中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页
机构
成果
学者
登录
注册
登陆
×
验证码:
换一张
忘记密码?
记住我
×
校外用户登录
CAS IR Grid
机构
大连化学物理研究所 [15]
昆明植物研究所 [12]
上海药物研究所 [11]
地理科学与资源研究所 [7]
动物研究所 [6]
植物研究所 [6]
更多
采集方式
OAI收割 [101]
内容类型
期刊论文 [101]
发表日期
2026 [1]
2025 [1]
2024 [7]
2023 [9]
2022 [11]
2021 [10]
更多
学科主题
Biochemist... [5]
天文学 [4]
Plant Scie... [3]
Chemistry [2]
Chemistry,... [2]
Environmen... [2]
更多
筛选
浏览/检索结果:
共101条,第1-10条
帮助
条数/页:
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
排序方式:
请选择
作者升序
作者降序
发表日期升序
发表日期降序
题名升序
题名降序
提交时间升序
提交时间降序
Introduction to the Chinese Space Station Survey Telescope (CSST)
期刊论文
OAI收割
SCIENCE CHINA-PHYSICS MECHANICS & ASTRONOMY, 2026, 卷号: 69, 期号: 3
作者:
Gong, Yan
;
Miao, Haitao
;
Zhan, Hu
;
Li, Zhao-Yu
;
Shangguan, Jinyi
  |  
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2026/02/05
telescope
cosmology
galaxy
Ultrahigh-energy gamma-ray emission associated with black hole-jet systems
期刊论文
OAI收割
NATIONAL SCIENCE REVIEW, 2025, 卷号: 12, 期号: 12
作者:
Cao, Zhen
;
Aharonian, Felix
;
Bai, Yun-Xiang
;
Bao, Yi-Wei
;
Bastieri, Denis
  |  
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2026/01/12
gamma ray
nonthermal radiation
cosmic ray
microquasar
Emerging Pollutants
期刊论文
OAI收割
PROGRESS IN CHEMISTRY, 2024, 卷号: 36, 期号: 11, 页码: 1607-1784
作者:
Wang, Yawei
;
Zhang, Qiurui
;
Yu, Nanyang
;
Wang, Yuan
;
Wei, Si
  |  
收藏
  |  
浏览/下载:105/0
  |  
提交时间:2025/04/03
emerging pollutants
occurrence level
environmental behavior
ecological risks
control strategies
EGCG-enabled Deep Tumor Penetration of Phosphatase and Acidity Dual-responsive Nanotherapeutics for Combinatory Therapy of Breast Cancer
期刊论文
OAI收割
SMALL, 2024, 页码: 20
作者:
Zhou, Mengxue
;
Zhou, Chuang
;
Geng, Huan
;
Huang, Zhiwei
;
Lin, Zhiyuan
  |  
收藏
  |  
浏览/下载:66/0
  |  
提交时间:2024/12/16
chemo/chemodynamic therapy
EGCG
nanomedicine
TGF-beta signaling
triple-negative breast cancer
Chemical constituents from the twigs with leaves of
Tetradium trichotomum
期刊论文
OAI收割
JOURNAL OF ASIAN NATURAL PRODUCTS RESEARCH, 2024, 页码: 7
作者:
Chen, Hong-Lian
;
Yao, Jia-Ying
;
Gao, Ming-Hui
;
Tan, Jun-Jie
;
Qu, Shi-Jin
  |  
收藏
  |  
浏览/下载:51/0
  |  
提交时间:2024/08/22
Rutaceae
Tetradium trichotomum
limonoids
amide alkaloids
immunosuppressant
lymphocytes
CSST large-scale structure analysis pipeline: I. Constructing reference mock galaxy redshift surveys (vol 529, pg 4015, 2024)
期刊论文
OAI收割
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 2024, 卷号: 531, 期号: 1, 页码: 1243-1243
作者:
Gu, Yizhou
;
Yang, Xiaohu
;
Han, Jiaxin
;
Wang, Yirong
;
Li, Qingyang
  |  
收藏
  |  
浏览/下载:64/0
  |  
提交时间:2024/06/11
CSST large-scale structure analysis pipeline: I. Constructing reference mock galaxy redshift surveys
期刊论文
OAI收割
Monthly Notices of the Royal Astronomical Society, 2024, 卷号: 529, 期号: 4, 页码: 4015-4027
作者:
Gu, Yizhou
;
Yang, Xiaohu
;
Han, Jiaxin
;
Wang, Yirong
;
Li, Qingyang
  |  
收藏
  |  
浏览/下载:69/0
  |  
提交时间:2024/05/13
methods: statistical
galaxies: haloes
dark matte
large
scale structure of Universe
Structure-based development of potent and selective type-II kinase inhibitors of RIPK1
期刊论文
OAI收割
ACTA PHARMACEUTICA SINICA B, 2024, 卷号: 14, 期号: 1, 页码: 319-334
作者:
Qin, Ying
;
Li, Dekang
;
Qi, Chunting
;
Xiang, Huaijiang
;
Meng, Huyan
  |  
收藏
  |  
浏览/下载:70/0
  |  
提交时间:2024/03/06
RIPK1
Necroptosis
Type-II kinase inhibitors
Rational design
Lead optimization
Structure-activity relationship
Anti-inflammation
Preclinical drug discovery
Limonoids and alkaloids from
Tetradium
austrosinense
(Hand.-Mazz.) TG Hartley
期刊论文
OAI收割
FITOTERAPIA, 2024, 卷号: 172, 页码: 5
作者:
Han, Feng
;
Yao, Jia-Ying
;
Tan, Jun-Jie
;
Qin, Nan
;
Jiang, Yu-Xia
  |  
收藏
  |  
浏览/下载:75/0
  |  
提交时间:2024/02/19
Rutaceae
Tetradium austrosinense
Limonoids
Alkaloids
TDDFT-ECD calculation
Anti-inflammation
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:89/0
  |  
提交时间:2023/12/04
Carbon cycles
Eddy covariance
Terrestrial ecosystems
Machine learning
Ecosystem responses