Zobrazeno 1 - 10
of 53
pro vyhledávání: '"Aiguo, Xia"'
Autor:
Rongrong Zhang, Yajia Huang, Mei Li, Lei Wang, Bing Li, Aiguo Xia, Ye Li, Shuai Yang, Fan Jin
Publikováno v:
mLife, Vol 2, Iss 4, Pp 450-461 (2023)
Abstract Synthetic biology relies on the screening and quantification of genetic components to assemble sophisticated gene circuits with specific functions. Microscopy is a powerful tool for characterizing complex cellular phenotypes with increasing
Externí odkaz:
https://doaj.org/article/21f12515f24747119dd1548341552373
Publikováno v:
Fractal and Fractional, Vol 8, Iss 6, p 331 (2024)
The balance between accuracy and computational complexity is currently a focal point of research in dynamical system modeling. From the perspective of model reduction, this paper addresses the mode selection strategy in Dynamic Mode Decomposition (DM
Externí odkaz:
https://doaj.org/article/cee340d5abd34781938b7cd57d9c8c6e
Publikováno v:
Propulsion and Power Research, Vol 12, Iss 1, Pp 138-152 (2023)
Based on the sample entropy algorithm in nonlinear dynamics, an improved sample entropy method is proposed in the aerodynamic system instability identification for the stall precursor detection based on the nonlinear feature extraction algorithm in a
Externí odkaz:
https://doaj.org/article/54c02fff6ed54c97b578281e49875159
Autor:
Wenhui Chen, Jinfeng Zhang, Feixuan Li, Congcong Wang, Yuchen Zhang, Aiguo Xia, Lei Ni, Fan Jin
Publikováno v:
mSystems, Vol 7, Iss 6 (2022)
ABSTRACT The part of expression noise that is brought about by transcriptional regulation (represented here as NTR) is an important criterion for estimating the regulatory mode of a gene. However, characterization of NTR is an under-explored area, an
Externí odkaz:
https://doaj.org/article/ae90fd12b693437ea3a2715103297d08
Publikováno v:
Biomimetics, Vol 8, Iss 2, p 132 (2023)
The prediction of a stall precursor in an axial compressor is the basic guarantee to the stable operation of an aeroengine. How to predict and intelligently identify the instability of the system in advance is of great significance to the safety perf
Externí odkaz:
https://doaj.org/article/0fd04538e62d4ca4899ea8ff0f58b1f6
Publikováno v:
Aerospace, Vol 9, Iss 6, p 320 (2022)
In order to effectively identify the signs of instability in the aerodynamic system of an axial compressor, a wavelet singular spectral entropy algorithm incorporated within the wavelet transform, singular value decomposition and information entropy
Externí odkaz:
https://doaj.org/article/68e2e4d5697641939cf12a55dcd8b3db
Autor:
Jia Huang, Yongzhao Lv, Aiguo Xia, Shengliang Zhang, Wei Tuo, Hongtao Xue, Yantao Sun, Xiuran He
Publikováno v:
Energies, Vol 15, Iss 12, p 4389 (2022)
Based on the COMSOL software, body forces substituted into the Reynolds-averaged Navier–Stokes (RANS) equations as the source terms instead of the actual blade rows were improved to better predict the compressor performance. Improvements in paralle
Externí odkaz:
https://doaj.org/article/a3ddb98d98f54ef3952f46bf26c8feb5
Autor:
Catherine R Armbruster, Calvin K Lee, Jessica Parker-Gilham, Jaime de Anda, Aiguo Xia, Kun Zhao, Keiji Murakami, Boo Shan Tseng, Lucas R Hoffman, Fan Jin, Caroline S Harwood, Gerard CL Wong, Matthew R Parsek
Publikováno v:
eLife, Vol 9 (2020)
Externí odkaz:
https://doaj.org/article/4fdbcf82b5d04bb4b59387c47ce58d61
Publikováno v:
Machines, Vol 10, Iss 2, p 122 (2022)
Focusing on the identification of dynamic system stability, a hybrid neural network model is proposed in this research for the rotating stall phenomenon in an axial compressor. Based on the data fusion of the amplitude of the spatial mode, the nonlin
Externí odkaz:
https://doaj.org/article/9d9b85faa99449599dda0db7ee68ef79
Publikováno v:
Nature Communications, Vol 9, Iss 1, Pp 1-11 (2018)
Pyoverdine is secreted by the opportunistic pathogen Pseudomonas aeruginosa to scavenge iron from its hosts. Here, the authors show that under stress conditions P. aeruginosa uses a ‘conditional privatization’ strategy, reserving pyoverdine intra
Externí odkaz:
https://doaj.org/article/aa65a6d85e2f49aea8cd1e0055be0add