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- Creator:
- Hung, Adam, Enninful Adu, Challen, and Moore, Talia Y.
- Description:
- The CAD files can be opened by any CAD software. The code is in Arduino and Python. The URDF was generated using Solidworks.
- Keyword:
- robotics, omnidirectional, tripod, ballbot, gliding, and rolling
- Citation to related publication:
- Hung, A., Enninful Adu, C., Moore, T.Y. (in review), SKOOTR: A SKating, Omni-Oriented, Tripedal Robot for dynamically stable indoor navigation. IEEE ICRA
- Discipline:
- Engineering
-
- Creator:
- Ponder, Brandon M., Ridley, Aaron J., Goel, Ankit, and Bernstein, Dennis S.
- Description:
- This research was completed to statistically validate that a data-model refinement technique could integrate real measurements to remove bias from physics-based models via changing the forcing parameters such as the thermal conductivity coefficients.
- Keyword:
- Thermosphere, GITM, CHAMP, GRACE, MSIS, Upper Atmosphere Modeling, and Data Assimilation
- Citation to related publication:
- Ponder, B. M., Ridley, A. J., Goel, A., & Bernstein, D. S. (2023). Improving forecasting ability of GITM using data-driven model refinement. Space Weather, 21, e2022SW003290. https://doi.org/10.1029/2022SW003290
- Discipline:
- Engineering and Science
-
Supporting data: Domain-agnostic predictions of nanoscale interactions in proteins and nanoparticles
- Creator:
- Saldinger, Jacob, Raymond, Matt , Elvati, Paolo, and Violi, Angela
- Description:
- The accurate and rapid prediction of generic nanoscale interactions is a challenging problem with broad applications. Much of biology functions at the nanoscale, and our ability to manipulate materials and purposefully engage biological machinery requires knowledge of nano-bio interfaces. While several protein-protein interaction models are available, they leverage protein-specific information, limiting their abstraction to other structures. Here, we present NeCLAS, a general, and rapid machine learning pipeline that predicts the location of nanoscale interactions, providing human-intelligible predictions. Two key aspects distinguish NeCLAS: coarse-grained representations, and the use of environmental features to encode the chemical neighborhood. We showcase NeCLAS with challenges for protein-protein, protein-nanoparticle and nanoparticle-nanoparticle systems, demonstrating that NeCLAS replicates computationally- and experimentally-observed interactions. NeCLAS outperforms current nanoscale prediction models, and it shows cross-domain validity, qualifying as a tool for basic research, rapid prototyping, and design of nanostructures., Software: - To reproduce all-atom molecular dynamics (MD) NAMD is required (version 2.14 or later is suggested). NAMD software and documentation can be found at https://www.ks.uiuc.edu/Research/namd/, - To reproduce coarse-grained MD simulations, LAMMPS (version 29 Sep 2021 - Update 2 or later is suggested). LAMMPS software and documentation can be found at https://www.lammps.org, - To rebuild free energy profiles, the PLUMED plugin (version 2.6) was used. PLUMED software and documentation can be found at https://www.plumed.org/ , and - To generate force matching potentials, the was used the OpenMSCG software was used. OpenMSCG software and documentation can be found at https://software.rcc.uchicago.edu/mscg/
- Keyword:
- Neural Networks, Proteins, Dimensionality Reduction, Nanoparticles, and Coarse-Graining
- Citation to related publication:
- https://www.biorxiv.org/content/10.1101/2022.08.09.503361v2
- Discipline:
- Science
-
- Creator:
- Sun, Hu, Ren, Jiaen, Chen, Yang, and Zou, Shasha
- Description:
- Our research focuses on providing a fully-imputed map of the worldwide total electron content with high resolution and spatial-temporal smoothness. We fill in the missing values of the original Madrigal TEC maps via estimating the latent feature of each latitude and local time along the 2-D grid and give initial guess of the missing regions based on pre-computed spherical harmonics map. The resulting TEC map has high imputation accuracy and the ease of reproducing. and All data are in HDF5 format and are easy to read using the h5py package in Python. The TEC map is grouped in folders based on years and each file contains a single-day data of 5-min cadence. Each individual TEC map is of size 181*361.
- Keyword:
- Total Electron Content, Matrix Completion, VISTA, Spherical Harmonics, and Spatial-Temporal Smoothing
- Citation to related publication:
- Sun, H., Hua, Z., Ren, J., Zou, S., Sun, Y., & Chen, Y. (2020). Matrix Completion Methods for the Total Electron Content Video Reconstruction. arXiv preprint arXiv:2012.01618. and Zou, S., Ren, J., Wang, Z., Sun, H., & Chen, Y. (2021). Impact of Storm-Enhanced Density (SED) on Ion Upflow Fluxes During Geomagnetic Storm. Frontiers in Astronomy and Space Sciences, 162.
- Discipline:
- Science
-
- 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:
- 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:
- Brenner, Austin, M
- Description:
- Coupling between the solar wind and magnetosphere can be expressed in terms of energy transfer through the separating boundary known as the magnetopause. Geospace simulation is performed using the Space Weather Modeling Framework (SWMF) of a multi-ICME impact event on February 18-20, 2014 in order to study the energy transfer through the magnetopause during storm conditions. The magnetopause boundary is identified using a modified plasma $\beta$ and fully closed field line criteria to a downstream distance of $-20R_{e}$. Observations from Geotail, Themis, and Cluster are used as well as the Shue 1998 model to verify the simulation field data results and magnetopause boundary location. Once the boundary is identified, energy transfer is calculated in terms of total energy flux \textbf{K}, Poynting flux \textbf{S}, and hydrodynamic flux \textbf{H}. Surface motion effects are considered and the regional distribution of energy transfer on the magnetopause surface is explored in terms of dayside $\left(X>0\right)$, flank $\left(X<0\right)$, and tail cross section $\left(X=X_{min}\right)$ regions. It is found that total integrated energy flux over the boundary is nearly balanced between injection and escape, and flank contributions dominate the Poynting flux injection. Poynting flux dominates net energy input, while hydrodynamic flux dominates energy output. Surface fluctuations contribute significantly to net energy transfer and comparison with the Shue model reveals varying levels of cylindrical asymmetry in the magnetopause flank throughout the event. Finally existing energy coupling proxies such as the Akasofu $\epsilon$ parameter and Newell coupling function are compared with the energy transfer results.
- Keyword:
- Space plasma, Magnetosphere, MHD simulations, Magnetopause, Substorm, Energy transfer, and Poynting flux
- Citation to related publication:
- Brenner A, Pulkkinen TI, Al Shidi Q and Toth G (2021) Stormtime Energetics: Energy Transport Across the Magnetopause in a Global MHD Simulation. Front. Astron. Space Sci. 8:756732. doi: 10.3389/fspas.2021.756732
- 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:
- Brasch, Jonathan M, Elipot, Shane, and Arbic, Brian
- Description:
- For Drifters, HYCOM, MITgcm: Spectra and kinetic energy files. Please see readme.txt for a description of all data and code contained here. and - Compare kinetic energies (KE) of high-resolution global ocean models estimated from rotary spectra to KE in surface drifter observations. - Near-inertial KE is closer to drifter observations in models with frequently updated wind forcing - Internal tide KE is closer to drifter observations in models with topographic wave drag
- Keyword:
- oceanography, rotary spectra, kinetic energy, sea surface velocity, and drifters
- Citation to related publication:
- Elipot, S., Lumpkin, R., Perez, R. C., Lilly, J. M., Early, J. J., & Sykulski, A. M. (2016). A global surface drifter data set at hourly resolution. Journal of Geophysical Research: Oceans, 121(5), 2937–2966. https://doi.org/10.1002/2016JC011716
- 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
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