Results 161 to 170 of about 3,265,059 (298)
From conflict to collaboration: how local natural resource management conventions foster peacebuilding between farmers and herders in central Mali. [PDF]
Ba B, Affognon H, Flintan F.
europepmc +1 more source
Permanent magnet putty (PMP) integrates high‐coercivity NdFeB particles with a dynamic polyborosiloxane–Ecoflex matrix, achieving rapid self‐healing (90% mechanical recovery in 10 s) and magnetic recovery within 20 min. With twice the sensitivity of commercial putties, PMP enables precise 5–30 N force detection and discrimination between pressing and ...
Ruotong Zhao +5 more
wiley +1 more source
Study on Water Seepage Characteristics of Coal under Triaxial Stress Based on Computed Tomography Reconstruction and Three-Dimensional Printing. [PDF]
Cui S, Chu X, Liu J.
europepmc +1 more source
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 Natural Law in the American Tradition [PDF]
O\u27Scannlain, Hon. Diarmuid F.
core +1 more source
The geometry of Nature's stingers is universal due to stochastic mechanical wear. [PDF]
Sebastian J, Jensen KH.
europepmc +1 more source
Compliant Pneumatic Feet with Real‐Time Stiffness Adaptation for Humanoid Locomotion
A compliant pneumatic foot with real‐time variable stiffness enables humanoid robots to adapt to changing terrains. Using onboard vision and pressure control, the foot modulates stiffness within each gait cycle, reducing impact forces and improving balance. The design, cast in soft silicone with embedded air chambers and Kevlar wrapping, offers durable,
Irene Frizza +3 more
wiley +1 more source
Physics-Informed Machine Learning for Carbonation Depth Prediction in Concrete. [PDF]
Abbas MM, Bărbulescu A.
europepmc +1 more source

