Results 121 to 130 of about 2,904,995 (278)
Time History Gaussian Process Regression for Modeling the Dynamics of Ankle Exoskeleton User Comfort
Exoskeletons need to be comfortable, but the perception of comfort may change over time. This study investigated if short‐term time history directly influences comfort. No previous trials’ input features were predictive of comfort. Including the previous trial's comfort score marginally improved model accuracy compared to a model using only the current
Axl Maberry, Bo Cheng, Anne E. Martin
wiley +1 more source
Magnetically Actuated Microrobot for Drug Delivery: Current Progress and Challenges
Magnetically actuated microrobots are reshaping targeted drug delivery through wireless propulsion, programmable materials, and localized therapeutic release. This review examines how fabrication, body material selection, structural architecture, loading mechanisms, and imaging‐guided control converge to enable microrobotic therapies while identifying ...
Yang Yang, David J. Cappelleri
wiley +1 more source
Review on Generalized Uncertainty Principle
Based on string theory, black hole physics, doubly special relativity and some "thought" experiments, minimal distance and/or maximum momentum are proposed. As alternatives to the generalized uncertainty principle (GUP), the modified dispersion relation, the space noncommutativity, the Lorentz invariance violation, and the quantum-gravity-induced ...
Tawfik, Abdel Nasser, Diab, Abdel Magied
openaire +2 more sources
Consensus Formation and Change are Enhanced by Neutrality
Neutral agents are shown to enhance both the formation and overturning of consensus in collective decision‐making. A general mathematical model and experiments with locusts and humans reveal that neutrality enables robust consensus via simple interactions and accelerates consensus change by reducing effective population size.
Andrei Sontag +3 more
wiley +1 more source
Generalized uncertainty principle and the Zeeman effect: Relativistic corrections unveiled
In this paper, we calculate the relativistic corrections to the Zeeman effect for hydrogen-like atoms based on the Generalized Uncertainty Principle (GUP).
Gaurav Bhandari +2 more
core +2 more sources
Generalized uncertainty principle corrections in Rastall–Rainbow Casimir wormholes
We explore wormhole solutions sourced by Casimir energy density involving generalized uncertainty principle corrections within the framework of Rastall–Rainbow gravity.
Emmanuele Battista +2 more
doaj +1 more source
Machine Learning for Green Solvents: Assessment, Selection and Substitution
Environmental regulations have intensified demand for green solvents, but discovery is limited by Solvent Selection Guides (SSGs) that quantify solvent sustainability. Training a machine learning model on GlaxoSmithKline SSG, a database of sustainability metrics for 10,189 solvents, GreenSolventDB is developed. Integrated with Hansen solubility metrics,
Rohan Datta +4 more
wiley +1 more source
Solid Harmonic Wavelet Bispectrum for Image Analysis
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown +3 more
wiley +1 more source
Longitudinal Morphomolecular Monitoring of Head and Neck Carcinogenesis
A miniaturized endoscopic probe that integrates Raman spectroscopy and optical coherence tomography, enabling simultaneous molecular and structural imaging of living tissue, was developed. Applied longitudinally in a mouse model of head and neck cancer, the system tracks disease progression from precancerous lesions to invasive cancer.
Jianrong Qiu +7 more
wiley +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source

