cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/72t63nzdmk
title: A Spreadsheet Tool to Simulate Equivalent Discrete Effective Returns Based on Combinations of Expected Continuous Returns and Volatility

description: In this spreadsheet tool (worksheet “Simulation”), we implement Equation (21.17) from John Hull (2022) using a Monte Carlo simulation as follows:

Input Cells (Parameters)

Cell B1: Initial capital S(0)
Cell B2: Expected continuously compounded annual return μ^
Cell B3: Investment horizon in years T
The initial capital, the expected continuously compounded annual return, and the investment horizon can be chosen freely.
Row 5: Annual volatility σ
The volatility values are predefined in the worksheet and increase in steps of 5 percentage points, ranging from 0% up to 300%.

Output Cells

For each combination of expected continuously compounded annual return and annual volatility:
 - Row 11: The resulting final capital is calculated using Equation (21.17), assuming continuous compounding.
 - Row 12: The equivalent discrete annual return is computed — that is, the discrete return that generates the same final capital as the continuously compounded return.

Beginning in Row 18, 1,000 simulation runs are performed for each combination of expected continuous return and volatility. In each simulation run, the equivalent discrete annual return is calculated according to the method in Row 12.

After the simulation runs, in:
 - Row 13: The arithmetic mean of the 1,000 simulated equivalent discrete annual returns is determined for each parameter combination.
 - Row 14: For comparison, the annual return is calculated that results when
 - the random term (the ε part) in Equation (21.17) is omitted, and
 - discrete compounding is assumed.
 - Row 15: The absolute difference between the simulated average (Row 13) and the analytical comparison value (Row 14) is reported.

Reference:
Hull, John C. (2022): Options, Futures, and other Derivatives, Global Edition, 11th Edition, Pearson, pp. 491-492.

We used AI (Microsoft Copilot) to check the consistency of our concept.
DOI: 10.17632/72t63nzdmk.1
title: A Spreadsheet Tool to Simulate Equivalent Discrete Effective Returns Based on Combinations of Expected Continuous Returns and Volatility

description: In this spreadsheet tool (worksheet “Simulation”), we implement Equation (21.17) from John Hull (2022) using a Monte Carlo simulation as follows:

Input Cells (Parameters)

Cell B1: Initial capital S(0)
Cell B2: Expected continuously compounded annual return μ^
Cell B3: Investment horizon in years T
The initial capital, the expected continuously compounded annual return, and the investment horizon can be chosen freely.
Row 5: Annual volatility σ
The volatility values are predefined in the worksheet and increase in steps of 5 percentage points, ranging from 0% up to 300%.

Output Cells

For each combination of expected continuously compounded annual return and annual volatility:
 - Row 11: The resulting final capital is calculated using Equation (21.17), assuming continuous compounding.
 - Row 12: The equivalent discrete annual return is computed — that is, the discrete return that generates the same final capital as the continuously compounded return.

Beginning in Row 18, 1,000 simulation runs are performed for each combination of expected continuous return and volatility. In each simulation run, the equivalent discrete annual return is calculated according to the method in Row 12.

After the simulation runs, in:
 - Row 13: The arithmetic mean of the 1,000 simulated equivalent discrete annual returns is determined for each parameter combination.
 - Row 14: For comparison, the annual return is calculated that results when
 - the random term (the ε part) in Equation (21.17) is omitted, and
 - discrete compounding is assumed.
 - Row 15: The absolute difference between the simulated average (Row 13) and the analytical comparison value (Row 14) is reported.

Reference:
Hull, John C. (2022): Options, Futures, and other Derivatives, Global Edition, 11th Edition, Pearson, pp. 491-492.

We used AI (Microsoft Copilot) to check the consistency of our concept.
DOI: 10.20350/digitalcsic/18084
title: Supplementary data New insights on active geodynamics of Iberia and Northwestern Africa from seismic stress and geodetic strain-rate fields [Dataset]
DOI: 10.17632/6pr47pty85.1
title: Enterococcus durans B21
DOI: 10.6084/m9.figshare.31306081
title: OpenCitations Index Database Dump

description: This OpenCitations (https://opencitations.net/) dataset contains a full dump of the OpenCitations Index Qlever database. It includes citation data between bibliographic entities stored in the OpenCiations Meta.This release includes citation data retrieved from the September 2025 version of Crossref (https://api.crossref.org/snapshots/monthly/2025/09/all.json.tar.gz), as well as the DataCite Public Data File of April 2024 (https://archive.org/details/datacite-2024-04-17).This version of the dataset:Contatins <b>2,422,432,262 Citations;</b>Coming from 6 different sources: Crossref, Datacite, PubMed, OpenAIRE, JaLC, and the OpenCitations Crowdsourcing service;Compressed size is: 69 GB (7z format)Uncompressed size: 140 GBNumber of triples: 10,172,822,234The data is provided as a multi-part 7zip archive. To extract it, please use the provided extraction scripts (`extract_archive.sh` for Linux/macOS and `extract_archive.bat` for Windows).Usage example (Linux/macOS):<br><code>bash extract_archive.sh oc-index-qlever-202602.7z.001 ./extracted_data</code><br>Usage example (Windows):<br><code>extract_archive.bat oc-index-qlever-202602.7z.001 .\extracted_data</code><br>For more information, please refer to the following paper: Heibi, I., Moretti, A., Peroni, S., & Soricetti, M. (2024). The OpenCitations Index: Description of a database providing open citation data. Scientometrics. https://doi.org/10.1007/s11192-024-05160-7<br>
DOI: 10.6084/m9.figshare.31306081.v1
title: OpenCitations Index Database Dump

description: This OpenCitations (https://opencitations.net/) dataset contains a full dump of the OpenCitations Index Qlever database. It includes citation data between bibliographic entities stored in the OpenCiations Meta.This release includes citation data retrieved from the September 2025 version of Crossref (https://api.crossref.org/snapshots/monthly/2025/09/all.json.tar.gz), as well as the DataCite Public Data File of April 2024 (https://archive.org/details/datacite-2024-04-17).This version of the dataset:Contatins <b>2,422,432,262 Citations;</b>Coming from 6 different sources: Crossref, Datacite, PubMed, OpenAIRE, JaLC, and the OpenCitations Crowdsourcing service;Compressed size is: 69 GB (7z format)Uncompressed size: 140 GBNumber of triples: 10,172,822,234The data is provided as a multi-part 7zip archive. To extract it, please use the provided extraction scripts (`extract_archive.sh` for Linux/macOS and `extract_archive.bat` for Windows).Usage example (Linux/macOS):<br><code>bash extract_archive.sh oc-index-qlever-202602.7z.001 ./extracted_data</code><br>Usage example (Windows):<br><code>extract_archive.bat oc-index-qlever-202602.7z.001 .\extracted_data</code><br>For more information, please refer to the following paper: Heibi, I., Moretti, A., Peroni, S., & Soricetti, M. (2024). The OpenCitations Index: Description of a database providing open citation data. Scientometrics. https://doi.org/10.1007/s11192-024-05160-7<br>
DOI: 10.17632/d7nzdgrjwy
title: Financial Openness and Wealth Inequality: The moderating role of financial development

description: This is a replication package of the paper "Financial Openness and Wealth Inequality: The moderating role of financial development".
DOI: 10.17632/d7nzdgrjwy.1
title: Financial Openness and Wealth Inequality: The moderating role of financial development

description: This is a replication package of the paper "Financial Openness and Wealth Inequality: The moderating role of financial development".
DOI: 10.17632/pkwk2xygdt
title: Mo isotopies+hydrothermal+seep carbonates

description: date of manuscript: "Mo isotopes distinguish seawater and hydrothermal inputs to seep carbonates".
DOI: 10.17632/pkwk2xygdt.1
title: Mo isotopies+hydrothermal+seep carbonates

description: date of manuscript: "Mo isotopes distinguish seawater and hydrothermal inputs to seep carbonates".
DOI: 10.17632/52nx7hcdft
title: Parallel Corpus of Banjar Dialect Hulu-Indonesian

description: This data was collected manually with reference to a dictionary of the Hulu dialect of Banjarese. A total of 7,005 data points were collected and verified by native speakers.
DOI: 10.17632/52nx7hcdft.1
title: Parallel Corpus of Banjar Dialect Hulu-Indonesian

description: This data was collected manually with reference to a dictionary of the Hulu dialect of Banjarese. A total of 7,005 data points were collected and verified by native speakers.
DOI: 10.17632/8rc8dzn6mk
title: Unstructured tetrahedral meshes for FEM-based transient EM modeling of continuous heterogeneous media (v1)

description: This dataset provides the original mesh files that correspond one-to-one to the mesh schematics shown in the paper. File names mirror the figure numbering (e.g., Fig2a-*.* corresponds to Fig. 2(a)). All meshes can be generated by COMSOL, so a model corresponding to the .mph file has been uploaded, software version 5.2/5.6. The cross-sectional mesh is displayed using Tecplot, so the corresponding .dat file has been uploaded, software version 2023R1.
DOI: 10.17632/8rc8dzn6mk.2
title: Unstructured tetrahedral meshes for FEM-based transient EM modeling of continuous heterogeneous media (v1)

description: This dataset provides the original mesh files that correspond one-to-one to the mesh schematics shown in the paper. File names mirror the figure numbering (e.g., Fig2a-*.* corresponds to Fig. 2(a)). All meshes can be generated by COMSOL, so a model corresponding to the .mph file has been uploaded, software version 5.2/5.6. The cross-sectional mesh is displayed using Tecplot, so the corresponding .dat file has been uploaded, software version 2023R1.
DOI: 10.17632/575fy2tm7k
title: Vibration-Based Pipeline Leak Detection Dataset Using Linear Discriminant Analysis (LDA)

description: This repository contains the experimental vibration data, extracted feature dataset, trained model parameters, and analysis scripts used in the study:
“Vibration-Based Leak Detection in fluid Pipelines Using Linear Discriminant Analysis.”
The dataset supports the results presented in the manuscript and enables full reproducibility of the experimental and machine-learning procedures.
DOI: 10.17632/575fy2tm7k.1
title: Vibration-Based Pipeline Leak Detection Dataset Using Linear Discriminant Analysis (LDA)

description: This repository contains the experimental vibration data, extracted feature dataset, trained model parameters, and analysis scripts used in the study:
“Vibration-Based Leak Detection in fluid Pipelines Using Linear Discriminant Analysis.”
The dataset supports the results presented in the manuscript and enables full reproducibility of the experimental and machine-learning procedures.
DOI: 10.15468/dl.kxaz6w
title: Occurrence Download

description: A dataset containing 873455 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Madagascar",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 873455 records from 344 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021761-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/p9w2fdtc7k
title: Data Extraction Dataset for a Systematic Literature Review on Machine Learning in Encrypted Data and Homomorphic Encryption

description: This is the data extraction dataset for a systematic literature review on machine learning in encrypted data and homomorphic encryption study.
DOI: 10.17632/p9w2fdtc7k.1
title: Data Extraction Dataset for a Systematic Literature Review on Machine Learning in Encrypted Data and Homomorphic Encryption

description: This is the data extraction dataset for a systematic literature review on machine learning in encrypted data and homomorphic encryption study.
DOI: 10.15468/dl.g8mnru
title: Occurrence Download

description: A dataset containing 248 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Spain",
 "Geometry POLYGON((-5.27583 36.29359,-3.65225 36.62174,-3.94902 37.88876,-5.49914 37.62937,-5.27583 36.29359))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Lavandula stoechas"
 ]
}

 The dataset includes 248 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021821-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/n9ptzv2fzb
title: Multidimensional Urban Morphology and Carbon Intensity: Nonlinear Drivers in Dense Cities

description: The multidimensional morphological attributes, encompassing three-dimensional metrics (e.g., FAR, SVF, and BHI) and two-dimensional indicators (e.g., BCD and BAD), were systematically quantified at the block scale. GIS-based zonal statistics were employed to integrate these morphological datasets with environmental constraints (such as Slope and DEM) and socioeconomic proxies (ANL and POI density). The functional typologies of urban blocks were rigorously categorized based on a "Dominant Function Identification" strategy, systematically integrating land-use data with POI ratios. Carbon emission intensity (CEI) was derived from the 2023 ODIAC high-resolution inventory. Additionally, Land Surface Temperature (LST) data were acquired from Landsat 8 imagery in August 2023 to physically validate the thermodynamic interaction effects. All statistical modeling, including XGBoost-SHAP analysis and spatial autocorrelation diagnostics, was executed using custom Python scripts.
DOI: 10.15468/dl.mjdxsx
title: Occurrence Download

description: A dataset containing 154 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Spain",
 "Geometry POLYGON((-5.27583 36.29359,-3.65225 36.62174,-3.94902 37.88876,-5.49914 37.62937,-5.27583 36.29359))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Genista hirsuta"
 ]
}

 The dataset includes 154 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021818-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/n9ptzv2fzb.1
title: Multidimensional Urban Morphology and Carbon Intensity: Nonlinear Drivers in Dense Cities

description: The multidimensional morphological attributes, encompassing three-dimensional metrics (e.g., FAR, SVF, and BHI) and two-dimensional indicators (e.g., BCD and BAD), were systematically quantified at the block scale. GIS-based zonal statistics were employed to integrate these morphological datasets with environmental constraints (such as Slope and DEM) and socioeconomic proxies (ANL and POI density). The functional typologies of urban blocks were rigorously categorized based on a "Dominant Function Identification" strategy, systematically integrating land-use data with POI ratios. Carbon emission intensity (CEI) was derived from the 2023 ODIAC high-resolution inventory. Additionally, Land Surface Temperature (LST) data were acquired from Landsat 8 imagery in August 2023 to physically validate the thermodynamic interaction effects. All statistical modeling, including XGBoost-SHAP analysis and spatial autocorrelation diagnostics, was executed using custom Python scripts.
DOI: 10.5061/dryad.w0vt4b96p
title: Data for: Moisture and temperature patterns of canopy humus and forest floor soil of a montane cloud forest, Costa Rica

description: Accumulations of organic material can be found in the crowns of trees in
 tropical wet forests.  We investigated moisture and temperature
 patterns of dead organic matter in the canopy and of soil in the upper
 horizons of the forest floor over a 42-month period. 
 Temperatures of the canopy material and forest floor soil fluctuated
 throughout the year (range = 11.5°C to 21.0°C), but remained within an
 average 1°C of each other. Both canopy material and forest floor soils
 were moist throughout the wet and misty seasons (over 70% water content).
 Although canopy organic substrate experienced periods of rapid and severe
 dehydration during the dry season (20%-40% water content), forest floor
 soils remained at a consistently high water content (60%-70%). 
 The more extreme and fluctuating moisture conditions of canopy organic
 material may be important in determining the distribution and activity of
 epiphytic plants and associated canopy organisms.
description: # Data for: Moisture and temperature patterns of canopy humus and forest
 floor soil of a montane cloud forest, Costa Rica Dataset DOI:
 [10.5061/dryad.w0vt4b96p](https://doi.org/10.5061/dryad.w0vt4b96p) ##
 Description of the data and file structure
 **Moisture_and_temperature_of_canopy_humus_and_forest_floor_soil.csv**
 Temperature and soil moisture measures (fresh weight, dry weight, percent
 moisture, and percent dry matter) were taken from canopy humus (CO) and
 the forest floor A and O horizons (FFA:FFO). Occasionally, temperature
 data was not gathered—temperature data for these cases is listed as
 “null”. Samples were taken across three seasons (wet, dry, and misty) an
 average of nine days apart from October 8^th^1987 through July 2^nd^1991
 for a total of 2,160 observations across 84 sampling periods. Forest floor
 measures (FFA and FFO) were paired and share Sample ID codes starting with
 “FF” followed by an alphabetic indicator for sampling period and a numeric
 value for the replicate on that day. Canopy samples have an ID starting
 with “C” followed by the tree ID number from which they were taken,
 followed by an alphabetic indicator for sampling period and a numeric
 value for the replicate on that day; these sample are not paired with
 forest floor measures.
DOI: 10.15468/dl.w8byec
title: Occurrence Download

description: A dataset containing 823 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Crocidura attenuata"
 ]
}

 The dataset includes 823 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021823-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q6h944
title: Occurrence Download

description: A dataset containing 212 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Year is greater than or equal to 1900",
 "TaxonKey is Eriachne glabrata"
 ]
}

 The dataset includes 212 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021824-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e3k6mx
title: Occurrence Download

description: A dataset containing 11053 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Buteo buteo buteo"
 ]
}

 The dataset includes 11053 records from 82 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021820-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3cajcb
title: Occurrence Download

description: A dataset containing 158794 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Acalypha phleoides, Alyssum turkestanicum, Anemonastrum canadense, Ditaxis humilis, Symphyotrichum oblongifolium, Atrema americanum, Oenothera serrulata, Carex duriuscula, Zeltnera beyrichii, Cleomella serrulata, Erigeron canadensis, Zephyranthes chlorosolen, Oreocarya glomerata, Delphinium carolinianum, Pelecyphora vivipara, Oenothera suffrutescens, Verbena bipinnatifida, Verbena pumila, Dianthera americana, Disakisperma dubium, Physaria arenosa, Physaria fendleri, Filago arvensis, Chthamalia biflora, Mimosa quadrivalvis, Blitum nuttallianum, Solidago rigida, Lithospermum occidentale, Packera thurberi, Elymus smithii, Hilaria mutica, Drymocallis arguta, Pediomelum tenuiflorum, Ladeania lanceolata, Muhlenbergia multiflora, Muhlenbergia paniculata, Sedum nuttallii, Viola rafinesquei, Festuca octoflora, Wedelia acapulcensis, Toxicoscordion venenosum)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Country is one of (United States of America, Canada, Mexico, Belize, Guatemala, El Salvador, Honduras, Nicaragua, Costa Rica, Panama, Cuba, Haiti, Dominican Republic, Jamaica, Bahamas, Trinidad and Tobago, Barbados, Grenada, Saint Lucia, Saint Vincent and the Grenadines, Antigua and Barbuda, Dominica, Saint Kitts and Nevis, Colombia, Venezuela (Bolivarian Republic of), Guyana, Suriname, French Guiana, Ecuador, Peru, Brazil, Bolivia (Plurinational State of), Paraguay, Uruguay, Argentina, Chile)",
 "BasisOfRecord is one of (Human Observation, Observation, Machine Observation)"
 ]
}

 The dataset includes 158794 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021770-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ttya6f
title: Occurrence Download

description: A dataset containing 204363 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is The reptiles and amphibians collection (RA) of the Muséum national d'Histoire Naturelle (MNHN - Paris)"
 ]
}

 The dataset includes 204363 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021806-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/wxtzh6c4m6
title: Website Performance Dataset using Web Scraping

description: The dataset contains website performance metrics collected through web scraping, including page load time, response time, page size, and UX/UI element counts. The dataset is used for clustering analysis using k-means and silhouette score evaluation
DOI: 10.17632/wxtzh6c4m6.1
title: Website Performance Dataset using Web Scraping

description: The dataset contains website performance metrics collected through web scraping, including page load time, response time, page size, and UX/UI element counts. The dataset is used for clustering analysis using k-means and silhouette score evaluation
DOI: 10.17632/f3c82nby4j
title: Dataset for: Who Are the Children That Environmental Education Targets? Mapping Geographic and Conceptual Boundaries in More-than-Human Environmental Education

description: This dataset contains the coding framework and extracted data for a systematic review examining representations of childhood and multispecies relationships in environmental education literature. The dataset includes 113 peer-reviewed articles (2009-2025) coded across four dimensions: geographic and demographic patterns, methodological approaches, conceptual framings, and rhetorical strategies. The Excel file includes 26 columns. This dataset accompanies the article: Who Are the Children That Environmental Education Targets? Mapping Geographic and Conceptual Boundaries in More-than-Human Environmental Education Research