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Spatial maps were processed by using an alternative hypothesis test based on the fitting a Gaussian/Gamma mixture model to the distribution of voxel intensities within spatial maps and a posterior probability threshold of p > 0.5.
Based on the fitting formula [14] of the three railway track irregularity spectrums in the U.S., Germany, and China and the analysis of the actual track inspection data, this reference documentation uses programming R and introduces the fitting formula of railway track irregularity power spectrum in our country: S f) = frac{{AB^{2} }}{{f^{2} (f^{2} + B^{2} )}} (3).
The 0.95 cutoff was determined based on the fitting a Pareto distribution to the correlation coefficient trace in Supplementary Figure 12 in the Supporting Information and establishing the cutoff at the 99th percentile.
The measured heat capacities were fitted to a series of theoretical and empirical models, and the corresponding thermodynamic functions were consequently calculated based on the fitting parameters.
Then, finalize the phase function of the reconstructed signal based on the fitting function.
The interpretation of the experimental results was based on the fitting of neural network models for predicting solid phase formation, and DOC concentration along the reaction time.
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We then excluded trials with RT likelihood <0.005 based on the fitted distribution.
The smoothed heat capacities and thermodynamic functions of the complex were calculated based on the fitted polynomial equation.
(Note that we determined the peak latency based on the fitted BOLD response collapsed over all conditions and all runs, per participant).
The smoothed molar heat capacities and thermodynamic functions of the complex relative to the standard reference temperature 298.15 K were calculated based on the fitted polynomial equation.
Point estimates and confidence intervals for each time point were generated based on the fitted longitudinal model, using the ESTIMATE statement in the MIXED procedure in SAS.
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