Boles, A., & Pluijm, B. van der. (2020). Locally Derived, Meteoric Fluid Infiltration Was Responsible for Widespread Late Paleozoic Illite Authigenesis in the Appalachian Basin. Tectonics, 39(7), e2020TC006137. https://doi.org/10.1029/2020TC006137
These datasets support the findings of Townsend et al. (2020). In this article, we quantify rock strength using two novel applications of hillslope stability models, resulting in estimates of cohesive and frictional strength at the spatial scale of small watersheds. We compare these results against the direct-shear test dataset here for validation of our approach. We find that cohesive strength is dependent on the original burial depth of the sedimentary rocks studied here. The low-temperature thermochronometry data was used to assess the magnitude of burial.
The object of this project is to provide researchers and students with a tool to allow them to develop an intuitive understanding of singular vectors and singular values. 2x2 matrices A with real entries map circles to ellipses; in particular, unit circles centered at the origin to ellipses centered at the origin. It is known that the points on the ellipse farthest from the origin correspond to the singular vectors of A. Users can use the GUI to enter matrices of their choice and explore to visually self-determine the singular vectors/values.
We sampled the near-Earth plasma sheet using data from the NASA Time History of Events and Macroscale Interactions During Substorms mission. For the observations of the plasma sheet, we used corresponding interplanetary observations using the OMNI database. We used these data to develop a data-driven model that predicts plasma sheet electron flux from upstream solar wind variations. The model output data are included in this work, along with code for analyzing the model performance and producing figures used in the related publication. and Data files are included in hdf5 and Python pickle binary formats; scripts included are set up for use of Python 3 to access and process the pickle binary format data.
Swiger, B. M., Liemohn, M. W., & Ganushkina, N. Y. (2020). Improvement of Plasma Sheet Neural Network Accuracy With Inclusion of Physical Information. Frontiers in Astronomy and Space Sciences, 7. https://doi.org/10.3389/fspas.2020.00042
Micron-scale robots require systems that can morph into arbitrary target configurations controlled by external agents such as heat, light, electricity, and chemical environment. Achieving this behavior using conventional approaches is challenging because the available materials at these scales are not programmable like their macroscopic counterparts. To overcome this challenge, we propose a design strategy to make a robotic machine that is both programmable and compatible with colloidal-scale physics. Our strategy uses motors in the form of active colloidal particles that constantly propel forward. We sequence these motors end-to-end in a closed chain forming a two-dimensional loop that folds under its mechanical constraints. We encode the target loop shape and its motion by regulating six design parameters, each scale-invariant and achievable at the colloidal scale. The research dataset includes simulation, visualization, and analysis scripts and results generated for the 2D chain loops of self-propelling particles.
File Description:, -- arrows_folding - Contains the data for the folded chain loop shapes resembling an arrowhead., -- bending_vs_variation - Contains the data to study the stability of a particular shape in simulations as one of the segments of the shape bends and/or the distribution of propulsion on it varies., -- curved_triangle - Contains the data to study motion and bending of a triangle shape made using chain loop., -- example_shapes - Contains data for various examples of shapes that can be generated by designing the chain loops., -- nskT_vs_fakT - Contains the data for a specific shape to study the effect of scaling up the number of particles (governed by ns) and the propulsion (governed by fa) in its chain., -- stability - Contains the data and theoretical model (stability.py) to study the stability of the six different shapes., -- tuning_design_forM - Contains the data for sequential tuning the design parameters to fold the shape "M" as described in the corresponding publication., and -- two_neighboring_cds_segments_ - Contains the data to study a system of two neighboring chain segments with respect to different parameters discussed in the publication.
These data, survey instruments (including informed consent) and analysis scripts come from Carol Moser's dissertation titled, Impulse Buying: Designing for Self-Control with E-commerce.
The data is comprised of 22 directories, each housing a .hdf file of the X-ray projections recorded during solidification of Al-Si-Cu-Sr. The flat and dark projections are also included as two separate .hdf files (total file count: 24). The raw data file is in .hdf format and can be reconstructed into .tiff, e.g., by using the TomoPy toolbox in Python.
Wang, Y., Gao, J., Ren, Y., De Andrade, V., & Shahani, A. J. (2020). Formation of a Three-Phase Spiral Structure Due to Competitive Growth of a Peritectic Phase with a Metastable Eutectic. JOM, 72(8), 2965–2973. https://doi.org/10.1007/s11837-020-04237-x
The editorial decision process for the Journal of Geophysics Research Space Physics is assisted by over 1,000 scientists every year, providing over 3,000 reviews per year. These statistics are presented for the years 2013 through 2018, showing some fluctuations but, overall, consistency in the response of the space physics research community to requests to serve as manuscript reviewers. Over half of these reviews are submitted on time, and the average time to review actually dropped as the load increased. This is greatly appreciated and the community is to be commended and thanked for their willingness to help make this journal thrive and remain a premiere publication in the field.
Liemohn, M. W. (2020). Editorial: Multiyear analysis of JGR Space Physics reviewing statistics. Journal of Geophysical Research Space Physics, 125, e2019JA027719. https://doi.org/10.1029/2019JA027719
This repository includes test instances of infinite-horizon Markov decision processes with multiple models of parameters (i.e., "Multi-model Markov decision processes"). We generated each test instance in the dataset using a Python script. The test instances can be read in using the provided C++ and Python script. See the README for details.
Crouzon FGFR2-C342Y/+ and wild type littermate pups on a C57BL/6 congenic background were injected with lentivirus expressing recombinant TNAP enzyme or phosphate buffered saline shortly after birth. Mice were euthanized 3 weeks after birth for analyses.
Nam, H. K., Vesela, I., Schutte, S. D., & Hatch, N. E. (2020). Viral delivery of tissue nonspecific alkaline phosphatase diminishes craniosynostosis in one of two FGFR2C342Y/+ mouse models of Crouzon syndrome. PLOS ONE, 15(5), e0234073. https://doi.org/10.1371/journal.pone.0234073
