994 resultados para Apolipoprotéine AI


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Three organophosphorus compounds- malathion, folithion and temephos- and two synthetic pyrethroids- alphamethrin and deltamethrin- were used for monitoring the susceptibility status of larvae and adults of six vector mosquitoe species: Culex quinquefasciatus (Filariasis) and Aedes albopictus (Dengue) (both laboratory and field strains); laboratory strains of Aedes aegypti (Dengue), Anopheles slephensi and Anopheles culicifacies (Malaria), and Culex tritaeniorhynchus (Japanese encephalitis) in India. From the LC50 values obtained for these insecticides, it was found that all mosquito species including the field strains of Cx. quinquefasciatus and Ae. albopictus were highly susceptible Except for Cx. quinquefasciatus (field strain) against malathion, 100% mortality was observed at the discriminating dosages recommended by World Health Organization. The residual effect of alphamethrin, deltamethrin, malathion and folithion at 25 mg (ai)/m² on different surfaces against six species of vector mosquitoes showed that alphamethrin was the most effective on all four treated surfaces (mud, plywood, cement and thatch). Nevertheless, residual efficacy lasted longer on thatch than on the other surfaces. Therefore, synthetic pyrethroids such as alphamethrin can be effectively employed in integrated vector control operations.

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A series of large area single layers and glass/ZnO:AVp(SixC1-x:H)/i(Si:H)/n(SixC1-x:H)/AI (0 < x < 1) heterojunction cells were produced by plasma-enhanced chemical vapour deposition (PE-CVD) at low temperature. Junction properties, carrier transport and photogeneration are investigated from dark and illuminated current-voltage (J-V) and capacitance-voltage (C-V) characteristics. For the heterojunction cells atypical J-V characteristics under different illumination conditions are observed leading to poor fill factors. High series resistances around 106 Q are also measured. These experimental results were used as a basis for the numerical simulation of the energy band diagram, and the electrical field distribution of the structures. Further comparison with the sensor performance gave satisfactory agreement. Results show that the conduction band offset is the most limiting parameter for the optimal collection of the photogenerated carriers. As the optical gap increases and the conductivity of the doped layers decreases, the transport mechanism changes from a drift to a diffusion-limited process.

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Power system organization has gone through huge changes in the recent years. Significant increase in distributed generation (DG) and operation in the scope of liberalized markets are two relevant driving forces for these changes. More recently, the smart grid (SG) concept gained increased importance, and is being seen as a paradigm able to support power system requirements for the future. This paper proposes a computational architecture to support day-ahead Virtual Power Player (VPP) bid formation in the smart grid context. This architecture includes a forecasting module, a resource optimization and Locational Marginal Price (LMP) computation module, and a bid formation module. Due to the involved problems characteristics, the implementation of this architecture requires the use of Artificial Intelligence (AI) techniques. Artificial Neural Networks (ANN) are used for resource and load forecasting and Evolutionary Particle Swarm Optimization (EPSO) is used for energy resource scheduling. The paper presents a case study that considers a 33 bus distribution network that includes 67 distributed generators, 32 loads and 9 storage units.

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Artificial intelligence techniques are being widely used to face the new reality and to provide solutions that can make power systems undergo all the changes while assuring high quality power. In this way, the agents that act in the power industry are gaining access to a generation of more intelligent applications, making use of a wide set of AI techniques. Knowledge-based systems and decision-support systems have been applied in the power and energy industry. This article is intended to offer an updated overview of the application of artificial intelligence in power systems. This article paper is organized in a way so that readers can easily understand the problems and the adequacy of the proposed solutions. Because of space constraints, this approach can be neither complete nor sufficiently deep to satisfy all readers’ needs. As this is amultidisciplinary area, able to attract both software and computer engineering and power system people, this article tries to give an insight into themost important concepts involved in these applications. Complementary material can be found in the reference list, providing deeper and more specific approaches.

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Mestrado em Contabilidade

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Lisbon is the largest urban area in the Western European coast. Due to this geographical position the Atlantic Ocean serves as an important source of particles and plays an important role in many atmospheric processes. The main objectives of this study were to (1) perform a chemical characterization of particulate matter (PM2.5) sampled in Lisbon, (2) identify the main sources of particles, (3) determine PM contribution to this urban area, and (4) assess the impact of maritime air mass trajectories on concentration and composition of respirable PM sampled in Lisbon. During 2007, PM2.5 was collected on a daily basis in the center of Lisbon with a Partisol sampler. The exposed Teflon filters were measured by gravimetry and cut into two parts: one for analysis by instrumental neutron activation analysis (INAA) and the other by ion chromatography (IC). Principal component analysis (PCA) and multilinear regression analysis (MLRA) were used to identify possible sources of PM2.5 and determine mass contribution. Five main groups of sources were identified: secondary aerosols, traffic, calcium, soil, and sea. Four-day backtracking trajectories ending in Lisbon at the starting sampling time were calculated using the HYSPLIT model. Results showed that maritime transport scenarios were frequent. These episodes were characterized by a significant decrease of anthropogenic aerosol concentrations and exerted a significant role on air quality in this urban area.

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Childhood excessive weight and obesity are a major public health concern from early childhood. Early childhood is an important period of development for developing healthy eating habits, that may be associated with an adequate present/future BMI. There is extensive evidence that children’s food intake is shaped by early experiences, suggesting ways in which parenting practices may be promoting obesity. But what leads parents to endorse healthier or detrimental educational practices and routines needs further study. 1. Perception of children’s weight: parents of overweight or obese children often fail to correctly perceive their children as overweight; failing to recognize their children’s excessive weight may impeach parents from implementing the best educational practices. 2. Concern: relation between the adequacy of mothers perception of their children’s weight and the level of concern - parental concern is be associated with parental practices. 3. Attribution of control: also, if parents do not consider their children’s eating behavior at least partially controllable by them, they may relinquish some of their responsibility in this area. Self-efficacy: evidence linking parental self-efficacy to parent competence and to parenting practices and behaviors; low parental self-efficacy related to the control of everyday behavior of young children may lead parents to abandon more consistent health practices and endorse permissive and inconsistent strategies. We designed 2 sequential studies that aim to contribute to the understanding of cognitive determinants of children’s eating patterns.

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Swarm Intelligence (SI) is a growing research field of Artificial Intelligence (AI). SI is the general term for several computational techniques which use ideas and get inspiration from the social behaviours of insects and of other animals. This paper presents hybridization and combination of different AI approaches, like Bio-Inspired Techniques (BIT), Multi-Agent systems (MAS) and Machine Learning Techniques (ML T). The resulting system is applied to the problem of jobs scheduling to machines on dynamic manufacturing environments.

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Involving groups in important management processes such as decision making has several advantages. By discussing and combining ideas, counter ideas, critical opinions, identified constraints, and alternatives, a group of individuals can test potentially better solutions, sometimes in the form of new products, services, and plans. In the past few decades, operations research, AI, and computer science have had tremendous success creating software systems that can achieve optimal solutions, even for complex problems. The only drawback is that people don’t always agree with these solutions. Sometimes this dissatisfaction is due to an incorrect parameterization of the problem. Nevertheless, the reasons people don’t like a solution might not be quantifiable, because those reasons are often based on aspects such as emotion, mood, and personality. At the same time, monolithic individual decisionsupport systems centered on optimizing solutions are being replaced by collaborative systems and group decision-support systems (GDSSs) that focus more on establishing connections between people in organizations. These systems follow a kind of social paradigm. Combining both optimization- and socialcentered approaches is a topic of current research. However, even if such a hybrid approach can be developed, it will still miss an essential point: the emotional nature of group participants in decision-making tasks. We’ve developed a context-aware emotion based model to design intelligent agents for group decision-making processes. To evaluate this model, we’ve incorporated it in an agent-based simulator called ABS4GD (Agent-Based Simulation for Group Decision), which we developed. This multiagent simulator considers emotion- and argument based factors while supporting group decision-making processes. Experiments show that agents endowed with emotional awareness achieve agreements more quickly than those without such awareness. Hence, participant agents that integrate emotional factors in their judgments can be more successful because, in exchanging arguments with other agents, they consider the emotional nature of group decision making.

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Jornadas "Ciência nos Açores – que futuro? Tema Ciências Naturais e Ambiente", Ponta Delgada, 7-8 de Junho de 2013.

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Jornadas "Ciência nos Açores – que futuro? Tema Ciências Naturais e Ambiente", Ponta Delgada, 7-8 de Junho de 2013.

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Jornadas "Ciência nos Açores – que futuro? Tema Ciências Naturais e Ambiente", Ponta Delgada, 7-8 de Junho de 2013.

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Jornadas "Ciência nos Açores – que futuro? Tema Ciências Naturais e Ambiente", Ponta Delgada, 7-8 de Junho de 2013.

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Fishing decreases the biomass of target species via reduction in the numbers and/or size of individuals. In natural systems, the strength of biological interactions, including predator-prey dynamics, are often density or size-dependent. Hence, changes in the numbers or size of key taxa may be expected to influence biological interactions but their effects do not need to be identical. Here we compare the effects of biomass reduction in populations of the exploited limpet Patella candei. Biomass removal was experimentally achieved by either removing individuals (density reduction) or by replacing large by small individuals (size reduction), while controlling for total limpet biomass in a laboratory-based experiment. At the experiment’s termination, biomass reduction led to proportional changes in area grazed. However, there was no difference whether this was achieved via changes in density or in size. Furthermore, no discernible effects of treatments were evident on different components of the algal assemblage. A field survey also revealed that P. candei biomass explained a greater proportion in variation in the area free of algae than density alone. Our results suggest that loss of biomass in populations of P. candei has quantitatively and qualitatively similar effects on algal cover regardless of whether it is caused by an equivalent (biomass) reduction in the numbers or size of individuals.

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Here, we describe the development of sporangial and gametangial conceptacles for Amphiroa beauvoisii and A. vanbosseae; sporangial conceptacles only for A. misakiensis; and gametangial conceptacles only for A. cryptarthrodia and A. rigida. The descriptions are based on the observation of histological preparations obtained from 112 specimens collected from the Gulf of California, in Mexico, and the Azores archipelago of Portugal. Information on the development of the sporangial conceptacle pore and conceptacle senescence is here described and illustrated for the first time. Four development patterns were observed: two for sporangial conceptacles; one for spermatangial conceptacles; and one for carposporangial conceptacles. The phases of development of the sporangial conceptacle were found to be useful in delimiting species within the genus. Based on the sporangium location on the cavity floor and the pore canal anatomy, the species A. beauvoisii, A. misakiensis and A. vanbosseae can be distinguished from each other.