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924 results for “TIPS”
Thresholds and Tipping Points in a Sarracenia Microecosystem at Harvard Forest 2012-2013
The primary goal of this project is to determine experimentally the amount of lead time required to prevent a state change. To achieve this goal, we will (1) experimentally induce state changes in a natural aquatic ecosystem - the Sarracenia microecosystem; (2) use proteomic analysis to identify potential indicators of states and state changes; and (3) test whether we can forestall state changes by experimentally intervening in the system. This work uses state-of-the art molecular tools to identify early warning indicators in the field of aerobic to anaerobic state changes driven by nutrient enrichment in an aquatic ecosystem. The study tests two general hypotheses: (1) proteomic biomarkers can function as reliable indicators of impending state changes and may give early warning before increasing variances and statistical flickering of monitored variables; and (2) well-timed intervention based on proteomic biomarkers can avert future state changes in ecological systems.
Correlated order at the tipping point in the kagome metal CsV3Sb5
<p>Data deposite for the manuscript entitled "Correlated order at the tipping point in the kagome metal CsV3Sb5". The manuscript will soon appear online. </p>
Dataset supporting the paper "Superconducting Scanning Tunneling Microscope Tip to Reveal Sub-millielectronvolt Magnetic Energy Variations on Surfaces. J. Phys. Chem Lett. 12, 2983 (2021)"
<p>Dataset corresponding to theoretical calculations in the supporting information of the paper "Superconducting Scanning Tunneling Microscope Tip to Reveal Sub-millielectronvolt Magnetic Energy Variations on Surfaces" J. Phys. Chem Lett. 12, 2983 (2021), <a href="https://doi.org/10.1021/acs.jpclett.1c00328">https://doi.org/10.1021/acs.jpclett.1c00328</a></p> <p>List of files:</p> <p>Several folders corresponding to the figures of the supporting information. They contain:</p> <ul> <li>.siesta files: STM images in WsXM format (http://www.wsxm.eu/) simulated using STMpw (<a href="https://doi.org/10.5281/zenodo.3581159">https://doi.org/10.5281/zenodo.3581159</a>).</li> <li>CONTCAR files: relaxed structures in VASP format. They can be visualized with VESTA (<a href="https://jp-minerals.org/vesta/en/">https://jp-minerals.org/vesta/en/</a>).</li> <li>.agr files: grace files (<a href="https://plasma-gate.weizmann.ac.il/Grace/">https://plasma-gate.weizmann.ac.il/Grace/</a>).</li> </ul>
Ensemble of ice shelf basal melt rates and ocean properties for tipped-over continental shelves
<p><strong>Summary</strong><strong>:</strong></p> <p>This dataset contains the reference and tipped states from several model configurations developed at the <a href="https://www.awi.de/en/">Alfred Wegener Institute (AWI)</a> and the <a href="https://www.ige-grenoble.fr/?lang=en">Institut des Géosciences de l’Environnement (IGE)</a>. They were gathered here in the context of the <a href="https://www.tipaccs.eu">TiPACCs European project</a> and constitute a useful ensemble of reference and tipped ocean–ice-shelf simulations that <strong>can be used to feed ice-sheet simulations or to train melt parameterizations</strong>.</p> <p>The simulations produced by AWI are based on the <a href="https://fesom.de">FESOM</a> global ocean–sea-ice model using either Z- or Sigma- coordinates and all show a cold-to-warm tipping point for Filchner-Ronne Ice Shelf. The two sets of simulations produced by IGE are based on the <a href="https://www.nemo-ocean.eu">NEMO</a> ocean–sea-ice model. They include a global configuration showing a cold-to-warm tipping point for Ross Ice Shelf, and regional Amundsen Sea configuration showing a warm-to-warmer transition (likely not a proper tipping point). </p> <p>The files include 3-dimensional and sea-floor ocean temperatures and salinities, ice-shelf melt rates, as well as topographic and grid data. All variables are interpolated onto the common 8km stereographic grid that was used to provide ocean forcing in ISMIP6 (<a href="https://doi.org/10.5194/tc-14-2331-2020">Nowicki et al. 2020</a>).</p> <p>We provide the reference state and the anomaly, so that the tipped state is:</p> <ul> <li><em>Tipped = Reference + Anomaly</em></li> </ul> <p>To have an overview of the reference and tipped states, have a look at these figures:</p> <ul> <li><em>figure_ref_and_anomalies_1.pdf</em></li> <li> <p><em>figure_ref_and_anomalies_2.pdf</em></p> </li> <li> <p><em>figure_seafloor_temp_zooms.pdf</em></p> </li> </ul> <p> </p> <p>_______________________________________________</p> <p><strong>Detailed Data Description</strong><strong>:</strong></p> <p> </p> <ul> <li><strong>reference_high_FESOM_sigma_AWI_TiPACCs.nc</strong> <ul> <li>contact: Ralph Timmermann <a href="mailto:ralph.timmermann@awi.de">ralph.timmermann@awi.de</a>, Verena Haid <a href="mailto:verena.haid@awi.de">verena.haid@awi.de</a></li> <li>model: FESOM1.4, sigma-coordinates (global with refined grid around Antarctica)</li> <li>atmospheric forcing: HadCM3 20C</li> <li>provided average: 1990-1999 (10-year mean)</li> <li>more: <a href="https://doi.org/10.1007/s10236-013-0642-0">Timmermann and Hellmer (2013)</a></li> </ul> </li> </ul> <p> </p> <ul> <li><strong>reference_low_FESOM_sigma_AWI_TiPACCs.nc</strong> <ul> <li>contact: Ralph Timmermann <a href="mailto:ralph.timmermann@awi.de">ralph.timmermann@awi.de</a>, Verena Haid <a href="mailto:verena.haid@awi.de">verena.haid@awi.de</a></li> <li>model: FESOM1.4, sigma-coordinates (global with refined grid around Antarctica)</li> <li>atmospheric forcing: HadCM3 20C</li> <li>provided average: 1990-1999 (10-year mean)</li> <li>more: <a href="https://doi.org/10.5194/os-13-765-2017">Timmermann and Goeller (2017)</a></li> </ul> </li> </ul> <p> </p> <ul> <li><strong>reference_FESOM_z_AWI_TiPACCs.nc</strong> <ul> <li>contact: Verena Haid <a href="mailto:verena.haid@awi.de">verena.haid@awi.de</a></li> <li>model: FESOM1.4, Z-coordinates (global with refined grid around Antarctica)</li> <li>atmospheric forcing: ERA Interim</li> <li>provided average: 2008-2017 (10-year mean), i.e. model year 30-39</li> <li>more: same mesh as <a href="https://doi.org/10.5194/tc-13-2317-2019">Gürses et al. (2019)</a></li> </ul> </li> </ul> <p> </p> <ul> <li><strong>reference_NEMO4_eORCA025.L121_IGE_TiPACCs.nc</strong> <ul> <li>contact: Pierre Mathiot <a href="mailto:pierre.mathiot@univ-grenoble-alpes.fr">pierre.mathiot@univ-grenoble-alpes.fr</a></li> <li>model: NEMO-4.0, eORCA025.L121 (Global, 1/4°, 121 vertical levels)</li> <li>atmospheric forcing: JRA55do</li> <li>provided average: 2<sup>nd</sup> cycle of 1989-1998 (10-year mean); we first run 1979-2018, and we redo 1979-1998 starting from the 2018 state.</li> <li>more: <a href="https://pmathiot.github.io/NEMOCFG/docs/build/html/simu_eORCA025_OPM021.html">https://pmathiot.github.io/NEMOCFG/docs/build/html/simu_eORCA025_OPM021.html</a></li> </ul> </li> </ul> <p> </p> <ul> <li><strong>reference_NEMO3_AMUXL12.L75_IGE_TiPACCs.nc</strong> <ul> <li>contact: Nicolas Jourdain <a href="mailto:nicolas.jourdain@univ-grenoble-alpes.fr">nicolas.jourdain@univ-grenoble-alpes.fr</a></li> <li>model: NEMO-3.6, AMUXL12.L75 (Amundsen, 1/12°, 75 vertical levels)</li> <li>atmospheric forcing: MAR (<a href="https://doi.org/10.5194/tc-14-229-2020">Donat-Magnin et al. 2020</a>)</li> <li>provided average: 1989-2009 (21-year mean)</li> <li>more: similar model set-up as <a href="https://doi.org/10.1016/j.ocemod.2018.11.001">Jourdain et al. (2019)</a>.</li> </ul> </li> </ul> <p> </p> <ul> <li><strong>anomaly_high_FESOM_sigma_AWI_TiPACCs.nc</strong> <ul> <li>continuation of reference_high_FESOM_sigma_AWI_TiPACCs.nc</li> <li>forced with HadCM3 A1B</li> <li>provided average: 2190-2199 (10-year mean)</li> </ul> </li> </ul> <p> </p> <ul> <li><strong>anomaly_low_FESOM_sigma_AWI_TiPACCs.nc</strong> <ul> <li>continuation of reference_low_FESOM_sigma_AWI_TiPACCs.nc</li> <li>forced with HadCM3 A1B</li> <li>provided average: 2190-2199 (10-year mean)</li> </ul> </li> </ul> <p> </p> <ul> <li><strong>anomaly_high_FESOM_z_AWI_TiPACCs.nc</strong> <ul> <li>same model set-up as reference_FESOM_z_AWI_TiPACCs.nc</li> <li>atmospheric forcing south of 60°S HadCM3 A1B starting 2050, otherwise ERA Interim starting 1979</li> <li>provided average: model year 69-78 (10-year mean), i.e. 2008-2017 of 2<sup>nd</sup> 39yr-cycle</li> </ul> </li> </ul> <p> </p> <ul> <li><strong>anomaly_medium_FESOM_z_AWI_TiPACCs.nc</strong> <ul> <li>same model set-up as reference_FESOM_z_AWI_TiPACCs.nc</li> <li>atmospheric forcing: ERA Interim modified with a strong imprint of the seasonal cycle of HadCM3 A1B 2070-2089</li> <li>provided average: model year 69-78 (10-year mean), i.e. 2008-2017 of 2<sup>nd</sup> 39yr-cycle</li> </ul> </li> </ul> <p> </p> <ul> <li><strong>anomaly_low_FESOM_z_AWI_TiPACCs.nc</strong> <ul> <li>same model set-up as reference_FESOM_z_AWI_TiPACCs.nc</li> <li>atmospheric forcing: manipulated ERA Interim with prolongued summer and shorter, milder winter south of 50°S, additional modification of winds in Weddell Sea region</li> <li>provided average: model year 108-117 (10-year mean), i.e. 2008-2017 of 3<sup>rd</sup> 39yr-cycle</li> </ul> </li> </ul> <p> </p> <ul> <li><strong>anomaly_NEMO4_eORCA025.L121_IGE_TiPACCs.nc</strong> <ul> <li>similar to reference_NEMO4_eORCA025.L121_IGE_TiPACCs.nc</li> <li>perturbation of the model parameters: Different iceberg distribution and different sea-ice–ocean drag and snow conductivity on sea-ice, leading to less sea-ice production in the eastern Ross Sea.</li> <li>More: <a href="https://pmathiot.github.io/NEMOCFG/docs/build/html/simu_eORCA025_OPM020.html">https://pmathiot.github.io/NEMOCFG/docs/build/html/simu_eORCA025_OPM020.html</a></li> </ul> </li> </ul> <p> </p> <ul> <li><strong>anomaly_NEMO3_AMUXL12.L75_IGE_TiPACCs.nc</strong> <ul> <li>similar to reference_NEMO3_AMUXL12.L75_IGE_TiPACCs.nc</li> <li>perturbation of atmospheric forcing: MAR forced by the CMIP5 multi-model anomaly under the RCP8.5 scenario (<a href="https://doi.org/10.5194/tc-15-571-2021">Donat-Magnin et al. 2021</a>).</li> <li>provided average: 2080-2100 (21-year average)</li> </ul> </li> </ul> <p> </p>
A 3-D model of The Bear Trap: A unique stone structure on the northwest tip of the Nuussuaq Peninsula, Greenland
<p>This dataset consists of five files. The .obj, .jpg., and .mtl files can be used to view a high-resolution 3D mesh model of ‘The Bear Trap’, a unique Norse ruin at the western end of the Nuussuaq Peninsula in NW Greenland (also called ‘Bjørnefælden’ in Danish, and ‘Putdlagssuaq’ or ‘The Great Trap’ Greenlandic Kalaallisut). The .laz file contains the dense cloud. The .avi shows a flyover video of the 3D model. The 3D model was created from 1686 photographs that were processed using Structure from Motion Multiview Stereo photogrammetry software (in this case Agisoft Metashape Pro v1.7; Linux Ubuntu). A 24.3 megapixel Sony a5100 APS-C mirrorless camera fitted with a 24 mm lens was used to acquire ground-level imagery of the structure. The image alignment or bundle adjustment was performed using ‘High’ accuracy, a key point limit of 60000 and no tie point limit. The sparse point cloud was scaled using three markers with known dimensions that were placed in the area of interest, and which remained stationary throughout the entire photo survey. The dense point cloud was computed using the ‘High’ setting. The dense point cloud was then used to compute the mesh model using the ‘High’ setting. Instructions are provided in the readme file that accompanies this dataset. </p> <p>The image survey of the Bear Trap was conducted as part of the Vaigat Iceberg-Microbial Oil Degradation and Archaeological Heritage Investigation (VIMOA) project, which was funded by the Danish Centre for Marine Research and supported by the Arctic Research Centre at Aarhus University, the National Museum of Denmark, the Greenland Institute of Natural Resources, and The Greenland National Museum and Archives in Nuuk. Permits for the survey were obtained in advance from the Greenland National Museum and Archives in Nuuk. Walsh et al. (2020) provides an overview of the archaeological surveys conducted during the VIMOA project and Walsh et al. (submitted) provides further details specific to The Bear Trap and surrounding archaeological contexts. </p> <p>Walsh et al. (2020) The VIMOA project and archaeological heritage in the Nuussuaq Peninsula of north-west Greenland. <em>Antiquity</em> 94:e6 doi:10.15184/aqy.2019.230</p> <p>Walsh, Matthew J., Daniel F. Carlson, Pelle Tejsner, and Steffen Thomsen. The Bear Trap: Reinvestigating a unique stone structure on the northwest tip of the Nuussuaq Peninsula, Greenland. Manuscript submitted to <em>Arctic Anthropology</em></p>
Self-excited Contact Resonance Operation of a Tactile Piezoresistive Cantilever Microprobe with Diamond Tip (Data)
<p>Raw data and figures used for the article "Self-excited Contact Resonance Operation of a Tactile Piezoresistive Cantilever Microprobe with Diamond Tip", published in the proceedings of Sensor and Measurement Science International 2021; 2021-05-03 - 2021-05-06; digital.</p>
Dataset for "A robust tip-less positioning device for near-field investigations: Press and Roll Scan (PROscan)"
<p>The dataset contains the data relevant for the publication "A robust tip-less positioning device for near-field investigations: Press and Roll Scan (PROscan)". The data has been acquired using optical measurement techniques as described in detail in the publication https://arxiv.org/abs/2203.05527. The data is structured according to Figures presented in the publication.</p> <p>The authors acknowledge financial support by the Max Planck Society and by the QuantERA project RouTe through the Federal Ministry of Education and Research (BMBF) (13N14839). This project has also received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska Curie Grant Agreement No. 101025918.</p>
Global forest cover loss tipping points leading to changing hydrologic responses
<p>This dataset describes the methods used to develop the results for study entitled: Global forest cover loss tipping points leading to changing hydrologic responses.</p> <p>EVENTS_List_45.docx is a table describing each deforestation event used for the study</p> <p>MATLAB Script 1: Plotting Hydrologic Sensitive Area against Tree cover loss every 10 % tree cover loss for all 45 events and adjusting Richard's curve function to obtain the parameters. This script uses EXCEL SHEET: HSiaresults.xlsx</p> <p>MATLAB Script 2: Computing the critical points of acceleration based on the Richards curve parameters. This script uses the parameters or results obtained in Script one.</p> <p>MATLAB Script 3: Plotting the climate and water yield direction against tree cover loss. This script used EXCEL SHEET: direction.xlsx</p>
Single-crystalline Al tips
<p>This repository contains all input data for simulating the field-evaporation process of specifically<br> oriented single-crystalline APT tips with representing f.c.c. aluminium using TAPSim.</p> <p>Having conducted all simulations, it contains all detector hit information for all ions and each tip.</p> <p>The authors have also personally stored the trajectories of all ions for each tip. However,<br> given the size of these particular additional binary data (approx. 100 - 200GB), they have<br> --- as a compromise --- not yet been uploaded. They are available from the authors for free upon request.</p> <p><br> The individual components of the dataset are as follows, where the * is a placeholder/wildcard.</p> <p>*SX_DetectorHits.zip<br> The simulation results here specifically all detector hit maps for each tip and the input files for tapsim</p> <p>*.cif<br> The Crystallography Open Database file used to define the unit cell</p> <p>*MeshgenInput.tar.gz<br> The compressed txt-based inputfiles for MESHGEN with which the inputfiles for TAPSim<br> for each tip were generated.</p> <p>*TapsimInput.tar.gz<br> the compressed binary inputfiles for TAPSim which specify at which locations<br> the atoms and mesh supporting points are located</p> <p>*BaseAndTip.zip<br> The compressed PNG-renditions of where the tip ions and the base plate supporting points are located.<br> The potential Moire effects apparent in the images are likely related to us reducing the rendering resolution.</p> <p>*Everything.zip<br> The compressed PNG-renditions of where the tip ions, the base plate supporting points, and mesh points are located.</p> <p>*Meta.mat and *PRNG.txt<br> The MATLAB workspace variables which hold the orientation of each tip as a rotation matrix and<br> the seed of the random number generator. The rotation matrix is of active sense premultiplying<br> point position vectors from the VESTA output into their actual locations from which subsequently the tip was carved.<br> A few tip orientations did not run, this was solved by rotating them by an additional 0.5 deg random rotor<br> in space about the projected orientation, the corresponding individual rotation matrices are stored in individual *.mat files<br> with the corresponding tip ID in the filename each</p> <p>*.vesta<br> The Vesta inputfile with which sufficiently sized lattice point clouds were<br> written out to subsequently rotate them and carve into a tip.</p> <p>*DetectorHits.tar.gz<br> The compressed raw data in the default TAPSim format encoding where each<br> ion hit the detector surplus additional pieces of information.</p> <p>*.pl<br> Perl scripts with which to extract runtime profile information from the TAPSim command line output</p> <p>*.sh<br> Shell scripts used to execute the batch queue. Two scripts were used.<br> The first, "run_queue_tapsim_job.sh" $1 $2 fires off independent sequential TAPSIM simulations on existent data<br> The second "run_single_tapsim_job.sh" is called by the first script to fire this of.</p> <p>tapsim_r3225.zip<br> The source code used to execute the simulations</p> <p>The *.tar.gz files in the *.zip archives can be unpacked with the unpack_dataset.sh shell script specifically<br> unpack_dataset.sh $1 $2 with the first argument $1 the start ID and the second argument $2 being the tip end ID to unpack.<br> Modification of the script might be necessary if file name of *.tar.gz archive has been changed...<br> Single *.tar.gz files in general can be most conveniently extracted with a Unix/Linux operating system via for instance the command:<br> tar -xvf nameofthefile.tar.gz<br> On Windows WinRAR can be used for decompression</p>
Single-crystalline Mg tips
<p>This repository contains all input data for simulating the field-evaporation process of specifically<br> oriented single-crystalline APT tips with representing h.c.p. magnesium using TAPSim.</p> <p>Having conducted all simulations, it contains all detector hit information for all ions and each tip.</p> <p>The authors have also personally stored the trajectories of all ions for each tip. However,<br> given the size of these particular additional binary data (approx. 100 - 200GB), they have<br> --- as a compromise --- not yet been uploaded. They are available from the authors for free upon request.</p> <p><br> The individual components of the dataset are as follows, where the * is a placeholder/wildcard.</p> <p>*SX_DetectorHits.zip<br> The simulation results here specifically all detector hit maps for each tip and the input files for tapsim</p> <p>*.cif<br> The Crystallography Open Database file used to define the unit cell</p> <p>*MeshgenInput.tar.gz<br> The compressed txt-based inputfiles for MESHGEN with which the inputfiles for TAPSim<br> for each tip were generated.</p> <p>*TapsimInput.tar.gz<br> the compressed binary inputfiles for TAPSim which specify at which locations<br> the atoms and mesh supporting points are located</p> <p>*BaseAndTip.zip<br> The compressed PNG-renditions of where the tip ions and the base plate supporting points are located.<br> The potential Moire effects apparent in the images are likely related to us reducing the rendering resolution.</p> <p>*Everything.zip<br> The compressed PNG-renditions of where the tip ions, the base plate supporting points, and mesh points are located.</p> <p>*Meta.mat and *PRNG.txt<br> The MATLAB workspace variables which hold the orientation of each tip as a rotation matrix and<br> the seed of the random number generator. The rotation matrix is of active sense premultiplying<br> point position vectors from the VESTA output into their actual locations from which subsequently the tip was carved.<br> A few tip orientations did not run, this was solved by rotating them by an additional 0.5 deg random rotor<br> in space about the projected orientation, the corresponding individual rotation matrices are stored in individual *.mat files<br> with the corresponding tip ID in the filename each</p> <p>*.vesta<br> The Vesta inputfile with which sufficiently sized lattice point clouds were<br> written out to subsequently rotate them and carve into a tip.</p> <p>*DetectorHits.tar.gz<br> The compressed raw data in the default TAPSim format encoding where each<br> ion hit the detector surplus additional pieces of information.</p> <p>*.pl<br> Perl scripts with which to extract runtime profile information from the TAPSim command line output</p> <p>*.sh<br> Shell scripts used to execute the batch queue. Two scripts were used.<br> The first, "run_queue_tapsim_job.sh" $1 $2 fires off independent sequential TAPSIM simulations on existent data<br> The second "run_single_tapsim_job.sh" is called by the first script to fire this of.</p> <p>tapsim_r3225.zip<br> The source code used to execute the simulations</p> <p>The *.tar.gz files in the *.zip archives can be unpacked with the unpack_dataset.sh shell script specifically<br> unpack_dataset.sh $1 $2 with the first argument $1 the start ID and the second argument $2 being the tip end ID to unpack.<br> Modification of the script might be necessary if file name of *.tar.gz archive has been changed...<br> Single *.tar.gz files in general can be most conveniently extracted with a Unix/Linux operating system via for instance the command:<br> tar -xvf nameofthefile.tar.gz<br> On Windows WinRAR can be used for decompression</p>
Single-crystalline W tips
<p>This repository contains all input data for simulating the field-evaporation process of specifically<br> oriented single-crystalline APT tips with representing b.c.c. tungsten using TAPSim.</p> <p>Having conducted all simulations, it contains all detector hit information for all ions and each tip.</p> <p>The authors have also personally stored the trajectories of all ions for each tip. However,<br> given the size of these particular additional binary data (approx. 100 - 200GB), they have<br> --- as a compromise --- not yet been uploaded. They are available from the authors for free upon request.</p> <p><br> The individual components of the dataset are as follows, where the * is a placeholder/wildcard.</p> <p>*SX_DetectorHits.zip<br> The simulation results here specifically all detector hit maps for each tip and the input files for tapsim</p> <p>*.cif<br> The Crystallography Open Database file used to define the unit cell</p> <p>*MeshgenInput.tar.gz<br> The compressed txt-based inputfiles for MESHGEN with which the inputfiles for TAPSim<br> for each tip were generated.</p> <p>*TapsimInput.tar.gz<br> the compressed binary inputfiles for TAPSim which specify at which locations<br> the atoms and mesh supporting points are located</p> <p>*BaseAndTip.zip<br> The compressed PNG-renditions of where the tip ions and the base plate supporting points are located.<br> The potential Moire effects apparent in the images are likely related to us reducing the rendering resolution.</p> <p>*Everything.zip<br> The compressed PNG-renditions of where the tip ions, the base plate supporting points, and mesh points are located.</p> <p>*Meta.mat and *PRNG.txt<br> The MATLAB workspace variables which hold the orientation of each tip as a rotation matrix and<br> the seed of the random number generator. The rotation matrix is of active sense premultiplying<br> point position vectors from the VESTA output into their actual locations from which subsequently the tip was carved.<br> A few tip orientations did not run, this was solved by rotating them by an additional 0.5 deg random rotor<br> in space about the projected orientation, the corresponding individual rotation matrices are stored in individual *.mat files<br> with the corresponding tip ID in the filename each</p> <p>*.vesta<br> The Vesta inputfile with which sufficiently sized lattice point clouds were<br> written out to subsequently rotate them and carve into a tip.</p> <p>*DetectorHits.tar.gz<br> The compressed raw data in the default TAPSim format encoding where each<br> ion hit the detector surplus additional pieces of information.</p> <p>*.pl<br> Perl scripts with which to extract runtime profile information from the TAPSim command line output</p> <p>*.sh<br> Shell scripts used to execute the batch queue. Two scripts were used.<br> The first, "run_queue_tapsim_job.sh" $1 $2 fires off independent sequential TAPSIM simulations on existent data<br> The second "run_single_tapsim_job.sh" is called by the first script to fire this of.</p> <p>tapsim_r3225.zip<br> The source code used to execute the simulations</p> <p>The *.tar.gz files in the *.zip archives can be unpacked with the unpack_dataset.sh shell script specifically<br> unpack_dataset.sh $1 $2 with the first argument $1 the start ID and the second argument $2 being the tip end ID to unpack.<br> Modification of the script might be necessary if file name of *.tar.gz archive has been changed...<br> Single *.tar.gz files in general can be most conveniently extracted with a Unix/Linux operating system via for instance the command:<br> tar -xvf nameofthefile.tar.gz<br> On Windows WinRAR can be used for decompression</p>
Single-crystalline Zr tips
<p>This repository contains all input data for simulating the field-evaporation process of specifically<br> oriented single-crystalline APT tips with representing h.c.p. zirconium using TAPSim.</p> <p>Having conducted all simulations, it contains all detector hit information for all ions and each tip.</p> <p>The authors have also personally stored the trajectories of all ions for each tip. However,<br> given the size of these particular additional binary data (approx. 100 - 200GB), they have<br> --- as a compromise --- not yet been uploaded. They are available from the authors for free upon request.</p> <p><br> The individual components of the dataset are as follows, where the * is a placeholder/wildcard.</p> <p>*SX_DetectorHits.zip<br> The simulation results here specifically all detector hit maps for each tip and the input files for tapsim</p> <p>*.cif<br> The Crystallography Open Database file used to define the unit cell</p> <p>*MeshgenInput.tar.gz<br> The compressed txt-based inputfiles for MESHGEN with which the inputfiles for TAPSim<br> for each tip were generated.</p> <p>*TapsimInput.tar.gz<br> the compressed binary inputfiles for TAPSim which specify at which locations<br> the atoms and mesh supporting points are located</p> <p>*BaseAndTip.zip<br> The compressed PNG-renditions of where the tip ions and the base plate supporting points are located.<br> The potential Moire effects apparent in the images are likely related to us reducing the rendering resolution.</p> <p>*Everything.zip<br> The compressed PNG-renditions of where the tip ions, the base plate supporting points, and mesh points are located.</p> <p>*Meta.mat and *PRNG.txt<br> The MATLAB workspace variables which hold the orientation of each tip as a rotation matrix and<br> the seed of the random number generator. The rotation matrix is of active sense premultiplying<br> point position vectors from the VESTA output into their actual locations from which subsequently the tip was carved.<br> A few tip orientations did not run, this was solved by rotating them by an additional 0.5 deg random rotor<br> in space about the projected orientation, the corresponding individual rotation matrices are stored in individual *.mat files<br> with the corresponding tip ID in the filename each</p> <p>*.vesta<br> The Vesta inputfile with which sufficiently sized lattice point clouds were<br> written out to subsequently rotate them and carve into a tip.</p> <p>*DetectorHits.tar.gz<br> The compressed raw data in the default TAPSim format encoding where each<br> ion hit the detector surplus additional pieces of information.</p> <p>*.pl<br> Perl scripts with which to extract runtime profile information from the TAPSim command line output</p> <p>*.sh<br> Shell scripts used to execute the batch queue. Two scripts were used.<br> The first, "run_queue_tapsim_job.sh" $1 $2 fires off independent sequential TAPSIM simulations on existent data<br> The second "run_single_tapsim_job.sh" is called by the first script to fire this of.</p> <p>tapsim_r3225.zip<br> The source code used to execute the simulations</p> <p>The *.tar.gz files in the *.zip archives can be unpacked with the unpack_dataset.sh shell script specifically<br> unpack_dataset.sh $1 $2 with the first argument $1 the start ID and the second argument $2 being the tip end ID to unpack.<br> Modification of the script might be necessary if file name of *.tar.gz archive has been changed...<br> Single *.tar.gz files in general can be most conveniently extracted with a Unix/Linux operating system via for instance the command:<br> tar -xvf nameofthefile.tar.gz<br> On Windows WinRAR can be used for decompression</p>
Dataset supporting the paper "Single-Spin Sensing: A Molecule-on-Tip Approach. ACS Nano 18, 13829 (2024)"
<p>Dataset corresponding to theoretical calculations in the paper "Single-Spin Sensing: A Molecule-on-Tip Approach" ACS Nano 18, 13829 (2024) DOI: https://doi.org/10.1021/acsnano.4c02470</p> <p>Please cite as:</p> <p>Alex Fétida, Olivier Bengone, Michelangelo Romeo, Fabrice Scheurer, Roberto Robles, Nicolás Lorente, and Laurent Limot. Dataset supporting the paper "Single-Spin Sensing: A Molecule-on-Tip Approach. ACS Nano 18, 13829 (2024)" DOI: 10.5281/zenodo.13774118</p> <p>List of files:</p> <p>Several folders corresponding to the figures of the paper. They contain:</p> <p>CONTCAR files: relaxed structures in VASP format. They can be visualized with VESTA (https://jp-minerals.org/vesta/en/).</p> <p>.agr: grace files (https://plasma-gate.weizmann.ac.il/Grace/).</p> <p>Image files in png format.</p>
Dataset related to the Journal Article 'Efficiency Enhancement of Marine Propellers via Reformation of Blade Tip-Rake Distribution'
<p>This Dataset contains results related to the Graphs shown in the publication titled "Efficiency Enhancement of Marine Propellers via Reformation of Blade Tip-Rake Distribution". The results refer to open water performance curves for the benchmark propeller geometries and the models with optimal tip-rake. In the Folder we provide the data for each figure in a specific folder with the number corresponding to the number of the figure in the published version of the paper. </p>
WP3-CT2 Alpine Glaciers Disappearance Tipping Point
<p>Glaciers Length changes starting from small, medium, and large glaciers.</p>
Icons of the tipping points in the Earth System from the H2020 COMFORT project (820989)
<p>Triple threat processes and/or other forcings can lead to changes in the ocean happening fast and abruptly. These changes, referred to as “tipping points”, are critical thresholds in a marine system that, when exceeded, can lead to a significant change in the state of the system, which often can be irreversible. This product has been prepared with the financial support of Norges forskningsråd (Research Council of Norway) (309382) and the European Union’s Horizon 2020 research and innovation programme under grant agreement No 820989 (project COMFORT, Our common future ocean in the Earth system – quantifying coupled cycles of carbon, oxygen, and nutrients for determining and achieving safe operating spaces with respect to tipping points). The work reflects only the author’s/authors’ view; the European Commission and their executive agency are not responsible for any use that may be made of the information the work contains.</p>
How to Ensure Researchers Share Their FAIR Data: Practical Tips and Tools [Online Workshop, Recording]
<p>The online hands-on workshop was aimed at trainers and support staff covering critical elements of data sharing and available tools and resources for supporting Open Science including:<br> • Open Science resources and Data Management Planning<br> • Consent and Ethical considerations<br> • Legislation and Licence frameworks<br> The objectives of the workshop were i) to raise awareness of key tools and resources available for Open Science training ii) to enable a platform to exchange ideas regarding key training topics and iii)n to provide training materials and worksheets for future reuse.<br> The workshop consisted of presentations, demos, a roundtable discussion on ethical considerations, a showcase of licence frameworks at different European archives and an exercise with all participants fostering an exchange of experiences focused on learnt lessons.</p> <p>The video is available on<a href="https://www.youtube.com/watch?v=uztTCRFRZHg"> the CESSDA Training YouTube channel</a>.</p>
Daily summary precipitation data from a tipping bucket rain gauge near former Jornada Basin LTER Biodiversity study site, 1996-ongoing
This data package contains daily precipitation values from a rain gauge near the former Biodiversity study site at the Jornada Basin LTER in southern New Mexico, USA. Data collection at the Biodiversity site began in 1996 and is now complete. Data collection from the tipping bucket rain gauge near this site commenced in April 1996. The data file included here reports daily precipitation totals in millimeters (mm). Data collection from this tipping bucket rain gauge is ongoing and collected on a monthly basis (data package may be updated less frequently).
High resolution precipitation event data from a tipping bucket gauge near former Jornada Basin LTER Biodiversity study site, 1996-ongoing
This data package contains high temporal resolution values from a tipping bucket rain gauge during rain events near the former Biodiversity study site at the Jornada Basin LTER in southern New Mexico, USA. Data collection at the Biodiversity site began in 1996 and is now complete. Data collection from the tipping bucket rain gauge near this site commenced in April 1996. The data file included here reports 1-second (1997-2016) or 1-minute (2016-present) frequency precipitation data, in millimeters, from this rain gauge during precipitation events. There are no data records for rain amounts less than 0.1 mm. Data collection from this tipping bucket rain gauge is ongoing and collected on a monthly basis (data package may be updated less frequently).
Figures 19-22. D. shardana holotype, right male bulb 19 prolateral view, general 20 prolateral view, tip detail 21 anterior view 22 P in Systematics and phylogeography of the Dysdera erythrina species complex (Araneae, Dysderidae) in Sardinia
Figures 19-22. D. shardana holotype, right male bulb 19 prolateral view, general 20 prolateral view, tip detail 21 anterior view 22 P, prolateral view.
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)
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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.