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Layered patterns in nature, medicine, and materials: quantifying anisotropic structures and cyclicity

Various natural patterns—such as terrestrial sand dune ripples, lamellae in vertebrate bones, growth increments in fish scales and corals, aortas and lamellar corpuscles in humans and animals—comprise layers of different thicknesses and lengths. Microstructures in manmade materials—such as alloys, p...

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Detalles Bibliográficos
Autores principales: Smolyar, Igor, Bromage, Tim, Wikelski, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797002/
https://www.ncbi.nlm.nih.gov/pubmed/31632849
http://dx.doi.org/10.7717/peerj.7813
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author Smolyar, Igor
Bromage, Tim
Wikelski, Martin
author_facet Smolyar, Igor
Bromage, Tim
Wikelski, Martin
author_sort Smolyar, Igor
collection PubMed
description Various natural patterns—such as terrestrial sand dune ripples, lamellae in vertebrate bones, growth increments in fish scales and corals, aortas and lamellar corpuscles in humans and animals—comprise layers of different thicknesses and lengths. Microstructures in manmade materials—such as alloys, perlite steels, polymers, ceramics, and ripples induced by laser on the surface of graphen—also exhibit layered structures. These layered patterns form a record of internal and external factors regulating pattern formation in their various systems, making it potentially possible to recognize and identify in their incremental sequences trends, periodicities, and events in the formation history of these systems. The morphology of layered systems plays a vital role in developing new materials and in biomimetic research. The structures and sizes of these two-dimensional (2D) patterns are characteristically anisotropic: That is, the number of layers and their absolute thicknesses vary significantly in different directions. The present work develops a method to quantify the morphological characteristics of 2D layered patterns that accounts for anisotropy in the object of study. To reach this goal, we use Boolean functions and an N-partite graph to formalize layer structure and thickness across a 2D plane and to construct charts of (1) “layer thickness vs. layer number” and (2) “layer area vs. layer number.” We present a parameter disorder of layer structure (DStr) to describe the deviation of a study object’s anisotropic structure from an isotropic analog and illustrate that charts and DStr could be used as local and global morphological characteristics describing various layered systems such as images of, for example, geological, atmospheric, medical, materials, forensic, plants, and animals. Suggested future experiments could lead to new insights into layered pattern formation.
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spelling pubmed-67970022019-10-18 Layered patterns in nature, medicine, and materials: quantifying anisotropic structures and cyclicity Smolyar, Igor Bromage, Tim Wikelski, Martin PeerJ Bioinformatics Various natural patterns—such as terrestrial sand dune ripples, lamellae in vertebrate bones, growth increments in fish scales and corals, aortas and lamellar corpuscles in humans and animals—comprise layers of different thicknesses and lengths. Microstructures in manmade materials—such as alloys, perlite steels, polymers, ceramics, and ripples induced by laser on the surface of graphen—also exhibit layered structures. These layered patterns form a record of internal and external factors regulating pattern formation in their various systems, making it potentially possible to recognize and identify in their incremental sequences trends, periodicities, and events in the formation history of these systems. The morphology of layered systems plays a vital role in developing new materials and in biomimetic research. The structures and sizes of these two-dimensional (2D) patterns are characteristically anisotropic: That is, the number of layers and their absolute thicknesses vary significantly in different directions. The present work develops a method to quantify the morphological characteristics of 2D layered patterns that accounts for anisotropy in the object of study. To reach this goal, we use Boolean functions and an N-partite graph to formalize layer structure and thickness across a 2D plane and to construct charts of (1) “layer thickness vs. layer number” and (2) “layer area vs. layer number.” We present a parameter disorder of layer structure (DStr) to describe the deviation of a study object’s anisotropic structure from an isotropic analog and illustrate that charts and DStr could be used as local and global morphological characteristics describing various layered systems such as images of, for example, geological, atmospheric, medical, materials, forensic, plants, and animals. Suggested future experiments could lead to new insights into layered pattern formation. PeerJ Inc. 2019-10-14 /pmc/articles/PMC6797002/ /pubmed/31632849 http://dx.doi.org/10.7717/peerj.7813 Text en © 2019 Smolyar et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Smolyar, Igor
Bromage, Tim
Wikelski, Martin
Layered patterns in nature, medicine, and materials: quantifying anisotropic structures and cyclicity
title Layered patterns in nature, medicine, and materials: quantifying anisotropic structures and cyclicity
title_full Layered patterns in nature, medicine, and materials: quantifying anisotropic structures and cyclicity
title_fullStr Layered patterns in nature, medicine, and materials: quantifying anisotropic structures and cyclicity
title_full_unstemmed Layered patterns in nature, medicine, and materials: quantifying anisotropic structures and cyclicity
title_short Layered patterns in nature, medicine, and materials: quantifying anisotropic structures and cyclicity
title_sort layered patterns in nature, medicine, and materials: quantifying anisotropic structures and cyclicity
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797002/
https://www.ncbi.nlm.nih.gov/pubmed/31632849
http://dx.doi.org/10.7717/peerj.7813
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