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Abstract Ancient buildings possess significant artistic and cultural value. The digitization of these structures is a crucial aspect of their restoration, providing foundational data for subsequent stress and health analyses. However, creating accurate models of ancient buildings is a challenging endeavor, even for experienced researchers, especially when dealing with a large number of structures. A pressing issue that needs addressing is how to quickly obtain accurate models of ancient buildings while ensuring both precision and efficiency. Currently, one of the more precise methods for reconstructing models of ancient buildings involves the use of scanned point clouds and manual reconstruction through modeling software. However, this method suffers from poor accuracy and low efficiency, making the modeling process complex and time-consuming. In this article, we will refer to the model generated from the point cloud of real components as the "current state model", and the unforced mesh model of the ancient building as the "standard model". An algorithm is proposed to construct the current state model of ancient buildings by guiding the deformation of the unforced standard model using the scanned point cloud model. First, this paper designs an automatic modeling method for ancient building components as the foundational data before deformation, addressing the issue of low modeling efficiency for ancient buildings. Second, it proposes a method for automatically calculating deformation control point pairs based on the characteristics of ancient buildings, solving the problem of manually locating control points. Finally, the proposed adaptive weight Laplacian deformation algorithm is applied to deform the standard model into the current state model.

Abstract In recent years, with the development of 3D digitization of cultural relics, most cultural sites contain a large number of fine 3D data of cultural relics, especially complex geometric objects such as painted cultural relics. At present, how to automatically extract surface damage information from the fine 3D color model of painted cultural relics and avoid the loss of accuracy caused by reducing the dimension using conventional methods is an urgentproblem. In view of the above issues, this paper proposes an automatic and high-precision extraction method for cultural relics surface shedding diseases based on 3D fine data. First, this paper designs a 2D and 3D integrated data conversion model based on OpenSceneGraph, a 3D engine, which performs mutual conversion between 3D color model textures and 2D images. Second, this paper proposes a simple linear iterative clustering segmentation algorithm with an adaptive k value, which solves the problem of setting the superpixel k value and improves the accuracy of image segmentation. Finally, through the 2D and 3D integrated models, the disease is statistically analyzed and labeled on the 3D model. Experiments show that for painted plastic objects with complex surfaces, the disease extraction method based on the 3D fine model proposed in this paper has improved geometric accuracy compared with the current popular orthophoto extraction method, and the disease investigation is more comprehensive. Compared with the current 3D manual extraction method in commercial software, this method greatly improves the efficiency of disease extraction while ensuring extraction accuracy. The research method of this paper activates many existing 3D fine data of cultural protection units and converts conventional 2D data mining and analysis into 3D, which is more in line with the scientific utilization of data in terms of accuracy and efficiency and has certain scientific research value, leading value and practical significance.

Pak choi exhibits a wide range of phenotypic and morphological variations, significantly impacting its carbohydrate composition. This study aimed to analyze these variations by employing UPLC-MS/MS technology on eight biological replicates of seven Pak choi cultivars. The untargeted metabolic analysis identified 513 metabolites, focusing on 16 key carbohydrates, including monosaccharides, disaccharides, and polysaccharides. Monosaccharides were the most prevalent, which were followed by di-, poly-, and oligosaccharides. Suzhouqing had the highest number of differentially accumulated metabolites (DAMs), while Xiangqingcai had the least. Notably, the cultivars Xiangqingcai, Suzhouqing, and Aijiaohuang showed significant metabolite differentiation. The study found 114 metabolites that differed significantly between Suzhouqing and Aijiaohuang, of which 69 were upregulated and 45 were downregulated. In Xiangqingcai and Aijiaohuang, 66 metabolites were upregulated and 49 were downregulated. Between Xiangqingcai and Suzhouqing, 80 metabolites were downregulated and 53 were upregulated. Key carbohydrate digestion and absorption pathways were identified alongside the most enriched flavonoid biosynthesis pathway in Xiangqingcai and Suzhouqing. The findings highlight the considerable carbohydrate variation among Pak choi cultivars, providing valuable insights for targeted carbohydrate extraction and improving nutritional and agricultural practices.

Numerous studies have been conducted to investigate the genomic characterization of bZIP genes and their involvement in the cellular response to endoplasmic reticulum (ER) stress. These studies have provided valuable insights into the coordinated cellular response to ER stress, which is mediated by bZIP transcription factors (TFs). However, a comprehensive and systematic investigations regarding the role of bZIP genes and their involvement in ER stress response in pak choi is currently lacking in the existing literature. To address this knowledge gap, the current study was initiated to elucidate the genomic characteristics of bZIP genes, gain insight into their expression patterns during ER stress in pak choi, and investigate the protein-to-protein interaction of bZIP genes with the ER chaperone BiP. In total, 112 members of the BcbZIP genes were identified through a comprehensive genome-wide analysis. Based on an analysis of sequence similarity, gene structure, conserved domains, and responsive motifs, the identified BcbZIP genes were categorized into 10 distinct subfamilies through phylogenetic analysis. Chromosomal location and duplication events provided insight into their genomic context and evolutionary history. Divergence analysis estimated their evolutionary history with a predicted divergence time ranging from 0.73 to 80.71 million years ago (MYA). Promoter regions of the BcbZIP genes were discovered to exhibit a wide variety of cis-elements, including light, hormone, and stress-responsive elements. GO enrichment analysis further confirmed their roles in the ER unfolded protein response (UPR), while co-expression network analysis showed a strong relationship of BcbZIP genes with ER-stress-responsive genes. Moreover, gene expression profiles and protein–protein interaction with ER chaperone BiP further confirmed their roles and capacity to respond to ER stress in pak choi.

The accumulation of misfolded proteins in the endoplasmic reticulum (ER) within plant cells due to unfavourable conditions leads to ER stress. This activates interconnected pathways involving reactive oxygen species (ROS) and unfolded protein response (UPR), which play vital roles in regulating ER stress. The aim of this study is to investigate the underlying mechanisms of tunicamycin (TM) induced ER stress and explore the potential therapeutic applications of tauroursodeoxycholic acid (TUDCA) in mitigating cellular responses to ER stress in Pak choi (Brassica campestris subsp. chinensis). The study revealed that ER stress in Pak choi leads to detrimental effects on plant morphology, ROS levels, cellular membrane integrity, and the antioxidant defence system. However, treatment with TUDCA in TM-induced ER stressed Pak choi improved morphological indices, pigment contents, ROS accumulation, cellular membrane integrity, and antioxidant defence system restoration. Additionally, TUDCA also modulates the transcription levels of ER stress sensors genes, ER chaperone genes, and ER-associated degradation (ERAD) genes during ER stress in Pak choi. Furthermore, TUDCA has demonstrated its ability to alleviate ER stress, stabilize the UPR, reduce oxidative stress, prevent apoptosis, and positively influence plant growth and development. These results collectively comprehend TUDCA as a promising agent for mitigating ER stress-induced damage in Pak choi plants and provide valuable insights for further research and potential applications in crop protection and stress management. [ABSTRACT FROM AUTHOR]