Results 231 to 240 of about 1,296,306 (327)

Student Efforts in Rural Areas to Face Problems Nahwu Mobile Learning Online

open access: diamond, 2022
Ade Destri Deviana   +4 more
openalex   +2 more sources

3D Printing of Stretchable, Compressible and Conductive Porous Polyurethane for Soft Robotics

open access: yesAdvanced Materials Technologies, EarlyView.
A 3D‐printable porous dopamine‐polyurethane acrylate elastomer results in conductive, stretchable, and compressible structures that can be metallized in situ through catechol‐mediated silver reduction. The resulting material function as both compliant soft robot with a and strain sensors without complex assemblies, enabling fully 3D‐printed soft ...
Ouriel Bliah   +3 more
wiley   +1 more source

Determinants affecting the medical students adoption of mobile learning: extended UTAUT. [PDF]

open access: yesBMC Med Educ
Suliman MAE   +4 more
europepmc   +1 more source

MOBILE-ASSISTED SECOND LANGUAGE LEARNING: DEVELOPING A LEARNER-CENTERED FRAMEWORK

open access: gold, 2014
Choy Khim Leow   +2 more
openalex   +1 more source

Cap‐oPMN: Oral Inflammatory Load Quantification Using Capillary Microfluidics and Automated Image Processing

open access: yesAdvanced Materials Technologies, EarlyView.
ABSTRACT Quantifying oral polymorphonuclear neutrophils (oPMNs) is a clinically validated approach for assessing periodontal inflammation. However, current methods, such as manual hemocytometry and flow cytometry, are time‐consuming (>3 h), require invasive sampling, and depend on staining and complex instrumentation, making them unsuitable for point ...
Mohsen Hassani   +9 more
wiley   +1 more source

Adhesive Double‐Network Granular Organogel E‐Skin

open access: yesAdvanced Materials Technologies, EarlyView.
We introduce a double‐network granular organogel adhesive for electronic skin, overcoming adhesion and strength trade‐offs. It provides reversible, robust bonding and ionic conductivity, enabling wearable and soft robotic e‐skin. Thanks to the e‐skin adhesive, a soft robotic trunk can recognize touch, temperature, humidity, and acidity.
Antonia Georgopoulou   +4 more
wiley   +1 more source

Adoption of mobile learning in the university context: Systematic literature review. [PDF]

open access: yesPLoS One
Valencia-Arias A   +4 more
europepmc   +1 more source

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