cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.gxez3k
title: Occurrence Download

description: A dataset containing 2498 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bauhinia variegata",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 2498 records from 273 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005764-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qw99hg
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Anotomys leander"
 ]
}

 The dataset includes 22 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005766-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2cpcz5
title: Occurrence Download

description: A dataset containing 49100 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Bistorta",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 49100 records from 370 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005765-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17174836
title: Paper: "Modeling climate-change impacts on the suitable habitat of Myristica yunnanensis using MaxEnt and Biomod2" research data, code, ruanj
DOI: 10.5281/zenodo.17174837
title: Paper: "Modeling climate-change impacts on the suitable habitat of Myristica yunnanensis using MaxEnt and Biomod2" research data, code, ruanj
DOI: 10.15468/dl.w5b7hu
title: Occurrence Download

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

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005767-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cznk5d
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyperus cyperoides",
 "Country is Samoa",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005769-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c6p3bf
title: Occurrence Download

description: A dataset containing 67 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyperus cyperoides",
 "Country is Papua New Guinea",
 "HasCoordinate is true"
 ]
}

 The dataset includes 67 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005768-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8yj764
title: Occurrence Download

description: A dataset containing 76881 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Naturbase - funksjonsområder for arter"
 ]
}

 The dataset includes 76881 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005751-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/7yt5dv
title: Observation and analysis of lower-hybrid-current-drive density limit in EAST

description: Lower hybrid current drive (LHCD) experiments with line-averaged density up to ~ 5.1x 1019/m3 were performed in EAST L-mode plasmas. When the line-averaged density rises above a critical value, the hard X-ray (HXR) emission fall to the noise level, indicating that the LHCD density limit is encountered. The experimental results show that the LHCD density limit can be increased with higher wave source frequency (f0) and higher magnetic field (Bt). Although a higher LHCD density limit is obtained by a higher magnetic field for both 2.45 GHz and 4.6 GHz waves, the results show a stronger dependence on the magnetic field for the 4.6 GHz case. Analysis suggests that, for the normal operation with relatively low magnetic field (1.6 T &lt; Bt &lt; 2.5T) on EAST, the dominant mechanisms responsible for the LHCD density limit are different between the 2.45 GHz and 4.6 GHz waves. The wave accessibility plays a more significant role during 4.6 GHz LHCD experiments, while parasitic losses due to parametric decay instability (PDIs) dominate the accessibility issue in the 2.45 GHz case. Collisional loss in the scrape-off layer (SOL) may explain the 4.6 GHz result when combined with the accessibility limit at high density and low temperature.
description: CITATION: M.H. Li et al 2022 Nucl. Fusion 62 126055<br><br>PUBLISHED VERSION DOI: http://doi.org/10.1088/1741-4326/ac99ed<br><br>PSFC REPORT PSFC/JA-22-130<br><br>This work is supported by the National Natural Science Foundation of China (Grant Nos. 11775259, 11975266, 11805233 and 11975276), the Comprehensive Research Facility for Fusion Technology Program of China under Contract No. 2018-000052-73-01-001228, Anhui Provincial Natural Science Foundation No. 2008085J04, and an International Collaboration Grant No. DE‐SC0010492 from the US Department of Energy.<br><br>If this record does not contain the full text, then the manuscript has been embargoed by the publisher thus restricting open access for 12 to 24 months after publication.
DOI: 10.15454/9dzlra
title: Replication Data for: Nutrition Transition and the Structure of Global Food Demand

description: Estimating future demand for food is a critical aspect of global food security analyses. The process linking dietary changes to wealth is known as the nutrition transition and presents well-identified features that help to predict consumption changes in poor countries. This study proposes to represent the nutrition transition with a nonhomothetic, flexible-in-income, demand system. The resulting model is estimated statistically based on cross-sectional information from FAOSTAT. It captures the main features of the nutrition transition: rise in demand for calories associated with income growth; diversification of diets away from starchy staples; and a large increase in caloric demand for animal-based products, fats, and sweeteners. The estimated model is used to project food demand between 2010 and 2050 based on a set of plausible futures (trend projections and Shared Socioeconomic Pathways scenarios). The main results of these projections are: (1) global food demand will increase by 47%, less than half the growth in the previous four decades; (2) this growth will be attributable mainly to lower-middle-income and low-income countries; (3) the structure of global food demand will change over the period, with a doubling of demand for animal-based calories and a much smaller 19% increase in demand for starchy staples; and (4) the analysis of a range of population and income projections reveals important uncertainties: depending on the scenario, the projected increases in demand for animal-based and vegetal-based calories range from 74 to 114% and from 20 to 42%, respectively.
DOI: 10.15468/dl.yupmug
title: Occurrence Download

description: A dataset containing 3589 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bellucia pentamera",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 3589 records from 178 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005771-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7807/immo:red:hm:suf:v11
title: RWI Real Estate Data - Houses for Rent - SUF
title: RWI Real Estate Data - Hausmiete - SUF
title: Version 11

description: ImmobilienScout24 is the largest real estate internet platform in Germany. Properties for private as well as commercial use are offered on the website. However, the data only cover residential properties. The dataset covers most characteristics collected on the platform like price, size and characteristics of the housing unit but also automatically generated items like the duration of the advertisement spell.
description: ImmobilienScout24 ist die größte Immobilien-Internetplattform in Deutschland. Auf der Website werden sowohl Immobilien zur privaten als auch zur gewerblichen Nutzung angeboten. Die Daten umfassen jedoch nur Wohnimmobilien. Der Datensatz umfasst die meisten auf der Plattform erhobenen Merkmale wie z.B. Preis, Größe und Ausstattung der Wohneinheit, aber auch generierte Informationen wie die Dauer der Inseratverfügbarkeit.
description: RWI-GEO-RED
description: RWI-GEO-RED
description: Computer-based observation
description: All houses for rent at ImmobilienScout24
description: Alle Häuser zur Miete auf der Webseite ImmobilienScout24
description: Full sample
DOI: 10.7807/immo:red:wk:suf:v11
title: RWI Real Estate Data - Apartments for Sale - SUF
title: RWI Real Estate Data - Wohnungskauf - SUF
title: Version 11

description: ImmobilienScout24 is the largest real estate internet platform in Germany. Properties for private as well as commercial use are offered on the website. However, the data only cover residential properties. The dataset covers most characteristics collected on the platform like price, size and characteristics of the housing unit but also automatically generated items like the duration of the advertisement spell.
description: ImmobilienScout24 ist die größte Immobilien-Internetplattform in Deutschland. Auf der Website werden sowohl Immobilien zur privaten als auch zur gewerblichen Nutzung angeboten. Die Daten umfassen jedoch nur Wohnimmobilien. Der Datensatz umfasst die meisten auf der Plattform erhobenen Merkmale wie z.B. Preis, Größe und Ausstattung der Wohneinheit, aber auch generierte Informationen wie die Dauer der Inseratverfügbarkeit.
description: RWI-GEO-RED
description: RWI-GEO-RED
description: Computer-based observation
description: All appartments for sale at ImmobilienScout24
description: Alle Wohnungen zum Verkauf auf der Webseite ImmobilienScout24
description: Full sample
DOI: 10.7807/immo:redx:suf:v14
title: Regional Real Estate Price Index for Germany - SUF, 2008-05/2024
title: Regional Real Estate Price Index for Germany - SUF, 2008-05/2024
title: Version 14

description: Based on the RWI-GEO-RED data that base on the data provided by ImmobilienScout24 hedonic housing price indices are estimated. The indices are on the grid level, LMR, district/county and municipality level. We conduct a hedonic price regression that covers characteristics of the object as well as regional fixed effects. The hedonic regression is estimated separately for houses for sale as well as apartments for rent and for sale. We also offer a combined index which combines the individual housing types into one index. There are three different specifications: First, the overall time development from 01/2008 to 05/2024 on grid level given yearly and quaterly; Second, cross-regional differences for each year separately and time development within one region from 01/2018 to 05/2024 (municipality, district, LMR, and grid level); third, the time-region fixed effect between 2008 and 2024, which is used to determine the price changes for all three region types to the base year of 2008.
description: Based on the RWI-GEO-RED data that base on the data provided by ImmobilienScout24 hedonic housing price indices are estimated. The indices are on the grid level, LMR, district/county and municipality level. We conduct a hedonic price regression that covers characteristics of the object as well as regional fixed effects. The hedonic regression is estimated separately for houses for sale as well as apartments for rent and for sale. We also offer a combined index which combines the individual housing types into one index. There are three different specifications: First, the overall time development from 01/2008 to 05/2024 on grid level given yearly and quaterly; Second, cross-regional differences for each year separately and time development within one region from 01/2018 to 05/2024 (municipality, district, LMR, and grid level); third, the time-region fixed effect between 2008 and 2024, which is used to determine the price changes for all three region types to the base year of 2008.
description: RWI-GEO-REDX
description: RWI-GEO-REDX
description: Other
description: The data is based on the data set RWI-GEO-RED, that collects all offers for private housing on ImmobilienScout24 between January 2008 and May 2024. ImmobilienScout24 is the largest listing website for real estate in Germany. The price indices are estimated labor market region, district and municipality level
description: The data is based on the data set RWI-GEO-RED, that collects all offers for private housing on ImmobilienScout24 between January 2008 and May 2024. ImmobilienScout24 is the largest listing website for real estate in Germany. The price indices are estimated labor market region, district and municipality level
description: Stratified random sampling
DOI: 10.7807/immo:redx:suf:v13
title: Regional Real Estate Price Index for Germany - SUF, 2008-11/2023
title: Regional Real Estate Price Index for Germany - SUF, 2008-11/2023
title: Version 13

description: Based on the RWI-GEO-RED data that base on the data provided by ImmobilienScout24 hedonic housing price indices are estimated. The indices are on the grid level, district/county and municipality level. We conduct a hedonic price regression that covers characteristics of the object as well as regional fixed effects. The hedonic regression is estimated separately for houses for sale as well as apartments for rent and for sale. We also offer a combined index which combines the individual housing types into one index. There are three different specifications: First, the overall time development from 01/2008 to 11/2023 on grid level given yearly and quaterly; Second, cross-regional differences for each year separately and time development within one region from 01/2018 to 11/2023 (municipality, district and grid level); third, the time-region fixed effect between 2008 and 2023, which is used to determine the price changes for all three region types to the base year of 2008 or year-quarter 2008-Q1.
description: Based on the RWI-GEO-RED data that base on the data provided by ImmobilienScout24 hedonic housing price indices are estimated. The indices are on the grid level, district/county and municipality level. We conduct a hedonic price regression that covers characteristics of the object as well as regional fixed effects. The hedonic regression is estimated separately for houses for sale as well as apartments for rent and for sale. We also offer a combined index which combines the individual housing types into one index. There are three different specifications: First, the overall time development from 01/2008 to 11/2023 on grid level given yearly and quaterly; Second, cross-regional differences for each year separately and time development within one region from 01/2018 to 11/2023 (municipality, district and grid level); third, the time-region fixed effect between 2008 and 2023, which is used to determine the price changes for all three region types to the base year of 2008 or year-quarter 2008-Q1.
description: RWI-GEO-REDX
description: RWI-GEO-REDX
description: Other
description: The data is based on the data set RWI-GEO-RED, that collects all offers for private housing on ImmobilienScout24 between January 2008 and November 2023. ImmobilienScout24 is the largest listing website for real estate in Germany. The price indices are estimated labor market region, district and municipality level.
description: The data is based on the data set RWI-GEO-RED, that collects all offers for private housing on ImmobilienScout24 between January 2008 and November 2023. ImmobilienScout24 is the largest listing website for real estate in Germany. The price indices are estimated labor market region, district and municipality level.
description: Stratified random sampling
DOI: 10.7807/immo:redx:puf:v13
title: Regional Real Estate Price Index for Germany - PUF, 2008-11/2023
title: Regional Real Estate Price Index for Germany - PUF, 2008-11/2023
title: Version 13

description: Based on the RWI-GEO-RED data that base on the data provided by ImmobilienScout24 hedonic housing price indices are estimated. The indices are on the grid level, district/county and municipality level. We conduct a hedonic price regression that covers characteristics of the object as well as regional fixed effects. The hedonic regression is estimated separately for houses for sale as well as apartments for rent and for sale. We also offer a combined index which combines the individual housing types into one index. There are three different specifications: First, the overall time development from 01/2008 to 11/2023 on grid level given yearly and quaterly; Second, cross-regional differences for each year separately and time development within one region from 01/2018 to 11/2023 (municipality, district and grid level); third, the time-region fixed effect between 2008 and 2023, which is used to determine the price changes for all three region types to the base year of 2008 or year-quarter 2008-Q1.
description: Based on the RWI-GEO-RED data that base on the data provided by ImmobilienScout24 hedonic housing price indices are estimated. The indices are on the grid level, district/county and municipality level. We conduct a hedonic price regression that covers characteristics of the object as well as regional fixed effects. The hedonic regression is estimated separately for houses for sale as well as apartments for rent and for sale. We also offer a combined index which combines the individual housing types into one index. There are three different specifications: First, the overall time development from 01/2008 to 11/2023 on grid level given yearly and quaterly; Second, cross-regional differences for each year separately and time development within one region from 01/2018 to 11/2023 (municipality, district and grid level); third, the time-region fixed effect between 2008 and 2023, which is used to determine the price changes for all three region types to the base year of 2008 or year-quarter 2008-Q1.
description: RWI-GEO-REDX
description: RWI-GEO-REDX
description: Other
description: The data is based on the data set RWI-GEO-RED, that collects all offers for private housing on ImmobilienScout24 between January 2008 and November 2023. ImmobilienScout24 is the largest listing website for real estate in Germany. The price indices are estimated labor market region, district and municipality level
description: The data is based on the data set RWI-GEO-RED, that collects all offers for private housing on ImmobilienScout24 between January 2008 and November 2023. ImmobilienScout24 is the largest listing website for real estate in Germany. The price indices are estimated labor market region, district and municipality level.
description: Stratified random sampling
DOI: 10.15468/dl.agukqz
title: Occurrence Download

description: A dataset containing 384 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Portulaca halimoides",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 384 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005772-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57745/7yvkdj
title: Replication data for: Estimating the Competitive Storage Model with Trending Commodity Prices

description: We present a method to estimate jointly the parameters of a standard commodity storage model and the parameters characterizing the trend in commodity prices. This procedure allows the influence of a possible trend to be removed without restricting the model specification, and allows model and trend selection based on statistical criteria. The trend is modeled deterministically using linear or cubic spline functions of time. The results show that storage models with trend are always preferred to models without trend. They yield more plausible estimates of the structural parameters, with storage costs and demand elasticities that are more consistent with the literature. They imply occasional stockouts, whereas without trend the estimated models predict no stockouts over the sample period for most commodities. Moreover, accounting for a trend in the estimation implies price moments closer to those observed in commodity prices. Our results support the empirical relevance of the speculative storage model, and show that storage model estimations should not neglect the possibility of long-run rice trends.
DOI: 10.15468/dl.rzq82q
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyperus cyperoides",
 "Country is Singapore",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005773-250920141307145/datasets/export for details.
DOI: 10.5525/gla.researchdata.2058
title: The Mere Exposure Effect in Voices [Closed Raw Data Archive]

description: Online experiment and questionnaire data from 2 studies that applied the mere exposure effect paradigm to voices.
DOI: 10.15468/dl.cqkdny
title: Occurrence Download

description: A dataset containing 362 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyperus cyperoides",
 "Country is South Africa",
 "HasCoordinate is true"
 ]
}

 The dataset includes 362 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005774-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3ch3d9
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyperus cyperoides",
 "Country is Tonga",
 "HasCoordinate is true"
 ]
}

 The dataset includes 8 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005775-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.