Zobrazeno 1 - 10
of 23 012
pro vyhledávání: '"Hong Liang"'
Autor:
Cheah, Hong Liang, Deghat, Mohammad
Publikováno v:
Australasian Conference on Robotics and Automation (ACRA 2024)
This paper proposes a finite-time input-to-state stable (FTISS) bearing-only formation control law that rejects unknown constant disturbances. Unlike existing finite-time bearing-based formation control laws, which typically rely on the availability
Externí odkaz:
http://arxiv.org/abs/2412.15757
Enzyme engineering enables the modification of wild-type proteins to meet industrial and research demands by enhancing catalytic activity, stability, binding affinities, and other properties. The emergence of deep learning methods for protein modelin
Externí odkaz:
http://arxiv.org/abs/2410.21127
Autor:
Amin, Al, Hasan, Kamrul, Zein-Sabatto, Saleh, Hong, Liang, Shetty, Sachin, Ahmed, Imtiaz, Islam, Tariqul
Healthcare industries face challenges when experiencing rare diseases due to limited samples. Artificial Intelligence (AI) communities overcome this situation to create synthetic data which is an ethical and privacy issue in the medical domain. This
Externí odkaz:
http://arxiv.org/abs/2410.12245
Immunogenicity prediction is a central topic in reverse vaccinology for finding candidate vaccines that can trigger protective immune responses. Existing approaches typically rely on highly compressed features and simple model architectures, leading
Externí odkaz:
http://arxiv.org/abs/2410.02647
Autor:
Hao, Yun-Chao, Krüger, Matthias, Antezza, Mauro, Zhou, Cheng-Long, Yi, Hong-Liang, Zhang, Yong
We explore near-field thermal radiation transport in nanoparticles embedded within a multilayer slab structure, focusing on dynamic modulation of heat flux via cavity interactions. Our findings reveal that by tuning the distance between reflectors an
Externí odkaz:
http://arxiv.org/abs/2409.12698
Autor:
Hua, Chenqing, Zhong, Bozitao, Luan, Sitao, Hong, Liang, Wolf, Guy, Precup, Doina, Zheng, Shuangjia
Publikováno v:
38th Conference on Neural Information Processing Systems (NeurIPS 2024) Track on Datasets and Benchmarks
Enzymes, with their specific catalyzed reactions, are necessary for all aspects of life, enabling diverse biological processes and adaptations. Predicting enzyme functions is essential for understanding biological pathways, guiding drug development,
Externí odkaz:
http://arxiv.org/abs/2408.13659
Accurate prediction of enzyme function is crucial for elucidating biological mechanisms and driving innovation across various sectors. Existing deep learning methods tend to rely solely on either sequence data or structural data and predict the EC nu
Externí odkaz:
http://arxiv.org/abs/2408.06391
Autor:
Zhou, Cheng-Long, Torbatian, Zahra, Yang, Shui-Hua, Zhang, Yong, Yi, Hong-Liang, Antezza, Mauro, Novko, Dino, Qiu, Cheng-Wei
Publikováno v:
Phys. Rev. Lett. 133, 066902 (2024)
Charge-order states of broken symmetry, such as charge density wave (CDW), are able to induce exceptional physical properties, however, the precise understanding of the underlying physics is still elusive. Here, we combine fluctuational electrodynami
Externí odkaz:
http://arxiv.org/abs/2408.03698
Autor:
Li, Chun-qian, Shi, Jian-rong, Yan, Hong-liang, Bai, Zhong-rui, Wang, Jiang-tao, Ding, Ming-yi
Publikováno v:
ApJS (2024), 273, 18
The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) has obtained more than 23 million spectra, opening an unprecedented opportunity to study stellar physics, as well as the formation and evolution of our Milky Way. In order to obta
Externí odkaz:
http://arxiv.org/abs/2407.13134
Autor:
Xie, Xiao-Jin, Shi, Jianrong, Yan, Hong-Liang, Chen, Tian-Yi, Prieto, Carlos Allende, Beers, Timothy C., Liu, Shuai, Li, Chun-Qian, Ding, Ming-Yi, Tang, Yao-Jia, Zhang, Ruizhi, Xie, Renjing
Publikováno v:
ApJL, 2024, Volume 970, Number 2, L30
Highly r-process-enhanced stars are rare and usually metal-poor ([Fe/H] < - 1.0), and mainly populate the Milky Way halo and dwarf galaxies. This study presents the discovery of a relatively bright (V = 12.72), highly r-process-enhanced (r-II) star (
Externí odkaz:
http://arxiv.org/abs/2407.11572