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Apparent interaction between a propagating hydraulic fracture and pre-existing natural fractures seems to be the key component explaining why some reservoirs exhibit more complex behaviors.
One significant predictive component explaining 88% of the variation in the power (R-squared-Y = 0.88, Q-squared = 0.52) was identified (Fig. 3a).
In fact, the first component (explaining 49% of variation) related well with all soil properties of reference samples (absolute correlation values of 0.55 0.96).
This spectrum is captured in a single principal component explaining 74% of variation in six key foliar traits within a global data set [GLOPNET; 13].
In the current study the educational component explaining the mechanisms of action was relatively brief and simplistic.
Genetic variances in each family were estimated as the variance component explaining variation between lines of the family.
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The first principal component loading explains the most variance and each subsequent component explains progressively less.
These are arranged in descending order according to the percentage of variance each component explains.
A single component explained 91.9% of variance.
The first component explained 37.4% of the variability.
The first principal component explains 30 40% of the variance; the first and second principal components explain 55 60%.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com