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Visual Molecular Dynamics Investigations of the Impact of Hydrophobic Nanoparticles on Prognosis of Alzheimer’s Disease and Cancers [PDF]

, 2012
The possible impact of hydrophobic lectin nanoparticles on the prognosis and progression of Alzheimer's disease (AD) and cancers was investigated by Visual Molecular Dynamics (VMD) computer modeling programs available from the Beckmann Advanced ...
I. C. Baianu, M Charles, V. I. Prisecaru
core +1 more source

Pion form factor in the Kroll-Lee-Zumino model

, 2007
The renormalizable Abelian quantum field theory model of Kroll, Lee, and Zumino is used to compute the one-loop vertex corrections to the tree-level, Vector Meson Dominance (VMD) pion form factor.
Bernard Willers +7 more
core +1 more source

Design of a robot system for improved stress classification using time–frequency domain feature extraction based on electrocardiogram

Paladyn
In recent days, stress is a major phenomenon that adversely affects both individuals and communities. The research in computing the stress factor has wider advantages as it improves personal learning, learning operations, and high productivity that ...
Malhotra Vikas +3 more
doaj +1 more source

Responses of groundwater to precipitation variability and ENSO in the Vietnamese Mekong Delta

Hydrology Research, 2021
Groundwater is a critical component of water resources and has become the primary water supply for agricultural and domestic uses in the Vietnamese Mekong Delta (VMD).
Phong V. V. Le +6 more
doaj +1 more source

Daily lake-level time series spectral analysis using EMD, VMD, EWT, and EFD

Journal of Water and Climate Change
This study investigates the dynamics of daily Urmia Lake level (ULL) changes using spectral analysis tools to discover fluctuating patterns in the ULL series.
Farhad Alizadeh, Kiyoumars Roushangar
doaj +1 more source

Vlasov simulation in multiple spatial dimensions

, 2011
A long-standing challenge encountered in modeling plasma dynamics is achieving practical Vlasov equation simulation in multiple spatial dimensions over large length and time scales.
Fried B. D. +5 more
core +1 more source

Machine Learning Models Coupled with Variational Mode Decomposition: A New Approach for Modeling Daily Rainfall-Runoff

Atmosphere, 2018
Accurate modeling for nonlinear and nonstationary rainfall-runoff processes is essential for performing hydrologic practices effectively. This paper proposes two hybrid machine learning models (MLMs) coupled with variational mode decomposition (VMD) to ...
Youngmin Seo, Sungwon Kim, Vijay P. Singh +2 more
doaj +1 more source

Application of a hybrid model based on GA–ELMAN neural networks and VMD double processing in water level prediction

Journal of Hydroinformatics, 2022
Accurate water level prediction is of great importance for water infrastructures such as dams, embankments, and agriculture. However, the water level has nonlinear characteristics, which make it very challenging to accurately predict the water level ...
Wen Yan Xing +4 more
doaj +1 more source

Optimization method for remaining life prediction of conventional circuit breaker based on deep learning

Diance yu yibiao
In the context of smart grid, aiming at the condition monitoring of conventional circuit breakers with complex mechanical actions, an optimization method for remaining life prediction of conventional circuit breaker based on deep learning is proposed ...
SUN Shuguang +5 more
doaj +1 more source

The hadronic light-by-light contribution to the muon anomalous magnetic moment and renormalization group for EFT

, 2012
We give a short overview of the theory of the muon anomalous magnetic moment with emphasis on the hadronic light-by-light and the pion loop contribution.
Abyaneh, Mehran Zahiri, Bijnens, Johan
core +1 more source

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