Results 221 to 230 of about 23,571 (300)

Microbe-disease associations prediction by graph regularized non-negative matrix factorization with $$ {L}_{2,1} $$ norm regularization terms. [PDF]

J Cell Mol Med
Chen Z, Zhang L, Li J, Chen H.
europepmc   +1 more source

Influence of Surface Finish on the Tribological Performance of AlTiBN Coatings Deposited on Forming Tools

Advanced Engineering Materials, EarlyView.
Aluminum and nitride coatings are used in industry because they are hard, resist wear, and protect against oxidation. Adding boron can improve friction behavior and other properties. This study tests coatings on surfaces with different finishes. Results show smoother surfaces perform better, while rough ones wear faster, although coatings can reduce ...
Adrián Claver, Iker Alfonso, Eneko Barba, Javier León, José Antonio García, Iñaki Zalakain, Iván Fernández Martínez, Arley García‐Carrero, Christian Almeyda, Daniel Salcedo   +9 more
wiley   +1 more source

Unsupervised learning of spatially-resolved ARPES spectra for epitaxially grown graphene via non-negative matrix factorization. [PDF]

Sci Rep
Imamura M, Takahashi K.
europepmc   +1 more source

From Shear to Sound: Mechanics–Acoustics Mapping of TPMS Lattices

Advanced Engineering Materials, EarlyView.
Triply periodic minimal surface (TPMS) lattices are mapped across mechanical and acoustic performance, revealing that descriptors validated in compression fail under shear. First‐time comparison with trusses included. A transition from porous to resonance‐driven absorption emerges at 25% density.
Lucía Doyle, María Ángeles Navacerrada, Johan Christensen, Carlos González   +3 more
wiley   +1 more source

Separation and Extraction of Compound-Fault Signal Based on Multi-Constraint Non-Negative Matrix Factorization. [PDF]

Entropy (Basel)
Wang M, Zhang W, Shao M, Wang G.
europepmc   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Retraction notice to "Non-negative matrix factorization model-based construction for molecular clustering and prognostic assessment of head and neck squamous carcinoma" [Heliyon 8 (2022) e10100]. [PDF]

Heliyon
Li XY, An HB, Zhang LY, Liu H, Shen YC, Yang XT.   +5 more
europepmc   +1 more source

Active Corrosion Protection of Sintered AA7075 Aluminum Alloy via Mn Powder Addition

Advanced Engineering Materials, EarlyView.
AA7075 containing Mn‐rich particles is fabricated via spark plasma sintering using AA7075 and Mn powders. Corrosion resistance is evaluated through dip‐and‐dry tests using 0.1 M NaCl (pH 6.0), and mass loss decreases with increasing Mn addition. Mn‐rich particles function as a source of Mn ions, and formation of Mn‐accumulation films on Cu‐containing ...
Ko Ebina, Masashi Nishimoto, Izumi Muto
wiley   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

scRNMF: An imputation method for single-cell RNA-seq data by robust and non-negative matrix factorization. [PDF]

PLoS Comput Biol
Qian Y, Zou Q, Zhao M, Liu Y, Guo F, Ding Y.   +5 more
europepmc   +1 more source