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- 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:
- 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 includes the following:, - Example Case A: complete process of creating a model, running the simulation and examining the results., - Example Case B: segmenting and imposing a patient-specific aortic inflow velocity profile from a provide PC-MRI dataset., - Example Case C: simulation of a patient under rest conditions, and then of the same patient under post-liver-transplant conditions., - GUI Windows Binary Executable (version 2019.11.01), and - Flow Solver Windows Binary Executable (version 1.4.4, 2019.11.01)
- 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
- Discipline:
- Engineering and Health Sciences
-
- Creator:
- Hegedus, Alexander M
- Description:
- This is the README for the LunarSynchrotronArray package, maintained by Dr. Alex Hegedus alexhege@umich.edu This code repository corresponds to the Hegedus et al. 2020 (accepted) Radio Science paper, "Measuring the Earth's Synchrotron Emission from Radiation Belts with a Lunar Near Side Radio Array". The arxiv link for the paper is https://arxiv.org/abs/1912.04482. The DOI link is https://doi.org/10.1029/2019RS006891 , The Earth's Ionosphere is home to a large population of energetic electrons that live in the balance of many factors including input from the Solar wind, and the influence of the Earth's magnetic field. These energetic electrons emit radio waves as they traverse Earth's magnetosphere, leading to short‐lived, strong radio emissions from local regions, as well as persistent weaker emissions that act as a global signature of the population breakdown of all the energetic electrons. Characterizing this weaker emission (Synchrotron Emission) would lead to a greater understanding of the energetic electron populations on a day to day level. A radio array on the near side of the Moon would always be facing the Earth, and would well suited for measuring its low frequency radio emissions. In this work we simulate such a radio array on the lunar near side, to image this weaker synchrotron emission. The specific geometry and location of the test array were made using the most recent lunar maps made by the Lunar Reconnaissance Orbiter. This array would give us unprecedented day to day knowledge of the electron environment around our planet, providing reports of Earth's strong and weak radio emissions, giving both local and global information. , This set of codes should guide you through making the figures in the paper, as well as hopefully being accessible enough for changing the code for your own array. I would encourage you to please reach out to collaborate if that is the case! Requirements: , and CASA 4.7.1 (or greater?) built on python 2.7 Example link for Red Hat 7 https://casa.nrao.edu/download/distro/casa/release/el7/casa-release-4.7.1-el7.tar.gz Users may follow this guide to download and install the correct version of CASA for their system https://casa.nrao.edu/casadocs/casa-5.5.0/introduction/obtaining-and-installing CASA executables should be fairly straightforward to extract from the untarred files. gcc 4.8.5 or above (or below?) GCC installation instructions can be found here: https://gcc.gnu.org/install/ SPICE (I use cspice here) https://naif.jpl.nasa.gov/naif/toolkit_C.html As seen in lunar_furnsh.txt which loads the SPICE kernels, you also must download KERNELS_TO_LOAD = ( '/home/alexhege/SPICE/LunarEph/moon_pa_de421_1900-2050.bpc' '/home/alexhege/SPICE/LunarEph/moon_080317.tf' '/home/alexhege/SPICE/LunarEph/moon_assoc_me.tf' '/home/alexhege/SPICE/LunarEph/pck00010.tpc' '/home/alexhege/SPICE/LunarEph/naif0008.tls' '/home/alexhege/SPICE/LunarEph/de430.bsp' ) All of which can be found at https://naif.jpl.nasa.gov/pub/naif/generic_kernels/ SLDEM2015_128_60S_60N_000_360_FLOAT.IMG for the lunar surface data by LRO LOLA found at http://imbrium.mit.edu/DATA/SLDEM2015/GLOBAL/FLOAT_IMG/
- Citation to related publication:
- Hegedus, A., Nenon, Q., Brunet, A., Kasper, J., Sicard, A., Cecconi, B., MacDowall, R., & Baker, D. (2019). Measuring the Earth's Synchrotron Emission from Radiation Belts with a Lunar Near Side Radio Array. https://arxiv.org/abs/1912.04482 and Hegedus, A., Nenon, Q., Brunet, A., Kasper, J., Sicard, A., Cecconi, B., MacDowall, R., & Baker, D. (2020). Radio Science. https://doi.org/10.1029/2019RS006891
- Discipline:
- Engineering and Science
-
- Creator:
- Chen, Yang and Manchester, Ward IV
- Description:
- GOES_flare_list: contains a list of more than 10,000 flare events. The list has 6 columns, flare classification, active region number, date, start time end time, emission peak time, GOES_B_flare_list: contains time series data of SDO/HMI SHARP parameters for B class solar flares , GOES_MX_flare_list: contains time series data of SDO/HMI SHARP parameters for M and X class solar flares, SHARP_B_flare_data_300.hdf5 and SHARP_MX_flare_data_300.hdf5 files contain time series more than 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., and B_HARPs_CNNencoded_part_xxx.hdf5 and M_X HARPs_CNNencoded_part_xxx.hdf5 include neural network encoded features derived from vector magnetogram images derived from the Solar Dynamics Observatory (SDO) Helioseismic and Magnetic Imager (HMI). These data files typically contains one or two sequences of magnetograms covering an active region for a period of 24h with a 1 hour cadence. We encode each magnetogram with frames of a fixed size of 8x16 with 512 channels.
- Keyword:
- machine learning, data science, and solar flare prediction
- Citation to related publication:
- Chen, Y., Manchester, W., Hero, A., Toth, G., DuFumier, B. Zhou, T., Wang, X., Zhu, H., Sun, Zeyu, Gombosi, T., Identifying Solar Flare Precursors Using Time Series of SDO/HMI Images and SHARP Parameters, Space Weather, 17, 1404–1426. https://doi.org/10.1029/2019SW002214 and Jiao, Z., Chen, Y., Manchester, W. (2020). Data for Solar Flare Intensity Prediction with Machine Learning Models [Data set]. University of Michigan - Deep Blue. https://doi.org/10.7302/b07j-bj08
- Discipline:
- Engineering and Science
-
- Creator:
- Mathieu, Johanna L, Balzano, Laura, and Ledva, Gregory S
- Description:
- This data set contains the relevant time series for constructing and testing electricity load models within the related paper. The files within are a '.mat' file that contains the data and a 'readme.txt' file detailing the contents of the data.
- Keyword:
- Output feedback, Online learning, Machine learning, Real-time filtering, and Energy disaggregation
- Discipline:
- Engineering
-
- Creator:
- Attari, Ali
- Description:
- Please refer to the "README.txt" for more details., MATLAB R2018a (Mathworks, Natick, MA, USA) was used to process this data., and Excel (Microsoft Office) was used to store survey data on the comfort of both systems and also to provide absolute and relative intraobserver variablities for the DM device.
- Keyword:
- Digital Manometry
- Citation to related publication:
- Comparison of anorectal function measured using wearable digital manometry and a high resolution manometry system Attari A, Chey WD, Baker JR, Ashton-Miller JA (2020) Comparison of anorectal function measured using wearable digital manometry and a high resolution manometry system. PLOS ONE 15(9): e0228761. https://doi.org/10.1371/journal.pone.0228761
- Discipline:
- Engineering, Science, and Health Sciences
-
- Creator:
- Whitaker, Steven T., Nataraj, Gopal, Nielsen, Jon-Fredrik, and Fessler, Jeffrey A.
- Description:
- File: P,jf06Sep2019,mese.7 The multi-echo spin echo (MESE) data was acquired using a 3D acquisition with an initial 90 degree excitation pulse followed by 32 refocusing (180 degree) pulses, resulting in 32 echoes with echo spacing of 10 ms. The repetition time of the sequence was 1200 ms. Each refocusing pulse was flanked by crusher gradients to impart 14 cycles of phase across the imaging volume. The initial excitation pulse had time-bandwidth product of 6, duration of 3 ms, and slab thickness of 0.9 cm, and each refocusing pulse had time-bandwidth product of 2, duration of 2 ms, and slab thickness of 2.1 cm. The scan took 36 min 11 s and covered a field of view (FOV) of 22 x 22 x 0.99 cm^3 with matrix size 200 x 200 x 9., File: P,jf06Sep2019,b1.7 The Bloch-Siegert (BS) scans were acquired using a 3D acquisition. The excitation pulse of these scans had time-bandwidth product of 8 and duration of 1 ms. The pair of scans used +/-4 kHz off-resonant Fermi pulses between excitation and readout. The BS scans took 2 min 40 s in total and covered a FOV of 22 x 22 x 0.99 cm^3 with matrix size 200 x 50 x 9., File: P,jf06Sep2019,mwf.7 The small-tip fast recovery (STFR) scans were acquired using a 3D acquisition. The first two and last two scans were pairs of spoiled gradient-recalled echo (SPGR) scans with echo time difference of 2.3 ms. (In the related paper, only the first set was used, i.e., only 11 of the 13 scans were used.) The remaining scans used scan parameters that were optimized to minimize the Cramer-Rao Lower Bound (CRLB) of estimates of myelin water fraction (MWF). The RF pulses had time-bandwidth product of 8 and duration of 1 ms. Each pair of SPGR scans took 58 s and the nine STFR scans took 3 min 36 s for a total scan time of 5 min 32 s (4 min 34 s if one pair of SPGR scans is ignored). The scans covered a field of view (FOV) of 22 x 22 x 0.99 cm^3 with matrix size 200 x 200 x 9., File: meseslice5.mat Contains the 32 echoes of the MESE image data for the middle slice of the imaging volume. Saved using Mathworks MATLAB R2019a., File: b1slice5.mat Contains the transmit field inhomogeneity map for the middle slice of the imaging volume., File: recon.jld Key "img" contains the 11 STFR images for the middle slice of the imaging volume. Key "b0map" contains a field map estimated from the two SPGR scans. Key "mask" contains a mask of the voxels for which to estimate MWF. Key "T1img" contains a T1-weighted image for anatomical reference., File: headmask.mat Contains a mask for visualizing just the brain (ignores the skull) for the middle slice of the imaging volume., File: rois.mat Contains masks for various regions of interest (ROIs), used for computing statistics. Keys "mtopleft", "mtopright", "mbottomleft", and "mbottomright" refer to the corresponding locations on the anatomical reference image (see related paper). Key "mic" refers to the internal capsules, and key "mgm" refers to a gray matter ROI., The raw data files (P-files) can be read into the Julia programming language using the Julia version of the Michigan Image Reconstruction Toolbox ( https://github.com/JeffFessler/MIRT.jl) or into MATLAB using TOPPE ( https://github.com/toppeMRI/toppe). The reconstructed slices used in the related paper are provided for convenience, and are stored in .mat files that can be loaded into Julia (using the package MAT.jl) or MATLAB, and a .jld file that can be loaded into Julia (using the package JLD.jl). The Julia code for processing the data to create MWF maps is hosted publicly on GitHub at https://github.com/StevenWhitaker/STFR-MWF., and Files: toppe-master.zip and MIRT.jl-master.zip are archived versions of the TOPPE and Michigan Image Reconstruction Toolbox code sets from GitHub as of 2/28/2020.
- Keyword:
- myelin, machine learning, kernel learning, magnetic resonance imaging, and scan design
- Citation to related publication:
- Whitaker, S. T., Nataraj, G., Nielsen, J.-F., & Fessler, J. A. (2020). Myelin water fraction estimation using small-tip fast recovery MRI. Magnetic Resonance in Medicine, 84(4), 1977–1990. https://doi.org/10.1002/mrm.28259
- Discipline:
- Health Sciences and Engineering
-
- Creator:
- Grosh, Karl and Li, Yizeng
- Description:
- In a sensitive cochlea, the basilar membrane response to transient excitation of any kind--normal acoustic or artificial intracochlear excitation--consists of not only a primary impulse but also a coda of delayed secondary responses with varying amplitudes but similar spectral content around the characteristic frequency of the measurement location. The coda, sometimes referred to as echoes or ringing, has been described as a form of local, short term memory which may influence the ability of the auditory system to detect gaps in an acoustic stimulus such as speech. Depending on the individual cochlea, the temporal gap between the primary impulse and the following coda ranges from once to thrice the group delay of the primary impulse (the group delay of the primary impulse is on the order of a few hundred microseconds). The coda is physiologically vulnerable, disappearing when the cochlea is compromised even slightly. The multicomponent sensitive response is not yet completely understood. We use a physiologically-based, mathematical model to investigate (i) the generation of the primary impulse response and the dependence of the group delay on the various stimulation methods, (ii) the effect of spatial perturbations in the properties of mechanically sensitive ion channels on the generation and separation of delayed secondary responses. The model suggests that the presence of the secondary responses depends on the wavenumber content of a perturbation and the activity level of the cochlea. In addition, the model shows that the varying temporal gaps between adjacent coda seen in experiments depend on the individual profiles of perturbations. Implications for non-invasive cochlear diagnosis are also discussed.
- Discipline:
- Engineering and Health Sciences
-
- Creator:
- Fries, Kevin J
- Description:
- This data is in support of the publication in review "Using sensor data to dynamically map large-scale models to site-scale forecasts: A case study using the National Water Model". It is all the raw data extracted from the NWM flow forecasts for Iowa and the IFIS stage readings. For the NWM data, each date has it's own tab-delimited file with columns being the time (hrs) and rows being the NHD site. For the IFIS gages, each tab delimited file is for a single site for the period of record.
- Keyword:
- student-friendly
- Discipline:
- Engineering