Digital Commons Network^™

The Case For Ice Rises At Ross Bank Since The Middle Miocene, William Weber

LSU Master's Theses

Many tens of ice rises exist at the marine margins of the Antarctic Ice Sheet. Isle-type ice rises in particular are those where an ice shelf is pinned to an underlying submarine bank. Recent and ongoing studies show that Ross Bank, on the middle continental shelf of central Ross Sea, was the former site of an important Ross Ice Shelf ice rise during the advance and retreat of the West Antarctic Ice Sheet (WAIS) in the last glacial cycle. Ross Bank is a broad and anomalously shallow water platform whose crest rises to 170 m water depth. Despite their importance …

Unraveling The Nanoscopic Characteristics Of The Heterogeneous Deep Eutectic Solvent Formed By Lauric Acid And N-Methylacetamide: An Experimental And Computational Approach, Laura X. Sepulveda

LSU Doctoral Dissertations

Deep eutectic solvents (DESs) are attractive systems for extraction and separation of compounds. One example of this is the DES formed by the combination of lauric acid (LA) and N-methylacetamide (NMA), system that has been shown to efficiently separate oil/water mixtures through gel formation between LA and oil molecules. Structural characterization of this system using small-angle X-ray scattering (SAXS) and vibrational spectroscopy revealed the existence of nanometer-scale LA domains embedded in a continuous polar NMA phase, where LA and NMA interact through hydrogen bonding. These LA domains are responsible for the separation efficiency of linear organic molecules. However, this DES …

Safe By Construction, Personalized By Design: Formal Methods Meet Human Feedback For Safe And Adaptive Autonomous Systems Behavior, Ruya Karagulle, Necmiye Ozay

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Explicit Safety Filters For Linear Systems: Dynamical Properties And Robustness Margins, Shima Sadat Mousavi, Pol Mestres, Aaron D. Ames

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Physics-Informed Sensing And Adaptive Control For Indoor Air Quality Management, Avijit Sarker, Saeid Chahardoli, Mina Lesan, Yi Xiao, Andrew Johannsen, Arup Bhattacharya

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Advances In Sampling-Based Uncertainty Quantification For Safe Learning-Based Control, Abdullah Tokmak, Thomas B. Schön, Dominik Baumann

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Blood Pressure Prediction During Hemorrhage And Blood Transfusion: A Population-Informed Sequential Inference Approach, Yi-Ming Kao, Parham Rezaei, Sina Masoumi Shahrbabak, Jeremy Alanano Pepino, Ian Sebastian Kirk Shogren, Yang Wang, Andrew Tomas Reisner, Jin-Oh Hahn

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Morphquad: Morphable Quadrotor For Superhuman Maneuverability, Manipulation, And Resiliency, José Díaz Peón González Pacheco, Jiawei Xu Dr., Andrew Zhao, Hongyu Zhou, Atharva Navsalkar, Andrew Scheffer, Amrith Malli Reddi, Sashreek Shankar, Yuqing Ivan Bao, Vasileios Tzoumas Dr.

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Bilevel Convex Identification Of Autonomous Multi-Mode Switching Systems, Kaito Iwasaki

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Autonomy For Lunar Surface Infrastructure Construction, John Cooper, Irina Kostitsyna, Olivia Irene B. Formoso, Dominic Bisio, Joshua N. Moser, Matthew P. Vaughan, Joshua N. Moser, Matthew K. Mahlin

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Modal Supervisory Coordination Of Power Source Transitions In Data Centers Via Lingua Franca And Simulink Co-Simulation, Md Rubel Ahmed, Md Kibria Saroare

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

A Multi-Scale Hierarchical Framework For Long-Horizon Sequential Robotic Manipulation, Mahdi Bonyani, Maryam Soleymani, Chao Wang Phd

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Scene-Aware Multimodal Grounding For Verifiable Robot Task Planning, Kshitiz Dhungana, Nina Jiang

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Newton-Flow Particle Filters Based On Generalized Cramér Distance, Uwe D. Hanebeck

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

Gap Metrics For Model Fidelity Quantification In Dynamical Systems, Quintin Nelson, Manoranjan Majji

2026 LSU Symposium on Control, Learning, and Intelligent Systems

No abstract provided.

The Statistical Distribution Of U.S. Corn And Soybean Futures Prices, Chiamaka D. Osigwe

LSU Master's Theses

This thesis investigates the best-fit empirical distribution for daily U.S. corn and soybean futures price changes and examines how distributional choices affect Value-at-Risk (VaR) and Expected Shortfall (ES) estimates. The dataset comprises daily nearby futures prices for corn (11/16/1994–04/23/2025) and soybeans (10/16/1979–02/15/2023), yielding 7,626 and 10,853 observations, respectively. An ARCH-LM test confirms the presence of Autoregressive Conditional Heteroskedasticity (ARCH). Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models were estimated, and to account for potential asymmetric effects, an EGARCH model was used. EGARCH (1,1) estimation reveals an inverse leverage effect, where positive price shocks generate higher volatility. Six heavy-tailed distributions were evaluated, and …

Evaluating Soil Health And Crop Yield In Louisiana Agricultural Systems: Impacts Of Best Management Practices And Prediction Models, Hector J. Mendoza Lagos

LSU Doctoral Dissertations

The adoption of conservation management practices is critical for improving soil health, enhancing nutrient use efficiency, and sustaining crop productivity in row crop systems in Louisiana. This study evaluated the role of conservation agronomic practices, soil biochemical indicators, and machine learning predictive models to improve soil nutrient dynamics, soil health indicators, microbial communities (MC), and crop productivity on a corn (Zea mays L.) research plot scale and in a commercial forty-hectare cotton (Gassypium hirsutum L.)-corn-soybean (Glycine max L.) rotation system in northeast Louisiana. The objectives of the study were to evaluate soil nutrient dynamics and MCs under …

Distributed File Carving, Brad J. Baudin

LSU Master's Theses

File carving is a fundamental technique in the digital forensics community, enabling analysts to recover deleted files from disk images without relying on filesystem metadata; however, as storage capacities continue to increase, modern file carving tools face significant scalability challenges, with carving time growing substantially alongside disk image size, particularly in the presence of file fragmentation. Fragmentation, a common behavior in modern filesystems, distributes file data across non-contiguous disk blocks to maximize space utilization, and in large disk images this distribution can span wide logical distances, increasing the search space and reducing carving efficiency, causing traditional approaches to struggle within …

The Effects Of Asymmetric Cervical Muscle Fatigue On Cervical Proprioception, Stepping, And Standing Postural Sway, Maryam Homafar

LSU Master's Theses

Background: The cervical spine contributes critically to proprioception and postural control through its dense mechanoreceptor population. The acute effects of asymmetrical cervical muscle fatigue on proprioception, gait, and balance remain understudied, especially considering its widespread occurrence in multiple populations.

Objective: To investigate the acute effects of asymmetrical cervical muscle fatigue on cervical proprioception, stepping ability, and standing postural sway in healthy young adults.

Methods: Eighteen of 25 healthy participants, who met the inclusion criterion of baseline cervical joint position error (CJPE) below 4.5° for left and right rotational directions, completed pre-fatigue and post-fatigue assessments with eyes closed, including CJPE test, …

Yoga And Young Children, Jayapriya Ranganathan, Cynthia F Dicarlo

Spark! Innovations in Early Childhood Education: A Research-to-Practice Journal for Educators

Abstract:

This article examines the role of yoga as an effective pedagogical tool to support social-emotional learning (SEL) and physical development in early childhood education settings. Grounded in current understandings of mindfulness and executive functioning, the integration of yoga practices—such as breathing exercises, meditation, and developmentally appropriate postures—can promote self-regulation, attention, and emotional resilience in young children. Drawing on classroom-based observations from a toddler program, the article outlines practical strategies for incorporating yoga into daily routines, emphasizing accessibility, consistency, and engagement through imaginative play and storytelling. The findings suggest that regular yoga practice fosters a calm, focused learning environment and …

Models, Agency, And Expectations: A Mixed-Methods Study Of How Character Develops In Middle School, Aaron J. Schwindt

LSU Doctoral Dissertations

This explanatory sequential mixed-methods study investigated how character develops among middle school students at an international school recognized as a "National School of Character." Despite significant investment in character education (CE), a lack of formal evaluation exists, particularly regarding the process of development during the critical middle school years, a period of intense neurological and social change. Grounded in Bandura's Social Cognitive Theory (SCT), this study aimed to (1) understand how character develops, (2) compare development before and after program enhancements, and (3) assess the program's impact on discipline. Phase 1 collected Character Growth Index (CGI) survey data from students …

Momentum Space Algorithm For Electronic Structure Of Double-Incommensurate Trilayer Graphene, Kenneth Silver Beard

LSU Doctoral Dissertations

Numerical algorithms for computing the electronic structure of incommensurate 2D-materials using ab initio models are critical for predicting material properties and guiding experiments. For bilayers, momentum space and continuum models have been introduced to approximate observables of ab initio tight-binding models using a momentum description, despite the lack of periodicity in the tight-binding model required for Bloch theory. A similar structure has been introduced for double-incommensurate trilayers using a continuum model, where the three lattices are mutually incommensurate. However, this description leads to a four-dimensional lattice space, and numerical convergence of the density of states has been observed to be …

Greedy Algorithms And Matroids, Kiri M. Strack

LSU Master's Theses

In a connected graph with weights on the edges, a minimum-weight spanning tree can be obtained by repeatedly choosing minimum-weight edges while avoiding choosing the edge set of any cycle. This algorithm is known as Kruskal’s Algorithm, although it was first introduced by Boruvka in 1926. Prim introduced an alternative algorithm in which, at each step, the chosen set of edges forms a connected graph. Both of these algorithms make locally optimal choices that eventually yield a global optimum. This thesis considers how these algorithms can be extended to matroids. In particular, it is shown that matroids are exactly the …

Automated Analysis Of Radiation Oncology Incident Reports Using Large Language Models, Nathan A. Dobranski

LSU Master's Theses

Patient safety incident reporting in radiation oncology requires expert analysis that is time-intensive and subject to variability. This thesis presents the development and technical validation of a locally deployed large language model (LLM) system for automated incident report analysis across multiple cancer centers. The system was designed for automated summarization and taxonomy assignment of Radiation Oncology Incident Learning System (RO-ILS) reports, operating entirely on local infrastructure to preserve patient privacy. A two-round, multi-rater evaluation methodology was employed, incorporating 600 total expert evaluations from two academic cancer centers. Round 1 established baseline performance using Mistral 7B and Mixtral 8x7B models with …

Noncontingent Parental Attention Leads To Independent Play And Is Preferred By Toddlers Over Screen Time, Kristen Newell

LSU Doctoral Dissertations

Caregivers often rely on screen media to occupy young children during periods when caregiver attention is unavailable, despite evidence linking early screen exposure to adverse developmental outcomes. An alternative approach is to provide high-quality, noncontingent attention (NCA) during play prior to independent activity. Although NCA reduces attention-maintained challenging behavior, the optimal duration of NCA and children’s preference for caregiver interaction relative to screen time remain unclear. This study evaluated the effects of varying durations of caregiver-delivered NCA on young children’s independent play, attention-seeking behavior, and preference for NCA compared to screen time. Three caregiver–child dyads participated in a multielement design …

Analyzer-Less X-Ray Interferometry With Super-Resolution Methods, Murtuza S. Taqi

LSU Master's Theses

X-ray interferometry provides valuable information on attenuation, small-angle scattering, and differential phase contrast. This multi-modal contrast can aid in many clinical applications, such as lung diseases and breast cancer. However, standard inter- ferometry has an analyzer grating that can increase the dose requirement to maintain the same image quality as a standard X-ray. We propose the use of super-resolution methods for X-ray grating interferometry without an analyzer, with detectors that fail to meet the Nyquist sampling rate needed for traditional image recovery algorithms. Detector phase- steps are used to nominally recover the sampling and iteratively recover the visibility and the …

Setbacks And Stigmas: The Career Consequences Of Mental Health Treatment For Soldiers In Combat Roles, Micah Mark Marchand

LSU Master's Theses

This study examines how potential career consequences, perceived stigma, and confidentiality concerns influence mental health help-seeking among United States Army Soldiers, with particular attention to differences across Military Occupational Specialty (MOS) categories. Despite the availability of behavioral health services, many service members delay or avoid treatment due to fears that seeking care may negatively impact their careers, including risks to promotion, deployment eligibility, and retention. Guided by Systems Theory, this research explores how interconnected military structures, policies, and cultural norms shape these perceptions and behaviors.

Using a confidential survey design, data were collected from current service members and recently separated …

Public Understanding Of Ai-Enabled Cyber Threats And Its Impact On Cybersecurity Governance In The United States, Charlotte M. Barbrick

LSU Master's Theses

Artificial intelligence is spreading quickly in workplaces and everyday life, and that fast growth is creating cybersecurity and privacy risks that current laws and organizational practices do not fully address. This thesis asks whether AI-specific knowledge shapes public support for cybersecurity governance of AI-enabled systems in the United States. Using nationally representative survey data from the Pew Research Center’s American Trends Panel (ATP) Wave 119, fielded December 12--18, 2022, I estimate weighted regression models to test how objective AI knowledge shapes support for cybersecurity governance. I also test whether concern about data misuse helps explain that relationship and whether AI …

Exploring Perspectives Of Autistic Individuals And Caregivers On Autism Inclusive Services In Public Libraries, Ayva J. Rose

LSU Master's Theses

Public libraries are increasingly recognized as important community hubs designed to promote literacy, learning, language, family engagement, and inclusivity. Despite this, autistic individuals may experience language, literacy, sensory, and social differences that could impact their ability to participate in literacy-based programming in libraries. Librarians currently report a desire to provide services that not only include but meaningfully support autistic children in their families; however, little research has examined how key stakeholders within the autism community perceive autism-inclusive programming within libraries. This research seeks to explore these perspectives and identify (1) perceived barriers to attending children’s library programs, (2) accommodations and …

Machine Learning Based Models For Simulation And Analysis Of Bulk Earth Melt System, Abin Shakya

LSU Doctoral Dissertations

Understanding the segregation of bulk Earth melt systems into metallic (core) and silicate (mantle) phases under high-pressure and high-temperature conditions is central to modeling Earth’s interior, yet relevant experimental and computational studies remain limited. This work develops a machine learning–based simulation pipeline that iteratively couples first-principles (quantum mechanical) calculations with neural network training to generate high-fidelity force fields. Using major-element Fe–Mg–Si–O melt systems, with and without H and N, as testbeds, we demonstrate that this framework enables large-scale molecular dynamics simulations at near first-principles accuracy. We further introduce a sequence of phase identification methods, progressing from statistical binning of elemental …