Results 71 to 80 of about 501,769 (296)

Improving approximate matrix factorizations for implicit time integration in air pollution modelling [PDF]

open access: yes, 2000
For a long time operator splitting was the only computationally feasible way of implicit time integration in large scale Air Pollution Models. A recently proposed attractive alternative is Rosenbrock schemes combined with Approximate Matrix Factorization
Botchev, M.A., Verwer, J.G.
core   +3 more sources

Measurements of strongly-anisotropic g-factors for spins in single quantum states

open access: yes, 2002
We have measured the full angular dependence, as a function of the direction of magnetic field, for the Zeeman splitting of individual energy states in copper nanoparticles. The g-factors for spin splitting are highly anisotropic, with angular variations
C. P. Slichter   +4 more
core   +1 more source

On regular splittings and graph compatible splittings of an M-matrix

open access: yesLinear Algebra and its Applications, 1992
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +1 more source

Rethinking plastic waste: innovations in enzymatic breakdown of oil‐based polyesters and bioplastics

open access: yesFEBS Open Bio, EarlyView.
Plastic pollution remains a critical environmental challenge, and current mechanical and chemical recycling methods are insufficient to achieve a fully circular economy. This review highlights recent breakthroughs in the enzymatic depolymerization of both oil‐derived polyesters and bioplastics, including high‐throughput protein engineering, de novo ...
Elena Rosini   +2 more
wiley   +1 more source

A Robust Hermitian and Skew-Hermitian Based Multiplicative Splitting Iterative Method for the Continuous Sylvester Equation

open access: yesMathematics
For solving the continuous Sylvester equation, a class of Hermitian and skew-Hermitian based multiplicative splitting iteration methods is presented. We consider two symmetric positive definite splittings for each coefficient matrix of the continuous ...
Mohammad Khorsand Zak   +1 more
doaj   +1 more source

Entanglement of random vectors

open access: yes, 2006
We analytically calculate the average value of i-th largest Schmidt coefficient for random pure quantum states. Schmidt coefficients, i.e., eigenvalues of the reduced density matrix, are expressed in the limit of large Hilbert space size and for ...
Marko Žnidarič   +5 more
core   +1 more source

Adaptive high-order splitting schemes for large-scale differential Riccati equations [PDF]

open access: yes, 2017
We consider high-order splitting schemes for large-scale differential Riccati equations. Such equations arise in many different areas and are especially important within the field of optimal control.
Stillfjord, Tony
core   +2 more sources

The MMP‐9/TIMP‐1 Ratio and Concentrations of Osteopontin Are Elevated in Cerebrospinal Fluid of People With Multiple Sclerosis and Decrease After Autologous Hematopoietic Stem Cell Transplantation

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives To evaluate the utility of cerebrospinal fluid (CSF) biomarkers—matrix metalloproteinase‐9 (MMP‐9), tissue inhibitor of metalloproteinases‐1 (TIMP‐1), the MMP‐9/TIMP‐1 ratio, and osteopontin (OPN)—as indicators of blood–brain barrier (BBB) integrity and disease activity in people with relapsing–remitting multiple sclerosis (pwMS ...
Ivan Pavlovic   +6 more
wiley   +1 more source

Improved convergence analysis on the accelerated modulus-based matrix splitting iteration method for nonlinear complementarity problems

open access: yesAIMS Mathematics
In this paper, we focused on the accelerated modulus-based matrix splitting iteration method for solving nonlinear complementarity problems. A thorough analysis of convergence conditions for the method was conducted. Compared to the work 'B. H. Huang, C.
Yanmei Chen, Yihang Lin, Jianwei Dong
doaj   +1 more source

Rank-Sparsity Incoherence for Matrix Decomposition [PDF]

open access: yes, 2009
Suppose we are given a matrix that is formed by adding an unknown sparse matrix to an unknown low-rank matrix. Our goal is to decompose the given matrix into its sparse and low-rank components.
Chandrasekaran, Venkat   +3 more
core   +7 more sources

Home - About - Disclaimer - Privacy