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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地理科学与资源研究... [41]
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期刊论文 [114]
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Ocean as source or sink for legacy persistent organic pollutants
期刊论文
OAI收割
JOURNAL OF HAZARDOUS MATERIALS, 2025, 卷号: 486, 页码: 136987
作者:
Chen, Chuchu
;
Yang, Fen
;
Wu, Qiang
;
Yu, Jun
;
Xie, Jingqian
  |  
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2025/03/18
Legacy persistent organic pollutants
Source-sink transformation
Sea-air fluxes
Boosted regression tree model
Sustainable futures for transformational forestry resource-based city: Linking landscape pattern and administrative policy
期刊论文
OAI收割
JOURNAL OF CLEANER PRODUCTION, 2025, 卷号: 496, 页码: 145087
作者:
Xu, Linlin
;
Yu, Hu
;
Zhong, Linsheng
  |  
收藏
  |  
浏览/下载:7/0
  |  
提交时间:2025/04/21
City transformation
Landscape ecology
Administrative division adjustment
PLUS model
Multi-scenario
Inertia effect of deformation in amorphous solids: A dynamic mesoscale model
期刊论文
OAI收割
JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS, 2024, 卷号: 193, 页码: 105917
作者:
Duan XM(段鑫淼)
;
Yu L(喻立)
;
Cai SL(蔡松林)
;
Dai LH(戴兰宏)
;
Jiang MQ(蒋敏强)
  |  
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2024/12/02
Amorphous solids
Dynamic deformation
Inertia effect
Shear transformation
Mesoscale model
Evaluation of tumor budding with virtual panCK stains generated by novel multi-model CNN framework
期刊论文
OAI收割
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2024, 卷号: 257, 页码: 18
作者:
Hou, Xingzhong
;
Guan, Zhen
;
Zhang, Xianwei
;
Hu, Xiao
;
Zou, Shuangmei
  |  
收藏
  |  
浏览/下载:9/0
  |  
提交时间:2024/12/06
Virtual Stain
Stain-to-stain transformation
Multi-model framework
Explainable AI
Tumor budding
Investigating the effects of industrial transformation and agglomeration on industrial eco-efficiency for green development: Evidence from enterprises in the Yangtze River Economic Belt
期刊论文
OAI收割
JOURNAL OF CLEANER PRODUCTION, 2024, 卷号: 479, 页码: 143949
作者:
Lu, Peng
;
Li, Zhihui
;
Wu, Haowei
  |  
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2024/12/20
Industrial eco-efficiency
Factory scatter index
Industrial structure upgrading and agglomeration
Industrial transformation
Super SBM-ML model
Similarity criterion for the nonlinear thermal analysis of the soil freezing process: considering the dual effect of nonlinear thermal parameters and boundary conditions
期刊论文
OAI收割
ACTA GEOTECHNICA, 2022, 卷号: 17, 期号: 12, 页码: 5709
作者:
Chen, Zhixiang
;
Feng, Yanfang
;
Zhang, Xuncheng
;
Guo, Xiaoxia
;
Shao, Longtan
  |  
收藏
  |  
浏览/下载:16/0
  |  
提交时间:2023/08/02
Frozen soil
Heat equation
Model test
Similar transformation method
Similarity criterion
Controller design and stability analysis for spinning missiles via tensor product
期刊论文
OAI收割
AEROSPACE SCIENCE AND TECHNOLOGY, 2022, 卷号: 130, 页码: 9
作者:
Zhou, Zhiming
;
Liu, Zhen
;
Pan, Yi
;
Yi, Jianqiang
  |  
收藏
  |  
浏览/下载:36/0
  |  
提交时间:2022/11/14
Spinning missile
Tensor product model transformation
Parallel distributed compensation
Model filtering
Stability analysis
Proportional allocation with soil depth improved mapping soil organic carbon stocks
期刊论文
OAI收割
SOIL & TILLAGE RESEARCH, 2022, 卷号: 224, 页码: 14
作者:
Zhang, Mo
;
Shi, Wenjiao
;
Ren, Yongxing
;
Wang, Zongming
;
Ge, Yong
  |  
收藏
  |  
浏览/下载:47/0
  |  
提交时间:2022/11/09
Soil organic carbon density
Equal-area spline function
Log -ratio transformation
Random forest
Generalized linear model
Proportional allocation
Proportional allocation with soil depth improved mapping soil organic carbon stocks
期刊论文
OAI收割
SOIL & TILLAGE RESEARCH, 2022, 卷号: 224, 页码: 14
作者:
Zhang, Mo
;
Shi, Wenjiao
;
Ren, Yongxing
;
Wang, Zongming
;
Ge, Yong
  |  
收藏
  |  
浏览/下载:21/0
  |  
提交时间:2022/11/09
Soil organic carbon density
Equal-area spline function
Log -ratio transformation
Random forest
Generalized linear model
Proportional allocation
Denoising of scanning electron microscope images for biological ultrastructure enhancement
期刊论文
OAI收割
JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, 2022, 卷号: 20, 期号: 03, 页码: 21
作者:
Chang, Sheng
;
Shen, Lijun
;
Li, Linlin
;
Chen, Xi
;
Han, Hua
  |  
收藏
  |  
浏览/下载:65/0
  |  
提交时间:2022/09/19
SEM
noise model
denoising
variance stabilization transformation
two-stage multi-loss
deep learning