cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/kf7h9f2bmc
title: Polimi-23+CH kinetic scheme

description: Kinetic scheme used for the study "Combustion in a coke oven battery: numerical modeling and testing with focus on NOx emission" submitted to "Thermal Sciences and Engineering Progress"
DOI: 10.17632/kf7h9f2bmc.1
title: Polimi-23+CH kinetic scheme

description: Kinetic scheme used for the study "Combustion in a coke oven battery: numerical modeling and testing with focus on NOx emission" submitted to "Thermal Sciences and Engineering Progress"
DOI: 10.17632/34czjt9xz7.1
title: Dystonia - Simulation model and traces

description: This research data repository comprises the simulation model (full source code supplied) and the results of running the model for a series of scenarios. There is also a user guide with instructions to assist in the model setup.
DOI: 10.17632/34czjt9xz7.2
title: Dystonia - Simulation model and traces

description: This research data repository comprises the simulation model (full source code supplied) and the results of running the model for a series of scenarios. There is also a user guide with instructions to assist in the model setup and a narrative on the research approach and methods.
DOI: 10.17632/34czjt9xz7.3
title: Dystonia - Simulation model and traces

description: This research data repository comprises the simulation model (full source code supplied) and the results of running the model for a series of scenarios. There is also a user guide with instructions to assist in the model setup and a narrative on the research approach and methods.
DOI: 10.17632/34czjt9xz7.4
title: Dystonia - Simulation model and traces

description: This research data repository comprises the simulation model (full source code supplied) and the results of running the model for a series of scenarios. There is also a user guide with instructions to assist in the model setup and a narrative on the research approach and methods.
DOI: 10.17632/34czjt9xz7.5
title: Dystonia - Simulation model and traces

description: This research data repository comprises the simulation model (full source code supplied) and the results of running the model for a series of scenarios. There is also a user guide with instructions to assist in the model setup and a narrative on the research approach and methods.
DOI: 10.17632/34czjt9xz7.6
title: Dystonia - Simulation model and traces

description: This research data repository comprises the simulation model (full source code supplied) and the results of running the model for a series of scenarios. There is also a user guide with instructions to assist in the model setup and a narrative on the research approach and methods.
DOI: 10.17632/34czjt9xz7.7
title: Dystonia - Simulation model and traces

description: This research data repository comprises the simulation model (full source code supplied) and the results of running the model for a series of scenarios. There is also a user guide with instructions to assist in the model setup and a narrative on the research approach and methods.
DOI: 10.17632/34czjt9xz7.8
title: Dystonia - Simulation model and traces

description: This research data repository comprises the simulation model (full source code supplied) and the results of running the model for a series of scenarios. There is also a user guide with instructions to assist in the model setup and a narrative on the research approach and methods.
DOI: 10.17632/cdyfk73scx.1
title: Age at Infection as a Key Predictor of Cyst Burden in Pigs Experimentally Infected with Taenia solium

description: Data from the manuscript "Age at Infection as a Key Predictor of Cyst Burden in Pigs Experimentally Infected with Taenia solium", corresponding to the number of Taenia solium cysts found at necropsy in pigs experimentally infected with 20,000 eggs at different ages. The dataset includes several other variables, which were incorporated into a negative binomial regression to assess statistical differences in the number of cysts present at necropsy and to develop a predictive model.
DOI: 10.17632/8vvwg2ygnm.1
title: Dataset_Enhancing Student Loyalty

description: This study examines how perceived service quality (PSQ), technological innovation (TIN), and career prospects (CAP) shape student loyalty (LOY) in higher education, with relationship quality (RQ) as a mediating mechanism. Grounded in relationship marketing theory and total quality management (TQM), the research addresses a gap concerning forward-looking drivers of loyalty in emerging educational contexts. A survey of 581 Vietnamese university students was analysed using structural equation modelling. The findings reveal that PSQ, TIN, and CAP all have significant direct and indirect effects on LOY via RQ. Among these, PSQ exerts the strongest overall influence, while CAP contributes notably through employability perceptions. RQ - comprising trust, satisfaction, and commitment - plays a central mediating role in loyalty formation
DOI: 10.17632/v9s7jtxhdr.1
title: Financial Socialization to Financial Well-Being

description: The methodology used is based on a quantitative, non-experimental, cross-sectional and correlational research study. To carry out the analysis, information provided by the National Survey on Financial Health (ENSAFI for its Spanish acronym), conducted in 2023 by the National Institute of Statistics and Geography (INEGI in Spanish) in collaboration with the National Commission for the Protection and Defense of Users of Financial Services (CONDUSEF in Spanish), was used. The unit of analysis was composed of individuals over 18 years of age, distributed throughout the country. In total, 20,448 people participated in the study.
DOI: 10.17632/78h3nvwggm.1
title: Supplementary figures and tables for "Skin microbiota differs between Black and White patients with cutaneous T-cell lymphoma"

description: This data set contains the supplementary figures (4), and supplementary tables (7), for our manuscript titled "Skin microbiota differs between Black and White patients with cutaneous T-cell lymphoma."
DOI: 10.17632/78h3nvwggm
title: Supplementary figures and tables for "Skin microbiota differs between Black and White patients with cutaneous T-cell lymphoma"

description: This data set contains the supplementary methods, supplementary figures (7), and supplementary tables (7), for our manuscript titled "Skin microbiota differs between Black and White patients with cutaneous T-cell lymphoma."
DOI: 10.17632/78h3nvwggm.2
title: Supplementary figures and tables for "Skin microbiota differs between Black and White patients with cutaneous T-cell lymphoma"

description: This data set contains the supplementary methods, supplementary figures (7), and supplementary tables (7), for our manuscript titled "Skin microbiota differs between Black and White patients with cutaneous T-cell lymphoma."
DOI: 10.17632/mpf5ryz8td.1
title: Combination of Carbon Dioxide (CO2) Laser and Triamcinolone Acetonide for Keloid and Hypertrophic Scar Treatment: A Systematic Review

description: Supplemental materials for the article titled "Combination of Carbon Dioxide (CO2) Laser and Triamcinolone Acetonide for Keloid and Hypertrophic Scar Treatment: A Systematic Review", published in the Journal of the American Academy of Dermatology.
DOI: 10.17632/m45vcmndvc.1
title: Brazilian Urban Mobility Image Dataset

description: The Brazilian Urban Mobility Image Dataset comprises 1000 JPEG images of Brazilian urban roadways. The image corpus encompasses scenes from four geographically distinct urban centers: Manaus (State of Amazonas), Barueri (State of São Paulo), Chapada (State of Mato Grosso), and Porto Velho (State of Rondônia). This dataset incorporates a total of 6932 annotations, categorized into four classes of objects prevalent in Brazilian urban traffic: passenger cars, motorcycles, buses, and a generalized "vehicle" class (including trucks, vans, ambulances, and similar). Annotations were performed using the Labelbox platform through the application of bounding boxes. The collected dataset was partitioned into three subsets: a training set comprising 60% of the data, a validation set containing 10%, and a test set accounting for the remaining 30%. Object annotations are provided in text files according to the YOLOv11 format.
DOI: 10.17632/rzgfjkpz64.1
title: Supplementary Material - JAAD-D-25-00903R1

description: Supplementary Figure for JAAD manuscript titled "Efficacy, Safety, and Recurrence in Seborrheic Dermatitis: A Dose-Dependent Analysis of Oral Isotretinoin (10 mg vs. 20 mg)"
Supplementary Figure 1. Receiver Operating Characteristic (ROC) curve for the predictive ability of the SDASI baseline score for recurrence
The ROC curve illustrates the sensitivity versus 1-specificity for the SDASI baseline score in predicting recurrence. The blue line represents the model's performance, while the red diagonal line indicates the reference classifier. A curve above the diagonal suggests predictive ability, whereas proximity to the diagonal indicates limited discriminative power. The presence of diagonal segments suggests tied values in the data.
DOI: 10.17632/yt3v7vw5pn.1
title: Good and Bad classification of Citrus sinensis

description: Here's a data description within 3000 characters for your project titled "Good and Bad Classification of Oranges":-


Project Title: Good and Bad Classification of Oranges

Dataset Description:-

This dataset is designed for a binary classification task aimed at distinguishing between good and bad quality oranges based on visual or measurable characteristics. It contains a total of 2000 samples, split evenly into:

1000 good orange samples

1000 bad orange samples

Each sample represents an individual orange, captured or measured through consistent methods to ensure quality and comparability.

Class Definitions:-

Good Orange:- An orange that meets criteria such as ripeness, vibrant color, uniform shape, lack of surface damage or mold, proper size, and firmness. These are suitable for sale and consumption.

Bad Orange:- An orange exhibiting qualities such as over-ripeness, under-ripeness, discoloration, mold growth, deformation, bruising, or soft/rotten spots, making them unsuitable for consumer use.


Features (may include, depending on data type):-

Visual Features:- Color histograms, texture, shape parameters, presence of defects or spots.

Physical Features:- Weight, diameter, firmness level.

Image Data (if applicable):- High-resolution images under uniform lighting and background.

Label:-Binary label indicating class: 1 for good, 0 for bad.

Data Collection Method:- Samples were collected from a variety of sources including local markets, farms, and storage facilities to include a diverse representation of both good and bad oranges. If image-based, photos were taken using a consistent camera setup. If physical measurements are involved, instruments like calipers, scales, and firmness testers were used.

Purpose of the Dataset:- The dataset is intended for machine learning model development and evaluation in tasks such as:

Quality control automation

Agricultural product grading

Computer vision-based fruit sorting systems


Applications:-

Deployment in smart sorting machines in fruit processing units

Mobile or embedded quality inspection tools

Consumer applications for home use to detect fruit quality

Dataset Format:

If structured data:-CSV or Excel format with each row as a sample and columns as features plus label

If image data:- Folder structure with labeled directories (e.g., /good/ and /bad/) or metadata file containing image names and labels

Ethical Considerations:- The dataset only contains non-personal, agricultural data. Usage should be aligned with fair and transparent machine learning practices, especially in agricultural automation that may impact farmers' livelihood.

Let me know if you need this description tailored for a report, website, or presentation format.
DOI: 10.17632/dd9v8y8f54.1
title: Supplemental Material for JAAD Article, "Outcomes of Mohs micrographic surgery versus wide local excision in sebaceous carcinoma: a retrospective cohort analysis"

description: Supplemental Material for JAAD Article, "Outcomes of Mohs micrographic surgery versus wide local excision in sebaceous carcinoma: a retrospective cohort analysis"
DOI: 10.17632/dd9v8y8f54.2
title: Supplemental Material for "Utilization and outcomes of Mohs micrographic surgery versus wide local excision in sebaceous carcinoma: a retrospective cohort analysis"

description: Supplementary Table I. Baseline demographic and tumor characteristics stratified by surgical modality
Supplementary Table II. Multivariate logistic regression analysis of factors associated with utilization of MMS
DOI: 10.17632/sx2tphzvcw.1
title: A UAV Image Dataset for Object Detection with Annotations Generated Using LabelImg and Roboflow

description: The dataset consists of drone images that were obtained for agricultural field monitoring to detect weeds and crops through computer vision and machine learning approaches. The images were obtained through high-resolution UAVs and annotated using the LabelImg and Roboflow tool. Each image has a corresponding YOLO annotation file that contains bounding box information and class IDs for detected objects.
The dataset includes:

Original images in .jpg format with a resolution of 4096 × 3072 pixels.

Annotation files (.txt) corresponding to each image, following the YOLO format: [class_id x_center y_center width height] (all normalized values).

A classes.txt file listing the object categories used in labeling (e.g., Weed, Crop).

The dataset is intended for use in machine learning model development, particularly for precision agriculture, weed detection, and plant health monitoring. It can be directly used for training YOLOv7 and other object detection models.
DOI: 10.15468/dl.9h2f5s
title: Occurrence Download

description: A dataset listing the 1 species recorded in GBIF matching the query:
{
 "TaxonKey" : [
 "is Meconopsis gakyidiana T.Yoshida, Yangzom & D.G.Long"
 ]
}

 The dataset's 1 records were derived from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017284-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/vf9n9f2z9z.1
title: CM chondrite equilibrium modelling

description: Geochemical modelling with PHREEQC (equilibrium models) to model the aqueous alteration of CM chondrites (see Haller&Lee "Controls on the petrologic type of CM carbonaceous chondrites evaluated by geochemical equilibrium modelling"). 
diagenesis_equi.dat: database with which to run the input script. Compiled from core10.dat (Neveu et al. 2017) and diagenesis.dat (Zhang et al. 2020)
.phr files: input files for each scenario (default, NoGas, NH3CO2, HighP, Asuka)
Model_results: Output from PHREEQC (see ReadMe in first sheet)
DOI: 10.17632/v9b7rwrwx9.1
title: Data for: Estimation of Cercospora Leaf Spot Disease Severity in Table Beets from UAS Multispectral Images

description: This dataset comprises multispectral images collected via Unmanned Aerial Systems (UAS) over study plots at Cornell Agritech in Geneva, NY, USA. The images capture various crop conditions and are paired with assessments of disease severity, specifically CLS (Cercospora Leaf Spot).

Data Collection:
The multispectral imagery spans two collections:
* Multispec_2021_2022: Contains images with five spectral bands (475 nm, 560 nm, 668 nm, 717 nm, 840 nm), collected during the 2021 and 2022 growing seasons.
*Multispec_2023: Includes imagery from four spectral bands (560 nm, 650 nm, 730 nm, 860 nm), collected in the 2023 growing season.

File naming convention:
Each image file is named according to the plot number and the date of capture, using the format plt_rYYYYMMDD, where:
* 'plt' stands for the plot number.
* 'YYYYMMDD' represents the date on which the image was captured (year, month, day).
For example, the file name 5_r20210715 corresponds to an image taken on July 15, 2021, from study plot 5.

Disease Severity data:
File named CLS_DS contain visual assessments of CLS disease severity, noted for each plot.
DOI: 10.15468/dl.vrkqs4
title: Occurrence Download

description: A dataset containing 865 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is True",
 "HasGeospatialIssue is False",
 "OccurrenceStatus is Present",
 "TaxonKey is Equus przewalskii Poliakov, 1881"
 ]
}

 The dataset includes 865 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017291-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/v9b7rwrwx9.2
title: Data for: Estimation of Cercospora Leaf Spot Disease Severity in Table Beets from UAS Multispectral Images

description: This dataset comprises multispectral images collected via Unmanned Aerial Systems (UAS) over study plots at Cornell Agritech in Geneva, NY, USA. The images capture various crop conditions and are paired with assessments of disease severity, specifically CLS (Cercospora Leaf Spot).

Data Collection:
The multispectral imagery spans two collections:
* Multispec_2021_2022: Contains images with five spectral bands (475 nm, 560 nm, 668 nm, 717 nm, 840 nm), collected during the 2021 and 2022 growing seasons.
*Multispec_2023: Includes imagery from four spectral bands (560 nm, 650 nm, 730 nm, 860 nm), collected in the 2023 growing season.

File naming convention:
Each image file is named according to the plot number and the date of capture, using the format plt_rYYYYMMDD, where:
* 'plt' stands for the plot number.
* 'YYYYMMDD' represents the date on which the image was captured (year, month, day).
For example, the file name 5_r20210715 corresponds to an image taken on July 15, 2021, from study plot 5.

Disease Severity data:
File named CLS_DS contain visual assessments of CLS disease severity, noted for each plot.
DOI: 10.17632/8dfrng5hxr.1
title: Data for a hydro-mechanical phase field model for hydraulic fracturing of grain structure rocks based on Voronoi tessellation

description: This is the dataset associated with the paper titled "A hydro-mechanical phase field model for hydraulic fracturing of grain-structured rocks based on Voronoi tessellation" . The paper is currently under peer review for potential publication in the journal "Rock Mechanics and Rock Engineering." The dataset includes the source code for the Voronoi tessellation post-processing program in MATLAB and the data in figures. The COMSOL source files can be obtained by contacting the first author at xingjq@tongji.edu.cn. The dataset will be updated following the formal publication of the paper, and the latest version in the repository should be considered the most accurate and complete.
DOI: 10.17632/8dfrng5hxr.2
title: Data for a hydro-mechanical phase field model for hydraulic fracturing of grain structure rocks based on Voronoi tessellation

description: This is the dataset associated with the paper titled "A hydro-mechanical phase field model for hydraulic fracturing of grain-structured rocks based on Voronoi tessellation" . The paper is currently under peer review for potential publication in the journal "Rock Mechanics and Rock Engineering." The dataset includes the source code for the Voronoi tessellation post-processing program in MATLAB and the data in figures. The COMSOL source files can be obtained by contacting the first author at xingjq@tongji.edu.cn. The dataset will be updated following the formal publication of the paper, and the latest version in the repository should be considered the most accurate and complete.
DOI: 10.17632/rnh9zbfjj7.1
title: Data for: Environmental impact mitigation in mega projects by TBL-based sustainable construction The mediation effect of sustainable practices and regulations

description: Implementing sustainable approaches in developing nations, particularly in the context of megaprojects, is not widespread. Consequently, it is seen as an innovative idea in these nations’ building sector. Sustainable growth is significantly hampered by the ineffective adoption and application of sustainable consumption (SC) (Marsh et al., 2021). 
 Megaprojects are vital to every nation’s progress. The building industry boosts national economies with its unquestionable contributions to the built environment and development. However, it is a fact that megaprojects have environmental effects, and our only option is to work toward their mitigation. Particularly in developing nations, several factors, including the pursuit of economic development, consumerism, corruption, and the financial implications of sustainable construction, often take precedence over considerations of environmental and ecological stability. As a result, in these countries, the objectives that conflict with sustainability and its implementation tend to outweigh them.
The research carried out is novel and innovative. This study examines the effects of sustainable building in megaprojects on environmental and ecological balance, shedding light on the implications of such initiatives. The implementation of sustainable practices (SP) and regulatory measures (R), with cost (R) acting as a moderating factor, mediates the impact in question, albeit to a minimal extent. The research analyzes indicators and their strengths in relation to their respective factors, utilizing the latest and most advanced analysis methods such as smart PLS.
Utilizing the research results and implementing the conceptual model standard will help mitigate the environmental impacts associated with megaprojects. Furthermore, these results will make a valuable contribution to the existing body of knowledge for experts, supply authorities with useful information, and be a valuable resource for environmental regulatory bodies in developing countries. Ultimately, this will promote the implementation of sustainable practices in these nations.