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Journal articleSahasranaman A, Jensen H, 2019,
Rapid migrations and dynamics of citizen response
, Royal Society Open Science, Vol: 6, Pages: 1-13, ISSN: 2054-5703One of the pressing social concerns of our timeis the need for meaningful responses to migrantsand refugees fleeing conflict and environmentalcatastrophe. We develop a computational model tomodel the influx of migrants into a city, varyingthe rates of entry, and find a non-linear inverserelationship between the fraction of resident populationwhose tolerance levels are breached due to migrantentry and the average time to such tolerancebreach. Essentially, beyond a certain rate of migrantentry, there is a rapid rise in the fraction ofresidents whose tolerances are breached, even as theaverage time to breach decreases. We also modelan analytical approximation of the computationalmodel and find qualitative correspondence in theobserved phenomenology, with caveats. The sharpincrease in the fraction of residents with tolerancebreach could potentially underpin the intensity ofresident responses to bursts of migrant entry intotheir cities. Given this non-linear relationship, it isperhaps essential that responses to refugee situationsare multi-country or global efforts so that sharpspikes of refugee migrations are equitably distributedamong nations, potentially enabling all participatingcountries to avoid impacting resident tolerancesbeyond limits that are socially sustainable.
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Journal articleDuarte D, Amarteifio S, Ang H, et al., 2019,
Defining the in vivo characteristics of acute myeloid leukemia cells behavior by intravital imaging
, Immunology and Cell Biology, Vol: 97, Pages: 229-235, ISSN: 0818-9641The majority of acute myeloid leukemia (AML) patients have a poor response to conventional chemotherapy. The survival of chemoresistant cells is thought to depend on leukemia-bone marrow (BM) microenvironment interactions, which are not well understood. The CXCL12/CXCR4 axis has been proposed to support AML growth but was not studied at the single AML cell level. We recently showed that T-cell acute lymphoblastic leukemia (T-ALL) cells are highly motile in the BM; however, the characteristics of AML cell migration within the BM remain undefined. Here, we characterize the in vivo migratory behavior of AML cells and their response to chemotherapy and CXCR4 antagonism, using high-resolution 2-photon and confocal intravital microscopy of mouse calvarium BM and the well-established MLL-AF9-driven AML mouse model. We used the Notch1-driven T-ALL model as a benchmark comparison and AMD3100 for CXCR4 antagonism experiments. We show that AML cells are migratory, and in contrast with T-ALL, chemoresistant AML cells become less motile. Moreover, and in contrast with T-ALL, the in vivo exploratory behavior of expanding and chemoresistant AML cells is unaffected by AMD3100. These results expand our understanding of AML cells-BM microenvironment interactions, highlighting unique traits of leukemia of different lineages.
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Conference paperRassouli B, Rosas F, Gunduz D, 2019,
Latent Feature Disclosure under Perfect Sample Privacy
, 10th IEEE International Workshop on Information Forensics and Security (WIFS), Publisher: IEEE, ISSN: 2157-4766 -
Journal articleVazquez P, del Rio JA, Cedano KG, et al., 2018,
Network characterization of the Entangled Model for sustainability indicators. Analysis of the network properties for scenarios
, PLoS ONE, Vol: 13, ISSN: 1932-6203Policy-makers require strategies to select a set of sustainability indicators that are useful for monitoring sustainability. For this reason, we have developed a model where sustainability indicators compete for the attention of society. This model has shown to have steady situations where a set of sustainability indicators are stable. To understand the role of the network configuration, in this paper we analyze the network properties of the Entangled Sustainability model. We have used the degree distribution, the clustering coefficient, and the interaction strength distribution as main measures. We also analyze the network properties for scenarios compared against randomly generated scenarios. We found that the stable situations show different characteristics from the unstable transitions present in the model. We also found that the complex emergent feature of sustainability shown in the model is an attribute of the scenarios, however, the randomly generated scenarios do not present the same network properties.
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Journal articleJensen H, 2018,
Tangled nature: A model of emergent structure and temporal mode among co-evolving agents
, European Journal of Physics, Vol: 40, ISSN: 0143-0807Understanding systems level behaviour of many interacting agents is challenging in various ways. In this review we will focus on how the interaction between components can lead to hierarchical structures with different types of dynamics, or causations, at different levels. We use the Tangled Nature model to discuss the co-evolutionary aspects of the connection between the microscopic level of the individual and the macroscopic systems level. At the microscopic level the individual agent may undergo evolutionary changes due to 'mutations of strategies'. The micro-dynamics always run at a constant rate. Nevertheless, the systems level dynamics exhibit a completely different type of intermittent abrupt dynamics where major upheavals keep throwing the system between metastable configurations. These dramatic transitions are described by a log-Poisson time statistics. The long time effect is a collective adaptation of the ecological networks. We discuss the ecological and macro-evolutionary consequences of the adaptive dynamics and briefly describe work using the Tangled Nature framework to analyse problems in economics, sociology, innovation and sustainability.
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Journal articleGarcia Millan R, Pausch J, Walter B, et al., 2018,
Field-theoretic approach to the universality of branching processes
, Physical Review E, Vol: 98, ISSN: 1539-3755Branching processes are widely used to model phenomena from networks to neuronal avalanching. In a large class of continuous-time branching processes, we study the temporal scaling of the moments of the instant population size, the survival probability, expected avalanche duration, the so-called avalanche shape, the n-point correlation function, and the probability density function of the total avalanche size. Previous studies have shown universality in certain observables of branching processes using probabilistic arguments; however, a comprehensive description is lacking. We derive the field theory that describes the process and demonstrate how to use it to calculate the relevant observables and their scaling to leading order in time, revealing the universality of the moments of the population size. Our results explain why the first and second moment of the offspring distribution are sufficient to fully characterize the process in the vicinity of criticality, regardless of the underlying offspring distribution. This finding implies that branching processes are universal. We illustrate our analytical results with computer simulations.
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Journal articleRosas De Andraca F, Chen K-C, Gunduz D, 2018,
Social learning for resilient data fusion against data falsification attacks
, Computational Social Networks, Vol: 5, ISSN: 2197-4314BackgroundInternet of Things (IoT) suffers from vulnerable sensor nodes, which are likely to endure data falsification attacks following physical or cyber capture. Moreover, centralized decision-making and data fusion turn decision points into single points of failure, which are likely to be exploited by smart attackers.MethodsTo tackle this serious security threat, we propose a novel scheme for enabling distributed decision-making and data aggregation through the whole network. Sensor nodes in our scheme act following social learning principles, resembling agents within a social network.ResultsWe analytically examine under which conditions local actions of individual agents can propagate through the network, clarifying the effect of Byzantine nodes that inject false information. Moreover, we show how our proposed algorithm can guarantee high network performance, even for cases when a significant portion of the nodes have been compromised by an adversary.ConclusionsOur results suggest that social learning principles are well suited for designing robust IoT sensor networks and enabling resilience against data falsification attacks.
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Journal articleJensen H, Tempesta P, 2018,
Group entropies: from phase space geometry to entropy functionals via group theory
, Entropy, Vol: 20, ISSN: 1099-4300The entropy of Boltzmann-Gibbs, as proved by Shannon and Khinchin, is based on four axioms, where the fourth one concerns additivity. The group theoretic entropies make use of formal group theory to replace this axiom with a more general composability axiom. As has been pointed out before, generalised entropies crucially depend on the number of allowed degrees of freedom N. The functional form of group entropies is restricted (though not uniquely determined) by assuming extensivity on the equal probability ensemble, which leads to classes of functionals corresponding to sub-exponential, exponential or super-exponential dependence of the phase space volume W on N. We review the ensuing entropies, discuss the composability axiom and explain why group entropies may be particularly relevant from an information-theoretical perspective.
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Journal articleRosas De Andraca FE, Martinez Mediano P, Ugarte M, et al., 2018,
An information-theoretic approach to self-organisation: Emergence of complex interdependencies in coupled dynamical systems
, Entropy, Vol: 20, ISSN: 1099-4300Self-organisation lies at the core of fundamental but still unresolved scientific questions, and holds the promise of de-centralised paradigms crucial for future technological developments. While self-organising processes have been traditionally explained by the tendency of dynamical systems to evolve towards specific configurations, or attractors, we see self-organisation as a consequence of the interdependencies that those attractors induce. Building on this intuition, in this work we develop a theoretical framework for understanding and quantifying self-organisation based on coupled dynamical systems and multivariate information theory. We propose a metric of global structural strength that identifies when self-organisation appears, and a multi-layered decomposition that explains the emergent structure in terms of redundant and synergistic interdependencies. We illustrate our framework on elementary cellular automata, showing how it can detect and characterise the emergence of complex structures.
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Journal articleSahasranaman A, Jensen HJ, 2018,
Ethnicity and wealth: the dynamics of dual segregation
, PLoS ONE, Vol: 13, ISSN: 1932-6203Creating inclusive cities requires meaningful responses to inequality and segregation. We build an agent-based model of interactions between wealth and ethnicity of agents to investigate ‘dual’ segregations—due to ethnicity and due to wealth. As agents are initially allowed to move into neighbourhoods they cannot afford, we find a regime where there is marginal increase in both wealth segregation and ethnic segregation. However, as more agents are progressively allowed entry into unaffordable neighbourhoods, we find that both wealth and ethnic segregations undergo sharp, non-linear transformations, but in opposite directions—wealth segregation shows a dramatic decline, while ethnic segregation an equally sharp upsurge. We argue that the decrease in wealth segregation does not merely accompany, but actually drives the increase in ethnic segregation. Essentially, as agents are progressively allowed into neighbourhoods in contravention of affordability, they create wealth configurations that enable a sharp decline in wealth segregation, which at the same time allow co-ethnics to spatially congregate despite differences in wealth, resulting in the abrupt worsening of ethnic segregation.
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