Sentence examples for lag where from inspiring English sources

Exact(6)

But the game functions on a lag where, by the time the system begins lurching into inflation, it is too late to pull back.

In pure chalks (Stevns Klint and Mons) however, the creep response is characterized by a time lag, where creep initially diminishes before a tertiary-like creep develops.

However, the correlation coefficients are larger for diversity measure based on annual population estimates with r = 0.40 compared to diversity based on a 3-year lag where r = 0.30.

To study the decay of the cross-correlation in each model, we estimate the point in lag where the cross-correlation attains a value that is half of the maximum, denoted by half-life of the protein-homomer cross-correlation.

(1) K p = J ss C d, D = h 2 6 · t lag, where D = diffusion coefficient within the skin (cm h−1), h = diffusional path length, and C d = initial drug concentration in donor compartment.

(1) C t = FD k 01 V k 01 - k 10 exp - k 10 × t - t lag - exp (- k 01 × t - t lag where C t) is the cimicoxib plasma concentration (μg/L) at time t (h), V/F (L/kg) is the apparent volume of distribution, k01 (1/h) is the rate constant of the initial ascending phase, k10 (1/h) the rate constant of the terminal phase, tlag is the lag time and D is the cimicoxib dose (mg/kg).

Similar(54)

Additional file 2 presents some examples of phase locked BioGRID gene pairs with significant phase lags, where the correlations are low, even with time-lagged correlations.

"There's a scene at the hour-and-four-minute mark" — Mr. Skin has noticed that nudity tends to crop up more commonly at certain points in films, perhaps when audiences' attention is lagging "where Patrick Swayze is sitting outside smoking a cigarette, and Kelly Lynch gets out of bed and starts to walk toward him.

Instead of constraining realizations to match a parametric target covariance model over a wide range of spatial lags, we constrain the realizations only at smaller lags where the available geophysical data cannot provide enough information.

The amplitudes of peaks and troughs attenuate with increasing lag distance and the sill level V here is only meaningful at the larger time lags, where vectors X (and Y) no longer exhibit any significant temporal correlation.

We have shown that the periodicity of the atrial signal can be exploited in two different ways: in a classical BSS approach based on second-order statistics helping in the selection of the time lags where the correlation function is computed (pSAD) and in a novel way introducing a cost function that is related to the periodicity (pICA).

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