This study introduces a reliability assessment methodology for high grade steel large diameter natural gas pipelines, which systematically accounts for the correlations and nonlinear coupling effects among the defects. The proposed method effectively reflects realistic risk levels in pipelines with multiple defects.

New research demonstrates that ball milling under nitrogen atmosphere significantly improves the catalytic activity of siderite-biochar composites, enabling efficient degradation of phenol in water.

The study, titled "Machine Learning Technique for Carbon Sequestration Estimation of Mango Orchards Area Using Sentinel-2 Data," is led by Prof. Sittichai Choosumrong from the Department of Natural Resources and Environment at Naresuan University in Phitsanulok Province, Thailand, and Prof. Tatsuya Nemoto from the Graduate School of Science at Osaka Metropolitan University in Osaka, Japan. This research offers a detailed analysis of how machine learning can enhance our understanding of carbon sequestration in agricultural landscapes.

Biochar, a carbon-rich material made from organic waste, is gaining attention for its ability to improve soils, clean water, and capture carbon. A new review in Biochar X highlights how machine learning (ML) is reshaping biochar research, making it faster, smarter, and more effective in tackling climate change.