73 Works

Why Iowa? University of Iowa Hawkeye Poll. Data

David P. Redlawsk, Caroline J. Tolbert & Todd Donovan
Data set consists of 63 variables selected from the Why Iowa survey instruments. Survey instruments include a questionnaire conducted March 29-31, 2007, a questionnaire conducted January 5-10, 2008, a caucus attendee poll conducted in 2008, a pre Feb 5 survey conducted Feb 1-4, 2008 and a post Feb 5 survey conducted Feb 7-10, 2008. With the cooperation of the Iowa Democratic and Republican Parties, one survey instrument was placed in each precinct in the state...

Primate Dental Microwear: Cebus Nigritus Robustus (Crested Capuchin)

Robert S. Scott
Data represents scans of tooth samples from the species Cebus Nigritus Robustus (Crested Capuchin). Data files include SUR Files, a .tar archive of 56 .sur files (SURF format used by MountainsMap software) and TFS Files, a tar archive of 1 .tfs files. The .sur files in Cebus_negritus_robustus_sur.tar are the surface mappings for each individual tooth surface scanned. The .tfs files in Cebus_negritus_robustus_tfs.tar describe the view settings for the .sur files.

Whole exome sequencing identifies centrosomal component gene mutations that increase human aneuploid conception risk, supplemental data

Katarzyna M. Tyc, Warif El Yakoubi, Aishee Bag, Jessica Landis, Yiping Zhan, Nathan R. Treff, Richard T. Scott, Xin Tao, Karen Schindler & Jinchuan Xing
This VCF file contains 162,365 SNVs identified across 160 individuals by whole exome sequencing that were used in the study. Allele counts (AC), total allele number (AN), and allele frequencies (AF) for either Low Aneuploidy Rate group (LRG) or High Aneuploidy Rateg group (HRG) were specified in the INFO tags.

Evaluating nanopore sequencing data processing pipelines for structure variation identification, supplemental data

Anbo Zhou, Timothy Lin & Jinchuan Xing
nanopore_03262018.fastq.gzDescription: DNA sample of individual NS12911 was sequenced by Oxford Nanopore (ONT) MinION using flowcell FLO-MIN106D. The library was constructed using ONT 1D Genomic DNA by ligation protocol. Basecalling was performed using ONT¡¯s Albacore 2.0.2 and the reads are provided in the fastq format.CallSetsDescription: Raw SV call outputs from the seven pipelines for the four datasets.Simulation_Chr20Description: Files for simulating nanopore reads from chromosome 20 using NanoSim.

NC350 Hycide 5 Wards Project

Akintola Hanif, Carrie Stetler, Rhys Valmonte, Manuel Acevedo, Stefan Brown, Nema Etebar, Tamara Fleming, Colleen Gutwein, Cesar Melgar, Fabian Palencia, Maria Ameen, Amy Kiger-Williams & Gisel Endara
The 5 Wards series, a project of HYCIDE magazine, explores the diverse landscapes and communities of Newark through photos, interviews with residents and stories about the city’s history and culture. It includes portraits of 25 Newarkers by HYCIDE Editor-in-Chief Akintola Hanif. The series was made possible with funding from Newark Celebration 350.

NC350 Finding Aid

Newark Celebration 350
This is all the metadata for each individual item archived within the Newark Celebration 350 Archive project. It includes information on all photos, videos, documents, digital projects and websites featured in the the exhibit.

NC350 Facebook Archive

No Name Supplied
This is the archive of Newark Celebration 350's Facebook page commemorating the yearlong celebration of Newark’s rich 350-year history by celebrating the talents of its citizenry and its remarkable accomplishments.

NC350 Archived Website

Newark Celebration 350
This is the archive of the Newark Celebration 350 website featuring events and programs from the commemoration of Newark’s 350th Anniversary year.

NC350: Flyers and Posters

No Name Supplied
Newark Celebration 350 (NC350) commemorated Newark’s rich 350-year history by celebrating the talents of its citizenry and its remarkable accomplishments. This is a compilation of flyers and posters from various events and programs hosted through out NC350's commemoration of Newark’s 350th year anniversary.

Promotion of CO Insertion into Metal Alkyl Bonds by Polar Molecules. Rate-Determining Displacement of an Agostic C-H Bond supplementary data

Tian Zhou, Santanu Malakar, Steven L. Webb, Karsten Krogh-Jespersen & Alan S. Goldman
Supplemental data for unpublished PNAS manuscript 201816339.

Incremental and Radical Innovations in Research Libraries: Data

Ronald C. Jantz
In an empirical analysis, this study examined the effects of ambidexterity, organizational structure, and leadership on innovation in research libraries. There is much published literature suggesting the research library must change, quickly and dramatically. These changes will likely take the form of new services, new products and new administrative practices – all of which are potential innovations. Much of the research literature on organizational innovation focuses on the for-profit sector of the economy. Based on...

Colon Crypt Model 060518 C++

Chase Cockrell
C++ code ported from NetLogo code. Colon Crypt Model 110514 G.nlogo written in the application NetLogo. The NetLogo code and model are available at https://doi.org/doi:10.7282/T3KH0QKV. The colon crypt model is described in the publication: Bravo R, Axelrod D. A calibrated agent-based computer model of stochastic cell dynamics in normal human colon crypts useful for in silico experiments. Theoret Biol Med Model. 2013;10:66-89, http://www.tbiomed.com/content/10/1/66

Simple expression domains are regulated by discrete CRMs during Drosophila oogenesis

Nir Yakoby
Three processed, alignment BAM files; three indexing BAI files, one file containing the raw RNA-seq data for all three samples, and an Excel file with the instructions on what was done and how to use the files.

Probability-weighted ensembles of U.S. county-level climate projections for climate risk analysis: Mapping

D. J. Rasmussen, Malte Meinshausen & Robert E. Kopp
Quantitative assessment of climate change risk requires a method for constructing probabilistic time series of changes in physical climate parameters. Here, we develop two such methods, Surrogate/Model Mixed Ensemble (SMME) and Monte Carlo Pattern/Residual (MCPR), and apply them to construct joint probability density functions (PDFs) of temperature and precipitation change over the 21st century for every county in the United States. Both methods produce likely (67% probability) temperature and precipitation projections consistent with the Intergovernmental...

Probability-weighted ensembles of U.S. county-level climate projections for climate risk analysis: OBS

D. J. Rasmussen, Malte Meinshausen & Robert E. Kopp
Quantitative assessment of climate change risk requires a method for constructing probabilistic time series of changes in physical climate parameters. Here, we develop two such methods, Surrogate/Model Mixed Ensemble (SMME) and Monte Carlo Pattern/Residual (MCPR), and apply them to construct joint probability density functions (PDFs) of temperature and precipitation change over the 21st century for every county in the United States. Both methods produce likely (67% probability) temperature and precipitation projections consistent with the Intergovernmental...

Decision-making for Coastal Adaptation: Sustaining Coastal Salt Marshes for Ecosystem Services along the Jersey Shore - Data

Rachael Sacatelli, Joshua Moody, Erin Reilly, LeAnn Haaf, Michael Kennish, Danielle Kreeger & Martha Maxwell-Doyle
This project builds on our conceptual model to generate salt marsh vulnerability maps (i.e., MarshFutures maps) that assess seaward edge erosion, platform “elevation capital”, and landward migration and which predict the fate for selected Marshes of Interest (MOIs). Seven MOIs were studied: 2 in Delaware Bay; 3 in Great Bay; and, 2 in Barnegat Bay/Little Egg Harbor. This concept of elevation capital relates accretion rates and the tidal zone that dominant plants require for optimal...

Probability-weighted ensembles of U.S. county-level climate projections for climate risk analysis: Table directory.

D. J. Rasmussen, Malte Meinshausen & Robert E. Kopp
Quantitative assessment of climate change risk requires a method for constructing probabilistic time series of changes in physical climate parameters. Here, we develop two such methods, Surrogate/Model Mixed Ensemble (SMME) and Monte Carlo Pattern/Residual (MCPR), and apply them to construct joint probability density functions (PDFs) of temperature and precipitation change over the 21st century for every county in the United States. Both methods produce likely (67% probability) temperature and precipitation projections consistent with the Intergovernmental...

Probability-weighted ensembles of U.S. county-level climate projections for climate risk analysis: Surrogate/Model Mixed Ensemble (SMME) data set RCP45

D. J. Rasmussen, Malte Meinshausen & Robert E. Kopp
Quantitative assessment of climate change risk requires a method for constructing probabilistic time series of changes in physical climate parameters. Here, we develop two such methods, Surrogate/Model Mixed Ensemble (SMME) and Monte Carlo Pattern/Residual (MCPR), and apply them to construct joint probability density functions (PDFs) of temperature and precipitation change over the 21st century for every county in the United States. Both methods produce likely (67% probability) temperature and precipitation projections consistent with the Intergovernmental...

Probability-weighted ensembles of U.S. county-level climate projections for climate risk analysis: Surrogate/Model Mixed Ensemble (SMME) data set RCP26

D. J. Rasmussen, Malte Meinshausen & Robert E. Kopp
Quantitative assessment of climate change risk requires a method for constructing probabilistic time series of changes in physical climate parameters. Here, we develop two such methods, Surrogate/Model Mixed Ensemble (SMME) and Monte Carlo Pattern/Residual (MCPR), and apply them to construct joint probability density functions (PDFs) of temperature and precipitation change over the 21st century for every county in the United States. Both methods produce likely (67% probability) temperature and precipitation projections consistent with the Intergovernmental...

Dataset S3 for Temperature-driven global sea-level variability in the Common Era

No Name Supplied
The sheets of this workbook comprise global sea level (GSL) curves and associated covariance matrices. The curves and covariance matrices are shown on separate sheets for each prior. The columns for GSL curves comprise year (Common Era), GSL height (mm), and 1σ errors for GSL height. Covariance matrices have columns and rows labeled by year, and covariance values in mm^2. Please remember to use the full covariance matrices if doing an analysis that involves multiple...

Dataset S1 for Temperature-driven global sea-level variability in the Common Era

No Name Supplied
(a) A summary of the sites included in the Common Era database, (b) a summary of the tide gauges incorporated into the metaanalysis, (c) hyperparameters of the different priors for the empirical hierarchical model, (d) prior estimates of GSL rates and amplitude of variability under different priors, (e) posterior estimates of GSL rates and amplitude of variability under different priors, (f) GSL rates under different data subsets, (g) RSL rates at different sites, (h) semiempirical...

Probability-weighted ensembles of U.S. county-level climate projections for climate risk analysis: Surrogate/Model Mixed Ensemble (SMME) data set RCP60

D. J. Rasmussen, Malte Meinshausen & Robert E. Kopp
Quantitative assessment of climate change risk requires a method for constructing probabilistic time series of changes in physical climate parameters. Here, we develop two such methods, Surrogate/Model Mixed Ensemble (SMME) and Monte Carlo Pattern/Residual (MCPR), and apply them to construct joint probability density functions (PDFs) of temperature and precipitation change over the 21st century for every county in the United States. Both methods produce likely (67% probability) temperature and precipitation projections consistent with the Intergovernmental...

Probability-weighted ensembles of U.S. county-level climate projections for climate risk analysis: Surrogate/Model Mixed Ensemble (SMME) data set RCP85

D. J. Rasmussen, Malte Meinshausen & Robert E. Kopp
Quantitative assessment of climate change risk requires a method for constructing probabilistic time series of changes in physical climate parameters. Here, we develop two such methods, Surrogate/Model Mixed Ensemble (SMME) and Monte Carlo Pattern/Residual (MCPR), and apply them to construct joint probability density functions (PDFs) of temperature and precipitation change over the 21st century for every county in the United States. Both methods produce likely (67% probability) temperature and precipitation projections consistent with the Intergovernmental...

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