机构

• 近代物理研究所 [26]
• 国家天文台 [20]
• 化学研究所 [11]
• 武汉物理与数学研究... [11]
• 合肥物质科学研究院 [11]
• 高能物理研究所 [10]
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采集方式

• OAI收割 [213]
• iSwitch采集 [9]

内容类型

• 期刊论文 [217]
• 会议论文 [4]
• 预印本 [1]

发表日期

• 2025 [1]
• 2024 [5]
• 2023 [12]
• 2022 [16]
• 2021 [17]
• 2020 [14]
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学科主题

• Physics [5]
• 天文学 [5]
• 生物科学::植物学 [4]
• Astronomy ... [3]
• Environmen... [2]
• Evolutiona... [2]
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筛选

浏览/检索结果: 共222条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Terrestrial ecosystem response to Early Cretaceous global environmental change: A calibrated, high-resolution Aptian record from Northeast China 期刊论文  OAI收割 EARTH AND PLANETARY SCIENCE LETTERS, 2025, 卷号: 653, 页码: 13 作者:  Sun, Ming-Dao;  Lin, Qin;  Ramezani, Jahandar;  Liu, Jiang-Si;  Lu, Zheng-An   |  收藏  |  浏览/下载：14/0  |  提交时间：2025/04/03 Early Cretaceous  Aptian  CA-ID-TIMS geochronology  Astrochronology  Carbon isotope stratigraphy   π-HuB: the proteomic navigator of the human body 期刊论文  OAI收割 NATURE, 2024, 卷号: 636, 期号: 8042, 页码: 322-331 作者:  He, Fuchu;  Aebersold, Ruedi;  Baker, Mark S.;  Bian, Xiuwu;  Bo, Xiaochen   |  收藏  |  浏览/下载：12/0  |  提交时间：2025/04/01 Soil spatial heterogeneity created by river-sea interaction influences Tamarix chinensis root features in the Yellow River Delta 期刊论文  OAI收割 EARTH SURFACE PROCESSES AND LANDFORMS, 2024, 页码: 10 作者:  Shi, Libin;  Suo, Lizhu;  Wang, Yi;  Zhao, Ying;  Chen, Xiaobing   |  收藏  |  浏览/下载：11/0  |  提交时间：2024/10/24 geographical locations  pathway analysis  soil-water-salt conditions  Tamarix chinensis  the Yellow River Delta   Sevoflurane acts as an antidepressant by suppression of GluN2D-containing NMDA receptors on interneurons 期刊论文  OAI收割 BRITISH JOURNAL OF PHARMACOLOGY, 2024, 页码: 20 作者:  Guo, Fei;  Zhang, Bing;  Shen, Fuyi;  Li, Qian;  Song, Yingcai   |  收藏  |  浏览/下载：27/0  |  提交时间：2024/06/27 antidepressant  disinhibition  GluN2D subunits  interneurons  sevoflurane   Biomimetic nano-chelate diethyldithiocarbamate Cu/Fe for enhanced metalloimmunity and ferroptosis activation in glioma therapy 期刊论文  OAI收割 JOURNAL OF CONTROLLED RELEASE, 2024, 卷号: 368, 页码: 84-96 作者:  Wang, Rui;  Song, Wenqin;  Zhu, Jie;  Shao, Xinyue;  Yang, Chenxiao   |  收藏  |  浏览/下载：13/0  |  提交时间：2024/05/22 Anti-glioma  Diethyldithiocarbamate Cu/Fe  Immunogenic cell death  Ferroptosis  Metalloimmunology  Albumin  Lactoferrin  Brain-targeted delivery   Altered global signal topography in Alzheimer's disease 期刊论文  OAI收割 eBioMedicine, 2024, 页码: 104455 作者:  Chen, Pindong;  Zhao, Kun;  Zhang, Han;  Wei, Yongbin;  Wang, Pan   |  收藏  |  浏览/下载：19/0  |  提交时间：2024/05/29 Ecosystem responses dominate the trends of annual gross primary productivity over terrestrial ecosystems of China during 2000-2020 期刊论文  OAI收割 AGRICULTURAL AND FOREST METEOROLOGY, 2023, 卷号: 343, 页码: 109758 作者:  Zhu, Xian-Jin;  Yu, Gui-Rui;  Chen, Zhi;  Zhang, Wei-Kang;  Han, Lang   |  收藏  |  浏览/下载：30/0  |  提交时间：2023/12/04 Carbon cycles  Eddy covariance  Terrestrial ecosystems  Machine learning  Ecosystem responses   Ni3Fe@N-doped carbon nanotubes 3D network induced by nanoconfined symmetry breaking for high-performance microwave absorption, corrosion protection, and pollutant purification 期刊论文  OAI收割 CARBON, 2023, 卷号: 213, 页码: 14 作者:  Li, Shuaizhen;  Xie, Tianwen;  Ma, Lin;  Lei, Zixuan;  Huang, Nan   |  收藏  |  浏览/下载：17/0  |  提交时间：2024/01/08 Ni3Fe catalyst  Nanoconfined symmetry breaking  Microwave absorption  Corrosion protection  Adsorption purification   A Spectral-timing Study of the Inner Flow Geometry in MAXI J1535-571 with Insight-HXMT and NICER 期刊论文  OAI收割 ASTROPHYSICAL JOURNAL, 2023, 卷号: 953, 期号: 2, 页码: 12 作者:  Yu, Wei;  Bu, Qing-Cui;  Liu, He-Xin;  Huang, Yue;  Zhang, Liang   |  收藏  |  浏览/下载：27/0  |  提交时间：2023/11/14 From shallow sea to deep sea: research progress in underwater image restoration 期刊论文  OAI收割 FRONTIERS IN MARINE SCIENCE, 2023, 卷号: 10, 页码: 24 作者:  Song, Wei;  Liu, Yaling;  Huang, Dongmei;  Zhang, Bing;  Shen, Zhihao   |  收藏  |  浏览/下载：16/0  |  提交时间：2023/10/07 shallow-sea image restoration  deep-sea image restoration  image formation  physical model  prior  deep learning