Results 211 to 220 of about 2,407,326 (339)
Steep‐Switching Memory FET for Noise‐Resistant Reservoir Computing System
We demonstrate the steep‐switching memory FET with CuInP2S6/h‐BN/α‐In2Se3 heterostructure for application in noise‐resistant reservoir computing systems. The proposed device achieves steep switching characteristics (SSPGM = 19 mV/dec and SSERS = 23 mV/dec) through stabilization between CuInP2S6 and h‐BN.
Seongkweon Kang+6 more
wiley +1 more source
Theoretical models to guide undergraduate medical curriculum development: an integrative review. [PDF]
Yin X+5 more
europepmc +1 more source
This work presents a high‐entropy doped NaV0.95 (Fe, Mn, Ni, Al, Ca)0.05PO4F cathode, which enables the whole utilization of Na ions, enhances the reaction kinetics without carbon coating, and realizes a solid‐solution reaction mechanism with a single‐crystal structure.
Yingkai Hua+10 more
wiley +1 more source
Developing a male-specific counselling curriculum for HIV treatment in Malawi. [PDF]
Mphande M+9 more
europepmc +1 more source
Electromagnetic interference (EMI) shields consisting of polylactic acid (PLA) in layers with different concentrations of multiwalled carbon nanotubes (MWCNT) are produced using additive manufacturing. The permittivity function of layers with different filler concentrations is learned using data of homogeneous and randomly ordered shields.
Stijn De Smedt+5 more
wiley +1 more source
Preparing for cognitive behavioural therapy: a Delphi exercise to develop a consensus curriculum. [PDF]
Turtle L+4 more
europepmc +1 more source
2D Borophene: In‐Plane Hyperbolic Polaritons in the Visible Spectral Range
Researchers have synthesized the χ3 phase of borophene, a 2D metal, using chemical vapor deposition. Combining theory and deep‐subwavelength spectroscopy, they uncover borophene's unique anisotropic optical behavior in the visible range. This breakthrough paves the way for advanced optoelectronic devices using borophene‐based heterostructures ...
Yaser Abdi+5 more
wiley +1 more source
Integration of early clinical exposure into curriculum enhances self-assessment of professional competencies in medical practice. [PDF]
Oshiro T+10 more
europepmc +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore+7 more
wiley +1 more source