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112 results on '"Liao, Ziyu"'

2. Structural Design and Stiffness Characteristics of a Passive Variable Stiffness Joint

Author

Liu, Keming, Chen, Bai, Liao, Ziyu, Chang, Tianzuo, Xu, Jiajun, Tu, Zhendong, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yang, Huayong, editor, Liu, Honghai, editor, Zou, Jun, editor, Yin, Zhouping, editor, Liu, Lianqing, editor, Yang, Geng, editor, Ouyang, Xiaoping, editor, and Wang, Zhiyong, editor

Published
2023
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3. A Development Control and HRI of Supernumerary Robotic Limbs Based on ROS

Author

Zheng, Qian, Liao, Ziyu, Chen, Bai, Chang, Tianzuo, Zhang, Zhicong, Wu, Hongtao, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yang, Huayong, editor, Liu, Honghai, editor, Zou, Jun, editor, Yin, Zhouping, editor, Liu, Lianqing, editor, Yang, Geng, editor, Ouyang, Xiaoping, editor, and Wang, Zhiyong, editor

Published
2023
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8. Design of Supernumerary Robotic Limbs and Virtual Test of Human–Machine Interaction Safety

Author

Chang, Tianzuo, Jiang, Surong, Chen, Bai, Liao, Ziyu, Lv, Junnan, Liu, Debin, Ceccarelli, Marco, Series Editor, Agrawal, Sunil K., Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, and Tan, Jianrong, editor

Published
2022
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20. Effective Temporal Graph Learning via Personalized PageRank.

Author

Liao, Ziyu, Liu, Tao, He, Yue, and Lin, Longlong

Subjects
*MATRIX decomposition, *REPRESENTATIONS of graphs, *INDIVIDUALIZED instruction, *CLASSIFICATION algorithms, *MACHINE learning, *NONNEGATIVE matrices, *GRAPH algorithms
Abstract

Graph representation learning aims to map nodes or edges within a graph using low-dimensional vectors, while preserving as much topological information as possible. During past decades, numerous algorithms for graph representation learning have emerged. Among them, proximity matrix representation methods have been shown to exhibit excellent performance in experiments and scale to large graphs with millions of nodes. However, with the rapid development of the Internet, information interactions are happening at the scale of billions every moment. Most methods for similarity matrix factorization still focus on static graphs, leading to incomplete similarity descriptions and low embedding quality. To enhance the embedding quality of temporal graph learning, we propose a temporal graph representation learning model based on the matrix factorization of Time-constrained Personalize PageRank (TPPR) matrices. TPPR, an extension of personalized PageRank (PPR) that incorporates temporal information, better captures node similarities in temporal graphs. Based on this, we use Single Value Decomposition or Nonnegative Matrix Factorization to decompose TPPR matrices to obtain embedding vectors for each node. Through experiments on tasks such as link prediction, node classification, and node clustering across multiple temporal graphs, as well as a comparison with various experimental methods, we find that graph representation learning algorithms based on TPPR matrix factorization achieve overall outstanding scores on multiple temporal datasets, highlighting their effectiveness. [ABSTRACT FROM AUTHOR]

Published
2024
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25. L‐Arginine‐Loaded Gold Nanocages Ameliorate Myocardial Ischemia/Reperfusion Injury by Promoting Nitric Oxide Production and Maintaining Mitochondrial Function

Author

Wang, Zekun, primary, Yang, Nana, additional, Hou, Yajun, additional, Li, Yuqing, additional, Yin, Chenyang, additional, Yang, Endong, additional, Cao, Huanhuan, additional, Hu, Gaofei, additional, Xue, Jing, additional, Yang, Jialei, additional, Liao, Ziyu, additional, Wang, Weiyun, additional, Sun, Dongdong, additional, Fan, Cundong, additional, and Zheng, Lemin, additional

Published
2023
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34. L-Arginine-Loaded Gold Nanocages Mitigates Myocardial Ischemia/Reperfusion Injury by Promoting NO Production and Maintaining Mitochondrial Functions

Author

Wang, Zekun, primary, Yang, Nana, additional, Cao, Huanhuan, additional, Hou, Yajun, additional, Fu, Xiaoting, additional, Hu, Gaofei, additional, Zhu, Pengfei, additional, Li, Yuqing, additional, Yin, Chenyang, additional, Yang, Endong, additional, Liao, Ziyu, additional, Wang, Weiyun, additional, Sun, Dongdong, additional, Fan, Cundong, additional, and Zheng, Lemin, additional

Published
2022
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40. Additional file 1 of Serum creatinine as a biomarker for dystrophinopathy: a cross-sectional and longitudinal study

Author

Wang, Liang, Xu, Min, Liu, Dawei, Liang, Yingyin, Feng, Pinning, Li, Huan, Zhu, Yuling, He, Ruojie, Lin, Jinfu, Zhang, Huili, Liao, Ziyu, and Zhang, Cheng

Abstract

Additional file 1 : Fig. S1. Renal function indexes in participants in the cross-sectional study. Fig. S2. Scatter plots of serum creatinine levels versus motor function scores in patients at different ages. Fig. S3. Scatter plots of serum creatinine levels versus time required for movement in patients at different ages. Fig. S4. Serum urea levels in patients in the longitudinal study.

Published
2021
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48. Inert Coats of Magnetic Nanoparticles Prevent Formation of Occlusive Intravascular Co-aggregates With Neutrophil Extracellular Traps

Author

Bilyy, Rostyslav, Unterweger, Harald, Weigel, Bianca, Dumych, Tetiana, Paryzhak, Solomiya, Vovk, Volodymyr, Liao, Ziyu, Alexiou, Christoph, Herrmann, Martin, and Janko, Christina

Subjects
Male, superparamagnetic iron oxide nanoparticles (SPIONs), Neutrophils, Immunology, neutrophil extracellular traps (NETs), clearance, Extracellular Traps, biocompatibility, vascular occlusion, Coated Materials, Biocompatible, Phagocytosis, Medizinische Fakultät, nanoparticle aggregation, Animals, Humans, Female, Rabbits, Vascular Diseases, ddc:610, Magnetite Nanoparticles, Reactive Oxygen Species, Original Research
Abstract

If foreign particles enter the human body, the immune system offers several mechanisms of response. Neutrophils forming the first line of the immune defense either remove pathogens by phagocytosis, inactivate them by degranulation or release of reactive oxygen species or immobilize them by the release of chromatin decorated with the granular proteins from cytoplasm as neutrophil extracellular traps (NETs). Besides viable microbes like fungi, bacteria or viruses, also several sterile inorganic particles including nanoparticles reportedly activate NET formation. The physicochemical nanoparticle characteristics fostering NET formation are still elusive. Here we show that agglomerations of non-stabilized superparamagnetic iron oxide nanoparticles (SPIONs) induce NET formation by isolated human neutrophils, in whole blood experiments under static and dynamic conditions as well as in vivo. Stabilization of nanoparticles with biocompatible layers of either human serum albumin or dextran reduced agglomeration and NET formation by neutrophils. Importantly, this passivation of the SPIONs prevented vascular occlusions in vivo even when magnetically accumulated. We conclude that higher order structures formed during nanoparticle agglomeration primarily trigger NET formation and the formation of SPION-aggregated NET-co-aggregates, whereas colloid-disperse nanoparticles behave inert and are alternatively cleared by phagocytosis.

Published
2018

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