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The more the absolute value of the correlation coefficient approaches 1, the stronger the dependence of the random quantities is.
Therefore we are interested in knowing the behavior of the random variable (3) T ′ = min { t : Y t ≤ t + 2 } (notice the dependence of the random variable T′ on n).
Therefore we are interested to know the behavior of the random variable (6) T ′ = min { t : Y t > 0 } (notice the dependence of the random variable T′ on n).
Now consider the random variable T′′ which is defined as follows T′′ = min{ k:∃ s(| s| = k & I s = ∅)}(notice the dependence of the random variable T′′ on n) and observe that T′′ > k if and only if ∀ s(| s| = k ⇒ I s ≠ ∅).
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Between 5 and 10 wt.%, we can only surmise that the mechanism of electron transfer consists of a mix of both, which are dominant electron transfers in PANI or continuous ZnO structure, indicating a strong dependence on the random placement of the ZnO NP during growth.
In (5) and (8), we use the subscript n in H n and h n to indicate the time-dependence of the random channel.
What is not shown explicitly in Fig. 6A and B is the time-dependence of the random variables R → and U →.
To highlight the dependence of the total random error on system size, we estimated the total random error of the 5929 protein folds with the three scoring functions.
We emphasize that there is no additional assumption on the dependence structure of the random variables.
Therefore, the dependence structure of the random variables can be uniquely represented by the corresponding copula function.
Overall, from the bivariate analysis of sample data, MECC may be directly applied to model the dependence structure of the random variables.
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CEO of Professional Science Editing for Scientists @ prosciediting.com