62021 research outputs found
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Identifying Escaped Members of Young Open Clusters
Full text linkIdentifying escaped members of open clusters provides insight into how stars join the field, but this task is challenging because escaped members are vastly outnumbered by field stars. I investigated the effect of including signs of youth in membership probability calculations to determine whether this information could identify escaped members. I focused on two young clusters: α Persei, a high proper motion cluster, and IC 4665, a low proper motion cluster. Using Hierarchical Density-Based Spatial Clustering of Applications with Noise, I calculated membership probabilities including only proper motion and distance information, then repeated the calculation including color and magnitude information. In α Persei, I investigated how membership probability correlated with Hα emission with data from a 2023 survey conducted at MDM and calculated updated membership probabilities. Adding color and magnitude information promoted many low-mass stars to membership in IC 4665, but fewer stars were promoted in α Persei because PD and PDCM membership probabilities were correlated in α Persei. 85% of likely α Persei members had Hα emission, so assuming 25% of field stars are Hα emitters, adding this information raises membership probabilities. This shows adding signs of youth can identify escaped members of these clusters.No embargoAcademic Major: Astronomy and AstrophysicsAcademic Major: Physic
The Biochemical Characterization of Plastin-3 (PLS3) variants linked to Congenital Diaphragmatic Hernia (CDH)
No full textCongenital Diaphragmatic Hernia (CDH) is a severe congenital disease characterized by an incomplete formation of the diaphragmatic septum leading to mis-localization of the abdominal organs (e.g., the liver, stomach, and bowel) to the chest cavity. Through a combination of clinical and genetic analysis, eight novel mutations in plastin-3 (PLS3), an actin-binding and bundling protein, were linked to CDH. PLS3 has two actin-binding domains, ABD1 and ABD2, which determine how the protein binds and bundles actin filaments (F-actin). The successful binding and bundling of F-actin are essential for the cell's normal functions. If the ability of PLS3 to bind and/or bundle F-actin is impaired by pathological mutations, the cell’s morphological features and critical functions will be severely altered. The CDH-linked PLS3 mutations studied in this project are localized at different domains of the protein, and their effects on the protein structure and function are characterized through high- and low-speed co-sedimentation assays, fluorescence anisotropy (FA), and differential scanning fluorimetry (DSF). All mutated plastins displayed a high degree of destabilization, when characterized through DSF, and significantly increased F-actin bundling activity, compared to wild-type (WT) protein.Thomas J Byers Memorial Scholarship, The Ohio State University Molecular Genetics DepartmentArts and Sciences Undergraduate Research Scholarship, The Ohio State University Arts and Sciences Honors CommitteeA three-year embargo was granted for this item.Academic Major: Molecular Genetic
Geometrical Effects on Non-spherical Extended Systems in Strong Laser Fields
Full text linkThis work explores how cluster geometry affects ionization in strong laser fields. Using molecular dynamics simulations, spheroidal argon clusters of equal volume but varying aspect ratios were exposed to near-infrared laser pulses (800–2000 nm). Prolate clusters consistently showed higher ion energies and ionization per atom, especially when the laser polarization aligned with the semi-major axis. A peak in energy absorption at 1400 nm suggests a crossover between dipole-enhanced ionization and plasma resonance effects. These results reveal that target geometry and orientation strongly influence laser-cluster interactions, with potential applications in structural probing and laser-driven control of anisotropic systems.No embargoAcademic Major: Physic
Design and Implementation of a Motion Control Architecture for WormPicker 2.0 Robotic System
Full text linkGenetic research relies on model organisms like C. elegans, microscopic nematodes valued for their genetic simplicity and short lifecycles. Researchers must physically transfer these worms between experimental conditions, a process traditionally performed manually with wire picks - creating significant bottlenecks in experimental throughput. Automation is critically needed for high-throughput studies. An integrated system combining a 6-axis robotic arm, motorized microscope, and AI-driven machine vision has been developed to address this challenge, known as WormPicker 2.0. This research presents the design and implementation of a comprehensive motion control architecture for WormPicker 2.0's Yaskawa GP4 robotic arm, enabling autonomous execution of complex protocols.
The developed software architecture follows a layered design pattern that transforms high-level experimental commands into precise robotic movements. At its core, the system employs ROS2 and MoveIt2 frameworks for motion planning and execution. It features a modular structure that separates concerns across five layers: interface, command processing, task generation, motion planning, and execution.
Key technical contributions include a command parser that processes multi-parameter instructions. The system also incorporates a task generation framework that dynamically creates motion sequences from workspace configurations. Additionally, it features a calibration system that maps between digital design models and physical workspace coordinates, along with multiple interfaces for remote network access and direct command-line control.
This motion control system enables WormPicker 2.0 to achieve a transfer rate of 13 animals per minute (4 times improvement over previous implementations) while maintaining precise navigation across 250 plates in a compact footprint. By automating worm manipulation, this work significantly enhances research capabilities for genetic screens, aging assays, drug response studies, and behavioral analysis. The modular software architecture provides a foundation for future enhancements, moving closer to a general-purpose tool for C. elegans laboratories that dramatically increases experimental throughput and reproducibility.No embargoAcademic Major: Biomedical Engineerin
Effect of Quantization on Data-Driven Model Predictive Control of Quadcopters
Full text linkThe increasing reliance on autonomy in aerospace systems has created high demand for robust and computationally efficient control methods. Unmanned aerial vehicles (UAVs), such as drones, are among the most common autonomous systems due to their versatility and widespread applications. However, these drones can be heavily affected by the environmental conditions, e.g., wind gusts, which are difficult to model. Therefore, data-driven system identification and subsequent controller design has become increasingly important in UAV operation. Due to their limited onboard computation power and memory, small UAVs are not always able to perform the system identification on board, and they need to communicate the acquired data to an edge server for system identification. This communication is done via a band-limited wireless channel where the data needs to be quantized to make efficient use of the available bandwidth. Quantization, the process of discretizing continuous-valued data into a smaller subset of discrete values, addresses these constraints by reducing the the bandwidth required to communicate the data and trading precision for efficiency. While theoretical studies have shown some degradation in system identification and control performance due to data quantization, its effects in experimental UAV settings remain minimally explored. This thesis investigates the effect of dither quantization to the Extended Dynamic Mode Decomposition (EDMD) method, a Koopman operator-based method for data-driven system identification and the subsequent Model Predictive Control (MPC) framework. The goal is to characterize and quantify the performance loss during experimental testing. The methodology of this research includes MATLAB simulations, software-in-the-loop simulations in Gazebo, and hardware validation using the PX4-Starling Drone Autonomy Developer Kit. These testing phases aim to determine the effects of quantization on model accuracy, control fidelity, and real-world UAV flight performance. Results from MATLAB simulations indicate that higher levels of quantization degrade both system identification and subsequent MPC performance. Hardware validation provides key information about the crosstalk between quantization and UAV dynamics, revealing practical challenges and opportunities for improvement. By bridging the gap between theory and application, this research advances the understanding of how communication bandwidth affects resource-limited data-driven MPC for multirotor UAVs. The findings contribute to the development of efficient, data-driven control strategies with broader implications in sensor fusion algorithms, real-time embedded systems, and wireless communications.The Ohio State University College of Engineering Undergraduate Research ScholarshipSystems, Optimization, and Autonomous Robotics Laboratory (SOAR)No embargoAcademic Major: Aerospace Engineerin
Investigating domain function and protein interactions of the ELMOD family proteins involved in pollen aperture formation in Arabidopsis
No full textIn flowering plants, the ancient eukaryotic Engulfment and Motility Domain (ELMOD) genes play a role in the formation of pollen apertures. Apertures are hole-like structures on the pollen surface that develop at distinct plasma membrane domains and lack pollen wall exine. Apertures are conserved within a plant species, yet quite diverse across species. Openings provided by the apertures can allow pollen tubes that carry sperm cells to exit from pollen grains and, in some plant species, loss of apertures leads to male sterility. Two of the Arabidopsis thaliana ELMOD proteins–ELMOD_B (also known as MCR) and ELMOD_A–control the number of apertures while a third protein, ELMOD_E, causes changes in aperture shape when mis-expressed in developing pollen. However, the biochemical function of ELMOD proteins in plants has yet to be deciphered. We have investigated the importance of the ELMOD protein domains by deleting and swapping domains of the ELMOD genes. We demonstrate that 1) all three protein domains in the Arabidopsis ELMODs are essential for these proteins’ function; 2) the C-terminus and the putative GAP region are important for nuclear enrichment; and 3) the N-terminus of ELMOD_E is responsible for its distinct effect on aperture formation while the N-terminus of MCR is important for its function. To identify interactors of the ELMOD proteins, we have also performed protein-protein interaction assays. So far, these assays have discovered weak protein interactions and suggested that plant ELMOD proteins may have biochemical activity different from their mammalian counterparts.Thomas Byers Memorial Scholarship, Ohio State University Department of Molecular GeneticsNSF grant MCB-1817836NSF grant MCB-2240972A five-year embargo was granted for this item.Academic Major: Molecular Genetic
Effects of Turbidity on Reaction Distance of Smallmouth Bass to Fishing Lures of Different Colors
No full textLake Erie is regularly experiencing massive changes in water quality that may affect commercially and recreationally important fish populations. Increases in turbidity result from summer algal blooms and meteorological events such as storms and wave movement that stir up sediments from the lake bottom. Algal and sedimentary turbidity both decrease light penetration, but algal turbidity leaves water with a green coloration, while sedimentary turbidity has no substantial effect on water coloration in Lake Erie. Smallmouth Bass (Micropterus dolomieu) are an economically important species in the Lake Erie sport fishing industry and are visual predators. Turbidity increases can substantially impact visual ability in Smallmouth Bass, potentially impacting their interactions with fishing lures. I studied the effects of algal and sedimentary turbidity on the reaction distance (i.e., the distance at which a fish detects an object) of Smallmouth Bass to two common lure colors, black and gold. I conducted experiments using wild-caught Smallmouth Bass in a controlled laboratory setting at Ohio State University’s F.T. Stone Laboratory in the Western Basin of Lake Erie. When tested under algal turbidity fish had the shortest reaction distance, followed closely by the sedimentary turbidity treatment, meaning they had to be closer to the lure in order to detect it. Reaction distance relative to the clear control treatment was reduced 41.4% under the sedimentary turbidity treatment and 58.3% under the algal turbidity treatment. There was no difference in reaction distance related to black or gold lure color. This research suggests that both algal and sedimentary turbidity significantly reduces the effectiveness of fishing lures, in particular during algal blooms.Ohio Sea GrantCollege of Food, Agriculture, and Environmental ScienceSchool of Environment and Natural ResourcesA one-year embargo was granted for this item.Academic Major: Environmental Scienc
The Machine in the Mind: AI to Support Empathic Deliberation Within
Full text linkEmpathy is essential to deliberative democracy, yet rising partisan animosity places it under increasing strain, and traditional methods to foster empathy remain difficult to scale. Meanwhile, artificial intelligence (AI) shows promise as a tool to support and scale deliberation, but its potential to enhance empathic “deliberation within” remains largely unexplored. This study tests whether AI can enhance citizens’ empathy toward policy opponents using a mixed experimental design with 378 participants. Each participant completed a standard perspective-taking control task and one of two AI-supported interventions powered by OpenAI’s GPT-4. Empathy scores were compared across conditions using within-subjects and between-subjects analyses. Contrary to expectations, the AI interventions did not enhance empathy beyond traditional perspective-taking instructions. Moreover, participants who engaged with AI first reported lower empathy in the subsequent control task, raising concerns that AI might undermine the internal, imaginative processes central to deliberation within. Further research is needed to understand how AI can be integrated into the deliberative system in ways that preserve, rather than diminish, citizens’ capacities for empathy and internal reflection.No embargoAcademic Major: Political ScienceAcademic Major: Economic
Patient Sense: Rhetorical Body Work in the Age of Technology
No full textIntroduction: The new healthcare landscape -- Rhetorical body work -- A feeling for the robot : embodying empathy in nursing simulations -- More than a massage : body work as boundary-work in a physical therapy lab -- Reaching through the screen : mediated body work in a virtual intensive care unit -- Conclusion: Body matters for the future of healthcare and technologyItem embargoed for three year