999 resultados para Inference mechanisms


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A new approach is presented to resolve bias-induced metastability mechanisms in hydrogenated amorphous silicon (a-Si:H) thin film transistors (TFTs). The post stress relaxation of threshold voltage (V(T)) was employed to quantitatively distinguish between the charge trapping process in gate dielectric and defect state creation in active layer of transistor. The kinetics of the charge de-trapping from the SiN traps is analytically modeled and a Gaussian distribution of gap states is extracted for the SiN. Indeed, the relaxation in V(T) is in good agreement with the theory underlying the kinetics of charge de-trapping from gate dielectric. For the TFTs used in this work, the charge trapping in the SiN gate dielectric is shown to be the dominant metastability mechanism even at bias stress levels as low as 10 V.

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Dopamine (DA) D-1 receptor compounds were examined in monkeys for effects on the working memory functions of the prefrontal cortex and on the fine motor abilities of the primary motor cortex. The D-1 antagonist, SCH23390, the partial D-1 agonist, SKF38393, and the full D-1 agonist, dihydrexidine, were characterized in young control monkeys, and in aged monkeys with naturally occurring catecholamine depletion. In addition, SKF38393 was tested in young monkeys experimentally depleted of catecholamines with chronic reserpine treatment. Injections of SCH23390 significantly impaired the memory performance of young control monkeys, but did not impair aged monkeys with presumed catecholamine depletion. Conversely, the partial agonist, SKF38393, improved the depleted monkeys (aged or reserpine-treated) but did not improve young control animals. The full agonist, dihydrexidine, did improve memory performance in young control monkeys, as well as in a subset of aged monkeys. Consistent with D, receptor mechanisms, agonist-induced improvements were blocked by SCH23390. Drug effects on memory performance occurred independently of effects on fine motor performance. These results underscore the importance of DA D-1 mechanisms in cognitive function, and provide functional evidence of DA system degeneration in aged monkeys. Finally, high doses of D-1 agonists impaired memory performance in aged monkeys, suggesting that excessive D-1 stimulation may be deleterious to cognitive function.

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The D2 dopamine (DA) receptor agonist, quinpirole, was characterized in young adult monkeys, young reserpine-treated monkeys and aged monkeys to assess the contribution of DA to age-related loss of prefrontal cortical (PFC) cognitive function, Monkeys were tested on a delayed response memory task that depends on the PFC, and a fine motor task that taps the functions of the motor cortex, In young adult monkeys, low quinpirole doses impaired performance of the PFC and fine motor tasks, while higher doses improved memory performance and induced dyskinesias and ''hallucinatory-like'' behaviors. The pattern of the quinpirole response in reserpine-treated monkeys suggested that the impairments in delayed response and fine motor performance resulted from drug actions at D2 autoreceptors, while the improvement in delayed response performance, dyskinesias and ''hallucinatory-like'' behaviors resulted from actions at postsynaptic receptors. In aged monkeys, low doses of quinpirole continued to impair fine motor performance, but lost their ability to impair delayed response performance. The magnitude of cognitive improvement and the incidence of ''hallucinatory-like'' behaviors were also reduced in the aged animals, suggesting some loss of postsynaptic D2 receptor function, The pattern of results is consistent with the greater loss of DA from the PFC than from motor areas in aged monkey brain (Goldman-Rakic and Brown, 1981; Wenk et al., 1989), and indicates that DA depletion contributes significantly to age-related cognitive decline.

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This paper describes a class of lightweight structures known as compliant shell mechanisms. These are novel reconfigurable solutions for advanced structures, such as morphing shells and deployable membranes. They have local, discrete corrugations, which articulate and deform to achieve dramatic changes in the overall shape of the shell. The unique kinematics are considered by highlighting examples and by performing analysis using established and novel concepts, and favourable predictions of shape compared with laboratory models are demonstrated.

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RFID is a technology that enables the automated capture of observations of uniquely identified physical objects as they move through supply chains. Discovery Services provide links to repositories that have traceability information about specific physical objects. Each supply chain party publishes records to a Discovery Service to create such links and also specifies access control policies to restrict who has visibility of link information, since it is commercially sensitive and could reveal inventory levels, flow patterns, trading relationships, etc. The requirement of being able to share information on a need-to-know basis, e.g. within the specific chain of custody of an individual object, poses a particular challenge for authorization and access control, because in many supply chain situations the information owner might not have sufficient knowledge about all the companies who should be authorized to view the information, because the path taken by an individual physical object only emerges over time, rather than being fully pre-determined at the time of manufacture. This led us to consider novel approaches to delegate trust and to control access to information. This paper presents an assessment of visibility restriction mechanisms for Discovery Services capable of handling emergent object paths. We compare three approaches: enumerated access control (EAC), chain-of-communication tokens (CCT), and chain-of-trust assertions (CTA). A cost model was developed to estimate the additional cost of restricting visibility in a baseline traceability system and the estimates were used to compare the approaches and to discuss the trade-offs. © 2012 IEEE.

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State-space inference and learning with Gaussian processes (GPs) is an unsolved problem. We propose a new, general methodology for inference and learning in nonlinear state-space models that are described probabilistically by non-parametric GP models. We apply the expectation maximization algorithm to iterate between inference in the latent state-space and learning the parameters of the underlying GP dynamics model. Copyright 2010 by the authors.

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Reconstruction of an image from a set of projections has been adapted to generate multidimensional nuclear magnetic resonance (NMR) spectra, which have discrete features that are relatively sparsely distributed in space. For this reason, a reliable reconstruction can be made from a small number of projections. This new concept is called Projection Reconstruction NMR (PR-NMR). In this paper, multidimensional NMR spectra are reconstructed by Reversible Jump Markov Chain Monte Carlo (RJMCMC). This statistical method generates samples under the assumption that each peak consists of a small number of parameters: position of peak centres, peak amplitude, and peak width. In order to find the number of peaks and shape, RJMCMC has several moves: birth, death, merge, split, and invariant updating. The reconstruction schemes are tested on a set of six projections derived from the three-dimensional 700 MHz HNCO spectrum of a protein HasA.

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Laser ablation of solid Silicon targets using pulsed Yb fiber lasers of pulse duration 1.5-400 ns Yb fiber lasers is studied in this work. Material responses of a range of pulse envelopes are examined including front peak (FP) and double peak (DP) pulses. Theoretical models for the interactions are examined and qualitative explanations of material response experiments are presented.