cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17143291
title: Supplementary data for "More frequent warm and dry spells along persistent cold and wet spells in the Baltics"

description: Data accompanying publication “Climate warming brings rise of warm and dry spells while cold and wet spells persist in the Baltics” (DOI: 10.1007/s00704-026-06099-w):

1.    [1_cell_id.csv] Cell identification and respective coordinates WGS84 reference system:

2.    [2_daily.csv] Mean daily temperature, precipitation, reference evapotranspiration and water balance calculated from original hourly ERA5-land reanalysis (data in Fig. 2):

3.    [3_DoY_stat.csv] Long term (1961-2020) 31-day moving window day-of-the-year (DoY) average and Q10 and Q90 temperature, precipitation, reference evapotranspiration and water balance:

4.    [4_all_spells.csv] Warm/cold and dry/wet spells stratified by grid cell

5.    [5_spell_stat.csv] Summary statistics for warm/cold and dry/wet spells stratified by grid cell and climate normal period:

6.    [6_spell_trend.csv] Linear trend for warm/cold and dry/wet spells during 1961 to 2020.

Explanation of abbreviations and variable names:

1.    Cell_ID – cell identifier

2.    X, Y – X and T coordinates in WGS 4 reference system

4.    Par – meteorological parameters

     T – mean daily 2m air temperature

     P – daily precipitation

     ET0 – reference evapotranspiration

     CWB – daily climatological water balance

4.    Stat – statistical parameter

     Q10 – 10th quantile

     Q90 – 90th quantile

     Mean – average 

     <1 mm – precipitation less than 1 mm

5.    Season – season of the year

     DJF – December, January, February

     MAM – March, April, May

     JJA – June, July, August

     SON – September, October, November 

6.    Npar – minim spell duration criteria

     N – at least 1 day

     N2 – at least 2 days

     Nmax – longest spell in a season

7.    Period – climate normal period

     Reference – 1961-1990

     Normal-3 – 1991-2020

8.    MeanDays – mean duration of episode of unusual weather (spell)

9.    MeanNumber – mean number of episodes of unusual weather (spell) in a season

10.    MeanLength – mean length of episode of unusual weather (spell)

11.    MaxDays – duration of longest episode of unusual weather (spell)

 

Data derived from ERA5-Land data set provided by the Copernicus Climate Change Service (C3S) Climate Data Store (https://cds.climate.copernicus.eu) accessed on 2024-04-26. ERA5-land data are described in Muñoz-Sabater et al. (2021).
DOI: 10.5281/zenodo.17143292
title: Supplementary data for "More frequent warm and dry spells along persistent cold and wet spells in the Baltics"

description: Data accompanying publication “Climate warming brings rise of warm and dry spells while cold and wet spells persist in the Baltics” (DOI: 10.1007/s00704-026-06099-w):

1.    [1_cell_id.csv] Cell identification and respective coordinates WGS84 reference system:

2.    [2_daily.csv] Mean daily temperature, precipitation, reference evapotranspiration and water balance calculated from original hourly ERA5-land reanalysis (data in Fig. 2):

3.    [3_DoY_stat.csv] Long term (1961-2020) 31-day moving window day-of-the-year (DoY) average and Q10 and Q90 temperature, precipitation, reference evapotranspiration and water balance:

4.    [4_all_spells.csv] Warm/cold and dry/wet spells stratified by grid cell

5.    [5_spell_stat.csv] Summary statistics for warm/cold and dry/wet spells stratified by grid cell and climate normal period:

6.    [6_spell_trend.csv] Linear trend for warm/cold and dry/wet spells during 1961 to 2020.

Explanation of abbreviations and variable names:

1.    Cell_ID – cell identifier

2.    X, Y – X and T coordinates in WGS 4 reference system

4.    Par – meteorological parameters

     T – mean daily 2m air temperature

     P – daily precipitation

     ET0 – reference evapotranspiration

     CWB – daily climatological water balance

4.    Stat – statistical parameter

     Q10 – 10th quantile

     Q90 – 90th quantile

     Mean – average 

     <1 mm – precipitation less than 1 mm

5.    Season – season of the year

     DJF – December, January, February

     MAM – March, April, May

     JJA – June, July, August

     SON – September, October, November 

6.    Npar – minim spell duration criteria

     N – at least 1 day

     N2 – at least 2 days

     Nmax – longest spell in a season

7.    Period – climate normal period

     Reference – 1961-1990

     Normal-3 – 1991-2020

8.    MeanDays – mean duration of episode of unusual weather (spell)

9.    MeanNumber – mean number of episodes of unusual weather (spell) in a season

10.    MeanLength – mean length of episode of unusual weather (spell)

11.    MaxDays – duration of longest episode of unusual weather (spell)

 

Data derived from ERA5-Land data set provided by the Copernicus Climate Change Service (C3S) Climate Data Store (https://cds.climate.copernicus.eu) accessed on 2024-04-26. ERA5-land data are described in Muñoz-Sabater et al. (2021).
DOI: 10.25345/c5hq3sc2z
title: MassIVE MSV000100744 - Itaconate as a regulator of HSPC
title: To investigate the role of itaconate on HSPC, we isolated ckit+ HSPC from Acod1-KO mice, which lack the enzyme necessary for the synthesis of itaconate. We found that Acod1 deficiency promotes HSC serial replating capacity and engraftment of WBM in non-lethally irradiated recipient mice. Omics analyses reveal that Acod1-deficiency promotes transcription of HSC stem cell genes at the consequence of downregulation of myeloid differentiation genes. These findings are complemented by downregulation of mitochondrial metabolism including TCA cycle/OXPHOS. These findings reveal the importance of itaconate in influencing HSPC fate
DOI: 10.15468/dl.rww6z8
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gibasoides laxiflora",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 23 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016450-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/dmvzgwhkk2
title: Vegetation structure data for Piatra Craiului Mountains

description: Height, diameter and age of sampled trees affected by snow avalanches in Piatra Craiului Mountains (Southern Carpathians).
DOI: 10.5281/zenodo.18506099
title: Datasets for testing the robustness of LiDAR vegetation metrics to varying point densities

description: The calculation of vegetation metrics from LiDAR point clouds might be affected by the available point density of a dataset. Testing how the same LiDAR vegetation metrics differ with different point densities can therefore inform about their robustness for upscaling metrics to other areas or other LiDAR point clouds. The datasets made available here were generated to test the robustness of LiDAR vegetation metrics to varying point densities and spatial resolutions (i.e., plots of 1 × 1 m, 2 × 2 m, 5 × 5 m and 10 × 10 m size). A total of 25 LiDAR vegetation metrics representing different aspects of vegetation height, vegetation cover and structural complexity were tested (see metric definition in Kissling et al. 2023, https://doi.org/10.1016/j.dib.2022.108798). The metric calculation was similar to the metric calculation in the Laserchicken software (Meijer et al. 2020, https://doi.org/10.1016/j.softx.2020.100626) and the Laserfarm workflow (Kissling et al. 2022, https://doi.org/10.1016/j.ecoinf.2022.101836). The Dutch AHN4 dataset from the years 2020–2022 with a point density of 20–30 points/m2 was used. Initially, 100 plots (i.e., squared polygons around centre points) were randomly placed across the Netherlands in Dutch Natura 2000 sites that predominantly contain woodland habitats (using shapefiles from the European Environmental Agency). For each centre point, square polygons of the desired resolutions (i.e., 1 × 1 m, 2 × 2 m, 5 × 5 m or 10 × 10 m plot size) were generated. The square polygons were subsequently used to clip the LiDAR point clouds from the Dutch AHN4 point cloud dataset. Since not all locations of the 100 randomly placed plots contained points, the actual sample sizes were slightly smaller than 100, i.e., 94 plots for the 1 × 1 m, 2 × 2 m and 5 × 5 m resolution and 95 plots for the 10 × 10 m resolution. Metrics were calculated with the original point density of the Dutch AHN4 dataset (20–30 points/m2) and with six systematically down-sampled point clouds for the same plots (i.e., keeping 5%, 10%, 20%, 40%, 60% and 80% of the points in the original point clouds). For each clipped point cloud of a plot at a given resolution, the points were first sorted according to their GPS acquisition time (from earliest to latest). Points were then systematically discarded and only 5%, 10%, 20%, 40%, 60% and 80% of the points in the original point clouds were kept. The kept points were used for calculating the 25 LiDAR vegetation metrics.
DOI: 10.17632/dmvzgwhkk2.1
title: Vegetation structure data for Piatra Craiului Mountains

description: Height, diameter and age of sampled trees affected by snow avalanches in Piatra Craiului Mountains (Southern Carpathians).
DOI: 10.5281/zenodo.13619387
title: Datasets for testing the robustness of LiDAR vegetation metrics to varying point densities

description: The calculation of vegetation metrics from LiDAR point clouds might be affected by the available point density of a dataset. Testing how the same LiDAR vegetation metrics differ with different point densities can therefore inform about their robustness for upscaling metrics to other areas or other LiDAR point clouds. The datasets made available here were generated to test the robustness of LiDAR vegetation metrics to varying point densities and spatial resolutions (i.e., plots of 1 × 1 m, 2 × 2 m, 5 × 5 m and 10 × 10 m size). A total of 25 LiDAR vegetation metrics representing different aspects of vegetation height, vegetation cover and structural complexity were tested (see metric definition in Kissling et al. 2023, https://doi.org/10.1016/j.dib.2022.108798). The metric calculation was similar to the metric calculation in the Laserchicken software (Meijer et al. 2020, https://doi.org/10.1016/j.softx.2020.100626) and the Laserfarm workflow (Kissling et al. 2022, https://doi.org/10.1016/j.ecoinf.2022.101836). The Dutch AHN4 dataset from the years 2020–2022 with a point density of 20–30 points/m2 was used. Initially, 100 plots (i.e., squared polygons around centre points) were randomly placed across the Netherlands in Dutch Natura 2000 sites that predominantly contain woodland habitats (using shapefiles from the European Environmental Agency). For each centre point, square polygons of the desired resolutions (i.e., 1 × 1 m, 2 × 2 m, 5 × 5 m or 10 × 10 m plot size) were generated. The square polygons were subsequently used to clip the LiDAR point clouds from the Dutch AHN4 point cloud dataset. Since not all locations of the 100 randomly placed plots contained points, the actual sample sizes were slightly smaller than 100, i.e., 94 plots for the 1 × 1 m, 2 × 2 m and 5 × 5 m resolution and 95 plots for the 10 × 10 m resolution. Metrics were calculated with the original point density of the Dutch AHN4 dataset (20–30 points/m2) and with six systematically down-sampled point clouds for the same plots (i.e., keeping 5%, 10%, 20%, 40%, 60% and 80% of the points in the original point clouds). For each clipped point cloud of a plot at a given resolution, the points were first sorted according to their GPS acquisition time (from earliest to latest). Points were then systematically discarded and only 5%, 10%, 20%, 40%, 60% and 80% of the points in the original point clouds were kept. The kept points were used for calculating the 25 LiDAR vegetation metrics.
DOI: 10.5281/zenodo.18506100
title: Passive Transponder Implantation in Theraphosidae: A Tool for Traceability and Conservation
DOI: 10.5281/zenodo.18506101
title: Passive Transponder Implantation in Theraphosidae: A Tool for Traceability and Conservation
DOI: 10.5281/zenodo.18505088
title: VibeOracle Experiment Data
DOI: 10.5281/zenodo.18505089
title: VibeOracle Experiment Data
DOI: 10.15468/dl.za8gxf
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Vigna caracalla"
 ]
}

 The dataset includes 3 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016452-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.en5n66
title: Occurrence Download

description: A dataset containing 250 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Murdannia divergens",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 250 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016453-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48804/uf0ah4
title: Dataset for Appendix 2 of Impact of Noise on the Welfare of Laboratory Animals

description: Dataset accompanying the report titled "Impact of Noise on the Welfare of Laboratory Animals". The aim of the report was to provide evidence-based recommendations for managing sound in laboratory animal facilities, funded by the Flemish Government, Department of Animal Welfare (specification number OMG_DWZ_2025_001). The data for this dataset was obtained through a systematic review to give an unbiased and representative picture of how different types of sounds impact reproduction, immune function, sleep, social behaviour (aggression), and anxiety/fear of laboratory rats, mice, pigs, chickens, and zebrafish. 

The dataset was used to create tile plots showing the direction score (DS) for broadband noise, music, urban noise, and narrowband noise (each on separate sheets) per outcome and species. The direction score (DS) was calculated to quantify the evidence that sound was having a positive, negative, no effect, or other effect on target species. DS was calculated based on the number of data points, as (n_positive - n_negative) divided by sum of all effects (n_positive + n_negative + n_none + n_other). Thus, DS ranges from +1 (all studies positive) to -1 (all studies negative). Confidence in DS was classified as ‘low’ when fewer than three unique studies contributed, and as ‘OK’ when three or more unique studies contributed data points to the score.
DOI: 10.5281/zenodo.18506120
title: THE EMERGENCE AND STAGES OF DEVELOPMENT OF RAILWAY TRANSPORT

description: Railway transport has played a crucial role in the economic, industrial, and social development of modern civilization. Since its emergence in the early nineteenth century, the railway system has undergone continuous technological and structural transformations. The evolution of railway transport reflects the progress of engineering, energy systems, and logistics management. This study aims to analyze the historical emergence of railway transport and identify the main stages of its development from early rail systems to modern high-speed and digital railways. A historical-analytical approach was applied through the review of scientific, technical, and historical sources. The results demonstrate that railway transport has evolved through several distinct stages, each characterized by significant innovations that enhanced speed, safety, and efficiency. The discussion highlights the long-term socio-economic impact of railways and their continuing importance in sustainable transportation systems. The study concludes that railway transport remains a strategic element of global infrastructure and continues to adapt to modern technological demands.
DOI: 10.5281/zenodo.18506119
title: THE EMERGENCE AND STAGES OF DEVELOPMENT OF RAILWAY TRANSPORT

description: Railway transport has played a crucial role in the economic, industrial, and social development of modern civilization. Since its emergence in the early nineteenth century, the railway system has undergone continuous technological and structural transformations. The evolution of railway transport reflects the progress of engineering, energy systems, and logistics management. This study aims to analyze the historical emergence of railway transport and identify the main stages of its development from early rail systems to modern high-speed and digital railways. A historical-analytical approach was applied through the review of scientific, technical, and historical sources. The results demonstrate that railway transport has evolved through several distinct stages, each characterized by significant innovations that enhanced speed, safety, and efficiency. The discussion highlights the long-term socio-economic impact of railways and their continuing importance in sustainable transportation systems. The study concludes that railway transport remains a strategic element of global infrastructure and continues to adapt to modern technological demands.
DOI: 10.21227/11tg-9s93
title: "Attention-Enhanced EfficientNet for Real-Time Forest Fire Detection"

description: "the Dataset consists of images with fire and without fire for testing and training purpose."
DOI: 10.21227/k7rj-fk73
title: "WELD"

description: "This dataset provides a collection of high-resolution weld surface images for industrial defect and anomaly detection. Each image is paired with a corresponding ground truth file that accurately delineates defective regions, enabling pixel-level evaluation. The dataset covers multiple typical weld defect types encountered in real manufacturing scenarios and reflects realistic variations in texture, illumination, and defect appearance.The dataset is designed to support research on industrial visual inspection, anomaly detection, and zero-shot or weakly supervised learning methods, where abnormal samples may be scarce or unavailable during training. By providing consistent image\u2013ground truth pairs, this dataset facilitates fair benchmarking for defect localization and detection tasks. It can serve as a valuable resource for both academic research and practical industrial applications."
DOI: 10.15468/dl.tbgr2f
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Palisota albertii",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016454-260129131611470/datasets/export for details.
DOI: 10.60905/pf9ujr
title: Estudiantes de la UdeA no enviar��n delegado a la Ceja

description: &lt;p&gt;Comunicado enviado por el consejo superior estudiantil donde se niegan a enviar y reconocer la representaci��n estudiantil en la reuni��n convocada por el ministro de educaci��n y el presidente de la rep��blica para tratar el tema del ���Plan b��sico de educaci��n superior���. En el texto consideran que bajo el gobierno actual no es posible una reforma de importancia ya que es necesario un cambio radical. Se invita las dem��s universidades para que asuman igual posici��n y que reafirmen lo definido en el encuentro nacional de estudiantes.&lt;/p&gt;
description: Demandas, manifestaciones y pliegos del sector obrero y sus centrales sindicales frente al alza de transporte, guerra fr��a y mensajes de Nixon frente a la paz, legitimidad de Lleras en municipios del pa��s, ingreso de 10.850 estudiantes nuevos a la UdeA (p.2), posturas y debates de acad��micos y pol��ticos sobre el papel de las universidades en el futuro
DOI: 10.15159/phytop.184
title: Koigi lakes

description: Phytoplankton biomass, diversity and abundance in samples collected from Koigi lakes during the period 1956-2001.
DOI: 10.15468/dl.xuv9wb
title: Occurrence Download

description: A dataset containing 491 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Epimedium brevicornu"
 ]
}

 The dataset includes 491 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016455-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10807669
title: TEST-Error potential EEG dataset for H3 exoskeleton Start - Project Regait

description: Dataset for error Potential characterization based on EEG signals.

 

Grant  PID2021-124111OB-C31 funded by MICIU/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”.
DOI: 10.5281/zenodo.10807670
title: TEST-Error potential EEG dataset for H3 exoskeleton Start - Project Regait

description: Dataset for error Potential characterization based on EEG signals.

 

Grant  PID2021-124111OB-C31 funded by MICIU/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”.
DOI: 10.34740/kaggle/dsv/9716206
title: Screen time And App usage survey
DOI: 10.15468/dl.m22nwh
title: Occurrence Download

description: A dataset containing 1171 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pollia condensata",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 1171 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016456-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18506168
title: STATE REGULATION AND SUPPORT OF THE TRANSPORT LOGISTICS SYSTEM, LOGISTICS COSTS AND LOGISTICS EFFICIENCY

description: This article highlights the main directions of state regulation of the transport logistics system, mechanisms for supporting logistics infrastructure, and the impact of logistics costs on economic processes. In addition, trends in the development of transport and logistics indicators in recent years are analyzed. Based on example statistical data, tables and diagrams are presented to assess the dynamics of logistics costs and logistics efficiency.
DOI: 10.5281/zenodo.18506167
title: STATE REGULATION AND SUPPORT OF THE TRANSPORT LOGISTICS SYSTEM, LOGISTICS COSTS AND LOGISTICS EFFICIENCY

description: This article highlights the main directions of state regulation of the transport logistics system, mechanisms for supporting logistics infrastructure, and the impact of logistics costs on economic processes. In addition, trends in the development of transport and logistics indicators in recent years are analyzed. Based on example statistical data, tables and diagrams are presented to assess the dynamics of logistics costs and logistics efficiency.