Results 121 to 130 of about 151,158 (307)

Probability Analysis of Hazardous Chemicals Storage Tank Leakage Accident Based on Neural Network and Fuzzy Dynamic Fault Tree

Applied Sciences
Aiming at the problems of complex calculation processes, insufficient risk data, and reliance on experts’ subjective judgments that exist in traditional probability analysis methods, this paper proposes a probability analysis method for hazardous ...
Xue Li, Wei’ao Liu, Ning Zhou, Xiongjun Yuan   +3 more
doaj   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Introgressed Variation in TaMYB7‐A1 Drives Graded Dormancy and Climate‐Adaptive Pre‐Harvest Sprouting Resistance in Wheat

Advanced Science, EarlyView.
TaMYB7‐A1 directly activates TaABI5 to enhance ABA signaling and regulate ABA‐GA homeostasis, enforcing seed dormancy. Its superior allele, derived from wild einkorn introgression, harbors a MITE insertion that elevates expression and two amino acid substitutions that enhance transcriptional activity, collectively generating graded PHS resistance for ...
Hao Wang, Dongzhi Wang, Yafei Guo, Qi Zheng, Min Zhang, James Simmonds, Jian Hou, Xuemei Liu, Xuelei Lin, Xiaomin Bie, Xiansheng Zhang, Xiaohui Li, Yuan Chen, Xueyong Zhang, Cristobal Uauy, Fei Lu, Chengcai Chu, Zhixi Tian, Jun Xiao   +18 more
wiley   +1 more source

Methods of swarm artificial intelligence in autonomous navigation tasks of UAVs

Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï
This paper presents a comparative analysis of nine swarm intelligence (SI) methods in terms of their suitability for onboard AI platforms in autonomous unmanned aerial vehicle (UAV) swarms.
Michael Zgurovsky, Yuriy Zaychenko, Andrii Tytarenko, Oleksii Kuzmenko   +3 more
doaj   +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

Empirical Evaluation of State Event Fault Tree and Dynamic Fault Tree for the Safety Analysis of Ambient Assisted Living [PDF]

, 2013
Most of the evolution in ambient assisted living is due to embedded systems that dynamically adapt themself to react to environmental changes or component/subsystem failures to maintain a certain level of safety.
Taibi, Davide (Dr.), Jamboti, Kavyashree, Mouaffo, Adrien   +2 more
core  

Enabling Fault-Tolerant and Load-Balanced Multi-Query Searchable Encryption With Multi-Level Revocation in Edge-Fog-Cloud for Electronic Health Records

IEEE Open Journal of the Communications Society
Secure and efficient data sharing in Internet of Things (IoT)–based Electronic Health Record (IoT-EHR) systems remains challenging due to heterogeneous query types, dynamic user revocation, and the massive volume of continuously generated data. In
Maneesha Perera, Somchart Fugkeaw
doaj   +1 more source

A Computational Strategy for Identifying Self‐Assembling Food‐Derived Molecules for Antiparasitic Nanotherapy

Advanced Science, EarlyView.
An integrated computational screening strategy identified ursolic acid (UA) and 18β‐glycyrrhetinic acid (18βGA) as a self‐assembling food‐derived molecular pair. The resulting carrier‐free nanoparticles (UA‐18βGA) showed synergistic antiparasitic activity, reduced combined toxicity, and host‐protective anti‐inflammatory effects in zebrafish and murine ...
Shenye Qu, Ting Wang, Jietao Liu, Jiacheng Qin, Bin Yang, Yihang Liu, Pengfei Li, Gaoxue Wang, Fei Ling   +8 more
wiley   +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

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source