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6,796 results on '"Yin Xiao"'

209. Realization and Performance Assessment of Uncombined Multi-GNSS PPP-RTK for Expressway Scenarios

Author

Yin, Xiao, Chai, Hongzhou, Zhao, Liang, Zhang, Yize, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Yang, Changfeng, editor, and Xie, Jun, editor

Published
2022
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234. Seeing Permeability From Images: Fast Prediction with Convolutional Neural Networks

Author

Wu, Jin-Long, Yin, Xiao-Long, and Xiao, Heng

Subjects
Physics - Computational Physics, 76S05
Abstract

Fast prediction of permeability directly from images enabled by image recognition neural networks is a novel pore-scale modeling method that has a great potential. This article presents a framework that includes (1) generation of porous media samples, (2) computation of permeability via fluid dynamics simulations, (3) training of convolutional neural networks (CNN) with simulated data, and (4) validations against simulations. Comparison of machine learning results and the ground truths suggests excellent predictive performance across a wide range of porosities and pore geometries, especially for those with dilated pores. Owning to such heterogeneity, the permeability cannot be estimated using the conventional Kozeny-Carman approach. Computational time was reduced by several orders of magnitude compared to fluid dynamic simulations. We found that, by including physical parameters that are known to affect permeability into the neural network, the physics-informed CNN generated better results than regular CNN, however improvements vary with implemented heterogeneity., Comment: 17 pages, 8 figures

Published
2018
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243. Hepatic Autophagy Deficiency Compromises Farnesoid X Receptor Functionality and Causes Cholestatic Injury.

Author

Khambu, Bilon, Li, Tiangang, Yan, Shengmin, Yu, Changshun, Chen, Xiaoyun, Goheen, Michael, Li, Yong, Lin, Jingmei, Cummings, Oscar, Lee, Youngmin, Friedman, Scott, Dong, Zheng, Feng, Gen-Sheng, Wu, Shangwei, and Yin, Xiao-Ming

Subjects
Animals, Autophagy, Bile Acids and Salts, Cholestasis, Intrahepatic, Female, Food Deprivation, Liver, Male, Mice, Transgenic, NF-E2-Related Factor 2, Receptors, Cytoplasmic and Nuclear
Abstract

Autophagy is important for hepatic homeostasis, nutrient regeneration, and organelle quality control. We investigated the mechanisms by which liver injury occurred in the absence of autophagy function. We found that mice deficient in autophagy because of the lack of autophagy-related gene 7 or autophagy-related gene 5, key autophagy-related genes, manifested intracellular cholestasis with increased levels of serum bile acids, a higher ratio of tauromuricholic acid/taurocholic acid in the bile, increased hepatic bile acid load, abnormal bile canaliculi, and altered expression of hepatic transporters. In determining the underlying mechanism, we found that autophagy sustained and promoted the basal and up-regulated expression of farnesoid X receptor (Fxr) in the fed and starved conditions, respectively. Consequently, expression of Fxr and its downstream genes, particularly bile salt export pump, and the binding of FXR to the promoter regions of these genes, were suppressed in autophagy-deficient livers. In addition, codeletion of nuclear factor erythroid 2-related factor 2 (Nrf2) in autophagy deficiency status reversed the FXR suppression. Furthermore, the cholestatic injury of autophagy-deficient livers was reversed by enhancement of FXR activity or expression, or by Nrf2 deletion. Conclusion: Together with earlier reports that FXR can suppress autophagy, our findings indicate that autophagy and FXR form a regulatory loop and deficiency of autophagy causes abnormal FXR functionality, leading to the development of intracellular cholestasis and liver injury.

Published
2019

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