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The dynamic mass balance equations are based on a multi-domain model structure for skeletal muscle consisting of a spatially-lumped capillary blood domain which exchanges nutrients and metabolic waste products with a spatially-lumped domain of tissue cells (Figure 2).
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The energy balance equation is based on fundamental physics and cannot itself be wrong, but its application in obesity research is increasingly considered problematic (Lustig, 2006; Taubes, 2008; Wells and Siervo, 2011).
The fundamental equations are based on momentum balance in radial coordinates.
These equations are based on a mass balance across the system and account for liquid density and liquid volume changing over the course of the experiment.
The model equations are based on dynamic mass balances of chemical species in capillary blood and tissue cells (cytosol and mitochondria) domains.
The dimensionless mass and momentum balance equations, which are based on lubrication theory, were solved for the velocity and pressure fields by using perturbation techniques, where the exiting sheet thickness represents an eigenvalue of the mathematical problem.
The mass and momentum balance equations, which are based on lubrication theory, were nondimensionalized and solved for the velocity and pressure fields by using perturbation and numerical techniques, where the leave-off distance represents an eigenvalue of the mathematical problem.
The derived equation is based on an average momentum and mass balance within the cavity.
After airflow among zones is established, mass balance equations are used to calculate pollutant concentrations based on the sources and sinks in each zone.
Based on the concept of averaging the field equations, conservation and balance equations are developed.
Within the context of CRNT alternative ways to encode the balance equations are used such that the connection between structure and dynamics can be more easily exploited [ 4]. Results in this paper rely on a particular representation of the balance equations already introduced in [ 8], which is based on the graph of complexes of a reaction network and briefly presented next.
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