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pro vyhledávání: '"Lee , Sung"'
Autor:
Wannhsin Chen, Chun-Hsiang Hou, Yi-Ling Chen, Hsin-Hsin Shen, Chen-Hsuan Lin, Cheng-Yi Wu, Meng-Hsueh Lin, Chih-Ching Liao, Jun-Jae Huang, Chi-Yu Yang, Yi-Chen Li, Hon-Kan Yip
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 10 (2023)
BackgroundThis study tested whether early left intracoronary arterial (LAD) administration of human bone marrow-derived mesenchymal stem cells (hBMMSCs, called OmniMSCs) in acute ST-segment elevation myocardial infarction (STEMI) of Lee-Sung pigs ind
Externí odkaz:
https://doaj.org/article/5a8d30f3d7e14f46b81fd19de251e277
Akademický článek
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Autor:
Cheong, Dhong Yeon, Hamaguchi, Koichi, Kanazawa, Yoshiki, Lee, Sung Mook, Nagata, Natsumi, Park, Seong Chan
Non-perturbative gravitational effects induce explicit global symmetry breaking terms within axion models. These exponentially suppressed terms in the potential give a mass contribution to the axion-like particles (ALPs). In this work we investigate
Externí odkaz:
http://arxiv.org/abs/2411.07713
Autor:
Park, Eunyoung, Kim, Sinwoo, Wang, Melody M., Hwang, Junha, Lee, Sung Yun, Shin, Jaeyong, Heo, Seung-Phil, Choi, Jungchan, Lee, Heemin, Jang, Dogeun, Kim, Minseok, Kim, Kyung Sook, Kim, Sangsoo, Eom, Intae, Nam, Daewoong, Gu, X. Wendy, Song, Changyong
Metallic glass is a frozen liquid with structural disorder that retains degenerate free energy without spontaneous symmetry breaking to become a solid. For over half a century, this puzzling structure has raised fundamental questions about how struct
Externí odkaz:
http://arxiv.org/abs/2411.02691
Federated Learning (FL) is a distributed machine learning framework that trains accurate global models while preserving clients' privacy-sensitive data. However, most FL approaches assume that clients possess labeled data, which is often not the case
Externí odkaz:
http://arxiv.org/abs/2410.23227
Autor:
Choi, Ryuhaerang, Chatterjee, Soumyajit, Spathis, Dimitris, Lee, Sung-Ju, Kawsar, Fahim, Malekzadeh, Mohammad
Developing new machine learning applications often requires the collection of new datasets. However, existing datasets may already contain relevant information to train models for new purposes. We propose SoundCollage: a framework to discover new cla
Externí odkaz:
http://arxiv.org/abs/2410.23008
Autor:
Lee, Sung-Hoon, Hong, Ki-Ha
In crystalline materials, atomic motion is generally confined to vibrations within a fixed lattice, with significant movement beyond vibrations usually associated with defect migration. Here, we present the discovery of collective ionic transport wit
Externí odkaz:
http://arxiv.org/abs/2410.22017
Autor:
Lee, Sung-Wook, Kuo, Yen-Ling
Recently, diffusion policy has shown impressive results in handling multi-modal tasks in robotic manipulation. However, it has fundamental limitations in out-of-distribution failures that persist due to compounding errors and its limited capability t
Externí odkaz:
http://arxiv.org/abs/2410.14868
Autor:
Jang, Deok-Kyeong, Yang, Dongseok, Jang, Deok-Yun, Choi, Byeoli, Shin, Donghoon, Lee, Sung-hee
This paper introduces ELMO, a real-time upsampling motion capture framework designed for a single LiDAR sensor. Modeled as a conditional autoregressive transformer-based upsampling motion generator, ELMO achieves 60 fps motion capture from a 20 fps L
Externí odkaz:
http://arxiv.org/abs/2410.06963
Autor:
Park, Eunyoung, Jung, Chulho, Hwang, Junha, Shin, Jaeyong, Lee, Sung Yun, Lee, Heemin, Heo, Seung Phil, Nam, Daewoong, Kim, Sangsoo, Kim, Min Seok, Kim, Kyung Sook, Eom, In Tae, Noh, Do Young, Song, Changyong
Photoinduced ultrafast phenomena in materials exhibiting nonequilibrium behavior can lead to the emergence of exotic phases beyond the limits of thermodynamics, presenting opportunities for femtosecond photoexcitation. Despite extensive research, the
Externí odkaz:
http://arxiv.org/abs/2409.15877