Results 131 to 140 of about 230,619 (245)

Motivational dynamics in technology-enhanced learning: a parsimonious model of self-efficacy, ICT use, and mathematics achievement. [PDF]

Front Psychol
Zhang Q, Zhou Q, Song M.
europepmc   +1 more source

Recomposable Layered Metasurfaces for Wavelength‐Multiplexed Optical Encryption via Modular Diffractive Deep Neural Networks

Advanced Functional Materials, EarlyView.
Modular diffractive deep neural network metasurfaces encode and reconstruct holograms across layer combinations and wavelengths, enabling secure, multifunctional operation. Each layer acts independently yet composes jointly, yielding up to m(2N −1) channels for m wavelengths and N layers.
Cherry Park, Youngsun Jeon, Seokho Lee, Yeseul Kim, Junsuk Rho   +4 more
wiley   +1 more source

Deep learning-based multi-criteria recommender system for technology-enhanced learning. [PDF]

Sci Rep
Salau L, Mohamed H, Abdulsalam YS, Mohammed H.   +3 more
europepmc   +1 more source

Perception of Technology-Enhanced Learning by Medical Students: an Integrative Review. [PDF]

Med Sci Educ, 2020
Plch L.
europepmc   +1 more source

Enhancing Synaptic Plasticity and Multistate Retention of Organic Neuromorphic Devices Using Anion‐Excessive Gel Electrolyte

Advanced Functional Materials, EarlyView.
Anion‐excessive gel‐based organic synaptic transistors (AEG‐OSTs) that can maintain electrical neutrality are developed to enhance synaptic plasticity and multistate retention. Key improvement is attributed to the maintenance of electrical neutrality in the electrolyte even after electrochemical doping, which reduces the Coulombic force acting on ...
Yousang Won, Jeongwoo Lee, Hyunwook Kim, Joon Hak Oh   +3 more
wiley   +1 more source

Advancing Medical Education: Assessing Technology-Enhanced Learning Through the Lens of the Canadian Medical Education Directions for Specialists (CanMEDS) Framework-A Perspective Study. [PDF]

Health Sci Rep
Asadi M, Karimian Z.
europepmc   +1 more source

PRELIVE: A Framework for Predicting Lipid Nanoparticles In Vivo Efficacy and Reducing Reliance on Animal Testing

Advanced Functional Materials, EarlyView.
PREdicting LNP In Vivo Efficacy (PRELIVE) framework enables the prediction of lipid nanoparticle (LNPs) organ‐specific delivery through dual modeling approaches. Composition‐based models using formulation parameters and protein corona‐based models using biological fingerprints both achieve high predictive accuracy across multiple organs.
Belal I. Hanafy, Chuan‐En Lu, Kai Liu, Audrey Gallud   +3 more
wiley   +1 more source

Universal Electronic‐Structure Relationship Governing Intrinsic Magnetic Properties in Permanent Magnets

Advanced Functional Materials, EarlyView.
Permanent magnets derive their extraordinary strength from deep, universal electronic‐structure principles that control magnetization, anisotropy, and intrinsic performance. This work uncovers those governing rules, examines modern modeling and AI‐driven discovery methods, identifies critical bottlenecks, and reveals electronic fingerprints shared ...
Prashant Singh
wiley   +1 more source

Putting ICAP to the test: how technology-enhanced learning activities are related to cognitive and affective-motivational learning outcomes in higher education. [PDF]

Sci Rep
Wekerle C, Daumiller M, Janke S, Dickhäuser O, Dresel M, Kollar I.   +5 more
europepmc   +1 more source

Designing Asymmetric Memristive Behavior in Proton Mixed Conductors for Neuromorphic Applications

Advanced Functional Materials, EarlyView.
Protonic devices that couple ionic and electronic transport are demonstrated as bioinspired neuromorphic elements. The devices exhibit rubber‐like asymmetric memristive behavior with slow voltage‐driven conductance increase and rapid relaxation, enabling simplified read–write operation.
Nada H. A. Besisa, Masaki Tsuji, Yoshihiro Furue, Yifan Geng, Satya P. Pati, Satoshi Hamasuna, Takeaki Yajima   +6 more
wiley   +1 more source