Critical excitation-inhibition balance in dense neural networks

Network Extraction and Analysis of Character Relationships in Chinese Literary Works

Character relationships in literary works can be interpreted and analyzed from the perspective of social networks. Analysis of intricate character relationships helps to better understand the internal logic of plot development and explore the significance of a literary work. This paper attempts to extract social networks from Chinese literary works based on co-word analysis. In order to analyze character relationships, both social network analysis and cluster analysis are carried out. Network analysis is performed by calculating degree distribution, clustering coefficient, shortest path length, centrality, etc. Cluster analysis is used for partitioning characters into groups. In addition, an improved visualization method of hierarchical clustering is proposed, which can clearly exhibit character relationships within clusters and the hierarchical structure of clusters. Finally, experimental results demonstrate that the proposed method succeeds in establishing a comprehensive framework for extracting networks and analyzing character relationships in Chinese literary works.

Phase transitions in biology: from bird flocks to population dynamics

Phase transitions are an important and extensively studied concept in physics. The insights derived from understanding phase transitions in physics have recently and successfully been applied to a number of different phenomena in biological systems. Here, we provide a brief review of phase transitions and their role in explaining biological processes ranging from collective behaviour in animal flocks to neuronal firing. We also highlight a new and exciting area where phase transition theory is particularly applicable: population collapse and extinction. We discuss how phase transition theory can give insight into a range of extinction events such as population decline due to climate change or microbial responses to stressors such as antibiotic treatment.