HyperCI: A higher order collective influence measure for hypernetwork dismantling

Network dismantling aims to scratch the network into unconnected fragments by removing an optimal set of nodes and has been widely adopted in many real-world applications such as epidemic control and rumor containment. However, conventional methods often disassemble the system from the perspective of classic networks, which have only pairwise interactions, and often ignored the more ubiquitous and nature group-wise interactions modeled by hypernetwork. Moreover, a simple network can't describe the collective behavior of multiple objects, it is necessary to solve related problems through hypernetwork dismantling. In this work, we designed a higher order collective influence measure to identify key node sets in hypernetwork. It comprehensively consider the environment in which the target node is located and its own characteristics to determine the importance of the node, so as to dismantle the hypernetwork by removing these selected nodes. Finally, we used the method to carry out a series of real-world hypernetwork dismantling tasks. Experimental results on five real-world hypernetworks demonstrate the effectiveness of our proposed measure

A virtual reality system to augment teaching of wood structure and protection

Medical students have enthusiastically embraced the use of virtual reality (VR) systems to help them understand the complex anatomy of body components. We hypothesize that students studying the structure and protection of wood will show similar acceptance of VR systems. We developed X-ray micro-CT models to show the distribution of silica in the Australian marine borer resistant timber, satinay and copper in treated pine. Students taking a course in wood protection used a VR device to explore the distribution of silica in satinay and copper in pine. Students were surveyed to assess their views on the system as a learning tool. The results showed that students were very positive about the VR system, and they frequently commented that the system was better than traditional methods at aiding understanding of wood structure/protection. We discuss the limitations and potential of our VR system as a learning tool for wood technology