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In order to disentangle the individual contribution of these components to the overall accessibility change, we make use of a productivity index that consider the change in population M t j, and its counterpart index representing the change in optimal travel time t t ij.
Several surfactants (cationic, anionic and non-ionic), as well as a range of Group I metal halides with differing cations were all investigated to assess the contribution of these components to the reduction of hydrogen peroxide at −0.1 V vs. Ag/AgCl.
In this study, the contribution of these components was investigated by both experimental and computational methods.
We examined the relative contribution of these components to the observed changes in a/n.
In each time period, the network had a core-periphery structure, however, the contribution of these components changed over time.
Deciphering the individual contribution of these components for a particular context (cell type/tumor type/stage) could determine the final fate of the cell.
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The exact contribution of these component phenotypes to overall OSA risk will be determined by their varying prevalence and relative risk conferred across ethnic groups.
But how can we estimate and disentangle the relative contributions of these components to observed behaviour?
Measured rates for fast (τfast) and slow (τslow) components of deactivation, in addition to the relative contributions of these components are given in Table S2.
Simple multilevel models of the variance in the observations allow determination of the relative contributions of these components.
Crystallization affected differently the contribution of these two components.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com