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您的检索式：作者名="Liangdong Qu"
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| 1 | Dimericbiscognienynes B and C: New diisoprenyl-cyclohexene-type meroterpenoid dimers from Biscogniauxia sp.显示文摘Dimericbiscognienynes B and C(1 and 2), two new diisoprenyl-cyclohexene-type meroterpenoid dimers,were isolated from Biscogniauxia sp. 71-10-1-1. Their structures, including the absolute configurations,were determined by spectroscopic analyses and ECD experiments. Meroterpenoids are special natural products that originate from mixed terpenoid-nonterpenoid pathway. As a member of meroterpenoid family, diisoprenyl-cyclohexene/ane-type meroterpenoids composed of two isoprenyl chains(C5 unit)and a cyclohexene/ane moiety(C6 unit), featuring diverse skeleton structures with wide range of bioactivities. In these reported diisoprenyl-cyclohexene/ane-type meroterpenoids, only three dimers were identified. The discovery of the two new dimers added members of this rare class of meroterpenoids. | Huan Zhao Meizhi Wang Guodong Chen Dan Hu Enqing Li Yibo Qu Libing Zhou Liangdong Guo Xinsheng Yao Hao Gao | 2019 | Chinese Chemical Letters2019，30，1： | 3 |
| 2 | Multi-Hop Routing Optimization Method Based on Improved Ant Algorithm for Vehicle to Roadside Network显示文摘 | Hao Dong Xiaohui Zhao Liangdong Qu Xuefen Chi Xinyu Cui | 2014 | Journal of Bionic Engineering2014，11，3： | 2 |
| 3 | Effective Vietnamese Sentiment Analysis Model Using Sentiment Word Embedding and Transfer Learning显示文摘Sentiment analysis is one of the most popular fields in NLP,and with the development of computer software and hardware,its application is increasingly extensive.Supervised corpus has a positive effect on model training,but these corpus are prohibitively expensive to manually produce.This paper proposes a deep learning sentiment analysis model based on transfer learning.It represents the sentiment and semantics of words and improves the effect of Vietnamese sentiment analysis model by using English corpus.It generated semantic vectors through Word2Vec,an open-source tool,and built sentiment vectors through LSTM with attention mechanism to get sentiment word vector.With the method of sharing parameters,the model was pre-training with English corpus.Finally,the sentiment of the text was classified by stacked Bi-LSTM with attention mechanism,with input of sentiment word vector.Experiments show that the model can effectively improve the performance of Vietnamese sentiment analysis under small language materials. | Yong Huang Siwei Liu Liangdong Qu Yongsheng Li | 2020 | 国际计算机前沿大会会议论文集2020，，2： | 0 |
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