cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/yrwd336rkz
title: Prediction of Heart Attack

description: The dataset consists of 1763 observations, each representing a unique patient, and 12 different attributes associated with heart disease. This dataset is a critical resource for researchers focusing on predictive analytics in cardiovascular diseases.

Variables Overview:
1. Age: A continuous variable indicating the age of the patient.
2. Sex: A categorical variable with two levels ('Male', 'Female'), indicating the gender of the patient.
3. CP (Chest Pain type): A categorical variable describing the type of chest pain experienced by the patient, with categories such as 'Asymptomatic', 'Atypical Angina', 'Typical Angina', and 'Non-Angina'.
4. TRTBPS (Resting Blood Pressure): A continuous variable indicating the resting blood pressure (in mm Hg) on admission to the hospital.
5. Chol (Serum Cholesterol): A continuous variable measuring the serum cholesterol in mg/dl.
6. FBS (Fasting Blood Sugar): A binary variable where 1 represents fasting blood sugar &gt; 120 mg/dl, and 0 otherwise.
7. Rest ECG (Resting Electrocardiographic Results): Categorizes the resting electrocardiographic results of the patient into 'Normal', 'ST Elevation', and other categories.
8. Thalachh (Maximum Heart Rate Achieved): A continuous variable indicating the maximum heart rate achieved by the patient.
9. Exng (Exercise Induced Angina): A binary variable where 1 indicates the presence of exercise-induced angina, and 0 otherwise.
10. Oldpeak (ST Depression Induced by Exercise Relative to Rest): A continuous variable indicating the ST depression induced by exercise relative to rest.
11. Slope (Slope of the Peak Exercise ST Segment): A categorical variable with levels such as 'Flat', 'Up Sloping', representing the slope of the peak exercise ST segment.
14. Target: A binary target variable indicating the presence (1) or absence (0) of heart disease.

Descriptive Statistics:
The patients' age ranges from 29 to 77 years, with a mean age of approximately 54 years. The resting blood pressure spans from 94 to 200 mm Hg, and the average cholesterol level is about 246 mg/dl. The maximum heart rate achieved varies widely among patients, from 71 to 202 beats per minute.

Importance for Research:
This dataset provides a comprehensive view of various factors that could potentially be linked to heart disease, making it an invaluable resource for developing predictive models. By analyzing relationships and patterns within these variables, researchers can identify key predictors of heart disease and enhance the accuracy of diagnostic tools. This could lead to better preventive measures and treatment strategies, ultimately improving patient outcomes in the realm of cardiovascular health
DOI: 10.6084/m9.figshare.1387732.v1
title: S2 Dataset Plant Species

description: Supporting information for Table 1: Botanical composition estimated before first cut in 2007 on fields, which were cut, cut and grazed in combination or only grazed on dairy farms with organic production system (ORG) and short-term (ORG-SG) or long-term grassland management (ORG-LG) and dairy farms with conventional production system (CON) and short-term (CON-SG) or long-term grassland management (CON-LG)
DOI: 10.6084/m9.figshare.19640052.v1
title: Data set of molecular properties used to train HIPNN+SEQM

description: This dataset was used to train the published HIPNN+SEQM model. Code can be found here: https://github.com/lanl/PYSEQM https://github.com/lanl/hippynn
DOI: 10.6084/m9.figshare.24243511.v1
title: Data for manuscript entitled "Photonic chip-based low noise microwave oscillator"

description: Data for the figures in the manuscript entitled "Photonic chip-based low noise microwave oscillator".<br>William Groman , Qing-Xin Ji , Joel Guo , Megan Kelleher , Dahyeon Lee , Takuma Nakamura , Charles McLemore , Pedram Shirmohammadi , Samin Hanifi , Haotian Cheng , Naijun Jin , LUE WU , Samuel Halladay , Yizhi Luo , Zhaowei Dai , Warren Jin , Junwu Bai , Yifan Liu , Wei Zhang , Chao Xiang , Vladimir Iltchenko , Owen Miller , Andrey Matsko , Steven Bowers , Peter Rakich , Joe C. Campbell , John Bowers , Kerry Vahala , Franklyn Quinlan , Scott Diddams
DOI: 10.6084/m9.figshare.29105219.v1
title: Differential Non-Conservative Behaviors of Dissolved Black Carbon Along A Major River-Estuary-Shelf Continuum

description: This dataset includes the water physicochemical properties and DBC concentrations and compositions along the Changjiang-Estuary-Shelf Transect.
DOI: 10.17632/jps788rr2c
title: Regional characteristics of heritage houses, Tibetan houses in the northeastern region of Aba prefecture, Classification Datasets

description: Interpreting regional characteristics of heritage houses based on 3D digital landscape and point cloud deep learning - Take Tibetan houses in the northeastern region of Aba prefecture as an example: Classification Datasets
DOI: 10.6084/m9.figshare.14371613.v1
title: R tutorial: How to create a resistance surface, compute effective distances, and create connectivity maps?

description: R tutorial associated to the paper: An overview of computational tools for preparing, constructing and using resistance surfaces in connectivity research.Unzip the archive, and follow the instruction in the file "script_how_to_create_resistance_surfaces.r"
DOI: 10.6084/m9.figshare.16713448.v1
title: COVID-19 Twitter Dataset

description: The current dataset contains Tweet IDs for tweets mentioning "COVID" (e.g., COVID-19, COVID19) and shared between March and July of 2020.<br><b>Sampling Method</b>: hourly requests sent to Twitter Search API using Social Feed Manager, an open source software that harvests social media data and related content from Twitter and other platforms.<br><b>NOTE:</b> 1) In accordance with Twitter API Terms, only Tweet IDs are provided as part of this dataset. <br>2) To recollect tweets based on the list of Tweet IDs contained in these datasets, you will need to use tweet 'rehydration' programs like Hydrator (https://github.com/DocNow/hydrator) or Python library Twarc (https://github.com/DocNow/twarc). <br>3) This dataset, like most datasets collected via the Twitter Search API, is a sample of the available tweets on this topic and is not meant to be comprehensive. Some COVID-related tweets might not be included in the dataset either because the tweets were collected using a standardized but intermittent (hourly) sampling protocol or because tweets used hashtags/keywords other than COVID (e.g., Coronavirus or #nCoV). <br>4) To broaden this sample, consider comparing/merging this dataset with other COVID-19 related public datasets such as: https://github.com/thepanacealab/covid19_twitter https://ieee-dataport.org/open-access/corona-virus-covid-19-tweets-dataset https://github.com/echen102/COVID-19-TweetIDs
DOI: 10.6084/m9.figshare.21028249.v4
title: MS and NGR data used in cyclostratigraphy analyses, and the magnetostratigraphy and cyclostratigraphy age data

description: The raw data, the linear interpolated data, and detrended data of MS and NGR used for Cyclostratigraphy Analyses, and the magnetostratigraphy and cyclostratigraphy age data.
DOI: 10.6084/m9.figshare.25298857.v1
title: Prophage sequence detection (DBSCAN-SWA)

description: Prophage sequence identification was done using DBSCAN-SWA, a command line software tool developed to predict prophage regions in bacterial genomes
DOI: 10.6084/m9.figshare.6216332.v1
title: Supplementary Material for: Sequence Analysis of Drug Target Genes with Suicidal Behavior in Bipolar Disorder Patients

description: <b><i>Background:</i></b> A number of genes have been implicated in recent genome-wide association studies of suicide attempt in bipolar disorder. More focused investigation of genes coding for protein targets of existing drugs may lead to drug repurposing for the treatment and/or prevention of suicide. <b><i>Methods:</i></b> We analyzed 2,457 DNA variants across 197 genes of interest to GlaxoSmithKline across the pipeline in our sample of European patients suffering from bipolar disorder (<i>N</i> = 219). We analyzed these variants for a possible association with the suicide severity score (ranging from suicidal ideation/plan to serious suicide attempt) from the Schedule for Clinical Assessment in Neuropsychiatry. We conducted tests of individual variants and gene-based tests. <b><i>Results:</i></b> We found a number of DNA variants in the transforming growth factor beta receptor 1 gene (<i>TGFBR1</i>) to be suggestively associated with suicide severity scores (<i>p</i> &lt; 0.005). The gene-based tests also pointed to <i>TGFBR1</i> to be associated with suicide severity (<i>p</i> = 0.0001). However, these findings were not replicated in an independent bipolar disorder sample. <b><i>Conclusions:</i></b> We report no significant association between DNA sequences of drug target genes and suicidal behavior. Additional larger sequencing studies could further interrogate associations between variants in drug target genes and suicidal behavior.
DOI: 10.15468/dl.79qmgv
title: Occurrence Download

description: A dataset containing 1375 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Jasminum fluminense Vell.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1375 records from 88 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013241-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.23301668.v1
title: Genome of Robinia pseudoacacia

description: Chromosome-level genome assembly and population genomics of Robinia pseudoacacia reveal the genetic basis for its wide cultivation
DOI: 10.6084/m9.figshare.25157096.v3
title: Wine consumer behavior New

description: This is bibliographical data retrieved from the Scopus database.
DOI: 10.6084/m9.figshare.27292317.v1
title: Response and sensitivity of urban plants with different seed dispersal modes

description: To check whether the responses of spontaneous plant richness to driving factors differ among dispersal modes, generalized linear mixed effect models (GLMMs) were used to analyze the driving factors of the richness of species with the four seed dispersal modes: anemochory, autochory, hydrochory and zoochory. We fitted a model with species richness as the response variable, using a Poisson distribution and “glmer” function within R package lme4 (version 1.1-35.1) with patch ID nested within site ID, and site ID nested within city ID as random effect (1|patch ID/site ID/city ID). As fixed effects, we used all natural factors, dispersal limitation, and habitat quality described above, as well as the interaction between these factors and seed dispersal modes (hereafter called ‘full model’). To start, the independent variables were standardized and centered to ensure uniform dimensionality. To avoid collinearity, if the correlation coefficient between independent variables was greater than 0.7, only the variable of the highest correlation with the dependent variables was chosen for further modelling. After model construction, the variance inflation factor (VIF) of the model was checked, and variables with VIF greater than 5 were removed from the model sequentially until all variables had a VIF ≤ 5. Residual diagnostics of models was then checked using the “simulateResiduals” function in R package DHARMa (version 0.4.6). The “Anova” function in the R package car (version 3.1-2) was employed to assess both the main effects and interaction effects in the full model. To assess differences in the response to predictor variables between dispersal modes, we used the “emtrends” function in the R package emmeans (version 1.10.1) to compare trend estimates of for the different dispersal modes. To further explore the driving factors within a dispersal mode, we separately ran the same GLMM analysis described above for each group. The “dredge” function in the R package MuMIn (version 1.47.5) was used on each separate model, which created a suite of models with all possible combinations of the initial variables and sorted them according to the Akaike Information Criterion (AIC). We then conducted model averaging on all models with ΔAIC &lt; 2 using the function “model.avg”. We used the “r.squaredGLMM” function in the R package MuMIn to calculate R2, then manually performed variance decomposition to assess the relative contribution of each driving factor and the random effects. We ran all analyses using the software R 4.3.2. <br>
DOI: 10.6084/m9.figshare.28571198.v1
title: Supp fig S8 Verification of deletion of the MR from BMDC

description: Verification of deletion of the MR from BMDCs. Western blot for the MR using an antibody raised to the MR N terminus. A band was detected in the wild type sample of the correct size for MR (Lanes 1 and 2) and substantially reduced expression in the Cre recombinase expressing mice (Lanes 3 and 4). Purified MR from mouse kidney (Lane 5) served as control.
DOI: 10.6084/m9.figshare.28658861.v5
title: Health policy at your fingertips? Mapping and evaluation of existing digital health policy repositories

description: This is a review aimed to map and evaluate digital infrastructure that systematically collate health policy documentation. The review assessed their scope, content, functionality, adherence to FAIR (Findability, Accessibility, Interoperability and Reuse) principles, and user interface and experiences (UI/UX).
DOI: 10.6084/m9.figshare.5241202.v1
title: Erratum: A Promising Therapeutic Approach for Treatment of Posterior Uveitis: Recombinant T Cell Receptor Ligand Protects Lewis Rats from Acute and Recurrent Experimental Autoimmune Uveitis

description: <i>Introduction:</i> Chronic autoimmune uveitis is a major cause of vision loss from intraocular inflammation in humans. In this study we report that a recombinant TCR ligand (RTL220) composed of the α1 and β1 domains of MHC class II molecules linked to the uveitogenic interphotoreceptor retinoid-binding protein (IRBP) 1177–1191 peptide is effective in the suppression of acute and recurrent experimental autoimmune uveitis (EAU). <i>Material and Methods:</i> EAU was induced with IRBP1177–1191 peptide or by adoptive transfer of specific T cells in Lewis rats. The rats received 5 doses of RTL220 subcutaneously every other day starting at the onset of clinic signs of EAU. <i>Results:</i> The administration of RTL220 resulted in a delayed onset and a significant amelioration of the disease severity at clinical levels and showed protection of the retina from inflammatory damage at histological levels. In treatment of recurrent EAU, RTL220 administrated at the first or second onset of clinical disease significantly inhibited EAU, modulated immune responses and provided protection from relapses of uveitis. The systemic and local proinflammatory cytokines were significantly reduced, including IL-17. There was local and systemic increase in IL-10 and reduction in the expression of the proinflammatory chemokines CCL2, CCL3 and CCL5. <i>Conclusions:</i> Our studies demonstrate a successful treatment of acute and recurrent EAU with RTL220, which effectively suppressed the recurrence of inflammation and reversed clinical and histological EAU by altering cytokine and chemokine expression. These findings strongly support a possible clinical application of this novel class of peptide/MHC class II drugs for patients with autoimmune uveitis.
DOI: 10.6084/m9.figshare.7842905.v1
title: Additional file 7: of A large close relative of C. elegans is slow-developing but not long-lived

description: Lifespan_data.tsv. Lifespan data. (TSV 42 kb)
DOI: 10.60893/figshare.apl.25914343.v1
title: Supplementary Information

description: Supplementary Information-revised
DOI: 10.15468/dl.k4mppx
title: Occurrence Download

description: A dataset containing 754 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Poa cusickii Vasey",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 754 records from 58 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013240-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/5pxs4ggx9s
title: Uquantchem: A versatile and easy to use quantum chemistry computational software

description: This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018) Abstract In this paper we present the Uppsala Quantum Chemistry package (UQUANTCHEM), a new and versatile computational platform with capabilities ranging from simple Hartree–Fock calculations to state of the art First principles Extended Lagrangian Born–Oppenheimer Molecular Dynamics (XL-BOMD) and diffusion quantum Monte Carlo (DMC). The UQUANTCHEM package is distributed under the general public license and can be directly downloaded from the code web-site (http://www.anst.uu.se/pesou087/DOWNLOAD-UQU... Title of program: Uquantchem Catalogue Id: AEQY_v1_0 Nature of problem Electronic structure, total energy and force calculation of molecules. Versions of this program held in the CPC repository in Mendeley Data AEQY_v1_0; Uquantchem; 10.1016/j.cpc.2013.09.014
DOI: 10.17632/ds45yy9jrc
title: Mulberry Leaf Dataset

description: Data collection: 
We collected the mulberry leaf cultivars from three regions of Thailand (northern, central, and northeast) that included five provinces in total (Chiang Mai, Phitsanulok, Nakhon Ratchasima, Burriram, and Mahasarakham). DSLR and phone cameras were used to take images with different perspectives from ten mulberry leaf cultivars recorded in the natural environments with different perspectives. The mulberry leaf dataset includes 5,262 images of 10 mulberry leaf cultivars: King Red, King White, Taiwan Maechor, Taiwan Strawberry, Black Austurkey, Black Australia, Chiang Mai 60, Buriram 60, Kamphaeng Saen 42, and Mixed Chiang Mai 60+Buriram 60.

Data description:
The mulberry leaf dataset was curated in 2020 using digital single-lens reflex (DSLR) and smartphone cameras to collect 5,262 images categorized into ten classes existing in diverse environmental conditions. No seasonal considerations were factored in during the data collection; however, all data was collected on the sunny days. There is no existence of external plants in the samples of the mulberry leaves, but there are some natural backgrounds of the brown soil and the mulberry tree, which exist in small proportion relative to the mulberry leaves. The image format of the mulberry leaf dataset exists in JPEG format and has varying resolution sizes. The researcher captured mulberry leaf images from various regions and provinces in Thailand for eight months. The image captures of mulberry leaves were taken from five Thai areas, as shown in Fig. 1. Further, the dataset was annotated by a domain expert responsible for classifying each of the mulberry leaves into their respective classes or categories. The leaves with similar features or properties were stored in a specific folder (class), resulting in ten possible classes. 

Data source location:
The mulberry leaf dataset was collected from three regions of Thailand: northern (Chiang Mai), central (Phitsanulok), and northest (Nakhon Ratchasima, Burriram, and Mahasarakham).

Related research article:
Chompookham, T. & Surinta, O. (2021). Ensemble methods with deep convolutional neural networks for plant leaf recognition. ICIC Express Letters, 15(6), 553-565. DOI: 10.24507/icicel.15.06.553
DOI: 10.6084/m9.figshare.12922543.v2
title: Littermates_uncorfiles

description: Raw, uncorrected segmentation data (.csv files) for immunofluorescence images (fixed samples) for reference littermate embryos (wild type, as well as Fgf4 allelic series) from Saiz et al., eLife 2020;9:e56079 (Figure 1-supplement 1, Figure 2, Figure 2-supplement 1, Figure 5-supplement 1)
DOI: 10.6084/m9.figshare.28830380.v1
title: Supplementary Material.docx

description: Soybean paste as one of the most extensively used traditional fermented condiments in our daily lives. The quality of AQ1 soybean paste has been proven to be related to microbial metabolic activities. However, the effect of different raw materials on the microbial diversity of soybean paste under the same incubation conditions remains unclear. For this, we investigated variation of microbial communities in soybean paste manufactured with two different raw materials (Tartary buckwheat flour and wheat flour) analyzed by amplicon sequencing. The results showed that the dominant bacteria in the two soybean pastes were y-proteobacteria, Cyanobacteria and Bacilli, the dominant fungal were Mucoromycetes, Tremellomycetes, Eurotiomycetes and Saccharomycetes. Bacterial diversity and abundance showed no significant difference in the two soybean pastes; fungal abundance showed no significant difference, whereas fungal diversity differed significantly (P &lt;0.05). Also, Bacterial abundance correlated positively with amino acid nitrogen (AAN) and total acidity (TA) in flour bean paste, while fungal diversity correlated negatively with AAN and TA in buckwheat bean paste. Collectively, raw materials have a significant effect on the microbial community of soybean paste. Besides, these results could provide valuable reference data for enhancing the quality and safety of soybean paste in manufacture.<br>
DOI: 10.6084/m9.figshare.29083505.v1
title: Gridded data of embodied carbon from gravel

description: 5,538,063 records are weight in urban building ECE of gravel in two urban agglomerations from 2000 to 2020 at 500×500m grid scale.
DOI: 10.6084/m9.figshare.29163980.v1
title: FuAR

description: Two files are source of FuAR.
DOI: 10.6084/m9.figshare.10252619.v1
title: Echo in a Single Vibrating Molecule

description: The data corresponds to Figs. 1, 2b, 3-6 in the paper.
DOI: 10.6084/m9.figshare.27198768.v2
title: Vital CEMET statistics based on 1322 multi-element-analysis of 33 metals in spot urine

description: This Excel file presents critical statistics for the Chelated Metal Expression Test (CEMET), conducted after intravenous provocation with GSH, Na-Ca-EDTA, and DMPS. It serves as a reference for evaluating CEMET results and establishing normal ranges for 33 potentially hazardous metals relevant to environmental medicine.<br>The dataset includes 1322 urine multi-element analyses (700 females, 622 males) from a representative Central European population, with metals measured via ICP-MS. The analyzed elements are Ag, Al, As, Au, B, Ba, Be, Bi, Cd, Co, Cr, Cs, Cu, Fe, Gd, Hg, Li, Mn, Mo, Ni, Pb, Pd, Pt, Sb, Se, Sn, Sr, Ti, Tl, U, V, Zn, Zr.<br>The file offers statistical insights for raw metal values (µg/L) and creatinine-corrected values (µg/g CRN) across men, women, and combined data. This includes geometric/arithmetic means (± SD), SEM, minimum/maximum values, percentiles (5th, 25th, 50th, 75th, 95th), detection limits, samples ≥ and &lt; DL.<br><br>Imputation techniques (log-normal or weighted exponential) were applied to address values below detection limits. The dataset represents both raw and imputed values. Creatinine levels (0.25 to 3.5 g/L) helped to minimize dilution bias.
DOI: 10.6084/m9.figshare.7799123.v4
title: ColPortal_microbiome_RawData

description: Microbiome raw data<br>