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- Creator:
- Klinich, Kathleen D, Lin, Brian, and Moore, Jamie L.
- Description:
- This dataset allows comparison of the different strategies implemented by vehicle manufacturers being used to communicate with drivers. Spreadsheets were created in MS Excel to summarize data for each vehicle, and include page numbers in each vehicle owner's manual for reference. The photos taken of each vehicle control panel allow detailed inspection of the displays and controls.
- Keyword:
- vehicle, controls, displays, and FMVSS 101
- Discipline:
- Engineering
-
- Creator:
- Martin, Tara L, Young, LR, Goldsteen, D, Nunamaker, EA, Reynolds, P, Thompson-Iritani, S, Thurston, SE, and LaFollette, MR
- Description:
- This dataset contains the results of a survey of mouse handling methods by personnel working with laboratory mice. The survey included questions about preferred handling methods, barriers to use of refined handling methods, and a knowledge quiz about refined mouse handling. Data was collected via Qualtrics survey as described in the methodology section. This dataset is associated with the following publication, accepted by PLOS One: PONE-D-23-01633R1 Title: Using refined methods to pick up mice: A survey benchmarking prevalence & beliefs about tunnel and cup handling Authors: Lauren Young, Donna Goldsteen, Elizabeth A. Nunamaker, Mark J. Prescott, Penny Reynolds, Sally Thompson-Iritani, Sarah E. Thurston, Tara L. Martin, Megan R. LaFollette
- Keyword:
- Mouse, Refined Handling, Tunnel Handling, Cup Handling, Laboratory Animal, and Animal Care
- Citation to related publication:
- Young LR, Goldsteen D, Nunamaker EA, Prescott MJ, Reynolds P, Thompson-Iritani S, Thurston SE, Martin TL, LaFollette MR. Using refined methods to pick up mice: A survey benchmarking prevalence & beliefs about tunnel and cup handling. PLOS ONE. 2023. In Press.
- Discipline:
- Science
-
- Creator:
- Matt, Cayenne, Gültekin, Kayhan, and Simon, Joseph
- Description:
- The data were used to create number density functions of supermassive black holes (SMBH) for redshifts 0.5 < z < 3.0. The goal of this research is to discern whether galaxy-black hole scaling relations produce black hole masses that are consistent with each other at high redshift. These number density functions were used to compare the high-mass SMBH distributions from each relation. In massive black hole binary based models, the highest-mass SMBHs have a significant influence on the gravitational wave background characteristic strain amplitude. To inform our understanding of the gravitational wave background, that pulsar timing arrays now show evidence for, we need to therefore have a solid foundation on the underlying SMBH population. In our paper we found that using different galaxy properties to inform our estimations of SMBH mass resulted in different distributions, especially at the high-mass end.
- Citation to related publication:
- https://iopscience.iop.org/article/10.1088/0067-0049/219/1/8, https://iopscience.iop.org/article/10.1088/0067-0049/196/1/11, https://iopscience.iop.org/article/10.1088/0004-637X/788/1/28, https://iopscience.iop.org/article/10.3847/1538-4357/ab7e27, and https://ui.adsabs.harvard.edu/abs/2023arXiv230704878M/abstract
- Discipline:
- Science
-
- Creator:
- Lojko, Alexander, Zhang, Yingxiao, Whitcomb, Morgan, Yang, Emily, Dacic, Natasha, and Holmes, Janelle
- Description:
- GIS (.lpkx) data layers that inform of areas to construct new rain gardens in Washtenaw County, Ann Arbor, Michigan. Data layers can be opened with a GIS program. There is a single .lpkx dataset that contains four layers. The first layer contains 'Wildlife Corridors' which contains information on where to prioritize new green infrastructure based on how well-connected different patches of forested areas are. The second layer, 'Social Inequality', shows where to prioritize new rain gardens based on social inequality criteria. The 'Creeksheds and Future Runoff' contains information on future changes in precipitation runoff based on climate change projections of rainfall. Lastly, 'Runoff/Water Quality' is a layer that includes a priority map regarding where new rain gardens should be developed based on areas that are most at risk of poor water quality and enhanced surface run-off. The project was completed for Washtenaw County Water Resources as part of a course taught at the University of Michigan, CLIMATE 592. A description of the course is also provided: "Introduction to individual and team research on real-world problems in the area of applied climate. On a research project started in CLIMATE 591 and guided by a mentor from a commercial or government laboratory, students will apply the principles of risk analysis and objective assessment of adaptive strategies".
- Keyword:
- GIS, Climate Change, Local, Community, and Graduate Student Project
- Citation to related publication:
- Dacic, N., Lojko, A., Zhang, Y., Yang, E., Whitcomb, M., Bassis, J., and Rood., R.B., 2023 'Modernizing the Climate Science Curriculum: Engaging in Local Government Collaboration Projects', In Preperation for the Bulletin of American Meteorological Society
- Discipline:
- Science
-
- Creator:
- Ludlow, Andrew and Kim, Jeongjin
- Description:
- Part of the regulation of telomerase activity includes the alternative splicing (AS) of the catalytic subunit telomerase reverse transcriptase (TERT). Although a therapeutic window for telomerase/TERT inhibition exists between cancer cells and somatic cells, stem cells express TERT and rely on telomerase activity for physiological replacement of cells. Therefore, identifying differences in TERT regulation between stem cells and cancer cells is essential for developing telomerase inhibition-based cancer therapies that reduce damage to stem cells. In this study, we measured TERT splice variant expression and telomerase activity in induced pluripotent stem cells (iPSCs), neural progenitor cells (NPCs), and non-small cell lung cancer cells (NSCLC, Calu-6 cells). We observed that a NOVA1-PTBP1-PTBP2 axis regulates TERT alternative splicing (AS) in iPSCs and their differentiation into NPCs. We also found that splice-switching of TERT, which regulates telomerase activity, is induced by different cell densities in stem cells but not cancer cells. Lastly, we identified cell type-specific splicing factors that regulate TERT AS. Overall, our findings represent an important step forward in understanding the regulation of TERT AS in stem cells and cancer cells. These data and subsequent studies may reveal a splicing factor(s) or their binding site(s) that could be targeted with small molecule drugs or antisense oligonucleotides, respectively, to reduce telomerase activity in cancer cells and promote durable cancer remissions.
- Keyword:
- Telomere, telomerase, TERT, alternative RNA splicing
- Citation to related publication:
- Dynamics of TERT Regulation via Alternative Splicing in Stem Cells and Cancer Cells. Accepted in Plos One
- Discipline:
- Science
-
- Creator:
- Lumeng, Julie C
- Description:
- Healthy full-term infants were enrolled in a longitudinal study designed to examine the development of infant eating behavior. Infant weight and length was measured, mothers completed questionnaires regarding infant eating behaviors, and infant capacity for regulation of energy intake was evaluated by comparing intake between two days: one with feedings given on demand and one with feedings offered hourly. The infant's ability to downregulate intake in response to more frequent feedings was calculated.
- Keyword:
- infant, eating, weight gain, feeding, and energy regulation
- Citation to related publication:
- Reynolds, L. A., McCaffery, H., Appugliese, D., Kaciroti, N. A., Miller, A. L., Rosenblum, K. L., ... & Lumeng, J. C. (2023). Capacity for Regulation of Energy Intake in Infancy. JAMA pediatrics, 177(6), 590-598.
- Discipline:
- Health Sciences
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering
-
- Creator:
- Skinner, Katherine A., Vasudevan, Ram, Ramanagopal, Manikandasriram S., Ravi, Radhika, Carmichael, Spencer, and Buchan, Austin D.
- Description:
- This dataset is part of a collection created to facilitate research in the use of novel sensors for autonomous vehicle perception. , The dataset collection platform is a Ford Fusion vehicle with a roof-mounted novel sensing suite, which specifically consists of forward-facing stereo uncooled thermal cameras (FLIR 40640U050-6PAAX), event cameras (iniVation DVXplorer), monochrome cameras (FLIR BFS-PGE-16S2M), and RGB cameras (FLIR BFS-PGE-50S5C) time synchronized with ground truth poses from a high precision navigation system. , Further information and resources (such as software tools for converting, managing, and viewing data files) are available on the project website: https://umautobots.github.io/nsavp , and CHANGE NOTICE (January 2024): We identified an error in our timestamp post-processing procedure that caused all camera timestamps to be offset by the exposure time of one of the cameras. We corrected the error, applied the corrected post-processing, and reuploaded the corrected files. The change impacts all camera data files. Prior to the change, the timestamps between the cameras were synchronized with submillisecond accuracy, but the camera and ground truth pose timestamps were offset by up to 0.4 ms, 3 ms, and 15 ms in the afternoon, sunset, and night sequences, respectively. This amounted in up to ~0.25 meters of position error in the night sequences. For consistency, camera calibration was rerun with the corrected calibration sequence files. The camera calibration results have therefore been updated as well, although they have not changed significantly. Finally, we previously downsampled the frame data in the uploaded calibration seqeuence, but we decided to provide the full frame data in the reupload.
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://sites.google.com/umich.edu/novelsensors2023, https://github.com/umautobots/nsavp_tools, and https://umautobots.github.io/nsavp
- Discipline:
- Engineering