Results 31 to 40 of about 2,509 (175)
Angewandte Chemie, EarlyView.Epimer discrimination remains challenging due to subtle NMR differences. Here, we propose a methodology based on 13C‐RCSA and RDC anisotropic parameters, enabling the assignment of two flexible tetraprenyltoluquinol epimers (1a and 1b) with remote stereoclusters.
Juan Carlos C. Fuentes‐Monteverde +6 more
wiley +2 more sources
Вестник рентгенологии и радиологии, 2019 Objective. To compare diffusion-tensor imaging (DTI) measures in different anatomic regions of the brain in patients with an isolated Alzheimer's disease (AD) and patients with AD and small-vessel disease (SVD).Material and methods.
V. A. Perepelov +6 more
doaj +1 more source
Mechanisms of cognitive impairment in cerebral small vessel disease: multimodal MRI results from the St George's cognition and neuroimaging in stroke (SCANS) study. [PDF]
PLoS ONE, 2013 Cerebral small vessel disease (SVD) is a common cause of vascular cognitive impairment. A number of disease features can be assessed on MRI including lacunar infarcts, T2 lesion volume, brain atrophy, and cerebral microbleeds.
Andrew J Lawrence +6 more
doaj +1 more source
Tensor-SVD Based Graph Learning for Multi-View Subspace Clustering [PDF]
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 Low-rank representation based on tensor-Singular Value Decomposition (t-SVD) has achieved impressive results for multi-view subspace clustering, but it does not well deal with noise and illumination changes embedded in multi-view data. The major reason is that all the singular values have the same contribution in tensor-nuclear norm based on t-SVD ...
Quanxue Gao +4 more
openaire +4 more sources
Serum Neurofilament Light Chain Levels Are Related to Small Vessel Disease Burden [PDF]
Journal of Stroke, 2018 Background and Purpose Neurofilament light chain (NfL) is a blood marker for neuroaxonal damage. We assessed the association between serum NfL and cerebral small vessel disease (SVD), which is highly prevalent in elderly individuals and a major cause of ...
Marco Duering +16 more
doaj +1 more source
Objects features extraction by singular projections of data tensor to matrices
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie ŚrodowiskaThe problem of multidimensional tensor objects features extraction in a manner of matrices is considered. The tensor’ elements Higher Order Singular Value Decomposition (SVD) is presented as the d-SVD which includes SVD of the tensor reshaped as a ...
Yuriy Bunyak +3 more
doaj +1 more source
Rank revealing‐based tensor completion using improved generalized tensor multi‐rank minimization
IET Signal Processing, 2021 The authors address the problem of tensor completion from limited samplings. An improved generalized tubal Kronecker decomposition is first proposed to reveal the tensor structure of the targeted data, and the improved generalized tensor tubal‐rank and ...
Wei Z. Sun, Peng Zhang, Bo Zhao
doaj +1 more source
Quantum Algorithms for Tensor-SVD
2024 IEEE International Conference on Quantum Computing and Engineering (QCE)9 pages, 8 ...
Jezer Jojo +2 more
openaire +2 more sources
Multi-Directional Tensor Average Rank Regularization for High-Order Tensor Completion
IEEE AccessRecently, the high-order tensor Singular Value Decomposition (t-SVD) and the t-SVD rank has achieved great success in tensor completion. However, the t-SVD rank lacks the flexibility to capture the correlations between different modes of a high-order ...
Zixuan Han, Mingjian Gu, Yong Hu
doaj +1 more source