The resilience of interdependent transportation networks under targeted attack

Modern world builds on the resilience of interdependent infrastructures characterized as complex networks. Recently, a framework for analysis of interdependent networks has been developed to explain the mechanism of resilience in interdependent networks. Here we extend this interdependent network model by considering flows in the networks and study the system's resilience under different attack strategies. In our model, nodes may fail due to either overload or loss of interdependency. Under the interaction between these two failure mechanisms, it is shown that interdependent scale-free networks show extreme vulnerability. The resilience of interdependent SF networks is found in our simulation much smaller than single SF network or interdependent SF networks without flows.Comment: 5 pages, 4 figure

A Generalized Spatial Measure for Resilience of Microbial Systems

The emergent property of resilience is the ability of a system to return to an original state after a disturbance. Resilience may be used as an early warning system for significant or irreversible community transition; that is, a community with diminishing or low resilience may be close to catastrophic shift in function or an irreversible collapse. Typically, resilience is quantified using recovery time, which may be difficult or impossible to directly measure in microbial systems. A recent study in the literature showed that under certain conditions, a set of spatial-based metrics termed recovery length, can be correlated to recovery time, and thus may be a reasonable alternative measure of resilience. However, this spatial metric of resilience is limited to use for step-change perturbations. Building upon the concept of recovery length, we propose a more general form of the spatial metric of resilience that can be applied to any shape of perturbation profiles (for example, either sharp or smooth gradients). We termed this new spatial measure “perturbation-adjusted spatial metric of resilience” (PASMORE). We demonstrate the applicability of the proposed metric using a mathematical model of a microbial mat

Macroeconomic resilience in a DSGE model

We use the dynamic stochastic general equilibrium (DSGE) model of Altig et al. (2005) to analyse the resilience of an economy in the face of external shocks. The term resilience refers to the ability of an economy to prosper in the face of shocks. The Altig et al. model was chosen because it combined both demand and supply shocks and because various market rigidities/imperfections, which have the potential to affect resilience, are modelled. We consider the level of expected discounted utility to be the relevant measure of resilience. The effect of market rigidities, eg. wage and price stickiness, on the expected level of utility is minimal. The effect on utility is especially small when compared to the effect of market competition, because the latter has a direct effect on the level of output. This conclusion holds for the family of constant-relative-risk-aversion-over-consumption utility functions. A similar conclusion was drawn by Lucas (1987) regarding the costs of business cycles. We refer to the literature that followed Lucas for ideas for how a DSGE model might be adjusted to give a more meaningful analysis of resilience. We conclude that the Altig et al. DSGE model does not produce a relationship between rigidities and the level of output and, hence, does not capture the effect of inflexibility on utility that one observes colloquially.

Non-Stationary Random Process for Large-Scale Failure and Recovery of Power Distributions

A key objective of the smart grid is to improve reliability of utility services to end users. This requires strengthening resilience of distribution networks that lie at the edge of the grid. However, distribution networks are exposed to external disturbances such as hurricanes and snow storms where electricity service to customers is disrupted repeatedly. External disturbances cause large-scale power failures that are neither well-understood, nor formulated rigorously, nor studied systematically. This work studies resilience of power distribution networks to large-scale disturbances in three aspects. First, a non-stationary random process is derived to characterize an entire life cycle of large-scale failure and recovery. Second, resilience is defined based on the non-stationary random process. Close form analytical expressions are derived under specific large-scale failure scenarios. Third, the non-stationary model and the resilience metric are applied to a real life example of large-scale disruptions due to Hurricane Ike. Real data on large-scale failures from an operational network is used to learn time-varying model parameters and resilience metrics.Comment: 11 pages, 8 figures, submitted to IEEE Sig. Pro

The relationship between resilience and sustainable development of ecological-economic systems

Resilience as a descriptive concept gives insight into the dynamic properties of a system. Sustainability as a normative concept captures basic ideas of inter- and intragenerational justice. In this paper we specify the relationship between resilience and sustainable development. Based on an ecological-economic model where two natural capital stocks provide ecosystem services that are complements for human well-being, we derive conditions on the dynamics of the ecological-economic system and the sustainability criterion, such that a) resilience of the system in a given regime is both necessary and sufficient for sustainable development, b) resilience of the system in a given regime is sufficient, but not necessary, c) resilience of the system in a given regime is necessary, but not sufficient, and d) resilience of the system in a given regime is neither necessary nor sufficient for sustainable development. We conclude that more criteria than the resilience of the current state of the system have to be taken into account when designing policies for sustainable management of ecological-economic systems.ecosystem resilience, sustainable development, management of ecological-economic systems

Bullying history and mental health In university students : the mediator roles of social support, personal resilience, and self-efficacy

Bullying victimization by peers is highly prevalent in childhood and adolescence. There is convincing evidence that victimization is associated with adverse mental health consequences. In contrast, it has been found that perpetrators suffer no adverse mental health consequences. These findings originate from Western countries such as Germany but have rarely been investigated in collectivistic societies such as China. Furthermore, it has been rarely studied whether positive intrapersonal characteristics (e.g., personal resilience and self-efficacy) and interpersonal positive resources (e.g., social support) may mediate the impact of bullying on mental health. The current study used a path analytic model to examine, firstly, whether previous bullying experiences (both victimization and perpetration) are associated with current positive and negative mental health in university students and, secondly, whether these influences are mediated by social support, resilience, and self-efficacy. The model was tested in 5,912 Chinese and 1,935 German university students. It was found that in both countries, higher victimization frequency was associated with lower levels of social support, personal resilience, and self-efficacy, which in turn predicted poorer mental health. Moreover, and only in China, perpetration was negatively associated with social support and personal resilience but not self-efficacy. In contrast, in the German sample, perpetration experience was found to enhance one's self-efficacy, and the later was associated with better mental health. The results support a mediation model in which social support, personal resilience, and self-efficacy partially mediate the influence of victimization on mental health in both countries. For the relationship between perpetration and mental health, self-efficacy was the only full mediator in Germany, whereas in China, both social support and personal resilience were partial mediators. In conclusion, peer victimization has adverse effects on mental health in both Germany and China. Only in China, however, is perpetration also associated with adverse mental health outcomes. In contrast, getting ahead by bullying in an individualistic society such as Germany is associated with increased self-efficacy and mental health. The differences found between an individualistic country and a collectivistic country have important implications for understanding and planning interventions to reduce bullying

Control over stress induces plasticity of individual prefrontal cortical neurons: A conductance-based neural simulation

Behavioral control over stressful stimuli induces resilience to future conditions when control is lacking. The medial prefrontal cortex(mPFC) is a critically important brain region required for plasticity of stress resilience. We found that control over stress induces plasticity of the intrinsic voltage-gated conductances of pyramidal neurons in the PFC. To gain insight into the underlying biophysical mechanisms of this plasticity we used the conductance- based neural simulation software tool, NEURON, to model the increase in membrane excitability associated with resilience to stress. A ball and stick multicompartment conductance-based model was used to realistically fit passive and active data traces from prototypical pyramidal neurons in neurons in rats with control over tail shock stress and those lacking control. The results indicate that the plasticity of membrane excitability associated with control over stress can be attributed to an increase in Na+ and Ca2+ T-type conductances and an increase in the leak conductance. Using simulated dendritic synaptic inputs we observed an increase in excitatory postsynaptic summation and amplification resulting in elevated action potential output. This realistic simulation suggests that control over stress enhances the output of the PFC and offers specific testable hypotheses to guide future electrophysiological mechanistic studies in animal models of resilience and vulnerability to stress

Knockouts, Robustness and Cell Cycles

The response to a knockout of a node is a characteristic feature of a networked dynamical system. Knockout resilience in the dynamics of the remaining nodes is a sign of robustness. Here we study the effect of knockouts for binary state sequences and their implementations in terms of Boolean threshold networks. Beside random sequences with biologically plausible constraints, we analyze the cell cycle sequence of the species Saccharomyces cerevisiae and the Boolean networks implementing it. Comparing with an appropriate null model we do not find evidence that the yeast wildtype network is optimized for high knockout resilience. Our notion of knockout resilience weakly correlates with the size of the basin of attraction, which has also been considered a measure of robustness.Comment: 11 pages, 3 figures, 3 table