Extraction methods and compositions of polyphenols in Shanxi aged vinegar.

The extraction, purification, qualification, and quantification of polyphenols (PPs) in vinegar are challenging owing to the complex matrix of vinegar and the specific physicochemical and structural properties of PPs. This study aimed to develop a simple, efficient, low-cost method for enriching and purifying vinegar PPs. The enrichment and purification effects of five solid phase extraction (SPE) columns and five macroporous adsorption resins (MARs) for PPs were compared. The results show that SPE columns were more effective in purifying vinegar PPs than MARs. Among them, the Strata-XA column showed a higher recovery (78.469 ± 0.949%), yield (80.808 ± 2.146%), and purity (86.629 ± 0.978%) than other columns. In total, 48 PPs were identified and quantified using SPE and gas chromatography-mass spectrometry from the SPE column extracts; phenolic acids, such as 4-hydroxyphenyllactic acid, vanillic acid, 4-hydroxycinnamic acid, 4-hydroxybenzoic acid, protocatechuic acid, and 3-(4-Hydroxy-3-methoxyphenyl) propionic acid, occupy a major position in SAV. Furthermore, considering the potential applications of PPs, the concentrates were characterized based on their bioactive properties. They exhibited high total PP, flavonoid, and melanoidin contents and excellent anti-glycosylation and antioxidant activities. These results indicate that the established methodology is a high-efficiency, rapid-extraction, and environment-friendly method for separating and purifying PPs, with broad application prospects in the food, chemical, and cosmetic industries.

Noise-tolerant Bessel-beam single-photon imaging in fog.

Reliable laser imaging is crucial to the autonomous driving. In unfavorable weather condition, however, it always suffers from the acute background noise and signal attenuation due to the harmful strong scattering. We demonstrate a noise-tolerant LiDAR with the help of Bessel beam illumination and single-photon detection. After a 31.5-m propagation in thick fog, the Bessel beam employed by our noise-tolerant LiDAR still owns a central spot with the diameter of 1.86 mm, which supports a receiving field of view as small as 60 µrad and a great suppression of the background noise. This noise-tolerant LiDAR simultaneously performs well both in depth and intensity imaging in unfavorable weather, which can be functioned as a reliable imaging sensor in automatic driving.