Digital Commons Network^™

Impairment Of The Glial Phagolysosomal System Drives Prion-Like Propagation Of Huntington’S Disease, Graham Davis

Theses and Dissertations

The ability of glia to tightly regulate neuronal health and homeostasis in the CNS is conserved across species. Yet, despite the ability to degrade protein aggregates, glia are vulnerable to the accumulation of neurotoxic amyloid aggregates during neurodegenerative disease progress, and even exacerbate their spread. A developing narrative highlights glia as a double-edged sword in neurodegenerative diseases: initially capable of dynamically responding to amyloid aggregate-ladened dying neurons but also capable of inducing chronic inflammation and creating seeding-competent amyloid oligomers. Thus, uncovering the mechanisms that allow glia to control aggregate deposition while preventing the neurotoxic effects and seed generation is vital …

Mri Image Regression Cnn For Bone Marrow Lesion Volume Prediction, Kevin Yanagisawa

Theses and Dissertations

Bone marrow lesions (BMLs), occurs from fluid build up in the soft tissues inside your bone. This can be seen on magnetic resonance imaging (MRI) scans and is characterized by excess water signals in the bone marrow space. This disease is commonly caused by osteoarthritis (OA), a degenerative join disease where tissues within the joint breakdown over time [1]. These BMLs are an emerging target for OA, as they are commonly related to pain and worsening of the diseased area until surgical intervention is required [2]–[4]. In order to assess the BMLs, MRIs were utilized as input into a regression …

Cloud Ecosystem In A Box Security Services, Chirone Gamble Jr

Theses and Dissertations

The recent years have witnessed a remarkable surge in the use of large-scale data analytics, significantly advancing research in data-driven fields [1, 2]. While these innovative technologies offer the promise of accelerated research, they concurrently introduce new security and privacy challenges, complicating collaborative efforts among researchers. These challenges are ubiquitous across various research domains, particularly in the realms of data collection, analysis, and collaboration [3, 4]. Predominantly, existing data collection and analytics platforms prioritize performance over security. This prioritization compels users to rely heavily on their collaborators for adhering to all relevant security and privacy protocols. Often, researchers find themselves …

Kodai: Framework Towards Data Augmentation Of Large Language Models In Machine Learning, Rick Rejeleene

Theses and Dissertations

Machine Learning is rapidly advancing at an incredible pace due to an increase in computational size, and availability of data. Data is the cornerstone of machine learning algorithms. Information quality has a profound impact on the performance of machine learning systems. Supervised, Unsupervised, and Reinforcement learning are three major ways of performing machine learning. Self-supervised learning, part of unsupervised learning, has made breakthroughs in engineering and research by using Large Language Models (LLM). LLM are a type of neural network, used for language understanding and generation. Recently, LLM has taken a distinct lead by demonstrating state-of-the-art capabilities in natural language …

New Mathematics Teachers' Goals, Orientations, And Resources That Influence Implementation Of Principles Learned In Brigham Young University's Teacher Preparation Program, Caroline S. Gneiting

Theses and Dissertations

Research in mathematics education shows that new mathematics teachers struggle to implement reform teaching practices that they learned in their teacher preparation programs. In this study, the researcher observed and interviewed three new mathematics teachers (within five years of graduation) to further explore the question of why new teachers use or do not use what they learned in their teacher preparation program. The study uses an expanded version of Schoenfeld's decision-making theory of Orientations, Goals, and Resources. This theory proved useful in the analysis of the research data, providing a framework to incorporate and organize the numerous reasons suggested by …

Degradation Of The Mechanical Properties And Hydrogen Generation In Cement Under Gamma Irradiation Assessed By Atomistic Simulation, Omar Al Najjar

Theses and Dissertations

Although understanding the effect of the gamma-ray on cement-based materials is essential for many applications, such as the concrete contaminate of nuclear reactors or the storage of radioactive waste in cement-based waste forms, such understanding is still not fully developed. The importance of having such an understanding is becoming of utmost importance, especially with calls to extend the lifetime of nuclear power plants, and also due to some recent incidents of failures of the concrete structure in the nuclear fields. In this work, the details of preparing three molecular models as a representative structure of the main binding phase of …

Performance Analysis And Evaluation Of Image Processing Techniques, Dcnn And Bsn Model For Detection And Classification Of Diabetic Retinopathy, Sudha S

Theses and Dissertations

Diabetes is a disorder that arises when blood sugar level increases. Insufficient secretion of insulin hormone is the ground for the evolution of diabetes, and it affects most of the critical organs in our body. Diabetes causes leakage of blood in the retinal blood vessels, inducing an eye disease, Diabetic Retinopathy (DR). The visual identification of micro features in fundus images makes the clinicians complex and challenging tasks. Therefore, timely diagnosis and proper treatment can prevent eye blindness. This research is proposed to identify and classify diabetic retinopathy using an Image Processing technique, Deep Convolutional Neural Network (DCNN), Biological Sensor …

Usability-Driven Security Enhancements In Person-To-Person Communication, Tarun Kumar Yadav

Theses and Dissertations

In the contemporary digital landscape, ensuring secure communication amid widespread data exchange is imperative. This dissertation focuses on enhancing the security and privacy of end-to-end encryption (E2EE) applications while maintaining or improving usability. The dissertation first investigates and proposes improvements in two areas of existing E2EE applications: countering man-in-the-middle and impersonation attacks through automated key verification and studying user perceptions of cryptographic deniability. Insights from privacy-conscious users reveal concerns about the lack of E2EE support, app siloing, and data accessibility by client apps. To address these issues, we propose an innovative user-controlled encryption system, enabling encryption before data reaches the …

Corporate Green Bond Market In Egypt: Barriers To Market Development, Aya Aly

Theses and Dissertations

Abstract

Green bonds have risen as a crucial financial tool for mobilizing capital for environmentally sustainable projects, aiming to address climate change and promote sustainable development. In Egypt, despite being a pioneer in issuing sovereign green bonds, the corporate bond market remains in its early stages, with relatively low issuance of corporate green bonds compared to other emerging economies. This study focuses on identifying the challenges facing the domestic corporate green bond market. Through interviews with eleven market participants, the analysis revealed general challenges that encompass the entire bond market, including lack of awareness, limited engagement of retail investors, lengthy …

Resisting Internalized Stigma (Ris): Acceptability And Feasibility Of A Cognitive Behavioral Stigma Intervention For Early Psychosis, Francesca Maria Crump

Theses and Dissertations

The clinical high-risk state for psychosis (CHR-P) was created to help identify individuals experiencing early signs of psychosis to help forestall worsening symptoms. CHR-P individuals may experience stigma that may stem from internal or external processes, including from receiving specialized care. Research has demonstrated associations between internalized stigma and psychosocial and functional outcomes, which underscores the need for interventions to help mitigate the impact of stigma while balancing the need for treatment. To date, there is only one stigma intervention specifically designed for individuals designated as CHR-P, which is psychoeducational in nature. Based on the recent call to action that …

Analyzing The Effects Of Data Variability & Volume On Predicting Particulate Matter (Pm2.5): Insights From A Machine Learning Approach, Jada A. Macharie

Theses and Dissertations

Accurately predicting PM_2.5 concentrations are imperative to the future of public health and environmental policies. Machine learning models incorporating spatial and temporal datasets to predict PM_2.5 are often limited by data availability constraints and poor resolution satellite imagery.

Development Of Monitoring Systems Using Computer Vision Techniques For Precise Fish Farming, Abinaya N.S

Theses and Dissertations

Fish farm is a biosystem with diversity and uncertainties demanding, an intelligent manual monitoring process, which is labor-intensive, invasive, costly, discontinuous, and persistent. The proposed work aims to develop Computer Vision (CV) -based monitoring techniques for precise fish farming to address these problems. Three major monitoring operations namely (i) Fish behavior analysis, (ii) Fish Classification (FC) and (iii) Biomass estimation have been investigated.

Fish schooling activity has been monitored using an overhead vision camera. Problems associated with fish occlusion are addressed using the weighted K-means clustering technique which provides an accurate estimation of fish school locations. Temporal variations of these …

Thin-Film Nanocomposite Membranes With Alumina Nanoparticles For Textile Wastewater Treatment Applications, Amr Mohamed Tayel

Theses and Dissertations

Thin-film nanocomposite (TFN) membranes are gaining great interest in industrial wastewater treatment due to their superior performance, especially for higher water flux and pollutants’ rejection, as well as improved chemical, thermal and mechanical stabilities, compared to other types of membranes. The performance of TFN membranes can be enhanced using different types of nanofillers, among which ceramic nanomaterials, such as Al2O3, offer a promising potential for applications involving treatment of industrial wastewater such as textile effluents, and this is due to their stability, hydrophilicity, and relative low cost. The study of the TFN membrane properties and structure allows the optimization and …

Exploring Ngos’ Perspectives And Their Role In Education Reform In Egypt, Ioanna Moriatis

Theses and Dissertations

This exploratory study elicits NGO perceptions regarding Egypt’s Ministry of Education and Technical Education’s (MOETE) reform efforts, their interest in participating in education reform and policy advocacy, and their existing relationship with the ministry. Drawing on the findings from semi-structured, in-depth interviews with 13 representatives of education NGOs based in Cairo and Giza, this thesis takes a qualitative approach toward answering the following research question: How do NGOs targeting K-12 youth perceive their role in shaping education reform in Egypt? Despite having to navigate a host of obstacles to accessing public schools and working with the MOETE, the NGOs represented …

Cardiac Active Tension Modeling Via Genetic Algorithm-Optimized Fractional Order Systems, Afnan Khaled Elhamshari

Theses and Dissertations

Developing a computational model to model cardiac activity has been increasingly important in recent decades. Accurate cell-level active tension modeling for cardiomyocytes is critical to understanding cardiac functionality on a patient-specific basis and developing an effective in-silico cardiac model. However, cell-level models in the literature fail to account for viscoelasticity and inter-patient variations in active tension. This research proposes a genetic algorithm-optimized, fractional order system to model cell-level active tension by extending Land’s state-of-the-art model of cardiac contraction. The model features the (left) Caputo derivative of six state variables that identify the mechanistic origins of viscoelasticity in a myocardial cell …

A 3d Imaging-Based Critique Of Wire Arc Additive Manufacturing (Waam) Simulations, Omar Oraby

Theses and Dissertations

Residual stresses play a critical role in the mechanical behavior and structural integrity of engineered components. Understanding and quantifying these stresses are essential for ensuring the reliable performance and durability of materials and structures. Traditionally destructive methods are used that involve sample sectioning and material removal. However, non-destructive methods have gained popularity due to their advantages in preserving the specimen's integrity for further testing and material waste reduction. Among these techniques, Digital Image Correlation (DIC) stands out as a powerful non-contact and full-field measurement approach. DIC captures displacements and strain distributions by analyzing the deformation of speckle patterns on the …

The Effect Of Mechanical Strain On The Electronic Conductivity Of Α- Fe2o3: A Density Functional Theory Study, Sheriff Naziru Abdulmutalib

Theses and Dissertations

Hydrogen has emerged as a promising future energy carrier due to its ability to produce zero carbon dioxide (CO2) emissions when burned. However, the limited natural abundance of hydrogen necessitates the development of cost-effective and environmentally friendly methods for large-scale hydrogen production. Among the different hydrogen production approaches, photoelectrochemical water splitting, which employs a photoanode material in a cell using solar energy to split water into hydrogen and oxygen, is the focus of this work. α-Fe2O3 (hematite) is a photoanode material that shows a promising future for hydrogen generation in a photoelectrochemical cells due to its cheapness, availability, and its …

Triberta And Beyond: Redefining Entity Resolution With Large Language Models, Bi Foua

Theses and Dissertations

Entity resolution (ER) plays a pivotal role across domains by enabling data integration and quality improvement. This dissertation delves into the evolving landscape of ER, introducing innovative approaches that redefine this fundamental task. The first contribution is TriBERTa, a novel representation learning model tailored for ER. TriBERTa sets new benchmarks in entity matching and demonstrates versatility across ER processes like data blocking and resolution. Empirical evaluations on diverse datasets showcase TriBERTa’s superior performance over existing representations, including from large language models. The second contribution explores the use generative language models like GPT-3.5 and Dolly 2.0 for cross-domain entity matching using …

Spectrum Of The Lakes: Unveiling Water Color Of Minnesota's Sentinel Lakes With Satellite Remote Sensing For Water Quality Monitoring., Andrew J. Dooley

Theses and Dissertations

Surface waters are precious natural resources requiring costly time and labor for effective water quality monitoring. New applications of water color analysis by satellite remote sensing are a promising approach to water quality monitoring for scientific, industrial, recreational, and cultural benefit. Water color is an inherent proxy of ecological health and water quality. This research expands previous applications of lake water color analysis and pioneers water color chromaticity analysis for midcontinent lakes in Minnesota, USA. The results of this project are the first accounts of Minnesota’s Sentinel Lake water color, variability of water color by ecoregion, and temporal consistency of …

Analyzing Novel Metal Alloys For Glucose Sensing And Electrocatalysis, Anna Grace Boddy

Theses and Dissertations

In pharmaceutical and medicinal chemistry, metals and metal alloys often receive less attention compared to biological or organic compounds due to many factors including toxicity in the body for drug development or the cost of these metals. However, metals can play an important role in pharmaceuticals, having an impact on original cancer drugs, such as platinum used for head and neck tumors. Electrocatalysis is also another topic that receives less attention over topics such as chromatography in pharmaceuticals due to its potential toxic catalysts and voltages that could be harmful to the body. Electrocatalytic sensors can play an important role …

Elastin-Like Polypeptide As A Model To Study Intrinsically Disordered Proteins, Sadegh Majdi

Theses and Dissertations

The elastin-like polypeptide (ELP) is a well-studied structural protein that is easily amenable to amino acid (AA) sequence modifications and has the potential to yield a wide variety of uses in bioengineering and biomedical applications. One unique property of ELP is the inclusion of intrinsically disordered domains (IDP) within the structure that allow for its diversity of physical properties. While it is generally understood that amino acid sequence dictates protein folding arrangements, the contributions of specific amino acid sequences to the intrinsic disorder of ELP has yet to be fully resolved. Therefore, identifying the contributions of specific amino acid sequences …

Unveiling The Unique Ras Isoform And Domain Specific Regulation Of Braf Kinase, Tarah Trebino

Theses and Dissertations

BRAF kinase is a key member of the MAPK pathway, important for cell growth and division. Upstream signals promote BRAF activation by interaction with the membrane bound GTPase, RAS, which leads to relief of autoinhibition and dimerization. The N-terminal regulatory domains of BRAF, including the BRAF specific region (BSR), the RAS binding domain (RBD), and the cysteine rich domain (CRD), govern the conformational state of the cytosolic, autoinhibited monomer and drive the RAS-RAF interaction. Active BRAF phosphorylates and activates its substrate MEK, which in turn phosphorylates and activates ERK. Mutations in RAS and BRAF are the cause of many cancers …

Behavioral Effects Of Novel Treatments For Pain Using Different Pathways, Danya M I Aldaghma

Theses and Dissertations

Pain is defined as an unpleasant sensation that is mostly caused by a stimulus from our surroundings. This sensation has the potential to become a significant concern, disrupting daily activities, and diminishing overall quality of life. However, it could also hold significant importance as it serves as a protective mechanism. Pain acts as an alarm system for the human body, alerting it to potentially harmful situations where tissues may be at risk of damage1. Despite the considerable advancements in pain treatment and the extensive knowledge scientists possess regarding the pathophysiology and pathways of pain, numerous medications aimed at alleviating pain …

Investigation Of Machine Learning Driven Adaptive Control Strategy For Heat Exchanger Under Varying Fouling Conditions, Reshma Madhu Pk

Theses and Dissertations

Fouling is an undesirable and inevitable phenomenon that affects Heat Exchanger (HE) dynamics, increases maintenance cost (>50%), and loss of production. Conventional fouling prediction and control techniques demand an in-depth understanding of the HE-specific fouling dynamics. Hence, machine learning emerges as an ideal tool for learning the fouling process from the available measurement dataset.

The proposed work aims to design a machine learning-driven adaptive control technique for an industrial HE, subjected to varying fouling conditions. Naphtha cooler, an industrial HE utilized in petroleum refineries, employs cooling water to lower Naphtha temperature, but the high impurities in the recycled cooling …

Deep Learning Model Compression On Edge Devices For Audio, Afsana Rahman Mou

Theses and Dissertations

Audio classification plays a crucial role in interpreting and understanding soundscapes, enabling applications like voice assistants, sound event detection, and music analysis. However, deploying deep learning models for audio classification on edge devices presents significant challenges. These models often require substantial computational resources and memory, which are limited on edge devices. Balancing performance, efficiency, and accuracy remains a key hurdle in this field. In this research, we explore various deep learning architectures, including Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and Audio Spectrogram Transformer (AST), for the purpose of audio classification on the ESC 50 and Audio Set datasets. …

Synthesis And Characterization Of Bio Based Amphiphilic Molecules, Vandana Singh

Theses and Dissertations

Among various molecular self-assemblies, low molecular weight gelators (LMWGs), that can form gels in organic solvents/water/oils, have gained much research attention due to their huge potential applications. Generally, gels are soft nanomaterials formed by the self-assembly of amphiphilic molecules into a three-dimensional fibrous network entrapping the solvent.

As these gels are formed by self-assembly via non-covalent interactions they are reversible and differ from macromolecular gels. To synthesize LMWGs, biomolecules such as fats, oils, fatty acids, lignocelluloses, sugars, amino acids, and peptides are commonly used as their inherent property favors self-assembly. In the current scenario, interest in synthesizing bio-based gelators has …

An Analysis Of Fathers’ And Toddlers’ Behaviors During Shared Book Reading, Caitlin Marie Kelly

Theses and Dissertations

Shared book reading interactions between parents and their children have been studied to draw correlations to a child’s vocabulary growth, language development, mathematical scores, and socioemotional skills. However, there is a lack of research regarding fathers’ and toddlers’ engagement and behaviors during shared book reading interactions. The current study investigated and analyzed father and toddler interactions during shared book reading. The data was collected from a larger longitudinal study. Seven father-child dyads participated in the study (Mage = 35 years; range = 30-43 years). The children included four males and two females, and up to two videos were collected for …

Open System Neural Networks, Bradley Hatch

Theses and Dissertations

Recent advances in self-supervised learning have made it possible to reuse information-rich models that have been generally pre-trained on massive amounts of data for other downstream tasks. But the pre-training process can be drastically different from the fine-tuning training process, which can lead to inefficient learning. We address this disconnect in training dynamics by structuring the learning process like an open system in thermodynamics. Open systems can achieve a steady state when low-entropy inputs are converted to high-entropy outputs. We modify the the model and the learning process to mimic this behavior, and attend more to elements of the input …

Integrated Computer-Aided Design, Experimentation, And Optimization Approach For Perovskites And Petroleum Packaging Processes, Swapana Subbarao Jerpoth

Theses and Dissertations

According to the World Economic Forum report, the U.S. currently has an energy efficiency of just 30%, thus illustrating the potential scope and need for efficiency enhancement and waste minimization. In the U.S. energy sector, petroleum and solar energy are the two key pillars that have the potential to create research opportunities for transition to a cleaner, greener, and sustainable future. In this research endeavor, the focus is on two pivotal areas: (i) Computer-aided perovskite solar cell synthesis; and (ii) Optimization of flow processes through multiproduct petroleum pipelines. In the area of perovskite synthesis, the emphasis is on the enhancement …

Art In The Age Of Algorithmic Automation And Artificial Intelligence, Milly Skellington

Theses and Dissertations

The 21st century is examined in order to understand how the artists tools have gained unprecedented autonomy.