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- Creator:
- University of Michigan Museum of Paleontology and CTEES
- Description:
- Reconstructed CT slices for vertebrae of Hyopsodus (University of Michigan Museum of Paleontology catalog number UMMP_VP_102495) as a series of TIFF images. Raw projections are not included in this dataset. The reconstructed slice data from the scan are offered here as a series of unsigned 16-bit integer TIFF images. The upper left corner of the first image (*_0000.tif) is the XYZ origin.
- Keyword:
- Paleontology, Fossil, CT, Hyopsodontidae, UMMP, University of Michigan Museum of Paleontology, Eocene, CTEES, and 01ee73fb-6b53-fe52-3a01-2857be88a65e
- Discipline:
- Science
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- Creator:
- Liu, Meichen
- Description:
- We intend to figure out the difference of stress drops, which is a characteristic source parameter, between shallow and deep-focus earthquakes. Significant stress drop difference may shed light on the difference of physical mechanisms of shallow and deep-focus earthquakes, which has been a elusive question. We select from deep-focus earthquakes (> 400 km) in 2000-2018 and obtain their stress drops using P and S waves. We find that stress drops of deep-focus earthquakes are about one order of magnitude higher than that of shallow earthquakes, indicating about one order of magnitude higher shear strength of shallow faults than faults in the mantle. The wide range of stress drops further suggests coexistence of phase transformation and shear-induced melting mechanisms of deep-focus earthquakes.
- Citation to related publication:
- Liu, M., Huang, Y., & Ritsema, J. (2020, March 4). Stress drop variation of deep-focus earthquakes based on empirical Green's function [preprint]. Submitted to Geophysical Research Letters. https://doi.org/10.31223/osf.io/8jx6p and Liu, M., Huang, Y., & Ritsema, J. (2020). Stress Drop Variation of Deep-Focus Earthquakes Based on Empirical Green’s Functions. Geophysical Research Letters, 47(9), e2019GL086055. https://doi.org/10.1029/2019GL086055
- Discipline:
- Science
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- Creator:
- Pasquinelli, Rennie, Hu, Xiaosu, Tessier, Anne-Michelle, Kovelman, Ioulia, Zwolan, Terry A., Karas, Zachary E., and Wagley, Neelima
- Description:
- This data is from a project examining prosodic processing in children and adults using functional near-infrared spectroscopy (fNIRS) neuroimaging. fNIRS data is optical data collected using a cap with an array of source and detector fibers that emit and detect infrared light, respectively. We used fNIRS neuroimaging to explore prosodic processing, rhyme judgement, and the "oddball" paradigm in children, adults, and a small sample of children with cochlear implants. Matlab scripts, including Ted Huppert's Nirs Toolbox, were used to process the neuroimaging data. The children also took a battery of behavioral assessments (OWLS, Digit Span, PPVT, CTOPP).
- Keyword:
- Prosodic Processing, fNIRS neuroimaging, Development, Cochlear Implants, and Rhyming
- Discipline:
- Science
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- Creator:
- van Velden, Grace and Reddy, Raghav
- Description:
- A household survey was developed to capture household perceptions and behaviors around drinking water use. It consisted of several modules: key informant and household demographics, household assets and consumption, water use behaviors in the dry season, water use behaviors during the rest of the year, and water supply maintenance and repair. Intervention and safe water device surveys were also developed; the household and intervention surveys were administered via Qualtrics. and This record consists of several survey instruments, exported where appropriate from Qualtrics into PDF and .qsf.
- Keyword:
- Bangladesh, arsenic, sustainability, survey
- Discipline:
- Engineering
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- Creator:
- Smith, Joeseph P., Gronewold, Andrew D., Read, Laura, Crooks, James L., School for Environment and Sustainability, University of Michigan, Department of Civil and Environmental Engineering, University of Michigan, and Cooperative Institute for Great Lakes Research
- 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/, and This data set has a shorter timespan to accommodate a prior which uses data not used in the likelihood functions.
- Keyword:
- Water, Balance, Great Lakes, Laurentian, Machine, Learning, Lakes, Bayesian, and Network
- Citation to related publication:
- Smith, J., Gronewald, A. et al. Summary Report: Development of the Large Lake Statistical Water Balance Model for Constructing a New Historical Record of the Great Lakes Water Balance. Submitted to: The International Watersheds Initiative of the International Joint Commission. Accessible at https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf, Large Lake Statistical Water Balance Model (L2SWBM). https://www.glerl.noaa.gov/data/WaterBalanceModel/, and Gronewold, A.D., Smith, J.P., Read, L. and Crooks, J.L., 2020. Reconciling the water balance of large lake systems. Advances in Water Resources, p.103505.
- Discipline:
- Science and Engineering
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- Creator:
- University of Michigan Museum of Paleontology and CTEES
- Description:
- Reconstructed CT slices for a series of vertebrae from the second lumbar through first sacral of Sifrhippus grangeri (University of Michigan Museum of Paleontology catalog number UMMP VP 115547) as a series of TIFF images. Raw projections are not included in this dataset. The reconstructed slice data from the scan are offered here as a series of unsigned 16-bit integer TIFF images. The upper left corner of the first image (*_0000.tif) is the XYZ origin. In some publications this species is referred to as Hyracotherium grangeri.
- Keyword:
- Paleontology, Fossil, CT, Equidae, UMMP, University of Michigan Museum of Paleontology, Eocene, CTEES, and ef48281d-2984-86f2-2bee-052b26cf8da9
- Discipline:
- Science
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- Creator:
- MacEachern, Mark P, Marti, Kyriaki C, Mylonas, Anastassios I, and Gruppen, Larry
- Description:
- The dataset includes most citations considered for inclusion in the scoping review. The citations are accessible in the Endnote (enlx) file, as well as the primary citation export files from each database. The literature search strategies are included for reproducibility and transparency purposes. See the methods of the article for more information.
- Keyword:
- Dental Education, Dentistry, Education, Humanities, and Scoping Review
- Citation to related publication:
- Marti KC, Mylonas AI, MacEachern M, Gruppen L. (2019). Humanities in predoctoral dental education: A scoping review. Journal of Dental Education, 83(10), 1174-1198. DOI: 10.21815/JDE.019.126, http://www.jdentaled.org/content/83/10/1174.long, and https://doi.org/10.21815/JDE.019.126
- Discipline:
- Health Sciences
-
- Creator:
- Gradwohl, Kelsey M.
- Description:
- The data set includes one file: Dermatology Clerkship Chalk Talks Raw Dataset which is the raw data collected from the surveys. This raw data was then coded and scored with the following analysis. Objective knowledge questions were asked for each chalk talk which was scored by authors. A knowledge assessment score was calculated by adding the total number of points accumulated by the student, dividing it by the total number of points possible, and summarizing the score as a percentage. Pre- and post-talk knowledge assessment scores were compared for each chalk talk and for the entire curriculum using 2-tailed paired sample t-tests with statistical significance if p<0.05., Before and after each talk, students were asked how confident they felt differentiating conditions within each disease group. For the erythroderma and immunobullous talks, students were also asked how confident they felt working up the conditions. Answer choices were on a Likert scale ranging from 1 (not at all confident) to 5 (extremely confident). Pre- and post-chalk talk scores were summarized as means with standard deviations and compared using 2-tailed paired sample t-tests with statistical significance if p<0.05. , After each talk, students were asked about its efficacy in terms of enhancing their understanding of the diseases, providing a framework or approach to work-up, and facilitating interaction between student and teacher. Answer choices were on a Likert scale ranging from 1 (not at all effective) to 5 (extremely effective), and summarized as means with standard deviations. Students were asked for written feedback regarding what they liked about the talk and suggestions for improvement. Qualitative data were sorted into categories and scored by two independent raters (cohen's kappa =0.8)., and In the response Likert scale, "Not at all"=1, "Not so (much)"=2, "Somewhat"=3, "Very"=4, and "Extremely"=5.
- Keyword:
- Chalk talk, Dermatology clerkship, Dermatology education, Virtual learning, and Online learning
- Discipline:
- Health Sciences
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- Creator:
- Mukhopadhyay, Agnit, Daniel T Welling, Michael W Liemohn, Aaron J Ridley, Shibaji Chakrabarty, and Brian J Anderson
- Description:
- An updated auroral conductance module is built for global models, using nonlinear regression & empirical adjustments to span extreme events., Expanded dataset raises the ceiling of conductance values, impacting the ionospheric potential dB/dt & dB predictions during extreme events., and Application of the expanded model with empirical adjustments refines the conductance pattern, and improves dB/dt predictions significantly.
- Keyword:
- Space Weather Forecasting, Extreme Weather, Ionosphere, Magnetosphere, MI Coupling, Ionospheric Conductance, Auroral Conductance, Aurora, SWMF, SWPC, Nonlinear Regression, and dB/dt
- Citation to related publication:
- Mukhopadhyay, A., Welling, D. T., Liemohn, M. W., Ridley, A. J., Chakraborty, S., & Anderson, B. J. (2020). Conductance Model for Extreme Events: Impact of Auroral Conductance on Space Weather Forecasts. Space Weather, 18(11), e2020SW002551. https://doi.org/10.1029/2020SW002551
- Discipline:
- Engineering and Science
-
- Creator:
- Umaña, María Natalia, Zambrano, Jenny, Weemstra, Monique, and Allen, Dave
- Description:
- The objective of this research was to improve our understanding of tree growth from underlying variation in leaf and root functional traits. This knowledge ultimately enhances our knowledge of the above- and belowground processes that are involved in structuring forest communities. To this end, we determine which, how and to what degree (combinations of) leaf and root traits influence growth rates across ten temperate tree species along a soil carbon (C) and N gradient growing at the Big Woods plot at the E.S. George Reserve, Pickney, MI. This plot is part of the Smithsonian Institution's Forest Global Earth Observatory (ForestGEO) global network of forest research sites. https://forestgeo.si.edu/ and This dataset contains data on the leaf and root traits of several individuals from tree species, as well as on the soil properties at the Big Woods plots at the E.S. George Reserve, Pickney, MI. Data were collected in June 2019, and used to explain and predict the growth rates of the trees at Big Woods. [Growth data were obtained from Allen et al., 2019, https://doi.org/10.7302/wx55-kt18]. Each file contains data on leaf traits, root traits, and soil properties. Trait data are presented per individual tree for each of the 10 study species. Soil data are represented per soil sample, with four soil samples collected per subplot throughout the Big Woods plot (see legend, and publication for explanation). Descriptions and units per variable/column are provided in the legend tab in each file.
- Keyword:
- ecology, forests, Michigan, ForestGEO, Big Woods, Roots, Leaves, Tree growth, and Forest soils
- Citation to related publication:
- M. Weemstra, J. Zambrano, D. Allen, MN Umaña. (In press) Tree growth increases through opposing above- and belowground resource strategies. Journal of Ecology. https://doi.org/10.1111/1365-2745.13729
- Discipline:
- Science