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Being able to predict the soluble microbial product (SMP) concentration, an important foulant in membrane bioreactors (MBRs), with mathematical models provides the opportunity to use foulant production as an MBR design and optimization parameter.
Coupling quantitative data with mathematical models provides some answers [ 41].
The use of mathematical models provides tools for the analysis of complex molecular interactions aiming at an understanding of processes occurring in living cells.
Quantification of drug- and biological system specific parameters in translational mathematical models provides the opportunity to re-scale the animal model up to humans [ 129- 131, 151- 153].
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The researchers emphasized the specific affordance of MEAs as mathematical models providing evidence of student thinking centered on targeted mathematics content.
Mathematical models provided crucial tools for engineering the mess.
Mathematical models provide a framework to test our understanding of how this is achieved.
Mathematical models provide the most compact and informative representation of a hypothesis of how a cell works.
Researchers highlight that mathematical models provide useful information for decision-makers to select appropriate choices and save cost.
This construction tends to generate candidate models with smoother small scales compared to mathematical models providing candidates as snapshots at a given epoch.
Kinetic and equilibrium adsorption studies reveal that Elovich and Redlich-Peterson mathematical models provide the best fits for the experimental data, respectively.
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