Results 61 to 70 of about 3,211,049 (333)

Normal‐Appearing White Matter Injury Mediates Chronic Deep Venous Hypoxia and Disease Progression in Multiple Sclerosis

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore how cerebral hypoxia and Normal‐Appearing White Matter (NAWM) integrity affect MS lesion burden and clinical course. Methods Seventy‐nine MS patients, including 13 clinically isolated syndrome (CIS) patients and 66 relapsing–remitting multiple sclerosis (RRMS) patients, and 44 healthy controls (HCs) were recruited from ...
Xinli Wang   +8 more
wiley   +1 more source

Differential Item Functioning on the Patient Health Questionnaire 8 by Disease Subtype, Language, Sex, and Age Among People With Systemic Sclerosis: A Scleroderma Patient‐Centered Intervention Network Cohort Study

open access: yesArthritis Care &Research, EarlyView.
Objective Somatic items used in depression assessments can potentially overlap with symptoms related to physical illness, including systemic sclerosis (SSc). No studies have looked at whether somatic depression items may be influenced by diffuse versus limited SSc disease subtypes, which are associated with varying degrees of symptom presentation.
Sophie Hu   +110 more
wiley   +1 more source

An unbiased estimator for the ellipticity from image moments [PDF]

open access: yes, 2017
An unbiased estimator for the ellipticity of an object in a noisy image is given in terms of the image moments. Three assumptions are made: i) the pixel noise is normally distributed, although with arbitrary covariance matrix, ii) the image moments are ...
Tessore, Nicolas
core   +2 more sources

A Robust Capon Beamforming Approach for Sparse Array Based on Importance Resampling Compressive Covariance Sensing

open access: yesIEEE Access, 2019
Reconstructing the interference-plus-noise covariance matrix instead of searching for the optimal diagonal loading factor for the sample covariance matrix is a good method for calculating the adaptive beamforming coefficients.
Yuguan Hou   +5 more
doaj   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

open access: yesAdvanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt   +8 more
wiley   +1 more source

Covariance Matrix Reconstruction of GRACE Monthly Solutions Using Common Factors and Individual Formal Errors

open access: yesIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Accurate error covariance is crucial for postprocessing gravity recovery and climate experiment (GRACE) gravity field solutions in terms of spherical harmonic coefficients (SHCs).
Lin Zhang   +3 more
doaj   +1 more source

Persymmetric Adaptive Detectors of Subspace Signals in Homogeneous and Partially Homogeneous Clutter

open access: yesLeida xuebao, 2015
In the field of adaptive radar detection, an effective strategy to improve the detection performance is to exploit the structural information of the covariance matrix, especially in the case of insufficient reference cells.
Ding Hao   +3 more
doaj   +1 more source

Moments of minors of Wishart matrices

open access: yes, 2008
For a random matrix following a Wishart distribution, we derive formulas for the expectation and the covariance matrix of compound matrices. The compound matrix of order $m$ is populated by all $m\times m$-minors of the Wishart matrix.
Drton, Mathias   +2 more
core   +2 more sources

Estimating Mean and Covariance Structure with Reweighted Least Squares [PDF]

open access: yes, 2020
Does Reweighted Least Squares (RLS) perform better in small samples than maximum likelihood (ML) for mean and covariance structure? ML statistics in covariance structure analysis are based on the asymptotic normality assumption; however, actual ...
Zheng, Bang Quan
core  

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