In this work, we report a novel strategy in improving the performance of UV-Vis self-powered CsPbBr₃ quantum dots (QDs) photodetectors (PDs) by ligand modification and P3HT embedding. Compared with those based on pure QDs, modified PDs show a shorten of response time by nearly 10 times, and an increase of maximum responsivity and specific detectivity for nearly 45 and 97 times, respectively. Such PDs also show a high stability with 90% of the initial photocurrent...

In this work, we report a novel strategy in improving the performance of UV-Vis self-powered CsPbBr₃ quantum dots (QDs) photodetectors (PDs) by ligand modification and P3HT embedding. Compared with those based on pure QDs, modified PDs show a shorten of response time by nearly 10 times, and an increase of maximum responsivity and specific detectivity for nearly 45 and 97 times, respectively. Such PDs also show a high stability with 90% of the initial photocurrent...

Abstract Background Cox proportional hazards regression models and machine learning models are widely used for predicting the risk of dementia. Existing comparisons of these models have mostly been based on empirical datasets and have yielded mixed results. This study examines the accuracy of various machine learning and of the Cox regression models for predicting time-to-event outcomes using Monte Carlo simulation in people with mild cognitive impairment (MCI). Methods The predictive accuracy of nine time-to-event regression...

Understanding the biological rhythms that influence young adult health is vital because the combination of biological changes and a circadian phase delay lead to young adults being at high risk of circadian misalignment. We have previously established a self-rating of biological rhythm disorder for adolescents (SBRDA). However, we did not externally validate the SBRDA against objective measures of biological rhythms such as dim light melatonin onset (DLMO)—the gold standard of the endogenous circadian phase. The...