WIMU instrumentation of assassin trainer & skeleton sled

Skeleton is a high‐speed Winter Olympic sport performed on the same twisting, downhill ice tracks used for Bobsleigh & Luge. The single rider sprints and pushes their sled for 20‐30m on a level start section before loading and going through a twisting course of over 1km, at speeds up to 140km/h, experiencing up to 5g. In competition, the top athletes can be within a fraction of a second of each other. The initial short pushing period is believed to be critical to overall performance but it is not well understood. A collaborative project between University of Bath, UK Sport and Tyndall National Institute is instrumenting skeleton athletes, training equipment and test tracks with Tyndall’s Wireless Inertial Measurement Unit technology in order to investigate and improve understanding of this phase of a skeleton run. It is hoped this will lead to improved training regimes and better performance of such elite, Olympic level athletes. This work presents an initial look at the system as implemented and data recorded.

Wavelength division multiplexing at 2μm

This paper shows, for the first time, the implementation of a WDM subsystem at the 2μm wavelength window with mixed formats. Three wavelength channels were directly modulated withBPSK Fast-OFDM at 5Gbit/s per channel, with a fourth channel NRZ-OOK externally modulated at8.5Gbit/s giving a total capacity in excess of 20 Gbit/s.

An examination of the construction of meanings for obesity in Ireland

Obesity has been defined as a consequence of energy imbalance, where energy intake exceeds energy expenditure and results in a build-up of adipose tissue. However, this scientific definition masks the complicated social meanings associated with the condition. This research investigated the construction of meaning around obesity at various levels of inquiry to inform how obesity is portrayed and understood in Ireland. A multi-paradigmatic approach was adopted, drawing on theory and methods from psychology and sociology and an analytical framework combining the Common Sense Model and framing theory was employed. In order to examine the exo-level meanings of obesity, content analysis was performed on two media data sets (n=479, n=346) and a thematic analysis was also performed on the multiple newspaper sample (n=346). At the micro-level, obesity discourses were investigated via the thematic analysis of comments sampled from an online message board. Finally, an online survey assessed individual-level beliefs and understandings of obesity. The media analysis revealed that individual blame for obesity was pervasive and the behavioural frame was dominant. A significant increase in attention to obesity over time was observed, manifestations of weight stigma were common, and there was an emotive discourse of blame directed towards the parents of obese children. The micro-level analysis provided insight into the weight-based stigma in society and a clear set of negative ‘default’ judgements accompanied the obese label. The survey analysis confirmed that the behavioural frame was the dominant means of understanding obesity. One of the strengths of this thesis is the link created between framing and the Common Sense Model in the development of an analytical framework for application in the examination of health/illness representations. This approach helped to ascertain the extent of the pervasive biomedical and individual blame discourse on obesity, which establishes the basis for the stigmatisation of obese persons.

The mobile cloud - more than a cloud

Nearly one billion smart mobile devices are now used for a growing number of tasks, such as browsing the web and accessing online services. In many communities, such devices are becoming the platform of choice for tasks traditionally carried out on a personal computer. However, despite the advances, these devices are still lacking in resources compared to their traditional desktop counterparts. Mobile cloud computing is seen as a new paradigm that can address the resource shortcomings in these devices with the plentiful computing resources of the cloud. This can enable the mobile device to be used for a large range of new applications hosted in the cloud that are too resource demanding to run locally. Bringing these two technologies together presents various difficulties. In this paper, we examine the advantages of the mobile cloud and the new approaches to applications it enables. We present our own solution to create a positive user experience for such applications and describe how it enables these applications.

Expert assessments of retrofitting coal-fired power plants with carbon dioxide capture technologies

A set of 13 US based experts in post-combustion and oxy-fuel combustion CO2 capture systems responded to an extensive questionnaire asking their views on the present status and future expected performance and costs for amine-based, chilled ammonia, and oxy-combustion retrofits of coal-fired power plants. This paper presents the experts' responses for technology maturity, ideal plant characteristics for early adopters, and the extent to which R&D and deployment incentives will impact costs. It also presents the best estimates and 95% confidence limits of the energy penalties associated with amine-based systems. The results show a general consensus that amine-based systems are closer to commercial application, but potential for improving performance and lowering costs is limited; chilled ammonia and oxy-combustion offer greater potential for cost reductions, but not without greater uncertainty regarding scale and technical feasibility. © 2011 Elsevier Ltd.

Information relaxations and duality in stochastic dynamic programs

We describe a general technique for determining upper bounds on maximal values (or lower bounds on minimal costs) in stochastic dynamic programs. In this approach, we relax the nonanticipativity constraints that require decisions to depend only on the information available at the time a decision is made and impose a "penalty" that punishes violations of nonanticipativity. In applications, the hope is that this relaxed version of the problem will be simpler to solve than the original dynamic program. The upper bounds provided by this dual approach complement lower bounds on values that may be found by simulating with heuristic policies. We describe the theory underlying this dual approach and establish weak duality, strong duality, and complementary slackness results that are analogous to the duality results of linear programming. We also study properties of good penalties. Finally, we demonstrate the use of this dual approach in an adaptive inventory control problem with an unknown and changing demand distribution and in valuing options with stochastic volatilities and interest rates. These are complex problems of significant practical interest that are quite difficult to solve to optimality. In these examples, our dual approach requires relatively little additional computation and leads to tight bounds on the optimal values. © 2010 INFORMS.

High-field FMRI reveals brain activation patterns underlying saccade execution in the human superior colliculus.

BACKGROUND: The superior colliculus (SC) has been shown to play a crucial role in the initiation and coordination of eye- and head-movements. The knowledge about the function of this structure is mainly based on single-unit recordings in animals with relatively few neuroimaging studies investigating eye-movement related brain activity in humans. METHODOLOGY/PRINCIPAL FINDINGS: The present study employed high-field (7 Tesla) functional magnetic resonance imaging (fMRI) to investigate SC responses during endogenously cued saccades in humans. In response to centrally presented instructional cues, subjects either performed saccades away from (centrifugal) or towards (centripetal) the center of straight gaze or maintained fixation at the center position. Compared to central fixation, the execution of saccades elicited hemodynamic activity within a network of cortical and subcortical areas that included the SC, lateral geniculate nucleus (LGN), occipital cortex, striatum, and the pulvinar. CONCLUSIONS/SIGNIFICANCE: Activity in the SC was enhanced contralateral to the direction of the saccade (i.e., greater activity in the right as compared to left SC during leftward saccades and vice versa) during both centrifugal and centripetal saccades, thereby demonstrating that the contralateral predominance for saccade execution that has been shown to exist in animals is also present in the human SC. In addition, centrifugal saccades elicited greater activity in the SC than did centripetal saccades, while also being accompanied by an enhanced deactivation within the prefrontal default-mode network. This pattern of brain activity might reflect the reduced processing effort required to move the eyes toward as compared to away from the center of straight gaze, a position that might serve as a spatial baseline in which the retinotopic and craniotopic reference frames are aligned.

Bayesian Gaussian Copula Factor Models for Mixed Data.

Gaussian factor models have proven widely useful for parsimoniously characterizing dependence in multivariate data. There is a rich literature on their extension to mixed categorical and continuous variables, using latent Gaussian variables or through generalized latent trait models acommodating measurements in the exponential family. However, when generalizing to non-Gaussian measured variables the latent variables typically influence both the dependence structure and the form of the marginal distributions, complicating interpretation and introducing artifacts. To address this problem we propose a novel class of Bayesian Gaussian copula factor models which decouple the latent factors from the marginal distributions. A semiparametric specification for the marginals based on the extended rank likelihood yields straightforward implementation and substantial computational gains. We provide new theoretical and empirical justifications for using this likelihood in Bayesian inference. We propose new default priors for the factor loadings and develop efficient parameter-expanded Gibbs sampling for posterior computation. The methods are evaluated through simulations and applied to a dataset in political science. The models in this paper are implemented in the R package bfa.

Neural networks supporting autobiographical memory retrieval in posttraumatic stress disorder.

Posttraumatic stress disorder (PTSD) affects the functional recruitment and connectivity between neural regions during autobiographical memory (AM) retrieval that overlap with default and control networks. Whether such univariate changes relate to potential differences in the contributions of the large-scale neural networks supporting cognition in PTSD is unknown. In the present functional MRI study, we employed independent-component analysis to examine the influence of the engagement of neural networks during the recall of personal memories in a PTSD group (15 participants) as compared to non-trauma-exposed healthy controls (14 participants). We found that the PTSD group recruited similar neural networks when compared to the controls during AM recall, including default-network subsystems and control networks, but group differences emerged in the spatial and temporal characteristics of these networks. First, we found spatial differences in the contributions of the anterior and posterior midline across the networks, and of the amygdala in particular, for the medial temporal subsystem of the default network. Second, we found temporal differences within the medial prefrontal subsystem of the default network, with less temporal coupling of this network during AM retrieval in PTSD relative to controls. These findings suggest that the spatial and temporal characteristics of the default and control networks potentially differ in a PTSD group versus healthy controls and contribute to altered recall of personal memory.

Dynamic neural networks supporting memory retrieval.

How do separate neural networks interact to support complex cognitive processes such as remembrance of the personal past? Autobiographical memory (AM) retrieval recruits a consistent pattern of activation that potentially comprises multiple neural networks. However, it is unclear how such large-scale neural networks interact and are modulated by properties of the memory retrieval process. In the present functional MRI (fMRI) study, we combined independent component analysis (ICA) and dynamic causal modeling (DCM) to understand the neural networks supporting AM retrieval. ICA revealed four task-related components consistent with the previous literature: 1) medial prefrontal cortex (PFC) network, associated with self-referential processes, 2) medial temporal lobe (MTL) network, associated with memory, 3) frontoparietal network, associated with strategic search, and 4) cingulooperculum network, associated with goal maintenance. DCM analysis revealed that the medial PFC network drove activation within the system, consistent with the importance of this network to AM retrieval. Additionally, memory accessibility and recollection uniquely altered connectivity between these neural networks. Recollection modulated the influence of the medial PFC on the MTL network during elaboration, suggesting that greater connectivity among subsystems of the default network supports greater re-experience. In contrast, memory accessibility modulated the influence of frontoparietal and MTL networks on the medial PFC network, suggesting that ease of retrieval involves greater fluency among the multiple networks contributing to AM. These results show the integration between neural networks supporting AM retrieval and the modulation of network connectivity by behavior.

A SURVEY OF FRENCH KEYBOARD MUSIC FROM 1880 TO 1950

French music flourished from the last quarter of the nineteenth century into the early twentieth century, especially in the genres of opera and orchestral music. Although French keyboard music enjoyed less popularity, being overshadowed by these predominant genres, prominent impressionist figures Claude Debussy (1862-1918) and Maurice Ravel (1875-1937) . . brought its revival to the French music. Scholars consider Debussy to be a frontrunner of Impressionism, and his influence had a major impact on subsequent composers. As a result of his popularity, other significant works by French composers seem to be overlooked by pianists and audiences and are not as often performed. Because keyboard works by Debussy and Ravel are a popular performance choice among pianists, I was eager to examine music by other French composers. Through my resea,rch, I found many great works that warranted further study and deserve a place in the keyboard repertoire. This recording project contains works by lesser-known French composers written between the years of 1880 and 1950, namely Emmanuel Chabrier (1841-1894), Gabriel-Urbain Faure (1845-1924), Charles Koechlin (1867-1950), Albert Roussel (1869-1937), Erik Satie (1866-1925), Francis Poulenc (1899-1963), Darius Milhaud (1892-1974), Robert Casadesus (1899-1972) and Henri Dutilleux (b.1916). Since piano repertoire is abundant, it is sometimes difficult to create a performance program. Therefore, it frequently becomes the default to choosing familiar repertoire rather than using the opportunity to expand the repertoire. As a pianist, I feel responsible to search for hidden musical treasures with which pianists and audiences alike are not so well acquainted. This recording project explores nine lesser-known French compositions written between 1880 and 1950. I expect this to be an opportunity to introduce both pianists and audiences to outstanding but unfamiliar works by French composers. This dissertation was recorded on two compact discs in Dekelboum Concert Hall at Clarice Smith Performing Arts Center of the University of Maryland. The recordings are archived in the University of Maryland Library.

Heteronormativity and practitioner-patient interaction.

Heteronormativity is the presumption of heterosexuality as the default sexual orientation and can result in discrimination against the lesbian, gay, and bisexual (LGB) population. This study serves as one of the first experimental studies to examine heteronormative perceptions in communication and their effects on practitioner-patient relationships. LGB participants were randomly assigned to read either heteronormative or non-heteronormative vignettes of a doctor-patient interaction. They then indicated how much health-relevant information they would disclose to the doctor in the vignette and their level of trust in the doctor. In the heteronormative condition, participants were less likely to disclose health-relevant information to the doctor in the vignette and were less trustful of the doctor as compared to those in the non-heteronormative condition. These results have important health implications, as lack of disclosure and trust may prevent people from getting needed care and prevent doctors from giving the best health advice possible. The results of this study provide further evidence that there is a need for more education for all health care professionals to feel comfortable while respectfully communicating with and treating patients who do not identify as heterosexual in order to ensure the best health care experience.

Legal Responsibilities When Hiring Migrant, Seasonal and H2-A Visa Workers

When farmers need to harvest a large amount of crops in a short period of time, migrant, seasonal, and H-2A Visa workers can often be the best solution to complete the job quickly and affordably. However, there are specific Federal and state legal duties and responsibilities for farmers who employ these types of workers and substantial criminal and civil penalties for failing to adhere to the law.

Towards policy-based self-configuration of embedded systems

This paper describes work towards the deployment of flexible self-management into real-time embedded systems. A challenging project which focuses specifically on the development of a dynamic, adaptive automotive middleware is described, and the specific self-management requirements of this project are discussed. These requirements have been identified through the refinement of a wide-ranging set of use cases requiring context-sensitive behaviours. A sample of these use-cases is presented to illustrate the extent of the demands for self-management. The strategy that has been adopted to achieve self-management, based on the use of policies is presented. The embedded and real-time nature of the target system brings the constraints that dynamic adaptation capabilities must not require changes to the run-time code (except during hot update of complete binary modules), adaptation decisions must have low latency, and because the target platforms are resource-constrained the self-management mechanism have low resource requirements (especially in terms of processing and memory). Policy-based computing is thus and ideal candidate for achieving the self-management because the policy itself is loaded at run-time and can be replaced or changed in the future in the same way that a data file is loaded. Policies represent a relatively low complexity and low risk means of achieving self-management, with low run-time costs. Policies can be stored internally in ROM (such as default policies) as well as externally to the system. The architecture of a designed-for-purpose powerful yet lightweight policy library is described. A suitable evaluation platform, supporting the whole life-cycle of feasibility analysis, concept evaluation, development, rigorous testing and behavioural validation has been devised and is described.