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Ensuring compliance with safety regulations regarding wearing is essential for the safety and security of those working on substation construction sites. However, relying on supervisors to monitor workers in real time on the work site or through remote surveillance videos is both unreasonable and inefficient. A deep learning network approach named FFA-YOLOv7 is presented in this study that utilizes an improved version of YOLOv7 to detect violations of worker wearing in real time during power construction site surveillance. In YOLOv7, the feature pyramid network (FPN) of the neck stage is constructed through continuous upsampling and skip connections for feature fusion, after continuous downsampling of the backbone. However, this process can result in the loss of precise shallow position information. To tackle this issue, we have introduced a novel feature fusion pathway to the FPN architecture, enabling each layer not only to fuse feature maps from the same level during the downsampling course but also to fuse feature maps from shallower levels. This approach combines precise positional information from shallow layers with rich semantic information from deep layers. Additionally, we utilized attention after feature fusion in each layer to optimize the feature map fusion effect and achieve better detection accuracy performance. In order to conduct comparative experiments, we trained six variations of the YOLO model as detectors using a dataset gathered from realistic construction sites. The experimental results indicate that our proposed FFA-YOLOv7 attained a detection precision of 95.92% and a recall rate of 97.13%, demonstrating a high level of accuracy and a low rate of missed detections. These outcomes effectively satisfy the requirements for robust and accurate detection of real-world power construction violations.

The E3 deubiquitinating enzyme ubiquitin-specific proteolytic enzyme 21 (USP21) plays vital roles in physiological activities and is required for Treg-cell-mediated immune tolerance. Using a murine model infected with Schistosoma japonicum, we observed that there were more cercariae developed into adults and more eggs deposited in the livers of the USP21fl/flFOXP3Cre (KO) mice. However, immunohistochemistry showed that the degree of egg granuloma formation and liver fibrosis was reduced. In USP21fl/flFOXP3Cre mice, levels of IFN-gamma, IL-4, anti-soluble egg antigen (SEA) IgG and anti-soluble worm antigen preparation (SWAP) IgG increased in blood, as determined using ELISAs and multiplex fluorescent microsphere immunoassays, while the levels of IL-10, lL-17A, IL-23, IL-9, and anti-SEA IgM decreased. In addition, the levels of the USP21 protein and mRNA in the liver and spleen of KO mice decreased. We further observed increased Th1 responses amplified by Tregs (regulatory T cells) and compromised Th17 responses, which alleviated the liver immunopathology. We speculated that these changes were related to polarization of Th1-like Tregs. Our results revealed the roles of USP21 in Treg-cell-mediated regulation of immune interactions between Schistosoma and its host. USP21 may have potential for regulating hepatic fibrosis in patients with schistosomiasis.

Sorghum (Sorghum bicolor (L.) Moench) is one of the most important cereals in the Northeast China. The physicochemical, pasting, texture, and cooking properties of 21 sorghum varieties were determined, which were mainly cultivated in Northeast China. Then, the evaluation of edible quality of sorghum was based on principal component analysis and fitted with the score of sensory evaluation. Five principal components (PCs) with a cumulative contribution rate of 86.19% could be picked out to describe the taste, pasting, flavor, cooking, and variety of sorghum, respectively. And a comprehensive equation of sorghum edible quality in Northeast China was constructed which was Z = 0.45F1 + 0.25F2 + 0.12F3 + 0.10F4 + 0.08F5. The edible quality of No. 14 and No. 15 was the best. The sensory evaluation was used to verify the above equation with the fitting coefficient of 0.81, which indicated that the equation could be more accurate to evaluate the edible quality of sorghum in Northeast China.

Soil respiration (Rs) is a major pathway for carbon cycling and is a complex process involving abiotic and biotic factors. Biological soil crusts (BSCs) are a key biotic component of desert ecosystems worldwide. In desert ecosystems, soils are protected from surface disturbance by BSCs, but it is unknown whether Rs is affected by disturbance of this crust layer. We measured Rs in three types of disturbed and undisturbed crusted soils (algae, lichen, and moss), as well as bare land from April to August, 2010, in Mu Us desert, northwest China. Rs was similar among undisturbed soils but increased significantly in disturbed moss and algae crusted soils. The variation of Rs in undisturbed and disturbed soil was related to soil bulk density. Disturbance also led to changes in soil organic carbon and fine particles contents, including declines of 60–70% in surface soil C and N, relative to predisturbance values. Once BSCs were disturbed, Q10 increased. Our findings indicate that a loss of BSCs cover will lead to greater soil C loss through respiration. Given these results, understanding the disturbance sensitivity impact on Rs could be helpful to modify soil management practices which promote carbon sequestration.