Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
Journal of Environmental Management|December 27, 2025
Fluoride ions removal from synthetic solutions and industrial wastewater using a carboxymethyl cellulose bioaerogel modified with biochar/CuFe<sub>2</sub>O<sub>4</sub>/La metal-organic frameworkHui Gao, Qianmin Gao, Lijuan Liu, et al.
Materials (Basel, Switzerland)|July 14, 2023
Effects of CO<sub>2</sub> Curing on the Properties of Pervious Concrete in Different Paste-Aggregate RatiosMingfang Ba, Siyi Fang, Wei Cheng, et al.
Behavior Research Methods|July 1, 2022
CCLOWW: A grade-level Chinese children's lexicon of written wordsLuan Li, Yang Yang, Ming Song, et al.
Scientific Reports|October 2, 2025
Synergistic effects of SAE/CaCO<sub>3</sub> on enhancing sulfate resistance in High-Strength cementitious compositesLei Ren, Puyan Wang, Siyi Fang, et al.
Medicine|April 17, 2026
Association between triglyceride-glucose-frailty index and metabolic dysfunction-associated fatty liver disease: Mediation analysis involving obesity indicators in the NHANESShixian Ruan, Shuanglong Liu, Xinmei Zhang, et al.
European Heart Journal. Digital Health|June 2, 2023
Automatic screening of patients with atrial fibrillation from 24-h Holter recording using deep learningPeng Zhang, Fan Lin, Fei Ma, et al.
Patterns (New York, N.Y.)|April 24, 2026
Hierarchical fusion of electrocardiogram and phonocardiogram data improves heart failure detectionFei Ma, Haobo Zhang, Siyi Fang, et al.
Food Chemistry|January 23, 2025
TMT-labelled quantitative proteomics reveals the mechanism of Rhodotorula mucilaginosa on proteolysis of dry-cured ham: Structural protein degradation, amino acid release and taste improvementTianmeng Zhang, Ying Wang, Jing Zhu, et al.
Med (New York, N.Y.)|April 12, 2025
Clinician-artificial intelligence collaboration: A win-win solution for efficiency and reliability in atrial fibrillation diagnosisPeng Zhang, Fan Lin, Fei Ma, et al.
Iscience|March 30, 2026
Glucose forecasting and hypoglycemia forewarning in type 1 and type 2 diabetes using deep learningSiyi Fang, Haowei Zhang, Die Hu, et al.
Pageof 1