cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e208282
title: Research on the Trends and Influencing Factors of Carbon Emission Reduction Efficiency in Cities Along the Yellow River in Shandong Province, China

description: Enhancing the
efficiency of carbon emission reduction is a crucial strategy to promote high-quality
economic growth. This study employs
a DEA-Malmquist carbon reduction efficiency evaluation model, along with an index
system, was employed to empirically analyze the dynamic characteristics of
carbon emission reduction efficiency. Utilizing statistical data on the input-output
index of carbon emission reduction efficiency in Shandong Coastal City from
2011 to 2020, the Tobit model was used to analyze the influencing factors of
carbon emission reduction efficiency and uncover socio-economic behaviors
impacting reduction efficiency. Factors considered included economic
development level, industrial structure, foreign direct investment, government
influence, and scientific and technological innovation input.

The main results are
as follows: (1) The average Malmquist Index for carbon reduction efficiency from
2011 to 2020 was 0.992, exhibiting a downward trend. From 2016 to 2020, the
average Malmquist index was 1.047 and had an upward trajectory. Jining, Tai'an,
and Dezhou had an average Malmquist Index value of less than 1, suggesting
deficiencies in carbon reduction efficiency. Binzhou, Zibo, and Dongying had an
average Malmquist index above 1, indicating greater efficiency in reducing
carbon emissions. (2) Output value of the secondary sector, general public
budget, and actual foreign capital expenditure were found to have positive
significant impacts on carbon reduction efficiency, while per capita GDP had a
significant negative effect. 

Based on these results, it
is recommended that cities along the Yellow River formulate customized regional
carbon reduction strategies, fostering the coordinated development of economic growth
and environmental protection. Other recommendations include increasing general
public budget expenditure, advocating for structural adjustment and upgrading
of the secondary sector of the economy, and giving full play inter-city
interactions and coordination functions, to support effective environmental
governance and sustainable economic growth in the Yellow River basin.
DOI: 10.3886/e208282v1
title: Research on the Trends and Influencing Factors of Carbon Emission Reduction Efficiency in Cities Along the Yellow River in Shandong Province, China

description: Enhancing the
efficiency of carbon emission reduction is a crucial strategy to promote high-quality
economic growth. This study employs
a DEA-Malmquist carbon reduction efficiency evaluation model, along with an index
system, was employed to empirically analyze the dynamic characteristics of
carbon emission reduction efficiency. Utilizing statistical data on the input-output
index of carbon emission reduction efficiency in Shandong Coastal City from
2011 to 2020, the Tobit model was used to analyze the influencing factors of
carbon emission reduction efficiency and uncover socio-economic behaviors
impacting reduction efficiency. Factors considered included economic
development level, industrial structure, foreign direct investment, government
influence, and scientific and technological innovation input.

The main results are
as follows: (1) The average Malmquist Index for carbon reduction efficiency from
2011 to 2020 was 0.992, exhibiting a downward trend. From 2016 to 2020, the
average Malmquist index was 1.047 and had an upward trajectory. Jining, Tai'an,
and Dezhou had an average Malmquist Index value of less than 1, suggesting
deficiencies in carbon reduction efficiency. Binzhou, Zibo, and Dongying had an
average Malmquist index above 1, indicating greater efficiency in reducing
carbon emissions. (2) Output value of the secondary sector, general public
budget, and actual foreign capital expenditure were found to have positive
significant impacts on carbon reduction efficiency, while per capita GDP had a
significant negative effect. 

Based on these results, it
is recommended that cities along the Yellow River formulate customized regional
carbon reduction strategies, fostering the coordinated development of economic growth
and environmental protection. Other recommendations include increasing general
public budget expenditure, advocating for structural adjustment and upgrading
of the secondary sector of the economy, and giving full play inter-city
interactions and coordination functions, to support effective environmental
governance and sustainable economic growth in the Yellow River basin.
DOI: 10.15468/dl.v4hn5m
title: Occurrence Download

description: A dataset containing 402805 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "not" : {
 "PublishingCountry" : [
 "is Norway"
 ]
 }
 },
 "Country is Svalbard and Jan Mayen"
 ]
}

 The dataset includes 402805 records from 740 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047172-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/9099321
title: WallStreetBets 2022
DOI: 10.15468/dl.5sryvf
title: Occurrence Download

description: A dataset containing 75 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Indonesia",
 "OccurrenceStatus is Present",
 "TaxonKey is Hydrornis guajanus (Müller & Pls, 1776)",
 "Year 2019-2023"
 ]
}

 The dataset includes 75 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047174-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ngpkby
title: Occurrence Download

description: A dataset containing 79554 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is International Barcode of Life project (iBOL)",
 "GadmLevel0Gid is NOR"
 ]
}

 The dataset includes 79554 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047173-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h3khap
title: Occurrence Download

description: A dataset containing 119 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Thaumoctopus mimicus Norman & Hochberg, 2005"
 ]
}

 The dataset includes 119 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047175-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26424463.v1
title: sequence of HTS of LUAD and controls.fq.gz

description: sequence of HTS of 4 LUAD patients and benign pulmonary lesions
DOI: 10.6084/m9.figshare.26424463
title: sequence of HTS of LUAD and controls.fq.gz

description: sequence of HTS of 4 LUAD patients and benign pulmonary lesions
DOI: 10.15468/dl.yjqzjf
title: Occurrence Download

description: A dataset containing 119 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Thaumoctopus mimicus Norman & Hochberg, 2005"
 ]
}

 The dataset includes 119 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047176-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k55yne
title: Occurrence Download

description: A dataset containing 168 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-68.9816 -22.5109,-68.93668 -22.5109,-68.93668 -22.485,-68.9816 -22.485,-68.9816 -22.5109))",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 168 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047177-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26490436
title: Interview with p6.docx

description: This is the data repository for the raw, anonymized dataset of the study exploring self-censorship within Nigerian newsrooms following the #EndSARS protests. The research focuses on how journalists navigate the use of user-generated content (UGC) under increased government scrutiny, sanctions, and fines. This research was part of a fulfillment for a Master's degree at the school of Journalism, media and Information of the University of Sheffield, the study involved in-depth interviews with 12 journalists from four major Nigerian news organizations affected by sanctions or fines in the past 24 months. The study examines journalistic practices over three years and identifies four primary strategies—conformity, avoidance, equilibrium, and cryptic approaches—employed to maintain professional standards while managing legal and safety challenges. The findings provide empirical evidence on the complex dynamics of self-censorship and UGC use in crisis reporting, laying the groundwork for future research on journalistic coping strategies in similar contexts.
DOI: 10.5281/zenodo.13205489
title: ELITE SLWR: global 1km daily SLDR at SIN Grid   (2011_305-365)

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 2011 (DOY: 305-365). Please click here to download the ELITE Daily SLDR product in 2012 (DOY: 001-059).

Dataset Characteristics:



Spatial Coverage: Global

Temporal Coverage: 2011-11-01 ~ 2011-12-31

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.13205490
title: ELITE SLWR: global 1km daily SLDR at SIN Grid   (2011_305-365)

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 2011 (DOY: 305-365). Please click here to download the ELITE Daily SLDR product in 2012 (DOY: 001-059).

Dataset Characteristics:



Spatial Coverage: Global

Temporal Coverage: 2011-11-01 ~ 2011-12-31

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: 10.25582/data.2023-08.2858827/2426078
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858796/2426079
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858453/2426080
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858867/2426081
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858519/2426082
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858479/2426083
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858891/2426084
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858571/2426085
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858913/2426086
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858520/2426087
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858886/2426088
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2859620/2426089
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2859460/2426090
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858522/2426091
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858523/2426092
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858857/2426093
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858549/2426094
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858833/2426095
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2859228/2426096
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858914/2426097
title: Data for EMSL Project 51287 from August 2023
DOI: 10.5281/zenodo.13201963
title: ELITE SLWR: global 1km daily SLDR at SIN Grid   (2011_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 2011 (DOY: 244-304). Please click here to download the ELITE Daily SLDR product in 2011 (DOY: 305-365).

Dataset Characteristics:



Spatial Coverage: Global

Temporal Coverage: 2011-09-01 ~ 2011-10-31

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.13201964
title: ELITE SLWR: global 1km daily SLDR at SIN Grid   (2011_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 2011 (DOY: 244-304). Please click here to download the ELITE Daily SLDR product in 2011 (DOY: 305-365).

Dataset Characteristics:



Spatial Coverage: Global

Temporal Coverage: 2011-09-01 ~ 2011-10-31

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: 10.25582/data.2023-08.2859100/2426098
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2859717/2426099
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858455/2426100
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858881/2426101
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858912/2426102
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858883/2426103
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858969/2426104
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858898/2426105
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2859364/2426106
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858509/2426107
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858927/2426108
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2859619/2426109
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858932/2426110
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858905/2426111
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858929/2426112
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858572/2426113
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858908/2426114
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858821/2426115
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2859286/2426116
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2859686/2426117
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858803/2426118
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858896/2426119
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858943/2426120
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858494/2426121
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858909/2426122
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858871/2426123
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858524/2426124
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858526/2426125
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858534/2426126
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858614/2426127
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858890/2426128
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858889/2426129
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858888/2426130
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858493/2426131
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858602/2426132
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858951/2426133
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2859217/2426134
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858958/2426135
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2859480/2426136
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858454/2426137
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858947/2426138
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2859745/2426139
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858942/2426140
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2859621/2426141
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858567/2426142
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2859142/2426143
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858478/2426144
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858945/2426145
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858830/2426146
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858940/2426147
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858532/2426148
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858818/2426149
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2859461/2426150
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858865/2426151
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2858510/2426152
title: Data for EMSL Project 51287 from August 2023