For this process the control structures based on Luybens rule ("fix a flow in every recycle loop") give infeasibility if we use the nominal optimal setpoints, but it is feasible with acceptable loss with robust optimal setpoints.
We hypothesized that loss of robust circadian rhythmicity in Kcnma1−/− mice was generated at the level of the SCN.
The loss of robust SFR rhythmicity in the SCN is overtly similar to the behavioral rhythm in Kcnma1−/− mice, including a decrease in the circadian amplitude of the SFR rhythm and a slight lengthening of the circadian period.
This loss of robust checkpoint control and subsequent escape from G2 arrest is likely due at least in part to destabilization of mutant p53, combined with a cellular state in which there is insufficient p21 activity (both intrinsically and via the HSP90 inhibitor-mediated loss of mutant p53) to enforce the checkpoints.
Subjects undergoing total sleep deprivation (TSD) display differential vulnerability to sleep loss, demonstrating robust inter-individual differences in response to the same laboratory conditions, as measured by various neurobehavioral tasks and physiological and subjective sleep measures sensitive to sleep loss [1] [6].
To test the hypothesis that loss of robust behavioral rhythmicity in Kcnma1−/− mice is due to the disruption of SFR rhythms in the SCN, we used multi-electrode arrays to record extracellular action potentials from acute wild-type (WT) and Kcnma1−/− slices.
Inhibition of mir-125a-5p mir-125a-5p mir-125a-5pf chinducesg transtabilizationubsequent lofs of robust chick oscilfngions, associatranscriptsrturbandonsubsequente formation and patterning [ 100].
Although our definition of follow-up loss was robust across a number of sensitivity analyses, it is unknown whether it can be generalized to locations outside of our urban primary-care setting in Zambia.
Müller and Welsh (2005) attributed this partly to non-robust loss function and hence non robust selection criterion and partly to the fact that some of the bootstrap samples may consist almost entirely of outliers.
In this study, we introduce a robust loss function, called Brownboost loss, which computes the feature quality and selects the optimal feature subsets to enhance robustness.
