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The ability of this modelling approach to accurately capture complex phenomena such as beating is demonstrated.
We did not look at how the addition of incidence assay data affects the ability of this modelling method to detect changes in HIV incidence over time.
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This agreement shows the excellent ability of this model in data predicting.
These findings provide further validation for the ability of this model to capture existing road safety trends.
Ability of this model to be able to understand the mechanism of convective heat transfer enhancement distinguishes the model from rest of the available numerical models.
In addition, the ability of this model to simulate the total absorption to within the resolution of a riometer will be demonstrated.
Two events of water-sediment regulation conducted in the Xiaolangdi Reservoir in 2004 and 2006 were simulated to test the ability of this model.
The predictive ability of this model was determined using a test set of 13 molecules that gave acceptable predictive correlation (r2Pred) values.
Furthermore, the predictive ability of this model was evaluated by external validation((n = 11, R2test = 0.72, and MAE = 0.170 log units).
It can be seen clearly from the key statistical indicators, coefficient of determination R2, mean squared error MSE and, value of Q2, that the predicting ability of this model is better than that of the linear model (MLR).
The comparisons demonstrate the ability of this model to reproduce accurately the overall mechanical behavior of granular media and to account for the influence of key parameters such as void ratio and mean stress.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com