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The answer to both questions is of course yes and so the next logical question is: are there any tests to measure these differences?
Isolating asymmetry in the rest of the body has proven difficult because researchers lacked instruments designed to measure these differences.
However, few studies have collected the data needed to measure these differences in the patterns of concurrency.
The intensity of codon selection varies between genomes and several approaches have been implemented to measure these differences [ 8, 10, 13, 22, 46, 47].
Two features were defined to measure these differences: bS : slope baseline, a measure of how concentrated slope values are around small values (baseline), computed as the 10th percentile of d filt ¯, nP : number of peaks above a fixed threshold in d filt ¯.
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Other market research companies such as Kantar are also measuring these differences.
Fourth, the two groups were unbalanced at baseline on several outcome measures, these differences were adjusted for in our statistical modelling.
If discrepancies exist between self-reported and objective measures, these differences will need to be adjusted so that the associations between sleep and other psychosocial factors are not overestimated [ 36].
Scores on outcome measures showed improvement at six months follow up, there was a slight benefit among the intervention arm on the chosen outcome measures These differences in outcome measures suggest that the intervention used in this pilot has the potential to be more effective than usual care.
Comparative Di-4 fluorescence lifetime studies of non-parasitized and parasitized HbAA, HbAS, and HbSS erythrocytes offer one measure of these differences.
To provide a simple measure of these differences, we summed up all phase differences (between LL and DD conditions) for all T cycles for each strain analyzed (see values in boldface type in Table S2).
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