Physiological and Cognitive Performance in F-22 Pilots During Day and Night Flying.

BACKGROUND: Many workers routinely transition between day and night shiftsincluding pilots, where night flights are commonly considered more stressful. The physiological toll from this transition is not fully understood, though fatigue is a factor in many aviation accidents. This research investigated the changes in physiological markers of stress and cognitive performance as F-22 pilots transitioned from day flying to night flying.METHODS: There were 17 fully-qualified F-22 pilots who took part in a 2-wk data collection using salivary swabs, wrist-worn activity monitors, the National Aeronautics and Space Administration-Task Load Index (NASA-TLX) inventory, and a go/no-go (GNG) test.RESULTS: No differences were found in comparing day and night flying on the GNG reaction time/accuracy, NASA-TLX scores, or sleep quantity. Cortisol levels were significantly higher than civilian levels in all experimental conditions and control days. Participants had higher than predicted cortisol levels postflight in the day-flying condition and lower than predicted cortisol levels postflight in the night-flying condition, relative to levels from control day patterns. We also found smaller changes in cortisol (pre- to postflight) in the day-flying condition for those with more F-22 experience. Finally, we found a negative correlation between Perceived Stress Scale scores and age of pilots (r 0.72).DISCUSSION: We hypothesized that the night-flying environment would be more stressful, but our results disputed this claim. Our results suggest day flying elicits more of a stress response; however, a larger sample size is required to verify results. Preliminary findings of potential stress adaptation may suggest stress adaptation in the F-22 community needs further investigation.Combs EK, Dahlman AS, Shattuck NL, Heissel JA, Whitaker LR. Physiological and cognitive performance in F-22 pilots during day and night flying. Aerosp Med Hum Perform. 2021; 92(5):303311.

Estimating distributions with increasing failure rate in an imperfect repair model.

A failed system is repaired minimally if after failure, it is restored to the working condition of an identical system of the same age. We extend the nonparametric maximum likelihood estimator (MLE) of a system's lifetime distribution function to test units that are known to have an increasing failure rate. Such items comprise a significant portion of working components in industry. The order-restricted MLE is shown to be consistent. Similar results hold for the Brown-Proschan imperfect repair model, which dictates that a failed component is repaired perfectly with some unknown probability, and is otherwise repaired minimally. The estimators derived are motivated and illustrated by failure data in the nuclear industry. Failure times for groups of emergency diesel generators and motor-driven pumps are analyzed using the order-restricted methods. The order-restricted estimators are consistent and show distinct differences from the ordinary MLEs. Simulation results suggest significant improvement in reliability estimation is available in many cases when component failure data exhibit the IFR property.