Results 191 to 200 of about 158,513 (260)
Gene Target Prediction of Environmental Chemicals Using Coupled Matrix-Matrix Completion. [PDF]
Wang K +7 more
europepmc +1 more source
A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora +4 more
wiley +1 more source
Modeling longitudinal data using matrix completion. [PDF]
Kidziński Ł, Hastie T.
europepmc +1 more source
Geometry‐driven thermal behavior in wire‐arc additive manufacturing (WAAM) influences microstructural evolution during nonequilibrium solidification of a chemically complex Fe–Cr–Nb–W–Mo–C nanocomposite system. By comparing different deposits configurations, distinct entropy–cooling rate correlations, segregation, and carbide evolution are revealed ...
Blanca Palacios +5 more
wiley +1 more source
The impact of the European Union emissions trading system on carbon dioxide emissions: a matrix completion analysis. [PDF]
Biancalani F +3 more
europepmc +1 more source
Low‐temperature imidization of PEG‐modified polyimide enables fully screen‐printed, roll‐to‐roll fabrication of flexible electrodes on PET substrates, delivering robust mechanical durability and reliable ECG/EMG signal performance for wearable electronics.
Akib Abdullah Khan, Jong‐Hoon Kim
wiley +1 more source
ANS-SCMC: A matrix completion method based on adaptive neighbourhood similarity and sparse constraints for predicting microbe-disease associations. [PDF]
Wen H, Zhong X, Lin L, Chen L.
europepmc +1 more source
Mg–Zn composites with a thickness of 0.21 mm were fabricated using roll bonding of a kirigami‐patterned Mg alloy inlay within a Zn matrix. Thermal activation following this process led to the formation of tailored intermetallic structures, which provided the composite with enhanced flexural strength.
Yaroslav Frolov +4 more
wiley +1 more source
Meta-learning-based Inductive logistic matrix completion for prediction of kinase inhibitors. [PDF]
Du M, Xie X, Luo J, Li J.
europepmc +1 more source

