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- Creator:
- Rida, Salam and Smith, Torri
- Description:
- Michigan-Mellon’s renewed Egalitarian Metropolis cycle of funding focuses on the city of Detroit and ways that creative practice and the urban humanities can equitably address urban recovery. In tangible ways, The University of Michigan Architecture Preparatory Program (ArcPrep) is already doing just that: creating a sense of optimism and agency for Detroit public high school juniors interested in design and its affiliated fields. , Through an intensive, semester-long studio taught by our Mellon Fellows in Architecture, young designers learn to critically discern Detroit’s complex spatial histories as they explore ways to shape the city’s possible futures. The program takes the students’ talents, creativity, and expertise very seriously, nurturing an inclusionary pedagogical model based broadly on egalitarian educational ideals. In the process, we bring together a network of Taubman College faculty and students, Detroit institutions, community and government organizations, and professional enterprises into conversation and collaboration with students. In the past, ArcPrep has partnered with the Detroit Public Library, the Detroit Institute of Arts, the Detroit Cultivator Community Land Trust, and the Sidewalk Festival, to name a few. With each partnership, we situated culturally contingent, place-based design exercises for students to directly engage with the city and its leaders., and More information about the Michigan Architecture Preparatory Program (ArcPrep) can be found at https://taubmancollege.umich.edu/academics/pre-college-programs/michigan-architecture-prep/
- Discipline:
- Social Sciences and Humanities
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- Creator:
- Nikolov, Denislav P, Srivastava, Siddhartha, Abeid, Bachir A, Scheven, Ulrich M, Arruda, Ellen M, Garikipati, Krishna, and Estrada, Jonathan B
- Description:
- Contemporary material characterisation techniques that leverage deformation fields and the weak form of the equilibrium equations face challenges in the numerical solution procedure of the inverse characterisation problem. As material models and descriptions differ, so too must the approaches for identifying parameters and their corresponding mechanisms. The widely-used Ogden material model can be comprised of a chosen number of terms of the same mathematical form, which presents challenges of parsimonious representation, interpretability, and stability. Robust techniques for system identification of any material model are important to assess and improve experimental design, in addition to their centrality to forward computations. Using fully 3D displacement fields acquired in silicone elastomers with our recently-developed magnetic resonance cartography (MR-u) technique on the order of ~20,000 points per sample, we leverage PDE-constrained optimisation as the basis of variational system identification of our material parameters. We incorporate the statistical F-test to maintain parsimony of representation. Using a new, local deformation decomposition locally into mixtures of biaxial and uniaxial tensile states, we evaluate experiments based on an analytical sensitivity metric, and discuss the implications for experimental design. This repository contains the acquired data and MRI processing code used in this work.
- Keyword:
- continuum mechanics, magnetic resonance, sensitivity, full-field deformations, physics inference, mechanics, mechanical engineering, and computational mechanics
- Citation to related publication:
- https://doi.org/10.48550/arXiv.2204.03122
- Discipline:
- Engineering
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- Creator:
- Blesh, Jennifer
- Description:
- This dataset contains three data files used in: Blesh, J. 2017. Functional traits in cover crop mixtures: biological nitrogen fixation and multifunctionality. Journal of Applied Ecology. There are also three corresponding metadata files. The file “Ecosystem_functions_soil_species.csv” contains data organized by farm, treatment, replicate block, and species combining the fall and spring sampling time points. These data include aboveground biomass, nitrogen and carbon content, and biological nitrogen fixation for the plant species. The dataset also includes measured soil characteristics for each farm site. The file “Ecosystem_functions_soil_treatment.csv” contains data organized by farm, treatment, and replicate block for the fall and spring sampling time points combined. These data include aboveground biomass, nitrogen and carbon content, and biological nitrogen fixation aggregated by treatment. The dataset also includes measured soil characteristics for each farm site. The file “Traits_unstandardized.csv” contains individual plant trait data, a subset of which were used to calculate an index of functional diversity after they were standardized to have zero mean and unit variance. These data are organized by farm, treatment, replicate block, and species. The corresponding metadata files: “Ecosystem_functions_soil_species_metadata.csv”, “Ecosystem_functions_soil_treatment_metadata.csv”, and “Traits_unstandardized_metadata.csv” provide a detailed description of all variables in each dataset and any abbreviations used. Note: On Dec 19th 2017, the format of the files was changed to csv to aid preservation. The following information was added to the three metadata files: the name of the data file the metadata refers to, an explanation as to the meaning of blank cells in the data file, a full citation to the paper where the author describes her findings and contact information for the author.
- Keyword:
- agroecology, biological nitrogen fixation, functional diversity, and cover crop
- Citation to related publication:
- Blesh J. Functional traits in cover crop mixtures: Biological nitrogen fixation and multifunctionality. J Appl Ecol. 2018;55:38–48. https://doi.org/10.1111/1365-2664.13011
- Discipline:
- Science
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- Creator:
- Bressler, Alison and Blesh, Jennifer
- Description:
- This dataset contains three data files and three corresponding metadata files used in Bressler, A., and J. Blesh. 2023. A grass-legume cover crop maintains nitrogen inputs and nitrous oxide fluxes from an organic agroecosystem. Ecosphere. The file “N2O_Flux.xls” contains daily nitrous oxide data organized by replicate block, treatment, and date. The file “Soil_N.xls” contains nitrate and ammonium data organized by replicate block, treatment, and date. The file “Cover_crop_corn_soil.xls” contains baseline soil fertility characteristics, cover crop and corn biomass, nitrogen and carbon content, legume BNF, and cumulative N2O content organized by replicate block and treatment. The corresponding metadata files: “N2O_Flux_metadata.xls”, “Soil_N_metadata.xls”, and “Cover_crop_corn_soil_metadata.xls” provide detailed descriptions of all variables in each data set and any abbreviations used.
- Keyword:
- cover crops, nitrous oxide, corn, biological nitrogen fixation, and legume-grass mixtures
- Citation to related publication:
- Bressler, A., and J. Blesh. 2023. A grass-legume cover crop maintains nitrogen inputs and nitrous oxide fluxes from an organic agroecosystem. Ecosphere. 14(2): e4428. https://doi.org/10.1002/ecs2.4428
- Discipline:
- Science
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- Creator:
- Bressler, Alison and Blesh, Jennifer
- Description:
- This dataset contains three data files and three corresponding metadata files used in Bressler, A., and J. Blesh. 2022. Episodic N2O emissions following tillage of a legume-grass cover crop mixture. Biogeosciences. The file “Cover_crop_soil_N2O.xls” contains data organized by site, replicate block, and treatment for spring cover crop biomass, nitrogen and carbon content, and legume BNF; soil fertility characteristics including potentially mineralizable nitrogen, particulate organic matter stocks, concentrations, and nitrogen content; and cumulative nitrous oxide data. The file “Soil_properties.xls” contains baseline soil data organized by site and replicate block. The file “Daily_N2O.xls” contains daily nitrous oxide data organized by site, replicate block, treatment, and date. The corresponding metadata files: “Cover_crop_soil_N2O_metadata.xls”, and “Soil_properties_metadata.xls”, and “Daily_N2O_metadata.xls” provided detailed descriptions of all variables in each data set and any abbreviations used.
- Keyword:
- cover crops, legume-grass mixtures, nitrous oxide, particulate organic matter, soil organic matter.
- Citation to related publication:
- Bressler, A., and J. Blesh. 2022. Episodic N2O emissions following tillage of a legume-grass cover crop mixture. Biogeosciences.
- Discipline:
- Science
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- Creator:
- Lori, Jody R., Moyer, Cheryl, Lockhart, Nancy, Zielinski, Ruth E., Kukula, Vida, Apetorgbor, Veronica, Awini, Elizabeth, Badu-Gyan, Georgina, and Williams, John
- Description:
- GRAND is a five-year, cluster randomized controlled trial. The study is registered on ClinicalTrials.gov, [ID#: NCT04033003] and is a collaboration between University of Michigan in the United States and the Dodowa Health Research Center in Ghana. , The study setting for GRAND is four districts (Akwapim North, Yilo Krobo, Nsawam-Adoagyiri, and Lower Manya Krobo) within the Eastern Region of Ghana. Health facilities were selected based the number ANC registrants per month and average gestational age of women at registration in each facility., and Facilities were then matched based on facility type, district, and number of monthly ANC registrants. A cluster randomized controlled trial was conducted in 14 facilities in four districts of the Eastern Region of Ghana. Health facilities were randomized using a matched pairs design; each pair was similar in the number of deliveries and average gestational age of the women at enrollment in antenatal care. The locations of the facilities were far enough apart to avoid cross-group contamination. In each pair of facilities, one was randomly assigned to the intervention (G-ANC) and the other to the control (I-ANC). Recruitment began July 2019 and ended when enrollment targets were met. Data collection ended July 2023 when data collection was complete.
- Keyword:
- Antenatal care, Ghana, and Maternal health
- Citation to related publication:
- Lori, J., Kukula, V., Liu, L. et al. Improving health literacy through group antenatal care: results from a cluster randomized controlled trial in Ghana. BMC Pregnancy Childbirth 24, 37 (2024). https://doi.org/10.1186/s12884-023-06224-x
- Discipline:
- International Studies and Health Sciences
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- 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.
- 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:
- Porter, David
- Description:
- Launched in response to the growing crisis of narrative infrastructure, the Detroit River Story Lab is a collaborative, public-facing initiative that leverages the sociocultural, economic, and ecological centrality of the Detroit River corridor to reimagine it as an urban case study in narrative placemaking and civic renewal. Beginning with the premise that place-based storymaking is vital to sustaining democratic values and community capacity for self-determination, the Lab partners on projects designed to support the narrative capacities of local urban communities through the story-telling channels of community journalism, place-based education, and public history., The Story Lab co-designs scalable interventions to strengthen community-based forms of narrative infrastructure. Participants draw upon archives and oral histories to document previously marginalized narratives centering the river. Drawing on this research, we prototype new approaches to place-based learning, within the university and beyond, to expand the publics involved in the production and circulation of local narratives of identity and urban memory., and More information about the Detroit River Story Lab (DRSL) can be found at https://sites.lsa.umich.edu/detroit-river-story-lab/.
- Discipline:
- Humanities and Social Sciences
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- Creator:
- Lee, Sophie Y., Schönhöfer Philipp W.A., and Glotzer, Sharon C.
- Description:
- This dataset was generated for our work: "Complex motion of steerable vesicular robots filled with active colloidal rods". In this project, we used Brownian molecular dynamics simulations to study the rich dynamical behavior of rigid kinked vesicles that contain self-propelling rod-shaped particles. We identified that kinks in the vesicle membrane bias the emergent clustering and alignment of the active agents. Based on the system's geometrical and material properties, we were able to design multiple types of directed motion of the vesicle superstructure. This dataset includes simulation data for two-dimensional systems of self-propelling rod particles confined by teardrop-shaped coarse-grained vesicles. The trajectory of each simulation is saved in a GSD format file with parameter metadata in a JSON file. Due to the large number of replicas of each pair of parameters, simulation data were grouped into 5 different folders. Collective quantitative analysis for simulated trajectories was performed with Jupyter Notebook. and Workspaces_simulations.zip contains all the workspaces of simulations Each folder has subfolders called 'dimer' and 'trimer' depending on the length of the propelling rod particles used in the simulation. (Except for the folder 'number-density_16' which has only 'dimer') In the subfolders, we include the Python scripts used in this work for simulating and trajectory analysis for individual trajectory data. The parameter space of each folder is noted in init.py. Analysis_jupyter_notebooks.zip includes Jupyter notebooks that can reproduce the collective analysis done for this work.
- Discipline:
- Engineering
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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