cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6941636
title: Gradients4-TN397-Optics-LISST-ACS-ECO_2022-04-07

description: Cruise Name: Gradients 4 , TN397 Vessel: R/V Thompson Funding: Simons Collaboration on Ocean Processes and Ecology (SCOPE) Dataset description: This dataset was collected on the R/V Thompson during the Gradients IV cruise which departed from San Diego, CA and ended in Honolulu, HI. A transect was performed on the 140 degree longitude line from roughly 19 degrees N to 2.5 degrees S before heading to Honolulu. Three biooptical instruments were plumbed to the underway uncontaminated seawater (intake depth 8m). Data for each instrument were averaged to the minute and matched to a timestamp on the minute. LISST: Filtered values (&lt;0.2 um) removed from all data. The summed volume concentration of particles (in uL/L), the standard LISST output, is presented for 3 size ranges: 1.25-2 µm, 2-20 µm, and 20-100 µm. Particle volume concentration can be converted to particle concentration by assuming spherical particles. Larger size classes are excluded due to low detection limits and scattering at density gradients. Note that data have not been processed to remove outliers. AC-S: Filtered values (&lt;0.2 um) removed from all data (see White et al., 2017, GRL); data corrected for residual temperature and scattering; AC-S chl a concentrations obtained from a Gaussian fit over absorbance spectra in the red portion of the spectrum, assuming in vivo chl-a specific absorption of 0.0203 m2/mg at 674 nm. ECO: filtered values (&lt;0.2 um) removed from chl and volume scattering data; chl fluorescence converted to mg/m3 using factory calibrations, and corrected to HPLC chlorophyll values. CDOM not included due to faulty channel.
DOI: 10.5281/zenodo.6941635
title: Gradients4-TN397-Optics-LISST-ACS-ECO_2022-04-07

description: Cruise Name: Gradients 4 , TN397 Vessel: R/V Thompson Funding: Simons Collaboration on Ocean Processes and Ecology (SCOPE) Dataset description: This dataset was collected on the R/V Thompson during the Gradients IV cruise which departed from San Diego, CA and ended in Honolulu, HI. A transect was performed on the 140 degree longitude line from roughly 19 degrees N to 2.5 degrees S before heading to Honolulu. Three biooptical instruments were plumbed to the underway uncontaminated seawater (intake depth 8m). Data for each instrument were averaged to the minute and matched to a timestamp on the minute. LISST: Filtered values (&lt;0.2 um) removed from all data. The summed volume concentration of particles (in uL/L), the standard LISST output, is presented for 3 size ranges: 1.25-2 µm, 2-20 µm, and 20-100 µm. Particle volume concentration can be converted to particle concentration by assuming spherical particles. Larger size classes are excluded due to low detection limits and scattering at density gradients. Note that data have not been processed to remove outliers. AC-S: Filtered values (&lt;0.2 um) removed from all data (see White et al., 2017, GRL); data corrected for residual temperature and scattering; AC-S chl a concentrations obtained from a Gaussian fit over absorbance spectra in the red portion of the spectrum, assuming in vivo chl-a specific absorption of 0.0203 m2/mg at 674 nm. ECO: filtered values (&lt;0.2 um) removed from chl and volume scattering data; chl fluorescence converted to mg/m3 using factory calibrations, and corrected to HPLC chlorophyll values. CDOM not included due to faulty channel.
DOI: 10.5281/zenodo.6941639
title: Gradients4-TN397-LISST-DEEP-Profiles_2022-04-28

description: Cruise Name: Gradients 4 , TN397 Vessel: R/V Thompson Funding: Simons Collaboration on Ocean Processes and Ecology (SCOPE) Dataset description:. This dataset was collected on the R/V Thompson during the Gradients IV cruise which departed from San Diego, CA and ended in Honolulu, HI. A transect was performed on the 140 degree longitude line from roughly 19 degrees N to 2.5 degrees S before heading to Honolulu. A Sequoia Scientific LISST-DEEP instrument was mounted to the R/V Thompson's rosette and ctd system and operated during CTD casts. The data presented here are blank-corrected using a deepwater background scattering calibration, and binned in 2-meter bins from 2 to 200m depths. The summed volume concentration of particles (in uL/L), the standard LISST output, is presented for 3 size ranges: 1.25-2 µm, 2-20 µm, and 20-100 µm. Particle volume concentration can be converted to particle concentration by assuming spherical particles. The total particle concentration (#/L) is calculated for particles with a diameter between 1.25 and 100 um. Larger size classes are excluded due to low detection limits and scattering at density gradients. Note that data have not been processed to remove outliers.
DOI: 10.5281/zenodo.6941638
title: Gradients4-TN397-LISST-DEEP-Profiles_2022-04-28

description: Cruise Name: Gradients 4 , TN397 Vessel: R/V Thompson Funding: Simons Collaboration on Ocean Processes and Ecology (SCOPE) Dataset description:. This dataset was collected on the R/V Thompson during the Gradients IV cruise which departed from San Diego, CA and ended in Honolulu, HI. A transect was performed on the 140 degree longitude line from roughly 19 degrees N to 2.5 degrees S before heading to Honolulu. A Sequoia Scientific LISST-DEEP instrument was mounted to the R/V Thompson's rosette and ctd system and operated during CTD casts. The data presented here are blank-corrected using a deepwater background scattering calibration, and binned in 2-meter bins from 2 to 200m depths. The summed volume concentration of particles (in uL/L), the standard LISST output, is presented for 3 size ranges: 1.25-2 µm, 2-20 µm, and 20-100 µm. Particle volume concentration can be converted to particle concentration by assuming spherical particles. The total particle concentration (#/L) is calculated for particles with a diameter between 1.25 and 100 um. Larger size classes are excluded due to low detection limits and scattering at density gradients. Note that data have not been processed to remove outliers.
DOI: 10.18434/m32086
title: MCV QoE Microcontroller Firmware 

description: Code for the TI MSP4030F5529LP board for PTT application with MCV QoE software
DOI: 10.6073/pasta/c560928d61e21ae42b32877160099554
title: SBC LTER: Time series of quarterly NetCDF files of kelp biomass in the canopy from Landsat 5, 7 and 8, since 1984 (ongoing)

description: This data file represents a time series of canopy area of giant kelp, Macrocystis pyrifera, and bull kelp, Nereocystis luetkeana, and canopy biomass of giant kelp derived from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), and Landsat 9 Operational Land Imager 2 satellite imagery, along with relevant metadata. The kelp canopy is composed of the portions of fronds and stipes floating on the surface of the water. Canopy area (m) data are given for individual 30 x 30 meter pixels for all coastal areas of Baja California, Mexico, California, Oregon, and the outer coast of Washington (including offshore islands). Biomass data (wet weight, kg) are given for individual 30 x 30 meter pixels in the coastal areas extending from near Ano Nuevo, CA through the southern range limit in Baja California (including offshore islands), representing the range where giant kelp is the dominant canopy forming species. Data were derived from the three Landsat sensors listed above. Observations are made on a 16 day repeat cycle, for each instrument, but the temporal coverage is irregular because of cloud cover, instrument failure, and the mission length of each sensor (TM: 1984 – 2011, ETM+: 1999 – present, OLI: 2013 – present). Estimates of canopy area are derived from the fractional cover of kelp canopy determined from satellite surface reflectance. Estimates of kelp canopy biomass are derived from the relationship between giant kelp fractional cover determined from satellite surface reflectance and empirical measurements of giant kelp canopy biomass in long-term SBC LTER study plots obtained using SCUBA. The different Landsat sensors were calibrated to each other using simulated Landsat data derived from hyperspectral imagery. Missing data due to the ETM+ scan line corrector error were filled using a synchrony-based gap filling method. Data are organized into a single NetCDF file and contain the quarterly area and biomass means for each Landsat pixel across the three sensors. Relevant metadata such as number of Landsat estimates from which the mean was derived, the number of estimates from each sensor, standard error for each quarterly estimate, spatial coordinates, and date are all included in the file. For assistance with the data, please contact sbclter@msi.ucsb.edu.
DOI: 10.5281/zenodo.6941002
title: Cheltenham Town 1932-1933 newspaper archive

description: Newspaper articles reporting on Cheltenham Town A.F.C. for the football season of 1932-1933. Articles cover the dates of 1932-04-01 to 1933-05-31. Articles are available as HTML files as well as a mix of jpeg and png scans of original articles and pictures. RIS file is available for import into reference management software. XML file available containing text of articles. The contents are considered to be public domain as it is over 70 years after the end of the year in which the work was created or first published.
DOI: 10.5281/zenodo.6111580
title: Cheltenham Town 1932-1933 newspaper archive

description: Newspaper articles reporting on Cheltenham Town A.F.C. for the football season of 1932-1933. Articles cover the dates of 1932-04-01 to 1933-05-31. Articles are available as HTML files as well as a mix of jpeg and png scans of original articles and pictures. RIS file is available for import into reference management software. XML file available containing text of articles. The contents are considered to be public domain as it is over 70 years after the end of the year in which the work was created or first published.
DOI: 10.6084/m9.figshare.19688043
title: Interictal high-density scalp EEG in focal epilepsy patients

description: This dataset includes de-identified interictal spike information in 20 focal epilepsy patients who became seizure-free after surgery. This dataset has been used and analyzed to study epilepsy sources and the results are reported in: Sun R, Sohrabpour A, Worrell GA, He B: “Deep Neural Networks Constrained by Neural Mass Models Improve Electrophysiological Source Imaging of Spatiotemporal Brain Dynamics.” <em>Proceedings of the National Academy of Sciences of the United States of America</em> 119.31 (2022): e2201128119. <br> Please cite the above paper if you use any data included in this dataset. Codes related to this study are also available from (https://github.com/bfinl/DeepSIF). Clinical information of the patients are described in the Supplementary Table S1 of the paper. This dataset was collected under support from the National Institutes of Health via grants NS096761 and EB021027 to Dr. Bin He and Dr. Greg Worrell. The human data were collected and de-identified as part of NIH funded research at Mayo Clinic, Rochester, overseen by Dr. Greg Worrell, and processed and organized at Dr. Bin He’s lab at Carnegie Mellon University. The data are shared for information only. The EEG recorded in this dataset follows a 10-10 system and contains 76 channels of recording. One channel is the reference channel and given that we use a common reference channel for source imaging this channel is removed from the topographical map data and the corresponding rows of the lead-field matrix for each patient, equals 75. The EEG data were filtered between 1-40 Hz and a common average reference was used to pre-process the data. <br> The data include three variables: * spike_peak_data: Contains the topographical EEG map at the peak of the spike selected in each individual patient. * patient_id: patient index corresponding to the patient ID in Supplementary Table S1 of the paper. * eloc: electrode information in EEGLAB (https://sccn.ucsd.edu/eeglab/index.php) format. <br>
DOI: 10.5519/qd.8ccnea9g
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (409 records)
DOI: 10.5281/zenodo.6941700
title: Arius mastersi RB0482 decontaminated gx

description: .
DOI: 10.5281/zenodo.6941699
title: Arius mastersi RB0482 decontaminated gx

description: .
DOI: 10.5281/zenodo.6941708
title: Paleozoanthus reticulatus decontaminated gx

description: .
DOI: 10.5281/zenodo.6941707
title: Paleozoanthus reticulatus decontaminated gx

description: .
DOI: 10.21227/jz08-dw27
title: Digital Twinning RFID Frequency Spectrum Signal Strength Dataset

description: This dataset has 2 different RFID manufacturer tags  (2 of each) with different EPC content. Signal Strength data of all 4 tags were taken in the frequency spectrum in the US UHF (900-910 MHz) range. There are 100 data readings per tag, so 400 files total.
DOI: 10.34740/kaggle/dsv/4003858
title: 1234567890
DOI: 10.6084/m9.figshare.19778830
title: Impacts of Plastic Waste Management

description: This dataset consists of the data used in the paper "Impacts of Plastic Waste Management Strategies", published in environmental reviews. <br> Note that for the study, reviews and commentaries were excluded. The intervetion categories marked OTHER and Multiple were also excluded. <br> Each row in the sheet corresponds to an impact of plastic waste mitigation identified in the literature. For our analysis, on the impacts marked "YES" in column J ("FINAL") were included in the analysis. <br> Please email Levi Helm (lthelm@asu.edu) with any questions.
DOI: 10.5281/zenodo.6926898
title: Dataset for Cloud Identification in Mars Daily Global Maps with Deep Learning

description: <strong>Overview:</strong> This repository stores cloud masks and MDGMS for Martian Years (MYs) 28-33. MDGMs were obtained from Harvard Dataverse (https://doi.org/10.7910/DVN/U3766S), and cloud masks were created using the cloudmask model (https://github.com/03kalven/cloudmask). The cloud masks contained in the binary folders have already been binarized using the threshold of 0.912. This dataset is considerably smaller in size than the floating-point cloud mask dataset and is suited for researchers that prefer to use the default threshold of 0.912. <strong>Quick breakdown of the files and folders:</strong> phase folders contain the complete set of MDGMs and cloud masks for Mars Reconnaisance Orbiter mission phases P, B, G, D, F, and J (MYs 28-33) phase_binary folders contain the complete set of binary MDGMs and cloud masks for Mars Reconnaisance Orbiter mission phases P, B, G, D, F, and J (MYs 28-33) view_masks.ipynb has a few handy methods to plot cloud masks and MDGMs <strong>Phase folders:</strong> Each folder is organized based on phase (P, B, G, D, F, J) and subphase (_01 to _23). In each subphase, there are cloudmasks and mdgms folders, as well as a .txt file with MY and solar longitude (Ls) data for each day. <strong>MDGM and cloud mask formats:</strong> mdgm: JPEG, 3600x1801 cloudmask: (NETCDF4_CLASSIC data model, file format HDF5): dimensions(sizes): x(3600), y(1801) variables(dimensions): float32 longitude(x), float32 latitude(y), float32/int16 cloudmask(y, x) The cloud masks' values for any pixel are -999 for NaN and a float from 0 to 1 reporting the model's confidence in that pixel being a cloud. The cloud masks can be binarized using get_cloudmask() included in view_masks.ipynb. A binarized mask would report -999 for NaN, 0 for no cloud, and 1 for cloud. The default threshold is 0.912, but this value can be adjusted if desired. The cloud masks' (0,0) coordinate is the lower left corner of the map, so it may be needed to flip the cloudmask vertically before plotting on a Martian map. The cloud mask NetCDF files are constructed the same way as Wang and González Abad's (https://doi.org/10.7910/DVN/WU6VZ8).
description: {"references": ["WANG, HUIQUN (Helen); Gonzalez Abad, Gonzalo, 2021, \"Cloud Masks derived from Mars Daily Global Maps for MRO\", https://doi.org/10.7910/DVN/WU6VZ8, Harvard Dataverse, V1", "WANG, HUIQUN (Helen); Battalio, Michael; Huber, Zachary, 2020, \"Replication Data for: MRO MARCI Mars Daily Global Maps V2\", https://doi.org/10.7910/DVN/U3766S, Harvard Dataverse, V2"]}
DOI: 10.5281/zenodo.6926897
title: Dataset for Cloud Identification in Mars Daily Global Maps with Deep Learning

description: <strong>Overview:</strong> This repository stores cloud masks and MDGMS for Martian Years (MYs) 28-33. MDGMs were obtained from Harvard Dataverse (https://doi.org/10.7910/DVN/U3766S), and cloud masks were created using the cloudmask model (https://github.com/03kalven/cloudmask). The cloud masks contained in the binary folders have already been binarized using the threshold of 0.912. This dataset is considerably smaller in size than the floating-point cloud mask dataset and is suited for researchers that prefer to use the default threshold of 0.912. <strong>Quick breakdown of the files and folders:</strong> phase folders contain the complete set of MDGMs and cloud masks for Mars Reconnaisance Orbiter mission phases P, B, G, D, F, and J (MYs 28-33) phase_binary folders contain the complete set of binary MDGMs and cloud masks for Mars Reconnaisance Orbiter mission phases P, B, G, D, F, and J (MYs 28-33) view_masks.ipynb has a few handy methods to plot cloud masks and MDGMs <strong>Phase folders:</strong> Each folder is organized based on phase (P, B, G, D, F, J) and subphase (_01 to _23). In each subphase, there are cloudmasks and mdgms folders, as well as a .txt file with MY and solar longitude (Ls) data for each day. <strong>MDGM and cloud mask formats:</strong> mdgm: JPEG, 3600x1801 cloudmask: (NETCDF4_CLASSIC data model, file format HDF5): dimensions(sizes): x(3600), y(1801) variables(dimensions): float32 longitude(x), float32 latitude(y), float32/int16 cloudmask(y, x) The cloud masks' values for any pixel are -999 for NaN and a float from 0 to 1 reporting the model's confidence in that pixel being a cloud. The cloud masks can be binarized using get_cloudmask() included in view_masks.ipynb. A binarized mask would report -999 for NaN, 0 for no cloud, and 1 for cloud. The default threshold is 0.912, but this value can be adjusted if desired. The cloud masks' (0,0) coordinate is the lower left corner of the map, so it may be needed to flip the cloudmask vertically before plotting on a Martian map. The cloud mask NetCDF files are constructed the same way as Wang and González Abad's (https://doi.org/10.7910/DVN/WU6VZ8).
description: {"references": ["WANG, HUIQUN (Helen); Gonzalez Abad, Gonzalo, 2021, \"Cloud Masks derived from Mars Daily Global Maps for MRO\", https://doi.org/10.7910/DVN/WU6VZ8, Harvard Dataverse, V1", "WANG, HUIQUN (Helen); Battalio, Michael; Huber, Zachary, 2020, \"Replication Data for: MRO MARCI Mars Daily Global Maps V2\", https://doi.org/10.7910/DVN/U3766S, Harvard Dataverse, V2"]}
DOI: 10.34740/kaggle/dsv/4003899
title: 1234567890
DOI: 10.25612/837.dx6rn0zm1g6d
title: Solar Radiation (63301_SORD) readings

description: Hourly readings of solar radiation (SORD - Parameter code 63301) from air quality/meteorology monitoring sites in the 13 counties of the Houston-Galveston Area Council.
DOI: 10.5281/zenodo.6941762
title: Valencia Archaeological Surveys (1990-2004), Arizona State University and University of Valencia

description: Archaeological survey data from Valencia, Spain
description: If you use this dataset, please cite it as below. Barton, C. M., Bernabeu Auban, J., Aura Tortosa, J. E., Diez Castillo, A., Molina Balaguer, L., McClure, S., Garcia Puchol, O., & Orozco Kohler, T. Valencia Archaeological Surveys (1990-2004), Arizona State University and University of Valencia (Version 1.0) [Data set]. https://github.com/cmbarton/valencia_surveys. 10.5281/zenodo.6941762. DOI: DOI: 10.5281/zenodo.6941762.
description: {"references": ["Barton, C. M., Bernabeu Aub\u00e1n, J., Aura Tortosa, J. E., & Garcia Puchol, O. (1999). Landscape dynamics and socioeconomic change: An example from the Polop Alto valley. American Antiquity, 64(4), 609\u2013634. https://doi.org/10.2307/2694208", "Bernabeu Aub\u00e1n, J., Barton, C. M., Garcia Puchol, O., & La Roca, N. (1999). Prospecciones sistem\u00e1ticas en el valle del Alcoi (Alicante): Primeros resultados. Arqueolog\u00eda Espacial, 21, 29\u201364.", "Bernabeu, J., Barton, C. M., Garcia Puchol, O., & La Roca, N. (2000). Systematic survey in Alicante, Spain: First results. T\u00fcrkyie Bilimer Akademisi Arkeoloji Dergisi, 3, 57\u201386.", "Barton, C. M., Bernabeu Aub\u00e1n, J., Aura Tortosa, J. E., Garcia Puchol, O., & La Roca, N. (2002). Dynamic landscapes, artifact taphonomy, and landuse modeling in the western Mediterranean. Geoarchaeology, 17(2), 155\u2013190. https://doi.org/10.1002/gea.10008", "Barton, C. M., Bernabeu Aub\u00e1n, J., Aura Tortosa, J. E., & Molina Balaguer, L. (2004). Historical contingency, nonlinearity, and the neolithization of the western Mediterranean. In L. Wandsnider & E. Athanassopoulos (Eds.), Current Issues in Mediterranean Landscape Archaeology (pp. 99\u2013124). University of Pennsylvania Press.", "Barton, C. M., Bernabeu Auban, J., Garcia Puchol, O., Schmich, S., & Molina Balaguer, L. (2004). Long-term socioecology and contingent landscapes. Journal of Archaeological Method and Theory, 11(3), 253\u2013295. https://doi.org/10.1023/B:JARM.0000047315.57162.b7", "Diez Castillo, A., Barton, C. M., La Roca Cervig\u00f3n, N., & Bernabeu Aub\u00e1n, J. (2008). Landscape socioecology in the Serpis Valley (10000-4000 BP). In A. Posluschny, K. Lambers, & I. Herzog (Eds.), Layers of Perception: Proceedings of the 35th CAA Conference, Berlin, April 2007. Dr.Rudolf Habel GmbH. Kolloquien zur Vor- und Fruhgeschichte, Vol. 10. http://hdl.handle.net/10550/58295", "Miller, A., & Barton, C. M. (2008). Exploring the land: A comparison of land-use patterns in the Middle and Upper Paleolithic of the western Mediterranean. Journal of Archaeological Science, 35, 1427\u20131437. https://doi.org/10.1016/j.jas.2007.10.007"]}