cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28263860.v1
title: Spatial-temporal Pore Pressure and Stress Evolution associated with the Impoundment of Two Contiguous Reservoirs in Jinsha River, China and Regional Seismicity

description: The file folder is the dataset for the manuscript entitled ''Spatial-temporal Pore Pressure and Stress Evolution associated with the Impoundment of Two Contiguous Reservoirs in Jinsha River, China and Regional Seismicity" by Miao et al., including the water level evolutions of Xiluodu and Xiangjiaba reservoirs, earthquake catalog with the pore pressure and the Coulomb stress change, 3D active faults distribution and the ABAQUS script of the standard model used in this manuscript. The fault data adopts the UTM coordinate system, WGS84, 48 zone. The water level evolution and earthquake catalog is in UTC+8. The Karstic area extends from the surface to a depth of 0 km.
DOI: 10.6084/m9.figshare.16575239.v1
title: Generic Aircraft Carrier Geometry and Data Sets

description: Here, the generic aircraft carrier ship (GAC) geometry file and a reference dataset including measured velocity profiles are shared in the public domain. This reference material is available in the open domain, from the shared metadata link and can be downloaded by the research community: It is intended that the availability of the prototype GAC geometry experimental datasets could be used for code validation purpose and pave the path to advance the research pertaining to the carrier-aircraft dynamic interface environments.
DOI: 10.6084/m9.figshare.19930178.v1
title: TF-C Pretrain SleepEEG

description: - Paper: Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency - Paper link: - Github repo: https://github.com/mims-harvard/TFC-pretraining - Project website: <br> <strong>SleepEEG </strong>contains 153 whole-night sleeping Electroencephalography (EEG) recordings that monitored by sleep cassette. The data is collected from 82 healthy subjects. The 1-lead EEG signal is sampled at 100 Hz. We segment the EEG signals into segments (window size is 200) without overlapping and each segment forms a sample. Every sample is associated with one of the five sleeping patterns/stages: Wake (W), Non-rapid eye movement (N1, N2, N3) and Rapid Eye Movement (REM). <br> <br>
DOI: 10.6084/m9.figshare.27612606.v1
title: Data for "<b>Extracting long-period Love waves (&gt;40 s) from ambient noise using a selection stacking method"</b>

description: This dataset contains dispersion curves, Love wave phase velocity maps, and the list of stations used for "Extracting long-period Love waves (&gt;40 s) from ambient noise using a selection stacking method". In this study, we report that reliable Love waves with periods of 40-80 seconds can be successfully retrieved from ambient noise using a root-mean-square ratio selection stacking (RMSR_SS) method. We further demonstrate that these broadband Love wave signals, retrieved from approximately two years of ambient noise data, can be used to constrain phase velocity maps. The extraction of long-period Love waves from ambient noise provides supplementary data for the study of radial anisotropy in the lithosphere or asthenosphere.
DOI: 10.6084/m9.figshare.14211239.v1
title: mBio_Wang_etal_2020_supplement_TableS5

description: <b>Supplemental Table S5. Gene ontology (GO) terms associated with uniformly expressed genes across the 21 <i>C. albicans </i>isolates. </b>The columns of each page include “GOID”, “GO term”, “Cluster frequency” to indicate the number of genes within the GO term among the 2036 identically expressed genes, “background Frequency” to indicate the total number of 6473 annotated genes in the <i>C. albicans </i>genome assigned to that GO term, “Corrected p-value” “False Discovery Rate”, and “Genes annotated to the term” to define the genes that contribute to the “Cluster Frequency” column. Tabs are broken out by “Component”, “Process”, and “Function”.
DOI: 10.6084/m9.figshare.16574792.v1
title: IDMSS-complete-nomenclature-of-market-shares-and -related-appendixes.zip

description: Complete nomenclature of market share structures, as described in a submitted paper.
DOI: 10.6084/m9.figshare.22683214.v1
title: Database Proyect PSPC1 PI19/01363

description: As some evidence suggests that hypoxia might be an inducer of nuclear paraspeckle formation, we explore whether intermittent hypoxia (IH)-mediated paraspeckle protein-1 (PSPC1) overexpression might contribute to the activation of tumor growth factor (TGF)β-SMAD pathway in patients with obstructive sleep apnea (OSA). This activation would promote changes in intracellular signaling that would explain the increased cancer aggressiveness reported in these patients. Here, we show that patients with OSA exhibit elevated PSPC1 levels both in plasma and in monocytes. Our data suggest that PSPC1 is ultimately delivered to the plasma through its cleavage from OSA monocytes by matrix metalloproteinase-2 (MMP2). In addition, IH promotes PSPC1, TGFβ, and MMP2 expression in monocytes through the hypoxia-inducible factor. Lastly, both PSPC1 and TGFβ induce increased expression of genes that drive the epithelial-to-mesenchymal transition. Our study details the mechanism by which hypoxemia upmodulates the extracellular release of PSPC1 by means of MMP2, such that plasma PSPC1 together with TGFβ activation signaling further promotes tumor metastasis and supports cancer aggressiveness in patients with OSA.
DOI: 10.6084/m9.figshare.29108447.v1
title: FINAL GAMIFICATION MODEL.sav

description: The infusion of gamification into educational settings has emerged as a transformative pedagogical strategy that seeks to amplify student engagement, enhance learning motivation, and elevate academic performance
DOI: 10.6084/m9.figshare.7427879.v2
title: Brgoch Superhard Materials Training Data

description: 2574 (2494) materials used for training regressors that predict shear and bulk modulus. The xlsx file provided consists of the original data used to train models described in reference 1 below. The json.gz file includes structural and composition based data from the Materials Project as well as mpid values. Several entries have been marked suspect in this file as they could not be properly cross referenced on the Materials Project database. An additional goup of materials have been marked suspect due to large discrepancies in shear and bulk modulus from the source file and current MP values.<br>Data is available as Monty Encoder encoded JSON and as a XLSX file. Recommended access method is with the matminer Python package using the datasets module.<br>Note on citations: If you found this dataset useful and would like to cite it in your work, please be sure to cite its original sources below rather than or in addition to this page.<br>Dataset discussed in:<br>Machine Learning Directed Search for Ultraincompressible, Superhard Materials Aria Mansouri Tehrani, Anton O. Oliynyk, Marcus Parry, Zeshan Rizvi, Samantha Couper, Feng Lin, Lowell Miyagi, Taylor D. Sparks, and Jakoah Brgoch Journal of the American Chemical Society <strong>2018</strong> <em>140</em> (31), 9844-9853 DOI: 10.1021/jacs.8b02717 <br>
DOI: 10.17632/4fmjjfpmyy
title: Dataset for a publication: "Comparison of Powder-Bed Fusion, Directed Energy Deposition, and Hybrid Additive Manufacturing of Ti6Al4V Components: Microstructure, Corrosion and Mechanical Properties"

description: These data are published as a part of the paper: Comparison of Powder-Bed Fusion, Directed Energy Deposition, and Hybrid Additive Manufacturing of Ti6Al4V Components: Microstructure, Corrosion and Mechanical Properties. The structure and organization of the data are outlined in the readme file.
DOI: 10.17632/j3xy2wz3z2
title: Gut microbiome metagenomic data - oral ingestion of TCE in rats

description: Shotgun sequenced metagenomic data from the gut microbiome of vehicle (olive oil) or trichloroethylene treated rats.
DOI: 10.6084/m9.figshare.15109236.v2
title: Bento spatial AnnData formatted datasets

description: u2os_merfish.h5ad: MERFISH spatial transcriptomics data measuring 135 RNA species, 5 of which are non-targeting controls in U2-OS cells. <br> merfish_processed: Processed version of the "u2os_merfish" dataset, with cells and genes filtered and main subcellular localization pattern analyses precomputed with Bento. <br> seqfish.h5ad: seqFISH+ spatial transcriptomics data measuring almost 10k RNA species in NIH-3T3 mouse fibroblast cells. <br> seqfish+_processed.h5ad: Processed version of the "seqfish" dataset, with cells and genes filtered and main subcellular localization pattern analyses precomputed with Bento.
DOI: 10.6084/m9.figshare.24314029.v2
title: Financial literacy article-data.xlsx

description: Hello,This dataset is for my "Financial Literacy Levels of Primary Mathematics Teachers and Primary Mathematics Teacher Candidates" article sent to "The Social Studies" journal.
DOI: 10.6084/m9.figshare.29145866.v1
title: <b>Empirical Evidence from Chinese Prefecture-Level Panel Data</b>

description: Patronage networks, as quintessential informal institutions, exert ambiguous effects on anti-corruption enforcement efficiency. Employing a tripartite "patron-supervisor-client" framework and prefecture-level panel data (2000-2015), this study reveals their dual role: enhancing general policy implementation while undermining anti-corruption efficacy.
DOI: 10.6084/m9.figshare.12477563.v1
title: Tasmanian devil (Sarcophilus harrisii) whisker growth, position and length data by Attard et al. 2021

description: The R script and data used in Attard <i>et al.</i> 2021 "Whisker growth in Tasmanian devils (<i>Sarcophilus harrisii</i>) and applications for stable isotope studies" published in the journal <i>Ecosphere</i>. Descriptions of each file are provided below.<br><b><br></b><b>R script: </b><b>Tasmanian devil vibrissae growth rate and length</b>This R script contains all code used to analyse data and create figures for the manuscript. The script uses Tasmanian devil whisker growth rate and length data available in csv files 1 to 3. <br><b>File 1: Tasmanian devil stable isotope whisker growth data</b><br><br>Stable isotope data for the longest facial whisker taken from six captive Tasmanian devils. A single whisker was taken per individual. Each whisker was cut into sections starting from the follicle (base) using a scalpel. The sections were standardised to weigh between 0.6 to 0.8 mg (2-8 mm length). The length of each whisker segment was recorded. The base of the whisker represents the date the whisker was removed, and peaks in nitrogen stable isotope values represent separate isotope labelling events, whereby animals were fed enriched isotope-labelled glycine (99% for carbon and 98% for nitrogen). These peaks were used to calculate the increase in whisker length over a unit of time.<br><b>File 2: Tasmanian devil whisker position and length data</b><br>Raw data for intradermal, extradermal and total length of whiskers taken from 13 Tasmanian devils used to assess the arrangement and relative length of mystacial whiskers on the face. Whisker length was taken at all positions on the left and right side of the face for each individual.<br><b>File 3: Asymptotic whisker length of wild Tasmanian devils</b><b><br></b>Raw data used to measure asymptotic length (L<sub>a</sub>) of the longest whisker collected from 617 live wild Tasmanian devils. For each position, estimated intradermal length is the mean intradermal length of 13 preserved Tasmanian devils (see File 2). Extradermal length is the length of the longest whisker cut from live wild Tasmanian devils. Estimated total length is the sum of estimated intradermal length and measured extradermal length of the longest whisker. Asymptotic length is the estimated total length + 1% of the estimated total length.<br><b>File 4: </b><b>Tasmanian devil average growth rate with root estimate</b>Average whisker growth rate is exported from the R script as a csv file. File 3 updates the total length of the whisker for two specimens with whiskers that were cut rather than plucked for the captive stable isotope study by adding the estimated intradermal root length (3.8 mm) of Tasmanian devil whiskers.
DOI: 10.6084/m9.figshare.25927285.v1
title: Relative population-specific acceleration intensity thresholds

description: All information on the research can be found in the corresponding article.
DOI: 10.6084/m9.figshare.28902161.v1
title: scopus EQM 1935e xls4.xls

description: Bibliometric data of Environmental Quality Management 1991-2025 (April).
DOI: 10.6084/m9.figshare.29095895.v1
title: Supplementary Dataset for: Rewiring Climate Governance—Diagnosing Systemic Inertia and Designing Transformative Policy Pathways

description: This dataset accompanies the review manuscript <i>"Rewiring Climate Governance: Diagnosing Systemic Inertia and Designing Transformative Policy Pathways"</i>. It contains all supplementary materials used to systematically analyse structural, discursive, and strategic dimensions of climate governance failure. The data were derived from a qualitative systematic review of 87 peer-reviewed articles, coded using a tripartite Subject–Predicate–Object (SPO) framework.The materials include:Cleaned article datasets by governance layer (structural, discursive, strategic)Term frequency and co-occurrence dataPRISMA screening protocols and eligibility criteriaSearch query logic for SCOPUS databaseConceptual and theoretical coding structuresGrounded theory synthesis visualisations and analytical matricesThese resources are intended to support reproducibility, secondary analysis, and methodological adaptation in climate policy and governance research. All files are formatted for compatibility with RStudio (≥v4.1) and Microsoft Excel (2016+), and are documented to facilitate replication.
DOI: 10.6084/m9.figshare.3570813.v1
title: Containers for portable, productive and performant scientific computing; supporting data and code.

description: This repository contains data, code and images to support the paper:<br>Containers for portable, productive and performant scientific computing, Jack S. Hale, Lizao Li, Chris Richardson, Garth N. Wells.<br>https://arxiv.org/abs/1608.07573<br>This repository is for long-term archival purposes and contains files of the code, data and images used at the time of producing the paper.<br>At the time of publication the same data is replicated on various cloud services linked to in the References section below.<br>
DOI: 10.6084/m9.figshare.8282537.v1
title: Primers used for qPCR reactions from Uncovering a mitochondrial unfolded protein response in corals and its role in adapting to a changing world

description: The Anthropocene will be characterized by increased environmental disturbances, leading to the survival of stress-tolerant organisms particularly in the oceans where novel marine diseases and elevated temperatures are re-shaping ecosystems. These environmental changes underscore the importance of identifying mechanisms which promote stress tolerance in ecologically important non-model species such as reef-building corals. Mitochondria are central regulators of cellular stress and have dedicated recovery pathways including the mitochondrial unfolded protein response, which increases the transcription of protective genes promoting protein homeostasis, free radical detoxification and innate immunity. In this investigation, we identify a mitochondrial unfolded protein response in the endangered Caribbean coral <i>Orbicella faveolata</i>, by performing <i>in vivo</i> functional replacement using a transcription factor (Of-ATF5) originating from a coral in the model organism <i>Caenorhabditis elegans</i>. In addition, we use RNA-seq network analysis and transcription factor-binding predictions to identify a transcriptional network of genes likely regulated by Of-ATF5 which is induced during the immune challenge and temperature stress. Overall, our findings uncover a conserved cellular pathway which may promote the ability of reef-building corals to survive increasing levels of environmental stress.
DOI: 10.6084/m9.figshare.c.3833362_d2.v1
title: Additional file 2 of Common and phylogenetically widespread coding for peptides by bacterial small RNAs

description: Machine learning validation on annotated ORFs. (TXT 8 kb)
DOI: 10.17632/9hz6f62gtk
title: SNT (Simulated Network Traffic Using Mininet and Ryu) DDoS Detection Dataset

description: Research Hypothesis
The primary hypothesis of this research is that machine learning (ML) models can effectively detect Distributed Denial of Service (DDoS) attacks in Software-Defined Networking (SDN) environments by leveraging flow-level network traffic features. The dataset was designed to evaluate ML algorithms' ability to distinguish between normal and malicious traffic under realistic network conditions.

What the Data Shows
This dataset captures detailed flow statistics for normal and malicious network traffic:

Normal Traffic: Simulated regular client-server communications in a realistic data center environment.
Malicious Traffic: Traffic generated by launching DDoS attacks such as ICMP flood, UDP flood, TCP SYN flood, and LAND attack.
The dataset provides labeled traffic data, allowing users to train and test ML models for binary classification (normal vs. DDoS) or multi-class classification (by attack type).

Notable Findings
Balanced Data Distribution: The dataset includes 1,034,669 records:
527,576 benign flows (normal traffic).
507,093 malicious flows (DDoS attacks).
Comprehensive Feature Set:
22 flow-level features, such as protocol type, packet counts, byte counts, and traffic duration, enabling detailed analysis of traffic patterns.
High-Quality Labels: Each flow is accurately labeled for supervised ML tasks, with attack traffic optionally classified by type.
How the Data Was Gathered
Simulation Environment:
Mininet: Used to simulate the network topology with multiple hosts and switches.
Ryu SDN Controller: Managed traffic and collected flow statistics via its flow monitoring feature.
Normal Traffic:
Generated using a Python script that simulated client-server interactions with randomized patterns, mimicking real-world user behavior.
Traffic size distribution was modeled on typical data center workloads.
Malicious Traffic:
Created by launching DDoS attacks (e.g., ICMP flood, UDP flood) using tools like hping3.
Attack patterns were randomized to simulate real-world scenarios.
The traffic was monitored, captured, and exported as a labeled CSV file for analysis.

Interpreting the Data
Labels:
1 for normal traffic.
0 for DDoS traffic (or further classified by attack type).
Features: Each row represents a single flow with detailed attributes such as packet counts, duration, and protocol type.
Use Cases:
Train ML models for DDoS detection.
Analyze traffic patterns for feature importance.
Explore SDN-based security and anomaly detection techniques.
Usage Recommendations
This dataset is ideal for researchers and practitioners working on:

DDoS detection and mitigation strategies.
Network traffic analysis in SDN environments.
Feature engineering for network security tasks.
DOI: 10.17632/p5cj9bg597
title: Mapa dos clubes de futebol em atividade no estado de São Paulo, fundados no período de 1895 à 1914

description: O mapa apresenta os clubes de futebol do estado de São Paulo, fundados no período de 1895 a 1914. A projeção é parte do artigo intitulado, "A situação geográfica da primeira democracia racial no futebol brasileiro", publicado no Boletim Campineiro de Geografia.
DOI: 10.6084/m9.figshare.12199754.v1
title: Wolbachia community acceptance survey

description: De-identified individual level results of baseline (2015) and pre-release (2016) household surveys of community acceptance of <i>Wolbachia </i>mosquito releases as a method for controlling dengue, in the quasi-experimental study intervention area in Yogyakarta, Indonesia. As described in Indriani et al (2020) submitted to Gates Open Research.
DOI: 10.6084/m9.figshare.14559510.v1
title: Data source_FLIB

description: Data source_FLIB
DOI: 10.6084/m9.figshare.22193353.v1
title: Supplementary materials.docx

description: Additional materials for metabonomics data analysis in adults with growth hormone deficiency 1. Eight pathways involved in metabolic and synthetic activities were enriched 2.Correlation analysis between 40 potential differential metabolites and clinical indicators.
DOI: 10.6084/m9.figshare.23648433.v2
title: The potential causal association between systemic lupus erythematosus and endocrine and metabolic disorders in the East Asian population: A bidirectional two-sample Mendelian randomization study

description: <strong>Supplementary Table 1：</strong>Details of 23 SNPs used as IVs for MR analysis of SLE on GD. <strong>Supplementary Table 2：</strong>Details of 25 SNPs used as IVs for MR analysis of SLE on T2DM. <strong>Supplementary Table 3：</strong>Details of 27 SNPs used as IVs for MR analysis of SLE on OP. <strong>Supplementary Table 4：</strong>Details of 7 SNPs used as IVs for MR analysis of GD on SLE. <strong>Supplementary Table 5：</strong>Details of 74 SNPs used as IVs for MR analysis of T2DM on SLE. <strong>Supplementary Table 6：</strong>Details of 35 SNPs used as IVs for MR analysis of OP on SLE. <strong>Supplementary Table 7：</strong>Results of MR analysis for the causal effect of SLE on GD. <strong>Supplementary Table 8：</strong>Results of MR analysis for the causal effect of SLE on T2DM. <strong>Supplementary Table 9：</strong>Results of MR analysis for the causal effect of SLE on OP. <strong>Supplementary Table 10：</strong>Results of MR analysis for the causal effect of GD on SLE. <strong>Supplementary Table 11：</strong>Results of MR analysis for the causal effect of T2DM on SLE. <strong>Supplementary Table 12：</strong>Results of MR analysis for causal effect of OP on SLE. <strong>Supplementary Figure 1: </strong>Scatter plots of causal effect estimates for SLE on GD (A), GD on SLE (B), SLE on T2DM (C), T2DM on SLE (D), SLE on OP (E), OP on SLE (F). <strong>Supplementary Figure 2: </strong>(A) Leave-one-out plot of the estimates from genetically predicted SLE on GD; (B) forest plot of the estimates from genetically predicted SLE on GD; (C) Leave-one-out plot of the estimates from genetically predicted GD on SLE; (B) forest plot of the estimates from genetically predicted GD on SLE. <strong>Supplementary Figure 3: </strong>(A) Leave-one-out plot of the estimates from genetically predicted SLE on T2DM; (B) forest plot of the estimates from genetically predicted SLE on T2DM; (C) Leave-one-out plot of the estimates from genetically predicted T2DM on SLE; (D) forest plot of the estimates from genetically predicted T2DM on SLE. <strong>Supplementary Figure 4:</strong> (A) Leave-one-out plot of the estimates from genetically predicted SLE on OP; (B) forest plot of the estimates from genetically predicted SLE on OP; (C) Leave-one-out plot of the estimates from genetically predicted OP on SLE; (D) forest plot of the estimates from genetically predicted OP on SLE. <strong>Supplementary Figure 5: </strong>Funnel plots of causal effect estimates for SLE on GD (A), GD on SLE (B), SLE on T2DM (C), T2DM on SLE (D), SLE on OP (E), OP on SLE (F).
DOI: 10.6084/m9.figshare.28840370.v1
title: Supplemental Table 5

description: Gene-sets enriched in <i>Pkd1</i><sup>RC/RC </sup>and WT at 1 month
DOI: 10.6084/m9.figshare.19499255.v1
title: patches and local annotations, slide 130, zoom 248x248 um2

description: patches and local annotations: data for slide with ID of the last 3 characters of the file name: local annotations in csv format and a folder with patches at zoom level indicated at the 6th character of the file name
DOI: 10.6084/m9.figshare.19661391.v1
title: Mouse SPCCT

description: Spectral photon-counting CT (SPCCT) images of an ApoE mouse at the first energy channel (7-40 keV).