cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/y8m4669bkn
title: Pharmacokinetic measurements of BRP levels following BRP administration in mice

description: Raw LC-MS data (raw.d files) generated on an Agilent 6470 Triple Quadrupole LC-MS instrument to provide evidence for the pharmacokinetic measurements of BRP peptide following administration in C57BL/6J male mice. Plasma and brains were collected 0, 1,10, 30, or 60 minutes after injection of BRP (10 mg/kg I.P.). By LC-QQQ, we successfully detected endogenous peaks with transitions corresponding to the parent ions (+2 and +3 charge) in mouse plasma and brain co-eluting at 14-15 minutes with the synthesized standard. Data also show the detection of two cleaved fragments from BRP, THRIL and LFNLC, in the plasma.
DOI: 10.6084/m9.figshare.20973643.v1
title: Sequence alignments and phylogenetic trees for Lophiostoma carabassense - Fungal Planet description sheets: 1436-1477 - December 2022

description: Sequence alignments and phylogenetic trees for Lophiostoma carabassense - Fungal Planet description sheets: 1436–1477 - December 2022
DOI: 10.6084/m9.figshare.21286500.v1
title: Supplementary Material for: The Joint Public Health Impact of Family History of Diabetes and Cardiovascular Disease among Adults in the United States: A Population-Based Study

description: <b><i>Introduction:</i></b> Family history is an established risk factor for both cardiovascular disease (CVD) and diabetes; however, no study has presented population-based prevalence estimates of family histories of CVD and diabetes and examined their joint impact on prevalence of diabetes, CVD, cardiometabolic risk factors, and mortality risk. <b><i>Methods:</i></b> We analyzed data from a representative sample of the US adult population including 29,440 participants from the National Health and Nutrition Examination Survey (2007–2018) and assessed self-reported first-degree family history of diabetes and CVD (premature heart disease before age of 50 years) as well as meeting criteria and/or having risk factors for CVD and diabetes. <b><i>Results:</i></b> Participants with joint family history exhibit 6.5 greater odds for having both diseases and are diagnosed with diabetes 6.6 years earlier than participants without family history. Healthy participants without prevalent CVD or diabetes but with joint family history exhibit a greater prevalence of diabetes risk factors compared to no family history counterparts. Joint family history is associated with an increase in all-cause mortality, but with no interactive effect. <b><i>Conclusion:</i></b> Over 44% of the US adult population has a family history of CVD and/or diabetes that is comparable in risk to common cardiometabolic risk factors. This wide presence of high-risk family history and its simplicity of ascertainment suggests that clinical and public health efforts should collect and act on joint family history of CVD and diabetes to improve population efforts in the prevention and early detection of these common chronic diseases.
DOI: 10.6084/m9.figshare.3807564.v2
title: Dual channel respiration data used for the paper: "Measuring and Characterizing the Human Nasal Cycle"

description: Here we provide dual channel respiration data collected and used for the paper: "Measuring and Characterizing the Human Nasal Cycle"We provide 33 files corresponding to 33 subjects. Each file contains data recorded during 24 hours. See READ_ME file for further details.
DOI: 10.17632/3pcn4zf54h
title:  stock market data set

description: Data files such as Python and Excel can be found in the 'Code and Data set' folder. Approximately 3113 records are contained within the excel sheet, with dates ranging from 09-02-2010 to 09-09-2022. In order to collect the data, we used Yahoo Finance (https://finance.yahoo.com). An algorithm is used to clean and predict data in the .py file.
There is an EXCEL file under the folder 'Data' that contains the data for the Reliance Group stock market.
DOI: 10.17632/t7ffy2dfcw
title: Surviving the Fintech Disruption (Replication package)

description: Replication files for "Surviving the Fintech Disruption" by Wei Jiang, Yuehua Tang, Rachel Xiao, and Vincent Yao. Additional information and instructions are provided in the Readme file.
DOI: 10.6084/m9.figshare.20195723.v1
title: Search Strategy - Artificial Intelligence to Improve Antimicrobial Prescribing- A Protocol for a Systematic Review

description: Search Strategy - Artificial Intelligence to Improve Antimicrobial Prescribing- A Protocol for a Systematic Review
DOI: 10.6084/m9.figshare.28173476.v1
title: Updated TCGA glioma classification through integration of molecular data following the 2021 WHO guidelines

description: Resumes the sample classification provided by Method-2021. This 1110 x 5 matrix reports, for each sample, the corresponding histological type currently available on TCGA (“TCGA-histological.type” column), the exact type nomenclature assigned by our method, in accordance with the 2021 WHO CNS taxonomy (“classification.2021_complete.labels” column), as well as the simplified name we attributed (“classification.2021_simplified.labels” column). The WHO-2021 nomenclature terms considered were: “astrocytoma_IDHmut” (if IDHmut without 1p/19qcodel), “olgodendroglioma_IDHmut_1p19qcodel” (if IDHmut with 1p/19q codel), “glioblastoma_IDHwt” (if IDHwt + histological or genetic hallmarks) and “unclassified” (in case of<br>missing information).
DOI: 10.6084/m9.figshare.5124658.v1
title: Supplementary Material for: A Novel Kernel for Correcting Size Bias in the Logistic Kernel Machine Test with an Application to Rheumatoid Arthritis

description: <b><i>Objectives:</i></b> The logistic kernel machine test (LKMT) is a testing procedure tailored towards high-dimensional genetic data. Its use in pathway analyses of case-control genome-wide association studies results from its computational efficiency and flexibility in incorporating additional information via the kernel. The kernel can be any positive definite function; unfortunately, its form strongly influences the test's power and bias. Most authors have recommended the use of a simple linear kernel. We demonstrate via a simulation that the probability of rejecting the null hypothesis of no association just by chance increases with the number of SNPs or genes in the pathway when applying a simple linear kernel. <b><i>Methods:</i></b> We propose a novel kernel that includes an appropriate standardization in order to protect against any inflation of false positive results. Moreover, our novel kernel contains information on gene membership of SNPs in the pathway. <b><i>Results:</i></b> When applying the novel kernel to data from the North American Rheumatoid Arthritis Consortium, we find that even this basic genomic structure can improve the ability of the LKMT to identify meaningful associations. We also demonstrate that the standardization effectively eliminates problems of size bias. <b><i>Conclusion:</i></b> We recommend the use of our standardized kernel and urge caution when using non-adjusted kernels in the LKMT to conduct pathway analyses.
DOI: 10.17632/x6c63j8bv8
title: CYCU pile load test database

description: The CYCU pile load test database consists of actual records of pile load tests collected from various countries around the world. It includes different types of pile foundations such as drilled shafts, drilled shafts with tip-post grouting, barrette piles, and driven piles, tested under various soil conditions and subjected to compression and uplift loading. The database contains actual load–displacement results, available geotechnical parameters, and interpreted capacities derived using various established methods.

Chen, Y.J., Topacio, A., Laveti, S., Jos, M.A.C., and Hsiao, M. (2024). Development and use of CYCU pile load test database. In CRC Press eBooks, 163–212.
DOI: 10.6084/m9.figshare.12736562.v2
title: Pupae behavior

description: This dataset has records on behavior of mosquito pupae (<i>Aedes aegypti</i>) when wriggling and at the water surface and its space use pattern when exposed to non-lethal predation threat from guppy fish (<i>Poecilia reticulata</i>)<br>
DOI: 10.6084/m9.figshare.17306786.v1
title: DAGE 4000Plus Three-point bend test data

description: Raw data from DAGE 4000Plus Three-point bend tests.
DOI: 10.6084/m9.figshare.7375883.v2
title: Advanced Atlas of 80 Bundles in MNI space

description: This is a dataset to be used by the RecoBundles algorithm to automatically extract anatomically relevant bundles from tractograms. RecoBundles is available in DIPY (http://dipy.org). The algorithm is explained in the paper:<br><br>Garyfallidis, Eleftherios, et al. "Recognition of white matter bundles using local and global streamline-based registration and clustering." NeuroImage 170 (2017): 283-297.<br>https://www.ncbi.nlm.nih.gov/pubmed/28712994<br>This dataset is curated from the dataset explained in the following paper:<br>Yeh, Fang-Cheng, et al. "Population-averaged atlas of the macroscale human structural connectome and its network topology." NeuroImage 178 (2018): 57-68.<br>https://www.sciencedirect.com/science/article/pii/S1053811918304324<br>All the bundles and trk (Trackvis) files are in MNI space ICBM 2009a.<br>Do contact the DIPY developers at https://gitter.im/nipy/dipy if you need the bundles at ICBM 2009c space.<br>For the Fornix (F) both left and right sides are included in one file. It is possible to easily separate them if you need to. Send an e-mail to dipy@python.org to learn how.<br>If you use this dataset please cite Garyfallidis et al. 2017 and Yeh et al. 2018 (see above).<br>Happy RecoBundling!<br>
DOI: 10.6084/m9.figshare.13172246.v3
title: 2020 01 03 VID00028 Analysis and Results

description: Typo on date has been corrected.<br>Slide presentation with frame-by-frame, context, and discussion with unambiguous detection and identification of at least two anomalous large non-human primates.<br>For transparency, includes the Java program used for custom frame-by-frame image stabilization, the anchor point data file, and a close up of the anchor point.<br><br>NOTE: The unrelated final GoPro segment from 3 January 2020 is also stored in this folder. See 2020 01 03 Field Notes for the first four segments. Then see 2020 01 09 Field Notes for GoPro video of the next hike starting from a location near to where this video drops off. The full set of GoPro videos provide a wide angle view of the areas surveyed along the primary route taken repeatedly in gathering data on the animals' behavioral patterns.
DOI: 10.6084/m9.figshare.17054564.v2
title: supplementary data for fineSTRUCTURE analysis of Vibrio fluvialis

description: these are supplementary data for fineSTRUCTURE analysis
DOI: 10.17632/hsh6dvv2zj
title: KinBot: Automated stationary point search on potential energy surfaces

description: KinBot is a Python code that automatically characterizes kinetically important stationary points on reactive potential energy surfaces and arranges the results into a form that lends itself easily to master equation calculations. This version of KinBot tackles C, H, O and S atom containing species and unimolecular (isomerization or dissociation) reactions. KinBot iteratively changes the geometry of the reactant to obtain initial guesses for reactive saddle points defined by KinBot’s reaction types, which are then optimized by a third-party quantum chemistry package. KinBot verifies the connectivity of the saddle points with the reactant and identifies the products through intrinsic reaction coordinate calculations. New calculations can be automatically spawned from the products to obtain complete potential energy surfaces. The utilities of KinBot include conformer searches, projected frequency and hindered rotor calculations, and the automatic determination of the rotational symmetry numbers. Input files for popular RRKM master equation codes are automatically built, enabling an automated workflow all the way to the calculation of pressure and temperature dependent rate coefficients. Four examples are included. (i) [1,3]-sigmatropic H-migration reactions of unsaturated hydrocarbons and oxygenates are calculated to assess the relative importance of suprafacial and antrafacial reactions. (ii) Saddle points on three products of gamma-valerolactone thermal decomposition are studied and compared to literature potential energy surfaces. (iii) The previously published propene+OH reaction is reproduced to show the capability of building an entire potential energy surface. (iv) All species up to C4 in the Aramco Mech 2.0 are subjected to a KinBot search.
DOI: 10.17632/rf3bt5f4hd
title: Segregation Energy Spectra of Co in Aluminum Grain Boundaries that span the 5D space of Crystallographic Character

description: This dataset provides segregation energy spectra information for cobalt solute in 7272 aluminum grain boundaries that span the 5D space of crystallographic character. The dataset and some of its characteristics are described in detail in https://doi.org/10.1016/j.actamat.2024.120448. The information about the segregation energy spectra are included in a CSV file. Each GB is identified by a computeID that is listed in the CSV file. The crystallographic character and selected properties for each GB, as well as its structure, are available in another dataset at https://doi.org/10.17632/4ykjz4ngwt, and which is described in an article at https://doi.org/10.1016/j.actamat.2022.118006. Note that the A README file provides a description of the columns of the CSV file.
DOI: 10.6084/m9.figshare.25845490.v1
title: GC-6G

description: GC-6G investigates the impact of different treatment on the gut microbiota in Clostridioides difficile infection. Fecal samples from mice post-infection were processed using Invitrogen with sequencing on the Ion Torrent NGS System. Analysis via Ion Reporter SW (16S) revealed shifts in microbial taxa dynamics over days 1, 3, and 6, shedding light on the potential of probiotics in modulating gut microbiota during C. difficile infection.The identification of the sample GC-6G:<br>G: Denotes the strain ST-104 of Clostridioides difficile.<br>C: Represents timepoint 2, indicating sampling after C. difficile infection.<br>6: Refers to the specific mouse number under investigation.G: Indicates the treatment administered, which in this case without treatment.
DOI: 10.6084/m9.figshare.26301214.v1
title: diabetic

description: diabetic
DOI: 10.6084/m9.figshare.7505777.v1
title: gene-cell expression matrix

description: the scaled gene-cell expression matrix after the batch and cell cycle effects are removed
DOI: 10.17632/rmycjhph5t
title: DATASET OF POLLUTANTS IN ORGANIC AND NON-ORGANIC FOOD-corr

description: Organic and non-organic equivalent corresponding type of foods were assessed for pollutants, 24 polycyclic aromatic hydrocarbons (PAHs), 800 pesticides and 11 heavy metals. In total, 35 samples of sausages and cheeses were tested from three western European countries, Spain, France, and Germany.  With small corrections on smoked and non-smoked samples in Table 1 in comparison to version 1, and light updates.
DOI: 10.17632/wnh653n3xb
title: A study of Villa et al. Unprocessed files

description: Western blots, protein synthesis assays, and soft agar images
DOI: 10.17632/x995snz7p3
title: Cauliflower Leaf Diseases: A Computer Vision Dataset for Smart Agriculture

description: The Cauliflower Leaf Disease Dataset is a curated collection of high-quality images designed for machine learning and deep learning applications in plant disease detection. The dataset comprises 2,661 images categorized into three classes: Healthy (934), Insect Hole (639), and Black Rot (1,088). The images are collected under varying lighting conditions and angles to enhance model generalization.

Key Features:
Healthy Leaves (934): Images of fresh, disease-free cauliflower leaves.
Insect Hole (639): Leaves showing visible insect damage, such as holes caused by pests.
Black Rot (1,088): Leaves affected by Xanthomonas campestris pv. campestris, a bacterial infection causing blackened veins and necrotic lesions.

Applications:
Computer Vision: Image segmentation, feature extraction, and object detection for plant pathology studies.
Machine Learning: Traditional classifiers (SVM, Random Forest) and feature engineering techniques for automated classification.
Deep Learning: Convolutional Neural Networks (CNNs), Transfer Learning (ResNet, VGG, EfficientNet), and Explainable AI (Grad-CAM) to identify disease patterns.
Agricultural Decision Support: Real-time disease monitoring, precision farming applications, and smartphone-based diagnosis for farmers.

This dataset is a crucial resource for researchers working on AI-driven plant disease identification and can contribute to the advancement of precision agriculture and sustainable farming solutions.
DOI: 10.6084/m9.figshare.11808843.v1
title: (PART 3 OF 5) 9 molecular dynamics simulations (500ps 3 x 3 replicates) of coronavirus 2019-nCoV protease unrefined crystal structure in complex with 3 different conformations of lopinavir.

description: See part 1.<br>Part 3 of 5:XHD_LC2b<br>XHD_LC2c
DOI: 10.6084/m9.figshare.22688404.v1
title: GWAS summary data of hypothalamus in UKB non white british population

description: GWAS summary data of hypothalamus in non white british population
DOI: 10.6084/m9.figshare.24803352.v1
title: Integrated Liver Data

description: This item contains the code and data to perform the integrated liver data analysis from the manuscript "<b>Niche-DE: niche differential gene expression analysis in spatial transcriptomics data identifies context-dependent cell-cell interactions</b>"
DOI: 10.6084/m9.figshare.3544538.v1
title: Appendix C. Model selection in the Sociable Weaver and European Dipper case studies.

description: Model selection in the Sociable Weaver and European Dipper case studies.
DOI: 10.6084/m9.figshare.5401525.v4
title: FPS analysis - input - input data

description: These files include the following input for the FPS procedure:<br>1. dye_positions.txt - a table that lists the unique name of the dye attachment point, the structure subunit (template or nontemplate strand, pdb files) to which the dye is conjugated, if it is an acceptor or a donor (A/D), the coarse-grained model used to calculate the dye AV, the dye coarse-grained dimensions (Linker length and width and ellipsoidal radii of fluorophore) and the atom ID (in the PDB file of the subunit) to which the dye is conjugated.2. distances_1_dwells.txt - a table that lists the D-A pairs and their distances, for the distance set classified as <i>RPo state</i>: the unique name of the acceptor attachment point, the unique name of the donor attachment point, the experimental mean D-A distance, the experimental D-A distance error lower boundary and the experimental D-A distance error upper boundary3. distances_2_dwells.txt - a table that lists the D-A pairs and their distances, for the distance set classified as <i>scrunched RPo state</i>The experimental mean D-A distances are shown in Fig. 4
DOI: 10.6084/m9.figshare.9860750.v1
title: Effect of psycho-social support by teachers on improving mental health and hope of adolescents in an earthquake-affected district in Nepal: a cluster randomized controlled trial

description: The data set comprised of baseline and follow data of adolescents from 15 schools in a district affected by earthquake in Nepal.
DOI: 10.17632/rgxgxwb9vc
title: Surveyed and Conducted Household Budget data (between 2014-2015)

description: Kindly, please find "User Guide" file beside the the Published Articles linked to the dataset.
DOI: 10.6084/m9.figshare.20050925.v4
title: Sense of Virtual Community. - Linux Kernel

description: Survey Questionnaire
DOI: 10.6084/m9.figshare.28235333.v1
title: Source_Data.rar

description: Source Data for Main Figures of the paper, the title of the paper is "High strength cellulose fibers enabled by molecular packing".
DOI: 10.6084/m9.figshare.14225111.v1
title: CR1000 Data

description: Data collected by the CR1000-based system.
DOI: 10.6084/m9.figshare.25628700.v2
title: Renewable energy + Weather + Power system blackout (large-scale outage)

description: <b>To use the data in your work, please cite the following references:</b><b>Zhao, J., Li, F. & Zhang, Q. Impacts of renewable energy resources on the weather vulnerability of power systems.</b><b> </b><b><i>Nat Energy</i></b><b> </b><b>(2024). https://doi.org/10.1038/s41560-024-01652-1</b>Please read ‘ReadMe’ for the introduction of all the datasets.The codes related to this work can be found at <i>https://github.com/JinZhaoTCD/NE_WeatherBlackout_Code</i>This repository contains combined weather, renewable energy, and power system blackout (large-scale outage) data of the U.S., developed by Professor Fangxing (Fran) Li at The University of Tennessee, his Research Scientist Jin Zhao (currently Assistant Professor at Trinity College Dublin) and his PhD Qiwei Zhang 2022-2024.This data set will be of interest to you if you conduct power system resilience studies, such as weather-impacted system operations and blackouts in renewable penetrated power grids. We organized and filtered over 2000 real-world bulk system blackout events, the corresponding daily weather data, and renewable (solar and wind) penetration levels across the 48 continental U.S. states from January 2001 to December 2020.Users can access the developed data set for all blackout information including the time and dates, event reasons, event intensities (duration, affected customer number, demand loss), weather conditions, and renewable penetration levels.
DOI: 10.6084/m9.figshare.28523411.v3
title: <sup>Supplementary Tables</sup><sup> for "A ~700-km-long Fossil Tonian Magmatic Arc Belt Hidden within the Yangtze Block’s Interior, South China" </sup><sup>submitted to JGR-Solid Earth</sup>

description: Fossil magmatic arcs preserve important archives of juvenile magmatism, crustal growth and differentiation, thereby aiding in our understanding of continental evolutionary histories. However, some ancient fossil arcs are situated in continental interiors, where they are buried beneath thick cover sequences, making their identification challenging. In this study, we present a dataset of deep boreholes, geochronology, geochemistry, and geophysics to investigate the basement properties and evolution of the Sichuan Basin in the Yangtze Block, South China. These results provide evidence for a large Tonian (ca. 820–770 Ma) magmatic arc belt hidden within the interior of the Yangtze Block. Seven deep boreholes (~3600–6500 m) penetrating into basin basement, together with geochronology and 3D seismic reflection profiles, show extensive Tonian (ca. 820–770 Ma) rhyolite/granites overlain by Ediacaran sediments. Aeromagnetic data reveal a NE-SW-trending, ~700-km-long high positive magnetic anomaly belt (PMAB) across the central Sichuan Basin, indicating the presence of (ultra-) mafic rocks in lower crust. Correspondingly, the Tonian felsic rocks drilled within PMAB range were likely sourced from a juvenile and thickened lower crust based on petrogenetic and geochemical studies. Thus, we interpret the PMAB as a record of mantle-derived melts input, followed by their evolution into granitic melts within the crust. This process was associated with a Tonian arc magmatic front that was once occurred in the Yangtze Block’s interior. Our finding broadens the range of the Tonian continental arc system in the region, reaching at least 400–900 km landward from block’s northwestern margin. Such a broad orogenic system played a vital role in continental evolution, element recycling, and basin formation of the Yangtze Block.