Zobrazeno 1 - 10
of 1 687
pro vyhledávání: '"Yang Yuxin"'
Publikováno v:
Open Life Sciences, Vol 19, Iss 1, Pp e28918-840 (2024)
Studying the effects of maternal iron deficiency anemia (IDA) is complex owing to its diverse causes, each independently impacting the placenta and fetus. Simple treatment with iron supplements does not always resolve the anemia. Therefore, delving i
Externí odkaz:
https://doaj.org/article/33d5eecc6f73489b8b74b0cfab796d39
Autor:
Li Ying, Guo Siren, Li Yudi, Wu Kaiyou, Zhao Linlin, Liu Xi, Yang Xulin, Wang Pan, Yang Yuxin, Sun Yan, Mou Zihao
Publikováno v:
Reviews on Advanced Materials Science, Vol 62, Iss 1, Pp pp. 3-19 (2023)
Helical carbon nanotubes (HCNTs) are chiral materials that can form an induced magnetic field when current passes through them, making them a desirable material for absorbing microwaves. However, poor electrical properties and inert surfaces limit th
Externí odkaz:
https://doaj.org/article/3d2345c8154e4291af26d6c7c17f5796
Autor:
Suryanarayanan, Parthasarathy, Qiu, Yunguang, Sethi, Shreyans, Mahajan, Diwakar, Li, Hongyang, Yang, Yuxin, Eyigoz, Elif, Saenz, Aldo Guzman, Platt, Daniel E., Rumbell, Timothy H., Ng, Kenney, Dey, Sanjoy, Burch, Myson, Kwon, Bum Chul, Meyer, Pablo, Cheng, Feixiong, Hu, Jianying, Morrone, Joseph A.
Foundation models applied to bio-molecular space hold promise to accelerate drug discovery. Molecular representation is key to building such models. Previous works have typically focused on a single representation or view of the molecules. Here, we d
Externí odkaz:
http://arxiv.org/abs/2410.19704
Federated graph learning (FedGL) is an emerging learning paradigm to collaboratively train graph data from various clients. However, during the development and deployment of FedGL models, they are susceptible to illegal copying and model theft. Backd
Externí odkaz:
http://arxiv.org/abs/2410.17533
Autor:
Jin Yingying, Yang Liu, Pan Chenxinyu, Shi Zhangxing, Cui Bowen, Xu Peizhen, Yang Yuxin, Zhou Ning, Guo Xin, Wang Pan, Tong Limin
Publikováno v:
Nanophotonics, Vol 10, Iss 11, Pp 2875-2881 (2021)
By placing a single Au nanoparticle on the surface of a cadmium sulfide (CdS) nanowire, we demonstrate strong coupling of localized surface plasmon resonance (LSPR) modes in the nanoparticle and whispering gallery modes (WGMs) in the nanowire. For a
Externí odkaz:
https://doaj.org/article/d3efc98d8b6b4f97a161bc4a9c480ff6
Autor:
HU Yang, WU Qiuxia, ZHANG Yanwei, QIN Hansheng, PANG Lei, LIANG Jinhu, YANG Yuxin, CHEN Minghu
Publikováno v:
Meikuang Anquan, Vol 52, Iss 5, Pp 66-71 (2021)
In order to be able to “see” the information inside the structure about premixed gas of air and gas deflagration flow field in a underground coal mine, to recognize the coupling relationship between shock wave and flame, obstacles accelerating th
Externí odkaz:
https://doaj.org/article/2d2f9d220706410693753abac27dddec
Federated learning (FL) is an emerging distributed learning paradigm without sharing participating clients' private data. However, existing works show that FL is vulnerable to both Byzantine (security) attacks and data reconstruction (privacy) attack
Externí odkaz:
http://arxiv.org/abs/2407.19703
Federated Learning (FL) is a novel client-server distributed learning framework that can protect data privacy. However, recent works show that FL is vulnerable to poisoning attacks. Many defenses with robust aggregators (AGRs) are proposed to mitigat
Externí odkaz:
http://arxiv.org/abs/2407.15267
Federated graph learning (FedGL) is an emerging federated learning (FL) framework that extends FL to learn graph data from diverse sources. FL for non-graph data has shown to be vulnerable to backdoor attacks, which inject a shared backdoor trigger i
Externí odkaz:
http://arxiv.org/abs/2407.08935
Autor:
Huang, Yiyang, Hao, Yuhui, Yu, Bo, Yan, Feng, Yang, Yuxin, Min, Feng, Han, Yinhe, Ma, Lin, Liu, Shaoshan, Liu, Qiang, Gan, Yiming
Embodied AI robots have the potential to fundamentally improve the way human beings live and manufacture. Continued progress in the burgeoning field of using large language models to control robots depends critically on an efficient computing substra
Externí odkaz:
http://arxiv.org/abs/2407.04292