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Dynamic origin–destination (OD) flow is a fundamental input for dynamic network models and simulators. Numerous studies have conducted dynamic OD estimations based on fixed detectors, where a high device coverage rate and data quality are often required to accomplish the desired results. Several existing methods have used probe vehicle trajectories as an additional data source, and generalized least squares (GLS) is commonly recognized as an effective framework. However, the prior matrices used in these models either came from historical data or data obtained by uniform scaling that neglected the variation in penetration rates and suffer from sparsity issues. Moreover, the microscopic information contained in the high-resolution probe vehicle trajectories has not been fully utilized. The possibility of estimating OD flows using only vehicle trajectories without external information is rarely discussed in current literature. Therefore, this paper introduces a dynamic OD flow estimation model solely using probe vehicle trajectories. In the proposed model, two methods based on probe OD pair distribution are proposed to infer prior OD flows. Then the GLS framework is extended by including link travel times as another objective term, and the solution algorithm is adapted to deal with uncertain priors. To validate the proposed model, extensive experiments were conducted on a simulation network. The results show that the proposed model could reliably estimate dynamic OD flows and showed superiority to two existing models. In sensitivity analysis concerning the penetration rate and degree of saturation, the proposed model presented satisfactory performance and could adapt to various conditions. [ABSTRACT FROM AUTHOR]

Signal phase and timing (SPaT) information is a necessary input for traffic performance evaluation. However, current SPaT estimation studies mainly focus on estimation of cycle length or green time of a certain movement, and are realized mostly by floating car data whose data quality significantly affects the estimation accuracy. As license plate recognition (LPR) systems are becoming a widely implemented and reliable data source in China, in this study, a SPaT estimation method is proposed using the LPR data for fixed-time controlled intersections. The SPaT estimation problem is formulated as a bi-level programming model to find the optimal match between the phase boundaries and the LPR passing time series in the study period. Evaluation is done with an empirical case and compared with an existing method, results show that the estimation accuracies of the phase duration can reach 90.0%, outperforming the existing method and demonstrating great potential for practical application. [ABSTRACT FROM AUTHOR]

A method for the determination of nine biogenic amines (BAs) in wine was established using ion chromatography–tandem mass spectrometry (IC-MS/MS) without derivatization. BAs were separated by a cation exchange column (IonPac CG17, 50 mm × 4 mm, 7 µm) with a gradient aqueous formic acid elution. Good linearity was obtained for nine BAs with coefficients of determination (R2) > 0.9972 within the range of 0.01–50 mg/L. The limits of detection and quantification were within the ranges of 0.6–40 µg/L and 2.0–135 µg/L, respectively, with the exception of spermine (SPM). The recoveries were demonstrated within the range of 82.6–103.0%, with relative standard deviations (RSDs) of less than 4.2%. This simple method featuring excellent sensitivity and selectivity was suitable for the quantification of BAs in wines. The occurrence of BAs in 236 wine samples that are commercially available in China was determined. The BA levels in wines of different geographical origins varied significantly. The acute dietary exposure assessment of BAs was carried out by calculating the estimated short-term intake (ESTI) and comparing the acute reference dose (ARfD) specified by the European Food Safety Authority (EFSA). Results showed that the exposure to histamine (HIS) and tyramine (TYR) via the consumption of wines was much lower than the recommended ARfD level for healthy individuals. However, exposure could lead to symptoms in susceptible individuals. These results provided basic data regarding the occurrence and risk of BAs in wines for wine production, health guidance and consumer safety. [ABSTRACT FROM AUTHOR]

Organic single crystals with low defect density are key functional materials for next‐generation electronics. Classical crystallization commonly results in a high density of molecular steps, which are defects that can trap charge carriers and reduce the mobility of organic semiconductors. Herein, a novel nonclassical crystallization mechanism involving nucleation, fusion, and growth is designed. The introduction of the fusion stage changes the crystal growth mode from three‐dimensional island growth to two‐dimensional layer‐by‐layer growth and leads to large‐area two‐dimensional molecular crystals with almost no molecular steps. Therefore, the average mobility is observed to improve from 1.26 to 2.07 cm2 V−1 s−1. The nonclassical crystallization mechanism paves the way for atomically flat single crystals to probe the intrinsic optoelectronic properties of organic semiconductors. [ABSTRACT FROM AUTHOR]