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The remaining six mutation pairs never generate transitions.
The logical functions of Table 1 generate transitions between states, given as vectors of variable values.
Simulations of the logical model, which was introduced above, generate transitions between states defined by the values of the variables at time t = 0, …, n.
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Post classification comparison is applied to generate transition maps.
When the rotating speed is sufficiently high, rotating disk electrode (RDE) could also generate transition and relatively turbulent flows.
Additionally, coarse-grained simulations [ 22– 26], normal mode analysis [ 27– 29], and plastic/elastic network approaches [ 30– 33] are also employed to generate transition pathways of ADK.
FRET transitions are used to generate transition density plots (TDPs), and lifetimes are used to assess the kinetics of the different conformations sampled for a given MutS DNA complex.
Crucially, because the empirical studies typically observe data used to generate transition probabilities over a limited follow-up period, the authors also employ statistical methods to extrapolate beyond the time horizon of observed data, for example the risk of revision.
An understanding of the underlying mechanisms generating transitions is however required for purposefully influencing transitions (to sustainability).
Thus, a new approach for generating transition curves is necessary.
Importantly, this delay should make it easier to find early neuronal responses in the replay condition with respect to the transition report (button release), as during a replayed transition – but not during internally generated transition – the neurons can respond to the physical changes that precede the perceptual change.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com