Results 71 to 80 of about 4,486 (172)

Effect of genetic background on the cardiac phenotype in a mouse model of Emery-Dreifuss muscular dystrophy

open access: yesBiochemistry and Biophysics Reports, 2019
A-type lamins gene (LMNA) mutations cause an autosomal dominant inherited form of Emery-Dreifuss muscular dystrophy (EDMD). EDMD is characterized by slowly progressive muscle weakness and wasting and dilated cardiomyopathy, often leading to heart failure-
Nicolas Vignier   +3 more
doaj   +1 more source

Phenotype-Genotype Analysis of Chinese Patients with Early-Onset LMNA-Related Muscular Dystrophy. [PDF]

open access: yesPLoS ONE, 2015
This study aimed to analyze the correlation between the phenotype and genotype of Chinese patients with early-onset lamin A (LMNA)-related muscular dystrophy (MD).
Dandan Tan   +8 more
doaj   +1 more source

MAPK signaling pathways and HDAC3 activity are disrupted during differentiation of emerin-null myogenic progenitor cells

open access: yesDisease Models & Mechanisms, 2017
Mutations in the gene encoding emerin cause Emery–Dreifuss muscular dystrophy (EDMD). Emerin is an integral inner nuclear membrane protein and a component of the nuclear lamina. EDMD is characterized by skeletal muscle wasting, cardiac conduction defects
Carol M. Collins   +2 more
doaj   +1 more source

Lamin A/C Assembly Defects in LMNA-Congenital Muscular Dystrophy Is Responsible for the Increased Severity of the Disease Compared with Emery–Dreifuss Muscular Dystrophy

open access: yesCells, 2020
LMNA encodes for Lamin A/C, type V intermediate filaments that polymerize under the inner nuclear membrane to form the nuclear lamina. A small fraction of Lamin A/C, less polymerized, is also found in the nucleoplasm. Lamin A/C functions include roles in
Anne T. Bertrand   +8 more
doaj   +1 more source

Integrating autoencoder with Koopman operator to design a linear data‐driven model predictive controller

open access: yesThe Canadian Journal of Chemical Engineering, Volume 103, Issue 3, Page 1099-1111, March 2025.
In this work we develop a data‐driven modelling approach which integrates an autoencoder‐like neural network and dynamic mode decomposition (DMD) methods, to result in a nonlinear modelling technique. In addition, we develop a quadratic programming based model predictive controller (MPC) for the proposed model and implement an observer using ...
Xiaonian Wang   +3 more
wiley   +1 more source

Linear stability analysis of detonations via numerical computation and dynamic mode decomposition

open access: yes, 2017
We introduce a new method to investigate linear stability of gaseous detonations that is based on an accurate shock-fitting numerical integration of the linearized reactive Euler equations with a subsequent analysis of the computed solution via the ...
Kabanov, Dmitry I., Kasimov, Aslan R.
core   +1 more source

Invariance of Gaussian RKHSs Under Koopman Operators of Stochastic Differential Equations With Constant Matrix Coefficients

open access: yesProceedings in Applied Mathematics and Mechanics, Volume 25, Issue 1, March 2025.
ABSTRACT We consider the Koopman operator semigroup (Kt)t≥0$(K^t)_{t\ge 0}$ associated with stochastic differential equations of the form dXt=AXtdt+BdWt$dX_t = AX_t\,dt + B\,dW_t$ with constant matrices A$A$ and B$B$ and Brownian motion Wt$W_t$. We prove that the reproducing kernel Hilbert space HC$\mathbb {H}_C$ generated by a Gaussian kernel with a ...
Friedrich M. Philipp   +4 more
wiley   +1 more source

Hard-disk equation of state: First-order liquid-hexatic transition in two dimensions with three simulation methods

open access: yes, 2012
We report large-scale computer simulations of the hard-disk system at high densities in the region of the melting transition. Our simulations reproduce the equation of state, previously obtained using the event-chain Monte Carlo algorithm, with a ...
Anderson, Joshua A.   +5 more
core   +1 more source

Small‐Signal Synchronization Stability Enhancement of GFL‐Based Renewable Energy Generation Using the Koopman Operator

open access: yesIET Renewable Power Generation, Volume 19, Issue 1, January/December 2025.
A method for system identification and prediction that combines the delay embedding technique with the Koopman operator is proposed. This novel approach allows for the recovery of system states even when only a partial set of state variables is measurable.
Le Zheng   +4 more
wiley   +1 more source

Noro-Frenkel scaling in short-range square well: A Potential Energy Landscape study

open access: yes, 2006
We study the statistical properties of the potential energy landscape of a system of particles interacting via a very short-range square-well potential (of depth $-u_0$), as a function of the range of attraction $\Delta$ to provide thermodynamic insights
D. C. Rapaport   +6 more
core   +1 more source

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