Search Constraints
Number of results to display per page
View results as:
Search Results
- Creator:
- Sun, Hu
- Description:
- Complete Global Total Electron Content Database based on the VISTA Algorithm
- Keyword:
- Total Electron Content, Matrix Completion, VISTA, Spherical Harmonics, and Spatial-Temporal Smoothing
- Discipline:
- Engineering
- Creator:
- Kort, Eric and Plant, Genevieve
- Description:
- Fossil energy production, processing, flaring, and transmission all can harm climate and air quality by emitting greenhouse gases and air pollutants. Studies now show that onshore oil and gas production emit much more methane than what is inventoried, and that local air quality impacts can be significant, however, natural gas flaring and offshore systems have been largely overlooked. The F3UEL (Flaring & Fossil Fuels: Uncovering Emissions & Losses) project aims to address these gaps by improving our understanding of offshore emissions, characterizing how flares behave in the real world, identifying what portion of the offshore system is responsible for emissions, and determining how such systems can be monitored. Spanning three years (2020-2022), the project employed an aircraft platform to measure including both greenhouse gas and air quality measurements. To sample the largest regions of current and potential future offshore production and flaring, airborne measurements targeted the Gulf of Mexico, offshore California and Alaska, the Bakken Formation (North Dakota) and the Permian and Eagle Ford Basins (Texas). Data provided here includes the airborne measurements collected using Scientific Aviation’s Mooney aircraft platform, equipped with spectroscopic instrumentation to measure methane, carbon dioxide, water vapor, nitrous oxide, and nitrogen oxide, in addition to meteorological variables such as wind speed and direction. Data products from our analysis of these airborne measurements are also provided, including estimated flare destruction removal efficiency for the Bakken, Eagle Ford, and Permian basins. Each data file is in .csv format and is accompanied by a readme file with further information and descriptors of the variables included. All users should cite the papers and datasets provided in the readme files for each individual dataset. Website: https://graham.umich.edu/f3uel This project is funded by the Alfred P. Sloan Foundation with additional support from the Environmental Defense Fund, Scientific Aviation, and University of Michigan (College of Engineering, Climate and Space Sciences and Engineering; Graham Sustainability Institute).
- Keyword:
- offshore oil & gas, flaring, methane, Nitrogen oxides, natural gas flaring, and oil & gas
- Discipline:
- Science
- Creator:
- Kort, Eric A., Plant, Genevieve, Brandt, Adam R., Chen, Yuanlei, Gorchov Negron, Alan M., Schwietzke, Stefan, Smith, Mackenzie L., and Zavala-Araiza, Daniel
- Description:
- As part of the Flaring & Fossil Fuels: Uncovering Emissions & Losses (F3UEL) project, in 2021 the aircraft measurement platform sampled offshore oil & gas facilities in Alaska and California to quantify facility-level emissions using the approach detailed in Conley et al. (2017). Onshore, the aircraft sampled downwind of flare combustion plumes in the Bakken region of North Dakota. Vertical profiles were conducted on each flight to capture the vertical structure and mixing depths of the atmosphere. The data file contains all merged flight data from each flight day. and Reference: Conley, S., Faloona, I., Mehrotra, S., Suard, M., Lenschow, D. H., Sweeney, C., Herndon, S., Schwietzke, S., Pétron, G., Pifer, J., Kort, E. A., and Schnell, R.: Application of Gauss’s theorem to quantify localized surface emissions from airborne measurements of wind and trace gases, Atmos. Meas. Tech., 10, 3345 – 3358, 2017.
- Keyword:
- Offshore Oil & Gas, Flaring, Methane, and Nitrogen Dioxides
- Discipline:
- Science
- Creator:
- Kort, Eric A., Plant, Genevieve, Smith, Mackenzie L., Brandt, Adam R., Chen, Yuanlei, Gorchov Negron, Alan M., Schwietzke, Stefan, and Zavala-Araiza, Daniel
- Description:
- As part of the Flaring & Fossil Fuels: Uncovering Emissions & Losses (F3UEL) project, in 2020 the aircraft measurement platform sampled offshore oil & gas facilities in the Gulf of Mexico to quantify facility-level emissions using the approach detailed in Conley et al. (2017). Onshore, the aircraft sampled downwind of flare combustion plumes in the Permian and Eagle Ford regions of Texas. Vertical profiles were conducted on each flight to capture the vertical structure and mixing depths of the atmosphere. The data file contains all merged flight data from each flight day. and Reference: Conley, S., Faloona, I., Mehrotra, S., Suard, M., Lenschow, D. H., Sweeney, C., Herndon, S., Schwietzke, S., Pétron, G., Pifer, J., Kort, E. A., and Schnell, R.: Application of Gauss’s theorem to quantify localized surface emissions from airborne measurements of wind and trace gases, Atmos. Meas. Tech., 10, 3345 – 3358, 2017.
- Keyword:
- Offshore Oil & Gas, Flaring, Methane, and Nitrogen Oxides
- Discipline:
- Science
- Creator:
- Engebretson, Mark J.
- Description:
- Large geomagnetic disturbances (GMDs, also denoted as MPEs - magnetic perturbation events) have sufficient amplitude to cause geomagnetically induced currents (GICs) that can damage technical infrastructure. In this study we present occurrence statistics for GMD / MPE events with derivatives ≥ 6 nT/s and ≥ 20 nT/s from five stations in the MACCS and AUTUMNX magnetometer arrays in Arctic Canada at magnetic latitudes ranging from 65° to 75°. Earlier studies using data from these arrays (Engebretson et al., 2019a,b, 2021a,b) covered only two years (2015 and 2017) and focused on latitude- and local time-dependent occurrence patterns and short-term dependencies on solar wind/IMF parameters and magnetospheric activity indices. This study presents all available data from these stations from 2011 through 2022 to analyze variations of GMD activity over a full solar cycle. Intense GMD activity did not closely follow the sunspot cycle, but instead was lowest during its rising phase and maximum (2011-2014), was highest during the early declining phase (2015-2017), and reached a subsequent minimum early in the following sunspot cycle (2020). GMDs with amplitude >20 nT/s followed the same yearly pattern but peaked even more strongly during 2015-2017. Most of these GMDs were associated with high-speed solar wind streams (Vsw > 600 km/s), but not with strongly negative values of the SYM/H index. The majority of these GMDs, irrespective of the Vsw value, were accompanied within 10 min (and most often less) by other events with amplitude ≥ 6 nT/s and showed a mostly poleward progression. These results show that large amplitude but spatially localized nighttime GMDs are primarily associated with high-speed stream geomagnetic drivers during the declining phase of the solar cycle. This indicates that large GIC hazard conditions can occur for a variety of solar wind drivers and geomagnetic conditions and not only for fast-coronal mass ejection driven storms.
- Keyword:
- geomagnetic disturbance events, geomagnetically induced currents
- Citation to related publication:
- Engebretson, M. J., Steinmetz, Yang, L., Pilipenko, V. A., Moldwin, M. B., McCuen, B. A., Connors, M. G., Weygand, J. M., Waters, C. L., Lyons, L. R., Nishimura, Y., Russell, C. T. (2023) Solar Cycle Dependence of Very Large Nighttime Geomagnetic Disturbances (GMDs) Observed in Eastern Arctic Canada. Journal of Geophysical Research – Space Physics
- Discipline:
- Science
996. 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
997. Data from "A Comparison of Lossless Compression Methods in Microscopy Data Storage Applications"
- Creator:
- Walker, Logan A, Li, Ye, McGlothlin, Maggie, and Cai, Dawen
- Description:
- These are datasets released from our manuscript "A Comparison of Lossless Compression Methods in Microscopy Data Storage Applications". Included in this data release are: `noise16.tif`: a file containing background noise collected from a 1000-frame acquisition of a ORCA-Fusion camera; `noise8.tif`: a file containing the 16-bit data collective above converted into a 8-bit form; `brainbow.tif`: This is a mouse Brainbow image originally published and described in Roossien, et al. Bioinformatics 2019; `bead.tif`: This is a 3D image of 100nm Invitrogen TetraSpeck fluorescent microspheres imaged in a blue channel using a custom microscope; `fly.tif`: This is a 3D image of a fly Bitbow brain collected as described in Li, et al. Front. Neural Circuits 2021; and `neurite.tif`: This is a 3D image of DiD-labeled mouse V1 tissue, collected using a custom microscope.
- Keyword:
- neuroscience, microscopy, and Bitbow
- Discipline:
- Health Sciences
998. VISTA TEC database
- 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:
- Reynolds, Mack B., Hong, Hanna S., Zhang, Li, Lyssiotis, Costas A., and O'Riordan, Mary X.
- Description:
- Untargeted lipidomics (Data S1) and targeted metabolomics (Data S2) analysis from in vitro culture of a murine macrophage cell line expressing shRNA targeted to Cardiolipin synthase (CRLS1), referred to as CRLS1 knockdown (KD), or a paired non-target shRNA-expressing (NT-Control). CRLS1 KD and NT-Control macrophages were either directly analyzed (untargeted lipidomics) or stimulated with lipopolysaccharide for a variety of timepoints and then analyzed (targeted metabolomics). Datasets are available as .csv files.
- Keyword:
- Lipidomics, Metabolomics, Cardiolipin, Macrophage, CRLS1, lipopolysaccharide, and LPS
- Citation to related publication:
- Reynolds M.B. et al. (2023). Cardiolipin coordinates inflammatory metabolic reprogramming through regulation of Complex II disassembly and degradation. Science Advances, 9(5). DOI: 10.1126/sciadv.ade8701
- Discipline:
- Health Sciences
1000. Data for Macroscopic Transition Metal Dichalcogenides Monolayers with Uniformly High Optical Quality
- Creator:
- Li, Qiuyang, Alfrey, Adam, Hu, Jiaqi, Lydick, Nathanial, Paik, Eunice, Liu, Bin, Sun, Haiping, Lu, Yang, Wang, Ruoyu, Forrest, Stephen, and Deng, Hui
- Description:
- This dataset contains raw and source data for all figures generated in the manuscript "Macroscopic Transition Metal Dichalcogenides Monolayers with Uniformly High Optical Quality" The raw data files include '.spe' data, which are spectral data collected by LightField Sofware, and '.dset' and '.vms' files, which are X-ray photoelectron spectroscopy (XPS) data and require CasaXPS to access. The source data files include the processed data that can be directly used for generating the corresponding figures in the manuscript.
- Keyword:
- 2D materials, Exciton-polaritons, and Photonics
- Discipline:
- Science