110 resultados para visualization environment

em University of Queensland eSpace - Australia


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A parallel computing environment to support optimization of large-scale engineering systems is designed and implemented on Windows-based personal computer networks, using the master-worker model and the Parallel Virtual Machine (PVM). It is involved in decomposition of a large engineering system into a number of smaller subsystems optimized in parallel on worker nodes and coordination of subsystem optimization results on the master node. The environment consists of six functional modules, i.e. the master control, the optimization model generator, the optimizer, the data manager, the monitor, and the post processor. Object-oriented design of these modules is presented. The environment supports steps from the generation of optimization models to the solution and the visualization on networks of computers. User-friendly graphical interfaces make it easy to define the problem, and monitor and steer the optimization process. It has been verified by an example of a large space truss optimization. (C) 2004 Elsevier Ltd. All rights reserved.

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Mineralogical, hydrochemical and S isotope data were used to constrain hydrogeochemical processes that produce acid mine drainage from sulfidic waste at the historic Mount Morgan Au–Cu mine, and the factors controlling the concentration of SO4 and environmentally hazardous metals in the nearby Dee River in Queensland, Australia. Some highly contaminated acid waters, with metal contents up to hundreds of orders of magnitude greater than the Australia–New Zealand environmental standards, by-pass the water management system at the site and drain into the adjacent Dee River. Mine drainage precipitates at Mt. Morgan were classified into 4 major groups and were identified as hydrous sulfates and hydroxides of Fe and Al with various contents of other metals. These minerals contain adsorbed or mineralogically bound metals that are released into the water system after rainfall events. Sulfate in open pit water and collection sumps generally has a narrow range of S isotope compositions (δ34S = 1.8–3.7‰) that is comparable to the orebody sulfides and makes S isotopes useful for tracing SO4 back to its source. The higher δ34S values for No. 2 Mill Diesel sump may be attributed to a difference in the source. Dissolved SO4 in the river above the mine influence and 20 km downstream show distinctive heavier isotope compositions (δ34S = 5.4–6.8‰). The Dee River downstream of the mine is enriched in 34S (δ34S = 2.8–5.4‰) compared with mine drainage possibly as a result of bacterial SO4 reduction in the weir pools, and in the water bodies within the river channel. The SO4 and metals attenuate downstream by a combination of dilution with the receiving waters, SO4 reduction, and the precipitation of Fe and Al sulfates and hydroxides. It is suggested here that in subtropical Queensland, with distinct wet and dry seasons, temporary reducing environments in the river play an important role in S isotope systematics

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The quantitative description of the quantum entanglement between a qubit and its environment is considered. Specifically, for the ground state of the spin-boson model, the entropy of entanglement of the spin is calculated as a function of α, the strength of the ohmic coupling to the environment, and ɛ, the level asymmetry. This is done by a numerical renormalization group treatment of the related anisotropic Kondo model. For ɛ=0, the entanglement increases monotonically with α, until it becomes maximal for α→1-. For fixed ɛ>0, the entanglement is a maximum as a function of α for a value, α=αM

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One of the challenges in scientific visualization is to generate software libraries suitable for the large-scale data emerging from tera-scale simulations and instruments. We describe the efforts currently under way at SDSC and NPACI to address these challenges. The scope of the SDSC project spans data handling, graphics, visualization, and scientific application domains. Components of the research focus on the following areas: intelligent data storage, layout and handling, using an associated “Floor-Plan” (meta data); performance optimization on parallel architectures; extension of SDSC’s scalable, parallel, direct volume renderer to allow perspective viewing; and interactive rendering of fractional images (“imagelets”), which facilitates the examination of large datasets. These concepts are coordinated within a data-visualization pipeline, which operates on component data blocks sized to fit within the available computing resources. A key feature of the scheme is that the meta data, which tag the data blocks, can be propagated and applied consistently. This is possible at the disk level, in distributing the computations across parallel processors; in “imagelet” composition; and in feature tagging. The work reflects the emerging challenges and opportunities presented by the ongoing progress in high-performance computing (HPC) and the deployment of the data, computational, and visualization Grids.

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The reconstruction of power industries has brought fundamental changes to both power system operation and planning. This paper presents a new planning method using multi-objective optimization (MOOP) technique, as well as human knowledge, to expand the transmission network in open access schemes. The method starts with a candidate pool of feasible expansion plans. Consequent selection of the best candidates is carried out through a MOOP approach, of which multiple objectives are tackled simultaneously, aiming at integrating the market operation and planning as one unified process in context of deregulated system. Human knowledge has been applied in both stages to ensure the selection with practical engineering and management concerns. The expansion plan from MOOP is assessed by reliability criteria before it is finalized. The proposed method has been tested with the IEEE 14-bus system and relevant analyses and discussions have been presented.

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Provides background on the development and nature of Antarctic tourism and associated environmental issues, as well as agreements and regulations affecting environmental management in Antarctica. Following an outline of the survey methodology and provision of information on the socioeconomic profiles of the respondents, results of a survey of Antarctic tourists on the Russian registered ship the ‘Akademik Ioffe’ are reported. The importance of Antarctic wildlife as an attraction for these Antarctic tourists is then given particular attention. The study considers amongst other things how important Antarctic wildlife was in convincing these tourists to undertake their trip to Antarctica, the importance to the tourists of seeing different species of wildlife and the relative importance of wildlife compared with other attractions of the tour to Antarctica. Views both prior to and following visits to Antarctica are given. The views of the tourists about selected environmental issues involving Antarctica were canvassed. These are reported and discussed. Amongst the subjects discussed is whether the sampled tourists favour an expansion in tourism to Antarctica and why. An overall assessment completes the study.

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The three-dimensional solution structure of the 40 residue amyloid beta-peptide, A beta(1-40), has been determined using NMR spectroscopy at pH 5.1, in aqueous sodium dodecyl sulfate (SDS) micelles, In this environment, which simulates to some extent a water-membrane medium, the peptide is unstructured between residues 1 and 14 which are mainly polar and likely solvated by water. However, the rest of the protein adopts an alpha-helical conformation between residues 15 and 36 with a kink or hinge at 25-27. This largely hydrophobic region is likely solvated by SDS. Based on the derived structures, evidence is provided in support of a possible new location for the transmembrane domain of A beta within the amyloid precursor protein (APP). Studies between pH 4.2 and 7.9 reveal a pH-dependent helix-coil conformational switch. At the lower pH values, where the carboxylate residues are protonated, the helix is uncharged, intact, and lipid-soluble. As the pH increases above 6.0, part of the helical region (15-24) becomes less structured, particularly near residues E22 and D23 where deprotonation appears to facilitate unwinding of the helix. This pH-dependent unfolding to a random coil conformation precedes any tendency of this peptide to aggregate to a beta-sheet as the pH increases. The structural biology described herein for A beta(1-40) suggests that (i) the C-terminal two-thirds of the peptide is an alpha-helix in membrane-like environments, (ii) deprotonation of two acidic amino acids in the helix promotes a helix-coil conformational transition that precedes aggregation, (iii) a mobile hinge exists in the helical region of A beta(1-40) and this may be relevant to its membrane-inserting properties and conformational rearrangements, and (iv) the location of the transmembrane domain of amyloid precursor proteins may be different from that accepted in the Literature. These results may provide new insight to the structural properties of amyloid beta-peptides of relevance to Alzheimer's disease.