cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14043938
title: BoneMarrow_IdentityPanel.zip

description: README<br>*** Heterogeneity panel (bone marrow cells) ***<br>Due to the low amount of cKit positive cells (progenitor cells) from our isolated neutrophils,we wanted to confirm that the cKit antibody was working properly. The antibodies that we used are CD11b(Vioblue), cKit(BV510), CD62L(FITC), CD81(PE), Ly6g(PerCP),Cxcr4(PE-Vio770), CD106(APC), Cxcr2(APC-Vio770). Compensation was performed prior to each analysis to account for new tubes/batch of antibodies used. Bone marrow cells were analyzed using the MacsQuant10, and gating of population was performed using FlowLogic version 7. A sample sheet is included in the folder to be able to distinguish the different groups.<br>
DOI: 10.6084/m9.figshare.14043938.v1
title: BoneMarrow_IdentityPanel.zip

description: README<br>*** Heterogeneity panel (bone marrow cells) ***<br>Due to the low amount of cKit positive cells (progenitor cells) from our isolated neutrophils,we wanted to confirm that the cKit antibody was working properly. The antibodies that we used are CD11b(Vioblue), cKit(BV510), CD62L(FITC), CD81(PE), Ly6g(PerCP),Cxcr4(PE-Vio770), CD106(APC), Cxcr2(APC-Vio770). Compensation was performed prior to each analysis to account for new tubes/batch of antibodies used. Bone marrow cells were analyzed using the MacsQuant10, and gating of population was performed using FlowLogic version 7. A sample sheet is included in the folder to be able to distinguish the different groups.<br>
DOI: 10.3886/e128941
title: Accounting for non-normal covariates in treatment effects from count regressions

description: This project contains supplementary material for Kiefer & Mayer (2021).<br>Abstract of the manuscript:<br>The effects of a treatment or an intervention on a count outcome is often of interest in applied research. When controlling for additional covariates, a negative binomial regression model is usually applied to estimate conditional expectations of the count outcome. The difference in conditional expectations under treatment and under control is then defined as the (conditional) treatment effect. While traditionally aggregates of these conditional treatment effects (e.g., average treatment effects) are computed by averaging over the empirical distribution, a recently proposed moment-based approach allows for computing aggregate effects as a function of distribution parameters. The moment-based approach makes it possible to control for (latent) multivariate normally distributed covariates and provides more reliable inferences under certain conditions. <br>In this project, we propose three different ways to account for non-normally distributed continuous covariates in this approach: (a) an alternative, known non-normal distribution, (b) a plausible factorization of the joint distribution, and (c) an approximation using finite Gaussian mixtures. A saturated model is used for categorical covariates, making a distributional assumption obsolete. <br><br>For illustration of our methods, we used a subset of the ACTIVE dataset:Tennstedt, Sharon, Morris, John, Unverzagt, Frederick, Rebok, George W., Willis, Sherry L., Ball, Karlene, and Marsiske, Michael. Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE), United States, 1999-2001. Inter-university Consortium for Political and Social Research [distributor], 2010-06-30. https://doi.org/10.3886/ICPSR04248.v3<br>Citation of project publication:Kiefer, C. & Mayer, A. (2021). Treatment effects on count outcomes with non-normal covariates. British Journal of Mathematical and Statistical Psychology. doi: 10.1111/bmsp.12237<br>Along with this project comes our R package CountEffects, which can perform effect analysis according to the three proposed approaches on the dACTIVE.rds file provided in this project. The Supplemental Material to our paper describes how CountEffects can be installed and used.<br><br><br>
DOI: 10.3886/e128941v2
title: Accounting for non-normal covariates in treatment effects from count regressions

description: This project contains supplementary material for Kiefer & Mayer (2021).<br>Abstract of the manuscript:<br>The effects of a treatment or an intervention on a count outcome is often of interest in applied research. When controlling for additional covariates, a negative binomial regression model is usually applied to estimate conditional expectations of the count outcome. The difference in conditional expectations under treatment and under control is then defined as the (conditional) treatment effect. While traditionally aggregates of these conditional treatment effects (e.g., average treatment effects) are computed by averaging over the empirical distribution, a recently proposed moment-based approach allows for computing aggregate effects as a function of distribution parameters. The moment-based approach makes it possible to control for (latent) multivariate normally distributed covariates and provides more reliable inferences under certain conditions. <br>In this project, we propose three different ways to account for non-normally distributed continuous covariates in this approach: (a) an alternative, known non-normal distribution, (b) a plausible factorization of the joint distribution, and (c) an approximation using finite Gaussian mixtures. A saturated model is used for categorical covariates, making a distributional assumption obsolete. <br><br>For illustration of our methods, we used a subset of the ACTIVE dataset:Tennstedt, Sharon, Morris, John, Unverzagt, Frederick, Rebok, George W., Willis, Sherry L., Ball, Karlene, and Marsiske, Michael. Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE), United States, 1999-2001. Inter-university Consortium for Political and Social Research [distributor], 2010-06-30. https://doi.org/10.3886/ICPSR04248.v3<br>Citation of project publication:Kiefer, C. & Mayer, A. (2021). Treatment effects on count outcomes with non-normal covariates. British Journal of Mathematical and Statistical Psychology. doi: 10.1111/bmsp.12237<br>Along with this project comes our R package CountEffects, which can perform effect analysis according to the three proposed approaches on the dACTIVE.rds file provided in this project. The Supplemental Material to our paper describes how CountEffects can be installed and used.<br><br><br>
DOI: 10.3886/e113372v1-79360
title: Replication data for: Tropical Economics

description: Why wealth is systematically lower in the tropics remains a puzzle. We point out that latitude may have fundamental economic consequence because it plays a key role in how countries experience geophysical processes that have economic implications. We demonstrate that annual fluctuations in the El Nino Southern Oscillation (ENSO) leads to hotter and dryer local weather across tropical countries and subsequently to substantial losses in agricultural yields, output, and value-added. If volatility in agricultural production impedes economic growth, the relatively stronger influence of ENSO on the tropics may offer yet another partial explanation for slower historical growth in the tropics.
DOI: 10.3886/e120462v1-79380
title: National Neighborhood Data Archive (NaNDA): Socioeconomic Status and Demographic Characteristics of ZIP Code Tabulation Areas, United States, 2008-2017

description: This dataset contains measures of socioeconomic and demographic characteristics by US ZIP code tabulation area (ZCTA) for the years 2008-2017. Example measures include population density; population distribution by race, ethnicity, age, and income; and proportion of population living below the poverty level, receiving public assistance, and female-headed families. The dataset also contains a set of index variables to represent neighborhood disadvantage and affluence.
description: A ZIP code to ZCTA crosswalk must be used to combine this dataset with ZIP code geocoded data. Such a crosswalk is available on the UDS Mapper website at https://www.udsmapper.org/zcta-crosswalk.cfm. Sample code for merging the UDS Mapper crosswalk with NaNDA datasets is available on the NaNDA repository at https://www.openicpsr.org/openicpsr/project/120088/.
description: ZCTAs in the United States. Smallest Geographic Unit: ZIP code tabulation area
DOI: 10.7277/2vdz-y281
title: Soil Improvement Strategies to Mitigate Impact of Seismic Ground Failures (NEES-2009-0731)

description: &lt;p&gt;&lt;strong&gt;Title: &lt;/strong&gt;Soil Improvement Strategies to Mitigate Impact of Seismic Ground Failures via Novel Integration of Experiment and Simulation (NEES-2009-0731)&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Year Of Curation: &lt;/strong&gt;2014&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Description: &lt;/strong&gt;This award is an outcome of the National Science Foundation 07-506 program solicitation &quot;George E. Brown, Jr. Network for Earthquake Engineering Simulation (NEES) Research&quot; competition. This project is led by the University of Illinois at Urbana-Champaign and includes a subaward to Valparaiso University. Seismically-induced ground failures are a pervasive and growing source of economic loss from earthquakes. Concurrently, the nation&#39;s growing infrastructure needs demand more and larger bridges with increased spans and traffic volumes, thus requiring the use of large, stiff foundations such as large diameter shaft groups or gravity caissons. When seismically-induced ground failures occur, these foundations must contend with large, but unknown lateral forces. A common solution is to conservatively remediate large blocks of soil susceptible to failure, which involves high construction costs, increased construction time, and greater environmental impacts. This project will evaluate novel ground improvement geometries, such as chevrons and arches, to &quot;deflect&quot; laterally moving soil thereby reducing: (1) lateral loads on large foundation elements; (2) ground improvement costs; and (3) time and environmental impacts. This will be accomplished via an innovative integration of centrifuge experiments (performed at the NEES equipment site at Rensselaer Polytechnic Institute) and Self-Learning Simulations (SelfSim) using the Open System for Earthquake Engineering Simulation software. This integration is termed &quot;Simulation-designed Experiment - Experiment-driven Simulation&quot; (SDE-EDS).&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Award: &lt;/strong&gt;http://www.nsf.gov/awardsearch/showAward?AWD_ID=0723697&lt;/p&gt; &lt;p&gt;&lt;strong&gt;PIs &amp; CoPIs: &lt;/strong&gt;Scott Olson, Youssef Hashash&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Dates: &lt;/strong&gt;September 01, 2007 - August 31, 2011&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Organizations: &lt;/strong&gt;University of Illinois at Urbana-Champaign, IL, United States&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Facilities: &lt;/strong&gt;Rensselaer Polytechnic Institute, Troy, NY, United States&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Sponsor: &lt;/strong&gt;NSF - n/a - 0723697&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Keywords: &lt;/strong&gt;liquefaction, Lateral spreading, rigid foundations, Lateral forces&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Publications:&lt;/strong&gt; N/A&lt;/p&gt; &lt;nb:citations&gt;&lt;/nb:citations&gt;
DOI: 10.5281/zenodo.4542796
title: Deep Learning-Based Multimodal Emotion Classification for Music Videos

description: This dataset is related to the paper entity "Deep Learning-Based Multimodal Emotion Classification for Music Videos". The processed file includes audio, video, and face information of each data sample.
description: Music video DB
DOI: 10.5281/zenodo.4542795
title: Deep Learning-Based Multimodal Emotion Classification for Music Videos

description: This dataset is related to the paper entity "Deep Learning-Based Multimodal Emotion Classification for Music Videos". The processed file includes audio, video, and face information of each data sample.
description: Music video DB
DOI: 10.5281/zenodo.4544037
title: CoVaxxy Tweet IDs data set

description: A collection of Tweet IDs related to Covid-19 Vaccines, gathered from Twitter since Jan 4, 2021. Please see https://arxiv.org/abs/2101.07694 for more information.
DOI: 10.6084/m9.figshare.13883765
title: Forensics_FORCAS

description: Dataset for paper - Forensic Coding Patterns to Development Supervised Learning-based Projects
DOI: 10.6084/m9.figshare.13883765.v1
title: Forensics_FORCAS

description: Dataset for paper - Forensic Coding Patterns to Development Supervised Learning-based Projects
DOI: 10.7277/kmxf-tg33
title: Dynamic Passive Pressure on Full-Scale Pile Caps (NEES-2007-0348)

description: &lt;p&gt;&lt;strong&gt;Title:&lt;/strong&gt; Dynamic Passive Pressure on Full-Scale Pile Caps (NEES-2007-0348)&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Year Of Curation: &lt;/strong&gt;2013&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Description: &lt;/strong&gt;For bridges and other structures subject to lateral loadings, passive earth pressure contributes&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Award: &lt;/strong&gt;http://www.nsf.gov/awardsearch/showAward?AWD_ID=0421312&lt;/p&gt; &lt;p&gt;&lt;strong&gt;PIs &amp; CoPIs: &lt;/strong&gt;Travis Gerber, Kyle Rollins&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Dates: &lt;/strong&gt;May 16, 2007 to Present&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Organizations: &lt;/strong&gt;Brigham Young University, UT, United States&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Facilities: &lt;/strong&gt;Brigham Young University, UT, United States,University of California, Los Angeles, CA, United States&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Sponsor: &lt;/strong&gt;NSF - 0421312&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Keywords: &lt;/strong&gt; N/A&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Publications: &lt;/strong&gt;&lt;/p&gt; &lt;p&gt;Colin R. Cummins; Joshua M. Pruett, &quot;Dynamic Passive Pressure on Abutments and Pile Caps&quot;&lt;/p&gt; &lt;p&gt;Colin Cummins, &quot;Behavior of a Full-Scale Pile Cap with Loosely and Densely Compacted Clean Sand Backfill under Cyclic and Dynamic Loadings&quot;&lt;/p&gt; &lt;p&gt;Joshua M. Pruett, &quot;Performance of a Full-Scale Lateral Foundation with Fine and Coarse Gravel Backfills Subjected to Static, Cyclic, and Dynamic Lateral Loads&quot;&lt;/p&gt; &lt;nb:citations&gt;&lt;/nb:citations&gt;
DOI: 10.5281/zenodo.4437076
title: Dissociation of task engagement and arousal effects in auditory cortex and midbrain -- dataset.

description: Single neuron data recorded from auditory cortex and midbrain during a tone detection behavior were used to dissociate effects of generalized arousal (as measured by pupil) and specific task engagement on auditory neural coding. These data are provided open-access accompanying the publication: D. Saderi, Z.P. Schwartz, C.R. Heller, J.R. Pennington, S.V. David. (2020) Dissociation of task engagement and arousal effects in auditory cortex and midbrain. <em>bioRxiv</em>. 2020.06.16.155432. Available at: https://doi.org/10.1101/2020.06.16.155432 The authors request that any work using this data cite this publication.
DOI: 10.6084/m9.figshare.12291281
title: MAGs from ETSP OMZ

description: HQMQ MAGs are being analyzed in unpublished work by Sun & Ward.
DOI: 10.6084/m9.figshare.13837499.v2
title: Fine Temporal Resolution Dataset of Suspended Sediment in Small Watersheds

description: The repository contains streamflow and suspended sediment concentration (SSC) measurements and the generated fine temporal resolution (15-min) timeseries for the period 1982-2002 at 12 stations in the Goodwin Creek, Mississippi, USA.<br>Description of dataset files can be found in ReadMe.txt file.More information about the measurements and methods used for generating the time series is available in:<br><br>Al-Ghorani, N., Hassan, M. A., & Langendoen, E. J. (2021). Spatiotemporal Patterns of Fractional Suspended Sediment Dynamics in Small Watersheds. In preparation.<br>
DOI: 10.7277/tq37-5v53
title: An Innovative Gap Damper to Control Seismic Isolator Displacements in Extreme Earthquakes (NEES-2011-1080)

description: &lt;p&gt;&lt;strong&gt;Title&lt;/strong&gt;: An Innovative Gap Damper to Control Seismic Isolator Displacements in Extreme Earthquakes (NEES-2011-1080)&lt;/p&gt; &lt;p&gt;&lt;b&gt;Year Of Curation: &lt;/b&gt;2015&lt;/p&gt; &lt;p&gt;&lt;b&gt;Description: &lt;/b&gt;This research project will study the use of a special gap damper that is designed to limit the excessive deformation without causing impact and the associated high frequency motions and accelerations. In the design of a seismic base isolation system for a building, an isolator must be allowed to deform a significant amount. At the same time, this deformation must be controlled to avoid structural damage due to its reaching the displacement limit in a rare but possible strong ground motion. The project involves advanced analytical and numerical simulation studies to determine the optimal gap damper characteristics for desired performance such as the size of gap element, the ratio of pre- and post-gap isolation system stiffness, and the energy dissipation demand to reduce displacements without inducing large accelerations in the building. Experimental studies on a standalone damper will be conducted in the Structural Research Laboratory at Auburn University to characterize the energy dissipation properties of the damper. Shaking table studies at the Large Scale Structures Laboratory at the University of Nevada, Reno will validate the effectiveness of the proposed gap damper scheme. This study will provide an experimentally and analytically validated framework leading to reliable performance-based isolator design of buildings under different seismic scenarios.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Award: &lt;/b&gt;http://www.nsf.gov/awardsearch/showAward?AWD_ID=1101105&lt;/p&gt; &lt;p&gt;&lt;b&gt;PIs &amp; CoPIs: &lt;/b&gt;Keri Ryan, Justin Marshall&lt;/p&gt; &lt;p&gt;&lt;b&gt;Dates: &lt;/b&gt;July 01, 2011 - June 30, 2014&lt;/p&gt; &lt;p&gt;&lt;b&gt;Organizations: &lt;/b&gt;University of Nevada-Reno, NV, United States&lt;/p&gt; &lt;p&gt;&lt;b&gt;Facilities: &lt;/b&gt;Auburn University, AL, United States,University of Nevada-Reno, NV, United States&lt;/p&gt; &lt;p&gt;&lt;b&gt;Sponsor: &lt;/b&gt;NSF - n/a - 1101105&lt;/p&gt; &lt;p&gt;&lt;b&gt;Keywords: &lt;/b&gt;nonstructural,fullscale,shaketabletesting&lt;/p&gt; &lt;p&gt;&lt;b&gt;Publications: --&lt;/b&gt;&lt;/p&gt; &lt;nb:citations&gt;&lt;/nb:citations&gt;
DOI: 10.6084/m9.figshare.14044097
title: Ribosomal protein database of Pantoea agglomerans Eh318

description: This work presents the ribosomal protein database of <i>Pantoea agglomerans </i>Eh318<i>. </i>Original data for the work came from the annotated proteome data of the bacterium downloaded from UniProt. Using an in-house MATLAB ribosomal protein database analysis software, the original proteome data file was parsed to extract protein name and amino acid sequence of all ribosomal proteins in the species. The database also includes calculated variables such as number of residues, molecular weight, and nucleotide sequence. Overall, the presented database could serve as a ribosomal protein mass fingerprint for use in microbial identification, or it could be used in fundamental studies seeking to uncover new insights into ribosomal protein biology.
DOI: 10.6084/m9.figshare.14044097.v1
title: Ribosomal protein database of Pantoea agglomerans Eh318

description: This work presents the ribosomal protein database of <i>Pantoea agglomerans </i>Eh318<i>. </i>Original data for the work came from the annotated proteome data of the bacterium downloaded from UniProt. Using an in-house MATLAB ribosomal protein database analysis software, the original proteome data file was parsed to extract protein name and amino acid sequence of all ribosomal proteins in the species. The database also includes calculated variables such as number of residues, molecular weight, and nucleotide sequence. Overall, the presented database could serve as a ribosomal protein mass fingerprint for use in microbial identification, or it could be used in fundamental studies seeking to uncover new insights into ribosomal protein biology.
DOI: 10.7277/1t2a-rz92
title: Mete Sozen's Digital Library

description: &lt;h2&gt; &lt;/h2&gt; &lt;div class="grid"&gt; &lt;div class="col span3"&gt;&lt;img alt="" src="/resources/14152/download/Mete_Sozen_.jpg" style="float: left; height: 450px; width: 280px" /&gt;&lt;/div&gt; &lt;div class="col span9 omega"&gt; &lt;p&gt;This database has been created to preserve documents collected by Dr. Mete A. Sozen during his work as a Professor of Civil Engineering at Purdue University and University of Illinois at Urbana Champaign.&lt;/p&gt; &lt;p&gt;This database is presented as a spreadsheet with each row containing the following information:&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Title:&lt;/strong&gt; Title of the document&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Keywords:&lt;/strong&gt; Words describing the dataset&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Report(s):&lt;/strong&gt; Related documentation&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Source:&lt;/strong&gt; Names of the people who generated the report&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Experiment End Date:&lt;/strong&gt; Publication or acceptance date of the documentation (if available). For documents only having the information of publication year and month, the day was assumed to be the first day of the month to be consistent with the date format. (Format: yyyy-mm-dd)&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Compiled by:&lt;/strong&gt; Names of the people who compiled the data&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Compiled on:&lt;/strong&gt; Date when the dataset was compiled (Format: yyyy-mm-dd)&lt;/p&gt; &lt;p&gt;The database will continue to be improved.&lt;/p&gt; &lt;p&gt;The following databases also contain work done by Dr. Mete A. Sozen during his career:&lt;/p&gt; &lt;p&gt;1) Earthquake Reconnaissance Slides by Drs. Mete A. Sozen and Nathan M. Newmark: &lt;a href="https://datacenterhub.org/resources/240"&gt;https://datacenterhub.org/resources/240&lt;/a&gt;&lt;/p&gt; &lt;p&gt;2) Earthquake Simulation tests: &lt;a href="https://datacenterhub.org/resources/378"&gt;https://datacenterhub.org/resources/378&lt;/a&gt;&lt;/p&gt; &lt;p&gt;3) NEES: Earthquake Simulator Video Archive: &lt;a href="https://datacenterhub.org/resources/258"&gt;https://datacenterhub.org/resources/258&lt;/a&gt;&lt;/p&gt; &lt;p&gt;4) Database of low-rise reinforced concrete buildings with earthquake damage: &lt;a href="https://datacenterhub.org/resources/123"&gt;https://datacenterhub.org/resources/123&lt;/a&gt;&lt;/p&gt; &lt;/div&gt; &lt;/div&gt; &lt;p&gt; &lt;/p&gt; &lt;div class="grid"&gt; &lt;div class="col span3"&gt; &lt;/div&gt; &lt;div class="col span3"&gt; &lt;/div&gt; &lt;div class="col span3"&gt; &lt;/div&gt; &lt;div class="col span3"&gt; &lt;/div&gt; &lt;div class="col span3"&gt; &lt;/div&gt; &lt;div class="col span3"&gt; &lt;/div&gt; &lt;div class="col span3"&gt; &lt;/div&gt; &lt;div class="col span3"&gt; &lt;/div&gt; &lt;/div&gt; &lt;nb:citations&gt;&lt;/nb:citations&gt;