Physical Sciences and Mathematics Commons^™

Towards A Practical Method For Monitoring Kinetic Processes In Polymers With Low-Frequency Raman Spectroscopy, Robert Vito Chimenti

Theses and Dissertations

Unlike liquids and crystalline solids, glassy materials exist in a constant state of structural nonequilibrium. Therefore, a comprehensive understanding of material kinetics is critical for understanding the structure-property-processing relationships of polymeric materials. Amorphous materials universally display low-frequency Raman features related to the phonon density of states resulting in a broad disorder band for Raman shifts below 100 cm-1, which is related to the conformational entropy and the modulus. This disorder band is dominated by the Boson peak, a feature due to phonon scattering because of disorder and can be related to the transverse sound velocity of the material, and a …

Development Of Salinomycin Derivatives As Potential Anticancer Agents, Viren Soni

Theses and Dissertations

Salinomycin is a poly-ionophore antibiotic that was originally isolated from Streptomyces albus by Miyazaki and colleagues from Kaken Chemicals Co., Ltd., Tokyo, Japan. Salinomycin exhibits antimicrobial activity against Gram-positive bacteria including Bacillus subtilis, Staphylococcus aureus, Micrococcus flavus, Sarcina lutea, Mycobacterium spp. Some filamentous fungi, Plasmodium falciparum, and Eimeria spp. as well as protozoan parasites responsible for the poultry disease coccidiosis. Hence, it is used in veterinary medicine. In 2009 Gupta et al demonstrated that salinomycin selectively killed human breast cancer stem cells (CSCs) with great efficacy, and the mechanism of action of this novel CSCs molecule was explored. To name …

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 …

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 …

Enhancing Inter-Document Similarity Using Sub Max, Richard Imorobebh Igbiriki

Theses and Dissertations

Document similarity, a core theme in Information Retrieval (IR), is a machine learning (ML) task associated with natural language processing (NLP). It is a measure of the distance between two documents given a set of rules. For the purpose of this thesis, two documents are similar if they are semantically alike, and describe similar concepts. While document similarity can be applied to multiple tasks, we focus our work on the accuracy of models in detecting referenced papers as similar documents using their sub max similarity. Multiple approaches have been used to determine the similarity of documents in regards to literature …

Dynamic Regulation Of Store-Operated Calcium Entry By Protein S-Acylation, Goutham Kodakandla

Theses and Dissertations

Calcium plays a pivotal role in many physiological functions in cells. Cytosolic calcium levels are finely tuned by calcium ion channels, pumps, and intracellular organelles. Store-operated calcium entry (SOCE) is when depletion of endoplasmic reticulum (ER) calcium stores activates a calcium sensor known as stromal interaction molecule 1 (STIM1). Activation of STIM1 leads to a conformational change from a compact state to an extended state. This extended state of STIM1 allows it to bind to a calcium channel in the plasma membrane (PM) known as Orai1. The binding of Orai1 and STIM1 leads to opening of Orai1 channels and calcium …

Fundamental Study Of Ionic Liquid Physicochemical Effects On Thermal Stability Of Model Biological Macromolecules, Austin Keith Clark

Theses and Dissertations

Ionic Liquids (ILs) are substances with a unique physical attribute compared to that of solid ionic salts. At room temperature, ILs are molten salts that have a variety of physical effects that can play a role in their impact on other molecules, as solvents or solutes. They can play the role of the solvent in a variety of applications, from biofuels to organic catalysis or as excipients in pharmaceutical formulations. These ILs have a desirable use as solvents due to their ability to be tunable substances. Changing the cation or anion of the IL causes a change in its physical …

Machine Learning And Causality For Interpretable And Automated Decision Making, Maria Lentini

Theses and Dissertations

This abstract explores two key areas in decision science: automated and interpretable decision making. In the first part, we address challenges related to sparse user interaction data and high item turnover rates in recommender systems. We introduce a novel algorithm called Multi-View Interactive Collaborative Filtering (MV-ICTR) that integrates user-item ratings and contextual information, improving performance, particularly for cold-start scenarios. In the second part, we focus on Student Prescription Trees (SPTs), which are interpretable decision trees. These trees use a black box "teacher" model to predict counterfactuals based on observed covariates. We experiment with a Bayesian hierarchical binomial regression model as …

Adversary Aware Continual Learning, Muhammad Umer

Theses and Dissertations

Continual learning approaches are useful as they help the model to learn new information (classes) sequentially, while also retaining the previously acquired information (classes). However, these approaches are adversary agnostic, i.e., they do not consider the possibility of malicious attacks. In this dissertation, we have demonstrated that continual learning approaches are extremely vulnerable to the adversarial backdoor attacks, where an intelligent adversary can introduce small amount of misinformation to the model in the form of imperceptible backdoor pattern during training to cause deliberate forgetting of a specific class at test time. We then propose a novel defensive framework to counter …

Computation Offloading Design For Deep Neural Network Inference On Iot Devices, Asmika Boosarapu

Theses and Dissertations

In recent times, advances in the technologies of Internet-of-Things (IoT) and Deep Neural Networks (DNN) have significantly increased the accuracy and speed of a variety of smart applications. However, one of the barriers to deploying DNN to IoT is the computational limitations of IoT devices as compared with the computationally expensive task of DNN inference. Computation offloading is an approach that addresses this problem by offloading DNN computation tasks to cloud servers. In this thesis we propose a collaborative computation offloading solution, in which some of the work is done on the IoT device, and the remainder of the work …

Artemisinin And Its Derivatives Reactions: Characterization Of The Reaction Products Using Lc/Tof Ms, Kogila Vijayan

Theses and Dissertations

Artemisinin (ART) is a sesquiterpene lactone and a popular malaria drug with potential anticancer properties. In this work, LC/TOF MS was used to investigate the reaction of ART with DNA bases and estradiol. ART-deoxyadenosine and ART-deoxycytidine interactions were studied in the presence of Fe (II) ions. ART-deoxyadenosine and ART-deoxycytidine reaction mixtures gave chromatographic signatures that remained unchanged at room temperature but grew after incubation at 37°C. The change in temperature from room temperature to 37°C was the main driver of adduct formation in these reactions. ART was found to react with Fe (II) ions as observed from several new chromatographic …

Development Of New Chemical Probes To Delineate The Polyamine Regulation & Molecular Strategies To Unravel Protein Polyamination, Vennela Tulluri

Theses and Dissertations

Polyamines such as putrescine, spermidine, and spermine modulate critical cellular processes, including gene expression and cell proliferation. Cellular polyamine regulation is a complex mechanism controlled by three different proteins: Ornithine decarboxylase (ODC), Antizyme (OAZ), and Antizyme Inhibitor (AZIN). While ODC is directly involved in polyamine biosynthesis, OAZ, and AZIN regulate the ODC activity via protein-protein interactions. The dysregulation of ODC, OAZ, and AZIN leads to elevated polyamines in numerous pathologies, making them attractive targets for controlling polyamine levels. Besides regulating polyamine synthesis, OAZ modulates polyamine transport. However, the precise mechanism remains elusive. In this research, we discuss our approach to …

Bacterial-Mediated Photocatalytic Organic Oxidation, Peter J. Pellegrinelli

Theses and Dissertations

Bacteria, though well-known and widespread in scientific application, have plenty more opportunity to grow in the field of organic synthesis. The primary objective of this project was to apply the use of bioluminescent bacteria in an organic photoredox reaction intending to use the bacteria as a renewable source of light. This sustainable method, as opposed to high wattage bulbs, paves a green pathway for organic photocatalytic reactions. Using bioluminescent E. coli, the focus was on performing organic oxidation reactions with a recyclable photocatalyst. When using bacteria in conjunction with chemicals like nitromethane, it was an obstacle to keep the E. …

Machine Learning Models Interpretability For Malware Detection Using Model Agnostic Language For Exploration And Explanation, Ikuromor Mabel Ogiriki

Theses and Dissertations

The adoption of the internet as a global platform has birthed a significant rise in cyber-attacks of various forms ranging from Trojans, worms, spyware, ransomware, botnet malware, rootkit, etc. In order to tackle the issue of all these forms of malware, there is a need to understand and detect them. There are various methods of detecting malware which include signature, behavioral, and machine learning. Machine learning methods have proven to be the most efficient of all for malware detection. In this thesis, a system that utilizes both the signature and dynamic behavior-based detection techniques, with the added layer of the …

Using Dielectric Scatters To Selectively Excite Embedded Eigenstates In Cavity Resonators, Olugbenga Joshua Gbidi

Theses and Dissertations

Bound states in the continuum (BICs) are waves that remain in the continuous spectrum of radiating waves that carry energy, however, still localized within the spectrum. BICs, also embedded eigenmodes, exhibit high quality factors that have been observed in optical and acoustic waveguides, photonic structures, and other material systems. Presently, there are limited means to select these BICs in terms of the quality factor and their excitation. In this work, we show that a different type of BIC, Quasi-BICs (Q-BICs), in open resonators can have their quality attuned by introducing embedded scatters. Using microwave cavities and dielectric scatters as an …

Investigating The Effects Of Ionic Liquids On Dna Gquadruplex And Protein Structure Using Molecular Dynamics Simulations, Nicholas J. Paradis

Theses and Dissertations

Nucleic acids and proteins have huge implications in biomedicine and bioengineering, however their storage instability limits their applicability and current storage protocols are expensive and globally-inaccessible. Finding an alternative biocompatible media to store nucleic acids and proteins would reduce costs and increase their applicability. Ionic liquids (ILs) are molten salt compounds that have been shown to modulate the stability and activity of nucleic acids and proteins. In this thesis, molecular modeling studies of DNA/RNA and protein structure in ILs will be discussed (Chapter 1) and this method will be used to study the IL effects on the structure on the …

Utilizing Federated Learning And Meta Learning For Few-Shot Learning On Edge Devices, Kousalya Soumya Lahari Voleti

Theses and Dissertations

The efficient and effective handling of few-shot learning tasks on mobile devices is challenging due to the small training set issue and the physical limitations in power and computational resources on these devices. In this thesis, we propose a solution that combines federated learning and meta-learning to handle independent few-shot learning tasks on multiple devices (or clients) and the server. In particular, we utilize the Prototypical Networks to perform meta-learning on all devices to learn multiple independent few-shot learning models and to combine the models in a centralized data distributed architecture using federated learning which can be reused by the …

Investigation Of Adhesion, Deformation Mechanics, And Electrical Properties Of Ag/Sio2/Pdms Tri-Layers For Stretchable Electronic Applications, Rhandy Joe Paladines

Theses and Dissertations

The motivation behind this research is to improve the interfacial layer bonding of metallic thin films to PDMS substrates with the aid of a buffer layer. The physical vapor deposition (PVD) technique of sputtering was used to deposit bilayer thin films of silver (Ag) and silicon dioxide (SiO2) on PDMS. Two chamber pressures were used in this work, 5 and 20 mTorr, to investigate the role of this parameter in determining the interfacial adhesion and the role in determining the resistance sensitivity. Studies of the surface energy and increased bonding strength for metallization are carried out. Surface characterization using atomic …

A Machine Learning Framework For Automatic Speech Recognition In Air Traffic Control Using Word Level Binary Classification And Transcription, Fowad Shahid Sohail

Theses and Dissertations

Advances in Artificial Intelligence and Machine learning have enabled a variety of new technologies. One such technology is Automatic Speech Recognition (ASR), where a machine is given audio and transcribes the words that were spoken. ASR can be applied in a variety of domains to improve general usability and safety. One such domain is Air Traffic Control (ATC). ASR in ATC promises to improve safety in a mission critical environment. ASR models have historically required a large amount of clean training data. ATC environments are noisy and acquiring labeled data is a difficult, expertise dependent task. This thesis attempts to …

Effective Immersive Analytics For Everyday Use, Benjamin D. Weidner

Theses and Dissertations

Data visualization is an important field of work that takes in uncountable amounts of indexes to create an easy-to-read interpretation of what was previously unreadable. Immersive analytics is the new field that brings 3D data visualization to virtual reality, immersing users directly into the data. Focusing on bringing humans and computers closer together through natural function can benefit the world of data science. In order to accurately utilize this field to benefit this world, principles must be laid out and observed to see which techniques and methods are best fit for an everyday immersive analytics platform. Our findings show that, …

Development Of Software Tools For Efficient And Sustainable Process Development And Improvement, Jake P. Stengel

Theses and Dissertations

Infrastructure is a key component in the well-being of our society that leads to its growth, development, and productive operations. A well-built infrastructure allows the community to be more competitive and promotes economic advancement. In 2021, the ASCE (American Society of Civil Engineers) ranked the American infrastructure as substandard, with an overall grade of C-. The overall ranking suffers when key infrastructure categories are not maintained according to the needs of the population. Therefore, there is a need to consider alternative methods to improve our infrastructure and make it more sustainable to enhance the overall grade. One of the challenges …

An Empirical Study On Sampling Approaches For 3d Image Classification Using Deep Learning, Nicholas Michelette

Theses and Dissertations

A 3D classification method requires more training data than a 2D image classification method to achieve good performance. These training data usually come in the form of multiple 2D images (e.g., slices in a CT scan) or point clouds (e.g., 3D CAD modeling) for volumetric object representation. The amount of data required to complete this higher dimension problem comes with the cost of requiring more processing time and space. This problem can be mitigated with data size reduction (i.e., sampling). In this thesis, we empirically study and compare the classification performance and deep learning training time of PointNet utilizing uniform …

A Digital Application For Assessment Of Neurocognitive Disabilities, Thomas H. Auriemma

Theses and Dissertations

Background: Neuropsychological assessment is designed to identify neurocognitive impairment and has traditionally relied on pen-and-paper tests. The behavior collected from these tests is usually expressed as a total summary score or a score that reflects a restricted number of features that assess errors. There is now interest in coupling traditional paper and pencil tests with digital assessment technology. In this context traditional metrics such as summary scores are still available. However, using digital technology, a host of time-based parameters can now be obtained. These time-based parameters include the total time to complete the task or total time to completion, as …

Assessing The Effect Of Interactivity On Virtual Reality Second Language Learning, Christene Harris

Theses and Dissertations

Virtual Reality (VR) being used as a helpful tool in language education is widely supported by the current literature. It can provide a variety of stimulating scenarios that keep learner engagement high. The use of VR for language learning is a research area that has shown promise in recent years. This makes it necessary for further research to be conducted in the field to determine ways to maximize its potential. This thesis aims to determine if the level of interactivity present in a VR Language Learning Application is a factor that will impact a user's capability to successfully learn a …

Low Memory Continual Learning Classification Algorithms For Low Resource Hardware, Autumn Lilly Chadwick

Theses and Dissertations

Continual Learning (CL) is a machine learning approach which focuses on continuous learning of data rather than single dataset-based learning. In this thesis, this same focus is applied with respect to the field of machine learning for embedded devices which is still in the early stages of development. This focus is further used to develop various algorithms such as utilizing prior trained starting networks, weighted output schemes, and replay or reduced datasets for training while maintaining a consistent focus on low resource devices to maintain acceptable performance. The experimental results show an improvement in model training times as compared to …

An Empirical Study On The Efficacy Of Evolutionary Algorithms For Automated Neural Architecture Search, Andrew D. Cuccinello

Theses and Dissertations

The configuration and architecture design of neural networks is a time consuming process that has been shown to provide significant training speed and prediction improvements. Traditionally, this process is done manually, but this requires a large amount of expert knowledge and significant investment of labor. As a result it is beneficial to have automated ways to optimize model architectures. In this thesis, we study the use of evolutionary algorithm for neural architecture search (NAS). Moreover, we investigate the effect of integrating evolutionary NAS into deep reinforcement learning to learn control policy for ATARI game playing. Empirical classification results on the …

Rebalancing Shared Mobility Systems By User Incentive Scheme Via Reinforcement Learning, Matthew Brian Schofield

Theses and Dissertations

Shared mobility systems regularly suffer from an imbalance of vehicle supply within the system, leading to users being unable to receive service. If such imbalance problems are not mitigated some users will not be serviced. There is an increasing interest in the use of reinforcement learning (RL) techniques for improving the resource supply balance and service level of systems. The goal of these techniques is to produce an effective user incentivization policy scheme to encourage users of a shared mobility system to slightly alter their travel behavior in exchange for a small monetary incentive. These slight changes in user behavior …

Using Molecular Dynamics Simulations To Understand Receptor-Complex Communication And Signaling, Hannah Margaret Hoag

Theses and Dissertations

The overarching purpose of this document is to use Computer-aided drug design and Molecular dynamic simulations to better understand elusive drug-receptor interactions, as well as various types of inter-receptor signaling. Chapter One introduces the theory and importance of Computer-aided drug design and the methodology used in both Chapters Two and Three.

Chapter Two uncovers the relationship between the well-studied ABCB1 transporter and a newly identified drug known as Xanthohumol (XN). XN is compared to a commonly used drug, Doxorubicin (DOX), in this chapter. If the ABCB1 transporter can be properly inhibited, cancer-fighting drugs will be able to stay within the …

Lorawan Device Security And Energy Optimization, John A. Stranahan Jr.

Theses and Dissertations

Resource-constrained devices are commonly connected to a network and become "things" that make up the Internet of Things (IoT). Many industries are interested in cost-effective, reliable, and cyber secure sensor networks due to the ever-increasing connectivity and benefits of IoT devices. The full advantages of IoT devices are seen in a long-range and remote context. However, current IoT platforms show many obstacles to achieve a balance between power efficiency and cybersecurity. Battery-powered sensor nodes can reliably send data over long distances with minimal power draw by adopting Long-Range (LoRa) wireless radio frequency technology. With LoRa, these devices can stay active …

Synthesis And Cytotoxicity Of Trisubstituted Imidazoles, Venkata Agasthya Kasibotla

Theses and Dissertations

Aza heterocyclic compounds are an important class of organic compounds that play a major role in medicinal chemistry. Majority of the heterocyclic motifs such as imidazoles, triazoles, piperazines etc. act as building blocks for synthesizing active pharmaceutical ingredients. Several pharmaceutical drugs include these motifs due to their varying physicochemical properties, which enable them to exhibit wide range of pharmacological activities ranging from anti-fungal, anti-neoplastic, anti-helmintic, anti-microbial etc. Owing to their electron rich ring system, imidazole and piperazine based motifs have become an attractive target for design and development of novel chemical structures as new drugs. In the current study, we …