Results 81 to 90 of about 8,113 (297)

Cyber-Physical GraphRAG: Safe, Real-Time, and Scalable Orchestration of Large-Scale Autonomous Fleets

IEEE Access
Large-scale autonomous fleet orchestration requires both geometric reasoning for path planning and semantic reasoning for task allocation and policy compliance.
Abdalrahman Ibrahim, Fadi Al Machot, Kyandoghere Kyamakya   +2 more
doaj   +1 more source

Inhibitory Decay and Supercritical Brain Dynamics During Sleep Deprivation

Advanced Science, EarlyView.
Sleep deprivation progressively shifts human brain dynamics from near‐critical toward supercritical states, as revealed by neuronal avalanche analysis of resting‐state fMRI. These changes track subjective sleep pressure rather than vigilance lapses and show marked network heterogeneity. A circuit model suggests that reduced inhibitory efficacy provides
Dai Zhang, Liqin Zhou, Rong Wang, Yuehua Han, Zhentao Zuo, Yanghua Tian, Ke Zhou   +6 more
wiley   +1 more source

TOWARDS A UNIFIED FRAMEWORK FOR KNOWLEDGE TRACING WITH GRAPH CONVOLUTIONAL AND NEURAL ARCHITECTURES

Malaysian Journal of Computing
This paper sets out to propose a unified theoretical framework for knowledge tracing (KT) that combines graph convolutional networks (GCNs) with neural sequence architectures in intelligent tutoring systems.
Yaxi Su, Mohamad Yusof Darus, Norizan Mat Diah, Jinpeng Huang, Azlin Ramli   +4 more
doaj   +1 more source

How Advanced Artificial Intelligence Technologies Shape Drug–Drug and Drug–Target Interaction Modeling

Advanced Science, EarlyView.
This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
wiley   +1 more source

3D Semantic Digital Twins: Data Streams and Ontologies for Risk Prediction in Heritage Contexts [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Sensor data are core for real-time monitoring in heritage contexts, allowing to ground the synchronization between the real asset and its Digital Twin (DT). Such synchronization can then be leveraged to perform risk prediction with a time aware reasoning
M. Codiglione, M. Codiglione, F. Remondino   +2 more
doaj   +1 more source

De Novo Design of Membrane‐Targeting Antimicrobial Peptides Against Gram‐Negative Bacteria Using a Generative Artificial Intelligence Framework

Advanced Science, EarlyView.
Antimicrobial resistance caused by Gram‐negative bacteria remains difficult to overcome due to the protective outer membrane. To address this challenge, a multi‐condition constrained generative AI framework, GenMTAMP is proposed for de novo membrane‐targeting antimicrobial peptide design by integrating physicochemical and spatial structure descriptors.
Jingxiao Yu, Da‐Wen Sun, QingYi Wei, Yibing Zhang, Jidong Tang, Hongbin Pu   +5 more
wiley   +1 more source

CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning

Advanced Science, EarlyView.
CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang, Zexi Chen, Yuanxiang Miao, Zuolin Shen, Deyu Cai, Shijie Tang, Yun Xue, Weifeng Guo, Hongbin Ji, Jian Liu, Kazuyuki Aihara, Luonan Chen   +11 more
wiley   +1 more source

Multi-Paradigm Reasoning for Access to Heterogeneous GIS [PDF]

, 2005
Accessing and querying geographical data in a uniform way has become easier in recent years. Emerging standards like WFS turn the web into a geospatial web services enabled place.
Lorenz, Bernhard, Colonna, François-Marie, Bry, François   +2 more
core   +1 more source

Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates

Advanced Science, EarlyView.
Often treated as unknown, information from the future remains underutilized.We demonstrate that in a coupled dynamical system, providing the future state of the effect enables accurate forecasting of the cause for a long timesteps. A time series forecasting paradigm that introduces anticipated covariates to represent such known future states is ...
Jintong Zhao, Yufei Liu, Ruixi Huang, Zhongxue Gan, Siyang Leng   +4 more
wiley   +1 more source

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

Advanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai, Ri He, Junxian Liu, Liangzhi Kou   +3 more
wiley   +1 more source