Evolution of Network Architecture in a Granular Material Under Compression

As a granular material is compressed, the particles and forces within the system arrange to form complex and heterogeneous collective structures. Force chains are a prime example of such structures, and are thought to constrain bulk properties such as mechanical stability and acoustic transmission. However, capturing and characterizing the evolving nature of the intrinsic inhomogeneity and mesoscale architecture of granular systems can be challenging. A growing body of work has shown that graph theoretic approaches may provide a useful foundation for tackling these problems. Here, we extend the current approaches by utilizing multilayer networks as a framework for directly quantifying the progression of mesoscale architecture in a compressed granular system. We examine a quasi-two-dimensional aggregate of photoelastic disks, subject to biaxial compressions through a series of small, quasistatic steps. Treating particles as network nodes and interparticle forces as network edges, we construct a multilayer network for the system by linking together the series of static force networks that exist at each strain step. We then extract the inherent mesoscale structure from the system by using a generalization of community detection methods to multilayer networks, and we define quantitative measures to characterize the changes in this structure throughout the compression process. We separately consider the network of normal and tangential forces, and find that they display a different progression throughout compression. To test the sensitivity of the network model to particle properties, we examine whether the method can distinguish a subsystem of low-friction particles within a bath of higher-friction particles. We find that this can be achieved by considering the network of tangential forces, and that the community structure is better able to separate the subsystem than a purely local measure of interparticle forces alone. The results discussed throughout this study suggest that these network science techniques may provide a direct way to compare and classify data from systems under different external conditions or with different physical makeup

Computer supported argument maps as a policy memory

This paper investigates to what extent Computer Supported Argument Visualisation can be designed to encourage debate and deliberation by citizens on public issues. Such argument maps use icons and arrows to represent the structure of a series of related viewpoints, reducing the amount of text necessary to convey the ideas, thereby clarifying the issue under consideration. Argument maps have the potential to provide a readily accessible medium by which citizens can follow and join in public debates on policy issues. In this paper we describe our approach, type of maps we have chosen to use and then demonstrate the potential of a collection of maps to form a ‘policy memory’ to support policy development. Our case study is the development of the ‘Smoking in Public Places’ policy in the Scottish Parliament. Our overall aim is to engage citizens in democratic decision-making leading to better policy-making and a more engaged citizenry

Sarcoptic mange in three alpacas treated successfully with amitraz

Sarcoptic mange is a serious skin disease in alpacas that can result in high morbidity and even mortality. Three alpacas were presented with sarcoptic mange that had previously failed to respond to repeated topical applications of eprinomectin, and an injection of doramectin. They were moderately to severely pruritic, had extensive lesions of alopecia, erythema, scaling and crusting, and had lost weight. As no drug is currently licensed for the treatment of sarcoptic mange in alpacas in the UK, they were treated with a topical solution of amitraz (50 mL in 10 L) after initial bathing with antibacterial or keratolytic shampoos. The clinical signs completely resolved with no relapse over a 10-month follow-up period. In this small group of alpacas, amitraz was an effective and well-tolerated treatment for sarcoptic mange.Peri Lau, Peter B. Hill, Jan Rybníček and Lynne Stee