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Articles

A BOA-LGBM framework driven by acoustic emission Mel-frequency cepstral coefficients for early identification of coal-rock fracture processes

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By Jingye Li, dong chen, Enyuan Wang
| Taylor & Francis Online
ABSTRACT Dynamic geotechnical hazards, such as rockbursts and coal–gas outbursts, threaten underground engineering safety. Accurate identification of coal–rock fracture processes is therefore essential for hazard monitoring and early warning. This study proposes an acoustic-emission-based identification framework integrating Mel-frequency cepstral coefficients (MFCCs) with time-domain features.
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Plasma proteomics framework predicts metabolic dysfunction-associated steatotic liver disease up to 16 years before onset

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By Shiyi Yu, Chunling Chen, Jing Feng, Qinming Li, Shuo Chen, Ruijie Zeng, Dongling Luo, Wentao Huang, Kexin Zhang, Yuying Ma, Lijun Zhang, Meijun Meng, Yanjun Wu, dong chen, Qizhou Lian, Felix Leung, Weihong Sha, Hao Chen, Chusi Wang
| Nature Verified
Abstract Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global health challenge, yet preclinical identification remains difficult owing to a lack of reliable predictive tools. Here we show that a panel of five plasma proteins, FUOM, ACY1, KRT18, CDHR2 and GGT1, identified and validated across over 50,000 participants from the Southern UK, Northern UK, EPIC-Norfolk and Southern China cohorts, serves as a predictive signature for incident MASLD.
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As US AI costs soar, global businesses pivot to China's low-cost, open-weight models

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By dong chen
| msn.com
Xinmei Shen A sharp narrowing of the performance gap is prompting some developers to shift from costly American giants to budget-friendly Chinese alternatives Global businesses are increasingly switching from premium, closed-source US software - such as OpenAI 's GPT and Anthropic's Claude - to cheaper Chinese open-weight models that offer near-frontier performance.
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