cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.1199011
title: EEG and audio dataset for auditory attention decoding

description: This dataset contains EEG recordings from 18 subjects listening to one of two competing speech audio streams. Continuous speech in trials of ~50 sec. was presented to normal hearing listeners in simulated rooms with different degrees of reverberation. Subjects were asked to attend one of two spatially separated speakers (one male, one female) and ignore the other. Repeated trials with presentation of a single talker were also recorded. The data were recorded in a double-walled soundproof booth at the Technical University of Denmark (DTU) using a 64-channel Biosemi system and digitized at a sampling rate of 512 Hz. Full details can be found in: <strong>Søren A. Fuglsang, Torsten Dau & Jens Hjortkjær (2017): Noise-robust cortical tracking of attended speech in real-life environments. <em>NeuroImage</em>, 156, 435-444</strong> and <strong>Daniel D.E. Wong, Søren A. Fuglsang, Jens Hjortkjær, Enea Ceolini, Malcolm Slaney & Alain de Cheveigné: A Comparison of Temporal Response Function Estimation Methods for Auditory Attention Decoding. Frontiers in Neuroscience, </strong>https://doi.org/10.3389/fnins.2018.00531 The data is organized in format of the publicly available COCOHA Matlab Toolbox. The preproc_script.m demonstrates how to import and align the EEG and audio data. The script also demonstrates some EEG preprocessing steps as used the Wong et al. paper above. The AUDIO.zip contains wav-files with the speech audio used in the experiment. The EEG.zip contains MAT-files with the EEG/EOG data for each subject. The EEG/EOG data are found in <strong>data.eeg</strong> with the following channels: channels 1-64: scalp EEG electrodes channel 65: right mastoid electrode channel 66: left mastoid electrode channel 67: vertical EOG below right eye channel 68: horizontal EOG right eye channel 69: vertical EOG above right eye channel 70: vertical EOG below left eye channel 71: horizontal EOG left eye channel 72: vertical EOG above left eye The <strong>expinfo</strong> table contains information about experimental conditions, including what what speaker the listener was attending to in different trials. The expinfo table contains the following information: attend_mf: attended speaker (1=male, 2=female) attend_lr: spatial position of the attended speaker (1=left, 2=right) acoustic_condition: type of acoustic room (1= anechoic, 2= mild reverberation, 3= high reverberation, see Fuglsang et al. for details) n_speakers: number of speakers presented (1 or 2) wavfile_male: name of presented audio wav-file for the male speaker wavfile_female: name of presented audio wav-file for the female speaker (if any) trigger: trigger event value for each trial also found in data.event.eeg.value DATA_preproc.zip contains the preprocessed EEG and audio data as output from preproc_script.m. The dataset was created within the COCOHA Project: Cognitive Control of a Hearing Aid
DOI: 10.5281/zenodo.13698408
title: An Evaluation of Equatorial Perturbation Electric Fields Using Empirical Vertical Drift Models

description: Dataset for the article titled "An Evaluation of Equatorial Perturbation Electric Fields Using Empirical Vertical Drift Models", submitted to Space Weather. The dataset includes the outputs from the four empirical vertical drift models used in the article: Fejer and Scherliess (1997), Kelley and Retterer (2008), Manoj and Maus (2012), and Scherliess and Fejer (1999).
DOI: 10.5281/zenodo.13708735
title: Energetic Compact Strokes as the Major Source of Downward Terrestrial Gamma-ray Flashes in Winter Thunderstorms

description: ECS-TGF_10km.csv contains a list of ECSs in Figure 1. Raw FALMA waveforms of these ECSs are in FALMA_wave.zip. For each ECS, waveforms of one or two seconds recorded at one FALMA site are provided. Some waveform data contain a PPS pulse. See PPS_pulse.txt in FALMA_wave.zip for more details.  The format of waveform data is described at https://tingwu.info/pylab/lab05.html.

ECS_100km.csv contains a list of ECSs in Figure 5.
DOI: 10.5281/zenodo.13840705
title: NOAA UFS data for 'Surface energy balance responses to radiative forcing in the Central Arctic from MOSAiC and models'

description: Output from the NOAA Unified Forecast System (UFS; Jacobs 2021) used in 'Surface energy balance responses to radiative forcing in the Central Arctic from MOSAiC and models', submitted to Journal of Geophysical Research: Atmospheres.

 

Data are 3 hour instantaneous values with 72 hour lead times and initialization over December 3, 2019 - March 14, 2020. Only data from the nearest gridcell to the Polarstern during the MOSAiC expedition is provided. Variables include radiative and turbulent surface fluxes, sea ice concentration, sea ice thickness, and snow depth.

 

Jacobs, Neil A. "Open innovation and the case for community model development." Bulletin of the American Meteorological Society 102.10 (2021): E2002-E2011.
DOI: 10.5281/zenodo.13989241
title: Annual 30 m land cover dataset on the Tibetan Plateau from 1990 to 2023

description: TPLUCD provided an annually updated land use and cover dataset for the Tibetan Plateau from 1990 to 2023, with a spatial resolution of 30 m, using the WGS-84 as the spatial reference, and publicly available in GeoTIFF format. The values ranged from 1 to 10, corresponding to the following land use types: 1 for cropland, 2 for forest, 3 for shrubland, 4 for alpine steppe, 5 for alpine meadow, 6 for water bodies, 7 for bare land, 8 for impervious surfaces, 9 for wetlands, and 10 for snow/ice.
DOI: 10.5281/zenodo.14010311
title: Data for "Shear Strain Evolution Spanning the 2020 Mw6.8 Elazığ and 2023 Mw7.8/Mw7.6 Kahramanmaraş Earthquake Sequence along the East Anatolian Fault Zone" manuscript

description: Data necessary to support the analysis presented in "Shear Strain Evolution Spanning the 2020 Mw6.8 Elazığ and 2023 Mw7.8/Mw7.6 Kahramanmaraş Earthquake Sequence along the East Anatolian Fault Zone" manuscript
DOI: 10.5281/zenodo.14156812
title: Fluxes of particulate organic carbon, nitrogen and mass from the Station M abyssal time series in the northeast Pacific, (1989-2022)

description: Overview:

This dataset provides particulate fluxes to Station M in the NE Pacific, from 1989 to 2022.  Samples were collected with McLane Parflux sequencing sediment traps deployed on moorings. Data are provided for traps 50 m above bottom and 600 m above bottom, with deployment bottom depths ranging from approximately 3900 m to 4500 m.  Gaps reflect lapses in funding, weather disruptions, clogs in sediment traps, or the occasional spilled sample.  Where available, GPS coordinates and ship-recorded bottom depth at deployment location are given. Where these are not available, approximate location and depth are given and noted.

 

Methods:

This program used McLane Parflux sequencing sediment traps. Attempts to avoid sediment trap clogs, which increasingly became an issue, included replacing manufacture-supplied plastic funnels with Teflon-coated fiberglass funnels (October 2014), doubling the size of sediment trap collection cups (from 250 ML to 500 ML starting in October 2014), and adding a function that periodically agitated material in the funnel constriction (starting in June 2015).

Before deployment, sediment trap cups were acid-washed and filled with a preservative (mercuric chloride from 1989 to 2009, 3%–5% buffered formalin from 2009 to 2022). Formalin brine recipe followed that recommended by McLane. Following sample recovery, zooplankton that many have swum into the traps were identified visually and manually removed (KLS). Samples were returned to the lab, freeze-dried, and weighed to calculate mass flux. The freeze-dried sample was analyzed for inorganic carbon content using a coulometer (UIC), and total carbon, hydrogen, and nitrogen using an elemental analyzer (Perkin-Elmer or Exeter Analytical, University of California Santa Barbara Marine Science Institute Analytical Laboratory). Dry mass was corrected for salt content using a AgNO3 titration (Strickland and Parsons, 1972). Data [mass flux, particulate organic carbon flux, and total nitrogen flux] from the 600 mab trap were used. Gaps in this data set were infilled using the linear relationship between data from the 600 mab and 50 mab traps. Full details of these methods can be found in Baldwin et al. (1998).

Data provided have been quality-controlled, and only usable data are included here.

 

References:

Baldwin, R. J., Glatts, R. C., & Smith Jr, K. L. (1998). Particulate matter fluxes into the benthic boundary layer at a long time-series station in the abyssal NE Pacific: composition and fluxes. Deep Sea Research Part II: Topical Studies in Oceanography, 45(4-5), 643-665.

Strickland, J.D.H., Parsons, T.R. (1972) A Practical Handbook of Seawater Analysis. Fisheries Research Board of Canada, Ottawa 

Smith, K. L., Huffard, C. L., & Ruhl, H. A. (2020). Thirty-year time series study at a station in the abyssal NE Pacific: An introduction. Deep Sea Research Part II: Topical Studies in Oceanography, 173, 104764.
DOI: 10.5281/zenodo.14180033
title: Raw data and scripts for "An ultra-broadband photonic-chip-based parametric amplifier"

description: Datasets and scripts for the manuscript "An ultra-broadband photonic-chip-based parametric amplifier".

Contains all raw data and codes used to produce the Main Figures and Extended Data Figures in the manuscript.
DOI: 10.5281/zenodo.14510532
title: Dataset of Size-driven phase evolution in ultrathin relaxor films

description: Dataset of Size-driven phase evolution in ultrathin relaxor films
DOI: 10.5281/zenodo.14678134
title: Simulation dataset for New Insights on the High Reconnection Rate and the Diminishment of Ion Outflow

description: The dataset contains simulation data used in the paper of "New Insights on the High Reconnection Rate and the Diminishment of Ion Outflow". Data are generated from a particle-in-cell simulation using the VPIC code. Please see the paper for the descriptions of the simulation setup.

The fields_moments.gda files in runs.7z are fields and plasma moments data of the simulations presented in the paper. The time step in unit of twci for each simulation is: A1:0.025, A2:0.1, A3:0.25, A4:0.25, A5:0.5, B1:0.1, B2:0.1, B3:0.1, B4:0.025, B5:0.05, C1:0.02, C2:0.02. Each file contains float-type data arrays with a size of (Lx/Δ)×1×(Lz/Δ), corresponding to x-y-z dimensions, respectively. Lx, Lz and Δ for each simulation are presented in the paper. Data can be read by softwares like IDL, python, matlab, etc., using the standard data reading methods.

The runs_Hparticle_t_x_z files contain ion particle data for the time step t, for the domain of x=[x-0.03, x+0.03]di, z=[z-0.03,z+0.03]di. The files are IDL save files. To read the data, use restore, file=file in IDL. Each data chunk constitues of the following variables in order: all_vxs, all_vys, all_vzs, ws, all_xs, all_ys. Here all_vxs, all_vys and all_vzs are velocities in unit of light speed (c); all_xs and all_ys are x and z locations in unit of de; ws represents the weight of the particles, so the contribution of a particle to the phase space density needs to multiply by this ws factor (In the paper, ws factors are re-normalized while the relative weights between particles remain the same).
DOI: 10.5281/zenodo.14714293
title: Witnessing the onset of Reionisation via Lyman-α emission at redshift 13
DOI: 10.5281/zenodo.14758969
title: Data from: Spatial and temporal interplay between oceanic circulation and biological production in shaping carbon export off the California coast

description: Abstract

A major challenge in understanding the oceanic carbon cycle is estimating the sinking flux of organic carbon exiting the sunlit surface ocean, termed carbon export. Existing algorithms derive carbon export from satellite ocean color, but neglect spatio-temporal offsets created by the temporal lag between production and export, and by horizontal advection. Here, we show that a Lagrangian “growth-advection” (GA) satellite-derived product, where plankton succession and export are mapped onto surface oceanic circulation following coastal upwelling, succeeds in representing in situ export off the California coast. In situ export is best represented by a combination of GA export (proportional to modeled zooplankton) and export derived from ocean color (related to local phytoplankton). Both products also correlate with a long-term time series of abyssal carbon flux. These results provide insights on export spatio-temporal patterns and a path towards improving satellite-derived carbon export in the California Current and beyond.

Data set description

This data set is a satellite-based 1993-2023 daily model of surface POC production (Cproduction) and the corresponding carbon export flux extrapolated at 100 m (C100) in the California Current upwelling system. These were modeled using the growth-advection method originally developed to represent krill hospots (Messié et al. (2022), corresponding dataset).

Details regarding data sources and calculations can be found in Messié et al. (2022) and Messié et al. (2025).
description: This work was primarily funded by the David and Lucile Packard Foundation. The original GA method was developed under a grant from the National Aeronautics and Space Administration (80NSSC17K0574).
DOI: 10.5281/zenodo.14765900
title: Processed and secondary data associated to Benedetti et al. (2025) - Global Change Biology

description: This present archive contains the data tables enclosing the results of our study on the global contemporary and future patterns of marine copepod functional diversity and how it relates to the functioning of the biological carbon pump (Benedetti et al., 2025, accepted in Global Change Biology).



'file1' contains the contemporary fields of mean annual copepod taxonomic (i.e., species richness) and functional diversity as well as the proxy variables of ecosystem functioning. The data of this file this allow to reproduce the following main figures of the manuscript: Figures 1,2,3 and 4

'file2' contains the future ensemble projections of mean annual relative changes (in %) in copepod species richness and functional diversity. The data of this file allow to reproduce the following main figures of the manuscript: Figure 5

the two readme files describe the content of each corresponding .txt files


The full methodology that lead to the present results is exhaustively described here: https://ecoevorxiv.org/repository/view/7433/ 

The R scripts used to make the study can be found at: https://zenodo.org/records/14747330 



This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no. 862923 (AtlantECO) and under grant agreement no. 101059915 (BIOceans5D). This output reflects only the author’s view, and the European Union cannot be held responsible for any use that may be made of the information contained therein.
DOI: 10.5281/zenodo.8296768
title: A High-Quality Reprocessed MODIS Leaf Area Index Dataset (HiQ-LAI)

description: The High-Quality Leaf Area Index (HiQ-LAI) is derived from reprocessed MODIS LAI C6.1 product by SpatioTemporal Information Compositing Algorithm (STICA). This method integrates information from multiple dimensions, including pixel quality information, spatiotemporal correlation, and original observations, to improve the raw MODIS LAI retrievals with poor quality. The HiQ-LAI covers the period from 2000 to 2022, with spatial resolutions of 500m/5km for global vegetation area and temporal resolutions of 8 days. Ground-based verification results show that HiQ-LAI performs better than the original MODIS product (MOD15A2H C6.1). Time series curves of the HiQ-LAI exhibit reduced abnormal fluctuations and better alignment with expected phenological patterns. Additionally, the agreement with ground measurements increases gradually as raw data quality decreases. HiQ-LAI was found to be more continuous and consistent than MODIS LAI on a global scale from both spatial and temporal perspectives, especially in the equatorial regions where optical remote sensing usually cannot achieve good performance. Thus, We anticipate that HiQ-LAI with better spatio-temporal continuity will better support varying global LAI time series applications. Here, we offer a product version with a spatial resolution of 5km and a temporal resolution of 8 days. Another version has a spatial resolution of 500 meters and is available through Google Earth Engine (https://code.earthengine.google.com/?asset=projects/verselab-398313/assets/HiQ_LAI/wgs_500m_8d). More details about HiQ-LAI can be found at https://github.com/tiramisu18/HiQ-LAI
DOI: 10.5281/zenodo.8381438
title: Data --- "Optimization of Convolutional Neural Network models for spatially coherent multi-site fire danger predictions"

description: Data to reproduce the results of the manuscript entitled "Optimization of Convolutional Neural Network models for spatially coherent multi-site fire danger predictions" submitted to Geophysical Research Letters. The companion jupyter notebook can be found in DOI: 10.5281/zenodo.8387558
DOI: 10.5439/1996977
title: tropoe (c1)

description: tropoe
DOI: 10.6073/pasta/15b300e96c2d2f9785d0155b3e18b0e9
title: Hubbard Brook Experimental Forest: Daily Streamflow by Watershed, 1956 - present

description: Streamflow at 9 watersheds (12-77 Hectares) within the Hubbard Brook Experimental Forest in New Hampshire, USA has been measured continuously from as early as 1955. Streams are gaged with V-notch weirs, in some cases in combination with rectangular San Dimas flumes, at the outlet of each watershed. Through 2012, stage heights were recorded by means of a mechanical spring-wound clock and pen on a strip-chart recorder. Beginning January 1, 2013, these analog chart recorders were replaced with digital sensors. Overlap with both measurement techniques occurred for several years at all weirs. Streamflow data were gathered by the Hubbard Brook Experimental Forest and contributed to the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
DOI: 10.6073/pasta/910469efbf1f7e8d54c2b1ca864edec9
title: AWE01 Meteorological data from the konza prairie headquarters weather station

description: The following weather data are included in this data set: hourly (record type 1): mean temperature, mean relative humidity, mean wind speed, mean wind direction, mean solar radiation, soil temperature, max wind speed; daily (record type 2): maximum air temperature, minimum air temperature, mean air temperature, mean relative humidity, total solar radiation, total precipitation, maximum soil temperature, minimum soil temperature, mean soil temperature, average wind speed. These data are collectecd by a micrologger at headquarters on Konza Prairie.
DOI: 10.6073/pasta/a47e2f761a5f4f99f31998aef065e2d1
title: North Temperate Lakes LTER: Fish Abundance 1981 - current

description: This data set is a derived data set based on fish catch data. Data are collected annually to enable us to track the fish assemblages of eleven primary lakes (Allequash, Big Muskellunge, Crystal, Sparkling, Trout, bog lakes 27-02 [Crystal Bog] and 12-15 [Trout Bog], Mendota, Monona, Wingra and Fish). Sampling on Lakes Monona, Wingra, and Fish started in 1995; sampling on other lakes started in 1981. Sampling is done at six littoral zone sites per lake with seine, minnow or crayfish traps, and fyke nets; a boat-mounted electrofishing system samples three littoral transects. Vertically hung gill nets are used to obtain two pelagic samples per lake from the deepest point. A trammel net samples across the thermocline at two sites per lake. In the bog lakes only fyke nets and minnow traps are deployed. Parameters measured include species-level identification and lengths for all fish caught, and weight and scale samples from a subset. Derived data sets include species richness, catch per unit effort, and size distribution by species, lake, and year. Protocol used to generate data: Day seines were only used in 1981 and have been eliminated from this data set to make sampling effort across years comparable. Number caught for each species is summed over repetitions of a gear within a lake and over depth. For information on fish stocking by the Wisconsin Department of Natural Resources in LTER lakes in Dane and Vilas counties, see https://dnr.wi.gov/fisheriesmanagement/Public/Summary/Index. Beach seining was discontinued after 2019. The only sampling done in 2020 were a single gill-netting sample in Sparkling, Crystal, and Trout lakes. Sampling in Fish Lake was missed in 2021 due to significant lake level changes. Data from the two bogs is missing in 2022. Sampling Frequency: annually. Number of sites: 11
DOI: 10.6073/pasta/bd03330e83fc52a5442bb39e131c95e9
title: North Temperate Lakes LTER: Phytoplankton - Madison Lakes Area 1995 - current

description: Phytoplankton samples for the 4 southern Wisconsin LTER lakes (Mendota, Monona, Wingra, Fish) have been collected for analysis by LTER since 1995 (1996 Wingra, Fish) when the southern Wisconsin lakes were added to the North Temperate Lakes LTER project. Samples are collected as a composite whole-water sample and are preserved in gluteraldehyde. Composite sample depths are 0-8 meters for Lake Mendota (to conform to samples collected and analyzed since 1990 for a UW/DNR food web research study), and 0-2 meters for the other three lakes. A tube sampler is used for the 0-8 m Lake Mendota samples; samples for the other lakes are obtained by collecting water at 1-meter intervals using a Kemmerer water sampler and compositing the samples in a bucket. Samples are taken in the deep hole region of each lake at the same time and location as other limnological sampling. Phytoplankton samples are analyzed by PhycoTech, Inc., a private lab specializing in phytoplankton analyses (see data protocol for procedures). Samples for Wingra and Fish lakes are archived but not routinely counted. Permanent slide mounts (3 per sample) are prepared for all analyzed Mendota and Monona samples as well as 6 samples per year for Wingra and Fish; the slide mounts are archived at the University of Wisconsin - Madison Zoology Museum. Phytoplankton are identified to species using an inverted microscope (Utermohl technique) and are reported as natural unit (i.e., colonies, filaments, or single cells) densities per mL, cell densities per mL, and algal biovolume densities per mL. Multiple entries for the same species on the same date may be due to different variants or vegetative states - (e.g., colonial or attached vs. free cell.) Biovolumes for individual cells of each species are determined during the counting procedure by obtaining cell measurements needed to calculate volumes for geometric solids (e.g., cylinders, spheres, truncated cones) corresponding to actual cell shapes. Biovolume concentrations are then computed by mulitplying the average cell biovolume by the cell densities in the water sample. Note that one million cubicMicrometers of biovolume PerMilliliter of water are equal to a biovolume concentration of one cubicMillimeterPerMilliliter. Assuming a cell density equal to water, a cubicMillimeterPerMilliliter of biovolume converts to a biomass concentration of one milligramPerLiter. Sampling Frequency: bi-weekly during ice-free season from late March or early April through early September, then every 4 weeks through late November; sampling is conducted usually once during the winter (depending on ice conditions). Number of sites: 4 Several taxonomic updates have been made to this dataset February 2013, see methods for details.