26 resultados para adaptive fusion

em University of Queensland eSpace - Australia


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A general, fast wavelet-based adaptive collocation method is formulated for heat and mass transfer problems involving a steep moving profile of the dependent variable. The technique of grid adaptation is based on sparse point representation (SPR). The method is applied and tested for the case of a gas–solid non-catalytic reaction in a porous solid at high Thiele modulus. Accurate and convergent steep profiles are obtained for Thiele modulus as large as 100 for the case of slab and found to match the analytical solution.

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Recent structural studies of proteins mediating membrane fusion reveal intriguing similarities between diverse viral and mammalian systems. Particularly striking is the close similarity between the transmembrane envelope glycoproteins from the retrovirus HTLV-1 and the filovirus Ebola. These similarities suggest similar mechanisms of membrane fusion. The model that fits most currently available data suggests fusion activation in viral systems is driven by a symmetrical conformational change triggered by an activation event such as receptor binding or a pH change. The mammalian vesicle fusion mediated by the SNARE protein complex most likely occurs by a similar mechanism but without symmetry constraints.

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From an experiment in which corals are transplanted between two depths on a Panamanian coral reef, Baker1 infers that bleaching may sometimes help reef corals to survive environmental change. Although Baker's results hint at further mechanisms by which reef-building corals may acclimatize to changing light conditions, we do not consider that the evidence supports his inference.

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The acceptance-probability-controlled simulated annealing with an adaptive move generation procedure, an optimization technique derived from the simulated annealing algorithm, is presented. The adaptive move generation procedure was compared against the random move generation procedure on seven multiminima test functions, as well as on the synthetic data, resembling the optical constants of a metal. In all cases the algorithm proved to have faster convergence and superior escaping from local minima. This algorithm was then applied to fit the model dielectric function to data for platinum and aluminum.

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Primary murine fetal hemopoietic cells were transformed with a fusion protein consisting of the ligand-binding domain of the estrogen receptor and a carboxyl-terminally truncated c-Myb protein (ERMYB), The ERMYB-transformed hemopoietic cells exhibit an immature myeloid phenotype when grown in the presence of beta-estradiol. Upon removal of beta-estradiol, the ERMYB cells display increased adherence, decreased clonogenicity and differentiate to cells exhibiting granulocyte or macrophage morphology, The expression of the c-myc, c-kit, cdc2 and bcl-2 genes, which are putatively regulated by Myb, was investigated in ERMYB cells grown in the presence or absence of beta-estradiol. Neither c-myc nor cdc2 expression was down-regulated after removal of beta-estradiol demonstrating that differentiation is not a consequence of decreased transactivation of these genes by ERMYB. While bcl-2 expression was reduced by 50% in ERMYB cells grown in the absence of beta-estradiol, there was no increase in DNA laddering, suggesting that Myb was not protecting ERMYB cells from apoptosis, In contrast, a substantial (200-fold) decrease in c-kit mRNA level was observed following differentiation of ERMYB cells, and c-kit mRNA could be partially re-induced by the re-addition of beta-estradiol. Furthermore, a reporter construct containing the c-kit promoter was activated when cotransfected with a Myb expression vector, providing further evidence of a role for Myb in the regulation of c-kit.

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Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.

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Coastal wetlands are dynamic and include the freshwater-intertidal interface. In many parts of the world such wetlands are under pressure from increasing human populations and from predicted sea-level rise. Their complexity and the limited knowledge of processes operating in these systems combine to make them a management challenge.Adaptive management is advocated for complex ecosystem management (Hackney 2000; Meretsky et al. 2000; Thom 2000;National Research Council 2003).Adaptive management identifies management aims,makes an inventory/environmental assessment,plans management actions, implements these, assesses outcomes, and provides feedback to iterate the process (Holling 1978;Walters and Holling 1990). This allows for a dynamic management system that is responsive to change. In the area of wetland management recent adaptive approaches are exemplified by Natuhara et al. (2004) for wild bird management, Bunch and Dudycha (2004) for a river system, Thom (2000) for restoration, and Quinn and Hanna (2003) for seasonal wetlands in California. There are many wetland habitats for which we currently have only rudimentary knowledge (Hackney 2000), emphasizing the need for good information as a prerequisite for effective management. The management framework must also provide a way to incorporate the best available science into management decisions and to use management outcomes as opportunities to improve scientific understanding and provide feedback to the decision system. Figure 9.1 shows a model developed by Anorov (2004) based on the process-response model of Maltby et al. (1994) that forms a framework for the science that underlies an adaptive management system in the wetland context.