Results 151 to 160 of about 3,413,435 (251)
President approved minutes of the 2012 Association for Learning Technology AGM [PDF]
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Molecular engineering of a nonconjugated radical polymer enables a significant enhancement of the glass transition temperature. The amorphous nature and tunability of the polymer, arising from its nonconjugated backbone, facilitates the fabrication of organic memristive devices with an exceptionally high yield (>95%), as well as substantial ...
Daeun Kim +14 more
wiley +1 more source
The issue - Vol. 13, n.2, 2017
Nicola Villa
doaj +1 more source
Associations Among Depression, Self-Compassion, and Learning Burnout in Nursing Students: A Three-Wave Longitudinal Study. [PDF]
Wang Q, Cao X, Du T.
europepmc +1 more source
Chemoselective Sequential Polymerization: An Approach Toward Mixed Plastic Waste Recycling
Inspired by biological protein metabolism, this study demonstrates the closed‐loop recycling of mixed synthetic polymers via ring‐closing depolymerization followed by a chemoselective sequential polymerizations process. The approach recovers pure polymers from mixed feedstocks, even in multilayer formats, highlighting a promising strategy to overcome a
Gadi Slor +5 more
wiley +1 more source
Linking childhood adversity with borderline and depressive symptoms: the role of reward processing. [PDF]
Oltean LE +3 more
europepmc +1 more source
Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha +18 more
wiley +1 more source
Connecting the Dots: Associative Transfer and Inference at 6 Months of Age. [PDF]
Townsend DA, Learmonth AE, Cuevas K.
europepmc +1 more source
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee +17 more
wiley +1 more source

