Sentence examples for follows exponentially from inspiring English sources

We assume t k follows exponentially distributed with mean value 1/α f(t)left{begin{array}{c}hfill alpha {e}^{-alpha t}left(t>0right)hfill hfill 0left tle 0righfillill end{array}right.. (12).

The effects of SR 25989 on cell survival was investigated in a clonogenic assay as follows: exponentially growing B16 F10 cells were used for the experiments.

Drug co-treatment was carried out as follows: exponentially growing cells were pre-treated with a chemosensitizer (1 h), then exposed to a DNA-damaging agent in the presence of the chemosensitizer (1 h), followed by post-incubation in medium containing the chemosensitizer (up to 24 h).

It follows an exponentially decaying behaviour, with a significantly large energy width of ϕ=100 meV, suggesting a high degree of potential disorder and scattering.

Whether the degree of node distribution in brain networks follows an exponentially truncated power law or a scale-free degree distribution (power law) is still disputed [24].

Supporting this hypothesis in MS is the observation that the occurrence of relapses follows an exponentially decaying distribution, implying that disease activity manifests randomly in time.

We created a willingness-to-travel model, which follows an exponentially decaying distribution, by fitting the model to national-scale NHTS data for privately operated vehicle travel (27 ).

However, another study reported that functional networks based on resting-state functional MRI (fMRI) data at the macroscale followed an exponentially truncated power law distribution [16].

Note that |h CBS‒Eav|2 and |h PBS‒Eav|2 follow independent exponentially distributed random variables with respective means σ CBS ‒ Eav 2 and σ PBS ‒ Eav 2. Thus, we obtain P intercept multiuser = π 0 exp - 2 R - 1 σ CBS ‒ Eav 2 γ s + π 1 σ CBS ‒ Eav 2 γ s σ PBS ‒ Eav 2 γ p 2 R - 1 + σ CBS ‒ Eav 2 γ s exp - 2 R - 1 σ CBS ‒ Eav 2 γ s. (38).

Moreover, we showed that the distribution of these nodal properties followed an exponentially truncated power law distribution model, implying a lack of nodes with extremely high values in these metrics (Figure 7).

Furthermore, we found that, in the spontaneous brain functional networks, both the node betweenness and degree distribution followed an exponentially truncated power law distribution pattern as opposed to a scale-free distribution (Figure 6 and Figure S4), implying that the lack of nodes with extremely high centrality.