Results 101 to 110 of about 24,065 (262)

Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers

Advanced Science, EarlyView.
FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao, Misheng Cai, Zhenghong Wang, Yan Wang, Yuqi Li, Bo Dong, Hewu Wang, Andrew F. Burke, Simona Onori, Stephen J. Harris   +9 more
wiley   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Transferable Deep Reinforcement Learning With Edge‐Contour‐Depth Fusion for Autonomous Wireless Capsule Endoscopy Navigation

Advanced Science, EarlyView.
This study presents an anatomical landmark‐guided DRL framework for autonomous wireless capsule endoscopy navigation. Using a lightweight edge‐contour‐depth fusion module, it achieves over 97% coverage across diverse gastric anatomies. To ensure reliability, a two‐stage sim‐to‐real pipeline with an adaptive dynamic programming controller mitigates ...
Haoxuan Wu, Haitao Gao, Qingyang Liu, Sishen Yuan, Haiyang Fang, Mingwu Su, Baijia Liang, Yongzun Yang, Long Bai, Wenzhen Dong, Dihong Xie, Shijian Su, Jiewen Lai, Shing Shin Cheng, Zhen Li, Xiuli Zuo, Hongliang Ren   +16 more
wiley   +1 more source

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source

Incoherent feedback from coupled amino acids and ribosome pools generates damped oscillations in growing E. coli

Nature Communications
Current theories of bacterial growth physiology demonstrate impressive predictive power but are often phenomenological, lacking mechanistic detail. Incorporating such details would significantly enhance our ability to predict and control bacterial growth
Rossana Droghetti, Philippe Fuchs, Ilaria Iuliani, Valerio Firmano, Giorgio Tallarico, Ludovico Calabrese, Jacopo Grilli, Bianca Sclavi, Luca Ciandrini, Marco Cosentino Lagomarsino   +9 more
doaj   +1 more source

Bootstrapping unobserved component models

, 2010
En esta tesis, proponemos el uso de técnicas bootstrap para incorporar la incertidumbre de la estimación de los parámetros en modelos de componentes inobservados expresado en un contexto de modelos de espacio de los estados. A lo largo de los capítulos usamos simulaciones Monte Carlo y datos reales para mostrar los resultados de los procedimientos ...
openaire   +2 more sources

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

Advanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei, Yong Li, Chenchong Wang, Lingyu Wang, Xiang Song, Keming Mao, Yu Zhang, Wei Xu   +7 more
wiley   +1 more source

Resistant Peanut Genotype Reprograms Rhizosphere Metabolism to Enhance Bacterial Wilt Suppression

Advanced Science, EarlyView.
The resistant peanut genotype selectively recruits beneficial bacteria, which coincides with the activation of salicylic acid (SA)‐dependent systemic acquired resistance (SAR) against Ralstonia solanacearum. Keystone rhizosphere metabolites are positively correlated with both beneficial microbiome assembly and SAR gene expression.
Rui Ren, Xiaogang Li, Hao Li, Zenghui Cao, Mengtian Hou, Chunlei Zhao, Nan Lou, Sasa Hu, Yanzhe Li, Qian Ma, Yaoyao Li, Yi Fan, Kunkun Zhao, Kai Zhao, Ding Qiu, Fangping Gong, Zhongfeng Li, Haitao Liu, Xingli Ma, Xingxiang Wang, Dongmei Yin   +20 more
wiley   +1 more source

StatGraph: an R package for complex network statistical analyses based on spectrum

SoftwareX
The analysis of complex networks has traditionally relied on descriptive measures, such as centrality and clustering coefficients, as well as algorithms for detecting partitions and components. Additionally, a range of software packages has been designed
Grover Enrique Castro Guzman, Diogo Ricardo da Costa, Eduardo Silva Lira, Suzana de Siqueira Santos, Taiane Coelho Ramos, Daniel Yasumasa Takahashi, Andre Fujita   +6 more
doaj   +1 more source

Learning Moisture‐Induced Damage From Vision: Diffusion Models for Real‐Time Monitoring of Additive Manufacturing Processes

Advanced Science, EarlyView.
We introduce a vision‐based real‐time monitoring system for additive manufacturing that detects subtle moisture‐induced degradation via a diffusion model‐based framework. The approach enables nondestructive assessment of moisture‐induced damage level and mechanical performance and establishes a practical route toward more intelligent, reliable, and ...
Jiyoung Jung, Yuna Yoo, Dharneedar Ravichandran, Dahyun Daniel Lim, Grace X. Gu   +4 more
wiley   +1 more source