2,056 research outputs found

    Behavior of susceptible-infected-susceptible epidemics on heterogeneous networks with saturation

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    We investigate saturation effects in susceptible-infected-susceptible (SIS) models of the spread of epidemics in heterogeneous populations. The structure of interactions in the population is represented by networks with connectivity distribution P(k)P(k),including scale-free(SF) networks with power law distributions P(k)∌k−γP(k)\sim k^{-\gamma}. Considering cases where the transmission of infection between nodes depends on their connectivity, we introduce a saturation function C(k)C(k) which reduces the infection transmission rate λ\lambda across an edge going from a node with high connectivity kk. A mean field approximation with the neglect of degree-degree correlation then leads to a finite threshold λc>0\lambda_{c}>0 for SF networks with 2<γ≀32<\gamma \leq 3. We also find, in this approximation, the fraction of infected individuals among those with degree kk for λ\lambda close to λc\lambda_{c}. We investigate via computer simulation the contact process on a heterogeneous regular lattice and compare the results with those obtained from mean field theory with and without neglect of degree-degree correlations.Comment: 6 figure

    On Resilient Behaviors in Computational Systems and Environments

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    The present article introduces a reference framework for discussing resilience of computational systems. Rather than a property that may or may not be exhibited by a system, resilience is interpreted here as the emerging result of a dynamic process. Said process represents the dynamic interplay between the behaviors exercised by a system and those of the environment it is set to operate in. As a result of this interpretation, coherent definitions of several aspects of resilience can be derived and proposed, including elasticity, change tolerance, and antifragility. Definitions are also provided for measures of the risk of unresilience as well as for the optimal match of a given resilient design with respect to the current environmental conditions. Finally, a resilience strategy based on our model is exemplified through a simple scenario.Comment: The final publication is available at Springer via http://dx.doi.org/10.1007/s40860-015-0002-6 The paper considerably extends the results of two conference papers that are available at http://ow.ly/KWfkj and http://ow.ly/KWfgO. Text and formalism in those papers has been used or adapted in the herewith submitted pape

    Scale-Free topologies and Activatory-Inhibitory interactions

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    A simple model of activatory-inhibitory interactions controlling the activity of agents (substrates) through a "saturated response" dynamical rule in a scale-free network is thoroughly studied. After discussing the most remarkable dynamical features of the model, namely fragmentation and multistability, we present a characterization of the temporal (periodic and chaotic) fluctuations of the quasi-stasis asymptotic states of network activity. The double (both structural and dynamical) source of entangled complexity of the system temporal fluctuations, as an important partial aspect of the Correlation Structure-Function problem, is further discussed to the light of the numerical results, with a view on potential applications of these general results.Comment: Revtex style, 12 pages and 12 figures. Enlarged manuscript with major revision and new results incorporated. To appear in Chaos (2006

    Modeling resilience and sustainability in ancient agricultural systems

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    The reasons why people adopt unsustainable agricultural practices, and the ultimate environmental implications of those practices, remain incompletely understood in the present world. Archaeology, however, offers unique datasets on coincident cultural and ecological change, and their social and environmental effects. This article applies concepts derived from ecological resilience thinking to assess the sustainability of agricultural practices as a result of long-term interactions between political, economic, and environmental systems. Using the urban center of Gordion, in central Turkey, as a case study, it is possible to identify mismatched social and ecological processes on temporal, spatial, and organizational scales, which help to resolve thresholds of resilience. Results of this analysis implicate temporal and spatial mismatches as a cause for local environmental degradation, and increasing extralocal economic pressures as an ultimate cause for the adoption of unsustainable land-use practices. This analysis suggests that a research approach that integrates environmental archaeology with a resilience perspective has considerable potential for explicating regional patterns of agricultural change and environmental degradation in the past

    Catastrophic Phase Transitions and Early Warnings in a Spatial Ecological Model

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    Gradual changes in exploitation, nutrient loading, etc. produce shifts between alternative stable states (ASS) in ecosystems which, quite often, are not smooth but abrupt or catastrophic. Early warnings of such catastrophic regime shifts are fundamental for designing management protocols for ecosystems. Here we study the spatial version of a popular ecological model, involving a logistically growing single species subject to exploitation, which is known to exhibit ASS. Spatial heterogeneity is introduced by a carrying capacity parameter varying from cell to cell in a regular lattice. Transport of biomass among cells is included in the form of diffusion. We investigate whether different quantities from statistical mechanics -like the variance, the two-point correlation function and the patchiness- may serve as early warnings of catastrophic phase transitions between the ASS. In particular, we find that the patch-size distribution follows a power law when the system is close to the catastrophic transition. We also provide links between spatial and temporal indicators and analyze how the interplay between diffusion and spatial heterogeneity may affect the earliness of each of the observables. We find that possible remedial procedures, which can be followed after these early signals, are more effective as the diffusion becomes lower. Finally, we comment on similarities and differences between these catastrophic shifts and paradigmatic thermodynamic phase transitions like the liquid-vapour change of state for a fluid like water

    Bivariate stochastic modeling of functional response with natural mortality

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    A correction due to Abbott (1925) is the standard method of dealing with control mortality in insect bioassay to estimate the mortality of an insect conditional on control mortality not having occurred. In this article a bivariate stochastic process for overall mortality is developed in which natural mortality and predation are jointly modeled to take account of the competing-risks associated with prey loss. The total mortality estimate from this model is essentially identical with that from more classical modeling. However, when predation loss is estimated in the absence of control mortality the results are somewhat different, with the estimate from the bivariate model being lower than that from using Abbott’s formula in conjunction with the classical model. It is argued that overdispersion in observed mortality data corresponds to correlated outcomes (death or survival) for the prey initially present, while Abbott’s correction relies implicitly on independence

    Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems

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    A generic mechanism - networked buffering - is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems. \ud \u
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