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The two models produce similar stochastic errors, but Nanbu's model gives smaller time step errors.
The obtained mass transfer rate model gives smaller values for the predicted mass transfer rate but shows a comparable dependence on water flow and saturation as in earlier published one-dimensional column experiments with identical characteristics for porous medium, DNAPL and surfactant.
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The three data sets gave similar non-linear damping models and in all cases the non-linear model gave smaller fitting errors than the linear model.
Simulation results on outage MIMO capacity with basic and modified SCM models show that the modified SCM model gives constantly smaller capacity values.
It can be seen that the proposed model gives the smallest NMAEs and NRMSEs for all of the four data sets, which indicates that the proposed model outperforms the other ones in both accuracy and stability.
Model B could be less precise than Model A given small to moderate ICC values, a phenomenon previously reported by Pickering and Weatherall [ 7].
This model gave the smallest MAE of about 15 min.
Therefore, the model giving the smallest value of the code is to be considered the best model explaining the data given the sample size.
As mentioned, this model gave the smallest APP response, and a significant increase compared to pre-inoculation was only observed for fibrinogen at day 18 p.i.
Model fitting was sequential based on the most significantly associated individual variable, with model fit assessed using the Akaike Information Criteria to ensure fitting the most parsimonious model given the small number of outcomes available for evaluation.
The model gives accurate hydration free energies on small molecules by simply adding the hydration energies of the fragments constituting the molecule.
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