102 resultados para Load shedding
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The present study was undertaken to elucidate the controversial issue regarding the small intestinal structural adaptation, in lactose fed rats. Three study groups were used. One experimental fed 60% lactose and two controls in which the lactose was substituted for similar amount of starch. One of them was fed ad libitum and another a limited amount of food to match the body weight of lactose group. The weight, length of the intestine and intestinal mucosal DNA and protein were determined at days 2, 5, 10 and 30 of the experiment. As compared to starch fed ad libitum controls, animals fed 60% lactose diet ate similar amount of food, grew at a slower rate and weighed 16,7% less at the end of the experiment. In contrast to retarded gain in body weight, small intestinal mucosa of these animals contained more DNA (22,5%) and protein (37,5%) than that of controls. These changes were paralleled by increase in length (17%) and weight of the intestine (24,2%). Therefore, the results of the present study confirmed the findings that the small intestine increases in size in response to lactose feeding and that this occurs in the abscense of hyperphagia. It was further demonstrated that this increase was due both to mucosal cell hyperplasia and hypertrophy.
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The stabilization of swine wastewaters from swine confined housing by the combination of a upflow anaerobic sludge blanket (UASB) reactor and waste stabilization ponds is a viable alternative to minimize the environmental impact caused by inadequate disposal of swine wastewaters. In the present study, the polluting load of pre-decanted swine wastewater treated with a series of two 0.705 m(3) UASB reactors and then in parallel in aerated and non-aerated stabilization tanks was investigated from January to July, 2000. Physicochemical and microbiological analyses were made adopting standard methods (Standard Methods for Examination of Water and Wastewater, 19th ed., American Public Health Association, Washington, DC, 1995). COD values decreased as the wastewater ran through the integrated biodigestion system dropping from about 3492 +/- 511-4094 mg l(-1) +/- 481 to 124 +/- 52-490 mg l(-1) +/- 230, while nitrate and nitrite levels increased in stabilization tanks, ranging respectively from 4 +/- 0 to 20 mg l(-1) +/- 3 and 3 +/- 1 to 11 mg l(-1) +/- 24. Although the removal of Escherichia coli was more than 97% +/- 6, the effluents of the treatment system still contained unacceptable levels of E. coli (1.6 x 10(3)-1.2 x 10(6) 100 ml(-1)) according to WHO guidelines for use of wastewater in agriculture and aquaculture. These results indicate the necessity of changes on operational characteristics of the treatment system such as an increase of the hydraulic retention time in UASB reactors or in stabilization tanks. (C) 2003 Published by Elsevier Ltd.
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We performed hyperglycemic clamps in 283 nondiabetic Caucasians and, with multiple linear regression, determined the contribution of beta-cell function and tissue insulin sensitivity to variations in glycemia and insulinemia during oral glucose tolerance tests (OGTTs). Impaired glucose tolerance (IGT) subjects had reduced insulin sensitivity(P < .02) and beta-cell function (P < .0001). Normal glucose tolerance (NGT) subjects with first-degree type 2 diabetic relatives had reduced first and second phase insulin secretion (both, P < .05), but normal insulin sensitivity(P = .37). beta-Cell function and insulin sensitivity accounted for one fourth of the variability in glucose tolerance. Fasting plasma glucose in subjects with NGT (n = 185) was a function of both phases of insulin secretion and of insulin sensitivity tall, P < .05), whereas, in IGT subjects (n = 98), it was a function of first phase insulin secretion and insulin sensitivity(P < .01). Two-hour glycemia was a function of second phase secretion and insulin sensitivity (P < .01). Fasting and 2-hour plasma insulin levels were determined by insulin sensitivity land glycemia) in NGT subjects (P < .001), but by second phase secretion in IGT (P < .001). We conclude that beta-cell function is reduced in subjects with IGT; glycemia and insulinemia are not regulated by the same mechanisms in IGT and NGT; insulin sensitivity does not contribute to insulinemia in IGT; family history of diabetes influences beta-cell function, but not insulin sensitivity in Caucasians. Copyright (C) 2000 by W.B. Saunders Company.
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This work describes a methodology for power factor control and correction of the unbalanced currents in four-wire electric circuits. The methodology is based on the insertion of two compensation networks, one wye-grounded neutral and other in delta, in parallel to the load. The mathematical development has been proposed in previous work [3]. In this paper, however, the determination of the compensation susceptances is based on the instantaneous values of load currents. The results are obtained using the MatLab-Simulink enviroment
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The induction motors are largely used in several industry sectors. The dimensioning of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this paper is to use artificial neural networks as tool for dimensioning of induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Simulation results are also presented to validate the proposed approach.
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Observe the loads associates application with in position of body, in the static or dynamic postures. Methods: the electromyographic study in erector spinae, rectus abdominis, glutaeous maximus and rectus femoris muscles was accomplished in female volunteers from 18 have 27 years old, previously selected. The muscles electric activities was gotten with surface electrodes, in standing and static posture, with the parallels and horizontal upper limbs with load on their hands. Conclusion: In this study it was clearly observed influence of the load and distance there is over studied musculature associated with standing erect posture.
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Extracellular matrix metalloproteinase inducer (EMMPRIN) or CD 147 is a transmembrane glycoprotein expressed by various cell types, including oral epithelial cells. Recent studies have brought evidence that EMMPRIN plays a role in periodontitis. In the present study, we investigated the effect of Porphyromonas gingivalis, a major pathogen in chronic periodontitis, on the shedding of membrane-anchored EMMPRIN and on the expression of the EMMPRIN gene by oral epithelial cells. A potential contribution of shed EMMPRIN to the inflammatory process of periodontitis was analyzed by evaluating the effect of recombinant EMMPRIN on cytokine and matrix metalloproteinase (MMP) secretion by human gingival fibroblasts. ELISA and immunofluorescence analyses revealed that P. gingivalis mediated the shedding of epithelial cell-surface EMMPRIN in a dose- and time-dependent manner. Cysteine proteinase (gingipain)-deficient P. gingivalis mutants were used to demonstrate that both Arg- and Lys-gingipain activities are involved in EMMPRIN shedding. Real-time PCR showed that P. gingivalis had no significant effect on the expression of the EMMPRIN gene in epithelial cells. Recombinant EMMPRIN induced the secretion of IL-6 and MMP-3 by gingival fibroblasts, a phenomenon that appears to involve mitogen activated protein kinases. The present study brought to light a new mechanism by which P. gingivalis can promote the inflammatory response during periodontitis. (C) 2011 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In this paper was evaluated, using the software ANSYS, the stiffness (El) of the log-concrete composite beams, of section T, with connectors formed by bonded-in steel rods, type CA-50, disposed in X, with application of cyclical load. The stiffness of the system was evaluated through the simulation of bending tests, considered 1/2 beam, with cyclical shipment varying among 40 % and 5 % of the strength of the connection with the load relationship R=0,125, for a total of 10 load cycles applied. The numeric results show a good agreement with experimental tests.
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A multi-agent framework for spatial electric load forecasting, especially suited to simulate the different dynamics involved on distribution systems, is presented. The service zone is divided into several sub-zones, each subzone is considered as an independent agent identified with a corresponding load level, and their relationships with the neighbor zones are represented as development probabilities. With this setting, different kind of agents can be developed to simulate the growth pattern of the loads in distribution systems. This paper presents two different kinds of agents to simulate different situations, presenting some promissory results.
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This work shows a computational methodology for the determination of synchronous machines parameters using load rejection test data. The quadrature axis parameters are obtained with a rejection under an arbitrary reference, reducing the present difficulties.
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The objective of this work is the development of a methodology for electric load forecasting based on a neural network. Here, it is used Backpropagation algorithm with an adaptive process based on fuzzy logic. This methodology results in fast training, when compared to the conventional formulation of Backpropagation algorithm. Results are presented using data from a Brazilian Electric Company and the performance is very good for the proposal objective.
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This work shows a computational methodology for the determination of synchronous machines parameters using load rejection test data. By machine modeling one can obtain the quadrature parameters through a load rejection under an arbitrary reference, reducing the present difficulties. The proposed method is applied to a real machine.
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This work presents a procedure for electric load forecasting based on adaptive multilayer feedforward neural networks trained by the Backpropagation algorithm. The neural network architecture is formulated by two parameters, the scaling and translation of the postsynaptic functions at each node, and the use of the gradient-descendent method for the adjustment in an iterative way. Besides, the neural network also uses an adaptive process based on fuzzy logic to adjust the network training rate. This methodology provides an efficient modification of the neural network that results in faster convergence and more precise results, in comparison to the conventional formulation Backpropagation algorithm. The adapting of the training rate is effectuated using the information of the global error and global error variation. After finishing the training, the neural network is capable to forecast the electric load of 24 hours ahead. To illustrate the proposed methodology it is used data from a Brazilian Electric Company. © 2003 IEEE.