cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20209142.v1
title: software defect prediction dataset

description: Class level software defect data of object oriented projects. <br> Link: https://www.openml.org/search?type=data&sort=runs&status=active <br>
DOI: 10.6084/m9.figshare.23896737.v4
title: Flower_visitors.xlsx

description: List of flower visitors of <i>Oberonia japonica</i>.
DOI: 10.6084/m9.figshare.25912954.v1
title: Reproduction Package and Data for Article 'Why the Proof Fails in Different Versions of Theorem Provers: An Empirical Study of Compatibility Issues in Isabelle'

description: <br>This is the artifact accompanying the study of compatibility issues in theorem provers, accepted for presentation at the ACM International Conference on the Foundations of Software Engineering (FSE) 2025. This artifact includes both the collected data and the reproduction package for data preparation and analysis.The source code was developed by the authors of the paper. The data were collected through regression testing of different versions of the Isabelle theorem prover on the Archive of Formal Proofs (AFP), a large repository of formal proof developments. Compatibility issues were identified during this process, and relevant data were extracted and analyzed using the source code.
DOI: 10.6084/m9.figshare.29069285.v1
title: Calculation of the extracted mines volume using DEM obtained from the Envisat radar satellite images (Case study: Gol Gohar Sirjan Mine)

description: <i>The 4th National Geology and Mining Explorations Symposium</i>
DOI: 10.6084/m9.figshare.19107383.v1
title: RBBHs for ASR

description: This file contains all RBBH analyses - and the relevant script - used to identify single-copy orthologues for the ancestral state reconstruction analysis. The orthologues identified here can be found in Supplementary Table S5.
DOI: 10.6084/m9.figshare.26389069.v1
title: BEHSOF: Advanced Non-alcoholic fatty liver dataset with clinical metadata and ultrasound images for Deep learning Models

description: The liver is regarded as one of the essential organs in the body, playing a crucial role in digestion, nutrient absorption, and food processing. This indispensable organ is tasked with cleansing the blood that flows from the digestive tract. Additionally, the liver detoxifies harmful substances and metabolizes various medications. A key function of this organ involves intricate metabolic processes that transform food into energy. However, the liver's heightened sensitivity makes it susceptible to a variety of common ailments, underscoring the need for careful attention to its health. Among liver diseases, fatty liver stands out as the most prevalent, characterized by the buildup of fat within liver cells. This condition is particularly common among individuals who are overweight or have abdominal obesity. Specifically, non-alcoholic fatty liver disease (NAFLD) refers to the excessive fat accumulation in liver cells, a condition known as steatosis. Various diagnostic techniques have been developed for this disease, each offering distinct advantages and drawbacks. Ultrasound imaging has gained popularity due to its accessibility, non-invasive nature, and affordability. One of the approaches utilized in this diagnostic process is the employment of deep learning models. Sporadic studies have been conducted to leverage the available data in diagnosing the degree of non-alcoholic fatty liver disease, and given the significance of the issue, this body of research is continually expanding. Developing robust model training and conducting comprehensive analyses necessitates access to a diverse and comprehensive data repository that can be leveraged for training and validating the proposed models. To this end, we present the BEHSOF dataset, which comprises a collection of samples gathered with varying degrees of non-alcoholic fatty liver disease. Specifically, this data bank consists of ultrasound images from a population of 113 individuals under study, along with the corresponding labels for the levels of steatosis and fibrosis. In addition to the ultrasound images, the data bank provides clinical information, blood test results, and Fibroscan outcomes for the participants, which serve as reference data for fibrosis assessment. Finally, we showcase the results of two deep learning models as examples for training and testing the introduced data set.
DOI: 10.6084/m9.figshare.7609766.v2
title: Dexmedetomidine on emergence delirium and postoperative behavioural changes.xlsx

description: This is a prospective, double-blind, randomized controlled study. The study was aimed to investigate the effects of single-dose dexmedetomidine on emergence delirium in children with sevoflurane anesthesia, and observe postoperative behavior changes through long-term follow-up. <br>
DOI: 10.17632/btf2mz4fhf
title: Data for: PAPILA dataset: a regional emission inventory of reactive gases for South America based on the combination of local and global information

description: PAPILA dataset is a collection of annual emission inventories of reactive gases (CO, NOx, NMVOCs, NH3 and SO2) from anthropogenic sources in South America, for the period 2014–2016. The dataset was developed on the basis of the existing data on the global dataset CAMS-GLOB-ANT v4.1 (developed by joining CEDS trends and EDGARv4.3.2 historical data), enriching it with derived data from locally available emission inventories for Argentina, Chile and Colombia. The inventories are presented as NetCDF4 files, one for each species and year, gridded with a spatial resolution of 0.1° x 0.1° covering the domain 32° W–120° W and 34° N–58° S. Each file contains 12 variables corresponding to the emissions in Tg/y from the following categories, which are organized and denominated using the nomenclature given by CAMS: thermal power plants (ENE); residential and commercial combustion (RES); road transportation (TRO); non-road transportation (TNR); fugitive emissions (FEF); industries (including fuel consumption in manufacturing industries and construction, refineries, industrial processes and solvent and other products use) (IND); agricultural soils (AGS); agriculture livestock (AGL); navigation (SHP); waste (including solid waste, wastewater and incineration) (SWD); and the sum of all sectors (SUM).
DOI: 10.17632/wbwtp3cx9k
title: Data for: Refractive index-assisted UV/Vis spectrophotometry to overcome spectral interference by impurities: applications from impurity analysis to salinity and protein measurements

description: It is a study on matrix effects and a new refractometric method that can help analytical techniques like UV/Vis spectrophotometry deal with matrix effects, specifically, spectral interference. Spectral interference due to matrix impurities is a primary reason that hinders the large-scale application of simple analytical techniques like UV/Vis spectrophotometry in complex samples like those in food, beverage, environmental and other industries. There are lengthy studies on the effects of possible interferents in specific cases. However, current approaches to ensure the absence of huge spectral interference errors are either slow or costly unless all possible impurities are known. We have introduced a simple, cost-effective, and rapid, refractive index-based technique which can assist UV/Vis spectrophotometry for detecting and reducing spectral interference in many of these cases. We verified it in more than ten solvents. We also performed more studies on its application in impurity analysis and its capability in detecting interference errors in the standard UV spectrophotometric methods for protein concentration measurement and salinity determination. We hope that the results would encourage the use of this new technique in certain branches of analytical chemistry. This dataset contains the data which was used for the figures and discussion of the results in the original manuscript. It includes, among others, 1) The UV spectra and refractometric measurements of benzene and N, N-Dimethylaniline in cyclohexane 2) Lorentz Lorenz mixing rule applied to refractometric measurements of benzene in ten different solvents (acetonitrile, n-butanol, cyclohexane, CCl4, p-xylene, toluene, o-xylene, chlorobenzene, N, N-Dimethylaniline and aniline) 3) Qualitative analysis of impurity compounds using Pearson's correlation coefficient, refractometry and UV spectrophotometry 4) The refractometric and UV spectrophotometric standard curves of protein and artificial seawater. Interference effects of DNA, RNA, lysozyme and Triton X-100 on protein (BSA) analysis and nitrates and nitrites on salinity measurement are included in the original paper.
DOI: 10.6084/m9.figshare.12807770.v1
title: Individual differences in intrinsic ankle stiffness and their relationship to body sway and ankle torque

description: Data from study "Individual differences in intrinsic ankle stiffness and their relationship to body sway and ankle torque", performed at the University of Birmingham. <br>Description is given in the file. <br>
DOI: 10.17632/4mxj6rpv48
title: Facial Profile Soft Tissue Annotations for Orthodontic Diagnosis and Classification

description: This dataset consists of 400 annotated facial soft tissue profile images curated for orthodontic research and deep learning model development. The images were annotated using the WebCeph tool, focusing on soft tissue landmarks such as the lips, nose, chin, and jawline. Additionally, the annotations include detailed skeletal and dental measurements, all validated by orthodontic specialists to ensure clinical relevance and precision.

Each CSV file includes comprehensive patient data with the following fields:

patients: Patient identifier (anonymized).
skeletal_status: General skeletal classification.
skeletal_maxilla: Skeletal condition of the maxilla.
skeletal_mandible: Skeletal condition of the mandible.
dental_status: Overall dental status of the patient.
dental_overjet: Measurement of the overjet.
dental_overbite: Measurement of the overbite.
dental_upper_incisor_inclination: Inclination of the upper incisors.
dental_lower_incisor_inclination: Inclination of the lower incisors.
dental_interincisal_angle: Angle between the upper and lower incisors.
dental_upper_incisal_display: Display of the upper incisors.
soft-tissue_upper_lip: Soft tissue condition of the upper lip.
soft-tissue_lower_lip: Soft tissue condition of the lower lip.
The dataset provides five classification categories for the soft tissue profiles: Plane, Concave, Convex, Convex-Concave, and Concave-Convex. This classification assists in understanding soft tissue structure and planning appropriate orthodontic treatments. The CSV files contain detailed annotations for each patient, enabling research into the relationships between skeletal, dental, and soft tissue characteristics.

This dataset is well-suited for developing deep learning models, such as convolutional neural networks (CNNs), to improve the accuracy and efficiency of orthodontic diagnosis and treatment planning.

Key Features:
Images: 400 high-quality profile images of patients’ facial soft tissues.
Annotations: Comprehensive skeletal, dental, and soft tissue annotations provided in CSV format, using the WebCeph tool.
Classes: Five classification categories for soft tissue profiles:

Plane
Concave
Convex
Convex-Concave
Concave-Convex

Format: Images in JPEG/PNG format, annotations in CSV format.
Validation: All annotations validated by orthodontic specialists for clinical accuracy.
Application: Orthodontic research, deep learning model development, AI-based diagnostics.
Use Case: Ideal for training machine learning models for enhanced diagnosis and treatment planning in orthodontics, focusing on the relationships between skeletal, dental, and soft tissue profiles.
Intended Audience:
This dataset is designed for researchers, data scientists, and developers working in orthodontics, artificial intelligence, and medical imaging. It offers a valuable resource for advancing research in AI-powered diagnostic tools and soft tissue analysis in orthodontics.
DOI: 10.17632/bhmgnb77fr
title: IDS Datasets

description: The NSL-KDD dataset is an enhanced version of the widely used KDD’99 dataset, developed to benchmark intrusion detection systems. It addresses several inherent flaws in the original KDD’99, such as redundant records and data imbalance, which could bias machine learning models.
The UNSW-NB15 dataset was developed by the Australian Centre for Cyber Security (ACCS) in 2015 to reflect contemporary real-world network traffic and attack scenarios. It was generated using the IXIA PerfectStorm simulation tool to emulate realistic network traffic over a cyber range, covering both normal behavior and malicious activities.
DOI: 10.6084/m9.figshare.24916206.v1
title: snRNA-seq dataset of aged human muscles and high IMF content pig muscles

description: This file contains the results of subcluster analysis, pseudotime analysis, RNA velocity analysis, and cell‒cell communication analysis in aged human muscles and high IMF content pig muscles.
DOI: 10.6084/m9.figshare.26089242.v1
title: HiGTS_2013s1

description: HiGTS is a high temporal resolution global gridded dataset of human thermal stress metrics. Derived using climate variables from ERA5-Land and ERA5, the HiGTS consists of hourly gridded maps of Universal Thermal Climate Index (UTCI), Universal Thermal Stress (UTS), and daily Thermal Stress Duration (TSD) at 0.1° × 0.1° spatial resolution over the global land surface.HiGTS_2013s1 contains the data from January 1, 2013 to March 31, 2013.
DOI: 10.6084/m9.figshare.3470753.v1
title: Supplementary Material for: Incidence and Outcomes of Acute Kidney Injury Requiring Renal Replacement Therapy: A Retrospective Cohort Study

description: <b><i>Background:</i></b> Incidence of acute kidney injury (AKI), requiring dialysis, is on the rise globally and is associated with high mortality and morbidity. <b><i>Aim:</i></b> This study is aimed at examining the incidence of AKI requiring renal replacement therapy (RRT) in the Tayside region of Scotland and the impact of RRT for AKI on morbidity, mortality and length of hospital stay. <b><i>Methods:</i></b> One hundred seventy eight patients (&gt;18 years of age) who received acute RRT between January 1, 2012 and December 31, 2012 were retrospectively selected for inclusion in the longitudinal cohort study. Incidence rate was calculated. Length of hospital stay, likely cause of AKI, renal recovery and mortality data were collected for a follow-up period of 1 year or until death. Chi-square test was used to compare the morbidity and mortality data between subgroups. RRT-free survival and time-until-event (death or RRT) analysis was performed using Kaplan-Meier plots. Cox-regression was used to examine the relationship between age, sex, diabetes and chronic kidney disease (CKD) on survival. <b><i>Results:</i></b> Incidence of AKI requiring RRT was 430 per million population per year. Median length of hospital stay was 21 days. In-patient mortality was 36%, mortality at 90 days was 44% and at 1 year 54%. Median time from start of RRT until death or chronic RRT was 90 days (95% CI 14-166). One-year cumulative RRT-free survival was 26% in the ward, 36% in high dependency units and 48% in intensive care unit subgroups. Diabetes, gender and CKD at baseline did not affect RRT-free survival in the cohort being studied. A quarter of the cohort regained full renal function and 15% of survivors were on a chronic dialysis programme at 1 year. <b><i>Conclusions:</i></b> This study gives a comprehensive summary of renal outcomes and mortality after a single episode of AKI requiring RRT. The findings of the study confirm that dialysis-dependent AKI is associated with increased length of hospital stay, high mortality and loss of renal function long term, emphasizing the importance of recognition, classification and prevention of AKI.
DOI: 10.6084/m9.figshare.7470086.v1
title: Porcine 50K SNP genetype of American and Canadian Duroc pig populations.zip

description: Porcine 50K SNP genetype of American and Canadian Duroc pig populations.
DOI: 10.17632/4r839t38sb
title: A combination of the frequent fungicides boscalid and dimoxystrobin with the neonicotinoid acetamiprid in field-realistic concentrations does not affect sucrose responsiveness and learning behavior of honeybees

description: The effect of the fungicide Cantus Gold and the neonicotinoid insecticide Mospilan on the mortality, the responsiveness to sucrose and the learning performance of honeybees was tested. Mortality studies were performed for a low and a high concentration to determine two suitable sublethal doses for behavioral experiments. PER (proboscis extension response) tests and olfactory conditioning were conducted to investigate possible negative synergistic effects of the plant protection products. During the PER tests, a series of sucrose concentrations was presented to the bees and the response was noted (1/0). During conditioning, a rewarded (Nonanol) and a punished odor (Eugenol) were used, which were interchanged during reversal learning. Only bees that reacted to the highest concentration of sucrose water and showed no spontaneous reaction for both odors were conditioned. It was noted when the bee showed a conditioned response. There were no treatment effects on the responsiveness to sucrose and the learning performance.
DOI: 10.17632/crxjtgk5bg
title: Brake Wear Particle Emission Factors from Dynamometer Tests

description: This dataset is aimed at enhancing the value of the existing studies to support brake wear particle (BWP) emission model development. It reviews and summaries BWP emission factors (EF) and detailed information of test settings, instruments, and drive cycle parameters from dynamometer tests in the last two decades, with a specific focus on PM10 and PM2.5. The dataset includes three files:
1) Data Dictionary: detailed definitions and explanations of items and the data collection criteria;
2) Summary-BWP EF: BWP EF (PM10 and PM2.5) data and corresponding test settings from 17 selected articles; and
3) Summary-Drive Cycles: detailed braking (stop) profiles and their summarized parameters.
DOI: 10.6084/m9.figshare.19838083.v1
title: Dataset

description: Infectious keratitis is a group of corneal disorders in which corneal tissues suffer inflammation and damage caused by pathogenic infections. Among these, Fungal Keratitis (FK) and Acanthamoeba Keratitis (AK) are some of the most severe, with a high chance of permanent blindness if they are not diagnosed early and accurately. In Vivo Confocal Microscopy (IVCM) allows the imaging of different layers of the cornea, providing an important tool for an early and more accurate diagnosis. In this paper, we introduce the IVCM-Keratitis dataset consisting of a total of 4001 sample images of AK and FK, as well as Non-Specific Keratitis (NSK) and healthy corneas classes. We also use this dataset to develop multiple deep-learning models based on Convolutional Neural Networks (CNNs) for the automated diagnosis of infectious keratitis. Among these models, Densenet161, had the best performance with accuracy, precision, recall, and F1 score of 93.55%, 92.52%, 94.77%, and 96.93%, respectively. These results demonstrate the potential of deep learning-based models in early and automated diagnosis of AK and FK. We further showed that these models can be used to highlight the areas of infection in the IVCM images and explain the reason behind their diagnosis by utilizing saliency maps as a technique used in eXplainable Artificial Intelligence (XAI) to interpret these models.
DOI: 10.6084/m9.figshare.28074941.v4
title: Replication Materials for "The Pivot Penalty in Research"

description: Replication Package for "The Pivot Penalty in Research"By Ryan Hill, Yian Yin, Carolyn Stein, Xizhao Wang, Dashun Wang, and Benjamin F. JonesAbstract:Scientists and inventors set the direction of their work amidst evolving questions, opportunities, and challenges, yet the extent to which research directions are adaptable remains unclear. Theories of creative search highlight the potential benefits of exploration but also emphasize difficulties in moving beyond one’s expertise. Here we introduce a measurement framework to quantify how far researchers move from their existing work and apply it to millions of papers and patents. We find a pervasive “pivot penalty”, where the impact of new research steeply declines the further a researcher moves from their prior work. The pivot penalty applies nearly universally across science and patenting and has been growing in magnitude over the past five decades. Larger pivots further exhibit weak engagement with established mixtures of prior knowledge, lower publication success rates, and less market impact. Unexpected shocks to the research landscape, which may push researchers away from existing areas or pull them into new ones, further demonstrate substantial pivot penalties, including in the context of the COVID-19 pandemic. The pivot penalty generalizes across fields, career stage, productivity, collaboration, and funding contexts, highlighting both the breadth and depth of the adaptive challenge. Overall, the findings point to large and increasing challenges in adapting to new opportunities and threats, with implications for individual researchers, research organizations, science policy, and the capacity of science and society as a whole to confront emergent demands.
DOI: 10.6084/m9.figshare.6989417.v1
title: Python scripts for adding depth stamp to OpenROV videos

description: Python scripts used to generate the depth-stamped videos from ROV video recordings and telemetry logs. mergevideos.py merges the multiple ROV recordings into a single file, depthstamp.py adds depth data from the telemetry logs, splitvideos.py splits into dives, avitomp4 converts back into mp4 format<br>
DOI: 10.17632/nh5fmdcxkd
title: Processed data for modeling - corrosion science

description: This dataset is based on the NIMS CoDS database, and a part of the source data is selected and processed. For specific data processing methods, please refer to the article content.
DOI: 10.6084/m9.figshare.24926325.v2
title: <i>Scurria viridula</i>

description: Genome annotation and assembly files for <i>Scurria viridula</i>. The files contain all scaffolds.
DOI: 10.17632/xwrssjt94b
title: Data for: Does health insurance improve health for all? Heterogeneous effects on children in Ghana

description: This data include the dataset and the replication .do file (STATA) for the replication of the article "Does health insurance improve health for all? Heterogeneous effects on children in Ghana"
DOI: 10.6084/m9.figshare.28039886.v1
title: <b>Mycorrhizal dominance and species richness inconsistently modify tree competition-facilitation balance along climatic gradients</b>

description: The effects of biotic (mycorrhizal dominance and species richness) and abiotic (MAP and MAT) on competition and facilitation among tree species based on the FIA dataset.
DOI: 10.6084/m9.figshare.28531836.v1
title: Supplementary References from The proteotranscriptomic characterization of venom in the white seafan Eunicella singularis elucidates the evolution of Octocorallia arsenal

description: Papers cited in the ESM
DOI: 10.17632/w43kw8nh7g
title: Environmental impact of shell materials in a retail building

description: This study set out to explore the impacts of shell materials in a retail building in Algarve, Portugal. This dataset consists of: i) bills of quantities for all building services, winning contractor’s bid, and energy bills of the store; ii) the worksheet where the weights of building materials were inserted to calculate the total mass of building elements downloaded from LEVEL(S) iii) the weights of building materials estimated based on product technical datasheets and catalogues; iv) the calculation of impacts of building in SimpaPro software, based on Ecoinvent database; and v) the sustainability reports of retailers mentioned in the study.
DOI: 10.6084/m9.figshare.21972953.v1
title: Untitled Item

description: Data