Results 81 to 90 of about 3,211,049 (333)
A Synovium‐on‐Chip Platform to Study Multicellular Interactions in Arthritis
The Synovium‐on‐Chip comprises a thin microporous PDMS membrane to support co‐culture of fibroblast‐like synoviocytes (FLS), THP‐1‐derived macrophages, and endothelial cells, enabling real‐time analysis of synovial‐vascular interactions. FLS migration through the pores drives endothelial remodeling, while TNF‐α stimulation induces robust inflammatory ...
Laurens R. Spoelstra +8 more
wiley +1 more source
The estimation of the large and high-dimensional covariance matrix and precision matrix is a fundamental problem in modern multivariate analysis. It has been widely applied in economics, finance, biology, social networks and health sciences. However, the
Xin Yuan +3 more
doaj +1 more source
Sample Space-time Covariance Matrix Estimation [PDF]
Estimation errors are incurred when calculating the sample space-time covariance matrix. We formulate the variance of this estimator when operating on a finite sample set, compare it to known results, and demonstrate its precision in simulations.
Delaosa, Connor +4 more
openaire +1 more source
Transition metal oxy/carbo‐nitrides show great promise as catalysts for sustainable processes. A Mn‐Mo mixed‐metal oxynitride attains remarkable performance for the direct synthesis of acetonitrile, an important commodity chemical, via sequential C─N and C─C coupling from syngas (C1) and ammonia (N1) feedstocks.
M. Elena Martínez‐Monje +7 more
wiley +1 more source
Portfolio Optimization Using a Consistent Vector-Based MSE Estimation Approach
This paper is concerned with optimizing the weights of the global minimum-variance portfolio (GMVP) in high-dimensional settings where both observation and population dimensions grow at a bounded ratio. Optimizing the GMVP weights is highly influenced by
Maaz Mahadi +3 more
doaj +1 more source
Convex Banding of the Covariance Matrix [PDF]
We introduce a new sparse estimator of the covariance matrix for high-dimensional models in which the variables have a known ordering. Our estimator, which is the solution to a convex optimization problem, is equivalently expressed as an estimator which ...
Bien, Jacob +2 more
core +2 more sources
Risk evaluation with enhanced covariance matrix [PDF]
We propose a route for the evaluation of risk based on a transformation of the covariance matrix. The approach uses a `potential' or `objective' function. This allows us to rescale data from different assets (or sources) such that each data set then has similar statistical properties in terms of their probability distributions.
Krzysztof Urbanowicz +2 more
openaire +2 more sources
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu +3 more
wiley +1 more source
Multivariate time series classification using kernel matrix
Multivariate time series (MTS) classification is a fundamental problem in time series mining, and the approach based on covariance matrix is an attractive way to solve the classification. In this study, it is noted that a traditional covariance matrix is
Jiancheng Sun +4 more
doaj +1 more source
On the regularity of the covariance matrix of a discretized scalar field on the sphere
We present a comprehensive study of the regularity of the covariance matrix of a discretized field on the sphere. In a particular situation, the rank of the matrix depends on the number of pixels, the number of spherical harmonics, the symmetries of the ...
Barreiro, R. B. +4 more
core +1 more source

