cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/h588hz3pbt
title: HyperPATH study cohort for all variables

description: International Hypertensive Pathotype (HyperPATH) Consortium, HyperPATH study, has been an on-going, multi-site study, aimed at investigating the pathophysiologic and genotypic mechanisms involved in hypertension and cardiovascular diseases. Participants were studied at four collaborating centers: Brigham and Women’s Hospital (Boston, MA), University of Utah Medical Center (Salt Lake City, UT), Vanderbilt University Hospital (Nashville, TN), and Hôpital Européen Georges Pompidou (Paris, France).
DOI: 10.17632/c6pdfrwxgj
title: Landscape and Selection of Vaccine Epitopes in SARS-CoV-2

description: Early in the pandemic, we designed a SARS-CoV-2 peptide vaccine containing epitope regions optimized for concurrent B cell, CD4+ T cell, and CD8+ T cell stimulation. The rationale for this design was to drive both humoral and cellular immunity with high specificity while avoiding undesired effects such as antibody-dependent enhancement (ADE). In this study, we combine computational prediction of T cell epitopes, recently published B cell epitope mapping studies, and epitope accessibility to select candidate peptide vaccines for SARS-CoV-2. We begin with an exploration of the space of possible T cell epitopes in SARS-CoV-2 with interrogation of predicted HLA-I and HLA-II ligands, overlap between predicted ligands, protein source, as well as concurrent human/murine coverage. Beyond MHC affinity, T cell vaccine candidates were further refined by predicted immunogenicity, viral source protein abundance, sequence conservation, coverage of high frequency HLA alleles and co-localization of CD4+ and CD8+ T cell epitopes. B cell epitope regions were chosen from linear epitope mapping studies of convalescent patient serum, followed by filtering to select regions with surface accessibility, high sequence conservation, spatial localization near functional domains of the spike glycoprotein, and avoidance of glycosylation sites. From 58 initial candidates, three B cell epitope regions were identified. By combining these B cell and T cell analyses, as well as a manufacturability heuristic, we propose a set of SARS-CoV-2 vaccine peptides for use in subsequent murine studies. The immunogenicity of the selected peptides was validated using ELISpot and ELISA following murine vaccination. We also curated a dataset of almost a thousand observed T-cell epitopes from convalescent COVID-19 patients across eight studies. Our vaccine selection process appears to be effective at predicting recurrent T-cell epitopes and strong T-cell responses were observed in mice following vaccination. Humoral responses were deficient, likely due to the unrestricted conformational space inhabited by linear vaccine peptides. Overall, we find our selection process and vaccine formulation to be appropriate for identifying T-cell epitopes and eliciting T-cell responses against those epitopes.
DOI: 10.17632/jz7xhmw52b
title: Offshore sediment samples of coastal compartments of western Victoria, Australia

description: This dataset is composed of 138 surficial sediment samples collected within six coastal compartments of western Victoria, Australia.
Unconsolidated substrate areas of the shoreface and inner continental shelf were targeted. 
15 samples were collected in the compartment of Discovery Bay (DB), 17 in Portland (PL), 27 in Port Fairy (PF), 31 in Port Campbell (PC), 37 in Great Ocean Road (GR) and 11 in Torquay (TQ), between October 2018 and November 2020.
Most samples were collected with a Shipek grab (n = 118) and only 20 samples (PF01-PF20) were collected with a Van Veen. The shallowest samples (PF11 and PF11) were retrieved from 4 m depth whereas the deepest sample (PC01) was collected from depths of 55 m.
Grain size and loss on ignition (carbonate and organic matter) analyses were conducted in the laboratory following salt extraction and oven dry at 60 ºC.
Approximately 200 g of sample was dry sieved down to 0 phi at half phi intervals to determine size fractions. Size of material finer than 0 phi was obtained by laser scanning using a Beckman Coulter laser diffraction particle size analyser. Grain size statistics have been calculated using Folk and Ward (1957) formulae. Individual sample results were obtained by running the grain size distribution and statistic software GRADISTAT (Blott and Pye, 2001).
Approximately 4 g of sediment per sample were used for determining carbonate and organic matter content via loss on ignition (Dean, 1974; Heiri et al., 2001). For that, crushed samples were placed in ceramic crucibles and exposed for 1 h at 105 ºC, 2 h at 550 ºC and 2 h at 950 ºC in a muffle furnace.
DOI: 10.6084/m9.figshare.12162531.v1
title: GTT-1-protein-045.dcd

description: Trajectories dataTrajectories of WW domain
DOI: 10.6084/m9.figshare.14798565.v1
title: swallowing acoustics.csv

description: We collected swallowing sounds from 30 healthy subjects ranging in age from 19-60 years old and self-reporting no history of swallowing disorders. Each participant swallowed liquids and foods regarding different consistency or texture with their head-trunk in neutral position.
DOI: 10.17632/gn6mkkdvh4
title: Data set for IFRS adoption and value relevance in SSA

description: Data was derived from the Bloomberg portal and DataStream. IFRS adoption was a dummy variable showing 1 if the company implemented IFRS in that year and 0 otherwise. The other variables are share price 3 months and 6 months after the fiscal year end, earnings (EPS), book value per share, operating cash flow, leverage, firm size (log total assets), and growth opportunity (market to book value). These data are available for South Africa, Nigeria and Kenya.
DOI: 10.17632/v2s5wn252v
title: Dataset for: Growing industrialization and poor conservation planning challenge natural resources’ management in the Amazon shelf off Brazil

description: Araujo et al. (2021), based on an extensive compilation of primary and secondary data, assessed the distribution of benthic habitats and spatial extent of the economic activities in Brazil’s Amazon Shelf. The present dataset was developed to support this manuscript providing geospatial data (vector and raster) in geographic latitude/longitude coordinate system (World Geodetic System; datum: WGS84), that included data about: (1) Bathymetry - main bathymetry isobaths; (2) Biodiversity Fauna - species occurrence records of sea turtles, marine mammals, marine and shore birds, and fishery resources; (3) Biodiversity Megahabitats - distribution of the main benthic megahabitats, mangrove and shoreline types; (4) Fisheries Activities - artisanal and industrial fishing; (5) Human Population - density population; (6) Infrastructure - seaports, waterway, railway, airports and marine traffic; (7) Mining Activities - mining blocks of Pará and Maranhão basins; (8) Oil & Gas Activities - drilling wells, sedimentary Basins and blocks (offered, returned, under concession); (9) Protected Areas - Protected Areas, Coastal and Marine Protected Areas (CMPA) and Priority Areas for Biodiversity Conservation, including Planned CMPA; (10) River Plume - Amazon River plume distribution. Additionally, the dataset includes two excel files, one with information about data sources and processing and another with the biodiversity database.
DOI: 10.17632/v6h5bf52jh
title: Systematic Literature Review Dataset

description: Ecosystem accounting is a systematic approach that combines environmental and economic data to track the full physical and monetary value of natural capital and can be applied at various spatial scales and for a range of purposes.  The main objective of this research is to identify where and how ecosystem accounting has been applied in the specific context of forest resource management. The research questions explore on what geographic and organisational levels System of Economic Ecosystem Accounting (SEEA) Ecosystem Accounting (EA) consistent ecosystem accounts have been compiled and identify gaps and challenges that may exist in the context of forestry. To address the objectives of the research, a systematic literature review was conducted. The uploaded data file contains the information extracted from the total (partially and fully analysed) publications (n=122) and a description of the variables examined in the review of the fully analysed publications (n=9).
DOI: 10.17632/z4hvxjgtbz
title: Double Pendulum Design and Data Repository

description: This repository includes a solidWorks (2019) CAD model of a research quality double pendulum. Additionally, we have provided video data with trackers recorded at 1000 FPS and Encoder data to validate the video data analysis.
DOI: 10.6084/m9.figshare.13468281.v1
title: Additional file 1 of Aligning text mining and machine learning algorithms with best practices for study selection in systematic literature reviews

description: Additional file 1:. Machine Learning Functions. Code used to apply the machine learning algorithms
DOI: 10.17632/5ny7cth7vw
title: Dataset_for_Analyzing_University_Students'_Behaviour

description: The dataset for behavior analysis of university students consists of 351 records and 51 questions, covering a range of factors that shed light on student demographics, academic performance, and social behavior. The mental health of a student can be scaled using this dataset. Key demographic variables include semester, age, height, weight, gender, religion, and family background. Academic performance is assessed through CGPA, daily study hours, and satisfaction with academic activities, while social behaviours include relationship status, social media usage, and smoking habits.

The dataset also explores extracurricular involvement, career outlook, and perceptions of social value related to students' fields of study. Critical mental health indicators such as suicidal thoughts, sleep patterns, and psychological symptoms like anxiety, agitation, and stress are captured. Questions about satisfaction with sleep, daily functioning, and emotional well-being further contribute to understanding students' mental health.

The mental health section is extensive, with multiple questions related to suicidal thoughts and behaviours. The dataset also covers sleep-related behaviors. Additionally, the dataset captures psychological symptoms through questions about difficulty winding down, experiencing breathing problems, lack of positive feelings, and difficulty relaxing. Indicators of anxiety, panic, and agitation, such as trembling, nervous energy, and overreaction to situations, are also recorded. The emotional state of the students is further explored, including feelings of worthlessness, a lack of enthusiasm, and feeling scared or that life is meaningless.

This dataset provides a detailed and comprehensive foundation for behavior analysis of university students, enabling researchers to assess academic, social, and psychological factors that influence student well-being. It is well-suited for applying machine learning models to predict behavioural and mental health outcomes.
DOI: 10.17632/ny2krr3vgg
title: Data for: Clusters of non-adherence to medication in neurological patients

description: Data from 429 patients were collected (consecutive sampling) either during their visit to the outpatient clinic or during their stay on the neurological ward in the Department of Neurology at the Jena University Hospital between January and May 2018. Neurological disorders mainly comprised movement disorders, cerebrovascular disorders, epilepsy, peripheral neurological disorders, inflammatory central nervous disorders. Demographical data include: age, gender, marital status, living situation, level of education, occupation, medical history such as diseases and details of their medication (who takes care of their daily medication and how much medication they take each day). Adherence was assessed using the German Stendal Adherence to Medication Score (SAMS) which is an extension of the validated German Essen Compliance Score to assess adherence (Franke et al. 2009; Jäger et al. 2009; Türk et al. 2009). The SAMS questionnaire includes 18 questions forming a cumulative scale (0 - 72) in which 0 indicates complete adherence and 72 complete non-adherence. It is generally considered that suboptimal adherence becomes clinically significant when &lt;80% of prescribed medication is taken (DiMatteo 2004; Malek, Heath, and Greene 2017; Offord et al. 2013; Karve et al. 2009). This leads to a study- and sample-specific SAMS cut-off of 10 points for a clinical meaningful/significant non-adherence in the current dataset. The patients can then be categorized into i) fully adherent (SAMS = 0), ii) moderate non-adherent (SAMS 1 - 10) and non-adherent (SAMS &gt; 10). References DiMatteo, M. R. 2004. 'Variations in patients' adherence to medical recommendations: a quantitative review of 50 years of research', Med Care,42:200-9. Franke, GH., M. Jagla, J. Reimer, et al. 2009. 'Erfassung von Medikamenten-Compliance bei erfolgreich Nierentransplantierten mit einer erweiterten Version des Morisky-Scores – dem Essener Compliance Score (ECS)', Psychotherapie, Psychosomatik, Medizinische Psychologie. Jäger, S., GH. Franke, J. Reimer, et al. 2009. 'Der Zusammenhang zwischen Medikamenten-Compliance und gesundheitsbezogener Lebensqualität bei Nierentransplantierten.', AK Klinische Psychologie im BDP: Psychische Störungen in der somatischen Rehabilitation:79-93. Karve, S., M. A. Cleves, M. Helm, et al. 2009. 'Good and poor adherence: optimal cut-point for adherence measures using administrative claims data', Curr Med Res Opin,25:2303-10. Malek, N., C. A. Heath, J. Greene. 2017. 'A review of medication adherence in people with epilepsy', Acta Neurol Scand, 135:507-15. Offord, S., J. Lin, B. Wong, et al. 2013. 'Impact of oral antipsychotic medication adherence on healthcare resource utilization among schizophrenia patients with Medicare coverage', Community Ment Health J, 49:625-9. Türk, T., GH. Franke, M. Jagla, et al. 2009. 'Development of the Essen Compliance Score – Measurement of adherence in kidney transplant patients', American Journal of Transplantation, 9.
DOI: 10.17632/chv7dmvtfm
title: Vegetable Recognition Dataset

description: An extensive dataset featuring over 8000 high-resolution images, with a diverse selection of 8 commonly utilized Indian vegetables: potato, tomato, ginger, garlic, chili, brinjal, carrot, and onion. This comprehensive collection encompasses a breadth of environmental conditions, including plain, cluttered, and natural backgrounds, as well as varied lighting scenarios such as bright and low-light conditions . The images offer a range of perspectives, from close-up shots to faraway angles, capturing the vegetables in different conditions. Every image within the dataset is meticulously self-clicked, ensuring authenticity and diversity in location, including markets, fields, and households. Explore this rich resource for robust insights and applications in image recognition, agriculture, and beyond.
DOI: 10.17632/cyyy6mwktp
title: Shellter project database - The Potential Use of Waste from Shellfish Aquaculture in the Production of New Construction Materials

description: The Shellter project was a collaboration between Instituto Superior Técnico, the University of Lisbon, and the Norwegian company Nofima, funded by the EEA Grants Bilateral Relations Fund—the project aimed to evaluate the potential for integrating oyster shells into the production of construction materials.
Two surveys were conducted across two countries: the first in Portugal from April 15 to 21, 2023, and the second in Norway from June 19 to 21, 2024. The data collection in Portugal focused on characterizing the shellfish circuit in Portugal’s Algarve region and exploring the potential use of oyster shells within the country. This survey covered several key dimensions related to bivalve shells, including the availability of waste and the feasibility of its reuse. It also aimed to identify potential stakeholders interested in transforming this waste into new construction materials, potentially leading to innovations in the circular economy.
In Norway, the data collection focused on the construction industry and academia to understand their perceptions of reusing shells in construction. The survey aimed to gauge respondents' views on product reuse and the promotion of circularity, as well as to assess their willingness and intention to engage in a more circular economy.
DOI: 10.17632/kcr4hndftx
title: Video abstract - Disease Characteristics, Comorbidities, Treatment Patterns and Quality of Life Impact in Children <12 Years Old with Atopic Dermatitis: Interim Results from the PEDISTAD Real-World Registry 

description: Author video for the article: 
Paller AS, et al. Disease Characteristics, Comorbidities, Treatment Patterns and Quality of Life Impact in Children <12 Years Old with Atopic Dermatitis: Interim Results from the PEDISTAD Real-World. J Am Acad Dermatol. 2022 Jan 23;S0190-9622(22)00092-5. doi: 10.1016/j.jaad.2022.01.018.
DOI: 10.17632/by2x3v7kdk
title: Comparative Safety Analysis of Anti-IL-4/IL-13 Inhibitors and JAK Inhibitors in Atopic Dermatitis

description: eText 1: ICD-10 Code Lists for Outcomes
DOI: 10.17632/gwhknphkkt
title: Data on Techno-Economic Analysis of MSW Gasification for Electricity Generation

description: This repository contains data used and results obtained from a techno-economic analysis of MSW Gasification for Electricity Generation
DOI: 10.17632/zndtmk8xc6
title: Raw "origscale" 24-h metabolomics intensity data from 8 different murine tissues under chow or high fat diet
DOI: 10.6084/m9.figshare.7973792.v1
title: Tozer et al., (2019) SRTM15+ GPlates project

description: A GPlates project for visualizing on a digital globe the data sets presented in Tozer et al., (2019) SRTM15+.
DOI: 10.17632/7vcnx338dv
title: Internet of Things for Learning Supply Chain Management

description: The study "Internet of Things for Learning Supply Chain Management" aims to introduce the use of the Internet of Things (IoT) in learning supply chain management. This research may utilize the following research methods to validate instruments, media, and learning materials:

1. Research Instruments for Validating Media and Learning Materials:
- Questionnaires: Possible use of questionnaires to measure participants' perceptions and satisfaction with the media and learning materials presented through the IoT platform.
- Observation: Direct observation of participants' interactions with learning media can provide additional insight into its effectiveness.
- Interviews: Interviews with participants to gain a deeper understanding of their experiences using learning media and materials.

2. Learning Media Validation Results:
- Usability Evaluation: Based on questionnaires or observations, research may obtain results regarding the ease of use of IoT learning media.
- Satisfaction Level: Assess the participant's level of satisfaction with the experience of using IoT learning media.

3. Learning Material Validation Results:
- Concept Understanding: Through questionnaires or exams, research can evaluate participants' understanding of learning material delivered via the IoT platform.
- Knowledge Increase: Measures the increase in participants' knowledge before and after using learning materials.

4. Learning Platform Validation Results:
- Platform Performance: Evaluate the technical performance of the IoT platform to ensure adequate availability and reliability.
- Security: Ensure that the platform is safe to use and protects personal data and other sensitive information.
- Availability and Accessibility: Assess the availability of the platform and ease of access for learning participants.
DOI: 10.6084/m9.figshare.3116656.v1
title: Data and code for: Are the discretised lognormal and hooked power law distributions plausible for citation data? Journal of Informetrics

description: Data and R code for: Are the discretised lognormal and hooked power law distributions plausible for citation data? Journal of Informetrics.R code for fitting and testing hooked power law data.R code for simulation and bootstrapping for the hooked power law and discretised lognormal distributions.<br><br>
DOI: 10.17632/5fhsz5fkkx
title: Data for: A SEMANTIC MEASURE OF ONLINE REVIEW HELPFULNESS AND THE IMPORTANCE OF MESSAGE ENTROPY

description: Reviews analyzed in the paper
DOI: 10.17632/h9fmgxy6f4
title: Data for: Identifying the mechanisms that shape fungal community and metacommunity patterns in Yunnan, China.

description: Additional results and data
DOI: 10.17632/bvcwx4tfjm
title: Mental health and well-being of university students during the fourth wave of the COVID-19 pandemic

description: The data include answers of 706 university students from Poland to demographic questions, mental and physical health, and well-being. The cross-sectional online survey was performed during the fourth wave of the COVID-19 pandemic, including measures of Exposure to Coronavirus (8 questions), Spirituality (2 questions), Physical Health (GSRH, 2-item), Perceived Stress (PSS-10), PTSD (Short PCL-6), anxiety (GAD-7), depression (PHQ-9), Life Satisfaction (SWLS), and Fear of COVID-19 (FoCV-19S). Differences between vaccinated and unvaccinated samples were investigated in the study using Pearson's Chi-square independence test, Student's t-test, and Mann-Whitney U-test. Also, network analysis was performed for unvaccinated and vaccinated university students, including selected demographic variables (age, gender, relationship status) and well-being dimensions. Overall, unvaccinated students showed better health and well-being than unvaccinated.
DOI: 10.17632/pt5rvhdh22
title: Dataset of dental periapical X-ray

description: Please see the paper in Data in brief journal
DOI: 10.6084/m9.figshare.22140542.v1
title: Sources of information and research

description: Sources of information and research
DOI: 10.17632/5f676j23m6
title: Data for: B diffusion, related isotope fractionation and the structural role of B in pegmatitic melts

description: We performed an experimental diffusion study investigating the self- and chemical diffusion of B in a pegmatitic melt under high temperature and pressure. The effect of water on the diffusivity was assessed by conducting nominally dry and water-bearing (3.1–3.9 wt % H2O) experiments. The files contain the diffusion profile data obtained by electron microprobe (D1), femtosecond laser ablation sector field ICP-MS (D2) and femtosecond laser ablation multi collector ICP-MS (D3). D4 shows near infrared spectroscopy data for the calibration of linear molar absorption coefficients. D5 gives all data for solid-state nuclear magnetic resonance experiments.
DOI: 10.17632/g97dmjymk5
title: Pig-Feces on Pig Skin Dataset

description: This dataset is used for training object detection models with the YOLOv9 method. The resulting model is used for implementation in pig cleaning robots. This robot is purpose to improve biosecurity on pig farms.
DOI: 10.17632/3dx6pnx869
title: Cloud condensation nuclei and hygroscopic growth measurement at Mace Head from 2009 to 2010

description: This dataset reports the results of in situ measurements of cloud condensation nuclei (CCN) number concentration, aerosol chemical composition, aerosol hygroscopic growth factor, particle number size distribution collected from 2009 to 2010 at Mace Head Research Station(53.33° N, 9.90 °W; 21m a.m.s.l; 300m from the waterline). This dataset is discussed in a manuscript titled "The impact of aerosol size-dependent hygroscopicity and mixing state on the cloud condensation nuclei over the Northeast Atlantic" by "Wei Xu, Kirsten. Fossum, Jurgita Ovadnevaite, Chunshui Lin, Ru-Jin Huang, Colin O’Dowd, Darius Ceburnis" which is submitted to Atmospheric Chemistry and Physics.
DOI: 10.6084/m9.figshare.28468244.v1
title: Differences in Exam Culture between China and the United States

description: Summarize the similarities and differences in standardized testing styles between China and the United States based on the characteristics of standardized exams, such as reliability, question types, scoring, etc