cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/8g4pnzy6fc
title: Good and bad characteristics of molina (Triticum durum)

description: Data Description for Good and Bad Classification of Triticum durum

The dataset used in this project focuses on the classification of Triticum durum (commonly known as durum wheat) into two categories: good and bad quality samples. The goal of the project is to build a reliable model that can accurately differentiate between high-quality and low-quality grains based on selected features.

The dataset comprises a total of 2000 samples, with an equal distribution of 1000 good and 1000 bad samples. Each sample represents a batch or unit of Triticum durum and is labeled according to quality assessment standards used in agricultural or industrial evaluation.

1. Data Collection

The samples were gathered from different harvests and suppliers to ensure variability in grain quality. Good quality samples represent grains suitable for milling and pasta production, showing desirable traits such as uniform size, color, low impurity content, and good hardness. Bad quality samples may include grains that are damaged, discolored, infested, or otherwise not meeting quality standards.

2. Features

Each sample in the dataset is characterized by several features (depending on available sensors or measurement tools), which may include:

Physical Attributes: kernel size, shape, and weight

Color Features: RGB or HSV color values from grain images

Texture Features: surface roughness or uniformity derived from image processing

Chemical/Quality Parameters (if available): protein content, moisture, and hardness index

Image-based Features: edge sharpness, contrast, or other pattern-based metrics (if machine vision is used)


These features may be numerical, categorical, or derived from digital image processing techniques.

3. Data Labeling

Each sample is labeled either as:

Good (Label = 1)

Bad (Label = 0)


Labeling was performed based on expert evaluation or using existing standards in grain quality assessment (e.g., ISO, USDA grading systems).

4. Data Format

The dataset is stored in a structured format such as:

CSV file: with rows representing individual samples and columns for each feature plus the label

Image folder (optional): if visual classification is performed, images are stored in labeled folders (e.g., /good/, /bad/) and may be linked to metadata in a CSV file


5. Purpose and Application

This dataset is designed to train and test machine learning models for the purpose of automating quality control in grain processing and agriculture. Accurate classification of Triticum durum quality can enhance supply chain efficiency, reduce waste, and improve food product quality.
DOI: 10.17632/bc5pkv53j5
title: Data for: Analysis of Risk Factors and Establishment of a Risk Prediction Model for Cardiothoracic Surgical Intensive Care Unit Readmission After Heart Valve Surgery in China: A Single-center Study

description: Analysis of Risk Factors for Cardiothoracic Surgical ICU Readmission After Heart Valve Surgery
DOI: 10.6084/m9.figshare.22036547.v2
title: Single cell profiling of LUAD

description: This data is an integrated scRNA-seq data.
DOI: 10.17632/nb737txvr5
title: Network Analysis of HOX genes in Endometriosis

description: The study identified causative genes of the HOX family in endometriosis. Co-expression networks were constructed by PCR-array data. The most DEGs are effective genes in development, metabolic and neural processes.
DOI: 10.17632/yk2pz4hcb5
title: Fine particulate matter (PM2.5) datasets for both Indoor and Outdoor environments at two South Texans residences.

description: This dataset includes high-frequency PM2.5 (µg/m3) measurements collected at 2-minute intervals, along with calculated 1-hour and daily average concentrations collected at two residences in the Rio Grande Valley (RGV), Texas, using PurpleAir-II-SD monitor. Additionally, it includes temperature (ºC) and relative humidity (%) measured by the sensors. The data was collected for one month during the summer from indoor (kitchen) and outdoor (front yard) environments at two locations: Home-1 in Weslaco from June 16, 2024, to July 16, 2024, and Home-2 in Mission from June 22, 2024, to July 16, 2024. Furthermore, the resultant wind speed and wind direction data were obtained from nearby Texas Commission on Environmental Quality (TCEQ) Continuous Ambient Monitoring Stations (CAMS), providing a broader understanding of meteorological influences on air quality. The raw PM2.5 data were corrected using Barkjohn's US-wide correction equation to increase the accuracy of the measurements and are presented in the datasets. The dataset is available in three CSV files: one for Home-1, one for Home-2, and one for wind data (Wind Rose) from the TCEQ stations.
DOI: 10.6084/m9.figshare.13079543.v1
title: Pancreas development preprocessed

description: Preprocessed scRNA-seq dataset of pancreatic development at E15.5 in mice assayed using 10x genomics. Total cell number is 2531. Contains RNA velocity (La Manno et al., Nature 2018) computed using scVelo (Bergen et al., Nature Biotechnology 2020).<br><br>Please cite the original publication: https://doi.org/10.1242/dev.173849
DOI: 10.6084/m9.figshare.2068011.v2
title: Dopamine PET and SPET images

description: [<sup>18</sup>F]FDOPA PET and [<sup>123</sup>I]FP-CIT SPET templates freely available at the NITRC website (http://www.nitrc.org/projects/spmtemplates/)
DOI: 10.6084/m9.figshare.27085870.v1
title: Climate effects of ecosystem change converge according to the ratio of the daytime to daily vapor flux

description: This dataset contains global eddy covariance data supporting the results in the paper accepted in The Innovation ("Climate effects of ecosystem change converge according to the ratio of the daytime to daily vapor flux"). Please contact the corresponding authors for permission to use the data.
DOI: 10.6084/m9.figshare.2068011.v1
title: Image data

description: [<sup>18</sup>F]FDOPA PET and [<sup>123</sup>I]FP-CIT SPET templates freely available at the NITRC website (http://www.nitrc.org/projects/spmtemplates/)
DOI: 10.6084/m9.figshare.5501638.v1
title: Floristic and climatic reconstructions of two Lower Cretaceous successions from Peru

description: Climate during the Early Cretaceous in tropical South America has often been reconstructed as arid. However, some areas seem to have been humid. We reconstructed the floristic composition of two tropical stratigraphic successions in Peru using quantitative palynology (rarefied species richness and abundance), and used the abundance of aridity vs. humidity indicator species to infer the predominant climate conditions of this region. The Berriasian to Hauterivian La Merced succession was dominated by fern spores and was predominantly humid. The Albian Aguas Frias succession yielded rich palynofloras, with 127 species, and also indicates predominantly humid conditions. These results support the hypothesis that the west margin of South America was humid during the Early Cretaceous, thus improving the tropical climate reconstructions during the Cretaceous severe global warming episodes.
DOI: 10.17632/55hr73zc4y
title: A Dataset of Restitution Coefficients as well as Dynamic and Rolling Frictions for Rockfall Analysis

description: These data were collected from different studies in the literature and uploaded in the form of an Excel spreadsheet. Columns A to D of this spreadsheet represent the normal restitution coefficient, the tangential restitution coefficient, the dynamic friction coefficient, and the rolling friction coefficient, respectively. Additionally, Column E indicates the rock type from which the variables were extracted, and Column F indicates the primary source of the data.
DOI: 10.17632/c4wpbkwwx4
title: Factores asociados a la lactancia materna exclusiva en un hospital de referencia nacional

description: Es una base de datos filtrada que estudia los factores asociados con la práctica de lactancia materna exclusiva al momento del egreso hospitalario.
DOI: 10.17632/fn64x6vpn4
title: Quantitative Interpretation of Protein Diffusion Coefficients in Mixed Protiated-Deuteriated Aqueous Solvents

description: Supporting data for Quantitative Interpretation of Protein Diffusion Coefficients in Mixed Protiated-Deuteriated Aqueous Solvents
*Excel document containing all calculations supporting the paper/SI.
*Excel sheet for calculating diffusion coefficients of molecules in mixed protiated-deuteriated aqueous solvents.
DOI: 10.17632/fx434zhdmr
title: Datasets of water geochemistry, sediment extractions, and FT-ICR MS results from the Songnen Basin, China

description: These datasets have been updated with surface water and groundwater geochemistry and the FT-ICR MS results from the Songnen Basin, China, to support the revised manuscript submitted to JGR Biogeosciences.
DOI: 10.17632/kt7xd5y62v
title: Large datasets on dynamic properties of carbon fibre/shape memory polymer composites under various total and local temperature field

description: Shape memory polymers and their composites as a class of promising smart materials have been widely applied in aerospace engineering, soft robotics and healthcare fields. Mechanical properties of composites based on shape memory polymers however are sensitive to temperature and loading methods. The data paper presents the dynamic properties of carbon fibre reinforced shape memory polymer composite under various thermal total and local fields. The thermal fields were provided by attached electrothermal film and tested by the thermal imaging camera. The initial velocity was loaded by knocking vibration excitation and the response velocity was measured by Laser Doppler Velocimetry. The raw datasets obtained could support further study in the area and development of carbon fibre reinforced shape memory polymer composites.
DOI: 10.6084/m9.figshare.28881596.v1
title: Work-family balance data of faculty

description: Labor Economics
DOI: 10.17632/dzwvt4bz4j
title: Benchmark dataset and instance generator for the Satellite-Image-Acquisition Scheduling Problem

description: The Satellite-Image-Acquisition Scheduling Problem (SIASP) is of great importance in the space industry; every day, satellite operators must face the challenge of selecting the optimal subset of images to be taken during the next orbit pass of a satellite with respect to some notion of value from a set of requests made by their clients. This dataset is composed of 20 different instances. These use cases have been selected because of their size, which is adequate for being solved by current Quantum Computers. Thus, 14 of the instances (in data folder) are part of the well-known SPOT5 benchmark [1], while six of them (in generated_data folder) have been created using an instance generator, also provided in this benchmark.

[1] E. Bensana, M. Lemaitre, and G. Verfaillie, “Earth observation satellite management,” Constraints, vol. 4, no. 3, pp. 293–299, 1999.
DOI: 10.17632/fj5pbdf95t
title: SPAMID-PAIR

description: Data post-comment pairs were collected from 13 selected Indonesian public figures (artists) / public accounts with more than 15 million followers and categorized as famous artists. It was collected from Instagram using an online tool and Selenium. Two persons labeled all pair data as an expert in a total of 72874 data. The data contains Unicode text (UTF-8) and emojis scrapped in posts and comments without account profile information.

It contains several fields:
-igid: Account ID,
-comment: Comment of a post,
-post: Post from an ID,
-emoji: Whether the data contains emojis or not (1 or 0),
-spam: Whether the data is spam or not (1 or 0),
-lengthcomment: The character length of the comment,
-lengthpost: The character length of the post,
-countemojicomment: Number of emoji symbol characters in comments,
-countemojicommentuniq: Number of emoji symbol characters in comments (unique),
-countemojipost: Number of emoji symbol characters in posts,
-countemojipostuniq: Number of emoji symbol characters in the post (unique)
DOI: 10.17632/jf34ktznk7
title: Vulvar Lichen Sclerosus and Vitiligo Overlap and Clinical Features 

description: PubMed, OVID, Scopus, and Web of Science were searched for cases of overlapping vulvar vitiligo and LS. Publications including reviews, reports without concurrent LS and vitiligo, and non-English studies were excluded. Seven studies involving 38 patients with vulvar LS and concomitant extragenital vitiligo (3), vulvar vitiligo (2), or unspecified vitiligo (33) were included. Clinical symptoms and findings for LS included pruritis, burning, dyspareunia, and textural changes (atrophy, lichenification, hyperkeratosis), while vitiligo was characterized by depigmented macules, and trichome.
DOI: 10.17632/rknjxtg2vn
title: High-Resolution Annotated Concrete Column Images for Object Detection

description: This dataset contains 501 high-resolution images of concrete columns captured from real buildings under construction in Iran. The photos were taken from approximately direct angles, providing clear views of the buildings' exteriors and focusing on the concrete columns located on the outer layer. Each image has been annotated with rectangular bounding boxes to highlight the exterior layer columns, which are at the built stage. The dataset is intended to facilitate detection tasks in machine learning and computer vision applications. The annotations, created using CVAT, are provided in YOLO format. This dataset is particularly valuable for researchers and practitioners working on object detection models, specifically in the fields of structural engineering, construction, and automated inspection systems.
Dataset Details:
• Total Images: 501
• Image Formats: JPEG and PNG
• Annotations: Each image is annotated with a single class representing the boundary box of the concrete columns on the exterior layer of the building. The annotations are provided in YOLO format, with labels as rectangular bounding boxes.
• Class: Outer Layer Concrete Column (Built Stage): 8,588 instances
• Bounding Box Format: YOLO (x_center, y_center, width, height, normalized by image dimensions)
DOI: 10.17632/thbg743tdz
title: Supporting data for strengthening and deformation behavior of as-cast CoCrCu1.5MnNi high entropy alloy with micro-/nanoscale precipitation 

description: The data presented here are related to the research article entitled “Strengthening and deformation behavior of as-cast CoCrCu1.5MnNi high-entropy alloy (HEA) with micro-/nanoscale precipitation. Non-equimolar CoCrCu1.5MnNi was cast by the conventional induction melting under a high-purity Ar atmosphere. Scanning electron microscopy equipped with energy dispersive spectroscopy (EDS), and transmission electron microscopy (TEM) were used for micro- and nanostructure characterization. Subsize tensile specimens with two different gage length to width ratio were tested at room and cryogenic temperatures to assess the accuracy of mechanical testing in the as-cast CoCrCu1.5MnNi HEAs. The mixing enthalpy (ΔHmix) versus lattice elastic energy (ΔHel) criterion was used to predict the stable phases. The data on the microstructural and nanostructural distribution of various phases on the strength and ductility in the as-cast HEA could be used in designing high entropy alloys with excellent as-cast mechanical properties.
DOI: 10.17632/yk8wj7xgdg
title: Immunostimulatory cancer-associated fibroblast subpopulations can predict immunotherapy response in head and neck cancer

description: RNA-Sequencing Data Associated with the manuscript "Immunostimulatory cancer-associated fibroblast subpopulations can predict immunotherapy response in head and neck cancer." Includes integrated single-cell RNA-Sequencing data & VIPER inferred protein activity matrix uploaded as Seurat Objects with patient and cluster metadata included, as well as sub-clustered fibroblast Seurat object and spatial geomx data. Also includes bulk RNA-Sequencing datasets of responders vs non-responders to treatment and bulk RNA-Sequencing datasets of sorted fibroblast populations used for cluster phenotyping and ex vivo co-culture experiments.
DOI: 10.6084/m9.figshare.22691407.v2
title: Untitled Item

description: The MIDOG++ dataset represents an extension of the data set used in the MIDOG 2021 and 2022 challenges. We provide region of interest images from 503 histological specimens of seven different tumor types with variable morphology: breast carcinoma, lung carcinoma, lymphosarcoma, neuroendocrine tumor, cutaneous mast cell tumor, cutaneous melanoma, and (sub)cutaneous soft tissue sarcoma. The human and canine samples were processed and stained at different human and veterinary pathology laboratories with standard H&E dye and digitized with different digital whole slide image scanners. We provide labels for 11,937 mitotic figures that have been differentiated against 14,351 imposter cells in a blinded consensus by two pathologists and a final decision by a third pathologist for disagreed labels.
DOI: 10.17632/4wgx2mprks
title: Data for article "A Machine Learning Approach to Rank Pricing Problems in Branch-and-Price"

description: This dataset accompanies the research paper titled "A Machine Learning Approach to Rank Pricing Problems in Branch-and-Price." It features a machine learning-based ranker designed to enhance the column generation process by guiding the search for new columns. The application of this ranker is evaluated within the context of operating room scheduling.

The dataset is splitted into two directories: "train" and "evaluate."

The "train" directory contains the data used for training the machine learning models as detailed in the publication. This directory includes a dataset description and a CSV file capturing the recorded features. Additionally, it houses an 'instance' directory subdivided into four subdirectories (r1_s2_d10, r1_s2_d5, r1_s4_d10, r1_s4_d5), each containing 30 instances. These instances are characterized by the number of patients (10, 20, 30), the number of days (5, 10), and the number of surgeons (2, 4), culminating in a total of 120 instances across all subdirectories.

The "evaluate" directory is structured to validate the methodologies developed in the research. It includes an 'input' folder with two subfolders (r1_s4_d5, r1_s4_d10), each containing 9 instances. These instances are characterized by the number of patients (30, 40, 50), the number of days (5, 10), and the number of surgeons (4), culminating in a total of 18 instances across all subdirectories. These instances are utilized to assess and validate the strategies delineated in the paper. The 'output' folder within the directory documents the results for each strategy (best and random branch-and-price, ML strategy, and ILP strategy) with 1, 3, 5, 10, 15, 20 patterns added. Results for each input instance are aggregated here, including CSV files of results, PDFs of branching trees, and output log files.

All instances are stored as JSON files and represent synthetically generated data that simulate real-life hospital environments. The methodology employed to generate the data is elaborated in the corresponding paper.
DOI: 10.17632/8b62nm2gmv
title: Job Dataset for IT Professionals

description: The dataset contains information about job title, job description and requirement for specific job in the sector of Information Technology.
DOI: 10.17632/zzwg3nnhsz
title: Algerian Dialect

description: These datasets have been gathered using the YouTube API. These comments are sorted by relevance from more than 30 Algerian press channels. The dataset consists of 45,000 annotated comments, with five class sentiments, namely very negative (0), negative (1), neutral (2), positive (3), and very positive (4). Here's the columns description: Column 1: comments Column 2: label (from 0 to 4) Column 3: collection date Column 4: like count Column 5: video URL from which the comment has been extracted Column 6: annotation datetime
DOI: 10.17632/7bw2hngcvz
title: ZD001

description: A fabric defect dataset was independently collected and constructed, with all original images sourced from the fabric inspection workshops of textile enterprises. A flaw imaging control system, based on computer vision, was developed in conjunction with industrial field equipment. The system integrates key technologies such as multi-light source fusion, high-precision visual sensing modules, edge computing platforms, and visual interaction. It is capable of multi-angle, high-quality, and high-resolution defect image acquisition and digital storage. For clarity, the dataset created is named ZD001_FD, which was used for training the IFD-GAN algorithm and validating its industrial application. The ZD001_FD dataset includes eight categories of cross-scale fabric defects: warp-direction defects, such as broken end, misdraw, and reediness; weft-direction defects, including thin place and thick place; and localized defects, such as hole, cotton ball, and kinky filling. 
The conventional approach to dividing test sets has limitations, as it often involves simplistic scenarios that fail to capture the complexity and diversity of real-world industrial applications, which are influenced by numerous interfering factors . To address these shortcomings, test sets were collected and created under various industrial scenarios to replicate edge-testing conditions, thereby assessing the model's adaptability and generalization capabilities.
Due to the flexible and high-fidelity cross-scale defect generation capability of IFD-GAN, the expansion and inter-class balancing of the ZD001_FD dataset were successfully achieved, resulting in enhanced diversity. The augmented dataset is named ZD001_FD_IG.
DOI: 10.17632/d89xscbjd9
title: Data for: Matrix-dependent size modifications of iron oxide nanoparticles (Ferumoxytol) spiked into rat blood cells and plasma: Characterisation with TEM, AF4-UV-MALS-ICP-MS/MS and spICP-MS.

description: AF4-UV-MALS-ICP-MS intensities of iron oxide nanoparticles spiked into rat blood cells and plasma
DOI: 10.17632/fk8vtdmxfk
title: A Method for the Extraction of Apocynum venetum L. Spatial Distribution in Yuli County, Xinjiang, via an Improved SegFormer Network

description: The collection of ground survey data is essential for creating more accurate samples during classification and for validating the subsequent identification and extraction accuracy of Apocynum. Ground surveys of Apocynum were conducted within the study area on 25 August, 2023, to obtain sample data for Apocynum within the plots. Photographs of the actual sample points were taken and preserved, and the latitude and longitude coordinates of each feature block, as well as the crop type, were recorded to facilitate the creation of training labels, which allows for a better grasp of the characteristics of the Apocynum. Based on the actual ground survey and visual interpretation, a total of 6,175 Apocynum sample points were obtained in an area of Yuli County where the Apocynum distribution is relatively dense (86.5°E, 41.3°N).The data for this study comes from field ecological surveys. No plant specimens were collected. Species were identified based on morphological features observed in the field. All necessary permits and permissions for the field research have been obtained.
DOI: 10.17632/n88f3ty2kc
title: Data for: A numerical study on the thermal conductivity of H2O/CO2/H2 mixtures in supercritical regions of water for coal supercritical water gasification system

description: This data article provides the results of the predicted thermal conductivity for H2O/CO2 binary mixtures, H2O/H2 binary mixtures, and H2O/CO2/H2 ternary mixtures via equilibrium molecular dynamics (EMD) simulations and four different theoretical calculation models: (1) KM model for nonpolar gas mixtures; (2) KM model for polar gas mixtures; (3) MS model for nonpolar gas mixtures; (4) MS model for polar gas mixtures. The data presented in this article are related to the article titled " A numerical study on the thermal conductivity of H2O/CO2/H2 mixtures in supercritical regions of water for coal supercritical water gasification system ".