Hui Wang

1 month ago | advanced.onlinelibrary.wiley.com | Qi Lu |Haiyan Duan |Kai Zhang |Hui Wang

Conflict of Interest The authors declare no conflict of interest. Supporting Information Filename Description adfm202507253-sup-0001-SuppMat.docx17.1 MB Supporting Information References 1a) , Nat. Sustain. 2024, 7, 525; b) , , Energy Environ. Sci. 2023, 16, 4983. 2a) , , , , , Water Res. 2025, 271, 122985; b) , , , , , Nat. Commun. 2024, 15, 2996. 3a) , , , , , , Science 2021, 372, 296; b) , , , , ACS Energy Lett. 2024, 9, 26.

2 months ago | cell.com | Jun Xiao |Weiyun Li |Xin Zheng |Linlin Qi |Hui Wang |Chi Zhang | +16 more

Main text(Immunity 52, 109–122.e1–e6; January 14, 2020)The authors note that Figure S6C showing normal lung tissue in the Akt3+/- Mock group is partially overlapped with the Akt3+/+ Mock control group. Figure S6A representing normal lung tissue in the AY9944-PBS group was mistakenly uploaded with one image from the PBS control group that also represents normal lung tissue. We have now provided the correct images for the Akt3+/- Mock (Figure S6C) and AY9944-PBS group (Figure S6A).

Jan 27, 2025 | mdpi.com | Hui Wang |Kaichao Zhang |Ke Jiang |Xiaobin Zhang

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.

Jan 10, 2025 | dx.doi.org | Sheng Xiang |Shaojun Zhang |Yu Yu |Hui Wang

Occurrence, Fate, and Transport of Contaminants in Indoor Air and AtmosphereJanuary 10, 2025 Sheng Xiang State Key Laboratory of Pollution Control and Resource Reuse (Tongji University), Shanghai 200092, PR China College of Environmental Science and Engineering, Tongji University, Shanghai 200092, P.R. China Shaojun Zhang School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, PR China State Environmental...

Jan 6, 2025 | link.aps.org | Hui Wang

Gradient-based meta-learning algorithms have gained popularity for their ability to train models on new tasks using limited data. Empirical observations indicate that such algorithms are able to learn a shared representation across tasks, which is regarded as a key factor in their success. However, the in-depth theoretical understanding of the learning dynamics and the origin of the shared representation remains underdeveloped.