A Spectral Algorithm with Additive Clustering for the Recovery of Overlapping Communities in Networks

This paper presents a novel spectral algorithm with additive clustering designed to identify overlapping communities in networks. The algorithm is based on geometric properties of the spectrum of the expected adjacency matrix in a random graph model that we call stochastic blockmodel with overlap (SBMO). An adaptive version of the algorithm, that does not require the knowledge of the number of hidden communities, is proved to be consistent under the SBMO when the degrees in the graph are (slightly more than) logarithmic. The algorithm is shown to perform well on simulated data and on real-world graphs with known overlapping communities.Comment: Journal of Theoretical Computer Science (TCS), Elsevier, A Para\^itr

Effects of Contact Network Models on Stochastic Epidemic Simulations

The importance of modeling the spread of epidemics through a population has led to the development of mathematical models for infectious disease propagation. A number of empirical studies have collected and analyzed data on contacts between individuals using a variety of sensors. Typically one uses such data to fit a probabilistic model of network contacts over which a disease may propagate. In this paper, we investigate the effects of different contact network models with varying levels of complexity on the outcomes of simulated epidemics using a stochastic Susceptible-Infectious-Recovered (SIR) model. We evaluate these network models on six datasets of contacts between people in a variety of settings. Our results demonstrate that the choice of network model can have a significant effect on how closely the outcomes of an epidemic simulation on a simulated network match the outcomes on the actual network constructed from the sensor data. In particular, preserving degrees of nodes appears to be much more important than preserving cluster structure for accurate epidemic simulations.Comment: To appear at International Conference on Social Informatics (SocInfo) 201

Effect of different levels of acute hypoxia on subsequent oral glucose tolerance in males with overweight: A balanced cross-over pilot feasibility study

Previous research has shown that ≤60 min hypoxic exposure improves subsequent glycaemic control, but the optimal level of hypoxia is unknown and data are lacking from individuals with overweight. We undertook a cross-over pilot feasibility study investigating the effect of 60-min prior resting exposure to different inspired oxygen fractions (CON FI O2  = 0.209; HIGH FI O2  = 0.155; VHIGH FI O2  = 0.125) on glycaemic control, insulin sensitivity, and oxidative stress during a subsequent oral glucose tolerance test (OGTT) in males with overweight (mean (SD) BMI = 27.6 (1.3) kg/m2 ; n = 12). Feasibility was defined by exceeding predefined withdrawal criteria for peripheral blood oxygen saturation (SpO2 ), partial pressure of end-tidal oxygen or carbon dioxide and acute mountain sickness (AMS), and dyspnoea symptomology. Hypoxia reduced SpO2 in a stepwise manner (CON = 97(1)%; HIGH = 91(1)%; VHIGH = 81(3)%, p  0.05). We observed no between-conditions differences in oxidative stress (p > 0.05), but dyspnoea and AMS symptoms increased in VHIGH (p < 0.05), with one participant meeting the withdrawal criteria. Acute HIGH or VHIGH exposure prior to an OGTT does not influence glucose homeostasis in males with overweight, but VHIGH is associated with adverse symptomology and reduced feasibility

The diplomat's dilemma: Maximal power for minimal effort in social networks

Closeness is a global measure of centrality in networks, and a proxy for how influential actors are in social networks. In most network models, and many empirical networks, closeness is strongly correlated with degree. However, in social networks there is a cost of maintaining social ties. This leads to a situation (that can occur in the professional social networks of executives, lobbyists, diplomats and so on) where agents have the conflicting objectives of aiming for centrality while simultaneously keeping the degree low. We investigate this situation in an adaptive network-evolution model where agents optimize their positions in the network following individual strategies, and using only local information. The strategies are also optimized, based on the success of the agent and its neighbors. We measure and describe the time evolution of the network and the agents' strategies.Comment: Submitted to Adaptive Networks: Theory, Models and Applications, to be published from Springe

Defecting or not defecting: how to "read" human behavior during cooperative games by EEG measurements

Understanding the neural mechanisms responsible for human social interactions is difficult, since the brain activities of two or more individuals have to be examined simultaneously and correlated with the observed social patterns. We introduce the concept of hyper-brain network, a connectivity pattern representing at once the information flow among the cortical regions of a single brain as well as the relations among the areas of two distinct brains. Graph analysis of hyper-brain networks constructed from the EEG scanning of 26 couples of individuals playing the Iterated Prisoner's Dilemma reveals the possibility to predict non-cooperative interactions during the decision-making phase. The hyper-brain networks of two-defector couples have significantly less inter-brain links and overall higher modularity - i.e. the tendency to form two separate subgraphs - than couples playing cooperative or tit-for-tat strategies. The decision to defect can be "read" in advance by evaluating the changes of connectivity pattern in the hyper-brain network

Flavor network and the principles of food pairing

The cultural diversity of culinary practice, as illustrated by the variety of regional cuisines, raises the question of whether there are any general patterns that determine the ingredient combinations used in food today or principles that transcend individual tastes and recipes. We introduce a flavor network that captures the flavor compounds shared by culinary ingredients. Western cuisines show a tendency to use ingredient pairs that share many flavor compounds, supporting the so-called food pairing hypothesis. By contrast, East Asian cuisines tend to avoid compound sharing ingredients. Given the increasing availability of information on food preparation, our data-driven investigation opens new avenues towards a systematic understanding of culinary practice.Comment: 39 pages, 15 figure

Potential of a cyclone prototype spacer to improve in vitro dry powder delivery

Copyright The Author(s) 2013. This article is published with open access at Springerlink.com. This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are creditedPurpose: Low inspiratory force in patients with lung disease is associated with poor deagglomeration and high throat deposition when using dry powder inhalers (DPIs). The potential of two reverse flow cyclone prototypes as spacers for commercial carrierbased DPIs was investigated. Methods: Cyclohaler®, Accuhaler® and Easyhaler® were tested with and without the spacers between 30-60 Lmin-1. Deposition of particles in the next generation impactor and within the devices was determined by high performance liquid chromatography. Results: Reduced induction port deposition of the emitted particles from the cyclones was observed due to the high retention of the drug within the spacers (e.g. salbutamol sulphate (SS): 67.89 ± 6.51 % at 30 Lmin-1 in Cheng 1). Fine particle fractions of aerosol as emitted from the cyclones were substantially higher than the DPIs alone. Moreover, the aerodynamic diameters of particles emitted from the cyclones were halved compared to the DPIs alone (e.g. SS from the Cyclohaler® at 4 kPa: 1.08 ± 0.05 μm vs. 3.00 ± 0.12 μm, with and without Cheng 2, respectively) and unaltered with increased flow rates. Conclusion: This work has shown the potential of employing a cyclone spacer for commercial carrier-based DPIs to improve inhaled drug delivery.Peer reviewe

REFERQUAL: A pilot study of a new service quality assessment instrument in the GP Exercise Referral scheme setting

Background The development of an instrument accurately assessing service quality in the GP Exercise Referral Scheme (ERS) industry could potentially inform scheme organisers of the factors that affect adherence rates leading to the implementation of strategic interventions aimed at reducing client drop-out. Methods A modified version of the SERVQUAL instrument was designed for use in the ERS setting and subsequently piloted amongst 27 ERS clients. Results Test re-test correlations were calculated via Pearson's 'r' or Spearman's 'rho', depending on whether the variables were Normally Distributed, to show a significant (mean r = 0.957, SD = 0.02, p < 0.05; mean rho = 0.934, SD = 0.03, p < 0.05) relationship between all items within the questionnaire. In addition, satisfactory internal consistency was demonstrated via Cronbach's 'α'. Furthermore, clients responded favourably towards the usability, wording and applicability of the instrument's items. Conclusion REFERQUAL is considered to represent promise as a suitable tool for future evaluation of service quality within the ERS community. Future research should further assess the validity and reliability of this instrument through the use of a confirmatory factor analysis to scrutinise the proposed dimensional structure

The interplay of microscopic and mesoscopic structure in complex networks

Not all nodes in a network are created equal. Differences and similarities exist at both individual node and group levels. Disentangling single node from group properties is crucial for network modeling and structural inference. Based on unbiased generative probabilistic exponential random graph models and employing distributive message passing techniques, we present an efficient algorithm that allows one to separate the contributions of individual nodes and groups of nodes to the network structure. This leads to improved detection accuracy of latent class structure in real world data sets compared to models that focus on group structure alone. Furthermore, the inclusion of hitherto neglected group specific effects in models used to assess the statistical significance of small subgraph (motif) distributions in networks may be sufficient to explain most of the observed statistics. We show the predictive power of such generative models in forecasting putative gene-disease associations in the Online Mendelian Inheritance in Man (OMIM) database. The approach is suitable for both directed and undirected uni-partite as well as for bipartite networks

Four patients with a history of acute exacerbations of COPD: implementing the CHEST/Canadian Thoracic Society guidelines for preventing exacerbations

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