Results 71 to 80 of about 25,940 (257)

A Convex Sparse PCA for Feature Analysis

CoRR, 2014
Principal component analysis (PCA) has been widely applied to dimensionality reduction and data pre-processing for different applications in engineering, biology and social science. Classical PCA and its variants seek for linear projections of the original variables to obtain a low dimensional feature representation with maximal variance.
Xiaojun Chang, Feiping Nie 0001, Yi Yang 0001, Heng Huang 0001   +3 more
openaire   +2 more sources

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

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

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

STAID: A Self‐Refining Deep Learning Framework for Spatial Cell‐Type Deconvolution with Biologically Informed Modeling

Advanced Science, EarlyView.
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu, Shuli Sun, Zhengliang Lv, Xinyu Liu, Yihua Wang, Bingqiang Liu   +5 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

PhosSight: A Unified Deep Learning Framework Boosting and Accelerating Phosphoproteome Identification to Enable Biological Discoveries

Advanced Science, EarlyView.
PhosSight is a unified deep‐learning framework for phosphoproteome identification, featured by a phosphorylation‐aware detectability predictor. It improves identification sensitivity in DDA through deep re‐localization and rescoring, accelerates DIA searches by detectability‐guided spectral library pruning, and expands phosphoproteome coverage to ...
Ben Wang, Zhiyuan Cheng, Chengying She, Hongwei Zhao, Jiahui Zhang, Lin Lv, Zhihao Yan, Hongwen Zhu, Lizhuang Liu, Yan Fu, Xinpei Yi   +10 more
wiley   +1 more source

Single‐Cell Annotation and Localization via Integrating Spatial Transcriptomics Maps the Mouse Ocular Atlas and RAO Dynamics

Advanced Science, EarlyView.
We developed the ASCAL pipeline, integrating complementary spatial transcriptomics, to construct a high‐fidelity mouse whole‐eye single‐cell atlas. Applying ASCAL to a retinal artery occlusion (RAO) model revealed spatially restricted immune activation localized to the ganglion cell layer and the selective depletion of a translationally active, outer ...
Chen Du, Yinming Li, Ziyue Li, Yuedan Wang, Shaopeng Li, Yijie Wang, Yingying Qu, Bingyang Lv, Ying Li, Ting Chen, Yu Zhou, Xuan Xiao   +11 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