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| 1 | Climate change and human activities: A case study in Xinjiang, China显示文摘 | Wu Zhouting Zhang Hongjun Krause C M | 2010 | Climate Change2010，99，34： | 1 |
| 2 | Editorial显示文摘The paradigm that our universe is dominated by non-luminous matter,i.e.,dark matter,rather than ordinary baryonic matter,has been established since the 1980s.However,the nature of dark matter remains almost unknown.Many ongoing space experiments are aiming at uncovering the particle nature of dark matter via precise measurements of the flux of cosmic-ray particles,with a hope to find fingerprints that tiny annihilations or decays of dark matter may have left.Such | YueLiang Wu RongGen Cai YuFeng Zhout | 2018 | Science China(Physics,Mechanics & Astronomy)2018，61，10： | 0 |
| 3 | Chinese Named Entity Recognition with Character-Level BLSTM and Soft Attention Model显示文摘Unlike named entity recognition(NER)for English,the absence of word boundaries reduces the final accuracy for Chinese NER.To avoid accumulated error introduced by word segmentation,a deep model extracting character-level features is carefully built and becomes a basis for a new Chinese NER method,which is proposed in this paper.This method converts the raw text to a character vector sequence,extracts global text features with a bidirectional long short-term memory and extracts local text features with a soft attention model.A linear chain conditional random field is also used to label all the characters with the help of the global and local text features.Experiments based on the Microsoft Research Asia(MSRA)dataset are designed and implemented.Results show that the proposed method has good performance compared to other methods,which proves that the global and local text features extracted have a positive influence on Chinese NER.For more variety in the test domains,a resume dataset from Sina Finance is also used to prove the effectiveness of the proposed method. | Jize Yin Senlin Luo Zhouting Wu Limin Pan | 2020 | Journal of Beijing Institute of Technology2020，29，1： | 0 |
| 4 | Pan-cancer analysis of RNA 5-methylcytosine reader (ALYREF)显示文摘The incre asing interest in RNA modifications has signifcantly advanced epigenomic and epitranscriptomic technologies.This study focuses on the immuno oncological impact of ALYREF in human cancer through a pan-cancer analysis,enhancing understanding of this gene's role in cancer.We observed differential ALYREF expression between tumor and normal samples,correl ating strongly with prognosis in various cancers,particularly kidney renal papillary cell carcinoma(KIRP)and liver hepatocellular carcinoma(LIHC).ALYREF showed a negative correlation with most tumor-infitrating cells in lung squamous cell carcinoma(LUSC)and lymphoid neoplasm difuse large B-cell lymphoma(DLBC),while positive correlations were noted in IIHC,kidney chromophobe(KICH),mesothelioma(MESO),KIRP,pheochromocytoma and paraganglioma(PARD),and glioma(GBMLGG).Aditionally,ALYREF expression was closely associated with tumor heterogeneity,stemness indices,and a high mutation rate in TP53 across these cancers.In conclusion,ALYREF may serve as an oncogenic biomarker in numerous cancers,meriting further research attention. | XING YE ZHOUTING TUO KAI CHEN RUICHENG WU JIE WANG QINGXIN YU LUXIA YE AKIRA MIYAMOTO KOO HAN YOO CHI ZHANG WURAN WEI DENGXIONG LI DECHAO FENG | 2024 | Oncology Research2024，32，3： | 0 |
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