3,978 research outputs found

    Структура іншомовної професійно зорієнтованої мовленнєвої компетентності

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    Розгляд та аналіз структури професійно зорієнтованої іншомовної мовленнєвої компетентності у порівнянні зі структурою загальної мовленнєвої компетентності, враховуючи особливості їх компонентів

    Incorporating scale dependence in disease burden estimates:the case of human African trypanosomiasis in Uganda

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    The WHO has established the disability-adjusted life year (DALY) as a metric for measuring the burden of human disease and injury globally. However, most DALY estimates have been calculated as national totals. We mapped spatial variation in the burden of human African trypanosomiasis (HAT) in Uganda for the years 2000-2009. This represents the first geographically delimited estimation of HAT disease burden at the sub-country scale.Disability-adjusted life-year (DALY) totals for HAT were estimated based on modelled age and mortality distributions, mapped using Geographic Information Systems (GIS) software, and summarised by parish and district. While the national total burden of HAT is low relative to other conditions, high-impact districts in Uganda had DALY rates comparable to the national burden rates for major infectious diseases. The calculated average national DALY rate for 2000-2009 was 486.3 DALYs/100 000 persons/year, whereas three districts afflicted by rhodesiense HAT in southeastern Uganda had burden rates above 5000 DALYs/100 000 persons/year, comparable to national GBD 2004 average burden rates for malaria and HIV/AIDS.These results provide updated and improved estimates of HAT burden across Uganda, taking into account sensitivity to under-reporting. Our results highlight the critical importance of spatial scale in disease burden analyses. National aggregations of disease burden have resulted in an implied bias against highly focal diseases for which geographically targeted interventions may be feasible and cost-effective. This has significant implications for the use of DALY estimates to prioritize disease interventions and inform cost-benefit analyses

    The what and where of adding channel noise to the Hodgkin-Huxley equations

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    One of the most celebrated successes in computational biology is the Hodgkin-Huxley framework for modeling electrically active cells. This framework, expressed through a set of differential equations, synthesizes the impact of ionic currents on a cell's voltage -- and the highly nonlinear impact of that voltage back on the currents themselves -- into the rapid push and pull of the action potential. Latter studies confirmed that these cellular dynamics are orchestrated by individual ion channels, whose conformational changes regulate the conductance of each ionic current. Thus, kinetic equations familiar from physical chemistry are the natural setting for describing conductances; for small-to-moderate numbers of channels, these will predict fluctuations in conductances and stochasticity in the resulting action potentials. At first glance, the kinetic equations provide a far more complex (and higher-dimensional) description than the original Hodgkin-Huxley equations. This has prompted more than a decade of efforts to capture channel fluctuations with noise terms added to the Hodgkin-Huxley equations. Many of these approaches, while intuitively appealing, produce quantitative errors when compared to kinetic equations; others, as only very recently demonstrated, are both accurate and relatively simple. We review what works, what doesn't, and why, seeking to build a bridge to well-established results for the deterministic Hodgkin-Huxley equations. As such, we hope that this review will speed emerging studies of how channel noise modulates electrophysiological dynamics and function. We supply user-friendly Matlab simulation code of these stochastic versions of the Hodgkin-Huxley equations on the ModelDB website (accession number 138950) and http://www.amath.washington.edu/~etsb/tutorials.html.Comment: 14 pages, 3 figures, review articl

    Newsprint coverage of smoking in cars carrying children : a case study of public and scientific opinion driving the policy debate

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    Acknowledgements Date of Acceptance:17/10/2014 Acknowledgements: This project was funded by Cancer Research UK (MC_U130085862) and the Scottish School of Public Health Research. Cancer Research UK and the Scottish School of Public Health Research was not involved in the collection, analysis, and interpretation of data, writing of the manuscript or the decision to submit the manuscript for publication. Shona Hilton, Karen Wood, Josh Bain and Chris Patterson are funded by the UK Medical Research Council as part of the Understandings and Uses of Public Health Research programme (MC_UU_12017/6) at the MRC/CSO Social and Public Health Sciences Unit, University of Glasgow. We thank Alan Pollock who provided assistance with coding.Peer reviewedPublisher PD

    Gene Function Classification Using Bayesian Models with Hierarchy-Based Priors

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    We investigate the application of hierarchical classification schemes to the annotation of gene function based on several characteristics of protein sequences including phylogenic descriptors, sequence based attributes, and predicted secondary structure. We discuss three Bayesian models and compare their performance in terms of predictive accuracy. These models are the ordinary multinomial logit (MNL) model, a hierarchical model based on a set of nested MNL models, and a MNL model with a prior that introduces correlations between the parameters for classes that are nearby in the hierarchy. We also provide a new scheme for combining different sources of information. We use these models to predict the functional class of Open Reading Frames (ORFs) from the E. coli genome. The results from all three models show substantial improvement over previous methods, which were based on the C5 algorithm. The MNL model using a prior based on the hierarchy outperforms both the non-hierarchical MNL model and the nested MNL model. In contrast to previous attempts at combining these sources of information, our approach results in a higher accuracy rate when compared to models that use each data source alone. Together, these results show that gene function can be predicted with higher accuracy than previously achieved, using Bayesian models that incorporate suitable prior information

    ERP evidence suggests executive dysfunction in ecstasy polydrug users

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    Background: Deficits in executive functions such as access to semantic/long-term memory have been shown in ecstasy users in previous research. Equally, there have been many reports of equivocal findings in this area. The current study sought to further investigate behavioural and electro-physiological measures of this executive function in ecstasy users. Method: Twenty ecstasy–polydrug users, 20 non-ecstasy–polydrug users and 20 drug-naïve controls were recruited. Participants completed background questionnaires about their drug use, sleep quality, fluid intelligence and mood state. Each individual also completed a semantic retrieval task whilst 64 channel Electroencephalography (EEG) measures were recorded. Results: Analysis of Variance (ANOVA) revealed no between-group differences in behavioural performance on the task. Mixed ANOVA on event-related potential (ERP) components P2, N2 and P3 revealed significant between-group differences in the N2 component. Subsequent exploratory univariate ANOVAs on the N2 component revealed marginally significant between-group differences, generally showing greater negativity at occipito-parietal electrodes in ecstasy users compared to drug-naïve controls. Despite absence of behavioural differences, differences in N2 magnitude are evidence of abnormal executive functioning in ecstasy–polydrug users

    Detection of the pairwise kinematic Sunyaev-Zel'dovich effect with BOSS DR11 and the Atacama Cosmology Telescope

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    We present a new measurement of the kinematic Sunyaev-Zeldovich effect using data from the Atacama Cosmology Telescope (ACT) and the Baryon Oscillation Spectroscopic Survey (BOSS). Using 600 square degrees of overlapping sky area, we evaluate the mean pairwise baryon momentum associated with the positions of 50,000 bright galaxies in the BOSS DR11 Large Scale Structure catalog. A non-zero signal arises from the large-scale motions of halos containing the sample galaxies. The data fits an analytical signal model well, with the optical depth to microwave photon scattering as a free parameter determining the overall signal amplitude. We estimate the covariance matrix of the mean pairwise momentum as a function of galaxy separation, using microwave sky simulations, jackknife evaluation, and bootstrap estimates. The most conservative simulation-based errors give signal-to-noise estimates between 3.6 and 4.1 for varying galaxy luminosity cuts. We discuss how the other error determinations can lead to higher signal-to-noise values, and consider the impact of several possible systematic errors. Estimates of the optical depth from the average thermal Sunyaev-Zeldovich signal at the sample galaxy positions are broadly consistent with those obtained from the mean pairwise momentum signal.Comment: 15 pages, 8 figures, 2 table

    Interacting Supernovae: Types IIn and Ibn

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    Supernovae (SNe) that show evidence of strong shock interaction between their ejecta and pre-existing, slower circumstellar material (CSM) constitute an interesting, diverse, and still poorly understood category of explosive transients. The chief reason that they are extremely interesting is because they tell us that in a subset of stellar deaths, the progenitor star may become wildly unstable in the years, decades, or centuries before explosion. This is something that has not been included in standard stellar evolution models, but may significantly change the end product and yield of that evolution, and complicates our attempts to map SNe to their progenitors. Another reason they are interesting is because CSM interaction is an efficient engine for making bright transients, allowing super-luminous transients to arise from normal SN explosion energies, and allowing transients of normal SN luminosities to arise from sub-energetic explosions or low radioactivity yield. CSM interaction shrouds the fast ejecta in bright shock emission, obscuring our normal view of the underlying explosion, and the radiation hydrodynamics of the interaction is challenging to model. The CSM interaction may also be highly non-spherical, perhaps linked to binary interaction in the progenitor system. In some cases, these complications make it difficult to definitively tell the difference between a core-collapse or thermonuclear explosion, or to discern between a non-terminal eruption, failed SN, or weak SN. Efforts to uncover the physical parameters of individual events and connections to possible progenitor stars make this a rapidly evolving topic that continues to challenge paradigms of stellar evolution.Comment: Final draft of a chapter in the "SN Handbook". Accepted. 25 pages, 3 fig

    Emergent complex neural dynamics

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    A large repertoire of spatiotemporal activity patterns in the brain is the basis for adaptive behaviour. Understanding the mechanism by which the brain's hundred billion neurons and hundred trillion synapses manage to produce such a range of cortical configurations in a flexible manner remains a fundamental problem in neuroscience. One plausible solution is the involvement of universal mechanisms of emergent complex phenomena evident in dynamical systems poised near a critical point of a second-order phase transition. We review recent theoretical and empirical results supporting the notion that the brain is naturally poised near criticality, as well as its implications for better understanding of the brain
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