cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17603/ds2-qxv7-v259
title: Rensselaer Polytechnic Institute Centrifuge Experiments of the Seismic Performance of Sheet Pile Walls in Liquefiable Soils
title: in LEAP-GWU-2022 Experiments:  Seismic Performance of Sheet Pile Walls in Liquefiable Soils

description: Four centrifuge tests (RPI2, RPI3, RPI4, RPI5) were conducted at Rensselaer Polytechnic Institute to evaluate the seismic response of sheet-pile retaining structures in liquefiable soils for the 2022 Liquefaction Experiments and Analysis Project (LEAP-GWU-2022).
description: As part of the Liquefaction Experiments and Analysis Projects (LEAP - an international collaboration among several institutions with expertise and capabilities in centrifuge modeling, constitutive modeling, and numerical modeling) LEAP-2022 investigated the seismic performance of sheet pile walls in liquefiable soils.  The results of twenty centrifuge model tests, performed as part of a round robin test program, are shared in this archive. The datasets produced by the model tests are published as six separate experiments in this archive (one experiment per centrifuge facility). Each "experiment" includes a few model tests and each model test includes between one and three destructive shaking events. All of the tests modeled a sheet pile wall supporting a liquefiable soil (Ottawa F-65 sand and Silica sand).  The tests covered a range of ground motion intensities and a range of relative densities to define the median response and the sensitivity of the response to relative density and shaking intensity. The six centrifuge facilities involved in this test program included Ehime University (Japan), Korea Advanced Institute of Science & Technology (ROK), National Central University (Taiwan), Rensselaer Polytechnic institute (USA), University of Cambridge (UK), and Zhejiang University (PRC).  For each "experiment", a presentation file (video), prepared for LEAP-GWU-2022 workshop, is also included.  The presentations describe the centrifuge experiments in each participating centrifuge facility and the observed responses in details. A Web application for visualization of LEAP-GWU-2022 centrifuge data and their comparisons with user-generated numerical simulations is provided in the Code Project (PRJ-4245) published in Design-Safe.
DOI: 10.17603/ds2-wqkk-tn91
title: TTUKa Deployment for Hurricane Delta (2020)
title: in TTUKa Measurements from the 2020 Hurricane Season

description: Raw radar measurements from the TTUKa radars during the landfall of Hurricanes Laura and Delta in 2020.
description: Raw TTUKa radar measurements of Delta at landfall.
DOI: 10.17603/ds2-zb18-ws58
title: Wind Tunnel Aeroelastic Model Tests of a Super-Tall Building with External Guywire Support

description: The data set shared herein is related to the test results of a set aeroelastic experiments, carried out in the wind tunnel of SOH Wind Engineering LLC. in Williston, VT (USA). The dynamic wind response of an aeroelastic super-tall building model with external guy wire support (bracing) was examined.  The wind tunnel data are made available to the research community.
DOI: 10.17603/ds2-e7s5-b025
title: Centrifuge Test on Bentonite Clay - Test UCLA JZB01
title: in Soil-Foundation-Structure Interaction Effects on the Cyclic Failure Potential of Silts and Clays

description: This experiment tested three structures resting on a fine-grained soil layer consisting of non-plastic silt blended with bentonite. A sequence of earthquake ground motions was applied to the model container. Measurements included acceleration, displacement, pore pressure, bending strain, and axial strain.
description: Earthquake-induced ground failure has resulted in billions of dollars of damage during recent earthquakes. Soils can be broadly characterized as exhibiting either "sand-like" or "clay-like" behavior with respect to strength loss during earthquakes. This project focuses on cyclic failure of "clay-like" soils, which are less well understood than "sand-like" soils. Cyclic failure of fine-grained soils are often constrained to the regions beneath structures, and not in the free-field soils away from the structures, indicating that soil-foundation-structure interaction plays an important role. This project utilizes centrifuge model testing to study cyclic failure of fine-grained soils beneath structures. This research has produced publicly accessible datasets containing all of the experimental measurements and metadata required for users to make sense of the data.
DOI: 10.17603/ds2-9vz8-7r76
title: A Scoping Literature Review: Cultural Competence for Hazards and Disaster Research

description: In the field of hazards and disaster research, which often involves rapid reconnaissance assessments in unfamiliar cultural and social contexts, cultural issues have been exacerbated by the increasing frequency and intensity of disasters, which propel more researchers into the field and into contexts where they may lack community-based cultural knowledge. In quick response research, in particular, rarely is there time or adequate resources for individual researchers or research teams to properly prepare for new cultural contexts where they will study affected populations. The challenges associated with hazards and disaster researchers conducting these types of reconnaissance studies have come under increased ethical scrutiny, as technological advancements have simultaneously allowed for new and different types of data collection.
 
Through a systematic review of the cultural competence literature, this project (1) examines existing cultural competence strategies, interventions, tools, plans, and training protocols as applicable for hazards and disaster researchers; (2) introduces a comprehensive framework for building cultural competence for hazards and disaster researchers; and (3) identifies gaps and high-priority research areas to advance cultural competence among members of the research community. This research argues that applying a cultural competence framework in hazards and disaster research offers the ability to improve interplay between researchers and participants (disaster survivors, emergency practitioners, and other service agencies) in order to better serve the individuals, families, and communities most affected by natural hazards, social inequalities, and consequent disasters.
 
This dataset includes all the publications for this systematic literature review, which were published from January 1, 1960 to March 20, 2018 in English, including journal articles, books, book chapters, and grey literature (governmental and non-governmental organization reports).
DOI: 10.17603/ds2-wqgn-nk91
title: StEER: Hurricane Otis Annotated Media Repository
title: in StEER - Hurricane Otis

description: This annotated media repository is a supplement to StEER’s Preliminary Virtual Reconnaissance Report (PVRR). The repository is a visual catalog of geolocated photographic evidence, organized by different hazard and structural classes, and annotated with team member interpretations and analyses.
description: This project encompasses the products of StEER's Level 1 and Level 2 responses to this event: Preliminary Virtual Reconnaissance Report (PVRR) with corresponding Media Repository and the Early Access Reconnaissance Report (EARR).
DOI: 10.17603/ds2-xcc1-7g16
title: ISROC Dataset for: Boulder coastal deposits at Favignana Island rocky coast (Sicily, Italy): Litho-structural and hydrodynamic control
title: in Inundation Signatures on Rocky Coastlines (ISROC) Global Coastal Boulder Deposits Datasets Version 1

description: This document contains standardized data as an Excel and NC file and explanatory notes for "Boulder coastal deposits at Favignana Island rocky coast (Sicily, Italy): Litho-structural and hydrodynamic control." The project includes 81 coastal boulder deposits from storm waves in Italy. Boulders and sockets in Favignana Island were compared to determine the origin of the coastal boulders on the rock platform. The boulders originated from the platform and were deposited by several storms.
description: This project is a collection of datasets on studies about coastal boulder deposits worldwide. Each document is a unique dataset that contains data from a published study. The document's name reflects the name of the associated paper, and all authors of papers are given credit in the respective document. Each dataset's data is standardized into an ISROC-formatted Excel and NC File. Also, every dataset has explanatory notes, which contain a data dictionary explaining data parameters and appropriate units, Some datasets have the raw data given to ISROC by the paper's authors. By creating a database in the public domain, ISROC hopes to promote academic collaboration in the field. ISROC, an NSF-funded research network, funds this project.
DOI: 10.17603/ds2-4der-1f10
title: USF Research Experiences for Undergraduates Weather Climate and Society (REU WCS): Research Products

description: This data page is dedicated to the University of South Florida REU addressing "Weather, Climate, and Society". On this landing page, you can find published work produced as part of the REU with student collaborators in addition to research conducted by the PI, Dr. Jennifer Collins, on the 2020 virtual REU experience in light of the COVID-19 pandemic. PLEASE ENSURE YOU ARE VIEWING THE MOST RECENT VERSION OF THIS PAGE BY CLICKING THE DROPDOWN MENU ABOVE.
DOI: 10.17603/ds2-584f-vz32
title: 2023 Social Science Extreme Events Research (SSEER) Network
title: in Social Science Extreme Events Research (SSEER) Network Data, Survey Instrument, and Annual Census

description: This dataset includes information regarding  1,620 social science researchers who signed up for the Social Science Extreme Events Research (SSEER) network between July 8, 2018 and December 31, 2023. Researchers’ information is collected via an online survey that consists of 19 questions and takes approximately 7 minutes to complete. The envisioned audience for this data and other information includes those who are interested in learning more about the composition of the social science hazards and disaster research workforce, the events that they study, and their skills and expertise.
description: This project includes a survey instrument, data, and annual census reports from the National Science Foundation (NSF)-funded Social Science Extreme Events Research (SSEER) network, which is headquartered at the Natural Hazards Engineering Research Infrastructure (NHERI) CONVERGE facility at the Natural Hazards Center at the University of Colorado Boulder. The SSEER network, which was launched in 2018, was formed, in part, to respond to the need for more specific information about the status and expertise of the social science hazards and disaster research workforce. The mission of SSEER is to identify and map social scientists involved in hazards and disaster research in order to highlight their expertise and connect social science researchers to one another, to interdisciplinary teams, and to communities at risk to hazards and affected by disasters. Ultimately, the goals of SSEER are to amplify the contributions of social scientists and to advance the field through expanding the available social science evidence base. To see the SSEER map and to learn more about the SSEER initiative, please visit:  https://converge.colorado.edu/research-networks/sseer. All social and behavioral scientists and those in allied disciplines who study the human, economic, policy, and health dimensions of disasters are invited to join this network via a short online survey. This DesignSafe project includes: (1) the SSEER survey instrument; (2) de-identified data, which is updated annually as new researchers join the SSEER network and returning members update their information; and (3) SSEER annual census reports. These resources are available to all who are interested in learning more about the composition of the social science hazards and disaster workforce. SSEER is part of a larger ecosystem of NSF-funded extreme events research and reconnaissance networks designed to help coordinate disciplinary communities in engineering and the sciences, while also encouraging cross-disciplinary information sharing and interdisciplinary integration. To learn more about the networks and research ecosystem, please visit: https://converge.colorado.edu/research-networks/.
DOI: 10.17603/ds2-arw3-9z86
title: 2020 Social Science Extreme Events Research (SSEER) Network
title: in Social Science Extreme Events Research (SSEER) Network Data, Survey Instrument, and Annual Census

description: This dataset includes information regarding 1,230 social science researchers from around the world who signed up for the Social Science Extreme Events Research (SSEER) network between July 8, 2018 and December 31, 2020. Researchers’ information is collected via an online survey that consists of 19 questions and takes approximately 7 minutes to complete. The envisioned audience for this data and other information includes those who are interested in learning more about the composition of the social science hazards and disaster research workforce, the events that they study, and their skills and expertise.
description: This project includes a survey instrument, data, and annual census reports from the National Science Foundation (NSF)-funded Social Science Extreme Events Research (SSEER) network, which is headquartered at the Natural Hazards Engineering Research Infrastructure (NHERI) CONVERGE facility at the Natural Hazards Center at the University of Colorado Boulder. The SSEER network, which was launched in 2018, was formed, in part, to respond to the need for more specific information about the status and expertise of the social science hazards and disaster research workforce. The mission of SSEER is to identify and map social scientists involved in hazards and disaster research in order to highlight their expertise and connect social science researchers to one another, to interdisciplinary teams, and to communities at risk to hazards and affected by disasters. Ultimately, the goals of SSEER are to amplify the contributions of social scientists and to advance the field through expanding the available social science evidence base. To see the SSEER map and to learn more about the SSEER initiative, please visit:  https://converge.colorado.edu/research-networks/sseer. All social and behavioral scientists and those in allied disciplines who study the human, economic, policy, and health dimensions of disasters are invited to join this network via a short online survey. This DesignSafe project includes: (1) the SSEER survey instrument; (2) de-identified data, which is updated annually as new researchers join the SSEER network and returning members update their information; and (3) SSEER annual census reports. These resources are available to all who are interested in learning more about the composition of the social science hazards and disaster workforce. SSEER is part of a larger ecosystem of NSF-funded extreme events research and reconnaissance networks designed to help coordinate disciplinary communities in engineering and the sciences, while also encouraging cross-disciplinary information sharing and interdisciplinary integration. To learn more about the networks and research ecosystem, please visit: https://converge.colorado.edu/research-networks/.
DOI: 10.15468/dl.ghkdaw
title: Occurrence Download

description: A dataset containing 83851 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Coordinate reprojected, The taxon concept ID was not used in backbone matching, The taxon ID was not used in backbone matching, Coordinate rounded, Continent derived from coordinates, Country derived from coordinates)",
 "OccurrenceStatus is Present",
 "TaxonKey is Gyps fulvus (Hablizl, 1783)",
 "Year 1970-2015"
 ]
}

 The dataset includes 83851 records from 259 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001280-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z5753g
title: Occurrence Download

description: A dataset containing 137822 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Month is one of (January, February, March, April, May, June, July, August, September, October, November, December)",
 "OccurrenceStatus is Present",
 "TaxonKey is Chelonia mydas (Linnaeus, 1758)",
 "Year 2010-2020"
 ]
}

 The dataset includes 137822 records from 225 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001037-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nespfq
title: Occurrence Download

description: A dataset containing 15904 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Helenium autumnale L."
 ]
}

 The dataset includes 15904 records from 343 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009734-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.txd5cq
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Taxus calcicola"
 ]
}

 The dataset includes 15 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029692-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qja8cw
title: Occurrence Download

description: A dataset containing 410756 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is Thailand",
 "DatasetKey is iNaturalist Research-grade Observations"
 ]
}

 The dataset includes 410756 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003146-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tfdp4n
title: Occurrence Download

description: A dataset containing 430 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Arbutus occidentalis"
 ]
}

 The dataset includes 430 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003152-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17430848
title: A dataset for "Novel height estimation formula that accounts for the effects of aging based on lumbar length measurements in postmortem CT images."

description: The data required to reproduce the results of the paper has been uploaded.
DOI: 10.5281/zenodo.17677851
title: A dataset for "Novel height estimation formula that accounts for the effects of aging based on lumbar length measurements in postmortem CT images."

description: The data required to reproduce the results of the paper has been uploaded.
DOI: 10.5281/zenodo.17086974
title: Forward and reverse weathering drive sedimentary porewater carbon cycling across contrasting diagenetic regimes in a large river estuary
DOI: 10.5281/zenodo.17086975
title: Forward and reverse weathering drive sedimentary porewater carbon cycling across contrasting diagenetic regimes in a large river estuary
DOI: 10.15468/dl.4nvnz4
title: Occurrence Download

description: A dataset containing 10334 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "License is one of (CC0 1.0, CC-BY 4.0, CC-BY-NC 4.0)",
 "TaxonKey is Urticaceae"
 ]
}

 The dataset includes 10334 records from 166 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003154-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16997784
title: Detrital zircon data supports stronger, inland-tracking hurricanes during the Miocene Climatic Optimum, Maryland USA
DOI: 10.5281/zenodo.17625669
title: Detrital zircon data supports stronger, inland-tracking hurricanes during the Miocene Climatic Optimum, Maryland USA
DOI: 10.15468/dl.v9h7z3
title: Occurrence Download

description: A dataset containing 933 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Haloxylon ammodendron"
 ]
}

 The dataset includes 933 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003155-251120083545085/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.30681534
title: Additional file 1 of Bioinformatic analysis and validation of candidate genes in the eutopic endometrium reveal differential expressions in diffuse adenomyosis, endometrioma, and their co-existence

description: Supplementary material 1. Fig. S1. Workflow of the study design. The left panel in the image represents bioinformatic analysis of transcriptomic datasets on adenomyosis, endometriosis and controls. The right panel shows the patient recruitment criteria for validation of the bioinformatic findings. GEO: Gene Expression Omnibus, BMI: body mass index, MUSA: Morphological Uterus Sonographic Assessment, TVUS: transvaginal ultrasound, qRT-PCR: quantitative reverse transcription polymerase chain reaction. Fig. S2. Box plots for the adenomyosis and endometriosis datasets. Box plots demonstrate the distribution of normalized datasetsadenomyosis vs. healthy subjectsfrom GSE78851 datasetadenomyosis vs. healthy subjectsfrom GSE7307 dataset andendometriosis vs. healthy subjectsfrom the GSE7307 dataset. X and Y-axis represent the patients selected and their gene expression levels, respectively.Fig. S3. Representative transvaginal ultrasoundimages of patients.adenomyosis with asymmetric myometrial thickening, irregular endometrial–myometrial junctionmyometrial cystand heterogeneous myometriumendometriomaco-existent adenomyosis–endometriosis showing asymmetric myometrial wallscontrol with uniform endometrium–myometrium thickness Fig. S4. Full blots of the proteins of interest. The blots consist of four lanes showing four groups of patients: Adenomyosis- A, co-existent adenomyosis–endometriosis- AE, endometriosis- E and controls- C. The ladder showing the corresponding molecular weights are shown.-The blots showing the bands of target proteins and-showing the bands of beta-actin