7 resultados para Structural modeling

em Aston University Research Archive


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Poverty alleviation and social upliftment of rural India is closely linked with the availability and use of energy for development. At the same time, sustainable supply of clean and affordable renewable energy sources is required if development is to be sustainable, so that it does not cause any environmental problems. The purpose of this paper is to determine the key variables of renewable energy implementation for sustainable development, on which the top management should focus. In this paper, an interpretive structural modeling (ISM) - based approach has been employed to model the implementation variables of renewable energy for sustainable development. These variables have been categorized under ‘enablers’ that help to increase the implementation of renewable energy for sustainable development. A major finding of this research is that public awareness regarding renewable energy for sustainable development is a very significant enabler. In this paper, an interpretation of variables of renewable energy for sustainable development in terms of their driving and dependence powers has been examined. For better results, top management should focus on improving the high-driving power enablers such as leadership, strategic planning, public awareness, top management support, availability of finance, government support, and support from interest groups.

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This study highlights the variables associated with the implementation of renewable energy (RE) projects for sustainable development in India, by using an interpretive structural modeling (ISM) - based approach to model variables' interactions, which impact RE adoption. These variables have been categorized under enablers that help to enhance implementation of RE projects for sustainable development. A major finding is that public awareness regarding RE for sustainable development is a very significant enabler. For successful implementation of RE projects, it has been observed that top management should focus on improving highdriving power enablers (leadership, strategic planning, public awareness, management commitment, availability of finance, government support, and support from interest groups).

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Purpose: Short product life cycle and/or mass customization necessitate reconfiguration of operational enablers of supply chain (SC) from time to time in order to harness high levels of performance. The purpose of this paper is to identify the key operational enablers under stochastic environment on which practitioner should focus while reconfiguring a SC network. Design/methodology/approach: The paper used interpretive structural modeling (ISM) approach that presents a hierarchy-based model and the mutual relationships among the enablers. The contextual relationship needed for developing structural self-interaction matrix (SSIM) among various enablers is realized by conducting experiments through simulation of a hypothetical SC network. Findings: The research identifies various operational enablers having a high driving power towards assumed performance measures. In this regard, these enablers require maximum attention and of strategic importance while reconfiguring SC. Practical implications: ISM provides a useful tool to the SC managers to strategically adopt and focus on the key enablers which have comparatively greater potential in enhancing the SC performance under given operational settings. Originality/value: The present research realizes the importance of SC flexibility under the premise of reconfiguration of the operational units in order to harness high value of SC performance. Given the resulting digraph through ISM, the decision maker can focus the key enablers for effective reconfiguration. The study is one of the first efforts that develop contextual relations among operational enablers for SSIM matrix through integration of discrete event simulation to ISM. © Emerald Group Publishing Limited.

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Receptor activity modifying proteins (RAMPs) are a family of single-pass transmembrane proteins that dimerize with G-protein-coupled receptors. They may alter the ligand recognition properties of the receptors (particularly for the calcitonin receptor-like receptor, CLR). Very little structural information is available about RAMPs. Here, an ab initio model has been generated for the extracellular domain of RAMP1. The disulfide bond arrangement (Cys 27-Cys82, Cys40-Cys72, and Cys 57-Cys104) was determined by site-directed mutagenesis. The secondary structure (a-helices from residues 29-51, 60-80, and 87-100) was established from a consensus of predictive routines. Using these constraints, an assemblage of 25,000 structures was constructed and these were ranked using an all-atom statistical potential. The best 1000 conformations were energy minimized. The lowest scoring model was refined by molecular dynamics simulation. To validate our strategy, the same methods were applied to three proteins of known structure; PDB:1HP8, PDB:1V54 chain H (residues 21-85), and PDB:1T0P. When compared to the crystal structures, the models had root mean-square deviations of 3.8 Å, 4.1 Å, and 4.0 Å, respectively. The model of RAMP1 suggested that Phe93, Tyr 100, and Phe101 form a binding interface for CLR, whereas Trp74 and Phe92 may interact with ligands that bind to the CLR/RAMP1 heterodimer. © 2006 by the Biophysical Society.

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PURPOSE. A methodology for noninvasively characterizing the three-dimensional (3-D) shape of the complete human eye is not currently available for research into ocular diseases that have a structural substrate, such as myopia. A novel application of a magnetic resonance imaging (MRI) acquisition and analysis technique is presented that, for the first time, allows the 3-D shape of the eye to be investigated fully. METHODS. The technique involves the acquisition of a T2-weighted MRI, which is optimized to reveal the fluid-filled chambers of the eye. Automatic segmentation and meshing algorithms generate a 3-D surface model, which can be shaded with morphologic parameters such as distance from the posterior corneal pole and deviation from sphericity. Full details of the method are illustrated with data from 14 eyes of seven individuals. The spatial accuracy of the calculated models is demonstrated by comparing the MRI-derived axial lengths with values measured in the same eyes using interferometry. RESULTS. The color-coded eye models showed substantial variation in the absolute size of the 14 eyes. Variations in the sphericity of the eyes were also evident, with some appearing approximately spherical whereas others were clearly oblate and one was slightly prolate. Nasal-temporal asymmetries were noted in some subjects. CONCLUSIONS. The MRI acquisition and analysis technique allows a novel way of examining 3-D ocular shape. The ability to stratify and analyze eye shape, ocular volume, and sphericity will further extend the understanding of which specific biometric parameters predispose emmetropic children subsequently to develop myopia. Copyright © Association for Research in Vision and Ophthalmology.

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Sol-gel-synthesized bioactive glasses may be formed via a hydrolysis condensation reaction, silica being introduced in the form of tetraethyl orthosilicate (TEOS), and calcium is typically added in the form of calcium nitrate. The synthesis reaction proceeds in an aqueous environment; the resultant gel is dried, before stabilization by heat treatment. These materials, being amorphous, are complex at the level of their atomic-scale structure, but their bulk properties may only be properly understood on the basis of that structural insight. Thus, a full understanding of their structure-property relationship may only be achieved through the application of a coherent suite of leading-edge experimental probes, coupled with the cogent use of advanced computer simulation methods. Using as an exemplar a calcia-silica sol-gel glass of the kind developed by Larry Hench, in the memory of whom this paper is dedicated, we illustrate the successful use of high-energy X-ray and neutron scattering (diffraction) methods, magic-angle spinning solid-state NMR, and molecular dynamics simulation as components to a powerful methodology for the study of amorphous materials.