Results 251 to 260 of about 41,847 (353)
Nanofiber-Enabled Rapid and Non-Destructive Sensors for Meat Quality and Shelf-Life Monitoring: A Review. [PDF]
Ramachandraiah K, Martin EM, Limayem A.
europepmc +1 more source
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
Electrospun Nanofiber Platforms for Advanced Sensors in Livestock-Derived Food Quality and Safety Monitoring: A Review. [PDF]
Ramachandraiah K, Martin EM, Limayem A.
europepmc +1 more source
City Slicker or Country Bumpkin?—Distinguishing Urban and Rural Residents From Subtle Facial Cues
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
Preparation and characterization of ultrasound-mediated Ocimum basilicum L. essential oil nanoemulsion and its application in meat preservation. [PDF]
Wang Y +8 more
europepmc +1 more source
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
Development and Evaluation of a BCG/BCP-Based Cellulose Acetate Freshness Indicator for Beef Loin During Cold Storage. [PDF]
Lim KJ, Kim JS, Heo YJ, Shin HS.
europepmc +1 more source
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

