Large eddy simulation of a low-pressure turbine cascade with turbulent end wall boundary layers

We present results of implicit large eddy simulation (LES) and different Reynolds-averaged Navier-Stokes (RANS) models of the MTU 161 low pressure turbine at an exit Reynolds number of 90,000 and exit Mach number of 0.6. The LES results are based on a high order discontinuous Galerkin method and the RANS is computed using a classical finite-volume approach. The paper discusses the steps taken to create realistic inflow boundary conditions in terms of end wall boundary layer thickness and free stream turbulence intensity. This is achieved by tailoring the input distribution of total pressure and temperature, Reynolds stresses and turbulent length scale to a Fourier series based synthetic turbulence generator. With this procedure, excellent agreement with the experiment can be achieved in terms of blade loading at midspan and wake total pressure losses at midspan and over the channel height. Based on the validated setup, we focus on the discussion of secondary flow structures emerging due to the interaction of the incoming boundary layer and the turbine blade and compare the LES to two commonly used RANS models. Since we are able to create consistent setups for both LES and RANS, all discrepancies can be directly attributed to physical modelling problems. We show that both a linear eddy viscosity model and a differential Reynolds stress model coupled with a state-of-the-art correlation-based transition model fail, in this case, to predict the separation induced transition process around midspan. Moreover, their prediction of secondary flow losses leaves room for improvement as shown by a detailed discussion turbulence kinetic energy and anisotropy fields.Comment: invited submission to Flow, Turbulence and Combustion Special Issue: 13th ERCOFTAC Workshop on Direct and Large Eddy Simulation - DLES1

Structural and magnetic properties of Co-V nanoparticles

We have investigated the structural and magnetic properties of Co1-xVx nanoparticles (NPs) with composition x = 0.25 (stoichiometric) and 0.29 (under-stoichiometric) prepared by the cluster-beam deposition (CBD) technique. Our data shows that the as-made Co1-xVx NPs are a mixture of the high-temperature phase (HTP) and the low-temperature phase (LTP) of Co3V and the particles are superparamagnetic at room temperature (RT) with blocking temperatures (TB) of 90 and 137 K for x = 0.25 and 0.29, respectively. This behavior contrasts with the bulk which are paramagnetic down to 4.2 K. When the Co75V25 NPs are annealed at 573 K, they undergo a phase separation into a mixture of phases and become ferromagnetic at room temperature with Curie temperature (Tc) of 515 K

Revealing Individual Neuroanatomical Heterogeneity in Alzheimer Disease Using Neuroanatomical Normative Modeling

BACKGROUND AND OBJECTIVES: Alzheimer's Disease (AD) is highly heterogeneous, with marked individual differences in clinical presentation and neurobiology. To explore this, we employed neuroanatomical normative modelling to index regional patterns of variability in cortical thickness. We aimed to characterise individual differences and outliers in cortical thickness in patients with AD, people with mild cognitive impairment (MCI) and controls. Furthermore, we assessed the relationships between cortical thickness heterogeneity and cognitive function, amyloid-beta, phosphor-tau, ApoE genotype. Finally, we examined whether cortical thickness heterogeneity was predictive of conversion from MCI to AD. METHODS: Cortical thickness measurements across 148 brain regions were obtained from T1-weighted MRI scans from 62 sites of the Alzheimer's Disease Neuroimaging Initiative. AD was determined by clinical and neuropsychological examination with no comorbidities present. MCI participants had reported memory complaints, and controls were cognitively normal. A neuroanatomical normative model indexed cortical thickness distributions using a separate healthy reference dataset (n= 33,072), employing hierarchical Bayesian regression to predict cortical thickness per region using age and sex, whilst adjusting for site noise. Z-scores per region were calculated, resulting in a z-score 'brain map' per participant. Regions with z-scores <-1.96 were classified as outliers. RESULTS: Patients with AD (n=206) had a median of 12 outlier regions (out of a possible 148), with the highest proportion of outliers (47%) in the parahippocampal gyrus. For 62 regions, over 90% of these patients had cortical thicknesses within the normal range. Patients with AD had more outlier regions than people with MCI (n=662) or controls (n=159) [F(2, 1022) = 95.39), P = 2.0×10-16]. They were also more dissimilar to each other than people with MCI or controls [F(2, 1024) = 209.42, P = 2.2×10-16]. A greater number of outlier regions was associated with worse cognitive function, CSF protein concentrations and an increased risk of converting from MCI to AD within three years (HR = 1.028, 95% CI[1.016,1.039], P =1.8×10-16). DISCUSSION: Individualised normative maps of cortical thickness highlight the heterogeneous impact of AD on the brain. Regional outlier estimates have the potential to be a marker of disease and could be used to track an individual's disease progression or treatment response in clinical trials

Tag suggestr: Automatic photo tag expansion using visual information for photo sharing websites

In this paper, we propose an automatic photo tag expansion system for the community photo collections, such as Flickr. Our aim is to suggest relevant tags for a target photograph uploaded to the system by a user, by incorporating the visual and textual cues from other related photographs. As the first step, the system requires the user to add only a few initial tags for each uploaded photo. These initial tags are used to retrieve related photos including the same tags in their tag lists. Then the set of candidate tags collected from a large pool of photos is weighted according to the similarity of the target photo to the retrieved photo including the tag. Finally, the tags in the highest rankings are used to automatically expand the tags of the target photo. The experimental results on Flickr photos show that, the use of visual similarity of semantically relevant photos to recommend tags improves the quality of suggested tags compared to only text-based systems. © 2008 Springer Berlin Heidelberg

Europe’s Farm to Fork Strategy and Its Commitment to Biotechnology and Organic Farming: Conflicting or Complementary Goals?

The European Commission's Farm to Fork (F2F) strategy, under the European Green Deal, acknowledges that innovative techniques, including biotechnology, may play a role in increasing sustainability. At the same time, organic farming will be promoted, and at least 25% of the EU's agricultural land shall be under organic farming by 2030. How can both biotechnology and organic farming be developed and promoted simultaneously to contribute to achieving the Sustainable Development Goals (SDGs)? We illustrate that achieving the SDGs benefits from the inclusion of recent innovations in biotechnology in organic farming. This requires a change in the law. Otherwise, the planned increase of organic production in the F2F strategy may result in less sustainable, not more sustainable, food systems

Towards good practice guidelines for the contour method of residual stress measurement

Accurate measurement of residual stress in metallic components using the contour method relies on the achievement of a good quality cut, on the appropriate measurement of the deformed cut surface and on the robust analysis of the measured data. There is currently no published standard or code of practice for the contour method. As a first step towards such a standard, this study draws on research investigations addressing the three main steps in the method: how best to cut the specimens; how to measure the deformation contour of the cut surface; and how to analyse the data. Good practice guidance is provided throughout the text accompanied by more detailed observations and advice tabulated in Appendi

Perceived economic self‑sufficiency: a countryand generation‑comparative approach

We thank Michael Camasso and Radha Jagannathan as well as Asimina Christoforou, Gerbert Kraaykamp, Fay Makantasi, Tiziana Nazio, Kyriakos Pierrakakis, Jacqueline O’Reilly and Jan van Deth for their contribution to the CUPESSE project (Seventh Framework Programme; Grant Agreement No. 61325). CUPESSE received additional funding from the Mannheim Centre for European Social Research (MZES) and the Field of Focus 4 “Self-Regulation and Regulation: Individuals and Organisations” at Heidelberg University. We further acknowledge helpful comments on this article by two anonymous reviewers. Julian Rossello provided valuable research assistance.Electronic supplementary material The online version of this article (https ://doi.org/10.1057/ s4130 4-018-0186-3) contains supplementary material, which is available to authorized users.Existing datasets provided by statistical agencies (e.g. Eurostat) show that the economic and financial crisis that unfolded in 2008 significantly impacted the lives and livelihoods of young people across Europe. Taking these official statistics as a starting point, the collaborative research project “Cultural Pathways to Economic Self-Sufficiency and Entrepreneurship in Europe” (CUPESSE) generated new survey data on the economic and social situation of young Europeans (18–35 years). The CUPESSE dataset allows for country-comparative assessments of young people’s perceptions about their socio-economic situation. Furthermore, the dataset includes a variety of indicators examining the socio-economic situation of both young adults and their parents. In this data article, we introduce the CUPESSE dataset to political and social scientists in an attempt to spark a debate on the measurements, patterns and mechanisms of intergenerational transmission of economic self-sufficiency as well as its political implications.CUPESSE project (Seventh Framework Programme; Grant Agreement No. 61325

Accuracy of TrUE-Net in comparison to established white matter hyperintensity segmentation methods: An independent validation study

White matter hyperintensities (WMH) are nearly ubiquitous in the aging brain, and their topography and overall burden are associated with cognitive decline. Given their numerosity, accurate methods to automatically segment WMH are needed. Recent developments, including the availability of challenge data sets and improved deep learning algorithms, have led to a new promising deep-learning based automated segmentation model called TrUE-Net, which has yet to undergo rigorous independent validation. Here, we compare TrUE-Net to six established automated WMH segmentation tools, including a semi-manual method. We evaluated the techniques at both global and regional level to compare their ability to detect the established relationship between WMH burden and age. We found that TrUE-Net was highly reliable at identifying WMH regions with low false positive rates, when compared to semi-manual segmentation as the reference standard. TrUE-Net performed similarly or favorably when compared to the other automated techniques. Moreover, TrUE-Net was able to detect relationships between WMH and age to a similar degree as the reference standard semi-manual segmentation at both the global and regional level. These results support the use of TrUE-Net for identifying WMH at the global or regional level, including in large, combined datasets

Detecting the translocation of DNA through a nanopore using graphene nanoribbons

Solid-state nanopores can act as single-molecule sensors and could potentially be used to rapidly sequence DNA molecules. However, nanopores are typically fabricated in insulating membranes that are as thick as 15 bases, which makes it difficult for the devices to read individual bases. Graphene is only 0.335 nm thick (equivalent to the spacing between two bases in a DNA chain) and could therefore provide a suitable membrane for sequencing applications. Here, we show that a solid-state nanopore can be integrated with a graphene nanoribbon transistor to create a sensor for DNA translocation. As DNA molecules move through the pore, the device can simultaneously measure drops in ionic current and changes in local voltage in the transistor, which can both be used to detect the molecules. We examine the correlation between these two signals and use the ionic current measurements as a real-time control of the graphene-based sensing device

Accelerated swell testing of artificial sulfate bearing lime stabilised cohesive soils

This paper reports on the physico-chemical response of two lime stabilised sulfate bearing artificial soils subject to the European Accelerated Volumetric Swell Test (EN13286-49). At various intervals during the test, a specimen was removed and subject to compositional and microstructural analysis. Ettringite was formed by both soils types, but with significant differences in crystal morphology. Ettringite crystals formed from kaolin based soils were very small, colloidal in size and tended to form on the surface of other particles. Conversely, those formed from montmorillonite were relatively large and typically formed away from the surface in the pore solution. It was concluded that the mechanism by which ettringite forms is determined by the hydroxide ion concentration in the pore solution and the fundamental structure of the bulk clay. In the kaolin soil, ettringite forms by a topochemical mechanism and expands by crystal swelling. In the montmorillonite soil, it forms by a through-solution mechanism and crystal growth