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- Creator:
- Shi, Xuetao, Elvati, Paolo, and Violi, Angela
- Description:
- Non-thermal plasma systems offer unique opportunities in the fields of bio-imaging, drug delivery, photovoltaics, microelectronics manufacturing. Such interests are largely inspired by the fact that hot plasma electrons coexist with neutral species and ions close to room-temperature under non-thermal plasma conditions. Modeling of these systems requires a deep understanding of the atomistic processes underlying the rich chemistry of the various radicals and ions with the nascent nanoparticle surface. A key parameter for determining the contribution of a certain radical/ion species to the nanoparticle surface growth, called sticking coefficient, is computed as a weighted sum from the simulated sticking outcomes with different collision velocities drawn from a Maxwell-Boltzmann distribution at certain temperatures. In this work, the collisions of SiHx (x=1-4) fragments and silicon cluster (Si4, Si2H6, and Si29H36) surfaces, responsible for the sticking coefficients, are simulated by molecular dynamics (MD) with a reactive force field. The dependence of sticking coefficients on temperature, H coverage of both silane fragments and cluster surfaces, and the size of the cluster, are systematically examined. And the mechanism underlying the sticking events, specifically the conversion of physical aggregation to chemisorption is investigated to better understand the complex interplay between factors influencing the surface growth. The detailed and multi-parameter model of sticking coefficients, accompanied by the mechanism study of physisorption to chemisorption conversion, provides a more accurate and robust approximation of surface growth rate using sticking coefficients, and a deeper understanding of surface growth processes, for the wider non-thermal plasma simulation community.
- Keyword:
- Sticking coefficients, Silanes, Molecular Dynamics, Non-equilibrium, and Aggregation mechanisms
- Citation to related publication:
- Shi, X., Elvati, P., Violi, A. (2021). On the growth of Si nanoparticles in non-thermal plasma: physisorption to chemisorption conversion. J. Phys. D. Submitted.
- Discipline:
- Science
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- Creator:
- Sergio E. Vidal-Luengo
- Description:
- This database contains spacecraft and ground-based magnetic field observations made to study the propagation of the preliminary impulse triggered by interplanetary shocks with different inclinations in the XZ plane.
- Keyword:
- Cluster, Dynamic pressure pulse, THEMIS, SuperMag, Magnetosphere, MMS, and Intermagnet
- Citation to related publication:
- (to be submitted) Vidal-Luengo, S. E., Moldwin, M. B. (2021). Shock Inclination Effects in Preliminary Impulse Propagation Observed by Ground-Based Magnetometers and the Heliophysics System Observatory
- Discipline:
- Science
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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:
- Carlson, Zachary
- Description:
- Data repository for supplemental data for manuscript. Article and data set are currently under review by publisher. Email for more information.
- Citation to related publication:
- Carlson, Z., Hafner, H., Mulcahy, M., Bullock, K., Zhu, A., Bridges, D., Bernal-Mizrachi, E., & Gregg, B. (2020). Lactational metformin exposure programs offspring white adipose tissue glucose homeostasis and resilience to metabolic stress in a sex-dependent manner. American Journal of Physiology-Endocrinology and Metabolism, 318(5), E600–E612. https://doi.org/10.1152/ajpendo.00473.2019
- Discipline:
- Science
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- Creator:
- Burger, Laura L , Wagenmaker, Elizabeth R., Phumsatitpong, Chayarndorn , Olson, David P., and Moenter, Suzanne M.
- Description:
- Polycystic ovary syndrome (PCOS) is the most common form of infertility in women. The causes of PCOS are not yet understood and both genetics and early-life exposure have been considered as candidates. With regard to the latter, circulating androgens are elevated in mid-late gestation in women with PCOS, potentially exposing offspring to elevated androgens in utero; daughters of women with PCOS are at increased risk for developing this disorder. Consistent with these clinical observations, prenatal androgenization (PNA) of several species recapitulates many phenotypes observed in PCOS. There is increasing evidence that symptoms associated with PCOS, including elevated luteinizing hormone (LH) (and presumably gonadotropin-releasing hormone (GnRH)) pulse frequency emerge during the pubertal transition. We utilized translating ribosomal affinity purification coupled with RNA sequencing to examine GnRH neuron mRNAs from prepubertal (3wk) and adult female control and PNA mice. Prominent in GnRH neurons were transcripts associated with protein synthesis and cellular energetics, in particular oxidative phosphorylation. The GnRH neuron transcript profile was affected more by the transition from prepuberty to adulthood than by PNA treatment, however PNA did change the developmental trajectory of GnRH neurons. This included families of transcripts related to both protein synthesis and oxidative phosphorylation, which were more prevalent in adults than in prepubertal mice but were blunted in PNA adults. These findings suggest that prenatal androgen exposure can program alterations in the translatome of GnRH neurons, providing a mechanism independent of changes in the genetic code for altered expression. These are Microsoft Excel Files
- Keyword:
- GnRH Neuron TRAP Seq
- Citation to related publication:
- Unprocessed RNASeq data is available at Gene Expression Omnibus ( https://www.ncbi.nlm.nih.gov/gds) accession GSE155314.
- Discipline:
- Science
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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:
- Valeriy Tenishev
- Description:
- This data represents examples of some applications of AMPS and illustrates the potential of the code for modeling various physical phenomena.
- Keyword:
- Monte Carlo, DSMC
- Citation to related publication:
- Tenishev, V., Shou, Y., Borovikov, D., Lee, Y., Fougere, N., Michael, A., & Combi, M. R. (2021). Application of the Monte Carlo Method in Modeling Dusty Gas, Dust in Plasma, and Energetic Ions in Planetary, Magnetospheric, and Heliospheric Environments. Journal of Geophysical Research: Space Physics, 126(2), e2020JA028242. https://doi.org/10.1029/2020JA028242
- Discipline:
- Science