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5,155 results for “Data Base”
Increase of active-power-based flexibility (data for KPI evaluation)
<p>There are stored data collected from new EV charging stations – this will be used as an aggregated source of active power-based flexibility procured for system operator (DSO) and managed through non frequency platform. Data originated from part of the CZ DEMO run directly by ČEZ distribuce called "e – fleet". At Zenodo there are data from all sites (EV charging poles while the first excel sheet contains calculation of the KPI “Increase of active-power-based flexibility”. Detailed explanation on KPI evaluation, data format and main findings from the tests are included in the <a title="link" href="https://www.onenet-project.eu/wp-content/uploads/2024/03/OneNet_D10.5_V1.0.pdf">Deliverable 10.5 (section 2.1.2). </a></p>
Data for: Caspase-Based Fusion Protein Technology: Substrate Cleavability Described by Computational Modeling and Simulation
<p>This dataset contains all files necessary to set up the simulations conducted in this work. It further contains the scripts that were used to do the stitching and combining of the CASPON-tag and the N-termini of the POIs. The manuscript was just submitted and accepted: <a href="https://doi.org/10.1021/acs.jcim.4c00316">10.1021/acs.jcim.4c00316</a></p>
Associated code and data for "A disease network-based deep learning approach for characterizing melanoma (doi:10.1002/IJC.33860)"
<p>This deposit contains the data, code, and analysis to recreate the results in the manuscript - Lai X, Zhou JF, Wissely A, Heppt M, Maier A, Berking C, Vera J, Zhang L. A disease network-based deep learning approach for characterizing melanoma. International Journal of Cancer. 2022; 150(6): 1029- 1044. <a href="http://www.researchgate.net/publication/355774213_A_disease_network-based_deep_learning_approach_for_characterizing_melanoma">doi:10.1002/IJC.33860</a>.</p> <p>If you have used the code for your research, please cite the original publication. Thank you very much.</p> <p> </p> <p> </p>
Wrapper Impact Workloads and BSC Slurm Simulator Output of Static Traces based on Data from LUMI Supercomputer
<p>This dataset contains the workloads, with the workflow added to them, and the results of the simulations of the static trace utilizing LUMI fitted data carried out using <a href="https://ieeexplore.ieee.org/abstract/document/8641556">BSC's SLURM Simulator</a>.</p> <p>It is organized in two folders: workloads and results. In the first, we find a folder per experiment, which is a different randomly generated workload file. Within each experiment we find a folder per fair share inidicating the target platform, the workflow it was based on, and the characteristics of the tracked job: number of cores and runtime. The results folder follows the same scheme but with a file extension of ".trace".</p>
Core individual-based model simulation script and landscape data
<p>Habitat loss and isolation caused by landscape fragmentation represent a growing threat to global biodiversity. Existing theory suggests that the process will lead to a decline in metapopulation viability. However, since most metapopulation models are restricted to simple networks of discrete habitat patches, the effects of real landscape fragmentation, particularly in stochastic environments, are not well understood. To close this major gap in ecological theory, we developed a spatially explicit, individual-based model applicable to realistic landscape structures, bridging metapopulation ecology and landscape ecology. This model reproduced classical metapopulation dynamics under conventional model assumptions, but on fragmented landscapes, it uncovered general dynamics that are in stark contradiction to the prevailing views in the ecological and conservation literature. Notably, fragmentation can give rise to a series of dualities: a) positive and negative responses to environmental noise, b) relative slowdown and acceleration in density decline, and c) synchronization and desynchronization of local population dynamics. Furthermore, counter to common intuition, species that interact locally ("residents") were often more resilient to fragmentation than long-ranging "migrants". This set of findings signals a need to fundamentally reconsider our approach to ecosystem management in a noisy and fragmented world.</p>
1-km high resolution model outputs using the WRF and WRF-Hydro model Raw data from the manuscipt "Process-based Atmosphere-Hydrology-Malaria Modeling: Performance for Spatio-temporal Malaria Transmission Dynamics in Sub-Saharan Africa "
<p>Here we provide the model outputs from the numerical climate model WRF (Weather Research and Forecasting) and its hydrological coupled model WRF-Hydro for the Health and Demographic Surveillance Systems (HDSS) site regions of Nouna in Burkina Faso. Model results are used for investigating the influence of surface hydrology representation, environmental and climate-sensitive driver factors on malaria incidence.<br>The experiments use the following model configuration: 1km horizontal resolution with 200*200 grid points, WSM6 microphysics, ACM2 PBL, and RRTM & Dudhia radiation scheme. WRF uses the Noah LSM, and WRF-Hydro uses the Noah LSM with enhanced lateral hydrological description (https://ral.ucar.edu/projects/wrf_hydro/overview). These simulations were conducted in the Karlsruhe Steinbuch Centre for Computing (SCC) Horeka.</p> <p>Model outputs are provided in daily step (originally derived from the hourly output). Filename with "wrf-hydro_pr_2000-2020_d02-1km.nc" provides Precipitation,<br>n mm/day"wrf-hydro_tas_2000-2020_d02-1km.nc" provides mean temperature in Celsius, "wrf-hydro_tasmax_2000-2020_d02-1km.nc" provides maximum temperature in Celsius, "wrf-hydro_tasmin_2000-2020_d02-1km.nc" provides minmum temperature in Celsius, "wrf-hydro_dtr_2000-2020_d02-1km.nc" provides diurnal temperature ranges in Celius, "wrf-hydro_rh_2000-2020_d02-1km.nc" provides relative humudity in % and "wrf-hydro_sw_2000-2020_d02-1km.nc" provides the surface hydrology.</p>
Thermochemical Data for Furan-based Monomer Candidates for Frontal Ring-Opening Metathesis Polymerization (FROMP)
<p>This dataset includes 471 furan-based monomer candidates for frontal ring-opening metathesis polymerization (FROMP) and relevant thermochemistry as calculated with density functional theory (DFT). The monomer candidates were combinatorically enumerated using Diels-Alder reactions of furan derivatives as dienes and four types of dienophiles (alkenes, alkynes, allenes, and benzynes). Common substituents were enumerated for the dienophile classes, and methyl substitution on the diene was explored. We used the SMILES arbitrary target specification (SMARTS) language to produce monomers and ring-opened structures from diene and dienophile precursor SMILES, and we studied the ring-opening reaction using a homodesmotic equation with ethene. RDKit conformers were initially generated from SMILES, then optimized with GFN2-xTB. The two conformers lowest in energy were then optimized with DFT using the wb97x-D3 functional, def2-TZVP basis set, and def2/J auxiliary basis set. Gibbs free energy corrections were obtained through frequency calculations. Structures with imaginary frequencies below -50 cm^{-1} were excluded from this work, and smaller imaginary modes were flipped to be positive for free energy calculations. Modes below 50 cm^{-1} were treated with the modified rigid rotor approximation, and all thermochemical values were calculated at T=200C. The CSV file contains the monomer SMILES, the free energy of reaction for Diels-Alder addition (G_DA_200), and the enthalpy of the ring-opening reaction (H_RO_200). All energies are given in kcal/mol. An interactive HTML is also included to visualize the monomers in this dataset.</p>
Research Data for Comparative Evaluation of RT-PCR and Antigen-based Rapid Diagnostic Tests (Ag-RDTs) for SARS-CoV-2 Detection: Performance, Variant Specificity, and Clinical Implications
<p>This dataset represents laboratory findings for the comparative evaluation of the diagnostic performance of Ag-RDTs (Flourescence Immunoassay and Lateral Flow Immunoassay) with RT-PCR</p>
Figure 3 in Synonymy of the water mite subgenera Orientmomonia and Kondia in the genus Momonia (Momoniidae, Acari): an evaluation based on morphology and molecular data
Figure 3 Male of Momonia(Orientmomonia) koreana. A – dorsal view of idiosoma; B – ventral view of idiosoma; C – left palp; D – I-L-1–6. E – IV-L-3–6. Scale bars: 100 μm.
Figure 5 in Synonymy of the water mite subgenera Orientmomonia and Kondia in the genus Momonia (Momoniidae, Acari): an evaluation based on morphology and molecular data
Figure 5 Maximum-likelihood phylogenetic tree based on the mitochondrial cytochrome oxidase subunit I (COI) gene sequences obtained for a set ofMomoniaspecimens. Bootstrap values (> 50%) related to the nodes are indicated (1,000 replicates).
Figure 1 in Synonymy of the water mite subgenera Orientmomonia and Kondia in the genus Momonia (Momoniidae, Acari): an evaluation based on morphology and molecular data
Figure 1 Provenance of the material used in the present study. Collection site A – Tatsuno City in Hyogo Prefecture; Collection site B – Aioi City in Hyogo Prefecture; Collection site C – Tsushima City in Nagasaki Prefecture.
Figure 4 in Synonymy of the water mite subgenera Orientmomonia and Kondia in the genus Momonia (Momoniidae, Acari): an evaluation based on morphology and molecular data
Figure 4 Female of Momonia(Kondia) sp. A – dorsal view of idiosoma; B – ventral aspect of unmounted specimen; C – ventral view of idiosoma; D – right palp; E – I-L-1–6; F – IV-L-3–6. Scale bars: 100 μm.
Metadata Profile for FAIR Sensor Data based on the SensOr Interfacing Language
<p>Metadata profile to provide FAIR sensor data. The profile is created using SHACL and is based on the SOSA ontology which accurately specifies restrictions on the properties of specific sensors using the QUDT and the SSN ontology. Generic metainformation is modeled using DCTerms. </p>
Data Sources for Bottom-Up Archetype-based Modelling of Nigerian Residential Dwellings for Scenario Analysis
<p><strong>Dataset Name:</strong><br><em>Literature Data, Archetype Parameter Sheets, and Schedules for the publication, named Bottom-Up Archetype-based Modelling of Nigerian Residential Dwellings for Scenario Analysis</em>.</p> <p><strong>Description:</strong><br>This dataset includes Excel sheets containing literature sources, archetypal data, and schedules for Nigerian residential dwelling typologies.</p> <p><strong>Files:</strong><br>The following files are included in the dataset:</p> <ul> <li> Nigeria<em>_LiteratureSources.xlsx:</em> Excel sheet containing literature sources and references,</li> <li> Nigeria<em>_ArchetypeParameters.xlsx</em>: Archetype models' semantic, geometric, and technical data used in the generation of energy models,</li> <li> Nigeria<em>_Schedules.xlsx:</em> Excel sheet containing the operation schedules compiled from literature sources and reorganized by expert consensus and given in Designbuilder input format.</li> </ul> <p><strong>Usage:</strong><br>The dataset is intended for researching and analyzing the Nigerian residential buildings. The literature sources included in the Nigeria_LiteratureSources.xlsx and Nigeria_ArchetypeParameters.xlsx files can be used to verify, support, or reproduce the research findings.</p> <p><strong>License:</strong><br>The dataset is licensed under Creative Commons Attribution 4.0 International.</p> <p><strong>Citation:</strong><br>If you use this dataset in your research, please cite it as follows and contact the corresponding author:</p> <p>Chibuikem Chrysogonus Nwagwu, Sahin Akin, and Edgar G. Hertwich. 2024. “Data Sources for Bottom-Up Archetype-based Modelling of Nigerian Residential Dwellings for Scenario Analysis” https://doi.org/10.5281/zenodo.10995123</p> <p><strong>Contact:</strong><br>The archetypes' energy models (DesignBuilder or IDF files) as well as full material and energy use result sheets can be provided on request. If you have any questions or comments about the dataset, please contact <strong>chibuikem.nwagwu@sintef.no, the corresponding author.</strong></p>
Dead Sea Scrolls data collection (images, labels, prediction plots) for dating ancient manuscripts using radiocarbon and AI-based writing style analysis
<p>The dataset is associated with the following article:<br>Title: <strong>Dating ancient manuscripts using radiocarbon and AI-based writing style analysis</strong><br>Authors: Mladen Popović, Maruf A. Dhali, Lambert Schomaker, Johannes van der Plicht, Kaare Lund Rasmussen, Jacopo La Nasa, Ilaria Degano, Maria Perla Colombini, and Eibert Tigchelaar<br><em>(Under review)</em></p> <p>This data set is collected for the ERC project:<br>The Hands that Wrote the Bible: Digital Palaeography and Scribal Culture of the Dead Sea Scrolls<br>PI: Mladen Popović<br>Grant agreement ID: 640497<br>Project website: <a href="https://cordis.europa.eu/project/id/640497">https://cordis.europa.eu/project/id/640497</a></p> <p> </p> <p><strong>Copyright (c) </strong> University of Groningen, 2024. All rights reserved.<br><strong>Disclaimer and copyright notice for all data contained on the *.tar.gz files:</strong></p> <p><strong>1)</strong> permission is hereby granted to use the data for research purposes. It is not allowed to distribute this data for commercial purposes.</p> <p><strong>2) </strong>provider gives no express or implied warranty of any kind, and any implied warranties of merchantability and fitness for purpose are disclaimed.</p> <p><strong>3) </strong>provider shall not be liable for any direct, indirect, special, incidental, or consequential damages arising out of any use of this data.</p> <p><strong>4) </strong>the user should refer to the first public article mentioned above on this data set.</p> <p><strong>5) </strong>the recipient should refrain from proliferating the data set to third parties external to his/her local research group. Please refer interested researchers to this site to obtain their own copy.</p> <p> </p> <p><strong>Organization of the data:<br></strong><em>(Update on 19 April 2024: OxCal data for accepted 2-sigma ranges are updated with the incusion and exclusion of minor peaks. New prediction plots are added after the model is trained with accepted 2-sigma ranges, including minor peaks. The old plots are also kept. <br><br><OLD Updates below; disregard><br>updated on 07-Feb-2024: OxCal data for selected ranges added in a new directory in addition to previously available original OxCal data. Enoch's prediction plots and test images are reorganized for easy access to the users.<br><OLD Updates above; disregard><br><br>Please use the files from this version and disregard the previous two versions: 10.5281/zenodo.10629480 and 10.5281/zenodo.8168210)</em></p> <p>There are four *.tar.gz files:</p> <p><em><strong>C14-Oxcal-data-updated.tar.gz</strong></em> contains one directory with radiocarbon data (OxCal [1] raw data) for all 30 manuscripts. Three additional directories contain name-corrected files for original OxCal data, files with accepted ranges, and files with accepted ranges including minor peaks. Please refer to the original article for details about OxCal data and the manuscripts. 25 out of 30 raw OxCal data are used (accepted ranges only) as the training labels during the training of Enoch, the date prediction model.</p> <p><em><strong>train-images-c14.tar.gz</strong></em> contains the clean and preprocessed (binarized, aligned, and arrangement corrected) training images for the 25 radiocarbon-dated training manuscripts (including 4Q52; 64 images in total). </p> <p><em><strong>test-images-all.tar.gz</strong></em> contains the clean and preprocessed test images for 135 previously undated manuscripts. The images are organized in three different directories: the first one with all 359 images for the 135 manuscripts, the second one with the selected 135 images, and the final one with 25 images to illustrate the poor quality of images. </p> <p><em><strong>Enoch-prediction-new-with-minor-peaks.tar.gz</strong></em> contains the new date prediction plots for each of the 135 test images, where Enoch was trained with the inclusion of minor peaks for the 2-sigma accepted ranges and with a data balancing threshold of 0.05. These plots are used by expert palaeographers' evaluation of Enoch's style-based date predictions of 135 previously undated manuscripts.</p> <p><em><strong>Enoch-predictions.tar.gz</strong></em> contains the date prediction plots for each of the 135 test images. There are two directories inside the *.tar.gz file:<br><br>- <em>prediction-plots-for-selected-135:</em> Prediction plots with data balancing threshold of 0.05. <br>- <em>extra-plots:</em> contains four additional directories:<br> - <em>Enoch-predictions-c14wo4Q52-balanced05:</em> Prediction plots with data balancing threshold of 0.05. <br> - <em>Enoch-predictions-c14wo4Q52-balanced10:</em> Prediction plots with data balancing threshold of 0.1.<br> - <em>Enoch-predictions-c14wo4Q52-unbalanced:</em> Unbalanced raw predictions.<br> - <em>Enoch-predictions-c14wo4Q52-combined:</em> Combined plots with all three prediction plots (unbalanced, 0.05, 0.1).<br>Please refer to the original article for more details.</p> <p>The updated code to run the plot is available here: <a href="https://doi.org/10.5281/zenodo.10998860">https://doi.org/10.5281/zenodo.10998860</a></p> <p><strong>If you have any questions, please get in touch with us:</strong><br>Mladen Popović <m.popovic(at)rug.nl><br>Maruf A. Dhali <m.a.dhali(at)rug.nl><br>Lambert Schomaker <l.r.b.schomaker(at)rug.nl></p> <p> </p> <p><strong>References:</strong><br>1. Bronk Ramsey, C. (2001). Development of the radiocarbon calibration program. <em>Radiocarbon</em>, <em>43</em>(2A), 355-363.</p>
A global land-use data cube 1992-2020 based on the Human Appropriation of Net Primary Production: Dataset 2
<p>This dataset is part of the LUIcube, a global dataset on land-use at 30 arcsecond spatial resolution. The LUIcube includes information on area, the change in NPP due to land conversions (HANPP<sub>luc</sub>), the harvested NPP (including losses, HANPP<sub>harv</sub>), and the NPP remaining in ecosystems after harvest (NPP<sub>eco</sub>) for 32 land-use classes in annual time-steps from 1992 to 2020. A detailed description of the LUIcube is available in the accompanying publication.</p> <p>The layers of land-use areas are provided in square kilometers (km²) per grid cell. All NPP flows are provided in tC/yr per grid cell. Adding HANPP<sub>harv</sub> to NPP<sub>eco</sub> results in the actual NPP available before harvest (NPP<sub>act</sub>=NPP<sub>eco</sub>+HANPP<sub>harv</sub>), and adding HANPP<sub>luc</sub> to NPP<sub>act</sub> results in the potential NPP available in the hypothetical absence of land use (NPP<sub>pot</sub>=NPP<sub>act</sub>+HANPP<sub>luc</sub>) for the given land-use class. Area-intensive values (in gC/m²/yr) can be calculated by dividing the NPP flows by the area of the respective land-use class per grid cell. HANPP in % of NPP<sub>pot</sub> can be calculated by summing up HANPP<sub>harv</sub> and HANPP<sub>luc</sub> and dividing it by NPP<sub>pot</sub>. Areas and NPP flows of land-use classes can be aggregated to calculate their overall HANPP. </p> <p>This Zenodo repository provides data on following land-use classes: grazing land characterized by open wooded lands (GL-owl)</p>
Measured and analyzed raw data for publication "Phase dynamics of tunnel Al-based ferromagnetic Josephson junctions"(https://doi.org/10.1063/5.0211006)
<p>The dataset provided here reports raw data published in June 2024 (Phase dynamics of tunnel Al-based ferromagnetic Josephson junctions): current-voltage I-V characteristics as a function of the temperature T; switching current distributions (SCD) as a function of T and calculated mean switching currents, standard deviations and skewness from the SCDs and superconducting branch resistance R0 as a function of the temperature. All the data for magnetic and non-magnetic Josephson junctions have been acquired, as highlighted in the corresponding reference.</p>
Supporting data for "Benchmarking the integration of hexagonal boron nitride crystals and thin films into graphene-based van der Waals heterostructures"
<p>Dataset for the publication "Benchmarking the integration of hexagonal boron nitride crystals and thin films into graphene-based van der Waals heterostructures"</p>
Filling the data gap between GRACE and GRACE-FO based on a two-step reconstruction method
<p><span>GRACE, </span><span>GRACE-FO</span><span>, Data gap, long short-term memory Bayesian convolutional neural network (LSTM-BCNN)</span></p>
Data, code, and outputs for the paper "Can Place-Based Crime Prevention Impacts be Sustained Over Long Durations? 11-Year Follow-Up of a Quasi-Experimental Evaluation of a CCTV Project"
<p>**********<br>Can Place-Based Crime Prevention Impacts be Sustained Over Long Durations? 11-Year Follow-Up of a Quasi-Experimental Evaluation of a CCTV Project<br>**********</p> <p>The phase-specific datasets for the main and displacement analyses are contained in the “1.datasets” folder. </p> <p>The scripts used to conduct the microsynthetic control matching analyses are contained in the “2.Rscripts” folder. The subfolders “3.outputs_main” and "4.outputs_displacement" contains all graphs and tables generated by the microsynth package. Please note that running the analysis will take several hours on most computer systems.</p> <p>The Microsoft Excel file displays the results of all models conducted for this analysis. Yellow tabs contain the WDD results presented in the text of the article. Red tabs are the per-capita (quarter-year) microsynth results used to calculate WDD values. All other tabs contain the raw microsynth outputs used to calculate the per-capita results. </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.