Sentence examples for predictions of temporal from inspiring English sources

We believe that future physical models of magnetic activity and spectral emissions in the solar chromosphere and transition region may make quantitative predictions of temporal relationships among full-disk solar indices for comparison with analyses such as ours.

The advent of crowdsourced data from devices and services carried by individuals on a daily basis has opened up the possibility of performing better predictions of temporal visitation patterns for locations and venues.

We investigate properties of the HMM technique such as how it benefits by incorporating hidden variables when making the predictions of temporal patterns of differential expression for given different biological conditions and how the number of chosen latent variables varies with conditions within a stage over a time period.

Taking a HMM approach, we seek SETI and multivariate coupled relationships among distinct trajectories into HMMs in each condition to investigate biological evolutionary trajectory that can be applied to a comprehensive set of RNA-seq time series data to make probabilistic predictions of temporal patterns for how differential expression will occur under different biological conditions.

Temporal variations of ECw and the small temporal variability of SWCavg prevented the prediction of temporal variability of SWCavg using ECapp measurements.

A12 Outcome prediction of temporal lobe epilepsy surgery from P-glycoprotein activity.

As demonstrated in a recent review by Land et al. [55], a generalized prediction of temporal trends in environmental concentrations of short-chain PFAAs is currently not feasible due to limited monitoring data and insignificant time trends shown in most of the studies.

Such shortening cannot be explained by a pacemaker rate account, but it does fit the prediction of temporal ventriloquism-like effects on the mode switch latency.

In the visual domain, there is behavioral evidence that processing and prediction of temporal regularity cannot be suppressed, even with participants are specifically instructed to ignore it (Rohenkohl et al. 2011).

The information gained from the RAPRASI study, including models that allow prediction of temporal changes in kidney toxicity, will add to our current understanding of partial kidney radiation dose response to improve outcomes (including maximizing the preservation of function) of kidney dose response and tolerance to radiation.

Since the understanding of this biological process - involving impact sensitivity and saturation effect - is still rather limited, i σ is expressed in terms of a nonnegative parameter tuple σ ∈ ( R 0 + ) 2. It turns out that this tuple has to be adapted frequently to ensure reasonable predictions of the temporal blood glucose evolution, see Section 5.