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The RSM model predicted both the trends and magnitude the most accurately when compared to the isotropic models.

In terms of desorption the model predicted both where desorption was occurring (solvent inlet, column, reboiler) and the total amount of CO2 desorbed.

By modelling interactions in existing tree mixtures, the model predicted both increases and reductions in the growth of mixtures (up to ±50% of stem volume at 7 years) compared to monocultures.

Thus, the model predicted both geographical and temporal variation well.

The model predicted both positive and negative effects of removing catabolism.

Our model predicted both previously demonstrated miRNA-protein associations and new candidate miRNA targets, and showed overall consistent miRNA-protein associations across three independent data sets.

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This new model predicts both flame height and flame shape.

The model predicts both the lowered modulation in naïve GC-ΔKCC2 mice and an increase in the modulation following the training.

The model predicts both separating and pooling equilibria, in which signaling does and does not occur respectively.

The model predicts both simple harmonic oscillations as well as a wide variety of nonperiodic chaotic oscillations.

It is found that the model predicts both the experimental results obtained under various conditions reasonably well.

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