UM

Browse/Search Results:  1-10 of 271 Help

Selected(0)Clear Items/Page:    Sort:
Deep learning-driven evaluation and prediction of ion-doped NASICON materials for enhanced solid-state battery performance Journal article
Zhao, Zirui, Wang, Xiaoke, Wu, Si, Zhou, Pengfei, Zhao, Qian, Xu, Guanping, Sun, Kaitong, Li, Hai Feng. Deep learning-driven evaluation and prediction of ion-doped NASICON materials for enhanced solid-state battery performance[J]. AAPPS Bulletin, 2024, 34(1), 26.
Authors:  Zhao, Zirui;  Wang, Xiaoke;  Wu, Si;  Zhou, Pengfei;  Zhao, Qian; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date:2024/10/10
Deep Learning Model  Electrochemical Properties  Ion Doping  Nasicon  Solid-state Electrolyte  
Current status of support for Automated External Defibrillators (AEDs) in public places and factors influencing their use in China: a cross-sectional study Journal article
Zhou,Zi yun, Zhang,Jin zi, Zhao,Xian qi, Niu,Yu yao, Zhang,Jing bo, Feng,Bojunhao, Ge,Pu, Liu,Xin yi, Zhou,Le Shan, Wu,Yi bo. Current status of support for Automated External Defibrillators (AEDs) in public places and factors influencing their use in China: a cross-sectional study[J]. JOURNAL OF PUBLIC HEALTH-HEIDELBERG, 2024, 32(11), 2105-2120.
Authors:  Zhou,Zi yun;  Zhang,Jin zi;  Zhao,Xian qi;  Niu,Yu yao;  Zhang,Jing bo; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:1.9/1.7 | Submit date:2023/08/03
Automated External Defibrillator  Public  Social Support  Family Health  Health Literacy  
Apoptosis-Sensitizing Tumor Nanomedicine by Regulating Pyroptosis-Associated Inflammatory Cell Death Review article
2024
Authors:  Du, Fangxue;  Zhao, Hongxin;  Song, Yangmeihui;  Feng, Ziyan;  Liu, Kai; et al.
Favorite | TC[WOS]:0 TC[Scopus]:1  IF:18.5/19.6 | Submit date:2024/09/03
Immune Therapy  Inflammatory Cell Death  Pyroptosis  Regulated Cell Death  Tumor Nanomedicine  
Selective multiple kernel fuzzy clustering with locality preserved ensemble Journal article
Zhang, Chuanbin, Chen, Long, Yu, Yu Feng, Zhao, Yin Ping, Shi, Zhaoyin, Wang, Yingxu, Bai, Weihua. Selective multiple kernel fuzzy clustering with locality preserved ensemble[J]. Knowledge-Based Systems, 2024, 301, 112327.
Authors:  Zhang, Chuanbin;  Chen, Long;  Yu, Yu Feng;  Zhao, Yin Ping;  Shi, Zhaoyin; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:7.2/7.4 | Submit date:2024/09/03
Clustering Ensemble  Feature Fusion  Graph  Multi-objective Optimization  Multiple Kernel Fuzzy Clustering  
Shining light on atomic vacancies in electrocatalysts for boosted water splitting Review article
2024
Authors:  Chen, Mingpeng;  Sun, Huachuan;  Lu, Qingjie;  Li, Dequan;  Liu, Di; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:13.3/13.2 | Submit date:2024/09/03
Atomic Vacancy  Characterization Technique  Electrocatalytic Water Splitting  Mechanistic Understanding  Synthetic Method  
Association between alcohol consumption and incidence of dementia in current drinkers: linear and non-linear mendelian randomization analysis Journal article
Zheng, Lingling, Liao, Weiyao, Luo, Shan, Li, Bingyu, Liu, Di, Yun, Qingping, Zhao, Ziyi, Zhao, Jia, Rong, Jianhui, Gong, Zhiguo, Sha, Feng, Tang, Jinling. Association between alcohol consumption and incidence of dementia in current drinkers: linear and non-linear mendelian randomization analysis[J]. eClinicalMedicine, 2024, 76, 102810.
Authors:  Zheng, Lingling;  Liao, Weiyao;  Luo, Shan;  Li, Bingyu;  Liu, Di; et al.
Favorite | TC[WOS]:0 TC[Scopus]:1 | Submit date:2024/10/10
Alcohol Consumption  Dementia  Mendelian Randomization  
NTIRE 2024 Restore Any Image Model (RAIM) in the Wild Challenge Conference paper
Liang, Jie, Yi, Qiaosi, Liu, Shuaizheng, Sun, Lingchen, Zhang, Xindong, Zeng, Hui, Zhang, Lei, Timofte, Radu, Huang, Yibin, Liu, Shuai, Li, Yongqiang, Feng, Chaoyu, Wang, Xiaotao, Lei, Lei, Chen, Yuxiang, Chen, Xiangyu, Chen, Qiubo, Chen, Jiaxu, Sun, Fengyu, Cui, Mengying, Hu, Zhenyu, Liu, Jingyun, Ma, Wenzhuo, Wang, Ce, Zheng, Hanyou, Sun, Wanjie, Chen, Zhenzhong, Luo, Ziwei, Gustafsson, Fredrik K., Zhao, Zheng, Sjölund, Jens, Schön, Thomas B., Dun, Xiong, Ji, Pengzhou, Xing, Yujie, Wang, Xuquan, Wang, Zhanshan, Cheng, Xinbin, Xiao, Jun, He, Chenhang, Wang, Xiuyuan, Liu, Zhi Song, Miao, Zimeng, Yin, Zhicun, Liu, Ming, Zuo, Wangmeng, Wu, Rongyuan, Li, Shuai. NTIRE 2024 Restore Any Image Model (RAIM) in the Wild Challenge[C]:IEEE Computer Society, 2024, 6632-6640.
Authors:  Liang, Jie;  Yi, Qiaosi;  Liu, Shuaizheng;  Sun, Lingchen;  Zhang, Xindong; et al.
Favorite | TC[Scopus]:16 | Submit date:2024/11/05
Degradation  Computer Vision  Reviews  Conferences  Computational Modeling  Benchmark Testing  Image Restoration  
Investigating Material Interface Diffusion Phenomena through Graph Neural Networks in Applied Materials Journal article
Zhao, Zirui, Li, Hai Feng. Investigating Material Interface Diffusion Phenomena through Graph Neural Networks in Applied Materials[J]. ACS Applied Materials & Interfaces, 2024, 16(39), 53153-53162.
Authors:  Zhao, Zirui;  Li, Hai Feng
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:8.3/8.7 | Submit date:2024/10/10
Graph Neural Networks (Gnns)  Interface Diffusion  Material Properties Prediction  Atomic Structure Modeling  Semiconductor Interfaces  
Predicting doping strategies for ternary nickel–cobalt–manganese cathode materials to enhance battery performance using graph neural networks Journal article
Zhao, Zirui, Luo, Dong, Wu, Shuxing, Sun, Kaitong, Lin, Zhan, Li, Hai Feng. Predicting doping strategies for ternary nickel–cobalt–manganese cathode materials to enhance battery performance using graph neural networks[J]. Journal of Energy Storage, 2024, 98, 112982.
Authors:  Zhao, Zirui;  Luo, Dong;  Wu, Shuxing;  Sun, Kaitong;  Lin, Zhan; et al.
Favorite | TC[WOS]:2 TC[Scopus]:2  IF:8.9/9.0 | Submit date:2024/08/05
Doping Strategies  Electrochemical Performance  Graph Neural Networks  Lithium-ion Batteries  Ternary Nickel–cobalt–manganese Cathode Materials  
Environment Sensing-aided Beam Prediction with Transfer Learning for Smart Factory Conference paper
Zhao, Chuanbing, Feng, Yuan, Gao, Feifei, Zhang, Yong, Ma, Shaodan, Poor, H. Vincent. Environment Sensing-aided Beam Prediction with Transfer Learning for Smart Factory[C]:Institute of Electrical and Electronics Engineers Inc., 2024, 2077-2082.
Authors:  Zhao, Chuanbing;  Feng, Yuan;  Gao, Feifei;  Zhang, Yong;  Ma, Shaodan; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date:2024/11/05
Beam Prediction  Environment Sensing  Mmwave  Transfer Learning  Adaptation Models  Costs  Accuracy  Simulation  Training Data  Predictive Models