Results 141 to 150 of about 10,384,830 (290)

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

Optimizing construction risk management through BIM integration and strategic planning. [PDF]

Sci Rep
Li R, Almenweer RA, Isleem HF, Metwally ASM.   +3 more
europepmc   +1 more source

ROS Self‐Supply Nanoplatform Based on Fenton Catalyst for Chemodynamic and Immunotherapy: Reprogramming Cold Tumor Into Hot Tumor in Cancer Treatment

Advanced Science, EarlyView.
A multifunctional HA‐conjugated nanoplatform (HA‐PGMC) integrates CuO2, glucose oxidase, and mil‐100 to enable cascade catalytic ROS generation in tumor microenvironments. This self‐supplying ROS strategy induces immunogenic cell death, reprograms “cold” tumors into “hot” ones, and synergizes with PD‐L1 blockade, achieving potent chemodynamic ...
Man Lung Lee, Jack Chun Hin Chen, Wai Wing Cheng, Kwan Yee Lau, Hiu Yee Kwan, Ngar‐Yun Ellen Poon, Hung‐Wing Li   +6 more
wiley   +1 more source

Assessing the impact of AI-enabled BIM digital twins on construction risks: a Bayesian Network of Jordanian expert beliefs. [PDF]

Front Artif Intell
Albtoush F, Al-Btoosh JAA, Rawashdeh TM, Al-Btoush MAKA.   +3 more
europepmc   +1 more source

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

Adaptive Momentum Langevin Dynamics for Efficient Posterior Sampling. [PDF]

Entropy (Basel)
Li Z, Xu J, Peng D, Hu S.
europepmc   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

RESCON: Educational project scheduling software. [PDF]

In this article we discuss a freely downloadable educational software tool for illustrating project scheduling and project management concepts. The tool features exact and heuristic scheduling procedures and visualizes project networks, project schedules,
Deblaere, Filip, Herroelen, Willy, Demeulemeester, Erik   +2 more
core  

Automated conceptual earned value management. [PDF]

Sci Rep
Elmousalami H, Alotaibi A.
europepmc   +1 more source

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