cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.13224311
title: ELITE SLWR: global 1km daily SLDR at SIN Grid   (2010_060-120)

description: The Essential thermal Infrared remoTe sEnsing (ELITE) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn).

 

This dataset is ELITE daily surface longwave downward radiation (SLDR) product at 1km spatial resolution. It is provided on a Sinusoidal grid and ranges from 2000 to 2022 (continuously updated). This dataset was generated from the ELITE surface longwave downward radiation (SLDR) product using the algorithms developed by Zeng et al. (2021).

 

This is the ELITE Daily SLDR product in 2010 (DOY: 060-120). Please click here to download the ELITE Daily SLDR product in 2010 (DOY: 121-181).

Dataset Characteristics:



Spatial Coverage: Global

Temporal Coverage: 2010-03-01 ~ 2010-04-30

Spatial Resolution: 1 km

Temporal Resolution: Daily

Data Format: h5

Projection: Sinusoidal

Scale: 0.05

Offset: -1000

Fill value: 999


 

Citation (Please cite these papers when using the data):



Zeng, Q., & Cheng, J. (2021). Estimating high-spatial resolution surface daily longwave radiation from the instantaneous Global LAnd Surface Satellite (GLASS) longwave radiation product. International Journal of Digital Earth, 14(11), 1674-1704.
DOI: 10.15468/dl.4sh5e7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.860712 -34.606049, 149.860712 -34.615032, 149.862958 -34.615032, 149.862958 -34.606049, 149.860712 -34.606049))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050927-240626123714530/datasets/export for details.
DOI: 10.15468/dl.czgepj
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((142.33504 -36.982104, 142.33504 -36.98435, 142.339531 -36.98435, 142.339531 -36.982104, 142.33504 -36.982104))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050928-240626123714530/datasets/export for details.
DOI: 10.6084/m9.figshare.26501514
title: Crypto household behavior and experience during COVID-19

description: Many households struggled both physically and financially during the COVID-19 crisis. In a time of such uncertainty, one might expect households to respond differently to financial instruments considered risker than others. Given the nature and general feelings around cryptocurrency, we expected there might be differences in how households that owned cryptocurrencies fared during the COVID-19 crisis as compared to those that did not own cryptocurrency. Our research found that cryptocurrency-owning households reported fewer financial challenges during the pandemic than households that did not own cryptocurrency. Specifically, they were less likely to experience food insecurity or miss payments on a variety of bills, including medical expenses and utilities. Crypto households experienced less unemployment, as both the head of the household and the partner more readily adapted to working from home. Crypto households were also less likely to experience death from COVID-19 than their counterparts were. Data from the Federal Reserve’s 2022 Survey of Consumer Finances (SCF) reveal that cryptocurrency-owning households in fact fared better than those who did not. The linear probability model results hold after correction for data imputation and controlling for financial literacy, willingness to take risks in the short- and long-term, income, wealth, gender, age, education level, work status, and race. These findings suggest a counternarrative to the mainstream opinion of cryptocurrency owners as risk-loving, irrational, retail day traders. This research contributes to the overall literature by showing households working with cryptocurrency make financially savvy decisions and are better off generally than their counterparts. As cryptocurrency continues to gain traction and assuming it grows at current rates, society will be greatly affected. First, more households may consider expanding their portfolios with cryptocurrency. Assuming this occurs, more individuals and companies will need to become more familiar with this risky asset and other mechanisms through which one can invest in crypto assets, such as exchange-traded funds. Second, cryptocurrency usage is not only increasing among households but businesses too, including public companies. Investors may want to review their other investments, particularly stocks, to see how they may be indirectly invested in cryptocurrency. This consideration may affect other investment motivation considerations in the impact investing space. Last, we demonstrated households had different experiences with the COVID-19 shock event. Individuals may consider cryptocurrency as another asset to diversify in moving forward depending on other potential shock events besides pandemics, such as global or regional recessions or country currency changes in international markets due to political risk.
DOI: 10.6084/m9.figshare.26501514.v1
title: Crypto household behavior and experience during COVID-19

description: Many households struggled both physically and financially during the COVID-19 crisis. In a time of such uncertainty, one might expect households to respond differently to financial instruments considered risker than others. Given the nature and general feelings around cryptocurrency, we expected there might be differences in how households that owned cryptocurrencies fared during the COVID-19 crisis as compared to those that did not own cryptocurrency. Our research found that cryptocurrency-owning households reported fewer financial challenges during the pandemic than households that did not own cryptocurrency. Specifically, they were less likely to experience food insecurity or miss payments on a variety of bills, including medical expenses and utilities. Crypto households experienced less unemployment, as both the head of the household and the partner more readily adapted to working from home. Crypto households were also less likely to experience death from COVID-19 than their counterparts were. Data from the Federal Reserve’s 2022 Survey of Consumer Finances (SCF) reveal that cryptocurrency-owning households in fact fared better than those who did not. The linear probability model results hold after correction for data imputation and controlling for financial literacy, willingness to take risks in the short- and long-term, income, wealth, gender, age, education level, work status, and race. These findings suggest a counternarrative to the mainstream opinion of cryptocurrency owners as risk-loving, irrational, retail day traders. This research contributes to the overall literature by showing households working with cryptocurrency make financially savvy decisions and are better off generally than their counterparts. As cryptocurrency continues to gain traction and assuming it grows at current rates, society will be greatly affected. First, more households may consider expanding their portfolios with cryptocurrency. Assuming this occurs, more individuals and companies will need to become more familiar with this risky asset and other mechanisms through which one can invest in crypto assets, such as exchange-traded funds. Second, cryptocurrency usage is not only increasing among households but businesses too, including public companies. Investors may want to review their other investments, particularly stocks, to see how they may be indirectly invested in cryptocurrency. This consideration may affect other investment motivation considerations in the impact investing space. Last, we demonstrated households had different experiences with the COVID-19 shock event. Individuals may consider cryptocurrency as another asset to diversify in moving forward depending on other potential shock events besides pandemics, such as global or regional recessions or country currency changes in international markets due to political risk.
DOI: 10.15468/dl.cr9nam
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.211676 -34.612786, 149.211676 -34.619524, 149.216168 -34.619524, 149.216168 -34.612786, 149.211676 -34.612786))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050929-240626123714530/datasets/export for details.
DOI: 10.15468/dl.yecurh
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((143.055941 -36.982104, 143.055941 -36.98435, 143.060433 -36.98435, 143.060433 -36.982104, 143.055941 -36.982104))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050930-240626123714530/datasets/export for details.
DOI: 10.6084/m9.figshare.25688508
title: Rapid, biochemical tagging of cellular activity history in vivo

description: Excel sheets with source data, and raw western blot gels
DOI: 10.6084/m9.figshare.25688508.v1
title: Rapid, biochemical tagging of cellular activity history in vivo

description: Excel sheets with source data, and raw western blot gels
DOI: 10.6084/m9.figshare.24776658
title: Evolution of Phytophthora infestans on its Potato Host since the Irish Potato Famine

description: Baits of RXLR effectors from P infestans and R genes from Solanum hosts used in this study
DOI: 10.6084/m9.figshare.24776658.v1
title: Evolution of Phytophthora infestans on its Potato Host since the Irish Potato Famine

description: Baits of RXLR effectors from P infestans and R genes from Solanum hosts used in this study
DOI: 10.15468/dl.jgvrhw
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.822534 -34.612786, 149.822534 -34.619524, 149.827025 -34.619524, 149.827025 -34.612786, 149.822534 -34.612786))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050931-240626123714530/datasets/export for details.
DOI: 10.15468/dl.tr7ywz
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((143.085137 -36.982104, 143.085137 -36.98435, 143.089628 -36.98435, 143.089628 -36.982104, 143.085137 -36.982104))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050932-240626123714530/datasets/export for details.
DOI: 10.6084/m9.figshare.26065441
title: Source Data

description: Structural Modeling, BRET biosensor GPCR pharmacology and kinetics, GIRK channel investigation and G protein activation, nucleotide binding and biolayer interferometry, molecular dynamics, radioligand binding, Cryo-electromicroscopy
DOI: 10.6084/m9.figshare.26065441.v1
title: Source Data

description: Structural Modeling, BRET biosensor GPCR pharmacology and kinetics, GIRK channel investigation and G protein activation, nucleotide binding and biolayer interferometry, molecular dynamics, radioligand binding, Cryo-electromicroscopy
DOI: 10.5281/zenodo.13221607
title: ELITE SLWR: global 1km daily SLDR at SIN Grid   (2010_001-059)

description: The Essential thermal Infrared remoTe sEnsing (ELITE) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn).

 

This dataset is ELITE daily surface longwave downward radiation (SLDR) product at 1km spatial resolution. It is provided on a Sinusoidal grid and ranges from 2000 to 2022 (continuously updated). This dataset was generated from the ELITE surface longwave downward radiation (SLDR) product using the algorithms developed by Zeng et al. (2021).

 

This is the ELITE Daily SLDR product in 2010 (DOY: 001-059). Please click here to download the ELITE Daily SLDR product in 2010 (DOY: 060-120).

Dataset Characteristics:



Spatial Coverage: Global

Temporal Coverage: 2010-01-01 ~ 2010-02-28

Spatial Resolution: 1 km

Temporal Resolution: Daily

Data Format: h5

Projection: Sinusoidal

Scale: 0.05

Offset: -1000

Fill value: 999


 

Citation (Please cite these papers when using the data):



Zeng, Q., & Cheng, J. (2021). Estimating high-spatial resolution surface daily longwave radiation from the instantaneous Global LAnd Surface Satellite (GLASS) longwave radiation product. International Journal of Digital Earth, 14(11), 1674-1704.
DOI: 10.5281/zenodo.13221608
title: ELITE SLWR: global 1km daily SLDR at SIN Grid   (2010_001-059)

description: The Essential thermal Infrared remoTe sEnsing (ELITE) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn).

 

This dataset is ELITE daily surface longwave downward radiation (SLDR) product at 1km spatial resolution. It is provided on a Sinusoidal grid and ranges from 2000 to 2022 (continuously updated). This dataset was generated from the ELITE surface longwave downward radiation (SLDR) product using the algorithms developed by Zeng et al. (2021).

 

This is the ELITE Daily SLDR product in 2010 (DOY: 001-059). Please click here to download the ELITE Daily SLDR product in 2010 (DOY: 060-120).

Dataset Characteristics:



Spatial Coverage: Global

Temporal Coverage: 2010-01-01 ~ 2010-02-28

Spatial Resolution: 1 km

Temporal Resolution: Daily

Data Format: h5

Projection: Sinusoidal

Scale: 0.05

Offset: -1000

Fill value: 999


 

Citation (Please cite these papers when using the data):



Zeng, Q., & Cheng, J. (2021). Estimating high-spatial resolution surface daily longwave radiation from the instantaneous Global LAnd Surface Satellite (GLASS) longwave radiation product. International Journal of Digital Earth, 14(11), 1674-1704.
DOI: 10.6084/m9.figshare.24570337.v1
title: Proteostasis perturbation of N-Myc leveraging HSP70 mediated protein turnover improves treatment of neuroendocrine prostate cancer

description: Whole exome sequencing (WES) and data from patient, PDX, and cell line.
DOI: 10.15468/dl.wa6ejp
title: Occurrence Download

description: A dataset containing 169 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.946053 -34.603803, 149.946053 -34.61054, 149.939315 -34.61054, 149.939315 -34.615032, 149.941561 -34.615032, 149.941561 -34.619524, 149.946053 -34.619524, 149.946053 -34.628507, 149.957282 -34.628507, 149.957282 -34.624015, 149.961773 -34.624015, 149.961773 -34.619524, 149.957282 -34.619524, 149.957282 -34.615032, 149.95279 -34.615032, 149.95279 -34.608295, 149.957282 -34.608295, 149.957282 -34.612786, 149.964019 -34.612786, 149.964019 -34.608295, 149.968511 -34.608295, 149.968511 -34.606049, 149.970756 -34.606049, 149.970756 -34.603803, 149.946053 -34.603803))"
 ]
}

 The dataset includes 169 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050933-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13228411
title: ELITE SLWR: global 1km daily SLDR at SIN Grid   (2010_244-304)

description: The Essential thermal Infrared remoTe sEnsing (ELITE) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn).

 

This dataset is ELITE daily surface longwave downward radiation (SLDR) product at 1km spatial resolution. It is provided on a Sinusoidal grid and ranges from 2000 to 2022 (continuously updated). This dataset was generated from the ELITE surface longwave downward radiation (SLDR) product using the algorithms developed by Zeng et al. (2021).

 

This is the ELITE Daily SLDR product in 2010 (DOY: 244-304). Please click here to download the ELITE Daily SLDR product in 2010 (DOY: 305-365).

Dataset Characteristics:



Spatial Coverage: Global

Temporal Coverage: 2010-09-01 ~ 2010-10-31

Spatial Resolution: 1 km

Temporal Resolution: Daily

Data Format: h5

Projection: Sinusoidal

Scale: 0.05

Offset: -1000

Fill value: 999


 

Citation (Please cite these papers when using the data):



Zeng, Q., & Cheng, J. (2021). Estimating high-spatial resolution surface daily longwave radiation from the instantaneous Global LAnd Surface Satellite (GLASS) longwave radiation product. International Journal of Digital Earth, 14(11), 1674-1704.
DOI: 10.5281/zenodo.13228412
title: ELITE SLWR: global 1km daily SLDR at SIN Grid   (2010_244-304)

description: The Essential thermal Infrared remoTe sEnsing (ELITE) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn).

 

This dataset is ELITE daily surface longwave downward radiation (SLDR) product at 1km spatial resolution. It is provided on a Sinusoidal grid and ranges from 2000 to 2022 (continuously updated). This dataset was generated from the ELITE surface longwave downward radiation (SLDR) product using the algorithms developed by Zeng et al. (2021).

 

This is the ELITE Daily SLDR product in 2010 (DOY: 244-304). Please click here to download the ELITE Daily SLDR product in 2010 (DOY: 305-365).

Dataset Characteristics:



Spatial Coverage: Global

Temporal Coverage: 2010-09-01 ~ 2010-10-31

Spatial Resolution: 1 km

Temporal Resolution: Daily

Data Format: h5

Projection: Sinusoidal

Scale: 0.05

Offset: -1000

Fill value: 999


 

Citation (Please cite these papers when using the data):



Zeng, Q., & Cheng, J. (2021). Estimating high-spatial resolution surface daily longwave radiation from the instantaneous Global LAnd Surface Satellite (GLASS) longwave radiation product. International Journal of Digital Earth, 14(11), 1674-1704.
DOI: 10.15468/dl.yu3x46
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((144.071042 -36.98435, 144.071042 -36.988841, 144.073288 -36.988841, 144.073288 -36.98435, 144.071042 -36.98435))"
 ]
}

 The dataset includes 18 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050934-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12759814
title: Datasets, figures and simulation scripts for "Quantum circuit compilation with quantum computers"

description: The files contain the datasets and figures with the results of the manuscript "Quantum circuit compilation with quantum computers".

The repository URL links to the repository with the simulation scripts used to produce the datasets and figures.
DOI: 10.5281/zenodo.12759815
title: Datasets, figures and simulation scripts for "Quantum circuit compilation with quantum computers"

description: The files contain the datasets and figures with the results of the manuscript "Quantum circuit compilation with quantum computers".

The repository URL links to the repository with the simulation scripts used to produce the datasets and figures.
DOI: 10.15468/dl.j9xasx
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.860712 -34.619524, 149.860712 -34.628507, 149.862958 -34.628507, 149.862958 -34.619524, 149.860712 -34.619524))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050935-240626123714530/datasets/export for details.
DOI: 10.5519/qd.l54r3fpy
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.15468/dl.ehk5a6
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((144.102484 -36.98435, 144.102484 -36.993333, 144.109221 -36.993333, 144.109221 -36.991087, 144.113713 -36.991087, 144.113713 -36.988841, 144.111467 -36.988841, 144.111467 -36.98435, 144.102484 -36.98435))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050936-240626123714530/datasets/export for details.
DOI: 10.15468/dl.puv6p2
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.818042 -34.63749, 149.818042 -34.639736, 149.815796 -34.639736, 149.815796 -34.644227, 149.822534 -34.644227, 149.822534 -34.63749, 149.818042 -34.63749))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050937-240626123714530/datasets/export for details.