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Historic data describing these interactions are used in this paper to "model" these transitions and to explain them.
In our present model these transitions are understood as random fluctuations caused by molecular level noise inherent in biological systems.
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Theoretical studies have supported the following model for these transitions [ 51- 53, 66] (see Figure 1A).
However, few soil C models consider these transitions.
Modeling of these transitions often assumes system bistability, in which cells can be resting in one of two stable states.
The rate parameters of the model estimate these transition rates.
In these models, the transitions leaving a given state compete only against each other, rather than against all other transitions in the model.
Our results, obtained for vastly different systems, allow us to trace some general conclusions concerning the modeling of these transition metal complexes.
Our results, obtained for vastly different systems, allow us to trace some general conclusions concerning the modeling of these transition metal complexes, casting the bases for the computational design and screening, even before their synthesis, of new and more efficient transition metal complexes for photonics applications.
The curve fitting procedures proposed use the same criteria as proposed previously but with the additional complexity of fitting of multiplet split spectra which has been done based on spectra of numerous reference materials and theoretical XPS modeling of these transition metal species.
The variable-index model can efficiently quantify these transitions, with the scale index varying linearly in time or space.
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