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- Creator:
- Jones, Kaylin, Fernández Correa, Mariana I., Malherbe, Julien, and Cotel, Aline J.
- Description:
- Sea lampreys (Petromyzon marinus) are an invasive species of concern in the Laurentian Great Lakes. Their predation on native species has degraded the ecological and economic health of the region. They are thus targeted for removal through various means, including trapping. Currently, sea lamprey traps are somewhat inefficient, believed to be partially due to their “entrance flows”, or the flow patterns induced by these traps that are felt by approaching sea lampreys. This study experimentally quantifies these flows. Models of two common sea lamprey trap designs were built and installed in a water tunnel in the University of Michigan Hydraulics Lab, and attraction flows were measured using Particle Image Velocimetry (PIV) with minimal background turbulence. Velocity, velocity gradient, and vorticity distributions in the flow are evaluated from the PIV data. These same models were installed in larger-scale raceways at USGS’ Hammond Bay Biological Station, and attraction flows were again measured using PIV to explore how these patterns change in a more turbulent environment that better mimics natural conditions. and Hammond Bay Biological Station (HBBS) is a research center that aims to develop control measures for sea lampreys and conduct research to aid native fish restoration. HBBS is a field station of the USGS Great Lakes Science Center (GLSC) managed by the Great Lakes Fishery Commission (GLFC). More information on HBBS can be found here: https://www.usgs.gov/centers/great-lakes-science-center/science/hammond-bay-biological-station.
- Keyword:
- Entrance Flows, sea lamprey, Great Lakes, hydrodynamics, invasive species, particle image velocimetry, sea lamprey, sea lamprey traps, and turbulence
- Citation to related publication:
- Jones, Kaylin, et. al. 2024. Investigating entrance hydrodynamics of sea lamprey traps. Canadian Journal of Fisheries and Aquatic Sciences. XX(X): XXX-XXX. https://doi.org/XX.XXXX/cjfas-XXXX.
- Discipline:
- Engineering
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- Creator:
- Zhu, Yongxian, Deng, Sidi, and Cooper, Daniel R
- Description:
- This dataset is curated as a byproduct of the "Material and Vehicle Design for High-Value Recycling of Aluminum and Steel Automotive Sheet" project, funded by the REMADE Institute of the Department of Energy and referred to as the "Clean Sheet Project" in the file "electricity scenarios slides.pptx." The dataset presents projected U.S. electricity emission factors (MJ primary energy or gCO2/kWh electricity delivered) under various scenarios, including different levels of uptake of the U.S. Inflation Reduction Act. The projections are based on estimated trends in the U.S. electricity generation mix, along with the authors' analysis of the energy and emission intensities of relevant power sources. The dataset supports research—particularly life cycle assessment—relying on U.S. regional energy profile and emissions factors.
- Keyword:
- Electricity Mix, Renewable Energy, Greenhouse Gas Emissions, Decarbonization, and Net-Zero
- Discipline:
- Engineering and General Information Sources
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- Creator:
- Mirshams Shahshahani, Payam
- Description:
- Please see Payam Mirshams Shahshahani's University of Michigan doctoral dissertation: https://deepblue.lib.umich.edu/bitstream/handle/2027.42/155254/mirshams_1.pdf?sequence=1
- Keyword:
- unipedal balance, hip muscle strength and endurance, age, hip moment
- Citation to related publication:
- Mirshams Shahshahani, Masteling and Ashton-Miller, article under review in IISE Transactions on Occupational Ergonomics & Human Factors, Supplement, Festschrift for Professor Thomas J. Armstrong
- Discipline:
- Engineering
-
- Creator:
- Fu, Xun, Zhang, Bohao, Weber, Ceri J., Cooper, Kimberly L., Vasudevan, Ram, and Moore, Talia Y.
- Description:
- Tails used as inertial appendages induce body rotations of animals and robots---a phenomenon that is governed largely by the ratio of the body and tail moments of inertia. However, vertebrate tails have more degrees of freedom (e.g., number of joints, rotational axes) than most current theoretical models and robotic tails. To understand how morphology affects inertial appendage function, we developed an optimization-based approach that finds the maximally effective tail trajectory and measures error from a target trajectory. For tails of equal total length and mass, increasing the number of equal-length joints increased the complexity of maximally effective tail motions. When we optimized the relative lengths of tail bones while keeping the total tail length, mass, and number of joints the same, this optimization-based approach found that the lengths match the pattern found in the tail bones of mammals specialized for inertial maneuvering. In both experiments, adding joints enhanced the performance of the inertial appendage, but with diminishing returns, largely due to the total control effort constraint. This optimization-based simulation can compare the maximum performance of diverse inertial appendages that dynamically vary in moment of inertia in 3D space, predict inertial capabilities from skeletal data, and inform the design of robotic inertial appendages. and 2025-01-31: In this update, we include the code required to run the simulations and optimizations. We updated the readme file to reflect this addition
- Keyword:
- simulation, inertial maneuvering, caudal vertebrae, trajectory optimization, and reconfigurable appendages
- Citation to related publication:
- Xun Fu, Bohao Zhang, Ceri J. Weber, Kimberly L. Cooper, Ram Vasudevan, Talia Y. Moore. (in review) Jointed tails enhance control of three-dimensional body rotation.
- Discipline:
- Engineering and Science
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- Creator:
- An, Yifu
- Description:
- We have ported our MHD code, BATSRUS ( https://github.com/SWMFsoftware/BATSRUS), to the GPU. This dataset contains the input parameters and raw timing results for the Paper. To reproduce the results, please follow the instructions and use the software specifications contained in readme.txt. and Abstract: BATSRUS, our state-of-the-art extended magnetohydrodynamic code, is the most used and one of the most resource-consuming models in the Space Weather Modeling Framework. It has always been our objective to improve its efficiency and speed with emerging techniques, such as GPU acceleration. To utilize the GPU nodes on modern supercomputers, we port BATSRUS to GPUs with the OpenACC API. Porting the code to a single GPU requires rewriting and optimizing the most used functionalities of the original code into a new solver, which accounts for around 1% of the entire program in length. To port it to multiple GPUs, we implement a new message passing algorithm to support its unique block-adaptive grid feature. We conduct weak scaling tests on as many as 256 GPUs and find good performance. The program has 50-60% parallel efficiency on up to 256 GPUs, and up to 95% efficiency within a single node (4 GPUs). Running large problems on more than one node has reduced efficiency due to hardware bottlenecks. We also demonstrate our ability to run representative magnetospheric simulations on GPUs. The performance for a single A100 GPU is about the same as 270 AMD "Rome" CPU cores, and it runs 3.6 times faster than real time. The simulation can run 6.9 times faster than real time on four A100 GPUs.
- Keyword:
- BATSRUS, GPU, and MHD simulation
- Citation to related publication:
- An, Y., Chen, Y., Zhou, H., Gaenko, A. and Toth, G. (2024). BATSRUS GPU: Faster than Real Time Magnetospheric Simulations with a Block Adaptive Grid Code. Being revised. A preprint is available at http://arxiv.org/abs/2501.06717.
- Discipline:
- Engineering
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- Creator:
- Chen, Hongfan, Sachdeva, Nishtha, Huang, Zhenguang, van der Holst, Bart, Manchester, Ward, Jivani, Aniket, Zou, Shasha, Chen, Yang, Huan, Xun, and Toth, Gabor
- Description:
- In this study, we show that coronal mass ejection (CME) simulations conducted with the Space Weather Modeling Framework (SWMF) can be assimilated with SOHO LASCO white-light (WL) coronagraph observations and solar wind observations at L1 prior to the CME eruption to improve the prediction of CME arrival time. L1 observations are used to constrain the background solar wind, while LASCO coronagraph observations filter the initial ensemble simulations by constraining the simulated CME propagation speed. We then construct probabilistic predictions for CME arrival time using the data-assimilated ensemble. Scripts in this work are written in R, Python and Julia.
- Keyword:
- Data Assimilation, Uncertainty Quantification, and Space Weather
- Discipline:
- Engineering
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- Creator:
- Sulkowski, Brendan and Collette, Matthew
- Description:
- This data set supports the published four-component integration problem using real-world weather forecasts from the European Centre for Medium-Range Weather Forecast and a simulated linear spring--mass--damper system excited by wave elevation. Each component in the spring--mass--damper system is monitored with techniques of differing accuracies representative of marine-type health uncertainties. Weather forecast uncertainty is included using weather predictions of significant wave height and peak period up to 10 days out. As well as their exact values, different test cases include the spring, mass, and damper being modeled as noisy sensors representative of sensors onboard a vessel, as well as the spring being modeled as a visually-inspected system component reflective of human impact onboard a vessel. Complete details are given in the referenced paper; this data set represents the inputs to the machine learning classifiers discussed.
- Keyword:
- Machine Learning, Inspection, Marine system, and Weather forecast
- Citation to related publication:
- Sulkowski, B and M. Collette. (2025) A comparison of machine learning classifiers in predicting safety for a multi-component dynamic system representation of an autonomous vessel. Applied Ocean Research, 154 (104368), https://doi.org/10.1016/j.apor.2024.104368
- Discipline:
- Engineering
-
- Creator:
- Teague, Seth, Yu, Zhiyuan, and Heemskerk, Idse
- Description:
- Images were collected as part of a project investigating the interpretation of BMP signaling dynamics by differentiating human pluripotent stem cells. Image files are in the proprietary Imaris (.ims) file format. MATLAB and Python code for image processing and quantification is provided with the data and at https://github.com/seth414/HeemskerkLabMethods. Processed data originally published in Teague et al., 2024 (see below).
- Keyword:
- cell tracking, human pluripotent stem cells, immunofluorescence, and signaling dynamics
- Citation to related publication:
- Teague, S., Primavera, G., Chen, B. et al. Time-integrated BMP signaling determines fate in a stem cell model for early human development. Nat Commun 15, 1471 (2024). https://doi.org/10.1038/s41467-024-45719-9
- Discipline:
- Health Sciences and Engineering
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- Creator:
- Burgin, Tucker and Mayes, Heather B.
- Description:
- This project aimed to discover and analyze the molecular mechanism of synthesis of two particular fucosylated oligosaccharide products in a mutant enzyme, Thermatoga maratima Alpha-L-Fucosidase D224G, whose wild type performs the opposite reaction (cleavage of fucosyl glycosidic bonds). Discovery of the mechanism was performed using an unbiased simulations method known as aimless shooting, whereas analysis of the mechanism in terms of the energy profile was performed using a separate method known as equilibrium path sampling. The data here concerns the latter method. and The contents of the atesa_master.zip are the ATESA GitHub project. A Python program for automating transition path sampling with aimless shooting using Amber. https://github.com/team-mayes/atesa
- Keyword:
- Equilibrium Path Sampling, Transition Path Sampling, Enzymatic Mechanism, and GH29
- Citation to related publication:
- Burgin, T., & Mayes, H. B. (2019). Mechanism of oligosaccharide synthesis via a mutant GH29 fucosidase. Reaction Chemistry & Engineering, 4(2), 402–409. https://doi.org/10.1039/C8RE00240A
- Discipline:
- Engineering
-
- Creator:
- Ruas, Terry, Ferreira, Charles H. P., Grosky, William, França, Fabrício O., and Medeiros, Débora M. R,
- Description:
- The relationship between words in a sentence often tell us more about the underlying semantic content of a document than its actual words, individually. Recent publications in the natural language processing arena, more specifically using word embeddings, try to incorporate semantic aspects into their word vector representation by considering the context of words and how they are distributed in a document collection. In this work, we propose two novel algorithms, called Flexible Lexical Chain II and Fixed Lexical Chain II that combine the semantic relations derived from lexical chains, prior knowledge from lexical databases, and the robustness of the distributional hypothesis in word embeddings into a single decoupled system. In short, our approach has three main contributions: (i) unsupervised techniques that fully integrate word embeddings and lexical chains; (ii) a more solid semantic representation that considers the latent relation between words in a document; and (iii) lightweight word embeddings models that can be extended to any natural language task. Knowledge-based systems that use natural language text can benefit from our approach to mitigate ambiguous semantic representations provided by traditional statistical approaches. The proposed techniques are tested against seven word embeddings algorithms using five different machine learning classifiers over six scenarios in the document classification task. Our results show that the integration between lexical chains and word embeddings representations sustain state-of-the-art results, even against more complex systems. Github: https://github.com/truas/LexicalChain_Builder
- Keyword:
- document classification, lexical chains, word embeddings, synset embeddings, chain2vec, and natural language processing
- Citation to related publication:
- Terry Ruas, Charles Henrique Porto Ferreira, William Grosky, Fabrício Olivetti de França, Débora Maria Rossi de Medeiros, "Enhanced word embeddings using multi-semantic representation through lexical chains", Information Sciences, 2020, https://doi.org/10.1016/j.ins.2020.04.048
- Discipline:
- Other, Science, and Engineering