Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Feifan Qi"'
Autor:
Mengdie Wu1,2, Feifan Qi2,3, Ren Qiu2,3, Jing Feng4, Xinshui Ren1,2, Shengzhong Rong5, Hongkun Ma5, Hongzhi Pan2 panhongzhilaoshi@163.com, Dong Chang6 dongchang1969@163.com
Publikováno v:
Journal of AOAC International. Jul/Aug2022, Vol. 105 Issue 4, p1175-1182. 8p. 5 Diagrams, 1 Chart, 3 Graphs.
Autor:
Mengdie Wu, Feifan Qi, Ren Qiu, Jing Feng, Xinshui Ren, Shengzhong Rong, Hongkun Ma, Hongzhi Pan, Dong Chang
Publikováno v:
Journal of AOAC International. 105(4)
Background Nuciferine is an amorphine alkaloid in lotus leaf that has anti-inflammatory, lipid-lowering and hypoglycemic effects, so the quantitation of detected nuciferine is important. Objective An electrochemical method was developed for nuciferin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1eb2836aebd9cb1f10976f5e8cdc108
https://pubmed.ncbi.nlm.nih.gov/35167658
https://pubmed.ncbi.nlm.nih.gov/35167658
Autor:
Mengdie, Wu, Simin, Liu, Feifan, Qi, Ren, Qiu, Jing, Feng, Xinshui, Ren, Shengzhong, Rong, Hongkun, Ma, Dong, Chang, Hongzhi, Pan
Publikováno v:
Talanta. 241
A label-free electrochemical immunosensor was constructed for cancer antigen 125 (CA125) detection based on multiple-enlargement means of layer-by-layer (LBL) assembly of ordered mesoporous carbon (CMK-3), gold nanoparticles (Au NPs) and MgAl layered
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::97361bb2cff8e0f55d13c04ef37e8f81
https://pubmed.ncbi.nlm.nih.gov/35101834
https://pubmed.ncbi.nlm.nih.gov/35101834
Autor:
Ren Qiu, Jianmin Dai, Lingqiang Meng, Hongmin Gao, Mengdie Wu, Feifan Qi, Jing Feng, Hongzhi Pan
Publikováno v:
Applied biochemistry and biotechnology. 194(7)
Porous carbon sphere materials have a large variety of applications in several fields due to the large surface area, adaptable porosity, and good conductivity they possess. Obtaining a steady carbon sphere using the green synthesis method remains a s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6a7032cf9ab305bbc9048b2593e8dbb9
https://pubmed.ncbi.nlm.nih.gov/35334069
https://pubmed.ncbi.nlm.nih.gov/35334069
Autor:
Mengdie Wu, Simin Liu, Feifan Qi, Ren Qiu, Jing Feng, Xinshui Ren, Shengzhong Rong, Hongkun Ma, Dong Chang, Hongzhi Pan
Publikováno v:
Talanta. 241:123254
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1116ea02a03c7d9ea12b6c0ae953536f
https://doi.org/10.1016/j.talanta.2022.123254
https://doi.org/10.1016/j.talanta.2022.123254
Publikováno v:
IEEE Access, Vol 11, Pp 48611-48627 (2023)
In industry, accurate remaining useful life (RUL) prediction is critical in improving system reliability and reducing downtime and accident risk. Numerous data-driven RUL prediction approaches have been proposed and achieved impressive performance in
Externí odkaz:
https://doaj.org/article/6c597a8571b54f658c2a2b548a723f6d
Publikováno v:
Sensors, Vol 23, Iss 11, p 5334 (2023)
This article introduces a novel framework for diagnosing faults in rolling bearings. The framework combines digital twin data, transfer learning theory, and an enhanced ConvNext deep learning network model. Its purpose is to address the challenges po
Externí odkaz:
https://doaj.org/article/1acbf67fee644a57a2c5c8c28c1bdb5f