cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.12751/g-node.w7s6wv
title: Neural effects of dopaminergic compounds revealed by multi-site electrophysiology in mice and interpretable machine-learning

description: The LFP_RawData folder contains local field potential (LFP) recordings obtained from depth electrodes in the mice brain regions,
including the prelimbic cortex (PrL), mediodorsal thalamus (MD), dorsal hippocampal fissure (dCA1),
dorsal hippocampal CA3 subfield (dCA3), and ventral hippocampal fissure (vHC).
Pharmaco-LFP experiments were conducted approximately every third day in a within-subject design with a latin-square,
randomized drug-assignment across the cohort. Applications included: saline (Sal; vehicle 1),
0.1% TWEEN80/saline (T/Sal; vehicle 2), 1 and 3 mg/kg clozapine (CLZ1 and CLZ3; clozapine dihydrochloride, HB6129, HelloBio, GB),
0.5 mg/kg raclopride (Raclo; S(-)raclopride(+)-tartrate, R121 Sigma, DE), 0.1 mg/kg SCH23390 (SCH; SCH23390 hydrochloride, 0925 Tocris, GB),
and 2 mg/kg amphetamine (Amph; d-amphetamine sulfate, A-5880, Sigma); vehicle 2 was used for raclopride,
all other compounds were applied in saline.
Mice were recorded in Type-III open-field cages (Tecniplast, IT) with fresh saw-dust for a 10 min baseline period,
after which the compound was applied i.p., followed by a further recording for 50 min.
description: IsSupplementTo: Kapanaiah, S. K. T., Rosenbrock, H., Hengerer, B., & Kätzel, D. (2024). Neural effects of dopaminergic compounds revealed by multi-site electrophysiology and interpretable machine-learning. Frontiers in Pharmacology, 15. https://doi.org/10.3389/fphar.2024.1412725. (https://doi.org/ 10.3389/fphar.2024.1412725)
description: IsReferencedBy: DA-Pharmacology-ephys-analysis-2024. Github. https://github.com/KaetzelLab/DA-Pharmacology-ephys-analysis-2024
DOI: 10.60600/yu/clawet/xxdcmo
title: 0769.TextGrid

description: :unav
DOI: 10.60600/yu/clawet/v5hhgg
title: 1001.TextGrid

description: :unav
DOI: 10.60600/yu/clawet/8jgb30
title: 0867.TextGrid

description: :unav
DOI: 10.60600/yu/clawet/5ahufa
title: 1036.wav

description: :unav
DOI: 10.60600/yu/clawet/cvcwau
title: 0917.wav

description: :unav
DOI: 10.5281/zenodo.12517579
title: Water level data from the Tarland Burn, Aberdeenshire, Scotland,  1st January - 31st December  2023

description: Water level was recorded, in hourly intervals, at four locations on the Tarland Burn,  Aberdeenshire, Scotland from 1st January to 31st december 2023.  Measurements were made using pressure transducers and logging equipment supplied by Campbell Scientific. Station latitude and longitude are provided. Blank cells in the data sheets are due to instrument failure or temporary loss of power.

This data can be used to extend the series of previously published data from 2013- 2022 (https://doi.org/10.5281/zenodo.7777653) which also included rating curves derived using a Valeport electromagnetic flow meter (801 model), or ADCP "boat" at higher water level.

This work has been funded by the Scottish Government as part of the strategic research programme and provides empirical data which underpins research on natural flood management, water quality, and biodiversity.
DOI: 10.5281/zenodo.12517580
title: Water level data from the Tarland Burn, Aberdeenshire, Scotland,  1st January - 31st December  2023

description: Water level was recorded, in hourly intervals, at four locations on the Tarland Burn,  Aberdeenshire, Scotland from 1st January to 31st december 2023.  Measurements were made using pressure transducers and logging equipment supplied by Campbell Scientific. Station latitude and longitude are provided. Blank cells in the data sheets are due to instrument failure or temporary loss of power.

This data can be used to extend the series of previously published data from 2013- 2022 (https://doi.org/10.5281/zenodo.7777653) which also included rating curves derived using a Valeport electromagnetic flow meter (801 model), or ADCP "boat" at higher water level.

This work has been funded by the Scottish Government as part of the strategic research programme and provides empirical data which underpins research on natural flood management, water quality, and biodiversity.
DOI: 10.60600/yu/clawet/azqlmc
title: 0651.wav

description: :unav
DOI: 10.15468/dl.4xw8c4
title: Occurrence Download

description: A dataset containing 190115 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Ireland, Svalbard and Jan Mayen, Portugal, Spain, France, Germany, Belgium, Netherlands, Denmark, Estonia, Latvia, Lithuania, Italy, Greece, Cyprus, Türkiye, Russian Federation, Ukraine, Romania, Bulgaria, Albania, Croatia, Austria, Slovakia, Poland)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Sedum acre L."
 ]
}

 The dataset includes 190115 records from 1191 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091502-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60600/yu/clawet/icmkrt
title: 0766.wav

description: :unav
DOI: 10.60600/yu/clawet/nutejt
title: 0847.TextGrid

description: :unav
DOI: 10.5281/zenodo.12516635
title: Source Parameters and Ground Motion Simulation of the 2023 MW 5.5 Pingyuan Earthquake in the North China Plain

description: Broadband seismic waveform data used for determining the focal mechanism and depth of the 2023 MW 5.5 Pingyuan earthquake
DOI: 10.5281/zenodo.12516636
title: Source Parameters and Ground Motion Simulation of the 2023 MW 5.5 Pingyuan Earthquake in the North China Plain

description: Broadband seismic waveform data used for determining the focal mechanism and depth of the 2023 MW 5.5 Pingyuan earthquake
DOI: 10.5281/zenodo.12517490
title: HDF5 JetClass train2
DOI: 10.5281/zenodo.12517491
title: HDF5 JetClass train2
DOI: 10.60600/yu/clawet/i5uhu3
title: 0936.TextGrid

description: :unav
DOI: 10.5281/zenodo.12513413
title: HDF5 JetClass train1
DOI: 10.5281/zenodo.12513414
title: HDF5 JetClass train1
DOI: 10.60600/yu/clawet/gcw7ry
title: 0864.TextGrid

description: :unav
DOI: 10.5281/zenodo.12516540
title: MUSES Leaf Area Index (LAI) Derived from MODIS Data Monthly Global 0.05º Geographic Grid Since 2000

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/).


This dataset is the MUSES global LAI product at 0.05º spatial resolution and monthly temporal resolution. The MUSES LAI product was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao et al., 2014; Xiao et al., 2016). It is provided on Geographic grid and spans from 2000 to 2019 (continuously updated). The MUSES LAI product is spatially complete and temporally continuous.


Dataset Characteristics:



	
Spatial Coverage: 180º W – 180º E, 90º S – 90º N
	
Temporal Coverage: 2000 – 2019
	
Spatial Resolution: 0.05º (approximately 5 km)
	
Temporal Resolution: 1 month
	
Projection: Geographic
	
Data Format: HDF
	
Scale: 0.01
	
Valid Range: 0 – 1000



Citation (Please cite this paper whenever these data are used):



	
Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. International Journal of Remote Sensing, 43(4), 1199-1225.
	
Xiao Zhiqiang, et al. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance. IEEE Transactions on Geoscience and Remote Sensing, 52, 209-223.
	
Xiao Zhiqiang, et al. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. IEEE Transactions on Geoscience and Remote Sensing, 54, 5301-5318.
	
Xiao Zhiqiang, et al. (2017). Evaluation of four long time-series global leaf area index products. Agricultural and Forest Meteorology, 246, 218-230.



If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7601296
title: MUSES Leaf Area Index (LAI) Derived from MODIS Data Monthly Global 0.05º Geographic Grid Since 2000

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/).


This dataset is the MUSES global LAI product at 0.05º spatial resolution and monthly temporal resolution. The MUSES LAI product was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao et al., 2014; Xiao et al., 2016). It is provided on Geographic grid and spans from 2000 to 2019 (continuously updated). The MUSES LAI product is spatially complete and temporally continuous.


Dataset Characteristics:



	
Spatial Coverage: 180º W – 180º E, 90º S – 90º N
	
Temporal Coverage: 2000 – 2019
	
Spatial Resolution: 0.05º (approximately 5 km)
	
Temporal Resolution: 1 month
	
Projection: Geographic
	
Data Format: HDF
	
Scale: 0.01
	
Valid Range: 0 – 1000



Citation (Please cite this paper whenever these data are used):



	
Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. International Journal of Remote Sensing, 43(4), 1199-1225.
	
Xiao Zhiqiang, et al. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance. IEEE Transactions on Geoscience and Remote Sensing, 52, 209-223.
	
Xiao Zhiqiang, et al. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. IEEE Transactions on Geoscience and Remote Sensing, 54, 5301-5318.
	
Xiao Zhiqiang, et al. (2017). Evaluation of four long time-series global leaf area index products. Agricultural and Forest Meteorology, 246, 218-230.



If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.60600/yu/clawet/rtnvwm
title: 0735.wav

description: :unav
DOI: 10.5517/ccdc.csd.cc2f5c66
title: CCDC 2239477: Experimental Crystal Structure Determination

description: Related Article: Lyazat K. Salkeyeva, Leonid M. Pevzner, Pavel Vojtíšek, Yelena V. Minayeva|2024|Eurasian J. Chem.|29|113|doi:10.31489/2959-0663/1-24-4
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2f5cll
title: CCDC 2239489: Experimental Crystal Structure Determination

description: Related Article: Lyazat K. Salkeyeva, Leonid M. Pevzner, Pavel Vojtíšek, Yelena V. Minayeva|2024|Eurasian J. Chem.|29|113|doi:10.31489/2959-0663/1-24-4
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.12518002
title: Supplementary repository associated with the manuscript submitted to the journal Scientific Reports and authored by Giampiero Iaffaldano, Juan Martin de Blas, Xu Rui, D. Sarah Stamps, and Zhao Bin
DOI: 10.5281/zenodo.12518003
title: Supplementary repository associated with the manuscript submitted to the journal Scientific Reports and authored by Giampiero Iaffaldano, Juan Martin de Blas, Xu Rui, D. Sarah Stamps, and Zhao Bin
DOI: 10.60600/yu/clawet/zagldu
title: 1026.wav

description: :unav
DOI: 10.60600/yu/clawet/hkozty
title: 0737.TextGrid

description: :unav
DOI: 10.60600/yu/clawet/m0zrbx
title: 0849.TextGrid

description: :unav
DOI: 10.15468/dl.qgsgje
title: Occurrence Download

description: A dataset containing 49250 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Geometry POLYGON((-79.39784 -57.44406,-48.72835 -57.44406,-52.12615 -23.03876,-59.95474 -20.13038,-72.80585 -15.2398,-79.39784 -57.44406))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Vultur gryphus Linnaeus, 1758"
 ]
}

 The dataset includes 49250 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091526-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60600/yu/clawet/mc3k7c
title: 0931.TextGrid

description: :unav
DOI: 10.7803/502.12.1.1.10
title: BIBB/BAuA-Erwerbstätigenbefragung 2012 – Arbeit und Beruf im Wandel. Erwerb und Verwertung beruflicher Qualifikationen (Vorversion) (SUF)
title: BIBB/BAuA Employment Survey of the Working Population on Qualification and Working Conditions in Germany 2012 (pre-release) (SUF)
DOI: 10.5287/ora-brgkzjedb
title: Climate Data 111+ : Synthesis of Hazard Data Sources

description: Climate Data 111+ is designed to be a comprehensive tool for researchers, policymakers, and practitioners in climate risk assessment and adaptation. With 111+ data sources meticulously described and categorized, Climate Data 111+ offers both depth and clarity, making it easier for users to find and understand data they need. Whether for academic research, policy development, or practical implementation, our database is a comprehensive resource for addressing the challenges of climate change. Importantly, Climate Data 111+ emphasizes open access, ensuring that all users can freely access climate data without financial barriers.

Climate Data 111+ is detailed in several dimensions and provides a thorough understanding of the scope, quality and applicability of the data. Descriptions include the specific climate hazards covered, such as floods, droughts, heatwaves, or wildfires; the relevant time period (historical, present, or future); and the frequency of data collection or updates, ranging from hourly to yearly intervals. The geographic area covered by the data is specified, from local to global scales, and the level of detail in the spatial data is indicated, including the source's native resolution and the approximate spatial resolution standardised to kilometres for easy comparison across sources.

Climate Data 111+ also includes advanced attributes. Information on the type of ensemble used, such as Scenario Ensembles, Initial Condition Ensembles, or Parameter Ensembles, helps users understand the robustness and variability captured in the data. Additionally, the climate scenarios included in the data, ranging from business-as-usual to various mitigation pathways, are detailed, along with any post-processing applied, including bias correction, spatial and/or temporal aggregation, and ensemble aggregation.

To facilitate data accessibility and usability, Climate Data 111+ includes key indicators or metrics provided by the data source. Information on the recency and update frequency of the data ensures users have access to the latest information. The format in which the data is available, such as CSV, NetCDF, or JSON, is also specified.

Comprehensive metadata is provided to facilitate data sourcing and credibility assessment. This includes the organization or institution responsible for the data, which provides context for regional expertise and focus, and direct links to access the data or more information about the source.
DOI: 10.60600/yu/clawet/lmqlkz
title: 0842.TextGrid

description: :unav
DOI: 10.15468/dl.9zwrwf
title: Occurrence Download

description: A dataset containing 129 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Germany",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aedes albopictus (Skuse, 1894)"
 ]
}

 The dataset includes 129 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091527-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60600/yu/clawet/qmutmv
title: 0639.TextGrid

description: :unav
DOI: 10.15468/dl.8ma4kh
title: Occurrence Download

description: A dataset containing 1692 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Material sample, Material citation, Specimen, Living Specimen, Occurrence evidence)",
 "Continent is Africa",
 "Country is Kenya",
 "DatasetKey is one of (Occurrence records of small and medium sized mammal species in Tana River Basin, Kenya, Occurrence records of mammal species in Tana River Basin, Kenya, Occurrence records of different mammal species from several localities in Kenya, Kenya Wildlife Service, Laikipia Samburu Aerial Census, 2008, iNaturalist Research-grade Observations, Observation.org, Nature data from around the World, Ground Census Data for Lake Nakuru and Nairobi National Parks, naturgucker, Kenya Virtual Museum Records, INSDC Sequences)",
 "Geometry POLYGON((35.27034 5.38917,34.27849 4.16823,34.92028 2.07107,33.81174 0.37955,33.81174 -0.84564,37.37072 -2.94476,37.6041 -3.93481,39.29607 -4.51666,41.92155 -1.42897,40.9297 -0.78731,40.98805 2.59573,41.92155 4.05184,40.69633 4.2846,39.64614 3.35318,38.71263 3.58612,36.32053 4.6336,35.27034 5.38917))",
 "HasGeospatialIssue is false",
 "TaxonKey is Syncerus caffer (Sparrman, 1779)",
 "Year 1950-2024"
 ]
}

 The dataset includes 1692 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091528-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60600/yu/clawet/j463wa
title: 0869.wav

description: :unav
DOI: 10.60600/yu/clawet/lac91c
title: 1004.TextGrid

description: :unav
DOI: 10.60600/yu/clawet/l1ovye
title: 0897.wav

description: :unav
DOI: 10.60600/yu/clawet/fgc5ra
title: 0866.wav

description: :unav
DOI: 10.7924/r43n2cd83
title: Data and Scripts from: Designing a GPU-accelerated communication layer for efficient fluid-structure interaction computations on heterogenous systems

description: This is data supporting results from the paper submission, Designing a GPU-Accelerated Communication Layer for Efficient Fluid-Structure Interaction Computations on Heterogenous Systems, that was accepted to appear in The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC'24). The data was collected through running our proprietary code, HARVEY, on the Polaris (Argonne National Laboratory) and Frontier (Oak Ridge National Laboratory) supercomputers. The data represents performance information that profiles different computational aspects of our code when running at scale on the Polaris and Frontier systems. Data is stored in CSV files automatically generated by HARVEY's internal profiler tools.

Publication abstract:

As biological research demands simulations with increasingly larger cell counts, optimizing these models for large-scale deployment on heterogeneous supercomputing resources becomes crucial. This requires the redesign of fluid-structure interaction tasks written around distributed data structures built for CPU-based systems, where design flexibility and overall memory footprint are key considerations, to instead be performant on CPU-GPU machines. This paper describes the trade-offs of offloading communication tasks to the GPUs and the corresponding changes to the underlying data structures required, along with new algorithms that significantly reduce time-to-solution. At scale performance of our GPU implementation is evaluated on both the Polaris and Frontier leadership systems. Real-world workloads involving millions of deformable cells are evaluated. We analyze the competing factors that come into play when designing a communication layer for a fluid-structure interaction code, including code efficiency, complexity, and GPU memory demands, and offer advice to other high performance computing applications facing similar decisions.
DOI: 10.60600/yu/clawet/2allvy
title: 0715.wav

description: :unav
DOI: 10.60600/yu/clawet/icerkv
title: 0659.TextGrid

description: :unav
DOI: 10.15468/dl.dkwg6v
title: Occurrence Download

description: A dataset containing 7157 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Ireland, Svalbard and Jan Mayen, Portugal, Spain, France, Germany, Belgium, Netherlands, Denmark, Estonia, Latvia, Lithuania, Italy, Greece, Cyprus, Türkiye, Russian Federation, Ukraine, Romania, Bulgaria, Albania, Croatia, Austria, Slovakia, Poland)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Seseli tortuosum L."
 ]
}

 The dataset includes 7157 records from 192 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091530-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60600/yu/clawet/hcrezo
title: 0688.TextGrid

description: :unav
DOI: 10.60600/yu/clawet/qyspwe
title: 0722.TextGrid

description: :unav
DOI: 10.60600/yu/clawet/k7mmuj
title: 0606.TextGrid

description: :unav
DOI: 10.60600/yu/clawet/h9sbpl
title: 0924.TextGrid

description: :unav
DOI: 10.60600/yu/clawet/2smgfu
title: 0638.wav

description: :unav
DOI: 10.15468/dl.wqtzzq
title: Occurrence Download

description: A dataset containing 279150 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Geometry POLYGON((-78.86332 44.93756,-76.54581 44.37446,-74.06757 45.52003,-73.67845 45.62728,-74.13022 48.49933,-79.95368 46.52383,-78.86332 44.93756))",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 279150 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0091525-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60600/yu/clawet/x035i2
title: 0728.wav

description: :unav
DOI: 10.60600/yu/clawet/dc0h1y
title: 1030.TextGrid

description: :unav