Results 121 to 130 of about 8,380,583 (373)
Dimensional reduction to hypersurface of foliation [PDF]
, 2013 When the bulk spacetime has a foliation structure, the collective dynamics of the hypersurfaces should reveal certain aspects of the bulk physics. The procedure of reducing the bulk to a hypersurface, called ADM reduction, was implemented in [3] where ...
I. Park
semanticscholar +1 more source
Molecular Oncology, EarlyView.CD226+CD8+ T cells express elevated levels of RUNX2, exhibit higher proliferation capacity, cytokines and cytolytic molecules expression, and migratory capacity. In contrast, CD226−CD8+ T cells display an exhausted phenotype associated with the increased expression of co‐inhibitory receptors and impaired effector functions.
Maryam Rezaeifar +4 more
wiley +1 more source
Chiral anomaly, dimensional reduction, and magnetoresistivity of Weyl and Dirac semimetals [PDF]
, 2013 By making use of the Kubo formula, we calculate the conductivity of Dirac and Weyl semimetals in a magnetic field. We find that the longitudinal (along the direction of the magnetic field) magnetoresistivity is negative at sufficiently large magnetic ...
E. V. Gorbar +2 more
semanticscholar +1 more source
Molecular Oncology, EarlyView.Transient receptor potential melastatin‐4 (TRPM4) is overexpressed in prostate cancer (PCa). Knockout of TRPM4 resulted in reduced PCa tumor spheroid size and decreased PCa tumor spheroid outgrowth. In addition, lack of TRPM4 increased cell death in PCa tumor spheroids.
Florian Bochen +6 more
wiley +1 more source
Low-rank methods for high-dimensional approximation and model order reduction [PDF]
, 2015 Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated.
A. Nouy
semanticscholar +1 more source
Dimensionality Reduction with Image Data [PDF]
, 2004 A common objective in image analysis is dimensionality reduction. The most common often used data-exploratory technique with this objective is principal component analysis. We propose a new method based on the projection of the images as matrices after a Procrustes rotation and show that it leads to a better reconstruction of images.
Benito Bonito, Mónica, Peña, Daniel
openaire +4 more sources
Dimensional reduction of Dirac operator [PDF]
Journal of Mathematical Physics, 2006 We construct an explicit example of dimensional reduction of the free massless Dirac operator with an internal SU(3) symmetry, defined on a 12-dimensional manifold that is the total space of a principal SU(3)-bundle over a four-dimensional (nonflat) pseudo-Riemannian manifold.
Petko A. Nikolov, Gergana R. Ruseva
openaire +3 more sources
Molecular Oncology, EarlyView.Prostate cancer is a leading malignancy with significant clinical heterogeneity in men. An 11‐gene signature derived from dysregulated epithelial cell markers effectively predicted biochemical recurrence‐free survival in patients who underwent radical surgery or radiotherapy.
Zhuofan Mou, Lorna W. Harries
wiley +1 more source
The class of infinite dimensional quasipolaydic equality algebras is not finitely axiomatizable over its diagonal free reducts [PDF]
arXiv, 2013 We show that the class of infinite dimensional quasipolaydic equality algebras is not finitely axiomatizable over its diagonal free ...
arxiv
A Local Similarity-Preserving Framework for Nonlinear Dimensionality Reduction with Neural Networks [PDF]
arXiv, 2021 Real-world data usually have high dimensionality and it is important to mitigate the curse of dimensionality. High-dimensional data are usually in a coherent structure and make the data in relatively small true degrees of freedom. There are global and local dimensionality reduction methods to alleviate the problem.
arxiv