330 research outputs found

    Community detection in temporal multilayer networks, with an application to correlation networks

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    Networks are a convenient way to represent complex systems of interacting entities. Many networks contain "communities" of nodes that are more densely connected to each other than to nodes in the rest of the network. In this paper, we investigate the detection of communities in temporal networks represented as multilayer networks. As a focal example, we study time-dependent financial-asset correlation networks. We first argue that the use of the "modularity" quality function---which is defined by comparing edge weights in an observed network to expected edge weights in a "null network"---is application-dependent. We differentiate between "null networks" and "null models" in our discussion of modularity maximization, and we highlight that the same null network can correspond to different null models. We then investigate a multilayer modularity-maximization problem to identify communities in temporal networks. Our multilayer analysis only depends on the form of the maximization problem and not on the specific quality function that one chooses. We introduce a diagnostic to measure \emph{persistence} of community structure in a multilayer network partition. We prove several results that describe how the multilayer maximization problem measures a trade-off between static community structure within layers and larger values of persistence across layers. We also discuss some computational issues that the popular "Louvain" heuristic faces with temporal multilayer networks and suggest ways to mitigate them.Comment: 42 pages, many figures, final accepted version before typesettin

    Pore space analysis of beech wood: The vessel network

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    Water transport in wood is vital for the survival of trees. With synchrotron radiation X-ray tomographic microscopy (SRXTM), it has become possible to characterize and quantify the three-dimensional (3D) network formed by vessels that are responsible for longitudinal transport. In the present study, the spatial size dependence of vessels and the organization inside single growth rings in terms of vessel-induced porosity was studied by SRXTM. Network characteristics, such as connectivity, were deduced by digital image analysis from the processed tomographic data and related to known complex network topologie

    Intragroup competition predicts individual foraging specialisation in a group-living mammal

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    Individual foraging specialisation has important ecological implications, but its causes in group-living species are unclear. One of the major consequences of group living is increased intragroup competition for resources. Foraging theory predicts that with increased competition, individuals should add new prey items to their diet, widening their foraging niche (‘optimal foraging hypothesis’). However, classic competition theory suggests the opposite: that increased competition leads to niche partitioning and greater individual foraging specialisation (‘niche partitioning hypothesis’). We tested these opposing predictions in wild, group-living banded mongooses (Mungos mungo), using stable isotope analysis of banded mongoose whiskers to quantify individual and group foraging niche. Individual foraging niche size declined with increasing group size, despite all groups having a similar overall niche size. Our findings support the prediction that competition promotes niche partitioning within social groups and suggest that individual foraging specialisation may play an important role in the formation of stable social groupings.Peer reviewe

    Intensity standardization methods in magnetic resonance imaging of head and neck cancer

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    BACKGROUND AND PURPOSE: Conventional magnetic resonance imaging (MRI) poses challenges in quantitative analysis because voxel intensity values lack physical meaning. While intensity standardization methods exist, their effects on head and neck MRI have not been investigated. We developed a workflow based on healthy tissue region of interest (ROI) analysis to determine intensity consistency within a patient cohort. Through this workflow, we systematically evaluated intensity standardization methods for MRI of head and neck cancer (HNC) patients.MATERIALS AND METHODS: Two HNC cohorts (30 patients total) were retrospectively analyzed. One cohort was imaged with heterogenous acquisition parameters (HET cohort), whereas the other was imaged with homogenous acquisition parameters (HOM cohort). The standard deviation of cohort-level normalized mean intensity (SD NMI c), a metric of intensity consistency, was calculated across ROIs to determine the effect of five intensity standardization methods on T2-weighted images. For each cohort, a Friedman test followed by a post-hoc Bonferroni-corrected Wilcoxon signed-rank test was conducted to compare SD NMI c among methods. RESULTS: Consistency (SD NMI c across ROIs) between unstandardized images was substantially more impaired in the HET cohort (0.29 ± 0.08) than in the HOM cohort (0.15 ± 0.03). Consequently, corrected p-values for intensity standardization methods with lower SD NMI c compared to unstandardized images were significant in the HET cohort (p &lt; 0.05) but not significant in the HOM cohort (p &gt; 0.05). In both cohorts, differences between methods were often minimal and nonsignificant. CONCLUSIONS: Our findings stress the importance of intensity standardization, either through the utilization of uniform acquisition parameters or specific intensity standardization methods, and the need for testing intensity consistency before performing quantitative analysis of HNC MRI.</p

    Which States Matter? An Application of an Intelligent Discretization Method to Solve a Continuous POMDP in Conservation Biology

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    When managing populations of threatened species, conservation managers seek to make the best conservation decisions to avoid extinction. Making the best decision is difficult because the true population size and the effects of management are uncertain. Managers must allocate limited resources between actively protecting the species and monitoring. Resources spent on monitoring reduce expenditure on management that could be used to directly improve species persistence. However monitoring may prevent sub-optimal management actions being taken as a result of observation error. Partially observable Markov decision processes (POMDPs) can optimize management for populations with partial detectability, but the solution methods can only be applied when there are few discrete states. We use the Continuous U-Tree (CU-Tree) algorithm to discretely represent a continuous state space by using only the states that are necessary to maintain an optimal management policy. We exploit the compact discretization created by CU-Tree to solve a POMDP on the original continuous state space. We apply our method to a population of sea otters and explore the trade-off between allocating resources to management and monitoring. We show that accurately discovering the population size is less important than management for the long term survival of our otter population

    Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

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    Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

    The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

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    The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

    Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

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    Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

    The diversity of population responses to environmental change

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    This is the final version. Available from Wiley via the DOI in this record.Data available from the Dryad Digital Repository: https:// doi.org/10.5061/dryad.d5f54s7The current extinction and climate change crises pressure us to predict population dynamics with ever-greater accuracy. Although predictions rest on the well-advanced theory of age-structured populations, two key issues remain poorly explored. Specifically, how the age-dependency in demographic rates and the year-to-year interactions between survival and fecundity affect stochastic population growth rates. We use inference, simulations and mathematical derivations to explore how environmental perturbations determine population growth rates for populations with different age-specific demographic rates and when ages are reduced to stages. We find that stage- vs. age-based models can produce markedly divergent stochastic population growth rates. The differences are most pronounced when there are survival-fecundity-trade-offs, which reduce the variance in the population growth rate. Finally, the expected value and variance of the stochastic growth rates of populations with different age-specific demographic rates can diverge to the extent that, while some populations may thrive, others will inevitably go extinct.Max Planck Society, Marie Curie FellowshipERCGerman Research FoundationSwiss National Science FoundationNational Science FoundationNational Institute of AgingRamon y Cajal Research GrantWenner-Gren FoundationLeakey FoundationNational Geographic SocietyZoological Society of San DiegoUniversity of PennsylvaniaArgentinean National Council of Researc
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