Exploring the Trend: Motives behind Online Second-Hand Fashion Consumption

This paper examines the motives behind online second-hand consumption and gets to the bottom of the recent second-hand trend. Using a qualitative research approach based on in-depth interviews, four overarching categories are identified into which the consumption motives can be classified: Individualism, saving expenses, sustainability and solidarity. While individualism and saving expenses were most frequently mentioned in the interviews, sustainability and solidarity motives are rather secondary for online second-hand consumption. In addition to the four abovementioned, a further category was identified that specifically highlights arguments in favor of purchasing second-hand fashion online: Convenience. Consumers aim for the same shopping experience online that they are used to from stationary thrift shops. However, not only is this feeling transported into the digital world, but the value proposition is extended through search functions and learning algorithms. This makes clear how technology is influencing purchasing behavior and thus shaping a new consumer culture. Due to the power of second-hand fashion to represent one's own individuality and thus stand out from the crowd, it becomes visible that when buying online second-hand fashion, elements of conspicuous consumption also play a role

Whole-heart dynamic three-dimensional magnetic resonance perfusion imaging for the detection of coronary artery disease defined by fractional flow reserve: determination of volumetric myocardial ischaemic burden and coronary lesion location

Aims Dynamic three-dimensional-cardiac magnetic resonance (3D-CMR) perfusion proved highly diagnostic for the detection of angiographically defined coronary artery disease (CAD) and has been used to assess the efficacy of coronary stenting procedures. The present study aimed to relate significant coronary lesions as assessed by fractional flow reserve (FFR) to the volume of myocardial hypoenhancement on 3D-CMR adenosine stress perfusion imaging and to define the inter-study reproducibility of stress inducible 3D-CMR hypoperfusion. Methods and results A total of 120 patients with known or suspected CAD were examined in two CMR centres using 1.5 T systems. The protocol included cine imaging, 3D-CMR perfusion during adenosine infusion, and at rest followed by delayed enhancement (DE) imaging. Fractional flow reserve was recorded in epicardial coronary arteries and side branches with ≥2 mm luminal diameter and >40% severity stenosis (pathologic FFR < 0.75). Twenty-five patients underwent an identical repeat CMR examination for the determination of inter-study reproducibility of 3D-CMR perfusion deficits induced by adenosine. Three-dimensional CMR perfusion scans were visually classified as pathologic if one or more segments showed an inducible perfusion deficit in the absence of DE. Myocardial ischaemic burden (MIB) was measured by segmentation of the area of inducible hypoenhancement and normalized to left ventricular myocardial volume (MIB, %). Three-dimensional CMR perfusion resulted in a sensitivity, specificity, and diagnostic accuracy of 90, 82, and 87%, respectively. Substantial concordance was found for inter-study reproducibility [Lin's correlation coefficient: 0.98 (95% confidence interval: 0.96-0.99)]. Conclusion Three-dimensional CMR stress perfusion provided high diagnostic accuracy for the detection of functionally significant CAD. Myocardial ischaemic burden measurements were highly reproducible and allowed the assessment of CAD severit

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

Reconstruction of divergence-free velocity fields from cine 3D phase-contrast flow measurements

Three-dimensional phase-contrast velocity vector field mapping shows great potential for clinical applications; however measurement inaccuracies may limit the utility and robustness of the technique. While parts of the error in the measured velocity fields can be minimized by background phase estimation in static tissue and magnetic field monitoring, considerable inaccuracies remain. The present work introduces divergence-reduction processing of 3D phase-contrast flow data based on a synergistic combination of normalized convolution and divergence-free radial basis functions. It is demonstrated that this approach effectively addresses erroneous flow for image reconstructions from both fully sampled and undersampled data. Using computer simulations and in vivo data acquired in the aorta of healthy subjects and a stenotic valve patient it is shown that divergence arising from measurement imperfections can be reduced by up to 87% resulting in improved vector field representations. Based on the results obtained it is concluded that integration of the divergence-free condition into postprocessing of vector fields presents an efficient approach to addressing flow field inaccuracies