cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14779344
title: Dataset: Differences between Neurodivergent and Neurotypical Software Engineers: Analyzing the 2022 Stack Overflow Survey

description: # Analysis and Figure Generation Scripts for the Paper "Differences between Neurodivergent and Neurotypical Software Engineers: Analyzing the 2022 Stack Overflow Survey"

This repository contains the necessary R scripts and session data to re-run all tests reported in the paper, as well as generate the figures we use (and a few others we did not use).

## Files- SO_analysis_EASE25.R: The main R script executing all other parts. Running this script will calculate and the p-values of all tests, sorted by condition (lines 10 to 602). These are the same as reported in the paper in Tables 1 to 7. Additionally, figures will be generated (lines 603 onwards).- SO_data_filtered_sampled.RData: A RData file containing the filtered and sampled data and functions necessary to run the tests/generate the figures.- 01_SO_preprocessing.R and 02_SO_random_sampling.R: Scripts containing filtering logic and sampling logic. If those files are executed within SO_analysis_EASE25.R instead of loading the RData file (lines 5 to 8), the filtering and sampling is re-run. Note that this results in different random samples, and therefore different results than our paper. Also, the effect size calculations then have to be adjusted to the results that are significant (lines 596 to 601).- generatedGraphs.zip: The graph files generated by the main R script.- paperFigures.zip: The graphs we used in the paper. These are the generated graphs, but edited for readability.

## LicenseThe Public 2022 Stack Overflow Developer Survey Results is made available under the Open Database License (ODbL): http://opendatacommons.org/licenses/odbl/1.0/. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/).We hereby would like to attribute Stack Overflow as the source of these results. All data we make available (i.e., the RData file) is a derivative work, and as such also shared under the under the ODbl.
DOI: 10.15468/dl.2b2k3a
title: Occurrence Download

description: A dataset containing 1924 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cyperus microiria Steud., Cyperus iria var. rectangularis Kük., Cyperus textorii Miq., Cyperus parviflorus Nees, Cyperus iria var. parviflorus Miq., Cyperus rectangularis (Kük.) Bennet, Cyperus amuricus var. textorii (Miq.) Kük.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 1924 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006221-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/45rm23ywx2
title: Data for: Energy efficiency, information, and the acceptability of rent increases: A multiple price list experiment with tenants

description: This dataset includes the data file (Stata format, .dta), the corresponding command file (Stata format, .do), and the questionnaire (.pdf), related to our article.
DOI: 10.5518/597
title: PATHWAY-27 Pilot study data

description: * NOTE: this record comprises the variable documents only. Access to the data files is restricted. Follow the first link in Related resources below to request access * PATHWAY-27 Pilot study data containing (at recruitment ; day 1 ; day 28): - serum triglycerides - High-density lipoprotein cholesterol - blood pressure - body height and weight, BMI - abdominal circumference - blood glucose (PATHWAY-27 is a multi-centre, randomized, double blind, parallel pilot dietary intervention study to identify the bioactive-enriched foods achieving the greatest effect on lipid parameters).
DOI: 10.5281/zenodo.7957870
title: Fechas de peritaje de cultivos herbáceos de secano en España 2012-2021

description: Datos de fechas (semana del año) de tasación de parcelas (suma de parcelas y suma de superficies) de cultivos trigo o cebada, entre 2012 y 2021, por comarcas agrarias de España. La procedencia de los datos es la compañía Agroseguro.
description: Estos datos hay que usarlos con cautela: Lo primero a tener en cuenta es que no se registran fechas de recolección reales, sino la que indican los agricultores según expectativas. Este dato no se somete a un control de calidad exhaustivo y hay casos en los que no se registra. Además, al ser datos del seguro e información sacada de tasación, sólo se trata a las parcelas aseguradas que estén siniestradas, que tengan información relativa a esa fecha y que sea una fecha coherente (se han quitado los registros con fechas en años que no estén entre la serie de años indicada y semanas de meses fuera de época de recolección). Por lo que los valores absolutos no son comparables entre diferentes campañas por su diferente siniestralidad y por la arbitrariedad de la toma del dato. De hacer ese uso directo de la superficie o del número de parcelas, la información va a estar sesgada. Una última anotación: las semanas se han calculado teniendo en cuenta que la semana empieza en lunes y la semana 1 es la 1ª semana que tenga 4 días en el año nuevo.
DOI: 10.5281/zenodo.7957871
title: Fechas de peritaje de cultivos herbáceos de secano en España 2012-2021

description: Datos de fechas (semana del año) de tasación de parcelas (suma de parcelas y suma de superficies) de cultivos trigo o cebada, entre 2012 y 2021, por comarcas agrarias de España. La procedencia de los datos es la compañía Agroseguro.
description: Estos datos hay que usarlos con cautela: Lo primero a tener en cuenta es que no se registran fechas de recolección reales, sino la que indican los agricultores según expectativas. Este dato no se somete a un control de calidad exhaustivo y hay casos en los que no se registra. Además, al ser datos del seguro e información sacada de tasación, sólo se trata a las parcelas aseguradas que estén siniestradas, que tengan información relativa a esa fecha y que sea una fecha coherente (se han quitado los registros con fechas en años que no estén entre la serie de años indicada y semanas de meses fuera de época de recolección). Por lo que los valores absolutos no son comparables entre diferentes campañas por su diferente siniestralidad y por la arbitrariedad de la toma del dato. De hacer ese uso directo de la superficie o del número de parcelas, la información va a estar sesgada. Una última anotación: las semanas se han calculado teniendo en cuenta que la semana empieza en lunes y la semana 1 es la 1ª semana que tenga 4 días en el año nuevo.
DOI: 10.17632/x74t7fckb6
title: Gearbox run-to-failure dataset (gear wear: abrasive wear and surface pitting)

description: This run-to-failure test (with and without lubrication) was conducted on the spur gearbox test rig at the University of New South Wales. The vibration signals were acquired regularly, at a 100 kHz sampling frequency and for a duration of 10 seconds. More descriptions can be found in 'Read me for data description'. When using this dataset, please give proper citations to our journal papers, which can be found using the related links.
DOI: 10.15468/dl.33t7ym
title: Occurrence Download

description: A dataset containing 51 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((13.45184 40.79229,13.44926 40.79301,13.45048 40.78714,13.4595 40.78693,13.46028 40.79208,13.45184 40.79229))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 51 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006224-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n2gqqh
title: Occurrence Download

description: A dataset containing 34485 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Occurrence evidence, Living Specimen, Machine Observation, Human Observation, Material citation, Material sample)",
 "Continent is North America",
 "OccurrenceStatus is Present",
 "TaxonKey is Zea mays L."
 ]
}

 The dataset includes 34485 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006223-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.trra9q
title: Occurrence Download

description: A dataset containing 6853 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cyperus odoratus L., Cyperus acicularis Schrad. ex Nees, Cyperus acicularis Schrad., Cyperus poeoides Desv. ex Ham., Torulinium confertum Desv. ex Ham., Cyperus ferax var. bulbiferus Barros, Diclidium odoratum (L.) Schrad., Cyperus jubiflorus Rudge, Cyperus squarrosus var. parvus Britton, Cyperus lomentaceus Nees & Meyen, Cyperus fastuosus Desv. ex Ham., Cyperus consocius Steud., Torulinium odoratum (L.) S.S.Hooper, Diclidium odoratum (L.) Schrad. ex Nees, Papyrus odorata (L.) Willd., Papyrus odorata (L.) Kunth)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 6853 records from 356 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006225-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.5798629
title: Quantitative GeoLInk-Rohdaten - Designzyklus 2

description: Quantitative Rohdaten (Designzyklus 2, SPSS) aus dem Projekt "Qualifizierung von Geographie-Lehrpersonen für Inklusive Bildung. Entwicklung und Evaluation von Aus- und Fortbildungsangeboten für inklusiven Geographieunterricht im Design-Based-Research" (GeoLInk).


Das Vorhaben wurde aus Mitteln des Bundesministeriums für Bildung und Forschung unter dem Förderkennzeichen 01NV1726 gefördert. Die Verantwortung für den Inhalt dieser Veröffentlichung liegt bei den Autor*innen.
DOI: 10.5281/zenodo.5798630
title: Quantitative GeoLInk-Rohdaten - Designzyklus 2

description: Quantitative Rohdaten (Designzyklus 2, SPSS) aus dem Projekt "Qualifizierung von Geographie-Lehrpersonen für Inklusive Bildung. Entwicklung und Evaluation von Aus- und Fortbildungsangeboten für inklusiven Geographieunterricht im Design-Based-Research" (GeoLInk).


Das Vorhaben wurde aus Mitteln des Bundesministeriums für Bildung und Forschung unter dem Förderkennzeichen 01NV1726 gefördert. Die Verantwortung für den Inhalt dieser Veröffentlichung liegt bei den Autor*innen.
DOI: 10.17632/b3jbzgnrwv.1
title: Exploring the Influence of Artificial Intelligence in Higher Education

description: This survey seeks to understand how artificial intelligence (AI) technology impacts education
DOI: 10.17632/8r8r5vvc3p.1
title: Single-cell morphological tracking of cell states to identify small-molecule modulators of liver differentiation. Graham et al.

description: Dataset published by Graham et al. 2024 which contains HepaRG Cell Painting features. 

Cell Painting screen using the liver progenitor cell line HepaRG which undergoes bilineage differentiation to produce hepatocyte-like and biliary-like cells. We performed a chemical screen to find small-molecules that promoted differentiation of the cells using the Cell Painting morphological features. The screen was performed using the median image level data (agg_screen_data). We then leveraged the single cell data to determine whether the hit compounds affected the proportions of hepatocyte-like and cholangiocyte-like cells. To do this we images the cells over the course of 4 weeks while they differentiated to generate a morphological atlas of HepaRG differentiation and then we overlaid the single cell drug treated cells. We used trajectory inference to quantify any changes. We found that SRK family kinase inhibitors led to an almost pure cell population of hepatocyte-like cells. 

File Description
Aggregated_screen_data_fig1_fig2 contains:
Primary_screen_aggregated_data.csv : primary screen image median aggregated data.
Val_01_agg_formatted.csv : validation dose response (rep 1) image median aggregated data.
Val_02_agg_formatted.csv : validation dose response (rep 2) image median aggregated data.
Val_03_agg_formatted.csv : validation dose response (rep 3) image median aggregated data.


Sc_raw_subsampled_timecourse_data.csv : raw single cell downsampled timecourse data of HepaRG differentiation
Sc_raw_subsampled_dose_response_data.csv : raw single cell downsampled dose response validation data 
Sc_cleaned_raw_features_timecourse_and_dose_responses_combined.csv : final cleaned dataset used in paper. Biological thresholds applied, doublets removed, and remaining extreme outlier cluster removed. Raw feature values (pre- standardisation). 

liver_pseudotime_cp_eddie.cppipe contains the CellProfiler pipeline used to generate the morphological features at the single cell level.
DOI: 10.17632/5vb27x4fxk.1
title: Datasets and R code for Bottini et al. (2022) Effects of methylmercury and food stress on migratory restlessness in song sparrows, Melospiza melodia

description: This folder contains all the datasets and R code needed to reproduce the analysis of manuscript from Bottini et al. 2022 “Effects of methylmercury and food stress on migratory activity in song sparrows, Melospiza melodia”, submitted in Hormones and Behavior journal.
DOI: 10.17632/5vb27x4fxk.2
title: Datasets and R code for Bottini et al. (2022) Effects of methylmercury and food stress on migratory restlessness in song sparrows, Melospiza melodia

description: This folder contains all the datasets and R code needed to reproduce the analysis of manuscript from Bottini et al. 2022 “Effects of methylmercury and food stress on migratory activity in song sparrows, Melospiza melodia”, published in Hormones and Behavior journal.
Link to the article is provided below.
Article's Highlights: 
    •    Exposure to contaminants and/or stressors can hinder songbirds' migration.
    •    Carry-over effects of MeHg exposure and food stress on song sparrows were assessed.
    •    Nocturnal activity increased in MeHg-exposed birds and varied with food stress.
    •    Treatments and time affected corticosterone and body mass, but not thyroxine.
    •    Fecal corticosterone was positively correlated with nocturnal activity.
DOI: 10.17632/5vb27x4fxk.3
title: Datasets and R code for Bottini et al. (2022) Effects of methylmercury and food stress on migratory activity in song sparrows, Melospiza melodia

description: This folder contains all the datasets and R code needed to reproduce the analysis of manuscript from Bottini et al. 2022 “Effects of methylmercury and food stress on migratory activity in song sparrows, Melospiza melodia”, published in Hormones and Behavior journal.
Link to the article is provided below.
Article's Highlights: 
 • Exposure to contaminants and/or stressors can hinder songbirds' migration.
 • Carry-over effects of MeHg exposure and food stress on song sparrows were assessed.
 • Nocturnal activity increased in MeHg-exposed birds and varied with food stress.
 • Treatments and time affected corticosterone and body mass, but not thyroxine.
 • Fecal corticosterone was positively correlated with nocturnal activity.
DOI: 10.15468/dl.b3jg9h
title: Occurrence Download

description: A dataset containing 36515 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Taxon occurrence data for the FungalRoot database"
 ]
}

 The dataset includes 36515 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006227-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28228148.v1
title: Structures of phage-related introns predicted using LinearTurboFold

description: Files used to create SVG illustrations shown in Supplementary figure S2 of the paper:1. LinearTurboFold alignments/structures2. GFF annotation files used to color structure (results of annotate_introns.py)<br>Annotation tsv files were created using:./reannotate_introns.py -f GIISSD_and_Bastille.unique_099.fasta -o Annotated_GIISSD_and_Bastille_introns(scripts used in the study are available from https://github.com/zwmuam/Bastilevirinae_introns)<br>The tsv files were used to color each structure in R2DT Docker container:r2dt.py templatefree ${intron_structure}.fasta ${intron_structure}python3 enrich_json.py --input-json ${intron_structure}.json --input-data ${intron_structure}.annot --output ${intron_structure}.enriched.jsonjson2svg.py -p colour_dict.json -i ${intron_structure}.enriched.json -o ${intron_structure}.enriched.svg
DOI: 10.6084/m9.figshare.28228148
title: Structures of phage-related introns predicted using LinearTurboFold

description: Files used to create SVG illustrations shown in Supplementary figure S2 of the paper:1. LinearTurboFold alignments/structures2. GFF annotation files used to color structure (results of annotate_introns.py)<br>Annotation tsv files were created using:./reannotate_introns.py -f GIISSD_and_Bastille.unique_099.fasta -o Annotated_GIISSD_and_Bastille_introns(scripts used in the study are available from https://github.com/zwmuam/Bastilevirinae_introns)<br>The tsv files were used to color each structure in R2DT Docker container:r2dt.py templatefree ${intron_structure}.fasta ${intron_structure}python3 enrich_json.py --input-json ${intron_structure}.json --input-data ${intron_structure}.annot --output ${intron_structure}.enriched.jsonjson2svg.py -p colour_dict.json -i ${intron_structure}.enriched.json -o ${intron_structure}.enriched.svg
DOI: 10.17632/dkph9pxpny.1
title: Friendly or Powerful? Fatted male phenomenon of collin’s squirrel monkeys

description: In species where sexual selection operates, reproduction is heavily influenced by morphological and behavioral traits that ultimately affect their copulation rates and reproductive success. Two of the most conspicuous of those traits are the sexual size dimorphism, the permanent or temporary enlargement of males, as in the case of squirrel monkeys. In this research, we unveil some central aspects regarding the “fatted male phenomenon” of the Amazonian Collins’ squirrel monkey, Saimiri collinsi. Closely monitoring four captive social groups under controlled conditions, we used a combination of techniques, observing their reproductive behavior, their social dominance and their social network power for more than 15 consecutive months.
DOI: 10.17632/dkph9pxpny.2
title: Friendly or Powerful? Fatted male phenomenon of collin’s squirrel monkeys

description: In species where sexual selection operates, reproduction is heavily influenced by morphological and behavioral traits that ultimately affect their copulation rates and reproductive success. Two of the most conspicuous of those traits are the sexual size dimorphism, the permanent or temporary enlargement of males, as in the case of squirrel monkeys. In this research, we unveil some central aspects regarding the “fatted male phenomenon” of the Amazonian Collins’ squirrel monkey, Saimiri collinsi. Closely monitoring four captive social groups under controlled conditions, we used a combination of techniques, observing their reproductive behavior, their social dominance and their social network power for more than 15 consecutive months.
DOI: 10.17632/dkph9pxpny.3
title: Friendly or Powerful? Fatted male phenomenon of collin’s squirrel monkeys

description: In species where sexual selection operates, reproduction is heavily influenced by morphological and behavioral traits that ultimately affect their copulation rates and reproductive success. Two of the most conspicuous of those traits are the sexual size dimorphism, the permanent or temporary enlargement of males, as in the case of squirrel monkeys. In this research, we unveil some central aspects regarding the “fatted male phenomenon” of the Amazonian Collins’ squirrel monkey, Saimiri collinsi. Closely monitoring four captive social groups under controlled conditions, we used a combination of techniques, observing their reproductive behavior, their social dominance and their social network power for more than 15 consecutive months.
DOI: 10.17632/s6crm7fdc7.1
title: Dataset. Self-Defining memories

description: Dataset. Associations of self-defining memories characteristics and transdiagnostic variables with depressive symptoms in older adults
DOI: 10.15468/dl.z439ra
title: Occurrence Download

description: A dataset containing 3863781 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OrderKey is Odonata",
 "Country is one of (Norway, Guernsey, Poland, Denmark, Kosovo, Latvia, France, Slovakia, Romania, Bulgaria, Croatia, Iceland, Ireland, Malta, Åland Islands, North Macedonia, Andorra, Montenegro, Germany, Belarus, Czechia, United Kingdom of Great Britain and Northern Ireland, Switzerland, Belgium, Gibraltar, Portugal, Monaco, Ukraine, Finland, Bosnia and Herzegovina, Hungary, Estonia, Greece, Serbia, Netherlands, Moldova, Republic of, Cyprus, Isle of Man, Lithuania, Slovenia, Albania, Sweden, Liechtenstein, Austria, Italy, Luxembourg, Spain, Jersey)",
 "HasCoordinate is TRUE",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "BasisOfRecord is one of (Living Specimen, Observation, Human Observation, Machine Observation, Occurrence evidence)"
 ]
}

 The dataset includes 3863781 records from 1384 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006222-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16966464
title: Machine Learning Prediction of ¹H NMR Chemical Shifts in Zinc Complexes

description: Title: Machine learning prediction of ¹H NMR chemical shifts in zinc complexes — Dataset

Description:This dataset contains all data and notebooks used in the study “Machine learning prediction of ¹H NMR chemical shifts in zinc complexes.” It includes:





Raw DFT calculations for 45 zinc complexes, including geometry optimizations and solvent-specific NMR shielding calculations.




Experimental ¹H NMR data, including raw spectra, processed spectra, and peak assignments for validation.




Compiled XYZ files used for ML descriptor extraction (SOAP) and clustering.



The notebooks reproduce the full machine learning workflow from raw data:





H_Clustering.ipynb — performs clustering of zinc complexes using the merged XYZ structures.




HNMR_lgbm.ipynb — extracts SOAP descriptors from hydrogen atoms, trains LightGBM models to predict ¹H NMR chemical shifts, and validates predictions against experimental data.



Dependencies / Required Python modules:python, numpy, pandas, scikit-learn, lightgbm, dscribe, ase, matplotlib