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127 results for “Setup”
IOW ESM minimal complete setup
<p>This a minimal setup for the IOW ESM (compatable to version 1.04.00).</p> <p>The coupled run is performed for 9 days (1959-01-01 to 1959-10-01) in chunks of 3 days. The atmospheric model is CCLM (version 5.00) with 0.22° horizontal resolution for the Eurocordex domain. The oceanic model for the Baltic Sea is the MOM5 model with 3nm horizontal resolution acompanied by the ERGOM ecosystem model. The forcing for CCLM is generated from the ERA5 reanalysis data.</p> <p>The setup is constructed for the HLRN supercomputer and has to be adapted for other target machines. See the related documentation at https://sven-karsten.github.io/iow_esm/intro.html.</p>
UFPTI 2105-BR05: Improving Breast Radiotherapy Setup and Delivery Using Mixed-Reality Visualization
ClinicalTrials.gov study NCT05178927. IPD Sharing: NO. Countries: 1. Publications: 1.
Dataset from UNIBO for the deliverables 7.1 and 7.2, and SydILUC model setup, calibration and validation
<p>STAR-ProBio_ILUCLiteratureReview_v1.0 _Spreadsheet: Inventory of existing key drivers and parameters for ILUC quantification and future strategies to reduce ILUC risks, and collection of standardisation work related to the sustainability of biofuels and biomaterials.</p> <p>STAR-ProBio_ModelParameters_v13.0 _Spreadsheet: Inventory of parameters and relationships used in the SydILUC model, with related metadata, i.e. source (literature), units, suggested update period, etc... </p> <p>STAR-ProBio_CalibrationGlobalFAOSTAT_v3.0_Spreadsheet: SydILUC model historical dataset of Maize market and production data to feed, calibrate, validate and run the model</p> <p>STAR-ProBio_MaizeNationalFAOSTAT_v1.0 _Spreadsheet: SydILUC model historical dataset of Maize market and production data to feed, calibrate, validate and run the model – for the regional version of the model</p> <p>STAR-ProBio_BioplasticProductionSydILUC_v1.0 _Spreadsheet: Collection of all the yields for different bioplastics from different sources (sugar, starch, oil) – from the documents by “Biopolymers facts and statistics” by IfBB</p>
Input files and setup for simulations of ancestral and modern glycosidases
<p>Input files, heme parameters, and representative structures from simulations of ancestral glycosidases and the modern glycosidase from the thermophilic <em>Halothermothrix orenii</em>. For details please see the README file provided.</p>
Dynamic Load Balancing for Predictions of Storm Surge and Coastal Flooding-Model setup and source code
<p>Source code and model setup/inputs for the paper titled "Dynamic Load Balancing for Predictions of Storm Surge and Coastal Flooding" article. Simulations were conducted using a modified version of ADCIRC+DLB (ADCIRC + Dynamic Load Balancing) on unstructured triangular meshes.</p> <p>Contains:</p> <ol> <li>Model input files. <ol> <li>ADCIRC model input files for the ideal channel setup and Hurricane Irene simulation (*.13, *.14, *.15)</li> </ol> </li> <li>Zipped archive of the ADCIRC code (adcirc-cg-DLB.zip) used to produce the simulations for the paper.</li> <li>Step-by-step compilation and usage instructions for ADCIRC+DLB. <ol> <li>Installation.html </li> <li>Usage.html</li> </ol> </li> </ol>
Development and evaluation of a test setup to investigate distance differences in immersive virtual environments
<p>Nowadays, with recent advances in virtual reality technology, it is easily possible to integrate real objects into<br> virtual environments by creating an exact virtual replication and enabling interaction with them by mapping the obtained tracking<br> data of the real to the virtual objects. The primary goal of our study is to develop a system to investigate distance differences for<br> near-field interaction in immersive virtual environments. In this context, the term distance difference refers to the shift between<br> a real object and the respective replication of the real object in the virtual environment of the same size. This could occur<br> for a number of reasons e.g. due to errors in motion tracking or mistakes in designing the virtual environment. Our virtual<br> environment is developed using the Unity3D game engine, while the immersive contents were displayed on an HTC Vive Pro headmounted display. The virtual room shown to the user includes a replication of the real testing lab environment, while one of<br> the two real objects is tracked and mirrored to the virtual world using an HTC Vive Tracker. Both objects are present<br> in the real as well as in the virtual world. To find perceivable distance differences in the near-field, the actual task in the<br> subjective test was to pick up one object and place it into another object. The position of the static object in the virtual<br> world is shifted by values between 0 and 4 cm, while the position of the real object is kept constant. The system is evaluated by<br> conducting a subjective proof-of-concept test with 18 test subjects. The distance difference is evaluated by the subjects through<br> estimating perceived confusion on a modified 5-point absolute category rating scale. The study provides quantitative insights<br> into allowable real-world vs. virtual-world mismatch boundaries for near-field interactions, with a threshold value of around 1 cm.</p>
setup
<p>setup</p>
Laboratory and Clinical Measurements - Influence of anode/filtration setup on X-ray multimeter energy response in mammography applications
<p>The data contains measurement results for selected types of X-ray multimeters in mammography applications. In the Laboratory conditions absolute and relative response were determined for available software settings of the tested multimeters. In the clinical mammography units the multimeters' response was evaluated in different anode/filtration setups.</p>
MITgcm model setup and output for "What determines the shape of the Pine-Island-like ice shelf?"
<p><strong>(Contents)</strong><br> Here it contains<br> <br> jim_run3 = CTRL (Similar to Jordan et al., 2018 but with smaller ocean)</p> <p>melt/run/ = IOCTRL, M(all)V(dyn)U(dyn)</p> <p>melt2/ = M( changing, see below ) V( dyn ) U( 0 )<br> melt2/run/ = M(all)V(dyn)U(0)<br> melt2/run2/ = M(20)V(dyn)U(0)<br> melt2/run3/ = M(GL10)V(dyn)U(0)<br> melt2/run4/ = M(GL20)V(dyn)U(0)</p> <p><br> melt3/ = M ( changing, see below ) V( changing ) U( 0 )<br> melt3/run5/ = M(all)V(2000)U(0)<br> melt3/run10/ = M(20)V(2000)U(0)</p> <p>%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%<br> Input melt data for running ice only experiments<br> #data.streamice#<br> meltCTRL.bin = M(all) ... melt rate data of CTRL for every time steps <br> meltCTRL2.bin = M(GL10)<br> meltCTRL3.bin = M(20 m/a)<br> meltCTRL4.bin = M(GL20)</p> <p>Input velocity data for running ice only experiments <br> melt3/<br> uvel_ext4.bin = U(0 m/a)<br> vvel_ext5.bin = V(2000 m/a)</p> <p><strong>(How to compile and run)</strong><br> mkdir build<br> cd build/<br> module load intel/2021.2.0<br> module load impi/2021.2.0<br> export LANG=en_US.UTF-8<br> export LC_ALL=en_US.utf8<br> ../../../tools/genmake2 -of ../../../tools/build_options/linux_amd64_ifort+mpi_ice_nas_tokyo3 -mpi -mods ../code/<br> make depend<br> export LANG=en_US.UTF-8<br> export LC_ALL=en_US.utf8<br> make -j 16</p> <p> mkdir ../run<br> cd ../run/<br> cp ../build/mitgcmuv .<br> cp ../input/* .<br> pjsub job*.pbs<br> <br> <strong>Other important links</strong><br> https://github.com/hgu784/MITgcm_67s<br> <br> For more info please send an email to Yoshihiro.Nakayama@lowtem.hokudai.ac.jp</p>
LAPD June 2021 Setup
<p>(a) Schematic of the experiment. The graphite target is located at x = −12 cm (origin is the axial center). The LIF probe beam</p> <p>is directed anti-parallel to the x-axis (blow-off axis). The PIMAX2 camera images along the y direction. The LIF probe beam is expanded</p> <p>along the z-axis (co-ordinates as indicated in the bottom-right of panel (a)). (b) Illustration of the imaged region of the laser plasma during</p> <p>the expansion (as indicated by the black rectangle). Panels (c) and (e) show a comparison between experimental and simulated emission from</p> <p>the entire debris cloud, including all C+4 self-emission lines as well as other species at 440 ns after laser ablation. Panels (d) and (f) show</p> <p>background-subtracted fluorescence maps for C+4 ions moving at 64 km/s (speed dictated by LIF beam wavelength). The simulated data (f)</p> <p>has been cut abruptly at the edge of the beam width (°æ2.5 cm in z).</p>
MIROC4-ACTM: Model setup, input and output data for CH4 LETKF (Bisht et al., GMD-D, 2022)
<p>Details in :</p> <p>Bisht, J. S. H., Patra, P. K., Takigawa, M., Sekiya, T., Kanaya, Y., Saitoh, N., and Miyazaki, K.: Estimation of CH<sub>4</sub> emission based on advanced 4D-LETKF assimilation system, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2022-719, 2022.</p>
Formation of c-C6H5CN ice using the SPACE TIGER experimental setup
<p>Benzonitrile (c-C6H5CN) has been recently detected in cold and dense regions of the interstellar medium (ISM), where it has been used as a signpost of a rich aromatic organic chemistry that might lead to the production of polycyclic aromatic hydrocarbons (PAHs).</p> <p>One possible origin of this benzonitrile is interstellar ice chemistry involving benzene (c-C6H6) and nitrile molecules (organic molecules containing the −C≡N group). We have addressed the plausibility of this c-C6H5CN formation pathway through laboratory experiments using the SPACE TIGER experimental setup.</p> <p>We have irradiated c-C6H6:CH3CN ice mixtures with 2 keV electrons (Experiments 3-5) and Ly-alpha photons (Experiment 6), and compared the results with those obtained after 2 keV electron irradiation of c-C6H6 (Experiment 1) and CH3CN (Experiment 2) ices. In addition, we have also irradiated H2O:c-C6H6:CH3CN (Experiments 7 and 8), and CO:c-C6H6:CH3CN (Experiments 9 and 10) ice mixtures with both, 2 keV electrons (Experiments 7 and 9) and Ly-alpha photons (Experiments 8 and 10). </p> <p>The results of these experiments are presented in</p> <table summary="Additional metadata"> <tbody> <tr> <td><a href="https://doi.org/10.48550/arXiv.2210.03827">https://doi.org/10.48550/arXiv.2210.03827</a></td> </tr> </tbody> </table>
Summary of problems and solutions from a brainstorming sessions with users having tested a basic mixed-presence setup with two wall-sized displays
<p>Summary of problems and solutions from a brainstorming session with participants having tested a basic mixed-presence setup with two wall-sized displays beforehand. The (excel) file includes descriptions, diagrams and scores used to rank the ideas.</p>
Dataset and scripts for "Multimode characterization of an optical beam deflection setup"
<p>The main files are the following :</p> <p><strong>Multimode_characterization_of_an_optical_beam_deflection_setup.pdf </strong>is the preprint of the article.</p> <p><strong>flexion_analysis.m</strong> is a Matlab script which analyses the amplitudes and frequencies of the contrasts corresponding to deflexion modes of the cantilever and stored in flexion_data.mat to compute the OBD spot position and size, and plot Figs. 3a, 3b, and 5b of the article.<br><strong>torsion_analysis.m</strong> is a Matlab script which analyses the amplitudes and frequencies of the contrasts corresponding to torsion modes of the cantilever and stored in flexion_data.mat to compute the OBD spot position and size, and plot Figs. 3c, 3d, and 5c of the article.<br><strong>ModeNumberStudy.m</strong> is a Matlab script which creates Fig. 4 of the article.</p> <p>All other matlab scripts and mat files are dependecies, their use is commented in the main scripts.</p> <p> </p>
NEMO/SAS-SI3 setup, forcing and output for SI3-BBM and SI3-default idealized "cyclone" simulations (Brodeau et al., 2024, final version)
<p>Model data and setup/forcing/configuration files for the "Cyclone" test-case experiments (Mehlmann et al.,2021) discussed and analyzed in the following paper:</p> <p>Implementation of a brittle sea-ice rheology in an Eulerian, finite-difference, C-grid modeling framework: <br>Impact on the simulated deformation of sea-ice in the Arctic</p> <p>by Laurent Brodeau, Pierre Rampal, Einar Ólason and Véronique Dansereau, in Geoscientific Model Development (GMD), 2024.</p>
Setup and Dataset for the Validation of an Eulerian-Lagrangian Coupling Method in the m-AIA framework
<p>This repository holds data files, code information and property files which are used to conduct performance analyses of a <br>Parallel Eulerian-Lagrangian Coupling Method. </p>
Setup and results data for the dissemination strategies
<p>Experiment setup and main results data considering the comparison of the different dissemination strategies</p>
Photogrammetry setup to record the stone surface - Application of Forensic Photogrammetry and 3D Modelling to Improve Epigraphic Reading: Study of the Roman Altar of Gravesano (Ticino, Switzerland)
<p>PDF document with lighting and camera setup to record the surface of the stone with multi-image photogrammetry.</p> <p>Page 1: Stone surface, images and camera positions</p> <p>Page 2: Setup of the raking light source</p> <p>Page 3: Adjustment of the angle of the light source to the stone surface. A slight upward angle relative to the horizon is chosen in the plane of the stone in order to keep an oblique incident light and project shadows in each character’s depression (see green long circular green arrow). The second angle is adjusted from the surface of the stone in order to define each character’s depression with sharp shadows.</p> <p>Page 4: Stone surface, images and camera positions with an the camera projection of the bottom right image outlined in red.</p>
Simulation output of the reference setup in "The comparative role of physical system processes in Hudson Strait ice stream cycling: a comprehensive model-based test of Heinrich event hypotheses"
<p>This supplementary material for "The comparative role of physical system processes in Hudson Strait ice stream cycling: a comprehensive model-based test of Heinrich event hypotheses" contains the simulation output of the 20 reference runs. Additional data is available upon request from the corresponding author.</p>
MITgcm model setup and output for "Antarctic Slope Current modulates ocean heat intrusions towards Totten Glacier"
<p>MITgcm model setup and output for "Antarctic Slope Current modulates ocean heat intrusions towards Totten Glacier</p> <p>Here, it contains the results of the East Antarctic simulation from 1992-2016. Model grid is lat-lon similar to LLC1080 grid resolution roughly 3-4 km in the region. See Nakayama et al., submitted to GRL for detail. </p> <p><strong>(Contents)</strong><br> code.zip (code to run this simulation)<br> input.zip (input file required for this simulation)<br> results_zenodo.zip (due to size limit of 50GB, please check <a href="https://ecco.jpl.nasa.gov/drive/files/ECCO2/LatLon_East_Antartic">https://ecco.jpl.nasa.gov/drive/files/ECCO2/LatLon_East_Antarctic</a> for complete model output. Complete datasets can also be obtained by rerunning the simulation.)</p> <p><strong>(How to build and run)</strong><br> mkdir build<br> ./../../tools/genmake2 -of ../../../tools/build_options/linux_amd64_ifort+mpi_ice_nas -mpi -mods ../code/<br> make depend<br> make -j 16<br> cd ..<br> mkdir test<br> cd test<br> ln -sf ../input/* .<br> ln -sf /nobackup/hzhang1/forcing/era_xx/ .<br> cp ../build/mitgcm_uv .<br> qsub run_omp_high_t1.pbs</p>
ScienceDex guides
Understand access before you commit
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.