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The distribution features of coal particle size are closely related to the analysis of methane gas propagation in coal. At present, the coal particle size analysis method based on image segmentation has become one of the mainstream solutions to obtain coal particle size. But there are problems such as loss of contextual information, improper fusion of coal particle features resulting in missed segmentation and over-segmentation of coal particles. In order to solve the above problems, a coal particle size analysis model based on bi-level routing attention (BRA) is designed. The BRA module is embedded in the residual U-shaped network ResNet-UNet to obtain the B-ResUNet network model. To reduce the problem of missed segmentation in coal particle segmentation, a BRA module is added before upsampling in the ResNet-UNet network. It allows the network to adjust the importance of the current feature layer based on the features of the previous layer, enhance the expression capability of features, and improve the transmission capability of long-distance information. To reduce the problem of over segmentation in coal particle segmentation, a BRA module is added after the feature concatenation module of the ResNet-UNet network. By dynamically selecting and aggregating important features, more effective feature fusion is achieved. The feature information from the segmented coal particles is extracted. The coal particle size of the coal particle dataset used in the experimental analysis is equivalent to the cell size. In order to accurately characterize the coal particle size, equivalent circular particle size is used to obtain the coal particle size and size distribution. The experimental results show the following points. ① The accuracy, average intersection to union ratio, and recall of the B-ResUNet network model have been improved by 06.%, 14.3%, and 35.9% compared to the ResNet-UNet basic network, with an accuracy of 99.6%, an average intersection to union ratio of 92.6%, and a recall of 94.4%. The B-ResUNet network model has good segmentation performance in coal samples and can detect relatively complete particle structures. ② When the BRA module is introduced before upsampling and after feature concatenation, the network pays sufficient attention to the edge areas of coal particles and reduces attention to some less important areas, thereby improving the computational efficiency of the network. ③ The particle size of coal particles shows a relatively balanced distribution trend within 1-2 mm, with the maximum proportion of coal particles within 1-2 mm being 99.04% and the minimum being 90.59%. It indicates that the image processing method based on BRA has high accuracy in particle size analysis.

Radar echo extrapolation by ground-based remote sensing is essential for weather prediction and flight guiding. Existing radar echo extrapolation methods can hardly capture complex spatiotemporal features, resulting in the low accuracy of predictions, and, therefore, severely restrict their use in extreme weather situations. A deep learning method was recently applied for extrapolating radar echoes; however, its accuracy declines too quickly over a short time. In this study, we introduce a solution: Residual Transformer and Unet (ResTUnet), a novel model that improves prediction accuracy and exhibits good stability with a slow rate of accuracy decline. This presented Rest-Net model is designed to solve the issue of declining prediction accuracy by integrating a 1*1 convolution to diminish the neural network parameters. We constructed an observed dataset by Zhengzhou East Airport radar observation from July 2022 to August 2022 and performed 90 min experiments comprising five aspects, including extrapolation images, the Probability of Detection (POD) index, the Critical Success Index (CSI), the False Alarm Rate (FAR) index, and the Heidke Skill Score (HSS) index. The experimental results show that the ResTUnet model improved the CSI, HSS index, and the POD index by 17.20%, 11.97%, and 11.35%, compared to current models, including Convolutional Long Short-Term Memory (convLSTM), the Convolutional Gated Recurrent Unit (convGRU), the Trajectory Gated Recurrent Unit (TrajGRU), and the improved recurrent network for video predictive learning, the Predictive Recurrent Neural Network++ (predRNN++). In addition, the mean squared error of the ResTUnet model remains stable at 15% between 0 and 60 min and starts to increase after 60–90 min, which is 12% better than the current models. This enhancement in prediction accuracy has practical applications in meteorological services and decision making. [ABSTRACT FROM AUTHOR]

In Older to analyze the transmission characteristics of non-circular gears in different transmission modes, Pascal worn line gear was taken as the research object, and the mathematical model of the Pascal worm line gear pitch curve was established in intern! meshing transmission, and a visualization platform for the transmission characteristics analysis of the Pascal worm line gear in internal meshing transmission was established by using MatLab based on the established mathematical model, the motion characteristics of the Pascal worm gear during internal and external meshing transmission were analyzed by using the developed visualization platform. The amplitude of the Pascal worm gear pair transmission ratio was affected by circle diameter occurs and exhibition length by compared and analyzed, and the Amplitude of the transmission ratio was not affected by the denatured coefficient, but position of the amplitude of the transmission ratio was affected by the denaturation coefficient. The range of transmission ratio variation during external meshing transmission was significantly larger than that during internal meshing transmission. In order to further explain the influence of transmission mode on motion characteristics, the guide bar mechanism was studied and analyzed as an example. If the transmission ratio changes greatly during design, the outer meshing transmission mode should be selected. If the transmission ratio change range is small and the structure is compact, choose the internal meshing transmission mode. [ABSTRACT FROM AUTHOR]

In order to optimize the performance of the weft insertion mechanism, innovative research was carried out on the basis of existing weft insertion mechanisms, and a new type of weft insertion mechanism with the combination of transmission of pascal worm gear and crank slider was proposed. In order to facilitate the analysis of the motion characteristics of the new type of weft insertion mechanism, a kinematic mathematical model of the mechanism was established based on numerical analysis and geometric graphics, and a visual design and analysis platform for the weft insertion mechanism was established using MatLab. In order to analyze the influence of various design parameters on the motion characteristics of the weft insertion mechanism, with the acceleration of the rapier belt as the optimization objective, the orthogonal experimental optimization method was used to optimize and analyze the mechanism. It was found that three parameters, namely the ratio of the elongation to the diameter of the generating circle, the ratio of the length of the connecting rod to the length of the crank, and the radius of the rapier wheel, have a significant impact on the weft insertion motion law; The coefficient of variation and the screw pitch have little effect. The research results pro-vide reference opinions for the comprehensive study of the motion characteristics of the weft insertion mechanism. [ABSTRACT FROM AUTHOR]

Bulk metallic glasses (BMGs) have garnered significant attention in recent decades due to the outstanding physical, chemical, and biomedical characteristics. The biomedical application of metallic glass also received extensive attention. This report investigates the interplay among antibacterial performance, crystallization and processing parameters of Zr-based bulk metallic glass (Zr-BMG) following nanosecond laser irradiation. We examined surface morphology, crystallization behavior, surface quality, binding energy, and ion release properties post-laser irradiation. Additionally, we evaluated the generation of reactive oxygen species upon immersion of Zr-BMG in phosphate-buffered saline using the 2′,7′-dichlorofluorescin diacetate method. Staphylococcus aureus was chosen to assess Zr-BMG's antibacterial performance, while mouse osteoblasts were utilized to investigate in vitro cytotoxicity. Our findings revealed that at laser energy intensities below 0.08 J/mm2, the amorphous structure of Zr-BMG remained intact after irradiation. Moreover, laser irradiation significantly enhanced the antibacterial performance of Zr-BMG. The release rate of ion, concentration of reactive oxygen species, and antibacterial properties exhibited direct proportionality to laser energy intensity. However, surfaces exhibiting high antibacterial efficacy also displayed elevated cytotoxicity. The surface irradiated with a 7 μJ ablation pulse and 200 mm/s irradiation speed demonstrated a superior balance between antibacterial and cytotoxic properties while maintaining an amorphous state. We hope this research can provide theoretical reference and data support for the application of metallic glass in biomedical application. [ABSTRACT FROM AUTHOR]

Background: Boswellic acids (BAs) showed promising effects in cancer treatment, immune response regulation, and anti-inflammatory therapy. We aimed to assess the roles of alpha-BA (α-BA) in treating acute wound healing. Methods: In vivo wound-healing models were established to evaluate the therapeutic effects of α-BA. Cell assays were conducted to assess the impact of α-BA on cellular biological functions. Western blot analysis was employed to validate the potential mechanisms of action of α-BA. Results: Animal models indicated that wound healing was notably accelerated in the α-BA group compared to the control group (P < 0.01). Hematoxylin and eosin (HE) staining and enzyme-linked immunosorbent assay (ELISA) assay preliminarily suggested that α-BA may accelerate wound healing by inhibiting excessive inflammatory reactions and increasing the protein levels of growth factors. Cell function experiments demonstrated that α-BA suppressed the proliferation and migration ability of human hypertrophic scar fibroblasts (HSFBs), thereby favoring wound healing. Additionally, α-BA exerted a significant impact on cell cycle progression. Mechanistically, the protein levels of key genes in nuclear factor kappa beta (NF-κB) signaling pathway, including cyclin D1, p65, IκBα, and p-IκBα, were downregulated by α-BA. Conclusions: α-BA demonstrated the ability to counteract the abnormal proliferation of skin scar tissues, consequently expediting wound healing. These findings suggest its potential for development as a new agent for treating acute wound healing. [ABSTRACT FROM AUTHOR]

Modified polyimide (MPI) flexible printed circuits (FPCs) are used as chip carrier boards. The quality of the FPC directly affects the reliability of the integrated circuit. Furthermore, micro-holes are critical components of FPCs. In this study, an ultraviolet (UV) femtosecond laser is used to drill micro-holes in double-layer flexible circuit boards with MPI as the substrate. The morphology of the micro-hole wall in the copper foil and MPI layer is observed, and the effects of the laser processing parameters on the diameter and depth of the micro-holes are analyzed. The drilling process and mechanism of micro-holes obtained using a UV femtosecond laser in MPI FPCs are discussed. The results show that the morphology of femtosecond laser-machined copper is closely related to the laser energy, and a periodic structure is observed during the machining process. Copper, MPI, and copper oxides are the most common molten deposits in micro-holes during drilling. The depth of the micro-holes increases with an increase in the energy of a single pulse, scanning time, and scanning overlap rate of the laser beam. However, the diameter exhibits no discernible alteration. The material removal rate increased significantly when laser processing was applied to the MPI resin layer. [ABSTRACT FROM AUTHOR]