170 resultados para Controlled Signals.


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Transmission imaging with an environmental scanning electron microscope (ESEM) (Wet STEM) is a recent development in the field of electron microscopy, combining the simple preparation inherent to ESEM work with an alternate form of contrast available through a STEM detector. Because the technique is relatively new, there is little information available on how best to apply this technique and which samples it is best suited for. This work is a description of the sample preparation and microscopy employed by the authors for imaging bacteria with Wet STEM (scanning transmission electron microscopy). Three different bacterial samples will be presented in this study: first, used as a model system, is Escherichia coli for which the contrast mechanisms of STEM are demonstrated along with the visual effects of a dehydration-induced collapse. This collapse, although clearly in some sense artifactual, is thought to lead to structurally meaningful morphological information. Second, Wet STEM is applied to two distinct bacterial systems to demonstrate the novel types of information accessible by this approach: the plastic-producing Cupriavidus necator along with wild-type and ΔmreC knockout mutants of Salmonella enterica serovar Typhimurium. Cupriavidus necator is shown to exhibit clear internal differences between bacteria with and without plastic granules, while the ΔmreC mutant of S. Typhimurium has an internal morphology distinct from that of the wild type.

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In dynamic centrifuge modelling, fluids with enhanced viscosity are often used to correct for the discrepancy in time scaling. However, great care must be taken when using a high viscosity fluid that hydraulic gradients during saturation do not become high enough to cause excessive model disturbance. This paper introduces the CAM-Sat system which aims to improve the saturation process by continually controlling the fluid flow into the model, limiting it to rates low enough to avoid model disturbance. A new method for measuring the fluid flow rate is then described, and its implementation & improvement to the system is discussed. © 2010 Taylor & Francis Group, London.

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The objective of this paper is to propose a signal processing scheme that employs subspace-based spectral analysis for the purpose of formant estimation of speech signals. Specifically, the scheme is based on decimative spectral estimation that uses Eigenanalysis and SVD (Singular Value Decomposition). The underlying model assumes a decomposition of the processed signal into complex damped sinusoids. In the case of formant tracking, the algorithm is applied on a small amount of the autocorrelation coefficients of a speech frame. The proposed scheme is evaluated on both artificial and real speech utterances from the TIMIT database. For the first case, comparative results to standard methods are provided which indicate that the proposed methodology successfully estimates formant trajectories.

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Graphene has extraordinary electronic and optical properties and holds great promise for applications in photonics and optoelectronics. Demonstrations including high-speed photodetectors, optical modulators, plasmonic devices, and ultrafast lasers have now been reported. More advanced device concepts would involve photonic elements such as cavities to control light-matter interaction in graphene. Here we report the first monolithic integration of a graphene transistor and a planar, optical microcavity. We find that the microcavity-induced optical confinement controls the efficiency and spectral selection of photocurrent generation in the integrated graphene device. A twenty-fold enhancement of photocurrent is demonstrated. The optical cavity also determines the spectral properties of the electrically excited thermal radiation of graphene. Most interestingly, we find that the cavity confinement modifies the electrical transport characteristics of the integrated graphene transistor. Our experimental approach opens up a route towards cavity-quantum electrodynamics on the nanometre scale with graphene as a current-carrying intra-cavity medium of atomic thickness. © 2012 Macmillan Publishers Limited. All rights reserved.

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Transmission imaging with an environmental scanning electron microscope (ESEM) (Wet STEM) is a recent development in the field of electron microscopy, combining the simple preparation inherent to ESEM work with an alternate form of contrast available through a STEM detector. Because the technique is relatively new, there is little information available on how best to apply this technique and which samples it is best suited for. This work is a description of the sample preparation and microscopy employed by the authors for imaging bacteria with Wet STEM (scanning transmission electron microscopy). Three different bacterial samples will be presented in this study: first, used as a model system, is Escherichia coli for which the contrast mechanisms of STEM are demonstrated along with the visual effects of a dehydration-induced collapse. This collapse, although clearly in some sense artifactual, is thought to lead to structurally meaningful morphological information. Second, Wet STEM is applied to two distinct bacterial systems to demonstrate the novel types of information accessible by this approach: the plastic-producing Cupriavidus necator along with wild-type and δmreC knockout mutants of Salmonella enterica serovar Typhimurium. Cupriavidus necator is shown to exhibit clear internal differences between bacteria with and without plastic granules, while the δmreC mutant of S. Typhimurium has an internal morphology distinct from that of the wild type. © 2012 Wiley Periodicals, Inc.

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There are many methods for decomposing signals into a sum of amplitude and frequency modulated sinusoids. In this paper we take a new estimation based approach. Identifying the problem as ill-posed, we show how to regularize the solution by imposing soft constraints on the amplitude and phase variables of the sinusoids. Estimation proceeds using a version of Kalman smoothing. We evaluate the method on synthetic and natural, clean and noisy signals, showing that it outperforms previous decompositions, but at a higher computational cost. © 2012 IEEE.

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This article introduces Periodically Controlled Hybrid Automata (PCHA) for modular specification of embedded control systems. In a PCHA, control actions that change the control input to the plant occur roughly periodically, while other actions that update the state of the controller may occur in the interim. Such actions could model, for example, sensor updates and information received from higher-level planning modules that change the set point of the controller. Based on periodicity and subtangential conditions, a new sufficient condition for verifying invariant properties of PCHAs is presented. For PCHAs with polynomial continuous vector fields, it is possible to check these conditions automatically using, for example, quantifier elimination or sum of squares decomposition. We examine the feasibility of this automatic approach on a small example. The proposed technique is also used to manually verify safety and progress properties of a fairly complex planner-controller subsystem of an autonomous ground vehicle. Geometric properties of planner-generated paths are derived which guarantee that such paths can be safely followed by the controller. © 2012 ACM.

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This paper introduces Periodically Controlled Hybrid Automata (PCHA) for describing a class of hybrid control systems. In a PCHA, control actions occur roughly periodically while internal and input actions may occur in the interim changing the discrete-state or the setpoint. Based on periodicity and subtangential conditions, a new sufficient condition for verifying invariance of PCHAs is presented. This technique is used in verifying safety of the planner-controller subsystem of an autonomous ground vehicle, and in deriving geometric properties of planner generated paths that can be followed safely by the controller under environmental uncertainties.

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We present a novel method for controlling the growth orientation of individual carbon nanotube (CNT) microstructures on a silicon wafer substrate. Our method controls the CNT forest orientation by patterning the catalyst layer used in the CNTs growth on slanted KOH edges. The overlap of catalyst area on the horizontal bottom and sloped sidewall surfaces of the KOH-etched substrate enables precise variation of the growth direction. These inclined structures can profit from the outstanding mechanical, electrical, thermal, and optical properties of CNTs and can therefore improve the performance of several MEMS devices. Inclined CNT microstructures could for instance be used as cantilever springs in probe card arrays, as tips in dip-pen lithography, and as sensing element in advanced transducers. ©2009 IEEE.

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We develop a group-theoretical analysis of slow feature analysis for the case where the input data are generated by applying a set of continuous transformations to static templates. As an application of the theory, we analytically derive nonlinear visual receptive fields and show that their optimal stimuli, as well as the orientation and frequency tuning, are in good agreement with previous simulations of complex cells in primary visual cortex (Berkes and Wiskott, 2005). The theory suggests that side and end stopping can be interpreted as a weak breaking of translation invariance. Direction selectivity is also discussed. © 2011 Massachusetts Institute of Technology.

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This paper addresses the speed and flux regulation of induction motors under the assumption that the motor parameters are poorly known. An adaptive passivity-based control is proposed that guarantees robust regulation as well as accurate estimation of the electrical parameters that govern the motor performance. This paper provides a local stability analysis of the adaptive scheme, which is illustrated by simulations and supported by a successful experimental validation on an industrial product. © 2009 IEEE.

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Inspired by molecular mechanisms that cells exploit to sense mechanical forces and convert them into biochemical signals, chemists dream of designing mechanochemical switches integrated into materials. Using the adhesion protein fibronectin, whose multiple repeats essentially display distinct molecular recognition motifs, we derived a computational model to explain how minimalistic designs of repeats translate into the mechanical characteristics of their fibrillar assemblies. The hierarchy of repeat-unfolding within fibrils is controlled not only by their relative mechanical stabilities, as found for single molecules, but also by the strength of cryptic interactions between adjacent molecules that become activated by stretching. The force-induced exposure of cryptic sites furthermore regulates the nonlinearity of stress-strain curves, the strain at which such fibers break, and the refolding kinetics and fraction of misfolded repeats. Gaining such computational insights at the mesoscale is important because translating protein-based concepts into novel polymer designs has proven difficult.

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Vertically oriented GaAs nanowires (NWs) are grown on Si(111) substrates using metal-organic chemical vapor deposition. Controlled epitaxial growth along the 111 direction is demonstrated following the deposition of thin GaAs buffer layers and the elimination of structural defects, such as twin defects and stacking faults, is found for high growth rates. By systematically manipulating the AsH 3 (group-V) and TMGa (group-III) precursor flow rates, it is found that the TMGa flow rate has the most significant effect on the nanowire quality. After capping the minimal tapering and twin-free GaAs NWs with an AlGaAs shell, long exciton lifetimes (over 700ps) are obtained for high TMGa flow rate samples. It is observed that the Ga adatom concentration significantly affects the growth of GaAs NWs, with a high concentration and rapid growth leading to desirable characteristics for optoelectronic nanowire device applications including improved morphology, crystal structure and optical performance. © 2012 IOP Publishing Ltd.