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The GENECLUSTER program (11) was used to analyse our UK1, Scotland1 and VQ58 samples specifically in order to test whether one- or two-SNP models better fitted the association signals in each SNP region.
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To test which of the coalescent models better fits the data, we compared them using Bayes factor values.
To avoid collinearity, only one severity scoring system was entered in multivariate models; SAPSII were chosen because the models better fits the data.
Subsequent likelihood rate comparisons were performed for M0 with M3 and M7 with M8 to determine which models better fit the data.
Yan model better fitted the experimental data of the breakthrough curves compared to Thomas and Bohart-Adams models with R2 of 0.9840.
The pseudo-second-order model better fitted the kinetic data while Langmuir isotherm model is found to be best represent the biosorption equilibrium.
A pseudo-second-order kinetic model better fitted the Q adsorption data than a first-order rate model when describing the adsorption rates on all materials.
The higher values of correlation coefficient reveal that Freundlich model better fitted the isotherm data compared to the Langmuir model.
The Korsmeyer Peppas model better fits the release data with the Fickian diffusion mechanism and zero order kinetics for synthesized mesoporous silicas.
Social network data analysis shows that our model better fits the evolved friendships compared to a well designed synthetic trust model, which is used as the baseline.
Nonetheless, the conditional model better fit most of the real data that we analyzed.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com