Results 41 to 50 of about 1,270 (253)
Jixie chuandong, 2019 Aiming at the two-phase flow characteristics of the automotive gear, based on the PLIC-VOF algorithm, the three-dimensional churning process model of the gear is numerically calculated by Matlab software.
Zou Lin Du Mingya Jia Bing Xu Jinli
doaj
T1 Over Squared Proton Density Ratio to Characterize Multiple Sclerosis Lesions
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Differentiating remyelinated from demyelinated lesions in MS remains challenging without histological confirmation. This study introduces the T1‐to‐PD2 ratio (TPR) imaging approach and evaluates its ability to characterize MS lesions alongside other quantitative MRI (qMRI) metrics. Methods Thirty individuals with MS (mean age: 47.5 ±
Sarah J. Wright +10 more
wiley +1 more source
A model formulation for the prediction of churning power loss in worm gear transmission
Tribology and Materials, 2022 Churning power loss is a complex process that causes significant loss of energy under splash lubrication of gear units. A set of empirical equations are available that allows for precise churning power losses calculation for only the parallel axis gears.
Hardik Chothani, Kalpesh Maniya
openaire +2 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To investigate which baseline clinical and imaging characteristics best predict TSPO‐PET‐measurable reduction in glial activation following treatment of multiple sclerosis (MS), to utilize this information for designing more efficient biomarker‐based clinical trials targeting glial activation.
Marlene T. Morch +5 more
wiley +1 more source
Divergent genome evolution caused by regional variation in DNA gain and loss between human and mouse. [PDF]
PLoS Computational Biology, 2018 The forces driving the accumulation and removal of non-coding DNA and ultimately the evolution of genome size in complex organisms are intimately linked to genome structure and organisation. Our analysis provides a novel method for capturing the regional
Reuben M Buckley +2 more
doaj +1 more source
Power Losses of Oil-Bath-Lubricated Ball Bearings—A Focus on Churning Losses
LubricantsThis study investigates the power losses of rolling element bearings (REBs) lubricated using an oil bath. Experimental tests conducted on two different deep-groove ball bearings (DGBBs) provide valuable insights into the behaviour of DGBBs under different oil levels, generating essential data for developing accurate models of power losses. Observations
Florian de Cadier de Veauce +6 more
openaire +2 more sources
Natural Frequencies of Levodopa‐Induced Dyskinesia in Parkinson's Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives Abnormal involuntary movements, known as dyskinesias, are common complications of levodopa treatment in patients with Parkinson's disease and can significantly impair quality of life. The underlying pathophysiology remains unclear, and current therapeutic options are limited.
Ioannis U. Isaias +3 more
wiley +1 more source
Flow Field Analysis of Spur Gear Meshing Period Under the State of Oil-immersion Lubrication
Jixie chuandong, 2018 In order to make clear the mechanism of oil churning loss of gearbox and to further improve the efficiency of gear transmission,the factors that effects on oil churning losses are studied.
Zhou Yajie, Wang Bin, Ling Jianhui
doaj
Stage‐Dependent β‐Synuclein Links MRI and Cognitive Decline in Alzheimer's Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Synaptic degeneration drives cognitive decline in Alzheimer's disease (AD), but synaptic biomarkers are scarce. Brain‐enriched β‐synuclein emerged as a synaptic damage marker. We investigated its diagnostic, prognostic, and structural correlates across the AD continuum.
Ulaş Ay +15 more
wiley +1 more source
Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn
CoRRPlasticity, or the ability of an agent to adapt to new tasks, environments, or distributions, is crucial for continual learning. In this paper, we study the loss of plasticity in deep continual RL from the lens of churn: network output variability for out-of-batch data induced by mini-batch training.
Hongyao Tang +4 more
openaire +3 more sources