Results 91 to 100 of about 556,837 (257)

In Situ X‐Ray Tomography and Acoustic Emission Monitoring of Damage Evolution in C/C‐SiC Composites Fabricated by Liquid Silicon Infiltration

Advanced Science, EarlyView.
This study investigates how the internal structure of fiber‐reinforced ceramic composites affects their resistance to damage. By combining 3D X‐ray imaging with acoustic emission monitoring during mechanical testing, it reveals how silicon distribution influences crack formation.
Yang Chen, Renato S. M. Almeida, Stefan Flauder, Guillaume Couégnat, Kamen Tushtev, Jürgen Horvath, Peter Wriggers, Kurosch Rezwan   +7 more
wiley   +1 more source

Consistency of Kernel Estimators of Heteroscedastic and Autocorrelated Covariance Matrices [PDF]

Conditions are derived for the consistency of kernel estimators of the covariance matrix of a sum of vectors of dependent heterogeneous random variables, which match those of the currently best-known conditions for the central limit theorem, as required ...
Jong, R.M. de, Davidson, J.
core  

Microscale Mapping of Fiber Strain and Damage in Composite Wrinkled Laminates Using Computed Tomography Assisted Wide‐Angle X‐Ray Scattering

Advanced Science, EarlyView.
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, James Trevarthen, Igor Dolbnya, Wadwan Singhapong, Nicholas Pilato, Richard Butler, Jiraphant Srisuriyachot, Alexander J. G. Lunt   +7 more
wiley   +1 more source

Prior for Structural Materials

EPJ Web of Conferences, 2012
The construction of a library containing prior cross sections and related covariance matrices for nine frequently measured reaction channels of 276 structural materials from 1 to 150 MeV is presented.
Wildpaner V., Srdinko Th., Leeb H., Gundacker St., Neudecker D.   +4 more
doaj   +1 more source

A simple procedure for the comparison of covariance matrices

BMC Evolutionary Biology, 2012
Background Comparing the covariation patterns of populations or species is a basic step in the evolutionary analysis of quantitative traits. Here I propose a new, simple method to make this comparison in two population samples that is based on comparing ...
Garcia Carlos
doaj   +1 more source

Selenium Nanoparticles Selectively Target KRAS G13D to Inhibit Colorectal Cancer

Advanced Science, EarlyView.
The mechanisms of SeNPs therapy in cancer treatment, encompass three parallel actions: (1) seleno‐amino acids, key metabolites, upregulate GPX2 expression, thereby inhibiting tumor metastasis via the GPX2‐HIF1α‐VEGF signaling pathway; (2) selenite (SeO32−), an inorganic metabolite, forms hydrogen bonds with amino acid residues 13–17 of the KRAS G13D ...
Xiaoting Liu, Chong Wu, Shiyao Song, Li Ma, Shaoqing Huang, Yuting He, Qinghai Li, Yanzhou Chang, Dan Jiang, Yong Mei, Junchao Cai, Zhenshuang Du, Tianfeng Chen, Weiling He   +13 more
wiley   +1 more source

Unconstrained Metropolis–Hastings Sampling of Covariance Matrices

Journal of Probability and Statistics
Markov chain Monte Carlo (MCMC), the predominant algorithm for fitting hierarchal models to data in a Bayesian setting, relies on the ability to sample from the full conditional distributions of unobserved parameters.
Daniel Turek
doaj   +1 more source

Portfolio risk measurement: the estimation of the covariance of stock returns [PDF]

A covariance matrix of asset returns plays an important role in modern portfolio analysis and risk management. Despite the recent interests in improving the estimation of a return covariance matrix, there remain many areas for further investigation. This
Liu, Lan
core  

BAYENV2 Covariance Matrices

, 2014
Resulting covariance matrices after removing the 14 top-ranked outliers from the 'control loci' data set. Tabs separate each successive covariance matrix.
Morgan, Theodore J., St. Amand, Paul, Bello, Nora M., Karen A. Garrett (225060), Maricle, Brian R., Sara G. Baer (538361), Paul St. Amand (466078), Baer, Sara G., Nora M. Bello (319413), Mary Knapp (3291480), Matthew B. Galliart (3291477), Miranda M. Gray (3291483), Akhunov, Eduard D., Galliart, Matthew B., Eduard D. Akhunov (533191), Gray, Miranda M., Johnson, Loretta C., Knapp, Mary, Theodore J. Morgan (205401), Loretta C. Johnson (2929833), Brian R. Maricle (2929830), Garrett, Karen A.   +21 more
core   +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