cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/qas6lg
title: Replication Data for: Estimating treatment effects for multiple, continuous treatments: Research success in liberal-arts college economics departments

description: Data are collected from faculty curricula vitae, institution websites, and where necessary through personal correspondence. Time-dependent variables (like number of years since receipt of PhD) are all clocked at Summer, 2018. We have more data—75 variables in all —but focus here on variables used in this paper’s estimations.
 Our pre-treatment matching variables include a binary variable for appointment to a research-assistant position while in graduate school, the PhD program’s rank (US News and World Report), the number of peer-reviewed journal articles in the first three years after receipt of the PhD (as an index of research-preparation quality of the PhD program), a binary variable indicating PhDs in traditionally theory-heavy fields (theory, econometrics, international), a binary variable for appointment to a post-doc position at completion of the PhD, a measure of the number of years since receipt of the PhD, and gender (male=0). 
Our treatment variables record the potential number of sabbatical leaves (given a subject’s time since PhD and institutional sabbatical policy), the number of economist colleagues (excluding self) and number of colleagues in the same subfield of economics, the institution’s average class size, the number of weeks of paid and unpaid family leave, the institution’s annual per-faculty travel funding, the institution’s teaching load (average courses per semester), a binary variable equal to one if the institution offers pre-tenure research leaves, the length of the institution’s tenure clock (in years), a binary variable equal to one if the participant has served as department chair, the institution’s rank among the top 50 national liberal arts colleges (2018 US News, #1 being top-ranked), and a binary variable equal to one if the economics department is housed within a context that is an accredited business program. 
Our primary outcome variable is the number of articles in journals that appear in the Australian Business Deans Council Journal Quality List.
DOI: 10.21227/5vjx-rj57
title: "The Landscape of File Formats and Comparisons Survey Result Data"

description: "Dataset containing amount of time needed to output a certain number of tokens when given a prompt. 3 different files were produced with common machine learning formats including safetensors, onnx, tensorrt, torch, and gguf."
DOI: 10.15468/dl.r3gdk2
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation)",
 "Continent is Oceania",
 "TaxonKey is Rupicapra rupicapra rupicapra"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069860-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17195455
title: Protective Effects of Herbal Toothpastes Against Dentin Erosion: An In Vitro Study – Raw Data

description: This dataset provides the experimental data generated during an in vitro study evaluating the preventive effects of different herbal and nano-hydroxyapatite toothpaste formulations on dentin erosion. The files include: (1) surface roughness (Ra, µm) values, (2) surface microhardness (VHN) values, and (3) original SEM and AFM micrographs of dentin surfaces at different experimental phases. These data support the findings reported in the associated manuscript.
DOI: 10.5281/zenodo.17195756
title: Protective Effects of Herbal Toothpastes Against Dentin Erosion: An In Vitro Study – Raw Data

description: This dataset provides the experimental data generated during an in vitro study evaluating the preventive effects of different herbal and nano-hydroxyapatite toothpaste formulations on dentin erosion. The files include: (1) surface roughness (Ra, µm) values, (2) surface microhardness (VHN) values, and (3) original SEM and AFM micrographs of dentin surfaces at different experimental phases. These data support the findings reported in the associated manuscript.
DOI: 10.6084/m9.figshare.30979507
title: <b>Exploring the Impact of Adaptive Perfectionism on Academic Engagement</b>

description: Academic engagement is a central indicator of students’ learning adaptation and developmental potential, yet the psychological mechanisms linking adaptive individual characteristics to engagement remain insufficiently clarified. This study examines whether adaptive perfectionism is associated with academic engagement through the sequential roles of self-control and meaning in life, introducing a resource– and motivation-based explanatory perspective to the field. A cross-sectional questionnaire survey was administered to 1,083 university students, and data were analyzed using structural equation modeling and bias-corrected bootstrap procedures. The results showed that adaptive perfectionism was positively associated with academic engagement. Self-control and meaning in life each mediated this association, and a significant sequential mediating pathway was identified. These findings indicate that adaptive perfectionism is linked to higher academic engagement partly through enhanced self-regulatory capacity and stronger meaning-based motivational experiences. The study contributes to existing theory by integrating Conservation of Resources Theory and Self-Determination Theory to explain how adaptive individual factors are associated with sustained academic engagement.
DOI: 10.6084/m9.figshare.30979507.v1
title: <b>Exploring the Impact of Adaptive Perfectionism on Academic Engagement</b>

description: Academic engagement is a central indicator of students’ learning adaptation and developmental potential, yet the psychological mechanisms linking adaptive individual characteristics to engagement remain insufficiently clarified. This study examines whether adaptive perfectionism is associated with academic engagement through the sequential roles of self-control and meaning in life, introducing a resource– and motivation-based explanatory perspective to the field. A cross-sectional questionnaire survey was administered to 1,083 university students, and data were analyzed using structural equation modeling and bias-corrected bootstrap procedures. The results showed that adaptive perfectionism was positively associated with academic engagement. Self-control and meaning in life each mediated this association, and a significant sequential mediating pathway was identified. These findings indicate that adaptive perfectionism is linked to higher academic engagement partly through enhanced self-regulatory capacity and stronger meaning-based motivational experiences. The study contributes to existing theory by integrating Conservation of Resources Theory and Self-Determination Theory to explain how adaptive individual factors are associated with sustained academic engagement.
DOI: 10.15468/dl.amk3tz
title: Occurrence Download

description: A dataset containing 426328 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Chaetura vauxi",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON((-180 -90, 180 -90, 180 90, -180 90, -180 -90))"
 ]
}

 The dataset includes 426328 records from 99 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069857-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vbxdaw
title: Occurrence Download

description: A dataset containing 1094 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Laticauda colubrina",
 "Year 1998-2025"
 ]
}

 The dataset includes 1094 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069861-251120083545085/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.30979567
title: The orchestrating role of universities in University Entrepreneurial Ecosystems:

description: This paper examines the role of universities as orchestrators of University Entrepreneurial Ecosystems (UEEs). In this work, we adopt a relational perspective that jointly investigates the perception of both academic and non-academic startups regarding the role universities should play within these ecosystems. Additionally, we explore the obstacles that may slow down the university-startups relationships in UEEs. Building on primary data collected through a survey administered to 136 startups located in the Italian province of Padua, we explore (1) how universities address heterogeneous needs of academic and non-academic ventures, and (2) what are the main obstacles that negatively influence their mutual relationships in those ecosystems. Our findings highlight the emerging role of universities as orchestrators of UEEs. Building on our results and the previous literature, we were able to develop a multi-level taxonomy of institutional, network-related, and ecosystemic obstacles that hinder university–startup relationships and constrain orchestration practices. By reframing the role of universities as ecosystem orchestrators, rather than pure resource providers, this research contributes to the UEE literature and defines a practical path for supporting university leaders, start-up founders and decision makers in managing the factors that may hinder UEEs growth in a more effective way.
DOI: 10.6084/m9.figshare.30979567.v1
title: The orchestrating role of universities in University Entrepreneurial Ecosystems:

description: This paper examines the role of universities as orchestrators of University Entrepreneurial Ecosystems (UEEs). In this work, we adopt a relational perspective that jointly investigates the perception of both academic and non-academic startups regarding the role universities should play within these ecosystems. Additionally, we explore the obstacles that may slow down the university-startups relationships in UEEs. Building on primary data collected through a survey administered to 136 startups located in the Italian province of Padua, we explore (1) how universities address heterogeneous needs of academic and non-academic ventures, and (2) what are the main obstacles that negatively influence their mutual relationships in those ecosystems. Our findings highlight the emerging role of universities as orchestrators of UEEs. Building on our results and the previous literature, we were able to develop a multi-level taxonomy of institutional, network-related, and ecosystemic obstacles that hinder university–startup relationships and constrain orchestration practices. By reframing the role of universities as ecosystem orchestrators, rather than pure resource providers, this research contributes to the UEE literature and defines a practical path for supporting university leaders, start-up founders and decision makers in managing the factors that may hinder UEEs growth in a more effective way.
DOI: 10.5281/zenodo.18109945
title: Sediment supply enhances bedload transport rate via longer transport distance

description: This repository contains all datasets used in the analysis presented in "Sediment supply enhances bedload transport rate via longer transport distance" by Fields et al. (2026). In addition, the R script for the virtual velocity bedload model developed by Fields (2024; https://digitalcommons.dartmouth.edu/dissertations/252/) and used in this paper is included. 

Running the R script should require only:

 1) downloading the datasets included here to a common location on your personal computer; 

2) updating the working directories in that script to reflect the location of those downloaded files, and then running the code section by section. 

There are code breaks built in so that the user pauses to make sure the above section has run successfully before proceeding. The code also produces all the figures presented in the main text of the manuscript. The script is well commented so should be interpretable by anyone with some experience working in R data.table. Please contact Jordan Fields (jordan.f.fields@gmail.com) with questions.
DOI: 10.5281/zenodo.18109944
title: Sediment supply enhances bedload transport rate via longer transport distance

description: This repository contains all datasets used in the analysis presented in "Sediment supply enhances bedload transport rate via longer transport distance" by Fields et al. (2026). In addition, the R script for the virtual velocity bedload model developed by Fields (2024; https://digitalcommons.dartmouth.edu/dissertations/252/) and used in this paper is included. 

Running the R script should require only:

 1) downloading the datasets included here to a common location on your personal computer; 

2) updating the working directories in that script to reflect the location of those downloaded files, and then running the code section by section. 

There are code breaks built in so that the user pauses to make sure the above section has run successfully before proceeding. The code also produces all the figures presented in the main text of the manuscript. The script is well commented so should be interpretable by anyone with some experience working in R data.table. Please contact Jordan Fields (jordan.f.fields@gmail.com) with questions.
DOI: 10.3886/e155161v94
title: Advance Layoff Notice Data from the WARN Act

description: We collect novel and timely data from advance layoff notices filed under the Worker Adjustment and Retraining Notification (WARN) Act. The act requires larger employers to notify affected workers at least 60 days before a potential mass layoff. We assemble WARN data from across the United States, and for many large states our data begin in the 1990s. We aggregate these data into an unbalanced, monthly panel of the state-level number of workers affected by WARN notices, and we update this panel twice a month. We also aggregate this panel to a national-level indicator of job loss (the "WARN factor") using a dynamic factor model.<br>

<b><br>Data Collection</b><br>We update the data twice a month by collecting WARN
notices from state websites. For many states, we have extended our historical
data by using digital archives of the internet and contacting state
officials.<br> <br><b>Citation</b><br>To learn more about
the data and the dynamic factor model, see:<br>Krolikowski, Pawel M. and Kurt G. Lunsford. 2022. “Advance Layoff Notices and Aggregate Job Loss.” Federal Reserve Bank of Cleveland, Working Paper no. 20-03R. https://doi.org/10.26509/frbc-wp-202003R.<br>Krolikowski, Pawel M., and Kurt G. Lunsford. 2024 “Advance Layoff Notices and Aggregate Job Loss.” Journal of Applied Econometrics. https://doi.org/10.1002/jae.3032.<b><br><br></b><b>File Description</b><br>The file labelled WARNFiles_YYYYMMDD.zip in the
main directory contains our most recent data. All data included in this zip
file were collected as of the date listed in the file name. Previous
vintages of our data appear in the `Archived_Vintages’ folder, with the same
naming convention.<br>
<br>The zip files contain three files:<br>
<br>


1. 
README.txt

<br>2. 
WARNData_NSA_YYYYMMDD.csv


 
 This .csv contains the number of workers affected by
 WARN notices by state and month. These data are not seasonally adjusted.
 These data are the input into the dynamic factor model.
 


3. 
WARNFactors_YYYYMMDD.csv


 
 This .csv contains the output of the dynamic factor
 model. The output is labeled as follows:
 
 WARN Factor: the estimates of the factor from the
 dynamic factor model.
 MSE: the estimated mean squared errors
 of the WARN factor.
 WARN_hat: the number of workers affected by
 WARN notices as implied by the WARN factor.
 WARN_sum: the sum of the number of
 workers affected by WARN notices from several states that form a
 balanced panel beginning in January 2006. These states can change every
 update.<b>Disclaimer</b><br>These data are
updated by the authors and are not an official product of the Federal Reserve Bank of Cleveland.<br>
description: Smallest Geographic Unit: State
DOI: 10.15468/dl.zw5wce
title: Occurrence Download

description: A dataset containing 8296922 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Geometry POLYGON((-5.30989 38.67811,-2.27498 38.67811,-2.27498 41.7712,-5.30989 41.7712,-5.30989 38.67811))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year 1990-2025"
 ]
}

 The dataset includes 8296922 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069859-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18108830
title: ctenopoma_ocellatum_spades_01.fasta.gz
DOI: 10.5281/zenodo.18108831
title: ctenopoma_ocellatum_spades_01.fasta.gz
DOI: 10.57967/hf/7410
title: hourly_population_US
DOI: 10.15468/dl.ep73yx
title: Occurrence Download

description: A dataset containing 6157 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "TaxonKey is Ara macao"
 ]
}

 The dataset includes 6157 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069862-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14356333
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.gsjrf6
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is France",
 "TaxonKey is Leiosporocerotopsida"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069864-251120083545085/datasets/export for details.
DOI: 10.15468/dl.ycf3r2
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is France",
 "TaxonKey is "
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069865-251120083545085/datasets/export for details.
DOI: 10.5281/zenodo.18110003
title: Curvature of Space from Classical Physics to CRVD

description: CRVD offers a framework where the geometry of space is an emergent property stemming from the dynamics and spatial distribution of quantum vacuum reactivity ($\rho$). While GR describes how mass curves spacetime, CRVD attempts to describe why the vacuum allows itself to be curved, linking gravity to the structure of zero-point energy through a defined curvature scalar $R(x)$ that stands as the CRVD analog to the celebrated Ricci scalar $R$.
DOI: 10.5281/zenodo.18110002
title: Curvature of Space from Classical Physics to CRVD

description: CRVD offers a framework where the geometry of space is an emergent property stemming from the dynamics and spatial distribution of quantum vacuum reactivity ($\rho$). While GR describes how mass curves spacetime, CRVD attempts to describe why the vacuum allows itself to be curved, linking gravity to the structure of zero-point energy through a defined curvature scalar $R(x)$ that stands as the CRVD analog to the celebrated Ricci scalar $R$.
DOI: 10.15468/dl.639ds2
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "Month is December",
 "OccurrenceStatus is Present",
 "TaxonKey is Puma concolor",
 "Year 2025-2025"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069866-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9v6p2z
title: Occurrence Download

description: A dataset containing 237 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-112.03583 22.80081,-107.67045 22.80081,-107.67045 24.54846,-112.03583 24.54846,-112.03583 22.80081))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Quercus brandegeei"
 ]
}

 The dataset includes 237 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069868-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.30707.18721
title: Balsaminaceae Literature 2025.12.31
DOI: 10.15468/dl.py82w7
title: Occurrence Download

description: A dataset containing 51 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((7.62118 49.45928,9.29256 49.45928,9.29256 50.12746,7.62118 50.12746,7.62118 49.45928))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Andricus kollari"
 ]
}

 The dataset includes 51 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069869-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/194799886af365609e377489f983d5d1
title: Soil Physical Data from the Shark River Slough, Everglades National Park (FCE), from November 2000 to January 2007

description: Soil pH, Eh and temperature readings are taken at SRS1b, SRS1c, SRS1d, SRS2 and SRS3. These measurements are taken only when the marsh is wet. Measurements are taken using an Orion model 250A meter, and the probes attached to the meter are the Orion Thermo pH probe and the Orion Eh probe. All readings are recorded in field notebooks, and then transferred into Microsoft Excel. The Eh reading is taken when the Eh probe is attached to the meter and the word "Ready" appears on the meter screen. The pH and temperature reading are taken when the pH probe is attached to the meter and the word "Ready" appears on the meter screen.
DOI: 10.5281/zenodo.18110040
title: انحنای فضا از فیزیک کلاسیک تا سی آر وی دی

description: این سند یک ارائٔه کامل و رسمی است که سیر تحول مفهوم انحنای فضا را از دیدگاههای فیزیک کلاسیک، مکانیک کوانتومی، نسبیت عام، و چارچوب نوین فضای پیوستٔه واکنشی  «سی آر وی دی» بررسی میکند. هدف این است که نشان دهیم چگونه فهم ما از هندسٔه فضا از یک پس زمینٔه ایستا به یک ساختار پویا و واکنشی تکامل یافته است
DOI: 10.5281/zenodo.18110041
title: انحنای فضا از فیزیک کلاسیک تا سی آر وی دی

description: این سند یک ارائٔه کامل و رسمی است که سیر تحول مفهوم انحنای فضا را از دیدگاههای فیزیک کلاسیک، مکانیک کوانتومی، نسبیت عام، و چارچوب نوین فضای پیوستٔه واکنشی  «سی آر وی دی» بررسی میکند. هدف این است که نشان دهیم چگونه فهم ما از هندسٔه فضا از یک پس زمینٔه ایستا به یک ساختار پویا و واکنشی تکامل یافته است
DOI: 10.5517/ccdc.csd.cc2q0cmr
title: CCDC 2502804: Experimental Crystal Structure Determination

description: Related Article: P.A. Buikin, A.A. Korlyukov, P.V. Dorovatovskii, A.V. Vologzhanina|2026|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|82|1|doi:10.1107/S2053229625010216
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.