A novel water-soluble flavonol-based fluorescent probe for highly specific and sensitive detection of Al3+ and its application in onion and zebrafish.

A novel and simple turn-on fluorescence probe (HD) for Al3+ detection was successfully developed based on flavonol derivatives. This probe exhibited a significantly enhanced fluorescence response toward Al3+ in aqueous solution which could be observed by naked-eye from poor fluorescence to strong light green emission. The probe HD displays highly specific detection for Al3+ over other competitive metal ions, and the detection limit of probe HD for Al3+ was determined to be 2.57 × 10-8 M, which are much lower than the World Health Organization (WHO) guideline value for drinking food/water. The binding stoichiometry of probe HD with Al3+ was determined to be 1:1 according to Job's plot and ESI-HRMS analysis, and the binding constant was calculated to be 2.01 × 104 M-1. The probe HD exhibited high selectivity, high sensitivity, good anti-interface ability, and wide pH application range as well as the quantitative determination in the detection of Al3+. The coordination mechanism of probe HD with Al3+ was supported by density functional theory (DFT) calculations and HRMS analysis. In addition, the probe HD was found to have good cell permeability and could be applied for live-cell imaging to detect Al3+ in onions and zebrafish.

Driving safety assessment for ride-hailing drivers.

Ride-hailing services, which have become increasingly prevalent in the last decade, provide an efficient travel mode by matching drivers and travelers via smartphone apps. Ride-hailing services enable millions of non-traditional taxi drivers to provide travel services, but may also raise safety concerns due to heterogeneity in the driver population. This study evaluated crash risk factors for ride-hailing drivers, including driving history and ride-hailing operational characteristics, using a sample of 189,815 drivers. We utilized the Poisson generalized additive model to accommodate for the potential nonlinear relationship between crash rate and risk factors. Results showed that crash history, the percentage of long-shift bookings, driving distance, operations during peak hours, years of being a ride-hailing driver, and passenger rating were significantly associated with crash risk. Several factors showed nonlinear relationships with crash risk. We adopted the SHapley Additive exPlanation (SHAP) method to assess and visualize the impact of each risk factor. The results indicated that passenger average rating, total driving distance, and crash history were the leading contributing factors. The findings of this study provide critical information for the development of safety countermeasures, driver education programs, as well as safety regulations for the ride-hailing industry.