中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
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地质与地球物理研究... [17]
近代物理研究所 [15]
自动化研究所 [12]
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期刊论文 [128]
会议论文 [13]
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2024 [7]
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Exploring microstructures of metal-doped oxides via simulated Raman spectrum
期刊论文
OAI收割
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2024, 卷号: 320, 页码: 5
作者:
Liu, Le
;
Xu, Yuxing
;
Su, Junchao
;
Wei, Jiangtao
;
Liu, Xingchen
  |  
收藏
  |  
浏览/下载:9/0
  |  
提交时间:2024/07/26
Metal-doped oxide
Global structure searching
Boltzmann distribution
Simulated Raman spectrum
Ce1-xZrxO2
Microstructure
Targeting STING oligomerization with licochalcone D ameliorates STING-driven inflammatory diseases
期刊论文
OAI收割
SCIENCE CHINA-LIFE SCIENCES, 2024, 页码: 14
作者:
Zhang, Yinghui
;
Liu, Yadan
;
Jiang, Bing
;
Chen, Lifan
;
Hu, Jie
  |  
收藏
  |  
浏览/下载:18/0
  |  
提交时间:2024/10/21
cGAS-STING signaling
STING inhibitor
TransformerCPI model
Licochalcone D
inflammatory diseases
Pollutant accumulation characteristics of substrates and mechanism of microbial action in different ecological ditches
期刊论文
OAI收割
ENVIRONMENTAL TECHNOLOGY, 2024, 页码: 17
作者:
Wang, Huiteng
;
Luo, Hui
;
Yang, Jing
;
Qin, Teng
;
Yang, Mingyu
  |  
收藏
  |  
浏览/下载:1/0
  |  
提交时间:2024/09/02
Cumulative characterisation
ecological ditches
potentially toxic elements
risk assessment
microbial communities
Removal effect of pollutants from stormwater runoff in shallow bioretention system with gramineous plants
期刊论文
OAI收割
WATER SCIENCE AND TECHNOLOGY, 2024, 页码: 15
作者:
Yang, Jing
;
Luo, Hui
;
Wang, Huiteng
;
Qin, Teng
;
Yang, Mingyu
  |  
收藏
  |  
浏览/下载:13/0
  |  
提交时间:2024/06/04
bioretention system
gramineous plants
plant optimization
pollutant removal
purification capacity
stormwater runoff
Operational effect of green roof systems with a modified substrate-adding soda residue soil
期刊论文
OAI收割
WATER SUPPLY, 2024, 页码: 11
作者:
Wang, Huiteng
;
Luo, Hui
;
Yang, Jing
;
Qin, Teng
;
Chen, Limin
  |  
收藏
  |  
浏览/下载:18/0
  |  
提交时间:2024/06/04
green roof
runoff quality index (RQI)
soda residue soil
stormwater runoff
substrate layer
Comprehensive review of modified clay minerals for phosphate management and future prospects
期刊论文
OAI收割
JOURNAL OF CLEANER PRODUCTION, 2024, 卷号: 447, 页码: 22
作者:
Bao, Teng
;
Damtie, Mekdimu Mezemir
;
Wang, Chu Yan
;
Chen, Zhijie
;
Tao, Qi
  |  
收藏
  |  
浏览/下载:9/0
  |  
提交时间:2024/09/12
Modified clay minerals
Removing/recovering phosphate
Adsorption mechanism
Agricultural applications
Phosphate management
Characterization and microbial mechanism of pollutant removal from stormwater runoff in the composite filler bioretention system
期刊论文
OAI收割
WATER REUSE, 2024, 页码: 20
作者:
Guo, Kaiwen
;
Wang, Hairuo
;
Mu, Teng
  |  
收藏
  |  
浏览/下载:21/0
  |  
提交时间:2024/04/07
biochar
biological filler
bioretention
matrix adsorption
microbial community
stormwater runoff
Comparative analysis of PacBio and ONT RNA sequencing methods for
Nemopilema
Nomurai
venom identification
期刊论文
OAI收割
GENOMICS, 2023, 卷号: 115, 期号: 6, 页码: 13
作者:
Ma, Yuzhen
;
Li, Jie
;
Yu, Huahua
;
Teng, Lichao
;
Geng, Hao
  |  
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2023/11/30
Nemopilema nomurai
Pacific biosciences
Oxford Nanopore Technologies
Venom
Jellyfish dermatitis
A molecular probe carrying anti-tropomyosin 4 for early diagnosis of cerebral ischemia/reperfusion injury
期刊论文
OAI收割
NEURAL REGENERATION RESEARCH, 2023, 卷号: 18, 期号: 6, 页码: 1321-1324
作者:
Yu, Teng-Fei
;
Wang, Kun
;
Yin, Lu
;
Li, Wen-Zhe
;
Li, Chuan-Ping
  |  
收藏
  |  
浏览/下载:26/0
  |  
提交时间:2023/02/22
cerebral ischemia/reperfusion injury
diagnosis
dynamic monitoring
ischemic stroke
middle cerebral artery occlusion
molecular probe
nanoshells
photoacoustic imaging
tropomyosin 4
ultrasound
Deep learning with biopsy whole slide images for pretreatment prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer : A multicenter study
期刊论文
OAI收割
BREAST, 2022, 卷号: 66, 页码: 183-190
作者:
Li, Bao
;
Li, Fengling
;
Liu, Zhenyu
;
Xu, FangPing
;
Ye, Guolin
  |  
收藏
  |  
浏览/下载:50/0
  |  
提交时间:2022/12/27
Breast cancer
Neoadjuvant chemotherapy
Pathological complete response
Whole-slide image
Deep learning