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- Creator:
- Swiger, Brian M, Liemohn, Liemohn W, Ganushkina, Natalia Y, and Dubyagin, Stepan V
- Description:
- The data included are those that were used in the creation of a model described in the manuscript titled "Predictions of Electron Flux in the near-Earth Plasma Sheet from Solar Wind Driving" by Swiger et al., 2022, published in the Space Weather Journal. doi: pending, TBD and The manuscript describes the development and assessment of a model that predicts electron flux (from 83 eV to 93 keV energies) in a region of Earth's magnetosphere called the plasma sheet. The model uses inputs of solar wind parameters including, but not limited, to solar wind speed and the interplanetary magnetic field.
- Keyword:
- magnetosphere plasma, machine learning, neural network, space weather forecasting, electrons in space, Earth's plasma sheet, and solar wind driving of magnetosphere
- Citation to related publication:
- Swiger, B. M., Liemohn, M. W., Ganushkina, N. Y., & Dubyagin, S. V. (2022). Energetic electron flux predictions in the near-Earth plasma sheet from solar wind driving. Space Weather, 20, e2022SW003150. https://doi.org/10.1029/2022SW003150
- Discipline:
- Science
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- Creator:
- McCuen, Brett A.
- Description:
- The data were used to study the high-frequency geomagnetic disturbances within the magnetic field data. Included in this repository are the python scripts that perform an identification and classification of high-frequency signals within the magnetometer data that is downloaded from the databases listed in the Methodology section. All analysis and plots were created using subsequent Python libraries. The machine learning study implemented libraries from the sci-kit learn software. All of the specific methodology can be accessed in the readme.txt script.
- Keyword:
- geomagnetic field, high frequency, space weather, transient-large-amplitude, TLA, high frequency dB/dt, and dB/dt search algorithm
- Discipline:
- Science
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- Creator:
- Murray, Kendra E, Niemi, Nathan A, and Clark, Marin C
- Description:
- These data were produced in the scope of research into understanding the application of zircon (U-Th)/He thermochronometric data derived from rocks with complex radiation damage distributions to the extraction of long-term (>1 Gyr) thermal histories of the Earth's upper crust. The samples used in this study were collected from the Front Range in Colorado, USA. The low-temperature (apatite and zircon (U-Th)/He) thermochronometric ages presented in this data set are sensitive to near-surface temperatures (~80C and 180C, respectively) and record the progressive exhumation of the rock mass from which the samples were collected towards the Earth's surface. These thermochronometric ages, and the differences between them, provide insight into the deep-time (~1000 Ma - 100 Ma) thermal history of the Colorado Front Range.
- Keyword:
- apatite, zircon, helium, (U-Th)/He, (U-Th-Sm)/He, thermochronometry, thermochronology, low-temperature, Colorado, Boulder, geology, Colorado Mineral Belt, and Front Range
- Discipline:
- Science
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- Creator:
- Larson, Joanna G, Hamar, Leslie, Whitcher, Courtney, Farrugia, Nicholas, and Schwarz, Eva
- Description:
- These are the data required to implement the authentic research experience (ARE) that we created and describe in our paper "The Batrachian Barf Bowl: An authentic research experience using ecological data from frog diets." We created an open-source “bowl game” competition that challenges students to identify, measure, and compare diet items across vouchered frog specimens.
- Keyword:
- Frog, Diet, Ecology, Science Education, Authentic Research Experience (ARE), Biodiversity, Herpetology, Museum Collections, Remote Learning, and Undergraduate
- Citation to related publication:
- Larson, J. G., Crowell, H. L., Walsh, L. L., & Davis Rabosky, A. R. (2022). The Batrachian Barf Bowl: An authentic research experience using ecological data from frog diets. Ecology and Evolution, 12, e9095. https://doi.org/10.1002/ece3.9095 and The above article is also available in Deep Blue Documents at https://hdl.handle.net/2027.42/174122
- Discipline:
- Science
-
- Creator:
- Bougher, S. W. and Parkinson, C. D.
- Description:
- Understanding the state and composition of an exoplanetary atmosphere depends upon several parameters such as heating, cooling, mixing and reactions between constituent chemical species. Only a few types of atmospheric species can be detected remotely spectroscopically and only if their abundance is large enough to be detectable. In this initial study, we model the atmosphere of a Venus-like planet orbiting the M-type star GJ 436 to determine the global neutral temperature structure, winds, and energy balance as the radial distance of the planet from the star decreases.
- Keyword:
- Venus-like exoplanet, upper atmospheres , and heat balances
- Citation to related publication:
- C. D. Parkinson, S. W. Bougher, F. P. Mills, R. Hu, G. Gronoff, J. Li, A. Brecht, D. Adams, and Y. L. Yung. Venus as an Exoplanet: I. An Initial Exploration of the 3-D Energy Balance for a CO2 Exoplanetary Atmosphere Around an M-Dwarf Star, J. Geophysical Research, X, (2022). doi:....
- Discipline:
- Science
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- Creator:
- Valeriy Tenishev
- Description:
- Here we present an investigation of the variability of Venus' extended oxygen corona. For that, we employ a combination of a fluid model VTGCM for simulating Venus' ionosphere and thermosphere and kinetic model AMPS. We have found excellent agreement of the model results with PVO observations of the corona when the modeling is done assuming the solar maximum conditions, which corresponds to the solar conditions during the observations. We also found that the oxygen density strongly depends on the solar conditions and varies by order of magnitude over a solar cycle. That explains why the extended oxygen corona was observed only at the solar maximum. The result presented in this paper will be used in a later study of the planet's interaction with the ambient solar wind, where the corona model defines the mass loading coefficient.
- Keyword:
- Venus, VTGCM, AMPS, and Venus extended corona
- Discipline:
- Science
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- Creator:
- Liu, Meichen
- Description:
- The raw seismic records are downloaded from Incorporated Research Institutions for Seismology. The facilities of IRIS Data Services, and specifically the IRIS Data Management Center, were used for access to waveforms, related metadata, and/or derived products used in this study. The synthetic seismograms are generated by SPECMFEM3D_Globe software which was downloaded from the Computational Infrastructure for Geodynamics ( https://geodynamics.org/).
- Keyword:
- Composition and structure of the mantle, Phase transitions, North America, Body waves, and Computational seismology
- Discipline:
- Science
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Dynamical Heating in the Martian Thermosphere: Temperatures, Winds and Thermal Balances using M-GITM
- Creator:
- Bougher, S. W. and Pilinski, M. D.
- Description:
- The NASA MAVEN (Mars Atmosphere and Volatile Evolution) spacecraft, which is currently in orbit around Mars, has been taking systematic measurements of the densities and deriving temperatures in the upper atmosphere of Mars (between about 140 to 240 km above the surface) since late 2014. Wind measurement campaigns have also been conducted once per month for 5-10 orbits since 2016. These densities, temperatures and winds change with time (e.g. solar cycle, season, local time) and location, and sometimes fluctuate quickly. Global dust storm events are also known to significantly impact these density, temperature and wind fields in the Mars thermosphere. For the current project, in-situ measured winds and corresponding argon density derived temperatures are combined to trace the circulation patterns and investigate their convergence and divergence locations and impacts throughout the Mars thermosphere. M-GITM computed thermal balance terms are subsequently extracted to investigate the processes required to maintain the temperature distribution around the planet. For this work, Mars Year #33 (MY33) Neutral Gas and Ion Mass Spectrometer (NGIMS) measurements have been obtained by the MAVEN team for this purpose (see these representative works: (Bougher et al., 2017; Stone et al., 2018; Benna et al., 2019). These temperature and wind fields are compared to simulations from a computer model of the Mars atmosphere called M-GITM (Mars Global Ionosphere-Thermosphere Model), developed at U. of Michigan. Since the global circulation plays a role in the structure, variability, and evolution of the atmosphere, understanding the processes that drive the winds in the upper atmosphere of Mars also provides the needed context for understanding temperature distributions and underlying thermal balances throughout the atmosphere. Three dimensional M-GITM simulations for three of the four Mars cardinal seasons (Ls = 0, 90, 270) for MY33 were conducted for detailed comparisons with NGIMS temperature and wind distributions (Pilinski et al. 2022). Corresponding M-GITM datacubes used to extract these temperatures (plus winds) along the trajectory of each orbit path between 140 and 240 km, are provided in this Deep Blue Data archive. A single README file is included that details the contents of each datacube file. In addition, this general README file summarizes the inputs and outputs of each M-GITM simulation interval used for this study. Finally, a basic version of the M-GITM code can be found on Github at https:/github.com/dpawlows/MGITM.
- Keyword:
- MAVEN, Mars thermosphere, global dynamics, and heat balances owing to winds
- Citation to related publication:
- Pilinski, M. D., K. J. Roeten, S. W. Bougher and M. Benna, Dynamical Heating in the Martian Thermosphere, Journal Geophysical Res., XXX, (forthcoming - 2022). doi: .....
- Discipline:
- Science
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- Creator:
- Song, Siliang and Zhang, Jianzhi
- Description:
- Fitness landscapes map genotypes to their corresponding fitness under given environments and allow explaining and predicting evolutionary trajectories. Of particular interest is the landscape ruggedness or the unevenness of the landscape, because it impacts many aspects of evolution such as the likelihood that a population is trapped in a local fitness peak. Although the ruggedness has been inferred from a number of empirically mapped fitness landscapes, it is unclear to what extent this inference is affected by fitness estimation error, which is inevitable in the experimental determination of fitness landscapes. Here we address this question by simulating fitness landscapes under various theoretical models, with or without fitness estimation error. We find that all eight examined measures of landscape ruggedness are overestimated due to imprecise fitness quantification, but different measures are affected to different degrees. We devise a method to use replicate fitness measures to correct this bias and show that our method performs well under realistic conditions. We conclude that previously reported fitness landscape ruggedness is likely upward biased owing to the negligence of fitness estimation error and advise that future fitness landscape mapping should include at least three biological replicates to permit an unbiased inference of the ruggedness.
- Keyword:
- adaptation, estimation error, evolution, NK model, Rough Mount Fuji model, and polynomial model
- Discipline:
- Science
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- Creator:
- Lester, Corey A, Al Kontar, Raed, and Chen, Qiyuan
- Description:
- The dataset contains images of pills inside a medication bottle from a top down view. The dataset was used to build an image classification model for predicting the national drug code (NDC) of the medication seen in the image. There are 13,955 images of 20 distinct NDC. The image data were used to create a machine learning algorithm which could predict the NDC.
- Keyword:
- Medication, Pills, and Image
- Discipline:
- Health Sciences