Sentence examples for when this condition is met from inspiring English sources

Exact(7)

When this condition is met a large set of lotteries are locally improving.

Rawls allows deviations from his fair equality of opportunity norm when this condition is met.

When this condition is met, the server creates the predefined number of reduce tasks.

"Even when this condition is met, for example, we still don't turn on all the features at once as this would create unnecessary drain on the BikeTag and user's smart phone battery.

When this condition is met, the algorithm can deal successfully with fixations that are not close to their respective stimuli (Fig.  3C), extremely poor calibrations (Fig.  3D), and even with some fixations in random locations (Fig.  4).

An EM replicate is considered to be "converged" if the increase of the log-likelihood log10ℙ(W|Ψ) in one iteration is <10−4; when this condition is met, we terminate the iteration process.

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Similar(53)

This condition is met when the average interaction energy between the chain and the sorbent equals that between two hydrophobic segments of the chain.

The most dismissive reject the demand for prior evidence outright, holding that we are justified in forming a belief if we will have sufficient evidence for its truth once formed, and that this condition is met when we are justified in forming an intention (Harman 1976, p. 164, n. 8; Velleman 1989, pp. 56 64).

This condition is met when the intracellular calcium level has reached a value low enough to enable maximal guanylate cyclase activation by GCAPs, and the fulfilment of this condition is verified as the same slope of photoresponse recovery for responses to stimuli of different strengths when read at a certain amplitude criterion level.

This condition is met when the null hypothesis (both ensembles come from the same distribution) of a Mann-Whitney U-test cannot be rejected at 10% significance.

When this condition was met, this gene had a substantial impact on the pattern of observed data, introducing a skew in the tail of the distribution of liability markers.

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