989 resultados para Delta Sigma Omicron. Alpha Chapter


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Field angle dependent critical current, magneto-optical microscopy and high resolution electron microscopy studies have been performed on YBa2Cu3O7-delta thin films grown on miscut substrates. High resolution electron microscopy images show that the films studied exhibited clean epitaxial growth with a low density of antiphase boundaries and stacking faults. Any antiphase boundaries (APBs) formed near the film substrate interface rapidly healed rather than extending through the thickness of the film. Unlike vicinal films grown on annealed substrates, which contain a high density of antiphase boundaries, magneto-optical imaging showed no filamentary flux penetration in the films studied. The flux penetration is, however, asymmetric. This is associated with intrinsic pinning of flux strings by the tilted a-b planes and the dependence of the pinning force on the angle between the local field and the a-b planes. Field angle dependent critical current measurements exhibited the striking vortex channeling effect previously reported in vicinal films. By combining the results of three complementary characterization techniques it is shown that extended APB free films exhibit markedly different critical current behavior compared to APB rich films. This is attributed to the role of APB sites as strong pinning centers for Josephson string vortices between the a-b planes. (C) 2003 American Institute of Physics.

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Adaptive changes in brain areas following drug withdrawal are believed to contribute to drug seeking and relapse. Cocaine withdrawal alters the expression of GluR1 and GluR2/3 subunits of alpha-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) rec

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灵长类大脑前额皮质与感觉联合皮质和皮质下结构有广泛的纤维联系, 可广 泛接受来自体内外的感觉信息。前额皮质与注意和短时记忆过程都有关, 可能 主沟区与短时空间记忆的关系更为密切, 北区的去甲肾上腺素能系统参与短时记 忆过程, alpha-2Ⅰ去甲肾上腺素亚型受体与增强记忆有关。参23

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The unscented Kalman filter (UKF) is a widely used method in control and time series applications. The UKF suffers from arbitrary parameters necessary for sigma point placement, potentially causing it to perform poorly in nonlinear problems. We show how to treat sigma point placement in a UKF as a learning problem in a model based view. We demonstrate that learning to place the sigma points correctly from data can make sigma point collapse much less likely. Learning can result in a significant increase in predictive performance over default settings of the parameters in the UKF and other filters designed to avoid the problems of the UKF, such as the GP-ADF. At the same time, we maintain a lower computational complexity than the other methods. We call our method UKF-L. © 2011 Elsevier B.V.