Zobrazeno 1 - 10
of 167
pro vyhledávání: '"Sha Long"'
Autor:
Lin-Jing Gou, Tian-Tian Liu, Qi Zeng, Wan-Rong Dong, Lu Wang, Sha Long, Jiang-Tao Su, Yu-Xin Chen, Gao Zhou
Publikováno v:
Molecules, Vol 28, Iss 9, p 3707 (2023)
This research aimed to investigate natamycin’s antifungal effect and its mechanism against the chestnut pathogen Neofusicoccum parvum. Natamycin’s inhibitory effects on N. parvum were investigated using a drug-containing plate culture method and
Externí odkaz:
https://doaj.org/article/01594fb30fd9476488cfb4db624c3da5
Publikováno v:
Horticulturae, Vol 8, Iss 4, p 279 (2022)
Red paddy soil is widely distributed in the south of China and has become an important production system for food and cash crops. However, the key factors limiting the quality of this soil type under the plastic shed cultivation system and the effect
Externí odkaz:
https://doaj.org/article/c6dc3e673bf2490c8b3f89048a409318
Publikováno v:
Molecules, Vol 18, Iss 10, Pp 12264-12289 (2013)
The review reports a short biography of the Italian naturalized chemist Hugo Schiff and an outline on the synthesis and use of his most popular discovery: the imines, very well known and popular as Schiff Bases. Recent developments on their “metall
Externí odkaz:
https://doaj.org/article/1e8971f9474247418fabe4da3a4003c9
Knowledge graph (KG) representation learning aims to encode entities and relations into dense continuous vector spaces such that knowledge contained in a dataset could be consistently represented. Dense embeddings trained from KG datasets benefit a v
Externí odkaz:
http://arxiv.org/abs/2204.07328
This paper presents a new end-to-end semi-supervised framework to learn a dense keypoint detector using unlabeled multiview images. A key challenge lies in finding the exact correspondences between the dense keypoints in multiple views since the inve
Externí odkaz:
http://arxiv.org/abs/2109.09299
Autor:
Luo, Kun1,2 (AUTHOR) 2021601022035@stu.zafu.edu.cn, Sha, Long1 (AUTHOR) 15188358315@163.com, Li, Tengyu1,2 (AUTHOR) tengyuli18@163.com, Wang, Chenlei1 (AUTHOR) wangchenlei18@163.com, Zhao, Xuan2 (AUTHOR), Pan, Jingwen1 (AUTHOR) 13849259577@163.com, Zhu, Shouhong1 (AUTHOR) zhushouhong@caas.cn, Li, Yan1 (AUTHOR) liyan06@caas.cn, Chen, Wei1 (AUTHOR) chenwei01@caas.cn, Yao, Jinbo1 (AUTHOR) yaojinbo@caas.cn, Rong, Junkang2 (AUTHOR) junkangrong@126.com, Zhang, Yongshan1 (AUTHOR) junkangrong@126.com
Publikováno v:
International Journal of Molecular Sciences. Apr2024, Vol. 25 Issue 8, p4349. 18p.
While nowadays most gradient-based optimization methods focus on exploring the high-dimensional geometric features, the random error accumulated in a stochastic version of any algorithm implementation has not been stressed yet. In this work, we propo
Externí odkaz:
http://arxiv.org/abs/2008.05969
In this work, we developed a deep learning model-based approach to forecast the spreading trend of SARS-CoV-2 in the United States. We implemented the designed model using the United States to confirm cases and state demographic data and achieved pro
Externí odkaz:
http://arxiv.org/abs/2008.05644
We demonstrated the existence of a group algebraic structure hidden in relational knowledge embedding problems, which suggests that a group-based embedding framework is essential for designing embedding models. Our theoretical analysis explores merel
Externí odkaz:
http://arxiv.org/abs/2005.10956
Central to all machine learning algorithms is data representation. For multi-agent systems, selecting a representation which adequately captures the interactions among agents is challenging due to the latent group structure which tends to vary depend
Externí odkaz:
http://arxiv.org/abs/1912.13107