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The value of the slope at T0, T1, T2 was reported at every time point as it is obtained by the interpolation of mean values in all blocks by linear regression equation.
Half inhibitory concentration (IC50) is calculated by linear regression equation.
We tested the correlations between measured VO2 and VO2 predicted by linear regression equation to validate previously proposed predictive equations, and the same was done for VO2 reserve.
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In this study, we tested the approximation between measured VO2 and VO2 reserve with VO2 and VO2 reserve predicted by linear regression equations in study groups.
Positive correlations were also obtained between measured VO2 and VO2 predicted values (r = 0.81 for CG and r = 0.75 for DG) by linear regression equations to CG (VO2 = 1.54 * ET speed + 52.34) and DG (VO2 = 1.16 * ET speed + 51.99).
The overall trend line for all of samples is expressed by the linear regression equation: ( {text{d}} = - 1.86,delta^{18} {text{O}} + 10.56 permille ) (R2 = 0.44).
After evaluation of data distribution using the Kolmogorov Smirnov test, the Student t-test was applied to reveal significant differences between actual BW and BW predicted by the linear regression equation.
Relating the random distribution functions by a linear regression equation enabled them to construct six new models to analyse the DNA sequences and quantify their similarities and dissimilarities.
The standard calibration curves for known amounts of ATP, ranging from 0.025 to 10.0 µmol/L, were linear (R>0.999) and could be described by the linear regression equation: y = 0.4992*x−0.0463 (n = 4, P<0.0001, r = 0.9997), in which y is the ATP concentration in micromoles and x is the chromatogram peak area.
The TAG concentration in the samples was calculated by the linear regression equation obtained from the calibration curve.
The relationship between VPW and PAOP is described by the linear regression equation: VPW = 57 + 0.9* PAOP) while the equation: VPW = 66.4 + 0.45* CVP) describes the correlation with CVP.
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