cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7302/t01g-7b18
title: Unused Pharmaceutical Disposal Model

description: Supporting Information for research article "Life cycle comparison of environmental emissions from three disposal options for unused pharmaceutical". This spreadsheet provides the calculations and values used for this study; please refer to the manuscript and supporting information (as text) available at http://dx.doi.org/10.1021/es203987b for details about how to use this spreadsheet.    We use life cycle assessment methodology to compare three disposal options for unused pharmaceuticals: (i) incineration after take-back to a pharmacy, (ii) wastewater treatment after toilet disposal, and (iii) landfilling or incineration after trash disposal. For each option, emissions of active pharmaceutical ingredients to the environment (API emissions) are estimated along with nine other types of emissions to air and water (non-API emissions). Under a scenario with 50% take-back to a pharmacy and 50% trash disposal, current API emissions are expected to be reduced by 93%. This is within 6% of a 100% trash disposal scenario, which achieves an 88% reduction. The 50% take-back scenario achieves a modest reduction in API emissions over a 100% trash scenario while increasing most non-API emissions by over 300%. If the 50% of unused pharmaceuticals not taken-back are toileted instead of trashed, all emissions increase relative to 100% trash disposal. Evidence suggests that 50% participation in take-back programs could be an upper bound. As a result, we recommend trash disposal for unused pharmaceuticals. A 100% trash disposal program would have similar API emissions to a take-back program with 50% participation, while also having significantly lower non-API emissions, lower financial costs, higher convenience, and higher compliance rates.
description: See manuscript
DOI: 10.7302/z27942w2
title: Data in support of the study "Climate response to negative greenhouse gas radiative forcing in polar winter"

description: Greenhouse gas (GHG) additions to Earth’s atmosphere initially reduce global outgoing longwave radiation (OLR), thereby warming the planet. In select environments with temperature inversions, however, increased GHG concentrations can actually increase local OLR. Negative top-of-atmosphere and effective radiative forcing (ERF) from this situation give the impression that local surface temperatures could cool in response to GHG increases. Here we consider an extreme scenario in which GHG concentrations are increased only within the warmest layers of winter near-surface inversions of the Arctic and Antarctic. We find, using a fully coupled Earth system model, that the underlying surface warms despite the GHG addition exerting negative ERF and cooling the troposphere in the vicinity of the GHG increase. This unique radiative forcing and thermal response is facilitated by the high stability of the polar winter atmosphere, which inhibits thermal mixing and amplifies the impact of surface radiative forcing on surface temperature. These findings also suggest that strategies to exploit negative ERF via injections of short-lived GHGs into inversion layers would likely be unsuccessful in cooling the planetary surface.;Note: A revised data description file was added to this work on April 11, 2018 containing additional information about the data set than was provided in the original description. Additional keywords and a full citation to the related article were added as well.   
description: The data are model output from climate simulations conducted with the Community Earth System Model (CESM) version 1.0.6
DOI: 10.7302/0zt4-2e62
title: Results from Morales et al. 2018 (JAS) - Orographic precipitation sensitivity analysis

description: The research that produced this data involves exploring the sensitivity of orographic precipitation to changes in microphysical parameters found in the Morrison microphysics scheme within CM1 model. These microphysical sensitivities are also tested within different environments. The tests can be described as "one-at-a-time" experiments, i.e., an individual parameter is perturbed while keeping the rest constant. Annareli Morales conducted this research for her PhD research while working at the Mesoscale and Microscale Meteorology lab at NCAR in Boulder, CO.  
description: The data is produced from Cloud Model 1 simulations of idealized orographic precipitation. The detailed methods used are found in Morales et al. 2018, Journal of Atmospheric Science. The model output is initially in a .dat format, which is then convert to netCDF using the cdo -f nc import_binary command in a Linux terminal. The analysis is performed using the NCAR Command Language (NCL), and the results and description of analysis methods and model configurations are found in Morales et al. 2018 (JAS). The data can be accessed using any programming language that reads in netCDF or binary files. We used NCL and GrADS.
DOI: 10.7302/9bj1-q884
title: Quantifying near-surface rock strength on a regional scale from hillslope stability models - dataset

description: These datasets support the findings of Townsend et al. (2020). In this article, we quantify rock strength using two novel applications of hillslope stability models, resulting in estimates of cohesive and frictional strength at the spatial scale of small watersheds. We compare these results against the direct-shear test dataset here for validation of our approach. We find that cohesive strength is dependent on the original burial depth of the sedimentary rocks studied here. The low-temperature thermochronometry data was used to assess the magnitude of burial.
description: Apatite (U-Th)/He thermochronometry data was produced using standard laboratory procedures. Please see Townsend et al. (2020) for detailed methodology.
description: Direct-Shear test data was compiled by the California Geological Survey (California Department of Conservation, 2002a, 2002b) for coseismic landslide hazards assessments. The data here is the subset of the California Geological Survey data used to support our study. Data was originally compiled from geotechnical engineering firms in Los Angeles and Ventura Counties.
description: California Department of Conservation. (2002a). Seismic hazard zone report for the Piru 7.5-minute quadrangle, Ventura County, California. California Division of Mines and Geology Seismic Hazard Zone Report 074, 54.
description: California Department of Conservation. (2002b). Seismic hazard zone report for the Val Verde 7.5-minute quadrangle, Los Angeles and Ventura Counties, California. California Division of Mines and Geology Seismic Hazard Zone Report 076, 52.
DOI: 10.7302/559r-t639
title: Data for Improvement of Plasma Sheet Neural Network Accuracy with Inclusion of Physical Information

description: We sampled the near-Earth plasma sheet using data from the NASA Time History of Events and Macroscale Interactions During Substorms mission. For the observations of the plasma sheet, we used corresponding interplanetary observations using the OMNI database. We used these data to develop a data-driven model that predicts plasma sheet electron flux from upstream solar wind variations. The model output data are included in this work, along with code for analyzing the model performance and producing figures used in the  related publication. ;Data files are included in hdf5 and Python pickle binary formats;  scripts included are set up for use of Python 3 to access and process the pickle binary format data.
description: Near-Earth plasma sheet data are from a sample of the NASA Time History of Events and Macroscale Interactions during Substorms (THEMIS) misssion. Solar wind data are from the OMNI dataset. Data from OMNI and THEMIS are publicly available at https://spdf.gsfc.nasa.gov/data/.
DOI: 10.7302/attc-n529
title: Estimating Student Capital of Community College Student Populations

description: Student capital is the set of skills, traits, and resources that an individual can draw upon to be successful in school. With dropout rates around 50%, community college students often don't have enough student capital to achieve their goals. The R code in this dataset estimates the average student capital of a group of community college students using data on their total credits and academic outcomes. It also contains R code to create figures, as found in the paper "The Shape of Educational Inequality" by Quarles, Budak & Resnick.
description: The dataset here is simulated, designed to mimic information about a cohort of degree-seeking community college students who aimed to transfer to a 4-year college. It contains information about the number of credits each simulated student earned and whether they dropped out, graduated with an associate's degree, or transferred to a four-year college. The dataset can be used as a template for running the associated R files.
DOI: 10.7302/ynq1-q130
title: CT Data of UMMP VP 85286, Carpodaptes stonleyi left dentary I/1-2, P/4

description: Reconstructed CT slices for a left dentary of Carpodaptes stonleyi (University of Michigan Museum of Paleontology catalog number UMMP VP 85286) as a series of TIFF images.  Raw projections are not included in this dataset.
description: Specimen UMMP VP 85286 was scanned with a Nikon XT H 225ST μCT system housed in the Department of Earth and Environmental Sciences at the University of Michigan. Scans were collected with the following settings: energy settings, 75kV, 130uA
description: source to object distance, 57.824192 mm
description: scanned with 3141 projections
description: voxel size, x = y = z = 0.0104659242056336 mm
description: slice dimension (in pixels),  x = 703, y = 693
description: number of slices, 1610 16-bit TIFF images. Additional metadata can be found in the xtek and ctprofile.xml files.
DOI: 10.7302/s7vx-9j38
title: Dogon Donno So Audio Files

description: Donno So is a Dogon language spoken over a wide area on the Dogon (Bandiagara) plateau, mainly between Bandiagara and the eastern edge of the plateau. It is also called Kamma So. A grammar was published electronically at Language Description Heritage Library in 2016:;https://ldh.clld.org/sources/item_2491630 This is backed up at Deep Blue documents. http://hdl.handle.net/2027.42/123062 Thirteen texts were recorded digitally in Wendekele village south of Bandiagara in approximately 2015. Because of equipment problems the texts are rather faint and difficult to transcribe. Five texts were transcribed and translated, and presented at the end of the grammar volume. The correspondences are these: 
Published volume: text 1, Recording: DS 02, title: hare and other animals (tale); 
text 2, DS 09, report on trip to Burkina;
text 3, DS 10, blacksmith;
text 4, DS 03, squirrel and hare (tale);
text 5, DS 11, Fulbe herders. 

Recordings DS 01(tale of stepmother), 04 (farming), 05 (construction),06 (animals), 07 (hunting), 08 (herding), 12 (marriage), and 13 (korobasinging) are not transcribed as of May 2018. I grant permission to other linguists to transcribe, translate, and/or analyse them. 
description: An audio recording
DOI: 10.7302/z29k48f3
title: Supporting data and scripts for the paper "Variability in the location of High Frequency Oscillations during prolonged intracranial EEG recordings"

description: This data is part of a large program to translate detection and interpretation of HFOs into clinical use. A zip file is included which contains hfo detections, metadata, and Matlab scripts.  The matlab scripts analyze this input data and produce figures as in the referenced paper (note: the blind source separation method is stochastic, and so the figures may not be exactly the same).  A file "README.txt" provides more detail about each individual file within the zip file.

description: Intracranial EEG data was acquired at two centers at either 4096 Hz or at a higher sampling rate and downsampled to 5000 Hz.  Data was processed with the qHFO algorithm, and the channel number and detection times are reported herein.  Sleep scoring was also performed on some patients using extracranial surface EEG data.  HFO detections are only included that occured either during NREM sleep or during 1-3 AM.
DOI: 10.7302/b24g-9671
title: GITM 2017 Eclipse Results

description: These are modeling results of the thermospheric and ionospheric response to the solar eclipse of August 21, 2017. The results are discussed in a research paper published in the Journal of Geophysical Research (doi: 10.1029/2018JA026402) .
description: The Global Ionosphere Thermosphere Model (GITM) was used to conduct the simulations.  The input files are included.  The model source code can be found at: https://github.com/aaronjridley/GITM.
DOI: 10.6084/m9.figshare.16587311.v10
title: AREAdata updating output files

description: AREAdata output files for automatically updating climate averages. These are daily climate estimates based on the CDS ERA-5 reanalysis, see pearselab.github.io/areadata/.<br>File names begin with the climate variable given:temp = Temperaturespechumid = Specific Humidityrelhumid = Relative Humidityprecip = Precipiationuv = Ultraviolet<br>File names contain the administrative division level:<br>countries - highest administrative division<br>GID1 - lower administrative division, equivalent to states<br>GID2 - lower administrative division, equivalent to counties<br>Files downloadable as RDS files for direct use in the R statistical programming environment (appended .RDS), or as zip-compressed tab delimited files for other applications (appended .zip).<br>
DOI: 10.7302/z2t151kh
title: Appendix1

description: Differential expression data from zebrafish regeneration and mouse degeneration models.
description: Methods are described in the dissertation, "Regulation of Müller Stem Cell Properties: Insights From a Zebrafish Model".
DOI: 10.7302/s6h1-d521
title: Large Lake Statistical Water Balance Model - Laurentian Great Lakes - 1 month time window - 1980 through 2015 monthly summary data and model output

description: Using the statistical programming package R ( https://cran.r-project.org/), and JAGS (Just Another Gibbs Sampler,  http://mcmc-jags.sourceforge.net/), we processed multiple estimates of the Laurentian Great Lakes water balance components -- over-lake precipitation, evaporation, lateral tributary runoff, connecting channel flows, and diversions -- feeding them into prior distributions (using data from 1950 through 1979), and likelihood functions. The Bayesian Network is coded in the BUGS language. Water balance computations assume that monthly change in storage for a given lake is the difference between beginning of month water levels surrounding each month. For example, the change in storage for June 2015 is the difference between the beginning of month water level for July 2015 and that for June 2015.;More details on the model can be found in the following summary report for the International Watersheds Initiative of the International Joint Commission, where the model was used to generate a new water balance historical record from 1950 through 2015:  https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf. Large Lake Statistical Water Balance Model (L2SWBM): https://www.glerl.noaa.gov/data/WaterBalanceModel/;This data set has a shorter timespan to accommodate a prior which uses data not used in the likelihood functions.
description: We use a Bayesian Network to assimilate multiple monthly-total estimates of the Laurentian Great Lakes -- Superior, Michigan-Huron, St. Clair, Erie, and Ontario -- water balance and components thereof, generating new estimates with quantified uncertainty.
DOI: 10.7302/z2xg9p2k
title: Influence of invasive quagga mussels, phosphorus loads, and climate on spatial and temporal patterns of productivity in Lake Michigan: A biophysical modeling study

description: Animation files show the 12-month “baseline” simulations for 2000, 2005, and 2010 (see Table 1 of the paper cited above). 

temp_1_animation.wmv: Surface temperature
Chl_1_animation.wmv: Surface chlorophyll-a
PO4_1_animation.wmv: Surface total dissolved phosphorus
Detritus_1_animation.wmv: Surface detritus concentration (particulate organic carbon, excluding phytoplankton and zooplankton).
Zooplankton_1_animation.wmv: Surface zooplankton carbon concentration
MRATION_1_animation.wmv: Rate of food assimilated by mussels, according to the product f_a F_A P in Equation 2, expressed as mg phytoplankton carbon per mg mussel biomass carbon per day  × 100%.
BIO_M_1_animation.wmv: Simulated mussel biomass in mg ash-free-dry-mass m^-2

description: These animations were created using output from a lower food web model linked to a three-dimensional hydrodynamic model. The lower food web was represented using a nutrient-phytoplankton-zooplankton-detritus (NPZD) model that included a quagga mussel (benthic filter feeder) bioenergetic model. The hydrodynamic model was the Finite Volume Community Ocean Model (FVCOM). The NPZD-mussel model was implemented using the General Ecological Module (GEM), which is part of the FVCOM code.

These animations were included in the supplemental material of a paper, additional details can be found there: 
Mark D. Rowe, Eric J. Anderson, Henry A. Vanderploeg, Steven A. Pothoven, Ashley K. Elgin, Jia Wang, Foad Yousef. 2017. Influence of invasive quagga mussels, phosphorus loads, and climate on spatial and temporal patterns of productivity in Lake Michigan: A biophysical modeling study. Limnology and Oceanography, in review.
DOI: 10.7302/z2qz284t
title: Survey of How Primary Care Providers Approach Iron Deficiency Anemia and Celiac Disease

description: See attached survey and codebook
description: Electronic multiple-choice survey of members of the American College of Physicians, using hypothetical patient scenarios
DOI: 10.7302/nw92-zt29
title: Interview Protocol on the Use of Information Spaces to Navigate Identity

description: This interview protocol was designed to investigate the research question: How do self-identified refugees in the receiving societies of Greece and Germany engage with information spaces to navigate identity during liminal and post-liminal portions of their refugee experiences?
description: We piloted this interview protocol in Ann Arbor, Michigan with individuals who represented our target interview populations. Feedback from pilot interviews informed the final interview protocol version presented here and used during field research at study sites Athens, Greece, and Hamburg, Germany with participants who self-identify as having had refugee experiences. The list of mobile applications featured on the structured mobile phone application questionnaire reflected anecdotal reports from community members in Athens, and from summary reports of web traffic on NetHope’s Wi-Fi hotspots at refugee camps in Athens and surrounding areas from February 11 to March 11, 2018. Though it was initially planned that each interview participant would fill out the structured questionnaire themselves, after the first two interviews using this approach in Athens, it became apparent that participants desired more guidance using the questionnaire. In subsequent interviews, the interview facilitator (Schöpke-Gonzalez) read out each survey question, asked follow-up prompts if needed, and made hand-written notes accordingly. Participants at both research locations spoke a wide variety of languages, including Arabic, Dari, English, Farsi, French, Greek, German, Kurdish, and Turkish. Schöpke-Gonzalez is natively proficient in English and German, and professionally proficient in French. She conducted interviews in those languages when needed. In interviews requiring translation, Schöpke-Gonzalez received translation assistance from community-trusted translators or friends or family members of participants. Though most interviews were conducted individually, some participants requested to share their thoughts through group interviews. 19 individuals in Athens, Greece, and 14 individuals in Hamburg, Germany participated in interviews.
DOI: 10.7302/pjng-ef66
title: A Simple Method for Correcting Empirical Model Densities during Geomagnetic Storms Using Satellite Orbit Data

description: The Multifaceted Optimization Algorithm (MOA) is a tool for generating corrected empirical model thermospheric densities during geomagnetic storms. It consists of a suite of Python functions that operate around the Spacecraft Orbit Characterization Kit (SpOCK), an orbital propagator developed by Charles D. Bussy-Virat, PhD, Joel Getchius, and Aaron J. Ridley, PhD at the University of Michigan, and it estimates new densities for the NRLMSISE-00 atmospheric model. MOA generates new model densities by estimating modifications to inputs to the NLRMSISE-00 model that minimize the orbit error between modeled spacecraft in SpOCK, and their actual altitudes as described in publicly-available Two-Line Element Sets (TLEs), made available online via Space-track.org.
MOA consists of three sub-process: (1) The Area Optimization Algorithm (AROPT), (2) the F10.7 Optimization Algorithm (FOPT), and (3) the Ap Optimization Algorithm (APOPT). AROPT computes the contribution to the drag of the modeled spacecraft due to their varying projected area. FOPT estimates modifications to the 10.7 cm solar radio flux in NRLMSISE-00, and APOPT estimates modifications to the Earth's magnetic activity in NRLMSISE-00. MOA finds these modifications across many spacecraft, and the medians of those modifications are then applied in NLRMSISE-00 along the orbit of another satellite to generate new densities for verification. In this instance, modifications are applied along the orbits of the Swarm spacecraft and compared to Swarm GPS-derived densities.
description: The Multifaceted Optimization Algorithm (MOA) was run for the first 10 CubeSats of the Flock 3P constellation between the dates of 2017-05-23 and 2017-06-02, with TLEs from those satellites covering dates between 2017-05-02 and 2017-06-02. MOA collected TLEs for the following Flock 3P satellites:
- FLOCK3P1
- FLOCK3P2
- FLOCK3P3
- FLOCK3P4
- FLOCK3P5
- FLOCK3P6
- FLOCK3P7
- FLOCK3P8
- FLOCK3P9
- FLOCK3P10
Those TLEs were used to initialize three subprocesses that computed the contributions to drag from satellite orientation, solar radio flux, and geomagnetic activity. Distributions of the CubeSats' cross-sectional areas during the time of interest, and modifications to the 10.7 cm solar radio flux (F10.7) and the terrestrial geomagnetic activity (ap) that minimized orbit error were computed by MOA, after which the median value of those corrections was applied to the NLRMSISE-00 empirical atmospheric model along the orbits of the Swarm spacecraft in order to generate new thermospheric densities.