cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/cc535s6
title: CCDC 152017: Experimental Crystal Structure Determination

description: Related Article: G.Linti, A.Rodig, W.Kostler|2001|Z.Anorg.Allg.Chem.|627|1465|doi:10.1002/1521-3749(200107)627:7<1465::AID-ZAAC1465>3.0.CO;2-#
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.
DOI: 10.5517/cc535t7
title: CCDC 152018: Experimental Crystal Structure Determination

description: Related Article: G.Linti, A.Rodig, W.Kostler|2001|Z.Anorg.Allg.Chem.|627|1465|doi:10.1002/1521-3749(200107)627:7<1465::AID-ZAAC1465>3.0.CO;2-#
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.
DOI: 10.5517/cc535v8
title: CCDC 152019: Experimental Crystal Structure Determination

description: Related Article: G.Linti, A.Rodig, W.Kostler|2001|Z.Anorg.Allg.Chem.|627|1465|doi:10.1002/1521-3749(200107)627:7<1465::AID-ZAAC1465>3.0.CO;2-#
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.
DOI: 10.5517/cc535w9
title: CCDC 152020: Experimental Crystal Structure Determination

description: Related Article: G.Linti, A.Rodig, W.Kostler|2001|Z.Anorg.Allg.Chem.|627|1465|doi:10.1002/1521-3749(200107)627:7<1465::AID-ZAAC1465>3.0.CO;2-#
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.
DOI: 10.5517/cc535xb
title: CCDC 152021: Experimental Crystal Structure Determination

description: Related Article: G.Linti, A.Rodig, W.Kostler|2001|Z.Anorg.Allg.Chem.|627|1465|doi:10.1002/1521-3749(200107)627:7<1465::AID-ZAAC1465>3.0.CO;2-#
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.
DOI: 10.5517/cc58cpg
title: CCDC 157005: Experimental Crystal Structure Determination

description: Related Article: M.Plitzner, U.Heinl, R.Mattes, R.Frohlich|2001|Z.Anorg.Allg.Chem.|627|1426|doi:10.1002/1521-3749(200107)627:7<1426::AID-ZAAC1426>3.0.CO;2-1
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.
DOI: 10.5517/cc55bg3
title: CCDC 154084: Experimental Crystal Structure Determination

description: Related Article: V.Kupfer, U.Thewalt|2001|Z.Anorg.Allg.Chem.|627|1423|doi:10.1002/1521-3749(200107)627:7<1423::AID-ZAAC1423>3.0.CO;2-J
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.
DOI: 10.5517/cc55bh4
title: CCDC 154085: Experimental Crystal Structure Determination

description: Related Article: V.Kupfer, U.Thewalt|2001|Z.Anorg.Allg.Chem.|627|1423|doi:10.1002/1521-3749(200107)627:7<1423::AID-ZAAC1423>3.0.CO;2-J
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.
DOI: 10.5281/zenodo.16317287
title: Piloting an interactive horizon scanning of the forest bioeconomy in Finland: Collected signals of change and participants' experiences

description: Data from: Mauno, T., Pelli, P., Bengston, D.N., Pykäläinen, J. & Hujala, T. 2025. Interactive Horizon Scanning of the Forest Bioeconomy with a Nested Business Environment Framework. Futures & Foresight Science. https://doi.org/10.1002/ffo2.70015 

This study piloted interactive horizon scanning to test how future signals information can be collected and processed in collaboration with forest bioeconomy stakeholders. In interaction with a diverse group of Finnish forest bioeconomy stakeholders (n=10), this exploratory, one-time horizon scanning exercise collected and interpreted signals of change that may have an impact on the forest bioeconomy. This horizon scanning campaign followed the typical steps of the scanning process: The process first included pre-scanning (with a research group consisting of 7 researchers), recruiting and training a team of scanners, followed by scanning and collecting signals of change online. An onsite signal interpretation workshop was then held, followed by a follow-up survey on participation and the analysis of the collected data.

Padlet (Padlet.com) was used as the database for this horizon scanning exercise. The online horizon scanning of this study lasted nine weeks from January 2024 to March 2024 (Jan 8, 2024 – Mar 13, 2024). During that time, participants had the opportunity to save their own scanning hits and comment on and like each other's posts. During nine weeks, a total of 10 horizon scanners participated in Padlet's activities: 42 scanning hits were saved, 29 comments were identified, and 47 likes (reactions) were given to the scanning hits. After the online horizon scanning, an onsite signal interpretation workshop was organized for participants, which was followed by a follow-up survey on participation.

This dataset includes: (i) Collected signals of change (including pre-scanning data) (ii) anonymized expertise matrix (participating stakeholders), and (iii) anonymized follow-up survey data (participants' experiences of the pilot interactive horizon scan). Analyzed data from the workshop are available from the article’s supplementary material.

For more information, please contact the corresponding author (data controller): Tuomas Mauno (University of Eastern Finland), tuomas.mauno@uef.fi
description: The collection of data and the preparation of the related article were funded by the Finnish Cultural Foundation and the University of Eastern Finland.
DOI: 10.5281/zenodo.15508214
title: TMPRSS2 inhibitor discovery data

description: Data accompanying the paper “Simulations and active learning enable efficient identification of an experimentally-validated broad coronavirus inhibitor”.
DOI: 10.5281/zenodo.15685087
title: Oxytocin signaling regulates maternally-directed behavior during early life

description: This dataset accompanies the research article "Oxytocin signaling regulates maternally-directed behavior during early life". It includes Matlab data structures for each of the figures in the article. Within each structure are entries for each panel in the figure, including all data points presented in the panel. Panels that do not include any quantitative data (for example images) are also associated with entries in the matlab structures, but these entries are empty.
DOI: 10.5281/zenodo.15596033
title: Mapped Landslide for Typhoon Ketsaan, Moalve and Tropical storm Podul in central Vietnam

description: The dataset includes shapefiles of landslides in central Vietnam triggered by Typhoon Ketsana (2009), Tropical Storm Podul (2013), and Typhoon Molave (2020). The number of landslides mapped for each event totals 8,744 for Ketsana, 915 for Podul, and 11,575 for Molave.
DOI: 10.15468/dl.b4277u
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lachesilla alpejia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0082963-250717081556266/datasets/export for details.
DOI: 10.15468/dl.apd58n
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lachesilla cintalapa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0082964-250717081556266/datasets/export for details.
DOI: 10.15468/dl.5b2mwg
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Asthenes usheri)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0082965-250717081556266/datasets/export for details.
DOI: 10.15468/dl.ue7u4f
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",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Mantidactylus betsileanus)",
 "Country is one of (Bermuda, Canada, Greenland, Saint Pierre and Miquelon, United States of America)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081867-250717081556266/datasets/export for details.
DOI: 10.5066/f7c827bx
title: Swath bathymetry collected offshore of Fire Island and western Long Island, New York in 2014, U.S. Geological Field Activity 2014-072-FA

description: Swath bathymetric data were collected offshore of Fire Island and western Long Island, New York in 2014 as a part of a collaborative effort between the U.S. Army Corps and USGS to assess the impact of Hurricane Sandy on this coastal region. These data were compared to swath bathymetric data collected by the USGS in the same area in 2011 to evaluate any modifications to the inner continental shelf, such as migration of bedforms, extensive erosion or deposition.
DOI: 10.15468/dl.bw35ka
title: Occurrence Download

description: A dataset containing 295 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Dataset of the Lampyridae (Coleoptera) from Morelia, Michoacán, México"
 ]
}

 The dataset includes 295 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010747-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/nbwf-aa58
title: CHEWING MUSCLE DATASET

description: The efficiency of the mastication process in humansis closely linked to various physiological and psychological conditions.Inadequate chewing or inefficient muscle activation patternsin the muscles of mastication can serve as early indicatorsof potential health issues. Early detection of such inefficienciesenables healthcare professionals to identify underlying causes orsignals of other diseases. In this research, we explore a novelapplication of AI to analyze muscle efficiency during chewing,leveraging machine learning techniques to detect inefficiencies.With prior consent, we collected electromyography (EMG) datafrom 11 healthy subjects, four of whom had dental ailments thataffected their chewing efficiency. Rather than labeling all theirmasticatory muscles as inefficient, we focused on analyzing specificsignal properties to determine which muscles were impactedby inefficiencies. For this purpose, we developed and trained fourseparate classifier models, each corresponding to a specific muscleinvolved in mastication. Each model generates predictions regardingmuscle efficiency, and the results are further interpretedby identifying the top three contributing factors influencingthose predictions. These insights allow us to provide suggestionsregarding potential causes of chewing inefficiency. Our approachachieved a maximum classification accuracy of 95.23 in detectingmuscle efficiency, demonstrating the effectiveness of machinelearning in this domain. This research marks a significant steptoward using AI to support early diagnosis and personalizedtreatment for chewing-related issues.
DOI: 10.6084/m9.figshare.29118491
title: <b>Dataset for Extracellular Vesicle-Derived miRNAs as Diagnostic Biomarkers for Pancreatic Ductal Adenocarcinoma: A Systematic Review of Methodological Rigor and Clinical Applicability</b>

description: <b>This project is a systematic review evaluating the diagnostic potential and methodological rigor of extracellular vesicle (EV)-derived microRNAs (miRNAs) for the early detection of pancreatic ductal adenocarcinoma (PDAC).</b> We searched PubMed, EMBASE, Medline, and Cochrane up to February 1, 2025, identifying 56 original human studies that assessed EV-miRNAs in non-invasively collected biofluids (e.g., plasma, serum, urine). Diagnostic metrics (sensitivity, specificity, AUC) were extracted, and each study was assessed for risk of bias using the QUADAS-2 tool.A novel aspect of this review was the application of a modified MISEV 2018 (updated 2023) checklist to quantitatively score EV validation. Key findings include widespread poor adherence to EV characterisation standards (e.g., &gt;70% lacked EV quantification), minimal use of external validation cohorts (only 2 studies), and frequent absence of blinding (54/56 studies). Although some biomarkers (e.g., miR-21, miR-10b, miR-451a) and multi-miRNA panels showed high AUCs (&gt;0.85), weak methodology often undermined the reliability of these findings.This dataset includes tables of extracted study characteristics, MISEV scores, diagnostic performance of individual and panel biomarkers, and risk of bias ratings. The findings highlight the urgent need for standardised protocols and external validation to support the clinical translation of EV-miRNA biomarkers in PDAC.<b>Data are shared in both Excel (</b><code><strong>.xlsx</strong></code><b>) and CSV formats. The Excel file retains merged cell formatting for clarity, while the CSV version ensures compliance with open data standards recommended by FAIRsharing.</b><b>PROSPERO Registration</b>: CRD42024501503<br><b>Word count</b>: 2840 (main text), 277 (abstract)<br><b>Number of included studies</b>: 56<br><b>Tools used</b>: PRISMA 2020, QUADAS-2, MISEV 2018 checklist<br><b>Funding</b>: None<br><b>Ethics</b>: Not required (systematic review of published studies)
DOI: 10.6084/m9.figshare.29118491.v3
title: <b>Dataset for Extracellular Vesicle-Derived miRNAs as Diagnostic Biomarkers for Pancreatic Ductal Adenocarcinoma: A Systematic Review of Methodological Rigor and Clinical Applicability</b>

description: <b>This project is a systematic review evaluating the diagnostic potential and methodological rigor of extracellular vesicle (EV)-derived microRNAs (miRNAs) for the early detection of pancreatic ductal adenocarcinoma (PDAC).</b> We searched PubMed, EMBASE, Medline, and Cochrane up to February 1, 2025, identifying 56 original human studies that assessed EV-miRNAs in non-invasively collected biofluids (e.g., plasma, serum, urine). Diagnostic metrics (sensitivity, specificity, AUC) were extracted, and each study was assessed for risk of bias using the QUADAS-2 tool.A novel aspect of this review was the application of a modified MISEV 2018 (updated 2023) checklist to quantitatively score EV validation. Key findings include widespread poor adherence to EV characterisation standards (e.g., &gt;70% lacked EV quantification), minimal use of external validation cohorts (only 2 studies), and frequent absence of blinding (54/56 studies). Although some biomarkers (e.g., miR-21, miR-10b, miR-451a) and multi-miRNA panels showed high AUCs (&gt;0.85), weak methodology often undermined the reliability of these findings.This dataset includes tables of extracted study characteristics, MISEV scores, diagnostic performance of individual and panel biomarkers, and risk of bias ratings. The findings highlight the urgent need for standardised protocols and external validation to support the clinical translation of EV-miRNA biomarkers in PDAC.<b>PROSPERO Registration</b>: CRD42024501503<br><b>Word count</b>: 2840 (main text), 277 (abstract)<br><b>Number of included studies</b>: 56<br><b>Tools used</b>: PRISMA 2020, QUADAS-2, MISEV 2018 checklist<br><b>Funding</b>: None<br><b>Ethics</b>: Not required (systematic review of published studies)
DOI: 10.6084/m9.figshare.29118491.v4
title: <b>Dataset for Extracellular Vesicle-Derived miRNAs as Diagnostic Biomarkers for Pancreatic Ductal Adenocarcinoma: A Systematic Review of Methodological Rigor and Clinical Applicability</b>

description: <b>This project is a systematic review evaluating the diagnostic potential and methodological rigor of extracellular vesicle (EV)-derived microRNAs (miRNAs) for the early detection of pancreatic ductal adenocarcinoma (PDAC).</b> We searched PubMed, EMBASE, Medline, and Cochrane up to February 1, 2025, identifying 56 original human studies that assessed EV-miRNAs in non-invasively collected biofluids (e.g., plasma, serum, urine). Diagnostic metrics (sensitivity, specificity, AUC) were extracted, and each study was assessed for risk of bias using the QUADAS-2 tool.A novel aspect of this review was the application of a modified MISEV 2018 (updated 2023) checklist to quantitatively score EV validation. Key findings include widespread poor adherence to EV characterisation standards (e.g., &gt;70% lacked EV quantification), minimal use of external validation cohorts (only 2 studies), and frequent absence of blinding (54/56 studies). Although some biomarkers (e.g., miR-21, miR-10b, miR-451a) and multi-miRNA panels showed high AUCs (&gt;0.85), weak methodology often undermined the reliability of these findings.This dataset includes tables of extracted study characteristics, MISEV scores, diagnostic performance of individual and panel biomarkers, and risk of bias ratings. The findings highlight the urgent need for standardised protocols and external validation to support the clinical translation of EV-miRNA biomarkers in PDAC.<b>Data are shared in both Excel (</b><code><strong>.xlsx</strong></code><b>) and CSV formats. The Excel file retains merged cell formatting for clarity, while the CSV version ensures compliance with open data standards recommended by FAIRsharing.</b><b>PROSPERO Registration</b>: CRD42024501503<br><b>Word count</b>: 2840 (main text), 277 (abstract)<br><b>Number of included studies</b>: 56<br><b>Tools used</b>: PRISMA 2020, QUADAS-2, MISEV 2018 checklist<br><b>Funding</b>: None<br><b>Ethics</b>: Not required (systematic review of published studies)
DOI: 10.15468/dl.scvtnb
title: Occurrence Download

description: A dataset containing 612 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Apteryx rowi)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 612 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081868-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a7ug5u
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",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Sternula nereis)",
 "Country is one of (Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivia (Plurinational State of), Bonaire, Sint Eustatius and Saba, Bouvet Island, Brazil, Cayman Islands, Chile, Colombia, Costa Rica, Cuba, Curaçao, Dominica, Dominican Republic, Ecuador, El Salvador, Falkland Islands (Malvinas), French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Montserrat, Nicaragua, Panama, Paraguay, Peru, Puerto Rico, Saint Barthélemy, Saint Kitts and Nevis, Saint Lucia, Saint Martin (French part), Saint Vincent and the Grenadines, Sint Maarten (Dutch part), South Georgia and the South Sandwich Islands, Suriname, Trinidad and Tobago, Turks and Caicos Islands, Uruguay, Venezuela (Bolivarian Republic of), Virgin Islands (British), Virgin Islands (U.S.))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081870-250717081556266/datasets/export for details.
DOI: 10.15468/dl.9cz7e8
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Sternula nereis)",
 "Country is one of (Afghanistan, Armenia, Azerbaijan, Bahrain, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cyprus, Georgia, Hong Kong, India, Indonesia, Iran (Islamic Republic of), Iraq, Israel, Japan, Jordan, Kazakhstan, Korea (Democratic People’s Republic of), Korea, Republic of, Kuwait, Kyrgyzstan, Lao People’s Democratic Republic, Lebanon, Macao, Malaysia, Maldives, Mongolia, Myanmar, Nepal, Oman, Pakistan, Palestine, State of, Philippines, Qatar, Saudi Arabia, Singapore, Sri Lanka, Syrian Arab Republic, Tajikistan, Thailand, Timor-Leste, Türkiye, Turkmenistan, United Arab Emirates, Uzbekistan, Viet Nam, Yemen)"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081869-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p2c94j
title: Occurrence Download

description: A dataset containing 640 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Peucaea aestivalis (M.H.K.Lichtenstein, 1823)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen",
 "Year is greater than or equal to 1810",
 "Year is less than or equal to 2019",
 "Month is greater than or equal to April",
 "Month is less than or equal to September",
 "EventDate is not null",
 "Country is United States of America",
 "Geometry POLYGON((-63 22, -63 51, -126 51, -126 22, -63 22))"
 ]
}

 The dataset includes 640 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010329-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.