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- Creator:
- Kort, Eric A., Plant, Genevieve, Brandt, Adam R., Chen, Yuanlei, Gorchov Negron, Alan M., and Smith, Mackenzie L.
- Description:
- As part of the Flaring & Fossil Fuels: Uncovering Emissions & Losses (F3UEL) project, in 2022 the aircraft measurement platform sampled offshore oil & gas facilities in the US Gulf of Mexico to quantify facility-level emissions using the approach detailed in Conley et al. (2017). 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. 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, Methane, Nitrogen Oxides, and Gulf of Mexico
- Discipline:
- Science
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- Creator:
- Kort, Eric A, Plant, Genevieve, and Dacic, Natasha
- Description:
- As part of the Measurement of Agriculture Illuminating farm-Zone Emissions of N2O (MAIZE) project, in 2022 an aircraft platform sampled atmospheric concentrations of nitrous oxide (N2O) in the agriculture regions of Iowa. Vertical profiles were conducted on each flight to capture the vertical structure and mixing depths of the atmosphere. The data files contain the merged data for each individual flight day.
- Keyword:
- Greenhouse Gases, Nitrous Oxide, and Agricultural soils
- Citation to related publication:
- Airborne measurements reveal high spatiotemporal variation and the heavy-tail characteristic of nitrous oxide emissions in Iowa" by Natasha Dacic, Genevieve Plant, and Eric A Kort. Journal of Geophysical Research: Atmospheres. Submitted. and 2021 dataset: Kort, E. A., Plant, G., Dacic, N. (2022). Aircraft Data (2021) for Measurement of Agriculture Illuminating farm-Zone Emissions of N2O (MAIZE) [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/0jvh-0c91
- Discipline:
- Science
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- Creator:
- Gorchov Negron, Alan M., Kort, Eric A., Conley, Stephen A., and Smith, Mackenzie L.
- Description:
- This data-set contains data used in the publication "Airborne Assessment of Methane Emissions from Offshore Platforms in the U.S. Gulf of Mexico" by Gorchov Negron et al. (2020). There are 46,032 rows and 45 columns in the data. and The aircraft sampled offshore facilities with two unique sampling strategies: facility-level samples and regional box samples. Gorchov Negron et al. used facility-level samples to calculate facility-level fluxes and regional box samples, in conjunction with vertical profiles, to calculate regional-level fluxes. Meteorological parameters in the data were evaluated to discern when assumptions for each method were met. The facility-level fluxes were used to generate a facility-level aerial measurement-based inventory that was scaled up for comparison with regional-level fluxes.
- Keyword:
- Methane Emissions, Offshore Oil and Gas Platforms, Airborne Measurements, Greenhouse Gas Mitigation, and Gulf of Mexico
- Citation to related publication:
- Alan M. Gorchov Negron, Eric A. Kort, Stephen A. Conley, Mackenzie L. Smith. "Airborne Assessment of Methane Emissions from Offshore Platforms in the U.S. Gulf of Mexico". Environ. Sci. Technol. 2020. http://dx.doi.org/10.1021/acs.est.0c00179
- Discipline:
- Science
-
- Creator:
- Murray, Kendra E, Niemi, Nathan A, and Clark, Marin C
- Description:
- These data were produced in the scope of research into understanding the application of zircon (U-Th)/He thermochronometric data derived from rocks with complex radiation damage distributions to the extraction of long-term (>1 Gyr) thermal histories of the Earth's upper crust. The samples used in this study were collected from the Front Range in Colorado, USA. The low-temperature (apatite and zircon (U-Th)/He) thermochronometric ages presented in this data set are sensitive to near-surface temperatures (~80C and 180C, respectively) and record the progressive exhumation of the rock mass from which the samples were collected towards the Earth's surface. These thermochronometric ages, and the differences between them, provide insight into the deep-time (~1000 Ma - 100 Ma) thermal history of the Colorado Front Range.
- Keyword:
- apatite, zircon, helium, (U-Th)/He, (U-Th-Sm)/He, thermochronometry, thermochronology, low-temperature, Colorado, Boulder, geology, Colorado Mineral Belt, and Front Range
- Discipline:
- Science
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- Creator:
- Tye, Alexander R, Niemi, Nathan A, Safarov, Rafig T, Kadirov, Fakhraddin A, Babayev, Gulam R
- Description:
- Apatite fission track thermochronometry data were collected from the Eastern Greater Caucasus orogen, Azerbaijan. Thermochronometry data constrain the history of exhumation and deformation of rocks within the orogen, which is an active accretionary prism. Thermochronometry data record the timing of cooling of a rock sample beneath a given closure temperature. Given an assumed or inferred geothermal gradient, thermochronometric ages can be used to infer exhumation rates and make interpretations about rates of deformation in orogens. The apatite fission track data presented here are analyzed in concert with apatite (U-Th)/He and zircon (U-Th)/He ages reported in Tye et al., in prep., to characterize the exhumation history of the Eastern Greater Caucasus.
- Keyword:
- thermochronometry, apatite fission track, Caucasus
- Citation to related publication:
- Tye, A. R., Niemi, N. A., Safarov, R. T., Kadirov, F. A., & Babayev, G. R. (2021). Sedimentary response to a collision orogeny recorded in detrital zircon provenance of Greater Caucasus foreland basin sediments. Basin Research, 33(2), 933–967. https://doi.org/10.1111/bre.12499
- Discipline:
- 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
-
- Creator:
- Keppel-Aleks, Gretchen and Liptak, Jessica
- Description:
- -CESM_bdrd _NEP_pulse_response_CO2.nc contains time series from the ‘FullyCoupled’ simulation -CESM_bdrcs_NEP_pulse_response_CO2.nc contains time series from the ‘NoRad’ simulation -CESM_bdrd_pftcon_NEP_pulse_response_CO2.nc contains data from the ‘NoLUC’ simulation -CESM_bdrd_Regional_Fluxes_NEP.nc contains NEP time series for each terrestrial source region from the FullyCoupled simulation - CESM_bdrcs_Regional_Fluxes_NEP.nc contains NEP time series for each terrestrial source region from the CESM ‘NoRad’ simulation - CESM_bdrd_pftcon_Regional_Fluxes_NEP.nc contains NEP time series for each terrestrial source region from the CESM ‘NoLUC’ simulation The 3-letter station IDs, latitudes, and longitudes of the sample locations are: ID Latitude (ºN) Longitude (ºE) 1. BRW 71.3 203.4 2. ZEP 78.9 11.9 3. SHM 52.7 174.1 4. THD 41.1 235.8 5. TAP 36.7 126.1 6. BMW 32.3 295.1 7. MLO 19.5 204.4 8. POCN15 15.0 215.0 9. ALT 82.5 297.5 10. BHD -41.4 174.9 11. EIC -27.2 250.6 12. GMI 13.4 144.7 13. HUN 47.0 16.7 14. IZO 28.3 343.5 15. LLN 23.5 120.9 16. NAT -5.8 324.7 17. WLG 36.3 100.9 18. HBA -75.6 333.8 19. BKT -0.20 100.3 20. UUM 44.5 111.1 21. CGO -40.7 144.5 22. SDZ 40.7 117.1 23. ASC -8.0 345.6 24. SEY -4.7 55.5 25. POCS20 -20.0 186.0 26. POCS35 -35.0 180.0 27. PSA -64.9 296.0 28. SYO -69.0 39.6 29. CHR 1.7 202.8 30. KEY 25.7 279.8 31. BAL 55.4 17.2 32. HPB 47.8 11.0 33. LMP 35.5 12.6 34. NMB -23.6 15.0 35. RPB 13.2 300.2 36. WIS 30.0 35.1 37. POCS10 -10.0 199.0 38. POCN10 10.0 211.0 39. MID 28.2 182.6 40. SMO -14.2 189.4 41. SPO -90.0 335.2 The terrestrial CO2 source region abbreviations are: 1. NBNA 2. SBNA 3. ETNA 4. WTNA 5. CNAM 6. AMZN 7. EASA 8. WESA 9. EURO 10. SAME 11. MDAF 12. AFRF 13. SOAF 14. EABA 15. WEBA 16. SOBA 17. CNAS 18. SEAS 19. EQAS 20. AUST 21. GNLD 22. ATCA
- Keyword:
- atmospheric CO2 annual cycle amplitude and CESM extended concentration pathway
- Citation to related publication:
- Hornick, T., Bach, L. T., Crawfurd, K. J., Spilling, K., Achterberg, E. P., Woodhouse, J. N., Schulz, K. G., Brussaard, C. P. D., Riebesell, U., & Grossart, H.-P. (2017). Ocean acidification impacts bacteria–phytoplankton coupling at low-nutrient conditions. Biogeosciences, 14(1), 1–15. https://doi.org/10.5194/bg-14-1-2017
- 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:
- McCuen, Brett A.
- Description:
- The data were used to study the high-frequency geomagnetic disturbances within the magnetic field data. Included in this repository are the python scripts that perform an identification and classification of high-frequency signals within the magnetometer data that is downloaded from the databases listed in the Methodology section. All analysis and plots were created using subsequent Python libraries. The machine learning study implemented libraries from the sci-kit learn software. All of the specific methodology can be accessed in the readme.txt script.
- Keyword:
- geomagnetic field, high frequency, space weather, transient-large-amplitude, TLA, high frequency dB/dt, and dB/dt search algorithm
- Discipline:
- Science
-
- Creator:
- Li, Jieming, Zhang, Leyou, Johnson-Buck, Alexander, and Walter, Nils G.
- Description:
- Traces from single-molecule fluorescence microscopy (SMFM) experiments exhibit photophysical artifacts that typically necessitate human expert screening, which is time-consuming and introduces potential for user-dependent expectation bias. Here, we have used deep learning to develop a rapid, automatic SMFM trace selector, termed AutoSiM, that improves the sensitivity and specificity of an assay for a DNA point mutation based on single-molecule recognition through equilibrium Poisson sampling (SiMREPS). The improved performance of AutoSiM is based on accepting both more true positives and fewer false positives than the conventional approach of hidden Markov modeling (HMM) followed by thresholding. As a second application, the selector was used for automated screening of single-molecule Förster resonance energy transfer (smFRET) data to identify high-quality traces for further analysis, and achieves ~90% concordance with manual selection while requiring less processing time. AutoSiM can be adapted readily to novel datasets, requiring only modest Transfer Learning.
- Keyword:
- deep learning, single-molecule fluorescence, total internal reflection microscopy, SiMREPS, smFRET, and Forster resonance energy transfer
- Citation to related publication:
- Li, J., Zhang, L., Johnson-Buck, A., & Walter, N. G. (2020). Automatic classification and segmentation of single-molecule fluorescence time traces with deep learning. Nature Communications, 11(1), 5833. https://doi.org/10.1038/s41467-020-19673-1 and Hayward, S., Lund, P., Kang, Q., Johnson-Buck, A., Tewari, M., Walter, N. (2018). Single-molecule microscopy image data and analysis files for "Ultra-specific and Amplification-free Quantification of Mutant DNA by Single-molecule Kinetic Fingerprinting" [Data set]. University of Michigan - Deep Blue. https://doi.org/10.7302/Z2CZ35DF
- Discipline:
- Science