Zobrazeno 1 - 10
of 594
pro vyhledávání: '"Kezhi, Li"'
Publikováno v:
JMIR Mental Health, Vol 11, p e57400 (2024)
BackgroundLarge language models (LLMs) are advanced artificial neural networks trained on extensive datasets to accurately understand and generate natural language. While they have received much attention and demonstrated potential in digital health,
Externí odkaz:
https://doaj.org/article/7ad362e59799406ab0abc4658b279972
Autor:
Ruyang Huang, Aifang Yao, Yongyong Yan, Jingyi Wang, Qingxiang Li, Kezhi Li, Yongqi Tian, Shaoyun Wang, Jiulin Wu
Publikováno v:
eFood, Vol 5, Iss 4, Pp n/a-n/a (2024)
Abstract Active compounds were usually incorporated into biopolymer films to enhance their properties. The tensile strength (TS) and elongation at break (EAB) of the gelatin composite films increased along with the addition of ε‐polylysine (ε‐P
Externí odkaz:
https://doaj.org/article/120073ff3638463db5673cb8bec305ce
Autor:
Yong Yin, Bingcheng Luo, Kezhi Li, Benjamin M. Moskowitz, Bar Mosevitzky Lis, Israel E. Wachs, Minghui Zhu, Ye Sun, Tianle Zhu, Xiang Li
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract Supported nanoclusters (SNCs) with distinct geometric and electronic structures have garnered significant attention in the field of heterogeneous catalysis. However, their directed synthesis remains a challenge due to limited efficient appro
Externí odkaz:
https://doaj.org/article/8a03fb10215d4ec8a8e09021e3fb332d
Autor:
Yong Yin, Bingcheng Luo, Kezhi Li, Benjamin M. Moskowitz, Bar Mosevitzky Lis, Israel E. Wachs, Minghui Zhu, Ye Sun, Tianle Zhu, Xiang Li
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-1 (2024)
Externí odkaz:
https://doaj.org/article/dd40dcdde765469e981e7d3b9b7bf586
Autor:
Chaojun Zhang, Sanchun An, Ruibo Lv, Kezhi Li, Haizhou Liu, Jilin Li, Yanping Tang, Zhengmin Cai, Tianren Huang, Long Long, Wei Deng
Publikováno v:
Virus Research, Vol 341, Iss , Pp 199317- (2024)
To find the predictors of early HCC based on the dynamic changes of HBV quasispecies, this study utilizing the second-generation sequencing (NGS) and high-order multiplex droplet digital PCR (ddPCR) technology to examine the HBV quasispecies in serum
Externí odkaz:
https://doaj.org/article/a8e8affc00334e6b899f9c583265f426
Publikováno v:
Journal of Materials Research and Technology, Vol 26, Iss , Pp 5696-5706 (2023)
With the aim of selecting suitable carbon fibers as reinforcement material for carbon/carbon composites, needled carbon fiber felt preforms are fabricated by T300 carbon fibers and TZ300 carbon fibers as raw material respectively. The industrial CT r
Externí odkaz:
https://doaj.org/article/a65d06e21074490fb90c07a751c3dbae
Publikováno v:
Molecules, Vol 29, Iss 13, p 2959 (2024)
In this study, a PtSn/Al2O3 catalyst with bimetallic uniform distribution in the sphere was synthesized. The PDH performance and characterization analyses, such as with FTIR, XPS, and NH3-TPD, were investigated. The effects of acid on the PDH perform
Externí odkaz:
https://doaj.org/article/dbd0acf05c3249a9be83b8cf0b5c7863
Publikováno v:
Agriculture, Vol 14, Iss 6, p 843 (2024)
This paper addresses the hole-forming process of a duckbilled hole-forming device. Based on a coupled simulation using the multi-body dynamics software RecurDyn and the discrete element software EDEM, the hole-forming mechanism of a duckbilled hole-f
Externí odkaz:
https://doaj.org/article/be96e5f060764dfe82840d4d633635e4
Publikováno v:
Cancer Biology & Therapy, Vol 23, Iss 1, Pp 424-438 (2022)
Mounting evidence has demonstrated that fatty acid binding protein 5 (FABP5) is commonly upregulated in many human malignancies. However, the mechanisms explaining the involvement of FABP5 in hepatocellular carcinoma (HCC) remain unclear. In this stu
Externí odkaz:
https://doaj.org/article/8d429fd9974841b8819254ae2e95fa8e
Autor:
Zella King, Joseph Farrington, Martin Utley, Enoch Kung, Samer Elkhodair, Steve Harris, Richard Sekula, Jonathan Gillham, Kezhi Li, Sonya Crowe
Publikováno v:
npj Digital Medicine, Vol 5, Iss 1, Pp 1-12 (2022)
Abstract Machine learning for hospital operations is under-studied. We present a prediction pipeline that uses live electronic health-records for patients in a UK teaching hospital’s emergency department (ED) to generate short-term, probabilistic f
Externí odkaz:
https://doaj.org/article/001d623296ef42d78609d2153482f171