Results 51 to 60 of about 3,075 (261)

Centering Data Improves the Dynamic Mode Decomposition [PDF]

SIAM Journal on Applied Dynamical Systems, 2020
Dynamic mode decomposition (DMD) is a data-driven method that models high-dimensional time series as a sum of spatiotemporal modes, where the temporal modes are constrained by linear dynamics. For nonlinear dynamical systems exhibiting strongly coherent structures, DMD can be a useful approximation to extract dominant, interpretable modes.
Seth M. Hirsh, Kameron Decker Harris, J. Nathan Kutz, Bingni W. Brunton   +3 more
openaire   +3 more sources

Transcriptional network analysis of PTEN‐protein‐deficient prostate tumors reveals robust stromal reprogramming and signs of senescent paracrine communication

Molecular Oncology, EarlyView.
Combining PTEN protein assessment and transcriptomic profiling of prostate tumors, we uncovered a network enriched in senescence and extracellular matrix (ECM) programs associated with PTEN loss and conserved in a mouse model. We show that PTEN‐deficient cells trigger paracrine remodeling of the surrounding stroma and this information could help ...
Ivana Rondon‐Lorefice, Jose I. Lopez, Aitziber Ugalde‐Olano, Maite Zufiaurre, Ianire Astobiza, Natalia Martin‐Martin, Laura Bozal‐Basterra, Saioa Garcia‐Longarte, Amaia Zabala‐Letona, Sofia Rey, Aida Santos‐Martin, Miguel Unda, Ana Loizaga‐Iriarte, Mariona Graupera, Paolo Nuciforo, Arkaitz Carracedo, Isabel Mendizabal   +16 more
wiley   +1 more source

Analysis of Pressure Fluctuation Characteristics of Central Swirl Combustors Based on Empirical Mode Decomposition

Sensors, 2022
In order to study the characteristics of pressure fluctuation during unstable combustion, experimental studies had been conducted on the mechanism model of the swirl combustor and the industrial swirl combustor.
Xuhuai Wang, Xiang Zhang, Chen Yang, Hao Li, Yong Liu   +4 more
doaj   +1 more source

Tensor-based dynamic mode decomposition [PDF]

Nonlinearity, 2018
Dynamic mode decomposition (DMD) is a recently developed tool for the analysis of the behavior of complex dynamical systems. In this paper, we will propose an extension of DMD that exploits low-rank tensor decompositions of potentially high-dimensional data sets to compute the corresponding DMD modes and eigenvalues.
Klus, Stefan, Gelß, Patrick, Peitz, Sebastian, Schütte, Christof   +3 more
openaire   +3 more sources

Peroxidasin enables melanoma immune escape by inhibiting natural killer cell cytotoxicity

Molecular Oncology, EarlyView.
Peroxidasin (PXDN) is secreted by melanoma cells and binds the NK cell receptor NKG2D, thereby suppressing NK cell activation and cytotoxicity. PXDN depletion restores NKG2D signaling and enables effective NK cell–mediated melanoma killing. These findings identify PXDN as a previously unrecognized immune evasion factor and a potential target to improve
Hsu‐Min Sung, David Bickel, Lena C. M. Krause, Daria Ezeriņa, Christian Ickes, Julian Wojtachnia, Christine S. Gibhardt, Magdalena Shumanska, Khadija Wahni, Andrea Paluschkiwitz, Julia Malo Pueyo, Ekaterina Baranova, Wim Vranken, Hedwig Stanisz, Ioana Stejerean‐Todoran, Michael P. Schön, Joris Messens, Ivan Bogeski   +17 more
wiley   +1 more source

Preconditioned dynamic mode decomposition and mode selection algorithms for large datasets using incremental proper orthogonal decomposition

AIP Advances, 2017
In this letter, we propose a simple and efficient framework of dynamic mode decomposition (DMD) and mode selection for large datasets. The proposed framework explicitly introduces a preconditioning step using an incremental proper orthogonal ...
Yuya Ohmichi
doaj   +1 more source

Data-Driven Pulsatile Blood Flow Physics with Dynamic Mode Decomposition

Fluids, 2020
Dynamic mode decomposition (DMD) is a purely data-driven and equation-free technique for reduced-order modeling of dynamical systems and fluid flow. DMD finds a best fit linear reduced-order model that represents any given spatiotemporal data.
Milad Habibi, Scott T. M. Dawson, Amirhossein Arzani   +2 more
doaj   +1 more source

Rethinking plastic waste: innovations in enzymatic breakdown of oil‐based polyesters and bioplastics

FEBS Open Bio, EarlyView.
Plastic pollution remains a critical environmental challenge, and current mechanical and chemical recycling methods are insufficient to achieve a fully circular economy. This review highlights recent breakthroughs in the enzymatic depolymerization of both oil‐derived polyesters and bioplastics, including high‐throughput protein engineering, de novo ...
Elena Rosini, Nicolò Antonelli, Gianluca Molla   +2 more
wiley   +1 more source

The Relationship Between Inflammation and Central Nervous System in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Aim Multiple sclerosis is an autoimmune demyelination disease that is seen especially in the young population and has a progressive course, causing motor, sensory, and cognitive deficits. In the literature, the pathogenesis of MS disease and the interconnection between the immune and central nervous system in the disease have not been fully ...
Gamze Ansen, Ali Behram Salar, Abdulkadir Ermis, Erkingul Birday, Lutfu Hanoglu, Bayram Ufuk Sakul   +5 more
wiley   +1 more source

Dynamic Mode Decomposition via Polynomial Root-Finding Methods

Mathematics
Dynamic mode decomposition (DMD) is a powerful data-driven tool for analyzing complex systems that has gained significant attention in various scientific and engineering disciplines.
Gyurhan Nedzhibov
doaj   +1 more source