cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17453999
title: Spatial prediction of Coarse fragments in Switzerland at 30 m resolution

description: The Coarse Fragment (CF) maps were developed using a quantile random forest machine learning approach. The model integrates remotely sensed and derived environmental covariates including terrain, climate, vegetation, and soil properties. The maps are provided in GeoTIFF format at a 30 m spatial resolution for four soil depths: 0, 30, 60, and 100 cm. The unit is percent by volume.

The methodology follows Gupta et al. (2024). Based on spatial five-fold cross-validation, the model performance was:

MEC: 0.18

CCC: 0.32

RMSE: 8.3

Bias: 0.56

Among all predictors, soil depth was the most important covariate, followed by topography, climate, and lithology.

Uncertainty was assessed using quantile regression. However, because coarse fragment values are often close to zero, the uncertainty estimates may be less reliable (Poggio et al., 2021). Therefore, these maps should be used with caution.

Other soil property maps for Switzerland including soil organic carbon (SOC), clay, sand, nitrogen, and phosphorus  can be downloaded here: https://doi.org/10.5281/zenodo.7821649 

The bulk density map for Switzerland can be downloaded from: https://doi.org/10.5281/zenodo.15274427 

References

Gupta, S., Hasler, J. K., & Alewell, C. (2024). Mining soil data of Switzerland: New maps for soil texture, soil organic carbon, nitrogen, and phosphorus. Geoderma Regional, 36, e00747.

Poggio, L., De Sousa, L. M., Batjes, N. H., Heuvelink, G. B., Kempen, B., Ribeiro, E., & Rossiter, D. (2021). SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty. Soil, 7(1), 217–240.
DOI: 10.5281/zenodo.17453998
title: Spatial prediction of Coarse fragments in Switzerland at 30 m resolution

description: The Coarse Fragment (CF) maps were developed using a quantile random forest machine learning approach. The model integrates remotely sensed and derived environmental covariates including terrain, climate, vegetation, and soil properties. The maps are provided in GeoTIFF format at a 30 m spatial resolution for four soil depths: 0, 30, 60, and 100 cm. The unit is percent by volume.

The methodology follows Gupta et al. (2024). Based on spatial five-fold cross-validation, the model performance was:

MEC: 0.18

CCC: 0.32

RMSE: 8.3

Bias: 0.56

Among all predictors, soil depth was the most important covariate, followed by topography, climate, and lithology.

Uncertainty was assessed using quantile regression. However, because coarse fragment values are often close to zero, the uncertainty estimates may be less reliable (Poggio et al., 2021). Therefore, these maps should be used with caution.

Other soil property maps for Switzerland including soil organic carbon (SOC), clay, sand, nitrogen, and phosphorus  can be downloaded here: https://doi.org/10.5281/zenodo.7821649 

The bulk density map for Switzerland can be downloaded from: https://doi.org/10.5281/zenodo.15274427 

References

Gupta, S., Hasler, J. K., & Alewell, C. (2024). Mining soil data of Switzerland: New maps for soil texture, soil organic carbon, nitrogen, and phosphorus. Geoderma Regional, 36, e00747.

Poggio, L., De Sousa, L. M., Batjes, N. H., Heuvelink, G. B., Kempen, B., Ribeiro, E., & Rossiter, D. (2021). SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty. Soil, 7(1), 217–240.
DOI: 10.5281/zenodo.17454088
title: Supplementary Materials associated with paper 'A comparative molecular study of rhizostome jellyfishes (Cnidaria, Scyphozoa, Rhizostomeae) from Japan reveals dominant Symbiodiniaceae associations with many and variable cassiosome production'

description: This is a repository for supporting figures associated with paper 'A comparative molecular study of rhizostome jellyfishes (Cnidaria, Scyphozoa, Rhizostomeae) from Japan reveals dominant Symbiodiniaceae associations with many and variable cassiosome production'
DOI: 10.15468/dl.r2gyv6
title: Occurrence Download

description: A dataset containing 2349 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "OccurrenceStatus is Present",
 "TaxonKey is Graellsia isabellae"
 ]
}

 The dataset includes 2349 records from 87 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002332-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48544/7d47f34a-7152-4513-9468-831d874521c4
title: Model & training for peer-to-peers ENSURE
DOI: 10.5518/1374
title: Dataset for "Phage Display Identifies Affimer Proteins that Direct Calcium Carbonate Polymorph"

description: Dataset supporting a study in which a phage display approach is used to identify proteins – rather than the short peptides typically identified using this method – that can direct calcium carbonate formation. A 1.3 X 1010 library of Affimer proteins was displayed on modified M13 phage, where Affimer is a 3 kDa protein scaffold that displays two variable regions of 9–13 residues. The phage displaying the Affimer library were then screened in binding assays against calcite and aragonite at pH 7.4, and four different strongly-binding proteins were identified. The two aragonite-binding proteins generated aragonite when calcium and magnesium ions were present at a 1:1 ratio, while the calcite-binding proteins produce magnesium-calcite under the same conditions. Calcite alone formed in the presence of all four proteins in the absence of magnesium ions. In combination with molecular dynamics simulations to evaluate the conformations of the proteins in solution, this work demonstrates the importance of conformation in polymorph control, and highlights the importance of magnesium ions, which are abundant in seawater, to reduce the energetic barriers associated with aragonite formation.
DOI: 10.5281/zenodo.17411121
title: Code for Extreme temperature events analysis
DOI: 10.15468/dl.jq4sxk
title: Occurrence Download

description: A dataset containing 707 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Human Observation, Material citation, Specimen, Occurrence evidence)",
 "Continent is one of (Africa, Europe)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Microsphaera alphitoides"
 ]
}

 The dataset includes 707 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002335-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bq7dsa
title: Occurrence Download

description: A dataset containing 939 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Vitis davidi"
 ]
}

 The dataset includes 939 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002334-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4wwf7h
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.28_1",
 "TaxonKey is Calligonum korlaense"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002333-251025141854904/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.30454062
title: Calculating the reward-rate manifold in the Gaussian-MSE case from Resource-rational reinforcement learning and sensorimotor causal states, and resource-rational maximiners

description: Calculates a reward-rate manifold when statistics are Gaussian and the reward function is a squared error. In this case, the generalized Blahut-Arimoto algorithm massively simplifies, and we can use the equations in Appendix D to find Fig 1.
DOI: 10.6084/m9.figshare.30454062.v1
title: Calculating the reward-rate manifold in the Gaussian-MSE case from Resource-rational reinforcement learning and sensorimotor causal states, and resource-rational maximiners

description: Calculates a reward-rate manifold when statistics are Gaussian and the reward function is a squared error. In this case, the generalized Blahut-Arimoto algorithm massively simplifies, and we can use the equations in Appendix D to find Fig 1.
DOI: 10.48544/89d75251-d004-44b0-ba25-5c7d59d9300f
title: Financing the circular economy in the tourism sector
DOI: 10.15468/dl.qk7ryj
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.28_1",
 "TaxonKey is Weigela florida"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002336-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f3p45t
title: Occurrence Download

description: A dataset containing 66691 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-90.00093977783314 35.2149022147768, -90.01114859353186 35.21661467681334, -90.02156849948219 35.21665858370785, -90.03179821934881 35.21503224372623, -90.04144384670117 35.21179831718225, -90.05013410222294 35.20708138388187, -90.05753469372513 35.20106310956181, -90.06336121307663 35.193975204107716, -90.0673900667957 35.1860904513985, -90.06946702017008 35.1777121655141, -90.06951303403285 35.16916248777031, -90.06752718373957 35.160769981429254, -90.06358656626148 35.152857004684115, -90.05784321851954 35.14572734721602, -90.05051818342972 35.13965460167356, -90.04189296550254 35.13487170994614, -90.03229871184509 35.131562076789095, -90.02210353440734 35.12985258235551, -90.01169845333668 35.12980875295012, -90.00148248801162 35.13143226850994, -89.99184745085621 35.13466089871433, -89.98316300892515 35.13937087007766, -89.97576256934323 35.14538157675553, -89.96993051711628 35.152462460967186, -89.96589128805847 35.16034180775376, -89.96380069643341 35.168717126037414, -89.96373985770589 35.177266726292196, -89.9657119534683 35.18566205705292, -89.96964198074973 35.1935803301346, -89.97537951489068 35.20071694953753, -89.98270439804534 35.20679726272212, -89.99133514883728 35.2115871756941, -90.00093977783314 35.2149022147768))",
 "Year is one of (2019, 2020, 2021, 2022, 2023, 2024, 2025)",
 "KingdomKey is one of (Animalia, Fungi, Plantae)"
 ]
}

 The dataset includes 66691 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002306-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/b8jn5rtwkg.2
title: Genome analysis dataset of Xylaria sp. KR-3U isolated from Catharanthus roseus leaves

description: This dataset contains secondary genome analysis files for Xylaria sp. KR-3U, including antiSMASH biosynthetic gene cluster predictions, dbCAN3 CAZyme annotations, KEGG pathway assignments, and BUSCO completeness reports. The dataset supports the forthcoming manuscript entitled "Draft genome dataset of Xylaria sp. KR-3U isolated from Catharanthus roseus leaves collected in India". This version 2 update includes the assembled genome (FASTA) and gene annotation (GFF3) of Xylaria sp. KR-3U.
DOI: 10.17632/6f5kvkgcjv
title: cryptocurrency macro adoption factors

description: This research, "Crypto adoption through the lens of institutional and Kirzner’s entrepreneurship theory," investigates the factors driving global cryptocurrency diffusion.

Research Hypothesis: The study hypothesized that high formal institutional quality acts as a deterrent to crypto adoption, suggesting that institutional weakness creates a market void that decentralized finance fills. The research aims to explain this pattern by synthesizing Institutional Theory and Kirznerian Entrepreneurship Theory.

Data and Methodology: Cross-country Bitcoin adoption scores from the Chainalysis 2024 report were analyzed for 137 nations. The data included over twenty institutional, entrepreneurial, macroeconomic, and demographic variables. A robust Automatic Machine Learning (AML) approach, specifically a Gradient-Boosted Decision Tree (GBDT) model, was used to capture complex, non-linear relationships, validated by OLS and Random Forest models.

Notable Findings and Interpretation: The analysis reveals a dual pattern of adoption driven by institutional fragility. The most influential finding is the strong negative correlation between governance stability (a measure of formal institutional quality) and adoption. This is interpreted to mean that the weakening of formal institutions creates an "institutional void" that cryptocurrencies are adopted to fill. Adoption is further enabled by Informal Entrepreneurship and a young median age, which are consistently significant factors. The data shows that adoption thrives in low-trust institutional environments where individuals display entrepreneurial alertness to market inefficiencies and use cryptocurrencies as a necessary hedge against systemic risk (like high inflation or unstable currencies), viewing it as a safer financial alternative. The data can be used to predict future adoption hot spots and informs policymakers that crypto growth is often a symptom of institutional failure, not technological novelty alone
DOI: 10.17632/6f5kvkgcjv.1
title: cryptocurrency macro adoption factors

description: This research, "Crypto adoption through the lens of institutional and Kirzner’s entrepreneurship theory," investigates the factors driving global cryptocurrency diffusion.

Research Hypothesis: The study hypothesized that high formal institutional quality acts as a deterrent to crypto adoption, suggesting that institutional weakness creates a market void that decentralized finance fills. The research aims to explain this pattern by synthesizing Institutional Theory and Kirznerian Entrepreneurship Theory.

Data and Methodology: Cross-country Bitcoin adoption scores from the Chainalysis 2024 report were analyzed for 137 nations. The data included over twenty institutional, entrepreneurial, macroeconomic, and demographic variables. A robust Automatic Machine Learning (AML) approach, specifically a Gradient-Boosted Decision Tree (GBDT) model, was used to capture complex, non-linear relationships, validated by OLS and Random Forest models.

Notable Findings and Interpretation: The analysis reveals a dual pattern of adoption driven by institutional fragility. The most influential finding is the strong negative correlation between governance stability (a measure of formal institutional quality) and adoption. This is interpreted to mean that the weakening of formal institutions creates an "institutional void" that cryptocurrencies are adopted to fill. Adoption is further enabled by Informal Entrepreneurship and a young median age, which are consistently significant factors. The data shows that adoption thrives in low-trust institutional environments where individuals display entrepreneurial alertness to market inefficiencies and use cryptocurrencies as a necessary hedge against systemic risk (like high inflation or unstable currencies), viewing it as a safer financial alternative. The data can be used to predict future adoption hot spots and informs policymakers that crypto growth is often a symptom of institutional failure, not technological novelty alone
DOI: 10.25375/uct.29300048.v2
title: Aligning local Climate Change Adaptation Programme Monitoring, Evaluation and Learning with National and Global reporting requirements: A focus on water

description: The research framework was developed by the PhD candidate during the course of research, based on an extensive literature review based on international good practices for climate change adaptation monitoring, evaluation and learning. The research framework is the first result to research question 1 and is in the process of being applied to evaluate how the South African monitoring, evaluation and learning policies, legislation and frameworks for climate change adaptation aligns and conforms to these globally recognised good practices. The final application of the framework will be on a local climate change adaptation programmes, implemented in South Africa.
DOI: 10.5281/zenodo.16788654
title: A quantum resistance memristor for an intrinsically traceable International System of Units standard - Dataset

description: This is the dataset of "A quantum resistance memristor for an intrinsically traceable International System of Units standard", Nature Nanotechnology, DOI: 10.1038/s41565-025-02037-5, (2025).

This work was supported by the European project MEMQuD, code 20FUN06, funder ID: 10.13039/100014132. This project (EMPIR 20FUN06 MEMQuD) has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme.
DOI: 10.5281/zenodo.16788655
title: A quantum resistance memristor for an intrinsically traceable International System of Units standard - Dataset

description: This is the dataset of "A quantum resistance memristor for an intrinsically traceable International System of Units standard", Nature Nanotechnology, DOI: 10.1038/s41565-025-02037-5, (2025).

This work was supported by the European project MEMQuD, code 20FUN06, funder ID: 10.13039/100014132. This project (EMPIR 20FUN06 MEMQuD) has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme.
DOI: 10.17632/6bc6zm7scm
title: Flood susceptibility NRB

description: This dataset contains the complete geospatial data and computational outputs used for flood susceptibility assessment of the Neyyar river basin using multi-criteria decision analysis and GIS-based weighted overlay approach. The data supports the methodology described in the associated research article and enables full reproducibility of the flood susceptibility mapping results.
DOI: 10.17632/6bc6zm7scm.1
title: Flood susceptibility NRB

description: This dataset contains the complete geospatial data and computational outputs used for flood susceptibility assessment of the Neyyar river basin using multi-criteria decision analysis and GIS-based weighted overlay approach. The data supports the methodology described in the associated research article and enables full reproducibility of the flood susceptibility mapping results.
DOI: 10.17632/c4tmm7nzvg
title: Supplemental material for “Response to Gronbeck et al.’s ‘Dermatologic toxicities of antibody–drug conjugates’: why ado-trastuzumab emtansine–associated telangiectasias deserve clinical attention”

description: This dataset contains Supplementary Table 1 from the Letter “Response to Gronbeck et al.’s ‘Dermatologic toxicities of antibody–drug conjugates’: why ado-trastuzumab emtansine–associated telangiectasias deserve clinical attention". The table summarises all published cases of telangiectasias associated with ado-trastuzumab emtansine (T-DM1) reported in the literature up to 2025. Data were extracted from case reports and case series and include the following: patient demographics; months to onset; clinical presentation; mucosal involvement; bleeding events; laboratory findings; and outcomes. This dataset has been compiled to provide an overview of the clinical spectrum and potential systemic vascular implications of T-DM1-associated telangiectasias. It is intended to facilitate future analyses and comparisons of vascular adverse events related to antibody–drug conjugates.
DOI: 10.17632/c4tmm7nzvg.1
title: Supplemental material for “Response to Gronbeck et al.’s ‘Dermatologic toxicities of antibody–drug conjugates’: why ado-trastuzumab emtansine–associated telangiectasias deserve clinical attention”

description: This dataset contains Supplementary Table 1 from the Letter “Response to Gronbeck et al.’s ‘Dermatologic toxicities of antibody–drug conjugates’: why ado-trastuzumab emtansine–associated telangiectasias deserve clinical attention". The table summarises all published cases of telangiectasias associated with ado-trastuzumab emtansine (T-DM1) reported in the literature up to 2025. Data were extracted from case reports and case series and include the following: patient demographics; months to onset; clinical presentation; mucosal involvement; bleeding events; laboratory findings; and outcomes. This dataset has been compiled to provide an overview of the clinical spectrum and potential systemic vascular implications of T-DM1-associated telangiectasias. It is intended to facilitate future analyses and comparisons of vascular adverse events related to antibody–drug conjugates.
DOI: 10.17632/4hkrzvkmfp
title: Experimental Data on Biodiversity Conservation and Brand Equity

description: This dataset supports the analyses reported in the manuscript “Building Brand Equity through Biodiversity Conservation: The Role of No Net Loss in Supply Chains under Good and Bad Uncertainty.” The data were collected through a vignette-based experimental study designed to test the hypotheses proposed in the paper. It includes survey responses from participants exposed to six experimental vignettes representing different sustainability and uncertainty scenarios. The key constructs measured include marketing capability, networking capability, customer value, brand equity, and uncertainty.

The dataset contains one .csv file used for statistical analysis and one accompanying Excel file detailing variable names, measurement items, and scale information. All participant data have been anonymized, and ethical approval for the study was obtained from the authors’ institutional research ethics committee.

This dataset is made available for academic research purposes only. Users are requested to cite both this dataset and the associated manuscript when using the data.
DOI: 10.17632/4hkrzvkmfp.1
title: Experimental Data on Biodiversity Conservation and Brand Equity

description: This dataset supports the analyses reported in the manuscript “Building Brand Equity through Biodiversity Conservation: The Role of No Net Loss in Supply Chains under Good and Bad Uncertainty.” The data were collected through a vignette-based experimental study designed to test the hypotheses proposed in the paper. It includes survey responses from participants exposed to six experimental vignettes representing different sustainability and uncertainty scenarios. The key constructs measured include marketing capability, networking capability, customer value, brand equity, and uncertainty.

The dataset contains one .csv file used for statistical analysis and one accompanying Excel file detailing variable names, measurement items, and scale information. All participant data have been anonymized, and ethical approval for the study was obtained from the authors’ institutional research ethics committee.

This dataset is made available for academic research purposes only. Users are requested to cite both this dataset and the associated manuscript when using the data.
DOI: 10.15468/dl.x6yqgd
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.28_1",
 "TaxonKey is Trollius chinensis"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002337-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17454189
title: strain_performance_summary
DOI: 10.17632/xr3pd87gpd
title: Ph+ALL and Luteolin

description: raw data of Luteolin induces apoptosis in Philadelphia chromosome-positive acute lymphoblastic leukemia cell by regulating the PI3K/AKT signaling pathway