Results 251 to 260 of about 4,480,200 (305)

Systemic Extracerebral Atherosclerotic Burden and Dementia Risk After Incident Stroke

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Stroke survivors are at increased risk of dementia, but clinically accessible markers of risk heterogeneity remain limited. Previous studies have largely examined atherosclerotic disease in individual vascular beds rather than the overall burden of systemic extracerebral atherosclerosis.
Zhexuan Yu, Tianxue Chen, Wei Jin, Weifeng Jin, Haitong Wan   +4 more
wiley   +1 more source

Finite Element Analysis of Fiber-Reinforced Pneumatic Soft Actuators: A Hybrid Analytical-Numerical Framework. [PDF]

Materials (Basel)
Fan R, Shao G, Tang J, Wang Y, Xu P.
europepmc   +1 more source

A mechano-integrated gradient electrolyte for long-cycling solid-state lithium metal batteries. [PDF]

Nat Commun
Yi X, Qi G, Pan W, Xiao K, Yang Y, Yang Y, Wang B, Zhao X, Liu X, Li H.   +9 more
europepmc   +1 more source

conMItion: an R package adjusting confounding factors for associations in multi-omics. [PDF]

Bioinformatics
Wang G, Liu F, Chen Z, Davoli T.
europepmc   +1 more source

From linear models to deep learning: statistical advances in genomic selection for animal breeding. [PDF]

J Anim Sci Biotechnol
Zhang L, Zhang M, Wang X, Chen C, Wang S, Zhao Y, Zhang Y, Wang R, Liu Y.   +8 more
europepmc   +1 more source

Non-Resolving Repair in Idiopathic Pulmonary Fibrosis: From Failed Cellular Transitions to Architectural Lock-In. [PDF]

Int J Mol Sci
Ge C, Cui C.
europepmc   +1 more source

On the fundamental bordered matrix of linear estimation [PDF]

, 1990
openaire   +2 more sources

Some of the next articles are maybe not open access.

Related searches:

A robust algorithm to estimate the fundamental matrix

Pattern Recognition Letters, 2000
Abstract A new method, the biepipole constraint algorithm, is developed to estimate the fundamental matrix (F-matrix) based on an 8-parameter model and the geometrical analysis. First, through the analysis of the new constraints, the four parameters of the F-matrix can be estimated by solving a nonlinear unconstraint optimization problem.
Long Quan, Zezhi Chen, Chengke Wu
exaly   +3 more sources

Robust estimation of the fundamental matrix

2010 IEEE International Conference on Image Processing, 2010
Most approaches to estimate the fundamental matrix assume a Gaussian distribution in the errors in view of mathematical tractability. However, this assumption is violated if the distribution computed is not normal. In this paper we propose a robust approach of estimating the fundamental matrix which does not rely on the Gaussian assumption.
Huiyu Zhou 0001, Gerald Schaefer
openaire   +1 more source