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      Connecting Ships: Using Dendrochronological Network Analysis to Determine the Wood Provenance of Roman-Period River Barges Found in the Lower Rhine Region and Visualise Wood Use Patterns

      1 , 2
      International Journal of Wood Culture
      Brill

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          Abstract

          This study combines standard dendrochronological analyses with network science and spatial analysis to determine the provenance of wood used to build river barges in the Roman period. The river barges studied were found in the Lower Rhine region and would have carried bulk goods, such as grain, military supplies, and building materials. The importance of these vessels in the supply of the local economy and military units is evident since many were found in the area, including some in the vicinity of military complexes. However, it remains unknown where these ships were built and how and where the raw materials for their construction were obtained. To better understand the provenance of the wood, network science was applied to visualise and understand the complex patterns of similarity between the tree-ring curves. For the interpretation of the networks we have studied the context, the position of the trees in the network and the use of these trees in shipbuilding. In addition, the shape of the converted timber was used to visualise the wood use patterns in this type of Roman-period shipbuilding. For the river barges, we were able to determine several possible regions for wood procurement. Based on the analysed material, we assume that there was at least one shipyard in the Lower Rhine region where two ships, found in separate excavations, were most likely produced at the same time.

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          Most cited references36

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            Collective dynamics of 'small-world' networks.

            Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.
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              Emergence of Scaling in Random Networks

              Systems as diverse as genetic networks or the World Wide Web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature was found to be a consequence of two generic mechanisms: (i) networks expand continuously by the addition of new vertices, and (ii) new vertices attach preferentially to sites that are already well connected. A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                International Journal of Wood Culture
                Int. J. Wood Cult.
                Brill
                2772-3186
                2772-3194
                December 23 2022
                December 23 2022
                : 1-29
                Affiliations
                [1 ]Saxion University of Applied Sciences Handelskade 75, 7417 DH Deventer The Netherlands
                [2 ]Vorst Wood Research Zaandam The Netherlands
                Article
                10.1163/27723194-bja10014
                839049c4-d3b9-4ebf-91bf-cca335304563
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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