26 resultados para Image of God


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BACKGROUND: Atrial fibrillation (AF) is largely regarded to be initiated from left atrial (LA) dilatation, with subsequent dilatation of the right atrium (RA) in those who progress to chronic AF. We hypothesized that in adult patients with right-sided congenital heart disease (CHD) and AF, RA dilatation will predominate with subsequent dilatation of the left atrium, as a mirror image. METHODS: Adult patients with diagnosis of right-sided, ASD or left-sided CHD who had undergone an echocardiographic study and electrocardiographic recording in 2007 were included. RA and LA area were measured from the apical view. AF was diagnosed from a 12-lead electrocardiogram or Holter recording. A multivariate logistic regression model was used to identify predictors of AF and linear regression models were performed to measure relationship between RA and LA area and AF. RESULTS: A total of 291 patients were included in the study. Multivariate analysis showed that age (p=0.0001), RA (p=0.025) and LA area (p=0.0016) were significantly related to AF. In patients with pure left-sided pathologies, there was progressive and predominant LA dilatation that paralleled the development of AF from none to paroxysmal to chronic AF. In patients with pure right-sided pathologies, there was a mirror image of progressive and predominant RA dilatation with the development of AF. CONCLUSION: We observed a mirror image atrial dilatation in patients with right sided disease and AF. This may provide novel mechanistic insight as to the origin of AF in these patients and deserves further studying in the form of targeted electrophysiological studies.

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This paper presents a new type of very fine grid hydrological model based on the spatiotemporal repartition of a PMP (Probable Maximum Precipitation) and on the topography. The goal is to estimate the influence of this rain on a PMF (Probable Maximum Flood) on a catchment area in Switzerland. The spatiotemporal distribution of the PMP was realized using six clouds modeled by the advection-diffusion equation. The equation shows the movement of the clouds over the terrain and also gives the evolution of the rain intensity in time. This hydrological modeling is followed by a hydraulic modeling of the surface and subterranean flow, done considering the factors that contribute to the hydrological cycle, such as the infiltration, the resurgence and the snowmelt. These added factors make the developed model closer to reality and also offer flexibility in the initial condition that is added to the factors concerning the PMP, such as the duration of the rain, the speed and direction of the wind. All these initial conditions taken together offer a complete image of the PMF.

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The purposes of this study were to characterize the performance of a 3-dimensional (3D) ordered-subset expectation maximization (OSEM) algorithm in the quantification of left ventricular (LV) function with (99m)Tc-labeled agent gated SPECT (G-SPECT), the QGS program, and a beating-heart phantom and to optimize the reconstruction parameters for clinical applications. METHODS: A G-SPECT image of a dynamic heart phantom simulating the beating left ventricle was acquired. The exact volumes of the phantom were known and were as follows: end-diastolic volume (EDV) of 112 mL, end-systolic volume (ESV) of 37 mL, and stroke volume (SV) of 75 mL; these volumes produced an LV ejection fraction (LVEF) of 67%. Tomographic reconstructions were obtained after 10-20 iterations (I) with 4, 8, and 16 subsets (S) at full width at half maximum (FWHM) gaussian postprocessing filter cutoff values of 8-15 mm. The QGS program was used for quantitative measurements. RESULTS: Measured values ranged from 72 to 92 mL for EDV, from 18 to 32 mL for ESV, and from 54 to 63 mL for SV, and the calculated LVEF ranged from 65% to 76%. Overall, the combination of 10 I, 8 S, and a cutoff filter value of 10 mm produced the most accurate results. The plot of the measures with respect to the expectation maximization-equivalent iterations (I x S product) revealed a bell-shaped curve for the LV volumes and a reverse distribution for the LVEF, with the best results in the intermediate range. In particular, FWHM cutoff values exceeding 10 mm affected the estimation of the LV volumes. CONCLUSION: The QGS program is able to correctly calculate the LVEF when used in association with an optimized 3D OSEM algorithm (8 S, 10 I, and FWHM of 10 mm) but underestimates the LV volumes. However, various combinations of technical parameters, including a limited range of I and S (80-160 expectation maximization-equivalent iterations) and low cutoff values (< or =10 mm) for the gaussian postprocessing filter, produced results with similar accuracies and without clinically relevant differences in the LV volumes and the estimated LVEF.

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Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

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The purpose of this work was to evaluate the ability of 80 MHz ultrasonography to differentiate intra-retinal layers and quantitatively assess photoreceptor dystrophy in small animal models. Four groups of 10 RCS rats each (five dystrophic and five controls) were explored at 25, 35, 45 and 55 days post-natal (PN). A series of retina cross-sections were obtained ex vivo from outside intact eyes using an 80 MHz three-dimensional ultrasound backscatter microscope (20-microm-axial resolution). Ultrasound features of normal retina were correlated to those of corresponding histology and thickness measurements of photoreceptor segment and nuclear layers were performed on all groups. To show the ability of 80 MHz ultrasonography to distinguish the retinal degeneration in vivo, one RCS rat was explored at 25 and 55 days post-natal. Ultrasound image of normal retina displayed four distinct layers marked by reflections at neurites/nuclei interfaces and permitted to differentiate the photoreceptor segment and nuclear layers. The backscatter level from the retina was shown to be related to the size, density and organization of the intra-layer structure. Ultrasound thickness measurements highly correlated with histologic measurements. A thinning (p<0.05) of outer nuclear layer (ONL) was detected over time for controls and was thought to be assigned to retina maturation. Retinal degeneration started at PN35 and resulted in a more pronounced ONL thinning (p<0.05) over time. ONL degeneration was accompanied by segment layer thickening (p<0.05) at PN35 and thinning thereafter. These changes may indicate accumulation of outer segment debris at PN35 then progressive destruction. In vivo images of rat intra-retinal structure showed the ability of the method to distinguish the photoreceptor layer changes. Our results indicate that 80 MHz ultrasonography reveals intra-retinal layers and is sensitive to age and degenerative changes of photoreceptors. This technique has great potential to follow-up retinal dystrophy and therapeutic effects in vivo.

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Statistics occupies a prominent role in science and citizens' daily life. This article provides a state-of-the-art of the problems associated with statistics in science and in society, structured along the three paradigms defined by Bauer, Allum and Miller (2007). It explores in more detail medicine and public understanding of science on the one hand, and risks and surveys on the other. Statistics has received a good deal of attention; however, very often handled in terms of deficit - either of scientists or of citizens. Many tools have been proposed to improve statistical literacy, the image of and trust in statistics, but with little understanding of their roots, with little coordination among stakeholders and with few assessments of impacts. These deficiencies represent as many new and promising directions in which the PUS research agenda could be expanded.

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The Swiss National Science Foundation Professorships Programme is presented as a scientific programme that aims to promote outstanding young scholars to professorial positions. Academic excellence is presented as the main selection criterion. The emphasis put on the research portfolio and on the age of the candidates means that the beneficiaries of these professorships put forward an image of excellence that is more embedded in data-based sciences than in the humanities and social sciences, thus strengthening the domination of a sector scientific activity essentially occupied by men over the sector that has opened up more widely to women. This paper aims to deconstruct the criteria of academic excellence as they appear in this programme and to show that what seem quality criteria are in fact inspired by a specific androcentric model. These biases tend to undermine the gender equality aims of the programme.

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Over the last few years, most OECD countries have extended their activation policy to new groups of non-working people, including the long-term unemployed (LTU). However, it is widely known that employers tend to regard LTU people as potentially problematic persons. This is likely to constitute a major obstacle for long-term unemployed jobseekers. On the basis of a survey among employers in a Swiss canton (N = 722), this article aims to shed light on the perception employers have of the long-term unemployed and whether this may matter for their recruitment practices. It also asks what, from the employer point of view, may facilitate access to employment for an LTU person. A key finding is that large companies have a worse image of the long-term unemployed and are less likely to hire them. Furthermore, independent of company size, a test period or the recommendation of a trustworthy person is seen as the factors most likely to facilitate access to jobs for LTU people.

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Assessment of image quality for digital x-ray mammography systems used in European screening programs relies mainly on contrast-detail CDMAM phantom scoring and requires the acquisition and analysis of many images in order to reduce variability in threshold detectability. Part II of this study proposes an alternative method based on the detectability index (d') calculated for a non-prewhitened model observer with an eye filter (NPWE). The detectability index was calculated from the normalized noise power spectrum and image contrast, both measured from an image of a 5 cm poly(methyl methacrylate) phantom containing a 0.2 mm thick aluminium square, and the pre-sampling modulation transfer function. This was performed as a function of air kerma at the detector for 11 different digital mammography systems. These calculated d' values were compared against threshold gold thickness (T) results measured with the CDMAM test object and against derived theoretical relationships. A simple relationship was found between T and d', as a function of detector air kerma; a linear relationship was found between d' and contrast-to-noise ratio. The values of threshold thickness used to specify acceptable performance in the European Guidelines for 0.10 and 0.25 mm diameter discs were equivalent to threshold calculated detectability indices of 1.05 and 6.30, respectively. The NPWE method is a validated alternative to CDMAM scoring for use in the image quality specification, quality control and optimization of digital x-ray systems for screening mammography.

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Altered bone micro-architecture is an important factor in accounting for fragility fractures. Until recently, it has not been possible to gain information about skeletal microstructure in a way that is clinically feasible. Bone biopsy is essentially a research tool. High-resolution peripheral Quantitative Computed Tomography, while non-invasive, is available only sparsely throughout the world. The trabecular bone score (TBS) is an imaging technology adapted directly from the Dual Energy X-Ray Absorptiometry (DXA) image of the lumbar spine. Thus, it is potentially readily and widely available. In recent years, a large number of studies have demonstrated that TBS is significantly associated with direct measurements of bone micro-architecture, predicts current and future fragility fractures in primary osteoporosis, and may be a useful adjunct to BMD for fracture detection and prediction. In this review, we summarize its potential utility in secondary causes of osteoporosis. In some situations, like glucocorticoid-induced osteoporosis and in diabetes mellitus, the TBS appears to out-perform DXA. It also has apparent value in numerous other disorders associated with diminished bone health, including primary hyperparathyroidism, androgen-deficiency, hormone-receptor positive breast cancer treatment, chronic kidney disease, hemochromatosis, and autoimmune disorders like rheumatoid arthritis. Further research is both needed and warranted to more clearly establish the role of TBS in these and other disorders that adversely affect bone.

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Recent research has shown that, in a University context, mastery goals are highly valued, and that students may endorse these goals either because they believe in their utility (i.e., social utility), in which case mastery goals are positively linked to achievement, or to create a positive image of themselves (i.e., social desirability), in which case mastery goals do not predict academic achievement. The present two experiments induced high vs. neutral levels of mastery goals' social utility and social desirability. Results confirmed that mastery goals predicted performance only when these goals were presented as socially useful but not socially desirable, especially among low achievers, those who need mastery goals the most to succeed.