96 research outputs found

    The consumption of protein-rich foods in older adults: An exploratory focus group study

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    Objective: Many older adults consume inadequate protein for their needs. This study explored the factors associated with the consumption of high-protein foods in older adults. Methods: Participants over the age of 65 years (n = 28) took part in 1 of 4 focus group discussions on meat, fish, eggs, dairy products, nuts, and pulses. Discussions were audio taped, transcribed, and analyzed using thematic analysis. Results: Numerous and various reasons for the consumption and non-consumption of high-protein foods were reported. Many of these reasons result from reductions in chemosensory, dental and physical abilities, and changes in living situation in the older population, and have impact specifically on high-protein foods because of their often hard, perishable and need-to-be-cooked nature, and high cost. Conclusions and Implications: Further work is required to establish the importance of each of thesereasons in relation to protein intakes, to prioritize those of likely greatest impact for increasing intakes. © 2013 Society for Nutrition Education and Behavior

    Broadband Meter-Wavelength Observations of Ionospheric Scintillation

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    Intensity scintillations of cosmic radio sources are used to study astrophysical plasmas like the ionosphere, the solar wind, and the interstellar medium. Normally these observations are relatively narrow band. With Low Frequency Array (LOFAR) technology at the Kilpisj\"arvi Atmospheric Imaging Receiver Array (KAIRA) station in northern Finland we have observed scintillations over a 3 octave bandwidth. ``Parabolic arcs'', which were discovered in interstellar scintillations of pulsars, can provide precise estimates of the distance and velocity of the scattering plasma. Here we report the first observations of such arcs in the ionosphere and the first broad-band observations of arcs anywhere, raising hopes that study of the phenomenon may similarly improve the analysis of ionospheric scintillations. These observations were made of the strong natural radio source Cygnus-A and covered the entire 30-250\,MHz band of KAIRA. Well-defined parabolic arcs were seen early in the observations, before transit, and disappeared after transit although scintillations continued to be obvious during the entire observation. We show that this can be attributed to the structure of Cygnus-A. Initial results from modeling these scintillation arcs are consistent with simultaneous ionospheric soundings taken with other instruments, and indicate that scattering is most likely to be associated more with the topside ionosphere than the F-region peak altitude. Further modeling and possible extension to interferometric observations, using international LOFAR stations, are discussed.Comment: 11 pages, 17 figure

    European Red List of Habitats Part 1. Marine habitats

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    The European Red List of Habitats provides an overview of the risk of collapse (degree of endangerment) of marine, terrestrial and freshwater habitats in the European Union (EU28) and adjacent regions (EU28+), based on a consistent set of categories and criteria, and detailed data and expert knowledge from involved countries1. A total of 257 benthic marine habitat types were assessed. In total, 19% (EU28) and 18% (EU28+) of the evaluated habitats were assessed as threatened in categories Critically Endangered, Endangered and Vulnerable. An additional 12% were Near Threatened in the EU28 and 11% in the EU28+. These figures are approximately doubled if Data Deficient habitats are excluded. The percentage of threatened habitat types differs across the regional seas. The highest proportion of threatened habitats in the EU28 was found in the Mediterranean Sea (32%), followed by the North-East Atlantic (23%), the Black Sea (13%) and then the Baltic Sea (8%). There was a similar pattern in the EU28+. The most frequently cited pressures and threats were similar across the four regional seas: pollution (eutrophication), biological resource use other than agriculture or forestry (mainly fishing but also aquaculture), natural system modifications (e.g. dredging and sea defence works), urbanisation and climate change. Even for habitats where the assessment outcome was Data Deficient, the Red List assessment process has resulted in the compilation of a substantial body of useful information to support the conservation of marine habitats

    Discretisation-invariant and computationally efficient correlation priors for Bayesian inversion

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    Abstract We are interested in studying Gaussian Markov random fields as correlation priors for Bayesian inversion. We construct the correlation priors to be discretisation-invariant, which means, loosely speaking, that the discrete priors converge to continuous priors at the discretisation limit. We construct the priors with stochastic partial differential equations, which guarantees computational efficiency via sparse matrix approximations. The stationary correlation priors have a clear statistical interpretation through the autocorrelation function. We also consider how to make structural model of an unknown object with anisotropic and inhomogeneous Gaussian Markov random fields. Finally we consider these fields on unstructured meshes, which are needed on complex domains. The publications in this thesis contain fundamental mathematical and computational results of correlation priors. We have considered one application in this thesis, the electrical impedance tomography. These fundamental results and application provide a platform for engineers and researchers to use correlation priors in other inverse problem applications

    Hyperpriors for matérn fields with applications in bayesian inversion

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    We introduce non-stationary Matérn fofield priors with stochastic partial differential equations, and construct correlation length-scaling with hyperpriors. We model both the hyperprior and the Matérn prior as continuousparameter random fields. As hypermodels, we use Cauchy and Gaussian random fields, which we map suitably to a desired correlation length-scaling range. For computations, we discretise the models with finite difference methods. We consider the convergence of the discretised prior and posterior to the discretisation limit. We apply the developed methodology to certain interpolation, numerical differentiation and deconvolution problems, and show numerically that we can make Bayesian inversion which promotes competing constraints of smoothness and edge-preservation. For computing the conditional mean estimator of the posterior distribution, we use a combination of Gibbs and Metropolis-within-Gibbs sampling algorithms

    Study of TEC fluctuation via stochasticmodels and Bayesian inversion

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    Abstract We propose stochastic processes to be used to model the total electron content (TEC) observation. Based on this, we model the rate of change of TEC (ROT) variation during ionospheric quiet conditions with stationary processes. During ionospheric disturbed conditions, for example, when irregularity in ionospheric electron density distribution occurs, stationarity assumption over long time periods is no longer valid. In these cases, we make the parameter estimation for short time scales, during which we can assume stationarity. We show the relationship between the new method and commonly used TEC characterization parameters ROT and the ROT Index (ROTI). We construct our parametric model within the framework of Bayesian statistical inverse problems and hence give the solution as an a posteriori probability distribution. Bayesian framework allows us to model measurement errors systematically. Similarly, we mitigate variation of TEC due to factors which are not of ionospheric origin, like due to the motion of satellites relative to the receiver, by incorporating a priori knowledge in the Bayesian model. In practical computations, we draw the so-called maximum a posteriori estimates, which are our ROT and ROTI estimates, from the posterior distribution. Because the algorithm allows to estimate ROTI at each observation time, the estimator does not depend on the period of time for ROTI computation. We verify the method by analyzing TEC data recorded by GPS receiver located in Ethiopia (11.6∘N, 37.4∘E). The results indicate that the TEC fluctuations caused by the ionospheric irregularity can be effectively detected and quantified from the estimated ROT and ROTI values
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