We applied the Hurst exponent technique to an experimental study of rough metallic surface profiles and the speckle patterns generated by them. Characterization of important statistical properties of the surface profile and speckle patterns were performed. We observed a clear correlation between the Hurst exponent of a surface profile and the one calculated from the associated speckle patterns. Therefore, in principle, information of the Hurst exponent of the profile can be obtained from the Hurst exponent of speckle patterns. Range and sampling analyses were performed in the Hurst exponent calculations showing the robustness of the method. As an additional application, we performed a basic simulation to show that the Hurst exponent is sensitive to surface waviness.
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http://dx.doi.org/10.1364/AO.390125 | DOI Listing |
Adv Sci (Weinh)
January 2025
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, H3A 2B4, Canada.
Excitation-inhibition (E/I) imbalance is theorized as a key mechanism in the pathophysiology of epilepsy, with ample research focusing on elucidating its cellular manifestations. However, few studies investigate E/I imbalance at the macroscale, whole-brain level, and its microcircuit-level mechanisms and clinical significance remain incompletely understood. Here, the Hurst exponent, an index of the E/I ratio, is computed from resting-state fMRI time series, and microcircuit parameters are simulated using biophysical models.
View Article and Find Full Text PDFJ Neural Eng
January 2025
Center for Complex Systems and Brain Sciences, Universidad Nacional de San Martin Escuela de Ciencia Y Tecnologia, 25 de Mayo y Francia, San Martín, Buenos Aires, 1650, ARGENTINA.
Objective Magnetic resonance imaging (MRI), functional MRI (fMRI) and other neuroimaging techniques are routinely used in medical diagnosis, cognitive neuroscience or recently in brain decoding. They produce three- or four-dimensional scans reflecting the geometry of brain tissue or activity, which is highly correlated temporally and spatially. While there exist numerous theoretically guided methods for analyzing correlations in one-dimensional data, they often cannot be readily generalized to the multidimensional geometrically embedded setting.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Biomedical Engineering, University of Connecticut, Storrs, CT 06269, USA.
The field of emotion recognition from physiological signals is a growing area of research with significant implications for both mental health monitoring and human-computer interaction. This study introduces a novel approach to detecting emotional states based on fractal analysis of electrodermal activity (EDA) signals. We employed detrended fluctuation analysis (DFA), Hurst exponent estimation, and wavelet entropy calculation to extract fractal features from EDA signals obtained from the CASE dataset, which contains physiological recordings and continuous emotion annotations from 30 participants.
View Article and Find Full Text PDFBMC Med Res Methodol
January 2025
Systems Engineering & Operations Research, George Mason University, Fairfax, VA, 22030, USA.
Background: In this work, we implement a data-driven approach using an aggregation of several analytical methods to study the characteristics of COVID-19 daily infection and death time series and identify correlations and characteristic trends that can be corroborated to the time evolution of this disease. The datasets cover twelve distinct countries across six continents, from January 22, 2020 till March 1, 2022. This time span is partitioned into three windows: (1) pre-vaccine, (2) post-vaccine and pre-omicron (BA.
View Article and Find Full Text PDFPlants (Basel)
November 2024
Inner Mongolia Dengkou Desert Ecosystem National Observation Research Station, Experimental Center of Desert Forestry, Chinese Academy of Forestry, Dengkou 015200, China.
With the intensification of climate change and anthropogenic impacts, the ecological environment in drylands faces serious challenges, underscoring the necessity for regionally adapted ecological quality evaluation. This study evaluates the suitability of the original Remote Sensing Ecological Index (oRSEI), modified RSEI (mRSEI), and adapted RSEI (aRSEI) in a typical dryland region of northern China. Spatio-temporal changes in ecological quality from 2000 to 2022 were analyzed using Theil-Sen median trend analysis, the Mann-Kendall test, and the Hurst exponent.
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