cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8145084
title: MERL Ground Penetrating Radar Dataset (MERL-GPR)

description: MERL-GPR is a simulated ground penetrating radar dataset generated using the open-source finite difference time domain tool for electromagnetic simulation gprMax. The dataset consists of 400 two dimensional underground structures with a domain size of 0.5m x 0.5m. The structures are composed of three layers, where the top layer is air with depth of 0.15m, and the bottom two layers are ground material with a total depth of 0.35m. The source is located 0.1m above the ground and emits a standard Ricker wavelet source with center frequency of 1GHz. The depth of the second ground layer d2 is sampled from a uniform distribution U(0.1, 0.3) and the depth of the first ground layer is d1 = 0.35 – d2. The first ground layer has a permittivity sampled from U(3, 5) and the second ground layer has permittivity sampled from U(5,10). Two cylinders are embedded int eh second ground layer. One cylinder is composed of air (permittivity 1), whereas the permittivity of the second cylinder is sampled from a uniform distribution U(3,10). Both cylinders have radii sampled from U(0.03, 0.06). From the time domain data generated by gprMax, we apply the Fourier transform and extract the wavefields with frequencies within the [0.5GHz, 1.5GHz] band discretized over 50 frequencies. <strong>At a Glance</strong> The size of the unzipped dataset is ~1.72GB The data directory contains both the freespace response as well as the total wavefield measured at every pixel in the computational domain. The complex frequency coefficients of the source wavelet are also provided. Two trained models are provided in the forward_model sub-directory, one model corresponds to the vanilla FNO architecture with 10 layers and the other model corresponds to the proposed BornFNO architecture also with 10 layers. A pretrained autoencoder is also provided under the priors sub-directory. <strong>Other Resources</strong> Pytorch code for training the models and solving the inverse problem is available at https://github.com/merlresearch/DeepBornFNO. <strong>Citation</strong> If you use MERL-GPR in your research, please cite our paper: <pre><code>@InProceedings{ Zhao_2023ICASSP, author = {Qingqing Zhao and Yanting Ma and Petros Boufounos and Saleh Nabi and Hassan Mansour}, title = {Deep Born Operator Learning for Reflection Tomographic Imaging}, booktitle = {Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, year = 2023, month = June } </code></pre> <strong>Copyright and License</strong> The MERL-GPR dataset is released under CC-BY-SA-4.0 license. All data: <pre><code>Created by Mitsubishi Electric Research Laboratories (MERL), 2023 SPDX-License-Identifier: CC-BY-SA-4.0</code></pre>
DOI: 10.5281/zenodo.8145083
title: MERL Ground Penetrating Radar Dataset (MERL-GPR)

description: MERL-GPR is a simulated ground penetrating radar dataset generated using the open-source finite difference time domain tool for electromagnetic simulation gprMax. The dataset consists of 400 two dimensional underground structures with a domain size of 0.5m x 0.5m. The structures are composed of three layers, where the top layer is air with depth of 0.15m, and the bottom two layers are ground material with a total depth of 0.35m. The source is located 0.1m above the ground and emits a standard Ricker wavelet source with center frequency of 1GHz. The depth of the second ground layer d2 is sampled from a uniform distribution U(0.1, 0.3) and the depth of the first ground layer is d1 = 0.35 – d2. The first ground layer has a permittivity sampled from U(3, 5) and the second ground layer has permittivity sampled from U(5,10). Two cylinders are embedded int eh second ground layer. One cylinder is composed of air (permittivity 1), whereas the permittivity of the second cylinder is sampled from a uniform distribution U(3,10). Both cylinders have radii sampled from U(0.03, 0.06). From the time domain data generated by gprMax, we apply the Fourier transform and extract the wavefields with frequencies within the [0.5GHz, 1.5GHz] band discretized over 50 frequencies. <strong>At a Glance</strong> The size of the unzipped dataset is ~1.72GB The data directory contains both the freespace response as well as the total wavefield measured at every pixel in the computational domain. The complex frequency coefficients of the source wavelet are also provided. Two trained models are provided in the forward_model sub-directory, one model corresponds to the vanilla FNO architecture with 10 layers and the other model corresponds to the proposed BornFNO architecture also with 10 layers. A pretrained autoencoder is also provided under the priors sub-directory. <strong>Other Resources</strong> Pytorch code for training the models and solving the inverse problem is available at https://github.com/merlresearch/DeepBornFNO. <strong>Citation</strong> If you use MERL-GPR in your research, please cite our paper: <pre><code>@InProceedings{ Zhao_2023ICASSP, author = {Qingqing Zhao and Yanting Ma and Petros Boufounos and Saleh Nabi and Hassan Mansour}, title = {Deep Born Operator Learning for Reflection Tomographic Imaging}, booktitle = {Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, year = 2023, month = June } </code></pre> <strong>Copyright and License</strong> The MERL-GPR dataset is released under CC-BY-SA-4.0 license. All data: <pre><code>Created by Mitsubishi Electric Research Laboratories (MERL), 2023 SPDX-License-Identifier: CC-BY-SA-4.0</code></pre>
DOI: 10.6084/m9.figshare.18316304
title: (Table S12) PDXEDEPMAP gene essentiality scores

description: Predicted gene essentiality of PDX models
DOI: 10.6084/m9.figshare.18316304.v2
title: (Table S10) PDXEDEPMAP gene essentiality scores

description: Predicted gene essentiality of PDX models
DOI: 10.5683/sp/gubpaj
title: Hockey Night in Canada, 2014

description: This survey examines Canadian’s opinion of the new Hockey Night in Canada format and on the role of hockey in Canadian society and culture.
DOI: 10.6084/m9.figshare.21382026
title: (Table S14) GTEXDEPMAP gene essentiality scores

description: GTEXDEPMAP gene essentiality scores. Rows are gene models and columns are GTEX samples.
DOI: 10.6084/m9.figshare.21382026.v2
title: (Table S11) GTEXDEPMAP gene essentiality scores

description: GTEXDEPMAP gene essentiality scores. Rows are gene models and columns are GTEX samples.
DOI: 10.26165/juelich-data/hhnvq3
title: Replication Data for: First Search for Axion-Like Particles in a Storage Ring Using a Polarized Deuteron Beam

description: This data, provided in the form of root files, was collected in the experiment conducted in April 2019, to search for Axion-Like Particles (ALPs), at the Cooler Synchrotron (COSY) located at the Forschungszentrum Jülich.
DOI: 10.6084/m9.figshare.23681274
title: Drive Test Logfile for MRT Putrajaya Line 06/04/2023

description: Logfile for drive test conducted along MRT Putrajaya Line Railway Track. Contain information on RSRP, RSRQ, RSSI, SNR, CQI and other contextual data
DOI: 10.34740/kaggle/ds/3515261
title: UCI Bike Sharing Data
DOI: 10.18434/mds2-2598
title: NIST Infiltration Correlations for DOE Prototype Commercial Buildings
DOI: 10.5281/zenodo.8144524
title: Sniffles2 supporting matetial: VCF

description: VCF showing the structural variants called by Sniffles and other methods (cuteSV, sniffles1, pbsv, svim, manta, OGM) that are used in the manuscript.<br> Samples included are: GIAB v0.6 and CMRG (HG002) HG002, HG003, HG004 and trio merge MSA-ONT germline, MSA-ONT mosaic, MSA-ILLUMINA, MSA-OGM (Bionano) COLO829 germline (ONT, Revio), COLO829 mosaic (ONT, Revio), COLO289BL germline (ONT, Revio), COLO289-merge germline, COLO289-merge mosaic
DOI: 10.5281/zenodo.8144523
title: Sniffles2 supporting matetial: VCF

description: VCF showing the structural variants called by Sniffles and other methods (cuteSV, sniffles1, pbsv, svim, manta, OGM) that are used in the manuscript.<br> Samples included are: GIAB v0.6 and CMRG (HG002) HG002, HG003, HG004 and trio merge MSA-ONT germline, MSA-ONT mosaic, MSA-ILLUMINA, MSA-OGM (Bionano) COLO829 germline (ONT, Revio), COLO829 mosaic (ONT, Revio), COLO289BL germline (ONT, Revio), COLO289-merge germline, COLO289-merge mosaic
DOI: 10.5281/zenodo.8145164
title: saccharina_sessilis_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.8145163
title: saccharina_sessilis_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.8145141
title: Test SpeX data for SpeXtool and pyspextool

description: This zip directory contains SpeX data for two modes and two different instrument configurations, that can be used for testing either SpeXtool or pyspextool: spex-prism: prism data from original SpeX instrument from 2003 May 21 program 2003A013 (PI Burgasser) spex-SXD: SXD data from original SpeX instrument 2003 Jul 7 program 2003A098 (PI Rayner) uspex-prism: prism data from upgraded SpeX instrument from 2022 Oct 19 program 2022B046 (PI Theissen) spex-SXD: SXD data from upgraded SpeX instrument from 2015 June 3 program 2015A078 (PI Rayner) These folders contain both raw data files ("data"), processed data files ("cals", "proc") and quality assurance files ("qa") based on a beta version of pyspextool. The most recent version of pyspextool can be downloaded at https://github.com/pyspextool/pyspextool
DOI: 10.5281/zenodo.8145140
title: Test SpeX data for SpeXtool and pyspextool

description: This zip directory contains SpeX data for two modes and two different instrument configurations, that can be used for testing either SpeXtool or pyspextool: spex-prism: prism data from original SpeX instrument from 2003 May 21 program 2003A013 (PI Burgasser) spex-SXD: SXD data from original SpeX instrument 2003 Jul 7 program 2003A098 (PI Rayner) uspex-prism: prism data from upgraded SpeX instrument from 2022 Oct 19 program 2022B046 (PI Theissen) spex-SXD: SXD data from upgraded SpeX instrument from 2015 June 3 program 2015A078 (PI Rayner) These folders contain both raw data files ("data"), processed data files ("cals", "proc") and quality assurance files ("qa") based on a beta version of pyspextool. The most recent version of pyspextool can be downloaded at https://github.com/pyspextool/pyspextool
DOI: 10.6084/m9.figshare.23681310
title: Table SA. <em>Shewanella </em>genomes dataset.

description: <em>Shewanella </em>genomes dataset
DOI: 10.6084/m9.figshare.23681310.v1
title: Table SA. <em>Shewanella </em>genomes dataset.

description: <em>Shewanella </em>genomes dataset
DOI: 10.25345/c57m0497z
title: MassIVE MSV000092438 - Proteome profiling of maize pils6 mutant
title: Proteomic profiling of pils6-1 (mu1047700) and W22 (WIldtype) roots was performed in the presence and absence of auxin treatment (10 uM IAA) for 1 hour. Proteins were extracted and processed using the Phenol-FASP method described in https://doi.org/10.1002/pmic.201800220. Samples were TMT labeled as follows: WT M_R1+126, WT M_R2+127N, WT M_R3+127C, POOLEDSamples+128N, WT IAA_R1+128C, WT IAA_R2+129N, WT IAA_R3+129C, WT IAA_R4+130N, pils6 M_R1+130C, pils6 M_R2+131N, pils6 M_R3+131C, pils6 M_R4+132N, pils6 IAA_R1+132C, pils6 IAA_R2+133N, pils6 IAA_R3+133C, pils6 IAA_R4+134N.
DOI: 10.6084/m9.figshare.3761562.v2645
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.23681328
title: FASTQ files, pig, fecal sample.

description: This submission comprises FASTQ files from a study conducted by the Department of Animal and Dairy Science at the University of Georgia. The files contain 16s paired-end sequencing data, each sequence being 250 nucleotides long, obtained from the microbiome of 93 fecal samples from swine. This meticulous dataset enables intricate genomic analyses and offers a valuable resource for further research.
DOI: 10.5281/zenodo.8144554
title: Tulane_Minibasin_Experiments_2023

description: Suite of experiments that explore the influence of input discharge rate and minibasin shape on the fluid and sediment transport dynamics of turbidity currents. TDWB-21-1 and 21-4 represent mid-flux conditions and circular basins. TDWB-21-2 represents low flux condition and circular basin. TDWB-21-3 represents high flux condition and circular basin. TDWB-21-5 represents mid-flux condition and long but narrow basin. TDWB-21-6 represents mid-flux condition and short but wide basin.
DOI: 10.5281/zenodo.8144553
title: Tulane_Minibasin_Experiments_2023

description: Suite of experiments that explore the influence of input discharge rate and minibasin shape on the fluid and sediment transport dynamics of turbidity currents. TDWB-21-1 and 21-4 represent mid-flux conditions and circular basins. TDWB-21-2 represents low flux condition and circular basin. TDWB-21-3 represents high flux condition and circular basin. TDWB-21-5 represents mid-flux condition and long but narrow basin. TDWB-21-6 represents mid-flux condition and short but wide basin.
DOI: 10.5281/zenodo.8145200
title: The GALEX-Gaia-EDR3 Catalogue of Single and Binary White Dwarfs

description: We present a catalogue of white dwarf candidates constructed from the GALEX and Gaia EDR3 catalogues.<br> The catalogue contains 332,111 candidate binary white dwarf systems and 111,996 candidate single white dwarfs. Where available, the catalogue is augmented with photometry from Pan-STARRS DR1, SDSS DR12 and classifications from StarHorse. We fit photometric data with modeled white dwarf cooling sequences to derive mass, age and effective temperature of the white dwarf as well as mass estimates for the companion. We test our classifications against StarHorse, the Gentile-Fusillo Gaia EDR3 catalogue, and white-dwarf-main-sequence binaries identified in SDSS DR12. This catalogue provides a unique probe of the binarity of white dwarfs as well as the abundance of white-dwarf giant binaries and large mass-ratio stellar binaries which are difficult to probe otherwise.
description: Empty entries are filled with 99.9 or 99.0.
DOI: 10.5281/zenodo.8145199
title: The GALEX-Gaia-EDR3 Catalogue of Single and Binary White Dwarfs

description: We present a catalogue of white dwarf candidates constructed from the GALEX and Gaia EDR3 catalogues.<br> The catalogue contains 332,111 candidate binary white dwarf systems and 111,996 candidate single white dwarfs. Where available, the catalogue is augmented with photometry from Pan-STARRS DR1, SDSS DR12 and classifications from StarHorse. We fit photometric data with modeled white dwarf cooling sequences to derive mass, age and effective temperature of the white dwarf as well as mass estimates for the companion. We test our classifications against StarHorse, the Gentile-Fusillo Gaia EDR3 catalogue, and white-dwarf-main-sequence binaries identified in SDSS DR12. This catalogue provides a unique probe of the binarity of white dwarfs as well as the abundance of white-dwarf giant binaries and large mass-ratio stellar binaries which are difficult to probe otherwise.
description: Empty entries are filled with 99.9 or 99.0.
DOI: 10.26093/cds/vizier.19030091
title: GAMA; Activity of emission-line systems in G23

description: VizieR online Data Catalogue associated with article published in journal Astronomical Journal (AAS) with title 'Galaxy and Mass Assembly (GAMA); A WISE Study of the Activity of Emission-line Systems in G23.' (bibcode: 2020ApJ...903...91Y)
DOI: 10.6084/m9.figshare.23671809
title: Dataset

description: The objective of the present study was to evaluate the ability of bioflocs to assimilate and transfer antioxidant compounds present in açaí <em>Euterpe oleracea </em>to juvenile <em>Penaeus vannamei</em> shrimps grown in a biofloc system. Juvenile shrimp were distributed into four treatments (control, 5, 20, and 80 mg açaí L-1), containing 31 shrimp/tank (90 L), and cultivated for 30 days. Every 24 h throughout the experimental period, the respective açaí concentrations were added directly to the cultivation water. The bioflocs and hepatopancreas lost their antioxidant capacity with increasing concentrations of açaí, however, lipid damage was mitigated after treatment with 20 mg of açaí L-1 (p &lt;0.05). The application of 20 mg açaí L-1 increased the mean values of the height and area of the anterior intestinal microvilli (p &lt; 0.05). Mortality and protein and lipid damage in shrimp muscle increased with daily administration of 80 mg açaí L-1 (p &lt; 0.05). It is concluded that the bioflocs were able to assimilate the antioxidants present in the açaí and transfer them to the shrimp, the administration of 20 mg açaí L-1 presented the best performance demonstrating the possibility of its application in the cultivation of <em>P. vannamei</em> in a biofloc system.
DOI: 10.6084/m9.figshare.23671809.v1
title: Dataset

description: The objective of the present study was to evaluate the ability of bioflocs to assimilate and transfer antioxidant compounds present in açaí <em>Euterpe oleracea </em>to juvenile <em>Penaeus vannamei</em> shrimps grown in a biofloc system. Juvenile shrimp were distributed into four treatments (control, 5, 20, and 80 mg açaí L-1), containing 31 shrimp/tank (90 L), and cultivated for 30 days. Every 24 h throughout the experimental period, the respective açaí concentrations were added directly to the cultivation water. The bioflocs and hepatopancreas lost their antioxidant capacity with increasing concentrations of açaí, however, lipid damage was mitigated after treatment with 20 mg of açaí L-1 (p &lt;0.05). The application of 20 mg açaí L-1 increased the mean values of the height and area of the anterior intestinal microvilli (p &lt; 0.05). Mortality and protein and lipid damage in shrimp muscle increased with daily administration of 80 mg açaí L-1 (p &lt; 0.05). It is concluded that the bioflocs were able to assimilate the antioxidants present in the açaí and transfer them to the shrimp, the administration of 20 mg açaí L-1 presented the best performance demonstrating the possibility of its application in the cultivation of <em>P. vannamei</em> in a biofloc system.
DOI: 10.6084/m9.figshare.23681379
title: DEPMAP predicted gene effect using expression only and multiomics model

description: CRISPR gene effect prediction using expression only and multiomics model
DOI: 10.15482/usda.adc/1529177
title: TERRA-REF Season 4 and 6 Sorghum phenotypes and agronomic metadata in BrAPI format: ARDN Products

description: ARDN (Agricultural Research Data Network) annotations for "TERRA-REF Season 4 and 6 Sorghum phenotypes and agronomic metadata in BrAPI format". The ARDN project (https://data.nal.usda.gov/ardn) is a network of datasets harmonized and aggregated using the ICASA vocabulary, as recommended by USDA NAL (https://data.nal.usda.gov/data-dictionary-examples) and described in detail here: www.tinyurl.com/icasa-mvl
ARDN provides dataset annotations which facilitate interoperability. For information on how to use ARDN annotations and other data products, see https://agmip.github.io/ARDN/ARDN_how.html.
This data represents a small subset of the TERRA-REF release available on Dryad (LeBauer et al 2020, https://doi.org/10.5061/dryad.4b8gtht99). In addition to harvested biomass for each cultivar, it includes plot location, planting date, harvest date, fertilizer application, genotype / accession names and metadata, and additional agronomic management metadata for a population of Sorghum bicolor evaluated over two growing seasons. Please refer to the parent dataset for additional information on experimental details.
DOI: 10.6084/m9.figshare.23681373
title: DEPMAP measured CRISPR effect

description: DEPMAP measured gene effect from DEPMAP portal
DOI: 10.15482/usda.adc/1529179
title: TERRA-REF Season 4 and 6 Sorghum phenotypes and agronomic metadata in BrAPI format

description: This data represents a small subset of the TERRA-REF release available on Dryad (LeBauer et al 2020, https://doi.org/10.5061/dryad.4b8gtht99). In addition to harvested biomass for each cultivar, it includes plot location, planting date, harvest date, fertilizer application, genotype / accession names and metadata, and additional agronomic management metadata for a population of Sorghum bicolor evaluated over two growing seasons. Please refer to the parent dataset for additional information on experimental details.
This dataset also contains an archive of software used to translate BrAPI formatted data into ARDN-compliant formats. The code and intermediate files used to demonstrate a run of the crop model DSSAT can be viewed on GitHub https://github.com/cct-datascience/ardn-terra-ref.
One way in which the data can be accessed is through a BrAPI-compliant endpoint at terraref.org/brapi. This dataset is a snapshot of the TERRA-REF BrAPI endpoint contents, representing the minimum data and metadata required to run a crop model. These BrAPI-compliant json files were downloaded from terraref.org/brapi. BrAPI is a data format widely used by plant breeders, and is described in Selby et al. 2019, https://doi.org/10.1093/bioinformatics/btz190
DOI: 10.15482/usda.adc/1529180
title: Floridan Aquifer Collaborative Engagement for Sustainability (FACETS) - Field trial data from Live Oak, Florida: ARDN products

description: ARDN (Agricultural Research Data Network) annotations for "Floridan Aquifer Collaborative Engagement for Sustainability (FACETS) - Field trial data from Live Oak, Florida". The ARDN project (https://data.nal.usda.gov/ardn) is a network of datasets harmonized and aggregated using a common vocabulary termed ICASA. ICASA is a recommended data dictionary by USDA NAL (https://data.nal.usda.gov/data-dictionary-examples) described in detail here:  www.tinyurl.com/icasa-mvl.
ARDN provides dataset annotations which facilitate interoperability. For information on how to use ARDN annotations and other data products, see https://agmip.github.io/ARDN/ARDN_how.html.
Research was conducted at the North Florida Research and Education Center - Suwannee Valley, located near Live Oak, Florida (30°18’22” N, 82°54’00” W). Corn, carrots, peanuts, and rye (cover crop) were grown on Hurricane, Chipley, and Blanton soil complexes that are all over 90% sand. They contain very little organic material or clays and have very low water holding capacity. The experimental design utilized a randomized complete block design with split plot that incorporated two fields with eight blocks (treatment replicates) and fifteen plots per block. The main plots contained four irrigation treatments, and the sub-plots contained three different nitrogen rates. The SMS irrigation treatment contained three additional nitrogen treatments. The plots were 12 m x 6 m separated by 6 m alleys. Each block was separated by a 12 m alley. The north field in the study (System 2) was a corn-cover crop-peanut-cover crop rotation, while the south field (System 1) was a corn-carrot-peanut-cover crop rotation. During each growing season, soil moisture was monitored using capacitance type soil moisture sensors, soil nitrogen was measured through bi-weekly soil samples at four depths, and biomass was collected four times with the final sample being collected just prior to harvest. Biomass included dry weight of separate plant tissues as well as Total Kjeldahl Nitrogen (TKN) and yield.