cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.25499230.v1
title: Ottelai_alismoides.proteins

description: Genome assembly of Ottelia alismoides, a multiple-carbon utilization aquatic plant
DOI: 10.17632/58w92f77g4
title: Organic substitution on phosphorus mineralization

description: Organic substitution on phosphorus mineralization in acidic soils
DOI: 10.17632/h56kbg2h52
title: Rail crack microscopy sections

description: High resolution microscope images of the crack network in an R260 rail, used to validate a novel crack detection method. Further details are available in Meyer, K. A., D. Gren, J. Ahlström, A. Ekberg (2021) “In-field Railhead Crack Detection Using Digital Image Correlation.” (Currently available as preprint, https://engrxiv.org/zhg5c/)
DOI: 10.17632/pbnzrc455v
title: A Complex Hierarchy of Avoidance Behaviors in a Single-Cell Eukaryote, Dexter et al. (Day 13)

description: Videos for Dexter et al. (Day 13)
DOI: 10.6084/m9.figshare.8091968.v1
title: ReviewArticles.csv

description: This Database belongs to “A Database for Using Machine Learning and Data Mining Techniques for Coronary Artery Disease diagnosis” research paper. This database includes 15 tables. We chose to index papers related to CAD detection using machine learning and data mining approaches that are published between 1992 and 2018. These criteria result in 126 papers in which 490 authors contributed to these papers. These papers studied 68 different datasets with almost more than 360 distinct features collected in 18 countries from Asia, Europe, and America. In these papers, 140 different machine learning or data mining techniques were applied to diagnose CAD. To use csv file, open it in excel or import it in your database.
DOI: 10.17632/t8z3jy9f96
title: Mixed-methods facilitaters/barriers RCB UB - Dataset

description: Ulaanbaatar, Mongolia, is in the midst of a winter air pollution crisis driven by the combustion of solid fuels in the peri-urban Ger districts to which young children, fetuses and pregnant women are particularly vulnerable. To address this, the Mongolian government banned the sale and use of raw coal in May 2019 and has subsidized and promoted refined coal briquettes as an alternative fuel. This mixed-methods study utilized semi-structured interviews (n=30) and a questionnaire survey (n=369) to identify facilitators and barriers to compliance with the ban amongst Mongolian mothers living in Ulaanbaatar. Four main themes were identified that affected compliance: knowledge about air pollution, information sources, initial policy impacts and governance. Facilitators of participants’ ban compliance included awareness of the severity of air pollution’s health impacts, support for the policy and governmental enforcement. Concerns regarding fuel alternative safety and cost implications, as well as uncertainty about the policy (inadequate information) were found to be barriers. Incorporation of these insights in future air pollution mitigation strategies could be beneficial for strengthening their effectiveness, both in Mongolia and settings that face similar challenges throughout the world, which in turn could be a crucial step in meeting the 2030 Sustainable Development Goals agenda.
DOI: 10.17632/n8nv4pmbpk
title: Data for: An improved method for grinding mill filling measurement and the estimation of load volume and mass

description: The spreadsheet "Mill Filling Calculator.xlsx" calculates the mill and load volume and load mass for a AG/SAG or ball mill. It includes a worked example for the mill described in the paper, but can be copied and modified for a different dataset.
DOI: 10.17632/zcvhywb5vf
title: EMPSGC

description: sup figure 3
DOI: 10.17632/zxyzs8h3vh
title: Data for: CO2 Capture using Phenoxide Salts; Alternatives to Amine-based Capture Agents, and Comparative Speciation Studies as Components in Solvent Blends.

description: Supplementary information to accompany paper. 1H NMR data and tables of speciation for all capture agents compositions discussed.
DOI: 10.17632/5hbctgk948
title: Data for: epidemiology of parasitic diseases with risk factors for the development of cancer in Brazil from 2005 to 2017
DOI: 10.17632/pn67m7ttf3
title: MBD5 DATA

description: This dataset includes the original images of agarose gel electrophoresis, sanger sequencing results of the proband and normal individuals, and sequencing results from minigene validation. Open the sequence file using SnapGene software.
DOI: 10.17632/9gs7w7s947
title: A Mediterranean-like fat blend protects against the development of severe colitis in the mucin-2 deficient murine model

description: Analysis of the bacteriome (Distal colon) in Mucin 2 deficient mice exposed to diets rich in a Mediterranean fat blend, corn oil, olive oil or anhydrous milk fat.
DOI: 10.17632/4c8wt75mk2
title: Data for: Developing Educational and Vocational Aspirations through International Child Sponsorship: Evidence from Kenya, Indonesia, and Mexico

description: Pooled data set from study of impact of child sponsorship on children's aspirations.
DOI: 10.17632/4m3jdbr8w7
title: Data for: The Ravenscrag Butte flora: Paleoclimate and paleoecology of an early Paleocene (Danian) warm-temperate deciduous forest near the vanishing inland Cannonball Seaway

description: The data provided here is for a paleoclimate and paleoenvironmental reconstruction of the Ravenscrag Butte fossil flora, located in southwestern Saskatchewan, Canada. The Ravenscrag Butte flora provides a record of an early Paleocene (Danian) forest ecosystem that followed the K-Pg boundary event. Plant macrofossil collections were investigated to assess the paleoclimate and paleoecology of the forest. In this study we employed both physiognomic and nearest living relative analyses but focus on an ensemble analysis approach where best probability climate estimates are produced from all proxies using a probability density function. In addition, paleoenvironmental variables such as the deciduous or evergreen habit of the flora, and the net primary production of the forest were also estimated using physiognomic data. Provided here are the leaf physiognomic and nearest living relative data used to reconstruct paleoclimate and paleoenvironmental variables. This includes the leaf margin analysis (LMA), leaf area analysis (LAA), CLAMP scores, and the NLR taxa and climate envelopes used to estimate mean annual temperature, mean annual precipitation and other climate variables. As well as the measurement data used to estimate leaf mass per area analysis (MA), and the leaf measurement data used to calculate NPP.
DOI: 10.17632/v4gvjzc3mw
title: Modeling and Verifying a Crash-Tolerant Causal Broadcast Algorithm Using SPIN

description: This source code models specify and verifies a crash-tolerant causal broadcast algorithm. This modeling uses Spin tool version 6.4.9 with the Promela language. Additionally, this model was implemented on a system with 8 GB of memory, an AMD A6 processor, and a Windows 10 operating system.
DOI: 10.17632/xn5bz6fdm6
title: Mandibular Third Molar (m-TM) Dataset

description: Overview

The m-TM dataset was created to address the lack of publicly available, labeled datasets specifically designed for detecting mandibular third molars (m-M3). Derived from the UESB dataset (Silva et al., 2018), which originally consisted of 1500 panoramic radiographs (PRs) intended for tooth segmentation tasks, the m-TM dataset has been repurposed into a specialized resource for m-M3 presence detection. During the preparation process, 183 PRs were excluded due to factors such as the m-M3 being in the germination stage, misalignment caused by missing teeth, anomalies within the mandibular region, or inadequate image quality. The remaining 1317 PR images were meticulously labeled by an expert oral and maxillofacial radiologist, creating a problem-specific, high-quality dataset that supports advanced research in AI-assisted dentistry.

Dataset Details

The m-TM dataset is organized into four distinct categories based on the presence or absence of m-M3 in the left and right mandibular regions. It includes 89 images where m-M3 is absent on the left but present on the right, 74 images where m-M3 is present on the left but absent on the right, 810 images where m-M3 is present on both sides, and 344 images where m-M3 is absent on both sides. This structured classification enhances the dataset's utility for benchmarking and facilitates advanced AI-driven dental research. Additionally, the dataset adheres to the FAIR Guiding Principles, ensuring it is findable, accessible, interoperable, and reusable. These principles support the dataset's accessibility and promote reproducibility, making it a valuable resource for the research community.

Significance

The m-TM dataset represents a pioneering contribution to AI-assisted dental research, serving as the first publicly available dataset explicitly developed for m-M3 presence detection. By adhering to the FAIR principles and incorporating expert annotations, the dataset establishes a standardized benchmark for researchers, facilitates interdisciplinary collaboration, and promotes the development of advanced AI methodologies for dental applications. This resource fills a critical gap in the field, supporting innovations in clinical decision support systems and advancing the integration of AI into dentistry.

Citations

Researchers utilizing the m-TM dataset are required to cite the following studies:

- Kayadibi, İ., Köse, U., Güraksın, G. E., & Çetin, B. (2025). An AI-assisted explainable mTMCNN architecture for detection of mandibular third molar presence from panoramic radiography. International Journal of Medical Informatics, 195, 105724.

- Silva, G., Oliveira, L., & Pithon, M. (2018). Automatic segmenting teeth in X-ray images: Trends, a novel dataset, benchmarking, and future perspectives. Expert Systems with Applications, 107, 15–31.

For additional details about the UESB dataset, please visit the following website: http://ivisionlab.ufba.br/
DOI: 10.17632/yz6tjnt9kj
title: KENNEDY SYSTEMATIC REVIEW DATA SET

description: The data comprises of Scopus retrieved files and Included articles in the systematic review
DOI: 10.17632/kgr7x9vs9v
title: User Reviews of BCA Mobile App from Google Play Store (June 2023 - May 2024)

description: This dataset comprises 26,261 user reviews of the BCA Mobile app collected from the Google Play Store between June 1, 2023, and May 31, 2024. Each review includes the user's name, the rating they provided (ranging from 1 to 5 stars), the timestamp of when the review was created, and the text content of the review. The dataset is in Indonesian and focuses on feedback from users in Indonesia. This data can be used to perform sentiment analysis, understand user experiences, identify common issues, and assess the overall performance of the BCA Mobile app during the specified timeframe. The reviews are sorted based on the newest first, providing the latest feedback at the top.
DOI: 10.6084/m9.figshare.26172610.v1
title: AK traverse soil cores_information

description: This file present the information of soil core collection sites.
DOI: 10.17632/8sjnppnbvj
title: Supplementary tables of Sun et al. submitted to GCA titled "Large correlated zinc isotope variability in the eastern Pacific mantle as a result of low-degree melt metasomatism"

description: Description for Supplementary Tables associated with this article:
Supplementary Table 1:
Major and trace element data of the near-EPR 5-15°N seamount lavas and standard reference materials
Supplementary Table 2:
Sr-Nd-Pb isotope data of the near-EPR 5-15°N seamount lavas and standard reference materials
Supplementary Table 3:
Modeling of the Zn isotope variation during partial melting of DMM
Supplementary Table 4:
Major element abundances corrected for the effect of fractional crystallization to Mg# = ~72
Supplementary Table 5:
Estimation for the age of the enriched source component
Supplementary Table 5.1: Estimation for the age of the enriched source component with Sr-Nd isotope compositions same as sample CD6-9 with a garnet peridotite lithology
Supplementary Table 5.2: Estimation for the age of the enriched source component with more radiogenic Sr-Nd isotope compositions with a garnet peridotite lithology
Supplementary Table 5.3: Estimation for the age of the enriched source component with Sr-Nd isotope compositions same as sample CD6-9 with a garnet pyroxenite lithology
Supplementary Table 5.4: Estimation for the age of the enriched source component with more radiogenic Sr-Nd isotope compositions with a garnet pyroxenite lithology
DOI: 10.21233/d0kr-4y41
title: Horseleech Pond diatom surface sample dataset

description: Raw data for the Horseleech Pond diatom surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.17632/xvm2yxsxx4
title: Data for: Distance-based customer detection in fake follower markets

description: The dataset includes legitimate users and customers of fake follower markets. Please Read Readme.txt file that has an description of each files. The files in the dataset includes the information about labled users, follower relationship, following relationship, and follower distance from users. Included files are legitimate_id.txt, buyer_id.txt, ffollower_id.txt, follower.txt, followee.txt, legitimate_distance.txt, buyer_distance.txt, and Readme.txt
DOI: 10.15468/dl.8fmmmn
title: Occurrence Download

description: A dataset containing 2373 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Observation, Human Observation, Machine Observation, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Thalpophila matura (Hufnagel, 1766)"
 ]
}

 The dataset includes 2373 records from 65 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009128-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1379713.10fu
title: SH1379713.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1379714.10fu
title: SH1379714.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1379715.10fu
title: SH1379715.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1379716.10fu
title: SH1379716.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1379717.10fu
title: SH1379717.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1379718.10fu
title: SH1379718.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1379719.10fu
title: SH1379719.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1379721.10fu
title: SH1379721.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.