cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/m3c8hjww2w
title: Multi-segment Positioning with Divergent Consumption Goals Study III

description: This data measures the impact of reinforcment messaging.
DOI: 10.17632/m3c8hjww2w.1
title: Multi-segment Positioning with Divergent Consumption Goals Study III

description: This data measures the impact of reinforcment messaging.
DOI: 10.15151/esrf-es-2232208242
title: RIXS Interferometry on Stripe-Ordered La1.8-xEu0.2SrxCuO4

description: We suggest to perform a resonant inelastic x-ray scattering (RIXS) interferometry experiment at the Cu K edge of the cuprate La1.8-xEu0.2SrxCuO4 (LESCO). We aim to establish RIXS interferometry at the Cu K edge as a means to study 3d transition-metal compounds and to clarify the microscopic origin of a feature appearing in RIXS spectra of La-based cuprates close to the charge-order wave vector.
DOI: 10.17632/963wzdvcdk
title: Multi-segment Positioning with Divergent Consumption Goals Study II

description: Data measures consumers perception of motivators and barriers to participating in piloting flight training.
DOI: 10.17632/963wzdvcdk.1
title: Multi-segment Positioning with Divergent Consumption Goals Study II

description: Data measures consumers perception of motivators and barriers to participating in piloting flight training.
DOI: 10.17632/8m4rybcrps
title: Uncovering the Impact of the “Zero-waste City” Pilot Policy on Urban Green Innovation Efficiency

description: Addressing environmental challenges throughout urban development can spur green innovation. Despite its central role in solid-waste governance, the Zero-waste City initiative’s effects and mechanisms for urban green innovation remain unclear. This study quantifies the causal impact of China’s Zero-waste City pilot on urban green innovation efficiency (GIE). Using a panel of 252 prefecture-level cities (2012–2022), we construct a city-level GIE index via a super-efficiency slack-based measure (SBM) and designate the 11 first-batch pilots as the experimental group. From the remaining cities, we select 39 comparable controls using a propensity-score matching (PSM) model based on six pre-policy covariates, including GIE, economic development, foreign investment, population density, industrial structure, and urbanization. Policy effects are evaluated with a difference-in-differences (DID) model, complemented by six robustness checks. Mechanisms of policy-driven GIE promotion are further examined using patent application counts and the frequency of “Zero-waste City”-related terms in government work reports.
DOI: 10.17632/8m4rybcrps.1
title: Uncovering the Impact of the “Zero-waste City” Pilot Policy on Urban Green Innovation Efficiency

description: Addressing environmental challenges throughout urban development can spur green innovation. Despite its central role in solid-waste governance, the Zero-waste City initiative’s effects and mechanisms for urban green innovation remain unclear. This study quantifies the causal impact of China’s Zero-waste City pilot on urban green innovation efficiency (GIE). Using a panel of 252 prefecture-level cities (2012–2022), we construct a city-level GIE index via a super-efficiency slack-based measure (SBM) and designate the 11 first-batch pilots as the experimental group. From the remaining cities, we select 39 comparable controls using a propensity-score matching (PSM) model based on six pre-policy covariates, including GIE, economic development, foreign investment, population density, industrial structure, and urbanization. Policy effects are evaluated with a difference-in-differences (DID) model, complemented by six robustness checks. Mechanisms of policy-driven GIE promotion are further examined using patent application counts and the frequency of “Zero-waste City”-related terms in government work reports.
DOI: 10.17632/b6t9h9vz9s
title: Comparative analysis of the fatty acid profiles and MFGM proteome in human and small ruminant colostrum and mature milk using data-independent acquisition for targeted infant nutrition improvement

description: Supplementary tables and supplementary figures
DOI: 10.17632/b6t9h9vz9s.3
title: Comparative analysis of the fatty acid profiles and MFGM proteome in human and small ruminant colostrum and mature milk using data-independent acquisition for targeted infant nutrition improvement

description: Supplementary tables and supplementary figures
DOI: 10.17632/fvnrxdfzxw
title: Aspect & Target-Aware Contextual Bengali Abusive Content Dataset

description: This dataset represents a context-aware Bengali abusive comment corpus, compiled from publicly available YouTube comments on Bangladeshi news channels such as JamunaTV, SomoyTV, ATN News and RTv. It consists of 1,500 manually collected and annotated comments, including both abusive and non-abusive instances, to support research in abusive language detection, sentiment analysis, target identification and computational social linguistics in low-resource languages.

Each record in the dataset contains the following fields:
ID, post_title, comment, parent, sequence, aspect, target, and abusive (Yes/No). The inclusion of parent and sequence fields enables contextual linkage between comments and their replies, supporting hierarchical analysis of online interactions.

Comments were categorized across 11 aspect classes (e.g., education, economy, sports political, social and so on) and 4 target types (e.g., individual, group, society, others). To clarify this schema, we provide two representative labeled comments: An abusive comment: “এরা ছাত্র না, এ রাজাকারের বাচ্চা।” → “They are not students; they are the children of the collaborators.” (labeled abusive(yes/no) = yes; aspect: politics; target: group). A non-abusive comment: “বাংলাদেশ দল আজ দারুণ খেলেছে, গর্বিত বোধ করছি।” → “The Bangladesh team played really well today; I feel proud.” (labeled abusive(yes/no) = no; aspect: sports; target: group). These paired examples demonstrate how we map Bengali comments to binary abuse labels while capturing aspect and target for richer analysis.
DOI: 10.17632/fvnrxdfzxw.2
title: Aspect & Target-Aware Contextual Bengali Abusive Content Dataset

description: This dataset represents a context-aware Bengali abusive comment corpus, compiled from publicly available YouTube comments on Bangladeshi news channels such as JamunaTV, SomoyTV, ATN News and RTv. It consists of 1,500 manually collected and annotated comments, including both abusive and non-abusive instances, to support research in abusive language detection, sentiment analysis, target identification and computational social linguistics in low-resource languages.

Each record in the dataset contains the following fields:
ID, post_title, comment, parent, sequence, aspect, target, and abusive (Yes/No). The inclusion of parent and sequence fields enables contextual linkage between comments and their replies, supporting hierarchical analysis of online interactions.

Comments were categorized across 11 aspect classes (e.g., education, economy, sports political, social and so on) and 4 target types (e.g., individual, group, society, others). To clarify this schema, we provide two representative labeled comments: An abusive comment: “এরা ছাত্র না, এ রাজাকারের বাচ্চা।” → “They are not students; they are the children of the collaborators.” (labeled abusive(yes/no) = yes; aspect: politics; target: group). A non-abusive comment: “বাংলাদেশ দল আজ দারুণ খেলেছে, গর্বিত বোধ করছি।” → “The Bangladesh team played really well today; I feel proud.” (labeled abusive(yes/no) = no; aspect: sports; target: group). These paired examples demonstrate how we map Bengali comments to binary abuse labels while capturing aspect and target for richer analysis.
DOI: 10.17632/dtf278skpw
title: Appropriate Crop Recommendation Dataset for Cultivation in Bangladesh using IoT and Machine Learning (CropRec-BD v1, 2025)

description: This dataset supports the study “Appropriate Crop Recommended System for Cultivation using IoT and ML” and was collected in Bangladesh (multiple regions) between 20XX–2025 using low-cost IoT sensors, farmer surveys, and agricultural records. It contains time-series environmental measurements (soil moisture, soil temperature, pH, ambient temperature, relative humidity, light), geo-located field metadata (district, soil type, elevation), crop outcome labels (suitable crop recommendations, historical yields), and contextual socio-economic variables (farm size, irrigation type, planting dates, fertilizer usage). The dataset is organized to facilitate supervised and semi-supervised machine learning for crop recommendation, yield prediction, and interpretability research. Data has been anonymized to remove personally-identifying information; consent was obtained from participating farmers. Example use cases: training crop recommendation classifiers, benchmarking transfer learning across regions, developing explainable AI models for agronomic advisories. The dataset includes raw CSV files, a cleaned/merged master table, feature dictionaries, and sample code (Python notebooks) demonstrating preprocessing and a baseline ML model. Licensed under CC BY 4.0 to enable academic and commercial reuse with attribution

The data was gathered over the past 5 years (2017 to 2022)
of agricultural data from the websites of the Bangladesh
Agricultural Research Institute and NASA. There are
roughly 3,000 records for nine different crops. Temperature,
humidity, and rainfall are all included in the crop-suggested
information.
The databases contain crop data from all of Bangladesh.
Several different types of crops are grown in Bangladesh. It is
challenging to analyse every crop variety. Therefore, we have
done the top 9 crops that are grown extensively. When it comes
to preprocessing, all the data are transformed into numerical data. A similar procedure was used for fertilizer data.
List of crops considered:
• Maize
• Strawberry
• Wheat
• Potato
• Banana
• Mango
• Jute
• Pineapple
• Sugercane
DOI: 10.17632/dtf278skpw.1
title: Appropriate Crop Recommendation Dataset for Cultivation in Bangladesh using IoT and Machine Learning (CropRec-BD v1, 2025)

description: This dataset supports the study “Appropriate Crop Recommended System for Cultivation using IoT and ML” and was collected in Bangladesh (multiple regions) between 20XX–2025 using low-cost IoT sensors, farmer surveys, and agricultural records. It contains time-series environmental measurements (soil moisture, soil temperature, pH, ambient temperature, relative humidity, light), geo-located field metadata (district, soil type, elevation), crop outcome labels (suitable crop recommendations, historical yields), and contextual socio-economic variables (farm size, irrigation type, planting dates, fertilizer usage). The dataset is organized to facilitate supervised and semi-supervised machine learning for crop recommendation, yield prediction, and interpretability research. Data has been anonymized to remove personally-identifying information; consent was obtained from participating farmers. Example use cases: training crop recommendation classifiers, benchmarking transfer learning across regions, developing explainable AI models for agronomic advisories. The dataset includes raw CSV files, a cleaned/merged master table, feature dictionaries, and sample code (Python notebooks) demonstrating preprocessing and a baseline ML model. Licensed under CC BY 4.0 to enable academic and commercial reuse with attribution

The data was gathered over the past 5 years (2017 to 2022)
of agricultural data from the websites of the Bangladesh
Agricultural Research Institute and NASA. There are
roughly 3,000 records for nine different crops. Temperature,
humidity, and rainfall are all included in the crop-suggested
information.
The databases contain crop data from all of Bangladesh.
Several different types of crops are grown in Bangladesh. It is
challenging to analyse every crop variety. Therefore, we have
done the top 9 crops that are grown extensively. When it comes
to preprocessing, all the data are transformed into numerical data. A similar procedure was used for fertilizer data.
List of crops considered:
• Maize
• Strawberry
• Wheat
• Potato
• Banana
• Mango
• Jute
• Pineapple
• Sugercane
DOI: 10.15468/dl.dq8p57
title: Occurrence Download

description: A dataset containing 17097 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Viet Nam",
 "Year is 2024",
 "InstitutionCode is iNaturalist"
 ]
}

 The dataset includes 17097 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012901-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qcmccn
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dacryopinax crenata"
 ]
}

 The dataset includes 4 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012902-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/48xkkxgdjg
title: Ecological Footprint (AD25)

description: This dataset presents the results of 233 High School students in Mexico that answered the Ecological Footprint Calculator operated by the Global Footprint Network. Students computed their ecological footprint at the begginging (variables which names end with "t.0") and at the end (variables which names end with "t.1") of the academic semester. The variable "Actions" denotes whether the student was part of the experiment group of the educational innovation, that is, if they received the pluralistic intervention and ecological actions activity. Demographic charactheristics of sex, age and year (academic semester of the student) were used to pair the observations of the "experiment" and "control groups" using the propensity score matching in a quasi-experiment methodology.
DOI: 10.17632/48xkkxgdjg.1
title: Ecological Footprint (AD25)

description: This dataset presents the results of 233 High School students in Mexico that answered the Ecological Footprint Calculator operated by the Global Footprint Network. Students computed their ecological footprint at the begginging (variables which names end with "t.0") and at the end (variables which names end with "t.1") of the academic semester. The variable "Actions" denotes whether the student was part of the experiment group of the educational innovation, that is, if they received the pluralistic intervention and ecological actions activity. Demographic charactheristics of sex, age and year (academic semester of the student) were used to pair the observations of the "experiment" and "control groups" using the propensity score matching in a quasi-experiment methodology.
DOI: 10.17632/djdmhv3ghs
title: Supplementary Material

description: Supplementary material
DOI: 10.17632/djdmhv3ghs.3
title: Supplementary Material

description: Supplementary material
DOI: 10.17632/8hcckh33ts
title: Sustainable Land Management by Agrivoltaics in Colombia’s Post-Conflict Regions: An Integrated Approach from the Water–Energy–Food Nexus

description: This dataset compiles the technical, economic, and social results from the agrivoltaic pilot simulations conducted in the municipalities of Pisba (Boyacá) and Cabrera (Cundinamarca), Colombia. It includes financial scenario bands (Free Cash Flow, revenues, and costs under conservative, moderate, and optimistic cases), as well as key performance indicators for photovoltaic generation, hydroponic yields, water-use efficiency, greenhouse gas mitigation, and local job creation. The data were produced under the project “Microgrids: energía flexible y eficiente para Cundinamarca” (BPIN: 2021000100523) using the expanded Water–Energy–Food–Soil–Climate–Communities (WEFSCC) nexus framework. The dataset supports reproducibility and potential scaling of agrivoltaic systems in Andean rural regions with similar agroclimatic conditions.
DOI: 10.17632/8hcckh33ts.1
title: Sustainable Land Management by Agrivoltaics in Colombia’s Post-Conflict Regions: An Integrated Approach from the Water–Energy–Food Nexus

description: This dataset compiles the technical, economic, and social results from the agrivoltaic pilot simulations conducted in the municipalities of Pisba (Boyacá) and Cabrera (Cundinamarca), Colombia. It includes financial scenario bands (Free Cash Flow, revenues, and costs under conservative, moderate, and optimistic cases), as well as key performance indicators for photovoltaic generation, hydroponic yields, water-use efficiency, greenhouse gas mitigation, and local job creation. The data were produced under the project “Microgrids: energía flexible y eficiente para Cundinamarca” (BPIN: 2021000100523) using the expanded Water–Energy–Food–Soil–Climate–Communities (WEFSCC) nexus framework. The dataset supports reproducibility and potential scaling of agrivoltaic systems in Andean rural regions with similar agroclimatic conditions.
DOI: 10.17632/g9fyc6zgbr.1
title: Iron mobility and redox transfer in the oceanic lithosphere during nascent subduction: Constraint from Fe isotope composition of Xigaze rodingite in southern Tibet

description: Supplementary Material S1-9
DOI: 10.17632/rjtvy2v4dx
title: Dataset for "A Novel Approach for Calibrating the Stress Categories of Thermal Indices"

description: This dataset contains thermal sensation and thermal acceptability votes collected during 15 periodic field campaigns, conducted over 13 days between May 2024 and May 2025 in Cairo, Egypt. Each record includes the corresponding Universal Thermal Climate Index (UTCI) value calculated from meteorological measurements, obtained using a HOBO-U30 weather station and an H-30 Globe thermometer. Binary indicators of short- and long-term adaptation are also provided. The dataset supports the study “A Novel Approach for Calibrating the Stress Categories of Thermal Indices.”
DOI: 10.17632/rjtvy2v4dx.1
title: Dataset for "A Novel Approach for Calibrating the Stress Categories of Thermal Indices"

description: This dataset contains thermal sensation and thermal acceptability votes collected during 15 periodic field campaigns, conducted over 13 days between May 2024 and May 2025 in Cairo, Egypt. Each record includes the corresponding Universal Thermal Climate Index (UTCI) value calculated from meteorological measurements, obtained using a HOBO-U30 weather station and an H-30 Globe thermometer. Binary indicators of short- and long-term adaptation are also provided. The dataset supports the study “A Novel Approach for Calibrating the Stress Categories of Thermal Indices.”
DOI: 10.17632/7g3j7c7kbt
title: A Three-Decade Bibliometric Investigation of Research Trends in Quantum Critical Behaviour Dataset

description: The dataset is for for research on A Three-Decade Bibliometric Investigation of Research Trends in Quantum Critical Behaviour. The dataset was downloaded from on the 19th of June 2023 from the Scopus database using the keywords ‘quantum-critical-behaviour’ OR ‘quantum-criticality’ OR ‘quantum-critical-point’ OR ‘quantum-phase-transition’ OR “quantum-critical-phenomena’ for publications from 1992 to 2022. The hyphen (-) ensures that the database searches for exact phrases in the title, abstract, author keywords, or Keywords Plus of publications. The dataset comprised of journal articles, conference papers, review articles, book chapters, books, and letters across all Scopus listed languages.
DOI: 10.17632/7g3j7c7kbt.1
title: A Three-Decade Bibliometric Investigation of Research Trends in Quantum Critical Behaviour Dataset

description: The dataset is for for research on A Three-Decade Bibliometric Investigation of Research Trends in Quantum Critical Behaviour. The dataset was downloaded from on the 19th of June 2023 from the Scopus database using the keywords ‘quantum-critical-behaviour’ OR ‘quantum-criticality’ OR ‘quantum-critical-point’ OR ‘quantum-phase-transition’ OR “quantum-critical-phenomena’ for publications from 1992 to 2022. The hyphen (-) ensures that the database searches for exact phrases in the title, abstract, author keywords, or Keywords Plus of publications. The dataset comprised of journal articles, conference papers, review articles, book chapters, books, and letters across all Scopus listed languages.
DOI: 10.15468/dl.jxuqwj
title: Occurrence Download

description: A dataset containing 144 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Iran (Islamic Republic of)",
 "Year is 2010",
 "InstitutionCode is iNaturalist"
 ]
}

 The dataset includes 144 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012904-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/dpw55tdsmj
title: Epidermolysis Bullosa Nevus: clinical and digital dermoscopy images

description: Epidermolysis Bullosa (EB) nevi are an infrequent condition characterized by acquired and asymmetrical melanocytic lesions that arise in areas of former blistering in patients with all forms of inherited EB. These lesions usually have irregular pigmentation, satellite lesions (Figure 1), and an eruptive growth. The evaluation of these benign moles with the ABCD rules for clinical recognition of melanoma (MM) often results in false positives. The dermoscopic pattern of EB nevi was previously reported, and most lesions presented melanoma-associated dermoscopic criteria, such as irregular dots/globules (Figure 2), atypical pigment network, irregular pigmentation, and structureless areas. No cases of malignant transformation of EB nevi have been reported in the literature. Still, adjuvant evaluation with reflectance confocal microscopy or early biopsy is recommended in highly suspicious lesions to differentiate EB nevus from melanoma.

Figure 1. EB nevus. Clinical image of nevus on back (arrows).
Figure 2. EB nevus. Digital dermoscopy showing irregular pigmentation and irregular dots and globules.
DOI: 10.17632/dpw55tdsmj.1
title: Epidermolysis Bullosa Nevus: clinical and digital dermoscopy images

description: Epidermolysis Bullosa (EB) nevi are an infrequent condition characterized by acquired and asymmetrical melanocytic lesions that arise in areas of former blistering in patients with all forms of inherited EB. These lesions usually have irregular pigmentation, satellite lesions (Figure 1), and an eruptive growth. The evaluation of these benign moles with the ABCD rules for clinical recognition of melanoma (MM) often results in false positives. The dermoscopic pattern of EB nevi was previously reported, and most lesions presented melanoma-associated dermoscopic criteria, such as irregular dots/globules (Figure 2), atypical pigment network, irregular pigmentation, and structureless areas. No cases of malignant transformation of EB nevi have been reported in the literature. Still, adjuvant evaluation with reflectance confocal microscopy or early biopsy is recommended in highly suspicious lesions to differentiate EB nevus from melanoma.

Figure 1. EB nevus. Clinical image of nevus on back (arrows).
Figure 2. EB nevus. Digital dermoscopy showing irregular pigmentation and irregular dots and globules.