cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.25008653.v3
title: The Python Software Quality Dataset

description: This content represents the dataset of the article "The Python Software Quality Dataset". Included is the database dump, instructions on how to restore it and CSV files of the most important dataset tables: Repository, Sonarqube Issues, Sonarqube Metrics, Sonarqube Analyses, Refactoring Records, SZZ Issues data, Github Issues and Github Pull Requests data.
DOI: 10.6084/m9.figshare.24260620.v3
title: <b>A mudança sazonal da cor da pelagem como modelo de estudo em evolução [</b><b>Seasonal coat colour change as a model to study evolution]</b>

description: [ENG below]Os documentos neste repositório são referentes ao artigo:Miranda et al (2024). <i>A mudança sazonal da cor da pelagem como modelo de estudo da Evolução em contexto escolar.</i> <b>Revista de Ciência Elementar</b>, v12(04):42. DOI:10.24927/rce2024.042Os ficheiros incluídos acompanham as diferentes secções da publicação original, incluindo:Instruções para a realização da atividade prática;Instruções para a implementação de sessões com vista à replicação do projeto;Exemplos das produções dos estudantes participantes.-------------------English version:The documents in this repository are related to the paper:Miranda et al (2024). <i>A mudança sazonal da cor da pelagem como modelo de estudo da Evolução em contexto escolar.</i> <i>[Seasonal coat colour change as a model to study Evolution in a school context].</i> <b>Revista de Ciência Elementar</b>, v12(04):42. DOI:10.24927/rce2024.042Files refer to the implementation of a scientific research project with a cohort of high school students, developed in the context of Biology classes, including:A practical activity to introduce the study system;Information on how to replicate the project;Examples of materials produced by the students.All documents are written in Portuguese, following the original language of the work.
DOI: 10.6084/m9.figshare.25633674.v1
title: Supplementary information

description: Raw data for all supplementary figures in 'Single-cell analysis of VACV infection reveals pathogen-driven timing of early and late phases and host-limited dynamics of virus production'.
DOI: 10.6084/m9.figshare.6098852.v1
title: Supplementary Material for: Identifying Risk Factors Shared by Bronchopulmonary Dysplasia, Severe Retinopathy, and Cystic Periventricular Leukomalacia in Very Preterm Infants for Targeted Intervention

description: <b><i>Background:</i></b> Bronchopulmonary dysplasia (BPD), severe retinopathy of prematurity (sROP), and cystic periventricular leukomalacia (cPVL) are 3 major morbidities with long-term neurodevelopmental impairments in preterm infants. <b><i>Objective:</i></b> To investigate the strength of associations and identify key risk factors shared by BPD, sROP, and cPVL for targeted intervention. <b><i>Methods:</i></b> We studied the Taiwanese very-preterm-infant registry data on 3,507 infants admitted to neonatal intensive care units and discharged at postmenstrual age ≥36 weeks between 2008 and 2013. <b><i>Results:</i></b> Of 3,507 infants, 1,497 presented with at least 1 morbidity (26 [1.7%], 386 [25.8%], and 1,085 [72.5%] exhibited 3, 2, and 1 morbidities, respectively). BPD was strongly associated with sROP (odds ratio 5.93; 95% confidence interval 5.02–7.03), followed by cPVL (2.08; 1.63–2.64), but sROP and cPVL were weakly associated (1.59; 1.17–2.13). Most risk factors contributed to BPD, which shared risk factors with sROP and cPVL. A birth weight of &lt; 1,000 g, male sex, and prolonged mechanical ventilation (MV) were shared by BPD and sROP, and chorioamnionitis, severe respiratory distress syndrome, and prolonged MV specifically contributed to BPD and cPVL. Prolonged MV was the single risk factor common to BPD, sROP, and cPVL. Avoiding prolonged MV reduced the risk of having at least 1 of the 3 morbidities by 37%. <b><i>Conclusions:</i></b> BPD and sROP were most strongly associated. Most risk factors contributed to BPD, with differentially shared effects on sROP and cPVL. Prolonged MV was the only risk factor shared by all 3 morbidities, and avoiding it potentially reduced the risk of having at least 1 of them.
DOI: 10.6084/m9.figshare.19153349.v1
title: Raw Data_RS, SORS, morphology

description: - The single Raman spectra of air-dried SM (N=27) collected using two different excitation wavelengths – 785 and 488 nm,<br>- The average SORS spectra,<br>- The morphology data before and after blood tranfusion<br>
DOI: 10.6084/m9.figshare.5766864.v1
title: plot area

description: plot area
DOI: 10.5281/zenodo.15312145
title: Auxiliary code and data associated to  "A statistical-physics approach for codon usage optimisation."

description: This entry contains the code for genome preprocessing and filtering, as well as the resulting datasets, that are used to learn a statistical-physics model for codon design, as explained in the article "A statistical-physics approach for codon usage optimisation". See the readme.txt file for more details on the data, and the associated paper for the codon optimisation approach.
DOI: 10.5281/zenodo.15312146
title: Auxiliary code and data associated to  "A statistical-physics approach for codon usage optimisation."

description: This entry contains the code for genome preprocessing and filtering, as well as the resulting datasets, that are used to learn a statistical-physics model for codon design, as explained in the article "A statistical-physics approach for codon usage optimisation". See the readme.txt file for more details on the data, and the associated paper for the codon optimisation approach.
DOI: 10.15468/dl.qmp2m7
title: Occurrence Download

description: A dataset containing 1896 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Observation, Human Observation, Machine Observation, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Melanotus villosus (Geoffroy, 1785)"
 ]
}

 The dataset includes 1896 records from 66 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009689-250426092105405/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.3512063.v1
title: Appendix A. Descriptions of soil water flux methods.

description: Descriptions of soil water flux methods.
DOI: 10.6084/m9.figshare.26603914.v1
title: Suppl Table 1 AF information.xlsx

description: The interplay between genetic and environmental factors during pregnancy can predispose to inflammatory diseases postnatally, including eosinophilic esophagitis, a chronic allergic disease triggered by food. Herein, we examined the effects of amniotic fluid (AF) on esophageal epithelial differentiation and responsiveness to pro-allergic stimuli. Multiplex analysis of AF revealed the expression of 66 cytokines, whereas 5 cytokines including IL-4 and TSLP were not detected. Several pro-inflammatory cytokines including TNFa and IL-12 were highly expressed in the AF from women who underwent preterm birth, while EGF was the highest in term birth samples. Exposure of esophageal epithelial cells to AF resulted in transient phosphorylation of ERK1/2 and the transcription of early response genes, highlighting the direct impact of AF on esophageal epithelial cells. In a 3-dimensional spheroid model, AF modified the esophageal epithelial differentiation program and enhanced the transcription of IL-13-target genes, including <i>CCL26</i> and <i>CAPN14, </i>which encodes for a major genetic susceptibility locus for eosinophilic esophagitis. Notably,<i> CAPN14</i> exhibited upregulation in spheroids exposed to preterm but not term AF following differentiation. Collectively, our findings call attention to the role of AF as a potential mediator of the intrauterine environment that influences subsequent esophageal disorders.
DOI: 10.6084/m9.figshare.22187113.v1
title: Supplementary tables

description: Tables S1-S18, except S10.
DOI: 10.6084/m9.figshare.21441501.v2
title: Three Gorges Dam operations affect the carbon dioxide sink

description: The research data in paper of Three Gorges Dam enhances the carbon dioxide sink of downstream large lake
DOI: 10.6084/m9.figshare.25858969.v1
title: Data supporting Pallarés et al. (Genomic, morphological and physiological data support fast ecotypic differentiation and incipient speciation in an alpine diving beetle)

description: The dataset contains all the input files used to perform the analyses described in the paper
DOI: 10.6084/m9.figshare.22548544.v1
title: Supplementary Material for: Construction of Prognostic Nomogram in Patients with N3-stage Nasopharyngeal Carcinoma

description: Introduction: To retrospectively identify the metastatic influence factors and predict the prognosis, and develop an individualized prognostic prediction model for patients with N3-stage nasopharyngeal carcinoma (NPC). Methods: The study collected 446 NPC patients with N3-stage from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. The patients were classified into subgroups based on the histological types and metastatic status. Multivariable logistic, Cox regression, and Kaplan-Meier (K-M) method with the log-rank test were performed. The nomogram model was created using the prognostic factors identified from Cox regression analysis. The predictive accuracy was determined based on the concordance index (c-index) and calibration curves. Results: The five-year overall survival (OS) of the NPC patients with N3-stage was 43.9%, and the prognosis of patients without any distant metastases was largely longer than that with metastases. No difference was observed between different pathological types in the entire cohort. However, patients with non-keratinized squamous cell carcinoma (NKSCC) had a better OS than that of the patients with keratinized squamous cell carcinoma (KSCC) in a nonmetastatic subgroup. Using the Cox regression analysis results, the nomogram successfully classified these patients into low- and high-risk subgroups and presented the survival difference. The c-index of the nomogram for predicting the prognosis was satisfactory. Discussion/Conclusion: This study identified metastatic risk factors and developed a convenient clinical tool for the prognosis of NPC patients. This tool can be used for individualized risk classification and decision-making regarding treatment of NPC patients with N3-stage.
DOI: 10.6084/m9.figshare.12470057.v1
title: Dataset for Deng's 2020 JGR paper

description: Dataset 1. All repeating earthquakes (CC≥0.9) found in this study (Format: Date, Time, Latitude, Longitude, Depth, Magnitude, Type, ID, Cluster_name, Nbranch). Dataset 2. The events before and after relocation at region 1. (Format: yr, mon, day, hr, min, sec, eID, latR, lonR, depR, mag, qID, cID, nbranch, qnpair, qndiffP, qndiffS, rmsP, rmsS, eh, ez, et, latC, lonC, depC) Dataset 3. The events before and after relocation at region 3. (Format: yr, mon, day, hr, min, sec, eID, latR, lonR, depR, mag, qID, cID, nbranch, qnpair, qndiffP, qndiffS, rmsP, rmsS, eh, ez, et, latC, lonC, depC)Dataset 4. Repeating earthquakes with CC≥0.95 found in this study (Format: Date, Time, Latitude, Longitude, Depth, Magnitude, Type, ID, Cluster_name, Nbranch).
DOI: 10.6084/m9.figshare.14260649.v1
title: Supplementary Material for: Physiological and Cognitive Determinants of Dual-Task Costs for Gait Parameters: The Yishun Study

description: <b><i>Background:</i></b> Studies indicate that physiological and cognitive aging are causally related and functionally interdependent. However, the relative contribution of physiological factors and cognition to dual-task costs (DTC) of gait parameters has not been well studied. In this cross-sectional study, we examined the trajectory of DTC of gait parameters across the adult age spectrum for both sexes and identified the contributions of physical and cognitive performance to DTC of gait. <b><i>Methods:</i></b> A total of 492 community-dwelling adults, aged 21–90 years, were randomly recruited into the study. Participants were divided into 7 age groups, with 10-year age range for each group. Demographic data, height, body mass, education level, and information on comorbidities were recorded. Cognition was measured using the Repeatable Battery for the Assessment of Neuropsychological Status. Physical performance included visual contrast sensitivity, postural sway, hand reaction time, handgrip strength, knee extensor strength, and single-task and dual-task gait assessments. Stepwise multivariable regression was used to examine the association between physical and cognitive performance with DTC of gait parameters. <b><i>Results:</i></b> Women were found to have significantly higher DTC of gait speed (<i>p</i> = 0.01), cadence (<i>p</i> &lt; 0.01), and double support time (<i>p</i> &lt; 0.01) than men. However, significant aging effect on DTC of gait speed (<i>p</i> = 0.01), step length (<i>p</i> = 0.01), and double support time (<i>p</i> = 0.01) was observed in men but not in women. Immediate memory was the primary determinant for the DTC of gait speed (β = −0.25, <i>p</i> &lt; 0.01), step length (β = −0.22<i>, p</i> &lt; 0.01), and cadence (β = −0.15<i>, p</i> = 0.03) in men. Besides immediate memory, postural sway (β = −0.13, <i>p</i> = 0.03) and hand reaction (β = 0.14, <i>p =</i> 0.02) were also significantly associated with DTC of step length and cadence, respectively, in women. <b><i>Conclusion:</i></b> There were sex differences in the amplitude and trajectories of DTC of gait parameters. The DTC increased with age in men but not in women. Immediate memory was the primary determinant of DTC of gait parameters in men while immediate memory, postural sway, and reaction time were associated with DTC of gait in women. Future studies should investigate the clinical implications of the sex differences in the DTC with fall risks.
DOI: 10.15468/dl.bax2z4
title: Occurrence Download

description: A dataset containing 968 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Observation, Human Observation, Machine Observation, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Pollenia amentaria (Scopoli, 1763)"
 ]
}

 The dataset includes 968 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009690-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a42txa
title: Occurrence Download

description: A dataset containing 4718 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Observation, Human Observation, Machine Observation, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Pheosia tremula (Clerck, 1759)"
 ]
}

 The dataset includes 4718 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009691-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15281287
title: Behavioural Data of Affect Labeling

description: Explanation of Data Files

With

IMPACT OF AFFECT LABELING AS AN IMPLICIT EMOTION REGULATION STRATEGY ON NEGATIVE AND POSITIVE EMOTIONS

Authors: Jinyu Chen, Irene van de Vijver, J. Leon Kenemans, Johanna M.P. Baas

Author affiliation: Experimental Psychology and Helmholtz Institute, Utrecht University

Materials

The selected pictures were divided into nine subsets, which were combinations of three possible Intervention levels (label, match, new) and three Valence levels (negative, neutral, positive). Six subsets were used during the first intervention phase of the task: label negative, label neutral, label positive, match negative, match neutral, match positive. Another three subsets (new negative, new neutral, new positive) were combined with the previous six subsets used during the second test phase of the identification task. 



The folder titled ‘Open_Data_Affect_Labeling_RTs’ contains an Excel file named ‘stimuli_picture’, which provides comprehensive information about the images used in the study. This file includes each image’s filename, transformed normative ratings (1-9 Likert scale) for arousal and valence, and Picture Valence (negative, neutral, positive). Additionally, the file indicates how each image was pseudorandomly assigned to specific experimental blocks and Intervention (label, match, new).


DATA

The Intervention Phase: The Label-and-Match Task



The folder titled ‘Open_Data_Affect_Labeling_RTs’ contains two Excel files, ‘intervention_ADS_RTs’ and ‘intervention_spider_fear_RTs’, which provide the mean response time, standard deviation, and total hit count for each participant. The columns include the following variables: Subject, Condition_Valence, mean response time, sd, hit-count, and Group. The Condition_Valence column specifies the combination of Intervention (label, match) and Valence (negative, neutral, positive), and the catch condition.


The Test Phase: The Identification Task



The folder titled ‘Open_Data_Affect_Labeling_RTs’ contains two Excel files, ‘test_ads’ and ‘test_spider_fear’, which include trial-level data from the test phase. These files record each trial's response time and response button, with missed trials already excluded. Each dataset includes the following columns: Subject, Condition_Valence, Marker, response button, Response Time, and Group. The Condition_Valence column identifies the condition for each trial, specifying the type of Intervention (label, match, new) and Valence (negative, neutral, positive). Trial accuracy can be determined using the values in the Marker column and the corresponding response button, following this logic:


If,

Marker = c(111:116, 211:216, 311:316), 

then response button  = 1

else if,

Marker = c(121:126, 221:226, 321:326), 

then response button  = 2

end
DOI: 10.5281/zenodo.15281288
title: Behavioural Data of Affect Labeling

description: Explanation of Data Files

With

IMPACT OF AFFECT LABELING AS AN IMPLICIT EMOTION REGULATION STRATEGY ON NEGATIVE AND POSITIVE EMOTIONS

Authors: Jinyu Chen, Irene van de Vijver, J. Leon Kenemans, Johanna M.P. Baas

Author affiliation: Experimental Psychology and Helmholtz Institute, Utrecht University

Materials

The selected pictures were divided into nine subsets, which were combinations of three possible Intervention levels (label, match, new) and three Valence levels (negative, neutral, positive). Six subsets were used during the first intervention phase of the task: label negative, label neutral, label positive, match negative, match neutral, match positive. Another three subsets (new negative, new neutral, new positive) were combined with the previous six subsets used during the second test phase of the identification task. 



The folder titled ‘Open_Data_Affect_Labeling_RTs’ contains an Excel file named ‘stimuli_picture’, which provides comprehensive information about the images used in the study. This file includes each image’s filename, transformed normative ratings (1-9 Likert scale) for arousal and valence, and Picture Valence (negative, neutral, positive). Additionally, the file indicates how each image was pseudorandomly assigned to specific experimental blocks and Intervention (label, match, new).


DATA

The Intervention Phase: The Label-and-Match Task



The folder titled ‘Open_Data_Affect_Labeling_RTs’ contains two Excel files, ‘intervention_ADS_RTs’ and ‘intervention_spider_fear_RTs’, which provide the mean response time, standard deviation, and total hit count for each participant. The columns include the following variables: Subject, Condition_Valence, mean response time, sd, hit-count, and Group. The Condition_Valence column specifies the combination of Intervention (label, match) and Valence (negative, neutral, positive), and the catch condition.


The Test Phase: The Identification Task



The folder titled ‘Open_Data_Affect_Labeling_RTs’ contains two Excel files, ‘test_ads’ and ‘test_spider_fear’, which include trial-level data from the test phase. These files record each trial's response time and response button, with missed trials already excluded. Each dataset includes the following columns: Subject, Condition_Valence, Marker, response button, Response Time, and Group. The Condition_Valence column identifies the condition for each trial, specifying the type of Intervention (label, match, new) and Valence (negative, neutral, positive). Trial accuracy can be determined using the values in the Marker column and the corresponding response button, following this logic:


If,

Marker = c(111:116, 211:216, 311:316), 

then response button  = 1

else if,

Marker = c(121:126, 221:226, 321:326), 

then response button  = 2

end
DOI: 10.15468/dl.uju76s
title: Occurrence Download

description: A dataset containing 49069 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "OccurrenceStatus is Present",
 "TaxonKey is Testudines",
 "Year 1995-2025"
 ]
}

 The dataset includes 49069 records from 181 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009693-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d9a7xh
title: Occurrence Download

description: A dataset containing 4404 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "OccurrenceStatus is Present",
 "TaxonKey is Crocodylia",
 "Year 1995-2025"
 ]
}

 The dataset includes 4404 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009694-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.339hrv
title: Occurrence Download

description: A dataset containing 3411 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Observation, Human Observation, Machine Observation, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Rhagonycha fulva (Scopoli, 1763)"
 ]
}

 The dataset includes 3411 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009695-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.thg6p2
title: Occurrence Download

description: A dataset containing 534945 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Abies amabilis Douglas ex J.Forbes, Abies grandis (Douglas ex D.Don) Lindl., Abies lasiocarpa (Hook.) Nutt., Abies procera Rehd., Acer macrophyllum Pursh, Alnus rubra Bong., Callitropsis nootkatensis (D.Don) D.P.Little, Picea engelmannii Parry ex Engelm., Picea sitchensis (Bong.) Carrière, Pinus albicaulis Engelm., Pinus contorta Douglas ex Loudon, Pinus monticola Douglas ex D.Don, Pinus ponderosa Douglas ex C.Lawson, Populus balsamifera L., Pseudotsuga menziesii (Mirb.) Franco, Taxus brevifolia Nutt., Thuja plicata Donn ex D.Don, Tsuga heterophylla (Raf.) Sarg., Tsuga mertensiana (Bong.) Carrière)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 534945 records from 1279 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009677-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.