Integrating motion physics knowledge into deep learning for accurate Parkinson's disease classification

Presented to the 21st Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at the Rhatigan Student Center, Wichita State University, April 11, 2025.Research completed in the School of Computing, College of Engineering.Parkinson’s Disease (PD) is a progressive neurological disorder characterized by a variety of motor and non-motor symptoms, significantly impacting patients’ quality of life. Early and accurate detection of PD is crucial for timely interventions and improved patient outcomes. Recent advancements have highlighted the potential of time-series data collected from Inertial Measurement Unit (IMU) sensors during patient-performed activities as a valuable source for PD detection. Previous studies have employed diverse data collection methodologies, ranging from single-device setups attached to the patient’s waist to multi-sensor configurations attached to various body segments. However, these approaches often face limitations due to missing modalities or complex sensor setups. To address these challenges, this research proposes a novel hybrid framework for PD detection and classification. The designed Physics-Informed Neural Network (PINN) model integrates kinematics formulas with neural networks to approximate kinematic parameters such as relative rotational angles between body segments. Then, the proposed Bayesian Neural Network (BNN) model classifies the severities of PD affected levels. The proposed method also focuses on data collected using IMU sensors strategically placed on the upper body—specifically the lower and upper arms on both sides, as well as the chest—to achieve simplified yet efficient data acquisition. Given the limited availability of clinical datasets, this study incorporates an extensive data augmentation pipeline. Techniques such as noise injection, Fourier-based transformations, time-warping, and scaling are applied to enrich the dataset, improving the generalization and robustness of the neural network models. By leveraging IMU sensor data captured during multiple activity performances, this work developed a scalable and practical solution for PD detection that reduces dependency on complex multi-modal systems. The proposed hybrid framework not only improves classification accuracy but also addresses critical challenges in current research, paving the way for more accessible and reliable PD monitoring solutions.Graduate School, Academic Affairs, University Librarie

Biomaterial nanofiber scaffolds for neural regeneration

Click on the DOI link to access this article at the publishers website (may not be free).Nanofiber scaffolds, with their promising applications in tissue regeneration and tissue engineering, are at the forefront of biomedical engineering. Their structure mirrors the extracellular matrix (ECM) morphology, allows for grafting in various damaged tissues, and facilitates tissue regeneration. Derived from biodegradable and biocompatible materials, these scaffolds exhibit low cytotoxicity to the cells. Electrospinning techniques can produce fibers with diameters ranging from tens to hundreds of nanometers, enhancing their adaptability in different tissue types and their customization in tissue engineering. A fascinating application of nanofiber scaffolds is in the treatment of neurological disorders such as traumatic brain injury (TBI), spinal cord injury (SCI), and Parkinson's disease. These scaffolds, known for their adaptability, can be engineered to mimic the architecture of the nervous system's extracellular matrix. The implantation of nanofiber scaffolds in the nervous system can act as cues for axon regrowth, neuron adhesion, and neural differentiation. This chapter will explore the latest advancements in investigating nanofibers and stem cells for treating neurological diseases, ensuring you are up to date with cutting-edge research. © 2025 Linh Huynh, Li Yao. All rights reserved

Collision avoidance and geofencing for fixed-wing aircraft with control barrier functions

This is an open access article under the CC BY license.Safety-critical failures often have fatal consequences in aerospace control. Control systems on aircraft, therefore, must ensure the strict satisfaction of safety constraints, preferably with formal guarantees of safe behavior. This article establishes the safety-critical control of fixed-wing aircraft in collision avoidance and geofencing tasks. A control framework is developed wherein a run-time assurance (RTA) system modulates the nominal flight controller of the aircraft whenever necessary to prevent it from colliding with other aircraft or crossing a boundary (geofence) in space. The RTA is formulated as a safety filter using control barrier functions (CBFs) with formal guarantees of safe behavior. CBFs are constructed and compared for a nonlinear kinematic fixed-wing aircraft model. The proposed CBF-based controllers showcase the capability of safely executing simultaneous collision avoidance and geofencing, as demonstrated by simulations on the kinematic model and a high-fidelity dynamical model. © 1993-2012 IEEE

Matrix Li–Yau–Hamilton estimates under Kähler–Ricci flow

Click on the DOI link to access this article at the publishers website (may not be free).We prove matrix Li–Yau–Hamilton estimates for positive solutions to the heat equation and the backward conjugate heat equation, both coupled with the Kähler–Ricci flow. These estimates are further extended to the constrained setting. As an application, we obtain a monotonicity formula. © Mathematica Josephina, Inc. 2025.Wichita State University, WSU; Division of Mathematical Sciences, DMS, (2405257); Division of Mathematical Sciences, DMS; National Science Foundation, NSF, (2316659); National Science Foundation, NSF; Simons Collaboration, (962228); National Natural Science Foundation of China, NSFC, (11571361); National Natural Science Foundation of China, NSFCXiaolong Li research is partially supported NSF-DMS #2405257, NSF LEAPS-MPS #2316659, Simons Collaboration Grant #962228, and a start-up grant at Wichita State University. Xin-An Ren research is partially supported by National Natural Science Foundation of China Grant #11571361

Examining modal shift in Japan's logistics

Published in SOAR: Shocker Open Access Repository by the Wichita State University Libraries Technical Services, October 2025.The current Japanese distribution industry is confronting difficulties that can be divided broadly into three categories. The first include those related to the shortage of truck drivers (labor shortages). The second category includes difficulties related to the CO2 emissions of trucks (environmental load). The last are difficulties related to a rapid increase in home-delivery services caused by the growth of e-commerce markets. In response to all of these difficulties, a modal shift from trunk cargo transportation that uses trucks to railroad or maritime transportation is important. Therefore, a comparative analysis of the characteristics of intercity truck, rail and vessel transportation in the total cargo volume of Japan conducted for this study is performed from the perspective of three factors including distance, time required and fares, with discussion of effective modes of transportation (modal shift)

A comparison of overall function between postpartum women with and without diastasis rectus abdominis

Presented to the 21st Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at the Rhatigan Student Center, Wichita State University, April 11, 2025.Research completed in the Department of Physical Therapy, College of Health Professions.INTRODUCTION: Diastasis rectus abdominis (DRA) is a separation of the left and right rectus abdominis at the linea alba (LA) and is prevalent in up to 83% of postpartum women. Previous research shows a relationship between DRA, urinary incontinence, and low back/ abdominal pain; however, DRA’s impact on a woman’s overall function in the postpartum period is not well understood. The effects DRA has on functional status needs to be investigated so that physical therapists and other providers can understand the rehabilitative needs of postpartum women. The null hypothesis of this study was that there would be no significant difference in overall functional ability between postpartum women who have DRA versus those who do not. PURPOSE: The purpose of this study was to examine the functional status of women after childbirth and determine differences in function in women with or without DRA. METHODS: In this methodological study, postpartum women ages 18-40 between 6-10 weeks postpartum were recruited through flyers and social media, surveyed with the Inventory of Functional Status After Childbirth (IFSAC), participated in a telehealth visit, and completed an in-person visit to measure the abdominal muscles with real-time ultrasound to determine DRA diagnosis status. IFSAC scores were compared between postpartum women with and those without a DRA. RESULTS: Twenty-six women who were on average 28 years old, 7.3 weeks postpartum, and experienced an average of 1.6 vaginal deliveries, completed all phases of this study. Results of an independent t-test revealed overall function IFSAC scores between women with DRA (M = 3.35, SE = 0.08) and women without DRA (M = 3.42, SE = 0.15). This difference, 0.07, CI 95% [-0.27, 0.41] was not significant t (26) = 0.406, p = 0.336, with a small-medium effect size of d = 0.37. CONCLUSION: The results of this study sheds light on potential functional effects of a DRA on postpartum women and bring awareness of the impact of pregnancy. This knowledge will guide practitioners in appropriate intervention selection for this population. Although this study did not find a statistically significant difference in overall functional scores between postpartum women with and postpartum women without DRA, it does show a potential downward trend of functional status in women with DRA. Further research should consider comparing women with more severe inter-rectus distances (greater than 4.0 cm). More severe separation has been shown to decrease lumbopelvic stability, and therefore, will likely impact overall function. More research is needed to understand the lingering musculoskeletal effects of pregnancy in the fourth trimester. These women must not only take care of a newborn baby but also need to rehabilitate their own bodies to return to a functional life beyond childbearing.Graduate School, Academic Affairs, University Librarie

Modeling electric vehicle charging load on power grid considering travel behavior

Click on the DOI link to access this article at the publishers website (may not be free).Electric vehicle (EV) usage increases every year, yet there is no accurate model to predict traveling or charging behavior. Current working models present inaccurate data as well as showing the same daily demand at different locations. These models do not consider the variations of human behavior and differences in geographic areas. However, an agent-based modeling (ABM) system is able to track individuals in a simulation to predict their behavior. NetLogo is an ABM platform implemented to show the behavior of EVs. Through the ABM simulation, travelers were simulated and recorded to predict their future load demand realistically and accurately on the grid. This simulation showed different peak times and load amounts between locations and slight differences in each iteration as expected. These results show a more accurate prediction of future EV load demand based on the input data such as vehicle type ratio, number of vehicles, and average range of city. © 2025 IEEE

2025-2026 University Staff Senate standing committees

(2025-2026 Staff Senate Committees): Awards & recognition -- Communication & website -- Election -- Policy review -- Professional development & service -- Shocker Strive Conference -- Scholarship -- (Campus/University Committee Representatives): Academic Forum -- Budget Advisory Committee -- Human Resources meeting -- Legislative update -- Library Appeals Committee -- Parking appeals committee -- Parking & traffic policy -- VP Finance and Admin one-on-one -- President executive constituency heads -- President's one-on-one -- RSC Board of Directors -- UPS & USS Council (KBOR