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Investigating the structure and physical properties of KCrTe2 and (RbK)0.5CrTe2
No full textPoster and abstract presented at the FYRE in STEM Showcase, 2025.Research project completed at the Department of Chemistry and Biochemistry.Chromium ditelluride (CrTe₂) is a layered transition metal dichalcogenide that has ferromagnetic transition above room temperature, making it a promising candidate for spintronic and quantum computing applications. The method for synthesizing 1T-CrTe₂ involves an indirect approach, where potassium is extracted from the precursor compound KCrTe₂. In this study, we investigated the chemical transformation from pristine KCrTe2, A1-xBxCrTe₂(A=Rb, B=Na, K, and x=0.5) to 1T-CrTe₂ and report the synthesis, crystal growth, and characterization. KCrTe₂ is a layered material in which potassium atoms are weakly held between CrTe₂ layers via ionic interactions. We hypothesize that introducing mixed cations could lead to the formation of a heterostructure. Heterostructures can enhance the electronic and magnetic properties of the material by changing the bandgap and allowing charge transfer between layers. The prepared compounds are characterized by Powder X-ray Diffraction (PXRD) and Energy-dispersive X-ray spectroscopy (EDX). These findings demonstrate that altering the stoichiometric ratios affects the crystal structure and physical properties of KCrTe₂ and A1-xBxCrTe₂(A=Rb, B=Na, K, and x=0.5). From a materials chemistry standpoint, this tunability presents a way to enhance properties critical to the development of future spintronic and quantum technologies
Orbital anomalies of CubeSats in solar synchronous orbit during initial orbit determination
No full textPoster and abstract presented at the FYRE in STEM Showcase, 2025.Research project completed at the Department of Aerospace Engineering.The SNAPPY Mission is a NASA-Funded project at the Wichita State University aiming to send a neutrino particle detector into a low earth orbit to collect high amounts of scientific data. The satellite will enter solar synchronous orbit, meaning that it will have an altitude of approximately 500-700 kilometers at an angle about 97 degrees from the equator. Due to the nature of this orbit, it will experience perturbations from solar radiation pressure, atmospheric drag, and gravitational perturbations. The aim of this study is to characterize these changes and note any anomalies in the trends of their Keplerian orbital elements (elements that define the orbit numerically) to support the operational procedures of launching the neutrino-detector-CubeSat. A large dataset of nano-satellite information was procured utilizing an API scrapping python algorithm that fetched data through queries to Space-Track.org. A separate python algorithm was developed to organize the data, which was then analyzed to determine dependencies of elements. The satellites of most interest were those launched from the Transporter-13 Falcon 9 ride share program. These satellites were also compared with a variety of satellites from launches dating as far back as 2013. It was determined that the majority of elements were time-dependent and followed trends with insignificant variations (R2 values were near or above .99 for all time dependent elements) in their orbit one month after launch. Furthermore, a high correlation was observed between B-Star (drag term) and solar radiation flux
Understanding college students' reproductive health knowledge at Wichita State: A data-driven approach
No full textPresented 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 Public Health Sciences, College of Health Professions.Reproductive health services, including contraceptive access, STI testing, and gynecological care, are essential for college students, yet barriers such as age, insurance status, and lack of education often hinder access. This study evaluates reproductive health knowledge and prior health education among students at Wichita State University (WSU), focusing on factors such as age and insurance status. The reproductive health study was nested within a larger survey about college student health needs and services available on campus. A 51-question survey, adapted from the National College Health Assessment, was administered online in February 2025 to approximately 13,000 students, yielding 2,558 responses (data collection ongoing). The survey included 17 demographic questions and 6 focused on reproductive health, covering use of campus health services, contraceptive methods, sources of sexual health education, access to information in high school, topics covered, and perceived quality of that education. Key findings include gaps in sexual health education, with younger students (18-24) primarily receiving information from parents/guardians, and older, uninsured students (25-44) less likely to use contraception. These findings highlight the need for targeted education to improve reproductive health knowledge among younger students, with an emphasis on increasing awareness of campus health services.Graduate School, Academic Affairs, University Librarie
Detection of release fabric defects in fiber-reinforced composites using through-transmission ultrasound
No full textThis is an open access article under the CC BY license.The detection of foreign material residues in fiber-reinforced composites (FRCs) is crucial, as such residues weaken the structural performance, especially when the acoustic impedance of the foreign material closely matches that of the composite material. To date, no methodology has been developed to improve the detection of such defects with similar acoustic impedance in the received signal without using echo-mode techniques. Release fabric was chosen because it is used in the fabrication of FRCs as a consumable, which must be removed after curing. An accidental residue of release fabric presents a significant challenge in detecting it within FRC laminates using through-transmission ultrasound (TTU) since its acoustic properties closely resemble the surrounding composite material, resulting in minimal impact on the transmitted signal and preventing accurate defect detection due to the lack of time-of-flight measurements. This paper leverages a novel threshold classifier to improve the detection of release fabric with through-transmission ultrasound (TTU), an inspection technique that operates without echo mode. Ultimately, this novel threshold classifier improves TTU inspection by offering greater sensitivity and detectability compared to conventional attenuation-based methods, particularly in the absence of echo mode and time-of-flight measurements. Future research will aim to investigate additional physical factors and deep learning approaches to further advance the TTU inspection method. © 2025 by the authors
TransfusionNet: Framework for cervical cancer detection using deep learning with multi-level fusion
No full textClick on the DOI link to access this article at the publishers website (may not be free).This paper presents a hybrid deep learning model, TransfusionNet, comprising VGG19, ResNet50, and ViT with fusion for early detection of cervical cancer. An improved medical image preprocessing technique combining contrast-limited adaptive histogram equalization (CLAHE), Laplacian sharpening, bilateral filtering, and unsharp masking has been applied to enhance image quality. An early-layer feature fusion strategy was used to enhance feature diversity and improve decision-making, unlike conventional methods that fuse only at final layers. The fusion strategy combines features from VGG19, ResNet50, and ViT at multiple stages using concatenation and element-wise addition, allowing integration of detailed and high-level information across different levels. Two separate transition blocks were used to align VGG19 and ResNet50 outputs at different layers. TransfusionNet is trained and tested on the publicly available SIPaKMeD dataset, containing 4,049 images of five classes. TransfusionNet is also verified on Herlev and LCPSI datasets. The five-fold cross-validation was employed to mitigate overfitting and enhance model's robustness and generalizability. TransfusionNet demonstrates promising results for early cervical cancer detection, achieving state-of-the-art performance on the SIPaKMeD dataset. For batch size 128, TransfusionNet achieved an average accuracy of 99.40%, an F1-score of 99.36%, sensitivity of 99.25%, and Cohen's Kappa of 99.67% across the five folds. On the SIPaKMeD dataset, the proposed model outperformed the best-performing model by 3.77% among the cited models. On the Herlev and LCPSI datasets, TransfusionNet surpassed the top-performing methods by 6.50% and 1.22% in accuracy, respectively. Future work will focus on validating the model on larger and more diverse datasets. The source code is available at https://github.com/souravbasakshuvo/TransFusionNet
Financial obligations for a feasibility study on a manufacturing facility
No full textPresented 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 Industrial, Systems, and Manufacturing Engineering, College of Engineering, and the Department of Applied Engineering, College of Engineering.INTRODUCTION: The expansion in key industries such as aerospace and automotive drives up the demand for high quality electromechanical components. Current electromechanical components produced do not meet the industry quality standards or they are priced at higher than average due to specialized manufacturing processes.
PURPOSE: This poster showcases the economic feasibility of setting up an electromechanical facility that manufactures component according to industry standards. This economic feasibility study is done using a plant investment graph for making economic decisions with the help of financial tools such as the 3 financial statements, financial ratios, and sensitivity analysis. This study examines financial investment using: 1) payback period, 2) internal rate of return (IRR), 3) profitability index (PI), and 4) net present value (NPV).
METHODS: This study sees the development of a plant investment graph to test the economic feasibility of an electromechanical manufacturing facility where the cashflow is compared against time. A 3-statement financial model will be used to calculate the costs such as R&D, plant investment, and working capital to calculate payback period, capital recovery, and profitability index (PI) during operation of the facility.
RESULTS: Using the financial statements on an annual basis, the graph shows the cash flow shifting from negative to positive over time. Initial investment is large even before starting the plant operation, however the payback period is within reasonable risk. Beyond the break-even point, profitability is achieved aiding in the recovery for land and working capital.
CONCLUSION: Financial tools and calculations that go into developing the investment graph are obtained from this study show that starting an electromechanical facility is economically feasible and manage to adhere to industry standards while keeping the cost as low as possible. The graph visualizes the feasibility comprehensively covering all aspects and risk of starting an electromechanical manufacturing facility.Graduate School, Academic Affairs, University Librarie
Exploring the drivers of inflation in Nigeria: the roles of insecurity, oil, food and crop production
No full textClick on the DOI link to access this article at the publishers website (may not be free).Purpose: Nigeria’s inflation surged after the COVID-19 pandemic, reaching 34.19% in 2023 – its highest in 28 years – with food inflation at 40.53%. In response, the Central Bank of Nigeria (CBN) implemented aggressive monetary tightening, raising interest rates from 18.75 to 26.25% and setting the cash reserve ratio (CRR) at a global high of 45%. Despite these measures, inflation worsened, the Naira depreciated to ₦1,600/$ and economic hardship deepened, reducing purchasing power and increasing poverty. Public protests have followed, demanding better governance. However, limited research has explored the influence of nonmonetary factors on inflation in the post-COVID-19 era, as most studies focus primarily on monetary policy. This study aims to examine the roles of insecurity, oil prices, food production and crop output in driving inflation in Nigeria, using the cost–push theory as a framework and assessing the effectiveness of monetary policy. Design/methodology/approach: The study uses time series data from 1986 to 2023 and applies the autoregressive distributed lag (ARDL) model, along with two robustness checks: canonical cointegration regression (CCR) and fully modified least squares (FMOLS). This approach captures both the short- and long-term effects of insecurity, oil prices, food and crop production and the monetary policy rate on inflation. Findings: The results show that insecurity and crop production increase inflation in both the short and long term. Oil prices have a positive short-term effect but a negative long-term effect. Food production and the monetary policy rate help reduce inflation across both periods, suggesting that monetary tightening is effective. The CCR and FMOLS results confirm these long-run relationships. Overall, effective inflation control in Nigeria requires addressing both nonmonetary and monetary factors. Practical implications: To manage inflation, Nigeria must address insecurity, support stable crop production, reduce reliance on oil and maintain a responsive monetary policy. Strengthening security would protect farmers and supply chains, supporting consistent food production and price stability. Enhancing agricultural productivity through subsidies, infrastructure and modern farming techniques can also reduce inflationary pressures. While oil price volatility affects inflation in the short term, long-term strategies should promote energy diversification. The findings support the continued use of interest rate adjustments to manage inflation, provided they remain responsive to economic trends. Originality/value: This study fills a research gap by focusing on nonmonetary drivers of inflation in Nigeria, specifically insecurity, oil prices and agricultural output, which are relatively underexplored factors. It also offers empirical insights into the effectiveness of monetary policy in the Nigerian context. These findings are relevant for achieving Sustainable Development Goals (SDGs) 2 (Zero Hunger) and 8 (Decent Work and Economic Growth) and can inform policy in other developing countries facing similar inflationary challenges. © 2025, Emerald Publishing Limited
Effects of encapsulant on thru-reflect-line calibrations within the frequency band for automotive radar
No full textThesis (M.S.)-- Wichita State University, College of Engineering, Dept. of Electrical and Computer EngineeringTesting semiconductors in the frequency band of 77-81GHz is of increasing importance, since many companies are producing technology for Automotive radar in this bandwidth and therefore must subject their products to the automotive qualification process. Providing reliable, high quality data at such high frequencies is challenging. Direct bonding of semiconductors to the printed circuit boards (PCBs) and using chip-on-board (COB) technology is advised to limit the impact that connections to the device under test (DUT) have on the data, but these methods also often require protection or support through the use of encapsulant covering the DUT. Encapsulant can also have a significant impact on high frequency measurements. This thesis looks at the impact encapsulant has on a thru-reflect-line (TRL) calibration used in the 77-81GHz bandwidth, and explores methods for accounting for the error produced by the encapsulant on the calibration. This thesis also demonstrates that Newton’s method for approximation can be used with a high level of confidence to solve the nonlinear system of equations produced by a realistic TRL calibration
Synthesis and degradation of aliphatic poly (ester carbonate) copolymers using novel chloroformates
No full textPoster project completed at Wichita State University, Department of Chemistry and BiochemistryPresented at the 22nd Annual Capitol Graduate Research Summit, Topeka, KS, March 25, 2025.Aliphatic polyesters and polycarbonates have been widely investigated due to their biodegradability, which is important for both biomaterials and sustainable plastics. We are exploring the synthesis and copolymerization of the new aliphatic monomer, 2- (chlorocarbonyl)ethyl chloroformate (CFEO), and its chlorinated analog Cl- CFEO. Both CFEO and Cl-CFEO have two reactive functional groups that will react with diols to produce alternating poly (ester carbonate)s under conditions that allow the more reactive acid chloride group to react before the chloroformate group, or statistical copolymers when both functional groups can react. In addition to developing copolymerization reactions, this presentation will compare the hydrolytic stability of the alternating and statistical copolymers and their corresponding polyester and polycarbonate analogs under basic and enzymatic conditions and then will discuss the implications of these properties in medical and biodegradable applications
A mathematical framework for optimizing immuno-radiotherapy treatments
No full textThesis (M.S.)-- Wichita State University, College of Engineering, Dept. of Industrial, Systems, and Manufacturing EngineeringImmunotherapy (IT) has recently emerged as an important modality for the treatment of advanced-stage cancers. Despite the encouraging clinical results, the numberof patients who durably respond to IT alone is small. Therefore, there has been clinical interest in combining IT with other cancer treatment modalities, particularly radiotherapy (RT). The combination of IT and RT, known as immunoradiotherapy (IRT), has shown great clinical promise to induce both local and systemic anti-tumor immune response, leading to a durable disease control. However, RT may also promote immune suppression by killing highly radiosensitive immune cells. The immune stimulant and suppressive effects of RT depend on the timing and dose of radiation and the immunotherapeutic agent.
The primary goal of this research is to develop a mathematical model that captures the interplay between RT and IT by modeling the interactions between tumor cells and immune cells under the influence of radiation and immune checkpoint inhibitors (ICI’s). Mathematical modeling of IRT can play a significant role in hypothesis generation for the design of promising clinical trials with the ultimate goal of improving the treatment efficacy for cancer patients.
A compartmental model is developed to simulate the population dynamics of tumor and immune cells. The proposed compartmental model accounts for primary and inactivated tumor cells, metastatic tumor cells and recruited lymphocytes. The model is incorporated into an optimization framework to determine the best IRT treatment schedule. A Monte-Carlo simulation approach is employed to account for parameter uncertainties in the model. Computational results focus on advanced-stage non-small cell lung cancer (NSCLC), which is commonly treated by IRT. In particular, to estimate the model parameters, the progression-free and overall survival curves obtained from the MC approach are fitted to the Kaplan-Meier survival curves reported from IRT clinical trials for NSCLC. The calibrated model is then used to design an IRT treatment regimen by optimizing the time-averaged progression-free survival for a patient cohort