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Estimates of the water balance of the Laurentian Great Lakes using the Large Lakes Statistical Water Balance Model (L2SWBM)
User Collection
- Creator:
- Smith, Joeseph P., Fry, Lauren M., Do, Hong X., and Gronewold, Andrew D.
- Description:
- This collection contains estimates of the water balance of the Laurentian Great Lakes that were produced by the Large Lakes Statistical Water Balance Model (L2SWBM). Each data set has a different configuration and was used as the supplementary for a published peer-reviewed article (see "Citations to related material" section in the metadata of individual data sets). The key variables that were estimated by the L2SWBM are (1) over-lake precipitation, (2) over-lake evaporation, (3) lateral runoff, (4) connecting-channel outflows, (5) diversions, and (6) predictive changes in lake storage. and Contact: Andrew Gronewold Office: 4040 Dana Phone: (734) 764-6286 Email: drewgron@umich.edu
- Keyword:
- Great Lakes water levels, statistical inference, water balance, data assimilation, Great Lakes, Laurentian, Machine learning, Bayesian, and Network
- Citation to related publication:
- Smith, J. P., & Gronewold, A. D. (2017). Development and analysis of a Bayesian water balance model for large lake systems. arXiv preprint arXiv:1710.10161., Gronewold, A. D., Smith, J. P., Read, L., & Crooks, J. L. (2020). Reconciling the water balance of large lake systems. Advances in Water Resources, 103505., and Do, H.X., Smith, J., Fry, L.M., and Gronewold, A.D., Seventy-year long record of monthly water balance estimates for Earth’s largest lake system (under revision)
- Discipline:
- Science and Engineering
5Works -
- Creator:
- Malik, Hafiz and Khan, Muhammad Khurran, King Saud University
- Description:
- Details of the microphone used for data collection, acoustic environment in which data was collected, and naming convention used are provided here. 1 - Microphones Used: The microphones used to collect this dataset belong to 7 different trademarks. Table (1) illustrates the number of used Mics of different trademarks and models. Table 1: Trademarks and models of Mics Mic Trademark Mic Model # of Mics Shure SM-58 3 Electro-Voice RE-20 2 Sennheiser MD-421 3 AKG C 451 2 AKG C 3000 B 2 Neumann KM184 2 Coles 4038 2 The t.bone MB88U 6 Total 22 2- Environment Description: A brief description of the 6 environments in which the dataset was collected is presented here: (i) Soundproof room: a small room (nearly 1.5m × 1.5m × 2m), which is closed and completely isolated. With an exception of a small window in the front side of the room which is made of glass, all the walls of the room are made of wood and covered by a layer of sponge from the inner side, and the floor is covered by carpet. (ii) Class room: standard class room (6m × 5m × 3m). (iii) Lab: small lab (4m × 4m × 3m). All the walls are made of glasses and the floor is covered by carpet. The lab contains 9 computers. (iv) Stairs: is in the second floor. The place of recording is 3m × 5m (v) Parking: is the college parking. (vi) Garden: is an open space outside the buildings. 3- Naming Convention: This set of rules were followed as a naming convention to give each file in the dataset a unique name: (i) The file name is 19 characters long, and consists of 5 sections separated by underscores. (ii) The first section is of 3 characters indicates the Microphone trademark. (iii) The second section of 4 characters indicates the microphone model as in table (2). (iv) The third section of 2 characters indicates a specific microphone within a set of microphones of the same trademark and model, since we have more than one microphone of the same trademark and model. (v) The fourth section of 2 characters indicates the environment, where Soundproof room --> 01 Class room --> 02 Lab --> 03 Stairs --> 04 Parking --> 05 Garden --> 06 (vi) The fifth section of 2 characters indicates the language, where Arabic --> 01 English --> 02 Chinese --> 03 Indonesian --> 04 (vii) The sixth section of 2 characters indicates the speaker. Table 2: Microphones Naming Criteria Original Mic Trademark and model --> Naming Convenient Shure SM-58 --> SHU_0058 Electro-Voice RE-20 --> ELE_0020 Sennheiser MD-421 --> SEN_0421 AKG C 451 --> AKG_0451 AKG C 3000 B --> AKG_3000 Neumann KM184 --> NEU_0184 Coles 4038 --> COL_4038 The t.bone MB88U --> TBO_0088 For example: SEN_0421_02_01_02_03 is an English file recorded by speaker number 3 in the soundproof room using microphone number 2 of Sennheiser MD-421
- Keyword:
- audio forensic, multimedia forensics, microphone identification, tamper detection, splicing detection, and codec identification
- Citation to related publication:
- Muhammad Khurram Khan, Mohammed Zakariah, Hafiz Malik & Kim-Kwang Raymond Choo (2018). A novel audio forensic data-set for digital multimedia forensics, Australian Journal of Forensic Sciences, 50:5, 525-542, http://dx.doi.org/10.1080/00450618.2017.1296186
- Discipline:
- Engineering, Government, Politics and Law, and Science
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- Creator:
- Bougher, Stephen W. (CLaSP Department, U. of Michigan) and Roeten, Kali J. (CLaSP Department, U. of Michigan)
- Description:
- The NASA MAVEN (Mars Atmosphere and Volatile Evolution) spacecraft, which is currently in orbit around Mars, has been taking monthly measurements of the speed and direction of the winds in the upper atmosphere of Mars between about 140 to 240 km above the surface. The observed wind speeds and directions change with time and location, and sometimes fluctuate quickly. These measurements 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. This is the first comparison between direct measurements of the winds in the upper atmosphere of Mars and simulated winds and is important because it can help to inform us what physical processes are acting on the observed winds. Some wind measurements have similar wind speeds or directions to those predicted by the M-GITM model, but sometimes, there are large differences between the simulated and measured winds. The disagreements between wind observations and model simulations suggest that processes other than normal solar forcing may become relatively more important during these observations and alter the expected circulation pattern. 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 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 30 Neutral Gas and Ion Mass Spectrometer (NGIMS) wind campaigns (of 5 to 10 orbits each) have been conducted by the MAVEN team (Benna et al., 2019). Five of these campaigns are selected for detailed study (Roeten et al. 2019). The Mars conditions for these five campaigns have been used to launch corresponding M-GITM code simulations, yielding 3-D neutral wind fields for comparison to these NGIMS wind observations. The M-GITM datacubes used to extract the zonal and meridional 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 upper atmosphere winds
- Citation to related publication:
- Roeten, K. J., Bougher, S. W., Benna, M., Mahaffy, P. R., Lee, Y., Pawlowski, D., et al. (2019). MAVEN/NGIMS thermospheric neutral wind observations: Interpretation using the M‐GITM general circulation model. Journal of Geophysical Research: Planets, 124, 3283– 3303. https://doi.org/10.1029/2019JE005957
- Discipline:
- Science and Engineering
-
- Creator:
- Crisp, Dakota N., Saggio, Maria L., Scott, Jared, Stacey, William C., Nakatani, Mitsuyoshi, Gliske, Stephen V., and Lin, Jack
- Description:
- This data and scripts are meant to test and show seizure differentiation based on bifurcation theory. A zip file is included which contains real and simulated seizure waveforms, Matlab scripts, and metadata. The matlab scripts allow for visual review validation and objective feature analysis. The file “README.txt” provides more detail about each individual file within the zip file. and Data citation: Crisp, D.N., Saggio, M.L., Scott, J., Stacey, W.C., Nakatani, M., Gliske, S.F., Lin, J. (2019). Epidynamics: Navigating the map of seizure dynamics - Code & Data [Data set]. University of Michigan Deep Blue Data Repository. https://doi.org/10.7302/ejhy-5h41
- Keyword:
- Bifurcation, Epilepsy, Seizure, and Divergence
- Citation to related publication:
- Saggio, M.L., Crisp, D., Scott, J., Karoly, P.J., Kuhlmann, L., Nakatani, M., Murai, T., Dümpelmann, M., Schulze-Bonhage, A., Ikeda, A., Cook, M., Gliske, S.V., Lin, J., Bernard, C., Jirsa, V., Stacey, W., 2020. In pre-print. Epidynamics characterize and navigate the map of seizure dynamics. bioRxiv 2020.02.08.940072. https://doi.org/10.1101/2020.02.08.940072
- Discipline:
- Engineering, Science, and Health Sciences
-
- Creator:
- Hall, Ryan J. and Larson, Ronald G.
- Description:
- This is data is a large assortment of over 50 1,4-polybutadiene star-linear blends that can be used for assessing and developing predictive models. The data are presented in CSV files.
- Keyword:
- polymers, rheology, star-linear polymer blends, and shear rheology
- Citation to related publication:
- Hall, R., Desai, P. S., Kang, B.-G., Huang, Q., Lee, S., Chang, T., Venerus, D. C., Mays, J., Ntetsikas, K., Polymeropoulos, G., Hadjichristidis, N., & Larson, R. G. (2019). Assessing the Range of Validity of Current Tube Models through Analysis of a Comprehensive Set of Star–Linear 1,4-Polybutadiene Polymer Blends. Macromolecules, 52(20), 7831–7846. https://doi.org/10.1021/acs.macromol.9b00642
- Discipline:
- Science and Engineering
-
- 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
- Discipline:
- Science and Engineering
-
- Creator:
- Gliske, Stephen V and Stacey, William C
- Description:
- This data is part of a large program to translate detection and interpretation of HFOs into clinical use. A zip file is included which contains hfo detections, metadata, and Matlab scripts. The matlab scripts analyze this input data and produce figures as in the referenced paper (note: the blind source separation method is stochastic, and so the figures may not be exactly the same). A file "README.txt" provides more detail about each individual file within the zip file.
- Keyword:
- hfo, high frequency oscillation, ripple, fast ripple, blind source separation, non-negative matrix factorization, and temporal variability
- Discipline:
- Science, Engineering, and Health Sciences
-
- Creator:
- Mirshams Shahshahani, Payam
- Description:
- Investigating minimum human reaction times is often confounded by the motivation, training, and state of arousal of the subjects. We used the reaction times of athletes competing in the shorter sprint events in the Athletics competitions in recent Olympics (2004-2016) to determine minimum human reaction times because there's little question as to their motivation, training, or state of arousal. The reaction times of sprinters however are only available on the IAAF web page for each individual heat, in each event, at each Olympic. Therefore we compiled all these data into two separate excel sheets which can be used for further analyses.
- Keyword:
- minimum reaction time, sprinter, Olympics, Athletics, sex difference, starting block, and false start
- Discipline:
- Engineering, Health Sciences, Science, Other, and General Information Sources
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- Creator:
- Ramasubramani, Vyas
- Description:
- The goal of the work is to elucidate the stability of a complex experimentally observed structure of proteins. We found that supercharged GFP molecules spontaneously assemble into a complex 16-mer structure that we term a protomer, and that under the right conditions an even larger assembly is observed. The protomer structure is very well defined, and we performed simulations to try and understand the mechanics underlying its behavior. In particular, we focused on understanding the role of electrostatics in this system and how varying salt concentrations would alter the stability of the structure, with the ultimate goal of predicting the effects of various mutations on the stability of the structure. There are two separate projects included in this repository, but the two are closely linked. One, the candidate_structures folder, contains the atomistic outputs used to generate coarse-grained configurations. The actual coarse-grained simulations are in the rigid_protein folder, which pulls the atomistic coordinates from the other folder. All data is managed by signac and lives in the workspace directories, which contain various folders corresponding to different parameter combinations. The parameters associated with a given folder are stored in the signac_statepoint.json files within each subdirectory. The atomistic data uses experimentally determined protein structures as a starting point; all of these are stored in the ConfigFiles folder. The primary output is the topology files generated from the PDBs by GROMACS; these topologies are then used to parametrize the Monte Carlo simulations. In some cases, atomistic simulations were actually run as well, and the outputs are stored alongside the topology files. In the rigid_protein folder, the ConfigFiles folder contains MSMS, the software used to generate polyhedral representations of proteins from the PDBs in the candidate_structures folder. All of the actual polyhedral structures are also stored in the ConfigFiles folder. The actual simulation trajectories are stored as general simulation data (GSD) files within each subdirectory of the workspace, along with a single .pos file that contains the shape definition of the (nonconvex) polyhedron used to represent a protein. The logged quantities, such as energies and MC move sizes, are stored in .log files. The logic for the simulations in the candidate_structures project is in the Python scripts project.py, operations.py, and scripts/init.py. The rigid_protein folder also includes the notebooks directory, which contains Jupyter notebooks used to perform analyses, as well as the Python scripts used to actually perform the simulations and manage the data space. In particular, the project.py, operations.py and scripts/init.py scripts contain most of the logic associated with the simulations.
- Keyword:
- Protein assembly, Cryo TEM, Hierarchical Assembly, Monte Carlo simulation, and Coarse-grained simulation
- Discipline:
- Science and Engineering
-
- Creator:
- Revzen, Shai
- Description:
- This repository contains both the data and python3 code that reads this data and reproduces the relevant figures. The code depends on NumPy >1.17 and matplotlib >3.1 and was tested on python 3.8
- Keyword:
- locomotion, slipping, low Reynolds number, walking, and slithering
- Discipline:
- Science and Engineering