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Reasonable success in predicting experimental trends has been achieved when correction factors are applied.
The uncertainty analysis shows that the model is well capable of predicting experimental and pilot result.
The scheme was validated by predicting experimental glucose diffusion through a nanofluidic membrane with a correlation coefficient of 0.999.
Additionally, Monod and Haldane kinetic models were applied to assess their feasibility in describing and predicting experimental data.
Due to the lack of knowledge about the material nature of the gene, however, the classical gene remained a largely formal and operational concept, i.e., had to be substantiated indirectly by the successes achieved in explaining and predicting experimental results.
The investigation contributes to the goals of understanding and predicting experimental phenomena, directing and optimizing biomaterial design, and manipulating integrin-dependent cell-substrate adhesion in tissue engineering.
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The model is used to predict experimental RTD-curves.
Two mechanisms were employed to predict experimental ignition data.
A low CV of 2.21% suggested a good precision and higher reliability of the models to predict experimental results.
Firstly, the proposed model was used to predict experimental results successfully.
The results showed that the Malzbender model predicted experimental data the best.
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