cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/fspk9kw98v.1
title: Customizable wave tailoring materials enabled by nonlinear bilevel inverse design 3

description: SOLIDWORKS and level set files for optimized spring design in support of manuscript.
DOI: 10.17632/xy2rdvvmwc.1
title: Retrospective Cohort Study on Outcomes of Children with Severe Dengue Managed via Telemedicine Consultation

description: Dataset uploaded as part of the submission for research article entitle "Retrospective Cohort Study on Outcomes of Children with Severe Dengue Managed via Telemedicine Consultation"
DOI: 10.17632/yjz7v8rknx.1
title: Species-level comparative metagenomic analysis of gut microbiome bacterial abundance in psoriasis, hidradenitis suppurativa, and pemphigus foliaceous patients using shotgun next-generation sequencing

description: Complete data from the metagenomic analysis of 55 patients with psoriasis, hidradenitis suppurativa, and pemphigus foliaceus. This dataset includes raw analysis data, a full list of identified microorganisms, and various statistical analysis modules. Interactive graphs are also available.
DOI: 10.17632/jfk7kr63ts.1
title: Data for: Climate warming and strengthened hydrologic cycle amplify CO2 release from rock weathering

description: Research data of a manuscript entitled ‘Climate warming and strengthened hydrologic cycle amplify CO2 release from rock weathering’.
DOI: 10.17632/tnwd64wfzk.1
title: Polygraph-Based Truth Detection System Dataset

description: Three sensors were used in this study Body Temperature Sensor, Galvanic Skin Response (GSR), and Heart Rate/Beats Per Minute (BPM Sensor). These sensors were mounted on two of the subject’s fingers.
The sensors are connected to an Arduino UNO R3 board through SDA (Serial DAta line) and SCL (Serial CLock line) connections. The Arduino controller is connected to a PC through a USB connection and through a designated serial communication port, the data is sent and synced at a Python script which stores the data in an Excel file. The subject’s ID is the input to the script to ID the file and like it with the subject’s details which is written by the operator before and during the presentation process, see Figure 4 for more details about the process flow. 
The study was conducted on 49 subjects, each had his name, age, height, and weight data inserted in an Excel datasheet by the operator. The operator then assigns an ID to the subject and starts the acquaintance test, followed by the main test to observe the answers and store T or F under one of each ten question columns. Besides this collective file (Subjects Data), there a 49 files for each subject containing an average of 130 lines of data signals recorded during the process by the previously mentioned sensors (each line represents a second with a reading from each sensor and a timestamp). The study was conducted on 34 male and 15 female subjects. 

For more data about the system that was used to collect this dataset and how the data were processed, please visit and cite our work: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5031332
For more information please contact: omar.o.shalash@aast.edu or prof.mail.metwalli@gmail.com
DOI: 10.17632/ntfw7d67nt
title: Evolution of fracture and creep properties of kerogen with maturation advancement: Implications for shale hydrocarbon development

description: Supplementary Information for “Evolution of fracture and creep properties of kerogen with maturation advancement: Implications for shale hydrocarbon development”
DOI: 10.17632/ntfw7d67nt.1
title: Evolution of fracture and creep properties of kerogen with maturation advancement: Implications for shale hydrocarbon development

description: Supplementary Information for “Evolution of fracture and creep properties of kerogen with maturation advancement: Implications for shale hydrocarbon development”
DOI: 10.17632/khvpypw8bs.1
title: Downy Mildew Detection in Luffa Leaves Dataset

description: In this dataset, a total of 3483 Luffa leaf samples were collected across various field plots in Ashulia, Dhaka, Bangladesh, during the 2024 growing season. The leaves were carefully documented and categorized into healthy and diseased groups to create a comprehensive dataset for accurate classification of Downy Mildew Disease caused by Phytophthora spp.. The distribution of leaf samples is as follows:
• Healthy Leaves: 414 samples
• Diseased Leaves: 3069 samples
• Augmented Healthy Leaves: 2483 samples
• Augmented Diseased Leaves: 17593 samples

Purpose:
The Luffa Downy Mildew Disease Detection Dataset serves a critical role in machine learning applications, particularly in image classification for automatic disease detection in Luffa plants. It can be used to train models like convolutional neural networks (CNNs) to identify and classify healthy and diseased leaves based on visual features such as leaf shape, color, and texture. The dataset includes both original and augmented images, enhancing model robustness by providing diverse samples that improve generalization in various real-world scenarios. This dataset is useful in areas like agricultural automation, early disease detection, and disease management in the Luffa farming industry. Additionally, it can be integrated with environmental data (e.g., temperature, humidity, rainfall) to improve predictive models that forecast disease risks under different climatic conditions. Ultimately, this dataset helps advance machine learning models for automated disease monitoring and management in the agricultural sector.
DOI: 10.5281/zenodo.11086225
title: Background material for the study titled: Governance for inclusion and societal values – a literature review of platform governance mechanisms in the public sector

description: Extra materials for the literature study reported in the submitted paper.
DOI: 10.5281/zenodo.14172909
title: Background material for the study titled: Platform Governance in the Public Sector: Governance Strategies and Mechanisms for Public Value Creation

description: Extra materials for the study in the submitted paper.
DOI: 10.17632/khvpypw8bs.2
title: Downy Mildew Detection in Luffa Leaves Dataset

description: In this dataset, a total of 3483 Luffa leaf samples were collected across various field plots in Ashulia, Dhaka, Bangladesh, during the 2024 growing season. The leaves were carefully documented and categorized into healthy and diseased groups to create a comprehensive dataset for accurate classification of Downy Mildew Disease caused by Phytophthora spp.. The distribution of leaf samples is as follows:
• Healthy Leaves: 414 samples
• Diseased Leaves: 3069 samples
• Augmented Healthy Leaves: 2483 samples
• Augmented Diseased Leaves: 17593 samples

Purpose:
The Luffa Downy Mildew Disease Detection Dataset serves a critical role in machine learning applications, particularly in image classification for automatic disease detection in Luffa plants. It can be used to train models like convolutional neural networks (CNNs) to identify and classify healthy and diseased leaves based on visual features such as leaf shape, color, and texture. The dataset includes both original and augmented images, enhancing model robustness by providing diverse samples that improve generalization in various real-world scenarios. This dataset is useful in areas like agricultural automation, early disease detection, and disease management in the Luffa farming industry. Additionally, it can be integrated with environmental data (e.g., temperature, humidity, rainfall) to improve predictive models that forecast disease risks under different climatic conditions. Ultimately, this dataset helps advance machine learning models for automated disease monitoring and management in the agricultural sector.
DOI: 10.17632/mbmf4rvygw.1
title: Data on LinkedIn Usage among students in Indonesia

description: Utilization of LinkedIn as a social networking site among students in Indonesia for education.
DOI: 10.17632/gz37zhdghp
title: paper dataset

description: The supplementary data for the article "Identification of DoSPL7s and DoSPL9 in Dendrobium officinale and analysis of the miR156a-2-SPL negative regulation module under diurnal temperature differences" include the following:
1.RT-qPCR data:Quantitative real-time PCR results.
2.LUC-REN data:Dual luciferase assay measurements.
3.Polysaccharide Content data:Polysaccharide content data under different treatments.
4.Pearson Correlation Matrix data:The specific values of the Pearson correlation analysis.
DOI: 10.17632/gz37zhdghp.1
title: paper dataset

description: The supplementary data for the article "Identification of DoSPL7s and DoSPL9 in Dendrobium officinale and analysis of the miR156a-2-SPL negative regulation module under diurnal temperature differences" include the following:
1.RT-qPCR data:Quantitative real-time PCR results.
2.LUC-REN data:Dual luciferase assay measurements.
3.Polysaccharide Content data:Polysaccharide content data under different treatments.
4.Pearson Correlation Matrix data:The specific values of the Pearson correlation analysis.
DOI: 10.17632/32mmbxrm8y
title: Sea Level Fluctuations and Silicate Weathering Dynamics Over 450 kyr: Insights from Lithium Isotopes in South China Sea Sediments

description: Table 1. δ7Li values, Li and REE concentrations*, Kaolinite/(Chlorite+Illite) ratios**,
TOC concentrations***, Fe/Al, and Mg/Al ratios of silicate fractions of core MD 05-2901
Table 2. 87Sr/86Sr and εNd compositions of silicate fractions of core MD 05-2901
DOI: 10.17632/32mmbxrm8y.1
title: Sea Level Fluctuations and Silicate Weathering Dynamics Over 450 kyr: Insights from Lithium Isotopes in South China Sea Sediments

description: Table 1. δ7Li values, Li and REE concentrations*, Kaolinite/(Chlorite+Illite) ratios**,
TOC concentrations***, Fe/Al, and Mg/Al ratios of silicate fractions of core MD 05-2901
Table 2. 87Sr/86Sr and εNd compositions of silicate fractions of core MD 05-2901
DOI: 10.17632/r77vg42g6m
title: Upadacitinib for Refractory Alopecia Areata Unresponsive to Prior Systemic Therapies: A Retrospective Study

description: Supplementary Materials of Upadacitinib for Refractory Alopecia Areata Unresponsive to Prior Systemic Therapies: A Retrospective Study
DOI: 10.17632/r77vg42g6m.1
title: Upadacitinib for Refractory Alopecia Areata Unresponsive to Prior Systemic Therapies: A Retrospective Study

description: Supplementary Materials of Upadacitinib for Refractory Alopecia Areata Unresponsive to Prior Systemic Therapies: A Retrospective Study
DOI: 10.17632/jkvyj5fmzw.1
title: Scrub Typhus India Dataset

description: Background
Scrub typhus, once known as Tsutsugamushi fever and attributed to Rickettsia, has transformed into a growing public health concern. Despite its increasing incidence in India, comprehensive spatiotemporal analyses of scrub typhus have been lacking. 
Methods 
This study examines the prevalence of scrub typhus cases reported from 2003 to 2023, utilizing available literature to provide a breakdown of cases by year and state in India, aiming to elucidate the disease's spatiotemporal dynamics. The etiologic association of Orientia tsutsugamushi and scrub typhus is based on geographical, immunological and molecular genetic findings. 
Findings
This analysis identified 47,650 cumulative cases of scrub typhus in India over the past two decades. The case fatality rate was ~2.4%. Variations in transmission dynamics and the Leptotrombidium (tick responsible for causing scrub typhus), the most common vector’s competence, may influence the disease's distribution. Nonetheless, there has been a notable increase in infections since 2010, peaking in 2019 and 2022. Curtailing and containing such an upsurge can be daunting and requires an interdisciplinary public health approach. Further, there is heterogeneity in studies on general, gastrointestinal, pulmonary, and inflammatory symptoms compared to studies on cardiac, hepatic, neurological and other symptoms. Weil-Felix test was the most common diagnostic technique used and doxycycline was the treatment for scrub typhus cases. 
Interpretations
This meta-analysis can help policymakers and researchers in India develop scrub typhus management and control policies.
DOI: 10.17632/4fmjjfpmyy.1
title: Datased for a publication: "Comparison of Powder-Bed Fusion, Directed Energy Deposition, and Hybrid Additive Manufacturing of Ti6Al4V Components: Microstructure, Corrosion and Mechanical Properties"

description: These data are published as a part of the paper: Comparison of Powder-Bed Fusion, Directed Energy Deposition, and Hybrid Additive Manufacturing of Ti6Al4V Components: Microstructure, Corrosion and Mechanical Properties. The structure and organization of the data are outlined in the readme file.
DOI: 10.17632/4fmjjfpmyy.2
title: Dataset for a publication: "Comparison of Powder-Bed Fusion, Directed Energy Deposition, and Hybrid Additive Manufacturing of Ti6Al4V Components: Microstructure, Corrosion and Mechanical Properties"

description: These data are published as a part of the paper: Comparison of Powder-Bed Fusion, Directed Energy Deposition, and Hybrid Additive Manufacturing of Ti6Al4V Components: Microstructure, Corrosion and Mechanical Properties. The structure and organization of the data are outlined in the readme file.
DOI: 10.17632/kd8hs7ch6t.4
title: Epipremnum aureum (Money Plant Leaf) datasets

description: Money plants are widely recognized for their significant spiritual and air-purifying benefits. Daily interaction with these vibrant indoor plants has been proven to effectively reduce anxiety and stress. The robust dataset of 4304 money plant images, captured under real-world conditions using smartphones.The dataset contains healthy, unhealthy leaves, making it useful for machine learning and plant health analysis. The dataset is collected from the educational hub Dr. D. Y. Patil Institute of Technology, Pune campus, Maharashtra, India. The dataset contain six folder: I) Healthy leaf II) Unhealthy leaf III) Yellow leaf IV) Real images V) Combined healthy_Unhealthy images VI) College premises photo.
DOI: 10.7294/27153213
title: Data Associated with Thermal Impacts of Atmospheric Gravity Waves in the Martian Thermosphere

description: Data included provides information on the observed spectra of atmospheric waves in difference chemical species in the Martian upper atmosphere, as well as the estimated thermal impacts of these waves. Locations, times, dates for the data are also provided.
DOI: 10.7294/27153213.v1
title: Data Associated with Thermal Impacts of Atmospheric Gravity Waves in the Martian Thermosphere

description: Data included provides information on the observed spectra of atmospheric waves in difference chemical species in the Martian upper atmosphere, as well as the estimated thermal impacts of these waves. Locations, times, dates for the data are also provided.
DOI: 10.7294/27153213.v2
title: Data Associated with Thermal Impacts of Atmospheric Gravity Waves in the Martian Thermosphere

description: Data included provides information on the observed spectra of atmospheric waves in difference chemical species in the Martian upper atmosphere, as well as the estimated thermal impacts of these waves. Locations, times, dates for the data are also provided.
DOI: 10.5281/zenodo.15040178
title: Benchmarking datasets for scMINER clustering analysis

description: Here are the 13 datasets used in the clustering benchmark of MICA (https://github.com/jyyulab/MICA), the cell clustering engine of scMINER(https://github.com/jyyulab/scMINER). The first 10 datasets (Yan, Goolam, Buettner, Pollen, Chung, Usoskin, Kolod, Klein, Zeisel and PBMC14K) contains the ground-truth cell types, and were used for clusteriing accuracy benchmarking. While the other three (HMC76K, COVID97K and COVID650K) do not contain ground-truth cell types, and were used for scalability bechmarking only.
DOI: 10.5281/zenodo.15040179
title: Benchmarking datasets for scMINER clustering analysis

description: Here are the 13 datasets used in the clustering benchmark of MICA (https://github.com/jyyulab/MICA), the cell clustering engine of scMINER(https://github.com/jyyulab/scMINER). The first 10 datasets (Yan, Goolam, Buettner, Pollen, Chung, Usoskin, Kolod, Klein, Zeisel and PBMC14K) contains the ground-truth cell types, and were used for clusteriing accuracy benchmarking. While the other three (HMC76K, COVID97K and COVID650K) do not contain ground-truth cell types, and were used for scalability bechmarking only.
DOI: 10.17632/89bddf2fnd.2
title: Servay data on fishermen perception of marine protected areas in West Coast of Malaysia

description: The dataset presents findings on fishermen's perceptions of marine protected areas (MPAs), along with demographic data and profiles of the fishing community. Employing a stratified random sampling technique, data were collected from 800 fishermen along the West Coast of Peninsular Malaysia (Perlis, Kedah, Pulau Pinang, Perak, Selangor, Negeri Sembilan, Melaka and West Johor). Data were obtained through face-to-face interviews using a self-structured questionnaire. Descriptive analysis utilizing frequencies and percentages was conducted on the data. The findings, illustrated in tables and figures, offered valuable insights into MPAs and the socio-economic status of fishermen, aiding government officials, policymakers, and researchers in enhancing the enforcement of marine protected areas to meet global targets. By 2030, Malaysia aimed to expand MPAs to 10 percent in line with international commitments at the United Nations with the current area being approximately 5.35 percent of the waters in Peninsular Malaysia and Borneo.
DOI: 10.17632/89bddf2fnd.1
title: Servay data on fishermen perception of marine protected areas in West Coast of Malaysia

description: Marine Protected Areas (MPA) in Malaysia Water’s covered around 5.35 percent in both Peninsular and Borneo mainly in form of marine park and no fishing zone. MPAs are important to the conservation of marine resources by providing sustainable habitats. By 2030, a national target to expand to 10 percent of MPAs was set up in line with the country’s commitment through international obligations at the United Nations level. This article aims to present data on fishermen’s perception on MPAs, as well as demography and fishermen profile. The stratified random sampling technique was used to choose fishermen from eight states of West Coast of Peninsular Malaysia. The dataset was obtained by a self-structured questionnaire involved 800 fishermen along the coast via face-to-face interview. Data was analyzed using descriptive analysis through frequencies and percentages. The findings presented in tables and figures provides extensive information and feedback on the MPA as well as the socio-economic status of fishermen. The data will assist the the government, policymakers and researchers to strengthen the enforcement of marine protected areas to achieve global targets.
DOI: 10.17632/89bddf2fnd.3
title: Servay data on fishermen perception of marine protected areas in West Coast of Malaysia

description: The dataset presents findings on fishermen's perceptions of marine protected areas (MPAs), along with demographic data and profiles of the fishing community. Employing a stratified random sampling technique, data were collected from 800 fishermen along the West Coast of Peninsular Malaysia (Perlis, Kedah, Pulau Pinang, Perak, Selangor, Negeri Sembilan, Melaka and West Johor). Data were obtained through face-to-face interviews using a self-structured questionnaire. Descriptive analysis utilizing frequencies and percentages was conducted on the data. The findings, illustrated in tables and figures, offered valuable insights into MPAs and the socio-economic status of fishermen, aiding government officials, policymakers, and researchers in enhancing the enforcement of marine protected areas to meet global targets. By 2030, Malaysia aimed to expand MPAs to 10 percent in line with international commitments at the United Nations with the current area being approximately 5.35 percent of the waters in Peninsular Malaysia and Borneo.
DOI: 10.15468/dl.dp2cdm
title: Occurrence Download

description: A dataset containing 12169 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lactarius helvus (Fr.) Fr."
 ]
}

 The dataset includes 12169 records from 219 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013127-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/6hp82tsb8g.1
title: Iron Ore Image Data

description: The dataset consists of Reflected Light Microscopic (RLM) Images of Iron Ores of four different grades. The zipped folder contains four sub folders, each representing and containing the raw images of a particular grade of iron ore. The grades of ores and the nomenclature used for naming the folders are - Blue Dust Ore (BDO), Hard Laminated Ore (HLO), Lateritic Ore (LO) and Soft Laminated Ore (SLO). The images are in TIF format of dimension 2048X1536. The dataset has been created for automating the task of characterization of iron ores using deep learning algorithms. The dataset can also be used for mineral composition analysis.
DOI: 10.17632/6hp82tsb8g.2
title: Iron Ore Image Data

description: The dataset consists of Reflected Light Microscopic (RLM) Images of Iron Ores of four different grades in two different magnification of the microscope objective. The zipped folder IronOreRLM.zip contains two sub folders (Objective-10x, Objective-20x), each representing the magnification of the microscope objective used. These sub folders further contains sub folders named as per the grades of the ore images it contains. Each subfolder contains the raw images of a particular grade of iron ore. The grades of ores and the nomenclature used for naming the folders are - Blue Dust Ore (BDO), Hard Laminated Ore (HLO), Lateritic Ore (LO) and Soft Laminated Ore (SLO). The images are in TIF format of dimension 2048X1536. The dataset has been created for automating the task of characterization of iron ores using deep learning algorithms. The dataset can also be used for mineral composition analysis. A separate folder has also been uploaded named, Sample Images.zip, which a smaller size dataset, and contains few samples images from each category that provides a quick view of how the overall dataset is.
DOI: 10.17632/xysbdg9yjm.1
title: Supplementary tables

description: Identification and exploration of the potential antiaging role of the novel antioxidant peptide DGGY derived from yak milk proteins Supplementary tables
DOI: 10.17632/bdkhkmy4xm.1
title: Gagnon et al. Muscle temperature on VO2_Qm relationship 2025

description: Data file containing Muscle blood flow (Qm), muscle oxygen consumption (mVO2), muscle tissue saturation (%TSI), total peripheral resistance (TPR), arterio-venous difference (A-VO2diff), mean arterial pressure (MAP), heart rate (HR), stroke volume (SV), cardiac output (CO), pulmonary VO2 (VO2pul), minute ventilation (VE), respiratory quotient (RQ), muscle temperature (Tm) and skin temperature (Tskin).
DOI: 10.15468/dl.vwqu3s
title: Occurrence Download

description: A dataset containing 594 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Marmota marmota marmota"
 ]
}

 The dataset includes 594 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013129-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/mxxw7x6wt6.1
title: How Do Immigrants Promote Exports?

description: This Mendeley repository contains the replication material for "How Do Immigrants Promote Exports"
DOI: 10.17632/mxxw7x6wt6.2
title: How Do Immigrants Promote Exports?

description: This Mendeley repository contains the replication material for Orefice G., Rapoport H. and G. Santoni (2025) "How Do Immigrants Promote Exports", Journal of Development Economics, 2025, vol.174, 103443