23671 research outputs found
Sort by
Department of Dental Hygiene Class of 1999
No full textFirst row (left to right): Barbara Gonzalez, RDH, MHS, Clinic Instructor; Lourdes Vasquez, RDH, MS, Assistant Professor; Patty Seery, RDH, MHS, Clinic Coordinator; Ron Neugent, Supervising Dentist; Denise Maseman, RDH, MS, Assistant Professor/Interim Chairperson; Diane E. Huntley, RDH, PhD, Associate Professor; Pamela Bumpurs, RDH, MHS, Clinical Educator; Mary Casey, Clinic ManagerSecond row (left to right): Cheree Brinlee, President; Tasha Farrar, Vice President; Mitzi Maxson, SADHA President; Jill Angst, Class LiaisonThird row (left to right): Angela Centlivre, Jeri Dunlap, Kay Carlton, Treasurer/Secretary; James Davis, SADHA Secretary/Treasurer; Anna Dunlavy, Jessica FrameFourth row (left to right): Brenda Friestad, Kristi Goodman, Gail Gross, Amy Hampton, Kendra Harper, Amy Hollingsworth, Jamie Hubbard, Tonya Jordan, Kimberly KissackFifth row (left to right): Rashelle Lindteigen, Michelle Martinez, Marsha Moorman, Vincent Nguyen, Monica Rogers, Shawn Rotolo-Utz, Tristin Rudd, Holly Smith, Mary WhiteDigitized by University Libraries' Technical Services Institutional Repository & Digitization group.Personal and non-profit use only
Multi-agent reinforcement learning approach for robot teaming in Mars exploration
No full textPoster project completed at College of Engineering, School of Computing.
Presented at the Kansas Undergraduate Student Research Day at the Capitol, Topeka, KS, February 26, 2025.
Sponsored by Undergraduate Research and Creative Activity Hub, Dorothy and Bill Cohen Honors College.Mars exploration is crucial for understanding the planet's potential to support life, its climate and geological history, and for preparing future human missions. However, Mars exploration poses challenges due to constrained communication capabilities. This research proposed a MARL-based method for autonomous path planning for robot-robot teaming. Group-oriented Multi-Agent Reinforcement Learning (GoMARL) is commonly employed for robot-robot teaming. However, this method faces limitations regarding computational complexity as the number of agents increases. The proposed approach designs a hierarchical structure to mitigate this complexity and enhance scalability. The proposed MARL structure organizes agents into multiple layers, where higher-level agents manage strategic decisions like group formation while lower-level agents focus on tactical execution like navigation, thereby reducing computational complexity and improving scalability for large teams of robots. Research ongoing. The experimental environment is set up in ROS2 to simulate Martian conditions. The preliminary reinforcement learning model showed promising results. The proposed method allows multiple robots to navigate autonomously with limited human interaction under extreme circumstances, like Mars. Kansas is highly prone to disasters like Tornados, and the proposed method can contribute to post-disaster rescue
A physics informed machine learning framework for state-of health assessment of lithium-ion batteries in resilient infrastructure applications
No full textPoster project completed at Wichita State University, Department of Electrical and Computer EngineeringPresented at the 22nd Annual Capitol Graduate Research Summit, Topeka, KS, March 25, 2025.Lithium-ion batteries (LIBs) are widely used as energy sources in transportation and grid energy storage due to their high energy density, efficiency, and long lifespan. For instance, in regions like Kansas, which are prone to severe weather events such as tornadoes, LIBs offer a feasible solution for backup power during outages, playing an essential role in maintaining essential services and supporting resilient infrastructure. However, LIBs degrade over time, and if their degradation mechanisms are not properly monitored and managed, they can lead to operational failures or thermal runaway. State of health (SOH) assessment is crucial for monitoring battery performance. However, traditional methods that rely solely on capacity changes are insufficient due to the complexity of LIBs degradation. This work presents a framework for SOH assessment using differential voltage analysis (DVA) and machine learning. Commercial LIBs were tested under various charge/discharge rates, depths of discharge (DOD), and temperatures. Reference performance tests (RPTs) were conducted until end-of-life (EOL), and DVA extracted significant parameters, including internal resistance, active mass loss, and electrode stoichiometries. Additionally, to predict EOL, a Random Forest machine learning model was implemented on a Raspberry Pi computer, to enable real-time monitoring and remote data transmission to a cloud service for a centralized disaster control agency. Cells cycled at 100% DOD experienced greater cathode material loss. The Random Forest model processed data in about 2.9 seconds and achieved an accuracy of 86.67%. This accuracy demonstrates the potential of the low-cost model to facilitate remote monitoring of SOH and for secure power supply in extreme conditions
Quantitative EEG metrics for determining HD-tDCS induced alteration of brain activity in stroke rehabilitation
No full textClick on the DOI link to access this article at the publishers website (may not be free).High-definition transcranial direct current stimulation (HD-tDCS) is a promising approach for stroke rehabilitation, which may induce functional changes in the cortical sensorimotor areas to facilitate movement recovery. However, it lacks an objective measure that can indicate the effect of HD-tDCS on alteration of brain activity. Quantitative electroencephalography (qEEG) has shown promising results as an indicator of post-stroke functional recovery. Therefore, this study aims to determine whether qEEG metrics could serve as quantitative measures to assess alteration in brain activity induced by HD-tDCS. Resting state EEG was collected from stroke participants before and after (1) anodal HD-tDCS of the lesioned hemisphere, (2) cathodal stimulation of the non-lesioned hemisphere, and (3) sham. The average power spectrum was calculated using the Fast Fourier Transform for frequency bands alpha, beta, delta, and theta. In addition, delta-alpha ratio (DAR), Delta-alpha-beta-theta ratio (DTABR), and directional brain symmetry index (BSI) were also evaluated. We found that both anodal and cathodal stimulation significantly decreased the DAR and BSI over various frequency bands, which are associated with reduced motor impairments and improved nerve conduction velocity from the brain to muscles. This result indicates that qEEG metrics DAR and BSI could be quantitative indicators to assess alteration of brain activity induced by HD-tDCS in stroke rehabilitation. This would allow future development of EEG-based neurofeedback system to guide and evaluate the effect of HD-tDCS on improving movement-related brain function in stroke. © The Author(s) 2025National Institute of General Medical Sciences, NIGMS; American Heart Association, AHA, (932980); American Heart Association, AHA; Oklahoma Shared Clinical and Translational Resources, (U54GM104938); National Science Foundation, NSF, (NSF 2401215); National Science Foundation, NSFThe authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The data collection of this work was supported by the American Heart Association (932980) and Oklahoma Shared Clinical and Translational Resources (U54GM104938) with an Institutional Development Award from National Institute of General Medical Sciences. The data analysis of this work was supported by National Science Foundation CAREER award (NSF 2401215)
Health care access for Mayan communities in Kansas
No full textShowstack, R., Rangel, R., & Francisco, M. (2025). Health care access for Mayan communities in Kansas. In Arnold, L., Avera, E., Corwin, I., & Guzmán, J. (Eds.), Language and health in action. Oxford University Press
Protein-based nanoparticles for antimicrobial and cancer therapy: implications for public health
No full textThis is an open access article under the CC BY license.This review discusses the growing potential of protein-based nanoparticles (PBNPs) in antimicrobial and cancer therapies, emphasizing their mechanisms of action, applications, and future prospects. In antimicrobial therapy, PBNPs exhibit several mechanisms of action, including disruption of microbial membranes, enhanced antibiotic delivery, immune modulation, and biofilm disruption. Protein nanoparticles like albumin, lactoferrin, gelatin, and peptide-based variants enhance the efficacy of antibiotics, offering targeted approaches to combat multidrug-resistant pathogens. Their ability to improve drug localization and enhance microbial eradication represents a significant advancement in infectious disease management. In cancer therapy, PBNPs facilitate targeted drug delivery, controlled release, tumor microenvironment modulation, and photothermal and photodynamic therapies. Nanoparticles such as Abraxane® and engineered ferritin nanocages are at the forefront of cancer treatment, enhancing the precision and effectiveness of chemotherapy while minimizing adverse effects. Additionally, silk fibroin nanoparticles are being explored for their biodegradability and targeting capabilities. Despite their promise, challenges remain, including the scalability of production, long-term safety concerns, regulatory approval processes, and environmental impact. Addressing these issues through rigorous research and innovation is crucial for integrating PBNPs into mainstream therapeutic practices. PBNPs offer transformative solutions in both antimicrobial and cancer therapies, with significant implications for improving public health outcomes globally. © 2025 The Royal Society of Chemistry
Forward Together: A monthly newsletter, April 2025
No full textWichita Biomedical Campus rising as a new force in Kansas health care -- (Forward Together podcast): April's 'Forward Together' podcast is all about the Wichita Biomedical Campus -- Wichita State names Dr. Sarah Beth Estes as new dean of Fairmount College of Liberal Arts and Sciences -- Wichita State names Dr. Sarah Beth Estes as new dean of Fairmount College of Liberal Arts and Sciences -- Spirit Squad competes at NCA/NDA Nationals, Shocker cheer finishes first -- Shocker women’s bowling competes in Final Four in first NCAA season Wichita State biology professor elected as prestigious AAAS Fellow -- Wichita State dedicates tree in honor of former dean of students, Dr. Rhatigan, in view of building namesake -- (Featured student research): Lille Nightingale, dancing with wildebeests -- Sejun Moon, exploring Mars -- Daniel Reichart, exploring the cosmos -- Anna Brake, bridging health care gaps -- Wichita State students learn varied skills as part of Athletics creatives team -- Shocker golf teams see AAC All-Conference honors, runner-up in championship -- Meet the 2025-26 class of Shocker Pride Scholar
Power distribution system restoration during extreme events: Equality or equity?
No full textPoster project completed at Wichita State University, Department of Electrical and Computer EngineeringPresented at the 22nd Annual Capitol Graduate Research Summit, Topeka, KS, March 25, 2025.22nd Capitol Graduate Research Summit (CGRS) -- University AwardExtreme events such as natural disasters, extreme weather and man-made attacks have the potential to disrupt the operation of power grid and in turn impact the society at large. Owing to the recent increase of these events which lead to sustained power outages, power system planners and policy makers are continuously interested in developing new and efficient post restoration schemes to improve grid resiliency. With the increased emergence of distributed energy resources (DERs) such as Solar PV plants and consumer owned diesel generators especially in the state of Kansas and worldwide at present, restoration can be acquired using these resources by forming possible microgrids and supplying critical loads.
However, the existence of different types of customers with varying social equity factors in a power distribution system urges the system operators to consider equitable load restoration. In current restoration schemes, these equity variations are less valued, resulting the people in rural areas or financially marginalized communities to have longer outage durations and limited access to resources. Taking this factor into account, this work proposes a method for power system restoration considering both social equity and consumer priority. The method is tested using actual data in a rural city in Kansas which is publicly available, and the results show both the significances of priority and equity-based power distribution system restoration. Further, the developed restoration algorithm provides valuable insights to system operators for faster restoration to communities with varying vulnerabilities which is frequent in states like Kansas
Luna AI navigation system for NASA Spacesuit User Interface Technologies for Students (SUITS) challenge
No full textPresented to the 24th Undergraduate Research and Creative Activity Forum (URCAF) held in Woolsey Hall, Wichita State University, April 25, 2025.Wichita State's CosmoShox team is an interdisciplinary group of undergraduate and graduate students working together on the NASA SUITS (Spacesuit User Interface Technologies for Students) design challenge. A major goal of the challenge is tasking schools to work together to ensure design interoperability since many of NASA's Artemis missions involve international collaboration. For 2025, the Wichita State CosmoShox team has been paired with the Columbia University Lunar Lions. The Lunar Lions are working on a spacesuit augmented reality display while the CosmoShox are designing the user interface and the Lunar User Navigation and tasking Assistant (LUNA) AI for a virtual pressurized rover. LUNA serves as the central processing unit, managing telemetry data, best path navigation, consumable resources, and updates shown in the user interface (UI) for the virtual pressurized rover (PR). The CosmoShox team has decided to work in Unreal Engine 5.5 since NASA's Digital Lunar Exploration Sites Unreal Simulation Tool (DUST) also uses Unreal Engine. As part of the design challenge, we are evaluating different UI configurations to test the usability and AI performance of LUNA which includes incorporating certain fonts and colors to enhance readability. A series of IRB-approved Human-In-The-Loop tests will coincide with our two-week design sprints as we develop LUNA and our User Interface in Unreal Engine. The evaluator pool is open to male and female participants, aged 20-40, who are currently physically active to best replicate the physical state of astronauts using the software. Feedback from design evaluators will be implemented in design sprints to ensure optimum usability. Open XR Lab faculty oversees XR development and evaluates psychological safety and performance outcomes linked to Agile product management processes. The CID design champions a holistic approach that builds professional skills for the student cohort