Results 81 to 90 of about 513,547 (285)
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 +3 more
wiley +1 more source
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 +3 more
openaire +3 more sources
Advanced Science, EarlyView.Using single‐cell transcriptomic and epigenomic profiling, researchers mapped microglial dysfunction across the lifespan of db/db mice. The authors uncovered a nonlinear microglial remodeling featuring early inflammatory priming, a mid‐stage transcriptional inflection, and late dysfunction.
Jizhou Zhang +6 more
wiley +1 more source
Impact of Data Preprocessing on Integrative Matrix Factorization of Single Cell Data
Frontiers in Oncology, 2020 Integrative, single-cell analyses may provide unprecedented insights into cellular and spatial diversity of the tumor microenvironment. The sparsity, noise, and high dimensionality of these data present unique challenges.
Lauren L. Hsu +3 more
doaj +1 more source
Low-rank and eigenface based sparse representation for face recognition. [PDF]
PLoS ONE, 2014 In this paper, based on low-rank representation and eigenface extraction, we present an improvement to the well known Sparse Representation based Classification (SRC).
Yi-Fu Hou +3 more
doaj +1 more source
Advanced Science, EarlyView.FES‐derived MGE spheroids exhibit progenitor‐stage alterations in developmental trajectory and hypoxia‐responsive transcriptional programs, followed by functional disruption. Gestational hypoxia recapitulates impaired progenitor proliferation, shortened cell‐cycle progression, interneuron developmental abnormalities, and schizophrenia‐like behaviors in
Peiyan Ni +17 more
wiley +1 more source
Advanced Science, EarlyView.Technical limitations often let dominant signals overshadow rare cell types and fine‐grained heterogeneity in spatial transcriptomics. SemanticST, a graph neural network using multi‐semantic graph fusion and a novel min‐cut loss, recovers these subtle patterns.
Roxana Zahedi +7 more
wiley +1 more source
Quaternion PCA and sparse PCA for shape variability
, 2020 Principal component analysis (PCA) is commonly used in the fields of computer graphics and geometry processing for constructing subspaces that represent the variability present in a dataset.
van Steijn, Z.A. (author)
core
Sparse PCA Asymptotics and Analysis of Tree Data [PDF]
, 2012 This research covers two major areas. The first one is asymptotic properties of Principal Component Analysis (PCA) and sparse PCA. The second one is the application of functional data analysis to tree structured data objects.
Shen, Dan
core +1 more source
Advanced Science, EarlyView.Photobiomodulated microglia release engineered extracellular vesicles that deliver UFL1 to the injured spinal cord. UFL1 competitively binds p53 with MDM2, inhibiting p53 ubiquitination and stabilizing p53 signaling. This dual mechanism simultaneously promotes anti‐inflammatory microglial polarization and directs neural stem cell differentiation toward
Yunxiao Fang +12 more
wiley +1 more source