Results 61 to 70 of about 1,853,525 (263)

A turbulence reduced order model based on non-interpolated convolutional autoencoder

open access: yesXibei Gongye Daxue Xuebao
Reduced-order modeling stands as a pivotal method in curbing the computational expenses linked with expansive fluid dynamics quandaries by employing proxy numerical simulations.
WU Pin, ZHANG Bo, SONG Chao, ZHOU Zhu
doaj   +1 more source

Reciprocal control of viral infection and phosphoinositide dynamics

open access: yesFEBS Letters, EarlyView.
Phosphoinositides, although scarce, regulate key cellular processes, including membrane dynamics and signaling. Viruses exploit these lipids to support their entry, replication, assembly, and egress. The central role of phosphoinositides in infection highlights phosphoinositide metabolism as a promising antiviral target.
Marie Déborah Bancilhon, Bruno Mesmin
wiley   +1 more source

Reduced Order Modeling and Sliding Mode Control of Active Magnetic Bearing

open access: yesIEEE Access, 2019
Due to the accelerated growth in the field of power electronics and controller design techniques, the usage of the active magnetic bearing has picked up in industries. Active magnetic bearing helps the rotor to rotate freely without any physical contact.
Sudipta Saha   +3 more
doaj   +1 more source

Calpain small subunit homodimerization is robust and calcium‐independent

open access: yesFEBS Letters, EarlyView.
Calpains dimerize via penta‐EF‐hand (PEF) domains. Using single‐molecule force spectroscopy, we measured the strength and kinetics of PEF–PEF homodimer binding. The interaction is robust, shows a transient conformational step before dissociation, and remains largely insensitive to Ca2+.
Nesha May O. Andoy   +4 more
wiley   +1 more source

Reduced order models based on pod method for schrödinger equations

open access: yesMathematical Modelling and Analysis, 2013
Reduced-order models (ROM) are developed using the proper orthogonal decomposition (POD) for one dimensional linear and nonlinear Schrödinger equations. The main aim of this paper is to study the accuracy and robustness of the ROM approximations.
Gerda Jankevičiutė   +3 more
doaj   +1 more source

An orifice shape-based reduced order model of patient-specific mitral valve regurgitation

open access: yesEngineering Applications of Computational Fluid Mechanics, 2021
Mitral valve regurgitation (MR) is one of the most prevalent valvular heart diseases. Its quantitative assessment is challenging but crucial for treatment decisions.
J. Franz   +12 more
doaj   +1 more source

Structural insights into an engineered feruloyl esterase with improved MHET degrading properties

open access: yesFEBS Letters, EarlyView.
A feruloyl esterase was engineered to mimic key features of MHETase, enhancing the degradation of PET oligomers. Structural and computational analysis reveal how a point mutation stabilizes the active site and reshapes the binding cleft, expading substrate scope.
Panagiota Karampa   +5 more
wiley   +1 more source

A Fractional-Order Model-Assisted Reduced-Order ADRC for Photoelectric Stabilized Platforms

open access: yesIEEE Access
To enhance the dynamic performance and disturbance rejection capability of photoelectric stabilized platforms, this study proposes a Fractional-Order Model-assisted Reduced-order Linear Active Disturbance Rejection Control (FO-MRLADRC) algorithm.
Guoyu Lin   +3 more
doaj   +1 more source

Valosin‐containing protein counteracts ATP‐driven dissolution of FUS condensates through its ATPase activity in vitro

open access: yesFEBS Letters, EarlyView.
Biomolecular condensates formed by fused in sarcoma (FUS) are dissolved by high ATP concentrations yet persist in cells. Using a reconstituted system, we demonstrate that valosin‐containing protein (VCP), an AAA+ ATPase, counteracts ATP‐driven dissolution of FUS condensates through its D2 ATPase activity.
Hitomi Kimura   +2 more
wiley   +1 more source

KROM: Kernelized Reduced Order Modeling

open access: yesCoRR
We propose KROM, a kernel-based reduced-order framework for fast solution of nonlinear partial differential equations. KROM formulates PDE solution as a minimum-norm (Gaussian-process) recovery problem in an RKHS, and accelerates the resulting kernel solves by sparsifying the precision matrix via sparse Cholesky factorization.
Aras Bacho, Jonghyeon Lee, Houman Owhadi
openaire   +2 more sources

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