Results 81 to 90 of about 80,806 (260)
Solid Harmonic Wavelet Bispectrum for Image Analysis
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown +3 more
wiley +1 more source
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong +7 more
wiley +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
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 +3 more
wiley +1 more source
Ubiquilin (UBQLN), like many other human proteins, contains both well‐folded and disordered regions. Here, we show that intramolecular interactions between disordered regions and folded domains modulate between open and closed topologies of UBQLN proteins, altering their structure and function.
Jessica K. Niblo +4 more
wiley +1 more source
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 +6 more
wiley +1 more source
Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability
The neurovisceral integration model has shown a key role of the amygdala in neural circuits underlying heart rate variability (HRV) modulation, and suggested that reciprocal connections from amygdala to brain regions centered on the central autonomic ...
Luqing Wei, Hong Chen, Guo-Rong Wu
doaj +1 more source
共分散構造分析は,構造方程式モデリング(SEM : structural equation modeling)とも呼ばれる統計解析技法である.近年,AMOS(SPSS社)など使いやすい優れたソフトウェアが利用できるようになってきたこともあり,社会・人文科学系では人気が高い.最大の特徴は,因果関係のモデルを自由に作って,それを検証することができることである.このモデルには計測されたデータだけでなく,研究者が想定した(実際には直接測定することのできない)構成概念も含めることができる.社会・人文科学系の研究者にとって,共分散構造分析を使う主眼はむしろ構成概念の分析にあり,共分散構造分析は構成概念間の因果関係を調べる手法と言ったほうが現実的な使い方に合っている.モデル構築が自由であるため,回帰分析や因子分析,
openaire +2 more sources
Multi‐trait genome‐wide association mapping identifies a central hub regulator, COLD AND CATECHINS REGULATOR 1 (CCR1), and its excellent natural allele variation, coordinately enhancing cold tolerance and promoting catechins biosyntheis. CsCCR1 interacts with CsCBF1/3 and is transcriptionally activated by CsLUX and CsKUA1 to promote catechins ...
Yanli Wang +10 more
wiley +1 more source
A novel exercise‐inducible myokine acidic ribosomal protein P2 (RPLP2), initially identified from human trials, is presented here, whose circulating levels negatively correlate with clinical anxiety severity. Muscle‐derived RPLP2 enhances hippocampal ribosomal assembly and adult neurogenesis to rescue stress‐induced anxiety deficits.
Peiyu Luo +18 more
wiley +1 more source
An empirical‐aided active learning framework is developed to optimize high‐throughput laser‐induced photothermal annealing of silicon suboxide anodes. By integrating probabilistic machine learning with empirical domain knowledge, this approach achieves optimal electrochemical performance using limited experiments.
Chaeyoung Park +3 more
wiley +1 more source

