Zobrazeno 1 - 10
of 65
pro vyhledávání: '"Huang-Mu Lo"'
Autor:
Cittrarasu Vetrivel, Ganesan Sivarasan, Kaliannan Durairaj, Chinnasamy Ragavendran, Chinnaperumal Kamaraj, Sankar Karthika, Huang-Mu Lo
Publikováno v:
Diagnostics, Vol 13, Iss 8, p 1464 (2023)
In order to support biomolecule attachment, an effective electrochemical transducer matrix for biosensing devices needs to have many specialized properties, including quick electron transfer, stability, high surface area, biocompatibility, and the pr
Externí odkaz:
https://doaj.org/article/cb21aac1689b42d881dd248100c48ab3
Autor:
Sivarasan Ganesan, Jagadeesh Kumar Alagarasan, Mohandoss Sonaimuthu, Kanakaraj Aruchamy, Fatemah Homoud Alkallas, Amira Ben Gouider Trabelsi, Fedor Vasilievich Kusmartsev, Veerababu Polisetti, Moonyong Lee, Huang-Mu Lo
Publikováno v:
Marine Drugs, Vol 20, Iss 12, p 733 (2022)
The controlled-release characteristic of drug delivery systems is utilized to increase the residence time of therapeutic agents in the human body. This study aimed to formulate and characterize salsalate (SSL)-loaded chitosan nanoparticles (CSNPs) pr
Externí odkaz:
https://doaj.org/article/20340d36f53c4060a00c134cced206ad
Autor:
Tzu-Yi Pai, Huang-Mu Lo, Terng-Jou Wan, Ya-Hsuan Wang, Yun-Hsin Cheng, Meng-Hung Tsai, Hsuan Tang, Yu-Xiang Sun, Wei-Cheng Chen, Yi-Ping Lin
Publikováno v:
Water, Vol 13, Iss 11, p 1580 (2021)
A sewer dynamic model (SDM), an innovative use of combined models, was established to describe the reactions of compounds in a pilot sewer pipe. The set of ordinary differential equations in the SDM was solved simultaneously using the fourth-order Ru
Externí odkaz:
https://doaj.org/article/c43d65aa71584a2da092eaaab59171fa
Publikováno v:
In Chemosphere October 2023 337
Autor:
Huang-Mu Lo, 羅玄灝
95
Grey model (GM) and artificial neural network (ANN) was employed to predict CO2, SO2 and O2 in the emissions from a medical incinerator. The results indicated that the minimum mean absolute percentage errors of 4.93 %, 13.05 % and 1.63 % for
Grey model (GM) and artificial neural network (ANN) was employed to predict CO2, SO2 and O2 in the emissions from a medical incinerator. The results indicated that the minimum mean absolute percentage errors of 4.93 %, 13.05 % and 1.63 % for
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/91055498090057827775
Autor:
Huang-Mu Lo, 羅煌木
90
The thesis investigates the effects of environmental stress on the vegetation at landfill and the physico-chemical properties of bottom ash generated from Taichung City incinerator. Experiments undertaken include ash characterisation, ash lea
The thesis investigates the effects of environmental stress on the vegetation at landfill and the physico-chemical properties of bottom ash generated from Taichung City incinerator. Experiments undertaken include ash characterisation, ash lea
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/18807337846411392852
Autor:
Sonaimuthu Mohandoss, Sivarasan Ganesan, K. Velsankar, Sakkarapani Sudhahar, Fatemah H. Alkallas, Amira Ben Gouider Trabelsi, Fedor V. Kusmartsev, Huang-Mu Lo, Yong Rok Lee
Publikováno v:
Journal of Biomaterials Science, Polymer Edition. 34:715-733
Publikováno v:
International Journal of Applied Science and Engineering. 19:1-9
Publikováno v:
AIP Conference Proceedings.
Autor:
Tzu-Yi Pai, Ray-Shyan Wu, Ching-Ho Chen, Huang-Mu Lo, Terng-Jou Wan, Min-Hsin Liu, Wei-Cheng Chen, Yi-Ping Lin, Chun-Tse Hsu
Publikováno v:
Water, Air, & Soil Pollution. 233