ASU Scholarship Showcase

Evolutionary games model a common type of interactions in a variety of complex, networked, natural systems and social systems. Given such a system, uncovering the interacting structure of the underlying network is key to understanding its collective dynamics. Based on compressive sensing, we develop an efficient approach to reconstructing complex networks under game-based interactions from small amounts of data. The method is validated by using a variety of model networks and by conducting an actual experiment to reconstruct a social network. While most existing methods in this area assume oscillator networks that generate continuous-time data, our work successfully demonstrates that the extremely challenging problem of reverse engineering of complex networks can also be addressed even when the underlying dynamical processes are governed by realistic, evolutionary-game type of interactions in discrete time.

Locating sources of diffusion and spreading from minimum data is a significant problem in network science with great applied values to the society. However, a general theoretical framework dealing with optimal source localization is lacking. Combining the controllability theory for complex networks and compressive sensing, we develop a framework with high efficiency and robustness for optimal source localization in arbitrary weighted networks with arbitrary distribution of sources. We offer a minimum output analysis to quantify the source locatability through a minimal number of messenger nodes that produce sufficient measurement for fully locating the sources. When the minimum messenger nodes are discerned, the problem of optimal source localization becomes one of sparse signal reconstruction, which can be solved using compressive sensing. Application of our framework to model and empirical networks demonstrates that sources in homogeneous and denser networks are more readily to be located. A surprising finding is that, for a connected undirected network with random link weights and weak noise, a single messenger node is sufficient for locating any number of sources. The framework deepens our understanding of the network source localization problem and offers efficient tools with broad applications.

Though many animal ornaments and signals are sensitive to and encode information about the oxidative balance (OB) of individuals (e.g., antioxidant supplies/activity, reactive oxygen species, cellular oxidative damage/repair), often the environmental and/or physiological sources of such OB are unknown. Urban development is among the most recent, pervasive, and persistent human stressors on the planet and impacts many environmental and physiological parameters of animals. Here we review the mechanistic underpinnings and functional consequences of how human urbanization drives antioxidant/oxidative status in animals and how this affects signal expression and use. Although we find that urbanization has strong negative effects on signal quality (e.g., visual, auditory, chemical) and OB across a range of taxa, few urban ecophysiological studies address signals and oxidative stress in unison, and even fewer in a fitness context. We also highlight particular signal types, taxa, life-histories, and anthropogenic environmental modifications on which future work integrating OB, signals, and urbanization could be centered. Last, we examine the conceptual and empirical framework behind the idea that urban conditions may disentangle signal expression from honesty and affect plasticity and adaptedness of sexually selected traits and preferences in the city.

Dynamical processes occurring on the edges in complex networks are relevant to a variety of real-world situations. Despite recent advances, a framework for edge controllability is still required for complex networks of arbitrary structure and interaction strength. Generalizing a previously introduced class of processes for edge dynamics, the switchboard dynamics, and exploit- ing the exact controllability theory, we develop a universal framework in which the controllability of any node is exclusively determined by its local weighted structure. This framework enables us to identify a unique set of critical nodes for control, to derive analytic formulas and articulate efficient algorithms to determine the exact upper and lower controllability bounds, and to evaluate strongly structural controllability of any given network. Applying our framework to a large number of model and real-world networks, we find that the interaction strength plays a more significant role in edge controllability than the network structure does, due to a vast range between the bounds determined mainly by the interaction strength. Moreover, transcriptional regulatory networks and electronic circuits are much more strongly structurally controllable (SSC) than other types of real-world networks, directed networks are more SSC than undirected networks, and sparse networks are typically more SSC than dense networks.

We develop a general framework to analyze the controllability of multiplex networks using multiple-relation networks and multiple-layer networks with interlayer couplings as two classes of prototypical systems. In the former, networks associated with different physical variables share the same set of nodes and in the latter, diffusion processes take place. We find that, for a multiple-relation network, a layer exists that dominantly determines the controllability of the whole network and, for a multiple-layer network, a small fraction of the interconnections can enhance the controllability remarkably. Our theory is generally applicable to other types of multiplex networks as well, leading to significant insights into the control of complex network systems with diverse structures and interacting patterns.

Vertebrates cannot synthesize carotenoid pigments de novo, so to produce carotenoid-based coloration they must ingest carotenoids. Most songbirds that deposit red carotenoids in feathers, bills, eyes, or skin ingest only yellow or orange dietary pigments, which they oxidize to red pigments via a ketolation reaction. It has been hypothesized that carotenoid ketolation occurs in the liver of vertebrates, but this hypothesis remains to be confirmed. To better understand the role of hepatocytes in the production of ketolated carotenoids in songbirds, we measured the carotenoid content of subcellular components of hepatocytes from wild male house finches (Haemorhous mexicanus) that were molting red, ketocarotenoid-containing feathers (e.g., 3-hydroxy-echinenone). We homogenized freshly collected livers of house finches and isolated subcellular fractions, including mitochondria. We found the highest concentration of ketocarotenoids in the mitochondrial fraction. These observations are consistent with the hypothesis that carotenoid pigments are oxidized on or within hepatic mitochondria, esterified, and then transported to the Golgi apparatus for secretory processing.