Results 221 to 230 of about 4,673,408 (346)

Shaping Microbial Motion with Light: A Contactless Approach Using Diffusioosmotic Flow

open access: yesAdvanced Materials Interfaces, EarlyView.
Light‐controlled, contactless manipulation of cyanobacteria using photoresponsive azobenzene surfactants. Reversible photo‐isomerization generates surface flow, enabling precise trapping, relocation, and directional control of single cells or ensembles with adjustable light intensity and wavelength for noninvasive, spatiotemporally resolved microbial ...
Maren Umlandt   +5 more
wiley   +1 more source

Printed Interconnects for Heterogeneous Systems Integration on Flexible Substrates

open access: yesAdvanced Materials Technologies, Volume 10, Issue 6, March 18, 2025.
Key components (sensors, energy devices, communication devices, computing chips, and interconnects) of flexible hybrid electronic (FHE) system connected via conductive printed metal tracks. The figure in the insets shows out‐of‐plane printed interconnects providing opportunities for lithography‐free formation of VIAs, in‐plane access of UTCs pads, and ...
Abhishek Singh Dahiya   +3 more
wiley   +1 more source

REMOTE PATIENT MONITORING FOR VADs AND OTHER IMPLANTABLE DEVICES

open access: bronze, 2000
Tofy Mussivand   +2 more
openalex   +1 more source

Remote Query Resonant-Circuit Sensors for Monitoring of Bacteria Growth: Application to Food Quality Control [PDF]

open access: gold, 2002
Keat Ghee Ong   +4 more
openalex   +1 more source

Remote Reactor Monitoring

open access: yes, 2014
Steve Dazeley   +7 more
openaire   +3 more sources

AI‐Enhanced Gait Analysis Insole with Self‐Powered Triboelectric Sensors for Flatfoot Condition Detection

open access: yesAdvanced Materials Technologies, Volume 10, Issue 6, March 18, 2025.
The given research presents an innovative insole‐based device employing self‐powered triboelectric nanogenerators (TENG) for flatfoot detection. By integrating TENG tactile sensors within an insole, the device converts mechanical energy from foot movements to electrical signals analyzed via machine learning, achieving an 82% accuracy rate in flatfoot ...
Moldir Issabek   +7 more
wiley   +1 more source

AI-Powered Remote Monitoring for Lower Extremity Wound Management: A Randomized Controlled Trial Protocol. [PDF]

open access: yesJVS Vasc Insights
Wu YHA   +8 more
europepmc   +1 more source

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