Results 121 to 130 of about 24,671,802 (285)

Astrocytic LMP2 Coordinates NF‐κB and TGF‐β1/Smad3 Signaling to Drive Neuroinflammation after Cerebral Ischemia/Reperfusion

Advanced Science, EarlyView.
ABSTRACT Astrocyte reactivity critically shapes neuroinflammatory outcomes after ischemic stroke, yet the upstream regulators governing astrocyte state transitions remain incompletely defined. Here, we identify the immunoproteasome subunit low molecular weight protein 2 (LMP2) as an important modulator of astrocyte functional remodeling following ...
Yanguang Mao, Rulan Ma, Zejing Lin, Huiying Zhao, Yuexian Liu, Yonghe Su, Xu Zhang, Xingyong Chen   +7 more
wiley   +1 more source

An incomplete multi-view multi-label learning with Universum

Abstract In current era, the incomplete multi-view multi-label data sets are widely encountered and they are hard to be processed due to the structure of each instance is complicated and some useful information maybe lost. To this end, this study uses the missing-information-index matrices and adopts Universum learning to promote the ...
Changming Zhu, Lei Wang
openaire   +1 more source

Semantic-Consistent Projective Learning Based Robust Incomplete Multi-View Clustering

In real-world scenarios, incomplete multi-view clustering (IMVC) aims to partition multi-view data into meaningful groups, while certain views are missing for some samples.
Shuping Zhao, Sen Xu, Xianjing Cheng, Kewei Wen   +3 more
core   +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

DTI-RME: a robust and multi-kernel ensemble approach for drug-target interaction prediction

BMC Biology
Background Drug-target interaction (DTI) refers to the specific mechanisms by which drug molecules interact with biological targets within a biological system.
Yuqing Qian, Xin Zhang, Yizheng Wang, Quan Zou, Chen Cao, Yijie Ding, Xiaoyi Guo   +6 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

Reliable Representations Learning for Incomplete Multi-View Partial Multi-Label Classification [PDF]

As a cross-topic of multi-view learning and multi-label classification, multi-view multi-label classification has gradually gained traction in recent years. The application of multi-view contrastive learning has further facilitated this process, however,
Xu, Yong, Nie, Liqiang, Zhang, Bob, Liu, Chengliang, Wen, Jie, Zhang, Min   +5 more
core   +1 more source

Deep learning-based approaches for multi-omics data integration and analysis

BioData Mining
Background The rapid growth of deep learning, as well as the vast and ever-growing amount of available data, have provided ample opportunity for advances in fusion and analysis of complex and heterogeneous data types.
Jenna L. Ballard, Zexuan Wang, Wenrui Li, Li Shen, Qi Long   +4 more
doaj   +1 more source

Magnetoelectric Nanoparticle‐Based Wireless Brain–Computer Interface: Underlying Physics and Projected Technology Pathway

Advanced Science, EarlyView.
Magnetoelectric nanoparticles (MENPs) enable fully wireless, minutely invasive neuromodulation, and potentially neural recording, by converting magnetic into electric and, conversely, electric into magnetic fields, respectively, at high spatiotemporal resolution.
Elric Zhang, Max Shotbolt, Mostafa Abdel‐Mottaleb, Shawnus Chen, Victoria Andre, Jieyuan Tian, Jonathan Shulgach, Max Murphy, Brian Noga, Ping Liang, Darcy Griffin, Douglas Weber, Marta Pardo, Salvador Pane, Sakhrat Khizroev   +14 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