AIMC Topic: China

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Exploring the drivers of digital transformation in Chinese port and shipping enterprises: A machine learning approach.

PloS one
With the transition to a global green low-carbon economy, the urgency for digital transformation in the port and shipping industry has become increasingly prominent in making enterprises more efficient and sustainable. This study focuses on how Chine...

A novel method for achieving ecological indicator based on vertical soil bacterial communities coupled with machine learning: A case study of a typical tropical site in China.

Journal of hazardous materials
Global industrialization has resulted in severe contamination of soil with heavy metals (HMs). Nevertheless, it is unclear if it affects the depth-resolved bacterial communities. Herein, we collected soil samples at different depths from a typical HM...

Integrating SHAP analysis with machine learning to predict postpartum hemorrhage in vaginal births.

BMC pregnancy and childbirth
OBJECTIVE: This study aimed to develop a machine learning (ML) model integrated with SHapley Additive exPlanations (SHAP) analysis to predict postpartum hemorrhage (PPH) following vaginal deliveries, offering a potential tool for personalized risk as...

Prediction of natural runoff in China based on multi-scenario climate models with self-attention neural networks.

Water research
Climate change is increasingly affecting the global water cycle. Developing high-quality climate-runoff relationship models can help assess its impact on surface natural runoff, thereby enhancing resilience to water resource risks. This study extends...

Prediction of anthropogenic I in the South China Sea based on machine learning.

Journal of environmental radioactivity
With the rapid increase in the number of nuclear power plants along the China coast and the potential for releases of radioactive substances to marine ecosystems, it is important to investigate and predict the dispersion of radionuclides in the seas ...

Unraveling four decades of soil acidification on the Qinghai-Tibetan Plateau: Patterns, drivers, and future projections.

Environmental pollution (Barking, Essex : 1987)
Soil acidification poses escalating threats to ecosystem functions, yet its spatiotemporal dynamics and drivers across vulnerable high-altitude regions remain poorly resolved. Here, we integrate four-decade soil surveys (1980s-2020s) with machine lea...

Spatiotemporal evolutions and drivers of ground-level ozone in China (2015-2020): A GTWR-Kriging approach.

Environmental research
Ground-level ozone pollution has emerged as a primary environmental challenge in China. An accurate and high-resolution analysis of ground-level ozone concentrations is crucial for effectively mitigating pollution and achieving sustainability goals. ...

Stricter cadmium and lead standards needed for organic fertilizers in China.

The Science of the total environment
This study aims to evaluate the adequacy of China's national standards for heavy metals in organic fertilizers by predicting their concentrations in grains using machine leaning. A comprehensive dataset was collected from literature, including soil p...

Mediating effect of AI attitudes and AI literacy on the relationship between career self-efficacy and job-seeking anxiety.

BMC psychology
As artificial intelligence (AI) technology quickly grows, college students have new worries and fears. Using Marx's theory of labour alienation, this study explores the complex relationship between college students' job-seeking anxiety (JSA) and care...

Using Machine Learning to Predict Cognitive Decline in Older Adults From the Chinese Longitudinal Healthy Longevity Survey: Model Development and Validation Study.

JMIR aging
BACKGROUND: Cognitive impairment, indicative of Alzheimer disease and other forms of dementia, significantly deteriorates the quality of life of older adult populations and imposes considerable burdens on families and health care systems worldwide. T...