Physical Sciences and Mathematics Commons^™

Introduction To Nuclear Magnetic Resonance Spectroscopy In A Geochemical Setting, Evan Mack

University Honors College

Nuclear magnetic resonance (NMR) spectroscopy is a powerful analytical tool that is heavily employed in organic chemistry, but lacks use in geochemistry. The technique is most useful for characterization and structural analysis of analytes, but also sees use in kinetics analysis, speciation, and detection. This work aims to answer these questions regarding NMR spectroscopy’s use in geochemical settings: Which nuclei are studied? For what purposes is each nucleus studied? What affects the scope of the technique and has caused it to not be widely used? How often is NMR spectroscopy used? What trends are there in the technique’s use? The …

Sustainable Accounting: The Benefits And Challenges Of Its Implementation, Collin Eckstein

University Honors College

This thesis is centered around the idea that sustainability is a necessary component within the world. Environmental, social, and governance (ESG) factors are key components of analyzing sustainable practices. Although accountants have historically focused on financial reporting, they now have the added function of sustainable accounting as environmental implications are an area of concern for companies. A substantial component of this thesis centers around analyzing how ESG factors contribute to an organization’s financial performance. It also observes how comprehensive sustainability reports impact investor decisions and examines the challenges that auditors face when providing assurance for sustainability initiatives. Furthermore, it examines …

The Effects Of Using Machine Translators On The Performance Of Second Language Learners, Kasey Myer

University Honors College

With the rise of technology has also come the development of various online language translators and artificial intelligence that are often utilized by individuals learning a second language. However, there is a wide range of quality between the different machine translation tools, and many people tend to be under the impression that it is inferior to the quality of interpretations provided by human translators. This paper considers the positives and negatives of machine translation as a tool for second language learning. Variations between the input and output languages on a grammatical and cultural level are analyzed. Machine translation is compared …

Ai: Is The Future Robots?, Ruthanne Fischer

University Honors College

The goal of this thesis is to analyze how Artificial Intelligence is actively changing. The newly developed technology that is known as Artificial Intelligence can potentially have implications that are not yet known. Artificial Intelligence impacts the business world in many ways. Things such as ChatGPT and Deepfakes are some of the biggest forms of Artificial Intelligence today. It is important to know how Artificial Intelligence is changing every day because no one knows the true implications of a technology like this. It is crucial for companies to understand how this technology can potentially be harmful to their employees. Artificial …

Cybervictimization And Depression: A Cultural Standpoint, Paige Heagy

University Honors College

The author’s aim was to investigate the relationship between cybervictimization and depression, as well as using peer attachment and culture as moderators by giving questionnaires to 1347 participants (age range = 11-15 years) from India and the United States. Through four questionnaires, adolescents reported their levels of endorsement in either individualism or collectivism culture, levels of cybervictimization, levels of depression/depressive symptoms, and their levels of peer attachment. Adolescents reported that there is a significantly positive correlation between cybervictimization and depression. Differences were found according to culture and peer attachment, as well. Cybervictimization has begun to erupt worldwide as internet usage …

Creating Interpretable Deep Learning Models To Identify Species Using Environmental Dna Sequences, Samuel Waggoner

Honors College

This research aims to develop an interpretable and fast machine learning (ML) model for identifying species using environmental DNA (eDNA). eDNA is a technique used to detect the presence or absence of species in an ecosystem by analyzing the DNA that animals naturally leave behind in water or soil. However, there can be millions of sequences to classify and the reference databases are sizeable, so traditional methods such as BLAST are slow. Convolutional neural networks (CNNs) have been shown to be 150 times faster at classifying sequences. In this work, we create a CNN that achieves 92.5% accuracy, surpassing the …

Effects Of Ecologically Relevant Concentrations Of Nitrate On Behavior In Betta Splendens, Sarah Janson

Honors College

Nitrate is a ubiquitous pollutant that is becoming more prevalent in both fresh and saltwater environments. Short term effects are often studied, but an organism’s response to stress can change due to whatever the stressor is. In order to research this, a study was run using environmentally relevant nitrate treatments (0 mg/L, 10 mg/L NO3-N, and 100 mg/L NO3-N) to see the effect of nitrate on scototaxis behaviors, a measure of anxiety. This study used Betta splendens because they are easy to rear and have very well documented behaviors. In addition to the scototaxis, the effect of temperature on mortality …

Development And Investigation Of Children's Manuscripts On Sustainable Agriculture And Place Based Interactions With The Land, Isabella Oliveira

Honors College

The goal of this project was to develop an illustrated educational manuscript for children, on the topic of environmentally sustainable practices and developing an interactive relationship with the environment around them. The decision-making of the contents of the manuscript was based in research on environmental pedagogy, the history of land use, place-based identity and environmentalism, and sustainable land practices. All of the illustrations and photography in the manuscript were taken in Maine over my time spent here in college. This manuscript is meant to engage children with the environment around them by introducing them to simplified scientific concepts using references …

Development Of Novel Immobilized Copper–Ligand Complex For Click Chemistry Of Biomolecules, Rene Kandler, Yomal Benaragama, Manoranjan Bera, Caroline Wang, Rasheda Aktar Samiha, W.M.C. Sameera, Samir Das, Arundhati Nag

Chemistry

Copper-catalyzed azide–alkyne cycloaddition click (CuAAC) reaction is widely used to synthesize drug candidates and other biomolecule classes. Homogeneous catalysts, which consist of copper coordinated to a ligand framework, have been optimized for high yield and specificity of the CuAAC reaction, but CuAAC reaction with these catalysts requires the addition of a reducing agent and basic conditions, which can complicate some of the desired syntheses. Additionally, removing copper from the synthesized CuAAC-containing biomolecule is necessary for biological applications but inconvenient and requires additional purification steps. We describe here the design and synthesis of a PNN-type pincer ligand complex with copper (I) …

Murmurations And Root Numbers, Alexey Pozdnyakov

University Scholar Projects

We report on a machine learning investigation of large datasets of elliptic curves and L-functions. This leads to the discovery of murmurations, an unexpected correlation between the root numbers and Dirichlet coefficients of L-functions. We provide a formal definition of murmurations, describe the connection with 1-level density, and provide three examples for which the murmuration phenomenon has been rigorously proven. Using our understanding of murmurations, we then build new machine learning models in search of a polynomial time algorithm for predicting root numbers. Based on our models and several heuristic arguments, we conclude that it is unlikely for …

An Educational Resource For Particle Identification (Pid) In Experimental Particle Physics Data, Richard Dube

University Scholar Projects

Although particle physics research is typically reserved for advanced undergraduates, algebra-based physics students can readily develop the foundational skills necessary to conduct particle physics research. Despite this, there is a shortage of educational resources that introduce particle physics to algebra-based physics students. This project, Particle Identification Playground, is a collection of Python-based activities that teach students about several fundamental topics in experimental particle physics research. Through these activities, students will learn about the common detectors used in particle physics, how they work, and how we can use these detectors to identify particles. Students are able to interact with 3D models …

Factors Influencing Performance Of Students In Software Automated Test Tools Course, Susmita Haldar, Mary Pierce, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

Formal software testing education is important for building efficient QA professionals. Various aspects of quality assurance approaches are usually covered in courses for training software testing students. Automated Test Tools is one of the core courses in the software testing post-graduate curriculum due to the high demand for automated testers in the workforce. It is important to understand which factors are affecting student performance in the automated testing course to be able to assist the students early on based on their needs. Various metrics that are considered for predicting student performance in this testing course are student engagement, grades on …

Why Evidence-Based Hope Is Crucial To Salish Sea Recovery And Beyond, Dr. Elin Kelsey, Ginny Broadhurst

Institute Publications

In April 2023 and March 2024, the Salish Sea Institute engaged hope scholar and thought-leader Elin Kelsey, for events with the common theme of sharing information about evidence-based hope and helping the audience apply that thinking to combat the pervasive doom and gloom narrative that persists about climate change and the environment in general.

The first event was a 2 ½ day Hope for the Salish Sea (HSS) intensive environmental leadership workshop specifically co-designed and led by Elin, Ginny Broadhurst, Director of the Salish Sea Institute, and Mavis Underwood of Tsawout Community, WSANEC Nation. The Salish Sea Institute also organized …

The Kruger Collection Reimagined: A Case Study In 3d Scanning And Interactive Exhibit Design, Annissa Davis

Anthropology Department: Theses

This thesis examines the use of 3D modeling in museum exhibition to create exploratory exhibits that facilitate unique relationships between the visitors and the collection beyond what is provided by the collection’s in person counterparts. Typical use of 3D modeling in museums is currently often representative rather than exploratory. By employing a Digital Humanities lens to approach the development of a digital exhibition utilizing 3D technology and interactive elements created in a video game engine (Unity), this thesis project evaluates these potential new relationships. Using the Eloise Kruger Collection of Miniatures as a case study, the following text details the …

Vr Circuit Simulation With Advanced Visualization For Enhancing Comprehension In Electrical Engineering, Elliott Wolbach

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

As technology advances, the field of electrical and computer engineering continuously demands innovative tools and methodologies to facilitate effective learning and comprehension of fundamental concepts. Through a comprehensive literature review, it was discovered that there was a gap in the current research on using VR technology to effectively visualize and comprehend non-observable electrical characteristics of electronic circuits. This thesis explores the integration of Virtual Reality (VR) technology and real-time electronic circuit simulation with enhanced visualization of non-observable concepts such as voltage distribution and current flow within these circuits. The primary objective is to develop an immersive educational platform that makes …

Multigprompt For Multi-Task Pre-Training And Prompting On Graphs, Xingtong Yu, Chang Zhou, Yuan Fang, Xinming Zhan

Research Collection School Of Computing and Information Systems

Graph Neural Networks (GNNs) have emerged as a mainstream technique for graph representation learning. However, their efficacy within an end-to-end supervised framework is significantly tied to the availability of task-specific labels. To mitigate labeling costs and enhance robustness in few-shot settings, pre-training on self-supervised tasks has emerged as a promising method, while prompting has been proposed to further narrow the objective gap between pretext and downstream tasks. Although there has been some initial exploration of prompt-based learning on graphs, they primarily leverage a single pretext task, resulting in a limited subset of general knowledge that could be learned from the …

Plug-And-Play Policy Planner For Large Language Model Powered Dialogue Agents, Yang Deng, Wenxuan Zhang, Wai Lam, See-Kiong Ng, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Proactive dialogues serve as a practical yet challenging dialogue problem in the era of large language models (LLMs), where the dialogue policy planning is the key to improving the proactivity of LLMs. Most existing studies enable the dialogue policy planning of LLMs using various prompting schemes or iteratively enhance this capability in handling the given case with verbal AI feedback. However, these approaches are either bounded by the policy planning capability of the frozen LLMs or hard to be transferred to new cases. In this work, we introduce a new dialogue policy planning paradigm to strategize LLMs for proactive dialogue …

Grasper: A Generalist Pursuer For Pursuit-Evasion Problems, Pengdeng Li, Shuxin Li, Xinrun Wang, Jakub Cerny, Youzhi Zhang, Stephen Mcaleer, Hau Chan, Bo An

Research Collection School Of Computing and Information Systems

Pursuit-evasion games (PEGs) model interactions between a team of pursuers and an evader in graph-based environments such as urban street networks. Recent advancements have demonstrated the effectiveness of the pre-training and fine-tuning paradigm in Policy-Space Response Oracles (PSRO) to improve scalability in solving large-scale PEGs. However, these methods primarily focus on specific PEGs with fixed initial conditions that may vary substantially in real-world scenarios, which significantly hinders the applicability of the traditional methods. To address this issue, we introduce Grasper, a GeneRAlist purSuer for Pursuit-Evasion pRoblems, capable of efficiently generating pursuer policies tailored to specific PEGs. Our contributions are threefold: …

Unraveling The ‘Anomaly’ In Time Series Anomaly Detection: A Self-Supervised Tri-Domain Solution, Yuting Sun, Guansong Pang, Guanhua Ye, Tong Chen, Xia Hu, Hongzhi Yin

Research Collection School Of Computing and Information Systems

The ongoing challenges in time series anomaly detection (TSAD), including the scarcity of anomaly labels and the variability in anomaly lengths and shapes, have led to the need for a more robust and efficient solution. As limited anomaly labels hinder traditional supervised models in anomaly detection, various state-of-the-art (SOTA) deep learning (DL) techniques (e.g., self-supervised learning) are introduced to tackle this issue. However, they encounter difficulties handling variations in anomaly lengths and shapes, limiting their adaptability to diverse anomalies. Additionally, many benchmark datasets suffer from the problem of having explicit anomalies that even random functions can detect. This problem is …

Statistical Modeling Of Right-Censored Spatial Data Using Gaussian Random Fields, Fathima Z. Sainul Abdeen, Akim Adekpedjou, Sophie Dabo Niang

Mathematics and Statistics Faculty Research & Creative Works

Consider a Fixed Number of Clustered Areas Identified by their Geographical Coordinates that Are Monitored for the Occurrences of an Event Such as a Pandemic, Epidemic, or Migration. Data Collected on Units at All Areas Include Covariates and Environmental Factors. We Apply a Probit Transformation to the Time to Event and Embed an Isotropic Spatial Correlation Function into Our Models for Better Modeling as Compared to Existing Methodologies that Use Frailty or Copula. Composite Likelihood Technique is Employed for the Construction of a Multivariate Gaussian Random Field that Preserves the Spatial Correlation Function. the Data Are Analyzed using Counting Process …

The Effect Of Vision On Lower Quarter Balance During Y-Balance Test Testing In College Students, Nathan Smith, Katelyn Mehr

Applied Health Sciences Student Works

Purpose: In order to maintain balance and stability, the body relies on the integration of information from the visual, vestibular, and proprioceptive systems. If an individual has an impairment or weakness in one or more systems, their ability to maintain balance may be impaired. Both postural stability and vision contribute to one’s ability to maintain balance in functions of everyday life. The Y-Balance Test (YBT) is a dynamic balance assessment. This study focuses on the visual system and its relation to postural balance, specifically if altered visual states affect one’s ability to maintain balance during a YBT via the use …

Deterministic Global 3d Fractal Cloud Model For Synthetic Scene Generation, Aaron M. Schinder, Shannon R. Young, Bryan J. Steward, Michael L. Dexter, Andrew Kondrath, Stephen Hinton, Ricardo Davila

Faculty Publications

This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the fractal functions which are tuned to …

Crystallographic Defects In Weyl Semimetal Laalge, Inseo Kim, Byungkyun Kang, Hyunsoo Kim, Minseok Choi

Physics Faculty Research & Creative Works

Crystallographic Defects in a Topological Semimetal Can Result in Charge Doping and Scattering Centers Which May Mask the Exotic Spectroscopic and Transport Properties, respectively. Here, We Investigate the Possible Crystallographic Defects Including Vacancy and Antisite in Weyl Semimetal LaAlGe using Hybrid-Density-Functional Theory Calculations. We Show that a Considerable Concentration of Al- and Ge-Related Defects Naturally Form during Growth Due to their Low Formation Enthalpy. Specifically, Al Can Be Easily Replaced by Ge in the I41md Phase of LaAlGe, Forming the Ge-On-Al Antisite, GeAl. the Counterpart, Al-On-Ge (AlGe), is Also Probable. the Most Abundant Defect GeAl is Donorlike, Effectively Electron Doping, …

Consequences Of The Megafauna Extinction: Changes In Food Web Networks On The Edwards Plateau Across The Pleistocene-Holocene Transition, Quentin A. Smith Jr.

School of Biological Sciences: Dissertations, Theses, and Student Research

We are experiencing biodiversity loss due to climate change and human impacts, which is not only harmful to the environment but can also alter the composition of communities and interactions among species. The late Pleistocene experienced a loss of large-bodied mammals which resulted in significant changes in community structure due to changes in body size, diet, and species associations. The impact of these changes on species interactions and community structure across the Pleistocene-Holocene transition remains poorly understood. Using a robust data set of species composition, stable isotopes, body size, and climate variables, we constructed and compared ecological networks of mammal …

Sliding Markov Decision Processes For Dynamic Task Planning On Uncrewed Aerial Vehicles, Trent Wiens

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Mission and flight planning problems for uncrewed aircraft systems (UASs) are typically large and complex in space and computational requirements. With enough time and computing resources, some of these problems may be solvable offline and then executed during flight. In dynamic or uncertain environments, however, the mission may require online adaptation and replanning. In this work, we will discuss methods of creating MDPs for online applications, and a method of using a sliding resolution and receding horizon approach to build and solve Markov Decision Processes (MDPs) in practical planing applications for UASs. In this strategy, called a Sliding Markov Decision …

Bidding Strategy For A Wind Power Producer In Us Energy And Reserve Markets, Anne Stratman

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Wind power is one of the world's fastest-growing renewable energy resources and has expanded quickly within the US electric grid. Currently, wind power producers (WPPs) may sell energy products in US markets but are not allowed to sell reserve products, due to the uncertain and intermittent nature of wind power. However, as wind’s share of the power supply grows, it may eventually be necessary for WPPs to contribute to system-wide reserves. This paper proposes a stochastic optimization model to determine the optimal offer strategy for a WPP that participates in the day-ahead and real-time energy and spinning reserve markets. The …

Seasonal Comparison Of Air Quality Variables And Evaluation Of Carbon Dioxide And Particulate Measurement Period In Classrooms, Daud Nosham

Durham School of Architectural Engineering and Construction: Dissertations, Theses, and Student Research

Indoor air quality and thermal environmental variables were measured in 55 classrooms in the mid-western United States spanning a full academic year. The studied air quality and environmental factors included carbon dioxide, temperature, relative humidity, particle counts, air velocity, formaldehyde, total volatile organic compounds, carbon monoxide, nitrogen dioxide, and ozone.

Carbon dioxide and Particulate matter concentrations were measured for a four-day measurement period. Then one-day, two-day, and four-day occupied time average concentrations were calculated which were then compared statistically to figure out an appropriate measurement period for these air quality variables. Kruskal Wallis test and Wilcoxon test were used to …

Navigate The World Of Rfid: Diversity, Capabilities, And Constraints Of Readers And Tags, Rachana Pandey

2024 Spring Honors Capstone Projects

Radio-Frequency Identification (RFID) technology, a method for storing and retrieving data through electromagnetic transmission to an RFID tag, is revolutionizing inventory and asset management in various sectors, including healthcare. This research explores the applications of RFID in a medical setting. It assesses various RFID readers and tags, focusing on their functional capabilities, ranges, and limitations within a medical environment. Employing a comprehensive approach, the study integrates an extensive literature review, comparative analysis, and empirical data from both experimental simulations and real-world healthcare scenarios. The aim is to identify RFID solutions that optimize surgical equipment management, thereby enhancing both operational efficiency …

A Dual-Polarimetric Analysis Of A Large Sample Of Left-Moving Supercells, Ben Schweigert

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

Supercells have been researched extensively since they were first described over 50 years ago. They are prolific severe weather producers, responsible for the most severe hail, severe wind gusts, and tornadoes. These rotating thunderstorms require attention from forecasters to protect life and property from their threats, most effectively done with Doppler radars. While extensive amounts of radar-based investigations have been completed, they focused almost exclusively on right-moving (RM) supercells, resulting in a knowledge gap surrounding their counter-rotating (left-moving, LM) partners. This study works to fill the void by developing a dataset of LM supercells and analyzing the dual-polarimetric features observed …

2024 May - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Report

No abstract provided.