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The sensitivity of polyaniline to pH variations was then used to design an enzymatic biosensor.
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Such variations are then spread by natural selection in the way that any beneficial mutation would be.
Their time variations are then studied.
The feature points that have the maximum local curvature variations are then extracted.
The illumination variations are then modeled by the principal component analysis embedded in the AAM.
The mean deviation of the estimated background variations is then calculated from (21).
Such spectral intensity variations are then converted into 2D spectra by a form of correlation analysis for subsequent interpretation.
The final variations are then ΔB x and ΔB z, and they give an indication of the EEJ current.
Tracking and regulation performance against gas velocity and unmeasured frother concentration variations were then successfully evaluated in a two-phase system.
Corrections for diurnal and other short-term external field variations are then made by reducing field station observations to night-time average values (see Korte et al. 2007 for details).
Genome-wide variations were then examined via SOAPsnp11 and SOAPsv using a conservative quality filter pipeline (Li et al. [2009]), and 307 627 SNPs, 57 372 InDels, and 3 096 SVs were yielded from the 7302R genome (Table 2, Additional files 12 and 3).
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