Results 151 to 160 of about 2,669 (298)

A chaotic parallel hash engine with dynamic stochastic diffusion for blockchain and cloud security. [PDF]

Sci Rep
Wang Q, Yang Y, Zhao M, Wan H, Li B, Yan X.   +5 more
europepmc   +1 more source

V2CTx MXene as a Sacrificial Promoter for NiFe Catalyst for Anion Exchange Membrane Electrolyzers

Advanced Science, EarlyView.
These findings demonstrate that V2CTx functions beyond passive conductive support as an active electronic participant whose structural legacy sustains durable performance even after vanadium leaching in Anion Exchange Membrane (AEM) Electrolysers. ABSTRACT Nickel‐iron layered double hydroxides (NiFe‐LDH) show excellent activity, their poor conductivity
Bastian Schmiedecke, Can Kaplan, Karuppasamy Dharmaraj, Axel Zuber, Merve Buldu‐Aktürk, Ningjun Chen, Mailis Lounasvuori, Xuyun Guo, Valeria Nicolosi, Thorsten Schultz, Norbert Koch, Johanna Rosen, Michelle P. Browne   +12 more
wiley   +1 more source

AutomataGPT: Transformer-Based Forecasting and Ruleset Inference for Two-Dimensional Cellular Automata. [PDF]

Adv Sci (Weinh)
Berkovich JA, David NS, Buehler MJ.
europepmc   +1 more source

Quantum Photothermal Self‐Monitoring Fiber Probes for In Vivo Photothermal Therapy

Advanced Science, EarlyView.
A miniaturized quantum photothermal fiber probe based on a metal/polymer/glass composite optoelectronic fiber that simultaneously guides lightwave and microwave was developed for the first time. The probe achieves enhanced photothermal conversion (13°C/mW, 25°C–120°C range) while providing real‐time self‐monitoring with 0.2°C thermal resolution at the ...
Wanjun Li, Ruixiao Hu, Jie Mao, Jin Wo, Yunsong Zhang, Liang Chen, Ying Liu, Zhibo Li, Yongxin Lin, Minghui Du, Yaofei Chen, Libing Zhou, Tuan Guo   +12 more
wiley   +1 more source

An XGBoost-based cellular automata for modeling PM₂.₅ concentration using ground and satellite data. [PDF]

Sci Rep
Farokhi S, Maleki J, Foroutan E.
europepmc   +1 more source

PancDS in Real‐World Practice: A Prospective Multicenter Validation of a Clinical Decision‐Support System Bridging Experience Gaps in Pancreatic Lesion Diagnosis

Advanced Science, EarlyView.
A biomimetic artificial intelligence system, PancDS, has been developed to distinguish pancreatic ductal adenocarcinoma from mass‐forming pancreatitis by adaptively integrating clinical data, radiomics, and deep learning features. Validated across multicenter, reader‐study, and prospective settings, PancDS improves diagnostic accuracy, particularly for
Zhibo Wang, Weinuo Qu, Wenwen Cai, Chuhuai Wang, Chenxi Lyu, Qingguo Xie, Qian Chu, Yaqi Shen, Peng Xiao, Feng Li, Qingpeng Zhang, Jiali Li, Jeong Min Lee, Zhen Li   +13 more
wiley   +1 more source

Optimizing ergonomic risk assessment using fuzzy irregular cellular automata: a novel approach to modeling musculoskeletal disorders in industrial workstations. [PDF]

Sci Rep
Kashani M, Zare A, Barzekar S, Jaamebozorgi MB, Moradpour MA, Sadeghi M.   +5 more
europepmc   +1 more source

Noninvasive Characterization of Tumor Heterogeneity in HNSCC: From Clinical Utility to Biological Correlates

Advanced Science, EarlyView.
This study establishes a CT‐based radiomics framework to quantify intratumoral heterogeneity (ITH) in HNSCC. Using unsupervised clustering, tumor ROIs and VOIs are analyzed to calculate 2D/3D ITH scores. The score shows strong predictive value for prognosis and immunotherapy response, and is associated with tumor metabolism and immune microenvironment,
Xinwei Chen, Rui Liu, Yuan Zhou, Yin Xiao, Chengmin Feng, Lin Chen, Yanshi Li, Mengna Wang, Zhaobo Cheng, Yuxi Luo, Long Liu, Lijing Niu, Yue Xiang, Juan Peng, Guohua Hu, Min Pan   +15 more
wiley   +1 more source

Mapping coastal transformations with a novel Cellular Automata-Markov-Random forest framework for land use change modeling. [PDF]

Sci Rep
Nikoo MR, Zarei E, Al-Wardy M.
europepmc   +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