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Although the determination of hydration entropy (ΔS hyd ) had been considered a very difficult task, it was reported recently that ΔS hyd could be estimated with reasonable accuracy by means of combining free energy perturbation (FEP) method and scaled particle theory (SPT) to calculate the electrostatic and hydrophobic contributions of solute-water interactions separately [30].
Data were normalized using the loess method and scaled with the Gquantile method [55], [56].
Normalization was performed using the print-tip loess method and scaled with the Gquantile method.
Normalization was performed using the print-tip loess method and scaled with the Gquantile method [ 30, 31].
During the normalization analyzes, we transformed the microarray signal intensities between channels within the same microarray using the "loess" method and scaled the data between microarrays using the method "Aquantile" in the R software package Limma.
For a list of genes differentially expressed between caseous human pulmonary TB granulomas and normal lung parenchyma, raw CHP files were summarized by MAS5 method and scaled to median of all samples, and the baseline was transformed to the median of all samples, by using GeneSpring GX 10.0.2 program (Agilent Technologies).
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It may be that scaling, via an appropriate method and scaling variable, maybe be of more clinical value in those athletes with smaller BSA's.
Use of recent advances on ADMM accelerated methods and scaling techniques (e.g., see [30]) is also an interesting option but need to be suitably adapted to a non-convex context.
Potential improvements include alternative methods for variance stabilization transformations (in contrast to the log transformation used in this case) and other normalization methods, for example, GC content correction methods and scaling methods like Trimmed mean of M values.
The pair-comparison method and scale method were adopted in the research methodology to simplify perceptual evaluations and enhance their validity.
We present an overview to the design of scalable derivative edge detectors, based on the finite element method, that addresses the issues of method and scale-adaptability.
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