Otoliths are calcified structures found in the inner ears of teleost fish, pivotal in marine biology for studies on metabolism, age, growth, and the identification of fish stocks, potentially leading to sustainable management practices. An important feature of this structure is its density, as it corresponds to modifications in the crystalline form of calcium carbonate during the fish's lifetime, resulting in variations in its final shape. The internal and external 3D radiodensity of otoliths from different species was obtained utilizing micro-computed tomography, however, an appropriate methodology for describing and conducting comparative studies on these data appears to be absent in the current body of literature. Therefore, we study otolith density variations from 3D computed tomography images, employing the Ball Mapper technique of Topological Data Analysis. We focus on reducing the computational cost of this analysis by applying probabilistic sampling and assessing its effects on the density variations provided by the Ball Mapper graph. To determine the sample size, we used the topology to establish what we term "Topological Sample Validation", which provided the minimum resolution with the same density information as raw data. Sample representativeness was validated through non-parametric statistical tests on the density variable. Based on the network's structural characteristics, network properties allowed for evaluating similarity between graphs. Besides the small sample size, remarkable correlations were obtained between age and network variables. Additionally, the Ball Mapper technique proved effective as a preprocessing algorithm for tomographic images, enabling the segmentation of undesired features in the object of interest.
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http://dx.doi.org/10.1016/j.micron.2024.103731 | DOI Listing |
Environ Monit Assess
January 2025
School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia.
This study investigates the effectiveness and efficiency of two topological data analysis (TDA) techniques, the conventional Mapper (CM) and its variant version, the Ball Mapper (BM), in analyzing the behavior of six major air pollutants (NO, PM, PM, O, CO, and SO) across 60 air quality monitoring stations in Malaysia. Topological graphs produced by CM and BM reveal redundant monitoring stations and geographical relationships corresponding to air pollutant behavior, providing better visualization than traditional hierarchical clustering. Additionally, a comparative analysis of topological graph structures was conducted using node degree distribution, topological graph indices, and Dynamic Time Warping (DTW) to evaluate the sensitivity and performance of these TDA techniques.
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January 2025
Graduate Program in Biometry and Applied Statistics, Federal Rural University of Pernambuco, Recife, Pernambuco, Brazil; Department of Statistics and Informatics, Federal Rural University of Pernambuco, Recife, Brazil. Electronic address:
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