Consumer Behavior Toward Andean Grains Among Young Peruvian Adults: Purchase Patterns, Motivations, and Barriers Across Cultural Contexts. [PDF]
Millones-Liza DY +5 more
europepmc +1 more source
To enhance through‐thickness conductivity without sacrificing impregnation, large spherical graphite particles are intentionally employed in a low‐viscosity resin. Unlike finer conductive fillers, these particles remain outside the fiber bundles and accumulate in resin‐rich interlaminar regions during molding.
Keito Hosoe +6 more
wiley +1 more source
Consumer Preference and Willingness to Pay for Nutraceuticals to Prevent Cardiovascular Diseases in Thailand: A Discrete Choice Experiment. [PDF]
Rayanakorn A +3 more
europepmc +1 more source
Rotary 3D Printing With Integrated Electroplating
A rotary material extrusion platform integrates localized copper electroplating with printing and encapsulation to fabricate cylindrical polymer–metal structures containing fully embedded, low‐resistance conductive pathways that enable internal Joule heating and thermally activated shape‐memory responses.
Antonio Zagaria +5 more
wiley +1 more source
Determinants of public preference for orthodontic appliances and treatment providers: a scoping review. [PDF]
Jiang L +4 more
europepmc +1 more source
Consumer choice between common generic and brand medicines in a country with a small generic market. [PDF]
Fraeyman J +5 more
europepmc +1 more source
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
Healthy Food Corners as Spatial Nudges: Consumer Awareness, Perceived Necessity, and Design Preferences in Convenience Stores. [PDF]
Lee J, Park HJ, Moon S, Yeo G, Oh J.
europepmc +1 more source
Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose +7 more
wiley +1 more source

