cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/3bs5f8mvbs
title: Visium data on human subcutaneous white adipose tissue (scWAT)

description: The deposited data is presented in the manuscript by Bäckdahl J & Franzén L, et al., with the title "Spatial Mapping Reveals Human Adipocyte Subpopulations with Distinct Sensitivities to Insulin". Visium data in the format of Space Ranger output can be found for each individual section analysed (S41-S55), which contains raw and filtered count matrices and spatial/image data. Sample metadata contains information for each sample with linked subject information. Seurat objects containing the downstream analyses can be found as well, which for instance contains the spot clustering information presented in the article. Output data from the stereoscope analysis described in the article can be found here as well.
DOI: 10.17632/7smjmdy4rk
title: Water Level IoT Monitoring System Data (Obtained & Analyzed)

description: This dataset contains an excel file and some useful figures. The excel file contains all data collected by the sensors of the Water Level IoT Monitoring System where it is analyzed and compared to another specifications. The data are in types of tables, graphs, and flowcharts. In addition, the uploaded four images are a described flowchart of the IoT system, functional process of the system, project prototype, project testing. Furthermore, the code of the system sensors is uploaded for further consideration for the used algorithm and sufficient structure.
DOI: 10.17632/jm4ndf8r9j
title: Development of a robotic-assisted handling and manipulation system for the high-scale bioproduction of 3D-bioprinted organ-on-a-chip devices

description: Organs-on-a-chip (OoCs) have proven to mimic the basic physiological behavior of organs and the influence of therapeutics on them in greater detail than conventional models, resulting in enormous projected market growth rates. However, the breakthrough to profitable commercialization of that technology has not yet been achieved, partly because the production process chain is characterized by a high proportion of manual laboratory work. The present work addresses this point. Utilizing affordable components, a demonstrator was developed that can be integrated into an existing 3D-bioprinting system and enables the automated production of perfusion-ready OoC devices starting from pre-fabricated injection-molded microfluidic chips. To this end, a corresponding process chain was first defined, and an expandable, configurable algorithm was developed and validated in the form of a finite state machine (FSM). This algorithm controls a modified 4-axis robot arm that covers the steps upstream and downstream of the printing process in the manufacturing process and achieves success rates of up to 100%. A virtual interface between the robot and printer enables mutual communication and full integration of the algorithm into the process chain. Steps that pose a challenge for the automation of the process chain and appropriate countermeasures and optimizations were identified. This lays the foundation for scaling and standardizing the automated production of OoCs.

This repository contains the design files (CAD, STLs) for the work described.
DOI: 10.17632/8bhhk7c5n9
title: Whole-cortex in situ sequencing reveals peripheral input-dependent cellular and area identity - pilot brain

description: BARseq was used as a standalone spatial transcriptomic method to interrogate the expression of 104 cell type maker genes in one hemisphere of the mouse cortex. Data consist of 40 hemi-coronal sections covering the whole cortex and subcortical areas. Include intermediate processed data and cell type spatial analysis. Associated clustering and gene expression-level analyses are provided at https://github.com/gillislab/barseq_analysis. Accompanying manuscript: https://doi.org/10.1101/2022.11.06.515380
DOI: 10.17632/bgyz8htmkd
title: Data for: An Improved Resistance-Based Thermal Model for a Pouch Lithium-ion Battery Considering Heat Generation of Tabs
DOI: 10.17632/jnvgdhtmd5
title: Data for: Infraestrutura Verde: conceitos, tipologias e terminologia no Brasil

description: Data for: Green infrastructure: concepts, typologies, and terminology in Brazil Description: These are the raw data of a literature review about the concepts, typologies, and terminology in green infrastructure studies in Brazil. Data for: Infraestrutura Verde: conceitos, tipologias e terminologia no Brasil Descrição: Neste DataSet estão compiladas as informações a respeito de 75 artigos publicados por periódicos indexados no Brasil (2008-2018) que apresentam uma definição do conceito de Infraestrutura Verde (IV). Foram levantados: (i) dados gerais do artigo, como o DOI, título do trabalho, nome do periódico, páginas, ano de publicação, nome dos autores e coautores, área de formação do autor principal, palavras-chave utilizadas e link onde o artigo está disponível; (ii) conceito de IV apresentado, com o excerto do texto onde o conceito de IV é apresentado, página de ocorrência e referência bibliográfica utilizada pelos autores; (iii) tipologias de IV, com os diferentes termos catalogados que são utilizados pelos autores para se referir às tipologias de IV. Para utilizar o DataSet é só realizar o download da planilha.
DOI: 10.17632/xsb2j3gs32
title: Stress-strain and fracture acoustic emission dataset of high-strength concrete for metro tunnel lining

description: The stress-strain and fracture acoustic emission dataset of high-strength concrete for metro tunnel lining contains lining cracks, water leakage, concrete fractures, stress-strain data and acoustic emission data.
DOI: 10.17632/7rvw8w8cdm
title: RNA sequencing of regional human astrocytes treated with cytokines

description: Commercially available (ScienCell Research Laboratories) primary human astrocytes were treated with 10ng/ml recombinant cytokine for 24 hours. RNA was collected and sequenced by the Cleveland Clinic Genomics Core.
DOI: 10.17632/fmb2fwb53f
title: GutierrezBarragan_CB2021_medIso_rsfMRI_mouse

description: Resting state fMRI data from n=14 mice under medetomidine-isoflurane anesthesia (0.05 mg/kg bolus and 0.1 mg/kg/h IV infusion, plus 0.5% isoflurane) from Gutierrez-Barragan et al. 2021  (DOI pending). Scans were acquired at the IIT laboratory in Rovereto (Italy) on a 7.0 Tesla MRI scanner (Bruker Biospin, Ettlingen) with a BGA-9 gradient set, a 72 mm birdcage transmit coil, and a three-channel  solenoid receive coil. Awake scans used a single-shot echo planar imaging (EPI) sequence with the following parameters: TR/TE=1000/15 ms, flip angle=60°, matrix=100 x 100, FOV=2.3 x 2.3 cm, 18 coronal slices (voxel-size 230 x 230 x 600 µm), slice thickness=600 µm and 1920 time points, for a total time of 32 minutes.  It is suggested to remove the first 120 scans (2 minutes) to account for thermal gradient equilibration.
DOI: 10.17632/v594mhbh56
title: Percolation of low-dimensional water at crystalline interfaces

description: Combining molecular dynamics simulations and thermodynamics calculations, we show that water can be intercalated into crystalline interfaces (graphite and mica interlayers), which is thermodynamically driven under appropriate pressure and temperature conditions. The data (data.docx) here are the pressure-temperature stability limits of monolayer and bilayer water at the crystalline interfaces. Input files for molecular dynamics simulations are in Simulation_input_files.rar, wherein a Read_me.txt file illustrates the input file information.
DOI: 10.17632/w3z4z4wwv6
title: Human Postnatal Thymus CITE-seq & ATAC-seq Data Repository

description: Human postnatal thymus datasets (4-33 months of age). Cells were enriched for CD45- and CD25+CD8- cells and then split for CITE-seq and ATAC-seq. CITE-seq cells were stained with the Biolegend TotalSeq-C human universal antibody panel v1.0 and captured with 10X Genomics 5' v2 kits. ATAC-seq nuclei were prepped using 10X Genomics reagents and captured using ATAC v1 kits.
DOI: 10.6084/m9.figshare.3557910.v1
title: Appendix E. Multi-dimensional scaling (MDS) ordinations illustrating effects of patch isolation and disturbance regime on beta diversity.

description: Multi-dimensional scaling (MDS) ordinations illustrating effects of patch isolation and disturbance regime on beta diversity.
DOI: 10.17632/bgx8yf3mfn
title: Replication Package for " Types of Employment and Well-being of Rural Residents: A Multinomial Endogenous Switching Regression Application"

description: This replication package contains the data and code necessary to reproduce the results presented in the article. The package is designed for use with Stata.
DOI: 10.17632/3fz9mb7592
title: replication materials for "Trade and Firm Financing", by Bergin, Feng and Lin

description: replication materials for "Trade and Firm Financing", by Bergin, Feng and Lin
DOI: 10.34740/kaggle/dsv/12816750
title: Trending Youtube Video Statistics (113 Countries)
DOI: 10.15468/dl.fsbyud
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Glyphorynchus spirurus (Vieillot, 1819))",
 "Country is one of (Algeria, Angola, Benin, Botswana, British Indian Ocean Territory, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Congo, Congo, Democratic Republic of the, Côte d’Ivoire, Djibouti, Egypt, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, French Southern Territories, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mayotte, Morocco, Mozambique, Namibia, Niger, Nigeria, Réunion, Rwanda, Saint Helena, Ascension and Tristan da Cunha, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, United Republic of, Togo, Tunisia, Uganda, Western Sahara, Zambia, Zimbabwe)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016508-250525065834625/datasets/export for details.
DOI: 10.7278/s5d-wern-v6kz
title: Alta-Atwater Micro Rain Radar Data 2022–2024
DOI: 10.18738/t8/hunomy
title: Researchers’ Participation in and Motivations for Engaging with Research Information Management Systems

description: Research data for a paper: "Researchers’ Participation in and Motivations for Engaging with Research Information Management Systems"
DOI: 10.18738/t8/jvwsyp
title: SYRIOS project: subset of Antioch Coins

description: This dataset contains 430 entries of a much larger total set. There are 20 fields of metadata. This subset refers exclusively to found coins which were minted in Antioch.
description: Professor Neumann will progressively release more of her dataset. Her website can currently
DOI: 10.18738/t8/ib379o
title: Replication Data for: A subdivision-stabilized B-spline mixed material point method

description: Supporting data and figures for this publication.
DOI: 10.18738/t8/kdbjh1
title: crude_medium_ca_matrix_M1

description: Fluid in place: crude oil
Capillary number: medium
Fracture status: none, M1
DOI: 10.18738/t8/n2uulg
title: Dunes beach profile 2007-2008

description: Historic beach profile data of Galveston Island
DOI: 10.15468/dl.j85256
title: Occurrence Download

description: A dataset containing 3534 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "OccurrenceStatus is Present",
 "TaxonKey is Procyon cancrivorus G"
 ]
}

 The dataset includes 3534 records from 189 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016509-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18738/t8/tnozkp
title: IPEDS Completers Data_2019-2023

description: This dataset has been compiled from publically accessible data. The dataset contains information regarding degree completion at institutions of higher education in the U.S., including U.S. territories. The dataset contains data from institutions that submitted data to the National Center for Education Statistics (NCES).
description: Raw data files are publicly available. The dataset provided here has been combined and cleaned for ease of use. For more detailed descriptions on terminology, use the "dictionary" files associated with each dataset type that found on this website: https://nces.ed.gov/ipeds/datacenter/DataFiles.aspx?gotoReportId=7&fromIpeds=true&sid=1f9eb9e4-f6f4-4f7a-a043-ba1e2092ba85&rtid=7
DOI: 10.15468/dl.bwn6ub
title: Occurrence Download

description: A dataset containing 744523 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Animalia",
 "Year is 2026",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 744523 records from 70 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005992-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6a9x8m
title: Occurrence Download

description: A dataset containing 600772 records in GBIF matching the query:
SELECT 
 "gbifid", "taxonkey", "phylum", "class", "order", "eventdate", "datasetkey", "countrycode", "stateprovince", "decimallongitude", "decimallatitude" 
FROM occurrence 
WHERE 
 ("hasgeospatialissues" = 'false') AND 
 ("hascoordinate" = 'true') AND 
 ("occurrencestatus" = 'PRESENT') AND 
 NOT("basisofrecord" IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')) AND 
 ("decimallatitude" &gt;= -90) AND 
 ("decimallatitude" &lt; 0) AND 
 ("decimallongitude" &gt;= -91) AND 
 ("decimallongitude" &lt; -90) AND 
 ("year" &lt;= 2025)

 The dataset's 600772 records were derived from 398 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005986-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g35dcj
title: Occurrence Download

description: A dataset containing 5905 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Melia azedarach",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 5905 records from 432 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006005-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fwamqr
title: Occurrence Download

description: A dataset containing 19724553 records in GBIF matching the query:
SELECT 
 "gbifid", "taxonkey", "phylum", "class", "order", "eventdate", "datasetkey", "countrycode", "stateprovince", "decimallongitude", "decimallatitude" 
FROM occurrence 
WHERE 
 ("hasgeospatialissues" = 'false') AND 
 ("hascoordinate" = 'true') AND 
 ("occurrencestatus" = 'PRESENT') AND 
 NOT("basisofrecord" IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')) AND 
 ("decimallatitude" &gt;= 41) AND 
 ("decimallatitude" &lt; 91) AND 
 ("decimallongitude" &gt;= -89) AND 
 ("decimallongitude" &lt; -88) AND 
 ("year" &lt;= 2025)

 The dataset's 19724553 records were derived from 697 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005988-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g54d6x
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-119.104 33.914,-118.333 33.914,-118.333 34.3,-119.104 34.3,-119.104 33.914))",
 "Month is one of (November, December)",
 "OccurrenceStatus is Present",
 "TaxonKey is Canis latrans",
 "Year is 2019"
 ]
}

 The dataset includes 12 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006006-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.8018624
title: Anthropogenic Specular Interference in the Operational GOES-R Fire Product

description: Dataset for the research paper "Anthropogenic Specular Interference in the Operational GOES-R Fire Product".

Large reflective structures like solar power plants and commercial greenhouses sometimes reflect sunlight directly into GOES-R sensors. These anthropogenic specular reflections, or "sparkles", cause commission errors in operational GOES-R ABI products like the Fire Detection and Characterization Algorithm (FDCA). Using the abi-sparkle library for Python (Dove-Robinson, 2023), we generated a dataset containing both detected anthropogenic specular reflection pixels and the coincident FDCA commission errors caused by them for the GOES-16 CONUS domain during the 2020 calendar year.

The dataset consists of two exported PostgreSQL tables: sparkle_pixels_g16_abi_conus_2020, which contains the detected anthropogenic specular reflection pixels at 500 m resolution, and fdca_commission_error_clusters_g16_abi_conus_2020, which contains clustered FDCA false alarm fire pixels caused by anthropogenic specular reflection at 2 km resolution. The FDCA pixels were only processed for fire mask codes 10-15 and 30-35; see Table 3.11 in Schmidt et al., 2013 for fire code definitions.

Each row in sparkle_pixels_g16_abi_conus_2020 is a detected specular reflection pixel in a GOES-16 CONUS image from the 2020 calendar year with a unique numeric ID sparkle_id and associated metadata from the detection algorithm abi-sparkle. The column sparkle_geom is a PostGIS geometry ST_Point object that can be used to plot the pixels on a map.

FDCA fire pixels at 2 km resolution were clustered based on their connectivity in a 3x3 pixel kernel and assigned a UUID fire_cluster_id in the table fdca_commission_error_clusters_g16_abi_conus_2020. Only the fire clusters that overlapped with sparkle pixels in time and space were retained in the table. In this way, each row of fdca_commission_error_clusters_g16_abi_conus_2020 is a unique cluster of errant FDCA fire pixels caused by anthropogenic specular reflection in every available scan start time for the GOES-16 CONUS domain in 2020. Every fire cluster centroid has a PostGIS geometry object fire_cluster_centroid_geom that can be used to plot the errant fire pixel clusters on a map.

The two tables relate with the column sparkle_ids in fdca_commission_error_clusters_g16_abi_conus_2020, which is an array of overlapping sparkle IDs from the sparkle_pixels_g16_abi_conus_2020 table. The combined dataset may therefore be generated with a simple SQL INNER JOIN:

SELECT * FROM fdca_commission_error_clusters_g16_abi_conus_2020 fcecgacINNER JOIN sparkle_pixels_g16_abi_conus_2020 spgac ON spgac.sparkle_id = ANY(fcecgac.sparkle_ids);

The tables can be imported into a PostgreSQL database version 12 or newer with PostGIS extensions installed. For example, to import the tables into a database in a Linux environment, run the following commands:

gunzip -c sparkle_pixels_g16_abi_conus_2020.sql.gz | psql -d your_database_namegunzip -c fdca_commission_error_clusters_g16_abi_conus_2020.sql.gz | psql -d your_database_name
DOI: 10.5281/zenodo.8018625
title: Anthropogenic Specular Interference in the Operational GOES-R Fire Product

description: Dataset for the research paper "Anthropogenic Specular Interference in the Operational GOES-R Fire Product".

Large reflective structures like solar power plants and commercial greenhouses sometimes reflect sunlight directly into GOES-R sensors. These anthropogenic specular reflections, or "sparkles", cause commission errors in operational GOES-R ABI products like the Fire Detection and Characterization Algorithm (FDCA). Using the abi-sparkle library for Python (Dove-Robinson, 2023), we generated a dataset containing both detected anthropogenic specular reflection pixels and the coincident FDCA commission errors caused by them for the GOES-16 CONUS domain during the 2020 calendar year.

The dataset consists of two exported PostgreSQL tables: sparkle_pixels_g16_abi_conus_2020, which contains the detected anthropogenic specular reflection pixels at 500 m resolution, and fdca_commission_error_clusters_g16_abi_conus_2020, which contains clustered FDCA false alarm fire pixels caused by anthropogenic specular reflection at 2 km resolution. The FDCA pixels were only processed for fire mask codes 10-15 and 30-35; see Table 3.11 in Schmidt et al., 2013 for fire code definitions.

Each row in sparkle_pixels_g16_abi_conus_2020 is a detected specular reflection pixel in a GOES-16 CONUS image from the 2020 calendar year with a unique numeric ID sparkle_id and associated metadata from the detection algorithm abi-sparkle. The column sparkle_geom is a PostGIS geometry ST_Point object that can be used to plot the pixels on a map.

FDCA fire pixels at 2 km resolution were clustered based on their connectivity in a 3x3 pixel kernel and assigned a UUID fire_cluster_id in the table fdca_commission_error_clusters_g16_abi_conus_2020. Only the fire clusters that overlapped with sparkle pixels in time and space were retained in the table. In this way, each row of fdca_commission_error_clusters_g16_abi_conus_2020 is a unique cluster of errant FDCA fire pixels caused by anthropogenic specular reflection in every available scan start time for the GOES-16 CONUS domain in 2020. Every fire cluster centroid has a PostGIS geometry object fire_cluster_centroid_geom that can be used to plot the errant fire pixel clusters on a map.

The two tables relate with the column sparkle_ids in fdca_commission_error_clusters_g16_abi_conus_2020, which is an array of overlapping sparkle IDs from the sparkle_pixels_g16_abi_conus_2020 table. The combined dataset may therefore be generated with a simple SQL INNER JOIN:

SELECT * FROM fdca_commission_error_clusters_g16_abi_conus_2020 fcecgacINNER JOIN sparkle_pixels_g16_abi_conus_2020 spgac ON spgac.sparkle_id = ANY(fcecgac.sparkle_ids);

The tables can be imported into a PostgreSQL database version 12 or newer with PostGIS extensions installed. For example, to import the tables into a database in a Linux environment, run the following commands:

gunzip -c sparkle_pixels_g16_abi_conus_2020.sql.gz | psql -d your_database_namegunzip -c fdca_commission_error_clusters_g16_abi_conus_2020.sql.gz | psql -d your_database_name
DOI: 10.34740/kaggle/dsv/14702145
title: BITCOIN Historical Datasets 2018-2026 Binance API
DOI: 10.15468/dl.p6tmhb
title: Occurrence Download

description: A dataset containing 171 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Munronia pinnata",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 171 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006007-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jmq97g
title: Occurrence Download

description: A dataset containing 11289763 records in GBIF matching the query:
SELECT 
 "gbifid", "taxonkey", "phylum", "class", "order", "eventdate", "datasetkey", "countrycode", "stateprovince", "decimallongitude", "decimallatitude" 
FROM occurrence 
WHERE 
 ("hasgeospatialissues" = 'false') AND 
 ("hascoordinate" = 'true') AND 
 ("occurrencestatus" = 'PRESENT') AND 
 NOT("basisofrecord" IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')) AND 
 ("decimallatitude" &gt;= 42) AND 
 ("decimallatitude" &lt; 91) AND 
 ("decimallongitude" &gt;= -88) AND 
 ("decimallongitude" &lt; -87) AND 
 ("year" &lt;= 2025)

 The dataset's 11289763 records were derived from 575 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005996-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.