Results 231 to 240 of about 5,958,314 (335)
Astrocytes enhance plasticity response during reversal learning. [PDF]
Squadrani L +6 more
europepmc +1 more source
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll +19 more
wiley +1 more source
Serial reversal learning in nectar-feeding bats. [PDF]
Chidambaram S +4 more
europepmc +1 more source
A Soft Microrobot for Single‐Cell Transport, Spheroid Assembly, and Dual‐Mode Drug Screening
A soft, untethered hydrogel microrobot enables precise single‐cell delivery, self‐assembly into 3D spheroids, and real‐time thermal actuation. Driven by light‐induced convection and embedded with gold nanorods and temperature sensors, the microrobot guides cells, modulates local microenvironments, and supports drug testing.
Philipp Harder +3 more
wiley +1 more source
Poly (I:C)-induced maternal immune activation generates impairment of reversal learning performance in offspring. [PDF]
Munarriz-Cuezva E, Meana JJ.
europepmc +1 more source
Effect of age on discrimination learning, reversal learning, and cognitive bias in family dogs
Patrizia Piotti +6 more
semanticscholar +1 more source
Physical Intelligence in Small‐Scale Robots and Machines
“Physical intelligence” (PI) empowers biological organisms and artificial machines, especially at the small scales, to perceive, adapt, and even reshape their complex, dynamic, and unstructured operation environments. This review summarizes recent milestones and future directions of PI in small‐scale robots and machines.
Huyue Chen, Metin Sitti
wiley +1 more source
Serial visual reversal learning in captive black-handed spider monkeys, Ateles geoffroyi. [PDF]
Dorschner J +2 more
europepmc +1 more source
Screen gate‐based transistors are presented, enabling tunable analog sigmoid and Gaussian activations. The SA‐transistor improves MRI classification accuracy, while the GA‐transistor supports precise Gaussian kernel tuning for forecasting. Both functions are implemented in a single device, offering compact, energy‐efficient analog AI processing ...
Junhyung Cho +9 more
wiley +1 more source

