Sentence examples for models of lag from inspiring English sources

Mathematical models of lag phase include Baranyi's model [ 19] in which biomass production relies on accumulation of bottleneck proteins in lag phase [ 18, 19], and models which focus on cell-cell variation in lag phase duration [ 4, 20].

The effects of cumulative exposure, assessed with distributed lag models of lags 0 2, were somewhat lower for European cities than for U.S. cities.

To allow comparison of relationships among the multiple components and outcomes with potentially different lag structures, we used 3-day unconstrained distributed lag models of lags 0 2 (where lag 0 refers to the day of the ED visit, lag 1 refers to the day before the visit, and so on).

We use here the term phasing model instead of lag model in reference to work on control: events are in phase when the lag equals 0 and antiphase when the average lag is half the average duration between events.

Here, we designed a model of lagging strand replication with RFC loaded PCNA that allows for maximal activity of the four-subunit human Pol δ holoenzyme, Pol η, and Pol κ in polymerase mixing assays.

For the subsequent analyses we used the best lag week, which had the smallest p-value for coefficients β among the four models of different lag weeks for each outcome.

All these measures were highly correlated (TSPs on the day of investigation with TSPs the day before, r = 0.83; TSPs on the day of investigation with the of the week before, r = 0.82), and the effect estimates did not change; that is, all relative differences of means ratios between models of different lags were < 1%.

Studies have shown that models of single day lags might underestimate the effect of air pollution on mortality, 17 thus we used a moving average concentration over two days (lag 0-1) fourour main analyses.

Data shown are the Poisson regression coefficients (using the negative binomial model) of a lagged variable after adjusting for effects of seasonality, population density, and province.

This finding can lead to refinements of modeling for better predictions of lag phase duration.

Unlike problems in areas like sensation and motor control, symbolic problems seem to exist on computers' "home turf". It is mysterious, therefore that modern models of symbolic problem solving lag so far behind human performance.