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Recombinant Dna Vaccine Design As A Potential Strategy Against Bovine Foot And Mouth Disease Virus (Fmdv), Taylor Haynie

LSU Master's Theses

Foot-and-mouth disease virus (FMDV) is the causative agent for foot-and-mouth disease (FMD) that infects primarily cloven-hoofed animals, the majority of which are domesticated cattle and other important livestock. FMD is highly transmissible and found in all secretions and excretions of infected animals. North America, Europe, and Australia have successfully eradicated the virus with the help of a well-defined fiscal infrastructure and access to successful control measures. Less developed regions, including many Asian and African countries, have maintained an endemic status for decades. African territories are of particular concern because of the indigenous African Buffalo population that serves as an important …

Characterizing And Modeling The Impact Photorepair Conditions Have On Parameters Governing The Regrowth Of Escherichia Coli After Uvc Irradiation, And Investigating Potential Mitigation Strategies, Andrea J. Martinez Ballen

LSU Master's Theses

Ultraviolet disinfection has been used to treat water and wastewater for decades. Previous studies highlight the significance of disinfection conditions and attempt to model bacterial regrowth behavior according to disinfection dosing parameters. The emergence of light-emitting diode (LED) technology provides the ability to further explore bacterial repair methods after UV disinfection, which has been a growing concern within the UV community. However, it is necessary to also consider post-disinfection conditions to model the regrowth patterns of bacterial organisms more accurately. By varying reactivation wavelengths, and their respective intensities, experiments using Escherichia coli ATCC 15597 revealed how these parameters impact the …

Beyond Machine Learning: An Fmri Domain Adaptation Model For Multi-Study Integration, Lauryn Michelle Burleigh

LSU Doctoral Dissertations

Traditional machine learning analyses are challenging with functional magnetic
resonance imaging (fMRI) data, not only because of the amount of data that needs to be
collected, adding a particular challenge for human fMRI research, but also due to the change in
hypothesis being addressed with various analytical techniques. Domain adaptation is a type of
transfer learning, a step beyond machine learning which allows for multiple related, but not
identical, data to contribute to a model, can be beneficial to overcome the limitation of data
needed but may address different hypothesis questions than anticipated given the analysis
computation. This dissertation assesses …

Control And Optimization Of Multi-Agent Systems With Applications In Connected And Autonomous Electric Vehicles, Shaopan Guo

LSU Doctoral Dissertations

A multi-agent system (MAS) is a system in which multiple autonomous agents interact with each other to achieve a common goal. Nevertheless, current designs of MAS controllers typically rely on particular requirements, such as time-triggered communication, linear dynamics, and access to global information. These limitations restrict the applicability of MASs. This thesis aims to eliminate these constraints and optimize the energy consumption of a specific MAS, namely connected autonomous electric vehicles (CAEVs).

This thesis first addresses the consensus problem of linear MASs with intermittent communication. An adaptive distributed control algorithm that integrates edge-based event-triggered (ET) communication mechanisms is presented in …

Physics-Based Crystal Plasticity Model For Predicting Microstructure Evolution And Dislocation Densities, Juyoung Jeong

LSU Doctoral Dissertations

This work presents three different studies investigating plastic deformation mechanisms in metals and alloys using crystal plasticity finite element (CPFE) modeling. The first study presents a new nonlocal crystal plasticity model for face-centered cubic single crystals under heterogeneous inelastic deformation. The model incorporates generalized constitutive relations that incorporate the thermally activated and drag mechanisms to cover different kinetics of viscoplastic flow in metals and describes the plastic flow and yielding of single-crystals using dislocation densities. The model is compared to micropillar compression experiments for copper single crystals and clarifies the complex microstructural evolution of dislocation densities in metals. The second …

Computational Reverse-Engineering Analysis For Scattering Experiments For Form Factor And Structure Factor Determination (“P(Q) And S(Q) Crease”), Christian M. Heil, Yingzhen Ma, Bhuvnesh Bharti, Arthi Jayaraman

Faculty Publications

In this paper, we present an open-source machine learning (ML)-accelerated computational method to analyze small-angle scattering profiles [I(q) vs q] from concentrated macromolecular solutions to simultaneously obtain the form factor P(q) (e.g., dimensions of a micelle) and the structure factor S(q) (e.g., spatial arrangement of the micelles) without relying on analytical models. This method builds on our recent work on Computational Reverse-Engineering Analysis for Scattering Experiments (CREASE) that has either been applied to obtain P(q) from dilute macromolecular solutions (where S(q) ∼1) or to obtain S(q) from concentrated particle solutions when P(q) is known (e.g., sphere form factor). This paper’s …

Frontal Polymerizations: From Chemical Perspectives To Macroscopic Properties And Applications, Benjamin A. Suslick, Julie Hemmer, Brecklyn R. Groce, Katherine J. Stawiasz, Philippe H. Geubelle, Giulio Malucelli, Alberto Mariani, Jeffrey S. Moore, John A. Pojman, Nancy R. Sottos

Faculty Publications

The synthesis and processing of most thermoplastics and thermoset polymeric materials rely on energy-inefficient and environmentally burdensome manufacturing methods. Frontal polymerization is an attractive, scalable alternative due to its exploitation of polymerization heat that is generally wasted and unutilized. The only external energy needed for frontal polymerization is an initial thermal (or photo) stimulus that locally ignites the reaction. The subsequent reaction exothermicity provides local heating; the transport of this thermal energy to neighboring monomers in either a liquid or gel-like state results in a self-perpetuating reaction zone that provides fully cured thermosets and thermoplastics. Propagation of this polymerization front …

Motivators And Preferences Of Route Diversion During Roadway Incidents, Grace Cole

LSU Master's Theses

When confronted with congestion and delay, drivers often divert their route. Depending on factors like purpose, urgency, destination, route alternatives, type of disruption, and mode options, common diversionary options can range from changing departure time, route, and mode to canceling a trip altogether. One of the foundational building blocks of travel forecasting is traffic assignment, which is used to distribute trips over a network using complex algorithms to aggregately represent the desire of drivers to minimize travel time.

While these assignment models are backed by decades of research and observational experience, they are also limited by the fact that they …

Stellar Binaries And Post-Merger Evolution: A Framework For Stellar Evolution And Nucleosynthesis In R Coronae Borealis Stars, Bradley Munson

LSU Doctoral Dissertations

We have developed a framework for simulating binary stars through all three relevant
timescales: the dynamical merger, thermal, and nuclear evolution. The framework begins by simulating a dynamical merger in a 3-dimensional hydrodynamics adaptive mesh refinement code, Octo-Tiger, and performing a spherical averaging calculation to map the post-merger remnant into the 1-dimensional stellar evolution code, MESA. In this work, we primarily utilize this framework for simulating double white dwarf mergers, which are believed to be the progenitor to R Coronae Borealis (RCB) stars. We evolve the post-merger in MESA and compare the computed surface abundances to those observed …

A Data-Driven Multivariate Process Monitoring Platform For Knowledge Discovery And Model Building In Industrial Applications, Estelle E. Seghers

LSU Master's Theses

In industrial chemical manufacturing processes, the amount of raw data generated can add complexity in the analysis and understanding of the process dynamics. Being able to properly interpret this data can help improve plant operation, especially regarding safety and profitability. This research has culminated in FastMan-JMP, a platform proposed for monitoring of industrial processes and optimization of the offline data-driven model-building process as part of the process monitoring workflow. FastMan-JMP is a tool developed in Python to apply various data mining and machine learning techniques quickly and easily to better understand valuable patterns and hidden trends in process data. One …

Strengthening The Ti/Tin Interface Against Shear Failure With Al Dopants: A Molecular Dynamics Study, Nisha Dhariwal, Abu Shama Mohammad Miraz, W. J. Meng, Collin D. Wick

Faculty Publications

The impact of Al doping on the stability and shear strength of the Ti/TiN interface was investigated using a newly developed modified embedded atom model interatomic potential. The model was parameterized to the interfacial properties of pure Al, TiAl and AlN binaries as well as TiAlN ternary system. The results of the new model are in reasonably good agreement with those obtained using Density Functional Theory and experimental data from the literature. A Ti/TiN system with a misfit dislocation network present on the Ti layer adjacent to the TiN interface was chosen for doping because of its low interfacial energy. …

Delineating The Effects Of Molecular And Colloidal Interactions Of Dissolved Organic Matter On Titania Photocatalysis, Mostafa Maghsoodi, Céline Jacquin, Benoit Teychené, Geoffroy Lesage, Samuel D. Snow

Faculty Publications

In the face of significant challenges to practical applications of photocatalysis for water treatment, recent reports revealed a potential route to overcome a problem posed by dissolved organic matter (DOM). These studies showed that inhibition of photocatalytic processes by DOM is driven largely by competition for active surface sites on TiO2 or other catalysts, and controlling the type of DOM present in solution could significantly mitigate DOM fouling. Whether or not control of solution parameters could achieve the same preventative action is not known. Here, a series of DOM isolates, including humic acid (HA) and transphilic (TPI), hydrophobic (HPO), or …

Uncovering The Optimal Molecular Characteristics Of Hydrophobe-Containing Polypeptoids To Induce Liposome Or Cell Membrane Fragmentation, Tianyi Yu, Marzhana Omarova, Meng Zhang, Istiak Hossain, Jianqiang Chen, Omead Darvish, Vijay T. John, Donghui Zhang

Faculty Publications

Cellular functions of membrane proteins are strongly coupled to their structures and aggregation states in the cellular membrane. Molecular agents that can induce the fragmentation of lipid membranes are highly sought after as they are potentially useful for extracting membrane proteins in their native lipid environment. Toward this goal, we investigated the fragmentation of synthetic liposome using hydrophobe-containing polypeptoids (HCPs), a class of facially amphiphilic pseudo-peptidic polymers. A series of HCPs with varying chain lengths and hydrophobicities have been designed and synthesized. The effects of polymer molecular characteristics on liposome fragmentation are systemically investigated by a combination of light scattering …

A Simulation Study Of Surfactant/Foam Processes In Shallow Subsurface Remediation: Using Foams For Mobility Control Vs. Blockage, Betty Cepeda

LSU Master's Theses

Many shallow ex-situ and in-situ remediation treatments come from the contamination of underground soils and groundwater sources by organic hydrocarbon components called non-aqueous phase liquids (NAPLs). These contaminants, if leaking, can impose long-term threats causing environmental and health concerns. One of the versatile in-situ remediation techniques is using surfactant/foam processes that can overcome subsurface heterogeneity and improve NAPL removal.

This simulation study investigates surfactant/foam processes, especially focusing on two different roles of foams during the treatment: foams for “mobility control” vs. foams for “blocking”. The first is based on the actual operations carried out in the pilot-test site for 23 …

Ranked Document Retrieval In External Memory, Rahul Shah, Cheng Sheng, Sharma Thankachan, Jeffrey Vitter

Faculty Publications

The ranked (or top-k) document retrieval problem is defined as follows: preprocess a collection {T1,T2,... ,Td} of d strings (called documents) of total length n into a data structure, such that for any given query (P,k), where P is a string (called pattern) of length p ≥ 1 and k ϵ [1,d] is an integer, the identifiers of those k documents that are most relevant to P can be reported, ideally in the sorted order of their relevance. The seminal work by Hon et al. [FOCS 2009 and Journal of the ACM 2014] presented an O(n)-space (in words) data structure …

Nsf/Ieee-Tcpp Curriculum On Parallel And Distributed Computing For Undergraduates - Version Ii - Big Data, Energy, And Distributed Computing, Sushil Prasad, Charles Weems, Alan Sussman, Anshul Gupta, Trilce Estrada, Ramachandran Vaidyanathan, Sheikh Ghafoor, Krishna Kant, Craig Stunkel

Faculty Publications

This special session will report on the updated NSF/IEEE-TCPP Curriculum on Parallel and Distributed Computing released in Nov 2020 by the Center for Parallel and Distributed Computing Curriculum Development and Educational Resources (CDER). The purpose of the special session is to obtain SIGCSE community feedback on this curriculum in a highly interactive manner employing the hybrid modality and supported by a full-time CDER booth for the duration of SIGCSE. In this era of big data, cloud, and multi- and many-core systems, it is essential that the computer science (CS) and computer engineering (CE) graduates have basic skills in parallel and …

Autonomous Single-Molecule Manipulation Based On Reinforcement Learning, Bernhard Ramsauer, Grant J. Simpson, Johannes J. Cartus, Andreas Jeindl, Victor García-López, James M. Tour, Leonhard Grill, Oliver T. Hofmann

Faculty Publications

Building nanostructures one-by-one requires precise control of single molecules over many manipulation steps. The ideal scenario for machine learning algorithms is complex, repetitive, and time-consuming. Here, we show a reinforcement learning algorithm that learns how to control a single dipolar molecule in the electric field of a scanning tunneling microscope. Using about 2250 iterations to train, the algorithm learned to manipulate the molecule toward specific positions on the surface. Simultaneously, it generates physical insights into the movement as well as orientation of the molecule, based on the position where the electric field is applied relative to the molecule. This reveals …

Attochemistry Regulation Of Charge Migration, Aderonke S. Folorunso, François Mauger, Kyle A. Hamer, Denawakage D. Jayasinghe, Imam S. Wahyutama, Justin R. Ragains, Robert R. Jones, Louis F. Dimauro, Mette B. Gaarde, Kenneth J. Schafer, Kenneth Lopata

Faculty Publications

Charge migration (CM) is a coherent attosecond process that involves the movement of localized holes across a molecule. To determine the relationship between a molecule's structure and the CM dynamics it exhibits, we perform systematic studies of para-functionalized bromobenzene molecules (X-C6H4-R) using real-time time-dependent density functional theory. We initiate valence-electron dynamics by emulating rapid strong-field ionization leading to a localized hole on the bromine atom. The resulting CM, which takes on the order of 1 fs, occurs via an X localized → C6H4delocalized → R localized mechanism. Interestingly, the hole contrast on the acceptor functional group increases with increasing electron-donating …

The Impact Of Case Management Intervention For Insured Asthma Patients In Louisiana, An Empirical Study, Mohamed Mohamed Ohaiba

LSU Doctoral Dissertations

Asthma is a chronic condition whose symptoms are managed/prevented using medication and interventions. The overarching objective of this study was to evaluate the impact of patients' demographics on case management enrollment and healthcare utilization, as well as to develop machine learning models to predict high-cost patients.

To accomplish these goals, the Man-Whiteness test, the chi-squares test, logistic regression and odds ratios, and machine learning models were implemented. The average cost of the non-enrolled CM group was significantly higher than the enrolled group (p-value .0001). In addition, the non-enrolled groups had considerably more visits to the emergency department than the other …

Temporal Variability In Soil Organic Matter Accretion Rates In Coastal Deltaic Wetlands Under Changing Depositional Environments, Yadav Sapkota, Kehui Xu, Kanchan Maiti, Patrick Inglett, John R. White

Faculty Publications

The Mississippi River Deltaic Plain experiences high relative sea level rise, limited sediment supply, and high marsh edge erosion, leading to the substantial coastal wetland and stored soil organic matter (SOM) loss. The objective of this study was to understand the SOM accumulation rates over the past 1000 years related to the changes in the depositional environment in these highly eroding coastal wetlands. Soil cores (2 m) were collected from four sites in Barataria Basin, LA and analyzed for proportion of organic and mineral matter, total C, N, P, particle size, and stable isotopic composition (δ¹³C and δ …

What Are The Most Effective Proxies In Identifying Storm-Surge Deposits In Paleotempestology? A Quantitative Evaluation From The Sand-Limited, Peat-Dominated Environment Of The Florida Coastal Everglades, Qiang Yao, Kam Biu Liu, Zhenqing Zhang, Erika Rodrigues, Marcelo Cohen, Kanchan Maiti, Yang Yang

Faculty Publications

Although many studies have attempted to reconstruct millennial-scale hurricane patterns using various proxy-based methods, it is still unclear what the most effective proxies are to identify storm surge deposits in different environmental settings. This study quantitatively compares the application of grain-size, loss-on-ignition, stable isotopes, X-ray fluorescence, and palynological proxies in paleotempestology from an organic-rich environment in the Florida Everglades. The nonparametric tests indicate that only 9 among the 27 parameters (mean diameter, %water, %organic, %carbonate, Ca, Sr, Ca/Ti, Cl/Br, and marine microfossils) exhibited significant differences between storm-surge and in situ deposits. The principal component analysis shows that five marine indicators …

Stratification Breakdown By Fall Cold Front Winds Over The Louisiana Shelf In The Northern Gulf Of Mexico: A Numerical Experiment, Mohammad Nabi Allahdadi, Chunyan Li, Nazanin Chaichitehrani

Faculty Publications

Cold fronts are meteorological phenomena that impact the northern Gulf of Mexico, mostly between the fall and spring seasons. On average, they pass the region every 3–7 days, with a duration ranging between 24 and 74 h. In the present study, a high-resolution FVCOM model with an unstructured mesh was used to simulate the effect of the fall cold front winds on water column mixing over the Louisiana shelf, which is often stratified in the summer, leading to hypoxia. Numerical experiments were conducted for October 2009, a period with five consecutive cold front events. Winds from an offshore station forced …

Multi-Agent Optimal Control For Central Chiller Plants Using Reinforcement Learning And Game Theory, Shunian Qiu, Zhenhai Li, Zhihong Pang, Zhengwei Li, Yinying Tao

Faculty Publications

To conserve building energy, optimal operation of a building’s energy systems, especially heating, ventilation and air-conditioning (HVAC) systems, is important. This study focuses on the optimization of the central chiller plant, which accounts for a large portion of the HVAC system’s energy consumption. Classic optimal control methods for central chiller plants are mostly based on system performance models which takes much effort and cost to establish. In addition, inevitable model error could cause control risk to the applied system. To mitigate the model dependency of HVAC optimal control, reinforcement learning (RL) algorithms have been drawing attention in the HVAC control …

Reproducibility And Determinants Of The Metabolic Responses During A Mixed-Meal Tolerance Test, Emma J. Stinson, Paolo Piaggi, Cassie M. Mitchell, Leanne M. Redman, Jonathan Krakoff

Clinical Research Faculty Publications

Objective: The aim of this study was to assess the reproducibility and physiological determinants of mixed-meal tolerance tests (MMTTs) on glucose and insulin responses. Methods: While inpatients on a weight-maintaining diet, 894 individuals (574 with normal and 267 with impaired glucose regulation and 53 with type 2 diabetes [T2D]) underwent 9-hour MMTTs (breakfast and lunch; 30% weight-maintaining diet each; 40% carbohydrate, 40% fat, and 20% protein). Total/incremental areas under the curve (AUC/iAUC) were calculated from MMTT plasma glucose/insulin concentrations. Acute insulin response (AIR) was quantified by intravenous glucose tolerance test and insulin action (M) via hyperinsulinemic-euglycemic clamp. A subset had …

Retrofitting Existing Distillation Columns For Improved Energy Efficiency And Increased Capacity, Justin Nijoka

Honors Capstones

No abstract provided.

Recovery Of Aconitic Acid From Sweet Sorghum Plant Extract Using A Solvent Mixture, And Its Potential Use As A Nematicide, K. Thomas Klasson, Yunci Qi, Gillian O. Bruni, Tristan T. Watson, Bretlyn T. Pancio, Evan Terrell

Faculty Publications

Trans-aconitic acid (TAA) is naturally present in sweet sorghum juice and syrup, and it has been promoted as a potential biocontrol agent for nematodes. Therefore, we developed a process for the extraction of aconitic acid from sweet sorghum syrup. The process economics were evaluated, and the extract was tested for its capability to suppress the motility of the nematodes Caenorhabditis elegans and Meloidogyne incognita. Aconitic acid could be efficiently extracted from sweet sorghum syrup using acetone:butanol:ethanol mixtures, and it could be recovered from this solvent with a sodium carbonate solution, with an overall extraction and recovery efficiency of 86%. The …

Field Applications Of Zein As A Precise Nanoscale Delivery System For Methoxyfenozide, C. A.R. Bonser, C. Tamez, J. C. White, C. E. Astete, C. M. Sabliov, J. A. Davis

Faculty Publications

When insecticides are applied in the environment, much of the product does not reach the target pest. Biopolymeric nanoparticles as nanocarriers have the potential to improve insecticide efficacy by improving absorption, coverage, and permeability while protecting the insecticide active ingredient from abiotic conditions and extending efficacy through controlled release. We conducted a series of experiments using a biopolymeric nanoparticle synthesized from zein, a biodegradable maize protein, to compare efficacy of a nanodelivered hydrophobic insect growth regulator (methoxyfenozide) against a commercial formulation. Positively charged zein nanoparticles (empty and loaded with methoxyfenozide) were compared to the formulated product, Intrepid 2F, as a …

Recent Advances And Challenges In Implementing Ipm Programmes In The Entomological Context Of Indian Agriculture, Ruchika Geedi, Gadi V.P. Reddy

Faculty Publications

Integrated pest management (IPM) programmes are based on using multiple methods to maintain nuisance insects below tolerant levels in crop fields. Recent advances in IPM in developed countries have incorporated biological pesticides, microbial products, semiochemicals, and beneficial insects, but few of such programmes have been successfully implemented in developing countries, such as India. Semiochemicals play critical roles as signals in various interspecific and intraspecific interactions between insects and plants, and among interacting insects, plants, and microbes. In India IPM programmes have included mechanical, chemical, cultural, and biological management strategies. However, among these methods, biological management has its own limitations. Indian …

A New Generation Of Dense-Graded Asphalt Mixtures With Superior Performance Against Stripping And Moisture Damage, Mostafa Elseifi, Zahid Hossain, Md. T.A Sarkar, Hossam Abohamer, Mohammad Oyan

Data

The presence of moisture beneath the pavement surface is a matter of great concerns as it is responsible for significant distresses such as asphalt concrete (AC) stripping, fatigue cracking, rutting, and poor durability of asphalt mixes. The objective of this study was to evaluate and recommend an asphalt mixture design that would provide superior performance against AC stripping and cracking. To achieve this objective, a laboratory test factorial was developed to evaluate the use of nanomaterials, emerging anti-stripping agents, warm-mix asphalt technologies, and adhesion promotors. In the experimental program, the modified Lottman test (AASHTO T 283) and the Indirect Tensile …

Initial Assessment Of The Toxicologic Effects Of Leachates From 3-Dimensional (3-D) Printed Objects On Sperm Quality In Two Model Fish Species, Matthew J. Schwing, Yue Liu, Jorge A. Belgodere, William T. Monroe, Terrence R. Tiersch, Ahmed Abdelmoneim

Faculty Publications

The use of 3-dimensional (3-D) printing is gaining popularity in life sciences and driving innovation in fields including aquatic sperm cryopreservation. Yet, little is known about the effects leachates from these objects may have on biological systems. In this study, we investigated if exposure to leachates from 3-D printed objects fabricated from different photo-curable resins could affect sperm quality in two model fish species, zebrafish (Danio rerio) and goldfish (Carassius auratus). Leachates were collected following contact periods of 10 min and 22 h with objects manufactured using a mask LCD resin printer and three different commercially available resins (i.e., standard, …