cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17931937
title: Transforming textile waste into materials using fungi

description: Textile waste from ‘fast fashion’ has considerable environmental impact and is an EU priority area. Colonising textiles with fungi provides a unique solution, with options to bond them together to create composite materials, fruit them to provide mushrooms (source of chitin-glucan complex), or both. We produced mycelium-textile composites in analogy to traditional prepreg-based composite manufacturing, consolidating multiple textile stacks colonised with Ganoderma lucidum into a single material of customisable thickness and free-form geometry. An oxygen gradient existed through the cross-section of textile stacks, resulting in more growth on surface than core plies. Consolidated composites comprising only surface layers achieved tensile strengths up to ~14 MPa. Their flexural and shear strengths (7 MPa and 0.5 MPa, respectively) indicated suitability for semi-structural construction applications. Waste textile substrate could also be fruited (5.7% w/w yield). These advances expand the stalled application of mycelium composites and provide a nature-based solution to textile upcycling.
DOI: 10.5281/zenodo.17931938
title: Transforming textile waste into materials using fungi

description: Textile waste from ‘fast fashion’ has considerable environmental impact and is an EU priority area. Colonising textiles with fungi provides a unique solution, with options to bond them together to create composite materials, fruit them to provide mushrooms (source of chitin-glucan complex), or both. We produced mycelium-textile composites in analogy to traditional prepreg-based composite manufacturing, consolidating multiple textile stacks colonised with Ganoderma lucidum into a single material of customisable thickness and free-form geometry. An oxygen gradient existed through the cross-section of textile stacks, resulting in more growth on surface than core plies. Consolidated composites comprising only surface layers achieved tensile strengths up to ~14 MPa. Their flexural and shear strengths (7 MPa and 0.5 MPa, respectively) indicated suitability for semi-structural construction applications. Waste textile substrate could also be fruited (5.7% w/w yield). These advances expand the stalled application of mycelium composites and provide a nature-based solution to textile upcycling.
DOI: 10.15468/dl.4rtcpk
title: Occurrence Download

description: A dataset containing 37922 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Opsarius kanaensis, Opsarius arunachalensis, Nannocharax hadros, Ctenochromis scatebra, Diplotaxodon dentatus, Epiplatys cashneri, Phenacogrammus, Phenacogrammus, Distichodus microps, Distichodus mbiniensis, Lacustricola nitida, Lacustricola chobensis, Lacustricola pygmaeus, Nothobranchius balamaensis, Serranochromis alvum, Serranochromis swartzi, Serranochromis cuanza, Serranochromis cacuchi, Maylandia koningsi, Diplotaxodon altus, Diplotaxodon longimaxilla, Clarias monsembulai, Haplochromis molossus, Hemimyzon, Rasbora adisi, Channa ara, Haplochromis gracilifur, Haplochromis relictidens, Devario memorialis, Laubuka hema, Labeobarbus nzadimalawu, Labeobarbus nzadinkisi, Enteromius alberti, Bagarius vegrandis, Labeo heladiva, Channa kelaartii, Schistura scripta, Austrolebias ephemerus, Betta omega, Characidium onca, Characidium kalunga, Cynolebias akroa, Harttia villasboas, Harttia panara, Harttia rondoni, Parakneria, Lentipes niasensis, Hypsolebias hamadryades, Hypsolebias gardneri, Hypsolebias splendissimus, Melanotaenia klasioensis, Melanotaenia longispina, Melanotaenia susii, Melanotaenia manibuii, Melanotaenia naramasae, Rhinogobius lingtongyanensis, Melanotaenia sembrae, Melanotaenia rumberponensis, Melanotaenia sikuensis, Rhinogobius yangminshanensis, Rhinogobius, Nothobranchius taiti, Austrolebias wichi, Jenynsia sulfurica, Sinocyclocheilus longicornus, Potamotrygon marquesi, Poeciliopsis jackschultzi, Hoplomyzon cardosoi, Hypsolebias martinsi, Hypsolebias faouri, Leiocassis rudicula, Lucifuga gibarensis, Hopliancistrus munduruku, Hopliancistrus wolverine, Hopliancistrus xikrin, Hopliancistrus xavante, Chinchaysuyoa ortegai, Microglanis nigrolineatus, Corumbataia lucianoi, Corumbataia liliai, Cyphocharax muyrakytan, Apistogramma psammophila, Astyanax anai, Marcusenius lambouri, Bryconamericus coeruleus, Cetopsis aspis, Farlowella gianetii, Trichomycterus donascimientoi, Ituglanis amphipotamus, Microlepidogaster negomata, Spectrolebias gracilis, Sicyopus beremeensis, Pareiorhina rosai, Parotocinclus fluminense, Peckoltia wernekei, Marcusenius verheyenorum, Planaltina kaingang, Ancistrus kellerae, Nothobranchius matanduensis, Ancistrus amaris)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 37922 records from 170 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002137-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/icpsr300499
title: A Blue Start: A large-scale pairwise and higher-order social network dataset
title: Archival Version

description: <p><span>This dataset consists of all starter packs and all following network data available on Bluesky as of late October 2025. Starter packs can be created by any Bluesky user. They are lists of users and curated feeds with a minimum of 6 and a maximum of 150 users, curated by the starter pack creator. The creator typically names them and provides a description. Other users can use a single click to follow all users in the starter pack, or they can scroll through a specific starter pack to decide who to follow within that starter pack. In our dataset, all DIDs (persistent, unique identifiers) are anonymized with a non-reversible hash function; users in the network, as well as users who created starter packs, or appear in starter packs, are identified by their hashed DIDs. Similarly, starter packs themselves are identified by their hashed identifiers.</span></p><p><span>First, we include the Bluesky following network as it appeared in late October 2025. This shows all available directed following relationships on Bluesky. We also include a network dataset of starter packs with information on creators and starter pack members. This is intended for users who wish to undertake a computational analysis of the networks created by starter packs or starter packs’ influences on networks.</span></p>
DOI: 10.3886/icpsr300499.v1
title: A Blue Start: A large-scale pairwise and higher-order social network dataset
title: Version 1

description: <p><span>This dataset consists of all starter packs and all following network data available on Bluesky as of late October 2025. Starter packs can be created by any Bluesky user. They are lists of users and curated feeds with a minimum of 6 and a maximum of 150 users, curated by the starter pack creator. The creator typically names them and provides a description. Other users can use a single click to follow all users in the starter pack, or they can scroll through a specific starter pack to decide who to follow within that starter pack. In our dataset, all DIDs (persistent, unique identifiers) are anonymized with a non-reversible hash function; users in the network, as well as users who created starter packs, or appear in starter packs, are identified by their hashed DIDs. Similarly, starter packs themselves are identified by their hashed identifiers.</span></p><p><span>First, we include the Bluesky following network as it appeared in late October 2025. This shows all available directed following relationships on Bluesky. We also include a network dataset of starter packs with information on creators and starter pack members. This is intended for users who wish to undertake a computational analysis of the networks created by starter packs or starter packs’ influences on networks.</span></p>
DOI: 10.5281/zenodo.18432494
title: INFLYATSIYA VA UNGA QARSHI KURASHISH USULLARI

description: Mazkur maqolada inflyatsiya jarayoni va uning iqtisodiy tizimga ko‘rsatadigan ta’siri har tomonlama tahlil qilinadi. Inflyatsiyaning kelib chiqish omillari, narxlar umumiy darajasining o‘sishi orqali aholi real daromadlariga, jamg‘arma va investitsiya jarayonlariga ta’siri ilmiy asosda yoritiladi. Shuningdek, inflyatsiyaning makroiqtisodiy barqarorlikka ta’siri, ayniqsa, milliy valyuta qadrsizlanishi va iqtisodiy o‘sish sur’atlariga bog‘liqligi ochib beriladi. Maqolada inflyatsiyaga qarshi kurashishning asosiy yo‘nalishlari — pul-kredit siyosati, fiskal choralar hamda institutsional islohotlarning o‘rni tahlil qilinadi. Markaziy bankning foiz stavkasi, pul massasi va inflyatsion kutilmalarni boshqarish mexanizmlari alohida ko‘rib chiqiladi. Shu bilan birga, davlat byudjeti muvozanatini ta’minlash, raqobat muhitini kuchaytirish va ishlab chiqarish hajmini kengaytirish orqali inflyatsion bosimni kamaytirish imkoniyatlari asoslab beriladi. Tadqiqot natijalari inflyatsiyani nazorat qilishda kompleks yondashuv zarurligini ko‘rsatadi hamda iqtisodiy siyosatni shakllantirish jarayonida ilmiy-amaliy ahamiyat kasb etadi.
DOI: 10.5281/zenodo.18432495
title: INFLYATSIYA VA UNGA QARSHI KURASHISH USULLARI

description: Mazkur maqolada inflyatsiya jarayoni va uning iqtisodiy tizimga ko‘rsatadigan ta’siri har tomonlama tahlil qilinadi. Inflyatsiyaning kelib chiqish omillari, narxlar umumiy darajasining o‘sishi orqali aholi real daromadlariga, jamg‘arma va investitsiya jarayonlariga ta’siri ilmiy asosda yoritiladi. Shuningdek, inflyatsiyaning makroiqtisodiy barqarorlikka ta’siri, ayniqsa, milliy valyuta qadrsizlanishi va iqtisodiy o‘sish sur’atlariga bog‘liqligi ochib beriladi. Maqolada inflyatsiyaga qarshi kurashishning asosiy yo‘nalishlari — pul-kredit siyosati, fiskal choralar hamda institutsional islohotlarning o‘rni tahlil qilinadi. Markaziy bankning foiz stavkasi, pul massasi va inflyatsion kutilmalarni boshqarish mexanizmlari alohida ko‘rib chiqiladi. Shu bilan birga, davlat byudjeti muvozanatini ta’minlash, raqobat muhitini kuchaytirish va ishlab chiqarish hajmini kengaytirish orqali inflyatsion bosimni kamaytirish imkoniyatlari asoslab beriladi. Tadqiqot natijalari inflyatsiyani nazorat qilishda kompleks yondashuv zarurligini ko‘rsatadi hamda iqtisodiy siyosatni shakllantirish jarayonida ilmiy-amaliy ahamiyat kasb etadi.
DOI: 10.5281/zenodo.18432506
title: spatial_indicators_full_agg_fleet_segments_csquare_grid
DOI: 10.5281/zenodo.18432507
title: spatial_indicators_full_agg_fleet_segments_csquare_grid
DOI: 10.15468/dl.7j66a8
title: Occurrence Download

description: A dataset containing 575 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Vasconcellea quercifolia",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 575 records from 71 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002139-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.set5fp
title: Occurrence Download

description: A dataset containing 3416 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "TaxonKey is Polistes apachus"
 ]
}

 The dataset includes 3416 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002140-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18432376
title: A Fully Synthetic Dataset Inspired by SpaceX Missions for Model Training

description: This dataset is fully synthetic and was generated using a combination of manual design and large language model (ChatGPT) assistance.It does not represent real-world measurements or observations and is intended solely for methodological testing, benchmarking, and demonstration purposes.
DOI: 10.5281/zenodo.18432377
title: A Fully Synthetic Dataset Inspired by SpaceX Missions for Model Training

description: This dataset is fully synthetic and was generated using a combination of manual design and large language model (ChatGPT) assistance.It does not represent real-world measurements or observations and is intended solely for methodological testing, benchmarking, and demonstration purposes.
DOI: 10.5281/zenodo.18432517
title: CULTURAL FEATURES OF ENGLISH IDIOMS AND ISSUES OF THEIR TRANSLATION INTO UZBEK

description: English idioms are not just linguistic expressions but cultural artifacts that reflect the historical experience and worldview of a nation. Translating idioms into Uzbek requires not only linguistic equivalence but also cultural and stylistic adaptation. This article explores the cultural foundations of English idioms, common challenges in translating them into Uzbek, and effective translation strategies. It also discusses the views of well-known translation theorists and provides practical examples of idioms with their Uzbek translations.
DOI: 10.5281/zenodo.18432518
title: CULTURAL FEATURES OF ENGLISH IDIOMS AND ISSUES OF THEIR TRANSLATION INTO UZBEK

description: English idioms are not just linguistic expressions but cultural artifacts that reflect the historical experience and worldview of a nation. Translating idioms into Uzbek requires not only linguistic equivalence but also cultural and stylistic adaptation. This article explores the cultural foundations of English idioms, common challenges in translating them into Uzbek, and effective translation strategies. It also discusses the views of well-known translation theorists and provides practical examples of idioms with their Uzbek translations.
DOI: 10.5281/zenodo.18432487
title: Millennials vs Gen Z Sustainable Consumption: How Environmental Knowledge, Environmental Care Attitude, Emotional Value, and Green Marketing affect Green Purchase Intention
DOI: 10.5281/zenodo.18432488
title: Millennials vs Gen Z Sustainable Consumption: How Environmental Knowledge, Environmental Care Attitude, Emotional Value, and Green Marketing affect Green Purchase Intention
DOI: 10.15468/dl.4jsxgs
title: Occurrence Download

description: A dataset containing 4013 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Synodus variegatus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 4013 records from 110 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002142-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s3pnza
title: Occurrence Download

description: A dataset containing 12957 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lablab purpureus"
 ]
}

 The dataset includes 12957 records from 374 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002141-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14677725
title: BOS Kemdikbud
DOI: 10.71830/6ils40
title: Replication package for: Exploring Spatial and Biodiversity Data with Python and JupyterLab
title: Release version v1.8.0

description: &lt;b&gt;EN&lt;/b&gt; This is the archive replication package for the IOER Jupyter-Book NFDI4Biodiversity training materials, available at &lt;a href="https://training.fdz.ioer.info/"&gt;training.fdz.ioer.info&lt;/a&gt; and developed in the git repository &lt;a href="https://gitlab.hrz.tu-chemnitz.de/ioer/fdz/jupyter-book-nfdi4biodiversity"&gt;gitlab.hrz.tu-chemnitz.de/ioer/fdz/jupyter-book-nfdi4biodiversity&lt;/a&gt;. The Jupyter Book is designed to help students, researchers, scientists and enthusiasts get started with data-driven research and good scientific practices for data handling and publication using Python and Jupyter notebooks. In particular, the Jupyter Book focuses on the use case of accessing biodiversity data from the GBIF Application Programming Interface (API) and merging it with spatial environmental data from the IOER Monitor API for spatial analysis and visualisation. This package contains the source code, example data, generated outputs (as of the archival date), and configuration files necessary to reproduce the training materials website and the analyses presented within the notebooks.&lt;br&gt;&lt;br&gt;

&lt;b&gt;DE&lt;/b&gt;: Dies ist das Archiv-Replikationspaket für das IÖR Jupyter-Buch NFDI4Biodiversity Schulungsmaterial, das unter &lt;a href="https://training.fdz.ioer.info/"&gt;training.fdz.ioer.info&lt;/a&gt; verfügbar ist und im Git-Repository &lt;a href="https://gitlab.hrz.tu-chemnitz.de/ioer/fdz/jupyter-book-nfdi4biodiversity"&gt;gitlab.hrz.tu-chemnitz.de/ioer/fdz/jupyter-book-nfdi4biodiversity&lt;/a&gt; entwickelt wurde. Das Jupyter-Buch soll Studenten, Forschern, Wissenschaftlern und Enthusiasten den Einstieg in die datengesteuerte Forschung und gute wissenschaftliche Praxis für die Datenverarbeitung und -veröffentlichung mittels Python und Jupyter Notebooks erleichtern. Das Jupyter-Buch konzentriert sich insbesondere auf den Anwendungsfall des Zugriffs auf Biodiversitätsdaten aus der GBIF-Anwendungsprogrammierschnittstelle (API) und deren Zusammenführung mit räumlichen Umweltdaten aus der IÖR-Monitor-API zur räumlichen Analyse und Visualisierung. Dieses Paket enthält den Quellcode, Beispieldaten, generierte Ergebnisse (Stand des Archivierungsdatums) und Konfigurationsdateien, die notwendig sind, um die Website der Schulungsmaterialien und die in den Notebooks dargestellten Analysen zu reproduzieren.
description: JupyterLab, v4.4.2
description: Carto-Lab Docker, v0.28.0
description: Replication Package
DOI: 10.5281/zenodo.18432544
title: PRONUNCIATION DIFFICULTIES EXPERIENCED BY UZBEK LEARNERS OF ENGLISH

description: Despite being an essential part of spoken communication, pronunciation is still one of the most difficult parts of learning English for Uzbek speakers. Learners frequently struggle to produce accurate and understandable speech because Uzbek and English sound systems differ significantly. The main pronunciation issues that Uzbek English language learners face are examined in this study, along with the causes of these issues. Undergraduate EFL students' classroom observations and questionnaires were used to gather data. The results show that vowel and consonant sounds, word stress, phrase stress, and intonation are the primary areas where issues arise. In order to increase students' speaking proficiency, the study highlights the significance of targeted pronunciation training and frequent oral practice.
DOI: 10.5281/zenodo.18432543
title: PRONUNCIATION DIFFICULTIES EXPERIENCED BY UZBEK LEARNERS OF ENGLISH

description: Despite being an essential part of spoken communication, pronunciation is still one of the most difficult parts of learning English for Uzbek speakers. Learners frequently struggle to produce accurate and understandable speech because Uzbek and English sound systems differ significantly. The main pronunciation issues that Uzbek English language learners face are examined in this study, along with the causes of these issues. Undergraduate EFL students' classroom observations and questionnaires were used to gather data. The results show that vowel and consonant sounds, word stress, phrase stress, and intonation are the primary areas where issues arise. In order to increase students' speaking proficiency, the study highlights the significance of targeted pronunciation training and frequent oral practice.
DOI: 10.15468/dl.4bypm3
title: Occurrence Download

description: A dataset containing 17423 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Polistes metricus"
 ]
}

 The dataset includes 17423 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002143-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f9yaf5
title: Occurrence Download

description: A dataset containing 1830 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Atriplex polycarpa (Torr.) S.Watson",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1970",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 1000",
 "Country is United States of America",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 1830 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007377-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rv6nxs
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-107.6688 23.39913, -107.5188 23.39913, -107.5188 23.54913, -107.6688 23.54913, -107.6688 23.39913))"
 ]
}

 The dataset includes 8 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034685-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7v9fjb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hiodon tergisus",
 "HasCoordinate is true",
 "Geometry POLYGON((-78 12, -73 12, -73 0, -78 0, -78 12))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034686-251025141854904/datasets/export for details.
DOI: 10.15468/dl.h7t746
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-107.5188 23.39913, -107.3688 23.39913, -107.3688 23.54913, -107.5188 23.54913, -107.5188 23.39913))"
 ]
}

 The dataset includes 10 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034687-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.