Zobrazeno 1 - 10
of 8 035
pro vyhledávání: '"Mengnan An"'
Autor:
Xinran Gao, Kaiqiang Hao, Zhichao Du, Sijia Zhang, Zhiping Wang, Mengnan An, Zihao Xia, Yuanhua Wu
Publikováno v:
Phytopathology Research, Vol 5, Iss 1, Pp 1-18 (2023)
Abstract RNA silencing plays an important role in plant antiviral responses, which trigger the production of virus-derived small interfering RNAs (vsiRNAs). The competing endogenous RNA (ceRNA) hypothesis revealed a unique mechanism in which circular
Externí odkaz:
https://doaj.org/article/eb5adec5a7fa48a1819051f45c468d51
Autor:
Lina Li, Yuxin Wang, He Liu, Wei Liu, Xinchen Zhang, Mengnan An, Miao Yu, Yuanhua Wu, Xinghai Li, Jianzhong Wang
Publikováno v:
Molecules, Vol 29, Iss 6, p 1413 (2024)
SYAUP-491 is a novel alkyl sulfonamide. In this study, in vivo and in vitro tests were performed along with a proteomic analysis to determine the effects and underlying mechanisms of the antibacterial activity of SYAUP-491 against the causative agent
Externí odkaz:
https://doaj.org/article/0dd5473cdc7e441cbafe0049d523d2d9
Autor:
Xinchun Li, Huihui Hou, Bin Li, Shiping Guo, Lianqiang Jiang, Chuantao Xu, Yunbo Xie, Mengnan An, Chong Zhang, Yuanhua Wu
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
Rhizoctonia solani as a cosmopolitan fungus is the causative agent of many crop diseases and leads to significant economic losses in crop production. To explore the toxin structure and physiological activity of R. solani AG-3 TB, high-performance liq
Externí odkaz:
https://doaj.org/article/d7eb2485b6d1443bb9e36109395bff23
Autor:
Chuantao Xu, Huiyan Guo, Rui Li, Xinyu Lan, Yonghui Zhang, Qiang Xie, Di Zhu, Qing Mu, Zhiping Wang, Mengnan An, Zihao Xia, Yuanhua Wu
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
Potato virus Y (PVY) mainly infects Solanaceous crops, resulting in considerable losses in the yield and quality. Iron (Fe) is involved in various biological processes in plants, but its roles in resistance to PVY infection has not been reported. In
Externí odkaz:
https://doaj.org/article/98b6fccc378c46e09a50a6a9df46fbea
Latent representation alignment has become a foundational technique for constructing multimodal large language models (MLLM) by mapping embeddings from different modalities into a shared space, often aligned with the embedding space of large language
Externí odkaz:
http://arxiv.org/abs/2411.05316
Autor:
Shu, Dong, Du, Mengnan
In-context learning can help Large Language Models (LLMs) to adapt new tasks without additional training. However, this performance heavily depends on the quality of the demonstrations, driving research into effective demonstration selection algorith
Externí odkaz:
http://arxiv.org/abs/2410.23099
Publikováno v:
Journal of Molecular Liquids, 2024, 414: 126190
The ionic selectivity of nanopores is crucial for the energy conversion based on nanoporous membranes. It can be significantly affected by various parameters of nanopores and the applied fields driving ions through porous membranes. Here, with finite
Externí odkaz:
http://arxiv.org/abs/2410.20365
Adversarial training (AT) refers to integrating adversarial examples -- inputs altered with imperceptible perturbations that can significantly impact model predictions -- into the training process. Recent studies have demonstrated the effectiveness o
Externí odkaz:
http://arxiv.org/abs/2410.15042
Intelligent reflecting surface (IRS) operating in the terahertz (THz) band has recently gained considerable interest due to its high spectrum bandwidth. Due to the exploitation of large scale of IRS, there is a high probability that the transceivers
Externí odkaz:
http://arxiv.org/abs/2410.08459
Large language models (LLMs) leveraging in-context learning (ICL) have set new benchmarks in few-shot learning across various tasks without needing task-specific fine-tuning. However, extensive research has demonstrated that the effectiveness of ICL
Externí odkaz:
http://arxiv.org/abs/2410.07523