cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5082220.v1
title: Data from Interacting stressors and the potential for adaptation in a changing world: responses of populations and individuals

description: To accurately predict the impact of environmental change, it is necessary to assay effects of key interacting stressors on vulnerable organisms, and the potential resiliency of their populations. Yet, for the most part, these critical data are missing. We examined the effects of two common abiotic stressors predicted to interact with climate change, salinity and temperature, on the embryonic survival and development of a model freshwater vertebrate, the rough-skinned newt (<i>Taricha granulosa</i>) from different populations. We found that salinity and temperature significantly interacted to affect newt embryonic survival and development, with the negative effects of salinity most pronounced at temperature extremes. We also found significant variation among, and especially within, populations, with different females varying in the performance of their eggs at different salinity–temperature combinations, possibly providing the raw material for future natural selection. Our results highlight the complex nature of predicting responses to climate change in space and time, and provide critical data towards that aim.
DOI: 10.17632/8gb9r2yhfc
title: Labeled dataset for bee detection and direction estimation on beehive landing boards

description: Bee detection/segmentation datasets contain directories of images and labels. Detection dataset contains 7200 frames. Segmentation dataset contains 2300 cropped images of bees labeled with triangle shape for direction vector estimation. Labels are saved in yolo format. Frame resolution 1920x1080. Frames were captured 30 cm above 8 different beehive landing boards. Time: June-July 2023. Location: Lithuania.

In version no. 5, labels were corrected in detection dataset.
Pose directory was added for bee direction estimation. Annotations in pose dataset were saved in yolo format.
If bee is fully visible then first point [px1, py1] marks a head, second point [px2, py2] marks stinger.
If only part of bee is visible then first point marks the front, second point marks the back.
Annotation format in pose dataset: [class=0, x, y, w, h, px1, py1, px2, py2]
Pose dataset contains total 400 frames of 8 beehives entrances. 50 frames per beehive.

In version no. 6, the ramp detection dataset was added. It contains 156 images.
Annotation format in ramp detection dataset: [class=0, x, y, w, h, px1, py1, px2, py2, px3, py3, px4, py4]
Here, x, y, w, h are coordinates of the bounding boxes and px1, py1, px2, py2, px3, py3, px4, py4 are coordinates of 4 keypoints: 1 - top left, 2 - top right, 3 - bottom right, 4 - bottom left.

The tracking and behavior datasets represent annotated MP4 files with tracks of bees during foraging, defense, fanning, and washboarding. It contains 17162 tracks, 21946 frames.
The tracks and behavior are annotated only for the bees that are in the entrance zone. The bounding boxes are normalized to the width and height of the frame.
Annotation format in tracking dataset: [frame-id, track-id, bb-left, bb-top, bb-width, bb-height].
Annotation format in behavior dataset: [frame-id, track-id, bb-left, bb-top, bb-width, bb-height, class-for, class-def, class-fan, class-wash]
DOI: 10.17632/pk3gf5f77n
title: Data for: Does biochar improve soil water retention? A systematic review and meta-analysis

description: Summary of data extracted from 82 studies that investigated biochar's effect on soil bulk density and water retention characteristics.
DOI: 10.17632/rxxch9vw59
title: BanglaLekhaImageCaptions

description: This dataset consists of images and annotations in Bengali. The images are human annotated in Bengali by two adult native Bengali speakers. All popular image captioning datasets have a predominant western cultural bias with the annotations done in English. Using such datasets to train an image captioning system assumes that a good English to target language translation system exists and that the original dataset had elements of the target culture. Both these assumptions are false, leading to the need of a culturally relevant dataset in Bengali, to generate appropriate image captions of images relevant to the Bangladeshi and wider subcontinental context. The dataset presented consists of 9,154 images.
DOI: 10.17632/2rjd8zy9rv
title: Development of the Digital Parental Mediation Scale - Survey Data (2020)

description: The goal of this study was to develop and validate a measure of parents’ attitudes about the mediation of digital technology. An internet-based survey was administered to 554 parents of children and adolescents in the US. Exploratory bifactor analysis revealed one general factor and four digital-specific factors: discursive mediation, restrictive mediation and monitoring, participatory mediation, and mediation by modeling. Confirmatory factor analysis supported a bifactor model of the Digital Parental Mediation Scale (DPMS); the general factor explained shared variance related to parenting style and skills in general, while the mediation factor represented digital-specific attitudes. Mediation factors were predicted differentially by perceived parenting efficacy and influence, parental worry about technology, child age, and parent and child technology use patterns.
DOI: 10.6084/m9.figshare.10072898.v2
title: Raw data - factors associated with depression

description: This raw data is a result of the questionnaire completed by 230 participants (pregnant adolescents) in the study of "predictive statistical model for the factor associated with prenatal depression among pregnant adolescents in Maha sarakham province, Thailand". <br><br>All terms, initials, and numbers presented in the raw data are explained in "Raw data dictionary" file.<br>The published article can be found on http://dx.doi.org/10.12688/f1000research.21007.1
DOI: 10.6084/m9.figshare.19160894.v1
title: Best classification performance of the XGBoost classifier based on channel information in handcraft features

description: This excel file contained best classification performance of the XGBoost classifier based on channel information in handcraft features.
DOI: 10.6084/m9.figshare.21382705.v1
title: Prevalence and impact of urinary symptoms on quality of life during the last month of pregnancy

description: Abstract Introduction Adaptations of the maternal organism can adversely affect the lower urinary tract, leading to urinary symptoms with impact in quality of life (QoL). Objective To determine the prevalence of urinary symptoms and the impact of urinary incontinence (UI) on QoL during the last month of pregnancy. Methods Retrospective cross-sectional study, envolving 96 women in the immediate postpartum period personally interviewed about urinary symptoms and QoL during their last four weeks of gestation. Women were divided into two groups according to the number of pregnancies: G1 = 1 pregnancy (n = 41) and G2 = ≥ 2 pregnancies (n = 55). Those who reported the presence of stress urinary incontinence (SUI) and/or urge incontinence (UUI) were also administered the International Consultation on Incontinence Questionnaire - Short Form (ICIQ-SF). Results The most common symptoms were nocturia (90.6%), urgency (82.3%), urinary frequency (71.9%) feeling of incomplete emptying (62.5%) and SUI and/or UUI (53.1%) with no differences between groups. Only the complaint of SUI in cough was significantly higher in G2 (p = 0.04). There was no difference on QoL between groups based on ICIQ-SF scores among those with UI (53.1%), however G1 reported serious impact and G2 very serious impact. Conclusion Almost all women reported some type of urinary symptom and the most prevalent were nocturia, urgency, pollakiuria, feeling of incomplete emptying and SUI and/or UUI. SUI was more prevalent among women with two or more pregnancies and during cough were significantly higher. Regardless of the number of pregnancies, the presence any type of UI had a negative impact on QoL.
DOI: 10.6084/m9.figshare.23614119.v1
title: M00212

description: This dataset contains GWAS summary file generated from sputum metagenomic data for COPD patients.
DOI: 10.6084/m9.figshare.28902638.v1
title: Supplementary Materials for JAPPL-00332-2025

description: Figure S1. Flowchart of screening and randomization of ITP patients. Figure S2. Specific effects of platelet counts and age on sleep latency, sleep disturbances, use of sleep medication, and subjective sleep quality. Note: (a-b, d) At platelet counts below 50×109/L, higher scores for sleep latency, sleep disturbances, and subjective sleep quality are observed across all age groups. (c) For platelet counts below 50×109/L, individuals older than 30 show a higher distribution of sleep medication scores (due to the small sample size and infrequent use of sleep medication among patients, this may not be representative). Figure S3. Specific contributing factors to sleep disturbances include insufficient sleep. Figure S4. Serotonin levels in the blood circulation between healthy individuals and ITP patients. Note: Serotonin (5-HT) levels in ITP patients are significantly lower than in healthy individuals (P&lt;0.001).
DOI: 10.11583/dtu.19722160.v2
title: Dataset for: "Settling velocity of microplastic particles having regular and irregular shapes"

description: -The "settlingVelocity.mat" is a MATLAB binary workspace file containing the dimensions, density, and settling velocity (mean and standard deviation) of all microplastic particle groups, with their time series of measured vertical particle positions. -The "settlingVelocity.xlsx" is an Excel worksheet listing the particle number, shape/particle code, material, dimensions, characteristic length scales, Corey shape factor, sphericity, density, settling velocity (mean and standard deviation), Reynolds number, and drag coefficient of all microplastic particle groups with the density and kinematic viscosity of water. -Example experimental videos for each microplastic particle group are provided with the naming convention "Particle_X(Shape).mp4", where “X” refers to the particle group number and “Shape” is the particle shape (e.g. sphere, circular disk, cube, etc.). Please note that the videos are low-quality when using the preview. For optimal quality, it is suggested to download the videos and play the files directly.
DOI: 10.17632/48ympv8jjf
title: Indian Currency Dataset

description: New Indian currency denomination dataset is not available online so a new dataset is created using Moto X-Play mobile camera has a 21MP camera. The size of all the currency images in the dataset which are captured in landscape mode is 5344×3006. Whereas the size of all the currency images in the dataset which are captured in portrait mode is 3006×5344. A total of 4657 images are captured to create the dataset. All the currency notes which are acceptable in the market are used like old and new 10 rupee notes, old 20 rupee notes, old and new 50 rupee notes, old and new 100 rupee notes, new 200, 500, and 2000 notes. To improve the dataset size data augmentation is applied to the currency note images. The different types of augmentations used are Zoom, Rotate90, Rotate270, Tilt, Distortion, and Flip. Dataset after data augmentation contains a total of 11657 images.
DOI: 10.17632/sbsg2tnfn6
title: Field simulation test data

description: energy dissipation rate, erosion amount, peak basal sheer stress and velocity
DOI: 10.6084/m9.figshare.19115972.v1
title: Dataset for: Integrative Metabolomic and Proteomic Signatures Define Clinical Outcomes in Severe COVID-19

description: <strong>Metabolomics and proteomics data for the paper "Integrative Metabolomic and Proteomic Signatures Define Clinical Outcomes in Severe COVID-19".</strong> <br> <strong>Paper link</strong>: Buyukozkan*, Alvarez-Mulett*, Racanelli* et al., https://www.cell.com/iscience/fulltext/S2589-0042(22)00884-7 <br> <strong>Code repository:</strong> https://github.com/krumsieklab/covid-omics
DOI: 10.6084/m9.figshare.24021465.v1
title: Australian saltmarsh and sparsely vegetated saltmarsh map version 1.0

description: The dataset contains a national map of saltmarsh and sparsely vegetated saltmarsh (also known as saltflats) ecosystems produced via a classification of Landsat 8 images.The map output of this classification and associated map data files are described below:1. JCU_Australia-saltmarsh-extent_v1-0.tiff: Contains a national map of saltmarsh ecosystems produced via a classification of Landsat 8 images. Pixel value is either 0 (Non Saltmarsh) or 1 (Saltmarsh).2. JCU_Australia-saltmarsh-probability_v1-0.tiff: Contains the associated probability map associated with the saltmarsh map. Pixel value represents percentage probability with values ranging from 0 – 100 (%).3. JCU_Australia-saltflat-extent_v1-0.tiff: Contains a national map of saltflats produced via a classification of Landsat 8 images. Pixel value is either 0 (Non Saltflats) or 1 (Saltflats).4. JCU_Australia-saltflat-probability_v1-0.tiff: Contains the associated probability map associated with the saltflat map. Pixel value represents percentage probability with values ranging from 0 – 100 (%).Suggested citation: Navarro, A., Canto, R., M., Lyons, M. & Murray, N.J. (2023) Australian saltmarsh and sparsely vegetated saltmarsh map version 1.0. James Cook University, Townsville. DOI: 10.6084/m9.figshare.24021465
DOI: 10.17632/vd4g9xjt4b
title: Financial data of banks listed in the Dhaka Stock Exchange (DSE)

description: This dataset contains the financial information of publicly traded commercial banks listed in the Dhaka Stock Exchange (DSE) of Bangladesh through 2006 to 2017. All data are compiled from the bank annual reports. The currency of this dataset is Bangladeshi Taka (BDT).
DOI: 10.6084/m9.figshare.107055.v1
title: Code archive accompanying paper "High-Resolution Finite Volume Modeling of Wave Propagation in Orthotropic Poroelastic Media"

description: This is an archive of the code used to generate the results in the paper, "High-Resolution Finite Volume Modeling of Wave Propagation in Orthotropic Poroelastic Media," by Grady I. Lemoine, M. Yvonne Ou, and Randall J. LeVeque. All results presented in the paper can be obtained from the code stored here. This code requires version 4.6 of the CLAWPACK finite volume methods package to run.
DOI: 10.6084/m9.figshare.25825984.v1
title: Dataset of <i>P</i><i>. latus </i>genome

description: Genome annotation file of <i>P. latus </i>(Broad mite)
DOI: 10.6084/m9.figshare.29049620.v2
title: <b>Investigation of the Phytoplankton Spring Bloom in the Oslofjord by Individual-Species and Common Garden Experiments</b>

description: Data and scripts connected to the master's thesis: <b>Investigation of the Phytoplankton Spring Bloom in the Oslofjord by Individual-Species and Common Garden Experiments</b>
DOI: 10.6084/m9.figshare.3564099.v1
title: Appendix A. Basal area increment, ring-width indices, soil chemistry data, and climate data across all sites.

description: Basal area increment, ring-width indices, soil chemistry data, and climate data across all sites.
DOI: 10.6084/m9.figshare.7951181.v3
title: Krause et al. (2019) Earth's Future

description: Output is from three dynamic vegetation models (LPJ-GUESS, LPJ and CABLE-POP) driven by three combinations of climate change and land-use change scenarios (SSP1xRCP26, SSP3xRCP60, SSP5xRCP85). The output also includes simulations in which either land use or climate and CO2 were kept constant from 2014 on to isolate the effects of future land-use change and climate change. Output variables are total carbon pools, NPP, evapotranspiration, surface January and July albedo and total runoff for four different time periods (2015, 2050, 2070, 2090, 20-year averages). Spatial resolution is 0.5° (LPJ-GUESS and LPJ) or 1° (CABLE-POP).<br>
DOI: 10.6084/m9.figshare.24125679.v1
title: NV center characteristic spectrum

description: Characteristic NV center spectrum as observed in our lab for initial testing of (ensemble) diamond sample
DOI: 10.6084/m9.figshare.5970823.v1
title: Linguistic laws in chimpanzee gestural communication

description: Datasets to calculate compression in chimpanzee gesture types and sequences
DOI: 10.6084/m9.figshare.25342924.v1
title: Fine-tuning Pre-trained Antibody Language Models for Antigen Specificity Prediction

description: AbstractAntibodies play a crucial role in the adaptive immune response, with their specificity to antigens being a fundamental determinant of immune function. Accurate prediction of antibody antigen specificity is vital for understanding immune responses, guiding vaccine design, and developing antibody-based therapeutics. In this study, we explore the effect of fine-tuning pre-trained antibody language models in improving binding specificity prediction to SARS-CoV-2 spike protein and influenza hemagglutinin. We fine-tuned four pre-trained antibody language models on labeled data specific to these antigens and demonstrated that fine-tuned language model classifiers exhibit enhanced predictive accuracy compared to classifiers trained on pre-trained model embeddings. Additionally, we investigated the change of model attention activations after fine-tuning to gain insights into the molecular basis of antigen recognition by antibodies. Furthermore, we applied the fine-tuned models to BCR repertoire data related to influenza and SARS-CoV-2 vaccination, demonstrating their ability to capture changes in repertoire following vaccination. Overall, our study highlights the effect of fine-tuning on pre-trained antibody language models as valuable tools to improve antigen specificity prediction.CodeAll code used for model training and testing is available on bitbucket https://bitbucket.org/kleinstein/projects/src/master/Wang2024/ . <br>An archived version of the Bitbucket repository is included in <i>code.zip</i>.DataThe following files are included in <i>data.zip</i><br><i>S_FULL.parquet</i>: Sequence and labels for S binding prediction (full-length).<br><i>S_CDR3.parquet</i>: Sequence and labels for S binding prediction (CDR3 only).<br><i>HA</i><i>_FULL</i><i>.parquet</i>: Sequence and labels for HA binding prediction (full-length).<br><i>HA</i><i>_FULL</i><i>.parquet</i>: Sequence and labels for HA binding prediction (CDR3 only).<br><i>S_repertoires.parquet</i>: Repertoires used for S binding prediction<br><i>HA_repertoires.parquet</i>: Repertoires used for HA binding prediction<br>
DOI: 10.6084/m9.figshare.13530929.v1
title: SuperMat

description: A growing number of papers are published in the area of superconducting materials science. However, novel text and data mining (TDM) processes are still needed to efficiently access and exploit this accumulated knowledge, paving the way towards data-driven materials design. Herein, we present SuperMat (Superconductor Materials), an annotated corpus of linked data derived from scientific publications on superconductors, which comprises 142 articles, 16052 entities, and 1398 links that are characterised into six categories: the names, classes, and properties of materials; links to their respective superconducting critical temperature (Tc); and parametric conditions such as applied pressure or measurement methods. The construction of SuperMat resulted from a fruitful collaboration between computer scientists and material scientists, and its high quality is ensured through validation by domain experts. The quality of the annotation guidelines was ensured by satisfactory Inter Annotator Agreement (IAA) between the annotators and the domain experts. SuperMat includes the dataset, annotation guidelines, and annotation support tools that use automatic suggestions to help minimise human errors.
DOI: 10.6084/m9.figshare.21701417.v1
title: Supplementary Material for: Domains for a Comprehensive Geriatric Assessment of Older Adults with Chronic Kidney Disease: Results from the CRIC Study

description: Introduction: A comprehensive geriatric assessment (CGA) tailored to the chronic kidney disease (CKD) population would yield a more targeted approach to assessment and care. We aimed to identify domains of a CKD-specific CGA (CKD-CGA), characterize patterns of these domains, and evaluate their predictive utility on adverse health outcomes. Methods: We used data from 864 participants in the Chronic Renal Insufficiency Cohort aged ≥55 years and not on dialysis. Constituents of the CKD-CGA were selected a priori. Latent class analysis informed the selection of domains and identified classes of participants based on their domain patterns. Predictive utility of class membership on mortality, dialysis initiation, and hospitalization was examined. Model discrimination was assessed with C-statistic. Results: The CKD-CGA included 16 domains: cardiovascular disease, diabetes, five frailty phenotype components, depressive symptoms, cognition, five kidney disease quality of life components, health literacy, and medication use. A two-class latent class model fit the data best, with 34.7% and 65.3% in the high- and low-burden of geriatric conditions classes, respectively. Relative to the low-burden class, participants in the high-burden class were at increased risk of mortality (aHR=2.09; 95% CI: 1.56, 2.78), dialysis initiation (aHR=1.63; 95% CI: 1.06, 2.52), and hospitalization (aOR=2.00; 95% CI: 1.38, 2.88). Model discrimination was the strongest for dialysis initiation (C-statistics=0.86), and moderate for mortality and hospitalization (C-statistics=0.70 and 0.66, respectively). Conclusion: With further validation in an external cohort, the CKD-CGA has the potential to be used in nephrology practices for assessing and managing geriatric conditions in older adults with CKD.
DOI: 10.6084/m9.figshare.27100795.v2
title: Susastho adolescent Dataset_18.02

description: Significant challenges are present in the development of Bangladesh, with adolescents being the most vulnerable among them. Their vulnerability is partly a predisposition wherein prevailing attitudes are themselves wrapped in taboo and secrecy about sexual, reproductive, and mental health This cultural reluctance impedes open discussion, leaving adolescents without crucial knowledge for their well-being. To address this, there is a plan to develop a chatbot to meet adolescents' informational needs.To build this chatbot, a dataset specifically focused on adolescents has been collected in the domains of Sexual, Reproductive, and Mental Health (SRMH). The goal of this dataset is to develop a conversational agent in Bengali that will help address adolescents' knowledge gaps on these topics and serve as a bridge to enhance understanding within this group. The dataset is qualitative rather than quantitative as it needs to be a source of information and acts as a knowledge base for the chatbot as the chatbot needs to answer queries about SRMH in Bengali. We scrapped the data using manual methods and it had web, domain expert consultation, user consultation, and crowdsourcing as sources. Furthermore, the dataset was preprocessed by domain experts in a Q/A format and queries vs information format. Also, strict ethical guidelines were followed to curate the dataset and it was done with obtaining approval from the UIU (United International University) ethical approval committee.The dataset is divided into two key domains: Sexual & Reproductive Health and Mental Health. Sexual Reproductive Health consists of a total of 1966 data and Mental Health consists of 470 data. These data were augmented later for a total of 7278 data of which 5849 were of Sexual Reproductive Health. The percentage of raw data for Sexual & Reproductive and Mental Health is 80.7% to 19.3% respectively. Furthermore, the percentage of augmented data for SRMH is 80.4% to 19.6% respectively. This clearly shows that we have a skewed distribution and the dataset is imbalanced.<br>
DOI: 10.6084/m9.figshare.1258799.v1
title: ASH Figshare Data

description: PONE-D-14-36012 10.1371/journal.pone.0115329 Raw data from above manuscript