The structure of nanoclusters is complex to describe due to their noncrystallinity, even though bonding and packing constraints limit the local atomic arrangements to only a few types. A computational scheme is presented to extract coordination motif
s from sample atomic configurations. The method is based on a clustering analysis of multipole moments for atoms in the first coodination shell. Its power to capture large-scale structural properties is demonstrated by scanning through the ground state of the Lennard-Jones and C$_{60}$ clusters collected at the Cambridge Cluster Database.
Inspired by studies on airline networks we propose a general model for weighted networks in which topological growth and weight dynamics are both determined by cost adversarial mechanism. Since transportation networks are designed and operated with o
bjectives to reduce cost, the theory of cost in micro-economics plays a critical role in the evolution. We assume vertices and edges are given cost functions according to economics of scale and diseconomics of scale (congestion effect). With different cost functions the model produces broad distribution of networks. The model reproduces key properties of real airline networks: truncated degree distributions, nonlinear strength degree correlations, hierarchy structures, and particulary the disassortative and assortative behavior observed in different airline networks. The result suggests that the interplay between economics of scale and diseconomics of scale is a key ingredient in order to understand the underlying driving factor of the real-world weighted networks.
