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The fractal properties of the spatial distribution pattern of 4 dominant plant populations and 7 rare and endangered plant populations were reflected through the box-counting dimensions. The results showed that the box-counting dimensions of 4 dominant populations ranged between 1.346 and 1.414, and occupied relatively larger ecological spaces in the community. Camellia cuspidata population occupied the largest ecological space because of its biggest box-counting dimensions. However, most of other populations occupied relatively smaller spaces due to their smaller values of the box-counting dimensions. The box-counting dimensions of 7 rare and endangered populations were smaller than 1 except Dipteronia sinensis population. The inflexion scales of 11 populations covered the range from 5 m to 12.5 m. According to the self-similarity of the fractal, the distribution pattern types under certain scales larger than the inflexion scale could be inferred as similar, and the results partly proved the ideas. The populations of Disopyros lotus, Pterostyrax psilophyllus, Davidia involucrata, Tetracentron sinense and Aesculus wilsonii were changed at the inflexion scale, and other 6 populations had the same distribution pattern types despite of the scale changed.
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Int Dent J
August 2025
Department of Public Dental Health, Semmelweis University, Budapest, Hungary.
Introduction And Aims: Fractal dimension (FD) and lacunarity are increasingly applied to assess trabecular bone structure, yet their predictive value for early dental implant failure remains uncertain. This study investigated whether FD and lacunarity, measured on panoramic radiographs and cone-beam computed tomography (CBCT), can predict early implant loss in the mandible.
Methods: A retrospective case-control study included 48 patients-24 with early implant failure and 24 with implants surviving at least 5 years without periimplantitis.
Introduction: Turbulence plays a crucial role in atherosclerosis. However, it is not currently quantified in carotid ultrasound studies due to the lack of a validated method. This study aims to develop a robust method for quantifying blood flow complexity in carotid Doppler ultrasound studies using the fractal dimension of the color Doppler signal.
View Article and Find Full Text PDFMicrosc Microanal
July 2025
Laboratório de Desenvolvimento e Aplicações de Nanomateriais da Amazônia (LADENA)-Departamento de Física de Materiais, Universidade Federal do Amazonas, Manaus, AM 69067-005, Brazil.
Deciphering the nanoscale architecture of mosquito wings is crucial for understanding species-specific flight adaptations and vectorial behaviors. In this study, we present a comprehensive quantitative analysis of the wing surface morphology of Anopheles darlingi and Anopheles aquasalis. By integrating high-resolution microscopy with Minkowski functionals and multifractal formalism, we reveal pronounced interspecific and dorso-ventral asymmetries in mosquito wing surfaces at both micro- and nanoscales.
View Article and Find Full Text PDFEur Radiol
August 2025
Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
Objectives: This study aimed to assess the potential role of 3-dimensional (3D) fractal dimension (FD) derived from contrast-enhanced CT images in predicting microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC).
Materials And Methods: This retrospective study included 655 patients with surgically confirmed HCC from two medical centers (training set: 406 patients; internal test set: 170 patients; external test set: 79 patients). Box-counting algorithms were used to compute 3D FD values from portal venous phase images.
Environ Monit Assess
August 2025
Department of Geomatics Engineering, Ondokuz Mayis University, Samsun, 55139, Turkey.
Accurate assessment of urban green areas is essential for enhancing livability and guiding sustainable urban planning. This study investigates green space distribution in Samsun, Turkey, by integrating spatial and fractal analyses. Green areas in 77 neighborhoods across the Atakum, Ilkadim, and Canik districts were identified using the normalized difference vegetation index (NDVI) derived from Sentinel-2A/2B imagery (July-October 2023).
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