cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/j8jjkfyx34
title: ADSC-Exosome on Parkinson's disease

description: The original IHC images from the animal studies
DOI: 10.17632/k68pdvdvnm
title: PRISMA Flow Diagram

description: PRISMA Flow Diagram
DOI: 10.17632/smc8mbb3jc
title: Data for: An open-label randomised clinical trial to compare the efficacy of dietary caloric restriction and physical activity for weight loss in overweight pet dogs

description: Supporting data for study: An open-label randomised clinical trial to compare the efficacy of dietary caloric restriction and physical activity for weight loss in overweight pet dogs
DOI: 10.17632/3cwf729p34
title: DairyFMBN: a database of studies on the bacterial microbiota of dairy products
DOI: 10.17632/rj6gnmnnmt
title: Datasets from "A framework to predict binary liquidus by combining machine learning and CALPHAD assessments"

description: These datasets are associated with the following publication, and the reader is referred to it for more details.
G. Deffrennes, K. Terayama, T. Abe, E. Ogamino, R. Tamura, A framework to predict binary liquidus by combining machine learning and CALPHAD assessments, Materials & Design (2023) https://doi.org/10.1016/j.matdes.2023.112111

In this work, 3 machine learning models are developed to predict the liquidus in binary systems.
Model 1 predicts the formation of liquid miscibility gaps.
Model 2 predicts the equilibrium onset temperature of solidification.
Model 3 predicts the critical temperature of liquid miscibility gaps.

The datasets that are used to build the models and evaluate their performance are found in the “CALPHAD Datasets” folder. They were collected from 466 CALPHAD assessments of binary phase diagrams listed in “Reference_list.csv”. It is emphasized that CALPHAD calculations in areas without experimental data were included in the training datasets. As a result, the datasets contain some unreliable data. This is especially true for the miscibility gap temperature regression dataset for Model 3, because (1) experimental data on liquid miscibility gaps are often lacking, especially at high temperatures, and (2) it includes extrapolations in metastable domains.

The performance of the models was evaluated from a nested group cross-validation approach. The predictions generated during this step are found the “Predictions inside the datasets” folder. For Model 2 and Model 3, visual comparisons between the predictions and the CALPHAD assessments are provided.

1563 binary liquidus are predicted from the models (all the two-by-two combinations between the 64 elements missing from the datasets), and the results are found in the “Predictions outside the datasets” folder.
They are obtained from the following procedure. Each model was trained on its whole dataset (expect for Model 3), after hyperparameters were tuned from a 10-fold cross validation. For Model 3, data on the B-Ga system that are unreliable were not taken into account. Besides, Model 3 is not valid in completely miscible systems, and was only used in systems where the probability of having a stable liquid miscibility gap is predicted by Model 1 to be greater or equal to 0.25.
It is emphasized that Model 3 only gives rough estimates, and predictions for elements not included in the training dataset that comprises 32 systems and 29 elements should be taken with caution.
DOI: 10.17632/d9scg7j8fp
title: CAIR-CVD-2025: An Extensive Cardiovascular Disease Risk Assessment Dataset from Bangladesh

description: This dataset comprises 1,529 patient samples collected from Jamalpur Medical College Hospital, Jamalpur, Bangladesh, from January 20, 2024, to January 1, 2025. The data were gathered following ethical guidelines, ensuring patient confidentiality and informed consent. The dataset provides a comprehensive collection of demographic, anthropometric, clinical, biochemical, and lifestyle parameters essential for assessing cardiovascular disease (CVD) risk and overall patient health.

The dataset includes a wide range of variables critical for CVD risk estimation, including basic demographic information, anthropometric measurements, clinical values, biochemical markers, and lifestyle factors. These variables are crucial for identifying risk factors, understanding disease progression, and developing preventive health strategies.


Clinical Parameters Included:

Sex: Male or Female.
Age: Patient’s age (in years).
Weight (kg): Patient’s weight in kilograms.
Height (m): Patient’s height in meters.
BMI: Body Mass Index, calculated from weight and height.
Abdominal Circumference (cm): Measurement of abdominal girth.
BP: Blood pressure readings.
Total Cholesterol: Total cholesterol levels in the blood.
HDL: High-density lipoprotein levels.
Fasting Blood Sugar: Blood glucose levels after fasting.
Smoking Status: Indicates whether the patient is a smoker.
Diabetes Status: Indicates whether the patient has diabetes.
Physical Activity Level: Level of physical activity.
Family History of CVD: Indicates if there is a family history of cardiovascular diseases.
CVD Risk Level: Classification of the patient’s CVD risk level.
Height (cm): Patient’s height in centimeters.
Waist-to-Height Ratio: Ratio of waist circumference to height.
Systolic BP: Systolic blood pressure.
Diastolic BP: Diastolic blood pressure.
Blood Pressure Category: Classification of blood pressure levels.
Estimated LDL: Estimated low-density lipoprotein levels.
CVD Risk Score: Numerical score representing the patient’s CVD risk.


Dataset Structure
Format: CSV
Rows: 1,529 (individual patient records)
Columns: 22 (including demographic, clinical, and lifestyle characteristics)

N.B. The data collection process was supported by the Cognitive AI & Informatics Research Lab (CAIR Lab), ensuring rigorous quality assessment and validation of the dataset.
DOI: 10.6084/m9.figshare.19134287.v1
title: NDPI-Sample-1-Stack-6 (WSI)

description: Dicomized distinct proprietary files of microscope imaging modalities
DOI: 10.17632/c2hb33kg46
title: SD-3000

description: The purpose of the dataset selection was to train a YOLO-based machine learning model for shadow detection. In surveillance systems, where accurate and timely shadow identification is crucial to enhancing security standards, this approach finds extensive application. The focus of the collection is on several shadow classes, including human, dog, cow, and gun shadows, which makes it flexible enough to be used in a range of surveillance scenarios.

• Human Shadow: The SD-3000 Dataset consists of 956 images associated with human shadows. Among these, 669 images are allocated for training, 143 for testing, and another 143 for validation. 

• Dog Shadow: For the dog shadow class, there are 877 images in total. Out of these, 614 are designated for training, 132 for testing, and an additional 132 for validation. 

• Cow Shadow: The cow shadow class is represented by 357 images in the dataset. Among these, 250 images are earmarked for training, 54 for testing, and an identical 54 for validation. 

• Gun Shadow: The gun shadow class contributes 810 images to the dataset. Of these, 567 are utilized for training, 122 for testing, and an equivalent 122 for validation.
DOI: 10.17632/4bzvjwzxs2
title: Impact of Basic Life Support Training on Nurses’ Knowledge and Practice

description: Introduction:
Sudden cardiac arrest (SCA) remains a significant cause of in-hospital mortality and morbidity in Ghana, with increasing incidence in the Assin Foso Municipality. Although nurses are continuously present at patients' bedsides, their ability to recognize and manage cardiac arrest using basic life support (BLS) is under scrutiny. This study aimed to evaluate the impact of a structured BLS training program on nurses' knowledge and practical application of BLS at St. Francis Xavier Hospital.
Methods:
A one-group pretest-posttest quasi-experimental design was adopted. Using a simple random sampling technique (lottery method), 101 nurses were selected. A seven-point Likert scale questionnaire based on the American Heart Association (AHA) 2020 guidelines assessed BLS knowledge, while practical skills were evaluated using the BLS task checklist from the Nursing and Midwifery Council of Ghana. Data were analyzed using paired sample t-tests and linear regression.
Results:
There was a significant improvement in BLS knowledge after training (p &lt; 0.001, Cohen’s d = 1.38; 95% CI: 1.105–1.651) and in BLS practice (p &lt; 0.001, Cohen’s d = 14.44; 95% CI: 12.40–16.42). Pre-training knowledge strongly predicted post-training knowledge (R² = 0.50), while pre-training practice moderately predicted post-training practice (R² = 0.12). Knowledge was not a predictor of practice at baseline but significantly influenced practice post-intervention (R² = 0.16).
Conclusion:
In-service BLS training significantly enhances both the knowledge and practical skills of nurses. Routine implementation of such programs may help reduce in-hospital mortality related to sudden cardiac arrest by strengthening frontline emergency response capacity.
DOI: 10.17632/p66kb9cdh8
title: Dataset of Production-Oriented Operational Activities with Fuzzy MCDM Methods

description: It is very important to determine which activities have the most impact and are more critical in the preparation of improvement studies related to environmental activities and the effective use of resources allocated for improvement. The importance scores of the activities can also be determined by MCDM methods. Operational activities affecting the environment were analyzed with F-ARAS, F-MOORA Ratio and F-MOORA Reference Point methods, and the data used and the results obtained are shared.   The data belong to the examinations made in the material stock field of an enterprise in the automotive sector in Turkey.
DOI: 10.17632/xn73ym9348
title: 5α-reductase inhibitor exposure for dermatologic conditions does not increase the risk of female breast or gynecologic cancers: A population-based propensity score-matched cohort study. JAAD. 2024.

description: Supplemental methods and results.
DOI: 10.17632/5v2fsf2cy7
title: Data for: Evaluation of the Beckman Coulter DxC 700 AU Chemistry Analyzer

description: The supplemental data is related to the article entitled “Evaluation of the Beckman Coulter DxC 700 AU Chemistry Analyzer”. The data provides one lab’s performance with the new Beckman Coulter DxC AU 700 compared to an older Siemen’s Vista 500. Performance characteristics included intra and inter-run precision, linearity/analytical measurement range, method correlation, reference range verification and calculated sigma values. A total of 53 assays including 11 critical care, 19 general chemistries, 11 proteins, 10 urines, and 2 CSF analytes were tested. Herein is a summary of the data for all analytes tested.
DOI: 10.17632/7m6dg8wzt3
title: Data for: Visible Photocatalytic Degradation of Methylene Blue on Magnetic SrFe12O19»

description: research data in origin opj format
DOI: 10.6084/m9.figshare.28375529.v1
title: NP_Fig2

description: Recovery of NDVI and NDII
DOI: 10.17632/3mfp77gdxk
title: Moral Injury_MH symptoms_dataset_results

description: 
The study aimed to extend our understanding of moral injury and associated mental health symptoms in civilian and combat population during the current war atrocities in Ukraine. The following set of research questions were formulated: 
(RQ1) Are there significant differences in moral injury, PTSD, depression and anxiety symptoms between active-duty soldiers and civilian groups?
(RQ2) Are there gender effects in the two groups (active-soldiers and civilians) in relation to moral injury and associated mental health symptoms? 
(RQ3) Is a family history of genocide associated with moral injury, PTSD, depression and anxiety?_ 
(RQ4) Is moral injury a predictor of PTSD in both groups?
DOI: 10.17632/ycxhvwhhp2
title: Tax haven

description: This data set is created for the paper: Capital round-tripping: Determinants of emerging market firm investments into offshore financial centers and their ethical implications
The replication data contains stata files and replication codes to run estimations reported in Tables 2-7 in this paper.
DOI: 10.6084/m9.figshare.22341265.v2
title: Using temperature to analyze the neural basis of a time-based decision

description: Raw data supporting the main findings of Monteiro, Rodrigues, Pexirra et al. 2023 (readme files included).
DOI: 10.17632/zcz8743fcv
title: Multiplexed Images of Melanoma Lymph Node Metastases

description: MIBI data containing 0.8x0.8mm2 multiplexed images from lymph nodes of multiple patients with melanoma metastases.
The data includes the clean images of multiple proteins, cell segmentation and cell classification.
The data is saved in CellSighter input format and was used to train and evaluate CellSighter on the task of cell classification. Further information can be found in our paper "CellSighter: A neural network to classify cells in highly multiplexed images".
DOI: 10.17632/35xtyptswp
title: The temporal evolution of light scattered by evaporating microdroplets of SiO2 nanoparticles suspension in DMSO.

description: The dataset comprises the results of measuring the temporal evolution of light intensity scattered by evaporating microdroplets of a SiO2 nanoparticle suspension with a diameter of 450 nm in DMSO. SiO2 concentration was ~2 wt%. These microdroplets were levitated in a quadrupole trap and illuminated by counter-propagating laser beams: a red (658 nm) vertically polarized (V) beam and a green (532 nm) horizontally polarized (H) beam, both with respect to the scattering plane. A comprehensive description of the experimental geometry is available in (M. Kolwas et al., Phys. Chem. Chem. Phys., 2015, 17, 6881--6888).

The *.csv file includes the following data:

Column 1: Time
Column 2: Intensity of scattered light integrated over the field of view, with the laser and detection channel both vertically polarized (V)
Column 3: Intensity of scattered light integrated over the field of view, with the laser vertically polarized (V) and the detection channel horizontally polarized (H) in cross-polarization
Column 4: Intensity of scattered light integrated over the field of view, with the laser and detection channel both horizontally polarized (H)
Column 5: Intensity of scattered light integrated over the field of view, with the laser horizontally polarized (H) and the detection channel vertically polarized (V) in cross-polarization
Column 6: DC voltage applied to the upper and lower electrodes of the electrodynamic balance required to counteract the gravitational force
Column 7: Operating frequency of the trapping AC electric field
Column 8: Time evolution of the radius of the evaporating droplet obtained using the library method described in (D. Jakubczyk et al., JQSRT 126 (2013) 99–104).
The *.avi files serve as examples of experimental measurements.
DOI: 10.17632/6wtd85p9h2
title: Digital Literacy Research Dataset (1997-2019)

description: The digital literacy research and publication dataset, which was indexed by Scopus from 1997 to 2019. The dataset contains data authors, authors ID Scopus, title, year, source title, volume, issue, article number in Scopus, DOI, link, affiliation, abstract, index keywords, references, Correspondence Address, editors, publisher, conference name, conference date, conference code, ISSN, language, document type, access type, and EID.
DOI: 10.17632/8kcy8thb59
title: Dataset_Effect of the U.S. quantitative easing policy on institutional investor flows of an emerging country
DOI: 10.6084/m9.figshare.19228050.v1
title: Sonobe et al.: The raw t-value maps of the searchlight analysis

description: The raw t-value maps of the searchlight analysis: 1) Cross-classification between visuotactile and visuomotor trials. 2) Within-classification of visuotactile trials. 3) Within-classification of visuomotor trials.
DOI: 10.17632/83kpndkrb2
title: Aerial images (UAV) of burned and unburned olive trees

description: Dataset includes 3624 images of burned and unburned olive trees. These images are subsets of UAV images acquired by (a) Phantom-4 PRO RTK, (b) Phantom-4 Multispectral RTK (RGB sensor), and (c) Lidar L1 (using the optical spectrum sensor) mounted on a MATRICE 300 RTK (DJI. The aforementioned flights were conducted at various altitudes, resulting in data with different Ground Sampling Distances (GSDs). The burned trees were identified by visual interpretation of UAV images and field trips in two states: either partially burned, where part of the canopy was damaged while the remaining portion stayed healthy (green foliage), or fully damaged, where the entire canopy was affected.
DOI: 10.6084/m9.figshare.15046566.v1
title: 2021 Roberson lab SSc list of read group samples

description: Data relevant to a 2021 study of SSc transcriptomes. This file contains a list of the read group sample names.<br>
DOI: 10.6084/m9.figshare.22590028.v2
title: <b>Global Climate Change Mitigation Policy Database</b>

description: GCCMPD covers a large range of policies amount to 73,625 policies of 216 entities. With expert knowledge-based dictionary mapping, probability statistics methods, and advanced natural language processing technology, GCCMD delivers comprehensive and consistent information of sectoral policy instruments regarding their objectives, target sectors, instruments, legal compulsion, administrative entities and so on.
DOI: 10.17632/fpfjcbgsb2
title: Mar3450 integrated data

description: Mar3450 data integrated to 1D diffraction patterns for the welds with 0, 0.5 and 1 mm laser beam offset to Ti plate
DOI: 10.17632/g6mmxc4pnb
title: Spring locations and descriptions in the Hikurangi Forearc (compiled by A. G. Reyes)

description: Spring locations and descriptions in the Hikurangi margin forearc compiled from the literature since 1877 and from fieldwork by A G Reyes since 1992
DOI: 10.17632/w4yg48s6jk
title: Tax policy and the heterogeneous costs of homeownership

description: Replication package for "Tax policy and the heterogeneous costs of homeownership", Journal of Urban Economics
DOI: 10.6084/m9.figshare.28513610.v1
title: Supplementary Material for: Pediatric Auricular Angiosarcoma: a Rare Case Report and Review of the Literature

description: Introduction: Limited evidence exists regarding the clinical characteristics of auricular angiosarcoma in the pediatric population. To our knowledge, this represents the inaugural case report of auricular angiosarcoma in early childhood. This report aims to delineate the unique clinical features and findings associated with pediatric auricular angiosarcoma. Case Presentation: We report a 7-year-old girl presented with a 2-years history of an enlarging, intermittently painful purplish-red mass in the left ear canal and undergo surgery with adjuvant chemotherapy. Conclusion: Although a rarity, auricular angiosarcoma can manifest in pediatric patients, necessitating vigilant consideration for diagnosis in this population. The evaluation and management of auricular angiosarcoma in pediatric cases demands heightened caution due to the patients' young age and the high risk of recurrence and metastases following primary treatments.
DOI: 10.17632/c9ddyxn75h
title: Financial inclusion effects of engagement with the fintech ecosystem

description: Financial inclusion data originally obtained from FinAcess Kenya Household Survey and, in some cases, used to develop new constructs.
DOI: 10.17632/mdwx8y545m
title: Student Affairs Assessment Leaders Nominal Group Technique Panels

description: Data were collected over a series of three modified nominal group technique (mNGT) panels.  Participants were current student affairs assessment leaders (SAAL) members and were practicing assessment at their respective places of employment--each was considered as "assessment expert".  Data were collected to inform the Board of Directors of SAAL. Results are being used for altering strategic plan of the organization.  A quantitative questionnaire will be developed using themes from this data also.  Data were collected under two separate university IRB approvals: Lamar University and West Texas A&M University, as the principal investigator changed jobs during this project.
DOI: 10.17632/5rptvch5z2
title: Customer segmentation

description: Customer segmentation refers to the mobility of the Swiss resident population in the submarkets (1) leisure travel for everyday purposes, (2) day trips with private purposes and (3) trips with overnight stays with private purposes. There is a focus on trips and travel by rail. This study categorises trips connected to a multi-local lifestyle – where people regularly visit, for example, vacation homes or apartments, relatives or friends, or partners living in a different location – as leisure traffic or travel in this study because they occur for private, non-commercial reasons and can involve considerable annual traffic. Trips for business purposes have been excluded because they feature different work-related reasons and require separate customer segmentation.
DOI: 10.17632/ffyn828yf4
title: GastroEndoNet: Comprehensive Endoscopy Image Dataset for GERD and Polyp Detection

description: This dataset contains a total of 24, 036 (primary 4,006 images with 6 augmented techniques) high-quality gastrointestinal endoscopy images categorized into four distinct classes: GERD, GERD Normal, Polyp, and Polyp Normal. The dataset is curated to aid research and advancements in medical image analysis, focusing on the automatic detection and classification of Gastroesophageal Reflux Disease (GERD) and gastrointestinal polyps, both critical conditions in gastroenterology.

- GERD: 974 * 6 = 5,844 images of patients diagnosed with GERD through endoscopic evaluation, depicting various manifestations of reflux damage in the esophagus.
- GERD Normal: 1,103 * 6 = 6,618 images of healthy gastrointestinal tracts without GERD, serving as control cases for the GERD category.
- Polyp: 779 * 6 = 4,674 images featuring gastrointestinal polyps, including various types and stages, aimed at supporting early detection of potentially precancerous conditions.
- Polyp Normal: 1,150 * 6 = 6,900 images representing normal gastrointestinal conditions with no polyps, included to provide a comparison for effective polyp detection.

This comprehensive dataset is ideal for developing and testing machine learning algorithms for diagnosis, classification, and detection of GERD and polyps, ultimately contributing to improved AI-driven healthcare solutions in the field of gastroenterology.

Note: Version 2 removed the duplicate images.
DOI: 10.17632/ytwf92vx7t
title: The dataset for validation of predictors of an online gamified professional development programme adoption for academic staffs

description: This dataset consists of the predictors of an online gamified professional development programme adoption for academic staffs. The data includes 32 responses from academic staffs in Malaysia. The content validation processes through Content Validity Ratio (CVR) and Content Validity Index (CVI) were applied. The data was assessed via the internal consistency reliability, convergent validity and discriminant validity.
DOI: 10.17632/538krtt5hy
title: Data for: Reliability and applicability of the revised Cochrane risk-of-bias tool for randomised trials (RoB 2): low inter-rater reliability and challenges in application

description: database underlying the findings of the study "Reliability and applicability of the revised Cochrane risk-of-bias tool for randomised trials (RoB 2): low inter-rater reliability and challenges in application" submitte to the Journal of Clinical Epidemiology
DOI: 10.17632/fy6hxrgw9t
title: Nutrient footprint versus EPA+DHA security in land-locked regions – more of local pond farmed, imported marine fish or fish oil capsules?

description: Containing the data and calculations presented in the article (from Figures 1 to 6; Experiments 1 and 2). Other data from literature sources or experimental conditions data are already part of the materials and methods text.