Digital Commons Network^™

Unraveling Phytosulfokine Trafficking In Arabidopsis Thaliana Using Fiber-Optic Fluorescence Microscopy, Issaka Obuaba

Electronic Theses and Dissertations

As sessile organisms, plants manage stress through complex signaling networks involving phytohormones such as phytosulfokine (PSK). PSK, a disulfated pentapeptide, regulates plant growth, development, and stress responses by interacting with specific PSK receptors (PSKRs). In this study, we explored the trafficking dynamics of PSK, its post-application fate, and the synthesis of an analog. We administered both native PSK and a fluorescent version tagged with TAMRA (5(6)-carboxytetramethylrhodamine) to various Arabidopsis thaliana genotypes, including wild type, a PSKR-deficient mutant, and a strain overexpressing PSKR1 tagged with green fluorescent protein (GFP) over the wild-type background. Fiber-optic fluorescence microscopy revealed that receptor presence influences …

Investigating Phytosulfokine Trafficking: Insights Into The Role Of Phytohormones In Plant Signaling, Martin Tindi

Electronic Theses and Dissertations

Phytosulfokine is a critical signaling peptide involved in plant growth, development, and stress responses. This thesis investigates the trafficking mechanisms of Phytosulfokine (PSK) in Arabidopsis thaliana, employing fluorescently labelled PSK for non-destructive imaging using a custom-built fiber-optic fluorescence microscope. The study aims to determine the mobility and fate of PSK in plant tissues. Experimental results reveal the short-range and long-range movement of PSK across leaves. Additionally, the project highlights the optimization of non-destructive imaging techniques and the synthesis of caged dexamethasone to facilitate optogenetic studies. These findings provide new insights into PSK trafficking mechanisms in plants, enhancing our understanding …

Investigating Nekton Response To Changing Salinities In The Mississippi Sound: An Experimental And Statistical Approach, Adam Murray

Master's Theses

The Mississippi Sound provides nursery habitats for many coastal species and is recognized for its commercial fisheries. Previous freshening events linked to the Bonnet Carré Spillway, a Mississippi River flood diversion structure, proved catastrophic for oyster populations in the Mississippi Sound, but effects on mobile fish and shellfish species are not well-defined. The planned Mid-Breton Sediment Diversion (MBSD), an initiative to combat wetland loss, is also forecasted to lower salinities in the region, increasing the need to better understand responses of commercially and ecologically important species to freshening events. The objective of this study was to characterize effects of salinity …

The Application Of High-Resolution Mass Spectrometry For The Analysis Of Biopolymers, Metabolites, And Biologically Relevant Small Molecules, Christ Duc Tran

Graduate Doctoral Dissertations

High-resolution mass spectrometry (HRMS), as its name suggests, possesses high resolving power that enables the separation of ions with very close mass values. This is particularly beneficial for analyzing complex samples where numerous compounds may have similar masses, as it helps prevent signal overlaps and ensures an accurate spectral analysis. The current work explores the diverse applications of high-resolution mass spectrometry in oligonucleotide research, organic synthesis and medicinal chemistry. Oligonucleotide research: Chapters 2-5 present the research results from studies that employed ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS) to understand the pharmacokinetics of RNA interference (RNAi) therapeutics. The …

User Acceptance Of Advice By Ai Agents: Expectation-System Fit Perspective, Jingyuan Cai, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

Algorithms have increasing influence on our daily decisions, especially when the recommendations are presented by human-like AI agents. This study applies the Theory of Effective Use to investigate how the fit between the user’s role expectation for an AI agent and the agent’s interaction style impacts AI advice adoption. We proposed a new concept termed Perceived Expectation-System Fit (PESF) and empirically examined its impact on user perceptions and advice acceptance. We found that low PESF reduces advice acceptance by diminishing cognitive and affective trust in the AI agent. Furthermore, increased algorithm transparency increases PESF's impact on decision-making. Our findings provide …

Mvgamba : Unify 3d Content Generation As State Space Sequence Modeling, Xuanyu Yi, Zike Wu, Qiuhong Shen, Qingshan Xu, Pan Zhou, Joo-Hwee Lim, Shuicheng Yan, Xinchao Wang, Hanwang Zhang

Research Collection School Of Computing and Information Systems

Recent 3D large reconstruction models (LRMs) can generate high-quality 3D content in sub-seconds by integrating multi-view diffusion models with scalable multi-view reconstructors. Current works further leverage 3D Gaussian Splatting as 3D representation for improved visual quality and rendering efficiency. However, we observe that existing Gaussian reconstruction models often suffer from multi-view inconsistency and blurred textures. We attribute this to the compromise of multi-view information propagation in favor of adopting powerful yet computationally intensive architectures (e.g., Transformers). To address this issue, we introduce MVGamba, a general and lightweight Gaussian reconstruction model featuring a multi-view Gaussian reconstructor based on the RNN-like State …

Classifying Supersonic Frequencies For Active Acoustic Side-Channel Exploitation, Destin Hinkel

Graduate Theses and Dissertations (2019 - present)

Computing side-channel research explores the manner in which physical emanations from systems can be used to reconstruct data. Acoustic side-channels are those physical emanations that produce a sonic frequency that is subsonic, supersonic, or considered in the range of human hearing [1]. Acoustic side-channel attacks (SCAs) are typically performed passively: a listening device captures aural frequencies from a machine via a microphone that are transmitted to the attacker for analysis [1]–[3]. Machine learning models have been presented to classify individual keystrokes according to variations in acoustic frequency [4]. Furthermore, the SonarSnoop framework presents a novel active approach that involves both …

Protocol Transformations Across Osi Network Stack Layers For Attack, Evasion, And Defense, Nathan Tusing

All Dissertations

Network endpoints frequently contend with errors and deviations within protocols. Many factors account for these deviations including noise, tampering, and algorithm implementations. Intermediate nodes are expected to modify instantiated protocols and not guarantee correctness. This ability to modify traffic enables all sides of network security to alter security and performance properties of protocols, and we define this intermediary modification of an instantiated protocol as a transformation. Protocol transformations traverse layers of the OSI reference model and changes a protocol's time series byte sequence. Within this thesis, we show that this framework applies to multiple domains and protocols. Common examples of …

Leveraging High-Frequency Water Quality Data And Machine Learning For Monitoring Harmful Algal Blooms, Ibrahim Busari

All Dissertations

Freshwater management is one of the most critical resources on the earth due to the plethora of water use and its limited availability. Increased algae proliferation is one of the significant problems of freshwater bodies that is triggered by nutrient enrichment and enabling conditions such as light and warm temperatures. This algal proliferation is toxic to the ecosystem through their biomass and potential toxin production that can cause hypoxic conditions and is often referred to as Harmful Algal Blooms (HABs). Current monitoring approaches include laboratory analysis of water samples to observe algal cells, monitoring of water quality parameters using water …

Recyclable Composites Prepared From Animal Coproducts And Industrial Waste Sulfur, Perla Y. Sauceda-Oloño

All Dissertations

Pursuing sustainable and environmentally friendly materials has become a significant objective in materials science, particularly flame retardants and construction materials. This dissertation explores the development and evaluation of novel composites and high sulfur-content materials (HSMs) as potential alternatives to conventional, environmentally harmful materials.

Chapter one reviews recent advancements in environmentally benign flame-retardant additives, highlighting the potential of bio-derived phenols, polysaccharide derivatives, and greener phosphorus sources. The review discusses how green additives can enhance the flame retardancy, thermal stability, and smoke suppression properties of various polymers while addressing the challenges and future directions in the field.

Chapter two investigates the production …

Mathematical And Statistical Methods To Harness Limited Data In Models For Ecological Space Use Under Global Change, Sarah C. Bogen

All Graduate Theses and Dissertations, Fall 2023 to Present

The dynamics of how plants and animals use space in their habitats has important implications for the fields of ecology and conservation. However, understanding and responding to these spatial and temporal dynamics is often limited by data availability, financial resources and biases. As average global temperatures increase, suitable habitats shift poleward and require local populations to move with suitable habitat, adapt to the changing environment, or risk extinction. Capacity to persist without movement may be estimated by considering changes to a combination of habitat characteristics. Capacity to track suitable habitat may be modeled through synthesizing information on species demographic mechanisms …

Using Luminescence Dating To Investigate Geomorphic And Archaeologic Features At The Wiggins Fork Bison Jump Complex, Northwestern Wyoming, Emma T. Krolczyk

All Graduate Theses and Dissertations, Fall 2023 to Present

The Wiggins Fork Bison Jump Complex, located in northwestern Wyoming, is comprised of thousands of human-placed rock piles, known as cairns, that were placed within lines to form an extensive network of drivelines and funnels leading to cliffs or steep slopes. These archaeological features were used by Native Americans as a bison hunting method, where the animals were driven off cliffs for harvest. This research uses luminescence dating, which determines when sediment was last exposed to sunlight, to date the timing of driveline construction and the deposition ages of the underlying river deposits.

Research focused on Jump #4, which had …

Redefining Approaches For Measuring Landscape Subsidence And Permafrost Degradation In Arctic Tundra Environments, Tabatha Lynn Fuson

Open Access Theses & Dissertations

As climate change accelerates in the Arctic, the degradation of permafrost is leading to significant landscape transformation in tundra landscapes. This dissertation investigates the multifaceted responses of permafrost systems to warming, focusing on the dynamics of surface elevation changes and active layer thickness (ALT) across the North Slope of Alaska. In this study, I explore the capacity of repeat Terrestrial Laser Scanning (TLS) technology for modeling tundra features and detecting surface subsidence, specifically how different climate and landscape conditions during scanning impact TLS model precision. We also compare TLS model precision estimates to TLS model accuracy by comparing elevation values …

The New Anthropocentrism: The Problem Of Water Conservation And Water Justice, Benjamin Stuart Milam

Open Access Theses & Dissertations

My objective with my thesis is to argue for and reinforce a type of anthropocentrism that is both environmentally conscious and consumable for an audience that is not necessarily well versed in philosophical literature. In the first chapter I go over philosophical frameworks, such as Anthropocentrism and Biocentrism, and why I believe they do not meet both of those criteria listed. After that I discuss New Anthropocentrism, coined by Clive Hamilton, and why I believe that a slightly modified version possesses qualities that I believe are needed for the crisis at hand. In chapter 2 I use that framework and …

The United States National Security And Policy Implications Of Desertification, Eric Olvera

Open Access Theses & Dissertations

Contemporary climate security literature reveals that desertification appears to be overlooked as a climate change security threat to the United States (US). This investigation demonstrates that an inequity exists between sea-level-rise- and desertification-based climate security literature. This inequity may reveal that the US may be ignoring desertification at a time when land use in some dryland areas is reaching a critical point where it can no longer support human activity. Due to the interdisciplinary nature (science and security) of this work, a review of the terminology used in the article is provided to establish a baseline understanding of “desertification” and …

Enhancing Predictive Accuracy In Noisy Data: A Robust Gradient Boosting Approach, Gabriela Alexa Acuna

Open Access Theses & Dissertations

This thesis aims to enhance the gradient boosting technique, a well-known machine learning method, in a regression setup. Gradient boosting techniques implement sequential weak learners, in this case, shallow trees that contribute to the model with a small percentage. The traditional gradient boosting approach uses regression trees that choose thresholds based on minimizing variance and makes predictions based on the mean of the target variable for the observations contained within each node. The residual sum of squares (RSS) and mean metrics are sensitive to outliers, which makes the model's predictions less robust. Outliers influence the predictions, resulting in a model …

Neural Network Architecture Search Enabled Wide-Deep Learning (Nas-Wd) Integrated Hyperspectral Imaging Understanding For Woody Breast In Poultry Processing, Chaitanya Kumar Reddy Pallerla

Graduate Theses and Dissertations

The development and implementation of a Wide & Deep (WD) learning model tailored for classification and regression tasks utilizing spectral data provides a robust solution to evaluate woody breast (WB) conditions in poultry fillets. This process begins with thorough data preprocessing, which includes loading spectral and classification datasets, imputing missing values with medians, and splitting the data into training and testing sets to ensure rigorous model evaluation. The WD model architecture integrates wide linear models and deep neural networks to harness the strengths of both approaches. The wide component excels at memorizing sparse feature interactions, while the deep component captures …

Microwave-Assisted Green Synthesis Of Spiroindolinopyranopyrazoles, Esther Owusu

Theses and Dissertations

Green Chemistry, usually known as sustainable chemistry, is widely implemented worldwide to safeguard human health and the environment. Recent investigations in organic synthesis and chemical transformation have demonstrated that green chemistry techniques are significantly reducing both chemical waste and reaction time. In order to fulfill this ecological requirement, it is crucial to lessen the utilization of perilous solvents and noxious chemicals, while also creating innovative reaction methods that decrease the production of trash. The implementation of such methodologies can greatly enhance the field of green chemistry. A more environmentally friendly synthetic method was utilized to generate spiro chemicals and their …

Multi-Criteria Decision-Making Approach Based On Correlation Coefficient For Multi-Polar Interval-Valued Neutrosophic Soft Set, Hamza Naveed, Saalam Ali

Neutrosophic Systems with Applications

The correlation coefficient between two factors is crucial in statistical computation, indicating the extent and evolution of the appropriate link. The precision of applicability evaluations frequently relies on the thoroughness and caliber of data obtained from a certain dataset. Statistical research sometimes entails data marked by intrinsic trade-offs and uncertainty. This study seeks to present m-polar interval-valued neutrosophic soft sets (mPIVNSSs) through the integration of m-polar fuzzy sets with interval-valued neutrosophic soft sets. The suggested mPIVNSS structure is a significantly generalized version of m-polar neutrosophic soft sets and serves as a substantial extension of interval-valued neutrosophic soft sets. In this …

Analysis Of Bck/Bci-Algebras Based On Bipolar Complex Intuitionistic Fuzzy Soft Ideals, Zeeshan Ali

Neutrosophic Systems with Applications

In this article, we design an informative and reliable technique of bipolar complex intuitionistic fuzzy soft sets with numerous operational laws by merging the model of soft sets, complex fuzzy sets, and bipolar intuitionistic fuzzy sets to handle imprecise data. In addition, an ideal in a BCK-algebra is derived based on bipolar complex intuitionistic fuzzy soft set theory are proposed which can capture the information of hesitancy, vagueness, and non-membership information within the circumstance of BCK-algebra. Moreover, we design union, intersection, AND, and OR based on bipolar complex intuitionistic fuzzy soft ideal and simplify it with the help of numerous …

Addressing Inference Time Of Machine Learning Models In Embedded Systems, Samuel Black

UNLV Theses, Dissertations, Professional Papers, and Capstones

Embedded Systems are used for a wide range of specialized computing purposes including surveyal, safety, security, and quality of life. Many areas that embedded systems are used in require the use of machine learning models. Constraints can be placed on embedded systems. Timeliness of execution, user satisfaction, security, power, and resource limitations must be considered when designing for embedded systems. Neural networks excel at complex tasks that are otherwise intractable, but their relatively high computational cost poses a challenge for inclusion in embedded systems. Neural network architectures should be optimized to reduce the total number of operations performed while maintaining …

Artificial Intelligence And Machine Learning In Cancer Pain: A Systematic Review, Vivian Salama, Brandon Godinich, Yimin Geng, Laia Humbert-Vidan, Laura Maule, Kareem A Wahid, Mohamed A Naser, Renjie He, Abdallah S R Mohamed, Clifton D Fuller, Amy C Moreno

Faculty, Staff and Student Publications

Background/objectives: Pain is a challenging multifaceted symptom reported by most cancer patients. This systematic review aims to explore applications of artificial intelligence/machine learning (AI/ML) in predicting pain-related outcomes and pain management in cancer.

Methods: A comprehensive search of Ovid MEDLINE, EMBASE and Web of Science databases was conducted using terms: "Cancer," "Pain," "Pain Management," "Analgesics," "Artificial Intelligence," "Machine Learning," and "Neural Networks" published up to September 7, 2023. AI/ML models, their validation and performance were summarized. Quality assessment was conducted using PROBAST risk-of-bias andadherence to TRIPOD guidelines.

Results: Forty four studies from 2006 to 2023 were included. Nineteen studies used …

Issue 41

The Synapse: Intercollegiate science magazine

No abstract provided.

Digging Up A New Era In Fertilizer: Investigating The Potential Of Electron Bifurcation In Ammonia Synthesiss, Ella Wurtzbacher

The Synapse: Intercollegiate science magazine

No abstract provided.

This Land Is Your Land, This Land Is My Land, Alexia Liu

The Synapse: Intercollegiate science magazine

No abstract provided.

Agricultural Water Use In South Carolina - A Series Of Investigations To Support Long-Term Planning, Charles Pellett

All Dissertations

Agricultural water use in South Carolina has been the subject of some public debate. While there are several sources of information available, the accuracy of the relevant data has been called into doubt. Self-reported estimates may be biased; survey sampling and extrapolation methods yield wide ranges of uncertainty; and reporting compliance or response rate can change over time.

Agricultural water users self-report that their estimates of water use volumes are less accurate than the other major sectors of water use. Center pivot irrigation is the largest and fastest growing kind of agricultural water use in SC. Since the year 2000, …

Environmental Dna Identifies Coastal Plant Community Shift 1,000 Years Ago In Torrens Island, South Australia, Nicole R. Foster, Alice R. Jones, Oscar Serrano, Anna Lafratta, Paul S. Lavery, Kor-Jent Van Dijk, Ed Biffin, Bronwyn M. Gillanders, Jennifer Young, Pere Masque, Patricia S. Gadd, Geraldine E. Jacobsen, Atun Zawadzki, Andria Greene, Michelle Waycott

Research outputs 2022 to 2026

Anthropogenic activities are causing detrimental changes to coastal plants– namely seagrass, mangrove, and tidal marshes. Looking beyond recent times to past vegetation dynamics is critical to assess the response and resilience of an environment to change. Here, we develop a high-resolution multi-proxy approach, providing a new evidence base to decipher long-term change in coastal plant communities. Combining targeted environmental DNA analysis with chemical analysis of soils, we reconstructed 4,000 years of change at a temperate wetland on Torrens Island South Australia and identified an ecosystem shift that occurred ~ 1000 years ago. What was once a subtidal seagrass system shifted …

Real-Time Motion Augmentation And Synthesis For Animating The Hands And Eyes Of Virtual Humans And Avatars, Ryan Canales

All Dissertations

Virtual Reality (VR) enables users to interact within virtual worlds via an embodied virtual representation of themselves called an “avatar”. Because avatars are essential for immersive experiences, it is important to consider how altering or augmenting avatar motion affects virtual experiences. This dissertation aims to improve virtual experiences by addressing some of the many challenges in animating avatars and virtual humans.

In our first study, we addressed the lack of tactile feedback during virtual grasping by using visual feedback techniques. We augmented the avatar’s hand motion to remain outside virtual objects (“outer hand”) even when the user’s hand penetrated them. …

The Relationship Between Salvinia Molesta Infestation And The Microbial Ecology Of Wetlands At Caddo Lake, Tx, Usa, Martin Hadsell

Electronic Theses and Dissertations

Wetlands are known to host many beneficial geochemical processes such as nutrient cycling and carbon sequestration. These processes are primarily driven by the microbial communities within a wetland. The establishment of non-native invasive species within wetlands has the potential to alter the once beneficial functionality of wetland microbial communities due to the sensitivity microbes have towards environmental changes. Because of this, several metagenomic studies have been conducted to assess microbial community response to aquatic plant invasion; however, there haven’t been any studies researching the influence of Salvinia molesta (D.S. Mitch.), commonly known as Giant Salvinia, on microbial communities. The goal …

Establishment Of Structure-Property-Processing Relationships For Design Of Sprayable Hydrogels And Amyloid/Peo Electrospun Composites, Xianjun Wang

Dissertations

The focus of this dissertation is the design, synthesis, characterization, and prototyping of bio-inspired materials to understand the role of structure, intermolecular interactions, and processing technique on the self-assembly, bioactive properties, and mechanical properties of the biomaterials. This work is divided into three research areas: 1) sprayable and adhesive glycopolymer based hydrogels; 2) decapeptide-based composite nanofiber mats; and 3) prototyping sutures and meshes via electrospinning. The established structure-property-processing relationships provide a foundation for designing biomaterials in the future.

The first chapter provides an introductory overview of the requirements necessary for the development of hydrogels, glycopolymers, and peptides, including relevant processing …