Results 61 to 70 of about 9,784 (260)
Ascidian Ciona larvae initially show strong clockwise tail twisting, which is largely corrected during development. However, a small residual twist remains. This study shows that organized helical myofibrils in tail muscles mechanically stabilize this residual asymmetry, preventing complete restoration of bilateral symmetry and revealing how embryos ...
Yuki S. Kogure +3 more
wiley +1 more source
Covid-19 pandemic data analysis using tensor methods [PDF]
In this paper, we use tensor models to analyze the Covid-19 pandemic data. First, we use tensor models, canonical polyadic, and higher-order Tucker decompositions to extract patterns over multiple modes. Second, we implement a tensor completion algorithm
Dipak Dulal +2 more
doaj +1 more source
Orthogonal tucker decomposition using factor priors for 2D+3D facial expression recognition
In this article, an effective approach is proposed to recognise the 2D+3D facial expression automatically based on orthogonal Tucker decomposition using factor priors (OTDFPFER).
Yunfang Fu +4 more
doaj +1 more source
Nonconvex Tensor Relative Total Variation for Image Completion
Image completion, which falls to a special type of inverse problems, is an important but challenging task. The difficulties lie in that (i) the datasets usually appear to be multi-dimensional; (ii) the unavailable or corrupted data entries are randomly ...
Yunqing Bai, Jihong Pei, Min Li
doaj +1 more source
Robust Tensor Completion Using Transformed Tensor SVD
In this paper, we study robust tensor completion by using transformed tensor singular value decomposition (SVD), which employs unitary transform matrices instead of discrete Fourier transform matrix that is used in the traditional tensor SVD. The main motivation is that a lower tubal rank tensor can be obtained by using other unitary transform matrices
Guang-Jing Song +2 more
openaire +2 more sources
Modelling stem cell differentiation related processes—A practical overview for biologists
Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
Low-Rank Tensor Completion via Tensor Nuclear Norm With Hybrid Smooth Regularization
As a convex surrogate of tensor multi rank, recently the tensor nuclear norm (TNN) obtains promising results in the tensor completion. However, only considering the low-tubal-rank prior is not enough for recovering the target tensor, especially when the ...
Xi-Le Zhao +4 more
doaj +1 more source
Efficient tensor completion: Low-rank tensor train
11 pages, 9 ...
Ho N. Phien +3 more
openaire +2 more sources
Concatenated image completion via tensor augmentation and completion [PDF]
7 pages, 6 figures, submitted to ICSPCS ...
Johann A. Bengua +3 more
openaire +2 more sources
Adenosine triphosphate as a modulator of protein interactions and stability
ATP is best known as the cell's energy currency, but it also shapes how proteins fold, interact, aggregate and form biomolecular condensates. This review explains the emerging physical principles behind these effects, including weak binding to charged protein regions, magnesium‐dependent behaviour and concentration‐dependent control of protein ...
Shuyuan Tan, Robin Curtis
wiley +1 more source

