Results 291 to 300 of about 13,725,960 (359)
This study analyzes 398 432 participants, identifying four distinct metabolic‐inflammatory subtypes. These subtypes show a significant association with digestive disease risk. Cluster‐associated metabolite signatures partially explain this link. Machine learning models using these metabolites accurately predict risk for ten digestive diseases. Key risk
Zhenhe Jin +10 more
wiley +1 more source
Real‐time and accurate monitoring of battery surface temperature is widely recognized as essential for ensuring operational safety. By synergistically combining high‐resolution sensing‐interrogation systems, optimized DOFS deployment scheme, and intelligent reconstruction algorithms, this study achieves full‐range and high‐fidelity temperature field ...
Yuhao Zhu +6 more
wiley +1 more source
The study proposes a universal strategy for the synthesis of high‐performance vanadium‐based PBAs (V‐PBAs) cathodes for aluminum ion batteries. It is find that the doped transition metals (Fe/Co/Ni) at carbon‐coordinated sites can markedly enhance the multi‐electron redox activity and inhibit the V dissolution, structural collapse, and other ...
Wanchang Feng +14 more
wiley +1 more source
Coastal dissolved organic carbon (DOC) represents one of the largest reduced carbon pools on Earth, and they are influenced by temperature. Across 7.6–35.9 °C ranges, the microbial‐mediated DOC dynamics is characterized by three temperature thresholds.
Junfu Dong +12 more
wiley +1 more source
Cytological Classification Diagnosis for Thyroid Nodules via Multimodal Model Deep Learning
This study introduces AI‐TFNA, an innovative artificial intelligence model designed to assist cytopathologists in classifying thyroid nodules based on The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC). The model effectively differentiates between benign and malignant thyroid nodules, demonstrating significant potential as a screening ...
Yuanzheng Lou +27 more
wiley +1 more source
Highly Efficient Discovery of 3D Mechanical Metamaterials via Monte Carlo Tree Search
Machine learning (ML), as a data‐driven method, has revolutionized metamaterial design, surpassing traditional intuition‐driven trial‐and‐error methods in both efficiency and performance. Here, MCTS‐AL, an active learning framework integrating finite element simulation (FEM), convolutional neural networks (CNNs), and Monte Carlo Tree Search (MCTS ...
Jiamu Liu +4 more
wiley +1 more source
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An Evidence‐Based Rationale for Adopting Weight‐Inclusive Health Policy
Social Issues and Policy Review, 2020Health policies routinely emphasize weight loss as a target for health promotion. These policies rest upon the assumptions: (1) that higher body weight equals poorer health, (2) that long-term weight loss is widely achievable, and (3) that weight loss ...
J. Hunger, Joslyn P. Smith, A. Tomiyama
semanticscholar +1 more source
Mental Health Policy in the Era of COVID-19.
Psychiatric Services, 2020The response to the global COVID-19 pandemic has important ramifications for mental health systems and the patients they serve. This article describes significant changes in mental health policy prompted by the COVID-19 crisis across five major areas ...
Matthew L. Goldman +11 more
semanticscholar +1 more source

