Results 91 to 100 of about 21,063 (212)

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

An Adaptive Online Knowledge Distillation Algorithm for Edge Computing Models Enhanced by Elite-Students

Mathematics
In recent years, deep learning models have exhibited exceptional performance across several tasks. However, the substantial computational and storage demands impede implementation on edge devices with constrained resources. Online Knowledge Distillation (
Jincheng Xia, Yan Zhou, Xu Yang, Chengyan Zhao   +3 more
doaj   +1 more source

Multiferroic‐Centric Materials and Systems Engineering for Battery Applications: An Insight Into Mechanisms, Strategies, and Characterizations

Advanced Science, EarlyView.
Multiferroic order parameters – polarization, magnetization, and ferroelastic strain – are positioned as dynamic design variables for batteries. Their mechanistic roles, practical tuning through fabrication and external fields, and ferroic‐resolved characterization routes are unified into a closed‐loop framework, revealing how coupled ferroic responses
Jiaqi Su, Yanda Zhu, Hao Peng, Manman Li, Xuzihan Zhang, Meixiao Wu, Siyuan Zhang, Yuhan Zeng, Jiwen Liao, Ming Luo, Hetaishan Huang, Yutong Wang, Sean Li, Wenxian Li   +13 more
wiley   +1 more source

Large Language Model‐Informed Dual‐Track AI Framework for the Synergistic Design of Crack‐Free and High‐Strength Superalloys

Advanced Science, EarlyView.
This paper illustrates a knowledge‐augmented dual‐track AI framework for advanced superalloy design. First, Large Language Models translate metallurgical heuristics into explicit rules to rapidly prune a vast compositional search space. Subsequently, LLM‐distilled priors safely guide a reinforcement learning agent during autonomous process optimization,
Jian Yao, Junkang Wu, Jie Su, Fuzhu Wang, Zi Wang, Li Wang, Liming Tan, Lan Huang, Feng Liu, Yong Liu   +9 more
wiley   +1 more source

From Defense Executor to Engineering Target: Harnessing Lignin for Crop Resistance

Advanced Science, EarlyView.
Lignin serves as both a physical and chemical executor of broad‐spectrum plant immunity. This review systematically summarizes classical and recent advances in lignin‐mediated immunity, outlines the multifaceted regulatory modules controlling lignification under biotic stress, discusses key physiological and biochemical mechanisms behind lignin‐based ...
Yanwen Yu, Ke Wang, Huachuan Tuo, Jiankun Li, Liping Xu, Chang‐Jun Liu, Mingyue Gou   +6 more
wiley   +1 more source

Natural Variation of COLD and CATECHINS REGULATOR 1 Coordinately Fine‐Tunes Cold Tolerance and Tea Quality in Tea Plants

Advanced Science, EarlyView.
Multi‐trait genome‐wide association mapping identifies a central hub regulator, COLD AND CATECHINS REGULATOR 1 (CCR1), and its excellent natural allele variation, coordinately enhancing cold tolerance and promoting catechins biosyntheis. CsCCR1 interacts with CsCBF1/3 and is transcriptionally activated by CsLUX and CsKUA1 to promote catechins ...
Yanli Wang, Wei Tong, Qiong Wu, Didi Wu, Yanrui Zhang, Qijuan Gao, Fangdong Li, Zhaoliang Zhang, Wenjie Wang, Chuankui Song, Enhua Xia   +10 more
wiley   +1 more source

CD177 Deficiency Defines a Stable Subtype of Human Neutrophil Granulocytes with Tumor Promoting Activity

Advanced Science, EarlyView.
Human neutrophils exist as two epigenetically imprinted subtypes defined by stable CD177 expression or absence — a ratio that persists across time, circadian rhythms, and inflammation. CD177− neutrophils display a distinct molecular landscape enriched in arginase 1 and lipid metabolism markers, accumulate in head‐and‐neck tumors, and associate with ...
Marcel Jung, Alexander Beer, Susmita Ghosh, Ekaterina Pylaeva, Belal Alshaar, Tobias Tertel, Nils Bastian Leimkühler, Thomas Schroeder, Janine Gronewold, Nina Hagemann, Ayan Mohamud Yusuf, Benedikt Frank, Yiqiao Zhang, Dennis Nagel, Kim Schloeßer, Laura Karsch, Emily Hedtfeld, Sabrina Lohmann, Kathrin Blank, Andreas Kraus, Max Krumbein, Nastassia Kabankova, Hongxiao Wang, Almke Bader, Mathis Richter, Fengjun Zhang, Raphael Chevre, Bernd Giebel, Stephan Lang, Anika Grüneboom, Daniela Maier‐Begandt, Anja Hasenberg, Oliver Soehnlein, Hans Christian Reinhardt, Sven Heiles, Jianxu Chen, Jadwiga Jablonska, Albert Sickmann, Dirk M. Hermann, Matthias Gunzer   +39 more
wiley   +1 more source

Deep Learning Network‐Tailored Microenvironment Matching of 4D Bioprinting Bioactive Scaffolds for Bone Regeneration

Advanced Science, EarlyView.
A DLN dataset was built to analyze MABS composition versus in vitro/in vivo osteogenesis and angiogenesis. An MLP neural network, taking BG morphological parameters as input, extracts bioactive features from these datasets. A rabbit tibial defect model then validates 4D‐printed MABS for adaptability and bone regeneration in critical defects.
Xiongjie Liang, Yuechi Zhang, Weifeng Hu, Shiyan Lv, Fan Jia, Yan Zhang, Feng Wu, Changjiang Yang, Guanqi Zhen, Jinglong Yan, Xu Cui, Wei Zhao, Guanghua Chen   +12 more
wiley   +1 more source

All‐Solution‐Processed Perovskite Light‐Emitting Transistors Enabled by a Fully Organic Architecture

Advanced Electronic Materials, EarlyView.
Fully solution‐processed light‐emitting transistors based on CsPbBr3 perovskite nanocrystals (Pe‐LETs) are demonstrated using an all‐organic platform. By optimizing film formation and device integration, the Pe‐LETs achieve bright green emission with excellent color purity and a peak external quantum efficiency of 4.17 × 10−3 %, marking a step forward ...
Kelment Zahoaliaj, Alice Fappani, Francesca Pallini, Valentina Bellotti, Nicolò Quaresima, Margherita Bolognesi, Mario Prosa, Luca Beverina, Stefano Toffanin   +8 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source