Results 241 to 250 of about 182,933 (316)
A climate region classification for California's warm season: apparent temperature clustering to support heat-health epidemiology. [PDF]
Villanueva M +6 more
europepmc +1 more source
Identified through the use of statistical design of experiments and metallographic investigation, this study exposes the stochastic origins of intergranular cracks in blown powder laser beam directed energy deposition additive manufacturing of pure molybdenum. It further demonstrates a successful crack mitigation approach with direct correlation to the
Nathaniel J. Lies +2 more
wiley +1 more source
Axial Load Capacity Prediction of Concrete-Filled Steel Tubes Using Machine Learning: A Comparative Study. [PDF]
Chen B, He W, Huang L, Shi X.
europepmc +1 more source
Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
wiley +1 more source
Identifying Risk Groups in 401,846 Osteoarthritis Patients Undergoing Total Hip Arthroplasty: A Machine Learning Clustering Analysis. [PDF]
Ahmadi A +7 more
europepmc +1 more source
Multimodal Data‐Driven Microstructure Characterization
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source
A Commentary on "Impact of preoperative frailty on venous thromboembolism risk following total hip and knee arthroplasty: a meta-analysis". [PDF]
Jin W, Shi L, Huang L.
europepmc +1 more source

