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For this study the dataset with resolution 100 m × 100 m has been used.
For our study, the dataset of 94 Korean firms (out of all 700 KOSPI listed firms) that have Bloomberg Environmental Social Governance (ESG) Disclosure scores for the period of 2008-2014 was used.
In our study, the dataset reported was generated using a 12-bp window, having previously explored a range of window sizes between 8 16 bp and empirically establishing that a 12-bp window was sufficient to capture the best motifs.
For the current study, the dataset was analyzed utilizing the code book developed during the previous phase of analysis, but now focusing on only those portions of the interviews relating to assessment in clinical practice modules.
In the present study, the dataset of Weinstein et al.[ 16] was analyzed to characterize the whole recombined sequence, and to investigate V (D) J distribution among all 14 fish and the mutations that occur within the sequences.
Due to the retrospective nature of our study, the dataset obtained may have subtle unobservable differences that would have been difficult to quantify, which may have affected the overall outcome.
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In this study, the datasets were reclassified into five categories: woodland, cropland, wetland, water body, and build-up.
As for migration studies, the dataset has a strong comparative advantage.
For the sitagliptin studies, the dataset was built manually by collecting information given in the different source publications.
For the linagliptin studies, the dataset was built from the original Boehringer Ingelheim database using SAS scripting.
Horgan et al based their study on the dataset from the INTEREST clinical trial.
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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