996 resultados para adaptation plan
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Recently, we demonstrated that humans can learn to make accurate movements in an unstable environment by controlling magnitude, shape, and orientation of the endpoint impedance. Although previous studies of human motor learning suggest that the brain acquires an inverse dynamics model of the novel environment, it is not known whether this control mechanism is operative in unstable environments. We compared learning of multijoint arm movements in a "velocity-dependent force field" (VF), which interacted with the arm in a stable manner, and learning in a "divergent force field" (DF), where the interaction was unstable. The characteristics of error evolution were markedly different in the 2 fields. The direction of trajectory error in the DF alternated to the left and right during the early stage of learning; that is, signed error was inconsistent from movement to movement and could not have guided learning of an inverse dynamics model. This contrasted sharply with trajectory error in the VF, which was initially biased and decayed in a manner that was consistent with rapid feedback error learning. EMG recorded before and after learning in the DF and VF are also consistent with different learning and control mechanisms for adapting to stable and unstable dynamics, that is, inverse dynamics model formation and impedance control. We also investigated adaptation to a rotated DF to examine the interplay between inverse dynamics model formation and impedance control. Our results suggest that an inverse dynamics model can function in parallel with an impedance controller to compensate for consistent perturbing force in unstable environments.
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This study compared adaptation in novel force fields where trajectories were initially either stable or unstable to elucidate the processes of learning novel skills and adapting to new environments. Subjects learned to move in a null force field (NF), which was unexpectedly changed either to a velocity-dependent force field (VF), which resulted in perturbed but stable hand trajectories, or a position-dependent divergent force field (DF), which resulted in unstable trajectories. With practice, subjects learned to compensate for the perturbations produced by both force fields. Adaptation was characterized by an initial increase in the activation of all muscles followed by a gradual reduction. The time course of the increase in activation was correlated with a reduction in hand-path error for the DF but not for the VF. Adaptation to the VF could have been achieved solely by formation of an inverse dynamics model and adaptation to the DF solely by impedance control. However, indices of learning, such as hand-path error, joint torque, and electromyographic activation and deactivation suggest that the CNS combined these processes during adaptation to both force fields. Our results suggest that during the early phase of learning there is an increase in endpoint stiffness that serves to reduce hand-path error and provides additional stability, regardless of whether the dynamics are stable or unstable. We suggest that the motor control system utilizes an inverse dynamics model to learn the mean dynamics and an impedance controller to assist in the formation of the inverse dynamics model and to generate needed stability.
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This study investigated the neuromuscular mechanisms underlying the initial stage of adaptation to novel dynamics. A destabilizing velocity-dependent force field (VF) was introduced for sets of three consecutive trials. Between sets a random number of 4-8 null field trials were interposed, where the VF was inactivated. This prevented subjects from learning the novel dynamics, making it possible to repeatedly recreate the initial adaptive response. We were able to investigate detailed changes in neural control between the first, second and third VF trials. We identified two feedforward control mechanisms, which were initiated on the second VF trial and resulted in a 50% reduction in the hand path error. Responses to disturbances encountered on the first VF trial were feedback in nature, i.e. reflexes and voluntary correction of errors. However, on the second VF trial, muscle activation patterns were modified in anticipation of the effects of the force field. Feedforward cocontraction of all muscles was used to increase the viscoelastic impedance of the arm. While stiffening the arm, subjects also exerted a lateral force to counteract the perturbing effect of the force field. These anticipatory actions indicate that the central nervous system responds rapidly to counteract hitherto unfamiliar disturbances by a combination of increased viscoelastic impedance and formation of a crude internal dynamics model.
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The Chilika Health report Card is based on three categories: water quality, fisheries and biodiversity.
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This project was on “Study of Slurry, as an enrichment compound, on growth and survival parameters of Rutilus firisii kutum Kamensky 1901 larva and compare with routine condition according to hypothesis that use of Slurry, fertile organic compound, to increase the efficiency of survivorship and growth of Rutilus firisii and in other hand adaptation of natural food was performance.” The object of this project is to compare growth of Rutilus firisii and in usual condition and the condition of use Slurry The experiences performed in culture and propagation center Dr. Yousefpour decent (Associan of Dr. Beheshti culture and propagation) in Siahkal village, 32 Km far from southeast, in North of Iran. In this plan, three different treatments and related these nine pools , in 1.7 hec area (in same condition) were determined so that the density of storage was 1.7 million/hec larva. In this research at first treatment m we use slurry as enrichment compound during larval within a period of 13 days, and it used all the days of during larval in second treatment. Then the result of this study compared to control treatment. The results have shown the level of this study compared to control treatment. The results have shown the level of survivorship in pools were nutrition by slurry was 1.7 million times or twice than pools were nutrition with usual concentrate. In addition, growth coefficient such as daily weight growing (DWG) index, daily length growth (DLG), specific growth ratio (SGR) were measured in this case. All of these parameters in slurry treatment were shown noticeable enhancement in first treatment Thereof in the first week there was significant difference (P<0.001) between the average of length and weight in first week , and in the second week there was a significant difference (P<0.05) between them.
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The report presents; terms of reference; work progress; surveys of shark fishers and traders; shark biodiversity survey; and a National Plan of Action (NPOA) for conservation and management of shark resources in Bangladesh.
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The priorities for the revised National Plan of Action include: strengthening current regulations; improved data collection of landings; identifying breeding and nursery grounds; study of ecology and biology of sharks; improved data acquisition of shark products and trade; and active enforcement at sea, landing sites and markets.
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Research included: population structure of Indian mackerel (Rastrelliger kanagurta); a National Plan of Action for the conservation and management of sharks; levels of heavy metals in shark products; and a database on rays.
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Hidden Markov model (HMM)-based speech synthesis systems possess several advantages over concatenative synthesis systems. One such advantage is the relative ease with which HMM-based systems are adapted to speakers not present in the training dataset. Speaker adaptation methods used in the field of HMM-based automatic speech recognition (ASR) are adopted for this task. In the case of unsupervised speaker adaptation, previous work has used a supplementary set of acoustic models to estimate the transcription of the adaptation data. This paper first presents an approach to the unsupervised speaker adaptation task for HMM-based speech synthesis models which avoids the need for such supplementary acoustic models. This is achieved by defining a mapping between HMM-based synthesis models and ASR-style models, via a two-pass decision tree construction process. Second, it is shown that this mapping also enables unsupervised adaptation of HMM-based speech synthesis models without the need to perform linguistic analysis of the estimated transcription of the adaptation data. Third, this paper demonstrates how this technique lends itself to the task of unsupervised cross-lingual adaptation of HMM-based speech synthesis models, and explains the advantages of such an approach. Finally, listener evaluations reveal that the proposed unsupervised adaptation methods deliver performance approaching that of supervised adaptation.
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研究测定了西藏那曲(4,500 m)、云南中甸(3,300 m)、云南德钦(3,300 m)地区3匹藏马线粒体全基因组序列.3个地区的藏马线粒体基因组全长以及结构均与韩国济州岛的马类似,但比瑞典马线粒体基因组短.藏马基因组在DNA序列上的两两相似性达99.3%.通过对线粒体蛋白编码区的分析发现,NADH6基因的蛋白序列在三匹藏马中均表现快速进化的现象.这表明NADH6基因在藏马高原适应进化过程中扮演着重要角色.此外,利用7匹藏马的D-loop区域序列以及与其亲缘关系较近的马的序列首次构建的藏马的系统发育树显示,那曲藏马与中甸、德钦藏马属于不同的分支,且存在较大的遗传多样性,表明藏马可能为多地区起源.
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Computational analyses of dendritic computations often assume stationary inputs to neurons, ignoring the pulsatile nature of spike-based communication between neurons and the moment-to-moment fluctuations caused by such spiking inputs. Conversely, circuit computations with spiking neurons are usually formalized without regard to the rich nonlinear nature of dendritic processing. Here we address the computational challenge faced by neurons that compute and represent analogue quantities but communicate with digital spikes, and show that reliable computation of even purely linear functions of inputs can require the interplay of strongly nonlinear subunits within the postsynaptic dendritic tree.Our theory predicts a matching of dendritic nonlinearities and synaptic weight distributions to the joint statistics of presynaptic inputs. This approach suggests normative roles for some puzzling forms of nonlinear dendritic dynamics and plasticity.