Results 251 to 260 of about 41,847 (353)

High‐Adhesion Quadruple Hydrogen‐Bonded Ionogels: A Dual‐Function Platform for Gesture Recognition and Real‐Time NH3 Detection in Multiscenario

open access: yesENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Quadruple hydrogen‐bonded high‐adhesion ionogels for gesture recognition and real‐time NH3 sensing. Ionogels have garnered significant attention in flexible sensing due to their outstanding mechanical properties, conductivity, and stability. However, establishing a robust and stable adhesive interface with various substrates remains a significant ...
Haohao Lin   +7 more
wiley   +1 more source

City Slicker or Country Bumpkin?—Distinguishing Urban and Rural Residents From Subtle Facial Cues

open access: yesEuropean Journal of Social Psychology, EarlyView.
ABSTRACT Stereotypes characterize urban and rural residents as differing in traits, values and social outcomes. Here, we examined how people's stereotypes about urban and rural residents differ, testing their validity using a lens model. Results showed that participants detected whether people resided in urban or rural areas from photos across three ...
McLean G. Morgan   +2 more
wiley   +1 more source

Construction ofa Sensing Platform Integrated witha CRISPR/Cas12a-Triggered Colorimetric Strategy for the QuantitativeDetection of Meat Freshness

open access: green
Junsheng Sheng (22303553)   +6 more
openalex   +1 more source

Distinctive genetic architecture of infantile epileptic spasms syndrome compared to self‐limited infantile epilepsy by trios whole‐exome sequencing

open access: yesEpilepsia Open, EarlyView.
Abstract Objective Infantile epileptic spasms syndrome (IESS) and self‐limited infantile epilepsy (SeLIE) are both genetically heterogeneous disorders during infancy with distinct prognoses. To better define the genetic spectrum of IESS, we performed a comparative genetic analysis using SeLIE cases as a reference group. Methods We performed whole‐exome
Yihong Sun   +6 more
wiley   +1 more source

Performance Monitoring of Photovoltaic Modules Using Machine‐Learning‐Based Solutions: A Survey of Current Trends

open access: yesEnergy Science &Engineering, EarlyView.
The graphical abstract presents the concept of applying machine‐learning algorithms to assess the performance of photovoltaic modules. Data from solar panels are fed to surrogates of intelligent models, to assess the following performance metrics: identifying faults, quantifying energy production and trend degradation over time. The combination of data
Nangamso Nathaniel Nyangiwe   +3 more
wiley   +1 more source

Home - About - Disclaimer - Privacy