Results 181 to 190 of about 238,744 (335)
Waveguide Photoactuators: Materials, Fabrication, and Applications
Waveguide photoactuators convert guided light into mechanical motion. Their tethered‐flexible design enables minimally invasive surgery and confined‐space robotics. This review aims to guide materials selection, device design, and system integration, accelerating the transition of waveguide photoactuators from laboratory prototypes to versatile ...
Minjie Xi +4 more
wiley +1 more source
The C2H2-type zinc finger protein SlHair5 acts as a regulatory node coordinating trichome development and leaf morphogenesis in tomato. [PDF]
Kim SM +5 more
europepmc +1 more source
Numerical Modeling of Photothermal Self‐Excited Composite Oscillators
We present a numerical framework for simulating photothermal self‐excited oscillations. The driving mechanism is elucidated by highlighting the roles of inertia and overshoot, as well as the phase lag between the thermal moment and the oscillation angle, which together construct the feedback loop between the system state and the environmental stimulus.
Zixiao Liu +6 more
wiley +1 more source
TDS-YOLO: a lightweight detection model for fine-grained segmentation of tea leaf diseases. [PDF]
Xie Q, Wang T, Zu W, Jusoh YY, Jia L.
europepmc +1 more source
Origami‐Inspired Structural Design for Aquatic‐Terrestrial Amphibious Robots
This work presents a lightweight amphibious origami robot actuated by a single shape memory alloy wire. A rigid foldable origami structure with displacement amplification enables efficient terrestrial crawling and aquatic swimming. The addition of fan‐shaped units allows controllable turning in both environments.
Weiqi Liu +5 more
wiley +1 more source
ZamYOLO-maize: a YOLOv8n-based deep learning framework for automated detection and classification of maize leaf diseases in field conditions in Zambia. [PDF]
Kalunga P, Kunda D, Zimba A.
europepmc +1 more source
Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling
A simulation‐driven framework for autonomous bulldozer leveling is presented, combining high‐fidelity terramechanics simulation with a neural‐network‐based reduced‐order model. Gradient‐based optimization enables efficient, low‐level blade control that balances leveling quality and operation time.
Harry Zhang +5 more
wiley +1 more source

