cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.4gtu6n
title: Occurrence Download

description: A dataset containing 1059 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is one of (Coleção Entomológica Padre Jesus Santiago Moure (DZUP) - Coleoptera, iNaturalist Research-grade Observations, MCTP-Insetos - Coleção de Insetos, Coleção Entomológica do Setor Palotina, Universidade Federal do Paraná, Taxonomic revision of the Canthidium Erichson, 1847 species of the gigas group (Coleoptera, Scarabaeidae, Scarabaeinae))",
 "Geometry POLYGON((-54.18051 -25.00873,-53.73547 -25.39865,-52.97773 -25.69287,-48.90681 -26.26181,-48.58665 -25.83473,-47.6607 -24.77001,-48.58665 -23.54801,-52.04224 -22.74427,-52.73414 -22.6302,-53.38607 -22.94219,-53.87504 -23.76162,-54.18051 -25.00873))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Scarabaeidae",
 "Year 2000-2025"
 ]
}

 The dataset includes 1059 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0085295-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/smrpc1
title: PAN-00155668 - spoon-bow brooch variant Brienenshof-Grave

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00155668&lt;/p&gt;
description: Modified: 2024-10-25T20:21:43+02:00
DOI: 10.3535/cel-4g8-96n
title: Psorergates crocidurae Lukoschus, 1968

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.15468/dl.d2kysf
title: Occurrence Download

description: A dataset containing 341 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-62.48133 8.70181,-56.23493 -34.84866,-41.95744 -36.30017,-38.83424 -32.62268,-25.00293 -26.4156,-19.2027 -8.19102,-29.91082 10.46152,-62.48133 8.70181))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Thunnus obesus (Lowe, 1839)",
 "Year 2000-2024"
 ]
}

 The dataset includes 341 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006998-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w3cx9w
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Portugal",
 "TaxonKey is Alkanna tinctoria subsp. tinctoria",
 "Year 1975-2025"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007000-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3eg4uv
title: Occurrence Download

description: A dataset containing 3312 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Platystoma seminationis (Fabricius, 1775)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3312 records from 89 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007002-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xxbtck
title: Occurrence Download

description: A dataset containing 196 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-37.59760 -42.45584,89.59760 -42.45584,89.59760 8.45584,-37.59760 8.45584,-37.59760 -42.45584))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Orycteropus afer afer"
 ]
}

 The dataset includes 196 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007003-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g85m97
title: Occurrence Download

description: A dataset containing 591316 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is eButterfly Surveys"
 ]
}

 The dataset includes 591316 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006995-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14961645
title: Single cell RNA sequencing of spinal cells from mice with cisplatin-induced neuropathic pain

description: Single cell RNA sequencing of spinal cells from mice with cisplatin-induced neuropathic pain.
DOI: 10.5281/zenodo.14961646
title: Single cell RNA sequencing of spinal cells from mice with cisplatin-induced neuropathic pain

description: Single cell RNA sequencing of spinal cells from mice with cisplatin-induced neuropathic pain.
DOI: 10.5281/zenodo.15019407
title: Cars in Stuttgart

description: This dataset is an educational toy dataset for object detection with remote sensing data. The dataset contains aerial imagery of the city of Stuttgart at 20cm ground sample distance together with bounding box labels indicating cars (single class) present in these images. Labels are present in the COCO format.

The dataset is split into three parts:* a training split (1000 images),* a validation split (190 images) and* a test split (190 images).

Each image features a height and width of 128 pixels each, contains RGB bands and is stored in the png format. Image data were cropped from aerial imagery of the city of Stuttgart taken in 2021, which are available through Stadtmessungsamt Stuttgart as open data under the CC BY 4.0 license: https://opendata.stuttgart.de/dataset/luftbilder-2021

This dataset has been labeled by Yilsey Terea Benavides Miranda, Khem Raj Devkota, David Michael Udoh and Gökhan Yücesan as part of the Master of Photogrammetry and Geoinformatics course "Remote Sensing Studio" in the 2024 summer term at the Stuttgart University of Applied Sciences.
DOI: 10.5281/zenodo.15019408
title: Cars in Stuttgart

description: This dataset is an educational toy dataset for object detection with remote sensing data. The dataset contains aerial imagery of the city of Stuttgart at 20cm ground sample distance together with bounding box labels indicating cars (single class) present in these images. Labels are present in the COCO format.

The dataset is split into three parts:* a training split (1000 images),* a validation split (190 images) and* a test split (190 images).

Each image features a height and width of 128 pixels each, contains RGB bands and is stored in the png format. Image data were cropped from aerial imagery of the city of Stuttgart taken in 2021, which are available through Stadtmessungsamt Stuttgart as open data under the CC BY 4.0 license: https://opendata.stuttgart.de/dataset/luftbilder-2021

This dataset has been labeled by Yilsey Terea Benavides Miranda, Khem Raj Devkota, David Michael Udoh and Gökhan Yücesan as part of the Master of Photogrammetry and Geoinformatics course "Remote Sensing Studio" in the 2024 summer term at the Stuttgart University of Applied Sciences.
DOI: 10.5281/zenodo.10514142
title: 50 Years of Load Simulation of the NREL 5MW OC4 Floating Wind Turbine

description: This dataset contains the post-processed results of 447073 one-hour simulations of the NREL 5MW OC4 Floating Offshore Wind Turbine (FOWT) [1]. The environmental conditions are derived for an offshore site west of the island of Barra (Scotland), with the procedure described in [2]. The code used to download and process the environmental conditions is adapted from [4]. Data spans from 01-01-1972 to 31-12-2022 for a total of 51 years. Simulations are performed using the open-source code OpenFAST v3.0.0 [3]. All simulations are one hour long. For each simulation and for each load sensor in the dataset, the following quantities are computed: 



statistics: mean, maximum and minimum value recorded, standard deviation, kurtosis and skewness of each load sensor in each simulation. 

damage equivalent loads: one-herz, zero-mean damage equivalent loads (DELs) for each simulation and each load sensor. 3600 equivalent cycles per simulation. 128 load bins are used to rainflow count the load cycles in each simulation. 


The first six columns of each file contain: timestamp, mean wind speed intensity at 100m above sea level, significant wave height (includes wind and swell waves), peak spectral period and wind-wave misalignment,  fixed nacelle yaw error, seed used in pseudo-random windfield generator (TurbSim) and wave-field generator (HydroDyn) and IEC turbulence class. Waves are considered uni-directional. 

 

More information on the dataset is contained in the following paper. Please cite it if you use this dataset in your work: Papi F., Bianchini A.: A New Perspective on Offshore Wind Turbine Certification Using High Performance Computing, proceedings of the "Science from Making Torque from the Wind" TORQUE 2024, Firenze, 29-31 Apr. 2024, DOI 10.1088/1742-6596/2767/5/052008, https://iopscience.iop.org/article/10.1088/1742-6596/2767/5/052008

 

References:

[1] Jonkman J, Butterfield S, Musial W and Scott G 2009 Definition of a 5-MW Reference Wind Turbine for Offshore System Development

[2] Papi F, Perignon Y and Bianchini A 2022 Derivation of Met-Ocean Conditions for the Simulation of Floating Wind Turbines: a European case study J. Phys. Conf. Ser. 2385 012117

[3] National Renewable Energy Laboratory, OpenFAST, GitHub, https://github.com/OpenFAST/openfast/releases/tag/v3.0.0 

[4] Francesco Papi. (2023). An Open-Source Procedure to Derive Met-Ocean Conditions for the Simulation of Floating Wind Turbines (1.1.0). Zenodo. https://doi.org/10.5281/zenodo.10102696
DOI: 10.5281/zenodo.10514143
title: 50 Years of Load Simulation of the NREL 5MW OC4 Floating Wind Turbine

description: This dataset contains the post-processed results of 447073 one-hour simulations of the NREL 5MW OC4 Floating Offshore Wind Turbine (FOWT) [1]. The environmental conditions are derived for an offshore site west of the island of Barra (Scotland), with the procedure described in [2]. The code used to download and process the environmental conditions is adapted from [4]. Data spans from 01-01-1972 to 31-12-2022 for a total of 51 years. Simulations are performed using the open-source code OpenFAST v3.0.0 [3]. All simulations are one hour long. For each simulation and for each load sensor in the dataset, the following quantities are computed: 



statistics: mean, maximum and minimum value recorded, standard deviation, kurtosis and skewness of each load sensor in each simulation. 

damage equivalent loads: one-herz, zero-mean damage equivalent loads (DELs) for each simulation and each load sensor. 3600 equivalent cycles per simulation. 128 load bins are used to rainflow count the load cycles in each simulation. 


The first six columns of each file contain: timestamp, mean wind speed intensity at 100m above sea level, significant wave height (includes wind and swell waves), peak spectral period and wind-wave misalignment,  fixed nacelle yaw error, seed used in pseudo-random windfield generator (TurbSim) and wave-field generator (HydroDyn) and IEC turbulence class. Waves are considered uni-directional. 

 

More information on the dataset is contained in the following paper. Please cite it if you use this dataset in your work: Papi F., Bianchini A.: A New Perspective on Offshore Wind Turbine Certification Using High Performance Computing, proceedings of the "Science from Making Torque from the Wind" TORQUE 2024, Firenze, 29-31 Apr. 2024, DOI 10.1088/1742-6596/2767/5/052008, https://iopscience.iop.org/article/10.1088/1742-6596/2767/5/052008

 

References:

[1] Jonkman J, Butterfield S, Musial W and Scott G 2009 Definition of a 5-MW Reference Wind Turbine for Offshore System Development

[2] Papi F, Perignon Y and Bianchini A 2022 Derivation of Met-Ocean Conditions for the Simulation of Floating Wind Turbines: a European case study J. Phys. Conf. Ser. 2385 012117

[3] National Renewable Energy Laboratory, OpenFAST, GitHub, https://github.com/OpenFAST/openfast/releases/tag/v3.0.0 

[4] Francesco Papi. (2023). An Open-Source Procedure to Derive Met-Ocean Conditions for the Simulation of Floating Wind Turbines (1.1.0). Zenodo. https://doi.org/10.5281/zenodo.10102696
DOI: 10.18112/openneuro.ds006001.v1.0.0
title: Probabilistic Mapping and Automated Segmentation of Human Brainstem White Matter Bundles
DOI: 10.6084/m9.figshare.27093856
title: There are issues with the data.

description: Here contains the genome data of male <i>Hippophae gyantsensis</i>, female <i>Hippophae salicifolia</i> and male <i>Hippophae salicifolia</i>. Male <i>Hippophae salicifolia</i> included two sets of haplotype data, hap1 and hap2.
DOI: 10.17043/tarfala-monthly-temperature-2
title: Monthly mean air temperatures from Tarfala Research Station, Kebnekaise Mountains, Northern Sweden
DOI: 10.15468/dl.5mj7b8
title: Occurrence Download

description: A dataset containing 591316 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is eButterfly Surveys"
 ]
}

 The dataset includes 591316 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006994-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10932357
title: Co-UDlabs_TA_USFD-03-Annular Morato_Annular Flume studies to test the effect on Antibiotic Resistant Genes and Use of CRISPR- Cas in E. coli from sediments affected by sewage pollution.

description: This document is a data storage report of the Co-UDlabs project, funded under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101008626.

The aim of this document is to describe the experimental campaign and how data were collected on the research activity “Annular Flume studies to test the effect on Antibiotic Resistant Genes and Use of CRISPR- Cas in E. coli from sediments affected by sewage pollution.”

This project aims to:

 · To characterise antimicrobial resistance in sediments affected by river faecal pollution by using annular flume tests under controlled conditions. 

·  To test the use of CRISPR-Cas9, genetic editing tool, as a mitigation technique of antibiotic resistance in rivers impacted by sediments derived from urban drainage system.
DOI: 10.5281/zenodo.10932358
title: Co-UDlabs_TA_USFD-03-Annular Morato_Annular Flume studies to test the effect on Antibiotic Resistant Genes and Use of CRISPR- Cas in E. coli from sediments affected by sewage pollution.

description: This document is a data storage report of the Co-UDlabs project, funded under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101008626.

The aim of this document is to describe the experimental campaign and how data were collected on the research activity “Annular Flume studies to test the effect on Antibiotic Resistant Genes and Use of CRISPR- Cas in E. coli from sediments affected by sewage pollution.”

This project aims to:

 · To characterise antimicrobial resistance in sediments affected by river faecal pollution by using annular flume tests under controlled conditions. 

·  To test the use of CRISPR-Cas9, genetic editing tool, as a mitigation technique of antibiotic resistance in rivers impacted by sediments derived from urban drainage system.
DOI: 10.5281/zenodo.14950398
title: Spatial Transcriptomics and Single Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver - ST BAM Female rAAV9-Treated Animals

description: You can find here the BAM files related to the datasets used in the publication: 

Amberg, B. et al.  Spatial Transcriptomics and Single Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver

In this particular upload, you can find the spatial transcriptomics  BAM files of the female rAAV9-treated animals.
DOI: 10.5281/zenodo.14950399
title: Spatial Transcriptomics and Single Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver - ST BAM Female rAAV9-Treated Animals

description: You can find here the BAM files related to the datasets used in the publication: 

Amberg, B. et al.  Spatial Transcriptomics and Single Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver

In this particular upload, you can find the spatial transcriptomics  BAM files of the female rAAV9-treated animals.
DOI: 10.5281/zenodo.14950428
title: Spatial Transcriptomics and Single Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver - ST BAM Male rAAV9-Treated Animals

description: You can find here the BAM files related to the datasets used in the publication: 

Amberg, B. et al.  Spatial Transcriptomics and Single Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver

In this particular upload, you can find the spatial transcriptomics  BAM files of the male rAAV9-treated animals.
DOI: 10.5281/zenodo.14950429
title: Spatial Transcriptomics and Single Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver - ST BAM Male rAAV9-Treated Animals

description: You can find here the BAM files related to the datasets used in the publication: 

Amberg, B. et al.  Spatial Transcriptomics and Single Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver

In this particular upload, you can find the spatial transcriptomics  BAM files of the male rAAV9-treated animals.
DOI: 10.5281/zenodo.14950548
title: Spatial Transcriptomics and Single Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver - ST FASTQ Male Control Animals 102 and 103

description: You can find here the FASTQ files related to the datasets used in the publication: 

Amberg, B. et al.  Spatial Transcriptomics and Single Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver

In this particular upload, you can find the spatial transcriptomics  FASTQ files of the male control animals from the samples SN393_A1_102 and SN387_B1_103
DOI: 10.5281/zenodo.14950549
title: Spatial Transcriptomics and Single Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver - ST FASTQ Male Control Animals 102 and 103

description: You can find here the FASTQ files related to the datasets used in the publication: 

Amberg, B. et al.  Spatial Transcriptomics and Single Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver

In this particular upload, you can find the spatial transcriptomics  FASTQ files of the male control animals from the samples SN393_A1_102 and SN387_B1_103
DOI: 10.5281/zenodo.14950677
title: Spatial Transcriptomics and Single Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver - ST FASTQ Female Control Animals 151 and 153

description: You can find here the FASTQ files related to the datasets used in the publication: 

Amberg, B. et al.  Spatial Transcriptomics and Single Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver

In this particular upload, you can find the spatial transcriptomics  FASTQ files of the female control animals from the samples SN275_C1_151 and SN275b_D1_153
DOI: 10.5281/zenodo.14950678
title: Spatial Transcriptomics and Single Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver - ST FASTQ Female Control Animals 151 and 153

description: You can find here the FASTQ files related to the datasets used in the publication: 

Amberg, B. et al.  Spatial Transcriptomics and Single Nucleus RNA Sequencing Reveal rAAV2- and rAAV9-Specific Transduction Signatures in the Mouse Liver

In this particular upload, you can find the spatial transcriptomics  FASTQ files of the female control animals from the samples SN275_C1_151 and SN275b_D1_153
DOI: 10.5281/zenodo.15019059
title: Input and output files of the case studies included in the manuscript "MUUMI: an R package for statistical and network-based meta-analysis for MUlti-omics data Integration".

description: This repository contains the input and output files necessary to reproduce the case studies reported in the manuscript "MUUMI: an R package for statistical and network-based meta-analysis for MUlti-omics data Integration". MUUMI is an R package implementing network-based data integration and statistical meta-analysis within a single analytical framework. MUUMI allows the identification of robust molecular signatures through multiple meta-analytic methods, inference and analysis of molecular interactomes and the integration of multiple omics layers. The functionalities of MUUMI are showcased in two case studies in which we analysed 17 transcriptomic datasets on idiopathic pulmonary fibrosis (IPF) from both microarray and RNA-Seq platforms and multi-omics data of THP-1 macrophages exposed to different polarising stimuli. Part of the data reported in this repository derive from the Zenodo entry https://doi.org/10.5281/zenodo.10692129 (Curated and harmonised transcriptomics datasets of interstitial lung disease patients). Other data derive from the following publication: Migliaccio G, Morikka J, del Giudice G, Vaani M, Möbus L, Serra A, Federico A, Greco D. Methylation and transcriptomic profiling reveals short term and long term regulatory responses in polarized macrophages, Comp and Struct Biotech J, 2024(25), 143-152. doi: 10.1016/j.csbj.2024.08.018.
DOI: 10.5281/zenodo.15019060
title: Input and output files of the case studies included in the manuscript "MUUMI: an R package for statistical and network-based meta-analysis for MUlti-omics data Integration".

description: This repository contains the input and output files necessary to reproduce the case studies reported in the manuscript "MUUMI: an R package for statistical and network-based meta-analysis for MUlti-omics data Integration". MUUMI is an R package implementing network-based data integration and statistical meta-analysis within a single analytical framework. MUUMI allows the identification of robust molecular signatures through multiple meta-analytic methods, inference and analysis of molecular interactomes and the integration of multiple omics layers. The functionalities of MUUMI are showcased in two case studies in which we analysed 17 transcriptomic datasets on idiopathic pulmonary fibrosis (IPF) from both microarray and RNA-Seq platforms and multi-omics data of THP-1 macrophages exposed to different polarising stimuli. Part of the data reported in this repository derive from the Zenodo entry https://doi.org/10.5281/zenodo.10692129 (Curated and harmonised transcriptomics datasets of interstitial lung disease patients). Other data derive from the following publication: Migliaccio G, Morikka J, del Giudice G, Vaani M, Möbus L, Serra A, Federico A, Greco D. Methylation and transcriptomic profiling reveals short term and long term regulatory responses in polarized macrophages, Comp and Struct Biotech J, 2024(25), 143-152. doi: 10.1016/j.csbj.2024.08.018.
DOI: 10.15468/dl.v86efj
title: Occurrence Download

description: A dataset containing 38 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Goeppertia dilabens (L.Andersson & H.Kenn.) Borchs. & S.Suárez"
 ]
}

 The dataset includes 38 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007005-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.