7,487 research outputs found
Fight against angiogenesis-related blindness
No full textAngiogenesis-Related Blindness (ARB) indicates the spectrum of retinal diseases that can lead to catastrophic visual loss: retinopathy of prematurity in infants, retinoblastoma in children, diabetic retinopathy in the middle aged, and age-related macular degeneration in the elderly. These retinopathies are characterized by pathologic angiogenesis and breakdown of blood-retinal barrier (BRB) in common. With the evidences that vascular endothelial growth factor (VEGF) plays important role in angiogenesis and permeability, anti-VEGF treatment has been one of the mainstay modalities in managing ARB. However, there are limitations of anti-VEGF treatment in that it might not cure pathologic angiogenesis but induce decrease in differentiation or function of retinal neuronal cells. Recently, researches are in progress on modulation of upstream and downstream signaling molecules, in particular, HIF-1α and VEGF receptor-2, to suppress retinal and choroidal neovascularization. Furthermore, regulation of other angiogenic molecules and pathophysiologic mechanisms should be considered. We expect further researches on treatment of ARB to be more target-specific and pathogenesis-based. © 2012 Nova Science Publishers, Inc. All rights reserved.N
Smooth boundary topology optimisation applied to an electrostatic actuator
No full textSmooth boundary topology optimisation in conjunction with the continuum design sensitivity analysis avoids many of the problems encountered by conventional cell-based systems coupled with material homogenisation or the density method. Shape optimisation becomes part of topology optimisation. The effectiveness of the proposed method is demonstrated through the design of an electrostatic MEMS actuator to generate maximum torque for a predefined maximum size (area)
Multivariable norm optimal iterative learning control with auxiliary optimization
No full textThe paper describes a substantial extension of Norm Optimal Iterative Learning Control (NOILC) that permits tracking of a class of finite dimensional reference signals whilst simultaneously converging to the solution of a constrained quadratic optimization problem. The theory is presented in a general functional analytical framework using operators between chosen real Hilbert spaces. This is applied to solve problems in continuous time where tracking is only required at selected intermediate points of the time interval but, simultaneously, the solution is required to minimize a specified quadratic objective function of the input signals and chosen auxiliary (state) variables. Applications to the discrete time case, including the case of multi-rate sampling, are also summarized. The algorithms are motivated by practical need and provide a methodology for reducing undesirable effects such as payload spillage, vibration tendencies and actuator wear whilst maintaining the desired tracking accuracy necessary for task completion. Solutions in terms of NOILC methodologies involving both feedforward and feedback components offer the possibilities of greater robustness than purely feedforward actions. Robustness of the feedforward implementation is discussed and the work is illustrated by experimental results from a robotic manipulator
Sound source localization system using explicitly adaptive time delay estimator and mechanically steerable microphone
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The dynamic performance analysis of foil journal bearings considering coulomb friction: Rotating unbalance response
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