Find research datasets worth reusing

Dataset for publication "Measurement of Dynamic Voltage Variation Effect on Instrument Transformers for Power Grid Applications"

This is dataset related to paper published in 2020 IEEE  I2MTC Conference proceedings: Crotti G., Giordano D., Letizia P. S., Delle Femine A., Gallo D., Landi C., Luiso M., Barbieri L., Mazza P., Pallidini D., (2020, October 29). Measurement of Dynamic Voltage Variation Effect on Instrument Transformers for Power Grid Applications. https://doi.org/10.5281/zenodo.4154617 Excel file contains the data for Figure  10 and following parameter evaluation.

Data Set for Publication "Traceable Characterization of Low Power Voltage Instrument Transformers for PQ and PMU Applications"

This is dataset for paper published in CPEM2020 Conference Proceedings: Crotti G., Delle Femine A., Gallo D., Giordano D., Landi C., Letizia P.,S.,  Luiso M., "Traceable Characterization of Low Power Voltage Instrument Transformers for PQ and PMU Applications". https://doi.org/10.5281/zenodo.4153819 Excel file provides data for Figure 2 and following evaluation

Data of "Recurrent Neural Networks (RNNs) with dimensionality reduction and break down in computational mechanics; application to multi-scale localization step."

Data related to =========== title = "Recurrent Neural Networks (RNNs) with dimensionality reduction and break down in computational mechanics; application to multi-scale localization step.", journal = "Computer Methods in Applied Mechanics and Engineering", volume ="390", year = "2022", doi = "https://doi.org/<a href="http://dx.doi.org/10.1016/j.cma.2021.114476">10.1016/j.cma.2021.114476</a> ", pages = "114476 ", author = "Wu, Ling and Noels, Ludovic" We would be grateful if you could cite the paper in the case in which you are using the data   The files replace version 1 whose zip was corrupted.

opencc-zeroNov 2021View details →

dryad40/100

Data from: Pitfalls and pointers: an accessible guide to marker gene amplicon sequencing in ecological applications

Next Generation Sequencing (NGS) is a powerful tool that has been rapidly adopted by many ecologists studying microbial communities. Despite the exciting demonstration of NGS technology as a tool for ecological research, cryptic pitfalls inherent to its use can obscure correct interpretation of NGS data. Here, we provide an accessible overview of a NGS process that uses marker gene amplicon sequences (MGAS) that will allow scientists, particularly community ecologists, to make appropriate methodological choices and understand limits on inference about community composition and diversity that can be drawn from MGAS data. We describe the MGAS pipeline, focusing specifically on cryptic sources of variation that have received less emphasis in the ecological literature, but which may substantially impact inference about microbial community diversity and composition. By simulating communities from published microbiome data, we demonstrate how these sources of variation can generate inaccurate or misleading patterns. We specifically highlight sample dilution without researcher awareness and lane-to-lane variability, two cryptic sources of variation arising during the MGAS pipeline. These sources of variation affect estimates of species presence and relative abundance, particularly for species with moderate to low abundances. Each of these sources of bias can lead to errors in the estimation of both absolute and relative abundance within, and turnover among, microbial communities. Awareness and understanding of what happens and, specifically, why it happens during MGAS generation is key to generating a strong data set and building a robust community matrix. Requesting sample dilution information from the sequencing center, including technical replicates across sequencing lanes, and understanding how sampling intensity and community taxa distribution patterns shape the measurement of community richness, evenness, and diversity are critical for drawing correct ecological inferences using MGAS data.

Data for: Germanene preparation methods, its applications and uses

This dataset contains information regarding the patented methods and uses (both application and granted patents) of germanene, a two-dimensional layered germanium allotrope, analog to graphene. <a href="https://worldwide.espacenet.com/">Espacenet</a> (a free-of-charge database provided by the European Patent Office), accessed on Nov. 27, 2021, was used for data mining. The file titled “Espacenet_search_results_germanene” contains information related to Title, Inventors, Applicants, Publication number, Earliest priority, IPC, CPC, Publication date, Earliest publication, and Family number. The patent searches were carried out by keywords and classification codes.  Both IPC (International Patent Classification) and CPC (Cooperative Patent Classification) codes were used.    Value of the dataset: prior art searches, technological trends    Steps to reproduce data: Query 1: ctxt=("two-dimensional" prox/ordered "layered") AND ctxt any "german*" Query 2: ctxt=("two-dimensional" prox/ordered "layered") AND cl any "C07F7/30" Query 3: ftxt=("germanium" prox/ordered "allotrope") Query 4: claims any "germanene"   cl=classification codes (IPC or CPC) ftxt=full text ctxt=title/abstract/claims prox/ordered is a proximity operator   Definition of the classification codes used   C07F7/30: Compounds containing elements of Groups 4 or 14 of the Periodic System •Germanium compounds

opencc-by-4.0Jun 2012View details →

Fig. 3 in Acoustic Discrimination Of Pipistrellus Kuhlii And Pipistrellus Nathusii (Chiroptera: Vespertilionidae) And Its Application To Assess Changes In Species Distribution

Fig. 3. Bar graph about the number of settlements where P. kuhlii and P. nathusii occurred or were absent in case of the two studied areas, from North and South Hungary

opencc-by-4.0Jun 2012View details →

Fig. 2 in Acoustic Discrimination Of Pipistrellus Kuhlii And Pipistrellus Nathusii (Chiroptera: Vespertilionidae) And Its Application To Assess Changes In Species Distribution

Fig. 2. Occurrences of the two species in the two studied areas from North and South Hungary. (open circle = none of the species found, black square = P. nathusii, black triangle = P. kuhlii, black circle =

opencc-by-4.0Jun 2012View details →

Fig. 1 in Acoustic Discrimination Of Pipistrellus Kuhlii And Pipistrellus Nathusii (Chiroptera: Vespertilionidae) And Its Application To Assess Changes In Species Distribution

Fig. 1. The distribution of the canonical scores between P. kuhlii and P. nathusii resulted from the discriminant function analysis based on 5 call parameters

Performance Prediction of Deep Learning Applications

The repository includes the source code and the datasets used to predict the performance of Deep Learning applications executed on different environments. The results are included in the AI-SPRINT project deliverable "D2.1 - First release and evaluation of the AI-SPRINT design tools".

Raw data for Ultrathin wide-bandgap a-Si:H based solar cells for transparent photovoltaic applications

In the following the raw data lying the foundation of the paper “Ultrathin wide-bandgap a-Si:H based solar cells for transparent photovoltaic applications” (Lopez-Garcia et al.) published in Solar Rapid Research Letters, DOI: 10.1002/solr.202100909 (2021), are described. They were obtained under the funding provided by the European Union H2020 Framework Programme under Grant Agreement no. 826002 (Tech4Win) and by the Mater-One (Refs. PID 2020-116719RB-C42 and PID 2020-116719RB-C41) and SCALED (Ref. PID 2019-109215RB-C4) projects funded by the Spanish MCIN/AEI/10.13039/5011000110033. UV–vis measurements were acquired with a dual-beam spectrophotometer setup (Perkin Elmer Lambda L35) in transmittance mode (light source and detector normal to sample’s surface (i.e., 0o)) and in reflectance mode (with an Integrating sphere) scanning from 300 to 800 nm. J–V measurements under illumination were carried out using a homemade setup consisting on a AAA solar simulator calibrated using a NREL-certified Si reference solar cell (Abet Technologies, Model 15150). Electrical measurements were carried out with a source-measure unit (Keithley 2400) in four-wire sense mode, controlled by the software Tracer (ReRa solutions) using a IEEE 488 GPIB Instrument Control Device (National Instruments GPIB-USB-HS).

Crosswalks IUCLID 6.6 EU PPP Microorganisms - active substance application (product) to KMA&KMP

This Excel file provides detailed crosswalks from the <a href="https://esubmission.ecpa.eu/toc/EU">EU Table of Contents (SANCO/10181/2013)</a> for microbial plant protection product (PPP) dossiers to <a href="https://iuclid6.echa.europa.eu/">IUCLID 6.6</a>. It includes two spreadsheets, containing the mappings for active substance (as laid out in Commission Regulation (EU) No 283/2013) and representative product (Commission Regulation (EU) No 284/2013): <ul> <li>EU_PPP_Micro_ActiveSubstance: mapping between the "KMA" ToC and IUCLID 6.5's working context "EU PPP Microorganisms - active substance information"</li> <li>EU_PPP_Micro_Product: mapping between the "KMP" ToC and IUCLID 6.5's working context "EU PPP Microorganisms - active substance application (product)"</li> </ul> The spreadsheets map each section of the original EU ToC to: <ul> <li>IUCLID section: name of the section in IUCLID where to input the corresponding data/information</li> <li>Endpoint study record: name of the document template used to report individual studies of the section (if exists). These usually correspond to OECD Harmonised Templates (OHT).</li> <li>Endpoint summary: name of the document template used to report the summary information of the studies presented in the section (if exists)</li> <li>Other IUCLID document: name of any other document template in IUCLID used to report information of the section (if exists)</li> <li>OHT: name/id of the OECD Harmonised Template used for the endpoint study record document (if exists)</li> <li>Additional context: fulI IUCLID paths indicating the section of the respective document where information needs to be provided and/or specific values to be indicated. If more than one path is provided, these are separated by ";". Operators "=" and "!=" are used to indicate values to be used and to be avoided, respectively. When more than one value is possible, "IN" and "NOT IN" operators are used, followed by the exhaustive list of possible values. This nomenclature was defined with the aim of making contents machine-readable.</li> </ul> Version 3 includes changes in the table of contents of IUCLID6.6.

BeMAGIC_Reduction of coercivity in magnetic materials upon voltage application

BeMAGIC ITN (GA861145) Reduction of coercivity in magnetic materials upon voltage application. Results from UCAM, IFW/TUC and INRIM.

Mask Detection Application Performance Models

The repository includes the source code and the datasets used to build performance models for OSCAR Mask Detection application. The results are included in the AI-SPRINT project deliverable "D2.1 - First release and evaluation of the AI-SPRINT design tools".

Vibration assisted drilling (VAD) application to the manufactured maraging steel X3NiCoMoTi18-9-5 (1.2709) and aluminium AlSi10Mg (EN AC-43000) parts

Repository containing data from vibration assisted drilling (VAD) experiments on steel and Aluminum 3D powderbed manufactured parts. Please refer to README.MD (or .PDF), which contains a brief description of the chosen materials, parts and tools An explanation of the data aquisition and processing methods, together with the used nomenclature is given as well.

Application of Mass Multivariate Analysis on Neuroimaging Data Sets for Precision Diagnosis of Depression: Data and code

In the archive are the datasets and code used to create the results in article "Application of Mass Multivariate Analysis on Neuroimaging Data Sets fo Precision Diagnosis of Depression". The methods is based on the Multivariate Linear toolbox mad F. Kherif’s lab and available on GitHub. <a href="https://github.com/LREN-CHUV/MLM">https://github.com/LREN-CHUV/MLM</a>.    A total of 44 patients with a current psychotic (n=19) or depressive (n=25) episode were analyzed by MLM (details can be found in the article itself) utilizing resting sate fMRI, tasks fMRI, and anatomical T1w images.  The data results are provided in MATLAB format, in a matrix called MLM.mat. The matrix includes the canonical variables for each of the three imaging modalities, chi-square statistics, and p-values for each brain region.  Additionally, we provided a function MLM_plot_fun that allows mapping the statistics results to a canonical three-dimensional brain as per the article.

Model output for "Numerically consistent budgets of potential temperature, momentum, and moisture in Cartesian coordinates: application to the WRF model"

These data were produced with WRFlux v1.2.1 (https://github.com/matzegoebel/WRFlux/) from a numerical simulation with the community model WRF. Simulations represent the evolution of a convective boundary layer in the atmosphere over an idealized 2D mountain ridge. The data are published in connection with the article "Numerically consistent budgets of potential temperature, momentum and moisture in Cartesian coordinates: Application to the WRF model" in "Geoscientific Model Development" (https://doi.org/10.5194/gmd-15-669-2022). Three-dimensional (x, z, t) fields of five prognostic variables are provided: Potential temperature (T), water vapor mixing ratio (Q), cross-mountain (U), along-mountain (V), and vertical windspeed (W). All fields are averaged in time (30 min averaging interval) and in the along-mountain direction y. The repository contains the following files: grid.nc : variables related to the WRF numerical grid, air density [U,W,T,Q]_flux.nc : resolved and subgrid-scale fluxes [U,W,T,Q]_tendency.nc : resolved and subgrid-scale tendency components UVWT_MEAN.nc : averaged values of the variables themselves plotting.py : python script to approximately reproduce the figures of the paper. Requires the python packages matplotlib, xarray, and netcdf4. Figure 6 in the paper cannot be accurately reproduced with these data since the original figure uses 4D (x, y, z, t) output. For details on the simulation, refer to the article.

Dataset for an application example of a unified theory for 3D Gear and Thread Metrology

The evaluation of this dataset is presented in Stein et al. (2021) as an example for the advantages of the suggested novel approach. We propose a unified theory for the metrological treatment of helical machine elements such as cylindrical and conical gears, worms, and screw threads. The main idea is to introduce a universal 3D geometry model for threaded components that provides for distinct parameterization using a unique set of geometry parameters and that offers and a functional description of the transverse profile. Using modern 3D coordinate measuring technology, a holistic evaluation algorithm yields the actual geometry as the result of a high dimensional best-fit procedure and form deviations as corresponding residuals. All determinants and evaluation parameters can then be calculated from the set of actual geometry parameters. By applying certain constraints to the model to be fitted, the novel method can be reduced to the established 2D methods and hence meets demands for the comparison of the two procedures. The results of the novel approach have proven to be very stable and they enable the evaluation of areal measurements with no loss of information.

Reproducing nonlinear seismic response from in-situ soil dynamic parameters: application to the Delaney Park Downhole Array, Alaska

The zip file named 'seismic data at DPDA.zip' contains all the seismic data used in our study. The DEEPSOIL file named 'ground response analysis at DPDA.dp' contains the numerical models used in our study.

openmit-licenseFeb 2022View details →

Hubble eXtreme Deep Field that has been clipped and processed for ML applications

This is a set of FITS files downloaded from https://archive.stsci.edu/ .   The *.npy file has been clipped to the 99.99th percentile and then minmax normalised along each channel.