Results 81 to 90 of about 11,461,097 (250)

Multidisciplinary Coupling Simulation System for Multi-body Separation Process of Near Space Vehicles

open access: yes, 2019
: The simulation of coupling dynamics from multi-body movement, flow field and structural stress field plays a significant role in the separation system design for a near space vehicle.
Ying, Yu   +5 more
core   +1 more source

Cognitive and Neuroimaging Divergence Between Juvenile and Adult FUS Amyotrophic Lateral Sclerosis

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterized by progressive motor neuron degeneration. Fused in sarcoma (FUS)‐associated juvenile ALS (jALS) represents a distinct and aggressive subgroup with rapid deterioration and poor prognosis.
Alexandra V. Jürs   +7 more
wiley   +1 more source

Experimental Study on Low-Frequency Characteristics of Typical Physical Fields for Small Undersea Vehicles

open access: yes水下无人系统学报
Current research on undersea multi-physical field detection mostly focuses on large-scale targets such as ships and submarines, while little attention has been paid to joint multi-physical field detection for small undersea vehicles.
Guangyuan ZHOU   +3 more
doaj   +1 more source

Multi‐Physical Field Coupling Mechanisms and Multi‐Scale Design for All‐Solid‐State Lithium Batteries

open access: yes
All‐solid‐state lithium batteries (ASSLBs) are regarded as a pivotal developmental route for next‐generation energy storage technologies owing to their inherent safety and promising high‐energy‐density capability.
Wenjie Lin   +6 more
core   +1 more source

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif   +17 more
wiley   +1 more source

Light-activated modulation and coupling in integrated polymer-liquid crystal systems [PDF]

open access: yes, 2014
We explore the transfer of an incident light pattern onto the liquid crystal (LC) bulk in a photorefractive cell through an integrated photoconducting layer that modulates the electric field applied to the device.
Buchnev, Oleksandr   +7 more
core   +1 more source

microRNA‐7‐5p and α‐Synuclein SAA Predict Parkinson's Disease Phenoconversion

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Corroborate blood neuron‐derived extracellular vesicle (NDEV) alpha‐synuclein (αSyn), the CSF αSyn seed amplification assay (αSyn‐SAA), and blood microRNA‐7‐5p (miR‐7‐5p) as markers for Parkinson's disease (PD) phenoconversion and determine if combining these markers would help select subjects who would be more likely to phenoconvert.
Shayan Zadegan   +4 more
wiley   +1 more source

Multi-code simulations: A generalized coupling approach

open access: yes, 2005
We present an approach to perform multi-physics simulations by coupling multiple solvers. In order to simplify the coupling process, we have developed the software module CHIMPS (Coupler for High-performance Integrated Multi-Physics Simulations) that ...
X Wu (660808)   +5 more
core  

Ferromagnetism and Superconductivity in the Multi-orbital Hubbard Model : Hund's Rule Coupling versus Crystal-Field Splitting

open access: yes, 2003
The multi-orbital Hubbard model in one dimension is studied using the numerical diagonalization method. Due to the effect of crystal-field splitting △, the fully polarized ferromagnetism, which is observed in the strong coupling regime, becomes ...
大野, 義章   +2 more
core   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli   +3 more
wiley   +1 more source

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