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This correlation improved significantly when the CTRA-based EAMIN was correlated with the mechanical testing based minimum axial rigidity results (EAMIN-CTRA = (1.052 × EAMIN-mech) + 69.17; F = 297.6, p < 0.0001; Pearson correlation = 0.919 and R = 0.84) (Fig. 5).
BMD was significantly correlated with BV/TV after defatting (r = 0.44, P < 0.03) but the correlation improved when cortices were taken into account (r = 0.70, P < 0.0001).
The correlation improved as the corn growth stage progressed, but weakened towards the end of the growing season.
However, during the time evolution of those flares, the correlation improved for higher and higher frequencies (≥ 800 MHz), suggesting that the acceleration region was displaced towards the photosphere.
Average model fit (rescaled Nagelkerke R2) and predictive accuracy (correlation) improved from 0.12 to 0.63 and 0.25 to 0.71, respectively, when spectral and LiDAR derived vegetation variables were included in the tree species abundance models.
However, such correlation improved with signal averaging.
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The correlation improves the fit to spontaneous imbibition data published in the literature.
Results showed that the proposed Ψ0.5 based correlation improves the predictive ability and generalization performance compared to the other corresponding theoretical and regression models.
We observe that the correlation improves marginally for non-linear fitting with solar EUV flux.
The quality of the correlation improves as the Transform-Tanimoto threshold is decreased.
However, it can be seen that by discarding the S1-14 sample, the correlation improves greatly.
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