996 resultados para C template metaprogramming


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Aim: In 2013 QUT introduced the Medical Imaging Training Immersive Environment (MITIE) as a virtual reality (VR) platform that allowed students to practice general radiography. The system software has been expanded to now include C-Arm. The aim of this project was to investigate the use of this technology in the pedagogy of undergraduate medical imaging students who have limited to no experience in the use of the C-Arm clinically. Method: The Medical Imaging Training Immersive Environment (MITIE) application provides students with realistic and fully interactive 3D models of C-Arm equipment. As with VR initiatives in other health disciplines (12) the software mimics clinical practice as much as possible and uses 3D technology to enhance 3D spatial awareness and realism. The application allows students to set up and expose a virtual patient in a 3D environment as well as creating the resultant image for comparison with a gold standard. Automated feedback highlights ways for the student to improve their patient positioning, equipment setup or exposure factors. The students' equipment knowledge was tested using an on line assessment quiz and surveys provided information on the students' pre-clinical confidence scale, with post-clinical data comparisons. Ethical approval for the project was provided by the university ethics panel. Results: This study is currently under way and this paper will present analysis of initial student feedback relating to the perceived value of the application for confidence in a high risk environment (i.e. operating theatre) and related clinical skills development. Further in-depth evaluation is ongoing with full results to be presented. Conclusion: MITIE C-Arm has a development role to play in the pre-clinical skills training for Medical Radiation Science students. It will augment their theoretical understanding prior to their clinical experience. References 1.Bridge P, Appleyard R, Ward J, Phillips R, Beavis A. The development and evaluation of a virtual radiotherapy treatment machine using an immersive visualisation environment. Computers and Education 2007; 49(2): 481494. 2.Gunn T, Berry C, Bridge P etal. 3D Virtual Radiography: Development and Initial Feedback. Paper presented at the 10th Annual Scientific Meeting of Medical Imaging and Radiation Therapy, March 2013 Hobart, Tasmania.

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When verifying or reverse-engineering digital circuits, one often wants to identify and understand small components in a larger system. A possible approach is to show that the sub-circuit under investigation is functionally equivalent to a reference implementation. In many cases, this task is difficult as one may not have full information about the mapping between input and output of the two circuits, or because the equivalence depends on settings of control inputs. We propose a template-based approach that automates this process. It extracts a functional description for a low-level combinational circuit by showing it to be equivalent to a reference implementation, while synthesizing an appropriate mapping of input and output signals and setting of control signals. The method relies on solving an exists/forall problem using an SMT solver, and on a pruning technique based on signature computation.

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Executive Summary: Completion of the Veloway 1 (V1) will provide a dedicated and safe route for cyclists between the Brisbane CBD and the Gateway Motorway off-ramp at Eight Mile Plains alongside the South East Motorway. The V1 is being delivered in stages and when completed will provide a dedicated 3m wide cycleway 17km in length. Two stages (D and E) remain to be constructed to complete the V1. Major trip attractors along the V1 include the Mater, Princes Alexandra and Greenslopes Hospitals, two campuses of Griffith University, Garden City shopping centre and the Australian Tax Office. This report assesses the available evidence on the impacts on cycling behaviour of the recently completed V1 Stage C. The data sources informing this review include three intercept surveys, motion activated traffic cameras and travel time surveys on the V1 and adjoining South East Freeway Bikeway (SEFB), Strava app data, and cyclist crash data along Logan Road. The key findings from the evidence are that the completed V1 Stage C has: a Attracted cyclists from Holland Park, Holland Park West, Mt Gravatt and southern parts of Tarragindi onto the V1 Stage C. b Reduced the crash exposure of pedestrians to cyclists by attracting higher speed cyclists off the adjoining SEFB onto the cycling dedicated V1 Stage C. c Reduced the potential crash exposure of cyclists to motor vehicles by attracting cyclists off Logan Road on to the V1. d Provided travel time benefits to cyclists and reduced road crossings (eight down to two). e Predominantly attracted adults commuting alone to and from work and university. The evidence shows that the two traffic crossings across Birdwood Road (required as a temporary measure until the V1 is completed) negate much of the travel time gains of the V1 Stage C compared to the adjoining SEFB for southbound cyclists. Many cyclists accessing the V1 Stage C from the south are cycling in high-volume vehicular traffic lanes to reduce their travel time along Birdwood Road, but in the process are increasing their exposure to crashes with motor vehicles. Based on these findings this report recommends that TMR: a. Continue with plans to complete the V1 Veloway b. Undertake an engineering feasibility assessment to determine the viability of constructing a section of the V1 Stage E from the intersection Weller and Birdwood Roads over Marshall Road and along Bapaume Road on the western side of the Motorway to the intersection of Bapaume and Sterculia Roads. c. In the interim, improve signage and Birdwood Road crossing points for cyclists accessing and egressing the southern end of the V1 Stage C. d. Work with Brisbane City Council to identify the safest and most practical bicycle facilities to facilitate cycle travel between Logan Road and the V1 south of Birdwood Road. e. Improve the awareness of the V1 Stage C through signage for cyclists approaching from the north with the aim of providing a better understanding of the route of the V1 to the south. f. Refine the use of motion activated traffic cameras to improve the capture rate of useable images and obtain an ongoing collection over time of V1 usage data. g. Undertake discussions with Strava, Inc. to refine the presentation of Strava data to improve visual understanding of maps showing before and after cycle route volumes along and on roads leading to the V1.

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Antioxidants in acute physical exercise and exercise training remain a hot topic in sport nutrition, exercise physiology and biology, in general (Jackson, 2008; Margaritis and Rousseau, 2008; Gomez-Cabrera et al., 2012; Nikolaidis et al., 2012). During the past few decades, antioxidants have received attention predominantly as a nutritional strategy for preventing or minimising detrimental effects of reactive oxygen and nitrogen species (RONS), which are generated during and after strenuous exercise (Jackson, 2008, 2009; Powers and Jackson, 2008). Antioxidant supplementation has become a common practice among athletes as a means to (theoretically) reduce oxidative stress, promote recovery and enhance performance (Peternelj and Coombes, 2011). However, until now, requirements of antioxidant micronutrients and antioxidant compounds for athletes training for and competing in different sport events, including marathon running, triathlon races or team sport events involving repeated sprinting, have not been determined sufficiently (Williams et al., 2006; Margaritis and Rousseau, 2008). Crucially, evidence has been emerging that higher dosages of antioxidants may not necessarily be beneficial in this context, but can also elicit detrimental effects by interfering with performance-enhancing (Gomez-Cabrera et al., 2008) and health-promoting training adaptations (Ristow et al., 2009). As originally postulated in a pioneering study on exercise-induced production of RONS by Davies et al. (1982) in the early 1980s, evidence has been increasing in recent years that RONS are not only damaging agents, but also act as signalling molecules for regulating muscle function (Reid, 2001; Jackson, 2008) and for initiating adaptive responses to exercise (Jackson, 2009; Powers et al., 2010). The recognition that antioxidants could, vice versa, interact with the signalling pathways underlying the responses to acute (and repeated) bouts of exercise has contributed important novel aspects to the continued discussion on antioxidant requirements for athletes. In view of the recent advances in this field, it is the aim of this report to examine the current knowledge of antioxidants, in particular of vitamins C and E, in the basic nutrition of athletes. While overviews on related topics including basic mechanisms of exercise-induced oxidative stress, redox biology, antioxidant defence systems and a summary of studies on antioxidant supplementation during exercise training are provided, this does not mean that this report is comprehensive. Several issues of the expanding and multidisciplinary field of antioxidants and exercise are covered elsewhere in this book and/or in the literature. Exemplarily, the reader is referred to reviews on oxidative stress (Konig et al., 2001; Vollaard et al., 2005; Knez et al., 2006; Powers and Jackson, 2008; Nikolaidis et al., 2012), redox-sensitive signalling and muscle function (Reid, 2001; Vollaard et al., 2005; Jackson, 2008; Ji, 2008; Powers and Jackson, 2008; Powers et al., 2010; Radak et al., 2013) and antioxidant supplementation (Williams et al., 2006; Peake et al., 2007; Peternelj and Coombes, 2011) in the context with exercise. Within the scope of the report, we rather aim to address the question regarding requirements of antioxidants, specifically vitamins C and E, during exercise training, draw conclusions and provide practical implications from the recent research.

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Explores how young people in Australia first come to inject drugs and how they learn about hepatitis C and sterile injecting drug use. Background on hepatitis C; Reasons for injecting drugs; Selection criteria for young people's participation in the i2i Project.

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In structural brain MRI, group differences or changes in brain structures can be detected using Tensor-Based Morphometry (TBM). This method consists of two steps: (1) a non-linear registration step, that aligns all of the images to a common template, and (2) a subsequent statistical analysis. The numerous registration methods that have recently been developed differ in their detection sensitivity when used for TBM, and detection power is paramount in epidemological studies or drug trials. We therefore developed a new fluid registration method that computes the mappings and performs statistics on them in a consistent way, providing a bridge between TBM registration and statistics. We used the Log-Euclidean framework to define a new regularizer that is a fluid extension of the Riemannian elasticity, which assures diffeomorphic transformations. This regularizer constrains the symmetrized Jacobian matrix, also called the deformation tensor. We applied our method to an MRI dataset from 40 fraternal and identical twins, to revealed voxelwise measures of average volumetric differences in brain structure for subjects with different degrees of genetic resemblance.

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Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8 1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.

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Despite substantial progress in measuring the 3D profile of anatomical variations in the human brain, their genetic and environmental causes remain enigmatic. We developed an automated system to identify and map genetic and environmental effects on brain structure in large brain MRI databases . We applied our multi-template segmentation approach ("Multi-Atlas Fluid Image Alignment") to fluidly propagate hand-labeled parameterized surface meshes into 116 scans of twins (60 identical, 56 fraternal), labeling the lateral ventricles. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps revealed 3D heritability patterns, and their significance, with and without adjustments for global brain scale. These maps visualized detailed profiles of environmental versus genetic influences on the brain, extending genetic models to spatially detailed, automatically computed, 3D maps.

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Despite substantial progress in measuring the anatomical and functional variability of the human brain, little is known about the genetic and environmental causes of these variations. Here we developed an automated system to visualize genetic and environmental effects on brain structure in large brain MRI databases. We applied our multi-template segmentation approach termed "Multi-Atlas Fluid Image Alignment" to fluidly propagate hand-labeled parameterized surface meshes, labeling the lateral ventricles, in 3D volumetric MRI scans of 76 identical (monozygotic, MZ) twins (38 pairs; mean age = 24.6 (SD = 1.7)); and 56 same-sex fraternal (dizygotic, DZ) twins (28 pairs; mean age = 23.0 (SD = 1.8)), scanned as part of a 5-year research study that will eventually study over 1000 subjects. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps, derived from path analysis, revealed patterns of heritability, and their significance, in 3D. Path coefficients for the 'ACE' model that best fitted the data indicated significant contributions from genetic factors (A = 7.3%), common environment (C = 38.9%) and unique environment (E = 53.8%) to lateral ventricular volume. Earlier-maturing occipital horn regions may also be more genetically influenced than later-maturing frontal regions. Maps visualized spatially-varying profiles of environmental versus genetic influences. The approach shows promise for automatically measuring gene-environment effects in large image databases.

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The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).

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Studies of cerebral asymmetry can open doors to understanding the functional specialization of each brain hemisphere, and how this is altered in disease. Here we examined hemispheric asymmetries in fiber architecture using diffusion tensor imaging (DTI) in 100 subjects, using high-dimensional fluid warping to disentangle shape differences from measures sensitive to myelination. Confounding effects of purely structural asymmetries were reduced by using co-registered structural images to fluidly warp 3D maps of fiber characteristics (fractional and geodesic anisotropy) to a structurally symmetric minimal deformation template (MDT). We performed a quantitative genetic analysis on 100 subjects to determine whether the sources of the remaining signal asymmetries were primarily genetic or environmental. A twin design was used to identify the heritable features of fiber asymmetry in various regions of interest, to further assist in the discovery of genes influencing brain micro-architecture and brain lateralization. Genetic influences and left/right asymmetries were detected in the fiber architecture of the frontal lobes, with minor differences depending on the choice of registration template.

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Brain asymmetry has been a topic of interest for neuroscientists for many years. The advent of diffusion tensor imaging (DTI) allows researchers to extend the study of asymmetry to a microscopic scale by examining fiber integrity differences across hemispheres rather than the macroscopic differences in shape or structure volumes. Even so, the power to detect these microarchitectural differences depends on the sample size and how the brain images are registered and how many subjects are studied. We fluidly registered 4 Tesla DTI scans from 180 healthy adult twins (45 identical and fraternal pairs) to a geometrically-centered population mean template. We computed voxelwise maps of significant asymmetries (left/right hemisphere differences) for common fiber anisotropy indices (FA, GA). Quantitative genetic models revealed that 47-62% of the variance in asymmetry was due to genetic differences in the population. We studied how these heritability estimates varied with the type of registration target (T1- or T2-weighted) and with sample size. All methods consistently found that genetic factors strongly determined the lateralization of fiber anisotropy, facilitating the quest for specific genes that might influence brain asymmetry and fiber integrity.

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We used diffusion tensor magnetic resonance imaging (DTI) to reveal the extent of genetic effects on brain fiber microstructure, based on tensor-derived measures, in 22 pairs of monozygotic (MZ) twins and 23 pairs of dizygotic (DZ) twins (90 scans). After Log-Euclidean denoising to remove rank-deficient tensors, DTI volumes were fluidly registered by high-dimensional mapping of co-registered MP-RAGE scans to a geometrically-centered mean neuroanatomical template. After tensor reorientation using the strain of the 3D fluid transformation, we computed two widely used scalar measures of fiber integrity: fractional anisotropy (FA), and geodesic anisotropy (GA), which measures the geodesic distance between tensors in the symmetric positive-definite tensor manifold. Spatial maps of intraclass correlations (r) between MZ and DZ twins were compared to compute maps of Falconer's heritability statistics, i.e. the proportion of population variance explainable by genetic differences among individuals. Cumulative distribution plots (CDF) of effect sizes showed that the manifold measure, GA, comparably the Euclidean measure, FA, in detecting genetic correlations. While maps were relatively noisy, the CDFs showed promise for detecting genetic influences on brain fiber integrity as the current sample expands.

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Information from the full diffusion tensor (DT) was used to compute voxel-wise genetic contributions to brain fiber microstructure. First, we designed a new multivariate intraclass correlation formula in the log-Euclidean framework. We then analyzed used the full multivariate structure of the tensor in a multivariate version of a voxel-wise maximum-likelihood structural equation model (SEM) that computes the variance contributions in the DTs from genetic (A), common environmental (C) and unique environmental (E) factors. Our algorithm was tested on DT images from 25 identical and 25 fraternal twin pairs. After linear and fluid registration to a mean template, we computed the intraclass correlation and Falconer's heritability statistic for several scalar DT-derived measures and for the full multivariate tensors. Covariance matrices were found from the DTs, and inputted into SEM. Analyzing the full DT enhanced the detection of A and C effects. This approach should empower imaging genetics studies that use DTI.

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Here we demonstrate that commercial carbon supported Pt nanoparticles react with [AuCl4]- ions at room temperature to produce a highly active Au/Pt/C material with an ultralow coverage of elemental Au on the Pt nanoparticles that exhibits significantly enhanced activity for ethanol oxidation when compared to Pt/C.