Mental fatigue impairs endurance performance in a time-to-exhaustion handgrip task: psychophysiological markers of effort engagement dynamics. [PDF]
Daneshgar-Pironneau S +4 more
europepmc +1 more source
A combinatorial library of dual‐functional antiviral oligomers incorporating N‐halamine and quaternary ammonium functionalities is developed for long‐lasting antiviral activity. The lead materials exhibit rapid and durable antiviral activity against SARS‐CoV‐2 variants and influenza H1N1, with 4 to 5 log reduction in viral copies at 5 mg mL−1 ...
Eid Nassar‐Marjiya +14 more
wiley +1 more source
Development and validation of a serial album on pregnancy for expectant mothers and healthcare professionals. [PDF]
Medeiros LDS +5 more
europepmc +1 more source
Controlled syntheses of lanthanide coordination polymers based on the dihydroxybenzoquinone (DHBQ) organic linker afforded large single crystals of Ln‐DHBQ CPs (Ln = Yb, Nd). A novel structural variant of Yb‐DHBQ is identified by means of single crystal diffraction analysis.
Marina I. Schönherr +7 more
wiley +1 more source
Between Suicide and Regret: Media Representations of Gender-Affirming Care for Transgender and Gender Diverse Youth. [PDF]
Linander I, Lauri J.
europepmc +1 more source
STON efficient subtitling in Dutch using state-of-the-art tools [PDF]
Demuynck, Kris +5 more
core
MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance
Metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) hold promise for advanced electronics. However, discrepancies in reported electrical conductivities highlight the importance of measurement methodologies. This review explores intrinsic charge transport mechanisms and extrinsic factors influencing performance, and critically ...
Jonas F. Pöhls, R. Thomas Weitz
wiley +1 more source
Systematic review of global historical marine ecology reveals geographical and taxonomic research gaps and biases. [PDF]
Del Valle E +4 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
Occupational health content in Spanish undergraduate nursing degrees: a nationwide cross-sectional study. [PDF]
Romero-Collado A +4 more
europepmc +1 more source

