convergence. Section 5 studies a 2R manipulator (i.e., a robot with two rotational joints/links) when the optimization trajectory considers two and five objectives. Sections 6 and 7 show the results for the 3R redundant manipulator with five goals and for other complementary experiments are described, respectively. Finally, section 8 draws the main conclusions.
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Estruturas
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Generating manipulator trajectories considering multiple objectives and obstacle avoidance is a non-trivial optimization problem. In this paper a multi-objective genetic algorithm based technique is proposed to address this problem. Multiple criteria are optimized considering up to five simultaneous objectives. Simulation results are presented for robots with two and three degrees of freedom, considering two and five objectives optimization. A subsequent analysis of the spread and solutions distribution along the converged non-dominated Pareto front is carried out, in terms of the achieved diversity.
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