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

description: A dataset containing 142 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lathyrus subandinus"
 ]
}

 The dataset includes 142 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034143-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n2wvum
title: Occurrence Download

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

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034144-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4mb5et
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Chrysemys picta)",
 "Country is one of (Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivia (Plurinational State of), Bonaire, Sint Eustatius and Saba, Bouvet Island, Brazil, Cayman Islands, Chile, Colombia, Costa Rica, Cuba, Curaçao, Dominica, Dominican Republic, Ecuador, El Salvador, Falkland Islands (Malvinas), French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Montserrat, Nicaragua, Panama, Paraguay, Peru, Puerto Rico, Saint Barthélemy, Saint Kitts and Nevis, Saint Lucia, Saint Martin (French part), Saint Vincent and the Grenadines, Sint Maarten (Dutch part), South Georgia and the South Sandwich Islands, Suriname, Trinidad and Tobago, Turks and Caicos Islands, Uruguay, Venezuela (Bolivarian Republic of), Virgin Islands (British), Virgin Islands (U.S.))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034147-250717081556266/datasets/export for details.
DOI: 10.15468/dl.7z5hux
title: Occurrence Download

description: A dataset containing 980 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Larrea nitida"
 ]
}

 The dataset includes 980 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034148-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/owov4b
title: STM images of multilayer PtTe2 and observed morphological changes after Ni deposition

description: STM images of multilayer PtTe2 and observed morphological changes after Ni deposition.
DOI: 10.15468/dl.hqnsvq
title: Occurrence Download

description: A dataset containing 95921 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Chrysemys picta)",
 "Country is one of (Bermuda, Canada, Greenland, Saint Pierre and Miquelon, United States of America)"
 ]
}

 The dataset includes 95921 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034145-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/wfn2rx8pz2
title: Generation Z Perspective about Fast Fashion And Its Environmental Impact

description: This data is based on a survey conducted via Google Form and in-depth interviews with Gen Z regarding their attitudes toward overconsumption and its impact on environmental sustainability. Respondents came from various regions in Indonesia, aged 15-18.
DOI: 10.17632/wfn2rx8pz2.1
title: Generation Z Perspective about Fast Fashion And Its Environmental Impact

description: This data is based on a survey conducted via Google Form and in-depth interviews with Gen Z regarding their attitudes toward overconsumption and its impact on environmental sustainability. Respondents came from various regions in Indonesia, aged 15-18.
DOI: 10.17632/hgcbnmxvr8.1
title: UAV-derived BRDF datasets for the wheat and peach trees

description: This dataset consists of multi-angle remote sensing data of wheat and peach trees collected in Pinggu District, Beijing, China, using a DJI Matrice 350 RTK UAV. The dataset spans key growth stages of the two crops, offering valuable insights into their canopy reflectance dynamics across different phenological periods and different remote sensing geometries.
The dataset includes the following components:
1、Raw Data:
Digital Number (DN) values directly exported from the onboard sensors of the UAV. These data represent uncalibrated radiometric measurements acquired at multiple view angles.
2、Processed Data:
Multi-angle reflectance data derived through radiometric calibration of the raw DN values, along with associated geometric parameters such as view and solar angles. These processed data are suitable for further remote sensing analysis, including vegetation index computation and BRDF characterization.
DOI: 10.15468/dl.p2xh7m
title: Occurrence Download

description: A dataset containing 981 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Larrea cuneifolia"
 ]
}

 The dataset includes 981 records from 70 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034150-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t7xue2
title: Occurrence Download

description: A dataset containing 2220 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Xymalos monospora"
 ]
}

 The dataset includes 2220 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034149-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12706802
title: Dataset for "Benchmarking for the automated detection of southern yellow-cheeked crested gibbon calls from passive acoustic monitoring data"

description: "Benchmarking automated detection and classification approaches for long-term acoustic monitoring of endangered species: a case study on gibbons from Cambodia"



Recent advances in deep learning and transfer learning have revolutionized our ability for the automated detection of acoustic signals from long-term soundscape recordings. Here, we provide a benchmark for the automated detection of southern yellow-cheeked crested gibbon (Nomascus gabriellae) calls recorded in Jahoo, Cambodia. For the benchmarking, we compared the performance of support vector machines (SVMs), a quasi-DenseNet architecture (Koogu), transfer learning with ResNet50 models trained on the ‘ImageNet’ dataset (ResNet), and transfer learning with embeddings from a global birdsong model (BirdNET). We also investigated the impact of varying the number of training samples on the performance of these models. Transfer learning models based on BirdNET embeddings had superior performance with a smaller number of training samples, whereas Koogu and ResNet models only had acceptable performance with a larger number of training samples (>200 gibbon samples). We deployed the BirdNET-based model over > 130,000 hours of continuous soundscape data, which, after manual review, resulted in >12,000 verified true positive detections. We found that gibbon calling events occurred mostly in the early morning hours between 05:00 to 0:600 local time. We had fewer gibbon detections during the monsoon period and found substantial variation in spatial patterns of calling events across months and years. We show that automated detection can be used to investigate long-term spatial and temporal patterns of gibbon calling events. Reliable automated detection approaches are a critical first step for using passive acoustic monitoring to assess endangered gibbon populations at ecologically relevant temporal- and spatial-scales. 

 Detailed instructions regarding use are provided on GitHub.


Link to GitHub: https://github.com/DenaJGibbon/benchmark-gibbon-calls.

Please cite both if you use these data: 

Clink, D., Cross-Jaya, H., Kim, J., Ahmad, A. H., Hong, M., Sala, R., Birot, H., Agger, C., Vu, T. T., Thi, H. N., Chi, T. N., & Klinck, H. (2024). Dataset for "Benchmarking for the automated detection of southern yellow-cheeked crested gibbon calls from passive acoustic monitoring data" [Data set]. Zenodo. https://doi.org/10.5281/zenodo.12706803

Clink DJ, Cross-Jaya H, Kim J, Ahmad AH, Hong M, Sala R, Birot H, Agger C, Vu TT, Thi HN, Chi TN. Benchmarking for the automated detection and classification of southern yellow-cheeked crested gibbon calls from passive acoustic monitoring data. bioRxiv. 2024:2024-08.
DOI: 10.5281/zenodo.15293138
title: Dataset for "Benchmarking for the automated detection of southern yellow-cheeked crested gibbon calls from passive acoustic monitoring data"

description: "Benchmarking automated detection and classification approaches for long-term acoustic monitoring of endangered species: a case study on gibbons from Cambodia"



Recent advances in deep learning and transfer learning have revolutionized our ability for the automated detection of acoustic signals from long-term soundscape recordings. Here, we provide a benchmark for the automated detection of southern yellow-cheeked crested gibbon (Nomascus gabriellae) calls recorded in Jahoo, Cambodia. For the benchmarking, we compared the performance of support vector machines (SVMs), a quasi-DenseNet architecture (Koogu), transfer learning with ResNet50 models trained on the ‘ImageNet’ dataset (ResNet), and transfer learning with embeddings from a global birdsong model (BirdNET). We also investigated the impact of varying the number of training samples on the performance of these models. Transfer learning models based on BirdNET embeddings had superior performance with a smaller number of training samples, whereas Koogu and ResNet models only had acceptable performance with a larger number of training samples (>200 gibbon samples). We deployed the BirdNET-based model over > 130,000 hours of continuous soundscape data, which, after manual review, resulted in >12,000 verified true positive detections. We found that gibbon calling events occurred mostly in the early morning hours between 05:00 to 0:600 local time. We had fewer gibbon detections during the monsoon period and found substantial variation in spatial patterns of calling events across months and years. We show that automated detection can be used to investigate long-term spatial and temporal patterns of gibbon calling events. Reliable automated detection approaches are a critical first step for using passive acoustic monitoring to assess endangered gibbon populations at ecologically relevant temporal- and spatial-scales. 

 Detailed instructions regarding use are provided on GitHub.


Link to GitHub: https://github.com/DenaJGibbon/benchmark-gibbon-calls.

Please cite both if you use these data: 

Clink, D., Cross-Jaya, H., Kim, J., Ahmad, A. H., Hong, M., Sala, R., Birot, H., Agger, C., Vu, T. T., Thi, H. N., Chi, T. N., & Klinck, H. (2024). Dataset for "Benchmarking for the automated detection of southern yellow-cheeked crested gibbon calls from passive acoustic monitoring data" [Data set]. Zenodo. https://doi.org/10.5281/zenodo.12706803

Clink DJ, Cross-Jaya H, Kim J, Ahmad AH, Hong M, Sala R, Birot H, Agger C, Vu TT, Thi HN, Chi TN. Benchmarking for the automated detection and classification of southern yellow-cheeked crested gibbon calls from passive acoustic monitoring data. bioRxiv. 2024:2024-08.
DOI: 10.6084/m9.figshare.29621402
title: sfgv_OB_proteome_datasets

description: Proteomic analysis of the Spodoptera frugiperda granulovirus Occlusion Body
DOI: 10.6084/m9.figshare.29621402.v1
title: sfgv_OB_proteome_datasets

description: Proteomic analysis of the Spodoptera frugiperda granulovirus Occlusion Body
DOI: 10.17632/dfpnxgzjx6
title: Product Recommendations Powered by AI : Impacting Gen Z Purchase Intention for Sustainable E-Commerce Business Models

description: Research Dataset of Product Recommendations Powered by AI : Impacting Gen Z Purchase Intention for Sustainable E-Commerce Business Models.
DOI: 10.17632/dfpnxgzjx6.1
title: Product Recommendations Powered by AI : Impacting Gen Z Purchase Intention for Sustainable E-Commerce Business Models

description: Research Dataset of Product Recommendations Powered by AI : Impacting Gen Z Purchase Intention for Sustainable E-Commerce Business Models.
DOI: 10.15468/dl.yt6v34
title: Occurrence Download

description: A dataset containing 60 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Togo",
 "OccurrenceStatus is Present",
 "TaxonKey is Hyphaene thebaica"
 ]
}

 The dataset includes 60 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034152-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c5wnc6
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Perna viridis",
 "Country is Philippines",
 "HasCoordinate is true"
 ]
}

 The dataset includes 32 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034151-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15791204
title: Impact of Deepfake Content Promotion to Customer Trust

description: This study was motivated by the impact of deepfake use in promotional content, due to the rapid advancement of AI that has made deepfakes more sophisticated and increased their use in advertising. It involved brand trust, satisfaction, and customer trust as mediators. This study employs a quantitative approach through an online survey of 445 respondents, with data collected in between April to May and analyzed using PLS-SEM. The results indicate that attitudes toward AI are the strongest predictor of brand trust, while information quality is the primary driver of customer satisfaction. Ultimately, customer trust was found to be the most significant factor in shaping customer loyalty. The study concluded that trust is a crucial mediator. Meanwhile, it can be concluded that the success of deepfake promotions heavily depends on marketers' ability to build positive perceptions and mitigate risks to gain customer trust and drive customer loyalty.
DOI: 10.5281/zenodo.15791205
title: Impact of Deepfake Content Promotion to Customer Trust

description: This study was motivated by the impact of deepfake use in promotional content, due to the rapid advancement of AI that has made deepfakes more sophisticated and increased their use in advertising. It involved brand trust, satisfaction, and customer trust as mediators. This study employs a quantitative approach through an online survey of 445 respondents, with data collected in between April to May and analyzed using PLS-SEM. The results indicate that attitudes toward AI are the strongest predictor of brand trust, while information quality is the primary driver of customer satisfaction. Ultimately, customer trust was found to be the most significant factor in shaping customer loyalty. The study concluded that trust is a crucial mediator. Meanwhile, it can be concluded that the success of deepfake promotions heavily depends on marketers' ability to build positive perceptions and mitigate risks to gain customer trust and drive customer loyalty.
DOI: 10.17632/dsg277dgk8
title: GHG Emissions in African Oil and Gas-Producing Economies

description: This dataset includes panel data from nine African oil- and gas-producing economies spanning 1995–2020. Variables cover greenhouse gas emissions, foreign direct investment, digitalization levels, tertiary education enrollment, technological innovation indicators, and relevant control variables such as GDP, population, trade openness, renewable energy consumption, and living standards. The dataset sourced from World Bank Indicators was used to perform unit root tests, cointegration analysis, GMM estimation, robustness checks, and causality tests.
DOI: 10.15468/dl.7nkz7q
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Phalaris canariensis",
 "Country is Malta",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034153-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/dsg277dgk8.1
title: GHG Emissions in African Oil and Gas-Producing Economies

description: This dataset includes panel data from nine African oil- and gas-producing economies spanning 1995–2020. Variables cover greenhouse gas emissions, foreign direct investment, digitalization levels, tertiary education enrollment, technological innovation indicators, and relevant control variables such as GDP, population, trade openness, renewable energy consumption, and living standards. The dataset sourced from World Bank Indicators was used to perform unit root tests, cointegration analysis, GMM estimation, robustness checks, and causality tests.
DOI: 10.5281/zenodo.15785070
title: From Scroll to Sale: How Interest and Opportunity Awareness Shape Digital Start-Up Readiness

description: This study aims to identify the factors influencing individuals' readiness to start a digital business in the Greater Jakarta area. Conducted in April 2025, the study used purposive sampling to collect data from 478 respondents who currently own or have previously intended to start an online business. Data were collected via an online questionnaire based on the Self-Enhancement and Self-Protection Strategies Scale (Short Form) and a Likert scale. The respondents were individuals in Indonesia who demonstrated an interest in digital entrepreneurship. Seven variables were analyzed: motivation in entrepreneurship (ME), resources (R), entrepreneurial ability (EA), opportunity identification (OI), government support (GS), information support (IS), and digital start-up readiness (SR). Six hypotheses were tested, and the results showed that five were significant: EA → SR (p = 0.000), R → SR (p = 0.005), OI → SR (p = 0.003), ME → SR (p = 0.000), and IS → SR (p = 0.008). However, GS → SR was not significant (p = 0.160). This study's main contribution is emphasizing the importance of internal factors, particularly entrepreneurial ability and information support, in enhancing individuals' digital readiness to build start-ups. These findings provide a useful basis for developing educational strategies and policy interventions to promote digital entrepreneurship in Indonesia.
DOI: 10.5281/zenodo.15785071
title: From Scroll to Sale: How Interest and Opportunity Awareness Shape Digital Start-Up Readiness

description: This study aims to identify the factors influencing individuals' readiness to start a digital business in the Greater Jakarta area. Conducted in April 2025, the study used purposive sampling to collect data from 478 respondents who currently own or have previously intended to start an online business. Data were collected via an online questionnaire based on the Self-Enhancement and Self-Protection Strategies Scale (Short Form) and a Likert scale. The respondents were individuals in Indonesia who demonstrated an interest in digital entrepreneurship. Seven variables were analyzed: motivation in entrepreneurship (ME), resources (R), entrepreneurial ability (EA), opportunity identification (OI), government support (GS), information support (IS), and digital start-up readiness (SR). Six hypotheses were tested, and the results showed that five were significant: EA → SR (p = 0.000), R → SR (p = 0.005), OI → SR (p = 0.003), ME → SR (p = 0.000), and IS → SR (p = 0.008). However, GS → SR was not significant (p = 0.160). This study's main contribution is emphasizing the importance of internal factors, particularly entrepreneurial ability and information support, in enhancing individuals' digital readiness to build start-ups. These findings provide a useful basis for developing educational strategies and policy interventions to promote digital entrepreneurship in Indonesia.
DOI: 10.5065/cz1y-9829
title: ICARUS Chamber Experiment: Ziemann_20150220_Methyl nitrite/Nitric oxide/5-Decanol_Hydroxyl radical_DOS

description: Goals: Determine SOA yield of OH radical oxidation of the VOCSummary: Experiments were conducted in an 8.0 m^3 FEP Teflon environmental chamber in Boulder, CO, that was filled with clean, dry air [less than 5 ppb of hydrocarbons and less than 1% relative humidity (RH)] from two Aadco clean air systems and operated at ambient temperature (23 C) and pressure (630 Torr). The VOC was added to the chamber by evaporating a measured amount of the compound from a heated glass bulb into a stream of ultrahigh-purity (UHP) N2. Approximately 200 g/m^3 dioctyl sebacate (DOS) seed particles in UHP N2 were added from an evaporation?condensation apparatus. Known amounts of methyl nitrite and NO were prepared on a vacuum manifold using a calibrated glass bulb and absolute pressure gauge and then flushed into the chamber with UHP N2. Reactions were initiated by turning on blacklights that covered two walls of the chamber at 50% intensity (JNO2 = 0.37 per hour) for one hour. Photolysis of methyl nitrite created OH radicals with an average concentration of 4 x 107 molecules cm^-3, as determined from the measured decay of the VOC and estimated OH reaction rate constants. The VOC, methyl nitrite, and NO concentrations were 1, 5, and 5 ppm.Organization: Ziemann Lab Affiliation: University of Colorado, Boulder, Boulder, CO, USA Chamber: Janet (Chamber 1)Experiment Category: Gas phase chemical reaction, Photolysis, any phase, Aerosol formation Oxidant: Hydroxyl radical Reactants: Methyl nitrite, Nitric oxide, 5-Decanol Reaction Type: Photooxidation Relative Humidity: less than1 Temperature: 23 Seed Name: DOS Pressure: 630
DOI: 10.17632/thdf5zz26t
title: Potsdam and Vaihingen and Massachusetts Buildings datasets

description: Both the images and labels are cropped to 512x512, and the labels are processed into two categories.
DOI: 10.17632/thdf5zz26t.1
title: Potsdam and Vaihingen and Massachusetts Buildings datasets

description: Both the images and labels are cropped to 512x512, and the labels are processed into two categories.
DOI: 10.15468/dl.ncgsue
title: Occurrence Download

description: A dataset containing 198 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Phalaris canariensis",
 "Country is Mexico",
 "HasCoordinate is true"
 ]
}

 The dataset includes 198 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034154-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.