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Ant species density was significantly higher in canopy samples, but this difference disappeared once abundance was considered.
PC2 (24%) partially identifies a shift between inoculated and non-inoculated samples, but this difference was also partly explained by PC1 (Fig. S5).
The collection method and hardware design are recognized to significantly affect the metabolomic content of EBC samples, but this has not been systematically studied.
Iron reduction at rates of 5 19 nmol Fe(II)/g dry weight/day was observed in only a few samples, but this may be related to a high detection limit for the iron reducing bioassay.
Likewise, a STRUCTURE14,15,16 analysis based on 13 nuclear microsatellite markers suggested K=3 as the most likely number of genetically distinct groups within our European samples, but this putative structuring was unrelated to the two mitochondrial lineages or host race identity (Fig. 3).
Nonparametric bispectrum estimation usually uses more data samples, but this approach can reduce the estimation variance and improve accuracy.
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Likewise, including 40 lags reduces the impact substantially for the full sample, but this effect is due entirely to the required shortening of the sample period.
It was thought that the prevalence of dizziness would be 100%% in the sample, but this was not the case.
The value of this parameter is always higher in S2 than in S1 sample, but this difference decreases when concentration rises.
The intensity of this peak was also enhanced in the powder sample, but this is likely due to an overlap with a MnTe peak located at 28.2°.
That's still a small sample, but this is the first time researchers have managed to create a system like this that works in a clinically relevant setting.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com