In order to study the effect of different metal doping and precipitation temperatures on the catalytic oxidation of CO by Cu-Mn type catalyst, the co-precipitation method was used to prepare Cu-Mn type CO catalyst, and the catalytic oxidation of CO by Cu-Mn type CO catalyst under different metal doping and precipitation temperatures was tested and analyzed. The pore characteristics and surface crystal structure of the catalyst were obtained by automatic physical adsorption analyzer and X-ray diffraction (XRD). The reaction process of catalytic oxidation of CO was revealed by in-situ diffuse reflection infrared spectroscopy, and the potential application of the catalyst in coal mines was introduced. The results show that during the test time (within 80 s), with the increase of reaction time, the volume fraction of CO gradually decreased, slowly increased and then tended to be flat, and the amount of reactive CO substance gradually increased. The better the catalytic oxidation of CO, the larger the specific surface area, the smaller the average pore size and the larger the total pore volume. When the doped metals are Sn, Fe and Ce, the catalytic oxidation characteristics of the three catalysts are as follows: CuMnO_x-Ce>CuMnO_x-Sn>CuMnO_x-Fe, the amount of CO involved in the reaction was 0.015 3, 0.009 3 and 0.020 3 mol, and the removal efficiency of CO was 61%, 47% and 77%, respectively. When the precipitation temperature is 70 ℃, the number of crystal nuclei of the catalyst is significantly higher than that of the precipitation temperature is 60 and 80 ℃. When the precipitation temperature is 60, 70 and 80 ℃ respectively, the catalytic oxidation characteristics of the three catalysts are as follows: CuMnO_x-Ce-70>CuMnO_x-Ce-80>CuMnO_x-Ce-60, the amount of CO involved in the reaction was 0.019 45, 0.020 3 and 0.019 8 mol, and the elimination rates of CO were 74%, 77% and 75%, respectively. Abundant surface oxygen vacancy is the key factor to improve the performance of CO oxidation reaction and catalytic oxidation. The presence of CeO₂ contributes to the formation, oxygen activation and migration of carbon-containing species.

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.

To deeply understand the competitive adsorption characteristics of O₂/CH₄ gas mixtures on the coal surface, the pore distribution and chemical structure of the coal surface were analyzed using the Grand Canonical Monte Carlo(GCMC) method. Molecular simulation was used to investigate adsorption capacity and heat variations during the competitive adsorption of O₂/CH₄ gas mixtures under varying concentrations, pressures, and temperatures. Moreover, the competitive adsorption mechanism of O₂/CH₄ gas mixtures on the coal surface was revealed by adsorption selectivity. The results indicated that the isothermal adsorption curves were identical when the concentration ratio of O₂ to CH₄ was 7/3. The integrated adsorption heat under different conditions was approximately 19.5-20.0 J/g for O₂ and 24.0-24.8 J/g for CH₄. When the concentration ratio of O₂ to CH₄ ranged between 7/3 and 2/8, the integrated adsorption heat of O₂ was higher than that of CH₄. The increased temperature decreased the adsorption capacity of both gases but increased the adsorption selectivity of O₂ to CH₄. Moreover, the effect of gas pressure on competitive adsorption weakened with pressure increase. CH₄ adsorbed faster than O₂ under low gas pressures, and CH₄ reached saturation adsorption earlier than O₂ when the total pressure increased. When the O₂ concentration in the gas mixtures increased, the adsorption selectivity of O₂ for CH₄ decreased. However, CH₄ consistently showed higher adsorption competitiveness than O₂.

To improve the theory and practice of nuclear power plant emergency management, a bibliometric approach was applied using CiteSpace software. A total of 355 relevant journal articles were collected from the Web of Science (WoS) database. By constructing mixed co-occurrence maps of researchers and institutions, keyword co-occurrence maps, keyword clustering maps, and visual timelines of keyword frequency, the research hotspots, focal areas, research forces, development paths, and frontier trends in nuclear power plant emergency management were analyzed in detail. The results indicate that, influenced by the Fukushima nuclear accident, research on nuclear power plant emergency management has gradually increased since 2011, particularly in the areas of risk assessment and decision support. The field of nuclear power plant emergency management research is characterized by its diversity, with a primary focus on accident management, performance monitoring, decision-making, and the application of simulation technologies. The interconnections between these topics fully demonstrate the complexity of nuclear power plant emergency management as an interdisciplinary field. Currently, the nuclear power sector is undergoing rapid development, and the emergency management system and capabilities of nuclear power plants are continuously improving to reduce the risks of potential accidents. Research from the perspective of interdisciplinary collaboration on emergency preparedness, response, and strategies for nuclear power plants has become a significant and emerging research direction.

To explore the "last-mile" problem of grassroots emergency response capacity, a MCDM based on grey theory was proposed to analyze the rural emergency response capacity under conventional and unconventional states based on the resilience theory. Firstly, from the perspective of resilience, the influencing factors obtained from literature review and field investigation were selected and optimized to construct a model of the influencing factors of rural emergency response capacity. Secondly, the MCDM model was used as a framework to analyze the causality, logical hierarchy, and characteristic state of the influencing factors. Finally, the key factors for the enhancement of the rural emergency response capacity and the resilience of rural villages were identified through the multi-criteria decision-making analysis. The results show that the centrality of leadership team structure is 2.95 and the driving force is 6, which is a tier 1 factor. The centrality of village grid management is 3.08 and the driving force is 6, which is a tier 2 factor. The centrality of normative document development is 2.7 and the driving force is 5, which is a tier 3 factor. The centrality of village network construction is 3.54 and the driving force is 9, which is a tier 3 factor. Leadership team structure, village grid management, normative document development and village network building constitute decision-making intersections, which are key catch-alls for the improvement of village emergency response capacity and resilience.

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 solve the problems of ambiguity and randomness in the process of fire safety resilience assessment of subway stations, and then effectively improve the level of fire safety resilience of subway stations, the fire safety resilience assessment model for subway stations based on WSR- extension cloud theory was constructed. First, based on WSR methodology, the factors affecting the fire safety resilience of subway stations were analyzed around "physical", "matter", and "human". Combined with the characterization of the resilience absorption, resistance, recovery and adaptive ability, the fire safety resilience assessment index system of subway stations was established in five aspects, namely, equipment factors, environmental factors, organization and management, material and technology, and personnel factors. Second, based on the blind number theory to construct the blind number matrix and calculate the comprehensive score of qualitative indexes, the fire safety resilience level of subway stations is derived by using the theory of extension cloud theory. Finally, a station of the Qingdao subway was used as an example to carry out the example analysis. The results show that the subway station fire safety resilience level of Ⅳ, in the higher resilience level, the credibility factor = 0.003 4 <0.01, indicating that the assessment results have a high degree of credibility. The WSR-extension cloud theory assessment model can provide a theoretical basis for the fire safety resilience assessment of subway stations.

To meet the growing demand for emergency talent in regional industrial development, the "government, industry, academia, research, and application" education model was used to investigate an integrated training model for emergency talent from undergraduate to master and doctoral degrees. Based on the issues of unclear hierarchical demands, core competency assessments, and knowledge system construction in the Western emergency industry, the FP-Growth algorithm was used to mine and divide the association rules between courses and corresponding competencies to evaluate core competency. Safety engineering capabilities were compared to determine the focus of capability training and explore talent training pathways. The industry-specific undergraduate "3+1/1" programs were developed by integrating industry, education, theory, and practice. Moreover, an "order-based" talent innovation training model for master and doctoral levels in government-school-enterprise cooperation was proposed. Finally, the concept of regional emergency talent full industry chain service was proposed by integrating industry-education and science-education efforts to cultivate emergency talent. The results indicated that the core competencies based on the four-tiered talent demand framework were highly associated with the curriculum system. The issues of homogeneity in talent output and competency emphasis were addressed by clarifying the training direction of safety and emergency disciplines from professional focus and application backgrounds. The proposed concept of regional emergency talent full-industrial chain service closely connected educational content with market demands, enhancing students' comprehensive abilities and contributing to the regional closed-loop development of the modern emergency management industry.

In order to solve the problem of bolt breaking and losing anchor due to the influence of strong mining stress in deep mining roadway, and effectively improve the pre-tightening force of the bolt, a stress uniform bolt with high pre-tightening force was designed. The theoretical analysis, static load drawing and drop hammer impact test, numerical calculation and DIC method were used to study the load-displacement distribution characteristics of the bolt in the process of static load drawing, and the stress concentration position of the bolt was obtained. The mechanical response characteristics of the bolt under dynamic load were studied by using Ansys numerical simulation of drop hammer impact test and SHPB impact test. The results show that the thread deformation of the ordinary bolt nut decreases exponentially along the axial direction away from the extrusion surface, and the strain is concentrated in the first three circles of the thread. The stress uniformly distributed bolt can achieve thread strain coordination, and the mechanical environment is good. The change of bolt axial force is divided into a rising zone, an oscillating zone and a stable zone. When the drop hammer impulse is the same, the stress uniform distribution bolt can reduce the impact force to 64% of the original, and reduce the amplitude frequency of bolt axial force. The stress uniform distribution bolt can reduce the amplitude and frequency of the stress wave waveform. The research results have been applied to deep roadways such as Zhuji mine, Paner mine and Dingji mine. The bolt has no broken anchor phenomenon, and the control effect of the roadway surrounding rock is good.

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.