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- Creator:
- Wu, Ziyou, Brunton, Steven L, and Revzen, Shai
- Description:
- These codes were produced as part of the Army Research Office Multi-University Research Initiative ARO MURI W911NF-17-1-0306 "From Data-Driven Operator Theoretic Schemes to Prediction, Inference, and Control of Systems" The code can be run using the runAll.sh shell script (in Linux and OS-X); code should work similarly under windows.
- Keyword:
- DMD, dimensionality reduction, dynamical systems, and nonlinear dynamics
- Discipline:
- Engineering and 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:
- Anahita, Amiri Farahani
- Description:
- this dataset is the output of WRF-Chem model for several simulations.
- Keyword:
- Lake spray aerosol
- Citation to related publication:
- Amiri-Farahani, A., Olson, N. E., Neubauer, D., Roozitalab, B., Ault, A. P., & Steiner, A. L. (2021). Lake Spray Aerosol Emissions Alter Nitrogen Partitioning in the Great Lakes Region. Geophysical Research Letters, 48(12), e2021GL093727. https://doi.org/10.1029/2021GL093727
- Discipline:
- Science
-
Bounce-Averaged Quasi-Linear Diffusion Model Simulation Input/Output on Mars’ Crustal Magnetic Field
- Creator:
- Alexander Shane
- Description:
- To study the effect of whistler mode waves on the superthermal electron velocity space at Mars, a numerical model was built to solve the bounce-averaged quasi-linear diffusion equation on a crustal field. This dataset includes the input and output variables to this model for the simulations performed in Shane and Liemohn, 2022. The studies using this dataset were conducted by Alex Shane in the Climate and Space Sciences and Engineering Department at the University of Michigan. This research was supported by the National Aeronautics and Space Administration (NASA) Grant NNX16AQ04G to the University of Michigan and the Rackham Predoctoral Fellowship.
- Keyword:
- Mars, Electron, and Crustal Fields
- Citation to related publication:
- Shane, A. D., & Liemohn, M. W. (2022). Modeling wave-particle interactions with photoelectrons on the dayside crustal fields of Mars. Geophysical Research Letters, 49, e2021GL096941. https://doi.org/10.1029/2021GL096941
- Discipline:
- Science
-
- Creator:
- Bustamante, Angela C., Opron, Kristopher, Ehlenbach, William J., Crane, Paul K., Keene, Dirk, Standiford, Theodore J., and Singer, Benjamin H.
- Description:
- This study was conducted to detect and analyze modules, or clusters of genes, associated with sepsis, using RNAseq data obtained from 12 participants who died of sepsis and 12 participants who died of non-infectious critical illness while hospitalized. This deposit contains the input data and parameters needed to reproduce the weighted gene co-expression network analysis (WGCNA) and gene enrichment analysis performed on this data. This analysis requires the R packages "WGCNA" version 1.68 and "DESeq2" version 1.22.2 available for download from bioconductor ( http://bioconductor.org). The external bioinformatics tool DAVID version 6.8 ( https://david.ncifcrf.gov/) was used as an additional gene enrichment analysis. Please see the supplemental methods document within this deposit and published research letter for more detailed information.
- Keyword:
- Sepsis, RNAseq, Transcriptomics, Human, and Brain
- Citation to related publication:
- Bustamante, A.C., Opron, K., Ehlenbach, W.J., Larson, E.B., Crane, P.K., Keene, C.D., Standiford, T.J., Singer, B.H., 2020. Transcriptomic Profiles of Sepsis in the Human Brain. Am J Respir Crit Care Med. https://doi.org/10.1164/rccm.201909-1713LE
- Discipline:
- Science
-
- Creator:
- Chatterjee, Tanmay, Knappik, Achim, Sandford, Erin, Tewari, Muneesh, Choi, Sung Won, Strong, William B., Thrush, Evan P., Oh, Kenneth J., Liu, Ning, Walter, Nils G., and Johnson-Buck, Alexander
- Description:
- The sensitive measurement of specific protein biomarkers is important for medical diagnostics and research. However, existing methods for quantifying proteins use antibody probes that cannot distinguish between specific and nonspecific binding, limiting their sensitivity and specificity. This work establishes a method for distinguishing between specific binding to the target protein and nonspecific binding to assay surfaces using single-molecule kinetic measurements with dynamically binding probes. This is significant because it permits extremely sensitive protein measurements without requiring a high-affinity detection antibody or any washing steps, enabling streamlined and sensitive quantification of proteins even when no pair of high-quality, tightly binding antibodies is available.
- Keyword:
- biomarker detection, single molecule fluorescence, kinetic fingerprinting, total internal reflection microscopy, and super resolution microscopy
- Citation to related publication:
- Chatterjee, T., et al. Direct kinetic fingerprinting and digital counting of single protein molecules. Proc Natl Acad Sci USA, In Press.
- Discipline:
- Science
-
- Creator:
- Zhang, Yan, Fujian Normal University, Yang, Ping, Fujian Normal University, Tong, Chuan, Fujian Normal University, Zhang, Xinyan, Chinese Academy of Sciences, Changchun, Liu, Xingtu, Chinese Academy of Sciences, Changchun, Zhang, Shaoqing, Chinese Academy of Sciences, Changchun, Meyers, Philip. University of Michigan, and Gao, Chuanyu , Chinese Academy of Sciences, Changchun
- Description:
- A high-resolution study of bulk properties in a peat sequence from the Xinjiang Altai Mountains of northwestern China, has allowed reconstruction of local variations in peat properties and peat C and N accumulation rates (CAR and NAR) during the Holocene. Analyses of peat bulk density, loss on ignition, and concentrations of TOC and TN and their elemental ratios and stable isotopic values suggest that changes in peat-forming vegetation types during different parts of this epoch are the major factors responsible for the variations of peat properties in this sequence.
- Keyword:
- peat properties, stable carbon and nitrogen isotopes, carbon and nitrogen accumulation rates, and Altai Mountains of northwestern China
- Citation to related publication:
- Zhang, Y., Yang, P., Gao, C., Tong, C., Zhang, X., Liu, X., Zhang, S., & Meyers, P. A. (2020). Peat Properties and Holocene Carbon and Nitrogen Accumulation Rates in a Peatland in the Xinjiang Altai Mountains, Northwestern China. Journal of Geophysical Research: Biogeosciences, 125(12), e2019JG005615. https://doi.org/10.1029/2019JG005615
- Discipline:
- Science
-
- Creator:
- Arbic, B.K., Elipot, S., Menemenlis, D., and Shriver, J.F.
- Description:
- The datafiles and Matlab code files in this repository contain the information needed to produce the figures in the paper. We also include the code used to process the raw model output files into spectra.
- Citation to related publication:
- B.K. Arbic, S. Elipot, J.M. Brasch, D. Menemenlis, A.L. Ponte, J.F. Shriver, X. Yu, E.D. Zaron, M.H. Alford, M.C. Buijsman, R. Abernathey, D. Garcia, L. Guan, P.E. Martin, and A.D. Nelson (2022), Near-surface oceanic kinetic energy distributions from drifter observations and numerical models. In review.
- Discipline:
- Science
-
- Creator:
- Light, Charles X, Arbic, Brian K, Martin, Paige E, Brodeau, Laurent, Farrar, J Thomas, Griffies, Stephen M, Kirtman, Ben P, Laurindo, Lucas, Menemenlis, Dimitris, Molod, Andrea, Nelson, Arin D, Nyadjro, Ebenezer, O'Rourke, Amanda K, Shriver, Jay, Siqueira, Leo, Small, R Justin, and Strobach, Udi
- Description:
- The precipitation data itself is the output of the models/datasets that we analyze in our paper. Most of it is in .nc or .nc4 format, although we provide code to extract the data into time series .mat files. We used MATLAB to perform our analysis.
- Keyword:
- precipitation and power spectra
- Citation to related publication:
- Light, C.X., Arbic, B.K., Martin, P.E., Brodeau, L., Farrar, J.T., Griffies, S.M., Kirtman, B.P., Laurindo, L.C., Menemenlis, D., Molod, A., Nelson, A.D., Nyadjro, E., O'Rourke, A.K., Shriver, J.F., Siqueira, L., Small, R.J., Strobach, E. (2022). Effects of grid spacing on high-frequency precipitation variance in coupled high-resolution global ocean-atmosphere models. Climate Dynamics, https://doi.org/10.1007/s00382-022-06257-6
- Discipline:
- Science
-
- Creator:
- Jiao, Zhenbang, Chen, Yang, and Manchester, Ward
- Description:
- GOES_flare_list: contains a list of more than 12,013 flare events. The list has 6 columns, flare classification, active region number, date, start time end time, emission peak time. SHARP_data.hdf5 files contain time series of 20 physical variables derived from the SDO/HMI SHARP data files. These data are saved at a 12 minute cadence and are used to train the LSTM model.
- Keyword:
- Solar Flare Prediction and Machine Learning
- Citation to related publication:
- Jiao, Z., Sun, H., Wang, X., Manchester, W., Gombosi, T., Hero, A., & Chen, Y. (2020). Solar Flare Intensity Prediction With Machine Learning Models. Space Weather, 18(7), e2020SW002440. https://doi.org/10.1029/2020SW002440 and Chen, Y., & Manchester, W. (2019). Data and Data products for machine learning applied to solar flares [Data set], University of Michigan - Deep Blue. https://doi.org/10.7302/qnsq-cs38
- Discipline:
- Engineering and Science