Results 161 to 170 of about 123,292 (253)

Bayesian‐Optimized Dual‐Mode Luminescence‐Based Optical Thermometry Enabled by Negative Thermal Expansion in Lu2(MoO4)3:Yb–Er–Tm Phosphor

Advanced Optical Materials, EarlyView.
A Bayesian optimization framework identifies the ideal composition for Lu2(MoO4)3:Yb–Er–Tm phosphors with minimal experimental trials. By leveraging the host's negative thermal expansion, the material achieves remarkable thermal quenching compensation.
Reiko Furukawa, Takuya Hasegawa, Tong Fang, Saneyuki Ohno, Tomoyo Goto, Yasushi Sato, Ayahisa Okawa, Shu Yin   +7 more
wiley   +1 more source

Reclaiming informed consent to train mental health AI with patient data. [PDF]

NPJ Digit Med
Larrauri CA, Martinez-Martin N, Torous J.   +2 more
europepmc   +1 more source

Machine Learning Enables Inverse Design of Optically Driven Microscopic Metavehicles

Advanced Optical Materials, EarlyView.
Machine‐learning‐based inverse design is used optimize “metavehicles” — flat microparticles based on metagratings that generate a strong lateral optical force from normally incident light. The optimized design exhibits a force efficiency of ∼88% and a measured propulsion speed in water much higher than previously reported, demonstrating that inverse ...
Vasilii Mylnikov, Mahdi Shanei, Mikael Käll   +2 more
wiley   +1 more source

Circularly Polarized Red‐NIR Emission With High Dissymmetry Factor From Achiral [Mo6I8(OCOC2F5)6]2− Cluster Anion Embedded in a Bent‐Core Liquid Crystal Host

Advanced Optical Materials, EarlyView.
Associating a chiral bent core liquid crystal molecule, that self‐assembles into helical nanofilaments, with an achiral red‐NIR phosphorescent octahedral molybdenum cluster produces a hybrid material exhibiting efficient red‐NIR circularly polarized emission under UV excitation.
Jeanne Rebours, Shamima Akhter, Md Kamrul Hasan, Serge Paofai, Maria Amela‐Cortes, Marianne Estelle Prévôt, Yann Molard   +6 more
wiley   +1 more source

The AHEPA EEG benchmark: setting the standard for machine learning in dementia diagnosis, a scoping review. [PDF]

Cogn Neurodyn
Miltiadous A, Ntetska A, Aspiotis V, Moustakli E, Tsipouras MG, Tzallas AT, Giannakeas N, Glavas E, Angelidis P, Tzimourta KD.   +9 more
europepmc   +1 more source

Soft Robotic Excretory Care Simulator for Nursing Education: Functional and Perceptual Biomimetics Approach

Advanced Robotics Research, EarlyView.
A soft robotic simulator is developed to replicate the digital removal of feces (DRF), a sensitive yet essential nursing procedure. Integrating soft actuators, sensors, and a realistic rectal model, the simulator balances functional fidelity with perceptual realism. Engineering evaluations and nurse feedback confirm its potential to enhance training in
Shoko Miyagawa, Sota Suzuki, Shizuka Watanabe, Zebing Mao, Young Ah Seong, Toshinori Fujie, Tatsuhiro Horii, Kenjiro Tadakuma, Koichi Suzumori, Hiroyuki Nabae, Shingo Maeda   +10 more
wiley   +1 more source

Preparing Emergency Medicine Residents to Lead Level 1 Multidisciplinary Trauma Teams: A Scoping Review. [PDF]

AEM Educ Train
Khan AS, Cushman CJ, Mecham C, Stroever S, Morris T.   +4 more
europepmc   +1 more source

The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?

Advanced Robotics Research, EarlyView.
Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley   +1 more source

Estimation of positron emission tomography amyloid load and related biomarkers in Alzheimer's disease using evoked potential tomography EEG: development and internal validation in a cross-sectional cohort. [PDF]

Alzheimers Res Ther
Rauchmann BS, Hamet J, Lai J, Kafi H, Rexwinkle J, Brendel M, Franzmeier N, Kurz C, Pogarell O, Levin J, Höglinger G, Perneczky R.   +11 more
europepmc   +1 more source

Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback

Advanced Robotics Research, EarlyView.
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, Ali Umut Kaypak, Prashanth Krishnamurthy, Ramesh Karri, Farshad Khorrami   +4 more
wiley   +1 more source