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At the population level, the diversity rank-score graphs on three common visual space definitions, M 0, M 1, and M 2, respectively provide a powerful visualization comparison, not only among all (sixteen) trials in an experiment, but also among all (three) analytic methods based on M 0, M 1, and M 2, respectively (see Fig. 5 and Sect. 2.3).
Measurements of DTG concentrations were performed using validated analytic methods based on protein precipitation, followed by high-performance liquid chromatography tandem mass spectrometry analysis [ 21].
Based on accurate allele frequency estimates, analytic methods based on individual-level allele frequencies are developed and successfully applied to discover genomic patterns of allele frequencies, detect chromosomal abnormalities, classify sample groups, identify outlier samples, and estimate the purity of tumor samples.
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In addition, FAMM is superior to the finite analytic method based on head-based Richards' equation (FAMH).
It is common to employ a collocation method or analytic method based on the use of polynomial base functions to solve Volterra integral equations.
This creates a great challenging opportunity for driving a new distributed analytic method based on the convergence of the latest mobile technologies.
It is common in the literature to justify the choice of an analytic method based on the assumption that equivalent numerical techniques are more computationally expensive.
Visual learning analytics methods based on AnnotationMaps and Heatmaps were developed to achieve an effective VBL learning experience.
In this article, we introduce the Chebyshev polynomial version of the known numerical-analytic method based on successive iterations.
An advanced analytic method, based mainly on thermorheological analysis of standard frequency sweeps at several temperatures, is introduced which can determine a host of rheological indicators for long-chain branched polyethylenes and other materials with an Arrhenius-type temperature dependence.
Moreover, when used for inpainting, the ITKrMM dictionaries often perform better than their dictionary learning counterparts, wKSVD and BPFA, analytic dictionaries like DCT or even more advanced methods based on analytic dictionaries like MCA, leading to notable improvements for images with moderate to medium corruption level or textured images with any corruption level.
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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