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These two models form an upper and lower bound for our topology search.
Atmospheric transport models form an intrinsic part of the air quality monitoring system.
Due to their nature, clinical models form an ideal candidate for evaluating diagnostic tests, developing glucose controllers, understanding disease progression, and predicting risks for complications.
Although land surface models form an integral part of GCMs and topographic and hydrologic factors play an important role in local transmission models, such processes are more readily included within microsimulations that typically lack analytic transparency.
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The models form a background for creating a control system for the process.
The candidate models form a class of non-Gaussian, stationary, stochastic processes.
These workflow models form a valuable resource for workflow domain knowledge, which should be reused to support workflow model design.
Mixed-effect models form a class of model that incorporates multilevel hierarchies in data and can account for the nested structure of our dataset.
Such reduced experimental models form a natural bridge between single cells and tissue/organ level experimental systems to validate and advance theoretical concepts of cardiac propagation and arrhythmias.
We observed that these residues in both models form a loop between two alpha-helices.
Computational multi-scale head models form a potentially powerful next generation of injury assessment tools.
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CEO of Professional Science Editing for Scientists @ prosciediting.com