cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14723414
title: Effects of condensation and dynamic exchange of phosphate diesters and hydroxyl groups

description: The datasets include all unprocessed files of all tested resins and dynamic materials used in the associated publication entitled Fundamental Insights into the Covalent Adaptable Networks of Phosphate Esters: Effects of Condensation and Dynamic Exchange of Phosphate Diesters with Hydroxyl Groups (Sustain. Mater. Technol. 2025 https://doi.org/10.1016/j.susmat.2025.e01270). The data sets consist of DMA storage modulus, loss modulus, tangent δ, stress-strain and stress relaxation (both tensile and flexural) of all relevant materials. All FT-IR spectra of comonomer blends, copolymers and homopolymers are included. Multiple DSC scans of polymer samples and DSC kinetic data on preheated samples are included in the appropriate folders (DSC General and DSC Kinetics). Thermogravimetric raw data are included in the TGA folder. P-NMR spectra are included for the four main copolymers tested before and after thermal processing.
description: The data can be accessed using dedicated software for the instrumentation (DMA instrument, DSC apparatus, TG apparatus, FT-IR spectroscope) as described in the publication Sustain. Mater. Technol. 2025 https://doi.org/10.1016/j.susmat.2025.e01270.

The molarity of the substrate used is indicated by the numbers next to the abbreviated name. For example: BMEP1-HEA2 stands for a molar ratio of BMEP/HEA of 1/2. If included, the additional descriptors indicate the thermal/mechanical processing conditions.
DOI: 10.5281/zenodo.14723415
title: Effects of condensation and dynamic exchange of phosphate diesters and hydroxyl groups

description: The datasets include all unprocessed files of all tested resins and dynamic materials used in the associated publication entitled Fundamental Insights into the Covalent Adaptable Networks of Phosphate Esters: Effects of Condensation and Dynamic Exchange of Phosphate Diesters with Hydroxyl Groups (Sustain. Mater. Technol. 2025 https://doi.org/10.1016/j.susmat.2025.e01270). The data sets consist of DMA storage modulus, loss modulus, tangent δ, stress-strain and stress relaxation (both tensile and flexural) of all relevant materials. All FT-IR spectra of comonomer blends, copolymers and homopolymers are included. Multiple DSC scans of polymer samples and DSC kinetic data on preheated samples are included in the appropriate folders (DSC General and DSC Kinetics). Thermogravimetric raw data are included in the TGA folder. P-NMR spectra are included for the four main copolymers tested before and after thermal processing.
description: The data can be accessed using dedicated software for the instrumentation (DMA instrument, DSC apparatus, TG apparatus, FT-IR spectroscope) as described in the publication Sustain. Mater. Technol. 2025 https://doi.org/10.1016/j.susmat.2025.e01270.

The molarity of the substrate used is indicated by the numbers next to the abbreviated name. For example: BMEP1-HEA2 stands for a molar ratio of BMEP/HEA of 1/2. If included, the additional descriptors indicate the thermal/mechanical processing conditions.
DOI: 10.15468/dl.cwmybb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((103.6497 12.36758, 103.6521 12.36903, 103.6525 12.37156, 103.6503 12.3721, 103.6464 12.37229, 103.6416 12.37083, 103.6391 12.37054, 103.6379 12.36848, 103.6397 12.3661, 103.6392 12.36275, 103.6367 12.36061, 103.6294 12.36058, 103.6214 12.36013, 103.6139 12.36125, 103.6089 12.36314, 103.6006 12.36556, 103.5948 12.36847, 103.5881 12.37117, 103.5882 12.36536, 103.5898 12.36461, 103.5933 12.3632, 103.5947 12.35978, 103.5977 12.35987, 103.6004 12.35831, 103.598 12.35467, 103.6025 12.35244, 103.6036 12.35648, 103.6064 12.35601, 103.6105 12.35549, 103.6142 12.35578, 103.6184 12.35539, 103.621 12.3537, 103.6193 12.35054, 103.6214 12.34911, 103.6234 12.35152, 103.6266 12.35044, 103.6306 12.34896, 103.6301 12.35114, 103.6298 12.35395, 103.6319 12.35594, 103.6352 12.35705, 103.6384 12.35666, 103.64 12.35441, 103.6437 12.35272, 103.646 12.35286, 103.6478 12.35499, 103.6414 12.36199, 103.6408 12.36398, 103.642 12.3659, 103.6451 12.36626, 103.6472 12.36449, 103.649 12.36478, 103.6497 12.36758))",
 "TaxonKey is Mammalia"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004977-250127130748423/datasets/export for details.
DOI: 10.5281/zenodo.14770335
title: Apendix to GoRS's evaluation
DOI: 10.5281/zenodo.14770336
title: Apendix to GoRS's evaluation
DOI: 10.15468/dl.686mek
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((103.4818 12.4333, 103.482 12.42831, 103.4911 12.42603, 103.4935 12.42235, 103.4895 12.42042, 103.4784 12.42186, 103.476 12.41836, 103.4742 12.41014, 103.4751 12.40406, 103.4788 12.3993, 103.4825 12.39843, 103.4846 12.40644, 103.4895 12.41009, 103.4958 12.4115, 103.4964 12.40534, 103.4941 12.39945, 103.4911 12.39615, 103.4894 12.39054, 103.4907 12.3876, 103.4956 12.38633, 103.5019 12.38999, 103.5065 12.38783, 103.5099 12.38579, 103.5128 12.38109, 103.5133 12.38698, 103.5217 12.38196, 103.5282 12.38159, 103.5382 12.38219, 103.5369 12.37951, 103.542 12.37448, 103.5369 12.3724, 103.5292 12.3727, 103.5269 12.36784, 103.5347 12.36492, 103.5449 12.36116, 103.5493 12.3685, 103.5567 12.36553, 103.559 12.36404, 103.56 12.36008, 103.5619 12.35435, 103.5715 12.35201, 103.5798 12.35307, 103.5788 12.3638, 103.5797 12.36962, 103.5809 12.37464, 103.5799 12.37831, 103.5739 12.38395, 103.5693 12.38741, 103.5663 12.39054, 103.5601 12.39673, 103.5532 12.40429, 103.546 12.41539, 103.5369 12.42464, 103.5285 12.43349, 103.526 12.43252, 103.5251 12.42752, 103.528 12.42159, 103.5376 12.41309, 103.5343 12.41205, 103.5279 12.40955, 103.5207 12.40944, 103.513 12.40633, 103.5091 12.40336, 103.505 12.40943, 103.5063 12.41607, 103.5082 12.41936, 103.5017 12.42076, 103.501 12.42752, 103.4983 12.43045, 103.4904 12.42917, 103.4818 12.4333))",
 "TaxonKey is Mammalia"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004978-250127130748423/datasets/export for details.
DOI: 10.5281/zenodo.14755346
title: Seismic assessment on different irregular structure considering incident angles and soil structure interactions

description: This dataset contains the input data and results from a numerical study investigating the impact of seismic vibration incident angle on the response of irregular reinforced concrete structures, considering soil-structure interaction (SSI).  The study examined two different 10-story irregular building configurations (L-shaped and C-shaped) designed according to BNBC-2020 guidelines.  The data includes:



Soil parameters: Site-specific soil properties used in the SSI model.

Seismic input: Data related to the seismic loading, including the BNBC-2020 spectrum and the El Centro earthquake time history.

Analysis results: Displacement data for each structure at 10-degree increments of incident wave angle, considering SSI conditions.


The research used the finite element method within SAP2000, employing the Newmark-beta method for time-history analysis.
DOI: 10.5281/zenodo.14755347
title: Seismic assessment on different irregular structure considering incident angles and soil structure interactions

description: This dataset contains the input data and results from a numerical study investigating the impact of seismic vibration incident angle on the response of irregular reinforced concrete structures, considering soil-structure interaction (SSI).  The study examined two different 10-story irregular building configurations (L-shaped and C-shaped) designed according to BNBC-2020 guidelines.  The data includes:



Soil parameters: Site-specific soil properties used in the SSI model.

Seismic input: Data related to the seismic loading, including the BNBC-2020 spectrum and the El Centro earthquake time history.

Analysis results: Displacement data for each structure at 10-degree increments of incident wave angle, considering SSI conditions.


The research used the finite element method within SAP2000, employing the Newmark-beta method for time-history analysis.
DOI: 10.5281/zenodo.14770301
title: Modified Stacking Model for crop yield Prediction  using L2 Regularization

description: This paper focuses on evaluating the performance of 11 crops categorized as Kharif and Rabi using the Optimized Stacking Framework (OSF) in comparison to six base machine learning models: Linear Regression (LR), Least Angle Regression (LAR), Decision Trees (DT), Random Forest (RF), XGBoost, and Support Vector Machines (SVM). The Kharif category comprises Rice, Groundnut, Maize, Jowar, Sugarcane,Soyabean, Jute, and Ragi, while the Rabi category includes Bajra, Barley, andWheat.
DOI: 10.5281/zenodo.14770302
title: Modified Stacking Model for crop yield Prediction  using L2 Regularization

description: This paper focuses on evaluating the performance of 11 crops categorized as Kharif and Rabi using the Optimized Stacking Framework (OSF) in comparison to six base machine learning models: Linear Regression (LR), Least Angle Regression (LAR), Decision Trees (DT), Random Forest (RF), XGBoost, and Support Vector Machines (SVM). The Kharif category comprises Rice, Groundnut, Maize, Jowar, Sugarcane,Soyabean, Jute, and Ragi, while the Rabi category includes Bajra, Barley, andWheat.
DOI: 10.15468/dl.fd492y
title: Occurrence Download

description: A dataset containing 180 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bathyplectes curculionis (Thomson, 1887)"
 ]
}

 The dataset includes 180 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004981-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/vkk7y34pdc
title: Influenza vaccination meta-analysis: run 1

description: Results of the statistical analysis with parameters set 1
DOI: 10.17632/7krjhg6474
title: Data for: Adoption of Autonomous Mining System in Pakistan – Policy, Skillset, Awareness and Preparedness of Stakeholders
DOI: 10.17632/gww7t6zpd2
title: Data_SW_China_Northern_Vietnam

description: Data share of Cross-correlation Functions and SH-velocity Models
DOI: 10.15468/dl.3sjmr8
title: Occurrence Download

description: A dataset containing 110270 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Martes martes (Linnaeus, 1758)"
 ]
}

 The dataset includes 110270 records from 1097 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004980-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14726189
title: Novel insights in cryptic diversity of snow and glacier ice algae communities combining 18S rRNA gene and ITS2 amplicon sequencing

description: Melting snow and glacier surfaces host microalgal blooms in polar and mountainous regions. The aim of this study was to determine the dominant taxa at the species level in the European Arctic and the Alps. A standardized protocol for amplicon metabarcoding using 18S rRNA gene and ITS2 markers was developed. This is important because previous biodiversity studies have been hampered by the dominance of closely related algal taxa in snow and ice. Due to the limited resolution of partial 18S rRNA Illumina sequences, the hypervariable ITS2 region was used to further discriminate between the genotypes. Our results show that red snow was caused by the cosmopolitan Sanguina nivaloides (Chlamydomonadales, Chlorophyta) and two as of yet undescribed Sanguina species. Arctic orange snow was dominated by S. aurantia, which was not found in the Alps. On glaciers, at least three Ancylonema species (Zygnematales, Streptophyta) dominated. Golden-brown blooms consisted of Hydrurus spp. (Hydrurales, Stramenophiles) and these were mainly an Arctic phenomenon. For chrysophytes, only 18S rRNA gene but not ITS2 sequences were amplified, showcasing how delicate the selection of eukaryotic “universal” primers for community studies is, and that primer specificity will affect diversity results dramatically. We propose our approach as a “best practice”.

The repository files contain the original (raw and annotated) marker sequences files used in the following study: 

https://doi.org/10.1093/femsec/fiad134

They were accidently not linked with the original supplmental material, which is also included here.
DOI: 10.5281/zenodo.14726190
title: Novel insights in cryptic diversity of snow and glacier ice algae communities combining 18S rRNA gene and ITS2 amplicon sequencing

description: Melting snow and glacier surfaces host microalgal blooms in polar and mountainous regions. The aim of this study was to determine the dominant taxa at the species level in the European Arctic and the Alps. A standardized protocol for amplicon metabarcoding using 18S rRNA gene and ITS2 markers was developed. This is important because previous biodiversity studies have been hampered by the dominance of closely related algal taxa in snow and ice. Due to the limited resolution of partial 18S rRNA Illumina sequences, the hypervariable ITS2 region was used to further discriminate between the genotypes. Our results show that red snow was caused by the cosmopolitan Sanguina nivaloides (Chlamydomonadales, Chlorophyta) and two as of yet undescribed Sanguina species. Arctic orange snow was dominated by S. aurantia, which was not found in the Alps. On glaciers, at least three Ancylonema species (Zygnematales, Streptophyta) dominated. Golden-brown blooms consisted of Hydrurus spp. (Hydrurales, Stramenophiles) and these were mainly an Arctic phenomenon. For chrysophytes, only 18S rRNA gene but not ITS2 sequences were amplified, showcasing how delicate the selection of eukaryotic “universal” primers for community studies is, and that primer specificity will affect diversity results dramatically. We propose our approach as a “best practice”.

The repository files contain the original (raw and annotated) marker sequences files used in the following study: 

https://doi.org/10.1093/femsec/fiad134

They were accidently not linked with the original supplmental material, which is also included here.
DOI: 10.5281/zenodo.14769634
title: DSC_paperSLB_txt
DOI: 10.5281/zenodo.14769635
title: DSC_paperSLB_txt
DOI: 10.17632/cm7vcsx49v
title: Research Project: Application of the ESA-CCI land cover maps dataset and the UNCCD land cover classes to assess Nicaragua’s agrarian frontier geospatial trend at the country-level and biosphere reserve-level

description: The advance of the agrarian frontier constitutes Nicaragua’s biggest environmental challenge as the major cause of complex processes of ecosystems degradation. I use the ESA-CCI land cover maps dataset and the UNCCD land cover classes (UNCCD-LC) to estimate its geospatial trend in terms of land cover changes at the country-level and the areas encompassing Bosawas and Río San Juan biosphere reserves from 1992 to 2015. The ESA-CCI land cover maps generated at 300 m spatial resolution on an annual basis from 1992 to 2015 in TIF format (raster layers) were collected from the official website of the ESA-CCI (https://www.esa-landcover-cci.org/). The coordinate reference system of the maps is a geographic coordinate system based on the World Geodetic System 84 (WGS84) reference ellipsoid. The processing of the geospatial data was carried out using QGIS. The 36 ESA-CCI land cover classes (ESA-CCI-LC) were re-classified to the 7 UNCCD-LC (i.e., tree-covered, grassland, cropland, wetland, artificial, other land, and water body). The global-level maps were clipped to the country-level (Nicaragua) using the vector layers in SHP format collected from the official website of GADM (https://gadm.org/), and at the biosphere reserve-level (Bosawas y Río San Juan) using the vector layers in SHP format collected from the official website of Protected Planet (https://www.protectedplanet.net/). A pixel count approach was used to estimate each UNCCD-LC area. STATA was used to calculate UNCCD-LC area estimates in squared kilometers, each pixel counting for 300 m x 300 m which is the ESA-CCI land cover maps spatial resolution. At the country-level, the analysis covered 124,552.2 km2. The total area might include land and water bodies. At the biosphere reserve-level, the analysis covered 19,548.2 km2 for Bosawas and 17,524.9 km2 for Río San Juan. In Basawas biosphere reserve, 41% (8,030.3 km2) of the total area belongs to core areas, whereas 69% (11,548.9 km2) to the buffer zone. In Río San Juan biosphere reserve, 48% (7,525.3 km2) of the total area belongs to core areas, whereas 52% (10,170.2 km2) to the buffer zone. The research finds that Nicaragua’s agrarian frontier has shown a remarkably strong advance during the last two decades, particularly from 1995 to 2007. The underlying land transition process has mainly implied the transformation of tree-covered into cropland or grassland areas. This process has also penetrated legally designated protected areas such as Bosawas and Río San Juan biosphere reserves.
DOI: 10.17632/frgtmpsffg
title: Data for: On data-driven choice of λ in nonparametric Gaussian regression via Propagation-Separation approach

description: The Data-folder provided contains: the source code of the CV method, the generated data and the results of simulation. The code is written in the statistical programming language R. Detailed information on how to use the code and the data is included in the respective R-scripts in each subfolder.
DOI: 10.5281/zenodo.14770374
title: Sandoval_Garzon-Massif
DOI: 10.5281/zenodo.14770375
title: Sandoval_Garzon-Massif
DOI: 10.13127/shakemaps/historical
title: ShakeMap Atlas of historical earthquakes in Italy

description: Italy has a rich history of studies on seismic history within the country and surrounding areas. Numerous archives and databases that focus on historical earthquake data, primarily intensity observations, are regularly updated. Macroseismic fields of past earthquakes are of foremost importance for evaluation of earthquake effects. To this purpose, we have implemented a strategy for generating historical earthquake shaking maps by adopting the ShakeMap service provided by the Istituto Nazionale di Geofisica e Vulcanologia (INGV).
For our analysis, we used this dataset which contains over 12,000 intensity observations collected from the Italian Macroseismic Database (DBMI15). We selected 79 earthquakes with a magnitude of 6.0 or higher that occurred before 1972. The resulting shaking maps have been available on the INGV ShakeMap portal and the ASMI (Archivio Storico Macrosismico Italiano, Rovida et al., 2017) platform.
To build the dataset, we adopted the configuration defined for the seismic settings in Italy, as described in the work of Michelini et al. (2020). We employed customized ground-motion-to-intensity conversion equations (GMICEs) and intensity prediction equations (IPEs). The conversion between ground motion and intensity was conducted using the regressions developed by Oliveti et al. (2022) and implemented in ShakeMap.
description: L'Italia può vantare un'ampia tradizione di studi e ricerche sulla sismologia storica. Esistono numerosi archivi e database che raccolgono dati storici relativi ai danni provocati dai terremoti, principalmente valori di intensità, che vengono regolarmente aggiornati. In questo contesto, la valutazione dell'impatto dei terremoti  storici si basa principalmente sui campi macrosismici degli eventi significativi. Alla luce di questo, abbiamo implementato una strategia per la creazione di shakemap storiche utilizzando il servizio ShakeMap fornito dall'Istituto Nazionale di Geofisica e Vulcanologia (INGV).
Per l'analisi effettuata, è stato utilizzato tale dataset che contiene oltre 12.000 osservazioni di intensità raccolte dal Database Macrosismico Italiano (DBMI15). Sono stati selezionati 79 terremoti con una magnitudo maggiore o uguale a 6 che si sono verificati prima del 1972. Le mappe di scuotimento degli eventi storici risultanti sono disponibili sul portale ShakeMap dell'INGV e sulla piattaforma ASMI (Archivio Storico Macrosismico Italiano, Rovida et al., 2017).
Per la costruzione del dataset, è stata adottata la configurazione descritta nel lavoro di Michelini et al. (2020). Sono state impiegate come equazioni di conversione tra parametri del moto del suolo e intensità macrosismica (GMICEs) quelle sviluppate da Oliveti et al. (2022) e come equazione di attenuazione in intensità (IPE) quella implementata di default in ShakeMap.
DOI: 10.17632/4v57tg3z84
title: Numerical prediction of surface roughness of as-built electron beam melting parts: experimental data

description: The "Roughness.xlsx" file contains the roughness values measured on a Ti6Al4V sample made by Electron Beam Melting (EBM). The measurements have been used to validate a finite element model of EBM process for predicting some build quality such as the surface roughness and the lack of fusion. These measurements are collected and indexed as follows: the first number (from 1 to 4) indicates the index of the surface, the second number (from 1 to 3) specifies the measure replica.
DOI: 10.15468/dl.ejdyt5
title: Occurrence Download

description: A dataset containing 6744 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Althenia filiformis F.Petit"
 ]
}

 The dataset includes 6744 records from 89 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004983-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28309040
title: Energy Poverty Data

description: The file includes data regarding the energy poverty extracted from MICS
DOI: 10.15468/dl.c4vgmz
title: Occurrence Download

description: A dataset containing 2112 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lepiota subincarnata J.E.Lange"
 ]
}

 The dataset includes 2112 records from 154 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004984-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sjkdv6
title: Occurrence Download

description: A dataset containing 80767 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eudyptes chrysolophus (Brandt, 1837)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 80767 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014246-210819072339941/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tyga8m
title: Occurrence Download

description: A dataset containing 2989 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Daimio tethys (Ménétriés, 1857)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2989 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072666-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c5w9b7
title: Occurrence Download

description: A dataset containing 28719 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ulmus laevis Pall."
 ]
}

 The dataset includes 28719 records from 498 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072676-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.