scholarly journals Amplitude, density, and current correlations of strongly disordered superconductors

2015 ◽  
Vol 92 (6) ◽  
Author(s):  
G. Seibold ◽  
L. Benfatto ◽  
C. Castellani ◽  
J. Lorenzana
Keyword(s):  
Disordered Superconductors ◽  
Amplitude Density ◽  
Current Correlations

Current Correlations in Strongly Disordered Superconductors

2015 ◽  
Vol 29 (3) ◽  
pp. 577-580
Author(s):  
G. Seibold ◽  
L. Benfatto ◽  
C. Castellani ◽  
J. Lorenzana
Keyword(s):  
Disordered Superconductors ◽  
Current Correlations

Heat capacity of mesoscopically disordered superconductors with emphasis on MgB2

2002 ◽  
Vol 14 (41) ◽  
pp. 9621-9629 ◽  
Author(s):  
A M Gabovich ◽  
Mai Suan Li ◽  
M Peka a ◽  
H Szymczak ◽  
A I Voitenko
Keyword(s):  
Heat Capacity ◽  
Disordered Superconductors

scholarly journals Low-temperature anomaly in disordered superconductors near Bc2 as a vortex-glass property

2018 ◽  
Vol 15 (1) ◽  
pp. 48-53 ◽  
Author(s):  
Benjamin Sacépé ◽  
Johanna Seidemann ◽  
Frédéric Gay ◽  
Kevin Davenport ◽  
Andrey Rogachev ◽  
...  
Keyword(s):  
Low Temperature ◽  
Temperature Anomaly ◽  
Vortex Glass ◽  
Disordered Superconductors ◽  
Glass Property

Optimal Spindle Detection Parameters for Predicting Cognitive Performance

SLEEP ◽  
2022 ◽  
Author(s):  
Noor Adra ◽  
Haoqi Sun ◽  
Wolfgang Ganglberger ◽  
Elissa M Ye ◽  
Lisa W Dümmer ◽  
...  
Keyword(s):  
Regression Models ◽  
Peak Frequency ◽  
Sleep Spindles ◽  
Methodological Challenge ◽  
Optimal Parameters ◽  
Mean Frequency ◽  
Multiple Regression Models ◽  
Parameter Interactions ◽  
Amplitude Density

Abstract Study Objectives Alterations in sleep spindles have been linked to cognitive impairment. This finding has contributed to a growing interest in identifying sleep-based biomarkers of cognition and neurodegeneration, including sleep spindles. However, flexibility surrounding spindle definitions and algorithm parameter settings present a methodological challenge. The aim of this study was to characterize how spindle detection parameter settings influence the association between spindle features and cognition and to identify parameters with the strongest association with cognition. Methods Adult patients (n=167, 49 ± 18 years) completed the NIH Toolbox Cognition Battery after undergoing overnight diagnostic polysomnography recordings for suspected sleep disorders. We explored 1000 combinations across seven parameters in Luna, an open-source spindle detector, and used four features of detected spindles (amplitude, density, duration, and peak frequency) to fit linear multiple regression models to predict cognitive scores. Results Spindle features (amplitude, density, duration, and mean frequency) were associated with the ability to predict raw fluid cognition scores (r=0.503) and age-adjusted fluid cognition scores (r=0.315) with the best spindle parameters. Fast spindle features generally showed better performance relative to slow spindle features. Spindle features weakly predicted total cognition and poorly predicted crystallized cognition regardless of parameter settings. Conclusion Our exploration of spindle detection parameters identified optimal parameters for studies of fluid cognition and revealed the role of parameter interactions for both slow and fast spindles. Our findings support sleep spindles as a sleep-based biomarker of fluid cognition.

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