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Zhengjiang Wang,1,2,* Jiaqi Xu,1,2,* Liqun Mo,1 Renshu Zhan,1,2 Jin Zhang,3 Li Liu,1,2 Jun Jiang,4 Yingying Zhang,1,2 Yiping Bai1,2 1Department of Anesthesiology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan Province, 646000, People’s Republic of China; 2Anesthesiology and Critical Care Medicine Key Laboratory of Luzhou, Southwest Medical University, Luzhou, Sichuan Province, 646000, People’s Republic of China; 3Department of Pharmacology and Toxicology, University of Mississippi Medical Center, Jackson, MS, 39216, USA; 4Department of General Surgery (Thyroid Surgery), The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan Province, 646000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yingying Zhang; Yiping Bai, Email yingyingzhang917@gmail.com; baiyiping0608@163.comAbstract: Irisin is a muscle factor induced by exercise, generated through the proteolytic cleavage of the membrane protein fibronectin type III domain-containing protein 5 (FNDC-5). Numerous studies have shown that irisin plays a significant role in regulating glucose and lipid metabolism, inhibiting oxidative stress, reducing systemic inflammatory responses, and providing neuroprotection. Additionally, irisin can exert immunomodulatory functions by regulating regulatory T cells (Tregs). Tregs are a highly differentiated subset of mature T cells that play a key role in maintaining self-immune homeostasis and are closely related to infections, inflammation, immune-related diseases, and tumors. Irisin exerts persistent positive effects on Treg cell functions through various mechanisms, including regulating Treg cell differentiation and proliferation, improving their function, modulating the balance of immune cells, increasing the production of anti-inflammatory cytokines, and enhancing metabolic functions, thereby helping to maintain immune homeostasis and prevent immune-related diseases

As an effective way to facilitate the increasing demand for reliable infrastructure, energy supply and sustainable urban development, underground utility tunnels have been developed rapidly in recent years. Due to the widespread distribution of utility tunnels, the safe operation of natural gas pipelines accommodated in utility tunnels has caused great concern considering fire, explosion, and other coupling consequences induced by the gas pipeline leakage. However, the limited information on leakage source terms in accidental leakage scenarios could preclude timely consequence assessment and effective emergency response. In this study, a BI-IEnKF coupling source term estimation (STE) model is developed, with the combination of gas dispersion model, Bayesian inference (BI) and iterative ensemble Kalman filter (IEnKF) method, to achieve the effective source term estimation (including leakage location and leakage rate) and gas concentration distribution prediction. The newly developed model is first evaluated by the twin experiment with good reliability and accuracy. Furthermore, three contributing factors affecting the performance of the developed BI-IEnKF coupling STE model were investigated to assist parameter selection for practical use. Additionally, the novel application of mobile sensors serving as an alternative for fixed sensors is explored, and an application framework is sequentially given to guide the deployment of the developed coupling model in utility tunnels. The results show that the developed model has great performance in accuracy, efficiency and robustness, as well as the potential to be applied in actual utility tunnel scenarios. This study can provide technical supports for safety control and emergency response in the case of natural gas pipeline leakage accidents in utility tunnels. Also, it could be helpful to reasonable references for gas lekage monitoring system design., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Civil Engineering & Geosciences, Safety and Security Science

Accidents induced by natural disasters at sports sites may cause catastrophic loss of great concern. However, previous studies on risk assessments of sports sites have only focused on operational risk and equipment failure. With the frequent occurrence of extreme disasters, the risk of domino chains caused by natural disasters at large-scale events, such as large-scale winter sports sites, cannot be ignored. In this study, a natural disaster-induced accident-chain evolution analysis model (NAEA model) is proposed. Based on the results of the NAEA model, a fuzzy Bayesian network for domino accidents triggered by an earthquake at large-scale winter sports sites was established. Through sensitivity analysis and scenario analysis, it was found that fire and explosion accidents and crowded stampede accidents are the main causes of serious loss in domino disaster chains in large-scale sports sites. Simultaneously, improving the early warning capability, reliability of electrical equipment, and automatic sprinkler systems are the most effective ways to prevent and control major accidents. In addition, an optimal safety strategy improvement analysis was performed to facilitate the decision-making of safety managers to prevent serious accidents and reduce accident loss., Safety and Security Science

In recent years, frequent large-scale power grid accidents have caused serious economic losses and bad social impact, which has drawn great attention from power grid enterprises. As one of the key elements of production, safety investment plays an important role in improving the safety level and reducing accident loss. In this paper, System dynamics (SD) and Bayesian network (BN) are integrated to develop a novel safety investment optimization model for power grid enterprises, which takes into account the impact of safety investment factors on accidents and the interactions between them. Based on sensitivity analysis, critical safety investment factors are determined to form the subsystem of the SD model. Subsequently, the optimal safety investment strategy is determined by a three-step simulation. The simulation results show that there are barrel effects and a diminishing marginal utility in safety investment. The proposed safety investment optimization model is practical to provide technical supports and guidance for determining an effective safety investment strategy in power grid enterprises., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Safety and Security Science