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- Creator:
- Agnit Mukhopadhyay, Sanja Panovska, Raven Garvey, Michael Liemohn, Natalia Ganjushkina, Austin Brenner, Ilya Usoskin, Michael Balikhin, and Daniel Welling
- Description:
- In the recent geological past, Earth’s magnetic field reduced to 4% of the modern values and the magnetic poles moved severely apart from the geographic poles causing the Laschamps geomagnetic excursion, which happened about 41 millennia ago. The excursion lasted for about two millennia, with the peak strength reduction and dipole tilting lasting for a shorter period of 300 years. During this period, the geomagnetic field exhibited significant differences from the modern nearly-aligned dipolar field, causing non-dipole variables to mimic a magnetic field akin to the outer planets while displaying a significantly reduced magnetic strength. However, the precise magnetospheric configuration and their electrodynamic coupling with the atmosphere have remained critically understudied. This dataset contains the first space plasma investigation of the exact geomagnetic conditions in the near-Earth space environment during the excursion. The study contains a full 3D reconstruction and analysis of the geospace system including the intrinsic geomagnetic field, magnetospheric system and the upper atmosphere, linked in sequence using feedback channels for distinct temporal epochs. The reconstruction was conducted using the LSMOD.2 model, Block Adaptive Tree Solar wind-Roe-Upwind Scheme (BATS-R-US) Model and the MAGnetosphere-Ionosphere-Thermosphere (MAGNIT) Auroral Precipitation Model, all of which are publicly-available models. The dataset contains the raw data from each of these models, in addition to the images/post-processing results generated using these models. Paleomagnetic data produced by LSMOD.2 can be visualized using a combination of linear plotting and contour plotting tools available commonly in visualization software like Python (e.g. Python/Matplotlib) or MATLAB. Standard tools to read and visualize BATS-R-US and MAGNIT output are already publicly available using IDL and Python (see SpacePy/PyBats - https://spacepy.github.io/pybats.html). For information and details about the post-processed data, visualization and analysis, please contact the authors for details. The anthropological dataset can be visualized using a shape file reader (e.g. Python/GeoPandas) and a linear plotting tool (e.g. Python/Matplotlib).
- Discipline:
- Engineering and Science
-
- Creator:
- Surdoval, Alison, Jain, Meha, Wang, Haoyu, and Blesh, Jennifer
- Description:
- We conducted a mixed-methods study to understand how financial incentive programs impact transitions to cover cropping in Michigan. Michigan farms span a wide range of soil types, climate conditions, and cropping systems that create opportunities for cover crop adoption in the state. We tested the relationship between Environmental Quality Incentives Program (EQIP) payments for cover crops and cover crop adoption between 2008-2019, as measured by remote sensing. Panel fixed effects regressions showed that EQIP increased winter cover crop presence. Every EQIP dollar for cover crops was associated with a 0.01 hectare increase in winter cover, while each hectare enrolled in an EQIP contract for cover crops was associated with a 0.86 – 0.93 hectare increase in winter cover.
- Keyword:
- adoption, cover crop, Environmental Quality Incentives Program, financial incentive program, Michigan, remote sensing
- Citation to related publication:
- Surdoval, A., Jain, M., Blair, E., Wang, H., and J. Blesh. In press. Financial incentive programs and farm diversification with cover crops: Assessing opportunities and challenges.
- Discipline:
- Science
-
- Creator:
- Capobianco, Alessio
- Description:
- Reconstructed CT slices for skull of Petrocephalus simus (University of Michigan Museum of Zoology catalog number UMMZ Fish 200167) as a series of TIFF images. Raw projections are not included in this dataset. The reconstructed slice data from the scan are offered here as a series of unsigned 16-bit integer TIFF images. The upper left corner of the first image (*_0000.tif) is the XYZ origin.
- Keyword:
- Zoology, Ichthyology, Fish, CT, Mormyridae, and UMMZ
- Discipline:
- Science
-
- Creator:
- CTEES
- Description:
- Reconstructed CT slices for skull of Pantodon buchholzi (University of Michigan Museum of Zoology catalog number UMMZ Fish 249782) as a series of TIFF images. Raw projections are not included in this dataset. The reconstructed slice data from the scan are offered here as a series of unsigned 16-bit integer TIFF images. The upper left corner of the first image (*_0000.tif) is the XYZ origin.
- Keyword:
- Zoology, Ichthyology, Fish, CT, Pantodontidae, and UMMZ
- Discipline:
- Science
-
- Creator:
- CTEES
- Description:
- Reconstructed CT slices for skull of Hiodon tergisus (University of Michigan Museum of Zoology catalog number UMMZ Fish 247425) as a series of TIFF images. Raw projections are not included in this dataset. The reconstructed slice data from the scan are offered here as a series of unsigned 16-bit integer TIFF images. The upper left corner of the first image (*_0000.tif) is the XYZ origin.
- Keyword:
- Zoology, Ichthyology, Fish, CT, Hiodontidae, and UMMZ
- Discipline:
- Science
-
- Creator:
- CTEES
- Description:
- Reconstructed CT slices for skull of Heterotis niloticus (University of Michigan Museum of Zoology catalog number UMMZ Fish 195004) as a series of TIFF images. Raw projections are not included in this dataset. The reconstructed slice data from the scan are offered here as a series of unsigned 16-bit integer TIFF images. The upper left corner of the first image (*_0000.tif) is the XYZ origin.
- Keyword:
- Zoology, Ichthyology, Fish, CT, Osteoglossidae, and UMMZ
- Discipline:
- Social Sciences
-
- Creator:
- Capobianco, Alessio
- Description:
- Reconstructed CT slices for skull of Chitala blanci (University of Michigan Museum of Zoology catalog number UMMZ Fish 232272) as a series of TIFF images. Raw projections are not included in this dataset. The reconstructed slice data from the scan are offered here as a series of unsigned 16-bit integer TIFF images. The upper left corner of the first image (*_0000.tif) is the XYZ origin.
- Keyword:
- Zoology, Ichthyology, Fish, CT, Notopteridae, and UMMZ
- Discipline:
- Science
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- Creator:
- Dariya, Malyarenko, Tariq, Humera, Kushwaha, Aman, Mourad, Rami, Heist, Kevin, Chenevert, Thomas L, Ross, Brian D, Chen, Heang-Ping, and Hadjiiski, Lubomir
- Description:
- The 3D GRE MRI data for murine model of myelofbifrosis with expert segmentations of mouse tibia was used to train Attention UNET model to automate bone marrow segmentation for measurements of imaging biomarkers. This dataset consists of three archives: (1) containing the source MRI images in Meta-image-header (MHD) format with resulting segmentation labels by two experts and four UNET models with different training scenarios; (2) corresponding training models; and (3) deep-learning (DL)-based segmentation tools for application to future murine tibia MRI data. and The MHD images are an ITK compatible format that can be viewed in standard image viewer, like 3D Slicer. The image archive is structured with a directory tree that contains \"mouseID"\"scan-date"\"segmentaion-scenario"\. The "training model" archive containes DL-model labeled by the data subset, and "deployment" archive containes the DL-segmentation software.
- Keyword:
- deep-learning segmentation, preclinical MRI, murine tibia, and mouse model of myelofibrosis
- Citation to related publication:
- Kushwaha A, Mourad RF, Heist K, Tariq H, Chan HP, Ross BD, Chenevert TL, Malyarenko D, Hadjiiski LM. Improved Repeatability of Mouse Tibia Volume Segmentation in Murine Myelofibrosis Model Using Deep Learning. Tomography. 2023 Mar 7;9(2):589-602. doi: 10.3390/tomography9020048. PMID: 36961007; PMCID: PMC10037585. and https://github.com/dumichgh/MFJK1_Segmentation_MHDs
- Discipline:
- Health Sciences
-
- Creator:
- Malyarenko, Dariya, Chenevert, Thomas L, Heist, Kevin, Bonham, Christopher, and Ross, Brian
- Description:
- The imaging data was used to measure repeatability and temporal trends of quantitative imaging biomarkers of myelofibrosis in bone marrow based on apparent diffusion coefficient, fat fraction and magnetization transfer ratio. The dataset consists of time series of the MRI Meta-image-header (MHD) images of wild type and diseased mice combined by the imaging time point. The MHD images are an ITK compatible format that can be viewed in standard image viewer, like 3D Slicer. Each time point image archive is structured with a directory tree that contains ./././"mouseID"/"scan-date"/"acquisition type"/
- Keyword:
- murine tibia MRI, bone marrow imaging, apparent diffusion coefficient (ADC), proton density fat fraction (PDFF), magnetization transfer ratio (MTR), and pre-clinical model of myelofibrosis
- Citation to related publication:
- Ross BD, Malyarenko D, Heist K, Amouzandeh G, Jang Y, Bonham CA, Amirfazli C, Luker GD, Chenevert TL. Repeatability of Quantitative Magnetic Resonance Imaging Biomarkers in the Tibia Bone Marrow of a Murine Myelofibrosis Model. Tomography. 2023 Feb 28;9(2):552-566. doi: 10.3390/tomography9020045. PMID: 36961004; PMCID: PMC10037563.
- Discipline:
- Health Sciences
-
- Creator:
- Bautista-Arredondo, Luis F., Muñoz-Rocha, T. Verenice, Figueroa, José L., Téllez-Rojo, Martha M., Torres-Olascoaga, Libni A., Cantoral, Alejandra, Arboleda-Merino, Laura C., Leung, Cindy, Peterson, Karen E., and Lamadrid-Figueroa, Héctor
- Description:
- Data was collected from participants of the Early Life Exposures in Mexico to ENvironmental Toxicants (ELEMENT) study, which consists of three sequentially-enrolled birth cohorts of pregnant women. Research protocols of this study were approved by the Institutional Review Board at University of Michigan and the Mexico National Institute of Public Health. We obtained informed consent from study participants prior to enrollment.
- Keyword:
- Food Insecurity, COVID-19 Pandemic, Mexico, Cohort
- Citation to related publication:
- Bautista-Arredondo LF, Verenice Muñoz-Rocha T, Figueroa JL, Téllez-Rojo MM, Torres-Olascoaga LA, Cantoral A, Arboleda-Merino L, Leung L, Peterson KE, and Lamadrid-Figueroa H. A surge in food insecurity during the COVID-19 pandemic in a cohort in Mexico City. 2022. Article in process of publication.
- Discipline:
- Health Sciences
-
- Creator:
- Sheppard, Anja, Sethuraman, Advaith V, Bagoren, Onur, Pinnow, Christopher, Anderson, Jamey, Havens, Timothy C, and Skinner, Katherine A
- Description:
- The AI4Shipwrecks dataset contains sidescan sonar images of shipwrecks and corresponding binary labels collected during 2022 and 2023 at the NOAA Thunder Bay National Marine Sanctuary in Alpena, MI. The data collection platform was an Iver3 Autonomous Underwater Vehicle (AUV) equipped with an EdgeTech 2205 dual-frequency ultra-high resolution sidescan sonar and 3D bathymetric system. The labels were compiled from reference labels created by experts in marine archaeology. The intended use of this dataset is to encourage development of semantic segmentation, object detection, or anomaly detection algorithms in the computer vision field. Comparisons of state-of-the-art segmentation networks on our dataset are shown in the paper. , The file structure is organized as described in the README.txt file, where images in 'images' directories are the waterfall product of sidescan sonar surveys, and images in 'labels' directories are binary representations of expert labels. Images across the 'images' and 'labels' directories are correlated by having identical filenames. In the label images, a pixel value of '0' represents the non-shipwreck/other class and '1' represents the shipwreck class for the correspondingly named image (<wreck_name>_<##>.png) in the images directory. , and The project webpage can be found at: https://umfieldrobotics.github.io/ai4shipwrecks/
- Keyword:
- machine learning, computer vision, field robotics, marine robotics, underwater robotics, sidescan sonar, semantic segmentation, and object detection
- Discipline:
- Engineering
-
- Creator:
- Xiantong Wang
- Description:
- Bursty bulk flows (BBFs) are identified as the fast earthward-propagating flows from magnetic reconnection in Earth's magnetotail. BBFs are related to particle energization process reported by satellite observations. For the first time, we use a novel numerical model that simulates kinetic physics directly in a global model. The energization of the electrons associated with BBF is demonstrated by the model. The electron velocity distribution functions (VDFs) extracted from multiple locations associated with BBF demonstrate good agreements with the observations. The energy-dependent electron pitch angle distribution at the leading part of the BBF can be explained by the enhancement of the local magnetic field.
- Discipline:
- Science
-
- Creator:
- Zhang, Yingxiao MI
- Description:
- We developed a new model framework based on WRF-Chem, simulating primary biological aerosol particle emissions and their interaction with clouds. We have designed different sensitivity tests to evaluate the effects of pollen and sub-pollen particles (SPPs), respectively. Our results show that SPPs have a larger effect on cloud microphysics and precipitation than whole pollen grains.
- Keyword:
- Aerosol-cloud interactions, Primary biological aerosol particles, Ice nucleating particles, Microphyscis scheme, and Pollen
- Discipline:
- Science
-
- 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. , and 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
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://umautobots.github.io/nsavp, https://github.com/umautobots/nsavp_tools, and https://sites.google.com/umich.edu/novelsensors2023
- 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. , and 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
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://umautobots.github.io/nsavp, https://github.com/umautobots/nsavp_tools, and https://sites.google.com/umich.edu/novelsensors2023
- 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. , and 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
- Keyword:
- novel sensing, perception, autonomous vehicles, thermal sensing, neuromorphic imaging, and event cameras
- Citation to related publication:
- https://umautobots.github.io/nsavp, https://github.com/umautobots/nsavp_tools, and https://sites.google.com/umich.edu/novelsensors2023
- Discipline:
- Engineering
-
- Creator:
- Cevidanes, Lucia
- Description:
- Image Pre-Processing To allow reliable detection and comparison of changes between several individuals or within the same individual at different time points, before extracting the quantitative bone texture/morphometry features, all hr-CBCT scans were pre-processed using validated protocols. Extraction of Trabecular Bone Texture-based and Morphometry Imaging Features Using the “crop-volume” tool in 3D Slicer, a rectangular shaped volume of interest (VOI) was cropped from the trabecular bone in the mandibular condyles and the articular fossa. Then, using the average minimum and maximum intensity values of all VOIs, we standardized the grey level intensities of the VOIs to eliminate inaccuracies of textural features calculation and possible dependency on the global characteristics of the images. Lastly, imaging markers were extracted from the standardized VOIs using “BoneTexture” module in 3D-slicer. Measurement of the 3D Articular Joint Space To assess the progression/improvement of osteoarthritic changes in the affected individuals, we measured the 3D superior joint space. We pre-labelled two landmarks in the sagittal view of the oriented CBCT scans: on the most superior point of the condyle and on the opposing surface of the articular fossa. To avoid biasing the landmarks’ placements, pre-labelling was performed simultaneously on T1 and T2 scans, using two independent windows in ITK-SNAP. After the volumetric reconstruction of the identified landmarks, linear measurements were obtained in millimeters using the Q3DC tool in 3D Slicer. Three-dimensional Shape Analyses and Quantification of Remodeling in the Condyles SPHARM-PDM software was used to compute the correspondence across 4002 surface points among all condyles. The output point-based models displayed color-coded maps that enabled visual evaluation of consistent parametrization of all condyles. An average condyle shape for the TMJ OA and control groups was calculated through propagation of original surface point correspondences across all stages of deformations and averaging the condyle surface meshes. For visualization of the 3D qualitative changes of the average models within the same group at different time points or among different groups, semi-transparent overlays were created using 3D Slicer software. The vector differences were presented on the condyle surfaces, scaled according to the magnitude of difference, and pointing towards the direction of bone change. For quantification of remodeling in the condyles, calculation of signed distances across condyles surface meshes reflected the quantitative bone changes in the TMJ OA and control samples. To quantify regional bone changes across the lateral and anterior surfaces of the condyles, we used the Pick ‘n Paint tool in 3D Slicer to propagate regional surface points to the corresponding regions of shapes across all subjects and time points.
- Keyword:
- Degenerative joint disease, Temporomandibular joint osteoarthritis, TMJ OA, Machine learning, Prognosis
- Discipline:
- Health Sciences
-
- Creator:
- Lumeng, Julie C
- Description:
- Infant eating behavior is likely driven not only by hunger and satiety reflective of caloric need, but also by the reward value of food. The reward value of food can be understood in terms of wanting, liking, and salience. Little is understood about infant response to the reward value of food, or its predictors, particularly prenatally. This project sought to understand whether prenatal factors during pregnancy predict infant reward response to food, as measured by questionnaires in early infancy.
- Keyword:
- wanting, liking, salience, infancy, eating, growth, and prenatal
- Discipline:
- Health Sciences
-
- Creator:
- Chung, Taewon , McClain, Taylor P. , Alonso-Mori, Roberto , Chollet, Matthieu , Deb, Aniruddha , Garcia-Esparza, Angel T. , Huang, Joel Ze En , Lamb, Ryan M. , Michocki, Lindsay B. , Reinhard, Marco , van Driel, Tim B. , Penner-Hahn, James E. , and Sension, Roseanne J.
- Description:
- UV-visible, X-ray absorption, and X-ray emission data used to characterize the dynamics of methyl cobalamin at low pH, so called "base off" configuration. Details of data collection and reduction are provided in the associated manuscript. Data files are all text files which contain tab-delimited columns of data corresponding to each figure in the manuscript
- Keyword:
- Ultrafast, X-ray, Transient absorption, cobalamin, vitamin B12, XAS, and XANES
- Citation to related publication:
- Chung, T., et al. (2024). "Ultrafast X-ray Absorption Spectroscopy Reveals Excited State Dynamics of B12 Coenzymes Controlled by the Axial Base". J. Phys. Chem. B. 2024, in press https://pubs.acs.org/doi/10.1021/acs.jpcb.3c07779
- Discipline:
- Science
-
- Creator:
- Rana, Gurpreet K., Reynolds, Christopher W., Rha, Jennifer Y., Lenselink, Allison M., Asokumar, Dhanya, Zebib, Laura, Giacona, Francesca L. , Islam, Nowshin N., Kannikeswaran, Sanjana, Manuel, Kara, Cheung, Allison, Marzoughi, Maedeh , and Heisler, Michele
- Description:
- The search data supports a literature review project on "Innovative strategies and implementation science approaches for health delivery among migrants in humanitarian settings". The data included in the dataset are the complete search strategies (rtf file) and the exported results of all citations from all databases (ris file) after removal of duplicate citations.
- Keyword:
- humanitarian setting, migrant, forced displacement , health delivery, implementation science, and scoping review
- Discipline:
- Health Sciences