14,663 research outputs found

    The fragility of decentralised trustless socio-technical systems

    Get PDF
    The blockchain technology promises to transform finance, money and even governments. However, analyses of blockchain applicability and robustness typically focus on isolated systems whose actors contribute mainly by running the consensus algorithm. Here, we highlight the importance of considering trustless platforms within the broader ecosystem that includes social and communication networks. As an example, we analyse the flash-crash observed on 21st June 2017 in the Ethereum platform and show that a major phenomenon of social coordination led to a catastrophic cascade of events across several interconnected systems. We propose the concept of “emergent centralisation” to describe situations where a single system becomes critically important for the functioning of the whole ecosystem, and argue that such situations are likely to become more and more frequent in interconnected socio-technical systems. We anticipate that the systemic approach we propose will have implications for future assessments of trustless systems and call for the attention of policy-makers on the fragility of our interconnected and rapidly changing world

    Modeling Structure and Resilience of the Dark Network

    Full text link
    While the statistical and resilience properties of the Internet are no more changing significantly across time, the Darknet, a network devoted to keep anonymous its traffic, still experiences rapid changes to improve the security of its users. Here, we study the structure of the Darknet and we find that its topology is rather peculiar, being characterized by non-homogenous distribution of connections -- typical of scale-free networks --, very short path lengths and high clustering -- typical of small-world networks -- and lack of a core of highly connected nodes. We propose a model to reproduce such features, demonstrating that the mechanisms used to improve cyber-security are responsible for the observed topology. Unexpectedly, we reveal that its peculiar structure makes the Darknet much more resilient than the Internet -- used as a benchmark for comparison at a descriptive level -- to random failures, targeted attacks and cascade failures, as a result of adaptive changes in response to the attempts of dismantling the network across time.Comment: 8 pages, 5 figure

    Constraints on inflation with LSS surveys: features in the primordial power spectrum

    Full text link
    We analyse the efficiency of future large scale structure surveys to unveil the presence of scale dependent features in the primordial spectrum --resulting from cosmic inflation-- imprinted in the distribution of galaxies. Features may appear as a consequence of non-trivial dynamics during cosmic inflation, in which one or more background quantities experienced small but rapid deviations from their characteristic slow-roll evolution. We consider two families of features: localized features and oscillatory extended features. To characterise them we employ various possible templates parametrising their scale dependence and provide forecasts on the constraints on these parametrisations for LSST like surveys. We perform a Fisher matrix analysis for three observables: cosmic microwave background (CMB), galaxy clustering and weak lensing. We find that the combined data set of these observables will be able to limit the presence of features down to levels that are more restrictive than current constraints coming from CMB observations only. In particular, we address the possibility of gaining information on currently known deviations from scale invariance inferred from CMB data, such as the feature appearing at the ℓ∌20\ell \sim 20 multipole (which is the main contribution to the low-ℓ\ell deficit) and a potential feature appearing at ℓ∌800\ell \sim 800.Comment: 37 pp., 5 Tabs., 10 Figs, v3: changed discussion around templates II, III, added clarifications, comments and references. Matches JCAP versio

    MuxViz: A Tool for Multilayer Analysis and Visualization of Networks

    Full text link
    Multilayer relationships among entities and information about entities must be accompanied by the means to analyze, visualize, and obtain insights from such data. We present open-source software (muxViz) that contains a collection of algorithms for the analysis of multilayer networks, which are an important way to represent a large variety of complex systems throughout science and engineering. We demonstrate the ability of muxViz to analyze and interactively visualize multilayer data using empirical genetic, neuronal, and transportation networks. Our software is available at https://github.com/manlius/muxViz.Comment: 18 pages, 10 figures (text of the accepted manuscript

    Multiscale autocorrelation function: a new approach to anisotropy studies

    Full text link
    We present a novel catalog-independent method, based on a scale dependent approach, to detect anisotropy signatures in the arrival direction distribution of the ultra highest energy cosmic rays (UHECR). The method provides a good discrimination power for both large and small data sets, even in presence of strong contaminating isotropic background. We present some applications to simulated data sets of events corresponding to plausible scenarios for charged particles detected by world-wide surface detector-based observatories, in the last decades.Comment: 18 pages, 9 figure

    Involvement of ras p2I in Neurotrophin-induced Response of Sensory, but Not Sympathetic Neurons

    Get PDF
    Little is known about the signal transduction mechanisms involved in the response to neurotrophins and other neurotrophic factors in neurons, beyond the activation of the tyrosine kinase activity of the neurotrophin receptors belonging to the trk family. We have previously shown that the introduction of the oncogene product ras p21 into the cytoplasm of chick embryonic neurons can reproduce the survival and neurite-outgrowth promoting effects of the neurotrophins nerve growth factor (NGF) and brain-derived neurotrophic factor (BDNF), and of ciliary neurotrophic factor (CNTF). To assess the potential signal- transducing role of endogenous ras p21, we introduced function-blocking anti-ras antibodies or their Fab fragments into cultured chick embryonic neurons. The BDNF-induced neurite outgrowth in E12 nodose ganglion neurons was reduced to below control levels, and the NGF- induced survival of E9 dorsal root ganglion (DRG) neurons was inhibited in a specific and dose-dependent fashion. Both effects could be reversed by saturating the epitope-binding sites with biologically inactive ras p21 before microinjection. Surprisingly, ras p21 did not promote the survival of NGF-dependent E12 chick sympathetic neurons, and the NGF-induced survival in these cells was not inhibited by the Fab-fragments. The survival effect of CNTF on ras-responsive ciliary neurons could not be blocked by anti-ras Fab fragments. These results indicate an involvement of ras p21 in the signal transduction of neurotrophic factors in sensory, but not sympathetic or ciliary neurons, pointing to the existence of different signaling pathways not only in CNTF-responsive, but also in neurotrophin-responsive neuronal populations