110 resultados para Maximal aerobic power
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Radio link quality estimation is essential for protocols and mechanisms such as routing, mobility management and localization, particularly for low-power wireless networks such as wireless sensor networks. Commodity Link Quality Estimators (LQEs), e.g. PRR, RNP, ETX, four-bit and RSSI, can only provide a partial characterization of links as they ignore several link properties such as channel quality and stability. In this paper, we propose F-LQE (Fuzzy Link Quality Estimator, a holistic metric that estimates link quality on the basis of four link quality properties—packet delivery, asymmetry, stability, and channel quality—that are expressed and combined using Fuzzy Logic. We demonstrate through an extensive experimental analysis that F-LQE is more reliable than existing estimators (e.g., PRR, WMEWMA, ETX, RNP, and four-bit) as it provides a finer grain link classification. It is also more stable as it has lower coefficient of variation of link estimates. Importantly, we evaluate the impact of F-LQE on the performance of tree routing, specifically the CTP (Collection Tree Protocol). For this purpose, we adapted F-LQE to build a new routing metric for CTP, which we dubbed as F-LQE/RM. Extensive experimental results obtained with state-of-the-art widely used test-beds show that F-LQE/RM improves significantly CTP routing performance over four-bit (the default LQE of CTP) and ETX (another popular LQE). F-LQE/RM improves the end-to-end packet delivery by up to 16%, reduces the number of packet retransmissions by up to 32%, reduces the Hop count by up to 4%, and improves the topology stability by up to 47%.
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Power law (PL) distributions have been largely reported in the modeling of distinct real phenomena and have been associated with fractal structures and self-similar systems. In this paper, we analyze real data that follows a PL and a double PL behavior and verify the relation between the PL coefficient and the capacity dimension of known fractals. It is to be proved a method that translates PLs coefficients into capacity dimension of fractals of any real data.
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Power laws, also known as Pareto-like laws or Zipf-like laws, are commonly used to explain a variety of real world distinct phenomena, often described merely by the produced signals. In this paper, we study twelve cases, namely worldwide technological accidents, the annual revenue of America׳s largest private companies, the number of inhabitants in America׳s largest cities, the magnitude of earthquakes with minimum moment magnitude equal to 4, the total burned area in forest fires occurred in Portugal, the net worth of the richer people in America, the frequency of occurrence of words in the novel Ulysses, by James Joyce, the total number of deaths in worldwide terrorist attacks, the number of linking root domains of the top internet domains, the number of linking root domains of the top internet pages, the total number of human victims of tornadoes occurred in the U.S., and the number of inhabitants in the 60 most populated countries. The results demonstrate the emergence of statistical characteristics, very close to a power law behavior. Furthermore, the parametric characterization reveals complex relationships present at higher level of description.
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Advances in technology have produced more and more intricate industrial systems, such as nuclear power plants, chemical centers and petroleum platforms. Such complex plants exhibit multiple interactions among smaller units and human operators, rising potentially disastrous failure, which can propagate across subsystem boundaries. This paper analyzes industrial accident data-series in the perspective of statistical physics and dynamical systems. Global data is collected from the Emergency Events Database (EM-DAT) during the time period from year 1903 up to 2012. The statistical distributions of the number of fatalities caused by industrial accidents reveal Power Law (PL) behavior. We analyze the evolution of the PL parameters over time and observe a remarkable increment in the PL exponent during the last years. PL behavior allows prediction by extrapolation over a wide range of scales. In a complementary line of thought, we compare the data using appropriate indices and use different visualization techniques to correlate and to extract relationships among industrial accident events. This study contributes to better understand the complexity of modern industrial accidents and their ruling principles.
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12th European Conference on Wireless Sensor Networks (EWSN 2015). 9 to 11, Feb, 2015. Porto, Portugal
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First IFAC Workshop on Fractional Differentiation and Its Application - 19-21 July 2004, Enseirb, Bordeaux, France - FDA'04
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This paper reports investigation on the estimation of the short circuit impedance of power transformers, using fractional order calculus to analytically study the influence of the diffusion phenomena in the windings. The aim is to better characterize the medium frequency range behavior of leakage inductances of power transformer models, which include terms to represent the magnetic field diffusion process in the windings. Comparisons between calculated and measured values are shown and discussed.
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In this paper, we apply the following four power indices to the Portuguese Parliament: Shapley–Shubik index, Banzhaf index, Deegan–Packel index and Public Good Index. We also present the main notions related with simple games and discuss the features of each power index by means of their axiomatic characterizations.
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Anxiety disorders are the most common psychiatric disorders observed currently. It is a normal adaptive response to stress that allows coping with adverse situations. Nevertheless, when anxiety becomes excessive or disproportional in relation to the situation that evokes it or when there is not any special object directed at it, such as an irrational dread of routine stimuli, it becomes a disabling disorder and is considered to be pathological. The traditional treatment used is medication and cognitive behavioral psychotherapy, however, last years the practice of physical exercise, specifically aerobic exercise, has been investigated as a new non-pharmacological therapy for anxiety disorders. Thus, the aim of this article was to provide information on research results and key chains related to the therapeutic effects of aerobic exercise compared with other types of interventions to treat anxiety, which may become a useful clinical application in a near future. Researches have shown the effectiveness of alternative treatments, such as physical exercise, minimizing high financial costs and minimizing side effects. The sample analyzed, 66.8% was composed of women and 80% with severity of symptoms anxiety as moderate to severe. The data analyzed in this review allows us to claim that alternative therapies like exercise are effective in controlling and reducing symptoms, as 91% of anxiety disorders surveys have shown effective results in treating. However, there is still disagreement regarding the effect of exercise compared to the use of antidepressant symptoms and cognitive function in anxiety, this suggests that there is no consensus on the correct intensity of aerobic exercise as to achieve the best dose-response, with intensities high to moderate or moderate to mild.
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The pathophysiology of depression is related to neurobiological changes that occur in the monoamine system, hypothalamic-pituitary-adrenal axis, neurogenesis system and the neuroimmune system. In recent years, there has been a growing interest in the research of the effects of exercise on brain function, with a special focus on its effects on brainderived neurotrophic factor (BDNF), cortisol and other biomarkers. Thus, the aim of this study is to present a review investigating the acute and chronic effects of aerobic exercise on BDNF and cortisol levels in individuals with depression. It was not possible to establish an interaction between aerobic exercise and concentration of BDNF and cortisol, which may actually be the result of the divergence of methods, such as type of exercises, duration of the sessions, and prescribed intensity and frequency of sessions.
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Smart Grids (SGs) have emerged as the new paradigm for power system operation and management, being designed to include large amounts of distributed energy resources. This new paradigm requires new Energy Resource Management (ERM) methodologies considering different operation strategies and the existence of new management players such as several types of aggregators. This paper proposes a methodology to facilitate the coalition between distributed generation units originating Virtual Power Players (VPP) considering a game theory approach. The proposed approach consists in the analysis of the classifications that were attributed by each VPP to the distributed generation units, as well as in the analysis of the previous established contracts by each player. The proposed classification model is based in fourteen parameters including technical, economical and behavioural ones. Depending of the VPP strategies, size and goals, each parameter has different importance. VPP can also manage other type of energy resources, like storage units, electric vehicles, demand response programs or even parts of the MV and LV distribution network. A case study with twelve VPPs with different characteristics and one hundred and fifty real distributed generation units is included in the paper.
Multi-criteria optimisation approach to increase the delivered power in radial distribution networks
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This study proposes a new methodology to increase the power delivered to any load point in a radial distribution network, through the identification of new investments in order to improve the repair time. This research work is innovative and consists in proposing a full optimisation model based on mixed-integer non-linear programming considering the Pareto front technique. The goal is to achieve a reduction in repair times of the distribution networks components, while minimising the costs of that reduction as well as non-supplied energy costs. The optimisation model considers the distribution network technical constraints, the substation transformer taps, and it is able to choose the capacitor banks size. A case study based on a 33-bus distribution network is presented in order to illustrate in detail the application of the proposed methodology.
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Depression is a common and disabling disease that affects over 100 million people worldwide and can have a significant impact on physical and mental health, reducing their quality of life. Thus, the aim of this article was to provide information on research results and key chains related to the therapeutic effects of chronic aerobic exercise compared with other types of interventions to treat depression, which may become a useful clinical application in a near future. Researches have shown the effectiveness of alternative treatments, such as physical exercise, minimizing high financial costs and minimizing side effects. In this review, the data analyzed allows us to claim that alternative therapies, such as exercise, are effective on controlling and reducing symptoms. 69.3% of the studies that investigated the antidepressant effects of exercise on depressive were significant, and the other 30.7% of the studies improved only in general physiological aspects, such as increased oxygen uptake, increased use of blood glucose and decreased body fat percentage, with no improvement on symptoms of depression. From the sample analyzed, 71.4% was composed of women, and regarding the severity of symptoms, 85% had mild to moderate depression and only 15% had moderate to severe depression. However, there is still disagreement regarding the effect of exercise compared to the use of antidepressants in symptomatology and cognitive function in depression, this suggests that there is no consensus on the correct intensity of aerobic exercise as to achieve the best dose-response, with intensities high to moderate or moderate to mild.
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Proceedings of the 13th International UFZ-Deltares Conference on Sustainable Use and Management of Soil, Sediment and Water Resources - 9–12 June 2015 • Copenhagen, Denmark
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Objective: To analyze the short- and long-term effects of microcurrent used with aerobic exercise on abdominal fat (visceral and subcutaneous). Methods: Forty-two female students from a university population were randomly assigned into five group: intervention group (IG) 1 (n=9), IG2 (n=9), IG3 (n=7), IG4 (n=8), and placebo group (PG) (n=9). An intervention program of 10 sessions encompassing microcurrent and aerobic exercise (performed with a cycloergometer) was applied in all groups, with slightly differences between them. In IG1 and IG2, microcurrent with transcutaneous electrodes was applied, with different frequency values; 30-minute exercise on the cycloergometer was subsequently performed. IG3 used the same protocol as IG1 but with different electrodes (percutaneous), while in IG4 the microcurrent was applied simultaneously with the cycloergometer exercise. Finally, the PG used the IG1 protocol but with the microcurrent device switched off. All groups were evaluated through ultrasound and abdominal perimeter measurement for visceral and subcutaneous abdominal fat assessment; through calipers for skinfolds measurement; through bioimpedance to evaluate weight, fat mass percentage, and muscular mass; and through blood analyses to measure cholesterol, triglyceride, and glucose levels. Results: After intervention sessions, visceral fat decreased significantly in IG1 compared with the PG. Subcutaneous fat was reduced significantly in all groups compared with the PG. After 4 weeks, almost all results were maintained. Conclusion: The addition of microcurrent to aerobic exercise may reduce fat more than does aerobic exercise alone.