Results 151 to 160 of about 80,587 (266)

Real-Time Forecast of Influenza Outbreak Using Dynamic Network Marker Based on Minimum Spanning Tree. [PDF]

Biomed Res Int, 2020
Yang K, Xie J, Xie R, Pan Y, Liu R, Chen P.   +5 more
europepmc   +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

Frontal Functional Network Disruption Associated with Amyotrophic Lateral Sclerosis: An fNIRS-Based Minimum Spanning Tree Analysis. [PDF]

Front Neurosci, 2020
Borgheai SB, McLinden J, Mankodiya K, Shahriari Y.   +3 more
europepmc   +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

EEG-based minimum spanning tree analysis reveals network disruptions in Alzheimer's disease spectrum: an observational study. [PDF]

Front Aging Neurosci
Ye X, Yan Y, Wang Y, Shi J.
europepmc   +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

Minimum spanning tree analysis of unimpaired individuals at risk of Alzheimer's disease. [PDF]

Brain Commun
García-Colomo A, López-Sanz D, Stam CJ, Hillebrand A, Carrasco-Gómez M, Spuch C, Comis-Tuche M, Maestú F.   +7 more
europepmc   +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

Enhancing energy balance in wireless sensor networks through optimized minimum spanning tree. [PDF]

PeerJ Comput Sci
Saad HM, Shdefat A, Nawaz A, El-Sherbeeny AM, El-Meligy MA, Rana MRR.   +5 more
europepmc   +1 more source

Functional Disorder at the Neural Interface: How Disordered Nanostructures Promote Proper Growth and Differentiation in In Vitro Neural Cultures

Advanced Science, EarlyView.
This work provides a practical guide for neuroengineers to design advanced neural interfaces, embracing and tailoring the concept of functional disorder. By bridging 2D and 3D in vitro models, this work highlights how non‐periodic, spatially heterogeneous, multiscale nanotopography can enable more physiologically relevant platforms for studying neural ...
F. Maita, E. Palmieri, I. Lucarini, L. Montaina, L. Maiolo   +4 more
wiley   +1 more source