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The triple variables x1 - x3, x4 - x6, x7 - x9,..., x298 - x300 within each group are highly correlated with a common correlation γ and there are no correlations between groups.
This common correlation structure is observed among neuronal populations in different regions of the brain and involved in divergent neural processes.
This phenomenon is in contrast with the most common correlation for polymer degradation, which predicts the existence of an asymptotic (but finite) limit to the reduced drag reduction.
Its good usability for kLa prediction is shown except for the case when common correlation is made together for axial and radial impellers.
An analysis of the most common correlation functionals, e.g. those introduced by Lee, Yang and Parr and by Perdew and Wang in 1991, will be also carried out.
In addition, the impeller power number Po was found to be a reliable predictor of kLa in a common correlation for various impeller types, when used together with the impeller tip speed term.
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Especially in higher hydrogen sulfide content in spite of ANN good predictions there was considerable deviation between experimental data and common correlations.
Also, they have been compared to the estimated values using the other common correlations which showed the superiority of the proposed model.
In addition, the experimentall obtained liquid side mass transfer coefficients were found to be very low, i.e. more than 10 times lower than the predictions from common correlations.
These experimental results were compared with the estimates generated using common correlations, and it was found that, in all cases, the measured diffusion coefficients were significantly lower than the estimated.
After the operation patterns change, the two neighboring modes still share some common correlations; (2) nonlinear reconstruction model is built based on traditional characteristics; and (3) a new fault direction matrix is designed to modify the reconstruction equation.
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