To prevent accidents caused by miners' unsafe behaviors induced by physical fatigue and reduce the impact of physical fatigue on safe behaviors abality, a physical fatigue response test was carried out. First, forty adult male participants were equally divided into two groups, with each group induced to develop MEF and MPF respectively. Subsequently, a series of operational performance tests were conducted to measure attention level, reaction speed, judgment accuracy, and body coordination ability. Then, paired sample t-tests were employed to analyze pre- and post-fatigue behavioral data, investigating the effects of physiological fatigue on safety-related performance capabilities. Finally, evidence-based management recommendations were formulated according to the analytical results. The findings reveal that muscular endurance fatigue significantly compromise attention levels through its effects on mean pupil diameter(P<0.01), blink frequency(P<0.01), and saccadic rate(P<0.05). While muscular explosive power fatigue also demonstrates measurable influence on attentional performance as evidenced by altered pupil diameter(P<0.01), its effect magnitude is statistically inferior to that of endurance fatigue. Also, muscular explosive power fatigue reduces the body coordination ability, as both hand-eye coordination ability(P<0.05) and fine operation ability(P<0.05)have significantly declined. However, muscle explosive fatigue does have a certain improvement effect on reaction speed, with simple reaction time increasing by 0.028 s(P<0.01) and comprehensive reaction time increasing by 0.020 s(P<0.01). Physiological fatigue has no significant impact on judgment accuracy.

In order to capture the evolving landscape of research on emergency-synergy in public health emergencies and systematically synthesize key studies and their characteristics in this domain, this study employed the scientific knowledge mapping tool CiteSpace to conduct a visual analysis of relevant literature from the past decade. Data were retrieved from core collections of China National Knowledge Infrastructure (CNKI) and Web of Science (WOS). Concurrently, existing research findings were systematically examined across five dimensions: synergistic models, mechanisms, subjects, decision-making processes, and model construction. The results indicate that research output on emergency-synergy in public health emergencies grew steadily alongside the progression of Corona Virus Disease 2019(COVID-19) pandemic, with a subsequent decline as the pandemic subsided. Overall publication volume in this field remains modest: the retrieval yielded 121 academic papers, 306 master's and doctoral theses, and 54 foreign-language documents. Research focus is predominantly concentrated in areas such as emergency management, collaboration mechanisms, and multi-stakeholder synergy. The analysis further reveals that evolutionary game theory and dynamic disease transmission theory have gained significant traction among researchers in modeling emergency-synergy. The synergistic mechanism featuring "government leadership, multi-party participation, and clear division of responsibilities" has garnered widespread recognition within the academic community. Nevertheless, challenges persist regarding the practical implementation of multi-subject emergency synergy under government leadership, warranting further in-depth investigation. It is projected that future research will advance toward theoretical refinement of emergency-synergy governance models and the diversification of synergistic subjects.

In order to clarify the research hotspots, development trends and accident risk characteristics of alcohol-based fuels, and point out the direction for the development of alcohol-based fuels, CiteSpace software was used to collect 3 951 relevant journal papers from 1978 to 2024 in China National Knowledge Infrastructure. Bibliometrics and knowledge map visualization analysis methods were used to systematically analyze the annual publication volume and subject distribution in this field, and analyze research hotspots from keyword co-occurrence, clustering and emergence. The results show that the research on alcohol-based fuels in China has experienced three stages of continuous growth, fluctuation adjustment and steady development. At present, driven by the development of national energy strategy and technology, the research attention has been steadily improved. The research involves many fields such as electric power, chemical industry, automobile, power and fuel. The research hotspots are highly concentrated in the four major themes of methanol fuel preparation technology, fuel cell application, power and environmental impact assessment of methanol fuel. Existing research significantly focuses on basic material properties and technology applications, and systematic research on safety risks is relatively scarce. Therefore, this paper further clarifies the bottleneck of current risk prevention and control, and puts forward that future research should focus on fuel intrinsic safety technology, construction of intelligent supervision system of the whole chain and improvement of emergency response capacity, so as to provide theoretical reference and direction for the safe development of alcohol-based fuel.

In order to effectively prevent the occurrence of civil aviation maintenance related events, a sample of 2 687 voluntary reports from the US Aviation Safety Reporting System (ASRS) database (2001-2023) was examined. Fourteen risk factors, including work environment and human factors, were analyzed using CiteSpace. Strong couplings between these factors were identified through UCINET and Gephi. The results show the following findings: Among the nine single risk factors, key risks are identified as landing gear system malfunctions, poor lighting, and rain (with frequencies of 103, 64, and 45, respectively). Among the five coupled risk factors, key risks are found to be airframe maintenance, communication breakdown, and human factors (with co-occurrence frequencies of 1 646, 1 448, and 1 206, respectively). The analysis of all risk factor couplings reveals that the strongest coupling exists between airframe maintenance and powerplant maintenance (with a weight value of 3 568). Additionally, a significant coupling relationship is observed between procedures and improper landing gear system operations (with a weight value of 118).

Safety management of long-distance oil and gas pipeline enterprises has been regarded as essential for ensuring energy security and maintaining social stability. As a key approach to enhancing safety management efficiency, audits of QHSE management systems are increasingly emphasized. In this study, traditional audit modes—including international safety rating audits, full-factor quantitative audits, and system certification audits—were systematically compared and analyzed. Additionally, the features and applicable contexts of emerging audit modes, such as data-driven audits and AI-based audits, were further explored. It was found that each audit mode presented distinct advantages and limitations, depending on the enterprise's stage of development, risk management demands, and resource capabilities. Accordingly, a comprehensive audit framework integrating conventional methods and intelligent technologies was constructed. Optimization strategies were proposed, including phased audit mode selection, risk-oriented focus, capacity enhancement, digital and intelligent transformation, and the establishment of a closed-loop rectification mechanism. The findings show that a multi-mode integrated audit system significantly improves the safety performance of long-distance oil and gas pipeline enterprises. The conclusions provide theoretical guidance and practical reference for the selection and optimization of QHSE audit modes in the oil and gas industry.

CBR can effectively address the issue of unclear elements in safety risk management. However, existing research lacks systematic reviews of its application status and development trends. To systematically summarize the current state of research on the application of CBR in construction safety risk management and to identify future research directions, this paper comprehensively reviewed 45 Chinese and 50 English papers, employing bibliometric analysis and content analysis. The results show that the number of publications shows a fluctuating upward trend and tends to stabilize, spanning multiple disciplines such as environmental science and computer science. Key scholars demonstrate both commonalities and differences in collaboration themes, with China ranking first in publication volume. The research themes have evolved from knowledge construction and methodological exploration toward integration and intelligent convergence. CBR has been widely applied in safety risk identification, analysis and assessment, response, and knowledge management, yet limitations remain regarding control targets, application scenarios, knowledge management, data integration, and workflow optimization. Future research should focus on expanding control targets, developing whole-process management scenarios, establishing collaborative knowledge management mechanisms, integrating multi-source heterogeneous data, and improving workflows to advance the development of intelligent safety risk management in construction projects.

In order to enhance the flight training capabilities of trainees, identify and evaluate flight trainees' situational awareness, an index system for evaluating flight trainees' situational awareness was established based on grounded theory. The combined weights were calculated using game theory to integrate subjective weights, which were determined by the G1 method, and objective weights, which were derived from the criteria importance through intercriteria correlation(CRITIC) method improved by the coefficient of variation method. Subsequently, a combined weighting cloud model was proposed: the digital characteristic values of the evaluation indices were input into a cloud generator to obtain situational awareness ratings, and the model was verified for the use of an example to evaluate the situation awareness of a flight trainee. The results indicate that the cloud model can comprehensively evaluate the situational awareness of flight trainees. The overall situational awareness of Trainee A was rated as excellent. Among the indicators, the flight discipline metric yielded the best evaluation result, contributing significantly to the maintenance of situational awareness. The flight operation skills metric was rated between the best and the poorest, while the professional knowledge indicator received the lowest score. Major deficiencies were identified in two primary evaluation indicators, emergency handling capability and adaptability to operational environments, which were found to adversely affect the maintenance of situational awareness.

To investigate the constituent elements and improve the performance of campus safety management work, the theoretical connotation and practical paths of the campus safety management evaluation system from the perspective of risk metaphor were explored. Firstly, the constituent elements of campus safety management were sorted out based on the safety management correlation model, and the dimensions of campus safety management were analyzed from the metaphorical characteristics of black swan risks, gray rhino risks, golden monkey risks, and white rabbit risks. Secondly, through sorting out campus safety policy texts and accident cases, the evaluation indicators for campus "safety management system-safety management behavior-safety management status" were systematically designed. Then, the weights of evaluation indicators were calculated using the fuzzy analytic hierarchy process(FAHP) and the entropy weight method(EWM). The game theory was introduced to determine the subjective-objective combined weights, and the technique for order preference by similarity to ideal solution was used to compare the levels of safety management performance. The safety management data of typical cases were entered into the information platform, and the campus safety management model was proposed for the evaluation results based on risk metaphor theory. The results show that the risk metaphor graph is an important tool for constructing campus safety management models by integrating multi-dimensional perspectives. The campus safety management evaluation system can present the scores of indicators at all levels and the overall safety management level, and the risk metaphor theory provides theoretical support and practical guidance for campus safety management.

To decouple the structural complexity of industrial and supply chains, address systemic risks, and enhance supply chain resilience, bidding transaction big data was employed. Taking the vaccine sector as an example, a framework for constructing a supply chain knowledge graph was designed, and a systematic supply chain knowledge graph was established. On this basis, complex network techniques were applied to examine the vulnerability and potential security risks of China's vaccine industry supply chain network from 2011 to 2023. The research encompassed complex knowledge queries of the industrial chain, an analysis of city degree distribution patterns, and simulations and analyses of supply chain risks. The study shows that the vaccine industry chain exhibits spatial imbalance, particularly between eastern and western regions. The production structure is highly dependent, with approximately 61.3% of vaccine varieties relying on a single manufacturer or overseas agent. Manufacturers with high centrality constitute potential risk points within the vaccine supply chain network, where disruptions to about 33 enterprises significantly hinder vaccine supply. Compared with core cities, the cumulative effects of cities with lower network status, such as Chongqing, Dalian, Shenzhen, and Shenyang, have a more pronounced impact on the efficiency of vaccine circulation.

To study the impact of cognitive bias on energy safety engineering decision-making, the Fukushima nuclear power plant accident was taken as the research object. A full-cycle decision-making analysis chain, covering risk identification (earthquake and tsunami assessment), crisis disposal (cooling system failure treatment), and aftermath management (information disclosure decision-making), was built through retrospective analysis of the accident timeline and key decision points. Cognitive psychology theory was used to analyze decision-making bias phenomena in energy engineering safety management, and the specific mechanisms of these biases in emergency response and risk assessment were revealed. Results show that six typical cognitive biases are present in the emergency decision-making during this accident, including confirmation bias, anchoring effect, representative heuristics, framing effect, loss aversion, and overconfidence. This analysis demonstrates that cognitive bias identification can enhance energy engineering safety management, and improve the effectiveness of safety emergency responses.