10 resultados para Local binary pattern

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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Reendothelialization involves endothelial progenitor cell (EPC) homing, proliferation, and differentiation, which may be influenced by fluid shear stress and local flow pattern. This study aims to elucidate the role of laminar flow on embryonic stem (ES) cell differentiation and the underlying mechanism. We demonstrated that laminar flow enhanced ES cell-derived progenitor cell proliferation and differentiation into endothelial cells (ECs). Laminar flow stabilized and activated histone deacetylase 3 (HDAC3) through the Flk-1-PI3K-Akt pathway, which in turn deacetylated p53, leading to p21 activation. A similar signal pathway was detected in vascular endothelial growth factor-induced EC differentiation. HDAC3 and p21 were detected in blood vessels during embryogenesis. Local transfer of ES cell-derived EPC incorporated into injured femoral artery and reduced neointima formation in a mouse model. These data suggest that shear stress is a key regulator for stem cell differentiation into EC, especially in EPC differentiation, which can be used for vascular repair, and that the Flk-1-PI3K-Akt-HDAC3-p53-p21 pathway is crucial in such a process.

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First-order time remaining until a moving observer will pass an environmental element is optically specified in two different ways. The specification provided by global tau (based on the pattern of change of angular bearing) requires that the element is stationary and that the direction of motion is accurately detected, whereas the specification provided by composite tau (based on the patterns of change of optical size and optical distance) does not require either of these. We obtained converging evidence,for our hypothesis. that observers are sensitive to composite tau in four experiments involving, relative judgments of, time to, passage with forced-choice methodology. Discrimination performance was enhanced in the presence of a local expansion component, while being unaffected when the detection of the direction of heading was impaired. Observers relied on the information carried in composite tau rather than on the information carried in its constituent components. Finally, performance was similar under conditions of observer motion and conditions of object motion. Because composite tau specifies first-order time remaining for a large number of situations, the different ways in which it may be detected are discussed.

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The processing of motion information by the visual system can be decomposed into two general stages; point-by-point local motion extraction, followed by global motion extraction through the pooling of the local motion signals. The direction aftereVect (DAE) is a well known phenomenon in which prior adaptation to a unidirectional moving pattern results in an exaggerated perceived direction diVerence between the adapted direction and a subsequently viewed stimulus moving in a diVerent direction. The experiments in this paper sought to identify where the adaptation underlying the DAE occurs within the motion processing hierarchy. We found that the DAE exhibits interocular transfer, thus demonstrating that the underlying adapted neural mechanisms are binocularly driven and must, therefore, reside in the visual cortex. The remaining experiments measured the speed tuning of the DAE, and used the derived function to test a number of local and global models of the phenomenon. Our data provide compelling evidence that the DAE is driven by the adaptation of motion-sensitive neurons at the local-processing stage of motion encoding. This is in contrast to earlier research showing that direction repulsion, which can be viewed as a simultaneous presentation counterpart to the DAE, is a global motion process. This leads us to conclude that the DAE and direction repulsion reflect interactions between motion-sensitive neural mechanisms at different levels of the motion-processing hierarchy.

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Neural adaptation and inhibition are pervasive characteristics of the primate brain, and are probably understood better within the context of visual processing than any other sensory modality. These processes are thought to underlie illusions in which one motion affects the perceived direction of another, such as the direction aftereffect (DAE) and direction repulsion. The DAE describes how, following prolonged viewing of motion in one direction, the direction of a subsequently viewed test pattern is misperceived. In the case of direction repulsion, the direction difference between two transparently moving surfaces is over-estimated. Explanations of the DAE appeal to neural adaptation whilst direction repulsion is accounted for through lateral inhibition. Here we report on a new illusion, the Binary DAE, in which superimposed slow and fast dots moving in the same direction are perceived to move in different directions following adaptation to a mixed-speed stimulus. This new phenomenon is essentially a combination of the DAE and direction repulsion. Interestingly the magnitude of the binary DAE is greater than would be expected simply through a linear combination of the DAE and direction repulsion, suggesting that the mechanisms underlying these two phenomena interact in a non-linear fashion.

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We perform a study of the energetics of KH2PO4 (KDP) by using a shell model (SM) which was constructed by adjusting the interaction parameters to ab initio calculations, and was fitted to reproduce phonons, polarization-inversion energies and structural properties. We calculate the energy profiles by performing global displacements and local distortions following the ferroelectric (FE) mode pattern in clusters of different sizes embedded in a paraelectric (PE) phase matrix. These properties are expected to be relevant to the PE-FE phase transition. The obtained SM results are compared to corresponding ab initio (AI) data. The global instabilities are found in good agreement for both KDP and DKDP. We also find qualitative good agreement in the KDP structure and even quantitative agreement in the expanded DKDP structure for the local distortions. The SM results reproduce well different trends like increasing instabilities as the cluster sizes grows, as the heavier atoms are included, and as the volume is increased, in accordance with the corresponding data from AI calculations.

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The maintenance or even replacement of cracked pavements requires considerable financial resources and puts a large burden on the budgets of local councils. In addition to these costs, local councils also face liability claims arising from uneven or cracked pedestrian pavements. These currently cost the Manchester City Council and Preston City Council around £6 million a year each. Design procedures are empirical. A better understanding of the interaction between paving blocks, bedding sand and subbase was necessary in order to determine the mode of failure of pavements under load. Increasing applied stress was found to mobilise ‘‘rotational interlock’’, providing increased pavement stiffness and thus increased load dissipation resulting in lower transmitted stress on the subgrade. The indications from the literature
review were that pavements are designed to fail by excessive deformation and that paving blocks remained uncracked at failure. This was confirmed with experimental data which was obtained from tests on segments of pavements that were laid/constructed in a purpose built test frame in the laboratory.

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Community structure depends on both deterministic and stochastic processes. However, patterns of community dissimilarity (e.g. difference in species composition) are difficult to interpret in terms of the relative roles of these processes. Local communities can be more dissimilar (divergence) than, less dissimilar (convergence) than, or as dissimilar as a hypothetical control based on either null or neutral models. However, several mechanisms may result in the same pattern, or act concurrently to generate a pattern, and much research has recently been focusing on unravelling these mechanisms and their relative contributions. Using a simulation approach, we addressed the effect of a complex but realistic spatial structure in the distribution of the niche axis and we analysed patterns of species co-occurrence and beta diversity as measured by dissimilarity indices (e.g. Jaccard index) using either expectations under a null model or neutral dynamics (i.e., based on switching off the niche effect). The strength of niche processes, dispersal, and environmental noise strongly interacted so that niche-driven dynamics may result in local communities that either diverge or converge depending on the combination of these factors. Thus, a fundamental result is that, in real systems, interacting processes of community assembly can be disentangled only by measuring traits such as niche breadth and dispersal. The ability to detect the signal of the niche was also dependent on the spatial resolution of the sampling strategy, which must account for the multiple scale spatial patterns in the niche axis. Notably, some of the patterns we observed correspond to patterns of community dissimilarities previously observed in the field and suggest mechanistic explanations for them or the data required to solve them. Our framework offers a synthesis of the patterns of community dissimilarity produced by the interaction of deterministic and stochastic determinants of community assembly in a spatially explicit and complex context.

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In this paper, we consider the variable selection problem for a nonlinear non-parametric system. Two approaches are proposed, one top-down approach and one bottom-up approach. The top-down algorithm selects a variable by detecting if the corresponding partial derivative is zero or not at the point of interest. The algorithm is shown to have not only the parameter but also the set convergence. This is critical because the variable selection problem is binary, a variable is either selected or not selected. The bottom-up approach is based on the forward/backward stepwise selection which is designed to work if the data length is limited. Both approaches determine the most important variables locally and allow the unknown non-parametric nonlinear system to have different local dimensions at different points of interest. Further, two potential applications along with numerical simulations are provided to illustrate the usefulness of the proposed algorithms.