1,833 research outputs found

    The Routing of Complex Contagion in Kleinberg's Small-World Networks

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    In Kleinberg's small-world network model, strong ties are modeled as deterministic edges in the underlying base grid and weak ties are modeled as random edges connecting remote nodes. The probability of connecting a node uu with node vv through a weak tie is proportional to 1/∣uv∣α1/|uv|^\alpha, where ∣uv∣|uv| is the grid distance between uu and vv and α≥0\alpha\ge 0 is the parameter of the model. Complex contagion refers to the propagation mechanism in a network where each node is activated only after k≥2k \ge 2 neighbors of the node are activated. In this paper, we propose the concept of routing of complex contagion (or complex routing), where we can activate one node at one time step with the goal of activating the targeted node in the end. We consider decentralized routing scheme where only the weak ties from the activated nodes are revealed. We study the routing time of complex contagion and compare the result with simple routing and complex diffusion (the diffusion of complex contagion, where all nodes that could be activated are activated immediately in the same step with the goal of activating all nodes in the end). We show that for decentralized complex routing, the routing time is lower bounded by a polynomial in nn (the number of nodes in the network) for all range of α\alpha both in expectation and with high probability (in particular, Ω(n1α+2)\Omega(n^{\frac{1}{\alpha+2}}) for α≤2\alpha \le 2 and Ω(nα2(α+2))\Omega(n^{\frac{\alpha}{2(\alpha+2)}}) for α>2\alpha > 2 in expectation), while the routing time of simple contagion has polylogarithmic upper bound when α=2\alpha = 2. Our results indicate that complex routing is harder than complex diffusion and the routing time of complex contagion differs exponentially compared to simple contagion at sweetspot.Comment: Conference version will appear in COCOON 201

    Seeds Buffering for Information Spreading Processes

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    Seeding strategies for influence maximization in social networks have been studied for more than a decade. They have mainly relied on the activation of all resources (seeds) simultaneously in the beginning; yet, it has been shown that sequential seeding strategies are commonly better. This research focuses on studying sequential seeding with buffering, which is an extension to basic sequential seeding concept. The proposed method avoids choosing nodes that will be activated through the natural diffusion process, which is leading to better use of the budget for activating seed nodes in the social influence process. This approach was compared with sequential seeding without buffering and single stage seeding. The results on both real and artificial social networks confirm that the buffer-based consecutive seeding is a good trade-off between the final coverage and the time to reach it. It performs significantly better than its rivals for a fixed budget. The gain is obtained by dynamic rankings and the ability to detect network areas with nodes that are not yet activated and have high potential of activating their neighbours.Comment: Jankowski, J., Br\'odka, P., Michalski, R., & Kazienko, P. (2017, September). Seeds Buffering for Information Spreading Processes. In International Conference on Social Informatics (pp. 628-641). Springe

    A measurement of the 4He(g,n) reaction from 23 < Eg < 70 MeV

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    A comprehensive set of 4He(g,n) absolute cross-section measurements has been performed at MAX-lab in Lund, Sweden. Tagged photons from 23 < Eg < 70 MeV were directed toward a liquid 4He target, and neutrons were identified using pulse-shape discrimination and the Time-of-flight Technique in two liquid-scintillator detector arrays. Seven-point angular distributions have been measured for fourteen photon energies. The results have been subjected to complementary Transition-coefficient and Legendre-coefficient analyses. The results are also compared to experimental data measured at comparable photon energies as well as Recoil-Corrected Continuum Shell Model, Resonating Group Method, and Effective Interaction Hyperspherical-Harmonic Expansion calculations. For photon energies below 29 MeV, the angle-integrated data are significantly larger than the values recommended by Calarco, Berman, and Donnelly in 1983.Comment: 16 pages, 14 figures, some more revisions, submitted to Physical Review

    Study protocol: A phase III randomised, double-blind, parallel arm, stratified, block randomised, placebo-controlled trial investigating the clinical effect and cost-effectiveness of sertraline for the palliative relief of breathlessness in people with chronic breathlessness

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    © Published by the BMJ Publishing Group Limited. Introduction: Breathlessness remains a highly prevalent and distressing symptom for many patients with progressive life-limiting illnesses. Evidence-based interventions for chronic breathlessness are limited, and there is an ongoing need for high-quality research into developing management strategies for optimal palliation of this complex symptom. Previous studies have suggested that selective serotonin reuptake inhibitors such as sertraline may have a role in reducing breathlessness. This paper presents the protocol for a large, adequately powered randomised study evaluating the use of sertraline for chronic breathlessness in people with progressive life-limiting illnesses. Methods and analysis: A total of 240 participants with modified Medical Research Council Dyspnoea Scale breathlessness of level 2 or higher will be randomised to receive either sertraline or placebo for 28 days in this multisite, double-blind study. The dose will be titrated up every 3 days to a maximum of 100 mg daily. The primary outcome will be to compare the efficacy of sertraline with placebo in relieving the intensity of worst breathlessness as assessed by a 0-100 mm Visual Analogue Scale. A number of other outcome measures and descriptors of breathlessness as well as caregiver assessments will also be recorded to ensure adequate analysis of participant breathlessness and to allow an economic analysis to be performed. Participants will also be given the option of continuing blinded treatment until either study data collection is complete or net benefit ceases. Appropriate statistical analysis of primary and secondary outcomes will be used to describe the wealth of data obtained. Ethics and dissemination: Ethics approval was obtained at all participating sites. Results of the study will be submitted for publication in peer-reviewed journals and the key findings presented at national and international conferences. Trial registration number ACTRN12610000464066

    Nanoscale imaging reveals laterally expanding antimicrobial pores in lipid bilayers

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    Antimicrobial peptides are postulated to disrupt microbial phospholipid membranes. The prevailing molecular model is based on the formation of stable or transient pores although the direct observation of the fundamental processes is lacking. By combining rational peptide design with topographical (atomic force microscopy) and chemical (nanoscale secondary ion mass spectrometry) imaging on the same samples, we show that pores formed by antimicrobial peptides in supported lipid bilayers are not necessarily limited to a particular diameter, nor they are transient, but can expand laterally at the nano-to-micrometer scale to the point of complete membrane disintegration. The results offer a mechanistic basis for membrane poration as a generic physicochemical process of cooperative and continuous peptide recruitment in the available phospholipid matrix

    Climate Dynamics: A Network-Based Approach for the Analysis of Global Precipitation

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    Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool to investigate the statistical interdependence of many interacting elements, is used here to analyze the spatial dynamics of annual precipitation over seventy years (1941-2010). The precipitation network is built associating a node to a geographical region, which has a temporal distribution of precipitation, and identifying possible links among nodes through the correlation function. The precipitation network reveals significant spatial variability with barely connected regions, as Eastern China and Japan, and highly connected regions, such as the African Sahel, Eastern Australia and, to a lesser extent, Northern Europe. Sahel and Eastern Australia are remarkably dry regions, where low amounts of rainfall are uniformly distributed on continental scales and small-scale extreme events are rare. As a consequence, the precipitation gradient is low, making these regions well connected on a large spatial scale. On the contrary, the Asiatic South-East is often reached by extreme events such as monsoons, tropical cyclones and heat waves, which can all contribute to reduce the correlation to the short-range scale only. Some patterns emerging between mid-latitude and tropical regions suggest a possible impact of the propagation of planetary waves on precipitation at a global scale. Other links can be qualitatively associated to the atmospheric and oceanic circulation. To analyze the sensitivity of the network to the physical closeness of the nodes, short-term connections are broken. The African Sahel, Eastern Australia and Northern Europe regions again appear as the supernodes of the network, confirming furthermore their long-range connection structure. Almost all North-American and Asian nodes vanish, revealing that extreme events can enhance high precipitation gradients, leading to a systematic absence of long-range patterns

    Characterization of complex networks: A survey of measurements

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    Each complex network (or class of networks) presents specific topological features which characterize its connectivity and highly influence the dynamics of processes executed on the network. The analysis, discrimination, and synthesis of complex networks therefore rely on the use of measurements capable of expressing the most relevant topological features. This article presents a survey of such measurements. It includes general considerations about complex network characterization, a brief review of the principal models, and the presentation of the main existing measurements. Important related issues covered in this work comprise the representation of the evolution of complex networks in terms of trajectories in several measurement spaces, the analysis of the correlations between some of the most traditional measurements, perturbation analysis, as well as the use of multivariate statistics for feature selection and network classification. Depending on the network and the analysis task one has in mind, a specific set of features may be chosen. It is hoped that the present survey will help the proper application and interpretation of measurements.Comment: A working manuscript with 78 pages, 32 figures. Suggestions of measurements for inclusion are welcomed by the author
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