Nonreciprocal Swarmalators With Reconfigurable and Controllable Formations for Robot Collectives
Advanced Robotics Research, EarlyView.Nonreciprocal swarmalator interactions are enabled through control barrier functions to transform self‐organizing robot collectives into reconfigurable, constraint‐aware systems. Complex two‐ and three‐dimensional shapes, continuous morphing, obstacle‐aware navigation, collective splitting, and object transport emerge from modulating agent‐level ...
Kush Patel +3 more
wiley +1 more source
Deep Learning-Based Intelligent Resource Management for Renewable Energy Engineering Projects. [PDF]
Ann N Y Acad SciYao Y.
europepmc +1 more source
Magnetically Actuated Microrobot for Drug Delivery: Current Progress and Challenges
Advanced Robotics Research, EarlyView.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
Designing a context-sensitive faculty development architecture for simulation facilitators: lessons from a practice-based implementation. [PDF]
Adv Simul (Lond)Gonçalves Campos D +3 more
europepmc +1 more source
Deep Contrastive Learning for High‐Throughput Prediction of Drug Resistance Mutations from Sequences
Advanced Science, EarlyView.This study presents DeepMutDTA, a deep learning framework aimed at predicting mutation‐induced changes in protein‐drug interactions and prioritizing variants potentially linked to drug resistance. Trained on large‐scale data, it incorporates SimSiam‐MuTF, a label‐aware contrastive fine‐tuning strategy that encourages separation between WT and MT ...
Xiaowen Hu +7 more
wiley +1 more source
Reinforcement Learning with Constrained Action
Reinforcement Learning (RL) is an important technique in machine learning that has gained special significance in solving real-world problems. Typically RL algorithms work under no constraints on the state of the environment or the actions taken by the agent.
openaire +1 more source
Learning Adaptive Search with Reinforcement Learning for Small and Fast Object Tracking. [PDF]
Sensors (Basel)Liu B +6 more
europepmc +1 more source
Machine Learning for Green Solvents: Assessment, Selection and Substitution
Advanced Science, EarlyView.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
Physics-constrained multimodal reinforcement learning for local UAV Navigation in complex static obstacle environments. [PDF]
Sci RepTian Y +6 more
europepmc +1 more source
Solid Harmonic Wavelet Bispectrum for Image Analysis
Advanced Science, EarlyView.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