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Platanus occidentalis L. fruit-derived carbon materials for electrochemical potassium storage.
Nanotechnology
January 2025
Chemistry, University College London, 20 Gordon Street, London, WC1H 0AJ, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.
In the post-lithium-ion battery era, potassium-ion batteries (PIBs) have been considered as a promising candidate because of their electrochemical and economic characteristics. However, as an emerging electrochemical storage technology, it is urgent to develop capable anode materials that can be produced at low cost and on a large scale to promote its practical application. Biomass-derived carbon materials as anodes of PIBs exhibit strong competitiveness by their merits of low weight, high stability, non-toxicity, and wide availability.
View Article and Find Full Text PDFUS Corn Belt enhances regional precipitation recycling.
Proc Natl Acad Sci U S A
January 2025
Research Applications Laboratory, NSF National Center for Atmospheric Research, Boulder, CO 80301.
Precipitation recycling, where evapotranspiration (ET) from the land surface contributes to precipitation within the same region, is a critical component of the water cycle. This process is especially important for the US Corn Belt, where extensive cropland expansions and irrigation activities have significantly transformed the landscape and affected the regional climate. Previous studies investigating precipitation recycling typically relied on analytical models with simplifying assumptions, overlooking the complex interactions between groundwater hydrology and agricultural management.
View Article and Find Full Text PDFANAC044 orchestrates mitochondrial stress signaling to trigger iron-induced stem cell death in root meristems.
Proc Natl Acad Sci U S A
January 2025
Ministry of Education Key Laboratory of Environment Remediation and Ecological Health, Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China.
While iron (Fe) is essential for life and plays important roles for almost all growth related processes, it can trigger cell death in both animals and plants. However, the underlying mechanisms for Fe-induced cell death in plants remain largely unknown. S-nitrosoglutathione reductase (GSNOR) has previously been reported to regulate nitric oxide homeostasis to prevent Fe-induced cell death within root meristems.
View Article and Find Full Text PDFQwen-2.5 Outperforms Other Large Language Models in the Chinese National Nursing Licensing Examination: Retrospective Cross-Sectional Comparative Study.
JMIR Med Inform
January 2025
Department of Science and Education, Shenzhen Baoan Women's and Children's Hospital, Shenzhen, China.
Background: Large language models (LLMs) have been proposed as valuable tools in medical education and practice. The Chinese National Nursing Licensing Examination (CNNLE) presents unique challenges for LLMs due to its requirement for both deep domain-specific nursing knowledge and the ability to make complex clinical decisions, which differentiates it from more general medical examinations. However, their potential application in the CNNLE remains unexplored.
View Article and Find Full Text PDFThe role of chromatin state in intron retention: A case study in leveraging large scale deep learning models.
PLoS Comput Biol
January 2025
Department of Computer Science, Colorado State University, Fort Collins, Colorado, United States of America.
Complex deep learning models trained on very large datasets have become key enabling tools for current research in natural language processing and computer vision. By providing pre-trained models that can be fine-tuned for specific applications, they enable researchers to create accurate models with minimal effort and computational resources. Large scale genomics deep learning models come in two flavors: the first are large language models of DNA sequences trained in a self-supervised fashion, similar to the corresponding natural language models; the second are supervised learning models that leverage large scale genomics datasets from ENCODE and other sources.
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