cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/k8sgs7fkvm.3
title: Mapping the UN Sustainable Development Goals to the European Sustainability Reporting Standards

description: We select the quantitative data point indicators from the European Sustainability Reporting Standards (ESRS) and we create a point-by-point mapping between the ESRS and the SDGs, partly using the methodological instruments provided by the GRI Standards (which are ESRS-compatible). We also include the EU Taxonomy indicators (Regulation 852/2020) into this mapping. 
The result of this process is a database of ESRS data points and EU Taxonomy ratios pointing to each SDG and clarifying the contributions to sustainable development. 
The dataset contains the Microsoft Access database that proposes a method to assess the contribution to the SDGs based on quantitative indicators (current versus past values).
DOI: 10.15468/dl.ch4daw
title: Occurrence Download

description: A dataset containing 1 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey)) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey)) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey)) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey)) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey)) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey)) genuscount,
 COUNT(*) occurrences
FROM
 occurrence
WHERE
 occurrence.countrycode = 'RO'
 AND occurrence.hascoordinate = TRUE
 AND occurrence.hasgeospatialissues = FALSE
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence.taxonkey = 2993094 OR occurrence.acceptedtaxonkey = 2993094 OR occurrence.kingdomkey = 2993094 OR occurrence.phylumkey = 2993094 OR occurrence.classkey = 2993094 OR occurrence.orderkey = 2993094 OR occurrence.familykey = 2993094 OR occurrence.genuskey = 2993094 OR occurrence.specieskey = 2993094)
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND occurrence.specieskey IS NOT NULL
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey

 The dataset's 1 records were derived from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011804-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.my9sdb
title: Occurrence Download

description: A dataset containing 32127 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Denmark",
 "OccurrenceStatus is Present",
 "CoordinateUncertaintyInMeters is less than 50000",
 "Year is 2025",
 "DecimalLongitude is greater than or equal to 7.38",
 "DecimalLongitude is less than or equal to 9.03",
 "DecimalLatitude is greater than or equal to 55.1",
 "DecimalLatitude is less than or equal to 56.06"
 ]
}

 The dataset includes 32127 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011811-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/pv7nm7tcv7.1
title: OCTAPACE

description: This dataset was collected pan-India from various staff and employees of higher education institutes in tourism and hospitality to understand the interaction of various organizational behavior parameters with job satisfaction indicators and organizational commitment.
DOI: 10.17632/pv7nm7tcv7.2
title: OCTAPACE

description: This dataset was collected pan-India from various staff and employees of higher education institutes in tourism and hospitality to understand the interaction of various organizational behavior parameters with job satisfaction indicators and organizational commitment.
DOI: 10.17632/pgf85kxnj2.1
title: LINF_130019500

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.15468/dl.fqtnyz
title: Occurrence Download

description: A dataset containing 1617885 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "Geometry POLYGON((-111.03862 43.87959,-107.21904 43.87959,-107.21904 45.90301,-111.03862 45.90301,-111.03862 43.87959))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1617885 records from 614 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011795-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/d6rbfmvpm5.1
title: Dataset for "The Permo-Carboniferous basins of the Catalan Pyrenees (NE Iberia): an example of tectonically controlled collapse calderas" by Saura et al

description: This dataset includes the data for the construction of the models presented in the paper: Dataset for "The Permo-Carboniferous basins of the Catalan Pyrenees (NE Iberia): an example of tectonically controlled collapse calderas" by Saura et al. submitted for publication to Tectonics on June 2024.
DOI: 10.17632/d6rbfmvpm5.2
title: Dataset for "The Permo-Carboniferous basins of the Catalan Pyrenees (NE Iberia): an example of tectonically controlled collapse calderas" by Saura et al

description: This dataset includes the data for the construction of the models presented in the paper: Dataset for "The Permo-Carboniferous basins of the Catalan Pyrenees (NE Iberia): an example of tectonically controlled collapse calderas" by Saura et al. submitted for publication to Tectonics on June 2024.
DOI: 10.15468/dl.jxztgu
title: Occurrence Download

description: A dataset containing 1966 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Global database of alien macrofungi"
 ]
}

 The dataset includes 1966 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011813-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/d6rbfmvpm5.3
title: Dataset for "The Permo-Carboniferous basins of the Catalan Pyrenees (NE Iberia): an example of interacting tectonics and collapse calderas"

description: This dataset includes the data for the construction of the models presented in the paper: "The Permo-Carboniferous basins of the Catalan Pyrenees (NE Iberia): an example of interacting tectonics and collapse calderas" by Saura et al. submitted for publication to Tectonics on April 2025.
DOI: 10.17632/knwmw9h94v.1
title: Carbon and oxygen isotopes in calcite from the CM chondrites Aguas Zarcas and MIL 13005: Implications for O and C sources and alteration conditions

description: Data for Paper in Preparation: "Carbon and oxygen isotopes in calcite from the CM chondrites Aguas Zarcas and MIL 13005: Implications for O and C sources and alteration conditions"

Abstract

Here we present petrographic, O isotope, and C isotope data on calcite and petrographic and O isotope data on magnetite in Aguas Zarcas (CM2) and Miller Range (MIL) 13005 (CM1/2) in an effort to test CM aqueous alteration models. Our O and C isotope data for Aguas Zarcas and MIL 13005 are within the ranges reported in previous work for calcite in CMs. Using O isotope data from Δ17O-matched calcite and magnetite grains in our samples, we calculated equilibrium-model formation temperatures for the analyzed calcites in each meteorite. Combining our isotopic and temperature data with literature data, we sort the data into less altered (CM2) and more altered (CM1/2 and CM1) categories, and examine that data for differences between the categories by analyzing the δ18O-δ17O, δ18O-δ13C, and model formation temperature data of the categories. We find potential differing trends between δ18O and δ13C in calcites between our two CM alteration categories, and find that sparse extant temperature data imply that more altered CMs (Types 1 and 1/2) may have undergone alteration at a lower average temperature than CM2s. We also find that the O isotopes between CM1s, CM2s, and CM1/2s do not differ significantly. Through use of a mass-balance model, we infer a pre-alteration ice Δ17O within the range of 5.29-13.31‰. Also from that model, we find two generations of calcite formation in MIL 13005 with different proportions of their O being sourced from ices and anhydrous silicates, and one generation of calcites within Aguas Zarcas. We used a mass-balancing model based on our calcite oxygen isotope data to infer a pre-alteration ice Δ17O composition of 5-15‰. We carried out concentration mixing models, which show that the calcite data can be readily explained using three C- and O-bearing sources.
DOI: 10.6084/m9.figshare.24988294
title: Artificial intelligence in supply chain management: enablers and constraints in pre-development, deployment, and post-development stages

description: This study presents a comprehensive investigation into the AI supply chain journey, combining a systematic literature review (SLR) and empirical interviews with supply chain experts. The objective is to identify and analyze key enablers and constraints influencing AI in the pre-development, deployment, and post-development stages. The research integrates empirical data with a Technology-Organization-Environment (TOE) framework, revealing the interactions between technological, organizational, and environmental factors. The thematic analysis uncovers six axial themes for the pre-development stage and one theme for the deployment and post-development stages respectively, providing valuable insights into factors influencing successful AI integration. Moreover, industry-specific insights are unveiled for the Airline, Agri-food, Retail, and Logistics sectors, emphasizing the importance of contextual factors and tailored AI strategies. The study contributes to the existing knowledge by offering practical implications for AI integration in supply chains, highlighting the significance of managing constraints and industry heterogeneity. By identifying and understanding the key constraints, this research provides a deeper understanding of the constraints faced during different stages of AI in supply chains. This study makes a substantial contribution to the current socio-technical discourse on the successful journey of AI in supply chains by deriving eight propositions that offer valuable insights. These propositions delve into the practical implications of addressing constraints and transforming them into enablers for achieving enhanced supply chain performance. The propositions offer guidance to both academic researchers and industry professionals, equipping them with actionable strategies to navigate the complexities and intricacies of integrating AI technologies into the supply chain. By embracing these propositions, stakeholders can effectively harness the power of AI to optimize various aspects of the supply chain, leading to improved efficiency, agility, and competitiveness. Ultimately, this research contributes to advancing the understanding of the AI journey in supply chains and offers practical solutions to drive the successful embracing of AI technologies in real-world supply chain environments.
DOI: 10.6084/m9.figshare.24988294.v1
title: Artificial intelligence in supply chain management: enablers and constraints in pre-development, deployment, and post-development stages

description: This study presents a comprehensive investigation into the AI supply chain journey, combining a systematic literature review (SLR) and empirical interviews with supply chain experts. The objective is to identify and analyze key enablers and constraints influencing AI in the pre-development, deployment, and post-development stages. The research integrates empirical data with a Technology-Organization-Environment (TOE) framework, revealing the interactions between technological, organizational, and environmental factors. The thematic analysis uncovers six axial themes for the pre-development stage and one theme for the deployment and post-development stages respectively, providing valuable insights into factors influencing successful AI integration. Moreover, industry-specific insights are unveiled for the Airline, Agri-food, Retail, and Logistics sectors, emphasizing the importance of contextual factors and tailored AI strategies. The study contributes to the existing knowledge by offering practical implications for AI integration in supply chains, highlighting the significance of managing constraints and industry heterogeneity. By identifying and understanding the key constraints, this research provides a deeper understanding of the constraints faced during different stages of AI in supply chains. This study makes a substantial contribution to the current socio-technical discourse on the successful journey of AI in supply chains by deriving eight propositions that offer valuable insights. These propositions delve into the practical implications of addressing constraints and transforming them into enablers for achieving enhanced supply chain performance. The propositions offer guidance to both academic researchers and industry professionals, equipping them with actionable strategies to navigate the complexities and intricacies of integrating AI technologies into the supply chain. By embracing these propositions, stakeholders can effectively harness the power of AI to optimize various aspects of the supply chain, leading to improved efficiency, agility, and competitiveness. Ultimately, this research contributes to advancing the understanding of the AI journey in supply chains and offers practical solutions to drive the successful embracing of AI technologies in real-world supply chain environments.
DOI: 10.17632/d7x878krhr.1
title: dataset

description: papaer data
DOI: 10.17632/8jmt7bjn8w.1
title: FSO Communication Parameters in Multi-User Systems under Variable Fog Conditions

description: This dataset comprises 3,000 data points collected from an advanced Free Space Optical (FSO) communication system designed for both SISO and MIMO configurations. The dataset captures key communication parameters, including range, Received Optical Power (ROP), Quality Factor (Q-factor), and Bit Error Rate (BER), under diverse fog conditions—Light Fog (LF), Medium Fog (MF), and Heavy Fog (HF). Each configuration (LF MIMO, HF MIMO, MF MIMO, LF SISO, HF SISO, MF SISO) is represented by 500 data points, offering a balanced distribution across the various scenarios.

The dataset is structured to support research on predictive modeling, handover optimization, and performance analysis in FSO networks. It has been preprocessed using a Min-Max normalization technique to ensure uniform scaling, making it ideal for machine learning applications such as regression and classification tasks. Detailed statistical summaries (mean, standard deviation, quartile ranges) and data distribution plots accompany the dataset, facilitating immediate use and benchmarking in studies of wireless communication performance under adverse atmospheric conditions.

Researchers can utilize this dataset to explore correlations between environmental factors and communication performance, develop adaptive handover strategies, and enhance overall FSO network reliability and efficiency. For further details and access, please contact the corresponding author.
DOI: 10.17632/4jm4fh2nk2.1
title: ALATDYN: A set of Anharmonic LATtice DYNamics codes to compute thermodynamic and thermal transport properties of crystalline solids

description: We introduce a lattice dynamics package which calculates elastic, thermodynamic and thermal transport properties of crystalline materials from data on their force and potential energy as a function of atomic positions. The data can come from density functional theory (DFT) calculations or classical molecular dynamics runs performed in a supercell. First, the model potential parameters, which are anharmonic force constants are extracted from the latter runs. Then, once the anharmonic model is defined, thermal conductivity and equilibrium properties at finite temperatures can be computed using lattice dynamics, Boltzmann transport theories, and a variational principle respectively. In addition, the software calculates the mechanical properties such as elastic tensor, Gruneisen parameters and the thermal expansion coefficient within the quasi-harmonic approximation (QHA). Phonons, elastic constants and thermodynamic properties results applied to the germanium crystal will be illustrated. Using the force constants as a force field, one may also perform molecular dynamics (MD) simulations in order to investigate the combined effects of anharmonicity and defect scattering beyond perturbation theory.
DOI: 10.17632/bn7k4w5zd9.1
title: Supplementary data on California power providers' rates and costs

description: Data on sales, costs, rates, area, rates of return and equity, and illustrative bills for power providers in California. Source data documents and cleaned tables are included.

Datasets included:
1. CCA JRC PDFs: Joint Rate Comparisons for Community Choice Aggregators, scraped from IOU website via the Wayback Machine
2. EIA Data: collected EIA Form 861 datasets
3. POU Financial Statements: annual audited financials of LADWP and SMUD
4. Residential and Commercial Rate Source PDFs: for IOUs and POUs, source files for rate time series
5. Appendix Data Part 1 - Rates, Usage, Area, Costs: 
 5a: Core CPI rates
 5b: Residential and Commercial Rate time series
 5c: IOU rate base
 5d: IOU O&M 
 5e: POU utility plant
 5f: POU O&M
 5g: CCA rate comparisons
 5h: detailed IOU O&M data
 5i: consolidated EIA sales data (all LSEs)
 5j: consolidated EIA sales data (selected LSEs)
 5k: CCA service area calculation
6. Appendix Data Part 2 - Illustrative Monthly Bills: comparisons between CCA and IOUs, with intermediate calculations
7. Appendix Data Part 3 - ROE and ROR: time series of rates of return for selected IOUs
DOI: 10.17632/bn7k4w5zd9.2
title: Supplementary data on California power providers' rates and costs

description: Data on sales, costs, rates, area, rates of return and equity, and illustrative bills for power providers in California. Source data documents and cleaned tables are included.

Datasets included:
1. CCA JRC PDFs: Joint Rate Comparisons for Community Choice Aggregators, scraped from IOU website via the Wayback Machine
2. EIA 861 Tables: collected EIA Form 861 datasets and associated datacleaning code
3. POU Financial Statements: annual audited financials of LADWP and SMUD
4. Residential and Commercial Rate Source PDFs: for IOUs and POUs, source files for rate time series
5. Appendix Data Part 1 - Rates, Usage, Area, Costs: 
 5a: Core CPI rates
 5b: Residential and Commercial Rate time series
 5c: IOU rate base
 5d: IOU O&M 
 5e: POU utility plant
 5f: POU O&M
 5g: CCA rate comparisons
 5h: detailed IOU O&M data
 5i: consolidated EIA sales data (all CA LSEs)
 5j: consolidated EIA sales data with average prices (selected CA and non-CA LSEs)
 5k: CCA service area calculation
 5l: interstate baseline residential rate comparison
 5m: extended sample of CA POUs O&M and utility plant
6. Appendix Data Part 2 - Illustrative Monthly Bills: comparisons between CCA and IOUs, with customer load shape and intermediate calculations
7. Appendix Data Part 3 - ROE and ROR: time series of rates of return and return on equity for selected IOUs
8. PUDL FERC1 Processing Code: Python code to pull latest stable PUDL dataset and extract IOU O&M data as required
DOI: 10.17632/gnyynhcyzt.1
title: Adverse early-life experiences are associated with stress-response behavioral alteration, hypothalamic-pituitary-adrenal axis hyperactivity, and a larger pituitary gland volume in adult CD-1 male mice

description: Mice's behavior was evaluated by forced swim test. Tissues were analyzed by ELISA assays. Analysis of brain and pituitary was performed using anatomic magnetic resonance imaging, and the diffusion-weighted imaging techniques (diffusion-weighted imaging and apparent diffusion coefficient).
DOI: 10.17632/gnyynhcyzt.2
title: Adverse early-life experiences are associated with stress-response behavioral alteration, hypothalamic-pituitary-adrenal axis hyperactivity, and a larger pituitary gland volume in adult CD-1 male mice

description: Mice's behavior was evaluated by forced swim test. Tissues were analyzed by ELISA assays. Analysis of brain and pituitary was performed using anatomic magnetic resonance imaging, and the diffusion-weighted imaging techniques (diffusion-weighted imaging and apparent diffusion coefficient).
DOI: 10.34740/kaggle/dsv/11249995
title: Hacker News Cumulative Data
DOI: 10.17632/96rz83s494.1
title: Salud espiritual y calidad de vida en pacientes con DM2, un estudio multicéntrico

description: Título: Correlación entre salud espiritual y calidad de vida relacionada con la salud en pacientes con diabetes mellitus tipo 2, un estudio multicéntrico.

Investigador: Dr. Daniel Alberto Valderrama Ruiz
Asesor principal: Dr. Héctor Riquelme Heras

El presente trabajo pretendía contestar la siguiente pregunta de investigación ¿Existe una correlación significativa entre la salud espiritual y la calidad de vida relacionada con la salud, en pacientes con diabetes mellitus tipo 2 en 3 hospitales de Nuevo León en el 2024?

Metodología
El estudio tuvo un enfoque empírico, transversal, descriptivo y correlacional. Se realizó en pacientes mayores de 18 años diagnosticados con diabetes mellitus tipo 2, atendidos en el Hospital Universitario “Dr. José Eleuterio González”, el Hospital La Carlota y el Hospital General de Montemorelos, en Nuevo León, durante el año 2024. Se utilizó el instrumento ESE-UM para medir la variable de salud espiritual y el instrumento D-39 para medir la calidad de vida relacionada con la salud. Ambos instrumentos fueron aplicados mediante la plataforma Questionpro. 
Resultados
Para probar la hipótesis de esta investigación, en primer lugar, se verificó la normalidad de la distribución de los datos para lo cual se aplicó la prueba de Kolmogorov-Smirnov. Se encontró que estos no mostraron una distribución normal, por lo tanto, se optó por utilizar la prueba no paramétrica Rho de Spearman para determinar la correlación entre las variables.
Para este análisis, la CVRS (D-39) se recodificó invirtiendo su escala original (1→7, 2→6, etc.), de modo que mayor puntaje indicara mejor CVRS, alineándose con ESE-UM (mayor puntaje = mejor salud espiritual). Se encontró una correlación positiva y significativa entre la salud espiritual y la calidad de vida relacionada con la salud en los pacientes con diabetes mellitus tipo 2, en 3 hospitales de Nuevo León en el 2024 (ρ = 0.338, p &lt; 0.001). 
Esto indica que a medida que la salud espiritual de los pacientes mejora, también lo hace su percepción de calidad de vida relacionada con la salud.
Este hallazgo subraya la importancia de incluir el bienestar espiritual en la atención integral de estos pacientes.
Conclusión
El estudio identificó una correlación positiva y significativa entre la salud espiritual y la calidad de vida en pacientes con diabetes mellitus tipo 2, lo que sugiere que aquellos con mayor bienestar espiritual tienden a experimentar una mejor calidad de vida. 
Por lo tanto, se recomienda que los profesionales de la salud consideren aspectos espirituales y emocionales en su enfoque terapéutico, para ofrecer una atención más integral y centrada en el paciente.