The operational efficiency of aircraft and maximization of aviation transportation benefits have consistantly been pursued by CAAC. It has been indicated by research that the Established on RNP AR (EoR) approach plays an irreplaceable role in improving efficiency, especially for short-distance parallel runway operations, thus, it has received widespread attention in the industry. The integration of EoR approach with sorting strategies was undertaken, with the aim of minimizing flight delay time serving as the objective function, leading to the establishment of a sorting model based on EoR. The impact of EoR-based independent operation versus correlated operation on flight delay time had been compared and analyzed. Addressing the large solution space and the time-sensitive nature of large-scale flight sequencing calculations, The S-shaped function based adaptive particle swarm optimization (SA-PSO) algorithm was proposed to solve the model. Taking the Kunming Changshui International Airport terminal area as an example for case verification, the RECAT-CN operational standard was adopted for wake turbulence safety separation. The results show that, compared to correlated operations, independent EoR operations result in an approximately 38% reduction in total delays. Additionally, the algorithm proposed in the study, when operated independently under the EoR mode results in a reduction of total delays by approximately 15.3%, compared to the first come first served (FCFS) algorithm.

To investigate the contents and pollution of heavy metals in calcium-containing biological minerals, 16 samples were collected from three primary categories: eggshells, shells, and animal bones. Inductively coupled plasma optical emission spectrometry (ICP-OES) was utilized to analyze the contents of seven metalloids and heavy metals (As, Cd, Pb, Cr, Cu, Zn, and Mn). The pollution degree and risk of heavy metals were evaluated using single-factor, Nemerow comprehensive pollution index method, Hakanson potential ecological risk index method, and health risk comprehensive assessment. The results show that As and Cd are not detected in all calcium-containing biological minerals, meanwhile Pb is not detected in both eggshells and shells. Five heavy metals (Pb, Cr, Cu, Zn, and Mn) are detected in the remaining samples, with their contents remaining below standard. Differences in heavy metal contents are observed among different categories and species. Cu, Mn, and Zn have the highest contents of 14.85, 21.47, and 201.99 mg/kg, respectively accumulated in eggshells, shells, and animal bones. The risk assessment results show that the single-factor pollution index of four heavy metals (Pb, Cr, Cu, Zn) in calcium-containing biological minerals is less than 1.0 and the comprehensive pollution index is less than 0.7. All samples are indicated as unpolluted. The potential ecological risk among three types of calcium-containing biological minerals is in descending order: animal bones > eggshells > shells. The non-carcinogenic total risk index of two exposure pathways for minors and adults is less than the safety threshold of 1.0. This finding indicates that five heavy metals in calcium-containing biological minerals are unlikely to threaten human health. Overall, calcium-containing biological minerals can be used as potential sources of fertilizers and soil conditioners in agricultural production. However, their usage should be controlled to prevent heavy metal accumulation and pollution.

In order to improve the fire extinguishing efficiency of forest fires and reduce the damage to forest resources and ecological environment, a three-phase class A foam extinguishing agent consisting of class A foam extinguishing agent with nano-SiO₂ particles was prepared. The effects of nano-SiO₂ mass fraction on foam stability and fire extinguishing efficacy were investigated by using the double injector method and the wood stack fire extinguishing test platform. The results show that the nano-SiO₂ significantly enhanced the foam stability and delaye the foam precipitation and foam coarsening; the three-phase class A foam extinguishing agent extinguishe the flame more quickly and efficiently under the same driving pressure without rekindling and at a lower dosage than the traditional class A foam extinguishing agent; and the three-phase class A foam extinguishing agent with 1.5% SiO₂ show the best extinguishing efficacy. The three-phase A-type foam extinguishing agent significantly improves the fire extinguishing efficiency, reduces the consumption of extinguishing agent, and has low cost, which makes it suitable for large-scale forest fires. The study provides a new solution for the efficient extinguishing of forest fires and has a wide range of practical applications.

Hydrogen energy is a promising secondary low-carbon energy source in the 21st century of global energy transition. However, HE hydrogen embrittlement in metallic materials refers to the diffusion of hydrogen into the metal in different forms, either in solid solution or as hydrides, causing severe lattice distortion, reducing ductility and toughness, and leading to embrittlement and fracture. It has raised a number of safety issues and limited the service life of hydrogen storage systems due to its insidious nature, abruptness, and diverse failures. In recent years, scholars have been conducting extensive research on hydrogen embrittlement, benefiting from improved experimental tests and numerical simulation methods. A comprehensive review of the latest advancements in hydrogen embrittlement research was provided: elucidating the concept of hydrogen embrittlement and the prevailing mechanism, analyzing the characteristics and factors influencing hydrogen embrittlement in storage vessels, and summarizing the characteristics and primary application scopes of the existing macro to micro, static and dynamic experimental methods in the evaluation of material hydrogen embrittlement. Special attention is given to the research progress in combining these methods with numerical simulation analyses, including their applicability and limitations in practical engineering. Insights and references might be offered to the ongoing development of evaluation methodologies for the hydrogen embrittlement resistance of metal materials.

In recent years, rapid development has been continuously observed in China’s manufacturing industry, where AGVs automated guided vehicles have been increasingly adopted by enterprises as core equipment in intelligent logistics systems. To ensure the efficiency of warehouse operations, addressing the issue of transportation path conflicts among AGVs has garnered growing attention from researchers. A literature review on the issue of multi-AGV path conflicts in warehouses was conducted from two perspectives. First, from the perspective of conflict types, the research problems were categorized into collision problems and deadlock problems, and the current state of research on multi-AGV collision avoidance strategies under different conflict types was analyzed. Second, from the perspective of model-solving algorithms, the study divides the approaches into heuristic algorithms and reinforcement learning algorithms, analyzing their application in multi-AGV path conflict issues in warehouses in recent years. Finally, the existing literature was summarized, and future directions for addressing multi-AGV path conflicts in warehouses were proposed.

CLT(cross-laminated timber) shear wall structure has emerged as one of the rapidly advancing mid-to-high-rise timber structural systems in recent years. Extensive research on the lateral resistance performance of CLT shear walls has been conducted by both domestic and international scholars. A comprehensive synthesis of findings concerning lateral resistance capabilities was conducted for CLT shear walls, including single-panel, multi-panel, and CLT shear walls with openings. Failure modes, load-bearing capacities, and stiffness characteristics were systematically examined across these structural variations. Comparative evaluations of multiple calculation methods for lateral bearing capacity and stiffness determination were performed, alongside a compilation of standardized methodologies from domestic and international specifications for timber shear wall analysis. Specialized recommendations were formulated specifically for CLT structural applications. Current research advancements were consolidated, and strategic directions were proposed to guide subsequent investigations into CLT shear wall performance under lateral loading conditions, establishing critical references for ongoing research development in this specialized engineering field.

Buildings are important carriers of human production activities. Accurate and fast extraction of building areas can play an important role in the field of natural resource management. Although significant progress has been made in building extraction from remote sensing images based on CNN(convolutional neural network), the constructed network model still needs to be optimized in feature extraction and feature fusion. Therefore, a coordinate attention and CCFNet(convolutional enhanced full-scale fusion building extraction network) was proposed. The constructed model consists of a residual encoder enhanced by coordinate attention and convolution and a full-scale fusion decoder. Coordinate attention was used in the encoder to build inter-channel dependencies and capture global information. The asymmetric convolution was used to enhance the edge feature extraction of ground objects, and it is more robust to rotation, flip distortion and uneven aspect ratio of ground objects. The full-scale fusion method used in the decoder helps to reconstruct the buildings. The experimental results on the dataset of typical Chinese city buildings show that compared with other building extraction networks, The CCFNet model constructed in this paper achieves the best experimental Accuracy of 93.84%, 84.08%, 72.53% and 82.59% in the four segmentation evaluation indicators of accuracy, F₁, IOU and MIOU, respectively. Experimental results show that the model can effectively extract building regions.

Accurately and in real-time understanding the changes in the scope and species communities of intertidal wetlands is an important foundation for achieving sustainable development and management of wetland intertidal zones. In recent years, global warming, rising sea levels, and human activities such as coastal development, reclamation, and aquaculture have caused serious damage to the intertidal zone. At present, there is a lack of systematic research on the classification of mangrove tidal flats in the intertidal zone of Guangxi. In order to achieve large-scale and high-precision extraction of intertidal resources in Guangxi, this article was based on GEE (Google Earth Engine) platform, using Landsat series image data of Guangxi coastal zone from 2012 to 2022, and threshold segmentation processing of the images. The various remote sensing features under the influence of tidal dynamic inundation were analyzed, and the intertidal zone range of coastal wetlands in Guangxi was extracted. Achieved the classification of tidal flats and water bodies, mangrove vegetation, and non-mangrove vegetation in the study area, with areas of 5 641.67 hm², 1 625.29 hm², and 2 156.04 hm² respectively. The overall classification accuracy reached 93.3%, with a Kappa coefficient of 0.9.

Further analysis is needed to comprehend how the trend of land subsidence in the Beijing plain area evolves following the implementation of a series of prevention and control measures. Based on the Sentinel-1A image data from 2017 to 2022, the PS-InSAR technique was employed to assess the current situation of land subsidence in the plain area of Beijing, and the geographical detector was utilized to analyze the main influencing factors of land subsidence and their interaction effects. The findings reveal the following: The main conclusions were as follows. The distribution of land subsidence in Beijing plain is uneven, and the maximum subsidence rate reaches 90 mm/a. The subsidence rate of non-funnel area shows a certain degree of slowing trend from 2020 to 2021, while the slowing trend of subsidence rate in funnel area is not obvious. Groundwater as the primary influencing factor of land subsidence, with the thickness of the compressible layer closely following. The interaction among all influencing factors demonstrates a factor enhancement relationship, with the interaction between groundwater and subway infrastructure exerting the most significant impact on land subsidence. This highlights that groundwater and urban construction jointly propel land subsidence in the Beijing plain area. These research findings provide a scientific foundation for the comprehensive assessment, precise prediction, and integrated prevention and control of land subsidence in the Beijing plain.

In order to reveal the spatiotemporal distribution characteristics and causative factors of the ground subsidence in Jiangdong New District, SBAS-InSAR(small baseline subsets interferometric synthetic aperture radar) technology was adopted to process and analyze 175 scenes of Sentinel-1A imagery data from January 2018 to February 2024, extracting the deformation parameters. The study found that the subsidence rate in Jiangdong New District has undergone a variation from very slow to fast and then back to slow, forming several severe subsidence areas mainly distributed along major traffic arteries and reclamation areas. The main causative factors of the subsidence were qualitatively and quantitatively analyzed, which include poor engineering geological conditions, consolidation in the reclamation areas, and land use change, etc. The acceleration of subsidence rate is closely related to the rapid development and construction of the region, among which the excessive load on the ground surface is becoming the main influencing factor of subsidence.