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Evaluation And Modulation Of The Circadian Clock In Human Keratinocytes And Epidermal Skin, William Harold Cvammen Iv
Evaluation And Modulation Of The Circadian Clock In Human Keratinocytes And Epidermal Skin, William Harold Cvammen Iv
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The circadian clock is a fundamental biological mechanism that regulates various physiological processes, including DNA repair, to synchronize with the day-night cycle. In human skin, exposure to ultraviolet (UV) light poses a significant challenge, inducing DNA damage that must be efficiently repaired to maintain genomic integrity and prevent carcinogenesis. This study delved into the complex interplay between the circadian clock, UV light exposure, DNA repair, and modulation of circadian transcriptional machinery in human skin. Initially, we examined the transcriptomic profile of the circadian clock in humans through in silico-based approaches and in vivo studies, revealing that core clock gene expression …
Examining The Nonprofit Leader From The Servant Leadership Theory : Impacts On Board Cohesion, Andrew Wonders
Examining The Nonprofit Leader From The Servant Leadership Theory : Impacts On Board Cohesion, Andrew Wonders
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n the context of nonprofit organizations, servant leadership (SL) has been studied on a limited basis. The present study attempted to forge a new path by examining the impact of SL and cohesion in the realm of nonprofit organizations. A total of 91 board members from 32 organizations participated in the study. Five statistical models of mixed effects linear regression were used in the analysis. The first model utilized the eight subscales of SL as independent variables and overall cohesion is the dependent variable while the other four models used overall SL as the independent variable. Each model also had …
Military Faculty Experience Within A Faculty Learning Community And Its Interest In Learning Technology Integration, Jonathan David Zemmer
Military Faculty Experience Within A Faculty Learning Community And Its Interest In Learning Technology Integration, Jonathan David Zemmer
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This study explored the experiences and perceptions of faculty members at an institution of military education participating in a Faculty Learning Community (FLC) focused on educational technology utilization during the 2022-2023 academic year. As the Department of Defense (DoD) emphasizes the importance of technology capabilities and workforce development, understanding faculty experiences in these settings becomes crucial for effective technology integration in teaching and learning. Utilizing a participatory action research (PAR) design, the study collected data through faculty artifacts, researcher reflexive journals, semi-structured interviews, bi-monthly meeting minutes, videos, and presentation materials. The research questions focused on the change of participants' understanding …
The Effects Of Actions And Characteristics In The Perception Of Aggressive Intentions : The Case Of Russia Border States After The 2022 Invasion Of Ukraine, Noah Duteil
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How alliance structures form and why states balance, bandwagon, or remain neutral against other states is an enduring and important question in international relations. This thesis adds to the discussion of how states make alliance decisions by testing whether perceptions matter in predicting state balancing behavior and by proposing a new theoretical framework which allows for a better understanding of the mechanisms which drive the perception of aggressive intentions as a factor within Stephen Walt’s balance of threat theory. In this thesis, I explore the construction of threat through a comparative case study analysis of border states of Russia following …
Exploring The Relationship Between Academic Program Assessment Practices And Institutional Performance, Nicholas T. Christian
Exploring The Relationship Between Academic Program Assessment Practices And Institutional Performance, Nicholas T. Christian
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Researchers (Stanny & Bryan, 2021; Tinto, 2012) have claimed without empirical evidence that academic program assessment is important to student success. This study used structural equation modeling (SEM) to identify the relationships between academic program assessment practices and institutional performance based on responses from faculty at U.S.-located four-year institutions of higher education. The theoretical foundations of best practices in program assessment, organizational learning, faculty motivation, and institutional performance were examined and included as the primary variables. Assessment practices in higher education are best summarized by the assessment loop: articulating the intended learning outcomes; selecting appropriate assessment measures; developing curriculum and …
Examining The Effects Of Parameter Correlation And Its Implications For Models Of Learning And Retention: A Large Scale Model Validation : Examining The Effects Of Parameter Correlation And Its Implications For Models Of Learning Andretention: A Large Scale Model Validation, Michael Gordon Collins
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Mathematical models of learning and retention have long been developed in psychology for both basic and applied research. For basic research, models of learning and retention attempt to explain how individuals acquire and retain information over time. While for applied research, models of learning and retention are used to inform education and training decisions. In both of these applications, the primary purpose of using a model is to fit and predict the performance of individuals. However, little attention has been paid to the interpretation of a model’s free parameters (i.e., learning and decay rates) and the effect that a model’s …
The Relationships Among Organizational Support, Teacher Well-Being, And Teacher Resilience In Secondary School Teachers, Lisa Journell
The Relationships Among Organizational Support, Teacher Well-Being, And Teacher Resilience In Secondary School Teachers, Lisa Journell
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This study examined the relationships among perceived organizational support, teacher well-being, and teacher resilience in secondary school teachers in Ohio public schools. An explanatory sequential mixed methods research design was employed. In phase one, survey data were collected from Ohio public school teachers (n = 254, grades 6-12), and structural equation modeling was used to analyze the structure of the relationships between the variables of interest. In phase two, using a phenomenological approach, follow-up interviews were conducted with a subset of participants (n = 10) to examine the lived experience of teachers with high and low levels of teacher resilience. …
Additively Manufactured Polymeric Surface-Based Lattice Structures For Vibration Attenuation, Imabin Kelvin Ekpelu
Additively Manufactured Polymeric Surface-Based Lattice Structures For Vibration Attenuation, Imabin Kelvin Ekpelu
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The focus of this study was to select triply periodic minimal surface (TPMS) structures made of 3D-printed polymers. The primary variables in this study were: TPMS shape, lattice volume ratio, and lattice material. Vibration absorption was characterized by damping ratio via transmissibility at the system’s natural frequency. The vibration testing was performed using an electro-dynamic shaker, a known mass, an input/control accelerometer, and an output/response accelerometer. The 3D-printed absorber/lattice was mounted to the shaker baseplate and a mass will be mounted on top of the absorber. One accelerometer will be mounted to the shaker baseplate and the other will be …
Friend Or Foe? The Role Of Transforming Growth Factor-Β (Tgfβ) Signaling In Calcineurin Inhibitor-Induced Renal Damage, Adaku Uwe
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With its incorporation into clinical practice in the early 1980s, the class of pharmacological agents known as calcineurin inhibitors (CNIs) quickly became the cornerstone of immunosuppressive therapy post-organ transplantation. However, its use is limited by irreversible kidney damage in the form of renal fibrosis. The molecular mechanism by which CNIs induce renal fibrosis remains to be better understood, and to date, there are no specific therapeutic strategies to mitigate this damage. This dilemma presents a critical need to explain mechanisms by which CNIs cause renal damage. Kidneys of patients on chronic CNI therapy show increased expression of the proinflammatory cytokine …
Icing Mitigation Via High-Pressure Membrane Dehumidification In An Aircraft Thermal Management, Danielle D. Hollon
Icing Mitigation Via High-Pressure Membrane Dehumidification In An Aircraft Thermal Management, Danielle D. Hollon
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Icing, or the formation of ice from water via freezing or water vapor via desublimation, is a phenomenon that commonly occurs within air cycle-based refrigeration systems and requires thermal control that limits system performance. In aircraft applications icing frequently occurs in the heat exchangers and turbine(s) that are part of the air cycle machine, the refrigeration unit of the environmental control system. Traditionally, water vapor is removed from an air cycle machine via condensing in a heat exchanger and subsequent high-pressure water separation. This approach is not capable of removing all of the vapor present at low altitude conditions, corresponding …
Tracking The Progression Of Defects At The Neuromuscular Junction In Huntington's Disease, Katherine A. Trittschuh
Tracking The Progression Of Defects At The Neuromuscular Junction In Huntington's Disease, Katherine A. Trittschuh
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Huntington’s disease (HD) is a genetic disorder associated with progressive cognitive and motor decline. Recent studies in HD models suggest primary peripheral pathologies arise independent of changes in the central nervous system. Our lab found defects in skeletal muscle occurring early in the progression of disease in transgenic R6/2 HD mice, resulting in membrane hyperexcitability. Additionally, there is evidence of decreased quantal content in late-stage R6/2 mice. Here, we investigate pre-synaptic and post-synaptic function at single neuromuscular junctions (NMJ) to make direct comparisons of disease progression in the muscle membrane and motor nerve terminal. We hypothesize that muscle membrane defects …
Direct Parameter Fitting Of Action Potentials In Skeletal Muscle Cells Which Include Longitudinal Segments, Tyme Suda
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Excitation of skeletal muscle cells triggers a large voltage spike known as an action potential (AP), leading to muscle contraction. Modeling of an AP is typically done using the method developed by scientists Hodgkin and Huxley (HH). In the HH method, voltage and time gated Na+ and K+ ionic currents are simulated, along with a positive “Leak” ionic current and capacitive current. Due to the complexity and the computational time required for simulation, direct fitting of HH parameters to experimental APs has rarely been attempted. A previous thesis at Wright State performed direct fitting for the case of a single …
Tracking The Progression Of Defects At The Neuromuscular Junction In Huntington's Disease, Katherine A. Trittschuh
Tracking The Progression Of Defects At The Neuromuscular Junction In Huntington's Disease, Katherine A. Trittschuh
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Huntington’s disease (HD) is a genetic disorder associated with progressive cognitive and motor decline. Recent studies in HD models suggest primary peripheral pathologies arise independent of changes in the central nervous system. Our lab found defects in skeletal muscle occurring early in the progression of disease in transgenic R6/2 HD mice, resulting in membrane hyperexcitability. Additionally, there is evidence of decreased quantal content in late-stage R6/2 mice. Here, we investigate pre-synaptic and post-synaptic function at single neuromuscular junctions (NMJ) to make direct comparisons of disease progression in the muscle membrane and motor nerve terminal. We hypothesize that muscle membrane defects …
The Impact Of Study Strategies On Academic Performance For Medical Students At Wright State University, Markia Black
The Impact Of Study Strategies On Academic Performance For Medical Students At Wright State University, Markia Black
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Studying plays an important role in the academic success of medical students. It is likely that ineffective study skills result in poor performances on required standardized exams. There is a concern for the lack of empirical data related to what study strategies are the most productive for medical students to practice. My goal is to 1) identify what study strategies students use in their pre-clinical years of medical school, 2) determine if these strategies impact students’ performance on Comprehensive Basic Science Exams and Step 1 exam, and 3) identify study methods that best support student achievement in the pre-clinical phase …
Green Synthesis Of Nanoparticles And Their Utilization In Electrochemical Detection Of Catechol- Or Phenol-Based Substances, Daniel Laurence Myers Iii
Green Synthesis Of Nanoparticles And Their Utilization In Electrochemical Detection Of Catechol- Or Phenol-Based Substances, Daniel Laurence Myers Iii
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PART A: GREEN SYNTHESIS OF COPPER NANOPARTICLES AND THEIR UTILIZATION IN THE DETECTION OF NEUROTRANSMITTERS Neurotransmitters, such as dopamine and epinephrine, are chemicals frequently found in the brain and are responsible for a number of human moods, needs, and emotions.1, 2 Detection of such neurotransmitters allows for a better judgement of a person’s physical and mental state, a utility that is vital in determining the presence of disease and mental illnesses.2 Electrochemical detectors used for such detections are often modified by materials such as metal nanoparticles.3 However, synthesizing nanoparticles can involve or produce chemicals, ammonium hydroxide among them, that are …
Microplastics In Wetlands Of West Central Ohio : Concentration And Distribution, Mitchell Link
Microplastics In Wetlands Of West Central Ohio : Concentration And Distribution, Mitchell Link
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Wetlands provide many valuable ecosystem services; however, an emerging global contaminant—microplastic (< 5 mm)—may be degrading this important resource. Few studies have extensively surveyed microplastic distribution in wetlands over a broad spatial area. Therefore, the goal of this study is to identify where microplastics are accumulating in wetlands, and whether there is any correlation between microplastic concentration and wetland quality. Soil samples were collected from 30 wetlands in west–central Ohio. Samples were physically separated, density separated, and digested. Average microplastic concentrations were 637 ± 494 items per kg soil per wetland. Higher quality wetlands are accumulating larger concentrations of microplastics. This relationship seems to be driven by greater accumulation of microplastics in forested wetlands than in wetlands surrounded by agriculture. There is no clear distribution pattern of microplastics within wetlands. These results provide insight into the role that wetlands have in association with microplastic accumulation.
Fuzzing Php Interpreters By Automatically Generating Samples, Jacob S. Baumgarte
Fuzzing Php Interpreters By Automatically Generating Samples, Jacob S. Baumgarte
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Modern web development has grown increasingly reliant on scripting languages such as PHP. The complexities of an interpreted language means it is very difficult to account for every use case as unusual interactions can cause unintended side effects. Automatically generating test input to detect bugs or fuzzing, has proven to be an effective technique for JavaScript engines. By extending this concept to PHP, existing vulnerabilities that have since gone undetected can be brought to light. While PHP fuzzers exist, they are limited to testing a small quantity of test seeds per second. In this thesis, we propose a solution for …
Enhancing Graph Convolutional Network With Label Propagation And Residual For Malware Detection, Aravinda Sai Gundubogula
Enhancing Graph Convolutional Network With Label Propagation And Residual For Malware Detection, Aravinda Sai Gundubogula
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Malware detection is a critical task in ensuring the security of computer systems. Due to a surge in malware and the malware program sophistication, machine learning methods have been developed to perform such a task with great success. To further learn structural semantics, Graph Neural Networks abbreviated as GNNs have emerged as a recent practice for malware detection by modeling the relationships between various components of a program as a graph, which deliver promising detection performance improvement. However, this line of research attends to individual programs while overlooking program interactions; also, these GNNs tend to perform feature aggregation from neighbors …
Anomaly Detection In Multi-Seasonal Time Series Data, Ashton Taylor Williams
Anomaly Detection In Multi-Seasonal Time Series Data, Ashton Taylor Williams
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Most of today’s time series data contain anomalies and multiple seasonalities, and accurate anomaly detection in these data is critical to almost any type of business. However, most mainstream forecasting models used for anomaly detection can only incorporate one or no seasonal component into their forecasts and cannot capture every known seasonal pattern in time series data. In this thesis, we propose a new multi-seasonal forecasting model for anomaly detection in time series data that extends the popular Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Our model, named multi-SARIMA, utilizes a time series dataset’s multiple pre-determined seasonal trends to increase …
To What Extent Do Non-Native Shrubs Support Higher Trophic Levels?, Ari Zakroff
To What Extent Do Non-Native Shrubs Support Higher Trophic Levels?, Ari Zakroff
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Invasive species threaten ecosystems and economies. Globally, biological invasions are estimated to have cost over $2.1 trillion since 1970. In Eastern North American woodlands, invasive plants are rapidly displacing natives. This is concerning, because invasive plants may not support the diverse and abundant arthropod communities essential to ecosystem function. Despite the conceptual understanding of invasive shrubs’ potential to transform forest communities, scant research has focused on the effect of invasive plants on higher trophic levels here in Ohio. To address this gap, I examined the diversity and abundance of arthropod communities, caterpillar performance, and caterpillar predation on two invasive shrubs, …
Friend Or Foe? The Role Of Transforming Growth Factor-Β (Tgfβ) Signaling In Calcineurin Inhibitor-Induced Renal Damage, Adaku Ume
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With its incorporation into clinical practice in the early 1980s, the class of pharmacological agents known as calcineurin inhibitors (CNIs) quickly became the cornerstone of immunosuppressive therapy post-organ transplantation. However, its use is limited by irreversible kidney damage in the form of renal fibrosis. The molecular mechanism by which CNIs induce renal fibrosis remains to be better understood, and to date, there are no specific therapeutic strategies to mitigate this damage. This dilemma presents a critical need to explain mechanisms by which CNIs cause renal damage. Kidneys of patients on chronic CNI therapy show increased expression of the proinflammatory cytokine …
Unsupervised-Based Distributed Machine Learning For Efficient Data Clustering And Prediction, Vishnu Vardhan Baligodugula
Unsupervised-Based Distributed Machine Learning For Efficient Data Clustering And Prediction, Vishnu Vardhan Baligodugula
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Machine learning techniques utilize training data samples to help understand, predict, classify, and make valuable decisions for different applications such as medicine, email filtering, speech recognition, agriculture, and computer vision, where it is challenging or unfeasible to produce traditional algorithms to accomplish the needed tasks. Unsupervised ML-based approaches have emerged for building groups of data samples known as data clusters for driving necessary decisions about these data samples and helping solve challenges in critical applications. Data clustering is used in multiple fields, including health, finance, social networks, education, and science. Sequential processing of clustering algorithms, like the K-Means, Minibatch K-Means, …
Data-Driven Strategies For Disease Management In Patients Admitted For Heart Failure, Ankita Agarwal
Data-Driven Strategies For Disease Management In Patients Admitted For Heart Failure, Ankita Agarwal
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Heart failure is a syndrome which effects a patient’s quality of life adversely. It can be caused by different underlying conditions or abnormalities and involves both cardiovascular and non-cardiovascular comorbidities. Heart failure cannot be cured but a patient’s quality of life can be improved by effective treatment through medicines and surgery, and lifestyle management. As effective treatment of heart failure incurs cost for the patients and resource allocation for the hospitals, predicting length of stay of these patients during each hospitalization becomes important. Heart failure can be classified into two types: left sided heart failure and right sided heart failure. …
Solidity Compiler Version Identification On Smart Contract Bytecode, Lakshmi Prasanna Katyayani Devasani
Solidity Compiler Version Identification On Smart Contract Bytecode, Lakshmi Prasanna Katyayani Devasani
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Identifying the version of the Solidity compiler used to create an Ethereum contract is a challenging task, especially when the contract bytecode is obfuscated and lacks explicit metadata. Ethereum bytecode is highly complex, as it is generated by the Solidity compiler, which translates high-level programming constructs into low-level, stack-based code. Additionally, the Solidity compiler undergoes frequent updates and modifications, resulting in continuous evolution of bytecode patterns. To address this challenge, we propose using deep learning models to analyze Ethereum bytecodes and infer the compiler version that produced them. A large number of Ethereum contracts and the corresponding compiler versions is …
Digital Beamforming Array Phase Calibration Techniques For Multi-Pass Interferometric Sar, Kelly Cheung
Digital Beamforming Array Phase Calibration Techniques For Multi-Pass Interferometric Sar, Kelly Cheung
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Calibration plays a critical role in the optimal performance of algorithms in digital beamforming arrays. Phase incoherency between elements results in poor beamforming with decreased gain and higher sidelobes, leading to a decrease in accuracy and sensitivity of measurements. A similar problem exists in performing multi-pass interferometric SAR (IFSAR) processing of SAR data stacks to generate topological maps of the scene, where phase errors translate to height errors. By treating each SAR image in the data stack like an element of a uniform linear array, this thesis explores several phase calibration techniques that can be used to calibrate digital beamforming …
Characterization Of Aerosol Jet Printed Silver Thin Films Sintered By A Scanning Laser, William A. Metzger
Characterization Of Aerosol Jet Printed Silver Thin Films Sintered By A Scanning Laser, William A. Metzger
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Direct write printing, which is part of additive manufacturing (AM) technology, offers unique capabilities that can complement traditional methods of electronics fabrication. Printing of electrical interconnects via aerosolization is one of the areas in AM that is very important in electronics fabrication. Post-print sintering is a critical step in printed electrical interconnects because it strongly influences the electrical resistivity of the interconnects. Interconnects require the lowest possible resistivity to achieve better performance. Thermal sintering is the most common technique employed in printed interconnects. However, it is limited to substrates that can handle the high temperature requirement for sintering. For polymers …
Efficient Cloud-Based Ml-Approach For Safe Smart Cities, Niveshitha Niveshitha
Efficient Cloud-Based Ml-Approach For Safe Smart Cities, Niveshitha Niveshitha
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Smart cities have emerged to tackle many critical problems that can thwart the overwhelming urbanization process, such as traffic jams, environmental pollution, expensive health care, and increasing energy demand. This Master thesis proposes efficient and high-quality cloud-based machine-learning solutions for efficient and sustainable smart cities environment. Different supervised machine-learning models for air quality predication (AQP) in efficient and sustainable smart cities environment is developed. For that, ML-based techniques are implemented using cloud-based solutions. For example, regression and classification methods are implemented using distributed cloud computing to forecast air execution time and accuracy of the implemented ML solution. These models are …
Bandgap Engineering Of 2d Materials And Its Electric And Optical Properties, Kumar Vishal
Bandgap Engineering Of 2d Materials And Its Electric And Optical Properties, Kumar Vishal
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Since their invention in 1958, Integrated Circuits (ICs) have become increasingly more complex, sophisticated, and useful. As a result, they have worked their way into every aspect of our lives, for example: personal electronic devices, wearable electronics, biomedical sensors, autonomous driving cars, military and defense applications, and artificial intelligence, to name some areas of applications. These examples represent both collectively, and sometimes individually, multi-trillion-dollar markets. However, further development of ICs has been predicted to encounter a performance bottleneck as the mainstream silicon industry, approaches its physical limits. The state-of-the-art of today’s ICs technology will be soon below 3nm. At such …
Modeling, Simulation, And Hardware Testing Of A Noise-Canceller Adc Architecture, Ethan R. Rando
Modeling, Simulation, And Hardware Testing Of A Noise-Canceller Adc Architecture, Ethan R. Rando
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Analog-to-Digital Converters (ADCs) are essential elements of most complex electronic devices. ADCs allow for an analog signal to be converted into the digital domain, and thus interpreted by a digital circuit or model. While ADCs are extremely common, they are not immune from common tradeoffs when being designed and implemented. The most prominent tradeoff when selecting or designing an ADC is whether to pursue a high conversion rate or a high resolution on the digital output. There are some ADC designs that allow for relatively high resolution while maintaining a respectable conversion rate, however these designs often come at the …
Path-Safe :Enabling Dynamic Mandatory Access Controls Using Security Tokens, James P. Maclennan
Path-Safe :Enabling Dynamic Mandatory Access Controls Using Security Tokens, James P. Maclennan
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Deploying Mandatory Access Controls (MAC) is a popular way to provide host protection against malware. Unfortunately, current implementations lack the flexibility to adapt to emergent malware threats and are known for being difficult to configure. A core tenet of MAC security systems is that the policies they are deployed with are immutable from the host while they are active. This work looks at deploying a MAC system that leverages using encrypted security tokens to allow for redeploying policy configurations in real-time without the need to stop a running process. This is instrumental in developing an adaptive framework for security systems …