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A Systematic Review and Meta-Analysis of Sodium-Glucose Cotransporter 2 (SGLT-2) Inhibitors and Their Impact on the Management of Heart Failure.
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Acute Medicine, Mid and South Essex NHS Foundation Trust, Southend-on-Sea, GBR.
Heart failure (HF) is a life-threatening condition with severe incapacitating consequences. Many body organs and systems may be affected, which may also hinder the quality of life and finances at the individual and societal levels. Sodium-glucose cotransporter-2 inhibitors (SGLT2i) have also emerged as potentially useful drugs in the HF domain and other medical fields, in addition to their glucose-lowering effect.
View Article and Find Full Text PDFDecoupling many-body interactions in the CeO(111) oxygen vacancy structure with statistical learning and cluster expansion.
Nanoscale
January 2025
Photon Science Research Center for Carbon Dioxide, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China.
Oxygen vacancies (V's) are of paramount importance in influencing the properties and applications of ceria (CeO). Yet, comprehending the distribution and nature of V's poses a significant challenge due to the vast number of electronic configurations and intricate many-body interactions among V's and polarons (Ce ions). In this study, we established a cluster expansion model based on first-principles calculations and statistical learning to decouple the interactions among the Ce ions and V's, thereby circumventing the limitations associated with sampling electronic configurations.
View Article and Find Full Text PDFStrategic Integration of Machine Learning in the Design of Excellent Hybrid Perovskite Solar Cells.
J Phys Chem Lett
January 2025
College of Chemistry and Materials Science, Hebei University, Baoding 071002, P. R. China.
The photoelectric conversion efficiency (PCE) of perovskites remains beneath the Shockley-Queisser limit, despite its significant potential for solar cell applications. The present focus is on investigating potential multicomponent perovskite candidates, particularly on the application of machine learning to expedite band gap screening. To efficiently identify high-performance perovskites, we utilized a data set of 1346 hybrid organic-inorganic perovskites and employed 11 machine learning models, including decision trees, convolutional neural networks (CNNs), and graph neural networks (GNNs).
View Article and Find Full Text PDFStructural Origin of Dynamic Heterogeneity in Supercooled Liquids.
J Phys Chem B
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Research Center for Advanced Science and Technology, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904, Japan.
As a liquid is supercooled toward the glass transition point, its dynamics slow significantly, provided that crystallization is avoided. With increased supercooling, the particle dynamics become more spatially heterogeneous, a phenomenon known as dynamic heterogeneity. Since its discovery, this characteristic of metastable supercooled liquids has garnered considerable attention in glass science.
View Article and Find Full Text PDFGenerative Modeling of Nucleon-Nucleon Interactions.
Phys Rev Lett
December 2024
Cornell University, Ithaca, New York 14853, USA.
Article Synopsis
- The study addresses the challenges of creating precise models for the nuclear force and managing uncertainties in quantum many-body calculations, which are crucial for understanding nuclei and nuclear matter.
- Researchers use generative machine learning to develop new nucleon-nucleon interaction instances by training on existing potential data from literature.
- The generative model successfully creates nucleon-nucleon potentials that yield high-quality scattering phase shifts, aiding in better estimation of theoretical uncertainties in nuclear calculations related to different nuclear interactions and resolution scales.
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