Background And Aims: Fractal analysis allows calculation of fractal dimension, fractal abundance and lacunarity. Fractal analysis of plant roots has revealed correlations of fractal dimension with age, topology or genotypic variation, while fractal abundance has been associated with root length. Lacunarity is associated with heterogeneity of distribution, and has yet to be utilized in analysis of roots. In this study, fractal analysis was applied to the study of root architecture and acquisition of diffusion-limited nutrients. The hypothesis that soil depletion and root competition are more closely correlated with a combination of fractal parameters than by any one alone was tested.
Model: The geometric simulation model SimRoot was used to dynamically model roots of various architectures growing for up to 16 d in three soil types with contrasting nutrient mobility. Fractal parameters were calculated for whole roots, projections of roots and vertical slices of roots taken at 0, 2.5 and 5 cm from the root origin. Nutrient depletion volumes, competition volumes, and relative competition were regressed against fractal parameters and root length.
Key Results: Root length was correlated with depletion volume, competition volume and relative competition at all times. In analysis of three-dimensional, projected roots and 0 cm slices, log(fractal abundance) was highly correlated with log(depletion volume) when times were pooled. Other than this, multiple regression yielded better correlations than regression with single fractal parameters. Correlations decreased with age of roots and distance of vertical slices from the root origin. Field data were also examined to see if fractal dimension, fractal abundance and lacunarity can be used to distinguish common bean genotypes in field situations. There were significant differences in fractal dimension and fractal abundance, but not in lacunarity.
Conclusions: These results suggest that applying fractal analysis to research of soil exploration by root systems should include fractal abundance, and possibly lacunarity, along with fractal dimension.
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http://dx.doi.org/10.1093/aob/mch116 | DOI Listing |
Food Chem
January 2025
State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, Jiangsu 214122, China; School of Food Science and Technology, Jiangnan University, Wuxi, Jiangsu 214122, China; Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi, Jiangsu 214122, China; International Joint Laboratory on Food Safety, Jiangnan University, Wuxi, Jiangsu 214122, China.
The effect of pores distribution on the multi-scale structure, enzyme accessibility, and pasting properties of the waxy maize starch granules with the same degree of hydrolysis were examined. Increased maltogenic α-amylase (MA) dosage obviously increased the shallow pores number and the roughness, whereas extended time increased the holes depth. Despite achieving the same hydrolysis degree and specific surface area, samples with numerous shallow holes exhibited a higher mass fractal dimension, a lower, peak viscosity, final viscosity and setback.
View Article and Find Full Text PDFAims: The aim of this study was to investigate the effect of two different bisphosphonate types on bone using dental panoramic radiographs (DPRs) and to compare these findings with a healthy cohort.
Study Design: Panoramic dental radiographs of bisphosphonate users (30) and healthy individuals (30) were retrospectively evaluated for the study. Regarding FA, standardized 50 × 50 pixel regions of interest (ROI) were identified for each patient.
PLoS One
January 2025
IT4Innovations, VSB - Technical University of Ostrava, Ostrava, Czech Republic.
Malware is a common word in modern era. Everyone using computer is aware of it. Some users have to face the problem known as Cyber crimes.
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.
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