Results 141 to 150 of about 22,226,095 (257)

A Robust Deep Temporal Causal Discovery Platform for Single‐Cell Gene Regulatory Network Reconstruction

Advanced Intelligent Discovery, EarlyView.
scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta, Madison Dautle, Shaoqiang Zhang, Yong Chen   +3 more
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, Erving Ximendes, Luís D. Carlos, Carlos D. S. Brites   +3 more
wiley   +1 more source

MolMiner: Toward Controllable, Three‐Dimensional‐Aware, Fragment‐Based Molecular Design

Advanced Intelligent Discovery, EarlyView.
MolMiner is a fragment‐based, geometry‐aware, and order‐agnostic generative model for molecular design with strong inductive biases. Using symmetry‐aware fragment assembly, dynamic three‐dimensional geometry, and multi‐property conditioning, MolMiner enables interpretable and controllable molecular generation.
Raul Ortega‐Ochoa, Tejs Vegge, Jes Frellsen   +2 more
wiley   +1 more source

A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design

Advanced Intelligent Discovery, EarlyView.
Active learning (AL) strategies are benchmarked for the binary design of planar multilayer nanophotonic structures. Factorization machines combined with quantum annealing (QA) become effective as dimensionality increases. Hybrid QA provides the strongest results for 100‐layer problems, highlighting the importance of optimization method selection in ...
Serang Jung, Seongmin Kim, Jaehyun Park, Chaeyoung Park, Zhihao Xu, Sanghyo Hwang, Baiqing Ye, Youn sang Kim, Sun‐Kyung Kim, Tengfei Luo, Eungkyu Lee   +10 more
wiley   +1 more source

Crystal Structure Prediction of Inorganic Materials: A Benchmark and Modern Evaluation

Advanced Intelligent Discovery, EarlyView.
Predicting a crystal’s structure from composition alone is a long‐standing challenge in materials discovery. The CSP180 benchmark of 180 inorganic crystals evaluates thirteen crystal structure prediction algorithms requiring no density functional theory (DFT) against DFT‐based baselines across twelve metrics.
Lai Wei, Sadman Sadeed Omee, Rongzhi Dong, Nihang Fu, Yuqi Song, Edirisuriya M. Dilanga Siriwardane, Meiling Xu, Ming Hu, Chris Wolverton, Jianjun Hu   +9 more
wiley   +1 more source

Motion and Morphology Planning for Autonomous Manipulation in Clutter With a Shape‐Shifting, Variable‐Stiffness Robot

Advanced Intelligent Systems, EarlyView.
A hybrid mobile robot with a modular Variable‐Stiffness Bridge transitions between a rigid locomotion platform and a flexible, shape‐conforming body. By enclosing objects within its deformable structure rather than relying on dedicated end effectors, the robot achieves orientation‐regulated planar transport, with conformal contact quality shown to ...
Luiza Labazanova, Liuming Qiu, Jose Guadalupe Romero, Li Cheng, Thrishantha Nanayakkara, David Navarro‐Alarcon   +5 more
wiley   +1 more source

Integrating Reinforcement Learning With Explainable Artificial Intelligence for Real‐Time Clinical Decision Support in Dynamic Healthcare Environments

Advanced Intelligent Systems, EarlyView.
A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha, MD Faiaz Zaman Dehan, Kazi Md. Tanvir Anzum   +2 more
wiley   +1 more source

Life-Cycle Assessment of Laboratory-Scale Extrusion of Virgin and Recycled Polyolefins: Influence of Operating Duration on Life-Cycle Inventory Development. [PDF]

Polymers (Basel)
Saleem J, Moghal ZKB, Mckay G.
europepmc   +1 more source

Ecoefficiency Analysis and Regression in Data Conversion for Spiking Neural Network Training

Advanced Intelligent Systems, EarlyView.
The environmental footprint of spiking neural networks is quantified during dataset encoding and training for autonomous driving regression across three benchmarks. Temporal depth emerges as the dominant driver of energy consumption and CO2 emissions, while the accuracy–energy trade‐off proves dataset‐dependent. On conventional hardware, spiking models
Fernando S. Martínez, Raúl Parada, Jordi Casas‐Roma, Laia Subirats   +3 more
wiley   +1 more source

A High-Throughput Memory Compression Architecture for Real-Time 3D Visual Tracking and Quantification on Edge Devices. [PDF]

Sensors (Basel)
Cheng Y, Guo L, Zhou R, Zhou Q, Li LH, Ivanović M, Li KC, Ye G.   +7 more
europepmc   +1 more source