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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
-
- Creator:
- Danforth, Shannon M.
- Description:
- This dataset includes three MATLAB data files for each subject: raw motion capture and force plate data, processed motion capture and force plate data, and sagittal-plane data segmented into individual trials labeled “nominal” or “tripped.” We include two example scripts for using the segmented trial data to tabulate trip recovery strategies across subjects and plot the sorted recovery strategies.
- Keyword:
- Trip recovery, Biomechanics, and Human locomotion
- Citation to related publication:
- S. M. Danforth, X. Liu, M. J. Ward, P.D. Holmes, and R. Vasudevan, "Predicting sagittal-plane swing hip kinematics in response to trips," IEEE Robotics and Automation Letters, 2022.
- Discipline:
- Engineering
-
- Creator:
- Dewaraja, Yuni K and Van, Benjamin J
- Description:
- This publication contains anonymized planar whole body images of two patients. Patient scans were taken at 4 different time points in the week following a therapeutic dose of Lu-177 DOTATATE. Both anterior and posterior views are provided. All images are in DICOM format.
- Keyword:
- Lu-177, Lutathera, Dosimetry, Radionuclide, and Planar
- Discipline:
- Health Sciences
-
- Creator:
- Dewaraja, Yuni, K and Van, Benjamin J
- Description:
- This publication contains the anonymized SPECT/CT scans of two patients. Patient scans were taken at 4 different time points in the week following a therapeutic dose of Lu-177 DOTATATE. Each of the scans contains 5 subfolders, 3 of which contain SPECT projection data used for reconstructing SPECT images, and 2 contain the linear attenuation coefficient maps for the CT scans that correspond to each patients SPECT projections. All images are in DICOM format.
- Keyword:
- Lu-177, Dosimetry, Radionuclide, SPECT, and CT
- Discipline:
- Health Sciences
-
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:
- Dulka, Eden A
- Description:
- This data is a subset of that originally produced as part of an effort to characterize GnRH neuron activity during prepubertal development in control and PNA mice and investigate the potential influences of sex and PNA treatment on this process (1). It was later used in (2) to further investigate the firing patterns of GnRH neurons in these categories of mice and determine how these patterns might differ based on age and treatment condition. The data files can be opened and examined using Wavemetric's Igor Pro software. Code used to further examine and visualize the data can be found at https://gitlab.com/um-mip/mc-project-code. This research was supported by National Institute of Health/Eunice Kennedy Shriver National Institute of Child Health and Human Development R01 HD34860 and P50 HD28934. (1) Dulka EA, Moenter SM. Prepubertal development of gonadotropin-releasing hormone (GnRH) neuron activity is altered by sex, age and prenatal androgen exposure. Endocrinology 2017; 158:3941-3953 (2) Penix JJ, DeFazio RA, Dulka EA, Schnell S, Moenter SM. Firing patterns of gonadotropin-releasing hormone (GnRH) neurons are sculpted by their biology. Pending.
- Keyword:
- action potential, Monte Carlo, polycystic ovary syndrome, puberty, and androgen
- Citation to related publication:
- Dulka EA, Moenter SM. Prepubertal development of gonadotropin-releasing hormone neuron activity is altered by sex, age and prenatal androgen exposure. Endocrinology 2017; 158:3943-3953. https://dx.doi.org/10.1210%2Fen.2017-00768 and Penix JJ, DeFazio RA, Dulka EA, Schnell S, Moenter SM. Firing patterns of gonadotropin-releasing hormone (GnRH) neurons are sculpted by their biology. Pending.
- Discipline:
- Health Sciences
-
- 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:
- Townsend, Whitney A, MacEachern, Mark P, and Song, Jean
- Description:
- We conducted a search through BioMed Central's 54 medicine and public health journals that provide OPR documentation in order to identify systematic review papers published in 2017. For each article we determined if OPR data, reviewer and author comments, were accessible. If so, we assessed the search methodology and reporting quality of the search process with a grading rubric based on PRISMA and PRESS standards, and then mined peer reviewer comments for references to the search methodology.
- Keyword:
- Systematic Reviews, Peer Review, Open Peer Review, Methodology, Research Methods, and Reporting
- Discipline:
- Health Sciences