The Beta-Jacobi Matrix Model, the CS Decomposition, and Generalized Singular Value Problems [PDF]
Alan Edelman, Brian Sutton
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Recycling of Thermoplastics with Machine Learning: A Review
This review shows how machine learning is revolutionizing mechanical, chemical, and biological pathways, overcoming traditional challenges and optimizing sorting, efficiency, and quality. It provides a detailed analysis of effective feature engineering strategies and establishes a forward‐looking research agenda for a truly circular thermoplastic ...
Rodrigo Q. Albuquerque +5 more
wiley +1 more source
Protocol for unsupervised inference of cell-cell communication using matrix decomposition. [PDF]
Liu Y, Chang X, Liu X.
europepmc +1 more source
Clutter suppression in ultrasound: performance evaluation and review of low-rank and sparse matrix decomposition methods. [PDF]
Zhang N, Ashikuzzaman M, Rivaz H.
europepmc +1 more source
A Polynomial Matrix QR Decomposition with Application to MIMO Channel Equalisation [PDF]
Joanne Foster +2 more
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A scalable biomimetic platform transforms bioinert poly(ethylene glycol) diacrylate into neuroinstructive matrices via integrating solvent transfer‐induced phase separation, microfluidics, and 3D bioprinting. Bicontinuous, hyperbolically curved microporous networks embedded within a fibrous construct elicit rapid adhesion, robust proliferation, and ...
Prince D. Okoro +8 more
wiley +1 more source
INSIDER: Interpretable sparse matrix decomposition for RNA expression data analysis. [PDF]
Zhao K +5 more
europepmc +1 more source
Closed orbit correction using singular value decomposition of the response matrix
Y. Chung, G. Decker, K. Evans
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Advances in Micro/Nanofiber‐Based Porous Materials for High‐Performance Thermal Insulation
Micro/nanofiber porous materials have engendered great interest in the thermal insulation field. Herein, the structural designs, fabrication techniques, and applications of the micro/nanofiber thermal insulation materials are systematically summarized.
Xiaobao Gong +5 more
wiley +1 more source
Posterior Approximate Clustering-Based Sensitivity Matrix Decomposition for Electrical Impedance Tomography. [PDF]
Wang Z, Sun Y, Li J.
europepmc +1 more source

