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The main aim of this work is to show the usefulness of a Computational Fluid Dynamics (CFD) model to interpret the results obtained from a reaction-precipitation process by using a spinning disc reactor (SDR).
In systems biology, the usefulness of a computational model is mainly determined by its predictive power.
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In our opinion these findings strength the usefulness of the combined use of a computational and an experimental approach, could have important implications in diagnostics and therapeutics of male infertility, as well in contraceptive strategies, and could contribute to the knowledge of the role played by cytoskeleton in cell signal transduction.
Objectives: We investigated the usefulness of an integrated computational systems biology approach in a case study involving the isomers and metabolites of the pesticide dichlorodiphenyltrichloroethane (DDT) to ascertain their possible links to relevant adverse effects.
In this study, we chose to use the computational model for a major pesticide to assess the usefulness of the computational approach as a tool to bridge gaps in our understanding of environmentally related disease processes by identifying potential mechanistic links.
The results demonstrate the usefulness of this computational model as a design and optimization tool.
Therein lies the usefulness of the computational analysis presented here.
Once the usefulness of the computational model was proven through comparisons with experimental results, and data generated for several ratios of building width to building heights, the flow field was examined to determine the length of the recirculation cavity as a function of the ratio of building width to building height both in front of and in the rear of the building.
We describe here a computational approach to extend the usefulness of a single protein-inhibitor structure in aiding the design of protein kinase inhibitors.
In this paper, the usefulness of Computational Fluid Dynamics (cfd) is illustrated, as a tool for the prediction of the air flow pattern and of food temperature inside the cabinet.
The results presented herein provide an improved understanding of differential flow meters operating at low Reynolds numbers, and demonstrate the usefulness of computational fluid dynamics in predicting discharge coefficient trends at very low Reynolds numbers.
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