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Due to the complexity of the automobile manufacturing process, some flexible and delicate assembly work relies on manual operations. However, high-frequency and high-load repetitive operations make assembly workers prone to physical fatigue. This study proposes a method for evaluating human physical fatigue for the manual assembly of automobiles with methods: NIOSH (National Institute for Occupational Safety and Health), OWAS (Ovako Working Posture Analysis System) and RULA (Rapid Upper Limb Assessment). The cerebral oxygenation signal is selected as an objective physiological index reflecting the human fatigue level to verify the proposed physical fatigue evaluation method. Taking auto seat assembly and automobile manual assembly as an example, 18 group experiments were carried out with the ARE platform (Augmented Reality-based Ergonomic Platform). Furthermore, predictions of metabolic energy expenditure were performed for experiments in Tecnomatix Jack. Finally, it is concluded that the proposed physical fatigue evaluation method can reflect the human physical fatigue level and is more accurate than the evaluation of metabolic energy consumption in Tecnomatix Jack because of the immersion that comes with the AR devices and the precision that comes with motion capture devices.

With the thriving of online deliberation, Wikipedia's Article for Deletion (AfD) discussion has drawn a number of researchers' attention in the past decade. In this thesis we aim to solve two main problems: 1) how to help new users effectively participate in the discussion; and 2) how to make it efficient for administrators to make decision based on the discussion. To solve the first problem, we obtain a knowledge repository for new users by recognizing imperatives. We propose a method to detect imperatives based on syntactic analysis of the texts. And the result shows a good precision and reasonable recall. To solve the second problem, we propose a decision making support system that provides administrators with an reorganized overview of a discussion. We first divide the arguments in the discussion into several groups based on similarity; then further divide each group into subgroups based on sentiment (positive, neutral and negative). In order to classify sentiment polarity, we propose a recursive algorithm based on the dependency structure of the text. Comparing with the state of the art sentiment analysis tool by Stanford, our algorithm shows a promising result of 3-categories classification without requiring a large training dataset.

Syphilis is a relatively common sexually transmitted disease worldwide. Its occurrence in pregnant women not only impacts their quality of life but also leads to various adverse pregnancy outcomes (APOs), including the potential for congenital syphilis. This study sought to examine adverse pregnancy outcomes in offspring among population witl syphilis infection. Multivariate logistic regression model was used to analyze the associations between maternal syphilis infection and APOs, and to explore its stability through subgroup analysis. Our study population consisted of 1624 with syphilis in Nanning, Guangxi spanning from 2016 to 2020. Among these women, 1426 (87.81%) did not experience APOs, whereas 198 (12.19%) did. The mean age of the participants was 31.46 ± 6.08 years, with most women being first married, accounting for 77.03%. Notably, 53.08% women were belonged to the Zhuang ethnicity, and 39.16% were of Han nationality. 57.14% reported a prior syphilis infection, and 20.26% had a history of APOs with their children. The multivariate logistic regression analysis revealed that being under 20 years of age (OR: 1.911, 95% CI 1.077–3.392), having an unknown titer prior to delivery (OR: 1.792, 95% CI 1.194–2.688), and undergoing non-standardized treatment (OR: 1.448, 95% CI 1.064–1.971) emerged as significant risk factors. The implementation of comprehensive preventative measures including early syphilis screening, eugenics assessment and standardized treatment and follow-up care for pregnant women with syphilis, is of great significance in reducing the incidence of APOs in this population.

Background: In dairy cows, the stress-related cortisol level increases the susceptibility to postpartum uterine diseases. Oxidative stress is an important component of the disease process and causes morphological and functional alterations in the bovine endometrium. Selenium (Se) has an antioxidant property, and an appropriate Se supplementation is recommended to enhance bovine disease resistance. Methods and results: Here, we aimed to answer two questions: (1) how does cortisol affect the oxidative status of bovine endometrial cells; and (2) does Se supplementation protect cells from oxidative injury with a high cortisol condition? The oxidative stress of primary bovine endometrial epithelial cells (BEECs) was established by Escherichia coli lipopolysaccharide (LPS) stimulation, as marked by the increased oxidative markers and the suppressions of antioxidant indicators and Nrf2 signaling. In the absence of LPS, cortisol levels of 15 ng/mL showed a more significant antioxidative effect than cortisol levels of 5 and 30 ng/mL. In the presence of LPS, cortisol levels of 15 and 30 ng/mL elicited antioxidation, whereas 5 ng/mL of cortisol did not. Regardless of LPS stimulation, Se pretreatment of 1, 2, and 4 μM protected BEEC from oxidative stress, as evidenced by the decreased oxidative markers, increased antioxidant indices, and the activated Nrf2 signaling. With the presence of 30 ng/mL of cortisol, there was an enhanced Se antioxidant effect, which can be abolished by the block of cortisol receptor. Conclusions: Both cortisol and Se elicited antioxidant properties in BEEC through the Nrf2 pathway. In addition, the Se antioxidation was enhanced by cortisol.

The green transformation of heavy-polluting enterprises under the carbon peaking and carbon neutrality goals needs the escort of command environmental regulation. This paper takes the first round of Central Environmental Protection Inspection as a natural experiment, reflecting the degree of green transformation through the environmental, social, and governance (ESG) level of enterprises. Taking Chinese A-share listed companies in Shanghai and Shenzhen from 2010 to 2022 as the research object, a dual machine learning model is used to determine whether this system can improve the ESG level of enterprises and promote their green transformation. Using a dual machine learning model, it is found that the system can enhance the ESG level of enterprises and promote their green transformation. Mechanism analyses show that the system promotes green transformation by enhancing green innovation capability, safeguarding the rights and interests of upstream and downstream supply chain actors, and enhancing governance diligence, thus encouraging enterprises to assume environmental, social, and governance responsibilities. It is also found that at the macro-policy level, with the migration of the inspection area to the west and the strengthening of local environmental governance, and at the micro-firm level, the higher the degree of digitization and the larger the size of assets, the deeper the system effect on the green transformation of heavy-polluting enterprises. It is further found that the spillover effect of green transformation within industries strengthens the positive effect of the Central Environmental Protection Inspection on the green transformation of enterprises compared to the inter-industry.

Background Polycystic ovary syndrome (PCOS) is highly prevalent in women of reproductive age worldwide, exhibits highly heterogeneous clinical presentation and biochemical parameters, and has no cure. This study aimed to investigate the role of miR-34a-5p in PCOS, its effect on glycolysis in granulosa cells (GCs), and its potential contribution to follicular dysregulation. Methods Herein, Follicular follicular fluid (FF) samples were collected from six patients with PCOS and six healthy controls undergoing in vitro fertilization-embryo transfer. The isolated extracellular vesicles were characterized by transmission electron microscopy, nanoparticle tracking analysis, and western blotting. Additionally, miRNA sequencing was performed to identify differentially expressed microRNAs, and their functions were analyzed through transcriptomics. The In vitro effects of miR-34a-5p on glycolysis, cell proliferation, and apoptosis were assessed in human ovarian granulosa tumour cell line (KGN cells). Targets of miR-34a-5p were identified by dual-luciferase reporter assays, and quantitative real-time polymerase chain reaction and western blotting were performed to determine gene and protein expression. Results The level of miR-34a-5p in FF-derived extracellular vesicles derived from patients with PCOS was significantly higher than that of the control group. Transcriptomic analysis highlighted miR-34a-5p as a key regulator of glycolysis and apoptosis. Furthermore, in vitro analysis showed that miR-34a-5p targeted lactate dehydrogenase A (LDHA), inhibited glycolysis, reduced energy supply to GCs, and promoted apoptosis of KGN cells. Conversely, miR-34a-5p inhibition restored glycolysis function and cell viability. Conclusion The findings of this study show that miR-34a-5p mediates GC apoptosis in PCOS by targeting LDHA and inhibiting glycolysis, suggesting its crucial role in PCOS pathophysiology, and offering potential therapeutic targets for improving follicular development and fertility outcomes in patients with PCOS. Further research is needed to explore the clinical implications of miR-34a-5p and its use as a biomarker for early diagnosis and prognosis of PCOS.

Background: Both sarcopenia and frailty are prevalent in patients with decompensated cirrhosis and associated with negative outcomes. However, few studies investigated the impact of their coexistence on mortality. We aimed to evaluate the role of sarcopenia and frailty on survival in a cohort of hospitalized cirrhotics. Methods: This was an observational cohort study including 221 patients hospitalized for decompensated events. The cutoff for low skeletal muscle index (SMI) at the third lumbar vertebra level on computed tomography built by our previous work (male: SMI <46.96 cm2/m2; female: SMI <32.46 cm2/m2) was used for the diagnosis of sarcopenia. Individuals with a Frailty Index >0.38 were considered frail. The sample was divided into four groups: sarcopenia and frailty (SF); sarcopenia and non-frailty (SN); non-sarcopenia and frailty (NF); and non-sarcopenia and non-frailty (NN). Follow-up for survival lasted 2 years. Results: Sarcopenia and frailty were present in 21.7% and 14.5% of the patients, respectively. The frequency of frailty in the group of sarcopenic patients was significantly higher than in the patients without sarcopenia (27.1% versus 11%, p = 0.009). In the survival analysis, the SF group showed a higher hazard ratio (2.604 in model 1; 4.294 in model 2) for mortality when compared with the NN group. In addition, the concurrence of those two conditions does give rise to incremental risk for mortality when compared with the group with each disturbance separately, namely, the SN/NF group. Conclusion: In conclusion, cirrhotic patients with sarcopenia and frailty combined showed higher mortality risk.

With the continuous advancement of deep learning technologies, deep learning-based medical image segmentation methods have achieved remarkable results. However, existing segmentation approaches still face several key challenges, including the insufficient extraction of local and global information from images and the inaccurate selection of core features. To address these challenges, this article proposes a novel medical image segmentation architecture—local-global multi-scale attention network (LGMANet). LGMANet introduces an innovative local-global information processing block (LGIPB) to effectively facilitate the deep mining of both local and global information during the downsampling process. In addition, an efficient multi-scale reconstruction attention (EMRA) module is designed to help the model accurately extract core features and multi-scale information while effectively suppressing irrelevant content. Experiments on the ISIC2018, CVC-ClinicDB, BUSI, and GLaS datasets demonstrate that LGMANet achieves IoU scores of 85.28%, 82.67%, 70.07%, and 88.90%, respectively, showcasing its superior segmentation performance.

Skeletal muscle and fat tissue show distinct pathophysiological roles and pivotal functions. The culmination of muscle wasting and fat accumulation represents an opposite terminal of each state. Specifically, this situation has been designated as sarcopenic obesity. However, sarcopenic obesity still lacks a unanimous definition, diagnostic criteria, and generalized modalities for assessment in the context of versatile liver diseases. Moreover, the underpinning mechanisms by which a combination of abnormal skeletal muscle and fat tissue leads to the progression of liver disease and impairs health‐related consequences are still elusive. Additionally, the interplay between skeletal muscle and fat, and the driving factors that shift different body compositions are not well understood. Therefore, in this review, we discuss skeletal muscle and fat components, with the purpose of conceptualization, as well as interpret their roles in liver diseases. We focus on the definitions, diagnostic criteria, and currently available measurements for sarcopenic obesity in the literature. We comprehensively discuss recent data and evidence regarding the potential role of sarcopenic obesity in the development and progression of numerous liver diseases and associated conditions, including nonalcoholic fatty liver disease, chronic viral hepatitis, cirrhosis, and liver transplantation. Furthermore, explicit information related to the pathogenesis of sarcopenic obesity from basic research is also provided in this narrative review. Finally, we discuss, from the clinical perspective of view, how to manage sarcopenic obesity using nutritional, physical, and pharmacological methods. The multifactorial and complicated pathogenesis of sarcopenic obesity in the context of liver diseases. Highlights Sarcopenic obesity may contribute to the development and progression of various liver diseases. The pathogenesis of sarcopenic obesity in the context of liver diseases is multifactorial and complicated. Potential avenues for therapeutic intervention by modifying sarcopenic obesity are urgently required.

Phyllotaxy is a key determinant of intraspecific variation in leaf functional traits, with different leaflet positions often representing distinct strategies of resource acquisition and utilization. Yet, the extent to which such phyllotactic differentiation is modulated by ontogenetic stage remains poorly understood. Here, we examined saplings and adult trees of Fraxinus mandshurica, a dominant compound-leaved species in temperate broadleaf forests, by quantifying four leaf economic traits and four stomatal traits across six phyllotactic positions. We further assessed the relative influences of phyllotaxy and environmental factors, including soil total nitrogen, soil water content, and canopy openness, on trait variation at different ontogenetic stages. Our results showed that economic traits varied significantly along phyllotaxy, whereas stomatal traits were relatively conservative. The effects of ontogenetic stage on traits at a given phyllotactic position were trait-specific. Within-group correlations of economic traits and of stomatal traits remained stable across ontogenetic stages and were consistently stronger than between-group correlations. Sapling traits were more strongly affected by soil total nitrogen and soil water content, whereas those in adult trees were primarily shaped by soil water content and canopy openness. Moreover, both trait–trait and trait–environment associations were weaker at the leaflet level than at the compound-leaf level. Our study highlights the critical role of ontogenetic stage in shaping leaf trait responses to phyllotaxy and environmental change, providing new insights into the mechanisms underlying intraspecific trait variation in compound-leaved tree species.