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Our first-principles modeling approach includes the metabolic and regulative networks that are believed to have a large impact on growth.
In this paper, 6-story and 12-story building models are studied with two different modeling approaches: the first modeling approach includes raft foundation, soil and super-structure interaction (SSI model), while the second modeling approach considers over-ground portion of building based on fixed base-rigid foundation/rigid soil hypothesis (NSSI model/fixed base model).
The combined material and structural modeling approach includes both material and geometric nonlinear effects.
An alternative modeling approach includes for instance the modified exponential function, as discussed in Albers and Skiera (2006).
The modeling approach includes a simplified tubular geometry and stack design including an integrated cooling structure, detailed pressure drop and gas property calculations, the electrical and physical constraints of the stack design that determine the current, as well as control strategies for the temperature.
Our modeling approach includes these factors.
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To identify suitable habitat for tigers in the Russian Far East, we adopted a niche-based tiger habitat modeling approach, including biotic interactions with ungulate prey species, human activities and environmental variables to identify mechanisms driving selection and distribution of tiger habitat.
Accordingly, the objective of this contribution is to estimate the potential density of unthinned forests using a detailed and comprehensive dataset and specific modeling approaches, including individual tree survival functions.
Population dynamics modeling approaches, including coupled, 3-D physical-biological modeling, focus on the effect of climate forcing (e.g. variability in circulation, water temperature, and pH) on key species (e.g., [146][147][148][149][150]).
Details of the liquid modeling approach, including thermodynamic specifications and descriptions of liquid spray at the nozzle outlet, influence the burning regime, mean gas temperatures, and emissions levels predicted by LES.
A backward-elimination approach starts with all candidate variables, and hypothesis tests are sequentially applied to determine which variables should be removed from the final model, whereas a full-model approach includes all candidate variables to avoid potential overfitting and selection bias.
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