Results 81 to 90 of about 46,024 (262)
Advanced Intelligent Discovery, EarlyView.The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy +8 more
wiley +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Machine‐Learning‐Assisted Onset‐Time Determination in Transient Luminescence Thermometry
Advanced Intelligent Discovery, EarlyView.Artificial neural networks enable autonomous extraction of onset times from transient heating curves in luminescence thermometry. Using Ln3+‐doped upconverting nanoparticles as luminescent thermometers, we combine experimental transients with physically motivated synthetic curves to enhance data diversity and improve generalization.
David J. Sousa +3 more
wiley +1 more source
SAGE Open NursingBackground The high prevalence of work-related musculoskeletal disorders (WRMSDs) among nursing professionals has profoundly affected their quality of life, contributed to absenteeism, and incurred considerable medical cost burdens for the nurses. Caring
Sonia Anak Nicholas Felix MSc +1 more
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.The hydration behavior of C3S in seawater‐relevant solutions is studied based on experiments, boundary nucleation and growth (BNG) modeling, and machine learning. The main ions included in seawater modify hydration mechanisms, with MgCl2 showing the strongest acceleration effect at the same concentration.
Yanjie Sun +6 more
wiley +1 more source
Programmable Flocks: Hierarchical Swarm Control via Dynamic Parameter Injection
Advanced Intelligent Systems, EarlyView.We present a method for the control of robot swarms which allows the shaping and the translation of patterns of simple robots (“smart particles”), using two types of devices. These two types represent a hierarchy: a larger group of simple, oblivious robots (which we call the workers) that is governed by simple local attraction forces and a smaller ...
Vivek Shankar Varadharajan +1 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.An large language model‐powered multimodal framework is developed for robotic endoscope control. It integrates speech recognition and real‐time instrument tracking, achieving 89.47% command accuracy with ~1s latency for natural human–robot interaction in minimally invasive surgery.
Yisen Huang +7 more
wiley +1 more source
Predictive value of R.E.N.A.L. nephrometry score in robotic assisted partial nephrectomy
Urology Research and Practice, 2019 Objective: In this study, we evaluated the predictive value of R.E.N.A.L. Nephrometry Score (RNS), a system to standardize the renal tumors according to size, location, and depth, for surgical outcomes of robotic partial nephrectomy.
Uğur Boylu +5 more
doaj +2 more sources
Australian Journal of Social Issues, EarlyView.ABSTRACT Following the Royal Commission into Aged Care Quality and Safety, the Australian Government set a target for no‐one under 65 years of age to be living in residential aged care (RAC) by 2025. The numbers of young people in residential aged care (YPIRAC) have significantly declined since the start of the targets.
Elroy Dearn +4 more
wiley +1 more source