cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/c7fjbxcgj9
title: Endoscopy Artefact Detection (EAD) Dataset (includes updated 2020 version)

description: We aim to establish a first large and comprehensive dataset for "Endoscopy artefact detection". The released data is a part of Endoscopy Artefact Detection IEEE ISBI challenge. With the Endoscopy Artefact Detection Challenge (EAD), we aim to identify hindrances like saturations, motion blur, specular reflections, bubbles, imaging artefacts, contrast and instrument using revolutionary techniques in artificial intelligence. This dataset has been updated with additional class instance (blood) and annotation samples. The provided challenge is important for endoscopy video processing task in obtaining more sensible temporal information. The challenge is sub-divided into three tasks: 1) Multi-class artefact detection: Localization of bounding boxes and class labels for 8 artefact classes for given frames 2) Region segmentation: Precise boundary delineation of detected artefacts for 5 artefact classes 3) Detection generalization: Detection performance independent of specific data type and source (test only) Useful tools for this dataset: https://sharibox.github.io/EAD2019/; https://github.com/sharibox/EndoCV2020 Updated version 2020: We have added an updated dataset of EAD2019 (https://data.mendeley.com/datasets/c7fjbxcgj9/2). Please note that several frames have been included in this dataset. If you use this dataset then please cite the listed works below: 1) Ali, S., Zhou, F., Daul, C., Braden, B., Bailey, A., Realdon, S., East, J., Wagni`eres, G., Loschenov, V., Grisan, E., et al., 2019. Endoscopy artifact detection (EAD 2019) challenge dataset. arXiv preprint arXiv:1905.03209 . 2) Ali, S., Zhou, F., Bailey, A., Braden, B., East, J.E., Lu, X., Rittscher, J., 2021. A deep learning framework for quality assessment and restoration in video endoscopy. Medical Image Analysis 68, 101900. doi:https://doi.org/10.1016/j.media.2020.101900. 3) Ali, S., Zhou, F., Braden, B., Bailey, A., Yang, S., Cheng, G., Zhang, P., Li, X., Kayser, M., Soberanis-Mukul, R.D., et al., 2020. An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy. Scientific reports 10, 1–15. 4) Ali, S., Dmitrieva, M., Ghatwary, N. et al. Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy. Medical Image Analysis, 2021. doi: https://doi.org/10.1016/j.media.2021.102002.
DOI: 10.17632/hfcrnhtmc3
title: Age and latent cytomegalovirus infection do not affect the magnitude of de novo SARS-CoV-2-specific CD8+ T cell responses_van den Dijssel et al.

description: The files in this data repository contain the source data described in the following study:

Title: Age and latent cytomegalovirus infection do not affect the magnitude of de novo SARS-CoV-2-specific CD8+ T cell responses

authors:Jet van den Dijssel, Veronique AL Konijn, Mariël C Duurland, Rivka de Jongh, Lianne Koets, Barbera Veldhuisen, Hilde Raaphorst, Annelies W Turksma, Julian J Freen-van Heeren, Maurice Steenhuis, Theo Rispens, C Ellen van der Schoot, S Marieke van Ham, Rene AW van Lier, Klaas PJM van Gisbergen, Anja ten Brinke and Carolien E van de Sandt
DOI: 10.6084/m9.figshare.12429224.v1
title: wilcox test.xlsx

description: Data base for comparison of Wilcoxon test. The data belong to a group of spider monkeys that solve a task of match-to-sample task. Data was separated in sheets and each one contain the data from different list sample size (3, 4, or 5).
DOI: 10.6084/m9.figshare.12818717.v1
title: Collaborative Cross and Diversity Outbred liver proteomics manuscript

description: This repository contains:1. Starting peptide data, R scripts to process them, and the resulting quantitative protein data2. R scripts to process the genetic data for the Collaborative Cross and Diversity Outbred mice for further analysis (e.g., QTL, mediation, heritability)3. R scripts to run all analyses reported in manuscript4. Results data5. R scripts to reproduce all figures in manuscript
DOI: 10.6084/m9.figshare.20131376.v1
title: Supplementary Material for: Effect of exposure to paternal smoking on overweight and obesity in children: findings from the Children Lifeway Cohort in Shenzhen, southern China

description: Introduction: Paternal smoking associated with childhood overweight and obesity has been a concern, but studies have not investigated smoking exposure and smoking details. We investigated the association of exposures from paternal smoking as well as smoking details on offspring overweight/obesity. Methods: A total of 4513 children (aged 7-8 years) in Shenzhen were enrolled. Four different exposures from paternal smoking as well as smoking quantity, duration of smoking and age of starting smoking details were the exposure variables and demographic characteristics, circumstances of birth, dietary intake, lifestyle and nonpaternal smoking exposure were covariates in logistic regression analysis to determine the effect of paternal smoking on childhood overweight/obesity, estimating odds ratios (ORs) and 95% confidence intervals (CIs). Results: Paternal smoking was positively associated with childhood overweight/obesity (p&lt;0.05). Moreover, only pre-conception exposure, and both pre- and post-conception exposure were significantly associated with childhood overweight/obesity (OR 1.54 (95% CI 1.14-2.08) and OR 1.73 (95% CI 1.14-2.61) respectively), restricted to boys but not girls. Furthermore, for children with only pre-conception paternal-smoking exposure, the dose–response relation was positive between smoking quantity, duration of smoking, age at starting and overweight/obesity for boy offspring (P trend &lt;0.001). We did not find any significant association between only post-natal exposure to paternal smoking and childhood overweight/obesity (P&gt;0.05). Conclusions: Our findings suggest that paternal smoking is associated with boys’ overweight/obesity, and this association may due to the paternal smoking exposure before conception rather than the post-natal exposure to paternal smoking. Reducing paternal smoking exposure before conception might help reduce overweight/obesity in boys.
DOI: 10.6084/m9.figshare.21299751.v1
title: Transcript interview

description: dataset
DOI: 10.6084/m9.figshare.8988008.v1
title: A rare retrobulbar and chiasmal meningioma in a dog

description: ABSTRACT: A 14-year-old female Dachshund was referred to a veterinary hospital with a history and signalment of head pressing, compulsive walking, and right circling. At ophthalmologic examination, a mature cataract and absence of photomotor reflex in the right eye were observed. The neurological exam revealed multifocal encephalic signs. At necropsy, a conical solid tan mass was observed involving the right optic nerve throughout its extension to the optic chiasm. Histopathological findings confirmed a retrobulbar papillary meningioma, considered rare and seldom included as differential diagnosis in patients with neurological signs.
DOI: 10.6084/m9.figshare.25903504.v1
title: TISHIP IN NIGERIA

description: This data is on the Tertiary Institution Social Health Insurance Program (TISHIP) collected in two tertiary institutions of a Metropolis in South-Western Nigeria.
DOI: 10.6084/m9.figshare.25987963.v1
title: Data for the Study of "Identification of Land Use Mix Using Point-Based Geospatial Data in Urban Areas"

description: Data and code used to support the research article entitled "Identification of Land Use Mix Using Point-Based Geospatial Data in Urban Areas".<b>Instructions on how to use the data and codes.</b>Codes are divided into R and Python scripts. Python scripts are essential for acquiring cadastral data, which could not be included within the dataset as they are too big to share. R scripts provide critical analysis and algorithms. You need to install Python and R to run them on your own.The dataset consists of POI and fishnet data. You need to alter the path variables within the code to use them.<br>
DOI: 10.17632/rvrt4zs969
title: Healthy and Loser Salmon Dataset

description: The "Healthy and Loser Salmon Dataset" contains images of farmed Atlantic salmon in sea cages, and corresponding annotations. For the detailed description of the dataset, the user is referred to the published open-access article "Identifying losers: Automatic identification of growth-stunted salmon in aquaculture using computer vision", which can be downloaded at https://doi.org/10.1016/j.mlwa.2024.100562.

The dataset contains a total of 207 images and their respective annotations files ("json" and "yolo" formats) for the bounding boxes of the 2 classes to be detected (healthy and loser salmon).
These 207 images present a total of 1750 instances of fish (1319 healthy and 431 loser).

The dataset is divided into three independent collections: training, validation and test sets. 
The training set comprises 145 images, 888 instances of healthy fish and 306 loser salmons; 
while the validation set presents 41 images, 260 instances of healthy fish and 86 of loser salmons;
and the test set has 21 images, 171 healthy fish instances and 39 loser instances.

The directories are organized as follows:

healthy_loser_salmon_dataset
 json
 test
 train
 valid
 yolo
 data.yaml
 images
 test
 train
 valid
 labels
 test
 train
 valid
 
The "json" directory presents three folders: "test", "train" and "valid". Each one of these directories presents the images (jpg) that belong to the respective set and their following json files (created using the "LabelMe" software) with the annotation of the bounding boxes.

The "yolo" directory has the classic structure used by Yolo, with a "data.yaml" file defining each set, number of classes and name of each class; the "image" folder that contains the images (png) of each set and is divided as test, train and valid, referring to each set; and finally, the directory "label", that presents the txt files of each location of the bounding boxes on the yolo pattern.
DOI: 10.6084/m9.figshare.23996670.v2
title: Questionnaire - Depression, anxiety, and stress among adolescents in Shivamogga, Karnataka

description: DASS21 Questionnaire
DOI: 10.6084/m9.figshare.28601489.v1
title: Dataset. Raw Results. Alone and Unaware. An Ethnography of Unidentified and Unacknowledged Unwanted Youth Loneliness

description: This article explores the often-hidden experience of unwanted loneliness among youth in an increasingly digital world, where opportunities for connection abound yet true intimacy remains elusive. Using a reflexive ethnographic approach, this study examines how young people in Alicante, Spain, navigate loneliness within both digital and physical spaces. The research integrates multiple methods, including: (1) questionnaires administered to 268 participants, (2) in-depth interviews with 16 young people who later took part in focus groups, (3) UCLA Loneliness Scale assessments with 44 participants before and after the study, and (4) ethnographic field notes. This study focuses on two key dimensions of loneliness: unidentified loneliness (when individuals do not recognize their own isolation) and unacknowledged loneliness (when they feel alone but refuse to verbalize it). Through the life stories of five focal participants, the findings reveal how cultural, social, and gendered dynamics shape youth loneliness, often masking it behind digital interactions. Reflexive ethnography proves essential in engaging deeply with these narratives, shedding light on the contradictions between hyperconnectivity and social disconnection. Ultimately, this research highlights the need for safe, authentic spaces that allow young people to confront and articulate their loneliness without stigma.
DOI: 10.6084/m9.figshare.715841.v7
title: "Insectivore" mammal skulls, ventral view

description: Photographs of ventral views of "insectivore" mammal skulls (Afrosoricida, Erinaceomorpha, Soricomorpha and Notoryctemorphia) from the American Museum of Natural History (AMNH) and the Smithsonian Institute (SI). I can provide a list of the species identities corresponding to each specimen ID number. Alternatively, species may be identified by searching the online museum databases for the specimen ID number. I photographed the skulls on a flat plane relative to the camera and the scale bar has 1mm as the smallest demarcation. Images are grey scale TIF files labelled with the museum specimen ID number, the specimen identity (cranial) and view (ventral) along with the date that I took the photograph. Some specimens were photographed three times, re-positioning the skull in between each picture. They are labelled with the same museum specimen number and then _1A, _2A and _3A to indicate that they are replicate pictures of the same skull. These photos form part of my research on morphological diversity in tenrecs compared to other mammal groups.
DOI: 10.6084/m9.figshare.13567409.v3
title: Analysis code & Data for the combined Cogcarsim studies 2017+2019

description: CODE--------R markdown script 'cogcarsim_analyses.Rmd' will recompute the analyses from Palomäki et al 2021, “The Link Between Flow and Performance is Moderated by Task Experience”. Precompiled HTML output of this script is also provided.<br>To run the script, download all contents of this Figshare object, load cogcarsim_analyses.Rmd in RStudio and knit (press Ctrl+Shift+k on Linux).<br>Note also that to export figures, uncomment the corresponding lines of code (e.g. line 116: #ggsave(“figure4.pdf”, width=12, height=6)<br>DATA-------SQL databases cogcarsim2_2017.db & cogcarsim2_2019.db contain the CogCarSim log data of 18 subjects, 9 from 2017 and 9 from 2019.<br>background_2017.csv & background_2019.csv contain original profile data on 18 subjects. background_cogcarsim_2017.csv & background_cogcarsim_2019.csv contain cleaned-up, mutually compatible profile data on 18 subjects.<br>fss_data_2017.csv & fss_data_2019.csv contain Flow Short Scale self-report data on 18 subjects. <br>fss_learning.csv combines them and adds variables on learning derived from models fitted to data from the SQL database files. This file is generated by the accompanying R code cogcarsim_analyses.R
DOI: 10.6084/m9.figshare.22251028.v5
title: EuDiS - A comprehensive database of the seed dispersal syndromes of the European flora

description: See detailed description in: Vargas, Heleno & Costa  (submitted) EuDiS - A comprehensive database of the seed dispersal syndromes of the European flora
<br>
Table structure: 
<strong>Species_Flora_Europaea: </strong>binomial from Flora Europaea
<strong>Species_POWO: </strong>binomial currently (as of 2022) accepted according to Plants of the World Online (https://powo.science.kew.org).
<strong>Family: </strong>botanical family of the respective species according to POWO.
<strong>Endozoochorous: </strong>coded as “1” when the species has diaspores with traits that facilitate internal dispersal by animals; coded as “0” otherwise.
<strong>Epizoochorous: </strong>coded as “1” when the species has diaspores with traits that facilitate external dispersal by animals; coded as “0” otherwise.
<strong>Thalassochorous: </strong>coded as “1” when the species has diaspores with traits that facilitate dispersal by transport on salt water; coded as “0” otherwise.
<strong>Anemochorous: </strong>coded as “1” when the species has diaspores with traits that facilitate dispersal by wind; coded as “0” otherwise.
<strong>Myrmecochorous: </strong>coded as “1” when the species has diaspores with traits that facilitate external dispersal by ants; coded as “0” otherwise.
<strong>Vertebrate_hoarding: </strong>coded as “1” when the species has diaspores with traits that facilitate dispersal by seed hoarding animals; coded as “0” otherwise.
<strong>Freshwater Hydrochorous: </strong>coded as “1” when the species has diaspores with traits that facilitate dispersal by fresh water; coded as “0” otherwise.
<strong>Ballochorous: </strong>coded as “1” when the species has traits that facilitate the dispersal by explosive mechanisms; coded as “0” otherwise.
<strong>Further_clarification_needed: </strong>marks specific syndromes whose classification is still doubtful or based on incomplete information and thus warrant further work: END: endozoochorous, EPI: epizoochorous, THA: thalassochorous, ANE: anemochorous, HYD: freshwater hydrochorous, MYR: myrmecochorous, BAL: ballochorous.  
<strong>Tree_or_shrub: </strong>coded as “1” when the species is a tree or a woody shrub; coded as “0” otherwise (herbaceous plants, climbers, and suffruticose chamaephytes).
<strong>Synonyms: </strong>binomials that were considered independent species in the volumes of Flora Europaea but are currently considered synonyms of the binomials listed in the field “Species_POWO”
<strong>References: </strong>sources used to code the syndromes.
DOI: 10.6084/m9.figshare.25286197.v1
title: Query tables in Parquet format for Deep DNAshape webserver

description: DNA shape query tables generated by Deep DNAshape model from 5-mer to 11-mer, separated in odd and even k-mers. Use odd.txt and bp.parquet for intra-bp features and minor groove features. Use even.txt and bpstep.parquet for inter-bp features.
DOI: 10.6084/m9.figshare.29047328.v1
title: Database of coffee leaves and source code

description: The database used for the system based on convolutional neural networks (CNN) for image classification and pattern recognition, based on Artificial Intelligence (AI), which allowed the recognition of diseases in coffee crops, is presented.
DOI: 10.17632/pnmt3dt6zr
title: Digital Literacy

description: faktor faktor yang membentuk literasi digital
DOI: 10.6084/m9.figshare.4000848.v1
title: Progress of endocytic CHRN to autophagic degradation is regulated by RAB5-GTPase and T145 phosphorylation of SH3GLB1 at mouse neuromuscular junctions in vivo

description: Endocytosed nicotinic acetylcholine receptors (CHRN) are degraded via macroautophagy/autophagy during atrophic conditions and are accompanied by the autophagic regulator protein SH3GLB1. The present study addressed the functional role of SH3GLB1 on CHRN trafficking and its implementation. We found an augmented ratio of total SH3GLB1 to threonine-145 phosphorylated SH3GLB1 (SH3GLB1:p-SH3GLB1) under conditions of increased CHRN vesicle numbers. Overexpression of T145 phosphomimetic (T145E) and phosphodeficient (T145A) mutants of SH3GLB1, was found to either slow down or augment the processing of endocytic CHRN vesicles, respectively. Co-expression of the early endosomal orchestrator RAB5 largely rescued the slow processing of endocytic CHRN vesicles induced by T145E. SH3GLB1 phosphomutants did not modulate the expression or colocalization of RAB5 with CHRN vesicles, but instead altered the expression of RAB5 activity regulators. In summary, these findings suggest that SH3GLB1 controls CHRN endocytic trafficking in a phosphorylation- and RAB5-dependent manner at steps upstream of autophagosome formation.
DOI: 10.17632/d7k2852xnm
title: Computational Finance Research Dataset (1996-2020)

description: The Computational Finance research & publication dataset, which was indexed by Scopus from 1996 to 2020. The dataset consist of 503 publication data in CSV format. 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: 10.6084/m9.figshare.11860224.v1
title: simulation and core data on surface conductivity and permeability

description: In Table 1, the simulation results of the electrical parameters of three fractals are present.In Tables 2 and 3, the conductivity measurements in high-salinity region by Waxman and Smits (1968) and Vinegar and Waxman (1984) are used to determine formation factor and suface conductivity with the method of linear fitting. Table 4 presents the petrophysical parameters (Zhang and weller, 2014) and the permeability calculated using Kozeny-Carman model and revised Kozeny-Carman model, respectively.
DOI: 10.6084/m9.figshare.25045667.v1
title: 2023 NMDC Ambassador Event Survey

description: This Post-Event survey was used for the 2023 cohort of NMDC Ambassadors. The Ambassadors provided this survey to their event participants who were able to answer anonymously, and summary data was collected for publication. The IRB for this survey was approved by the Lawrence Berkeley Lab Human Subjects Committee as an exempt IRB protocol under #394NR002
DOI: 10.6084/m9.figshare.7907672.v1
title: DMR.txt

description: pre-in-follicle
DOI: 10.17632/4hf842sbw3
title: urbanization intensity index

description: urbanization intensity index
DOI: 10.17632/6jxyrx4rff
title: Supplement data for "A vascular filarial nematode in sika deer (Cervus nippon): Morphological and molecular characterization of Elaeophora in Japan"

description: Multiple alignment files used for publication in Tokiwa et al. (2025) A vascular filarial nematode in sika deer (Cervus nippon): Morphological and molecular characterization of Elaeophora in Japan. All files are in FASTA format. https://doi.org/10.1016/j.ijppaw.2025.101068.
DOI: 10.17632/b69mjhr5yx
title: Short-distance vesicle transport via phase separation. Qiu et al

description: Using the reconstituted presynaptic terminal local vesicle transport as a paradigm, Qiu and Wu et al. demonstrate that short-distance and directional vesicle transport can be achieved via regulated phase separation of vesicles with different protein condensates without involving molecular motors.
DOI: 10.17632/y4mnw9nd8r
title: MSME's Performance Data

description: MSME's Performance Data DIB Data Tabulation
DOI: 10.6084/m9.figshare.13055585.v4
title: Gesticulator: Ablation User Study Results

description: Result of the user study we conducted in our ICMI 2020 paper "Gesticulator: A framework for semantically-aware speech-driven gesture generation" to evaluate 6 different ablations of the proposed model.<br>
DOI: 10.6084/m9.figshare.14673141.v1
title: S2_Data.csv.zip

description: <b>S2 Data. Annotated pangenome. </b>All genes of the pangenome (gene) annotated with a unique gene family ID (num_fam) and the category (type) presented on Fig 1B.
DOI: 10.6084/m9.figshare.25684293.v1
title: Host Predictions for Prokaryotic Viruses

description: Host predictions generated for prokaryotic viruses using iPHOP and SpacePHARER.
DOI: 10.6084/m9.figshare.27606408.v1
title: xdm_individual_shrinkage_data.csv

description: This third file of the <i>XyloDensMap</i> collection provides the wood volumetric shrinkage measured on a subset of 23,828 wood cores, intended for their average estimation across the tree species, or a more sophisticated modelling approach accounting for individual tree/core attributes.
DOI: 10.6084/m9.figshare.28009532.v1
title: <b>LOCAL SCALE CLIMATE VARIABILITY: Case of Mandraka slope, eastern central of Madagascar</b>

description: This dataset supports the research article entitled <i>"LOCAL SCALE CLIMATE VARIABILITY: CASE OF MANDRAKA SLOPE, EASTERN CENTRAL OF MADAGASCAR"</i>. It incorporates:<b>Observed data</b>: Monthly rainfall, maximum, and minimum temperatures from the Directorate General of Meteorology of Madagascar (2010–2020).<b>Estimated data</b>: Climate variables interpolated using Inverse Distance Weighting (IDW) based on gridded data from the University of Delaware (Version 5.01).<br>
DOI: 10.17632/n3s5g457fm
title: Gai3 and Gai1/2/3 Blots for Maziarz et al. 2020

description: Enclosed TIF file contains a compilation of un-cropped immunoblots probed with three different antibodies: 1. Rabbit polyclonal anti-Gαi3 (C-10) (Santa Cruz Biotechnology, Cat# sc-262) 2. Rabbit polyclonal anti-Gαi1/2/3 (Cell Signaling Technology, Cat# 5290) 3. Rabbit polyclonal anti-Gαi3 (Aviva Systems Biology, Cat# OAAB19207) Lead Contact: Mikel Garcia-Marcos, Boston University (mgm1@bu.edu).