Results 61 to 70 of about 277,175 (273)

Risk of Retinopathy Associated with Long‐Term Use of Hydroxychloroquine in Patients with Rheumatic Diseases: A Systematic Review and Meta‐Analysis

open access: yesArthritis Care &Research, EarlyView.
Objective We aimed to estimate the prevalence and cumulative incidence of hydroxychloroquine retinopathy (HCQ‐R) and its risk factors among patients receiving long‐term HCQ with rheumatic diseases through a systematic review and meta‐analysis of observational studies that used spectral‐domain optical coherence tomography (SD‐OCT) for screening ...
Narsis Daftarian   +4 more
wiley   +1 more source

The Association of Physical Function With Psychosocial Patient‐Reported Outcomes in People With Systemic Lupus Erythematosus

open access: yesArthritis Care &Research, EarlyView.
Objective To evaluate how modifiable psychosocial factors and fatigue relate to physical functioning in patients with systemic lupus erythematosus (SLE). Methods In this cross‐sectional study of two demographically distinct cohorts (Approaches to Positive, Patient‐Centered Experiences of Aging with Lupus [APPEAL] and California Lupus Epidemiology Study
Mrinalini Dey   +8 more
wiley   +1 more source

Sparse recovery for Earth Mover Distance [PDF]

open access: yes2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2010
We initiate the study of sparse recovery problems under the Earth-Mover Distance (EMD). Specifically, we design a distribution over m × n matrices A, for m « n, such that for any x, given Ax, we can recover a k-sparse approximation to x under the EMD distance.
Gupta, Rishi V.   +2 more
openaire   +2 more sources

Sparse signal recovery in Hilbert spaces [PDF]

open access: yes2012 IEEE International Symposium on Information Theory Proceedings, 2012
This paper reports an effort to consolidate numerous coherence-based sparse signal recovery results available in the literature. We present a single theory that applies to general Hilbert spaces with the sparsity of a signal defined as the number of (possibly infinite-dimensional) subspaces participating in the signal's representation.
Pope, Graeme, Bölcskei, Helmut
openaire   +2 more sources

Harnessing Fungal Biowelding for Constructing Mycelium‐Engineered Materials

open access: yesAdvanced Engineering Materials, EarlyView.
Mycelium‐bound composites (MBCs) offer low‐carbon alternatives for construction, yet interfacial bonding remains a critical challenge. This review examines fungal biowelding as a biocompatible adhesive, elucidating mycelium‐mediated interfacial mechanisms and their role in material assembly. Strategies to optimize biowelding are discussed, highlighting
Xue Brenda Bai   +2 more
wiley   +1 more source

Robust Sparse Recovery in Impulsive Noise via M-Estimator and Non-Convex Regularization

open access: yesIEEE Access, 2019
Robust sparse recovery aims at recovering a sparse signal or image from its compressed and contaminated measurements. Under the impulsive noise condition, the performance of traditional sparse recovery algorithms may deteriorate seriously for exploiting &
Le Gao   +5 more
doaj   +1 more source

On the Lightweight Potential of Laser Additive Manufactured NiTi Triply Periodic Minimal Sheet Lattices

open access: yesAdvanced Engineering Materials, EarlyView.
This study explores the lightweight potential of laser additive‐manufactured NiTi triply periodic minimal surface sheet lattices. It systematically investigates the effects of relative density and unit cell size on surface quality, deformation recovery, compression behavior, and energy absorption.
Haoming Mo   +3 more
wiley   +1 more source

A Survey on Nonconvex Regularization-Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning

open access: yesIEEE Access, 2018
In the past decade, sparse and low-rank recovery has drawn much attention in many areas such as signal/image processing, statistics, bioinformatics, and machine learning.
Fei Wen   +3 more
doaj   +1 more source

Sparse Recovery Using Sparse Random Matrices [PDF]

open access: yes, 2010
Over the recent years, a new linear method for compressing high-dimensional data (e.g., images) has been discovered. For any high-dimensional vector x, its sketch is equal to Ax, where A is an m×n matrix (possibly chosen at random). Although typically the sketch length m is much smaller than the number of dimensions n, the sketch contains enough ...
openaire   +1 more source

Performance Analysis for Sparse Support Recovery [PDF]

open access: yesIEEE Transactions on Information Theory, 2010
Submitted to IEEE Trans.
Tang, Gongguo, Nehorai, Arye
openaire   +2 more sources

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