6,792 research outputs found
Release of soluble metal ions from copper based dental alloys mesured by ICP-MS
Describes the release of soluble metal ions from copper based dental alloys mesured by ICP-MS. Presented at the annual congress of the british toxicology society
Fast computation of the deviance information criterion for latent variable models
© 2014 Elsevier B.V. The deviance information criterion (DIC) has been widely used for Bayesian model comparison. However, recent studies have cautioned against the use of certain variants of the DIC for comparing latent variable models. For example, it has been argued that the conditional DIC–based on the conditional likelihood obtained by conditioning on the latent variables–is sensitive to transformations of latent variables and distributions. Further, in a Monte Carlo study that compares various Poisson models, the conditional DIC almost always prefers an incorrect model. In contrast, the observed-data DIC–calculated using the observed-data likelihood obtained by integrating out the latent variables–seems to perform well. It is also the case that the conditional DIC based on the maximum a posteriori (MAP) estimate might not even exist, whereas the observed-data DIC does not suffer from this problem. In view of these considerations, fast algorithms for computing the observed-data DIC for a variety of high-dimensional latent variable models are developed. Through three empirical applications it is demonstrated that the observed-data DICs have much smaller numerical standard errors compared to the conditional DICs. The corresponding MATLAB code is available upon request
A Bayesian Model Comparison for Trend-Cycle Decompositions of Output
© 2017 The Ohio State University We compare a number of widely used trend-cycle decompositions of output in a formal Bayesian model comparison exercise. This is motivated by the often markedly different results from these decompositions—different decompositions have broad implications for the relative importance of real versus nominal shocks in explaining variations in output. Using U.S. quarterly real GDP, we find that the overall best model is an unobserved components model with two features: (i) a nonzero correlation between trend and cycle innovations and (ii) a break in trend output growth in 2007. The annualized trend output growth decreases from about 3.4% to 1.2%–1.5% after the break. The results also indicate that real shocks are more important than nominal shocks. The slowdown in trend output growth is robust when we expand the set of models to include bivariate unobserved components models
I\u27d Like To See You Sunday : In The Afternoon
https://digitalcommons.library.umaine.edu/mmb-vp/1742/thumbnail.jp
When You\u27re In Love With Someone Who Is Not In Love With You
https://digitalcommons.library.umaine.edu/mmb-vp/2707/thumbnail.jp
Promoting First Nations science capital: reimagining a more inclusive curriculum
This article offers a critical examination of First NationsFootnote1 perspectives in the newly revised Australian Science Curriculum. Despite recent revisions, our analysis indicates that the curriculum continues to marginalise and overlook the rich scientific contributions of First Nations communities in Australia. We employ a science capital lens to probe the design of the curriculum. While the curriculum incorporates elaborations related to First Nations contexts, they are offered to educators as optional, or only intended to be embedded through content descriptions as a cross-curriculum priority. Our research proposes the possibility of a transformative curriculum, one that better acknowledges and embeds First Nations science capital. Emphasising the need for local relevance, this approach advocates for co-constructing learning experiences with First Nations communities and repositioning First Nations perspectives in the curriculum. The study explores the dynamics of collaborating with First Nations stakeholders in curriculum design, highlighting how such partnerships can enrich the exchange of science capital and contribute to a more holistic science education. This integration is crucial for preparing all students to navigate and contribute to the increasingly diverse and multicultural dimensions of society-which include different perspectives of science and science capital, and ultimately promotes a more inclusive science education
A monolithic resonant terahertz sensor element comprising a metamaterial absorber and micro-bolometer
In this article a monolithic resonant terahertz sensor element with a noise equivalent power superior to that of typical commercial room temperature single pixel terahertz detectors and capable of close to real time read-out rates is presented. The detector is constructed via the integration of a metamaterial absorber and a micro-bolometer sensor. An absorption magnitude of 57% at 2.5 THz, a minimum NEP of inline image and a thermal time constant of 68 ms for the sensor are measured. As a demonstration of detector capability, it is employed in a practical Nipkow terahertz imaging system. The monolithic resonant terahertz detector is readily scaled to focal plane array formats by adding standard read-out and addressing circuitry enabling compact, low-cost terahertz imaging
A 16 x 16 CMOS amperometric microelectrode array for simultaneous electrochemical measurements
There is a requirement for an electrochemical sensor technology capable of making multivariate measurements in environmental, healthcare, and manufacturing applications. Here, we present a new device that is highly parallelized with an excellent bandwidth. For the first time, electrochemical cross-talk for a chip-based sensor is defined and characterized. The new CMOS electrochemical sensor chip is capable of simultaneously taking multiple, independent electroanalytical measurements. The chip is structured as an electrochemical cell microarray, comprised of a microelectrode array connected to embedded self-contained potentiostats. Speed and sensitivity are essential in dynamic variable electrochemical systems. Owing to the parallel function of the system, rapid data collection is possible while maintaining an appropriately low-scan rate. By performing multiple, simultaneous cyclic voltammetry scans in each of the electrochemical cells on the chip surface, we are able to show (with a cell-to-cell pitch of 456 ÎĽm) that the signal cross-talk is only 12% between nearest neighbors in a ferrocene rich solution. The system opens up the possibility to use multiple independently controlled electrochemical sensors on a single chip for applications in DNA sensing, medical diagnostics, environmental sensing, the food industry, neuronal sensing, and drug discovery
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