Publications by authors named "Ma Kaifeng"

Article Synopsis
  • A novel photogrammetric technique was used to accurately measure the size and thermal deformation of a satellite antenna, demonstrating measurement errors below 0.04 mm, which is suitable for technical requirements.
  • The study found that the antenna's surface shape and rib precision decline as temperatures drop, with the most significant deformation occurring at -60 °C, yet still meeting the design accuracy standards.
  • For temperature variations of 40 °C and 80 °C, the radial mean square errors (RMSE) for surface shape deformation were 0.216 mm and 0.411 mm, respectively, confirming that the design criteria for antenna accuracy were achieved.
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Depending on the size, shape, and gray intensity distribution of charge-coupled device (CCD) imaging retro-reflective targets (RRTs) in close-range photogrammetry, and based on conventional grayscale centroiding, this paper proposes grayscale threshold variable-index weighted centroiding (GTVIWC). The centroid location accuracy of CCD imaging RRTs was analyzed and compared using simulated and measured target images, respectively. The experimental results demonstrated that the centroid location accuracy of the algorithms used in the experiment was relatively high, reaching the subpixel level.

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A high-quality dataset is a basic requirement to ensure the training quality and prediction accuracy of a deep learning network model (DLNM). To explore the influence of label image accuracy on the performance of a concrete crack segmentation network model in a semantic segmentation dataset, this study uses three labelling strategies, namely pixel-level fine labelling, outer contour widening labelling and topological structure widening labelling, respectively, to generate crack label images and construct three sets of crack semantic segmentation datasets with different accuracy. Four semantic segmentation network models (SSNMs), U-Net, High-Resolution Net (HRNet)V2, Pyramid Scene Parsing Network (PSPNet) and DeepLabV3+, were used for learning and training.

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Bridge crack detection based on deep learning is a research area of great interest and difficulty in the field of bridge health detection. This study aimed to investigate the effectiveness of coupling a deep learning framework (DLF) with a convolutional neural network (CNN) for bridge crack detection. A dataset consisting of 2068 bridge crack images was randomly split into training, verification, and testing sets with a ratio of 8:1:1, respectively.

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Article Synopsis
  • Mei (Prunus mume) is unique for its floral fragrance, but the mechanisms behind its aroma compound production need further investigation.
  • An analysis of the volatile compounds in two Prunus mume cultivars revealed 44 different aroma compounds, with key contributors being eugenol, cinnamyl acetate, hexyl acetate, and benzyl acetate, whose varying concentrations affect the scent profile.
  • The study identified important genes and enzymes involved in the biosynthesis of aroma compounds, suggesting potential targets for future research on enhancing floral fragrance in these plants.*
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Background: The evolution of resistance to antimicrobials is a ubiquitous phenomenon. The evolution of antibiotic resistance in Staphylococcus aureus suggests that there is no remedy with sustaining effectiveness against this pathogen. The limited number of antibacterial drug classes and the common occurrence of cross-resistant bacteria reinforce the urgent need to discover new compounds targeting novel cellular functions.

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DNA methylation is a common epigenetic modification involved in regulating many biological processes. However, the epigenetic mechanisms involved in the formation of floral scent have rarely been reported within a famous traditional ornamental plant emitting pleasant fragrance in China. By combining whole-genome bisulfite sequencing and RNA-seq, we determined the global change in DNA methylation and expression levels of genes involved in the biosynthesis of floral scent in four different flowering stages of .

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Trehalose and its key synthase (trehalose-6-phosphate synthase, TPS) can improve the drought tolerance of plants. However, little is known about the roles of trehalose and the TPS family in response to drought. In our study, we discovered that the trehalose content in leaf, root, and stem tissues significantly increased in in response to drought.

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Epigenetic changes caused by methylcytosine modification participate in gene regulation and transposable element (TE) repression, resulting in phenotypic variation. Although the effects of DNA methylation and TE repression on flower, fruit, seed coat, and leaf pigmentation have been investigated, little is known about the relationship between methylation and flower color chimerism. In this study, we used a comparative methylomic⁻transcriptomic approach to explore the molecular mechanism responsible for chimeric flowers in "Danban Tiaozhi".

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This study focused on the construction of a database of transposable elements (TEs) from Rosaceae plants, the third most economically important plant family in temperate regions, and its transcriptomics applications. The evolutionary effects of TEs on gene regulation have been explored, and TE insertions can be the molecular bases of changes in gene structure and function. However, a specific Rosaceae plant TE database (RPTEdb) is lacking.

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Mei (Prunus mume) is an ornamental woody plant that has been domesticated in East Asia for thousands of years. High diversity in floral traits, along with its recent genome sequence, makes mei an ideal model system for studying the evolution of woody plants. Here, we investigate the genetic architecture of floral traits in mei and its domestication history by sampling and resequencing a total of 351 samples including 348 mei accessions and three other Prunus species at an average sequencing depth of 19.

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Increasing evidence shows that epigenetics plays an important role in phenotypic variance. However, little is known about epigenetic variation in the important ornamental tree . We used amplified fragment length polymorphism (AFLP) and methylation-sensitive amplified polymorphism (MSAP) techniques, and association analysis and sequencing to investigate epigenetic variation and its relationships with genetic variance, environment factors, and traits.

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Mei, Prunus mume Sieb. et Zucc., is an ornamental plant popular in East Asia and, as an important member of genus Prunus, has played a pivotal role in systematic studies of the Rosaceae.

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Dioecious plants have evolved sex-specific floral development mechanisms. However, the precise gene expression patterns in dioecious plant flower development remain unclear. Here, we used andromonoecious poplar, an exceptional model system, to eliminate the confounding effects of genetic background of dioecious plants.

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The productivity, distribution and population structure of poplar are affected by temperature transitions. Poplar floral buds develop in a fluctuating environment and the molecular basis of temperature-dependent flowering regulation has been extensively studied, but little is known about how sex-specific floral bud development responds to temperature transitions. Here, morphological observations indicated that floral bud growth rates were affected by maximum and minimum air temperature at the later stages of enlargement (stage 4) and later stage of dormancy (stage 8), respectively.

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Background: It is thought that methylcytosine can be inherited through meiosis and mitosis, and that epigenetic variation may be under genetic control or correlation may be caused by neutral drift. However, DNA methylation also varies with tissue, developmental stage, and environmental factors. Eliminating these factors, we analyzed the levels and patterns, diversity and structure of genomic methylcytosine in the xylem of nine natural populations of Chinese white poplar.

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Although the molecular basis of poplar sex-specific flower development remains largely unknown, increasing evidence indicates an essential role for microRNAs (miRNAs). The specific miRNA types and precise miRNA expression patterns in dioecious plant flower development remain unclear. Here, we used andromonoecious poplar, an exceptional model system, to eliminate the confounding effects of genetic background of dioecious plants.

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Article Synopsis
  • The study focuses on the SUP gene family in dioecious woody plants, specifically examining the diversification and expression patterns of these genes in Populus.
  • Analysis reveals that PtoSUP1 is highly conserved and its evolution is shaped by strong purifying selection, indicating its important role in floral development.
  • The research suggests that gender-specific expression of SUP genes affects flower development, particularly highlighting the suppression of PtoSUP1 mRNA in gynomonoecious poplar flowers as a factor in stamen development.
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KEY MESSAGE : We report that low fertility during intraspecific hybridization in Chinese white poplar was caused by prefertilization barriers, reduced ovules, and embryonic abortion. Hormone concentrations and gene expression patterns were also evaluated during the fertilization process. Hybrid vigor holds tremendous potential for yield increases and trait improvement; however, some hybridization combinations within Populus show very low fertility.

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Unlabelled: The andromonoecious poplar is an exceptional model system for studying sex-specific flower development in dioecious plants. There is increasing evidence that epigenetic regulation, particularly DNA methylation, is an important regulatory factor during flower development. Here, methylation-sensitive amplified polymorphism (MSAP) was used to screen for sex-specific DNA methylation alterations in the andromonoecious poplar.

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