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The effect of the particle density on gas-liquid mass transfer could not be modelled through its effect on the liquid holdup.
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To maximize the prediction power, the first input defines the drugs' polypharmacological profiles by considering both strong and weak drug-target interactions, so that the effect of a drug combination can be modeled through its (multiple) target interactions.
The transition from Stage II to Stage III was modelled through its direct relation to R. Finally, the areas of general yielding and toughness failure were modelled through the relationship between Δσ and R. The accuracy of the modelling for each area is validated with experimental results.
However, the likelihood cannot be modelled through using the human's sensing information.
If there is no neighboring solution, DA can be modeled through random walk.
The video recapturing process can be modeled through expanding the general image recapturing model presented by Gao et al. [10].
Probability of these hidden binary classes can be modeled through a liability-normal mixture model.
Adhesion is modelled through an adhesive zone model.
The hybrid LC-plasmonic tuning mechanism is modelled through a combination of finite element (FEM), Jones calculus and finite difference time domain (FDTD) simulation techniques.
Column elements were modelled through inelastic frame elements.
The mechanical material behaviour was modelled through the rheological models of Maxwell, Kelvin Voigt and Boltzmann.
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