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363 results on '"Zhang, Xuening"'

43. In‐locus gene silencing in plants using genome editing.

Author

Shen, Rundong, Yao, Qi, Tan, Xinhang, Ren, Wendan, Zhong, Dating, Zhang, Xuening, Li, Xinbo, Dong, Chao, Cao, Xuesong, Tian, Yifu, Zhu, Jian‐Kang, and Lu, Yuming

Subjects
GENE expression, RNA interference, TRANSGENE expression, GENE silencing, PHENOTYPES
Abstract

Summary: Gene silencing is crucial in crop breeding for desired trait development. RNA interference (RNAi) has been used widely but is limited by ectopic expression of transgenes and genetic instability. Introducing an upstream start codon (uATG) into the 5′untranslated region (5′UTR) of a target gene may 'silence' the target gene by inhibiting protein translation from the primary start codon (pATG).Here, we report an efficient gene silencing method by introducing a tailor‐designed uATG‐containing element (ATGE) into the 5′UTR of genes in plants, occupying the original start site to act as a new pATG.Using base editing to introduce new uATGs failed to silence two of the tested three rice genes, indicating complex regulatory mechanisms. Precisely inserting an ATGE adjacent to pATG achieved significant target protein downregulation. Through extensive optimization, we demonstrated this strategy substantially and consistently downregulated target protein expression. By designing a bidirectional multifunctional ATGE4, we enabled tunable knockdown from 19% to 89% and observed expected phenotypes. Introducing ATGE into Waxy, which regulates starch synthesis, generated grains with lower amylose, revealing the value for crop breeding.Together, we have developed a programmable and robust method to knock down gene expression in plants, with potential for biological mechanism exploration and crop enhancement. See also the Commentary on this article by Li & Wei, 243: 2052–2054. [ABSTRACT FROM AUTHOR]

Published
2024
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45. Bud-YOLO: A Real-Time Accurate Detection Method of Cotton Top Buds in Cotton Fields.

Author

Zhang, Xuening and Chen, Liping

Subjects
DEEP learning, BUDS, COTTON, PREDICTION models, ROBOTS
Abstract

Cotton topping plays a crucial and indispensable role in controlling excessive growth and enhancing cotton production. This study aims to improve the operational efficiency and accuracy of cotton topping robots through a real-time and accurate cotton top bud detection algorithm tailored for field operation scenarios. We propose a lightweight structure based on YOLOv8n, replacing the C2f module with the Cross-Stage Partial Networks and Partial Convolution (CSPPC) module to minimize redundant computations and memory access. The network's neck employs an Efficient Reparameterized Generalized-FPN (Efficient RepGFPN) to achieve high-precision detection without substantially increasing computational cost. Additionally, the loss calculation of the optimized prediction frame was addressed with the Inner CIoU loss function, thereby enhancing the precision of the model's prediction box. Comparison experiments indicate that the Bud-YOLO model is highly effective for detecting cotton top buds, with an AP50 of 99.2%. This performance surpasses that of other YOLO variants, such as YOLOv5s and YOLOv10n, as well as the conventional Faster R-CNN model. Moreover, the Bud-YOLO model exhibits robust performance across various angles, occlusion conditions, and bud morphologies. This study offers technical insights to support the migration and deployment of the model on cotton topping machinery. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Comparative Study on the Seismic Vulnerability of Continuous Bridges with Steel–Concrete Composite Girder and Reinforced Concrete Girder.

Author

Xu, Baishun, Sun, Chuanzhi, Song, Shuai, Zhang, Xuening, Zhao, Bin, and Zhang, Wenhao

Subjects
CONTINUOUS bridges, STEEL-concrete composites, COMPOSITE construction, CONCRETE beams, REINFORCED concrete, LATIN hypercube sampling, STEEL framing
Abstract

For medium- and small-span bridges, the weight of the superstructure in steel–concrete composite girder bridges is lighter than that of a reinforced concrete girder bridge. However, it is still uncertain whether steel–concrete composite girder bridges exhibit superior seismic performance compared to reinforced concrete girder bridges. This study quantitatively compared the seismic performance of the two types of bridges. Using the theory of probabilistic seismic demand analysis, the seismic vulnerability curves of bridges were derived. To conduct seismic demand analysis for probabilistic analysis on the OpenSEES platform, bridge samples were generated using the Latin hypercube stratified sampling method, which considers the uncertainties associated with the two types of bridges. The vulnerability curves of the piers, bearings, abutments, and the system of the two bridges were established using probabilistic analysis of the time history analyses. The results showed that the seismic vulnerabilities of components and the overall system of the steel–concrete composite girder bridge were both lower than those of the reinforced concrete girder bridge. When the peak ground acceleration (PGA) of the ground motion was 0.3 g, the moderate and serious damage probabilities of the piers in the steel–concrete composite bridge were only 54.61% and 60.89%, respectively, of those of the reinforced concrete bridge. Consequently, replacing the upper reinforced concrete girders with steel–concrete composite girders can significantly improve the seismic performance of a large number of existing bridges. [ABSTRACT FROM AUTHOR]

Published
2024
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