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In this section, we analyze the particular results reported in [11] using the Anderson-Darling test, which is one of the most powerful tools to assess normality of a sample based on its empirical distribution function [25].
A preliminary evaluation of a sample based on the semantic group Chemicals and Drugs provides 83% precision.
Robertson et al. (2016) developed an R package capable of implementing alternative geographic coordinates for a sample based on common errors encountered in GBIF.
The color bar indicates the range of the percentage of a genus in a sample, based on the color key (log scale) at the top right.
The results presented demonstrate the ability of pixellated XRD to identify a sample based on the molecular structure of its constituent materials, and therefore the potential to search for specific compounds/substances amongst other masking materials.
The X-ray diffraction data presented for the three simulant samples demonstrate the ability of XRD to identify the different materials present in a sample based on their individual molecular structures, and therefore the possibility of implementation in a system which can search for specific materials hidden inside packages or baggage.
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What's below is just a sampling, based on works that could be seen early this week; a more comprehensive list is at asiaweekny.com and jada-ny.org and in free guides that can be picked up along the way.
We developed a new stepwise, adaptive approach, DescRep, combining an iteratively refined descriptor selection with a sampling based on the putatively most representative compounds.
It is a probability sample based on a stratified sampling scheme of clusters designed to provide representative estimates for the whole nation, regions, and individual states.
This was a cross-sectional survey of a national sample based on a multistage complex design which has been described in detail previously [ 18, 19].
This study was designed as an exploratory descriptive investigation, and as such is limited as a pilot sample based on a small number of respondents.
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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