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In the digital era, modelling has advanced significantly in the last decades.
Predictive modelling has advanced in scope and complexity to integrate: (i) projected shifts in climate suitability, with (ii) spatial patterns of landscape habitat quality and rates of dispersal.
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Experimental work and modelling have advanced the state of the art in the areas of how impurities in CO2 affect thermo-physical properties, fluid flow, corrosion, and reservoir chemical reactivity.
Assimilation of surface geomagnetic observations and geodynamo models has advanced very quickly in recent years.
We emphasize models that are integrated with biological experiments and suggest how recent progress in computational modeling has advanced our understanding of airway branching morphogenesis.
PK/PD modeling has advanced the understanding of the time course of the clinical effects of opioids after various dosing regimens.
The model has advanced beyond the state-of-the-art as loading rate effects, in addition to bearing damage, are accounted for through a novel conic damage approximation function.
Computational modeling has advanced our understanding of drug absorption, tissue distribution, excretion and toxicity profiles by providing both direct and indirect knowledge of drug transporter interactions that would otherwise be unavailable using experimental methods.
Previously, mathematical modeling has advanced our understanding of CD4+ T cell differentiation [ 27- 32].
During its 10 years of existence, the model has advanced in various aspects.
In summary, cardiac modeling has advanced over several decades to become a valuable tool for studying heart function.
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