To optimize the emergency management system for plateau disasters and to address the scientific demand for improving governance effectiveness under extreme plateau environments, this study developed a dual-network framework—"risk propagation-emergency response"—using the Ms6.8 Shigatse earthquake in Tibet as a case study. Based on complex network theory, it uncovered the cascading dynamics of seismic risks and multi-actor coordination governance patterns. The analysis demonstrates that the cascading disaster network exhibits a core-periphery structure, where critical nodes trigger multi-level chain reactions via infrastructure fragility and cultural sensitivity. Plateau-specific disaster chains are identified, such as "cold survival crisis → mass livestock deaths → pressure of harmless treatment", alongside culturally embedded risks like "language barriers" and "religious site damage", and their impacts further promote the cultural adaptive reconstruction of the traditional emergency management system. The coordination network shows a decentralized, short-path, high-density topology, indicating efficient collaboration despite persistent hierarchical redundancy.

In order to study the influence characteristics of different driving conditions on driving behavior of small-clearance interchanges, eye tracker was used to collect the drivers' eye movement data in the real vehicle experiment. k-medoids dynamic clustering method was used to divide the drivers' visual interest area. A comparative analysis of gaze behavior and saccade characteristics of drivers was conducted of under mainline entry and exit conditions at conventional clear-distance and small-clearance interchanges and across different driving stages. The driving behavior characteristics of drivers under high-density interchange of the expressway were revealed. The results show that drivers mainly focus on the area of road ahead and instrument panel, and they also pay special attention to the area of the left mirror when driving into mainline conditions. The 500 ms gaze time is a common time window for drivers to capture key information. The mean value of the gaze time on small-clearance interchange is higher than that on regular-clearance interchanges. There is a clear bias in observing the horizontal and vertical information in different driving phases. The mean gaze duration was higher in the small-clearance interchanges than in the conventional interchanges. The reduction of clear distance of the interchanges increases drivers' scanning amplitude and changed the scanning direction, which is most obvious in the interweaving section. The scanning amplitude is uniformly distributed in the range of 200 px. There is no significant difference in the mean distribution of fixation time between drivers of different driving ages. There is no significant monotonic relationship between the drivers' gaze duration and scanning speed and amplitude, while there is a significant positive correlation between scanning speed and amplitude of scanning.

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.

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.

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.

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 reduce the occurrence of building construction safety accidents, association rules were used to reveal the mechanism of accident association, and the optimized RF was fused to predict the occurrence of accidents. First, the causal factors of 388 case reports of construction safety accidents were extracted using 24Model as the theoretical basis. Then, Apriori algorithm was used to excavate the interrelated action paths between the accident causal factors. Finally, hyper-parameters of RF were optimized using GWO algorithm, and the GWO-RF prediction model of construction safety accidents was constructed. And the accident causal factors were the characteristic importance ranking was carried out. The results show that: unsafe behavior, safety ability of organization members, safety management system and safety culture elements constitute a combination of strong correlation conditions. GWO can effectively optimize the hyper-parameters of RF, and prediction accuracy of the optimized GWO-RF model is as high as 93.2%. The characteristic importance ranking shows that: safety education and training have the greatest influence on the prediction of construction safety accidents, with a weighting of 10.5% and a weighting of 10.5%. The importance ranking of features shows that: safety education and training has the greatest influence on the prediction of building construction safety accidents, with a weight of 10.5%. And safety integration management, safety production rules and regulations, and safety production responsibility system are the important factors affecting the prediction of building construction safety accidents, with weights of 7.5%, 7%, and 6%, in that order.

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.

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).

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.