Sentence examples for distribution of flux from inspiring English sources

By analyzing these data, we are able to examine the distribution of flux around key branchpoints.

Thus breakthroughs of one passive and two reactive tracers can provide the mean and variance of the distribution of flux over cumulative reactivity.

The inverse technique requires the breakthrough curve of a passive tracer to determine the distribution of flux over travel time, and additional breakthrough curves of reactive tracers provide additional moments of the distribution of flux over cumulative reactivity given travel time.

The approach requires both reactive-transport solutions for a representative ensemble of one-dimensional convective dispersive reactive streamtubes and the distribution of flux over the streamtube ensemble variants, and it does not allow for lateral mixing between streamtubes.

The breakthrough curve of a nonreactive tracer in the ensemble is expressed as a combined Volterra–Fredholm integral equation, which serves as the basis for estimation of the distribution of flux over the variant of the ensemble, travel time.

We argue that iterative cycles of (dry) mathematical modeling and (wet) laboratory testing will become increasingly important for simulating the distribution of flux in plant metabolic networks and deriving rational experimental designs for metabolic engineering efforts.

Results of the two-dimensional finite element analysis indicate that there are losses and nonuniform distribution of fluxes at junctions and boundaries, especially at the parallel steel plates.

This step will create the basis for an optimization based Flux Balance Analysis [FBA] model, such that the distribution of fluxes can be predicted with a limited number of values [active flux bounds] [51], [56].

In a reaction system with branched pathways, like the protein N-glycosylation pathway, the branch points determine the distribution of fluxes and are the controlling points where fluxes can be directed towards a particular product.

These changes in the usage of EFMs, resulting from data-driven network extraction, can be regarded as changes in the distribution of fluxes through the networks.

Relative to the influx, the distribution of fluxes from FBA method (blue bars, Figure 4) does not change with the concentration of exogenous serine (SerE).