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6,452 results for “Application”
Overview of Automatic Preliminary Boundary Delineation Tool developed as part of UC2 (Prefilled Application) in NIVA4CAP
<p>UC2 Pre-filled application seeks to make it easier and more accurate for farmers to annually declare their lands by reducing the time needed to draw the new parcels boundaries or update the existing ones, thus, prevent the mistakes with input of the data on crops grown. The work focussed on (1) Creating an automatic preliminary boundary delineation tool, (2) Testing an early stage corp type/ land use classification tool and (3) Finding and testing a robotic process automation tool suitable for data harvesting from external registers. This document gives an overview of the parcel boundary delineation tool and is supplemented by a complementary report summarising results from tests of that tool in Lithuania and Spain and referenced below.</p>
The computation results of coupled hydrological and hydrodynamic modelling application for the Nemunas River watershed – Curonian Lagoon – South-Eastern Baltic Sea continuum
<p>The datasets provided here were used to analyse the cumulative impacts of climate change in a Nemunas River watershed – Curonian Lagoon – South‑Eastern Baltic Sea continuum by applying a state-of-the-art coupled modelling system, which consists of hydrological and hydrodynamic models.</p> <p>Meteorological data used for running the models were acquired from CORDEX (Coordinated Regional Downscaling Experiment) scenarios for Europe from the Rossby Centre high-resolution regional atmospheric climate model (RCA4), which consisted of four sets of simulations (downscaling) driven by four global climate models:</p> <table> <tbody> <tr> <th>Abbreviation in datasets</th> <th>Model</th> <th><strong>Institution</strong></th> </tr> </tbody> <tbody> <tr> <td>ICHEC</td> <td>EC-Earth</td> <td>Irish Centre for High-End Computing</td> </tr> <tr> <td>IPSL</td> <td>IPSL-CM 5A-MR</td> <td>The Institut Pierre-Simon Laplace</td> </tr> <tr> <td>MOHC</td> <td>HadGEM2-ES</td> <td>Met Office Hadley Centre</td> </tr> <tr> <td>MPI</td> <td>MPI-ESM-LR</td> <td>Max Planck Institute for Meteorology</td> </tr> </tbody> </table> <p> </p> <p>Climate change scenarios and periods:</p> <ul> <li>Historical/reference (1970-2005);</li> <li>RCP4.5 (2005-2100);</li> <li>RCP8.5 (2005-2100).</li> </ul> <p>The datasets consist of time series for the parameters of:</p> <ul> <li><strong>Ice thickness</strong> - average ice thickness in the Curonian Lagoon;</li> <li><strong>Meteorological data</strong> - bias-corrected temperature and precipitation data for the marine and terrestrial areas;</li> <li><strong>Nemunas River discharge</strong> - simulated average daily values for the discharge and water temperature;</li> <li><strong>Salinity</strong> - selected points in the south-eastern Baltic Sea and one point next to Juodkrantė (in the Curonian Lagoon);</li> <li><strong>Water fluxes</strong> - through four predefined cross-sections in the Curonian Lagoon;</li> <li><strong>Water level</strong> - in 10 preselected points in the Curonian Lagoon and South-eastern Baltic Sea;</li> <li><strong>Water residence time</strong> - in the total Curonian Lagoon area, as well as its northern and southern parts;</li> <li><strong>Water temperature</strong> - in 10 preselected points in the Curonian Lagoon and South-eastern Baltic Sea.</li> </ul> <p>Some of the datasets (zip files) have additional information (coordinates, data column explanations, units, etc.) in READ_ME.txt files.</p>
Data analysis of LiP-MS data for high-throughput applications
<p>Proteins regulate biological processes by changing their structure or abundance to accomplish a specific function. In response to any perturbation or stimulus, protein structure may be altered by a variety of molecular events, such as post translational modifications, protein-protein interactions, aggregation, allostery, or binding to other molecules. The ability to probe these structural changes in thousands of proteins simultaneously in cells or tissues can provide valuable information about the functional state of a variety of biological processes and pathways. Here we present an updated protocol for LiP-MS, a proteomics technique combining limited proteolysis with mass spectrometry, to detect protein structural alterations in complex backgrounds and on a proteome-wide scale (Cappelletti et al., 2021; Piazza et al., 2020; Schopper et al., 2017). We describe advances in the throughput and robustness of the LiP-MS workflow and implementation of data-independent acquisition (DIA) based mass spectrometry, which together achieve high reproducibility and sensitivity, even on large sample sizes. In addition, we introduce MSstatsLiP, an R package dedicated to the analysis of LiP-MS data for the identification of structurally altered peptides and differentially abundant proteins. Altogether, the newly proposed improvements expand the adaptability of the method and allow for its wide use in systematic functional proteomic studies and translational applications. </p>
Dataset for: "Quantification of Geometric Errors Made Simple: Application to Main-Group Molecular Structures"
<p>This dataset contains geometric energy offset (GEO') values for a set of density functional theory (DFT) methods for the B2se set of molecular structures. The data was generated as part of a research project aimed at quantifying geometric errors in main-group molecular structures. The dataset is in XLSX format created with MS Excel (version 16.69), and contains multiple worksheets with GEO' values for different basis sets and DFT methods. The worksheet headings, such as "AVQZ AVTZ AVDZ VQZ VTZ VDZ" represent different basis sets of Dunning theory, and the naming convention "(A)VnZ = aug-cc-pVnZ" is being used to label the worksheets. The data is organized in columns, with the first column providing the molecular ID and the names of the DFT methods specified in the first row of each worksheet. The molecular structures corresponding to each of these IDs can be found in Figure S1 of the supplementary information of the underlying publication [<a href="https://pubs.acs.org/doi/suppl/10.1021/acs.jpca.1c10688/suppl_file/jp1c10688_si_001.pdf">https://pubs.acs.org/doi/suppl/10.1021/acs.jpca.1c10688/suppl_file/jp1c10688_si_001.pdf</a>]. The data have been generated from quantum-chemical calculations from the G16 and ORCA 5.0.0 packages, with further computational details, methodology, and data validation strategies (e.g., comparisons with higher-level quantum-chemical calculations) given in the supplementary information of the underlying publication [<em>J. Phys. Chem. A</em> 2022, 126, 7, 1300–1311] and its supporting information [<a href="https://pubs.acs.org/doi/suppl/10.1021/acs.jpca.1c10688/suppl_file/jp1c10688_si_001.pdf">https://pubs.acs.org/doi/suppl/10.1021/acs.jpca.1c10688/suppl_file/jp1c10688_si_001.pdf</a>].<br> The dataset is expected to be useful to researchers in the field of computational chemistry and materials science. All values are given in kcal/mol. The data is generated by the authors of the underlying publication and it is shared under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. The data is expected to be re-usable and the quality of the data is assured by the authors. The size of the data is 71 KB.</p>
Fast Initiating Furan-Containing Hoveyda-Type Complexes: Synthesis and Applications in Metathesis Reactions
<p>Data confirming the structure of the new compounds obtained within the project, published in <em>Chemistry</em> <strong>2022</strong>, <em>4</em>(3), 786-795; <a href="https://doi.org/10.3390/chemistry4030056">https://doi.org/10.3390/chemistry4030056</a></p> <p>The research was performed within SONATA BIS project and was funded by National Science Centre, Poland, grant number DEC-2021/42/E/ST4/00187.</p> <p> </p> <p> </p>
Companion data of Summarizing task-based applications behavior over many nodes through progression clustering
<p>This is the companion data for the paper *Summarizing task-based applications behavior over many nodes through progression clustering* by Lucas Leandro Nesi, Vinícius Garcia Pinto, Lucas Mello Schnorr, and Arnaud Legrand accept for publication in 31st Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (<a href="https://www.pdp2023.org/">PDP 2023</a>). The remaining of the companion is at: https://gitlab.com/lnesi/companion-pdp-2023.</p>
Starspot mapping with adaptive parallel tempering. II. Application to TESS data for M-dwarf flare stars, AU Microscopii, YZ Canis Minoris, and EV Lacertae (Flare Tables)
<p>For TESS PDC-SAP data of AU Mic (Sector 1 and 27), YZ CMi (Sector 7 and 34), and EV Lac (Sector 16), detected flare properties are listed: the peak time (BJD-2745000), amplitude, equivalent duration (sec), and e-folding time (day).</p>
Earthquake catalogs for: A specific earthquake processing workflow for studying long-lived explosive volcanic eruptions with application to the 2008 Okmok eruption
<p>Repository for the seismic catalogs from Garza-Giron et al. (2023a,b). These include the catalog with absolute locations using NonLinLoc (Lomax et al., 2001; Lomax and Curtis, 2001), and the relocated catalogs using hypoDD (Waldhauser and Ellsworth, 2000) and GrowClust (Trugman and Shearer, 2017).</p> <p>The header of the CSV files is as follows:</p> <p><strong>Date</strong> (year/month/day), <strong>Time</strong> (hr:min:sec:msec), <strong>Latitude</strong> (decimal degrees), <strong>Longitude</strong> (decimal degrees), <strong>Depth</strong> (km), <strong>Magnitude</strong> (Ml calculated for this study), <strong>Event_type</strong> (VT:vulcano-tectonic;LP:long-period), <strong>Number of stations</strong> where the event was detected, <strong>ID</strong></p> <p>References:</p> <div>Garza‐Giron, R., Brodsky, E. E., Spica, Z. J., Haney, M. M., & Webley, P. W. (2023a). A specific earthquake processing workflow for studying long‐lived, explosive volcanic eruptions with application to the 2008 Okmok Volcano, Alaska, eruption. <em>Journal of Geophysical Research: Solid Earth</em>, e2022JB025882.</div> <div> </div> <div> <div>Garza‐Girón, R., Brodsky, E. E., Spica, Z. J., Haney, M. M., & Webley, P. W. (2023b). Earthquakes record cycles of opening and closing in the enhanced seismic catalog of the 2008 Okmok Volcano, Alaska, eruption. <em>Journal of Geophysical Research: Solid Earth</em>, <em>128</em>(7), e2023JB026893.</div> <div> </div> </div> <p>Lomax A, Curtis A (2001) Fast, probabilistic earthquake location in 3-D models using oct-tree importance sampling. Geophys Res Abstracts, 3:955.</p> <p>Lomax, A., Zollo, A., Capuano, P., and Virieux, J. (2001). Precise, absolute earthquake location under Somma‐Vesuvius volcano using a new 3D velocity model.Geophysical Journal International,146, 313–331.</p> <p>Trugman, D. T., and Shearer, P. M. (2017). GrowClust: A hierarchical clustering algorithm for relative earthquake relocation, with application to the Spanish Springs and Sheldon, Nevada, earthquake sequences. Seismological Research Letters, 88(2A), 379-391.</p> <p>Waldhauser, F., and Ellsworth, W. L. (2000). A double-difference earthquake location algorithm: Method and application to the northern Hayward fault, California. Bulletin of the Seismological Society of America, 90(6), 1353-1368.</p>
Deep Learning and Procrustes Analysis for Early Dysgraphia Risk Detection with a Tablet Application - DATASET
<p>Data to support the findings reported in the journal paper</p> <p>Lomurno, E., Dui, L. G., Gatto, M., Bollettino, M., Matteucci, M., & Ferrante, S. (2023). Deep Learning and Procrustes Analysis for Early Dysgraphia Risk Detection with a Tablet Application. <em>Life</em>, <em>13</em>(3), 598.</p> <ul> <li>Caratterizzazione_y3b_pulito.xls: <ul> <li>Subject ID</li> <li>Age at the beginning of the study</li> <li>Handedness</li> <li>Sex</li> </ul> </li> <li>Score_BVSCO_pulito.xls: <ul> <li>Subject ID</li> <li>columns B-D: graphemes in the three tests of the BVSCO-2</li> <li>columns E-G: z-score computed on normative data for the three tests of the BVSCO-2</li> <li>median z-score: computed on columns E-G</li> <li>at risk: if median z-score is under the -2 threshold (0=not at risk, 1=at risk)</li> </ul> </li> <li>executions.mat: a matrix for each time point (y1, y2a, y2b, y3a, y3b) and game (copa_q = copy square, copia_seq = copy sequence, tunnel_q = tunnel square, tunnel_ele = tunnel word). <ul> <li>first column of all the cell arrays: subject ID</li> <li>second column for the copy games: three sub-matrices with an execution for each level (spontaneous, big, small)</li> <li>columns 2:N for the tunnel games: an average execution for each index of difficulty</li> <li>for each execution, the columns of the sub-matrices are normalized time, normalized x, normalized y and pressure</li> </ul> </li> </ul> <p> </p> <p>Copy games</p> <ul> <li>A matrix for each game and each time point with a number of rows equal to the number of children and a number of columns equal to 2: <ul> <li>First column: array with school and child code</li> <li>Second column: executions</li> </ul> </li> <li>For the two copy games, the data has a dimension of 3 x 1, where 3 are the modalities (spontaneous, big, small) and 1 is the data matrix.</li> <li>By accessing the data matrix we have four variables, i.e., normalized time, normalized x, normalized y and pressure.</li> </ul> <p> </p> <p>Tunnel games</p> <ul> <li>A matrix for each game and each time point with a number of rows equal to the number of children and a number of columns equal to index of difficulty number +1: <ul> <li>First column: array with school and child code</li> <li>From the second column onwards: executions, each column corresponds to the "typical" execution (the average) of an ID (5 for square tunnel and 8 for ele tunnel). Sub-matrices contain the data matrix with its four variables. i.e., normalized time, normalized x, normalized y and pressure.</li> </ul> </li> </ul>
A novel R744 multi-temperature cycle for refrigerated transport applications with low-temperature ejector: experimental ejector characterization and thermodynamic cycle assessment - Ejector experimental data
<p>Experimental data obtained during the characterization of a R744 ejector in low-temperature suction operating conditions.</p> <p>The complete description of the experimental setup and of the R744 cooling unit concept designed to employ the tested ejector, as well as the discussion on the experimental data, are available in:</p> <p>Fabris, F., Pardiñas, Á. Á., Marinetti, S., Rossetti, A., Hafner, A., Minetto, S. (2023). A novel R744 multi-temperature cycle for refrigerated transport applications with low-temperature ejector: experimental ejector characterization and thermodynamic cycle assessment. International Journal of Refrigeration.</p>
Unsupervised neural network for single cell Multi-omics INTegration (UMINT): An application to health and disease
<p>This dataset repository corresponds to the project Unsupervised neural network for single cell Multi-omics INTegration (UMINT): An application to health and disease.</p>
Hydrothermal Synthesis of Ni3TeO6 and Cu3TeO6 Nanostructures for Magnetic and Photoconductivity Applications
<p>See the reference:</p> <p>Fernández-Catalá, J.; Singh, H.; Wang, S.; Huhtinen, H.; Paturi, P.; Bai, Y.; Cao, W <em>ACS Appl. Nano Mater.</em> <strong>2023 </strong>(https://doi.org/10.1021/acsanm.3c00630)</p>
Virtual sensors for wind energy applications benchmark study data - preliminary version
<p>Test version of the time series data for the wind energy virtual sensing benchmark study data.</p>
Design of Blockchain-based Applications using Model-Driven Engineering and Low-Code / No-Code Platforms - SLR Dataset
<p>Dataset of the publications collected at various stages of the Structured Literature Review titled "<a href="https://link.springer.com/article/10.1007/s10270-023-01109-1">Design of Blockchain-based Applications using Model-Driven Engineering and Low-Code / No-Code Platforms</a>" published in Software and Systems Modeling:</p> <p>The creation of blockchain-based software applications requires today considerable technical knowledge, particularly in software design and programming. This is regarded as a major barrier in adopting this technology in business and making it accessible to a wider audience. As a solution, low-code and no-code approaches have been proposed that require only little or no programming knowledge for creating full-fledged software applications. In this paper we extend a review of academic approaches from the discipline of model-driven engineering as well as industrial low-code and no-code development platforms for blockchains. This includes a content-based, computational analysis of relevant academic papers and the derivation of major topics. In addition, the topics were manually evaluated and refined. Based on these analyses we discuss the spectrum of approaches in this field and derive opportunities for further research.</p>
Integration of Renewable Energy Sources into the Water-Energy-Food (WEF) Nexus – Modelling a Demand Side Management Approach and Application to a Microgrid Farm in Morocco Dataset
<p>Here you can find the official data used for the publication "Integration of Renewable Energy Sources into the Water-Energy-Food (WEF) Nexus – Modelling a Demand Side Management Approach and Application to a Microgrid Farm in Morocco"</p> <p>If you want to run the model, please update line 11 in the run.jl file, to select the dataset from the scenario you want to look at. It is also recommended to change the result path, to a directory that corresponts to the current model run in order to find the results files quicker.</p> <p> </p> <p>To create a new plot a file called newPlot.jl can be found, that already take care of most data handling, only lines 136 and 141 need to be changed, in order to read in the result files of the results you want to investigate.</p>
Data for "The use of bibliometrics in nursing research: topics, data sources and applications"
<p>Dataset to reproduce the analysis of the paper "The use of bibliometrics in nursing research: topics, data sources and applications". It contains a list of 129 nursing bibliometric articles and, or each article, the topic of the study, the data source employed to gather the literature, the time frame, the number of records considered, and whether the article analysed, or not, fourteen variables.</p>
Supporting data and tool, for the paper "A standardized methodology for the validation of air quality forecast applications (F-MQO): Lessons learnt from its application across Europe"
<p>This 'Zenodo' contains supporting data and tools, for the paper 'A standardized methodology for the validation of air quality forecast applications (F-MQO): Lessons learnt from its application across Europe'.</p> <p>The repository includes the source code (<a href="https://zenodo.org/api/files/fdcaf2a5-5289-44f5-96db-6dda29c5cb6c/DELTA_7.2.zip">DELTA_7.2.zip</a>) and the dataset (<a href="https://zenodo.org/api/files/fdcaf2a5-5289-44f5-96db-6dda29c5cb6c/GMD_Vitali_et_all_data_20230516.zip">GMD_Vitali_et_all_data_20230516.zip</a>).</p>
Supplementary data for a systematic literature review on source code similarity measurement and clone detection: techniques, applications, and challenges
<p>The Microsoft Excel files containing the supplementary data and diagrams for the paper:</p> <p><strong>A systematic literature review on source code similarity measurement and clone detection: techniques, applications, and challenges</strong></p> <p>The article is under review in the Journal of Systems and Software.</p> <p>In this version, the literature search has been performed between April and May 2023, and studies published until that date has been mentioned in the attached Excel files.</p> <p>This version (v3.4.0) corresponds to the third revision (R3) of the manuscript.</p> <p> </p>
User Reviews of nine Social VR applications
<p>These user reviews are collected from nine social VR applications on two digital distributation platforms (Steam and Oculus). All these are in English.</p> <p>Five social VR applications are from Steam: VRChat, Rec Room, PokerStars VR, Altspace, VR, Sansar.</p> <p>Eight social VR applications are from Oculus: VRChat, Rec Room, Echo VR, PokerStars VR, Real VR Fishing, Poker VR, Altspace VR, vTime VR.</p>
Reprocessing script and data for the Bilzingsleben antlers dataset to visualise it with the archeoViz web application
<p>This files were created to be used for visualisation with the <a href="https://analytics.huma-num.fr/archeoviz/bilzingsleben"><em>archeoViz</em> application</a>.</p> <p>This record includes:</p> <ul> <li>Reprocessed data from: Vollbrecht, Jürgen. 2000. “The antler finds at Bilzingsleben, excavations 1969-1993”, <em>Internet Archaeology</em>, 8. DOI: <a href="https://doi.org/10.11141/ia.8.1">10.11141/ia.8.1</a></li> <li>and an R script with the code used to the reprocess this dataset.</li> </ul> <p>In the resulting files,</p> <ul> <li><strong>bilzingsleben-data.csv</strong>: partialy reprocessed Vollbrecht's data.</li> <li><strong>bilzingsleben.csv</strong>: output file of the reprocessing: the objects (antlers) are associated with the ranges of coordinates of the square they were found, links to their record in Vollbrecht's database are included.</li> <li><strong>bilzingsleben-refits.csv</strong>: refitting data are reformated in a convenient format.</li> <li><strong>bilzingsleben-timeline.csv</strong>: the year the squares were excavated were deduced using Vollbrecht 2000 and recoded. This made it possible to generate:</li> <li><strong>bilzingsleben-timeline-map.jpg</strong>: a map of the site giving the year the squares were excavated and the labels arbitrary attributed for the <em>archeoViz</em> visualisation.</li> </ul> <p> </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.