To optimize the pathways for cross-regional collaboration in natural disaster management, focused on Yangtze River delta—a pioneering region in cross-provincial collaborative practices—and employed social network analysis and QAP analysis to construct a cross-regional emergency collaboration network for natural disaster response in the area. The study examined both the overall and nodal characteristics of the network to assess the current state of cross-regional emergency collaboration and identify the driving factors behind such cooperation. The results indicate that with the establishment and development of Yangtze River delta emergency management task force, intercity collaboration barriers have gradually diminished, and the emergency collaboration network has become increasingly dense, reflecting more frequent interregional cooperative governance. Provincial governments, represented by the three provinces and one municipality (Jiangsu, Zhejiang, Anhui and Shanghai), serve as the dominant actors in the collaborative network, while municipal governments such as Xuancheng, Jiaxing, and Suzhou act as proactive facilitators. Key factors driving the formation of this cross-regional collaborative governance mechanism include geographical proximity, industrial structure, transportation infrastructure, interprovincial administrative relationships, and historical cooperative ties.

In order to address the significant safety risks posed by frequent extreme weather to the source, grid, and load-side equipment of the new power system, a risk assessment model for urban new power systems under extreme weather conditions was proposed. First, risk factors of the urban new power system were identified based on disaster theory, and an ISM was applied to clarify the interrelationships among these risk factors. Subsequently, the topological structure of the disaster chain was mapped into a BN. The prior probabilities of each risk factor node were determined using fuzzy comprehensive evaluation and accident statistics. Sensitivity analysis and scenario analysis were employed to derive key risk nodes for urban new power system accidents and the consequences of multi-hazard coupled accidents. Finally, MC simulation was utilized to conduct operational optimization analysis on "transmission towers" from the perspective of wind resistance level design. The results indicate that the constructed BN-MC coupled model effectively quantifies and enhances the analysis of extreme weather risks in urban new power systems. Under multiple superimposed extreme weather conditions, the failure probability of photovoltaic generators reaches as high as 60%, with strong winds being the key driving factor. Furthermore, improving the wind resistance level of transmission towers significantly reduces their failure probability. At a real-time wind speed of 36 km/h, increasing the wind resistance level from 35 km/h to 40 km/h reduces the failure probability by 59.39%. This effect exhibits a nonlinear characteristic, with a greater reduction in risk probability in the low wind speed range than in the medium wind speed range.

Traditional manual methods for detecting wall hollowing suffered from strong subjectivity, low efficiency, and difficulties in large-scale application. To address these issues, this study proposed an intelligent detection method based on a fully automatic hollowing signal acquisition device and an optimized signal processing algorithm. Firstly, a fully automatic hollowing signal acquisition device capable of stable operation on building walls was designed to achieve standardized tapping and high-precision acoustic signal acquisition. Secondly, VMD and EEMD optimized by Bayesian Optimization (BO) were employed to denoise the original signals, thereby enhancing the features of hollowing signals. Then, MSC and MFCC features of the signals were extracted and fused at the frame level to form an MFCC+MSC feature set. Finally, a majority voting ensemble learning model was utilized for classification, enabling high-precision hollowing detection. The results indicate that the classification accuracy of the proposed method reaches 99.31%, significantly outperforming traditional methods. These results validate the feasibility and effectiveness of combining automated devices with optimized signal processing techniques for wall hollowing detection.

In order to address the limitations of traditional earthquake rescue training disaster site, including low simulation fidelity, poor safety, high costs and inadequate quantitative monitoring, this study developed a standardized, full-process earthquake emergency rescue training system using VR technology based on the Unity 3D engine, creating a virtual training scenario for earthquake disaster scenes. While systematically improving rescuers' tactical skills and practical abilities, the system enables quantitative measurement of training effectiveness. On one hand, this paper describes the model building, scene design, functional modules, and interactive design process of the earthquake emergency rescue training system. On the other hand, through pre-test and post-test control experiments, participants' performance is evaluated in terms of theoretical knowledge of earthquake disaster rescue, operational skills, and rescue strategies. The results show that subjects receiving training through this system significantly outperformed the traditional training group in both immediate knowledge acquisition and two-week knowledge transfer efficiency (P < 0.05^*, Cohen's d = 1.0), particularly in skill and strategy learning outcomes (P < 0.05^*, d = 1.23). Meanwhile, subjective experience evaluations confirmed high satisfaction ratings from subjects, corroborating the system's practical efficiency in knowledge transfer performance (P < 0.01^**, 1.1 ≤ d ≤ 3.9).

In order to reduce the dynamic loads on risers under harsh sea conditions and enhance their adaptability to complex marine environments, a multifunctional suspension system for deepwater riser was proposed, which included a suspension system, a hydraulic compensation system, and a measurement and control system, in order to ensure the safety of the suspended riser under severe sea conditions such as typhoons in the South China Sea. In addition, the system can also be applied to transit with a suspended riser between wells, which can significantly reduce the load of the suspension riser. The suspension system suspends a single bearing riser system, and relieves the stress concentration on the top of the riser by means of a centralizer and a hinge joint; the hydraulic compensation system adopts three working modes of differential throttling compensation, passive non-throttling compensation and throttling shielding to meet the requirements of platform avoidance and inter-well transit. The measurement and control system monitors and warns in real time, regulates and controls the telescopic movement of the hollow hydraulic cylinder, and realizes the real-time compensation of the dynamic load of the riser system. The system has undergone sea trial applications, the results show that the proposed multi-function suspension system can significantly reduce the riser top stress and dynamic load amplitude, especially in the differential throttle compensation and passive non-throttle compensation modes. At the same time, the downstream and upstream speeds of the platform are increased to 1.0 knots, which significantly improves the operation efficiency. The system helps to overcome the challenge of traditional suspension mode, provides a safe and efficient solution for deepwater drilling riser operations, and reduces the disaster risk of suspension riser under extreme sea conditions such as typhoons.

To reveal the co-evolutionary relationship between disease transmission intensity and emotional diffusion rate, based on a two-layer complex network structure, this study integrated the classical Susceptible-Exposed-Infected-Recovered (SEIR) epidemic model with a five-state emotional dynamics framework (S_e-E_e-I_e-G_e-R_e) to construct a coupled dynamics model (SEIR-S_eE_eI_eG_eR_e). Theoretical derivation and simulation validation were conducted using the microscopic Markov chain approach and Monte Carlo simulation. The findings reveal that although reducing the disease infection probability can mitigate the scale of emotional propagation, its inhibitory effect on the peak of emotional propagation remains limited. In contrast, shortening the disease incubation period and improving the recovery rate significantly regulate the spread of negative emotions, exhibiting a two-stage propagation pattern characterized by emotional metabolic hysteresis and the density threshold effect of emotional guides. Furthermore, enhancing individuals' compliance with epidemic preventive measures can effectively delay the spread and reduce the scale of negative emotions through three pathways: blocking transmission chains, reinforcing social norms, and correcting cognitive biases.

In order to explore the emotional expression characteristics of different types of groups under emergencies, and to deeply analyze the influence of gender, temperament type and accident environment on the stress state emotions of the groups, a stress state emotional stimulation test based on facial expression technology was designed. A cohort of 137 participants was exposed to five categories of accident videos. Facial expression data for six basic emotions were collected using FaceReader software, with the Kruskal-Wallis test employed to analyze differences across gender, temperament types, and accident scenarios. A k-means clustering model was further constructed based on arousal dynamic features. The results show that female participants exhibit significantly higher intensities of sadness and fear, whereas males show stronger anger responses. Sanguine individuals demonstrate the most pronounced emotional reactivity, while phlegmatic types achieve the fastest arousal modulation. Fear responses are most pronounced in building fire scenarios. Males outperform females in arousal self-regulation capacity.

To address the issue of spontaneous coal combustion caused by air leakage from fissures, grouting is commonly employed to seal fissures. PSES is a new type of air-leakage plugging material, whose durability and reliability of sealing performance depend directly on its intrinsic failure process. Uniaxial compression experiments, in conjunction with a single-hole model, the semi-empirical M-T model, and the CDP model, were employed to investigate the mechanical behavior of PSES across micro-, meso-, and macro-scales. The results reveal that at the microscale, the inner wall of the vesicle constitutes a primary weak point within the PSES structure, and the critical external pressure signifies the onset of localized yielding; at the mesoscale, the semi-empirical M-T model accurately predicts the equivalent effective modulus and confirms its capability to characterize the relationship between porosity and stiffness; at the macroscale, the porosity-corrected CDP model accurately fits the stress-strain curve, with the Mean Absolute Percentage Error (MAPE) ranging from 0.23% to 2.69%. Furthermore, the corrected damage factor closely corresponds with the material's actual condition, effectively characterizing its damage evolution characteristics. This, in turn, provides a reliable basis for evaluating the long-term service performance of the air-leakage plugging material.

In order to explore the influence of laying foam slurry insulation layer on the temperature field of surrounding rock in high temperature mines, the heat transfer differential equation of unsteady surrounding rock and the two-dimensional unsteady heat transfer differential equation of foam slurry insulation layer were established by using Fourier 's law. The finite difference method was used to solve the differential equations, so as to explore the temperature change of surrounding rock after laying the foam slurry insulation layer and the influence of initial temperature on foam slurry insulation layer. The results show that the temperature tends to be stable with time due to the small thermal conductivity of the foam slurry insulation layer. The temperature difference between the rock strata adjacent to the foam slurry insulation layer is large, and the larger the thickness of the foam slurry insulation layer, the higher the temperature of the rock mass. It can be seen that the laying of the foam slurry insulation layer hinders the transfer of a certain amount of heat to the roadway so that the temperature gradient of the rock mass increases. When the initial temperature of the foam slurry insulation layer is closer to the air flow temperature, the temperature gradient inside the foam slurry is smaller and the temperature can reach a steady state in a short time.

To address the problems of information distortion, transmission interruption, and response failure in emergency information systems during urban extreme rainstorm disasters, the study first identified five categories of risk—information source, information acquisition, information storage, information processing, and information transmission—from the perspective of the information processing lifecycle. Taking "7·20" Zhengzhou rainstorm event as a case, the risk factors of emergency information were systematically revealed. Subsequently, the connotation of emergency information resilience was defined, and a resilience structure was constructed. Finally, a "risk-resilience" coupling theoretical framework of emergency information resilience for urban extreme rainstorm disasters was established. The Results show that emergency information resilience is formed by the coupled effect of institutional resilience, social resilience, organizational resilience, and physical resilience. The theoretical framework of emergency information resilience consists of four stages. Including scientific construction of information resilience, integration of information risk early warning and response, cutting off the path of information risk diffusion, and enhancing the adaptability of information systems. The theoretical framework of the role of urban mega-rainstorm disaster emergency information resilience constructed in the text significantly improves the absorption capacity, recovery capacity and adaptability of information systems in response to complex disaster impacts.