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Intriguingly, our data show that for proteins that are part of the cytochrome-c oxidase complex (COX1, COX2, COX3) and the cytochrome b protein, the normalized mean relative variability (of variable sites) is higher in Primates/Dermoptera than in Rodentia, while the number of perfectly conserved sites is lower in Primates/Dermoptera.
Conversely, for proteins that are components of complex I (NADH dehydrogenase complex) the mean relative variability of variable sites is somewhat lower in Primates/Dermoptera than in Rodentia while the number of perfectly conserved sites tends to be higher in Rodentia.
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Therefore, future work which expands on our core data set should consider time variability of variables.
Our use of a cross-cultural study spanning two regions with vast differences in suicidal rates, socio-cultural environment, and health service organization ensures greater variability of variables of interest.
For example, although the 24-hr food consumption questionnaire properly reflects population food consumption, it does not enable the establishment of individual associations amongst biochemical variables due to the high intra-individual variability of this variable.
The influence of the independent variables on the dependent variables was estimated, and the determination coefficient was determined to explain the variability of the variable PCS or MCS (in percentages) in the covariance model used in the study.
Such background values could distort both the estimation of the variable at nonsampled locations and the inference of the spatial structure of variability of the variable.
Moreover, in this study, the diagnostic threshold that they measured for PLR-induced increases in femoral peak velocity was 8%, while the inter-observer variability of this variable was as large as 8.4 ± 9.2%.
Ultimately, the success of different sampling strategies designed for use in continental-scale environmental analysis will largely depend on the ability to anticipate the spatial variability of the variable being measured.
Regarding creatinine, we included the average value of the last two measurements of each year in order to account for the important within-subject variability of this variable.
It is possible to increase the variability of this variable (%TAV) expanding the variation range of the parameters and/or using a smaller synthetic population (< 1,000 individuals).
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