48 resultados para 191-1179C


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Human sensorimotor control has been predominantly studied using fixed tasks performed under laboratory conditions. This approach has greatly advanced our understanding of the mechanisms that integrate sensory information and generate motor commands during voluntary movement. However, experimental tasks necessarily restrict the range of behaviors that are studied. Moreover, the processes studied in the laboratory may not be the same processes that subjects call upon during their everyday lives. Naturalistic approaches thus provide an important adjunct to traditional laboratory-based studies. For example, wearable self-contained tracking systems can allow subjects to be monitored outside the laboratory, where they engage spontaneously in natural everyday behavior. Similarly, advances in virtual reality technology allow laboratory-based tasks to be made more naturalistic. Here, we review naturalistic approaches, including perspectives from psychology and visual neuroscience, as well as studies and technological advances in the field of sensorimotor control.

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This paper presents a preliminary theoretical and numerical investigation of 4H-SiC JFET and MOSFET at 6.5 kV. To improve the on-state/breakdown performance of the JFET, buried layers in conjunction with a highly doped buffer layer have been used. Trench technology has been employed for the MOSFET. The devices were simulated and optimized using MEDICI[I] simulator. From the comparison between the two devices, it turns out that the JFET offers a better on-state/breakdown trade-off, while the trench MOSFET has the advantage of MOS-control.

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The combination of high frequency, high power, high efficiency capabilities is a feature of vacuum tube technology. For most of applications, large bandwidths are required, and therefore the modulation method should also allow large bandwidth operation. Optically modulated cold cathodes, avoiding the use of resonant cavities, should satisfy this requirement. This is the reason why we have developed carbon nanotube based photocathode.© 2009 IEEE.

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We present a new haplotype-based approach for inferring local genetic ancestry of individuals in an admixed population. Most existing approaches for local ancestry estimation ignore the latent genetic relatedness between ancestral populations and treat them as independent. In this article, we exploit such information by building an inheritance model that describes both the ancestral populations and the admixed population jointly in a unified framework. Based on an assumption that the common hypothetical founder haplotypes give rise to both the ancestral and the admixed population haplotypes, we employ an infinite hidden Markov model to characterize each ancestral population and further extend it to generate the admixed population. Through an effective utilization of the population structural information under a principled nonparametric Bayesian framework, the resulting model is significantly less sensitive to the choice and the amount of training data for ancestral populations than state-of-the-art algorithms. We also improve the robustness under deviation from common modeling assumptions by incorporating population-specific scale parameters that allow variable recombination rates in different populations. Our method is applicable to an admixed population from an arbitrary number of ancestral populations and also performs competitively in terms of spurious ancestry proportions under a general multiway admixture assumption. We validate the proposed method by simulation under various admixing scenarios and present empirical analysis results from a worldwide-distributed dataset from the Human Genome Diversity Project.