Zobrazeno 1 - 10
of 63
pro vyhledávání: '"Jiecheng Yang"'
Autor:
Yu Chen, Hui Chen, Ying Wang, Fangzhou Liu, Xiao Fan, Chengyu Shi, Xinwan Su, Manman Tan, Yebin Yang, Bangxing Lin, Kai Lei, Lei Qu, Jiecheng Yang, Zhipeng Zhu, Zengzhuang Yuan, Shanshan Xie, Qinming Sun, Dante Neculai, Wei Liu, Qingfeng Yan, Xiang Wang, Jianzhong Shao, Jian Liu, Aifu Lin
Publikováno v:
Advanced Science, Vol 11, Iss 10, Pp n/a-n/a (2024)
Abstract High‐fat diet (HFD)‐induced obesity is a crucial risk factor for metabolic syndrome, mainly due to adipose tissue dysfunctions associated with it. However, the underlying mechanism remains unclear. This study has used genetic screening t
Externí odkaz:
https://doaj.org/article/48ce7448a18a4b208e3f87b701292137
Autor:
Xiuwen Xu, Wei Qian, Jian Wang, Jiecheng Yang, Jianwei Chen, Shuang Xiao, Yongshuai Ge, Shihe Yang
Publikováno v:
Advanced Science, Vol 8, Iss 21, Pp n/a-n/a (2021)
Abstract Perovskite materials in different dimensions show great potential in direct X‐ray detection, but each with limitations stemming from its own intrinsic properties. Particularly, the sensitivity of two‐dimensional (2D) perovskites is limit
Externí odkaz:
https://doaj.org/article/ceeba9647e2b41dcadc3d1a7620c11f8
Publikováno v:
Energies, Vol 13, Iss 7, p 1841 (2020)
The effects of particle shape differences on binary mixture shear flows are investigated using the Discrete Element Method (DEM). The binary mixtures consist of frictionless rods and disks, which have the same volume but significantly different shape
Externí odkaz:
https://doaj.org/article/38e2166b5d9041ae83779bc20014c3a7
Publikováno v:
Acta Pharmaceutica Sinica B, Vol 4, Iss 1, Pp 52-59 (2014)
Air flow and particle–particle/wall impacts are considered as two primary dispersion mechanisms for dry powder inhalers (DPIs). Hence, an understanding of these mechanisms is critical for the development of DPIs. In this study, a coupled DEM–CFD
Externí odkaz:
https://doaj.org/article/5d3a63d1cf34413cbd9a204854ff9f4c
Autor:
Zhenzhen Kong, Zonghu Li, Gang Cao, Jiale Su, Yiwen Zhang, Jinbiao Liu, Jingxiong Liu, Yuhui Ren, Huihui Li, Laiming Wei, Guo-ping Guo, Yuanyuan Wu, Henry H. Radamson, Junfeng Li, Zhenhua Wu, Hai-ou Li, Jiecheng Yang, Chao Zhao, Tianchun Ye, Guilei Wang
Publikováno v:
ACS Applied Materials & Interfaces.
Publikováno v:
Powder Technology. 387:9-15
The homogeneous cooling process of binary mixtures of large aspherical particles and small spheres is modeled using DEM. The dissipation rate increases with the increasing total solid volume fraction of the mixture. For a specified total solid volume
Publikováno v:
Cancer letters. 543
Evidence accumulated over the past decade has verified that long non-coding RNAs (lncRNAs) exert important functions in multiple cell programs. As a novel class of cellular regulatory molecules, lncRNAs interact with different molecules, such as DNA,
Autor:
Fangzhou Liu, Tian Tian, Zhen Zhang, Shanshan Xie, Jiecheng Yang, Linyu Zhu, Wen Wang, Chengyu Shi, Lingjie Sang, Kaiqiang Guo, Zuozhen Yang, Lei Qu, Xiangrui Liu, Jian Liu, Qingfeng Yan, Huai-qiang Ju, Wenqi Wang, Hai-long Piao, Jianzhong Shao, Tianhua Zhou, Aifu Lin
Publikováno v:
Nature metabolism. 4(8)
Cholesterol contributes to the structural basis of biological membranes and functions as a signaling molecule, whose dysregulation has been associated with various human diseases. Here, we report that the long non-coding RNA (lncRNA) SNHG6 increases
Autor:
Xin Zhang, Ting Su, Jiecheng Yang, Jiongtao Zhu, Dongmei Xia, Hairong Zheng, Dong Liang, Yongshuai Ge
Publikováno v:
Medical physicsREFERENCES. 49(2)
The purpose of this study is to evaluate and compare the quantitative material decomposition performance of the dual-energy CT (DECT) and differential phase contrast CT (DPCT) via numerical observer studies.The electron density (The model observer re
Autor:
Ting Su, Xindong Sun, Jiecheng Yang, Donghua Mi, Yikun Zhang, Haodi Wu, Shibo Fang, Yang Chen, Hairong Zheng, Dong Liang, Yongshuai Ge
Publikováno v:
Medical physicsREFERENCES. 49(2)
The purpose of this paper is to present an end-to-end deep convolutional neural network to improve the dual-energy CT (DECT) material decomposition performance.In this study, we proposes a unified mutual-domain (sinogram domain and CT domain) materia