cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5332240.v1
title: ELISPOTS

description: ELISpots data for specific plasma cells against influenza viruses
DOI: 10.6084/m9.figshare.5979421.v1
title: advertiser.xlsx

description: A study with 200 customers to publish an Ad
DOI: 10.17632/56td5w4wz2
title: Fruits (Banana and Guava) datasets for non-destructive quality classifications

description: This article provides fruit (banana and guava) image dataset for non-destructive quality classifications. The images were captured with a Redmi Note 10-Pro mobile camera in natural sunlight. All the images were captured at different angles and saved in JPG format. A total of 1738 images were collected. The images were classified into three different classes; Class A, Class B, and Defect Quality, according to the maturity stages of fruits. Further, the image datasets were saved into their respective folder. This dataset allows researchers to study different machine learning and deep learning algorithms for the quality classification of fruits. The dataset provides the foundation for the future study of fruit physiological behaviors underlying postharvest enzymatic browning. Because, in the later stage of the ripening the degradation of fruit peel color from yellow to brown is the major issue in the supply chain and the storage industries.
DOI: 10.17632/dnf8ssyw4n
title: Data for: Fast tracking of moving objects using single-pixel imaging

description: real-time tracking video
DOI: 10.6084/m9.figshare.28516898.v1
title: Code for <b>GenFair</b>

description: This repository contains multiple components related to medical report summarization and evaluation. It includes both baseline and proposed methods for generating and evaluating reports, as well as test datasets.
DOI: 10.17632/mk38nk4yd7
title: Data for: Exploratory Behavior and Developmental Skill Acquisition in Infants with Down Syndrome

description: This dataset represents one timepoint of data collection for a sample of infants with Down syndrome. Complete Bayley-III information is provided, as well as demographic information and child medical/health history information. In addition, infants were administered a short exploration task that involved presenting the infant with a teether in their line of vision, and then placing it on the table before them. Exploration trials were coded for the percentage of time the infant spent visually, manually, and orally exploring the object.
DOI: 10.6084/m9.figshare.2199001.v3
title: D-BRAIN: simulated diffusion MRI brain data.

description: Diffusion MRI phantom data sets - D-BRAIN data sets - "acquired" at different b-values. The data are stored in NIFTI format, the corresponding b-matrices are stored in txt files.<br>
DOI: 10.6084/m9.figshare.22691122.v2
title: Untitled Item

description: The MIDOG++ dataset represents an extension of the data set used in the MIDOG 2021 and 2022 challenges. We provide region of interest images from 503 histological specimens of seven different tumor types with variable morphology: breast carcinoma, lung carcinoma, lymphosarcoma, neuroendocrine tumor, cutaneous mast cell tumor, cutaneous melanoma, and (sub)cutaneous soft tissue sarcoma. The human and canine samples were processed and stained at different human and veterinary pathology laboratories with standard H&E dye and digitized with different digital whole slide image scanners. We provide labels for 11,937 mitotic figures that have been differentiated against 14,351 imposter cells in a blinded consensus by two pathologists and a final decision by a third pathologist for disagreed labels.
DOI: 10.17632/x9vdrdwyfh
title: Data and Results for paper End-to-end on-line rescheduling from Gantt chart images using Deep Reinforcement Learning

description: In this dataset, the initial schedules used to perform the training and testing processes for the reference paper can be found. In addition, the results summarization archives are available.
DOI: 10.6084/m9.figshare.14635842.v1
title: Unigems extra parts

description: Extra DNA sequences in SnapGene format with proposed parts to extend the existing Unigems parts and plasmids. The parts are untested, particularly the LuxI/LuxR system may not work. These resources accompany the Siddall et al. 2023 paper.
DOI: 10.6084/m9.figshare.16673974.v1
title: P02

description: Zip of CCEP files for patient 2
DOI: 10.6084/m9.figshare.5567038.v1
title: Dynamic time sweep and creep test measurement for 4.2 wt% waste activated sludge at various gas flow rates (0.5 – 1.5 LPM).

description: This submission contains the raw rheometer files from time sweep and creep test measurements of waste activated sludge (total solids content = 4.2 wt %). The sludge samples were measured at various gas flow rates (0.54 LPM and 1.5 LPM). The dynamic time sweep measurements were generated from the sludge sample first without gas at 0.08% strain across 25 minutes. Then the sample was conditioned and the gas was injected for 20 minutes before the measurement at similar conditions. Similarly, the dynamic creep test measurements were generated from the sludge sample first without gas at 0.89pa stress across 10 minutes. The measurements were carried out on a DHR-3 rheometer (TA-Instruments), equipped custom made cup. For detail procedure refer: Bobade, V, et al. 2017, 'Impact of gas injection on the apparent viscosity and viscoelastic property of waste activated sewage sludge', <i>Water Research</i>, vol. 114, pp. 296-307. Detailed experimental protocol is recorded in the .tri (TRIOS) file attached with each data set. This file can be read using the TRIOS software made available on TA-Instruments website (http://www.tainstruments.com/support/software-downloads-support/downloads/). Rheometer geometry dimensions and other details are also obtainable from these files.<br>Please contact authors for access to files. Contact: nicky.eshtiaghi@rmit.edu.au RMITRheologyGroup@gmail.com
DOI: 10.6084/m9.figshare.6790013.v1
title: Data from wall-modelled LES of channel flow and flow over a backward-facing step

description: This dataset accompanies the following article<br>T. Mukha, S. Rezaeiravesh, M. Liefvendahl, A library for wall-modelled large-eddy simulation based on OpenFOAM technology, Computer Physics Communications, 2019,DOI: 10.1016/j.cpc.2019.01.016<br>The contents of the archive are simulation cases the results from which are presented in the paper. This includes WMLES of turbulent channel flow and the flow over a backward-facing step (BFS). For all the simulations, a full OpenFOAM case, including initial condition fields, is provided. <br><br>The following conventions apply- The number at the beginning of the case's name refers to the density of the gird n/delta.<br>- h1 and h2 refer to sampling from the wall-adjacent and second off-wall cell.<br>- linear and lust correspond to using the respective schemes for discretising the convective term.<br>- For all cases, the grid can be constructed using blockMesh<br>- For channel flow cases, the profiles directory holds averaged data. For completeness even moments that should be zero are included.<br>- For the BFS, the fields averaged in time and the spanwise direction are held in the average.vtm file. This can be opened with Paraview, turbulucid or other VTK-based software.<i><br></i><i>Note: </i>the backflow field in the BFS cases actually holds the probability of forward-flow.<br>The correspondence between the directory structure of the archive and the sections of the article should be straight-forward to understand.<br><br>Note, the BFS cases require generating inflow fields. The precursor simulations that can be used for this purpose are included in the archive. To convert the generated surface-samples into a single hdf5 file we recommend using the Python package eddylicious, seehttp://eddylicious.readthedocs.iofor documentation and guidelines for using with OpenFOAM.<br><br><br><br><br>
DOI: 10.6084/m9.figshare.8981741.v2
title: ImTecho Survey Data set and Code book

description: The data represents the Cluster Randomized trial of mHealth intervention called " ImTECHO" (Improve Delivery of Maternal, Neonatal and Child Care services through Community Based Accredited Social Health Activists.
DOI: 10.17632/wnshbvdxs2
title: An EEG Recordings Dataset for Mental Stress Detection

description: This article presents an EEG dataset collected using the EMOTIV EEG 5-Channel Sensor kit during four different types of stimulation: Complex mathematical problem solving, Trier mental challenge test, Stroop colour word test, and Horror video stimulation, Listening to relaxing music. The dataset consists of EEG recordings from 22 subjects for Complex mathematical problem solving, 24 for Trier mental challenge test, 24 for Stroop colour word test, 22 for horror video stimulation, and 20 for relaxed state recordings. The data was collected in order to investigate the neural correlates of stress and to develop models for stress detection based on EEG data. The dataset presented in this article can be used for various applications, including stress management, healthcare, and workplace safety. The dataset provides a valuable resource for researchers and developers working on stress detection using EEG data, while the stress detection method provides a useful tool for evaluating the effectiveness of different stress detection models. Overall, this article contributes to the growing body of research on stress detection and management using EEG data and provides a useful resource for researchers and practitioners working in this field.
DOI: 10.17632/zvgfwm8x4h
title: Supplementary Material and Supplementary Tables for Tracing DUPAL anomaly evolution in the Tethyan-Indian oceanic mantle

description: Supplementary Material and Supplementary Tables for Tracing DUPAL anomaly evolution in the Tethyan-Indian oceanic mantle
DOI: 10.6084/m9.figshare.11393661.v1
title: MOESM1 of Prediction and clinical utility of a contralateral breast cancer risk model

description: Additional file 1 Table S1. Data source flowchart. Table S2. Description of the studies included in the analyses. Table S3. Patients and first primary breast cancer characteristics used in the contralateral breast cancer risk prediction model in the complete case and all case analyses. Table S4. Results of multivariable subdistributional hazard model using the complete case dataset. Table S5. List of BCAC studies (including ABCS source) with the corresponding country and geographic area. Table S6. Main patient and disease characteristics. Table S7. Clinical utility of the 5-year contralateral breast cancer risk prediction model. Table S8. Results of multivariable subdistributional hazard model for breast cancer patients without BRCA mutations. Table S9. Clinical utility of the 5-year contralateral breast cancer risk prediction model in non-BRCA tested patients. Table S10. Clinical utility of the 10-year contralateral breast cancer risk prediction model in non-BRCA tested patients.
DOI: 10.6084/m9.figshare.21787079.v2
title: Surface Charge as Universal Activity Descriptors for Electrochemical CO2 Reduction to Multi-Carbon Products on Organic-Functionalised Cu

description: Accompanying Dataset for "Surface Charge as Universal Activity Descriptors for Electrochemical CO2 Reduction to Multi-Carbon Products on Organic-Functionalised Cu" Intended for publication in Nature Catalysis (2023). Contents<strong>: </strong>CO2 reduction product quantification, EIS, Pulsed Voltammetry, Variable Rate Cyclic Voltamettry, and Python Code for Pulsed Voltammetry analysis.
DOI: 10.6084/m9.figshare.24581740.v2
title: Data analysis files with R code from Maths anxiety and subjective perception of control, value and success expectancy in mathematics

description: please rename the file to have ZIP extension and extract
DOI: 10.6084/m9.figshare.28225535.v1
title: <b>Passport data and phenotypic characterization of sequenced accessions</b>

description: <i>Bromus auleticus</i>, a valuable forage grass native to the Pampa biome, is currently suffering genetic erosion. Therefore, it is central to assess the appropriate methodologies for developing population genomic studies and contributing to the conservation of this plant genetic resource. This study evaluated five accessions using two genotyping strategies: individual sequencing (ind-seq) and pooled sequencing (pool-seq). To compare their efficacy, was investigated the correlation between allele frequencies calculated using each approach. Geneticdiversity and population structure were also analyzed using both methods. These comparisons explicitly accounted for the potential effects of one or more of the following parameters: sample size, missing data, sequencing depth, and minor allele frequencies. Notably, the highest concordance and percentage of common SNPs between ind-seq and pool-seq was achieved using 30 to 60 plants per accession, with a maximum missing data threshold of 10% and a more tolerant minimum allele frequency threshold for pool-seq (0.01) compared to ind-seq (0.05). Reaching maximum similarity in allele frequencies also required a higher sequencing depth for pool-seq (4.8 million reads-Mr) than for ind-seq (0.9 Mr). Pools of 50 individuals yielded the highest number of polymorphic sites, averaging over 9,000 across all accessions at a sequencing depth of 4.8 Mr. Under these conditions, pool-seq consistently yielded a means across all accessions of 0.09 higher expected heterozygosity and 0.24 lower allelic richness compared to ind-seq across all accessions. The population structure detected with both methodologies showed agreement, aligning with the outcrossing nature of <i>B. auleticus</i> and the geographical origin of each accession. The average inbreeding coefficient of 0.2 indicates signs of inbreeding, highlighting the importance of conservation efforts of this valuable plant genetic resource. Based on these findings, two workflows were proposed to carry out population genomics studies of <i>Bromus auleticus</i>.
DOI: 10.6084/m9.figshare.28236887.v1
title: tpab_-1.0.0.zip

description: Implementation of TPAB model in the paper titled "Generalizable Recommender System During Temporal Popularity Distribution Shifts" KDD'25 V1
DOI: 10.6084/m9.figshare.28256123.v1
title: <b>Soil Fungal Diversity, Network Structure and Distribution in Different Habitats of Southwestern Tibet</b>

description: This study applied ITS high-throughput sequencing to analyze the composition, diversity, and network structure of soil fungal communities in different habitats in the southwestern Tibetan Plateau.
DOI: 10.6084/m9.figshare.29148836.v1
title: RepeatMasker annotation file of <i>Gomphocerus sibiricus</i>.

description: We merged the curated non-redundant species-specific repeat library generated in this project together with Arthropoda consensus sequences from Repbase (Bao et al. 2015) to annotate the chromosome-level assembly with RepeatMasker v4.1.0 (Smit et al. 2019).
DOI: 10.6084/m9.figshare.3523838.v1
title: Appendix A. A table showing the results of GLM analyses.

description: A table showing the results of GLM analyses.
DOI: 10.17632/d3gzygskyx
title: Data set of digital leadership in Malaysia

description: The digital leadership  data was collected  among pincipals in Malaysia.
DOI: 10.17632/j45dj8bgfc
title: Smoker Detection Dataset

description: The dataset contains 1120 images divided equally into two classes, where 560 images are of Smoking (smokers) and remaining 560 images belong to NotSmoking  (non-smokers) class. The dataset is curated by scanning through various search engines by entering multiple keywords that include cigarette smoking, smoker, person, coughing, taking inhaler, person on the phone, drinking water etc. We tried to consider versatile images in both classes for creating a certain degree of inter-class confusion in order to better train the model. For instance, Smoking class contains images of smokers from multiple angles and various gestures. Moreover, the images in NotSmoking class consists of images of non-smokers with slightly similar gestures as that of smoking images such as people drinking water, using inhaler, holding the mobile phone, coughing etc. The dataset can be used by the prospective researchers to propose deep learning algorithms for automated detection and screening of smoker towards ensuring the green environment and performing surveillance in smart cities. All images in the dataset are preprocessed and resized to a resolution of 250×250. We considered 80% of the data for training and validation purposes and 20% for the testing.

Please cite this article if you use this dataset in your research:
A. Khan, S. Khan, B. Hassan, and Z. Zheng, “CNN-Based Smoker Classification and Detection in Smart City Application,” Sensors, vol. 22, no. 3, pp. 892, 2022.
DOI: 10.6084/m9.figshare.11888898.v1
title: Genes differentially expressed in the pigmentation areas of Drosophila guttifera.

description: This data set is obtained from transcriptome analysis of <i>Drosophila guttifera</i>. This species has plka-dotted pigmentation pattern on its wings. We identified upregulated or downregulated differentially expressed genes (DEGs) in the pigmentation area around a campaniform sensilla (cs), a tip of a wing vein (vt). We also identified upregulated or downregulated DEGs in the area where <i>wingless</i> gene is overexpressed (wg).
DOI: 10.6084/m9.figshare.19706506.v1
title: Data --- Hot & Cold Ions Density, 100% O+, Hodges

description: This is the set of simulation data including the energetic ion density and the associated charge-exchange byproduct cold protons density, for the 3-phase 72 hours idealized storm. The energetic heavy ion density is set to be 100% O+, under the Hodges 1994 neutral geocorona model.
DOI: 10.17632/2w3ckb8knw
title: Gel pictures - Kinases expression in E. Coli

description: This dataset includes SDS-PAGE pictures of expression and purification of EGFR-KD, AurKA-KD and MKK3 using specialized bacterial strains. The findings indicate the effects of expression conditions (temperature, inducer concentration and induction time) on soluble expression. The findings were submitted as a manuscript for peer review and this paragraph will be updated to cite it for access.
DOI: 10.17632/z3f8hsttxb
title: Hausa Speech Dataset

description: This is a Hausa speech Dataset recorded in three different locations which are: Nile University audio studio, News broadcasting studio, and Quiet rooms at different homes.
DOI: 10.6084/m9.figshare.13591535.v1
title: COVID_Study_Italy_0405

description: In the frame of Semiotic Cultural Psychosocial Theory, the study examines the meanings of being online during the COVID-19 pandemic, based on narratives from Italian college students. Content analysis was used to map the Dimensions of Meaning (DS) characterizing the texts; ANOVA to examine (dis)similarities in DS related to sociodemographic characteristics and Internet connotations (IC); Pearson’s correlations to examine relationships between DS and well-being. Two main DS emerged: being online in daily life (‘rupture’/‘continuity’) and Internet functions during pandemic (‘health emergency’/‘daily activities’). Findings suggest that Internet use impacts IC and well-being depending on meanings attributed to being online.
DOI: 10.6084/m9.figshare.16556655.v1
title: abgenbank_sequence.tsv

description: Nanobody sequences from AbGenBank
DOI: 10.6084/m9.figshare.21383760.v1
title: Gynandropsis gynandra genome assembly v3.0 - Hoang et al., 2023. Plant Cell. https://doi.org/10.1093/plcell/koad018

description: Gynandropsis gynandra genome assembly v3.0 - Supplemental Data - supporting the findings in "<strong>The </strong><em><strong>Gynandropsis gynandra</strong></em><strong> genome provides insights into whole-genome duplications and the evolution of C4 photosynthesis in Cleomaceae", </strong>Hoang et al. 2023. Plant Cell. https://doi.org/10.1093/plcell/koad018
DOI: 10.6084/m9.figshare.29161781.v1
title: train.zip

description: Dataset source https://www.spinesegmentation-challenge.com/It is a segmented dataset with a data format of nii.gz. Segmented magnetic resonance T2 lumbar sagittal plane, with a total of 20 categories including S, L5, L4, L3, L2, L1, T12, T11, T10, T9 vertebral bodies and intervertebral discs L5/S, L4/L5, L3/L4, L2/L3, L1/L2, T12/L1, T11/T12, T10/T11, T9/T10
DOI: 10.6084/m9.figshare.8309708.v2
title: REAP-seq protein and mRNA counts

description: Protein count data were acquired from https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM2685243, file GSM2685243_protein_2_PBMCs_matrix.txt.gz, and processed into csv format.<br>Aligned bam file was acquired from https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM2685238, file mRNA_2_PBMCs_possorted_genome_bam.bam.<br><code>velocyto</code> processing:<code>velocyto run (bam directory)/mRNA_2_PBMCs_possorted_genome_bam.bam(transcriptome directory)/genes/genes.gtf</code>
DOI: 10.17632/3m6f42982y
title: Spectral Signature Taxonomy

description: A spectrometer is used to capture spectral data from plant leaves. By utilizing advanced embedded filtering technology, this spectroscopy integrates up to eight wavelength-selective sensors within a compact 9x9mm matrix. Spanning a wavelength range of 400 to 1100 nm, the electromagnetic spectrum is segmented into eight distinct bands, facilitating the detection and classification of plant diseases.
DOI: 10.17632/78864km3bx
title: Influence of enzyme concentration on the Michaelis-Menten constant: A new theory for isolated cases

description: The classical Michaelis-Menten equation assumes that the Michaelis constant (Km) is independent of enzyme concentration. However, this study presents a novel theoretical framework suggesting that Km increases with enzyme concentration due to electrostatic and steric effects influencing substrate binding. By analyzing kinetic data and mathematical modeling, we demonstrate that traditional approximations such as the quasi-steady-state assumption (QSSA) and reactant stationary approximation (RSA) may not fully describe enzymatic behavior under varying enzyme concentrations. Our findings suggest a fundamental revision in enzyme kinetics, with potential applications in metabolic regulation and drug development. The implications extend to the design of enzyme inhibitors, particularly in therapeutic strategies targeting metabolic pathways in diseases such as cancer and autoimmune disorders. This paradigm shift challenges conventional enzymology and provides new perspectives on enzyme-substrate interactions.
DOI: 10.6084/m9.figshare.1152811.v2
title: Estimation of Global Network Statistics from Incomplete Data

description: <strong>Twitter Reply Networks</strong> We apply our techniques to Twitter reply networks. These networks are constructed from tweets we collected via Twitter gardenhose API service between September 9, 1998 and November 17, 1998. Each network is weighted and directed, whereby entries in the (i,j) cell of the adjacency matrix represent the number of replies directed from node i to node j. Note that there is no correlation between node labels from week to week. For example, the individual represented by node 1 in Week 1 is not the same individual represented by node 1 in Weeks 2, 3 and so forth. Each network is presented as a Matlab (.mat) file. Please cite as: Bliss, C. A., Danforth, C. M. & P. S. Dodds. (2014). Estimation of Global Network Statistics from Incomplete Data. PLOSONE (Accepted). For additional data, see: http://www.uvm.edu/~storylab/share/papers/bliss2014a/data.html