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- Creator:
- Elvati, Paolo, Luyet, Chloe, Wang, Yichun, Liu, Changjiang, VanEpps, J. Scott, Kotov, Nicholas A., and Violi, Angela
- Description:
- Amyloid nanofibers are abundant in microorganisms and are integral components of many biofilms, serving various purposes, from virulent to structural. Nonetheless, the precise characterization of bacterial amyloid nanofibers has been elusive, with incomplete and contradicting results. The present work focuses on the molecular details and characteristics of PSMa1-derived functional amyloids present in Staphylococcus aureus biofilms, using a combination of computational and experimental techniques, to develop a model that can aid the design of compounds to control amyloid formation. Results from molecular dynamics simulations, guided and supported by spectroscopy and microscopy, show that PSMa1 amyloid nanofibers present a helical structure formed by two protofilaments, have an average diameter of about 12 nm, and adopt a left-handed helicity with a periodicity of approximately 72 nm. The chirality of the self-assembled nanofibers, an intrinsic geometric property of its constituent peptides, is central to determining the fibers' lateral growth.
- Keyword:
- molecular self-assembly, computational nanotechnology, nanobiotechnology, and structural properties
- Citation to related publication:
- Paolo Elvati, Chloe Luyet, Yichun Wang, Changjiang Liu, J. Scott VanEpps, Nicholas A. Kotov, and Angela Violi ACS Applied Nano Materials 2023 6 (8), 6594-6604 DOI: 10.1021/acsanm.3c00174
- Discipline:
- Engineering and Science
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- Creator:
- Brian, Chen
- Description:
- The procedure followed while creating this data is summarized in Section II of Chen, Brian, et al. "Behavioral cloning in atari games using a combined variational autoencoder and predictor model." 2021 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2021. This data is not a result of a research but an intermediate product that is used in research. This dataset is generated to train a behavioral cloning framework from gameplay screen captures and keystrokes of an "expert" player. The RL agent that is trained using "RL Baselines Zoo package" acts as the "expert" player, whose decision making process we desire to learn. In addition to behavioral cloning experiments, this dataset is further used to demonstrate the efficacy of a novel incremental tensor decomposition algorithm on image-based data streams.
- Keyword:
- Imitation Learning, Behavioral Cloning, Reinforcement Learning, Machine Learning, and Gameplay Data
- Citation to related publication:
- Chen, Brian, et al. "Behavioral cloning in atari games using a combined variational autoencoder and predictor model." 2021 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2021., Aksoy, Doruk, et al. "An Incremental Tensor Train Decomposition Algorithm." arXiv preprint arXiv:2211.12487 (2022)., and Chen, Brian, et al. "Low-Rank Tensor-Network Encodings for Video-to-Action Behavioral Cloning", forthcoming
- Discipline:
- Engineering and Science
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- Creator:
- Dwyer, Tobias, Moore, Timothy C., Anderson, Joshua A. , and Glotzer, Sharon C.
- Description:
- This dataset was generated for our work: "Tunable Assembly of Host–Guest Colloidal Crystals". The data set contains data for 5 different binary systems of star particles and convex guests, and one system of only star particles. All simulation were formed at constant pressure. The data set contains GSD files for each of the simulations used in this work along with the corresponding python code used to produce the simulations. We also include the python code and jupyter notebook to produce the free volume calculations used in this work. and How to use this Data: Simulation Data: We include GSD files that can be uploaded into a visualization or analysis software such as Ovito or Freud for independent analysis. Simulation python scripts (workspaces_for_HPMC_simulations.zip): We include the python scripts used in this work for simulating host guest systems at constant pressure. Free Volume Data (Free_volume_calculations_and_analysis.zip): You can run the jupyter notebook included here to reproduce the free volume analysis for this work. We also include the python scripts for the free volume calculation python scripts that get the data for these free volume calculations.
- Citation to related publication:
- Dwyer, T, Moore, TC, Anderson, JA, & Glotzer, SC. Tunable Assembly of Host–Guest Colloidal Crystals. Soft Matter (Provisional Citation)
- Discipline:
- Engineering
-
- Creator:
- Wallace, Dylan M, Benyamini, Miri, Nason-Tomaszewski, Samuel R, Costello, Joseph T, Cubillos, Luis H, Mender, Matthew J, Temmar, Hisham, Willsey, Matthew S, Patil, Parag P, Chestek, Cynthia A, and Zacksenhouse, Miriam
- Description:
- This is data from Wallace, Benyamini et al., 2023, Journal of Neural Engineering. There are two sets of data included: 1. Neural features and error labels used to train error classifiers for each day used in the study 2. Trial data from an example experiment day (Monkey N, Day 6), with runs for offline calibration, online brain control, error monitoring, and error correction. The purpose of this study was to investigate the use of error signals in motor cortex to improve brain-machine interface (BMI) performance for control of two finger groups. All data is contained in .mat files, which can be opened using MATLAB or the Python SciPy library.
- Keyword:
- Brain-machine interface (BMI), Error detection, and Neural recording
- Citation to related publication:
- Wallace, D. M., Benyamini, M., Nason-Tomaszewski, S. R., Costello, J. T., Cubillos, L. H., Mender, M. J., Temmar, H., Willsey, M. S., Patil, P. G., Chestek, C. A., & Zacksenhouse, M. (2023). Error detection and correction in intracortical brain–machine interfaces controlling two finger groups. Journal of Neural Engineering, 20(4), 046037. https://doi.org/10.1088/1741-2552/acef95
- Discipline:
- Engineering, Science, and Health Sciences
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- Creator:
- Brenner, Austin M
- Description:
- Results of computer simulation of near Earth space is looked at in a new way to understand how energy moves around the global system. It is found that in addition to a pathway of energy from the outside into the system and back again there is an internal loop which recirculates energy. These new methods will greatly improve our understanding how the whole magnetosphere system evolves and will help address evolution of processes that have space weather impacts.
- Keyword:
- Energy flux, geospace, magnetopause, magnetosphere, poynting flux, and reconnection
- Citation to related publication:
- Austin Brenner, Tuija I. Pulkkinen, Qusai Al Shidi, et al. Dissecting Earth’s Magnetosphere: 3D Energy Transport in a Simulation of a Real Storm Event. ESS Open Archive . August 04, 2023.
- Discipline:
- Science and Engineering
-
- Creator:
- Chaoran Xu, Davlasheridze, Meri, Nelson-Mercer, Benjamin T., Bricker, Jeremy D., Jia, Jianjun, and Ross, Ashley D.
- Description:
- Hurricane Ike, which struck the United States in September 2008, was the ninth most expensive hurricane in terms of damages. It caused nearly $30 billion in damage, of which nearly $12B were insured losses, after making landfall on the Bolivar Peninsula, Texas. We used the Delft3d-FM/SWAN hydrodynamic and spectral wave model to simulate the storm surge inundation around Galveston Bay during Hurricane Ike. Damage curves were established through the eight hydrodynamic parameters (water depth, flow velocity, unit discharge, flow momentum flux, significant wave height, wave energy flux, total water depth (flow depth plus wave height), and total (flow plus wave) force) simulated by the model. We found that the damage curves are sensitive to the model grid resolution, building elevation, and the number of stories.
- Citation to related publication:
- Xu et al. (2023). Damage curves derived from Hurricane Ike in the west of Galveston Bay based on insurance claims and hydrodynamic simulations.
- Discipline:
- Engineering
-
- Creator:
- Lin, Brian T. W.
- Description:
- This footage is an output of a USDOT-funded project titled "Development of Machine-Learning Models for Autonomous Vehicle Decisions on Weaving Sections of Freeway Ramps." It showcases an automated weaving maneuver within an augmented reality environment. During the demonstration, Mcity's automated vehicle navigates through a highway weaving section, making a lane change while interacting with a virtual vehicle. In this instance, Mcity's vehicle was operated by automated driving systems, which executed the lane change based on the detection for external environmental factors and parameter inputs received from the virtual vehicle.
- Discipline:
- Engineering
-
- Creator:
- Gill, Tate M, Sercel, Christopher L, and Jorns, Benjamin A
- Description:
- Rotating Magnetic Field (RMF) thrusters are a form of electrodeless plasma propulsion. This technology is a low maturity but potentially enabling candidate for high-power in-space propulsion for use with alternative propellants. The purpose of the data here, and the associated publication is to evaluate the phenomenological efficiency modes for this thruster test article to explain and understand its overall efficiency. These modes include divergence, power coupling, mass utilization, and plasma/acceleration efficiency. Additional time-resolved measurements of the internal plasma properties were performed using a triple Langmuir probe to evaluate energy loss processes within the thruster.
- Keyword:
- Electric Propulsion, Rotating Magnetic Field Thrusters, Inductive Pulsed Plasma Thrusters, and Magnetic Nozzles
- Citation to related publication:
- Gill, T.M., Sercel, C.L., and Jorns, B.A., "Experimental Investigation into Efficiency Loss in Rotating Magnetic Field Thrusters", Plasma Sci. Sources and Tech. 2023 (In Review)
- Discipline:
- Engineering
-
- Creator:
- Lee, Sophie Y., Schönhöfer Philipp W.A., and Glotzer, Sharon C.
- Description:
- This dataset was generated for our work: "Complex motion of steerable vesicular robots filled with active colloidal rods". In this project, we used Brownian molecular dynamics simulations to study the rich dynamical behavior of rigid kinked vesicles that contain self-propelling rod-shaped particles. We identified that kinks in the vesicle membrane bias the emergent clustering and alignment of the active agents. Based on the system's geometrical and material properties, we were able to design multiple types of directed motion of the vesicle superstructure. This dataset includes simulation data for two-dimensional systems of self-propelling rod particles confined by teardrop-shaped coarse-grained vesicles. The trajectory of each simulation is saved in a GSD format file with parameter metadata in a JSON file. Due to the large number of replicas of each pair of parameters, simulation data were grouped into 5 different folders. Collective quantitative analysis for simulated trajectories was performed with Jupyter Notebook. and Workspaces_simulations.zip contains all the workspaces of simulations Each folder has subfolders called 'dimer' and 'trimer' depending on the length of the propelling rod particles used in the simulation. (Except for the folder 'number-density_16' which has only 'dimer') In the subfolders, we include the Python scripts used in this work for simulating and trajectory analysis for individual trajectory data. The parameter space of each folder is noted in init.py. Analysis_jupyter_notebooks.zip includes Jupyter notebooks that can reproduce the collective analysis done for this work.
- Discipline:
- Engineering
-
- Creator:
- Hawes, Jason K, Goldstein, Benjamin P. , Newell, Joshua P. , Dorr, Erica , Caputo, Silvio , Fox-Kämper, Runrid , Grard, Baptiste , Ilieva, Rositsa T. , Fargue-Lelièvre, Agnès , Poniży, Lidia , Schoen, Victoria , Specht, Kathrin , and Cohen, Nevin
- Description:
- Urban agriculture (UA) is a widely proposed strategy to make cities and urban food systems more sustainable. However, its carbon footprint remains understudied. In fact, the few existing studies suggest that UA may be worse for the climate than conventional agriculture. This is the first large-scale study to resolve this uncertainty across cities and types of UA, employing citizen science at 73 UA sites in Europe and the United States to compare UA products to food from conventional farms. The results reveal that food from UA is six times as carbon intensive as conventional agriculture (420g vs 70g CO2 equivalent per serving). Some UA crops (e.g., tomatoes) and sites (e.g., 25% of individually-managed gardens), however, outperform conventional agriculture. These exceptions suggest that UA practitioners can reduce their climate impacts by cultivating crops that are typically greenhouse grown or air-freighted, maintaining UA sites for many years, and leveraging waste as inputs.This database contains the necessary reference material to trace the path of our analysis from raw garden data to carbon footprint and nutrient results. It also contains the final results of the analyses in various extended forms not available in the publication. For more information, see manuscript at link below. (Introduction partially quoted from Hawes et al., 2023)
- Citation to related publication:
- Hawes, J. K., Goldstein, B. P., Newell, J. P., Dorr, E., Caputo, S., Fox-Kämper, R., Grard, B., Ilieva, R. T., Fargue-Lelièvre, A., Poniży, L., Schoen, V., Specht, K., & Cohen, N. (2024). Comparing the carbon footprints of urban and conventional agriculture. Nature Cities, 1–10. https://doi.org/10.1038/s44284-023-00023-3
- Discipline:
- Engineering