Results 221 to 230 of about 476,299 (305)
Low‐index and low‐loss vdW muscovite represents an emerging robust dielectric platform for the creation of next‐generation all‐vdW nanophotonic architectures. Its utilization as a low‐index building‐block in all‐vdW multilayers enables extreme optical contrast when paired with MoS2, paving the way to the realization of few‐layer ultrathin DBS ...
Meri H. Hayrapetyan +10 more
wiley +1 more source
Naphthopyran–benzophenone compounds can act simultaneously as photoinitiators and photochromic molecules for two‐photon polymerization. Using a single‐step process, liquid photoresist is encapsulated within polymerized 3D microstructures, preserving reversible UV–vis photochromism after fabrication.
João P. Leote +5 more
wiley +1 more source
varGuid: R and Python Implementations of Variance-Guided Regression for Robust Effect-Size Estimation in Linear Models. [PDF]
Liu S, Wang Z, Lu M.
europepmc +1 more source
Electric fields drive dynamic photonic assemblies that reversibly generate structural color. By tuning nanoscale organization through controlled particle disorder, the presented system exhibits a unique binary color response, switching between blue and pink depending on viewing angle. Combined with metameric design, this allows for a two‐factor optical
Flora Schöfbeck +9 more
wiley +1 more source
avbirt: A Python Package for Flexible Item Factor Analysis with Adversarial Variational Bayes. [PDF]
Luo N, Ji F.
europepmc +1 more source
An AI‐powered, robot‐assisted framework automatically produces, images, and analyzes 3D tumor spheroids to evaluate drug efficacy. Integrated modules handle spheroid formation, live/dead staining, brightfield imaging, and automated image analysis, including spheroid segmentation, viability and metrics to assess the drug treatment efficacy. The workflow
Dalia Mahdy +13 more
wiley +1 more source
Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
wiley +1 more source

