cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/cjz3dn2z95.3
title: Designing a Sustainable Social Campaign to Reduce Food Waste: A Case Study of 'Makan Sampai Titik' for Generation Z Awareness

description: Food waste is a global issue with significant environmental, economic, and social impacts. In Indonesia, the habit of leaving food uneaten remains common, especially among the younger generation. The campaign “Makan Sampai Titik” was designed as an educational effort to raise awareness of the importance of finishing meals, using a visual communication design approach tailored to the characteristics of Generation Z. The design process involved problem analysis, literature studies, observation, creative strategy development, and visual style exploration. This campaign delivers its core message through the tagline “Slay Your Meals, No Crumb Left,” presented via main media platforms such as Instagram, TikTok, and ambient media. Additionally, promotional materials such as printed posters, merchandise, and other supporting media are used to expand the campaign’s reach and reinforce its visual identity. The results indicate that an appropriate visual approach and relevant communication style can effectively strengthen the delivery of social messages. Currently, audience testing is underway to evaluate the overall impact of the campaign. This campaign is expected to contribute to raising awareness and encouraging behavior change in food consumption among young people.
DOI: 10.25326/ccqe-k305
title: Atmospheric simulation chamber study: furan+trans-2-butene + OH - Gas-phase oxidation - kinetic study - 2020-02-03
DOI: 10.25326/hrgy-d247
title: Atmospheric simulation chamber study: furan+isoprene + OH - Gas-phase oxidation - kinetic study - 2020-01-24
DOI: 10.25326/5hzh-2a72
title: Atmospheric simulation chamber study: E-2-hexenal + O3 - Gas-phase oxidation - kinetic study - 2005-01-17
DOI: 10.25326/ws6w-se49
title: Atmospheric simulation chamber study: E-2-hexenal + O3 - Gas-phase oxidation - kinetic study - 2005-01-14
DOI: 10.25326/7565-aj05
title: Atmospheric simulation chamber study: Z-2-hexenal  + O3 - Gas-phase oxidation - kinetic study - 2005-05-07
DOI: 10.25326/pwk3-hw05
title: Atmospheric simulation chamber study: E-2-hexenal + O3 - Gas-phase oxidation - kinetic study - 2005-01-19
DOI: 10.15468/zdn4w7
title: 2006 BP Exploration and Production BP Exploration operating company Ltd. UKCS 9/23b Harding site survey May-June 2006 environmental report - Harding

description: The object of this survey was to investigate the seabed, prior to the installation of a sub-sea pipeline, to determine changes in contaminant status and macrofaunal species assemblages since the time of the previous survey.
DOI: 10.25326/aqcn-m987
title: Atmospheric simulation chamber study: Z-2-hexenal  + O3 - Gas-phase oxidation - kinetic study - 2005-07-05
DOI: 10.25326/djyv-rt51
title: Atmospheric simulation chamber study: Z-2-hexenal  + O3 - Gas-phase oxidation - kinetic study - 2005-07-04
DOI: 10.25326/ff11-5c70
title: Atmospheric simulation chamber study: Z-2-hexenal  + O3 - Gas-phase oxidation - kinetic study - 2005-07-06
DOI: 10.25326/rv8n-ta80
title: Atmospheric simulation chamber study: Z-3-hexenal + O3 - Gas-phase oxidation - kinetic study - 2005-02-03
DOI: 10.25326/x8r7-fp45
title: Atmospheric simulation chamber study: Z-3-hexenal + O3 - Gas-phase oxidation - kinetic study - 2005-02-07
DOI: 10.25326/apa0-vj81
title: Atmospheric simulation chamber study: Z-3-hexenal + O3 - Gas-phase oxidation - kinetic study - 2005-02-09
DOI: 10.15468/dl.qz3x5b
title: Occurrence Download

description: A dataset containing 50313 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Issue is one of (Coordinate rounded, Continent derived from country, Continent derived from coordinates, The scientific name ID was not used in backbone matching, The taxon concept ID was not used in backbone matching, The taxon ID was not used in backbone matching, Elevation min max swapped)",
 "OccurrenceStatus is Present",
 "TaxonKey is Necrosyrtes monachus (Temminck, 1823)",
 "Year 1970-2025"
 ]
}

 The dataset includes 50313 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067110-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21947/2570104
title: Site G - Cup Anemometer / Reviewed Data

description: This dataset contains cup anemometer data deployed on tethered balloon system at AWAKEN site G. The cup data include time stamp, wind speed, wind direction, gust wind speed, vertical wind speed, roll, pitch, latitude, longitude, and altitude. Z04 refers to the fourth height position of the cup anemometers mounted on the tethered balloon.
DOI: 10.25326/pw1g-sf78
title: Atmospheric simulation chamber study: trans-2-butene+cyclohexane + Cl - Gas-phase oxidation - kinetic study - 2020-09-11
DOI: 10.25326/30sg-nb26
title: Atmospheric simulation chamber study: propene+trans-2-butene + O3 - Gas-phase oxidation - kinetic study - 2020-03-03
DOI: 10.17632/9cc8k5v7w4.1
title: BanglaMood: A Rich Audio Dataset for Eight Emotion Recognition in Bangla Speech

description: The BanglaMOOD dataset comprises 3,220 audio files in .wav format, each capturing vocal expressions of human emotion in Bangla. The dataset features eight emotion categories: Angry, Happy, Sad, Neutral, Surprised, Fear, Disappointment, and Excitement. Each audio sample ranges from 1 to 5 seconds in duration, with all files standardized to 5 seconds for consistency in feature extraction. The audio was collected from a wide variety of real-life contexts, including short stories, vlogs, and sports highlights sourced from YouTube, ensuring a broad range of expressive and natural vocalizations. Both male and female voices are included to provide gender diversity. In terms of distribution, the Neutral emotion has the highest number of samples, followed by Angry, while Excitement has the lowest. Specifically, there are 302 Happy samples (185 male and 117 female), 336 Sad samples (152 male and 184 female), 630 Angry samples (421 male and 209 female), 693 Neutral samples (549 male and 144 female), 285 Surprise samples (195 male and 90 female), 391 Fear samples (288 male and 103 female), 330 Disappointment samples (200 male and 130 female), and 253 Excitement samples (200 male and 53 female). In most categories, male voices are more prevalent, except for the Sad emotion, where female samples are more numerous. For the Angry emotion, female voices have the highest number of samples. The dataset is accompanied by visualizations, including a pie chart illustrating the proportion of each emotion class and a bar chart showing the gender distribution for each emotion. All audio files are standardized to a duration of 5 seconds. Overall, the BanglaMOOD dataset offers a diverse and balanced collection of emotional speech samples in Bangla, making it a valuable resource for research and development in speech emotion recognition and related fields.
DOI: 10.25326/efdn-wm90
title: Atmospheric simulation chamber study: Acrolein+Propene + Cl - Gas-phase oxidation - kinetic study - 2020-05-25
DOI: 10.25326/ezhy-6m90
title: Atmospheric simulation chamber study: E-2-Butene+Isoprene + OH - Gas-phase oxidation - kinetic study - 2020-05-11
DOI: 10.25326/2sbc-6838
title: Atmospheric simulation chamber study: Cyclohexane+Acrolein + Cl - Gas-phase oxidation - kinetic study - 2020-05-25
DOI: 10.25326/b63y-2j59
title: Atmospheric simulation chamber study: cyclohexane+propene + Cl - Gas-phase oxidation - kinetic study - 2020-10-13
DOI: 10.25326/c2w9-6776
title: Atmospheric simulation chamber study: trans-2-butene+isoprene + Cl - Gas-phase oxidation - kinetic study - 2020-11-09
DOI: 10.25326/75qh-dw19
title: Atmospheric simulation chamber study: trans-2-butene+Acrolein + Cl - Gas-phase oxidation - kinetic study - 2020-09-25
DOI: 10.5281/zenodo.15728574
title: Data complementing the Avian influenza overview March - June 2025

description: Data complementing the Avian influenza overview March - June 2025

 

Annex A – Data on wild birds

The annex contains figures and tables on HPAI virus detections in wild birds in Europe and worldwide.

Annex B – Characteristics of the HPAI-affected poultry establishments

The annex contains a table with the characteristics of the HPAI-affected poultry establishments by affected European country with suspicion dates between 22 January 2025 and 17 May 2025 (and not yet reported in previous reports).
description: EU; en; xlsx; BIOHAW@efsa.europa.eu
DOI: 10.5281/zenodo.15728573
title: Data complementing the Avian influenza overview March - June 2025

description: Data complementing the Avian influenza overview March - June 2025

 

Annex A – Data on wild birds

The annex contains figures and tables on HPAI virus detections in wild birds in Europe and worldwide.

Annex B – Characteristics of the HPAI-affected poultry establishments

The annex contains a table with the characteristics of the HPAI-affected poultry establishments by affected European country with suspicion dates between 22 January 2025 and 17 May 2025 (and not yet reported in previous reports).
description: EU; en; xlsx; BIOHAW@efsa.europa.eu
DOI: 10.5281/zenodo.15729264
title: Thermal conductivity and thermal diffusivity of lunar mantle olivine
DOI: 10.17632/d4tzvjsysx
title: Beyond Human Bias? The Halo Effect Paradox and Reversal in Product Design Evaluation by LLMs

description: This study examines the consistency of Large Language Models (such as GPT -4o) in aligning with human experts in evaluating product design proposals, as well as the potential biases that may arise in this process. The experiment was based on submissions from a well-known design competition. GPT-4o was tasked with scoring designs under three different prompt conditions: a structured evaluation framework, a structured evaluation framework with background information, and a structured evaluation framework with background information plus suppression instructions. The consistency of its scores was then compared to those of human experts. The results showed that under the structured evaluation framework alone, the model's scores closely matched those of human evaluators, demonstrating its ability to recognize differences in multi-scheme comparisons. However, when provided additional background information, the consistency significantly decreased, indicating that the model exhibited cognitive biases similar to the halo effect. The introduction of suppression instructions effectively mitigated these biases. This study offers valuable insights for optimizing the use of Large Language Models in product design evaluation and enhancing the reliability of intelligent evaluation methods.
DOI: 10.17632/d4tzvjsysx.1
title: Beyond Human Bias? The Halo Effect Paradox and Reversal in Product Design Evaluation by LLMs

description: This study examines the consistency of Large Language Models (such as GPT -4o) in aligning with human experts in evaluating product design proposals, as well as the potential biases that may arise in this process. The experiment was based on submissions from a well-known design competition. GPT-4o was tasked with scoring designs under three different prompt conditions: a structured evaluation framework, a structured evaluation framework with background information, and a structured evaluation framework with background information plus suppression instructions. The consistency of its scores was then compared to those of human experts. The results showed that under the structured evaluation framework alone, the model's scores closely matched those of human evaluators, demonstrating its ability to recognize differences in multi-scheme comparisons. However, when provided additional background information, the consistency significantly decreased, indicating that the model exhibited cognitive biases similar to the halo effect. The introduction of suppression instructions effectively mitigated these biases. This study offers valuable insights for optimizing the use of Large Language Models in product design evaluation and enhancing the reliability of intelligent evaluation methods.
DOI: 10.5281/zenodo.15649038
title: Thermal conductivity and thermal diffusivity of lunar mantle olivine
DOI: 10.5281/zenodo.15649039
title: Thermal conductivity and thermal diffusivity of lunar mantle olivine
DOI: 10.21947/2570105
title: Site A1 - Atmospheric Sensor / Reviewed Data

description: This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site A1. Z04 refers to the fourth height position of the iMet-XQ2 mounted on the tethered balloon.
DOI: 10.17632/jtxfcvt39k
title: Appendix of Explainable AI for coal Hardgrove grindability index prediction: a genetic programming and linear regression approach

description: This file, provided as an appendix to the paper “Explainable AI for Coal Hardgrove Grindability Index Prediction: A Genetic Programming and Linear Regression Approach,” contains two main parts that offer detailed background information on the prediction models for the Coal Hardgrove Grindability Index (HGI) and related coal sample statistics.

1. Summary of Regression Models (Appendix A):
 This section summarizes various regression models from multiple publications used for HGI prediction, including information about the datasets from different countries (such as Serbia, Poland, India, China, Turkey, and Kentucky).
2. Statistical Analysis and Visualization of the CAER Dataset (Appendix B):
 This part provides a detailed statistical description of 902 coal samples from the CAER (University of Kentucky Center for Applied Energy Research (CAER) dataset).
 The variables include moisture, ash, volatile matter, carbon, hydrogen, nitrogen, oxygen, sulfur, various mineral components, and other coal properties (such as different organic matter contents and reflectance indices).
 The table presents the minimum value, maximum value, mean, and standard deviation for each variable, enabling users to gain a comprehensive understanding of the physical and chemical properties of the coal samples. This information is crucial for developing regression models related to coal grindability prediction.
 In addition to the statistical table, we have also included boxplots for the CAER dataset to visually illustrate the distribution and variability of key variables.

Additional Information:
In addition to the tabular data and boxplot figures, related literature references are provided, allowing users to trace the original studies and methods, thereby enhancing the reliability and reproducibility of the dataset.
DOI: 10.17632/jtxfcvt39k.5
title: Appendix of Explainable AI for coal Hardgrove grindability index prediction: a genetic programming and linear regression approach

description: This file, provided as an appendix to the paper “Explainable AI for Coal Hardgrove Grindability Index Prediction: A Genetic Programming and Linear Regression Approach,” contains two main parts that offer detailed background information on the prediction models for the Coal Hardgrove Grindability Index (HGI) and related coal sample statistics.

1. Summary of Regression Models (Appendix A):
 This section summarizes various regression models from multiple publications used for HGI prediction, including information about the datasets from different countries (such as Serbia, Poland, India, China, Turkey, and Kentucky).
2. Statistical Analysis and Visualization of the CAER Dataset (Appendix B):
 This part provides a detailed statistical description of 902 coal samples from the CAER (University of Kentucky Center for Applied Energy Research (CAER) dataset).
 The variables include moisture, ash, volatile matter, carbon, hydrogen, nitrogen, oxygen, sulfur, various mineral components, and other coal properties (such as different organic matter contents and reflectance indices).
 The table presents the minimum value, maximum value, mean, and standard deviation for each variable, enabling users to gain a comprehensive understanding of the physical and chemical properties of the coal samples. This information is crucial for developing regression models related to coal grindability prediction.
 In addition to the statistical table, we have also included boxplots for the CAER dataset to visually illustrate the distribution and variability of key variables.

Additional Information:
In addition to the tabular data and boxplot figures, related literature references are provided, allowing users to trace the original studies and methods, thereby enhancing the reliability and reproducibility of the dataset.
DOI: 10.6084/m9.figshare.29390672
title: Grain size parameters and profile elevation data of Dasha Beach

description: The dataset includes grain size parameters from four survey sessions and profile elevation data from Dasha Beach on Nantian Island, Zhejiang Province, China. Surveys A, B, C, and D were conducted on August 12, 2022, September 7, 2022, September 17, 2022, and December 23, 2022, respectively, to study the response and recovery processes of Dasha Beach under the influence of typhoon events.
DOI: 10.6084/m9.figshare.29390672.v1
title: Grain size parameters and profile elevation data of Dasha Beach

description: The dataset includes grain size parameters from four survey sessions and profile elevation data from Dasha Beach on Nantian Island, Zhejiang Province, China. Surveys A, B, C, and D were conducted on August 12, 2022, September 7, 2022, September 17, 2022, and December 23, 2022, respectively, to study the response and recovery processes of Dasha Beach under the influence of typhoon events.
DOI: 10.25326/knst-jp28
title: Atmospheric simulation chamber study: alpha-terpinene + NO3 - Gas-phase oxidation - kinetic study - 2017-12-19
DOI: 10.25326/j6cz-7484
title: Atmospheric simulation chamber study: alpha-terpinene + NO3 - Gas-phase oxidation - kinetic study - 2017-12-14
DOI: 10.25326/jy9e-we04
title: Atmospheric simulation chamber study: alpha-terpinene + NO3 - Gas-phase oxidation - kinetic study - 2017-12-14
DOI: 10.25326/kb20-fn74
title: Atmospheric simulation chamber study: 3-methyl-3-penten-2-one+cyclohexene + O3 - Gas-phase oxidation - kinetic study - 2020-05-04
DOI: 10.25326/kj3x-xq65
title: Atmospheric simulation chamber study: 3-methyl-3-penten-2-one+cyclohexene + O3 - Gas-phase oxidation - kinetic study - 2020-05-04
DOI: 10.25326/kzzs-y024
title: Atmospheric simulation chamber study: 3-methyl-3-penten-2-one+trans-2-butene + O3 - Gas-phase oxidation - kinetic study - 2020-05-05
DOI: 10.25326/nxmv-td81
title: Atmospheric simulation chamber study: 3-methyl-3-penten-2-one+trans-2-butene + O3 - Gas-phase oxidation - kinetic study - 2020-05-06
DOI: 10.25326/vz9m-cw77
title: Atmospheric simulation chamber study: 3-methyl-3-penten-2-one+trans-2-butene + O3 - Gas-phase oxidation - kinetic study - 2020-05-05
DOI: 10.25326/a62e-ta20
title: Atmospheric simulation chamber study: 3-methyl-3-penten-2-one+2-methylpropene + O3 - Gas-phase oxidation - kinetic study - 2020-05-18
DOI: 10.25326/hacr-f578
title: Atmospheric simulation chamber study: 3-methyl-3-penten-2-one+2-methylpropene + O3 - Gas-phase oxidation - kinetic study - 2020-05-18
DOI: 10.25326/5ktp-z082
title: Atmospheric simulation chamber study: 3-penten-2-one+cyclohexene + O3 - Gas-phase oxidation - kinetic study - 2020-05-21
DOI: 10.25326/js4j-v381
title: Atmospheric simulation chamber study: 3-penten-2-one+cyclohexene + O3 - Gas-phase oxidation - kinetic study - 2020-05-21
DOI: 10.25326/4z72-5787
title: Atmospheric simulation chamber study: 4-methyl-3-penten-2-one+1,3-butadiene + O3 - Gas-phase oxidation - kinetic study - 2020-06-17
DOI: 10.25326/70yn-e312
title: Atmospheric simulation chamber study: 3-penten-2-one+isobutylene + O3 - Gas-phase oxidation - kinetic study - 2020-05-26
DOI: 10.25326/cajx-xs98
title: Atmospheric simulation chamber study: 3-penten-2-one+isoprene + O3 - Gas-phase oxidation - kinetic study - 2020-05-26
DOI: 10.25326/6qd7-gq11
title: Atmospheric simulation chamber study: 4-methyl-3-penten-2-one+1,3-butadiene + O3 - Gas-phase oxidation - kinetic study - 2020-06-01
DOI: 10.25326/b2z4-0669
title: Atmospheric simulation chamber study: 4-methyl-3-penten-2-one+isobutylene + O3 - Gas-phase oxidation - kinetic study - 2020-06-01
DOI: 10.25326/d905-5373
title: Atmospheric simulation chamber study: 4-methyl-3-penten-2-one+isobutylene + O3 - Gas-phase oxidation - kinetic study - 2020-06-02
DOI: 10.25326/hhs3-5q15
title: Atmospheric simulation chamber study: methyl 3-methyl-2-butenoate+1,3-butadiene + O3 - Gas-phase oxidation - kinetic study - 2020-06-02
DOI: 10.25326/3tg0-n145
title: Atmospheric simulation chamber study: methyl 3-methyl-2-butenoate+1,3-butadiene + O3 - Gas-phase oxidation - kinetic study - 2020-06-10
DOI: 10.25326/bt95-ht87
title: Atmospheric simulation chamber study: methyl 3-methyl-2-butenoate+1,3-butadiene + O3 - Gas-phase oxidation - kinetic study - 2020-06-03
DOI: 10.25326/ybk7-md50
title: Atmospheric simulation chamber study: methyl 3-methyl-2-butenoate+ethene + O3 - Gas-phase oxidation - kinetic study - 2020-06-03
DOI: 10.25326/1nd4-w778
title: Atmospheric simulation chamber study: methyl 3-methyl-2-butenoate+ethene + O3 - Gas-phase oxidation - kinetic study - 2020-07-07
DOI: 10.25326/my27-s520
title: Atmospheric simulation chamber study: methyl 3-methyl-2-butenoate+ethene + O3 - Gas-phase oxidation - kinetic study - 2020-06-10
DOI: 10.25326/cymg-ax78
title: Atmospheric simulation chamber study: methyl crotonate+1,3-butadiene + O3 - Gas-phase oxidation - kinetic study - 2020-06-08
DOI: 10.25326/fwnx-bz15
title: Atmospheric simulation chamber study: methyl crotonate+ethene + O3 - Gas-phase oxidation - kinetic study - 2020-06-08
DOI: 10.25326/2zmt-9503
title: Atmospheric simulation chamber study: methyl crotonate+isobutylene + O3 - Gas-phase oxidation - kinetic study - 2020-06-17
DOI: 10.25326/bp3g-my81
title: Atmospheric simulation chamber study: methyl crotonate+ethene + O3 - Gas-phase oxidation - kinetic study - 2020-07-07
DOI: 10.25326/ke9z-tg58
title: Atmospheric simulation chamber study: methyl methacrylate+ethene + O3 - Gas-phase oxidation - kinetic study - 2020-06-18
DOI: 10.25326/ckj6-0n56
title: Atmospheric simulation chamber study: methyl methacrylate+isobutylene + O3 - Gas-phase oxidation - kinetic study - 2020-09-07
DOI: 10.25326/rey0-3061
title: Atmospheric simulation chamber study: methyl methacrylate+isobutylene + O3 - Gas-phase oxidation - kinetic study - 2020-06-18
DOI: 10.25326/8ekh-4c74
title: Atmospheric simulation chamber study: methyl methacrylate+isobutylene + O3 - Gas-phase oxidation - kinetic study - 2020-09-07
DOI: 10.25326/mnmv-r935
title: Atmospheric simulation chamber study: methyl methacrylate+isobutylene + O3 - Gas-phase oxidation - kinetic study - 2020-09-10
DOI: 10.25326/sjbv-5n63
title: Atmospheric simulation chamber study: methyl tiglate+cyclohexene + O3 - Gas-phase oxidation - kinetic study - 2020-09-10
DOI: 10.25326/tq61-ay19
title: Atmospheric simulation chamber study: methyl tiglate+cyclohexene + O3 - Gas-phase oxidation - kinetic study - 2020-10-14
DOI: 10.25326/fpd4-sf20
title: Atmospheric simulation chamber study: methyl tiglate+trans-2-butene + O3 - Gas-phase oxidation - kinetic study - 2020-10-12
DOI: 10.25326/xmbs-bt75
title: Atmospheric simulation chamber study: methyl tiglate+cyclohexene + O3 - Gas-phase oxidation - kinetic study - 2020-10-14
DOI: 10.25326/z8dg-w412
title: Atmospheric simulation chamber study: methyl tiglate+trans-2-butene + O3 - Gas-phase oxidation - kinetic study - 2020-10-12
DOI: 10.25326/34y9-hf81
title: Atmospheric simulation chamber study: methyl tiglate+trans-2-butene + O3 - Gas-phase oxidation - kinetic study - 2020-10-15
DOI: 10.25326/4saj-0109
title: Atmospheric simulation chamber study: cyclohexene+E-2-Butene + O3 - Gas-phase oxidation - kinetic study - 2020-01-20
DOI: 10.25326/62z7-4t79
title: Atmospheric simulation chamber study: Z-2-Hexenal+methyl vinyl ketone + O3 - Gas-phase oxidation - kinetic study - 2018-09-17