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- Creator:
- Bougher, S. W. (CLaSP Department, U. of Michigan), Roeten, K. J. (CLaSP Department, U. of Michigan), and Sharrar, R. (Astronomy Department, U. of Michigan)
- Description:
- The NASA MAVEN (Mars Atmosphere and Volatile Evolution) spacecraft, which is currently in orbit around Mars, has been taking daily (systematic) measurements of the densities and temperatures in the upper atmosphere of Mars between about 140 to 240 km above the surface. Wind measurement campaigns are also conducted once per month for 5-10 orbits. These densities, temperatures and winds change with time (e.g. 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. Such global dust storm period measurements can be compared to simulations from a computer model of the Mars atmosphere called M-GITM (Mars Global Ionosphere-Thermosphere Model), developed at U. of Michigan. This is the first detailed comparison between direct global dust storm period measurements in the upper atmosphere of Mars and simulated MGITM fields and is important because it can help to inform us what physical processes are acting on the upper atmosphere during such large dust events. 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 key context for understanding how the atmosphere behaves as a whole system. A basic version of the M-GITM code can be found on Github as follows: https:/github.com/dpawlows/MGITM and About 4 months of Neutral Gas and Ion Mass Spectrometer (NGIMS) measurements of densities and winds have been made by the MAVEN team during the summer of 2018 (Elrod et al., 2019). Nine reference measurement intervals during this global dust storm (1-June through 30-August 2018) are selected for detailed study (Elrod et al. 2019). The Mars conditions for these nine intervals have been used to launch corresponding M-GITM code simulations, yielding 3-D neutral density, temperature and wind fields for comparison to these NGIMS measurements. The M-GITM datacubes used to extract the density, temperature and neutral winds, along the trajectory of each orbit path between 140 and 240 km, are provided in this Deep Blue Data archive. README files are provided for each datacube, detailing the contents of each file. A general README file is also provided that summarizes the inputs and outputs of the M-GITM code simulations for this study.
- Keyword:
- Mars, MAVEN Spacecraft, Mars Thermosphere, and Mars Global Dust Storm of 2018
- Citation to related publication:
- Elrod, M. K., S. W. Bougher, K. Roeten, R. Sharrar, J. Murphy, Structural and Compositional Changes in the Upper Atmosphere related to the PEDE-2018 Dust Event on Mars as Observed by MAVEN NGIMS, Geophys. Res. Lett., (2019). doi: 10.1029/2019GL084378. Jain, S. K., S. W. Bougher, J. Deighan, N. M. Schneider, F. Gonzalez-Galindo, A. I. F. Stewart, R. Sharrar, D. Kass, J. Murphy, and D. Pawlowski, Martian Thermospheric Warming Associated with the Planet Encircling Dust Storm Event of 2018, Geophys. Res. Lett., submitted (2019).
- Discipline:
- Science and Engineering
- Title:
- Mars Thermospheric Responses to a Global Dust Storm (PEDE-2018): Mars Global Ionosphere-Thermosphere Model (M-GITM) Simulated Datasets for Comparison to MAVEN Spacecraft Measurements
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- Creator:
- Alsip, Peter
- Description:
- Percent Weight Change Data: The model was run continuously on a daily time step for seasonal intervals (Spring: March thru May; Summer: June thru August; Fall: September thru November) as well as contiguously from Spring to Fall to assess total growth over the likely growing season (March thru November). CSV files represent the simulated weight change (%) of Bighead and Silver Carp for the respective time periods associated with the file name. Initial fish mass for each seasonal interval and growing season was 4350 g for Silver Carp and 5480 g for Bighead Carp. Maximum and mean total weight change (%) was determined for three depth ranges (near surface depths [NS]: 0 – 10 m; deep chlorophyll layer depths [DCL]: 10 - 50 m; and whole water column [WC]). Coordinates are in decimal degrees. File naming convention: speciesSeasonWtChange (e.g. bigheadFallWtChange = % weight change of Bighead Carp from September through November) , Monthly Habitat Quality Data: Rdata files contain matrices of Bighead or Silver carp growth rate potential as represented as a mass-proportional growth rate (gram of carp/gram of carp/day [g/g/d]) for the 15th day of each month. Habitats with growth rate potential >= 0 g/g/d were deemed suitable. Matrix attributes: Rows: Row numbers refer to the spatial node with 20 equally-spaced vertical layers. Columns: Columns 1-20 refer to the growth rate potential value for each vertical layer of each node. Vertical layers are evenly spaced based on the total depth of the water column for each node. Depth for each node can be found in the grid attributes data file. Columns 21 ("meanG") and 22 ("Gmax") represent the average and maximum growth rate potential, respectively, of the fish across the whole water column for the corresponding node. File naming convention: species_MonthNumber (e.g. silver_06 = Silver carp growth rate potential in June) Spatial coordinates for each node can be found in the grid attributes data files., Grid attributes data: This Rdata file provides the spatial reference data and other grid attributes. Coordinates are provided in UTM (x & y) and latitude and longitude (decimal degrees). Depth (meters) for each node is listed in this file. , GRP Model code: Details bioenergetics equations, foraging equation, functions for running the model on a monthly time-step and daily time step, and functions for basic analyses. Model is coded in R., and The simulated input data (prey and temperature) used to run our model is not included in this data set. Instead we provide the model code, grid attributes, and outputs of the model. The readRDS() function (R Base Package v.3.5.1) is required to read in .Rdata files in R.
- Keyword:
- Asian Carp, Laurentian Great Lakes, Habitat Suitability, Invasive Species, Lake Michigan, and Ecological Modeling
- Citation to related publication:
- Alsip, P.J. (2018). Modeling Lake Michigan’s Suitability for Bigheaded Carps: The Importance of Diet Flexibility and Subsurface Habitat. (Master's thesis). Retrieved from https://deepblue.lib.umich.edu/handle/2027.42/145424
- Discipline:
- Science
- Title:
- Spatially-explicit model code and outputs of Bighead and Silver carp growth rate potential in Lake Michigan
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- Creator:
- Carson IV, William F.
- Description:
- Raw data and analysis files for the figures corresponding to the manuscript submission entitled "CCL2 enhances macrophage inflammatory responses via miR-9 mediated downregulation of the ERK1/2 phosphatase Dusp6"
- Citation to related publication:
- Discipline:
- Science
- Title:
- Raw Data - CCL2 enhances macrophage inflammatory responses via miR-9 mediated downregulation of the ERK1/2 phosphatase Dusp6
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- Creator:
- Dr. Francis C. Evans
- Description:
- The Evans Old Field Plant Database contains FileMaker and Excel files of data collected by Dr. Francis C. Evans during a 50-year study on successional change on Evans Old Field on the Edwin S. George Reserve. Data include plant phenology, location, and abundances observed from 1948 to 1997.
- Citation to related publication:
- Discipline:
- Science
- Title:
- Evans Old Field Plant Database, 1948-1997
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- Creator:
- Geng, Yina, Van Anders, Greg, and Glotzer, Sharon C.
- Description:
- The data are the 13 target structures used in developing our model for predicting colloidal crystal structures from the geometries of particular shapes. The target structures are: simple cubic (SC), body-centered cubic (BCC), face-centered cubic (FCC), simple chiral cubic (SCC), hexagonal (HEX-1-0.6), diamond (D), graphite (G), honeycomb (H), body-centered tetragonal (BCT-1-1-2.4), high-pressure Lithium (Li), Manganese (beta-Mn), Uranium (beta-U), Tungsten (beta-W). At least nine simulations were run on each of the target structures. All of the data are formatted as .pos files.
- Keyword:
- Inverse Design and Machine Learning
- Citation to related publication:
- " Yina Geng, Greg van Anders, Sharon C. Glotzer, ""Predicting colloidal crystals from shapes via inverse design and machine learning [pre-print]"" https://arxiv.org/pdf/1801.06219.pdf"
- Discipline:
- Science
- Title:
- Predicting Crystal Structures using Digital Alchemy Inverse Materials Design and the Random Forest Technique of Machine Learning
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- Creator:
- Hodgins-Davis, Andrea, Duveau, Fabien, Walker, Elizabeth, and Wittkopp, Patricia J
- Description:
- Understanding how phenotypes evolve requires disentangling the effects of mutation generating new variation from the effects of selection filtering it. Tests for selection frequently assume that mutation introduces phenotypic variation symmetrically around the population mean, yet few studies have tested this assumption by deeply sampling the distributions of mutational effects for particular traits. Here, we examine distributions of mutational effects for gene expression in the budding yeast Saccharomyces cerevisiae by measuring the effects of thousands of point mutations introduced randomly throughout the genome. We find that the distributions of mutational effects differ for the ten genes surveyed and are inconsistent with normality. For example, all ten distributions of mutational effects included more mutations with large effects than expected for normally distributed phenotypes. In addition, some genes also showed asymmetries in their distribution of mutational effects, with new mutations more likely to increase than decrease the gene’s expression or vice versa. Neutral models of regulatory evolution that take these empirically determined distributions into account suggest that neutral processes may explain more expression variation within natural populations than currently appreciated.
- Keyword:
- gene expression, evolution, mutation, mutagenesis, regulatory evolution, YFP, reporter construct, yeast, TDH1, TDH2, TDH3, GPD1, OST1, PFY1, STM1, RNR1, and RNR2
- Citation to related publication:
- Hodgins-Davis, A., Duveau, F., Walker, E. A., & Wittkopp, P. J. (2019). Empirical measures of mutational effects define neutral models of regulatory evolution in Saccharomyces cerevisiae. BioRxiv, 551804. https://doi.org/10.1101/551804
- Discipline:
- Science
- Title:
- Dataset for "Empirical measures of mutational effects define neutral models of regulatory evolution in Saccharomyces cerevisiae"
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- Creator:
- Kort, EA, Gvakharia, A, Smith, ML, and Conley, S
- Description:
- Data is collected from research flights based in West Memphis, Arkansas, covering the Mississippi River Valley. The data file contains all merged flight data from each flight day.
- Keyword:
- Greenhouse gas
- Citation to related publication:
- Gvakharia, A., Kort, E. A., Smith, M. L., and Conley, S.: Testing and evaluation of a new airborne system for continuous N2O, CO2, CO, and H2O measurements: the Frequent Calibration High-performance Airborne Observation System (FCHAOS), Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-201, in review, 2018.
- Discipline:
- Science
- Title:
- Airborne Data from the Fertilizer Emissions Airborne Study (FEAST). Nitrous Oxide, Carbon Dioxide, Carbon Monoxide, Methane, Ozone, Water Vapor, and meteorological variables over the Mississippi River Valley.
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- Creator:
- Larson, Ronald G., Wen, Fei, Huang, Wenjun, and Huang, Ming
- Description:
- We provide the parameters used in Umbrella Sampling simulations reported in our study "Efficient Estimation of Binding Free Energies between Peptides and an MHC Class II Molecule Using Coarse-Grained Molecular Dynamics Simulations with a Weighted Histogram Analysis Method", namely the set positions and spring constants for each window in simulations. Two tables are provided. Table 1 lists the names of the peptides and their corresponding sequences. Table 2 lists the parameters. The abstract of our work is the following: We estimate the binding free energy between peptides and an MHC class II molecule using molecular dynamics (MD) simulations with Weighted Histogram Analysis Method (WHAM). We show that, owing to its more thorough sampling in the available computational time, the binding free energy obtained by pulling the whole peptide using a coarse-grained (CG) force field (MARTINI) is less prone to significant error induced by biased-sampling than using an atomistic force field (AMBER). We further demonstrate that using CG MD to pull 3-4 residue peptide segments while leaving the remain-ing peptide segments in the binding groove and adding up the binding free energies of all peptide segments gives robust binding free energy estimations, which are in good agreement with the experimentally measured binding affinities for the peptide sequences studied. Our approach thus provides a promising and computationally efficient way to rapidly and relia-bly estimate the binding free energy between an arbitrary peptide and an MHC class II molecule.
- Keyword:
- Molecular Dynamics, Binding Free Energy, Protein, MHC, and Coarse-Grained
- Citation to related publication:
- M. Huang, W. Huang, F. Wen, R. G. Larson. J. Comput. Chem. 2017, 38, 2007–2019. https://doi.org/10.1002/jcc.24845
- Discipline:
- Engineering and Science
- Title:
- Simulation Parameters used in the Study titled "Efficient Estimation of Binding Free Energies between Peptides and an MHC Class II Molecule Using Coarse-Grained Molecular Dynamics Simulations with a Weighted Histogram Analysis Method"
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- Creator:
- Thomaz, Andréa T. (UMICH) and Knowles, L. Lacey (UMICH)
- Description:
- The eastern coastal basins of Brazil are a series of small and isolated rivers that drain directly into the Atlantic Ocean. During the Pleistocene, sea-level retreat caused by glaciations exposed the continental shelf, resulting in enlarged paleodrainages that connected rivers that are isolated today. Using Geographic Information System (GIS), we infer the distribution of these paleodrainages, and their properties for the east Brazilian coast. Here, we publicly make available the shapefiles that demonstrate the paleodrainage structure along the Brazilian coast during the largest sea-level retreats in the Pleistocene, the riverine vectors during the same period and the coastal line for a drop of -125m in the sea.
- Keyword:
- Paleodrainages, Glaciations, Pleistocene, Brazil, Neotropical, and Sea-level retreat
- Citation to related publication:
- Thomaz Andréa T., Knowles L. Lacey. Flowing into the unknown: inferred paleodrainages for studying the ichthyofauna of Brazilian coastal rivers. Neotrop. ichthyol. [Internet]. 2018; 16(3): e180019. http://dx.doi.org/10.1590/1982-0224-20180019
- Discipline:
- Science
- Title:
- Flowing into the unknown: inferred paleodrainages for studying the ichthyofauna of Brazilian coastal rivers - paleodrainages shapefiles
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- Creator:
- Clarke, Phillipa J., Veinot, Tiffany C, Okullo, Dolorence, Gomez-Lopez, Iris N., Reddy, Shruthi, Goodspeed, Robert, and Data Driven Detroit
- Description:
- The information and education environment refers to: 1) the presence of information infrastructures such as broadband Internet access and public libraries in a location; 2) a person’s proximity to information infrastructures and sources; 3) the distribution of information infrastructures, sources and in a specific location; and 4) exposure to specific messages (information content) within a specific location. Coverage for all data: 10-county Detroit-Warren-Ann Arbor Combined Statistical Area.
- Keyword:
- Residential Broadband Data Adoption Rates, Census tract level, Broadband Internet Access and Speed, Colleges and Universities, Public Libraries, Spatial Measures, and Schools
- Citation to related publication:
- Discipline:
- Health Sciences, Science, and Social Sciences
- Title:
- Neighborhood effects : Information and Education Environment