Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1001/jamapediatrics.2024.6075 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Topology Design of Soft Phononic Crystals for Tunable Band Gaps: A Deep Learning Approach.
Materials (Basel)
January 2025
School of Mechanical and Electrical Engineering, Hainan University, Haikou 570228, China.
The phononic crystals composed of soft materials have received extensive attention owing to the extraordinary behavior when undergoing large deformations, making it possible to provide tunable band gaps actively. However, the inverse designs of them mainly rely on the gradient-driven or gradient-free optimization schemes, which require sensitivity analysis or cause time-consuming, lacking intelligence and flexibility. To this end, a deep learning-based framework composed of a conditional variational autoencoder and multilayer perceptron is proposed to discover the mapping relation from the band gaps to the topology layout applied with prestress.
View Article and Find Full Text PDFMachine learning to identify environmental drivers of phytoplankton blooms in the Southern Baltic Sea.
Sci Rep
January 2025
Institute for Chemistry and Biology of the Marine Environment, Carl von Ossietzky University Oldenburg, Oldenburg, Germany.
Phytoplankton blooms exhibit varying patterns in timing and number of peaks within ecosystems. These differences in blooming patterns are partly explained by phytoplankton:nutrient interactions and external factors such as temperature, salinity and light availability. Understanding these interactions and drivers is essential for effective bloom management and modelling as driving factors potentially differ or are shared across ecosystems on regional scales.
View Article and Find Full Text PDFLongitudinal Metabolomics Data Analysis Informed by Mechanistic Models.
Metabolites
December 2024
Department of Data Science and Knowledge Discovery, Simula Metropolitan Center for Digital Engineering, 0130 Oslo, Norway.
: Metabolomics measurements are noisy, often characterized by a small sample size and missing entries. While data-driven methods have shown promise in terms of analyzing metabolomics data, e.g.
View Article and Find Full Text PDFIntegrating machine learning with advanced processing and characterization for polycrystalline materials: a methodology review and application to iron-based superconductors.
Sci Technol Adv Mater
December 2024
JST-CREST, Saitama, Japan.
In this review, we present a new set of machine learning-based materials research methodologies for polycrystalline materials developed through the Core Research for Evolutionary Science and Technology project of the Japan Science and Technology Agency. We focus on the constituents of polycrystalline materials (i.e.
View Article and Find Full Text PDFPatent research in academic literature. Landscape and trends with a focus on patent analytics.
Front Res Metr Anal
January 2025
Institute for Future Initiatives, The University of Tokyo, Tokyo, Japan.
Patent analytics is crucial for understanding innovation dynamics and technological trends. However, a comprehensive overview of this rapidly evolving field is lacking. This study presents a data-driven analysis of patent research, employing citation network analysis to categorize and examine research clusters.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!