cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.31429595.v1
title: Supplementary Material for: Varicella Zoster Virus Reactivation in the Cervix During Labor in a Vaccinated Pregnant Woman: A Novel Case Report

description: Introduction
Obstetric and pediatric providers are increasingly challenged by the evolving presentations of perinatal infections. While varicella zoster virus (VZV) reactivation during pregnancy is typically considered benign and poses a low risk for neonatal transmission, this assessment is based on dermatomal, non-genital presentations. Genital involvement, especially when isolated to the cervix, is rare and not addressed in the current guidelines. 
Case Presentation 
We present the case of a fully vaccinated, immunocompetent 22-year-old woman with cervical VZV infection at the time of delivery. She was suspected to have reactivation of the vaccine strain and was delivered via caesarean section. The infant remained asymptomatic and did not require therapy to prevent or treat the infection. 
Conclusion
This case underscores the diagnostic utility of multiplex viral testing and highlights a critical gap in the guidelines for managing genital VZV reactivation during pregnancy. Genital VZV, similar to herpes simplex virus, may warrant special consideration in delivery planning and neonatal care.
DOI: 10.13140/rg.2.2.25461.44000
title: DATA Beyond Verbal Counseling: Music-Integrated CBT for Reducing Academic Anxiety in Secondary Schools
DOI: 10.6084/m9.figshare.31429598
title: Supplementary Material for: Efficacy and Safety of No-Touch versus Conventional Saphenous Vein Harvesting in Coronary Artery Bypass Grafting: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

description: Introduction:
Saphenous vein graft (SVG) failure is a key determinant of long-term outcomes after coronary artery bypass grafting (CABG), particularly in individuals with multivessel disease or diabetes. This meta-analysis aimed to evaluate whether the no-touch SVG harvesting technique reduces graft occlusion and improves cardiovascular outcomes compared with the conventional approach. 
Methods:
A comprehensive literature search of PubMed, Embase, Web of Science, and the Cochrane Library was conducted up to May 2025 to identify randomized controlled trials (RCTs) comparing the no-touch and conventional saphenous vein harvesting techniques in CABG. A random-effects model was used for meta-analysis, and the certainty of evidence was evaluated using the GRADE framework. 
Results:
Eight RCTs involving 4,258 CABG patients (no-touch: 2,144; conventional: 2,114) were included. The no-touch technique significantly reduced the risk of vein graft occlusion (RR, 0.59; 95% CI: 0.47–0.73; P &lt; 0.00001; I² = 31%). Subgroup analyses confirmed the consistency of this effect across regions and follow-up durations. Although differences in secondary outcomes—including all-cause and cardiovascular mortality, myocardial infarction, stroke, and repeat revascularization—were not statistically significant, most effect estimates favored the no-touch approach. The certainty of evidence was rated as moderate for the primary and several secondary outcomes according to the GRADE assessment. 
Conclusion:
This meta-analysis shows that no-touch saphenous vein harvesting is associated with a lower risk of graft occlusion compared with conventional harvesting in CABG. However, current randomized evidence does not demonstrate a definitive improvement in major cardiovascular outcomes. These findings highlight the need to balance angiographic benefits against potential trade-offs and underscore the need for large-scale, event-driven randomized trials to clarify the net clinical benefit of this technique.
DOI: 10.6084/m9.figshare.31429598.v1
title: Supplementary Material for: Efficacy and Safety of No-Touch versus Conventional Saphenous Vein Harvesting in Coronary Artery Bypass Grafting: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

description: Introduction:
Saphenous vein graft (SVG) failure is a key determinant of long-term outcomes after coronary artery bypass grafting (CABG), particularly in individuals with multivessel disease or diabetes. This meta-analysis aimed to evaluate whether the no-touch SVG harvesting technique reduces graft occlusion and improves cardiovascular outcomes compared with the conventional approach. 
Methods:
A comprehensive literature search of PubMed, Embase, Web of Science, and the Cochrane Library was conducted up to May 2025 to identify randomized controlled trials (RCTs) comparing the no-touch and conventional saphenous vein harvesting techniques in CABG. A random-effects model was used for meta-analysis, and the certainty of evidence was evaluated using the GRADE framework. 
Results:
Eight RCTs involving 4,258 CABG patients (no-touch: 2,144; conventional: 2,114) were included. The no-touch technique significantly reduced the risk of vein graft occlusion (RR, 0.59; 95% CI: 0.47–0.73; P &lt; 0.00001; I² = 31%). Subgroup analyses confirmed the consistency of this effect across regions and follow-up durations. Although differences in secondary outcomes—including all-cause and cardiovascular mortality, myocardial infarction, stroke, and repeat revascularization—were not statistically significant, most effect estimates favored the no-touch approach. The certainty of evidence was rated as moderate for the primary and several secondary outcomes according to the GRADE assessment. 
Conclusion:
This meta-analysis shows that no-touch saphenous vein harvesting is associated with a lower risk of graft occlusion compared with conventional harvesting in CABG. However, current randomized evidence does not demonstrate a definitive improvement in major cardiovascular outcomes. These findings highlight the need to balance angiographic benefits against potential trade-offs and underscore the need for large-scale, event-driven randomized trials to clarify the net clinical benefit of this technique.
DOI: 10.15468/dl.9rn9aw
title: Occurrence Download

description: A dataset containing 0 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)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Lepidamia multitaeniata"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001610-260226173443078/datasets/export for details.
DOI: 10.15468/dl.4mpt9c
title: Occurrence Download

description: A dataset containing 1048 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Amaranthus tricolor, , , , , , , , , , , , , , , , , , , , , , , , , , , , Hishimonus phycitis, Glomeraria tricolor, , , , Amaranthus roxburghianus, , Amaranthus rotundifolius, , , , , , , , , , , , , , , , , , Amaranthus versicolor, , , , Glomeraria bicolor, , , , , , , , , , , , , , , , , , Amaranthus lividus, Amaranthus japonicus, Amaranthus melancholicus, , , , , , , , , , , , , , , , , Amaranthus japonicus, Amaranthus bicolor, Pyxidium melancholicum, Amaranthus lancifolius, Amaranthus mangostanus, Amaranthus gangeticus, , , Blitum gangeticum, , , , , , , , , , , , , , , , , , , , , , , , , , , Amaranthus lanceolatus, , Amaranthus tristis, Euxolus polygamus, Amaranthus salicifolius, Amaranthus inamoenus, , , Amaranthus cuspidatus, , , , , , , , , , , , , , , , , , Amaranthus tristis, , Amaranthus japonicus, Amaranthus oleraceus, Amaranthus polygamus, , , Amaranthus versicolor, , Amaranthus roxburgianus, Blitum melancholicum, , , , , , , , , , , , , , , , , , Amaranthus mucronatus, Amaranthus flexuosus, , Amaranthus bicolor, Glomeraria bicolor, , Amaranthus tenuifolius, , , , , , , , , , , , , , , , , , , Pyxidium gangeticum, , , Amaranthus polygamus, Amaranthus henderi, Amaranthus amboinicus, , , , , , , , , , , , , , , , , , , Amaranthus polygamus, Amaranthus mangostanus, Albersia polygama, , , , , , , , , , , , , , )",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1048 records from 124 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001611-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5pnn9t
title: Occurrence Download

description: A dataset containing 6019 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ctenopharyngodon idella, Ctenopharyngodon idellos, Ctenopharingodon idellus, Ctenopharygodon idella, Polyodon spathula, Coregonus oxyrinchus, Coregonus clupeaformis, Coregonus clupeiformis, Coregonus artedi, Coregonus actedii)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "CoordinateUncertaintyInMeters is less than 10000",
 "Year is greater than or equal to 1900",
 "BasisOfRecord is one of (Human Observation, Machine Observation)",
 "DistanceFromCentroidInMeters is greater than or equal to 1000"
 ]
}

 The dataset includes 6019 records from 84 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001612-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b2dfu9
title: Occurrence Download

description: A dataset containing 90 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Browningia hertlingiana"
 ]
}

 The dataset includes 90 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001613-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18709027
title: Supplementary data for: A revised phylogenetic circumscription of Entosthodon and Physcomitrellopsis (Bryophyta: Funariaceae)

description: Supplementary data [two files] for the study: "A revised phylogenetic circumscription of Entosthodon and Physcomitrellopsis (Bryophyta: Funariaceae)". 

File 1: Four chloroplast gene alignment. Gene order in alignment: atpB [1-770], psbA [771-1328], rps4 [1329-2012], trnL-F [2013-2619]. 

File 2: ML tree from the RAxML-NG analysis.
DOI: 10.5281/zenodo.18709028
title: Supplementary data for: A revised phylogenetic circumscription of Entosthodon and Physcomitrellopsis (Bryophyta: Funariaceae)

description: Supplementary data [two files] for the study: "A revised phylogenetic circumscription of Entosthodon and Physcomitrellopsis (Bryophyta: Funariaceae)". 

File 1: Four chloroplast gene alignment. Gene order in alignment: atpB [1-770], psbA [771-1328], rps4 [1329-2012], trnL-F [2013-2619]. 

File 2: ML tree from the RAxML-NG analysis.
DOI: 10.5281/zenodo.18348349
title: TEMA AIIA_flood Dataset

description: General description of the dataset

The dataset for the flood binary segmentation task comprises 720 images consolidated from two sources: Mantoudi and Arthal trials. Mantoudi contributes with 338 images (198 train set, 140 test set) and Arthal with 382 images (230 train set, 152 test set), resulting in an approximate 60% – 40% training-validation distribution. The annotation masks are binary, where pixels are labeled as 0 for background and 1 for floodwater. If one uses any part of these datasets in his/her work, he/she is kindly asked to cite the following papers.



 P. Mentesidis, V. Mygdalis and I.Pitas, "Improve Real-time flood segmentation by encoding and distilling foreground information", IEEE International Conference on Image Processing (ICIP), Anchorage, Alaska, USA, 13-17 September, 2025.

A. Gerontopoulos, D. Papaioannou, C. Papaioannidis and I.Pitas, "Real-Time Flood Water Segmentation with Deep Neural Networks", IEEE 25th International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW), Tromsø, Norway, pp. 85-91, 2025


Dataset Structure

It is structured into distinct directories for each source (Mantoudi and Arthal), each containing standard train and validation splits with separate folders for images (.jpg) and labels (.png).

 

Mora information about the dataset can be found here.
DOI: 10.5281/zenodo.18377521
title: TEMA AIIA_flood Dataset

description: General description of the dataset

The dataset for the flood binary segmentation task comprises 720 images consolidated from two sources: Mantoudi and Arthal trials. Mantoudi contributes with 338 images (198 train set, 140 test set) and Arthal with 382 images (230 train set, 152 test set), resulting in an approximate 60% – 40% training-validation distribution. The annotation masks are binary, where pixels are labeled as 0 for background and 1 for floodwater. If one uses any part of these datasets in his/her work, he/she is kindly asked to cite the following papers.



 P. Mentesidis, V. Mygdalis and I.Pitas, "Improve Real-time flood segmentation by encoding and distilling foreground information", IEEE International Conference on Image Processing (ICIP), Anchorage, Alaska, USA, 13-17 September, 2025.

A. Gerontopoulos, D. Papaioannou, C. Papaioannidis and I.Pitas, "Real-Time Flood Water Segmentation with Deep Neural Networks", IEEE 25th International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW), Tromsø, Norway, pp. 85-91, 2025


Dataset Structure

It is structured into distinct directories for each source (Mantoudi and Arthal), each containing standard train and validation splits with separate folders for images (.jpg) and labels (.png).

 

Mora information about the dataset can be found here.
DOI: 10.34804/supra.20210928145
title: Determination of the kinetics underlying the pKa shift for the 2-aminoanthracenium cation binding with cucurbit[7]uril

description: The binding dynamics of the 2-aminoanthracenium cation (AH+) and 2-aminoanthracene (A) with cucurbit[7]uril (CB[7]) was studied using stopped-flow experiments. The kinetics was followed by measuring the fluorescence changes over time for AH+ and A, which emit at different wavelengths. The studies at various pH values showed different mechanisms for the formation of the AH+@CB[7] complex, with this complex formed either by the binding of AH+ or by the initial binding of A followed by protonation. In the latter case, it was possible to determine the protonation ((1.5 ± 0.4) × 109 M−1 s−1) and deprotonation (89 ± 7 s−1) rate constants for complexed A/AH+, which showed that the pKa shift of +3.1 for A/AH+ in the complex is mainly due to a lower deprotonation rate constant.
DOI: 10.15468/dl.g7jfjz
title: Occurrence Download

description: A dataset containing 417 records in GBIF matching the query:

SELECT
 GBIF_ISEA3HCode(
 7, 
 decimalLatitude,
 decimalLongitude,
 COALESCE(coordinateUncertaintyInMeters, 1000)
 ) AS geogrid_id,
 CASE 
 WHEN classKey IN ('359') THEN 'Mammals'
 WHEN classKey IN ('212') THEN 'Birds'
 WHEN familyKey IN ('1103', '1104', '494', '495', '1105', '496', '497', '1106', '498', '499', '1107', '537', '538', '1153', '547', '1162', '548', '549', '550', '1163', '1164', '1165', '1166', '1167', '1305', '1067', '1306', '1307', '1308', '1068', '1069', '587', '1310', '588', '589', '1311', '1312', '1313', '590', '708', '890', '774', '889', '773', '772', '888', '765', '879') THEN 'Bony Fish'
 WHEN classKey IN ('131') THEN 'Amphibians'
 WHEN classKey IN ('216') THEN 'Insects'
 WHEN classKey IN ('11418114', '11569602', '11592253', '11493978') THEN 'Reptiles'
 WHEN phylumKey IN ('52') THEN 'Molluscs'
 WHEN classKey IN ('367') THEN 'Arachnids'
 WHEN classKey IN ('220', '196') THEN 'Flowering Plants'
 WHEN classKey IN ('194', '244', '228', '282') THEN 'Gymnosperms'
 WHEN orderKey IN ('392') THEN 'Ferns'
 WHEN phylumKey IN ('35') THEN 'Mosses'
 WHEN phylumKey IN ('95') THEN 'Sac Fungi'
 WHEN phylumKey IN ('34') THEN 'Basidiomycota'
 END AS taxonomic_group,
 COUNT(DISTINCT speciesKey) AS species_count
FROM occurrence
WHERE countryCode = 'DZ'
 AND hasCoordinate = TRUE
 AND hasGeospatialIssues = FALSE
 AND coordinateUncertaintyInMeters &lt;= 2000
 AND occurrenceStatus = 'PRESENT'
 AND speciesKey IS NOT NULL
 AND basisOfRecord != 'FOSSIL_SPECIMEN'
 AND taxonRank = 'SPECIES'
 AND (
 classKey IN ('359', '212', '131', '216', '11418114', '11569602', '11592253', '11493978', '367', '220', '196', '194', '244', '228', '282')
 OR familyKey IN ('1103', '1104', '494', '495', '1105', '496', '497', '1106', '498', '499', '1107', '537', '538', '1153', '547', '1162', '548', '549', '550', '1163', '1164', '1165', '1166', '1167', '1305', '1067', '1306', '1307', '1308', '1068', '1069', '587', '1310', '588', '589', '1311', '1312', '1313', '590', '708', '890', '774', '889', '773', '772', '888', '765', '879')
 OR phylumKey IN ('52', '35', '95', '34')
 OR orderKey IN ('392')
 )
GROUP BY geogrid_id, taxonomic_group;


 The dataset's 417 records were derived from 97 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001603-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18799006
title: PEDAGOGICAL CRITERIA FOR ENHANCING STUDENTS' LINGUISTIC COMPETENCE IN LANGUAGE EDUCATION

description: This article examines pedagogical criteria for enhancing students’ linguistic competence within the framework of modern language education. Linguistic competence is interpreted as an integrated system of grammatical, lexical, phonetic, stylistic, and pragmatic knowledge and skills. The study highlights methodological approaches to developing linguistic competence through theory-based instruction, pragmatic exercises, text analysis, and creative language activities. Particular attention is paid to the role of practical tasks, independent text creation, and reflective assessment in improving learners’ speech culture. The article provides methodological recommendations aimed at developing coherent, logical, and communicatively effective oral and written speech.
DOI: 10.5281/zenodo.18799007
title: PEDAGOGICAL CRITERIA FOR ENHANCING STUDENTS' LINGUISTIC COMPETENCE IN LANGUAGE EDUCATION

description: This article examines pedagogical criteria for enhancing students’ linguistic competence within the framework of modern language education. Linguistic competence is interpreted as an integrated system of grammatical, lexical, phonetic, stylistic, and pragmatic knowledge and skills. The study highlights methodological approaches to developing linguistic competence through theory-based instruction, pragmatic exercises, text analysis, and creative language activities. Particular attention is paid to the role of practical tasks, independent text creation, and reflective assessment in improving learners’ speech culture. The article provides methodological recommendations aimed at developing coherent, logical, and communicatively effective oral and written speech.
DOI: 10.15468/dl.34w9w3
title: Occurrence Download

description: A dataset containing 18 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)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Fowleria aurita"
 ]
}

 The dataset includes 18 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001615-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18799032
title: Doping S=1 antiferromagnet in one-dimension

description: Dataset for "Doping S=1 antiferromagnet in one-dimension", Phys. Rev. B 113, 024424; DOI: 10.1103/kzwg-8853
DOI: 10.5281/zenodo.18799033
title: Doping S=1 antiferromagnet in one-dimension

description: Dataset for "Doping S=1 antiferromagnet in one-dimension", Phys. Rev. B 113, 024424; DOI: 10.1103/kzwg-8853
DOI: 10.5281/zenodo.18348074
title: TEMA AIIA_wildfire Dataset

description: General description of the dataset

The TEMA AIIA_wildfire dataset is a collection of 2,237 natural disaster images designed for semantic segmentation, focusing on burnt areas, smoke, and fire. It aggregates and standardizes images from three distinct sources: the BLAZE classification dataset (https://aiia.csd.auth.gr/blaze-fire-classification-segmentation-dataset/), Finland’s wildfire dataset  and Sardegna’s wildfire dataset. If one uses any part of these datasets in his/her work, he/she is kindly asked to cite the following paper:



 M. Siavrakas, C. Papaioannidis and I.Pitas, "BLAZE: A dataset for wildfire and burnt area UAV image classification and segmentation", IEEE International Conference on Image Processing (ICIP), Anchorage, Alaska, USA, 13-17 September, 2025.


Dataset Structure

The dataset is organized by source, each with standard train/validation splits containing .jpg images and corresponding .png label masks. The corresponding folder for each source are BLAZE (BLAZE1), Finland’s (KAHY) and Sardegna’s (RAS). Labels follow a four-class hierarchy (0: background, 1: burnt, 2: smoke, 3: fire). The final composition is 985 images from BLAZE (655 annotated), 584 from KAHY, and 668 from RAS, split into 1,528 training and 655 validation images almost a 70 – 30% split.

 

Details on acquiring the dataset can be found here.
DOI: 10.5281/zenodo.18377592
title: TEMA AIIA_wildfire Dataset

description: General description of the dataset

The TEMA AIIA_wildfire dataset is a collection of 2,237 natural disaster images designed for semantic segmentation, focusing on burnt areas, smoke, and fire. It aggregates and standardizes images from three distinct sources: the BLAZE classification dataset (https://aiia.csd.auth.gr/blaze-fire-classification-segmentation-dataset/), Finland’s wildfire dataset  and Sardegna’s wildfire dataset. If one uses any part of these datasets in his/her work, he/she is kindly asked to cite the following paper:



 M. Siavrakas, C. Papaioannidis and I.Pitas, "BLAZE: A dataset for wildfire and burnt area UAV image classification and segmentation", IEEE International Conference on Image Processing (ICIP), Anchorage, Alaska, USA, 13-17 September, 2025.


Dataset Structure

The dataset is organized by source, each with standard train/validation splits containing .jpg images and corresponding .png label masks. The corresponding folder for each source are BLAZE (BLAZE1), Finland’s (KAHY) and Sardegna’s (RAS). Labels follow a four-class hierarchy (0: background, 1: burnt, 2: smoke, 3: fire). The final composition is 985 images from BLAZE (655 annotated), 584 from KAHY, and 668 from RAS, split into 1,528 training and 655 validation images almost a 70 – 30% split.

 

Details on acquiring the dataset can be found here.