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A one-parameter bifurcation diagrama in Figure 4a demonstrates how the interspike intervals evolve as gK1 varies at a fixed value of the BK conductance, b = 0.01.
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ST-1 lysis interval evolved to be ~2 min shorter, qualitatively in accord with predictions.
However, lysis interval evolved to a similar endpoint (10.0 min ± 0.11 min standard error for ΦX174ΔslyDlow as compared to 11.2 ± 0.54 min for ΦX174ΔslyD (p < 0.13 by 2-tailed t-test).
The universal outcome for ΦX174 adaptations was a lysis interval indistinguishable from that of wild-type, despite the predictions of the optimality model that a shorter lysis interval should evolve.
Finally, the lysis interval still evolved to the same endpoint when the environment was altered to delay optimal lysis interval.
Phylogenetic analysis of the Slfn genes indicated that the Slfn gene region, located in an otherwise conserved human-mouse interval, is evolving rapidly, possibly in response to selective pressure related to their function in the immune response [7].
The ΦX174 lysis interval did not evolve detectably when the phage was adapted to normal hosts, indicating complete failure of optimality predictions.
The former implies that the control operation is activated only when the states enter the certain region which is often pregiven; while the later activates the control only in some finite time intervals; the system evolves freely when the time goes out of those intervals.
Risk assessments for infrastructure with expected service periods of a century or more are highly uncertain, and there is compelling evidence that climatology will evolve over such intervals.
The lysis interval (11.4 min) did not evolve to the predicted optimum of 5.5 min (calculated using lysis time variance as in equation 3, p < 0.0002 by the parametric model).
During that time interval, f(x) evolves to some other density operator ft(x) since Tt is measure preserving.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com