Zobrazeno 1 - 10
of 459
pro vyhledávání: '"Xun, Lei"'
Autor:
Xiaoxin Zhou, Xiaoqian Lin, Jing Yu, Yi Yang, Hira Muzammel, Said Amissi, Valérie B. Schini-Kerth, Xun Lei, Pedro A. Jose, Jian Yang, Dan Shi
Publikováno v:
Nutrition Journal, Vol 23, Iss 1, Pp 1-14 (2024)
Abstract Background Time-restricted eating (TRE), a popular form of intermittent fasting, has shown benefits for improving metabolic diseases and cardiometabolic health. However, the effect of TRE in the regulation of blood pressure in primary hypert
Externí odkaz:
https://doaj.org/article/090cdb7bc18048efb518c564ef01ccb3
Deep neural network (DNN) inference is increasingly being executed on mobile and embedded platforms due to low latency and better privacy. However, efficient deployment on these platforms is challenging due to the intensive computation and memory acc
Externí odkaz:
http://arxiv.org/abs/2206.02525
Publikováno v:
BMC Cancer, Vol 24, Iss 1, Pp 1-12 (2024)
Abstract Purpose There is an aberrant expression of NBAT-1 in various human cancers, which was proven to limit the proliferation, invasion, and metastasis of tumour cells via multiple approaches. Most existing research focuses on sample size and disc
Externí odkaz:
https://doaj.org/article/fe48e1d52d7e459dacd0f2aac4da89dc
Publikováno v:
BMC Infectious Diseases, Vol 23, Iss 1, Pp 1-9 (2023)
Abstract Background Hand, foot, and mouth disease (HFMD) is a common infectious disease that poses a serious threat to children all over the world. However, the current prediction models for HFMD still require improvement in accuracy. In this study,
Externí odkaz:
https://doaj.org/article/41e64032dbda4d789aa5925aa9a691fd
The Transformer architecture is widely used for machine translation tasks. However, its resource-intensive nature makes it challenging to implement on constrained embedded devices, particularly where available hardware resources can vary at run-time.
Externí odkaz:
http://arxiv.org/abs/2107.08199
Machine learning inference is increasingly being executed locally on mobile and embedded platforms, due to the clear advantages in latency, privacy and connectivity. In this paper, we present approaches for online resource management in heterogeneous
Externí odkaz:
http://arxiv.org/abs/2105.03608
Inference for Deep Neural Networks is increasingly being executed locally on mobile and embedded platforms due to its advantages in latency, privacy and connectivity. Since modern System on Chips typically execute a combination of different and dynam
Externí odkaz:
http://arxiv.org/abs/2105.03600
Mobile and embedded platforms are increasingly required to efficiently execute computationally demanding DNNs across heterogeneous processing elements. At runtime, the available hardware resources to DNNs can vary considerably due to other concurrent
Externí odkaz:
http://arxiv.org/abs/2105.03596
Autor:
Yaqi Wen, Laixi Zhang, Shengping Li, Tiankun Wang, Ke Jiang, Lingxi Zhao, Yuzhao Zhu, Wen Zhao, Xun Lei, Manoj Sharma, Yong Zhao, Zumin Shi, Jun Yuan
Publikováno v:
Public Health Nutrition, Vol 27 (2024)
Abstract Objective: We aimed to examine the association between dietary Se intake and CVD risk in Chinese adults. Design: This prospective cohort study included adults above 20 years old in the China Health and Nutrition Survey (CHNS), and they we
Externí odkaz:
https://doaj.org/article/028942e756374f9a87d0a60b1c0daede
Autor:
Xiaoxin Zhou, Longlong Zhang, Xiaoqian Lin, Xi Chen, Hong Liu, Xiaoli Yuan, Qiuxia Zhao, Weiwei Wang, Xun Lei, Pedro A Jose, Chunyan Deng, Jian Yang
Publikováno v:
Clinical and Experimental Hypertension, Vol 45, Iss 1 (2023)
ABSTRACTBackground Thrombospondins (TSPs) play important roles in several cardiovascular diseases. However, the association between circulating (plasma) thrombospondin 2 (TSP2) and essential hypertension remains unclear. The present study was aimed t
Externí odkaz:
https://doaj.org/article/aea1fe53e18b4849832c7fc3b468b5eb