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We get this result by using Granger causality tests – statistical tests designed to determine causation – of a kind well suited to the long time series that our datasets provide.
Our datasets provide a valuable resource for the community of baseline protease and inhibitor relative expression in normal human tissues and can be used for comparison with diseased tissue, e.g. ovarian cancer, to decipher pathogenesis, and to aid drug development.
Our datasets provide a good opportunity to test this hypothesis.
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Secondly, our dataset provides information on borrower's labor status and the type of contract if occupied.
Although our dataset provides information about only three levels, in this section, we introduce a general definition of edge-labeled multigraph which covers any multi-layered setting.
Our dataset provides information about registration codes that categorize ownership (i.e., types of state-owned, privately owned, and foreign-owned types).
Conclusion: Our dataset provides an interesting insight into the drugs involved in and clinical pattern of toxicity outcome of acute recreational drug toxicity presentations at the ED, despite possible under-declaration and coding.
These findings are applicable if geophysical logging tools be used after the drilling of wells to ascertain properties such as porosity; our dataset provides useful means to address complex reservoir problems.
Our dataset provides direct information on the types of contracts used by firms in each year of the sample, from which conversion rates at the firm level can be retrieved.
In addition to registration codes that categorize ownership, our dataset provides information about affiliation codes that distinguish the government levels to which a firm is affiliated (i.e., levels of central government, provincial government, prefectural and city government, county government, and township and village government).
Finally, our dataset provides information about the regulation of further Aβ dependent genes, which could turn out to be important in AD.
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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