cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/3gms2zvykb
title: Façade Thermal Performance Dataset for Maintenance and Retrofit

description: This dataset contains in-situ U-value measurements of walls and windows and thermal images from a building in Ireland. It includes time-series heat flux and temperature data, along with calculated U-values for multiple façade elements. The data support façade maintenance and retrofit assessment.
DOI: 10.17632/3gms2zvykb.1
title: Façade Thermal Performance Dataset for Maintenance and Retrofit

description: This dataset contains in-situ U-value measurements of walls and windows and thermal images from a building in Ireland. It includes time-series heat flux and temperature data, along with calculated U-values for multiple façade elements. The data support façade maintenance and retrofit assessment.
DOI: 10.17632/vgpr6b99vf
title: Dataset of illicit drugs consumption through wastewater during and post COVID-19 in San Pedro de la Paz, Chile.

description: This dataset was generated to apply the wastewater-based epidemiology (WBE), for the first time, in a Chilean municipality to quantify community-level illicit drug consumption using standardized sampling and analytical procedures. The study selected four metabolites (benzoylegnonine, THCCOOH, Anfetamine and MDMA) of illicit drugs present in wastewater to measure in LC–MS/MS and converted, through back-calculation, into normalized estimates of consumption that are comparable across time when similar protocols are used. To evaluate this, 24 h composite samples were collected at the San Pedro de la Paz Wastewater Treatment Plant (WWTP) in two distinct periods: (i) during COVID-19: twelve days in August 2021 and; (ii) Pos-COVID-19: weekly sampling from September 2022 to October 2023.
All samples were collected, preserved with sodium metabisulfite, stored at 4 °C, and processed within three days to ensure consistency across both sampling periods. The data were then normalized using wastewater flow rates and the estimated population served by the WWTP to obtain consumption estimates expressed as mg/day/1000 inhabitants. The data show the presence and quantification in population-normalized mass load (PNML) of drug metabolites in each sampling event. Users can examine the data as a normalized consumption values for population-level comparisons. These data can be interpreted as measurements of metabolite loads entering the WWTP during defined 24 h periods. Researchers may use the provided normalization approach to compare with other WBE studies. The dataset can also be reused to integrate with epidemiological information, or perform temporal and cross-regional comparisons using standardized WBE metrics.
DOI: 10.17632/vgpr6b99vf.1
title: Dataset of illicit drugs consumption through wastewater during and post COVID-19 in San Pedro de la Paz, Chile.

description: This dataset was generated to apply the wastewater-based epidemiology (WBE), for the first time, in a Chilean municipality to quantify community-level illicit drug consumption using standardized sampling and analytical procedures. The study selected four metabolites (benzoylegnonine, THCCOOH, Anfetamine and MDMA) of illicit drugs present in wastewater to measure in LC–MS/MS and converted, through back-calculation, into normalized estimates of consumption that are comparable across time when similar protocols are used. To evaluate this, 24 h composite samples were collected at the San Pedro de la Paz Wastewater Treatment Plant (WWTP) in two distinct periods: (i) during COVID-19: twelve days in August 2021 and; (ii) Pos-COVID-19: weekly sampling from September 2022 to October 2023.
All samples were collected, preserved with sodium metabisulfite, stored at 4 °C, and processed within three days to ensure consistency across both sampling periods. The data were then normalized using wastewater flow rates and the estimated population served by the WWTP to obtain consumption estimates expressed as mg/day/1000 inhabitants. The data show the presence and quantification in population-normalized mass load (PNML) of drug metabolites in each sampling event. Users can examine the data as a normalized consumption values for population-level comparisons. These data can be interpreted as measurements of metabolite loads entering the WWTP during defined 24 h periods. Researchers may use the provided normalization approach to compare with other WBE studies. The dataset can also be reused to integrate with epidemiological information, or perform temporal and cross-regional comparisons using standardized WBE metrics.
DOI: 10.17632/jyrcz5y887
title: The impact of historical land-use change on the simulated global yield of wheat, maize, and rice

description: Considering land-use change in dynamic global vegetation models has improved the simulation of vegetation state and carbon cycling since the legacies of past land-use changes persist in soil carbon and nitrogen concentrations for several years. However, the influence of land-use and management history on crop yields is not well explored in large-scale modelling. This study assessed the effect of land-use changes on global crop yield estimates with LPJ-GUESS for wheat, maize and rice and their interaction with climatic and management drivers. A total of 56 global simulations were performed by combining three different factors: (1) Four global land-use setups before the crop simulation: cropland, natural vegetation, conversion of natural vegetation to pasture before conversion to cropland, and a historical land-use change reconstruction; (2) The individual contributions of five drivers, atmospheric CO2, precipitation, radiation, temperature, and fertilisation; (3) Two different climate forcing datasets, CRU-NCEP and AgMERRA to assess the relative size of uncertainty from two different climate models. Yields simulated based on both climate-forcing datasets showed a similar relative response in trends and interannual variability. Simulations with previous land-use of natural vegetation and pastures caused higher soil nitrogen and carbon pools, increasing yields at the beginning of the simulations. Similarly, fertilisation was the main driver impacting the trend in yields and interannual variability. Simulations in which land was assumed to have always been cropland had similar trends to those using the land-use change database. All the land-use setups tended to converge over time to give similar yields, but convergence could take several decades. The main results highlight the critical role of historical land-use in simulating crop yield at subregional to local scales, particularly in locations with low fertilisation. At global to regional scales, the assumption of previous cropland cover simplifies simulations without affecting accuracy significantly.
DOI: 10.17632/jyrcz5y887.1
title: The impact of historical land-use change on the simulated global yield of wheat, maize, and rice

description: Considering land-use change in dynamic global vegetation models has improved the simulation of vegetation state and carbon cycling since the legacies of past land-use changes persist in soil carbon and nitrogen concentrations for several years. However, the influence of land-use and management history on crop yields is not well explored in large-scale modelling. This study assessed the effect of land-use changes on global crop yield estimates with LPJ-GUESS for wheat, maize and rice and their interaction with climatic and management drivers. A total of 56 global simulations were performed by combining three different factors: (1) Four global land-use setups before the crop simulation: cropland, natural vegetation, conversion of natural vegetation to pasture before conversion to cropland, and a historical land-use change reconstruction; (2) The individual contributions of five drivers, atmospheric CO2, precipitation, radiation, temperature, and fertilisation; (3) Two different climate forcing datasets, CRU-NCEP and AgMERRA to assess the relative size of uncertainty from two different climate models. Yields simulated based on both climate-forcing datasets showed a similar relative response in trends and interannual variability. Simulations with previous land-use of natural vegetation and pastures caused higher soil nitrogen and carbon pools, increasing yields at the beginning of the simulations. Similarly, fertilisation was the main driver impacting the trend in yields and interannual variability. Simulations in which land was assumed to have always been cropland had similar trends to those using the land-use change database. All the land-use setups tended to converge over time to give similar yields, but convergence could take several decades. The main results highlight the critical role of historical land-use in simulating crop yield at subregional to local scales, particularly in locations with low fertilisation. At global to regional scales, the assumption of previous cropland cover simplifies simulations without affecting accuracy significantly.
DOI: 10.17632/z6459vntbr
title: Microplastics_SEM

description: Here are the datasets for the paper (Automatic quantification and classification of microplastics in scanning electron micrographs via deep learning) published the Science of the Total Environment. The complete training dataset of semantic segmentation and shape classification is in dataset1.zip. The dataset of instance segmentation is present in multiple forms in dataset2.zip. The experiment setting for each micrograph was recorded together with the original SEM micrographs and all ground-truth labels in the file dataset3.zip. Main results were saved in result.zip.

Paper link: https://doi.org/10.1016/j.scitotenv.2022.153903
Code link: https://github.com/benjamin3344/Microplastics_Unet

Updates on 2026-02-22: Pre-trained weights for models of different sizes (4*5 fold) are included in result_weights.zip.

Any further cooperation can be addressed to Professor Jane Howe.
DOI: 10.17632/z6459vntbr.3
title: Microplastics_SEM

description: Here are the datasets for the paper (Automatic quantification and classification of microplastics in scanning electron micrographs via deep learning) published the Science of the Total Environment. The complete training dataset of semantic segmentation and shape classification is in dataset1.zip. The dataset of instance segmentation is present in multiple forms in dataset2.zip. The experiment setting for each micrograph was recorded together with the original SEM micrographs and all ground-truth labels in the file dataset3.zip. Main results were saved in result.zip.

Paper link: https://doi.org/10.1016/j.scitotenv.2022.153903
Code link: https://github.com/benjamin3344/Microplastics_Unet

Updates on 2026-02-22: Pre-trained weights for models of different sizes (4*5 fold) are included in result_weights.zip.

Any further cooperation can be addressed to Professor Jane Howe.
DOI: 10.17632/9jxvtgh325
title: Tomato Leaf and Fruit Disease Image Dataset

description: 1. This dataset has seven different tomato classes: Healthy Leaf, Healthy Fruit, Early Blight Leaf, Late Blight Leaf, Leaf Curl Leaf, Bushy Stunt Leaf, and Target Spot Fruit. It is intended for developing computer vision-based algorithms.


2. The dataset contains 3,500 images of tomatoes, all captured in actual fields. To increase the number of data points, data augmentation techniques such as shifting, flipping, zooming, shearing, brightness enhancement, and rotation were applied, resulting in a total of 24,500 augmented images.
DOI: 10.17632/9jxvtgh325.1
title: Tomato Leaf and Fruit Disease Image Dataset

description: 1. This dataset has seven different tomato classes: Healthy Leaf, Healthy Fruit, Early Blight Leaf, Late Blight Leaf, Leaf Curl Leaf, Bushy Stunt Leaf, and Target Spot Fruit. It is intended for developing computer vision-based algorithms.


2. The dataset contains 3,500 images of tomatoes, all captured in actual fields. To increase the number of data points, data augmentation techniques such as shifting, flipping, zooming, shearing, brightness enhancement, and rotation were applied, resulting in a total of 24,500 augmented images.
DOI: 10.17632/jw7hp6r5gj
title: Rice Disease Image Dataset

description: 1. This dataset contains eight different rice classes—Healthy Leaf, Healthy Rice, Healthy Stem, Potassium Fertilizer Deficiency, Rice Ear Borer, Rice Leafroller, Rice Stem Rot Disease, and Bacterial Blight—created for developing machine vision–based algorithms. 

2. A total of 500 rice images were collected from actual fields. To increase the number of data samples, data augmentation techniques such as shifting, flipping, zooming, shearing, brightness enhancement, and rotation were applied, generating a total of 24,000 augmented images from the original images.
DOI: 10.17632/jw7hp6r5gj.1
title: Rice Disease Image Dataset

description: 1. This dataset contains eight different rice classes—Healthy Leaf, Healthy Rice, Healthy Stem, Potassium Fertilizer Deficiency, Rice Ear Borer, Rice Leafroller, Rice Stem Rot Disease, and Bacterial Blight—created for developing machine vision–based algorithms. 

2. A total of 500 rice images were collected from actual fields. To increase the number of data samples, data augmentation techniques such as shifting, flipping, zooming, shearing, brightness enhancement, and rotation were applied, generating a total of 24,000 augmented images from the original images.
DOI: 10.17632/kk2fh77nx8
title: Illustrative Online Trainee Discussions About APC Costs

description: Supplementary Table
DOI: 10.15468/dl.2vdyyx
title: Occurrence Download

description: A dataset containing 315 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eviota epiphanes"
 ]
}

 The dataset includes 315 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004440-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/kk2fh77nx8.1
title: Illustrative Online Trainee Discussions About APC Costs

description: Supplementary Table
DOI: 10.17632/wsbd9tgbd2
title: Novel Role of Human RBC on Vascular Tonus: RBCs Contribute to Adrenergic Vasoconstriction via Generation of Thromboxane A2

description: This data set includes the detailed methodology and results of the following article:
Novel role of human RBC in vascular tonus: RBCs contribute to adrenergic vasoconstriction via generation of thromboxane A₂
Ahmet Yildirim, Fatma Zehra Hapil, Nihal Ozturk, Ulku Arslan Yildiz, Melike Cengiz, Nazmi Yaras, Filiz Basrali, Ibrahim Basarici, Ozan Salim, James Dixon Reynolds, Pinar Ulker
DOI: 10.1016/j.brci.2026.100057
DOI: 10.17632/wsbd9tgbd2.1
title: Novel Role of Human RBC on Vascular Tonus: RBCs Contribute to Adrenergic Vasoconstriction via Generation of Thromboxane A2

description: This data set includes the detailed methodology and results of the following article:
Novel role of human RBC in vascular tonus: RBCs contribute to adrenergic vasoconstriction via generation of thromboxane A₂
Ahmet Yildirim, Fatma Zehra Hapil, Nihal Ozturk, Ulku Arslan Yildiz, Melike Cengiz, Nazmi Yaras, Filiz Basrali, Ibrahim Basarici, Ozan Salim, James Dixon Reynolds, Pinar Ulker
DOI: 10.1016/j.brci.2026.100057
DOI: 10.17632/7nyxrvmjv3
title: First Lidar Observations of Ionosphere–Thermosphere–Mesosphere (ITM) Na Transition Layer (~120–95 km): Regular Occurrence Over Boulder (40.13°N, 105.24°W) and Possible Formation Mechanisms

description: The dataset published here supports the article entitled "First Lidar Observations of Ionosphere–Thermosphere–Mesosphere (ITM) Na Transition Layer (~120–95 km): Regular Occurrence Over Boulder (40.13°N, 105.24°W) and Possible Formation Mechanisms", submitted to Geophysical Research Letters (GRL) in 2026. The data are provided in MatLab format along with MatLab plotting code.
DOI: 10.17632/7nyxrvmjv3.1
title: First Lidar Observations of Ionosphere–Thermosphere–Mesosphere (ITM) Na Transition Layer (~120–95 km): Regular Occurrence Over Boulder (40.13°N, 105.24°W) and Possible Formation Mechanisms

description: The dataset published here supports the article entitled "First Lidar Observations of Ionosphere–Thermosphere–Mesosphere (ITM) Na Transition Layer (~120–95 km): Regular Occurrence Over Boulder (40.13°N, 105.24°W) and Possible Formation Mechanisms", submitted to Geophysical Research Letters (GRL) in 2026. The data are provided in MatLab format along with MatLab plotting code.
DOI: 10.17632/vf9343v63j
title: Continuous release of saline fluids from a permeable subducting slab

description: The authors provide the datasets on Mendeley data, including all tables, cumulative frequency curves, frequency distribution histograms, and theoretical Flat-Flat (FF) angle to support our research.
DOI: 10.17632/vf9343v63j.1
title: Continuous release of saline fluids from a permeable subducting slab

description: The authors provide the datasets on Mendeley data, including all tables, cumulative frequency curves, frequency distribution histograms, and theoretical Flat-Flat (FF) angle to support our research.
DOI: 10.17632/rrd6ngpz8r
title: Dataset of 132 Citizenship Behavior Incidents in the Tehran Subway

description: This dataset contains 132 refined instances of Citizenship Behavior (CB) observed and recorded by frequent subway users during routine travel in the Tehran Subway system. The dataset was developed to examine how everyday commuter interactions within shared transit environments may unintentionally contribute to experiences of inclusion or exclusion among riders.
The underlying premise of the study is that, beyond formal accessibility measures and infrastructural design, social dynamics within transit interiors are shaped by routine micro-behaviors enacted by passengers. These behaviors—such as offering space, assisting with navigation, repositioning within crowded environments, or selectively engaging with others—may influence how access to comfort, safety, and recognition is distributed among riders. While many of these actions are prosocial in intent, their enactment may be conditional, situationally constrained, or directed toward specific individuals based on visible markers of vulnerability or social appropriateness.
The CB incidents included in this dataset were collected through participant-kept travel diaries over a two-week period and subsequently translated from Persian into English. Each entry documents an observed or enacted instance of CB within the subway car interior. Through inductive thematic analysis, these incidents were coded and organized into focused behavioral categories and four higher-order themes that capture recurring patterns of selective assistance, cultural normativity, spatial organization, and institutionally reinforced behavioral expectations.
The dataset may be used to explore how informal interactional practices shape access to shared transit space, how prosocial behaviors are distributed across rider groups, and how routine social coordination contributes to the organization of public environments. It can support further qualitative analysis of commuter behavior, inform comparative studies across transit systems, or serve as a reference for design and policy-oriented research on inclusive mobility and transport justice.
DOI: 10.17632/rrd6ngpz8r.1
title: Dataset of 132 Citizenship Behavior Incidents in the Tehran Subway

description: This dataset contains 132 refined instances of Citizenship Behavior (CB) observed and recorded by frequent subway users during routine travel in the Tehran Subway system. The dataset was developed to examine how everyday commuter interactions within shared transit environments may unintentionally contribute to experiences of inclusion or exclusion among riders.
The underlying premise of the study is that, beyond formal accessibility measures and infrastructural design, social dynamics within transit interiors are shaped by routine micro-behaviors enacted by passengers. These behaviors—such as offering space, assisting with navigation, repositioning within crowded environments, or selectively engaging with others—may influence how access to comfort, safety, and recognition is distributed among riders. While many of these actions are prosocial in intent, their enactment may be conditional, situationally constrained, or directed toward specific individuals based on visible markers of vulnerability or social appropriateness.
The CB incidents included in this dataset were collected through participant-kept travel diaries over a two-week period and subsequently translated from Persian into English. Each entry documents an observed or enacted instance of CB within the subway car interior. Through inductive thematic analysis, these incidents were coded and organized into focused behavioral categories and four higher-order themes that capture recurring patterns of selective assistance, cultural normativity, spatial organization, and institutionally reinforced behavioral expectations.
The dataset may be used to explore how informal interactional practices shape access to shared transit space, how prosocial behaviors are distributed across rider groups, and how routine social coordination contributes to the organization of public environments. It can support further qualitative analysis of commuter behavior, inform comparative studies across transit systems, or serve as a reference for design and policy-oriented research on inclusive mobility and transport justice.
DOI: 10.17632/hgyrn38grp
title: Replication Package for “Face-to-Face Social Interactions and Local Informational Advantage”

description: This replication package reproduces the tables and figures reported in the paper “Face-to-Face Social Interactions and Local Informational Advantage” by Robin Lee. It includes all code necessary to clean the data and replicate the empirical analyses, along with pseudo datasets corresponding to the derived analysis files. The README file provides further details on raw data sources and replication procedures.
DOI: 10.17632/hgyrn38grp.1
title: Replication Package for “Face-to-Face Social Interactions and Local Informational Advantage”

description: This replication package reproduces the tables and figures reported in the paper “Face-to-Face Social Interactions and Local Informational Advantage” by Robin Lee. It includes all code necessary to clean the data and replicate the empirical analyses, along with pseudo datasets corresponding to the derived analysis files. The README file provides further details on raw data sources and replication procedures.
DOI: 10.17632/vfk99z43b6
title: Totora rolls and computer aided design integration data

description: These data files correspond to the research titled: Synergy between participatory design and computational design to promote the uses diversification of the traditional totora fiber in indigenous communities. 
The research studies hoy traditional materials, such as the totora (Schoenoplectus californicus) plant that has been used by several indigenous communities to make a wide range of objects from handicrafts to boats and floating islands, can be studied at a scientific level to understand its mechanical properties and the potential of computer-aided design and automation to develop a diversification of the uses for this plant. The main research question is if computer-based design can encourage an evolution of traditional techniques and the creation of new production possibilities using traditional materials and collaborative processes with indigenous communities. 
The data shows the mechanical tests results of compressive and flexural strength of totora rolls tied with plastic straps or a spiral cotton thread based on the principles for the totora boat´s construction techniques. 
Another part of the data shows the parameters used for the grasshopper software to find optimized shapes considering the mechanical properties loaded to the program.