cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.11583/dtu.23093495.v1
title: Sparsely sampled planar sound field in a furnished room (Jabra - GN Audio)

description: This dataset consists of 136 Room Impulse Responses (RIRs) measured at Jabra offices in Ballerup, Denmark. These RIRs were obtained using a 1/4" GRAS microphone and a single KEF LS50 loudspeaker. The positions of both the microphone and loudspeaker were tracked using a Vicon motion capture system. The Vicon system is mounted on a rack close to the ceiling on a square rack. The tracking area depends on the camera orientation on the side of the tracked object. There are 8 cameras that are placed at the corners of the square and in the middle of the sides. The room was lightly damped and used for meetings and speech communication experiments. It was fully furnished during the measurement process, and the measurement positions were chosen randomly within an approximate 2.6$\times$2.3 m$^2$ space at the end of the room with both microphone and loudspeaker placed at the same height. The loudspeaker was placed in the middle of the room. From the 136 RIRs, 6 were measured in the nearfield of the loudspeaker. These positions are denoted as `ref_mic_grid' in the dataset. The layout of the data set can be seen in the figure 'Jabra_measurements.png'. <br> The room is of size 8m × 5m × 2.5m with an average reverberation time (T60) of 0.55 s. <br> The data are available as H5 (Hierarchical Data Formats) with the following structure: Dataset "Jabra data - HDF5 datastructure"<br> Dataset.attributes<br> └── fs (1) 32000 int<br> ├── loudspeaker_position (3x1) float64 ├── mic_grid (130x3) float64 ├── ref_mic_grid (6x3) float64 ├── ref_rirs (6x64000) float64 └── rirs(130x64000) float64 <br> Use with Matlab: https://mathworks.com/help/matlab/hdf5-files.html Use with Python: https://docs.h5py.org/en/stable/<br> This dataset is part of the project <em>Danish Sound Cluster </em>project titled "<strong>Physics-informed Neural Networks for Sound Field Reconstruction</strong>" [url]. Find more datasets here: Project Page
DOI: 10.11583/dtu.23093495
title: Sparsely sampled planar sound field in a furnished room (Jabra - GN Audio)

description: This dataset consists of 136 Room Impulse Responses (RIRs) measured at Jabra offices in Ballerup, Denmark. These RIRs were obtained using a 1/4" GRAS microphone and a single KEF LS50 loudspeaker. The positions of both the microphone and loudspeaker were tracked using a Vicon motion capture system. The Vicon system is mounted on a rack close to the ceiling on a square rack. The tracking area depends on the camera orientation on the side of the tracked object. There are 8 cameras that are placed at the corners of the square and in the middle of the sides. The room was lightly damped and used for meetings and speech communication experiments. It was fully furnished during the measurement process, and the measurement positions were chosen randomly within an approximate 2.6$\times$2.3 m$^2$ space at the end of the room with both microphone and loudspeaker placed at the same height. The loudspeaker was placed in the middle of the room. From the 136 RIRs, 6 were measured in the nearfield of the loudspeaker. These positions are denoted as `ref_mic_grid' in the dataset. The layout of the data set can be seen in the figure 'Jabra_measurements.png'. <br> The room is of size 8m × 5m × 2.5m with an average reverberation time (T60) of 0.55 s. <br> The data are available as H5 (Hierarchical Data Formats) with the following structure: Dataset "Jabra data - HDF5 datastructure"<br> Dataset.attributes<br> └── fs (1) 32000 int<br> ├── loudspeaker_position (3x1) float64 ├── mic_grid (130x3) float64 ├── ref_mic_grid (6x3) float64 ├── ref_rirs (6x64000) float64 └── rirs(130x64000) float64 <br> Use with Matlab: https://mathworks.com/help/matlab/hdf5-files.html Use with Python: https://docs.h5py.org/en/stable/<br> This dataset is part of the project <em>Danish Sound Cluster </em>project titled "<strong>Physics-informed Neural Networks for Sound Field Reconstruction</strong>" [url]. Find more datasets here: Project Page
DOI: 10.5281/zenodo.7304516
title: Lists of magnetopause and bow shock crossings, as measured by Juno/Waves and Juno/MAG.

description: Lists of magnetopause (boundary_crossings_caracteristics_MP.pdf, boundary_crossings_caracteristics_MP.csv) and bow shock crossings (boundary_crossings_caracteristics_BS.pdf, boundary_crossings_caracteristics_BS.csv), as measured by Juno/Waves and Juno/MAG (see below to download the files). <br> For each crossing, number of the crossing (MP#), day of the year (DOY), date (year/month/day format) and time (hours:minutes format) are indicated, as well as the boundary crossed (magnetopause in this case), the direction of the crossing (in: from the magnetosphere to the magnetosheath; out: from the magnetosheath to the magnetosphere). The column “Notes” indicates whether the magnetopause has potentially not been completely crossed (see Fig. 1c of the article). Position of the crossings are given in the Cartesian JSS (Jupiter-­‐De-­Spun-­Sun) and IAU (International Astronomical Union) coordinate systems, and IAU spherical coordinates system. Finally, the dynamic pressure of the solar wind, and the standoff distance of the magnetopause and the bow shock, derived from the model of Joy et al. (2002), are given in the last three columns. header = ['#', "Day of Year", "Date (year/month/day)", "Time (HH:MM)", "Boundary", "In/Out", "Notes", "x (JSS)", "y (JSS)", "z (JSS)", "x (IAU)", "y(IAU)", "z (IAU)", "r (IAU)", "theta (IAU)", "phi (IAU)", "Dynamic Pressure (nPa)", "Magnetopause Standoff Distance (Jovian radius)", "Bow Shock Standoff Distance (Jovian radius)"] A python function to read the lists is provided (read_boundary_crossings_list.py). Example: <pre><code class="language-python">from read_boundary_crossings_list import * (header, indice, date, boundary, direction_crossing, notes, xyz_jss, xyz_iau, rtp_iau, pdyn, standoff_dist_mp, standoff_dist_bs) = read_boundary_crossings_list("boundary_crossings_caracteristics_MP.csv")</code></pre> This dataset is linked to the following publication: Louis, C. K., Jackman, C. M., Hospodarsky, G., O’Kane Hackett, A., Devon-Hurley, E., Zarka, P., et al. (2023). Effect of a magnetospheric compression on Jovian radio emissions: In situ case study using Juno data. Journal of Geophysical Research: Space Physics, 128, e2022JA031155. https://doi.org/10.1029/2022JA031155
DOI: 10.5281/zenodo.7304517
title: Lists of magnetopause and bow shock crossings, as measured by Juno/Waves and Juno/MAG.

description: Lists of magnetopause (boundary_crossings_caracteristics_MP.pdf, boundary_crossings_caracteristics_MP.csv) and bow shock crossings (boundary_crossings_caracteristics_BS.pdf, boundary_crossings_caracteristics_BS.csv), as measured by Juno/Waves and Juno/MAG (see below to download the files). <br> For each crossing, number of the crossing (MP#), day of the year (DOY), date (year/month/day format) and time (hours:minutes format) are indicated, as well as the boundary crossed (magnetopause in this case), the direction of the crossing (in: from the magnetosphere to the magnetosheath; out: from the magnetosheath to the magnetosphere). The column “Notes” indicates whether the magnetopause has potentially not been completely crossed (see Fig. 1c of the article). Position of the crossings are given in the Cartesian JSS (Jupiter-­‐De-­Spun-­Sun) and IAU (International Astronomical Union) coordinate systems, and IAU spherical coordinates system. Finally, the dynamic pressure of the solar wind, and the standoff distance of the magnetopause and the bow shock, derived from the model of Joy et al. (2002), are given in the last three columns. header = ['#', "Day of Year", "Date (year/month/day)", "Time (HH:MM)", "Boundary", "In/Out", "Notes", "x (JSS)", "y (JSS)", "z (JSS)", "x (IAU)", "y(IAU)", "z (IAU)", "r (IAU)", "theta (IAU)", "phi (IAU)", "Dynamic Pressure (nPa)", "Magnetopause Standoff Distance (Jovian radius)", "Bow Shock Standoff Distance (Jovian radius)"] A python function to read the lists is provided (read_boundary_crossings_list.py). Example: <pre><code class="language-python">from read_boundary_crossings_list import * (header, indice, date, boundary, direction_crossing, notes, xyz_jss, xyz_iau, rtp_iau, pdyn, standoff_dist_mp, standoff_dist_bs) = read_boundary_crossings_list("boundary_crossings_caracteristics_MP.csv")</code></pre> This dataset is linked to the following publication: Louis, C. K., Jackman, C. M., Hospodarsky, G., O’Kane Hackett, A., Devon-Hurley, E., Zarka, P., et al. (2023). Effect of a magnetospheric compression on Jovian radio emissions: In situ case study using Juno data. Journal of Geophysical Research: Space Physics, 128, e2022JA031155. https://doi.org/10.1029/2022JA031155
DOI: 10.4121/13516592.v1
title: Data belonging to the publication "High precipitation rates characterize biomineralization in the foraminifer Ammonia beccarii."

description: This entry contains the original NanoSIMS maps that were used for the publication "High precipitation rates characterize biomineralization in foraminifera". The maps are provided as csv.files and were not processed before uploading here.
DOI: 10.4121/13516592
title: Data belonging to the publication "High precipitation rates characterize biomineralization in the foraminifer Ammonia beccarii."

description: This entry contains the original NanoSIMS maps that were used for the publication "High precipitation rates characterize biomineralization in foraminifera". The maps are provided as csv.files and were not processed before uploading here.
DOI: 10.57841/casdc.0002577
title: 氧化铝/石墨-硫酸钡层状复合材料的摩擦学性能及润滑机理
DOI: 10.5281/zenodo.8347059
title: TexBiG Dataset for Analysing Complex Document Layouts in the Digital Humanities

description: This is the dataset for the paper "A Dataset for Analysing Complex Document Layouts in the Digital Humanities and its Evaluation with Krippendorff ’s Alpha" in its second version, containing an update of the test images (without annotations) from the paper "Drawing the Same Bounding Box Twice? Coping Noisy Annotations in Object Detection with Repeated Labels". Organization of the dataset is also updated to make it easier to use. TexBiG (from the German Text-Bild-Gefüge, meaning Text-Image-Structure) is a document layout analysis dataset for historical documents in the late 19th and early 20th century. The dataset provides instance segmentation (bounding boxes and polygons/masks) annotations for 19 different classes with more then 52.000 instances. The added test images can be used to make submission on the leaderboard on EvalAI. The annotation guideline can be found in the first of the dataset.
DOI: 10.5281/zenodo.6885143
title: TexBiG Dataset for Analysing Complex Document Layouts in the Digital Humanities

description: This is the dataset for the paper "A Dataset for Analysing Complex Document Layouts in the Digital Humanities and its Evaluation with Krippendorff ’s Alpha" in its second version, containing an update of the test images (without annotations) from the paper "Drawing the Same Bounding Box Twice? Coping Noisy Annotations in Object Detection with Repeated Labels". Organization of the dataset is also updated to make it easier to use. TexBiG (from the German Text-Bild-Gefüge, meaning Text-Image-Structure) is a document layout analysis dataset for historical documents in the late 19th and early 20th century. The dataset provides instance segmentation (bounding boxes and polygons/masks) annotations for 19 different classes with more then 52.000 instances. The added test images can be used to make submission on the leaderboard on EvalAI. The annotation guideline can be found in the first of the dataset.
DOI: 10.57841/casdc.0002578
title: 燃油稀释对柴油机油性能影响规律研究
DOI: 10.4121/16722949
title: Dataset to plot neutral stability curve for symmetric bifurcations

description: This is dataset to plot neutral stability curve for symmetric river bifurcation in Figure 6 (Iwantoro et al., subm) produced by Matlab. There are three sets of data:1. Shields stress vs w/hThis dataset is to produce the plot that indicates the stability threshold of the stability of symmetric bifurcation for different tidal influence in the range of ebb-averaged Shields stress and width-to-depth ratio.2. Shields stress vs u<sub>2</sub>u<sub>0</sub>This dataset is to produce the plot that indicates the stability threshold of the stability of symmetric bifurcation for upstream channel width-to-depth ratio of 30, 50 and 70 in the range of ebb averaged Shields stress and tidal influenced. The tidal influence is indicated by tidal flow amplitude of tide-averaged flow at bifurcation.3. Asymmetry index vs shields stressThis dataset is to produce the plot to indicate the asymmetry of bifurcations in a range of Shields stress for different tidal influence.<br><br>
DOI: 10.4121/16722949.v1
title: Dataset to plot neutral stability curve for symmetric bifurcations

description: This is dataset to plot neutral stability curve for symmetric river bifurcation in Figure 6 (Iwantoro et al., subm) produced by Matlab. There are three sets of data:1. Shields stress vs w/hThis dataset is to produce the plot that indicates the stability threshold of the stability of symmetric bifurcation for different tidal influence in the range of ebb-averaged Shields stress and width-to-depth ratio.2. Shields stress vs u<sub>2</sub>u<sub>0</sub>This dataset is to produce the plot that indicates the stability threshold of the stability of symmetric bifurcation for upstream channel width-to-depth ratio of 30, 50 and 70 in the range of ebb averaged Shields stress and tidal influenced. The tidal influence is indicated by tidal flow amplitude of tide-averaged flow at bifurcation.3. Asymmetry index vs shields stressThis dataset is to produce the plot to indicate the asymmetry of bifurcations in a range of Shields stress for different tidal influence.<br><br>
DOI: 10.5281/zenodo.8382566
title: Dependency Taxonomy in Microservice Systems

description: This dataset encompasses the following components: - Data pertaining to the Systematic Literature Review process. - Dependency Artifacts and the corresponding outcomes of the taxonomy process steps.
DOI: 10.5281/zenodo.8382565
title: Dependency Taxonomy in Microservice Systems

description: This dataset encompasses the following components: - Data pertaining to the Systematic Literature Review process. - Dependency Artifacts and the corresponding outcomes of the taxonomy process steps.
DOI: 10.5281/zenodo.7919668
title: The linear baroclinic model ouput forced by Indian summer monsoonal diabatic heating.

description: The linear baroclinic model (Watanabe and Kimoto 2000, 2001) ouput forced by Indian summer monsoonal diabatic heating. The LBM source code can be requested via https://ccsr.aori.u-tokyo.ac.jp/~lbm/sub/lbm.html. Forcing file: ISM_forcing.nc<br> Simulation output files: LBM_T42_xxx.nc; each file denotes different monthly mean atmohpsheric basic state is used from May to September. The data are generated and analyzed in the following study: Li, S., Sato, T., Nakamura, T. <em>et al.</em> East Asian summer rainfall stimulated by subseasonal Indian monsoonal heating. <em>Nat Commun</em> <strong>14</strong>, 5932 (2023). https://doi.org/10.1038/s41467-023-41644-5
DOI: 10.5281/zenodo.7919667
title: The linear baroclinic model ouput forced by Indian summer monsoonal diabatic heating.

description: The linear baroclinic model (Watanabe and Kimoto 2000, 2001) ouput forced by Indian summer monsoonal diabatic heating. The LBM source code can be requested via https://ccsr.aori.u-tokyo.ac.jp/~lbm/sub/lbm.html. Forcing file: ISM_forcing.nc<br> Simulation output files: LBM_T42_xxx.nc; each file denotes different monthly mean atmohpsheric basic state is used from May to September. The data are generated and analyzed in the following study: Li, S., Sato, T., Nakamura, T. <em>et al.</em> East Asian summer rainfall stimulated by subseasonal Indian monsoonal heating. <em>Nat Commun</em> <strong>14</strong>, 5932 (2023). https://doi.org/10.1038/s41467-023-41644-5
DOI: 10.5281/zenodo.7212810
title: Ambisonic-Binaural

description: A dataset collected for ambisonic-based binaural rendering. The recordings are collected at ByteDance in Nov. 2021. We recorded 31 minutes and 18 minutes of audios for training and testing respectively. These audios are paired ambisonics and binaurals.
DOI: 10.5281/zenodo.7212782
title: Ambisonic-Binaural

description: A dataset collected for ambisonic-based binaural rendering. The recordings are collected at ByteDance in Nov. 2021. We recorded 31 minutes and 18 minutes of audios for training and testing respectively. These audios are paired ambisonics and binaurals.
DOI: 10.5519/qd.6823jcxy
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (9814 records)
DOI: 10.34740/kaggle/dsv/6553176
title: AutoXGB
DOI: 10.34740/kaggle/dsv/6553177
title: OnlineFree
DOI: 10.6084/m9.figshare.24204045
title: <b>Validity and Reliability Evidence and Norms of the Spanish Version of the Sexual Inhibition/Sexual Excitation Scales-Short Form</b>

description: <b>Validity and Reliability Evidence and Norms of the Spanish Version of the Sexual Inhibition/Sexual Excitation Scales-Short Form</b>This study was approved by the Ethics Committee in Human Research at the University of Granada.
DOI: 10.5281/zenodo.8382597
title: Optical and Tactile Measurements on SiC Sample Defects - Dataset

description: No description provided.
DOI: 10.5281/zenodo.8382596
title: Optical and Tactile Measurements on SiC Sample Defects - Dataset

description: No description provided.
DOI: 10.57841/casdc.0002579
title: 机械密封在干摩擦状态下的摩擦界面热力耦合分析
DOI: 10.6084/m9.figshare.22203211
title: <b>Methane oxidation minimizes emissions and offsets to carbon burial in mangroves</b>

description: Observations from six seawater-dominated mangrove tidal creeks across a latitudinal gradient in Australia. Field studies were undertaken in pristine mangrove tidal creeks on the northern, eastern and southern Australian coastlines over a latitudinal range covering all climatic regions relevant to mangroves. Field study sites had low lying catchments (&lt; 5.5 m) and had minimal freshwater inputs with no riverine water sources. Site characteristics followed a latitudinal trend, with an overall increased average rainfall, temperature, and mangrove diversity at lower latitudes.<br>Dissolved CO2 and CH4 concentrations and δ13C isotopes were measured near the mouth of mangrove tidal creeks at the six field sites. High precision concentrations and isotopes were measured using a cavity ring down spectrometer (CRDS) (Picarro G2201-I) coupled with a showerhead exchanger with a flow rate of approximately 2.8 L min-1. Concentrations and isotopes of dissolved gases were measured at one second intervals and averaged over one minute intervals. High resolution measurements of water depth and current velocity were taken at the same sites using an acoustic doppler current profiler (SonTek Argonaut), with measurements taken at one second intervals and averaged over one minute intervals. Additional water parameters (salinity, temperature and luminescent dissolved oxygen) were measured at one minute intervals using a multi-parameter water quality sonde (Hydrolab DS 5X).<br>Dissolved CH4 concentrations were calculated from <i>p</i>CH4 using the temperature and salinity dependant solubility equations of Wiesenburg and Guinasso (1979). Emissions of CH4 (FCH4) from surface waters were calculated according to:FCH4 = <i>k</i>α(Δ<i>p</i>CH4) (Eq. 1)where <i>k</i> is the transfer velocity, α is the temperature and salinity solubility and Δ<i>p</i>CH4 is the difference between atmospheric <i>p</i>CH4 and water column <i>p</i>CH4. The gas transfer velocity was calculated using four different empirical relationships in order to provide ranges of estimations.In addition to the raw data of the continuous, real time measurements, we are also including the raw data of our compilation used to make the Figures 1A, 1B and 4 (Global upscaling of annual CH4 emissions and organic carbon burial in sediments of mangroves).
DOI: 10.6084/m9.figshare.22203211.v1
title: <b>Methane oxidation minimizes emissions and offsets to carbon burial in mangroves</b>

description: Observations from six seawater-dominated mangrove tidal creeks across a latitudinal gradient in Australia. Field studies were undertaken in pristine mangrove tidal creeks on the northern, eastern and southern Australian coastlines over a latitudinal range covering all climatic regions relevant to mangroves. Field study sites had low lying catchments (&lt; 5.5 m) and had minimal freshwater inputs with no riverine water sources. Site characteristics followed a latitudinal trend, with an overall increased average rainfall, temperature, and mangrove diversity at lower latitudes.<br>Dissolved CO2 and CH4 concentrations and δ13C isotopes were measured near the mouth of mangrove tidal creeks at the six field sites. High precision concentrations and isotopes were measured using a cavity ring down spectrometer (CRDS) (Picarro G2201-I) coupled with a showerhead exchanger with a flow rate of approximately 2.8 L min-1. Concentrations and isotopes of dissolved gases were measured at one second intervals and averaged over one minute intervals. High resolution measurements of water depth and current velocity were taken at the same sites using an acoustic doppler current profiler (SonTek Argonaut), with measurements taken at one second intervals and averaged over one minute intervals. Additional water parameters (salinity, temperature and luminescent dissolved oxygen) were measured at one minute intervals using a multi-parameter water quality sonde (Hydrolab DS 5X).<br>Dissolved CH4 concentrations were calculated from <i>p</i>CH4 using the temperature and salinity dependant solubility equations of Wiesenburg and Guinasso (1979). Emissions of CH4 (FCH4) from surface waters were calculated according to:FCH4 = <i>k</i>α(Δ<i>p</i>CH4) (Eq. 1)where <i>k</i> is the transfer velocity, α is the temperature and salinity solubility and Δ<i>p</i>CH4 is the difference between atmospheric <i>p</i>CH4 and water column <i>p</i>CH4. The gas transfer velocity was calculated using four different empirical relationships in order to provide ranges of estimations.In addition to the raw data of the continuous, real time measurements, we are also including the raw data of our compilation used to make the Figures 1A, 1B and 4 (Global upscaling of annual CH4 emissions and organic carbon burial in sediments of mangroves).
DOI: 10.25345/c50c4sw00
title: MassIVE MSV000092972 - Ttttttttttttttttttttttttttttttttttttttteszt8
title: trallalalalallalltrallalallallallaltrallaalallalal
DOI: 10.17189/1519543
title: MRO SHARAD REDUCED DATA RECORD V1.0