cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14457/rmutk.the.2023.23
title: Influence of Vivo Mobile Brand Sponsorship of Sports Events on Consumer Purchase Intention

description: Effective sports sponsorship necessitates consideration of multiple factors. Previous scholars have primarily focused on the brand assets of sponsors and enhancing the reputation that sponsoring brings to businesses. There has been limited exploration from the perspective of sports events in terms of brand assets and the direct impact of these assets on sponsor audience purchase intention. This research aimed to analyze the influences of VIVO mobile brand sponsorship, including brand assets, brand fit, and audience engagement of sports events, on consumer purchase intention—the research framework laid on the Stimulus-Organism-Response model. The sample size was 400 audiences attending the 22nd FIFA World Cup in Guangzhou, China. Statistics used to analyze data were descriptive statistics, including Frequency, Percentage, Mean, and Standard Deviation, and inferential statistics, including Independent Samples t-test, One-way ANOVA, LSD, Simple Linear Regression, and Multiple Linear Regression at the statistical significance level of 0.05. The results found that most respondents were male, married, aged 25-35 years old, at an educational level high school or vocational school, had a monthly income of 5,000 - 10,000 yuan, and were company employees. The hypothesis results found that age and occupation affect consumer purchase intention. Event brand assets, including brand image and awareness, positively correlate with consumer purchase intention, with multiple correlations (R) = .566. The ability to predict the analytical equation is 31.70 %. Accordingly, brand fit and Audience engagement influenced consumer purchase intention with correlation (R) = 0.485 and 0.469.
DOI: 10.14457/rmutk.the.2023.24
title: The Influence of Marketing Mix 7Ps, Health Consciousness and Social Media on Consumer Purchase Intention at Heytea Physical Stores

description: In recent years, the Chinese-style modern tea shop business has prevailed in China, and its secret of success, especially in consumer behavior and business innovation, deserves further study. Nowadays, two prevailing societal trends may affect the modern Chinese tea shop business, including social media and health consciousness. The research domain is HEYTEA, the No.1 brand within its field and famous for its marketing strategies and innovation. This study aims to analyze the impact of identified factors on consumer purchase intention at HEYTEA physical stores, focusing on the influence of marketing mix 7Ps, health consciousness, and social media. Self-completion online questionnaires were distributed to those who live in the 12 selected cities of China. Data obtained are analyzed using advanced and modern statistical programs focusing on descriptive and inferential statistics. The findings indicate that differences in Gender and Age generate differences in Consumer Purchase Intention, and differences in Age and living in a City generate differences in Purchase Intention, with evidence by Two-Way ANOVA. Differences in Gender, Age, and Net Income per Month generate differences in Consumer Purchase Intention with evidence by Three-Way ANOVA. The Multiple Semi Log-Linear Regression Analysis found that all aspects of Marketing Mix 7Ps, Health Consciousness, and Social Media influence consumer purchase intention towards HEYTEA’s drinks at its physical stores. This study provides practical implications for HEYTEA brand management and modern Chinese-style tea shop management.
DOI: 10.21249/dzhw:gsl2015:1.0.0
title: DZHW-Stu­di­en­be­rech­tig­ten­pa­nel 2015 - Aus­bil­dungs­we­ge von Stu­di­en­be­rech­tig­ten
title: DZHW Panel Study of School Leavers 2015 - Ed­u­ca­tional paths of school leavers with a higher ed­u­ca­tion en­trance qual­i­fi­ca­tion

description: Das DZHW-Stu­di­en­be­rech­tig­ten­pa­nel 2015 ist Teil der DZHW-Studien­berechtigten­befragungs­reihe, in der an­hand von stan­dar­di­sier­ten Mehr­fach­be­fra­gun­gen In­for­ma­tio­nen zu den nach­schu­li­schen Wer­de­gän­gen von Schul­ab­gän­ger(inne)n mit (schu­li­scher) Hoch­schul­zu­gangs­be­rech­ti­gung er­fasst wer­den. In der Regel wer­den für jeden Stu­di­en­be­rech­tig­ten­jahr­gang meh­re­re Be­fra­gungs­wel­len zu un­ter­schied­li­chen Zeit­punk­ten vor und nach Er­werb der Hoch­schul­zu­gangs­be­rech­ti­gung durch­ge­führt. Dem­nach han­delt es sich um ein kom­bi­nier­tes Ko­hor­ten-Panel-De­sign. Beim Stu­di­en­be­rech­tig­ten­pa­nel 2015 han­delt es sich um die 20. Ko­hor­te der Stu­di­en­rei­he mit ak­tu­ell zwei Wel­len.
description: The DZHW Panel Study of School Leavers 2015 is part of the School Leavers panel se­ries of the DZHW, which records in­for­ma­tion on post-school ed­u­ca­tional and ca­reer paths of school leavers with a higher ed­u­ca­tion en­trance qual­i­fi­ca­tion. For every grad­u­ate year (co­hort) a se­ries of sur­vey waves are car­ried out with each wave oc­cur­ring at a dif­fer­ent time be­fore and after grad­u­a­tion, im­ple­mented as a com­bined co­hort-panel-de­sign. The Panel Study of School Leavers 2015 com­prises the 20th co­hort of the sur­vey se­ries with two sur­vey waves.
description: Self-administered questionnaire: Paper
description: Stu­di­en­be­rech­tig­ten­pa­nel 2015 - erste Welle: Standardisierte postalische Befragung
description: Panel Study of School Leavers 2015 - first wave: Standardised 
self-administered survey
description: Self-administered questionnaire: Paper
description: Stu­di­en­be­rech­tig­ten­pa­nel 2015 - zwei­te Welle: Standardisierte postalische Befragung
description: Panel Study of School Leavers 2015 - sec­ond wave: Standardised 
self-administered survey
description: <strong>Stu­di­en­be­rech­tig­ten­pa­nel 2015 - erste Welle:</strong>
 Schul­ab­gän­ger(innen) all­ge­mein­bil­den­der und be­ruf­li­cher Schu­len des Schul­jah­res 2014/2015 mit bun­des­deut­scher Hoch­schul­rei­fe
 
 <strong>Stu­di­en­be­rech­tig­ten­pa­nel 2015 - zwei­te Welle:</strong>
 Schul­ab­gän­ger(innen) all­ge­mein­bil­den­der und be­ruf­li­cher Schu­len des Schul­jah­res 2014/2015 mit bun­des­deut­scher Hoch­schul­rei­fe
description: <strong>Panel Study of School Leavers 2015 - first wave:</strong>
 School leavers of schools of gen­eral ed­u­ca­tion and vo­ca­tional schools of the year 2014/2015 with a higher ed­u­ca­tion en­trance qual­i­fi­ca­tion
 
 <strong>Panel Study of School Leavers 2015 - sec­ond wave:</strong>
 School leavers of schools of gen­eral ed­u­ca­tion and vo­ca­tional schools of the year 2014/2015 with a higher ed­u­ca­tion en­trance qual­i­fi­ca­tion
description: Sonstige
DOI: 10.21249/dzhw:gsl2015:1.0.1
title: DZHW-Studienberechtigtenpanel 2015 - Ausbildungswege von Studienberechtigten
title: DZHW Panel Study of School Leavers 2015 - Educational paths of school leavers with a higher education entrance qualification

description: The DZHW Panel Study of School Leavers 2015 is part of the School Leavers panel series of the DZHW, which records information on post-school educational and career paths of school leavers with a higher education entrance qualification. For every graduate year (cohort) a series of survey waves are carried out with each wave occurring at a different time before and after graduation, implemented as a combined cohort-panel-design. The Panel Study of School Leavers 2015 comprises the 20th cohort of the survey series with two survey waves.
description: Das DZHW-Studienberechtigtenpanel 2015 ist Teil der DZHW-Studienberechtigtenbefragungsreihe, in der anhand von standardisierten Mehrfachbefragungen Informationen zu den nachschulischen Werdegängen von Schulabgänger(inne)n mit (schulischer) Hochschulzugangsberechtigung erfasst werden. In der Regel werden für jeden Studienberechtigtenjahrgang mehrere Befragungswellen zu unterschiedlichen Zeitpunkten vor und nach Erwerb der Hochschulzugangsberechtigung durchgeführt. Demnach handelt es sich um ein kombiniertes Kohorten-Panel-Design. Beim Studienberechtigtenpanel 2015 handelt es sich um die 20. Kohorte der Studienreihe mit aktuell zwei Wellen.
description: School leavers of schools of general education and vocational schools of the year 2014/2015 with a higher education entrance qualification
description: Schulabgänger(innen) allgemeinbildender und beruflicher Schulen des Schuljahres 2014/2015 mit bundesdeutscher Hochschulreife
description: School leavers of schools of general education and vocational schools of the year 2014/2015 with a higher education entrance qualification
description: Schulabgänger(innen) allgemeinbildender und beruflicher Schulen des Schuljahres 2014/2015 mit bundesdeutscher Hochschulreife
DOI: 10.15468/dl.yfbfcx
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-106.9188 22.04913, -106.7688 22.04913, -106.7688 22.19913, -106.9188 22.19913, -106.9188 22.04913))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041199-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dsseq9
title: Occurrence Download

description: A dataset containing 1700 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "OccurrenceStatus is Present",
 "TaxonKey is Neophron percnopterus",
 "Year 2000-2014"
 ]
}

 The dataset includes 1700 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041201-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16312722
title: EFSA Opinion derivation of a health-based guidance value for Δ8-tetrahydrocannabinol (Δ8-THC) and its occurrence in food: Annex on the Occurrence data in food submitted to EFSA

description: Annex to EFSA’s Opinion on the derivation of a health-based guidance value for Δ8-tetrahydrocannabinol (Δ8-THC) and its occurrence in food: Annex D includes the occurrence data in food extracted from EFSA Data Warehouse and submitted to EFSA in the period between 2014 and 2024.
description: EU; en; xlsx; FEEDCO@efsa.europa.eu
DOI: 10.5281/zenodo.16312723
title: EFSA Opinion derivation of a health-based guidance value for Δ8-tetrahydrocannabinol (Δ8-THC) and its occurrence in food: Annex on the Occurrence data in food submitted to EFSA

description: Annex to EFSA’s Opinion on the derivation of a health-based guidance value for Δ8-tetrahydrocannabinol (Δ8-THC) and its occurrence in food: Annex D includes the occurrence data in food extracted from EFSA Data Warehouse and submitted to EFSA in the period between 2014 and 2024.
description: EU; en; xlsx; FEEDCO@efsa.europa.eu
DOI: 10.5281/zenodo.17544338
title: Meteorological time series in Brazil - automatic stations

description: Hourly meteorological time series from automatic climate stations in Brazil.

This dataset is a mirror of official and public data released by Brazil's meteorological public services (INMET). The dataset here is streamlined for processing and managing large volumes of data.

Files

AUTO_DATABASE.gpkg -- spatial database with the following layers:



fields -- table of field names and metadata;

stations -- points of climate stations with attributes;

series -- time series of meteorological varibales.




Note: data values are scaled by a factor to improve storage efficiency. See fields layer.


query.py -- standalone python script for data retrieval. See docstring for instructions.

Info

Number of stations in catalog: 564

Start of sampling: 2000-01-01 00:00:00

End of sampling: 2025-01-01 00:00:00

Meteorological variables:



p -- Total hourly precipitation (mm);

ap -- Atmospheric pressure at the station level hourly (MB);

rad -- Global radiation (kJ/m²)

tas -- Dry bulb hourly air temperature (°C);

tdp -- Dew point hourly temperature (°C);

hur -- Relative hourly air moisture (%)

windd -- Wind hourly direction (°);

windg -- Wind hourly maximal gust speed (m/s);

winds -- Wind hourly speed (m/s);



Query data

SQL tool

Data can be retrieved in QGIS via SQL tool with this query:



SELECT d.*,s.cd_stationFROM series AS dLEFT JOIN stations AS sON d.id_station = s.id_station-- define station codeWHERE s.cd_station = 'A001'-- define datetime rangeAND d.datetime BETWEEN '2024-01-01' AND '2024-12-31'ORDER BY d.datetime;


This query can be imported as a table to QGIS and then exported as a CSV file.

Warning: data values are scaled. Check the fields layer for scale constants.

Python script

Using the terminal, go to folder with AUTO_DATABASE.gpkg and query.py



>>> cd path/to/folder


Then call the query passing the arguments:



>>> python -m query -o "path/to/output" -s "A001" --start "2020-01-01" --end "2022-01-01"


Where -s is the station code string.

 

This will yield a CSV file for the query in the output folder. 

Note: This method already converts the values to the actual numerical range.

Warning: Pandas and Geopandas are required dependencies.

 



Source

Data was sourced from:

INMET (2025). Meteorological Database for Education and Research (BDMEP) from National Institute of Meteorology (Instituto Nacional de Meteorologia - INMET). Available at: https://bdmep.inmet.gov.br/ Latest access: February of 2025.

 

Logs

1.0.0 -- Operational release. Changes in some fields names. Changes in file name. Changes in layer names (data changed to series). Changes in no-data value (-1 changed to -9999).

0.0.1 -- Testing release. Data updated to 2025-01-01.
DOI: 10.5281/zenodo.17635078
title: Meteorological time series in Brazil - automatic stations

description: Hourly meteorological time series from automatic climate stations in Brazil.

This dataset is a mirror of official and public data released by Brazil's meteorological public services (INMET). The dataset here is streamlined for processing and managing large volumes of data.

Files

AUTO_DATABASE.gpkg -- spatial database with the following layers:



fields -- table of field names and metadata;

stations -- points of climate stations with attributes;

series -- time series of meteorological varibales.




Note: data values are scaled by a factor to improve storage efficiency. See fields layer.


query.py -- standalone python script for data retrieval. See docstring for instructions.

Info

Number of stations in catalog: 564

Start of sampling: 2000-01-01 00:00:00

End of sampling: 2025-01-01 00:00:00

Meteorological variables:



p -- Total hourly precipitation (mm);

ap -- Atmospheric pressure at the station level hourly (MB);

rad -- Global radiation (kJ/m²)

tas -- Dry bulb hourly air temperature (°C);

tdp -- Dew point hourly temperature (°C);

hur -- Relative hourly air moisture (%)

windd -- Wind hourly direction (°);

windg -- Wind hourly maximal gust speed (m/s);

winds -- Wind hourly speed (m/s);



Query data

SQL tool

Data can be retrieved in QGIS via SQL tool with this query:



SELECT d.*,s.cd_stationFROM series AS dLEFT JOIN stations AS sON d.id_station = s.id_station-- define station codeWHERE s.cd_station = 'A001'-- define datetime rangeAND d.datetime BETWEEN '2024-01-01' AND '2024-12-31'ORDER BY d.datetime;


This query can be imported as a table to QGIS and then exported as a CSV file.

Warning: data values are scaled. Check the fields layer for scale constants.

Python script

Using the terminal, go to folder with AUTO_DATABASE.gpkg and query.py



>>> cd path/to/folder


Then call the query passing the arguments:



>>> python -m query -o "path/to/output" -s "A001" --start "2020-01-01" --end "2022-01-01"


Where -s is the station code string.

 

This will yield a CSV file for the query in the output folder. 

Note: This method already converts the values to the actual numerical range.

Warning: Pandas and Geopandas are required dependencies.

 



Source

Data was sourced from:

INMET (2025). Meteorological Database for Education and Research (BDMEP) from National Institute of Meteorology (Instituto Nacional de Meteorologia - INMET). Available at: https://bdmep.inmet.gov.br/ Latest access: February of 2025.

 

Logs

1.0.0 -- Operational release. Changes in some fields names. Changes in file name. Changes in layer names (data changed to series). Changes in no-data value (-1 changed to -9999).

0.0.1 -- Testing release. Data updated to 2025-01-01.
DOI: 10.15468/dl.4mzyfe
title: Occurrence Download

description: A dataset containing 33 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-106.7688 22.04913, -106.6188 22.04913, -106.6188 22.19913, -106.7688 22.19913, -106.7688 22.04913))"
 ]
}

 The dataset includes 33 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041202-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.34654.91202
title: 50W optical power laser 450nm on drone
DOI: 10.5281/zenodo.17636856
title: MSFECGAN-OpticalReconstruction-Dataset

description: The MSFECGAN-OpticalReconstruction-Dataset is a remote sensing dataset designed to support research on optical image reconstruction using multi-source data. It is developed in conjunction with the MSF-ECGAN (Multi-Source Fusion Enhanced Conditional GAN) model, which aims to generate high-quality optical time series from auxiliary sources such as SAR imagery and previous optical observations. The dataset contains temporally-aligned, co-registered multi-source inputs and their corresponding reconstructed optical outputs at 10-meter resolution and 8-day intervals, matching Sentinel-2 specifications. It is intended to facilitate the development and benchmarking of deep learning models for cloud-robust optical image reconstruction, spatiotemporal information fusion, and Earth observation applications.
DOI: 10.5281/zenodo.17636855
title: MSFECGAN-OpticalReconstruction-Dataset

description: The MSFECGAN-OpticalReconstruction-Dataset is a remote sensing dataset designed to support research on optical image reconstruction using multi-source data. It is developed in conjunction with the MSF-ECGAN (Multi-Source Fusion Enhanced Conditional GAN) model, which aims to generate high-quality optical time series from auxiliary sources such as SAR imagery and previous optical observations. The dataset contains temporally-aligned, co-registered multi-source inputs and their corresponding reconstructed optical outputs at 10-meter resolution and 8-day intervals, matching Sentinel-2 specifications. It is intended to facilitate the development and benchmarking of deep learning models for cloud-robust optical image reconstruction, spatiotemporal information fusion, and Earth observation applications.
DOI: 10.15468/dl.8zj3ek
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Hoolock hoolock"
 ]
}

 The dataset includes 9 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041203-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17636196
title: Dataset for PRA - AE12881

description: Dataset for "Spectral phase control of an ultrashort pulse for exploring Autler-Townes effect in Hydrogen atomic ionization through resonant state".Abstract: We present a bound-continuum ionization model combined with numerical simulations to investigate the asymmetric features of Autler-Townes (AT) splitting in the ionization spectra of hydrogen atoms, induced by a spectrally phase-modulated ultrashort pulse. This model incorporates a resonance-enhanced two-photon ionization process, enabling transitions from the ground electronic state to the continuum state via the first excited electronic state through the absorption of two photons. By comparing our model predictions with exact numerical simulations based on time-dependent electronic wavepacket calculations, we demonstrate that the characteristics of the AT doublets, shaped by the spectral phase, emerge from the competing effects of selective population of dressed states and the transition amplitude to the continuum. In addition, through a perturbative analysis of the photoelectronic spectrum and the application of the Magnus expansion, we reveal a correlation between the number of AT fringes, resonant states, and pulse area, while drawing insights from bound states. This work enhances our understanding of how spectral phase can be utilized to explore bound-state effects in ultrafast ionization dynamics.
DOI: 10.5281/zenodo.17636195
title: Dataset for PRA - AE12881

description: Dataset for "Spectral phase control of an ultrashort pulse for exploring Autler-Townes effect in Hydrogen atomic ionization through resonant state".Abstract: We present a bound-continuum ionization model combined with numerical simulations to investigate the asymmetric features of Autler-Townes (AT) splitting in the ionization spectra of hydrogen atoms, induced by a spectrally phase-modulated ultrashort pulse. This model incorporates a resonance-enhanced two-photon ionization process, enabling transitions from the ground electronic state to the continuum state via the first excited electronic state through the absorption of two photons. By comparing our model predictions with exact numerical simulations based on time-dependent electronic wavepacket calculations, we demonstrate that the characteristics of the AT doublets, shaped by the spectral phase, emerge from the competing effects of selective population of dressed states and the transition amplitude to the continuum. In addition, through a perturbative analysis of the photoelectronic spectrum and the application of the Magnus expansion, we reveal a correlation between the number of AT fringes, resonant states, and pulse area, while drawing insights from bound states. This work enhances our understanding of how spectral phase can be utilized to explore bound-state effects in ultrafast ionization dynamics.
DOI: 10.15468/dl.pw2rh6
title: Occurrence Download

description: A dataset containing 5483 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Saudi Arabia, Jordan, Iraq, Israel, Iran (Islamic Republic of), Lebanon, Syrian Arab Republic, United Arab Emirates, Oman, Bahrain, Qatar, Türkiye, Greece, Cyprus, Yemen)",
 "OccurrenceStatus is Present",
 "TaxonKey is Neophron percnopterus",
 "Year 2000-2014"
 ]
}

 The dataset includes 5483 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041204-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ybb9b8
title: Occurrence Download

description: A dataset containing 61 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-106.6188 22.04913, -106.4688 22.04913, -106.4688 22.19913, -106.6188 22.19913, -106.6188 22.04913))"
 ]
}

 The dataset includes 61 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041205-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d8z5bh
title: Occurrence Download

description: A dataset containing 59668 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Canadian Museum of Nature Mammal Collection"
 ]
}

 The dataset includes 59668 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041194-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.