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- Creator:
- Ponder, Brandon M., Ridley, Aaron J., Goel, Ankit, and Bernstein, Dennis S.
- Description:
- This research was completed to statistically validate that a data-model refinement technique could integrate real measurements to remove bias from physics-based models via changing the forcing parameters such as the thermal conductivity coefficients.
- Keyword:
- Thermosphere, GITM, CHAMP, GRACE, MSIS, Upper Atmosphere Modeling, and Data Assimilation
- Citation to related publication:
- Ponder, B. M., Ridley, A. J., Goel, A., & Bernstein, D. S. (2023). Improving forecasting ability of GITM using data-driven model refinement. Space Weather, 21, e2022SW003290. https://doi.org/10.1029/2022SW003290
- Discipline:
- Engineering and Science
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- Creator:
- Danforth, Shannon M.
- Description:
- This dataset includes three MATLAB data files for each subject: raw motion capture and force plate data, processed motion capture and force plate data, and sagittal-plane data segmented into individual trials labeled “nominal” or “tripped.” We include two example scripts for using the segmented trial data to tabulate trip recovery strategies across subjects and plot the sorted recovery strategies.
- Keyword:
- Trip recovery, Biomechanics, and Human locomotion
- Citation to related publication:
- S. M. Danforth, X. Liu, M. J. Ward, P.D. Holmes, and R. Vasudevan, "Predicting sagittal-plane swing hip kinematics in response to trips," IEEE Robotics and Automation Letters, 2022.
- Discipline:
- Engineering
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- Creator:
- Light, Charles X, Arbic, Brian K, Martin, Paige E, Brodeau, Laurent, Farrar, J Thomas, Griffies, Stephen M, Kirtman, Ben P, Laurindo, Lucas, Menemenlis, Dimitris, Molod, Andrea, Nelson, Arin D, Nyadjro, Ebenezer, O'Rourke, Amanda K, Shriver, Jay, Siqueira, Leo, Small, R Justin, and Strobach, Udi
- Description:
- The precipitation data itself is the output of the models/datasets that we analyze in our paper. Most of it is in .nc or .nc4 format, although we provide code to extract the data into time series .mat files. We used MATLAB to perform our analysis.
- Keyword:
- precipitation and power spectra
- Citation to related publication:
- Light, C.X., Arbic, B.K., Martin, P.E., Brodeau, L., Farrar, J.T., Griffies, S.M., Kirtman, B.P., Laurindo, L.C., Menemenlis, D., Molod, A., Nelson, A.D., Nyadjro, E., O'Rourke, A.K., Shriver, J.F., Siqueira, L., Small, R.J., Strobach, E. (2022). Effects of grid spacing on high-frequency precipitation variance in coupled high-resolution global ocean-atmosphere models. Climate Dynamics, https://doi.org/10.1007/s00382-022-06257-6
- Discipline:
- Science
-
Defect patterns on the curved surface of fish retinae suggest a mechanism of cone mosaic formation
User Collection- Creator:
- Nunley, Hayden, Nagashima, Mikiko, Martin, Kamirah, Lorenzo Gonzalez, Alcides, Suzuki, Sachihiro C., Norton, Declan A., Wong, Rachel O. L., Raymond, Pamela A., and Lubensky, David K.
- Description:
- The outer epithelial layer of zebrafish retinae contains a crystalline array of cone photoreceptors, called the cone mosaic. As this mosaic grows by mitotic addition of new photoreceptors at the rim of the hemispheric retina, topological defects, called “Y-Junctions”, form to maintain approximately constant cell spacing. The generation of topological defects due to growth on a curved surface is a distinct feature of the cone mosaic not seen in other well-studied biological patterns like the R8 photoreceptor array in the _ Drosophila compound eye. Since defects can provide insight into cell-cell interactions responsible for pattern formation, here we characterize the arrangement of cones in individual Y-Junction cores (see Set of images for Figures 1 and 2 and 6 and Supplementary Figure 7) as well as the spatial distribution of Y-junctions across entire retinae (see Dataset for analyzing spatial distribution of Y-junctions in flat-mounted retinae). We find that for individual Y-junctions, the distribution of cones near the core corresponds closely to structures observed in physical crystals (see Set of images for Figures 1 and 2 and 6 and Supplementary Figure 7). In addition, Y-Junctions are organized into lines, called grain boundaries, from the retinal center to the periphery (see Dataset for analyzing spatial distribution of Y-junctions in flat-mounted retinae and Dataset for measuring tendency of Y-junctions to line up into grain boundaries during incorporation into retinae). In physical crystals, regardless of the initial distribution of defects, defects can coalesce into grain boundaries via the mobility of individual particles. By imaging in live fish, we demonstrate that grain boundaries in the cone mosaic instead appear during initial mosaic formation, without requiring defect motion (see Dataset for measuring tendency of Y-junctions to line up into grain boundaries during incorporation into retinae and Dataset for analyzing Y-junction motion in live fish retinae). Motivated by this observation, we show that a computational model of repulsive cell-cell interactions generates a mosaic with grain boundaries (see Code and example simulations of phase-field crystal model (for cone mosaic formation)). In contrast to paradigmatic models of fate specification in mostly motionless cell packings (see Code and accompanying input data for simulating lateral inhibition on motionless cell packing), this finding emphasizes the role of cell motion, guided by cell-cell interactions during differentiation, in forming biological crystals. Such a route to the formation of regular patterns may be especially valuable in situations, like growth on a curved surface, where the resulting long-ranged, elastic, effective interactions between defects can help to group them into grain boundaries.
- Keyword:
- zebrafish cone mosaic, lattice vectors, topological defects, tissue patterning, grain boundaries, lateral inhibition, photoconversion, phase-field crystal model, and defect motion
- Discipline:
- Science
7Works -
- Creator:
- Ansong, Joseph K. and Arbic, Brian K.
- Description:
- This is the model and observational data referenced in our manuscript entitled “surface and sub-subsurface internal gravity wave kinetic energy spectra from global ocean models and observations.” The model data for the 7 regions from the two global simulations (HYCOM and MITgcm) can be found here.
- Keyword:
- vertical wavenumber spectra of internal waves, surface kinetic energy spectra, and ratio of high versus low-frequency surface kinetic energy
- Citation to related publication:
- Ansong, J.K., et al., "forthcoming", Surface and sub-subsurface internal gravity wave kinetic energy spectra in global ocean models and observations
- Discipline:
- Science
-
- Creator:
- Nunley, Hayden, Nagashima, Mikiko, Martin, Kamirah, Lorenzo Gonzalez, Alcides, Suzuki, Sachihiro C., Norton, Declan A., Wong, Rachel O. L., Raymond, Pamela A., and Lubensky, David K.
- Description:
- This dataset contains images of UV cone nuclei near the retinal margin in live fish. These UV cones express a transgenic fluorescent reporter (that is nuclear-localized and photoconvertible). The most important images in this dataset are: Zoomed-out (1X magnification) images immediately after photoconversion Zoomed-out (1X magnification) images two to four days after photoconversion In the images immediately after photoconversion, we check if the row orientation rotates by more than a certain amount (10 degrees, 12 degrees, 14 degrees, etc.) at the retinal margin. If so, we call the region coinciding with this domain rotation an existing grain boundary. We, then, check where new Y-junctions are incorporated (by the time of later imaging) to see if they are preferentially incorporated near existing grain boundaries.
- Keyword:
- zebrafish cone mosaic, topological defects, tissue patterning, grain boundaries, and photoconversion
- Citation to related publication:
- Nunley, H., Nagashima, M., Martin, K., Gonzalez, A. L., Suzuki, S. C., Norton, D. A., Wong, R. O. L., Raymond, P. A., & Lubensky, D. K. (2020). Defect patterns on the curved surface of fish retinae suggest a mechanism of cone mosaic formation. PLOS Computational Biology, 16(12), e1008437. https://doi.org/10.1371/journal.pcbi.1008437 and Hayden Nunley, Mikiko Nagashima, Kamirah Martin, Alcides Lorenzo Gonzalez, Sachihiro C. Suzuki, Declan Norton, Rachel O. L. Wong, Pamela A. Raymond, David K. Lubensky. Defect patterns on the curved surface of fish retinae suggest mechanism of cone mosaic formation. bioRxiv 806679; doi: https://doi.org/10.1101/806679
- Discipline:
- Science
-
- Creator:
- Nunley, Hayden, Nagashima, Mikiko, Martin, Kamirah, Lorenzo Gonzalez, Alcides, Suzuki, Sachihiro C., Norton, Declan A., Wong, Rachel O. L., Raymond, Pamela A., and Lubensky, David K.
- Description:
- This dataset contains images of UV cone nuclei near the retinal margin in live zebrafish. These UV cone nuclei are labelled by transgenic expression of a fluorescent reporter (that is photoconvertible). The most important data are: 1. The zoomed-in (4X magnification) images of UV cone nuclei immediately after photoconversion 2. The zoomed-in (4X magnification) images of UV cone nuclei 2-4 days after photoconversion Also included is code for segmenting UV cone nuclei (both in image from immediately after photoconversion and in image from days later) and for shifting and rotating the two images to maximally align corresponding UV cone nuclei. After aligning corresponding UV cones, we compute triangulations over UV cone nuclei positions (for both images) and identify bonds that are common to both images. We use these common bonds to calculate the lattice vectors for the UV cone lattice.
- Keyword:
- zebrafish cone mosaic, tissue patterning, lattice vectors, and photoconversion
- Citation to related publication:
- Nunley, H., Nagashima, M., Martin, K., Gonzalez, A. L., Suzuki, S. C., Norton, D. A., Wong, R. O. L., Raymond, P. A., & Lubensky, D. K. (2020). Defect patterns on the curved surface of fish retinae suggest a mechanism of cone mosaic formation. PLOS Computational Biology, 16(12), e1008437. https://doi.org/10.1371/journal.pcbi.1008437 and Hayden Nunley, Mikiko Nagashima, Kamirah Martin, Alcides Lorenzo Gonzalez, Sachihiro C. Suzuki, Declan Norton, Rachel O. L. Wong, Pamela A. Raymond, David K. Lubensky. Defect patterns on the curved surface of fish retinae suggest mechanism of cone mosaic formation. bioRxiv 806679; doi: https://doi.org/10.1101/806679
- Discipline:
- Science
-
- Creator:
- Nunley, Hayden, Nagashima, Mikiko, Martin, Kamirah, Lorenzo Gonzalez, Alcides, Suzuki, Sachihiro C., Norton, Declan A., Wong, Rachel O. L., Raymond, Pamela A., and Lubensky, David K.
- Description:
- This dataset contains images of UV cone nuclei (labelled by transgenic expression of a photoconvertible fluorescent protein) near the retinal margin in live fish. The most important images in the dataset are the following: 1. Images (at 4X magnification) of UV cones immediately after photoconversion of a patch near the retinal margin 2. Images (at 4X magnification) of UV cones 2-4 days after photoconversion of a patch near the retinal margin Also, included is code for calculating triangulations (which connect UV cone nuclei which are nearest neighbors). This code allows us to check for motion of UV cones relative to each other between the time of photoconversion and subsequent imaging.
- Keyword:
- zebrafish cone mosaic, topological defects, tissue patterning, grain boundaries, photoconversion, and defect motion
- Citation to related publication:
- Nunley, H., Nagashima, M., Martin, K., Gonzalez, A. L., Suzuki, S. C., Norton, D. A., Wong, R. O. L., Raymond, P. A., & Lubensky, D. K. (2020). Defect patterns on the curved surface of fish retinae suggest a mechanism of cone mosaic formation. PLOS Computational Biology, 16(12), e1008437. https://doi.org/10.1371/journal.pcbi.1008437 and Hayden Nunley, Mikiko Nagashima, Kamirah Martin, Alcides Lorenzo Gonzalez, Sachihiro C. Suzuki, Declan Norton, Rachel O. L. Wong, Pamela A. Raymond, David K. Lubensky. Defect patterns on the curved surface of fish retinae suggest mechanism of cone mosaic formation. bioRxiv 806679; doi: https://doi.org/10.1101/806679
- Discipline:
- Science
-
- Creator:
- Nunley, Hayden, Nagashima, Mikiko, Martin, Kamirah, Lorenzo Gonzalez, Alcides, Suzuki, Sachihiro C., Norton, Declan A., Wong, Rachel O. L., Raymond, Pamela A., and Lubensky, David K.
- Description:
- This dataset is composed of eight flat-mounted (dissected and fixed) retinae from juvenile and adult zebrafish. Rows of UV cones have been traced in each retina; additionally, we have identified locations of Y-junctions (row insertions). Also included is MATLAB code for calculating which Y-junctions belong to grain boundaries. Please see the readme file for a description of included codes and image files.
- Keyword:
- zebrafish cone mosaic, topological defects, tissue patterning, and grain boundaries
- Citation to related publication:
- Nunley, H., Nagashima, M., Martin, K., Gonzalez, A. L., Suzuki, S. C., Norton, D. A., Wong, R. O. L., Raymond, P. A., & Lubensky, D. K. (2020). Defect patterns on the curved surface of fish retinae suggest a mechanism of cone mosaic formation. PLOS Computational Biology, 16(12), e1008437. https://doi.org/10.1371/journal.pcbi.1008437 and Hayden Nunley, Mikiko Nagashima, Kamirah Martin, Alcides Lorenzo Gonzalez, Sachihiro C. Suzuki, Declan Norton, Rachel O. L. Wong, Pamela A. Raymond, David K. Lubensky. Defect patterns on the curved surface of fish retinae suggest mechanism of cone mosaic formation. bioRxiv 806679; doi: https://doi.org/10.1101/806679
- Discipline:
- Science
-
- Creator:
- Wallace, Dylan M, Benyamini, Miri, Nason-Tomaszewski, Samuel R, Costello, Joseph T, Cubillos, Luis H, Mender, Matthew J, Temmar, Hisham, Willsey, Matthew S, Patil, Parag P, Chestek, Cynthia A, and Zacksenhouse, Miriam
- Description:
- This is data from Wallace, Benyamini et al., 2023, Journal of Neural Engineering. There are two sets of data included: 1. Neural features and error labels used to train error classifiers for each day used in the study 2. Trial data from an example experiment day (Monkey N, Day 6), with runs for offline calibration, online brain control, error monitoring, and error correction. The purpose of this study was to investigate the use of error signals in motor cortex to improve brain-machine interface (BMI) performance for control of two finger groups. All data is contained in .mat files, which can be opened using MATLAB or the Python SciPy library.
- Keyword:
- Brain-machine interface (BMI), Error detection, and Neural recording
- Citation to related publication:
- Wallace, D. M., Benyamini, M., Nason-Tomaszewski, S. R., Costello, J. T., Cubillos, L. H., Mender, M. J., Temmar, H., Willsey, M. S., Patil, P. G., Chestek, C. A., & Zacksenhouse, M. (2023). Error detection and correction in intracortical brain–machine interfaces controlling two finger groups. Journal of Neural Engineering, 20(4), 046037. https://doi.org/10.1088/1741-2552/acef95
- Discipline:
- Engineering, Science, and Health Sciences
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