Glaze Station Expansion and Building

https://scholarworks.moreheadstate.edu/student_scholarship_posters/1042/thumbnail.jp

Development and Training of a Neural Controller for Hind Leg Walking in a Dog Robot

Animals dynamically adapt to varying terrain and small perturbations with remarkable ease. These adaptations arise from complex interactions between the environment and biomechanical and neural components of the animal’s body and nervous system. Research into mammalian locomotion has resulted in several neural and neuro-mechanical models, some of which have been tested in simulation, but few “synthetic nervous systems” have been implemented in physical hardware models of animal systems. One reason is that the implementation into a physical system is not straightforward. For example, it is difficult to make robotic actuators and sensors that model those in the animal. Therefore, even if the sensorimotor circuits were known in great detail, those parameters would not be applicable and new parameter values must be found for the network in the robotic model of the animal. This manuscript demonstrates an automatic method for setting parameter values in a synthetic nervous system composed of non-spiking leaky integrator neuron models. This method works by first using a model of the system to determine required motor neuron activations to produce stable walking. Parameters in the neural system are then tuned systematically such that it produces similar activations to the desired pattern determined using expected sensory feedback. We demonstrate that the developed method successfully produces adaptive locomotion in the rear legs of a dog-like robot actuated by artificial muscles. Furthermore, the results support the validity of current models of mammalian locomotion. This research will serve as a basis for testing more complex locomotion controllers and for testing specific sensory pathways and biomechanical designs. Additionally, the developed method can be used to automatically adapt the neural controller for different mechanical designs such that it could be used to control different robotic systems

Growing and marketing Chinese chestnuts

"Chinese chestnut (Castanea mollissima) is an emerging tree nut crop for Missouri and throughout the eastern half of the United States. Chestnut cultivation for nut production in the Midwest and eastern U.S. is accelerating, with the number of farms increasing 57% between 2012 and 2017, and more than 600 orchards reaching bearing age (USDA, 2018)."--Page 1.by Ron Revord (Ph.D., Assistant Research Professor, UMCA), Michael Gold (Ph.D., Associate Director, UMCA), Nicholas Meier (Ph.D., Senior Research Specialist, UMCA), J. Bryan Webber (M.S., Senior Research Specialist, UMCA), Ken Hunt (Ph.D., Retired, UMCA), and Michele Warmund (Ph.D., Professor of Horticulture, MU Division of Plant Sciences)Taken from Extension website: Reviewed: August 2022

Biomechanical and Sensory Feedback Regularize the Behavior of Different Locomotor Central Pattern Generators

This work presents an in-depth numerical investigation into a hypothesized two-layer central pattern generator (CPG) that controls mammalian walking and how different parameter choices might affect the stepping of a simulated neuromechanical model. Particular attention is paid to the functional role of features that have not received a great deal of attention in previous work: the weak cross-excitatory connectivity within the rhythm generator and the synapse strength between the two layers. Sensitivity evaluations of deafferented CPG models and the combined neuromechanical model are performed. Locomotion frequency is increased in two different ways for both models to investigate whether the model’s stability can be predicted by trends in the CPG’s phase response curves (PRCs). Our results show that the weak cross-excitatory connection can make the CPG more sensitive to perturbations and that increasing the synaptic strength between the two layers results in a trade-off between forced phase locking and the amount of phase delay that can exist between the two layers. Additionally, although the models exhibit these differences in behavior when disconnected from the biomechanical model, these differences seem to disappear with the full neuromechanical model and result in similar behavior despite a variety of parameter combinations. This indicates that the neural variables do not have to be fixed precisely for stable walking; the biomechanical entrainment and sensory feedback may cancel out the strengths of excitatory connectivity in the neural circuit and play a critical role in shaping locomotor behavior. Our results support the importance of including biomechanical models in the development of computational neuroscience models that control mammalian locomotion

The SDSS-2MASS-WISE Ten Dimensional Stellar Color Locus

We present the fiducial main sequence stellar locus traced by 10 photometric colors observed by SDSS, 2MASS, and WISE. Median colors are determined using 1,052,793 stars with r-band extinction less than 0.125. We use this locus to measure the dust extinction curve relative to the r-band, which is consistent with previous measurements in the SDSS and 2MASS bands. The WISE band extinction coefficients are larger than predicted by standard extinction models. Using 13 lines of sight, we find variations in the extinction curve in H, Ks, and WISE bandpasses. Relative extinction decreases towards Galactic anti-center, in agreement with prior studies. Relative extinction increases with Galactic latitude, in contrast to previous observations. This indicates a universal mid-IR extinction law does not exist due to variations in dust grain size and chemistry with Galactocentric position. A preliminary search for outliers due to warm circumstellar dust is also presented, using stars with high signal-to-noise in the W3-band. We find 199 such outliers, identified by excess emission in Ks-W3. Inspection of SDSS images for these outliers reveals a large number of contaminants due to nearby galaxies. Six sources appear to be genuine dust candidates, yielding a fraction of systems with infrared excess of 0.12$\pm$0.05%.Comment: 11 pages, 10 figures, MNRAS Accepted. Tables 1 and 2 available online: https://github.com/jradavenport/wise_locu

MOST Observations of the Flare Star AD Leo

We present continuous, high-precision photometric monitoring data with 1 minute cadence of the dM3e flare star AD Leo with the {\it MOST} satellite. We observed 19 flares in 5.8 days, and find a flare frequency distribution that is similar to previous studies. The light curve reveals a sinusoidal modulation with period of $2.23^{+0.36}_{-0.27}$ days that we attribute to the rotation of a stellar spot rotating into and out of view. We see no correlation between the occurrence of flares and rotational phase, indicating that there may be many spots distributed at different longitudes, or possibly that the modulation is caused by varying surface coverage of a large polar spot that is viewed nearly pole-on. The data show no correlation between flare energy and the time since the previous flare. We use these results to reject a simple model in which all magnetic energy is stored in one active region and released only during flares.Comment: 20 Pages, 8 Figures, PASP Accepte