6 resultados para Predictive Function

em CentAUR: Central Archive University of Reading - UK


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Prediction mechanism is necessary for human visual motion to compensate a delay of sensory-motor system. In a previous study, “proactive control” was discussed as one example of predictive function of human beings, in which motion of hands preceded the virtual moving target in visual tracking experiments. To study the roles of the positional-error correction mechanism and the prediction mechanism, we carried out an intermittently-visual tracking experiment where a circular orbit is segmented into the target-visible regions and the target-invisible regions. Main results found in this research were following. A rhythmic component appeared in the tracer velocity when the target velocity was relatively high. The period of the rhythm in the brain obtained from environmental stimuli is shortened more than 10%. The shortening of the period of rhythm in the brain accelerates the hand motion as soon as the visual information is cut-off, and causes the precedence of hand motion to the target motion. Although the precedence of the hand in the blind region is reset by the environmental information when the target enters the visible region, the hand motion precedes the target in average when the predictive mechanism dominates the error-corrective mechanism.

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In the present study, to shed light on a role of positional error correction mechanism and prediction mechanism in the proactive control discovered earlier, we carried out a visual tracking experiment, in which the region where target was shown, was regulated in a circular orbit. Main results found in this research were following. Recognition of a time step, obtained from the environmental stimuli, is required for the predictive function. The period of the rhythm in the brain obtained from environmental stimuli is shortened about 10%, when the visual information is cut-off. The shortening of the period of the rhythm in the brain accelerates the motion as soon as the visual information is cut-off, and lets the hand motion precedes the target motion. Although the precedence of the hand in the blind region is reset by the environmental information when the target enters the visible region, the hand precedes in average the target when the predictive mechanism dominates the error-corrective mechanism.

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The cupin superfamily is a group of functionally diverse proteins that are found in all three kingdoms of life, Archaea, Eubacteria, and Eukaryota. These proteins have a characteristic signature domain comprising two histidine- containing motifs separated by an intermotif region of variable length. This domain consists of six beta strands within a conserved beta barrel structure. Most cupins, such as microbial phosphomannose isomerases (PMIs), AraC- type transcriptional regulators, and cereal oxalate oxidases (OXOs), contain only a single domain, whereas others, such as seed storage proteins and oxalate decarboxylases (OXDCs), are bi-cupins with two pairs of motifs. Although some cupins have known functions and have been characterized at the biochemical level, the majority are known only from gene cloning or sequencing projects. In this study, phylogenetic analyses were conducted on the conserved domain to investigate the evolution and structure/function relationships of cupins, with an emphasis on single- domain plant germin-like proteins (GLPs). An unrooted phylogeny of cupins from a wide spectrum of evolutionary lineages identified three main clusters, microbial PMIs, OXDCs, and plant GLPs. The sister group to the plant GLPs in the global analysis was then used to root a phylogeny of all available plant GLPs. The resulting phylogeny contained three main clades, classifying the GLPs into distinct subfamilies. It is suggested that these subfamilies correlate with functional categories, one of which contains the bifunctional barley germin that has both OXO and superoxide dismutase (SOD) activity. It is proposed that GLPs function primarily as SODs, enzymes that protect plants from the effects of oxidative stress. Closer inspection of the DNA sequence encoding the intermotif region in plant GLPs showed global conservation of thymine in the second codon position, a character associated with hydrophobic residues. Since many of these proteins are multimeric and enzymatically inactive in their monomeric state, this conservation of hydrophobicity is thought to be associated with the need to maintain the various monomer- monomer interactions. The type of structure-based predictive analysis presented in this paper is an important approach for understanding gene function and evolution in an era when genomes from a wide range of organisms are being sequenced at a rapid rate.

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The aim of this study was to determine whether any differences in the GH-IGF-I axis in juvenile calves were predictive of fertility problems as adult cows. Endogenous metabolic hormone profiles before and after feeding and the response to a GH-releasing factor (GRF) challenge were measured in prepubertal (6 month) dairy calves. These metabolic parameters were subsequently related to physical characteristics at puberty and to ovarian function during the first lactation. Milk progesterone analysis was used to categorize the animals into those with normal progesterone profiles following calving (n = 17) and those that developed delayed ovulation (DOV1, n = 9) or persistent corpus luteum (PCL1, n = 6) profiles. There were associations between prepubertal GH parameters, glucose and non-esterified fatty acid (NEFA) concentrations and the body condition score at which the animals attained puberty. The calves which subsequently developed DOV1 profiles as cows tended to have a higher GH pulse amplitude during fasting than normal profile animals, they did not show the anticipated decrease in circulating glucose concentrations following a post-prandial rise in insulin and they also had the lowest IGF-I concentrations. The calves that later developed PCL1 had a significantly larger GH pulse amplitude and pulse area than normal profile animals in the fed period and had the highest IGF-I concentrations. There were no differences in prepubertal insulin or NEFA concentrations or in the GH response to a GRF challenge between the different progesterone profile categories. Plasma IGF-I concentrations in prepubertal animals were positively correlated with their post-calving concentrations, whereas glucose concentrations had a negative correlation between these time-periods. These results suggested that the different juvenile endocrine profiles of the DOV1 cows may predispose them to a higher rate of tissue mobilization during lactation and a consequent reduction in fertility, while altered GH and IGF-I levels in PCL1 cows may later contribute to the maintenance of the persistent corpus luteum. Therefore metabolic differences in prepubertal calves were later reflected by altered reproductive function during the first lactation.

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An automatic nonlinear predictive model-construction algorithm is introduced based on forward regression and the predicted-residual-sums-of-squares (PRESS) statistic. The proposed algorithm is based on the fundamental concept of evaluating a model's generalisation capability through crossvalidation. This is achieved by using the PRESS statistic as a cost function to optimise model structure. In particular, the proposed algorithm is developed with the aim of achieving computational efficiency, such that the computational effort, which would usually be extensive in the computation of the PRESS statistic, is reduced or minimised. The computation of PRESS is simplified by avoiding a matrix inversion through the use of the orthogonalisation procedure inherent in forward regression, and is further reduced significantly by the introduction of a forward-recursive formula. Based on the properties of the PRESS statistic, the proposed algorithm can achieve a fully automated procedure without resort to any other validation data set for iterative model evaluation. Numerical examples are used to demonstrate the efficacy of the algorithm.

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In this paper stability of one-step ahead predictive controllers based on non-linear models is established. It is shown that, under conditions which can be fulfilled by most industrial plants, the closed-loop system is robustly stable in the presence of plant uncertainties and input–output constraints. There is no requirement that the plant should be open-loop stable and the analysis is valid for general forms of non-linear system representation including the case out when the problem is constraint-free. The effectiveness of controllers designed according to the algorithm analyzed in this paper is demonstrated on a recognized benchmark problem and on a simulation of a continuous-stirred tank reactor (CSTR). In both examples a radial basis function neural network is employed as the non-linear system model.