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The results were within 3% of the model's predictions, demonstrating the validity and value of predictive modelling in catalyst optimization.
Comparison with an existing function prediction algorithm resulted in similar predictions demonstrating the efficiency of our approach to predict functions of genes.
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The good agreement between the measurements and predictions demonstrates the efficiency of the proposed approach.
These model predictions demonstrate the applicability of kinetic procedures and parameters determined in this study.
The BEM predictions demonstrated the acoustic attenuation effectiveness of the hybrid silencer over a wide frequency range.
The accurate predictions demonstrate the effectiveness of the algorithm in stabilising solutions and minimising the surface instabilities generated by the inevitable errors associated with truncated kernels.
The model predictions demonstrate the importance of large canopy species to urban hillslope stability, particularly on steep slopes and in areas where soils tend to retain water.
Results derived using the two turbulence closures are in general in close accord, although real space predictions demonstrate the superiority of results derived on the basis of the second-moment turbulence closure.
The evaluation of our predictions demonstrates the following advantages of ClusterBFS over the compared approaches.
These differential predictions demonstrate the interaction between additive genetic variance and environment.
The evaluation and analysis of our predictions demonstrate the several advantages of our method over other state-of-the-art techniques.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com