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Computational trends in solvation and transport in liquids.
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The difference between the computational efficiency trends of the algorithms under the same-domain and the across-domains settings is interesting.
In particular, we stress current computational and cognitive trends in the field, such as dynamic logics and belief revision.
For computational models, some trends have been identified, but no detailed investigation of the cause of the instabilities in numerical simulations has been undertaken to date.
A very likely foreseeable step to pursue this computational and flexibility trend is the generalization of on-chip multiprocessor platforms (MPSoC).
In the case of analysis performed on computational data, this trend cannot be easily noticed.
To help reverse this trend, computational approaches have emerged to complement experimental techniques in the analysis of structure function relationships of carbohydrate protein interactions.
Finally, we identify trends in computational modelling research to outline possible future directions of the discipline.
Some perspectives are also given on the future trends of computational modeling in biological thermodynamics.
Current trends in computational de novo design provide a fresh approach to 'scaffold-hopping' in drug discovery.
Ever-decreasing latency, bandwidth enhancement, a growing number of available tools and computational resources, all these trends are expected to change several aspects of the teaching/learning interaction.
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