969 resultados para High level architecture


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The hallucinogenic serotonin(IA&2A) agonist psilocybin is known for its ability to induce illusions of motion in otherwise stationary objects or textured surfaces. This study investigated the effect of psilocybin on local and global motion processing in nine human volunteers. Using a forced choice direction of motion discrimination task we show that psilocybin selectively impairs coherence sensitivity for random dot patterns, likely mediated by high-level global motion detectors, but not contrast sensitivity for drifting gratings, believed to be mediated by low-level detectors. These results are in line with those observed within schizophrenic populations and are discussed in respect to the proposition that psilocybin may provide a model to investigate clinical psychosis and the pharmacological underpinnings of visual perception in normal populations.

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Apropos the basal ganglia, the dominant striatum and globus pallidus internus (GPi) have been hypothesised to represent integral components of subcortical language circuitry. Working subcortical language theories, however, have failed thus far to consider a role for the STN in the mediation of linguistic processes, a structure recently defined as the driving force of basal ganglia output. The aim of this research was to investigate the impact of surgically induced functional inhibition of the STN upon linguistic abilities, within the context of established models of basal ganglia participation in language. Two males with surgically induced 'lesions' of the dominant and non-dominant dorsolateral STN, aimed at relieving Parkinsonian motor symptoms, served as experimental subjects. General and high-level language profiles were compiled for each subject up to 1 month prior to and 3 months following neurosurgery, within the drug-on state (i.e., when optimally medicated). Comparable post-operative alterations in linguistic performance were observed subsequent to surgically induced functional inhibition of the left and right STN. More specifically, higher proportions of reliable decline as opposed to improvement in post-operative performance were demonstrated by both subjects on complex language tasks, hypothesised to entail the interplay of cognitive-linguistic processes. The outcomes of the current research challenge unilateralised models of functional basal ganglia organisation with the proposal of a potential interhemispheric regulatory function for the STN in the mediation of high-level linguistic processes.

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To examine the genetic controls of endosperm (ES) specificity, several cereal seed storage protein (SSP) promoters were isolated and studied using a transient expression analysis system. An oat globulin promoter (AsGlo1) capable of driving strong ES-specific expression in barley and wheat was identified. Progressive 5' deletions and cis element mutations demonstrated that the mechanism of specificity in the AsGlo1 promoter was distinct from that observed in glutelin and prolamin promoters. A novel interrupted palindromic sequence, ACATGTCAT-CATGT, was required for ES specificity and substantially contributed to expression strength of the AsGlo1 promoter. This sequence was termed the endosperm specificity palindrome (ESP) element. The GCN4 element, which has previously been shown to be required for ES specificity in cereal SSP promoters, had a quantitative role but was not required for tissue specificity. The 960-bp AsGlo1 promoter and a 251-bp deletion containing the ESP element also drove ES-specific expression in stably transformed barley. Reporter gene protein accumulated at very high levels (10% of total soluble protein) in ES tissues of plants transformed with an AsGlo1:GFP construct. Expression strength and tissue specificity were maintained over five transgenic generations. These attributes make the AsGlo1 promoter an ideal promoter for biotechnology applications. In conjunction with previous findings, our data demonstrate that there is more than one genetically distinct mechanism by which ES specificity can be achieved in cereal SSP promoters, and also suggest that there is redundancy between transcriptional and post-transcriptional tissue specificity mechanisms in cereal globulin genes.

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Aims: Identification of a gene for self-protection from the antibiotic-producing plant pathogen Xanthomonas albilineans, and functional testing by heterologous expression. Methods and Results: Albicidin antibiotics and phytotoxins are potent inhibitors of prokaryote DNA replication. A resistance gene (albF) isolated by shotgun cloning from the X. albilineans albicidin-biosynthesis region encodes a protein with typical features of DHA14 drug efflux pumps. Low-level expression of albF in Escherichia coli increased the MIC of albicidin 3000-fold, without affecting tsx-mediated albicidin uptake into the periplasm or resistance to other tested antibiotics. Bioinformatic analysis indicates more similarity to proteins involved in self-protection in polyketide-antibiotic-producing actinomycetes than to multi-drug resistance pumps in other Gram-negative bacteria. A complex promoter region may co-regulate albF with genes for hydrolases likely to be involved in albicidin activation or self-protection. Conclusions: AlbF is the first apparent single-component antibiotic-specific efflux pump from a Gram-negative antibiotic producer. It shows extraordinary efficiency as measured by resistance level conferred upon heterologous expression. Significance and Impact of the Study: Development of the clinical potential of albicidins as potent bactericidial antibiotics against diverse bacteria has been limited because of low yields in culture. Expression of albF with recently described albicidin-biosynthesis genes may enable large-scale production. Because albicidins are X. albilineans pathogenicity factors, interference with AlbF function is also an opportunity for control of the associated plant disease.

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Enzyme products did not have a significant effect (P>0.05) on weekly fed intake and weight gain of birds. But feed intake tended to drop and weight gain tended to increase in response to supplementation of the three enzymes. Weight gain of the birds was increased by 0.6% with lipase, 3.7% with phytase and 2.4% with xylanase. Xylanase had a marked effect (P

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Formal methods have significant benefits for developing safety critical systems, in that they allow for correctness proofs, model checking safety and liveness properties, deadlock checking, etc. However, formal methods do not scale very well and demand specialist skills, when developing real-world systems. For these reasons, development and analysis of large-scale safety critical systems will require effective integration of formal and informal methods. In this paper, we use such an integrative approach to automate Failure Modes and Effects Analysis (FMEA), a widely used system safety analysis technique, using a high-level graphical modelling notation (Behavior Trees) and model checking. We inject component failure modes into the Behavior Trees and translate the resulting Behavior Trees to SAL code. This enables us to model check if the system in the presence of these faults satisfies its safety properties, specified by temporal logic formulas. The benefit of this process is tool support that automates the tedious and error-prone aspects of FMEA.

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We address the question of how to obtain effective fusion of identification information such that it is robust to the quality of this information. As well as technical issues data fusion is encumbered with a collection of (potentially confusing) practical considerations. These considerations are described during the early chapters in which a framework for data fusion is developed. Following this process of diversification it becomes clear that the original question is not well posed and requires more precise specification. We use the framework to focus on some of the technical issues relevant to the question being addressed. We show that fusion of hard decisions through use of an adaptive version of the maximum a posteriori decision rule yields acceptable performance. Better performance is possible using probability level fusion as long as the probabilities are accurate. Of particular interest is the prevalence of overconfidence and the effect it has on fused performance. The production of accurate probabilities from poor quality data forms the latter part of the thesis. Two approaches are taken. Firstly the probabilities may be moderated at source (either analytically or numerically). Secondly, the probabilities may be transformed at the fusion centre. In each case an improvement in fused performance is demonstrated. We therefore conclude that in order to obtain robust fusion care should be taken to model the probabilities accurately; either at the source or centrally.

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THE PURPOSE OF THIS ARTICLE is two-fold, first to provide a general overview of two of the main cognitive neuroscientific techniques available, specifically functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS); and secondly to apply these techniques to elaborate a discussion of an aspect of higher level vision, namely implied motion, that is the perception of movement from a static image.

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In this paper a new method for image retrieval using high level color semantic features is proposed. It is based on extraction of low level color characteristics and their conversion into high level semantic features using Johannes Itten theory of color, Dempster-Shafer theory of evidence and fuzzy production rules.

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Feature selection is important in medical field for many reasons. However, selecting important variables is a difficult task with the presence of censoring that is a unique feature in survival data analysis. This paper proposed an approach to deal with the censoring problem in endovascular aortic repair survival data through Bayesian networks. It was merged and embedded with a hybrid feature selection process that combines cox's univariate analysis with machine learning approaches such as ensemble artificial neural networks to select the most relevant predictive variables. The proposed algorithm was compared with common survival variable selection approaches such as; least absolute shrinkage and selection operator LASSO, and Akaike information criterion AIC methods. The results showed that it was capable of dealing with high censoring in the datasets. Moreover, ensemble classifiers increased the area under the roc curves of the two datasets collected from two centers located in United Kingdom separately. Furthermore, ensembles constructed with center 1 enhanced the concordance index of center 2 prediction compared to the model built with a single network. Although the size of the final reduced model using the neural networks and its ensembles is greater than other methods, the model outperformed the others in both concordance index and sensitivity for center 2 prediction. This indicates the reduced model is more powerful for cross center prediction.