Results 71 to 80 of about 27,772 (256)

Pre‐Regenerative Endothelial Cells Empowered by Antler Blood Exosomes Orchestrate Peripheral Nerve Repair

Advanced Science, EarlyView.
The pre‐regenerative vascular niche (PVN) is essential for nerve repair, yet its endothelial blueprint remains unclear. We identified angiogenic ECs (AECs) as the dominant pre‐regenerative subset and found that antler blood–derived exosomes (AB‐EXO) promote repair via IMP3.
Jinsheng Huang, Qiang Chen, Aihua Jin, Xiaoqi Yang, Hui Zhou, Weiquan Gong, Jin Cheng, Jun Dai, Minjin Wang, Meihua Piao, Yuanyi Wang, Nan Zhou   +11 more
wiley   +1 more source

Single‐Cell Transcriptomic Analysis of Tumor Heterogeneity and the Microenvironment in Pseudomyxoma Peritonei

Advanced Science, EarlyView.
This study presents a single‐cell atlas of pseudomyxoma peritonei spanning primary and paired metastatic lesions. Distinct epithelial substates, stromal remodeling, immune exclusion, lipid metabolic reprogramming, and a candidate angiogenic network were identified in metastatic lesions.
Xi Li, Lei Wang, Lei Ai, Zimeng Li, Zhaochangci Chen, Yuchen Luo, Tianran Zhang, Mengjia Liao, Songhao Wang, Jiajia Cui, Ke Liu, Chengxian Guo, Guodong Liu, Jiye Yin, Wei Wu   +14 more
wiley   +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

Data Reduction in Proportional Hazards Models Applied to Reliability Prediction of Centrifugal Pumps

Machines
This paper presents the use of proportional hazards regression models for predicting the Mean Time Between Failures (MTBF) of centrifugal pumps in the oil and gas industry.
Marc Vila Forteza, Diego Galar, Uday Kumar, Kai Goebel   +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

Deciphering Short‐Range Order in 2D Transition Metal Dichalcogenides: From Origin to Multi‐Scale Property Modulation

Advanced Science, EarlyView.
Short‐range order in 2D transition metal dichalcogenides is revealed as a new design paradigm. Driven by chemical affinity and atomic size, it governs properties across scales. Weak ordering tunes site‐resolved magnetism and d‐band centers, while strong ordering eliminates gap states to open band gaps.
Hanyu Liu, Linggang Zhu, Jian Zhou, Zhimei Sun   +3 more
wiley   +1 more source

Sparse PCA via matrix (2,1)-norm regularization with an application to feature selection

Results in Applied Mathematics
This paper is concerned with sparse PCA via the matrix (2,1)-norm regularization (PCA2,1). It can produce a row-sparse projection, a useful tool in machine learning when it comes to, for example, feature selection, that aims to choose most relevant ...
Li Wang, Jiawei Wang, Ren-Cang Li
doaj   +1 more source

Condition‐Associated Pattern Extraction and Recovery From Multi‐Condition Single‐Cell RNA‐seq Data With CAPER

Advanced Science, EarlyView.
Decoupling biological signals from unwanted variation in multi‑condition single‑cell RNA sequencing data remains challenging. CAPER disentangles condition‑associated biological effects from sample heterogeneity through matrix factorization, producing interpretable latent factors and a batch‑corrected expression matrix.
Ye Li, Jin Ning, An Wang, Minxi Shi, Yuanze Chen, Guoliang Liu, Shiquan Sun   +6 more
wiley   +1 more source

Machine‐Learning Framework for Designing Stable Interfaces in All‐Solid‐State Lithium‐Ion Batteries

Advanced Science, EarlyView.
A data‐driven strategy is developed to discover coating materials for all‐solid‐state lithium batteries. Using calculations of interfacial reactivity, unsupervised pattern recognition, and machine‐learning prediction, the study identifies low‐reactivity compositional patterns and screens new lithium‐based oxide and polyanion candidates, extending ...
Sehyeok Park, Myeongcho Jang, Hun‐Gi Jung, Kyung Yoon Chung, Seungho Yu   +4 more
wiley   +1 more source

Image Compressive Sensing Reconstruction Based on z-Score Standardized Group Sparse Representation

IEEE Access, 2019
Non-local similarity-based group sparse representation (GSR) has shown great potential in image restoration. Considering the universal existing non-stationarity of natural images and the statistic characteristic differences of different components in the
Zhirong Gao, Lixin Ding, Qiming Xiong, Zhongyi Gong, Chengyi Xiong   +4 more
doaj   +1 more source