Results 51 to 60 of about 257,716 (284)
FEBS Open Bio, EarlyView.This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill +4 more
wiley +1 more source
Fast Matrix Multiplication with Big Sparse Data
Cybernetics and Information Technologies, 2017 Big Data becameabuzz word nowadays due to the evolution of huge volumes of data beyond peta bytes. This article focuses on matrix multiplication with big sparse data.
Somasekhar G., Karthikeyan K.
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Direct multiplicative methods for sparse matrices. Newton methods [PDF]
Компьютерные исследования и моделирование, 2017 We consider a numerically stable direct multiplicative algorithm of solving linear equations systems, which takes into account the sparseness of matrices presented in a packed form. The advantage of the algorithm is the ability to minimize the filling of
Anastasiya Borisovna Sviridenko
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Universality and the circular law for sparse random matrices
, 2012 The universality phenomenon asserts that the distribution of the eigenvalues of random matrix with i.i.d. zero mean, unit variance entries does not depend on the underlying structure of the random entries.
Wood, Philip Matchett
core +1 more source
Aging and Cancer, EarlyView.Natural products target the aging kidney in diabetic nephropathy by restoring the AMPK–SIRT1–Nrf2 axis, reducing oxidative stress, inflammation, fibrosis, and cellular senescence while enhancing mitochondrial biogenesis and antioxidant defenses.
Sherif Hamidu +8 more
wiley +1 more source
The Rank Distribution of Sparse Random Linear Network Coding
IEEE Access, 2019 Sparse random linear network coding (SRLNC) is a promising solution for reducing the complexity of random linear network coding (RLNC). RLNC can be modeled as a linear operator channel (LOC).
Wenlin Chen, Fang Lu, Yan Dong
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Sparse Sums of Positive Semidefinite Matrices [PDF]
ACM Transactions on Algorithms, 2015 Many fast graph algorithms begin by preprocessing the graph to improve its sparsity. A common form of this is spectral sparsification, which involves removing and reweighting the edges of the graph while approximately preserving its spectral properties. This task has a more general linear algebraic formulation in terms of approximating sums of rank-one
de Carli Silva, Marcel K. +2 more
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Glymphatic Dysfunction Reflects Post‐Concussion Symptoms: Changes Within 1 Month and After 3 Months
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Mild traumatic brain injury (mTBI) may alter glymphatic function; however, its progression and variability remain obscure. This study examined glymphatic function following mTBI within 1 month and after 3 months post‐injury to determine whether variations in glymphatic function are associated with post‐traumatic symptom severity ...
Eunkyung Kim +3 more
wiley +1 more source
A constructive bandwidth reduction algorithm—A variant of GPS algorithm
AKCE International Journal of Graphs and Combinatorics, 2016 In this paper, a new viable bandwidth reduction algorithm for reducing the bandwidth of sparse symmetric matrices, is described. The proposed algorithm provides a reliable procedure to reduce the bandwidth and can easily be applied to the sparse ...
L. Jones Tarcius Doss, P. Arathi
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Spectra of sparse random matrices [PDF]
Journal of Physics A: Mathematical and Theoretical, 2008 22 papges, 8 figures (one on graph-Laplacians added), one reference added, some typos ...
openaire +3 more sources