cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.2908/ilc_ats21
title: Persons in households paying for professional homecare services received within the household by disability (activity limitation) and difficulty to pay professional homecare services
title: Personnes des ménages payant des services professionnels de soins à domicile reçus au sein du ménage, selon le handicap (limitation d’activité) et la difficulté à payer ces services professionnels de soins à domicile
title: Personen in Haushalten, die für im Haushalt erbrachte professionelle häusliche Pflegeleistungen zahlen, nach Behinderung (Aktivitätseinschränkung) und Schwierigkeit, diese professionellen häuslichen Pflegeleistungen zu bezahlen

description: Dieser Indikator misst den Anteil der Personen, die in einem Haushalt leben, der für professionelle häusliche Pflegeleistungen bezahlt, die im Haushalt erbracht werden. Die Daten werden alle sechs Jahre im EU-SILC-Modul „Zugang zu Dienstleistungen“ erhoben. Die Ergebnisse werden nach Behinderung (Aktivitätseinschränkung) und der Schwierigkeit, professionelle häusliche Pflegeleistungen zu bezahlen, aufgeschlüsselt.
description: This indicator measures the share of persons living in a household paying for professional homecare services received within the household. The data are collected every six years in the EU-SILC module on ‘access to services’. The results are broken down by sdisability (activity limitation) and difficulty to pay professional homecare services.
description: Cet indicateur mesure la part des personnes vivant dans un ménage qui paie des services professionnels de soins à domicile reçus au sein du ménage. Les données sont collectées tous les six ans dans le module EU-SILC sur « l’accès aux services ». Les résultats sont ventilés selon le handicap (limitation d’activité) et la difficulté à payer les services professionnels de soins à domicile.
DOI: 10.15468/dl.gbvdae
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Procyon lotor",
 "HasCoordinate is true",
 "Country is Norway"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000726-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/g2bk1g
title: Replication Data for: Countering Misinformation Early: Evidence from a Classroom-Based Field Experiment in India

description: Misinformation poses serious risks for democratic governance, conflict, and health. This study evaluates whether sustained, classroom-based education against misinformation can equip schoolchildren to become more discerning consumers of information. Partnering with a state government agency in Bihar, India, we conducted a field experiment in 583 villages with 13,500 students, using a 4-month curriculum designed to build skills, shift norms, and enhance knowledge about health misinformation. Intent-to-treat estimates demonstrate that treated respondents were significantly better at discerning true from false information, altered their health preferences, relied more on science, and reduced their dependence on unreliable news sources. We resurveyed participants 4 months post-intervention and found that effects persisted, as well as extended to political misinformation. Finally, we observe within-household treatment diffusion, with parents of treated students becoming more adept at discerning information. As many countries seek long-term solutions to combat misinformation, these findings highlight the promise of sustained classroom-based education.
description: <strong>APSR Data Editors' Note:</strong> APSR Data Editors have reviewed included documentation for completeness and have successfully reproduced all figures and tables in the article using the code and data included in this deposit. Data editors do not review results presented in appendices or supplementary materials.
DOI: 10.15468/dl.8dwjfb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "CoordinateUncertaintyInMeters 0.0-120.0",
 "HasCoordinate is True",
 "HasGeospatialIssue is False",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae",
 {
 "or" : [
 "GadmGid is U",
 "GadmGid is S",
 "GadmGid is A",
 "GadmGid is .",
 "GadmGid is 4",
 "GadmGid is 5",
 "GadmGid is _",
 "GadmGid is 1"
 ]
 },
 "Year 2010-2025"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000727-251009101135966/datasets/export for details.
DOI: 10.82144/86aaf0c5
title: Visual contacts from research cruises in the Med sea, 1994-2001

description: Original provider:
Claudio Fossati, University of Pavia

Dataset credits:
Claudio Fossati and Giulia Romè, CIBRA Center for Bioacoustics, University of Pavia

Abstract:
CIBRA Center for Bioacoustics, Univ. of Pavia, organizes research cruises in the Med sea since 1994. Visual and acoustic contacts (1994 - 2001) are available on OBIS-SEAMAP, while acoustic recordings are stored in our Sound library and available upon request.
DOI: 10.15468/dl.yc9w6v
title: Occurrence Download

description: A dataset containing 5488615 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "Geometry POLYGON((-78.39835 0.69328,-74.13441 0.69754,-74.39023 4.22311,-78.39835 4.22311,-78.39835 0.69328))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Animalia"
 ]
}

 The dataset includes 5488615 records from 953 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011180-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15300711
title: India Healthtech Market 2024 To 2033

description: India Healthtech Market Size, Trends and Insights By Technology (Digital Health Systems, Health Analytics, Health Information Technology, mHealth, Telehealthcare), By Component (Hardware, Software, Services), By End-User (Healthcare Providers, Healthcare Payers, Healthcare Consumers, Pharmaceutical Companies, Others), By Applications (Cardiology, Diabetes, Neurology, Sleep Apnea, Oncology, Others), By Delivery Modes (Cloud-Based, On-premises), and By Region - Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2024–2033.

Reports Description

India Healthtech Market was valued at USD 6,500 Million in 2024 and is expected to reach USD 78,374.3 Million by 2033, at a CAGR of 28.67%% during the forecast period 2024 – 2033.

Healthtech, short for Healthcare technology, is the broad term for any technology that is used in the healthcare industry. This can include a wide range of things, from medical devices and wearables to electronic health records (EHR) systems and telemedicine platforms.

Healthtech has the potential to improve the quality, efficiency, and affordability of healthcare. For example, telemedicine can make it easier for patients to access care, while wearables can help patients track their health and wellness goals.

The healthtech market is booming, driven by factors such as the aging population, the rising cost of healthcare, and the increasing demand for convenient and accessible care. The healthtech market is constantly evolving, and new technologies are emerging all the time. This is an exciting time for the healthcare industry, as healthtech has the potential to revolutionize the way we deliver and receive care.

For more information, DOWNLOAD FREE SAMPLE Now at https://www.custommarketinsights.com/request-for-free-sample/?reportid=45742
DOI: 10.5281/zenodo.15300712
title: India Healthtech Market 2024 To 2033

description: India Healthtech Market Size, Trends and Insights By Technology (Digital Health Systems, Health Analytics, Health Information Technology, mHealth, Telehealthcare), By Component (Hardware, Software, Services), By End-User (Healthcare Providers, Healthcare Payers, Healthcare Consumers, Pharmaceutical Companies, Others), By Applications (Cardiology, Diabetes, Neurology, Sleep Apnea, Oncology, Others), By Delivery Modes (Cloud-Based, On-premises), and By Region - Industry Overview, Statistical Data, Competitive Analysis, Share, Outlook, and Forecast 2024–2033.

Reports Description

India Healthtech Market was valued at USD 6,500 Million in 2024 and is expected to reach USD 78,374.3 Million by 2033, at a CAGR of 28.67%% during the forecast period 2024 – 2033.

Healthtech, short for Healthcare technology, is the broad term for any technology that is used in the healthcare industry. This can include a wide range of things, from medical devices and wearables to electronic health records (EHR) systems and telemedicine platforms.

Healthtech has the potential to improve the quality, efficiency, and affordability of healthcare. For example, telemedicine can make it easier for patients to access care, while wearables can help patients track their health and wellness goals.

The healthtech market is booming, driven by factors such as the aging population, the rising cost of healthcare, and the increasing demand for convenient and accessible care. The healthtech market is constantly evolving, and new technologies are emerging all the time. This is an exciting time for the healthcare industry, as healthtech has the potential to revolutionize the way we deliver and receive care.

For more information, DOWNLOAD FREE SAMPLE Now at https://www.custommarketinsights.com/request-for-free-sample/?reportid=45742
DOI: 10.15156/bio/sh0168777.10fu
title: SH0168777.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0168778.10fu
title: SH0168778.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0168779.10fu
title: SH0168779.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0168780.10fu
title: SH0168780.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0168781.10fu
title: SH0168781.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0168782.10fu
title: SH0168782.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0168783.10fu
title: SH0168783.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0168784.10fu
title: SH0168784.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.25921/esff-pv90
title: National Coral Reef Monitoring Program: Erosion data from bioerosion monitoring units (BMUs) deployed at select coral reef sites in the Pacific Ocean

description: The erosion rates provided in this collection were gathered from bioerosion monitoring units (BMUs) retrieved at existing long-term monitoring sites at Wake Island and the Hawaiian and Mariana Archipelagos during NOAA Pacific Islands Fisheries Science Center (PIFSC), Coral Reef Ecosystem Program (CREP) led National Coral Reef Monitoring Program (NCRMP) missions. The samples were analyzed at NOAA’s Atlantic Oceanographic and Meteorological Laboratory (AOML), as part of NOAA's ongoing NCRMP. BMUs are constructed from clean coral skeletons and left on the reef for a period of 3 years. This collection of data contains the first run of BMUs that has ever been produced, and as such, the protocol established at the time was shortly thereafter amended in order to give a more thorough picture of bioerosion rates. Early analysis procedures utilized a benchtop micro computed tomography scanner (microCT, Bruker) for initial scans (pre-deployment), while post collection analyses (including those in this collection) were analyzed by a larger Computed Tomography device (CT scanner, Siemens).

BMUs are CT scanned for changes in density, volume and mass in which rates of bioerosion can be assessed. Annual erosion and accretion rates can be determined from these data in terms of loss of reef structure volume as well as mass in grams of calcium carbonate. Accretion rates given in this collection are determined by finding the volume of non-original carbonate material found on the external surface of the BMUs divided by the number of years the BMU was deployed on the reef. These rates can detect accretion signals when calcifying organisms, such as corals or algae, have grown on their exteriors. Rates of macroboring were determined by changes in the internal volume of the BMUs (e.g., that removed by bore holes) divided by the number of years the BMU was deployed on the reef. Macroboring can occur from eroders such as clionaid sponges, annelids and other macroboring fauna.
DOI: 10.15156/bio/sh0168785.10fu
title: SH0168785.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0168786.10fu
title: SH0168786.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.