Digital Commons Network^™

Engineering Microphysiological Systems To Investigate Cellular Responses To Biophysical Cues In Human Tissue Microenvironments, Mehran Mansouri

Theses

Cells constantly sense and respond to biophysical cues in their microenvironment. Understanding how they interpret these mechanical signals is essential for advancing tissue modeling, studying disease mechanisms, and developing more predictive in vitro platforms. This dissertation presents a series of engineered microphysiological systems (MPS) designed to investigate how mechanical stimuli shape cellular behavior in distinct human tissue microenvironments. In Aim 1, I developed a reconfigurable microfluidic platform that mimics key features of human vascular barriers. This system supports the integration of porous membranes, 3D hydrogels, and flow channels, enabling precise control over both mechanical and biochemical cues. The modularity of …

Mechanisms For Oxygen Vacancy Defect Migration In Srtio3/Nio Heterostructures, Anish Rajesh More

Theses

Perovskite-based oxide heterostructures display promising properties resulting from interface phenomena, making them good candidates for next-generation solid oxide fuel cell electrolytes. Amongst the different features exhibited by these interfaces, misfit dislocations play an important role in influencing ionic transport, yet their role remains poorly understood, which is the case in rock salt-perovskite interfaces too. In SrTiO3/NiO heterostructures, to comprehend interface ionic transport, we investigate oxygen vacancy migration near misfit dislocations. To this end, we developed a high-throughput framework that integrates atomistic simulations with nudged elastic band method to predict migration energy barriers across disparate interface atomic environments. By comprehensively mapping …

Investigating Hardware Injections In Ligo O3 Data: Simulated Signals From A Neutron Star In A Low-Mass X-Ray Binary, Jediah Gofhaone Tau

Theses

Simulated continuous gravitational wave (CW) signals, called hardware (HW) injections were added to the data in the LIGO detectors' third observing run (O3), including two periodic signals mimicking a spinning neutron star in a binary system, similar to the Low-Mass X-Ray Binary (LMXB) Scorpius X-1 (Sco X-1). Using a cross-correlation pipeline, which searched for CWs from Sco X-1 in O3, we searched for these HW injections, using an uncertainty around the true signal parameters akin to the uncertainty associated with the parameters of Sco X-1. One of the signals, residing in the 230-235 Hz frequency band, was detected. The other …

Parsing Of Math Formulas And Chemical Diagrams Using Graph-Based Representation And Attention Models, Ayush Kumar Shah

Theses

Mathematical formulas and chemical diagrams appear frequently in scientific documents but are often embedded as visual content, either rasterized or vector-based images, limiting their accessibility and automated analysis. This thesis aims to bridge this gap by presenting a graph-based visual parsing framework that recognizes and parses these notations from both vector and raster image inputs in digital documents. For mathematical formulas in born-digital PDFs, we construct Symbol Layout Trees (SLTs) using a graph defined over vector-based primitives, capturing spatial relationships, avoiding relying on OCR. For born-digital chemical diagrams, we introduce a Minimum Spanning Tree (MST)-based technique that extracts molecular structure …

Modeling Femtosecond Laser Interaction With Glass For Optical Fabrication, Nathan Klein

Theses

The fabrication of precision optics is critical for a wide range of applications, including biosensors, virtual and augmented reality, medical imaging, and micro-electronics. However, it is challenging to meet the demands of these applications with conventional chemical and mechanical fabrication methods, as they can introduce chemical waste, mid-spatial-frequency errors, and subsurface damage that degrades image quality. Femtosecond lasers have emerged as a promising alternative, offering fast, non-contact, and chemical-free machining with single digit nanometer precision. This thesis presents a computational model designed to investigate the interaction process between a high-intensity femtosecond laser pulse and dielectric material. A pulse propagation model …

Observational Predictions For Convective Common Envelopes, Nikki Noughani

Theses

Common envelopes (CEs) are thought to be the main method for producing tight binary systems in the universe, as the orbital period shrinks by several orders of magnitude during this phase. Despite their importance for many stellar evolution channels, direct detections are rare, and thus observational constraints on common envelope physics are often inferred from post-CE populations. Recently, galactic population observations suggest that the CE phase must be highly inefficient at using orbital energy to drive envelope ejection for low-mass systems and highly efficient for high-mass systems. Such a dichotomy has been explained by an interplay between convection, radiation, and …

Multi-Point And Multi-Station Orbit Propagation For Non-Functional Drifting Geo Satellites, Hritik Mitra

Theses

Currently, there are thousands of man-made space objects that are orbiting the Earth. These satellites serve a host of essential purposes (scientific research, technical applications, services) and they are all required to remain within their mission parameters. Most critical for them is to maintain the orbital parameters that are specified to achieve a particular mission’s objectives. If a satellite deviates beyond a certain limit, there is not only a risk of mission failure but there is a major hazard for possible collisions with other objects such as active satellites, space debris and even natural objects in some cases. There is …

Investigation And Prediction Of Excessive Water Production In Bottom Water-Drive Naturally Fractured Reservoirs Using Machine And Deep Learning, Sami Abderraouf Belkhir

Theses

Naturally Fractured Reservoirs (NFRs) are characterized by dual-porosity and dual-permeability systems, posing significant challenges in managing water production due to highly conductive fracture networks that facilitate rapid water migration from bottom aquifers, often bypassing oil stored in the matrix, thus resulting in early water breakthrough and water channeling phenomena. The main objective of this thesis is to develop and validate deep learning and machine learning models to predict water production, water breakthrough time (tbt), and ultimate water cut (WCult) in NFRs, thereby enabling more effective reservoir management strategies. This work also aims to evaluate the sensitivity of water behavior to …

Measurement And Improvement Of Photon Identification Efficiencies Using Machine Learning Techniques In The Atlas Detector At The Lhc, Abdulla Esam Mahboub

Theses

Photons play a crucial role in numerous analyses at the Large Hadron Collider (LHC), particularly in studies like the Higgs boson decay to two photons. Precise photon identification is essential for enhancing the sensitivity and accuracy of such measurements. This thesis focuses on the development of a machine learning (ML)-based photon identification algorithm to improve the photon identification efficiency within the ATLAS detector, using a Deep Neural Network (DNN) approach. The primary goal is to boost photon identification efficiency by using advanced neural network techniques. Traditional photon identification relies on cuts applied to shower shape variables, which can limit the …

Associations Between Vitamin D Deficiency And Sociodemographic Factors, Lifestyle Behaviors, And Metabolic Conditions: A Cross-Sectional Study From The Hnnhs In Greece, Asmae Mohamad Sadek

Theses

Vitamin D deficiency (VDD) is a widespread global health concern associated with various sociodemographic, lifestyle, dietary, and metabolic factors. While previous studies examined VDD in Greece, few provided a comprehensive analysis across multiple determinants using representative national data. This study aimed to assess the prevalence and predictors of VDD among Greek adults and to examine its associations with sociodemographic, dietary, behavioral, and metabolic variables using data from the Hellenic National Nutrition and Health Survey (HNNHS). A cross-sectional analysis was conducted among 978 adults (≥19 years) from the HNNHS. Serum 25-hydroxyvitamin D [25(OH)D] concentrations < 20 ng/mL were defined as deficient and ≥20 ng/mL as normal. The median age of participants was 40.2 years, and 62.0% were female. The overall prevalence of VDD was 46.0%, with the highest rate observed among adults aged ≥60 years (62.2%). VDD was significantly associated with older age (p < 0.001), retirement status (62.9% among retired; p < 0.001), low and sedentary physical activity (32.7% and 32.6% vs. 50.8% among highly active; p < 0.001), higher HDL (median 52.0 vs. 49.0 mg/dL among VDD vs Normal; p = 0.001), elevated serum calcium (median 9.4 vs. 9.2 mg/dL among VDD vs Normal; p = 0.020), and lower insulin levels (median 7.5 vs. 8.0 μIU/mL among VDD vs Normal; p = 0.044). Dietary intake (total energy and macronutrients) and body composition were not significantly associated with VDD. In the multivariate model, significant independent predictors of VDD included being retired (AOR = 2.383; 95% CI: 1.596–3.558; p < 0.001), having higher serum calcium levels (AOR = 1.563; 95% CI: 1.078–2.266; p = 0.019), and higher HDL levels (AOR = 1.016; 95% CI: 1.005–1.027; p = 0.001). Physical activity level was also a key determinant; participants classified as sedentary or low active had significantly higher odds of deficiency compared to highly active individuals (AOR = 0.468; 95% CI: 0.319–0.690; p < 0.001). This counterintuitive result may be influenced by factors such as increased indoor physical activity, and warrants further investigation. Dietary intake and body composition were not significantly associated with VDD. The findings underscore the importance of incorporating sociodemographic and lifestyle factors into prevention strategies. Interventions should particularly focus on older adults, retired individuals, even if they have higher HDL and calcium levels, and are physically active.

Exploring The Quality Of Professional Development In Addressing Challenges With Behavior Management Of Special Needs Students In Inclusive Classrooms: An Instrumental Case Study, Reem Hussein Abuwatfa

Theses

Inclusive education has become a major educational priority globally and within the United Arab Emirates (UAE), driven by policies promoting the full participation of students with special educational needs (SEN) in inclusive classrooms. This study explores how elementary-level general education teachers perceive the quality of professional development (PD) in addressing their challenges with behavior management of students with SEN in inclusive classrooms. A qualitative case study approach was used, utilizing semi-structured interviews. The findings indicated that teachers face challenges from the behavioral issues of SEN students in inclusive classrooms, affecting both typical peers and teachers. Moreover, teachers had mixed perceptions …

Data-Driven Machine Learning Applications For Predictive Modeling Of Petrochemical And Ecofriendly Systems, Noora Saleh Al Mansoori

Theses

Traditional experimental approaches in industrial processes, such as Fourier Transform Infrared Spectroscopy (FTIR) spectroscopy, thermogravimetric analysis (TGA), and well-drilling operations, are often constrained by time, cost, and operational limitations. This research explores the application of data-driven Machine Learning (ML)-based predictive modeling to improve efficiency and reduce dependency on resource-intensive experimentation. The study develops ML models for three distinct processes: FTIR intensity prediction of bitumen thermal cracking products, thermal degradation of Medium-Density Fibreboard (MDF) using TGA data, and Rate of Penetration (ROP) prediction in petrochemical industry. Six algorithms: Linear Regression (LinReg), Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), Gradient …

Design Of A Deployable Rolled Antenna System For Satellite Applications, Ashwaq Abdulla Alkaabi

Theses

This project presents the development of a deployable Synthetic Aperture Radar (SAR) antenna designed for a 16U CubeSat platform. The primary challenge in SAR satellite design lies in the need for large antennas to achieve high-resolution imaging, which traditionally results in increased satellite size and cost. To address this, the proposed solution employs a scalable 4 × 21 patch antenna array operating at 1.275 GHz, fabricated on a flexible Polyimide-based Printed Circuit Board (PCB). This flexible PCB allows the antenna to safely roll during deployment, avoiding damage and facilitating compact storage. However, Polyimide poses challenges due to higher losses and …

Numerical Methods For Approximating Line Integrals Over Implicitly Defined Curves, Raghd Alsaadawi

Theses

In this thesis, we develop and investigate a predictor-corrector method for the numerical tracing of implicitly defined curves. The study begins with the introduction of modified numerical integration techniques — specifically, the modified trapezoidal and modified midpoint rules — for evaluating the line integral of a vector field along an implicitly defined curve. Furthermore, we explore higher-order methods aimed at improving the accuracy of such integrals. Theoretical and numerical results, including asymptotic error expansions, are presented to support the analysis. In addition, several numerical experiments are carried out to illustrate the effectiveness and robustness of the proposed approaches.

Wavelet-Based Multi-Step Methods For Systems Of Differential Equations, Rashad Assad Hijji

Theses

Wavelets have been widely used in many areas of engineering and mathematics, including the development of multistep algorithms to solve initial value problems (IVPs) in the context of the Galerkin method using Daubechies' wavelets. The main scope of our work is to build a comprehensive framework for solving Systems of Differential equations using the compactly supported wavelets proposed by I. Daubechies. Wavelets are mathematical functions that decompose data into distinct frequency components, and each element is analyzed with a resolution that matches its scale. Compact support of Daubechies wavelets is key in allowing them to be computationally efficient for high-dimensional …

Electrospun Membranes From Bio-Renewable Poly (Ethylene Furanoate)/Poly (Ethylene Teraphthalate) (Pef/Pet) Blend For Emulsification Application, Aya Ismat Sayed

Theses

This thesis focuses on manufacturing electrospun fibrous membranes from a blend of poly (ethylene terephthalate) and poly (ethylene furanoate) and using in premix emulsification. Poly (ethylene furanoate), which is a 100% bio-renewable polymer being blended with synthetic poly (ethylene terephthalate) for membrane fabrication contributes towards sustainability in the production of food and pharmaceutical emulsions. The primary objective of this research is to optimize the fabrication conditions of poly (ethylene terephthalate)/poly (ethylene furanoate) porous membranes, characterize their properties, and evaluate their performance in emulsification. This study compares poly (ethylene terephthalate) / poly (ethylene furanoate) blend membranes with individual poly (ethylene terephthalate) …

The Virgin Of Guadalupe And The Liminality Of Pregnancy, Jason Oosting

Theses

This thesis suggests that the image of the Virgin of Guadalupe, during the Colonial Period, provided the diverse population of colonial New Spain (and, in particular, Mexico City/Tenochtitlán) with an image that functioned to unify even some of the most seemingly disparate belief systems, those of Christian Spaniards and Indigenous Nahuatl traditions. More specifically, this thesis argues that this unification was achieved because the image of the Virgin of Guadalupe in the 16th and 17th centuries was likely understood as representing a divine pregnant woman to many colonial viewers—a state that bound viewers, both Spanish and Indigenous alike, to shared …

Personifying The Goddess: Contrasting Representation Of The Deified Body In Feminist Art, Kelly Lorraine Phillips

Theses

Goddess imagery, the representation of a female deity or a concept of divine feminine power through various forms, symbols, and narratives, has been used by artists to communicate a multitude of sentiments, from spiritual reverence to political ideology. This study probes the evolution of representations of the deified female body from the 1970s to the current era to reveal contrasts in how these icons of female power have transformed over time. The artwork of second-wave feminist and self-identified “Goddess artist” Mary Beth Edelson is examined as a foundation for second-wave Goddess sentiment. Edelson’s collage work, which incorporates figures from a …

Experimental Evaluation Of Novel Nano Polymer Hybrid Enhanced Oil Recovery In Carbonate Reservoir, Altamish Ahmed Pakeer

Theses

Innovative enhanced oil recovery (EOR) strategies are needed to unlock additional reserves in heterogeneous, oil-wet carbonate reservoirs. This study evaluates hybrid nano-polymer flooding by integrating silica nanoparticles (SiO₂) and single-walled carbon nanotubes (CNT) with novel HPAM polymers (Sav10 and Sav10 VHM) to optimize wettability alteration, rheological parameters, and recovery mechanisms.

A comprehensive experimental approach was employed, where rheological tests assessed viscosity enhancement under varying shear conditions, and wettability alteration was quantified via contact angle measurements using HPAM-SiO₂, HPAM-CNT, Sav10 VHM-SiO₂, and Sav10 VHM-CNT systems. Core floods were performed in three consecutive phases; waterflooding (baseline), standalone nanoparticle flooding, and hybrid nano-polymer …

Advancing Academic Advising With Knowledge Graphs: Integrating Machine Learning And Llms For Personalized Course Planning, Sara Alshamsi

Theses

Academic advising plays a critical role in helping students make informed decisions, improve academic performance, and successfully navigate their university journey. However, with increasing university enrollment, traditional advising methods often struggle to scale, leading to student frustration and overburdened advisors. Additionally, designing course offerings that match student demand is a complex and error-prone process involving multiple stakeholders. To address these challenges, this thesis proposes an automated, data-driven system for generating personalized academic plans for students. The primary aim of this thesis is to develop a system that reduces students’ dependency on advisors while simultaneously providing accurate estimates of course demand …

Utilizing Date Fruit Pomace As A Corrosion Green Inhibitor For Non Ferrous Alloys, Sardor Rustam Odilov

Theses

This thesis explores a novel green corrosion inhibitor derived from date fruit pomace extract (DFPE) for the protection of aluminum alloy 3003 in highly corrosive environments, specifically hydrochloric acid (HCl) and natural seawater. The central aim is to promote the sustainable reuse of agro-waste as an effective and eco-friendly alternative to conventional toxic inhibitors, aligning with environmental and industrial safety goals.

A comprehensive methodology was employed, including Soxhlet extraction (using both non-polar n-hexane and polar methanol-water solvents), rotary evaporation, and FTIR analysis to identify the active functional groups responsible for inhibition. Corrosion behavior was systematically evaluated using both mechanical (weight …

A Novel Framework For Dynamic Graph Representation Learning With Mamba, Ashish Pandey

Theses

Dynamic graph embedding is a key technique for modeling temporal dependencies in evolving networks. While transformer-based models perform well, their quadratic complexity limits scalability on long graph sequences. This thesis compares transformer approaches with the Mamba architecture-a linear-complexity state-space model—for temporal graph embedding.

Two frameworks are proposed: DG-Mamba and GDG-Mamba. DG-Mamba uses standard GCN-based spatial encoding, while GDG-Mamba incorporates domain-aware edge features using Graph Isomorphism Network with Edge Convolution (GraphGINE). Experiments on UCI, Reality Mining, Slashdot, Bitcoin-OTC, and SBM datasets show that Mamba-based models match or exceed transformer performance, especially on graphs with high temporal variability.

The thesis also applies …

Gamified Gait Rehabilitation Via Real-Time Biofeedback And Adaptive Hip-Exoskeleton Control, Mariya Huzaifa Tohfafarosh

Theses

Gait impairments arise from systemic diseases, age-related degeneration, musculoskeletal dysfunctions, or neurological conditions. While traditional rehabilitation can be effective, they often face challenges such as high costs, inaccessibility, and low patient engagement. To address these challenges, my work introduces a virtual reality-based rehabilitation (VRBR) system, integrating real-time motion and electromyographic (EMG) muscle activation feedback with a gamified virtual environment for enhanced adaptability and engagement. The system includes a custom-designed hip-exoskeleton that provides adaptive spring-like assistance or resistance, supporting both mobility-impaired users and strength training. Assistance levels can be tuned to match the user's progress. Additionally, a custom pressure insole was …

Analytical Studies Of Black Hole Systems, Alessandro Ciarfella

Theses

This work includes a series of analytical projects aimed at providing accurate initial data parameters for full Numerical Relativity evolutions of binary black holes (BBH), allow the evolution of multiple black hole systems, and the interpretation and modeling of high- energy collision of black holes. We first describe how to obtain accurate initial data for the evolution of BBH by extending the determination of quasi-circular orbital parameters described in [1] to 3.5PN, and by incorporating the small mass ratio limit by explicitly including the Schwarzschild and Kerr limits [2]. We then focus on eccentric binary black hole systems, developing a …

Predicting Patient No-Show Rate In Healthcare To Improve Operational Excellence, Saeed Ahmed Al Wari

Theses

The challenge of integrating no-show predictive models into healthcare environments is complex and multifaceted, extending far beyond the distinct technical challenge of building accurate models. This thesis will discuss more on the subject of incorporating machine learning into healthcare. While algorithmic accuracy and model validation are critical, they are a mere sub-system of a much larger operational, technological, ethical, legal and human ecosystem. Predictive models face mass deployment in healthcare systems which are complex networks of stakeholders across strict regulatory frameworks and deeply embedded workflows (AlMuhaideb et al., 2019). However, for these models to result in long term and real …

Future Of Inclusive Education In The Uae: Supporting Learning Disabilities In Higher Education, Christina Ayub

Theses

Inclusive education is a critical component of higher education, ensuring that students with learning disabilities (LDs) receive equitable access to academic opportunities and institutional support. While global advancements in inclusive education have been significant, the UAE’s higher education sector faces unique challenges in accommodating students with LDs, particularly as technological disruptions, demographic shifts, and evolving policies reshape the broader educational landscape. This research investigates how a higher education institution in the UAE, such as RIT Dubai, might adapt its support systems for students with LDs, such as ADHD, dyslexia, dyscalculia, dysgraphia, and dyspraxia, under a range of plausible future conditions …

Transmit And Deceive: Addressing The Insider Threat To Beacon Security, Noah Troy

Theses

IEEE 802.11 Beacon frames exist at the forefront of modern Wi-Fi networks and facilitate a wide array of essential network functionality, from discovery to time synchronization and even transmit power control. However, the central role Beacon frames play in initial network advertisement comes at the price of incomplete security guarantees, leaving these frames historically vulnerable to forgery and granting significant leverage over proximal wireless devices to a malicious actor that can effectively spoof them. With the publication of IEEE Std 802.11-2020, beacon protection was introduced to enable the authentication of received Beacon frames, placating most concerns. However, beacon protection is …

On The Use Of Nonlinear Electrophoresis For Separating Particles And Cells In Insulator-Based Electrokinetic Systems, Alaleh Vaghef-Koodehi

Theses

The increasing demand for efficient separation processes of micron-sized particles, including microorganisms, highlights the importance of developing low-cost, non-labor-intensive, and time-efficient techniques. Insulator-based electrokinetic (iEK) systems have proven to be a practical alternative to bench-scale methodologies such as centrifugation and membrane filtration. Several studies have reported the separation of microparticles by employing direct current (DC) voltages. However, all of them have overlooked the phenomenon of nonlinear electrophoresis (EPNL) and its role in the electrokinetic migration of particles. This study combines mathematical modeling and experiments to extend the capabilities of iEK systems. This dissertation has four aims: (1) to separate microparticles …

Peach Street, Anastasia Lawrence

Theses

Peach Street connects to the universal phenomenon of losing innocence of childhood and navigating the perils and disappointments of the adult world and visualizes my ongoing experience with anxiety and what psychiatrists call derealization, the feeling of being detached from reality. Set in the same location as where I first felt immense panic, my photos create a fictional narrative where a small town, its residents, and the environment are being controlled by a force emanating from the town’s lake. The lake’s aura blinds the residents to its control, forcing them to live in a set way without personal expression or …

Wooden Spatial Analogies: Playful, Transformative Design Process Kit With Inclusion In Mind, Sarah R. Baxter

Theses

This paper concerns solutions to insufficient support in educational inclusivity through the subject of the five design process steps. It leverages the insights of researchers, such as Linda Silverman, regarding ‘visual-spatial learners’, individuals who perceive the world through images rather than words and thrive in navigating complex tasks, yet often face challenges with linear, step-by-step processes. This work critiques the conventional educational methods that frequently overlook the profound potential of spatially adept students. A final prototyped solution was assembled. The outcome was shaped, sanded, and painted wooden spatial analogies of play, designed for rearrangement, and interactively representative of the design …