Results 141 to 150 of about 2,382 (198)

Self‐Service and Home Delivery Combined: Coordinating the Route of a Mobile Parcel Locker With the Delivery Tasks of Its Human Driver

Networks, Volume 88, Issue 2, Page 192-210, September 2026.
ABSTRACT In response to the increasing volume of parcels, last‐mile delivery innovations are exploring the integration of multiple delivery modes. The most prominent examples are delivery vans that, next to being the base for the delivery tasks of their human drivers, also function as mobile launching platforms for drones or autonomous delivery robots.
Nils Boysen, Dirk Briskorn, Stefan Schwerdfeger   +2 more
wiley   +1 more source

SphereDiff-TS: Sphere Space Diffusion Modeling for Accurate 3D Transition State Geometry Prediction. [PDF]

ACS Omega
Zhao C, Li P, Zhang S, Li C, Li Z, Tang Y, Linghu K, Tang L, Yang Y.   +8 more
europepmc   +1 more source

AVIDbase: A biologically accurate structural dataset of nanobody‐antigen complexes

Protein Science, Volume 35, Issue 9, September 2026.
Abstract Accurate structural data in a standardized format is one of the key factors behind the success of machine learning (ML)‐based methods for protein design and structure prediction. However, their application to nanobody‐antigen complexes has lower success rates compared to globular protein complexes, partly due to the limited amount of high ...
Tadej Medved, Jurij Lah, Goran Miličić, San Hadži   +3 more
wiley   +1 more source

Contact-aware multi-skill learning framework with hybrid force-motion control for stability and force regulation in robotic physiotherapy. [PDF]

Front Robot AI
Zhai X, Feng Q, Zheng H, Luo Y, Hao H, Yan A, Wu H.   +6 more
europepmc   +1 more source

Key Technical Fields and Future Outlooks of Space Manipulators: A Survey

SmartBot, Volume 2, Issue 3, September 2026.
This paper systematically reviews the technological development of space manipulators, emphasizing the unique challenges posed by space environments. It examines four areas: structural design, modeling, planning, and control, while introducing typical ground test platforms.
Gang Chen, Zeyuan Huang, Ying Yan, Xiaokang An, Zhikai Zhao, Jirong Lin, Xiangrong Zhao, Xianyuan Gao, Junyi Zong, Xuewen Jia, Zhipeng Yao, Jianliang Liao, Ning Ji   +12 more
wiley   +1 more source

Simplex polynomial in complex networks and its applications to compute the Euler characteristic. [PDF]

Front Comput Neurosci
Wang Z, Fu X, Deng B, Chen Y, Zhao H.
europepmc   +1 more source

Deep Learning for Protein Modeling: From Single Structure to Bound Complex and Thermodynamic Ensemble, With a Focus on Architectural Design

WIREs Computational Molecular Science, Volume 16, Issue 5, September/October 2026.
Protein deep learning is moving from single structure prediction toward bound complex modeling and conformational ensemble generation. An architectural perspective shows how symmetry, evolutionary information, generative sampling, and energetic grounding shape performance and generalization.
Daniele Angioletti, Matteo Carli, Marco Nobile, Vittorio Limongelli   +3 more
wiley   +1 more source

Hybrid task and motion planning with reactive collision handling for multi-robot disassembly of complex products: application to EV batteries. [PDF]

Front Robot AI
Shaarawy A, Erdogan C, Stolkin R, Rastegarpanah A.   +3 more
europepmc   +1 more source

Explainable Artificial Intelligence for Clinical Trust in Parkinson's Disease: A Scoping Review on Non‐Invasive Digital Biomarkers

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 3, September 2026.
Explainable artificial intelligence is expanding Parkinson's disease research by improving model transparency, supporting biomarker discovery and optimizing predictive models, but further validation and clinical integration are needed before routine healthcare implementation. ABSTRACT Parkinson's disease (PD) increasingly relies on non‐invasive digital
Lorenzo Rettori, Erika Rovini, Hamido Fujita, Filippo Cavallo   +3 more
wiley   +1 more source

Formation of topologically associated chromatin domains using quantum annealing. [PDF]

Sci Rep
Kempe T, Tabei SMA, Ansari MH.
europepmc   +1 more source