Physical Sciences and Mathematics Commons^™

Metabolic Characterization Of Porcine Hepatocytes, Sophie Swart, Ainslie Robinson, Daiki Jonouchi, Marcus Blankespoor, Kip Cullinan, Zachary Varpness, Ryan Schulze

Celebration of Research

No abstract provided.

H(Hydrogen)-Alpha Spectral Imaging Of Z>5 Quasars, Pratik Paudel, Mari Hirota, Hyunsung Jun

Celebration of Research

We aim to measure the H-alpha line excess over the photometric continuum for distant quasi-stellar radio objects, or quasars. Supermassive black holes grow in mass through accretion of stars or gas nearby, often outshining the total stellar light of the galaxies they reside in, for quasars. On the other hand, the structure of these active galactic nuclei are hard to resolve, where we often rely on the relationship in between different light emission regions to better understand the geometry and emission mechanisms. In this work, we measure the H-alpha luminosity of 44 quasars at z>5 (light coming from less …

The Impact Of Blood Flow Restriction On Heart Rate And Muscle Activation, Janaya Battles, Rajat Singh, Daniel Swier

Celebration of Research

Blood Flow Restriction (BFR) is a rehabilitation technique used in physical therapy to improve muscle growth in patients. The technique involves using blood cuffs on the limbs to occlude blood flow within the muscles, thus limiting the buildup of muscle growth inhibitors. The current literature provides information regarding these aspects but is limited in providing information regarding the impact of BFR on neural muscular coordination. Therefore, the purpose of this study was to determine how various pressure levels of the BFR cuffs can impact the muscle activation of the restrained muscles and heart rate. Our results have shown that a …

Latent Classification Of Multi-Model Non-Homogeneous Continuous-Time Markov Chains, Joonha Chang

Dissertations and Theses (Open Access)

The continuous-time Markov chain (CTMC) model and latent clustering models are commonly used to study longitudinal measures of categorical outcomes. Because of its simple but powerful Markovian property, CTMC models have been widely used in medical and public health researches. Due to limitations in the standard CTMC model, there have been some studies on non-homogeneous continuous-time Markov chain (NH-CTMC) that utilized time-dependent rates, but the progresses have been limited. NH-CTMC can be more powerful than CTMC by its default nature of time-dependent rate that can be fitted to a wider range of applications in medical studies. In this study, we …

Context-Aware Affective Behavior Modeling And Analytics, Md Taufeeq Uddin

USF Tampa Graduate Theses and Dissertations

Affective computing (AC) is a sub-domain of AI that has the potential to assist people by assessing mental states and making appropriate recommendations to patients, loved ones, caregivers, and domain experts. Humans usually produce an enormous amount of data (such as face videos) every day. One of the major challenges for affective computer vision is to efficiently deal with high volumes of data to facilitate automated model development. To cope with this challenge, we developed computer vision algorithms that measure the expressivity of the human face from video data. More precisely, the developed algorithms can map complex affect information from …

2024 April 11 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Patterns, Drivers, And Implications Of Postfire Delayed Tree Mortality In Temperate Conifer Forests Of The Western United States, Sebastian Busby, Cody Evers, Andrés Holz

Geography Faculty Publications and Presentations

Conifer forest resilience may be threatened by increasing wildfire activity and compound disturbances in western North America. Fire refugia enhance forest resilience, yet may decline over time due to delayed mortality—a process that remains poorly understood at landscape and regional scales. To address this uncertainty, we used high-resolution satellite imagery (5-m pixel) to map and quantify delayed mortality of conifer tree cover between 1 and 5 years postfire, across 30 large wildfires that burned within three montane ecoregions in the western United States. We used statistical models to explore the influence of burn severity, topography, soils, and climate moisture deficit …

Protecting American Children: A Social-Ecological Analysis Of Pactp4, Julia Rossmiller

Student Works

The quantity of pesticides used annually in the United States exceeds one billion pounds every year, and the amount is only rising. The current law that governs the use of pesticides—The Federal Insecticide, Fungicide and Rodenticide Act (FIFRA), permits the use of 72 known pesticides that have been proven harmful and are banned in other countries. Research links the usage of pesticides to the health of individuals, families, and whole communities within the environment. Moreover, dangerous pesticides have been shown to disproportionately affect children, agricultural workers, people of color, and low-income communities. Despite the mounting evidence that confirms the adverse …

Shared Genomic Segments Analysis Identifies Mhc Class I And Class Iii Molecules As Genetic Risk Factors For Juvenile Idiopathic Arthritis, Cecile N. Avery, Nicole D. Russell, Cody J. Steely, Aimee O. Hersh, John F. Bohnsack, Sampath Prahalad, Lynn B. Jorde

Markey Cancer Center Faculty Publications

Juvenile idiopathic arthritis (JIA) is a complex rheumatic disease encompassing several clinically defined subtypes of varying severity. The etiology of JIA remains largely unknown, but genome-wide association studies (GWASs) have identified up to 22 genes associated with JIA susceptibility, including a well-established association with HLA-DRB1. Continued investigation of heritable risk factors has been hindered by disease heterogeneity and low disease prevalence. In this study, we utilized shared genomic segments (SGS) analysis on whole-genome sequencing of 40 cases from 12 multi-generational pedigrees significantly enriched for JIA. Subsets of cases are connected by a common ancestor in large extended pedigrees, increasing the …

Identifying A Group Of Factors Predicting Cognitive Impairment Among Older Adults, Longgang Zhao, Yuan Wang, Eric Mishio Bawa, Zichun Meng, Jingkai Wei, Sarah Newman-Norlund, Tushar Trivedi, Hatice Hasturk, Roger Newman-Norlund, Julius Fridriksson Ph.D., Anwar T. Nerchant

Faculty Publications

Background

Cognitive impairment has multiple risk factors spanning several domains, but few studies have evaluated risk factor clusters. We aimed to identify naturally occurring clusters of risk factors of poor cognition among middle-aged and older adults and evaluate associations between measures of cognition and these risk factor clusters.

Methods

We used data from the National Health and Nutrition Examination Survey (NHANES) III (training dataset, n = 4074) and the NHANES 2011–2014 (validation dataset, n = 2510). Risk factors were selected based on the literature. We used both traditional logistic models and support vector machine methods to construct a composite score …

The Effectiveness Of Using Near-Peer Role Models And Mentoring: A Phenomenological Reflection On Stem For Success, Bruce G. Bukiet, Cristo Leon, James Lipuma

STEM for Success Resources

The proper study of communication from existing models opens the doors to scientific research that allows exploring language and coding as an integral part of effective communication to generate new models that include Trans-Disciplinary Collaboration. The authors analyze the communication factors to describe the application of Trans-Disciplinary Communication. This paper aims to define communication processes and their relationship with language, considering their impact on trans-disciplinary collaboration and innovation. After conducting a systematic literature review, the article explored the concepts of communication, functions, language, and Trans-Disciplinary Communication. This led to its application in the convergence research approach presented in the Collaborative …

Machine Learning Techniques For Intermediate Mass Gap Lepton Partner Searches At The Large Hadron Collider, Bhaskar Dutta, Tathagata Ghosh, Alyssa Horne, Jason Kumar, Sean Palmer, Pearl Sandick, Marcus Snedeker, Patrick Stengel, Joel W. Walker

Michigan Tech Publications

We consider machine learning techniques associated with the application of a boosted decision tree (BDT) to searches at the Large Hadron Collider (LHC) for pair-produced lepton partners which decay to leptons and invisible particles. This scenario can arise in the minimal supersymmetric Standard Model (MSSM), but can be realized in many other extensions of the Standard Model (SM). We focus on the case of intermediate mass splitting (∼30 GeV) between the dark matter (DM) and the scalar. For these mass splittings, the LHC has made little improvement over LEP due to large electroweak backgrounds. We find that the use of …

Variable Drought Impacts On Stream Habitat Across The Northwestern Us, Sophia Withers

Student Research Symposium

The United States has been in a continuous drought since 2002. Stream quality, specifically in the context of fish habitat, depends on many variables, including vegetation quality. Drought conditions affect vegetation conditions, however it is unclear how drought conditions impact stream habitat quality for fish. Objectives for my project include:

• How does stream habitat quality relate to drought across National Forests of the Northwestern US?
• Has drought increased impacts on riparian vegetation over the past 20 years?

Simulating Ice Nuclei Under Atmospheric Electric Fields, Joseph Cooney

Student Research Symposium

Orographic clouds generally form over mountains when valleys are sunny. The unstable atmosphere can trigger clouds over the mountains, which can be convective. When this happens, the cloud particles (water droplets and ice particles) become charged, ultimately creating ice crystals. In this study, we want to evaluate the impact of electricity on the formation of ice crystals and used a simulation to do so.

Assessing The Promise And Pitfalls Of Chatgpt For Automated Cs1-Driven Code Generation, Fawad Khan, Max Ramsdell

Student Research Symposium

Definition and Overview of Large Language Models:

• Large Language Models (LLMs) are advanced AI algorithms designed to understand, generate, and interact with human language at a vast scale.

The Evolution of LLMs:

• The development of LLMs has progressed
• 1960 - Basic LLM - basic predictive text functions
• 2017- Transformers - Core model powering ChatGPT introduced
• 2022 - ChatGPT context-aware systems

Chemtrails: Deadly Skies Or Dangerous Misinformation?, Abigail Foust

Undergraduate Research Symposium

A common sight on a clear day is a thin strip of white across the otherwise blue sky: A contrail. Most people do not think anything of these contrails, and assume they have little to no impact on the world at large. Suppose for a moment, however, that they are not as harmless as some believe. Suppose these cloud trails are actually composed of dangerous chemicals, and are being used by sinister forces in a conspiracy to kill off the weak, mind-control the population, or simply dull our minds in preparation for a government takeover. As far-fetched as this may …

Assessing Chatgpt As A Programming Exercise Generator, Maxwell Ramsdell, Fawad Khan

Student Research Symposium

Motivation

• Proximal Zone of Development
• Teaching Efficiency
• Cross-Discipline Applications

For these to work, we need to evaluate the effectiveness with which chatGPT writes coding exercises

Teaching A Computer To Do Mechanics, Andrew Watson

Student Research Symposium

Classical Mechanics

- Used for determining motion of objects

- Three Main Formulations of Classical Mechanics

• Newtonian Mechanics: Revolves around Newton’s 2nd Law (F = ma)
• Lagrangian Mechanics: Revolves around the Lagrangian
• Hamiltonian Mechanics: Revolves around the Hamiltonian

- Hamiltonian Mechanics provides the most powerful view of mechanics – but it’s complicated!

• My goal is to get the computer to do Hamiltonian Mechanics.

Enhancing Galaxy Surveys With Machine Learning, Steven Karst

Undergraduate Research Conference at Missouri S&T

Applications of machine learning (ML) or artificial intelligence (AI) to problems in astrophysics and cosmology have recently entered a golden era. In response, we have updated two of our recent ML/ AI efforts that contribute to galaxy surveys whose main scientific target is to reveal the nature of the Cosmic Acceleration or Dark Energy. We first revised our effort to infer cosmological information beyond the survey geometry using Graph Neural Networks (GNN) to take advantage of supercomputing resources on campus. We then updated our reinforcement learning methods for galaxy target selection in the Subaru Prime Focus Spectrograph (PFS) survey with …

Visualization Of Ultracold Atomic Samples, Samuel Schrader

Undergraduate Research Conference at Missouri S&T

Laser cooling techniques have evolved into a powerful experimental tool to perform precision spectroscopy (for instance, atomic clocks), study fundamental few-body dynamics, and create well-controlled systems for quantum information applications. When the atoms are captured, it is critical to analyze the laser-cooled atomic samples carefully and characterize their properties, such as density, temperature, population distribution, etc., in order to perform these advanced tasks. A straightforward way to measure these properties is detecting the visible optical photons emitted from the sample with a camera. Throughout this project, I have written and developed a computer application that controls a camera and extracts …

Gender And The Billboard Top 40 Charts Between 1958 And 2023, Brileigh Cates, Justin W. Pope

Undergraduate Research Conference at Missouri S&T

Is there an inherent bias towards male artists in the music industry? Evidence has been shown in previous studies, the most recent being from 2017, that there may be bias towards male artists appearing in Billboard Magazine s Hot 100 list. This study not only updates previous data to include 2017 through 2023, but also looks at the top 40 charts on a week-by-week bias as opposed to the year-end charts that other studies used for their data. We coded each song so as to indicate the gender of the artist(s) as well as whether or not the artists appeared …

Ta Theoretical Framework For Comparing Rlhf Method, Matthew Dominicis

Undergraduate Research Conference at Missouri S&T

Reinforcement Learning from Human Feedback (RLHF) can be used as a means to align Al agents and Large Language Models (LLM) to better represent human expectations. There is a myriad of RLHF methods that exist, however it is difficult to benchmark and compare such methods in terms of alignment, training cost, data collection cost, and other metrics. This project aims to create a robust classification for different RLHF methods from a theoretical point of view. Additionally, this project will attempt to propose bounds for the degree of influence on LLMs that stems from human feedback. Open source LLMs will be …

Heat's Effect On Asphalt Binders Using Nmr, Kaitlin Miles

Undergraduate Research Conference at Missouri S&T

Nuclear Magnetic Resonance (NMR) spectroscopy is a well-known analytical technique that uses the excitation of nuclear spins for solving chemical structures and conformations. Relaxometry is a special field of NMR spectroscopy where information is gained about interactions of 100 nuclear spins with their molecular surroundings. The deterioration of asphalt is a major infrastructure problem, and its rejuvenation back toward its original virgin state is an important field of research and development. The current asphalt industry relies on visual inspection on site and invasive or destructive physical methods to assess emerging asphalt failures. This study examines the chemical changes environmental factors …

Amorphous Transparent Oxide P-Type Semiconductors, Joshua Santy

Undergraduate Research Conference at Missouri S&T

For decades, n-type transparent conducting oxides (TCOs) have been extensively studied and applied in various energy and optoelectronic devices. However, the search for high-performance p-type TCOs, crucial for transparent p-n junctions and next-generation microelectronics - remains uncertain. The most studied p-type TCOs (e.g ., Cu2O-based delafossite family) exhibit the carrier mobilities (<1 cm2Ns) that are much smaller than those in typical n-type TCOs (10-100 cm2Ns). In contrast to the Cu-based layered materials with a relatively flat Cu d10 valence band (resulting in the hole effective mass of 2.5me), Sn2+ in SnO has s2 electronic configuration giving rise to a significantly more dispersed valence band (the hole effective mass is 0.5me) and, hence, to higher hole mobility. Currently, the practical use of SnO is limited due to (i) stability issues of SnO associated with tin preference for valence 4 (as in SnO2, a well-known n-type TCO); (ii) small band gap ~0.7 eV; and (iii) anisotropic hole effective mass in the crystalline phase. Further search for p-type TCOs should involve amorphous phases of SnO-based multi-cation materials where metal composition helps stabilize Sn2+ and open the band gap, whereas the disordered structure is expected to result in uniform isotropic electronic properties and low scattering due to absence of grain boundaries.

Effects Of Reproduction On Senescence In Local Species, Nathan Smith

Undergraduate Research Conference at Missouri S&T

Understanding the impact of reproduction on the aging process within species populations remains an ongoing challenge in ecological and evolutionary research. In this study, we aim to clarify the relationship between reproduction and senescence using agent-based modeling using wild species data sets. Our objectives include investigating how variations in reproductive rates influence the lifespan and aging trajectories of individuals within populations, as well as identifying potential mechanisms underlying these effects. We will employ agent-based modeling to simulate populations and explore the dynamics of reproduction and senescence using publicly available datasets of local wild species. By manipulating parameters related to reproductive …

Enhancing Galaxy Surveys With Machine Learning, Steven Karst

Undergraduate Research Conference at Missouri S&T

Applications of machine learning (ML) or artificial intelligence (Al) to problems in astrophysics and cosmology have recently entered a golden era. In response, we have updated two of our recent ML/Al efforts that contribute to galaxy surveys whose main scientific target is to reveal the nature of the Comsic Acceleration or Dark Energy. We first revised our effort to infer cosmological information beyond the survey geometry using Graph Neural Networks (GNNs) to take advantage of supercomputing resources on campus. We then updated our methods for galaxy target selection in the Subaru Prime Focus Spectrograph (PFS) survey with modern reinforcement learning …

Effect Of Heat On Virgin And Uv-Aged Asphalt Binders Determined By Nuclear Magnetic Resonance Relaxometry, Kaitlin Miles

Undergraduate Research Conference at Missouri S&T

Nuclear Magnetic Resonance (NMR) spectroscopy is a well-known analytical technique that uses the excitation of nuclear spins for solving chemical structures and conformations. Relaxometry is a special field of NMR spectroscopy where information is gained about interactions of nuclear spins with their molecular surroundings. The deterioration of asphalt is a major infrastructure problem, and its rejuvenation back toward its original virgin state is an important field of research and development. The current asphalt industry relies on visual inspection on site and invasive or destructive physical methods to assess emerging asphalt failures. This study examines the chemical changes environmental factors have …

Application Of T Gates For Anti-Concentration In Clifford Circuits, Matthew Dominicis, Mason Toombs, Gabriel Riddle, Parineeta Puja Saha, Himanth Bobba

Undergraduate Research Conference at Missouri S&T

Our study examines the integration of non-Clifford T gates into randomly generated Clifford circuits to enhance their universal unitary capacity. We investigate the impact of T gates on circuit output randomness, focusing on generating random Clifford circuits and analyzing the effects of T gates. Through simulations and analysis, we assess the effectiveness of this modification in achieving outputs consistent with Anti concentration properties while minimizing the required number of Clifford gates. Our findings provide valuable insights into quantum circuits, with implications for quantum computing applications.

The Search For The Akwamu People In The Americas, 1729-1733, Ben Brown, Justin Pope

Undergraduate Research Conference at Missouri S&T

This Poster presentation attempts to trace the journey of one nation of Africans into the Americas. In 1729, the Akwamu Empire, in modern day Ghana, West Africa, suffered a terrible collapse. Rival African armies enslaved thousands of Akwamu subjects and sold them to European slavers on the Gold Coast. This nation later led the biggest island wide slave revolt prior to the age of revolution in the Americas. Using primary and secondary resources such as the "Transatlantic Slave Trade Database," we will attempt to identify the European slave ships that purchased enslaved Akwamu people and trace their journey into the …

The History Of The Billboard Hot 100 And Its Process, Brileigh Cates

Undergraduate Research Conference at Missouri S&T

The Billboard Hot 100 has been around for decades, and it is believed without much accreditation. What really is Billboard, and why is it so popular? Why have other charting companies not taken up as much popularity? How does Billboard determine the popularity of artists? How has this changed with the introduction of the internet? This research project addresses all of these question, allowing the validity of the data collection to be addressed.