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It was found that Langmuir model showed the best fit with the zeolite 13X and zeolite 4A while Freunlich model provided excellent fit with AC.
This model provided excellent discriminative capability towards LND (C-statistics=0.86, CI 0.76 to 0.95).
This model provided excellent discriminative capability towards END (C-statistics=0.87, CI 0.82 to 0.92).
Experimental validation of the optimal solution showed that the co-culture model provided excellent agreement with measured concentration profiles.
This higher-order six-factor model provided excellent fit to the data (RMSEA = 0.04, CFI =.96, TLI = 0.96).
Further validation indicated that the OPLS-DA model provided excellent predictive power for distinguishing between the sample groups (p =1.7 × 10−6; control vs S. Typhi vs S. Paratyphi A).
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For energy optimization, the model provides excellent relative accuracy too.
It is shown that the FE model provides excellent correlations with experimental results.
The new model provides excellent agreement with the experimental data in a wide range of conversions and reaction temperatures.
The model provides excellent prediction of commercial units' performance, as it incorporates hydrocracking kinetics of paraffins, naphthenes, and aromatics.
As a result, this model provides excellent insight into the underlying physical mechanisms by which the film thickness and temperature affect the electrical resistivity.
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