Results 111 to 120 of about 662,175 (342)

Metformin promotes mitochondrial integrity through AMPK‐signaling in Leber's hereditary optic neuropathy

open access: yesFEBS Open Bio, EarlyView.
Metformin mediates mitochondrial quality control in Leber's hereditary optic neuropathy (LHON) fibroblasts carrying mtDNA mutations. At therapeutic levels, metformin activates AMPK signaling to restore mitochondrial dynamics by promoting fusion and restraining fission, while preserving mitochondrial mass, enhancing autophagy/mitophagy and biogenesis ...
Chatnapa Panusatid   +3 more
wiley   +1 more source

Confidence-Level-Based New Adaptive Particle Filter for Nonlinear Object Tracking

open access: yesInternational Journal of Advanced Robotic Systems, 2012
Nonlinear object tracking from noisy measurements is a basic skill and a challenging task of mobile robotics, especially under dynamic environments. The particle filter is a useful tool for nonlinear object tracking with non-Gaussian noise.
Xiaoyong Zhang   +3 more
doaj   +1 more source

Geometrical Optimization of Closed-End Cylindrical Air Filter Using CFD Simulation [PDF]

open access: yes대한환경공학회지
This research aims to evaluate the effect of porous filter configuration on flow characteristics within filter using CFD simulation. This simulation model was chosen for comprehensive analysis that considers different variables affecting the filter ...
K D Lakshitha Rukshan   +2 more
doaj   +1 more source

Wearable Robot Sensor Signal Prediction Algorithm Analysis and Study based on Particle Filtering [PDF]

open access: bronze, 2022
Yanli Zhang   +33 more
openalex   +1 more source

Particle Filtering and Smoothing Using Windowed Rejection Sampling [PDF]

open access: yes, 2014
"Particle methods" are sequential Monte Carlo algorithms, typically involving importance sampling, that are used to estimate and sample from joint and marginal densities from a collection of a, presumably increasing, number of random variables.
Corcoran, J. N., Jennings, D.
core  

Bridging the ensemble Kalman and particle filter

open access: yes, 2012
In many applications of Monte Carlo nonlinear filtering, the propagation step is computationally expensive, and hence, the sample size is limited. With small sample sizes, the update step becomes crucial.
Frei, Marco, Künsch, Hans R.
core   +1 more source

Bernoulli Race Particle Filters

open access: yes, 2019
19 ...
Schmon, S, Deligiannidis, G, Doucet, A
openaire   +3 more sources

SNUPN‐Related Muscular Dystrophy: Novel Phenotypic, Pathological and Functional Protein Insights

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective SNUPN‐related muscular dystrophy or LGMDR29 is a new entity that covers from a congenital or childhood onset pure muscular dystrophy to more complex phenotypes combining neurodevelopmental features, cataracts, or spinocerebellar ataxia. So far, 12 different variants have been described.
Nuria Muelas   +18 more
wiley   +1 more source

Implementation of unknown parameter estimation procedure for hybrid and discrete non‐linear systems

open access: yesIET Radar, Sonar & Navigation
The application of the hybrid extended Kalman filter (HEKF), hybrid unscented Kalman filter (HUKF), hybrid particle filter (HPF), and hybrid extended Kalman particle filter (HEKPF) is discussed for hybrid non‐linear filter problems, when prediction ...
Mahdi Razm‐Pa
doaj   +1 more source

Hopfield Neural Networks for Online Constrained Parameter Estimation With Time‐Varying Dynamics and Disturbances

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley   +1 more source

Home - About - Disclaimer - Privacy