cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1376876.08fu
title: SH1376876.08FU

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/sh1376877.08fu
title: SH1376877.08FU

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/sh1583549.08fu
title: SH1583549.08FU

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: 10.5281/zenodo.5749994
title: Data analysis of LiP-MS data for high-throughput applications

description: Proteins regulate biological processes by changing their structure or abundance to accomplish a specific function. In response to any perturbation or stimulus, protein structure may be altered by a variety of molecular events, such as post translational modifications, protein-protein interactions, aggregation, allostery, or binding to other molecules. The ability to probe these structural changes in thousands of proteins simultaneously in cells or tissues can provide valuable information about the functional state of a variety of biological processes and pathways. Here we present an updated protocol for LiP-MS, a proteomics technique combining limited proteolysis with mass spectrometry, to detect protein structural alterations in complex backgrounds and on a proteome-wide scale (Cappelletti et al., 2021; Piazza et al., 2020; Schopper et al., 2017). We describe advances in the throughput and robustness of the LiP-MS workflow and implementation of data-independent acquisition (DIA) based mass spectrometry, which together achieve high reproducibility and sensitivity, even on large sample sizes. In addition, we introduce MSstatsLiP, an R package dedicated to the analysis of LiP-MS data for the identification of structurally altered peptides and differentially abundant proteins. Altogether, the newly proposed improvements expand the adaptability of the method and allow for its wide use in systematic functional proteomic studies and translational applications.
description: Here we provide any code relating to the "Proteome-wide structural changes measured with limited proteolysis-mass spectrometry: an advanced protocol for high-throughput applications" publication (Malinovska et al.)
DOI: 10.5281/zenodo.5749993
title: Data analysis of LiP-MS data for high-throughput applications

description: Proteins regulate biological processes by changing their structure or abundance to accomplish a specific function. In response to any perturbation or stimulus, protein structure may be altered by a variety of molecular events, such as post translational modifications, protein-protein interactions, aggregation, allostery, or binding to other molecules. The ability to probe these structural changes in thousands of proteins simultaneously in cells or tissues can provide valuable information about the functional state of a variety of biological processes and pathways. Here we present an updated protocol for LiP-MS, a proteomics technique combining limited proteolysis with mass spectrometry, to detect protein structural alterations in complex backgrounds and on a proteome-wide scale (Cappelletti et al., 2021; Piazza et al., 2020; Schopper et al., 2017). We describe advances in the throughput and robustness of the LiP-MS workflow and implementation of data-independent acquisition (DIA) based mass spectrometry, which together achieve high reproducibility and sensitivity, even on large sample sizes. In addition, we introduce MSstatsLiP, an R package dedicated to the analysis of LiP-MS data for the identification of structurally altered peptides and differentially abundant proteins. Altogether, the newly proposed improvements expand the adaptability of the method and allow for its wide use in systematic functional proteomic studies and translational applications.
description: Here we provide any code relating to the "Proteome-wide structural changes measured with limited proteolysis-mass spectrometry: an advanced protocol for high-throughput applications" publication (Malinovska et al.)
DOI: 10.6084/m9.figshare.21856749
title: MAT_cult.sav

description: This is the dataset (MAT_cult) of a cross-sectional study focused on examining the relationships between cultural dimensions, emotional intelligence, resilience and subjective well-being in Spanish adult population. The sample is composed of 3,419 participants. The main measures are: the <em>Individual Cultural Values Scale</em> (CVSCALE), the <em>Trait Meta Mood Scale</em> (TMMS), the <em>Connor Davidson Resilience Scale</em> (CD-RISC-10-item), the <em>International Positive and Negative Affect Schedule Short-Form</em> (PANAS-SF), and the <em>Satisfaction With Life Scale</em> (SWLS). The dataset also includes some other sociodemographic variables easily identifiable by its labels.
DOI: 10.21227/st74-ja80
title: VTS 2022 AAM Concepts Innovation Challenge - Hermes

description: We present Hermes – a novel, low-cost, wireless, batteryless, energy harvesting system for aerial vehicles for sensing wind speed and Angle of Attack (AoA) concurrently. Hermes comprises a set of piezoelectric films which flutter due to incoming wind and the characteristics of this aeroelastic flutter are utilized for determining the wind speed and AoA of the head-wind. Hermes consists of five piezoelectric flags that are mounted on rigid clamps specifically placed at different angles. We designed Hermes to maximize the sensing performance and energy harvesting capability simultaneously, without compromising either accuracy or harvesting efficiency. Our current prototype can harvest the power of 440 μW on average. Over a wide range AoA from -10° to 30°, the estimation of the wind speed is within 0.7 km/h error with 90% probability, and AoA error is within 1.2° with 90% probability. Since Hermes necessitates no wires and batteries and is a low-cost sensor, it is well suited for a range of UAVs, gliders, and aircraft, which require flexible sensor placement and do not require new wiring, which is often complex in aircraft. Hermes is the first of its kind that exploits piezoelectric energy harvesting to simultaneously sense AoA and wind speed.
DOI: 10.2908/t2020_rd100
title: Productivity of artificial land
title: Productivité des sols artificiels
title: Produktivität der künstlich angelegten Flächen

description: Produktivität der künstlich angelegte Flächen ist definiert als das Bruttoinlandsprodukt (BIP) eines Landes dividiert durch die gesamten künstlich angelegte Flächen. Künstlich angelegte Flächen bestehen aus bebauten Flächen (Flächen mit Gebäuden und Gewächshäusern) und außerhalb geschlossener Ortschaften aus Straßen und versiegelten Flächen. Die Produktivität künstlich angelegter Flächen zeigt, ob bebaute und unbebaute Gebiete wirksam genutzt werden und einen wirtschaftlichen Mehrwert erzeugen. Für die Berechnung der künstlichen Bodenproduktivität verwendet Eurostat das BIP in KKS (Kaufkraftstandard). Diese Einheit erlaubt einen Vergleich der Länder innerhalb des gleichen Jahres. Weitere Informationen über Bodenbedeckung/Bodennutzung hier.
description: Productivity of artificial land is defined as the gross domestic product (GDP) of a country divided by its total artificial land. Artificial land consists of built-up areas (areas covered with buildings and greenhouses) and non built-up areas (streets and sealed surfaces). Artificial land productivity shows whether built-up and non built-up areas are efficiently used to generate added economic value. For the calculation of artificial land productivity Eurostat uses the GDP in millions of PPS (Purchasing Power Standard). This unit allows to compare countries for the same year. More information on land cover/land use can be found here.
description: La productivité des sols artificiels est définie comme le produit intérieur brut (PIB) d'un pays divisé par la totalité de ses sols artificiels. Les sols artificiels se composent de zones bâties (les zones couvertes de bâtiments et les serres) et les zones non bâties (les routes et les surfaces étanches). La productivité des sols artificiels indique que les zones bâties et non bâties sont efficacement utilisées pour générer de la valeur ajoutée économique. Pour le calcul de la productivité des sols artificiels, Eurostat utilise le PIB en millions de SPA (Standard de Pouvoir d'Achat). Cette unité permet de comparer les pays pour la même année. Plus d'informations sur la couverture des sols / utilisation des sols peuvent être trouvés ici.
DOI: 10.2908/t2020_rd110
title: Built-up areas
title: Terrains bâtis
title: Bebaute Gebiete

description: Der Indikator misst i) die gesamte bebaute Fläche eines Landes (in km²) und ii) die bebaute Fläche als Anteil der Gesamtfläche des Landes. Bebaute Gebiete sind Gebiete mit Gebäuden und Gewächshäusern, wobei unbebaute Gebiete Straßen und versiegelten Flächen umfassen. Land ist eine begrenzte Ressource und wenn es zur Stadtentwicklung und der städtischen Infrastruktur genutzt wird, ist diese Entwicklung kaum noch reversible. Dazu werden landwirtschaftliche Flächen und fragmentierte Lebensräume benutzt, welches ein Risiko für diese natürlichen Ressourcen darstellen. Die Daten wurden aus der statistischen Stichprobenerhebung zur Bodennutzung/Bodenbedeckung (LUCAS) bezogen. Weitere Informationen sind hiereinzusehen.
description: The indicator measures i) the total built-up area in a country (in km2) and ii) the total built-up area as a share of the total surface area of land in the country. Built-up areas are areas covered with buildings and greenhouses whereas non built-up areas include streets and sealed surfaces. Land is a finite resource and land taken by urban development and infrastructure presents a high risk of being irreversible. It consumes mostly agricultural land and increases fragmentation of habitats, thus causing risk to these natural resources. The data refers to the land use/cover area frame survey (LUCAS). More information can be found here.
description: L’indicateur mesure i) le total de terrains bâtis dans un pays (en km²) et ii) le total de terrains bâtis en tant que part de la surface totale de terre dans le pays. Les terrains bâtis sont des zones couvertes par des bâtiments et des serres tandis que les terrains non-bâtis incluent les routes et les surfaces imperméables. La terre est une ressource limitée et les terres occupées par le développement urbain et par des infrastructures présentent un risque élevé de non réversibilité. Cela utilise principalement des terres agricoles et augmente la fragmentation des habitats, et donc cause un risque sur ces ressources naturelles. Les données réfèrent à l’enquête sur la couverture des sols/l’utilisation des sols (LUCAS). Plus d’informations sont disponibles ici.
DOI: 10.2908/t2020_rd320
title: Energy dependence
title: Dépendance énergétique
title: Energieabhängigkeit

description: Der Indikator zeigt, in welchem Umfang eine Wirtschaft auf Importe angewiesen ist, um ihren Energiebedarf zu decken. Es wird berechnet als Nettoimporte dividiert durch die Brutto verfügbare Energie. Energieabhängigkeit = Nettoimporte / Brutto verfügbare Energie. Nettoimporte werden als Gesamtimporte minus Gesamtexporte berechnet. Brutto verfügbare Energie ist ein berechneter Wert, definiert als: Primärproduktion + wiedergewinnung & wiederverwertete Produkte + Importe - Exporte + Bestandsveränderungen. Die Energieabhängigkeit kann bei den Nettoexporteurländern negativ sein, während positive Werte über 100% auf die Anhäufung von Beständen während des Referenzjahres hinweisen.
description: The indicator shows the extent to which an economy relies upon imports in order to meet its energy needs. It is calculated as net imports divided by the gross available energy. Energy dependence = Net imports / Gross available energy. Net imports are calculated as total imports minus total exports. Gross available energy is a calculated value, defined as: Primary production + Recovered & recycled products + Imports – Exports + Stock changes Energy dependency may be negative in the case of net exporter countries while positive values over 100 % indicate the accumulation of stocks during the reference year.
description: Cet indicateur montre à quel degré une économie dépend des importations pour faire face à ses besoins énergétiques. Il est calculé comme le ratio entre les importations nettes et l'énergie disponible brute. La dépendance énergétique = importations nettes /énergie disponible brute. Les importations nettes sont calculées comme les importations totales moins les exportations totales. L'énergie disponible brute est une valeur calculée, définie comme suit : production primaire + produits récupérés & recyclés + importations - exportations + variation de stock. La dépendance énergétique peut être négative dans le cas des pays exportateurs nets, tandis que des valeurs positives supérieures à 100% indiquent une accumulation de stocks au cours de l'année de référence.
DOI: 10.6084/m9.figshare.21856791.v1
title: No Relationship between Male Pubertal Timing and Depression – New Insights from Epidemiology and Mendelian Randomization

description: Genetic data
DOI: 10.6084/m9.figshare.21856791
title: No Relationship between Male Pubertal Timing and Depression – New Insights from Epidemiology and Mendelian Randomization

description: Genetic data
DOI: 10.2908/t2020_rd330
title: Share of renewable energy in gross final energy consumption
title: Part des énergies renouvelables dans la consommation finale brute d'énergie
title: Anteil erneuerbarer Energien am Bruttoendenergieverbrauch

description: Der Indikator misst den Anteil des Verbrauchs erneuerbarer Energien am Bruttoendenergieverbrauch gemäß der Richtlinie Erneuerbare Energien. Der Bruttoendenergieverbrauch ist der Energieverbrauch der Endverbraucher (Endenergieverbrauch) zuzüglich der Netzverluste und des Eigenverbrauchs der Kraftwerke. Dieser Indikator wird auf der Grundlage der Richtlinie 2009/28/EG zur Förderung der Nutzung von Energie aus erneuerbaren Quellen berechnet. Die Berechnung basiert auf Daten, die im Rahmen der Energiestatistik Verordnung (EG) Nr. 1099/2008 erhoben und durch spezifische Zusatzdaten ergänzt wurden, die von den nationalen Verwaltungen an Eurostat übermittelt wurden. In einigen Ländern sind die statistischen Systeme noch nicht vollständig entwickelt, um alle Anforderungen der Richtlinie 2009/28/EG zu erfüllen, insbesondere in Bezug auf die Umgebungswärme, die von Wärmepumpen aus der Umgebung gewonnen wird.
description: The indicator measures the share of renewable energy consumption in gross final energy consumption according to the Renewable Energy Directive. The gross final energy consumption is the energy used by end-consumers (final energy consumption) plus grid losses and self-consumption of power plants. This indicator is calculated on the basis of Directive 2009/28/EC on the promotion of the use of energy from renewable sources. The calculation is based on data collected in the framework of Regulation (EC) No 1099/2008 on energy statistics and complemented by specific supplementary data transmitted by national administrations to Eurostat. In some countries the statistical systems are not yet fully developed to meet all requirements of Directive 2009/28/EC, in particular with respect to ambient heat captured from the environment by heat pumps.
description: L'indicateur mesure la part des énergies renouvelables dans la consommation finale brute d'énergie selon la Directive sur l'énergie renouvelable. La consommation finale brute d'énergie est l'énergie utilisée par les consommateurs finaux (consommation finale d'énergie) plus les pertes sur le réseau et la consommation propre des centrales électriques. Cet indicateur est calculé sur la base de la Directive 2009/28/CE sur la promotion de l’utilisation de l’énergie provenant des sources renouvelables. Le calcul est basé sur les données collectées dans le cadre du Règlement (CE) n° 1099/2008 sur les statistiques de l’énergie et complété par des données spécifiques additionnelles transmises à Eurostat par des administrations nationales. Dans certains pays les systèmes statistiques ne sont pas encore totalement développés pour répondre aux exigences de la Directive 2009/28/CE, en particulier par rapport à la chaleur ambiante captée de l'environnement par les pompes à chaleur.
DOI: 10.2908/t2020_rk310
title: Modal split of passenger transport
title: Répartition modale du transport de voyageurs
title: Personenbeförderung nach Verkehrszweig

description: Dieser Indikator wird definiert als der Prozentanteil jedes Verkehrszweiges am Gesamtverkehr zu Lande in Personenkilometern. Der Personenverkehr zu Lande schließt die Personenbeförderung in Pkw, Linien- sowie Reisebussen und Zügen ein. Alle Daten sollen anhand von Bewegungen innerhalb des Staatsgebiets - unabhängig von der Nationalität des Fahrzeugs - ermittelt werden. Die Datenerfassungsmethode ist auf dem EU-Ebene jedoch nicht harmonisiert.
description: This indicator is defined as the percentage share of each mode of transport in total inland transport, expressed in passenger-kilometres (pkm). It is based on transport by passenger cars, buses and coaches, and trains. All data should be based on movements on national territory, regardless of the nationality of the vehicle. However, the data collection methodology is not harmonised at the EU level.
description: Cet indicateur est défini comme la part en pourcentage de chaque mode de transport dans le total des transports intérieurs, mesurés en passager-kilomètre (pkm). L'indicateur comprend les transports par route, rail et voies navigables intérieures. Les données sont censées se fondre sur les déplacements sur le territoire national, indépendamment de la nationalité du véhicule ou navire. Néanmoins, la méthodologie de collecte de données n'est pas harmonisée au niveau de l'UE.
DOI: 10.2908/t2020_rk320
title: Modal split of freight transport
title: Répartition modale du transport de fret
title: Güterverkehr nach Verkehrszweig

description: Dieser Indikator wird definiert als der Prozentanteil jedes Verkehrszweiges am Gesamtverkehr zu Lande in Tonnenkilometern. Dieser Indikator umfasst den Güterverkehr auf der Straße, der Schiene und den Binnenwasserwegen. Der Güterverkehr auf der Straße wird anhand der Bewegung sämtlicher im Meldeland registrierten Fahrzeuge ermittelt. Der Güterverkehr auf Schiene und Binnenwasserwegen wird anhand von Bewegungen innerhalb des Staatsgebiets - unabhängig von der Nationalität des Fahrzeugs oder Schiffs - ermittelt, aber es gibt je nach Land teilweise Abweichungen von dieser Definition.
description: This indicator is defined as the percentage share of each mode of transport in total inland transport expressed in tonne-kilometres (tkm). It includes transport by road, rail and inland waterways. Road transport is based on all movements of vehicles registered in the reporting country. Rail and Inland waterways transport is generally based on movements on national territory, regardless of the nationality of the vehicle or vessel, but there are some variations in definitions from country to country.
description: Cet indicateur est défini comme la part en pourcentage de chaque mode de transport dans le total des transports intérieurs, mesurés en tonne-kilomètre (tkm). L'indicateur comprend les transports par route, rail et voies navigables intérieures. Les données sur le transport routier se fondent sur tous les déplacements de véhicules immatriculés dans le pays déclarant. En ce qui concerne le rail et les voies navigables intérieures, les données sur le transport se fondent sur les déplacements sur le territoire national, indépendamment de la nationalité du véhicule ou navire, mais il y a certaines variations dans les définitions d'un pays à l'autre.
DOI: 10.2908/t2020_rk330
title: Moyenne des émissions de CO2 par kilomètre provenant de véhicules particuliers neufs (source: AEE, DG-CLIMA)
title: Average CO2 emissions per km from new passenger cars (source: EEA, DG-CLIMA)
title: Durchschnittlicher CO2- Ausstoß pro km von neuen Personenkraftwagen (Quelle: EUA, DG-CLIMA)

description: Dieser Indikator beschreibt den durchschnittlichen Kohlendioxyd-Ausstoß pro Kilometer von registrierten Neuwagen in einem Jahr.
description: This indicator is defined as the average emissions of carbon dioxide per kilometre by new passenger cars registered in a given year.
description: Cet indicateur est défini comme les émissions moyennes de dioxyde de carbone par kilomètre pour les véhicules particuliers neufs enregistrés au cours d´une année donnée.