Physical Sciences and Mathematics Commons^™

Bandwagon Behavior In Major League Baseball, Daniel E. Erro

Master's Theses

This study investigates “bandwagon” behavior among Major League Baseball (MLB) fans by analyzing Google search interest data from 2004 to 2019. Drawing on publicly available information from Google Trends, the analysis explores how fluctuations in search activity align with team performance during both the regular season and postseason. Hierarchical linear models are used to estimate expected levels of fan interest based on team performance and market characteristics. Deviations from these expectations during the regular season are interpreted as evidence of bandwagon or anti-bandwagon behavior. A drop-off in interest following playoff elimination is also examined to capture shifts in fan attention …

Babies, Babes, And Bayes: Modeling Mother-Infant Feedings With Bayesian Multilevel Hidden Markov Models, Zachary G. Felix

Master's Theses

Understanding the interaction between mother and baby during feeding is critical for the long-term development health of the baby. Overfeeding can lead to later obesity, while underfeeding can lead to malnutrition. In a recent study, the behaviors exhibited by mother-infant dyads across multiple ages of infants have been observed and coded according to the Baby Behaviors when Satiated (BABES) coding scheme. However, creating models using the data obtained from this coding is no simple task since the data coding is continuous, multivariate, and longitudinal in nature. The specific model utilized for these data is a hidden Markov model, since there …

Efficient Gan-Based Adversarial Example Generation Against Ml-Based Network Intrusion Detection Systems, Darren D. Hartono

Master's Theses

In the realm of network security, Network Intrusion Detection Systems (NIDS) are essential for identifying and mitigating malicious activities targeting networked devices. Traditionally, these systems have relied on signature-based and anomaly-based detection techniques. However, the increasing complexity and adapt- ability of cyber threats have driven the adoption of Machine Learning (ML) ap- proaches in modern NIDS, significantly improving their ability to detect a wider range of attack vectors. Despite these advancements, ML-based NIDS remain vulnerable to adversarial examples—deliberately crafted inputs designed to mislead models and trigger incorrect classifications. Originally identified in the field of computer vision, adversarial examples now pose …

Topiarism: The Kernel Embedding Of Distributions Applied To Modern Portfolio Theory, Stephen G. Cook

Master's Theses

The method of kernel embedding of distributions on a set $\Omega$ into a reproducing kernel Hilbert space is a method of studying the space of measures on a set $\Omega$ using Hilbert space geometry. Because positively weighted portfolios can be interpreted as nonnegative probability measures on the space of assets, we are able to apply this technique to portfolio theory. In this thesis, we discuss the theory of "topiarism", the study of positively weighted probability measures on compact sets under the kernel embedding of distributions. Given a specific payoff function $\psi$ on the set of assets $\Omega$, we optimize a …

Poa Annua Ecology, Biology, And Integrated Weed Management Practices In Turfgrass, David Ervin

Environmental Science and Management Faculty Publications and Presentations

Poa annua L. is one of the most widespread and troublesome weeds of turfgrass. It persists as both an annual and perennial and is adaptable to almost any static maintenance regime, including adaptation to mowing heights and evolution of herbicide resistance. This management guide is intended to provide stakeholders with a summary of new and existing knowledge on integrated Poa annua management. Here we review the basic biology and ecology, as well as practical integrated weed management (IWM) strategies developed for its control.

A Critical Evaluation Of The Criticisms Against Neutrosophic Statistical Methods, Muhammad Aslam, Abdulrahman Alaita, Florentin Smarandache

Neutrosophic Systems with Applications

Neutrosophic statistical analysis has gained attention for incorporating the degree of indeterminacy when analyzing imprecise and interval data under uncertainty–-an aspect often overlooked by classical statistics, fuzzy statistical analysis, and interval statistics. Recently, critical discussions have emerged regarding the use and applications of neutrosophic statistics, with some questioning its usefulness and validity. In this paper, we present a critical assessment of the existing literature, focusing on areas where misunderstandings and misinterpretations of neutrosophic statistical methods have occurred. We also examine flawed comparisons made between the results of neutrosophic statistics and interval statistics. Furthermore, substantial issues have been identified in the …

The Influence Of Black Soldier Fly Residue On Watermelon Growth And The Properties Of A Coarse-Textured Ultisol, Benedict Onyebuchi Unagwu, Chidiebere Fransica Odu, Chinedu Felix Amuji, Michael Onyedika Eze, Nancy Ekene Ebido, Chidike Ude Abara, Chioma Rosita Igboka, Uchechukwu Paschal Chukwudi

Chemistry Faculty Research & Creative Works

Improving the fertility status of nutrient-depleted soils is critical to achieving food security. The negative effects of chemical fertilizers on soils necessitate the global quest for eco-friendly, effective, and sustainable alternatives. This work assessed the effect of black soldier fly (BSF) residue application on soil properties and watermelon growth. The study was set up in a completely randomized design with six replications. The treatments were BSF1 (BSF applied at 10 t ha⁻¹), BSF2 (20 t ha⁻¹), BSF3 (30 t ha⁻¹), and control. The plant data collected in this study were vine length, leaf width, …

Efficient Blending Of Large Language Models, Sandeep Chatterjee

Master’s Dissertations

Due to the limited capabilities of single Large Language Models (LLMs), multiple LLMs can be employed in tandem for better reliability of answers. Blending refers to combining the strengths of various LLMs to make use of their complementary capabilities for generating high-quality responses. It is a non-trivial problem, and the task becomes even more difficult when aiming for minimal latency and supervising the blending components. The standard framework, LLM- Blender, approaches this in three stages: response generation, candidate selection via ranking, and response fusion through summarization. However, this pipeline faces two critical limita- tions—high latency due to repeated ranking steps, …

Geometry Based Uav Trajectory Planning For Mixed User Traffic In Mm Wave Communication, Sk Abid Hasan

Master’s Dissertations

Unmanned aerial vehicle (UAV) assisted communication is a revolutionary technology that has been recently presented as a potential candidate for beyond fifth-generation millimeter wave (mmWave) communications. Although mmWaves can o↵er a notably high data rate, their high penetration and propagation losses mean that line of sight (LoS) is necessary for e↵ective communication. Due to the presence of obstacles and user mobility, UAV trajectory planning plays a crucial role in improving system performance. In this work, we propose a novel computational geometry-based trajectory planning scheme by considering the user mobility, the priority of the delay sensitive ultra-reliable low-latency communications (URLLC) and …

Word Level Attack For Text Ranking, Tanmay Karmakar

Master’s Dissertations

Neural Ranking Models (NRMs) have become state-of-the-art in information retrieval, demonstrating remarkable effectiveness across various search and ranking tasks. However, their increasing deployment in real-world systems raises critical concerns about their robustness and susceptibility to adversarial attacks. This project investigates the fragility of modern NRMs by proposing and evaluating a document perturbation method based on targeted, single-word perturbation. Our approach strategically identifies an influential word depending on the query to be substituted or added in the document. We have done experiments on benchmark datasets to assess the impact of these minimal perturbations on ranking performance. Our findings reveal that even …

Designing A Model To Empower Rural Communities For Self-Sufficiency In Zanjan Province, Iran, Azra Ganjkhanloo, Alireza Poursaeed, Roya Eshraghi Samani, Marjan Vahedi

The Philippine Agricultural Scientist

In this research, empowerment is conceptualized as the process through which rural villagers organize themselves to enhance their self-sufficiency, assert their right to independent decision-making, gain control over resources, and address and overcome poverty. This study aimed to develop an empowerment model for rural communities in Zanjan Province, Iran, focusing on achieving self-sufficiency and assessing the model using structural equation modeling. The study compared the main components of the model using the post-event technique and validated the variables of self-sufficiency in rural communities through a descriptive-correlational design and structural equation modeling. The sample comprised 384 villagers selected via stratified random …

Collision Kinematics For Fast Positron Impact Ionization Of Argon, Robert D. Dubois, Károly Tőkési

Physics Faculty Research & Creative Works

Classical trajectory Monte Carlo calculations for 1 keV positron impact ionization of argon are presented. A combination of energy-weighted triple differential cross-sections is shown to provide good to excellent agreement compared with experimental data, depending on the ejected electron azimuthal angular acceptance range used to define in-plane scattering. For ejected electron energies less than 100 eV, information about the influence of pre- (the impact parameter) and post-(the direction of scattering) collision kinematics on the triple differential level is obtained. An overall picture of these kinematic properties is also presented for single differential cross-sections as a function of ejected electron energy …

A Proposed Mathematical Framework For Fuzzy It Service Management (F-Itsm) And Neutrosophic It Service Management (N-Itsm), Takaaki Fujita

Neutrosophic Systems with Applications

Fuzzy sets, rough sets, hyperrough sets, intuitionistic fuzzy sets, neutrosophic sets, plithogenic sets , and other frameworks for handling uncertainty are under active research every day. These concepts can model a wide range of real-world phenomena and are frequently investigated to facilitate more efficient decision-making. IT Service Management is a systematic approach to designing, delivering, managing, and improving IT services in alignment with organizational objectives. In this paper, we explore the Mathematical Frameworks for Fuzzy IT Service Management (F-ITSM) and Neutrosophic IT Service Management (N-ITSM), which combine these uncertainty-based ideas with IT Service Management practices.

Linear Systems Over Pura Vida Neutrosophic Algebra, Rayyanu Abdullahi Muhammad, Abdulhadi Aminu

Neutrosophic Systems with Applications

Neutrosophic numbers offers a strong foundation for representing uncertainty, indeterminacy, and imprecision within mathematical systems. Pura Vida Neutrosophic Algebra (PVNA) expands upon max-plus algebra (also known as tropical algebra or path algebra) using neutrosophic numbers. In this study, we propose a novel extension of the Pura Vida Neutrosophic Algebra (PVNA) by formulating and analyzing linear systems within this algebraic context–an area that, to the best of our knowledge, has not been previously examined. Specifically, we introduce the concept of Neutrosophic Max-Plus Linear Systems, develop an algebraic methodology for their representation, and establish the necessary and sufficient conditions for the existence …

Biochar Suppresses Growth, Pupation And Eclosion Success Of A Specialist (Manduca Sexta) And A Generalist (Spodoptera Frugiperda) Insect Herbivore, Nischal Wagle, Soumya Unnikrishnan, Satinderpal Kaur, Engil Isadora Pujol Pereira, Rupesh R. Kariyat

School of Earth, Environmental, & Marine Sciences Faculty Publications

Biochar is a charcoal-like substance made by the pyrolysis of organic material from agricultural and forestry waste. While biochar is well documented for altering soil physicochemical conditions, few studies have investigated its possible effects on the management of arthropod pests. Tobacco hornworm (Manduca sexta) and fall armyworm (Spodoptera frugiperda, FAW) are specialist and generalist insect herbivores respectively, that can cause significant defoliation in natural and agricultural ecosystems. In this study, we examined whether walnut shell biochar can affect growth and development of these herbivores. Specifically, we investigated how biochar influences parameters such as mass gain, length …

Capfish Project Report : Summer Academy For The Pacific Islands, Kathleen Auld, Francis Neat, Raphaël Baumler

Reports

The CAPFISH Project was created in response to an identified need for capacity-building to address illegal, unreported and unregulated (IUU) fishing and related matters - a complex problem affecting aquatic ecosystems, coastal communities, fishers and fish workers, and economic and national security. Over the last four years, the CAPFISH Project has provided training and educational materials on IUU fishing to developing country administrations around the world, most recently with a two-week regional Summer Academy for the Pacific Islands. This Academy ran for two weeks and included delegates from fisheries, labour, safety, maritime, foreign affairs, and enforcement administrations in the Pacific …

Integrating Universal Generative Ai Platforms In Educational Labs To Foster Critical Thinking And Digital Literacy, Vasiliy S. Znamenskiy, Joel Hernandez, Rafael Niyazov

Publications and Research

This study investigates the educational potential of generative artificial intelligence (GenAI) platforms based on large language models (LLMs), such as ChatGPT, Claude, and Gemini, as tools for studentcentred learning. Recognizing the current limitations of GenAI, particularly its propensity for generating inaccurate or misleading information—the paper proposes a novel instructional strategy: an interdisciplinary laboratory designed to foster critical evaluation of GenAI-generated outputs. In this pedagogical model, students engage with GenAI systems by posing questions or solving problems drawn from topics they have already studied and understand. Equipped with correct answers, students are positioned to assess the accuracy and relevance of AI-generated …

Tailoring Evaluations Of Chronic Rhinosinusitis: Understanding Sleep And Its Effect On Memory Through Actigraphy, Donyea Moore, Rachel Nolte, Yitong Pepper Huang, Shreya Maharana, Pavan Nataraj, Bichun Ouyang, Mahboobeh Mahdavinia

Mathematics Sciences: Faculty Publications

Background/Objectives: Chronic rhinosinusitis (CRS) is a persistent inflammatory condition of the sinonasal mucosa lasting for at least three months. For patients, CRS-related sleep disturbances can significantly disrupt circadian rhythms, leading to further health complications such as cognitive impairment. Despite the well-documented sleep disturbances associated with CRS, there is limited research on objective assessment methods. Additionally, the severity of these issues can vary among patients. This study aims to assess sleep quality and timing in CRS patients and investigate their impact on cognition, providing guidance for personalized and tailored assessment and management of CRS. Methods: Our case–control study compares sleep patterns …

Specialization Or Diversification? Creators’ Strategies On User-Generated Content Platforms, Ziwei Ye

Theses and Dissertations in Business Administration

Recent advancements in digital platforms have reshaped content creation and distribution. User-generated content (UGC), created and shared by internet users, is transforming entertainment, communication, and information sharing. The rise of UGC has fueled the growth of the "creator economy"—an ecosystem of creators, users, and advertisers facilitated by platforms such as YouTube and TikTok. While prior research has primarily explored how UGC platforms incentivize content quantity and quality, this study advances the literature by examining how creators' content strategies influence consumer attention and how platform mechanisms shape this relationship, offering new insights into the interplay between creator behavior and platform design. …

Pfas In Naturally Occurring Surface Water Foams, Donovan S. Vitale

Masters Theses

Surface Water Foam (SWF) and underlying Surface Water (SW) were collected from six distinct sites across Michigan using a novel sampling device. PFAS were detected in all SWF samples with total PFAS concentrations (Σ41 compounds, n=14) varying widely from 2,693 to 402,172 ng/L .SWF samples were enriched in high and intermediate molecular volume PFAS relative to SW samples (n=10) which were dominated by low molecular volume, short-chain PFAS with total PFAS concentrations ranging from 4.4 to 31 ng/L. Wet and dry SWFs were distinguished by appearance, liquid content, and PFAS composition. Dry SWFs had higher total PFAS concentrations than wet …

The Gauge/Gravity Holographic Duality Between String Theory And Quantum Field Theory: A Full Introduction, Alex A. Short

Physics

The Anti-deSitter Spacetime / Conformal Field Theory (AdS/CFT) correspondence is a well known holographic duality between ten dimensional superstring theories and conformal quantum field theories. The existence of such a correspondence is fascinating and the duality provides a powerful tool-set for working out problems in both string theory and quantum field theory. The correspondence defines a dictionary of terms that exist dual to one another in each theory, allowing theorists to understand the dynamics in one system based on quantities from another. Furthermore, when one side of the duality has strong coupling (meaning the approximations of perturbation theory are no …

Understanding And Managing Parent–Child Well Interactions In The Bakken, Kyoung Min, Xue Yu, Nicholas A. Azzolina, Darren D. Schmidt, Bethany A. Kurz, James A. Sorensen

EERC Publications, Papers, & Presentations

This study proposes actionable strategies to mitigate parent–child interactions and negative production impacts. Key approaches, including wider well spacing, optimized stimulation designs, and refracturing, minimize interference while enhancing recovery efficiency.

Comparison Of Gravity Waves Observed By Atmospheric Waves Experiment (Awe) And Simulated By High-Resolution Waccm-X, Jiarong Zhang, Han-Li Liu, Yucheng Zhao, Dominique Pautet, Ludger Scherliess, Michael Taylor

Space Dynamics Laboratory Publications

Outline

Data: AWE and High-Resolution Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (HR-WACCMX) simulation

• Quantify gravity wave (GW) activity
• Compare GW activity observed by AWE and simulated by high-resolution WACCMX
• GW activity over Western Europe

Search For Gravitational Waves Emitted From Sn 2023ixf, A. G. Abac, R. Abbott, Teviet Creighton, Mario C. Diaz, Francisco Llamas Villarreal, Soma Mukherjee, Volker Quetschke, Wenhui Wang

Physics & Astronomy Faculty Publications

We present the results of a search for gravitational-wave transients associated with core-collapse supernova SN 2023ixf, which was observed in the galaxy Messier 101 via optical emission on 2023 May 19, during the LIGO–Virgo–KAGRA 15th Engineering Run. We define a five-day on-source window during which an accompanying gravitational-wave signal may have occurred. No gravitational waves have been identified in data when at least two gravitational-wave observatories were operating, which covered ∼14% of this five-day window. We report the search detection efficiency for various possible gravitational-wave emission models. Considering the distance to M101 (6.7 Mpc), we derive constraints on the gravitational-wave …

Radiation-Induced Cardiotoxicity In Hypertensive Salt-Sensitive Rats: A Feasibility Study, Dayeong An, Alison Kriegel, Suresh N. Kumar, Heather A. Himburg, Brian Fish, S. Klawikowski, Daniel B. Rowe, Marek Lenarczyk, John Baker, El Sayed H. Ibrahim

Mathematical and Statistical Science Faculty Research and Publications

Radiation therapy (RT) plays a vital role in managing thoracic cancers, though it can lead to adverse effects, including significant cardiotoxicity. Understanding the risk factors like hypertension in RT is important for patient prognosis and management. A Dahl salt-sensitive (SS) female rat model was used to study hypertension effect on RT-induced cardiotoxicity. Rats were fed a high-salt diet to induce hypertension and then divided into RT and sham groups. The RT group received 24 Gy of whole-heart irradiation. Cardiac function was evaluated using MRI and blood pressure measurements at baseline, 8 weeks and 12 weeks post-RT. Histological examination was performed …

A Novel Closed Monoidal Structure On The Nucleus Of A Profunctor, Samantha K. Jarvis

Dissertations, Theses, and Capstone Projects

We describe a novel closed monoidal structure on the nucleus of a profunctor enriched over a posetal category, a distinguished subcategory of the category of presheaves given by the invariant part of an adjunction induced by the profunctor. Our structure is motivated by a connection to a notion of type given by orthogonality. For specific examples, we consider the two-element enriching category {0,1} and the reals.

Unpacking The Orders, Leonard J. Santos

Dissertations, Theses, and Capstone Projects

At the end of the first week of his presidency this year in 2025, Donald Trump signed a total of thirty-six executive orders. After only one month, that number had gone up to seventy-six. He is currently on track to sign the highest number of executive orders in his first year in office of any president in the last 50 years, and potentially even the last 100 years if he keeps moving at this rate. In the first 90 days of his term, Donald Trump has signed 159 executive orders, more than any other president in the history of the …

Parametrization Of Formal Norm Compatible Sequences, Joseph Dicapua

Dissertations, Theses, and Capstone Projects

We give a classification of power series parametrizing Lubin-Tate trace compatible sequences. This proof answers a question posed in the literature by Berger and Fourquaux. Lubin-Tate trace compatible sequences are a generalization of norm compatible sequences, which arise in Iwasawa theory and local class field theory. The result we prove generalizes the interpolation theorem proved by Coleman in the classical norm compatible sequence case. We also, jointly with Victor Kolyvagin, give a method for finding such series explicitly in certain special cases.

Evaluating Disaster Relief In Supply Chains Using A Neutrosophic Mcdm Approach, Nada A. Nabeeh

Neutrosophic Systems with Applications

Disaster-prone regions and affected areas encounter persistent challenges in maintaining supply chain continuity due to environmental uncertainties and infrastructure disruptions. Effective supply chain disaster management (SCDM) is essential for relief disaster disruptions, specifically in upstream processes and functions within the humanitarian supply chain. The integration of advanced technologies like the metaverse and Multiple-Criteria Decision-Making (MCDM) methods supports strategic planning and enhances resilience. This study presents a multi-criteria decision-making (MCDM) proposed approach for disaster relief evaluation in supply chain management. The proposed model integrates Interval-Valued Neutrosophic Numbers (IVNNs) to manage uncertainty and ambiguity inherent in disaster various criteria which are often …

Unveiling Exosomal Biomarkers In Neurodegenerative Diseases: Lc-Ms-Based Profiling, Yue Bi, Liang Wang, Chunyan Li, Zhiying Shan, Lanrong Bi

Michigan Tech Publications

Exosomes, small extracellular vesicles secreted by various cell types, play a critical role in intercellular communication and are increasingly recognized as key players in the progression of neurodegenerative diseases (NDs). Their ability to carry and propagate pathogenic proteins such as amyloid-beta, tau, and alpha-synuclein have established exosomal biomarkers as both key players in disease pathology and promising indicators for early diagnosis. Liquid chromatography-mass spectrometry (LC-MS) has emerged as a powerful tool for the comprehensive analysis of exosomal cargo, enabling the identification of proteins, metabolites, and other molecules associated with neurodegeneration. This review explores the structural composition, biogenesis, and role of …