Effects of a 40-min nap on performance following evening exercise before, during, and after Ramadan fasting.

This study examined the effect of a 40-min nap (N40) the day after a night session of the Loughborough Intermittent Shuttle Test (LIST), before, during and after Ramadan. In a randomized crossover design, fifteen male soccer players completed the LIST in the evening (2100h), followed by either a N40 or no nap (N0) the next day, at 1400h. Performance on the 5-m shuttle run test (5mSRT), digit cancellation test (DCT), and subjective measures (i.

Photoreceptor layer elevation due to subretinal fluid: Impact on visual acuity measurements and simulation from biometrics.

Purpose: Visual acuity (VA) is a primary outcome measure that defines the success of clinical interventions for retinal diseases such as age-related macular degeneration (AMD) or diabetic macular oedema (DME). These conditions can lead to the presence of subretinal fluid, causing substantial photoreceptor layer elevation. Hyperopic defocus then occurs, affecting the VA measurements.

Association of dietary insulin index (DII) and dietary insulin load (DIL) with circadian rhythm and quality of sleep among overweight and obese women: a cross-sectional study.

Background: Obesity is a global issue, with over 1.9 billion adults overweight. Disruption of circadian rhythms (CR) leads to obesity and metabolic disorders.

Winners and Losers From Climate Change: An Analysis of Climate Thresholds for Tree Growth and Survival for Roughly 150 Species Across the Contiguous United States.

Changes in temperature and precipitation are already influencing US forests and that will continue in the future even as we mitigate climate change. Using spatiotemporally matched data for mean annual temperature (MAT) and mean annual precipitation (MAP), we used simulated annealing to estimate critical thresholds for changes in the growth and survival of roughly 150 tree species (153 spp. for growth, 159 spp.

A unified subregional framework for modeling stream water quality across watersheds of a hydrologic subregion.

Modeling stream water quality is informed by knowledge about pertinent factors and processes. The models must be validated against water quality observations, which may exist sufficiently in some watersheds (data rich watersheds) but may be limited or lacking in other cases (i.e.