cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.4214532.v5
title: CDEMRIS fibrosis scar challenge dataset

description: The DatasetThe dataset includes Late Gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging used to visualise regions of fibrosis and scarring in the left atrium (LA) myocardium. <br>This can be important for treatment stratification of patients with atrial fibrillation (AF) and for assessment of treatment after radio frequency catheter ablation (RFCA). The datasets included are from a segmentation challenge where the aim was to create a benchmarking framework for algorithms classifying fibrosis and scar from LGE CMR images. <br>Dataset contentsThe dataset includes two subsets called <b>pre</b> and <b>post</b>. These refer to the time-points when the images were acquired. The <b>pre </b>data contains pre-ablation imaging of fibrosis. The 'post' data contains the post-ablation imaging data. There are 30 datasets in each <b>pre </b>and <b>post</b> folders. <br>The folders are arranged as pXX, where XX is the case number. Within each folder you will find two images in NRRD format. <br>These images follow a naming convention: de_xx_nnla_seg_xx_nnThe 'xx' can be 'a' or 'b'. The 'a' refers to the pre-scan and the 'b' refers to the post-scan. The 'nn' refers to the case number<br>Note the de_xx_nn refers to the delayed-enhancement (DE) scan. And the la_seg_xx_nn refers to the binary segmentation of the left atrial endocardium. The segmentation is registered to the delayed-enhancement scan. The images will generally be of varying quality. <br>ReferencesKarim et. al. <i>Evaluation of current algorithms for segmentation of scar tissue from late Gadolinium enhancement cardiovascular magnetic resonance of the left atrium</i> in <b>Journal of Cardiovascular Magnetic Resonance</b>, 15(105), 2013. Link<br>
DOI: 10.17632/6s8z9cyh78
title: Programmable cell aggregation by a synthetic biosilicification approach

description: The source data for the paper "Programmable cell aggregation by a synthetic biosilicification approach".
DOI: 10.17632/8g68gfvfjy
title: Medication History

description: Background: An accurate medication history is crucial for maintaining continuity of care. There are numerous opportunities for discrepancies to occur, such as medication omissions, commissions, incorrect dosing, incorrect frequencies, or incorrect formulations. Medication discrepancies may prolong hospital length of stay, increase the number of future emergency department (ED) visits, and increase hospital readmissions. Numerous studies have established the advantages of utilizing pharmacy technicians to complete medication histories. This study aimed to compare the accuracy of obtaining medication histories through pharmacy technicians compared to nursing staff. Objective: To compare the accuracy of obtaining medication histories through pharmacy technicians compared to nursing staff in the emergency department. Methods: This was a single-center, retrospective, observational analysis of patients presenting to the ED between December 2018 through January 2019. A pharmacy technician received on-site training on how to properly obtain a medication history and performed medication histories on the days the pharmacy resident was present between 10:00 and 18:00. Medication histories were obtained by nurses on the days the pharmacy technician was not present. All study medication histories were reviewed for discrepancies by the pharmacy resident. Results: Medication histories conducted by a pharmacy technician (n=102) resulted in a greater number of accurate medication histories [96 (94.1%) versus 59 (57.8%); p &lt; 0.01] when compared to those conducted by nurses (n=102). A total of seven discrepancies were found in the pharmacy technician group compared to 131 in the nursing group (p &lt; 0.01). There was also a statistically significant lower amount of high impact discrepancies in the pharmacy technician group compared to nursing (1 versus 15; p &lt; 0.01). Conclusions: Pharmacy technicians in the ED provided more accurate medication histories when compared to nursing staff, thereby reducing potential medication errors.
DOI: 10.17632/ssdf8grtpf
title: Pollen dataset from Cedar Keys, Florida, USA

description: This dataset contains the raw pollen counts of the 58 samples from cores CK-2 and SNK-2. The sampled core was taken from Cedar Keys, Florida, USA. For each sample, approximately 1 ml of sediment was used for pollen analysis. One tablet of Lycopodium spores containing 20,848 grains was added to each sample as an exotic marker to aid the calculation of pollen concentration (grains/cm3) following the formula: Pollen concentration = Pc ∗ La / Lc ∗ V. Where Pc is the number of fossil pollen counted, La is the number of Lycopodium spores added (20,848), Lc is the number of Lycopodium spores counted, and V is the volume of the sample. Approximately 300 grains of pollen and spores were counted for each sample by using an Olympus Light Microscope with a LC35 camera (3.5-megapixel CMOS sensor) in conjunction with ZEN Blue 2012 imaging software to photograph pollen grains under 1000x magnification. Cluster analysis dendrograms and pollen diagrams were plotted by using TILIA (v.1.7.16).
DOI: 10.17632/xzy9mh2z65
title: Medicinal Plant Leaf Dataset with name table(mostly found in Paschim Maharashtra.)

description: Digitizing a medicinal plant leaf dataset enhances its utility, accessibility, and potential for research and innovation in the fields of botany, pharmacology, and natural medicine. Digital datasets enable advanced data analysis techniques, such as machine learning algorithms, statistical analysis, and data mining. Researchers can uncover patterns, correlations, and trends within the dataset, leading to new insights and discoveries.
With advancements in technology and analytical techniques, future generations can leverage this dataset to identify potential drug candidates from natural sources. By studying the chemical composition and biological activity of medicinal leaves, they can develop new pharmaceuticals with improved efficacy and fewer side effects.
dataset consists of 45 classes of plant species found in Paschim Maharashtra, totaling around 8000 images. These images were captured using a Redmi K50 with a 64 MP camera. The dataset was likely compiled through a combination of methods, including manual collection and web scraping. Each plant species is associated with its common name and medicinal significance. This dataset serves as a valuable resource for researchers and enthusiasts interested in studying the medicinal properties of various plant species native to the region.
Accurate classification of medicinal leaves helps in identifying plants with therapeutic properties. This is crucial for Ayush practitioners who rely on specific plants for preparing herbal medicines and remedies.
The dataset can be used to train machine learning models for image classification tasks. By feeding the model with labeled images of medicinal plants, it can learn to classify new images into one of the predefined classes. This can aid in automated identification of plant species, which is useful for botanists, pharmacologists, and herbalists.
DOI: 10.17632/fcsjwd9gr6
title: Forest Fire Dataset

description: The "Forest Fire Dataset" is a comprehensive and meticulously curated resource, specifically designed to support the development of algorithms for forest fire detection and object detection tasks. The dataset consists of 2,974 images dedicated to fire classification, which are divided into two primary categories: the first category includes images documenting active forest fires, while the second category contains images of intact, fire-free forest environments. This clear distinction within the dataset is crucial for training models to accurately differentiate between fire-affected and unaffected areas in forested regions. In addition to the fire classification data, the dataset includes 1,690 images dedicated to object detection, enhancing its applicability in machine learning and computer vision research.

The dataset is carefully structured with a thoughtful distribution across training, validation, and test sets, with proportions of 80%, 15%, and 5%, respectively, to ensure that models trained on this data can generalize effectively to new, unseen data. The data were collected from various online sources and underwent rigorous manual filtering to maintain high data integrity. Additionally, a portion of the dataset was generated through controlled simulations of forest fires, conducted after obtaining the necessary approvals from relevant authorities. This simulated portion adds diversity and reliability to the dataset, providing a more comprehensive training ground for algorithms.

By integrating both real-world and simulated scenarios, the "Forest Fire Dataset" offers a robust foundation for developing advanced fire detection systems, significantly contributing to forest conservation and disaster management efforts.

For scientific research and advanced applications in the fields of forest fire detection and computer vision, the "Forest Fire Dataset" is a valuable tool. Researchers and practitioners are encouraged to refer to the published article that details the development of the system based on this dataset. To cite the article related to this dataset, the following citation can be used:
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I. Shamta and B. E. Demir, “Development of a deep learning-based surveillance system for forest fire detection and monitoring using UAV,” ِ Artica: PLoS One, vol. 19, no. 3, p. e0299058, 2024.
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Link to Article: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0299058
ORCID: https://orcid.org/my-orcid?orcid=0009-0003-1280-679X
Google Academik: https://scholar.google.com/citations?user=xP6CvtQAAAAJ&hl=tr
DOI: 10.17632/jzvddk26cy
title: Jas4pp — A data-analysis framework for physics and detector studies

description: This paper describes the Jas4pp framework for exploring physics cases and for detector-performance studies of future particle collision experiments. Jas4pp is a multi-platform Java program for numeric calculations, scientific visualization in 2D and 3D, storing data in various file formats and displaying collision events and detector geometries. It also includes complex data-analysis algorithms for function minimization, regression analysis, event reconstruction (such as jet reconstruction), limit settings and other libraries widely used in particle physics. The framework can be used with several scripting languages, such as Python/Jython, Groovy and JShell. Several benchmark tests discussed in the paper illustrate significant improvements in the performance of the Groovy and JShell scripting languages compared to the standard Python implementation in C. The improvements for numeric computations in Java are attributed to recent enhancements in the Java Virtual Machine.
DOI: 10.17632/prrbpsprst
title: A dataset of social network and operational performance of tourism businesses in Vietnam: The mediating role of resource access

description: The outbreak of Covid-19 severely impacted the operational performance of businesses in the tourism industry. Many firms have gone bankrupt and dissolved. Therefore, managers’ social networks are to access external support resources to overcome the crisis, keeping extremely crucial importance. Based on social network theory, this data’s purpose was to shed light on the impact of social networks on operational performance through the mediating role of access to resources. The study used the Partial Least Squares Structural Equation Modeling (PLS-SEM) method with a sample size of 212 managers of tourism businesses in Vietnam. The results showed that Government agency ties and Business partner ties positively and significantly related to operational performance. Additionally, the study’s dataset explored the mediating role of resource access between the social network (Government agency ties and Business partner ties) and operational performance. The results have practical significance for managers in building social networks to increase the ability to access support resources in coping with the crisis of COVID-19
DOI: 10.17632/sb5ybjhxs5
title: TPC288 Diatom Abundance for MIS 5e

description: The downcore combined relative percentage abundance of two diatom species, Fragilariopsis curta and Fragilariopsis cylindrus (F. c+cy), for the period covering MIS 5e in the marine sediment core TPC288. The F. c+cy abundance is related to the seasonal sea ice extent (SSIE) using the thresholds in Gersonde & Zielinski (2000), with values &gt;3% (&gt;1%) indicating a location south of the average (maximum) SSIE. The age model for this core was produced by Pugh et al. (2009). Gersonde R. & Zielinski U. 2000. The reconstruction of late Quaternary Antarctic sea-ice distribution - the use of diatoms as a proxy for sea-ice. Palaeogeography, Palaeoclimatology, Palaeoecology, 162: 263-286. Pugh R.S., McCave I.N., Hillenbrand C-D. & Kuhn G. 2009. Circum-Antarctic age modelling of Quaternary marine cores under the Antarctic Circumpolar Current: Ice-core dust-magnetic correlation. Earth and Planetary Science Letters, 284(1-2): 113-123.
DOI: 10.17632/rfpjy3r4pg
title: The Amazon Urban Weft: Database of SocioSpatial and Nature Dimensions

description: In the Amazon, urbanized areas, beyond cities, constitute a complex urban network involving exchanges of economic and sociocultural capital, mediated by the management of sociobiodiversity. Despite its potential for an open future, this territory is often rendered invisible by the instruments and methods used to apprehend and represent urbanization in the Amazon. This database is a contribution to expanding the understanding of the extensive and complex urban weft in the context of the Pará Amazon. Divided into two dimensions of analysis - sociospatial and nature - the proposed approach is a reinterpretation of the situation classes of the census tract meshes of 2000, 2010, and 2021 (https://www.ibge.gov.br/geociencias/organizacao-do-territorio/malhas-territoriais/26565-malhas-de-setores-censitarios-divisoes-intramunicipais.html). Based on the official definition of the situation classes, it was possible to propose a regrouping to assist in defining an urban gradient, including the urban, as a representation of the process of consolidation of the industrial urban in the territory, and three more intermediate classes, as a formal representation of the multiple narratives and trajectories that describe the peri-urban Amazon, the space bearing possibilities, not yet completely transformed and/or subjected to the logic of capitalist occupation and transformation.

These data, combined with mapping data from PRODES-INPE 2022 (https://terrabrasilis.dpi.inpe.br/downloads/), mediated by the presence and percentage of primary forest and rivers, help to identify territories with more or fewer possibilities for reproducing urbanization processes more adjusted to the reality of the territory. The shapefile of the urban weft adopts 1km² cells as the unit of analysis, simultaneously seeking the classification of the urban gradient, which integrates the definitions of situation classes established by IBGE, with their temporal evolution, in a continuous spatial representation that, although associated with census boundaries (census tracts with nucleated occupation), is independent of their historical differences.
DOI: 10.17632/yjxxv9xbds
title: Lip prints database

description: The database contains lip prints taken from 143 people; 7 lip prints were taken for each person. 
Each lip print is stored in a separate file.
The naming convention of the files is UxLy, where x is the user ID and y is the lip print ID.
DOI: 10.6084/m9.figshare.5902369.v1
title: Country central coordinates

description: This dataset is a .csv file containing central latitude and longitude points for all countries around the globe
DOI: 10.6084/m9.figshare.14265332.v1
title: XFM Data

description: XFM data of Figures 4 and 5 and Supplemental Figures 4, 5, and 6
DOI: 10.17632/nbc2yff7w8
title: TORC1 autonomously controls its spatial partitioning via the Rag GTPase tether Tco89

description: This data set contains: all the unprocessed immunoblots used in this manuscript and their relative replicates used for quantification; unprocessed images of yeast solid medium plates; microscopy pictures used in this manuscript; supplementary tables. Folder name indicates the Figure/Panel number. The Quantifications spreadsheet contains all data points used to create the graphs in the manuscript.
DOI: 10.17632/p3jr4555tf
title: Foggy-Hazy License Plates Images

description: The study of locating and reading license plates from foggy or hazy vehicle images is a relatively emerging field of research. Each passing vehicle can be recorded with the help of the license plate reader's ability to automatically read the characters on the plates. In images where fog or haze is present, license plate recognition and detection are hindered. This dataset contains 1001 foggy- hazy images of vehicles with license plates. The dataset will be a research aid for the researchers and the society for performing license plate detection and recognition of foggy or hazy license plates. Images for this dataset were manually collected using Canon-DSLR-1500D Digital SLR cameras. The dataset includes images taken at various locations in Jaipur, Delhi, and Gurugram. Zip files of both foggy- hazy images, along with their corresponding ground truth images are included in the dataset.
DOI: 10.6084/m9.figshare.6050105.v2
title: British (GB) postcode polygons for area and district levels

description: Postcode area and district polygons derived from Ordnance Survey Open Data using R and GRASS. Method used was creating voronoi polygons from point postcode data and dissolving boundaries based on postcode area and district attributes.<br><br>Contains OS data © Crown Copyright [and database right] (2018)<br><br>File descriptions:<br><b>postcode_polygons.gpkg</b>: geopackage file containing area and district level polygons.<br><b>postcode_aggregator.R</b>: R script to extract area and district from full postcode.<br><b>postcode_aggregator.sh</b>: GRASS/Bash script to convert point postcode data into polygons.<br><b>postcode_overview.png</b>: image of polygons available.<br>
DOI: 10.6084/m9.figshare.1275190.v2
title: Experiment_Materials

description: This file contains the materials of our controlled experiment which contains the follwoing folders: 1- Colleced data and analysis results 2- Instructions for safety analysis tasks 3- pre- and post-experiment questionnaire 4- Template sheets
DOI: 10.17632/57k8ntns4w
title: Undergraduate students' attitudes towards artificial intelligence

description: The data were collected from various universities in Ho Chi Minh City, Vietnam. The sample comprised 460 undergraduate students (196 males and 264 females). Data collection was conducted using a cross-sectional survey design in November and December 2023. The data shows the attitudes toward artificial intelligence of undergraduate students in Vietnam.
DOI: 10.17632/9gcrpt6tpt
title: Technological Pedagogical Content Knowledge (TPACK) Self-Assessment Survey Data Set (January 2006 - March 2020)

description: This dataset was developed to locate a reliable and valid self-assessment of faculty TPACK for a quantitative research study. It was expanded to include additional categories to ease the location of quality instrumentation for other scholars given the large number of articles and instruments available. The initial data were collected by searching the Education Resources Information Center (ERIC), Web of Science, Scopus, and PsycINFO databases using the search terms “technological pedagogical content knowledge,” “TPCK,” and “TPACK.” Searches were limited to articles in peer-reviewed journals that were available in English during the period January 2006 – March 2020. Search results were downloaded combined, and duplicates were eliminated, leaving 552 unique articles. Exclusions: 19 were unavailable, 18 were not in English, 282 did not use a TPACK self-assessment survey, and 8 were excluded for study type (e.g., case study) or respondent type (student). After eliminations, a total of 233 articles were included for analysis and their records are available in this dataset. The initial spreadsheets contained only four fields: author(s), article title, journal title, and publication year. To facilitate the evaluation of TPACK self-assessment instruments, the researcher added 41 additional fields (columns) were included such as whether or not the survey instrument is included in the article, respondent characteristics, factor analytics data, anchors, and sample items, among many others. This data set is made available for researcher use with proper citation.
DOI: 10.17632/g6m6884znc
title: Safety and efficacy of eblasakimab, an IL-13R alpha 1 monoclonal antibody, in adults with moderate-to-severe atopic dermatitis: a phase 1b, multiple-ascending dose study. Supplementary information.

description: This dataset contains figures, tables, and documents referenced in: Safety and efficacy of eblasakimab, an IL-13R alpha 1 monoclonal antibody, in adults with moderate-to-severe atopic dermatitis: a phase 1b, multiple-ascending dose study. (Blauvelt et al.)
DOI: 10.6084/m9.figshare.12552257.v1
title: Whistlers in the Magnetospheric Ducts.

description: The dataset contains executable code and data files for simulations of 2D electron MHD equations describing VLF whistler-mode waves in the magnetospheric ducts. This are supplementary materials for the paper "Observations and Modeling of Whistler-Mode Waves in the Magnetospheric Density Ducts" submitted to JGR in 2020. The dataset includes data files for initiation of the simulations, and the output 2D density and Ex electric field, shown in Figures 4 and 5 in that paper.
DOI: 10.17632/36yhsg4b36
title: Broad and potently neutralizing monoclonal antibodies isolated from human survivors of New World hantavirus infection

description: This is the original source data for figures in manuscript "Broad and potently neutralizing monoclonal antibodies isolated from human survivors of New World hantavirus infection"