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986 results for “exchange”
Analysis of the DLR Knowledge Exchange Workshop Series on Software Engineering
<p>This repository is used to analyze the workshops of the DLR internal workshop series on software<br> engineering. These workshops are two-day events of the DLR software engineering community and<br> focus on different main topics every year.</p>
Finite element mesh of fusion energy heat exchange component: hybrid CAD/IBSim model including a graphite foam interlayer
<p>Image-Based Simulation (IBSim) mesh:<br> A finite element mesh of a conceptual design for a fusion energy heat exchange component (monoblock). The mesh is a hybrid from a computer aided design (CAD) drawing for the pipe and armour and IBSim for the interlayer. The IBSim interlayer is generated directly from a 3D volumetric image of a graphite foam block (KFoam). The 3D image was generated with an X-ray tomography scan performed by Dr Llion Evans with Manchester X-ray Imaging Facility equipment, which was funded in part by the EPSRC (grants EP/F007906/1, EP/F001452/1 and EP/I02249X/1). Conversion of the data to FE mesh was achieved using ScanIP, part of the Simpleware suite of programmes, version 7 (Synopsys Inc., Mountain View, CA, USA).</p> <p>The FE mesh data uses the EnSight Gold file format and may be visualised using Paraview (<a href="https://www.paraview.org">https://www.<strong>paraview</strong>.org</a>).</p> <p>The CT data used for the mesh is available as a separate dataset:</p> <p>This data was used originally for the following publications (please cite if re-using the data):<br> Ll.M. Evans, L. Margetts, P.D. Lee, C.A.M. Butler, E. Surrey, “Image based in silico characterisation of the effective thermal properties of a graphite foam”, Carbon, Vol. 143, pp. 542-558, 2018. <a href="https://doi.org/10.1016/j.carbon.2018.10.031">https://doi.org/10.1016/j.carbon.2018.10.031</a></p> <p>Ll.M. Evans, L. Margetts, P.D. Lee, C.A.M. Butler, E. Surrey, “Improving modelling of complex geometries in novel materials using 3D imaging”, Proceedings of NEA International Workshop on Structural Materials for Innovative Nuclear Systems, Manchester, UK, July 2016. <a href="https://www.oecd-nea.org/science/smins4/documents/P1-18_LlME_SMINS4_paper_reviewed.pdf">https://www.oecd-nea.org/science/smins4/documents/P1-18_LlME_SMINS4_paper_reviewed.pdf</a></p>
X-ray tomography (CT) image data of tungsten fusion energy heat exchange components
<p>X-ray tomography (CT) image data of tungsten fusion energy heat exchange components.</p> <p>The dataset includes images of four samples:</p> <ul> <li>CCFE_MB_ROI (Culham Centre for Fusion Energy thermal break concept monoblock, region of interest sample)</li> <li>IPP_Wf-Cu (Max-Planck-Institut für Plasmaphysik tungsten fibre / copper matrix coolant pipe)</li> <li>ITER_HHFT_ROI (ITER reference monoblock which has undergone high heat flux testing, region of interest sample)</li> <li>ITER_MB_ROI (ITER reference monoblock, region of interest sample)</li> </ul> <p>This data was used originally for the following publication (please cite if re-using the data) where further details on the data may be obtained:</p> <p>Ll.M. Evans, L. Margetts, P.D. Lee, C.A.M. Butler, E. Surrey, “Image based in silico characterisation of the effective thermal properties of a graphite foam”, Carbon, Vol. 143, pp. 542-558, 2018. <a href="https://doi.org/10.1016/j.carbon.2018.10.031">https://doi.org/10.1016/j.carbon.2018.10.031</a></p> <p>Each of the sample directories include reconstructed slices in Tiff format. To visualise the 3D volume use software such as ImageJ (https://imagej.net/Fiji/Downloads). CCFE_MB_ROI also includes raw radiographs; scan & reconstruction parameter settings file.</p> <p>A Neutron CT version of this data is available for comparison: <a href="https://doi.org/10.5281/zenodo.3533418">https://doi.org/10.5281/zenodo.3533418</a></p> <p>Image-based simulation (IBSim) meshes were generated directly from these datasets: <a href="https://doi.org/10.5281/zenodo.3533422">https://doi.org/10.5281/zenodo.3533422</a></p>
Neutron tomography (CT) image data of tungsten fusion energy heat exchange components
<p>Neutron tomography (CT) image data of tungsten fusion energy heat exchange components.</p> <p>The dataset includes three sets of images:</p> <ul> <li>ITER_171T-WA-0002_MB (ITER reference monoblock)</li> <li>CCFE_ThBr_MB (Culham Centre for Fusion Energy thermal break concept monoblock)</li> <li>ROIsamples_Stack (A stack of four region of interest samples*)</li> </ul> <p>The region of interest samples within the stack are as below:</p> <ul> <li>CCFE_ThBr_ROI (Culham Centre for Fusion Energy thermal break concept monoblock)</li> <li>IPP_Wf-Cu_p5_s1 (Max-Planck-Institut für Plasmaphysik tungsten fibre / copper matrix coolant pipe)</li> <li>ITER_HHFT_ROI (ITER reference monoblock which has undergone high heat flux testing)</li> <li>ITER_17IT-WA-0002_ROI (ITER reference monoblock)</li> </ul> <p>This data was used originally for the following publication (please cite if re-using the data) where further details on the data may be obtained:</p> <p>Ll.M. Evans, L. Margetts, P.D. Lee, C.A.M. Butler, E. Surrey, “Image based in silico characterisation of the effective thermal properties of a graphite foam”, Carbon, Vol. 143, pp. 542-558, 2018. <a href="https://doi.org/10.1016/j.carbon.2018.10.031">https://doi.org/10.1016/j.carbon.2018.10.031</a></p> <p>Each of the sample directories include reconstructed slices in Tiff format. To visualise the 3D volume use software such as ImageJ (https://imagej.net/Fiji/Downloads).</p> <p>CCFE_ThBr_ROI and ROIsamples_Stack include raw radiographs; dark and flat field images; scan & reconstruction parameter settings file.</p> <p>ITER_171T-WA-0002_MB includes data relating to the modulation transfer function (MTF) measurement.</p> <p>An X-Ray CT version of the ROI data is available for comparison: <a href="https://doi.org/10.5281/zenodo.3533420">https://doi.org/10.5281/zenodo.3533420</a></p> <p>Image-based simulation (IBSim) meshes were generated directly from these datasets: <a href="https://doi.org/10.5281/zenodo.3533422">https://doi.org/10.5281/zenodo.3533422</a></p>
Figure 2 in Heart rate response and bimodal gas eXchange in three developmental stages of the bullfrog Lithobates catesbeianus (Anura: Ranidae)
Figure 2. Representative data recording of electrocardiogram (A) and aerial ventilation (B) in a premetamorphic Lithobates catesbeianus at 25°C. In B the signals show a ventilatory event where the tadpole renewed the air in its lungs, resulting in a marked drop in PO2 and an increase in PCO2. Following the ventilatory event, the expired air was mixed with the remaining air within the closed respirometry system, resulting in a PO2 slightly lower, and a PCO2 slightly greater, than before ventilation.
Figure 1 in Heart rate response and bimodal gas eXchange in three developmental stages of the bullfrog Lithobates catesbeianus (Anura: Ranidae)
Figure 1. Scheme of non-invasive apparatus to measure gas exchange in water (A) and air (B), and heart rate (C).
Figure 4 in Heart rate response and bimodal gas eXchange in three developmental stages of the bullfrog Lithobates catesbeianus (Anura: Ranidae)
Figure 4. Mass-specific oxygen consumption (A) and carbon dioxide released (B) for aerial (red lines and points) and aquatic (blue lines and points) gas exchange during development of Lithobates catesbeianus.
Figure 5 in Heart rate response and bimodal gas eXchange in three developmental stages of the bullfrog Lithobates catesbeianus (Anura: Ranidae)
Figure 5. Relationship between Log whole-body oxygen consumption (A) and carbon dioxide release (B) (µmol h-1) in 10 air (filled symbols) and water (open symbols), and Log10 body mass (g) in larval (blue triangles), premetamorphic (orange squares) and metamorphic (green circles) stages of Lithobates catesbeianus. Each point represents a measurement from a single animal. The regression lines correspond to aerial (red) and aquatic (blue) gas exchange. Dotted lines represent no significant correlation.
Figure 1 in Gene Flow Patterns of the Aedes aegypti (Diptera: Culicidae) Mosquito in Colombia: a Continental Comparison Suggests Multiple Invasion Routes and Gene Exchange
Figure 1 Geographic location of the A. aegypti populations included in this study and gene-flow models evaluated. In both graphics, circles indicate the populations and arrows represent the gene flow between populations. A) Scale at American continent level (N = 2,996 specimens from six locations: Mexico – North America (M-NA), Venezuela (VZ), Peru (PE), Brazilian Amazon (BrAm), southeastern Brazil (SEBr), and Colombia (CO). B) Scale at South America level (N = 1,083 specimens from six locations: Venezuela, Peru, Brazilian Amazon (5 locations; Brazilian Amazon (BrAM), Manaus (MAO), Belém (BL). Boa Vista (BV), Rio Branco (RB), Porto Velho (PV)), Southeastern Brazil (SEBr) and Colombia (2 locations; Sucre (S), Quindio (Q)).
Figure 4. Phylogeny constructed through Bayesian inference estimated from the 35H in Gene Flow Patterns of the Aedes aegypti (Diptera: Culicidae) Mosquito in Colombia: a Continental Comparison Suggests Multiple Invasion Routes and Gene Exchange
Figure 4. Phylogeny constructed through Bayesian inference estimated from the 35H found of the ND4 gene for the A. aegypti populations in the American continent. The blue horizontal bars above the branches reflect the 95% CI for the branch supports. The color bars (blue, green, and red) on the tree terminals indicate which haplotypes are exclusive for a specific population. The dotted lines on the right side of the tree and numbers I or II indicate to what clade each of the terminals belong. H1-Col (Colombia (Sucre and Quindio), Venezuela, Peru, M-NA, Brasil (MA-O, RBPV, SEBr, BE-L)), H4 (Venezuela, M-NA, Brasil (MA-O, RBPV, BEL)), H3 (Venezuela, M-NA, Brazil (RBPV, SEBr, BE-L)), H2-Col (Colombia (Sucre), Venezuela, Peru, M-NA, Brazil (RBPV, SEBr, BE-L)), H13 (M-NA, Brazil (SEBr)), H8 (Venezuela, Brazil (SEBr)).
Figure 3 in Gene Flow Patterns of the Aedes aegypti (Diptera: Culicidae) Mosquito in Colombia: a Continental Comparison Suggests Multiple Invasion Routes and Gene Exchange
Figure 3. Representation of the gene-flow model with greater subsequent probability in the scenarios of the Americas and South America.A. Scale at American continent level (N = 2,996 specimens from six locations: Mexico–North America, Venezuela, Peru, Brazilian Amazon, southeastern Brazil, and Colombia. Within the continent context, the Stepping Stone 1 model shows through the green vectors the way the gene flow occurs among the different populations evaluated. B. Scale at South America level; the Full-migration model indicates migration among all the populations, hence, plotting of the potential migration routes through passive land transport (Pan-American highway) and riverine paths (principal rivers).
Figure 1 in Discovery of a Nearctic vicariant bumblebee (Hymenoptera: Apidae) in Eurasia uncovers secondary trans-Beringian exchanges of insect faunas
Figure 1. Distribution map of Bombus kirbiellus Curtis 1835. The red circles indicate new samples from Asia (this study; N = 3); the blue circles indicate published records from North America (GBIF Secretariat 2023; GBIF Occurrence Download: https://doi.org/10.15468/dl.ck3xk3; N = 185). Map: Mikhail Y. Gofarov.
Figure 2 in Discovery of a Nearctic vicariant bumblebee (Hymenoptera: Apidae) in Eurasia uncovers secondary trans-Beringian exchanges of insect faunas
Figure 2. Morphology of Bombus kirbiellus Curtis 1835 from north-eastern Asia (Chukotka Peninsula). (A) Lateral view of a female. (B) Hind view of a female. (C) Lateral view of a male. (D) Hind view of a male. (E) Male genitalia. Scale bars = 5 mm (A, B, C, D) and 2 mm (E). (Photos: Grigory S. Potapov).
Lab Study Dataset: Fast and Secure Contact Exchange in Groups
<p>This record contains the <strong>lab study dataset</strong> and <strong>evaluation R source code</strong> from the paper <em>"Sounds Good? Fast and Secure Contact Exchange in Groups"</em> by Florentin Putz, Steffen Haesler, and Matthias Hollick in Proceedings of the ACM on Human-Computer Interaction (CSCW '24).</p> <p> </p> <p><strong>Abstract:</strong></p> <p>Trustworthy digital communication requires the secure exchange of contact information, but current approaches lack usability and scalability for larger groups of users. We evaluate the usability of two secure contact exchange systems: the current state of the art, SafeSlinger, and our newly designed protocol, <em>PairSonic</em>, which extends trust from physical encounters to spontaneous online communication. Our lab study (N=45) demonstrates PairSonic's superior usability, automating the tedious verification tasks from previous approaches via an acoustic out-of-band channel. Although participants significantly preferred our system, minimizing user effort surprisingly decreased the perceived security for some users, who associated security with complexity. We discuss user perceptions of the different protocol components and identify remaining usability barriers for CSCW application scenarios.</p> <p> </p> <p><strong>Dataset:</strong></p> <p>Our pseudonymous dataset contains usability, security, and preference scores, completion times, reported usage of nine types of social and collaborative tools, and seven demographic and control variables, for each of our 45 participants.</p> <p> </p> <p><strong>Analysis source code:</strong></p> <p>Our R Markdown source code includes the full reproducible code of our analysis. This code generates all statistical figures from our paper. The code can also be used to reproduce our quantitative results and tables.</p> <p>Please refer to the README.md file and our paper for further details about the dataset and the lab study.</p> <p> </p> <p><strong>Acknowledgments:</strong></p> <p>This work has been funded by the LOEWE initiative (Hesse, Germany) within the emergenCITY center [LOEWE/1/12/519/03/05.001(0016)/72].</p>
Neural-network-based molecular dynamics simulations reveal that proton transport in water is doubly gated by sequential hydrogen-bond exchange: Neural network potentials training data
<h1>Neural network potentials of an excess proton in bulk water, training data</h1> <p>This dataset contains 2188 configurations labeled at two hybrid DFT levels (revPBE0-D3 and B3LYP-D3).</p> <p>The configurations are given as a single XYZ file: configurations.xyz</p> <p>The box dimensions are written in box.txt</p> <p>The energies for all configurations at a given level of theory are written in energies_LEVEL.txt (one configuration per line)</p> <p>The atomic forces for each configuration at a given level of theory are gathered in a XYZ file: forces_LEVEL.xyz</p> <p>The relative displacements of the Wannier centroids, with respect to the closest oxygen atom, for each configuration at a given level of theory, are in the following XYZ file: wannier-centroids-displacements_LEVEL.xyz</p>
Dataset to accompany publication "Photodeposition-Based Synthesis of TiO2@IrOx Core-Shell Catalyst for Proton-Exchange Membrane Water Electrolysis with Low Iridium Loading"
<h2>Dataset description</h2> <p>This dataset provides the raw data for the manuscript "Photodeposition-Based Synthesis of TiO<sub>2</sub>@IrO<sub>x</sub> Core-Shell Catalyst for Proton-Exchange Membrane Water Electrolysis with Low Iridium Loading"<strong> </strong>published in <em>Advanced Science </em>on 14 June 2024 (DOI: <a href="https://doi.org/10.1002/advs.202402991">https://doi.org/10.1002/advs.202402991</a>).</p> <p>The data consists of:</p> <ol> <li>XRD pattern of TiO<sub>2</sub>@IrO<sub>x</sub> (40 wt% Ir) as shown in Fig. 3e.</li> <li>XPS spectra of 3 samples: <strong>2.1</strong> TiO<sub>2</sub>@IrO<sub>x</sub> (40 wt% Ir) as shown in Fig. 3f.; <strong>2.2 </strong>TiO<sub>2</sub>@IrO<sub>x</sub> (only shell) as shown in Fig. 3g; <strong>2.3</strong> TiO<sub>2</sub>@IrO<sub>x</sub> (photodeposited seeds) as shown in Fig. S8.</li> <li>Datasets for NanoCT of the TiO<sub>2</sub>@IrO<sub>x</sub> catalyst layer as shown in Fig. 5 a-c : <strong>3.1</strong> HRES Tilt series; <strong>3.2 </strong>reconstructed slices.</li> </ol> <h2>Abstract</h2> <p>The widespread application of green hydrogen production technologies requires cost reduction of crucial elements. To achieve this, a viable pathway to reduce the iridium loading in proton exchange membrane water electrolysis (PEMWE) is explored. Herein, we present a scalable synthesis method based on a photodeposition process for a TiO<sub>2</sub>@IrO<sub>x</sub> core-shell catalyst with a reduced iridium content as low as 40 wt%. Using this synthesis route, we obtain titania support particles homogeneously coated with a thin iridium oxide shell of only 2.1 ± 0.4 nm. The catalyst exhibits not only high ex situ activity, but also decent stability compared to commercially available catalysts. Furthermore, the unique core-shell structure provides a threefold increased electrical powder conductivity compared to structures without the shell. In addition, the low iridium content facilitates the fabrication of sufficiently thick catalyst layers at decreased iridium loadings mitigating the impact of crack formation in the catalyst layer during PEMWE operation. We demonstrate that the novel TiO<sub>2</sub>@IrO<sub>x</sub> core-shell catalyst clearly outperforms the commercial reference in single-cell tests with an iridium loading below 0.3 mg<sub>Ir</sub> cm<sup>‑2 </sup>exhibiting a superior iridium-specific power density of 17.9 kW g<sub>Ir</sub><sup>-1 </sup>compared to 10.4 kW g<sub>Ir</sub><sup>-1 </sup>for the commercial reference.</p>
Confined dipole and exchange spin waves in a bulk chiral magnet with Dzyaloshinskii-Moriya interaction-Data files
<p>Raw data associated to the manuscript ‘Confined dipole and exchange spin waves in a bulk chiral magnet with Dzyaloshinskii-Moriya interaction.” File formats are described in info.txt files in the concerning folders. For plotting and data evaluation Matlab 2019b and OriginPro 2018b were used. </p> <p>We acknowledge financial support from the Swiss National Science Foundation (SNSF) via Grant No. 171003 Sinergia project Nanoskyrmionics, the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Grant No. TRR80 (From Electronic Correlations to Functionality, Project No. 107745057, and Projects No. E1 and No. F7), SPP2137 (Skyrmionics, Project No. 403191981, Grant No. PF393/19), and the excellence cluster MCQST under Germany’s Excellence Strategy EXC-2111 (Project No. 390814868). Financial support by the European Research Council (ERC) through Advanced Grants No. 291079 (TOPFIT) and No. 788031 (ExQuiSid) is gratefully acknowledged.</p> <p>Paper abstract:</p> <p>The Dzyaloshinskii-Moriya interaction (DMI) has an impact on excited spin waves in the chiral magnet Cu<sub>2</sub>OSeO<sub>3</sub> by means of introducing asymmetry in their dispersion relations. The confined eigenmodes of a chiral magnet are hence no longer the conventional standing spin waves. Here we report a combined experimental and micromagnetic modeling study by broadband microwave spectroscopy, and we observe confined spin waves up to eleventh order in bulk Cu<sub>2</sub>OSeO<sub>3</sub> in the field-polarized state. In micromagnetic simulations we find similarly rich spectra. They indicate the simultaneous excitation of both dipole- and exchange-dominated spin waves with wavelengths down to (47.2 ± 0.05) nm attributed to the exchange interaction modulation. Our results suggest the DMI to be effective in creating exchange spin waves in a bulk sample without the challenging nanofabrication and thereby in exploring their scattering with noncollinear spin textures.</p>
Dataset for "Inter-annual variability of summer net ecosystem CO2 exchange in High Arctic tundra" by Braybrook et al.
<p>A dataset with 30 min net ecosystem carbon dioxide exchange measurements (NEE) with and without gap-filling, derived component fluxes, gross primary productivity (GPP) and ecosystem respiration (R<sub>eco</sub>) and ancillary weather variables used to investigate how summer NEE, GPP and R<sub>eco</sub> varied over five years (2008, 2009, 2010, 2012, and 2014) at the Cape Bounty Arctic Watershed Observatory (CBAWO) (74.92˚N, 109.58˚W). The eddy covariance technique was used to measure NEE and a combined light and temperature response model was used to partition NEE into GPP and R<sub>eco</sub>. Further measurement and data processing details are described in the research paper, "Inter-annual variability of summer net ecosystem CO<sub>2</sub> exchange in High Arctic tundra", JGR Biogeosciences, 2021.</p>
The importance of turbulent ocean-sea ice nutrient exchanges for simulation of ice algal biomass and production with CICE6.1 and Icepack 1.2 - paper figures
<p>This file contains the figures to the paper "The importance of turbulent ocean-sea ice nutrient exchanges for simulation of ice algal biomass and production with CICE6.1 and Icepack 1.2 - model simulations", including the supplementary ones, in jpg format at 300 dpi.</p>
Data for: Analysis of Conformational Exchange Processes using Methyl-TROSY-Based Hahn Echo Measurements of Quadruple-Quantum Relaxation
<p>Raw experimental data used in associated publication. A full list of experiments is provided in the README.md file.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.