In order to timely and effectively detect the explosives hidden in luggage，packages and individuals，multiple explosives such as trinitrotoluene(TNT)，hexahydro-1，3，5-trinitro-1，3，5-triazine(RDX)，triacetone triperoxide(TATP)，ammonium nitrate(AN)，etc. were detected by FQ and IMS instruments by wiping and aspiration sampling methods. The comparison was mainly made from two aspects: alarm time and recovery time. The experimental results show that under wiping sampling，the average alarm time of FQ is about 2 seconds less than that of IMS，and the average recovery time is about 30 seconds less than that of IMS，which has higher detection efficiency. In the case of aspirated sampling，FQ instruments can detect TNT and TATP，while it is difficult for IMS instruments to detect explosives.

To definite the diffusion characteristics of blasting fumes in downward drift filling mining stopes，taking the downhole filling mining method of Longshou Mine in Jinchuan as an example，numerical simulations and field tests were conducted. The spatial distribution of airflow in drifts and layered roads was studied，and the diffusion patterns of CO and NO₂ in drifts were analyzed. Furthermore，the effects of ventilation shaft locations and drift lengths on CO diffusion were explored，and the ventilation parameters of the Longshou Mine were determined. The results indicated that the airflow field in drifts and layered drifts can be divided into the inflow zone，neutral zone，and return zone. The airflow velocity in the drift. shows the S-shaped distribution，with higher velocity at the bottom，lower in the middle，and moderate at the top. In the vertical cross-section of the drift，the CO volume fraction continuously increases with height. While horizontally，it exhibits a "decrease-then-increase" pattern from the inner to outer side. At the drift waistline，the CO diffusion velocity shows a logarithmic decreasing trend with ventilation time.NO₂ is primarily concentrated below the midline of the drift，and its diffusion velocity is significantly faster than that of CO. The CO diffusion rate is negatively correlated with both the distance from the ventilation shaft to the drift entrance and drift length. When the distance between the ventilation shaft and the drift entrance is ≤40 m，and the drift length is ≤55 m，the CO and NO₂ concentrations in the natural ventilation blasting fumes are below the standard limits below after 30 minutes.

To quantify the transportation risks associated with biological samples using UAVs, this study first identified 32 risk factors across five dimensions-human, machine, environment, management, and hazard-based on national standards and relevant literature. A BN for risk assessment was constructed using Netica software, with prior probabilities determined through expert knowledge and fuzzy set quantitative analysis. The proposed risk assessment model was then used for bidirectional reasoning and scenario analysis. A case study of a UAV company in Shenzhen was presented to evaluate the transportation risks of biological samples and identify key influencing factors. The results indicate that the risk probability of biological sample transportation, as calculated through forward reasoning, is approximately 2.203×10^-5. The primary risk factors are related to hazardous materials, followed by equipment and facility-related issues. The core risk factors influencing biological sample transportation include the size, quantity and weight of hazardous material packages, the temperature control effectiveness of specialized cold chain logistics boxes, the integrity of emergency response plans, emergency handling capabilities, safety management and education, and the presence of obstacles.

In order to reveal the complex causality between EWSV and their multiple antecedent conditions，and to improve the efficiency of safety governance，a comprehensive model integrating contemporary deterrence theory，protection motivation theory，and social learning theory was constructed from a perspective of complexity theory. Based on this，six antecedent conditions affecting EWSV were identified from three perspectives: leader，coworker，and employee. Then，the fsQCA was used to reveal what configuration of antecedent conditions would lead to high level of EWSV. The results show that a single antecedent condition is insufficient to explain high level of EWSV but safety-specific leader punishment omission and coworker work safety violations(CWSV) play universal roles in forming high level of EWSV. Three types of driving modes composed of five condition configurations can lead to high level of EWSV. Three types of condition configurations lead to non-high level of EWSV. Reducing CWSV and improving employees' perception for formal sanctions are crucial for achieving non-high level of EWSV. Different combinations of multiple antecedent conditions can lead to high level of EWSV，and there is a complex causality (concurrency，equivalence，and asymmetry) between high level of EWSV and their antecedent conditions.

To clarify the essential characteristics and differences between inherent safety, behavior-based safety, process safety, and functional safety and to promote a virtuous cycle of high-quality development and high-level safety, this study employed literature review and comparative analysis methods to explore their basic connotations and evolution processes, interrelationships, realistic challenges, and development paths based on the safety management paradigm shift. The results indicate that inherent safety is an idealized form of safety. Behavior-based safety is an interdisciplinary field that involves the theories and methods of safety science and behavioral science. Process safety protects humans, machines, and the environment through systematic approaches from a full life cycle perspective. Functional safety aims at preventing unacceptable risks caused by functional failures of systems. The four types of safety, led by inherent safety, involve a gradual progression from concepts to practice. These types of safety share a unified internal structure encompassing the elements of humans, machines, environment and management. The current representative standards cover various industry sectors and focus on accident prevention. In the future, the synergistic effect of the four in safety governance should be fully utilized. By using artificial intelligence technology to empower the new engine of safety production, the four should be continuously improved in specific practices tailored to local conditions.

In order to improve urban governance and promote sustainable development，the resilience measurement of core cities in Chinese mainland was analyzed based on panel data from 25 core cities (municipalities directly under the central government，provincial capitals，and regional capitals) between 2011 and 2020. Technique for order preference by similarity to an ideal solution(TOPSIS)-Entropy Weight Method was applied. The resilience situation for 2026 and 2029 was predicted using a BP neural network model. This research aimed to explore the dynamic spatial differentiation of regional resilience. The results show that the standard deviation of the resilience index across cities fluctuates around 0.180，with the resilience disparity between cities remaining relatively stable. However，some cities show a downward trend in their resilience index year by year. The standard deviation of the predicted resilience index for 2026 decreases to 0.173，indicating a reduction in the resilience disparity between cities and a narrowing of the resilience gap. In the four time points of 2014，2020，2026，and 2029，the spatial heterogeneity of urban resilience evolves relatively stably. The urban resilience rankings are as follows: Eastern region > Central region > Western region > Northeastern region. Among them，the economic and infrastructure resilience in the Eastern region is the highest，while the social and ecological resilience in the Central region is the highest.

In order to clarify the correlation of eVTOL risk factors，and explore their impact on risk prevention and control in the UAM ecosystem，complex network theory was used to establish a risk evolution model. Based on the UAV accident database at home and abroad and the statistics of general aviation accidents，combined with the operation characteristics of eVTOL in urban low-altitude scenes，35 types of risk factors and 10 types of dangerous events were identified from the perspective of human-machine-environment. Gephi software was used to construct the network model，and the key nodes were evaluated comprehensively by the node degree，proximity centrality，internode centrality and PageRank(PR) algorithm. The key edges were evaluated by the internode number，so as to determine the key risk propagation path. In order to reduce the system risk，the measures to reduce the chain breaking disaster were proposed，and the system safety after chain breaking control was measured by network efficiency index. The results show that there are strong correlations among the eVTOL risk factors in the UAM ecosystem，and there are eight key risk transmission chains. The system safety is improved by 4.74%，16.21% and 18.10% by blocking key human factors，key system technical failure factors and key intermediate dangerous events，respectively.

Cultivating professional master's students is essential to addressing the shortage of high-level applied talents. To meet the industry demand for safety engineering professionals, this study analyzes challenges in China's training processes based on domestic and international practices. It introduces the "professional group + action learning method" model, alongside reforms in curriculum, teaching methods, training bases, faculty, and evaluation standards, using China University of Mining and Technology-Beijing as a case study. Data from the 2023 cohort validate the model's effectiveness in improving graduate quality, enhancing competencies, and addressing traditional education shortcomings, proving its feasibility and reference value.

In order to address the "fragmentation" issue in emergency collaboration networks and enhance the effectiveness of emergency management in response to accident disasters，three typical accident disasters were selected. Based on theory of collaborative governance，a "network density-average path distance" analytical framework was constructed using SNA to map the collaborative relationships among various emergency response entities. At the macro level，indicators such as network size，density，shortest path，cohesion，and centralization were employed to portray the overall characteristics of the emergency collaboration networks. At the meso level，cohesive subgroups were analyzed to explore the clustering patterns of emergency collaboration，with the criterion for subgroup division being the professional nature of emergency matters in all three cases. At the micro level，the characteristics of nodes within the networks were evaluated through the triple indices of degree centrality，closeness centrality，and betweenness centrality. The results indicate that emergency collaboration networks of Changsha self-built building collapse，Xiangshui explosion，and Xinjia hotel collapse accidents exhibited tight-collaboration，tight-centralization，and loose-collaboration structures，respectively. It is recommended that the emergency collaboration networks be optimized from three dimensions: clarifying the rights and responsibilities of emergency response stakeholders，adjusting heterogeneous interest demands，strengthening the leadership of core nodes and leveraging their pivotal roles，and promoting the deep embedding of emergency culture to empower endogenous collaborative governance.

In order to promote the safe operation and safety management of wind turbines in icing areas during winter under the new situation，the safety risk of wind turbine falling ice，equipment operation risk，and power supply risk were analyzed，and they are the most serious risks of blade icing. Based on these risks，a comprehensive ice monitoring method based on the combination of blade ice thickness monitoring method and wind turbine operation data monitoring method was proposed，and the safe operation of the wind turbine was classified. This article elaborated on the design and construction process of the first composite coating anti-icing technology scheme for large-scale in-service wind turbines in China. The results indicate that the composite coating anti-icing technology solution can effectively solve the problem of wind turbine icing and can provide a reference for similar engineering projects.