In order to explore the influence of environmental lighting on visual fatigue during safety sign identification, 12 mixed lighting environments were designed with illuminance and color temperature as environmental variables. Eye movement data were tested under different conditions by eye-tracking technology and a two-factor ANOVA was conducted.Combined with the test results of reaction speed and comfort, the changes of visual fatigue under different lighting conditions were analyzed.The experimental results show that the change of illumination has a significant effect on visual fatigue, subjects are more prone to visual fatigue in low illumination environment; The change of color temperature has little effect on visual fatigue, but in different mixed lighting environments, the change of color temperature will affect the visual comfort of the subjects, and the fatigue state will change accordingly.The suitable color temperature range for the lighting conditions in the working environment is 2 100~3 500 K, and the illuminance range is 550~900 lx. It is concluded that companies should pay attention to improving the lighting conditions during production, avoid reducing the recognition efficiency of safety signs by workers due to visual fatigue, and ensure the safety and health of workers.

As the operational carrier of civil aviation transportation network, the air route network undertakes the important task of ensuring the safe and efficient operation of aircraft. When important waypoints fail due to thunderstorm disturbances, it is easy to chain reaction to adjacent nodes, ultimately leading to a significant decrease in network performance. Aiming at the problem that existing complex network node importance evaluation models do not effectively consider thunderstorm disturbances, the characteristics of thunderstorm disturbances were incorporated into the waypoint importance evaluation system for thunderstorm weather scenarios. The evaluation indicators were weighted using game theory methods, and the TOPSIS(technique for order preference by similarity to an ideal solution) comprehensive evaluation method was improved based on gravity model theory. A node importance evaluation model based on game theory improved TOPSIS method was established, and the K-medoids algorithm was then used to achieve waypoint clustering and grading. Taking flight operations in the Beijing-Tianjin-Hebei region as an example, the importance of air route network nodes in thunderstorm weather scenarios was evaluated. The results show that within the Beijing-Tianjin-Hebei route network, route points in the southern region are more susceptible to thunderstorm weather and are more densely distributed. The route network contains 9 important route points. When important route points in the route network fail due to thunderstorm impact, it will have a significant negative impact on the performance of the route network. The proposed node importance evaluation model based on game theory-improved TOPSIS method can effectively identify important waypoints in the route network during thunderstorm seasons or areas with high thunderstorm incidence, providing effective basis for optimizing the route network structure and resource allocation in thunderstorm scenarios.

The voltage fluctuations in the high-voltage DC bus of the train traction converter have a significant impact on the output power quality of the traction system. Therefore, it is necessary to improve the response speed of the intermediate stage isolated DC/DC converter to reduce the power coupling between the high-voltage stage and the low-voltage stage. Taking the isolated DC/DC converter as the research object, an unbiased model predictive control and sampling noise suppression strategy was proposed to address its inherent problems of high sensitivity to circuit parameters and susceptibility to sampling noise. Firstly, the operation principle of the dual-bridge series resonant converter and the causes of the steady-state errors were analyzed, and a feedback correction method based on recursive least square algorithm was designed to eliminate the steady-state error. Then, the introduction of noise suppression coefficient reduces the sensitivity of the control variable to the control target through a simple and effective method. Furthermore, the virtual current was utilized in predictive model instead of the actual current sampling value, and it further reduces the system costs. Finally, an experimental platform was built to verify the improvement of the proposed strategy in both steady-state and dynamic performance.

The stability of double-limb high pier cannot be ignored in the process of construction. In order to ensure the safety of construction, finite element models were established for three construction stages: bare high pier, large cantilever, and completed bridge to study the stability of double-limb high pier, based on the Miaoluhe bridge of Zhengzhou-Luoyang Expressway. The buckling modes and stability coefficient of double-limb high pier were obtained, and the nonlinear stability analysis of the most unfavorable construction stage was carried out. Finally, the influencing factors on stability such as the alignment deviation, the hole defects, the pier height and the number of crossbeams were analyzed. The results show that under the three construction stages, the double-limb high pier are longitudinal instability, and the stability coefficient of the most unfavorable conditions are 70.092, 33.513, and 55.034.After considering geometric nonlinearity and geometric and material double nonlinearity, the stability of the large cantilever stage has decreased by 15% and 57%, compared to linear analysis. The alignment deviation and the hole defects occurring in the climbing formwork construction of double-limb high piers have an impact on the stability. Therefore, it is necessary to control alignment deviations and repair holes in time. As the height of the pier increases, stability decreases continuously. When one crossbeam is installed between the two limbs, stability improves by 140%. However, further increasing the number of crossbeams does not significantly improve stability. Therefore setting one crossbeam within the range of 50~70 m pier height is the best.

The growing sophistication of deepfake speech poses significant security threats to ASV(automatic speaker verification) systems. Current anti-spoofing models based on CNNs(convolutional neural networks) are constrained by inadequate global feature extraction and limited generalization capability against unseen spoofing attacks. To address these challenges, a novel network architecture integrating CT-DSCNet(channel-temporal attention mechanisms with depthwise separable convolutions) was proposed. Building upon the RawNet2 framework, the developed model incorporates dual-domain attention modules to enhance discriminative feature representation while suppressing irrelevant acoustic artifacts. Furthermore, depthwise separable convolutional residual blocks were strategically implemented to optimize computational efficiency and real-time processing capabilities. Comprehensive evaluations were conducted across three benchmark datasets: ASVspoof2019 LA, ASVspoof2021 DF, and FMFCC-A. Experimental results demonstrate state-of-the-art performance with EER(equal error rate) of 1.53% on ASVspoof2019 LA, representing a 70.58% relative improvement over baseline systems. Notably, the proposed architecture exhibits superior cross-dataset generalization, achieving a 25.35% lower EER on the FMFCC-A evaluation set compared with conventional approaches. These findings validate the effectiveness of the hybrid attention-convolution design in advancing spoofing detection robustness and domain adaptability.

The flow pattern and its characteristics in the flood discharge stilling basin with step-down floors play dominant roles in effectively dissipating the discharged flooding water energy, guaranteeing the safety of the hydraulic structure and its downstream river bank stability as well as navigable flow conditions. A three-dimensional numerical model for water-air two-phase flows with strong nonlinearity, involving large free surface deformation and complicated solid-wall boundary conditions was established, and was applied to analyze flow characteristics in Xiangjiaba flood discharge stilling Basin with step-down floors. RANS(Reynolds-averaged Navier-Stokes) equations, Realizable k-ε turbulence model and VOF free surface tracking method were used in the developed numerical model. The model was firstly validated through comparisons of the simulated results and measured data for the flow patterns as well as the time-averaged pressure at the dam surface induced by the flood discharge jet. It is then applied to simulate the 3-D flow structure and fluctuation characteristics in the stilling basin with step-down floors induced by flood discharge from dam under the same discharge amount but different flood discharge scenarios. The results show that, for the flood discharge stilling basin with high and low step-down floors,under the same flood discharge condition, different scenarios of dam discharge gate open mode significantly affects the three-dimensional structure and characteristics of discharged flow in the dissipative pool induced by flood jets. The combined discharge from dam surface and middle holes results in the strong turbulent mixing of submerged multi-layer and multi-jet flows, effectively dissipating the energy of the discharged water and reducing the water surface fluctuations. The established numerical model can better reproduce the high-speed flooding jets and its turbulent motion in the dissipative pool associated with flood water discharge.

Low level wind shear is an important factor affecting aircraft flight safety. Based on the observations from a three-dimensional scanning wind lidar at Baiyun Airport, Guangzhou during March 2023, the measurements from the wind lidar were preprocessed firstly. Then, TSSI (two-step identification method for wind shear) was proposed, which combined TDSI (two-dimensional synthetic wind shear identification) method with an adaptive window and the temporal wind shear identification method. The wind shear results recognized by the TSSI and TDSI methods were compared, and the evolutions of wind shear were analyzed. The main conclusions are as follows. Data preprocessing effectively removes isolated points and radial fluctuations observed by wind lidar, and fills in the missing data. The TSSI method is conducive to early warning of wind shear. During the observation period at Baiyun Airport, Guangzhou in March 2023, a total of 25 wind shear processes are identified by the TSSI. Among them, 21 cases are warned ahead of the TDSI, with an average warning time of 3~5 minutes, and TSSI also has a good alarm recognition function for both time and space dimension wind shear. Most of the identified wind shear processes occur around noon (e.g. 11:00-15:00) and last for about 15 minutes. The wind shear position is greatly influenced by the background wind field. The TSSI method proposed in this study can identify low-level wind shear earlier and more comprehensively, which is helpful to improve the accuracy of wind shear warning and provide guarantees for aircraft flight safety.

Pipeline leakage is a major cause of urban road collapse accidents. Understanding the evolution process and catastrophic mechanisms of road subsidence is crucial for preventing such safety incidents. Focusing on sewage pipelines in Beijing municipal roads, this study employs DEM-CFD(discrete element method-computational fluid dynamics) coupled flow-solid approach. Microscopic model parameters were calibrated based on laboratory experiments to simulate deformation and cavity evolution in sandy soil layers under various pipeline leakage locations and burial depths. Key parameters, including particle displacement, soil compactness, and medium flow, were analyzed during cavity formation. The results indicate that leakage at the top and middle of the pipeline leads to the formation of a funnel-shaped cavity as water and soil are lost. Without traffic load, the road surface exhibits negligible settlement. By analyzing particle displacement and compactness variations, the soil deformation was divided into stable, loose, and cavity zones, and an elliptical partition model was established for the loose zone. Based on the particle loss rate, the progressive failure process of the soil was classified into three stages: particle migration, rapid loss, and gradual convergence. In terms of cavity formation time, subsidence extent, particle loss rate, and total particle loss, leakage at the pipeline’s middle section yielded the highest values, followed by the top section, with the lowest at the bottom section. However, bottom leakage resulted in the largest loose zone. These findings provide theoretical support for detecting and identifying underground risks associated with urban road collapse disasters.

Bolts are the key to the stable connection of high-altitude equipment, but they are prone to abnormalities such as loosening under the influence of various factors, threatening the safety of the equipment. Currently, bolt detection methods based on deep learning are faced with the problems of class imbalance and label missing. Existing deep-learning-based bolt detection methods suffer from class imbalance and missing labels. A HDWL(historical dynamic weighted loss) model based on semi-supervised pseudo-label learning was proposed. By dynamic weighted orthogonality and class-adaptive fair punishment, the model classification was evaluated with historical data. Adaptive punishment was introduced to prevent overfitting and focus more on hard-to-classify samples, boosting model performance. Experiments showed that the HDWL model achieved significantly higher accuracy than other methods, with advantages in minority-class training and feature focus.

Microwave assisted cutter breaking has a strong application prospect, in order to deeply analyse the auxiliary effect of microwave irradiation on cutter breaking, the TBM scale cutter breaking test after microwave irradiation was carried out. Firstly, the rock was irradiated by microwave using different parameters, and the influence law of different microwave parameters on the surface temperature of the rock was studied. After the rock is back to room temperature, the damaged rock was taken as the basis to carry out the TBM scale cutter rotary rock breaking experiment, to study the influence of microwave irradiation time and power on the cutter thrust, cutter torque, rock ballast weight, cutter wear and the specific energy of rock breaking. The results show that: with the increase of microwave irradiation time and irradiation power, the rock surface temperature increases, the rock heating rate increases, the highest temperature of the rock surface is 172.6 ℃. The cutter thrust is fluctuating in the breaking rock, the rock below the cutter is crushed to powder, the cutter side produces block ballast. With the increase of microwave irradiation time and microwave power, the cutter thrust decreases, the disc torque decreases, the weight of the rock ballast increases, the amount of cutter abrasion decreases, and the specific energy of rock breaking decreases. The best microwave irradiation time should be more than 40 s and the microwave power should be more than 7 kW for the test of Chifeng basalt, which provides a certain experimental basis for the microwave-assisted cutter rock-breaking.