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Design Refinement of Catalytic System for Scale-Up Mild Nitrogen Photo-Fixation.
Nanomicro Lett
March 2025
School of Chemistry and Chemical Engineering, Southwest University, Chongqing, 400715, People's Republic of China.
Ammonia and nitric acid, versatile industrial feedstocks, and burgeoning clean energy vectors hold immense promise for sustainable development. However, Haber-Bosch and Ostwald processes, which generates carbon dioxide as massive by-product, contribute to greenhouse effects and pose environmental challenges. Thus, the pursuit of nitrogen fixation through carbon-neutral pathways under benign conditions is a frontier of scientific topics, with the harnessing of solar energy emerging as an enticing and viable option.
View Article and Find Full Text PDFIntegrated surveillance and early warning system of emerging infectious diseases in China at community level: current status, gaps and perspectives.
Sci One Health
December 2024
School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
Emerging infectious diseases (EIDs) pose a significant threat to public health. Effective surveillance and early warning systems that monitor EIDs in a timely manner are crucial for their control. Given that more than half of EIDs are zoonotic, traditional integrated surveillance systems remain inadequate.
View Article and Find Full Text PDFDevelopment and validation of an interpretable machine learning model for predicting the risk of hepatocellular carcinoma in patients with chronic hepatitis B: a case-control study.
BMC Gastroenterol
March 2025
Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China.
Background: The aim of this study was to develop and internally validate an interpretable machine learning (ML) model for predicting the risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB) infection.
Methods: We retrospectively collected clinical data from patients with HCC and CHB treated at the Fourth Affiliated Hospital of Guangxi Medical University from January 2022 to December 2022, including demographics, comorbidities, and laboratory parameters. The datasets were randomly divided into a training set (361 cases) and a validation set (155 cases) in a 7:3 ratio.
Comparison of machine learning models for rock UCS prediction using measurement while drilling data.
Sci Rep
March 2025
SINOHYDRO Bureau 14CO.LTD, Kunming, 650200, China.
Accurately determining the uniaxial compressive strength (UCS) of rocks is crucial for various rock engineering applications. However, traditional methods of obtaining UCS are often time-consuming, labor-intensive, and unsuitable for fractured rock sections. In recent years, using Measurement-while-drilling data to identify UCS has gained traction as an alternative approach.
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