945 resultados para lipid-lowering agents


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Tese de doutoramento, Farmácia (Biologia Celular e Molecular), Universidade de Lisboa, Faculdade de Farmácia, 2016

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Sexual dimorphism in adiposity is well described in adults, but the age at which differences first manifest is uncertain. Using a prospective cohort, we describe longitudinal changes in directly measured adiposity and intrahepatocellular lipid (IHCL) in relation to sex in healthy term infants. At median ages of 13 and 63 days, infants underwent quantification of adipose tissue depots by whole-body magnetic resonance imaging and measurement of IHCL by in vivo proton magnetic resonance spectroscopy. Longitudinal data were obtained from 70 infants (40 boys and 30 girls). In the neonatal period girls are more adipose in relation to body size than boys. At follow-up (median age 63 days), girls remained significantly more adipose. The greater relative adiposity that characterises girls is explained by more subcutaneous adipose tissue and this becomes increasingly apparent by follow-up. No significant sex differences were seen in IHCL. Sex-specific differences in infant adipose tissue distribution are in keeping with those described in later life, and suggest that sexual dimorphism in adiposity is established in early infancy.

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Much recent commentary on citizen media has focused on online platforms as means through which citizens may disseminate self-produced media content that challenges dominant discourses or makes visible hidden realities. This chapter goes beyond a concern with media content to explore the much broader range of socially situated practices that develop around citizen media. Drawing on Couldry’s proposal for a practice paradigm in media research, it suggests shifting the focus from ‘citizen media’ to ‘citizen media practices’ and demonstrates, through a case study of communication activism in the World Social Forum, how this framework can bring into view a broad range of citizen media practices (beyond those directly concerned with the production and circulation of media content), the different forms of agency that such practices make possible, and the social fabric they can help generate. I conclude by arguing that a practice framework necessitates a rethink of the way that the concept of (counter-) publics is used in the context of citizen media. Citizen media practices of the kind described here can be understood not only as practices of ‘making public’ previously unreported issues and perspectives, but as practices of public¬-making: practices that support the formation of publics.

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Background: Parenteral nutrition is central to the care of very immature infants. Current international recommendations favor higher amino acid intakes and fish oil–containing lipid emulsions. Objective: The aim of this trial was to compare 1) the effects of high [immediate recommended daily intake (Imm-RDI)] and low [incremental introduction of amino acids (Inc-AAs)] parenteral amino acid delivery within 24 h of birth on body composition and 2) the effect of a multicomponent lipid emulsion containing 30% soybean oil, 30% medium-chain triglycerides, 25% olive oil, and 15% fish oil (SMOF) with that of soybean oil (SO)-based lipid emulsion on intrahepatocellular lipid (IHCL) content. Design: We conducted a 2-by-2 factorial, double-blind, multicenter randomized controlled trial. Results: We randomly assigned 168 infants born at ,31 wk of gestation. We evaluated outcomes at term in 133 infants. There were no significant differences between Imm-RDI and Inc-AA groups for nonadipose mass [adjusted mean difference: 1.0 g (95% CI: 2108, 111 g; P = 0.98)] or between SMOF and SO groups for IHCL [adjusted mean SMOF:SO ratio: 1.1 (95% CI: 0.8, 1.6; P = 0.58]. SMOF does not affect IHCL content. There was a significant interaction (P = 0.05) between the 2 interventions for nonadipose mass. There were no significant interactions between group differences for either primary outcome measure after adjusting for additional confounders. Imm-RDI infants were more likely than Inc-AA infants to have blood urea nitrogen concentrations .7 mmol/L or .10 mmol/L, respectively (75% compared with 49%, P , 0.01; 49% compared with 18%, P , 0.01). Head circumference at term was smaller in the Imm-RDI group [mean difference: 20.8 cm (95% CI: 21.5, 20.1 cm; P = 0.02)]. There were no significant differences in any prespecified secondary outcomes, including adiposity, liver function tests, incidence of conjugated hyperbilirubinemia, weight, length, mortality, and brain volumes. Conclusion: Imm-RDI of parenteral amino acids does not benefit body composition or growth to term and may be harmful. This trial was registered at www.isrctn.com as ISRCTN29665319 and at eudract.ema.europa.eu as EudraCT 2009-016731-34.

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Electricity markets are complex environments, involving numerous entities trying to obtain the best advantages and profits while limited by power-network characteristics and constraints.1 The restructuring and consequent deregulation of electricity markets introduced a new economic dimension to the power industry. Some observers have criticized the restructuring process, however, because it has failed to improve market efficiency and has complicated the assurance of reliability and fairness of operations. To study and understand this type of market, we developed the Multiagent Simulator of Competitive Electricity Markets (MASCEM) platform based on multiagent simulation. The MASCEM multiagent model includes players with strategies for bid definition, acting in forward, day-ahead, and balancing markets and considering both simple and complex bids. Our goal with MASCEM was to simulate as many market models and player types as possible. This approach makes MASCEM both a short- and mediumterm simulation as well as a tool to support long-term decisions, such as those taken by regulators. This article proposes a new methodology integrated in MASCEM for bid definition in electricity markets. This methodology uses reinforcement learning algorithms to let players perceive changes in the environment, thus helping them react to the dynamic environment and adapt their bids accordingly.

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Competitive electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is an electricity market simulator able to model market players and simulate their operation in the market. As market players are complex entities, having their characteristics and objectives, making their decisions and interacting with other players, a multi-agent architecture is used and proved to be adequate. MASCEM players have learning capabilities and different risk preferences. They are able to refine their strategies according to their past experience (both real and simulated) and considering other agents’ behavior. Agents’ behavior is also subject to its risk preferences.

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This paper consist in the establishment of a Virtual Producer/Consumer Agent (VPCA) in order to optimize the integrated management of distributed energy resources and to improve and control Demand Side Management DSM) and its aggregated loads. The paper presents the VPCA architecture and the proposed function-based organization to be used in order to coordinate the several generation technologies, the different load types and storage systems. This VPCA organization uses a frame work based on data mining techniques to characterize the costumers. The paper includes results of several experimental tests cases, using real data and taking into account electricity generation resources as well as consumption data.

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The main purpose of this paper is to propose a Multi-Agent Autonomic and Bio-Inspired based framework with selfmanaging capabilities to solve complex scheduling problems using cooperative negotiation. Scheduling resolution requires the intervention of highly skilled human problem-solvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing (AC) evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference.

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Electricity markets are complex environments with very particular characteristics. A critical issue regarding these specific characteristics concerns the constant changes they are subject to. This is a result of the electricity markets’ restructuring, which was performed so that the competitiveness could be increased, but it also had exponential implications in the increase of the complexity and unpredictability in those markets scope. The constant growth in markets unpredictability resulted in an amplified need for market intervenient entities in foreseeing market behaviour. The need for understanding the market mechanisms and how the involved players’ interaction affects the outcomes of the markets, contributed to the growth of usage of simulation tools. Multi-agent based software is particularly well fitted to analyze dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This dissertation presents ALBidS – Adaptive Learning strategic Bidding System, a multiagent system created to provide decision support to market negotiating players. This system is integrated with the MASCEM electricity market simulator, so that its advantage in supporting a market player can be tested using cases based on real markets’ data. ALBidS considers several different methodologies based on very distinct approaches, to provide alternative suggestions of which are the best actions for the supported player to perform. The approach chosen as the players’ actual action is selected by the employment of reinforcement learning algorithms, which for each different situation, simulation circumstances and context, decides which proposed action is the one with higher possibility of achieving the most success. Some of the considered approaches are supported by a mechanism that creates profiles of competitor players. These profiles are built accordingly to their observed past actions and reactions when faced with specific situations, such as success and failure. The system’s context awareness and simulation circumstances analysis, both in terms of results performance and execution time adaptation, are complementary mechanisms, which endow ALBidS with further adaptation and learning capabilities.

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Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

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The most consumed squid species worldwide were characterized regarding their concentrations of minerals, fatty acids, cholesterol and vitamin E. Interspecific comparisons were assessed among species and geographical origin. The health benefits derived from squid consumption were assessed based on daily minerals intake and on nutritional lipid quality indexes. Squids contribute significantly to daily intake of several macro (Na, K, Mg and P) and micronutrients (Cu, Zn and Ni). Despite their low fat concentration, they are rich in long-chain omega-3 fatty acids, particularly docosahexaenoic (DHA) and eicosapentanoic (EPA) acids, with highly favorable ω-3/ω-6 ratios (from 5.7 to 17.7), reducing the significance of their high cholesterol concentration (140–549 mg/100 g ww). Assessment of potential health risks based on minerals intake, non-carcinogenic and carcinogenic risks indicated that Loligo gahi (from Atlantic Ocean), Loligo opalescens (from Pacific Ocean) and Loligo duvaucelii (from Indic Ocean) should be eaten with moderation due to the high concentrations of Cu and/or Cd. Canonical discriminant analysis identified the major fatty acids (C14:0, C18:0, C18:1, C18:3ω-3, C20:4ω-6 and C22:5ω-6), P, K, Cu and vitamin E as chemical discriminators for the selected species. These elements and compounds exhibited the potential to prove authenticity of the commercially relevant squid species.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics