Aggregating Centrality Rankings: A Novel Approach to Detect Critical Infrastructure Vulnerabilities

Assessing critical infrastructure vulnerabilities is paramount to arrange efficient plans for their protection. Critical infrastructures are network-based systems hence, they are composed of nodes and edges. The literature shows that node criticality, which is the focus of this paper, can be addressed from different metric-based perspectives (e.g., degree, maximal flow, shortest path). However, each metric provides a specific insight while neglecting others. This paper attempts to overcome this pitfall through a methodology based on ranking aggregation. Specifically, we consider several numerical topological descriptors of the nodes’ importance (e.g., degree, betweenness, closeness, etc.) and we convert such descriptors into ratio matrices; then, we extend the Analytic Hierarchy Process problem to the case of multiple ratio matrices and we resort to a Logarithmic Least Squares formulation to identify an aggregated metric that represents a good tradeoff among the different topological descriptors. The procedure is validated considering the Central London Tube network as a case study

Macro-level Modeling of the Response of C. elegans Reproduction to Chronic Heat Stress

A major goal of systems biology is to understand how organism-level behavior arises from a myriad of molecular interactions. Often this involves complex sets of rules describing interactions among a large number of components. As an alternative, we have developed a simple, macro-level model to describe how chronic temperature stress affects reproduction in C. elegans. Our approach uses fundamental engineering principles, together with a limited set of experimentally derived facts, and provides quantitatively accurate predictions of performance under a range of physiologically relevant conditions. We generated detailed time-resolved experimental data to evaluate the ability of our model to describe the dynamics of C. elegans reproduction. We find considerable heterogeneity in responses of individual animals to heat stress, which can be understood as modulation of a few processes and may represent a strategy for coping with the ever-changing environment. Our experimental results and model provide quantitative insight into the breakdown of a robust biological system under stress and suggest, surprisingly, that the behavior of complex biological systems may be determined by a small number of key components