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Semen is a complex fluid that contains spermatozoa and also functions as a dynamic bacterial microecosystem, comprising probiotics, pathogenic bacteria, and natural antimicrobial substances. Probiotic bacteria, such as Lactobacillus and Bifidobacterium, along with pathogenic bacteria like Pseudomonas aeruginosa and Escherichia coli, play significant roles in semen preservation and reproductive health. Studies have explored the impact of pathogenic bacteria on sperm quality, providing insights into the bacterial populations in mammalian semen and their influence on sperm function. These reviews highlight the delicate balance between beneficial and harmful bacteria, alongside the role of natural antimicrobial substances that help maintain this equilibrium. Moreover, we discuss the presence and roles of antimicrobial substances in semen, such as lysozyme, secretory leukocyte peptidase inhibitors, lactoferrin, and antimicrobial peptides, as well as emerging antibacterial substances like amyloid proteins. Understanding the interactions among probiotics, pathogens, and antimicrobial agents is crucial for elucidating semen preservation and fertility mechanisms. Additionally, the potential for adding probiotic bacteria with recombinant antibacterial properties presents a promising avenue for the development of new semen extenders. This review offers updated insights to understand the equilibrium of the bacterial microecosystem in semen and points toward innovative approaches for improving semen preservation. [ABSTRACT FROM AUTHOR]

In maintaining roads and ensuring safety, promptly detecting and repairing pavement defects is crucial. However, conventional detection methods demand substantial manpower, incur high costs, and suffer from low efficiency. To enhance road maintenance efficiency and reduce costs, we propose an improved algorithm based on YOLOv8. Our method incorporates several key enhancements. First, we replace conventional convolutions with a module composed of spatial-to-depth layers and nonstrided convolution layers (SPD-Conv) in the network backbone, enhancing the capability of recognizing small-sized defects. Second, we replace the neck of YOLOv8 with the neck of the ASF-YOLO network to fully integrate spatial and scale features, improving multiscale feature extraction capability. Additionally, we introduce the FasterNet block from the FasterNet network into C2f to minimize redundant computations. Furthermore, we utilize Wise-IoU (WIoU) to optimize the model's loss function, which accounts for the quality factors of objects more effectively, enabling adaptive learning adjustments based on samples of varying qualities. Our model was evaluated on the RDD2022 road damage dataset, demonstrating significant improvements over the baseline model. Specifically, with a 2.8% improvement in m A P and a detection speed reaching 43 FPS, our method proves to be highly effective in real-time road damage detection tasks. [ABSTRACT FROM AUTHOR]

Remote transportation microwave sensor (RTMS) technology is being promoted for China's highways. The distance is about 2 to 5 km between RTMSs, which leads to missing data and data sparseness problems. These two problems seriously restrict the accuracy of travel time prediction. Aiming at the data-missing problem, based on traffic multimode characteristics, a tensor completion method is proposed to recover the lost RTMS speed and volume data. Aiming at the data sparseness problem, virtual sensor nodes are set up between real RTMS nodes, and the two-dimensional linear interpolation and piecewise method are applied to estimate the average travel time between two nodes. Next, compared with the traditional K-nearest neighbor method, an optimal KNN method is proposed for travel time prediction. optimization is made in three aspects. Firstly, the three original state vectors, that is, speed, volume, and time of the day, are subdivided into seven periods. Secondly, the traffic congestion level is added as a new state vector. Thirdly, the cross-validation method is used to calibrate the K value to improve the adaptability of the KNN algorithm. Based on the data collected from Jinggangao highway, all the algorithms are validated. The results show that the proposed method can improve data quality and prediction precision of travel time., 1. Introduction Travel time is a traffic parameter that can reflect traffic conditions effectively, and it is the most popular traffic information for travelers. How to predict travel time accurately [...]

Rockeries, which imitate nature in a special form, are an essential element of Chinese classical garden design and one of the most fascinating features that distinguish Chinese culture from other traditions of the world. This study takes rockeries in Huanxiu Shanzhuang—one of the exceptional rockeries in China—as an example to study the methods of digital survey, documentation and research of Chinese cultural heritage. Using techniques of terrestrial laser scanning and digital photogrammetry, this study made surveys, 3D models and morphometric measurements of piled mountains and single monoliths in Huanxiu Shanzhuang. A survey and document approach for different kinds of rockeries in Chinese classical gardens was studied by comparing the related techniques applied in different situations. Using the methods studied in this research, rockeries in Huanxiu Shanzhuang were documented and measured. [ABSTRACT FROM AUTHOR]

Zinc finger DHHC-type palmitoyltransferase 9 (ZDHHC9) has been reported to play an important role in the occurrence and development of several types of cancer. However, its effects on colon cancer growth remain unclear. Using Gene Expression Profiling Interactive Analysis and Tumor Immune Estimation Resource, data obtained from The Cancer Genome Atlas were analyzed, and the results showed that ZDHHC9 was highly expressed in colon cancer and that patients with higher ZDHHC9 expression levels had a worse prognosis. Inhibition of ZDHHC9 expression promoted the proliferation of colon cancer cells in vitro but decreased their growth in vivo. Additionally, inhibition of ZDHHC9 expression in cancer cells enhanced CD8+ T cell-mediated cytotoxicity in vitro and increased CD8+ T infiltration and activation in vivo. Furthermore, ZDHHC9 promoted IFN-γ-induced JAK/STAT1 activation and upregulated programmed death-ligand 1 (PD-L1) expression in colon cancer cells. In conclusion, the present findings showed that ZDHHC9 promoted colon cancer growth by upregulating the expression of PD-L1 and inhibiting the function of CD8+ T cells. [ABSTRACT FROM AUTHOR]