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Lsu General Catalog 2024-2025, Louisiana State University And Agricultural And Mechanical College

LSU General Catalog

The LSU General Catalog describes all undergraduate and graduate departments and programs with degree requirements and courses offered for each one. The LSU General Catalog includes information on registration and financial aid as well as academic services offered to all students.

A Cogroupoid Associated To Preregular Forms, Hongdi Huang, Van C. Nguyen, Charlotte Ure, Kent B. Vashaw, Padmini Veerapen, Xingting Wang

Faculty Publications

We construct a family of cogroupoids associated to preregular forms and recover the Morita–Takeuchi equivalence for Artin–Schelter regular algebras of dimension two, observed by Raedschelders and Van den Bergh. Moreover, we study the 2-cocycle twists of pivotal analogues of these cogroupoids, by developing a categorical description of preregularity in any tensor category that has a pivotal structure.

On The Maximum Spread Of Planar And Outerplanar Graphs, Zelong Li, William Linz, Linyuan Lu, Zhiyu Wang

Faculty Publications

The spread of a graph G is the difference between the largest and smallest eigenvalue of the adjacency matrix of G. Gotshall, O’Brien and Tait conjectured that for sufficiently large n, the n-vertex outerplanar graph with maximum spread is the graph obtained by joining a vertex to a path on n − 1 vertices. In this paper, we disprove this conjecture by showing that the extremal graph is the graph obtained by joining a vertex to a path on ⌈(2n − 1)/3⌉ vertices and ⌊(n − 2)/3⌋ isolated vertices. For planar graphs, we show that the extremal n-vertex planar graph …

Negotiating Quotidian Justice In The Science Classroom, Christopher Irwin, Joshua Ellis

Faculty Publications

In this conceptual paper, we explore how science teachers might enact social justice through their everyday science instruction. Drawing on empirical literature and our own K-12 teaching experience, we develop a heuristic for mapping classroom discourses to engage in action and reflection to change both the world of the classroom community, and the world beyond the school. We suggest how this heuristic can be used for justice-oriented science teaching independently of (or as a supplement to) any existing frameworks for science teaching to promote social justice. Our proposed model for social justice through disciplinary science teaching frames justice not as …

Summer-Wet Hydrologic Cycle During The Middle Miocene Of The United States: New Evidence From Fossil Fungi, Jennifer M.K. O’Keefe, Matthew J. Pound, Ingrid C. Romero, Noelia B. Nuñez Otaño, Martha E. Gibson, Jessica Mccoy, Margaret E. Alden, C. Jolene Fairchild, Julia Fitzpatrick, Emily Hodgson, Taylor Horsfall, Savannah Jones, June E. Lennex-Stone, Christopher A. Marsh, Alyssa A. Patel, Tyler M. Spears, Laikin Tarlton, Liberty F. Smallwood, O. L. Vanderespt, Jeremyah R. Cabrera, Cortland F. Eble, William C. Rember, James E. Starnes, Mac H. Alford, Alyson Brink, Sophie Warny

Faculty Publications

Hydrologic reconstructions from North America are largely unknown for the Middle Miocene. Examination of fungal palynomorph assemblages coupled with traditional plant-based palynology permits delineation of local, as opposed to regional, climate signals and provides a baseline for study of ancient fungas. Here, the Fungi in a Warmer World project presents paleoecology and paleoclimatology of 351 fungal morphotypes from 3 sites in the United States: the Clarkia Konservat-Lagerstätte site (Idaho), the Alum Bluff site (Florida), and the Bouie River site (Mississippi). Of these, 83 fungi are identified as extant taxa and 41 are newly reported from the Miocene. Combining new plant-based …

Accelerating L-Shaped Two-Stage Stochastic Scuc With Learning Integrated Benders Decomposition, Fouad Hasan, Amin Kargarian

Faculty Publications

Benders decomposition is widely used to solve large mixed-integer problems. This article takes advantage of machine learning and proposes a variant of Benders decomposition to tackle two-stage stochastic security-constrained unit commitment (SCUC). The problem is decomposed into a master problem (MP) and subproblems (SPs) corresponding to individual load scenarios. The primary objective is to mitigate computational expenses and memory consumption associated with Benders decomposition by generating tighter cuts and reducing the MP's dimensions. A regressor reads load profile scenarios and predicts objective function proxy values for the SPs, enabling the creation of tighter cuts for the MP. The numerical difference …

Performance Optimization Of Software-Defined Industrial Internet-Of-Things (Sd-Iiot), Jehad Ali, Celestine Iwendi, Gaoyang Shan, Hsiao Chun Wu, Mohammed J.F. Alenazi, Zaid Bin Faheem, Cresantus N. Biamba

Faculty Publications

Software-Defined Networking (SDN) offers a centralized network management approach that can effectively address the complex and varied traffic demands characteristic of Industrial Internet of Things (IIoT) environments by decoupling the control plane from the data plane. The centralized control architecture of SDN necessitates the performance optimization of controllers to manage diverse traffic efficiently within IIoT applications. This paper explores the criteria for selecting controllers in SDN-enabled IIoT (SD-IIoT) environments, utilizing the Less Complex Analytic Network Process (LC-ANP) to establish their prioritization. A ranking system for SD-IIoT controllers is formulated using LC-ANP, and experimental validation of this method underscores its effectiveness …

Tensor Z -Transform, Shih Yu Chang, Hsiao Chun Wu

Faculty Publications

The multi-input multioutput (MIMO) systems involving multirelational signals generated from distributed sources have been emerging as the most generalized model in practice. The existing work for characterizing such a MIMO system is to build a corresponding transform tensor, each of whose entries turns out to be the individual z-transform of a discrete-time impulse response sequence. However, when a MIMO system has a global feedback mechanism, which also involves multirelational signals, the aforementioned individual z-transforms of the overall transfer tensor are quite difficult to formulate. Therefore, a new mathematical framework to govern both feedforward and feedback MIMO systems is in crucial …

Fractal Surface Recovery And Self-Healing Contributed To Sustainable Superhydrophobicity: A Review, Yunfei Peng, Zhihang Ma, Xiao Wang, Junru Li, Xinlin Li, Chuanwei Zhang, Tian He, Guoqiang Li, Pengfei Zhang

Faculty Publications

The concept of superhydrophobicity has been widely used after years of theoretical and experimental exploration. Researchers have obtained materials with excellent surface superhydrophobicity for numerous areas (e.g. textiles, paints, and coatings industries), through different design and synthesis methods using low surface energy components (LSECs) and micro/nanohierarchy composite structures. However, the durability of superhydrophobic material surfaces has gradually become a prominent obstacle to restricting applications. In this paper, advances in improving the durability of superhydrophobic surfaces in the past decade are reviewed, covering different schemes for recovering fractal surfaces based on the LSECs and micro/nanocomposite structures. It also presents a balanced …

Review Of Artificial Neural Networks For Wind Turbine Fatigue Prediction, Alshannaq, Aly Mousaad Aly

Faculty Publications

Wind turbines have emerged as a prominent renewable energy source globally. Efficient monitoring and detection methods are crucial to enhance their operational effectiveness, particularly in identifying fatigue-related issues. This review focuses on leveraging artificial neural networks (ANNs) for wind turbine monitoring and fatigue detection, aiming to provide a valuable reference for researchers in this domain and related areas. Employing various ANN techniques, including General Regression Neural Network (GRNN), Support Vector Machine (SVM), Cuckoo Search Neural Network (CSNN), Backpropagation Neural Network (BPNN), Particle Swarm Optimization Artificial Neural Network (PSO-ANN), Convolutional Neural Network (CNN), and nonlinear autoregressive networks with exogenous inputs (NARX), …

Reliability Analysis Of End Cracking In Continuous Prestressed Concrete Girders, A. M. Okeil, S. Ghimire

Faculty Publications

Constructing bridges using precast prestressed concrete girders is extremely popular because of their durability and ease of construction. Establishing continuity between precast girders has its advantages and has been employed in many projects. It causes the development of positive restraint moments at intermediate supports as a result of long-term effects such as creep, shrinkage and thermal gradients. Prestressed concrete girder end cracking occurs if the positive restraint moments exceed the girder’s cracking moment. In this study, the probability of girder end cracking in continuous prestressed concrete bridges is assessed using structural reliability concepts. This study focuses on two bridge configurations …

Water Wave Optimization Algorithm-Based Dynamic Optimal Dispatch Considering A Day-Ahead Load Forecasting In A Microgrid, Duy C. Huynh, Loc D. Ho, Hieu M. Pham, Matthew W. Dunnigan, Corina Barbalata

Faculty Publications

A novel strategy is proposed to tackle an optimal dispatch of a microgrid in response to dynamic conditions, utilizing a water wave optimization (WWO) algorithm and considering a day-ahead load forecasting. Amongst meta-heuristic algorithms, the WWO algorithm stands out in terms of population size, parameter tuning, exploitation and exploration, convergence speed, as well as optimization mechanism. It leverages its ability to efficiently explore solution spaces and adapt to changing conditions. It is applied to the dynamic optimal dispatch of a microgrid with the uncertainty of load power considered and solved by day-ahead load forecasting. It dynamically adjusts the microgrid operation …

Machine Learning For Automated Sand Transport Monitoring In A Pipeline Using Distributed Acoustic Sensor Data, Harrison Gietz, Jyotsna Sharma, Mayank Tyagi

Faculty Publications

Uncontrolled sand production presents a substantial challenge to wellbore and pipeline integrity and efficiency of hydrocarbon production operations, often leading to equipment damage and compromised productivity. Traditional sand detection methods on the surface alert operators to sanding issues, but they are often a lagging indicator of downhole sanding events and do not provide precise identification of the problematic reservoir zones. Addressing this limitation, this study harnesses a combination of efficient signal processing and machine learning (ML) to analyze data from optical-fiber-based distributed acoustic sensors (DASs), thus serving as the first instance (to the authors' knowledge) of an automated and real-time …

Vehicle Classification Technologies For Toll Collection, Samir Ahmed

Publications

Toll facilities (roads, bridges, and tunnels) are intended for revenue generation to pay off the long-term debt issued to finance construction, capacity expansion, operations, and maintenance of these facilities. Tolls are one form of a broad concept known as road pricing. In addition to revenue generation, road pricing is used for other reasons including transportation demand management to reduce peak hour travel and the recurring traffic congestion on some corridors. The aim of this study is to provide the tolling industry with detailed analysis of the suitability of various non‐ pavement‐intrusive vehicle classification technologies (imaging using radar, Lidar, thermal profiling, …

Framework Of Internal Damage Identification In Inhomogeneous Medium Interweaving Wave Scattering Model And Deep Learning, Suyun Ham, Stefan Romanoschi, Yin Chao Wu, Dafnik Saril Kumar David

Publications

The primary objective of this project is to investigate the framework of internal damage identification in inhomogeneous media (IHM) using deep learning techniques and wave scattering. The study focuses on two main steps: 1) analyzing the wave response pattern in homogeneous media (HM) and 2) characterizing the wave response variation (WRV) in IHM with different aggregate sizes and random distributions. The WRV patterns are then classified and used to predict internal damage using a convolutional neural network (CNN). The accuracy of the finite element (FE) model is verified using laboratory tests with artificial internal crack models of varying depths. The …

Identifying Wrong-Way Driving Entry Points On Interstate Highways Using Land-Use Impact Assessment And 911 Calls, Farman Mia, Samer Dessouky

Publications

The research aims to provide insight into the initiation event of Wrong-way Driving (WWD) on highways. The intense severity of a WWD accident is encouraging the authorities to install mitigation systems that will ensure safety for motorists on highways. The WWD events are mostly resulting of intoxicated driving, where the unconscious driver takes the wrong way to enter the highway and place other motorists into life-threatening danger. This research attempted to explore from basic knowledge of WWD occurrence to examine the origin and driving philosophy of intoxicated drivers from land-use impact and mathematical modeling point of views. To identify the …

Smart3pm: Smart Pavement Monitoring, Management, And Maintenance, Damien Stephens, Mena Souliman, Mukul Shirvaikar, Samer Dessouky

Publications

An application specific multi-platform smartphone application can utilize on-board accelerometer, gyroscope, and GPS sensors, along with software derived signals from the same sensors, to sample vibrational and geolocation datasets to capture pavement distresses such as potholes when mounted in a standardized configuration in a vehicle. Several observations were made with regard to the signals obtained from the accelerometer, gyroscope, and GPS sensors, and it was determined that the raw sensor outputs are capable of sampling statistically significant datasets which can be used to distinguish pavement distress from normal driving conditions. Furthermore, an approximate sensor noise margin is established, and a …

Development Of A Web Application For Traffic Accident Mapping And Analysis, Susan Bogus Halter, Su Zhang, Arian Golrokh Amin

Publications

It is widely accepted that road traffic safety is a significant public health issue. One of the effective ways to improve road traffic safety is analyzing crash data to understand where traffic accidents occur, identify associated spatial and temporal patterns, and determine causation. In the State of New Mexico, locations of traffic accidents are currently visualized using a variety of static maps. Although these statics maps are easier to create and producers can control how users view the data, users cannot customize these maps to meet their special needs. That being said, new maps need to be created for any …

Atmospheric Flash Drought In The Caribbean, Craig A. Ramseyer, Paul W. Miller

Faculty Publications

Despite the intensifying interest in flash drought both within the United States and globally, moist tropical landscapes have largely escaped the attention of the flash drought community. Because these ecozones are acclimatized to receiving regular, near-daily precipitation, they are especially vulnerable to rapid-drying events. This is particularly true within the Caribbean Sea basin where numerous small islands lack the surface and groundwater resources to cope with swiftly developing drought conditions. This study fills the tropical flash drought gap by examining the pervasiveness of flash drought across the pan-Caribbean region using a recently proposed criterion based on the evaporative demand drought …

New Insights In The Mechanisms Of Weight-Loss Maintenance: Summary From A Pennington Symposium, Emily W. Flanagan, Redin Spann, Sarah E. Berry, Hans Rudolf Berthoud, Stephanie Broyles, Gary D. Foster, Jonathan Krakoff, Ruth J.F. Loos, Michael R. Lowe, Danielle M. Ostendorf, Tiffany M. Powell-Wiley, Leanne M. Redman, Michael Rosenbaum, Philip R. Schauer, Randy J. Seeley, Boyd A. Swinburn, Kevin Hall, Eric Ravussin

Division of Basic Science Faculty Publications

Obesity is a chronic disease that affects more than 650 million adults worldwide. Obesity not only is a significant health concern on its own, but predisposes to cardiometabolic comorbidities, including coronary heart disease, dyslipidemia, hypertension, type 2 diabetes, and some cancers. Lifestyle interventions effectively promote weight loss of 5% to 10%, and pharmacological and surgical interventions even more, with some novel approved drugs inducing up to an average of 25% weight loss. Yet, maintaining weight loss over the long-term remains extremely challenging, and subsequent weight gain is typical. The mechanisms underlying weight regain remain to be fully elucidated. The purpose …

Modeling Of Cryopreservation Pathway Operation At An Aquatic Biomedical Stock Center For Zebrafish, Sarah Bodenstein, Fidan Abdullayeva, Joy M. Murphy, Zoltan M. Varga, Terrence R. Tiersch

Faculty Publications

Aquatic biomedical model organisms play a substantial role in advancing our understanding of human health, however, comparably little work has been directed towards developing dependable, high-throughput storage programs for valuable genetic resources. The Zebrafish International Resource Center (ZIRC) has developed a standardized cryopreservation pathway and stored thousands of genetic lines in their repository for use by the biomedical research community. This has yet to be replicated in other facilities, and an overall repository-level pathway has never been analyzed for aquatic species. To encourage repository development for other biomedical models and to improve the ZIRC storage process and system, this study …

Physiologic Hormone Administration Improves Hba1c In Native Americans With Type 2 Diabetes: A Retrospective Study And Review Of Insulin Secretion And Action, Candida J. Rebello, Tyler S. Morales, Katsya Chuon, Shu Dong, V. Tyrone Lam, Dan Purner, Stanley Lewis, Jonathan Lakey, Robbie A. Beyl, Frank L. Greenway

Clinical Research Faculty Publications

Insulin is secreted in pulses from pancreatic beta-cells, and these oscillations maintain fasting plasma glucose levels within a narrow normal range. Within islets, beta-cells exhibit tight synchronization of regular oscillations. This control circuit is disrupted in type 2 diabetes, and irregularities in pulse frequency and amplitude occur. The prevalence of type 2 diabetes is three times higher in American Indian and Native Alaskans compared to Whites, and their genetic ancestry is associated with low beta-cell function. Obesity in this population compounds their vulnerability to adverse outcomes. The purpose of this article is to review insulin secretion and action and its …

Precision Subclassification Of Type 2 Diabetes: A Systematic Review, Shivani Misra, Shivani Misra, Robert Wagner, Bige Ozkan, Martin Schön, Magdalena Sevilla-Gonzalez, Katsiaryna Prystupa, Caroline C. Wang, Raymond J. Kreienkamp, Sara J. Cromer, Mary R. Rooney, Daisy Duan, Anne Cathrine Baun Thuesen, Amelia S. Wallace, Aaron Leong, Aaron J. Deutsch, Mette K. Andersen, Liana K. Billings, Liana K. Billings, Robert H. Eckel, Wayne Huey Herng Sheu, Torben Hansen, Norbert Stefan, Mark O. Goodarzi, Debashree Ray, Elizabeth Selvin, Jose C. Florez, Paul W. Franks, Stephen S. Rich, Tina Vilsbøll, Kimberly K. Vesco, Miriam S. Udler, Tiinamaija Tuomi, Arianne Sweeting

Clinical Research Faculty Publications

Background: Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients. Methods: We searched PubMed and Embase for publications that used ‘simple subclassification’ approaches using simple categorisation of clinical characteristics, or ‘complex subclassification’ approaches which used machine learning or ‘omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical …

African Bovid Tribe Classification Using Transfer Learning And Computer Vision, Manuel Domínguez-Rodrigo, Juliet Brophy, Gregory J. Mathews, Marcos Pizarro-Monzo, Enrique Baquedano

Faculty Publications

Objective analytical identification methods are still a minority in the praxis of paleobiological sciences. Subjective interpretation of fossils and their modifications remains a nonreplicable expert endeavor. Identification of African bovids is a crucial element in the reconstruction of paleo-landscapes, ungulate paleoecology, and, eventually, hominin adaptation and ecosystemic reconstruction. Recent analytical efforts drawing on Fourier functional analysis and discrimination methods applied to occlusal surfaces of teeth have provided a highly accurate framework to correctly classify African bovid tribes and taxa. Artificial intelligence tools, like computer vision, have also shown their potential to be objectively more accurate in the identification of taphonomic …

Sediment Delivery To Sustain The Ganges-Brahmaputra Delta Under Climate Change And Anthropogenic Impacts, Jessica L. Raff, Steven L. Goodbred, Jennifer L. Pickering, Ryan S. Sincavage, John C. Ayers, Md Saddam Hossain, Carol A. Wilson, Chris Paola, Michael S. Steckler, Dhiman R. Mondal, Jean Louis Grimaud, Celine Jo Grall, Kimberly G. Rogers, Kazi Matin Ahmed, Syed Humayun Akhter, Brandee N. Carlson, Elizabeth L. Chamberlain, Meagan Dejter, Jonathan M. Gilligan, Richard P. Hale, Mahfuzur R. Khan, Md Golam Muktadir, Md Munsur Rahman, Lauren A. Williams

Faculty Publications

The principal nature-based solution for offsetting relative sea-level rise in the Ganges-Brahmaputra delta is the unabated delivery, dispersal, and deposition of the rivers’ ~1 billion-tonne annual sediment load. Recent hydrological transport modeling suggests that strengthening monsoon precipitation in the 21st century could increase this sediment delivery 34-60%; yet other studies demonstrate that sediment could decline 15-80% if planned dams and river diversions are fully implemented. We validate these modeled ranges by developing a comprehensive field-based sediment budget that quantifies the supply of Ganges-Brahmaputra river sediment under varying Holocene climate conditions. Our data reveal natural responses in sediment supply comparable to …

Give Me A Break, Oil Companies Don’T Need Them: A Case Study Of Drilling Incentives In Louisiana Oil & Gas, Samuel Camacho

Honors Capstones

No abstract provided.

Transverse Knot Invariants Across Transverse Knot Concordance, Nicholas Kearns

Honors Capstones

No abstract provided.

Performative Mixing For Immersive Audio, Brian A. Elizondo

LSU Doctoral Dissertations

Immersive multichannel audio can be produced with specialized setups of loudspeakers, often surrounding the audience. These setups can feature as few as four loudspeakers or more than 300. Performative mixing in these environments requires a bespoke solution offering intuitive gestural control. Beyond the usual faders for gain control, advancements in multichannel sound demand interfaces capable of quickly positioning sounds between channels. The Quad Cartesian Positioner is such a solution in the form of a Eurorack module for surround mixing for use in live or studio performances.

Diffusion/mixing methods for live multichannel immersive music often rely on the repurposing of hardware …

An Intersection Of Science & Art: Vitrification Approaches And Open-Fabricated Tools For The Biomedical Model Sea Hare, Aplysia Californica, Allyssa M. Oune

LSU Master's Theses

The California sea hare (Aplysia californica) is an important biomedical model for molecular neurobiology, electrophysiology, learning, and memory due to their well-mapped and large neurons and well-characterized learning capabilities. The National Resource for Aplysia (NRA, University of Miami) maintains large stocks of live animals and relies on regular shipments of wild-caught individuals to maintain genetic diversity. This is labor and cost-intensive, and environmental changes could alter the availability of wild animals increasing the need to preserve this genetic resource. One solution is vitrification, ultra-fast cooling which produces an amorphous glass that minimizes damage to cells. Aplysia californica presents …

Chiral Fermion Anomaly As A Memory Effect, Adrián Del Río, Ivan Agullo

Faculty Publications

We study the nonconservation of the chiral charge of Dirac fields between past and future null infinity due to the Adler-Bell-Jackiw chiral anomaly. In previous investigations [A. del Rio, Phys. Rev. D 104, 065012 (2021)PRVDAQ2470-001010.1103/PhysRevD.104.065012], we found that this charge fails to be conserved if electromagnetic sources in the bulk emit circularly polarized radiation. In this article, we unravel yet another contribution coming from the nonzero, infrared "soft"charges of the external, electromagnetic field. This new contribution can be interpreted as another manifestation of the ordinary memory effect produced by transitions between different infrared sectors of Maxwell theory, but now on …