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Due to the irregularity and complexity of ground and non-ground objects, filtering non-ground data from airborne LiDAR point clouds to create Digital Elevation Models (DEMs) remains a longstanding and unresolved challenge. Recent advancements in deep learning have offered effective solutions for understanding three-dimensional semantic scenes. However, existing studies lack the capability to model global semantic relationships and fail to integrate global and local semantic information effectively, which are crucial for the ground filtering of point cloud data, especially for larger objects. This study focuses on ground filtering challenges in large scenes and introduces an elevation offset-attention (E-OA) module, which considers global semantic features and integrates them into existing network frameworks. The performance of this module has been validated on three classic benchmark models (RandLA-Net, point transformer, and PointMeta-L). It was compared with two traditional filtering methods and the advanced CDFormer model. Additionally, the E-OA module was compared with three state-of-the-art attention frameworks. Experiments were conducted on two distinct data sources. The results show that our proposed E-OA module improves the filtering performance of all three benchmark models across both data sources, with a maximum improvement of 6.15%. The performance of models was enhanced with the E-OA module, consistently exceeding that of traditional methods and all competing attention frameworks. The proposed E-OA module can serve as a plug-and-play component, compatible with existing networks featuring local feature extraction capabilities. [ABSTRACT FROM AUTHOR]

The fatigue crack initiation life of unwelded steel components accounts for the majority of the total fatigue life, and the accurate prediction of it is of vital importance. In this study, a numerical model utilizing the extended finite element method (XFEM) and Smith–Watson–Topper (SWT) model is established to predict the fatigue crack initiation life of notched details extensively used in orthotropic steel deck bridges. Using the user subroutine UDMGINI in Abaqus, a new algorithm was proposed to calculate the damage parameter of SWT under high-cycle fatigue loads. The virtual crack-closure technique (VCCT) was introduced to monitor crack propagation. Nineteen tests were performed, and the results were used to validate the proposed algorithm and XFEM model. The simulation results show that the proposed XFEM model with UDMGINI and VCCT can reasonably predict the fatigue lives of the notched specimens within the regime of high-cycle fatigue with a load ratio of 0.1. The error for the prediction of fatigue initiation life ranges from −27.5% to 41.1%, and the prediction of total fatigue life has a good agreement with the experimental results with a scatter factor of around 2. [ABSTRACT FROM AUTHOR]

Magnesium matrix composites are essential lightweight metal matrix composites, following aluminum matrix composites, with outstanding application prospects in automotive, aerospace lightweight and biomedical materials because of their high specific strength, low density and specific stiffness, good casting performance and rich resources. However, the inherent low plasticity and poor fatigue resistance of magnesium hamper its further application to a certain extent. Many researchers have tried many strengthening methods to improve the properties of magnesium alloys, while the relationship between wear resistance and plasticity still needs to be further improved. The nanoparticles added exhibit a good strengthening effect, especially the ceramic nanoparticles. Nanoparticle-reinforced magnesium matrix composites not only exhibit a high impact toughness, but also maintain the high strength and wear resistance of ceramic materials, effectively balancing the restriction between the strength and toughness. Therefore, this work aims to provide a review of the state of the art of research on the matrix, reinforcement, design, properties and potential applications of nano-reinforced phase-reinforced magnesium matrix composites (especially ceramic nanoparticle-reinforced ones). The conventional and potential matrices for the fabrication of magnesium matrix composites are introduced. The classification and influence of ceramic reinforcements are assessed, and the factors influencing interface bonding strength between reinforcements and matrix, regulation and design, performance and application are analyzed. Finally, the scope of future research in this field is discussed. [ABSTRACT FROM AUTHOR]

Low-carbon society is calling for advanced electrochemical energy storage and conversion systems and techniques, in which functional electrode materials are a core factor. As a new member of the material family, two-dimensional amorphous nanomaterials (2D ANMs) are booming gradually and show promising application prospects in electrochemical fields for extended specific surface area, abundant active sites, tunable electron states, and faster ion transport capacity. Specifically, their flexible structures provide significant adjustment room that allows readily and desirable modification. Recent advances have witnessed omnifarious manipulation means on 2D ANMs for enhanced electrochemical performance. Here, this review is devoted to collecting and summarizing the manipulation strategies of 2D ANMs in terms of component interaction and geometric configuration design, expecting to promote the controllable development of such a new class of nanomaterial. Our view covers the 2D ANMs applied in electrochemical fields, including battery, supercapacitor, and electrocatalysis, meanwhile we also clarify the relationship between manipulation manner and beneficial effect on electrochemical properties. Finally, we conclude the review with our personal insights and provide an outlook for more effective manipulation ways on functional and practical 2D ANMs. [ABSTRACT FROM AUTHOR]

A micro vibratory platform driven by converse piezoelectric effects is a promising in-situ recalibration platform to eliminate the influence of bias and scale factor drift caused by long-term storage of micro-electro–mechanical system (MEMS) inertial sensors. The calibration accuracy is critically determined by the stable and repeatable vibration of platform, and it is unavoidably impacted by the residual stress of micro structures and lead zirconate titanate (PZT) hysteresis. The abnormal phenomenon of the observed displacement response in experiments was investigated analytically using the stiffness model of beams and hysteresis model of piezoelectric material. Rather than the hysteresis, the initial deflection formed by the residual stress of the beam was identified as the main cause of the response error around the zero position. This conclusion provides guidelines to improve the performance and control of micro vibratory platforms. [ABSTRACT FROM AUTHOR]

Simple Summary: The red palm weevil is an exotic and highly endangered pest that is extremely harmful to palm plants. In order to effectively control this pest, we propose an algorithm to automatically detect and count adult red palm weevils in traps. Previously, the trapping and counting of adult red palm weevils was done manually. The population density and damage level were then inferred from the number of adults trapped to guide control efforts. However, the efficiency of this method is very low. The algorithm proposed in this paper solves the drawbacks of manual counting, and the recognition accuracy reaches 93.8%, which also improves the efficiency of agricultural monitoring. The red palm weevil (RPW, Rhynchophorus ferrugineus) is an invasive and highly destructive pest that poses a serious threat to palm plants. To improve the efficiency of adult RPWs' management, an enhanced YOLOv5 object detection algorithm based on an attention mechanism is proposed in this paper. Firstly, the detection capabilities for small targets are enhanced by adding a convolutional layer to the backbone network of YOLOv5 and forming a quadruple down-sampling layer by splicing and down-sampling the convolutional layers. Secondly, the Squeeze-and-Excitation (SE) attention mechanism and Convolutional Block Attention Module (CBAM) attention mechanism are inserted directly before the SPPF structure to improve the feature extraction capability of the model for targets. Then, 2600 images of RPWs in different scenes and forms are collected and organized for data support. These images are divided into a training set, validation set and test set following a ratio of 7:2:1. Finally, an experiment is conducted, demonstrating that the enhanced YOLOv5 algorithm achieves an average precision of 90.1% (mAP@0.5) and a precision of 93.8% (P), which is a significant improvement compared with related models. In conclusion, the enhanced model brings a higher detection accuracy and real-time performance to the RPW-controlled pest pre-detection system, which helps us to take timely preventive and control measures to avoid serious pest infestation. It also provides scalability for other pest pre-detection systems; with the corresponding dataset and training, the algorithm can be adapted to the detection tasks of other pests, which in turn brings a wider range of applications in the field of monitoring and control of agricultural pests. [ABSTRACT FROM AUTHOR]

To investigate the fatigue performance of vertical web stiffener to deck plate welded joints in weathering steel box girders, six specimens of the weathering steel (WS) Q345qNH, four specimens of WS Q420qNH, and four specimens of the plain carbon steel (CS) Q345q for comparison were tested by a vibratory fatigue testing machine, considering different steel grades, yield strengths, stiffener plate thicknesses, and weld types. The fatigue strength was evaluated based on S-N curves and the crack propagation was analyzed by linear elastic fracture mechanics (LEFM). The results show that the fatigue crack of the welded joints was initiated from the end weld toe of the deck plate and subsequently propagated both along the thickness of the deck plate and in the direction perpendicular to the stiffener plate. The fatigue crack initiation and propagation life of WS Q345qNH specimens were longer than those of CS Q345q specimens. The fatigue crack propagation life of WS Q345qNH specimens was longer than that of WS Q420qNH specimens, while the initiation life bore little relationship to the yield strength. Increasing the stiffener plate thickness effectively delayed crack initiation and slowed down its propagation. Compared with fillet welds, full penetration welds extended the fatigue crack propagation life, while no significant improvement was implied for the initiation life. The WS and CS specimens could be classified as having the same fatigue strengths by nominal stress, hot spot stress, and effective notch stress approaches, which were FAT 50, FAT 100, and FAT 225, respectively. Meanwhile, their material constants for LEFM were relatively close to each other. [ABSTRACT FROM AUTHOR]