Wind tunnel turning vanes of modern design

Rehabilitation of the Altitude Wind Tunnel includes the need for new corner turning vanes to match its upgraded performance. The design and experimental performance results from a 0.1-full scale model of the highest speed corner (M = 0.35) are presented and discussed along with some two dimensional inviscid analyses of two vaned corners. With a vane designed by an inverse two dimensional technique, the overall corner loss was about 12% of the inlet dynamic pressure of which about 4% was caused by vane skin friction. Comparable values with a conventionally designed circular arc vane were about 14% overall with about 7% due to skin friction

Design and performance of a fixed, nonaccelerating, guide vane cascade that operates over an inlet flow angle range of 60 deg

A unique set of wind tunnel guide vanes are designed with an inverse design code and analyzed with a panel method and an integral boundary layer code developed at the NASA Lewis Research Center. The fixed guide vanes, 80 feet long with 6-foot chord length, were designed for the NASA Ames 40 x 80/80 x 120 ft Wind Tunnel. Low subsonic flow is accepted over a 60 deg range of inlet angle from either the 40 x 80 leg or the 80 x 120 leg of the wind tunnel, and directed axially into the main leg of the tunnel where drive fans are located. Experimental tests of 1/10-scale models were conducted to verify design calculations

Ames 40 X 80/80 X 120 Foot Wind Tunnel: Turning Vanes Design

A number of different turning vanes are designed for the NASA Ames wind tunnel. Computer codes are used to design and analyze the turning vanes to insure that they comply with their individual constraints. The presentation is given in viewgraph format and displays pressure coefficients for the different turning vanes as well as loss coefficients versus inlet flow angles

Finding Strong Gravitational Lenses in the Kilo Degree Survey with Convolutional Neural Networks

The volume of data that will be produced by new-generation surveys requires automatic classification methods to select and analyze sources. Indeed, this is the case for the search for strong gravitational lenses, where the population of the detectable lensed sources is only a very small fraction of the full source population. We apply for the first time a morphological classification method based on a Convolutional Neural Network (CNN) for recognizing strong gravitational lenses in $255$ square degrees of the Kilo Degree Survey (KiDS), one of the current-generation optical wide surveys. The CNN is currently optimized to recognize lenses with Einstein radii $\gtrsim 1.4$ arcsec, about twice the $r$-band seeing in KiDS. In a sample of $21789$ colour-magnitude selected Luminous Red Galaxies (LRG), of which three are known lenses, the CNN retrieves 761 strong-lens candidates and correctly classifies two out of three of the known lenses. The misclassified lens has an Einstein radius below the range on which the algorithm is trained. We down-select the most reliable 56 candidates by a joint visual inspection. This final sample is presented and discussed. A conservative estimate based on our results shows that with our proposed method it should be possible to find $\sim100$ massive LRG-galaxy lenses at z\lsim 0.4 in KiDS when completed. In the most optimistic scenario this number can grow considerably (to maximally $\sim$2400 lenses), when widening the colour-magnitude selection and training the CNN to recognize smaller image-separation lens systems.Comment: 24 pages, 17 figures. Published in MNRA

Searching for galaxy clusters in the Kilo-Degree Survey

In this paper, we present the tools used to search for galaxy clusters in the Kilo Degree Survey (KiDS), and our first results. The cluster detection is based on an implementation of the optimal filtering technique that enables us to identify clusters as over-densities in the distribution of galaxies using their positions on the sky, magnitudes, and photometric redshifts. The contamination and completeness of the cluster catalog are derived using mock catalogs based on the data themselves. The optimal signal to noise threshold for the cluster detection is obtained by randomizing the galaxy positions and selecting the value that produces a contamination of less than 20%. Starting from a subset of clusters detected with high significance at low redshifts, we shift them to higher redshifts to estimate the completeness as a function of redshift: the average completeness is ~ 85%. An estimate of the mass of the clusters is derived using the richness as a proxy. We obtained 1858 candidate clusters with redshift 0 < z_c < 0.7 and mass 13.5 < log(M500/Msun) < 15 in an area of 114 sq. degrees (KiDS ESO-DR2). A comparison with publicly available Sloan Digital Sky Survey (SDSS)-based cluster catalogs shows that we match more than 50% of the clusters (77% in the case of the redMaPPer catalog). We also cross-matched our cluster catalog with the Abell clusters, and clusters found by XMM and in the Planck-SZ survey; however, only a small number of them lie inside the KiDS area currently available.Comment: 13 pages, 15 figures. Accepted for publication on Astronomy & Astrophysic

Recombinant Filaggrin Is Internalized and Processed to Correct Filaggrin Deficiency

This study was designed to engineer a functional filaggrin (FLG) monomer linked to a cell-penetrating peptide (RMR) and to test the ability of this peptide to penetrate epidermal tissue as a therapeutic strategy for genetically determined atopic dermatitis (AD). A single repeat of the murine filaggrin gene (Flg) was covalently linked to a RMR motif and cloned into a bacterial expression system for protein production. Purified FLG+RMR (mFLG+RMR) was applied in vitro to HEK-293T cells and a reconstructed human epidermis (RHE) tissue model. Immunochemistry demonstrated RMR-dependent cellular uptake of FLG+RMR in a dose- and time-dependent manner in HEK cells. Immunohistochemical staining of the RHE model identified penetration of FLG+RMR to the stratum granulosum, the epidermal layer at which FLG deficiency is thought to be pathologically relevant. In vivo application of FLG+RMR to FLG-deficient flaky tail (ft/ft) mice skin demonstrated internalization and processing of recombinant FLG+RMR to restore the normal phenotype. These results suggest that topically applied RMR-linked FLG monomers are able to penetrate epidermal tissue, be internalized into the appropriate cell type, and be processed to a size similar to wild-type functional barrier peptides to restore necessary barrier function, and prove to be therapeutic for patients with AD

Target and (Astro-)WISE technologies - Data federations and its applications

After its first implementation in 2003 the Astro-WISE technology has been rolled out in several European countries and is used for the production of the KiDS survey data. In the multi-disciplinary Target initiative this technology, nicknamed WISE technology, has been further applied to a large number of projects. Here, we highlight the data handling of other astronomical applications, such as VLT-MUSE and LOFAR, together with some non-astronomical applications such as the medical projects Lifelines and GLIMPS, the MONK handwritten text recognition system, and business applications, by amongst others, the Target Holding. We describe some of the most important lessons learned and describe the application of the data-centric WISE type of approach to the Science Ground Segment of the Euclid satellite.Comment: 9 pages, 5 figures, Proceedngs IAU Symposium No 325 Astroinformatics 201

Evaluating the effects of climate change on US agricultural systems: sensitivity to regional impact and trade expansion scenarios

Agriculture is one of the sectors that is expected to be most significantly impacted by climate change. There has been considerable interest in assessing these impacts and many recent studies investigating agricultural impacts for individual countries and regions using an array of models. However, the great majority of existing studies explore impacts on a country or region of interest without explicitly accounting for impacts on the rest of the world. This approach can bias the results of impact assessments for agriculture given the importance of global trade in this sector. Due to potential impacts on relative competitiveness, international trade, global supply, and prices, the net impacts of climate change on the agricultural sector in each region depend not only on productivity impacts within that region, but on how climate change impacts agricultural productivity throughout the world. In this study, we apply a global model of agriculture and forestry to evaluate climate change impacts on US agriculture with and without accounting for climate change impacts in the rest of the world. In addition, we examine scenarios where trade is expanded to explore the implications for regional allocation of production, trade volumes, and prices. To our knowledge, this is one of the only attempts to explicitly quantify the relative importance of accounting for global climate change when conducting regional assessments of climate change impacts. The results of our analyses reveal substantial differences in estimated impacts on the US agricultural sector when accounting for global impacts vs. US-only impacts, particularly for commodities where the United States has a smaller share of global production. In addition, we find that freer trade can play an important role in helping to buffer regional productivity shocks