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The detection of traffic signs is easily affected by changes in the weather, partial occlusion, and light intensity, which increases the number of potential safety hazards in practical applications of autonomous driving. To address this issue, a new traffic sign dataset, namely the enhanced Tsinghua-Tencent 100K (TT100K) dataset, was constructed, which includes the number of difficult samples generated using various data augmentation strategies such as fog, snow, noise, occlusion, and blur. Meanwhile, a small traffic sign detection network for complex environments based on the framework of YOLOv5 (STC-YOLO) was constructed to be suitable for complex scenes. In this network, the down-sampling multiple was adjusted, and a small object detection layer was adopted to obtain and transmit richer and more discriminative small object features. Then, a feature extraction module combining a convolutional neural network (CNN) and multi-head attention was designed to break the limitations of ordinary convolution extraction to obtain a larger receptive field. Finally, the normalized Gaussian Wasserstein distance (NWD) metric was introduced to make up for the sensitivity of the intersection over union (IoU) loss to the location deviation of tiny objects in the regression loss function. A more accurate size of the anchor boxes for small objects was achieved using the K-means++ clustering algorithm. Experiments on 45 types of sign detection results on the enhanced TT100K dataset showed that the STC-YOLO algorithm outperformed YOLOv5 by 9.3% in the mean average precision (mAP), and the performance of STC-YOLO was comparable with that of the state-of-the-art methods on the public TT100K dataset and CSUST Chinese Traffic Sign Detection Benchmark (CCTSDB2021) dataset. [ABSTRACT FROM AUTHOR]

• Herein, a reliable method using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) was established in order to conduct a comprehensive analysis of chemical constituents of DZP, as well as their metabolites in rat plasma, urine and feces after gastric perfusion. • The metabolic pathways, including phase I reactions (hydroxylation, dehydroxylation and hydrogenation) and phase II reactions (acetylation, sulfation, glucuronidation and methylation), for the absorbed constituents, were explored and summarized. • This is the first systematic study on the components of DZP and their metabolites in vivo. Results from this study provide a valid analytical strategy for the characterization of chemical compounds and metabolites of TCM formulas. • Moreover, an integrative strategy was proposed for the characterization and identification of chemical constituents and metabolites for additional TCM prescriptions. A reliable method using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) was established to conduct a comprehensive analysis of the chemical constituents of Du-zhi pill (DZP) as well as their metabolites in rat plasma, urine and feces after gastric perfusion. The efficient on-line mass data acquisition modes combined the various off-line mass data mining strategy was applied. A full mass scan was performed, and then accurate MS/MS datasets were obtained through the use of a multiple mass defect filter (MMDF) and dynamic background subtraction (DBS)-dependent data acquisition method. Furthermore, post-acquisition data processing was conducted using various data-mining tools, including extracted ion chromatography (XIC), mass defect filtering (MDF), product ion filtering (PIF), and neutral loss filtering (NLF) (MetabolitePilot™). Finaly, a total of 176 compounds were identified or tentatively characterized in DZP. Moreover, a total of 233 components in vivo , which includes 92 prototype components and 141 metabolites, were unambiguously or tentatively identified in rat plasma, urine and feces. The metabolic pathways, including phase I reactions (hydroxylation, dehydroxylation and hydrogenation) and phase II reactions (acetylation, sulfation, glucuronidation and methylation), for the absorbed constituents, were explored and summarized. This is the first systematic study on the components of DZP and their metabolites in vivo. This study provide a valid analytical strategy for the characterization of chemical compounds and metabolites of TCM formulas. Moreover, an integrative strategy was proposed for the characterization and identification of chemical constituents and metabolites for additional TCM prescriptions. [ABSTRACT FROM AUTHOR]

Hypericin is widely utilized for its precise antidepressant properties, but its exact antidepressant mechanism remains unclear. Gap junctions, which were predominantly expressed in astrocytes in the central nervous system, are concerned with the pathogenesis of depression. However, the role of hypericin in gap junctional dysfunction in depression has rarely been investigated. Here, we found that gap junctions were ultra-structurally broadened in the chronic unpredictable stress (CUS) rat model of depression, while hypericin repaired the dysfunction of gap junctions. Suppression of gap junctions by bilateral injection of carbenoxolone (CBX) in the prefrontal cortex of rats significantly inhibited the restoration of gap junctional dysfunction in depression by hypericin. Meanwhile, hypericin failed to show antidepressant benefits. Furthermore, in corticosterone (CORT)-stimulated primary astrocytes derived from neonatal rats, hypericin dramatically reversed the phosphorylation of connexin 43 (Cx43), normalizing the expression of Cx43 and thereby ameliorating gap junctional dysfunction. Comparatively, CBX inhibited the remission of hypericin on gap junctional intercellular communication function. Gap junctional function might be a novel therapeutic target for hypericin in the treatment of depression and provide potential novel insights into the antidepressant mechanism of other herbal ingredients. [Display omitted] • Hypericin has therapeutic efficacy in treating depression. • Hypericin repaired the dysfunction of gap junctions in depression. • Hypericin interacts with Cx43-gap junction channel by molecular docking. • Hypericin relieves depression by improving Cx43-based gap junctional function. [ABSTRACT FROM AUTHOR]

During the rice quality testing process, the precise segmentation and extraction of grain pixels is a key technique for accurately determining the quality of each seed. Due to the similar physical characteristics, small particles and dense distributions of rice seeds, properly analysing rice is a difficult problem in the field of target segmentation. In this paper, a network called SY-net, which consists of a feature extractor module, a feature pyramid fusion module, a prediction head module and a prototype mask generation module, is proposed for rice seed instance segmentation. In the feature extraction module, a transformer backbone is used to improve the ability of the network to learn rice seed features; in the pyramid fusion module and the prediction head module, a six-layer feature fusion network and a parallel prediction head structure are employed to enhance the utilization of feature information; and in the prototype mask generation module, a large feature map is used to generate high-quality masks. Training and testing were performed on two public datasets and one private rice seed dataset. The results showed that SY-net achieved a mean average precision (mAP) of 90.71% for the private rice seed dataset and an average precision (AP) of 16.5% with small targets in COCO2017. The network improved the efficiency of rice seed segmentation and showed excellent application prospects in performing rice seed quality testing. [ABSTRACT FROM AUTHOR]

In the present study, thin-layer drying has been applied to improve drying efficiency and perfume production from E. rutaecarpa. Thus, the effects of the drying kinetics and temperature on the quality of E. rutaecarpa for essential oil production were studied. Seven kinds of mathematical models, such as Midilli et al., Overhults et al. and Lewis et al., were applied to model and verify the relationship between moisture ratio and time in the drying process. The Midilli et al. model could simulate the drying process very well. The essential oils obtained before and after different drying process were extracted via steam distillation, and the extracted essential oil components were identified with GC-MS. The moisture diffusion of E. rutaecarpa under hot air drying and vacuum drying at 35°C, 45°C and 55°C are 8.39×10-9, 1.07×10-8, 1.37×10−8, and 1.02×10−8, 1.16×10−8, 1.19×10−8, respectively, and the activation energy is 20.51 kJ/mol and 6.63 kJ/mol. Based on the quality of the essential oil of the E. rutaecarpa leaves obtained at different temperatures, the proposed approximate drying temperature of E. rutaecarpa for application was 45-55°C. During the drying process, the moisture of E. rutaecarpa in this temperature range may drop below the safe moisture within 7-5.5 h for storage with 12.1-9.7 % essential oil loss. This study showed the oil quality and quantity of the essential oil of E. rutaecarpa as well as the fresh sample in different drying methods and drying temperatures were compared, while the drying quality of E. rutaecarpa was further compared. [ABSTRACT FROM AUTHOR]