The catenary system, which is regarded as a critical component of the high-speed rail traction power supply system, is deemed essential for the normal operation of high-speed trains. It has been demonstrated by previous earthquake disasters that the catenary system is susceptible to varying degrees of damage under seismic effects. The seismic research progress of the catenary system was systematically reviewed from four aspects: the dynamics modeling and inherent dynamic characteristics of the catenary system, the seismic damage characteristics and common types of failures, the seismic response of the catenary system and its influencing factors, and an overview of the current state of earthquake resistance research, which includes a comparative analysis of the seismic design standards and regulations for catenary systems in different countries and regions. By summarizing the relevant research, prospects for future research directions are provided.

FDS(flocculation-dehydration-solidification) coupling process has been proven to significantly enhance the efficiency of resource conversion in engineering waste soil. However, the material fate within the process and the advantages of recycling press-filter filtrate remain to be further investigated. FDS experiments were conducted to analyze the material fate of each component in the flocculant-solidifying agent during the FDS process. Based on the findings, the potential benefits of recycling press-filter filtrate were explored. The results reveal that approximately 18% to 35.57% of Na⁺ and 0.1% to 0.56% of Si elements are detected in the press-filter filtrate, whereas Ca, Mg, and Al elements primarily remained in the filter cake, with proportions close to or equal to 100%. The recycling of highly alkaline press-filter filtrate into the process is found to not only improve the dissociation efficiency of mud and sand but also serve as a “pretreatment” for subsequent FDS stages. Waste soil particles are observed to adsorb residual materials from the filtrate, enabling dynamic adjustments in material dosage according to material transformation patterns and filter cake performance requirements. This approach ensures that materials lost in the filtrate are continuously recycled and utilized, maintaining a dynamic circular process.

Multi-object tracking is an important branch in the field of computer vision. Owing to the rapid development of computer hardware and deep learning technology, significant progress has been made in deep learning-based multi-object tracking, yielding remarkable results. To promote the research progress in the field of visual multi-object tracking, a comprehensive review of recent innovative outcomes was conducted to discuss the current state of research advancements.On the basis of introducing the background and application scenarios of multi-object tracking, the research progress was discussed in four aspects: tracking by detection,joint detecting and tracking,transformer-based tracking,referring multi-object tracking. Common benchmark datasets and evaluation metrics for multi-tracking algorithms were summarized, and a comparative analysis of the algorithms mentioned was conducted on these datasets. Ultimately, exploring the prospective evolution of deep learning-based visual multi-object tracking, three future research directions were proposed for scholars actively engaged in this field.

Recently, SSVEP(steady-state visual evoked potential-based BCI(brain-computer interface) researches have achieved significant development. However, the practical application of BCIs are still limited by several factors, one of which is the visual stimulus source. Most SSVEP-BCI systems rely on monitors, which are not portable and thus restrict the practical use in daily life. VR glasses, as wearable and portable devices, can provide realistic and immersive stimulus sources, which do not rely on monitors. Thus, they offer significant potentials for BCI applications. The VR(virtual reality) technology was introduced to display VR-SSVEP visual stimuli in 3D environment and enables subjects to immersively engage in BCI. The performance of 3D and 2D visual stimuli based on VR-SSVEP were compared in this study. The experimental results demonstrate that the performance of 3D visual stimuli is better than that of 2D visual stimuli. The average classification accuracy of 3D stimuli reaches 90.10%, which is 7.08% higher than 2D stimuli. Additionally, a 2-second stimulation duration achieves an optimal information transfer rate. This study confirms that 3D visual stimuli can effectively enhance SSVEP recognition performance, which indicates a practical use of the system and provides a novel approach for applying VR devices to the SSVEP paradigm.

Aiming at the thermoacoustic oscillation in the combustion process of a new generation of gas turbine, several time-domain analysis methods of high frequency data signals were retested and compared by constructing a complex network model. The results show that the two complex network models, node strength and network diameter, can give an earlier warning of thermoacoustic oscillations than the traditional time-domain analysis methods(root mean square and time kurtosis). Coupling prediction effect and data processing time, the node strength is preferred to construct the complex network model. Finally, the method was applied to the experimental data analysis of multi-nozzle micro-mixing burners, and it was found that the characteristic turning point of the method is about 2.3 s ahead of limit cycle analysis and the characteristic point of statistical analysis.

The super-large cross-section tunnel is prone to large deformation when passing through soft rock stratum. The reasonable selection of excavation method is of great significance for construction safety. In order to explore the applicability of the double-side nine-step excavation method to the construction of super-large cross-section tunnels, based on a 500 m² super-large cross-section soft rock tunnel under construction in Chongqing, the mechanical properties of sandy mudstone were revealed by laboratory experiments. The deformation characteristics of surface and super-large cross-section tunnel structures were compared and analyzed by numerical simulation and field monitoring. The excavation sequence, temporary support measures and excavation step length were optimized. The results show that the stress-strain curves of sandy mudstone samples under different confining pressures and different unloading rates are similar, and the triaxial compressive strength and deformation characteristics of rock samples change significantly. With the excavation of the core rock mass of the upper step, the displacement of the super-large section tunnel is abruptly changed. When the temporary support measures are removed, the deformation of the super-large section tunnel is further aggravated. Different excavation steps cause successive disturbance of surrounding rock, resulting in different unloading rates of surrounding rock and affecting the deformation of surface and tunnel structure. The temporary transverse bracing effectively limits the convergence of the arch waist, and the convergence of the arch waist is reduced by about 10.0 mm under all the layout conditions. In addition, the shorter the length of the excavation step, the smaller the deformation of the surface and the super large section tunnel.

The rudder in the coaxial twin-rotor is a complex mechatronic position-following control system, and its control accuracy plays a key role in manipulating the flight attitude. Because the common rudder is lacking in adapting to the unique flight environment of the aircraft, the accuracy of tracking declination and the stability performance need to improve. The manipulation principle and structure of micro UAV were analyzed, the mathematical models of position loop, current loop double PID steering gear control system and transition position loop Fuzzy PID steering gear control system were established respectively. Combined with the actual flight conditions, the dynamic and static characteristics of the coaxial twin-rotor steering gear control system were analyzed by using Fuzzy editor and Simulink module. The results show that the rudder control system with current loop PID and position loop Fuzzy PID control has 28.6% less overshoot, 28% less adjustment time and faster response than the dual PID control system. Meanwhile, the Fuzzy PID parameters are adjusted in real time to track the changes, which can adapt to the complex and variable flight conditions of the coaxial twin-rotor more quickly. The obtained control system based on dual-loop Fuzzy PID shows high accuracy and meets the requirements of stable, accurate and robust working under complex working conditions, which is of great significance for the control system design of coaxial dual-rotor aircraft.

In order to enhance the safety and efficiency of operations in the double-channel U-shaped apron area of large airports, an optimized operational procedure for the double-channel U-shaped area was studied. Firstly, the utilization and partitioning of taxiways in the double-channel U-shaped apron area were designed, and the positions of pushback holding points were optimized. Secondly, based on the partitioning of the double-channel U-shaped apron area and the optimized positions of pushback holding points, different operational procedures for aircraft were designed for various scenarios. Then, evaluation indicators were designed from the perspectives of safety and efficiency, and corresponding evaluation models were established. Finally, simulation experiments were conducted using Wuhan Tianhe Airport as the object. The results show that the proposed optimized operational procedure can reduce the total operation time by 13.3%, total waiting time by 31.4%, and waiting rate by 22.4%. The flight density was gradually increased until reaching the maximum theoretical capacity of the U-shaped apron area, and further verification was conducted. The results indicate that the proposed optimized operational procedure performs better across different indicators under varying flight volumes, verifying its effectiveness and providing theoretical references for current and future operational procedures of double-channel U-shaped apron areas.

In dense scenes, the frequent occurrence of occluded or small-scale pedestrian objects poses significant challenges to traditional object detection models, frequently leading to a high number of missed detections and false positives. In order to solve the problem of high false negative rate and false positive rate in pedestrian detection in such dense scenes, a novel dense scene pedestrian detection framework called ST-YOLO was proposed. Firstly, the low-level small object detection layer in YOLOv5's backbone network was integrated into the feature pyramid network and path aggregation network structure, adding a pedestrian detection layer for detecting small objects. Secondly, the neck network of YOLOv5 was improved by utilizing multi-scale global information based on Swin Transformer and local information extracted by convolutional neural networks (CNN) to construct aggregated features and enhance the network's feature extraction capability. And the SIoU (scalable IoU) loss function was introduced in the prediction process to accelerate the convergence speed of the model and improve detection capability. Finally, Soft NMS (soft non maximum suppression) was used instead of the original non maximum suppression (NMS) algorithm to reduce the problem of mistakenly deleting detection boxes during the non maximum suppression stage and lower the false alarm rate of the detection algorithm. A large number of experiments on the Wide Person dataset have shown that the improved ST-YOLO algorithm has improved accuracy and mAP_0.5 by 5.7% and 3.6% respectively compared to the current mainstream YOLOv9 algorithm.

As large-scale fracturing in the development of deep shale gas results in rapid production decline, the accurate understanding of gas-liquid flow patterns is considered essential for stabilizing gas well production. Gas well models with two different wellbore trajectory structures were established, and OLGA software was applied to conduct transient calculations on models with varying tubing depths. The results indicate that in deep shale gas well A₁, slug flow only occurs in the build-up section and above, while in well B₁, slug flow appears in the horizontal section and near the build-up section. Considering cumulative gas production and liquid loading, the optimal tubing depth for deep shale gas wells A₁ and B₁ is at the heel of the horizontal section, while for conventional shale gas wells A and B, the optimal tubing depths are at the heel of the horizontal section and one-third of the horizontal section. Deep shale gas wells are more favorable for drainage and production compared to conventional shale gas wells.The optimal tubing setting depths for conventional shale gas wells with two deep formation wellbore configurations are at the horizontal section heel and the one-third point of the lateral, respectively. It is determined that deep shale gas wells are more advantageous for drainage and production compared to conventional shale gas wells. As the tubing size decreases, both the gas production and the corresponding critical gas flow rate for liquid carryover are reduced. It is also found that the greater the light hydrocarbon content in the shale gas composition, the higher the gas production. This study is intended to provide a reference for determining the rational tubing placement in the drainage and gas production processes of deep shale gas wells.