Search Results (11)

Background/Objectives: Drinking natural bicarbonate water (NBW) has been associated with decreased bone resorption, improved lipid profile, and reduced cardiovascular risk. However, the specific molecular mechanisms underlying these effects remain unclear. Methods: Twenty 10-month-old female Sprague Dawley rats were randomly allocated to two experimental groups; one received purified water (PW) and the other was administered NBW over a three-month intervention period. The liver’s metabolic properties were analyzed using a comprehensive quantitative targeted metabolomics technique. Results: Sixty-nine differential metabolites (67 upregulated and 2 downregulated) were detected in the NBW group compared to the PW group. These metabolites included 34 amino acids, 11 carbohydrates, 7 fatty acids, 7 short-chain fatty acids (SCFAs), and 10 other biomolecules. Furthermore, 10 metabolic pathways exhibited significant alterations: aminoacyl-tRNA biosynthesis; alanine-aspartate-glutamate metabolism; nitrogen-butanoate metabolism; histidine-phenylalanine metabolism; arginine-proline metabolism; glycine-serine-threonine metabolism; valine-leucine-isoleucine biosynthesis; and phenylalanine-tyrosine-tryptophan biosynthesis. The NBW group demonstrated a statistical tendency toward lower urinary calcium/creatinine ratio compared to the PW group. Conclusions: These findings suggest that the consumption of NBW may induce positive nitrogen balance, enhance the level of certain polyunsaturated fatty acids and SCFAs, and improve calcium balance. Such metabolic alterations could potentially explain the beneficial effects of NBW. Full article

Helmet-wearing detection for electric vehicle riders is essential for traffic safety, yet existing detection models often suffer from high target occlusion and low detection accuracy in complex road environments. To address these issues, this paper proposes YOLO-CBF, an improved YOLOv7-based detection network. The proposed model integrates coordinate convolution to enhance spatial information perception, optimizes the Focal EIOU loss function, and incorporates the BiFormer dynamic sparse attention mechanism to achieve more efficient computation and dynamic content perception. These enhancements enable the model to extract key features more effectively, improving detection precision. Experimental results show that YOLO-CBF achieves an average mAP of 95.6% for helmet-wearing detection in various scenarios, outperforming the original YOLOv7 by 4%. Additionally, YOLO-CBF demonstrates superior performance compared to other mainstream object detection models, achieving accurate and reliable helmet detection for electric vehicle riders. Full article

Perilous rock mass disasters are typical forms of collapse disasters. Perilous rock masses are widely distributed in mountainous areas around the world and often pose a great threat to residents and line engineering. The correct evaluation of the stability and disaster-causing ability of perilous rock is important for the guarantee of sustainable development for human beings living in mountainous areas. The dynamic disaster effects of perilous rock collapse have always been a hot topic in the field of engineering geological disaster research. This study takes typical #WY8 and #WY47 perilous rock masses in a zone called the Jiaohua rock perilous rock zone in Chongqing, China, as a case study. The Jiaohua perilous rock mass is located in the Kaizhou District of the Three Gorges Reservoir area in China, which is mainly distributed in a ‘long strip’. The initial deformation and collapse of the perilous rock zone occurred in September 2004, and many local collapses have occurred since. In this study, the basic characteristics of the perilous rock belt of Jiaohua rock were first analyzed, and the failure mechanism of the perilous rock mass of Jiaohua rock was then summarized. Then, a numerical model of the perilous rock mass was established by DAN-W, and the disaster process of perilous rock collapse was analyzed. According to the characteristics of perilous rock and cliffs, considering the collapse partition, the collapse path of debris flow can be divided into three sections: the collapse section, slip section, and accumulation section. The calculation results show that the maximum velocity of the front edge of the #WY8 debris flow is 27.26 m/s, the maximum velocity of the trailing edge is 16.71 m/s, the maximum sliding distance is 437 m, and the impact force of the debris flow on the building is up to 52.29 kPa. The maximum velocity of the front edge of the #WY47 debris flow is 31.05 m/s, the maximum velocity of the trailing edge is 21.99 m/s, the maximum sliding distance is 194.31 m, and the impact force of the debris flow on the building is 241.15 kPa. Civil buildings within the scope of collapse are at risk of being completely destroyed. The research results of this study provide a certain theoretical basis for disaster prevention and mitigation work in the hidden danger area of rock avalanche disasters in the Three Gorges Reservoir area. Full article

The initial enrichment of rare earth elements (REE) in granites plays an important role for the generation of ion-adsorption type REE deposits. It has been summarized that the mineralization-related granitoids are mostly peraluminous, but the enrichment mechanism of REE in this peraluminous granite is currently not well understood. In this study, we conducted geochronology, petrological, and geochemical investigations on the biotite granite and muscovite granite from the Shangyou complex in Ganzhou, Jiangxi Province. Zircon U-Pb dating indicates that both the biotite granite and muscovite granite generated in the Early Silurian (ca. 433–434 Ma). The high aluminum saturation index and occurrence of muscovite and old zircon cores indicate that they belong to the S-type granite and are derived from the melting of metagreywacke. The relatively higher FeO^T contents, Mg# values, and zirconium saturation temperatures (760–873 °C) for the biotite granite resulted from hydrous melting with the involvement of mantle material. In contrast, the muscovite granite with low FeO^T contents, Mg# values, Nb/Ta ratios, and zirconium saturation temperatures (748–761 °C) indicates a purely crust-derived melt formed by muscovite dehydration melting. There is a positive correlation of REE contents with the formation temperature and Th contents in both the Shangyou granites and the data collected from global peraluminous granites. This indicates that temperature plays a key role in the REE enrichment in peraluminous granites, as the high-temperature condition could promote the melting of REE-rich and Th-rich accessory minerals of allanite and REE-phosphate and result in the increases in both REE contents and Th contents in the melts. Given the fact that the parent granites for ion-adsorbing REE deposits are mostly peraluminous and generated in the extensional setting in South China, we concluded that peraluminous granite formed under high-temperature extensional tectonic settings favors initial REE enrichment, which further contributes to the formation of ion-adsorbing REE deposits in South China. Full article

This study looked at how desalinated seawater, which has low minerals and high boron, could affect bone health. Prior research suggests that low mineral water may harm bone health and boron could be beneficial, but the overall impact on bone health is still unclear. Eighty-nine-week-old male Balb/C mice were allocated into eight groups and administered either tap water or purified water with varying boron concentrations (0, 5, 40, and 200 mg/L). They were kept in an environment mimicking tropical conditions (35–40 °C, 70–80% humidity) and underwent daily treadmill exercise for 13 weeks. At the 14th week, serum, femora, and lumbar vertebrae were collected for mineral metabolism, bone biomarker, microstructure, and biomechanics evaluation. Boron exposure improved bone formation, microstructure, and biomechanics initially but the benefits weakened with higher levels of exposure (p < 0.05). Co-exposure to purified water elevated serum boron but weakened the promotion of boron on bone minerals and the bone benefits of boron compared to tap water (p < 0.05). Thus, when studying the health effects of boron in desalinated seawater, it is crucial to look at various health effects beyond bone health. Furthermore, it is important to consider the mineral composition of drinking water when using boron for bone health benefits. Full article

The consumption of low-mineral water has been increasing worldwide. Drinking low-mineral water is associated with cardiovascular disease, osteopenia, and certain neurodegenerative diseases. However, the specific mechanism remains unclear. The liver metabolic alterations in rats induced by drinking purified water for 3 months were investigated with a metabolomics-based strategy. Compared with the tap water group, 74 metabolites were significantly changed in the purified water group (6 increased and 68 decreased), including 29 amino acids, 11 carbohydrates, 10 fatty acids, 7 short chain fatty acids (SCFAs), and 17 other biomolecules. Eight metabolic pathways were significantly changed, namely aminoacyl–tRNA biosynthesis; nitrogen metabolism; alanine, aspartate and glutamate metabolism; arginine and proline metabolism; histidine metabolism; biosynthesis of unsaturated fatty acids; butanoate metabolism; and glycine, serine and threonine metabolism. These changes suggested that consumption of purified water induced negative nitrogen balance, reduced expression of some polyunsaturated fatty acids and SCFAs, and disturbed energy metabolism in rats. These metabolic disturbances may contribute to low-mineral-water-associated health risks. The health risk of consuming low-mineral water requires attention. Full article

Video reversible data hiding technology can be applied to copyright protection, medical images, the military, and other fields, but it cannot guarantee high visual quality with an effective embedded capacity. In this paper, a high-embedding and low-distortion reversible data hiding scheme based on a discrete cosine transform (DCT) coefficients method is proposed. The scheme first decodes the original video stream with entropy, obtains all the DCT blocks, and selects the embeddable DCT blocks according to the capacity of the zero factor. Then, it divides the coefficients in the DCT blocks into the shift and embedding coefficients. The shift coefficients directly generate a one-dimensional histogram; the embedding coefficients generate a two-dimensional histogram according to paired strategies. Finally, the secret data can be successfully embedded according to the proposed two-dimensional histogram shift reversible data hiding scheme. This scheme performed more effectively than existing schemes in terms of the embedded capacity, peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM). Full article

Automated industrial quality detection (QD) boosts quality-detection efficiency and reduces costs. However, current quality-detection algorithms have drawbacks such as low efficiency, easily missed detections, and false detections. We propose QD-YOLO, an attention-based method to enhance quality-detection efficiency on computer mainboards. Firstly, we propose a composite attention module for the network’s backbone to highlight appropriate feature channels and improve the feature fusion structure, allowing the network to concentrate on the crucial information in the feature map. Secondly, we employ the Meta-ACON activation function to dynamically learn whether the activation function is linear or non-linear for various input data and adapt it to varied input scenarios with varying linearity. Additionally, we adopt Ghost convolution instead of ordinary convolution, using linear operations as possible to reduce the number of parameters and speed up detection. Experimental results show that our method can achieve improved real-time performance and accuracy on the self-created mainboard quality defect dataset, with a mean average precision (mAP) of 98.85% and a detection speed of 31.25 Frames Per Second (FPS). Compared with the original YOLOv5s model, the improved method improves mAP@0.5 by 2.09% and detection speed by 2.67 FPS. Full article

Open claims to Confucian values, often associated with cultural traditionalism and a larger revival of Confucianism among the Chinese population from the 2000s onwards, have gained momentum in the world of entrepreneurs. The intensity of this phenomenon can be explained by a wide variety of motivations, among which a desire to establish a belief, a sort of xin 信 towards traditional values, has emerged from within the “Confucian” company. Based on fieldwork carried out between 2017 and 2018 at TW, a private company located in Dongguan (Guangdong), this paper aims to analyze the efforts undertaken by “Confucian” managers to use the spiritual guidance role of Confucianism. Our work is organized into three sections. First, we analyze the main modalities of proselytizing within TW. Then, based on the personal experiences of three employees of this company, we try to understand how they live the jiaohua and to what extent this “educational” experience inspired by Confucianism has allowed them to reorient themselves towards a new way of perceiving the world. Finally, by placing it in a broader context, that of contemporary Chinese society’s crisis of values, we question the role Confucianism can play in the foundation of a population’s beliefs. Full article

Traditional image steganography needs to modify or be embedded into the cover image for transmitting secret messages. However, the distortion of the cover image can be easily detected by steganalysis tools which lead the leakage of the secret message. So coverless steganography has become a topic of research in recent years, which has the advantage of hiding secret messages without modification. But current coverless steganography still has problems such as low capacity and poor quality .To solve these problems, we use a generative adversarial network (GAN), an effective deep learning framework, to encode secret messages into the cover image and optimize the quality of the steganographic image by adversaring. Experiments show that our model not only achieves a payload of 2.36 bits per pixel, but also successfully escapes the detection of steganalysis tools. Full article

Recently, searchable encrypted image retrieval in a cloud environment has been widely studied. However, the inappropriate encryption mechanism and single feature description make it hard to achieve the expected effects. Therefore, a major challenge of encrypted image retrieval is how to extract and fuse multiple efficient features to improve performance. Towards this end, this paper proposes a searchable encrypted image retrieval based on multi-feature adaptive late-fusion in a cloud environment. Firstly, the image encryption is completed by designing the encryption function in an RGB color channel, bit plane and pixel position of the image. Secondly, the encrypted images are uploaded to the cloud server and the convolutional neural network (CNN) is fine-tuned to build a semantic feature extractor. Then, low-level features and semantic features are extracted. Finally, the similarity score curves of each feature are calculated, and adaptive late-fusion is performed by the area under the curve. A large number of experiments on public dateset are used to validate the effectiveness of our method. Full article