cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.29300756.v1
title: Supplementary Material for: German National Guideline for Treating Chronic Respiratory Failure with Non-Invasive Ventilation

description: The german guideline on non-invasive ventilation offers comprehensive recommendations for the treatment of chronic respiratory failure in various underlying conditions, such as COPD, thoraco-restrictive diseases, obesity-hypoventilation syndrome, and neuromuscular diseases. The aim of the guideline is to improve the treatment of patients with chronic respiratory insufficiency using non-invasive ventilation and to make the indications and therapy recommendations accessible to all involved in the treatment process. It is based on the latest scientific evidence and replaces the previous guideline from 2017. This revised guideline provides detailed recommendations on the application of non-invasive ventilation, ventilation settings, and the subsequent follow-up of treatment. In addition to the updated evidence, important new features of this guideline include new recommendations on patient care and numerous detailed treatment pathways that make the guideline more user-friendly. Furthermore, a completely revised section is dedicated to ethical issues and offers recommendations for end-of-life care. This guideline is an important tool for physicians and other healthcare professionals to optimize the care of patients with chronic respiratory failure.
DOI: 10.6084/m9.figshare.29300759
title: Supplementary Material for: Application of a general LLM-based classification system to retrieve information about oncological trials

description: Purpose: The automated classification of clinical trials and key categories within the medical literature is increasingly relevant, particularly in oncology, as the volume of publications and trial reports continues to expand. Large Language Models (LLMs) may provide new opportunities for automating diverse classification tasks. They could be used for general-purpose text classification retrieving information about oncological trials.
Methods and Materials: A general text classification framework with adaptable prompt, model and categories for the classification was developed. The framework was tested with four datasets comprising nine binary classification questions related to oncological trials. Evaluation was conducted using a locally hosted Mixtral-8x7B-Instruct v0.1-GPTQ model and three cloud-based LLMs: Mixtral-8x7B-Instruct v0.1, Llama3.1-70B-Instruct, and Qwen-2.5-72B.
Results: The system consistently produced valid responses with the local Mixtral-8x7B-Instruct model and the Llama3.1-70B-Instruct model. It achieved a response validity rate of 99.70% and 99.88% for the cloud-based Mixtral and Qwen models, respectively. Across all models, the framework achieved an overall accuracy of &gt;94%, precision of &gt;92%, recall of &gt;90%, and an F1-score of &gt;92%. Question-specific accuracy ranged from 86.33% to 99.83% for the local Mixtral model, 85.49% to 99.83% for the cloud-based Mixtral model, 90.50% to 99.83% for the Llama3.1 model, and 77.13% to 99.83% for the Qwen model.
Conclusions: The LLM-based classification framework exhibits robust accuracy and adaptability across various oncological trial classification tasks. While there remain some challenges such as strong prompt dependence and high computational and hardware demands, LLMs will play a crucial role for automating the classification of oncological trials and literature as the technology continues to advance.
DOI: 10.6084/m9.figshare.29300759.v1
title: Supplementary Material for: Application of a general LLM-based classification system to retrieve information about oncological trials

description: Purpose: The automated classification of clinical trials and key categories within the medical literature is increasingly relevant, particularly in oncology, as the volume of publications and trial reports continues to expand. Large Language Models (LLMs) may provide new opportunities for automating diverse classification tasks. They could be used for general-purpose text classification retrieving information about oncological trials.
Methods and Materials: A general text classification framework with adaptable prompt, model and categories for the classification was developed. The framework was tested with four datasets comprising nine binary classification questions related to oncological trials. Evaluation was conducted using a locally hosted Mixtral-8x7B-Instruct v0.1-GPTQ model and three cloud-based LLMs: Mixtral-8x7B-Instruct v0.1, Llama3.1-70B-Instruct, and Qwen-2.5-72B.
Results: The system consistently produced valid responses with the local Mixtral-8x7B-Instruct model and the Llama3.1-70B-Instruct model. It achieved a response validity rate of 99.70% and 99.88% for the cloud-based Mixtral and Qwen models, respectively. Across all models, the framework achieved an overall accuracy of &gt;94%, precision of &gt;92%, recall of &gt;90%, and an F1-score of &gt;92%. Question-specific accuracy ranged from 86.33% to 99.83% for the local Mixtral model, 85.49% to 99.83% for the cloud-based Mixtral model, 90.50% to 99.83% for the Llama3.1 model, and 77.13% to 99.83% for the Qwen model.
Conclusions: The LLM-based classification framework exhibits robust accuracy and adaptability across various oncological trial classification tasks. While there remain some challenges such as strong prompt dependence and high computational and hardware demands, LLMs will play a crucial role for automating the classification of oncological trials and literature as the technology continues to advance.
DOI: 10.15468/dl.racnu8
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is MEX.25.18_2",
 "TaxonKey is Passer domesticus (Linnaeus, 1758)"
 ]
}

 The dataset includes 6 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037792-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qg5p54
title: Occurrence Download

description: A dataset containing 112 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Rhoicissus tridentata (L.fil.) Wild & R.B.Drumm.",
 "Geometry POLYGON((29.76451 -26.09643, 32.1599 -26.09643, 32.1599 -22.51877, 29.76451 -22.51877, 29.76451 -26.09643))"
 ]
}

 The dataset includes 112 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037793-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15640047
title: Dataset for: "Using AI to detect misinformation and emotions on Telegram: a comparison with the media"

description: This dataset contains the raw data used in the article “Using AI to detect misinformation and emotions on Telegram: a comparison with the media”, accepted for publication in index.comunicación. The data includes: • Telegram dataset (tg_messages.csv): 54,456 posts extracted from 33 public Telegram channels between 23 July and 16 November 2023, related to the political debate around the Amnesty Law in Spain. Each entry includes message metadata such as channel, date, views, and content. • News headlines dataset (Titulares.csv): 46,022 news headlines mentioning “amnesty”, extracted from 377 Spanish national media outlets indexed in MediaCloud, during the same period. • Analysis scripts: Available upon request or pending publication in the article’s supplementary materials.

The data was used for topic modelling, sentiment and emotion detection with NLP techniques based on Python libraries like BERTopic and pysentimiento. All data is anonymized and publicly accessible or derived from open sources.
DOI: 10.5281/zenodo.15640048
title: Dataset for: "Using AI to detect misinformation and emotions on Telegram: a comparison with the media"

description: This dataset contains the raw data used in the article “Using AI to detect misinformation and emotions on Telegram: a comparison with the media”, accepted for publication in index.comunicación. The data includes: • Telegram dataset (tg_messages.csv): 54,456 posts extracted from 33 public Telegram channels between 23 July and 16 November 2023, related to the political debate around the Amnesty Law in Spain. Each entry includes message metadata such as channel, date, views, and content. • News headlines dataset (Titulares.csv): 46,022 news headlines mentioning “amnesty”, extracted from 377 Spanish national media outlets indexed in MediaCloud, during the same period. • Analysis scripts: Available upon request or pending publication in the article’s supplementary materials.

The data was used for topic modelling, sentiment and emotion detection with NLP techniques based on Python libraries like BERTopic and pysentimiento. All data is anonymized and publicly accessible or derived from open sources.
DOI: 10.15468/dl.2jnb83
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Schmidtia pappophoroides Steud. ex J.A.Schmidt",
 "Geometry POLYGON((29.76451 -26.09643, 32.1599 -26.09643, 32.1599 -22.51877, 29.76451 -22.51877, 29.76451 -26.09643))"
 ]
}

 The dataset includes 25 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037794-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kmckac
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Searsia longispina (Eckl. & Zeyh.) Moffett",
 "Geometry POLYGON((29.76451 -26.09643, 32.1599 -26.09643, 32.1599 -22.51877, 29.76451 -22.51877, 29.76451 -26.09643))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037795-250525065834625/datasets/export for details.
DOI: 10.15468/dl.gsrfra
title: Occurrence Download

description: A dataset containing 3705 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Pereskia aculeata Mill."
 ]
}

 The dataset includes 3705 records from 263 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037797-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26195/nbst-2658
title: Photocaging of Mitochondrial uncouplers
DOI: 10.15468/dl.p9jc9x
title: Occurrence Download

description: A dataset containing 3954 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.countrycode = 'SO'
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence."year" &gt;= 2000 AND occurrence."year" &lt;= 2025)
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year"

 The dataset's 3954 records were derived from 66 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037789-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15151/esrf-es-2114003266
title: Structural biology at Umea University

description: The BAG consists out of 5 groups that are heavily involved in macromolecular crystallography, as well as other structural biology techniques, at Umeå University, Sweden
DOI: 10.15151/esrf-es-2143607003
title: Determining the conformational changes of multi-domain adaptor proteins driving clathrin mediated endocytosis

description: Clathrin-mediated endocytosis (CME) is driven by the assembly of adaptor proteins that participate in cargo selection, clathrin recruitment and membrane bending. Eps15, Dab2 and FCHo1/2 are early initiators of CME and they work together to recruit the adaptor proteins that drive vesicle formation. Multivalent interactions through both folded domains and intrinsically disordered regions of these proteins facilitate an interconnected protein network, that triggers the formation of biological condensates. However, the molecular details of
both the interactions and domain reorganization are still unkown. Using NMR spectroscopy, we have unveiled the local structure and the interaction modes of these proteins, suggesting the presence of long-range contacts affecting the global conformations. Therefore, we aim to understand the global conformational changes occurring within Eps15, FCHo1/2 and Dab2 proteins during the initiation of CME and how they relate to liquid-liquid phase separation.
DOI: 10.15151/esrf-es-2136300891
title: Rise and fall of the Rhynchocephalia: understanding rates of morphological change, dental evolution, and growth patterns using multi-resolut

description: Rhynchocephalia is the sister-group of Squamata (lizards and snakes). Originating in the earliest Triassic, their fossil record is very rich and diverse during the Mesozoic, but today they are represented only by the Tuatara of New Zealand. To understanding their unique evolutionary trajectory, including the interaction with peculiar traits like acrodont dentition and slow growth pattern, we aim to study a fossil of the basalmost confirmed species, Diphydontosaurus. Since a prior attempt to µCT scan the specimen failed, we propose a multi resolution PPC-SRµCT to image the whole specimen, teeth, and femur to gain access to its postcranial anatomy, dental morphology and bone microanatomy. We aim to provide new insights into the macroevolutionary patterns of rhynchocephalians, focusing on their initial abundance and subsequent decline.
DOI: 10.5281/zenodo.15645685
title: Respiratorische Synzytialvirusfälle in Deutschland

description: Im Datensatz "Respiratorische Synzytialvirusfälle in Deutschland" werden die Fallzahlen und Inzidenzen (Fälle pro 100.000 Personen) der nach den Vorgaben des Infektionsschutzgesetzes (IfSG) von den Gesundheitsämtern in Deutschland an die zuständigen Landesbehörden und das Robert Koch-Institut (RKI) übermittelten Infektionen mit dem Respiratorischen Synzytial-Virus (RSV) nach Meldewoche bereitgestellt.
DOI: 10.15151/esrf-es-2134370305
title: Resolution of the high-pressure phase of Hydrochlorothiazide

description: Hydrochlorothiazide (HCT) exhibits pressure-induced polymorphism. The new high-pressure form can be accessed above 0.8 GPa. During this reconstructive phase transition, the single crystal turns to a powder that is exhibits extremely insolubility. Our usual methods to anneal into a single crystal, via heat treating a solution of hydrochlorothiazide, have failed due to the apparent steep pressure-dependent solubility. We are able to recover the phase, however the powder diffraction pattern is a mixed phase with the known form. We have previously been allocated beamtime (CH6625) for this study that enabled us to explore the conditions in the press to be able to provide the best dataset for structural solution and refinement. This has been challenging due to the large strain in the sample over the transition. The set of parameters that we have found will provide our best opportunity to solve the structure of this simple yet intriguing solid.
DOI: 10.5281/zenodo.15645686
title: Laborbestätigte Influenzafälle in Deutschland

description: Im Datensatz "Laborbestätigte Influenzafälle in Deutschland" werden die wöchentlichen Fallzahlen und Inzidenzen (Fälle pro 100.000 Personen) der nach den Vorgaben des Infektionsschutzgesetzes (IfSG) von den Gesundheitsämtern in Deutschland an die zuständigen Landesbehördne und das Robert Koch-Institut (RKI) übermittelten laborbestätigten Influenzafälle bereitgestellt.
DOI: 10.5281/zenodo.15645663
title: DLBCL
DOI: 10.5281/zenodo.15645664
title: DLBCL
DOI: 10.6084/m9.figshare.29300780
title: Leaf_Dataset_Metadata_and_Sample_Info

description: Pepper and Maize are two essential crops that hold significant agricultural importance 408on a worldwide basis. This study utilized two distinct datasets consisting of photos of 409pepper and Maize leaves to assess the efficiency of the CNN-BiLSTM model in reducing 410the complexity of labelled features for improved leaf detection and classification tasks. 411
DOI: 10.6084/m9.figshare.29300780.v1
title: Leaf_Dataset_Metadata_and_Sample_Info

description: Pepper and Maize are two essential crops that hold significant agricultural importance 408on a worldwide basis. This study utilized two distinct datasets consisting of photos of 409pepper and Maize leaves to assess the efficiency of the CNN-BiLSTM model in reducing 410the complexity of labelled features for improved leaf detection and classification tasks. 411
DOI: 10.15151/esrf-es-2158047837
title: The SAXS/SANS platform a the Partnership for Structural Biology

description: This proposal seeks time on BM29 to allow joint SAXS and SANS measurements to be carried out as part of the PSB SAXS/SANS platform. The BAG services this user-platform by allowing the allocation of SAXS beamtime in connection to SANS measurements so that full advantage of co-location of SAXS and SANS facilities on the EPN can be provided to users. The scientific case for each joint request is evaluated by the ILL review committees of its Scientific Council and the allocation of time for successful proposals coordinated between the ILL and ESRF user offices.
DOI: 10.15468/dl.3jr5fu
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Setaria neglecta de Wit",
 "Geometry POLYGON((29.76451 -26.09643, 32.1599 -26.09643, 32.1599 -22.51877, 29.76451 -22.51877, 29.76451 -26.09643))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037798-250525065834625/datasets/export for details.
DOI: 10.15468/dl.z4h7jr
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Setaria sphacelata (Schumach.) Stapf & C.E.Hubb. ex Moss",
 "Geometry POLYGON((29.76451 -26.09643, 32.1599 -26.09643, 32.1599 -22.51877, 29.76451 -22.51877, 29.76451 -26.09643))"
 ]
}

 The dataset includes 30 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037799-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ww2jg8
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Solanum tomentosum L.",
 "Geometry POLYGON((29.76451 -26.09643, 32.1599 -26.09643, 32.1599 -22.51877, 29.76451 -22.51877, 29.76451 -26.09643))"
 ]
}

 The dataset includes 8 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037800-250525065834625/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.28440992.v1
title: Additional data for publication: "<i>Genomic epidemiology of IMP carbapenemases: an emerging global problem with diverse IMP variants, bacterial host strains and plasmid types</i>"

description: Additional data for publication: "<i>The rise and global spread of IMP carbapenemases (1996-2023): a genomic epidemiology study</i>"Contains additional supplemental information referenced in preprint/paper
DOI: 10.15468/dl.g8qgeu
title: Occurrence Download

description: A dataset containing 375 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Country is one of (United States of America, Mexico, Guatemala, Honduras, El Salvador, Panama, Jamaica, Haiti, Cuba)",
 "OccurrenceStatus is Present",
 "TaxonKey is Carthamus lanatus L.",
 "Year 1900-2025"
 ]
}

 The dataset includes 375 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037801-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ktd2mz
title: Occurrence Download

description: A dataset containing 1239 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Country is one of (Mexico, United States of America, Panama, El Salvador, Honduras, Guatemala, Jamaica, Haiti, Cuba)",
 "OccurrenceStatus is Present",
 "TaxonKey is Centaurea calcitrapa L.",
 "Year 1900-2025"
 ]
}

 The dataset includes 1239 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037802-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ssnev3
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Sporobolus ioclados (Nees ex Trin.) Nees",
 "Geometry POLYGON((29.76451 -26.09643, 32.1599 -26.09643, 32.1599 -22.51877, 29.76451 -22.51877, 29.76451 -26.09643))"
 ]
}

 The dataset includes 45 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037803-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15645747
title: AKTIN - Daten zur Aufenthaltsdauer in Notaufnahmen

description: Die Belastung von Notaufnahmen hängt von verschiedenen Faktoren ab, wie z.B. der Anzahl der Patient:innen, der Schwere ihrer Fälle, der Personalsituation und der Kapazität der Intensivbetten. Die durchschnittliche Aufenthaltsdauer in der Notaufnahme kann als Indikator für die Belastungssituation herangezogen werden.
Der Datensatz "AKTIN - Daten zur Aufenthaltsdauer in Notaufnahmen" enthält aggregierte Daten der Routinedokumentation aus einer Auswahl deutscher Notaufnahmen aus dem AKTIN-Notaufnahmeregister. Zur Erfassung der speziellen Belastungssituation während der COVID-19-Pandemie werden im vorliegenden Datensatz Daten zur durchschnittliche Aufenthaltsdauer von Patienti:innen in den Notaufnahmen bereitgestellt und mit den Werten vor der Pandemie verglichen.