cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7627484.v1
title: 3482151116 NGS-immunoglobulins.xlsx

description: Peripheral blood mononuclear cells (PBMCs) were resuspended in staining buffer (PBS supplemented with 1% fetal bovine serum) and stained with mouse-anti-human CD27-AF647 (AbD Serotec), mouse-anti-human CD19-PB (AbD Serotec) and goat-anti-human IgM-AF488 (Life Technologies) for 1 hour at 4°C, protected from light. Cells were washed, resuspended, and stained with propidium iodide (Sigma-Aldrich) at a final concentration of 10 ug/mL. Cells gated CD19+ were sorted on BD FACSAria Fusion flow cytometer (BD Biosciences).Sorted B cells were resuspended in RNA extraction buffer (QuickExtract RNA Extraction Kit, Lucigen). cDNA was generated using the Maxima H Minus cDNA Synthesis Master Mix (Thermo Fisher) using 5 uL of extraction buffer per 10 uL reaction as per manufacturer’s protocol. 2 uL of cDNA product was directly used in 20 uL reactions with Platinum Taq Master Mix as per manufacturer’s protocol for separate amplification of the heavy and light chain variable regions. Illumina adaptor and barcode sequences added by further PCR with Q5 Hot Start Hi-Fidelity Master Mix and the PCR products purified with AMPure XP magnetic beads. Purified PCR products were pooled in the same molar ratio as the number of B cells from each of the four samples, diluted to 8 pM and sequenced on the Illumina MiSeq with 2x300 bp kit with 25% PhiX spike in. Individual reads were separated by sample and analyzed with MIXCR to derive unique clonotypes based on CDR1 and 3 homology. The corresponding germline sequences were retrieved from IMGT, the international ImMunoGeneTics database®.
DOI: 10.6084/m9.figshare.22362739.v1
title: GDSC2 single agent responses

description: GDSC2 monotherapy data for comparison
DOI: 10.6084/m9.figshare.27216204.v1
title: Microarray data of EOPE&control plancenta

description: This is a subset of GSE149812 on Gene Expression Omnibus (GEO) database. The matrix contains microarray data of placental tissue from early onset preeclampsia (EOPE) and control pregnancies. Early onset preeclampsia (EOPE) was defined as onset of the disease before 34 weeks of gestation (between 20 and 34 completed gestational weeks). More details can be found on GEO.
DOI: 10.17632/rryrbf7b54
title: Vaginal discharge score_Figueiredo et al.

description: Vaginal discharge score for dairy cows
DOI: 10.17632/swgs6fdd83
title: Rawdata of the Speech-in-noise Comprehension Experiment for "The modulating effect of musical expertise on lexical semantic prediction in speech-in-noise comprehension: evidence from an EEG study"

description: The dataset includes the raw data coming from the EEG Experiment, for 26 musician subjects and 30 non-musicians of the Speech-in-noise Comprehension Experiment for the article "The modulating effect of musical expertise on lexical semantic prediction in speech-in-noise comprehension: evidence from an EEG study". Data of all subjects were uploaded online, whereas six of these subjects were not excluded in the formal analysis of the present study due to the matching procedure between groups in their reading experience (Subject 5 of the Musician group, Subject 5, 8, 10, 13 and 25 of the Non-musician group). You can find the detailed description of the data in the corresponding folders.
DOI: 10.17632/x9krf9cbn7
title: The dataset of comments on YouTube videos containing instructions on first aid

description: This dataset contains English-language comments extracted from YouTube video-sharing platform (YouTube LLC, California, USA) in November 2022. 
The comments were collected as follows:
(1) Titles of the first aid-related videos found on YouTube with a “first aid” keyword were screened, and videos potentially providing instructions on how to administer first aid in a health emergency situation were selected (n=104); (2) all comments to the videos (n=16,091) were automatically extracted using the web scraping technique based on a Python script developed by the authors; (3) non-English, duplicate and apparently irrelevant comments and comment replies were excluded (n=15,390).
Eventually, a total of 701 comments composed the dataset.
DOI: 10.6084/m9.figshare.25427476.v1
title: The chromosome level genome assembly of the Asian green mussel, Perna viridis

description: The chromosome level genome assembly of the Asian green mussel, Perna viridis
DOI: 10.6084/m9.figshare.28823159.v7
title: CODERData2.1.0

description: Cancer Organoid Data
DOI: 10.17632/2rsrxwck2r
title: Potato Crop Disease Augmentation Dataset

description: The PotatoCropDiseaseAugmentationDataset is a comprehensive collection of images designed to aid in the development and evaluation of machine learning models for detecting and classifying diseases in potato crops. This dataset includes augmented images representing both healthy and diseased potato plants, encompassing various stages of disease progression. The dataset is structured to support tasks such as disease detection, crop health monitoring, and disease classification.
Subfolders in the Dataset:
The dataset is organized into two main levels of subfolders:

Top-Level Subfolders:

augmented: Contains the disease categories and their corresponding augmented images.
common_scab
cut
dry_rot
gangrene
healthy
violet_root_rot
Inside Each Disease Folder: Each disease or health status subfolder contains images of potato plants with different augmentations applied, including:

Color_Intensity_Modifications
Cutout_Occlusion
Gaussian_Blur
Geometric_Transformations
Noise_Addition
Perspective_Transformation
Random_Brightness_Contrast
Random_Cropping
Random_Hue
Super_Resolution

####Raw_Data:: Shuvo Kumar Basak. (2025). Potato Crop Disease and Health Dataset [Data set]. Kaggle. https://doi.org/10.34740/KAGGLE/DSV/10503599

 Note for Researchers Using the dataset
This dataset was created by Shuvo Kumar Basak. If you use this dataset for your research or academic purposes, please ensure to cite this dataset appropriately. If you have published your research using this dataset, please share a link to your paper. Good Luck.
DOI: 10.6084/m9.figshare.19709134.v1
title: Single-input dual-output 3D shape reconstruction

description: This dataset is used to train the SIDO network which converts a single structured-light (fringe) image to two intermediate outputs before subsequent 3D shape reconstruction. <br> If you use the datasets for your research, please consider citing our related publications: <br> 1) H. Nguyen, Y. Wang, and Z. Wang, "Single-Shot 3D Shape Reconstruction Using Structured Light and Deep Convolutional Neural Networks," <em>Sensors</em> <strong>20</strong>, 3718, 2020. 2) H. Nguyen and Z. Wang, "Accurate 3D Shape Reconstruction from Single Structured-Light Image via Fringe-to-Fringe Network," <em>Photonics</em> <strong>8</strong>, 459, 2021. 3) H. Nguyen, E. Novak, and Z. Wang, "Accurate 3D reconstruction via fringe-to-phase network," <em>Measurement</em> <strong>190</strong>, 110663, 2022. 4) AH. Nguyen, K. Ly, C. Li, and Z. Wang, "Single-shot 3D shape acquisition using a learning-based structured light technique," <em>Appl. Opt.</em> <strong>61</strong>, 8589-8599, 2022. 5) AH. Nguyen, O. Rees, and Z. Wang, "Learning-based 3D imaging from single structured-light image," <em>Graph. Models</em> <strong>126</strong>, 101171, 2023.
DOI: 10.6084/m9.figshare.27730353.v1
title: Music Genre Preferences Among High School Students

description: This dataset presents the results of a survey conducted to analyze music genre preferences among high school students. The survey aimed to uncover trends in music listening habits. Students were asked about their favorite music genres while in school.The research behind this dataset aims to understand the cultural and social influences that shape young people's music tastes. By analyzing these preferences, educators, researchers, and marketers can gain insight into the factors that drive music choices in adolescents and possibly how music preferences correlate with lifestyle, mood, and social circles. This dataset can be beneficial for studies in fields such as psychology, sociology, education, and even marketing, as it provides a foundation for exploring the influence of peer groups, family background, and other social factors on youth culture.
DOI: 10.6084/m9.figshare.3569385.v2
title: Andean region: a shapefile of Morrone’s (2015) biogeographical regionalisation

description: This is a shapefile of the geographic limits proposed by Morrone (2015) based on occurrence data of endemic animals and plants within South America.
DOI: 10.6084/m9.figshare.6143210.v1
title: The rate of improvement of pain and function in mid-portion Achilles tendinopathy with loading protocols: A Systematic Review and Longitudinal Meta-Analysis.

description: Murphy, M., Travers, M., Gibson, W., Chivers, P., Debenham, J., Docking, S., & Rio, E. The rate of improvement of pain and function in mid-portion Achilles tendinopathy with loading protocols: A Systematic Review and Longitudinal Meta-Analysis. Sports Medicine. 2018: In Press
DOI: 10.17632/g47td7swv3
title: Get AQI in One Shot-2 (GAOs-2)

description: Get AQI in One Shot-2 (GAOs-2)
DOI: 10.6084/m9.figshare.21158947.v1
title: Apathy, cognition and schizophrenia

description: It is a dataset from a research project titled "Neurocognitive basis of apathy in schizophrenia". We assessed the relationship between apathy, cognition and functionality in a small sample of schizophrenia patients using traditional and ecological neuropsychological instruments.
DOI: 10.6084/m9.figshare.28517402.v1
title: High-flux gaseous hydrogen emissions in a back-arc basin: Qianyuan vents

description: <br>Data S1. Raman spectra of Qianyuan vents fluids and mixed gas hydrates collected in the gas collection tank.<br>Movie S1.<i> </i><i>In situ</i> detection of gas components at the Qianyuan vents using in situ Raman spectroscopy.Movie S2. Collection of gases from the Qianyuan vents using a gas collection tank and evaluation of the hydrogen flux at the Qianyuan vents based on this.Movie S3.<i> </i><i>In situ</i> Raman spectra collection from gases in the gas collection tank by inserting the Raman spectroscopy probe, detecting the formation of mixed gas hydrates.
DOI: 10.6084/m9.figshare.28783343.v1
title: XRD.zip

description: <b>XRD pattern </b><b>of synthesized nanoparticles</b>.
DOI: 10.6084/m9.figshare.5128333.v1
title: Supplementary Material for: HIV Nosode: The Homeopathic Pathogenetic Trial

description: <b><i>Background:</i></b> Deriving clinical indications for the HIV nosode by conducting a double-blind, placebo-controlled homeopathic pathogenetic trial (HPT) with the aim to introduce a new nosode to the profession. <b><i>Method:</i></b> The HPT was conducted in 22 volunteers, 15 of which received HIV nosode in 30c potency pills, while 7 received identical placebo pills orally, once a week, for 4 weeks. The volunteers' symptoms during initial 7 days of run-in period were noted. All symptoms for both groups produced during run-in period were excluded from final analysis. Informed consent form, approval by Ethics Committee, laboratory investigations as well as safety and ethical measures were provided. The volunteers were trained to write data in prescribed diaries, and the data were analyzed. <b><i>Results:</i></b> The HPT of the HIV nosode exhibited qualitatively distinct symptoms, which can be applied in clinical practice. Number of symptoms reported in verum group was 130, in placebo group 60. Quantitative pathogenetic index was 0.285 in verum group, 0.238 in placebo group; qualitative pathogenetic index was 0.1402 in the verum group as compared to placebo (0.0907). Safe use was documented. <b><i>Conclusion:</i></b> This study brought in guiding symptoms, which will help the profession to employ this nosode in practice.
DOI: 10.17632/63k65f2d47
title: Data for: Ion irradiation and FLiNaK molten salt corrosion of Hastelloy N

description: Accompanying data for the paper "Ion irradiation and FLiNaK molten salt corrosion of Hastelloy N".  Please read Excel workbook "Data_for_HastelloyN_paper.xlsx" for details of where to find data for each figure in the paper.
DOI: 10.17632/f43c7snks5
title: BRACETS: Bimodal Repository of Auscultation Coupled with Electrical Impedance Thoracic Signals

description: Background and Objective: Respiratory diseases are among the most significant causes of morbidity and mortality worldwide, causing substantial strain on society and health systems. Over the last few decades, there has been increasing interest in the automatic analysis of respiratory sounds and electrical impedance tomography (EIT). Nevertheless, no publicly available databases with both respiratory sound and EIT data are available.

Methods: In this work, we have assembled the first open-access bimodal database focusing on the differential diagnosis of respiratory diseases (BRACETS: Bimodal Repository of Auscultation Coupled with Electrical Impedance Thoracic Signals). It includes simultaneous recordings of single and multi-channel respiratory sounds and EIT. Furthermore, we have proposed several machine learning-based baseline systems for automatically classifying respiratory diseases in six distinct evaluation tasks using respiratory sound and EIT (A1, A2, A3, B1, B2, B3). These tasks included classifying respiratory diseases at sample and subject levels. The performance of the classification models was evaluated using a 5-fold cross-validation scheme (with subject isolation between folds). 

Results: The resulting database consists of 1097 respiratory sounds and 795 EIT recordings acquired from 78 adult subjects in two countries (Portugal and Greece). In the task of automatically classifying respiratory diseases, the baseline classification models have achieved the following average balanced accuracy: Task A1 - 77.9±13.1%; Task A2 - 51.6±9.7%; Task A3 - 38.6±13.1%; Task B1 - 90.0±22.4%; Task B2 - 61.4±11.8%; Task B3 - 50.8±10.6%. 

Conclusion: The creation of this database and its public release will aid the research community in developing automated methodologies to assess and monitor respiratory function, and it might serve as a benchmark in the field of digital medicine for managing respiratory diseases. Moreover, it could pave the way for creating multi-modal robust approaches for that same purpose.
DOI: 10.17632/msyc6mzvhg
title: Dataset of Pairs of an Image and Tags for Cataloging Image-based Records

description: 
## Brief Explanation

This dataset is created to develop and evaluate a cataloging system which assigns appropriate metadata to an image record for database management in digital libraries. That is assumed for evaluating a task, in which given an image and assigned tags, an appropriate Wikipedia page is selected for each of the given tags.

A main characteristic of the dataset is including ambiguous tags. Thus, visual contents of images are not unique to their tags. For example, it includes a tag 'mouse' which has double meaning of not a mammal but a computer controller device. The annotations are corresponding Wikipedia articles for tags as correct entities by human judgement.

The dataset offers both data and programs that reproduce experiments of the above-mentioned task. Its data consist of sources of images and annotations. The image sources are URLs of 420 images uploaded to Flickr. The annotations are a total 2,464 relevant Wikipedia pages manually judged for tags of the images. The dataset also provides programs in Jupiter notebook (scripts.ipynb) to conduct a series of experiments running some baseline methods for the designated task and evaluating the results.
 

## Structure of the Dataset

1. data directory
     1.1. image_URL.txt
     	This file lists URLs of image files.

     1.2. rels.txt
     	This file lists collect Wikipedia pages for each topic in topics.txt

     1.3. topics.txt
     	This file lists a target pair, which is called a topic in this dataset, of an image and a tag to be disambiguated. 

     1.4. enwiki_20171001.xml
     	This file is extracted texts from the title and body parts of English Wikipedia articles as of 1st October 2017. This is a modified data of Wikipedia dump data (https://archive.org/download/enwiki-20171001).

2. img directory
     This directory is a placeholder directory to fetch image files for downloading.

3. results directory
     This directory is a placeholder directory to store results files for evaluation. It maintains three results of baseline methods in sub-directories. They contain json files each of which is a result of one topic, and are ready to be evaluated using an evaluation scripts in scripts.ipynb for reference of both usage and performance. 

4. scripts.ipynb
     The scripts for running baseline methods and evaluation are ready in this Jupyter notebook file.
DOI: 10.6084/m9.figshare.25699275.v1
title: Figure 2a Distribution of average network-based proximity (<i>P</i><sub><em>QAB</em></sub>) between a query disease module (Q) and drug modules (A and B).

description: This dataset contains the network-based proximity between 1,488 drug modules and six disease modules. This is a 6637968 rows by 5 columns matrix. You can load this data by R using "load" function. Run "Scripto_for_Figure2a.R" for making figure 2a in the manuscript.<br><br>Drug_A: KEGG drug ID of one of the drug pairs (Drug A)Drug_B: KEGG drug ID of the other of the drug pairs (Drug B)<br>variable: disease namevalue: the network-based proximity between Drug A and Drug B<br>IF: if the drug combination is effective on the disease. "ALL" means No, "posi" means yes
DOI: 10.6084/m9.figshare.28559198.v1
title: Supplementary Material for: A Combined Index of Steady-state Pattern Electroretinogram and Optical Coherence Tomography improved the Detection of Early Glaucoma

description: Introduction: To evaluate the structure-function relationship between steady-state pattern electroretinogram (ssPERG), optical coherence tomography (OCT), and visual field (VF) tests, and to investigate indicators that enhance the detection of preperimetric and early-stage primary open angle glaucoma (POAG).
Methods: In this retrospective cohort study, patients with POAG and normal subjects who underwent ssPERG, OCT, and VF tests were included. We defined the ratio of the amplitudes from 0.8° checks to 16° checks as the pattern electroretinogram ratio (PERGratio). The thickness of the macular ganglion cell inner plexiform layer and the peripapillary retinal nerve fiber layer (cpRNFL) were measured using spectral-domain OCT. We compared the areas under the receiver operating characteristic curves (AUCs) for ssPERG, OCT, and VF test parameters. A combined index using structural and functional measures was generated using logistic regression models to improve diagnostic accuracy.
Results: Four parameters had AUCs higher than 0.8; PERGratio (AUC = 0.890), average cpRNFL thickness (AUC = 0.827), 7 o’clock cpRNFL thickness (AUC = 0.844), and inferior quadrant cpRNFL thickness (AUC = 0.830). The new index, which combines the PERGratio and 7 o’clock cpRNFL thickness, significantly improved diagnostic accuracy (AUC = 0.951), outperforming the best four parameters (all P ≤ 0.004). Furthermore, the combined index of PERGratio and 7 o’clock cpRNFL thickness showed significantly higher diagnostic accuracy compared to those combining the 7 o’clock cpRNFL thickness with visual field mean deviation, pattern standard deviation, and visual field index.
Conclusion: Combined index of ssPERG, indicative of RGC dysfunction, and the OCT test, indicative of focal structural damage, improved the detection of patients with POAG in its early stage.
DOI: 10.17632/t3tt7rjszv
title: Nature's Diabetes Helpers: Insulin Leaves Repository

description: This database comprises a total of 429 images depicting both healthy (265 
images) and diseased (164 images) leaves of the insulin plant (Scientific name: Chamaecostus cuspidatus). 
All the images included in this database are captured by the creators of this database from the real fields 
located in the Ranaghat district of West Bengal, India.
The images in this database consist of intricate backgrounds that include elements like weeds, soil, and 
portions of other plants. The primary objective behind creating this database is to offer a comprehensive 
assortment of labeled foliage images of insulin plants. These images are intended for training deep neural 
networks to autonomously classify them into either diseased or healthy categories. The incorporation of 
foliage images with complex backgrounds and captured under varied illumination condition in this database 
enhances its capability to effectively train deep neural networks, enabling precise real-world identification 
for the specified task.
The images included in this database were captured using mobile phones, specifically the Redmi Note 9 
Pro Max with a camera array featuring 64MP+8MP+2MP+2MP and Redmi Note 9 Pro Max with a camera 
array featuring 64MP+8MP+5MP+2MP, utilizing Artificial Intelligence (AI) technology.
As this database contains the diseased and healthy leaves of insulin plants which serves as natural remedy 
for diabetes, so we have termed this database as “Nature's Diabetes Helpers: Insulin Leaves Repository.”
DOI: 10.6084/m9.figshare.24458833.v1
title: 基于改进YOLOv5的PCB表面缺陷检测

description: 表基线和表NWDBRA支持图7.1和图7.2中的数据。
DOI: 10.25392/leicester.data.12045261.v3
title: Myocardial infarction complications Database

description: This dataset contains a database for Myocardial Infarction complication prediction (csv file) , collected in 1992-1995 in Krasnoyarsk with associated description (pdf file). Descriptive statistics of all database attributes are presented in Descriptive Statistics file.
DOI: 10.6084/m9.figshare.17869043.v1
title: World Health Organization’s Agenda For COVID-19 and Its Effects: A Network Agenda-Setting Study with Twitter Users

description: The Tweets posted by WHO (the world health organization) from January 2020 to July 2020. <br>AND the English language Tweets posted by six groups of WHO followers on Twitter from January 2020 to July 2020 related to COVID-19.
DOI: 10.6084/m9.figshare.7108778.v2
title: Piezoelectric Tensor Data

description: Piezoelectric tensor data. Available as Monty Encoder encoded JSON and CSV files. The recommended access method is through the matminer Python package using the datasets module.<br><br>Note on citations: If you found this dataset useful and would like to cite it in your work, please be sure to cite its original sources below rather than or in addition to this page.<br>Dataset is described in the following:<br>De Jong M, Chen W, Geerlings H, Asta M, Persson K (2015) A database to enable discovery and design of piezoelectric materials. Scientific Data 2: 150053. https://doi.org/10.1038/sdata.2015.53<br>Data adapted from JSON files available here:<br>De Jong M, Chen W, Geerlings H, Asta M, Persson K (2015) Data from: A database to enable discovery and design of piezoelectric materials. Dryad Digital Repository. https://doi.org/10.5061/dryad.n63m4
DOI: 10.6084/m9.figshare.9722210.v1
title: DSF dataset

description: It is built by GeneX, Inc.
DOI: 10.17632/3sfbbds4xd
title: Modified Sinclair Scale for Female Pattern Hair Loss in Men

description: Supplemental Figure 2 (Short Hair) and Figure 3 (Long Hair). A modified Sinclair scale for use in men with female pattern hair loss (FPHL). Grade 1: normal hair density; Grade 2: minimal rarefaction of hair on the mid-frontal scalp and crown; Grade 3: noticeable reduction in hair density (greater than Grade 2) on the mid-frontal scalp and crown; Grade 4: profound rarefaction of hair on the mid-frontal scalp and crown re-sulting in a “see-through” appearance; Grade 5: most severe stage of hair loss with little or no hair in the centroparietal region. NB: the anterior hairline is preserved in all hair loss severity grades. Supplemental Table 1. Interrater and intrarater reliability of the modified Sinclair Scale for female pattern hair loss in men.
DOI: 10.17632/sw8mhr5bm7
title: Data for: Designing local renewable energy communities to increase social acceptance: Evidence from a choice experiment in Austria, Germany, Italy, and Switzerland