51,086 research outputs found

    Integrating the processes in the evolutionary system of domestication

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    Genetics has long been used as a source of evidence to understand domestication origins. A recent shift in the emphasis of archaeological evidence from a rapid transition paradigm of hunter-gatherers to agriculturalists, to a protracted transition paradigm has highlighted how the scientific framework of interpretation of genetic data was quite dependent on archaeological evidence, resulting in a period of discord in which the two evidence types appeared to support different paradigms. Further examination showed that the discriminatory power of the approaches employed in genetics was low, and framed within the rapid paradigm rather than testing it. In order to interpret genetic data under the new protracted paradigm it must be taken into account how that paradigm changes our expectations of genetic diversity. Preliminary examination suggests that a number of features that constituted key evidence in the rapid paradigm are likely to be interpreted very differently in the protracted paradigm. Specifically, in the protracted transition the mode and mechanisms involved in the evolution of the domestication syndrome have become much more influential in the shape of genetic diversity. The result is that numerous factors interacting over several levels of organization in a domestication system need to be taken into account in order to understand the evolution of the process. This presents a complex problem of integration of different data types which is difficult to describe formally. One possible way forward is to use Bayesian approximation approaches that allow complex systems to be measured in a way that does not require such formality

    Automatic covariate selection in logistic models for chest pain diagnosis: A new approach

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    A newly established method for optimizing logistic models via a minorization-majorization procedure is applied to the problem of diagnosing acute coronary syndromes (ACS). The method provides a principled approach to the selection of covariates which would otherwise require the use of a suboptimal method owing to the size of the covariate set. A strategy for building models is proposed and two models optimized for performance and for simplicity are derived via ten-fold cross-validation. These models confirm that a relatively small set of covariates including clinical and electrocardiographic features can be used successfully in this task. The performance of the models is comparable with previously published models using less principled selection methods. The models prove to be portable when tested on data gathered from three other sites. Whilst diagnostic accuracy and calibration diminishes slightly for these new settings, it remains satisfactory overall. The prospect of building predictive models that are as simple as possible for a required level of performance is valuable if data-driven decision aids are to gain wide acceptance in the clinical situation owing to the need to minimize the time taken to gather and enter data at the bedside

    Human computer interaction and theories

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    Mathematical modelling of zika virus in Brazil

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    In this paper we study some deterministic mathematical models that seek to explain the expansion of zika virus, as a viral epidemic, using published data for Brazil. SIR type models are proposed and validated using the epidemic data found, considering several aspects in the spread of the disease. Finally, we confirmed that the crucial epidemic parameter such as R0R_0 is consistent with those previously reported in the literature for other areas. We also explored variations of the parameters within Brazil for different federal entities. We concluded that a parsimonious model that includes both human and vector populations best describe the epidemic parameters

    Asperger's and the Effective Learning Environment

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    This meta-synthesis of the literature on developing an effective learning environment for children with Asperger Syndrome examines four critical areas that help support academic and social growth and self-advocacy. Early intervention and social skills instruction, while considering the specific needs of the child are foremost and provide the foundation from which all future learning will evolve. Effective learning not only encompasses approaches that are person-centered but also requires adaptations that support transition. For the Asperger child, as he moves into adulthood, transitioning can be especially challenging. As an adult, with ongoing support and interventions, transitions can be opportunities for self-awareness and growth

    Cost-efficient vaccination protocols for network epidemiology

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    We investigate methods to vaccinate contact networks -- i.e. removing nodes in such a way that disease spreading is hindered as much as possible -- with respect to their cost-efficiency. Any real implementation of such protocols would come with costs related both to the vaccination itself, and gathering of information about the network. Disregarding this, we argue, would lead to erroneous evaluation of vaccination protocols. We use the susceptible-infected-recovered model -- the generic model for diseases making patients immune upon recovery -- as our disease-spreading scenario, and analyze outbreaks on both empirical and model networks. For different relative costs, different protocols dominate. For high vaccination costs and low costs of gathering information, the so-called acquaintance vaccination is the most cost efficient. For other parameter values, protocols designed for query-efficient identification of the network's largest degrees are most efficient

    Statistical modelling under epistemic data imprecision : some results on estimating multinomial distributions and logistic regression for coarse categorical data

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    Paper presented at 9th International Symposium on Imprecise Probability: Theories and Applications, Pescara, Italy, 2015. Abstract: The paper deals with parameter estimation for categorical data under epistemic data imprecision, where for a part of the data only coarse(ned) versions of the true values are observable. For different observation models formalizing the information available on the coarsening process, we derive the (typically set-valued) maximum likelihood estimators of the underlying distributions. We discuss the homogeneous case of independent and identically distributed variables as well as logistic regression under a categorical covariate. We start with the imprecise point estimator under an observation model describing the coarsening process without any further assumptions. Then we determine several sensitivity parameters that allow the refinement of the estimators in the presence of auxiliary information

    Towards more balanced news access? A study on the impact of cost-cutting and Web 2.0 on the mediated public sphere

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    In order to assess the impact of cost-cutting and digitalization on the expansion or contraction of the mediated public sphere, we developed a quantitative and longitudinal content analysis focused on sourcing practices for foreign news reporting in four Belgian newspapers (1995-2010). The results show little to no shift in the news access of different types of sources. Political sources dominate foreign news output, but ordinary citizens also play a significant role. Although it becomes clear that Belgian journalists often do not explicitly mention their use of news agency copy, recycled news articles or PR material, our findings indicate that concerns about cost-cutting in newsrooms or sanguinity about the democratic potential of Web 2.0 seem fairly exaggerated, at least in the Belgian context
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