Search Constraints
« Previous |
1 - 20 of 33
|
Next »
Number of results to display per page
View results as:
Search Results
-
- Creator:
- Hong, Yi, Fry, Lauren M., Orendorf, Sophie, Ward, Jamie L., Mroczka, Bryan, Wright, David, and Gronewold, Andrew
- Description:
- Accurate estimation of hydro-meteorological variables is essential for adaptive water management in the North American Laurentian Great Lakes. However, only a limited number of monthly datasets are available nowadays that encompass all components of net basin supply (NBS), such as over-lake precipitation (P), evaporation (E), and total runoff (R). To address this gap, we developed a daily hydro-meteorological dataset covering an extended period from 1979 to 2022 for each of the Great Lakes. The daily P and E were derived from six global gridded reanalysis climate datasets (GGRCD) that include both P and E estimates, and R was calculated from National Water Model (NWM) simulations. Ensemble mean values of the difference between P and E (P – E) and NBS were obtained by analyzing daily P, E, and R. Monthly averaged values derived from our new daily dataset were validated against existing monthly datasets. This daily hydro-meteorological dataset has the potential to serve as a validation resource for current data and analysis of individual NBS components. Additionally, it could offer a comprehensive depiction of weather and hydrological processes in the Great Lakes region, including the ability to record extreme events, facilitate enhanced seasonal analysis, and support hydrologic model development and calibration. The source code and data representation/analysis figures are also made available in the data repository.
- Keyword:
- Great Lakes, Hydrometeorological, National Water Model, Daily, Overlake precipitation, Overlake evaporation, Total runoff, Net Basin Supply, and Water Balance
- Discipline:
- Science and Engineering
-
- Creator:
- Vo, Thi and Glotzer, Sharon C.
- Description:
- The goal of this project is to develop a first principle driven approach for predicting the self-assembly behavior of entropically driven crystallization. We first developed a set of mean-field theoretical framework that captures the relevant energetic contributions to the assembly process and then evaluate relevant terms within our framework to determine the excess free energy of formation for each lattice (matlab/octave codes). We then validate theoretical predictions of relevant features like shape and bonding orbitals using standard MD simulations using HOOMD-Blue (simulation scripts). and This research was supported by the Office of the Undersecretary of Defense for Research and Engineering (OUSD(R&E)), Newton Award for Transformative Ideas during the COVID-19 Pandemic, Award number HQ00342010030.
- Keyword:
- Self-Assembly, Entropy, Thermodynamics, Simulations, and Theory
- Citation to related publication:
- Vo, T., & Glotzer, S. C. (2021). Microscopic Theory of Entropic Bonding for Colloidal Crystal Prediction. ArXiv:2107.02081 [Cond-Mat]. http://arxiv.org/abs/2107.02081
- 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:
- Penner, Joyce E., Zhou, Cheng, Garnier, Anne, and Mitchell, David
- Description:
- This data set contains the scripts and data sets needed to create the 9 figures in the referenced publication.
- Keyword:
- Anthropogenic Aerosol indirect effects, cirrus clouds, and ice nucleation
- Citation to related publication:
- Penner, J. E., Zhou, C., Garnier, A., & Mitchell, D. L. (2018). Anthropogenic aerosol indirect effects in cirrus clouds. Journal of Geophysical Research: Atmospheres,123, 11,652–11,677. https://doi.org/10.1029/2018JD029204
- Discipline:
- Science
-
- Creator:
- Nasser, Ahmad and Gumise, Wonder
- Description:
- The work on accelerating authenticated boot for embedded system resulted in designing an algorithm in python to perform the random address generation and cryptographic MAC calculation. The Sampled Boot schemes implemented in this package allow a significant reduction of the time needed to authenticate firmware images during startup, while still retaining a high degree of trust. This is particularly useful for automotive applications in which startup time constraints make secure boot a time prohibitive process. and Citation for this dataset: Nasser, A., Gumise, W. (2019). Authenticated Boot Acceleration Algorithm [Code and data]. University of Michigan Deep Blue Data Repository. https://doi.org/10.7302/yeh1-1x17
- Keyword:
- Trusted Computing, IOT security, Embedded Security, and Cyber Physical Systems
- Citation to related publication:
- Nasser, A., Gumise, W., and Ma, D., "Accelerated Secure Boot for Real-Time Embedded Safety Systems," SAE Int. J. Transp. Cyber. & Privacy 2(1) : 35-48, 2019, https://doi.org/10.4271/11-02-01-0003
- Discipline:
- Science
-
- Creator:
- Zhang, Yizhen
- Description:
- We collected hours of functional magnetic resonance imaging data from human subjects listening to natural stories. We developed a predictive model of the voxel-wise response and further applied it to thousands of new words to understand how the brain stores and connects different concepts. and This is a dataset for the paper: Zhang, Y., Han, K., Worth, R., & Liu, Z. (2020). Connecting concepts in the brain by mapping cortical representations of semantic relations. Nature communications, 11(1), 1-13. https://doi.org/10.1038/s41467-020-15804-w. This project is also documented at https://osf.io/eq2ba/.
- Keyword:
- fMRI, natural story comprehension, neural encoding, semantic processing, word relations, and naturalistic stimuli
- Citation to related publication:
- Zhang, Y., Han, K., Worth, R., & Liu, Z. (2020). Connecting concepts in the brain by mapping cortical representations of semantic relations. Nature communications, 11(1), 1-13. https://doi.org/10.1038/s41467-020-15804-w
- Discipline:
- Science
-
- Creator:
- Figueroa, Carlos A., Computational Vascular Biomechanics Lab, University of Michigan, and et al.
- Description:
- This collection concerns the CRIMSON (CardiovasculaR Integrated Modelling and SimulatiON) software environment. CRIMSON provides a powerful, customizable and user-friendly system for performing three-dimensional and reduced-order computational haemodynamics studies via a pipeline which involves: 1) segmenting vascular structures from medical images; 2) constructing analytic arterial and venous geometric models; 3) performing finite element mesh generation; 4) designing, and 5) applying boundary conditions; 6) running incompressible Navier-Stokes simulations of blood flow with fluid-structure interaction capabilities; and 7) post-processing and visualizing the results, including velocity, pressure and wall shear stress fields. , The minimum specifications to run CRIMSON are: Any AMD64 CPU (note: Intel Core i series are AMD64), Windows (only tested on Windows 10 but might work on Windows 7), 8 GB of RAM , If you are running non-trivial models you will want to have: Quad core CPU or higher, Solid state drive for storing data, Windows, 16 GB of RAM, Dedicated discrete GPU for rendering models. , and Software in this collection is a snapshot; please visit https://github.com/carthurs/CRIMSONGUI & www.crimson.software for more general information and the most up to date version of the software.
- Keyword:
- Blood Flow Simulation, Patient-specific, Open-source Software, Image-based simulation, Cardiovascular Medical Image, Segmentation, and Finite Element Simulation
- Citation to related publication:
- CRIMSON: An Open-Source Software Framework for Cardiovascular Integrated Modelling and Simulation C.J. Arthurs, R. Khlebnikov, A. Melville, et al. bioRxiv 2020.10.14.339960; doi: https://doi.org/10.1101/2020.10.14.339960
- Discipline:
- Health Sciences and Engineering
4Works -
- Creator:
- Arthurs, Christopher J., Khlebnikov, Rostislav, Melville, Alexander, Marčan, Marija, Gomez, Alberto, Dillon-Murphy, Desmond, Cuomo, Federica, Vieira, Miguel, Schollenberger, Jonas, Lynch, Sabrina, Tossas-Betancourt, Christopher, Iyer, Kritika, Hopper, Sara, Livingston, Elizabeth, Youssefi, Pouya, Noorani, Alia, Ben Ahmed, Sabrina, Nauta, Foeke J.N., van Bakel, Theodorus M.J., Ahmed, Yunus, van Bakel, Petrus A.J., Mynard, Jonathan, Di Achille, Paolo, Gharahi, Hamid, Lau, Kevin D., Filonova, Vasilina, Aguirre, Miquel, Nama, Nitesh, Xiao, Nan, Baek, Seungik, Garikipati, Krishna, Sahni, Onkar, Nordsletten, David, and Figueroa, Carlos A.
- Description:
- This repository contains the source code for the CRIMSON Flow Solver as required in the PLOS Computational Biology publication: CRIMSON: An Open-Source Software Framework for Cardiovascular Integrated Modelling and Simulation by the same authors., This is a snapshot of the software. Please visit https://github.com/carthurs/CRIMSONFlowsolver/releases/tag/PLOS_Comp_Bio & www.crimson.software for more general information and the most up to date version of the software. , and Software can be compiled in Cygwin and Linux.
- Keyword:
- Blood Flow Simulation, Patient-specific, Open-source Software, Image-based simulation, Cardiovascular Medical Image, Segmentation, and Finite Element Simulation
- Citation to related publication:
- CRIMSON: An Open-Source Software Framework for Cardiovascular Integrated Modelling and Simulation C.J. Arthurs, R. Khlebnikov, A. Melville, M. Marčan, A. Gomez, D. Dillon-Murphy, F. Cuomo, M.S. Vieira, J. Schollenberger, S.R. Lynch, C. Tossas-Betancourt, K. Iyer, S. Hopper, E. Livingston, P. Youssefi, A. Noorani, S. Ben Ahmed, F.J.H. Nauta, T.M.J. van Bakel, Y. Ahmed, P.A.J. van Bakel, J. Mynard, P. Di Achille, H. Gharahi, K. D. Lau, V. Filonova, M. Aguirre, N. Nama, N. Xiao, S. Baek, K. Garikipati, O. Sahni, D. Nordsletten, C.A. Figueroa bioRxiv 2020.10.14.339960; doi: https://doi.org/10.1101/2020.10.14.339960 and Arthurs, C., Khlebnikov, R., Melville, A., Marčan, M., Gomez, A., Dillon-Murphy, D., Cuomo, F., Vieira, M., Schollenberger, J., Lynch, S., Tossas-Betancourt, C., Iyer, K., Hopper, S., Livingston, E., Youssefi, P., Noorani, A., Ben Ahmed, S., Nauta, F., van Bakel, T., Ahmed, Y., van Bakel, P., Mynard, J., Di Achille, P., Gharahi, H., Lau, K., Filonova, V., Aguirre, M., Nama, N., Xiao, N., Baek, S., Garikipati, K., Sahni, O., Nordsletten, D., Figueroa, C. (2021). CRIMSON open source project - Graphical User Interface (GUI) Source Code for PLOS Computational Biology [Data set]. University of Michigan - Deep Blue. https://doi.org/10.7302/679b-dw96
- Discipline:
- Engineering and Health Sciences
-
- Creator:
- Arthurs, Christopher J., Khlebnikov, Rostislav, Melville, Alexander, Marčan, Marija, Gomez, Alberto, Dillon-Murphy, Desmond, Cuomo, Federica, Vieira, Miguel, Schollenberger, Jonas, Lynch, Sabrina, Tossas-Betancourt, Christopher, Iyer, Kritika, Hopper, Sara, Livingston, Elizabeth, Youssefi, Pouya, Noorani, Alia, Ben Ahmed, Sabrina, Nauta, Foeke J.N., van Bakel, Theodorus M.J., Ahmed, Yunus, van Bakel, Petrus A.J., Mynard, Jonathan, Di Achille, Paolo, Gharahi, Hamid, Lau, Kevin D., Filonova, Vasilina, Aguirre, Miquel, Nama, Nitesh, Xiao, Nan, Baek, Seungik, Garikipati, Krishna, Sahni, Onkar, Nordsletten, David, and Figueroa, Carlos A.
- Description:
- This repository contains the source code for the CRIMSON GUI, as required in the PLOS Computational Biology publication: CRIMSON: An Open-Source Software Framework for Cardiovascular Integrated Modelling and Simulation by the same authors., This is a snapshot of the software; build dependencies can be found at https://doi.org/10.7302/ssj9-n788. Please visit https://github.com/carthurs/CRIMSONGUI/releases/tag/PLOS_Comp_Bio & www.crimson.software for more general information and the most up to date version of the software., and Software can be compiled in Windows.
- Keyword:
- Blood Flow Simulation, Patient-specific, Open-source Software, Image-based simulation, Cardiovascular Medical Image, Segmentation, and Finite Element Simulation
- Citation to related publication:
- CRIMSON: An Open-Source Software Framework for Cardiovascular Integrated Modelling and Simulation C.J. Arthurs, R. Khlebnikov, A. Melville, M. Marčan, A. Gomez, D. Dillon-Murphy, F. Cuomo, M.S. Vieira, J. Schollenberger, S.R. Lynch, C. Tossas-Betancourt, K. Iyer, S. Hopper, E. Livingston, P. Youssefi, A. Noorani, S. Ben Ahmed, F.J.H. Nauta, T.M.J. van Bakel, Y. Ahmed, P.A.J. van Bakel, J. Mynard, P. Di Achille, H. Gharahi, K. D. Lau, V. Filonova, M. Aguirre, N. Nama, N. Xiao, S. Baek, K. Garikipati, O. Sahni, D. Nordsletten, C.A. Figueroa bioRxiv 2020.10.14.339960; doi: https://doi.org/10.1101/2020.10.14.339960 and Computational Vascular Biomechanics Lab @ the University of Michigan and other collaborators, The Qt Company, NSIS Team and contributors, PostgreSQL Global Development Group, Oracle Corporation, Kitware. CRIMSON open source project - Build Dependencies [Data set], (2021). University of Michigan - Deep Blue. https://doi.org/10.7302/ssj9-n788
- Discipline:
- Health Sciences and Engineering
-
- Creator:
- Liemohn, Michael W, Adam, Joshua G, and Ganushkina, Natalia Y
- Description:
- Many statistical tools have been developed to aid in the assessment of a numerical model’s quality at reproducing observations. Some of these techniques focus on the identification of events within the data set, times when the observed value is beyond some threshold value that defines it as a value of keen interest. An example of this is whether it will rain, in which events are defined as any precipitation above some defined amount. A method called the sliding threshold of observation for numeric evaluation (STONE) curve sweeps the event definition threshold of both the model output and the observations, resulting in the identification of threshold intervals for which the model does well at sorting the observations into events and nonevents. An excellent data-model comparison will have a smooth STONE curve, but the STONE curve can have wiggles and ripples in it. These features reveal clusters when the model systematically overestimates or underestimates the observations. This study establishes the connection between features in the STONE curve and attributes of the data-model relationship. The method is applied to a space weather example.
- Keyword:
- space physics, statistical methods, and STONE curve
- Citation to related publication:
- Liemohn, M. W., Adam, J. G., & Ganushkina, N. Y. (2022). Analysis of features in a sliding threshold of observation for numeric evaluation (STONE) curve. Space Weather, 20, e2022SW003102. https://doi.org/10.1029/2022SW003102
- Discipline:
- Science
-
- Creator:
- Malhotra, Garima and Ridley, Aaron
- Description:
- This research aims to understand the importance of lower thermospheric atomic oxygen on the upper thermosphere. O number densities between 95-100 km from WACCM-X are much closer to the observations from SABER instrument on TIMED satellite as compared to those from MSIS. We show in this study that the correction of the lower boundary atomic oxygen yields better agreement between GITM and GUVI O/N2 in the upper thermosphere .
- Keyword:
- Lower Thermosphere Atomic Oxygen, Thermospheric Dynamics, Thermospheric composition and mixing, Lower-Upper Thermosphere Vertical Coupling, GITM - WACCMX coupling, and Global Ionosphere Thermosphere Model
- Citation to related publication:
- Malhotra, G., Ridley, A. J., Marsh, D. R., Wu, C., Paxton, L. J., & Mlynczak, M. G. (2020). Impacts of Lower Thermospheric Atomic Oxygen on Thermospheric Dynamics and Composition Using the Global Ionosphere Thermosphere Model. Journal of Geophysical Research: Space Physics, e2020JA027877. https://doi.org/10.1029/2020JA027877
- Discipline:
- Science
-
- Creator:
- Swiger, Brian M., Liemohn, Michael W., and Ganushkina, Natalia Y.
- Description:
- We sampled the near-Earth plasma sheet using data from the NASA Time History of Events and Macroscale Interactions During Substorms mission. For the observations of the plasma sheet, we used corresponding interplanetary observations using the OMNI database. We used these data to develop a data-driven model that predicts plasma sheet electron flux from upstream solar wind variations. The model output data are included in this work, along with code for analyzing the model performance and producing figures used in the related publication. and Data files are included in hdf5 and Python pickle binary formats; scripts included are set up for use of Python 3 to access and process the pickle binary format data.
- Keyword:
- neural network, plasma sheet, solar wind, machine learning, keV electron flux, deep learning, and space weather
- Citation to related publication:
- Swiger, B. M., Liemohn, M. W., & Ganushkina, N. Y. (2020). Improvement of Plasma Sheet Neural Network Accuracy With Inclusion of Physical Information. Frontiers in Astronomy and Space Sciences, 7. https://doi.org/10.3389/fspas.2020.00042
- Discipline:
- Science and Engineering
-
- Creator:
- Liemohn, Michael W
- Description:
- Earth’s upper atmosphere above 500 km altitude constantly loses charged particles to outer space in a process called ionospheric outflow. This outflow is important for the dynamics of the near-Earth space environment (“space weather”) yet is poorly understood on a global scale. A mission is needed to observe the global patterns of ionospheric outflow and its relation to space weather driving conditions. The science objectives of such a mission could include not only the reconstruction of global outflow patterns but also the relation of these patterns to geomagnetic activity and the spatial and temporal nature of outflow composition. A study is presented to show that four well-placed spacecraft would be sufficient for reasonable outflow reconstructions.
- Keyword:
- ionosphere, magnetosphere, satellite mission concept, and space weather
- Citation to related publication:
- Liemohn, M. W., Jörg-Micha Jahn, Raluca Ilie, Natalia Y. Ganushkina, Daniel T. Welling, Heather Elliott, Meghan Burleigh, Kaitlin Doublestein, Stephanie Colon-Rodriguez, Pauline Dredger, & Philip Valek (2024). Reconstruction analysis of global ionospheric outflow patterns. Journal of Geophysical Research Space Physics, 129, e2023JA032238. https://doi/org/10.1029/2024JA032238
- Discipline:
- Science
-
- Creator:
- Mukhopadhyay, Agnit, Daniel T Welling, Michael W Liemohn, Aaron J Ridley, Shibaji Chakrabarty, and Brian J Anderson
- Description:
- An updated auroral conductance module is built for global models, using nonlinear regression & empirical adjustments to span extreme events., Expanded dataset raises the ceiling of conductance values, impacting the ionospheric potential dB/dt & dB predictions during extreme events., and Application of the expanded model with empirical adjustments refines the conductance pattern, and improves dB/dt predictions significantly.
- Keyword:
- Space Weather Forecasting, Extreme Weather, Ionosphere, Magnetosphere, MI Coupling, Ionospheric Conductance, Auroral Conductance, Aurora, SWMF, SWPC, Nonlinear Regression, and dB/dt
- Citation to related publication:
- Mukhopadhyay, A., Welling, D. T., Liemohn, M. W., Ridley, A. J., Chakraborty, S., & Anderson, B. J. (2020). Conductance Model for Extreme Events: Impact of Auroral Conductance on Space Weather Forecasts. Space Weather, 18(11), e2020SW002551. https://doi.org/10.1029/2020SW002551
- Discipline:
- Engineering and Science
-
- Creator:
- Agnit Mukhopadhyay
- Description:
- Conducting quantitative metrics-based performance analysis of first-principles-based global magnetosphere models is an essential step in understanding their capabilities and limitations, and providing scope for improvements in order to enhance their space weather prediction capabilities for a range of solar conditions. In this study, a detailed comparison of the performance of three global magnetohydrodynamic (MHD) models in predicting the Earth’s magnetopause location and ionospheric cross polar cap potential (CPCP) has been presented. Using the Community Coordinated Modeling Center’s Run-on-Request system and extensive database on results from various magnetospheric scenarios simulated for a variety of solar wind conditions, the aforementioned model predictions have been compared for magnetopause standoff distance estimations obtained from six empirical models, and with cross polar cap potential estimations obtained from the Assimmilative Mapping of Ionospheric Electrodynamics (AMIE) Model and the Super Dual Auroral Radar Network (SuperDARN) observations. We have considered a range of events spanning different space weather activity to analyze the performance of these models. Using a fit performance metric analysis for each event, we have quantified the models’ reproducibility of magnetopause standoff distances and CPCP against empirically-predicted observations, and identified salient features that govern the performance characteristics of the modeled magnetospheric and ionospheric quantities.
- Citation to related publication:
- Mukhopadhyay, A., Jia, X., Welling, D. T., & Liemohn, M. W. (2021). Global Magnetohydrodynamic Simulations: Performance Quantification of Magnetopause Distances and Convection Potential Predictions. Frontiers in Astronomy and Space Sciences, 8. https://doi.org/10.3389/fspas.2021.637197
- Discipline:
- Engineering and Science
-
- Creator:
- Zhou, Hongyang
- Description:
- The largest moon in the solar system, Ganymede, is the only moon known to possess a strong intrinsic magnetic field and a corresponding magnetosphere. Using the latest version of Space Weather Modeling Framework (SWMF), we study the upstream plasma interactions and dynamics in this sub-Alfvenic system. Results from the Hall MHD and the coupled MHD with embedded Particle-in-Cell (MHD-EPIC) models are compared. We find that under steady upstream conditions, magnetopause reconnection occurs in a non-steady manner. Flux ropes of Ganymede's radius in length form on the magnetopause at a rate about 2/minute and create spatiotemporal variations in plasma and field properties. Upon reaching proper grid resolutions, the MHD-EPIC model can resolve both electron and ion kinetics at the magnetopause and show localized non-gyrotropic behavior inside the diffusion region. The estimated global reconnection rate from the models is about 80 kV with 60% efficiency, and there is weak evidence of about 1 minute periodicity in the temporal variations due to the dynamic reconnection process.
- Keyword:
- MHD, PIC, Ganymede, and magnetosphere
- Citation to related publication:
- Zhou, H., Tóth, G., Jia, X., & Chen, Y. (2020). Reconnection-Driven Dynamics at Ganymede’s Upstream Magnetosphere: 3-D Global Hall MHD and MHD-EPIC Simulations. Journal of Geophysical Research: Space Physics, 125(8), e2020JA028162. https://doi.org/10.1029/2020JA028162
- Discipline:
- Science
-
- Creator:
- Ahluwalia, Vinayak S., Steimle, Lauren N., and Denton, Brian T.
- Description:
- This repository includes test instances of infinite-horizon Markov decision processes with multiple models of parameters (i.e., "Multi-model Markov decision processes"). We generated each test instance in the dataset using a Python script. The test instances can be read in using the provided C++ and Python script. See the README for details.
- Keyword:
- Markov decision processes, mixed-integer programming, stochastic programming, and dynamic programming
- Citation to related publication:
- Ahluwalia, Steimle, and Denton. "Policy-based branch-and-bound for infinite-horizon Multi-model Markov decision processes". 2020.
- Discipline:
- Engineering
-
- Creator:
- Dariya, Malyarenko, Tariq, Humera, Kushwaha, Aman, Mourad, Rami, Heist, Kevin, Chenevert, Thomas L, Ross, Brian D, Chen, Heang-Ping, and Hadjiiski, Lubomir
- Description:
- The 3D GRE MRI data for murine model of myelofbifrosis with expert segmentations of mouse tibia was used to train Attention UNET model to automate bone marrow segmentation for measurements of imaging biomarkers. This dataset consists of three archives: (1) containing the source MRI images in Meta-image-header (MHD) format with resulting segmentation labels by two experts and four UNET models with different training scenarios; (2) corresponding training models; and (3) deep-learning (DL)-based segmentation tools for application to future murine tibia MRI data. and The MHD images are an ITK compatible format that can be viewed in standard image viewer, like 3D Slicer. The image archive is structured with a directory tree that contains \"mouseID"\"scan-date"\"segmentaion-scenario"\. The "training model" archive containes DL-model labeled by the data subset, and "deployment" archive containes the DL-segmentation software.
- Keyword:
- deep-learning segmentation, preclinical MRI, murine tibia, and mouse model of myelofibrosis
- Citation to related publication:
- Kushwaha A, Mourad RF, Heist K, Tariq H, Chan HP, Ross BD, Chenevert TL, Malyarenko D, Hadjiiski LM. Improved Repeatability of Mouse Tibia Volume Segmentation in Murine Myelofibrosis Model Using Deep Learning. Tomography. 2023 Mar 7;9(2):589-602. doi: 10.3390/tomography9020048. PMID: 36961007; PMCID: PMC10037585. and https://github.com/dumichgh/MFJK1_Segmentation_MHDs
- Discipline:
- Health Sciences
-
- Creator:
- Eckels, Joshua D.
- Description:
- The goal of the research was to train a surrogate model for the prediction of electric field distribution for a given electrospray emitter geometry design. The surrogate is to be used in reduced-fidelity modeling of electrospray thruster arrays. The code repository is included in the README.txt file.
- Keyword:
- Electrospray design, Martinez-Sanchez hyperboloid solution, and Electrospray engineering toolkit (ESPET)
- Citation to related publication:
- J.D. Eckels, C.B. Whittaker, B.A. Jorns, A.A. Gorodetsky, B. St. Peter, R.A. Dressler, “Simulation-based surrogate methodology of electric field for electrospray emitter geometry design and uncertainty quantification”, presented at the 37th International Electric Propulsion Conference, Boston, MA USA, June19-23, 2022 Available: https://www.electricrocket.org/IEPC_2022_Papers.html
- Discipline:
- Engineering
-
- Creator:
- Nason, Samuel R., Mender, Matthew J., Vaskov, Alex K., Willsey, Matthew S., Ganesh Kumar, N., Kung, Theodore A., Patil, Parag G., and Chestek, Cynthia A.
- Description:
- This data is a subset of the data used to generate components of all figures in the manuscript and supplement in Nason et al., 2021, Neuron. The purpose of the study was to demonstrate the first-ever simultaneous brain-control of two independent groups of fingers in one hand with some analysis of cortical tuning to finger movements in nonhuman primates. This advises future brain-machine interfaces for the control of finger movements with humans. All of the data is contained in .mat files, which can be commonly opened by Matlab and the Python scipy library. The Matlab packages (and versions) used for the manuscript are: MATLAB (9.4), Signal Processing Toolbox (8.0), Statistics and Machine Learning Toolbox (11.3), and Curve Fitting Toolbox (3.5.7).
- Keyword:
- Brain-machine interface, Prosthesis, and Upper extremity
- Citation to related publication:
- Nason, S.R., Mender, M.J., Vaskov, A.K., Willsey, M.S., Ganesh Kumar, N., Kung, T.A., Patil, P.G., and Chestek, C.A. (2021). Real-Time Linear Prediction of Simultaneous and Independent Movements of Two Finger Groups Using an Intracortical Brain-Machine Interface. Neuron (accepted).
- Discipline:
- Engineering